In recent years, walkability is increasingly integrated into sustainability strategies, considering its many health and environmental benefits. Besides, thermal comfort also has been progressively promoted as a critical measure for pedestrian comfort and wellbeing. Despite the relevance of the two concepts, few studies combined them in a comprehensive model. This study considers thermal comfort in assessing walkability by developing a new measurement tool, the Street Walkability and Thermal Comfort Index (SWTCI), which focuses on comfort facilities and Physiological Equivalent Temperature (PET), at the street scale. The applied point system method requires combining a questionnaire survey, observations, and in situ measurements (air temperature, wind velocity, and relative humidity). The questionnaire survey (330 responders) measured 21 street design indicators’ importance, using a five-point Likert scale ranging from 1 (least important) to 5 (very important). The observation technique seeks to evaluate every pedestrian comfort indicator score (Si(s)). The in situ measurements permit Envi-met’s calibrated data validation and getting the mean radian temperature (T(mrt)). Those were considered in the PET’s calculation using Rayman software. Three distinct streets have been chosen in Annaba city, Algeria, within the Mediterranean climate (Csa). The results show that the SWTCI achieves its highest score on the three streets when the thermal perception is neutral (20 < PET <26), and its lowest score, with a warm thermal sensation (28 < PET < 31). Despite the divergence in PET values, the highest score of SWTCI was 33%, reflecting a low comfort quality and minimal pedestrian facilities. Applying the SWTCI method can transform uncomfortable streets into an ideal walkable and pleasant path by finding the problems and proposing improvements.
While climate change is a global challenge, its impact is generally felt in local communities, particularly cities. The impact of climate change in urban settings is exacerbated by the built environment, high energy usage, air pollution and urbanisation, among other factors. Due to urbanisation, more children will be born and raised, or migrate to live in cities. Children in cities are vulnerable to the impact of climate change due to their physiology and developmental needs. City authorities are expected to utilise their constitutional and legislative powers in climate governance to protect children from the impact of climate change. The central inquiry of this article is to explore how city-level climate law and policy protects children in the context of climate change. Using Kenya and South Africa, as key examples, it illustrates that cities have constitutional powers and legislative authority to plan, implement and govern in certain climate-related functional areas and that could be leveraged to ensure the protection of children. The discussion of cities, children’s rights and climate change governance has global significance given the trends of urban growth in the present and coming decade.
The changes in climatic conditions and their associated impacts are contributing to a worsening of existing gender inequalities and a heightening of women’s socioeconomic vulnerabilities in South Africa. Using data collected by research methods inspired by the tradition of participatory appraisals, we systematically discuss the impacts of climate change on marginalized women and the ways in which they are actively responding to climate challenges and building their adaptive capacity and resilience in the urban areas of KwaZulu-Natal, South Africa. We argue that changes in climate have both direct and indirect negative impacts on women’s livelihoods and well-being. Less than one-half (37%) of the women reported implementing locally developed coping mechanisms to minimize the impacts of climate-related events, whereas 63% reported lacking any form of formal safety nets to deploy and reduce the impacts of climate-induced shocks and stresses. The lack of proactive and gender-sensitive local climate change policies and strategies creates socioeconomic and political barriers that limit the meaningful participation of women in issues that affect them and marginalize them in the climate change discourses and decision-making processes, thereby hampering their efforts to adapt and reduce existing vulnerabilities. Thus, we advocate for the creation of an enabling environment to develop and adopt progendered, cost-effective, transformative, and sustainable climate change policies and adaptation strategies that are responsive to the needs of vulnerable groups (women) of people in society. This will serve to build their adaptive capacity and resilience to climate variability and climate change-related risks and hazards.
Social vulnerability indices (SVI) can predict communities’ vulnerability and resilience to public health threats such as drought, food insecurity or infectious diseases. Parity has yet to be investigated as an indicator of social vulnerability in young women. We adapted an SVI score, previously used by the US Centre for Disease Control (CDC), and calculated SVI for young urban South African women (n = 1584; median age 21.6, IQR 3.6 years). Social vulnerability was more frequently observed in women with children and increased as parity increased. Furthermore, young women classified as socially vulnerable were 2.84 times (95% CI 2.10-3.70; p < 0.001) more likely to report household food insecurity. We collected this information in 2018-2019, prior to the current global COVID-19 pandemic. With South Africa having declared a National State of Disaster in March 2020, early indicators suggest that this group of women have indeed been disproportionally affected, supporting the utility of such measures to inform disaster relief efforts.
Erratic temperatures and precipitation influence nutrition, human capital investment, and living standards, particularly for children. This study investigates the effect of climate change (changes in the monthly maximum average near-surface temperature and total monthly precipitation) on children’s health outcomes, particularly stunting and underweight, in Nigeria. We combine Living Standards Measurement Study -Integrated Surveys on Agriculture (LSMS-ISA) data with high resolution gridded climate data. We find that the rise in temperature is associated with higher levels of stunting – even more so in rural areas. The paper’s findings highlight the need for climate-friendly policies to mitigate the long-term effect of climate change on malnourishment. Without such policies, climate change could reverse years of progress in lowering children’s malnutrition.
The urban poor in cities of developing countries tend to be the most affected by climate change. This is because of the intersection of their socio-economic characteristics and the hazardous bio-physical environments they inhabit, which usually have limited social services. This study, conducted through interviews with 320 residents of Bauleni and Misisi residential areas of Lusaka, applied the concept of intersectionality to investigate climate risk and social vulnerabilities in informal settlements of Lusaka. The study was based on both quantitative and qualitative data. Quantitative data was analysed using the two-sample proportions Z test and descriptive statistics with the aid of Minitab 17 statistical package, while qualitative data was analysed using thematic analysis with the aid of a qualitative data analysis software called QDA miner. The respondents identified floods, diseases and crime as the major social and climatic risks. Apart from flooding and crime, the risks were not perceived to affect the value of housing in the study sites. This was due to a lack of affordable housing alternatives for the urban poor. The social and climatic risks had differentiated effects on women, men and children. Housing property owners and tenants continue to reside in the risky environments because of the lower cost of land, low cost of living and proximity to the city’s central business district. The study recommends that policy measures aimed at improving informal settlements residents’ well-being should be directed at improving their ability to adjust to and recover from impacts of the climatic disasters and reducing social vulnerabilities.
Nairobi’s settlements are vulnerable to urban flooding exacerbated by anthropogenic factors. Households living in flood-prone areas suffer perennially. However, little scientific evidence exists on the relationship between impacts of flooding and coping strategies in Nairobi’s settlements. In this study, primary data was obtained through ground-truth surveys and administration of questionnaires to 310 households in Nairobi’s crowded informal settlements of Mathare Kosovo and Kibera Mashimoni. Information captured included their bio-data, knowledge and perception of flooding, socio-economic, susceptibility and recovery indicators. Secondary data was mainly from literature review. The findings of the canonical correlation revealed that an insignificant relationship of 0.2964 and 0.2503 existed between flooding impacts and coping strategies adopted by households and communities respectively. Floods caused inaccessibility of houses, workplaces and schools, damages to settlements infrastructure, drowning, diseases and displacement of residents. The indirect impacts were loss of livelihoods, environmental degradation, loss of manhours in traffic jams and economic loss. This study is novel in that it provides empirical scientific evidence on the nexus between impacts of flooding and coping strategies in an urban settlement. It augments existing literature on flood risks in urban settlements. It also provides an entry point for policy and decision makers such as scientists, private sector leaders, urban planners and government technocrats to make informed policy guidelines and intervention strategies.
Climate change presents significant threats to human health, especially for low-income urban communities in the Global South. Despite numerous studies of heat stress, surprisingly little is known about the temperatures actually encountered by people in their homes, or the benefits of affordable adaptations. This paper examines indoor air temperature measurements gathered from 47 living rooms within eight low-income communities of Accra and Tamale, Ghana. Using multiple temperature indices and a tiered analysis, we evaluate indoor temperature variations linked to roof type, ceiling insulation, presence of fans, and tree shade, for different housing types and locations. Our data reveal indoor temperatures in the range 22.4 degrees C to 45.9 degrees C for Accra, and 22.2 degrees C to 43.0 degrees C in Tamale. Using dummy regression analysis, we find that tree shade reduces the number of very hot days (>40 degrees C) and nights (>30 degrees C) by about 12 and 15 d per year, respectively. Building materials also strongly moderate indoor temperatures but in opposing ways: rooms with traditional mud walls and thatch roofs are on average 4.5 degrees C cooler than rooms in concrete block houses with uninsulated metal roofs during the day but are 1.5 degrees C warmer at night; rooms with ceiling insulation are on average 6.9 degrees C cooler in the day but 1.4 degrees C warmer at night. We conclude that sub-daily data are necessary for reporting extreme indoor temperatures, and that trade-offs between minimum and maximum temperatures require interventions to be assessed carefully before attempting to counter extreme heat inside homes.
The ability of poor urban populations in developing countries to adapt to rapid increase in surface temperature and likely health effect of a 1.5 °C increase in global temperature is uncertain. Rapid urbanization and poor socio, economic, and technological development may increase heat vulnerabilities of poor urban populations in tropical cities. This study examines the thermal perception of urban populations in Ibadan, south western Nigeria, and sociodemographic characteristics of individuals that influence thermal perception, self-reported health effects, and coping strategies to heat stress using a purposefully designed questionnaire and interviews with aged individuals in the five local government areas of Ibadan metropolis. Differences in sociodemographic characteristics of respondents such as inequalities in monthly income, occupation, ethnicity, housing characteristics, and length of stay in Ibadan significantly influence thermal perception, self-reported health effects of heat exposure, and coping strategies adopted. Perceived thermal conditions reported were warmer temperatures during the day and night (43.75%), warmer day-time temperatures (40.25%), and warmer night-time temperatures (16%). Dehydration and sweating (56%): heat rash, heat exhaustion, headaches, sleep disturbances and dehydration (15.25%), and sleep disturbance and sweating (12.25%) were major combinations of self-reported health effects. Other effects include fainting, diarrhea, raised blood pressure, and restlessness. Temperature variations (minimum and maximum) examined from 1971 to 2018 shows that warmer conditions are being experienced in Ibadan. Increased heat-health awareness and urban designs that respond to people’s thermal perception should be encouraged in developing thermally comfortable environments in Ibadan.
Both climate change and rapid urbanization accelerate exposure to heat in the city of Kampala, Uganda. From a network of low-cost temperature and humidity sensors, operational in 2018-2019, we derive the daily mean, minimum and maximum Humidex in order to quantify and explain intra-urban heat stress variation. This temperature-humidity index is shown to be heterogeneously distributed over the city, with a daily mean intra-urban Humidex Index deviation of 1.2 degrees C on average. The largest difference between the coolest and the warmest station occurs between 16:00 and 17:00 local time. Averaged over the whole observation period, this daily maximum difference is 6.4 degrees C between the warmest and coolest stations, and reaches 14.5 degrees C on the most extreme day. This heat stress heterogeneity also translates to the occurrence of extreme heat, shown in other parts of the world to put local populations at risk of great discomfort or health danger. One station in a dense settlement reports a daily maximum Humidex Index of >40 degrees C in 68% of the observation days, a level which was never reached at the nearby campus of the Makerere University, and only a few times at the city outskirts. Large intra-urban heat stress differences are explained by satellite earth observation products. Normalized Difference Vegetation Index has the highest (75%) power to predict the intra-urban variations in daily mean heat stress, but strong collinearity is found with other variables like impervious surface fraction and population density. Our results have implications for urban planning on the one hand, highlighting the importance of urban greening, and risk management on the other hand, recommending the use of a temperature-humidity index and accounting for large intra-urban heat stress variations and heat-prone districts in urban heat action plans for tropical humid cities.
Over the past years, cities have become more prone to extreme and frequent heatwaves. In this regard, urban form plays an important role and several typomorphological classifications have been developed to describe the urban form characteristics that can exacerbate heat stress and influence people’s health and comfort negatively (i.e. the environmental dimension of heat-stress resilience). Nevertheless, evidence from past heatwave disasters indicates that other urban form characteristics, not included in existing typomorphological classifications, can significantly affect heat-stress resilience by influencing the conditions of social interaction and the state of social ties and solidarities in urban neighborhoods (i.e. the social dimension). Therefore, this paper proposes a broader approach combining the aforementioned environmental and social dimensions in the classification of urban form types; and demonstrates its application in a real-world case by developing a data-driven typomorphological classification that complements existing ones with the missing social dimension. The results showed the possi-bility of numerically identifying neighborhood types that, through distinct urban form characteristics, have different potentials for enhancing the social dimension of heat-stress resilience. This has direct planning and design relevance as the quantifiable characteristics of these types can be translated into guidelines/rules and incorporated into local regulations/codes.
Heat stress-related illness attributed to the changing climate, particularly the more frequent extreme high temperatures, is becoming a theme of public concern, especially in the most vulnerable regions, such as the African continent. Knowledge of the existing research directions and gaps on heat stress and human health is vital for informing future strategic research foci capable of influencing policy development, planning, adaptation, and mitigation efforts. In this regard, a bibliometric analysis was conducted, with an emphasis on Africa, to assess regional research contributions to heat stress impacts on human health. The goals of the study were to review publication growth and patterns of the scientific publications and to identify key players (especially collaborating institutions and countries) and the evolution of research themes on the African continent, while paying attention to global trends and emergent hot topics and methodology of heat stress research. Using the Web of Science (WoS) and Scopus core collection databases, a structured keyword search was undertaken, which yielded 463 and 58 research publications from around the world and Africa, respectively. The retrieved scientific documents, published between 1968 and 2020, were analyzed and visualized using a bibliometric analysis technique and the VOSviewer software tool. The results indicate low statistics and slow scientific growth in publication output, with the highest peak having been reached in 2018, resulting in 13 scientific publications. While global research collaborations are successfully reflected in the literature, there is a considerable gap in understanding heat stress and related collaborations between African countries and international institutions. The review study has identified key opportunities that can benefit Africa through the expansion of the scope of heat stress and human health research on the continent. These opportunities can be achieved by closing the following research gaps: (1) vulnerability assessments within demographic classes, such as the elderly, (2) personal exposure and associated risks, (3) Urban Heat Island (UHI) evaluation for urban environments, and (4) heat adaptation research, which will enable informed and targeted preventive actions that will limit future heat health impacts. The authors opine that the pursuit of such studies will be most impactful if the current knowledge gaps are bridged through transdisciplinary research supported by local, regional, and international collaborators.
Climate change and expected weather patterns in the long-term threaten the livelihood inside oases settlements in arid lands, particularly under the recurring heat waves during the harsh months. This paper investigates the impact of climate change on the outdoor thermal comfort within a multifamily housing neighborhood that is considered the most common residential archetype in Algerian Sahara, under extreme weather conditions in the summer season, in the long-term. It focuses on assessing the outdoor thermal comfort in the long-term, based on the Perceived Temperature index (PT), using simulation software ENVI-met and calculation model RayMan. Three different stations in situ were conducted and combined with TMY weather datasets for 2020 and the IPCC future projections: A1B, A2, B1 for 2050, and 2080. The results are performed from two different perspectives: to investigate how heat stress evolution undergoes climate change from 2020 till 2080; and for the development of a mathematical algorithm to predict the outdoor thermal comfort values in short-term, medium-term and long-term durations. The results indicate a gradual increase in PT index values, starting from 2020 and progressively elevated to 2080 during the summer season, which refers to an extreme thermal heat-stress level with differences in PT index averages between 2020 and 2050 (+5.9 degrees C), and 2080 (+7.7 degrees C), meaning no comfortable thermal stress zone expected during 2080. This study gives urban climate researchers, architects, designers and urban planners several insights into predicted climate circumstances and their impacts on outdoor thermal comfort for the long-term under extreme weather conditions, in order to take preventive measures for the cities’ planning in the arid regions.
In 2015 and 2016, South Africa experienced a severe drought resulting in water restrictions and food price inflation. A year later, while the proportion of food secure households remained constant, the proportion of those experiencing severe food insecurity increased. This paper investigates the socio-economic determinants of increasing food insecurity during and after the drought. Two cross-sectional household surveys were carried out in the district of iLembe in November 2016 and 2017. Household food insecurity was measured using the Coping Strategies Index. The results indicated changes in socio-economic determinants of food insecurity over time, with the poorest households experiencing the worst levels of food insecurity. After the drought, having a child under-five years was positively associated with food insecurity, while being located in a rural area was negatively associated. Policies that limit household vulnerability to price inflation, and interventions that protect poorer households from the effects of drought should be considered.
According to the Intergovernmental Panel on Climate Change (IPCC), the global mean temperature is expected to increase from 1.4°C to 5.8°C by 2100. The implications will be particularly significant in urban areas as indoor and outdoor comfort levels will be disrupted, leading to significant health impacts. One of the expected impacts is indoor overheating, as it has been identified as one of the major causes of thermal discomfort and is directly linked to the potential increase in mortality levels in the future. This paper focuses on the potential implications of increased overheating hours on human health in an old low-income residential neighborhood. We study the effect of three main factors: population coping capacity, building thermal performance, and human physiological response to heat exposure. This is achieved by examining an old low-income neighborhood in Cairo, Egypt, whose residents have limited cooling systems access. Results indicate higher overheating risks in older buildings with a projected increase of 18% in indoor temperature and higher health risks, especially for elderly residents. The study’s findings can be considered a starting point to examine the relationship between exposure duration, indoor air temperature range, and potential health risks for vulnerable urban communities with limited access to cooling mechanisms such as AC units.
In this article we draw on an interdisciplinary study on drinking water quality in Maputo, the capital of Mozambique, to examine the nature, scale, and politics of waterborne diseases. We show how water contamination and related diseases are discursively framed as household risks, thereby concealing the politics of uneven exposure to contaminated water and placing the burden of being healthy on individuals. In contrast, we propose that uneven geographies of waterborne diseases are best understood as the product of Maputo’s urban metabolism, in which attempts at being sanitary and healthy are caught up in relations of power, class, and variegated citizenship. Waterborne diseases are the result of complex and fragmented circulations and intersections of (waste)waters, generated by uneven urban development, heterogeneous infrastructure configurations, and everyday practices to cope with basic service deficits, in conjunction with increasing climatic variability. The latrine-from which ultimately contamination and diseases spread-is an outcome of these processes, rather than the site to be blamed. This article also advances an interdisciplinary framework for analyzing urban metabolism and deepening its explanatory potential. It serves as a demonstration of how interdisciplinary approaches might be taken forward to generate new readings of more-than-human metabolic processes at distinct temporal and spatial scales.
Dengue contributes a significant burden on global public health and economies. In Africa, the burden of dengue virus (DENV) infection is not well described. This review was undertaken to determine the prevalence of dengue and associated risk factors. A literature search was done on PubMed/MEDLINE, Scopus, Embase, and Google Scholar databases to identify articles published between 1960 and 2020. Meta-analysis was performed using a random-effect model at a 95% confidence interval, followed by subgroup meta-analysis to determine the overall prevalence. Between 1960 and 2020, 45 outbreaks were identified, of which 17 and 16 occurred in East and West Africa, respectively. Dengue virus serotype 1 (DENV-1) and DENV-2 were the dominant serotypes contributing to 60% of the epidemics. Of 2211 cases reported between 2009 and 2020; 1954 (88.4%) were reported during outbreaks. Overall, the prevalence of dengue was 29% (95% CI: 20-39%) and 3% (95% CI: 1-5%) during the outbreak and non-outbreak periods, respectively. Old age (6/21 studies), lack of mosquito control (6/21), urban residence (4/21), climate change (3/21), and recent history of travel (3/21) were the leading risk factors. This review reports a high burden of dengue and increased risk of severe disease in Africa. Our findings provide useful information for clinical practice and health policy decisions to implement effective interventions.
Bangladesh, being the world’s most climate-vulnerable country, is affected by plenty of climate-related hazards every year, mostly along its south-western coast. As a consequence, many people relocated from these regions’ worst-affected neighborhoods to Khulna city, and began to live as slum dwellers. They faced a variety of issues in these informal settlements, particularly regarding water, sanitation, and hygiene (WASH) facilities and livelihood options, but no research has been conducted in Bangladesh. With an emphasis on WASH services and livelihood prospects, this study therefore aimed to provide a comprehensive understanding of the challenges/hardships and needs of climate migrants living in urban slums in both general and COVID-19 contexts. Qualitative methods were applied to collect data from the climate migrants of slums in five wards (3, 12, 17, 21, and 30) of the Khulna City Corporation. Nine focus group discussions and four key informant interviews were conducted to collect the data from primary (community people) and secondary (local government and non-government and community-based organizations officials) stakeholders. The thematic analysis was used to analyze the data. The findings revealed that climate migrants experienced significant water scarcity, insufficient drainage systems, a lack of toilets, tube wells, and bathing facilities, inadequate hygiene management, a lack of core skills required for urban jobs, low payment, and an income shortage. Similarly, sustainable drinking water sources, sanitary toilets with WASH blocks, personal hygiene materials and awareness building, skill development for diverse livelihood opportunities, and income-generating capacity development were their top priorities. Overall, the findings of this study provided a holistic overview of the challenges/hardships and needs of climate migrants in urban slums regarding WASH services and livelihood opportunities. The authorities should intervene and develop policy initiatives to alleviate the hardships and meet the needs of climate migrants.
Long-term trends in air quality by studying the criteria pollutants (PM2.5, PM10, CO, O-3, NO2, and SO2) and climate variables (temperature, surface pressure, and relative humidity) were depicted in this study. The 17-year (2003-2019) average values of PM2.5, PM10, CO, O-3, NO2, and SO2 were 88.69 +/- 9.76 mu g/m(3), 124.57 +/- 12.75 mu g/m(3), 0.69 +/- 0.06 ppm, 51.42 +/- 1.82 ppb, 14.87 +/- 2.45 ppb, and 8.76 +/- 2.07 ppb, respectively. The trends among the ambient pollutants were increasingly significant (p < 0.05) except for O-3 with slopes of 1.83 +/- 0.15 mu g/m(3)/year, 2.35 +/- 0.24 mu g/m(3)/year, 0.01 +/- 0.002 ppm/year, 0.47 +/- 0.03 ppb/year, and 0.40 +/- 0.02 ppb/year for PM2.5, PM10, CO, NO2, and SO2, respectively. Pearson correlations revealed a significant association among the pollutants while a noteworthy correlation was observed between ambient pollutants and surface temperature. Principal component analysis (PCA) and positive matrix factorization (PMF) have been employed collectively to examine the main sources of the pollutants. PCA revealed similar trends for PMs and CO, as well as NO2 and SO2 being equally distributed variables. PMF receptor modeling resulted in attributing four sources to the pollutants. The factors inferred from the PMF modeling were signified as vehicular emissions, road/soil dust, biomass burning, and industrial emissions. The hazard quotient (HQ) values were not antagonistic (HQ < 1) in acute exposure levels for the three age groups (infants, children, and adults) while showing significant health risk (HQ < 1) in chronic exposure for infants and children. Children are identified as the worst sufferers among the age groups, which points to low breathing levels and high exposure to traffic pollution in Dhaka, Bangladesh.
Toxic gaseous organic air pollutants such as benzene, toluene, ethylbenzene, and xylene isomers (m, p, and o-x) (BTEX) are considered hazardous due to its adverse impacts on human health and on climate change. This review identifies the major research questions addressed so far and the research gap in research articles, published between 2001 and 2022, focusing on the ambient BTEX concentrations in different locations in India along with its sources, ozone formation potential (OFP), and associated health risks. The ambient levels of BTEX were also compared with those of other Asian countries. A comparison of ambient BTEX levels with different microenvironments in India is also presented. BTEX concentrations were found in the range of 30.95 to 317.18 mu g m(-3) and multi-fold higher in urban environments than those measured in the rural air. In most reported studies, the order of occurrence of BTEX compounds was toluene > benzene > xylene isomers > ethylbenzene and winter had higher concentrations than in other seasons, including summer. As far as BTEX levels in classified areas of urban environments are concerned, traffic locations have shown the highest BTEX concentrations, followed by residential, commercial, and industrial locations. OFP indicated that xylene isomers and toluene contributed to ozone formation. The major gaps in reported studies on BTEX measurement are (1) source apportionment; (2) impact on lower tropospheric chemistry, human health, and climate change; and (3) removal techniques from air.
Climate change and air pollution have been a matter of serious concern all over the world in the last few decades. The present review has been carried out in this concern over the Indian cities with significant impacts of both the climate change and air pollution on human health. The expanding urban areas with extreme climate events (high rainfall, extreme temperature, floods, and droughts) are posing human health risks. The intensified heat waves as a result of climate change have led to the elevation in temperature levels causing thermal discomfort and several health issues to urban residents. The study also covers the increasing air pollution levels above the prescribed standards for most of the Indian megacities. The aerosols and PM concentrations have been explored and hazardous health impacts of particles that are inhaled by humans and enter the respiratory system have also been discussed. The air quality during COVID-2019 lockdown in Indian cities with its health impacts has also been reviewed. Finally, the correlation between climate change, air pollution, and urbanizations has been presented as air pollutants (such as aerosols) affect the climate of Earth both directly (by absorption and scattering) and indirectly (by altering the cloud properties and radiation transfer processes). So, the present review will serve as a baseline data for policy makers in analyzing vulnerable regions and implementing mitigation plans for tackling air pollution. The adaptation and mitigation measures can be taken based on the review in Indian cities to reciprocate human health impacts by regular air pollution monitoring and addressing climate change as well.
Global temperature rises in response to accumulating greenhouse gases is a well-debated issue in the present time. Historical records show that greenhouse gases positively influence temperature. Lockdown incident has brought an opportunity to justify the relation between greenhouse gas centric air pollutants and climatic variables considering a concise period. The present work has intended to explore the trend of air quality parameters, and air quality induced risk state since pre to during the lockdown period in reference to India and justifies the influence of pollutant parameters on climatic variables. Results showed that after implementation of lockdown, about 70% area experienced air quality improvement during the lockdown. The hazardous area was reduced from 7.52% to 5.17%. The spatial association between air quality components and climatic variables were not found very strong in all the cases. Still, statistically, a significant relation was observed in the case of surface pressure and moisture. From this, it can be stated that pollutant components can control the climatic components. This study recommends that pollution source management could be a partially good step for bringing climatic resilience of a region.
This study was carried out to evaluate the heavy metals (Lead (Pb), Nickel (Ni), Chromium (Cr), Copper (Cu), Cadmium (Cd) and Zinc (Zn)) pollution in the Noyyal River of South India by collecting 130 river water samples (65 each in pre- and post-monsoon). The heavy metals were measured using Atomic Absorption Spectrophotometer (AAS). The data were used to calculate the associated health hazards for the inhabitants consume river water. Correlation analyses and average concentration of heavy metals denoted that post-monsoon metal concentrations were lesser compared to the pre-monsoon due to dilution effect. Modified Contamination Degree (MCD) indicated that 45% of pre-monsoon and 25% of post-monsoon samples were classified under extremely polluted category. Heavy metal pollution index (HPI) showed that all the regions fall under highly polluted category except ‘Region I’ where 20% of samples were under safe category during the pre-monsoon, whereas 9%,28%, 17% and 26% of samples in Regions I, II, III and IV were highly polluted during the post-monsoon season, respectively. Ecological Risk Index (ERI) revealed that high risks attained in Regions II (78%) and III (82%) during pre-monsoon, and reduced risks found in Regions II (28%) and III (45%) during post-monsoon season due to dilution by monsoon rainfall. Non-carcinogenic risks as inferred by the Hazard Index (HI) indicated that 78% and 52% of samples for infants, 75% and 49% of samples for teens and 71% and 45% of samples for adults exceeded the threshold limits of USEPA (HI > 1) and possessed risks during pre- and post-monsoon, respectively. The cancer risk assessment based on ingestion of heavy metals indicated that the order of risk is Ni > Cr > Cu. The HI for infants and teens was notably high to that of adults in both the seasons. This study will be useful to develop effective strategies for improving river water quality and to reduce human health hazards.
Climate-induced pressures spur on the need for urban green infrastructure (UGI) planning. This approach offers a possible way to improve ecosystem functionality and human well-being in adversely affected urban regions, wherein UGI is perceived as a green and nature-based climate change mitigation/adaptation strategy. In Pakistan, the Khyber Pakhtunkhwa (KP) province lacks such urban landscape and greening policies (ULGP) or legislative frameworks for transitioning to green action plans (GAP), to alleviate the risk of multi-climatic hazards. Thus, this study aims to investigate a sustainable UGI-indicator-based framework model, based on the due inclusion of the concerned stakeholders. The relative importance index (RII) and inter-quartile range (IQR) techniques are employed for field data analysis. The findings proclaim excellent reliability (alpha > 0.7) and internal consistency, wherein sustainable UGI indicators are grouped based on their importance. The results portray the ecological and economic sustainability dimensions as being important (RII = 0.835 and RII = 0.807, respectively), socio-cultural dimensions as being moderately important (RII = 0.795), and a set of UGS elements (RII >= 0.77) as vital for bolstering individual UGI indicators. The main UGS elements emerging in each category can be grouped as follows: ecological category-“reducing rainwater runoff” (RII = 0.94); socio-cultural category-“enhancement of mental and physical health” (RII = 0.90); and eco category-“minimizing the risk of flood disasters” (RII = 0.96). The simulation results demonstrate the need for an inclusive perspective when building the urban green space (UGS) infrastructure (and standards) that will be most suitable for ensuring climate-resilient urban regions. This study contributes to putting the scientific research knowledge of the natural green-landscape-based (NBLB) approach into practice. The study calls for the establishment of an effective, pragmatic relationship between the urban landscape and greening policies, alongside a constructive relationship with the native inhabitants to ensure eco-friendly and resilient settlements.
Severe pneumonia is one of the leading contributors to morbidity and deaths among hospitalized under-five children. We aimed to assess the association of the socio-demographic characteristics of the patients and the climatic factors with the length of hospital stay (LoS) of under-five children with severe pneumonia managed at urban hospitals in Bangladesh. We extracted relevant data from a clinical trial, as well as collecting data on daily temperature, humidity, and rainfall from the Meteorological Department of Bangladesh for the entire study period (February 2016 to February 2019). We analyzed the data of 944 children with a generalized linear model using gamma distribution. The average duration of the hospitalization of the children was 5.4 ± 2.4 days. In the multivariate analysis using adjusted estimation of duration (beta; β), extended LoS showed remarkably positive associations regarding three variables: the number of household family members (β: 1.020, 95% confidence intervals (CI): 1.005-1.036, p = 0.010), humidity variation (β: 1.040, 95% Cl: 1.029-1.052, p < 0.001), and rainfall variation (β: 1.014, 95% Cl: 1.008-1.019), p < 0.001). There was also a significant negative association with LoS for children's age (β: 0.996, 95% Cl: 0.994-0.999, p = 0.006), well-nourishment (β: 0.936, 95% Cl: 0.881-0.994, p = 0.031), and average rainfall (β: 0.980, 95% Cl: 0.973-0.987, p < 0.001). The results suggest that the LoS of children admitted to the urban hospitals of Bangladesh with severe pneumonia is associated with certain socio-demographic characteristics of patients, and the average rainfall with variation in humidity and rainfall.
Urban parks play an essential role in urban settings; significantly contribute to the health of every age group person. Parks provide opportunities for families to connect with nature and breathe in the fresh air. Due to global climate change and increased urbanisation in the past few decades, extreme heat can be experienced in urban areas. Mental and physical health issues arise primarily due to a sedentary lifestyle in cities. Staying at parks for a longer duration could promote stress reduction and perceived physical health. The present study aims to assess the thermal comfort conditions at an urban park in the hot semi-arid climate(BSh) of Haryana, India. The present study investigated the outdoor thermal comfort range and thermal sensations of visitors at a park during the summer season using the onsite monitoring of the microclimate parameters and questionnaire survey in the hot-semi arid region of India. Thermal comfort indices, Physiological equivalent temperature (PET) and Universal Thermal Climate Index (UTCI) and Wet bulb globe temperature(WBGT) have been applied to investigate the outdoor thermal comfort conditions. The seven-point sensation scale has been used to record the visitors’ thermal sensations. The results indicated that:1) WBGT was found to be the most suitable index to investigate the OTC conditions. The neutral UTCI, PET, and WBGT ranged within 28.03 degrees C to 35.6 degrees C, 24.04 degrees C to 37.5 degrees C, and 23.5 degrees C to 26.1 degrees C, respectively. 2) The neutral PET ,UTCI, and WBGT were found to be 30.8 degrees C, 31.8 degrees C, and 24.8 degrees C, respectively.3) Dry bulb temperature is the most significant thermal comfort parameter affecting visitors’ thermal sensations, followed by mean radiant temperature.4) Thermal comfort indices were found to be most significantly affected by globe temperature. The study’s outcome could provide theoretical design reference to urban designers to develop new parks and existing parks, ultimately promoting public health. Copyright (c) 2022 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the F-EIR Conference 2021 on Environment Concerns and its Remediation: Materials Science
Rapid and unplanned urbanization has resulted in the settlement and expansion of marginalized communities in flood-prone areas. Consequently, the devastating impacts of urban flooding have increased recently, further augmented by the changing climatic patterns resulting in more frequent flooding. However, to effectively enhance resilience at the community level, it is essential first to understand its components and indicators. This study proposed and tested a methodology to assess community resilience against urban flooding – 57 indicators of resilience were identified, which were classified into six domains, namely social, economic, infrastructural, institutional, natural, and psychological. The data was collected through a questionnaire survey in three com-munities of Rawalpindi, Sialkot, and Muzaffargarh cities in the province of Punjab, Pakistan. The data of resilience indicators were standardized, and an index-based approach was used to assess the community resil-ience in the six domains. The relative importance of each domain was evaluated through input from field experts translated into weights through the analytic hierarchy process method. Thereafter, overall community resilience was constructed, and statistical methods were employed to compare resilience and its domains. A significant difference in resilience was observed among the selected communities. Recommendations based on relative urgency, complexity, and impact were devised to help institutions make informed decisions to improve com-munity resilience against floods.
BACKGROUND: Studies have documented a significant association between temperature and all-cause mortality for various cities but such data are unavailable for Hyderabad City. OBJECTIVE: The objective of this work was to assess the association between the extreme heat and all-cause mortality for summer months (March to June) from 2006 to 2015 for Hyderabad city population. METHODS: We obtained the data on temperature and all-cause mortality for at least ten years for summer months. Descriptive and Bivariate analysis were conducted. Pearson correlation coefficient was used to study the relationship between heat and all-cause mortality for lag time effect. RESULTS: A total of 122,117 deaths for 1,220 summer days (2006 to 2015) were analyzed with mean daily all-cause mortality was 100.1±21.5. There is an increase of 16% and 17% per day mean all-cause mortality at the maximum temperature of less than or equal to 40 degrees C and for extreme danger days (Heat Index greater than 54 degrees C) respectively. The mean daily all-cause mortality shows a significant association with maximum temperature (P < 0.001) and Heat Index from caution to extreme danger risk days (P<0.0183). The lag effect of extreme heat on all-cause mortality for the study period (2006 to 2015) was at peak on same day of the maximum temperature (r = 0.273 at p<0.01). CONCLUSION: The study concludes that the impact of ambient heat in the rise of all-cause mortality is clearly evident (16% mean deaths/day). There was no lag effect from the effect of extreme heat on all-cause mortality as the peak period was the same as the maximum temperature. Hence heat action plans are needed. However, extreme heat-related mortality merits further analysis.
BACKGROUND: Record-breaking temperatures have occurred more frequently worldwide under the trend of climate change. It has increased the number of people at heat related medical conditions resulting in both mortality and morbidity from heat stress. This study aimed to assess factors associated with vulnerability to heat stress, its health effects among people of Nepalgunj Sub-metropolitan, and identify various coping strategies adopted. METHODS: Cross-sectional analytical study was conducted among 366 research participants selected through multi-stage random sampling technique in Nepalgunj Sub-metropolitan. Heat Index was assessed using secondary analysis of meteorological data of Nepalgunj (Airport) station. Chi-square test was done to analyze the primary data. RESULTS: Out of 366 participants, 224 (61.2%) participants had heat related symptoms in the past 6 months (April to September) from the date of the interview. Sex, education, income, roof construction, Cross-ventilation, working hour per day, presence of chronic disease, and medications use had a significant association with heat related symptoms among the participants (p<0.05) The most common coping strategies adopted to manage heat stress were the use of cooling methods, wearing light clothing, and bathing by cold water. The average monthly heat index was highest in August (42 °C) and lowest in April (29°C). CONCLUSIONS: The majority of the participants had heat related symptoms in the study area. In order to mitigate the heat stress in the urban town like Nepalgunj, measures such as tree plantation, reducing vehicle smoke emissions, and developing proper housing ventilation can be applied.
As a result of global climate change, the frequency and intensity of heat waves have increased significantly. According to the World Meteorological Organization (WMO), extreme temperatures in southwestern Pakistan have exceeded 54 degrees C in successive years. The identification and assessment of heat-health vulnerability (HHV) are important for controlling heat-related diseases and mortality. At present, heat waves have many definitions. To better describe the heat wave mortality risk, we redefine the heat wave by regarding the most frequent temperature (MFT) as the minimum temperature threshold for HHV for the first time. In addition, different indicators that serve as relevant evaluation factors of exposure, sensitivity and adaptability are selected to conduct a kilometre-level HHV assessment. The hesitant analytic hierarchy process (H-AHP) method is used to evaluate each index weight. Finally, we incorporate the weights into the data layers to establish the final HHV assessment model. The vulnerability in the study area is divided into five levels, high, middle-high, medium, middle-low and low, with proportions of 3.06%, 46.55%, 41.85%, 8.53% and 0%, respectively. Health facilities and urbanization were found to provide advantages for vulnerability reduction. Our study improved the resolution to describe the spatial heterogeneity of HHV, which provided a reference for more detailed model construction. It can help local government formulate more targeted control measures to reduce morbidity and mortality during heat waves.
Internally displaced people (IDP) due to conflict and violence were estimated as 41.3 million in 55 countries as the end of the year 2019, the highest figure ever recorded. Sri Lanka has not yet prioritized the health and wellbeing of households in building designing, with the emerging heat island effect making the lives more desperate for IDP. This study focused on the effect of energy poverty on occupant comfort in determining the quality of life of people and adaptive behaviors to manage heat strain in overheated interiors of rehabilitated residences in Jaffna, Sri Lanka. Field investigations consisted of personal monitoring, questionnaire surveying and physical measurements in four clusters of rehabilitation residence programmes in four regions. The study found that IDP were suffering from hidden energy poverty, with mean electricity consumption of 52 kWh per household per month. Residents have marginal (29%) access to clean fuels for cooking and accountable for an abnormal particulate matter count of 360 951 particles per cubic centimeter. Findings explicitly revealed the presence of overheated spaces with mean thermal preference of-0.6 conveying the need of cooler indoor environment. People tend to exhibit behavioral adjustments to cope up with prevailing extreme temperatures. Severity of heat stress informed by modified wet bulb globe temperature (WBGT) reporting 90% (28-31 degrees C) of households facing higher risk of heat strain while remaining 10% (>31 degrees C) are in hazardous situation. Predicted mean vote (PMV) was 1.29 explains warm sensation with predicted percentage of dissatisfied (PPD) 44.1% not complying to ASHRAE 55 standards. This detrimental combination of fuel poverty, lack of thermal comfort, and unacceptable indoor air quality has been a significant factor for 62% of the residences reporting at least one type of illness and being more prone to cardiovascular and respiratory disorders (37%). Thus, the study evidenced the presence of energy poverty and overheated interiors in the IDP’s residences in hot tropics of Sri Lanka. (c) 2021 Elsevier B.V. All rights reserved.
Extreme heat is an increasing climate risk due to climate change and the urban heat island (UHI) effect and can jeopardize points of dispensing (PODs) for COVID-19 vaccination distribution and broader public health emergency preparedness (PHEP) response operations. These PODs were often located on large parking lot sites with high heat severity and did not take heat mitigation or management strategies into account for unacclimated workers and volunteers. To investigate the personal heat exposure of workers, volunteers, and clients at three PODs in Tucson, Arizona, we collected ambient air temperatures, wet bulb globe temperatures (WBGT), surface temperatures, and thermal images. We also made qualitative observations and compared data against daily meteorological records. Ambient air temperatures at all three PODs exceeded the meteorological recorded high. WBGT on average were 8°F (4.4 °C) higher in full sun locations than shaded locations such as tents. Evaporative cooling decreased ambient air temperatures by 2°F (1.2 °C) when placed one per tent, but decreased ambient air temperatures by 7°F (3.9 °C) when placed en masse in a larger tent. Vehicle surface temperatures exceeded recommended safe limits of 140°F (60 °C) at all three sites, with a maximum temperature recorded at 170.9°F (77.2 °C). Public health professionals should consider heat resilience, including heat mitigation and management measures, in POD and PHEP response operations to reduce exposure. This includes considering the UHI effect in the siting of PODs, applying heat mitigation strategies in the design of PODs such as the adaptive use of solar panels for shading, and improving heat safety guidance for workers and volunteers.
The Intergovernmental Panel on Climate Change (IPCC) report highlights the projected increase in heat wave (HW) frequency, intensity, and duration. Globally, HW events have caused massive deaths in the past. India has also experienced severe HWs and thousands have reportedly died during the past decade. The study uses the Local Climate Zone (LCZ) classification developed by Stewart and Oke (2012) for evaluating heat stress at the city level during the summer period. Stationery surveys were conducted to collect micro-meteorological data in different LCZs. The study analyses the unique behaviour of mapped LCZs in Nagpur, a tropical landlocked Indian city using widely adopted heat indices (heat index and humidex). It investigates two kinds of probabilities, the distribution of heat stress levels in a particular LCZ and how vulnerable are various LCZs to a given heat stress level. It adopts a statistical approach fitting a predictive logit model to estimate the probability of heat stress in various LCZs. The results show that temperature regimes differ significantly across the LCZs. Secondly, heat stress varies greatly depending upon the LCZs. The mapping scheme and the corresponding heat stress provides indispensable information for targeted heat response planning and heat stress mitigation strategies in heat-prone areas.
The unplanned and uncontrolled urbanization of Indian cities has put them under different ecological and environmental threats. Urban heat island (UHI) is one such critical ecological hazard, whereby an urban area is experiencing higher land surface temperature (LST) as compared to the surrounding rural area. In the present study, the relationship of LST and surface urban heat island (SUHI) with the degree of impervious surface (IS) and green spaces (GS) in four rapidly growing Indian cities is presented. This study utilizes different geospatial techniques, including urban-rural gradient analysis, surface urban heat island estimation using Landsat OLI/TIRS data. The results signify a strong negative correlation of LST with the IS for Ahmedabad, Jodhpur, and Nagpur, while a positive correlation is seen over Guwahati. The negative correlation is the manifestation of the urban cool island, pertaining to higher LST over rural areas. On the other hand, Guwahati is surrounded by green vegetation, which provides natural cooling and thus lowers the LST, resulting in positive SUHI. The density of GS is found to be a significant contributor of SUHI in Guwahati city, whereas in the other three cities, its impact is insignificant due to its presence in very less amount in rural surroundings.
Extreme heat and heat waves have been established as disasters which can lead to a great loss of life. Several studies over the years, both within and outside of India, have shown how extreme heat events lead to an overall increase in mortality. However, the impact of extreme heat, similar to other disasters, depends upon the vulnerability of the population. This study aims to assess the extreme heat vulnerability of the population of four cities with different characteristics across India. This cross-sectional study included 500 households from each city across the urban localities (both slum and non-slum) of Ongole in Andhra Pradesh, Karimnagar in Telangana, Kolkata in West Bengal and Angul in Odisha. Twenty-one indicators were used to construct a household vulnerability index to understand the vulnerability of the cities. The results have shown that the majority of the households fell under moderate to high vulnerability level across all the cities. Angul and Kolkata were found to be more highly vulnerable as compared to Ongole and Karimnagar. Further analysis also revealed that household vulnerability is more significantly related to adaptive capacity than sensitivity and exposure. Heat Vulnerability Index can help in identifying the vulnerable population and scaling up adaptive practices.
Heat waves are expected to intensify around the globe in the future, with a potential increase in heat stress and heat-induced mortality in the absence of adaptation measures. India has high current exposure to heat waves, and with limited adaptive capacity, impacts of increased heat waves might be quite severe. This paper presents a comparative analysis of urban heat stress/heatwaves by combining temperature and vapour pressure through two heat stress indices, i.e., Wet Bulb Globe Temperature (WBGT) and humidex index. For the years 1970-2000 (historical) and 2041-2060 (future), these two indicators were estimated in Jaipur. Another goal of this research is to better understand Jaipur land use changes and urban growth. For the land use study, Landsat 5 TM and Landsat 8 OLI satellite data from the years 1993, 2010, and 2015 were examined. During the research period, urban settlement increased and the majority of open land is converted to urban settlements. In the coming term, all months except three, namely July to September, have seen an increase in the WBGT index values; however, these months are classified as dangerous. Humidex’s historical value has been 21.4, but in RCP4.5 and RCP8.5 scenarios, it will rise to 25.5 and 27.3, respectively, and slip into the danger and extreme danger categories. The NDVI and SAVI indices are also used to assess the city’s condition during various periods of heat stress. The findings suggest that people’s discomfort levels will rise in the future, making it difficult for them to work outside and engage in their usual activities.
Urban climate changes and the warming of the cities are serious issues that cannot be overlooked. One of the most common inferences for these changes is unprecedented and unplanned urbanization, which further causes a rise in local, regional, and even global temperatures. Although the rate of urbanisation defines and greatly influences the city’s socioeconomic worth and GDP per capita, if the urban expansion is hap-hazardous, it can cause serious environmental harm.There has been a steep rise in global urban population over the past three decades, and the highest growth rates have been observed in Asian and African cities. These two continents have been predicted to contribute to almost 90% of the total urban growth from the present to 2050. India is one of the few highly susceptible countries to the harsh effects of climate change in terms of rise in temperatures. After 1990s’, India has observed substantial changes in the landscape due to urbanization, which has led to a significant rise in the surface and ambient air temperatures, further affecting the planet’s health. Elevated temperature drastically affects the health of urban dwellers leading to a rise in stress and discomfort levels. Estimation of Land Surface Temperature (LST) can play a vital role in understanding the region-specific alterations in temperatures as it uses satellite data that captures the entire region and provides the information in the form of pixels. Traditionally, the temperature was measured at meteorological stations and extrapolated for the entire region,whichinduces inaccuracies. This ambiguity can be amended by developing a relationship between LST and ambient air temperature. This communication focuses on LST estimation using Radiative Transfer Equation algorithm corresponding to various Landuse categories. The study also attempts to create a relationship between the LST and the ambient air temperature observed at two meteorological stations. An overall assessment of the number of days under stress for the residents was also performed over several years. Kolkata Metropolitan Area was considered the study area to represent the results and understand the complete analysis. A rise of 6.77 degrees C was observed in LST over the study period (2000-2019) due to an increment of 200% in the urban area. Analysis of the number of days under stress showed an increasing trend for the study area due to alterations in urban temperatures. These results and the suggestions from the scientific community, urban planners, and climate experts will help develop or modify the current policy frameworks for creating a balance between development and the environment, thus creating sustainable urban development.
The elderly are one of the most vulnerable groups to heat-related illnesses and mortality. In tropical countries like India, where heat waves have increased in frequency and severity, few studies have focused on the level of stress experienced by the elderly. The study presented here included 130 elderly residents of Kolkata slums and 180 elderly residents of rural villages about 75 km south of Kolkata. It used miniature monitoring devices to continuously measure temperature, humidity, and heat index experienced during everyday activities over 24-h study periods, during hot summer months. In the Kolkata slum, construction materials and the urban heat island effect combined to create hotter indoor than outdoor conditions throughout the day, and particularly at night. As a result, elderly slum residents were 4.3 times more likely to experience dangerous heat index levels (≥ 45°C) compared to rural village elderly. In both locations, the median 24-h heat indexes of active elderly were up to 2°C higher than inactive/sedentary elderly (F = 25.479, p < 0.001). Among Kolkata slums residents, there were no significant gender differences in heat exposure during the day or night, but in the rural village, elderly women were 4 times more likely to experience dangerous heat index levels during the hottest times of the day compared to elderly men. Given the decline in thermoregulatory capacity associated with aging and the increasing severity of extreme summer heat in India, these results forecast a growing public health challenge that will require both scientific and government attention.
The impact of heat stress among the elderly in India-particularly the elderly poor-has received little or no attention. Consequently, their susceptibility to heat-related illnesses is virtually unknown, as are the strategies they use to avoid, or deal with, the heat. This study examined perceptions of comfort, heat-related symptoms, and coping behaviors of 130 elderly residents of Kolkata slums and 180 elderly residents of rural villages south of Kolkata during a 90-day period when the average 24-h heat indexes were between 38.6 °C and 41.8 °C. Elderly participants in this study reported being comfortable under relatively warm conditions-probably explained by acclimatization to the high level of experienced heat stress. The prevalence of most heat-related symptoms was significantly greater among elderly women, who also were more likely to report multiple symptoms and more severe symptoms. Elderly women in the rural villages were exposed to significantly hotter conditions during the day than elderly men, making it likely that gender differences in symptom frequency, number and severity were related to gender differences in heat stress. Elderly men and elderly village residents made use of a greater array of heat-coping behaviors and exhibited fewer heat-related symptoms than elderly women and elderly slum residents. Overall, heat measurements and heat-related symptoms were less likely to be significant predictors of most coping strategies than personal characteristics, building structures and location. This suggests that heat-coping behaviors during hot weather were the result of complex, culturally influenced decisions based on many different considerations besides just heat stress.
Cities are becoming hotter day-by-day because heat is trapped near the earth’s surface due to a decrease in green cover, rapid urbanization, energy-intensity activities, and concrete structures. The four major metropolitan cities of India, i.e. Kolkata, Chennai, Delhi and Mumbai, have experienced heat waves and heat stress frequently during the summer season. This study analyses heat wave and heat stress patterns in these cities using 30 years of data from 1990 to 2019 during the summer season. We used daily maximum temperature, relative humidity, wind speed and solar radiation datasets for the above mentioned period in this study. To understand the episode of a heat wave, we have used the 95th percentile method. Furthermore, we have also used Humidity Index (HD) to evaluate the degree of discomfort and the Universal Thermal Climate Index (UTCI) to categorize the level of heat stress. The analysis indicates that the number of heat wave events in the Delhi region is 26.31%, 31.58% and 63.16% higher than Kolkata, Chennai, and Mumbai regions respectively. It is also seen that the risks of extreme heat stress and dangerous-heat stroke events in the Chennai region during heat wave periods are higher than that experienced in other metropolitan cities because of high temperature with higher values of relative humidity. The risk of extreme heat stress is less in Delhi because of lower relative humidity compared to other metropolitan cities although temperature is higher in this region. However, the risk of extreme heat stress is lower in Mumbai region because of relatively lower temperature than Chennai during summer season. The likelihood of experiencing great discomfort during heat wave periods in Kolkata city is higher than that experienced in other metropolitan cities in India, however, during non-heat wave periods the probability of extreme discomfort is higher in Chennai.
Introduction: Dengue is a mosquito borne viral disease. found in tropical and subtropical countries. Dengue virus (DENV) infected mosquitoes of Aedes species are crucial for the transmission of disease. It has emerged as a threat to the public health systems. Dengue is endemic in many parts of India but still the status of dengue cases in Rewa Madhya Pradesh is not reported convincingly. Aim: To investigate the presence of dengue in Rewa district of Madhya Pradesh. Materials and Methods: This cross-sectional study was conducted in the Department of Microbiology at Shyam Shah Medical college Rewa under National Vector Borne Disease Control Programme (NVBDCP), Rewa, Madhya Pradesh, India, including 1113 Outpatient/Inpatient Department samples received during March 2021 to October 2021. Blood samples were collected from patients having febrile illness and after serum separation, serum were subjected to NS1 Enzyme Linked Immunosorbent Assay (ELISA) test. Descriptive statistics and Chi-square tests were applied for data analysis. Results: A total of 1113 sample were received and tested for dengue NS1 out of that 108 sample were found NS1 positive by ELISA. The cases of dengue started from the month of July 2021. But in the month of October dengue positivity was highest in number. Dengue cases reported were 297 (6.73%) in the rainy season (July-August), but the dengue positivity increased (713, 9.3%) in the post rainy season (September-October). Overall prevalence of dengue was higher in the 21-30 years (34.3%) age group followed by 11-20 years (24.1%), 31-40 years (18.5%), 41-50 years (18.5%), 51-60 years (7.4%) and >60 years (3.70%) age groups with respect to total positive cases. The prevalence of dengue was higher in male (12.94%) in comparison to females (5.54%). Conclusion: This study warrants the dengue virus infection as one of the important causes of fever during rainy and post rainy season in this region. Early diagnosis and reporting of cases are important for the better management of disease.
In recent decades, dengue has been expanding rapidly in the tropical cities. Even though environmental factors and landscape features profoundly impact dengue vector abundance and disease epidemiology, significant gaps exist in understanding the role of local environmental heterogeneity on dengue epidemiology in India. In this study, we assessed the role of remotely sensed climatic factors (rainfall, temperature and humidity) and landscape variables (land use pattern, vegetation and built up density) on dengue incidence (2012-2019) in Bhopal city, Central India. Dengue hotspots in the city were assessed through geographical information system based spatial statistics. Dengue incidence increased from 0.59 cases in 2012 to 9.11 cases in 2019 per 10,000 inhabitants, and wards located in Southern Bhopal were found to be dengue hotspots. Distributed lag non-linear model combined with quasi Poisson regression was used to assess the exposure-response association, relative risk (RR), and delayed effects of environmental factors on dengue incidence. The analysis revealed a non-linear relationship between meteorological variables and dengue cases. The model shows that the risk of dengue cases increases with increasing mean temperature, rainfall and absolute humidity. The highest RR of dengue cases (~2.0) was observed for absolute humidity ≥60 g/m3 with a 5-15 week lag. Rapid urbanization assessed by an increase in the built-up area (a 9.1% increase in 2020 compared to 2014) could also be a key factor driving dengue incidence in Bhopal city. The study sheds important insight into the synergistic effects of both the landscape and climatic factors on the transmission dynamics of dengue. Furthermore, the study provides key baseline information on the climatic variables that can be used in the micro-level dengue prediction models in Bhopal and other cities with similar climatic conditions.
Mitigation behaviours regarding climate change are actions that seek to halt or reduce greenhouse gas emissions. Adaptive responses, on the other hand, are coping reactions to this phenomenon. The research presented here tested out an explanatory model for mitigation behaviours and coping reactions in response to the phenomenon of climate change (perceived risk and impact on the environment and health) based on beliefs regarding CC, obstacles to protect oneself from this phenomenon and intention to act. A total of 370 people from two Mexican cities took part in the research. The findings, processed by a structural equations model, show that beliefs regarding CC influence coping responses and intention to act, which in turn positively impact mitigation behaviours in response to CC. Beliefs regarding CC did not affect the perception of obstacles to protect oneself from climate change. Furthermore, the perception of obstacles and coping responses similarly did not influence intention to act.
This research was carried out to analyze variations in indoor and outdoor ozone concentrations and their health impact on local communities of megacities in Pakistan. For indoor ozone measurements, industrial units of an economic zone, Hattar Industrial Estate, Haripur, KPK, Pakistan, were selected. For outdoor ozone measurements, maximum and minimum peaks from different selected stations of three megacities (Islamabad, Abbottabad, and Haripur Hattar) in Pakistan were analyzed for paired comparisons. The tropospheric ozone levels were measured with the help of a portable SKY 2000-WH-O-3 meter from December 2018 to November 2019. According to the findings of this investigation, the indoor ozone concentrations at Hattar Industrial Estate exceeded the permissible limit devised by the WHO. The highest concentration (0.37 ppm) was recorded in the month of May in the food industry, while the lowest concentration (0.00 ppm) was recorded in the cooling area of the steel industry in the month of December. For outdoor ozone concentrations, the maximum concentration (0.23 ppm) was detected in Islamabad in the month of March 2019, whereas the rest of year showed comparatively lower concentrations. In Haripur, the maximum concentration (0.22 ppm) was detected in the month of February 2019 and a minimum concentration (0.11 ppm) was found in the month of November 2019. In Abbottabad, the maximum concentration (0.21 ppm) was detected in the month of March 2019 and the minimum concentration was 0.082 ppm. Increasing tropospheric ozone levels might be harmful for local communities and industrial laborers in the winter season because of the foggy weather. In the Abbottabad and Hattar regions, since COVID infection is indirectly related to low temperature and high emission of gases may compromise the respiratory systems of humans. The results of the present study were shared with industrialists to set precautions for ambient air quality and support the adoption of low emission techniques in industries for the safety of labour and nearby residents.
Pakistan ranks third in the world in terms of mortality attributable to air pollution, with aerosol mass concentrations (PM2.5) consistently well above WHO (World Health Organization) air quality guidelines (AQG). However, regulation is dependent on a sparse network of air quality monitoring stations and insufficient ground data. This study utilizes long-term observations of aerosols and trace gases to characterize and rank the air pollution scenarios and pollution characteristics of 80 selected cities in Pakistan. Datasets used include (1) the Aqua and Terra (AquaTerra) MODIS (Moderate Resolution Imaging Spectmradiometer) Level 2 Collection 6.1 merged Dark Target and Deep Blue (DTB) aerosol optical depth (AOD) retrieval products; (2) the CAMS (Copernicus Atmosphere Monitoring Service) reanalysis PM1, PM2.5, and PM10 data; (3) the MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Version 2) reanalysis PM2.5 data, (4) the OMI (Ozone Monitoring Instrument) tropospheric vertical column density (TVCD) of nitrogen dioxide (NO2), and VCD of sulfur dioxide (SO2) in the Planetary Boundary Layer (PBL), (5) the VIIRS (Visible Infrared Imaging Radiometer Suite) Nighttime Lights data, (6) MODIS Collection 6 Version 2 global monthly fire location data (MCD14ML), (7) population density, (8) MODIS Level 3 Collection 6 land cover types, (9) AERONET (AErosol RObotic NETwork) Version 3 Level 2.0 data, and (10) ground-based PM2.5 concentrations from air quality monitoring stations. Potential Source Contribution Function (PSCF) analyses were performed by integrating with ground-based PM2.5 concentrations and the NOAA (National Oceanic and Atmospheric Administration) HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) air parcel back trajectories to identify potential pollution source areas which are responsible for extreme air pollution in Pakistan. Results show that the ranking of the top polluted cities depends on the type of pollutant considered and the metric used.For example, Jhang, Multan, and Vehari were characterized as the top three polluted cities in Pakistan when considering AquaTerra DTB AOD products; for PM1, PM2.5, and PM10 Lahore, Gujranwala, and Okara were the top three; for tropospheric NO2 VCD Lahore, Rawalpindi, and Islamabad and for PBL SO2 VCD Lahore, Mirpur, and Gujranwala. The results demonstrate that Pakistan’s entire population has been exposed to high PM2.5 concentrations for many years, with a mean annual value of 54.7 mu g/m(3), over all Pakistan from 2003 to 2020.This value exceeds Pakistan’s National Environmental Quality Standards (Pak-NEQS, i.e., <15 mu g/m(3) annual mean) for ambient air defined by the Pakistan Environmental Protection Agency (Pak-EPA) as well as the WHO Interim Target-1 (i.e., mean annual PM2.5 < 35 mu g/m(3)).The spatial analyses of the concentrations of aerosols and trace gases in terms of population density, nighttime lights, land cover types, and fire location data, and the PSCF analysis indicate that Pakistan's air quality is strongly affected by anthropogenic sources inside of Pakistan, with contributions from surrounding countries.Statistically significant positive (increasing) trends in PM1, PM2. 5, PM10, tropospheric NO2 VCD, and SO2 VCD were observed in similar to 89%, similar to 67%, similar to 48%, 91%, and similar to 88% of the Pakistani cities (80 cities), respectively. This comprehensive analysis of aerosol and trace gas levels, their characteristics in spatio-temporal domains, and their trends over Pakistan, is the first of its kind. Results will be helpful to the Ministry of Climate Change (Government of Pakistan), Pak-EPA, SUPARCO (Pakistan Space and Upper Atmosphere Research Commission), policymakers, and the local research community to mitigate air pollution and its effects on human health.
Air pollution is one of the most challenging global sustainability problems in the world. Roughly 90% of global citizens live in areas that exceed the acceptable air pollution levels according to the World Health Organization air quality guidelines. However, socially disadvantaged groups are disproportionately located in areas exposed to higher levels of air pollution. Understanding the association between risk exposure to air pollutants and the underlying socio-economic factors determining risk is central for sustainable urban planning. The purpose of this study was to explore environmental inequalities in Mexico City, specifically the spatial association between air pollutants and socioeconomic status (SES) indicators. We propose that SES indicators will be expected to spatially cluster vulnerable individuals and groups into heavily polluted areas. To test this hypothesis, we used 2017-2019 data from governmental records to perform spatial interpolations to explore the spatial distribution of criteria pollutants. We carried out spatial autocorrelations of air pollutants and SES indicators using the bivariate Moran’s I index. Our findings provide strong evidence of spatial heterogeneity in air pollution exposure in Mexico City. We found that socially deprived areas located in the southern periphery of Mexico City were exposed to higher ozone concentrations. On the contrary, wealthiest areas concentrated in the city center were exposed to greater concentrations of nitrogen dioxide and carbon monoxide. Our findings highlight the need for policy-driven approaches that take into consideration not only the geographic variability and meteorological dynamics associated with air pollution exposure, but also the management of socioeconomic risk factors aimed at reducing disparate exposure to air pollution and potential health impacts.
The urban heat island (UHI) is mostly due to urbanization. This phenomenon in concert with the high temperatures caused by global climate change may profoundly affect human thermal comfort, which can influence human productivity and morbidity especially in spring/summer period. The main objective of this investigation was to determine changes in degree of thermal comfort of Mexico City’s inhabitants and compare it with the physiological equivalent temperature (PET) to evaluate whether PET and its categorization are adequate to be applied in Mexico City. A series of microclimatological measurements to estimate PET were made at four sites including the city’s center. Concomitantly, a series of surveys of thermal perception were applied to 1300 passersby. The results show that PET has increased from 1990 to 2020 from 0.1208 degrees C/year to 0.1498 degrees C/year in the study sites, in addition to overestimating the degree of thermal comfort of people according to the stablished categories or classes. It is concluded that it is necessary to adjust thermal stress categories. Knowing the percentages of people without thermal comfort will lead us to determine different ranges in environmental parameters to define an acceptable environment for most people.
Canada’s cities are leading the efforts to stem the harmful effects of the climate emergency on human health. Paul Webster reports from Toronto.
The built environment is a physical determinant of health essential to the planning and development of a more equitable society. Communities face growing challenges due to environmental stressors such as climate change, with vulnerable communities experiencing a disproportionate burden of adverse health outcomes. The interdependencies between urban planning and public health outcomes are inextricable, with respect to improving access to healthier built environments for vulnerable and marginalized groups. Widespread implementation of nature-based solutions, such as green infrastructure, provides a multi-functional strategy to support sustainable development, increase climate resilience, enhance ecological connectivity, and create healthier communities. A Health Equity Impact Assessment presents the findings of a participatory research study utilizing key informant interviews of public health unit professionals (eight) and a survey of green infrastructure volunteers and workers (36) on the impact of green infrastructure on individual and community mental and physical well-being, service use, and perceived unmet needs, using Ontario, Canada as a case study. Study findings indicate that where green infrastructure is both productive and publicly accessible, the benefits were significant for vulnerable populations. These benefits include increased social connectivity, skills development, and food security. Green infrastructure could be a viable strategy to address environmental stressors, improve health equity, and support localization of the UN Sustainable Development Goals (SDGs).
We examined the extent to which cities’ climate change adaptation plans, in U.S. cities broadly and in shrinking cities, discuss health equity/justice, including injustices related to green spaces. Using content analysis of 88 cities’ climate change adaptation plans, we coded for health, equity/justice, parks/green space, and joint usage of these terms. We made comparisons of keyword usage between shrinking and non-shrinking cities to examine how shrinking cities-with overlapping vulnerabilities and industrial legacies-differ from stronger market cities. Although health (97%) and equity/justice (81%) were common, only half of the cities discussed health and equity/justice concurrently, with overrepresentation from shrinking cities. Parks/green space were discussed alongside these themes in 28% of cities. Health equity emerged more in shrinking cities and recent plans (e.g., since 2018), suggesting recent shifts toward equity. Many cities vaguely described health equity solutions, necessitating clearer solutions for injustices, including parks/green space as climate adaptation and health infrastructure.
Natural and anthropogenic hazards are increasingly becoming commonplace due to climate change and population pressures. The state of Texas is particularly vulnerable to these hazards and is ranked first in the USA due to the immense variety and frequency of large-scale events. While much research has looked at the immediate impacts these incidents have on mental health, little research has addressed the effects of compounding and repeated exposure to hazards. This cross-sectional study (N = 1224) collected survey data from a representative sample within the Houston Metropolitan Statistical Area. Utilizing the 12 item Short Form Health Survey version 2, a general composite score assessing mental health was compared against the type and frequency of hazard exposures. Findings revealed an observed reduction in mental health scores as participants had repeated exposures to major disasters. Further, the only significant result (p < 0.001) in dictating a reduced mental health scores was repeat exposure to hazards even after adjusting for demographic data and socioeconomic variables. This research reveals the long-term mental impact hazard exposures can have and underscores the need for target public health interventions and engaged community efforts.
The increase in worldwide population is putting much pressure on the existent urban management plans. In this context, strategies and policies should be updated to conserve natural resources, but more importantly, to improve inhabitants’ well-being. Studies focusing on pervious areas have many potentials, particularly regarding the assessment of potential green infrastructures within the vicinities of cities. This study highlights the pervious area change between 2001 and 2016 within every county in the CONtiguous United States (CONUS) based on the National Land Cover Database (NLCD). The study found that 43 different counties can be considered dense. A statistical analysis is followed, highlighting the air temperature, wind speed, precipitation, solar radiation, and Normalized Difference Vegetation Index (NDVI) trends in five characteristic counties. These datasets were retrieved from diverse remote sensing and satellite platforms between 1980 and 2019. The main results also found that air temperature was significantly (at alpha = 0.95) increasing for the same period. The other climatic variables depict fluctuating and usually insignificant trends. Such information would benefit decisionand policy makers to focus their initiatives towards the most vulnerable counties while projecting different scenarios based on their current and historical conditions. Furthermore, this approach can be portable to other countries.
While conceptual definitions provide a foundation for the study of disasters and their impacts, the challenge for researchers and practitioners alike has been to develop objective and rigorous measures of resilience that are generalizable and scalable, taking into account spatiotemporal dynamics in the response and recovery of localized communities. In this paper, we analyze mobility patterns of more than 800,000 anonymized mobile devices in Houston, Texas, representing approximately 35% of the local population, in response to Hurricane Harvey in 2017. Using changes in mobility behavior before, during, and after the disaster, we empirically define community resilience capacity as a function of the magnitude of impact and time-to-recovery. Overall, we find clear socioeconomic and racial disparities in resilience capacity and evacuation patterns. Our work provides new insight into the behavioral response to disasters and provides the basis for data-driven public sector decisions that prioritize the equitable allocation of resources to vulnerable neighborhoods. Understanding how cities respond to extreme weather is critical; as such events are becoming more frequent. Using anonymized mobile phone data for Houston, Texas during Hurricane Harvey in 2017, the authors find that mobility behavior exposes neighborhood disparities in resilience capacity and recovery.
Natural disasters such as floods and hurricanes impact urbanized estuarine environments. Some impacts pose potential environmental and public health risks because of legacy or emerging chemical contamination. However, characterizing the baseline spatial and temporal distribution of environmental chemical contamination before disasters remains a challenge. To address this gap, we propose using systematic evidence mapping (SEM) in order to comprehensively integrate available data from diverse sources. We demonstrate this approach is useful for tracking and clarifying legacy chemical contamination reporting in an urban estuary system. We conducted a systematic search of peer-reviewed articles, government monitoring data, and grey literature. Inclusion/exclusion criteria are used as defined by a Condition, Context, Population (CoCoPop) statement for literature from 1990 to 2019. Most of the peer-reviewed articles reported dioxins/furans or mercury within the Houston Ship Channel (HSC); there was limited reporting of other organics and metals. In contrast, monitoring data from two agencies included 89-280 individual chemicals on a near-annual basis. Regionally, peer-reviewed articles tended to record metals in Lower Galveston Bay (GB) but organics in the HSC, while the agency databases spanned a wider spatial range in GB/HSC. This SEM has shown that chemical data from peer-reviewed and grey literature articles are sparse and inconsistent. Even with inclusion of government monitoring data, full spatial and temporal distributions of baseline levels of legacy chemicals are difficult to determine. There is thus a need to expand the chemical, spatial, and temporal coverage of sampling and environmental data reporting in GB/HSC.
The health benefits of green space are well known, but the health effects of green infrastructure less so. Green infrastructure goes well beyond the presence of green space and refers more to a strategically planned network of natural and seminatural areas, with other environmental features designed and managed to deliver a wide range of ecosystem services and possibly to improve human health. In this narrative review, we found that small green infrastructure, such as green roofs and walls, has the potential to mitigate urban flooding, attenuate indoor temperatures and heat islands, improve air quality, and muffle noise, among other benefits, but these effects have not been linked directly to health. Larger green infrastructure has been associated with reduced temperatures, air pollution, and crimes and violence, but less so with health, although some evidence suggests that it may be beneficial for health (e.g., good health, decreased mortality). Finally, parks and street trees show many health benefits, but it is not clear if they can always be considered green infrastructure.
There is a consensus that future sea-level rise (SLR) will increase the exposure of population and assets to coastal flooding. However, the extent to which SLR affects flood hazards and human vulnerability to flooding in the built environment is not well understood. This study investigates the effects of future SLR on coastal flood hazards and human vulnerability to flooding in New York City’s built environment. With a focus on a hurricane-induced flood event, we utilize a building-scale hydrodynamic model to simulate flood hazards under different 21st-century SLR scenarios. We further implement a human vulnerability model to reveal how the physical vulnerability of individuals to flooding would respond to the effects of SLR on flood hazards. We find that SLR would result in a substantial increase in not only the floodwater depth but also the floodwater velocity in the study area. For example, under a 1.04 m SLR scenario, the increase in the max floodwater speed exceeds 2.7 m/s (1271%) in 5% of the area that was flooded under the no-SLR scenario (control run). Model results show that, due to nonlinear interactions, the floodwater depth simulated by the hydrodynamic model for a SLR scenario could substantially differ from the depth estimated based on a linear addition of the SLR to the control-run floodwater depth. We find that the effects of SLR on flood hazards would, in turn, substantially affect the extent, intensity, and duration of human physical vulnerability to flooding, which could potentially increase the number of injuries and mortalities.
With increasing population growth and urban sprawl, many coastal lowlands are unprecedentedly vulnerable to climate change and its impacts, such as rising sea levels, increasing extreme storm events, and coastal flooding. Quantifying coastal flood vulnerability serves as a tool to identify a system’s weakness, monitor its change, and support making targeted climate adaptation policies. The assessment framework proposed in this research uses principal component analysis (PCA) and a weighting method to build a composite indicator of flood vulnerability index and evaluate the vulnerability for 256 coastal census tracts and 24 municipalities along the coast of Connecticut, USA. The research uses Keiser-Meyer-Olkin (KMO) test and Bartlett’s test of sphericity to test sample adequacy and performs data standardization for all indicators. Through PCA, 30 coastal vulnerability-related indicators were grouped into four major dimensions: hazard exposure, socio-economic, physical/land use and land cover, and natural. The findings highlight the variations of flood vulnerability across highly ur-banized areas, suburban areas, and rural areas; and the gradient from coastal low-elevation region to high-elevation inland area. This variance is unevenly caused by different dimensions although they may trade-off with each other when aggregated, the dominant dimensions play a significant or decisive role in the vulnera-bility assessment. This research built an automatic and objective assessment framework that is flexible enough to be applied at a smaller scale so as to obtain detailed analysis and it can be used as a decision-making support system.
Wildfires are an essential part of a healthy ecosystem, yet the expansion of the wildland-urban interface, combined with climatic changes and other anthropogenic activities, have led to the rise of wildfire hazards in the past few decades. Managing future wildfires and their multi-dimensional impacts requires moving from traditional reactive response to deploying proactive policies, strategies, and interventional programs to reduce wildfire risk to wildland-urban interface communities. Existing risk assessment frameworks lack a unified analytical method that properly captures uncertainties and the impact of decisions across social, ecological, and technical systems, hindering effective decision-making related to risk reduction investments. In this paper, a conceptual probabilistic wildfire risk assessment framework that propagates modeling uncertainties is presented. The framework characterizes the dynamic risk through spatial probability density functions of loss, where loss can include different decision variables, such as physical, social, economic, environmental, and health impacts, depending on the stakeholder needs and jurisdiction. The proposed approach consists of a computational framework to propagate and integrate uncertainties in the fire scenarios, propagation of fire in the wildland and urban areas, damage, and loss analyses. Elements of this framework that require further research are identified, and the complexity in characterizing wildfire losses and the need for an analytical-deliberative process to include the perspectives of the spectrum of stakeholders are discussed.
Alabama currently experiences an above-average threat from extreme heat events compared to the remaining states in the USA. More than 160,000 people living in the state (infants, elderly age groups, or poverty-ridden populations) remain vulnerable to heat events. The risk of heat-related mortalities and morbidities disproportionately impacts the growing Alabama cities due to increasing hot-weather episodes and several underlying social vulnerability factors. The exposure threat in 2050 is projected to increase by more than 90 average heat days a year and the number of heat-wave days is predicted to increase from 15 to more than 70 days a year. Although the state’s hazard mitigation plan covers extreme heat issues and heat emergency plans, Alabama lacks heat adaptation plans and is conducting heat vulnerability assessments from time to time. This study focused on determining the social drivers of heat vulnerability and identifying regions within the state that experienced intense heat island effects over the course of five years (2015-2019). 15 sociodemographic factors data from the 2018 American Community Survey (ACS), and 6 health outcome variables (asthma, obesity, stroke, high blood pressure, diabetes) were analyzed to assess cumulative social vulnerability using principal component analysis (PCA). Using Spatial Autoregression (SAR) model, exposure risk was measured as a function of environmental parameters including proportional vegetation, normalized difference water index (NDWI), digital elevation model (DEM), and percent imperviousness of land surface. A heat risk index calculated as a product of social vulnerability and exposure risk was analyzed for Alabama’s eight largest and growing cities (Birmingham, Huntsville, Hoover, Montgomery, Mobile, Tuscaloosa, Auburn, and Dothan) at the block-group census resolution. Spatial data depicting the physical landscape characteristics across the cities revealed differing levels of and factors in exposure to urban heat effects across the city.
Climate change has led to prolonged, more frequent, intense, and severe extreme weather events, such as summertime heatwaves, creating many challenges on the economy and society and human health and energy resources. For example, the 2010 and 2018 heatwave in Quebec, Canada, resulted in about 280 and 93 heat-related deaths, and there were around 500 fatalities due to overheated indoor environments in 2021 around entire Canada. Therefore, it is imperative to understand and evaluate the overheating conditions in buildings, for which selecting suitable future reference weather data under climate change is one of the first critical steps. This study evaluated a reference year selection method in terms of typical and extreme reference years based on future climate datasets to assess both outdoor and indoor overheating in the future. The future climate data were collected from the Coordinated Regional Downscaling Experiment (CORDEX) program. Three Canadian cities (Montreal, Toronto, Vancouver) were selected for the overheating evaluation during three selected periods (2001-2020, 2041-2060, 2081-2100). The CORDEX climate projections were first bias-corrected by the multivariate quantile mapping correction method with the observational data. Then, the typical and extreme reference year data were generated as well as climate data from the design summer year for comparison. The performance of the reference year selection method was evaluated by comparing the maximum, minimum, and average overheating hours for the 20-years data of each period. This study demonstrates that the multivariate quantile mapping bias correction method can improve the reliability of future climate data making it one of the most important steps for any future weather projection study. Besides, the reference year selection method could efficiently capture maximum and minimum monthly overheating hours providing the upper and lower boundary of possible outdoor and indoor overheating conditions.. In contrast, neither the severest nor the typical monthly outdoor and indoor overheating conditions could be predicted by the design summer year method. Finally, owing to the effects of climate change, average monthly overheating hours normally increase by around one time (from 50% to 150%) until the mid-term future (2041-2060) and by around two to three times (even up to nine times for some scenarios) during the long-term future (2081-2100).
The troubling trend of rising heat-associated mortalities in an urban desert region (Maricopa County, AZ, USA) has motivated us to explore the extent to which environmental factors may contribute to increased heat-health risks. Summertime data from 2010 to 2019 were used to construct a suite of models for daily heat-associated mortalities. The best-performing full model included the following predictors, ordered from strongest to weakest influence: daily average air temperature, average of previous 5 days daily average air temperature, year, day of year, average of previous 5 days daily average dew point temperature, average of previous 5 days daily average PM(2.5), and daily average PM(10). This full model exhibited a 5.39% reduction in mean absolute error in daily heat-associated mortalities as compared to the best-performing model that included only air temperature as an environmental predictor. The extent to which issued and modeled excessive heat warnings (from both the temperature only and full models) corresponded with heat-associated mortalities was also examined. Model hindcasts for 2020 and 2021 showed that the models were able to capture the high number of heat-associated mortalities in 2020, but greatly undercounted the highest yet observed number of heat-associated mortalities in 2021. Results from this study lend insights into environmental factors corresponding to an increased number of heat-associated mortalities and can be used for informing strategies towards reducing heat-health risks. However, as the best-performing model was unable to fully capture the observed number of heat-associated mortalities, continued scrutiny of both environmental and non-environmental factors affecting these observations is needed.
Upward trends in ground-level warming are expected to intensify, affecting the health of human populations. Specific to the United States, the Northeast (NE) region is one of the most vulnerable to these warming trends. Previous research has found social disparities in the distribution of heat, while recent studies have examined associations between metropolitan racial/ethnic segregation and heat exposures. We advance upon previous research by including a novel measure of neighborhood-level racial/ethnic diversity in our examination of social inequalities in heat for NE neighborhoods (census tracts). We paired data derived from the United States Geological Survey on mean land surface temperature (LST) for the summer months of 2013-2017 with sociodemographic data from the American Community Survey (5-year estimates, 2013-2017). We use multivariable generalized estimating equations (GEEs) that adjust for geographic clustering. Findings reveal heat exposure disparities across NE neighborhoods. Neighborhoods with higher proportions of racial/ethnic minorities, people of lower socioeconomic status, households without access to an automobile, and greater diversity experience higher temperatures. Diversity was more strongly related to increased heat in neighborhoods with lower Latinx and lower Black composition suggesting that neighborhood homogeneity confers a differentially greater cooling effect based on higher White composition. The social groups that carry the unequal thermal burdens are also those who are most vulnerable. Interventions to reduce heat risks in the NE should therefore prioritize reducing the burden on historically disadvantaged communities.
In recent years, demographic growth has caused cities to expand their urban areas, increasing the risk of overheating, creating insurmountable microclimatic conditions within the urban area, which is why studies have been carried out on the urban heat island effect (UHI) and its mitigation. Therefore, this research aims to evaluate the cooling potential in the application of strategies based on biomimicry for the microclimate in a historical heritage city of Panama. For this, three case studies (base case, case 1, and case 2) of outdoor thermal comfort were evaluated, in which the Envi-met software was used to emulate and evaluate the thermal performance of these strategies during March (highest temperature month) and October (rainier month). The strategies used were extracted from the contrast of zebra skin, human skin, evaporative cooling, and ant skin. The results showed a reduction of 2.8 °C in the air temperature at 11:00, the radiant temperature decreased by 2.2 °C, and the PET index managed to reduce the thermal comfort indicator among its categories. The importance of thinking based on biomimicry in sustainable strategies is concluded; although significant changes were obtained, high risks of discomfort persist due to the layout and proximity of the building.
Emerging research suggests that internet search patterns may provide timely, actionable insights into adverse health impacts from, and behavioral responses to, days of extreme heat, but few studies have evaluated this hypothesis, and none have done so across the United States. We used two-stage distributed lag nonlinear models to quantify the interrelationships between daily maximum ambient temperature, internet search activity as measured by Google Trends, and heat-related emergency department (ED) visits among adults with commercial health insurance in 30 US metropolitan areas during the warm seasons (May to September) from 2016 to 2019. Maximum daily temperature was positively associated with internet searches relevant to heat, and searches were in turn positively associated with heat-related ED visits. Moreover, models combining internet search activity and temperature had better predictive ability for heat-related ED visits compared to models with temperature alone. These results suggest that internet search patterns may be useful as a leading indicator of heat-related illness or stress.
Place-based structural inequalities can have critical implications for the health of vulnerable populations. Historical urban policies, such as redlining, have contributed to current inequalities in exposure to intra-urban heat. However, it is unknown whether these spatial inequalities are associated with disparities in heat-related health outcomes. The aim of this study is to determine the relationships between historical redlining, intra-urban heat conditions, and heat-related emergency department visits using data from 11 Texas cities. At the zip code level, the proportion of historical redlining was determined, and heat exposure was measured using daytime and nighttime land surface temperature (LST). Heat-related inpatient and outpatient rates were calculated based on emergency department visit data that included ten categories of heat-related diseases between 2016 and 2019. Regression or spatial error/lag models revealed significant associations between higher proportions of redlined areas in the neighborhood and higher LST (Coef. = 0.0122, 95% CI = 0.0039-0.0205). After adjusting for indicators of social vulnerability, neighborhoods with higher proportions of redlining showed significantly elevated heat-related outpatient visit rate (Coef. = 0.0036, 95% CI = 0.0007-0.0066) and inpatient admission rate (Coef. = 0.0018, 95% CI = 0.0001-0.0035). These results highlight the role of historical discriminatory policies on the disparities of heat-related illness and suggest a need for equity-based urban heat planning and management strategies.
Much research has shown a general decrease in the negative health response to extreme heat events in recent decades. With a society that is growing older, and a climate that is warming, whether this trend can continue is an open question. Using eight additional years of mortality data, we extend our previous research to explore trends in heat-related mortality across the United States. For the period 1975-2018, we examined the mortality associated with extreme-heat-event days across the 107 largest metropolitan areas. Mortality response was assessed over a cumulative 10-day lag period following events that were defined using thresholds of the excess heat factor, using a distributed-lag nonlinear model. We analyzed total mortality and subsets of age and sex. Our results show that in the past decade there is heterogeneity in the trends of heat-related human mortality. The decrease in heat vulnerability continues among those 65 and older across most of the country, which may be associated with improved messaging and increased awareness. These decreases are offset in many locations by an increase in mortality among men 45-64 (+1.3 deaths per year), particularly across parts of the southern and southwestern United States. As heat-warning messaging broadly identifies the elderly as the most vulnerable group, the results here suggest that differences in risk perception may play a role. Further, an increase in the number of heat events over the past decade across the United States may have contributed to the end of a decades-long downward trend in the estimated number of heat-related fatalities.
IMPORTANCE: Firearm violence is a leading public health crisis in the US. Understanding whether and how ambient temperature is associated with firearm violence may identify new avenues for prevention and intervention. OBJECTIVE: To estimate the overall and regional association between hotter temperatures and higher risk of firearm violence in the US. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study used distributed lag nonlinear models, controlling for seasonality and long-term time trends by city and pooled results overall and by climate region. The most populous cities in the US with the highest number of assault-related firearm incidence (ie, shootings) from 2015 to 2020 were analyzed. Data analysis was performed from October 2021 to June 2022. EXPOSURES: Maximum daily temperature by city. MAIN OUTCOMES AND MEASURES: The primary outcome was the number of assault-related firearm shootings by city. RESULTS: A total of 116 511 shootings in 100 cities were included in this analysis. The pooled analysis estimated that 6.85% (95% CI, 6.09%-7.46%) of all shootings were attributable to days hotter than city-specific median temperatures. This equates to 7973 total shootings (95% CI, 7092-8688 total shootings) across the 100 cities over the 6-year study period, although the number of total persons injured or killed would be higher. Estimated risk of firearm incidents increased almost monotonically with higher temperatures, with a local peak at the 84th percentile of the temperature range corresponding to a relative risk of 1.17 (95% CI, 1.12-1.21) compared with the median temperature. However, even moderately hot temperatures were associated with higher risk of shootings. Although significant, there was low heterogeneity between cities (I2 = 11.7%; Cochran Q test, P = .02), indicating regional or climate-specific variation in the daily temperature and incident shootings relationship. CONCLUSIONS AND RELEVANCE: These findings underscore the importance of heat adaptation strategies broadly throughout the year to reduce shootings, rather than focusing on only the hottest days.
Here we use remotely sensed land surface temperature measurements to explore the distribution of the United States’ urban heating burden, both at high resolution (within cities or counties) and at scale (across the whole contiguous United States). While a rich literature has documented neighborhood-level disparities in urban heat exposures in individual cities, data constraints have precluded comparisons across locations. Here, drawing on urban temperature anomalies during extreme summer surface temperature events from all 1,056 US counties with more than 10 developed census tracts, we find that the poorest tracts (and those with lowest average education levels) within a county are significantly hotter than the richest (and more educated) neighborhoods for 76% of these counties (54% for education); we also find that neighborhoods with higher Black, Hispanic, and Asian population shares are hotter than the more White, non-Hispanic areas in each county. This holds in counties with both large and small spreads in these population shares, and for 71% of all counties the significant racial urban heat disparities persist even when adjusting for income. Although individual locations have different histories that have contributed to race- and class-based geographies, we find that the physical features of the urban environments driving these surface heat exposure gradients are fairly uniform across the country. Systematically, the disproportionate heat surface exposures faced by minority communities are due to more built-up neighborhoods, less vegetation, and—to a lesser extent—higher population density.
BACKGROUND: Emerging literature has documented heat-related impacts on child health, yet few studies have evaluated the effects of heat among children of different age groups and comparing emergency department (ED) and hospitalisation risks. OBJECTIVES: To examine the differing associations between high ambient temperatures and risk of ED visits and hospitalisations among children by age group in New York City (NYC). METHODS: We used New York Statewide Planning and Research Cooperative System (SPARCS) data on children aged 0-18 years admitted to NYC EDs (n = 2 252 550) and hospitals (n = 228 006) during the warm months (May-September) between 2005 and 2011. Using a time-stratified, case-crossover design, we estimated the risk of ED visits and hospitalisations associated with daily maximum temperature (Tmax) for children of all ages and by age group. RESULTS: The average Tmax over the study period was 80.3°F (range 50°, 104°F). Tmax conferred the greatest risk of ED visits for children aged 0-4, with a 6-day cumulative excess risk of 2.4% (95% confidence interval [CI] 1.7, 3.0) per 13°F (ie interquartile range) increase in temperature. Children and adolescents 5-12 years (0.8%, 95% CI 0.1, 1.6) and 13-18 years (1.4%, 95% CI 0.6, 2.3) are also sensitive to heat. For hospitalisations, only adolescents 13-18 years had increased heat-related risk, with a cumulative excess risk of 7.9% (95% CI 2.0, 14.2) per 13°F increase in Tmax over 85°F. CONCLUSIONS: This urban study in NYC reinforces that young children are particularly vulnerable to effects of heat, but also demonstrates the sensitivity of older children and adolescents as well. These findings underscore the importance of focussing on children and adolescents in targeting heat illness prevention and emergency response activities, especially as global temperatures continue to rise.
Climate change is expected to exacerbate the urban heat island (UHI) effect in cities worldwide, increasing the risk of heat-related morbidity and mortality. Solar reflective ‘cool pavement’ is one of several mitigation strategies that may counteract the negative effects of the UHI effect. An increase in pavement albedo results in less heat absorption, which results in reduced surface temperatures (T (surface)). Near surface air temperatures (T (air)) could also be reduced if cool pavements are deployed at sufficiently large spatial scales, though this has never been confirmed by field measurements. This field study is the first to conduct controlled measurements of the impacts of neighborhood-scale cool pavement installations. We measured the impacts of cool pavement on albedo, T (surface), and T (air). In addition, pavement albedo was monitored after installation to assess its degradation over time. The field site (similar to 0.64 km(2)) was located in Covina, California; similar to 30 km east of Downtown Los Angeles. We found that an average pavement albedo increase of 0.18 (from 0.08 to 0.26) corresponded to maximum neighborhood averaged T (surface) and T (air) reductions of 5 degrees C and 0.2 degrees C, respectively. Maximum T (surface) reductions were observed in the afternoon, while minimum reductions of 0.9 degrees C were observed in the morning. T (air) reductions were detected at 12:00 local standard time (LST), and from 20:00 LST to 22:59 LST, suggesting that cool pavement decreases T (air) during the daytime as well as in the evening. An average albedo reduction of 30% corresponded to a similar to 1 degrees C reduction in the T (surface) cooling efficacy. Although we present here the first measured T (air) reductions due to cool pavement, we emphasize that the tradeoffs between T (air) reductions and reflected shortwave radiation increases are still unclear and warrant further investigation in order to holistically assess the efficacy of cool pavements, especially with regards to pedestrian thermal comfort.
BACKGROUND: The effect of heatwaves on adverse birth outcomes is not well understood and may vary by how heatwaves are defined. The study aims to examine acute associations between various heatwave definitions and preterm and early-term birth. METHODS: Using national vital records from 50 metropolitan statistical areas (MSAs) between 1982 and 1988, singleton preterm (< 37 weeks) and early-term births (37-38 weeks) were matched (1:1) to controls who completed at least 37 weeks or 39 weeks of gestation, respectively. Matching variables were MSA, maternal race, and maternal education. Sixty heatwave definitions including binary indicators for exposure to sustained heat, number of high heat days, and measures of heat intensity (the average degrees over the threshold in the past 7 days) based on the 97.5(th) percentile of MSA-specific temperature metrics, or the 85(th) percentile of positive excessive heat factor (EHF) were created. Odds ratios (OR) for heatwave exposures in the week preceding birth (or corresponding gestational week for controls) were estimated using conditional logistic regression adjusting for maternal age, marital status, and seasonality. Effect modification by maternal education, age, race/ethnicity, child sex, and region was assessed. RESULTS: There were 615,329 preterm and 1,005,576 early-term case-control pairs in the analyses. For most definitions, exposure to heatwaves in the week before delivery was consistently associated with increased odds of early-term birth. Exposure to more high heat days and more degrees above the threshold yielded higher magnitude ORs. For exposure to 3 or more days over the 97.5(th) percentile of mean temperature in the past week compared to zero days, the OR was 1.027 for early-term birth (95%CI: 1.014, 1.039). Although we generally found null associations when assessing various heatwave definitions and preterm birth, ORs for both preterm and early-term birth were greater in magnitude among Hispanic and non-Hispanic black mothers. CONCLUSION: Although associations varied across metrics and heatwave definitions, heatwaves were more consistently associated with early-term birth than with preterm birth. This study's findings may have implications for prevention programs targeting vulnerable subgroups as climate change progresses.
OBJECTIVE: Schools with aging infrastructure may expose students to extreme temperatures. Extreme outdoor temperatures have previously been linked to more asthma-related health care utilization. Explore the relationship between classroom temperatures and school-based health care visits for asthma in an urban school building with an outdated heating and cooling system. METHODS: Participants were students in grades K-8 who received health care from a school-based health center (SBHC) (n = 647) or school nurse (n = 1244) in 2 co-located urban public schools between 2016 and 2018. The probability of an asthma visit to the SBHC or school nurse was modeled as a function of indoor temperature exposure using generalized estimating equations with covariates accounting for grade, sex, outdoor temperature, days at risk of asthma visit, nonasthma visits, month, and year fixed effects. RESULTS: Classroom temperatures ranged from 48.0 °F to 100.6 °F. Higher mean grade-level indoor temperatures from a baseline of approximately 70 °F to 76 °F were associated with increased rates of asthma-related visits to the SBHC or school nurse on same day of exposure. Model-generated estimates suggest that an increase of 10 degrees F in indoor temperature relative to a baseline of 75 °F was associated with a 53% increase in the rate of asthma-related SBHC visits. CONCLUSIONS: Elevated classroom temperatures may be associated with more school-based health care utilization for asthma. Low-income and students from racial and ethnic minority groups have disproportionately higher rates of asthma and are also more likely to attend schools with poor infrastructure. The potential benefits of school infrastructure investments for student health, health care costs, and health equity merit further investigation.
Objectives. To determine the effect of heat waves on emergency department (ED) visits for individuals experiencing homelessness and explore vulnerability factors. Methods. We used a unique highly detailed data set on sociodemographics of ED visits in San Diego, California, 2012 to 2019. We applied a time-stratified case-crossover design to study the association between various heat wave definitions and ED visits. We compared associations with a similar population not experiencing homelessness using coarsened exact matching. Results. Of the 24 688 individuals identified as experiencing homelessness who visited an ED, most were younger than 65 years (94%) and of non-Hispanic ethnicity (84%), and 14% indicated the need for a psychiatric consultation. Results indicated a positive association, with the strongest risk of ED visits during daytime (e.g., 99th percentile, 2 days) heat waves (odds ratio = 1.29; 95% confidence interval = 1.02, 1.64). Patients experiencing homelessness who were younger or elderly and who required a psychiatric consultation were particularly vulnerable to heat waves. Odds of ED visits were higher for individuals experiencing homelessness after matching to nonhomeless individuals based on age, gender, and race/ethnicity. Conclusions. It is important to prioritize individuals experiencing homelessness in heat action plans and consider vulnerability factors to reduce their burden. (Am J Public Health. 2022;112(1):98-106. https://doi.org/10.2105/AJPH.2021.306557).
Elevated air temperatures in urban neighborhoods due to the Urban Heat Island effect is a form of heat pollution that causes thermal discomfort, higher energy consumption, and deteriorating public health. Mitigation measures can be expensive, with the need to maximize benefits from limited resources. Here we show that significant mitigation can be achieved through a limited application of reflective surfaces. We use a Computational Fluid Dynamics model to resolve the air temperature within a prototypical neighborhood for different wind directions, building configurations, and partial application of reflective surfaces. While reflective surfaces mitigate heat pollution, their effectiveness relative to cost varies with spatial distribution. Although downstream parts experience the highest heat pollution, applying reflective surfaces to the upstream part has a disproportionately higher benefit relative to cost than applying them downstream.
Practitioners and researchers use vulnerability indices to understand the conditions that influence hazard risk. However, there has been little research on how well such indices depict household-scale vulnerability to specific hazards. We examined relationships between an all-hazard index and a hazard-specific index with householdlevel adaptive resources, adaptive behaviors, proximate sensitivities, and self-reported health outcomes related to extreme heat. Household measures were drawn from a stratified random sample survey conducted in Phoenix, Arizona, USA (n = 163). The results point to different experiences between households in more and less heat vulnerable areas. The largest differences between households stratified by the hazard-specific index (Heat Vulnerability Index) primarily involved adaptive resources and behaviors, whereas indicators of proximate sensitivity were more strongly differentiated by the all-hazard index (Social Vulnerability Index). Differences in health outcomes between more and less vulnerable neighborhoods were more evident using HVI than SoVI, although effect sizes using either index were small and confidence intervals were wide. The relationship between vulnerability indices and several survey measures varied across four study sites. The specific ways in which more and less vulnerable communities differ from one another varies based on the adaptation, sensitivity, or outcome measure of interest, location within the city, and choice of vulnerability index.
There is a pressing need for strategies to prevent the heat-health impacts of climate change. Cooling urban areas through adding trees and vegetation and increasing solar reflectance of roofs and pavements with higher albedo surface materials are recommended strategies for mitigating the urban heat island. We quantified how various tree cover and albedo scenarios would impact heat-related mortality, temperature, humidity, and oppressive air masses in Los Angeles, California, and quantified the number of years that climate change-induced warming could be delayed in Los Angeles if interventions were implemented. Using synoptic climatology, we used meteorological data for historical summer heat waves, classifying days into discrete air mass types. We analyzed those data against historical mortality data to determine excess heat-related mortality. We then used the Weather Research and Forecasting model to explore the effects that tree cover and albedo scenarios would have, correlating the resultant meteorological data with standardized mortality data algorithms to quantify potential reductions in mortality. We found that roughly one in four lives currently lost during heat waves could be saved. We also found that climate change-induced warming could be delayed approximately 40-70 years under business-as-usual and moderate mitigation scenarios, respectively.
Urban tree cover contributes to human well-being through a variety of ecosystem services. In this study, we focus on the role that trees can play in reducing temperature during warm seasons and associated impacts on human health and well-being. We introduce a method for quantifying and valuing changes in premature mortality from extreme heat due to the changes in urban tree cover and apply this method to Baltimore City, Maryland. The model i-Tree Cool Air uses a water and energy balance to estimate hourly changes in air temperature due to alternative scenarios of tree cover applied across 653 Census Block Groups. The changes in temperature are applied to existing temperature?mortality models to estimate changes in health outcomes and associated values. Existing tree cover in Baltimore is estimated to reduce annual mortality by 543 deaths as compared to a 0% tree cover scenario. Increasing the area of current tree cover by 10% of each Census Block Group reduced baseline annual mortality by 83 to 247 deaths (valued at $0.68 ?2.0 billion applying Value of Statistical Life estimates). Over half of the reduced mortality is from the over 65 year age group, who are among the most vulnerable to extreme heat. Reductions in air temperature due to increased tree cover were greatest in downtown Baltimore where tree cover is relatively low and impervious cover is relatively high. However, the greatest reductions in mortality occurred in the outskirts of Baltimore where a greater number of people who are over 65 years in age reside. Quantifying and valuing the health benefits of changes in air temperatures due to increased tree cover can inform climate adaptation and mitigation plans by decision makers. Developing adaptation strategies to effectively address these issues will become increasingly important in the future under changing climates and an aging population.
BACKGROUND: Short-term associations between extreme heat events and adverse health outcomes are well-established in epidemiologic studies. However, the use of different exposure definitions across studies has limited our understanding of extreme heat characteristics that are most important for specific health outcomes or subpopulations. METHODS: Logic regression is a statistical learning method for constructing decision trees based on Boolean combinations of binary predictors. We describe how logic regression can be utilized as a data-driven approach to identify extreme heat exposure definitions using health outcome data. We evaluated the performance of the proposed algorithm in a simulation study, as well as in a 20-year time-series analysis of extreme heat and emergency department visits for 12 outcomes in the Atlanta metropolitan area. RESULTS: For the Atlanta case study, our novel application of logic regression identified extreme heat exposure definitions that were associated with several heat-sensitive disease outcomes (e.g., fluid and electrolyte imbalance, renal diseases, ischemic stroke, and hypertension). Exposures were often characterized by extreme apparent minimum temperature or maximum temperature over multiple days. The simulation study also demonstrated that logic regression can successfully identify exposures of different lags and duration structures when statistical power is sufficient. CONCLUSION: Logic regression is a useful tool for identifying important characteristics of extreme heat exposures for adverse health outcomes, which may help improve future heat warning systems and response plans.
Urban heat stress poses a major risk to public health. Case studies of individual cities suggest that heat exposure, like other environmental stressors, may be unequally distributed across income groups. There is little evidence, however, as to whether such disparities are pervasive. We combine surface urban heat island (SUHI) data, a proxy for isolating the urban contribution to additional heat exposure in built environments, with census tract-level demographic data to answer these questions for summer days, when heat exposure is likely to be at a maximum. We find that the average person of color lives in a census tract with higher SUHI intensity than non-Hispanic whites in all but 6 of the 175 largest urbanized areas in the continental United States. A similar pattern emerges for people living in households below the poverty line relative to those at more than two times the poverty line.
Cities inadvertently create warmer and drier urban climate conditions than their surrounding areas through urbanization that replaces natural surfaces with impervious materials. These changes cause heat-related health problems and many studies suggest microclimatic urban design (MUD) as an approach to address these problems. In MUD-related research, although terrestrial radiation plays an important role in human thermal comfort and previous studies use thermal comfort models to identify human heat stress, few studies have addressed the effect of terrestrial radiation. This study develops the ground ratio factor (GRF) model to estimate the different terrestrial radiation according to different ground conditions. Three types of ground materials (asphalt, concrete, and grass) were considered in the model, and field studies were conducted in humid subtropical climate (Cfa) zone during the hot season (13 July to 19 September 2020). The model was validated by comparing the predicated terrestrial radiation (PTR) from the model with the actual terrestrial radiation (ATR). The results showed that there is a statistically significant strong correlation between PTR and ATR. The model can contribute to MUD strategies by updating existing human energy budget models, which can lead to the measurement of more accurate human thermal comfort for mitigating thermal environments.
Background: Extreme heat is a leading cause of morbidity and mortality during summer months in the United States. Risk of heat exposure and associated health outcomes are disproportionately experienced by people with lower incomes, people of color, and/or immigrant populations.Methods: As qualitative research on the experiences of residents in heat islands is limited, this community-based study examined barriers and coping strategies for keeping cool among residents of Chelsea and East Boston, Massachusetts-environmental justice (EJ) areas that experience the urban heat island effect-through semistructured interviews and qualitative content analysis.Results: Results indicate that all participants (n = 12) had air conditioning, but high energy bills contributed to low use. Eight participants were self-described heat-sensitive, with five experiencing poor health in heat. In addition, nine reported insufficient hydration due to work schedules, distaste of water, or perceptions of it being unsafe.Discussion: This research highlights the importance of understanding perceptions of residents in EJ communities to contextualize vulnerability and identify multipronged heat coping strategies and targeted interventions.
Beliefs in climate change are influenced by personal experiences and sociodemographic charac-teristics; yet justice considerations are often overlooked. We unveil the influence of these factors? on climate change beliefs in a large American city facing substantial climate change impacts, Phoenix, Arizona. Using the Phoenix Area Social Survey that includes data collected from (n = 806) households across fourteen cities in the Phoenix metropolitan area, we investigate what factors influence a belief that ?global warming and climate change are already occurring.? Engaging adaptive capacity and justice literatures with climate belief models, we find that belief in climate change and global warming is positively associated with race specifically other than non-Hispanic Whites, high levels of education, personal experience with heat-related illnesses, and liberal beliefs. Widespread agreement about climate change is found within the scientific community, but general populations, especially in the USA, lag behind in accepting climate change. Critically, there are important justice dimensions absent in the existing literature relevant to understanding belief in and the impacts of climate change. Unpacking these factors could help inform policy makers and civil society organizations in their efforts to design more ?just adaptation? strategies.
Recent studies have characterized individually experienced temperatures or individually experienced heat indices, including new exposure metrics that capture dimensions of exposure intensity, frequency, and duration. Yet, few studies have examined the personal thermal exposure in underrepresented groups, like outdoor workers, and even fewer have assessed corresponding changes in physiologic heat strain. The objective of this paper is to examine a cohort of occupationally exposed grounds and public safety workers (n = 25) to characterize their heat exposure and resulting heat strain. In addition, a secondary aim of this work is to compare individually heat index exposure (IHIE) across exposure metrics, fixed-site in situ weather stations, and raster-derived urban heat island (UHI) measurements in Charleston, SC, a humid coastal climate in the Southeastern USA. A Bland-Altman (BA) analysis was used to assess the level of agreement between the personal IHIE measurements and weather-station heat index (HI) and Urban Heat Island (UHI) measurements. Linear mixed-effect models were used to determine the association between individual risk factors and in situ weather station measurements significantly associated with IHIE measurements. Multivariable stepwise Cox proportional hazard modeling was used to identify the individual and workplace factors associated with time to heat strain in workers. We also examined the non-linear association between heat strain and exposure metrics using generalized additive models. We found significant heterogeneity in IHIE measurements across participants. We observed that time to heat strain was positively associated with a higher IHIE, older age, being male, and among Caucasian workers. Important nonlinear associations between heat strain occurrence and the intensity, frequency, and duration of personal heat metrics were observed. Lastly, our analysis found that IHIE measures were significantly similar for weather station HI, although differences were more pronounced for temperature and relative humidity measurements. Conversely, our IHIE findings were much lower than raster-derived UHI measurements. Real-time monitoring can offer important insights about unfolding temperature-health trends and emerging behaviors during thermal extreme events, which have significant potential to provide situational awareness.
The growing frequency, intensity, and duration of extreme heat events necessitates interventions to reduce heat exposures. Local opportunities for heat adaptation may be optimally identified through collection of both quantitative exposure metrics and qualitative data on perceptions of heat. In this study, we used mixed methods to characterize heat exposure among urban residents in the area of Boston, Massachusetts, US, in summer 2020. Repeated interviews of N = 24 study participants ascertained heat vulnerability and adaptation strategies. Participants also used low-cost sensors to collect temperature, location, sleep, and physical activity data. We saw significant differences across temperature metrics: median personal temperature exposures were 3.9 °C higher than median ambient weather station temperatures. Existing air conditioning (AC) units did not adequately control indoor temperatures to desired thermostat levels: even with AC use, indoor maximum temperatures increased by 0.24 °C per °C of maximum outdoor temperature. Sleep duration was not associated with indoor or outdoor temperature. On warmer days, we observed a range of changes in time-at-home, expected given our small study size. Interview results further indicated opportunities for heat adaptation interventions including AC upgrades, hydration education campaigns, and amelioration of energy costs during high heat periods. Our mixed methods design informs heat adaptation interventions tailored to the challenges faced by residents in the study area. The strength of our community-academic partnership was a large part of the success of the mixed methods approach.
Temperature profiles of the lower atmosphere (<3 km) over complex urban areas are related to health risks, including heat stress and respiratory illness. This complexity leads to uncertainty in numerical simulations, and many studies call for more observations of the lower atmosphere over cities. Using 20 years of observations from the Aircraft Meteorological Data Relay (AMDAR) program over Dallas-Fort Worth, Texas, average profiles every 0.5 h are created from the 1.5 million individual soundings. Dallas-Fort Worth is ideal because it is a large urban area in the central Great Plains, has no major topographic or coastal influences, and has two major airports near the center of the urban heat island. With frequent and high-quality measurements over the city, we investigate the evolution of the lower atmosphere around sunrise to quantify the stability, boundary layer height, and duration of the morning transition when there are southerly winds, few clouds, and no precipitation so as to eliminate transient synoptic events. Characteristics of the lower atmosphere are separated by season and maximum wind speed because the the Great Plains low-level jet contributes to day-to-day variability. In all seasons, stronger wind over the city leads to a weaker nocturnal temperature inversion at sunrise and a shorter morning transition period, with the greatest difference during autumn and the smallest difference during summer. During summer, the boundary layer height at sunrise is higher on average, deepens the most as wind strengthens, and has the fewest days exhibiting a surface temperature inversion over the city. Significance StatementCities impact health by creating an urban heat island caused by more heating at the surface, less evaporative cooling, and increased anthropogenic waste heat, and they can have high pollution. Cooling overnight stabilizes the lower atmosphere and traps pollutants near the surface until surface heating after sunrise mixes them away. Inadequate pollution observations make it difficult to study these issues. The greatest mixing occurs about 2 h after sunrise but can be modulated by wind speed. Observations from 1.5 million aircraft landing and taking off over Dallas-Fort Worth, Texas, reveal that strong low-level wind leads to morning transitions ending 0.84 h earlier on average than with light wind. Details from this vast dataset contribute to improved understanding of the lower atmosphere over cities and provide a baseline for simulations.
Urban areas have complex thermal distribution. We examined the association between extreme temperature and mortality in urban Ontario, using two temperature data sources: high-resolution and weather station data. We used distributed lag non-linear Poisson models to examine census division-specific temperature-mortality associations between May and September 2005-2012. We used random-effect multivariate meta-analysis to pool results, adjusted for air pollution and temporal trends, and presented risks at the 99th percentile compared to minimum mortality temperature. As additional analyses, we varied knots, examined associations using different temperature metrics (humidex and minimum temperature), and explored relationships using different referent values (most frequent temperature, 75th percentile of temperature distribution). Weather stations yielded lower temperatures across study months. U-shaped associations between temperature and mortality were observed using both high-resolution and weather station data. Temperature-mortality relationships were not statistically significant; however, weather stations yielded estimates with wider confidence intervals. Similar findings were noted in additional analyses. In urban environmental health studies, high-resolution temperature data is ideal where station observations do not fully capture population exposure or where the magnitude of exposure at a local level is important. If focused upon temperature-mortality associations using time series, either source produces similar temperature-mortality relationships.
INTRODUCTION: Mean daily temperatures in Canada rose 1.7°C between 1948 and 2016, and the frequency, severity, and duration of extreme heat events has increased. These events can exacerbate underlying health conditions, bringing patients to emergency departments (EDs). This retrospective analysis assessed the impact of temperature and humidex on ED volume and length of stay (LOS). METHODS: LOS is an indicator of ED overcrowding and system performance. Using daily maximum temperatures and humidex values, this study investigated the impact of mean 3-d temperatures and humidex preceding ED presentation on the median and maximum ED LOS and patient volume in 2 community hospitals in Montreal, Quebec, during the summer months of 2016 to 2018. Data were analyzed with 1-way analysis of variance with post hoc Fisher least significant difference tests and Spearman correlation tests. RESULTS: The mean maximum temperature and humidex were 26.1°C and 30.4°C, respectively (n=276 d). Mean 3-d temperatures ≥30°C were associated with higher daily ED volumes in both hospitals (138 vs 121, P=0.002 and 132 vs 125, P=0.03) and with increased median LOS at 1 hospital (8.9 vs 7.6 h, P=0.03). Mean 3-d humidex ≥35 was associated with higher daily ED volumes at both hospitals as well (136 vs 123, P=0.01 and 133 vs 125, P=0.009) with an increased median LOS at 1 hospital (8.6 vs 6.9 h, P=0.0001) with humidex values of 25 to 29.9°C. CONCLUSIONS: Heat events were associated with increased ED presentations and LOS. This study suggests that a warming climate can impede emergency service provision by increasing the demand for and delaying timely care.
Due to climate change, heat events in Canada have become more extreme in intensity and frequency and will continue to do so according to the Intergovernmental Panel on Climate Change’s global predictions. Environmental justice research has indicated that extreme heat exposure disproportionally affects socio-economically disadvantaged populations in cities. The objective of this research was to determine whether such a phenomenon exists in Montreal, Canada. Temperature data were obtained through in-situ sensors and governmental weather stations, while census data were retrieved from Statistics Canada through the Census mapper. Correlation tests were run between temperature and five demographic and socio-economic variables measured inside a 500 m buffer around the temperature sensors. The variables included Indigenous Peoples (IND), people of 65 years old and over (Over 65), people between 25 and 64 years old without a high school degree (No HS), and low-income (LI). A positive correlation was found for LI and No HS (p < 0.05). A regression test performed with interpolated temperature and the demographic and socio-economic variables across the study area revealed no significant correlation due to spatial heterogeneity.
Heatwave warning systems rely on forecasts made for fixed-point weather stations (WS), which do not reflect variation in temperature and humidity experienced by individuals moving through indoor and outdoor locations. We examined whether neighborhood measurement improved the prediction of individually experienced heat index in addition to nearest WS in an urban and rural location. Participants (residents of Birmingham, Alabama [N = 89] and Wilcox County, Alabama [N = 88]) wore thermometers clipped to their shoe for 7 days. Shielded thermometers/hygrometers were placed outdoors within participant’s neighborhoods (N = 43). Nearest WS and neighborhood thermometers were matched to participant’s home address. Heat index (HI) was estimated from participant thermometer temperature and WS humidity per person-hour (HI[individual]), or WS temperature and humidity, or neighborhood temperature and humidity. We found that neighborhood HI improved the prediction of individually experienced HI in addition to WS HI in the rural location, and neighborhood heat index alone served as a better predictor in the urban location, after accounting for individual-level factors. Overall, a 1 °C increase in HI[neighborhood] was associated with 0.20 °C [95% CI (0.19, 0.21)] increase in HI[individual]. After adjusting for ambient condition differences, we found higher HI[individual] in the rural location, and increased HI[individual] during non-rest time (5 a.m. to midnight) and on weekdays.
It is important to quantify human heat exposure in order to evaluate and mitigate the negative impacts of heat on human well-being in the context of global warming. This study proposed a human-centric framework to examine human personal heat exposure based on anonymous GPS trajectories data mining and urban microclimate modeling. The mean radiant temperature (T-mrt) that represents human body’s energy balance was used to indicate human heat exposure. The meteorological data and high-resolution 3D urban model generated from multispectral remotely sensed images and LiDAR data were used as inputs in urban microclimate modeling to map the spatio-temporal distribution of the T-mrt, in the Boston metropolitan area. The anonymous human GPS trajectory data collected from fitness Apps was used to map the spatio-temporal distribution of human outdoor activities. By overlaying the anonymous GPS trajectories on the generated spatio-temporal maps of T-mrt, this study further examined the heat exposure of runners in different age-gender groups in the Boston area. Results show that there is no significant difference in terms of heat exposure for female and male runners. The female runners in the age of 45-54 are exposed to more heat than female runners of 18-24 and 25-34, while there is no significant difference among male runners. This study proposed a novel method to estimate human heat exposure, which would shed new light on mitigating the negative impacts of heat on human health.
Extreme heat in the United States is a leading cause of weather-related deaths, disproportionately affecting low-income communities of color who tend to live in substandard housing with limited indoor cooling and fewer trees. Trees in cities have been documented to improve public health in many ways and provide climate regulating ecosystem services via shading, absorbing, and transpiring heat, measurably reducing heat-related illnesses and deaths. Advancing “urban forest equity” by planting trees in marginalized neighborhoods is acknowledged as a climate health equity strategy. But information is lacking about the efficacy of tree planting programs in advancing urban forest equity and public wellbeing. There is a need for frameworks to address the mismatch between policy goals, governance, resources, and community desires on how to green marginalized neighborhoods for public health improvement-especially in water-scarce environments. Prior studies have used environmental management-based approaches to evaluate planting programs, but few have focused on equity and health outcomes. We adapted a theory-based, multi-dimensional socio-ecological systems (SES) framework regularly used in the public health field to evaluate the Tree Ambassador, or Promotor Forestal, program in Los Angeles, US. The program is modeled after the community health worker model-where frontline health workers are trusted community members. It aims to address urban forest equity and wellbeing by training, supporting, and compensating residents to organize their communities. We use focus groups, surveys, and ethnographic methods to develop our SES model of community-based tree stewardship. The model elucidates how interacting dimensions-from individual to society level-drive urban forest equity and related public health outcomes. We then present an alternative framework, adding temporal and spatial factors to these dimensions. Evaluation results and our SES model highlight drivers aiding or hindering program trainees in organizing communities, including access to properties, perceptions about irrigation responsibilities, and lack of trust in local government. We also find that as trainee experience increases, measures including self- and collective efficacy and trust in their neighbors increase. Findings can inform urban forestry policy, planning, and management actions at the government and non-profit levels that aim to increase tree cover and reduce heat exposure in marginalized communities.
Extreme heat events induced by climate change present a growing risk to transit passenger comfort and health. To reduce exposure, agencies may consider changes to schedules that reduce headways on heavily trafficked bus routes serving vulnerable populations. This paper develops a schedule optimization model to minimize heat exposure and applies it to local bus services in Phoenix, Arizona, using agent-based simulation to inform travel demand and rider characteristics. Rerouting as little as 10% of a fleet is found to reduce network-wide exposure by as much as 35% when operating at maximum fleet capacity. Outcome improvements are notably characterized by diminishing returns, owing to skewed ridership and the inverse relationship between fleet size and passenger wait time. Access to spare vehicles can also ensure significant reductions in exposure, especially under the most extreme temperatures. Rerouting, therefore, presents a low-cost, adaptable resilience strategy to protect riders from extreme heat exposure.
BACKGROUND: This article describes the first Community Assessment for Public Health Emergency Response (CASPER) rapid needs assessment project to be conducted in Wisconsin. The project focused on extreme heat preparedness. METHODS: Fifteen teams conducted household surveys in 30 census blocks in the city of Milwaukee, Wisconsin. RESULTS: Survey results indicated that the majority of households were unaware of the location of a nearby cooling center. Although the vast majority of households reported some form of air conditioning in their house, over half felt too hot inside their home sometimes, most of the time, or always. DISCUSSION: The community partnerships ensured that this project was conducted with local partner input and that the data could be used to inform extreme heat response.
Problem, research strategy, and findings Extreme heat is the deadliest climate hazard in the United States. Climate change and the urban heat island effect are increasing the number of dangerously hot days in cities worldwide and the need for communities to plan for extreme heat. Existing literature on heat planning focuses on heat island mapping and modeling, whereas few studies delve into heat planning and governance processes. We surveyed planning professionals from diverse cities across the United States to establish critical baseline information for a growing area of planning practice and scholarship that future research can build on. Survey results show that planners are concerned with extreme heat risks, particularly environmental and public health impacts from climate change. Planners already report impacts from extreme heat, particularly to energy and water use, vegetation and wildlife, public health, and quality of life. Especially in affected communities, planners claim they address heat in plans and implement heat mitigation and management strategies such as urban forestry, emergency response, and weatherization, but perceive many barriers related to human and financial resources and political will. Takeaway for practice Planners are concerned about extreme heat, especially in the face of climate change. They are beginning to address heat through different strategies and plan types, but we see opportunities to better connect planners to existing heat information sources and leverage existing planning tools, including vegetation, land use regulations, and building codes, to mitigate risks. Although barriers to heat planning persist, including human and capital resources, planners are uniquely qualified to coordinate communities’ efforts to address the rising threat of extreme heat.
Long-term community resilience, which privileges a long view look at chronic issues influencing communities, has begun to draw more attention from city planners, researchers and policymakers. In Phoenix, resilience to heat is both a necessity and a way of life. In this paper, we attempt to understand how residents living in Phoenix experience and behave in an extreme heat environment. To achieve this goal, we introduced a smartphone application (ActivityLog) to study spatio-temporal dynamics of human interaction with urban environments. Compared with traditional paper activity log results we have in this study, the smartphone-based activity log has higher data quality in terms of total number of logs, response rates, accuracy, and connection with GPS and temperature sensors. The research results show that low-income residents in Phoenix mostly stay home during the summer but experience a relatively high indoor temperature due to the lack/low efficiency of air-conditioning (AC) equipment or lack of funds to run AC frequently. Middle-class residents have a better living experience in Phoenix with better mobility with automobiles and good quality of AC. The research results help us better understand user behaviors for daily log activities and how human activities interact with the urban thermal environment, informing further planning policy development. The ActivityLog smartphone application is also presented as an open-source prototype to design a similar urban climate citizen science program in the future.
Extreme heat does not affect all urban residents equally. While vulnerability is often defined as a combination of exposure, sensitivity, and adaptive capacity, many scholars have argued that the quantitative representation of adaptive capacity is particularly difficult. How people who live in vulnerable situations change their behavior to cope with and manage extreme urban temperatures, and the resources necessary to prevent adverse health effects, highlight different adaptive capacity within a city. Our understanding and depiction of how and why the impacts of urban heat vary between individuals and groups is constrained by contemporary approaches to quantify vulnerability using aggregate-scale data drawn from censuses, surveys, and administrative records. Thus, adaptive capacity is likely poorly represented in modern heat vulnerability analyses and their applications. This article explores how different city residents understand and adapt to increasing extreme urban heat, the tradeoffs different populations must make between generic and specific adaptive capacity, and the coping strategies that influence heat adaptive capacity at various scales. Using metropolitan Phoenix as a test site, open-ended interviews were conducted in which residents told their stories about past and present extreme heat adaptive capacity and adaptive behaviors. Three narratives emerged: heat is an inconvenience, heat is a manageable problem, and heat is a catastrophe. Framing heat vulnerability using these differing narratives can help evaluate if standard recommendations for coping with heat adequately represent solutions for the lived experiences of different vulnerable groups. Learning how and under what circumstances vulnerable people are motivated to make necessary changes to increase thermal comfort and safeguard public health will ensure that targeted heat mitigation and adaptation policies are widely adopted. Heat adaptation and mitigation policy makers need to be cognizant of the gap in heat risk perception across different segments of the population and reflect on whether those decisions reflect their experience (of likely belonging to the inconvenience group) or incorporate differing scales of heat adaptive capacity.
Current bioclimate and air quality indices provide insufficient information about the combined effect on human physiology in outdoor spaces. This work examined, large scale gridded meteorological observations, including air temperature, wind speed, solar radiation, and relative humidity, to derive Universal Thermal Climate Index (UTCI) at hourly intervals along with the air quality index (AQI) derived from Environmental Protection Agency (EPA) observation stations. UTCI and AQI were combined into a single framework using geospatial analytics and a newly developed lookup table approach. High risk areas for heat stress and poor air quality were identified using Moran’s I and Getis-Ord GI* statistics. Moderate to strong heat stress was observed during the summer months of 2015-2019, with UTCI ranging from 26 degrees C to 38 degrees C. Coastal regions consistently experienced higher UTCI during noon due to higher humidity but the effect subsided with cooler air circulation from the ocean, especially in the morning and evening. Results also indicated the vulnerability of this region due to the combined impact of heat stress and poor air quality based on 95th percentile values. The final products from this analysis can provide valuable insights for urban planning and preventative measures to ensure improved public health in outdoor environments.
Exposure to heat is a growing public health concern as climate change accelerates worldwide. Different socioeconomic and racial groups often face unequal exposure to heat as well as increased heat-related sickness, mortality, and energy costs. We provide new insight into thermal inequities by analyzing 20 Southwestern U.S. metropolitan regions at the census block group scale for three temperature scenarios (average summer heat, extreme summer heat, and average summer nighttime heat). We first compared average temperatures for top and bottom decile block groups according to demographic variables. Then we used spatial regression models to investigate the extent to which exposure to heat (measured by land surface temperature) varies according to income and race. Large thermal inequities exist within all the regions studied. On average, the poorest 10% of neighborhoods in an urban region were 2.2 °C (4 °F) hotter than the wealthiest 10% on both extreme heat days and average summer days. The difference was as high as 3.3-3.7 °C (6-7 °F) in California metro areas such as Palm Springs and the Inland Empire. A similar pattern held for Latinx neighborhoods. Temperature disparities at night were much smaller (usually ~1 °F). Disparities for Black neighborhoods were also lower, perhaps because Black populations are small in most of these cities. California urban regions show stronger thermal disparities than those in other Southwestern states, perhaps because inexpensive water has led to more extensive vegetation in affluent neighborhoods. Our findings provide new details about urban thermal inequities and reinforce the need for programs to reduce the disproportionate heat experienced by disadvantaged communities.
Extreme heat exposure and sensitivity have been a growing concern in urban regions as the effects of extreme heat pose a threat to public health, the water supply, and the infrastructure. Heat-related illnesses demand an immediate Emergency Medical Service (EMS) response since they might result in death or serious disability if not treated quickly. Despite increased concerns about urban heat waves and relevant health issues, a limited amount of research has investigated the effects of heat vulnerability on heat-related illnesses. This study explores the geographical distribution of heat vulnerability in the city of Austin and Travis County areas of Texas and identifies neighborhoods with a high degree of heat vulnerability and restricted EMS accessibility. We conducted negative binomial regressions to investigate the effects of heat vulnerability on heat-related EMS incidents. Heat-related EMS calls have increased in neighborhoods with more impervious surfaces, Hispanics, those receiving social benefits, people living alone, and the elderly. Higher urban capacity, including efficient road networks, water areas, and green spaces, is likely to reduce heat-related EMS incidents. This study provides data-driven evidence to help planners prioritize vulnerable locations and concentrate local efforts on addressing heat-related health concerns.
BACKGROUND: British Columbia, Canada, was impacted by a record-setting heat dome in early summer 2021. Most households in greater Vancouver do not have air conditioning, and there was a 440% increase in community deaths during the event. Readily available data were analyzed to inform modifications to the public health response during subsequent events in summer 2021 and to guide further research. METHODS: The 434 community deaths from 27 June through 02 July 2021 (heat dome deaths) were compared with all 1,367 community deaths that occurred in the same region from 19 June through 09 July of 2013-2020 (typical weather deaths). Conditional logistic regression was used to examine the effects of age, sex, neighborhood deprivation, and the surrounding environment. Data available from homes with and without air conditioning were also used to illustrate the indoor temperatures differences. RESULTS: A combined index of material and social deprivation was most predictive of heat dome risk, with an adjusted odds ratio of 2.88 [1.85, 4.49] for the most deprived category. Heat dome deaths also had lower greenness within 100 m than typical weather deaths. Indoor temperatures in one illustrative home without air conditioning ranged between 30°C and 40°C. CONCLUSIONS: Risk of death during the heat dome was associated with deprivation, lower neighborhood greenness, older age, and sex. High indoor temperatures likely played an important role. Public health response should focus on highly deprived neighborhoods with low air conditioning prevalence during extreme heat events. Promotion of urban greenspace must continue as the climate changes.
Rising global temperatures and the urban heat island effect can amplify heat-related health risks to urban res-idents. Cities are considering various heat adaptation actions to improve public health, enhance social equity, and cope with future conditions beyond past experience. We present the City-Heat Equity Adaptation Tool (City -HEAT), which suggests optimal investments for mitigating urban heat and reducing health impacts through modifications of built (cool roofs/pavements) and natural (urban afforestation) environments and reductions of people’s heat exposure (cooling centers). The optimization considers multiple public health and social objectives under a wide range of future scenarios. An application to Baltimore, MD (USA) demonstrates how City-HEAT can generate Pareto-efficient multi-year heat adaptation plans. We quantify effectiveness-efficiency-equity tradeoffs among alternative plans and show the advantages of flexible decision-making. City-HEAT can be adapted to the natural, built, and social environments of other cities to support their urban heat adaptation planning, recog-nizing local objectives and uncertainty.
Although research indicates health and well-being benefits of greenspace, little is known regarding how greenspace may influence adaptation to health risks from heat, particularly how these risks change over time. Using daily hospitalization rates of Medicare beneficiaries ≥65 years for 2000-2016 in 40 U.S. Northeastern urban counties, we assessed how temperature-related hospitalizations from cardiovascular causes (CVD) and heat stroke (HS) changed over time. We analyzed effect modification of those temporal changes by Enhanced Vegetation Index (EVI), approximating greenspace. We used a two-stage analysis including a generalized additive model and meta-analysis. Results showed that relative risk (RR) (per 1 °C increase in lag0-3 temperature) for temperature-HS hospitalization was higher in counties with the lowest quartile EVI (RR = 2.7, 95% CI: 2.0, 3.4) compared to counties with the highest quartile EVI (RR = 0.40, 95% CI: 0.14, 1.13) in the early part of the study period (2000-2004). RR of HS decreased to 0.88 (95% CI: 0.31, 2.53) in 2013-2016 in counties with the lowest quartile EVI. RR for HS changed over time in counties in the highest quartile EVI, with RRs of 0.4 (95% CI: -0.7, 1.4) in 2000-2004 and 2.4 (95% CI: 1.6, 3.2) in 2013-2016. Findings suggest that adaptation to heat-health associations vary by greenness. Greenspace may help lower risks from heat but such health risks warrant continuous local efforts such as heat-health plans.
Concurrent with a rapid rise in temperatures within US cities, the frequency of regional electric grid system failures is also rising in recent decades, resulting in a growing number of blackouts during periods of extreme heat. As mechanical air conditioning is a primary adaptive technology for managing rising temperatures in cities, we examine in this paper the impact of a prolonged blackout on heat exposure in residential structures during heat wave conditions, when air conditioning is most critical to human health. Our approach combines a regional climate modeling system with a building energy model to simulate how a concurrent heat wave and grid failure event impacts residential building-interior temperatures across Phoenix. Our results find a substantial increase in heat exposure across residential buildings in response to the loss of electrical power and mechanical cooling systems, with such an event potentially exposing more than one million residents to hazardous levels of heat. We further find the installation of cool roofing to measurably lower the risk of extreme heat exposure for residents of single-story structures.
The urban heat island (UHI) effect is caused by intensive development practices in cities and the diminished presence of green space that results. The evolution of these phenomena has occurred over many decades. In many cities, historic zoning and redlining practices barred Black and minority groups from moving into predominately white areas and obtaining financial resources, a practice that still affects cities today, and has forced these already disadvantaged groups to live in some of the hottest areas. In this study, we used a new dataset on the spatial distribution of temperature during a heat wave in Richmond, Virginia to investigate potential associations between extreme heat and current and historical demographic, socioeconomic, and land use factors. We assessed these data at the census block level to determine if blocks with large differences in temperature also had significant variation in these covariates. The amount of canopy cover, percent impervious surface, and poverty level were all shown to be strong correlates of UHI when analyzed in conjunction with afternoon temperatures. We also found strong associations of historical policies and planning decisions with temperature using data from the University of Richmond’s Digital Scholarship Lab’s “Mapping Inequality” project. Finally, the Church Hill area of the city provided an interesting case study due to recent data suggesting the area’s gentrification. Differences in demographics, socioeconomic factors, and UHI were observed between north and (more gentrified) south Church Hill. Both in Church Hill and in Richmond overall, our research found that areas occupied by people of low socioeconomic status or minority groups disproportionately experienced extreme heat and corresponding impacts on health and quality of life.
INTERVENTION: Ontario’s Harmonized Heat Warning and Information System (HWIS) brings harmonized, regional heat warnings and standard heat-health messaging to provincial public health units prior to periods of extreme heat. RESEARCH QUESTION: Was implementation of the harmonized HWIS in May 2016 associated with a reduction in emergency department (ED) visits for heat-related illness in urban locations across Ontario, Canada? METHODS: We conducted a population-based interrupted time series analysis from April 30 to September 30, 2012-2018, using administrative health and outdoor temperature data. We used autoregressive integrated moving average models to examine whether ED rates changed following implementation of the harmonized HWIS, adjusted for maximum daily temperature. We also examined whether effects differed in heat-vulnerable groups (≥65 years or <18 years, those with comorbidities, those with a recent history of homelessness), and by heat warning region. RESULTS: Over the study period, heat alerts became more frequent in urban areas (6 events triggered between 2013 and 2015 and 14 events between 2016 and 2018 in Toronto, for example). The mean rate of ED visits was 47.5 per 100,000 Ontarians (range 39.7-60.1) per 2-week study interval, with peaks from June to July each year. ED rates were particularly high in those with a recent history of homelessness (mean rate 337.0 per 100,000). Although rates appeared to decline following implementation of HWIS in some subpopulations, the change was not statistically significant at a population level (rate 0.04, 95% CI: -0.03 to 0.1, p=0.278). CONCLUSION: In urban areas across Ontario, ED encounters for heat-related illness may have declined in some subpopulations following HWIS, but the change was not statistically significant. Efforts to continually improve HWIS processes are important given our changing Canadian climate.
Heat-related mortality (HRM) is increasing because of the climate change and urbanization leading to extreme heat events. This paper summarizes the results of the excess mortality attributed to excessive heat events in two largest cities in Canada, Toronto and Montreal, during three heat wave periods. We present an application of a fine-resolution, urban-mesoscale model to assess the impacts of heat and heat mitigation strategy on heat death. The Weather Research and Forecasting model (WRF) is coupled with a multi-layer of the Urban Canopy Model (ML-UCM) to assess the impacts of heat and heat mitigation strategy on heat-related death. The background albedo of 0.2 for urban surfaces are respectively increased to 0.65, 0.60, and 0.45 for roofs, walls, and grounds. The changes of the air mass category, ambient and apparent temperatures interpret the impacts of extreme heat and the potential of increasing surface albedo (ISA) on HRM. Here, the calculations and estimations of HRM is based on the data obtained from Canadian Environmental Health Atlas (CEHA) indicating an average of 120 heat-induced deaths in Toronto and Montreal. ISA affords a reduction in air temperature (1-2 degrees C), a decrease in dew point temperature (0.2-0.5 degrees C), and a slight increase in near-surface wind speed (-0.01 to-0.4 m/s). Increase in albedo shifts days into more benign conditions by nearly 60%. The HRM will lessen by 3-7%, pointing that seven to eighteen lives could be saved. Cooling the urban climate will improve discomfort index, lessen the impacts of elevated temperature, enhance human thermal comfort, and decrease HRM to some significant extent. (c) 2020 Elsevier B.V. All rights reserved.
Global climate change has increased the risks of extreme weather-related disasters, leading to severe public health burdens. In February 2021, Winter Storm Uri brought severe cold to southern United States and caused unprecedented health and safety concerns. Residents in subsidized rental housing were among the most vulnerable to cold stress during such a cold storm. However, existing research on the assessment and mitigation of cold stress in underserved neighborhoods in warmer climate zones is limited, which results in the negligence of cold event preparedness and mitigation policies. Therefore, this study aims to assess the micrometeorological conditions and human cold stress in subsidized housing neighborhoods during the 2021 Winter Storm and determine the extent to which cold mitigation windbreak designs are effective in reducing cold stress. Field measurements, ENVI-met simulations, and biometeorological calculations were conducted to reconstruct the microclimate conditions and cold stress during the storm, and three cold-mitigation windbreak designs with varying foliage densities were evaluated. Results showed that the conditions were categorized as extreme cold stress for the majority of the day, but especially during nighttime. Areas close to the buildings were generally warmer, and the wind-blocking effects of a building decreased as the distance to the building increased. A moderately dense-foliage windbreak was the most effective in reducing wind speed and improving thermal comfort. Intentional environmental modifications to alter wind velocity and disaster relief programs that provide emergency clothing supplies during power outage may be beneficial to these underserved communities.
Health researchers have examined the physiological impacts of extreme air temperature on the human body. Yet, the mental health impacts of temperature have been understudied. Research has shown that the environment can create circumstances that exacerbate mental health issues. This may be particularly challenging for some of the fastest growing cities, located in hot, dry climates. Given the theoretical relationship between air temperature and mental health, we seek to measure the association between temperature and schizophrenia hospital admissions in an arid urban climate and quantify the associated public health burden. We collected 86,672 hospitalization records for schizophrenia from 2006 to 2014 in Maricopa County, Arizona, USA. Using a distributed lag non-linear model (DLNM), we tested for a statistical association between temperature and schizophrenia hospital admissions after controlling for year, season, weekends, and holidays. We calculated the cumulative attributable risk of nighttime temperature on schizophrenia for the entire dataset as well as among demographic subgroups. The relative risk of schizophrenia hospital admissions increased with both high and low temperatures. Statistical models using daily minimum temperature were more strongly associated with hospitalization than those using mean or maximum. Schizophrenia hospital admissions increased on days with minimum temperatures above 30 °C and below 3 °C, with some subgroups experiencing higher rates of hospitalization. The total fraction of schizophrenia hospital admissions attributable to non-optimal minimum temperature is 3.45 % (CI: -4.91-10.80 %) and high minimum temperature is 0.28 % (CI: -1.18-1.78 %). We found that non-whites and males appear to be at a slightly increased risk than the general population, although there did not appear to be a statistically significant difference. A conservative estimate of healthcare costs annually from non-optimal temperature attributed schizophrenia hospitalization is $1.95 million USD. Therefore, nighttime cooling strategies and efforts could increase the accessibility of shelters to reduce overnight exposure to extreme air temperature.
BACKGROUND: Health disparities exist between urban and rural populations, yet research on rural-urban disparities in temperature-mortality relationships is limited. As inequality in the United States increases, understanding urban-rural and regional differences in the temperature-mortality association is crucial. OBJECTIVE: We examined regional and urban-rural differences of the temperature-mortality association in North Carolina (NC), USA, and investigated potential effect modifiers. METHODS: We applied time-series models allowing nonlinear temperature-mortality associations for 17 years (2000-2016) to generate heat and cold county-specific estimates. We used second-stage analysis to quantify the overall effects. We also explored potential effect modifiers (e.g. social associations, greenness) using stratified analysis. The analysis considered relative effects (comparing risks at 99th to 90th temperature percentiles based on county-specific temperature distributions for heat, and 1st to 10th percentiles for cold) and absolute effects (comparing risks at specific temperatures). RESULTS: We found null effects for heat-related mortality (relative effect: 1.001 (95% CI: 0.995-1.007)). Overall cold-mortality risk for relative effects was 1.019 (1.015-1.023). All three regions had statistically significant cold-related mortality risks for relative and absolute effects (relative effect: 1.019 (1.010-1.027) for Coastal Plains, 1.021 (1.015-1.027) for Piedmont, 1.014 (1.006-1.023) for Mountains). The heat mortality risk was not statistically significant, whereas the cold mortality risk was statistically significant, showing higher cold-mortality risks in urban areas than rural areas (relative effect for heat: 1.006 (0.997-1.016) for urban, 1.002 (0.988-1.017) for rural areas; relative effect for cold: 1.023 (1.017-1.030) for urban, 1.012 (1.001-1.023) for rural areas). Findings are suggestive of higher relative cold risks in counties with the less social association, higher population density, less green-space, higher PM(2.5,) lower education level, higher residential segregation, higher income inequality, and higher income (e.g., Ratio of Relative Risks 1.72 (0.68, 4.35) comparing low to high education). CONCLUSION: Results indicate cold-mortality risks in NC, with potential differences by regional, urban-rural areas, and community characteristics.
BACKGROUND: Accurate and precise estimates of ambient air temperatures that can capture fine-scale within-day variability are necessary for studies of air temperature and health. METHOD: We developed statistical models to predict temperature at each hour in each cell of a 927-m square grid across the Northeast and Mid-Atlantic United States from 2003 to 2019, across ~4000 meteorological stations from the Integrated Mesonet, using inputs such as elevation, an inverse-distance-weighted interpolation of temperature, and satellite-based vegetation and land surface temperature. We used a rigorous spatial cross-validation scheme and spatially weighted the errors to estimate how well model predictions would generalize to new cell-days. We assess the within-county association of temperature and social vulnerability in a heat wave as an example application. RESULTS: We found that a model based on the XGBoost machine-learning algorithm was fast and accurate, obtaining weighted root mean square errors (RMSEs) around 1.6 K, compared to standard deviations around 11.0 K. We found similar accuracy when validating our model on an external dataset from Weather Underground. Assessing predictions from the North American Land Data Assimilation System-2 (NLDAS-2), another hourly model, in the same way, we found it was much less accurate, with RMSEs around 2.5 K. This is likely due to the NLDAS-2 model’s coarser spatial resolution, and the dynamic variability of temperature within its grid cells. Finally, we demonstrated the health relevance of our model by showing that our temperature estimates were associated with social vulnerability across the region during a heat wave, whereas the NLDAS-2 showed a much weaker association. CONCLUSION: Our high spatiotemporal resolution air temperature model provides a strong contribution for future health studies in this region.
Aedes aegypti and Aedes albopictus are important pathogen-carrying vectors that broadly exhibit similar habitat suitability, but that differ at fine spatial scales in terms of competitive advantage and tolerance to urban driven environmental parameters. This study evaluated how spatial and temporal patterns drive the assemblages of these competing species in cemeteries of New Orleans, LA, applying indicators of climatic variability, vegetation, and heat that may drive habitat selection at multiple scales. We found that Ae. aegypti was well predicted by urban heat islands (UHI) at the cemetery scale and by canopy cover directly above the cemetery vase. As predicted, UHI positively correlate to Ae. aegypti, but contrary to predictions, Ae. aegypti, was more often found under the canopy of trees in high heat cemeteries. Ae. albopictus was most often found in low heat cemeteries, but this relationship was not statistically significant, and their overall abundances in the city were lower than Ae. aegypti. Culex quinquefasciatus, another important disease vector, was also an abundant mosquito species during the sampling year, but we found that it was temporally segregated from Aedes species, showing a negative association to the climatic variables of maximum and minimum temperature, and these factors positively correlated to its more direct competitor Ae. albopictus. These findings help us understand the mechanism by which these three important vectors segregate both spatially and temporally across the city. Our study found that UHI at the cemetery scale was highly predictive of Ae. aegypti and strongly correlated to income level, with low-income cemeteries having higher UHI levels. Therefore, the effect of excessive heat, and the proliferation of the highly competent mosquito vector, Ae. aegypti, may represent an unequal disease burden for low-income neighborhoods of New Orleans that should be explored further. Our study highlights the importance of considering socioeconomic aspects as indirectly shaping spatial segregation dynamics of urban mosquito species.
Urban floods can be contaminated with fecal material and pathogens. Evidence on infection risks associated with exposure to waterborne pathogens in urban floods is lacking. We address this gap by assessing the risk of infection from exposure to Giardia lamblia in urban flood water samples in Mexico City using a QMRA. Historical flood data was used to build severity indices and to test for correlations with risk of infection estimates. Results indicate similar maximal pathogen densities in urban flood water samples to those from wastewater treatment plants. Significant positive correlations between risk of G. lamblia infection and severity indices suggest that floods could act as an important source of pathogen transmission in Mexico City. Risk of infection to G. lamblia is greater in the city’s periphery, which is characterized by high marginalization levels. We argue that these risks should be managed by engaging citizens, water, and health authorities in decision making.
Urban floodwater could lead to significant risk for public and environmental health from mobilization of microbial pathogens and overflow of wastewater treatment systems. Here, we attempted to assess this risk by obtaining metagenomic profiles of antibiotic resistance genes (ARGs), virulence factors (VFs) and pathogens present in floodwater samples collected in urban Atlanta, GA that were categorized in two distinct groups: floods that occurred after periods of drought and those after regular (seasonal) rain events. Even though no major (known) pathogens were present at the limit of detection of our sequencing effort (~3 Gbp/sample), we observed that floodwaters after drought showed a 2.5-fold higher abundance of both ARGs and VFs compared to floodwater after rainy days. These differences were mainly derived by several novel species of the Pseudomonas genus, which were more dominant in the former versus the latter samples and carried several genes to cope with osmotic stress in addition to ARGs and VFs. These results revealed that there are previously undescribed species that become mobilized after flooding events in the Southeast US urban settings and could represent an increased public health risk, especially after periods of drought, which warrants further attention.
Dengue is one of the major health problems in the state of Chiapas. Consequently, spatial information on the distribution of the disease can optimize directed control strategies. Therefore, this study aimed to develop and validate a simple Bayesian prediction spatial model for the state of Chiapas, Mexico. This is an ecological study that uses data from a range of sources. Dengue cases occurred from January to August 2019. The data analysis used the spatial correlation of dengue cases (DCs), which was calculated with the Moran index statistic, and a generalized linear spatial model (GLSM) within a Bayesian framework, which was considered to model the spatial distribution of DCs in the state of Chiapas. We selected the climatological, geographic, and sociodemographic variables related to the study area. A prediction of the model on Chiapas maps was carried out based on the places where the cases were registered. We find a spatial correlation of 0.115 (p value=0.001)between neighboring municipalities using the Moran index. The variables that have an effect on the number of confirmed cases of dengue are the maximum temperature (Coef=0.110; 95% CrI: 0.076 – 0.215), rainfall (Coef=0.013; 95% CrI:0.008 – 0.028), and altitude (Coef=0.00045; 95% CrI:0.00002 – 0.00174) of each municipality. The predicting power is notably better in regions that have a greater number of municipalities where DCs are registered. The model shows the importance of considering these variables to prevent future DCs in vulnerable areas.
Canadians face an emerging threat of Lyme disease due to the northward expansion of the tick vector, Ixodes scapularis. We evaluated the degree of I. scapularis population establishment and Borrelia burgdorferi occurrence in the city of Ottawa, Ontario, Canada from 2017-2019 using active surveillance at 28 sites. We used a field indicator tool developed by Clow et al. to determine the risk of I. scapularis establishment for each tick cohort at each site using the results of drag sampling. Based on results obtained with the field indicator tool, we assigned each site an ecological classification describing the pattern of tick colonization over two successive cohorts (cohort 1 was comprised of ticks collected in fall 2017 and spring 2018, and cohort 2 was collected in fall 2018 and spring 2019). Total annual site-specific I. scapularis density ranged from 0 to 16.3 ticks per person-hour. Sites with the highest density were located within the Greenbelt zone, in the suburban/rural areas in the western portion of the city of Ottawa, and along the Ottawa River; the lowest densities occurred at sites in the suburban/urban core. B. burgdorferi infection rates exhibited a similar spatial distribution pattern. Of the 23 sites for which data for two tick cohorts were available, 11 sites were classified as “high-stable”, 4 were classified as “emerging”, 2 were classified as “low-stable”, and 6 were classified as “non-zero”. B. burgdorferi-infected ticks were found at all high-stable sites, and at one emerging site. These findings suggest that high-stable sites pose a risk of Lyme disease exposure to the community as they have reproducing tick populations with consistent levels of B. burgdorferi infection. Continued surveillance for I. scapularis, B. burgdorferi, and range expansion of other tick species and emerging tick-borne pathogens is important to identify areas posing a high risk for human exposure to tick-borne pathogens in the face of ongoing climate change and urban expansion.
Environmental changes triggered by deforestation, urban expansion and climate change are present-day drivers of the emergence and reemergence of leishmaniasis. This review describes the current epidemiological scenario and the feasible influence of environmental changes on disease occurrence in the state of Yucatan, Mexico. Relevant literature was accessed through different databases, including PubMed, Scopus, Google, and Mexican official morbidity databases. Recent LCL autochthonous cases, potential vector sandflies and mammal hosts/reservoirs also have been reported in several localities of Yucatan without previous historical records of the disease. The impact of deforestation, urban expansion and projections on climate change have been documented. The current evidence of the relationships between the components of the transmission cycle, the disease occurrence, and the environmental changes on the leishmaniasis emergence in the state shows the need for strength and an update to the intervention and control strategies through a One Health perspective.
Wildfires can be detrimental to urban and rural communities, causing impacts in the form of psychological stress, direct physical injury, and smoke-related morbidity and mortality. This study examined the area burned by wildfires over the entire state of California from the years 2000 to 2020 in order to quantify and identify whether burned area and fire frequency differed across Census tracts according to socioeconomic indicators over time. Wildfire data were obtained from the California Fire and Resource Assessment Program (FRAP) and National Interagency Fire Center (NIFC), while demographic data were obtained from the American Community Survey. Results showed a doubling in the number of Census tracts that experienced major wildfires and a near doubling in the number of people residing in wildfire-impacted Census tracts, mostly due to an over 23,000 acre/year increase in the area burned by wildfires over the last two decades. Census tracts with a higher fire frequency and burned area had lower proportions of minority groups on average. However, when considering Native American populations, a greater proportion resided in highly impacted Census tracts. Such Census tracts also had higher proportions of older residents. In general, high-impact Census tracts tended to have higher proportions of low-income residents and lower proportions of high-income residents, as well as lower median household incomes and home values. These findings are important to policymakers and state agencies as it relates to environmental justice and the allocation of resources before, during, and after wildfires in the state of California.
The increased frequency of wildfires in the Western United States has raised public awareness of the impact of wildfire smoke on air quality and human health. Exposure to wildfire smoke has been linked to an increased risk of cancer and cardiorespiratory morbidity. Evidence-driven interventions can alleviate the adverse health impact of wildfire smoke. During wildfires, public health guidance is based on regional air quality data with limited spatiotemporal resolution. Recently, low-cost air quality sensors have been used in air quality studies, given their ability to capture high-resolution spatiotemporal data. We demonstrate the use of a network of low-cost particulate matter (PM) sensors to gather indoor and outdoor PM2.5 data from seven locations in the urban Seattle area, along with a personal exposure monitor worn by a resident living in one of these locations during the 2020 Washington wildfire event. The data were used to determine PM concentration indoor/outdoor (I/O) ratios, PM reduction, and personal exposure levels. The result shows that locations equipped with high-efficiency particulate air (HEPA) filters and HVAC filtration systems had significantly lower I/O ratios (median I/O = 0.43) than those without air filtration (median I/O = 0.82). The median PM2.5 reduction for the locations with HEPA is 58% compared to 20% for the locations without HEPA. The outdoor PM sensor showed a high correlation to the nearby regional air quality monitoring stations (pre-calibration R-2 = 0.92). The personal monitor showed higher variance in PM measurements as the user moved through different microenvironments and could not be fully characterized by the network of indoor or outdoor monitors. The findings imply that evidence-based interventions can be developed to reduce pollution exposure when combining data from indoor and outdoor sensors. Personal exposure monitoring captured temporal spikes in PM exposure.
BACKGROUND: Rising temperatures due to climate change are expected to impact human adaptive response, including changes to home cooling and ventilation patterns. These changes may affect air pollution exposures via alteration in residential air exchange rates, affecting indoor infiltration of outdoor particles. We conducted a field study examining associations between particle infiltration and temperature to inform future studies of air pollution health effects. METHODS: We measured indoor fine particulate matter (PM(2.5)) in Atlanta in 60 homes (810 sampling-days). Indoor-outdoor sulfur ratios were used to estimate particle infiltration, using central site outdoor sulfur concentrations. Linear and mixed-effects models were used to examine particle infiltration ratio-temperature relationships, based on which we incorporated projected meteorological values (Representative Concentration Pathways intermediate scenario RCP 4.5) to estimate particle infiltration ratios in 20-year future (2046-2065) and past (1981-2000) scenarios. RESULTS: The mean particle infiltration ratio in Atlanta was 0.70 ± 0.30, with a 0.21 lower ratio in summer compared to transition seasons (spring, fall). Particle infiltration ratios were 0.19 lower in houses using heating, ventilation, and air conditioning (HVAC) systems compared to those not using HVAC. We observed significant associations between particle infiltration ratios and both linear and quadratic models of ambient temperature for homes using natural ventilation and those using HVAC. Future temperature was projected to increase by 2.1 °C in Atlanta, which corresponds to an increase of 0.023 (3.9%) in particle infiltration ratios during cooler months and a decrease of 0.037 (6.2%) during warmer months. DISCUSSION: We estimated notable changes in particle infiltration ratio in Atlanta for different 20-year periods, with differential seasonal patterns. Moreover, when stratified by HVAC usage, increases in future ambient temperature due to climate change were projected to enhance seasonal differences in PM(2.5) infiltration in Atlanta. These analyses can help minimize exposure misclassification in epidemiologic studies of PM(2.5), and provide a better understanding of the potential influence of climate change on PM(2.5) health effects.
Air pollution, climate change, and other environmental factors contribute to increasing asthma in many cities, including Washington, DC. This work provides a case study of how community input, neighborhood-level health surveys, and air quality monitoring can inform the understanding of asthma and air pollution. A partnership between residents, concerned citizens, scientists, and educators has been working for environmental health in a DC neighborhood located on a major roadway, next to concrete batch plants and close to several construction projects. A 2016 Community Health and Safety Study by the DC Department of Health, Office of Health Equity, recognized this particular neighborhood as more vulnerable to health impacts from recent construction in the area, compared with the surrounding areas, due to lower average income and higher percentage of seniors and children. This work presents neighborhood health surveys and air quality monitoring data at a more granular, local level than available from DC government agencies. The health surveys documented residents’ experiences around air pollution, asthma, and other health concerns. A key finding was evidence that asthma might be undercounted in this neighborhood; among residents who did not indicate a diagnosis of asthma, many discussed having symptoms that could reflect asthma. Air quality monitoring (particulate matter [PM]) did not indicate that federal air quality standards have been violated. Real-time PM data, however, illustrated how current PM standards, such as 1- and 24-hour averages, may fail to capture shorter duration high PM events that are consistent with resident concerns.
The increasing number and severity of wildfires is negatively impacting air quality for millions of California residents each year. Community exposure to PM(2.5) in two main population centers (San Francisco Bay area and Los Angeles County area) was assessed using the low-cost PurpleAir sensor network for the record-setting 2020 California wildfire season. Estimated PM(2.5) concentrations in each study area were compared to census tract-level environmental justice vulnerability indicators, including environmental, health, and demographic data. Higher PM(2.5) concentrations were positively correlated with poverty, cardiovascular emergency department visits, and housing inequities. Sensors within 30 km of actively burning wildfires showed statistically significant increases in indoor (~800 %) and outdoor (~540 %) PM(2.5) during the fires. Results indicate that wildfire emissions may exacerbate existing health disparities as well as the burden of pollution in disadvantaged communities, suggesting a need to improve monitoring and adaptive capacity among vulnerable populations.
Nitrogen dioxide (NO2) is responsible for aggravating respiratory diseases, particularly asthma. The aim of this study is to investigate the association between NO2 exposure and asthma emergency department (ED) visits during the cold season (November-February) in five populated locations (Sacramento, San Francisco, Fresno, Los Angeles, and San Diego) of California from 2005 to 2015 (1320 Days). Conditional logistic regression models were used to obtain the odds ratio (OR) and 95% confidence interval Cl)( associated with a 5 ppb increase in NO2 concentration for the 19,735 ED visits identified. An increase in NO2 exposure increased the odds of having asthma ED visits for the studied population. The potential effect modification by sex (female and male), race (White, Black, Hispanic, and Asian), and age (2-5, 6-18, 19-40, 41-64, and ?65) was explored. A 5 ppb increase in the concentration of NO2 during lag 0-30 was associated with a 56% increase in the odds of having an asthma ED visit (OR 1.560, Cl: 1.428-1.703). Sex was not found lo be a modifier. Asthma ED visits among all the racesiehnicities (except Asians) were associated with NO2 exposure. Whiles had the highest OR 75% (OR 1.750, CI: 1A17-2.160) at lag 0-30 in response to NO2 exposure. The association between NO2 exposure and asthma ED visits was positive among all age groups except fur 19 to 40 years old; the OR was higher among 2 to 18 year old (al lag 0-30: age group 2-5 (OR – 1.699, CI: 1.399-2.062), and age group 6-18 (OR – 1.568, CII.348-1.825)). For stratification by location, San Diego and Fresno were found to have the highest OR, compared lo the other studied locations. (C) 2020 Elsevier B.V. All rights reserved.
Pollen and molds are environmental allergens that are affected by climate change. As pollen and molds exhibit geographical variations, we sought to understand the impact of climate change (temperature, carbon dioxide (CO(2)), precipitation, smoke exposure) on common pollen and molds in the San Francisco Bay Area, one of the largest urban areas in the United States. When using time-series regression models between 2002 and 2019, the annual average number of weeks with pollen concentrations higher than zero increased over time. For tree pollens, the average increase in this duration was 0.47 weeks and 0.51 weeks for mold spores. Associations between mold, pollen and meteorological data (e.g., precipitation, temperature, atmospheric CO(2), and area covered by wildfire smoke) were analyzed using the autoregressive integrated moving average model. We found that peak concentrations of weed and tree pollens were positively associated with temperature (p < 0.05 at lag 0-1, 0-4, and 0-12 weeks) and precipitation (p < 0.05 at lag 0-4, 0-12, and 0-24 weeks) changes, respectively. We did not find clear associations between pollen concentrations and CO(2) levels or wildfire smoke exposure. This study's findings suggest that spore and pollen activities are related to changes in observed climate change variables.
This study focused on the measurement of BTEX (benzene, toluene, ethylbenzene and xylene) concentrations in the air of various regions and indoor-outdoor environments in Bandar Abbas, Iran. Air samples were taken actively and analyzed by gas chromatography-mass spectrometry (GC-MS) during two one-month periods i.e., Feb 2020 (period I) and Sep/Oct 2020 (period II). The mean air temperature and the levels of all BTEX compounds were higher in period II. The highest total BTEX (t-BTEX) levels (median [min-max]) were found in the urban region (18.00 [5.21-67.24] μg m(-3)), followed by industrial region (7.00 [2.05-14.76] μg m(-3)) and rural region (2.81 [ND-7.38] μg m(-3)). The significant positive correlations between all BTEX compounds and T/B ratio >1 indicated the vehicular traffic as the main source of emission. At 95th percentile probability, the non-cancer risk of t-BTEX in urban region was only less than one order of magnitude below the threshold level of unity (1.91E-01) and the cancer risk of benzene exceeded the recommended level of 1.0E-06 by U.S. EPA in urban (7.69E-06) and industrial (2.97E-06) regions. It was found that the indoor/outdoor ratio of BTEX concentration in beauty salon and hospital was greater than 1. Overall, the current levels of BTEX in the ambient air of study area, especially near urban roadside and in some indoor environments, should not be overlooked and appropriate mitigation actions should be undertaken.
Evidence shows that climate change may have adverse effects on human health. The purpose of this study was to investigate the relation between Physiologically Equivalent Temperature (PET) and cardiovascular hospital admissions in Ahvaz. Distributed Lag Non-linear Models (DLNM) combined with quasi-Poisson regression models were used to investigate the effect of PET on hospital admissions. Low PET values (6.4 °C, 9.9 °C and 16.9 °C) in all lags, except lag 0-30, significantly decreased the risk of hospital admissions for total cardiovascular diseases, hypertension, ischemic heart diseases, and cardiovascular admissions in men, women and ≤65 years. But, low PET (6.4 °C) in lags 0 and 0-2 significantly increased the risk of hospital admissions for cerebrovascular diseases; and high PET values increased the risk of ischemic heart diseases and in men. Both cold and hot stress are involved in cardiovascular hospital admissions.
In this study, the variability and trends of the outdoor thermal discomfort index (DI) in the Kingdom of Saudi Arabia (KSA) were analyzed over the 39-year period of 1980-2018. The hourly DI was estimated based on air temperature and relative humidity data obtained from the next-generation global reanalysis from the European Center for Medium-Range Weather Forecasts and in-house high-resolution regional reanalysis generated using an assimilative Weather Research Forecast (WRF) model. The DI exceeds 28°C, that is, the threshold for human discomfort, in all summer months (June to September) over most parts of the KSA due to a combination of consistently high temperatures and relative humidity. The DI is greater than 28°C for 8-16 h over the western parts of KSA and north of the central Red Sea. A DI of >28°C persistes for 7-9 h over the Red Sea and western KSA for 90% of summer days. The spatial extent and number of days with DI > 30°C, that is, the threshold for severe human discomfort, are significantly lower than those with DI > 28°C. Long-term trends in the number of days with DI > 28°C indicate a reduced rate of increase or even a decrease over some parts of the southwestern KSA in recent decades (1999-2018). Areas with DI > 30°C, in particular the northwestern regions of the Arabian Gulf and its adjoining regions, also showed improved comfort levels during recent decades. Significant increases in population and urbanization have been reported throughout the KSA during the study period. Analysis of five-years clinical data suggests a positive correlation between higher temperatures and humidity with heat-related deaths during the Hajj pilgrimage. The information provided herein is expected to aid national authorities and policymakers in developing necessary strategies to mitigate the exposure of humans to high levels of thermal discomfort in the KSA.
OBJECTIVES: To study the epidemiology of dengue incidence and understand the dynamics of dengue transmission in Makkah, Kingdom of Saudi Arabia (KSA), between 2017-2019. METHODS: This is a cross-sectional study. Health and demographic data was obtained for all confirmed dengue cases in Makkah, KSA, in the years 2017-2019 from the Vector-Borne and Zoonotic Diseases Administration (VBZDA) in Makkah and the Makkah Regional Laboratory, KSA. In addition, entomological data about Aedes density was obtained from the VBZDA. Descriptive epidemiological methods were used to determine the occurrence and distribution of dengue cases. RESULTS: Laboratory-confirmed dengue cases were higher in 2019 as compared to 2017 and 2018, suggesting an outbreak of dengue in Makkah, KSA, in 2019. The incidence of confirmed dengue cases was 204 in 2017, 163 in 2018 and 748 in 2019. Dengue mostly affected people in the 25-44 age group, accounting for approximately half of the annual dengue cases each year. Men were at a higher dengue incidence risk when compared to women, and Saudi women had a higher risk rate for dengue cases when compared to non-Saudi women in all 3 years studied. There was no dengue related death in these 3 years. CONCLUSION: The dengue incidence increased in Makkah, KSA, in 2019 as compared to the previous 2 years, owing to heavy rainfall in 2019. Post-rainfall Vector control efforts may help contain the disease in Makkah, KSA.
Polycyclic aromatic hydrocarbons (PAHs) represent one of the major toxic pollutants associated with PM(2.5) with significant human health and climate effects. Because of local and long-range transport of atmospheric PAHs to receptor sites, higher global attentions have been focused to improve PAHs pollution emission management. In this study, PM(2.5) samples were collected at three urban sites located in the capital of Iran, Tehran, during the heating and non-heating periods (H-period and NH-period). The US EPA 16 priority PAHs were analyzed and the data were processed to the following detailed aims: (i) investigate the H-period and NH-period variations of PM(2.5) and PM(2.5)-bound PAHs concentrations; (ii) identify the PAHs sources and the source locations during the two periods; (iii) carry out a source-specific excess cancer risk (ECR) assessment highlighting the potential source locations contributing to the ECR using a hybrid approach. Total PAHs (TPAHs) showed significantly higher concentrations (1.56-1.89 times) during the H-period. Among the identified PAHs compounds, statistically significant periodical differences (p-value < 0.05) were observed only between eight PAHs species (Nap, BaA, Chr, BbF, BkF, BaP, IcdP, and DahA) at all three sampling sites which can be due to the significant differences of PAHs emission sources during H and NH-periods. High molecular weight (HMW) PAHs accounted for 52.7% and 46.8% on average of TPAHs during the H-period and NH-period, respectively. Positive matrix factorization (PMF) led to identifying four main PAHs sources including industrial emissions, petrogenic emissions, biomass burning and natural gas emissions, and vehicle exhaust emissions. Industrial and petrogenic emissions exhibited the highest contribution (19.8%, 27.2%, respectively) during the NH-period, while vehicle exhaust and biomass burning-natural gas emissions showed the largest contribution (40.7%, 29.6%, respectively) during the H-period. Concentration weighted trajectory (CWT) on factor contributions was used for tracking the potential locations of the identified sources. In addition to local sources, long-range transport contributed to a significant fraction of TPHAs in Tehran both during the H- and NH-periods. Source-specific carcinogenic risks assessment apportioned vehicle exhaust (44.2%, 2.52 × 10(-4)) and biomass burning-natural gas emissions (33.9%, 8.31 × 10(-5)) as the main cancer risk contributors during the H-period and NH-period, respectively. CWT maps pointed out the different distribution patterns associated with the cancer risk from the identified sources. This will allow better risk management through the identification of priority PAHs sources.
In this review, seven pieces of research on climate variability and its impact on human health in Buenos Aires City between 1995 and 2015 were evaluated. The review highlighted continuities and ruptures in the methodology, variables, and statistics data of the research, considering their similarities and differences in the period of study and the methodology applied. Contributions, pending issues, and public policies on climate change challenges in the city aimed at improving living conditions were considered. Six studies contributed evidence on the relationship between climate and health and its impacts on the population; two studies suggested the development of early warning systems and one study is a preliminary approach.
(1) Background: Increasing and improving green spaces have been suggested to enhance health and well-being through different mechanisms. Latin America is experiencing fast population and urbanization growth; with rising demand for interventions to improve public health and mitigate climate change. (2) Aim: This study aimed to review the epidemiological evidence on green spaces and health outcomes in Latin America. (3) Methods: A systematic literature review of green spaces and health outcomes was carried out for studies published in Latin America before 28 September 2020. A search strategy was designed to identify studies published in Medline via PubMed and LILACS. The search strategy included terms related to green spaces combined with keywords related to health and geographical location. No time limit for the publication was chosen. The search was limited to English, Spanish, Portuguese, and French published articles and humans’ studies. (4) Findings: This systematic review found 19 epidemiological studies in Latin America related to green spaces and health outcomes. Nine studies were conducted in Brazil, six in Mexico, three in Colombia, and one in Chile. In terms of study design, 14 were cross-sectional studies, 3 ecological, and 2 cohort studies. The population included among the studies ranged from 120 persons to 103 million. The green space definition used among studies was green density or proximity (eight studies), green presence (five studies), green spaces index (four studies), and green space visit (two studies). The health outcomes included were mental health (six studies), overweight and obesity (three studies), quality of life (three studies), mortality (two studies), cardiorespiratory disease (one study), disability (one study), falls (one study), and life expectancy (one study). Eleven studies found a positive association between green spaces and health, and eight studies found no association. (5) Conclusion: This systematic review identified 19 epidemiological studies associating green spaces and health outcomes in Latin America. Most of the evidence suggests a positive association between green spaces and health in the region. However, most of the evidence was supported by cross-sectional studies. Prioritizing longitudinal studies with harmonized exposure and outcome definitions and including vulnerable and susceptible populations is needed in the region.
Urban ecosystem services have become a main issue in contemporary urban sustainable development, whose efforts are challenged by the phenomena of world urbanization and climate change. This article presents a study about the ecosystem services of green infrastructure towards better respiratory health in a socioeconomic scenario typical of the Global South countries. The study involved a data science approach comprising basic and multivariate statistical analysis, as well as data mining, for the municipalities of the state of Parana, in Brazil’s South region. It is a cross-sectional study in which multiple data sets are combined and analyzed to uncover relationships or patterns. Data were extracted from national public domain databases. We found that, on average, the municipalities with more area of biodiversity per inhabitant have lower rates of hospitalizations resulting from respiratory diseases (CID-10 X). The biodiversity index correlates inversely with the rates of hospitalizations. The data analysis also demonstrated the importance of socioeconomic issues in the environmental-respiratory health phenomena. The data mining analysis revealed interesting associative rules consistent with the learning from the basic statistics and multivariate analysis. Our findings suggest that green infrastructure provides ecosystem services towards better respiratory health, but these are entwined with socioeconomics issues. These results can support public policies towards environmental and health sustainable management.
The present analysis uses the data of confirmed incidence of dengue cases in the metropolitan region of Panama from 1999 to 2017 and climatic variables (air temperature, precipitation, and relative humidity) during the same period to determine if there exists a correlation between these variables. In addition, we compare the predictive performance of two regression models (SARIMA, SARIMAX) and a recurrent neural network model (RNN-LSTM) on the dengue incidence series. For this data from 1999-2014 was used for training and the three subsequent years of incidence 2015-2017 were used for prediction. The results show a correlation coefficient between the climatic variables and the incidence of dengue were low but statistical significant. The RMSE and MAPE obtained for the SARIMAX and RNN-LSTM models were 25.76, 108.44 and 26.16, 59.68, which suggest that any of these models can be used to predict new outbreaks. Although, it can be said that there is a limited role of climatic variables in the outputs the models. The value of this work is that it helps understand the behaviour of cases in a tropical setting as is the Metropolitan Region of Panama City, and provides the basis needed for a much needed early alert system for the region.
BACKGROUND: Temperature and rainfall patterns are known to influence seasonal patterns of dengue transmission. However, the effect of severe drought and extremely wet conditions on the timing and intensity of dengue epidemics is poorly understood. In this study, we aimed to quantify the non-linear and delayed effects of extreme hydrometeorological hazards on dengue risk by level of urbanisation in Brazil using a spatiotemporal model. METHODS: We combined distributed lag non-linear models with a spatiotemporal Bayesian hierarchical model framework to determine the exposure-lag-response association between the relative risk (RR) of dengue and a drought severity index. We fit the model to monthly dengue case data for the 558 microregions of Brazil between January, 2001, and January, 2019, accounting for unobserved confounding factors, spatial autocorrelation, seasonality, and interannual variability. We assessed the variation in RR by level of urbanisation through an interaction between the drought severity index and urbanisation. We also assessed the effect of hydrometeorological hazards on dengue risk in areas with a high frequency of water supply shortages. FINDINGS: The dataset included 12 895 293 dengue cases reported between 2001 and 2019 in Brazil. Overall, the risk of dengue increased between 0-3 months after extremely wet conditions (maximum RR at 1 month lag 1·56 [95% CI 1·41-1·73]) and 3-5 months after drought conditions (maximum RR at 4 months lag 1·43 [1·22-1·67]). Including a linear interaction between the drought severity index and level of urbanisation improved the model fit and showed the risk of dengue was higher in more rural areas than highly urbanised areas during extremely wet conditions (maximum RR 1·77 [1·32-2·37] at 0 months lag vs maximum RR 1·58 [1·39-1·81] at 2 months lag), but higher in highly urbanised areas than rural areas after extreme drought (maximum RR 1·60 [1·33-1·92] vs 1·15 [1·08-1·22], both at 4 months lag). We also found the dengue risk following extreme drought was higher in areas that had a higher frequency of water supply shortages. INTERPRETATION: Wet conditions and extreme drought can increase the risk of dengue with different delays. The risk associated with extremely wet conditions was higher in more rural areas and the risk associated with extreme drought was exacerbated in highly urbanised areas, which have water shortages and intermittent water supply during droughts. These findings have implications for targeting mosquito control activities in poorly serviced urban areas, not only during the wet and warm season, but also during drought periods. FUNDING: Royal Society, Medical Research Council, Wellcome Trust, National Institutes of Health, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, and Conselho Nacional de Desenvolvimento Científico e Tecnológico. TRANSLATION: For the Portuguese translation of the abstract see Supplementary Materials section.
The relationship between hydrometeorological disasters and the health of affected populations is still hardly discussed in Rio Grande do Sul (RS), Brazil. Hepatitis A is a disease that involves health and urban environment issue and is an avoidable disease. This study aims to analyze the relationship between flood areas and waterborne diseases, in this case, Hepatitis A. A database of confirmed cases of Hepatitis A and flood events in the municipality of Encantado-RS, Brazil between 2012 and 2014 was structured. These data were analyzed spatially from the kernel estimator of the occurrence points of Hepatitis A cases and correlated to the urban perimeter. It was verified that 44 cases were registered in the three months following the occurrence of flood, an increase of almost 300% in the records of Hepatitis A. The results identified that all the confirmed cases are in the urban area located in the floodplain. This reaffirms the importance of encouraging the formulation and implementation of policies to prevent outbreaks of waterborne diseases post hydrometeorological disaster.
This article compares urban and rural household water insecurity experiences during the last major drought period (2011-17) in the semi-arid interior region of Ceara, Brazil. Using data from a household survey (N = 322), we determined that households in small urban areas are more and differently water insecure than rural counterparts. Factor analysis and an ordinal logistic regression pinpoint key dimensions, such as water distress, water-sharing and intermittency, contribute differently to water insecurity in rural and urban households. Policy recommendations are made.
A significant fraction of Brazil’s population has been exposed to drought in recent years, a situation that is expected to worsen in frequency and intensity due to climate change. This constitutes a current key environmental health concern, especially in densely urban areas such as several big cities and suburbs. For the first time, a comprehensive assessment of the short-term drought effects on weekly non-external, circulatory, and respiratory mortality was conducted in 13 major Brazilian macro-urban areas across 2000-2019. We applied quasi-Poisson regression models adjusted by temperature to explore the association between drought (defined by the Standardized Precipitation-Evapotranspiration Index) and the different mortality causes by location, sex, and age groups. We next conducted multivariate meta-analytical models separated by cause and population groups to pool individual estimates. Impact measures were expressed as the attributable fractions among the exposed population, from the relative risks (RRs). Overall, a positive association between drought exposure and mortality was evidenced in the total population, with RRs varying from 1.003 [95% CI: 0.999-1.007] to 1.010 [0.996-1.025] for non-external mortality related to moderate and extreme drought conditions, from 1.002 [0.997-1.007] to 1.008 [0.991-1.026] for circulatory mortality, and from 1.004 [0.995-1.013] to 1.013 [0.983-1.044] for respiratory mortality. Females, children, and the elderly population were the most affected groups, for whom a robust positive association was found. The study also revealed high heterogeneity between locations. We suggest that policies and action plans should pay special attention to vulnerable populations to promote efficient measures to reduce vulnerability and risks associated with droughts.
Dengue is steadily increasing worldwide and expanding into higher latitudes. Current non-endemic areas are prone to become endemic soon. To improve understanding of dengue transmission in these settings, we assessed the spatiotemporal dynamics of the hitherto largest outbreak in the non-endemic metropolis of Buenos Aires, Argentina, based on detailed information on the 5,104 georeferenced cases registered during summer-autumn of 2016. The highly seasonal dengue transmission in Buenos Aires was modulated by temperature and triggered by imported cases coming from regions with ongoing outbreaks. However, local transmission was made possible and consolidated heterogeneously in the city due to housing and socioeconomic characteristics of the population, with 32.8% of autochthonous cases occurring in slums, which held only 6.4% of the city population. A hierarchical spatiotemporal model accounting for imperfect detection of cases showed that, outside slums, less-affluent neighborhoods of houses (vs. apartments) favored transmission. Global and local spatiotemporal point-pattern analyses demonstrated that most transmission occurred at or close to home. Additionally, based on these results, a point-pattern analysis was assessed for early identification of transmission foci during the outbreak while accounting for population spatial distribution. Altogether, our results reveal how social, physical, and biological processes shape dengue transmission in Buenos Aires and, likely, other non-endemic cities, and suggest multiple opportunities for control interventions.
Dengue is a re-emerging disease, currently considered the most important mosquito-borne arbovirus infection affecting humankind, taking into account both its morbidity and mortality. Brazil is considered an endemic country for dengue, such that more than 1,544,987 confirmed cases were notified in 2019, which means an incidence rate of 735 for every 100 thousand inhabitants. Climate is an important factor in the temporal and spatial distribution of vector-borne diseases, such as dengue. Thus, rainfall and temperature are considered macro-factors determinants for dengue, since they directly influence the population density of Aedes aegypti, which is subject to seasonal fluctuations, mainly due to these variables. This study examined the incidence of dengue fever related to the climate influence by using temperature and rainfall variables data obtained from remote sensing via artificial satellites in the metropolitan region of Rio de Janeiro, Brazil. The mathematical model that best fits the data is based on an auto-regressive moving average with exogenous inputs (ARMAX). It reproduced the values of incidence rates in the study period and managed to predict with good precision in a one-year horizon. The approach described in present work may be replicated in cities around the world by the public health managers, to build auxiliary operational tools for control and prevention tasks of dengue, as well of other arbovirus diseases.
Efficient and accurate dengue risk prediction is an important basis for dengue prevention and control, which faces challenges, such as downloading and processing multi-source data to generate risk predictors and consuming significant time and computational resources to train and validate models locally. In this context, this study proposed a framework for dengue risk prediction by integrating big geospatial data cloud computing based on Google Earth Engine (GEE) platform and artificial intelligence modeling on the Google Colab platform. It enables defining the epidemiological calendar, delineating the predominant area of dengue transmission in cities, generating the data of risk predictors, and defining multi-date ahead prediction scenarios. We implemented the experiments based on weekly dengue cases during 2013-2020 in the Federal District and Fortaleza, Brazil to evaluate the performance of the proposed framework. Four predictors were considered, including total rainfall (R(sum)), mean temperature (T(mean)), mean relative humidity (RH(mean)), and mean normalized difference vegetation index (NDVI(mean)). Three models (i.e., random forest (RF), long-short term memory (LSTM), and LSTM with attention mechanism (LSTM-ATT)), and two modeling scenarios (i.e., modeling with or without dengue cases) were set to implement 1- to 4-week ahead predictions. A total of 24 models were built, and the results showed in general that LSTM and LSTM-ATT models outperformed RF models; modeling could benefit from using historical dengue cases as one of the predictors, and it makes the predicted curve fluctuation more stable compared with that only using climate and environmental factors; attention mechanism could further improve the performance of LSTM models. This study provides implications for future dengue risk prediction in terms of the effectiveness of GEE-based big geospatial data processing for risk predictor generation and Google Colab-based risk modeling and presents the benefits of using historical dengue data as one of the input features and the attention mechanism for LSTM modeling.
Dengue fever is re-emerging worldwide, however the reasons of this new emergence are not fully understood. Our goal was to report the incidence of dengue in one of the most populous States of Brazil, and to assess the high-risk areas using a spatial and spatio-temporal annual models including geoclimatic, demographic and socioeconomic characteristics. An ecological study with both, a spatial and a temporal component was carried out in Sao Paulo State, Southeastern Brazil, between January 1st, 2007 and December 31st, 2019. Crude and Bayesian empirical rates of dengue cases following by Standardized Incidence Ratios (SIR) were calculated considering the municipalities as the analytical units and using the Integrated Nested Laplace Approximation in a Bayesian context. A total of 2,027,142 cases of dengue were reported during the studied period. The spatial model allocated the municipalities in four groups according to the SIR values: (I) SIR<0.8; (II) SIR 0.8<1.2; (III) SIR 1.2<2.0 and SIR>2.0 identified the municipalities with higher risk for dengue outbreaks. “Hot spots” are shown in the thematic maps. Significant correlations between SIR and two climate variables, two demographic variables and one socioeconomical variable were found. No significant correlations were found in the spatio-temporal model. The incidence of dengue exhibited an inconstant and unpredictable variation every year. The highest rates of dengue are concentrated in geographical clusters with lower surface pressure, rainfall and altitude, but also in municipalities with higher degree of urbanization and better socioeconomic conditions. Nevertheless, annual consolidated variations in climatic features do not influence in the epidemic yearly pattern of dengue in southeastern Brazil.
BACKGROUND: This research addresses two questions: (1) how El Niño Southern Oscillation (ENSO) affects climate variability and how it influences dengue transmission in the Metropolitan Region of Recife (MRR), and (2) whether the epidemic in MRR municipalities has any connection and synchronicity. METHODS: Wavelet analysis and cross-correlation were applied to characterize seasonality, multiyear cycles, and relative delays between the series. This study was developed into two distinct periods. Initially, we performed periodic dengue incidence and intercity epidemic synchronism analyses from 2001 to 2017. We then defined the period from 2001 to 2016 to analyze the periodicity of climatic variables and their coherence with dengue incidence. RESULTS: Our results showed systematic cycles of 3-4 years with a recent shortening trend of 2-3 years. Climatic variability, such as positive anomalous temperatures and reduced rainfall due to changes in sea surface temperature (SST), is partially linked to the changing epidemiology of the disease, as this condition provides suitable environments for the Aedes aegypti lifecycle. CONCLUSION: ENSO may have influenced the dengue temporal patterns in the MRR, transiently reducing its main way of multiyear variability (3-4 years) to 2-3 years. Furthermore, when the epidemic coincided with El Niño years, it spread regionally and was highly synchronized.
Tropical countries face urgent public health challenges regarding epidemic control of Dengue. Since effective vector-control efforts depend on the timing in which public policies take place, there is an enormous demand for accurate prediction tools. In this work, we improve upon a recent approach of coarsely predicting outbreaks in Brazilian urban centers based solely on their yearly climate data. Our methodological advancements encompass a judicious choice of data pre-processing steps and usage of modern computational techniques from signal-processing and manifold learning. Altogether, our results improved earlier prediction accuracy scores from 0.72 to 0.80, solidifying manifold learning on climate data alone as a viable way to make (coarse) dengue outbreak prediction in large urban centers. Ultimately, this approach has the potential of radically simplifying the data required to do outbreak analysis, as municipalities with limited public health funds may not monitor a large number of features needed for more extensive machine learning approaches.
According to the World Health Organization, dengue is a neglected tropical disease. Latin America, specifically Colombia is in alert regarding this arbovirosis as there was a spike in the number of reported dengue cases at the beginning of 2019. Although there has been a worldwide decrease in the number of reported dengue cases, Colombia has shown a growing trend over the past few years. This study performed a Poisson multilevel analysis with mixed effects on STATA® version 16 and R to assess sociodemographic, climatic, and entomological factors that may influence the occurrence of dengue in three municipalities for the period 2010-2015. Information on dengue cases and their sociodemographic variables was collected from the National Public Health Surveillance System (SIVIGILA) records. For climatic variables (temperature, relative humidity, and precipitation), we used the information registered by the weather stations located in the study area, which are managed by the Instituto de Hidrologia, Meteorologia y Estudios Ambientales (IDEAM) or the Corporación Autónoma Regional (CAR). The entomological variables (house index, container index, and Breteau index) were provided by the Health office of the Cundinamarca department. SIVIGILA reported 1921 dengue cases and 56 severe dengue cases in the three municipalities; of them, three died. One out of four cases occurred in rural areas. The age category most affected was adulthood, and there were no statistical differences in the number of cases between sexes. The Poisson multilevel analysis with the best fit model explained the presentation of cases were temperature, relative humidity, precipitation, childhood, live in urban area and the contributory healthcare system. The temperature had the biggest influence on the presentation of dengue cases in this region between 2010 and 2015.
No abstract available.
This systematic review of reviews was conducted to examine housing precarity and homelessness in relation to climate change and weather extremes internationally. In a thematic analysis of 15 reviews (5 systematic and 10 non-systematic), the following themes emerged: risk factors for homelessness/housing precarity, temperature extremes, health concerns, structural factors, natural disasters, and housing. First, an increased risk of homelessness has been found for people who are vulnerably housed and populations in lower socio-economic positions due to energy insecurity and climate change-induced natural hazards. Second, homeless/vulnerably-housed populations are disproportionately exposed to climatic events (temperature extremes and natural disasters). Third, the physical and mental health of homeless/vulnerably-housed populations is projected to be impacted by weather extremes and climate change. Fourth, while green infrastructure may have positive effects for homeless/vulnerably-housed populations, housing remains a major concern in urban environments. Finally, structural changes must be implemented. Recommendations for addressing the impact of climate change on homelessness and housing precarity were generated, including interventions focusing on homelessness/housing precarity and reducing the effects of weather extremes, improved housing and urban planning, and further research on homelessness/housing precarity and climate change. To further enhance the impact of these initiatives, we suggest employing the Human Rights-Based Approach (HRBA).
The recent outbreak of coronavirus disease 2019 (COVID-19) and concerns about several other pandemics in the 21st century have attracted extensive global attention. These emerging infectious diseases threaten global public health and raise urgent studies on unraveling the underlying mechanisms of their transmission from animals to humans. Although numerous works have intensively discussed the cross-species and endemic barriers to the occurrence and spread of emerging infectious diseases, both types of barriers play synergistic roles in wildlife habitats. Thus far, there is still a lack of a complete understanding of viral diffusion, migration, and transmission in ecosystems from a macro perspective. In this review, we conceptualize the ecological barrier that represents the combined effects of cross-species and endemic barriers for either the natural or intermediate hosts of viruses. We comprehensively discuss the key influential factors affecting the ecological barrier against viral transmission from virus hosts in their natural habitats into human society, including transmission routes, contact probability, contact frequency, and viral characteristics. Considering the significant impacts of human activities and global industrialization on the strength of the ecological barrier, ecological barrier deterioration driven by human activities is critically analyzed for potential mechanisms. Global climate change can trigger and expand the range of emerging infectious diseases, and human disturbances promote higher contact frequency and greater transmission possibility. In addition, globalization drives more transmission routes and produces new high-risk regions in city areas. This review aims to provide a new concept for and comprehensive evidence of the ecological barrier blocking the transmission and spread of emerging infectious diseases. It also offers new insights into potential strategies to protect the ecological barrier and reduce the wide-ranging risks of emerging infectious diseases to public health.
As society tries to tackle climate change around the globe, communities need to reduce its impact on human health. The purpose of this review is to identify key stakeholders involved in mitigating and adapting to climate change, as well as the type and characteristics of community empowerment actions implemented so far to address the problem. Published and unpublished studies from January 2005 to March 2022 in English and Portuguese were included in this review. The search, conducted on PubMed, CINAHL, Scopus, MEDLINE, Scopus, Web of Science, SciELO, and RCAAP (Repositório Científico de Acesso Aberto de Portugal), followed a three-step search strategy. Data extraction was performed by two independent reviewers, using an extraction tool specifically designed for the review questions. Twenty-seven studies were eligible for inclusion: six used interviews as a qualitative method, three were systematic reviews, three were case study analyses, three used surveys and questionnaires as quantitative methods, two used integrative baseline reviews, and three utilized a process model design. Six studies targeted local, public and private stakeholders. Community settings were the context target of fifteen studies, whereas twelve specifically referred to urban settings. Seven types of community actions were acknowledged across the globe, characterised as hybrid interventions and referring to the leading stakeholders: local governments, non-governmental organizations, civil society, universities, public health, and private sectors.
Cities must address many challenges including air quality, climate change and the health and wellbeing of communities. Public authorities and developers increasingly look to improve these through the implementation of interventions and innovations, such as low traffic neighbourhoods, deep housing retrofits and green infrastructure. Monitoring the impacts of interventions is essential to determine the success of such projects and to build evidence for broader urban transformation. In this paper we present a mixed-method cross-disciplinary approach that brings together cutting edge atmospheric and data science, measurements of activity in public spaces and novel methods to assess wellbeing-promoting behaviours. The Manchester Urban Observatory focuses on living areas that have a high density of inter-related systems, which require observation, understanding and intervention at multiple levels. This must be completed in line with urban planning goals as well as a clear and succinct data solution that allows robust scientific conclusions to be made and viewed in real time. Delivery of such a monitoring strategy is not trivial and is time, resource and expertise heavy. This paper discusses the methods employed by the Manchester Urban Observatory to monitor the effectiveness off interventions implemented within cities and effective communication strategies with local communities.
Urban climate policy offers a significant opportunity to promote improved public health. The evidence around climate and health cobenefits is growing but has yet to translate into widespread integrated policies. This article presents two systematic reviews: first, looking at quantified cobenefits of urban climate policies, where transportation, land use, and buildings emerge as the most studied sectors; and second, looking at review papers exploring the barriers and enablers for integrating these health cobenefits into urban policies. The latter reveals wide agreement concerning the need to improve the evidence base for cobenefits and consensus about the need for greater political will and leadership on this issue. Systems thinking may offer a way forward to help embrace complexity and integrate health cobenefits into decision making. Knowledge coproduction to bring stakeholders together and advance policy-relevant research for urban health will also be required. Action is needed to bring these two important policy agendas together.
Urban areas continue to be the center of action for many countries due to their contribution to economic development. Many urban areas, through the urbanization process, have become vulnerable to climate risk, thereby making risk mitigation and adaptation essential components in urban planning. The study assessed the impacts of IPCC Assessment Reports (ARs) on academic research on risk mitigation and adaptation concerns in urban areas. The study systematically reviewed literature through searches of the Web of Science and Scopus databases; 852 papers were retrieved and 370 were deemed eligible. The results showed that the East Asia and Pacific, and Europe and Central Asia regions were most interested in IPCC ARs, while Sub-Saharan Africa showed little interest. Several urban concerns, including socio-economic, air quality, extreme temperature, sea level rise/flooding, health, and water supply/drought, were identified. Additionally, studies on negative health outcomes due to extreme temperatures and air pollution did not appear in the first four IPCC ARs. However, significant studies appeared after the launch of the AR5. Here, we must state that climate-related problems of urbanization were known and discussed in scientific papers well before the formation of the IPCC. For instance, the works of Clarke on urban structure and heat mortality and Oke on climatic impacts of urbanization. Though the IPCC ARs show impact, their emphasis on combined mitigation and adaptation policies is limited. This study advocates more combined risk mitigation and adaptation policies in urban areas for increased resilience to climate risk.
Megacities are metropolitan areas with populations over 10 million, and many of them are facing significant global environmental challenges such as air pollution. Intense economic and human activities in megacities result in air pollution emissions, inducing high levels of air pollutants in the atmosphere that harm human health, cause regional haze and acid deposition, damage crops, influence regional air quality, and contribute to climate change. Since the Great London Smog and the first recognized episode of Los Angeles photochemical smog seventy years ago, substantial progress has been achieved in improving the scientific understanding of air pollution and in developing emissions reduction technologies and control measures. However, much remains to be understood about the complex processes of atmospheric transport and reaction mechanisms; the formation and evolution of secondary particles, especially those containing organic species; and the influence of emerging emissions sources and changing climate on air quality and health. Molina (DOI: ) has provided an excellent overview of the sources of emissions in megacities, atmospheric physicochemical processes, air quality trends and management, and the impacts on health and climate for the introductory lecture of this Faraday Discussion.
It has been widely recognised that the threats to human health from global environmental changes (GECs) are increasing in the Anthropocene epoch, and urgent actions are required to tackle these pressing challenges. A scoping review was conducted to provide an overview of the nine planetary boundaries and the threats to population health posed by human activities that are exceeding these boundaries in the Anthropocene. The research progress and key knowledge gaps were identified in this emerging field. Over the past three decades, there has been a great deal of research progress on health risks from climate change, land-use change and urbanisation, biodiversity loss and other GECs. However, several significant challenges remain, including the misperception of the relationship between human and nature; assessment of the compounding risks of GECs; strategies to reduce and prevent the potential health impacts of GECs; and uncertainties in fulfilling the commitments to the Paris Agreement. Confronting these challenges will require rigorous scientific research that is well-coordinated across different disciplines and various sectors. It is imperative for the international community to work together to develop informed policies to avert crises and ensure a safe and sustainable planet for the present and future generations.
Cities emit the majority of greenhouse gas emissions globally and are increasingly committing to aggressive mitigation actions. Cities are also experiencing poor-and in some cases worsening-air quality, contributing to large disease burdens for adults and children. Integrated planning frameworks can help cities leverage and prioritize measures that achieve climate, air quality, and health benefits simultaneously. We developed and applied an integrated climate action planning process that includes air quality, utilizing Pathways-AQ, a new assessment tool, in six pilot cities: Accra, Ghana; Addis Ababa, Ethiopia; Buenos Aires, Argentina; the metropolitan area of Guadalajara, Mexico; Johannesburg, South Africa; and Lima, Peru. Implementing the “ambitious” greenhouse gas reduction scenarios in these cities’ climate action plans would reduce in-city contributions to fine particulate matter (PM2.5) concentrations and would avoid 230-1,040 annual premature deaths per city, by 2050. This new integrated climate action planning process revealed the importance of (i) geographic scales of analysis, (ii) data integration across climate and air quality, (iii) local civic engagement, and (iv) nuanced health messaging. Rapidly scaling up and applying this integrated approach can broaden the group of municipal stakeholders involved in climate-related planning goals, potentially leading to greater ambition by integrating climate, air pollution, and health objectives.
Nuclear science and technology (NST) offers a multitude of applications and tools and has a high level of regulation. However, its contribution to the achievement of global development goals is still incipient. Although its application is directly related to many fields, especially sustainability, the current literature does not relate it to socio-environmental issues, hindering the adoption of public policies based on isotopic and nuclear solutions. In large and megacities, the promotion of human well-being and the conservation of ecosystems are urgent global challenges, especially as a function of the growing expansion of land use modification, water scarcity, and climate change. The relationship between society and NST is addressed in this study, which aims to show how and in what ways the emerging and innovative nuclear and isotopic solutions contribute to the urban dimension of the United Nations 2030 Agenda, expressed by SDG 11 (Sustainable Cities and Communities), and its connection to land, water, and climate change in cities. This gap in knowledge compromises the targeting of resources to improve NST as a development strategy. Demystifying NST and increasing collaboration between ecosystem services and other issues related to sustainability in cities are key to implementing global development policies, especially at the local governance level.
The recent and projected upward trends in the frequency and intensity of climate-induced events in cities have enhanced the focus on adaptation. In addition to enhancing the capacity of cities to prepare for and absorb risks, adaptation measures provide multiple co-benefits. However, health co-benefits are among the least explored. These are now seen as increasingly important with the renewed focus on public health since the COVID-19 pandemic. This study reviews literature focused on the health co-benefits of urban climate change adaptation measures. Health co-benefits of seven different categories of adaptation measures are discussed. Results showed that existing evidence is mainly related to some categories such as critical infrastructure, nature-based solutions, and urban planning and design measures. Other adaptation categories like early warning systems; policy, management & governance, including local adaptation policies; and measures and strategies related to ‘knowledge, perceptions & behavior’ that mainly involve people’s understanding and individual responses to climate change, are relatively underexplored. Moreover, it was discussed that some adaptation measures may result in health trade-offs and these needs to be further studied. Overall, through identifying health co-benefits, results of this review can make a strong case for further promotion of climate change adaptation in cities.
Record climate extremes are reducing urban liveability, compounding inequality, and threatening infrastructure. Adaptation measures that integrate technological, nature-based, and social solutions can provide multiple co-benefits to address complex socioecological issues in cities while increasing resilience to potential impacts. However, there remain many challenges to developing and implementing integrated solutions. In this Viewpoint, we consider the value of integrating across the three solution sets, the challenges and potential enablers for integrating solution sets, and present examples of challenges and adopted solutions in three cities with different urban contexts and climates (Freiburg, Germany; Durban, South Africa; and Singapore). We conclude with a discussion of research directions and provide a road map to identify the actions that enable successful implementation of integrated climate solutions. We highlight the need for more systematic research that targets enabling environments for integration; achieving integrated solutions in different contexts to avoid maladaptation; simultaneously improving liveability, sustainability, and equality; and replicating via transfer and scale-up of local solutions. Cities in systematically disadvantaged countries (sometimes referred to as the Global South) are central to future urban development and must be prioritised. Helping decision makers and communities understand the potential opportunities associated with integrated solutions for climate change will encourage urgent and deliberate strides towards adapting cities to the dynamic climate reality.
Climate change is increasing the frequency and intensity of extreme precipitation events, the impacts of which disproportionately impact urban populations. Pluvial flooding and flooding related sewer backups are thought to result in an increase in potentially hazardous human-pathogen encounters. However, the extent and nature of associations between flooding events and non-communicable respiratory diseases such as chronic bronchitis, asthma, and chronic obstructive pulmonary disease (COPD) are not well understood. This research seeks to characterize the state of research on flooding and NCRDs through a systematic review of the scientific literature. We conducted a systematic search of PubMed, Web of Science, and Scopus for published scholarly research papers using the terms flooding, monsoon, and tropical storm with terms for common NCRDs such as asthma, COPD, and chronic bronchitis. Papers were included if they covered research studies on individuals with defined outcomes of flooding events. We excluded review papers, case studies, and opinion pieces. We retrieved 200 articles from PubMed, 268 from Web of Science and 203 from Scopus which comprised 345 unique papers. An initial review of abstracts yielded 38 candidate papers. A full text review of each left 16 papers which were included for the review. All papers except for one found a significant association between a severe weather event and increased risk for at least one of the NCRDs included in this research. Our findings further suggest that extreme weather events may worsen pre-existing respiratory conditions and increase the risk of development of asthma. Future work should focus on more precisely defining measure of health outcomes using validated tools to describe asthma and COPD exacerbations. Research efforts should also work to collect granular data on patients’ health status and family history and assess possible confounding and mediating factors such as neighborhood water mitigation infrastructure, housing conditions, pollen counts, and other environmental variables.
Outdoor thermal comfort is significantly affected by climate, including macroclimate, local climate, and microclimate. However, the combined impacts of macroclimate and microclimate factors are less understood in previous thermal comfort studies. This paper employed 43 previ-ously published studies to comprehensively explore the impacts of macro-and micro-climatic factors on the outdoor thermal comfort. The relative importance of these influencing factors was assessed via five verified artificial neural network (ANN) models. For studies employing subjec-tive thermal indices which collected participants’ thermal perceptions, the neutral temperature expressed by physiologically equivalent temperature (PET) was found to be significantly corre-lated with macroclimate factors, especially the latitude and season. In studies employing only objective thermal indices, it was found that macroclimate factors, such as the latitude, distance from the sea, and altitude, have similar contribution to the outdoor thermal comfort as micro-climate factors, such as height to width ratio (H/W) and sky view factor. Results resonated with previous findings that outdoor comfort can be improved by changing urban geometry, vegetation, surfaces, and waterbodies. Future design and planning works should consider both macroclimate and microclimate factors and carefully design urban geometry and morphology to improve out-door thermal comfort for regions with disadvantageous macroclimates.
Urban floods are becoming more and more intense and frequent allover the world. Extreme events are the main triggering factors of such floods, and merit attention for what concerns the urban planning and emergency strategies. Numerical models aimed at investigating the optimal paths for evacuees escaping a flooded urban environment may be used by local authorities to properly understand how to improve people safety and mitigate the flood risk. Implementation of empirical laws in such models to describe the people stability in flooded areas is thus crucial to understand the behavior of evacuees and rescuers during emergency conditions. Laboratory experiments have been undertaken using a physical model representing a human body at quasi-natural scale, towed by an electrical engine in the water at rest. This represents a novel laboratory approach which exploits a non-inertial reference frame in motion with the model. The experimental results, obtained using different combinations of water depth and flow speed, have led to empirical laws which outline the stability conditions occurring when either the model front or the model back faces the flow, these respectively corresponding to Backward Toppling Instability (BTI) and Forward Toppling Instability (FTI). Such laws have been found through comparison with reference literature works, using various statistical methods. The FTI condition has been seen to largely improve the human stability compared to BTI, in contrast to the results of previous literature works, which stated an overall similarity between the results of the two toppling conditions. To better understand the role of the water flow during the different tests, hydraulic forces and moments have been measured. It has been seen that dynamic and static effects are comparable during high-speed conditions, especially due to a relevant fluid-model interaction and an increase of the water-surface level, while dynamic effects are negligible during low-speed conditions. The results of the present contribution can represent an important step forward for the numerical models applied to the framework of urban and emergency planning.
Potentially toxic elements (PTEs) in urban soil environments pose a noticeable risk to both ecosystem and human health; however, only a fraction of the elemental content is available for biota. To better know the potential risk of PTEs in the urban soil environment, geochemical fractionation, bioaccessibility, and potential bioavailability of four PTEs (Cd, Cu, Pb, and Zn) were investigated by the combined use of different methods. The results showed that a high non-residual chemical fraction is related to a high bioavailability of the selected elements. The ranges of labile concentration of Cu, Zn, Cd and Pb in all sampling sites measured by diffusive gradients in thin films (DGT) were 3.5-18.0, 14.2-26.5, 0.09-1.0, and 1.8-15.7 μg/L, respectively. The high non-residual contents pointed out a serious hazard to the urban environment. The bioaccessible concentrations in gastric and lung phases were closely positively correlated with DGT-measured content (r = 0.63-0.99, p < 0.05), suggesting the potential use of DGT for the prediction of PTEs risk to human health. Moreover, the correlation of DGT results with the soluble and reducible fractions of PTEs may allow DGT use for quick screenings of the PTEs fraction potentially mobilizable during flooding events in urban soil environments. Our study suggests that combing DGT, bioaccessibility and biogeochemical fractionation could provide a more accurate assessment of the urban environmental quality and be helpful for pollution control and urban planning.
This study presents a global explanatory analysis of the interplay between the severity of flood losses and human presence in floodplain areas. In particular, we relate economic losses and fatalities caused by floods during 1990-2000, with changes in human population and built-up areas in floodplains during 2000-2015 by exploiting global archives. We found that population and built-up areas in floodplains increased in the period 2000-2015 for the majority of the analyzed countries, albeit frequent flood losses in the previous period 1990-2000. In some countries, however, population in floodplains decreased in the period 2000-2015, following more severe floods losses that occurred in the period 1975-2000. Our analysis shows that (i) in low-income countries, population in floodplains increased after a period of high flood fatalities; while (ii) in upper-middle and high-income countries, built-up areas increased after a period of frequent economic losses. In this study, we also provide a general framework to advance knowledge of human-flood interactions and support the development of sustainable policies and measures for flood risk management and disaster risk reduction.
Policy and technology responses to increased temperatures in urban heat islands (UHIs) are discussed in a variety of research; however, their interaction is overlooked and understudied. This is an important oversight because policy and technology are often developed in isolation of each other and not in conjunction. Therefore, they have limited synergistic effects when aimed at solving global issues. To examine this aspect, we conducted a systematic literature review and synthesised 97 articles to create a conceptual structuring of the topic. We identified the following categories: (a) evidence base for policymaking including timescale analysis, effective policymaking instruments as well as decision support and scenario planning; (b) policy responses including landscape and urban form, green and blue area ratio, albedo enhancement policies, transport modal split as well as public health and participation; (c) passive technologies including green building envelopes and development of cool surfaces; and (d) active technologies including sustainable transport as well as energy consumption, heating, ventilation and air conditioning, and waste heat. Based on the findings, we present a framework to guide future research in analysing UHI policy and technology responses more effectively in conjunction with each other.
The concept of nature-based solutions (NBSs) has become increasingly popular among urban policymakers and planners to help them tackle the urban challenges arising from urban expansion and climate change. Stakeholders’ involvement is a fundamental step, and stakeholders’ perceptions and preferences can affect the development of NBS projects. This study aims to identify stakeholders’ perceptions of the most critical urban challenges, the priority interventions, the preferred NBSs and the benefits of the NBSs, and to identify the determinants of these perceptions. A survey was administered to assess stakeholders’ perceptions and views on implementing NBSs in two Portuguese cities with distinct urban, geographical, and socio-economic contexts. A binary logistic regression model was used to understand the determinants of the likelihood of the stakeholders’ answers. According to the stakeholders, climate change is one of the main concerns in the urban context. It is usually associated with the incidence of heatwaves and water scarcity. Additionally, stakeholders are concerned about the low quantity and poor management of green spaces (GSs). They believe that it will be necessary to increase the GS, to recover some degraded areas, and to increase mobility. The preferred NBSs were planting more urban trees, making green shaded areas, and rehabilitating riverbanks. The main expected benefits were benefits for leisure and relaxation, reductions in air temperature, purer air, and improvements in public health. The results showed mostly coherent connections between the main concerns/priorities of the stakeholders and the perceived NBS benefits; however, some stakeholders did not present coherent connections, indicating low awareness of the current policy for implementing NBSs to overcome existing and future urban challenges.
To fully address the multi-faceted challenges of urban heat, it is paramount that humans are placed at the center of the agenda. This is manifested in a recent shift in urban heat studies that aim to achieve a ‘human-centric’ approach, i.e. focusing on personalized characteristics of comfort, well-being, performance, and health, as opposed to the one-size-fits-all solutions and guidelines. The proposed article is focused on systematically reviewing personalized urban heat studies and detailing the objectives posed, methodologies utilized, and limitations yet to be addressed. We further summarize current knowledge and challenges in addressing the impact of personal heat exposure on human life by discussing the literature linked with urban heat studies at the human, building, and city scales. Lastly, this systematic review reveals the need for future evaluations focused on accuracy and standardization of human-centric data collection and analytics, and more importantly, addressing critical geographic and socio-economic knowledge gaps identified in the field.
Prolonged and/or extreme heat has become a natural hazard that presents a significant risk to humans and the buildings, technologies, and infrastructure on which they have previously relied on to provide cooling. This paper presents a conceptual model of a resilient cooling system centred on people, the socio-cultural-technical contexts they inhabit, and the risks posed by the temperature hazard. An integrative literature review process was used to undertake a critical and comprehensive evaluation of published research and grey literature with the objective of adding clarity and detail to the model. Two databases were used to identify risk management and natural hazard literature in multiple disciplines that represent subcomponents of community resilience (social, economic, institutional, infrastructure and environment systems). This review enabled us to characterise in more detail the nature of the temperature hazard, the functionality characteristics of a resilient cooling system, and key elements of the four subsystems: people, buildings, cooling technologies and energy infrastructure. Six key messages can be surmised from this review, providing a guide for future work in policy and practice.
Increased exposure to extreme heat from both climate change and the urban heat island effect-total urban warming-threatens the sustainability of rapidly growing urban settlements worldwide. Extreme heat exposure is highly unequal and severely impacts the urban poor. While previous studies have quantified global exposure to extreme heat, the lack of a globally accurate, fine-resolution temporal analysis of urban exposure crucially limits our ability to deploy adaptations. Here, we estimate daily urban population exposure to extreme heat for 13,115 urban settlements from 1983 to 2016. We harmonize global, fine-resolution (0.05°), daily temperature maxima and relative humidity estimates with geolocated and longitudinal global urban population data. We measure the average annual rate of increase in exposure (person-days/year(-1)) at the global, regional, national, and municipality levels, separating the contribution to exposure trajectories from urban population growth versus total urban warming. Using a daily maximum wet bulb globe temperature threshold of 30 °C, global exposure increased nearly 200% from 1983 to 2016. Total urban warming elevated the annual increase in exposure by 52% compared to urban population growth alone. Exposure trajectories increased for 46% of urban settlements, which together in 2016 comprised 23% of the planet’s population (1.7 billion people). However, how total urban warming and population growth drove exposure trajectories is spatially heterogeneous. This study reinforces the importance of employing multiple extreme heat exposure metrics to identify local patterns and compare exposure trends across geographies. Our results suggest that previous research underestimates extreme heat exposure, highlighting the urgency for targeted adaptations and early warning systems to reduce harm from urban extreme heat exposure.
This article presents a customized system dynamics model to facilitate the informed development of policy for urban heat island mitigation within the context of future climate change, and with special emphasis on the reduction of heat-related mortality. The model incorporates a variety of components (incl.: the urban heat island effect; population dynamics; climate change impacts on temperature; and heat-related mortality) and is intended to provide urban planning and related professionals with: a facilitated means of understanding the risk of heat-related mortality within the urban heat island; and location-specific information to support the development of reasoned and targeted urban heat island mitigation policy.
BACKGROUND: The earth’s climate is warming and the frequency, duration, and severity of heat waves are increasing. Meanwhile, the world’s population is rapidly aging. Epidemiological data demonstrate exponentially greater increases in morbidity and mortality during heat waves in adults ≥65 years. Laboratory data substantiate the mechanistic underpinnings of age-associated differences in thermoregulatory function. However, the specific combinations of environmental conditions (i.e., ambient temperature and absolute/relative humidity) above which older adults are at increased risk of heat-related morbidity and mortality are less clear. METHODS: This review was conducted to (1) examine the recent (past 3 years) literature regarding heat-related morbidity and mortality in the elderly and discuss projections of future heat-related morbidity and mortality based on climate model data, and (2) detail the background and unique methodology of our ongoing laboratory-based projects aimed toward identifying the specific environmental conditions that result in elevated risk of heat illness in older adults, and the implications of using the data toward the development of evidence-based safety interventions in a continually-warming climate (PSU HEAT; Human Environmental Age Thresholds). RESULTS: The recent literature demonstrates that extreme heat continues to be increasingly detrimental to the health of the elderly and that this is apparent across the world, although the specific environmental conditions above which older adults are at increased risk of heat-related morbidity and mortality remain unclear. CONCLUSION: Characterizing the environmental conditions above which risk of heat-related illnesses increase remains critical to enact policy decisions and mitigation efforts to protect vulnerable people during extreme heat events.
Globally, extreme temperatures have severe impacts on the economy, human health, food and water security, and ecosystems. Mortality rates have been increased due to heatwaves in several regions. Specifically, megacities have high impacts with the increasing temperature and everexpanding urban areas; it is important to understand extreme temperature changes in terms of duration, magnitude, and frequency for future risk management and disaster mitigation. Here we framed a novel Semi-Parametric quantile mapping method to bias-correct the CMIP6 minimum and maximum temperature projections for 199 megacities worldwide. The changes in maximum and minimum temperature are quantified in terms of climate indices (ETCCDI and HDWI) for the four Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). Cities in northern Asia and northern North America (Kazan, Samara, Heihe, Montre ‘ al, Edmonton, and Moscow) are warming at a higher rate compared to the other regions. There is an increasing and decreasing trend for the warm and cold extremes respectively. Heatwaves increase exponentially in the future with the increase in warming, that is, from SSP1-2.6 to SSP5-8.5. Among the CMIP6 models, a huge variability is observed, and this further increases as the warming increases. All climate indices have steep slopes for the far future (2066-2100) compared to the near future (2031-2065). Yet the variability among CMIP6 models in near future is high compared to the far future for cold indices.
Surface temperatures are generally higher in cities than in rural surroundings. This phenomenon, known as Surface Urban Heat Island (SUHI), increases the risk of heat-related human illnesses and mortality. Past global studies analysed this phenomenon aggregated at city scale or over seasonal and annual time periods, while human impacts strongly depend on shorter term heat stress experienced locally. Here we develop a global longterm high-resolution dataset of daytime SUHI, offering an insight into the space-time variability of the urban-rural temperature differences which is unprecedented at global scale. Our results show that across urban areas worldwide over the period 2003-2020, 3-day SUHI extremes are on average more than twice as high as the warm-season median SUHI, with local exceedances up to 10 K. Over this period, SUHI extremes have increased more rapidly than warm-season medians, and averaged worldwide are now 1.04 K or 31% higher compared to 2003. This can be linked with increasing urbanisation, more frequent heatwaves, and greening of the earth, processes that are all expected to continue in the coming decades. Within many cities there are hotspots where extreme SUHI intensity is 10-15 K higher compared to relatively cooler city parts. Given the limited human adaptability to heat stress, our results advocate for mitigation strategies targeted at reducing SUHI extremes in the most vulnerable and exposed city neighbourhoods.
Over the past decades, the world has experienced increasing heatwave intensity, frequency, and duration. This trend is projected to increase into the future with climate change. At the same time, the global population is also projected to increase, largely in the world’s cities. This urban growth is associated with increased heat in the urban core, compared to surrounding areas, exposing residents to both higher temperatures and more intense heatwaves than their rural counterparts. Regional studies suggest that Asia and Africa will be significantly affected. How many people may be exposed to levels of extreme heat events in the future remains unclear. Identifying the range in number of potentially exposed populations and where the vulnerable are located can help planners prioritize adaption efforts. We project the ranges of population exposed to heatwaves at varying levels to 2,100 for three future periods of time (2010-2039, 2040-2069, 2070-2099) using the Shared Socio-Economic Pathways (SSPs) and the Representative Concentration Pathways (RCPs). We hypothesize that the largest populations that will be exposed to very warm heatwaves are located in Asia and Africa. Our projections represent the warmest heatwaves for 15 days during these three periods. By the 2070-2099 period, the exposure levels to extreme heatwaves (>42 degrees) exceed 3.5 billion, under the sustainability scenario (RCP2.6-SSP1). The number of those exposed in cities climbs with greater projected climate change. The largest shares of the exposed populations are located in Southern Asia and tropical countries Western and Central Africa. While this research demonstrates the importance of this type of climate change event, urban decision-makers are only recently developing policies to address heat. There is an urgent need for further research in this area.
Climate change lead to more intense, higher frequent and prolonged heat extremes. Under-standing the spatial pattern of heatwave is vital for providing the corresponding weather services, making climate change adaptation strategies and heat-health actions. In this study, we present an approach to estimate the heatwave spatial patterns by utilizing the WUDAPT Level 0 data and machine learning. The analysis is based on two years (2009 and 2016) of air temperature data from 86 meteorological monitoring stations in Guangdong province of China, a subtropical region with frequent hot and sultry weather in summer. First, heatwave conditions were quantified by calculating the number of hot days and frequency of heatwave events in each year and used as the response variables. Then, random forest models were built by using a geospatial dataset con-sisting of WUDAPT and urban canopy parameters (UCP) as predictor variables. Based on the resultant models, spatial patterns of heatwave were estimated and mapped at 100 m spatial -resolution. The results show that this approach is able to estimate heatwave spatial patterns using open data and inform urban policy and decision-making. The study is also a new perspective and a feasible pathway of utilizing WUDPAT Level 0 product to facilitate urban environment applications.
Urban overheating, driven by global climate change and urban development, is a major contemporary challenge that substantially impacts urban livability and sustainability. Overheating represents a multifaceted threat to the well-being, performance, and health of individuals as well as the energy efficiency and economy of cities, and it is influenced by complex interactions between building, city, and global scale climates. In recent decades, extensive discipline-specific research has characterized urban heat and assessed its implications on human life, including ongoing efforts to bridge neighboring disciplines. The research horizon now encompasses complex problems involving a wide range of disciplines, and therefore comprehensive and integrated assessments are needed that address such interdisciplinarity. Here, our objective is to go beyond a review of existing literature and instead provide a broad overview and integrated assessments of urban overheating, defining holistic pathways for addressing the impacts on human life. We (a) detail the characterization of heat hazards and exposure across different scales and in various disciplines, (b) identify individual sensitivities to urban overheating that increase vulnerability and cause adverse impacts in different populations, (c) elaborate on adaptive capacities that individuals and cities can adopt, (d) document the impacts of urban overheating on health and energy, and (e) discuss frontiers of theoretical and applied urban climatology, built environment design, and governance toward reduction of heat exposure and vulnerability at various scales. The most critical challenges in future research and application are identified, targeting both the gaps and the need for greater integration in overheating assessments.
Extreme heat, the deadliest summer weather-related hazard in the USA, is projected to increase in intensity, duration, frequency, and magnitude, especially in urban areas that account for 80% of the population. Spatial visualization and representation are crucial in establishing the hotspots of vulnerability to the heat hazard. However, despite the progress in the science of vulnerability, there lacks a systematic and consistent conceptual framework. The quantification of variables is unchecked, resulting in subjective decisions regarding the weighting of variables, selection of indicators, and the suitability of the proxies. Moreover, contradicting approaches generate disparate outputs such as; inductive versus deductive, area-based versus population-based, and raster versus vector designs. The qualitative approach, meant to provide supplementary data, is often ignored. This review provides a perspective of the lacunae in the existing literature and builds on these gaps to derive a conceptual framework towards harmonizing theoretical and statistical relationships. The framework is anchored on the longitudinal study approach as the socioeconomic, biophysical, and geodemographic dimensions have an inherent temporal variance. The review calls for a precise and accurate depiction of heat vulnerability in urban areas to inform targeted adaptation and mitigation measures and the long term projection of coupled systems behavior.
When inferring on the magnitude of future heat-related mortality due to climate change, human adaptation to heat should be accounted for. We model long-term changes in minimum mortality temperatures (MMT), a well-established metric denoting the lowest risk of heat-related mortality, as a function of climate change and socio-economic progress across 3820 cities. Depending on the combination of climate trajectories and socio-economic pathways evaluated, by 2100 the risk to human health is expected to decline in 60% to 80% of the cities against contemporary conditions. This is caused by an average global increase in MMTs driven by long-term human acclimatisation to future climatic conditions and economic development of countries. While our adaptation model suggests that negative effects on health from global warming can broadly be kept in check, the trade-offs are highly contingent to the scenario path and location-specific. For high-forcing climate scenarios (e.g. RCP8.5) the maintenance of uninterrupted high economic growth by 2100 is a hard requirement to increase MMTs and level-off the negative health effects from additional scenario-driven heat exposure. Choosing a 2 °C-compatible climate trajectory alleviates the dependence on fast growth, leaving room for a sustainable economy, and leads to higher reductions of mortality risk.
The absence of vegetation in urban areas contributes to the establishment of the urban heat island, markedly increasing thermal stress for residents, driving morbidity and mortality. Mitigation strategies are, therefore, needed to reduce urban heat, particularly against a background of urbanization, anthropogenic warming and increasing frequency and intensity of heatwaves. In this Review, we evaluate the potential of green infrastructure as a mitigation strategy, focusing on greenery on the ground (parks) and greenery on buildings (green roofs and green walls). Green infrastructure acts to cool the urban environment through shade provision and evapotranspiration. Typically, greenery on the ground reduces peak surface temperature by 2-9 degrees C, while green roofs and green walls reduce surface temperature by similar to 17 degrees C, also providing added thermal insulation for the building envelope. However, the cooling potential varies markedly, depending on the scale of interest (city or building level), greenery extent (park shape and size), plant selection and plant placement. Urban planners must, therefore, optimize design to maximize mitigation benefits, for example, by interspersing parks throughout a city, allocating more trees than lawn space and using multiple strategies in areas where most cooling is required. To do so, improved translation of scientific understanding to practical design guidelines is needed.
Climate change causes global effects on multiple levels. The anthropogenic input of greenhouse gases increases the atmospheric mean temperature. It furthermore leads to a higher probability of extreme weather events (e.g., heat waves, floods) and thus strongly impacts the habitats of humans, animals, and plants. Against this background, research and innovation activities are increasingly focusing on potential health-related aspects and feasible adaptation and mitigation strategies. Progressing urbanization and demographic change paired with the climate change-induced heat island effect exposes humans living in urban habitats to increasing health risks. By employing scientometric methods, this scoping study provides a systematic bird’s eye view on the epistemic landscapes of climate change, its health-related effects, and possible technological and nature-based interventions and strategies in order to make urban areas climate proof. Based on a literature corpus consisting of 2614 research articles collected in SCOPUS, we applied network-based analysis and visualization techniques to map the different scientific communities, discourses and their interrelations. From a public health perspective, the results demonstrate the range of either direct or indirect health effects of climate change. Furthermore, the results indicate that a public health-related scientific discourse is converging with an urban planning and building science driven discourse oriented towards urban blue and green infrastructure. We conclude that this development might mirror the socio-political demand to tackle emerging climate change-induced challenges by transgressing disciplinary boundaries.
BACKGROUND: In hot weather, electric fans can potentially provide effective cooling for people, with lower greenhouse gas emissions and cost than air conditioning. However, international public health organisations regularly discourage fan use in temperatures higher than 35°C, despite little evidence. We aimed to determine humidity-dependent temperature thresholds at which electric fans would become detrimental in different age groups. METHODS: We used biophysical modelling to determine the upper humidity-dependent temperature thresholds at which fan use would become detrimental (ie, worsen heat stress) for healthy young adults (aged 18-40 years), healthy older adults (aged ≥65 years), and older adults taking anticholinergic medication. We also obtained hourly environmental data for the period Jan 1, 2007, to Dec 31, 2019, for 108 populous cities to determine the number of days fan use would be effective for cooling, standardised to a 31-day hot weather month. We established simplified temperature thresholds for future fan use recommendations on the basis of temperatures below which fan use would never have been detrimental between Jan 1, 2007, and Dec 31, 2019, across all prevailing levels of ambient humidity. FINDINGS: According to our model, fan use would have been beneficial on 30·0 (96·6%) of 31 hot weather days for healthy young adults and 29·4 (94·9%) of 31 hot weather days for both older adults and older adults taking anticholinergic medication between Jan 1, 2007, and Dec 31, 2019. Adherence to the current WHO recommendation of fan use below temperatures of 35°C only, fan use would have been recommended on 27·2 days (87·7%) of 31 hot weather days. According to our simplified thresholds for fan use (at temperatures <39·0°C for healthy young adults, <38·0°C for healthy older adults, and <37·0°C for older adults taking anticholinergic medication), fan use would have been recommended on 29·6 (95·5%) of 31 hot weather days in healthy young adults, 29·4 (94·8%) days in healthy older adults, and 28·8 (93·0%) days in older adults taking anticholinergic medication between Jan 1, 2007, and Dec 31, 2019. INTERPRETATION: Electric fan use, particularly for healthy young adults, would not have worsened heat stress on the majority of study days between 2007 and 2019. Our newly proposed thresholds for fan use provide simple guidelines that improve future heatwave fan use recommendations. FUNDING: None.
The ambition to develop sustainable and healthy cities requires city-specific policy and practice founded on a multidisciplinary evidence base, including projections of human-induced climate change. A cascade of climate models of increasing complexity and resolution is reviewed, which provides the basis for constructing climate projections-from global climate models with a typical horizontal resolution of a few hundred kilometres, through regional climate models at 12-50 km to convection-permitting models at 1 km resolution that permit the representation of urban induced climates. Different approaches to modelling the urban heat island (UHI) are also reviewed-focusing on how climate model outputs can be adjusted and coupled with urban canopy models to better represent UHI intensity, its impacts and variability. The latter can be due to changes induced by urbanisation or to climate change itself. City interventions such as greater use of green infrastructure also have an effect on the UHI and can help to reduce adverse health impacts such as heat stress and the mortality associated with increasing heat. Examples for the Complex Urban Systems for Sustainability and Health (CUSSH) partner cities of London, Rennes, Kisumu, Nairobi, Beijing and Ningbo illustrate how cities could potentially make use of more detailed models and projections to develop and evaluate policies and practices targeted at their specific environmental and health priorities. PRACTICE RELEVANCE: Large-scale climate projections for the coming decades show robust trends in rising air temperatures, including more warm days and nights, and longer/more intense warm spells and heatwaves. This paper describes how more complex and higher resolution regional climate and urban canopy models can be combined with the aim of better understanding and quantifying how these larger scale patterns of change may be modified at the city or finer scale. These modifications may arise due to urbanisation and effects such as the UHI, as well as city interventions such as the greater use of grey and green infrastructures.There is potential danger in generalising from one city to another-under certain conditions some cities may experience an urban cool island, or little future intensification of the UHI, for example. City-specific, tailored climate projections combined with tailored health impact models contribute to an evidence base that supports built environment professionals, urban planners and policymakers to ensure designs for buildings and urban areas are fit for future climates.
Urban heat island and regional climate change raise the ambient temperature in cities and increase the levels of heat related mortality. Higher albedo values lower the ambient temperature and reduce the impact of excess urban heat on health. The present work reviews and analyses fourteen detailed studies investigating the impact of increased urban albedo on the ambient temperature and heat related mortality. It is found that the real magnitude of the afternoon temperature drop caused by the albedo increase is close to 0.09C per 0.1 rise of the albedo, and it is highly determined by the specific climatic, landscape and layout characteristic of cities. A statistically significant association of the temperature drop with the albedo increase, the greenery and street ratio in cities is found. It is observed that the levels of heat related mortality increase significantly as a function of the population size of the cities and the local poverty levels, Increased urban albedo is found to reduce heat related mortality between 0.1 and 4 deaths per day, corresponding to an average decrease of deaths close to 19.8% per degree of temperature drop, or 1.8% per 0.1 increase of the albedo. Mortality drop is found to be in statistically significant association with the initial heat related mortality levels, albedo increase and socioeconomic parameters like the local poverty levels. Accurate parametric functions to predict the magnitude of the temperature drop and heat mortality reduction are developed.
Climate change and rapid urbanization increase/amplify urban heat islands (UHIs). Green infrastructure (GI) is an effective and popularly strategy used to moderate UHIs. This paper aims to better understand the progress of different GI types (urban parks, urban forests, street trees, green roofs, green walls) in mitigating UHIs, and what benefits they provide. Firstly, this paper used CiteSpace to analyze 1243 publications on the Web of Science from 1990 to 2021, then analyzed the function/regulation of ecosystem services/benefits and values of GI types in reducing UHIs. The historical review results show that research on all GI types showed rapid growth since 2013, and their GR increased rapidly. The highest-ranking keywords were urban heat island/heat island, climate/climate change/microclimate, and temperature/land surface temperature/air temperature. “Design,” “vegetation,” “quality,” and “reduction” are the top four strongest keyword bursts. The most published countries are the People’s Republic of China, USA, Australia, Germany, and Italy, and the top three institutions are the Chinese Academy of Sciences, Arizona State University, and the National University of Singapore. Landscape and Urban Planning, Building and Environment, Energy and Building, and Urban Forestry and Urban Greening are the most published journals. In urban areas, different GI types as a form of ecosystem hardware provide multiple functions (reduced land surface temperatures, lower building energy usage, improved thermal comfort and enhanced human health, reduced morbidity and mortality, etc.). GI thus provides a regulated ecosystem service to ameliorate UHIs primarily through temperature regulation and shade. At the same time, GI provides benefits and values (ecological, economic, social, and cultural) to humans and urban sustainable development. GI types determine the functions they provide, afford corresponding regulated ecosystem services, and provide benefits and values in a logical/recycle system. Overall, this review highlights the development and importance of GI, as well as the relationship of GI types and functions of regulating the ecosystem service benefits and values to mitigate UHI, and advances the study of climate change adaptation in cities.
BACKGROUND: Identifying how greenspace impacts the temperature-mortality relationship in urban environments is crucial, especially given climate change and rapid urbanization. However, the effect modification of greenspace on heat-related mortality has been typically focused on a localized area or single country. This study examined the heat-mortality relationship among different greenspace levels in a global setting. METHODS: We collected daily ambient temperature and mortality data for 452 locations in 24 countries and used Enhanced Vegetation Index (EVI) as the greenspace measurement. We used distributed lag non-linear model to estimate the heat-mortality relationship in each city and the estimates were pooled adjusting for city-specific average temperature, city-specific temperature range, city-specific population density, and gross domestic product (GDP). The effect modification of greenspace was evaluated by comparing the heat-related mortality risk for different greenspace groups (low, medium, and high), which were divided into terciles among 452 locations. FINDINGS: Cities with high greenspace value had the lowest heat-mortality relative risk of 1·19 (95% CI: 1·13, 1·25), while the heat-related relative risk was 1·46 (95% CI: 1·31, 1·62) for cities with low greenspace when comparing the 99(th) temperature and the minimum mortality temperature. A 20% increase of greenspace is associated with a 9·02% (95% CI: 8·88, 9·16) decrease in the heat-related attributable fraction, and if this association is causal (which is not within the scope of this study to assess), such a reduction could save approximately 933 excess deaths per year in 24 countries. INTERPRETATION: Our findings can inform communities on the potential health benefits of greenspaces in the urban environment and mitigation measures regarding the impacts of climate change. FUNDING: This publication was developed under Assistance Agreement No. RD83587101 awarded by the U.S. Environmental Protection Agency to Yale University. It has not been formally reviewed by EPA. The views expressed in this document are solely those of the authors and do not necessarily reflect those of the Agency. EPA does not endorse any products or commercial services mentioned in this publication. Research reported in this publication was also supported by the National Institute on Minority Health and Health Disparities of the National Institutes of Health under Award Number R01MD012769. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Also, this work has been supported by the National Research Foundation of Korea (2021R1A6A3A03038675), Medical Research Council-UK (MR/V034162/1 and MR/R013349/1), Natural Environment Research Council UK (Grant ID: NE/R009384/1), Academy of Finland (Grant ID: 310372), European Union’s Horizon 2020 Project Exhaustion (Grant ID: 820655 and 874990), Czech Science Foundation (22-24920S), Emory University’s NIEHS-funded HERCULES Center (Grant ID: P30ES019776), and Grant CEX2018-000794-S funded by MCIN/AEI/ 10.13039/501100011033 The funders had no role in the design, data collection, analysis, interpretation of results, manuscript writing, or decision to publication.
Urban areas are expanding due to rural-urban migration and due to population increases. Their resilience is being challenged due to socio-political consequences of increasingly frequent and severe storms, due to climate changes, influx of human and animal refugees and as a consequence of the COVID-19 pandemic. The authors prepared a systematic literature of ways cities can be transformed into more resilient, and sustainable regions by creatively enhancing the quality and quantity of blue and green areas in and around them. The literature review was conducted to provide holistic insights into selection, implementation monitoring, assessment, and valuation of Nature-based Solutions in diverse urban regions. The authors reviewed no fewer than 298 articles from 109 academic journals and related sources, published within 1997-2020. The focus of the articles was upon ‘nature-based’ changes that are being implemented in urban areas, globally to enhance their resilience and the ‘quality-of-life’ of humans and other species. By implementing nature-based solutions, and complimentary ‘urban wilding’ approaches, urban areas and their hinterlands are expanding their ‘blue’ and ‘green’ areas and are thereby decreasing the ‘heat-island’ effects, while improving human health by surrounding them with rich bio-diversities of locally adapted, aquatic and terrestrial plants and animals. Although, many NBS options have been documented to be beneficial, their environmental, economic and social/psychological dimensions have not been adequately quantified, especially in the context of climate changes, and with regard to COVID-19. It is essential that the benefits of NBS are quantified with easily measurable outcomes, that are readily understood by practitioners, city policy-makers and members of community organizations, based upon specific geographical and climatological contexts. This will help them accelerate implementation of NBS and wilding into their urban systems. The reviewers found that more research is needed on anticipatory learning, backcasting and community participation to help to effectively implement the appropriate NBS for improving the sustainability of urban systems. The reviewers provide guidance for urban leaders to incorporate NBS into their policies and strategies to improve urban resilience and equity and to more effectively reduce impacts of climate change, population growth and pandemics. (C) 2020 Elsevier Ltd. All rights reserved.
Water supply and wastewater systems are essential infrastructure affected by floods. Additional risk is posed in developing countries, where access to sanitation is not universal. Few studies assess the flood risk to the sanitation-health nexus. Therefore, this study aims to present a theoretical and general framework for assessing the resilience of flood-sanitation-public health nexus in urban environments, composed by risk estimation and risk management assessment. The framework was developed from a system analysis approach focusing on central supply systems. Regarding risk assessment, the main vulnerability and exposure factors identified were land use, social vulnerability, coverage of sanitation systems, occurrence of waterborne diseases, number of people affected by floods and intersection with the flood map. From the risk management assessment stage three main typologies of trade-offs and synergies were identified: urban territorial planning versus runoff control, water quality versus sanitation infrastructure and flood management policy versus social behavior.
Modelling urban inundation and its associated health implications is numerous in its many applications. Flood modelling research contains a broad wealth of material, and microbial risk assessment has gained more popularity over the last decade. However, there is still a relative lack of understanding of how the microbial risk can be quantified from urban sewer flooding. This article intends to review the literature encompassing contemporary urban flood modelling approaches. Hydrodynamic and microbial models that can be applied for quantitative microbial risk assessment will be discussed. Consequently, urban sewer flooding will be the focus. This review found that the literature contains a variety of different hazards posed by urban flooding. Yet, far fewer examples encompass microbial risk from sewer system exceedance. To date, there is no evidence of a perfect model or technique, to carry out a quantitative microbial risk assessment from hydrodynamic simulations. The literature details many different methods. We intend to detail the advantages and limitations of each method. Along similar lines, hydraulic data constitutes a large part of the uncertainty which is inherent to this research field. Many studies in the literature detail data paucity and uncertainty in input data. As such, any advancement in this discipline will very likely aid future research.
Heat exposure is a well-known health hazard, which causes several problems ranging from thermal discomfort or productivity reduction to the aggravation of existing illnesses and death. Climate projections foresee an increase in the frequency and intensity of heat-related impacts on human health. To reduce these climate risks, governments need a better understanding of not only the scale and the factors affecting those risks, but also how to prepare and protect the city and citizens against these risks and prevent them through effective policy making. Therefore, climate adaptation decisions need to be made in complex systems with manifold uncertainties. In response to these deep uncertainties, different planning approaches have been developed to assist policymakers in decision making. This paper is focused on one of the dynamic adaptive policy planning approaches: the adaptation pathway. This approach allows designing alternative feasible plans that are flexible and can respond when new information appears or when conditions in the environment change. This paper presents a structured methodology for designing adaptation pathways. The work describes a high-level adaptation pathway covering heatwave impacts on productivity and health at city level in Antwerp to ensure the city adapts to future conditions. Lastly, a summary is provided of the lessons learned and the challenges of this approach are discussed.
This review highlights two intersecting environmental phenomena that have significantly impacted the Tokyo Summer Olympic and Paralympic Games: infectious disease outbreaks and anthropogenic climate change. Following systematic searches of five databases and the gray literature, 15 studies were identified that addressed infectious disease and climate-related health risks associated with the Summer Games and similar sports mega-events. Over two decades, infectious disease surveillance at the Summer Games has identified low-level threats from vaccine-preventable illnesses and respiratory conditions. However, the COVID-19 pandemic and expansion of vector-borne diseases represent emerging and existential challenges for cities that host mass gathering sports competitions due to the absence of effective vaccines. Ongoing threats from heat injury among athletes and spectators have also been identified at international sports events from Asia to North America due to a confluence of rising Summer temperatures, urban heat island effects and venue crowding. Projections for the Tokyo Games and beyond suggest that heat injury risks are reaching a dangerous tipping point, which will necessitate relocation or mitigation with long-format and endurance events. Without systematic change to its format or staging location, the Summer Games have the potential to drive deleterious health outcomes for athletes, spectators and host communities.
BACKGROUND: Mosquito-borne diseases are expanding their range, and re-emerging in areas where they had subsided for decades. The extent to which climate change influences the transmission suitability and population at risk of mosquito-borne diseases across different altitudes and population densities has not been investigated. The aim of this study was to quantify the extent to which climate change will influence the length of the transmission season and estimate the population at risk of mosquito-borne diseases in the future, given different population densities across an altitudinal gradient. METHODS: Using a multi-model multi-scenario framework, we estimated changes in the length of the transmission season and global population at risk of malaria and dengue for different altitudes and population densities for the period 1951-99. We generated projections from six mosquito-borne disease models, driven by four global circulation models, using four representative concentration pathways, and three shared socioeconomic pathways. FINDINGS: We show that malaria suitability will increase by 1·6 additional months (mean 0·5, SE 0·03) in tropical highlands in the African region, the Eastern Mediterranean region, and the region of the Americas. Dengue suitability will increase in lowlands in the Western Pacific region and the Eastern Mediterranean region by 4·0 additional months (mean 1·7, SE 0·2). Increases in the climatic suitability of both diseases will be greater in rural areas than in urban areas. The epidemic belt for both diseases will expand towards temperate areas. The population at risk of both diseases might increase by up to 4·7 additional billion people by 2070 relative to 1970-99, particularly in lowlands and urban areas. INTERPRETATION: Rising global mean temperature will increase the climatic suitability of both diseases particularly in already endemic areas. The predicted expansion towards higher altitudes and temperate regions suggests that outbreaks can occur in areas where people might be immunologically naive and public health systems unprepared. The population at risk of malaria and dengue will be higher in densely populated urban areas in the WHO African region, South-East Asia region, and the region of the Americas, although we did not account for urban-heat island effects, which can further alter the risk of disease transmission. FUNDING: UK Space Agency, Royal Society, UK National Institute for Health Research, and Swedish Research Council.
Background: The rapid circulation of arboviruses in the human population has been linked with changes in climatic, environmental, and socio-economic conditions. These changes are known to alter the transmission cycles of arboviruses involving the anthropophilic vectors and thus facilitate an extensive geographical distribution of medically important arboviral diseases, thereby posing a significant health threat. Using our current understanding and assessment of relevant literature, this review aimed to understand the underlying factors promoting the spread of arboviruses and how the three most renowned interdisciplinary and holistic approaches to health such as One Health, Eco-Health, and Planetary Health can be a panacea for control of arboviruses. Methods: A comprehensive structured search of relevant databases such as Medline, PubMed, WHO, Scopus, Science Direct, DOAJ, AJOL, and Google Scholar was conducted to identify recent articles on arboviruses and holistic approaches to health using the keywords including arboviral diseases, arbovirus vectors, arboviral infections, epidemiology of arboviruses, holistic approaches, One Health, Eco-Health, and Planetary Health. Results: Changes in climatic factors like temperature, humidity, and precipitation support the growth, breeding, and fecundity of arthropod vectors transmitting the arboviral diseases. Increased human migration and urbanization due to socio-economic factors play an important role in population increase leading to the rapid geographical distribution of arthropod vectors and transmission of arboviral diseases. Medical factors like misdiagnosis and misclassification also contribute to the spread of arboviruses. Conclusion: This review highlights two important findings: First, climatic, environmental, socio-economic, and medical factors influence the constant distributions of arthropod vectors. Second, either of the three holistic approaches or a combination of any two can be adopted on arboviral disease control. Our findings underline the need for holistic approaches as the best strategy to mitigating and controlling the emerging and reemerging arboviruses.
The twenty-first century has witnessed a wave of severe infectious disease outbreaks, not least the COVID-19 pandemic, which has had a devastating impact on lives and livelihoods around the globe. The 2003 severe acute respiratory syndrome coronavirus outbreak, the 2009 swine flu pandemic, the 2012 Middle East respiratory syndrome coronavirus outbreak, the 2013-2016 Ebola virus disease epidemic in West Africa and the 2015 Zika virus disease epidemic all resulted in substantial morbidity and mortality while spreading across borders to infect people in multiple countries. At the same time, the past few decades have ushered in an unprecedented era of technological, demographic and climatic change: airline flights have doubled since 2000, since 2007 more people live in urban areas than rural areas, population numbers continue to climb and climate change presents an escalating threat to society. In this Review, we consider the extent to which these recent global changes have increased the risk of infectious disease outbreaks, even as improved sanitation and access to health care have resulted in considerable progress worldwide.
The policies of response to and prevention of heat waves in France in 2003 and in South Korea in 2018 were compared and reviewed to see how public health policy orientation was being expanded in connection with urban and social policies. The statistics of the patients with heat illness and resulted death in France in 2003 and South Korea in 2018 were analyzed. The results and limitations of the French and Korean responses to heat waves were compared and discussed. The heat wave in France in 2003 caused an excess death of 14,802. The 2018 heat wave in South Korea resulted in 4,526 cases of heat illness and 48 deaths. France’s National Heat wave Plan established in 2004 introduced the warning system and strengthened support for the vulnerable. The heat wave in South Korea in 2018 revealed the success and limitations of the national measures that have been gradually implemented since the mid-2000s. Both France and South Korea are making efforts in preventing heat illness and managing health risk through the warning systems, providing public and social support for the vulnerable, and expanding urban infrastructure. Paris puts priority on the long-term prevention of heat wave, in the wider context of climate change response, while Seoul shows a relatively strong point in immediate infrastructural expansion. In order to respond to the climate crisis and the following health risk, public health policies need to be contrived with deeper connection with urban social policies for sustainable development.
Climate change is one of the biggest health threats facing humanity and can directly affect human health through heat waves. This study aims to evaluate excess deaths during heat waves between the summer months of 2004 and 2017 in Istanbul and to determine a definition of heat waves that can be used in the development of an early warning system, a part of prospective urban heat-health action plans. In this study, heat waves were determined using the Excess Heat Factor, an index based on a three-day-averaged daily mean temperature. The death rates during heat waves and non-heat wave days of the summer months were compared with a Z test of the difference of natural logarithms. Thirty heat waves were recorded in Istanbul during the summer months of 2004-2017. In 67% of the heat waves, the death rate was significantly higher than the reference period and 4281 excess deaths were recorded. The mortality risk was especially higher during heat waves of higher intensity. The study showed an excess risk of mortality during heat waves in Istanbul, and the findings suggest that the Excess Heat Factor could be an appropriate tool for an early warning system in Istanbul.
The effects of climate change on the built environment represents an important research challenge. Today, green roofs (GRs) represent a viable solution for enhancing energy and urban resilience in the face of climate change, as they can have a positive impact on the building’s indoor thermal comfort and energy demand, as well as inducing various environmental benefits (easing urban heat island effects, improving the management of runoff water, reducing air pollution, etc.). Thus, it is important to be able to assess their effectiveness, both today and under future climate conditions, in order to evaluate whether they can also provide a valid long-term solution. In this paper, a simulation approach is proposed to evaluate the energy and indoor-comfort efficacy of GRs installed on a cluster of buildings with respect to climate change and demographic growth. To illustrate the proposed methodology, it has been applied to two European urban environments characterized by very different climatic conditions (Esch-sur-Alzette in Luxembourg and Palermo in Italy) considering their behaviour over a period of 60 years (2020, 2050, 2080). Results showed that, with respect to standard existing roofs (i.e., without the presence of green coverage), and considering the rising temperatures due to climate change, during cooling seasons GRs enabled significant energy savings (ranging from 20% to 50% for Esch-sur-Alzette and from 3% to 15% for Palermo), improvement of the indoor comfort (reduction of the average predicted mean votes – PMVs) and attenuation of the ceiling temperatures (2-5 degrees C for both contexts) of the buildings’ top floors.
The study assesses the extent to which public health is integrated into European national and urban climate change adaptation policy and planning. We analyse national adaptation documents from the 27 European Union member states and interview city-level experts (n = 17) on the integration of three categories of adaptation efforts: general efforts to minimize health impacts related to climate change, targeted efforts to enhance resilience in health systems, and supportive efforts to foster the potential of the first two categories. At a national level, general efforts to address vector-borne diseases and heat-related illness are covered comprehensively, whereas efforts addressing several climate-related health risks are neglected (e.g. water-borne diseases, injuries from extreme weather and cardiopulmonary health) or overlooked (e.g. malnutrition and mental health). Targeted efforts to inform policy decisions, such as carrying out research, risk monitoring and assessments, are often described in detail, but efforts to manage day-to-day health care delivery and emergency situations receive little attention. At the urban level, health issues receive less attention in climate adaptation policy and planning. If health topics are included, they are often described as indirect benefits of adaptation efforts in other sectors and not perceived as the priority of the involved authorities. This effectively means that general and targeted efforts are the responsibility of other sectoral departments, while supportive efforts are the responsibility of the national government or external organizations. As a result, at an urban level, climate-related health system adaptation is not a policy aim in its own right, and many potentially high health risks are being ignored. In order for health risks to be better integrated into adaptation policy and planning, it is critical to interconnect national and urban levels, reduce sectoral thinking and welcome external expertize and facilitate large-scale data collection and sharing of health and climate indicators.Key policy insightsWe recommend focussing on cooperatively drafting strategies for integrating health issues into climate policy and planning with stakeholders at the national and urban levels, in different policy sectors and in society.Policy planners can build on the strengths of adaptation documents from other countries or cities and take note of any weaknesses.We advocate to foster co-benefits for health and climate action of various adaptation measures (e.g. by promoting active mobility and urban greenery, health impacts related to heat, (mental and physical) stress and air pollution are reduced).Large-scale data collection and sharing of health and climate indicators should be facilitated to support learning and pro-active decision-making.
Air pollution poses a major threat to human health. Far from unidimensional, air pollution is multifaceted, but quasi-experimental studies have been struggling to grasp the consequences of the multiple hazards. By selecting optimal instruments from a novel and large set of altitude-weather instrumental variables, we disentangle the impact of five air pollutants in a comprehensive assessment of their short-term health impact in the largest urban areas of France over 2010-2015. We find that higher levels of at least two air pollutants, ozone and sulfur dioxide, lead to more respiratory-related emergency admissions. Children and elderly are mostly affected. Carbon monoxide increases emergency admissions for cardiovascular diseases while particulate matter is found responsible for increasing the cardiovascular-related mortality rate, and sulfur dioxide the respiratory-related mortality rate. Assuming a five air pollutants context, we show that an analyst who ignored the presence of interrelations between air pollutants would have reached partially false conclusions.
Objectives: The rapid growth in population, urbanization, and industrialization reduces the natural green space environment and increases air pollution on the planet. The green space environment minimizes air pollutants, and swift climate changes and provides fresh and clean air. This study investigates the prevalence of diabetes mellitus in environmentally highly green and less green countries in Europe. Subjects and methods: Based on the Environmental Performance Index (EPI) score, which rates a country’s environment, 43 European countries with 760 million people were selected. The EPI score was recorded from the USA’s Environmental Performance Index (EPI) website. 60% of the EPI score is based on seven categories related to ecosystem vitality: biodiversity and habitat, ecosystem, fisheries, climate change, pollution emissions, agriculture, and water resources. 40% of the score is based on four categories related to environmental health: air quality, sanitation and drinking water, heavy metals, and waste management system. The prevalence of diabetes mellitus in all 43 European countries was obtained from the International Diabetes Federation (IDF). The European countries’ populations were obtained from the World Bank. We divided the countries into three groups based on each country’s EPI score. The 11 countries with an EPI score of more than 75 were classified as highly green space, 24 countries with an EPI score of 50-75 were classified as moderately green space, and 8 countries with an EPI score of less than 50 were classified as less green space environment countries in Europe. Results: The mean prevalence of diabetes mellitus for highly green space environment countries was 7.49 +/- 1.53%; moderately green space countries were 8.98 +/- 2.38%, and for less green space environment countries was 9.79 +/- 3.05%. In countries with less green space (i.e., environment, EPI scores less than 50), the prevalence of DM was significantly higher than in green space countries with EPI scores of more than 75 (p = 0.041). The results revealed a negative correlation between the green space environment (EPI Score) and the prevalence of diabetes mellitus. Conclusions: The prevalence of diabetes mellitus is significantly reduced in environmentally high green space countries than in low green space countries in Europe. This means that countries with environmentally sustainable environment policies have less diabetes. It is suggested to establish strategies to keep the living environment green and clean to minimize air pollution and fight against diabetes mellitus. (C) 2022 The Author(s). Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
BACKGROUND: Despite mounting evidence, there is uncertainty on the impact of the interplay between weather and pollution features on the risk of acute cerebrovascular events (CVE). We aimed at appraising role of weather and pollution on the daily risk of CVE. METHODS: Anonymized data from a hub CVE center in a large metropolitan area were collected and analyzed according to weather (temperature, pressure, humidity, and rainfall) and pollution (carbon monoxide [CO], nitrogen dioxide [NO2], nitrogen oxides [NOX], ozone [O3], and particulate matter [PM]) on the same and the preceding days. Poisson regression and time series analyses were used to appraise the association between environmental features and daily CVE, distinguishing also several subtypes of events. RESULTS: We included a total of 2534 days, with 1363 days having ≥1 CVE, from 2012 to 2017. Average daily rate was 1.56 (95% confidence interval: 1.49; 1.63) for CVE, with other event rates ranging between 1.42 for stroke and 0.01 for ruptured intracranial aneurysm. Significant associations were found between CVE and temperature, pressure, CO, NO2, NOX, O3, and PM <10 µm (all P<0.05), whereas less stringent associations were found for humidity, rainfall, and PM <2.5 µm. Time series analysis exploring lag suggested that associations were stronger at same-day analysis (lag 0), but even environmental features predating several days or weeks were significantly associated with events. Multivariable analysis suggested that CO (point estimate 1.362 [1.011; 1.836], P=0.042) and NO2 (1.011 [1.005; 1.016], P<0.001) were the strongest independent predictors of CVE. CONCLUSIONS: Environmental features are significantly associated with CVE, even several days before the actual event. Levels of CO and NO2 can be potentially leveraged for population-level interventions to reduce the burden of CVE.
Urban greening is an effective mitigation option for climate change in urban areas. In this contribution, a European Union (EU)-wide assessment is presented to quantify the benefits of urban greening in terms of availability of green water, reduction of cooling costs and CO(2) sequestration from the atmosphere, for different climatic scenarios. Results show that greening of 35% of the EU’s urban surface (i.e. more than 26,000 km(2)) would avoid up to 55.8 Mtons year(-1) CO(2) equivalent of greenhouse gas emissions, reducing energy demand for the cooling of buildings in summer by up to 92 TWh per year, with a net present value (NPV) of more than 364 billion Euro. It would also transpire about 10 km(3) year(-1) of rain water, turning into “green” water about 17.5% of the “blue” water that is now urban runoff, helping reduce pollution of the receiving water bodies and urban flooding. The greening of urban surfaces would decrease their summer temperature by 2.5-6 °C, with a mitigation of the urban heat island effect estimated to have a NPV of 221 billion Euro over a period of 40 years. The monetized benefits cover less than half of the estimated costs of greening, having a NPV of 1323 billion Euro on the same period. Net of the monetized benefits, the cost of greening 26,000 km(2) of urban surfaces in Europe is estimated around 60 Euro year(-1) per European urban resident. The additional benefits of urban greening related to biodiversity, water quality, health, wellbeing and other aspects, although not monetized in this study, might be worth such extra cost. When this is the case, urban greening represents a multifunctional, no-regret, cost-effective solution.
The data presented in this article is part in essence of a more extensive dataset aimed at evaluating patterns of change in the temperature-mortality relationship on population health in the city of Valencia, Spain on population health in the city of Valencia, Spain. The complete dataset was used in the framework of the European multi-city project PHASE (Public Health Adaptation Strategies to Extreme weather events) [1]. The data includes daily counts of all-cause mortality, excluding external causes and cardiovascular and respiratory diseases. All-cause mortality is also classified by gender and age groups. Besides temperature, we included other meteorological variables and air pollutants from the PHASE dataset, as well as influenza epidemics. The variable Saharan dust events was also added. All these data were collected from public Governmental data repositories accessible under request. The dataset of this article provides a basis for comparison with similar models for time-series regression, allowing researchers to integrate additional model components without duplication of effort.
We aimed to investigate the relation between air pollution and the number of daily hospitalizations due to pneumonia, asthma, bronchitis in children aged 0-18 in Bursa city of Turkey, between the years 2013-2018. The daily values of air pollutants (PM10, SO2, NO2, NOx, CO, and O3) from 2013 until 2018, were obtained. Adjusted Quasi-Poisson regression models including distributed lags, controlled for climate variables were used for data analysis. Increases in SO2, ozone, PMs, and nitrogen oxides were associated with pneumonia hospitalizations, increases in SO2 NOx and PMs were associated with asthma hospitalizations, and increases in SO2 and ozone were associated with bronchitis hospitalizations. Male hospitalization was related with SO2, ozone, and NOx; while female hospitalization was only related with SO2. This study showed that short-term exposure to air pollution is associated with an increased risk of pneumonia, asthma, and bronchitis hospitalization among children in Bursa.
Greenhouse gases emissions resulting from the combustion of fossil fuels are worsening air quality and affecting the climate system. While climate change impacts on meteorological variables affects air quality by altering the concentration and distribution of pollutants, air pollution significantly influences the climate, leading to negative impacts on human health. Due to the combination of high temperatures, air pollution, and high population density, cities are particularly vulnerable to climate change impacts. The planning and design of public spaces aimed at climate change mitigation and adaptation can result in multiple co-benefits for human health, while reducing social inequalities. To address the major research gaps in the communication between health and planning experts, and the lack of capacity among public sectors and policy makers, it is necessary to promote capacity building and knowledge sharing between the planning and health sectors. The purpose of this article is to develop preliminary recommendations for a process that allows a comprehensive assessment of the interlinkages between climate and health, social, environmental, and economic vulnerabilities, and the quality of the urban spaces, to support local governments, policymakers, and education institutions in making informed decisions for public spaces. The methods applied were a literature review and interviews with experts.
The European Union is significantly investing in the Green Deal that introduces measures to guide Member States to face sustainability and health challenges, especially employing Nature-Based Solutions (NBS) in urban contexts. National governments need to develop appropriate strategies to coordinate local projects, face multiple challenges, and maximize NBS effectiveness. This paper aims to introduce a replicable methodology to integrate NBS into a multi-scale planning process to maximize their cost-benefits. Using Italy as a case study, we mapped three environmental challenges nationwide related to climate change and air pollution, identifying spatial groups of their co-occurrences. These groups serve as functional areas where 24 NBS were ranked for their ecosystem services supply and land cover. The results show eight different spatial groups, with 6% of the national territory showing no challenge, with 42% showing multiple challenges combined simultaneously. Seven NBS were high-performing in all groups: five implementable in permeable land covers (urban forests, infiltration basins, green corridors, large parks, heritage gardens), and two in impervious ones (intensive, semi-intensive green roofs). This work provides a strategic vision at the national scale to quantify and orient budget allocation, while on a municipal scale, the NBS ranking acts as a guideline for specific planning activities based on local issues.
To address the inter-connected climate and biodiversity crises, it is crucial to understand how multifunctional urban green infrastructure (UGI) is perceived to contribute to carbon neutrality, biodiversity, human well-being, and justice outcomes in cities. We explore how urban residents, including youth, associate carbon-related meanings with multifunctional UGI and how these meanings relate to co-benefits to biodiversity, well-being, and broader sustainability outcomes. Our findings are based on a survey distributed among urban residents of Helsinki, Finland (n = 487) and reveal how carbon-related meanings of UGI manifest at different levels of abstraction, agency, and scale, and incorporate community values and concerns attributed to the planning, features, functions, and transformational dimensions of UGI. Core carbon-related meanings of UGI emphasize either actions towards sustainability, carbon neutrality, biodiversity, or unfamiliarity towards such meanings. Perceived justice concerns and the socio-demographic contexts of the respondents covaried with carbon-related meanings associated with UGI. The results illustrate community perceptions of how it is not only possible, but rather expected, that multifunctional UGI is harnessed to tackle climate change, human well-being, and biodiversity loss in cities. Challenges for implementing the carbon-related benefits of UGI include navigating the different expectations placed on UGI and including residents with diverse socio-economic backgrounds during the process. Our findings contribute to a holistic understanding of how multifunctional UGI can help bridge policy agendas related to carbon neutrality, biodiversity protection, and human well-being that cities can implement when aiming for sustainable, just, and socially acceptable transitions towards a good Anthropocene.
Cities are facing the challenges of climate change. The application of nature-based solutions (NBS) to the urban structure is often mentioned in climate change adaptation strategies. In an effort to ensure the greatest possible well-being of citizens in the form of environmentally positive elements, the opinions of citizens are forgotten. This paper presents the results of research focusing on the feelings of unsafety associated with the application of NBS elements directly into the urban structure. In two pilot areas (Ostrava (CZ) and the part of Upper Silesian agglomeration (PL)) the feelings of the inhabitants and the possible feeling of fear or danger in the application of NBS were investigated. In Ostrava, a questionnaire survey was conducted in relation to specific elements of the NBS without discussion of specific locations. In the Upper Silesian agglomeration, residents’ feelings about specific NBS were surveyed at specific locations using guided interviews. Both approaches resulted in the identification of elements of concern. Respondents who discussed a specific location had a better understanding of the urban context and worried less. The two approaches demonstrated the need to communicate with residents before finalizing the design of a particular public space and the desirability of discussing site-specific issues with citizens.
Landslides are the most frequent and diffuse natural hazards in Italy causing the greatest number of fatalities and damage to urban areas. The integration of natural hazard information and social media data could improve warning systems to enhance the awareness of disaster managers and citizens about emergency events. The news about landslide events in newspapers or crowdsourcing platforms allows fast observation, surveying and classification. Currently, few studies have been produced on the combination of social media data and traditional sensors. This gap indicates that it is unclear how their integration can effectively provide emergency managers with appropriate knowledge. In this work, rainfall, human lives, and earmarked fund data sources were correlated to “landslide news”. Analysis was applied to obtain information about temporal (2010-2019) and spatial (regional and warning hydrological zone scale) distribution. The temporal distribution of the data shows a continuous increase from 2015 until 2019 for both landslide and rainfall events. The number of people involved and the amount of earmarked funds do not exhibit any clear trend. The spatial distribution displays good correlation between “landslide news”, traditional sensors (e.g., pluviometers) and possible effects in term of fatalities. In addition, the cost of soil protection, in monetary terms, indicates the effects of events.
The consequences of climate change are becoming increasingly evident and highlight the important interdependence between the well-being of people and ecosystems. Although climate change is a global phenomenon, its causes and consequences vary dramatically across territories and population groups. Among settings particularly susceptible to health impacts from climate change are cities with a Mediterranean climate. Here, impacts will put additional pressure on already-stressed ecosystems and vulnerable economies and societies, increasing health inequalities. Therefore, this article presents and discusses a conceptual framework for understanding the complex relationship between climate change and health in the context of cities with Mediterranean climate from a social and climate justice approach. The different elements that integrate the conceptual framework are: (1) the determinants of climate change; (2) its environmental and social consequences; (3) its direct and indirect impacts on health; and (4) the role of mitigation and adaptation policies. The model places special emphasis on the associated social and health inequalities through (1) the recognition of the role of systems of privilege and oppression; (2) the distinction between structural and intermediate determinants of climate change at the root of health inequalities; (3) the role of individual and collective vulnerability in mediating the effects of climate change on health; and (4) the need to act from a climate justice perspective to reverse health inequities.
Urban and peri-urban areas are subject to major societal challenges, like food security, climate change, biodiversity, resource efficiency, land management, social cohesion, and economic growth. In that context, Urban and Peri-urban Agriculture (UPA), thanks to its multifunctionality, could have a high value in providing social, economic, and environmental co-benefits. UPA is an emerging field of research and production that aims to improve food security and climate change impact reduction, improving urban resilience and sustainability. In this paper, a replicable GIS-based approach was used to localize and quantify available areas for agriculture, including both flat rooftop and ground-level areas in the mainland of the city of Venice (Italy). Then, possible horticultural yield production was estimated considering common UPA yield value and average Italian consumption. Climate change mitigation, like CO2 reduction and sequestration, and climate change adaptation, like Urban Flooding and Urban Heat Island reduction, due to the new UPA areas’ development were estimated. Despite the urban density, the identified areas have the potential to produce enough vegetables for the residents and improve climate change mitigation and adaptation, if transformed into agricultural areas. Finally, the paper concludes with a reflection on the co-benefits of UPA multifunctionality, and with some policy suggestions.
Well-being is transversal to different urban-related challenges such as increasing urbanization or adaptation to the effects of climate change. One possible response to these challenges is the use of nature in cities. The aim of this study is to investigate how the objective quantity of natural space near the home, the perception of these natural elements, and their perceived availability, moderated by the effect of connectedness to nature, could explain levels of well-being. A survey was conducted among a sample of 1343 participants living in seven European cities. Data were collected online via a questionnaire. Indicators of the objective quantity of urban natural space based on remotely sensed satellite imagery were also used. Regression models highlight the association between well-being and perceived amount of nature, accessibility to a community garden, and level of connectedness to nature. A moderating and negative effect of connectedness to nature on the association between the perceived quantity of nature and well-being was also identified. Perception of nature seems to be a better indicator of well-being than the objective one. Results highlight the importance of the social dimension of collective gardens in enhancing well-being. Connectedness to nature could facilitate appropriation of natural elements and its effects on well-being.
Intensive urbanization and related increase of impervious surfaces, causes negative impacts on the hydrological cycle, amplifying the risk of urban floods. These impacts can get even worse due to potential climate change impacts. The urban areas of the Simeto River Valley (SRV), the largest river valley in Sicily (Italy), have been repeatedly hit by intense rainfall events in the last decades that lead to urban flooding, causing several damages and, in some instances, threats to population. In this paper, we present the results of a 10-question survey on climate change and risk perception in 11 municipalities of the SRV carried out within the activities of the LIFE project SimetoRES, which allowed to collect 1143 feedbacks from the residents. The survey investigated: (a) the level of worry about climate change in relation to extreme storms, (b) elements of urban flooding risk preparedness: the direct experience of the residents during heavy rain events, their trust in a civil protection regional alert system, and their knowledge of the correct behavior in case of flood, and (c) the willingness of citizens to implement sustainable drainage actions for climate change adaptation in their own municipality and real estates. The results show that more than 52% of citizens has inadequate knowledge of the correct behavior during flooding events and only 30% of them feel responsible for mitigation of flooding risk. There is a modest willingness by the population to support the construction of sustainable urban drainage infrastructures. A statistical cross-analysis of the answers to the different questions, based on contingency matrices and conditional frequencies, has shown that a greater worry about climate change has no significant impact either on the behavior of people in dangerous situations occurring during flooding events or on the willingness to support financially sustainable solutions. These results suggest that to build a higher worry about climate change and related urban flooding risk is not sufficient to have better preparedness, and that more direct educative actions are necessary in the area.
Climate-change induced disasters, like floods, are expected to increase in the future. In outdoor built environments, flood risk to evacuees depends on interactions between floodwater spreading, built environment features, flood-induced modifications, and individuals’ reaction in emergency phases. Disaster risk reduction strategies should mitigate the immediate flood impacts and improve the community resilience, while being easy-toimplement and effectively supporting evacuees during the initial phases of the emergency. Simulation-based methodologies could support safety planners in evaluating the effectiveness of such strategies, especially if basing on a micro-scale-oriented approach that represents emergency interactions between each individual and the surrounding outdoor built environment. This study adopts an existing micro-scale simulator (FlooPEDS) reproducing experimental-based flood evacuation behaviours. According to a behavioural design-based approach, simulation results focus on individual responses in the outdoor built environment through Key Performance Indicators (KPIs) aimed at providing evidence of critical interactions between evacuees, floodwaters and the outdoor built environment. A case study is selected by considering different flood scenarios to test such KPIs. Risk reduction solutions are then provided, and their effectiveness is checked by simulations. Results show the micro-scale and behavioural design-based approach capabilities in proposing multi-scenarios solutions (e.g.: architectural elements to support evacuees; emergency planning).
This paper joins the growing scholarly concern for the sharpening of social and environmental inequalities in European cities, particularly those generated in Eastern Europe by evictions of poor Roma from inner-city areas and by the invisibilization of their extreme conditions. We argue that these processes – evictions and invisibilizations – create a heightened vulnerability to climate change impacts for these individuals. The paper uses secondary survey data on compact Roma groups in Romania and analyses qualitative and cartographic information collected by the authors (2019) in two mid-sized cities in Romania to flesh out the particular slum ecologies that emerge following evictions. The focus is also on the subtle processes of invisibilization that render displaced Roma vulnerable and rob them of the “right to the city” in terms of climate change adaptation. Our finding is that evicted Roma experience innumerable, “routine” weather-related impacts, such as floods, storms or cold. By exploring Roma’s heightened exposure, sensitivity and reduced adaptive capacity, we show how these impacts increase their vulnerability to future extreme weather events. These findings are indicative of a broader process of fragmentation taking place in urban areas throughout Eastern Europe, which render invisible some very real barriers to climate change adaptation.
In the recent years, the effects of extreme climate phenomena (mainly heat-related) on agricultural crops, infrastructure and human health have become increasingly severe as a result of their complex interactions with the particularities of the urban/rural habitat, as well as the social and economic factors. In Romania, heat-related phenomena (e.g. drought, heat waves) are affecting wide areas in the southern half of the territory where the study area (Bucharest Metropolitan Area) lies. The paper aims to develop a multi-criteria vulnerability assessment using both quantitative and qualitative methods. 23 indicators were selected and processed in order to assess various components of socio-economic and environmental vulnerability to heat-related phenomena using the statistical data available at local administrative units (LAU). The indicators were grouped into the three key components of vulnerability (potential exposure, sensitivity and adaptive capacity) on two dimensions (socio-economic and environmental) resulting two indexes: Socio-Economic Vulnerability Index (SEVI) and Environmental Vulnerability Index (EVI). Finally, an integrated Heat Vulnerability Index (HVI) (using Hull score, average 50 and standard deviation 14) was computed.
BACKGROUND: Europe has emerged as a major climate change hotspot, both in terms of an increase in seasonal averages and climate extremes. Projections of temperature-attributable mortality, however, have not been comprehensively reported for an extensive part of the continent. Therefore, we aim to estimate the future effect of climate change on temperature-attributable mortality across Europe. METHODS: We did a time series analysis study. We derived temperature-mortality associations by collecting daily temperature and all-cause mortality records of both urban and rural areas for the observational period between 1998 and 2012 from 147 regions in 16 European countries. We estimated the location-specific temperature-mortality relationships by using standard time series quasi-Poisson regression in conjunction with a distributed lag non-linear model. These associations were used to transform the daily temperature simulations from the climate models in the historical period (1971-2005) and scenario period (2006-2099) into projections of temperature-attributable mortality. We combined the resulting risk functions with daily time series of future temperatures simulated by four climate models (ie, GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, and MIROC5) under three greenhouse gas emission scenarios (ie, Representative Concentration Pathway [RCP]2.6, RCP6.0, and RCP8.5), providing projections of future mortality attributable fraction due to moderate and extreme cold and heat temperatures. FINDINGS: Overall, 7·17% (95% CI 5·81-8·50) of deaths registered in the observational period were attributed to non-optimal temperatures, cold being more harmful than heat by a factor of ten (6·51% [95% CI 5·14-7·80] vs 0·65% [0·40-0·89]), and with large regional differences across countries-eg, ranging from 4·85% (95% CI 3·75-6·00) in Germany to 9·87% (8·53-11·19) in Italy. The projection of temperature anomalies by RCP scenario depicts a progressive increase in temperatures, more exacerbated in the high-emission scenario RCP8.5 (4·54°C by 2070-2099) than in RCP6.0 (2·89°C) and RCP2.6 (1·67°C). This increase in temperatures was transformed into attributable fraction. Projections consistently indicated that the increase in heat attributable fraction will start to exceed the reduction of cold attributable fraction in the second half of the 21st century, especially in the Mediterranean and in the higher emission scenarios. The comparison between scenarios highlighted the important role of mitigation, given that the total attributable fraction will only remain stable in RCP2.6, whereas the total attributable fraction will rapidly start to increase in RCP6.0 by the end of the century and in RCP8.5 already by the middle of the century. INTERPRETATION: The increase in heat attributable fraction will start to exceed the reduction of cold attributable fraction in the second half of the 21st century. This finding highlights the importance of implementing mitigation policies. These measures would be especially beneficial in the Mediterranean, where the high vulnerability to heat will lead to an imbalance between the decreasing cold and increasing heat-attributable mortality. FUNDING: None.
There is an increasing need to obtain climate projections for cities using an ensemble approach for uncertainty estimation. Yet, current-day computational resources are too limited to dynamically downscale GCM ensembles to urban scale. Here, a recently developed and validated statistical-dynamical computationally-cheap method is employed to downscale ten EURO-CORDEX climate projections over Brussels (Belgium) covering the period 1971-2100. Results show that, under the Paris agreement, summer mean projected temperature in Brussels will rise by 3.6 degrees C to 4.1 degrees C [+ – 0.7 degrees C] on average. The Urban Heat Island (UHI) intensity does not increase under future global warming with even a slight decrease under heatwave (HW) conditions by 0.1 degrees C (+/- 0.1 degrees C). However, the number of HW days is projected to be 30.6% and 158.9% higher for the 2 degrees C and 3 degrees C Global Warming Levels (GWL), respectively, as compared to 1.5 degrees C GWL. The heat stress during HW periods also follows the same trend: compared to a 1.5 degrees C GWL, the number of extreme heat stress days at 2 degrees C (3 degrees C) GWL will increase by 29% (91%) on average inside the city. The results can be used in support of adaptation measures, which should be considered for future resilience of the city of Brussels.
Global warming increases the risk of heat stress in Europe. Hence, heat stress must be considered as a health hazard for individuals working in outdoors and indoors conditions. Physiologically equivalent temperature (PET) is more related to the perceived temperature, but most of the current Local Climate Zone (LCZ) studies focus on measured temperature, instead of PET. Therefore, in this research, PET was applied to evaluate the thermal component of the outdoor microclimate for the f rst time in Berlin during a (1) hot spell, and (2) a normal period during July to August 2018. The aim of the present study is to explore the impacts of outdoor surroundings on human thermal comfort and its perception during the day and nighttime. Based on 32 micrometeorological stations located in different LCZs, the outdoor thermal sensation was investigated in order to f nd hourly thermal stress level conditions. Based on the mean hourly thermal sensation, the highest PET value was observed in, LCZ 4, “open high-rise” with 33.76 degrees C at 1400 CET, which represents a thermal stress level of “moderate heat stress”. The LCZ 2 showed “slight heat stress”, at the same time. High Sky View Factor (SVF) and relative humidity in “open high-rise” caused the highest PET. From the afternoon around 1800 CET to early morning 0600 CET, LCZ 2 is one thermal stress level warmer than all other existing LCZs in Berlin. During the hot spell, the hottest time period of the day was between 1600 CET to 1700 CET. In the morning from 0700 CET and midnight, the LCZ 2 was warmer than other local climate zones as the heat capacity of the buildings is high. Maximum hourly PET values illustrate that LCZ 4 was the warmest LCZ in which thermal sensation was ‘very hot’ between 0800 CET to 1700 CET. According to minimum hourly of PET, LCZ 4 was the coldest LCZs during the night and early in the morning.
Recent evidence suggests a synergistic acute effect between temperature, ozone and particulate matter (PM) on premature mortality. Several studies reported higher air pollution-related mortality risks during warm days, and higher heat-related mortality risk during polluted days. We investigated if interactions between temperature and air pollution modified the mortality response to an extent that would support the need for joint heat and air pollution warning systems. We developed a multicentre time-series design for 17 French cities for the period 2000-2015, investigating the influence of season and temperature on the air pollution (PM10 and ozone)-mortality relationship, and the in-fluence of air pollution on the temperature-mortality relationship. Ozone and PM10 mortality risks exhibit an increasing gradient between spring, summer and heat waves. For instance, a 10 mu g/m(3) increase in PM10 was associated with a 3% [Confidence interval (CI) 95% 2.1:3.9] increase in mortality during summer, and with a 14.2% [CI 95% 5.6:23.4] increase in mortality during heat waves. The heat-mortality response was slightly influenced by air pollution, especially during the most extreme heat waves. Our results suggest that air pollution warnings should take season into account, using lower thresholds during summer and heat waves. Heat warning systems may not be improved by air pollution data, as its added value would be limited, compared to the complexity it would add to the warning systems. Efforts should be made to reduce ozone and PM10 concentrations during heat waves, even when they are already below regulatory thresholds.
Climate change can cause multiply potential health issues in urban areas, which is the most susceptible environment in terms of the presently increasing climate volatility. Urban greening strategies make an important part of the adaptation strategies which can ameliorate the negative impacts of climate change. It was aimed to study the potential impacts of different kinds of greenings against the adverse effects of climate change, including waterborne, vector-borne diseases, heat-related mortality, and surface ozone concentration in a medium-sized Hungarian city. As greening strategies, large and pocket parks were considered, based on our novel location identifier algorithm for climate risk minimization. A method based on publicly available data sources including satellite pictures, climate scenarios and urban macrostructure has been developed to evaluate the health-related indicator patterns in cities. The modelled future- and current patterns of the indicators have been compared. The results can help the understanding of the possible future state of the studied indicators and the development of adequate greening strategies. Another outcome of the study is that it is not the type of health indicator but its climate sensitivity that determines the extent to which it responds to temperature rises and how effective greening strategies are in addressing the expected problem posed by the factor.
Air pollution is responsible for many adverse effects on human beings. Thermal discomfort, on the other hand, is able to overload the human body and eventually provoke health implications due to the heat imbalance. Methods: The aim of the presented work is to study the behavior of two bio-climatic indices and statistical characteristics of the air quality index for Sofia city-the capital of Bulgaria for the period 2008-2014. The study is based on the WRF-CMAQ model system simulations with a spatial resolution of 1 km. The air quality is estimated by the air quality index, taking into account the influence of different pollutants and the thermal conditions by two indices, respectively, for hot and cold weather. It was found that the recurrence of both the heat and cold index categories and of the air quality categories have heterogeneous space distribution and well manifested diurnal and seasonal variability. For all of the situations, only O-3 and PM10 are the dominant pollutants-these which determine the AQI category. It was found that AQI1, AQI2, and AQI3, which fall in the “Low” band, have the highest recurrence during the different seasons, up to more than 70% in some places and situations. The recurrence of AQI10 (very high) is rather small-no more than 5% and concentrated in small areas, mostly in the city center. The Heat index of category “Danger” never appears, and the Heat index of category “Extreme caution” appears only in the spring and summer with the highest recurrence of less than 5% in the city center. For the Wind-chill index category, “Very High Risk” never appears, and the category “High Risk” appears with a frequency of about 1-2%. The above leads to the conclusion that both from a point of view of bioclimatic and air quality indices, the human health risks in the city of Sofia are not as high.
Urbanization, anthropogenic activities, and social determinants such as poverty and literacy rate greatly contribute to heat-related mortalities. The 2003 strong heat wave (Lucifer) in France resulted in catastrophic health consequences in the region that may be attributed to urbanization and other anthropogenic activities. Amiens is a medium-sized French city, where the average temperature has increased since the year 2000. In this study, we evaluated the Heat Vulnerability Index (HVI) in Amiens for extreme heat days recorded during three years (2018-2020). We used the principal component analysis (PCA) technique for fine-scale vulnerability mapping. The main types of considered data included (a) socioeconomic and demographic data, (b) air pollution, (c) land use and cover, (d) elderly heat illness, (e) social vulnerability, and (f) remote sensing data (land surface temperature (LST), mean elevation, normalized difference vegetation index (NDVI), and normalized difference water index (NDWI)). The output maps identified the hot zones through comprehensive GIS analysis. The resultant maps showed that high HVI exists in three typical areas: (1) areas with dense population and low vegetation, (2) areas with artificial surfaces (built-up areas), and (3) industrial zones. Low-HVI areas are in natural landscapes such as rivers and grasslands. Our analysis can be implemented in other cities to highlight areas at high risk of extreme heat and air pollution.
Cities are increasingly confronted with multiple environmental and climatic stressors. Especially during heatwaves, street canyons are both producers and sufferers of air pollution and urban heat island (UHI) effects, with severe risks on public health. To better design mitigation measures, it is important to consider both the microclimate behaviors as well as the perceptions of the local population. Therefore, this study examined pedestrian perceptions and microclimate modelings to understand outdoor thermal comfort conditions and air pollution dispersion in the case study neighborhood of Dortmund Marten, Germany. A field survey with measurement points at two street canyons for climatic variables and questionnaires on subjective thermal comfort and air pollution was conducted on a hot day during the heatwave period in August 2020. As a cost-effective method for modeling input generation, we extracted spatial and spectral data like albedo, roof materials and tree locations out of remote sensing imageries. Finally, we compared the modeling results of the physiological equivalent temperature (PET) index, particulate matter concentrations and air temperatures with empirical field measurement data and the questionnaire responses. Results indicate that during hot summer days with light winds from the east, the north-south orientated street canyon with tree arrangements tends to act as a tunnel for particulate matter accumulation. Coincidently, pedestrians show less thermal discomfort than calculated PET values in that particular area during morning and daytime, which underlines the dichotomy of such places. On the other hand, the low rise east-west orientated street canyon shows higher PET votes than predicted by the model. However, particulate matter concentrations were considerably underestimated by the model, while air temperature predictions provided meaningful results. The proposed workflow shows the potential to accelerate future preparations of input data for microclimate modelings, while the results can enhance wind-sensitive planning procedures and heat stress resilience in mid-latitude urban neighborhoods.
Monitoring microclimate variables within cities with high accuracy is an ongoing challenge for a better urban resilience to climate change. Assessing the intra-urban characteristics of a city is of vital importance for ensuring fine living standards for citizens. Here, a novel mobile microclimate station is applied for monitoring the main microclimatic variables regulating urban and intra-urban environment, as well as directionally monitoring shortwave radiation and illuminance and hence systematically map for the first time the effect of urban surfaces and anthropogenic heat. We performed day-time and night-time monitoring campaigns within a historical city in Italy, characterized by substantial urban structure differentiations. We found significant intra-urban variations concerning variables such as air temperature and shortwave radiation. Moreover, the proposed experimental framework may capture, for the very first time, significant directional variations with respect to shortwave radiation and illuminance across the city at microclimate scale. The presented mobile station represents therefore the key missing piece for exhaustively identifying urban environmental quality, anthropogenic actions, and data driven modelling toward risk and resilience planning. It can be therefore used in combination with satellite data, stable weather station or other mobile stations, e.g. wearable sensing techniques, through a citizens’ science approach in smart, livable, and sustainable cities in the near future.
The objective of this study was to analyze and compare the effect of high temperatures on daily mortality in the urban and rural populations in Madrid. Data were analyzed from municipalities in Madrid with a population of over 10,000 inhabitants during the period from January 1, 2000 to December 31, 2020. Four groups were generated: Urban Metropolitan Center, Rural Northern Mountains, Rural Center, and Southern Rural. The dependent variable used was the rate of daily mortality due to natural causes per million inhabitants (CIE-X: A00-R99) between the months of June and September for the period. The primary independent variable was maximum daily temperature. Social and demographic “context variables” were included: population >64 years of age (%), deprivation index and housing indicators. The analysis was carried out in three phases: 1) determination of the threshold definition temperature of a heat wave (Tumbral) for each study group; 2) determination of relative risks (RR) attributable to heat for each group using Poisson linear regression (GLM), and 3) calculation of odds ratios (OR) using binomial family GLM for the frequency of the appearance of heat waves associated with context variables. The resulting percentiles (for the series of maximum daily temperatures for the summer months) corresponding to Tthreshold were: 74th percentile for Urban Metropolitan Center, 76th percentile for Southern Rural, 83rd for Rural Northern Mountains and 98th percentile for Center Rural (98). Greater vulnerability was found for the first two. In terms of context variables that explained the appearance of heat waves, deprivation index level, population >64 years of age and living in the metropolitan area were found to be risk factors. Rural and urban areas behaved differently, and socioeconomic inequality and the composition of the population over age 64 were found to best explain the vulnerability of the Rural Center and Southern Rural zones.
BACKGROUND: Heat waves are correlated with increased mortality in the aged population. Social isolation is known as a vulnerability factor. This study aims at evaluating the correlation between an intervention to reduce social isolation and the increase in mortality in the population over 80 during heat waves. METHODS: This study adopted a retrospective ecologic design. We compared the excess mortality rate (EMR) in the over-80 population during heat waves in urban areas of Rome (Italy) where a program to reduce social isolation was implemented, to others where it was not implemented. We measured the mortality of the summer periods from 2015 to 2019 compared with 2014 (a year without heat waves). Winter mortality, cadastral income, and the proportion of people over 90 were included in the multivariate Poisson regression. RESULTS: The EMR in the intervention and controls was 2.70% and 3.81%, respectively. The rate ratio was 0.70 (c.i. 0.54-0.92, p-value 0.01). The incidence rate ratio (IRR) of the interventions, with respect to the controls, was 0.76 (c.i. 0.59-0.98). After adjusting for other variables, the IRR was 0.44 (c.i. 0.32-0.60). CONCLUSIONS: Reducing social isolation could limit the impact of heat waves on the mortality of the elderly population.
Global warming is causing increasing Heat Waves that affect human health. High temperatures markedly increase morbidity and mortality. Urban Heat Islands increase the effects of Heat Waves and are a serious inconvenience to human health and comfort. Cities can substantially increase local temperatures and reduce temperature drop at night. During the night, the greater thermal inertia of the central areas reduces their cooling capacity. On the other hand, it is important to highlight that urban vegetation plays a key role in adapting cities to Global Warming and Urban Heat Island. Green areas have lower temperatures than the rest of land uses and generate a cooling effect that spreads to their surroundings creating a “cool island” effect. The main objective of this paper is to establish the nocturnal land surface temperature and land surface air temperature of Barcelona Metropolitan Area (35 municipalities, 636 km(2), 3.3 million inhabitants) in an episode of a nocturnal heatwave and to estimate its possible impact on health and mortality. Subsequently, nighttime temperatures are analysed in this extreme heat context to determine their spatial distribution and detect the urban landscapes that are most vulnerable to extreme night heat. Modelling of land surface temperature must reveal the elements that determine night Urban Heat Island and consequently identify actions that can be implemented at urban planning level to refresh the environment during the night and thus increase the resilience of the most vulnerable landscapes and improve residents’ health. This paper studies the effect of urban greenery and green infrastructures on Nighttime Urban Heat Island and propose climate adaptation measures and design for urban green areas to decrease high temperature in a Heat Wave context, which contributes to reducing the serious negative impacts on people’s health.
In Europe, regional climate change prospects indicate the urgency of adapting to extreme weather events. While increasing temperature trends have already been detected, in the last decades, the adoption of a European heatwave (HW) early-warning index is not yet consensual, partially due to the significant number of alternative algorithms, in some cases adjusted to the measurement of sector-specific impacts (as per the Expert Team on Climate Risk and Sector-specific Indices (ET-SCI)). In particular, the Excess Heat Factor (EHF) has been shown to accurately predict heat-related human health outcomes, in mid-latitude climates, provided that local summer exposure to excess heat is mostly driven by extreme air temperatures, with a lower contribution from relative humidity. Here, annual summaries of EHF-based HW detection were calculated for the European region, using daily maximum and minimum temperatures from the homogenised version of the E-OBS gridded dataset. Annual HW frequencies, duration, mean magnitude, maximum amplitude, and severity were subject to climatology and trend analysis across the European biogeographical regions, considering the 1961-1990 period as the baseline reference for anomaly detection in the more recent (1991-2018) decades. As HW-dependent morbidity/mortality affects mostly the elderly, an EHF-based HW Exposure Index was also calculated, by multiplying the recent probability of severe events per the number of people aged 65, or more, in the European Functional Urban Areas (FUAs). Results show that recent historical EHF-based patterns diverge across European Biogeographical regions, with a clear latitudinal gradient. Both the historical mean and recent trends point towards the greater exposure in the southern European Mediterranean region, driven by the significant increase of HW frequency, duration and maximum severity, especially in the last 3 decades; conversely, annual maximum EHF intensities (i.e., greatest deviations from the local 90th daily mean temperature) are mostly found in the northern and/or high altitude Boreal, Alpine and Continental regions, as a consequence of the latitudinal effect of local climatology on the HWM/HWA indices (this also translates into greater magnitudes of change, in this regions). Nonetheless, by simultaneously considering the probability of Severe HW occurrence in the last three decades, together with the log transformation of people aged 65 or more, results show that greater HW Exposure Indices affect FUAs across the whole Europe, irrespective of its regional climate, suggesting that more meaningful vulnerability assessments, early warning and adaptation measures should be prioritized accordingly.
This paper presents a new methodological approach for analysing the impacts of climate change on the urban habitat and improving the quality of life for citizens. The study falls within the diagnostic phase of the Climate Change and Urban Health Resilience (CCUHRE) research project applied to the rationalist neighbourhood of Monticelli, a suburb of Ascoli Piceno (Italy). The methodological approach tests innovative and multidisciplinary cognitive tools to quantify the impacts of climate change and create refined risk maps combining remote sensing, spatial data, satellite images, and thermal fluid dynamic (CFD) simulations. These tools created an atlas of green areas and surfaces using scientific indexes that describe the relationship between the urban form and heat and between the type of ground and materials. The information yielded by geoprocessing will allow critical aspects in the context to be addressed with site-specific strategies. In fact, through downscaling, it is possible to analyse the thermal fluid dynamics characteristics of the most significant urban areas and identify the related weather/climate characteristics, perceptual scenarios, and thermal stressed regions. The results have provided a dataset that defines the degree of vulnerability of the neighbourhood and identifies the areas exposed to thermal risk.
Rural areas cool off by night but built-up urban areas lack similar relief and may threaten vulnerable people’s health during heat waves. Temperature varies within a city due to the heterogenous nature of urban environments, but official measurement stations are unable to capture local variations, since they use few measurement stations typically set up outside of urban areas. Meteorological measurements may as such be at odds with citizen sensing, where absolute accuracy is sacrificed in pursuit of increased coverage. In this article, we use geographic information processing methodologies and generate 144 hourly apparent temperature surfaces for Rotterdam during a six-day heat wave that took place in July 2019 in The Netherlands. These surfaces are used to generate a humidex degree hours (HDH) composite map. The HDH metric integrates apparent temperature intensity with duration into one spatially explicit value and is used to identify geographical areas in Rotterdam where citizens may experience adverse health effects of prolonged heat exposure. Combining the HDH map with demographic data allows us to identify the most heat-exposed areas with the largest share of vulnerable population. These neighbourhoods may be the locations most in need of adaptation measures.
With global warming, heat waves are becoming more frequent and intense, particularly in northern latitudes, where the pace of warming is faster. Due to its northern location, Swedish society has been built primarily to manage a cold climate, and is less prepared to manage heat, which the 2018 heat wave demonstrated. While young children are recognized as vulnerable to heat, and are reliant on preschool care, few studies have examined how the young and vulnerable people are cared for during heat waves in the institutional preschool setting. This exploratory study demonstrates how children in preschool environments are vulnerable to heat, in order to identify management needs by assessing experienced impacts and responses to the 2018 heat wave in Sweden. Empirically, the study builds on a survey completed by 33 unit heads responsible for 77 preschools in the focused municipality, and qualitative interviews with five educators and five parents, as well as temperature measurements in three selected preschools. This study shows that: (i) children and educators are exposed to both high indoor and outdoor temperatures in the preschools; (ii) both children and educators were affected by the heat wave in the preschools, and their sensitivity is deeply intertwined due to their dependency relationship, rendering a form of double sensitivity to heat; and (iii) the preschool heads and educators were unprepared to sufficiently cope with the heat wave, and organizational strategies for managing heat were lacking, indicating weak adaptive capacity. The significant exposure to heat in preschool environments, the dual sensitivity of children and preschool educators, and the low organizational readiness resulting in uncoordinated responses to reduce heat stress suggest a pronounced vulnerability to heat waves in preschools.
Constant urban growth exacerbates the demand for residential, commercial and traffic areas, leading to progressive surface sealing and urban densification. With climate change altering precipitation and temperature patterns worldwide, cities are exposed to multiple risks, demanding holistic and anticipatory urban planning strategies and adaptive measures that are multi-beneficial. Sustainable urban planning requires comprehensive tools that account for different aspects and boundary conditions and are capable of mapping and assessing crucial processes of land-atmosphere interactions and the impacts of adaptation measures on the urban climate system. Here, we combine Computational Fluid Dynamics (CFD) and Geographic Information System (GIS) capabilities to refine an existing 2D urban micro- and bioclimatic modelling approach. In particular, we account for the vertical and horizontal variability in wind speed and air temperature patterns in the urban canopy layer. Our results highlight the importance of variability of these patterns in analysing urban heat development, intensity and thermal comfort at multiple heights from the ground surface. Neglecting vertical and horizontal variability, non-integrated CFD modelling underestimates mean land surface temperature by 7.8 °C and the Universal Thermal Climate Index by 6.9 °C compared to CFD-integrated modelling. Due to the strong implications of wind and air temperature patterns on the relationship between surface temperature and human thermal comfort, we urge caution when relying on studies solely based on surface temperatures for urban heat assessment and hot spot analysis as this could lead to misinterpretations of hot and cool spots in cities and, thus, mask the anticipated effects of adaptation measures. The integrated CFD-GIS modelling approach, which we demonstrate, improves urban climate studies and supports more comprehensive assessments of urban heat and human thermal comfort to sustainably develop resilient cities.
Our study plans to quantify the effect of higher temperatures on different critical Turkish health outcomes mainly to chart future developments and to identify locations in Turkey that may be potential vulnerable hotspots. The general structure of the temperature mortality function was estimated with different fixed-level effects, with a specific focus on the mortality effect of maximum apparent temperature. Regional models were fitted to pinpoint the thresholds where the temperature-mortality relation changes, thus investigating whether the thresholds are determined nationally or regionally. The future patterns were estimated by extrapolating from future temperature trends: analyzing possible future mortality trends under the restricting assumption of minimal acclimation. Using the fixed effect regression structure, social and developmental variables acting as heat effect modifiers were also identified. In the largest dataset, the initial fixed effect regression specification supports the hypothesis summarized by the U-shaped relationship between temperature and mortality. This is a first corroboration for Turkish climate and health research. In addition, intermediation effects were substantiated for the level of urbanization and population density, and the human development and health development within provinces. Regional heterogeneity is substantiated by the mortality-temperature relationship and the significant threshold deviations from the national average.
Over the last few decades, heat waves have intensified and have led to excess mortality. While the probability of being affected by heat stress has significantly increased, the risk of heat mortality is rarely quantified. This quantification of heat mortality risk is necessary for systematic adaptation measures. Furthermore, heat mortality records are sparse and short, which presents a challenge for assessing heat mortality risk for future climate projections. It is therefore crucial to derive indicators for a systematic heat mortality risk assessment. Here, risk indicators based on temperature and mortality data are developed and applied tomajor cities in Germany, France, and Spain using regional climatemodel simulations. Biascorrected dailymaximum, minimum, and wet-bulb temperatures show increasing trends in future climate projections for most considered cities. In addition, we derive a relationship between daily maximum temperatures and mortality for producing future projections of heatmortality risk fromextreme temperatures that is based on low(representative concentration pathway RCP2.6) and high (RCP8.5) emission scenario future climate projections. Our results illustrate that heatmortality increases by about 0.9% decade(-1) in Germany, 1.7% decade(-1) in France, and 7.9% decade(-1) in Spain for RCP8.5 by 2050. The future climate projections also show that wet-bulb temperatures above 30 degrees C will be reached regularly, withmaxima above 40 degrees C likely by 2050. Our results suggest a significant increase of heat mortality in the future, especially in Spain. On average, our results indicate that themortality risk trend is almost 2 times as high in all three countries for the RCP8.5 scenario relative to RCP2.6. SIGNIFICANCE STATEMENT: Anthropogenic greenhouse gas emissions have led to an increase in temperatures over the last century. This general warming leads to more intensive and more frequent heat waves that affect humans adversely. Extreme temperatures exert heat stress on the human body and can lead to reduced productivity, sickness, and death. Herewe derive a statistical relationship between extreme temperatures and the number of deaths inmajor cities in three European countries so as to be able to use future climate simulations to determine likely numbers of heat-related deaths. Our results show that the number of heat-related deaths will increase in major European cities by 2050 and will be 2 times as high for high greenhouse gas emissions simulations as for low greenhouse gas emissions simulations.
INTRODUCTION: There is currently little knowledge and few published works on the subject of vulnerability to heat in rural environments at the country level. Therefore, the objective of this study was to determine whether rural areas are more vulnerable to extreme heat than urban areas in Spain. This study aimed to analyze whether a pattern of vulnerability depends on contextual, environmental, demographic, economic and housing variables. METHODS: An ecological, longitudinal and retrospective study was carried out based on time series data between January 01, 2000 and December 31, 2013 in 42 geographic areas in 10 provinces in Spain. We first analyzed the functional relationship between the mortality rate per million inhabitants and maximum daily temperature (Tmax). We then determined the summer temperature threshold (Pthreshold) (June-September) at which increases in mortality are produced that are attributable to heat. In a second phase, based on Pthreshold, a vulnerability variable was calculated, and its distribution was analyzed using mixed linear models from the Poisson family (link = log). In these models, the dependent variable was vulnerability, and the independent variables were exposure to high temperatures, aridity of the climate, deprivation index, percentage of people over age 65, rurality index, percentage of housing built prior to 1980 and condition of dwellings. RESULTS: Rurality was a protective factor, and vulnerability in urban areas was six times greater. In contrast, risk factors included aridity (RR = 5.89 (2.26 15.36)), living in cool summer zones (2.69 (1.23, 5.91)), poverty (4.05 (1.91 8.59)) and the percentage of dysfunctional housing (1.13 (1.04 1.24)). CONCLUSIONS: Rural areas are less vulnerable to extreme heat than the urban areas analyzed. Also, population groups with worse working conditions and higher percentages of dwellings in poor conditions are more vulnerable.
Using a mixed-method approach consisting of interviews with preschool teachers and modelling of the outdoor thermal conditions using the mean radiant temperature as an indicator of heat stress, the occurrence of heat stress in Gothenburg preschools during the summer of 2018 and its effects have been studied. One third of 440 preschool yards modelled have more than 50% of the preschool yard-area exposed to strong heat stress during a warm and sunny summer day, implying children in many preschools have considerably less play area than current guidelines deem sufficient. Shade, where present, was mostly from trees within the preschool yards themselves rather from objects in surrounding areas, provided effective heat mitigation. In-terviews confirmed that excessive heat conditions at preschool yards resulted in tired, drowsy and overheated children as well as forcing the preschool to prioritise care over pedagogical activities. The results demonstrated that heat stress occurs at Gothenburg preschools, with difficulties in ensuring the well-being of children at many preschools as a consequence. Many preschools need more shade, preferably from trees to provide healthy and secure environments for preschool children. Finally, the study highlights the need for more research on how weather and outdoor environments affect children’s activity and well-being.
The understanding of intra-urban air temperature variations is crucial to assess strategies for cities’ adaptation to impacts of present and future anthropogenic climate change. Depending on extensive measurement networks, high-resolution air temperature measurements in urban environments are challenging due to high instrumentation and maintenance costs. Here, we present a low-cost measurement device (LCD) consisting of a temperature logger and a custom-made, naturally ventilated radiation shield. Besides intercomparisons with automated weather stations (AWS) at three reference sites during record-dry summer 2018, we tested the potential of the devices using a network of 79 LCDs to assess the intra-urban variability of urban heat island (UHI) patterns in the city of Bern, Switzerland. We found positive mean measurement biases between LCDs and AWS of 0.61 to 0.93 K (RMSE: 0.78 to 1.17 K) during daytime, of which up to 82.8% of the variance could be explained statistically by solar irradiance (radiative heating) and wind speed (insufficient ventilation). During night, average measurement biases were markedly lower and eventually negative with -0.12 to 0.23 K (RMSE: 0.19 to 0.34 K). Our results highlight the importance of sensor intercomparisons being conducted at multiple locations with differing urban land-cover, structure, and metabolism given that biases varied considerably between the reference sites. Data retrieved by the city-wide measurement network showed that the LCD approach is well suited for the analysis of spatiotemporal UHI patterns during night and adds considerable value compared to the few existing AWS in detecting fine-scale air temperature variability. In conclusion, the current LCD measurement approach represents a valuable option for cost-effective analyses of urban air temperature variability across multiple scales, which may be of particular value for the development, appliance, and monitoring of adaptation strategies to climate change in cities with restricted financial resources.
In response to urbanization and global warming, which amplify heatwave effects and might lead to urban heat stress, this paper proposes a practical approach to characterize the local microclimate at the neigh-borhood scale. In this approach, the local urban climate is described using suitable indicators, to support the ecodistrict design process or refurbishment. Experimental and numerical results illustrate the approach in a case study of a French coastal city, La Rochelle. In the first step, we set up urban and rural weather stations to characterize the local urban climate over a summer period and to identify local tem-perature differences. The measurements highlighted a daytime urban cooling effect due to the local sea breeze. While the Urban Weather Generator (UWG) simulation tool used for this study does not capture coastal effects, the results were consistent with the urban heat island (UHI) measurements. We proposed two indicators to quantify the local climate modifications: local UHI and overheating intensity. The parameters of the adaptation strategies were assessed through a sensitivity analysis for these two indi-cators. For this case-study, we identified vegetation cover, building height and road albedo as key param-eters that can be used to mitigate local overheating. (c) 2021 Elsevier B.V. All rights reserved.
Environmental and technological design for climate adaptation in the urban built environment can no longer be separated from the generation, collection, or use of data (big data). ICT tools (Information and Communication Technologies), for the modelling and simulation of the built urban environment are identified as measuring devices and provide knowledge on the impacts of climate change in design practice based on an environmentally data-driven approach. This study aims to define a framework for the evaluation of environmental health and comfort parameters applicable to simulation tools, with a specific focus on thermal and environmental exchanges between indoor and outdoor spaces, to define those factors that affect the perception of user’s well-being in thermal stress conditions (e.g., heatwaves), both indoor and outdoor. Through the definition of two study cases in the city of Naples, Italy, special attention was paid to investigating the interaction between outdoor and indoor performance when urban temperatures rise. A comparison between a daily survey for occupants and simulations was conducted to confirm the validity of the data obtainable from the perceived thermal sensations. The obtained results show that the designed framework can reliably simulate real outdoor and indoor conditions according to comfort indices such as the predicted mean vote and adaptive comfort model. The methodological framework developed can guarantee the interoperability of data to simulate indoor and outdoor environments responding to real conditions and determine a favourable condition for the development of urban redevelopment interventions through the application of climate adaptive design strategies.
BACKGROUND: Heat waves can be considered as an emerging challenge among the potential health risks generated by urbanization and climate changes. Heat waves are becoming more frequent, long and intense, and can be defined as meteorological extreme events consisting in prolonged time of extremely high temperatures in a particular region. The following paper addresses health threats due to heat waves presenting the case study of Lecce, a city located in Southern Italy; the Mediterranean area is already recognized in international literature as a hot-spot for climate changes. This work assesses the potential impact of two different adaptation strategies. METHODS: We have tested the effectiveness of cool surfaces and urban forestry as adaptation approaches to cope with heat waves. The microclimate computer-based model “ENVI-met” was adopted to predict thermal scenarios arising from the two proposed interventions. The parameters analysed consisted in temperature and relative humidity. RESULTS: Urban forestry approach seem to lower temperature (that represents the major cause of urban overheating) better than cool surfaces strategy, but relative humidity produced by the evapotranspiration processes of urban forestry has also negative influences on temperature perceived by pedestrians (thermal discomfort). CONCLUSION: Vegetation represents both an adaptation and a mitigation strategy to climate changes that guarantees an improvement of air quality, with consequent psychological and physical benefits. Wide campaigns aimed at planting trees and increasing the urban green coverage should be systematically planned and fostered by national, regional and local institutions preferably with the involvement of research departments, schools and citizens’ associations.
Urban green infrastructure, especially trees, are widely regarded as one of the most effective ways to reduce urban temperatures in heatwaves and alleviate the adverse impacts of extreme heat events on human health and well-being. Nevertheless, urban planners and decision-makers are still lacking methods and tools to spatially evaluate the cooling effects of urban green spaces and exploit them to assess greening strategies at the urban agglomeration scale. This article introduces a novel spatially explicit approach to simulate urban greening scenarios by increasing the tree canopy cover in the existing urban fabric and evaluating their heat mitigation potential. The latter is achieved by applying the InVEST urban cooling model to the synthetic land use/land cover maps generated for the greening scenarios. A case study in the urban agglomeration of Lausanne, Switzerland, illustrates the development of tree canopy scenarios following distinct spatial distribution strategies. The spatial pattern of the tree canopy strongly influences the human exposure to the highest temperatures, and small increases in the abundance of tree canopy cover with the appropriate spatial configuration can have major impacts on human health and well-being. The proposed approach supports urban planning and the design of nature-based solutions to enhance climate resilience.
Temperatures in Mediterranean cities are rising due to the effects of climate change, with a consequent increase in the heat waves frequency. Recent research has shown the tempering potential of semi-outdoor spaces such as courtyards, which are semi-enclosed spaces that are widely used by the users of buildings in Mediterranean cities. International standards addressing thermal comfort parameters provide technical guidelines for indoor spaces only. Expanding this concept, this paper focuses on the potential to extend and interpret the existing calculation models for indoor thermal comfort, EN 16798 and ASHRAE 55, to determine thermal comfort, monitoring two different courtyards in Cordoba, Spain, during both typical summer and heat wave periods. The results show that during the typical summer, the monitored courtyards can reach temperatures up to 8.4 degrees C cooler than outside. Subsequently can be considered to be in thermal comfort on average for 88% of the time according to EN 16798, and 75% according to ASHRAE 55, which drop to 71% and 52% respectively during heat wave (HW) periods, in spite of increasing thermal gap (TG) up to 13.9 degrees C. The results are also compared with the PET indicator used for evaluation of outdoor thermal comfort, which provides comparable figures: 81% summer and 73% HW. Implications of implementing passive shading strategies to increase comfort in these transition spaces are also evaluated. The research highlights the thermal potential and usefulness of courtyards in warm climates, so they can ultimately be included in the building analysis as a potentially comfortable and habitable space.
Urban areas are characterised by the dominance of impervious surfaces and decreased presence of vegetation compared to their rural surroundings. The resultant increase in temperature is known to amplify global warming, with negative impacts on health and increased energy requirements for cooling. Intra-urban variations in temperature have received less attention than urban-rural variations, although the former can be even larger than the latter. Land cover composition is known to influence surface temperature, while the influence of heights, of buildings and vegetation, is less explored. There are also fewer studies in high-latitude cities although extreme heat events are increasing in frequency and severity in these cities, and high-resolution geospatial datasets are often available for detailed analysis. The aim of this study is therefore to assess the influence of selected land cover variables on the estimated surface temperature in the four largest cities in Denmark-Copenhagen, Aarhus, Odense and Aalborg. Land surface temperatures (LST) of the four cities were estimated using Band 10 (10.60-11.19 mu m) from Landsat 8 imagery. Vegetation cover, building cover, vegetation height and building height were estimated using 4-band aerial imagery, building footprints and LiDAR-based elevation models, and their correlations with LST were estimated. Moving average filters, with window sizes from 3 x 3 (90 m x 90 m) to 11 x 11 (330 m x 330 m), were used to understand the area of influence of surrounding land cover on the LST within 30-m cells. When vegetation cover and building cover increased from 0-5% to 95-100%, median values of LST decreased by 4.16 +/- 0.76 degrees C and increased by 4.31 +/- 0.69 degrees C, respectively. Land cover variables within 7 x 7 windows (210 m x 210 m) are shown to have strong correlations with the LST of 30-m cells. The area of influence of building heights on the LST of 30-m cells was the largest in Copenhagen, which also has the tallest buildings among the cities. LST reduced by 4.10 degrees C when the mean vegetation height within a 30-m cell increased from 0-2 m to 20-22 m, and by 5.75 degrees C for 210 m x 210 m patches with the same height range. A combination of increased vegetation cover and height could therefore be used to regulate temperature in or close to hot spots in cities depending on the availability of space.
Surface temperature is often used to examine heat exposure in multi-city studies and for informing urban heat mitigation efforts due to scarcity of urban air temperature measurements. Cities also have lower relative humidity, traditionally not accounted for in large-scale observational urban heat risk assessments. Here, using crowdsourced measurements from over 40,000 weather stations in approximate to 600 urban clusters in Europe, we show the moderating effect of this urbanization-induced humidity reduction on outdoor heat stress during the 2019 heatwave. We demonstrate that daytime differences in heat index between urban clusters and their surroundings are weak, and associations of this urban-rural difference with background climate, generally examined from the surface temperature perspective, are diminished due to moisture feedbacks. We also examine the spatial variability of surface temperature, air temperature, and heat index within these clusters-relevant for detecting hotspots and potential disparities in heat exposure-and find that surface temperature is a poor proxy for the intra-urban distribution of heat index during daytime. Finally, urban vegetation shows much weaker (similar to 1/6th as strong) associations with heat index than with surface temperature, which has broad implications for optimizing urban heat stress mitigation strategies. These findings are valid for operational metrics of heat stress for shaded conditions (apparent temperature and humidex), thermodynamic proxies (wet-bulb temperature), and empirical heat indices. Based on this large-scale empirical evidence, surface temperature, used due to the lack of better alternatives, may not be suitable for accurately informing heat mitigation strategies within and across cities, necessitating more urban-scale observations and better urban-resolving models.
Extreme Heat Events (EHE) are a major concern for many urban areas worldwide and are considered as one of the deadliest natural hazards globally. Climate change and socioeconomic trends (exposure and susceptibility) are expected to exacerbate the risk of urban heat stress. Several urban areas have recently declared a climate emergency and initiated the adaptation process, but progress is still patchy, uncoordinated, and of varied quality. The main constraint is the lack of mechanisms for monitoring and reporting adaptation strategies, not allowing the supervision and evaluation of the adaptation process. The EU-funded project U-ADAPT! (Urban-Adaptation) focuses on the concrete expression of adaptation to evaluate the current implementation and effectiveness of adaptation measures and strategies to reduce Heat Disaster Risk (HDR), moving the emphasis from the study of vulnerability, resilience, and potential adaptation (adaptation capacity) of communities to the actual depth and pace of the past and current adaptation process. In this article, we discuss the theoretical support and design of the project and set the base for next project stages, which ultimately aims to create a unique interdisciplinary framework and a replicable multidimensional indicator on adaptation to EHE that empower European Union citizens to demand a safe and sustainable environment and hold institutions accountable for the adaptation process to current and upcoming risks.
Urbanization and ongoing climate change increase the exposure of the populations to heat stress, and the urban heat island (UHI) effect may magnify heat-related mortality, especially during heatwaves. We studied temperature-related mortality in the city of Helsinki-with urban and suburban land uses-and in the surrounding Helsinki-Uusimaa hospital district (HUS-H, excluding Helsinki)-with more rural types of land uses-in southern Finland for two decades, 2000-2018. Dependence of the risk of daily all-cause deaths (all-age and 75+ years) on daily mean temperature was modelled using the distributed lag nonlinear model (DLNM). The modelled relationships were applied in assessing deaths attributable to four intensive heatwaves during the study period. The results showed that the heat-related mortality risk was substantially higher in Helsinki than in HUS-H, and the mortality rates attributable to four intensive heatwaves (2003, 2010, 2014 and 2018) were about 2.5 times higher in Helsinki than in HUS-H. Among the elderly, heat-related risks were also higher in Helsinki, while cold-related risks were higher in the surrounding region. The temperature ranges recorded in the fairly coarse resolution gridded datasets were not distinctly different in the two considered regions. It is therefore probable that the modelling underestimated the actual exposure to the heat stress in Helsinki. We also studied the modifying, short-term impact of air quality on the modelled temperature-mortality association in Helsinki; this effect was found to be small. We discuss a need for higher resolution data and modelling the UHI effect, and regional differences in vulnerability to thermal stress.
With climate change and socioeconomic trends expected to exacerbate the risk of urban heat stress, implementing adaptation measures is paramount to limit adverse impacts of heat on urban inhabitants. Identification of the best options needs to be based on sound, localised assessments of risk, understood as the interaction of hazard, exposure and vulnerability. Yet a review of the literature reveals that minimal research to date considers the perceived impacts of heat among urban residents. Based on a household survey in Bonn, Germany, this paper adopts an integrated approach to assess how different socioeconomic groups are affected by heat stress and explores the connections between perceived impacts of heat and indicators of exposure and vulnerability across groups. Results indicate that all socioeconomic groups are at risk of urban heat stress, though to differing extents and for different reasons. Exposure was found to be lowest in groups typically considered to be of higher risk, such as older respondents, who at the same time have the highest susceptibility. Students and other younger respondents, on the other hand, face comparably high exposure and have the lowest coping and adaptive capacities. At the same time, each group has its own capacities with the potential to mitigate risk. The study shows that urban inhabitants beyond “classic risk groups” usually addressed in literature and policy are affected by heat stress in ways that may not be accounted for in current urban policy.
Populations in high-density urban areas are exposed to higher levels of heat stress in comparison to rural areas. New spatially explicit approaches that identify highly exposed and vulnerable areas are needed to inform current urban planning practices to cope with heat hazards. This study proposes an extreme heat stress risk index for Dublin city across multiple decades (2020s-2050s) and for two representative concentration pathways (RCPs). In order to consider the interactions between greenhouse gas emissions and urban expansion, a climate-based urban land cover classification and a simple climate model have been combined to compute air temperature values accounting for urban heat island effect. This allowed the derivation of an improved hazard indicator in terms of extreme heat stress which, when integrated with information on current levels of vulnerability (i.e., socioeconomic factors assessed using principal component analysis (PCA), provides a heat hazard risk index for Dublin city at a fine spatial scale. Between the 2020s and 2050s, urban areas considered at highest risk are expected to increase by about 70% and 96% under RCP 4.5 and 8.5 respectively. For the 2050s, enhanced levels of heat risk under the RCP 8.5 scenario are particularly visible in the core city centre and in the northern and western suburbs. This study provides a valuable reference for decision makers for urban planning and provides an approach to help prioritise management decisions for the development of heat resilient and sustainable cities.
The mitigation of urban heat islands (UHIs) is crucial for promoting the sustainable development of urban areas. Geographic information systems (GISs) together with satellite-derived data are powerful tools for investigating the spatiotemporal distribution of UHIs. Depending on the availability of data and the geographic scale of the analysis, different methodologies can be adopted. Here, we show a complete open source GIS-based methodology based on satellite-driven data for investigating and mapping the impact of the UHI on the heat-related elderly risk (HERI) in the Functional Urban Area of Padua. Thermal anomalies in the territory were mapped by modelling satellite data from Sentinel-3. After a socio-demographic analysis, the HERI was mapped according to five levels of risk. The highest vulnerability levels were localised within the urban area and in three municipalities near Padua, which represent about 20% of the entire territory investigated. In these municipalities, a percentage of elderly people over 20%, a thermal anomaly over 2.4 degrees C, and a HERI over 0.65 were found. Based on these outputs, it is possible to define nature-based solutions for reducing the UHI phenomenon and promote a sustainable development of cities. Stakeholders can use the results of these investigations to define climate and environmental policies.
Remotely sensed Land Surface Temperature (LST) is widely used to characterize Surface Urban Heat Island (SUHI) intensity and spatial variability. SUHI may differ significantly from the Urban Heat Island (UHI), which is related to air temperature and is more representative of human wellbeing. The lack of information and results on UHI development is due to the difficulty in having measurements with high spatial density within the city and the uncertainties in finding relationships between air and surface temperatures. Characterizing UHI is fundamental when dealing with human thermal wellbeing especially when extreme events occur. A new index, named Urban Heatwave Thermal Index (UHTI), was presented here to quantify daytime air temperature variability patterns in an urban environment during a meteorological heatwave. UHTI integrates a) air temperature recorded by local sensors; b) structural microclimatic Envi-met fluidodynamic modeling simulations; and c) remotely sensed environmental indicators. UHTI is a reliable representation of thermal criticalities in the city for its inhabitants. A case study on Bologna (Italy) municipality is presented. Moreover, UHTI was calculated and compared with the Urban Thermal Field Variance Index (UTFVI), commonly used for urban climate character-ization. Results showed a high degree of correlation (R2 = 0.795) between the two indexes; re-sidual mapping and hot-spot detection indicated that their biggest differences are next to dense urban fabric areas like historical centers and water body areas.
The work describes diurnal meteorological and biometeorological conditions in June 2019 in the urban areas of Central Europe. UTCI, STI, Oh_H, WL, and OV indices were calculated based on 24-h data from Bydgoszcz (Poland) for hot days. The degree of risk connected with heat stress of different intensities, risk of hyperthermia, body water loss, and decreased oxygen volume was determined. The studies showed that June 2019 was an example of an extreme situation with a heatwave that generated high stress for the inhabitants of urban areas. The conditions were burdensome mostly due to “very strong” and “strong” heat stress and periodic risk of dehydration, situations that could quickly lead to overheating of the body and a decreased oxygen volume leading to stress.
The vast majority of studies on heat-related mortality are focused on large cities. The aim of this study is to fill this research gap and to estimate the impact of high temperatures on the risk of death in smaller towns and villages. The results show that increased mortality is not only a problem in large cities. The risk of death, although usually slightly lower than in highly populated areas, may be higher for the age-related risk group. At temperatures above 35 degrees C, it may exceed 1.3 in smaller towns and even 1.6 in villages. The increase in mortality during five selected heat waves of high intensity and long duration was also studied for two regions of Poland: Malopolska and Wielkopolska. Towns with a population of less than 10,000 in Malopolska region, during the 2006 heatwave, experienced an increase in the number of deaths by as much as 18%. At the same time in the largest city of Malopolska-Krakow, the death toll rose by 4%. This paper also presents some differences between regions in terms of the impact of heat waves: in the lowland region of Wielkopolska, the mortality rate is generally higher than in the upland region of Malopolska.
Although regulatory improvements for air quality in the European Union have been made, air pollution is still a pressing problem and, its impact on health, both mortality and morbidity, is a topic of intense research nowadays. The main goal of this work is to assess the impact of the exposure to air pollutants on the number of daily hospital admissions due to respiratory causes in 58 spatial locations of Portugal mainland, during the period 2005-2017. To this end, INteger Generalised AutoRegressive Conditional Heteroskedastic (INGARCH)-based models are extensively used. This family of models has proven to be very useful in the analysis of serially dependent count data. Such models include information on the past history of the time series, as well as the effect of external covariates. In particular, daily hospitalisation counts, air quality and temperature data are endowed within INGARCH models of optimal orders, where the automatic inclusion of the most significant covariates is carried out through a new block-forward procedure. The INGARCH approach is adequate to model the outcome variable (respiratory hospital admissions) and the covariates, which advocates for the use of count time series approaches in this setting. Results show that the past history of the count process carries very relevant information and that temperature is the most determinant covariate, among the analysed, for daily hospital respiratory admissions. It is important to stress that, despite the small variability explained by air quality, all models include on average, approximately two air pollutants covariates besides temperature. Further analysis shows that the one-step-ahead forecasts distributions are well separated into two clusters: one cluster includes locations exclusively in the Lisbon area (exhibiting higher number of one-step-ahead hospital admissions forecasts), while the other contains the remaining locations. This results highlights that special attention must be given to air quality in Lisbon metropolitan area in order to decrease the number of hospital admissions.
The urban microclimate is gradually changing due to climate change, extreme weather conditions, urbanization, and the heat island effect. In such an altered environment, outdoor thermal comfort can have a strong impact on public health and quality of life in urban areas. In this study, three main urban areas in Serbia were selected: Belgrade (Central Serbia), Novi Sad (Northern Serbia), and Nis (Southern Serbia). The focus was on the temporal assessment of OTC, using the UTCI over a period of 20 years (1999-2018) during different seasons. The main aim is the general estimation of the OTC of Belgrade, Novi Sad, and Nis, in order to gain better insight into the bioclimatic condition, current trends and anomalies that have occurred. The analysis was conducted based on an hourly (7 h, 14 h, and 21 h CET) and “day by day” meteorological data set. Findings show the presence of a growing trend in seasonal UTCI anomalies, especially during summer and spring. In addition, there is a notable increase in the number of days above the defined UTCI thresholds for each season. Average annual UTCIs values also show a positive, rising trend, ranging from 0.50 degrees C to 1.33 degrees C. The most significant deviations from the average UTCI values, both seasonal and annual, were recorded in 2000, 2007, 2012, 2015, 2017, and 2018.
The analysis of the bioclimatic conditions is becoming increasingly relevant in climate interpretations for human needs, particularly in spatial planning, tourism, public health, sports events, bio-prognosis, etc. In this context, our study presents general temporal bioclimatic conditions in Belgrade, defined based on the PET, mPET and UTCI heat budget indices. Monthly, seasonal and annual indices were analyzed for urban and suburban weather stations based on 43 annual sets of meteorological data obtained by hourly observations at 7 h and 14 h CET. This study aims to present the distribution of PET, mPET and UTCI indices to show the pattern of each index in a mild climate location and to examine annual and seasonal differences of each index in the Belgrade urban center and suburban part of the city. The study results indicate higher biothermal stress in the urban area compared to the suburban zone and that the indices are congruent during the summer. At the same time, during the winter, they are more difficult to compare due to their peculiarities becoming more noticeable. The results obtained of all mean monthly and mean annual values of all three indices clearly indicate the difference that follows the definition of the urban heat island (UHI), particularly those from morning observation and winter season. The UTCI index shows the most significant monthly, seasonal and annual difference between urban and suburban areas for both observations. The annual difference of ΔUTCI7h amounts to 1.5 °C is the same as the annual difference of minimum temperatures (Δtmin). In contrast, the annual differences of ΔPET7h ΔmPET7h are °smaller (0.8 °C and 0.7 °C) and closer to the annual differences of maximum temperatures Δtmax amounted of 0.6 °C.
BACKGROUND: In Spain, two synoptic-scale conditions influence heat wave formation. The first involves advection of warm and dry air masses carrying dust of Saharan origin (North African Dust (NAF) = 1). The second entails anticyclonic stagnation with high insolation and stability (NAF) = 0). Some studies show that the meteorological origin of these heat waves may affect their impact on morbidity and mortality. OBJECTIVE: To determine whether the impact of heat waves on health outcomes in Madrid (Spain) during 2013-2018 varied by synoptic-scale condition. METHODOLOGY: Outcome data consist of daily mortality and daily hospital emergency admissions (morbidity) for natural, circulatory, and respiratory causes. Predictors include daily maximum and minimum temperatures and daily mean concentrations of NO(2), PM(10), PM(2.5), NO(2), and O(3). Analyses adjust for insolation, relative humidity, and wind speed. Generalized linear models were performed with Poisson link between the variables controlling for trend, seasonality, and auto-regression in the series. Relative Risks (RR) and Attributable Risks (AR) were determined. The RRs for mortality attributable to high temperatures were similar regardless of NAF status. For hospital admissions, however, the RRs for hot days with NAF = 0 are higher than for days with NAF = 1. We also found that atmospheric pollutants worsen morbidity and mortality, especially PM(10) concentrations when NAF = 1 and O(3) concentrations when NAF = 0. RESULTS: The effect of heat waves on morbidity and mortality depends on the synoptic situation. The impact is greater under anticyclonic stagnation conditions than under Saharan dust advection. Further, the health impact of pollutants such as PM(10) and O(3) varies according to the synoptic situation. CONCLUSIONS: Based on these findings, we strongly recommend prevention plans to include data on the meteorological situation originating the heat wave, on a synoptic-scale, as well as comprehensive preventive measures against the compounding effect of high temperatures and pollution.
Previous research has found higher levels of heatwave mortality and morbidity among urban residents with a migration background because of their social, health and environmental conditions. The purpose of the study was to investigate and compare heat induced changes in the outdoor recreation behaviours of Turkish migrants with those of non-migrants on hot days in Vienna. Specifically, the study compared coping behaviours due to heat such as inter-area, intra-area, temporal and activity displacement between migrants and non-migrants. The study interviewed 400 migrants and non-migrants in four public green spaces of different area sizes and asked about their outdoor recreation motives and activities, as well as behavioural changes, due to summer heat. Results show that migrants have different motives for visiting urban green spaces on hot days, and that they visit these less frequently on hot days compared to non-migrants. While both groups shift their outdoor uses more to shady areas and the cooler times of the day, more migrants visit green spaces in the afternoon, perform more energetic recreational activities, and use sunnier sites more frequently than non-migrants on hot days. Few migrants and non-migrants stated that they would visit alternative green spaces when it is hot. The results indicate that migrants’ behaviours result in higher heat exposure, while making less use of the opportunities larger green spaces such as forests can provide for heat relief. Recommendations on how green and city planners could reduce heat related health risks for both study groups are presented.
Cities experience temperature differences during heat events, in part modulated by green spaces. In the face of climate change, vegetation and green infrastructure are increasingly important for residents’ thermal comfort. Generally, socio-economically marginalised communities are more likely to live in neighbourhoods with less access to green spaces, which can lead to the experience of hotter temperatures and higher incidences of poor health during heat-waves. Building on three bodies of literature – thermal inequity and green space planning, risk and vulnerability, and critical urban theory – an interdisciplinary approach was employed to understand residents’ perceptions of heat and vulnerability, and disparities in distribution of green space arising due to urban planning in Antwerp, Belgium. Using census data, a high and low-vulnerability district – Borgerhout and Wilrijk – were selected as case studies. Park audits and interviews were carried out to provide insights into parks’ cooling ability and residents’ potential responses to extreme heat. Results demonstrated an unequal distribution, access and quality of green spaces between inner-city Borgerhout and suburban Wilrijk, suggesting that lower-income, vulnerable residents are systematically disadvantaged by municipal green space planning. All Borgerhout interviewees described feeling too hot in summer, whilst the opposite held true for interviewees in Wilrijk. Results were situated within Antwerp planning documents to understand how neoliberalism and social exclusion drive and reproduce patterns of injustice, introducing the term heat injustice to describe entrenched injustice in green space distribution and corresponding resident perceptions, experiences of and vulnerabilities to heat within the city.
Intensive urbanization and global warming are impacting the health and well-being of urban population. Nevertheless, urban environments with different designs will have different micro and local climate conditions. This study used data from micrometeorological measurements performed in different urban spaces (downtown, urban park, riverside) in Banja Luka, Bosnia and Herzegovina, on hot summer days in June 2021. Air temperature, relative humidity, wind speed, and globe temperature were measured and Mean Radiant Temperature (Tmrt), Psychologically Equivalent Temperature (PET), and modified Psychologically Equivalent Temperature (mPET) were calculated for each location. Results show that the downtown is the most uncomfortable area in terms of the highest Ta, Tg, Tmrt, PET, and mPET values registered at this location. The urban park is the most comfortable area with the lowest values of Tg, Tmrt, PET, and mPET. Relative humidity is the highest at the riverside and the lowest in downtown. Furthermore, riverside had lower average Ta during summer daytime compared to urban park and downtown likely due to the synergy between river cooling effect (evaporation and sensible heat transfer) and tree shade.
Climate change at the regional and local levels is forcing strong implementation of urban adaptation strategies related to climate-conscious urbanization and public health. Accordingly, the application of parameters that assess thermal stress in urban areas, such as outdoor thermal comfort (OTC) indices, is of paramount importance. As a contribution to this statement, long-term (1961-2020) datasets of daily OTC indices for the city of Banja Luka (Bosnia and Hercegovina) were used. Detailed temporal analysis using Physiologically Equivalent Temperature (PET), Universal Thermal Climate Index (UTCI), and Mean Radiant Temperature (Tmrt) was performed for (a) the entire research period, (b) the decadal level, and (c) defined heat/cold stress subcategories. The results show an intensive increase in extreme/strong heat days in the last 20 years, and the number of these days is five times higher than in the’70 s and’80 s. Decreasing tendencies are noticed in extreme/strong cold days towards the last two decades.
Background The frequency and intensity of heatwaves are expected to increase in the coming years. To promote resilient cities, it is key to have insights in populations with low preparedness levels. This study investigated personal characteristics associated with heatwave-protective knowledge, and preferred information channels and sources on this topic in cities in Georgia. Methods We undertook a street survey among three large cities in Georgia, including the capital Tbilisi. We collected demographic, socio-economic, medical and behavioural characteristics as potential risk factors for reduced heatwave-protective knowledge. Furthermore, we asked respondents about information channels and sources they use and prefer to obtain information on heatwave-protective measures. Results Being male, parent of children under the age of 12 and having a lower educational level are risk factors for lower knowledge levels on heatwave protection. Being homemakers, retiree, having fasted and using medication are protective factors. Television and internet are the channels more often used for obtaining information on heatwave-protective measures, and people prefer to receive information on this topic from health authorities. Conclusion Our findings identified characteristics that make people more vulnerable to heatwaves, due to a reduced knowledge level on heatwave protection. Targeted communication towards these groups, using information sources and media specifically aimed at this target audience, could improve this.
As climate change progresses, it is causing more frequent and severe heat waves, resulting in higher indoor temperatures. Various temperature thresholds for indicating indoor overheating have been proposed in different contexts, extending from reduced comfort in buildings to subjective heat stress and onset of first or serious health problems. This study reviews these thresholds and identifies threshold values for subjective heat stress of occupants in the city of Augsburg, Germany, distinguishing between vulnerable and non-vulnerable households. Survey data from 427 private households are analysed using unpaired analysis of variances (ANOVA), t-tests and regression analysis to identify factors related to subjective heat stress at home during night-time. The findings imply that health implications during heat waves, age, local climate zones favouring the urban heat island effect and higher indoor temperature represent significant factors for subjective heat stress. A significant difference in subjective heat stress among different groups related to temperature could be identified for thresholds of 24.8 degrees C (people living alone) and 26.7 degrees C (people with chronic disease). As WHO threshold for health risk from overheating is 24 degrees C, people are apparently at heat-related risk without feeling that they are at risk, especially when they have chronic diseases; thus they may not see the urgency of taking adaptation measures.
Exposure to heat has a range of potential negative impacts on human health; hot weather may exacerbate cardiovascular and respiratory illness or lead to heat stroke and death. Urban populations are at increased risk due to the Urban Heat Island (UHI) effect (higher urban temperatures compared with rural ones). This has led to extensive investigation of the summertime UHI and its effects, whereas far less research focuses on the wintertime UHI. Exposure to low temperature also leads to a range of illnesses, and in fact, in the UK, annual cold-related mortality outweighs heat-related mortality. It is not clearly understood to what extent the wintertime UHI may protect against cold related mortality. In this study we quantify the UHI intensity in wintertime for a heavily urbanized UK region (West Midlands, including Birmingham) using a regional weather model, and for the first time, use a health impact assessment (HIA) to estimate the associated impact on cold-related mortality. We show that the population-weighted mean winter UHI intensity was +2.3 °C in Birmingham city center, and comparable with that of summer. Our results suggest a potential protective effect of the wintertime UHI, equivalent to 266 cold-related deaths avoided (~15% of total cold-related mortality over ~11 weeks). When including the impacts of climate change, our results suggest that the number of heat-related deaths associated with the summer UHI will increase from 96 (in 2006) to 221 in the 2080s, based on the RCP8.5 emissions pathway. The protective effect of the wintertime UHI is projected to increase only slightly from 266 cold-related deaths avoided in 2009 to 280 avoided in the 2080s. The different effects of the UHI in winter and summer should be considered when assessing interventions in the built environment for reducing summer urban heat, and our results suggest that the future burden of temperature-related mortality associated with the UHI is likely to increase in summer relative to winter.
In the context of dense urban environments and climate change, pedestrians’ thermal experience plays an increasingly significant role in people’s health and well-being. In this research, the authors combine the fields of architecture, climate-responsive design, and robotic fabrication with the goal of investigating strategies to improve outdoor thermal comfort for pedestrians in cities with frequent extreme heat events. Based on a case study in the city of Munich, this paper presents findings into the technological approaches and methods for location-specific climate-resilient brick facades using robotic assembly. To achieve this goal, different bricklaying patterns were investigated to create a self-shading effect and thus reduce solar radiation and ultimately achieve an improved thermal condition for pedestrians moving along urban facades at street level. Using computer-aided microclimate simulation, generic self-shading brick pattern designs were tailored to highly location-specific microclimate requirements. Robotic assembly technology was used to produce such tailored, non-standard brickwork facades. The results of this research led to a data-informed design process with a demonstrator object being realized at 1:1 scale with a height of 2 m and a length of 3 m using a collaborative robot on site. Thermal measurements on the built demonstrator provided indications of reduced surface temperatures despite high solar radiation and thus validated the location-specific self-shading effects according to solar radiation simulation.
BACKGROUND: Adapting the urban environment to heat is a public health priority in the context of climate change. Cities are now considering interventions on specific urban characteristics known to contribute to the urban heat island (UHI) such as vegetation and imperviousness. OBJECTIVES: To explore how these urban characteristics influence the temperature-mortality relationship in the Paris region. METHODS: We modeled the temperature-mortality relationship for the 1300 municipalities of the region from 1990 to 2015, while including an interaction with indicators that summarize the municipalities’ main urban characteristics. Four indicators were tested: lack of green spaces, lack of trees, proportion of impervious surface, and overexposed population to a potential night UHI. RESULTS: The shape of the temperature-mortality relationship was similar across all municipalities, but with a higher slope at the highest temperatures in municipalities with less green spaces, less trees, and more impervious soil. For instance, in Paris and its close suburbs, the relative risk associated with a temperature in the 99th percentile of the temperature distribution (compared to the 50th percentile) was 2.17 [IC95% 1.98:2.38] in municipalities with 40% of their surface covered by trees compared to 2.57 [IC 95% 2.47:2.68] in municipalities with only 3% of their surface covered by trees. DISCUSSION: A lack of vegetation and a high degree of imperviousness were associated with a higher risk of heat-related mortality in the Paris region. Therefore, we can assume that interventions targeting these characteristics could reduce the health impacts of extreme heat. Such interventions should be coupled with other initiatives such as protecting the most vulnerable and promoting appropriate behaviors.
Urbanization, environmental change and ageing are putting urban health at risk. In many cities, heat stress is projected to increase. Urban green spaces are considered as an important resource to strengthen the resilience of city dwellers. We conducted a questionnaire survey in two structurally distinct parks in Leipzig, Germany, on hot summer days in 2019. We assessed the respondents? activity patterns, satisfaction with the existing infrastructure, heat-related health impairment, changes in park use during heat waves and evaluation of the role of parks in coping with heat stress. We found that the old-grown, tree-rich park was used significantly more frequently for experiencing nature, while the newer, less tree-rich park developed on a former railway-brownfield site was used more often for socializing and having BBQs and picnics. Satisfaction with available drinking fountains and public toilets was generally low and satisfaction with lighting was assessed less satisfactory in the old-grown park. Safety was assessed as satisfactory in general but significantly less satisfactory by female respondents. The heat stress summary score indicating heat-related health impairment was significantly higher for participants in the newer park. A high share of respondents stated that they used parks during heat waves as frequently as usual in the summer (46 %), while some respondents stated that they adapted their park use behaviour (18 %), e.g., by coming later in the evening. Regarding the participants? responses about the role of parks under summer heat conditions, we matched 138 statements to several regulating and cultural ecosystem services, and we found cooling and recreation to be mentioned most often. We concluded that green space planning should diminish usage barriers, such as insufficient lighting and insufficient sanitary infrastructure, to ensure equal park use opportunities for all city dwellers. Specific local environmental and sociocultural conditions, changing environments and climate adaptation must be considered. To maintain ecological processes and functions and to cope with climate change, urban planning should preserve older parks with a large amount of tree coverage while respecting demands for particular built infrastructure.
For both tree-lined sidewalks of a shallow and deep E-W street canyon located in the city of Freiburg (Southwest Germany), the solar elevation impact on the magnitude of the daytime human heat stress mitigation (hhsm) is analysed in dependence of different tree scenarios. Identic ENVI-met simulations are carried out on the summer solstice day 21 June 2003 and heat wave day 4 August 2003. All simulation scenarios indicate an almost negligible solar elevation impact on hhsm in terms of spatiotemporal averaged air temperature. The results achieved on both simulation days for the spatiotemporal averaged mean radiation temperature (T-mrt) and physiologically equivalent temperature (PET) as well as spatially high-resolution PET reflect that the north-facing sidewalk in both street canyons is entirely shaded by the south-bounding building. Secondarily it is influenced by lower radiant flux densities from the trees near the curb edges of both sidewalks. On both simulation days, the south-facing sidewalk in the shallow street canyon is only shaded by the tree crowns. In the deep street canyon, however, the south-facing sidewalk is completely shaded on 4 August by the south-bounding building, while on 21 June this shade is limited to its southern half, i.e. its northern half is directly influenced by the shade of trees. Due to these shading conditions, the results focused on pedestrians on both sidewalks show different patterns of the solar elevation impact on T-mrt and PET as well as hhsm in terms of T-mrt and PET. While increasing tree crown projection areas lead to a lower solar elevation impact on T-mrt and PET, they cause a more distinct hhsm in terms of T-mrt and PET for higher solar elevations. The non-negligible magnitude of the solar elevation impact in all scenarios leads to the recommendation to carry out ensemble simulations in order to achieve T-mrt, PET, hhsm-T-mrt and hhsm-PET results, which are reliable for planning applications.
This paper analyses the probabilistic future behaviour of heat-waves (HWs) in the city of Madrid in the twenty-first century, using maximum daily temperatures from twenty-one climate circulation models under two representative concentration pathways (RCP 8.5 & RCP 4.5). HWs are modelled considering three factors: number per annum, duration and intensity, characterised by three stochastic processes: Poisson, Gamma and truncated Gaussian, respectively. Potential correlations between these processes are also considered. The probabilistic temperature behaviour is combined with an epidemiological model with stochastic mortality risk following a generalized extreme value distribution (gev). The objective of this study is to obtain probability distributions of mortality and risk measures such as the mean value of the 5% of worst cases in the 21st century, in particular from 2025 to 2100. Estimates from stochastic models for characterising HWs and epidemiological impacts on human health can vary from one climate model to another, so relying on a single climate model can be problematic. For this reason, the calculations are carried out for 21 models and the average of the results is obtained. A sensitivity adaptation analysis is also performed. Under RCP 8.5 for 2100 for Madrid city a mean excess of 3.6 °C over the 38 °C temperature threshold is expected as the average of all models, with an expected attributable mortality of 1614 people, but these figures may be substantially exceeded in some cases if the highest-risk cases occur.
Due to phenomena such as urban heat islands, outdoor thermal comfort of the cities’ residents emerges as a growing concern. A major challenge for mega-cities in changing climate is the design of urban spaces that ensure and promote pedestrian thermal comfort. Understanding pedestrian behavioural adaptation to urban thermal environments is critically important to attain this goal. Current research in pedestrian behaviour lacks controlled experimentation, which limits the quantitative modelling of such complex behaviour. Combining well-controlled experiments with human participants and computational methods inspired by behavioural ecology and decision theory, we examine the effect of sun exposure on route choice in a tropical city. We find that the distance walked in the shade is discounted by a factor of 0.86 compared to the distance walked in the sun, and that shadows cast by buildings have a stronger effect than trees. The discounting effect is mathematically formalised and thus allows quantification of the behaviour that can be used in understanding pedestrian behaviour in changing urban climates. The results highlight the importance of assessment of climate through human responses to it and point the way forward to explore scenarios to mitigate pedestrian heat stress.
Increases in the magnitude and frequency of climate and other disruptive factors are placing environmental, economic, and social stresses on coastal systems. This is further exacerbated by land use transformations, urbanization, over-tourism, sociopolitical tensions, technological innovations, among others. A scenario-informed multicriteria decision analysis (MCDA) was applied in the Metropolitan City of Venice integrating qualitative (i.e., local stakeholder preferences) and quantitative information (i.e., climate-change projections) with the aim of enhancing system resilience to multiple climate-related threats. As part of this analysis, different groups of local stakeholders (e.g., local authorities, civil protection agencies, SMEs, NGOs) were asked to identify critical functions that needs to be sustained. Various policy initiatives were considered to support these critical functions. The MCDA was used to rank the initiatives across several scenarios describing main climate threats (e.g., storm surges, floods, heatwaves, drought). We found that many climate change scenarios were considered to be disruptive to stakeholders and influence alternative ranking. The management alternatives acting on physical domain generally enhance resilience across just a few scenarios while cognitive and informative initiatives provided resilience enhancement across most scenarios considered. With uncertainty of multiple stressors along with projected climate variability, a portfolio of cognitive and physical initiatives is recommended to enhance resilience.
Background While many studies analyze the effect of extreme thermal events on health, little has been written about the effects of extreme cold on mortality. This scarcity of papers is particularly relevant when we search studies about extreme cold on the health of rural population. Therefore, we tried to analyze the effect of cold waves on urban areas and rural areas from Madrid and to test whether differentiated effects exist between both population classes. For this purpose, we analyzed data from the municipalities with over 10,000 inhabitants for the period from January 1, 2000 through December 31, 2013. Municipalities were classified as urban or rural (Eurostat), and they were grouped into similar climatological zones: Urban Metropolitan Centre (UMC), Rural Northern Mountains (RNM), Rural Centre (RC) and Southern Rural (SR). The dependent variable was the daily mortality rate due to natural causes per million inhabitants (CIE-X: A00-R99) that occurred between the months of November and March for the period. The independent variable was minimum daily temperature (oC) (T-min). Social and demographic contextual variables were used, including: population > age 64 (%), deprivation index and housing indicators. The analysis was carried out in three phases: (1) determination of the threshold temperature (T-threshold) which defines the cold waves; (2) determination of the relative risk (RR) for cold waves using Poisson linear regression (GLM); and (3) using GLM of the binomial family, Odds Ratios (OR) were calculated to analyze the relationship between the frequency of the appearance of cold waves and the socioeconomic variables. Results The UMC zone experienced 585 extreme cold events related to attributable increases in the mortality rate. The average number of cold waves in the rural zones was 319. The primary risk factor was the percentage of population over age 64, and the primary protective factor was housing rehabilitation. As a whole, the period experienced more cold waves (1542) than heat waves (1130). Conclusion The UMC was more vulnerable than the rural areas. Furthermore, the results support the development of prevention policies, especially considering the fact that cold wave events were more frequent than heat waves.
Human health can be negatively impacted by hot or cold weather, which often exacerbates respiratory or cardiovascular conditions and increases the risk of mortality. Urban populations are at particular increased risk of effects from heat due to the Urban Heat Island (UHI) effect (higher urban temperatures compared with rural ones). This has led to extensive investigation of the summertime UHI, its impacts on health, and also the consideration of interventions such as reflective ‘cool’ roofs to help reduce summertime overheating effects. However, interventions aimed at limiting summer heat are rarely evaluated for their effects in wintertime, and thus their overall annual net impact on temperature-related health effects are poorly understood. In this study we use a regional weather model to simulate the winter 2009/10 period for an urbanized region of the UK (Birmingham and the West Midlands), and use a health impact assessment to estimate the impact of reflective ‘cool’ roofs (an intervention usually aimed at reducing the UHI in summer) on cold-related mortality in winter. Cool roofs have been shown to be effective at reducing maximum temperatures during summertime. In contrast to the summer, we find that cool roofs have a minimal effect on ambient air temperatures in winter. Although the UHI in summertime can increase heat-related mortality, the wintertime UHI can have benefits to health, through avoided cold-related mortality. Our results highlight the potential annual net health benefits of implementing cool roofs to reduce temperature-related mortality in summer, without reducing the protective UHI effect in winter. Further, we suggest that benefits of cool roofs may increase in future, with a doubling of the number of heat-related deaths avoided by the 2080s (RCP8.5) compared to summer 2006, and with insignificant changes in the impact of cool-roofs on cold-related mortality. These results further support reflective ‘cool’ roof implementation strategies as effective interventions to protect health, both today and in future.
In light of climate change, health risks are expected to be exacerbated by more frequent high temperatures and reduced by less frequent cold extremes. To assess the impact of different climate change scenarios, it is necessary to describe the current effects of temperature on health. A time-stratified case-crossover design fitted with conditional quasi-Poisson regressions and distributed lag non-linear models was applied to estimate specific temperature-mortality associations in nine urban agglomerations in Belgium, and a random-effect meta-analysis was conducted to pool the estimates. Based on 307,859 all-cause natural deaths, the mortality risk associated to low temperature was 1.32 (95% CI: 1.21-1.44) and 1.21 (95% CI: 1.08-1.36) for high temperature relative to the minimum mortality temperature (23.1 °C). Both cold and heat were associated with an increased risk of cardiovascular and respiratory mortality. We observed differences in risk by age category, and women were more vulnerable to heat than men. People living in the most built-up municipalities were at higher risk for heat. Air pollutants did not have a confounding effect. Evidence from this study helps to identify specific populations at risk and is important for current and future public health interventions and prevention strategies.
Climate change and climate-sensitive disasters caused by climatic hazards have a significant and increasing direct and indirect impact on human health. Due to its vast area, complex geographical environment and various climatic conditions, Russia is one of the countries that suffers significantly from frequent climate hazards. This paper provides information about temperature extremes in Russia in the beginning of the 21st century, and their impact on human health. A literature search was conducted using the electronic databases Web of Science, Science Direct, Scopus, and e-Library, focusing on peer-reviewed Researchs published in English and in Russian from 2000 to 2021. The results are summarized in 16 studies, which are divided into location-based groups, including Moscow, Saint Petersburg and other large cities located in various climatic zones: in the Arctic, in Siberia and in the southern regions, in ultra-continental and monsoon climate. Heat waves in cities with a temperate continental climate lead to a significant increase in all-cause mortality than cold waves, compared with cities in other climatic zones. At the same time, in northern cities, in contrast to the southern regions and central Siberia, the influence of cold waves is more pronounced on mortality than heat waves. To adequately protect the population from the effects of temperature waves and to carry out preventive measures, it is necessary to know specific threshold values of air temperature in each city.
New gridded climate datasets (GCDs) on spatially resolved modeled weather data have recently been released to explore the impacts of climate change. GCDs have been suggested as potential alternatives to weather station data in epidemiological assessments on health impacts of temperature and climate change. These can be particularly useful for assessment in regions that have remained understudied due to limited or low quality weather station data. However to date, no study has critically evaluated the application of GCDs of variable spatial resolution in temperature-mortality assessments across regions of different orography, climate, and size. Here we explored the performance of population-weighted daily mean temperature data from the global ERA5 reanalysis dataset in the 10 regions in the United Kingdom and the 26 cantons in Switzerland, combined with two local high-resolution GCDs (HadUK-grid UKPOC-9 and MeteoSwiss-grid-product, respectively) and compared these to weather station data and unweighted homologous series. We applied quasi-Poisson time series regression with distributed lag nonlinear models to obtain the GCD- and region-specific temperature-mortality associations and calculated the corresponding cold- and heat-related excess mortality. Although the five exposure datasets yielded different average area-level temperature estimates, these deviations did not result in substantial variations in the temperature-mortality association or impacts. Moreover, local population-weighted GCDs showed better overall performance, suggesting that they could be excellent alternatives to help advance knowledge on climate change impacts in remote regions with large climate and population distribution variability, which has remained largely unexplored in present literature due to the lack of reliable exposure data.
BACKGROUND: To date, little is known about the temporal variation of the temperature-mortality association among different demographic and socio-economic groups. The aim of this work is to investigate trends in cold- and heat- attributable mortality risk and burden by sex, age, education, marital status, and number of household occupants in the city of Turin, Italy. METHODS: We collected daily time-series of temperature and mortality counts by demographic and socio-economic groups for the period 1982-2018 in Turin. We applied standard quasi-Poisson regression models to data subsets of 25-year moving subperiods, and we estimated the temperature-mortality associations with distributed lag non-linear models (DLNM). We provided cross-linkages between the evolution of minimum mortality temperatures, relative risks of mortality and temperature-attributable deaths under cold and hot conditions. RESULTS: Our findings highlighted an overall increase in risk trends under cold and heat conditions. All-cause mortality at the 1st percentile increased from 1.15 (95% CI: 1.04; 1.28) in 1982-2006 to 1.24 (95% CI: 1.11; 1.38) in 1994-2018, while at the 99th percentile the risk shifted from 1.51 (95% CI: 1.41; 1.61) to 1.59 (95% CI: 1.49; 1.71). In relation to social differences, women were characterized by greater values in respect to men, and similar estimates were observed among the elderly in respect to the youngest subgroup. Risk trends by educational subgroups were mixed, according to the reference temperature condition. Finally, individuals living in conditions of isolation were characterized by higher risks, with an increasing vulnerability throughout time. CONCLUSIONS: The overall increase in cold- and heat- related mortality risk suggests a maladaptation to ambient temperatures in Turin. Despite alert systems in place increase public awareness and improve the efficiency of existing health services at the local level, they do not necessarily prevent risks in a homogeneous way. Targeted public health responses to cold and heat in Turin are urgently needed to adapt to extreme temperatures due to climate change.
Using novel weekly mortality data for London spanning 1866-1965, we analyze the changing relationship between temperature and mortality as the city developed. Our main results show that warm weeks led to elevated mortality in the late nineteenth century, mainly due to infant deaths from digestive diseases. However, this pattern largely disappeared after WWI as infant digestive diseases became less prevalent. The resulting change in the temperature-mortality relationship meant that thousands of heat-related deaths-equal to 0.9-1.4 percent of all deaths- were averted. These findings show that improving the disease environment can dramatically alter the impact of high temperature on mortality.
The Asian tiger mosquito (Aedes albopictus), a vector of dengue, Zika and other diseases, was introduced in Europe in the 1970s, where it is still widening its range. Spurred by public health concerns, several studies have delivered predictions of the current and future distribution of the species for this region, often with differing results. We provide the first joint analysis of these predictions, to identify consensus hotspots of high and low suitability, as well as areas with high uncertainty. The analysis focused on current and future climate conditions and was carried out for the whole of Europe and for 65 major urban areas. High consensus on current suitability was found for the northwest of the Iberian Peninsula, southern France, Italy and the coastline between the western Balkans and Greece. Most models also agree on a substantial future expansion of suitable areas into northern and eastern Europe. About 83% of urban areas are expected to become suitable in the future, in contrast with ~ 49% nowadays. Our findings show that previous research is congruent in identifying wide suitable areas for Aedes albopictus across Europe and in the need to effectively account for climate change in managing and preventing its future spread.
This study aimed to estimate dynamic changes in seroprevalence of Toxoplasma gondii within the general population living in the northern part of the Republic of Serbia (Province of Vojvodina) during a 14-year period. The differences in prevalence of anti-toxoplasma antibodies were analyzed in correlation with age, gender, residential area (rural/urban) and meteorological factors. In this cohort retrospective study, 24,440 subjects between 1 and 88 years old were enrolled. To determine the presence of T. gondii-specific IgM and IgG antibodies in serum samples, commercially available ELISA kits were used (Euroimmun, Luebeck, Germany). During the study period, the overall T. gondii seroprevalence was 23.5%. The seroprevalence continuously decreased over time from 31.7% in 2008 to 20.4% in 2021 (0.81% per year, p < 0.001). Approximately 2% of patients had a serologic profile positive for both anti-Toxoplasma IgG and IgM antibodies. The seroprevalence was higher (28.87%) among men compared to women (24.28%), while urban residents (24.94%) had lower seroprevalence than the rural population (28.17%). A statistically significant negative correlation (r = -0.559) was found between serologic profile of patients positive for both T. gondii IgG and IgM antibodies and the annual mean air temperature. No significant association was observed between seropositivity to T. gondii infection and examined meteorological factors. These data could be useful to national and regional health authorities to create an optimal health policy to reduce rate of T. gondii infections.
Compared to soil or aquatic ecosystems, the atmosphere is still an underexplored environment for microbial diversity. In this study, we surveyed the composition, variability and sources of microbes (bacteria and fungi) in the near surface atmosphere of a highly populated area, spanning ~ 4,000 Km(2) around the city center of Madrid (Spain), in different seasonal periods along two years. We found a core of abundant bacterial genera robust across space and time, most of soil origin, while fungi were more sensitive to environmental conditions. Microbial communities showed clear seasonal patterns driven by variability of environmental factors, mainly temperature and accumulated rain, while local sources played a minor role. We also identified taxa in both groups characteristic of seasonal periods, but not of specific sampling sites or plant coverage. The present study suggests that the near surface atmosphere of urban environments contains an ecosystem stable across relatively large spatial and temporal scales, with a rather homogenous composition, modulated by climatic variations. As such, it contributes to our understanding of the long-term changes associated to the human exposome in the air of highly populated areas.
During the ongoing global COVID-19 pandemic disease, like several countries, Romania experienced a multiwaves pattern over more than two years. The spreading pattern of SARS-CoV-2 pathogens in the Bucharest, capital of Romania is a multi-factorial process involving among other factors outdoor environmental variables and viral inactivation. Through descriptive statistics and cross-correlation analysis applied to daily time series of observational and geospatial data, this study aims to evaluate the synergy of COVID-19 incidence and lethality with air pollution and radon under different climate conditions, which may exacerbate the coronavirus’ effect on human health. During the entire analyzed period 1 January 2020-21 December 2021, for each of the four COVID-19 waves were recorded different anomalous anticyclonic synoptic meteorological patterns in the mid-troposphere, and favorable stability conditions during fall-early winter seasons for COVID-19 disease fast-spreading, mostly during the second, and the fourth waves. As the temporal pattern of airborne SARS-CoV-2 and its mutagen variants is affected by seasonal variability of the main air pollutants and climate parameters, this paper found: 1) the daily outdoor exposures to air pollutants (particulate matter PM2.5 and PM10, nitrogen dioxide-NO(2), sulfur dioxide-SO(2), carbon monoxide-CO) and radon – (222)Rn, are directly correlated with the daily COVID-19 incidence and mortality, and may contribute to the spread and the severity of the pandemic; 2) the daily ground ozone-O(3) levels, air temperature, Planetary Boundary Layer height, and surface solar irradiance are anticorrelated with the daily new COVID-19 incidence and deaths, averageingful for spring-summer periods. Outdoor exposure to ambient air pollution associated with radon is a non-negligible driver of COVID-19 transmission in large metropolitan areas, and climate variables are risk factors in spreading the viral infection. The findings of this study provide useful information for public health authorities and decision-makers to develop future pandemic diseases strategies in high polluted metropolitan environments.
Climate extremes affected cities and their populations during the last decades. Future climate projections indicate climate extremes will increasingly impact urban areas during the 21st century. Humidity related fluctuations and extremes directly underpin convective processes, as well as can influence human health conditions. Regional climate models are a powerful tool to understand regional-to-local climate change processes for cities and their surroundings. Convection-permitting regional climate models, operating on very high resolutions, indicate improved simulation of convective extremes, particularly on sub-daily timescales and in regions with complex terrain such as cities. This research aims to understand how crossing spatial resolutions from similar to 12.5 km to similar to 3 km grid size affect humidity extremes and related variables under future climate change for urban areas and its surroundings. Taking Berlin and its surroundings as the case study area, the research identifies two categories of unprecedented future extreme atmospheric humidity conditions happening under 1.5 degrees C and 2.0 degrees C mean warming based on statistical distributions, respectively near surface specific humidity >0.02 kg/kg and near surface relative humidity <30%. Two example cases for each future extreme condition are dynamically downscaled for a two months period from the 0.44 degrees horizontal resolution following a double-nesting approach: first to the 0.11 degrees (similar to 12.5 km) horizontal resolution with the regional climate model REMO and thereafter to the 0.0275 degrees (similar to 3 km) horizontal resolution with the non-hydrostatic version of REMO. The findings show that crossing spatial resolutions from similar to 12.5 km to similar to 3 km grid size affects humidity extremes and related variables under climate change. Generally, a stronger decrease in moisture (up to 0.0007-0.005 kg/kg SH and 10-20% RH) and an increase in temperature (1-2 degrees C) is found on the 0.0275 degrees compared to the 0.11 degrees horizontal resolution, which is more profound in Berlin than in the surroundings. The convection-permitting scale mitigates the specific humidity moist extreme and intensifies the relative humidity dry extreme in Berlin, posing challenges with respect to health for urban dwellers.
Urban Built Environments (UBE) are increasingly prone to SLow-Onset Disasters (SLODs) such as air pollution and heatwaves. The effectiveness of sustainable risk-mitigation solutions for the exposed individuals’ health should be defined by considering the effective scenarios in which emergency conditions can appear. Combining environmental (including climatic) conditions and exposed users’ presence and behaviors is a paramount task to support decision-makers in risk assessment. A clear definition of input scenarios and related critical conditions to be analyzed is needed, especially while applying simulation-based approaches. This work provides a methodology to fill this gap, based on hazard and exposure peaks identification. Quick and remote data-collection is adopted to speed up the process and promote the method application by low-trained specialists. Results firstly trace critical conditions by overlapping air pollution and heatwaves occurrence in the UBE. Exposure peaks (identified by remote analyses on the intended use of UBEs) are then merged to retrieve critical conditions due to the presence of the individuals over time and UBE spaces. The application to a significant case study (UBE in Milan, Italy) demonstrates the approach capabilities to identify key input scenarios for future human behavior simulation activities from a user-centered approach.
Ragweed pollen is an important component of biological pollution in the urban environment, responsible for increasing respiratory allergies and significant contribution to the health impact of air pollution in the Bucharest area. The aim of this paper is to present the eight-year ragweed pollen monitoring data from Bucharest, to place them in the context of local air pollution, public health regulations and available data on the health impact of ragweed pollen in the urban environment. Our pollen data were correlated with major air pollutant concentrations and with meteorological factors in a recently published local paper and the clinical data of patients with ragweed-induced respiratory symptoms were collected and published in 2019. The ragweed pollen monitoring data, correlated with field data reported by patients and plant specialists confirm the rapid spread of Ambrosia in the Bucharest city area, in addition to some stringent environmental local problems due to air pollution. The number of patients addressed to allergists almost doubled from one year to another, confirming the real alarming health impact of this environmental hazard. Our study confirms the need for more coherent strategies to control ragweed spread, based on application of existing local and international regulations, air pollution control and evaluation of consequences on human health.
Pollen grains emitted by urban vegetation are the main primary biological airborne particles (PBAPs) which alter the biological quality of urban air and have a significant impact on human health. This work analyses the interactions which exist between pollen-type PBAPs, meteorological variables, and air pollutants in the urban atmosphere so that the complex relationships and trends in future scenarios of changing environmental conditions can be assessed. For this study, the 1992-2018 pollen data series from the city of Granada (southeast Spain) was used, in which the dynamics of the total pollen as well as the 8 main pollen types (Cupressaceae, Olea, Pinus, Platanus, Poaceae, Populus, Quercus and Urticaceae) were analysed. The trend analysis showed that all except Urticaceae trended upward throughout the series. Spearman’s correlations with meteorological variables showed that, in general, the most influential variables on the pollen concentrations were the daily maximum temperature, relative humidity, water vapor pressure, global radiation, and insolation, with different effects on different pollen types. Parallel analysis by neural networks (ANN) confirmed these variables as the predominant ones, especially global radiation. The correlation with atmospheric pollutants revealed that ozone was the pollutant with the highest influence, although some pollen types also showed correlation with NO(2), SO(2), CO and PM(10). The Generalized Linear Models (GLM) between pollen and pollutants also indicated O(3) as the most prominent variable. These results highlight the active role that pollen-type PBAPs have on urban air quality by establishing their interactions with meteorological variables and pollutants, thereby providing information on the behaviour of pollen emissions under changing environmental conditions.
The London plane tree is frequently used in gardens, parks, and avenues in European urban areas for ornamental purposes with the aim to provide shade, and given its tolerance to atmospheric pollution. Nevertheless, unfortunately, over recent decades, bioaerosols such as Platanus pollen grains cause increasing human health problems such as allergies or respiratory tract infections. An aerobiological sampling of airborne Platanus pollen and Pla a 1 allergen was performed using two volumetric traps placed on the roof of the Science Faculty building of the city of Ourense from 2009 to 2020. A volumetric sampler Hirst-type Lanzoni VPPS 2000 (Lanzoni s.r.l. Bologna, Italy) was used for pollen sampling. Pla a 1 aeroallergen was sampled by using a Burkard Multi-Vial Cyclone Sampler (Burkard Manufacturing Co., Ltd., Hertfordshire, UK) and by means of the enzyme-linked immunosorbent assay (ELISA) technique. Data mining algorithms, C5.0 decision trees, and rule-based models were assessed to evaluate the effects of the main meteorological factors in the pollen or allergen concentrations. Plane trees bloom in late winter and spring months in the Northwestern Spain area. Regarding the trends of the parameters that define the Platanus pollen season, the allergen values fitted the concentrations of pollen in the air in most cases. In addition, it was observed that a decrease in maximum temperatures causes a descent in both pollen and allergen concentrations. However, the presence of precipitations only increases the level of allergens. When the risk of allergy symptomatology was jointly assessed for both the concentration of pollen and allergens in the study area, the number of days with moderate and high risk for pollen allergy in sensitive people increased with respect to traditional alerts considering only the pollen values.
Associated with rapid urbanization and escalation of bushfire events, Sydney has experienced significant air quality degradation in the XXI century. In this study, we present a 15-year retrospective analysis on the influence of individual meteorological factors on major air pollutants (NO(2), O(3), PM(10) and PM(2.5)) at 14 different sites in Greater Sydney and Illawarra. By applying a newly developed “zooming in” approach to long-term ground-based data, we disclose general, seasonal, daily and hourly patterns while increasing the level of spatial associativity. We provide evidence on the pivotal role played by urbanization, sprawling dynamics, global warming and bushfires on local meteorology and air pollution. We strike associations between temperature and O(3), both as average trends and extremes, on account of increasing heat island effects. The role of wind in a coastal-basin environment, influenced by a vast desert biome inland, is investigated. A steady trend towards stagnation is outlined, boosted by enhanced urban roughness and intensified heat island circulation. Relative humidity is also crucial in the modulation between NO(2) and O(3). With a sharp tendency towards drier and hotter microclimates, NO(2) levels dropped by approximately 50% over the years at all locations, while O(3)’s median levels almost doubled in the last 10 years. Further, O(3) and PMs shifted towards more frequent extreme events, strongly associated with the exacerbation of bushfire events. Such results suggest an urgent need to prioritize emission control, building air tightness improvement and urban heat mitigation, towards a future-proof governance in Sydney and similar regions in the world.
BACKGROUND: The associations between ambient temperatures and stroke are still uncertain, although they have been widely studied. Furthermore, the impact of latitudes or climate zones on these associations is still controversial. The Tropic of Cancer passes through the middle of Taiwan and divides it into subtropical and tropical areas. Therefore, the Taiwan National Health Insurance Database can be used to study the influence of latitudes on the association between ambient temperature and stroke events. METHODS: In this study, we retrieved daily stroke events from 2010 to 2015 in the New Taipei and Taipei Cities (the subtropical areas) and Kaohsiung City (the tropical area) from the National Health Insurance Research Database. Overall, 70,338 and 125,163 stroke events, including ischemic stroke and intracerebral hemorrhage, in Kaohsiung City and the Taipei Area were retrieved from the database, respectively. We also collected daily mean temperatures from the Taipei and Kaohsiung weather stations during the same period. The data were decomposed by ensemble empirical mode decomposition (EEMD) into several intrinsic mode functions (IMFs). There were consistent 6-period IMFs with intervals around 360 days in most decomposed data. Spearman’s rank correlation test showed moderate-to-strong correlations between the relevant IMFs of daily temperatures and events of stroke in both areas, which were higher in the northern area compared with those in the southern area. CONCLUSIONS: EEMD is a useful tool to demonstrate the regularity of stroke events and their associations with dynamic changes of the ambient temperature. Our results clearly demonstrate the temporal association between the ambient temperature and daily events of ischemic stroke and intracranial hemorrhage. It will contribute to planning a healthcare system for stroke seasonally. Further well-designed prospective studies are needed to elucidate the meaning of these associations.
A substantial number of studies have demonstrated the association between air pollution and adverse health effects. However, few studies have explored the potential interactive effects between meteorological factors and air pollution. This study attempted to evaluate the interactive effects between meteorological factors (temperature and relative humidity) and air pollution ([Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text]) on cardiovascular diseases (CVDs). Next, the high-risk population susceptible to air pollution was identified. We collected daily counts of CVD hospitalizations, air pollution, and weather data in Nanning from January 1, 2014, to December 31, 2015. Generalized additive models (GAMs) with interaction terms were adopted to estimate the interactive effects of air pollution and meteorological factors on CVD after controlling for seasonality, day of the week, and public holidays. On low-temperature days, an increase of [Formula: see text] in [Formula: see text], [Formula: see text], and [Formula: see text] was associated with increases of 4.31% (2.39%, 6.26%) at lag 2; 2.74% (1.65%, 3.84%) at lag 0-2; and 0.13% (0.02%, 0.23%) at lag 0-3 in CVD hospitalizations, respectively. During low relative humidity days, a [Formula: see text] increment of lag 0-3 exposure was associated with increases of 3.43% (4.61%, 2.67%) and 0.10% (0.04%, 0.15%) for [Formula: see text] and [Formula: see text], respectively. On high relative humidity days, an increase of [Formula: see text] in [Formula: see text] was associated with an increase of 5.86% (1.82%, 10.07%) at lag 0-2 in CVD hospitalizations. Moreover, elderly (≥ 65 years) and female patients were vulnerable to the effects of air pollution. There were interactive effects between air pollutants and meteorological factors on CVD hospitalizations. The risk that [Formula: see text], [Formula: see text], and [Formula: see text] posed to CVD hospitalizations could be significantly enhanced by low temperatures. For [Formula: see text] and [Formula: see text], CVD hospitalization risk increased in low relative humidity. The effects of [Formula: see text] were enhanced at high relative humidity.
Background: The impacts of temperature variability on cardiac autonomic function remain unclear. Objective: To explore the short-term associations between daily temperature variability and parameters of heart rate variability (HRV). Methods: This is a repeated-measure study among 78 eligible participants in Shanghai, China. We defined temperature variability as diurnal temperature range (DTR), the standard-deviation of temperature (SDT) and temperature variability (TV). We evaluated 3 frequency-domain HRV parameters (VLF, LF and HF) and 4 time domain parameters (SDNN, SDANN, rMSSD and pNN50). We used linear mixed-effect models to analyze the data after controlling for environmental and individual confounders. Results: Temperature variability was significantly associated with decreased HRV, especially on the concurrent day. The exposure-response relationships were almost inversely linear for most parameters. Every one inter quartile range (IQR) increase of DTR was associated with a decrease of 3.92% for VLF, 6.99% for LF, 5.88% for HF, 3.94% for rMSSD and 1.30% for pNN50. Each IQR increase of SDT was associated with a decline of 6.48% for LF, 5.91% for HF, 4.26% for rMSSD and 1.87% for pNN50. Every IQR increase of SDT was associated with a decrease of 4.39% for VLF, 7.67% for LF, 6.52% for HF, 3.22% for SDNN, 2.98% for SDANN, 4.05% for rMSSD, and 1.41% for pNN50. The decrements in HRV associated with temperature variability were more prominent in females. Conclusion: Temperature variability on the concurrent day could significantly decrease cardiac autonomic function, especially in females.
Building envelopes are a key element of green building design due to the immense amount of building energy and consumables. However, the quantitative evaluation of the embodied environmental impact of the envelope structure in green buildings is limited. This study aims to minimize the embodied environmental impact of the envelope structure. First, the types of embodied environmental impacts are classified into 12 categories (global warming, ozone depletion, eutrophication, smog, acidification, criteria air pollutants, indoor air quality, human health, ecotoxicity, habitat alteration, water intake, and fossil fuel combustion) using the causal network method and the equivalent factor method. Second, a quantitative model for evaluating the embodied environmental impact is developed based on the distance-to-target approach. Third, a green building in Jiangsu Province, China, is used as a case to form a green building envelope technology checklist by considering building envelope design principles. Building for Environment and Economic Sustainability (BEES) software is used to calculate the life cycle environmental impact inventory and embodied environmental impact. Furthermore, C# programming language is used to select 25 green building envelope packages with minimal environmental impact. This study offers an indepth understanding of the embodied environmental impact of green building envelope. The developed model not only calculates the accurate embodied environmental impact of green building but also provides an effective platform for identifying and determining the best building envelope structure to minimize the environmental impact of green buildings.
INTRODUCTION: It has been demonstrated that weather conditions have significant impacts on freeway safety. However, when employing an econometric model to examine freeway crash injury severity, most of the existing studies tend to categorize several different adverse weather conditions such as rainy, snowy, and windy conditions into one category, “adverse weather,” which might lead to a large amount of information loss and estimation bias. Hence, to overcome this issue, real-time weather data, the value of meteorological elements when crashes occurred, are incorporated into the dataset for freeway crash injury analysis in this study. METHODS: Due to the possible existence of spatial correlations in freeway crash injury data, this study presents a new method, the spatial multinomial logit (SMNL) model, to consider the spatial effects in the framework of the multinomial logit (MNL) model. In the SMNL model, the Gaussian conditional autoregressive (CAR) prior is adopted to capture the spatial correlation. In this study, the model results of the SMNL model are compared with the model results of the traditional multinomial logit (MNL) model. In addition, Bayesian inference is adopted to estimate the parameters of these two models. RESULT: The result of the SMNL model shows the significance of the spatial terms, which demonstrates the existence of spatial correlation. In addition, the SMNL model has a better model fitting ability than the MNL model. Through the parameter estimate results, risk factors such as vertical grade, visibility, emergency medical services (EMS) response time, and vehicle type have significant effects on freeway injury severity. Practical Application: According to the results, corresponding countermeasures for freeway roadway design, traffic management, and vehicle design are proposed to improve freeway safety. For example, steep slopes should be avoided if possible, and in-lane rumble strips should be recommended for steep down-slope segments. Besides, traffic volume proportion of large vehicles should be limited when the wind speed exceeds a certain grade.
Delivery of automatic electrical defibrillator (AED) by unmanned aerial vehicle (UAV) was suggested for out-of-hospital cardiac arrest (OHCA). The goal of this study is to assess the effect of topographic and weather conditions on call to AED attach time by UAV-AED. We included OHCA patients from 2013 to 2016 in Seoul, South Korea. We developed a UAV-AED flight simulator using topographic information of Seoul for Euclidean and topographic flight pathway including vertical flight to overcome high-rise structures. We used 4 kinds of UAV flight scenarios according to weather conditions or visibility. Primary outcome was emergency medical service (EMS) call to AED attach time. Secondary outcome was pre-arrival rate of UAV-AED before current EMS based AED delivery. Call to AED attach time in topographic pathway was 7.0 min in flight and control advanced UAV and 8.0 min in basic UAV model. Pre-arrival rate in Euclidean pathway was 38.0% and 16.3% for flight and control advanced UAV and basic UAV. Pre-arrival rate in the topographic pathway was 27.0% and 11.7%, respectively. UAV-AED topographic flight took longer call to AED attach time than Euclidean pathway. Pre-arrival rate of flight and control advanced UAV was decreased in topographic flight pathway compared to Euclidean pathway.
With global warming and rapid urban growth, cities get warmer, which poses additional stress on human thermal comfort and health. Complex three-dimensional (3D) urban forms change radiation fluxes and shade patterns in cities, but most studies that link urban form to thermal exposure have traditionally investigated the horizontal, two-dimensional composition and configuration of urban landscapes. Supported by high-precision airborne LiDAR data and IKONOS satellite data, this study calculates 3D urban landscape metrics for central Nanjing, China, including vegetation above ground biomass (AGB), building volume (V-B), standard deviation of building and vegetation heights (HSDB, HSDV), the building normalized compactness radio (nCR), sky view factor (SVF), surface roughness (SR), and shadow patterns (SP). Diurnal hourly mean radiant temperature (T-mrt) is simulated using the UMEP (Urban Multi-scale Environmental Predictor) tool forced with fixed-point observation data for a typical hot summer day. Correlation and multiple regression analyses are conducted to investigate the relationship between the 3D form metrics and T-mrt and to identify key factors that influence the thermal environment. T-mrt varies spatially and diurnally and is strongly related to SP during the day, revealing the importance of solar access for modulating the thermal environment. AGB is negatively, but SVF, SP, and building nCR are positively correlated with daytime T-mrt. At night, T-mrt is more homogeneous across space and mainly impacted by the urban fabric’s ability to lose heat. Open areas cool faster than areas with low SVF and complex urban forms with high building nCR. Findings from this study have great scientific and practical significance for optimizing urban landscape patterns from a human-centered heat exposure perspective and will guide planning and design strategies to promote thermally comfortable urban environments.
BACKGROUND: Although mounting evidence has associated air pollution and environmental temperature with children’s health problems, it is unclear whether there is an interaction between these factors on childhood asthma. OBJECTIVES: To explore the effects of temperature-pollution interactions during pre- and post-natal periods on asthma among pre-schoolers. METHODS: A retrospective cohort study of 39,782 pre-schoolers was performed during 2010-2012, in seven cities in China. Exposure to three temperature indicators (TI) and three critical ambient air pollutants, including particulate matter with aerodynamic diameter ≤ 10 μm (PM(10)), sulfur dioxide (SO(2)) and nitrogen dioxide (NO(2)) as proxies of industrial and vehicular air pollution, was estimated by an inverse distance weighted (IDW) method. Two-level logistical regression analysis was used to examine the association between both pre- and post-natal exposure and childhood asthma in terms of odds ratio (OR) and 95 % confidence interval (CI). RESULTS: Asthma prevalence in pre-schoolers at age of 3-6 years (6.9 %) was significantly associated with traffic-related air pollutant (NO(2)) exposure, with ORs (95 % CI) of 1.17 (1.06, 1.28), 1.19 (1.05-1.34) and 1.16 (1.03-1.31) for an IQR increase in NO(2) exposure during lifetime, pregnancy, and entire postnatal period respectively. Furthermore, childhood asthma was positively associated with exposure to increased temperature during lifetime, pregnancy, and entire postnatal period with ORs (95 % CI) = 1.89 (1.66, 2.16), 1.47 (1.34, 1.61), and 1.15 (1.11, 1.18) respectively, while was negatively associated with decreased temperatures. Childhood asthma was positively related with exposure to extreme heat days (EHD) during postnatal period particularly in first year of life respectively with ORs (95 % CI) = 1.23 (1.04, 1.46) and 1.26 (1.07, 1.47), but was not related with extreme cold days (ECD) exposure. A combination of high air pollutant levels and high temperatures significantly increased the risk of asthma during both pre- and post-natal periods. Strikingly, we found a significantly positive interaction of temperature and PM(10) or SO(2) on asthma risk among boys and younger children. CONCLUSIONS: Prenatal and postnatal exposure to ambient air pollution and high temperatures are independently and jointly associated with asthma risk in early childhood.
BACKGROUND: Several studies have shown the health effects of air pollutants, especially in China, North American and Western European countries. But longitudinal cohort studies focused on health effects of long-term air pollution exposure are still limited in Southeast Asian countries where sources of air pollution, weather conditions, and demographic characteristics are different. The present study examined the association between long-term exposure to air pollution and self-reported morbidities in participants of the Thai cohort study (TCS) in Bangkok metropolitan region (BMR), Thailand. METHODS: This longitudinal cohort study was conducted for 9 years from 2005 to 2013. Self-reported morbidities in this study included high blood pressure, high blood cholesterol, and diabetes. Air pollution data were obtained from the Thai government Pollution Control Department (PCD). Particles with diameters ≤10 μm (PM(10)), sulfur dioxide (SO(2)), nitrogen dioxide (NO(2)), ozone (O(3)), and carbon monoxide (CO) exposures were estimated with ordinary kriging method using 22 background and 7 traffic monitoring stations in BMR during 2005-2013. Long-term exposure periods to air pollution for each subject was averaged as the same period of person-time. Cox proportional hazards models were used to examine the association between long-term air pollution exposure with self-reported high blood pressure, high blood cholesterol, diabetes. Results of self-reported morbidity were presented as hazard ratios (HRs) per interquartile range (IQR) increase in PM(10), O(3), NO(2), SO(2), and CO. RESULTS: After controlling for potential confounders, we found that an IQR increase in PM(10) was significantly associated with self-reported high blood pressure (HR = 1.13, 95% CI: 1.04, 1.23) and high blood cholesterol (HR = 1.07, 95%CI: 1.02, 1.12), but not with diabetes (HR = 1.05, 95%CI: 0.91, 1.21). SO(2) was also positively associated with self-reported high blood pressure (HR = 1.22, 95%CI: 1.08, 1.38), high blood cholesterol (HR = 1.20, 95%CI: 1.11, 1.30), and diabetes (HR = 1.21, 95%CI: 0.92, 1.60). Moreover, we observed a positive association between CO and self-reported high blood pressure (HR = 1.07, 95%CI: 1.00, 1.15), but not for other diseases. However, self-reported morbidities were not associated with O(3) and NO(2). CONCLUSIONS: Long-term exposure to air pollution, especially for PM(10) and SO(2) was associated with self-reported high blood pressure, high blood cholesterol, and diabetes in subjects of TCS. Our study supports that exposure to air pollution increases cardiovascular disease risk factors for younger population.
RATIONALE Chronic obstructive lung disease (COPD) is a chronic progressive disease. Although smoking is the most important risk factor, 30% of COPD patients are never smokers, and environmental agents are also influential. The effects of air pollutants and meteorological factors on COPD exacerbations have not been studied extensively. OBJECTIVE We aimed to investigate the air pollutants and meteorological factors that impact the incidence of COPD exacerbations. METHODS We obtained clinical data of COPD exacerbation cases from The National Health Insurance Service (NHIS) and merged it with 24-hour average values of air pollutants and meteorological factors from national databases. Patients who reside in eight metropolitan cities, where observatory stations are densely located, were selected for analysis. RESULTS In 1,404,505 COPD patients between 2013 and 2018, 15,282 COPD exacerbations leading to hospitalization or emergency room visits were identified. Among the various air pollutants and meteorological factors, particulate matter (PM)2.5, PM10, NO2, SO2, CO, O3, average temperature and diurnal temperature range (DTR) were associated with COPD exacerbations. GAM model analysis with cubic splines showed an inverted U-shaped relationship with PM2.5, PM10, CO, NO2, SO2, O3, DTR and humidity, while it displayed a U-shaped pattern with the average temperature. Distinct patterns were found from 2015-2016 to 2017-2018. CONCLUSIONS PM2.5, PM10, CO, NO2, O3, SO2, average temperature, humidity, and DTR affected the incidence of COPD exacerbations in various patterns, up to 10 lag days.
This study analyzes how climate change affects the economy, society, and environment in South Korea. Then, the study explores the ways to strengthen capabilities that can alleviate climate change impacts. To find them, the study employs a system dynamics simulation method and builds a model with several sectors including the urban, rural, population, and social-environmental sectors. The study compares the size of climate change damages in rural and urban areas. The results with representative concentration path (RCP) 8.5 show that the size of climate change damage will continue to increase by 2050. The projected damages from the reduced industrial outputs in urban areas will be larger than that in rural areas. The results also show that the service sector will face stronger impacts from climate change than the manufacturing and agricultural sectors. However, the total size of damage in the rural areas will be bigger than that of the urban areas. It is because the size of reduced industrial outputs per capita in the rural areas is twice bigger than that of the urban areas. The climate change damage in the social and environmental sectors (including a loss of biodiversity and an increase in health costs) account for the largest part of the total damage. The study finally provides suggestions and policies that can improve the capabilities to reduce the climate change damages. One of the major suggestions of this study is that the increase in the climate change budget corresponding to the GDP growth can minimize the size of climate change impacts.
INTRODUCTION: This focused ethnographic study used qualitative, ethnographic, and participatory methods to explore determinants of maternal, infant, and young child nutrition (MIYCN) during the first 1,000 days of life as part of efforts to address the double burden of malnutrition in Solomon Islands. METHODS: An iterative study design was used to first explore and then confirm findings related to food and nutrition security and social and behavioral determinants of MIYCN in urban and rural settings. The first phase included in-depth interviews, household observations, free lists, and seasonal food availability calendar workshops while the second phase included focus group discussions, pile sorts, participatory community workshops, and repeated household observations. RESULTS AND DISCUSSION: We found that MIYCN is shaped by a complex interaction of factors at the macro- and micro-levels. At the macro-level, globalization of the food system, a shifting economy, and climate change are driving a shift toward a delocalized food system based on imported processed foods. This shift has contributed to a food environment that leaves Solomon Islanders vulnerable to food and nutrition insecurity, which we found to be the primary determinant of MIYCN in this context. At the micro-level, this food environment leads to household- and individual-level food decisions that often do not support adequate MIYCN. Multi-sectoral interventions that address the macro- and micro-level factors shaping this nutrition situation may help to improve MIYCN in Solomon Islands.
Conventional local public health planning and monitoring are insufficiently addressing the conjugated impact of urban development change and climate change in the future. The existing checklist and index often ignore the spatial-network interaction determining urban public health services in forward-looking aspects. This study offers and demonstrates a climate-resilient operationalization framework for urban public health services considering the interaction between urban development change and climate change across scales. A combination of collaborative scenario planning and tailor-made composite indicators were applied based on the IPCC Fifth Assessment Report (AR5)’s climate risk concept to adhere to local realities and diverse sets of scenarios. The framework was contested in a medium-sized city with a universal health care coverage setting, Khon Kaen city, Thailand. The results show that the coupling of collaborative scenario planning and composite indicators allows local public health care to operationalize their potential impact and climate-resilient targets in the future(s) in multiple service operation aspects. The scenarios assessment outcomes prove that although public health devotion can be fail-safe, achieving climate-resilient targets requires sectoral integration with urban development and health determining domains. Further exploration and disputation of the framework with a wider scale and diversified settings are recommended to enhance their robustness and universality.
OBJECTIVE: Although several studies have reported that some meteorological factors such as ambient temperature and atmospheric pressure, affect the incidence of spontaneous intracerebral hemorrhage (ICH), the correlation remains unclear. This retrospective time-series analysis was aimed to clarify the effects of meteorological parameters on the incidence of ICH. MATERIALS AND METHODS: Data of patients with ICH were obtained from a population-based survey of acute stroke patients between April 2016 and March 2019. All days during the study period were categorized into “no ICH day” when no ICHs occurred, “single ICH day” when only one ICH occurred, and “cluster day” when two or more ICHs occurred. Meteorological data were compared for among the three categories. RESULTS: 1,691 ICH patients from 19 hospitals were registered. In a total of 1,095 days, 250 were categorized as no ICH days, 361 as single ICH days, and 484 as cluster days. Daily ambient temperature declined in parallel with the daily number of ICHs, and it was a significant predictor for single ICH days and cluster days. Furthermore, the incidence of ICH in patients aged 65 years or above, men, those who emerged at home, those with modified Rankin Scale 3-5; and those with hypertension; and ICHs in the basal ganglia, brain stem, and cerebellum were more likely to be affected by low ambient temperature. CONCLUSION: Daily ambient temperature was significantly associated with ICH incidence. Patients’ activity, history of hypertension, and location of hemorrhage were also related to the impact of low ambient temperature on the incidence of ICH.
We investigated decadal (2010-2019) cardiovascular, cerebrovascular, and respiratory mortality sensitivity to annual warm temperatures in major Japanese cities: Sapporo, Tokyo (23 wards), and Osaka. The summer mortalities (June-August) increased with the monthly mean temperature for acute myocardial infarction, other acute ischemic heart diseases, cerebral infarction, and pneumonia in the three cities. Monthly mean temperatures were an indicator of these disease mortalities in Japan. However, similar responses were not found for cardiac arrhythmia and heart failure (excluding Sapporo), subarachnoid hemorrhage, and intracerebral hemorrhage. The decadal sensitivities and risk ratios between the maximum and minimum monthly mean temperatures were calculated using a linear regression model. In Sapporo, Tokyo, and Osaka, for example, the analyses of acute myocardial infarction showed summer positive responses of 0.19-0.25, 0.13-0.18, and 0.12-0.30, respectively, as the mortality rate (per 100,000 population) per 1 degrees C of monthly mean temperature, which estimated increased risks (between the coolest and hottest months) of 37-65% in Sapporo, 31-42% in Tokyo, and 35-39% in Osaka.
BACKGROUND: Climate change exacerbates temperature-related mortality, but effects may vary by geographic characteristics. We hypothesize that higher greenness may mitigate temperature-related mortality, and that the effect may vary in different areas. OBJECTIVE: We examined how mortality among older adults in China was associated with temperature for 2000-2014, and how geolocation and residential greenness may modulate this association. METHODS: We used health data from the China Longitudinal Healthy Longevity Survey (CLHLS), and meteorological data from the Global Surface Summary of Day (GSOD) product by National Climate Data Center. We used a case-crossover study design with distributed nonlinear modeling to estimate mortality risks in relation to temperature, and stratified analysis by quartile of greenness. Greenness was estimated by Normalized Difference Vegetation Index (NDVI) from remote-sensed imagery. In addition to the national analysis, we also assessed three provinces (Jiangsu, Guangdong, and Liaoning) to examine differences by climatic regions. RESULTS: Extreme temperatures had a significant association with higher mortality, with regional differences. Findings from the national analysis suggest that individuals in the lowest quartile of greenness exposure had a ratio of relative risks (RRR) of 1.38 (0.79, 2.42) for mortality risk on extreme hot days at the 95th percentile compared to those at the 50th percentile, compared to those in the highest quartile, which means those residing in the lowest quartile of greenness had a 38% higher RR than those residing in the highest quartile of greenness, where RR refers to the risk of mortality on days at the 95th percentile of temperature compared to days at the 50th percentile. The RRR for the highest to lowest quartiles of greenness for mortality risk on extreme cold days at the 5th percentile compared to the 50th percentile was 2.08 (0.12, 36.2). In Jiangsu and Guangdong provinces, both the heat effects and cold effects were the lowest in the highest greenness quartile, and the results in Liaoning province were not statistically significant, indicating different regional effects of greenness on modulating the temperature-mortality relationship. DISCUSSION: We elucidated one pathway through which greenness benefits health by decreasing impact from extreme high temperatures. The effects of greenness differed by climatic regions. Policymakers should consider vegetation in the context of climate change and health.
OBJECTIVE: Gout is a chronic disease caused by the deposition of sodium urate (MSU) crystals. Available data on the association between environmental hazards and gout are scarce. The present study was present to investigate the relationship between short-term exposure to air pollution and hospitalizations for acute gout from 2016 to 2020 in Anqing City, China. METHODS: Daily records of hospital admissions for acute gout in Anqing from 1 January 2016 to 31 December 2020 were retrieved from the tertiary first-class hospitals in Anqing. Air pollutants and meteorological data were obtained from the China Environmental Monitoring Station and China Meteorological Data Service Center respectively. We used a time-series analysis to explore the association between air pollution (NO(2), O(3), and CO) and hospitalizations for acute gout, and conducted stratified analyses by gender, age and season. RESULTS: We observed an association between NO(2) and hospitalizations for gout (lag 0, relative risk (RR):1.022, 95% confidence interval (CI):1.004-1.041). For every 1 mg/m(3) increase in CO concentration, hospitalizations for gout increased by 3.9% (lag 11 days, RR=1.039, 95% CI: 1.004-1.076). Intriguingly, there was a negative association between O(3) and hospitalizations for gout (lag0, RR=0.986, 95% CI: 0.976-0.996). Stratified analyses showed that exposure to high levels of NO(2) was considered to be more vulnerable to gout in cold season. CONCLUSION: Our study showed that short-term exposure to NO(2) and CO has a significant effect on hospitalizations for acute gout.
BACKGROUND: In the context of global climate changes, increasing extreme weather events have aroused great public concern. Limited evidence has focused on the association between extreme precipitation and hospitalizations for acute myocardial infarction (AMI). Our study aimed to examine the effect of extreme precipitation on AMI hospitalizations. METHODS: Daily AMI hospitalizations, weather variables and air pollution data in Beijing from 2013 to 2018 were obtained. We used a time-series analysis with a distributed lag model to evaluate the association of extreme precipitation (≥95th percentile of daily precipitation) with AMI hospitalizations. Subgroup analysis was conducted to identify the vulnerable subpopulations and further assessed the attributable burden. RESULTS: Extreme precipitation increased the risk of AMI hospitalizations with significant single-day effects from Lag 4 to Lag 11, and the maximum cumulative effects at Lag 0-14 (CRR = 1.177, 95% CI: 1.045, 1.326). Older people (≥65 years) and females were more vulnerable to extreme precipitation. The attributable fraction and numbers of extreme precipitation on AMI hospitalizations were 0.68% (95% CI: 0.20%, 1.12%) and 854 (95% CI: 244, 1,395), respectively. CONCLUSION: Extreme precipitation is correlated with a higher risk of AMI hospitalizations. The elderly (≥65 years) and females are more susceptible to AMI triggered by extreme precipitation.
BACKGROUND: Studies on the associations between ambient temperature and asthma hospitalizations are limited, and the results are controversial. We aimed to assess the short-term effects of ambient temperature on the risk of asthma hospitalizations and quantify the hospitalization burdens of asthma attributable to non-optimal temperature in adults in Beijing, China. METHODS: We collected daily asthma hospitalizations, meteorological factors and air quality data in Beijing from 2012 to 2015. We applied a time-stratified case-crossover design and fitted a distributed lag non-linear model with a conditional quasi-Poisson regression to explore the association between ambient temperature and adult asthma hospitalizations. The effect modifications of these associations by gender and age were assessed by stratified analyses. We also computed the attributable fractions and numbers with 95% empirical confidence intervals (eCI) of asthma hospitalizations due to extreme and moderate temperatures. RESULTS: From 2012 to 2015, we identified a total of 18,500 hospitalizations for asthma among adult residents in Beijing, China. Compared with the optimal temperature (22 °C), the cumulative relative risk (CRR) over lag 0-30 days was 2.32 with a 95% confidence interval (CI) of 1.57-3.42 for extreme cold corresponding to the 2.5th percentile (- 6.5 °C) of temperature distribution and 2.04 (95% CI 1.52-2.74) for extreme heat corresponding to the 97.5th percentile (29 °C) of temperature distribution. 29.1% (95% eCI 17.5-38.0%) of adult asthma hospitalizations was attributable to non-optimum temperatures. Moderate cold temperatures yielded most of the burdens, with an attributable fraction of 20.3% (95% eCI 9.1-28.7%). The temperature-related risks of asthma hospitalizations were more prominent in females and younger people (19-64 years old). CONCLUSIONS: There was a U-shaped association between ambient temperature and the risk of adult asthma hospitalizations in Beijing, China. Females and younger patients were more vulnerable to the effects of non-optimum temperatures. Most of the burden was attributable to moderate cold. Our findings may uncover the potential impact of climate changes on asthma exacerbations.
Prior research has shown that environmental hazards, such as limited green space, air pollution, and harmful weather, have the strong adverse impact on older adults’ cognitive function; however, most of the studies were conducted in developed countries and limited to cross-sectional analyses. China has the largest aging population in the world so the research evidence from it can offer an insight to the study in other developing countries facing similar issues and inform future public health policy and disease control. This study examined the long-term impact of environmental factors, namely, green space coverage, air pollution, and weather conditions on cognitive function using a nationally representative sample consisting of adults aged 45 years and older selected from the China Health and Retirement Longitudinal Study (CHARLS 2011-2018), the China City Statistical Yearbook, and other sources. Multilevel growth curve models were utilized for analysis and the mediator effects of physical activity and social engagement on the relationship between environmental factors and cognitive function were examined. Findings of this study showed that after controlling for sociodemographic characteristics, annual precipitation of 80 cm or more, living in areas with July temperature of 28°C or higher, urban community, and green space coverage were positively associated with cognition score at the baseline and lower precipitation, urban community, and greater green space coverage were associated with slower cognitive decline over a 7-year period. The impact of gross domestic product (GDP) seemed to take into effect more and more over time. These effects did not substantially change after weekly total hours of physical activities and levels of social engagement were added. More research on the mechanisms of the effect of environmental factors on cognition is needed such as the subgroup analyses and/or with more aspects of environmental measures.
It is known that air pollution is harmful to creatures, though until now most of the human thermal comfort indices that existed were calculated only with meteorological conditions. Therefore, a new index – meteorology and environment comfort (MEC) – was given out in this paper that considers both meteorology and air pollution conditions and presents the comprehensive and synergistic effects of meteorological and air pollution. The meteorology and air pollution data were used to establish the influence function of the five air pollutants (PM(2.5), PM(10), O(3), NO(2), and SO(2)) according to Fechner’s law; then, we calculated the somatosensory temperature (ST, a class of human thermal comfort indices) and MEC values of five typical cities (Beijing, Xining, Nanjing, Kunming, and Guangzhou). The results showed average improvements of five cities on MEC as a new comprehensive human comfort index to new ST. In spring, the MEC comfort proportion fell by 29.25%. Besides, the extreme heat discomfort ratio in Nanjing and Kunming has increased over 20%. In summer, the comfort proportion fell 12.54%; the extreme heat discomfort proportion of Beijing increased 37.86% and Kunming increased 24.09%. Air pollution significantly raised discomfort stress in Beijing. In fall, the comfort proportion fell by 20.87%; and the extreme heat discomfort of Nanjing increased 23.67% caused by poor air quality. About winter, the comfort ratio decreased 12.72%, and the cold discomfort proportion of Nanjing increased 30.30%, signifying awful air quality in winter. Air pollution levels significantly affect the comfort levels in all seasons, which is more evident with good weather patterns. MEC can offer early warnings of extreme weather events and provide a basis for the better prevention and control of air pollution to protect human health basing on the predictions of meteorological and environmental impact factors.
BACKGROUND: Two cervical cancer screening (CCS) projects have been ongoing for years in Guangxi Zhuang autonomous region (Guangxi), and some Trichomonas vaginalis infection (TVI) cases have been found as an opportunistic finding. This study aimed to identify the high-risk population and expound the spatial epidemiological features of TVI in Guangxi. METHODS: This study was based on CCS from 2012 to 2019. Adjusted odds ratio (AOR), and spatial analyses were used to identify the high-risk subgroups, as well as to depict the spatial epidemiological feature and its relationship with meteorological factors. RESULTS: The infection rate of TVI was 0.38% in 873,880 samples. Significant association with a high risk of TVI was found in the following: females aged 40-49 years (aOR=4.464; 95% CI, 3.359-5.932; p<0.001), aged 50-59 years (aOR=3.169; 95% CI, 2.370-4.237; p<0.001), from urban (aOR=1.577; 95% CI, 1.471-1.691; p<0.001), from minority areas (aOR=1.183; 95% CI, 1.060-1.320; p=0.003), areas with GPD <41,500 CNY (aOR=1.191; 95% CI, 1.106-1.282; p<0.001), and inland areas (aOR=1.520; 95% CI, 1.339-1.726; p<0.001). Counties with higher infection rate were concentrated in northwest Guangxi's mountainous area (Z-score=3.9656, p<0.001), in the upper reaches of the Hongshui River and Yu River, and with a significant spatial autocorrelation (Moran's I=0.581, p=0.002). Spatial error model showed significantly negative regressions among temperature (B=-0.295, p=0.002), annual temperature range (B=-0.295, p=0.002), and TVI spatial distribution. CONCLUSION: The spatial clustering and disparity of TVI in northwest Guangxi warrant further study, and meteorological conditions may play an important role in TVI in northwest Guangxi.
Zoonoses impart a significant public health burden in Australia particularly in Queensland, a state with increasing environmental stress due to extreme weather events and rapid expansion of agriculture and urban developments. Depending on the organism and the environment, a proportion of zoonotic pathogens may survive from hours to years outside the animal host and contaminate the air, water, food, or inanimate objects facilitating their transmission through the environment (i.e. environmentally transmitted). Although most of these zoonotic infections are asymptomatic, severe cases that require hospitalisation are an important indicator of zoonotic infection risk. To date, no studies have investigated the risk of hospitalisation due to environmentally transmitted zoonotic diseases and its association with proxies of sociodemographic and environmental stress. In this study we analysed hospitalisation data for a group of environmentally transmitted zoonoses during a 15-year period using a Bayesian spatial hierarchical model. The analysis incorporated the longest intercensal-year period of consistent Local Government Area (LGA) boundaries in Queensland (1996-2010). Our results showed an increased risk of environmentally transmitted zoonoses hospitalisation in people in occupations such as animal farming, and hunting and trapping animals in natural habitats. This risk was higher in females, compared to the general population. Spatially, the higher risk was in a discrete set of north-eastern, central and southern LGAs of the state, and a probability of 1.5-fold or more risk was identified in two separate LGA clusters in the northeast and south of the state. The increased risk of environmentally transmitted zoonoses hospitalisations in some LGAs indicates that the morbidity due these diseases can be partly attributed to spatial variations in sociodemographic and occupational risk factors in Queensland. The identified high-risk areas can be prioritised for health support and zoonosis control strategies in Queensland.
BACKGROUND: Hemorrhagic fever with renal syndrome (HFRS), a rodent-borne disease, is a severe public health threat. Previous studies have discovered the influence of meteorological factors on HFRS incidence, while few studies have concentrated on the stratified analysis of delayed effects and interaction effects of meteorological factors on HFRS. OBJECTIVE: Huludao City is a representative area in north China that suffers from HFRS with primary transmission by Rattus norvegicus. This study aimed to evaluate the climate factors of lag, interaction, and stratified effects of meteorological factors on HFRS incidence in Huludao City. METHODS: Our researchers collected meteorological data and epidemiological data of HFRS cases in Huludao City during 2007-2018. First, a distributed lag nonlinear model (DLNM) for a maximum lag of 16 weeks was developed to assess the respective lag effect of temperature, precipitation, and humidity on HFRS incidence. We then constructed a generalized additive model (GAM) to explore the interaction effect between temperature and the other two meteorological factors on HFRS incidence and the stratified effect of meteorological factors. RESULTS: During the study period, 2751 cases of HFRS were reported in Huludao City. The incidence of HFRS showed a seasonal trend and peak times from February to May. Using the median WAT, median WTP, and median WARH as the reference, the results of DLNM showed that extremely high temperature (97.5th percentile of WAT) had significant associations with HFRS at lag week 15 (RR = 1.68, 95% CI: 1.04-2.74) and lag week 16 (RR = 2.80, 95% CI: 1.31-5.95). Under the extremely low temperature (2.5th percentile of WAT), the RRs of HFRS infection were significant at lag week 5 (RR = 1.28, 95% CI: 1.01-1.67) and lag 6 weeks (RR = 1.24, 95% CI: 1.01-1.57). The RRs of relative humidity were statistically significant at lag week 10 (RR = 1.19, 95% CI: 1.00-1.43) and lag week 11 (RR = 1.24, 95% CI: 1.02-1.50) under extremely high relative humidity (97.5th percentile of WARH); however, no statistically significance was observed under extremely low relative humidity (2.5th percentile of WARH). The RRs were significantly high when WAT was -10 degrees Celsius (RR = 1.34, 95% CI: 1.02-1.76), -9 degrees Celsius (1.37, 95% CI: 1.04-1.79), and -8 degrees Celsius (RR = 1.34, 95% CI: 1.03-1.75) at lag week 5 and more than 23 degrees Celsius after 15 weeks. Interaction and stratified analyses showed that the risk of HFRS infection reached its highest when both temperature and precipitation were at a high level. CONCLUSIONS: Our study indicates that meteorological factors, including temperature and humidity, have delayed effects on the occurrence of HFRS in the study area, and the effect of temperature can be modified by humidity and precipitation. Public health professionals should pay more attention to HFRS control when the weather conditions of high temperature with more substantial precipitation and 15 weeks after the temperature is higher than 23 degrees Celsius.
Climate disasters pose a risk to residents’ well-being globally. However, information about the impact of climate disasters among urban and rural residents remains lacking, especially in Indonesia. This study aims to fill the gap by investigating the impact of climate disaster on subjective well-being based on urban and rural typology model. The data were cross-sectional, involving 7110 Indonesian residents who had experienced climate disasters, 3813 from urban areas and 3297 from rural areas. An ordered probit model was employed to estimate the impact of climate disasters on subjective well-being (i.e., happiness and life satisfaction). In general, the empirical results show that climate disasters do not significantly affect the happiness of Indonesian residents, but they significantly and negatively impact their life satisfaction. Further analysis reveals that climate disasters impact urban and rural residents differently. The subjective well-being of rural residents is more severely affected than those living in urban areas. Further estimation also indicated that climate disaster significantly reduces residents’ subjective well-being at the lowest income level for both rural and urban residents. Our finding confirms that rural residents remain the most vulnerable to the impacts of climate change.
Although active transport contributes to environmental and human health, only limited research has been conducted on what makes people participate in active transport in tourism-related contexts. To fill this gap, research was conducted on theoretically conceptualized relationships between pro-social behavior on active transport, air quality, climate change mitigation, and health with a moderator of leisure and tourism activity. In order to collect data, an online survey was conducted targeting Korean cyclists and walkers, and PLS-SEM and deep learning were applied for data analysis. Results revealed that pro-social behavior on active transport has a great effect on perceived air quality. Health is strongly influenced by pursuing climate change mitigation and a strong impact of active transport on health was identified. There were greater effects between pro-social behavior and air quality as well as pro-social behavior and climate change mitigation for those engaged in active transport for tourism than for leisure, while the leisure group has a stronger relationship between pro-social behavior and health than for tourism. The results are valuable for encouraging active transport behavior.
Public health is threatened by air pollution and high temperature, especially in urban areas and areas impacted by climate change. Well-designed urban forms have co-benefits on promoting human health and mediating atmospheric environment-related threats (e.g., high temperature and air pollution). Previous studies overlooked these mediating effects of urban form on suicide mortality. This study used partial least squares modeling and countywide data in Taiwan to identify the crucial influences and pathways of urban environment, socioeconomic status, and diseases on suicide mortality. The model considered the impact of the characteristics of urban form (i.e., urban development intensity, land mix, and urban sprawl), urban industrial status (i.e., industrial level), urban greening (i.e., green coverage), disease (i.e., important diseases morbidity of human immunodeficiency virus [HIV], cerebrovascular disease [CVD], chronic liver disease and cirrhosis [CLDC], nephritis, nephrotic syndrome and nephrosis [NNSN], malignant tumor [MT]), socioeconomic status (i.e., income level and aging population rate), and the atmospheric environment (i.e., air pollution and high temperature) on suicide mortality. Optimizing land mix and minimizing urban development intensity and urban sprawl have been found to reduce suicide mortality. The mediating effect of urban form on suicide mortality originated from air pollution and high temperature, and mediating air pollution was greater than high temperature. Furthermore, industrial level, important diseases (HIV, CVD, CLDC, NNSN, and MT) morbidity, an aging population rate, air pollution, and high temperature were associated with an increase in suicide mortality, whereas green coverage and income level were associated with a reduction in suicide rates. The findings demonstrate that appropriate urban policy and urban planning may lower suicide mortality, be useful strategies for suicide prevention, and be a foundation for building a healthy city. Moreover, this study provides clarity on the complex relationship of suicide and the urban environment while identifying crucial factors.
Climate change impacts the urban environment and landscape changes worldwide. To understand how South Korean citizens perceive these changes and what they expect for the future landscape, this study analyzed urban residents’ perceptions through text mining. Data related to the keywords “future landscape”, “future environment”, “well-being”, and “climate change” were collected from July 2020 to July 2021 from the Korean search engines Naver, Daum, and Google using the tool TEXTOM. Keywords, importance, and related words were derived through word frequency, TF-IDF, and N-gram analysis. CONCOR analysis was used to derive the meaning and relevance of the words. In “future landscape”, results showed a high frequency of the words “complex”, “apartment”, “future value”, and “sale”, and the connection strength was higher between “complex”, “landscape”, and “future value”. In “future environment”, “eco-friendly” showed the highest word frequency, and the words “New Deal”, “hydrogen” and “mobility” showed a high frequency and correlation. For “well-being”, “Green Cross” (a well-being-related company) showed the highest frequency, and the connection strength between satisfaction indexes was high. For “climate change”, “response” showed the highest frequency, and the connection strength between “carbon-neutral”, “UN-convention”, and “plan-establishment” was high. These results showed that South Koreans associate landscaping with the value of apartment complexes, that they expect solutions to mitigate climate change impacts with green and eco-friendly strategies, and lastly that well-being-related companies are receiving a great deal of public attention. Thus, it is expected that the results will help plan effective landscaping approaches to respond to environmental changes.
Coastal hazards, particularly cyclones, floods, erosion and storm surges, are emerging as a cause for major concern in the coastal regions of Vijayawada, Andhra Pradesh, India. Serious coastal disaster events have become more common in recent decades, triggering substantial destruction to the low-lying coastal areas and a high death toll. Further, women living in informal and slum housing along the Vijayawada coastline of Andhra Pradesh (CAP), India, suffer from multiple social, cultural and economic inequalities as well. These conditions accelerate and worsen women’s vulnerability among this coastal population. The existing literature demonstrates these communities’ susceptibility to diverse coastal disasters but fails to offer gender-specific vulnerability in urban informal housing in the Vijayawada area. Accordingly, the current study developed a novel gender-specific Women’s Coastal Vulnerability Index (WCVI) to assess the impact of coastal disasters on women and their preparedness in Vijayawada. Field data was collected from over 300 women through surveys (2) and workshops (2) between November 2018 and June 2019, and Arc-GIS tools were used to generate vulnerability maps. Results show that women are more vulnerable than men, with a higher death rate during coastal disaster strikes. The current study also found that gender-specific traditional wear is one of the main factors for this specific vulnerability in this area. Furthermore, the majority of the women tend to be located at home to care for the elders and children, and this is associated with more fatalities during disaster events. Homes, particularly for the urban poor, are typically very small and located in narrow and restricted sites, which are a barrier for women to escape from unsafe residential areas during disasters. Overall, the research reveals that most of the coastal disaster events had a disproportionately negative impact on women. The results from this present study offer valuable information to aid evidence-based policy- and decision-makers to improve existing or generate innovative policies to save women’s lives and improve their livelihood in coastal areas.
Assessment of urban river sediment quality is paramount to understanding the impacts of urbanization on aquatic ecosystems and public health. The study evaluated the health impacts and sources of heavy metal pollutants in the Mangonbangon river, Tacloban City. With the abundance of heavy metal contaminants in the river sediment (Fe>Mn>Zn>Cu>Cr>Ni>Co), Hazard indices (HIs) ranged from 0.04 to 0.10 for adults and 0.31 to 0.90 for children suggesting little or no non-carcinogenic effects to the population. Lifetime cancer risk (LCR) is below the tolerable threshold of 10(-4), with Co contributing 61% of the cancer risk. Using unconstrained ordination and the GIS-based method (UOGM), we showed two non-multidimensional scaling groups of pollutants distributed based on dwelling density, presence of informal settlers, and types of activity at the sample sites. Given that sampling was performed three years after the city-wide destruction by Typhoon Haiyan (Yolanda), our analysis indicated the return of anthropogenic activities and pollution-related health problems in Tacloban. Our results reinforce the urgent need for proper river management and economic zoning to help curb the rapidly growing heavy metal pollution problem at its earliest stage.
Assessments of vulnerability to flooding can generate useful data for planners and policy makers. To the best of the authors knowledge, no flood-vulnerability study has combined geophysical modelling of floods with socioeconomic assessments of vulnerability at finer municipal or household scale. In addition, the extent to which vulnerability assessments actually feed into flood adaptation policies remains largely unknown. A new flood vulnerability index, and associated methodology, is proposed, combining high-resolution hydrological-hydraulic modelling with built-environment and socio-economic indicators at the smallest spatial scale at which socio-economic data is available. The main advantage of the methodology is its ability to incorporate place-specific data, hence yielding more refined simulations of floods and the capacity to make projections into climate futures at local scale. The index is built and applied to the inter-city suburb of Marrickville in Sydney and used to assess the effects of future climate change on vulnerability mapping in the suburb. Finally, the results of the assessment are presented to, and discussed with, the local government authority responsible for implementing flood adaptation policies for Marrickville. Locally specific modelling of floods, combined with socio-economic and built-environment mapping, has yielded a rich set of information on flood vulnerability and significant variability within a single suburb. Flood duration is projected to increase by more than 100% under some climate change scenarios, as a result of reduced drainage caused by sea level rise. Feedback from municipal council has highlighted the potential usefulness of the knowledge generated by the assessment, especially for emergency services.
By the 2050s, more than 120 million people are predicted to settle in the Pearl River Delta (PRD), which covers large coastal cities such as Guangzhou, Shenzhen and Hong Kong. Cities in the PRD are vitally important to China in relation to their socio-economic contributions. From recent evidence, this strongly urbanized area is vulnerable to, and currently facing bigger incidences of, coastal and urban flooding. Flood risk is growing in low-lying coastal areas due to rapid urbanization and increasing flood hazards exacerbated by climate change. Frequent intensive rainstorms, sea-level rise, typhoons and surges threaten large populations and their economic assets, causing severe socio-economic and ecological impacts in the PRD cities. Current flood risk management (FRM) in the delta is still predominately focused on using traditional techno-fixes and infrastructure paradigms, lacking sufficient strategic planning and flood protection to develop adequate flood resilience. Recent urban floods, enhanced by storm surges and intensive rainstorms, have affected multiple PRD cities and drawn attention to flood risk as a major challenge in the PRD’s coastal cities. This review encourages development of long-term FRM practices with provincial and municipal authorities working together more closely to develop better-integrated regional FRM strategies for the PRD.
Emergency medical service (EMS) is important for rescuing victims suffering from life-threatening illnesses or accidents, and is highly time-sensitive by nature. Many uncertain contexts in the urban environment can prolong EMS response time and deteriorate its performance. Using the enhanced two-step floating catchment area (E2SFCA) method, this study measures EMS accessibility with the effect of a regular uncertain context (i.e., the city dynamics like time-varying population and traffic) and an irregular uncertain context (i.e., an extreme pluvial flood event which can cause extensive road closures). The results indicate that, in the central urban area of Shanghai, mid-west areas with denser populations have higher accessibility than eastern peripheral areas. Flooding can cause a remarkable decline of accessibility which falls to the lowest point slightly earlier than the time when the worst road connectivity emerges. The night time exhibits better accessibility than especially the peak hours during the daytime. The GWR results reveal that increasing facility richness and road density while decreasing flood-induced road closures have a positive effect on EMS accessibility. The study indicates that both regular and irregular uncertain contextual factors can influence EMS accessibility in a highly complex manner. Carefully taking these uncertainties into account would enable EMS planning in other contexts and regions to face the enormous challenges posed by the changing climate and increasingly complex urban environment.
In recent years, the rainstorm and flood disasters frequently happened in cities and posed increasingly wide challenges. Therefore, the whole development process of urban rainstorm and flood disaster should be carried out for the reasonable and quantitative assessment on cities’ ability to respond to rainstorm and flood disasters, and the index system of risk assessment on regional flood disaster is constructed based on the three attributes of vulnerability, adaptability and restorability. 3 first-class and 14 s-class indexes are set up accordingly. The weight of each index is calculated by weighting methods which are both subjective and objective based on entropy-weight order relation. Then, the theoretical model for risk assessment is established by weighted clustering assessment. Finally, the empirical analysis was conducted on the current situation of rainstorm and flood disaster in 8 regions of a city in China. The results show that among the risk grade of rainstorm and flood disaster in 8 regions, there are 2 regions with grade-II higher risk, 5 regions with grade-III general risk and 1 region with grade-IV low risk. The consistency between assessment results and actual operation of cities indicates this model can be applied and effective to some extent.
People are always susceptible to a loss of stability in urban floodwaters that leads to serious casualties. Thus, the safety criterion for the instability of people in floodwaters must be determined. In this study, the hydrodynamic criterion of the instability of people in floodwaters in terms of the incipient velocity and water depth is derived using the probability method based on Shannon entropy theory. The derived model can characterize variations in the incipient velocity of people in floodwaters with respect to the inundating water depth. Furthermore, a comparison with seven experimental datasets available in the literature shows the validity of the proposed entropy-based model considering data scattering. A sensitivity analysis of the derived model to some of the incorporated parameters was performed, and the qualitative results are in accordance with our understanding of the physical mechanism of the instability of people in floodwaters. Taking the physical parameters (height and mass) of Chinese adults and children as a representative example, this study also showed the vulnerability degree of Chinese adults and children subject to floodwaters. These findings could provide a reference for administrators and stakeholders for flood hazard mitigation and flood strategy management. This study shows that an entropy-based method could be a valuable addition to existing deterministic models for characterizing the instability criterion of people in an urban flooding event.
The evaluation of emergency response capability under different pluvial flooding scenarios is an essential approach to improve the emergency response capability of flood disasters. A new evaluation method of emergency response capacity of urban public services is proposed based on urban pluvial flooding scenario simulation. Firstly, inundation area and depth under different pluvial flooding scenarios are simulated based on the SCS-CN model. Following that, space densities of all indicators include inundation area and depth, road network and the emergency public service institutions. Then, the indicator weight is determined by the combined weighting method of entropy weight and coefficient of variation. Finally, the emergency response capacity index (of each pixel) is calculated based on the graph stacking method. Taking Erqi District, Zhengzhou City as an example, the emergency response capacity of public service under different urban flooding scenarios is evaluated. The results show that the spatial distribution difference of public service emergency response capacity in Erqi District, Zhengzhou City is obvious, and with the increase of the precipitation return period, the high value area of public service emergency response capability decreases gradually and the low value area increases gradually. This method takes into account the specific urban flooding scenario and the layout of public service institutions and road networks that have strong practicability. the results of the evaluation can provide a reference for the construction of urban flood emergency response capacity and provide support for emergency decision-making.
Billions of people live in urban poverty, with many forced to reside in disaster-prone areas. Research suggests that such disasters harm child nutrition and increase adult morbidity. However, little is known about impacts on mental health, particularly of people living in slums. In this paper we estimate the effects of flood disasters on the mental and physical health of poor adults and children in urban Indonesia. Our data come from the Indonesia Family Life Survey and new surveys of informal settlement residents. We find that urban poor populations experience increases in acute morbidities and depressive symptoms following floods, that the negative mental health effects last longer, and that the urban wealthy show no health effects from flood exposure. Further analysis suggests that worse economic outcomes may be partly responsible. Overall, the results provide a more nuanced understanding of the morbidities experienced by populations most vulnerable to increased disaster occurrence.
Due to climate change and rapid urbanization, contemporary cities face the dual challenges of providing sufficient stormwater management and adequate park services, which potentially conflict over limited space and resources. To solve these problems, cities are increasingly combining stormwater infrastructure with park space in ways that create new efficiencies. To date, most research has focused on the stormwater management performance aspect of these combinations and not the techniques employed to achieve the combined goals. To fill this gap, 23 sponge city parks in Shanghai were investigated to examine the combination of stormwater and park services. Our findings show that stormwater techniques were primarily combined with the park facilities of water areas, paved open spaces, and pathways. Additionally, we found that larger parks employed a wider range of techniques for managing stormwater runoff and supported broader sets of park activities, while those at smaller scales prioritized infiltration, detention, and purification measures, as well as concentrated on social and economic activities. This study is the first to explore SPC parks that integrate stormwater management and park services, thereby providing implications for SPC development in China and insights into the ways that the two properties can be combined in other cities.
BACKGROUND: /Objective: Flooding risk is a global issue, and various approaches have been established to prevent flooding risk around the world. China is one of the heavily flood-affected countries and has been implementing the Sponge City program since 2015 to defend against flooding. Unfortunately, flooding has been common in China in recent years, causing severe health risks to citizens. This research mainly focuses on (a) evaluating the implementation of China’s Sponge City program and the associated impacts on human health and (b) exploring the future improvement of the Sponge City program in China. METHODS: The Interpretive Document Approach was used to explore an inclusive review of the Sponge City program and its implications on human health. RESULTS: /Findings: The Sponge City program in China is still insufficient to prevent flooding risks effectively. In the past eight years, 24/34 provinces have recorded flooding, which caused a total of 4701 deaths and over 525.5 billion RMB (around 72.9 billion US$) in economic loss. Till now, only 64/654 cities have promulgated local legislation to manage sponge city construction, although the Sponge City was implemented in 2015. Besides, the completed Sponge City program constructions cannot fully prevent flooding risks, the flood prevention capacity is limited. The Sponge City program is not granted priority, lacking national legislation hinders Sponge City program implementation in China. CONCLUSIONS: China needs to make national legislation on the Sponge City program and update the Sponge City program technology guidelines. Local governments should implement Sponge City construction according to local geographic environments.
INTRODUCTION: There is a large body of epidemiological evidence showing significantly increased mortality risks from air pollution and temperature. However, findings on the modification of the association between air pollution and mortality by temperature are mixed. METHODS: We used a varying coefficient distributed lag model to assess the complex interplay between air temperature and PM(2.5) on daily mortality in Guangzhou City from 2013 to 2020, with the aim of establishing the PM(2.5)-mortality association at different temperatures and exploring synergetic mortality risks from PM(2.5) and temperature on vulnerable populations. RESULTS: We observed near-linear concentration-response associations between PM(2.5) and mortality across different temperature levels. Each 10 μg/m³ increase of PM(2.5) in low, medium, and high temperature strata was associated with increments of 0.73% [95% confidence interval (CI): 0.38%, 1.09%], 0.12% (95% CI: -0.27%, 0.52%), and 0.46% (95% CI: 0.11%, 0.81%) in non-accidental mortality, with a statistically significant difference between low and medium temperatures (P=0.02). There were significant modification effects of PM(2.5) by low temperature for cardiovascular mortality and among individuals 75 years or older. CONCLUSIONS: Low temperatures may exacerbate physiological responses to short-term PM(2.5) exposure in Guangzhou, China.
BACKGROUND: Although low temperature and air pollution exposures have been associated with the risk of anxiety, their combined effects remain unclear. OBJECTIVE: To investigate the independent and interactive effects of low temperature and air pollution exposures on anxiety. METHOD: Using a case-crossover study design, the authors collected data from 101,636 outpatient visits due to anxiety in three subtropical Chinese cities during the cold season (November to April in 2013 through 2018), and then built conditional logistic regression models based on individual exposure assessments [temperature, relative humidity, particulate matter (PM(2.5), PM(10)), sulfur dioxide (SO(2)), and nitrogen dioxide (NO(2))] and twelve cold spell definitions. Additive-scale interactions were assessed using the relative excess risk due to interaction (RERI). RESULTS: Both cold spell and air pollution were significantly associated with outpatients for anxiety. The effects of cold spell increased with its intensity, ranging from 8.98% (95% CI: 2.02%, 16.41%) to 15.24% (95% CI: 6.75%, 24.39%) in Huizhou. Additionally, each 10 μg/m(3) increase of PM(2.5), PM(10), NO(2) and SO(2) was associated with a 1.51% (95% CI: 0.61%, 2.43%), 1.58% (95% CI: 0.89%, 2.28%), 13.95% (9.98%, 18.05%) and 11.84% (95% CI: 8.25%, 15.55%) increase in outpatient visits for anxiety. Synergistic interactions (RERI >0) of cold spell with all four air pollutants on anxiety were observed, especially for more intense cold spells. For particulate matters, these interactions were found even under mild cold spell definitions [RERI: 0.11 (95% CI: 0.02, 0.21) for PM(2.5), and 0.24 (95% CI: 0.14, 0.33) for PM(10)]. Stratified analyses yielded a pronounced results in people aged 18-65 years. CONCLUSIONS: These findings indicate that both cold spell and air pollution are important drivers of the occurrence of anxiety, and simultaneous exposure to these two factors might have synergistic effects on anxiety. These findings highlight the importance of controlling air pollution and improving cold-warning systems.
Thermal comfort and environmental health in scenic open spaces, a communication bridge between tourists and their environment, are prerequisites for tourism activities. In this study, scenic open spaces in an urban area of Xi’an, China were selected. Thermal perception (thermal sensation, comfort and acceptability) of residents and tourists were investigated through meteorological measurement and questionnaire survey. Physiological equivalent temperature (PET) was used to determine thermal benchmarks of all visitors to the site. Variables that influence individual thermal perception assessment (physical, individual, society and psychology) were measured and compared. Finally, a series of strategies and suggestions were proposed based on meteorological characteristics and influencing factors of thermal perception from perspectives of designers and scenic spot managers. Results show that: 1) Neutral PET (NPET) of respondents were 17.3 °C (residents) and 15.5 °C (tourists). Neutral PET ranges (NPETR) were 8.9-25.8 °C (residents) and 7.2-23.8 °C (tourists). Preferred PET values were 20.1 °C (residents) and 19.7 °C (tourists). Thermal acceptability ranges (TAR) were 6.3-37.8 °C (residents) and 0.5-39.9 °C (tourists). 2) In winter, physical factors were primary influencers of residents’ thermal perception, followed by social factors, while tourists’ thermal perception was mainly influenced by physical factors. In spring, physical factors were still the primary influencers for residents, followed by individual factors. Physical factors were also dominant for tourists, followed by psychological. In summer, physical factors were the major influencing factors for residents and tourists’ thermal perceptions.
Individual and meteorological factors are associated with cognitive function in older adults. However, how these two factors interact with each other to affect cognitive function in older adults is still unclear. We used mixed effects models to assess the association of individual and meteorological factors with cognitive function among older adults. Individual data in this study were from the database of China Family Panel Studies. A total of 3448 older adults from 25 provinces were included in our analysis. Cognitive functions were measured using a memory test and a logical sequence test. We used the meteorological data in the daily climate dataset of China’s surface international exchange stations, and two meteorological factors (i.e., average temperature and relative humidity) were assessed. The empty model showed significant differences in the cognitive scores of the older adults across different provinces. The results showed a main impact of residence (i.e., urban or rural) and a significant humidity-residence interaction on memory performance in older adults. Specifically, the negative association between humidity and memory performance was more pronounced in urban areas. This study suggested that meteorological factors may, in concert with individual factors, be associated with differences in memory function in older adults.
Human exposure to a hot environment may result in various heat-related illnesses (HRIs), which range in severity from mild and moderate forms to life-threatening heatstroke. The Hajj is one of the largest annual mass gatherings globally and has historically been associated with HRIs. Hajj attracts over two million Muslim pilgrims from more than 180 countries to the holy city of Makkah, Kingdom of Saudi Arabia. Several modifiable and non-modifiable factors render Hajj pilgrims at increased risk of developing HRIs during Hajj. These include characteristics of the Hajj, its location, population, and rituals, as well as pilgrims’ knowledge of HRIs and their attitude and behavior. Makkah is characterized by a hot desert climate and fluctuating levels of relative humidity. Pilgrims are very diverse ethnically and geographically, with different adaptations to heat. Significant proportions of the Hajj population are elderly, obese, and with low levels of fitness. In addition, many have underlying health conditions and are on multiple medications that can interfere with thermoregulation. Other factors are inherent in the Hajj and its activities, including crowding, physically demanding outdoor rituals, and a high frequency of infection and febrile illness. Pilgrims generally lack awareness of HRIs, and their uptake of preventive measures is variable. In addition, many engage in hazardous behaviors that increase their risk of HRIs. These include performing rituals during the peak sunshine hours with no sun protection and with suboptimal sleep, nutrition, and hydration, while neglecting treatment for their chronic conditions. HRIs preventive plans for Hajj should incorporate measures to address the aforementioned factors to reduce the burden of these illnesses in future Hajj seasons. Lessons from the Hajj can be used to inform policy making and HRIs preventive measures in the general population worldwide.
An innovative bioclimatic metric based on the Universal Thermal Climate Index (UTCI) is developed to quantify human thermal physiological heat stress. The Heat Stress Exposure (HSE) metric includes both duration and intensity dimensions of heat exposure, and in this paper it is applied to the Sydney Australia climatology. Geographic Information Systems (GIS) were used to spatially represent and visualize Sydney’s HSE. The first stage of the analysis collated observed meteorological data from 10 weather stations across the Sydney metropolitan region, extending from coastal Sydney to approximately 50 km inland in 2017. The second stage of the analysis integrated the radiative meteorological data into estimates of hourly Mean Radiant Temperature which were then applied to UTCI. In the final stage, a threshold UTCI value of 26 degrees C was selected for the calculation of HSE, which was then cumulated to represent the duration of heat exposure throughout the year. The difference between each UTCI hourly reading and the 26 degrees C threshold defined a UTCI exceedance (Delta UTCI; degrees C). The cumulative total of all Delta UTCI throughout the year defined n-ary sumation Delta UTCI in units of degree hours (degrees C.hr), thereby capturing both intensity and duration of exposure to heat stress. Weather systems driving westerly winds from the Australian continent’s central deserts brought the highest HSE to Sydney’s inland western suburbs, with values ranging between 4,000-6,000 n-ary sumation Delta UTCI (degrees C.hr). Coastal eastern Sydney experienced considerably lower HSE values ranging from 1,600-3,000 n-ary sumation Delta UTCI (degrees C.hr), reflecting the moderating influences of sea breezes and evaporative cooling.
Public health risks resulting from urban heat in cities are increasing due to rapid urbanisation and climate change, motivating closer attention to urban heat mitigation and adaptation strategies that enable climate-sensitive urban design and development. These strategies incorporate four key factors influencing heat stress in cities: the urban form (morphology of vegetated and built surfaces), urban fabric, urban function (including human activities), and background climate and regional geographic settings (e.g. topography and distance to water bodies). The first two factors can be modified and redesigned as urban heat mitigation strategies (e.g. changing the albedo of surfaces, replacing hard surfaces with pervious vegetated surfaces, or increasing canopy cover). Regional geographical settings of cities, on the other hand, cannot be modified and while human activities can be modified, it often requires holistic behavioural and policy modifications and the impacts of these can be difficult to quantify. When evaluating the effectiveness of urban heat mitigation strategies in observational or traditional modelling studies, it can be difficult to separate the impacts of modifications to the built and natural forms from the interactions of the geographic influences, limiting the universality of results. To address this, we introduce a new methodology to determine the influence of urban form and fabric on thermal comfort, by utilising a comprehensive combination of possible urban forms, an urban morphology data source, and micro-climate modelling. We perform 9814 simulations covering a wide range of realistic built and natural forms (building, roads, grass, and tree densities as well as building and tree heights) to determine their importance and influence on thermal environments in urban canyons without geographical influences. We show that higher daytime air temperatures and thermal comfort indices are strongly driven by increased street fractions, with maximum air temperatures increases of up to 10 and 15 ? as street fractions increase from 10% (very narrow street canyons and/or extensive vegetation cover) to 80 and 90% (wide street canyons). Up to 5 ? reductions in daytime air temperatures are seen with increasing grass and tree fractions from zero (fully urban) to complete (fully natural) coverage. Similar patterns are seen with the Universal Thermal Climate Index (UTCI), with increasing street fractions of 80% and 90% driving increases of 6 and 12 ?, respectively. We then apply the results at a city-wide scale, generating heat maps of several Australian cities showing the impacts of present day urban form and fabric. The resulting method allows mitigation strategies to be tested on modifiable urban form factors isolated from geography, topography, and local weather conditions, factors that cannot easily be modified.
Urban overheating (UO) may interact with synoptic-scale weather conditions. The association between meteorological parameters and UO has already been a subject of considerable research, however, the impact of synoptic-scale weather conditions on UO magnitude, particularly in a coastal city that is also near the desert landmass (Sydney) has never been investigated before. The present research examines the influence of synoptic-scale weather conditions on UO magnitude in Sydney by utilizing the newly developed gridded weather typing classification (GWTC). The diurnal, and seasonal variations in suburban-urban temperature contrast (ΔT) in association with synoptic-scale weather conditions, and ΔT response to synoptic air-masses during extreme heat events are investigated in three zones of Sydney. Generally, an exacerbation in UO magnitude was reported at daytime over the years, whereas the nocturnal UO magnitude was alleviated over time. The humid warm (HW), and warm (W) air-masses were found primarily responsible for exacerbated daytime UO during extreme heat events and in all other seasons, raising the mean daily maximum ΔT to 8-10.5 °C in Western Sydney, and 5-6.5 °C in inner Sydney. The dry warm (DW), and W conditions were mainly responsible for urban cooling (UC) at nighttime, bringing down the mean daily minimum ΔT to – 7.5 to – 10 °C in Western Sydney, and – 6 to – 7.5 °C in inner Sydney. The appropriate mitigation technologies can be planned based on this study to alleviate the higher daytime temperatures in the Sydney suburbs.
BACKGROUND: Though inconsistent, acute effects of ambient nitrogen oxides on cardiovascular mortality have been reported. Whereas, interactive roles of temperature on their relationships and joint effects of different indicators of nitrogen oxides were less studied. This study aimed to extrapolate the independent roles of ambient nitrogen oxides and temperature interactions on cardiovascular mortality. METHODS: Data on mortality, air pollutants, and meteorological factors in Shenzhen from 2013 to 2019 were collected. Three indicators including nitric oxide (NO), nitrogen dioxide (NO(2)), and nitrogen oxides (NO(X)) were studied. Adjusted generalized additive models (GAMs) were applied to analyse their associations with cardiovascular mortality in different groups. RESULTS: The average daily concentrations of NO, NO(2), and NO(X) were 11.7 μg/m^3, 30.7 μg/m^3, and 53.2 μg/m3, respectively. Significant associations were shown with each indicator. Cumulative effects of nitrogen oxides were more obvious than distributed lag effects. Males, population under 65 years old, and population with stroke-related condition were more susceptible to nitrogen oxides. Adverse effects of nitrogen oxides were more significant at low temperature. Impacts of NO(2) on cardiovascular mortality, and NO on stroke mortality were the most robust in the multi-pollutant models, whereas variations were shown in the other relationships. CONCLUSIONS: Low levels of nitrogen oxides showed acute and adverse impacts and the interactive roles of temperature on cardiovascular mortality. Cumulative effects were most significant and joint effects of nitrogen oxides required more attention. Population under 65 years old and population with stroke-related health condition were susceptible, especially days at lower temperature.
The heat increase caused by climate change has worsened the urban heat environment and damaged human health, which has led to heat-related mortality. One of the most important ways to respond to heat-related damage is to develop effective forecasting tools. However, accurately predicting heatwave damage is difficult in regions in a city with different conditions. Damage due to extreme heat can be evaluated differently in each region, as climatic, demographic and socioeconomic sectors are diversely distributed across local areas. In this study, we develop a random forest-based model for estimating the occurrence of heat-related mortality in a detailed spatial unit within a city. Through hyperparameter optimization, the model yielded accuracy, F1-score and AUC values of 90.3%, 94.75%, and 86%, respectively. The estimation results of the model were interpreted from the global and local perspectives by introducing the latest SHAP method. As a result of interpretation, demographic, socioeconomic and climatic sectors were determined to contribute the most to the estimation process. This is the first study of partial scenarios through the development and interpretation of a spatial unit machine learning-based occurrence estimation model for heat-related mortality.
The frequency and intensity of compound hot extremes will be likely to increase in the context of global warming. Epidemiological studies have demonstrated the adverse effect of simple hot extreme events on mortality, but little is known about the effects of compound hot extremes on mortality. Daily meteorological, demographic, and mortality data during 2011-2017 were collected from 160 streets in Guangzhou City, China. We used distributed lag non-linear model (DLNM) to analyze the associations of different hot extremes with mortality risk in each street. Street-specific associations were then combined using a meta-analysis approach. To assess the spatial distribution of vulnerability to compound hot extremes, vulnerable characteristics at street level were selected using random forest model, and then we calculated and mapped spatial vulnerability index (SVI) at each street in Guangzhou. At street level, compared with normal day, compound hot extreme significantly increased mortality risk (relative risk(RR)=1.43, 95%CI:1.28-1.59) with higher risk for female (RR=1.54 [1.35-1.76]) and the elderly(RR for aged 65-74=1.41 [1.14-1.74]; RR for ≥75years=1.63 [1.45-1.84]) than male (RR=1.32 [1.15-1.52]) and population <65 years (RR=1.01 [0.83-1.22]). Areas with high vulnerability were in the urban center and the edge of suburban. High proportion of population over 64 years old in urban center, and high proportions of outdoor workers and population with illiteracy in suburban areas were the determinants of spatial vulnerability. We found that compound hot extreme significantly increased mortality risk at street level, which is modified by socio-economic and demographic factors. Our findings help allocate resources targeting vulnerable areas at fine-spatial scale.°.
BACKGROUND: Previous studies have reported numerous environmental factors for atopic dermatitis (AD), such as allergens and chemical stimulants. However, few studies have addressed the relationship between ambient air pollution and AD at a population level. OBJECTIVE: To evaluate the effect of air pollutants on medical care visits for AD and to identify susceptible populations. METHODS: In this time-series study conducted on 513,870 medical care visits for AD from 2012 to 2015 identified by reviewing national health insurance claim data in Incheon, Republic of Korea. Treating daily number of medical care visits for AD as a dependent variable, generalized additive models with Poisson distributions were constructed, which included air pollutant levels, ambient temperature, relative humidity, day of the week, national holiday, and season. Risks were expressed as relative risks (RR) with 95% confidence intervals (95% CIs) per interquartile range increase of each air pollutant. RESULTS: Higher levels of particulate matter of diameter ≤10 μm (PM(10)) (RR, 1.009; 95% CI, 1.007-1.012), ozone (1.028; 1.023-1.033), and sulfur dioxide (1.033; 1.030-1.037) were significantly associated with increased risk of medical care visits for AD on same days. In all age and sex groups, ozone was associated with a significantly higher risk of medical care visits, with the greatest risk among 13- to 18-year-old males (RR, 1.127; 95% CI, 1.095-1.159). CONCLUSION: This study suggests relationships of ambient PM(10), ozone, and sulfur dioxide levels with medical care visits for AD.
Several air pollution episodes occurred in Beijing before and after the 2014 Asia-Pacific Economic Cooperation (APEC) summit, during which air-pollution control measures were implemented. Within this autumn-winter transit season, domestic heating started. Such interesting period merits comprehensive chemical characterization, particularly the organic species, to look into the influence of additional heating sources and the control measures on air pollution. Therefore, this study performed daily and 6h time resolved PM2.5 sampling from the 24th October to 7th December, 2014, followed by comprehensive chemical analyses including water-soluble ions, elements and organic source-markers. Apparent alterations of chemical profiles were observed with the initiation of domestic heating. Through positive matrix factorization (PMF) source apportionment modeling, six PM2.5 sources including secondary inorganic aerosol (SIA), traffic emission, coal combustion, industry emission, biomass burning and dust were separated and identified. Coal combustion was successfully distinguished from traffic emission by hopane diagnostic ratio. The result of this study reveals a gradual shift of dominating sources for PM pollution episodes from SIA to primary sources after starting heating. BaPeq toxicity from coal combustion increased on average by several to dozens of times in the heating period, causing both long-term and short-term health risk. Air mass trajectory analysis highlights the regional influence of the industry emissions from the area south to Beijing. Control measures taken during APEC were found to be effective for reducing industry source, but less effective in reducing the overall PM2.5 level. These results provide implications for policy making regarding appropriate air pollution control measures. (c) 2021 Elsevier Ltd. All rights reserved.
The urban heat island (UHI) phenomenon has become a major concern for city sustainability in the wake of global warming and rapid urbanization. This has resulted in increased heat stress and worsened outdoor thermal comfort in urban microclimates. The study demonstrated that outdoor thermal stress pedestrians can be reduced in single streets by adopting mitigation strategies, that is, cool materials, vegetation, and water bodies. In this article, computational fluid dynamics (CFD) simulations using URANS modeling for four different scenarios have been performed to investigate the effectiveness of different mitigation measures in hot, humid urban climates conditions. The reduction of ambient air temperature and surface temperature characterizing the mitigation (cooling) intensity is examined at pedestrian height and diverse vertical levels. The analysis shows that on its own, water provides the largest reduction in air temperature at pedestrian height (2 degrees C), and cool materials provide a larger reduction in surface temperature (6 degrees C). When applied individually, cool materials are the more effective in the vertical direction with a UHI mitigation intensity of 1.5 degrees C, followed by vegetation, with a mitigation intensity of 1.0 degrees C. Furthermore, the impact (temperature reduction) is more significant when all three measures are combined, with a large reduction of 2 degrees C in air temperature and 9 degrees C in surface temperature observed compared to the reference case.
This study aims to develop and validate prediction models for the number of all heatstroke cases, and heatstrokes of hospital admission and death cases per city per 12 h, using multiple weather information and a population-based database for heatstroke patients in 16 Japanese cities (corresponding to around a 10,000,000 population size). In the testing dataset, mean absolute percentage error of generalized linear models with wet bulb globe temperature as the only predictor and the optimal models, respectively, are 43.0% and 14.8% for spikes in the number of all heatstroke cases, and 37.7% and 10.6% for spikes in the number of heatstrokes of hospital admission and death cases. The optimal models predict the spikes in the number of heatstrokes well by machine learning methods including non-linear multivariable predictors and/or under-sampling and bagging. Here, we develop prediction models whose predictive performances are high enough to be implemented in public health settings.
Urban heat islands (UHI) are a widely documented phenomenon that adversely increases urban overheating and, among other effects, contributes to heat-related mortalities and morbidities in urban areas. Consequently, comprehensive UHI-mitigating measures are essential for improving urban microclimate environments and contributing to salutogenic urban design practices. This study proposed urban cooling strategies involving different tree percentages and leaf area densities in a dense urban area during the summertime in Korea. The cooling effects of sixteen various combinations of proposed scenarios based on common urban tree types were studied via in-situ field measurements and numerical modeling, considering both vegetated and exposed areas. It was observed that by changing the characteristics of the leaf area density (LAD) per plant of our vegetated base area—for instance, from 4% trees to 60% trees, from a low LAD to a high LAD—the daily average and daily maximum temperatures were reduced by approximately 3 °C and 5.23 °C, respectively. The obtained results demonstrate the usefulness of urban trees to mitigate urban heating, and they are particularly useful to urban designers and policymakers in their efforts to minimize UHI effects.
A few studies on outdoor human thermal comfort (HTC) have been conducted in the tropical region in a hot and humid climate; however, there is a paucity of discussions on how exactly different spatial settings influence HTC. Thus, this paper aims to examine how land use land cover (LULC) affects HTC on the basis of the simulation of Predicted Mean Vote (PMV) and Physiologically Equivalent Temperature (PET) indices via ENVI-met and Rayman. The results reveal that people living in the urban area have a higher tendency to experience strong heat stress (25% of the areas with PMV ranging from 3.4 to 3.9 and 2% of the areas, where PMV reached 4.1), followed by the rural area (43% of the areas with PMV ranging from 2.1 to 2.4), and the suburban area (more than 50% of the areas with PMV values less than 2.4). Surprisingly, a concrete LULC in the suburb area exhibits a higher air temperature than an asphalt surface at 4 p.m., due to the large area of high albedo that increases the reflection of solar radiation, subsequently contributing to warming up the airmass. Similarly, sandy, and loamy LULC tend to emit more heat during nighttime, while the heat is absorbed slowly during daytime, and it is then slowly released during nighttime after 6 p.m. Spatial settings that promote heat stress in the urban area are mainly contributed by an LULC of asphalt, concrete, sandy, and loamy areas. Meanwhile, people in the suburban and rural areas are less likely to experience heat stress, due to agricultural plantations and lowland forest that provide shade, except for the barren lands-loamy areas. The result also indicates that tree-covered areas near the river in the suburban area afforded the best thermal experience with PMV of 2.1 and PET of 30.7. From the LULC comparison, it is pivotal to consider tree species (canopy density), surface material (albedo), sky-view factor, wind direction, and speed toward designing a more comfortable and sustainable environment.
In this study, we aimed to develop and validate a machine learning-based mortality prediction model for hospitalized heat-related illness patients. After 2393 hospitalized patients were extracted from a multicentered heat-related illness registry in Japan, subjects were divided into the training set for development (n = 1516, data from 2014, 2017-2019) and the test set (n = 877, data from 2020) for validation. Twenty-four variables including characteristics of patients, vital signs, and laboratory test data at hospital arrival were trained as predictor features for machine learning. The outcome was death during hospital stay. In validation, the developed machine learning models (logistic regression, support vector machine, random forest, XGBoost) demonstrated favorable performance for outcome prediction with significantly increased values of the area under the precision-recall curve (AUPR) of 0.415 [95% confidence interval (CI) 0.336-0.494], 0.395 [CI 0.318-0.472], 0.426 [CI 0.346-0.506], and 0.528 [CI 0.442-0.614], respectively, compared to that of the conventional acute physiology and chronic health evaluation (APACHE)-II score of 0.287 [CI 0.222-0.351] as a reference standard. The area under the receiver operating characteristic curve (AUROC) values were also high over 0.92 in all models, although there were no statistical differences compared to APACHE-II. This is the first demonstration of the potential of machine learning-based mortality prediction models for heat-related illnesses.
The changing climate has introduced new and unique challenges and threats to humans and their environment. Urban dwellers in particular have suffered from increased levels of heat stress, and the situation is predicted to continue to worsen in the future. Attention toward urban climate change adaptation has increased more than ever before, but previous studies have focused on indoor and outdoor temperature patterns separately. The objective of this research is to assess the indoor and outdoor temperature patterns of different urban settlements. Remote sensing data, together with air temperature data collected with temperature data loggers, were used to analyze land surface temperature (outdoor temperature) and air temperature (indoor temperature). A hot and cold spot analysis was performed to identify the statistically significant clusters of high and low temperature data. The results showed a distinct temperature pattern across different residential units. Districts with dense urban settlements show a warmer outdoor temperature than do more sparsely developed districts. Dense urban settlements show cooler indoor temperatures during the day and night, while newly built districts show cooler outdoor temperatures during the warm season. Understanding indoor and outdoor temperature patterns simultaneously could help to better identify districts that are vulnerable to heat stress in each city. Recognizing vulnerable districts could minimize the impact of heat stress on inhabitants.
Global climate is changing as a result of anthropogenic warming, leading to higher daily excursions of temperature in cities. Such elevated temperatures have great implications on human thermal comfort and heat stress, which should be closely monitored. Current methods for heat exposure assessments (surveys, microclimate measurements, and laboratory experiments), however, present several limitations: measurements are scattered in time and space and data gathered on outdoor thermal stress and comfort often does not include physiological and behavioral parameters. To address these shortcomings, Project Coolbit aims to introduce a human-centric approach to thermal comfort assessments. In this study, we propose and evaluate the use of wrist-mounted wearable devices to monitor environmental and physiological responses that span a wide range of spatial and temporal distributions. We introduce an integrated wearable weather station that records (a) microclimate parameters (such as air temperature and humidity), (b) physiological parameters (heart rate, skin temperature and humidity), and (c) subjective feedback. The feasibility of this methodology to assess thermal comfort and heat stress is then evaluated using two sets of experiments: controlled-environment physiological data collection, and outdoor environmental data collection. We find that using the data obtained through the wrist-mounted wearables, core temperature can be predicted non-invasively with 95 percent of target attainment within +/- 0.27 degrees C. Additionally, a direct connection between the air temperature at the wrist (T-a,T-w) and the perceived activity level (PAV) of individuals was drawn. We observe that with increased T-a,T-w, the desire for physical activity is significantly reduced, reaching ‘Transition only’ PAV level at 36 degrees C. These assessments reveal that the wearable methodology provides a comprehensive and accurate representation of human heat exposure, which can be extended in real-time to cover a large spatial distribution in a given city and quantify the impact of heat exposure on human life.
Extreme heat is a leading cause of weather-related human mortality throughout much of the world, posing a significantly heavy burden on the development of healthy and sustainable cities. To effectively reduce heat health risk, a better understanding of where and what risk factors should be targeted for intervention is necessary. However, little research has examined how different risk factors for heat-related mortality operate at varying spatial scales. Here, we present a novel application of the multiscale geographically weighted regression (GWR) approach to explore the scale of effect of each underlying risk factor using Hong Kong as a case study. We find that a hybrid of global and local processes via multiscale GWR yields a better fit of heat-related mortality risk than models using GWR and ordinary least squares (OLS) approaches. Predictor variables are categorized by the scale of effect into global variables (i.e., age and education attainment, socioeconomic status), intermediate variables (i.e., work place, birth place and language), and local variables (i.e., thermal environment, low in-come). These findings enrich our understanding of the spatial scale-dependent risk factors for heat-related mortality and shed light on the importance of hierarchical policy-making and site-specific planning processes in effective heat hazard mitigation and climate adaptation strategies.
Rising temperatures are causing distress across the world, and for those most vulnerable, it is a silent killer. Information about indoor air temperature in residential dwellings is of interest for a range of reasons, such as health, thermal comfort and coping practices. However, there have been only few studies that measure indoor heat exposure, and contrast these to outdoor temperatures in rural-urban areas, of which none are in South Asia. We aim to close this knowledge gap with our indoor and outdoor heat measurement dataset, covering five low-income sites in South Asia. Two sites are in rural areas (Maharashtra, India), while three sites focus on urban areas (Dhaka, Delhi and Faisalabad). Data are based on 206 indoor temperature data loggers and complemented by data from five outdoor automated weather stations. The data-set can be used to examine temperature and humidity variation in low-socioeconomic status households in rural and urban areas and to better understand factors aggravating heat stress. This is important to plan and implement actions for combating heat stress.
The health and economic impacts of extreme heat on humans are especially pronounced in populations without the means to adapt. We deployed a sensor network across 12 informal settlements in Makassar, Indonesia to measure the thermal environment that people experience inside and outside their homes. We calculated two metrics to assess the magnitude and frequency of heat stress conditions, wet bulb temperature and wet bulb globe temperature, and compared our in situ data to that collected by weather stations. We found that informal settlement residents experience chronic heat stress conditions, which are underestimated by weather stations. Wet bulb temperatures approached the uppermost limits of human survivability, and wet bulb globe temperatures regularly exceeded recommended physical activity thresholds, both in houses and outdoors. Under a warming climate, a growing number of people living informally will face potentially severe impacts from heat stress that have likely been previously overlooked or underestimated.
The Intergovernmental Panel on Climate Change (IPCC) projects that the frequency of heat waves (HWs) is likely to increase over most land areas in the twenty-first century. Recurrent HWs are an emerging environmental and health concern and already distress in rapidly growing and fast urbanizing South Asia. A review of original research publications of the past five decades from peer-reviewed journals and conference proceedings, covering South Asia, revealed that the region is constantly experiencing the warmest temperatures. The review attempts to comprehend HWs in different contexts, geographic locations, and on previous studies. The paper presents a compre-hensive review of existing plans/policies/guidelines in South Asia at the national/regional/city level to counter extreme heat risk. The study is extended to identify the issues and gaps in the current policies and frameworks in the larger setting of urban planning measures for adaptation and mitigation efforts. A specific set of long-term actions and vulnerability assessment concen-trated on cities must be developed and integrated into a defined heat action plan coupled with improvements in urban and regional planning. Policies and actions must address the issues of the built environment in land use/planning and address the existing institutional and implementation gaps.
Heat risk assessment is important due to serious health problems caused by heat waves. The complexity and diversity of socio-ecological characteristics in urban areas that lead to heat risk are more serious in heat-exposed areas, while risk assessments and determinant based on individuals in heat-exposed areas have been neglected in previous studies. This study pursues a new idea of combining questionnaire surveys and remote sensing analysis to identify urban heat-exposed areas and assess heat risk in heat-exposed areas of Beijing, China. Morphological spatial pattern analysis (MSPA) was used to identify large and continuous hotspot regions as urban heat-exposed areas based on summer surface temperature from 2011 to 2017. A total of 1484 valid questionnaires were completed by residents of heat-exposed areas. The majority of respondents (96.4%) indicated that they perceived heat risk. Moreover, the residents without a local “hukou” were a potentially vulnerable group (note: hukou refers to the population registration management system.). This study further analysed the diversity of community types within the heat-exposed areas. There were significant differences in heat risk among the different community types of multi-story residential districts, Hutong (a traditional architectural form) residential districts and city villages. In particular, the degree of heat risk perceived by residents living in these the community types was determined by whether they had pre-existing medical conditions; however, age only played a decisive role in city villages. This study not only enriches the current understanding of health risks affected by heat waves but also explores the determinants contributing to the severity of heat risk. The output provides important information for future development of heat mitigation and adaptation strategies.
In recent years, the phenomenon of urban warming has become increasingly serious, and with the number of urban residents increasing, the risk of heatstroke in extreme weather has become higher than ever. In order to mitigate urban warming and adapt to it, many researchers have been paying increasing attention to outdoor thermal comfort. The mean radiant temperature (MRT) is one of the most important variables affecting human thermal comfort in outdoor urban spaces. The purpose of this paper is to predict the distribution of MRT around buildings based on a commonly used multilayer neural network (MLNN) that is optimized by genetic algorithms (GA) and backpropagation (BP) algorithms. Weather data from 2014 to 2018 together with the related indexes of the grid were selected as the input parameters for neural network training, and the distribution of the MRT around buildings in 2019 was predicted. This study obtained very high prediction accuracy, which can be combined with sensitivity analysis methods to analyze the important input parameters affecting the MRT on hot summer days (the days with the highest air temperature over 30 degrees C). This has significant implications for the optimization strategies for future building and urban designers to improve the thermal conditions around buildings.
Urban heat challenges are increasingly severe, along with climate change and urbanisation. Despite significant environmental, economic, and social consequences, limited actions have been conducted to address urban heat challenges. To support the formulation of heat-health plans and guidelines at the city and community scale, this study presented results, through a questionnaire survey among 584 respondents in Shanghai, China, on heat-induced physiological and psychological impacts and analysed the variability of them with demographic characteristics. The results indicate that psychological impacts were more severe than physiological impacts in severity and susceptible people. Skin heat damage and digestive system diseases were ignored in previous studies, compared with fatal cardiovascular and respiratory diseases. Emotional irritability and difficulty in controlling temper were the two most prominent psychological symptoms. The elderly and health-vulnerable groups were more susceptible to heat-induced physiological and psychological impacts than other groups. Among different demographic groups, the most critical physiological and psychological symptoms could vary significantly. Afterwards, suggestions for heat-health plans or guidelines have been proposed. Overall, this study provides a reference for the understanding of heat-induced impacts and enhancing the capacity to cope with urban heat challenges.
This study proposes the methodology to identify heatwave hotspots in Seoul, the metropolis of Korea, using high-resolution data. Resident credit data, population mobility data, and temperature observation data are analyzed to determine vulnerable regions to heatwaves. Potentially vulnerable regions are derived in two ways: static vulnerable regions (SVRs) and dynamic vulnerable regions (DVRs), depending on their characteristics. SVRs are determined by lowincome (lower 20% income quantile) residential areas fixed on time. In contrast, DVRs vary with the time and day of the week. DVRs are defined by the place less responsive to heatwaves, where are with low population variability and low correlation with temperature. The final vulnerable regions, so-called hotspots, are determined by the high temperature predicted area where the SVRs and DVRs intersect. We examine how to remove commuting-related displacement signals, which are represented as noise when analyzing population mobility. An example of the hotspots identification result is also shown using temperature hindcast data generated by the Korean Meteorological Administration short-range forecast system. Applying the vulnerability information can improve the quality of disaster planning and decision-making by highlighting the time and area of need for resources in the implementation of short-and long-term disaster response.
Heat stress events in urban areas are increasing as a result of global warming and urban heat islands. In response to heat stress, outdoor activators naturally often move themselves to a less hot place. An understanding of human physiological responses in dynamic outdoor thermal environments is desired. This study aims to reveal the dynamic physiological adjustment and thermal perception response characteristics under varying outdoor heat stress conditions. A robust model for predicting dynamic thermal sensation outdoors has been developed. Experiments involving heat stress changes in a hot summer were conducted with 25 subjects. Three categories of data were collected including meteorological data, physiological parameters, and thermal perception. The results showed that lower-arm skin temperature (T-lowerarm) is more sensitive to changes in the outdoor thermal environment, and correlates closely with the thermal sensation vote (TSV). For a better practical application, based on the strong linear relationship between T-lowerarm and T-ty, the new dynamic outdoor thermal sensation model has been developed involving two parameters: T-lowerarm and delta T-lowerarm/delta t (the change rate of T-lowerarm). The validity of the model in transient outdoor conditions was verified. The algorithm can be integrated into a wearable armband to predict practical thermal sensation responses. This contribution will advance technologies based on the scientific findings to provide alert services to support human health and wellbeing, consequently increasing urban resilience and sustainability.
Climate change (CC) and urban heat island (UHI) are important environmental forces that have serious consequences for the existing buildings, such as increased resource consumption and environmental footprint, adverse human health effects and reduced occupant comfort. In this context, educational buildings represent a critical category amongst other building typologies, due to their high energy use, high occupant density, atypical daily/annual occupancy patterns, and their occupants’ high vulnerability to heat. Poor indoor conditions can reduce the health and productivity of students and teachers, worsen learning performance and reduce attendance. Retrofitting educational buildings is an effective solution to tackle this challenge. This study investigates the impact of CC&UHI on educational building performance and demonstrates the effectiveness of passive retrofit scenarios targeting CC&UHI mitigation and adaptation. These investigations are based on a systematic approach that consists of (i) the generation and analyses of CC&UHI-modified weather datasets, and (ii) simulation-based comparative analyses of the as-is building and various retrofit scenarios. An existing secondary school building in Ankara, Turkey is selected as a case study for evaluations of the selected performance indicators including energy use, global warming potential (GWP) and thermal comfort. Obtained results indicate that total energy consumption can be reduced up to 50% with retrofit, whereas possible reductions in indoor discomfort are even more pronounced, underlining the significance of selecting the optimal combination of passive measures for maximum impact towards the adaptation of the existing educational buildings to the changes in climatic conditions.
Elderly residents are prominent users of urban parks and comfortable open spaces in parks have been shown to improve their physical health and mental well-being. In this study, the thermal perceptions (thermal sensation, thermal comfort and thermal acceptability) of elderly visitors to an urban park in Xi’an, China was investigated using meteorological measurements, questionnaire surveys and activity records. Physiological equivalent temperature (PET) was used to determine thermal benchmarks. Spatial-temporal distributions of the elderly in open spaces were recorded and relationships among elderly residents’ thermal perceptions, their age and chronic disease were analyzed. Finally, optimal design strategies for open spaces suitable for the elderly were proposed based on meteorological characteristics, elderly residents’ attendance patterns and their thermal perceptions. Results showed that: 1) globe temperature (T(g)) and air temperature (T(a)) were the primary meteorological factors that influenced elderly residents’ thermal sensation while clothing insulation and activity intensity were negatively correlated with their thermal sensation. 2) Attendance was significantly affected by the outdoor microclimate, space functionality and facilities in spaces. The elderly mainly participated in dynamic activities and social interaction. 3) The neutral PET (NPET) was 13.2 °C, with NPET range (NPETR) of 3.1-23.2 °C. The 90% thermal acceptable PET ranged between 10.9 and 25.9 °C, and the preferred PET was 14.4 °C. Compared with the ISO7730 standard, the predicted percentage of dissatisfied (PPD) elderly park users was lower than users of indoor spaces when -1 ≤ MTSV ≤ + 1, indicating that the elderly preferred to conduct activities outside when the environment was comfortable. Additionally, NPET for the elderly with respiratory disease was higher than those with cardiovascular diseases and diabetes. 4) Optimal design strategies for open spaces were proposed for elderly residents based on their physical, physiological and psychological preferences.
Actively addressing urban heat challenges is an urgent task for numerous cities. Existing studies have primarily developed heat mitigation strategies and analyzed their cooling performance, while the adaptation strategies are far from comprehensive to protect citizens from heat-related illnesses and deaths. To address this research gap, this paper aims to enhance people’s adaptation capacity by investigating walkability within fifteen-minute cities (FMC). Taking cognizance of thermal comfort, health, and safety, this paper developed a dynamic attenuation model (DAM) of heat stress, along with heat stress aggravation, continuance, and alleviation. An indicator of remaining tolerant heat discomfort (R (t) ) was proposed with the integration of the Universal Thermal Climate Index (UTCI) to assess heat-related walkability. Following an empirical study among 128 residents in Mianyang, China, and assessing four levels of heat stress, the maximum tolerant heat discomfort was determined to be 60 min. Furthermore, the DAM was applied to an FMC with 12 neighborhoods in Fucheng, Mianyang, China. The results indicate that for each neighborhood, the street was generally walkable with an R (t) ranging between 15 and 30 min, after walking for 900 m. A population-based FMC walkability was further determined, finding that the core area of the FMC was favorable for walking with an R (t) of 45-46 min, and the perpetual areas were also walkable with an R (t) of 15-30 min. Based on these results, suggestions on the frequency of public services (frequently used, often used, and occasionally used) planning were presented. Overall, this paper provides a theoretical model for analyzing walkability and outlines meaningful implications for planning heat adaptation in resilient, safe, comfortable, and livable FMCs.
Due to direct exposure to high temperatures in summer, sanitation workers can easily experience heat-related illness and even mortality. This paper aims to determine the thresholds of the environmental parameters for sanitation workers in summer. Firstly, a field test of sanitation workers was conducted, the environmental parameters (solar radiation intensity, dry bulb temperature, wind speed and relative humidity) and mean skin temperature were measured, and the thermal comfort and work willingness were investigated via a questionnaire. Then, the mathematical programming method was adopted to obtain the safety limits and danger limits of the environmental parameters. Finally, the thresholds of the outdoor heat stress indexes, namely, the environmental stress index (ESI), discomfort index (DI), heat index (HI) and relative strain index (RSI) were obtained. The results indicate that a high solar radiation intensity, high dry bulb temperature, high wind speed and low humidity will cause more adverse effects on sanitation workers in summer. The safety limits of the solar radiation intensity, dry bulb temperature, wind speed and relative humidity are 182.42 W/m(2), 28.42 degrees C, 0.15 m/s and 71.35%, respectively, and the danger limit value are 876.86 W/m(2), 34.98 degrees C, 1.27 m/s and 36.59%, respectively. In addition, the safety limit values of the ESI, DI, HI and RSI are 27.08 degrees C, 26.23 degrees C, 31.71 degrees C and 0.13, respectively; and the danger limit values are 29.60 degrees C, 27.84 degrees C, 36.21 degrees C and 0.24, respectively. This paper can provide a study method and reference data for the work arrangement and health protection of sanitation workers in summer.
BACKGROUND: Although urbanization is often an important topic in climate change studies, the complex effect of urbanization on heat vulnerability in urban and rural areas has rarely been studied. We investigated the disparate effects of urbanization on heat vulnerability in urban and rural areas, using nationwide data. METHODS: We collected daily weather data for all 229 administrative districts in South Korea (2011-17). Population density was applied as an urbanization indicator. We calculated the heat-mortality risk using a distributed lag nonlinear model and analysed the relationship with population density. We also examined district characteristics that can be related to the spatial heterogeneity in heat-mortality risk. RESULTS: We found a U-shaped association between population density and heat-mortality risk, with the highest risk for rural populations; in urban areas, risk increases with increasing population density. Higher heat-mortality risk was associated with a lower number of hospital beds per person and higher percentage of people requiring recuperation. The association between hospital beds and heat-mortality risk was prominent in high-density urban areas, whereas the association between the percentage of people requiring recuperation and heat-mortality risk was pronounced in rural areas. CONCLUSIONS: Our findings indicate that the association between population density and heat-mortality risk is different in urban and rural areas, and that district characteristics related to heat-mortality risk also differ by urbanicity. These results can contribute to understanding the complex role of urbanization on heat vulnerability and can provide evidence to policy makers for prioritizing resources.
Access to urban greenspace has many benefits such as improved health and social cohesion. If access differs by population, these benefits make access to greenspace an environmental justice issue, but little is known regarding accessibility of parks among different sub-groups in Seoul, South Korea. We explored potential socioeconomic inequities for access to parks in Seoul measuring two park provision metrics: total park area per capita (TPPC), and park accessibility index determined by size and proximity of parks. We assessed correlations between a deprivation index for the 25 Gus (administrative unit equivalent to the US borough) and each park provision metric. Regression analyses were applied for the associations between eight socioeconomic indicators of the 424 Dongs (equivalent to the US neighborhood) and each park provision metric. An interquartile range (IQR) increase in percent elderly (> 65 years) (3.2%) was significantly associated with larger TPPC (1.6 m(2)/person, 95% CI: 0.8, 2.4). Park accessibility index was associated with more socioeconomic variables than was TPPC. An IQR increase in percent elderly and divorce rates (1.2/1000 population) was associated with increased park accessibility by 3571 km (95% CI: 1103, 6040) and decreased park accessibility by 1387 (95% CI: -2706, -67), respectively. An IQR increase in percentage of the population receiving social low-income support aid (2.2%) was associated with increased park accessibility (reflecting park size and proximity of parks) of residential parks near residential areas by 1568 (95% CI: 15, 3120). Results suggest higher park access for socioeconomically disadvantaged regions. Findings indicate that measures of detailed park access considering spatial proximity and park size may more accurately measure park inequity compared to more basic metrics (e.g. TPPC), which may bias estimation of park inequity by capturing only one characteristic of parks. Detailed park measures should be considered in urban planning and health studies of greenspace.
Heat waves are unusually high temperature events over consecutive days and may cause adverse impacts such as morbidity and mortality. The interaction between heat waves and urban heat island (UHI) effects has remained a subject of debate, as some studies prove heat wave-UHI synergy while others do not. Furthermore, heat waves affect tropical cities more severely than mid-latitude cities, but there is a disproportionate lack of heat wave studies focusing on tropical cities. We attempt to narrow this gap by studying the heat wave in Singapore in April 2016 using ground observations and the Weather Research and Forecasting (WRF) model. Compared to non-heat wave days, the ground observations show that daytime temperatures can be 3 degrees C higher during the heat wave. Despite the temperature spike, the UHI intensity is not amplified during the heat wave, maintaining its peak near 2.5 degrees C during both heat wave and non-heat wave periods. WRF simulation results also agree well with measurements and predict UHI peaks near 2.5 degrees C during both periods, showing no heat wave-UHI synergy. The spatially averaged UHI intensity also shows no such synergy. There is no significant change of wind speed, soil moisture availability or heat storage flux during the heat wave. Therefore, the lack of heat wave-UHI synergy in our study is consistent with current understanding of factors contributing to UHI. This study shows that the heat wave-UHI interaction in a tropical city can be different from that in cities in the temperate climate zone and more studies should be conducted in tropical cities, which are projected to suffer larger impacts of increasing heat stress.
Climate change causing an increase of frequency and magnitude of heat waves has a huge impact on the urban population worldwide. In Indonesia, the Southeast Asian country in the tropical climate zone, the increasing heat wave duration due to climate change will be also magnified by projected rapid urbanization. Therefore, not only climate change mitigation measures but also adaptation solutions to more frequent extreme weather events are necessary. Adaptation is essential at local levels. The projected increase of the heat wave duration will trigger greater health-related risks. It will also drive higher energy demands, particularly in urban areas, for cooling. New smart solutions for growing urbanization for reducing urban heat island phenomenon are critical, but in order to identify them, analyzing the changing magnitude and spatial distribution of urban heat is essential. We projected the current and future spatial variability of heat stress index in three cities in Indonesia, namely, Medan, Surabaya, and Denpasar, under climate change and land-cover change scenarios, and quantified it with the Universal Thermal Climate Index (UTCI) for two periods, baseline (1981-2005) and future (2018-2042). Our results demonstrated that currently the higher level of the UTCI was identified in the urban centers of all three cities, indicating the contribution of urban heat island phenomenon to the higher UTCI. Under climate change scenarios, all three cities will experience increase of the heat, whereas applying the land-cover scenario demonstrated that in only Medan and Denpasar, the UTCI is likely to experience a higher increase by 3.1 degrees C; however, in Surabaya, the UTCI will experience 0.84 degrees C decrease in the period 2018-2042 due to urban greening. This study advanced the UTCI methodology by demonstrating its applicability for urban heat warning systems and for monitoring of the urban green cooling effect, as well as it provides a base for adaptation measures’ planning.
As a highly important meteorological hazard, heat waves notably impact human health and socioeconomics, and accurate heat wave risk identification and assessment are effective ways to address this issue. The current spatial scale of heat wave risk assessment is relatively coarse, hardly meeting fine-scale heat wave risk assessment requirements. Therefore, based on multi-source fine-scale remote sensing data and socioeconomic data, this paper evaluates the heat wave risk along the Jakarta-Bandung high-speed railway, obtains the spatial distribution of heat wave risk in 2005, 2014 and 2019, and analyzes spatiotemporal risk variations over the past 15 years. The results show that most high-risk areas were affected by high-temperature hazards. Over time, the hazard, exposure, vulnerability and risk levels increased by 25.82%, 3.31%, 14.82% and 6.97%, respectively, from 2005-2019. Spatially, the higher risk in the northwest is mainly distributed in Jakarta. Additionally, a comparative analysis was conducted on the risk results, and the results showed that the 100-m scale showed more spatial differences than the kilometer scale. The research results in this paper can provide scientific advice on heat wave risk prevention considering the Jakarta-Bandung high-speed railway construction and regional economic and social development.
BACKGROUND: Climate change, as a defining issue of the current time, is causing severe heat-related illness in the context of extremely hot weather conditions. In Japan, the remarkable temperature increase in summer caused by an urban heat island and climate change has become a threat to public health in recent years. METHODS: This study aimed to determine the potential risk factors for heatstroke by analysing data extracted from the records of emergency transport to the hospital due to heatstroke in Fukuoka City, Japan. In this regard, a negative binomial regression model was used to account for overdispersion in the data. Age-structure analyses of heatstroke patients were also embodied to identify the sub-population of Fukuoka City with the highest susceptibility. RESULTS: The daily maximum temperature and wet-bulb globe temperature (WBGT), along with differences in both the mean temperature and time-weighted temperature from those of the consecutive past days were detected as significant risk factors for heatstroke. Results indicated that there was a positive association between the resulting risk factors and the probability of heatstroke occurrence. The elderly of Fukuoka City aged 70 years or older were found to be the most vulnerable to heatstroke. Most of the aforementioned risk factors also encountered significant and positive associations with the risk of heatstroke occurrence for the group with highest susceptibility. CONCLUSION: These results can provide insights for health professionals and stakeholders in designing their strategies to reduce heatstroke patients and to secure the emergency transport systems in summer.
BACKGROUND: The complex role of urbanisation in heat-mortality risk has not been fully studied. Japan has experienced a rapid population increase and densification in metropolitan areas since the 2000s; we investigated the effects of population concentration in metropolitan areas on heat-mortality risk using nationwide data. METHODS: We collected time-series data for mortality and weather variables for all 47 prefectures in Japan (1980-2015). The prefectures were classified into three sub-areas based on population size: lowest (<1 500 000), intermediate (1 500 000 to 3 000 000), and highest (>3 000 000; i.e. metropolitan areas). Regional indicators associated with the population concentration of metropolitan areas were obtained. RESULTS: Since the 2000s, the population concentration intensified in the metropolitan areas, with the highest heat-mortality risk in prefectures with the highest population. Higher population density and apartment % as well as lower forest area and medical services were associated with higher heat-mortality risk; these associations have generally become stronger since the 2000s. CONCLUSIONS: Population concentration in metropolitan areas intensified interregional disparities in demography, living environments, and medical services in Japan; these disparities were associated with higher heat-mortality risk. Our results can contribute to policies to reduce vulnerability to high temperatures.
A heat danger day is defined as an extreme when the heat stress index (a combined temperature and humidity measure) exceeding 41 degrees C, warranting public heat alerts. This study assesses future heat risk (i.e. heat danger days times the population at risk) based on the latest Coupled Model Intercomparison Project phase 6 projections. In recent decades (1995-2014) China’s urban agglomerations (Beijing-Tianjin-Hebei, Yangtze River Delta, Middle Yangtze River, Chongqing-Chengdu, and Pearl River Delta (PRD)) experienced no more than three heat danger days per year, but this number is projected to increase to 3-13 days during the population explosion period (2041-2060) under the high-emission shared socioeconomic pathways (SSP3-7.0 and SSP5-8.5). This increase will result in approximately 260 million people in these agglomerations facing more than three heat danger days annually, accounting for 19% of the total population of China, and will double the current level of overall heat risk. During the period 2081-2100, there will be 8-67 heat danger days per year, 60%-90% of the urban agglomerations will exceed the current baseline number, and nearly 310 million people (39% of the total China population) will be exposed to the danger, with the overall heat risk exceeding 18 times the present level. The greatest risk is projected in the PRD region with 67 heat danger days to occur annually under SSP5-8.5. With 65 million people (68% of the total population) experiencing increased heat danger days, the overall heat risk in the region will swell by a factor of 50. Conversely, under the low-emission pathways (SSP1-2.6 and SSP2-4.5), the annual heat danger days will remain similar to the present level or increase slightly. The result indicates the need to develop strategic plans to avoid the increased heat risk of urban agglomerations under high emission-population pathways.
Urban heat island (UHI), referring to higher temperatures in urban extents than its surrounding rural regions, is widely reported in terms of negative effects to both the ecological environment and human health. To propose effective mitigation measurements, spatiotemporal variations and control machines of surface UHI (SUHI) have been widely investigated, in particular based on the indicator of SUHI intensity (SUHII). However, studies on SUHI frequency (SUHIF), an important temporal indicator, are challenged by a large number of missing data in daily land surface temperature (LST). Whether there is any city with strong SUHII and low SUHIF remains unclear. Thanks to the publication of daily seamless all-weather LST, this paper is proposed to investigate spatiotemporal variations of SUHIF, to compare SUHII and SUHIF, to conduct a pattern classification, and to further explore their driving factors across 305 Chinese cities. Four main findings are summarized below: (1) SUHIF is found to be higher in the south during the day, while it is higher in the north at night. Cities within the latitude from 20 degrees N and 40 degrees N indicate strong intensity and high frequency at day. Climate zone-based variations of SUHII and SUHIF are different, in particular at nighttime. (2) SUHIF are observed in great diurnal and seasonal variations. Summer daytime with 3.01 K of SUHII and 80 of SUHIF, possibly coupling with heat waves, increases the risk of heat-related diseases. (3) K-means clustering is employed to conduct pattern classification of the selected cities. SUHIF is found possibly to be consistent to its SUHII in the same city, while they provide quantitative and temporal characters respectively. (4) Controls for SUHIF and SUHII are found in significant variations among temporal scales and different patterns. This paper first conducts a comparison between SUHII and SUHIF, and provides pattern classification for further research and practice on mitigation measurements.
Due to global warming and human activities, heat stress (HS) has become a frequent extreme weather event around the world, especially in megacities. This study aims to quantify the responses of urban HS (UHS) to anthropogenic heat (AH) emission and its antrophogenic sensible heat (ASH)/anthropogenic latent heat (ALH) components and increase in the size of cities in the south and north China for the 2019 summer based on observations and numerical simulations. AH release could aggravate UHS drastically, producing maximal increment in moist entropy (an effective HS metric) above 1 and 2 K over the south and north high-density urban regions mainly through ALH. In contrast, future urban expansion leads to an increase in HS coverage, and it has a larger impact on UHS intensity change (6 and 2 K in south and north China) relative to AH. The city radius of 60 km is a possible threshold to plan to city sprawl. Above that city size, the HS intensity change due to urban expansion tends to slow down in the north and inhibit in the south, and about one-third of the urban regions might be hit by extreme heat stress (EHS), reaching maximal hit ratio. Furthermore, changes in warmest EHS events are more associated with high humidity change responses, irrespective of cities being in the north or south of China, which support the idea that humidity change is the primary driving factor of EHS occurrence. The results of this study serve for effective urban planning and future decision making.
Rapid urbanization greatly alters land surface vegetation cover and heat distribution, leading to the development of the urban heat island (UHI) effect and seriously affecting the healthy development of cities and the comfort of living. As an indicator of urban health and livability, monitoring the distribution of land surface temperature (LST) and discovering its main impacting factors are receiving increasing attention in the effort to develop cities more sustainably. In this study, we analyzed the spatial distribution patterns of LST of the city of Wuhan, China, from 2013 to 2019. We detected hot and cold poles in four seasons through clustering and outlier analysis (based on Anselin local Moran’s I) of LST. Furthermore, we introduced the geographical detector model to quantify the impact of six physical and socio-economic factors, including the digital elevation model (DEM), index-based built-up index (IBI), modified normalized difference water index (MNDWI), normalized difference vegetation index (NDVI), population, and Gross Domestic Product (GDP) on the LST distribution of Wuhan. Finally, to identify the influence of land cover on temperature, the LST of croplands, woodlands, grasslands, and built-up areas was analyzed. The results showed that low temperatures are mainly distributed over water and woodland areas, followed by grasslands; high temperatures are mainly concentrated over built-up areas. The maximum temperature difference between land covers occurs in spring and summer, while this difference can be ignored in winter. MNDWI, IBI, and NDVI are the key driving factors of the thermal values change in Wuhan, especially of their interaction. We found that the temperature of water area and urban green space (woodlands and grasslands) tends to be 5.4 degrees C and 2.6 degrees C lower than that of built-up areas. Our research results can contribute to the urban planning and urban greening of Wuhan and promote the healthy and sustainable development of the city.
The purpose of this work was to assess population vulnerability to heat-related health risks and its relationship with urbanization levels to provide essential information for the future development and policy-making for climate change adaptation. We constructed a heat vulnerability index (HVI), quantified the population heat vulnerability in each county across China by a principal component analysis (PCA) of multiple factors, and assessed urbanization levels in each county using multisource data. Then, the HVI was validated using the heat-attributable fraction (heat-AF) of nonaccidental mortality based on death monitoring data and meteorological data from 95 counties across China. The results showed that our HVI was significantly positively associated with the heat AF of nonaccidental mortality. A negative correlation was observed between the urbanization level and the HVI. The HVI was generally higher in less urbanized western China and lower in the more urbanized eastern regions. The baseline mortality occupies the top position in the importance ranking of the heat-vulnerability indicators at all three urbanization levels, but the other indicators, including the aging rate, agricultural population rate, education, ethnic structure, economic status, air conditioner ownership rate, and number of hospitals, ranked differently among different urbanization levels. This finding indicates that to reduce population heat vulnerability, the most important approach is to improve the health status of the whole population and reduce baseline mortality; additionally, regional-specific measures and emphasis should be adjusted reasonably along with the process of urbanization according to the characteristics and key factors of local heat vulnerability.
Global warming, high temperatures, and heatwave weather are some of the factors affecting human settlement environment health. In high-temperature weather, human production and life are seriously threatened, as long-term exposure to high temperatures causes a variety of diseases, and children and elderly, who have poor tolerance, require strengthened protection. From a human perspective, this study calculated the thermal duration distribution of high temperatures based on maximum temperature data in a central urban area of Beijing combined with the results of the sixth population census of Beijing, investigated the population distribution of individuals under 15 years old and over 65 years old, and analyzed the spatial distribution of a thermal exposure space in a central urban area of Beijing with the help of the ArcGIS platform. Based on 130 district districts, streets with high-risk heat exposure spaces in the central urban area of Beijing were reddened to determine the distribution of high-risk grades. Using the semantic segmentation method and a street view map, the high-risk thermal exposure space environment from the humanistic perspective was restored, and the typical characteristics were summarized and analyzed. Finally, the environmental characteristics of the high-risk thermal exposure space were analyzed from the humanistic perspective, and an improvement strategy for thermal exposure spaces was proposed based on the perspective of emotional relief.
The surface urban heat island (SUHI) effect poses a significant threat to the urban environment and public health. This paper utilized the Local Climate Zone (LCZ) classification and land surface temperature (LST) data to analyze the seasonal dynamics of SUHI in Wuhan based on the Google Earth Engine platform. In addition, the SUHI intensity derived from the traditional urban-rural dichotomy was also calculated for comparison. Seasonal SUHI analysis showed that (1) both LCZ classification and the urban-rural dichotomy confirmed that Wuhan’s SHUI effect was the strongest in summer, followed by spring, autumn and winter; (2) the maximum SUHI intensity derived from LCZ classification reached 6.53 °C, which indicated that the SUHI effect was very significant in Wuhan; (3) LCZ 8 (i.e., large low-rise) had the maximum LST value and LCZ G (i.e., water) had the minimum LST value in all seasons; (4) the LST values of compact high-rise/midrise/low-rise (i.e., LCZ 1-3) were higher than those of open high-rise/midrise/low-rise (i.e., LCZ 4-6) in all seasons, which indicated that building density had a positive correlation with LST; (5) the LST values of dense trees (i.e., LCZ A) were less than those of scattered trees (i.e., LCZ B) in all seasons, which indicated that vegetation density had a negative correlation with LST. This paper provides some useful information for urban planning and contributes to the healthy and sustainable development of Wuhan.
BACKGROUND: Despite emerging recognition of the benefits of green and blue spaces on human health, evidence for their effect modifications on heat-mortality associations is limited. We aimed to investigate the effect modifications of green and blue spaces on heat-mortality associations among different age and sex groups and at different heat levels. METHODS: Daily mortality and meteorological data from 2008 to 2017 in Hong Kong, China were collected. The Normalized Difference Vegetation Index and distance to coast were used as proxies for green and blue space exposure, respectively. Time-series analyses was performed using fitting generalized linear mixed models with an interaction term between heat and levels of exposure to either green or blue space. Age-, sex-, and heat level-stratified analyses were also conducted. RESULTS: With a 1 °C increase in temperature above the 90th percentile (29.61 °C), mortality increased by 5.7% (95% confidence interval [CI]: 1.6, 10.1%), 5.4% (1.4, 9.5%), and 4.6% (0.8, 8.9%) for low, medium and high levels of green space exposure, respectively, and by 7.5% (3.9, 11.2%) and 3.5% (0.3, 6.8%) for low and high levels of blue space exposure, respectively. Significant effect modifications of green and blue spaces were not observed for the whole population or any specific age and sex group, either at a moderate heat level or a heat level (Ps > 0.05). CONCLUSIONS: No significant effect modifications of green and blue spaces on heat-related mortality risk were observed in Hong Kong. These findings challenge the existing evidence on the prominent protective role of green and blue spaces in mitigating heat-related mortality risks.
Anthropogenic modification of the natural environment has caused significant impacts on the local atmosphere and far-reaching changes to the global climate. Taking Hong Kong as a case study, high-resolution (250 m) mesoscale simulations are conducted using Meso-NH coupled with the multi-layer Town Energy Balance to investigate the effects of past (early 1960s), present (2018), and future (late 2040s) urban developments on the city’s surface energy balance, heat island, boundary layer structure, and heat stress during a prolonged heatwave event. Overall, horizontal and vertical urban expansion has caused the urban areas to become warmer, drier, less ventilated, and more susceptible to hot nights. The dense built-up urban core in the Kowloon peninsula is also found to deepen the urban boundary layer and enhance the coastal urban heat island circulation. Reclaimed land exhibits the largest differences in 2-m air temperature relative to a no urban scenario due to the drastic change in surface thermal properties. Areas downwind of the planned artificial islands in East Lantau are expected to experience warmer and calmer conditions due to the altered wind field. Study findings raise awareness regarding the increasingly long durations of strong heat stress in urban areas and the need for heat stress mitigation.
With the increases in hot weather frequency and intensity induced by observed and predicted climate change, heat exposure is an evolving challenge. We estimated a fixed effect econometric model to data on 5,404 individuals drawn from the China Health and Retirement Longitudinal Study database. These observations were used to examine the effect of heat stress on cognitive performance for those above 40 years of age who are often household decision-makers. We found today’s heat stress decreases performance on verbal and math test scores, and that cumulative heat exposure over the last 3 days adversely affects verbal test scores. We also found that middle-aged women and people in rural areas exhibit substantial heat stress-induced reductions on cognitive test scores. This finding implies that continuing climate change may well diminish decision-making capacity and effectiveness.
Long-lasting heatwaves have seriously threatened human health. Exploring the distribution of heat vulnerability is important for urban risk management. A model of heat vulnerability coupled with physical and social conditions based on exposure, sensitivity, and adaptation was established in Chongqing, a mountainous megacity in China, and 11 indicators were adopted to assess heat vulnerability. Heat perception evaluated by social media data is used to validate heat vulnerability. Four primary outcomes emerged. First, integration of high physical and low social heat vulnerabilities was found in central areas, while low physical and high social heat vulnerabilities were concentrated in suburban areas. Second, the spatial distribution of heat vulnerability is consistent with that of heat perception. Third, high social exposure, high physical and social sensitivity, and low physical adaptation led to high heat vulnerability in central areas, while high heat vulnerability in suburban areas was primarily caused by high physical exposure and low social adaptation. Finally, due to the barriers of mountains and rivers, both physical and social heat vulnerabilities form unique decentralized patterns following urbanization. According to the finding of heat vulnerability, mitigative and adaptive strategies (e.g. hierarchical layouts, green measures, and vulnerable health databases) are proposed to improve climate resilience.
This study investigates public participation in heat impact reduction by analysing adaptive behaviours, familiarity with urban heat island (UHI) and cooling strategies, the perceived urgency of heat impact actions and citizen’s willingness to pay through a questionnaire survey in Chongqing, China. The results indicate that airconditioning systems are the dominant cooling facility in both work and living environments. Respondents had a moderately familiar understanding of several cooling strategies such as urban vegetation, shading devices, water-based artificial facilities, urban design for shading and ventilation and water bodies. Familiarity with innovative materials and techniques for pavements, roofs and facades was less than moderate. Urban planning and design for heat resilient cities was thought to be the most urgent intervention, followed by the establishment of temporary cooling facilities. Most respondents indicated that cost-sharing mechanisms for urban heat prevention and control systems should at least include the government, whilst 50% of the respondents preferred collaborative payment among government, developers, and owners. Only 41.6% of the interviewees expressed their willingness to pay, with a share varying between 20 and 80 RMB. A conservative estimate indicated that there could be an average payment of 45.95 RMB and 19.10 RMB among the 234 respondents who were willing to pay and all 562 respondents regardless of willingness, respectively. Respondents’ heat-related responses and actions towards urban heat challenges were dependent on a wide range of factors like gender, age, education, economic status, health, exposure, habit formation and behavior change, social acceptance, etc. Moreover, such factors could interact with each other affecting public behavior with different weights. Overall, this study increases our understanding of people’s perceptions and proactiveness in reducing urban heat and provides guidance for decision-makers towards a novel user-aware approach to the implementation of urban heat prevention, adaptation, and mitigation strategies.
High temperatures pose great threats to the health of urban populations. The use of air conditioners (AC) is an important adaptive means to reduce the morbidity and mortality of heat-related diseases. However, it remains unclear how exposure and sensitivity factors affect residents’ AC use. This study aimed to answer this question through a case study in 78 residential areas in Beijing, China. We conducted over 7,000 structured interviews during June 20-August 5, 2017 to learn respondents’ AC use, health conditions and socioeconomic status. We also used remote sensing data to obtain land surface temperature (LST) and proportion of greenspace in residential areas. We applied a multilevel logistic regression to assess the influences of these factors on probability of frequent AC use. The results showed mixed impacts from sensitivity factors on AC use. While respondents with chronic diseases were 14.7% more likely to use AC every day, probability of AC use decreased by 29.2% with the increase of age groups. Instead of economic cost, the main reason preventing respondents from using AC was “feeling uncomfortable” or consider it as “unhealthy”. At the scale of residential area, results did not find significant impact of LST on AC use, while proportion of greenspace posed a negative impact on probability of using AC every day even when LST was considered.
More than half of the total population in China are living in cities. Especially, the people in highly developed and spatially integrated city clusters, i.e., urban agglomerations (UAs), are facing increasing human-perceived heat stress that describes the combined effects of hot temperature, high humidity, and lowered surface wind speed. By analyzing multiple indicators over 20 major UAs across China, we demonstrate that summer heat stress has been significantly intensifying in nearly all UAs during 1971–2014. This intensification is more profound in northern than southern regions and is especially stronger in more urbanized and densely populated areas (e.g., Beijing-Tianjin-Hebei and the Yangtze River Delta). Based on a dynamic classification of weather stations using time-varying land use/land cover maps, we find that urban core areas exhibit distinctly stronger increasing heat stress trends than their surrounding rural areas. On average, urbanization contributes to approximately one-quarter of the total increase in mean heat stress over urban core areas of UAs and nearly half of the total increase in extreme heat stress events. The urbanization effect is also dependent on the geographical region within China. Urbanization tends to have stronger intensifying effects on heat stress in UAs with higher population density in low-altitude areas, while it has a relatively weaker intensifying and even weakening effect in some arid and high-altitude regions. Moreover, as various heat stress metrics may yield different estimations of long-term trend and urbanization contribution, the particular choice of heat stress indicator is of critical importance for investigations on this subject matter.
Due to the progress in global warming, the frequency, duration and intensity of climate extremes are increasing. As one of these extremes, heat waves influence the well-being of human beings and increase societies’ energy consumption. The Water-Cooling Island (WCI) effect of urban water bodies (UWBs) is important in urban heat wave mitigation. In this paper, the impact of WCI, especially the landscape pattern of the surrounding area, was explored. The results indicate that water bodies with a larger total area and simpler shape have a longer cooling effect. In the areas surrounding UWBs, a lower percentage or discrete distribution of impervious surfaces or green land provide a longer cooling effect. The amplitude of WCI is mainly decided by the impervious surface in the surrounding areas. A lower percentage or discrete distribution of impervious surfaces or green land leads to a smaller-amplitude WCI. The gradient is impacted by the shape of the UWB and surrounding green land. A complex shape and discrete distribution of green land lead to a higher gradient of WCI. The linear regress model was significant in terms of WCI range and gradient, while the model of WCI amplitude was not significant. This indicates that WCI is directly decided by impact factors through gradient and range. The conclusions provide a methodology for WCI prediction and optimization, which is important when mitigating summer heat waves.
Urban heatwaves increase residential health risks. Identifying urban residential sensitivity to heatwave risks is an important prerequisite for mitigating the risks through urban planning practices. This research proposes a new paradigm for urban residential sensitivity to heatwave risks based on social media Big Data, and describes empirical research in five megacities in China, namely, Beijing, Nanjing, Wuhan, Xi’an and Guangzhou, which explores the application of this paradigm to real-world environments. Specifically, a method to identify urban residential sensitive to heatwave risks was developed by using natural language processing (NLP) technology. Then, based on remote sensing images and Weibo data, from the perspective of the relationship between people (group perception) and the ground (meteorological temperature), the relationship between high temperature and crowd sensitivity in geographic space was studied. Spatial patterns of the residential sensitivity to heatwaves over the study area were characterized at fine scales, using the information extracted from remote sensing information, spatial analysis, and time series analysis. The results showed that the observed residential sensitivity to urban heatwave events (HWEs), extracted from Weibo data (Chinese Twitter), best matched the temporal trends of HWEs in geographic space. At the same time, the spatial distribution of observed residential sensitivity to HWEs in the cities had similar characteristics, with low sensitivity in the urban center but higher sensitivity in the countryside. This research illustrates the benefits of applying multi-source Big Data and intelligent analysis technologies to the understand of impacts of heatwave events on residential life, and provide decision-making data for urban planning and management.
High-density cities are faced with growing extreme hot weather driven by climate change and local urbanization, but localized heat risk detection is still at an early stage for most cities (Watts et al., 2019). This study developed a spatiotemporal hazard-exposure-vulnerability assessment of the extreme heat risk in Hong Kong for 2006, 2011, and 2016 integrating cumulative very hot day hours and hot night hours in summer, population density and a principal component analysis (PCA) of demo-socioeconomic characteristics. The risk was found spatially variant, and high-risk spots were identified at the community scale for both daytime and nighttime with underlying determinants behind. In both the daytime and the nighttime, high risk mainly occurred in the core urban areas. Nearly 10 more hot-spots were found in the nighttime than those in the daytime. Several old communities in Kowloon stayed at high risk from 2006 to 2016. Some new towns in the New Territories turned to be at higher risk in 2016 compared to 2006 and 2011, and this result showed signs to be emerging hot-spots in the near future. This study would be a useful reference for community-scale heat risk assessment and mitigation for the development of healthy and sustainable high-density cities.
Large-scale modifications to urban underlying surfaces owing to rapid urbanization have led to stronger urban heat island (UHI) effects and more frequent urban heat wave (HW) events. Based on observations of automatic weather stations in Beijing during the summers of 2014–2020, we studied the interaction between HW events and the UHI effect. Results showed that the UHI intensity (UHII) was significantly aggravated (by 0.55°C) during HW periods compared to non-heat wave (NHW) periods. Considering the strong impact of unfavorable weather conditions and altered land use on the urban thermal environment, we evaluated the modulation of HW events and the UHI effect by wind speed and local climatic zones (LCZs). Wind speeds in urban areas were weakened due to the obstruction of dense high-rise buildings, which favored the occurrence of HW events. In detail, 35 HW events occurred over the LCZ1 of a dense high-rise building area under low wind speed conditions, which was much higher than that in other LCZ types and under high wind speed conditions (< 30 HW events). The latent heat flux in rural areas has increased more due to the presence of sufficient water availability and more vegetation, while the increase in heat flux in urban areas is mainly in the form of sensible heat flux, resulting in stronger UHI effect during HW periods. Compared to NHW periods, lower boundary layer and wind speed in the HW events weakened the convective mixing of air, further expanding the temperature gap between urban and rural areas. Note that LCZP type with its high-density vegetation and water bodies in the urban park area generally exhibited, was found to have a mitigating effect on the UHI, whilst at the same time increasing the frequency and duration of HW events during HW periods. Synergies between HWs and the UHI amplify both the spatial and temporal coverage of high-temperature events, which in turn exposes urban residents to additional heat stress and seriously threatens their health. The findings have important implications for HWs and UHII forecasts, as well as for scientific guidance on decision-making to improve the thermal environment and to adjust the energy structure.
Nighttime heat waves have greater impacts on human society than daytime because nighttime heat waves deprive humans to recover from daytime heat and increase energy consumption for cooling. In this study, we found increased occurrence and severity of nighttime heat waves across China during 1980-2017 based on measurements from more than 2,000 meteorological stations. The nighttime heat waves have been longer lasting and occurred more often in spring and fall. Compared to rural areas, urban areas have shown enhanced frequency, intensity, and duration of nighttime heat waves. Urbanization accounted for nearly 50% of the extended duration and nearly 40% of the enhanced intensity and frequency of nighttime heat waves in urban areas relative to rural areas. Urban expansion, causing reduced evapotranspiration and weakened wind speed that normally cools the lower atmosphere by turbulent heat loss and cooled air advection, led to nighttime urban heat island, thus magnifying nighttime heat extremes. Plain Language Summary Extreme temperature events will likely increase and cause severe damage to human society and natural ecosystem under climate change and urbanization. Compared to daytime, nighttime heat waves reduce people’s ability to cool off and prevent the human body recovering from daytime heat exposure, and therefore increase the risks of heat illnesses and deaths. Here, we show that nighttime heat waves have been more frequent, longer lasting, and severer, and occurred increasingly in spring and fall in China. These changes have been more intensive in urban areas than their surrounding rural areas. Urbanization accounted for nearly 50% of the extended duration, and nearly 40% of the enhanced intensity and frequency of nighttime heat waves in urban areas relative to rural areas. Nighttime urban heat island due to rapid urban expansion magnified nighttime heat extremes.
Global climate change results in an increased risk of high urban temperatures, making it crucial to conduct a comprehensive assessment of the high-temperature risk of urban areas. Based on the data of 194 meteorological stations in China from 1986 to 2015 and statistical yearbooks and statistical bulletins from 2015, we used GIS technology and mathematical statistics to evaluate high-temperature spatial and temporal characteristics, high-temperature risk, and high-temperature vulnerability of 31 cities across China. Over the past 30 years, most Chinese cities experienced 5-8 significant oscillation cycles of high-temperature days. A 15-year interval analysis of high-temperature characteristics found that 87% of the cities had an average of 5.44 more high-temperature days in the 15-year period from 2001 to 2015 compared to the period from 1986 to 2000. We developed five high-temperature risk levels and six vulnerability levels. Against the background of a warming climate, we discuss risk mitigation strategies and the importance of early warning systems.
In the context of climate change, the outdoor thermal environment is essential for urban health, particularly in hot and humid climate zones. In most cities in southern China, traditional shophouse neighbourhoods are regarded as a reference for climate-responsive urban morphology because multiple shading strategies are integrated, including deep canyons, semi-open arcades, and vegetation. In total, four shading strategies, namely, the height-to-width ratio of canyons and arcades, tree coverage area, and orientation, are employed in this study to compare their cooling efficiency in street canyons during summer daytime. The ENVI-met is employed for the microclimatic simulations and validated by site measurement data. The impact of varying sky view factor on the physiologically equivalent temperature was quantified to assess the cooling efficiency of each shading strategy. Our results demonstrate that the cooling efficiency of orientations varies significantly with sky view factor and is negatively associated with pedestrian thermal comfort in alleys, but positive in street canyons with arcades and trees. Varying the height-to-width ratio of canyons in arcade streets presents the best cooling efficiency, except in the east-west orientation. Shading by arcades shows a slightly higher cooling efficiency than tree coverage.
Extreme high-temperature events pose a threat to human beings on Earth. In coastal cities, the sea breeze is widely known as a prevailing wind that can cool the near-surface air. However, the cumulative cooling effect and its attenuation process during the sea breeze penetration have not been well investigated. In this study, we analyze sea breeze cooling capacity (SBCC) and propose a new method in estimating the penetration distance of sea breeze cooling in metropolitan Adelaide during summer using data from the Adelaide urban heat island monitoring network. The results show that during a sea breeze day, wind direction rapidly changes from southeast to southwest in the morning, and it gradually returns to southeast in the afternoon. It takes 67 min on average for the sea breeze cooling fronts to penetrate inside metropolitan Adelaide. The SBCC value is 21.3 degrees C h per event averaged spatially in Adelaide summer. During the penetration process, the SBCC values decrease at a rate of 0.7 and 0.9 degrees C h per kilometer from coast to inland on an average sea breeze day and a hot sea breeze day, respectively. Correspondingly, the mean cooling penetration distances are 42 and 29 km along the prevailing wind path. A multiple linear regression analysis indicates that the distance from the coast and elevation at the onshore point together explain 88% of the spatial variability of the temporally average SBCC in the study area. The spatial pattern and penetration distance of the cumulative sea breeze cooling effect contribute to a better understanding of this common cooling source for heat mitigation in coastal cities where a large number of people reside.
The warming trend over recent decades has already contributed to the increased prevalence of heat-vulnerable chronic diseases in many regions of the world. However, understanding the relationship between heat-vulnerable chronic diseases and heatwaves remains incomplete due to the complexity of such a relationship mingling with human society, urban and natural environments. Our study extends the Social Ecological Theory by constructing a tri-environmental conceptual framework (i.e., across social, built, and natural environments) and contributes to the first nationwide study of the relationship between heat-vulnerable chronic diseases and heatwaves in Australia. We utilize the random forest regression model to explore the importance of heatwaves and 48 tri-environmental variables that contribute to the prevalence of six types of heat-vulnerable diseases. We further apply the local interpretable model-agnostic explanations and the accumulated local effects analysis to interpret how the heat-disease nexus is mediated through tri-environments and varied across urban and rural space. The overall effect of heatwaves on diseases varies across disease types and geographical contexts (latitudes; inland versus coast). The local heat-disease nexus follows a J-shape function-becoming sharply positive after a certain threshold of heatwaves-reflecting that people with the onset of different diseases have various sensitivity and tolerance to heatwaves. However, such effects are relatively marginal compared to tri-environmental variables. We propose a number of policy implications on reducing urban-rural disparity in Healthcare and service distribution, delineating areas, and identifying the variations of sensitivity to heatwaves across urban/rural space and disease types. Our conceptual framework can be further applied to examine the relationship between other environmental problems and health outcomes.
Heatwaves are associated with increased mortality and are exacerbated by the urban heat island (UHI) effect. Thus, to inform climate change mitigation and adaptation, we quantified the mortality burden of historical heatwave days in Sydney, Australia, assessed the contribution of the UHI effect and used climate change projection data to estimate future health impacts. We also assessed the potential for tree cover to mitigate against the UHI effect. Mortality (2006-2018) records were linked with census population data, weather observations (1997-2016) and climate change projections to 2100. Heatwave-attributable excess deaths were calculated based on risk estimates from a published heatwave study of Sydney. High resolution satellite observations of UHI air temperature excesses and green cover were used to determine associated effects on heat-related mortality. These data show that >90% of heatwave days would not breach heatwave thresholds in Sydney if there were no UHI effect and that numbers of heatwave days could increase fourfold under the most extreme climate change scenario. We found that tree canopy reduces urban heat, and that widespread tree planting could offset the increases in heat-attributable deaths as climate warming progresses.
Heatwaves are an accustomed extreme event of the Australian climate, which can cause catastrophic impacts on human health, agriculture, and urban and natural systems. We have analyzed the trends in Australia-wide heatwave metrics (frequency, duration, intensity, number, cumulative magnitude, timing, and season duration) across 69 extended summer seasons (i.e., from November-1951 to March-2020). Our findings not only emphasize that heatwaves are becoming hotter, longer, and more frequent, but also signify that they are occurring with excess heat, commencing much earlier, and expanding their season over many parts of Australia in recent decades. The Australian heatwave trends have strengthened since last observed Australian study was conducted. We also investigated the heatwave and severe heatwave trends at a local city-scale using three different observational products (AWAP and SILO gridded datasets and ACORN_SATV2 station data) over selected time periods (1911-2019, 1911-1964, and 1965-2019). Results suggest that heatwave trends are noticeably different amongst the three datasets. However, the results highlight that the severe heatwave cumulative magnitude and their season duration have been increasing significantly in recent decades over Australia’s southern coastal cities (like Melbourne and Adelaide). The climatological mean of the most heatwave and severe heatwave metrics is substantially higher in recent decades compared to earlier periods across all the cities considered. The findings of our study have significant implications for the development of advanced heatwave planning and adaptation strategies.
Most studies evaluating future changes in climate extremes over Australia have examined events that occur once or more each year. However, it is extremes that occur less frequently than this that generally have the largest impacts on sectors such as infrastructure, health and finance. Here we use an ensemble of high resolution (similar to 10 km) climate projections from the NSW and ACT Regional Climate Modelling (NARCliM) project to provide insight into how such rare events may change over southeast Australia in the future. We examine changes in the frequency of extremes of heat, rainfall, bushfire weather, meteorological drought and thunderstorm energy by the late 21st century, focusing on events that currently occur once every 20 years (those with a 5% Annual Exceedance Probability). Overall the ensemble suggests increases in the frequency of all five extremes. Heat extremes exhibit the largest change in frequency and the greatest ensemble agreement, with current 1-in-20 year events projected to occur every year in central Australia and at least every 5 years across most of southeast Australia, by the late 21st century. The five capital cities included in our model domain are projected to experience multiple climate extremes more than twice as frequently in the late 21st century, with some cities projected to experience 1-in-20 year events more than six times as frequently. Although individual simulations show decreases in some extremes in some locations, there is no strong ensemble agreement for a decrease in any of the climate extremes over any part of southeast Australia. These results can support adaptation planning and should motivate further research into how extremely rare events will change over Australia in the future.
Information on the spatiotemporal characteristics of Beijing’s urban-rural near-surface air temperature difference, known as the canopy layer urban heat island (UHI), is important for future urban climate management strategies. This paper investigates the variation of near-surface air temperatures within Beijing at a neighbourhood-scale resolution (similar to 100 m) during winter 2016 and summer 2017. We perform simulations using the urban climate component of the ADMS-Urban model with land surface parameters derived from both local climate zone classifications and OpenStreetMap land use information. Through sensitivity simulations, the relative impacts of surface properties and anthropogenic heat emissions on the temporal variation of Beijing’s UHI are quantified. Measured UHI intensities between central Beijing (Institute of Atmospheric Physics) and a rural site (Pinggu) during the Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-China) campaigns, peak during the evening at similar to 4.5 degrees C in both seasons. In winter, the nocturnal UHI is dominated by anthropogenic heat emissions but is underestimated by the model. Higher-resolution anthropogenic heat emissions may capture the effects of local sources (e.g. residential buildings and adjacent major roads). In summer, evening UHI intensities are underestimated, especially during heatwaves. The inability to fully replicate the prolonged release of heat stored in the urban fabric may explain this. Observed negative daytime UHI intensities in summer are more successfully captured when surface moisture levels in central Beijing are increased. However, the spatial correlation between simulated air temperatures and satellite-derived land surface temperatures is stronger with a lower urban moisture scenario. This result suggests that near-surface air temperatures at the urban meteorological site are likely influenced by fine-scale green spaces that are unresolved by the available land cover data and demonstrates the expected differences between surface and air temperatures related to canopy layer advection. This study lays the foundations for future studies of heat-related health risks and UHI mitigation strategies across Beijing and other megacities.
The urbanization process leads to the enhancement of the urban heat island (UHI) effect, and the high temperature brought by it exacerbates the risk of heat exposure and seriously endangers human health. Analyzing the spatiotemporal characteristics and levels of heat exposure risk is important for formulating heat risk prevention and control measures. Therefore, this study analyzes the spatiotemporal characteristics of heat exposure risk based on the UHI footprint (FP) and explores the relationship between it and urbanization factors in the Beijing-Tianjin-Hebei (BTH) region from 2000 to 2020, and obtains the following conclusions: (1) The BTH region suffers from severe UHI problems, with FP ranging from 6.05 km (Chengde) to 32.51 km (Beijing), and the majority of cities show significant trends of FP increase. (2) With the increase in FP, massive populations are exposed within the heat risk areas, with the average annual population at risk across cities ranging from 269,826 (Chengde) to 166,020,390 (Beijing), with a predominance of people exposed to high risk (more than 65% of the total) and generally showing increasing trends. (3) The population at risk of heat exposure is significantly correlated with urbanization factors, indicating that urbanization is an important reason for the increase in the risk population and the enhancement of the risk level. These results suggest that with the continuous urbanization process, the heat exposure risk problem faced by cities in the BTH region will persist and gradually worsen, which must be paid attention to and effective mitigation measures must be taken.
Both extreme heat and heavy air pollution can cause adverse health impacts on urban inhabitants. To understand heat stress and its relationship with boundary layer structure and air pollution in Beijing, this study analyzed surface meteorological observations, radiosonde measurements, and ground-level PM2.5 and O3 concentrations in summer from 2015 to 2019, in conjunction with simulated air quality and MERRA-2 data. We measured the heat stress using a heat index that combines temperature and humidity to quantify the sensible temperature as perceived by humans, and found that high heat risk in Beijing was often associated with a low boundary layer height and poor air quality. To reveal the underlying physical mechanism involved, we objectively classified the synoptic conditions in North China. The typical synoptic pattern associated with the coupling of heat and pollution in Beijing was found to feature a southeast-to-north pressure gradient at the 700-hPa level, leading to westward warm advection above planetary boundary layer (PBL) and southward movement of warm, humid, and polluted air masses within the PBL towards Beijing. The elevated warm advection can enhance the capping of thermal inversion over the PBL and suppress the PBL’s development and the vertical dispersion of pollutants. With mountains to the north and west, pollutants and heat can be trapped in a limited volume in Beijing, increasing the health risk from heat and pollution. These findings on the meteorological mechanisms of the coupling between heat and pollution in Beijing may have important implications for limiting the current health risk and preparing for any projected changes in it in the future.
The growing elderly population living in high density cities undergoing mass urbanization raises concerns over age-friendliness of neighborhood open space, an essential component for healthy aging-in-place as elderly tend to spend most of their time at home and immediate home environment. This study discusses factors that influence age-friendly open space design pertaining to outdoor thermal environment and physical design element for highdensity high-rise housing in hot weather, using the case of public housing developments in Hong Kong. Field measurements, observations and linear regression data analyses are used to understand dynamic thermal condition, adaptive elderly user behavior and response to planned open space. It is demonstrated that four influential factors are important to correlate with elderly residents’ use of open space: 1) mean radiant temperature (MRT); 2) air temperature; 3) greenery; and 4) outdoor seating. Moreover, it is found that MRT, specifically longwave MRT, is the most influential and impacts the effectiveness of greenery and outdoor seating. In addition, the study proposes guide points to reflect the effect of each factor and shed more insight into improving age-friendly neighborhood open space design against climate-change induced heat-related health issues.
Extreme urban heat alongside higher ambient temperatures in urban areas causes serious energy, comfort, health and environmental problems. The implementation of urban heat mitigation techniques can significantly reduce urban temperatures and counterbalance the impact of extreme urban heat. This study assesses the potential cooling ability of modified urban albedo strategies through the implementation of reflective and super reflective materials, as well as the global climatic impacts on a subtropical desert urban environment in Dubai, UAE. Three scenarios using low, average and high albedo modifications are designed and evaluated in parallel to a reference scenario. A physically-based mesoscale urban modeling system is used to assess the thermal and meteorological impacts of the albedo modifications during both the summer and winter seasons at a city scale. The reduction of ambient temperature during the peak of a summer day (14:00 LT) is shown to be 0.6 degrees C, 1.4 degrees C and 2.6 degrees C when urban albedo is increased by 0.20, 0.45 and 0.60 respectively. The winter cooling penalty ranges between 0.6 degrees C and 1.1 degrees C for the different albedo scenarios. The increase of the urban albedo also significantly reduces the planetary boundary layer (PBL) depth due to the loss of sensible heat and decreases the intensity of the convective mixing and advection flows from the desert to the city, improving the mitigation potential of the reflective materials; however this increases the risk of a higher pollutants concentration. A much higher mitigation potential is observed for the high-density parts of the city when compared to that of the low-density parts of the city. Irrespective of linear function in the drop of ambient temperature and changing fraction of global albedo, our results reported that the cooling potential of reflective materials is highly influenced by the climate, landscape, and urban characteristics of the cities.
Mapping the elderly population exposure to heat hazard in urban areas is important to inform adaptation strategies for increasingly-deadly urban heat under climate change. However, fine-scale mapping is lacking, because global climate change projections have not previously been integrated with urban heat island effects especially with urban three-dimensional characteristics for within-city heat risk analyses. This study compared the spatial patterns of deadly heat exposure for elderly populations in two East Asian megacities, Seoul and Tokyo, using current climate (2006-2015) and two future periods (2040s and 2090s). We integrated global warming projections (the Shared Socioeconomic Pathway 5 based on Representative Concentration Pathway 8.5) with local urban characteristics and demographics. We found that, for the historical period, the overall hotspots of elderly population exposure to urban heat was larger in Tokyo because of relatively higher maximum air temperatures and lack of green spaces, whereas in the future periods, Seoul will have larger hotspots because the elderly population density will have increased. About 20% of the area in Seoul and 0.3-1% of Tokyo will be hotpots in the 2040s, and the size of these hotspots increases to 25-26% and 2-3%, respectively, in the 2090s. The spatial patterns of hotspots identify different types of priority areas and suggest that alternative adaptation strategies for two cities are appropriate. The approach introduced here will be useful for identifying sustainable thermal environments in other cities with high density elderly population and severe heat hazard. (c) 2021 Elsevier B.V. All rights reserved.
Urban heat islands (UHI) exacerbates the heat-related risk associated with global warming, increasing morbidity and mortality of urban residents. While the impacts of the spatial pattern of urban greenspace (UG) and its change on urban heat have been widely examined, there is less understanding of the aggregate effect of the change of UG-considering the loss and gain of UG simultaneously -on urban temperature. This study aims to fill this gap by using Beijing, China as a case study. Using a newly developed index -dynamic index of UG (UGDI) that simultaneously measures the loss and gain of UG in a certain unit of analysis, we investigated how changes in UG affect the daytime and nighttime land surface temperature (LST). We found: (1) A substantial proportion (49.90%) of grids with increased UG cover had increased LST during the daytime, with a magnitude ranging from 0.02 to 1.82 ?, indicating that the increase in UG does not always result in reduction of LST. (2) UGDI had a significantly positive correlation with LST change, suggesting that increase in UG does not necessarily result in decrease of LST, which can be affected by the degree of dynamics of UG. (3) The evapotranspiration (ET) rate of vegetation for lost greenspace was higher than that of new greenspace, indicating that adding the same amount of UG might not able to provide the same amount of cooling effects provided by lost ones. Results can enhance our understanding on how (landscape) process affects ecological effect. Future research and practical manage-ment strategies shall move beyond net increase of UG and focus more on its change process. This finding provides new evidence for explaining the effect of the change of UG on LST, and offers new insights for planning and managing urban natural resource to enhance resilience of cities to climate warming.
Rapid urbanization has led to altered thermal circulations in major cities that are responsible for the increasing occurrence of urban heat islands (UHIs) and events such as tropical nights and heat waves. To effectively mitigate such events, low-impact development (LID) and green infrastructure strategies have been developed. In Korea, LID techniques focus mainly on road pavement materials; however, issues regarding the reliability of measurements due to differences in the measurement equipment and studied specimens persist. This study presents the design of a green infrastructure surface temperature measurement (GSTM) instrument and a reliable methodology developed to evaluate the performance of pavement materials under controlled climate conditions. The developed GSTM instrument and methodology were tested by monitoring the surface temperature of materials based on LID practices and dense-graded asphalt and evaluating their ability to mitigate UHI and tropical night phenomena. The experiments were conducted under controlled climate conditions, using summer climate conditions of Seoul’s typical meteorological year data. The UHI and tropical night phenomena mitigation performance of the pavement materials was evaluated by analyzing the correlation between the pavement materials’ albedo and surface temperature using porous block specimens of different colors and LID-based pavement materials. The greening block recorded the most significant reduction in surface temperature, showing a difference of 22.6 °C, 185 min to the dense-graded asphalt. The white and yellow porous blocks showed surface temperature differences of 10.2 °C and 8.2 °C respectively compared to the dense-graded asphalt. The results revealed that pavement materials with higher albedo, more evaporation, and lower heat capacity have superior performance in mitigating UHI and tropical night events.
Urban areas generally have higher near-surface air temperature and lower air humidity than rural areas. Little is known about how heat stress, the combined effect of high air temperature and high humidity on human physiology, will be affected by future urban land expansion. Here we use a mesoscale numerical weather prediction model to examine the effects of urban land expansion from 2000 to 2050 on heat stress (measured as wet-bulb globe temperature, WBGT) in the urban areas of China, India, and Nigeria, which are projected to account for one-third of global urban population growth through 2050. Our results show that urban expansion slightly reduces heat stress during the day (similar to 0.2 degrees C) but substantially intensifies it at night, by similar to 1 degrees C on average and by up to 2-3 degrees C in five mega-urban regions (MURs). These effects exist with or without climate change induced by rising concentrations of greenhouse gases (GHGs). Installing cool roofs-an urban heat island mitigation measures-can reduce the daytime WBGT by 0.5-1 degrees C, partially offsetting the heat stress conditions caused by GHG-induced climate change. However, even with cool roofs, the nighttime WBGTs are higher by 0.3-0.9 degrees C over the whole countries studied, and by 1-2 degrees C in the MURs under the urban expansion scenario, compared to the situation in which urban areas remain unchanged. These results show that future urban expansion and heat island mitigation can result in potential daytime benefits but also persistent nighttime risks.
Average global temperatures and frequencies of heat waves are increasing with detrimental effects on health and wellbeing. This study presents a case study from two cities in the Northern Territory with the aim of exploring if and how people make deliberate adaptations to cope with increasing heat. Results show that 37% of all respondents made adjustments, with the most common being increased use of air-conditioning (65% of those responding to heat), followed by staying inside more often (22%) and passive cooling through modifications of house and garden (17%). Young people increasingly refrain from outside activities as temperatures increase. We also found that adaptive capacity was a function of education, long-term residency, home ownership and people’s self-rated wellbeing. Homeowners were more likely to adjust their living environment to the heat and renters less so. Being a property owner was commonly associated with the installation of solar panels to pay for high energy bills needed to run air-conditioning. Those who had solar panels at home were about ten times more likely to use air-conditioning more frequently in response to increasing heat. Our results confirm a growing dependence on artificially controlled environments to cope with heat in cities.
BACKGROUND: Previous studies have reported that high ambient temperature is associated with increased risk of suicide; however, the association has not been extensively investigated with drug overdose which is the most common method of unsuccessful suicidal behavior in Japan. Therefore, this study aims to examine the short-term association between daily mean temperature and the incidence of self-harm attempts by drug overdose in Tokyo, Japan. METHODS: We collected the emergency ambulance dispatch data and daily meteorological data in Tokyo from 2010 to 2014. A quasi-Poisson regression model incorporating a distributed lag non-linear function was applied to estimate the non-linear and delayed association between temperature and drug overdose, adjusting for relative humidity, seasonal and long-term trends, and days of the week. Sex, age and location-specific associations of ambient temperature with drug overdose was also estimated. RESULTS: 12,937 drug overdose cases were recorded during the study period, 73.9% of which were female. We observed a non-linear association between temperature and drug overdose, with the highest risk observed at 21 °C. The highest relative risk (RR) was 1.30 (95% Confidence Interval (CI): 1.10-1.67) compared with the risk at the first percentile of daily mean temperature (2.9 °C) over 0-4 days lag period. In subgroup analyses, the RR of a drug overdose at 21 °C was 1.36 (95% CI: 1.02-1.81) for females and 1.07 (95% CI: 0.66-1.75) for males. Also, we observed that the risk was highest among those aged ≥65 years (RR = 2.54; 95% CI: 0.94-6.90), followed by those aged 15-34 years (RR = 1.25; 95% CI: 0.89-1.77) and those aged 35-64 years (RR = 1.15; 95% CI: 0.78-1.68). There was no evidence for the difference in RRs between urban (23 special wards) and sub-urban areas in Tokyo. CONCLUSIONS: An increase in daily mean temperature was associated with increased drug overdose risk. This study indicated the positive non-linear association between temperature and incomplete attempts by drug overdose. The findings of this study may add further evidence of the association of temperature on suicidal behavior and suggests increasing more research and investigation of other modifying factors.
Vietnam is highly vulnerable to climate change-related extreme weather events such as heatwaves. This study assesses the association between heatwaves and hospitalizations due to mental and behavioral disorders (MBDs) in Ho Chi Minh City (HCMC). We collected daily MBD hospital admissions data at the HCMC Mental Health Hospital from 2017 to 2019. Heatwaves effects were characterized into the main effect (i.e., the intensity of temperature during heatwaves) and the added effect (i.e., the duration of heatwaves). Time series Poisson regression coupled with a distributed lag linear model (DLM) was used to quantify the 14-day lags effect of heatwaves. Confounders including long-term trend, seasonality, days of the week, holidays, and relative humidity were included in the model. Heatwaves increased all-cause MBD hospitalization by 62% (95%Cl, 36-93%) for the main effect and by 8% (95% Cl, - 3% to 19%) for the added effect. Noticeably, the group aged 18-60 years old was affected by the main effect of the heatwave, while the group aged 61 years and older was affected by the added effect of the heatwave. The effects of heatwaves differed among groups of MBD hospitalizations. The mental and behavioral disorder group due to psychoactive substance use was significantly affected by the main effect of heatwaves (RR:2.21; 95%Cl:1.55-3.15). The group of schizophrenia, schizotypal and delusional disorders were highly vulnerable towards both the main and the added effect of heatwaves with RR = 1.50 (95%CI, 1.20-1.86) and RR = 1.14 (95%CI, 1.01-1.30), respectively.
The combined effect of global warming and the heat island effect keeps the temperature of cities rising in the summer, seriously threatening the physical and mental health of urban residents. Taking the area within the Sixth Ring Road of Beijing as an example, based on Landsat remote sensing images, meteorological stations, and questionnaires, this study established a relational model between temperature and hostility and then analyzed the changes in the emotional health risk (hostility) in the study area and the mechanism of how outdoor activity duration influences hostility. Results show that: (1) the area within the Sixth Ring Road of Beijing had a higher and higher temperature from 1991 to 2020. Low-temperature areas gradually shrank, and medium- and high-temperature areas extended outwards from the center. (2) The threat of high temperature to residents’ hostility gradually intensified-the sphere of influence expanded, low-risk areas quickly turned into medium-high-risk areas, and the level of hostility risk increased. Level 1 risk areas of hostility had the most obvious reduction-a 74.33% reduction in area proportion; meanwhile, Level 3 risk areas had the most significant growth-a 50.41% increase in area proportion. (3) In the first 120 min of outdoor activities under high temperature, residents’ hostility was negatively correlated with outdoor activity duration; after more than 120 min, hostility became positively correlated with duration. Therefore, figuring out how temperature changes influence human emotions is of great significance to improving the living environment and health level of residents. This study attempts to (1) explore the impact of temperature changes and outdoor activity duration on hostility, (2) evaluate residents’ emotional health risk levels affected by high temperature, and (3) provide a theoretical basis for the early warning mechanism of emotional health risk and the planning of healthy cities.
The association between heat and diseases has been extensively reported. However, its associated healthcare costs and attributable fraction due to heat were scarcely explored. The aim of this study was to estimate hospitalisation costs attributable to heat in Sydney, and to project future costs under climate change scenarios. Using a distributed lag nonlinear model, this study estimated heat-attributable hospitalisation costs in Sydney; and using 2010-2016 data as baseline, future costs for 2030s and 2050s were estimated under three climate change scenarios depending on greenhouse gas emissions – Representative Concentration Pathway (RCP)2.6, RCP4.5, and RCP8.5. Higher temperatures were found to be associated with increased hospitalisation costs. About 8-9% of the total hospitalisation costs were attributable to heat. The total costs attributable to heat over the baseline period 2010-2016 were estimated to be AU$252 million, with mental health hospitalisation making the largest contribution. Hospitalisation costs are estimated to increase substantially to AU$387-399 million in the 2030s, and AU$506-570 million by midcentury under different climate change scenarios. Urgent action is required to reduce heatattributable illness in our communities, particularly for mental health conditions. Relevant preparations including healthcare workforce capacity building and resource allocation are needed to deal with these challenges in the context of climate change.
Urban heat island can exacerbate the harmful influence on human health and urban environment in historical and cultural block within Beijing Old City, China. To improve urban resilience and human well-being, protect historical and cultural heritage, nature-based solutions for urban heat mitigation are being the hotspot of research. However, only few studies focused on the comprehensive thermal environment of historical and cultural block from the social, ecological and technical aspects. Thus, we set-up scenarios combining with the three domains, to explore the cooling effect and thermal comfort improvement of Dashilar Block through ENVI-met. The results showed that 1) The areas with highest air temperature (Ta) and physiological equivalent temperature (PET) were mainly distributed in Peizhi Hutong and Zongshu Toutiao. 2) Five mitigation scenarios adapting to historical protection requirements and public preferences were vertical greening, traditional greening, quality improvement greening, high-albedo paving, and comprehensive. 3) The comprehensive and vertical greening scenarios could reduce the mean Ta of whole block by 1.01 degrees C or 0.38 degrees C, decrease the percentage of Ta hotter zone by 13.87% or 19.63%, and reduce the local Ta inside the block by 0.65 degrees C-1.80 degrees C or 0.33 degrees C-1.05 degrees C, respectively, which turned out the cooling effect and thermal comfort improvement of abovementioned two scenarios could significantly alleviate the heat stress. The comprehensive and vertical greening can act as the preferred nature-based solution for heat mitigation in Dashilar Block. We believed that this study would provide novel insights into the balance between urban heat mitigation and heritage protection during the renewal of Beijing Old City.
Older people are more vulnerable to climate change and with its increasing elderly population, inadequate research on the health impacts of climate change has focused on this particular population in China. This study evaluates climate change and health-related knowledge, attitudes and practices (KAP) of elderly residents in three cities Suzhou, Hefei and Xiamen. This cross-sectional study included 3466 participants. Data analysis was undertaken using descriptive methods (Chi-square test). Results showed that the elderly were most concerned about heatwaves, flooding and drought and the main perceived health risks included heatstroke and respiratory diseases. Finally, over half of the participants from Suzhou city reported that they did not receive enough government assistance in extreme events (56%). Findings from this work provide important insights for new adaptation strategies targeting the elderly population. It is recommended that the government should focus on creating awareness of the necessary adaptations the elderly will need to take to alleviate the impact of climate change on their physical health.
Background: Short-term heat exposure might induce stroke morbidity and mortality, and there were several studies explored the possible vulnerable populations. At present, the research on the modification effect of intra-urban landscape characteristics on the association between heat and stroke morbidity is limited, especially in China. Methods: We collected data on 22,424 first-ever strokes between 2010 and 2016 in Shenzhen, from June to August of each year. We adopted the case-only study combined with logistic regression models to examine the modification effects of 5 urban landscape characteristics. We studied the characteristics of relevant vulnerable populations through stratification analyses. Results: High values (refer to the median values) of nighttime land surface temperature (LST) and the proportion of impervious surface may aggravate the harmful effects of heat on stroke morbidity, with the OR values (95% CI) of 1.205 (1.053, 1.357) and 1.115 (1.010, 1.220); while, high values of NDVI and the proportion of water bodies may alleviate the harmful effects of heat, with the OR values (95% CI) of 0.772 (0.699, 0.845) and 0.821 (0.741, 0.901). The OR value of daytime LST was 1.004 (0.861, 1.147). Statistically significant modification effects were located in the population without Shenzhen’s household registration; as for nighttime LST, statistically significant modification effects were located in females and the elderly. Conclusions: High values of nighttime LST and the proportion of impervious surface might aggravate the harmful effects of heat on stroke morbidity, while high green space and water cover might alleviate its effects. Immigrants were the related vulnerable populations. The government should take measures to cope with climate warming and pay attention to the health effects of heat on immigrants. (c) 2021 Published by Elsevier B.V.
Playgrounds in urban parks are important for children’s physical and mental health, but global warming has led to a worsening outdoor environment and children’s outdoor activities have been affected. Improving the outdoor thermal comfort (OTC) of playgrounds can encourage children to engage in more and safer outdoor activities. However, there are a limited number of studies focusing on preschoolers’ outdoor thermal comfort (OTC) and most of them have substituted children’s thermal comfort with caregivers’ evaluations. To investigate the differences between children’s and caregivers’ evaluations of thermal sensation, thermal benchmarks and thermal adaptive behavior for children, we conducted meteorological measurements on representative playgrounds in three parks in Wuhan, China, and administered thermal perception questionnaires to preschool children and their caregivers. In addition, the Physiological Equivalent Temperature (PET) was used to establish evaluation criteria for children’s OTC and to make recommendations for the improvement of the playground environment. We draw five conclusions by analyzing 719 valid questionnaires: (1) Children were less sensitive to changes in meteorological factors than caregivers and had better tolerance of cold environments. (2) The NPET for preschoolers was evaluated by children and by caregivers, respectively, as 22.9 degrees C and 22.3 degrees C in summer and 10.6 degrees C and 11.2 degrees C in winter. (3) Playgrounds in Wuhan’s parks are uncomfortable for a long time in summer and a short time in winter. (4) Both children and caregivers want to improve summer comfort by lowering the temperature and winter comfort by increasing solar radiation. At the same time, children and caregivers show different preferences in adaptive behavior choices. (5) Adding deciduous trees and water play facilities can improve the site thermal environment. Furthermore, the OTC of humans can be improved by adding more service facilities on playgrounds.
Due to limits to standard methods for surveying outdoor thermal comfort (OTC), it is difficult to compare thermal benchmarks and thermal index calibrations among studies and climatic regions. Using uniform standard meteorological measurements and questionnaire surveys, our study conducted an OTC study in urban parks in Beijing, Xi’an and Hami; representative of cities in China’s cold regions. The Universal Thermal Climate Index (UTCI) was used as the thermal comfort index, and differences in residents’ thermal perceptions and outdoor thermal benchmarks among these cities were compared. Results showed that: 1) air temperature (T(a)) and globe temperature (T(g)) were two primary factors affecting residents’ thermal sensations in the three cities during winter. Residents’ thermal sensation in Beijing and Hami was negatively correlated with wind speed (V(a)). Residents in Xi’an and Hami preferred a higher relative humidity (RH). Residents in Beijing and Hami preferred a lower V(a) to improve OTC related to local climatic characteristics. 2) Xi’an residents had the highest neutral UTCI (NUTCI) (17.3 °C), followed by Beijing (17.0 °C) and Hami (6.4 °C). Xi’an residents had slightly wider neutral UTCI range (NUTCIR) (7.9-26.7 °C) compared to Beijing (8.7-25.4 °C), while Hami residents had the narrowest NUTCIR (1.5-11.3 °C). The “no thermal stress” range in the three cities was 6.1-26.0 °C in Beijing, 6.7-25.5 °C in Xi’an, and -2.2-12.2 °C in Hami. 3) Calibrated thermal indices, based on the ASHRAE 7-point scale, were gained to judge the thermal qualities of an environment for all three cities.
Although numerous studies have investigated premature deaths attributable to temperature, effects of temperature on years of life lost (YLL) remain unclear. We estimated the relationship between temperatures and YLL, and quantified the YLL per death caused by temperature in China. We collected daily meteorological and mortality data, and calculated the daily YLL values for 364 locations (2013-2017 in Yunnan, Guangdong, Hunan, Zhejiang, and Jilin provinces, and 2006-2011 in other locations) in China. A time-series design with a distributed lag nonlinear model was first employed to estimate the location-specific associations between temperature and YLL rates (YLL/100,000 population), and a multivariate meta-analysis model was used to pool location-specific associations. Then, YLL per death caused by temperatures was calculated. The temperature and YLL rates consistently showed U-shaped associations. A mean of 1.02 (95% confidence interval: 0.67, 1.37) YLL per death was attributable to temperature. Cold temperature caused 0.98 YLL per death with most from moderate cold (0.84). The mean YLL per death was higher in those with cardiovascular diseases (1.14), males (1.15), younger age categories (1.31 in people aged 65-74 years), and in central China (1.34) than in those with respiratory diseases (0.47), females (0.87), older people (0.85 in people ≥75 years old), and northern China (0.64) or southern China (1.19). The mortality burden was modified by annual temperature and temperature variability, relative humidity, latitude, longitude, altitude, education attainment, and central heating use. Temperatures caused substantial YLL per death in China, which was modified by demographic and regional characteristics.
People in urban agglomerations (UAs) are increasingly exposed to elevated extreme temperature events under global warming and local human activities such as urbanization. While the urbanization effects on local temperature changes have been well studied, possibly different effects on human perceived temperature (HPT), which measures the compound influences of multiple indicators (e.g., temperature, humidity, and wind), remain much less understood. Here, we examine the long-term changes in mean and extreme HPT in 20 major UAs across the mainland of China since the 1970s, and evaluate the effect of urbanization based on a dynamic classification of urban and rural stations using time-varying land use/land cover maps. The results show that mean HPT and actual near-surface air temperature (T) in both summer and winter seasons display significant trends in most portions of China, while the frequency of extreme HPT and T events in summer (winter) exhibits increasing (decreasing) tendency. These trends are particularly stronger in more populated and urbanized UAs. It is estimated that urbanization averagely accounts for around 1/6 of the total increasing trend in mean HPT and T in the urban core areas of 20 UAs. In both seasons, the effects of urbanization on mean HPT are more profound than T. Moreover, urbanization significantly increases the occurrence frequency of summertime hot extremes and decreases the occurrence of wintertime cold events. Regionally, northern UAs in general exhibit more remarkable trends than the south. The urbanization process exerts more prominent effects in HPT than T in nearly three-quarters of all UAs, except several regions with a complex topography and lower urbanization level. These findings reported here can provide suggestions and support for urban planning of decision-maker and human perceived thermal comfort choices of humans living in UAs.
Deleterious effect of cold on overall mortality is well-established. We studied associations between the air temperature and the number f ambulance calls for asthma in Nur-Sultan, Kazakhstan – the second coldest capital in the world. Daily counts of ambulance calls for asthma in Nur-Sultan for the cold seasons (October-March) 2006-2010 were obtained from the Municipal Ambulance Station. Associations between the number of calls and mean and minimum apparent temperatures (average for lags 0-15) were studied using first-order Poisson auto-regression models controlling for wind speed and effects of month, year, weekends and holidays. Altogether, there were 7373 ambulance calls for asthma during the study period. An inverse association between minimum apparent temperature and the number of calls was observed for the age-group 60 years and older. A decrease of the minimum apparent temperature by 1 °C was associated with an increase in the number of calls by 1.7% (95% CI: 0.1%-3.3%) across the whole temperature spectrum. No associations in other age groups were found. Our results suggest an inverse association between the average 15-day lag minimum apparent temperature and the number of ambulance calls during the cold season in Nur-Sultan, but this is limited to the oldest age-group.
As the global climate continues to warm, there is an increased focus on heat, but the role of low temperatures on health has been overlooked, especially for developing countries. Methods We collected the admission data of childhood asthma in 2013-2016 from Anhui Provincial Children’s Hospital, as well as meteorological data from the Meteorological Bureau for the study period and collected data of pollutants from 10 monitoring stations around Hefei city. Poisson’s generalized additive model (GAM) combined with a distributed lag non-linear model (DLNM) was used to estimate the short-term effects of cold spell on childhood asthma in cold seasons (November to March). 16 definitions of cold spells were clearly compared, which combining 4 temperature indexes (daily minimum and mean temperature; daily minimum and mean apparent temperature), 2 temperature thresholds (2.5th and 5th) and 3 durations of at least 2-4 days. We then have an analysis of the modifying effect of characteristics of cold spells and individuals(gender and age), with a view to discovering the susceptible population to cold spell. Results There was significant association between cold spells and admission risk for childhood asthma. And the definition, in which daily minimum apparent temperature falls below 5th percentile for at least 3 consecutive days, produced the optimum model fit performance. Based on this optimal fit we found that, for the total population, the effect of cold spell lasted approximately five days (lag1-lag5), with the largest effect occurring in lag 3 (RR = 1.110; 95% CI: 1.052-1.170). In subgroup analysis, the cumulative effect of lag0-7 was higher in males and school-age children than in females and other age groups, respectively. In addition, we found that the effect of is higher as the duration increases. Conclusion This study suggests an association between cold spell and childhood asthma, and minimum AT may be a better indicator to define the cold spells. Boys and school-age children are more vulnerable to cold spell. And one of our very interesting findings is that if a cold spell lasts for several days, the impact of the cold spell on those later days is likely to be greater than that of the previous days. In conclusion, we should pay more attention to the protection of boys and school-aged children in our future public health protection and give more attention to those cold spells that last longer. Therefore, we recommend that schools and health authorities need to take targeted measures to reduce the risk of asthma in children during the cold spell.
Ambient temperature is an important contributor to mortality burden worldwide, most of which is from cold exposure. However, little is known about the cold impact on life expectancy loss. This paper aimed to estimate cold-related life expectancy loss from cause-, age-, and gender-specific cardiovascular and respiratory diseases. Daily deaths from cardiovascular and respiratory diseases and weather records were acquired for Hong Kong, China during 2000-2016. Years of life lost (YLL) that considers life expectancy at the time of death was calculated by matching each death by age and sex to annual life tables. Using a generalized additive model that fits temperature-YLL association, we estimated loss of years in life expectancy from cold. Cold was estimated to cause life expectancy loss of 0.9 years in total cardiovascular disease, with more years of loss in males than in females and in people aged 65 years and older than in people aged up to 64 years. Cold-related life expectancy loss in total respiratory diseases was 1.2 years, with more years of loss in females than in males and comparable years of loss in people aged up to 64 years and in people aged 65 years and older. Among cause-specific diseases, we observed the greatest life expectancy loss in pneumonia (1.5 years), followed by ischaemic heart disease (1.2 years), COPD (1.1 years), and stroke (0.3 years). Between two periods of 2000-2007 and 2008-2016, cold-related life expectancy loss due to cardiovascular disease did not decrease and cold-related life expectancy loss due to respiratory disease even increased by five times. Our findings suggest an urgent need to develop prevention measures against adverse cold effects on cardiorespiratory disease in Hong Kong.
Loss and Damage studies have tended to focus on rapid-onset events with lesser attention to slow-onset events such as drought. Even when discussed, narratives around droughts emphasize implications on rural populations and there remain empirical and conceptual gaps on drought impacts in urban areas. We focus on losses and damages associated with urban drought and water insecurity through a review of interventions and policies in seven Asian countries. We find evidence of urban droughts leading to tangible losses (e.g. groundwater over-extraction, economic impacts) and intangible losses (e.g. conflict, increased drudgery). We highlight examples of Asian cities minimizing urban drought-related losses and damages through nature-based, institutional, technological, and behavioral adaptation interventions. We argue that water management policies that take into account current and projected L&D of urban droughts as well as beyond-urban dynamics of water availability and sharing are essential for effective climate adaptation.
BACKGROUND: There is a paucity of studies investigating extreme cold events and asthma exacerbations. This study examined whether an association exists between cold spells and daily hospital admissions for asthma in Beijing, China from 2012 to 2016. METHODS: Daily hospital admissions for asthma, meteorological variables and air quality data were collected during 2012-2016 in Beijing. A cold spell was defined as a period of at least two consecutive days with the daily mean temperature below or at the 5th percentile (-7 °C) in cold seasons (November to March) during the study period. We applied a time-series design using quasi-Poisson regression combined with a distributed lag model to estimate the risk of asthma hospital admissions associated with cold spells. Stratified analyses by gender and age groups were conducted to identify the potential susceptible subpopulations to cold spells. We also explored the effect modification by air quality by dividing the daily air quality index (AQI) into two levels (high and low) based on the median value. RESULTS: Cold spells increased the risk of asthma hospital admissions, with the maximum cumulative relative risk (CRR) over three weeks (Lag0-21) in the total population. The highest single-day relative risk (RR) was found on the days of cold spells (Lag0) with the RR = 1.059 (95% CI: 1.008-1.113), and the CRR at Lag0-21 was 1.333 (95% CI: 1.049-1.693). Across different gender and age groups, younger people (<65 years) were more sensitive to cold spells. No significant effect modification by AQI was detected. CONCLUSION: Short-term exposure to cold spells is associated with an increased risk of hospital admissions for asthma in Beijing. During the cold spells, younger people aged <65 years were at particular risk for asthma exacerbations. Our results suggest that extreme cold events have a significant impact on asthma.
BACKGROUND: Dengue is an endemic vector-borne disease influenced by environmental factors such as landscape and climate. Previous studies separately assessed the effects of landscape and climate factors on mosquito occurrence and dengue incidence. However, both factors concurrently coexist in time and space and can interact, affecting mosquito development and dengue disease transmission. For example, eggs laid in a suitable environment can hatch after being submerged in rain water. It has been difficult for conventional statistical modeling approaches to demonstrate these combined influences due to mathematical constraints. OBJECTIVES: To investigate the combined influences of landscape and climate factors on mosquito occurrence and dengue incidence. METHODS: Entomological, epidemiological, and landscape data from the rainy season (July-December) were obtained from respective government agencies in Metropolitan Manila, Philippines, from 2012 to 2014. Temperature, precipitation and vegetation data were obtained through remote sensing. A random forest algorithm was used to select the landscape and climate variables. Afterward, using the identified key variables, a model-based (MOB) recursive partitioning was implemented to test the combined influences of landscape and climate factors on ovitrap index (vector mosquito occurrence) and dengue incidence. RESULTS: The MOB recursive partitioning for ovitrap index indicated a high sensitivity of vector mosquito occurrence on environmental conditions generated by a combination of high residential density areas with low precipitation. Moreover, the MOB recursive partitioning indicated high sensitivity of dengue incidence to the effects of precipitation in areas with high proportions of residential density and commercial areas. CONCLUSIONS: Dengue dynamics are not solely influenced by individual effects of either climate or landscape, but rather by their synergistic or combined effects. The presented findings have the potential to target vector surveillance in areas identified as suitable for mosquito occurrence under specific climatic conditions and may be relevant as part of urban planning strategies to control dengue.
BACKGROUND: Despite concerns regarding increasingly frequent and intense heat waves due to global warming, there is still a lack of information on the effects of extremely high temperatures on the adult abundance of mosquito species that are known to transmit vector-borne diseases. This study aimed to evaluate the effects of extremely high temperatures on the abundance of mosquitoes by analyzing time series data for temperature and mosquito abundance in Incheon Metropolitan City (IMC), Republic of Korea, for the period from 2015 to 2020. METHODS: A generalized linear model with Poisson distribution and overdispersion was used to model the nonlinear association between temperature and mosquito count for the whole study area and for its constituent urban and rural regions. The association parameters were pooled using multivariate meta-regression. The temperature-mosquito abundance curve was estimated from the pooled estimates, and the ambient temperature at which mosquito populations reached maximum abundance (TMA) was estimated using a Monte Carlo simulation method. To quantify the effect of extremely high temperatures on mosquito abundance, we estimated the mosquito abundance ratio (AR) at the 99th temperature percentile (AR(99th)) against the TMA. RESULTS: Culex pipiens was the most common mosquito species (51.7%) in the urban region of the IMC, while mosquitoes of the genus Aedes (Ochlerotatus) were the most common in the rural region (47.8%). Mosquito abundance reached a maximum at 23.5 °C for Cx. pipiens and 26.4 °C for Aedes vexans. Exposure to extremely high temperatures reduced the abundance of Cx. pipiens mosquitoes {AR(99th) 0.34 [95% confidence interval (CI) 0.21-0.54]} to a greater extent than that of Anopheles spp. [AR(99th) 0.64 (95% CI 0.40-1.03)]. When stratified by region, Ae. vexans and Ochlerotatus koreicus mosquitoes showed higher TMA and a smaller reduction in abundance at extreme heat in urban Incheon than in Ganghwa, suggesting that urban mosquitoes can thrive at extremely high temperatures as they adapt to urban thermal environments. CONCLUSIONS: We confirmed that the temperature-related abundance of the adult mosquitoes was species and location specific. Tailoring measures for mosquito prevention and control according to mosquito species and anticipated extreme temperature conditions would help to improve the effectiveness of mosquito-borne disease control programs.
Already climate-related hazards are impacting sanitation systems in Indonesia and elsewhere, and climate models indicate these hazards are likely to increase in frequency and intensity. Without due attention, to maintain existing progress on Sustainable Development Goal 6’s target 6.2 and to increase it to meet ambitions for 2030 will be difficult. City governments need new forms of evidence to respond, as well as approaches to enable them to consider sufficient breadth of strategies to adapt effectively. This paper describes a co-production research process which engaged local governments in four cities in Indonesia experiencing different climate hazards. Local government engagement took place across three stages of (i) inception and design, (ii) participation as key informants and (iii) joint analysis and engagement on the findings. We adapted and simplified a risk prioritisation process based on current literature and employed a novel framework of a ‘climate resilient sanitation system’ to prompt articulation of current and proposed climate change adaptation response actions. In contrast to many current framings of climate resilience in sanitation that focus narrowly on technical responses, the results paint a rich picture of efforts needed by city governments across all domains, including planning, institutions, financing, infrastructure and management options, user awareness, water cycle management and monitoring and evaluation. Local government commitment and improved comprehension on the implications of climate change for sanitation service delivery were key outcomes arising from the co-production process. With strengthened policy and capacity building initiatives from national level, this foundation can be supported, and Indonesian city governments will be equipped to move forward with adaptation actions that protect on-going access to sanitation services, public health and the environment.
BACKGROUND: Many studies have reported the interactive effects between relative humidity and temperature on infectious diseases. However, evidence regarding the combined effects of relative humidity and temperature on bacillary dysentery (BD) is limited, especially for large-scale studies. To address this research need, humidex was utilized as a comprehensive index of relative humidity and temperature. We aimed to estimate the effect of humidex on BD across mainland China, evaluate its heterogeneity, and identify potential effect modifiers. METHODS: Daily meteorological and BD surveillance data from 2014 to 2016 were obtained for 316 prefecture-level cities in mainland China. Humidex was calculated on the basis of relative humidity and temperature. A multicity, two-stage time series analysis was then performed. In the first stage, a common distributed lag non-linear model (DLNM) was established to obtain city-specific estimates. In the second stage, a multivariate meta-analysis was conducted to pool these estimates, assess the significance of heterogeneity, and explore potential effect modifiers. RESULTS: The pooled cumulative estimates showed that humidex could promote the transmission of BD. The exposure-response relationship was nearly linear, with a maximum cumulative relative risk (RR) of 1.45 [95% confidence interval (CI): 1.29-1.63] at a humidex value of 40.94. High humidex had an acute adverse effect on BD. The humidex-BD relationship could be modified by latitude, urbanization rate, the natural growth rate of population, and the number of primary school students per thousand persons. CONCLUSIONS: High humidex could increase the risk of BD incidence. Thus, it is suitable to incorporate humidex as a predictor into the early warning system of BD and to inform the general public in advance to be cautious when humidex is high. This is especially true for regions with higher latitude, higher urbanization rates, lower natural growth rates of population, and lower numbers of primary school students per thousand persons.
BACKGROUND: Dengue fever (DF) is a mosquito-borne infectious disease that has threatened tropical and subtropical regions in recent decades. An early and targeted warning of a dengue epidemic is important for vector control. Current studies have primarily determined weather conditions to be the main factor for dengue forecasting, thereby neglecting that environmental suitability for mosquito breeding is also an important factor, especially in fine-grained intra-urban settings. Considering that street-view images are promising for depicting physical environments, this study proposes a framework for facilitating fine-grained intra-urban dengue forecasting by integrating the urban environments measured from street-view images. METHODS: The dengue epidemic that occurred in 167 townships of Guangzhou City, China, between 2015 and 2019 was taken as a study case. First, feature vectors of street-view images acquired inside each township were extracted by a pre-trained convolutional neural network, and then aggregated as an environmental feature vector of the township. Thus, townships with similar physical settings would exhibit similar environmental features. Second, the environmental feature vector is combined with commonly used features (e.g., temperature, rainfall, and past case count) as inputs to machine-learning models for weekly dengue forecasting. RESULTS: The performance of machine-learning forecasting models (i.e., MLP and SVM) integrated with and without environmental features were compared. This indicates that models integrating environmental features can identify high-risk urban units across the city more precisely than those using common features alone. In addition, the top 30% of high-risk townships predicted by our proposed methods can capture approximately 50-60% of dengue cases across the city. CONCLUSIONS: Incorporating local environments measured from street view images is effective in facilitating fine-grained intra-urban dengue forecasting, which is beneficial for conducting spatially precise dengue prevention and control.
In 2014 and 2015, Southern Taiwan experienced two unprecedented outbreaks, with more than 10,000 laboratory-confirmed dengue cases in each outbreak. The present study was aimed to investigate the influence of meteorological and spatial factors on dengue outbreaks in Southern Taiwan and was conducted in Kaohsiung City, which is the most affected area in Taiwan. The distributed lag nonlinear model was used to investigate the role of climatic factors in the 2014 and 2015 dengue outbreaks. Spatial statistics in the Geographic Information System was applied to study the relationship between the dengue spreading pattern and locations of traditional markets (human motility) in the 2015 dengue outbreak. Meteorological analysis results suggested that the relative risk of dengue fever increased when the weekly average temperature was more than 15°C at lagged weeks 5 to 18. Elevated relative risk of dengue was observed when the weekly average rainfall was more than 150 mm at lagged weeks 12 to 20. The spatial analysis revealed that approximately 83% of dengue cases were located in the 1000 m buffer zone of traditional market, with statistical significance. These findings support the influence of climatic factors and human motility on dengue outbreaks. Furthermore, the study analysis may help authorities to identify hotspots and decide the timing for implementation of dengue control programs.
Japanese encephalitis (JE) is an important mosquito-borne infectious disease in rural areas of Asia that is caused by Japanese encephalitis virus (JEV). Culex tritaeniorhynchus is the major vector of JEV, nevertheless there are other mosquitoes that may be able to transmit JEV. This study confirms that the midgut, head tissue, salivary glands, and reproductive tissue of Aedes albopictus, Armigeres subalbatus, and Culex quinquefasciatus are all able to be infected with JEV after a virus-containing blood meal was ingested by female mosquitoes. Even though the susceptibility to JEV of the different tissues varies, the virus-positive rate increased with the number of days after JEV infection. Moreover, once JEV escapes the midgut barrier, the oral transmission rates of JEV were 16%, 2%, and 21% for Ae. albopictus, Ar. subalbatus, and Cx. quinquefasciatus at 14 days after infection at 30 °C, respectively. There is no supporting evidence to suggest vertical transmission of JEV by the tested mosquitoes. Collectively, raising the temperature enhances JEV replication in the salivary gland of the three mosquito species, suggesting that global warming will enhance mosquito vector competence and that this is likely to lead to an increase in the probability of JEV transmission.
BACKGROUND: Previous studies have shown associations between local weather factors and dengue incidence in tropical and subtropical regions. However, spatial variability in those associations remains unclear and evidence is scarce regarding the effects of weather extremes. OBJECTIVES: We examined spatial variability in the effects of various weather conditions on the unprecedented dengue outbreak in Guangdong province of China in 2014 and explored how city characteristics modify weather-related risk. METHODS: A Bayesian spatial conditional autoregressive model was used to examine the overall and city-specific associations of dengue incidence with weather conditions including (1) average temperature, temperature variation, and average rainfall; and (2) weather extremes including numbers of days of extremely high temperature and high rainfall (both used 95th percentile as the cut-off). This model was run for cumulative dengue cases during five months from July to November (accounting for 99.8% of all dengue cases). A further analysis based on spatial variability was used to validate the modification effects by economic, demographic and environmental factors. RESULTS: We found a positive association of dengue incidence with average temperature in seven cities (relative risk (RR) range: 1.032 to 1.153), a positive association with average rainfall in seven cities (RR range: 1.237 to 1.974), and a negative association with temperature variation in four cities (RR range: 0.315 to 0.593). There was an overall positive association of dengue incidence with extremely high temperature (RR:1.054, 95% credible interval (CI): 1.016 to 1.094), without evidence of variation across cities, and an overall positive association of dengue with extremely high rainfall (RR:1.505, 95% CI: 1.096 to 2.080), with seven regions having stronger associations (RR range: 1.237 to 1.418). Greater effects of weather conditions appeared to occur in cities with higher economic level, lower green space coverage and lower elevation. CONCLUSIONS: Spatially varied effects of weather conditions on dengue outbreaks necessitate area-specific dengue prevention and control measures. Extremes of temperature and rainfall have strong and positive associations with dengue outbreaks.
Transmission of dengue virus is a complex process with interactions between virus, mosquitoes and humans, influenced by multiple factors simultaneously. Studies have examined the impact of climate or socio-ecological factors on dengue, or only analyzed the individual effects of each single factor on dengue transmission. However, little research has addressed the interactive effects by multiple factors on dengue incidence. This study uses the geographical detector method to investigate the interactive effect of climate and socio-ecological factors on dengue incidence from two perspectives: over a long-time series and during outbreak periods; and surmised on the possibility of dengue outbreaks in the future. Results suggest that the temperature plays a dominant role in the long-time series of dengue transmission, while socio-ecological factors have great explanatory power for dengue outbreaks. The interactive effect of any two factors is greater than the impact of single factor on dengue transmission, and the interactions of pairs of climate and socio-ecological factors have more significant impact on dengue. Increasing temperature and surge in travel could cause dengue outbreaks in the future. Based on these results, three recommendations are offered regarding the prevention of dengue outbreaks: mitigating the urban heat island effect, adjusting the time and frequency of vector control intervention, and providing targeted health education to travelers at the border points. This study hopes to provide meaningful clues and a scientific basis for policymakers regarding effective interventions against dengue transmission, even during outbreaks.
Japanese encephalitis (JE) is the major cause of viral encephalitis (VE) in most Asian-Pacific countries. In Vietnam, there is no nationwide surveillance system for JE due to lack of medical facilities and diagnoses. Culex tritaeniorhynchus, Culex vishnui, and Culex quinquefasciatus have been identified as the major JE vectors in Vietnam. The main objective of this study was to forecast a risk map of Culex mosquitoes in Hanoi, which is one of the most densely populated cities in Vietnam. A total of 10,775 female adult Culex mosquitoes were collected from 513 trapping locations. We collected temperature and precipitation information during the study period and its preceding month. In addition, the other predictor variables (e.g., normalized difference vegetation index [NDVI], land use/land cover and human population density), were collected for our analysis. The final model selected for estimating the Culex mosquito abundance included centered rainfall, quadratic term rainfall, rice cover ratio, forest cover ratio, and human population density variables. The estimated spatial distribution of Culex mosquito abundance ranged from 0 to more than 150 mosquitoes per 900m2. Our model estimated that 87% of the Hanoi area had an abundance of mosquitoes from 0 to 50, whereas approximately 1.2% of the area showed more than 100 mosquitoes, which was mostly in the rural/peri-urban districts. Our findings provide better insight into understanding the spatial distribution of Culex mosquitoes and its associated environmental risk factors. Such information can assist local clinicians and public health policymakers to identify potential areas of risk for JE virus. Risk maps can be an efficient way of raising public awareness about the virus and further preventive measures need to be considered in order to prevent outbreaks and onwards transmission of JE virus.
Dengue is a viral borne disease with complex transmission dynamics. Disease outbreak can exert an increasing pressure on the health system with high mortality. Understanding and predicting the outbreaks of dengue transmission is vital in controlling the spread. Mathematical models have become important tool in predicting the dynamics of dengue. Due to the complexity of the disease, general time series models do not describe the impact of the external parameters. In this work, we propose a generalised linear regression model to understand the dynamics of the dengue disease and predict the future outbreaks. To moderate the model, cross-correlation between reported dengue cases and climatic factors were identified using Pearson cross-correlation formula. Then threshold value was defined based on reported data in order to identify minimum risk level for the states of dengue outbreaks. Further, obtained results were compared.
Previous studies have explored the effect between ambient temperature and infectious diarrhea (ID) mostly using relative risk, which provides limited information in practical applications. Few studies have focused on the disease burden of ID caused by temperature, especially for different subgroups and cities in a multi-city setting. This study aims to estimate the effects and attributable risks of temperature on category C ID and explore potential modifiers among various cities in Guangdong. First, distributed lag non-linear models (DLNMs) were used to explore city-specific associations between daily mean temperature and category C ID from 2014 to 2016 in Guangdong and pooled by applying multivariate meta-analysis. Then, multivariate meta-regression was implemented to analyze the potential heterogeneity among various cities. Finally, we assessed the attributable burden of category C ID due to temperature, low (below the 5th percentile of temperature) and high temperature (above the 95th percentile of temperature) for each city and subgroup population. Compared with the 50th percentile of daily mean temperature, adverse effects on category C ID were found when the temperature was lower than 12.27 ℃ in Guangdong Province. Some city-specific factors (longitude, urbanization rate, population density, disposable income per capita, and the number of medical technicians and beds per thousand persons) could modify the relationship of temperature-category C ID. During the study period, there were 60,505 category C ID cases (17.14% of total cases) attributable to the exposure of temperature, with the attributable fraction (AF) of low temperature (4.23%, 95% empirical confidence interval (eCI): 1.79-5.71%) higher than high temperature (1.34%, 95% eCI: 0.86-1.64%). Males, people under 5 years, and workers appeared to be more vulnerable to temperature, with AFs of 29.40%, 19.25%, and 21.49%, respectively. The AF varied substantially at the city level, with the largest AF of low temperature occurring in Shaoguan (9.58%, 95% eCI: 8.36-10.09%), and that of high temperature occurring in Shenzhen (3.16%, 95% eCI: 2.70-3.51%). Low temperature was an important risk factor for category C ID in Guangdong Province, China. The exposure-response relationship could be modified by city-specific characteristics. Considering the whole population, the attributable risk of low temperature was much higher than that of high temperature, and males, people under 5 years, and workers were vulnerable populations.
BACKGROUND: The effects of extreme temperature on infectious diseases are complex and far-reaching. There are few studies to access the relationship of pulmonary tuberculosis (PTB) with extreme temperature. The study aimed to identify whether there was association between extreme temperature and the reported morbidity of PTB in Shandong Province, China, from 2005 to 2016. METHODS: A generalized additive model (GAM) was firstly conducted to evaluate the relationship between daily reported incidence rate of PTB and extreme temperature events in the prefecture-level cities. Then, the effect estimates were pooled using meta-analysis at the provincial level. The fixed-effect model or random-effect model was selected based on the result of heterogeneity test. RESULTS: Among the 446,016 PTB reported cases, the majority of reported cases occurred in spring. The higher reported incidence rate areas were located in Liaocheng, Taian, Linyi and Heze. Extreme low temperature had an impact on the reported incidence of PTB in only one prefecture-level city, i.e., Binzhou (RR = 0.903, 95% CI: 0.817-0.999). While, extreme high temperature was found to have a positive effect on reported morbidity of PTB in Binzhou (RR = 0.924, 95% CI: 0.856-0.997) and Weihai (RR = 0.910, 95% CI: 0.843-0.982). Meta-analysis showed that extreme high temperature was associated with a decreased risk of PTB (RR = 0.982, 95% CI: 0.966-0.998). However, extreme low temperature was no relationship with the reported incidence of PTB. CONCLUSION: Our findings are suggested that extreme high temperature has significantly decreased the risk of PTB at the provincial levels. The findings have implications for developing strategies to response to climate change.
BACKGROUND: The association between the incidence of hand, foot, and mouth disease (HFMD) and ambient temperature has been well documented. Although the severity of symptoms is an important indicator of disease burden and varies significantly across cases, it usually was ignored in previous studies, potentially leading to biased estimates of the health impact of temperature. METHODS: We estimated the disability-adjusted life year (DALY) by considering the severity of symptoms for each HFMD case reported during 2010-2012 in Guangdong and used distributed lag-nonlinear models to estimate the association between the daily average temperature and daily DALY of HFMD cases at the city-level. We investigated the potential effect modifiers on the pathway between temperature and DALY and pooled city-specific estimates to a provincial association using a meta-regression. The overall impact of temperature was further evaluated by estimates of DALYs that could be attributed to HFMD. RESULTS: The overall cumulative effect of daily mean temperature on the DALY of HFMD showed an inverse-U shape, with the maximum effect estimated to be β = 0.0331 (95%CI: 0.0199-0.0463) DALY at 23.8°C. Overall, a total of 6.432 (95%CI: 3.942-8.885) DALYs (attributable fraction = 2.721%, 95%CI: 1.660-3.759%) could be attributed to temperature exposure. All the demographic subgroups had a similar trend as the main analysis, while the magnitude of the peak of the temperature impact tended to be higher among the males, those aged ≥3yrs or from the Pear-River Delta region. Additionally, the impact of temperature on DALY elevated significantly with the increasing population density, per capita GDP, and per capita green space in parks. CONCLUSIONS: Temperature exposure was associated with increased burden of HFMD nonlinearly, with certain groups such as boys and those from areas with greater population density being more vulnerable.
BACKGROUND: Acute respiratory infections (ARIs) are among the most common human illnesses globally. Previous studies that examined the associations between climate variability and ARIs or ARI pathogens have reported inconsistent findings. Few studies have been conducted in Southeast Asia to date, and the impact of climatic factors are not well-understood. This study aimed to investigate the short-term associations between climate variability and ARIs in Singapore. METHODS: We obtained reports of ARIs from all government primary healthcare services from 2005 to 2019 and analysed their dependence on mean ambient temperature, minimum temperature and maximum temperature using the distributed lag non-linear framework. Separate negative binomial regression models were used to estimate the association between each temperature (mean, minimum, maximum temperature) and ARIs, adjusted for seasonality and long-term trend, rainfall, relative humidity, public holidays and autocorrelations. For temperature variables and relative humidity we reported cumulative relative risks (RRs) at 10th and 90th percentiles compared to the reference value (centered at their medians) with corresponding 95% confidence intervals (CIs). For rainfall we reported RRs at 50th and 90th percentiles compared to 0 mm with corresponding 95% CIs. RESULTS: Statistically significant inverse S-curve shaped associations were observed between all three temperature variables (mean, minimum, maximum) and ARIs. A decrease of 1.1 °C from the median value of 27.8 °C to 26.7 °C (10th percentile) in the mean temperature was associated with a 6% increase (RR: 1.06, 95% CI: 1.03 to 1.09) in ARIs. ARIs also increased at 23.9 °C (10th percentile) compared to 24.9 °C of minimum temperature (RR: 1.11, 95% CI: 1.07 to 1.16). The effect of maximum temperature for the same comparison (30.5 °C vs 31.7 °C) was non-significant (RR: 1.02, 95% CI: 0.99 to 1.05). An increase in ambient temperature to 28.9 °C (90th percentile) was associated with an 18% decrease (RR: 0.82, 95% CI: 0.80 to 0.83) in ARIs. Similarly, ARIs decreased with the same increase to 90th percentile in minimum (RR: 0.84, 95% CI: 0.80 to 0.87) and maximum (RR: 0.89, 95% CI: 0.86 to 0.93) temperatures. Rainfall was inversely associated with ARIs and displayed similar shape in all three temperature models. Relative humidity, on the other hand, exhibited a U-shaped relationship with ARIs. CONCLUSION: Our findings suggest that lower temperatures increase the risk of ARIs. Anticipated extreme weather events that reduce ambient temperature can be used to inform increased healthcare resource allocation for ARIs.
Background: Existing evidence suggests that mumps epidemics, a global public health issue, are associated with meteorological factors and air pollutants at the population scale. However, the interaction effect of meteorological factors and air pollutants on mumps remains underexplored.Methods: Daily cases of mumps, meteorological factors, and air pollutants were collected in Ningxia, China, from 2015 to 2019. First, a distributed lag nonlinear model (DLNM) was employed to assess the confounding-adjusted relationship between meteorological factors, ambient air pollutants, and mumps incidences. According to the results of DLNM, stratification in both air pollutants and meteorological factors was adopted to further explore the interaction effect of particulate matter less than or equal to 2.5 mu m in aerodynamic diameter (PM2.5) and ground-level ozone (O-3) with temperature and relative humidity (RH).Results: We reported significant individual associations between mumps incidences and environmental factors, including temperature, relative humidity, PM2.5, and O-3. Evident multiplicate and additive interactions between meteorological factors and PM2.5 were found with interaction relative risk (IRR) of 1.14 (95%CI: 1.01, 1.29) and relative excess risk due to interaction (RERI) of 0.17 (95%CI: 0.02, 0.32) for a moderate level of temperature at 12 degrees C, and IRR of 1.37 (95%CI: 1.14, 1.66), RERI of 0.36 (95%CI: 0.11, 0.60) for a high level of temperature at 20 degrees C, respectively. These results indicated that PM2.5 and temperature have a significant synergistic effect on the cases of mumps, while no interaction between relative humidity and PM2.5 is observed. Regarding O-3 and meteorological factors (temperature = 12 degrees C, 20 degrees C), IRR and RERI were 1.33 (95%CI: 1.17, 1.52) and 0.30 (95%CI: 0.16, 0.45), 1.91 (95%CI: 1.46, 2.49) and 0.69 (95%CI: 0.32, 1.07), respectively. And IRR of 1.17 (95%CI: 1.06, 1.29), RERI of 0.13 (95%CI: 0.04, 0.21) for a middle level of relative humidity at 48%.Conclusion: Our findings indicated that meteorological factors and air pollutants imposed a significantly lagged and nonlinear effect on the incidence of mumps. The interaction between low temperature and O-3 showed antagonistic effects, while temperature (medium and high) with PM2.5 and O-3 presented synergistic effects. For relative humidity, the interaction with O-3 is synergistic. These results provide scientific evidence to relevant health authorities for the precise disease control and prevention of mumps in arid and semi-arid areas.
BACKGROUND: Sentinel physician surveillance in communities has played an important role in detecting early signs of epidemics. The traditional approach is to let the primary care physician voluntarily and actively report diseases to the health department on a weekly basis. However, this is labor-intensive work, and the spatio-temporal resolution of the surveillance data is not precise at all. In this study, we built up a clinic-based enhanced sentinel surveillance system named “Sentinel plus” which was designed for sentinel clinics and community hospitals to monitor 23 kinds of syndromic groups in Taipei City, Taiwan. The definitions of those syndromic groups were based on ICD-10 diagnoses from physicians. METHODS: Daily ICD-10 counts of two syndromic groups including ILI and EV-like syndromes in Taipei City were extracted from Sentinel plus. A negative binomial regression model was used to couple with lag structure functions to examine the short-term association between ICD counts and meteorological variables. After fitting the negative binomial regression model, residuals were further rescaled to Pearson residuals. We then monitored these daily standardized Pearson residuals for any aberrations from July 2018 to October 2019. RESULTS: The results showed that daily average temperature was significantly negatively associated with numbers of ILI syndromes. The ozone and PM2.5 concentrations were significantly positively associated with ILI syndromes. In addition, daily minimum temperature, and the ozone and PM2.5 concentrations were significantly negatively associated with the EV-like syndromes. The aberrational signals detected from clinics for ILI and EV-like syndromes were earlier than the epidemic period based on outpatient surveillance defined by the Taiwan CDC. CONCLUSIONS: This system not only provides warning signals to the local health department for managing the risks but also reminds medical practitioners to be vigilant toward susceptible patients. The near real-time surveillance can help decision makers evaluate their policy on a timely basis.
The bacteria (including pathogenic bacteria) attached to road deposited sediments (RDS) may interrelate with the microbe in the atmosphere, soil and water through resuspension and wash-off, and is of great significance to human and ecological health. However, the characteristics of bacterial communities with different time scale on RDS were unknown to dates. Climate change prolonged the dry days between rain events in many areas, making the varied trend of bacterial communities might be more significant in short term. This study revealed the characteristics of bacterial communities on RDS in urban and suburban areas through seasonal and daily scale. The correlations between other factors (land use, particle size, and chemical components) and the bacterial communities were also analyzed. It was found that the season showed a higher association with the bacterial community diversity than land use and particle size in urban areas. The bacterial community diversity increased substantially throughout the short-term study period (41 days) and the variation of dominant bacteria could be fitted by quadratic function in suburbs. In addition, urbanization notably increased the bacterial community diversity, while the potential pathogenic bacteria were more abundant in the suburban areas, coarse RDS (>75 μm), and in spring. The chemical components on RDS showed special correlations with the relative abundance of dominant bacteria. The research findings would fill the knowledge gap on RDS bacterial communities and be helpful for the future research on the assembly process of bacterial communities.
Biomass burning and dust storm have significant impacts on air pollution, aerosol properties and potential human health. In order to investigate the influences of them on the chemical component and sources of aerosols, PM2.5 are collected in spring and summer in Beijing. There are two special periods in the whole campaign. (1) Event I, from 16 to 18 April. Air quality is extremely poor during this period mainly affected by biomass burning. (2) Event II, from 4 to 5 May, the biggest dust storm happened on 4 May. In addition, we choose a relative clean period as (3) Event III, from 24 to 29 July, with the lowest PM2.5 levels (16-31 mu g m(-3)) in the whole campaign. Contributions of NO3, SO42-, and NH4+ to PM2.5 in Event I are 22.1%, 11.3%, and 8.3%, respectively, and decreased dramatically to 2.4%, 5.4%, and 0.9% in Event II, suggesting secondary aerosols are more significant in haze period. Both ratios of phytane & pristane and PAHs to OC in Event I and II are comparable, indicating contribution of local primary organic aerosols from fossil fuel combustions to PM2.5 are not significant differences between polluted and dust period. In contrast, ratio of levoglucosan to OC is much higher in Event I and ratio of trehalose to OC is much higher in Event II, suggesting the contribution of regional primary organic aerosols from biomass burning to PM2.5 is important during polluted period, while contribution of regional primary organic aerosols from dust to PM2.5 is significant in dust storm. Based on the organic markers, this work also estimates the source apportionment of PM2.5. Dust and biomass burning are the main contributors in polluted period, while vehicle and cooking are the main contributors in clean period.
The early identification and prediction of hand-foot-and-mouth disease (HFMD) play an important role in the disease prevention and control. However, suitable models are different in regions due to the differences in geography, social economy factors. We collected data associated with daily reported HFMD cases and weather factors of Zibo city in 2010 similar to 2019 and used the generalised additive model (GAM) to evaluate the effects of weather factors on HFMD cases. Then, GAM, support vectors regression (SVR) and random forest regression (RFR) models are used to compare predictive results. The annual average incidence was 129.72/100 000 from 2010 to 2019. Its distribution showed a unimodal trend, with incidence increasing from March, peaking from May to September. Our study revealed the nonlinear relationship between temperature, rainfall and relative humidity and HFMD cases and based on the predictive result, the performances of three models constructed ranked in descending order are: SVR > GAM > RFR, and SVR has the smallest prediction errors. These findings provide quantitative evidence for the prediction of HFMD for special high-risk regions and can help public health agencies implement prevention and control measures in advance.
OBJECTIVES: Hand, foot, and mouth disease (HFMD) is a viral infectious disease that poses a substantial threat in the Asia-Pacific region. It is widely reported that meteorological factors are associated with HFMD. However, the relationships between air pollutants and HFMD are still controversial. In addition, the interactive effects between meteorological factors and air pollutants on HFMD remain unknown. To fill this research gap, we conducted a time-series study. DESIGN: A time-series study. SETTING AND PARTICIPANTS: Daily cases of HFMD as well as meteorological and air pollution data were collected in Chengdu from 2011 to 2017. A total of 184 610 HFMD cases under the age of 15 were included in our study. OUTCOME MEASURES: Distributed lag nonlinear models were used to investigate the relationships between HFMD and environmental factors, including mean temperature, relative humidity, SO(2), NO(2), and PM(10). Then, the relative excess risk due to interaction (RERI) and the proportion attributable to interaction were calculated to quantitatively evaluate the interactions between meteorological factors and air pollutants on HFMD. Bivariate response surface models were used to visually display the interactive effects. RESULTS: The cumulative exposure-response curves of SO(2) and NO(2) were inverted ‘V’-shaped and ‘M’-shaped, respectively, and the risk of HFMD gradually decreased with increasing PM(10) concentrations. We found that there were synergistic interactions between mean temperature and SO(2), relative humidity and SO(2), as well as relative humidity and PM(10) on HFMD, with individual RERIs of 0.334 (95% CI 0.119 to 0.548), 0.428 (95% CI 0.214 to 0.642) and 0.501 (95% CI 0.262 to 0.741), respectively, indicating that the effects of SO(2) and PM(10) on HFMD were stronger under high temperature (>17.3°C) or high humidity (>80.0%) conditions. CONCLUSIONS: There were interactive effects between meteorological factors and air pollutants on HFMD. Our findings could provide guidance for targeted and timely preventive and control measures for HFMD.
Despite a conspicuous exacerbation of asthma among patients hospitalized due to influenza infection, no study has attempted previously to elucidate the relationship between environmental factors, influenza activity, and asthma simultaneously in adults. In this study, we examined this relationship using population-based hospitalization records over 22 years. Daily numbers of hospitalizations due to asthma in adults of 41 public hospitals in Hong Kong during 1998-2019 were obtained. The data were matched with meteorological records and air pollutant concentrations. We used type-specific and all-type influenza-like illness plus (ILI+) rates as proxies for seasonal influenza activity. Quasi-Poisson generalized additive models together with distributed-lag non-linear models were used to examine the association. A total of 212,075 hospitalization episodes due to asthma were reported over 22 years. The cumulative adjusted relative risk (ARR) of asthma hospitalizations reached 1.15 (95 % confidence interval [CI], 1.12-1.18) when the ILI+ total rate increased from zero to 20.01 per 1000 consultations. Compared with the median temperature, a significantly increased risk of asthma hospitalization (cumulative ARR = 1.10, 95 % CI, 1.05-1.15) was observed at the 5(th) percentile of temperature (i.e., 14.6 °C). Of the air pollutants, oxidant gas was significantly associated with asthma, but only at its extreme level of concentrations. In conclusion, cold conditions and influenza activities are risk factors to asthma exacerbation in adult population. Influenza-related asthma exacerbation that appeared to be more common in the warm and hot season, is likely to be attributable to influenza A/H3N2. The heavy influence of both determinants on asthma activity implies that climate change may complicate the asthma burden.
Varicella is a rising public health issue. Several studies have tried to quantify the relationships between meteorological factors and varicella incidence but with inconsistent results. We aim to investigate the impact of temperature and relative humidity on varicella, and to further explore the effect modification of these relationships. In this study, the data of varicella and meteorological factors from 2011 to 2019 in 21 cities of Guangdong Province, China were collected. Distributed lag nonlinear models (DLNM) were constructed to explore the relationship between meteorological factors (temperature and relative humidity) and varicella in each city, controlling in school terms, holidays, seasonality, long-term trends, and day of week. Multivariate meta-analysis was applied to pool the city-specific estimations. And the meta-regression was used to explore the effect modification for the spatial heterogeneity of city-specific meteorological factors and social factors (such as disposable income per capita, vaccination coverage, and so on) on varicella. The results indicated that the relationship between temperature and varicella in 21 cities appeared nonlinear with an inverted S-shaped. The relative risk peaked at 20.8 ℃ (RR = 1.42, 95% CI: 1.22, 1.65). The relative humidity-varicella relationship was approximately L-shaped, with a peaking risk at 69.5% relative humidity (RR = 1.25, 95% CI: 1.04, 1.50). The spatial heterogeneity of temperature-varicella relationships may be caused by income or varicella vaccination coverage. And varicella vaccination coverage may contribute to the spatial heterogeneity of the relative humidity-varicella relationship. The findings can help us deepen the understanding of the meteorological factors-varicella association and provide evidence for developing prevention strategy for varicella epidemic.
WHAT IS ALREADY KNOWN ABOUT THIS TOPIC? Ozone (O(3)) is a weather-driven photochemical ambient pollutant, and its harm to human health may be affected by meteorological factors such as temperature. However, there is conflicting evidence regarding whether temperature can modify the effects of ozone on health. WHAT IS ADDED BY THIS REPORT? Short-term exposure to O(3) in the Beijing Municipality, Tianjin Municipality, Hebei Province, and surrounding areas was associated with an increased risk of human mortality and that association was positive modified by relatively higher (>75th 24 h-average temperature) or extreme cold temperature (<10th 24 h-average temperature). Under extreme temperatures (>90th 24 h-average temperature) modification, the associations were further increased. Cardiopulmonary diseases, as vulnerable diseases of air pollution, their mortality risks associated with O(3) were markedly strengthened by uncomfortable temperatures. WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE? This study suggests that policymakers should pay attention to the synergistic effect between ozone and heat or extreme cold on human health, as well as provide evidence for establishing an integrated early-warning system to protect the public against both uncomfortable temperature and air pollution.
Heatwaves (HWs) paired with higher ozone (O-3) concentration at the surface level pose a serious threat to human health. Their combined modulation of synoptic patterns and urbanization remains unclear. Using 5 years of summertime temperature and O-3 concentration observation in Beijing, this study explored potential drivers of compound HWs and O-3 pollution events and their public health effects. Three favorable synoptic weather patterns were identified to dominate the compound HWs and O-3 pollution events. These weather patterns contributing to enhance those conditions are characterized by sinking air motion, low boundary layer height, and high temperatures. Under the synergy of HWs and O-3 pollution, the mortality risk from all non-accidental causes increased by approximately 12.31 % (95 % confidence interval: 4.66 %, 20.81 %). Urbanization caused a higher risk of HWs and O-3 in urban areas than at rural stations. Particularly, due to O(3 )depletion caused by NO titration at traffic and urban stations, the health risks related to O(3 )pollution in different regions are characterized as follows: suburban stations > urban stations > rural stations > traffic stations. In general, favorable synoptic patterns and urbanization enhanced the health risk of these compound events in Beijing by 33.09 % and 18.95 %, respectively. Our findings provide robust evidence and implications for forecasting compound HWs and O-3 pollution events and their health risks in Beijing or in other urban areas all over the world that have high concentrations of O-3 and high-density populations.
The 2019-20 bushfires that raged in eastern Australia were an overwhelming natural disaster leading to lives lost or upended, and communities destroyed. For almost a month, Canberra, Australia’s capital city in the Australian Capital Territory (ACT), was obscured by smoke from fires which threatened the outer suburbs. While smoke itself is experientially different from many natural disasters, it nevertheless poses a significant public health threat. As the impact of extended bushfire smoke in an urban setting is relatively unexplored we aimed to capture the individual and community-level experiences of the event and their importance for community and social functioning. We responded rapidly by conducting semi-structured interviews with a range of Canberra residents who, due to their personal or social circumstances, were potentially vulnerable to the effects of the smoke. Three major themes emerging from the narratives depicted disruption to daily life, physical and psychological effects, and shifting social connectedness. This study highlighted the ambiguous yet impactful nature of a bushfire smoke event, and identified four simple key messages that may be critically relevant to policy making in preparation for similar smoke events in the future.
OBJECTIVE: To determine the association of meteorological factors and air pollutants (MFAPs) with fracture and to estimate the effect size/time lag. DESIGN: This is a nationwide population-based ecological study from 2008 to 2017. SETTING: Eight large metropolitan areas in Korea. PARTICIPANTS: Of 8 093 820 patients with fractures reported in the Korea National Health Insurance database, 2 129 955 were analysed after the data set containing patient data (age, sex and site of fractures) were merged with MFAPs. Data on meteorological factors were obtained from the National Climate Data Center of the Korea Meteorological Administration. Additionally, data on air pollutants (atmospheric particulate matter ≤2.5 µm in diameter (PM(2.5)), PM(10), ozone, nitrogen dioxide, sulfur dioxide and carbon monoxide) were obtained from the Air Korea database. PRIMARY AND SECONDARY OUTCOME MEASURES: We hypothesised that there would be an association between MFAPs and the incidence of fracture. A generalised additive model was used while factoring in the non-linear relationship between MFAPs and fractures as well as a time lag ≤7 days. Multivariate analysis was performed. Backward elimination with an Akaike information criterion was used to fit the multivariate model. RESULTS: Overall, in eight urban areas, 2 129 955 patients with fractures were finally analysed. These included 370 344, 187 370, 173 100, 140 358, 246 775, 6501, 228 346, 57 183 and 719 978 patients with hip, knee, shoulder, elbow, wrist, hand, ankle, foot and spine fractures, respectively. Various MFAPs (average temperature, daily rain, wind speed, daily snow and PM(2.5)) showed significant association with fractures, with positive correlations at time lags 7, 5-7, 5-7, 3-7 and 6-7 days, respectively. CONCLUSIONS: Various MFAPs could affect the occurrence of fractures. The average temperature, daily rain, wind speed, daily snow and PM(2.5) were most closely associated with fracture. Thus, improved public awareness on these MFAPs is required for clinical prevention and management of fractures.
To examine Beijing residents’ risk perception of contracting smog-related diseases, we proposed a model in which air-pollution knowledge is a theoretical mechanism accounting for the influence on risk perception of exposure to environmental news and exposure to Under the Dome, an environmental documentary about smog in China, which has been censored. Data (N = 523) were collected from Beijing residents from February to March in 2017. We analyzed the data using Hayes’ PROCESS macro. Findings revealed that environmental-news exposure is positively associated with both air-pollution knowledge and risk perception. Exposure to environmental news has an indirect effect on risk perception through air-pollution knowledge. Exposure to Under the Dome is positively related to risk perception but is not related to air-pollution knowledge. We contributed to the literature by empirically testing the impact of Under the Dome, which has been largely studied via the critical theory approach. Implications included that Under the Dome is a successful risk communication model and that its impact goes beyond increasing public risk perception of smog.
BACKGROUND: While temperature changes have been confirmed as one of the contributory factors affecting human health, the association between high-frequency temperature variability (HFTV, i.e., temperature variation at short time scales such as 1, 2, and 5 days) and the hospitalization of chronic obstructive pulmonary disease (COPD) was rarely reported. OBJECTIVES: To evaluate the associations between high-frequency temperature variabilities (i.e., at 1, 2, and 5-day scales) and daily COPD hospitalization. METHODS: We collected daily records of COPD hospitalization and meteorological variables from 2013 to 2017 in 21 cities of Guangdong Province, South China. A quasi-Poisson regression with a distributed lag nonlinear model was first employed to quantify the effects of two HFTV measures, i.e., the day-to-day (DTD) temperature change and the intraday-interday temperature variability (IITV), on COPD morbidity for each city. Second, we used multivariate meta-analysis to pool the city-specific estimates, and stratified analyses were performed by age and sex to identify vulnerable groups. Then, the meta-regression with city-level characteristics was employed to detect the potential sources of the differences among 21 cities. RESULTS: A monotonic increasing curve of the overall exposure-response association was observed, suggesting that positive HFTV (i.e., increased DTD and IITV) will significantly increase the risk of COPD admission. Negative DTD was associated with reduced COPD morbidity while positive DTD elevated the COPD risk. An interquartile range (IQR) increase in DTD was associated with a 24% (95% CI: 12-38%) increase in COPD admissions. An IQR increase in IITV(0-1) was associated with 18% (95% CI: 7-27%) increase in COPD admissions. Males and people aged 0-64 years appeared to be more vulnerable to the DTD effect than others. Potential sources of the disparity among different cities include urbanization level, sex structure, industry structure, gross domestic product (GDP), health care services, and air quality. CONCLUSIONS: The increases of DTD and IITV have significant adverse impacts on COPD hospitalization. As climate change intensifies, precautions need to be taken to mitigate the impacts of high-frequency temperature changes.
OBJECTIVE: Most evidence comes from studies show that ambient ozone(O(3)) pollution has become a big issue in China. Few studies have investigated the impact of ozone spatiotemporal patterns on respiratory mortality and cardiovascular mortality in Nanchang city. Thus, this study aimed to explore the health effect of ozone exposure on respiratory mortality and cardiovascular mortality in Nanchang, Jiangxi Province. METHODS: Using the daily mortality data, atmospheric routine monitoring data and meteorological data in Nanchang from 2014 to 2020, we performed a generalized additive model (GAM) based on the poisson distribution in which time-series analysis to calculate the risk correlation between respiratory mortality and cardiovascular mortality and ozone exposure level (8h average ozone concentration, O(3)-8h). Besides, analyses were also stratified by season, age and sex. RESULTS: In the single-pollutant model, for every 10 μg/m(3) increase in ozone, respiratory mortality increased 1.04% with 95% confidence interval (CI) between 0.04 and 1.68%, and cardiovascular mortality increased 1.26% (95%CI: 0.68 ~ 1.83%). In the multi-day moving average lag model, the mortality of respiratory diseases and cardiovascular diseases reached a relative risk peak on the cumulative lag5 (1.77%,95%CI: 0.99 ~ 2.57%) and the cumulative lag3 (1.68%,95%CI: 0.93 ~ 2.45%), respectively. The differences were statistically significant (P < 0.05). Results of the stratified analyses showed the effect value of respiratory mortality in people aged ≥65 years was higher than aged <65 years, whereas the greatest effect of cardiovascular mortality in people aged <65 years than aged ≥65 years. Ozone had a more profound impact on females than males in respiratory diseases and cardiovascular diseases. In winter and spring, ozone had a obvious impact on respiratory mortality, and effects of ozone pollution on cardiovascular mortality were stronger in summer and winter. There was a statistically significant difference of respiratory mortality in winter and spring and of cardiovascular mortality in summer and winter (P < 0.05). CONCLUSIONS: In the long run, the more extreme the pollution of ozone exposure, the higher the health risk of residents' respiratory mortality and cardiovascular mortality. Therefore, the government should play an important role in the prevention and control ways of decreasing and eliminating the ozone pollution to protect the resident's health. The findings provide valuable data for further scientific research and improving environmental policies in Nanchang city.
Ambient ozone (O(3)) has emerged as an important public health issue worldwide. Previous studies found an association between O(3) and cardiorespiratory mortality. However, evidence was limited regarding the risk of O(3) on mortality from other diseases. In this study, we aimed to estimate the association between O(3) and mortality from a broad spectrum of diseases in Guangzhou, China, which has experienced a rapid increase in O(3) concentration over the past decades. Daily data were obtained on cause-specific mortality, air pollutant concentrations and weather conditions during 2013-2018. A generalized additive model with quasi-Poisson regression was applied to examine the association between O(3) and mortality from 10 broad causes and 26 refined subcategories, with adjustment of long-term and seasonal trends, weather conditions, public holidays and days of the week. We found that the threshold concentrations of O(3) were 40 μg/m(3) for all-cause, non-accidental, cardiovascular and respiratory mortality. Mortality risk increased monotonically with O(3) concentrations above the threshold. Per 10 μg/m(3) increase of O(3) at lag 0-3 days was associated with 0.54% (95%CI: 0.34-0.74%), 0.56% (95%CI: 0.36-0.76%), 0.59% (95%CI: 0.30-0.88%), 0.78% (95%CI: 0.33-1.24%) and 0.52% (95%CI: 0.21-0.83%) elevated risk of death from all causes, non-accidental causes, cardiovascular diseases, respiratory diseases and neoplasms, respectively. Among the subcategories, the largest effect estimate was observed in people with chronic obstructive pulmonary disease. The elderly suffered from a higher mortality risk from O(3). Stringent emission control strategies and multi-sectoral collaborations are needed to reduce the detrimental impact of O(3) on vulnerable populations.
Facing the dual challenges of climate change and air pollution, China has made great efforts to explore the co-control strategies for the both. We assessed the benefits of carbon and pollution control policies on air quality and human health, with an integrated framework combining an energy-economic model, an air quality model and a concentration-response model. With a base year 2015, seven combined scenarios were developed for 2030 based on three energy scenarios and three end-of-pipe control ones. Policy-specific benefits were then evaluated, indicated by the reduced emissions, surface concentrations of major pollutants, and premature deaths between scenarios. Compared to the 2030 baseline scenario, the nationwide PM(2.5)- and O(3)-related mortality was expected to decline 23% or 289 (95% confidence interval: 220-360) thousand in the most stringent scenario, and three quarters of the avoided deaths were attributed to the end-of-pipe control measures. Provinces in heavily polluted and densely populated regions would benefit more from carbon and pollution control strategies. The population fractions with PM(2.5) exposure under the national air quality standard (35 μg/m(3)) and WHO guideline (10 μg/m(3)) would be doubled from 2015 to 2030 (the most stringent scenario), while still very few people would live in areas with the WHO guideline achieved for O(3) (100 μg/m(3)). Increased health impact of O(3) suggested a great significance of joint control of PM(2.5) and O(3) in future policy-making.
Background This study investigated risks of mortality from and morbidity (emergency room visits (ERVs) and outpatient visits) of asthma and chronic obstructive pulmonary disease (COPD) associated with extreme temperatures, fine particulate matter (PM2.5), and ozone (O3) by sex, and age, from 2005 to 2016 in 6 metropolitan cities in Taiwan. Methods The distributed lag non-linear model was employed to assess age (0–18, 19–39, 40–64, and 65 years and above), sex-cause-specific deaths, ERVs, and outpatient visits associated with extreme high (99th percentile) and low (5th percentile) temperatures and PM2.5 and O3 concentrations at 90th percentile. Random-effects meta-analysis was adopted to investigate cause-specific pooled relative risk (RR) and 95% confidence intervals (CI) for the whole
studied areas. Results Only the mortality risk of COPD in the elderly men was significantly associated with the extreme low temperatures. Exposure to the 90th percentile PM2.5 was associated with outpatient visits for asthma in 0–18 years old boys [RR = 1.15 (95% CI: 1.09–1.22)]. Meanwhile, significant elevation of ERVs of asthma for females aged 40–64 years was associated with exposure to ozone, with the highest RR of 1.21 (95% CI: 1.05–1.39). Conclusions This study identified vulnerable subpopulations who were at risk to extreme events associated with ambient environments deserving further evaluation for adaptation.
BACKGROUND: The health effect of particulate matter pollution on stroke has been widely examined; however, the effect among patients with comorbid type 2 diabetes (T2D) in developing countries has remained largely unknown. METHODS: A time-series study was conducted to investigate the short-term effect of fine particulate matter (PM(2.5)) and inhalable particulate matter (PM(10)) on hospital admissions for stroke among patients with T2D in Beijing, China, from 2014 to 2018. An over-dispersed Poisson generalized additive model was employed to adjust for important covariates, such as weather conditions and long-term and seasonal trends. RESULTS: A total of 159,298 hospital admissions for stroke comorbid with T2D were reported. Approximately linear exposure-response curves were observed for PM(2.5) and PM(10) in relation to stroke admissions among T2D patients. A 10 μg/m(3) increase in the four-day moving average of PM(2.5) and PM(10) was associated with 0.14% (95% confidence interval [CI]: 0.05-0.23%) and 0.14% (95% CI: 0.06-0.22%) incremental increases in stroke admissions among T2D patients, respectively. A 10 μg/m(3) increase in PM(2.5) in the two-day moving average corresponded to a 0.72% (95% CI: 0.02-1.42%) incremental increase in hemorrhagic stroke, and a 10 μg/m(3) increase in PM(10) in the four-day moving average corresponded to a 0.14% (95% CI: 0.06-0.22%) incremental increase in ischemic stroke. CONCLUSIONS: High particulate matter might be a risk factor for stroke among patients with T2D. PM(2.5) and PM(10) have a linear exposure-response relationship with stroke among T2D patients. The study provided evidence of the risk of stroke due to particulate matter pollution among patients with comorbid T2D.
OBJECTIVE: To explore the relationship between ambient PM(2.5) level and outpatient visits of children with respiratory diseases in a megacity, Zhengzhou, in central China. METHODS: We collected daily outpatient visit data, air pollutant data, and meteorological data at the monitoring points of Zhengzhou from the time period 2018 to 2020 and used Spearman’s rank correlation to analyze the correlation between children’s respiratory outpatient visits and air pollutants and meteorological factors. Generalized additive models were used to analyze the association between PM(2.5) exposures and children’s respiratory outpatient visits. A stratified analysis was further carried out for the seasons. RESULTS: From 2018 to 2020, the total number of outpatients with children’s respiratory diseases was 79,1107, and the annual average concentrations of PM(2.5), PM(10), SO(2), NO(2), CO, and O(3)-8h in Zhengzhou were respectively 59.48 μg/m(3), 111.12 μg/m(3), 11.10 μg/m(3), 47.77 μg/m(3), 0.90 mg/m(3) and 108.81 μg/m(3). The single-pollutant model showed that the risk of outpatient visits for children with respiratory disease increased by 0.341% (95%CI: 0.274-0.407%), 0.532% (95%CI: 0.455-0.609%) and 0.233% (95%CI: 0.177-0.289%) for every 10 μg/m(3) increase in PM(2.5) with a 3-day lag, 1-day lag, and 1-day lag respectively for the whole year, heating period, and non-heating period. The multi-pollutant model showed that the risk of PM(2.5) on children’s respiratory disease visits was robust. The excess risk of PM(2.5) on children’s respiratory disease visits increased by 0.220% (95%CI: 0.147-0.294%) when SO(2) was adjusted. However, the PM(2.5) effects were stronger during the heating period than during the non-heating period. CONCLUSION: The short-term exposure to PM(2.5) was significantly associated with outpatient visits for children’s respiratory diseases. It is therefore necessary to strengthen the control of air pollution so as to protect children’s health.
Atmospheric coarse particulate matter (PM(10)) enriched with heavy metal(loid)s could pose potentially significant health risk to humans, while accurate health risk assessment calls for characterization of their bioaccessibility, besides the total contents. The health risk of major toxic heavy metal(loid)s in the PM(10) from four large cities in northern China via inhalation was investigated based on their total contents and bioaccessibility. The annual mean concentrations of PM-bound Zn, As, Pb, and Mn in the atmosphere of the four cities were 650, 305, 227, and 177 ng⋅m(-3), respectively. The levels of heavy metal(loid)s in the PM(10) were generally higher in winter but lower in summer in all four cities, which resulted primarily from the emissions associated with coal combustion for district and household heating and the unfavorable meteorological conditions in winter. The bioaccessibility of heavy metal(loid)s in the PM(10) ranged from 0.9 to 48.7%, following the general order of Mn > Co > Ni > Cd > Cu > As > Cr > Zn > Pb. Based on their total contents in the PM(10), most heavy metal(loid)s posed significant public health risk via inhalation exposure in the four cities. However, after accounting for the bioaccessibility of metal(loid)s, the non-carcinogenic risk of most metal(loid)s was negligible, except for As in the PM(10) of Jinzhong, while only the carcinogenic risk posed by Cr and As in the PM(10) exceeded the acceptable level. These findings demonstrate the importance of characterizing the bioaccessibility of airborne PM-bound heavy metal(loid)s in health risk assessment and could guide the on-going efforts on reducing the public health risk of PM(10) in northern China.
Air pollution has a serious fallout on human health, and the influences of the different urban morphological characteristics on air pollutants cannot be ignored. In this study, the relationship between urban morphology and air quality (wind speed, CO, and PM(2.5)) in residential neighborhoods at the meso-microscale was investigated. The changes in the microclimate and pollutant diffusion distribution in the neighborhood under diverse weather conditions were simulated by Computational Fluid Dynamics (CFD). This study identified five key urban morphological parameters (Building Density, Average Building Height, Standard Deviation of Building Height, Mean Building Volume, and Degree of Enclosure) which significantly impacted the diffusion and distribution of pollutants in the neighborhood. The findings of this study suggested that three specific strategies (e.g. volume of a single building should be reduced, DE should be increased) and one comprehensive strategy (the width and height of the single building should be reduced while the number of single buildings should be increased) could be illustrated as an optimized approach of urban planning to relief the air pollution. The result of the combined effects could provide a reference for mitigating air pollution in sustainable urban environments.
A reduction in the energy-related emissions of air pollutants would not only mitigate climate change but would also improve local air quality and public health. This paper aimed to analyze the trends of air quality index (AQI) and greenhouse gas (GHG) emissions in Taiwan by using the latest official statistics. In addition, this study also summarized regulatory measures for controlling air pollution from the energy sector with relevance to sustainable development goals (SDGs). With the joint efforts by the public and private sectors, the change in the total GHG emissions did not vary much with the exception of 2009, ranging from 250 to 272 million metric tons of CO2 equivalent from 2005 through 2019. Based on the data on AQI, the percentage of AQI by station-day with AQI > 100 has decreased from 18.1% in 2017 to 10.1% in 2020, indicating a decreasing trend for all criteria air pollutants. On the other hand, the coronavirus disease (COVID-19) lockdown, in 2019, has positively impacted Taiwan’s urban air quality, which was consistent with those observed in other countries. This consistent situation could be attributed to the climate change mitigation policies and promotional actions under the revised Air Pollution Control Act and the Greenhouse Gas Reduction and Management Act of 2015. In response to the SDGs launched by the Taiwan government in 2018, achieving the relevant targets by 2030 can be prospective.
Previous observational studies have shown that exposure to ambient temperature and air pollution were associated with the incidence of gestational diabetes mellitus (GDM). However, the susceptible time window of non-optimal temperature on GDM is still unknown, and the interaction with air pollution has not been examined. We conducted a prospective cohort study in Guangzhou, China to investigate the windows of susceptibility of temperature extremes and variability on the risk of GDM and to explore any interaction effect with air pollution. Daily maximum (T(max)), minimum temperature (T(min)) and diurnal temperature range (DTR) were obtained from Guangdong Meteorological Service. Distributed lag non-linear models with a logistic regression were applied to assess the effect of temperature extremes and DTR in different weeks of gestation on GDM. To examine the interaction effect, relative excess risk due to interaction index, attributable proportion and synergy index were calculated. There were 5,165 pregnant women enrolled, of which 604 were diagnosed with GDM (11.7%). Compared with a reference temperature (50th percentile of T(max)), we found that extreme high temperature (99th percentile of T(max)) exposure during 21st and 22nd gestational weeks was associated with an increased risk of GDM. Extreme low temperature (1st percentile of T(max)) exposure during 14th to 17th weeks increased the risk of GDM. We observed that per 1 °C increment of DTR during 21st to 24th weeks was associated with an elevated GDM risk. No interaction effect of temperature extremes or variability with air pollution on GDM were observed. Our results suggested that non-optimal temperature is an independent risk factor of GDM. The time window of susceptibility for extreme temperatures and DTR exposure on the risk of GDM generally occurred in second trimester of pregnancy. In the context of climate change, our study has important implications for reproductive health and justifies more research in different climate zones.
There are increasing concerns with regard to spontaneous abortion (SAB), the loss of pregnancy without external intervention before 20 weeks of gestation, among reproductive-aged women. To date, limited evidence is available concerning the association between SAB and air pollutants, especially in developing countries. Daily baseline outpatient data for SAB from January 1, 2014, to December 31, 2018 (1826 days) were obtained in Chongqing, a metropolis of southwest China. The over-dispersed Poisson generalized additive model with control of meteorological conditions and day of week was used to estimate the short-term effects of ambient air pollution on the daily number of SAB outpatients. A total of 42,334 SAB outpatient visits for SAB were recorded. No statistically significant association was observed between SAB and CO, PM(2.5), PM(10), O(3), and SO(2). The positive association only appeared for NO(2): positive associations between SAB and NO(2) were observed in both single-day models (lag 0, lag 1, lag 3, and lag 4) and cumulative exposure models (lag 01, lag 03, and lag 05) and the most significant effects were observed at lag 05 (3.289%; 95% CI: 1.568%, 5.011%). Moreover, the women with higher ages (30-39 and > 39) were more sensitive than those with lower ages (18-29), and the effect estimates were more evident in cool seasons. Collectively, our results suggested that short-term NO(2) exposure was associated with higher risk of SAB, especially in elder women and cool seasons, which may contribute to further understand the role of air pollution on SAB and other adverse obstetric outcomes.
Airborne pollen causes various types of allergies in humans, and the extent of allergic infection is related to the presence of different types of sporo-pollen and existing meteorological conditions in a certain area. Therefore, an aeropalynological study of 72 airborne samples with a hydrofluoric acid (HF) treatment was conducted in the Haizhu district of Guangzhou, China, in 2016, to identify the temporal variations in airborne sporo-pollen and the relationship between airborne sporo-pollen concentrations and different meteorological variables in Guangzhou, China. Forty-five types of airborne pollen, seven types of airborne spores, and some undetermined sporo-pollen taxa were identified with two separate plant habitats occurring during this period (from January to December 2016): arboreal pollen (tree-based) and non-arboreal pollen (herb, shrub, aquatic, liane, etc.). Furthermore, the daily records of four key meteorological variables (temperature, precipitation, relative humidity, and wind speed) were acquired to distinguish the pollen seasons and correlated with Spearman’s rho test to establish a pollen-weather data book with the seasonal variations. The two leading seasons were identified based on pollen abundance: spring and autumn. Among them, the primary dominant sporo-pollen families during the spring season were Poaceae, Pinaceae, Euphorbiaceae, Moraceae, Microlepia sp., and Polypodiaceae. Conversely, Artemisia sp., Asteraceae, Cyperaceae, Poaceae, Alnus sp., Corylus sp., Myrtaceae, and Rosaceae were the dominant pollen species during autumn. However, few pollen grains were identified in January, May-July, and December. The statistical analysis revealed that temperature had both positive and negative correlations with sporo-pollen concentrations. However, precipitation and relative humidity had a strong impact on the sporo-pollen dispersion and exhibited a negative correlation with the sporo-pollen concentrations. The wind speed had a positive but strong correlation with the sporo-pollen concentration during the study period. Some inconsistent results were found due to environmental variations, vegetation type, and climate change around the study area. This study will facilitate the identification of pollen seasons to prevent the occurrence of pollen-related allergies in the Guangzhou city area.
The growing concerns over urbanization and climate change have resulted in an exponential growth in publications on urban climatology in recent decades. However, an advanced synthesis that characterizes the existing studies is lacking. In this review, we used citation network analysis and a text mining approach to identify research trends and extract common research topics and the emerging domains in urban climatology. Based on the clustered networks, we found that aerosols and ozone, and urban heat island are the most popular topics. Together with other clusters, four emerging topical fields were identified: secondary organic aerosols, urban precipitation, flood risk and adaptation, and greenhouse gas emissions. The city case studies’ geographical information was analyzed to explore the spatial-temporal patterns, especially in the emerging topical fields. Interdisciplinary research grew in recent years as the field of urban climatology expanded to interact with urban hydrology, health, energy issues, and social sciences. A few knowledge gaps were proposed: the lack of long-term high-temporal-resolution observational data of organic aerosols for model validation and improvements, the need for predictions of urban effects on precipitation and extreme flooding events under climate change, and the lack of a framework for cooperation between physical sciences and social sciences under urban settings. To fill these gaps, we call for more observational data with high spatial and temporal resolution, using high-resolution models that adequately represent urban processes to conduct scenario analyses for urban planning, and the development of intellectual frameworks for better integration of urban climatology and social-economical systems in cities. This article is categorized under: Climate, History, Society, Culture > Disciplinary Perspectives
Wind-related disasters will bring more devastating consequences to cities in the future with a changing climate, but relevant studies have so far provided insufficient information to guide adaptation actions. This study aims to provide an in-depth elaboration of the contents discussed in open access literature regarding wind disaster adaptation in cities. We used the Latent Dirichlet Allocation (LDA) to refine topics and main contents based on 232 publications (1900 to 2019) extracted from Web of Science and Scopus. We conducted a full-text analysis to filter out focal cities along with their adaptation measures. The results show that wind disaster adaptation research in cities has formed a systematic framework in four aspects: 1) vulnerability and resilience of cities, 2) damage evaluation, 3) response and recovery, and 4) health impacts of wind disaster. Climate change is the background for many articles discussing vulnerability and adaptation in coastal areas. It is also embedded in damage evaluation since it has the potential to exacerbate disaster consequences. The literature is strongly inclined towards more developed cities such as New York City and New Orleans, among which New York City associated with Hurricane Sandy ranks first (38/232). Studies on New York City cover all the aspects, including the health impacts of wind disasters which are significantly less studied now. Distinct differences do exist in the number of measures regarding the adaptation categories and their subcategories. We also find that hard adaptation measures (i.e., structural and physical measures) are far more popular than soft adaptation measures (i.e., social and institutional measures). Our findings suggest that policymakers should pay more attention to cities that have experienced major wind disasters other than New York. They should embrace the up-to-date climate change study to defend short-term disasters and take precautions against long-term changes. They should also develop hard-soft hybrid adaptation measures, with special attention on the soft side, and enhance the health impact study of wind-related disasters.
Purpose of reviewThe purpose of this chapter is to review allergic disease and how it is potentially impacted by climate change. It is difficult to measure the direct impact climate change has on allergic disease. This is difficult because there are many variables impacting human health as well as what capacity humans have to adapt to these changes. Asthma is tightly associated with allergies and environmental factors, especially in children. In this review, we will explore evidence of environmental changes associated with climate change and the potential impacts on allergy and associated respiratory disease. Furthermore, this paper is to review the impact of climate change on allergy to atmospheric fungi which are known to cause a common allergic response. In this review, we will explore evidence of environmental changes associated with climate change and the potential impacts on allergy.Recent findingsThe climate has been measurably changing for the past 100 years and has been described as the most significant health threat of the twenty-first century. How climate change impacts human health is varied and coming more into focus. While direct effects, such as heatwaves, severe weather, drought, and flooding, are well reported, effects that are indirect or secondary impacts involving changes in ecosystems are less obvious, though the body of data is growing and becoming more robust. It is these changes in ecosystems that may have the greatest impact on allergic and respiratory diseases. Otherwise, the airborne pollens and spores have also been linked with upper and lower respiratory conditions. Atmospheric pollen and spore concentrations are influenced by a wide array of environmental, meteorological, and biological factors and various interspecies interactions. Pollen and spores underlie seasonal variations. Especially climatic factors and circadian patterns influence the spectrum of their species and their concentrations in the environment. It may have the greatest impact on respiratory allergic diseases.SummaryThis review will explore some of the impacts our changing climate, current and predicted, has which influences upper and lower respiratory allergic diseases. The discussion will focus on changing pollination with altered pollen patterns, as well as alteration of the composition and transformation of atmospheric allergic fungi with increased CO2 air pollution and heat stress. The sporulation of fungi is likely to be amplified as CO2 concentration increases with climate change, potentially contributing to the increasing prevalence and severity of asthma and other respiratory allergies.
The coronavirus disease 2019 (COVID-19) pandemic caused a crisis worldwide, due to both its public health impact and socio-economic consequences. Mental health was consistently affected by the pandemic, with the emergence of newly diagnosed psychiatric disorders and the exacerbation of pre-existing ones. Urban areas were particularly affected by the virus spread. In this review, we analyze how the urban environment may influence mental health during the COVID-19 pandemic, considering two factors that profoundly characterize urbanization: air pollution and migration. Air pollution serves as a possibly risk factor for higher viral spread and infection severity in the context of urban areas and it has also been demonstrated to play a role in the development of serious mental illnesses and their relapses. The urban environment also represents a complex social context where minorities such as migrants may live in poor hygienic conditions and lack access to adequate mental health care. A global rethinking of the urban environment is thus required to reduce the impact of these factors on mental health. This should include actions aimed at reducing air pollution and combating climate change, promoting at the same time a more inclusive society in a sustainable development perspective.
INTRODUCTION: Type 2 diabetes and climate change are forefront global challenges of the 21st century. Both are on a progressive incline with intergenerational effects on the wellbeing, health and security of the population. The aim of this review was to explore the interconnection relationship between type 2 diabetes and climate change. METHODS: A literature review search of MEDLINE publications from 2010 to March 2020 was performed. English-language articles using terms “diabetes” AND “climate change” OR “temperature change” OR “temperature rise” OR “hot temperature” OR “extreme heat” were reviewed. RESULTS: Climate change and diabetes are interconnected through a direct and indirect pathway. Temperature changes can trigger a person’s susceptibility to develop diabetes as well as impose adverse effects on those diagnosed with diabetes (such as increased incidence of hospitalization, dehydration and mortality). Both temperature extremes have been reported to lead to negative effects on diabetes. Concurrently, both phenomena have shared predisposing vectors (such as sedentary lifestyle, urbanisation, unhealthy diets) that lead to their progressive development. CONCLUSION: A bidirectional relationship exists between type 2 diabetes and climate change. This relationship originates through a multifactorial pathway involving biological, social, environmental, geophysical and economic factors. An integrated action plan targeting the common predisposing vectors should be set up. This should support a low environmental impact while promoting equity and wellbeing.
PURPOSE OF REVIEW: Atopic dermatitis (AD) is a chronic inflammatory skin disorder affecting up to 20% of children and up to 5% of adults worldwide, contributing to significant disease-related morbidity in this patient cohort. Its aetiopathogenesis is underpinned by multiple factors, including genetic susceptibility, skin barrier defects, a skewed cutaneous immune response and microbiome perturbation in both the skin and the gut. In this review, we aim to examine the biological effects of key environmental exposures (the sum of which is termed the “exposome”) at the population, community and individual levels in order to describe their effect on AD pathogenesis. RECENT FINDINGS: It is now understood that as well as considering the type of environmental exposure with regard to its effect on AD pathogenesis, the dosage and timing of the exposure are both critical domains that may lead to either exacerbation or amelioration of disease. In this review, we consider the effects of population-wide exposures such as climate change, migration and urbanization; community-specific exposures such as air pollution, water hardness and allergic sensitisation; and individual factors such as diet, microbiome alteration, psychosocial stress and the impact of topical and systemic therapy. SUMMARY: This review summarises the interaction of the above environmental factors with the other domains of AD pathogenesis, namely, the inherent genetic defects, the skin barrier, the immune system and the cutaneous and gut microbiota. We specifically emphasise the timing and dosage of exposures and its effect on the cellular and molecular pathways implicated in AD.
Heart failure is a major contributor to healthcare expenditures. Many clinical risk factors for the development and exacerbation of heart failure had been reported, including diabetes, renal dysfunction, and respiratory disease. In addition to these clinical parameters, the effects of social factors, such as occupation or lifestyle, and environmental factors may have a great impact on disease development and progression of heart failure. However, the current understanding of social and environmental factors as contributors to the clinical course of heart failure is insufficient. To present the knowledge of these factors to date, this comprehensive review of the literature sought to identify the major contributors to heart failure within this context. Social factors for the risk of heart failure included occupation and lifestyle, specifically in terms of the effects of specific occupations, occupational exposure to toxicities, work style, and sleep deprivation. Socioeconomic factors focused on income and education level, social status, the neighborhood environment, and marital status. Environmental factors included traffic and noise, air pollution, and other climate factors. In addition, psychological stress and behavior traits were investigated. The development of heart failure may be closely related to these factors; therefore, these data should be summarized for the context to improve their effects on patients with heart failure. The present study reviews the literature to summarize these influences.
Sensing and measuring meteorological and physiological parameters of humans, animals, and plants are necessary to understand the complex interactions that occur between atmospheric processes and the health of the living organisms. Advanced sensing technologies have provided both meteorological and biological data across increasingly vast spatial, spectral, temporal, and thematic scales. Information and communication technologies have reduced barriers to data dissemination, enabling the circulation of information across different jurisdictions and disciplines. Due to the advancement and rapid dissemination of these technologies, a review of the opportunities for sensing the health effects of weather and climate change is necessary. This paper provides such an overview by focusing on existing and emerging technologies and their opportunities and challenges for studying the health effects of weather and climate change on humans, animals, and plants.
Research on heat waves (periods of excessively hot weather, which may be accompanied by high humidity) is a newly emerging research topic within the field of climate change research with high relevance for the whole of society. In this study, we analyzed the rapidly growing scientific literature dealing with heat waves. No summarizing overview has been published on this literature hitherto. We developed a suitable search query to retrieve the relevant literature covered by the Web of Science (WoS) as complete as possible and to exclude irrelevant literature (n?=?8,011 papers). The time evolution of the publications shows that research dealing with heat waves is a highly dynamic research topic, doubling within about 5 years. An analysis of the thematic content reveals the most severe heat wave events within the recent decades (1995 and 2003), the cities and countries/regions affected (USA, Europe, and Australia), and the ecological and medical impacts (drought, urban heat islands, excess hospital admissions, and mortality). An alarming finding is that the limit for survivability may be reached at the end of the twenty-first century in many regions of the world due to the fatal combination of rising temperatures and humidity levels measured as “wet-bulb temperature” (WBT). Risk estimation and future strategies for adaptation to hot weather are major political issues. We identified 104 citation classics, which include fundamental early works of research on heat waves and more recent works (which are characterized by a relatively strong connection to climate change).
Air pollution disproportionately affects marginalized populations of lower socioeconomic status. There is little literature on how socioeconomic status affects the risk of exposure to air pollution and associated health outcomes, particularly for children’s health. The objective of this article was to review the existing literature on air pollution and children’s health and discern how socioeconomic status affects this association. The concept of environmental injustice recognizes how underserved communities often suffer from higher air pollution concentrations in addition to other underlying risk factors for impaired health. This exposure then exerts larger effects on their health than it does in the average population, affecting the whole body, including the lungs and the brain. Children, whose organs and mind are still developing and who do not have the means of protecting themselves or creating change, are the most vulnerable to the detrimental effects of air pollution and environmental injustice. The adverse health effects of air pollution and environmental injustice can harm children well into adulthood and may even have transgenerational effects. There is an urgent need for action in order to ensure the health and safety of future generations, as social disparities are continuously increasing, due to social discrimination and climate change.
Global atmospheric warming leads to climate change that results in a cascade of events affecting human mortality directly and indirectly. The factors that influence climate change-related mortality within the peer-reviewed literature were examined using Whittemore and Knafl’s framework for an integrative review. Ninety-eight articles were included in the review from three databases-PubMed, Web of Science, and Scopus-with literature filtered by date, country, and keywords. Articles included in the review address human mortality related to climate change. The review yielded two broad themes in the literature that addressed the factors that influence climate change-related mortality. The broad themes are environmental changes, and social and demographic factors. The meteorological impacts of climate change yield a complex cascade of environmental and weather events that affect ambient temperatures, air quality, drought, wildfires, precipitation, and vector-, food-, and water-borne pathogens. The identified social and demographic factors were related to the social determinants of health. The environmental changes from climate change amplify the existing health determinants that influence mortality within the United States. Mortality data, national weather and natural disaster data, electronic medical records, and health care provider use of International Classification of Disease (ICD) 10 codes must be linked to identify climate change events to capture the full extent of climate change upon population health.
Water is indispensable for human survival. Freshwater scarcity and unsustainable water are the main growing concerns in the world. It is estimated that about 800 million people worldwide do not have basic access to drinking water and about 2.2 billion people do not have access to safe water supply. Southeast Asia is most likely to experience water scarcity and water demand as a result of climate change. Climate change and the increasing water demand that eventually contribute to water scarcity are focused upon here. For Southeast Asia to adapt to the adverse consequences of global climate change and the growing concern of environmental water demand, fog water harvesting is considered as the most promising method to overcome water scarcity or drought. Fog water collection technique is a passive, low maintenance, and sustainable option that can supply fresh drinking water to communities where fog is a common phenomenon. Fog water harvesting system involves the use of mesh nets to collect water as fog passes through them. Only minimal cost is required for the operation and maintenance. In conclusion, fog water harvesting seems to be a promising method that can be implemented to overcome water scarcity and water demand in Southeast Asia.
Kerala is one of India’s most vulnerable states in India when it comes to climate-induced disasters. Kerala’s public health department grappled with a flood of unprecedented magnitude in August 2018. Situating the flood in the context of Kerala’s state and society, this paper addresses three questions: What was the level of flood-prevention preparedness? What were the public health effects and how were they managed? Finally, what policy lessons were learned? Drawing from reports of relevant national and state agencies responsible for disaster management as well as first-hand accounts of nongovernmental organizations and media coverage, this paper argues that while Kerala’s flood-prevention preparedness was far from ideal, its postflood response in mounting a rapid and effective rescue and relief operation as well as in preventing a public health crisis was commendable. The paper also shows that impressive achievements in climate-disaster health management can be achieved through a decentralized and participatory public health system in which coordinated public action is managed by a capacious state with the active collaboration of civil society.
Under the climate change scenario, the negative impacts of urban heat island (UHI) will exacerbate due to unsustainable urban planning and human activities. Thermal comfort has close relationships with UHI in urban areas. This paper is based on the studies of urban heat island, thermal comfort, microclimate, and urban planning in cities in the recent decade, combined with a method of research into design. The key topics include vegetation and water conditions, the albedo of materials, and urban morphology. By the comparative case studies in landscape projects, the results further reveal that the density of tree canopies, the natural structure and density of ground cover, the form of water features, the color and texture of materials, and the scale of shading structures have different cooling effect and performance in outdoor thermal comfort improvement with specific features in the landscape design. It is also found that there are some external conditions that can influence design determinations in real practices. The purpose of this study is to provide theoretical research methods and evaluation of thermal comfort landscape design elements and to provide guidance for future sustainable city research and landscape design.
Cities produce more than 70% of global greenhouse gas emissions. Action by cities is therefore crucial for climate change mitigation as well as for safeguarding the health and wellbeing of their populations under climate change. Many city governments have made ambitious commitments to climate change mitigation and adaptation and implemented a range of actions to address them. However, a systematic record and synthesis of the findings of evaluations of the effect of such actions on human health and wellbeing is currently lacking. This, in turn, impedes the development of robust knowledge on what constitutes high-impact climate actions of benefit to human health and wellbeing, which can inform future action plans, their implementation and scale-up. The development of a systematic record of studies reporting climate and health actions in cities is made challenging by the broad landscape of relevant literature scattered across many disciplines and sectors, which is challenging to effectively consolidate using traditional literature review methods. This protocol reports an innovative approach for the systematic development of a database of studies of climate change mitigation and adaptation actions implemented in cities, and their benefits (or disbenefits) for human health and wellbeing, derived from peer-reviewed academic literature. Our approach draws on extensive tailored search strategies and machine learning methods for article classification and tagging to generate a database for subsequent systematic reviews addressing questions of importance to urban decision-makers on climate actions in cities for human health and wellbeing.
The new severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) pandemic was first recognized at the end of 2019 and has caused one of the most serious global public health crises in the last years. In this paper, we review current literature on the effect of weather (temperature, humidity, precipitation, wind, etc.) and climate (temperature as an essential climate variable, solar radiation in the ultraviolet, sunshine duration) variables on SARS-CoV-2 and discuss their impact to the COVID-19 pandemic; the review also refers to respective effect of urban parameters and air pollution. Most studies suggest that a negative correlation exists between ambient temperature and humidity on the one hand and the number of COVID-19 cases on the other, while there have been studies which support the absence of any correlation or even a positive one. The urban environment and specifically the air ventilation rate, as well as air pollution, can probably affect, also, the transmission dynamics and the case fatality rate of COVID-19. Due to the inherent limitations in previously published studies, it remains unclear if the magnitude of the effect of temperature or humidity on COVID-19 is confounded by the public health measures implemented widely during the first pandemic wave. The effect of weather and climate variables, as suggested previously for other viruses, cannot be excluded, however, under the conditions of the first pandemic wave, it might be difficult to be uncovered. The increase in the number of cases observed during summertime in the Northern hemisphere, and especially in countries with high average ambient temperatures, demonstrates that weather and climate variables, in the absence of public health interventions, cannot mitigate the resurgence of COVID-19 outbreaks.
Heat related morbidity and mortality, especially during extreme heat events, are increasing due to climate change. More Americans die from heat than from all other natural disasters combined. Identifying the populations and locations that are under high risk of heat vulnerability is important for urban planning and design policy making as well as health interventions. An increasing number of heat vulnerability/risk models and indices (HV/R) have been developed based on indicators related to population heat susceptibility such as sociodemographic and environmental factors. The objectives of this study are to summarize and analyze current HV/R’s construction, calculation, and validation, evaluate the limitation of these methods, and provide directions for future HV/R and related studies. This systematic review used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework and used 5 datasets for the literature search. Journal articles that developed indices or models to assess population level heat-related vulnerability or risks in the past 50?years were included. A total of 52 papers were included for analysis on model construction, data sources, weighting schemes and model validation. By synthesizing the findings, we suggested: (1) include relevant and accurately measured indicators; (2) select rational weighting methods and; (3) conduct model validation. We also concluded that it is important for future heat vulnerability models and indices studies to: (1) be conducted in more tropical areas; (2) include a comprehensive understanding of energy exchanges between landscape elements and humans; and (3) be applied in urban planning and policy making practice.
While the East Asia Pacific (EAP) region has experienced tremendous economic growth and development, the resulting public health gains from reductions in its neglected tropical diseases (NTDs) have been less than expected due to opposing forces of urbanization, political instability, food insecurity, and climate change, together with co-morbidities with non-communicable diseases, including diabetes and hypertension. To be sure there’s been progress towards the elimination of lymphatic filariasis and trachoma through mass drug administration, and there are opportunities to extend MDA to yaws and scabies, but for most of the other NTDs we’ll require new biotechnologies. So far, EAP’s major technology hubs in China, Japan, Malaysia, Singapore, South Korea, and Taiwan have mostly failed to shift their attention towards new innovations for the NTDs, including new drugs, diagnostics, and vaccines, and vector control. Unless this situation changes the EAP could be facing a new grim reality of unhealthy megacities beset by emerging arbovirus infections, widespread antimicrobial resistance, and urban helminth infections.
Urban outdoor thermal conditions, and its impacts on the health and well-being for the city inhabitants have reached increased attention among biometeorological studies during the last two decades. Children are considered more sensitive and vulnerable to hot ambient conditions compared to adults, and are affected strongly by their thermal environment. One of the urban outdoor environments that children spend almost one third of their school time is the schoolyard. The aims of the present manuscript were to review studies conducted worldwide, in order to present the biophysical characteristics of the typical design of the urban schoolyard. This was done to assess, in terms of bioclimatology, the interactions between the thermal environment and the children’s body, to discuss the adverse effects of thermal environment on children, especially the case of heat stress, and to propose measures that could be applied to improve the thermal environment of schoolyards, focusing on vegetation. Human thermal comfort monitoring tools are mainly developed for adults, thus, further research is needed to adapt them to children. The schemes that are usually followed to design urban schoolyards create conditions that favour the exposure of children to excessive heat, inducing high health risks to them. The literature survey showed that typical urban schoolyard design (i.e., dense surface materials, absence of trees) triggered high surface temperatures (that may exceed 58 degrees C) and increased absorption of radiative heat load (that may exceed 64 degrees C in terms of Mean Radiant Temperature) during a clear day with intense solar radiation. Furthermore, vegetation cover has a positive impact on schoolyard’s microclimate, by improving thermal comfort and reducing heat stress perception of children. Design options for urban schoolyards and strategies that can mitigate the adverse effects of heat stress are proposed with focus on vegetation cover that affect positively their thermal environment and improve their aesthetic and functionality.
Human health and wellbeing and the health of the biosphere are inextricably linked. The state of Earth’s life-support systems, including freshwater, oceans, land, biodiversity, atmosphere, and climate, affect human health. At the same time, human activities are adversely affecting natural systems. This review paper is the outcome of an interdisciplinary workshop under the auspices of the Future Earth Health Knowledge Action Network (Health KAN). It outlines a research agenda to address cross-cutting knowledge gaps to further understanding and management of the health risks of these global environmental changes through an expert consultation and review process. The research agenda has four main themes: (1) risk identification and management (including related to water, hygiene, sanitation, and waste management); food production and consumption; oceans; and extreme weather events and climate change. (2) Strengthening climate-resilient health systems; (3) Monitoring, surveillance, and evaluation; and (4) risk communication. Research approaches need to be transdisciplinary, multi-scalar, inclusive, equitable, and broadly communicated. Promoting resilient and sustainable development are critical for achieving human and planetary health.
INTRODUCTION: We are witnessing an alarming increase in the burden and range of mosquito-borne arboviral diseases. The transmission dynamics of arboviral diseases is highly sensitive to climate and weather and is further affected by non-climatic factors such as human mobility, urbanization, and disease control. As evidence also suggests, climate-driven changes in species interactions may trigger evolutionary responses in both vectors and pathogens with important consequences for disease transmission patterns. AREAS COVERED: Focusing on dengue and chikungunya, we review the current knowledge and challenges in our understanding of disease risk in a rapidly changing climate. We identify the most critical research gaps that limit the predictive skill of arbovirus risk models and the development of early warning systems, and conclude by highlighting the potentially important research directions to stimulate progress in this field. EXPERT OPINION: Future studies that aim to predict the risk of arboviral diseases need to consider the interactions between climate modes at different timescales, the effects of the many non-climatic drivers, as well as the potential for climate-driven adaptation and evolution in vectors and pathogens. An important outcome of such studies would be an enhanced ability to promulgate early warning information, initiate adequate response, and enhance preparedness capacity.
According to United Nations, cities situated in the tropical belt occupy only 36% of the Earth’s surface yet account for 1/3 of the entire global population. The increasing number of compact dense cities and the rapid population growth in the tropics have also been accompanied by increased urban air temperature. Increased air temperature is often associated with heat waves, and increased energy consumption. Therefore, the urban heat island (UHI) phenomenon and thermal stress have received much research attention and, as a result, the establishment of heat mitigation technologies has become critical. Although studies on urban climate in the tropics have shown progress, the situation in these areas remains complex and warrants further investigation. Accordingly, this paper examines the available heat mitigation techniques and their effectiveness in tropical areas from five perspectives, namely, shading (modifications in urban geometry), urban ventilation (street orientation, sun, and wind), urban greening (green roofs, trees, parks, and walls), albedo, and water bodies. This review paper showed that adopting a combination of mitigation approaches is the most effective method in reducing temperature in tropical cities. The use of shading and/or urban ventilation has also been proven to be more promising than the extensive use of vegetation, water bodies, or albedo modifications in reducing air temperature in tropical cities, where there is already a high level of humidity exists. Some key planning actions to combat UHI and thermal discomfort in tropical areas are eventually provided that can help urban planners integrate urban climatic knowledge into their practices.
The aim of the UN Sustainable Development Goals (SDGs) is to achieve a better and more sustainable future for all by 2030. Since the majority of the global population lives in cities, it is crucial to identify, evaluate and implement urban interventions (such as zero carbon housing, active transport, better urban connectivity, air pollution control, clean household fuels, and protection from heat and flood events) that will improve health and wellbeing and make our natural and built environment more sustainable. This Virtual Special Issue (VSI) comprises of 14 diverse case studies, methods and tools that provide suggestions for interventions which directly or indirectly support the achievement of the UN SDGs.
Cities in Australia are experiencing unprecedented levels of urban overheating, which has caused a significant impact on the country’s socioeconomic environment. This article provides a comprehensive review on urban overheating, its impact on health, energy, economy, and the heat mitigation potential of a series of strategies in Australia. Existing studies show that the average urban heat island (UHI) intensity ranges from 1.0 degrees C to 13.0 degrees C. The magnitude of urban overheating phenomenon in Australia is determined by a combination of UHI effects and dualistic atmospheric circulation systems (cool sea breeze and hot desert winds). The strong relation between multiple characteristics contribute to dramatic fluctuations and high spatiotemporal variabilities in urban overheating. In addition, urban overheating contributes to serious impacts on human health, energy costs, thermal comfort, labour productivity, and social behaviour. Evidence suggest that cool materials, green roofs, vertical gardens, urban greenery, and water-based technologies can significantly alleviate the UHI effect, cool the ambient air, and create thermally balanced cities. Urban greenery, especially trees, has a high potential for mitigation. Trees and hedges can reduce the average maximum UHI by 1.0 degrees C. The average maximum mitigation performance values of green roofs and green walls are 0.2 degrees C and 0.1 degrees C, respectively. Reflective roofs and pavements can reduce the average maximum UHI by 0.3 degrees C. In dry areas, water has a high cooling potential. The average maximum cooling potential using only one technology is 0.4 degrees C. When two or more technologies are used at the same time, the average maximum UHI drop is 1.5 degrees C. The mitigation strategies identified in this article can help the governments and other stakeholders manage urban heating in the natural and built environment, and save health, energy, and economic costs.
Introduction: This study aimed to identify climatic and environmental factors influencing the occurrence of heatstroke. Methods: A systematic review was conducted in February 2020 and 428 potentially relevant records were searched among PubMed, Scopus, Science Direct, and Web of Science and Google scholar databases in English language. After quality assessment and cross-checking by two independent researchers, finally, 14 articles included in this systematic review. Results: Solar radiant heat, ambient temperature, humidity, maximum and minimum daily temperature and humidity, water vapor pressure, wet bulb globe temperature (WBGT) index, Heat index (HI), sub-tropical climate, heatwaves, Urban Heat Island (UHI) effect, urbanization, daytime population density, surface temperature, high activity level in indoor/outdoor settings and local ambient temperatures were positive correlated factors of exertional heat illnesses (EHI) and exertional heat stroke (EHS) incidence and mortality. Seasonal acclimation, vegetative cover, cool roofs, tree canopy cover, cloud cover, wind speed and shading were inversely related factors of EHI and EHS. Conclusion: According to the results of the study, in order to prevent the increase of heat-related illnesses, it is necessary to consider and strengthen the factors affecting the reduction of the incidence of EHI and EHS, which were identified as negative correlated factors in this study.
Of all-natural disasters, extreme high temperatures events are the main cause of weather-related mortality. The compact urban settings of cities, the dependency on infrastructural systems as well as the larger concentration of people and economic activities make urban areas particularly vulnerable to health risks due to heat. To investigate vulnerabilities to heat, the study illustrates how vulnerability factors together with the hazard and the urban parameters determine the nexus between the heat and the health outcome, here called heat-health nexus. Peer-reviewed articles with no language limitations were searched from the first available record subjected to the imposed selection criteria. First, the information related to the study area were analysed, taking into consideration the level of resolution to investigate the scale of analysis. Then, the specific hazard parameters, divided in simple or combined weather indices, were evaluated. For sensitivity and adaptive capacity aspects, the study considered four distinct categories of determinants: mental and physical health, demographics, social and economic status. Finally, when looking at enhanced exposure, groups of determinants of vulnerability, divided between those describing indoor and outdoor environment conditions were analysed. Results demonstrated a heterogeneous spatial distribution of the identified case studies about heat and health in the urban context and highlighted different characteristics related to climate hazard, exposure, vulnerability and enhanced exposure factors in relation to the health of the population. This literature review demonstrate that a detailed identification of sensitivity, adaptive capacity and enhanced exposure elements is crucial in the implementation of effective adaptation measures in the health context.
Increasing health and wellbeing in cities that experience water scarcity presents challenges, but can be done, say Howard Frumkin and colleagues
Since the publication of the last American Heart Association scientific statement on air pollution and cardiovascular disease in 2010, unequivocal evidence of the causal role of fine particulate matter air pollution (PM2.5, or particulate matter <= 2.5 mu m in diameter) in cardiovascular disease has emerged. There is a compelling case to provide the public with practical personalized approaches to reduce the health effects of PM2.5. Such interventions would be applicable not only to individuals in heavily polluted countries, high-risk or susceptible individuals living in cleaner environments, and microenvironments with higher pollution exposures, but also to those traveling to locations with high levels of PM2.5. The overarching motivation for this document is to summarize the current evidence supporting personal-level strategies to prevent the adverse cardiovascular effects of PM2.5, guide the use of the most proven/viable approaches, obviate the use of ineffective measures, and avoid unwarranted interventions. The significance of this statement relates not only to the global importance of PM2.5, but also to its focus on the most tested interventions and viable approaches directed at particulate matter air pollution. The writing group sought to provide expert consensus opinions on personal-level measures recognizing the current uncertainty and limited evidence base for many interventions. In doing so, the writing group acknowledges that its intent is to assist other agencies charged with protecting public health, without minimizing the personal choice considerations of an individual who may decide to use these interventions in the face of ongoing air pollution exposure.
Urban overheating is documented for more than 400 major cities in the world. Numerous experimental data show that the magnitude of the average temperature increase may exceed 4-5 C, while at the peak may exceed 10 C. Increased ambient temperatures cause a serious impact on the cooling energy consumption, peak electricity demand, heat related mortality and morbidity, urban environmental quality, local vulnerability and comfort. Synergies between urban heat island and heat waves increase further the amplitude of urban overheating The present paper reviews and reports the recent progress and knowledge on the specific impact of current and projected urban overheating in energy, peak electricity demand, air quality, mortality and morbidity and urban vulnerability. In parallel, it discusses new findings related to the characteristics and the magnitude of urban overheating, and reports and analyse the recent knowledge on the synergies between urban heat island and heat waves. (C) 2019 Elsevier B.V. All rights reserved.
Climate change is a worldwide challenge. Its consequences do encompass severe threats not only for the existence and somatic health, but also for the mental health of children and adolescents. Mental health can be impaired by three types of consequences. Direct consequences of climate change, such as natural disasters and indirect consequences, such as loss of land, flight and migration, exposure to violence, change of social, ecological, economic or cultural environment. Moreover, the increasing awareness of the existential dimension of climate change in children and adolescents can influence their well-being or challenge their mental health. Consequences of climate change for somatic health may interact with mental health or have psychological sequelae in children and adolescents. Based on the estimates by the United Nations Intergovernmental Panel on Climate Change, we have summarized current data on these differential pathways as to how climate change affects the mental health of children worldwide through selective literature research on Pubmed. Mental health sequelae of direct and indirect consequences of climate change, increased awareness and physical health problems caused by climate change are presented. We give insights into special vulnerabilities of children and adolescents and identify high-risk groups. As the “Fridays for Future” movement has been initiated in northern Europe, we will discuss these results with a focus on children and adolescents in Europe. The results indicate that climate change is a serious threat to children and adolescent mental health. Children´s rights, mental health and climate change should not continue to be seen as separate points; instead, they need to be brought together to address this major challenge determining the future of our children and their descendants.
To protect public health, heat-related policies are increasingly being adopted by city authorities to address the unequal impact of heatwaves. Ahmedabad’s Heat Action Plan (HAP) is an acclaimed and successful policy response in India and beyond. While the pilot evaluation of the initiative suggests that almost a thousand deaths were avoided annually after its implementation, it is not yet clear whose lives were saved, and to what extent this statistic was due to the HAP, rather than other factors. By reviewing the published and grey literature centering on the HAP target groups, outreach strategies, and impacts on urban services, this paper points out major knowledge gaps concerning the potentials and impacts of the HAP, which may lead to the systematical exclusion of vulnerable and disadvantaged groups from the intended benefits. In this paper, it is argued that the effectiveness and inclusiveness of the HAP predominantly depend on its integration into urban development projects, which is a challenging task given the existing horizontal and vertical fragmentation in the planning of city projects. Moreover, urban plans and policies, including the HAP, are shown to be overly focused on technology, and as a consequence, they do not realize their limited scope in addressing the associated issues, which are fundamentally social, deep, and structural, such as spatial inequality in Indian cities.
In the wake of the SARS-CoV-2 pandemic, the world has woken up to the importance of biosecurity and the need to manage international borders. Yet strong sectorial identities exist within biosecurity that are associated with specific international standards, individual economic interests, specific research communities, and unique stakeholder involvement. Despite considerable research addressing human, animal, plant, and environmental health, the science connections between these sectors remain quite limited. One Biosecurity aims to address these limitations at global, national, and local scales. It is an interdisciplinary approach to biosecurity policy and research that builds on the interconnections between human, animal, plant, and environmental health to effectively prevent and mitigate the impacts of invasive alien species. It provides an integrated perspective to address the many biosecurity risks that transcend the traditional boundaries of health, agriculture, and the environment. Individual invasive alien plant and animal species often have multiple impacts across sectors: as hosts of zoonotic parasites, vectors of pathogens, pests of agriculture or forestry, as well as threats to biodiversity and ecosystem function. It is time these risks were addressed in a systematic way. One Biosecurity is essential to address several major sociological and environmental challenges to biosecurity: climate change, increasing urbanisation, agricultural intensification, human global mobility, loss of technical capability as well as public resistance to pesticides and vaccines. One Biosecurity will require the bringing together of taxonomists, population biologists, modellers, economists, chemists, engineers, and social scientists to engage in a new agenda that is shaped by politics, legislation, and public perceptions.
India is urbanizing at an alarming rate and the impact of climate change is becoming more visible each passing day. The rapid urbanization and climate change have severe direct and indirect consequences, such as increasing poverty, inequality, massive displacement, public health concerns, and challenges of urban governance, among others. This paper identifies some of the most pressing issues faced by urban India in the context of climate change. It also details the interventions undertaken at the local, national, and international levels to counter the effect of the climate change. In addition, it critically evaluates the role of government organizations, especially in terms of undertaking regulatory and planning functions. The paper argues that the implementation of institutional reforms would enable the government to reach out to the private sector to improve urban service delivery. It also provides examples of best practices from India and the world in combating climate change through adaptation and mitigation approaches.
Leptospirosis is a zoonotic and waterborne disease worldwide. It is a neglected, reemerging disease of global public health importance with respect to morbidity and mortality both in humans and animals. Due to negligence, rapid, unplanned urbanization, and poor sanitation, leptospirosis emerges as a leading cause of acute febrile illness in many of the developing countries. Every individual has a risk of getting infected as domestic and wild animals carry leptospires; the at-risk population varies from the healthcare professionals, animal caretakers, farmers and agricultural workers, fishermen, rodent catchers, water sports people, National Disaster Response Force (NDRF) personnel, people who volunteer rescue operations in flood-affected areas, sanitary workers, sewage workers, etc. The clinical manifestations of leptospirosis range from flu-like illness to acute kidney failure (AKF), pneumonia, jaundice, pulmonary hemorrhages, etc. But many rare and uncommon clinical manifestations are being reported worldwide. This review will cover all possible updates in leptospirosis from occurrence, transmission, rare clinical manifestations, diagnosis, treatment, and prophylactic measures that are currently available, their advantages and the future perspectives, elaborately. There are less or very few reviews on leptospirosis in recent years. Thus, this work will serve as background knowledge for the current understanding of leptospirosis for researchers. This will provide a detailed analysis of leptospirosis and also help in finding research gaps and areas to focus on regarding future research perspectives.
This article explores the development of public health infrastructure in George Town, Penang, before the 1930s. It argues that the extreme weather of the tropical climate led to a unique set of health challenges for George Town’s administrators, as the town grew from a small British base to a multi-cultural and thriving port. Weather and public health were (and still are) integrally connected, although the framing of this relationship has undergone significant shifts in thinking and appearance over time. One lens into this association is the situation and expression of these elements within municipal structures. During the nineteenth century, government departments were fewer and shared roles and responsibilities. The Medical Department, for example, observed the weather. making connections between rain. drought and the incidence of disease. Engineers asked critical questions about mortality rates from disease after floods. As ideas about climate and health developed and changed, the shift became evident in the style, concerns and proliferation of governmental departments. This article thus considers the different ways in which weather, public health, and town planning were understood, managed and enacted by the Straits Settlements’ administration until the 1930s. It will start by exploring the situation facing the settlement’s inhabitants, in terms of specific climate and health challenges. It will then consider how these challenges were understood and addressed, why and by whom, and how these elements were repositioned over the period in question.
INTRODUCTION: Scientists from a wide variety of fields of knowledge are increasingly interested in climate change issues. The importance given to the phenomenon is explained by the uncertainties surrounding it and its consequences not yet fully known. However, there is wide agreement that human activities are modifying the Earth’s climate beyond the natural cyclical changes and that these changes impact human health. This scoping review aimed to understand how research on the links between climate change and human health in urban areas is conducted and how this research is approached holistically or not. METHODS AND ANALYSIS: This scoping review is mainly guided by the Arskey and O’Malley scoping review framework. A broad range of databases will be used, including PubMed, ScienceDirect, Web of Science Core Collection, GreenFILE and Information Science & Technology Abstracts. Predefined inclusion and exclusion criteria will be used, with a focus on climate change and human health outcome studies published between January 1990 and July 2019. An interdisciplinary team has formulated search strategies and the reviewers will independently screen eligible studies for final study selection. We will apply a thematic analysis to evaluate and categorise the study findings. We expect to map the research according to the scientific research methods, the scientific fields and the determinants of health studied. Along these lines, we will be able to understand how holistic the research is. ETHICS AND DISSEMINATION: No primary data will be collected since all data presented in this review are based on published articles and publicly available documents. Therefore, ethics committee approval is not a requirement. The findings will be disseminated through publication in a peer-reviewed journal, presentations at conferences relevant to the field of this research, as well as presentations to relevant stakeholders.
The primary needs for climate services in China, in the form of climate information for decision-making, are to better prepare for and manage meteorological-related disasters, adaptation to climate change, and sustainable development. In this paper, the vision, structure, content, and governance of the China Framework for Climate Services, which is designed to respond to these primary needs, is described. This paper reflects on practice, lessons, and experience developing and delivering climate services in China for disaster risk reduction, agriculture, water, energy, urbanization, and major engineering projects. Four key aspects of successful climate services are highlighted: the transition of climate research to operational climate services; delivering relevant, tailored, and usable climate information; effective engagement between users and providers of climate services; and building interdisciplinary professional teams. Key challenges and opportunities for climate services are recognized in this paper: a growing gap between climate science and services capability and societal need, a lack of awareness in user communities of the climate service value for their activities, and the important need for closer and more meaningful interactions between users and providers of climate services. The delivery and uptake of high-quality, relevant, usable, and effective climate services will facilitate climate-smart decisions that will reduce climate risks and improve Chinese societal resilience.
Cities are prone to excess heat, manifesting as urban heat islands (UHIs). UHIs impose a heat penalty upon urban inhabitants that jeopardizes human health and amplifies the escalating effects of background temperature rises and heatwaves, presenting barriers to participation in city life that diminish interaction and activity. This review paper investigates how green infrastructure, passive design and urban planning strategies-herein termed as green infrastructure and design solutions (GIDS)-can be used to cool the urban environment and improve city vitality. A systematic literature review has been undertaken connecting UHIs, city vitality and GIDS to find evidence of how qualities and conditions fundamental to the vitality of the city are diminished by heat, and ways in which these qualities and conditions may be improved through GIDS. This review reveals that comfortable thermal conditions underpin public health and foster activity-a prerequisite for a vital city-and that reducing environmental barriers to participation in urban life enhances physical and mental health as well as activity. This review finds that GIDS manage urban energy flows to reduce the development of excess urban heat and thus improve the environmental quality of urban spaces. Furthermore, it finds that the most equitable approach to urban cooling is one that reduces the intensity of the meso-scale UHI that affects all urban inhabitants. Subsequently, a cooler urban fabric based on GIDS is proposed. A cohesive approach to the widespread adoption of GIDS shows potential to produce a cooler urban fabric that is human-centered in its function and aesthetic to enhance participation in public life and stimulate life on the streets. Four spatial scales are presented in which a combination of GIDS may be collectively implemented to reduce the meso-scale UHI, including the urban, intra-urban, building and body scales. This approach considers the interacting nature of GIDS applied within contrasting urban landscapes, and aims to produce cooler urban conditions, better walking environments, and ecosystem co-benefits to stimulate participation in physical activity and public life to underpin public health, productivity and livelihoods, thereby inducing city vitality.
Urban vegetation provides undeniable benefits to urban climate, health, thermal comfort and environmental quality of cities and represents one of the most considered urban heat mitigation measures. Despite the plethora of available scientific information, very little is known about the holistic and global impact of a potential increase of urban green infrastructure (GI) on urban climate, environmental quality and health, and their synergies and trade-offs. There is a need to evaluate globally the extent to which additional GI provides benefits and quantify the problems arising from the deployment of additional greenery in cities which are usually overlooked or neglected. The present paper has reviewed and analysed 55 fully evaluated scenarios and case studies investigating the impact of additional GI on urban temperature, air pollution and health for 39 cities. Statistically significant correlations between the percentage increase of the urban GI and the peak daily and night ambient temperatures are obtained. The average maximum peak daily and night-time temperature drop may not exceed 1.8 and 2.3 degrees C respectively, even for a maximum GI fraction. In parallel, a statistically significant correlation between the peak daily temperature decrease caused by higher GI fractions and heat-related mortality is found. When the peak daily temperature drops by 0.1 degrees C, then the percentage of heat-related mortality decreases on average by 3.0% The impact of additional urban GI on the concentration of urban pollutants is analysed, and the main parameters contributing to decrease or increase of the pollutants’ concentration are presented.
Since air pollutants are difficult and expensive to control, a strong scientific underpinning to policies is needed to guide mitigation aimed at reducing the current burden on public health. Much of the evidence concerning hazard identification and risk quantification related to air pollution comes from epidemiological studies. This must be reinforced with mechanistic confirmation to infer causality. In this review we focus on data generated from four contrasting sources of particulate air pollution that result in high population exposures and thus where there remains an unmet need to protect health: urban air pollution in developing megacities, household biomass combustion, wildfires and desert dust storms. Taking each in turn, appropriate measures to protect populations will involve advocating smart cities and addressing economic and behavioural barriers to sustained adoption of clean stoves and fuels. Like all natural hazards, wildfires and dust storms are a feature of the landscape that cannot be removed. However, many efforts from emission containment (land/fire management practices), exposure avoidance and identifying susceptible populations can be taken to prepare for air pollution episodes and ensure people are out of harm’s way when conditions are life-threatening. Communities residing in areas affected by unhealthy concentrations of any airborne particles will benefit from optimum communication via public awareness campaigns, designed to empower people to modify behaviour in a way that improves their health as well as the quality of the air they breathe.
In 2010, the American Heart Association published a statement concluding that the existing scientific evidence was consistent with a causal relationship between exposure to fine particulate matter and cardiovascular morbidity and mortality, and that fine particulate matter exposure is a modifiable cardiovascular risk factor. Since the publication of that statement, evidence linking air pollution exposure to cardiovascular health has continued to accumulate and the biological processes underlying these effects have become better understood. This increasingly persuasive evidence necessitates policies to reduce harmful exposures and the need to act even as the scientific evidence base continues to evolve. Policy options to mitigate the adverse health impacts of air pollutants must include the reduction of emissions through action on air quality, vehicle emissions, and renewable portfolio standards, taking into account racial, ethnic, and economic inequality in air pollutant exposure. Policy interventions to improve air quality can also be in alignment with policies that benefit community and transportation infrastructure, sustainable food systems, reduction in climate forcing agents, and reduction in wildfires. The health care sector has a leadership role in adopting policies to contribute to improved environmental air quality as well. There is also potentially significant private sector leadership and industry innovation occurring in the absence of and in addition to public policy action, demonstrating the important role of public-private partnerships. In addition to supporting education and research in this area, the American Heart Association has an important leadership role to encourage and support public policies, private sector innovation, and public-private partnerships to reduce the adverse impact of air pollution on current and future cardiovascular health in the United States.
Climate change and disaster risk are serious concerns considering the vulnerability of coastal areas and cities to various climate-disaster threats. Hence, the urban populace and planning stakeholders are grappling with the challenges of seeking ways to integrate adaptation measures into human livelihoods and planning systems. However, the synergy between climate change adaptation (CCA) and disaster risk reduction (DRR) remains fragmented and vague. Therefore, this review highlighted recent theoretical and practical methodologies for sustainable planning outcomes in relation to CCA and DRR themes. This paper provides a new model, Problem analysis model (PAM), designed to analyse Origin-Cause-Effect (impacts)-Risks identification and Answers to climate-related disaster at the local or community level. Lastly, three identified enablers were extensively discussed (policy, programme and practice) as a step towards the model implementation and to improve sustainable planning outcomes.
The preliminary determination of the article is to investigate the effects of pollution and climate change. In this regard, the authors want to highlight that this real and critical issue must take seriously because each of us contributes to pollution and climate change, which is very real, and which will be aggravated by not taking action. Global warming currently involves two major problems for humanity: on the one hand, the need to dramatically diminish greenhouse gas emissions to stabilize the concentration of these gases in the atmosphere to prevent anthropogenic influence on the climate system and enable ecosystems, contrastingly the need to accommodate to the consequence of climate change, given that these effects are already visible and inevitable due to the activity of the climate system, regardless of the outcome of emission reduction actions. The main problem with pollution is air quality, which has fallen considerably, especially in urban areas. The” World Health Organization” approximates, more than seven million people die each year from air pollution. The authors also conducted a case study on the local effects of climate change – Timisoara and its peri-urban area. Therefore, we concluded that if Timisoara is successful in reducing greenhouse gas emissions, this will create a test market for Romania’s ecological technologies and help the environmental industries to locate in Timisoara.
As the world deals with COVID-19, there is increasing attention to the threat of emerging and re-emerging infectious diseases. India is especially vulnerable to climate-induced health risks and a hotspot for infectious diseases. In this study we use a scoping review to synthesize evidence on the impact of climate on infectious diseases. We use this to uncover gaps and understand the implications for policymaking and health system preparedness. There is a strong evidence base linking climate change to disease outbreaks, both directly and indirectly. Socio-economic factors are the modifiers that determine disease severity in different populations and locations.
Heat-related mortality is one of the leading causes of weather-related deaths in the United States. With changing climates and an aging population, effective adaptive strategies to address public health and environmental justice issues associated with extreme heat will be increasingly important. One effective adaptive strategy for reducing heat-related mortality is increasing tree cover. Designing such a strategy requires decision-support tools that provide spatial and temporal information about impacts. We apply such a tool to estimate spatially and temporally explicit reductions in temperature and mortality associated with a 10% increase in tree cover in 10 U.S. cities with varying climatic, demographic, and land cover conditions. Two heat metrics were applied to represent tree impacts on moderately and extremely hot days (relative to historical conditions). Increasing tree cover by 10% reduced estimated heat-related mortality in cities significantly, with total impacts generally greatest in the most populated cities. Mortality reductions vary widely across cities, ranging from approximately 50 fewer deaths in Salt Lake City to about 3800 fewer deaths in New York City. This variation is due to differences in demographics, land cover, and local climatic conditions. In terms of per capita estimated impacts, hotter and drier cities experience higher percentage reductions in mortality due to increased tree cover across the season. Phoenix potentially benefits the most from increased tree cover, with an estimated 22% reduction in mortality from baseline levels. In cooler cities such as Minneapolis, trees can reduce mortality significantly on days that are extremely hot relative to historical conditions and therefore help mitigate impacts during heat wave conditions. Recent studies project highest increases in heat-related mortality in the cooler cities, so our findings have important implications for adaptation planning. Our estimated spatial and temporal distributions of mortality reductions for each city provide crucial information needed for promoting environmental justice and equity. More broadly, the methods and model can be applied by both urban planners and the public health community for designing targeted, effective policies to reduce heat-related mortality. Additionally, land use managers can use this information to optimize tree plantings. Public stakeholders can also use these impact estimates for advocacy.
Featured Application The data and analysis can be applied to shipping emissions issues at five governmental levels: local (ports and port cities), subnational regional (port authorities), national (Italy and other countries), international regional (European Union and Mediterranean Sea coastal areas), and global (IMO). Ships’ emissions of air pollutants pose problems for local and regional public health and agricultural production, as well as global climate change. The Italian government’s endorsement in 2019 of the creation of a Mediterranean Emission Control Area is a reflection of increasing concern about the emissions. Also, ongoing developments in the International Maritime Organization and in the European Union add to the Italian government’s maritime shipping agenda and increase its complexity and uncertainty. In that context, this review paper addresses two central questions: What are the consequences for human health and agricultural production of ships’ emissions in Italian ports and coastal areas? How can their emissions be reduced? The approach to these questions is inter-disciplinary. It applies the results of studies in atmospheric chemistry and physics; maritime shipping engineering; public health; agriculture; economics; and international law and policymaking to assess current and prospective policy issues in Italy. The principal conclusions are that: (1) Black carbon emissions are threats to human health and agricultural production in Italy, as well as to the global climate. (2) It is important that black carbon emissions receive more serious attention in policymaking processes in order to reflect the significant analytic progress that has been made in terms of understanding the problems it poses and the technological and policy solutions. (3) There are cost-effective, emission-reducing measures that are readily available, as well as other measures needing more time before full-scale implementation. (4) Although existing multi-level governance systems pose complex analytic and policymaking challenges, they also offer opportunities to institute new policies with significant short-term and long-term co-benefits from reductions in emissions.
Approximately 1 billion people currently live in informal settlements, primarily in urban areas in low- and middle-income countries. Informal settlements are defined by poor-quality houses or shacks built outside formal laws and regulations. Most informal settlements lack piped water or adequate provision for sanitation, drainage, and public services. Many are on dangerous sites because their inhabitants have a higher chance of avoiding eviction. This paper considers how to build resilience to the impacts of climate change in informal settlements. It focuses on informal settlements in cities in low- and middle-income countries and how these concentrate at-risk populations. This paper also reviews what is being done to address climate resilience in informal settlements. In particular, community- and city-government-led measures to upgrade settlements can enhance resilience to climate-change risks and serve vulnerable groups. It also discusses how the barriers to greater scale and effectiveness can be overcome, including with synergies with the Sustainable Development Goals.
A city’s climate is affected both by global warming and the local factors such as built form and the landscape. The temperature related impacts of climate change make urban areas more vulnerable particularly due to higher population concentration as well as heat island effect. Cities in India are already experiencing enhanced temperature and precipitation related impacts of climate change and extreme events, e.g., >2 degrees C warming in some places. This study describes a case of Ahmedabad a city of around 5 million people (Census, 2011) and currently almost 7.8 million, located in the hot and humid western part of India to understand the current temperature-related mortality impacts and the role of land use. Satellite images (MODIS from NASA), temperature data from India Meteorological Department (IMD) and daily all-cause mortality from Ahmedabad Municipal Corporation between 2001 and 2015 have been used to create a distributed lag non-linear model. Using land surface temperature for mortality risk assessment gives significantly different results as compared to using air temperature for mortality risk assessment. This indicates impacts of localized temperature variations on mortality risks. Thus, the microclimate in a city as represented by land surface temperatures is a better indicator for estimating relative risk of temperature related mortality as compared to air temperature. The study also infers that with increase in built-up spaces by 1% in the land use mix, the relative risk of heat related mortality increases by 0.59 points at 40 degrees C and by 0.78 points at 45 degrees C.
The urban heat island is a representative urban climate characteristic, which can affect heat-stress conditions and extreme precipitation that are closely connected with human life. Better understanding of urban-climate interactions, therefore, is crucial to ultimately support better planning and adaptation in various application fields. This study assesses urban-climate interactions during summer for eastern North America using regional climate model simulations at 0.22° resolution. Two regional climate model experiments, with and without realistic representation of urban regions, are performed for the 1981–2010 period. Comparison of the two experiments shows higher mean temperatures and reduced mean precipitation in the simulation with realistic urban representation, which can be attributed primarily to reduced albedo and soil moisture for the urban regions in this simulation. Furthermore, the mean temperature and precipitation in the simulation with improved urban representation is also closer to that observed. Analysis of short-duration precipitation extremes for climatologically different sub-regions, however, suggests that, for higher temperatures, the magnitudes of precipitation extremes are generally higher in the simulation with realistic urban representation, particularly for coastal urban regions, and are collocated with higher values of convective available potential energy and cloud fraction. Enhanced sea and lake breezes associated with lower sea level pressure found around these regions, contribute additional water vapor and further enhance dynamic convective development, leading to higher precipitation intensities. Analysis of temperature extremes clearly demonstrates that urban regions experience aggravated heat-stress conditions due to relatively higher temperatures despite reduced relative humidity. Double the number of extreme heat spells lasting six or more days are noted for the coastal urban regions in the study domain. This study, in addition to demonstrating the differences in urban-climate interactions for climatologically different regions, also demonstrates the need for better representation of urban regions in climate models to generate realistic climate information.
Climate change and urbanization are converging to challenge the flood control in the Pearl River Delta (PRD) due to their adverse impacts on precipitation extremes and the urban areas environment. Previous studies have investigated temporal changes in flood risk with various single factor, few have considered the joint effects of climate change, urbanization and socio-economic development. Here, based on the representative concentration pathway (RCP) scenarios, we conducted a comprehensive assessment of future (2030-2050) flood risk over the PRD combined with a thorough investigation of climate change, urbanization and socio-economic development. Precipitation extremes were projected using the regional climate model RegCM4.6, and urbanization growth was projected based on the CA-Markov model. The economic and population development was estimated by the shared socio-economic pathways (SSPs). Flood risk mapping with different RCPs-urbanization-SSPs scenarios was developed for the PRD based on the set pair analyze theory. The results show that climate change and urbanization are expected to exacerbate flood risk in most parts of the PRD during the next few decades, concurrently with more intense extreme precipitation events. The high flood risk areas are projected mainly in the urban regions with unfavorable terrain and dense population. The highest flood risk areas are expected to increase by 8.72% and 19.80% under RCP4.5 and RCP8.5 scenarios, respectively. Reducing greenhouse gas emissions may effectively mitigate the flood risk over the PRD. This study highlight the links between flood risk and changing environment, suggesting that flood risk management and preventative actions should be included in regional adaptation strategies.
BACKGROUNDS: Studies on the association between ambient temperature and human mortality have been widely reported, focusing on common diseases such as cardiopulmonary diseases. However, multi-city studies on the association between both high and low temperatures and mortality of nervous system diseases were scarce, especially on the evidence of vulnerable populations. METHODS: Weekly meteorological data, air pollution data and mortality data of nervous system were collected in 5 cities in China. A quasi-Poisson regression with distributed lag non-linear model (DLNM) was applied to quantify the association between extreme temperatures and mortality of nervous system diseases. Multivariate meta-analysis was applied to estimate the pooled effects at the overall levels. The attributable fractions (AFs) were calculated to assess the mortality burden attributable to both high and low temperatures. Stratified analyses were also performed by gender and age-groups through the above steps. RESULTS: A total of 12,132 deaths of nervous system diseases were collected in our study. The overall minimum mortality temperature was 23.9 °C (61.9th), the cumulative relative risks of extreme heat and cold for nervous system diseases were 1.33(95%CI: 1.10, 1.61) and 1.47(95%CI: 1.27, 1.71). The mortality burden attributed to non-optimal temperatures accounted for 29.54% (95%eCI: 13.45%, 40.52%), of which the mortality burden caused by low temperature and high temperature accounted for 25.89% (95%eCI: 13.03%, 34.36%) and 3.65% (95%eCI: 0.42%, 6.17%), respectively. The mortality burden attributable to ambient temperature was higher in both males and the elderly (>74 years old), with the AF of 31.85% (95%eCI: 20.68%, 39.88%) and 31.14% (95%eCI: -6.83%, 49.51%), respectively. CONCLUSIONS: The non-optimal temperature can increase the mortality of nervous system diseases and the males and the elderly over 74 years have the highest attributable burden. The findings add the evidence of vulnerable populations of nervous system diseases against ambient temperatures.
(1) Background: The health effect of temperature has become a rising public health topic. The objective of this study is to assess the association between apparent temperature and non-accidental deaths, and the mortality burden attributed to cold and heat temperature; (2) Methods: The daily data on temperature and deaths were collected from 10 cities in Thailand, Korea and China. We fitted a time-series regression with a distributed lag nonlinear model (DLNM) to derive the health risk of temperature for each city and then pooled them to get the overall cumulative risk by multivariate meta-analysis. Additionally, we calculated the attributable fraction of deaths for heat and cold, which was defined as temperatures above and below minimum-mortality temperature (MMT); (3) Results: There are regional heterogeneities in the minimum mortality percentiles (MMP) and attributable fractions for different countries. The MMP varied from about the 5-10th percentile in Thailand to 63-93rd percentile in China and Korea. The attributable fractions of the total deaths due to short-term exposure to temperature in Asia is 7.62%, of which the cold effect (6.44%) is much higher than the heat effect (1.18%); (4) Conclusions: Our study suggested that apparent temperature was associated with an increase in non-accidental mortality. Most of the temperature-related mortality burden was attributable to cold, except for Thailand.
Research on climate change mitigation and adaptation is pressing in order to understand its implications and risks in different urban areas. It is especially critical for those who face high degrees of urban inequality in the context of an uneven state presence. This paper is an explorative and investigative study which uses Cairo as a case. The focus of the study is on mapping state and private sector efforts in mitigating climate change issues, specifically for vulnerable groups who have limited access to public services. The study adopted an investigative approach where a literature search and bibliometric mapping were used to identify the gap in knowledge in the field of architecture and urban climate change mitigation and adaptation, followed by a field survey which included conducting interviews and questionnaires with different stakeholders from the public and private sector to investigate the link between the efforts for climate change mitigation. The explorative part of the study concluded that there is a huge knowledge gap in the Middle East and in Egypt when it comes to research efforts related to climate change with a focus on the built environment. The results of the investigative part of this study revealed that-apart from already limited efforts on ground-there is no synchronization in efforts between the public and private sector. Climate change issues are still not a priority when poverty, economy, and health are still a prime concern and take precedence over climate change. There is uneven presence of public efforts for climate change adaptation and mitigation. The efforts that do exist in the public sphere are self-help unorganized work (efforts) conducted by the civil society.
The association between meteorological factors and infectious diarrhea has been widely studied in many countries. However, investigation among children under 5 years old in Jiangsu, China remains quite limited. Data including infectious diarrhea cases among children under five years old and daily meteorological indexes in Jiangsu, China from 2015 to 2019 were collected. The lag-effects up to 21 days of daily maximum temperature (Tmax) on infectious diarrhea were explored using a quasi-Poisson regression with a distributed lag non-linear model (DLNM) approach. The cases number of infectious diarrhea was significantly associated with seasonal variation of meteorological factors, and the burden of disease mainly occurred among children aged 0-2 years old. Moreover, when the reference value was set at 16.7°C, Tmax had a significant lag-effect on cases of infectious diarrhea among children under 5 years old in Jiangsu Province, which was increased remarkably in cold weather with the highest risk at 8°C. The results of DLNM analysis implicated that the lag-effect of Tmax varied among the 13 cities in Jiangsu and had significant differences in 8 cities. The highest risk of Tmax was presented at 5 lag days in Huaian with a maximum RR of 1.18 (95% CI: 1.09, 1.29). Suzhou which had the highest number of diarrhea cases (15830 cases), had a maximum RR of 1.04 (95% CI:1.03, 1.05) on lag 15 days. Tmax is a considerable indicator to predict the epidemic of infectious diarrhea among 13 cities in Jiangsu, which reminds us that in cold seasons, more preventive strategies and measures should be done to prevent infectious diarrhea.
Compositional and contextual characteristics of a place capture the collective fnancial, physical, human, and social capital of an area and its ability to prevent, plan for, and recover from severe weather events. Research that examines the compositional and contextual characteristics of places with elevated food risk is largely limited to urban-centric analyses and case studies. However, rural areas of the USA are not immune to fooding. In this paper, we integrate social and physical data to identify the social correlates of food risk and determine if and how they vary across the rural–urban continuum for all census tracts in the coterminous USA. Our results show that risk of fooding is higher in rural tracts, in tracts with larger relative shares of socioeconomically vulnerable populations, and in tracts reliant on food-vulnerable industries. We also show that compositional social correlates of fooding are not consistent across rural–urban areas. This work widens the scope of discourse on fooding to attend to the heterogeneity of social correlates and the implications for policy and future research.
Small-scale flash flood events are climate-related disasters which can put multiple aspects of the system at risk. The consequences of flash floods in densely populated cities are increasingly becoming problematic around the globe. However, they are largely ignored in disaster impact assessment studies, especially in assessing socioeconomic loss and damage, which can provide a significant insight for disaster risk reduction measures. Using a structured questionnaire survey, this study applied a statistical approach and developed a structural equation model (SEM) for assessing several socioeconomic dimensions including physical impacts, mobility disruption, lifeline facilities, health and income-related impacts. The study reveals that respondents have experienced a stronger impact on direct tangible elements such as household contents and buildings as well as direct intangible elements with ? coefficients 0.703, 0.576 and 0.635, respectively, at p?
BACKGROUND: Ambient temperature observations from single monitoring stations (usually located at the major international airport serving a city) are routinely used to estimate heat exposures in epidemiologic studies. This method of exposure assessment does not account for potential spatial variability in ambient temperature. In environmental health research, there is increasing interest in utilizing spatially-resolved exposure estimates to minimize exposure measurement error. METHODS: We conducted time-series analyses to investigate short-term associations between daily temperature metrics and emergency department (ED) visits for well-established heat-related morbidities in five US cities that represent different climatic regions: Atlanta, Los Angeles, Phoenix, Salt Lake City, and San Francisco. In addition to airport monitoring stations, we derived several exposure estimates for each city using a national meteorology data product (Daymet) available at 1?km spatial resolution. RESULTS: Across cities, we found positive associations between same-day temperature (maximum or minimum) and ED visits for heat-sensitive outcomes, including acute renal injury and fluid and electrolyte imbalance. We also found that exposure assessment methods accounting for spatial variability in temperature and at-risk population size often resulted in stronger relative risk estimates compared to the use of observations at airports. This pattern was most apparent when examining daily minimum temperature and in cities where the major airport is located further away from the urban center. CONCLUSION: Epidemiologic studies based on single monitoring stations may underestimate the effect of temperature on morbidity when the station is less representative of the exposure of the at-risk population.
Understanding and improving the public risk perception have become an important element in the management of flood risk. In China, the risk government is of so-called nationwide catastrophe response mode which is different from the widely adopted “bottom up” risk governance mode in the Western countries. Such a particular mode may make Chinese people perceive risk in a different way from people in other countries. Hence, a further discussion of risk perception is of great value in China. ?This paper presents a case study on the public perception of flood hazard and flood risk in a city prone to floods. The relationship between risk perception and exposure was examined by spatial analysis. Meanwhile, inferential testing with chi-squared tests was undertaken regarding experience, social trust, and protective behaviors. Our results suggest that (1) the relationship between exposure and risk perception of people in Nanjing is positive and statistically significant, (2) flood experience was strongly related to risk perception, (3) trust showed a significant relationship to risk perception, and (4) people who have perceived the probability of floods and associated loss of life have a higher willingness to take more protective measures. These findings will help local government to develop effective flood risk communication strategies for improving public awareness creation, emergency response and preparedness.
Increasing urban heat island and global warming have aroused serious thermal environmental problems and even harm people’s thermal health. Because of the importance in people’s daily life, a commercial pedestrianized block represents a symbol of a city or metropolis; therefore, focusing the attention on the thermal environment in such regions is very necessary. Most of the researches on the urban thermal environment are calculated by remote sensing data; limited by the low spatial resolution of remote sensing image, it may not obviously reflect the true thermal environment of the research site, especially in some microscale regions. Based on this, the new software ENVI-met is developed to research the thermal environment and forecast people’s thermal sensation in a microscale region. Therefore, the objective of this study aims at conducting field measurement and numerical simulation to assess the thermal environment of a typical commercial pedestrianized space in southern China and assess the different urban design parameters in ameliorating the urban heat island effect. Our final results demonstrate a quantitative evidence for establishing a comprehensive standard for improving the thermal environment in a microscale region, and this study also can be a supplementary in the research field about improving thermal health.
Epidemiological studies have suggested an association between particulate air pollution, increased temperatures, and morbidity related to pregnancy outcomes. However, the roles of desert dust storms and climatological factors have not been fully addressed. The objectives of the present study were to investigate the association between desert dust storms, particulate matter with a diameter ?10 ?m (PM(10)), daily temperatures, and toxemia of pregnancy and spontaneous abortion in Gaziantep, South East Turkey. The study was conducted retrospectively at emergency department of two hospitals in Gaziantep city. Data from January 1, 2009, to March 31, 2014, were collected. Patients, who were diagnosed with toxemia of pregnancy and spontaneous abortion by radiological imaging modalities, were included in the study. Daily temperature ranges, mean temperature values, humidity, pressure, wind speed, daily PM10 levels, and records of dust storms were collected. A generalized additive regression model was designed to assess variable effects on toxemia of pregnancy and spontaneous abortion, while adjusting for possible confounding factors. Our findings demonstrated that presence of dust storms was positively associated with the toxemia of pregnancy both in outpatient admissions (OR=1.543 95% CI=1.186-2.009) and inpatient hospitalizations (OR=1.534; 95% CI=1.162-2.027). However, neither PM(10) nor maximum temperature showed a marked association with spontaneous abortion or toxemia of pregnancy in our study population. Our findings suggest that desert dust storms may have an impact on the risk for adverse pregnancy outcomes such as toxemia of pregnancy. Health authorities should take necessary measures to protect pregnant women against detrimental effects of these storms.
This study evaluated the effect of extreme temperatures on events requiring emergency room visits (ERVs) for hypertensive disease, ischemic heart disease (IHD), cerebrovascular disease, and chronic kidney disease (CKD) for population stratified by sex and age living in Taiwan’s metropolitan city from 2000 to 2014. The distributed lag non-linear model was adopted to examine the association between ambient temperature and area-age-sex-disease-specific ERVs for a population aged 40 years and above. The reference temperature was defined by a percentile value to describe the temperature in each city. Area-age-sex-disease-specific relative risk (RR) and 95% confidence intervals (CI) were estimated in association with extreme high (99th percentile) and low (5th percentile) temperatures. Temperature-related ERV risks varied by area, age, sex, and disease. Patients with CKD tend to have comorbidities with hypertensive disease. All study populations with hypertensive disease have significant risk associations with extreme low temperatures with the highest RR of 2.64 (95% CI: 2.08, 3.36) appearing in New Taipei City. The risk of IHD was significantly associated with extreme high temperature for male subpopulation aged 40-64 years. A less significant association was observed between the risks of cerebrovascular disease with extreme temperature. The risk of CKD was most significantly associated with extreme high temperature especially for a subpopulation aged 40-64 years. All study subpopulations with hypertensive disease have significant risk associations with extreme low temperature. Male subpopulations were more vulnerable to extreme temperatures, especially for those aged 40-64 years.
This study evaluated the effect of extreme temperatures on events requiring emergency room visits (ERVs) for hypertensive disease, ischemic heart disease (IHD), cerebrovascular disease, and chronic kidney disease (CKD) for population stratified by sex and age living in Taiwan’s metropolitan city from 2000 to 2014. The distributed lag non-linear model was adopted to examine the association between ambient temperature and area-age-sex-disease-specific ERVs for a population aged 40 years and above. The reference temperature was defined by a percentile value to describe the temperature in each city. Area-age-sex-disease-specific relative risk (RR) and 95% confidence intervals (CI) were estimated in association with extreme high (99th percentile) and low (5th percentile) temperatures. Temperature-related ERV risks varied by area, age, sex, and disease. Patients with CKD tend to have comorbidities with hypertensive disease. All study populations with hypertensive disease have significant risk associations with extreme low temperatures with the highest RR of 2.64 (95% CI: 2.08, 3.36) appearing in New Taipei City. The risk of IHD was significantly associated with extreme high temperature for male subpopulation aged 40-64 years. A less significant association was observed between the risks of cerebrovascular disease with extreme temperature. The risk of CKD was most significantly associated with extreme high temperature especially for a subpopulation aged 40-64 years. All study subpopulations with hypertensive disease have significant risk associations with extreme low temperature. Male subpopulations were more vulnerable to extreme temperatures, especially for those aged 40-64 years.
The Paris Agreement has prompted much interest in the societal and health impacts of limiting global warming to 1.5 degrees C and 2 degrees C. Previous assessments of differential impacts of two targets indicate that 1.5 degrees C warming target would substantially reduce the impact on human health compared to 2 degrees C, but they mainly focused on the magnitude of temperature changes under future climate change scenarios without any consideration of greater frequency of cumulative heat exposures within a day. Here we quantified the health risks of compound daytime and night-time hot extremes using morbidity data in a megacity of China, and also identified the time-period of heat exposure with higher risks. Then we projected future morbidity burden attributable to compound hot extremes due to the half-degree warming. We estimated that the 2 degrees C warming scenario by 2100 as opposed to 1.5 degrees C would increase annual heat-related ambulance dispatches by 31% in Shenzhen city. Substantial additional impacts were associated with occurrence of consecutive hot days and nights, with ambulance dispatches increased by 82%. Our results suggested that compound hot extremes should be considered in assessment of heat-related health impacts, particularly in the context of climate change. Minimizing the warming of climate in a more ambitious target can significantly reduce the health damage.
The human population is increasing. The ongoing urbanization process, in conjunction with climate change, is causing larger environmental footprints. Consequently, quality of life in urban systems worldwide is under immense pressure. Here, the seasonal characteristics of Maribor’s urban thermal environment were studied from the perspectives of surface urban heat island (SUHI) and urban heat island (UHI) A remote sensing thermal imagery time series and in-situ measurements (stationary and mobile) were combined with select geospatial predictor variables to model this atmospheric phenomenon in its most intensive season (summer). Finally, CMIP6 climate change scenarios and models were considered, to predict future UHI intensity. Results indicate that Maribor’s UHI intensity maximum shifted from winter to spring and summer. The implemented generalized additive model (GAM) underestimates UHI intensity in some built-up parts of the study area and overestimates UHI intensity in green vegetated areas. However, by the end of the century, UHI magnitude could increase by more than 60% in the southern industrial part of the city. Such studies are of particular concern, in regards to the increasing frequency of heat waves due to climate change, which further increases the (already present) heat stress in cities across the globe.
The impact of extreme weather conditions on humans is one of the most important topics in biometeorology studies. The main objective of this study is to analyze the relationship between temperature-related weather conditions and natural mortality in the five most populated cities of Romania, namely, Bucharest, Cluj-Napoca, Constan?a, Ia?i, and Timi?oara. The results of this study aim to bridge a gap in national research. In the present paper, we used daily natural mortality data and daily minimum and maximum air temperatures. The distributed lag nonlinear model (DLNM) allowed us to identify weather conditions associated with natural mortality. The most important results are as follows: (i) a higher daily mortality is related to a high frequency of heat stress conditions; (ii) a higher maximum temperature increases the relative risk (RR) of natural mortality; (iii) the maximum number of fatalities is recorded on the first day of high-temperature events; and (iv) individuals much more easily adapt to cold stress conditions. The main conclusion in this study is that the inhabitants of the most populated cities in Romania are more sensitive to high-temperature stress than to low-temperature stress.
Urban Heat Island (UHI) is posing a significant challenge due to growing urbanisations across the world. Green infrastructure (GI) is popularly used for mitigating the impact of UHI, but knowledge on their optimal use is yet evolving. The UHI effect for large cities have received substantial attention previously. However, the corresponding effect is mostly unknown for towns, where appreciable parts of the population live, in Europe and elsewhere. Therefore, we analysed the possible impact of three vegetation types on UHI under numerous scenarios: baseline/current GI cover (BGI); hypothetical scenario without GI cover (HGI-No); three alternative hypothetical scenarios considering maximum green roofs (HGR-Max), grasslands (HG-Max) and trees (HT-Max) using a dispersion model ADMS-Temperature and Humidity model (ADMS-TH), taking a UK town (Guildford) as a case study area. Differences in an ambient temperature between three different landforms (central urban area, an urban park, and suburban residential area) were also explored. Under all scenarios, the night-time (0200 h; local time) showed a higher temperature increase, up to 1.315 °C due to the lowest atmospheric temperature. The highest average temperature perturbation (change in ambient temperature) was 0.563 °C under HGI-No scenario, followed by HG-Max (0.400 °C), BGI (0.343 °C), HGR-Max (0.326 °C) and HT-Max (0.277 °C). Furthermore, the central urban area experienced a 0.371 °C and 0.401 °C higher ambient temperature compared with its nearby suburban residential area and urban park, respectively. The results allow to conclude that temperature perturbations in urban environments are highly dependent on the type of GI, anthropogenic heat sources (buildings and vehicles) and the percentage of land covered by GI. Among all other forms of GI, trees were the best-suited GI which can play a viable role in reducing the UHI. Green roofs can act as an additional mitigation measure for the reduction of UHI at city scale if large areas are covered.
Some studies have demonstrated that precipitation is an important risk factor of dengue epidemics. However, current studies mostly focused on a single precipitation variable, and few studies focused on the impact of precipitation patterns on dengue epidemics. This study aims to explore optimal precipitation patterns for dengue epidemics. Weekly dengue case counts and meteorological data from 2006 to 2018 in Guangzhou of China were collected. A generalized additive model with Poisson distribution was used to investigate the association between precipitation patterns and dengue. Precipitation patterns were defined as the combinations of three weekly precipitation variables: accumulative precipitation (Pre_A), the number of days with light or moderate precipitation (Pre_LMD), and the coefficient of precipitation variation (Pre_CV). We explored to identify optimal precipitation patterns for dengue epidemics. With a lead time of 10 weeks, minimum temperature, relative humidity, Pre_A, and Pre_LMD were positively associated with dengue, while Pre_CV was negatively associated with dengue. A precipitation pattern with Pre_A of 20.67-55.50 mm per week, Pre_LMD of 3-4 days per week, and Pre_CV less than 1.41 per week might be an optimal precipitation pattern for dengue epidemics in Guangzhou. The finding may be used for climate-smart early warning and decision-making of dengue prevention and control.
Poverty and discrimination compound vulnerability to disasters. Yet, people who experience these are some of the least involved groups in Disaster Risk Reduction (DRR) dialogue and research. This study aims to fill that gap by narrating the lived experience of underprivileged flood-affected communities. We conducted in-depth interviews (N = 48) with community members (n = 36) and staff members of collaborating non-governmental organisations (n = 12). We also conducted focus group discussions with staff members of the same NGOs. The results describe how systemic issues entrenched with socio-economic and cultural factors impact a community?s ability to prepare for floods. These communities received no warning or timely evacuation messages, and perceived the received support as inadequate and unfair. Communities recovered through their resourcefulness and thoughtfulness. They resented the government for its lack of action throughout the disaster cycle. Priorities for future efforts involve actively engaging these vulnerable groups and tailoring DRR activities for them.
Urban air pollution can have negative short- and long-term impacts on health, including cardiovascular, neurological, immune system and developmental damage. The irritant qualities of pollutants such as ozone (O(3)), nitrogen dioxide (NO(2)) and particulate matter (PM) can cause respiratory and cardiovascular distress, which can be heightened during physical activity and particularly so for those with respiratory conditions such as asthma. Previously, research has only examined marathon run outcomes or running under laboratory settings. This study focuses on elite 5-km athletes performing in international events at nine locations. Local meteorological and air quality data are used in conjunction with race performance metrics from the Diamond League Athletics series to determine the extent to which elite competitors are influenced during maximal sustained efforts in real-world conditions. The findings from this study suggest that local meteorological variables (temperature, wind speed and relative humidity) and air quality (ozone and particulate matter) have an impact on athletic performance. Variation between finishing times at different race locations can also be explained by the local meteorology and air quality conditions seen during races.
Culex mosquitoes are important vectors of West Nile Virus (WNV), St. Louis Encephalitis Virus (SLEV) and Japanese Encephalitis Virus (JEV). Climate change is expected to alter their ability to spread diseases in human populations. Studies examining the influence of climate variability on Culex mosquitoes in South East Asia are scarce. We examined the influence of climate variability on reported Culex mosquito larval habitats from 2009 to 2018 in Singapore. We analysed the non-linear immediate and lagged weather dependence of Culex habitats over 5 weeks in negative binomial regression models using nationally representative data. We adjusted for the effects of long-term trend, seasonality, public holidays and autocorrelation. There were 41,170 reported Culex larval habitats over the study period. Non-residential premises were associated with more reports of habitats compared to residential premises [Rate Ratio (RR): 113.9, 95% CI: 110.9, 116.9]. Larvae in more than 90% of these habitats were entomologically identified as Culex quinquefasciatus. In residences, every 10 mm increase in rainfall above a 90 mm threshold was associated with a 10.1% [Incidence Rate Ratio (IRR): 0.899, 95% CI: 0.836, 0.968] cumulative decline in larval habitats. Public holidays were not significantly included in the model analysing larval habitats in residences. In non-residences, a 1 °C increase in the ambient air temperature with respect to the mean was associated with a 36.0% (IRR: 1.360, 95% CI: 1.057, 1.749) cumulative increase in Culex larval habitats. Public holidays were associated with a decline in Culex larval habitats in the same week. Our study provides evidence of how ambient air temperature and rainfall variability influences the abundance of Culex mosquito larval habitats. Our findings support the utility of using weather data in predictive models to inform the timing of vector control measures aimed at reducing the risk of WNV and other Culex-borne flavivirus transmission in urban areas.
Drought is a devastating natural hazard that significantly affects human health and social and economic activities. This study aims to explore the short-term association between drought and outpatient visits for respiratory diseases (RDs) in four northwest cities, China. In this study, we obtained daily outpatient visits for RDs, meteorological factors, and air pollutant data in four cities (Lanzhou from 2014 to 2016, Wuwei from 2016 to 2018, Tianshui and Zhangye from 2015 to 2018) of northwest China. We used the daily Standardized Precipitation Index (SPI) as an indicator of drought and estimated the effects of drought on outpatient visits with RDs by using a generalized additive model (GAM) in each city, controlling for daily temperature, time trends, and other confounding factors. The city-specific estimates were pooled by random-effects meta-analysis. There were 1,134,577 RDs cases in the hospitals across the four cities. We found that a 1-unit decrease in daily exposure to SPI-1 was positively associated with daily outpatient visits for RDs, with estimated RR of 1.0230 (95% CIs: 1.0096, 1.0366). Compared to non-drought periods, the RR of daily outpatient visits for RDs for exposure to all drought conditions was 1.0431 (95% CIs: 1.0309, 1.0555). In subgroup analysis, the estimated effects of drought on outpatient visits for RDs appeared larger for males than females though not statistically different, and the estimated effects in children and adolescents were the greatest among different age groups. Drought likely increases the risk of respiratory diseases, particularly among children and adolescents. We highlight that public health adaptations to drought such as drought monitoring, mitigation measures, and adaptation strategies are necessary.
Influenza is an acute respiratory disease that seriously threatens public health. The occurrence of influenza has been proved to be related to a variety of meteorological factors. However, less attention has been paid to the effect of relative humidity (RH) on different types of influenza, especially in subtropical regions. Daily data on laboratory-confirmed influenza cases, weather variables, and air pollutants in Hefei covering the 2014-2019 period were collected. The seasonality and trend of daily influenza cases were explored by the time series seasonal decomposition method. Generalized linear model was fitted in conjunction with distributed lag nonlinear model to quantify the associations of RH with influenza A and influenza B. Subgroup analyses were conducted by sex, age (0-4, 5-17, and ?18 years), and season (cold and warm seasons). A total of 5238 influenza cases including 2847 influenza A cases and 2391 influenza B cases were recorded. The epidemic of influenza presented a distinct seasonal pattern, and the number of daily influenza cases increased steadily since 2016. High RH was related to an increased risk of influenza A (maximum RR = 1.683, 95%CI: 1.365-2.076), especially among males, females, and school-age children. Low RH was associated with an increased risk of influenza B (maximum RR = 1.252, 95%CI: 1.169-1.340). The contrasting relationships of RH with influenza A and B remained significant in cold seasons. High RH and low RH were significantly associated with the increased risk of influenza A and B, respectively. The findings of our study may provide clues for proposing new effective interventions.
People experiencing homelessness (PEH) face extreme weather exposure and limited social support. However, few studies have empirically assessed biophysical and social drivers of health outcomes among unsheltered PEH. Social network, health, and outdoor exposure data were collected from a convenience sample of unsheltered PEH (n = 246) in Nashville, TN, from August 2018-June 2019. Using multivariate fixed-effects linear regression models, we examined associations between biophysical and social environments and self-reported general health and emotional well-being. We found that study participants reported the lowest general health scores during winter months-Nashville’s coldest season. We also found a positive association between the number of nights participants spent indoors during the previous week and general health. Participants who spent even one night indoors during the past week had 1.8-point higher general health scores than participants who spent zero nights indoors (p < 0.01). Additionally, participants who experienced a conflict with a social contact in the past 30 days had lower emotional well-being scores than participants who experienced no conflict. Finally, women had worse general health and emotional well-being than men. Ecologically framed research about health and well-being among PEH is critically needed, especially as climate change threatens to increase the danger of many homeless environments.
PURPOSE: Diurnal temperature range (DTR) is a meteorological indicator closely associated with global climate change. Thus, we aim to explore the effects of DTR on the outpatient and emergency room (O&ER) admissions for cardiovascular diseases (CVDs), and related predictive research. METHODS: The O&ER admissions data for CVDs from three general hospitals in Jinchang of Gansu Province were collected from 2013 to 2016. A generalized additive model (GAM) with Poisson regression was employed to analyze the effect of DTR on the O&ER admissions for all cardiovascular diseases, hypertension, ischemic heart disease (IHD) and stoke. GAM was also used to preform predictive research of the effect of DTR on the O&ER admissions for CVDs. RESULTS: There were similar positive linear relationships between DTR and the O&ER visits with the four cardiovascular diseases. And the cumulative lag effects were higher than the single lag effects. A 1 °C increase in DTR corresponded to a 1.30% (0.99-1.62%) increase in O&ER admissions for all cardiovascular diseases. Males and elderly were more sensitivity to DTR. The estimates in non-heating season were higher than in heating season. The trial prediction accuracy rate of CVDs based on DTR was between 59.32 and 74.40%. CONCLUSIONS: DTR has significantly positive association with O&ER admissions for CVDs, which can be used as a prediction index of the admissions of O&ER with CVDs.
In recent years, there have been considerable changes in the distribution of diseases that are potentially tied to ongoing climate variability. The aim of this study was to investigate the association between the incidence of cutaneous leishmaniasis (CL) and climatic factors in an Iranian city (Isfahan), which had the highest incidence of CL in the country. CL incidence and meteorological data were acquired from April 2010 to March 2017 (108 months) for Isfahan City. Univariate and multivariate seasonal autoregressive integrated moving average (SARIMA), generalized additive models (GAM), and generalized additive mixed models (GAMM) were used to identify the association between CL cases and meteorological variables, and forecast CL incidence. AIC, BIC, and residual tests were used to test the goodness of fit of SARIMA models; and R(2) was used for GAM/GAMM. 6798 CL cases were recorded during this time. The incidence had a seasonal pattern and the highest number of cases was recorded from August to October. In univariate SARIMA, (1,0,1) (0,1,1)(12) was the best fit for predicting CL incidence (AIC=8.09, BIC=8.32). Time series regression (1,0,1) (0,1,1)(12) showed that monthly mean humidity after 4-month lag was inversely related to CL incidence (AIC=8.53, BIC=8.66). GAMM results showed that average temperature with 2-month lag, average relative humidity with 3-month lag, monthly cumulative rainfall with 1-month lag, and monthly sunshine hours with 1-month lag were related to CL incidence (R(2)=0.94). The impact of meteorological variables on the incidence of CL is not linear and GAM models that include non-linear structures are a better fit for prediction. In Isfahan, Iran, meteorological variables can greatly predict the incidence of CL, and these variables can be used for predicting outbreaks.
Urbanization models that do not comply with the planning criteria are affecting human lives. In urban areas, street trees have positive contributions to the ecosystem and human thermal comfort. In this study, the thermal comfort of the main streets that connect people to each other and provide access and transportation has been thermally explored. Cumhuriyet Street, which is one of the vibrant streets in Erzurum, was selected as a case study scenario in the winter and summer periods in 2018 by using the ENVI-met V. 4.4.2 winter model. A different green scenario is proposed, and the best thermal comfort scenario in both seasons is determined. The results show that, in the summer period, the air temperature of the greener street scenario is about 1.0 °C cooler than the existing condition and about 2.0 °C warmer in the winter period. Physiological equivalent temperature (PET) value was better in narrow canyon streets in winter months, but in wide canyon streets in summer months. The green scenarios of wide canyon streets positively affect the outdoor thermal comfort in both seasons. These results clearly imply that green streets are an appropriate strategy for city streets that suffer from discomfort levels in cold winter and hot summer periods. It has been concluded that it is possible to increase thermal comfort through improvement in the open space in street and more suitable plant preferences for livable urbanization. Planning streets in a new city characterized by summer and winter seasons should take into consideration an accurate decision for providing a thermal comfort level and healthy urbanization.
The paper analyses the temporal and spatial variability of the Universal Thermal Climate Index (UTCI) in Poland in summer. Summer is the season with the highest intensity of tourism traffic that is why it is important to determine biometeorological conditions, especially in popular tourist destinations such as coastal, mountain and urban areas, in the times of climate changes. The analysis was based on data from 18 stations of IMGW-PIB (Institute of Meteorology and Water Management-National Research Institute), distributed evenly in the territory of the country, and representing all eight bioclimatic regions. The data include air temperature, relative humidity, wind velocity and cloudiness at 12 UTC from summer months: June, July and August from the years 2001-2018. Thermoneutral zone was the most frequently occurring UTCI class in Poland. It was recorded during 56-75% of summer days (with the exception of mountain stations, where it occurred on 30-35% of days). Moderate heat stress is the second most frequently occurring category with a frequency from 18 to 29% with the exception of mountain and coastal areas. Extreme and very strong cold stress occurred particularly in high mountain stations, and was sporadically observed at the coast of the Baltic Sea; however, the occurrence of such conditions decreases, which if favourable for beach tourism. No cases of extreme heat stress were recorded in any of the stations. The most unfavourable bioclimatic conditions were characteristic of the Upland Region (IV), represented by Kraków and Sandomierz, where very strong heat stress occurred with a 10% frequency. This is a limitation for urban tourism in those regions. The highest UTCI values were recorded in Kraków on 17 July 2007 and 29 July 2005. The highest number of cases with strong and very strong heat stress was recorded in 2015 as a consequence of the heat wave observed in Poland in the first half of August. In the majority of the analysed stations, in the second half of the analysed period (2010-2018), an increase in the number of days with strong and very strong heat stress was observed in comparison with the first half of period (2001-2009). The highest frequency of such days was observed in July. Based on the data, there are 4 potential periods of occurrence of such days, with two most intense being 26. July-13 August and 14-22 July.
Higher temperatures are associated with morbidity and mortality. Most epidemiological studies use outdoor temperature data, however, people spend most of their time indoors. Indoor temperatures and determinants of indoor temperatures have rarely been studied on a large scale. We measured living room and bedroom temperature in 113 homes of elderly subjects, as well as outdoor temperatures, in two cities in the Netherlands. Linear regression was used to determine the influence of building characteristics on indoor living room and bedroom temperatures in the warm episode. During the warm episode, indoor temperatures were higher during the night and lower during the day than outdoor temperatures. Indoor temperatures on average exceeded outdoor temperatures. The weekly average indoor temperature in living rooms varied between 23.1 and 30.2 °C. Dwellings that warmed up easily, also cooled down more easily. Outdoor and indoor temperatures were moderately correlated (R(2) = 0.36 and 0.34 for living rooms and bedrooms, respectively). Building year before 1930 and rooms being located on the top floor were associated with higher indoor temperatures. Green in the vicinity was associated with lower temperatures in bedrooms. This study shows that indoor temperatures vary widely between dwellings, and are determined by outdoor temperatures and building characteristics. As most people, especially the elderly, spend most of the time indoor, indoor temperature is a more exact predictor of heat exposure than outdoor temperature. The importance of mitigating high indoor temperatures will be more important in the future because of higher temperatures due to climate change.
Current development of temperature-related health early warning systems mainly arises from knowledge of temperature-related mortality or hospital-based morbidity. However, due to the delay in data reporting and limits in hospital capacity, these indicators cannot be used in health risk assessments timely. In this study, we examine temperature impacts on emergency ambulance and discuss the benefits of using this near real-time indicator for risk assessment and early warning. We collected ambulance dispatch data recording individual characteristics and preliminary diagnoses between 2015 and 2016 in Shenzhen, China. Distributed lag nonlinear model was used to examine the effects of high and low temperatures on ambulance dispatches during warm and cold seasons. Lag effects were also assessed to evaluate the sensitivity of ambulance dispatches in reflecting immediate health reactions. Stratified analyses by gender, age, and a wide range of diagnoses were performed to identify vulnerable subgroups. Disease-specific numbers of ambulance dispatches attributable to non-optimal temperature were calculated to determine the related medical burdens. Effects of temperature on ambulance dispatches appeared to be acute on the current day. Males, people aged 18-44 years, were more susceptible to non-optimal temperatures. Highest RR during heat exposure by far was for urinary disease, alcohol intoxication, and traumatic injury, while alcohol intoxication and cardiovascular disease were especially sensitive to cold exposure, causing the main part of health burden. The development of local health surveillance systems by utilizing ambulance dispatch data are important for temperature impact assessments and medical resource reallocation.
Brazil is the country with the highest social inequality in South America. This socioeconomic disparity reflects not only on the families’ income but also on their spatial localization in the city, as well as on the urban design. These urban environments can alter the urban microclimate, and consequently, interfere in dwellers’ thermal comfort. This research investigated the relationship between socio-spatial inequalities and thermal comfort in two different Local Climate Zones (LCZ) using a combination of measurement and modeling. Air temperature (Tair) was obtained by on-site measurements in compact high-rise (LCZ1) and compact low-rise buildings (LCZ3) and Mean radiant temperature (Tmrt) was simulated using SOlar and LongWave Environmental Irradiance Geometry (SOLWEIG). The results indicated that in LCZ1 seafront-localized buildings, in which residents have a higher income, the temperature remains in a range classified as comfortable, mainly due to shading and sea breeze. On the other hand, LCZ3, located in the periphery of the city, in which the low-income population is concentrated and is marked by a precariousness urban environment, presented a higher air temperature and Tmrt values, exposing the dwellers to heat stress throughout the year, especially during the summer season. These observations suggested that public and private actions tend to promote better urban designs in areas with a higher concentration of income. Public reforms aimed at improving the urban environment and promoting thermal comfort should be a priority for the warmest LCZ, where the poorest residents live. Public agents should rethink the distribution of environmental resources to promote equitable urban spaces.
The aim of this study was to analyse the association between season of birth, temperature and neonatal mortality according to socioeconomic status in northern Sweden from 1880 to 1950. The source material for this study comprised digitised parish records combined with local weather data. The association between temperature, seasonality, socioeconomic status and neonatal mortality was modelled using survival analysis. We can summarise our findings according to three time periods. During the first period (1880–1899), temperature and seasonality had the greatest association with high neonatal mortality, and the socioeconomic differences in vulnerability were small. The second period (1900–1929) was associated with a decline in seasonal and temperature-related vulnerabilities among all socioeconomic groups. For the last period (1930–1950), a new regime evolved with rapidly declining neonatal mortality rates involving class-specific temperature vulnerabilities, and there was a particular effect of high temperature among workers. We conclude that the effect of season of birth on neonatal mortality was declining for all socioeconomic groups (1880–1950), whereas weather vulnerability was pronounced either when the socioeconomic disparities in neonatal mortality were large (1880–1899) or during transformations from high to low neonatal rates in the course of industrialisation and urbanisation.
This study attempts to measure the spatial correlation length (SCL) of summer extreme heat stress in any location by using a characterized scale identification method. Daily datasets of multiple meteorological variables from 2,134 observation stations over eastern China during 1961-2010 were used. Three types of heat indexes (a total of seven indexes) were applied to characterize the heat stress. The first type used a single variable, that is, daily maximum temperature (T-max) or daily minimum temperature (T-min), while the second used mean temperature (T) and relative humidity, and the third used T, vapour pressure, and 10-m wind speed. A 90th percentile of the climatology of local heat stress was applied to identify hot days. The SCLs of heat stress were analysed in three regions: North China (NC), the Yangtze River Valley (YRV), and South China (SC). Results showed that the trend changes in heat stress had obvious temporal and geographical characteristics, especially in NC and YRV. Generally, the SCLs of heat stress in NC were the largest, reaching more than 440 km for T-max, with YRV second, about 350 km, and SC the smallest, only about 185 km. This phenomenon could be found for almost all indexes. Moreover, the SCLs of the first two types of heat indexes (except T-min) for the three regions were greater than that of the third one, particularly in NC and YRV, which was related to inconsistent changes in the variables used and the primary role of which one characterized the heat stress. The spatial distributions of high SCLs for all indexes were in line with that of the major urban agglomeration in eastern China. The SCL of heat stress for a location was related not only to the changes themselves, but also to the surroundings, involving the number and spatial distribution of hot days.
The Urban Heat Island effect has been the focus of several studies concerned with the effects of urbanisation on human and ecosystem health. Humidity, however, remains much less studied, although it is useful for characterising human thermal comfort, the Urban Dryness Island effect and vegetation development. Furthermore, variability in microscale climate due to differences in land cover is increasingly crucial for understanding urbanisation effects on the health and wellbeing of living organisms. We used regression analysis to investigate the spatial and temporal dynamics of temperature, humidity and heat index in the tropical African city of Kampala, Uganda. We gathered data during the wet to dry season transition from 22 locations that represent the wide range of urban morphological differences in Kampala. Our analysis showed that the advancement of the dry season increased variability of climate in Kampala and that the most built-up locations experienced the most profound seasonal changes in climate. This work stresses the need to account for water availability and humidity to improve our understanding of human and ecosystem health in cities.
PURPOSE: The aim of the present study was to investigate the effect of short-term exposure to ambient black carbon (BC) on daily cause-specific mortality, including mortality due to respiratory, cardiovascular, ischemic heart and cerebrovascular diseases in Tehran, Iran. MATERIALS AND METHODS: Daily non-accidental death counts, meteorological data and hourly concentrations of air pollutants from 2014 to 2017 were collected in Tehran. A distributed lag non-linear model was used to assess the association between exposure to BC and daily mortality. RESULTS: The mean daily BC concentration during the study period was 3.96?±?1.19 µg/m(3). The results indicated that BC was significantly associated with cardiovascular, ischemic heart disease, and cerebrovascular mortality, but not with respiratory mortality. In first model, each 10 µg/m(3) increase in at lag 3, lag 4 and lag 5 were associated with cardiovascular mortality in 16-65 year age group with the relative risks (RRs) of 1.17 (95?% CI: 1.02-1.33), 1.17 (95?% CI: 1.04-1.31) and 1.12 (95?% CI: 1.02-1.24), respectively. The highest mortality rate per 10 µg/m(3) increase in exposure was found for ischemic heart diseases with RR of 3.98 (95?% CI: 1.04-1.81, lag 01) for 16-65 age group. Cerebrovascular mortality was associated with 10 µg/m(3) increases in non-cumulative exposure with RR of 1.17 (95?% 1.009-1.35, lag 5) in the age group ? 65 years. In the second model for a 10 µg/m(3) increase in BC, cardiovascular mortality at specific lag days (5 and 6 days) in the age group ? 16 years were associated with RR of 1.34 (95?% CI 1.08-1.66) and 1.35(95?% CI 1.02-1.77), respectively. CONCLUSIONS: This study in Tehran found significant effects of BC exposure on daily mortality for cardiovascular, ischemic heart disease, cerebrovascular disease. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40201-021-00659-0.
Ischemic stroke is one of the most common causes of death worldwide, and uncomfortable meteorological and built environments may increase its risk. Residents in different built environments are exposed to different risks of ischemic stroke in cold and hot weather. By using the data from 3547 patients hospitalized, a distributed lag non-linear model was established to compare the differences in the risk of ischemic stroke in urban areas with respect to different Building Height, Building Density, Normalized Differential Vegetation Index, and Distance to Water under the meteorological condition. The results showed that lower Building Height is related to the negative cold effects in winter, and higher Building Height is related to increased risks at high temperatures. Built environments with Building Heights of 10-15 m in hot weather and above 15 m in cold weather have low risks. Higher Building Density was found to be associated with reduced negative cold effects; however, the negative hot effects increased in summer. Built environments with a Building Density of more than 0.3 showed low risks, regardless of the weather conditions. Increasing NDVI seemed to mitigate negative effects in uncomfortable weather, and built environments with higher NDVI were found to be associated with lower risks of ischemic stroke. Built environments with shorter Distance to Water seemed to pose higher risks in summer, and longer Distance to Water was correlated with higher risks in winter. Built environments with Distance to Water in the range of 0.65-2.30 km showed low risks. The research results could have some implications for urban planners to form reasonable built environments under certain meteorological factors which can be beneficial for the mitigation of incidence of ischemic stroke. (C) 2020 Elsevier B.V. All rights reserved.
Previous studies demonstrated that global warming can lead to deteriorated air quality even when anthropogenic emissions were kept constant, which has been called a climate change penalty on air quality. It is expected that anthropogenic emissions will decrease significantly in the future considering the aggressive emission control actions in China. However, the dependence of climate change penalty on the choice of emission scenario is still uncertain. To fill this gap, we conducted multiple independent model simulations to investigate the response of PM(2.5) to future (2050) climate warming (RCP8.5) in China but with different emission scenarios, including the constant 2015 emissions, the 2050 CLE emissions (based on Current Legislation), and the 2050 MTFR emissions (based on Maximum Technically Feasible Reduction). For each set of emissions, we estimate climate change penalty as the difference in PM(2.5) between a pair of simulations with either 2015 or 2050 meteorology. Under 2015 emissions, we find a PM(2.5) climate change penalty of 1.43 ?g m(-3) in Eastern China, leading to an additional 35,000 PM(2.5)-related premature deaths [95% confidence interval (CI), 21,000-40,000] by 2050. However, the PM(2.5) climate change penalty weakens to 0.24 ?g m(-3) with strict anthropogenic emission controls under the 2050 MTFR emissions, which decreases the associated PM(2.5)-related deaths to 17,000. The smaller MTFR climate change penalty contributes 14% of the total PM(2.5) decrease when both emissions and meteorology are changed from 2015 to 2050, and 24% of total health benefits associated with this PM(2.5) decrease in Eastern China. This finding suggests that controlling anthropogenic emissions can effectively reduce the climate change penalty on PM(2.5) and its associated premature deaths, even though a climate change penalty still occurs even under MTFR. Strengthened controls on anthropogenic emissions are key to attaining air quality targets and protecting human health in the context of future global climate change.
INTRODUCTION: Enteric Fever (EF) affects over 14.5 million people every year globally, with India accounting for the largest share of this burden. The water-borne nature of the disease makes it prone to be influenced as much by unsanitary living conditions as by climatic factors. The detection and quantification of the climatic effect can lead to improved public health measures which would in turn reduce this burden. METHODOLOGY: We obtained a list of monthly Widal positive EF cases from 1995 to 2017 from Ahmedabad and Surat Municipalities. We obtained population data, daily weather data, and Oceanic Niño Index values from appropriate sources. We quantified the association between extreme weather events, phases of El Niño Southern Oscillations (ENSO) and incidence of EF. RESULTS: Both cities showed a seasonal pattern of EF, with cases peaking in early monsoon. Risk of EF was affected equally in both cities by the monsoon season — Ahmedabad (35%) and Surat (34%). Extreme precipitation was associated with 5% increase in EF in Ahmedabad but not in Surat. Similarly, phases of ENSO had opposite effects on EF across the two cities. In Ahmedabad, strong El Niño months were associated with 64% increase in EF risk while strong La Niña months with a 41% reduction in risk. In Surat, strong El Niño was associated with 25% reduction in risk while moderate La Niña with 21% increase in risk. CONCLUSIONS: Our results show that the risk of EF incidence in Gujarat is highly variable, even between the two cities only 260 kms apart. In addition to improvements in water supply and sewage systems, preventive public health measures should incorporate variability in risk across season and phases of ENSO. Further studies are needed to characterize nationwide heterogeneity in climate-mediated risk, and to identify most vulnerable populations that can benefit through early warning systems.
Purpose Quantitative and spatial-explicit flood risk information is of great importance for strengthening climate change adaptation and flood resilience. Shanghai is a coastal megacity at large estuary delta with rising flood risks. This study aims to quantify the overall economic-societal risks of storm flooding and their spatial patterns in Shanghai. Design/methodology/approach Based on multiple storm flood scenarios at different return periods, as well as fine-scale data sets including gridded GDP, gridded population and vector land-use, a probabilistic risk model incorporating geographic information system is used to assess the economic-societal risks of flooding and their spatial distributions. Findings Our results show that, from 1/200 to 1/5,000-year floods, the exposed assets will increase from USD 85.4bn to USD 657.6bn, and the direct economic losses will increase from USD 3.06bn to USD 52bn. The expected annual damage (EAD) of assets is around USD 84.36m. Hotpots of EAD are mainly distributed in the city center, the depressions along the upper Huangpu River in the southwest, the north coast of Hangzhou Bay, and the confluence of the Huangpu River and Yangtze River in the northeast. From 1/200 to 1/5,000-year floods, the exposed population will rise from 280 thousand to 2,420 thousand, and the estimated casualties will rise from 299 to 1,045. The expected annual casualties (EAC) are around 2.28. Hotspots of casualties are generally consistent with those of EAD. Originality/value In contrast to previous studies that focus on a single flood scenario or a particular type of flood exposure/risk in Shanghai, the findings contribute to an understanding of overall flood risks and their spatial patterns, which have significant implications for cost-benefit analysis of flood resilience strategies.
Recent studies have reported a variety of health consequences of climate change. However, the vulnerability of individuals and cities to climate change remains to be evaluated. We project the excess cause-, age-, region-, and education-specific mortality attributable to future high temperatures in 161 Chinese districts/counties using 28 global climate models (GCMs) under two representative concentration pathways (RCPs). To assess the influence of population ageing on the projection of future heat-related mortality, we further project the age-specific effect estimates under five shared socioeconomic pathways (SSPs). Heat-related excess mortality is projected to increase from 1.9% (95% eCI: 0.2-3.3%) in the 2010s to 2.4% (0.4-4.1%) in the 2030?s and 5.5% (0.5-9.9%) in the 2090?s under RCP8.5, with corresponding relative changes of 0.5% (0.0-1.2%) and 3.6% (-0.5-7.5%). The projected slopes are steeper in southern, eastern, central and northern China. People with cardiorespiratory diseases, females, the elderly and those with low educational attainment could be more affected. Population ageing amplifies future heat-related excess deaths 2.3- to 5.8-fold under different SSPs, particularly for the northeast region. Our findings can help guide public health responses to ameliorate the risk of climate change.
Climate change is an urgent challenge in urban planning. Weather extremes and resulting impacts such as heat waves and flash floods are already influencing the quality of life in cities and impact on infrastructure, human health and city life. In this study, we investigated perception of and economic preferences for adaptation to climate change in one of Europe’s capital cities to inform its planning policy. Through a choice experiment, we elicit the preferences of a sample (n = 550) from Prague, Czech Republic, for a citywide policy which would increase the use of six commonly used nature-based solutions (NBS) in public spaces and on public buildings across the city. Three attributes were used to describe this policy: (i) the locations where NBS would predominantly be implemented, (ii) the species diversity of these measures, and (iii) their implied costs for households. Our results showed that the NBS policy is widely supported by the public over the status quo and that this preference is mirrored in citizens’ concerns about climate change and the risks posed by heatwaves particularly. Species diversity matters in the portrayed scenarios, suggesting that (bio)diverse NBS generate additional public value over single species measures and that policy which targets biodiversity may gain support. Implementation of NBS in public spaces (e.g., street trees, rain gardens) is preferred over measures implemented on public buildings (green roofs and facades). Furthermore, adverse experiences with heatwaves has increased support for the policy. The presented results provide evidence that adaptation planning through NBS is likely to generate significant public value which is expected to increase with the intensifying effects of climate change.
Urban green spaces (UGS) are known for providing a cooling effect by evapotranspiration, shade, and by altering the albedo. Heat mitigation by UGS reduces the space cooling demand, provides comfort, and enhances productivity. Rapid urbanization in developing countries has resulted in dwindling green spaces and their protective role is often neglected. We have quantified the heat mitigation by UGS using the InVEST model (Integrated Valuation of Ecosystem Services and Trade-offs) for present and future scenarios of Nagpur City which is situated in a heatwave-affected zone. Four future plausible scenarios were generated with a combination of drivers-economic development and commitment to promoting UGS, using the two-axis scenario analysis method. The simulated UGS in each future scenario (by allowing 10% variation in the land use) is utilized for quantification of heat mitigation and energy conserved. In comparison with the present situation, 21-29% less space cooling energy is conserved in scenarios driven by economic development (least commitment to UGS), whereas 17% more energy is conserved when UGS are promoted. In similar lines, the average temperature is increased by 0.5-0.7 degrees C when UGS are neglected, while the temperature dropped by 0.5 degrees C when UGS are promoted in Nagpur City. The methodology presents an integration of scenario analysis with heat mitigation modeling which can enable urban planners and researchers to improve their understanding of the ecological structure of urban centers and can aid in appreciating the potential of UGS in heat mitigation for human wellbeing.
Household flooding has wide ranging social, economic and public health impacts particularly for people in resource poor communities. The determinants and public health outcomes of recurrent home flooding in urban contexts, however, are not well understood. A household survey was used to assess neighborhood and household level determinants of recurrent home flooding in Detroit, MI. Survey activities were conducted from 2012 to 2020. Researchers collected information on past flooding, housing conditions and public health outcomes. Using the locations of homes, a “hot spot” analysis of flooding was performed to find areas of high and low risk. Survey data were linked to environmental and neighborhood data and associations were tested using regression methods. 4803 households participated in the survey. Flooding information was available for 3842 homes. Among these, 2085 (54.26%) reported experiencing pluvial flooding. Rental occupied units were more likely to report flooding than owner occupied homes (Odd ratio (OR) 1.72 [95% Confidence interval (CI) 1.49, 1.98]). Housing conditions such as poor roof quality and cracks in basement walls influenced home flooding risk. Homes located in census tracts with increased percentages of owner occupied units (vs. rentals) had a lower odds of flooding (OR 0.92 [95% (CI) 0.86, 0.98]). Household factors were found the be more predictive of flooding than neighborhood factors in both univariate and multivariate analyses. Flooding and housing conditions associated with home flooding were associated with asthma cases. Recurrent home flooding is far more prevalent than previously thought. Programs that support recovery and which focus on home improvement to prevent flooding, particularly by landlords, might benefit the public health. These results draw awareness and urgency to problems of urban flooding and public health in other areas of the country confronting the compounding challenges of aging infrastructure, disinvestment and climate change.
BACKGROUND: Severe hand-foot-and-mouth disease (HFMD) is a life-threatening contagious disease among young children and infants. Although enterovirus A71 has been well acknowledged to be the dominant cause of severe HFMD, there still remain other unidentified risk factors for severe HFMD. Previous studies mainly focused on identifying the individual-level risk factors from a clinical perspective, while rare studies aimed to clarify the association between regional-level risk factors and severe HFMD, which may be more important from a public health perspective. METHODS: We retrieved the clinical HFMD counts between 2008 and 2014 from the Chinese Center for Disease Control and Prevention, which were used to calculated the case-severity rate in 143 prefectural-level cities in mainland China. For each of those 143 cities, we further obtained city-specific characteristics from the China City Statistical Yearbook (social and economic variables) and the national meteorological monitoring system (meteorological variables). A Poisson regression model was then used to estimate the associations between city-specific characteristics (reduced by the principal component analysis to avoid multicollinearity) and the case-severity rate of HFMD. The above analysis was further stratified by age and gender to examine potential modifying effects and vulnerable sub-populations. RESULTS: We found that the case-severity rate of HFMD varied dramatically between cities, ranging from 0 to 8.09%. Cities with high case-severity rates were mainly clustered in Central China. By relating the case-severity rate to city-specific characteristics, we found that both the principal component characterized by a high level of social and economic development (RR = 0.823, 95%CI 0.739, 0.916) and another that characterized by warm and humid climate (RR = 0.771, 95%CI 0.619, 0.960) were negatively associated with the case-severity rate of HFMD. These estimations were consistent across age and gender sub-populations. CONCLUSION: Except for the type of infected pathogen, the case-severity rate of HFMD was closely related to city development and meteorological factor. These findings suggest that social and environmental factors may also play an important role in the progress of severe HFMD.
Exposure to air pollution has been suggested to be associated with an increased risk of women’s health disorders. However, it remains unknown to what extent changes in ambient air pollution affect gynecological cancer. In our case-control study, the logistic regression model was combined with the restricted cubic spline to examine the association of short-term exposure to air pollution with gynecological cancer events using the clinical data of 35,989 women in Beijing from December 2008 to December 2017. We assessed the women’s exposure to air pollutants using the monitor located nearest to each woman’s residence and working places, adjusting for age, occupation, ambient temperature, and ambient humidity. The adjusted odds ratios (ORs) were examined to evaluate gynecologic cancer risk in six time windows (Phase 1-Phase 6) of women’s exposure to air pollutants (PM(2.5), CO, O(3), and SO(2)) and the highest ORs were found in Phase 4 (240 days). Then, the higher adjusted ORs were found associated with the increased concentrations of each pollutant (PM(2.5), CO, O(3), and SO(2)) in Phase 4. For instance, the adjusted OR of gynecological cancer risk for a 1.0-mg m(-3) increase in CO exposures was 1.010 (95% CI: 0.881-1.139) below 0.8 mg m(-3), 1.032 (95% CI: 0.871-1.194) at 0.8-1.0 mg m(-3), 1.059 (95% CI: 0.973-1.145) at 1.0-1.4 mg m(-3), and 1.120 (95% CI: 0.993-1.246) above 1.4 mg m(-3). The ORs calculated in different air pollution levels accessed us to identify the nonlinear association between women’s exposure to air pollutants (PM(2.5), CO, O(3), and SO(2)) and the gynecological cancer risk. This study supports that the gynecologic risks associated with air pollution should be considered in improved public health preventive measures and policymaking to minimize the dangerous effects of air pollution.
We analyzed two historical extreme heat events in Los Angeles to explore the potential of increasing vegetative cover and surface solar reflectance (albedo) to reduce total exposure (indoor and outdoor) to dangerously hot conditions. We focus on three population subgroups, the elderly, office workers, and outdoor workers, and explore the extreme case where each subgroup does not have functioning air conditioning in their residences. For each heat event, we conducted atmospheric model simulations for a control case and four mitigation cases with varying levels of increased albedo and vegetation cover. Simultaneously, we conducted building simulations of representative residential buildings that lacked mechanical air conditioning. These simulations factored in both the indirect cooling effects associated with neighborhood implementation of mitigation strategies and the direct effects of high albedo roofing on the individual buildings. From both the atmospheric and building models, we exported hourly values of air temperature and dew point temperature, and used this information in combination with various scenarios of occupant behavior to create profiles of individual heat exposure. We also gathered heat-mortality data for the two heat events and developed a synoptic climatology-based relationship between exposure and excess mortality. This relationship was then applied to the scenarios in which albedo and canopy cover were increased. The results suggest that improvements in indoor thermal conditions are responsible for a sizable portion of the health benefit of large-scale implementation of heat mitigation strategies.
Climate risks and vulnerability continue to disproportionately affect the urban poor given their constrained adaptive capacity. This paper examines the urban poor’s perceptions and vulnerability to climate change in Kampala. Data was collected from a proportionate sample of 534 respondents drawn from households that were randomly selected from the city’s informal settlements and interviewed using a structured questionnaire. Six focus group discussions and 15 key informant interviews were conducted whose participants were purposively selected because of their knowledge and experiences. Quantitative data was analyzed using chi-square tests while content analysis was used to analyze qualitative data from key informant interviews and focus group discussions. A total of 96.6% of the households were aware of climate change, mainly perceived as rising temperatures and reduction in rainfall. Floods (53.4%) and droughts (27%) were the most commonly experienced climate risks, with the former considered more frequent and severe. Perceptions and vulnerability to climate risk varied with incomes, education level, marital status, main occupation, housing conditions and length of stay. Individuals with less wealth and education, employed in informal business and having insecure housing tenure were most vulnerable to flooding than they are to drought. The sensitivity of the urban poor communities is heightened by ecosystem degradation, poor access to urban infrastructure, utilities and services. With socio-economic attributes highly associated to climate change vulnerabilities, incorporating social dimensions and exchange of information between the vulnerable communities, planners and decision makers is necessary to inform the city’s adaptation policy and building long-term urban resilience. Partnerships are necessary between the urban authorities, communities, civil society and donors/financiers to improve housing and livelihoods in slums settlements. At the same time, strengthening co-production of climate information services, building climate change awareness, restoration of critical ecosystems and a broader inclusive adaptation planning are avenues for building resilient urban poor communities.
Extreme heat is an increasing climate threat, most pronounced in urban areas where poor populations are at particular risk. We analyzed heat impacts and vulnerabilities of 1027 outdoor workers who participated in a KAP survey in Hanoi, Vietnam in 2018, and the influence of their mitigation actions, their knowledge of heat-risks, and access to early warnings. We grouped respondents by their main income (vendors, builders, shippers, others, multiple jobs, and non-working) and analyzed their reported heat-health impacts, taking into consideration socioeconomics, knowledge of heat impacts and preventive measures, actions taken, access to air-conditioning, drinking amounts and use of weather forecasts. We applied linear and logistic regression analyses using R. Construction workers were younger and had less knowledge of heat-health impacts, but also reported fewer symptoms. Older females were more likely to report symptoms and visit a doctor. Access to air-conditioning in the bedroom depended on age and house ownership, but did not influence heat impacts as cooling was too expensive. Respondents who knew more heat exhaustion symptoms were more likely to report impacts (p < 0.01) or consult a doctor (p < 0.05). Similarly, those who checked weather updates were more likely to report heat impacts (p < 0.01) and experienced about 0.6 more symptoms (p < 0.01). Even though occupation type did not explain heat illness, builders knew considerably less (40%; p < 0.05) about heat than other groups but were twice as likely to consult a doctor than street vendors (p < 0.01). Knowledge of preventive actions and taking these actions both correlated positively with reporting of heat-health symptoms, while drinking water did not reduce these symptoms (p < 0.01). Child carers and homeowners experienced income losses in heatwaves (p < 0.01). The differences support directed actions, such as dissemination of educational materials and weather forecasts for construction workers. The Red Cross assisted all groups with cooling tents, provision of drinks and health advice.
Because of climate change and rapid urbanization, urban impervious underlying surfaces have expanded, causing Chinese cities to become strongly affected by flood disasters. Therefore, research on urban flood risks has greatly increased over the past decade, with studies focusing on reducing the risk of flood disaster. From 2012 to 2020, the impervious underlying surface has increased, and the permeable underlying surface has decreased annually in Kunming City. This study was conducted to investigate the impact of continuous changes in the urban underlying surface on flood disasters in the Runcheng area south of Kunming City from 2012 to 2020. We constructed a two-dimensional flood model to conduct flood simulations and flood risk analysis for this area. The relationship between the permeability of the underlying surface and urban flood risk was simulated and analyzed by varying the urban underlying surface permeability (0-60%). The simulation results show that the model can accurately simulate urban waterlogging, and the increase in urban waterlogging risk is related to the underlying surface permeability. Urban flood risk decreases with the increase in permeable underlying surface. The increase rate of flood risk in the part with permeability of 0-35% is greater than that the part with permeability of 35-60%, that is, when the permeability of underlying surface is lower than 35%, the flood risk rate will be higher. We demonstrated the impact of the urban underlying surface permeability on the risk of urban flood disasters, which is useful for urban planning decisions and urban flooding risk controls.
Exposure to air pollution is of great concern for public health although studies on the associations between exposure estimates and personal exposure are limited and somewhat inconsistent. The aim of this study was to quantify the associations between personal nitrogen oxides (NO(x)), ozone (O(3)) and particulate matter (PM(10)) exposure levels and ambient levels, and the impact of climate and time spent outdoors in two cities in Sweden. Subjects (n?=?65) from two Swedish cities participated in the study. The study protocol included personal exposure measurements at three occasions, or waves. Personal exposure measurements were performed for NO(x) and O(3) for 24 h and PM(10) for 24 h, and the participants kept an activity diary. Stationary monitoring stations provided hourly data of NO(x), O(3) and PM, as well as data on air temperature and relative humidity. Data were analysed using mixed linear models with the subject-id as a random effect and stationary exposure and covariates as fixed effects. Personal exposure levels of NO(x), O(3) and PM(10) were significantly associated with levels measured at air pollution monitoring stations. The associations persisted after adjusting for temperature, relative humidity, city and wave, but the modelled estimates were slightly attenuated from 2.4% (95% CI 1.8-2.9) to 2.0% (0.97-2.94%) for NO(x), from 3.7% (95% CI 3.1-4.4) to 2.1% (95% CI 1.1-2.9%) for O(3) and from 2.6% (95% 0.9-4.2%) to 1.3% (95% CI?-?1.5-4.0) for PM(10). After adding covariates, the degree of explanation offered by the model (coefficient of determination, or R(2)) did not change for NO(x) (0.64 to 0.63) but increased from 0.46 to 0.63 for O(3), and from 0.38 to 0.43 for PM(10). Personal exposure to NO(x), O(3) and PM has moderate to good association with levels measured at urban background sites. The results indicate that stationary measurements are valid as measure of exposure in environmental health risk assessments, especially if they can be refined using activity diaries and meteorological data. Approximately 50-70% of the variation of the personal exposure was explained by the stationary measurement, implying occurrence of misclassification in studies using more crude exposure metrics, potentially leading to underestimates of the effects of exposure to ambient air pollution.
Although Ahvaz is considered as one of the warmest cities around the world, few epidemiological studies have been conducted on the adverse effects of temperature on human health using thermal indices in this city. This study investigates the relation between physiologically equivalent temperature (PET) and respiratory hospital admissions in Ahvaz. Distributed lag non-linear models (DLNMs) combined with quasi-Poisson regression models were used to investigate the relation between PET and respiratory disease hospital admissions, adjusted for the effect of time trend, air pollutants (NO(2), SO(2), and PM(10)), and weekdays. The analysis was performed by utilizing R software. Low PET values significantly decreased the risk of hospital admissions for total respiratory diseases, respiratory diseases in men and women, chronic obstructive pulmonary diseases (COPD), and bronchiectasis. However, low PET (16.9°C) in all lags except lag 0-30 significantly increased the risk of hospital admissions for asthma. The results indicate that in Ahvaz, which has a warm climate, cold weather decreased overall respiratory hospital admissions, except for asthma.
Climate change has important population health impacts, and cities are often on the frontlines. However, health is reported to be less active in climate adaptation than other sectors. To contribute to better understanding urban health adaptation efforts and identifying gaps we developed a City Climate Health Adaptation Typology and tested it with adaptation actions of 106 large world cities (population > 1 million) reported to a major publicly-available adaptation database. We found two-thirds of actions of these ‘active adapter’ cities were health-associated. Half were health information activities (e.g., hazard mapping, early warnings); and nearly one-third addressed climate-relevant health determinants in the urban built environment (e.g., green space). Forty percent of cities were in low- or middle-income countries. Our proposed typology provides a systematic framework for monitoring and comparing city health adaptation actions. Reported city actions are suggestive of increasing depth and breadth of urban health-associated adaptation. However, even among these adaptation-engaged cities, a health adaptation gap was apparent in key climate health services (e.g., mental health), and in climate-related public health governance and capacity building. The COVID-19 pandemic has demonstrated pressing need for strong public health institutions. We recommend better integration of public health agencies into local climate action planning, enhanced modes of collaboration between health and non-health agencies and with non-governmental actors, and strengthening of city public health adaptive capacity including through networking.
The current increase and severity of the natural disasters whose effects on the public health are likely to be even more extreme and complex, requires enhancing and developing the disaster preparedness on the population level. In order to be able to do so, it is inevitable and determinative to know the factors that affect people’s preparedness on the population level. Therefore, the objective of this article is to present the results from assessing the factors related to the population preparedness for the disasters on a sample of citizens living from the Slovak Republic. Our research is based on the exploration of the questionnaire survey’ results aimed at investigating the preparedness and preventive proactive behaviour of the population against the disasters. The search for the initiators of such a behaviour and assessment of the influence of various aspects (e.g., the respondents’ experience with disasters, their vulnerability to disasters, the risk awareness, the perception of the disaster risks in the changing environment, etc.) on the respondents’ behaviour against disasters is the main part of the article and is supported by the statistical analysis. The results of the survey suggest that the disaster risk awareness and overall disaster preparedness level is rather poor and the population is inactive. The proactive behaviour of the respondents against the disasters is partially affected by some of their personality and socio-economic characteristics, especially the younger respondents currently incline more to adopting the protective measures. In addition, other aspects, e.g., the negative experience with the disasters in the past influence the preparedness. However, the impacts must have been relatively serious for the proactive behaviour to be influenced. The influences of other aspects as well as the possible methods for improving the disaster preparedness and the possibilities of increasing the resilience of the population as a whole are also discussed in this article.
Under the dual effects of climate change and urban heat islands (UHI), non-optimum temperature-related mortality burdens are complex and uncertain, and are rarely discussed in China. In this study, by applying city-specific exposure-response functions to multiple temperature and population projections under different climate and urbanization scenarios, we comprehensively assessed the non-optimum temperature-related mortality burdens in China from 2000 to 2050. Our results showed that temperature-related deaths will decrease from 1.19 million in 2010 to 1.08-1.17 million in 2050, with the exception of the most populous scenario. Excess deaths attributable to non-optimal temperatures under representative concentration pathway 8.5 (RCP8.5) were 2.35% greater than those under RCP4.5. This indicates that the surge in heat-related deaths caused by climate change will be offset by the reduction in cold-related deaths. As the climate changes, high-risk areas will be confronted with more severe health challenges, which requires health protection resource relocation strategies. Simultaneously, the net effects of UHIs are beneficial in the historical periods, preventing 3493 (95% CI: 22-6964) deaths in 2000. But UHIs will cause an additional 6951 (95% CI: -17,637-31,539, SSP4-RCP4.5) to 17,041 (95% CI: -10,516-44,598, SSP5-RCP8.5) deaths in 2050. The heavier health burden in RCP8.5 than RCP4.5 indicates that a warmer climate aggravates the negative effects of UHIs. Considering the synergistic behavior of climate change and UHIs, UHI mitigation strategies should not be developed without considering climate change. Moreover, the mortality burden exhibited strong spatial variations, with heavy burdens concentrated in the hotspots including Beijing-Tianjin Metropolitan Region, Yangtze River Delta, Chengdu-Chongqing City Group, Guangzhou, Wuhan, Xi’an, Shandong, and Henan. These hotspots should be priority areas for the allocation of the national medical resources to provide effective public health interventions.
According to the European Environment Agency, the year 2015 was the warmest on record to that point, with a series of heat waves from May to September resulted in high levels of tropospheric ozone. The implications of such a year on the human well-being and health are therefore of multiple nature and can be quantified referring to the exceedances of the corresponding thresholds. This work focused on the analysis of the May-September period of 2015 in the city of Milan (Italy) in terms of Mediterranean Outdoor Comfort Index (MOCI) and ozone concentrations, recorded by monitoring stations and modeled through the Weather Research and Forecasting model. Main findings show that thermo-hygrometric stress events (periods of at least six consecutive days characterized by daily maximum values of the MOCI higher than 0.5) are characterized by daily ozone higher than the guideline level of the World Health Organization (equal to 100 ?gm(-3)). This means that thermo-hygrometric stress conditions are added up to poor air quality conditions, with severe risks for human health. Moreover, a daily MOCI-daily ozone correlation coefficient equal to 0.6 was found for the whole period. The degree of correspondence between ozone events (defined according to the European Air Quality Directive) and MOCI events was also investigated pointing out that 86% and 95% of days during ozone events are correctly predicted by events of recorded and modeled MOCI respectively, with a corresponding false alarm rate of 3% and 9%.
Early adolescence (12-13 years old) is a critical but under-researched demographic for the formation of attitudes related to climate change. We address this important area by exploring adolescent views about climate change. This paper presents opinions collected from surveys of?463 1st-year secondary school students (12-13 years old) in public secondary schools in inner-urban centres in Austria and Australia on whether climate change is (1) something about which to worry, (2) caused by humans and (3) happening now. Eligible respondents in both countries showed similar levels of agreement that climate change was probably or definitely something we should (1) worry about (84.6% Austria, 89.1% Australia), which is significantly higher than either country’s adult population. Eligible respondents agreed that climate change probably or definitely is (2) caused by humans (75.6% Austria, 83.6% Australia) and that climate change is probably or definitely something that is (3) happening now (73.1% Austria, 87.5% Australia). Their response differed from the respective adult populations, but in opposite directions. Our results suggest that socio-cultural worldview may not have as much influence on this age group as it does on the respective adult populations and suggests that this age group would be receptive and ready for climate science education and engagement initiatives.
The aim of the study was to establish to what extent extreme thermal conditions have changed and how they affected mortality, and what conditions favor lower mortality rates or conversely, higher mortality rates. Heat/cold exposure was measured with the Universal Thermal Climate Index (UTCI). Daily mortality and meteorological data for 8 large Polish cities (Bia?ystok, Gda?sk, Kraków, Lublin, ?ód?, Pozna?, Warszawa, and Wroc?aw) in the period 1975-2014 were analyzed. Generalized additive models were used to investigate the relationship between UTCI and mortality, and TBATS models were used for the evaluation of time series UTCI data. Most of the cities experienced a clear and statistically significant at p???0.05 decrease in cold stress days of 0.8-3.3 days/year and an increase in the frequency of thermal heat stress days of 0.3-0.6 days/year until 1992-1994. There was a clear difference as regards the dependence of mortality on UTCI between cities located in the “cooler” eastern part of Poland and the “warmer” central and western parts. “Cool” cities were characterized by a clear thermal optimum, approx. in the range of 5-30 °C UTCI, changing slightly depending on cause of death, age, or sex. For UTCI over 32 °C, in most of the cities except Gda?sk and Lublin, the relative risk of death (RR) rose by 10 to 20%; for UTCI over 38 °C, RR rose to 25-30% in central Poland. An increase in mortality on cold stress days was noted mainly in the “cool” cities: RR of total mortality increased even by 9-19% under extreme cold stress.
Mosquitoes propagate many human diseases, some widespread and with no vaccines. The Ae. aegypti mosquito vector transmits Zika, Chikungunya, and Dengue viruses. Effective public health interventions to control the spread of these diseases and protect the population require models that explain the core environmental drivers of the vector population. Field campaigns are expensive, and data from meteorological sites that feed models with the required environmental data often lack detail. As a consequence, we explore temporal modeling of the population of Ae. aegypti mosquito vector species and environmental conditions- temperature, moisture, precipitation, and vegetation- have been shown to have significant effects. We use earth observation (EO) data as our source for estimating these biotic and abiotic environmental variables based on proxy features, namely: Normalized difference vegetation index, Normalized difference water index, Precipitation, and Land surface temperature. We obtained our response variable from field-collected mosquito population measured weekly using 791 mosquito traps in Vila Velha city, Brazil, for 36 weeks in 2017, and 40 weeks in 2018. Recent similar studies have used machine learning (ML) techniques for this task. However, these techniques are neither intuitive nor explainable from an operational point of view. As a result, we use a Generalized Linear Model (GLM) to model this relationship due to its fitness for count response variable modeling, its interpretability, and the ability to visualize the confidence intervals for all inferences. Also, to improve our model, we use the Akaike Information Criterion to select the most informative environmental features. Finally, we show how to improve the quality of the model by weighting our GLM. Our resulting weighted GLM compares well in quality with ML techniques: Random Forest and Support Vector Machines. These results provide an advancement with regards to qualitative and explainable epidemiological risk modeling in urban environments.
Epidemiological studies on the impact of determining environmental factors on human health have proved that temperature extremes and variability constitute mortality risk factors. However, few studies focus specifically on susceptible individuals living in Portuguese urban areas. This study aimed to estimate and assess the health burden of temperature-attributable mortality among age groups (0-64 years; 65-74 years; 75-84 years; and 85+ years) in Lisbon Metropolitan Area, from 1986-2015. Non-linear and delayed exposure-lag-response relationships between temperature and mortality were fitted with a distributed lag non-linear model (DLNM). In general, the adverse effects of cold and hot temperatures on mortality were greater in the older age groups, presenting a higher risk during the winter season. We found that, for all ages, 10.7% (95% CI: 9.3-12.1%) deaths were attributed to cold temperatures in the winter, and mostly due to moderately cold temperatures, 7.0% (95% CI: 6.2-7.8%), against extremely cold temperatures, 1.4% (95% CI: 0.9-1.8%). When stratified by age, people aged 85+ years were more burdened by cold temperatures (13.8%, 95% CI: 11.5-16.0%). However, for all ages, 5.6% of deaths (95% CI: 2.7-8.4%) can be attributed to hot temperatures. It was observed that the proportion of deaths attributed to exposure to extreme heat is higher than moderate heat. As with cold temperatures, people aged 85+ years are the most vulnerable age group to heat, 8.4% (95% CI: 3.9%, 2.7%), and mostly due to extreme heat, 1.3% (95% CI: 0.8-1.8%). These results provide new evidence on the health burdens associated with alert thresholds, and they can be used in early warning systems and adaptation plans.
Over the past decade, Brazil has experienced and continues to be impacted by extreme climate events. This study aims to evaluate the association between daily average temperature and mortality from respiratory disease among Brazilian elderlies. A daily time-series study between 2000 and 2017 in 27 Brazilian cities was conducted. Data outcomes were daily counts of deaths due to respiratory diseases in the elderly aged 60 or more. The exposure variable was the daily mean temperature from Copernicus ERA5-Land reanalysis. The association was estimated from a two-stage time series analysis method. We also calculated deaths attributable to heat and cold. The pooled exposure-response curve presented a J-shaped format. The exposure to extreme heat increased the risk of mortality by 27% (95% CI: 15-39%), while the exposure to extreme cold increased the risk of mortality by 16% (95% CI: 8-24%). The heterogeneity between cities was explained by city-specific mean temperature and temperature range. The fractions of deaths attributable to cold and heat were 4.7% (95% CI: 2.94-6.17%) and 2.8% (95% CI: 1.45-3.95%), respectively. Our results show a significant impact of non-optimal temperature on the respiratory health of elderlies living in Brazil. It may support proactive action implementation in cities that have critical temperature variations.
The application of green infrastructure presents an opportunity to mitigate rising temperatures using a multi-faceted ecosystems-based approach. A controlled field study in Toronto, Ontario, Canada, evaluates the impact of nature-based solutions on near surface air temperature regulation focusing on different applications of green infrastructure. A field campaign was undertaken over the course of two summers to measure the impact of green roofs, green walls, urban vegetation and forestry systems, and urban agriculture systems on near surface air temperature. This study demonstrates that multiple types of green infrastructure applications are beneficial in regulating near surface air temperature and are not limited to specific treatments. Widespread usage of green infrastructure could be a viable strategy to cool cities and improve urban climate.
Heat waves (HWs) and urban heat islands (UHIs) can potentially interact. The mechanisms behind their synergy are not fully disclosed. Starting from the localized UHI phenomenon, this study aims i) to reveal their associated impacts on human thermal comfort through three different definitions of HW events, based on air temperature (airT), wet-bulb globe temperature (WBGT) and human-perceived temperature (AppT) respectively, and ii) to understand the role of air moisture and wind. The analysis was conducted in four districts (NH, JD, MH and XJH) with different urban development patterns and geographic conditions, in the megacity of Shanghai with a subtropical humid climate. Results evidenced the localized interplay between HWs and UHIs. The results indicate that less urbanized districts were generally more sensitive to the synergies. JD district recorded the highest urban heat island intensity (UHII) amplification, regardless of the specific HW definition. Notably, during AppT-HWs, the increment was observed in terms of maximum (1.3 °C), daily average (0.8 °C), diurnal (0.4 °C) and nocturnal UHII (1.0 °C). Nevertheless, localized synergies between HWs and UHIs at different stations also exhibited some commonalities. Under airT-HW, the UHII was amplified throughout the day at all stations. Under WBGT-HW, diurnal UHII (especially at 11:00-17:00 LST) was consistently amplified at all stations. Under AppT-HW conditions, the nocturnal UHII was slightly amplified at all stations. Air moisture and wind alleviated the synergistic heat exacerbation to the benefit of thermal comfort. The extent depended on geographic condition, diurnal and nocturnal scenarios, temperature type and HW/normal conditions. Stronger HW-UHI synergies indicate the necessity to develop specific urban heat emergency response plans, able to capture and intervene on the underlying mechanisms. This study paves to way to their identification.
The short-term effects of ambient temperature on mortality have been widely investigated. However, the epidemiological evidence on the long-term effects of temperature on mortality is rare. In present study, we conducted a nationwide quasi-experimental design, which based on a variant of difference-in-differences (DID) approach, to examine the association between long-term exposure to ambient temperature and mortality risk in China, and to analyze the effect modification of population characteristics and socioeconomic status. Data on mortality were collected from 364 communities across China during 2006-2017, and environmental data were obtained for the same period. We estimated a 2.93 % (95 % CI: 2.68 %, 3.18 %) increase in mortality risk per 1 °C decreases in annual temperature, the greater effects were observed on respiratory diseases (5.16 %, 95 % CI: 4.53 %, 5.79 %) than cardiovascular diseases (3.43 %, 95 % CI: 3.06 %, 3.80 %), and on younger people (4.21 %, 95 % CI: 3.73 %, 4.68 %) than the elderly (2.36 %, 95 % CI: 2.06 %, 2.65 %). In seasonal analysis, per 1 °C decreases in average temperature was associated with 1.55 % (95 % CI: 1.23 %, 1.87 %), -0.53 % (95 % CI: -0.89 %, -0.16 %), 2.88 % (95 % CI: 2.45 %, 3.31 %) and 4.21 % (95 % CI: 3.98 %, 4.43 %) mortality change in spring, summer, autumn and winter, respectively. The effects of long-term temperature on total mortality were more pronounced among the communities with low urbanization, low education attainment, and low GDP per capita. In total, the decrease of average temperature in summer decreased mortality risk, while increased mortality risk in other seasons, and the associations were modified by demographic characteristics and socioeconomic status. Our findings suggest that populations with disadvantaged characteristics and socioeconomic status are vulnerable to long-term exposure of temperature, and targeted policies should be formulated to strengthen the response to the health threats of temperature exposure.
In the context of global climate change, far less is known about the impact of long-term temperature variability (TV), especially in developing countries. The current study aimed to estimate the effect of long-term TV on the incidence of cardiovascular disease (CVD) in China. A total of 23,721 individuals with a mean age of 56.15 years were enrolled at baseline from 2012 to 2016 and followed up during 2017-2019. TV was defined as the standard deviation of daily temperatures during survey years and was categorized into tertiles (lowest? 8.78 °C, middle = 8.78-10.07 °C, highest ? 10.07 °C). The Cox proportional hazards regression was used to estimate the multivariable-adjusted hazard ratio (HR) between TV and CVD. During the median follow-up of 4.65 years, we ascertained 836 cases of incident CVD. For per 1 °C increase in TV, there was a 6% increase of CVD (HR = 1.06 [95% confidence interval (CI): 1.01-1.11]). A significant positive trend was observed between CVD risk and increasing levels of TV compared to the lowest tertile [HR = 1.34 (95% CI: 1.13-1.59) for the medium tertile, HR = 1.72 (95% CI: 1.35-2.19) for the highest tertile, P(trend) < 0.001]. Exposure to high TV would lose 2.11 disease-free years for the population aged 35-65 years and 66 CVD cases (or 7.95% cases) could been attributable to TV higher than 8.11 °C in the current study. The current findings suggested that long-term TV was associated with a higher risk of CVD incidence, it is needed to reduce the TV-related adverse health effect.
Disaster planning for slow-onset city-wide shocks will be become increasingly necessary, particularly as cities face increasingly severe climate hazards. This paper provides unique insight into the disaster planning and management that was undertaken by the City of Cape Town government in response to its most severe hydrological drought on record. It describes how risk was understood and why decisions were made on key elements of the plan, including trigger points, risk prioritisation and mitigation, and the location and design of points of distribution of water rations for the public. Reflecting upon the authors’ experience and interviews with senior City officials who worked on the drought disaster planning and response, the paper extracts five key lessons learnt that have since been applied during the COVID-19 pandemic: (i) the need for cross-functional planning and response skills, (ii) the need for integrated, up-to-date and scale-appropriate data; (iii) the importance of scenario-based simulations, communication and rapid costing to enable the rapid scaling-up of a response; (iv) the value of being able to use outsourced expert capacity effectively; and (v) the application of previously used disaster management and planning experience to build resilience in cities. These lessons, captured in a visual framework, help reflect on capabilities required for responding to future city-scale disasters. The paper provides an informative case study for other cities and risk managers, and will be particularly useful for global South contexts that face drought and other slow-onset disasters, most recently illustrated by the COVID-19 pandemic.
Livability, resilience, and justice in cities are challenged by climate change and the historical legacies that together create disproportionate impacts on human communities. Urban green infrastructure has emerged as an important tool for climate change adaptation and resilience given their capacity to provide ecosystem services such as local temperature regulation, stormwater mitigation, and air purification. However, realizing the benefits of ecosystem services for climate adaptation depend on where they are locally supplied. Few studies have examined the potential spatial mismatches in supply and demand of urban ecosystem services, and even fewer have examined supply-demand mismatches as a potential environmental justice issue, such as when supply-demand mismatches disproportionately overlap with certain socio-demographic groups. We spatially analyzed demand for ecosystem services relevant for climate change adaptation and combined results with recent analysis of the supply of ecosystem services in New York City (NYC). By quantifying the relative mismatch between supply and demand of ecosystem services across the city we were able to identify spatial hot- and coldspots of supply-demand mismatch. Hotspots are spatial clusters of census blocks with a higher mismatch and coldspots are clusters with lower mismatch values than their surrounding blocks. The distribution of mismatch hot- and coldspots was then compared to the spatial distribution of socio-demographic groups. Results reveal distributional environmental injustice of access to the climate-regulating benefits of ecosystem services provided by urban green infrastructure in NYC. Analyses show that areas with lower supply-demand mismatch tend to be populated by a larger proportion of white residents with higher median incomes, and areas with high mismatch values have lower incomes and a higher proportion of people of color. We suggest that urban policy and planning should ensure that investments in “nature-based” solutions such as through urban green infrastructure for climate change adaptation do not reinforce or exacerbate potentially existing environmental injustices.
The rising temperature makes the weather becoming more extreme. Understanding how extreme hot temperature-heat wave events (HWEs)-are likely to alter individual heat exposure and sensitivity is crucial for developing climate change mitigation and adaptation strategies. Despite the importance, little is known about the real-time impacts of HWEs on individual daily life in developing nations, like China. To fill this gap, we adopt over 1544 thousand Weibo (Chinese Twitter) social media data, coupled with meteorological conditions people face when posting, to assess the heat exposure and people’s sensitivity to HWEs across 31 mega-cities in China. The results show the hotspot of Weibo heat is coincident with the extremely hot temperature, with a correlation of 0.7 (p < 0.05). The intensities, frequencies, and durations of HWEs in both geographical and social media space have high spatial heterogeneity. Its spatial variation can be explained by the type of climate zone and the unique geographical environment. The cities with extreme hot weather are more likely to adapt to the heatwave and less sensitivity to HWEs. The proposed framework, which integrates the real-time social media semantic analysis, statistical method, and spatial techniques, provides a new paradigm to assess the HWEs exposure and sensitivity analysis in China.
Home health care (HHC) services are of vital importance for the health care system of many countries. Further increases in their demand must be expected and with it grows the need to sustain these services in times of disasters. Existing risk assessment tools and guides support HHC service providers to secure their services. However, they do not provide insights on interdependencies of complex systems like HHC. Causal-Loop-Diagrams (CLDs) are generated to visualize the impacts of epidemics, blackouts, heatwaves, and floods on the HHC system. CLDs help to understand the system design as well as cascading effects. Additionally, they simplify the process of identifying points of action in order to mitigate the impacts of disasters. In a case study, the course of the COVID-19 pandemic and its effects on HHC in Austria in spring 2020 are shown. A decision support system (DSS) to support the daily scheduling of HHC nurses is presented and applied to numerically analyze the impacts of the COVID-19 pandemic, using real-world data from a HHC service provider in Vienna. The DSS is based on a Tabu Search metaheuristic that specifically aims to deal with the peculiarities of urban regions. Various transport modes are considered, including time-dependent public transport.
BACKGROUND: Short-term exposure to PM(2.5) has been widely associated with human morbidity and mortality. However, most up-to-date research was conducted at a daily timescale, neglecting the intra-day variations in both exposure and outcome. As an important fraction in PM(2.5), PM(1) has not been investigated about the very acute effects within a few hours. METHODS: Hourly data for size-specific PMs (i.e., PM(1), PM(2.5), and PM(10)), all-cause emergency department (ED) visits and meteorological factors were collected from Guangzhou, China, 2015-2016. A time-stratified case-crossover design with conditional logistic regression analysis was performed to evaluate the hourly association between size-specific PMs and ED visits, adjusting for hourly mean temperature and relative humidity. Subgroup analyses stratified by age, sex and season were conducted to identify potential effect modifiers. RESULTS: A total of 292,743 cases of ED visits were included. The effects of size-specific PMs exhibited highly similar lag patterns, wherein estimated odds ratio (OR) experienced a slight rise from lag 0-3 to 4-6 h and subsequently attenuated to null along with the extension of lag periods. In comparison with PM(2.5) and PM(10), PM(1) induced slightly larger effects on ED visits. At lag 0-3 h, for instance, ED visits increased by 1.49% (95% confidence interval: 1.18-1.79%), 1.39% (1.12-1.66%) and 1.18% (0.97-1.40%) associated with a 10-?g/m(3) rise, respectively, in PM(1), PM(2.5) and PM(10). We have detected a significant effect modification by season, with larger PM(1)-associated OR during the cold months (1.017, 1.013 to 1.021) compared with the warm months (1.010, 1.005 to 1.015). CONCLUSIONS: Our study provided brand-new evidence regarding the adverse impact of PM(1) exposure on human health within several hours. PM-associated effects were significantly more potent during the cold months. These findings may aid health policy-makers in establishing hourly air quality standards and optimizing the allocation of emergency medical resources.
Cities are experiencing more and more frequent extreme heat events in hot summers in the context of rising global temperatures. A precise understanding of the spatial distribution of the human outdoor heat exposure across neighborhoods in cities is of great importance for urban heat management. Different from remote sensing based the land surface temperature, this study calculated the mean radiant temperature, which is more objective to indicate human heat stress, to study the spatial distribution of human outdoor heat exposure in Philadelphia, Pennsylvania. The SOLWEIG (SOlar and LongWave Environmental Irradiance Geometry) model was applied to estimate the mean radiant temperature based on the high-resolution urban 3D model and meteorological data. This study further examined the spatial distributions of heat exposure levels across neighborhoods of different groups in Philadelphia. Results show that there is no significant disparity in terms of outdoor heat exposure levels for different racial/ethnic groups in Philadelphia. Generally, the elderly, who usually are more vulnerable to extreme heat, tend to live in neighborhoods with less outdoor heat exposure in summer (p<0.001). The higherincome people tend to live in thermally more comfortable neighborhoods (p<0.001). The study provides a precise understanding of the heat distribution across neighborhoods, which would further help to develop strategies to allocate resources to the most needed neighborhoods to maximumly mitigate the negative impact of urban heat.
Urban heat island (UHI) and cool island (UCI) effects are well-known and prevalent in cities worldwide. An increasing trend of extreme heat events has been observed over the last few decades and is expected to continue in the foreseeable future. In this study, warm periods (May to September) of 2000-2018 were examined to acquire a comprehensive understanding of the UHI and UCI characteristics for the case study of Hong Kong, China. Twenty-two weather stations in Hong Kong were classified into four categories, namely urban, urban oasis, suburban, and rural, with reference to the local climate zone (LCZ) scheme, to analyze UHI and UCI phenomena during extreme heat and non-extreme heat situations. One representative type of extreme heat events was considered in this study: three consecutive hot nights with two very hot days in between (2D3N). Results show that both the UHI and UCI effects are exacerbated during extreme heat events. Using the concept of the UHI degree hours (UHIdh) and UCI degree hours (UCIdh), their spatial patterns in Hong Kong during extreme heat and non-extreme heat situations were mapped based on multiple linear regression models. It is found that the predictor variable – windward/leeward index is a significant influential factor of both UHIdh and UCIdh during extreme heat events. The resulting UHIdh and UCIdh maps not only enhance our understanding on the spatial pattern and characteristics of the UHI and UCI during extreme heat events, but could also serve as a useful reference in climate change adaptation, heat-health risk detection, cooling-energy estimation and policy making.
Increasing resilience to natural hazards and climate change is critical for achieving many Sustainable Development Goals (SDGs). In recent decades, China has experienced rapid economic development and became the second-largest economy in the world. This rapid economic expansion has led to large-scale changes in terrestrial (e.g., land use and land cover changes), aquatic (e.g., construction of reservoirs and artificial wetlands) and marine (e.g., land reclamation) environments across the country. Together with climate change, these changes may significantly influence flood risk and, in turn, compromise SDG achievements. The Luanhe River Basin (LRB) is one of the most afforested basins in North China and has undergone significant urbanisation and land use change since the 1950s. However, basin-wide flood risk assessment under different development scenarios has not been considered, although this is critically important to inform policy-making to manage the synergies and trade-offs between the SDGs and support long-term sustainable development. Using mainly open data, this paper introduces a new framework for systematically assessing flood risk under different social and economic development scenarios. A series of model simulations are performed to investigate the flood risk under different land use change scenarios projected to 2030 to reflect different development strategies. The results are systematically analysed and compared with the baseline simulation based on the current land use and climate conditions. Further investigations are also provided to consider the impact of climate change and the construction of dams and reservoirs. The results potentially provide important guidance to inform future development strategies to maximise the synergies and minimise the trade-offs between various SDGs in LRB.
Medical statistics collected by WHO indicates that dengue fever is still ravaging developing regions with climates befitting mosquito breeding amidst moderate-to-weak health systems. This work initiates a study over 2009-2017 panel data of dengue incidences and meteorological factors in Jakarta, Indonesia to bear particular understanding. Using a panel random-effect model joined by the pooled estimator, we show positively significant relationships between the incidence level and meteorological factors. We ideate a clustering strategy to decompose the meteorological datasets into several more datasets such that more explanatory variables are present and the zero-inflated problem from the incidence data can be handled properly. The resulting new model gives good agreement with the incidence data accompanied by a high coefficient of determination and normal zero-mean error in the prediction window. A risk measure is characterized from a one-step vector autoregression model relying solely on the incidence data and a threshold incidence level separating the low-risk and high-risk regime. Its magnitude greater than unity and the weak stochastic convergence to the endemic equilibrium mark a persistent cyclicality of the disease in all the five districts in Jakarta. Moreover, all districts are shown to co-vary profoundly positively in terms of epidemics occurrence, both generally and timely. We also show that the peak of incidences propagates almost periodically every year on the districts with the most to the least recurrence: Central, South, West, East, and North Jakarta.
PM(2.5) pollution has adverse health effects on humans. Urbanization and long-term meteorological variations play important roles in influencing the PM(2.5) concentration and its associated health effects. Our results indicate that the urbanization process can enhance the PM(2.5) concentration globally. The PM(2.5)-caused mortality density (deaths/100 km(2)) is also positively correlated with the urbanization degree in both developed and developing countries. The results from machine learning technique revealed that the meteorology-driven variation in PM(2.5)-caused health burden has increased with the increase in the urbanization degree from 1980 to 2018, suggesting that residents living in urban areas are more vulnerable to experiencing unfavorable meteorological conditions (e.g. low wind speed and planetary boundary layer height). The maximum difference in PM(2.5)-caused mortality due to the variation in annual meteorological conditions (between 2013 and 1986) was 270 600 (196 800-317 900). Our findings indicate an urgent need to understand the driving force behind the appearance of unfavorable meteorological situations and propose suitable climate mitigation measures.
From 21 to 22 July 2012, Beijing and its surrounding areas suffered from an extreme precipitation event that was unprecedented relative to the past 61 years, and the event caused 79 deaths and reported direct economic losses of 11.64 billion Yuan. However, current models have difficulty to simulate the spatial and temporal distribution characteristics of such events. Therefore, improved simulations of these extreme precipitation processes are needed. In this study, nudging methods, including grid nudging (GN) and spectral nudging (SN), and more accurate surface type data retrieved from remote sensing were used in the Weather Research and Forecasting (WRF) model to simulate this extreme precipitation case. When the default city underlay surface of the WRF model was replaced by a more accurate urban surface (NU), the precipitation intensity could be better simulated, but the peak moment of precipitation seriously lagged. Although the peak precipitation intensity simulated by the GN experiment was weak, the simulated precipitation time was basically consistent with the observations. Using GN in only the outside domain could better simulate precipitation peaks, while using GN in both the inside and outside domains could better simulate the spatial distribution characteristics of precipitation. Additionally, the precipitation from GN could be better simulated than that from SN. Overall, the two nudging methods could contribute to better simulations of this case because the nudging methods could improve the simulations of 500-hPa geopotential height, 850-hPa water vapor transport, and low-level weather systems, which are the key factors in adjusting the spatial and temporal distributions of precipitation. This study is the basis for the investigation of the mechanism and attribution of extreme precipitation processes, and the results are of great significance for promoting understanding of and mitigating disasters caused by extreme precipitation.
Urban resilience is a major indicator of a city’s sustainability. Climate change increases the frequency and intensity of extreme weather events, thereby increasing uncertainty and disaster risk. A city’s capacity to cope with climatic risks can be improved by developing resilience. In China, heavy rainfall is the most frequent and costly extreme weather event. We conducted a comparative case study on Beijing’s extraordinary 7.21 rainstorm disaster in 2012 and the 7.20 rainstorm in 2016. Taken generic resilience and specific resilience as the analytical framework, we found that generic resilience is mainly determined by the socio-economic development level and geography of each district; while the combination of engineering and non-engineering adaptive measures after 2012 disaster has improved the specific resilience to rainstorm disaster, which contributed a good performance in the 2016 rainstorm. As a megacity in China, Beijing is a representative case that provides guidance for other cities to improve their urban resilience to rainstorm disasters.
Hydro-meteorological risks are a growing issue for societies, economies and environments around the world. An effective, sustainable response to such risks and their future uncertainty requires a paradigm shift in our research and practical efforts. In this respect, Nature-Based Solutions (NBSs) offer the potential to achieve a more effective and flexible response to hydro-meteorological risks while also enhancing human well-being and biodiversity. The present paper describes a new methodology that incorporates stakeholders’ preferences into a multi-criteria analysis framework, as part of a tool for selecting risk mitigation measures. The methodology has been applied to Tamnava river basin in Serbia and Nangang river basin in Taiwan within the EC-funded RECONECT project. The results highlight the importance of involving stakeholders in the early stages of projects in order to achieve successful implementation of NBSs. The methodology can assist decision-makers in formulating desirable benefits and co-benefits and can enable a systematic and transparent NBSs planning process.
Most studies focused on the temporal trend of mortality risk associated with temperature exposure. The relative role of heat, cold, and temperature variation (TV) on morbidity and its temporal trends are explored insufficiently. This study aims to investigate the temporal trends of emergency ambulance dispatch (EAD) risk and the attributable burden of heat, cold, and hourly temperature variation (HTV). We collected time-series data of daily EAD and ambient temperature in Shenzhen from 2010 to 2017. HTV was calculated as the standard deviation of the hourly temperatures between 2 consecutive days. Quasi-Poisson generalized additive models (GAM) with a time-varying distributed lag nonlinear model (DLNM) were applied to examine temporal trends of the HTV-, heat-, and cold-EAD association. The temporal variation of the attributable fraction (AF%) and attributable number (AN) for different temperature exposures was also calculated. The largest RR was observed in extreme cold [1.30 (95% CI: 1.18, 1.43)] and moderate cold [1.25 (95% CI: 1.17, 1.34)]. Significant increasing trends in HTV-related effects and burden were observed, especially for the extreme HTV effects (P for interaction < 0.05). Decreasing trends were observed in the heat-related effect and burden, though it showed no significance (P for interaction = 0.46). There was no clear change pattern of cold-related effects and burdens. Overall, the three temperature exposure caused 13.7% of EAD, of which 4.1%, 4.3%, and 5.3% were attributed to HTV, heat, and cold, respectively. All the temperature indexes in this study, especially the cold effect, are responsible for the increased risk of EAD. People have become more susceptible to HTV over the recent decade. However, there is no clear evidence to support the temporal change of the population's susceptibility to heat and cold. Thus, in addition to heat and cold, the emergency ambulance service department should pay more attention to HTV under climate change.
With the increasing awareness of the risks and impacts of climate change, scholars tend to pay more attention to the applications of indicators, which access the effectiveness of climate change adaptation. This study aims to evaluate the overall progress of climate change adaptation in China during 2010-2018 in a quantitative manner. The Index for Climate Change Adaptation in China (ICCAC) has been thus developed by adopting the analytic hierarchy process weighting and expert scoring method. Namely, ICCAC is composed of national climate change impacts, adaptation actions in key sectors, adaptation progress in key sectors, and the national adaptation policy framework. Overall, the ICCAC and its four sub-indexes increased significantly from 2010 to 2018, on a yearly-basis. Each sub-index implied that the socio-economic impacts caused by climate change in China have been alleviated gradually; specifically, the mainstream endeavor of key sectors has witnessed remarkable progress, however, it is worth noting that the gap between individual adaptation actions and policies still exists; the implementation effect of policies in key sectors is not as affluent as that of actions; the current adaptation endeavor in key areas is still closely related to the mainstream business of corresponding competent ministries rather than adaptation-aimed actions; the national adaptation policy framework has been primarily formed, but there are still some deficiencies. As a result, the gap in China’s adaptation process could be mainly manifested in the following five aspects: i) adaptation effectiveness assessment in forestry and urban infrastructure is urgently needed; ii) policies in marine and water resources sectors need structural reforms; iii) evaluation criteria for national adaptation are not necessarily sufficient; iv) the improvement of adaptive management efficiency has stagnated recently; and v) the adaptation works of relevant Ministries should be coordinated and put forward the corresponding strategies. Finally, this study presents four proposals: conducting an evaluation of adaptation actions in all key sectors, integrating climate change impacts into sectoral planning decisions, launching concrete action plans for adaptation, establishing a complete policy framework on adaptation.
Heat exposure of a population is often estimated by applying temperatures from outdoor monitoring stations. However, this can lead to exposure misclassification if residents do not live close to the monitoring station and temperature varies over small spatial scales due to land use/built environment variability, or if residents generally spend more time indoors than outdoors. Here, we compare summertime temperatures measured inside 145 homes in low-income households in Baltimore city with temperatures from the National Weather Service weather station in Baltimore. There is a large variation in indoor temperatures, with daily-mean indoor temperatures varying from 10 °C lower to 10 °C higher than outdoor temperatures. Furthermore, there is only a weak association between the indoor and outdoor temperatures across all houses, indicating that the outdoor temperature is not a good predictor of the indoor temperature for the residences sampled. It is shown that much of the variation is due to differences in the availability of air conditioning (AC). Houses with central AC are generally cooler than outdoors (median difference of -?3.4 °C) while those with no AC are generally warmer (median difference of 1.4 °C). For the collection of houses with central or room AC, there is essentially no relationship between indoor and outdoor temperatures, but for the subset of houses with no AC, there is a weak relationship (correlation coefficient of 0.36). The results presented here suggest future epidemiological studies of indoor exposure to heat would benefit from information on the availability of AC within the population.
The aim of this study was to compare airborne levels of Phl p 1 and Phl p 5, with Poaceae pollen concentrations inside and outside of the pollen season, and to evaluate their association with symptoms in grass allergic patients and the influence of climate and pollution. The Hirst and the Burkard Cyclone samplers were used for pollen and allergen quantification, respectively. The sampling period ran from 23 March 2009 to 27 July 2010. Twenty-three patients with seasonal allergic asthma and rhinitis used an electronic symptom card. The aerosol was extracted and quantified for Phl p 1 and Phl p 5 content. Descriptive statistics, non-parametric paired contrast of Wilcoxon, Spearman’s correlations, and a categorical principal component analysis (CatPCA) were carried out. Significant variations in pollen, aeroallergen levels, pollen allergen potency, and symptoms score were observed in this study. Phl p 5 pollen allergen potency was higher at the beginning of the 2010 grass pollen season. Presence of Phl p 1 outside the pollen season with positive O(3) correlation was clinically relevant. 45.5% of the variance was explained by two dimensions in the CatPCA analysis, showing the symptom relationships dissociated in two dimensions. In the first one, the more important relationship was with grass pollen grains concentration and Phl p 5 and to a lesser extent with Phl p 1 and levels of NO(2) and O(3), and in the second dimension, symptoms were associated with humidity and SO(2). Clinically relevant out-season Phl p 1 was found with a positive O(3) correlation. The effect of climate and pollution may have contributed to the higher seasonal allergic rhinitis symptom score recorded in 2009.
Particulate matter (PM) has been occurring regularly during the dry season in the upper north of Thailand including Lamphun Province that might be influenced by various factors including climatologic and other pollutants. This paper aims to investigate the climatologic and gaseous factors influencing the occurrence of PM(10) concentration using Pollution Control Department (PCD) data. The secondary data of 2009 to 2017 obtained from the PCD was used for analysis. We used descriptive statistics, Pearson’s correlation coefficient, multiple regression and graphic presentation using R program (R packages of ‘open air’ and ‘ncdf4’) and Microsoft Excel Spreadsheet®. In addition, the periodic measurement of PM(2.5) and PM(10) were investigated to determine the ratio of PM(2.5)/PM(10). The results indicated that haze episodes (daily PM(10) concentration always over the PCD standard) normally occur during the dry season from February to April. The maximum concentration was always found in March. The PM(10) concentration was negatively associated with relative humidity and temperature while the PM(10) concentration showed a strongly positive association with CO and NO(2) concentration with correlation values of 0.70 and 0.57, respectively. Furthermore, we found CO and PM(10) concentration was associated with ozone concentration. This finding will benefit local communities and the public health sector to provide a warning system for preparation and response plans to react to PM(10) episodes in their responsible areas.
The International Agency for Research on Cancer (IARC) classifies benzene in group 1 (carcinogenic to humans). Particulate matter (PM) has recently also been classified in this category. This was an advance toward prioritizing the monitoring of particles in urban areas. The aim of the present study was to assess levels of PM(2.5) and BTEX (benzene, toluene, ethylbenzene, and xylene), the influence of meteorological variables, the planetary boundary layer (PBL), and urban variables as well as risks to human health in the city of Fortaleza, Brazil, in the wet and dry periods. BTEX compounds were sampled using the 1501 method of NIOSH and determined by GC-HS-PID/FID. PM(2.5) was monitored using an air sampling pump with a filter holder and determined by the gravimetric method. Average concentrations of BTEX ranged from 1.6 to 45.5 ?g m(-3), with higher values in the wet period, which may be explained by the fact that annual distribution is influenced by meteorological variables and the PBL. PM(2.5) levels ranged from 4.12 to 33.0 ?g m(-3) and 4.18 to 86.58 ?g m(-3) in the dry and wet periods, respectively. No seasonal pattern was found for PM(2.5), probably due to the influence of meteorological variables, the PBL, and urban variables. Cancer risk ranged from 2.46E(-04) to 4.71E(-03) and 1.72E(-04) to 2.01E(-03) for benzene and from 3.07E(-06) to 7.04E(-05) and 3.08E(-06) to 2.85E(-05) for PM(2.5) in the wet and dry periods, respectively. Cancer risk values for benzene were above the acceptable limit established by the international regulatory agency in both the dry and wet periods. The results obtained of the noncarcinogenic risks for the compounds toluene, ethylbenzene, and xylene were within the limits of acceptability. The findings also showed that the risk related to PM is always greater among smokers than nonsmokers.
Achieving environmental sustainability by improving the urban microclimate is a key principle in mitigating the urban heat island (UHI) effect. This study aimed to (a) investigate the outdoor thermal comfort by establishing Heat Index (HI) values to identify thermal hot spots and (b) model green infrastructure possibilities to alleviate UHI in Colombo urban metropolitan in Sri Lanka using ENVImet climate model. Daytime temperature and humidity values of 14 urban locations were collected to determine HI to recognize thermal urban hotspots in Colombo area. A pretested comprehensive random-stratified questionnaire survey has been conducted to appraise the thermal discernment of the general public. ENVImet microclimate model was accompanied to test the temperature reduction levels in different bioclimatic green infrastructure scenarios [Two belts (R-1), three belts (R-2), four belts (R-3), five belts (R-4)] in the selected study site. Five sites (Borella, Colombo Fort, Maradana, Wellawaththa, Liberty junction) were identified as thermal hotspots in Colombo metropolitan. HI values were fluctuated within 33.82-40.35 degrees C range and the highest average day time HI value was observed at Maradana (40.35 degrees C) and the lowest HI was observed at Thummulla (33.82 degrees C). Survey results revealed that 89.3% people are affected with thermal uncomfortability and 5% were affected with heat-related skin diseases. Inserting trees into curbsides (R-4) reduced temperature remarkably by 2.07 degrees C in the urban metropolitan. Therefore, the proposed green infrastructure scenario has proved to be the most suitable way to improve the thermal comfort conditions of urban environment, as it can reduce the UHI effects.
The aim of this interdisciplinary study is to assess the heat risk for Bratislava. The following layers were created to compute the risk index: the hazard layer of air temperature, a mitigation layer of tree vegetation, an exposure layer of population and a vulnerability layer of individuals over 65 years of age. The MUKLIMO_3 model was used to evaluate the field of mean surface air temperature at 9 PM during selected days of the summer heat wave in August 2018. The tree vegetation layer, in the form of percentage per grid cell, was derived from Sentinel-2 satellite data. Population density data are based on mobile positioning data, and elderly population data are based on a gridded database from the statistical census. Input layers were unified into a resolution of 500 × 500 m, and the heat risk index was calculated by summation of the weighted input layers. The results reflect the variability of the population and the elderly population within the city, as well as the variability of the temperature field, which is caused by the joint effect of an urban heat island and topography. The highest values of risk index occur within the broader city centre, with specific hot spots at several places.
As the world’s population is expected to be over 2/3rd urban by 2050, climate action in cities is a growing area of interest in the inter-disciplines of development policy, disaster mitigation and environmental governance. The climate impacts are expected to be quite severe in the developing world, given its urban societies are densely packed, vastly exposed to natural elements while possessing limited capabilities. There is a notable ambiguity and complexity that inhibits a methodical approach in identifying urban resilience measures. The complexity is due to intersection of large number of distinct variables in climate geoscience (precipitation and temperature anomalies at different locations, RCPs, timeline), adaptation alternatives (approach, priority, intervention level) and urban governance (functional mandate, institutional capacity, and plans & policies). This research examines how disparate and complex knowledge and information in these inter-disciplines can be processed for systematic ‘negotiation’ to situate, ground and operationalize resilience in cities. With India as a case, we test this by simulating mid-term and long-run climate scenarios (2050 & 2080) to map regional climate impacts that shows escalation in the intensity of climate events like heat waves, urban flooding, landslides and sea level rise. We draw on suitable adaptation measures for five key urban sectors- water, infrastructure (including energy), building, urban planning, health and conclude a sleuth of climate resilience building measures for policy application through national/ state policies, local urban plans and preparation of city resilience strategy, as well as advance the research on ‘negotiated resilience’ in urban areas.
The excessively warm weather, especially in cities, can lead to several adverse impacts, including heat-related mortality, becoming an increasingly important public health issue. Previous studies on heat-related mortality have assessed risk factors at the municipal scale, missing the intra-urban variability in heat risk and vulnerability. The knowledge of the spatial intra-variability can help to design spatially targeted measures to better protect citizens’ health. Through hot spot analysis, we identified the neighbourhood-scale spatial pattern of heat-related cardiorespiratory mortality in the elderly, during the yearly warmest five months of a three years period. Potential associations between spatial variability in heat-related mortality and several independent factors in each neighbourhood were investigated and their predictions. Two approaches were adopted: one is eminently statistical, using Generalized Linear Models (GLM) and another using Geographically Weighted Regression (GWR). This new recent regression technique is increasing in international attention on spatial modelling. The spatial model explains about 60% of the spatial variations in elderly’s heat-related cardiorespiratory mortality. The two-analyses produced an overlapping set of predictor variables, with emphasis on the elderly, vegetation cover and employment. The results also show that the areas where heat-related mortality is high, are also the areas where the number of deaths is higher than expected. These neighbourhoods should be considered as the most vulnerable to heat-related mortality. We concluded that studying human health outcomes at neighbourhood-scale is relevant for public health heat-related plans. Essential suggestions are provided to decision-making support and city planners designing strategies to reduce heat-related mortality.
Human health vulnerability (HHV) to different climate change-related phenomena, that is, summer heat extremes, is related to the exposure, sensitivity, and adaptive capacity of the affected entities. The current research is an empirical regional assessment of the human health effects of summer heat extremes in the Romania-Bulgarian Danube floodplain Calafat-Vidin-Turnu Magurele-Nikopol (CV-TMN) sector. The external biophysical and socioeconomic factors that shape the vulnerability are supported by the climate approach. The research relies on processing meteorological data from the most representative climate stations in the study area based on which some indicators-significant for measuring the impact on human health-were computed (e.g., number of extremely hot days, number of tropical days, number of tropical nights) and integrated into a composite summer heat extremes index (SHEI). To assess HHV to summer heat extremes, the vulnerability framework was completed by the internal socioeconomic factors revealed by the characteristics of the population living in urban and rural settlements in terms of demographic, health provisions, and quality of indoor living spaces. Finally, the authors computed the index of human health vulnerability to summer heat extremes (HHVI) as the Hull Score at the level of territorial local administrative units.
Difficulties in controlling the effects of outdoor thermal environment on the human body are attracting considerable research attention. This study investigated the outdoor thermal comfort of urban pedestrians by assessing their perceptions of the tropical, micrometeorological, and physical conditions via a questionnaire survey. Evaluation of the outdoor thermal comfort involved pedestrians performing various physical activities (sitting, walking, and standing) in outdoor and semi-outdoor spaces where the data collection of air temperature, globe temperature, relative humidity, wind speed, solar radiation, metabolic activity, and clothing insulation data was done simultaneously. A total of 1011 participants were interviewed, and the micrometeorological data were recorded under outdoor and semi-outdoor conditions at two Malaysian university campuses. The neutral temperatures obtained which were 28.1 °C and 30.8 °C were within the biothermal acceptable ranges of 24-34 °C and 26-33 °C of the PET thermal sensation ranges for the outdoor and semi-outdoor conditions, respectively. Additionally, the participants’ thermal sensation and preference votes were highly correlated with the PET and strongly related to air and mean radiant temperatures. The findings demonstrated the influence of individuals’ thermal adaptation on the outdoor thermal comfort levels. This knowledge could be useful in the planning and designing of outdoor environments in hot and humid regions to create better thermal environments.
Climate change-induced extreme weather events have been at their worst increase in the past decade (2010-2020) across Africa and globally. This has proved disruptive to global socio-economic activities. One of the challenges that has been faced in this regard is the increased coastal flooding of cities. This study examined the trends and impacts of coastal flooding in the Western Cape province of South Africa. Making use of archival climate data and primary data from key informants and field observations, it emerged that there is a statistically significant increase in the frequency of flooding and consequent human and economic losses from such in the coastal cities of the province. Flooding in urban areas of the Western Cape is a factor of human and natural factors ranging from extreme rainfall, usually caused by persistent cut off-lows, midlatitude cyclones, cold fronts and intense storms. Such floods become compounded by poor drainage caused by vegetative overgrowth on waterways and land pollution that can be traced to poor drainage maintenance. Clogging of waterways and drainage systems enhances the risk of flooding. Increased urbanisation, overpopulation in some areas and non-adherence to environmental laws results in both the affluent and poor settling on vulnerable ecosystems. These include coastal areas, estuaries, and waterways, and this worsens the risk of flooding. The study recommends a comprehensive approach to deal with factors that increase the risk of flooding as informed by the provisions of both the Sustainable Development Goals framework and the Sendai Framework for Disaster Risk Reduction 2015-2030 in a bid to de-risking human settlement in South Africa.
The world’s most important mosquito vector of viruses, Aedes aegypti, is found around the world in tropical, subtropical and even some temperate locations. While climate change may limit populations of Ae. aegypti in some regions, increasing temperatures will likely expand its territory thus increasing risk of human exposure to arboviruses in places like Europe, Northern Australia and North America, among many others. Most studies of Ae. aegypti biology and virus transmission focus on locations with high endemicity or severe outbreaks of human amplified urban arboviruses, such as dengue, Zika, and chikungunya viruses, but rarely on areas at the margins of endemicity. The objective in this study is to explore previously published global patterns in the environmental suitability for Ae. aegypti and dengue virus to reveal deviations in the probability of the vector and human disease occurring. We developed a map showing one end of the gradient being higher suitability of Ae. aegypti with low suitability of dengue and the other end of the spectrum being equal and higher environmental suitability for both Ae. aegypti and dengue. The regions of the world with Ae. aegypti environmental suitability and no endemic dengue transmission exhibits a phenomenon we term ‘aegyptism without arbovirus’. We then tested what environmental and socioeconomic variables influence this deviation map revealing a significant association with human population density, suggesting that locations with lower human population density were more likely to have a higher probability of aegyptism without arbovirus. Characterizing regions of the world with established populations of Ae. aegypti but little to no autochthonous transmission of human-amplified arboviruses is an important step in understanding and achieving aegyptism without arbovirus.
Climate change driven increases in the frequency of extreme heat events (EHE) and extreme precipitation events (EPE) are contributing to both infectious and non-infectious disease burden, particularly in urban city centers. While the share of urban populations continues to grow, a comprehensive assessment of populations impacted by these threats is lacking. Using data from weather stations, climate models, and urban population growth during 1980-2017, here, we show that the concurrent rise in the frequency of EHE, EPE, and urban populations has resulted in over 500% increases in individuals exposed to EHE and EPE in the 150 most populated cities of the world. Since most of the population increases over the next several decades are projected to take place in city centers within low- and middle-income countries, skillful early warnings and community specific response strategies are urgently needed to minimize public health impacts and associated costs to the global economy.
Proposed ways of improving adaptation to climate change have most often been supported by narrowly framed and separate analysis. This article investigates how different levels of vulnerability and resilience interplay with adaptation to extreme temperatures, what is the nature of these relationships and whether lower vulnerability and higher resilience contribute to increased adaptation. This article explores the governance implications of a project that, unlike other, brings together vulnerability, resilience and adaptation assessments. The project has made significant advances in addressing the current deficit integrated assessments for shaping governance propositions. Such propositions argue that the diverse levels of vulnerability and resilience convey important bases for (1) targeting at-risk older individuals; (2) developing vulnerability reduction actions; (3) resilience building actions; and (4) understanding ‘success cases’ and learn from them for developing appropriate policy measures. Taken together, these propositions offer a social, psychological and health framework not simply for governing extreme temperatures but for governing responses to climate change at large.
The effects of meteorological factors on health outcomes have gained popularity due to climate change, resulting in a general rise in temperature and abnormal climatic extremes. Instead of the conventional cross-sectional analysis that focuses on the association between a predictor and the single dependent variable, the distributed lag non-linear model (DLNM) has been widely adopted to examine the effect of multiple lag environmental factors health outcome. We propose several novel strategies to model mortality with the effects of distributed lag temperature measures and the delayed effect of mortality. Several attempts are derived by various statistical concepts, such as summation, autoregressive, principal component analysis, baseline adjustment, and modeling the offset in the DLNM. Five strategies are evaluated by simulation studies based on permutation techniques. The longitudinal climate and daily mortality data in Taipei, Taiwan, from 2012 to 2016 were implemented to generate the null distribution. According to simulation results, only one strategy, named MV(DLNM), could yield valid type I errors, while the other four strategies demonstrated much more inflated type I errors. With a real-life application, the MV(DLNM) that incorporates both the current and lag mortalities revealed a more significant association than the conventional model that only fits the current mortality. The results suggest that, in public health or environmental research, not only the exposure may post a delayed effect but also the outcome of interest could provide the lag association signals. The joint modeling of the lag exposure and the delayed outcome enhances the power to discover such a complex association structure. The new approach MV(DLNM) models lag outcomes within 10 days and lag exposures up to 1 month and provide valid results.
BACKGROUND: Acute coronary syndrome is a disease with high prevalence and high mortality. Exposure to heat or cold increases the risks of myocardial infarction significantly. Gender-specific effects of this have not yet been examined. Our goal was to determine whether extreme weather conditions, which become more and more frequent, are gender-specific risk factors for myocardial infarction, in order to help provide faster diagnosis and revascularization therapy for patients. METHODS: We analysed the incidence of ST-elevation myocardial infarction (STEMI) in a large urban area over a 65-months period in a cohort study. A day was the unit of analysis. Incidence rate ratios (IRR) with Poisson regression models were calculated. All patients with STEMI on Saturdays and Sundays were included. Gender, high or low perceived temperatures (PT), a function of temperature, wind speed and humidity, and meteorological cold and heat warnings by the Austrian Central Institute for Meteorology and Geodynamics (ZAMG) were considered as risk factors. RESULTS: During the 562 days of the study period, a total of 1109 patients with STEMI (803; 72% men, mean age 61;14 years) were included. The gender difference between men and women was much more pronounced on cold (0 °C) days (85% of patients male; 1.8 per day) than on hot (20 °C) days (71% male; 1.4 per day) or days without extreme temperatures (72% male; 1.4 per day). We found significant interaction between gender and cold days (IRR of the interaction term 2.3 (95% CI 1.2-4.6), p = 0.02). No gender-specific effect was observed on warm days (IRR for interaction 0.9 (95% CI 0.6-1.3), p = 0.3). CONCLUSION: Low perceived temperature pronouncedly increases the already elevated risk for STEMI in males. Whether this effect is based on gender alone, or on one of the cardiovascular risk factors which are more common in men, is up to further study.
This study focuses on Guizhou Province, a region with difficult geographical conditions and poor economic development, to examine the effect of rainfall shocks on contemporaneous infant health and long-run socioeconomic outcomes in China. The study results indicate that negative rainfall shocks are robustly correlated with higher infant mortality and lower birth weight. In the long run, early life rainfall shortages limit an individual’s income and housing conditions. The study findings indicate a significant interaction of rainfall shock with the severity of water scarcity. This result implies that drinking water safety is an essential channel through which early life rainfall shocks influence individual health endowments. However, agriculture production is not a likely channel for rainfall effects despite its association with infant mortality. Accordingly, our empirical results suggest that improving public facility coverage will reduce the vulnerability of infant health to adverse rainfall shocks in Guizhou and other developing areas.
Climate change can cause property damage and deaths in cities. City-scale climate projections are essential for making informed decisions towards climate change mitigation and adaptation at city levels. This study aims at developing ensemble projections of temperature extremes at the city-level and quantifying the contributions of various factors to the resulting uncertainty of the ensemble projections. The city of Toronto will be used here as an example to demonstrate the effectiveness of the proposed research framework. In particular, the stepwise cluster analysis (SCA) model will be used to perform climate downscaling to three GCM datasets (GFDL, IPSL, and MPI) under three emission scenarios (RCP2.6, RCP4.5, and RCP8.5) in order to generate city-level climate projections for the city of Toronto. The SCA model is demonstrated to be capable of capturing the inter- and intra-annual variations of the daily maximum, mean, and minimum temperatures in the studied city. The results suggest that mean temperatures in Toronto are projected to increase at the rate of 0.15 and 0.5 degrees C/decade under RCP4.5 and RCP8.5, respectively, while no significant warming trend is detected for RCP2.6. In terms of temperature extremes, extreme warm events are projected to increase while extreme cold events decrease under all emission scenarios. The decrease in the heating demand is two to four times larger than the increase in the cooling demand, indicating a decrease in the city’s total energy use. The projected warming might be beneficial for the urban growers because of the significant increases in the growing season length and growing degree days; however, the residents of the city of Toronto are likely to experience simultaneous increases in the intensity, duration, and frequency of heatwave events in future summers. Because of the warming, coldwave events in winters are likely to become less frequent and be shorter in duration, but their intensity is expected to increase significantly. Through decomposition of the resulting uncertainty of the ensemble projections, emission scenario is found to be the dominant factor for the uncertainty associated with urban climate projection.
Temperature change between neighboring days (TCN) is an important trigger for cardiovascular diseases, but the modulated effects by seasonal temperature trends have been barely taken into account. A quantified comparison between impacts of positive TCNs (temperature rise) and negative situations (temperature drop) is also needed. We evaluated the associations of TCNs with emergency room (ER) visits for coronary heart disease (CHD) and cerebral infarction (CI) in Beijing, China, from 2008 to 2012. A year was divided into two segments dominated by opposite temperature trends, quasi-Poisson regression with distributed lag nonlinear models estimating TCN-morbidity relations were employed, separately for each period. High morbidities of CHD and CI both occurred in transitional seasons accompanied by large TCNs. Under warming backgrounds, positive TCNs increased CHD risk in patients younger than 65 years, and old people showed limited sensitivity. In the cooling periods, negative TCNs induced CHD risk in females and the elderly; the highest RR showed on lag 6 d. In particular, a same diurnal temperature decrease (e.g., – 2°C) induced greater RR (RR = 1.113, 95% CIs: 1.033-1.198) on old people during warming periods than cooling counterparts (RR = 1.055, 95% CIs: 1.011-1.100). Moreover, positive TCNs elevated CI risk regardless of background temperatures, and males were particularly vulnerable. Seasonal temperature trends modify TCN-cardiovascular morbidity associations significantly, which may provide new insights into the health impact of unstable weathers.
The present study was planned to explore the pollution characteristics, health risks, and influence of atmospheric fine particulate matter (PM(2.5)) and its components on blood routine parameters in a typical industrial city (Xinxiang City) in China. In this study, 102 effective samples 28 (April-May), 19 (July-August), 27 (September-October), 28 (December-January) of PM(2.5) were collected during different seasons from 2017 to 2018. The water-soluble ions and metal elements in PM(2.5) were analyzed via ion chromatography and inductively coupled plasma-mass spectrometry. The blood routine physical examination parameters under different polluted weather conditions from January to December 2017 and 2018, the corresponding PM(2.5) concentration, temperature, and relative humidity during the same period were collected from Second People’s Hospital of Xinxiang during 2017-2018. Risk assessment was carried out using the generalized additive time series model (GAM). It was used to analyze the influence of PM(2.5) concentration and its components on blood routine indicators of the physical examination population. The “mgcv” package in R.3.5.3 statistical software was used for modeling and analysis and used to perform nonparametric smoothing on meteorological indicators such as temperature and humidity. When Akaike’s information criterion (AIC) value is the smallest, the goodness of fit of the model is the highest. Additionally, the US EPA exposure model was used to evaluate the health risks caused by different heavy metals in PM(2.5) to the human body through the respiratory pathway, including carcinogenic risk and non-carcinogenic risk. The result showed that the air particulate matter and its chemical components in Xinxiang City were higher in winter as compared to other seasons with an overall trend of winter > spring > autumn > summer. The content of nitrate (NO(3)(-)) and sulfate (SO(4)(2)(-)) ions in the atmosphere were higher in winter, which, together with ammonium, constitute the main components of water-soluble ions in PM(2.5) in Xinxiang City. Source analysis reported that mobile pollution sources (coal combustion emissions, automobile exhaust emissions, and industrial emissions) in Xinxiang City during the winter season contributed more to atmospheric pollution as compared to fixed sources. The results of the risk assessment showed that the non-carcinogenic health risk of heavy metals in fine particulate matter is acceptable to the human body, while among the carcinogenic elements, the order of lifetime carcinogenic risk is arsenic (As) > chromium(Cr) > cadmium (Cd) > cobalt(Co) > nickel (Ni). During periods of haze pollution, the exposure concentration of PM(2.5) has a certain lag effect on blood routine parameters. On the day when haze pollution occurs, when the daily average concentration of PM(2.5) rises by 10 ?g·m(-3), hemoglobin (HGB) and platelet count (PLT) increase, respectively, by 9.923% (95% CI, 8.741-11.264) and 0.068% (95% CI, 0.067-0.069). GAM model analysis predicted the maximum effect of PM(2.5) exposure concentration on red blood cell count (RBC) and PLT was reached when the hysteresis accumulates for 1d (Lag0). The maximum effect of exposure concentration ofPM(2.5) on MONO is reached when the lag accumulation is 3d (Lag2). When the hysteresis accumulates for 6d (Lag5), the exposure concentration of PM(2.5) has the greatest effect on HGB. The maximum cumulative effect of PM(2.5) on neutrophil count (NEUT) and lymphocyte (LMY) was strongest when the lag was 2d (Lag1). During periods of moderate to severe pollution, the concentration of water-soluble ions and heavy metal elements in PM(2.5) increases significantly and has a significant correlation with some blood routine indicators.
Heatwaves and greenness have been shown to affect health, but the evidence on their joint effects is limited. We aim to assess the associations of the combined exposure to greenness and heatwaves. We utilized five waves (February 2000-October 2014) of the Chinese Longitudinal Healthy Longevity Survey (CLHLS), a prospective cohort of older adults aged 65. We defined heatwaves as the daily maximum temperature ?92.5th percentile with duration ?3 days. We calculated the number of heatwave days in one year before death to and cumulative Normalized Difference Vegetation Index (NDVI) during follow-up to assess individual long-term exposure to heatwaves and greenness. Cox proportional hazards models were used to assess the effects of greenness, heatwaves, and their interaction on mortality, adjusted for covariates. We conducted subgroup analyses by residence, gender, and age. There were 20,758 participants in our study, totaling 67,312 person-years of follow-up. The mean NDVI was 0·41 (SD 0.13), and the mean number of heatwave days was 8.92 (2.04). In the adjusted model, the mortality hazard ratio (HR) for each 3-day increase in heatwave days was 1.04 (95% CI 1.04, 1.05), each 0.1-unit decrease in cumulative NDVI was 1.06 (1.05, 1.07). In the adjusted model with an interaction term, the HR for the interaction term was 1.01 (1.01, 1.02) with a p-value less than 0.001. In our subgroup analyses, the HR for each 3-day increase in heatwave days was higher in urban areas than in rural areas (1.06 vs. 1.03), and the HR for 0.1-unit decrease in NDVI was higher in urban areas than in rural areas (1.08 vs. 1.04). Greenness can protect against the effect of heatwaves on mortality, and heatwaves affect the health effects of greenness. Urban dwellers have a higher response to the detrimental effect of heatwaves and a higher marginal benefit from greenness exposure.
Malaria is a climate-sensitive infectious disease. Many ecological studies have investigated the independent impacts of ambient temperature on malaria. However, the optimal temperature measures of malaria and its interaction with other meteorological factors on malaria transmission are less understood. This study aims to investigate the effect of ambient temperature and its interactions with relative humidity and rainfall on malaria in Suzhou, a temperate climate city in Anhui Province, China. Weekly malaria and meteorological data from 2005 to 2012 were obtained for Suzhou. A distributed lag nonlinear model was conducted to quantify the effect of different temperature measures on malaria. The best measure was defined as that with the minimum quasi-Akaike information criterion. GeoDetector and Poisson regression models were employed to quantify the interactions of temperature, relative humidity, and rainfall on malaria transmission. A total of 13,382 malaria cases were notified in Suzhou from 2005 to 2012. Each 5 °C rise in average temperature over 10 °C resulted in a 22% (95% CI: 17%, 28%) increase in malaria cases at lag of 4 weeks. In terms of cumulative effects from lag 1 to 8 weeks, each 5 °C increase over 10 °C caused a 175% growth in malaria cases (95% CI: 139%, 216%). Average temperature achieved the best performance in terms of model fitting, followed by minimum temperature, most frequent temperature, and maximum temperature. Temperature had an interactive effect on malaria with relative humidity and rainfall. High temperature together with high relative humidity and high rainfall could accelerate the transmission of malaria. Meteorological factors may affect malaria transmission interactively. The research findings could be helpful in the development of weather-based malaria early warning system, especially in the context of climate change for the prevention of possible malaria resurgence.
The present study explored the association between daily ambient air pollution and daily emergency room (ER) visits due to acute respiratory symptoms in children of Delhi. The daily counts of ER visits (ERV) of children (?15 years) having acute respiratory symptoms were obtained from two hospitals of Delhi for 21 months. Simultaneously, data on daily concentrations of particulate matter (PM(10) and PM(2.5)), nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), carbon monoxide (CO), and ozone (O(3)) and weather variables were provided by the Delhi Pollution Control Committee. K-means clustering with time-series approach and multi-pollutant generalized additive models with Poisson link function was used to estimate the 0-6-day lagged change in daily ER visits with the change in multiple pollutants levels. Out of 1,32,029 children screened, 19,120 eligible children having acute respiratory symptoms for ?2 weeks and residing in Delhi for the past 4 weeks were enrolled. There was a 29% and 21% increase in ERVs among children on high and moderate level pollution cluster days, respectively, compared to low pollution cluster days on the same day and previous 1-6 days of exposure to air pollutants. There was percentage increase (95% CI) 1.50% (0.76, 2.25) in ERVs for acute respiratory symptoms for 10 ?g/m(3) increase of NO(2) on previous day 1, 46.78% (21.01, 78.05) for 10 ?g/m(3) of CO on previous day 3, and 13.15% (9.95, 16.45) for 10 ?g/m(3) of SO(2) on same day of exposure. An increase in the daily ER visits of children for acute respiratory symptoms was observed after increase in daily ambient air pollution levels in Delhi.
Industrialization and urbanization have aggravated the contradiction between environmental protection and economic growth, leading to health issues. While there are considerable interests in understanding the health effects of carbon emissions in the context of climate change, little is observed at regional scale and by econometric methods. Applying regression analysis on 2002-2017 Chinese provincial-level panel data, this study explores the intermediary mechanisms and regional differences of carbon emissions on residents’ health. The results indicate that: (1) Carbon emissions have a long-term adverse impact on residents’ health-a 1% rise in carbon emission adds 0.298% more outpatients and 0.162% more inpatients; (2) The rise in carbon emissions impairs residents’ health mainly by raising the temperature; (3) In areas with high levels of industrialization and urbanization, increased carbon emissions bring greater health risks; and (4) In terms of China’s unique “leading industrialization and lagging urbanization” situation, only by upgrading industrial structure, improving urbanization quality, and promoting coordinated industrialization and urbanization can the harm of carbon emissions to residents’ health be reduced. Therefore, the “one-size-fits-all” policy model is not suitable for China’s current situation. To address global “climate change” issues, China must act according to local conditions by applying mitigating (adaptive) measures in economically developed (less developed) regions. Simultaneously, the authorities must focus on the interaction and synergy between industrialization and urbanization.
Since the early twentieth century, the intensity of malaria transmission has decreased sharply worldwide, although it is still an infectious disease with a yearly estimate of 228 million cases. The aim of this study was to expand our knowledge on the main drivers of malaria in Spain. In the case of autochthonous malaria, these drivers were linked to socioeconomic and hygienic and sanitary conditions, especially in rural areas due to their close proximity to the wetlands that provide an important habitat for anopheline reproduction. In the case of imported malaria, the main drivers were associated with urban areas, a high population density and international communication nodes (e.g. airports). Another relevant aspect is that the major epidemic episodes of the twentieth century were strongly influenced by war and military conflicts and overcrowding of the healthcare system due to the temporal overlap with the pandemic flu of 1918. Therefore, military conflicts and overlap with other epidemics or pandemics are considered to be drivers of malaria that can-in a temporary manner-exponentially intensify transmission of the disease. Climatic factors did not play a relevant role as drivers of malaria in Spain (at least directly). However, they did influence the seasonality of the disease and, during the epidemic outbreak of 1940-1944, the climate conditions favored or coadjuvated its spread. The results of this study provide additional knowledge on the seasonal and interannual variability of malaria that can help to develop and implement health risk control measures. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s41207-021-00245-8.
Many methods have been developed to verify the correlation between meteorological conditions and air pollutants; however, all have limitations that lead to biased or incomplete conclusions. Hence, improved methods are urgently required to describe this correlation comprehensively and accurately. In this study, we demonstrated the ability of the Copula function to apply time-varying correlations between meteorological factors and atmospheric pollutants. A mixed Copula model was constructed using meteorological monitoring data for Beijing and Guangzhou from 2014 to 2019 to dynamically analyse the correlation characteristics and tail dependence between these factors. We then performed a correlation analysis for the data from the average, lower, and upper tails to obtain a more accurate and comprehensive correlation description. Dynamic analysis results demonstrated significant seasonal fluctuations between meteorological conditions and pollutants relationships. Moreover, the correlation coefficient variations differ according to their average and tail values. High humidity is more likely to be accompanied by increased NO2 compared with average summer humidity. Our proposed model represents a novel application of the Copula function for determining the factors influencing air pollution. This model emphasizes the tail dependence between meteorological conditions and air pollutant concentrations and can be used to guide more targeted prevention and control strategies.
Air pollution has been a rising concern of the 21st due to its effects to public health. Air Monitoring Stations are state-of-the-art equipment used to measure airborne pollutants concentration i.e. carbon monoxide, nitrogen oxide, sulphur dioxide, particulate matter (PM10) and ozone (O-3), as well as the meteorological parameters (i.e. ambient air temperature, relative humidity, wind speed and wind direction). Effects of climate change will affect the ambient temperature and humidity, which may induce a direct effect on air quality. In light of this, feed forward artificial neural network was employed to simulate the dynamic variations of PM10 and O-3 with relative humidity, temperature, and windspeed data being the inputs under 12 different training algorithms. Based on the results obtained, Bayesian regularization with 12 hidden neurons is the optimized network structure, with mean absolute percentage error in testing dataset of O-3 and PM10 at 51.31% and 36.49%, respectively. The models performed better in O-3 prediction as it is a photochemical reaction where ozone concentration varies according to temperature, the effect of meteorological parameters is significant. On the other hand, PM10 is not heavily dependent on meteorological parameters as the diversity of particulate matter components where most of its sources are dormant to changes in climate.
Some epidemiological and ecological aspects of Zoonotic cutaneous leishmaniasis (ZCL) in Ouarzazate province, southern Morocco, were explored with the objective of analyzing ZCL distribution and associated ecological factors. Information on cutaneous leishmaniasis patients attending the local health centers of Ouarzazate during the period 2002-2009 was gathered and compiled. Urban, peri-urban, rural origin, precipitation, wind speed, temperature, water irrigation, dam volume, and altitude were studied. The findings show that the disease affected 5405 person during this period; the major part was found in the municipalities near both oases (desert oasis) and water resources, with a high concentration of cases in the peri-urban area. The highest percentage of cases was recorded mainly in September. Considerable associations were found between relative humidity and wind speed with ZCL occurrence. A large number of cases were recorded in areas with altitude ranging from 800 to 2000 m.a.s.l. and spatial precipitation from 15 to 150 mm. The statistical analysis showed a strong association between water storage volume and water irrigation with the annual ZCL occurrence recorded in the downstream area (Zagora province). The results will lead us to understand ZCL risk areas for effective control. Further work is needed mainly for gathering these variables in one single and simplest model.
BACKGROUND: Many studies have explored the association between meteorological factors and infectious diarrhea (ID) transmission but with inconsistent results, in particular the roles from temperatures. We aimed to explore the effects of temperatures on the transmission of category C ID, to identify its potential heterogeneity in different climate zones of China, and to provide scientific evidence to health authorities and local communities for necessary public health actions. METHODS: Daily category C ID counts and meteorological variables were collected from 270 cities in China over the period of 2014-16. Distributed lag non-linear models (DLNMs) were applied in each city to obtain the city-specific temperature-disease associations, then a multivariate meta-analysis was implemented to pool the city-specific effects. Multivariate meta-regression was conducted to explore the potential effect modifiers. Attributable fraction was calculated for both low and high temperatures, defined as temperatures below the 5th percentile of temperature or above the 95th percentile of temperature. RESULTS: A total of 2,715,544 category C ID cases were reported during the study period. Overall, a M-shaped curve relationship was observed between temperature and category C ID, with a peak at the 81st percentile of temperatures (RR = 1.723, 95% CI: 1.579-1.881) compared to 50th percentile of temperatures. The pooled associations were generally stronger at high temperatures compared to low ambient temperatures, and the attributable fraction due to heat was higher than cold. Latitude was identified as a possible effect modifier. CONCLUSIONS: The overall positive pooled associations between temperature and category C ID in China suggest the increasing temperature could bring about more category C infectious diarrhea cases, which warrants further public health measurements.
Aedes aegypti is the main vector of dengue globally. The variables that influence the abundance of dengue vectors are numerous and complex. This has generated a need to focus on areas at risk of disease transmission, the spatial-temporal distribution of vectors, and the factors that modulate vector abundance. To help guide and improve vector-control efforts, this study identified the ecological, social, and other environmental risk factors that affect the abundance of adult female and immature Ae. aegypti in households in urban and rural areas of northeastern Thailand. A one-year entomological study was conducted in four villages of northeastern Thailand between January and December 2019. Socio-demographic; self-reported prior dengue infections; housing conditions; durable asset ownership; water management; characteristics of water containers; knowledge, attitudes, and practices (KAP) regarding climate change and dengue; and climate data were collected. Household crowding index (HCI), premise condition index (PCI), socio-economic status (SES), and entomological indices (HI, CI, BI, and PI) were calculated. Negative binomial generalized linear models (GLMs) were fitted to identify the risk factors associated with the abundance of adult females and immature Ae. aegypti. Urban sites had higher entomological indices and numbers of adult Ae. aegypti mosquitoes than rural sites. Overall, participants’ KAP about climate change and dengue were low in both settings. The fitted GLM showed that a higher abundance of adult female Ae. aegypti was significantly (p < 0.05) associated with many factors, such as a low education level of household respondents, crowded households, poor premise conditions, surrounding house density, bathrooms located indoors, unscreened windows, high numbers of wet containers, a lack of adult control, prior dengue infections, poor climate change adaptation, dengue, and vector-related practices. Many of the above were also significantly associated with a high abundance of immature mosquito stages. The GLM model also showed that maximum and mean temperature with four-and one-to-two weeks of lag were significant predictors (p < 0.05) of the abundance of adult and immature mosquitoes, respectively, in northeastern Thailand. The low KAP regarding climate change and dengue highlights the engagement needs for vector-borne disease prevention in this region. The identified risk factors are important for the critical first step toward developing routine Aedes surveillance and reliable early warning systems for effective dengue and other mosquito-borne disease prevention and control strategies at the household and community levels in this region and similar settings elsewhere.
OBJECTIVE: This study evaluated the relationships between the occurrence of recent and recurring natural disasters on the incidence of acute and chronic health outcomes at the census tract level in 500 cities across the United States between 2001 and 2015. METHODS: Using the Centers for Disease Control and Prevention (CDC) 500 cities data set, the CDC Social Vulnerability Index, and the US Small Business Administration (SBA) Disaster Loan Database, we modeled the incidence of self-reported, poor mental and physical health, or a clinical diagnosis of high blood pressure or asthma in census tracts (N = 27 204 tracts in 500 cities) that had experienced recent or recurring natural disasters while controlling for social and environmental risk factors. RESULTS: Communities that experienced a natural disaster in the previous 5 years compared to those that had not had a higher incidence of poor mental health (RR: 1.02, 95% CI: 1.01-1.02), poor physical health (RR: 1.03, 95% CI: 1.02-1.04), high blood pressure (RR: 1.04, 95% CI: 1.02-1.05), and asthma (RR: 1.01, 95% CI: 1.01-1.02). The incidence of these poor health outcomes increased 1-2% with each additional year that a community experienced a disaster. CONCLUSIONS: Prevention and preparedness plans that work to build resilience in communities before disasters should focus on closing the gap in environmental and social determinants that have been linked with disproportionate health burdens and slow recovery post-disaster.
Increasing summer temperatures in a warming climate will increase the exposure of the UK population to heat-stress and associated heat-related mortality. Urban inhabitants are particularly at risk, as urban areas are often significantly warmer than rural areas as a result of the urban heat island phenomenon. The latest UK Climate Projections include an ensemble of convection-permitting model (CPM) simulations which provide credible climate information at the city-scale, the first of their kind for national climate scenarios. Using a newly developed urban signal extraction technique, we quantify the urban influence on present-day (1981-2000) and future (2061-2080) temperature extremes in the CPM compared to the coarser resolution regional climate model (RCM) simulations over UK cities. We find that the urban influence in these models is markedly different, with the magnitude of night-time urban heat islands overestimated in the RCM, significantly for the warmest nights (up to 4 degrees C), while the CPM agrees much better with observations. This improvement is driven by the improved land-surface representation and more sophisticated urban scheme MORUSES employed by the CPM, which distinguishes street canyons and roofs. In future, there is a strong amplification of the urban influence in the RCM, whilst there is little change in the CPM. We find that future changes in soil moisture play an important role in the magnitude of the urban influence, highlighting the importance of the accurate representation of land-surface and hydrological processes for urban heat island studies. The results indicate that the CPM provides more reliable urban temperature projections, due at least in part to the improved urban scheme.
BACKGROUND: The impact of simultaneous adverse climate conditions in the risk of myocardial infarction (MI) was not tested before. The aim of the present study was to investigate the impact of the combination of climate and air pollution features in the number of admissions and mortality due to acute myocardial infarction in 39 municipalities of São Paulo from 2012 to 2015. METHODS: Data about MI admissions were obtained from the Brazilian public health system (DataSUS). Daily information on weather were accessed from the Meteorological Database for Teaching and Research. Additionally, daily information on air pollution were obtained from the Environmental Company of the State of São Paulo. A hierarchical cluster analysis was applied for temperature, rainfall patterns, relative air humidity, nitrogen dioxide, particulate matter 2.5 and particulate matter 10. MI admissions and in-hospital mortality were compared among the clusters. RESULTS: Data analysis produced 3 clusters: High temperature variation-Low humidity-high pollution (n=218 days); Intermediate temperature variation/high humidity/intermediate pollution (n=751 days) and low temperature variation/intermediate humidity-low pollution (n=123 days). All environmental variables were significantly different among clusters. The combination of high temperature variation, dry weather and high pollution resulted in a significant 9% increase in hospital admissions for MI [30.5 (IQR 25.0-36.0)]; patients/day; P<0.01). The differences in weather and pollution did not have impact on in-hospital mortality (P=0.88). CONCLUSION: The combination of atmospheric conditions with high temperature variation, lower temperature, dryer weather and increased inhalable particles was associated with a marked increase of hospital admissions due to MI.
As awareness of climate change increases, U.S. cities are beginning to implement climate mitigation and adaptation initiatives to reduce population vulnerabilities to climate risks. This study contributes to a growing literature that quantitatively describes the relationships between sociodemographic variables and climate adaptation interventions in U.S. cities. Ordinary linear and simultaneous autoregressive models are used to evaluate early flood adaptation actions in Austin, Texas, to assess relationships between flood risk, green infrastructure, and measures of race and income. Findings of unequal exposure to flood risk and uneven access to flood resilience initiatives contribute to our understanding of color-blind urban planning responses to climate change and their potential to amplify inequitable protection from climate risks.
Climate change has been linked to poor childhood growth and development through maternal stress, nutritional insults related to lean harvests, and exposure to infectious diseases. Vulnerable populations are often most susceptible to these stressors. This study tested whether susceptibility to linear growth faltering is higher among Peruvian children from indigenous, rural, low-education, and low-income households. High-resolution weather and household survey data from Demographic and Health Survey 1996-2012 were used to explore height-for-age z-scores (HAZ) at each year of life from 0 to 5. Rural, indigenous children at age 0-1 experience a HAZ reduction of 0.35 units associated with prenatal excess rainfall which is also observed at age 4-5. Urban, non-indigenous children at age 4-5 experience a HAZ increase of 0.07 units associated with postnatal excess rainfall, but this advantage is not seen among rural, indigenous children. These findings highlight the need to consider developmental stage and social predictors as key components in public health interventions targeting increased climate change resilience.
Around 27% of South Americans live in central and southern Brazil. Of 19,400 human malaria cases in Brazil in 2018, some were from the southern and southeastern states. High abundance of malaria vectors is generally positively associated with malaria incidence. Expanding geographic distributions of Anopheles vector mosquito species (e.g. A. cruzii) in the face of climate change processes would increase risk of such malaria transmission; such risk is of particular concern in regions that hold human population concentrations near present limits of vector species’ geographic distributions. We modeled effects of likely climate changes on the distribution of A. cruzii, evaluating two scenarios of future greenhouse gas emissions for 2050, as simulated in 21 general circulation models and two greenhouse gas scenarios (RCP 4.5 and RCP 8.5) for 2050. We tested 1305 candidate models, and chose among them based on statistical significance, predictive performance, and complexity. The models closely approximated the known geographic distribution of the species under current conditions. Under scenarios of future climate change, we noted increases in suitable area for the mosquito vector species in São Paulo and Rio de Janeiro states, including areas close to 30 densely populated cities. Under RCP 8.5, our models anticipate areal increases of >75% for this important malaria vector in the vicinity of 20 large Brazilian cities. We developed models that anticipate increased suitability for the mosquito species; around 50% of Brazilians reside in these areas, and ?89% of foreign tourists visit coastal areas in this region. Under climate change thereefore, the risk and vulnerability of human populations to malaria transmission appears bound to increase.
BACKGROUND: Understanding the association between floods and bacillary dysentery (BD) incidence is necessary for us to assess the health risk of extreme weather events. This study aims at exploring the association between floods and daily bacillary dysentery cases in main urban areas of Chongqing between 2005 and 2016 as well as evaluating the attributable risk from floods. METHODS: The association between floods and daily bacillary dysentery cases was evaluated by using distributed lag non-linear model, controlling for meteorological factors, long-term trend, seasonality, and day of week. The fraction and number of bacillary dysentery cases attributable to floods was calculated. Subgroup analyses were conducted to explore the association across age, gender, and occupation. RESULTS: After controlling the impact of temperature, precipitation, relative humidity, long-term trend, and seasonality, a significant lag effect of floods on bacillary dysentery cases was found at 0-day, 3-day, and 4-day lag, and the cumulative relative risk (CRR) over a 7-lag day period was 1.393 (95%CI 1.216-1.596). Male had higher risk than female. People under 5?years old and people aged 15-64?years old had significantly higher risk. Students, workers, and children had significantly higher risk. During the study period, based on 7-lag days, the attributable fraction of bacillary dysentery cases due to floods was 1.10% and the attributable number was 497 persons. CONCLUSIONS: This study confirms that floods can increase the risk of bacillary dysentery incidence in main urban areas of Chongqing within an accurate time scale, the risk of bacillary dysentery caused by floods is still serious. The key population includes male, people under 5?years old, students, workers, and children. Considering the lag effect of floods on bacillary dysentery, the government and public health emergency departments should advance to the emergency health response in order to minimize the potential risk of floods on public.
In addition to several negative environmental effects, climate change, which reduces bioclimatic comfort levels especially in urban areas, also has economic implications, especially in cities where the economic structure is tourism-oriented. Considering most of the tourism practices are based on outdoor activities in cities such as Antalya, it is of great importance to determine bioclimatic comfort level as well as the attitudes of people toward climate change who live in those conditions to be able to take proper precautions in terms of tourism and urban planning. Therefore, the purpose of this study was to reveal the bioclimatic comfort conditions of Antalya city center, and a comprehensive questionnaire was conducted with the people living in the area questioning the opinions on reasons and consequences of climate change, perceivable effects of climate change in Antalya, and suggestions to prevent or reduce the adverse effects. The areas with appropriate bioclimatic comfort conditions were determined and mapped via geographical information systems using temperature and relative humidity data of the years between 1960 and 2018. The data gathered via questionnaires were analyzed using confirmatory factor analysis, regression, correlation, and structural equation modelling via SPSS and AMOS software. According to the results, it was determined that in some parts of city center the bioclimatic comfort conditions decreased to levels that could reach harmful dimensions for human health and the analysis of the questionnaires revealed that people living in that area state that the effects of climate change are perceivable as the precipitation seasons have become irregular. According to the participants, it was determined that a 1-unit increase in environmental measures causes a decrease of 0.136 units in disasters (R(2)?=?1.1%). In comparison, 1-unit increase of Administrative Precautions will cause 0.030 units decrease in effects of climate change on vital needs (R(2)?=?1.4%). These analysis results show that the respondents expect the disaster scenarios to decrease when environmental measures are increased.
Both global climate change and urbanization trends will demand adaptation measures in cities. Large agglomerations and impacts on landscape and natural environments due to city growth will require guided densification schemes in urban areas, particularly in developing countries. Human biometeorological indices such as the Universal Thermal Climate Index (UTCI) could guide this process, as they provide a clear account of expected effects on thermal sensation from a given change in outdoor settings. However, an earlier step should optimally include an adequacy test of suggested comfort and thermal stress ranges with calibration procedures based on surveys with the target population. This paper compares obtained thermal comfort ranges for three different locations in Brazil: Belo Horizonte, 20° S, Aw climate type; Curitiba, 25.5° S, Cfb subtropical climate, both locations in elevation (above 900 m a.s.l.); and Pelotas, at sea level, latitude 32° S, with a Cfa climate type. In each city, a set of outdoor comfort field campaigns has been carried out according to similar procedures, covering a wide range of climatic conditions over different seasons of the year. Obtained results indicate a variation of neutral temperatures up to 3 °C (UTCI units) as a possible latitude and local climate effect between the southern locations relative to the northernmost location. Low UTCI values were found in the two subtropical locations for the lower threshold of the thermal comfort band as compared with the original threshold. A possible explanation for that is a longer exposure to cold conditions as buildings are seldom provided with heating systems.
Urban areas are increasingly affected by extreme heat in the face of climate change, while the size and vulnerability of exposed populations are shifting due to economic development, demographic change, and urbanization. In addition to the need to assess future urban heat-related health risks, there is also an increasing need to design adaptation strategies that will be effective under varying levels of socioeconomic development and climate change. We use the case study of Houston, Texas, to develop and demonstrate a scenario-based approach to explore the effectiveness of both autonomous and planned heat-related adaptations under multiple plausible futures. We couple a heat risk model with urban climate projections (under the Representative Concentration Pathways) and vulnerability projections (under locally extended Shared Socioeconomic Pathways) to investigate the impact of different adaptation strategies under multiple scenario combinations. We demonstrate that, in the context of Houston, community-based adaptation strategies aiming to reduce social isolation are the most effective and the least challenging to implement across all plausible futures. Scenario-based approaches can provide local policymakers with context-specific assessments of possible adaptation strategies that account for uncertain futures.
What is already known on this topic? The health risk caused by high-temperatures depends on the interaction between high temperature exposure and the sensitivity and adaptability of the affected populations. What is added by this report? A comprehensive assessment model was established by principal component analysis using the data of 19 cities, 15 provincial-level administrative divisions and used to identify regional characteristics and major influencing factors of health vulnerability to extreme heat in China. What are the implications for public health practice? The results of the health vulnerability assessment could effectively identify the regions highly vulnerable to extreme heat in China and provide scientific evidence for the development of adaptive measures and resource allocation plans.
People with chronic obstructive pulmonary disease, cardiovascular disease, or hypertension have a high risk of developing severe coronavirus disease 2019 (COVID-19) and of COVID-19 mortality. However, the association between long-term exposure to air pollutants, which increases cardiopulmonary damage, and vulnerability to COVID-19 has not yet been fully established. We collected data of confirmed COVID-19 cases during the first wave of the epidemic in mainland China. We fitted a generalized linear model using city-level COVID-19 cases and severe cases as the outcome, and long-term average air pollutant levels as the exposure. Our analysis was adjusted using several variables, including a mobile phone dataset, covering human movement from Wuhan before the travel ban and movements within each city during the period of the emergency response. Other variables included smoking prevalence, climate data, socioeconomic data, education level, and number of hospital beds for 324 cities in China. After adjusting for human mobility and socioeconomic factors, we found an increase of 37.8% (95% confidence interval [CI]: 23.8%-52.0%), 32.3% (95% CI: 22.5%-42.4%), and 14.2% (7.9%-20.5%) in the number of COVID-19 cases for every 10-?g/m(3) increase in long-term exposure to NO(2), PM(2.5), and PM(10), respectively. However, when stratifying the data according to population size, the association became non-significant. The present results are derived from a large, newly compiled and geocoded repository of population and epidemiological data relevant to COVID-19. The findings suggested that air pollution may be related to population vulnerability to COVID-19 infection, although the extent to which this relationship is confounded by city population density needs further exploration.
In the present study, we aim to evaluate the delayed and cumulative effect of ozone (O(3)) exposure on mumps in a megacity with high population density and high humidity. We took Chongqing, a megacity in Southwest China, as the research area and 2013-2017 as the research period. A total of 49,258 confirmed mumps cases were collected from 122 hospitals of Chongqing. We employed the distributed lag nonlinear models with quasi-Poisson link to investigate the relationship between prevalence of mumps and O(3) exposure after adjusting for the effects of meteorological conditions. The results show that the effect of O(3) exposure on mumps was mainly manifested in the lag of 0-7 days. The ?single-day ;lag effect was the most obvious on the 4th day, with the relative risk (RR) of mumps occurs of 1.006 (95% CI: 1.003-1.007) per 10 ?g/m(3) in the O(3) exposure. The cumulative RR within 7 days was 1.025 (95% CI: 1.013-1.038). Our results suggest that O(3) exposure can increase the risk of mumps infection, which fills the gap of relevant research in mountainous areas with high population density and high humidity.
Studies focused on the seasonal distribution of pollen and spores in semiarid cities are scarce. At these sites, climate change potentiates the emission and transport of fine (PM(10)) to ultrafine particles (PM(2.5)), easily attached to pollen surfaces, causing allergen’s release. This study examines the potential correlation of seasonal variations of pollen, fungal spores, PM(10), and meteorological parameters with allergic reactions of 150 people living in a Sonoran desert city. We collected PM(10), airborne pollen, and spores during a year. We also studied topsoil and road dust samples as potential PM-emission sources. We obtained dust-mineralogy, chemistry, and particle size attached to pollen by X-ray diffraction and scanning electron microscope. Results show that seasonal high PM-loading in the urban atmosphere coincides with aeroallergens promoting micro- to nanoparticles’ attachment to pollen’s surface. A collapsed membrane was observed in several samples after individual grains show the following maximum wall coverage: Poaceae 28%, Asteraceae 40%, Chenopodiaceae-Amaranthacea 29%, Fabaceae 18%. Most of the particles covering pollen’s surface have a geogenic origin mixed with metals linked to traffic (bromide, chlorine, and antimony). Mineralogical, granulometric analysis, and main wind-direction show that two local soil-types are the main contributors to PM. A high frequency of positive sensitization to pollen with high particle loading was detected. These results suggest that climate-driven dust emissions may alter pollen and spore surfaces’ physicochemical characteristics with the further consequences in their allergenic potential.
BACKGROUND: Ozone pollution keeps deteriorating in the context of climate change. Maternal ozone exposure may be associated with low birth weight (LBW), but the results are still inconsistent. The identification of the critical exposure windows, a specific period of particular susceptibility during pregnancy, remains unresolved. We aimed to evaluate whether ozone exposure was associated with term LBW and further identify the susceptible exposure windows. METHODS: A retrospective cohort study was conducted in Guangzhou, a megacity in the most populous and economically developed city clusters in China. We included 444,096 singleton live births between January 2015 and July 2017. From 11 fixed stations, we collected daily 1-h maximum and 8-h maximum moving average ozone level (O(3)-1 h and O(3)-8 h) and calculated exposures for each participant based on their district of residence during pregnancy. We used traditional Logistic regression to estimate the trimester-specific association between ozone exposure and term LBW, and further estimated monthly- and weekly association by distributed lag models (DLMs) with Logistic regression. Odds ratios (ORs) and 95% confidence intervals (CIs) of term LBW were calculated for an interquartile range (IQR) increase in ozone exposure. Stratified analyses and heterogeneity tests were conducted by maternal age and infant sex. RESULTS: The incidence of term LBW was 1.9%. During the study period, the mean O(3)-1 h and O(3)-8 h levels were 112.6 µg/m(3) and 84.5 µg/m(3), respectively. Increased O(3)-1 h (IQR: 90 µg/m(3)) and O(3)-8 h (73 µg/m(3)) exposure during the second trimester were associated with increased risk of term LBW. At a monthly level, the term LBW risk was associated with O(3)-1 h exposure during the 4th-6th month and O(3)-8 h exposure during the 6th month. By estimating the weekly-specific association, we observed that critical exposure windows were the 15th- 26th gestational weeks for O(3)-1 h, and the 20th-26th weeks for O(3)-8 h, respectively. Estimated ORs and 95% CIs ranged from 1.012 (1.000, 1.024) to 1.023 (1.007, 1.039). When examined by subgroups, the effects were present among women ? 35 years or < 25 years old and those with female babies. CONCLUSIONS: This study provides compelling evidence that exposure to O(3) was associated with increased risk of term LBW, and gestational weeks 15th- 26th was found to be particularly susceptible. These findings provide a research basis for further mechanism examination, public health interventions, and targeted environmental policy-making.
Most studies of short-term exposure to ambient air pollution and cerebrovascular diseases focused on specific stroke-related outcomes, and results were inconsistent due to data unavailability and limited sample size. It is unclear yet how ambient air pollution contributes to the total cardiovascular mortality in central China. Daily deaths from cerebrovascular diseases were obtained from the Disease Surveillance Point System (DSPs) of Wuhan Center for Disease Control and Prevention during the period from 2013 to 2019. Air pollution data were obtained from Wuhan Ecology and Environment Institute from 10 national air quality monitoring stations, including average daily PM(2.5), PM(10), SO(2), NO(2), and O(3). Average daily temperature and relative humidity were obtained from Wuhan Meteorological Bureau. We performed a Poisson regression in generalized additive models (GAM) to examine the association between ambient air pollution and cerebrovascular disease mortality. We observed a total of 84,811 deaths from cerebrovascular diseases from 1 January 2013 to 31 December 2019 in Wuhan. Short-term exposure to PM(2.5), PM(10), SO(2), and NO(2) was positively associated with daily deaths from cerebrovascular diseases, and no significant association was found for O(3). The largest effect on cerebrovascular disease mortality was found at lag0 for PM(2.5) (ERR: 0.927, 95% CI: 0.749-1.105 per 10 ?g/m3) and lag1 for PM(10) (ERR: 0.627, 95% CI: 0.493-0.761 per 10 ?g/m(3)), SO(2) (ERR: 2.518, 95% CI: 1.914, 3.122 per 10 ?g/m(3)), and NO(2) (ERR: 1.090, 95% CI: 0.822-1.358 per 10 ?g/m(3)). The trends across lags were statistically significant. The stratified analysis demonstrated that females were more susceptible to SO(2) and NO(2), while elder individuals aged above 65 years old, compared with younger people, suffered more from air pollution, especially from SO(2). Short-term exposure to PM(2.5), PM(10), SO(2), and NO(2) were significantly associated with a higher risk of cerebrovascular disease mortality, and elder females seemed to suffer more from air pollution. Further research is required to reveal the underlying mechanisms.
For two decades, the flood risk has become a challenge for all authorities in the world. However, its mitigation can be conducted through structural and non-structural measures. The non-structural measures include the flood risk assessment and management, the evacuating process during the flood, and land use management. This case study used HEC-RAS and HEC-LifeSim models to assess the potential flood risk, Mohammedia (Morocco), associated with Malleh dam rupture. The HEC-RAS2D Hydraulic model was calibrated for one flood and its sensitivity to the Manning was analysed. Thus, the potential life loss simulation was conducted using the socio-economic and Hydraulic data using HEC-LifeSim according to two alternatives of the evacuation process. The results showed that traffic management during floods decreases the probability of life loss. Overall results showed that the city is vulnerable to the disaster simulated in terms of road network capacity that can be used for the evacuation process.
The disclosed study undertook a ‘human centred-approach’ that ascertained and categorised environmental human thermophysiological risk factors by relating them to the human biometeorological system through the use of three widely utilised energy balance model (EBM) indices, the physiologically equivalent temperature (PET), the modified PET, and the universal thermal climate index (UTCI). The disclosed assessment was carried out over the past decade (i.e., 2010-2019) with a 3-h temporal resolution for the case of Ankara through two WMO meteorological stations to compare both local urban and peri-urban environmental conditions. The study recognised extreme annual variability of human physiological stress (PS) during the different seasons as a result of the biometeorological processing of the singular variables, which in the case of average PET for both stations, varied by up to 75 °C between the winter and summer for the same annual dataset (2012). In addition, all EBMs indicated higher heat stress within the city centre that were conducive of both urban extreme heatwaves and very hot days during the summer months, with extreme heat stress levels lasting for longer than a week with PET values reaching a maximum of 48 °C. Similar cold extremes were found for the winter months, with PET values reaching -?30 °C, and average PS levels varying lower in the case of the peri-urban station. Graphical abstract.
Hot weather not only impacts upon human physical comfort and health, but also impacts the way that people access and experience active travel options such as walking and cycling. By evaluating the street thermal environment of a city alongside an assessment of those communities that are the most vulnerable to the effects of heat, we can prioritise areas in which heat mitigation interventions are most needed. In this paper, we propose a new approach for policy makers to determine where to delegate limited resources for heat mitigation with most effective outcomes for the communities. We use eye-level street panorama images and community profiles to provide a bottom-up, human-centred perspective of the city scale assessment, highlighting the situation of urban tree shade provision throughout the streets in comparison with environmental and social-economic status. The approach leverages multiple sources of spatial data including satellite thermal images, Google street view (GSV) images, land use and demographic census data. A deep learning model was developed to automate the classification of streetscape types and percentages at the street- and eye-view level. The methodology is metrics based and scalable which provides a data driven assessment of heat-related vulnerability. The findings of this study first contribute to sustainable development by developing a method to identify geographical areas or neighbourhoods that require heat mitigation; and enforce policies improving tree shade on routes, as a heat adaptation strategy, which will lead to increasing active travel and produce significant health benefits for residents. The approach can be also used to guide post COVID-19 city planning and design.
Surface characteristics play a vital role in simulations for urban bioclimatic conditions. Changing relationships and distribution patterns of sealed and vegetated surfaces as well as building geometry across different scales in urban environments influence surface temperatures. Cities comprise different urban forms, which, depending on their surface characteristics, enhance the heating process, increasing the emergence of urban heat islands (UHIs). Detecting priority areas to introduce multi-beneficial climate change adaptation measures is set to be a key task for the cities long-term strategies to improve climatic conditions across different urban structures and scales. We introduce a simple and fast spatial modelling approach to carry out fine-scale simulations for land surface temperature (LST), mean radiant temperature (MRT) and Universal Thermal Climate Index (UTCI) in a 2D environment. Capabilities of our modelling approach are demonstrated in evaluating urban thermal comfort in the alpine city of Innsbruck, the capital of Tyrol in western Austria. Results show a major contrast between sealed and vegetated surfaces reflected in the distributional patterns and values of LST, MRT and UTCI, correlating with the appearance and frequency of specific surface classes. We found the Sky View Factor to have a substantial impact on calculations for bioclimatic conditions and see high-albedo surfaces decrease LST but increase the apparent temperature (MRT and UTCI values) effecting human thermal comfort. Furthermore, MRT and UTCI are more sensitive to changes in emissivity values, whereas LST is more sensitive to changes in Bowen Ratio values. Application of our modelling approach can be used to identify priority areas and maximise multi-functionality of climate change adaptation measures, to support urban planning processes for heat mitigation and the implementation of policy suggestions to achieve sustainable development goals and other political objectives.
BACKGROUND: Climate change influences patterns of human mobility and health outcomes. While much of the climate change and migration discourse is invested in quantitative predictions and debates about whether migration is adaptive or maladaptive, less attention has been paid to the voices of the people moving in the context of climate change with a focus on their health and wellbeing. This qualitative research aims to amplify the voices of migrants themselves to add nuance to dominant migration narratives and to shed light on the real-life challenges migrants face in meeting their health needs in the context of climate change. METHODS: We conducted 58 semi-structured in-depth interviews with migrants purposefully selected for having moved from rural Bhola, southern Bangladesh to an urban slum in Dhaka, Bangladesh. Transcripts were analysed using thematic analysis under the philosophical underpinnings of phenomenology. Coding was conducted using NVivo Pro 12. FINDINGS: We identified two overarching themes in the thematic analysis: Firstly, we identified the theme “A risk exchange: Exchanging climate change and health risks at origin and destination”. Rather than describing a “net positive” or “net negative” outcome in terms of migration in the context of climate change, migrants described an exchange of hazards, exposures, and vulnerabilities at origin with those at destination, which challenged their capacity to adapt. This theme included several sub-themes-income and employment factors, changing food environment, shelter and water sanitation and hygiene (WaSH) conditions, and social capital. The second overarching theme was “A changing health and healthcare environment”. This theme also included several sub-themes-changing physical and mental health status and a changing healthcare environment encompassing quality of care and barriers to accessing healthcare. Migrants described physical and mental health concerns and connected these experiences with their new environment. These two overarching themes were prevalent across the dataset, although each participant experienced and expressed them uniquely. CONCLUSION: Migrants who move in the context of climate change face a range of diverse health risks at the origin, en route, and at the destination. Migrating individuals, households, and communities undertake a risk exchange when they decide to move, which has diverse positive and negative consequences for their health and wellbeing. Along with changing health determinants is a changing healthcare environment where migrants face different choices, barriers, and quality of care. A more migrant-centric perspective as described in this paper could strengthen migration, climate, and health governance. Policymakers, urban planners, city corporations, and health practitioners should integrate the risk exchange into practice and policies.
The mean radiant temperature (T(mrt)) is the most important meteorological factor influencing human thermal comfort in urban areas. Numerous methods have been implemented for estimating T(mrt) using measured radiometer or thermometer data, and exhibit different levels of accuracy. This study presents a simple technique based on the traditional method (T(mrt_TM)) to estimate T(mrt) by utilizing measured radiation data from the radiometers. The estimated T(mrt) values from the six-directional method (T(mrt_SM)) and two black globe thermometer methods (T(mrt_BG) and T(mrt_BGv)) at two stations (sky view factor 0.69 and 0.94) in Jeju, Republic of Korea, for 8 days (5 sunny days, 3 (semi-) cloudy days) in spring and summer were used to validate the T(mrt_TM). The results showed that the mean differences between T(mrt_TM) and T(mrt_SM) were within the required accuracy for comfort in ISO 7726 (±?2 ?) on sunny days and were reduced to 0.1-0.3 ? in high T(mrt) conditions such as clear summer days. The T(mrt_BG) in most sunny and semi-cloudy days and T(mrt_BGv) on all days resulted in large mean differences from the T(mrt_TM) that exceeded the required accuracy for thermal stress in ISO 7726 (±?5 ?). Therefore, both black globe thermometer methods should be used carefully when estimating T(mrt), especially during sunny days. The correlations between T(mrt_TM) and T(mrt_SM) were highly significant, 0.93 on all days (p?=?0.01). The newly developed regression equations between T(mrt_TM) and T(mrt_SM) could reduce mean differences within 0.5 ? for all days, and their r(2) values exceeded 0.87. Therefore, the simple T(mrt_TM) technique can be used for T(mrt) estimation in human thermal comfort studies.
While weather stations generally capture near-surface ambient air temperature (Ta) at a high temporal resolution to calculate daily values (i.e., daily minimum, mean, and maximum Ta), their fixed locations can limit their spatial coverage and resolution even in densely populated urban areas. As a result, data from weather stations alone may be inadequate for Ta-related epidemiology particularly when the stations are not located in the areas of interest for human exposure assessment. To address this limitation in the Megalopolis of Central Mexico (MCM), we developed the first spatiotemporally resolved hybrid satellite-based land use regression Ta model for the region, home to nearly 30 million people and includes Mexico City and seven more metropolitan areas. Our model predicted daily minimum, mean, and maximum Ta for the years 2003-2019. We used data from 120 weather stations and Land Surface Temperature (LST) data from NASA’s MODIS instruments on the Aqua and Terra satellites on a 1?×?1 km grid. We generated a satellite-hybrid mixed-effects model for each year, regressing Ta measurements against land use terms, day-specific random intercepts, and fixed and random LST slopes. We assessed model performance using 10-fold cross-validation at withheld stations. Across all years, the root-mean-square error ranged from 0.92 to 1.92?K and the R (2) ranged from .78 to .95. To demonstrate the utility of our model for health research, we evaluated the total number of days in the year 2010 when residents ?65?years old were exposed to Ta extremes (above 30°C or below 5°C). Our model provides much needed high-quality Ta estimates for epidemiology studies in the MCM region.
Over the 21st century, human-caused climate change is projected to vastly increase the occurrence of severe heat, which has deleterious health, economic, and societal impacts. Over the same period, global human population is expected to increase from 7.8 to 10.9 billion, placing more people in harm’s way. Here, we combine projections of sustained heat from climate models with spatially explicit population projection scenarios. We find that: (1) by 2090, high climate change and population growth scenarios show a -5-, -10-, and -100-1000-fold increase in the population exposed to a mean hottest monthly temperature of 30 degrees C, 35 degrees C, and 40 degrees C, respectively; (2) globally, population growth, warming, and their interaction, are the major drivers for the increase in exposure at milder, harsher, and extreme, temperatures, respectively; and (3) differences between population growth scenarios show that policy can potentially reduce the level of increase in exposure by up to 70%. Based on our analyses, the major driver for the increased heat exposure is the dangerous combination between global warming and population growth in already-warm cities in regions like Africa, India, and the Middle East.
Air pollution has become a threat to human health in urban settlements, ultimately leading to negative impacts on overall economic system as well. Already developed nations and still developing countries both are at the risk of air pollution globally. In this scenario, this work aims to investigate the associations of asthma (AS) and acute upper respiratory infection (ARI) patients with satellite-based aerosol optical depth (AOD) and meteorological factors, i.e., relative humidity (RH), temperature (TEMP), and wind speed (WS). We applied second-generation unit root tests to provide empirical evidence. Two sets of unit root tests confirmed mix order of integration, and the other Westerlund co-integration test further showed strong linkages between estimated variables. Fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) tests were applied, only to explore that TEMP and WS lower the number of AS and ARI patients, but RH and AOD increase the number of patients. Therefore, in accordance with these findings, our study provides some important policy instruments to improve the health status in megacities of Pakistan.
Heatwaves-excessively hot ambient conditions that are considered a serious threat to human health-are often associated with poor air quality. The aim of this study was to examine the impact of an early heatwave episode in an industrialized plain in the eastern Mediterranean region (Thriasio, Greece) on human thermal discomfort and urban air quality. The heatwave occurred in mid (15-20) May 2020, shortly after some of the restrictions that were improsed to halt the spread of coronavirus disease 2019 (COVID-19) in Greece were lifted (on 4 May). The discomfort index (DI) and the daily air quality index (DAQI) were calculated on an hourly basis throughout spring 2020 (March, April, May) using data from two stations that measure meteorological parameters and air pollutant concentrations in the Thriasio Plain. The analysis showed that the air temperature increased during 7-17 May to levels that were more than 10 °C above the monthly average value (25.8 °C). The maximum measured air temperature was 38 °C (on 17 May). The results showed a high level of thermal discomfort. The DI exceeded the threshold of 24 °C for several hours during 13-20 May. Increased air pollution levels were also identified. The average DAQI was estimated as 0.83?±?0.1 and 1.14?±?0.2 at two monitoring stations in the region of interest during the heatwave. Particulate matter (diameter < 10 ?m) appeared to contribute significantly to the poor air quality. Significant correlations between the air temperature, DI, and AQSI were also identified.
There is a well-established relationship between temperature and mortality, with older individuals being most at risk in high-income settings. This raises the question of the degree to which lives are being shortened by exposure to heat or cold. Years of life lost (YLL) take into account population life expectancy and age at which mortality occurs. However, YLL are rarely used as an outcome-metric in studies of temperature-related mortality. This represents an important gap in knowledge; to better comprehend potential impacts of temperature in the context of climate change and an ageing population, it is important to understand the relationship between temperature and YLL, and also whether the risks of temperature related mortality and YLL have changed over recent years. Gridded temperature data derived from observations, and mortality data were provided by the UK Met Office and the Office for National Statistics (ONS), respectively. We derived YLL for each death using sex-specific yearly life expectancy from ONS English-national lifetables. We undertook an ecological time-series regression analysis, using a distributed-lag double-threshold model, to estimate the relationship between daily mean temperature and daily YLL and mortality between 1996 and 2013 in Greater London, the West Midlands including Birmingham, and Greater Manchester. Temperature-thresholds, as determined by model best fit, were set at the 91st (for heat-effects) and 35th (for cold-effects) percentiles of the mean temperature distribution. Secondly, we analysed whether there had been any changes in heat and cold related risk of YLL and mortality over time. Heat-effects (lag 0-2 days) were greatest in London, where for each 1 °C above the heat-threshold the risk of mortality increased by 3.9% (CI 3.5%, 4.3%) and YLL increased by 3.0% (2.5%, 3.5%). Between 1996 and 2013, the proportion of total deaths and YLL attributable to heat in London were 0.50% and 0.40% respectively. Cold-effects (lag 0-27 days) were greatest in the West Midlands, where for each 1 °C below the cold-threshold, risk of mortality increased by 3.1% (2.4%, 3.7%) and YLL also increased by 3.1% (2.2%, 3.9%). The proportion of deaths and YLL attributable to cold in the West Midlands were 3.3% and 3.2% respectively. We found no evidence of decreasing susceptibility to heat and cold over time. The addition of life expectancy information into calculations of temperature-related risk and mortality burdens for English cities is novel. We demonstrate that although older individuals are at greatest risk of temperature-related mortality, heat and cold still make a significant contribution to the YLL due to premature death.
BACKGROUND: Extreme weather events happen more frequently along with global warming and they constitute a challenge for public health preparedness. For example, many investigations showed heavy rainfall was associated with an increased risk of acute gastroenteritis. In this study, we examined the associations between different meteorological factors and paediatric acute gastroenteritis in an affluent setting in China controlling for pollutant effects. METHODS: Aggregated total weekly number of intestinal infection-related hospital admissions, and meteorological and air pollution data during 1998-2018 in Hong Kong were collected and analysed by a combination of quasi-Poisson generalized additive model and distributed lag nonlinear model. Study population was restricted to children under 5 years of age at the time of admission. RESULTS: While heavy rainfall did not exhibit a statistically significant association with the risk of paediatric admission due to intestinal infections, low temperature and humidity extremes (both relative humidity and vapour pressure) did. Compared with the temperature at which the lowest risk was detected (i.e. 22.5 °C), the risk was 6.4% higher (95% confidence interval: 0.0% to 13.0% at 15.1 °C (i.e. the 5th percentile)). We also found the risk of paediatric admission was statistically significantly associated with an increase in the number of extreme cold days in a week over the study period. CONCLUSION: Cold condition may have greater impact on disease transmission through increased stability and infectivity of enteric viruses in affluent settings like Hong Kong and thus resulted in an increased risk for paediatric acute gastroenteritis. On the contrary, an insignificant impact from heavy rainfall and high temperature may indicate a minor effect on disease transmission through bacterial growth in contaminated food and water. With the identified impacts of weather factors, extreme weather events are likely to distort the prevalence and seasonal pattern of diarrhoeal diseases in the future.
The purpose of this study is to analyze and compare the human suffering exacerbation processes in the coastal metropolitan areas of Nagoya, New Orleans and Metro Manila caused by 1959 Typhoon Isewan, 2005 Hurricane Katrina and 2009 Tropical Storm Ondoy, respectively, in order to understand disasters. The research method applied was firstly to create a timeline of each disaster process with disaster responses by referring to newspapers, literature, and others, then the facts were categorized with similar social conditions and government responses to establish a hypothesis. Field surveys were conducted to verify the hypothesis. The research outcome shows the human suffering exacerbation processes of these three large-scale disasters can be seen that the pattern of the process is the same; however, the duration and content of each disaster are quite different. These differences mainly depend on social backgrounds, disaster subculture, and disaster management by local and national governments. Based on the above research findings, a useful view for disaster investigation and disaster management is clarified, along with the possible contributions of disaster countermeasures’ timeline development, especially for the disaster management in metropolitan areas.
To prevent the risk associated with heat-related health, several countries and institutions have built heat-health warning systems (HHWS). An HHWS is designed to alert the general public and decision-makers about the danger of high temperature by triggering a series of actions that avoid adverse health outcomes. The comparison of the various HHWS is complicated because there is no universal quantitative definition to predict and define a heatwave. The slightest variability at the threshold of definition the heatwave can trigger considerable differences in the action plan, health service demand and the time the population at risk must prepare. The choice of the index influences the number of days of heatwaves and its characteristics, such as severity. Estimating the risk of mortality associated with heatwave is variable according to the indexes, and the selection of the threshold is essential to prevent the burdens of heat on public health. The aim is the comparison between two metrics to know, which has higher predictive power to prevent health risks related to heat. On the one hand, a new way of defining heatwaves that have generated high consensus worldwide – the Excess Heat Factor (EHF); on the other hand, the Generalized Accumulated Thermal Overload (GATO IV) – an opportunity to improve the existing Lisbon heatwaves surveillance system. Daily mortalities and air temperatures from 1980 to 2016 in Lisbon with both indexes are modelled using Generalized Linear Models, with the calculation of the predictive power of the models using ROC curves for two levels of mortality severity. It is concluded that for total mortality, both indexes were statistically significant. Though, for daily mortality in individuals with 65 years or older with all diseases of the circulatory and respiratory system, when considering both indexes together, GATO IV was the only index significantly predicting the impact of heatwaves on mortality. GATO IV metric seems to have the best statistical properties. Nevertheless, EHF also stands out as a good indicator to predict heat-related mortality in Lisbon.
Urban Heat Island (UHI) effect has become one of the most significant hazards for cities, presenting a challenge for dense anthropic areas affected by climate change with enormous consequences for health and human wellbeing. Ecosystem Services (ES) are increasingly attracting attention for their use in setting urban design parameters and criteria which can be deployed in planning and projects, also considering the Cooling Capacity (CC) useful to mitigate heatwaves effect and high temperatures. The paper investigates how ES assessment could support the definition of urban design parameters influencing the CC of cities. We modelled CC in the city of Milan using InVEST software identifying the urban design criteria that most influence temperature and associated urban comfort. This empirical test was conducted by selecting different urban districts built during four main historical periods which correspond to four urban planning approaches, namely: 1) Cited Berutiana; 2) Clan Moderna; 3) Gina anni ’60-’70 and 4) Cited Contemporanea. Results demonstrate how different urban planning approaches have shaped the design of the city in terms of green areas, permeability, built-up footprint, and tree density and cover while influencing the CC of the system.
Since the first report in December 2019, the novel coronavirus (COVID-19) has spread to most parts of the world, with over 21.5 million people infected and nearly 768,000 deaths to date. Evidence suggests that transmission of the virus is primarily through respiratory droplets and contact routes, and airborne carriers such as atmospheric particulates and aerosols have also been proposed as important vectors for the environmental transmission of COVID-19. Sewage and human excreta have long been recognized as potential routes for transmitting human pathogens. The causative agent of the COVID-19 pandemic, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been detected in human feces and urine, where it could remain viable for days and show infectivity. Urban flooding, a common threat in summer caused by heavy rainfalls, is frequently reported in urban communities along with sewage overflows. With summer already underway and economy re-opening in many parts of the world, urban flooding and the often-accompanied sewage overflows could jeopardize previous mitigation efforts by posing renewed risks of virus spread in affected areas and communities. In this article, we present the up-to-date evidence and discussions on sewage-associated transmission of COVID-19, and highlighted the roles of sewage overflow and sewage-contaminated aerosols in two publicized events of community outbreaks. Further, we collected evidence in real-life environments to demonstrate the shortcuts of exposure to overflowed sewage and non-dispersed human excreta during a local urban flooding event. Given that communities serviced by combined sewer systems are particularly prone to such risks, local municipalities could prioritize wastewater infrastructure upgrades and consider combined sewer separations to minimize the risks of pathogen transmission via sewage overflows during epidemics.
Mitigation and adaption measures must be designed strategically by urban planners, designers, and decision-makers to reduce urban heat island (UHI) related risks. We employed the Weather Research and Forecasting (WRF) model to assess UHI mitigation scenarios for the tropical city of Singapore during April 2016, including two heat wave periods. The local climate zones for Singapore were used as the land use/land cover data to account for the intra-urban variability. The simulations show that the canopy layer UHI intensity in Singapore can reach up to 5 degrees C in compact areas during nighttime. The results reveal that city-scale deployment of cool roofs can provide an overall reduction of 1.3 degrees C in the near-surface daytime air temperature in large lowrise areas. Increasing the thermostat set temperature to 25 degrees C from 21 degrees C in city-wide buildings can potentially reduce the air temperature due to less (similar to 20%) waste heat discharge from airconditioning units. A densification scenario considering an increase from approximately 7 841 people/km(2) (2016) to 9040-9,600 people/km(2) (2030) under the current climate leads to air temperature increase of 1.4 degrees C, which demonstrates the importance of limiting the densification of less compact areas in maintaining thermal comfort in the future.
Objectives. To examine the relationships among environmental characteristics, temperature, and health outcomes during heat advisories at the geographic scale of street segments.Methods. We combined multiple data sets from Boston, Massachusetts, including remotely sensed measures of temperature and associated environmental characteristics (e.g., canopy cover), 911 dispatches for medical emergencies, daily weather conditions, and demographic and physical context from the American Community Survey and City of Boston Property Assessments. We used multilevel models to analyze the distribution of land surface temperature and elevated vulnerability during heat advisories across streets and neighborhoods.Results. A substantial proportion of variation in land surface temperature existed between streets within census tracts (38%), explained by canopy, impervious surface, and albedo. Streets with higher land surface temperature had a greater likelihood of medical emergencies during heat advisories relative to the frequency of medical emergencies during non-heat advisory periods. There was no independent effect of the average land surface temperature of the census tract.Conclusions. The relationships among environmental characteristics, temperature, and health outcomes operate at the spatial scale of the street segment, calling for more geographically precise analysis and intervention. (Am J Public Health. Published online ahead of print May 21, 2020: e1-e8. doi:10.2105/AJPH.2020.305636).
Heat stress has been recognized as one of the consequences of climate change in urban areas. Its adverse effects on the urban population range from economy, social, environment, and human health. With the increasing urbanization and economic development in cities, heat stress is expected to worsen. This particular study aims to achieve two objectives: (1) to understand the determinants of heat stress, especially the roles of the urban environment in exacerbating the heat stress, and (2) to explore the effects of heat stress to human health using self-reported health assessment. We employed a cross-sectional study using a survey questionnaire from 505 respondents living in the urban area of Bangkok, Thailand. We found that socioeconomic conditions of the individual and urban environment were significant determinants of urban heat stress. Low-income urban populations living in high-density areas with less green open space were more likely to experience heat stress. We also found that heat stress significantly affects human health. Those who reported a higher level of heat stress were more likely to have adverse health and well-being outcomes. The findings suggest that the increased risk of heat stress represents a major problem in the Bangkok, Thailand. It is necessary to address heat stress in adaptation policy and measures at the city levels amid the continued increase of global temperature and climate change.
The urban heat island effect creates warmer and drier conditions in urban areas than in their surrounding rural areas. This effect is predicted to be exacerbated in the future, under a climate change scenario. One way to mitigate this effect is to use the urban green infrastructure as a way to promote the cooling island effect. In this study we aimed to model, with a high spatial resolution, how Mediterranean urban parks can be maximized to be used as cooling islands, by answering the following questions: i) which factors influence the cooling effect and when?; ii) what type of green spaces contributes the most to the cooling effect?; iii) what is the cooling distance of influence? To answer these questions we established a sampling design where temperature and relative humidity were measured in different seasons, in locations with contrasting characteristics of green and grey cover. We were able to model the effect of green and grey spaces in the cooling island effect and build high spatial resolution predicting maps for temperature and relative humidity. Our study showed that even green spaces with reduced areas can regulate microclimate, alleviating temperature by 1-3 °C and increasing moisture by 2-8%, on average. Green spaces with a higher density of trees were more efficient in delivering the cooling effect. The morphology, aspect and level of exposure of grey surfaces to the solar radiation were also important features included in the models. Green spaces influenced temperature and relative humidity up to 60 m away from the parks’ limits, whereas grey areas influenced in a much lesser range, from 5 m up to 10 m. These models can now be used by citizens and stakeholders for green spaces management and human well-being impact assessment.
As the literature on heat tolerance suggests that the elderly are generally more heat-intolerant and suffer more from the substantial impacts of excessive heat on human health, exacerbated by their higher rate of chronic diseases, it is important to learn how to better protect this vulnerable population. Moreover, many studies have shown that, despite their vulnerability, the elderly do not necessarily perceive themselves as being at risk or see heat waves as a danger to their health. This lower risk perception could hinder their adoption of adaptive behavior. Thus, using the theory of planned behavior and the health belief model, this study aimed at developing a more thorough understanding of what motivates older people from the province of Quebec, Canada, to adopt pro-adaptive behaviors to protect themselves from the heat, to better predict and explain their self-reported heat adaptation behaviors, and to identify their most important beliefs. In this quantitative study, a telephone sample of 1002 persons was used to explore the decision-making process of seniors in a way that led us to illustrate specific variables that could be targeted for awareness raising. All three variables of the theory of planned behavior (i.e., attitude, perceived social pressure, and perceived behavioral control) had a statistically significant impact on intention to adapt, while intention itself was linked to adoption of adaptive behaviors. This shows that increasing elderly people’s intention to adapt can have a positive impact on their adaptation to heat, which could help prevent this at-risk population from suffering the dangerous effects of heat waves.
BACKGROUND: In the Republic of Congo, hot temperature and seasons distortions observed may impact the development of malaria parasites. We investigate the variation of malaria cases, parasite density and the multiplicity of Plasmodium falciparum infection throughout the year in Brazzaville. METHODS: From May 2015 to May 2016, suspected patients with uncomplicated malaria were enrolled at the Hôpital de Mfilou, CSI « Maman Mboualé», and the Laboratoire National de Santé Publique. For each patient, thick blood was examined and parasite density was calculated. After DNA isolation, MSP1 and MSP2 genes were genotyped. RESULTS: A total of 416, 259 and 131 patients with suspected malaria were enrolled at the CSI «Maman Mboualé», Hôpital de Mfilou and the Laboratoire National de Santé Publique respectively. Proportion of malaria cases and geometric mean parasite density were higher at the CSI «Maman Mboualé» compared to over sites (P-value <0.001). However the multiplicity of infection was higher at the Hôpital de Mfilou (P-value <0.001). At the Laboratoire National de Santé Publique, malaria cases and multiplicity of infection were not influenced by different seasons. However, variation of the mean parasite density was statistically significant (P-value <0.01). Higher proportions of malaria cases were found at the end of main rainy season either the beginning of the main dry season at the Hôpital de Mfilou and the CSI «Maman Mboualé»; while, lowest proportions were observed in September and January and in September and March respectively. Higher mean parasite densities were found at the end of rainy seasons with persistence at the beginning of dry seasons. The lowest mean parasite densities were found during dry seasons, with persistence at the beginning of rainy seasons. Fluctuation of the multiplicity of infection throughout the year was observed without significance between seasons. CONCLUSION: The current study suggests that malaria transmission is still variable between the north and south parts of Brazzaville. Seasonal fluctuations of malaria cases and mean parasite densities were observed with some extension to different seasons. Thus, both meteorological and entomological studies are needed to update the season's periods as well as malaria transmission intensity in Brazzaville.
Cities are particularly sensitive to the effects of climate change, causing an increasing incidence of heat waves. Extreme temperatures can impair the use of public spaces in cities, as heat stress endangers human well-being and health. Identifying suitable adaptation measures to maintain the full functionality of public spaces requires a multidimensional approach, accounting for interrelated scientific, social, and practical aspects. As one result we introduce an inter- and transdisciplinary concept that addresses the challenge of adapting public spaces to climate change. Additionally we present a pilot study from Heidelberg, Germany, where a new, sustainable urban quarter experienced more pronounced heat stress than the historic city centre in the hot and dry summer of 2018. The study shows the suitability of our approach to identify appropriate heat adaptation measures. Solar potential modelling and mental map surveys proved to be particularly effective methods. We find that adaptation measures generate synergy effects by improving both climatic and social conditions.
INTRODUCTION: Epidemic thunderstorm asthma (ETSA) is due to a complex interaction of environmental and individual susceptibility factors, with outbreaks reported globally over the last four decades. Australia has been particularly susceptible with nearly half of episodes reported internationally, culminating in the catastrophic Melbourne 2016 event. AREAS COVERED: Reported ETSA episodes are reviewed for common environmental and meteorological risk factors. Allergen aerobiology interaction with thunderstorm activity and rapid weather condition changes is examined. Assessment of the clinical and immunological data highlights risk factors for ETSA presentation, hospital admission, and intensive care admission. Risk factors associated with ETSA deaths are evaluated. Public health strategies, as well as pharmacological and immunological management approaches to reduce individual susceptibility and prevent ETSA are discussed. EXPERT OPINION: Improved understanding of the specific meteorological factors predisposing to the greatest risk of ETSA to improve forecasting is required. Better monitoring of aeroallergen levels in areas of greatest geographic risk, with further research into allergen aerobiology underpinning mechanisms of allergen exposure is needed. The role of climate change in increasing the risk of ETSA outbreaks requires further research. Public awareness and education are required to reduce exposure, and to improve uptake of pharmacological and immunological risk reduction and preventive strategies.
Nitrogen dioxide (NO(2)) is an air pollutant discharged from combustion of human activities. Nitrous acid (HONO), measured as NO(2), is thought to impact respiratory function more than NO(2). HONO and NO(2) have an equilibrium relationship, and their reaction is affected by climate conditions. This study was conducted to discuss the extent of HONO contained in NO(2), depending on the level of urbanization. Whether climate conditions that promote HONO production enhanced the level of NO(2) measured was investigated using time series analysis. Climate and outdoor air pollution data measured in April 2009-March 2017 in urban (Tokyo, Osaka, and Aichi) and rural (Yamanashi) areas in Japan were used for the analysis. Air temperature had a trend of negative associations with NO(2), which might indicate the decomposition of HONO in the equilibrium between HONO and NO(2). The associations of relative humidity with NO(2) did not have consistent trends by prefecture: humidity only in Yamanashi was positively associated with NO(2). In high relative humidity conditions, the equilibrium goes towards HONO production, which was observed in Yamanashi, suggesting the proportion of HONO in NO(2) might be low/high in urban/rural areas.
BACKGROUND: We assessed the association between multiple meteorological factors and air pollutants and the number of acute myocardial infarction (AMI) cases using a multi-step process. METHODS: Daily AMI hospitalizations matched with 16 meteorological factors and air pollutants in 7 metropolitan provinces of the Republic of Korea from 2002 to 2017 were analyzed. We chose the best fit model after conducting the Granger causality (GC) test and examined the daily lag time effect on the orthogonalized impulse response functions. To define dose-response relationships, we performed a time series analysis using multiple generalized additive lag models based on seasons. RESULTS: A total of 196,762 cases of AMI in patients older than 20 years admitted for hospitalization were identified. The distribution of meteorological factors and air pollutants showed characteristics of a temperate climate. The GC test revealed a complex interaction between meteorological factors, including air pollutants, and AMI. The final selected factors were NO(2) and temperature; these increased the incidence of AMI on lag day 4 during summer (NO(2): population-attributable fraction [PAF], 3.9%; 95% confidence interval [CI], 3.6-4.0; mean temperature: PAF, 3.3%; 95% CI, 2.7-3.9). CONCLUSIONS: This multi-step time series analysis found that average temperature and NO(2) are the most important factors impacting AMI hospitalizations, specifically during summer. Based on the model, we were able to visualize the effect-time association of meteorological factors and air pollutants and AMI.
OBJECTIVES: Preterm births (PTBs) represent significant health risks, and several studies have found associations between high outdoor temperatures and PTB. We estimated both the total and natural direct effects (independent of particulate matter, ozone and nitrogen dioxide air pollutants) of the prior 2-day mean apparent temperature (AT) on PTB. We evaluated effect modification by maternal age, race, education, smoking status and prenatal care. DESIGN AND SETTING: We obtained birth records and meteorological data for the Detroit, Michigan, USA area, for the warm months (May to September), 1991 to 2001. We used a time series Poisson regression with splines of AT, wind speed, solar radiation and citywide average precipitation to estimate total effects. To accommodate multiple mediators and exposure-mediator interactions, AT inverse odds weights, predicted by meteorological and air pollutant covariates, were added in a subsequent model to estimate direct effects. RESULTS: At 24.9°C relative to 18.6°C, 10.6% (95% CI: 3.8% to 17.2%) of PTBs were attributable to the total effects of AT, and 10.4% (95% CI: 2.2% to 17.5%) to direct effects. Relative excess risks of interaction indicated that the risk of PTB with increasing temperature above 18.6°C was significantly lower among black mothers and higher among mothers less than 19, older than 30, with late or no prenatal care and who smoked. CONCLUSION: This additional evidence of a direct association between high temperature and PTB may motivate public health interventions to reduce extreme heat exposures among pregnant women, particularly among those who may have enhanced vulnerability.
It is well known that sudden variations of air temperature have the potential to cause severe impacts on human health. Therefore, it becomes necessary to provide information capable of quantifying the severity of the problem, considering that the continuous increase of temperature due to global warming and urban development will cause more intense effects in heavily populated areas. Due to its geographical location and local characteristics, Ecuador, a country located on the western coast of South America, is characterized by a high vulnerability to climatic extremes. The present research develops an evaluation of urban climate change effects through the analysis of extreme temperature indices using four meteorological stations situated in the city of Guayaquil (southwest Ecuador). Since the available data are not adequate for extreme temperature indices criteria, it was necessary to employ an infilling method for times series in an innovative way that can be applicable at the small scale. Thus, a cross-correlation-enhanced inverse distance weighting (CC-IDW) method was proposed. The method entails a spatial interpolation based on data of urban stations situated outside of Guayaquil by taking into account cross-correlation among times series at precise lags that leads to an improvement in the way of estimating the missing values. Subsequently, a homogeneity test, data quality control and the calculation of extreme temperature indices chosen from those proposed by the World Meteorological Organization (WMO) were implemented. The results show that there is a general tendency of warming with quite homogenous temperatures for all considered stations. However, it should be recognized that the climate pattern of this region is strongly modulated by the El Nino Southern Oscillation (ENSO) cycle. Only for two extreme indices: the highest maximum temperature (TXx) and the warm days (TX90p), are the resulting trend co-efficients statistically significant. The study suggests a deteriorated climatic condition due to heat stress that warrants further study using the available database for the city of Guayaquil.
Disaster risk is a complex, uncertain and evolving threat to society which changes based on broad drivers of hazard, exposure and vulnerability such as population, economic and climatic change, along with new technologies and social preferences. It also evolves as a function of decisions of public policy and public/private investment which alters future risk profiles. These factors however are often not captured within disaster risk assessments and explicitly excluded from the UN General Assembly definition of a disaster risk assessment which focuses on the current state of risk. This means that 1) we cannot adequately capture changes in risk and risk assessments are out of date as soon as published but also 2) we cannot show the benefit of proactive risk treatments in our risk assessments. This paper therefore outlines a generic, scale-neutral, framework for integrating foresight – thinking about the future – into risk assessment methodologies. This is demonstrated by its application to a disaster risk assessment of heatwave risk in Tasmania, Australia, and shows how risk changes across three future scenarios and what proactive treatments could be possible mitigating the identified drivers of future risk.
Climate change is imposing substantial consequences across physical and social infrastructures. The extent of social disruption and risk to human health are, however, potentially much broader than these general consequences, taken individually, would suggest. To address this gap, we assess the distribution of contaminated sites in the United States (US) and then estimate the impact that flood hazards in urban areas will have on these contaminated sites. Using these measures, we draw inferences about the risk of contamination from climate impacted extreme weather events, climate adaptation at the local level, social risk and how it is distributed, and a broader understanding of the potential global consequences of climate change. In this paper we address three critical points: 1) the role classification of contaminated sites on our understanding of risk due to climate change; 2) the relationship between contaminated sites and flood risk; and 3) the potential for climate adaption strategies to mediate this risk. We estimate that of the roughly one-third of the US population living in urban areas, up to 3,338,518 people, are living in high-risk flood zones near contaminated sites. Our results suggest severe potential implications for estimates of the negative consequences from climate change and contamination and provide critical insights into the relationship between climate change and the built environment for urban planners and environmental policy makers and managers alike.
Ticks may transmit a variety of human and animal pathogens. Prevalence of Borrelia spp., Rickettsia spp. and Anaplasma phagocytophilum in ticks has been monitored in the city of Hanover, Germany, since 2005. However, to determine the infection risk for humans and animals, not only pathogen prevalence, but also tick abundance and seasonality need to be taken into account. Therefore, the aim of this study was to investigate tick abundance at ten different collection sites in the city of Hanover, Germany. Collection of questing ticks was performed by the flagging method in the first and second half of each month during the tick season (April-October) in 2017 and 2018. At each 200 m² collection site, one of four 50 m² fields was sampled per visit on a rotational basis, resulting in 100 m² sampled per month. In addition, data on weather conditions, near-ground temperature, relative humidity and vegetation composition were noted at each collection event. In 2017, a total of 1770 ticks were collected, while 1866 ticks were collected in 2018. Ixodes ricinus was the most prevalent species (97.0 % of all ticks, 98.0 % of nymphs, 91.6 % of adults) followed by I. inopinatus (2.3 % of all ticks, 1.1 % of nymphs, 8.0 % of adults), I. frontalis (0.6 % of all ticks, 0.6 % of nymphs, 0.3 % of adults) and I. hexagonus (0.03 % of all ticks, 0.03 % of nymphs, 0.0 % of adults). Using generalized linear mixed modeling, density of I. ricinus and I. inopinatus in 2017 was significantly higher than in 2018. Regarding different landscape types, ticks were significantly more abundant in mixed forests than in parks, with more than 50 ticks/100 m² on average in both years. In urban parks, average tick density amounted to 15 ticks/100 m² in 2017 and 11 ticks/100 m² in 2018 and in broad-leaved forests average tick density was 13 and 18 ticks/100 m² in 2017 and 2018, respectively. Tick density showed a marked peak in June 2017 and in May 2018 at most sites, whereas a less pronounced peak was recognizable in September. Tick density varied considerably between collection sites. However, no statistically significant effect of (micro-)climatic variables, including near-ground temperature, relative humidity and saturation deficit, was found. Thus, further factors, such as the abundance of wildlife hosts, need to be considered in future studies to explain the differences between collection sites.
The aim of the paper is to describe the spread forest fire event occurred in the Italian Alps in 2017 under extremely drought conditions. In the study the root causes of wildfires and their direct relapses to the air quality of the Western Po valley and the urban centre of Torino have been assessed by means of air pollution measurements (focused to particulate matter with reference samplers and optical particle counters OPCs), meteorological indicators and additional public data. Results show a good correlation among different urban sites and instrument technologies. Concentration data, compared with environmental conditions and historical values describe the clear impact of fires on both local and regional air quality. Indeed, the deferred impact of wildfires on the local wood biomass energy supply chain is briefly outlined. (C) 2019 Published by Elsevier Ltd.
Climate change is resulting in heatwaves that are more frequent, severe, and longer lasting, which is projected to double-to-triple the heat-related mortality in Boston, MA if adequate climate change mitigation and adaptation strategies are not implemented. A case-only analysis was used to examine subject and small-area neighborhood characteristics that modified the association between hot days and mortality. Deaths of Boston, Massachusetts residents that occurred from 2000-2015 were analyzed in relation to the daily temperature and heat index during the warm season as part of the case-only analysis. The modification by small-area (census tract, CT) social, and environmental (natural and built) factors was assessed. At-home mortality on hot days was driven by both social and environmental factors, differentially across the City of Boston census tracts, with a greater proportion of low-to-no income individuals or those with limited English proficiency being more highly represented among those who died during the study period; but small-area built environment features, like street trees and enhanced energy efficiency, were able to reduce the relative odds of death within and outside the home. At temperatures below current local thresholds used for heat warnings and advisories, there was increased relative odds of death from substance abuse and assault-related altercations. Geographic weighted regression analyses were used to examine these relationships spatially within a subset of at-home deaths with high-resolution temperature and humidity data. This revealed spatially heterogeneous associations between at-home mortality and social and environmental vulnerability factors.
High air temperatures are a public health threat, causing 1300 deaths annually in the United States (US) along with heat-related morbidity and increased electricity consumption for air-conditioning (AC). Increasing tree canopy cover has been proposed as one way to reduce urban air temperatures. Here, we assemble tree cover and developed land-cover information for 97 US cities, housing 59 million people, and use regression relationships to analyze how much current urban tree cover reduces summer (JJA) air temperatures and associated heat-related mortality, morbidity, and electricity consumption. We find that 78% of urban dwellers are in neighborhoods with less than 20% tree cover. Some 15.0 million people (25% of total) experience a reduction of 0.5-1.0 degrees C from tree cover, with another 7.9 million (13% of total) experiencing a reduction of greater than 1.0 degrees C. Current relationships between temperature and health outcomes imply that urban tree cover helps avoid 245-346 deaths annually. Heat-mortality relationships in the 1980s, when a smaller fraction of US households had AC, imply a greater role in the past for urban tree cover in avoiding heat-related mortality. As AC availability has increased, the value of tree cover for avoiding heat-related mortality has decreased, while the value of tree cover for reducing electricity consumption likely has increased. Currently, for the 97 cities studied, the total annual economic value of avoided mortality, morbidity, and electricity consumption is an estimated $1.3-2.9 billion, or $21-49 annually per capita. Applying our results to the entire US urban population, we estimate urban tree cover annually supplies heat-reduction services worth $5.3-12.1 billion.
Citizen observatories are a relatively recent form of citizen science. As part of the flood risk management strategy of the Brenta-Bacchiglione catchment, a citizen observatory for flood risk management has been proposed and is currently being implemented. Citizens are involved through monitoring water levels and obstructions and providing other relevant information through mobile apps, where the data are assimilated with other sensor data in a hydrological- hydraulic model used in early warning. A cost-benefit analysis of the citizen observatory was undertaken to demonstrate the value of this approach in monetary terms. Although not yet fully operational, the citizen observatory is assumed to decrease the social vulnerability of the flood risk. By calculating the hazard, exposure and vulnerability of three flood scenarios (required for flood risk management planning by the EU Directive on Flood Risk Management) with and without the proposed citizen observatory, it is possible to evaluate the benefits in terms of the average annual avoided damage costs. Although currently a hypothetical exercise, the results showed a reduction in avoided damage of 45 % compared to a business as usual scenario. Thus, linking citizen science and citizen observatories with hydrological modelling to raise awareness of flood hazards and to facilitate two-way communication between citizens and local authorities has great potential in reducing future flood risk in the Brenta-Bacchiglione catchment. Moreover, such approaches are easily transferable to other catchments.
Temperature is widely known to influence the spatio-temporal dynamics of vector-borne disease transmission, particularly as temperatures vary across critical thermal thresholds. When temperature conditions exhibit such ‘transcritical variation’, abrupt spatial or temporal discontinuities may result, generating sharp geographical or seasonal boundaries in transmission. Here, we develop a spatio-temporal machine learning algorithm to examine the implications of transcritical variation for West Nile virus (WNV) transmission in the Los Angeles metropolitan area (LA). Analysing a large vector and WNV surveillance dataset spanning 2006-2016, we found that mean temperatures in the previous month strongly predicted the probability of WNV presence in pools of Culex quinquefasciatus mosquitoes, forming distinctive inhibitory (10.0-21.0°C) and favourable (22.7-30.2°C) mean temperature ranges that bound a narrow 1.7°C transitional zone (21-22.7°C). Temperatures during the most intense months of WNV transmission (August/September) were more strongly associated with infection probability in Cx. quinquefasciatus pools in coastal LA, where temperature variation more frequently traversed the narrow transitional temperature range compared to warmer inland locations. This contributed to a pronounced expansion in the geographical distribution of human cases near the coast during warmer-than-average periods. Our findings suggest that transcritical variation may influence the sensitivity of transmission to climate warming, and that especially vulnerable locations may occur where present climatic fluctuations traverse critical temperature thresholds.
The physical nature of the built urban environment gives rise to urban heat islands (UHI), making many cities frequently thermally uncomfortable in the summer, with potentially serious effects on human health. When climate change effects of higher summer temperatures and prolonged heatwaves are factored in, it is clear that adaptive measures are needed to ensure the liveability of cities. The shade provided by planting trees is one such adaptation measure. This study, in Bolzano, Italy, used a thermal camera to record the surface temperatures of three common urban surfaces – asphalt, porphyry, and grass – in the shade of 332 single tree crowns, of 85 different species, during the peak temperature period of summer days. By comparing with the temperature of adjacent unshaded ground, estimates of the degree of surface cooling were made. Measurements at three locations within the shadow revealed higher cooling in the centre and at the western edge. The cooling was related to a multitude of tree traits, of which Leaf Area Index estimate (LAIcept) and crown width were the most important. Median average cooling of 16.4, 12.9 and 8.5 degrees C was seen in the western edge of the tree shade for asphalt, porphyry and grass, respectively. Maximum temperatures were reduced by roughly 19 degrees C for all surface types. Coniferous trees were capable of providing high cooling, however, crown dimensions may limit the receiving surface area. Descriptive and predictive multiple linear regression models were able to predict cooling with some success from several of the predictor variables (LAIcept and gap fraction). Strategic planting of single trees in cities can have significant impacts on the absorption of solar radiation by ground surface materials thus reducing the heat storage that contributes to UHIs.
The interactive effects between particulate matter (PM) and heat waves on circulatory mortality are under-researched in the context of global climate change. We aimed to investigate the interaction between heat waves and PM on circulatory mortality in Fuzhou, a city characterized by a humid subtropical climate and low level of air pollution in China. We collected data on deaths, pollutants, and meteorology in Fuzhou between January 2016 and December 2019. Generalized additive models were used to examine the effect of PM on circulatory mortality during the heat waves, and to explore the interaction between different PM levels and heat waves on the circulatory mortality. During heat waves, circulatory mortality was estimated to increase by 8.21% (95% confidence intervals (CI): 0.32-16.72) and 3.84% (95% CI: 0.28-7.54) per 10 ?g/m(3) increase of PM(2.5) and PM(10), respectively, compared to non-heat waves. Compared with low-level PM(2.5) concentration on non-heat waves layer, the high level of PM(2.5) concentration on heat waves layer has a significant effect on the cardiovascular mortality, and the effect value was 48.35% (95% CI: 6.37-106.89). Overall, we found some evidence to suggest that heat waves can significantly enhance the impact of PM on circulatory mortality.
Levees protect floodplain areas from frequent flooding, but they can paradoxically contribute to more severe flood losses. The construction or reinforcement of levees can attract more assets and people in flood-prone area, thereby increasing the potential flood damage when levees eventually fail. Moreover, structural protection measures can generate a sense of complacency, which can reduce preparedness, thereby increasing flood mortality rates. We explore these phenomena in the Jamuna River floodplain in Bangladesh. In this study area, different levels of flood protection have co-existed alongside each other since the 1960s, with a levee being constructed only on the right bank and its maintenance being assured only in certain places. Primary and secondary data on population density, human settlements, and flood fatalities were collected to carry out a comparative analysis of two urban areas and two rural areas with different flood protection levels. We found that the higher the level of flood protection, the higher the increase of population density over the past decades as well as the number of assets exposed to flooding. Our results also show that flood mortality rates associated with the 2017 flooding in Bangladesh were lower in the areas with lower protection level. This empirical analysis of the unintended consequences of structural flood protection is relevant for the making of sustainable policies of disaster risk reduction and adaptation to climate change in rapidly changing environments.
The impacts of heat waves in a warming climate depend not only on changing temperatures but also on changing humidity. Using 35 simulations from the Community Earth System Model Large Ensemble (CESM LENS), we investigate the long-term evolution of the joint distribution of summer relative humidity (RH) and daily maximum temperature (Tmax) near four U.S. cities (New York City, Chicago, Phoenix, and New Orleans) under the high-emissions Representative Concentration Pathway (RCP) 8.5. We estimate the conditional quantiles of RH givenTmaxwith quantile regression models, using functions of temperature for each city in July for three time periods (1990-2005, 2026-2035, and 2071-2080). Quality-of-fit diagnostics indicate that these models accurately estimate conditional quantiles for each city. As expected, each quantile ofTmaxincreases from 1990-2005 to 2071-2080, while mean RH decreases modestly. Conditional upon a fixed quantile ofTmax, the median and high quantiles of RH decrease, while those of the Heat Index (HI) and dew point both increase. This result suggests that, despite a modest decrease in median relative humidity, heat stress measured by metrics considering both humidity and temperature in a warming climate will increase faster than that measured by temperatures alone would indicate. For a fixedTmax, the high quantiles of RH (and thus of HI and dew point) increase from 1990-2005 to 2071-2080 in all four cities. This result suggests that the heat stress of a day at a givenTmaxwill increase in a warming climate due to the increase of RH.
During intense heat episodes, the human population suffers from an increased morbidity and mortality. In order to minimize such negative health impacts, the general public and the public health authorities are informed and warned by means of an advanced procedure known as a “heat health warning system” (HHWS). It is aimed at triggering interventions and at taking preventive measures. The HHWS in Germany has been in operation since 2005. The present work is aimed at showing the updated structure of an advanced HHWS that has been developed further several times during its 15 years of operation. This is to impart knowledge to practitioners about the concept of the system. In Germany, dangerous heat episodes are predicted on the basis of the numerical weather forecast. The perceived temperature as an appropriate thermal index is calculated and used to assess the levels of heat stress. The thermo-physiologically based procedure contains variable thresholds taking into account the short time acclimatization of the people. The forecast system further comprises the nocturnal indoor conditions, the specific characteristics of the elderly population, and the elevation of a region. The heat warnings are automatically generated, but they are published with possible adjustments and a compulsory confirmation by the biometeorology forecaster. Preliminary studies indicate a reduction in the heat related outcomes. In addition, the extensive duration of the strongest heat wave in summer 2018, which lasted three weeks, highlights the necessity of the HHWS to protect human health and life.
Although seasonal influenza viruses circulate globally, prevention and treatment occur at the level of regions, cities, and communities. At these scales, the timing, duration and magnitude of epidemics vary substantially, but the underlying causes of this variation are poorly understood. Here, based on analyses of a 15-year city-level dataset of 18,250 laboratory-confirmed and antigenically-characterised influenza virus infections from Australia, we investigate the effects of previously hypothesised environmental and virological drivers of influenza epidemics. We find that anomalous fluctuations in temperature and humidity do not predict local epidemic onset timings. We also find that virus antigenic change has no consistent effect on epidemic size. In contrast, epidemic onset time and heterosubtypic competition have substantial effects on epidemic size and composition. Our findings suggest that the relationship between influenza population immunity and epidemiology is more complex than previously supposed and that the strong influence of short-term processes may hinder long-term epidemiological forecasts.
Although there is significant scientific evidence on the impact of heat waves, there are few studies that analyze the effects of sociodemographic factors on the impact of heat waves below the municipal level. The objective of this study was to analyze the role of income level, percent of the population over age 65, existence of air conditioning units and hectares (Ha) of green zones in districts in Madrid, in the impact of heat on daily mortality between January 1, 2010 and December 31, 2013. Seventeen districts were analyzed, and Generalized Linear (GLM) Poisson Regression Models were used to calculate relative risks (RR) and attributable risks (RA) for the impact of heat waves on mortality due to natural causes (CIEX:A00-R99). The pattern of risks obtained was analyzed using GLM univariates and multivariates of the binomial family (link logit), introducing the socioeconomic and demographic variables mentioned above. The results indicate that heat wave had an impact in only three of the districts analyzed. In the univariate models, all of the variables were statistically significant, but Ha of green zones lost significance in the multivariate model. Income level, existence of air conditioning units, and percent of the population over age 65 in the district remained as variables that modulate the impact of heat wave on daily mortality in the municipality of Madrid. Income level was the key variable that explained this behavior. The results obtained in this study show that there are factors at levels below the municipal level (district level) that should be considered as focus areas for health policy in order to decrease the impact of heat and promote the process of adaptation to heat in the context of climate change.
Urban waterways are underutilised assets, which can provide benefits ranging from climate-change mitigation and adaptation (e.g., reducing flood risks) to promoting health and well-being in urban settings. Indeed, urban waterways provide green and blue spaces, which have increasingly been associated with health benefits. The present observational study used a unique 17-year longitudinal natural experiment of canal regeneration from complete closure and dereliction in North Glasgow in Scotland, U.K. to explore the impact of green and blue canal assets on all-cause mortality as a widely used indicator of general health and health inequalities. Official data on deaths and socioeconomic deprivation for small areas (data zones) for the period 2001-2017 were analysed. Distances between data zone population-weighted centroids to the canal were calculated to create three 500 m distance buffers. Spatiotemporal associations between proximity to the canal and mortality were estimated using linear mixed models, unadjusted and adjusted for small-area measures of deprivation. The results showed an overall decrease in mortality over time (? = -0.032, 95% confidence interval (CI) [-0.046, -0.017]) with a closing of the gap in mortality between less and more affluent areas. The annual rate of decrease in mortality rates was largest in the 0-500 m buffer zone closest to the canal (-3.12%, 95% CI [-4.50, -1.73]), with smaller decreases found in buffer zones further removed from the canal (500-1000 m: -3.01%, 95% CI [-6.52, 0.62]), and 1000-1500 m: -1.23%, 95% CI [-5.01, 2.71]). A similar pattern of results was found following adjustment for deprivation. The findings support the notion that regeneration of disused blue and green assets and climate adaptions can have a positive impact on health and health inequalities. Future studies are now needed using larger samples of individual-level data, including environmental, socioeconomic, and health variables to ascertain which specific elements of regeneration are the most effective in promoting health and health equity.
BACKGROUND: For pediatric pneumonia, the meteorological and air pollution indicators had been frequently investigated for their association with viral circulation, however, not for their impact on disease severity. METHODS: We performed a 10-year prospective observational study in one hospital in Chongqing, China to recruit children with pneumonia. Eight commonly seen respiratory viruses were tested. Autoregressive distributed lag (ADL) and Random forest (RF) models were performed to fit monthly detection rates of each virus at population level and predict the possibility of severe pneumonia at individual level, respectively. RESULTS: Between 2009?2018, 6 611 pediatric pneumonia patients were included, and 4 846 (73.3%) tested positive for at least one respiratory virus. The median age of the patients was 9 (IQR: 4?20) months. ADL models demonstrated a decent fitting of detection rates of four viruses (R2 >0.7 for RSV, HRV, PIV, and HMPV). Based on the RF models, the AUC for host-related factors alone is 0.88 (95% CI: 0.87?0.89), 0.86 (95% CI: 0.85?0.88) for meteorological and air pollution indicators alone, and 0.62 (95% CI: 0.60?0.63) for viral infections alone. The final model indicated that nine weather and air pollution indicators were important determinants of severe pneumonia, with relative contribution of 62.53%, significantly higher than respiratory viral infections (7.36%). CONCLUSIONS: Meteorological and air pollution predictors contributed more to severe pneumonia in children than respiratory viruses. These meteorological data could help predict times when children would be at increased risk for severe pneumonia, and interventions such as reducing outdoor activities, may be warranted.
BACKGROUND: Little is known about the association between ambient temperature and cause-specific mental disorders, especially in subtropical areas. OBJECTIVE: To investigate the effect of ambient temperature on mental disorders in subtropical cities. METHOD: Daily morbidity data for mental disorders in three Chinese cities (Shenzhen, Zhaoqing, and Huizhou) were collected from medical record systems of local psychiatric specialist hospitals, covering patients of all ages. Case-crossover design combined with a distributed lag nonlinear model (DLNM) was used to assess the nonlinear and delayed effects of temperatures on five specific mental disorders (affective disorders, anxiety, depressive disorders, schizophrenia, and organic mental disorders), with analyses stratified by gender and age. The temperature of minimum effect was used as the reference value to calculate estimates. RESULTS: We observed inversed J-shaped exposure-response curves between temperature and mental morbidity and observed that low temperatures had a significant and prolonged effect on most types of mental disorders in the three cities. For example, the effect of the cold (2.5th percentile) on anxiety was consistently observed in the three cities with an odds ratio (OR) of 1.29 (95% CI: 1.06-1.57) in Zhaoqing, 1.26 (95% CI: 1.18-1.34) in Shenzhen, and 1.45 (95% CI: 1.17-1.81) in Huizhou. Low temperature was also associated with an increased risk of depressive disorders and schizophrenia. For the high temperature exposure (97.5th percentile), we only observed a significant, harmful effect on anxiety [OR = 1.30 (95% CI: 1.08, 1.58) in Shenzhen, OR = 1.16 (95% CI: 1.00, 1.34) in Zhaoqing], affective disorders [OR = 1.32 (95% CI: 1.08, 1.62) in Shenzhen], and schizophrenia [OR = 1.24 (95% CI: 1.03, 1.48) in Zhaoqing, OR = 1.03 (95% CI: 1.00, 1.06) in Huizhou]. CONCLUSIONS: Our study suggests that both low and high temperatures might be important drivers of morbidity from mental disorders, and low temperature may have a more general and wide-spread effect on this cause-specific morbidity than high temperature.
Exposure to high ambient temperatures is an important cause of avoidable, premature death that may become more prevalent under climate change. Though extensive epidemiological data are available in the United States, they are largely limited to select large cities, and hence, most projections estimate the potential impact of future warming on a subset of the U.S. population. Here we utilize evaluations of the relative risk of premature death associated with temperature in 10 U.S. cities spanning a wide range of climate conditions to develop a generalized risk function. We first evaluate the performance of this generalized function, which introduces substantial biases at the individual city level but performs well at the large scale. We then apply this function to estimate the impacts of projected climate change on heat-related nationwide U.S. deaths under a range of scenarios. During the current decade, there are 12,000 (95% confidence interval 7,400-16,500) premature deaths annually in the contiguous United States, much larger than most estimates based on totals for select individual cities. These values increase by 97,000 (60,000-134,000) under the high-warming Representative Concentration Pathway (RCP) 8.5 scenario and by 36,000 (22,000-50,000) under the moderate RCP4.5 scenario by 2100, whereas they remain statistically unchanged under the aggressive mitigation scenario RCP2.6. These results include estimates of adaptation that reduce impacts by ~40-45% as well as population increases that roughly offset adaptation. The results suggest that the degree of climate change mitigation will have important health impacts on Americans.
The increase in the frequency and intensity of heat waves is one of the most unquestionable effects of climate change. Therefore, the progressive increase in maximum temperatures will have a clear incidence on the increase in mortality, especially in countries that are vulnerable due to geographical location or their socioeconomic characteristics. Different research studies show that the mortality attributable to heat is decreasing globally, and research is centred on future scenarios. One way of detecting the existence of a lesser impact of heat is through the increase in the so-called temperature of minimum mortality (TMM). The objective of this study is to determine the temporal evolution of TMM in two Spanish provinces (Seville and Madrid) during the 1983-2018 period and to evaluate whether the rate of adaptation to heat is appropriate. We used the gross rate of daily mortality due to natural causes (CIEX: A00-R99) and the maximum daily temperature (°C) to determine the quinquennial TMM using dispersion diagrams and realizing fit using quadratic and cubic curvilinear estimation. The same analysis was carried out at the annual level, by fitting an equation to the line of TMM for each province, whose slope, if significant (p < 0.05) represents the annual rate of variation in TMM. The results observed in this quinquennial analysis showed that the TMM is higher in Seville than in Madrid and that it is higher among men than women in the two provinces. Furthermore, there was an increase in TMM in all of the quinquennium and a clear decrease in the final period. At the annual level, the linear fit was significant for Madrid for the whole population and corresponds to an increase in the TMM of 0.58 °C per decade. For Seville the linear fits were significant and the slopes of the fitted lines was 1.1 °C/decade. Both Madrid and Seville are adapting to the increase in temperatures observed over the past 36 years, and women are the group that is more susceptible to heat, compared to men. The implementation of improvements and evaluation of prevention plans to address the impact of heat waves should continue in order to ensure adequate adaptation in the future.
West Nile virus (WNV) has consistently been reported to be associated with human cases of illness in the region near Chicago, Illinois. However, the number of reported cases of human illness varies across years, with intermittent outbreaks. Several dynamic factors, including temperature, rainfall, and infection status of vector mosquito populations, are responsible for much of these observed variations. However, local landscape structure and human demographic characteristics also play a key role. The geographic and temporal scales used to analyze such complex data affect the observed associations. Here, we used spatial and statistical modeling approaches to investigate the factors that drive the outcome of WNV human illness on fine temporal and spatial scales. Our approach included multi-level modeling of long-term weekly data from 2005 to 2016, with weekly measures of mosquito infection, human illness and weather combined with more stable landscape and demographic factors on the geographical scale of 1000m hexagons. We found that hot weather conditions, warm winters, and higher MIR in earlier weeks increased the probability of an area of having a WNV human case. Higher population and the proportion of urban light intensity in an area also increased the probability of observing a WNV human case. A higher proportion of open water sources, percentage of grass land, deciduous forests, and housing built post 1990 decreased the probability of having a WNV case. Additionally, we found that cumulative positive mosquito pools up to 31 weeks can strongly predict the total annual human WNV cases in the Chicago region. This study helped us to improve our understanding of the fine-scale drivers of spatiotemporal variability of human WNV cases.
Embedding nature-based solutions (NBS) in cities is expected to bring quantifiable benefits, including resilience to flooding, drought, and heatwaves, and air quality improvement. Among NBS, green roofs have an important role in temperature regulation in buildings and in lowering the damaging effects of heatwaves on human health. In this paper a spatial microsimulation model is implemented to simulate temperature impacts of green roofs installations in cities and their capacity to attenuate the effects of heatwave episodes. Particularly vulnerable to heatwaves are elderly people with limited mobility, who have limited means to seek cooling and create cooler indoor environments. The model, implemented using the Netlogo platform (version 6.0.4), considers as agents the elderly citizens in a city area and simulates the heatwave-related health impacts, which are measured in mortality likelihood. In particular, the model simulates a generalised 1.5 degrees C to 3 degrees C indoor temperature reduction range induced by green roofs (based on inferences from green roof literature) in four different European cities: Szeged (Hungary), Alcal’a de Henares (Spain), Metropolitan City of Milan (Italy) and Cankaya municipality (Turkey). The simulation utilises a ceteris paribus modelling approach, meaning that the relationships of the observed phenomenon (mortality induced by heatwaves) with other possible influencing factors (e.g. level of sport and physical activities practiced by people) are not taken into account. In the case of Szeged, Alcal’a de Henares, and Cankaya municipality a substantial reduction in mortality is found to occur associated with green roofs roll out. In the case of the Metropolitan city of Milan, green roofs installations show a low mitigation effect in some scenarios. The underlying factor is the temperature threshold parameter of the model, above which heatwave mortality occurs. This parameter was inferred from the literature (Baccini M., et al., 2008) and it resulted to be substantially higher in the Metropolitan city of Milan (31.8 degrees C) than in the other cities. The simulation helps in obtaining results which are specific to a given city and particular scenarios therein, and provides additional insights, such as expected temperature mitigation effect induced by green roofs under climate change conditions, or the indoor temperature reduction targets that are needed for a particular city to have a maximum desired heatwave mitigation impact. However, the model parameters have to be carefully selected, after an accurate study of the domain literature.
More than 330 million people around the world suffer from asthma, a chronic respiratory disease that is produced by environmental conditions such as air pollution, mold, and seasonal change. In Philadelphia, Pennsylvania, high asthma prevalence rates and poor asthma control is attributed to urban air pollution and substandard housing, both of which will be made worse by climate change in the Mid-Atlantic region. Climate change will increase air pollution, worsen indoor environmental conditions, and bring more unpredictable weather, all of which will make asthma more difficult to manage. This article describes a public education project designed to teach vulnerable local communities about climate change and its impact on asthma management. The Climate Ready Philly project provided basic information on the mechanisms of global climate change, presented research on how climate change would impact the city of Philadelphia, and facilitated hands-on activities to help workshop participants learn what they could do to address climate change at home. Our workshops paired healthy homes and energy efficiency strategies, for example, to explore relationships between outdoor and indoor environments, as well as impacts on occupant health. By utilizing climate learning science, our workshops allowed participants to explore relationships between existing health and environmental conditions-such as asthma-and the anticipated impacts of climate change. Using surveys, interviews, and ethnographic data collection, we found that more resources are needed to repair housing infrastructure and help low-income community members access resources that can improve indoor air quality. We conclude by highlighting the need for climate adaptation programs that provide support for housing, in addition to other public infrastructures, which will be needed to reduce the burden of asthma in Philadelphia.
Hot weather episodes are globally associated with excess mortality rates. Elevated ozone concentrations occurring simultaneously also contribute to excess mortality rates during these episodes. However, the relative importance of both stressors for excess mortality rates is not yet known and assumed to vary from region to region. This study analyzes time series of daily observational data of air temperature and ozone concentrations for eight of the largest German cities during the years 2000 and 2017 with respect to the relative importance of both stressors for excess mortality rates in each city. By using an event-based risk approach, various thresholds for air temperature were explored for each city to detect hot weather episodes that are statistically associated with excess mortality rates. Multiple linear regressions were then calculated to investigate the relative contribution of variations in air temperature and ozone concentrations to the explained variance in mortality rates during these episodes, including the interaction of both predictors. In all cities hot weather episodes were detected that are related to excess mortality rates. Across the cities, a strong increase of this relation was observed around the 95th percentile of each city-specific air temperature distribution. Elevated ozone concentrations during hot weather episodes are also related to excess mortality rates in all cities. In general, the relative contribution of elevated ozone concentrations on mortality rates declines with increasing air temperature thresholds and occurs mainly as a statistically inseparable part of the air temperature impact. The specific strength of the impact of both stressors varies across the investigated cities. City-specific drivers such as background climate and vulnerability of the city population might lead to these differences and could be the subject of further research. These results underline strong regional differences in the importance of both stressors during hot weather episodes and could thus help in the development of city-specific heat- ozone-health warning systems to account for city-specific features.
INTRODUCTION: This study aims to determine the association between temperature and preeclampsia and whether it is affected by seasonality and rural/urban lifestyle. METHODS: This cohort study included women who delivered at our medical center from 2004 to 2013 (31,101 women, 64,566 deliveries). Temperature values were obtained from a spatiotemporally resolved estimation model performing predictions at a 1×1km spatial resolution. In “Warm” pregnancies >50% of gestation occurred during the spring-summer period. In cold pregnancies >50% of gestation occurred during the fall and winter. Generalized estimating equation multivariable models were used to estimate the association between temperature and incidence of preeclampsia. RESULTS: 1) The incidence of preeclampsia in at least one pregnancy was 7% (2173/64,566); 2) during “warm” pregnancies, an elevation of one IQR of the average temperature in the 1st or the 3rd trimesters was associated with an increased risk to develop preeclampsia [patients with Jewish ethnicity: 1st trimester: relative risk (RR) of 2.38(95%CI 1.50; 3.80), 3rd trimester 1.94(95%CI 1.34;2.81); Bedouins: 1st trimester: RR = 2.91(95%CI 1.98;4.28), 3rd trimester: RR = 2.37(95%CI 1.75;3.20)]; 3) In “cold” pregnancies, an elevation of one IQR of average temperature was associated with a lower risk to develop preeclampsia among patients with Bedouin-Arab ethnicity RR = 0.68 (95% CI 0.49-0.94) for 1st trimester and RR = 0.62 (95% CI 0.44-0.87) for 3rd trimester. CONCLUSIONS: 1) Elevated averaged temperature during the 1st or 3rd trimesters in “warm” pregnancies confer an increased risk for the development of preeclampsia, especially in nomadic patients; 2) Of interest, during cold pregnancies, elevated averaged temperature was associated with a lower risk to develop preeclampsia for nomadic patients. 3) These findings suggest temperature might be associated with perturbations in maternal heat homeostasis resulting in reallocation of energy resources and their availability to the fetus that may increase the risk for preeclampsia. This observation is especially relevant in the context of global warming and its effects on maternal/fetal reproductive health.
Exposure to particulate matter of smaller than 2.5 ?m in diameter (PM(2.5)) is linked to increased human mortality, and could be further complicated by concurrent ambient air temperatures. Published reports indicate that the association between ambient temperatures and mortality due to PM(2.5) exposure is dissimilar across different geographic areas. Thus, it is unclear how ambient temperatures at different geographic locations can together modulate the influence of PM(2.5) on mortality. In this paper, we examined how temperature modulated the association between mortality and PM(2.5) exposure in 15 Chinese cities during 2014-2016. For analysis, First, Poisson generalized additive models under different temperature stratifications (<10th, 10-90th, and >90th temperature percentiles) was used to estimate PM(2.5) associations to mortality, which were specific to different cities. Second, we used a meta-analysis to combine the effects at each temperature stratum and region (southern and northern China). Results revealed that high temperatures (daily mean temperature >90th percentile) robustly amplified observed associations of mortality and PM(2.5) exposure, and the modifications were heterogeneous geographically. In the northern regions, a 10 ?g/m(3) increment in PM(2.5) was associated with 0.18%, 0.28%, and 1.54% increase in non-accidental mortalities and 0.33%, 0.39%, and 1.32% increase in cardiovascular mortalities at low, moderate, and high temperature levels, respectively. In the southern regions, a 10 ?g/m(3) increment in PM(2.5) was associated with 0.52%, 0.62%, and 1.90% increase in non-accidental mortalities and 0.55%, 0.98%, and 2.25% increase in cardiovascular mortalities at low, moderate, and high temperature levels, respectively. It is concluded that temperature altered PM(2.5)-mortality associations in southern and northern China synergistically, but the effect was more pronounced in the south. Therefore, geography and temperature need to be considered when studying how PM(2.5) affects health.
BACKGROUND: Investigating future changes in temperature-related mortality as a function of global mean temperature (GMT) rise allows for the evaluation of policy-relevant climate change targets. So far, only few studies have taken this approach, and, in particular, no such assessments exist for Germany, the most populated country of Europe. METHODS: We assess temperature-related mortality in 12 major German cities based on daily time-series of all-cause mortality and daily mean temperatures in the period 1993-2015, using distributed-lag non-linear models in a two-stage design. Resulting risk functions are applied to estimate excess mortality in terms of GMT rise relative to pre-industrial levels, assuming no change in demographics or population vulnerability. RESULTS: In the observational period, cold contributes stronger to temperature-related mortality than heat, with overall attributable fractions of 5.49% (95%CI: 3.82-7.19) and 0.81% (95%CI: 0.72-0.89), respectively. Future projections indicate that this pattern could be reversed under progressing global warming, with heat-related mortality starting to exceed cold-related mortality at 3 °C or higher GMT rise. Across cities, projected net increases in total temperature-related mortality were 0.45% (95%CI: -0.02-1.06) at 3 °C, 1.53% (95%CI: 0.96-2.06) at 4 °C, and 2.88% (95%CI: 1.60-4.10) at 5 °C, compared to today’s warming level of 1 °C. By contrast, no significant difference was found between projected total temperature-related mortality at 2 °C versus 1 °C of GMT rise. CONCLUSIONS: Our results can inform current adaptation policies aimed at buffering the health risks from increased heat exposure under climate change. They also allow for the evaluation of global mitigation efforts in terms of local health benefits in some of Germany’s most populated cities.
Different authors have identified geographic variations in the rates of suicide. This study aims to discuss the limitations of the officially recorded suicide data and to evaluate the statistical relationship between a biometeorological index, Apparent Temperature (AT), and suicide in Madrid and Lisbon. We performed a time-series study. The association was analyzed using a quasi-Poisson regression model. To assess potential delayed and non-linear effects of AT on suicides, a lag non-linear model was fitted in a generalized additive model. There was an average rate of 3.30 suicides/100,000 inhabitants in Madrid and of 7.92 suicides/100,000 inhabitants in Lisbon, and a downward trend was found throughout the period. In Madrid, there is no statistically significant association between AT and suicide. However, in Lisbon, under higher AT, there was a higher risk of suicide. The highest accumulated statistically significant Relative Risk (RR) of suicide was detected at 7 days after the exposure, when at 38 °C, the risk of suicide is 2.7 times that existing at the median AT, 20.62°. The average mortality rate recorded in Lisbon was 41.6% higher than that registered in Madrid. However, the limitations of suicide record databases in Spain and Portugal have to be taken into account when analyzing incidence and especially when comparing data from different countries. It is necessary to improve the filing systems of violent deaths in order to perform reliable epidemiological studies.
A thunderstorm is a risk factor for severe respiratory allergy or asthma attacks in patients suffering from pollen/spore allergy. This study aimed to investigate the changes in the spectrum and quantity of pollen and fungal spores in the air of Bratislava during summer storms as well as the impact of selected environmental parameters on these changes. Pollen/spore samples were collected using a Burkard volumetric aerospore trap during summer 2016. To identify those types of pollen/spores that may harm human health during the storm episodes, we analysed how the concentration of individual bioparticles in the air changed during pre-storm/storm/post-storm periods. The effect of environmental variables on the concentration of selected pollen/spore types was evaluated through Spearman’s correlation analysis. The results of our study suggest that thunderstorm-related respiratory allergy symptoms in the study area may be caused by (1) spores of Myxomycetes, the airborne concentration of which increases due to an increase in wind speed during the pre-storm period; (2) ruptured pollen and Diatripaceae spores, the concentration of which increases due to increase in precipitation and relative air humidity, respectively, during the storm period; and (3) spores of Fusarium and Leptosphaeria, the concentration of which increases due to increase in precipitation and air temperature, respectively, during the post-storm period.
This study consists of nine case studies addressing thermal comfort in the public areas of city centres, with particular emphasis on the measurable effects of blue and green infrastructure on thermal exposure. Daytime on-site measurements were taken in summer in the paved areas of squares, in the proximity of water fountains, and in the shade of trees in order to evaluate levels of heat stress based on the universal thermal climate index (UTCI). The differences in UTCI values between the research points confirm substantial cooling associated with high vegetation (trees induced differences up to 10.5 degrees C in UTCI), while the measurable cooling effect of low vegetation was negligible (not more than 2.3 degrees C UTCI). It was also quite low around water fountains, spray fountains, and misting systems. It follows that municipal authorities should consider the differences in cooling effect potential of individual types of blue and green infrastructure when incorporating climate adaptation measures into urban planning.
The sub-divided unit (SDU) is the major type of substandard housing in Hong Kong. This study monitored the microclimatic conditions in eight SDUs for 24 h in summer. The mean CO2 concentration (1012 mg/m(3)) under natural ventilation was much higher than the outdoor level (similar to 410 mg/m(3)), suggesting that ventilation was ineffective in most SDUs. The mean predicted mean vote (PMV) was 1.7 (warm), corresponding to 75% predicted percentage dissatisfied (PPD). None of the SDUs was thermally acceptable (PPD < 20%) at any time in the monitoring period. If the adaptive thermal comfort standard was considered, the acceptable temperature range would be between 23.4 degrees C and 30.4 degrees C in operative temperature and the thermally acceptable time would be 47%. Larger openable window size, larger external wall area and poor ventilation significantly contributed to higher maximum indoor air temperature.
As heat waves become more extreme, there is a growing concern for the health of elderly city dwellers who have poor living conditions and limited access to resources. Much research has documented socioeconomic links to heat vulnerability, but limited studies have investigated the detailed living conditions of vulnerable populations, despite increasing requests from local communities. In this paper, we examine the summertime thermal performance of 24 senior apartments within 3 public housing sites (2 conventional multifamily and 1 LEED-rated building), and the seniors’ adaptive responses in Elizabeth, NJ, USA. Time-series data were collected from sensors, interviews and observations on the thermal environment and behavior, from May-October 2017. Our multi-level, occupant-centric approach utilizes the indoor heat index as a proxy for heat stress, against site and building characteristics, and environmental and personal variables. Panel regressions show thermal variations among sites/apartments and illustrate the significant effect of actions, such as window opening and air conditioner use. Results also show how the seniors’ adaptive responses vary by site; residents with central air-conditioning use it, while residents from the two older sites engage in a wider range of adaptive actions, and in some cases achieve similar indoor heat indexes as apartments from the green building. Indoor heat stress experienced by low-income seniors can be greatly reduced through cost-effective strategies that target individual behaviors and outdoor amenities. This implies the need for integrated solutions to the heat waves problem across scales; including changes to residents’ habits, building envelopes, building operations, and outdoor spaces.
The effects of heat waves (HW) are more pronounced in urban areas than in rural areas due to the additive effect of the urban heat island (UHI) phenomenon. However, the synergies between UHI and HW are still an open scientific question and have only been quantified for a few metropolitan cities. In the current study, we explore the synergies between UHI and HW in Seoul city. We consider summertime data from two non-consecutive years (i.e., 2012 and 2016) and ten automatic weather stations. Our results show that UHI is more intense during HW periods than non-heat wave (NHW) periods (i.e., normal summer background conditions), with a maximum UHI difference of 3.30°C and 4.50°C, between HW and NHW periods, in 2012 and 2016 respectively. Our results also show substantial variations in the synergies between UHI and HW due to land use characteristics and synoptic weather conditions; the synergies were relatively more intense in densely built areas and under low wind speed conditions. Our results contribute to our understanding of thermal risks posed by HW in urban areas and, subsequently, the health risks on urban populations. Moreover, they are of significant importance to emergency relief providers as a resource allocation guideline, for instance, regarding which areas and time of the day to prioritize during HW periods in Seoul.
Numerous studies have demonstrated the relationship between summer temperatures and increased heat-related deaths. Epidemiological analyses of the health effects of climate exposures usually rely on observations from the nearest weather station to assess exposure-response associations for geographically diverse populations. Urban climate models provide high-resolution spatial data that may potentially improve exposure estimates, but to date, they have not been extensively applied in epidemiological research. We investigated temperature-mortality relationships in the city of Barcelona, and whether estimates vary among districts. We considered georeferenced individual (natural) mortality data during the summer months (June-September) for the period 1992-2015. We extracted daily summer mean temperatures from a 100-m resolution simulation of the urban climate model (UrbClim). Summer hot days (above percentile 70) and reference (below percentile 30) temperatures were compared by using a conditional logistic regression model in a case crossover study design applied to all districts of Barcelona. Relative Risks (RR), and 95% Confidence Intervals (CI), of all-cause (natural) mortality and summer temperature were calculated for several population subgroups (age, sex and education level by districts). Hot days were associated with an increased risk of death (RR = 1.13; 95% CI = 1.10-1.16) and were significant in all population subgroups compared to the non-hot days. The risk ratio was higher among women (RR = 1.16; 95% CI= 1.12-1.21) and the elderly (RR = 1.18; 95% CI = 1.13-1.22). Individuals with primary education had similar risk (RR = 1.13; 95% CI = 1.08-1.18) than those without education (RR = 1.10; 95% CI= 1.05-1.15). Moreover, 6 out of 10 districts showed statistically significant associations, varying the risk ratio between 1.12 (95% CI = 1.03-1.21) in Sants-Montjuïc and 1.25 (95% CI = 1.14-1.38) in Sant Andreu. Findings identified vulnerable districts and suggested new insights to public health policy makers on how to develop district-specific strategies to reduce risks.
Urban heat islands (UHIs) can present significant risks to human health. Santiago, Chile has around 7 million residents, concentrated in an average density of 480 people/km(2). During the last few summer seasons, the highest extreme maximum temperatures in over 100 years have been recorded. Given the projections in temperature increase for this metropolitan region over the next 50 years, the Santiago UHI could have an important impact on the health and stress of the general population. We studied the presence and spatial variability of UHIs in Santiago during the summer seasons from 2005 to 2017 using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery and data from nine meteorological stations. Simple regression models, geographic weighted regression (GWR) models and geostatistical interpolations were used to find nocturnal thermal differences in UHIs of up to 9 degrees C, as well as increases in the magnitude and extension of the daytime heat island from summer 2014 to 2017. Understanding the behavior of the UHI of Santiago, Chile, is important for urban planners and local decision makers. Additionally, understanding the spatial pattern of the UHI could improve knowledge about how urban areas experience and could mitigate climate change.
Fecal coliform bacteria are a key indicator of human health risks; however, the spatiotemporal variability and key influencing factors of river fecal coliform have yet to be explored in a rural-suburban-urban watershed with multiple land uses. In this study, the fecal coliform concentrations in 21 river sections were monitored for 20 months, and 441 samples were analyzed. Multivariable regressions were used to evaluate the spatiotemporal dynamics of fecal coliform. The results showed that spatial differences were mainly dominated by urbanization level, and environmental factors could explain the temporal dynamics of fecal coliform in different urban patterns except in areas with high urbanization levels. Reducing suspended solids is a direct way to manage fecal coliform in the Beiyun River when the natural factors are difficulty to change, such as temperature and solar radiation. The export of fecal coliform from urban areas showed a quick and sensitive response to rainfall events and increased dozens of times in the short term. Landscape patterns, such as the fragmentation of impervious surfaces and the overall landscape, were identified as key factors influencing urban non-point source bacteria. The results obtained from this study will provide insight into the management of river fecal pollution.
We have evaluated the spread of SARS-CoV-2 through Latin America and the Caribbean (LAC) region by means of a correlation between climate and air pollution indicators, namely, average temperature, minimum temperature, maximum temperature, rainfall, average relative humidity, wind speed, and air pollution indicators PM(10), PM(2.5), and NO(2) with the COVID-19 daily new cases and deaths. The study focuses in the following LAC cities: Mexico City (Mexico), Santo Domingo (Dominican Republic), San Juan (Puerto Rico), Bogotá (Colombia), Guayaquil (Ecuador), Manaus (Brazil), Lima (Perú), Santiago (Chile), São Paulo (Brazil) and Buenos Aires (Argentina). The results show that average temperature, minimum temperature, and air quality were significantly associated with the spread of COVID-19 in LAC. Additionally, humidity, wind speed and rainfall showed a significant relationship with daily cases, total cases and mortality for various cities. Income inequality and poverty levels were also considered as a variable for qualitative analysis. Our findings suggest that and income inequality and poverty levels in the cities analyzed were related to the spread of COVID-19 positive and negative, respectively. These results might help decision-makers to design future strategies to tackle the spread of COVID-19 in LAC and around the world.
Several studies emphasize that temperature-related mortality can be expected to have differential effects on different subpopulations, particularly in the context of climate change. This study aims to evaluate and quantify the future temperature-attributable mortality due to circulatory system diseases by age groups (under 65 and 65+ years), in Lisbon metropolitan area (LMA) and Porto metropolitan area (PMA), over the 2051-2065 and 2085-2099 time horizons, considering the greenhouse gas emissions scenario RCP8.5, in relation to a historical period (1991-2005). We found a decrease in extreme cold-related deaths of 0.55% and 0.45% in LMA, for 2051-2065 and 2085-2099, respectively. In PMA, there was a decrease in cold-related deaths of 0.31% and 0.49% for 2051-2065 and 2085-2099, respectively, compared to 1991-2005. In LMA, the burden of extreme heat-related mortality in age group 65+ years is slightly higher than in age group <65 years, at 2.22% vs. 1.38%, for 2085-2099. In PMA, only people aged 65+ years showed significant temperature-related burden of deaths that can be attributable to hot temperatures. The heat-related excess deaths increased from 0.23% for 2051-2065 to 1.37% for 2085-2099, compared to the historical period.
Occupational heat stress has an important negative impact on the well-being, health and productivity of workers and should; therefore, be recognized as a public health issue in Europe. There is no comprehensive heat health warning system in Slovenia combining public health measures with meteorological forecasts. The aim of this research was to provide insight into the development of such a system in Slovenia, turning the communication from the current meteoalarm into a broader system that has more information for different social groups. To achieve this goal, the following steps were used: Analysis of summer temperatures and issued meteoalarms, a survey of the general knowledge about heat among the public, organization and management of two stakeholder symposia, and a final survey on workers’ opinions on heat stress and measures, supplemented by interviews with employers. Summer average daily temperature distributions in Slovenia changed during the investigated period (1961-2019) and the mean values increased over time by 2-3 °C. Additionally, the number of days with fulfilled yellow (potentially dangerous) and especially orange (dangerous) meteoalarm conditions increased significantly after 1990. The survey of the general public about heat stress and warnings showed that efforts to raise awareness of heat issues need to be intensified and that public health measures should effectively target vulnerable groups. Stakeholder symposia and further surveys have shown that awareness and understanding of the negative effects of heat stress on health and productivity are still quite low, so effective ways of disseminating information to different sectors while striking the best balance between efficiency, feasibility and economic cost have to be found.
Although several studies have reported that social isolation is one of the important health risk factors in the elderly population living in urban areas, its effects on vulnerability to heatwaves have been studied relatively less than climatic and other socio-economic factors. Thus, we investigated the association between social isolation levels and heatwave-related mortality risk in the elderly population in 119 urban administrative districts in Korea, using a time-series multi-city dataset (2008-2017). We used a two-stage analysis. In the first stage, we estimated the heatwave-related mortality risk in the elderly population (age ? 65) for each district using a time-series regression with a distributed lag model. Subsequently, in the second stage, we applied meta-regressions to pool the estimates across all the districts and estimate the association between social isolation variables and heatwave-related mortality risk. Our findings showed that higher social gathering and mutual aid levels were associated with lower heatwave-related mortality risk. Further, the lower percentage of single elderly households living in detached houses was also related to higher heatwave-related mortality risk. The associations were generally more evident in males compared to females. Our findings suggest that vulnerability to heatwave-related mortality among the urban, city-dwelling, elderly population may be amplified by higher isolation indicators.
BACKGROUND: Heat exposure, which will increase with global warming, has been linked to increased risk of a range of types of cause-specific hospitalizations. However, little is known about socioeconomic disparities in vulnerability to heat. We aimed to evaluate whether there were socioeconomic disparities in vulnerability to heat-related all-cause and cause-specific hospitalization among Brazilian cities. METHODS AND FINDINGS: We collected daily hospitalization and weather data in the hot season (city-specific 4 adjacent hottest months each year) during 2000-2015 from 1,814 Brazilian cities covering 78.4% of the Brazilian population. A time-stratified case-crossover design modeled by quasi-Poisson regression and a distributed lag model was used to estimate city-specific heat-hospitalization association. Then meta-analysis was used to synthesize city-specific estimates according to different socioeconomic quartiles or levels. We included 49 million hospitalizations (58.5% female; median [interquartile range] age: 33.3 [19.8-55.7] years). For cities of lower middle income (LMI), upper middle income (UMI), and high income (HI) according to the World Bank’s classification, every 5°C increase in daily mean temperature during the hot season was associated with a 5.1% (95% CI 4.4%-5.7%, P < 0.001), 3.7% (3.3%-4.0%, P < 0.001), and 2.6% (1.7%-3.4%, P < 0.001) increase in all-cause hospitalization, respectively. The inter-city socioeconomic disparities in the association were strongest for children and adolescents (0-19 years) (increased all-cause hospitalization risk with every 5°C increase [95% CI]: 9.9% [8.7%-11.1%], P < 0.001, in LMI cities versus 5.2% [4.1%-6.3%], P < 0.001, in HI cities). The disparities were particularly evident for hospitalization due to certain diseases, including ischemic heart disease (increase in cause-specific hospitalization risk with every 5°C increase [95% CI]: 5.6% [-0.2% to 11.8%], P = 0.060, in LMI cities versus 0.5% [-2.1% to 3.1%], P = 0.717, in HI cities), asthma (3.7% [0.3%-7.1%], P = 0.031, versus -6.4% [-12.1% to -0.3%], P = 0.041), pneumonia (8.0% [5.6%-10.4%], P < 0.001, versus 3.8% [1.1%-6.5%], P = 0.005), renal diseases (9.6% [6.2%-13.1%], P < 0.001, versus 4.9% [1.8%-8.0%], P = 0.002), mental health conditions (17.2% [8.4%-26.8%], P < 0.001, versus 5.5% [-1.4% to 13.0%], P = 0.121), and neoplasms (3.1% [0.7%-5.5%], P = 0.011, versus -0.1% [-2.1% to 2.0%], P = 0.939). The disparities were similar when stratifying the cities by other socioeconomic indicators (urbanization rate, literacy rate, and household income). The main limitations were lack of data on personal exposure to temperature, and that our city-level analysis did not assess intra-city or individual-level socioeconomic disparities and could not exclude confounding effects of some unmeasured variables. CONCLUSIONS: Less developed cities displayed stronger associations between heat exposure and all-cause hospitalizations and certain types of cause-specific hospitalizations in Brazil. This may exacerbate the existing geographical health and socioeconomic inequalities under a changing climate.
INTRODUCTION: Leptospirosis is an endemic disease in Brazil that can become an epidemic during the rainy season resulting from floods in areas susceptible to natural disasters. These areas are widespread in Santa Catarina, particularly in the coastal region. Therefore, the objective of this study was to identify environmental, climatic, and demographic factors associated with the incidence of leptospirosis in the municipalities of Santa Catarina from 2001 to 2015, taking into account possible spatial dependence. METHODS: This was an ecological study aggregated by municipality. To evaluate the association between the incidence of leptospirosis and the factors under study (temperature, altitude, occurrence of natural disasters, etc.) while taking into account spatial dependence, linear regression models and models with global spatial error were used. RESULTS: Lower altitudes, higher temperatures, and areas of natural disaster risk in the municipality contributed the most to explaining the variability in the incidence rate. After taking spatial dependence into account, only the minimum altitude variable remained significant. The regions of lower altitude, where the highest rates of leptospirosis were recorded, corresponded to the eastern portion of the state near the coastal region, where floods, urban floods, and overflows are common occurrences. No associations were found concerning demographic factors. CONCLUSIONS: The incidence of leptospirosis in Santa Catarina was associated with environmental factors, particularly low altitude, even when considering the spatial dependence structure present in the data. The spatial error model allowed for adequate modeling of spatial autocorrelation.
Based on the disaster census data of four types of meteorological disasters (floods induced by rainstorms, droughts, damages due to low temperatures and high temperatures and heat waves) in 637 counties (districts) of East China, the spatial distribution and inter-annual variation in the number of records and the amount of impacts or losses caused by the four types of disasters were analyzed. The results indicate that rainstorm-induced flood disasters had the largest number of records and the largest affected population, death population, affected crop, total crop failure and direct economic loss in East China. The yearly percentage of affected population and direct economic loss caused by the four types of meteorological disasters increased significantly at rates of 1.4 and 2.2% per decade, respectively, but the deaths decreased significantly at a rate of 2.2% per decade during 1984-2010. There was no statistical significance in the percentage change of affected crop area and total crop failure area in East China. Spatially, the total number of people affected by the four types of meteorological disasters was higher in Anhui and Jiangxi, and the deaths were more in southern Anhui, Jiangxi, Zhejiang, and Fujian. Both the affected area and the total failure area of crops were higher in northern Anhui, eastern Jiangsu and eastern Shandong, and the direct economic losses were higher in the southern part of East China and Anhui province.
OBJECTIVE: To assess short term mortality risks and excess mortality associated with exposure to ozone in several cities worldwide. DESIGN: Two stage time series analysis. SETTING: 406 cities in 20 countries, with overlapping periods between 1985 and 2015, collected from the database of Multi-City Multi-Country Collaborative Research Network. POPULATION: Deaths for all causes or for external causes only registered in each city within the study period. MAIN OUTCOME MEASURES: Daily total mortality (all or non-external causes only). RESULTS: A total of 45?165?171 deaths were analysed in the 406 cities. On average, a 10 µg/m(3) increase in ozone during the current and previous day was associated with an overall relative risk of mortality of 1.0018 (95% confidence interval 1.0012 to 1.0024). Some heterogeneity was found across countries, with estimates ranging from greater than 1.0020 in the United Kingdom, South Africa, Estonia, and Canada to less than 1.0008 in Mexico and Spain. Short term excess mortality in association with exposure to ozone higher than maximum background levels (70 µg/m(3)) was 0.26% (95% confidence interval 0.24% to 0.28%), corresponding to 8203 annual excess deaths (95% confidence interval 3525 to 12?840) across the 406 cities studied. The excess remained at 0.20% (0.18% to 0.22%) when restricting to days above the WHO guideline (100 µg/m(3)), corresponding to 6262 annual excess deaths (1413 to 11?065). Above more lenient thresholds for air quality standards in Europe, America, and China, excess mortality was 0.14%, 0.09%, and 0.05%, respectively. CONCLUSIONS: Results suggest that ozone related mortality could be potentially reduced under stricter air quality standards. These findings have relevance for the implementation of efficient clean air interventions and mitigation strategies designed within national and international climate policies.
Extreme air temperature directly affected human health. However, the short-term effect of extreme air temperature on the incidence of cardiovascular diseases has rarely been reported in China. In this study, we focused on Beijing, China, and assessed the effects of cold/warm days and nights on the number of hospital emergency room (ER) visits for cardiovascular diseases from 2009 to 2012. We used a generalized additive model (GAM) to estimate the association between extreme air temperature and the number of hospital ER visits for cardiovascular diseases. We divided the entire study group into two gender subgroups and three age subgroups. The results showed that the short-term effect of extreme air temperature on hospital ER visits for cardiovascular diseases was more profound in females and the elderly (aged ??75 years). Among all the study subgroups, the highest relative risk (RR) of cardiovascular diseases associated with extremely cold days, warm days, cold nights, and warm nights was 3.0% (95% CI, 1.6%-4.4%), 0.8% (95% CI, -?0.9%-2.6%), 2.8% (95% CI, 1.6%-4.2%), and 1.8% (95% CI, 0.6%-4.3%), respectively. Overall, the effect of extremely low air temperature (during both days and nights) on the incidence of cardiovascular diseases was stronger and more acute than that of extremely high air temperature.
BACKGROUND: Evidence on the acute effect of short-term exposure to nitrogen dioxide (NO(2)) on years of life lost (YLL) is rare, especially in multicity setting. METHODS: We conducted a time series study among 48 major Chinese cities covering more than 403 million people from 2013 to 2017. The relative percentage changes of NO(2)-YLL were estimated by generalized additive models in each city, then were pooled to generate average effects using random-effect models. In addition, stratified analyses by individual demographic factors and temperature as well as meta-regression analyses incorporating city-specific air pollutant concentrations, meteorological conditions, and socioeconomic indicators were performed to explore potential effect modification. RESULTS: A 10 ?g/m(3) increase in two-day moving average (lag01) NO(2) concentration was associated with 0.64% (95% CI: 0.47%, 0.81%), 0.47% (95% CI: 0.27%, 0.68%), and 0.68% (95% CI: 0.34%, 1.02%) relative increments in YLL due to nonaccidental causes, cardiovascular diseases (CVD), and respiratory diseases (RD), respectively. These associations were generally robust to the adjustment of co-pollutants, except for NO(2)-CVD that might be confounded by fine particulate matter. The increased YLL induced by NO(2) were more pronounced in elderly people, hotter days, and cities characterized by less severe air pollution or higher temperature. CONCLUSIONS: Our results demonstrated robust evidence on the associations between NO(2) exposure and YLL due to nonaccidental causes, CVD, and RD, which provided novel evidence to better understand the disease burden related to NO(2) pollution and to facilitate allocation of health resources targeting high-risk subpopulation.
Short-term effects of air pollution on the health of residents in the Metropolitan Area of Monterrey, Mexico were assessed from 2012-2015 using a time-series approach. Guadalupe had the highest mean concentrations for SO(2), CO and O(3); whereas Santa Catarina showed the highest NO(2) concentrations. Escobedo and Garcia registered the highest levels for PM(10). Only PM(10) and O(3) exceeded the maximum permissible values established in the Mexican official standards. Most of pollutants and municipalities showed a great number of associations between an increase of 10% in their current concentrations and mortality, especially for people >60 years. Different scenarios resulting from climatic change were built (increases of 5-25% in daily mean temperature), but only the increase of 25% (5 °C) showed a significant association with air pollutant concentrations and mortality. All pollutants and municipalities showed significant increases in relative risk indexes (RRI) resulting from an increase of 5 °C when people >60 years was considered. Results were comparable to those reported by other authors around the world. The RRI were low but significant, and thus are of public concern. This study demonstrated that the elderly is strongly threatened not only by atmospheric pollution but also by climatic change scenarios in warm and semiarid places.
Extreme temperature-related cardiovascular diseases (CVDs) have become a growing public health concern. However, the impact of temperature on the cause of specific CVDs has not been well studied in the study area. The objective of this study was to assess the impact of temperature on cause-specific cardiovascular hospital admissions in Beijing, China. We obtained data from 172 large general hospitals from the Beijing Public Health Information Center Cardiovascular Case Database and China. Meteorological Administration covering 16 districts in Beijing from 2013 to 2017. We used a time-stratified case crossover design with a distributed lag nonlinear model (DLNM) to derive the impact of temperature on CVD in hospitals back to 27 days on CVD admissions. The temperature data were stratified as cold (extreme and moderate ) and hot (moderate and extreme ). Within five years (January 2013-December 2017), a total of 460,938 (male 54.9% and female 45.1%) CVD admission cases were reported. The exposure-response relationship for hospitalization was described by a “J” shape for the total and cause-specific. An increase in the six-day moving average temperature from moderate hot (30.2 °C) to extreme hot (36.9 °C) resulted in a significant increase in CVD admissions of 16.1%(95% CI = 12.8%-28.9%). However, the effect of cold temperature exposure on CVD admissions over a lag time of 0-27 days was found to be non significant, with a relative risk of 0.45 (95% CI = 0.378-0.55) for extreme cold (-8.5 °C)and 0.53 (95% CI = 0.47-0.60) for moderate cold (-5.6 °C). The results of this study indicate that exposure to extremely high temperatures is highly associated with an increase in cause-specific CVD admissions. These finding may guide to create and raise awareness of the general population, government and private sectors regarding on the effects of current weather conditions on CVD.
BACKGROUND: Numerous studies have demonstrated the potential association between rainfall and hand, foot and mouth disease (HFMD), but the results are inconsistent. This study aimed to quantify the relationship between rainfall and HFMD based on a multicity study and explore the potential sources of spatial heterogeneity. METHODS: We retrieved the daily counts of childhood HFMD and the meteorological variables of the 143 cities in mainland China between 2009 and 2014. A common time series regression model was applied to quantify the association between rainfall and HFMD for each of the 143 cities. Then, we adopted the meta-regression model to pool the city-specific estimates and explore the sources of heterogeneity by incorporating city-specific characteristics. RESULTS: The overall pooled estimation suggested a nonlinear exposure-response relationship between rainfall and HFMD. Once rainfall exceeded 15?mm, the HFMD risk stopped increasing linearly and began to plateau with the excessive risk ratio (ERR) peaking at 21?mm of rainfall (ERR?=?3.46, 95% CI: 2.05, 4.88). We also found significant heterogeneity in the rainfall-HFMD relationships (I(2) =?52.75%, P
Many of the six million residents of unincorporated communities in the United States depend on well-water to meet their needs. One group of unincorporated communities is the colonias, located primarily in several southwestern U.S. states. Texas is home to the largest number of these self-built communities, of mostly low-income families, lacking basic infrastructure. While some states have regulations that mandate minimum infrastructure for these communities, water and sewage systems are still lacking for many of their residents. Unprotected wells and self-built septic/cesspool systems serve as the primary infrastructure for many such colonias. This research was designed to probe how wells and septic/cesspool systems are influenced by heavy rainfall events. Such events are hypothesized to impact water quality with regard to human health. Inorganic and microbiological water quality of the wells in nine colonias located in Nueces County, Texas, were evaluated during dry and wet periods. Nueces County was selected as an example based on its flooding history and the fact that many colonias there depend entirely on well-water and septic/cesspool systems. The results demonstrate that well-water quality in these communities varies seasonally with respect to arsenic (up to 35 ?g/L) and bacterial contamination (Escherichia coli), dependent on the amount of rainfall, which leaves this population vulnerable to health risks during both wet and dry periods. Microbial community analyses were also conducted on selected samples. To explore similar seasonal contamination of well-water, an analysis of unincorporated communities, flooding frequency, and arsenic contamination in wells was conducted by county throughout the United States. This nationwide analysis indicates that unincorporated communities elsewhere in the United States are likely experiencing comparable challenges for potable water access because of a confluence of socioeconomic, infrastructural, and policy realities.
Hand, foot, and mouth disease (HFMD) is a common infectious disease in the Asia-Pacific region that primarily affects children younger than 5 years. Previous studies have confirmed that the seasonal transmission of this disease is strongly related to meteorological factors, but the results are not consistent. In addition, the associations between weather conditions and HFMD in northwestern China have not been investigated. Therefore, we aimed to examine this issue in Xi’an, the largest city of northwestern China that has been suffering from serious HFMD epidemics. In the current study, data for HFMD and six meteorological factors were collected from 2009 to 2018. Using cross-correlation analysis, the Granger causality test, and the distributed lag nonlinear model, we estimated the quantitative relationships and exposure-lag-response effects between weekly meteorological factors and HFMD incidence among children. We found that the seasonal distribution of HFMD in Xi’an has two peaks each year and is significantly impacted by the weekly temperature, precipitation, and evaporation over an 8-week period. Higher values of temperature and evaporation had positive associations with disease transmission, whereas the association between precipitation and HFMD showed an inverted-U shape. The maximum relative risks (RRs) of HFMD for the weekly mean temperature (approximately 31.1°C), weekly cumulative evaporation (57.9 mm), and weekly cumulative precipitation (30.0 mm) were 1.56 (95% CI: 1.35-1.81), 1.40 (95% CI: 1.05-1.88), and 1.16 (95% CI: 1.11-1.70), respectively. The identified risk determinants and lag effects could provide important information for early interventions to reduce the local disease burden.
This study combines wearable sensors, weather data, and self-reported mood surveys to assess mental stress on older adults from heat experience. It is designed as a pilot and feasibility study in preparation for a large-scale experiment of older adults; mental wellbeing during extreme heat events. Results show that on-body temperatures from two i-Button sensors coupled with heart rate monitored from a smart watch are important indicators to evaluate individualized heat stress given a relatively uniform outdoor temperature. Furthermore, assessing their mood in their own environment demonstrates potential for understanding mental wellbeing that can change with varying time and location.
OBJECTIVES: There has been increasing interest in identifying the adverse effects of ambient environmental factors on asthma exacerbations (AE), but season-stratified effects of meteorological factors on childhood asthma remain unclear. We explored the season-stratified effects of meteorological factors on childhood AE in Shanghai, China. METHODS: Poisson generalized linear regression model combined with a distributed lag nonlinear model was used to examine the lagged and nonlinear effects of meteorological factors on childhood AE after adjustment for putative confounders. We also performed a season-stratified analysis to determine whether the season modified the relationship between meteorological factors and childhood AE. RESULTS: There were 23,103 emergency department visits (EDVs) for childhood AE, including 15,466 boys and 7637 girls during 2008-2017. Most meteorological factors (e.g., temperature, diurnal temperature range (DTR), relative humidity (RH) and wind speed (WS)) were significantly associated with EDVs for childhood AE, even after adjustment for the confounding effects of air pollutants. In the whole year, extreme cold, moderate heat, higher DTR, lower RH and WS increased the relative risk (RR) for childhood AE. In the cold season, lower RH and wind speed increased the risks of childhood AE (RR(lag0-28) for the 5th percentile (p5) of RH: 9.744, 95% CI: 3.567, 26.616; RR(lag0-28) for the p5 of wind speed: 10.671, 95% CI: 1.096, 103.879). In the warm season, higher temperature and DTR, lower RH and WS increased the RR for childhood AE (RR(lag0-5) for the p95 of temperature: 1.871, 95% CI: 1.246, 2.810; RR(lag0-2) for the p95 of DTR: 1.146, 95% CI: 1.010, 1.300; RR(lag0-5) for the p5 of RH: 1.931, 95% CI: 1.191, 3.128; RR(lag0-2) for the p5 of WS: 1.311, 95% CI: 1.005, 1.709). CONCLUSIONS: Extreme meteorological factors appeared to be triggers of EDVs for childhood AE in Shanghai and the effects modified by season. These findings provide evidence for developing season-specific and tailored strategies to prevent and control childhood AE.
BACKGROUND: Between 1999 and 2008 Russia experienced a flare-up of transmission of vivax malaria following its massive importation with more than 500 autochthonous cases in European Russia, the Moscow region being the most affected. The outbreak waned soon after a decrease in importation in mid-2000s and strengthening the control measures. Compared with other post-eradication epidemics in Europe this one was unprecedented by its extension and duration. METHODS: The aim of this study is to identify geographical determinants of transmission. The degree of favourability of climate for vivax malaria was assessed by measuring the sum of effective temperatures and duration of season of effective infectivity using data from 22 weather stations. For geospatial analysis, the locations of each of 405 autochthonous cases detected in Moscow region have been ascertained. A MaxEnt method was used for modelling the territorial differentiation of Moscow region according to the suitability of infection re-emergence based on the statistically valid relationships between the distribution of autochthonous cases and environmental and climatic factors. RESULTS: In 1999-2004, in the beginning of the outbreak, meteorological conditions were extremely favourable for malaria in 1999, 2001 and 2002, especially within the borders of the city of Moscow and its immediate surroundings. The greatest number of cases occurred at the northwestern periphery of the city and in the adjoining rural areas. A significant role was played by rural construction activities attracting migrant labour, vegetation density and landscape division. A cut-off altitude of 200 m was observed, though the factor of altitude did not play a significant role at lower altitudes. Most likely, the urban heat island additionally amplified malaria re-introduction. CONCLUSION: The malariogenic potential in relation to vivax malaria was high in Moscow region, albeit heterogeneous. It is in Moscow that the most favourable conditions exist for vivax malaria re-introduction in the case of a renewed importation. This recent event of large-scale re-introduction of vivax malaria in a temperate area can serve as a case study for further research.
The human-biometeorological conditions in Kyiv (Ukraine) and changes in the frequency of heat stress during the summer period due to recent climate trends were analyzed. The evaluation based on physiologically equivalent temperature (PET). The results revealed the highest probability of thermal comfortable conditions in Kyiv is from the last 10-day period of April to the end of June and from the last 10-day period of August to the end of September. The probability of heat stress reached nearly 90% during the second and third 10-day periods of July. A pronounced increase in thermal stress during the studied heat wave cases (HW), as well as increasing amount of days with heat stress in the period 1991-2015, were found.
INTRODUCTION: As the global climate changes, heat waves are having a disproportionate impact on seniors and other socially vulnerable groups. In order to mitigate the threats of extreme heat, it is critical to develop and promote resources for coping during these events. A better understanding of the role of risk perceptions and the factors that influence them is needed in order to improve public responses to threatening events, particularly among seniors. METHODS: This mixed-methods study examined risk perceptions and coping practices in seniors using qualitative interviews (n = 15) and a survey (n = 244) of seniors across Waterloo Region, Ontario. RESULTS: Seniors showed relatively accurate risk tracking as indicated by the link between measures of actual risk and perception of personal risk. While vulnerability to heat is often believed to be associated with inaccurate perceptions of risk, within our sample, vulnerability appears more strongly related to social location and access to resources. Participants described social connections as important resources for resilience, but the stigma surrounding vulnerability, and other social norms, as barriers to seeking support. CONCLUSION: The positive relationship between participants’ risk perceptions and actual risk for negative consequences of extreme heat was an important finding, given that problems of emergency preparedness and risk reduction are often framed as issues of awareness of risk, rather than social location and inequality. Along with increased public resources for coping with extreme heat, communicating about resources, fostering social connections and reducing stigma may be important leverage points for increasing the resiliency of seniors to heat waves.
This study aimed to evaluate the relationship between weather factors (temperature, humidity, solar radiation, wind speed, and rainfall) and COVID-19 infection in the State of Rio de Janeiro, Brazil. Solar radiation showed a strong (-0.609, p < 0.01) negative correlation with the incidence of novel coronavirus (SARS-CoV-2). Temperature (maximum and average) and wind speed showed negative correlation (p < 0.01). Therefore, in this studied tropical state, high solar radiation can be indicated as the main climatic factor that suppress the spread of COVID-19. High temperatures, and wind speed also are potential factors. Therefore, the findings of this study show the ability to improve the organizational system of strategies to combat the pandemic in the State of Rio de Janeiro, Brazil, and other tropical countries around the word.
Pollen is an important component of bioaerosol and the distribution of pollen and its relationship with meteorological parameters can be analyzed to better prevent hay fever. Pollen assemblages can also provide basic data for analyzing the relationship between bioaerosol and PM. We collected 82 samples of airborne pollen using a TSP large flow pollen collector from June 1, 2015 to June 1, 2016, from central Zhanjiang city in South China. We also conducted a survey of the nearby vegetation at the same time, in order to characterize the major plant types and their flowering times. We then used data on daily temperature, relative humidity, precipitation, vapor pressure and wind speed from a meteorological station in the center of Zhanjiang City to assess the relationship between the distribution of airborne pollen and meteorological parameters. Our main findings and conclusions are as follows: (1) We identified 15 major pollen types, including Pinus, Castanopsis, Myrica, Euphorbiaceae, Compositae, Gramineae, Microlepia and Polypodiaceae. From the vegetation survey, we found that the pollen from these taxa represented more than 75% of local pollen, while the pollen of Podocarpus, Dacrydium and other regional pollen types represented less than 25%. (2) The pollen concentrations varied significantly in different seasons. The pollen concentrations were at a maximum in spring, consisting mainly of tree pollen; the pollen concentrations were at an intermediate level in autumn and winter, consisting mainly of herb pollen and fern spores; and the pollen concentrations in summer were the lowest, consisting mainly of fern spores. (3) Analysis of the relationship between airborne pollen concentrations and meteorological parameters showed that variations in the pollen concentrations were mainly affected by temperature and relative humidity. In addition, there were substantial differences in these relationships in different seasons. In spring, pollen concentrations were mainly affected by temperature; in summer, they were mainly affected by the direction of the maximum wind speed; in autumn, they were mainly affected by relative humidity and temperature; and in winter, they were mainly affected by relative humidity and wind speed. Temperature and relative humidity promote plant growth and flowering. Notably, the variable wind direction in summer and the increased wind speed in winter and spring are conductive to pollen transmission. (4) Of the 15 major pollen types, Moraceae, Artemisia and Gramineae are the main allergenic pollen types, with peaks in concentration during April-May, August-September, and October-December, respectively. (5) Atypical weather conditions have substantial effects on pollen dispersal. In South China, the pollen concentrations in the sunny day were usually significantly higher than that of the rainy day. The pollen concentrations increased in short rainy days, which usually came from the Herb and Fern pollen. The pollen concentrations decreased in continuous rainy days especially for the Tree and Shrub pollen. the pollen concentrations in the sunny days were usually significantly higher than that in the rainy days. The pollen concentrations increased in short and strong rainfall.
BACKGROUND: Gastroesophageal reflux disease (GERD) is a highly prevalent disease of the upper gastrointestinal tract, and it is associated with environmental and lifestyle habits. Due to an increasing interest in the environment, several groups are studying the effects of meteorological factors and air pollutants (MFAPs) on disease development. AIM: To identify MFAPs effect on GERD-related medical utilization. METHODS: Data on GERD-related medical utilization from 2002 to 2017 were obtained from the National Health Insurance Service of Korea, while those on MFAPs were obtained from eight metropolitan areas and merged. In total, 20071900 instances of GERD-related medical utilizations were identified, and 200000 MFAPs were randomly selected from the eight metropolitan areas. Data were analyzed using a multivariable generalized additive Poisson regression model to control for time trends, seasonality, and day of the week. RESULTS: Five MFAPs were selected for the prediction model. GERD-related medical utilization increased with the levels of particulate matter with a diameter ? 2.5 ?m (PM(2.5)) and carbon monoxide (CO). S-shaped and inverted U-shaped changes were observed in average temperature and air pollutants, respectively. The time lag of each variable was significant around nine days after exposure. CONCLUSION: Using five MFAPs, the final model significantly predicted GERD-related medical utilization. In particular, PM(2.5) and CO were identified as risk or aggravating factors for GERD.
Mosquito-borne diseases affect millions of individuals worldwide; the area of endemic transmission has been increasing due to several factors linked to globalization, urban sprawl, and climate change. The Aedes aegypti mosquito plays a central role in the dissemination of dengue, Zika, chikungunya, and urban yellow fever. Current preventive measures include mosquito control programs; however, identifying high-risk areas for mosquito infestation over a large geographic region based only on field surveys is labor-intensive and time-consuming. Thus, the objective of this study was to assess the potential of remote satellite images (WorldView) for determining land features associated with Ae. aegypti adult infestations in São José do Rio Preto/SP, Brazil. We used data from 60 adult mosquito traps distributed along four summers; the remote sensing images were classified by land cover types using a supervised classification method. We modeled the number of Ae. aegypti using a Poisson probability distribution with a geostatistical approach. The models were constructed in a Bayesian context using the Integrated nested Laplace Approximations and Stochastic Partial Differential Equation method. We showed that an infestation of Ae. aegypti adult mosquitoes was positively associated with the presence of asbestos roofing and roof slabs. This may be related to several other factors, such as socioeconomic or environmental factors. The usage of asbestos roofing may be more prevalent in socioeconomically poor areas, while roof slabs may retain rainwater and contribute to the generation of temporary mosquito breeding sites. Although preliminary, our results demonstrate the utility of satellite remote sensing in identifying landscape differences in urban environments using a geostatistical approach, and indicated directions for future research. Further analyses including other variables, such as land surface temperature, may reveal more complex relationships between urban mosquito micro-habitats and land cover features.
Parks benefit public health in many ways, from improving stormwater management to mitigating disparities associated with physical and mental health. Parks and recreational areas can be adversely impacted by disasters. Perceptions of postdisaster environmental contamination of parks can limit residents’ willingness to use parks and thus their benefits. In this study, teams of trained interviewers surveyed residents in Houston, Texas, who were using parks in the months following Hurricane Harvey. Data about resident perception of and emotional response to environmental pollution, as well as self-rated postdisaster mental and physical health, were collected. Respondents felt certain that Hurricane Harvey caused environmental contamination in their communities and that this contamination would impact health. Of respondents, 40% reported anger, while only 21.4% felt afraid. Survey respondents had significantly lower mental health composite scores than a national comparison group. Although residents report strong concerns and need information about hurricane-associated environmental contamination, little data have been collected or made available to residents by federal or state agencies. The use of recreational areas for flood mitigation potentially exposes residents to environmental contamination after flooding. More information is needed about risks to health from these exposures.
Non-point stormwater runoff is a major contamination source of receiving waterbodies. Heightened incidence of waterborne disease outbreaks related to recreational use and source water contamination is associated with extreme rainfall events. Such extreme events are predicted to increase in some regions due to climate change. Consequently, municipal separate storm sewer systems (MS4s) conveying pathogens to receiving waters are a growing public health concern. In addition, the spread of antibiotic resistance genes (ARGs) and antibiotic resistant bacteria in various environmental matrices, including urban runoff, is an emerging threat. The resistome and microbiota profile of MS4 discharges has yet to be fully characterized. To address this knowledge gap, we first analyzed the relationship between rainfall depth and intensity and E. coli densities (fecal indicator) in stormwater from four MS4 outflows in Columbus, Ohio, USA during the spring and summer of 2017. Microbial source tracking (MST) was conducted to examine major fecal contamination sources in the study sewersheds. A subset of samples was analyzed for microbial and resistome profiles using a metagenomic approach. The results showed a significant positive relationship between outflow E. coli density and rainfall intensity. MST results indicate prevalent fecal contamination from ruminant populations in the study sites (91% positive among the samples tested). Protobacteria and Actinobacteria were two dominant bacteria at a phylum level. A diverse array of ARGs and potentially pathogenic bacteria (e.g. Salmonella enterica Typhimurium), fungi (e.g. Scedosporium apiospermum), and protists (e.g. Acanthamoeba palestinensis) were found in urban stormwater outflows that discharge into adjacent streams. The most prevalent ARGs among samples were ?-lactam resistance genes and the most predominant virulence genes within bacterial community were related with Staphylococcus aureus. A comprehensive contamination profile indicates a need for sustainable strategies to manage urban stormwater runoff amid increasingly intense rainfall events to protect public and environmental health.
Aedes aegypti is the main vector of dengue, Zika, chikungunya, and yellow fever viruses. Controlling populations of vector mosquito species in urban environments is a major challenge and being able to determine what aquatic habitats should be prioritized for controlling Ae. aegypti populations is key to the development of more effective mosquito control strategies. Therefore, our objective was to leverage on the Miami-Dade County, Florida immature mosquito surveillance system based on requested by citizen complaints through 311 calls to determine what are the most important aquatic habitats in the proliferation of Ae. aegypti in Miami. We used a tobit model for Ae. aegypti larvae and pupae count data, type and count of aquatic habitats, and daily rainfall. Our results revealed that storm drains had 45% lower percentage of Ae. aegypti larvae over the total of larvae and pupae adjusted for daily rainfall when compared to tires, followed by bromeliads with 33% and garbage cans with 17%. These results are indicating that storm drains, bromeliads and garbage cans had significantly more pupae in relation to larvae when compared to tires, traditionally know as productive aquatic habitats for Ae. aegypti. Ultimately, the methodology and results from this study can be used by mosquito control agencies to identify habitats that should be prioritized in mosquito management and control actions, as well as to guide and improve policies and increase community awareness and engagement. Moreover, by targeting the most productive aquatic habitats this approach will allow the development of critical emergency outbreak responses by directing the control response efforts to the most productive aquatic habitats.
This time-series study collects data on stroke-related mortality, years of life lost (YLL), air pollution, and meteorological conditions in 96 Chinese cities from 2013 to 2016 and proposes a three-stage strategy to generate the national and regional estimations of avoidable YLL, gains in life expectancy and stroke-related population attributable fraction by postulating that the daily fine particulate matter (PM(2.5)) has been kept under certain standards. A total of 1 318 911 stroke deaths are analyzed. Each 10 µg m(-3) increment in PM(2.5) at lag(03) is associated with a city-mean increase of 0.31 (95% CI: 0.19, 0.44) years of life lost from stroke. A number of 914.11 (95% CI: 538.28, 1288.94) years of city-mean life lost from stoke could be avoided by attaining the WHO’s Air Quality Guidelines (AQG) (25 µg m(-3)). Moreover, by applying the AQG standard, 0.11 (0.08, 0.15) years of life lost might be prevented for each death, and about 0.91% (95% CI: 0.62%, 1.19%) of the total years of life lost from stroke might be explained by the daily excess PM(2.5) exposure. This study indicates that stroke patients can have a longer life expectancy if stricter PM(2.5) standards are put in place, especially ischemic stroke patients.
This study reveals the best combination of meteorological variables for the prediction of the number of emergency transport due to heat stroke over 64 years old in Tokyo metropolis based on a generalized linear model using 2008-2016 data. Temperature, relative humidity, wind speed, and solar radiation were used as candidates of the explanatory variables. The variable selection with Akaike’s information criterion (AIC) showed that all the four meteorological elements were selected for the prediction model. Additional analysis showed that the combination of daily mean temperature, maximum relative humidity, maximum wind speed, and total solar radiation as explanatory variables gives the best prediction, with approximately 19% less error than the conventional single-variable model which only uses the daily mean temperature. Finally, we quantitatively estimated the relative contribution of each variable to the prediction of the daily number of heat stroke patients using standardized partial regression coefficients. The result reveals that temperature is the largest contributor. Solar radiation is second, with approximately 20% of the temperature effect. Relative humidity and wind speed make relatively small contributions, each contributing approximately 10% and 9% of the temperature, respectively. This result provides helpful information to propose more sophisticated thermal indices to predict heat stroke risk.
Here, we develop a dry eye syndrome (DES) incidence rate prediction model using air pollutants (PM10, NO2, SO2, O-3, and CO), meteorological factors (temperature, humidity, and wind speed), population rate, and clinical data for South Korea. The prediction model is well fitted to the incidence rate (R-2= 0.9443 and 0.9388,p< 2.2 x 10(-16)). To analyze regional deviations, we classify outpatient data, air pollutant, and meteorological factors in 16 administrative districts (seven metropolitan areas and nine states). Our results confirm NO(2)and relative humidity are the factors impacting regional deviations in the prediction model.
The rising probability of extremely high temperatures and an increasing number of consecutive hot days caused by climate change-combined with the impact of these high temperatures on human health-is widely discussed in the literature. There are calls for the development of heatwave adaptation measures by governmental and scientific institutions. In this research, the predictors of health-related heat risk perception of urban citizens in Augsburg, Germany, were investigated. An online survey was conducted with 468 citizens, asking about their heat risk perception, knowledge about heat risks, and demographic data and health information. Statistical methods (Spearman correlation, unpaired t-test, ANOVA and multiple regression) were used to determine which factors were significant and relevant. The results show that the knowledge of heat risks, heat risk sensitivity and an external locus of control are the most important factors for heat risk perception. The health implication score and chronic disease show significant effects in descriptive statistics. Furthermore, younger people showed the highest heat risk perception of all age groups. Surprisingly, income, education, living alone and gender did not play a role in heat risk perception. The findings imply a need for better and intensified heat risk communication in urban areas-especially among elderly people-and thus are important for creating acceptance towards heat wave risks, which is a prerequisite of willingness to adapt.
The coronavirus disease 2019 (COVID-19) pandemic is the most severe global health and socioeconomic crisis of our time, and represents the greatest challenge faced by the world since the end of the Second World War. The academic literature indicates that climatic features, specifically temperature and absolute humidity, are very important factors affecting infectious pulmonary disease epidemics – such as severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS); however, the influence of climatic parameters on COVID-19 remains extremely controversial. The goal of this study is to individuate relationships between several climate parameters (temperature, relative humidity, accumulated precipitation, solar radiation, evaporation, and wind direction and intensity), local morphological parameters, and new daily positive swabs for COVID-19, which represents the only parameter that can be statistically used to quantify the pandemic. The daily deaths parameter was not considered, because it is not reliable, due to frequent administrative errors. Daily data on meteorological conditions and new cases of COVID-19 were collected for the Lombardy Region (Northern Italy) from 1 March, 2020 to 20 April, 2020. This region exhibited the largest rate of official deaths in the world, with a value of approximately 1700 per million on 30 June 2020. Moreover, the apparent lethality was approximately 17% in this area, mainly due to the considerable housing density and the extensive presence of industrial and craft areas. Both the Mann-Kendall test and multivariate statistical analysis showed that none of the considered climatic variables exhibited statistically significant relationships with the epidemiological evolution of COVID-19, at least during spring months in temperate subcontinental climate areas, with the exception of solar radiation, which was directly related and showed an otherwise low explained variability of approximately 20%. Furthermore, the average temperatures of two highly representative meteorological stations of Molise and Lucania (Southern Italy), the most weakly affected by the pandemic, were approximately 1.5 °C lower than those in Bergamo and Brescia (Lombardy), again confirming that a significant relationship between the increase in temperature and decrease in virulence from COVID-19 is not evident, at least in Italy.
BACKGROUND: The prevalence of Acute Myocardial Infarction (AMI) varies from region to region caused by seasonal climate changes and temperature variation. This study aimed to assess the relationship between changing meteorological conditions and incidence of AMI in Iran. METHODS: This retrospective prevalence study was based on medical records of the heart center of Mazandaran Province on all patients diagnosed with AMI in Mazandaran, northern Iran between 2013 and 2015. Patients’ sex and the day, month, year and time of hospital admission were extracted from patients’ records. Moreover, the meteorological reports were gathered. RESULTS: A statistically significant difference was found between the distributions of AMI cases across 12 months of the year (P < 0.01). Fuzzy clustering analysis using 16 different climatic variables showed that March, April, and May were in the same cluster together. The other 9 months were in different clusters. CONCLUSION: Significant increase in AMI was seen in March, April and May (cold to hot weather).
This is the first study to look at future temporal urban heath island (UHI) trends of Athens (Greece) under different UHI intensity regimes. Historical changes in the Athens UHI, spanning 1971-2016, were assessed by contrasting two air temperature records from stable meteorological stations in contrasting urban and rural settings. Subsequently, we used a five-member regional climate model (RCM) sub-ensemble from EURO-CORDEX with a horizontal resolution of 0.11 degrees (similar to 12 x 12 km) to simulate air temperature data, spanning the period 1976-2100, for the two station sites. Three future emissions scenarios (RCP2.6, RCP4.5, and RCP8.5) were implanted in the simulations after 2005 covering the period 2006-2100. Two 20-year historical reference periods (1976-1995 and 1996-2015) were selected with contrasting UHI regimes; the second period had a stronger intensity. The daily maximum and minimum air temperature data (T(max)and T-min) for the two reference periods were perturbed to two future periods, 2046-2065 and 2076-2095, under the three RCPs, by applying the empirical quantile mapping (eqm) bias-adjusting method. This novel approach allows us to assess future temperature developments in Athens under two UHI intensity regimes that are mainly forced by differences in air pollution and heat input. We found that the future frequency of days with T-max> 37 degrees C in Athens was only different from rural background values under the intense UHI regime. Thus, the impact of heatwaves on the urban environment of Athens is dependent on UHI intensity. There is a large increase in the future frequency of nights with T-min> 26 degrees C in Athens under all UHI regimes and climate scenarios; these events remain comparatively rare at the rural site. This large urban amplification of the frequency of extremely hot nights is likely caused by air pollution. Consequently, local mitigation policies aimed at decreasing urban atmospheric pollution are expected to be highly effective in reducing urban temperatures and extreme heat events in Athens under future climate change scenarios. Such policies directly have multiple benefits, including reduced electricity (energy) needs, improved living quality and strong health advantages (heat- and pollution-related illness/deaths).
Heatwaves are likely to increase over different regions of the world as the climate warms, which poses potential risk to the environment, society, and public health. Concurrent daytime and nighttime heatwaves have a more significant impact on human health than individually occurring heatwaves, especially in regions with high population density. The Huai River Basin (HRB) is taken as a case in this study to explore the characteristics of concurrent daytime and nighttime heatwaves in a high-population-density area, including quantification of the population’s exposure to concurrent heatwaves. Nighttime hot events are found to increase to greater extent than daytime hot events from 1961 to 2017. A single daytime or nighttime hot event can provide 40-60 % capacity for the concurrent daytime and nighttime hot events. The concurrent daytime and nighttime heatwaves show an obvious southeast-northwest gradient with high values in the southeast and low values in the northwest of the HRB. Daytime hot events, nighttime hot events, and concurrent daytime and nighttime heatwave events all show significant upward trends from 1987 to 2017. The population exposed to the heat extremes increased significantly over this period, especially in regards to concurrent daytime and nighttime heatwaves. The population exposure in terms of the quantity, duration, and magnitude of concurrent daytime and nighttime heatwaves increased by around 5-, 9-, and 35-fold from 1984 to 2017. Atmospheric circulation analysis of the 2013 concurrent daytime and nighttime heatwaves in the HRB shows a long-lasting anomalous circulation background (e.g., anomalous high pressure system and low cloud water content) leading to severe concurrent daytime and nighttime heatwaves.
Research on population exposure to extreme heat is hindered by the limited spatial coverage of weather station and single exposure characteristic. In this study, a random forest regression model was developed to estimate monthly mean maximum temperature and extreme temperature. A cross-regional statistics in mean maximum temperature and extreme temperature was created to calculate a threshold which was used to reflect extreme temperature events. The threshold was used to develop the frequency, intensity and duration in extreme heat exposure for mean maximum temperature and extreme temperature, and quantified their spatiotemporal trends across residential areas in China in summer, 2001-2013. Results show that the risk of extreme heat was the highest in East China and was lower in Northeast and Northwest. The frequency of extreme heat exposure increased in most areas for mean maximum temperature, decreased in northern areas and increased in southern areas for extreme temperature. The intensity of extreme heat exposure increased in East, Central, South, and Southwest China for both mean maximum temperature and extreme temperature. The duration of extreme heat exposure increased nationwide for mean maximum temperature, and decreased in northern areas for extreme temperature. Frequency, intensity and duration of extreme heat exposure increased significantly, accompanied by high frequency, intense intensity and long-lasting in East, Central, Southwest, and South China. Overall, the results identify the high-risk hotspots over China in summer, 2000-2013.
Long endemicity of the Highly Pathogenic Avian Influenza (HPAI) H5N1 subtype in Egypt poses a lot of threats to public health. Contrary to what is previously known, outbreaks have been circulated continuously in the poultry sectors all year round without seasonality. These changes call the need for epidemiological studies to prove or deny the influence of climate variability on outbreak occurrence, which is the aim of this study. This work proposes a modern approach to examine the degree to which the HPAI-H5N1disease event is being influenced by climate variability as a potential risk factor using generalized estimating equations (GEEs). GEE model revealed that the effect of climate variability differs according to the timing of the outbreak occurrence. Temperature and relative humidity could have both positive and negative effects on disease events. During the cold seasons especially in the first quarter, higher minimum temperatures, consistently show higher risks of disease occurrence, because this condition stimulates viral activity, while lower minimum temperatures support virus survival in the other quarters of the year with the highest negative effect in the third quarter. On the other hand, relative humidity negatively affects the outbreak in the first quarter of the year as the humid weather does not support viral circulation, while the highest positive effect was found in the second quarter during which low humidity favors the disease event.
Many cities are developing mitigation plans in an effort to reduce the population health impacts from expected future increases in the frequency and intensity of heat waves. To inform heat mitigation and adaptation planning, information is needed on the extent to which available mitigation strategies, such as reflective and green roofs, could result in significant reductions in heat exposure. Using the Weather Research and Forecasting (WRF) model, we analysed the impact of green and cool (reflective) roofs on the urban heat island (UHI) and temperature-related deaths in the Greater Boston area (GBA) and New England area (NEA) in summer and winter. In the GBA, green and cool roofs reduced summertime population-weighted temperature by 0.35 degrees C and 0.40 degrees C, respectively. In winter, green roofs did not affect temperature, whereas cool roofs caused a temperature reduction of 0.40 degrees C. In the NEA, the cooler summers induced by green and cool roofs were estimated to reduce the heat-related mortality rates by 0.21% and 0.17%, respectively, compared to baseline. Cool-roof-induced temperature reduction in winter could increase the cold-related mortality rate by 0.096% compared to baseline. These results suggest that both green and cool roofing strategies have the potential to reduce the impact of heat on premature deaths. Additionally, the differing effects in winter suggest the need for a careful consideration of health trade-offs in choosing heat island mitigation strategies.
As climate change progresses, understanding the impact on human health associated with the temperature and air pollutants has been paramount. However, the predicted effect on temperature associated with particulate matter (PM(10)) is not well understood due to the difficulty in predicting the local and regional PM(10). We compared temperature-attributable mortality for the baseline (2003-2012), 2030s (2026-2035), 2050s (2046-2055), and 2080s (2076-2085) based on a distributed lag non-linear model by simultaneously considering assumed levels of PM(10) on historical and projected temperatures under representative concentration pathway (RCP) scenarios. The considered projected PM(10) concentrations of 35, 50, 65, 80, and 95 ?g/m(3) were based on historical concentration quantiles. Our findings confirmed greater temperature-attributable risks at PM(10) concentrations above 65 ?g/m(3) due to the modification effect of the pollutants on temperature. In addition, this association between temperature and PM(10) was higher under RCP8.5 than RCP4.5. We also confirmed regional heterogeneity in temperature-attributable deaths by considering PM(10) concentrations in South Korea with higher risks in heavily populated areas. These results demonstrated that the modification association of air pollutants on health burdens attributable to increasing temperatures should be considered by researchers and policy makers.
Identifying Aedes aegypti breeding hotspots in urban areas is crucial for the design of effective vector control strategies. Remote sensing techniques offer valuable tools for mapping habitat suitability. In this study, we evaluated the association between urban landscape, thermal features, and mosquito infestations. Entomological surveys were conducted between 2016 and 2019 in Vila Toninho, a neighborhood of São José do Rio Preto, São Paulo, Brazil, in which the numbers of adult female Ae. aegypti were recorded monthly and grouped by season for three years. We used data from 2016 to 2018 to build the model and data from summer of 2019 to validate it. WorldView-3 satellite images were used to extract land cover classes, and land surface temperature data were obtained using the Landsat-8 Thermal Infrared Sensor (TIRS). A multilevel negative binomial model was fitted to the data, which showed that the winter season has the greatest influence on decreases in mosquito abundance. Green areas and pavements were negatively associated, and a higher cover of asbestos roofs and exposed soil was positively associated with the presence of adult females. These features are related to socio-economic factors but also provide favorable breeding conditions for mosquitos. The application of remote sensing technologies has significant potential for optimizing vector control strategies, future mosquito suppression, and outbreak prediction.
Rivers are representative of the overall contamination found in their catchment area. Contaminant concentrations in watercourses depend on numerous factors including land use and rainfall events. Globally, in Mediterranean regions, rainstorms are at the origin of fluvial multipollution phenomena as a result of Combined Sewer Overflows (CSOs) and floods. Large loads of urban-associated microorganisms, including faecal bacteria, are released from CSOs which place public health – as well as ecosystems – at risk. The impacts of freshwater contamination on river ecosystems have not yet been adequately addressed, as is the case for the release of pollutant mixtures linked to extreme weather events. In this context, microbial communities provide critical ecosystem services as they are the only biological compartment capable of degrading or transforming pollutants. Through the use of 16S rRNA gene metabarcoding of environmental DNA at different seasons and during a flood event in a typical Mediterranean coastal river, we show that the impacts of multipollution phenomena on structural shifts in the particle-attached riverine bacteriome were greater than those of seasonality. Key players were identified via multivariate statistical modelling combined with network module eigengene analysis. These included species highly resistant to pollutants as well as pathogens. Their rapid response to contaminant mixtures makes them ideal candidates as potential early biosignatures of multipollution stress. Multiple resistance gene transfer is likely enhanced with drastic consequences for the environment and human-health, particularly in a scenario of intensification of extreme hydrological events.
Energy-poor households in Africa’s burgeoning urban informal settlements are especially likely to suffer from heatwaves because of thermally inefficient dwellings and lack of affordable cooling options. This study utilised a controlled experiment to assess the effectiveness of passive cooling through specially formulated paints (cool coatings) in standard informal structures. The test structures were built to simulate typical shack dwellings in South Africa’s urban informal settlements. Results showed that the mean daily maximum temperatures of the coated structure were up to 4.3 degrees C lower than those in the uncoated structure. The same cooling trend was observed for the minimum daily temperatures, which were lower by an average of 2.2 degrees C. Besides, the annual frequency of maximum temperature exceedances beyond the critical heat stroke value of 40 degrees C dropped from 19% for the uncoated structure to 1% for the coated structure. These temperature differences were found to be statistically and subjectively significant, implying that cool coatings may be effective in promoting thermal comfort and climate resilience in poor urban communities. It is recommended that governmental authorities and relevant role players invest in the production and assisted application of cool coatings in urban informal settlements. The interventions promise hope of reduced energy burden on poor households and could be implemented in parallel with ongoing efforts focused on the design and implementation of low-cost, durable and thermally comfortable houses for indigent communities. Ultimately, the endeavours could be a potential policy change to assist in expanding poor households’ access to alternative and green energy resources.
Over the years, Jamaica has experienced sporadic cases of dengue fever. Even though the island is vulnerable to dengue, there is paucity in the spatio-temporal analysis of the disease using Geographic Information Systems (GIS) and remote sensing tools. Further, access to time series dengue data at the community level is a major challenge on the island. This study therefore applies the Water-Associated Disease Index (WADI) framework to analyze vulnerability to dengue in Jamaica based on past, current and future climate change conditions using three scenarios: (1) WorldClim rainfall and temperature dataset from 1970 to 2000; (2) Climate Hazard Group InfraRed Precipitation with Station data (CHIRPS) rainfall and land surface temperature (LST) as proxy for air temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) for the period 2002 to 2016, and (3) maximum temperature and rainfall under the Representative Concentration Pathway (RCP) 8.5 climate change scenario for 2030 downscaled at 25 km based on the Regional Climate Model, RegCM4.3.5. Although vulnerability to dengue varies spatially and temporally, a higher vulnerability was depicted in urban areas in comparison to rural areas. The results also demonstrate the possibility for expansion in the geographical range of dengue in higher altitudes under climate change conditions based on scenario 3. This study provides an insight into the use of data with different temporal and spatial resolution in the analysis of dengue vulnerability.
In 2015, Karachi saw its first ever epidemic of severe heatrelated illnesses that resulted in an extraordinary number of hospital admissions, especially in the intensive care, for fatal heat stroke within-hospital mortality of 3.7%.We conducted this study to elucidate the patient-related factors that lead to an increase in hospital admissions with heat-related illnesses in a tertiary care hospital. It was a descriptive case series conducted in the department of medicine at the Aga Khan University in June 2015. A total of 134 patients were admitted with heat-related illnesses of which 76(56.7%) were males. The mean age of the patients was 66 ±14.5 years. Heatstroke was present in 86 (64.2%) patients, followed by heat exhaustion in 48 (35.8%) and in-hospital mortality from heat-related illnesses was 5(3.7%). Hypertension (OR 2(95 % CI 1.0, 3.6) and insufficient sleep or food or water intake (OR 1.7(95 % CI 0.8, 3.8) was associated with severe heat-related illnesses. The effects remained even after adjusting for type and area of residence.
Climate change, especially as reflected in heat waves, is a rising threat worldwide. Appropriate use of cooling devices can protect people from health impacts during a heat wave. A population-based telephone survey was conducted in a representative sample of residents in Hong Kong to investigate ownership and use of domestic cooling devices, identify correlates, and examine their associations with risk perception of potential health impact of climate change. More than 90% of the 1002 respondents owned and used cooling devices at home. The majority (57.7%) perceived the potential health risk of climate change at a high level. However, risk perception had no relationship with ownership and utilization of cooling devices. Old people (>= 65 years), the low-educated, those with low income, and those with chronic diseases were more likely not to use air conditioners when feeling hot. Our findings suggest that there are no signs showing people have taken more protective actions although half of respondents recognized climate change as a threat. Familial economic condition may be a major determinant in ownership and use of air conditioners at home. Old people and those with chronic diseases are at high risk of adverse exposure to climate change and therefore should be equipped with appropriate measures to use cooling devices.
Heat stress caused by high air temperature and high humidity is a serious health concern for urban residents. Mobile measurement of these two parameters can complement weather station observations because of its ability to capture data at fine spatial scales and in places where people live and work. In this paper, we describe a smart temperature and humidity sensor (Smart-T) for use on bicycles to characterize intracity variations in human thermal conditions. The sensor has several key characteristics of internet of things (IoT) technology, including lightweight, low cost, low power consumption, ability to communicate and geolocate the data (via the cyclist’s smartphone), and the potential to be deployed in large quantities. The sensor has a reproducibility of 0.03 degrees-0.05 degrees C for temperature and of 0.18%-0.33% for relative humidity (one standard deviation of variation among multiple units). The time constant with a complete radiation shelter and moving at a normal cycling speed is 9.7 and 18.5 s for temperature and humidity, respectively, corresponding to a spatial resolution of 40 and 70 m. Measurements were made with the sensor on street transects in Nanjing, China. Results show that increasing vegetation fraction causes reduction in both air temperature and absolute humidity and that increasing impervious surface fraction has the opposite effect.
In response to more frequent heatwaves, various regional or national heat-health warning systems (HHWSs) have been developed recently as adaptation measures. A wide range of methodologies have been utilized to issue warnings, as there is no universal definition of “heat event” or “heatwave”, nor are there quantified thresholds of human-health tolerance to extreme weather. The performance of these warning systems has rarely been evaluated with actual heat-health data, especially the morbidity data, in regions with severe impact. In this study, we assessed the performance of the Shanghai HHWS based on heat-related illness data collected by the Chinese Center for Disease Control and Prevention (China CDC) and then conducted a comparative analysis among the Shanghai HHWS, the China Meteorological Administration HHWS, the Chinese national standard for heatwave indexes, the heat index adopted by the USA’s National Weather Service and the definition suggested by the World Meteorological Organization to understand their potential performance for application in Shanghai and to evaluate the temperature thresholds and different meteorological indices employed. The results show that: 1) during the research period, 50% of heat-related illnesses and 58.2% of heat-related deaths in Shanghai occurred on dates that had no heat warnings; 2) for the current threshold (35 °C), the single metric of temperature outperformed the temperature-duration two-parameter method; 3) different from existing studies, while infants and seniors are deemed as vulnerable population groups to heat, young and middle-aged males were found to suffer more heat-related illnesses in hot weather. More detailed analyses reveal that the performance of heat-health warning systems needs to be evaluated and revised periodically, and warning thresholds utilized must be localized to reflect public tolerance to heat and to address the vulnerability of target population groups. Temperature is the dominant threshold in heat-related morbidity and mortality analysis. While a decrease in the temperature threshold would definitely increase the warning frequency and socioeconomic costs, it might also cause warning fatigue. The trade-off between these two aspects is essential for decision-makers and other stakeholders in HHWS design and improvement.
The duration and intensity of future heat waves are analyzed for 53 cities in the Middle East and the North Africa (MENA) region for the 21st century under two different scenarios (RCP4.5 and RCP8.5). A consistent approach is carried out using data from 13 Regional models within the framework of the Coordinated Regional Climate Downscaling Experiment (CORDEX). By the end of the century, 80% of the most populated MENA cities are expected to be at least 50% of the days under heat wave conditions during the warm season. In addition, the mean and maximum intensity of the heat waves will also increase. Changes in the duration and intensity of heat waves have shown to be negatively correlated. Therefore, the vulnerability of the MENA cities to future heat waves was determined using a cumulative index (CI) that takes into account both duration and intensity. This CI indicates that Middle East and the eastern part of Africa will suffer the most unfavorable temperature conditions in the future. Assuming no intervention trough adaptation/mitigation strategies, these results, together with the particular properties of the MENA region, such as aridity or lack of precipitation, make it likely that the area will be affected by disease or famine.
This study aims to assess the physical and social vulnerability of floods, which occurred in the year 2015 in Adyar Basin of Chennai, Tamil Nadu. Thematic layers, such as rainfall, land use land cover (LULC), drainage density, slope, soil, and roads per watershed, were prepared and assigned the ranks using rank sum method. The knowledge based weighted indexed overlay analysis was employed based on causative factors, to prepare vulnerability map of the Adyar Basin. This research would help the community to find the vulnerability based on multi criteria analysis, by considering certain indicators like household, residential properties of the people living in Adyar basin. This engineering geological study, can play a vital role in comparing the physical and social vulnerability along with the real time vulnerability to ensure public safety, cost-effective solution for planning mitigation measures and preparedness in flood prone areas.
Organophosphate esters (OPEs) in atmospheric fine particles (PM(2.5)) were comprehensively investigated in the Beijing-Tianjin-Hebei (BTH) region from April 2016 to March 2017. The concentrations of ?(8)OPEs in all the five sampling sites ranged from 90 to 8291 pg/m(3) (mean 1148 ± 1239 pg/m(3); median 756 pg/m(3)). The highest level (median 1067 pg/m(3)) was found at one of the urban sites in Beijing, followed by Tianjin (746 pg/m(3)) and Shijiazhuang (724 pg/m(3)). Tris(2-chloroethyl) phosphate (TCEP) and tri[(2R)-1-chloro-2-propyl] phosphate (TCPP) were the dominant compounds across the five sampling locations. Generally, the concentrations of chlorinated OPEs were relatively higher in summer than in winter (p < 0.05), but no significant seasonal difference was discovered for non-chlorinated individual OPEs. The concentrations of tri-n-butyl phosphate (TBP), TCEP, TCPP and triphenyl phosphate (TPP) were positively correlated with the meteorological parameters (i.e. temperature and relative humidity) (p < 0.05), indicating an evident influence of meteorological condition on OPE distribution. We observed a negative correlation (p < 0.05) between octanol-air partition coefficients (logK(oa)) and the ratio of PM(2.5)-bound OPE concentrations to total suspended particulates-bound OPE concentrations, suggesting that physicochemical properties affect the particle-size distribution of OPEs. Furthermore, the median value of cancer hazard quotients (HQs) of TCEP was higher than TBP and tris(2-ethylhexyl) phosphate (TEHP). The health risk assessment showed that HQ values for children were ~1.6 times higher than those for adults. Relatively higher health risk induced by PM(2.5)-bound OPEs via inhalation was found during severe hazy days than in clear days.
Climate change is one of the most significant environmental issues facing communities, while poor construction and absence of effective air-conditioning (AC) predominantly cause indoor overheating. Although AC may help meeting indoor comfort, it increases the vulnerability of low-income residents, triggers large energy consumption, and generates anthropogenic heat, which worsens heat stress out-door. The capacity of buildings to maintain comfortable thermal conditions without mechanical cooling is the key factor protecting occupants against the rising temperature. Residents of Darwin, Australia, will be largely affected by increasing temperature where the annual peak ambient temperature may increase by 7.4 degrees C in 2060, while the number of hours above 30 degrees C will rise by 70%. Based on regional climate modelling for the Australian area and using a building energy simulation platform, we computed that by 2060 the indoor air temperature in a typical residential building may exceed 30 degrees C for over 4000 h under free-floating condition, with a peak daytime and night-time temperatures of 39 degrees C and 36.5 degrees C, respectively. The sensible thermal energy need for cooling per unit area under thermostatically controlled condition will increase from the current level of 110.7 kWh/m 2 to 196.8 kWh/m(2) in 2060. Different adaptation techniques when applied to the typical residential building yield to the peak indoor air temperature drop by 3.3-12 degrees C, and cooling energy needs reductions by 23.5-195.3 kWh/m(2) (12-99.7%) for low, medium, and high retrofit buildings compared to the typical residential building in 2060. Our study indicates that improved building quality is necessary to enhance survivability and energy efficiency in Darwin considering the role of building adaptation measures to counterbalance the impacts of global warming. (C) 2020 Elsevier B.V. All rights reserved.
Outdoor Thermal Comfort (OTC) is largely influenced by urban morphology and geometry of the urban landscape. In this study, the Local Climatic Zones (LCZs) approach was adopted to assess the OTC in different settings of Sriniketan-Santiniketan Planning Area (SSPA) during the summer season. The basic objective of this study is to assess OTC from both subjective and objective perspectives over eight LCZs. This study assessed OTC over LCZs using both field measurements and questionnaire survey. Non-parametric tests such as ANOVA and Kruskal-Wallis tests were also performed to find out the significant difference of perception across LCZs. The result of ANOVA and Krushkal-Walls test showed that subjective perception of OTC across LCZs varied due to diversified physical landscape settings. The result also showed that the maximum (above 40 degrees C) and minimum (28 degrees C) temperature was recorded in built types (particularly compact low rise) and natural land cover types (dense forest and water) respectively. Highest PET was also recorded over the built-up LCZs (about 50 degrees C) that led to this planning region thermally very hot or extreme heat stress. The respondents living in LCZ3 and LCZ6 were more sensitive to the thermal sensation as compared to those living in other LCZs.This study was probably the first attempt dealing with the assessment of OTC over the tropical planning region using LCZ approach from subjective and objective perspectives. Therefore, this research study has an immense potentiality to formulate strategies to deal with the outdoor thermal conditions as well to implement climate sensitive planning for urban sustainability in tropical cities.
Extreme heat and associated health risks increasingly become threats to urban populations, especially in developing countries of the tropics. Although human thermal exposure in cities has been studied across the globe, current narratives insufficiently discuss mixed-used spaces, informal economic activity settings, and informal settlements. This study assessed outdoor human thermal comfort in the tropical city of Kolkata, India where uncomfortable hot and humid climatic conditions prevail year-round. Thermal Comfort Perception Surveys (TCPS) and biometeorological observations were conducted during summer and winter in three microentrepreneurial neighborhoods (Kumartuli, Boipara, and Mallickghat). A one-way ANOVA was performed to investigate the variance in Physiologically Equivalent Temperature (PET) values of 318 survey samples across neighborhoods. Through multiple linear regression and ANCOVA, significant relationships were established between various climatic and non-climatic parameters. No respondent reported a neutral thermal sensation during the summer. Annual neutral PET across neighborhoods was 23.6 °C with a neutral PET range of 19.5 °C to 27.6 °C. Annual neutral PET was 22.7 °C and 26.5 °C in Mallickghat and Boipara, respectively. Respondents in Boipara were more sensitive towards warmer sensation than in Mallickghat. Even in the winter, people reported warmer sensation votes. PET was a better predictor of the mean Thermal Sensation Vote (mTSV) compared to air temperature. In a few cases, acclimatization and expectations improved thermal comfort. Results can be useful in formulating strategies towards improving outdoor microclimate and heat health in tropical cities.
Thermal comfort plays a main role in encouraging people to use outdoor spaces, specifically in hot arid and humid climates. The reconciliation of climatic aspects during the urban design phase is limited in implementation, due to the need for multidisciplinary collaboration between desperate scientific fields of climatology, urban planning, and urban environmental modelling. This paper aims to create an integrated interface between the microclimate, outdoor thermal comfort, and design guidelines. The investigation combines subjective and objective approaches, including on-site field measurements, a structured questionnaire using the seven-point American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE 55) thermal sensation votes, and a correlation study of these votes and the microclimatic parameters. Pedestrian thermal comfort was then examined under six shading scenarios, addressing the form and opening of shading devices using computational fluid dynamics. Modelling is based on four dependent variables: wind velocity, ventilation flow rate, air temperature, and the physiological equivalent temperature (PET) index. Findings indicate that the form and location of apertures of the shading devices were the dominant factors in achieving thermal comfort on the urban scale, and led to a reduction in air temperature and a physiological equivalent temperature of 2.3-2.4 degrees C. Subjective votes indicate that people who live in hot arid climates have a wider range of adaptation and tolerance to local climatic conditions Accordingly, a psychometric chart, for the case study outdoor thermal comfort was developed.
Background: Iran is a disaster-prone country, and many flood events occur in its provinces annually. The unprecedented amount of rainfall in the northern region of Iran (from March 17 to 22, 2019) led to flash flooding of the Golestan Province. Objectives: This study assessed the challenges and strengths of health-related needs in the first 10 days after the great flood in Golestan; via interviews with experts. Methods: This cross-sectional and qualitative study was carried out in Gonbad-e-Kavoos, Anbar Alum, Aq-Qala, Simin Shahr, and Gomishan cities of the flood-hit province of Golestan from March 21, to April 13 in 2019. The data were collected using the researcher’s field observations and interviews with 26 experts and policymakers. Results: The findings were categorized into 10 main groups namely mental health, environmental health, health education, maternal, infant, and child health, nutrition, epidemics, drugs, mobile hospitals, non-communicable diseases, and management. Environmental health issues were faced with a wide range of challenges. Conclusion: Due to the insufficient development of many health infrastructures in underdeveloped and developing countries, health policymakers and disaster management experts should collaborate before and after the disaster to detect and resolve the flaws. This could help reduce health problems and challenges when a natural disaster occurs, particularly by diminishing the number of morbidities and mortalities.
In this study, we applied the Weather Research and Forecasting model to project 2050 urban and rural temperature. We applied a time-stratified analysis to compare it with mortality between 2001 and 2014 and between 2011 and 2014, to estimate the elevated risk of a 2050 heat event. We included change in daytime versus nighttime and urban versus rural temperatures as factors to project mortality, to evaluate the potential influence of climate change on mortality risk. Increases of 2.9 degrees C and 2.6 degrees C in maximum and minimum air temperature are projected in a 2050 heat event, with a day and a night that will have respective temperatures 9.8 degrees C and 4.9 degrees C higher than 2001-2014. Significantly higher mortality risk is forecasted in 2050 compared to 2001-2014 (IRR 1.721 [1.650, 1.796]) and 2011-2014 (IRR 1.622 [1.547, 1.701]) without consideration of temperature change. After consideration of changing temperature, change in maximum temperature in rural areas will induce the highest mortality risk during 2050, possibly due to rapid urbanization across the city, and with the second highest mortality risk induced by the change in minimum temperature in urbanized areas, possibly because local people in the city have been adapted to the maximum level of urban thermal stress during a summer day. Improvements to heat warning systems and sustainable planning protocols are urgently needed for climate change mitigation.
Mountains are characterized by their specificities such as fragility, marginality and remoteness. They are prone to various hazards such as drought, flood, forest fire, landslide and therefore physical, ecological and social systems of the mountains are at risk. Climate change adds to intensifying the magnitude of multi-hazard risk in mountains. The present study attempts to evaluate risk induced by multi-hazard and climate change in the Indian Himalayan Region (IHR) using the Intergovernmental Panel on Climate Change (IPCC) framework. The proposed multi-hazard risk index was based on indicators from a broader domain and applied on 109 administrative districts of IHR. Exposure, sensitivity, adaptive capacity, and coping capacity were defined using comprehensive and sub-regional indicators identified through inductive and deductive approaches. The result showed that the differential risks among the districts of IHR were governed by the multiplicity of the factor such as demography, amenities, natural capital, partnership, technology and spatial specificities of the districts. The result highlighted the need of inclusion of spatial specificities for the risk mitigation in the IHR and therefore a Mountain Specific Risk Management Framework (MSMRMF) was proposed for sustaining the mountainous communities. The proposed MSMRMF contained two broad components as risk assessment and risk addressal. The framework detailed the risk mitigation and coping strategies (based on adjustment of internal and external strengths) for addressing risks. Risk mitigation was proposed to achieved through habitation resilience, natural capital enhancement, external partnerships, climate change adaptation, and technological interventions. The framework would provide an insight of risk and risk management strategies for the multi-hazard prone mountain regions for the sustainable development under the global change.
Air pollution and heat are significant threats to public health, especially in urban areas with intensive human activities under the trend of climate change. However, the mediation effects of urban form on health via air pollution and heat have been overlooked in previous investigations. This study explored the potential impacts and pathways of urban form on cardiovascular mortality through air pollutants and heat by using partial least squares model with data from Taiwan. The measurable characteristics of urban form include city size, urban sprawl, and mixed land use. Other factors that influence cardiovascular mortality, such as urban industrial level, economic status, aging population, and medical resource, were also considered in the model. Results revealed that maximizing mixed land use and minimizing city size and urban sprawl can help reduce cardiovascular mortality, and the minimizing city size was the most important one. Urban industrial level, economic status, aging population, and medical resource were also influential factors. This is the first study to consider the pathways and impacts of urban form on cardiovascular mortality, and our results indicate that proper urban planning and policy could reduce cardiovascular mortality.
OBJECTIVE: The Lighthouse Project (2017-2018) explored the role that faith-based organizations (FBOs) might play as resilience hubs for climate-related stresses and extreme weather emergencies in disadvantaged urban environments of three cities. This paper discusses the role that public health played in these initiatives and makes an appeal for more participatory, community-engaged public health in light of the persistent gaps in its approach to equitable climate change preparedness. METHODS: Pilots were initiated in the Greater Toronto and Hamilton Area (GTHA): Brampton’s Emergency Managers offered pre-selected FBO volunteers specialized training to be part of the city’s emergency response in establishing FBO sites as emergency muster stations. An environmental organization in Hamilton explored how its existing networks could rally around a local social resilience challenge, and a community organizer in Toronto undertook network building to support mostly newcomer populations in one inner-city neighbourhood. All pilots used a mix of cold calling, workshops, municipal presentations, and participation in local programming and public events. Two convened local working groups. RESULTS: By the end of the pilot, Brampton’s Emergency Management Office had made one contractual relationship with an FBO and its volunteers. In Hamilton, a multi-stakeholder network emerged to support the climate preparedness of agencies serving local vulnerable populations. In Toronto, a residents’ working group was established to address neighbour well-being and emergency response in one apartment tower. Work in all three communities is ongoing. CONCLUSION: Multi-stakeholder support for community organizations and local volunteers can enable partnerships in neighbourhood-level climate resilience-before, during and after extreme weather events. Public Health, while not typically top-of-mind as a key ally in this work, is well positioned to make a contribution. Consistent with place-based approaches, an emergent community development design enabled community animators to catalyze collaborations to suit the on-the-ground realities of each site.
Although previous studies have reported that meteorological factors might affect the risk of Japanese encephalitis (JE), the relationship between meteorological factors and JE remains unclear. This study aimed to evaluate the relationship between meteorological factors and JE and identify the threshold temperature. Daily meteorological data and JE surveillance data in Dazhou, Sichuan, were collected for the study period from 2005 to 2012 (restricting to May-October because of the seasonal distribution of JE). A distributed lag nonlinear model was used to analyze the lagged and cumulative effect of daily average temperature and daily rainfall on JE transmission. A total of 622 JE cases were reported over the study period. We found JE was positively associated with daily average temperature and daily rainfall with a 25-day lag and 30-day lag, respectively. The threshold value of the daily average temperature is 20°C. Each 5°C increase over the threshold would lead to a 13% (95% CI: 1-17.3%) increase in JE. Using 0 mm as the reference, a daily rainfall of 100 mm would lead to a 132% (95% CI: 73-311%) increase in the risk of JE. Japanese encephalitis is climate-sensitive; meteorological factors should be taken into account for the future prevention and control measure making, especially in a warm and rainy weather condition.
BACKGROUND: More than 80,000 dengue cases including 215 deaths were reported nationally in less than 7 months between 2016 and 2017, a fourfold increase in the number of reported cases compared to the average number over 2010-2016. The region of Negombo, located in the Western province, experienced the greatest number of dengue cases in the country and is the focus area of our study, where we aim to capture the spatial-temporal dynamics of dengue transmission. METHODS: We present a statistical modeling framework to evaluate the spatial-temporal dynamics of the 2016-2017 dengue outbreak in the Negombo region of Sri Lanka as a function of human mobility, land-use, and climate patterns. The analysis was conducted at a 1?km?×?1?km spatial resolution and a weekly temporal resolution. RESULTS: Our results indicate human mobility to be a stronger indicator for local outbreak clusters than land-use or climate variables. The minimum daily temperature was identified as the most influential climate variable on dengue cases in the region; while among the set of land-use patterns considered, urban areas were found to be most prone to dengue outbreak, followed by areas with stagnant water and then coastal areas. The results are shown to be robust across spatial resolutions. CONCLUSIONS: Our study highlights the potential value of using travel data to target vector control within a region. In addition to illustrating the relative relationship between various potential risk factors for dengue outbreaks, the results of our study can be used to inform where and when new cases of dengue are likely to occur within a region, and thus help more effectively and innovatively, plan for disease surveillance and vector control.
Previous studies have consistently analyzed the impact that extreme temperatures will have on human health. However, there are very few data on temperature-related mortality burden considering future demographic changes in a context of climate change in Portugal. This study aims to quantify the impact of climate change on heat-, cold-, and net change mortality burdens, taking into account the future demographic changes in Lisbon Metropolitan Area, Portugal. We applied a time-series generalized linear model with a quasi-Poisson model via a distributed lag nonlinear model to project temperature-related mortality burden for two climatological scenarios: a present (or reference, 1986-2005) scenario and a future scenario (2046-2065), in this case the Representative Concentration Pathway RCP8.5, which reflects the worst set of expectations (with the most onerous impacts). The results show that the total attributable fraction due to temperature, extreme and moderate cold, is statistically significant in the historical period and the future projected scenarios, while extreme and moderate heat were only significant in the projected future summer period. Net differences were attributed to moderate cold in the future winter months. Projections show a consistent and significant increase in future heat-related mortality burden. The attributable fraction due to heat in the future period, compared to the historical period, ranges from 0 to 1.5% for moderate heat and from 0 to 0.5% for extreme heat. Adaptation should be implemented at the local level, so as to prevent and diminish the effects on citizens and healthcare services, in a context of climate change.
The flaviviruses are small single-stranded RNA viruses that are typically transmitted by mosquitoes or tick vectors and are etiological agents of acute zoonotic infections. The viruses are found around the world and account for significant cases of human diseases. We investigated population of culicine mosquitoes in central region of Korean Peninsula, Incheon Metropolitan City and Hwaseong-si. Aedes vexans nipponii was the most frequently collected mosquitoes (56.5%), followed by Ochlerotatus dorsalis (23.6%), Anopheles spp. (10.9%), and Culex pipiens complex (5.9%). In rural regions of Hwaseong, Aedes vexans nipponii was the highest population (62.9%), followed by Ochlerotatus dorsalis (23.9%) and Anopheles spp. (12.0%). In another rural region of Incheon (habitat of migratory birds), Culex pipiens complex was the highest population (31.4%), followed by Ochlerotatus dorsalis (30.5%), and Aedes vexans vexans (27.5%). Culex pipiens complex was the predominant species in the urban region (84.7%). Culicine mosquitoes were identified at the species level, pooled up to 30 mosquitoes each, and tested for flaviviral RNA using the SYBR Green-based RT-PCR and confirmed by cDNA sequencing. Three of the assayed 2,683 pools (989 pools without Anopheles spp.) were positive for Culex flaviviruses, an insect-specific virus, from Culex pipiens pallens collected at the habitats for migratory birds in Incheon. The maximum likelihood estimation (the estimated number) for Culex pipiens pallens positive for Culex flavivirus was 25. Although viruses responsible for mosquito-borne diseases were not identified, we encourage intensified monitoring and long-term surveillance of both vector and viruses in the interest of global public health.
Purpose The purpose of this paper is to examine the role of high intensity precipitation events in increasing the vulnerability to floods in Mediterranean Spain. Precipitation intensity in this area appears to have augmented in the last two decades in association with warming trends of the Mediterranean Sea. At the same time, intense urbanization processes, occupying and transforming flood prone land, have produced an important increase in exposure. The main objective is to assess whether higher intensity precipitation and changing patterns in exposure aggravate vulnerability to floods. Design/methodology/approach In this paper, vulnerability is understood as the result of the interrelationships between exposure, sensitivity, impacts and adaptive capacity. Consequently, methods used involved the compilation and analysis of published and unpublished precipitation data, population and land use data, data on insurance claims, and media sources related to those variables. Findings Changes toward episodes of more intense precipitation in the expanding urban areas of Mediterranean Spain increase exposure but not necessarily vulnerability, at least in terms of human deaths. However, adaptative capacity needs to be formulated. Actions that attempt to absorb and eventually reuse flood flows (as the flood park in Alicante) appear to be more effective than traditional hydraulic solutions (as in Majorca). Originality/value The paper provides a systematic and coherent approach to vulnerability analysis taking into account the changing dynamics of its components. Especially, it signals the limits of current adaptive approaches to flooding and advocates for changes toward a more circular and less linear approach to urban drainage.
The connection between mental health and weather extremes is a public health concern, but less studied to date than physical health. This exploratory study examines the mental health impacts of two kinds of weather extremes increasingly linked to climate change-summer heat waves and extreme winter weather-in a low- to middle-income population in the Southeastern U.S. The distribution of mental health impacts, and potential pathways to them, are examined with a focus on race. Data are from a random-sample survey of 426 participants and are analyzed with bivariate statistics and path analysis. Self-reported mental health impacts, in both seasons, were common in our study, with White participants tending to report worse impacts than participants who identified with other racial groups. Physical health had direct effects on mental health across several models, overall and by racial group. For summer heat waves, concern about climate change and social cohesion had direct and indirect effects, respectively, on mental health in White participants only. For extreme winter weather, preparedness had a direct negative effect on mental health in White, but not Black, participants. Results suggest that there may be racial differences in the influence of human and social capital factors on mental health related to weather extremes, warranting further study of this critical topic and with larger racial subgroup samples.
INTRODUCTION: Respiratory syncytial virus (RSV) infection is a major cause of hospitalization in children. Meteorological factors are known to influence seasonal RSV epidemics, but the relationship between meteorological factors and RSV infection in children is not well understood. We aimed to explore the relationship between meteorological factors and RSV infections among hospitalized children, using different statistical models. METHODS: We conducted a retrospective review concerning children with RSV infections admitted to a tertiary pediatric hospital in Wenzhou, China, between January 2008 and December 2017. The relationship between meteorological factors (average daily temperatures, average daily relative humidity, rainfall, rainfall days, and wind speed) and the incidence of RSV in hospitalized children was analyzed using three time-series models, namely an autoregressive integrated moving average (ARIMA) model, a generalized additive model (GAM), and a least absolute shrinkage and selection operator (LASSO)-based model. RESULTS: In total, 15?858 (17.6%) children tested positive for RSV infection. The ARIMA model revealed a marked seasonal pattern in the RSV detection rate, which peaked in winter and spring. The model was a good predictor of RSV incidence (R(2) : 83.5%). The GAM revealed that a lower temperature and higher wind speed preceded increases in RSV detection. The LASSO-based model revealed that temperature and relative humidity were negatively correlated with RSV detection. CONCLUSIONS: Seasonality of RSV infection in hospitalized children correlated strongly with temperature. The LASSO-based model can be used to predict annual RSV epidemics using weather forecast data.
Floods are a prominent risk factor in the world of public health, as there is a risk of dispersal of harmful biological and chemical contaminants in floodwater. As climate change increases, the occurrence of natural disasters and risk of adverse health outcomes due to flash flooding also increases. Fecal indicator bacteria, such as Escherichia coli and Enterococci, are often encountered in contaminated floodwater and can cause gastrointestinal illnesses as well as a variety of infections. In August 2016, East Baton Rouge and surrounding parishes in Louisiana suffered heavy floods due to intense rainfall. No study of water quality during flooding has been conducted previously in Baton Rouge, Louisiana. Twenty-three pre-flush and post-flush water samples were collected immediately from accessible homes that had been affected by the floods in order to quantify concentrations of fecal indicator bacteria. These samples were analyzed for the presence of E. coli and Enterococci through both quantitative polymerase chain reaction (qPCR) and the IDEXX enzyme substrate method. The qPCR results indicated that 30% of the samples contained Enterococci and 61% of the samples contained E. coli, with the highest concentrations found in the pre-flush outdoor hose and the pre-flush kitchen tap. The IDEXX method yielded total coliforms in 65% of the samples, E. coli in 4%, and Enterococci in 35%, with the highest concentrations in the pre-flush outdoor faucet and the pre-flush post-filtration kitchen tap. Physical parameters including temperature, barometer pressure, dissolved oxygen, oxidation reduction potential, pH, conductivity, and salinity of these samples were also recorded. Of these parameters, conductivity and salinity were significant, suggesting they may positively influence E. coli and Enterococci growth.
Numerous studies in epidemiology, meteorology, and climate change research have demonstrated a significant association between abnormal ambient temperature and mortality. However, there is a shortage of research attention to a systematic assessment of potential mitigation measures which could effectively reduce the heat-related morbidity and mortality risks. This study first illustrates a conceptualization of a systems analysis version of urban framework for climate service (UFCS). It then constructs a system dynamics (SD) model for the UFCS and employs this model to quantify the impacts of heat waves on public health system in Shanghai and to evaluate the performances of two mitigation measures in the context of a real heat wave event in July 2013 in the city. Simulation results show that in comparison with the baseline without mitigation measures, if the hospital system could prepare 20% of beds available for emergency response to heat waves once receiving the warning in advance, the number of daily deaths could be reduced by 40-60 (15.8-19.5%) on the 2 days of day 7 and day 8; if increasing the minimum living allowance of 790 RMB/month in 2013 by 20%, the number of daily deaths could be reduced by 50-70 (17.7-21.9%) on the 2 days of day 8 and day 12. This tool can help policy makers systematically evaluate adaptation and mitigation options based on performance assessment, thus strengthening urban resilience to changing climate.
Extreme heat threatens desert city residents throughout the hot summer months and inhibits outdoor recreation and activity. Ecosystem services provide various benefits for urban environments. For desert cities, few are more critical than microclimate regulation and water treatment and conservation. This study evaluates the degree to which artificial wetlands support cooler microclimates and reduce the local urban heat island effect. The authors use (a) remotely sensed temperature data for Avondale, Arizona, to measure temperature differences between neighborhoods with and without water features and (b) resident surveys to evaluate perceptions of potential cooling effects. Results show substantial differences in the daytime surface temperatures for the wetland neighborhood compared to those without water features. More than a third of residents perceived a cooling effect throughout the year. The authors conclude that artificial wetlands within a desert city increase human comfort by reducing surface and air temperature and should be considered an urban heat island mitigation strategy.
Dengue is one of the most serious vector-borne infectious diseases in India, particularly in Kolkata and its neighbouring districts. Dengue viruses have infected several citizens of Kolkata since 2012 and it is amplifying every year. It has been derived from earlier studies that certain meteorological variables and climate change play a significant role in the spread and amplification of dengue infections in different parts of the globe. In this study, our primary objective is to identify the relative contribution of the putative drivers responsible for dengue occurrences in Kolkata and project dengue incidences with respect to the future climate change. The regression model was developed using maximum temperature, minimum temperature, relative humidity and rainfall as key meteorological factors on the basis of statistically significant cross-correlation coefficient values to predict dengue cases. Finally, climate variables from the Coordinated Regional Climate Downscaling Experiment (CORDEX) for South Asia region were input into the statistical model to project the occurrences of dengue infections under different climate scenarios such as Representative Concentration Pathways (RCP4.5 and RCP8.5). It has been estimated that from 2020 to 2100, dengue cases will be higher from September to November with more cases in RCP8.5 (872 cases per year) than RCP4.5 (531 cases per year). The present research further concludes that from December to February, RCP8.5 leads to suitable warmer weather conditions essential for the survival and multiplication of dengue pathogens resulting more than two times dengue cases in RCP8.5 than in RCP4.5. Furthermore, the results obtained will be useful in developing early warning systems and provide important evidence for dengue control policy-making and public health intervention.
The first long-term monitoring to document both activity and density of questing ixodid ticks in Vienna, Austria, is introduced. It was started in 2017 and is planned to run over decades. Such long-term monitorings are needed to quantify possible effects of climate change or to develop tick density forecast models. The monthly questing tick density at three sites has been observed by using a standardized sampling method by dragging an area of [Formula: see text] at each occasion. Popular recreational areas were chosen as study sites. These are the Prater public park, the wooded Kahlenberg, and a wildlife garden in Klosterneuburg. First results show a 3-year time series of nymphs and adults of the Ixodes ricinus species complex and Haemaphysalis concinna for the period 2017-2019. Whereas questing nymphs of the I. ricinus species complex were collected from February to November, H. concinna nymphs were only dragged from May to October. The peak of nymphal activity of the I. ricinus species complex was in May, that of H. concinna in August. In addition, a brief overview is given about ticks and tick-borne pathogens occurring in urban and suburban areas of Vienna.
Urbanisation and industrialisation led to the increase of ambient particulate matter (PM) concentration. While subsequent regulations may have resulted in the decrease of some PM matrices, the simultaneous changes in climate affecting local meteorological conditions could also have played a role. To gain an insight into this complex matter, this study investigated the long-term trends of two important matrices, the particle mass (PM(2.5)) and particle number concentrations (PNC), and the factors that influenced the trends. Mann-Kendall test, Sen’s slope estimator, the generalised additive model, seasonal decomposition of time series by LOESS (locally estimated scatterplot smoothing) and the Buishand range test were applied. Both PM(2.5) and PNC showed significant negative monotonic trends (0.03-0.6 ?g m(-3). yr(-1) and 0.40-3.8 × 10(3) particles. cm(-3). yr(-1), respectively) except Brisbane (+0.1 ?g m(-3). yr(-1) and +53 particles. cm(-3). yr(-1), respectively). For the period covered in this study, temperature increased (0.03-0.07 °C.yr(-1)) in all cities except London; precipitation decreased (0.02-1.4 mm. yr(-1)) except in Helsinki; and wind speed was reduced in Brisbane and Rochester but increased in Helsinki, London and Augsburg. At the change-points, temperature increase in cold cities influenced PNC while shifts in precipitation and wind speed affected PM(2.5). Based on the LOESS trend, extreme events such as dust storms and wildfires resulting from changing climates caused a positive step-change in concentrations, particularly for PM(2.5). In contrast, among the mitigation measures, controlling sulphur in fuels caused a negative step-change, especially for PNC. Policies regarding traffic and fleet management (e.g. low emission zones) that were implemented only in certain areas or in a progressive uptake (e.g. Euro emission standards), resulted to gradual reductions in concentrations. Therefore, as this study has clearly shown that PM(2.5) and PNC were influenced differently by the impacts of the changing climate and by the mitigation measures, both metrics must be considered in urban air quality management.
Heat-health risk is a growing concern in many regions of China due to the more frequent occurrence of extremely hot weather. Spatial indexes based on various heat assessment frameworks can be used for the assessment of heat risks. In this study, we adopted two approaches-Crichton’s risk triangle and heat vulnerability index (HVI) to identify heat-health risks in the Northern Jiangxi Province of China, by using remote sensing and socio-economic data. The Geographical Information System (GIS) overlay and principal component analysis (PCA) were separately used in two frameworks to integrate parameters. The results show that the most densely populated community in the suburbs, instead of city centers, are exposed to the highest heat risk. A comparison of two heat assessment mapping indicates that the distribution of HVI highlights the vulnerability differences between census tracts. In contrast, the heat risk index of Crichton’s risk triangle has a prominent representation for regions with high risks. The stepwise multiple linear regression zero-order correlation coefficient between HVI and outdoor workers is 0.715, highlighting the vulnerability of this particular group. Spearman’s rho nonparametric correlation and the mean test reveals that heat risk index is strongly correlated with HVI in most of the main urban regions in the study area, with a significantly lower value than the latter. The analysis of variance shows that the distribution of HVI exhibits greater variety across urban regions than that of heat risk index. Our research provides new insight into heat risk assessment for further study of heat health risk in developing countries.
BACKGROUND: Extreme heat poses current and future risks to human health. Heat vulnerability indices (HVIs), commonly developed using principal components analysis (PCA), are mapped to identify populations vulnerable to extreme heat. Few studies critically assess implications of analytic choices made when employing this methodology for fine-scale vulnerability mapping. OBJECTIVE: We investigated sensitivity of HVIs created by applying PCA to input variables and whether training input variables on heat-health data produced HVIs with similar spatial vulnerability patterns for Detroit, Michigan, USA. METHODS: We acquired 2010 Census tract and block group level data, land cover data, daily ambient apparent temperature, and all-cause mortality during May-September, 2000-2009. We used PCA to construct HVIs using: a) “unsupervised”-PCA applied to variables selected a priori as risk factors for heat-related health outcomes; b) “supervised”-PCA applied only to variables significantly correlated with proportion of all-cause mortality occurring on extreme heat days (i.e., days with 2-d mean apparent temperature above month-specific 95th percentiles). RESULTS: Unsupervised and supervised HVIs yielded differing spatial vulnerability patterns, depending on selected land cover input variables. Supervised PCA explained 62% of variance in the input variables and was applied on half the variables used in the unsupervised method. Census tract-level supervised HVI values were positively associated with increased proportion of mortality occurring on extreme heat days; supervised PCA could not be applied to block group data. Unsupervised HVI values were not associated with extreme heat mortality for either tracts or block groups. DISCUSSION: HVIs calculated using PCA are sensitive to input data and scale. Supervised HVIs may provide marginally more specific indicators of heat vulnerability than unsupervised HVIs. PCA-derived HVIs address correlation among vulnerability indicators, although the resulting output requires careful contextual interpretation beyond generating epidemiological research questions. Methods with reliably stable outputs should be leveraged for prioritizing heat interventions. https://doi.org/10.1289/EHP4030.
Extreme heat is the leading cause of heat-related mortality around the world. Extracting heat vulnerability information from the urban complexity system is crucial for urban health studies. Using heat vulnerability index (HVI) is the most common approach for urban planners to locate the places with high vulnerability for intervention and protection. Previous studies have demonstrated that HVI can play a vital role in determining which areas are at risk of heat-related deaths. Both equal weight approach (EWA) and principal component analysis (PCA) are the conventional methods to aggregate indicators to HVI. However, seldom studies have compared the differences between these two approaches in estimating HVI. In this paper, we evaluated the HVIs in Hangzhou in 2013, employing EWA and PCA, and assessed the accuracies of these two HVIs by using heat-related deaths. Our results show that both HVI maps showed that areas with high vulnerability are located in the central area while those with low vulnerability are located in the suburban area. The comparison between HVI(EWA)and HVI(PCA)shows significantly different spatial distributions, which is caused by the various weight factors in EWA and PCA. The relationship between HVI(EWA)and heat-related deaths performs better than the relationship between HVI(PCA)and deaths, implying EWA could be a better method to evaluate heat vulnerability than PCA. The HVI(EWA)can provide a spatial distribution of heat vulnerability at intracity to direct heat adaptation and emergency capacity planning.
Leptospirosis is a serious bacterial infection that occurs worldwide, with fatality rate of up to 40% in the most severe cases. The number of cases peaks during the rainy season and may reach epidemic proportions in the event of flooding. It is possible that people living in areas affected by natural disasters are at greater risk of contracting the disease. The aim of this study was to identify clusters of relatively higher risk for leptospirosis occurrence, both in space and time, in six municipalities of Santa Catarina, Brazil, which had the highest incidence of the disease between 2000 and 2016, and to evaluate if these clusters coincide with the occurrence of natural disasters. The cases were geocoded with the geographic coordinates of patients’ home addresses, and the analysis was performed using SaTScan software. The areas mapped as being at risk for hydrological and mass movements were compared with the locations of detected leptospirosis clusters. The disease was more common in men and in the age group from 15 to 69 years. In the scan statistics performed, only space-time showed significant results. Clusters were detected in all municipalities in 2008, when natural disasters preceded by heavy rainfall occurred. One of the municipalities also had clusters in 2011. In these clusters, most of the cases lived in urban areas and areas at risk for experiencing natural disasters. The interaction between time (time of disaster occurrence) and space (areas at risk of experiencing natural disasters) were the determining factors affecting cluster formation.
Exposure to extreme heat contributes to high morbidity and mortality relative to other climate hazards. The city of Philadelphia, PA is particularly vulnerable to the impacts of extreme heat, due to the urban heat island effect and high prevalence of sensitive populations. We developed a heat vulnerability index, which identified priority areas that are most at-risk of experiencing adverse heat-related health outcomes and in need of preparedness and mitigation interventions. An interactive website was created to display the maps and allow the public to navigate the data with links to potential resources for relief from extreme heat days. Such methods can be adapted for other cities that wish to identify and target long-term priority areas.
The impacts of climate change and human activities are challenging water sustainability in many cities around the world. Advanced understanding of the future long-term coevolution of coupled urban human-water systems is of considerable interest in this context. This study uses a previously developed sociohydrologic model to explore the coevolutionary trajectories of Beijing City’s human-water system over the 2015-2099 period under possible climate changes. The effects of multiple human adaptive actions under alternative climate scenarios are investigated in particular. Results show that there might be a recurrent competition for water between humans and the natural environment (e.g., groundwater aquifer) in the long-term future, indicating that effective water management needs to ensure that this competition remains within a safe operating space. Three regimes of the human-environment competition are revealed, including a sustainable development regime in which human society and groundwater aquifer are both safe throughout their coevolutionary trajectories, a regime that may lead to severe population loss due to overaggressive population control actions, and a regime that may cause aquifer depletion due to under-perception of the drawdown of groundwater table. Results also show that relying too much on interbasin water diversion project might slacken human water conservation measures and eventually cause more severe aquifer depletion in the long run. Maintaining a high community sensitivity to drawdown of groundwater table and moderate measures to control population growth are keys to avoid unintended, negative consequences.
Several studies have reported that air pollution and climatic factors are major contributors to human morbidity and mortality globally. However, the combined interactive effects of air pollution and climatic factors on human health remain largely unexplored. This study aims to investigate the interactive effects of air pollution and climatic factors on circulatory and respiratory mortality in Xi’an, China. Time-series analysis and the distributed lag non-linear model (DLNM) were employed as the study design and core statistical method. The interaction relative risk (IRR) and relative excess risk due to interaction (RERI) for temperature and Air Quality Index (AQI) interaction on circulatory mortality were 0.973(0.969, 0.977) and -0.055(-0.059, -0.048), respectively; while for relative humidity and AQI interaction, 1.098(1.011, 1.072) and 0.088(0.081, 0.107) respectively, were estimated. Additionally, the IRR and RERI for temperature and AQI interaction on respiratory mortality were 0.805(0.722, 0.896) and -0.235(-0.269, -0.163) respectively, while 1.008(0.965, 1.051) and -0.031(-0.088, 0.025) respectively were estimated for relative humidity and AQI interaction. The interaction effects of climatic factors and AQI were synergistic and antagonistic in relation to circulatory and respiratory mortality, respectively. Interaction between climatic factors and air pollution contributes significantly to circulatory and respiratory mortality.
A comprehensive analysis of meteorological (air temperature, relative humidity, wind speed and global radiation) and outdoor thermal comfort (OTC) conditions (Physiological Equivalent Temperature and Mean Radiant Temperature) was carried out in six Local Climate Zones (LCZs) in Ghent (Belgium) on annual and seasonal level (2017) and during two heat waves (moderate in 2017 and record-breaking in 2019). The continuously monitored data originates from the local urban climate network MOCCA (Monitoring the City’s Climate and Atmosphere). The maximum hourly urban heat island (UHI) of 8.7 degrees C was noticed during the record-breaking 2019 heat wave. OTC was calculated with RayMan based on the observations from the MOCCA network and characteristics of the micro-environment which affect the estimated OTC conditions. The results show that cold stress is more apparent in Ghent during all seasons, except for summer. Downtown locations had more comfortable conditions on seasonal and annual level when compared to the rural location which had the most uncomfortable OTC conditions mostly due to cold stress. However, during the daytime period of heat waves, the open downtown and rural location were most frequently exposed to extreme heat stress, while the urban park in the sparsely built LCZ was the most comfortable area because it was able to effectively mitigate heat stress. This study illustrates the subtlety of the results of a thermal comfort study if one investigates both heat and cold stress on a yearly basis and during the extreme heat wave periods in a city with a moderate climate.
There is currently an increase in the number of heat waves occurring worldwide. Moscow experienced the effects of an extreme heat wave in 2010, which resulted in more than 10,000 extra deaths and significant economic damage. This study conducted a comprehensive assessment of the social risks existing during the occurrence of heat waves and allowed us to identify the spatial heterogeneity of the city in terms of thermal risk and the consequences for public health. Using a detailed simulation of the meteorological regime based on the COSMO-CLM regional climate model and the physiologically equivalent temperature (PET), a spatial assessment of thermal stress in the summer of 2010 was carried out. Based on statistical data, the components of social risk (vulnerabilities and adaptive capacity of the population) were calculated and mapped. We also performed an analysis of their changes in 2010-2017. A significant differentiation of the territory of Moscow has been revealed in terms of the thermal stress and vulnerability of the population to heat waves. The spatial pattern of thermal stress agrees quite well with the excess deaths observed during the period from July to August 2010. The identified negative trend of increasing vulnerability of the population has grown in most districts of Moscow. The adaptive capacity has been reduced in most of Moscow. The growth of adaptive capacity mainly affects the most prosperous areas of the city.
Urbanization is one of the most significant contributing factors to anthropogenic climate change. However, a lack of projected city land use data has posed significant challenges to factoring urbanization into climate change modeling. Thus, the results from current models may contain considerable errors in estimating future climate scenarios. The Pearl River Delta region was selected as a case study to provide insight into how large-scale urbanization and different climate change scenarios impact the local climate. This study adopts projected land use data from freely available satellite imagery and applies dynamic simulation land use results to the Weather Research and Forecasting Model (WRF). The simulation periods cover the summer periods in 2010 and 2029-2031, the latter of which is averaged to represent the year 2030. The WRF simulation used the observed local climate conditions in 2010 to represent the current scenario and the projected local climate changes for 2030 as the future scenario. Under all three future climate change scenarios, the warming trend is prominent (around 1-2 degrees C increase), with a widespread reduction in wind speed in inland areas (1-2 ms(-1)). The vulnerability of human health to thermal stress was evaluated by adopting the wet-bulb globe temperature (WBGT). The results from the future scenarios suggest a high public health risk due to rising temperatures in the future. This study provides a methodology for a more comprehensive understanding of future urbanization and its impact on regional climate by using freely available satellite images and WRF simulation tools. The simulated temperature and WBGT results can serve local governments and stakeholders in city planning and the creation of action plans that will reduce the potential vulnerability of human health to excessive heat.
The increasing frequency of extreme hot days has a considerable impact on health and energy. Heat stress related to high temperatures cause increased rates of mortality and morbidity, particularly amongst vulnerable populations such as those belonging to lower socio-economic groups. Most studies on heat related mortality and morbidity generally use temperatures from weather stations that do not consider the urban heat island (UHI) effect, leading to inaccurate predictions, particularly during heat waves. This study uses data collected by citizen scientists in predicting outdoor thermal comfort as well as indoor heat stress and peak cooling energy for low income housing in Australia. The results show that the outdoor Universal thermal climate index (UTCI) values estimated during hot afternoon ranged from 26 degrees C to 46 degrees C which equate to moderate to extreme heat stress. The indoor Discomfort index (DI) values calculated inside the living and bedrooms were below the heat stress limits (DI < 28) when Bureau of Meteorology (BoM) data was used as the input for calculation. However, indoor DI exceeded the threshold when actual on-ground data was used in the calculations, indicating that people will be at severe risks of heat related illnesses. It was also found that 60% of the time DI exceeded the threshold value as opposed to 2% with the use of BoM data. Furthermore, the peak cooling load was increased by 24% when on-ground data was used. The results show that low income houses and the neighbourhoods where they are located can cause significant heat related health risks which are normally overlooked in typical simulation studies. This study demonstrated a cost-effective way of collecting microclimate data for urban heat island mitigation and adaptation studies. (C) 2020 Published by Elsevier B.V.
Climate change has led to increases in global temperatures, raising concerns regarding the threat of lethal heat waves and deterioration of the thermal environment. In the present study, we adopted two methods for spatial modelling of the thermal environment based on sensible heat and temperature. A vulnerability map reflecting daytime temperature was derived to plot thermal vulnerability based on sensible heat and climate change exposure factors. The correlation (0.73) between spatial distribution of sensible heat vulnerability and mortality rate was significantly greater than that (0.30) between the spatial distribution of temperature vulnerability and mortality rate. These findings indicate that deriving thermally vulnerable areas based on sensible heat are more objective than thermally vulnerable areas based on existing temperatures. Our findings support the notion that the distribution of sensible heat vulnerability at the community level is useful for evaluating the thermal environment in specific neighbourhoods. Thus, our results may aid in establishing spatial planning standards to improve environmental sustainability in a metropolitan community.
BACKGROUND: Both extreme heat and air pollution exposure during pregnancy have been associated with preterm birth; however, their combined effects are unclear. OBJECTIVES: Our goal was to estimate the independent and joint effects of heatwaves and fine particulate matter [PM < 2.5 ?m in aerodynamic diameter (PM2.5)], exposure during the final gestational week on preterm birth. METHODS: Using birth registry data from Guangzhou, China, we included 215,059 singleton live births in the warm season (1 May-31 October) between January 2015 and July 2017. Daily meteorological variables from 5 monitoring stations and PM2.5 concentrations from 11 sites were used to estimate district-specific exposures. A series of cut off temperature thresholds and durations (2, 3, and 4 consecutive d) were used to define 15 different heatwaves. Cox proportional hazard models were used to estimate the effects of heatwaves and PM2.5 exposures during the final week on preterm birth, and departures from additive joint effects were assessed using the relative excess risk due to interaction (RERI). RESULTS: Numbers of preterm births increased in association with heatwave exposures during the final gestational week. Depending on the heatwave definition used, hazard ratios (HRs) ranged from 1.10 (95% CI: 1.01, 1.20) to 1.92 (1.39, 2.64). Associations were stronger for more intense heatwaves. Combined effects of PM2.5 exposures and heatwaves appeared to be synergistic (RERIs > 0) for less extreme heatwaves (i.e., shorter or with relatively low temperature thresholds) but were less than additive (RERIs < 0) for more intense heatwaves. CONCLUSIONS: Our research strengthens the evidence that exposure to heatwaves during the final gestational week can independently trigger preterm birth. Moderate heatwaves may also act synergistically with PM2.5 exposure to increase risk of preterm birth, which adds new evidence to the current understanding of combined effects of air pollution and meteorological variables on adverse birth outcomes. https://doi.org/10.1289/EHP5117.
The sensitivities of meteorological and chemical predictions to urban effects over four major North American cities are investigated using the high-resolution (2.5-km) Environment and Climate Change Canada’s air quality model with the Town Energy Balance (TEB) scheme. Comparisons between the model simulation results with and without the TEB effect show that urbanization has great impacts on surface heat fluxes, vertical diffusivity, air temperature, humidity, atmospheric boundary layer height, land-lake circulation, air pollutants concentrations and Air Quality Health Index. The impacts have strong diurnal variabilities, and are very different in summer and winter. While the diurnal variations of the impacts share some similarities over each city, the magnitudes can be very different. The underlying mechanisms of the impacts are investigated. The TEB impacts on the predictions of meteorological and air pollutants over Toronto are evaluated against ground-based observations. The results show that the TEB scheme leads to a great improvement in biases and root-mean-square deviations in temperature and humidity predictions in downtown, uptown and suburban areas in the early morning and nighttime. The scheme also leads to a big improvement of predictions of NOx, PM2.5 and ground-level ozone in the downtown, uptown and industrial areas in the early morning and nighttime.
Urbanization and climate change have been rapidly occurring globally. Evidence-based healthy city development is required to improve living quality and mitigate the adverse impact of the outdoor neighborhood environment on public health. Taking Guangzhou as an example to explore the association of neighborhood environment and public health and preferably to offer some implications for better future city development, we measured ten environmental factors (temperature (T), wind-chill index (WCI), thermal stress index (HSI), relative humidity (RH), average wind speed (AWS), negative oxygen ions (NOI), PM2.5, luminous flux (LF), and illuminance (I)) in four seasons in four typical neighborhoods, and the SF-36 health scale was employed to assess the physical and mental health of neighborhood residents in nine subscales (health transition(HT), physiological functions (PF), general health status (GH), physical pain (BP), physiological functions (RP), energy vitality (VT), mental health (MH), social function (SF), and emotional functions (RE)). The linear mixed model was used in an analysis of variance. We ranked the different environmental factors in relation to aspects of health and weighted them accordingly. Generally, the thermal environment had the greatest impact on both physical and mental health and the atmospheric environment and wind environment had the least impact on physical health and mental health, respectively. In addition, the physical health of the resident was more greatly affected by the environment than mental health. According to the results, we make a number of strategic suggestions for the renewal of the outdoor neighborhood environment in subtropical monsoon climate high-density cities and provide a theoretical basis for improving public health through landscape architecture at the neighborhood scale.
Rationale: There is significant evidence of increased healthcare utilization from cardiopulmonary causes in adults from exposure to wildfire smoke, but evidence in pediatric age groups is limited.Objectives: To quantify and examine the healthcare utilization effects of the December 2017 Lilac Fire in San Diego County among pediatric patients at the Rady Children’s Hospital (RCH) emergency department and urgent care (UC) clinics.Methods: Using data from 2011 to 2017, including data on daily particulate matter <2.5 ?m (PM(2.5)) in an inverse-distance interpolation model and RCH electronic medical records, we retrospectively analyzed pediatric respiratory visits at the RCH emergency department and UC clinics during the Santa Ana wind (SAW)-driven Lilac Fire from December 7 to 16, 2017. An interrupted time series study design was applied as our primary analysis to compare the observed pediatric respiratory visits from December 7 to 16, 2017 to what would have occurred in a counterfactual situation, namely, if the Lilac Fire had not occurred. A complementary descriptive spatial analysis was also used to evaluate the geographic distribution of respiratory visits in relationship to satellite imaging of the Lilac Fire and the associated wind pattern.Results: The Lilac Fire was associated with 16.0 (95% confidence interval [CI], 11.2-20.9) excess respiratory visits per day at the RCH emergency department across all pediatric age groups. Children aged 0 to 5 years had the highest absolute excess respiratory visits per day with 7.3 (95% CI, 3.0-11.7), whereas those aged 6 to 12 years had the highest relative increase in visits, with 3.4 (95% CI, 2.3-4.6). RCH UC clinics had similar results. The top five ZIP codes in San Diego County with the highest standard deviations of age-adjusted respiratory visits were all located generally downwind of the fire perimeter, as expected for the SAW pattern.Conclusions: We have demonstrated an increase in pediatric respiratory visits during the SAW-driven Lilac Fire in San Diego County in a patterned geographic distribution that is attributable to an increase in PM(2.5) exposure. Younger children were particularly affected. Climate change is expected to result in more frequent and extensive wildfires in the region and will require greater preparedness and adaptation efforts to protect vulnerable populations, such as young children.
INTRODUCTION: Snakebites represent a serious global public health problem, especially in tropical countries. In Brazil, the incidence of snakebites ranges from 19 to 22 thousand cases per 100000 persons annually. The state of Rondônia, in particular, has had an increasing incidence of snakebites. METHODS: A retrospective cross-sectional study on snakebites was conducted from January 2007 to December 2018. Brazil’s Information System for Notifiable Diseases was queried for all snakebites reported in Porto Velho, Ariquemes, Cacoal, and Vilhena. Data on land surface temperatures during the day and night, precipitation, and humidity were obtained using the Google Earth Engine. A Bayesian time series model was constructed to describe the pattern of snakebites and their relationship with climate data. RESULTS: In total, 6326 snakebites were reported in Rondônia. Accidents were commonly caused by Bothrops sp. (n=2171, 81.80%). Snakebites most frequently occurred in rural areas (n=2271, 85.5%). Men, with a median age of 34 years (n=2101, 79.1%), were the most frequent bitten. Moderate clinical manifestation was the most common outcome of an accident (n=1101, 41.50%). There were clear seasonal patterns with respect to rainfall, humidity, and temperature. Rainfall and land surface temperature during the day or night did not increase the risk of snakebites in any city; however, changes in humidity increased the risk of snakebites in all cities. CONCLUSION: This study identified the population exposed to snakes and the influence of anthropic and climatic factors on the incidence of snakebites. According to climate data, changes in humidity increased the risk of snakebites.
BACKGROUND: Taiwan is geographically located in a zone that is vulnerable to earthquakes, typhoons, floods, and landslide hazards and has experienced various disasters. Six Regional Emergency Medical Operation Centers (REMOCs) are integrated and administered by the Ministry of Health and Welfare (MOHW) to be responsible for emergency situations during disastrous events, such as the emission of chemical toxicants, traffic accidents, industrial materials containment, and typhoons. OBJECTIVE: To analyze events reported by the six REMOCs during the 2014 to 2018 for the government policy reference. METHODS: Data were collected from injured and death toll reports provided by local designated hospitals in the emergency medical reporting system. Disaster events were categorized into three categories: natural disaster (NDs), disasters associated with technology (DTs), and disasters associated with security/violence/others (DSVOs). The three categories were further subdivided into sub-categories. Variables considered for trend analyses included the number of wounded and deaths, event characteristics, date/time, and triage. The frequency of disaster events among the six REMOCs was compared using the chi-square test. We used the global information system (GIS) to describe the distribution of events in Taiwan metropolitan cities. The ?-level was set at 0.05. RESULTS: Of 580 events during the study period, the distribution of disaster characteristics in the jurisdictions of the six REMOCs were different. The majority of disaster events were DTs (64.5%), followed by NDs (24.5%) and DSVOs (11.0%). Events for the three disaster categories in the six REMOCs were different (?(2)-test, p < 0.001). Furthermore, for the Taipei branch (Northern Taiwan), other NDs, especially heatwaves and cold spells, were most reported in New Taipei City (92.2%) and showed an increasing annual trend; for the Kaohsiung branch (Southern Taiwan), DT events were the most reported, especially in Kaohsiung City; and for the Taichung branch (Central Taiwan), DSVOs were the most reported, especially in Taichung City. CONCLUSION: Our data revealed that extreme weather precautions reported in the Taipei branch were increasing. Disaster characteristics were different in each metropolitan city. Upgrading the ability to respond to natural disasters is ineluctable.
Introduction and objectives. The increase in mortality and hospital admissions associated with high and low temperatures is well established. However, less is known about the influence of extreme ambient temperature conditions on cardiovascular ambulance dispatches. This study seeks to evaluate the effects of minimum and maximum daily temperatures on cardiovascular morbidity in the cities of Vigo and A Coruña in North-West Spain, using emergency medical calls during the period 2005-2017. Methods. For the purposes of analysis, we employed a quasi-Poisson time series regression model, within a distributed non-linear lag model by exposure variable and city. The relative risks of cold- and heat-related calls were estimated for each city and temperature model. Results. A total of 70,537 calls were evaluated, most of which were associated with low maximum and minimum temperatures on cold days in both cities. At maximum temperatures, significant cold-related effects were observed at lags of 3-6 days in Vigo and 5-11 days in A Coruña. At minimum temperatures, cold-related effects registered a similar pattern in both cities, with significant relative risks at lags of 4 to 12 days in A Coruña. Heat-related effects did not display a clearly significant pattern. Conclusions. An increase in cardiovascular morbidity is observed with moderately low temperatures without extremes being required to establish an effect. Public health prevention plans and warning systems should consider including moderate temperature range in the prevention of cardiovascular morbidity.
BACKGROUND: Associations between extreme temperatures and health outcomes, such as mortality and morbidity, are often observed. However, relatively little research has investigated the role of extreme temperatures upon ambulance dispatches. METHODS: A time series analysis using London Ambulance Service (LAS) incident data (2010-2014), consisting of 5,252,375 dispatches was conducted. A generalized linear model (GLM) with a quasi-likelihood Poisson regression was applied to analyse the associations between ambulance dispatches and temperature. The 99(th) (22.8°C) and 1(st) (0.0°C) percentiles of temperature were defined as extreme high and low temperature. Fourteen categories of ambulance dispatches were investigated, grouped into ‘respiratory’ (asthma, dyspnoea, respiratory chest infection, respiratory arrest and chronic obstructive pulmonary disease), ‘cardiovascular’ (cardiac arrest, chest pain, cardiac chest pain RCI, cardiac arrhythmia and other cardiac problems) and ‘other’ non-cardiorespiratory (dizzy, alcohol related, vomiting and ‘generally unwell’) categories. The effects of long-term trends, seasonality, day of the week, public holidays and air pollution were controlled for in the GLM. The lag effect of temperature was also investigated. The threshold temperatures for each category were identified and a distributed lag non-linear model (DLNM) was reported using relative risk (RR) values at 95% confidence intervals. RESULTS: Many dispatch categories show significant associations with extreme temperature. Total calls from 999 dispatches and ‘generally unwell’ dispatch category show significant RRs at both low and high temperatures. Most respiratory categories (asthma, dyspnoea and RCI) have significant RRs at low temperatures represented by with estimated RRs ranging from 1.392 (95%CI: 1.161-1.699) for asthma to 2.075 (95%CI: 1.673-2.574) for RCI. The RRs for all other non-cardiorespiratory dispatches were often significant for high temperatures ranging from 1.280 (95% CI: 1.128-1.454) for ‘generally unwell’ to 1.985 (95%CI: 1.422-2.773) for alcohol-related. For the cardiovascular group, only chest pain dispatches reported a significant RR at high temperatures. CONCLUSIONS: Ambulance dispatches can be associated with extreme temperatures, dependent on the dispatch category. It is recommended that meteorological factors are factored into ambulance forecast models and warning systems, allowing for improvements in ambulance and general health service efficiency.
Extreme weather events pose significant threats to urban health in low- and middle-income countries, particularly in sub-Saharan Africa where there are systemic health challenges. This paper investigates health system vulnerabilities associated with flooding and extreme heat, along with strategies for resilience building by service providers and community members, in Accra and Tamale, Ghana. We employed field observations, rainfall records, temperature measurements, and semi-structured interviews in health facilities within selected areas of both cities. Results indicate that poor building conditions, unstable power supply, poor sanitation and hygiene, and the built environment reduce access to healthcare for residents of poor urban areas. Health facilities are sited in low-lying areas with poor drainage systems and can be 6 °C warmer at night than reported by official records from nearby weather stations. This is due to a combination of greater thermal inertia of the buildings and the urban heat island effect. Flooding and extreme heat interact with socioeconomic conditions to impact physical infrastructure and disrupt community health as well as health facility operations. Community members and health facilities make infrastructural and operational adjustments to reduce extreme weather stress and improve healthcare provision to clients. These measures include: mobilisation of residents to clear rubbish and unclog drains; elevating equipment to protect it from floods; improving ventilation during extreme heat; and using alternative power sources for emergency surgery and storage during outages. Stakeholders recommend additional actions to manage flood and heat impacts on health in their cities, such as, improving the capacity of drainage systems to carry floodwaters, and routine temperature monitoring to better manage heat in health facilities. Finally, more timely and targeted information systems and emergency response plans are required to ensure preparedness for extreme weather events in urban areas.
Major perturbations in soil and water quality are factors that can negatively impact human health. In soil environments of urban areas, changes in antibiotic-resistance profiles may represent an increased risk of exposure to antibiotic-resistant bacteria via oral, dermal, or inhalation routes. We studied the perturbation of antibiotic-resistance profiles and microbial communities in soils following a major flooding event in Houston, Texas, caused by Hurricane Harvey. The main objective of this study was to examine the presence of targeted antibiotic-resistance genes and changes in the diversity of microbial communities in soils a short time (3-5?months) and a long time (18?months) after the catastrophic flooding event. Using polymerase chain reaction, we surveyed fourteen antibiotic-resistance elements: intI1, intI2, sul1, sul2, tet(A) to (E), tet(M), tet(O), tet(W), tet(X), and bla(CMY-2). The number of antibiotic-resistance genes detected were higher in short-time samples compared to samples taken a long time after flooding. From all the genes surveyed, only tet(E), bla(CMY-2), and intI1 were prevalent in short-time samples but not observed in long-time samples; thus, we propose these genes as indicators of exogenous antibiotic resistance in the soils. Sequencing of the V3-V4 region of the bacterial 16S rRNA gene was used to find that flooding may have affected bacterial community diversity, enhanced differences among bacterial lineages profiles, and affected the relative abundance of Actinobacteria, Verrucomicrobia, and Gemmatimonadetes. A major conclusion of this study is that antibiotic resistance profiles of soil bacteria are impacted by urban flooding events such that they may pose an enhanced risk of exposure for up to three to five months following the hurricane. The occurrence of targeted antibiotic-resistance elements decreased eighteen months after the hurricane indicating a reduction of the risk of exposure long time after Harvey.
People exposed to heat experience symptoms of varying severity, from mild manifestations to heat stroke. Due to global warming, interest in the impact of heat exposure on human health has been increasing. This study investigated the association between outdoor thermal conditions and heat-related symptoms experienced by pedestrians in a temperate-Mediterranean and hot semi-arid climate. In the study, pedestrians participated in questionnaire-based surveys at outdoor sites in Cyprus in summer and autumn 2019 while the weather conditions at the sites were recorded. In the surveys, pedestrians reported whether they had experienced heat-related symptoms. The physiologically equivalent temperature (PET) was used to estimate the effect of the thermal environment. Statistical analyses of the data included the use of multivariable logistic regression models. In total, 1880 individuals (999 males, 54.2%; mean age +/- standard deviation 38.4 +/- 18.4 years) responded to the surveys of heat-related symptoms. An increase of 1 degrees C in air temperature (adjusted odds ratio (aOR): 1.10, 95% confidence interval (CI): 1.04-1.16) or PET (aOR: 1.04, 95% CI: 1.01-1.07) was associated with an elevated probability of reporting heat-related symptoms. The magnitude of the association of PET with the reporting of heat-related symptoms was found to be higher for nonpermanent residents in Cyprus (aOR: 1.11, 95% CI: 1.02-1.21). Females were more likely than males to report heat-related symptoms (aOR: 2.36, 95% CI: 1.82-3.06). Visiting the monitoring site for work (aOR: 1.69, 95% CI: 1.26-2.26) or reporting a medical history of respiratory disease (aOR: 3.60, 95% CI: 2.39-5.42) were associated with an increased likelihood of reporting heat-related symptoms. The thermal conditions and participant characteristics were associated with increased reporting of heat-related symptoms during non-heat-wave but warm periods in Cyprus. These results could have implications for adaptation measures, healthcare delivery, and public health services.
More than four hundred million people suffer from respiratory diseases each year. Respiratory diseases are associated with a large disease burden. Heatwaves and cold spells, the two most common extreme weather events, have been shown to have crucial negative effects on the prevalence of respiratory diseases. However, impacts of extreme weather on the prevalence of respiratory diseases has been largely overlooked in western China, where more intense and frequent extreme temperature events have been occurring over the past decades. This research gap will obtain an attribution bias in the effects of extreme weather events on the prevalence of respiratory diseases. Therefore, in this study, we analyzed the impact of heatwaves and cold spells on the morbidity of respiratory diseases using a distributed lag nonlinear model with daily disease cases from 2013 to 2016 in Lanzhou, one of the largest cities in western China. A reverse U-shaped relationship depicted the relationship between temperature and the morbidity of respiratory diseases. The highest relative risk was found at 2.6 degrees C by 1.15 (95% confidence interval: 1.09-1.21). Furthermore, we found a significant decrease in the relative risk for heatwaves and a significant increase in the relative risk of cold spells when the temperature exceeded the corresponding threshold by 1 degrees C. Heatwaves and cold spells play harvest effects on the morbidity of respiratory diseases. Our study suggest that the relative risk of respiratory diseases will increase as the climate warms in the future, and thus a preventive system is needed for individuals and medical policy-makers.
The purpose of the present study is to explore the associations between novel coronavirus disease 2019 (COVID-19) case counts and meteorological factors in 30 provincial capital cities of China. We compiled a daily dataset including confirmed case counts, ambient temperature (AT), diurnal temperature range (DTR), absolute humidity (AH) and migration scale index (MSI) for each city during the period of January 20th to March 2nd, 2020. First, we explored the associations between COVID-19 confirmed case counts, meteorological factors, and MSI using non-linear regression. Then, we conducted a two-stage analysis for 17 cities with more than 50 confirmed cases. In the first stage, generalized linear models with negative binomial distribution were fitted to estimate city-specific effects of meteorological factors on confirmed case counts. In the second stage, the meta-analysis was conducted to estimate the pooled effects. Our results showed that among 13 cities that have less than 50 confirmed cases, 9 cities locate in the Northern China with average AT below 0 °C, 12 cities had average AH below 4 g/m(3), and one city (Haikou) had the highest AH (14.05 g/m(3)). Those 17 cities with 50 and more cases accounted for 90.6% of all cases in our study. Each 1 °C increase in AT and DTR was related to the decline of daily confirmed case counts, and the corresponding pooled RRs were 0.80 (95% CI: 0.75, 0.85) and 0.90 (95% CI: 0.86, 0.95), respectively. For AH, the association with COVID-19 case counts were statistically significant in lag 07 and lag 014. In addition, we found the all these associations increased with accumulated time duration up to 14 days. In conclusions, meteorological factors play an independent role in the COVID-19 transmission after controlling population migration. Local weather condition with low temperature, mild diurnal temperature range and low humidity likely favor the transmission.
This paper aims to scrutinize in what way peri-urbanization triggers climate change vulnerabilities. By using spatial analysis techniques, the study undertakes the following tasks. First, the study demarcates Dhaka’s-the capital of Bangladesh-peri-urban growth pattern that took place over the last 24-year period (1992-2016). Afterwards, it determines the conformity of ongoing peri-urban practices with Dhaka’s stipulated planning documents. Then, it identifies Dhaka’s specific vulnerabilities to climate change impacts-i.e., flood, and groundwater table depletion. Lastly, it maps out the socioeconomic profile of the climate change victim groups from Dhaka. The findings of the study reveal that: (a) Dhaka lacks adequate development planning, monitoring, and control mechanisms that lead to an increased and uncontrolled peri-urbanization; (b) Dhaka’s explicitly undefined peri-urban growth boundary is the primary factor in misguiding the growth pockets-that are the most vulnerable locations to climate change impacts, and; (c) Dhaka’s most vulnerable group to the increasing climate change impacts are the climate migrants, who have been repeatedly exposed to the climate change-triggered natural hazards. These study findings generate insights into peri-urbanization-triggered climate change vulnerabilities that aid urban policymakers, managers, and planners in their development policy, planning, monitoring and control practices.
Urban heat island (UHI) is the best acknowledged climate-change related phenomenon also because it affects population health conditions in dense urban areas, even exacerbated during heat waves. While most of field studies are performed by means of permanent weather stations, this paper presents an intra-urban microclimate analysis through wearable sensing techniques for monitoring and characterizing granular peculiarities as perceived by urban pedestrians. The study is implemented in four areas of New York City presenting already mitigation techniques. These strategies are specifically analyzed from the pedestrians’ perspective, who may walk along parks and sidewalks, to better study real boundary conditions responsible for thermal perception, even in those areas where vehicles are not allowed. A novel cluster analysis procedure is then carried out to perform data-driven identification of urban microclimate peculiarities in relation to its morphology (e.g. urban canyons etc.). Results show a non-negligible dependency from urban configuration both in winter and in summer. Measurements in the high-packed district winter daytime show a drop off of 0.6 degrees C in air temperature close to small parks. The packed low-rise district presents highest values of CO2, with respect to the other monitored areas both in winter and in summer. The same areas are automatically recognized through the data-driven clustering process. The data-driven approach may be therefore successfully integrated into classic measurements to investigate UHI and heat stress in dense anthropized areas.
The negative effects of urban heat islands (UHIs) on citizens’ well-being and life quality are widely acknowledged, but they still represent critical challenges, particularly since urban population is predicted to rise to 60% of the world population by 2030. Computational models have become useful tools for addressing these challenges and investigating urban microclimate repercussions on citizens’ comfort and urban liveability. Despite that, humans typically remain absent from such models. This work bridges this gap, moving beyond purely thermodynamic Urban Canopy Models (UCMs) to highlight the importance of integrating even simplified pedestrians’ biophysics for comfort assessment. Human physiology parameterization is therefore introduced into the Princeton Urban Canopy Model (PUCM), which had been designed to investigate the effect of greenery and novel materials on the UHI. Human thermal comfort is assessed in terms of the skin temperature and then evaluated against the apparent temperature, a widely-used thermal comfort indicator. Different configurations of the same urban canyon are therefore tested to assess the effectiveness of cool materials and trees for human thermal comfort enhancement. Results show that cool skins in the canyon’s built environment lead to an air temperature reduction up to 1.92 K, but slightly worsen human comfort in terms of a warmer computed skin temperature by 0.27 K. The indirect effect of trees, that exclude shading, are negligible for human thermal comfort. The new integrated human-centric model can help policymakers and urban planners to easily assess the potential benefits or threats to citizens’ well-being associated with specific urban configurations.
INTRODUCTION: Hurricanes have increased in severity over the past 35 years, and climate change has led to an increased frequency of catastrophic flooding. The impact of floods on emergency department (ED) operations and patient health has not been well studied. We sought to detail challenges and lessons learned from the severe weather event caused by Hurricane Harvey in Houston, Texas, in August 2017. METHODS: This report combines narrative data from interviews with retrospective data on patient volumes, mode of arrival, and ED lengths of stay (LOS). We compared the five-week peri-storm period for the 2017 hurricane to similar periods in 2015 and 2016. RESULTS: For five days, flooding limited access to the hospital, with a consequent negative impact on provider staffing availability, disposition and transfer processes, and resource consumption. Interruption of patient transfer capabilities threatened patient safety, but flexibility of operations prevented poor outcomes. The total ED patient census for the study period decreased in 2017 (7062 patients) compared to 2015 (7665 patients) and 2016 (7770) patients). Over the five-week study period, the arrival-by-ambulance rate was 12.45% in 2017 compared to 10.1% in 2016 (p < 0.0001) and 13.7% in 2015 (p < 0.0001). The median ED length of stay (LOS) in minutes for admitted patients was 976 minutes in 2015 (p < 0.0001) compared to 723 minutes in 2016 and 591 in 2017 (p < 0.0001). For discharged patients, median ED LOS was 336 minutes in 2016 compared to 356 in 2015 (p < 0.0001) and 261 in 2017 (p < 0.0001). Median boarding time for admitted ED patients was 284 minutes in 2016 compared to 470 in 2015 (p < 0.0001) and 234.5 in 2017 (p < 0.001). Water damage resulted in a loss of 133 of 179 inpatient beds (74%). Rapid and dynamic ED process changes were made to share ED beds with admitted patients and to maximize transfers post-flooding to decrease ED boarding times. CONCLUSION: A number of pre-storm preparations could have allowed for smoother and safer ride-out functioning for both hospital personnel and patients. These measures include surplus provisioning of staff and supplies to account for limited facility access. During a disaster, innovative flexibility of both ED and hospital operations may be critical when disposition and transfer capibilities or bedding capacity are compromised.
Background: There is a lack of knowledge concerning the effects of ambient heat exposure on morbidity in Northern Europe. Therefore, this study aimed to evaluate the relationships of daily summertime temperature and heatwaves with cardiorespiratory hospital admissions in the Helsinki metropolitan area, Finland. Methods: Time series models adjusted for potential confounders, such as air pollution, were used to investigate the associations of daily temperature and heatwaves with cause-specific cardiorespiratory hospital admissions during summer months of 2001-2017. Daily number of hospitalizations was obtained from the national hospital discharge register and weather information from the Finnish Meteorological Institute. Results: Increased daily temperature was associated with a decreased risk of total respiratory hospital admissions and asthma. Heatwave days were associated with 20.5% (95% CI: 6.9, 35.9) increased risk of pneumonia admissions and during long or intense heatwaves also with total respiratory admissions in the oldest age group (?75 years). There were also suggestive positive associations between heatwave days and admissions due to myocardial infarction and cerebrovascular diseases. In contrast, risk of arrhythmia admissions decreased 20.8% (95% CI: 8.0, 31.8) during heatwaves. Conclusions: Heatwaves, rather than single hot days, are a health threat affecting morbidity even in a Northern climate.
Temperature record-breaking events, such as the observed more intense, longer-lasting, and more frequent heat waves, pose a new global challenge to health sectors worldwide. These threats are of particular interest in low-income regions with limited investments in public health and a growing urban population, such as Brazil. Here, we apply a comprehensive interdisciplinary climate-health approach, including meteorological data and a daily mortality record from the Brazilian Health System from 2000 to 2015, covering 21 cities over the Metropolitan Region of Rio de Janeiro. The percentage of absolute mortality increase due to summer extreme temperatures is estimated using a negative binomial regression modeling approach and maximum/minimum temperature-derived indexes as covariates. Moreover, this study assesses the vulnerability to thermal stress for different age groups and both genders and thoroughly analyzes four extremely intense heat waves during 2010 and 2012 regarding their impacts on the population. Results showed that the highest absolute mortality values during heat-related events were linked to circulatory illnesses. However, the highest excess of mortality was related to diabetes, particularly for women within the elderly age groups. Moreover, results indicate that accumulated heat stress conditions during consecutive days preferentially preceded by persistent periods of moderate-temperature, lead to higher excess mortality rather than sporadic single hot days. This work may provide directions in human health policies related to extreme climate events in large tropical metropolitan areas from developing countries, contributing to altering the historically based purely reactive response.
Assessing heatwave-induced human health risk is of critical importance in order to mitigate hazards caused by extreme environmental events. Air temperature or land surface temperature in previous studies was often used to characterize the severity of heatwaves, and human perception of the thermal environment was neglected as a key component in the heatwave-induced risk assessment. In order to redress this issue, in this study we applied the Universal Thermal Climate Index (UTCI) to represent human thermal comfort perception and embedded the measure within an assessment framework of heat stress-social vulnerability-human exposure. The heatwave-induced human health risk was then evaluated in Wuhan City, China across 177 blocks covering the entire city area and local risk governance measures were also explored based on risk zoning. The results showed that spatial patterns of heatwave-induced human health risk followed a decreasing trend from the city center towards the surrounding areas, with the average risk of the main urban area being 1.6 times that beyond the metropolitan development area. Through the heatwave-induced human health risk zoning, about 73.45% of the 177 blocks in Wuhan City demonstrated a positive relationship between heat stress and human exposure, and both were opposite with social vulnerability. Multiple linear regression between UTCI and the proportion of greenspace, water body and construction land indicated that, more blue or green infrastructure should be integrated within the urban fabric to help mitigate heat stress particularly in the main urban area, while in the metropolitan development area construction land dominating heat stress should be strictly regulated. Furthermore, protecting vulnerable groups such as left-behind children and elderly people should be a priority in rural areas that were generally associated with higher levels of social vulnerability. This study proposed a new heatwave-induced human health risk framework with a local evidence in Wuhan City, and further emphasized that risk zoning could be used as a basic yet important approach to facilitating more effective urban planning guidelines for risk governance.
Studies on the pattern of heatwave mortality using nationwide data that include rural areas are limited. This study aimed to assess the risk of heatwave-related mortality and evaluate the health risk-based definition of heatwave. We collected data on daily temperature and mortality from 229 districts in South Korea in 2011-2017. District-specific heatwave-related mortality risks were calculated using a distributed lag model. The estimates were pooled in the total areas and for each urban and rural area using meta-regression. In the total areas, the threshold point of heatwave mortality risk was estimated at the 93rd percentile of temperature, and it was lower in urban areas than in rural areas (92nd percentile vs. 95th percentile). The maximum risk of heatwave-related mortality in the total area was 1.11 (95% CI: 1.01-1.22), and it was slightly greater in rural areas than in the urban areas (RR: 1.23, 95% CI: 0.99-1.53 vs. RR: 1.10, 95% CI: 1.01-1.20). The results differ by age- and cause-specific deaths. In conclusion, the patterns of heatwave-related mortality risk vary by area and sub-population in Korea. Thus, more target-specific heatwave definitions and action plans should be established according to different areas and populations.
Diarrheal diseases remain a significant contributor to the global burden of disease. Climate change may increase their incidence by altering the epidemiology of waterborne pathogens through changes in rainfall patterns. To assess potential impacts of future changes in rainfall patterns, we analyzed 33,927 cases of diarrhea across all Ministry of Health clinical facilities in Esmeraldas Province, Ecuador, for a 24-month period from 2013 to 2014, using mixed-effects Poisson regression. We assessed the association between the incidence of diarrheal diseases and heavy rainfall events (HREs) and antecedent rainfall conditions. In rural areas, we found no significant associations between HREs and incidence. In urban areas, dry antecedent conditions were associated with higher incidence than wet conditions. In addition, HREs with dry antecedent conditions were associated with elevated incidence by up to 1.35 (incidence rate ratio, 95% CI: 1.14-1.60) times compared with similar conditions without HREs. These patterns may be driven by accumulation of fecal contamination during dry periods, followed by a flushing effect during HREs. This phenomenon is more important in dense urban environments with more impervious surfaces. These findings suggest that projected increases in rainfall variability and HREs may increase diarrhea burden in urban regions, which are rapidly expanding globally.
Cities must adapt to aging populations and mitigate the effects of climate change and urbanization on health. This study analyses the outdoor thermal and acoustic comfort of older adults in public spaces in Madrid. We compared the subjective perception with real environmental conditions measured in-situ and two thermal comfort indices Physiological Equivalent Temperature (PET) and Universal Thermal Index (UTCI). Additionally, use and stay of older people in those public spaces was assessed. Results showed that older adults represent 26.35% of the users, environmental variables such as mean radiant temperature, air temperature, and noise levels are the most relevant variables for them to decide to stay in these places. Although most of the 413 interviewees perceived the environment as comfortable, this research shows that in dense urban areas there is a significant health risk due to noise pollution and extreme temperatures. Average noise levels measured exceed the maximum threshold recommended by the World Health Organization and according to PET and UTCI indices around 73% of the interviewees would be in risk of thermal stress in winter and 98.2% in summer. The need for further research to find strategies to mitigate the environmental risks of older people in public spaces is evident.
Global warming with increasing weather extremes, like heat events, is enhancing impacts to public health. This essay focuses on unusual extreme summer heat extremes occurring in Germany at higher frequency, longer duration, and with new temperature records. Large areas of the country are affected, particularly urban settlements, where about 77% of the population lives, which are exposed to multiple inner-city threats, such as urban heat islands. Because harm to public health is directly released by high ambient air temperatures, local and national studies on heat-related morbidity and mortality indicate that vulnerable groups such as the elderly population are predominantly threatened with heat-related health problems. After the severe mortality impacts of the extreme summer heat 2003 in Europe, in 2008, Germany took up the National Adaptation Strategy on Climate Change to tackle and manage the impacts of weather extremes, for example to protect people’s health against heat. Public health systems and services need to be better prepared to improve resilience to the effects of extreme heat events, e.g., by implementing heat health action plans. Both climate protection as well as adaptation are necessary in order to be able to respond as adequate as possible to the challenges posed by climate change.
More than half of the world’s population currently live in urban areas and are particularly at risk from the combined effects of the urban heat island phenomenon and heat increases due to climate change. Here, by using remotely sensed surface temperature data and social-ecological indicators, focusing on the hot dry season, and applying the risk framework of the Intergovernmental Panel on Climate Change, we assessed the current heat health risk in 139 Philippine cities, which account for about 40% of the country’s total population. The cities at high or very high risk are found in Metro Manila, where levels of heat hazard and exposure are high. The most vulnerable cities are, however, found mainly outside the national capital region, where sensitivity is higher and capacity to cope and adapt is lower. Cities with high levels of heat vulnerability and exposure must be prioritized for adaptation. Our results will contribute to risk profiling in the Philippines and to the understanding of city-level heat health risks in developing regions of the Asia-Pacific.
BACKGROUND: Summer temperatures are expected to increase and heat waves will occur more frequently, be longer, and be more intense as a result of global warming. A growing body of evidence indicates that increasing temperature and heatwaves are associated with excess mortality and therefore global heating may become a major public health threat. However, the heat-mortality relationship has been shown to be location-specific and differences could largely be explained by the most frequent temperature. So far, in Belgium there is little known regarding the heat-mortality relationship in the different urban areas. OBJECTIVES: The objective of this study is to assess the heat-mortality relationship in the two largest urban areas in Belgium, i.e. Antwerp and Brussels for the warm seasons from 2002 until 2011 taking into account the effect of air pollution. METHODS: The threshold in temperature above which mortality increases was determined using segmented regressions for both urban areas. The relationship between daily temperature and mortality above the threshold was investigated using a generalized estimated equation with Poisson distribution to finally determine the percentage of deaths attributable to the effect of heat. RESULTS: Although only 50 km apart, the heat-mortality curves for the two urban areas are different. More specifically, an increase in mortality occurs above a maximum temperature of 25.2 °C in Antwerp and 22.8 °C in Brussels. We estimated that above these thresholds, there is an increase in mortality of 4.9% per 1 °C in Antwerp and of 3.1% in Brussels. During the study period, 1.5% of the deaths in Antwerp and 3.5% of the deaths in Brussels can be attributed to the effect of heat. The thresholds differed considerably from the most frequent temperature, particularly in Antwerp. Adjustment for air pollution attenuated the effect of temperature on mortality and this attenuation was more pronounced when adjusting for ambient ozone. CONCLUSION: Our results show a significant effect of temperature on mortality above a city-specific threshold, both in Antwerp and in Brussels. These findings are important given the ongoing global warming. Recurrent, intense and longer episodes of high temperature and expected changes in air pollutant levels will have an important impact on health in urban areas.
There is an urgent need to map the geographic location of climate change risks and vulnerability, especially for cities in sub-Saharan Africa, which are experiencing the greatest urban development challenges and vulnerability to climate change impacts. The aim of this study is to investigate current and projected future heat risk, expressed as a heat stress exposure index using high-resolution climate change projections, and a social vulnerability index, to identify areas of potential future heat stress risk in the Durban (eThekwini) metropolitan area, South Africa. Additionally, this is the first study to use high-resolution downscaled climate change projections under Representative Concentration (RCP) 8.5, to construct the heat exposure index using apparent temperature and increases in minimum temperature and a social vulnerability index, using demographic and socio-economic census and land use data to, derived from principal component analysis (PCA) to spatially characterize heat stress within a South African city. Results show that while heat stress is not a current concern, it is projected to increase and become a future concern, mainly as a function of social vulnerability due to household demographic and infrastructural characteristics, and will be experienced in both the rural and inner-city areas of the metro. This study contributes a heat risk framework to identify locations for specific research and adaptation activities on heat stress risk and for urban planning in sub-Saharan African cities, which are characterized by both rural and urban contexts, to address climate change adaptation targeting and priority setting.
Heat waves are the deadliest type of natural hazard among all weather extremes in the United States. Given the observed and anticipated increase in heat risks associated with ongoing climate change, this study examines community vulnerability to extreme heat and the degree to which heat island mitigation (HIM) actions by state/local governments reduce heat-induced fatalities. The analysis uses all heat events that occurred over the 1996-2011 period for all United States counties to model heat vulnerability. Results show that: (1) Higher income reduces extreme heat vulnerability, while poverty intensifies it; (2) living in mobile homes or rental homes heightens susceptibility to extreme heat; (3) increased heat vulnerability due to the growth of the elderly population is predicted to result in a two-fold increase in heat-related fatalities by 2030; and (4) community heat island mitigation measures reduce heat intensities and thus heat-related fatalities. Findings also show that an additional locally implemented measure reduces the annual death rate by 15%. A falsification test rules out the possibility of spurious inference on the life-saving role of heat island mitigation measures. Overall, these findings inform efforts to protect the most vulnerable population subgroups and guide future policies to counteract the growing risk of deadly heat waves.
The Metropolitan Region of Sao Paulo (MRSP) is one of the main regions of Brazil that in recent years has shown an increase in the number of days with heat waves, mainly affecting the health of the most sensitive populations, such as the elderly. In this study, we identified the heat waves in the MRSP using three different definitions regarding the maximum daily temperature threshold. To analyze the impact of heat waves on elderly mortality, we used distributed lag nonlinear models (dlnm) and we quantified the heat wave-related excess mortality of elderly people from 1985 to 2005 and made projections for the near future (2030 to 2050) and the distant future (2079-2099) under the climate change scenarios RCP4.5 and RCP8.5 (RCP: Representative Concentration Paths). An important aspect of this research is that for the projections we take into account two assumptions: non-adaptation and adaptation to the future climate. Our projections show that the heat wave-related excess of elderly mortality will increase in the future, being highest when we consider no adaptation, mainly from cardiovascular diseases in women (up to 587 deaths per 100,000 inhabitants per year). This study can be used for public policies to implement preventive and adaptive measures in the MRSP.
BACKGROUND: Although many studies have provided evidence for all-cause mortality attributed to extreme temperature across India, few studies have provided a systematic analysis of the association between all-cause mortality and temperature. OBJECTIVE: To estimate the risk associated with heat waves during two major heat waves of Nagpur occurred in 2010 and 2014. METHODS: The association between temperature and mortality was measured using a distributed lag non-linear model (DLNM) and the attributable deaths associated with the heat waves with forward perspective in the DLNM framework. RESULTS: From the ecological analysis, we found 580 and 306 additional deaths in 2010 and 2014, respectively. Moving average results also gave similar findings. DLNM results showed that the relative risk was 1.5 for the temperature above 45 °C; forward perspective analysis revealed that the attributable deaths during 2010 and 2014 were 505 and 376, respectively. Results from different methods showed that heat waves in different years had variable impacts for various reasons. However, all the results were consistent during 2010 and 2014; there were 30% and 14% extra-mortalities due to heat comparing to non-heat wave years. CONCLUSION: We strongly recommend the city Government to implement the action plans based on this research outcome to reduce the risk from the heat wave in future.
The Gulf of Mexico (GoM) region is prone to disasters, including recurrent oil spills, hurricanes, floods, industrial accidents, harmful algal blooms, and the current COVID-19 pandemic. The GoM and other regions of the U.S. lack sufficient baseline health information to identify, attribute, mitigate, and facilitate prevention of major health effects of disasters. Developing capacity to assess adverse human health consequences of future disasters requires establishment of a comprehensive, sustained community health observing system, similar to the extensive and well-established environmental observing systems. We propose a system that combines six levels of health data domains, beginning with three existing, national surveys and studies plus three new nested, longitudinal cohort studies. The latter are the unique and most important parts of the system and are focused on the coastal regions of the five GoM States. A statistically representative sample of participants is proposed for the new cohort studies, stratified to ensure proportional inclusion of urban and rural populations and with additional recruitment as necessary to enroll participants from particularly vulnerable or under-represented groups. Secondary data sources such as syndromic surveillance systems, electronic health records, national community surveys, environmental exposure databases, social media, and remote sensing will inform and augment the collection of primary data. Primary data sources will include participant-provided information via questionnaires, clinical measures of mental and physical health, acquisition of biological specimens, and wearable health monitoring devices. A suite of biomarkers may be derived from biological specimens for use in health assessments, including calculation of allostatic load, a measure of cumulative stress. The framework also addresses data management and sharing, participant retention, and system governance. The observing system is designed to continue indefinitely to ensure that essential pre-, during-, and post-disaster health data are collected and maintained. It could also provide a model/vehicle for effective health observation related to infectious disease pandemics such as COVID-19. To our knowledge, there is no comprehensive, disaster-focused health observing system such as the one proposed here currently in existence or planned elsewhere. Significant strengths of the GoM Community Health Observing System (CHOS) are its longitudinal cohorts and ability to adapt rapidly as needs arise and new technologies develop.
Wildfires have a significant adverse impact on air quality in the United States (US). To understand the potential health impacts of wildfire smoke, many epidemiology studies rely on concentrations of fine particulate matter (PM) as a smoke tracer. However, there are many gas-phase hazardous air pollutants (HAPs) identified by the Environmental Protection Agency (EPA) that are also present in wildfire smoke plumes. Using observations from the Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption, and Nitrogen (WE-CAN), a 2018 aircraft-based field campaign that measured HAPs and PM in western US wildfire smoke plumes, we identify the relationships between HAPs and associated health risks, PM, and smoke age. We find the ratios between acute, chronic noncancer, and chronic cancer HAPs health risk and PM in smoke decrease as a function of smoke age by up to 72% from fresh (<1 day of aging) to old (>3 days of aging) smoke. We show that acrolein, formaldehyde, benzene, and hydrogen cyanide are the dominant contributors to gas-phase HAPs risk in smoke plumes. Finally, we use ratios of HAPs to PM along with annual average smoke-specific PM to estimate current and potential future smoke HAPs risks.
Accounting for only a limited fraction of Earth’s land surface, urban areas accommodate more than half the global population. The projected increasing severe heat waves with global warming exert a profound threat to the dense urban population and infrastructure. Despite abundant past studies on heat waves, there was a lack of attention to the daytime-nighttime compound heat waves. Here, we categorize summertime heat waves into three distinct types, that is, independent daytime or nighttime heat waves and compound heat waves. Using a universal heat wave metric, we identify the strongest compound heat waves on record (1961-2015) in three vast urban agglomerations in China. We demonstrate substantial increase of the land areas affected by severe compound heat waves over the past three decades. We further quantify the changes in areal and population exposures to future unprecedented compound heat waves. Our results show that under a high-end emission scenario, 50% (100%) of the land area in the Beijing-Tianjin-Hebei region, the Yangtze River Delta, and the Pearl River Delta will be exposed to historically unprecedented compound heat waves on a regular basis by 2050 (2090), 2050 (2070), and 2030 (2050), respectively. Such enhancing heat hazard will induce increasing population exposure of nearly 70, 90, and 60 million to unprecedented compound heat waves by the end of this century (relative to the 2010s). Our findings call for effective mitigation and adaptation strategies to alleviate the risks of unprecedented compound heat waves in rapidly developing populous urban areas. Plain Language Summary Extreme heat waves impose devastating impacts on human health, economy, and the environment. The risk of extreme heat stress tends to be higher in urban areas than in surroundings, due to greater population exposure and added heat stress from urban heat island. Compared to daytime- or nighttime-only heat waves, the risk of compound heat waves that combine scorching days and sweltering nights sequentially tends to be higher. Focusing on top three populous urban agglomerations in China, this study dissects summertime heat waves into three nonoverlapping types and identifies the strongest heat waves on record based on a universal metric of heat wave magnitude. Projections show that unprecedented compound heat waves will become the norm since around 2045 (2060), 2045 (2065), and 2030 (2040) in the Beijing-Tianjin-Hebei region, the Yangtze River Delta, and the Pearl River Delta, respectively, under RCP8.5 (RCP4.5) emission scenario. Enhancing heat hazards will translate into increasing population exposure of about 70, 90, and 60 million to unprecedented compound heat waves by the end of this century, which are concentrated on the highly urbanized areas, such as Beijing, Shanghai, Guangzhou, and Shenzhen. This study highlights the urgent adaptation and mitigation efforts for cities against compound heat waves in particular.
Urban areas are increasingly impacted by the urban heat island effect, especially during heat waves. In the context of improving energy efficiency in buildings, passive and energy-efficient cooling methods are needed for reducing indoor heat stress and lowering building energy consumption during heat waves. In this study, a whole building simulation model that includes both moisture and heat transport in wall envelopes and indoor environment is developed. An analytical solution and two test cases are used to validate the developed model. The developed model is applied to study indoor thermal conditions in urban areas in Zurich, Switzerland in a hot summer. The results show that indoor temperature could not be accurately simulated when moisture transport in the wall envelopes is neglected. Due to the urban heat island effect, night ventilation is not sufficient to cool down the indoor environment during the heat wave in the urban area. The potential of precooling before the heat wave and moisture-desorption cooling from hygroscopic materials have been studied to reduce indoor heat stress in the urban area. The average operative temperature during the heat wave can be reduced by 0.43 degrees C by precooling before the start of the heat wave, whereas desorption cooling from hygroscopic materials could reduce the average operative temperature during heat waves by 1.31 degrees C. A combination of these two mitigation measures could lead to enhanced passive cooling effect. There is a large potential of using desorption of hygroscopic material to reduce heat stress during heatwaves, while minimizing energy consumption of buildings.
BACKGROUND: As a mosquito-borne infectious disease, dengue fever (DF) has spread through tropical and subtropical regions worldwide in recent decades. Dengue forecasting is essential for enhancing the effectiveness of preventive measures. Current studies have been primarily conducted at national, sub-national, and city levels, while an intra-urban dengue forecasting at a fine spatial resolution still remains a challenging feat. As viruses spread rapidly because of a highly dynamic population flow, integrating spatial interactions of human movements between regions would be potentially beneficial for intra-urban dengue forecasting. METHODOLOGY: In this study, a new framework for enhancing intra-urban dengue forecasting was developed by integrating the spatial interactions between urban regions. First, a graph-embedding technique called Node2Vec was employed to learn the embeddings (in the form of an N-dimensional real-valued vector) of the regions from their population flow network. As strongly interacting regions would have more similar embeddings, the embeddings can serve as “interaction features.” Then, the interaction features were combined with those commonly used features (e.g., temperature, rainfall, and population) to enhance the supervised learning-based dengue forecasting models at a fine-grained intra-urban scale. RESULTS: The performance of forecasting models (i.e., SVM, LASSO, and ANN) integrated with and without interaction features was tested and compared on township-level dengue forecasting in Guangzhou, the most threatened sub-tropical city in China. Results showed that models using both common and interaction features can achieve better performance than that using common features alone. CONCLUSIONS: The proposed approach for incorporating spatial interactions of human movements using graph-embedding technique is effective, which can help enhance fine-grained intra-urban dengue forecasting.
Construction materials and systems for the thermal building envelope have played a key role in the improvement of energy efficiency in buildings. Urban heat islands together with the upcoming rising global temperature demand construction solutions that are adapted to the specific microclimate conditions. These circumstances are even more dramatic in the case of healthcare buildings where the need to preserve constant indoor temperatures is a priority for the proper recovery of patients. A new neonatal hospital, located in Madrid (Spain), has been monitored, and building energy simulations were performed to evaluate the effect of the building envelope on the energy demand. Based on the simulation results, the design of the building envelope was found to be insufficiently optimised to properly protect the building from the external heat flow. This is supported by the monitored results of the indoor temperatures, which went over the standard limit for about 50% of the hours, achieving up to 27 degrees C in June and July, and 28 degrees C in August. The results showed, on one hand, that solar radiation gains transmitted through the facade have an important impact on the indoor temperature in the analysed rooms. Heat gains through the opaque envelope showed an average of 8.37 kWh/day, followed by heat gains through the glazing with an average value of 5.29 kWh/day; while heat gains from lighting and occupancy were 5.21 kWh/day and 4.47 kWh/day, respectively. Moreover, it was shown that a design of the envelope characterised by large glass surfaces and without solar protection systems, resulted in excessive internal thermal loads that the conditioning system was not able to overcome.
Thermal comfort is an important determinant of quality of life and economic vitality in cities. Strategies to improve thermal comfort may become a more critical part of urban sustainability efforts with projections of continued urban growth and climate change. A case study was performed in the hot, dry summertime climate of Tempe, Arizona to quantify the influence of evaporative misters on the thermal environment in outdoor restaurants and to understand business managers’ motivations to use misters. Microclimate measurements (air temperature (T(a)), wind speed, relative humidity, globe temperature) were taken at five restaurants midday within four exposures: misted sun, misted shade, sun only, and shade only. We assessed T(a), mean radiant temperature (MRT), universal thermal climate index (UTCI), and physiological equivalent temperature (PET) between these four conditions within each location. Misters improved thermal comfort across all days, sites, and exposure conditions. MRT was on average 7.6 °C lower in misted locations, which significantly lowered average PET (- 6.5 °C) and UTCI (- 4.4 °C) (p < 0.05). Thermal comfort was most improved using mist in combination with shade. Under such conditions, PET and UTCI were reduced by 15.5 °C and 9.7 °C (p < 0.05), respectively. Business managers identified customer comfort and increased seating capacity as the principal factors for mister use. Esthetics of misters further encouraged use, while cost and environmental concerns were perceived to be less important. While this case study demonstrates value in outdoor misting in a hot, dry climate, additional work is needed to more fully evaluate tradeoffs between cost, water use, and comfort with continuing urban growth.
BACKGROUND: Climate change may contribute to higher incidence and wider geographic spread of vector borne diseases (VBDs). Effective monitoring and surveillance of VBDs is of paramount importance for the prevention of and timely response to outbreaks. Although international regulations exist to support this, barriers and operational challenges within countries hamper efficient monitoring. As a first step to optimise VBD surveillance and monitoring, it is important to gain a deeper understanding of system characteristics and experiences in to date non-endemic regions at risk of becoming endemic in the future. Therefore, this study qualitatively analyses the nature and flexibility of VBD surveillance and response in Beijing. METHODS: In this qualitative study, eleven experts working in Beijing’s vector-borne diseases surveillance and response system were interviewed about vector-borne disease surveillance, early warning, response, and strengths and weaknesses of the current approach. RESULTS: Vector-borne disease surveillance occurs using passive syndromic surveillance and separate vector surveillance. Public health authorities use internet reporting networks to determine vector-borne disease risk across Beijing. Response toward a vector-borne disease outbreak is uncommon in this setting due to the currently low occurrence of outbreaks. CONCLUSIONS: A robust network of centralised institutions provides the continuity and flexibility needed to adapt and manage possible vector-borne disease threats. Opportunities exist for population-based health promotion and the integration of environment and climate monitoring in vector-borne disease surveillance.
Background: Determination of the key factors affecting dengue occurrence is of significant importance for the successful response to its outbreak. Yunnan and Guangdong Provinces in China are hotspots of dengue outbreak during recent years. However, few studies focused on the drive of multi-dimensional factors on dengue occurrence failing to consider the possible multicollinearity of the studied factors, which may bias the results. Methods: In this study, multiple linear regression analysis was utilized to explore the effect of multicollinearity among dengue occurrences and related natural and social factors. A principal component regression (PCR) analysis was utilized to determine the key dengue-driven factors in Guangzhou city of Guangdong Province and Xishuangbanna prefecture of Yunnan Province, respectively. Results: The effect of multicollinearity existed in both Guangzhou city and Xishuangbanna prefecture, respectively. PCR model revealed that the top three contributing factors to dengue occurrence in Guangzhou were Breteau Index (BI) (positive correlation), the number of imported dengue cases lagged by 1 month (positive correlation), and monthly average of maximum temperature lagged by 1 month (negative correlation). In contrast, the top three factors contributing to dengue occurrence in Xishuangbanna included monthly average of minimum temperature lagged by 1 month (positive correlation), monthly average of maximum temperature (positive correlation), monthly average of relative humidity (positive correlation), respectively. Conclusion: Meteorological factors presented stronger impacts on dengue occurrence in Xishuangbanna, Yunnan, while BI and the number of imported cases lagged by 1 month played important roles on dengue transmission in Guangzhou, Guangdong. Our findings could help to facilitate the formulation of tailored dengue response mechanism in representative areas of China in the future.
Floods are acknowledged as one of the most serious threats to people’s lives and properties worldwide. To mitigate the flood risk, it is possible to act separately on its components: hazard, vulnerability, exposure. Emergency management plans can actually provide effective nonstructural practices to decrease both human exposure and vulnerability. Crowding maps depending on characteristic time patterns, herein referred to as dynamic exposure maps, represent a valuable tool to enhance the flood risk management plans. In this paper, the suitability of mobile phone data to derive crowding maps is discussed. A test case is provided by a strongly urbanized area subject to frequent flooding located on the western outskirts of Brescia (northern Italy). Characteristic exposure spatiotemporal patterns and their uncertainties were detected with regard to land cover and calendar period. This novel methodology still deserves verification during real-world flood episodes, even though it appears to be more reliable than crowdsourcing strategies, and seems to have potential to better address real-time rescues and relief supplies.
The effectiveness of urban hydrological processes in mitigating the urban heat island (UHI) effect and human thermal stress in the megacity of Nanjing during an extreme heat wave event (6th-10th August 2013) was assessed using Weather Research and Forecasting Single-Layer Urban Canopy Models. The inclusion of urban hydrological processes improved model performance, with more reasonable diurnal cycles and smaller mean errors, root mean square errors, and normalized root mean square errors for meteorological variables. Through evaporative cooling, urban hydrological processes can greatly increase specific and relative humidity, while reducing near-surface and surface temperatures, wind speed, and planetary boundary layer (PBL) height, and the cooling and wetting effects could affect the entire PBL, especially in low-intensity residential areas. Urban hydrological processes can effectively mitigate both the near-surface and surface UHI effect. The city-wide mitigation effectiveness of near-surface UHI ranged between 0.9 degrees C and 1.1 degrees C throughout the day, while the city-wide mitigation effectiveness of surface UHI at noon reached similar to 5 degrees C. The maximum reduction of near-surface and surface UHI in low-intensity residential areas reached 1.3 degrees C and 10.0 degrees C, respectively. Changes in heat stress indices indicate that the cooling effect improves human thermal comfort at night, while the increased humidity outweighs the cooling effect and exacerbates human thermal discomfort during daytime. The city-wide thermal stress increased by up to 0.4 degrees C, 0.2 degrees C, and 0.5 degrees C during daytime and decreased by up to 0.4 degrees C, 0.3 degrees C, and 0.6 degrees C at night for wet-bulb globe temperature, apparent temperature, and humidity index, respectively.
Sri Lanka is experiencing various social and environmental challenges, including drought, storms, floods, and landslides, due to climate change. One of Sri Lanka’s biggest cities, Kurunegala, is a densely populated city that is gradually turning into an economic revitalization area. This fast-growing city needs to establish an integrated urban plan that takes into account the risks of climate change. Thus, a climate change risk assessment was conducted for both the water and heat wave risks via discussions with key stakeholders. The risk assessment was conducted as a survey based on expert assessment of local conditions, with awareness surveys taken by residents, especially women. The assessment determined that the lack of drinking water was the biggest issue, a problem that has become more serious due to recent droughts caused by climate change and insufficient water management. In addition, the outbreak of diseases caused by heat waves was identified as a serious concern. Risk assessment is integral to developing an action plan for minimizing the damage from climate change. It is necessary to support education and awareness in developing countries so that they can perform risk assessment well and develop both problem-solving and policy-making abilities to adapt to a changing climate.
Climatic variability affects many underlying determinants of child malnutrition, including food availability, access, and utilization. Evidence of the effects of changing temperatures and precipitation on children’s nutritional status nonetheless remains limited. Research addressing this knowledge gap is merited given the shortand long-run consequences of malnutrition. We address this issue by estimating the effects of temperature and precipitation anomalies on the weight and wasting status of children ages 0-59 months across 18 countries in sub-Saharan Africa. Linear regression models show that high temperatures and low precipitation are associated with reductions in child weight, and that high temperatures also lead to increased risk of wasting. We find little evidence of substantively meaningful differences in these effects across sub-populations of interest. Our results underscore the vulnerability of young children to climatic variability and its second-order economic and epidemiological effects. The study also highlights the corresponding need to design and assess interventions to effectively mitigate these impacts.
Air pollution regulation requires knowing major sources on any given zone, setting specific controls, and assessing how health risks evolve in response to those controls. Receptor models (RM) can identify major sources: transport, industry, residential, etc. However, RM results are typically available for short term periods, and there is a paucity of RM results for developing countries. We propose to combine a cluster analysis (CA) of air pollution and meteorological measurements with a short-term RM analysis to estimate a long-term, hourly source apportionment of ambient PM(2.5) and PM(10). We have developed a proof of the concept for this proposed methodology in three case studies: a large metropolitan zone, a city with dominant residential wood burning (RWB) emissions, and a city in the middle of a desert region. We have found it feasible to identify the major sources in the CA results and obtain hourly time series of their contributions, effectively extending short-term RM results to the whole ambient monitoring period. This methodology adds value to existing ambient data. The hourly time series results would allow researchers to apportion health benefits associated with specific air pollution regulations, estimate source-specific trends, improve emission inventories, and conduct environmental justice studies, among several potential applications.
Because of fast-paced industrialization, urbanization, and population growth in Indonesia, there are serious health issues in the country resulting from air pollution. This study uses geospatial modelling technologies, namely land-use regression (LUR), geographically weighted regression (GWR), and geographic and temporal weighted regression (GTWR) models, to assess variations in particulate matter (PM(10)) and nitrogen dioxide (NO(2)) concentrations in Surabaya City, Indonesia. This is the first study to implement spatiotemporal variability of air pollution concentrations in Surabaya City, Indonesia. To develop the prediction models, air pollution data collected from seven monitoring stations from 2010 to 2018 were used as dependent variables, while land-use/land cover allocations within a 250 m to 5000 m circular buffer range surrounding the monitoring stations were collected as independent variables. A supervised stepwise variable selection procedure was applied to identify the important predictor variables for developing the LUR, GWR, and GTWR models. The developed models of LUR, GWR, and GTWR accounted for 49%, 50%, and 51% of PM(10) variations and 46%, 47%, and 48% of NO(2) variations, respectively. The GTWR model performed better (R(2) = 0.51 for PM(10) and 0.48 for NO(2)) than the other two models (R(2) = 0.49-0.50 for PM(10) and 0.46-0.47 for NO(2)), LUR and GWR. In the PM(10) model four predictor variables, public facility, industry and warehousing, paddy field, and normalized difference vegetation index (NDVI), were selected during the variable selection procedure. Meanwhile, paddy field, residential area, rainfall, and temperature played important roles in explaining NO(2) variations. Because of biomass burning issues in South Asia, the paddy field, which has a positive correlation with PM(10) and NO(2), was selected as a predictor. By using long-term monitoring data to establish prediction models, this model may better depict PM(10) and NO(2) concentration variations within areas across Asia.
People are exposed to multiple stimuli in urban environments, but most studies have investigated the unimodal effect of thermal and visual conditions on human comfort perception. It remains unclear whether the cross-modal effect found in indoor multisensory studies applies to outdoor environments. To understand the cross-modal effect of thermal and visual conditions on outdoor comfort perception, we conducted a thermal comfort survey (n = 4304) in Guangzhou and Zhuhai (September 2018). We used the Universal Thermal Climate Index (UTCI) heat stress classification and sky conditions to stratify our results. The thermal sensation vote was positively correlated with sun sensation vote. There was a significant interaction between UTCI heat stress conditions and sunlight preference vote on thermal comfort vote. The sun sensation (brightness) and sunlight preference vote had a cross-modal effect on thermal sensation and thermal comfort vote under various UTCI heat stress conditions. Under extreme heat stress, respondents’ thermal sensation did not differ significantly between different sun sensation and sunlight preference groups. Thermal sensation, preference and comfort vote had a cross-modal effect on sun sensation and sunlight preference under different sky conditions. Under partly cloudy conditions, sun sensation did not differ significantly between certain thermal sensation and preference groups. A theoretical framework is provided to explain the cross-modal effect between thermal and visual perception. Our findings suggest outdoor thermal discomfort can be alleviated by improving visual comfort and vice versa. Therefore, urban design should consider the combined effect of visual-thermal stimulants in optimizing overall pedestrian comfort and promoting urban liveability.
This paper investigates the problems and stresses of the contemporary city, mainly due to natural and health factors, related to climate change and the pandemic COVID19. Besides highlighting the characteristics of climate change and the ongoing pandemic, this study focuses on the analysis of the main effects and consequences that these phenomena have produced on the city and the vulnerabilities of the urban system. To understand how these events have impacted the urban environment, directly and indirectly, this research undertakes to define some specific indicators capable of comparing the phenomena and assessing their repercussions. The Methodology is based on the following focal points: on the analysis of the urban shocks that have affected the cities in the last decade, on the comparison between contemporary survey data and those relating to historical trends, on the definition of the main urban sectors particularly affected by the onset of urban shocks, and on the definition of strategies, actions, and tools deemed to be effective in the implementation of a post-pandemic and climate-proof city. These results were achieved through complementary urban design and tools capable of creating a post-pandemic and climate-proof adaptive city, within a cross-disciplinary approach.
The shift towards the new paradigm, that is, the “ecological and humanistic” paradigm, introduced by the United Nations in the Agenda 2030, and the current period of health emergency due to COVID-19 place the human dimension at the centre of the development strategies for our cities. The humanistic dimension, in particular, is related to human wellbeing, health and living conditions. The health and wellbeing of citizens depend on factors and actions that go beyond the health sector. In particular, here, the attention is focused on the negative impacts produced by pollution and climate change, issues that concern (and that are closely related to) most urban agglomerations in the world. The pandemic due to COVID-19 has highlighted the close relationship existing among social, natural and economic systems. Each system is interdependent on the other. Thus, the pandemic has boosted the necessity to accelerate efforts to address climate change. Therefore, in this framework, new urban development models are required. The circular economy model is proposed as a model able to reduce the negative impacts of urban transformations. The attention is then focused on implementation tools for improving decision-making processes and, in particular, on the evaluation tools for assessing the multidimensional impacts of urbanisation on human health.
Overheating in residential building is a challenging problem that causes thermal discomfort, productivity reduction, and health problems. This paper aims to assess the climate change impact on thermal comfort in a Belgian reference case. The case study represents a nearly zero energy building that operates without active cooling during summer. The study quantifies the impact of climate change on overheating risks using three representative concentration pathway (RCP) trajectories for greenhouse gas concentration adopted by the Intergovernmental Panel on Climate Change (IPCC). Building performance analysis is carried out using a multizone dynamic simulation program EnergyPlus. The results show that bioclimatic and thermal adaptation strategies, including adaptive thermal comfort models, cannot suppress the effect of global warming. By 2050, zero energy buildings will be vulnerable to overheating.
BACKGROUND: Dengue, a febrile illness, is caused by a Flavivirus transmitted by Aedes aegypti and Aedes albopictus mosquitoes. Climate influences the ecology of the vectors. We aimed to identify the influence of climatic variability on the occurrence of clinical dengue requiring hospitalization in Zone-5, a high incidence area of Dhaka City Corporation (DCC), Bangladesh. METHODS AND FINDINGS: We retrospectively identified clinical dengue cases hospitalized from Zone-5 of DCC between 2005 and 2009. We extracted records of the four major catchment hospitals of the study area. The Bangladesh Meteorological Department (BMD) provided data on temperature, rainfall, and humidity of DCC for the study period. We used autoregressive integrated moving average (ARIMA) models for the number of monthly dengue hospitalizations. We also modeled all the climatic variables using Poisson regression. During our study period, dengue occurred throughout the year in Zone-5 of DCC. The median number of hospitalized dengue cases was 9 per month. Dengue incidence increased sharply from June, and reached its peak in August. One additional rainy day per month increased dengue cases in the succeeding month by 6% (RR = 1.06, 95% CI: 1.04-1.09). CONCLUSIONS: Dengue is transmitted throughout the year in Zone-5 of DCC, with seasonal variation in incidence. The number of rainy days per month is significantly associated with dengue incidence in the subsequent month. Our study suggests the initiation of campaigns in DCC for controlling dengue and other Aedes mosquito borne diseases, including Chikunguniya from the month of May each year. BMD rainfall data may be used to determine campaign timing.
In today’s urban environments with complex design and configurations, heterogeneous spatial clusters of communities with different socioeconomic characteristics may result in disproportionate exposure of some groups of citizens to natural hazards. The objective of this study was to compare the associations between communities’ socioeconomic characteristics and exposure to different types of natural hazards in New York City (NYC) to examine whether commonly accepted indicators of social vulnerability are associated with similar levels of exposure across various natural hazards. First, we collected socioeconomic data (e.g., population, median income, unemployment rate) at a zip code level of granularity provided by the United States Census Bureau. Next, we identified and gathered spatial data for coastal storms, flooding, extreme heat, and pandemic disease in NYC. We then conducted a pairwise Kendall’s tau-b test to compare the associations. The outcomes showed that the significance and direction of the associations depend on the type of natural hazard. Particularly, the results indicated that zip codes with lower socioeconomic factors and greater percentage of minority ethnicities are exposed disproportionately to extreme heat and COVID-19. On the other hand, zip codes with higher percentage of areas prone to flooding have relatively higher socioeconomic factors. Furthermore, the results did not show any statistically significant association between socioeconomic factors and exposure to coastal storm inundations. The outcomes of this study will help decision makers design and implement better optimized and effective emergency preparedness plans by prioritizing their target areas based on socioeconomic factors in order to enhance social justice.
Future heat stress under six future global warming (Delta T-GW) scenarios (IPCCRCP8.5) in an Asian megacity (Osaka) is estimated using a regional climate model with an urban canopy and air-conditioning (AC). An urban heat ‘stress’ island is projected in all six scenarios (Delta T-GW = +0.5 to +3.0 degrees C in 0.5 degrees C steps). Under. TGW = +3.0 degrees C conditions, people outdoors experience ‘extreme’ heat stress, which could result in dangerously high increases in human body core temperature. AC-induced feedback increases heat stress roughly linearly as Delta T-GW increases, reaching 0.6 degrees C(or 12% of the heat stress increase). As this increase is similar to current possible heat island mitigation techniques, this feedback needs to be considered in urban climate projections, especially where AC use is large.
Indigenous Solomon Islanders, like many living in Pacific Small Island Developing States (PSIDS), are currently experiencing the global syndemic-the combined threat of obesity, undernutrition, and climate change. This mixed-method study aimed to assess nutrition transitions and diet quality by comparing three geographically unique rural and urban indigenous Solomon Islands populations. Participants in rural areas sourced more energy from wild and cultivated foods; consumed a wider diversity of foods; were more likely to meet WHO recommendations of >400g of non-starchy fruits and vegetables daily; were more physically active; and had significantly lower body fat, waist circumference, and body mass index (BMI) when compared to urban populations. Urban populations were found to have a reduced ability to self-cultivate agri-food products or collect wild foods, and therefore consumed more ultra-processed foods (classified as NOVA 4) and takeout foods, and overall had less diverse diets compared to rural populations. Clear opportunities to leverage traditional knowledge and improve the cultivation and consumption of underutilized species can assist in building more sustainable and resilient food systems while ensuring that indigenous knowledge and cultural preferences are respected.
Recurrent floods are severely affecting the built assets and people of numerous Indian cities. Urban flood being a comparatively nascent area of research is often dealt with strategies apt for other disasters. The conventional approach of hazard zonation lacks vital information on human vulnerability. This paper addresses this lacuna by identifying vulnerable population and their precise cause of vulnerability for a case study of the city of Guwahati. It is the largest urban and financial centre of north-east India, a disaster hotspot and exclusive link connecting the region and the mainland. Guwahati’s 31 municipal wards were gradedparallel for flood hazard and human vulnerability in five categories each (very high to very low). Analytic Hierarchy Process based survey with 16 domain experts and Geographic Information System were used for hazard mapping using factors causing urban flood grouped under environment and urbanization. For vulnerability mapping, questionnaire survey, based on the Human Development Index and other published disaster vulnerability indices, was carried out with 1023 citizens. For 38.70% cases, wards descended by one category from hazard grouping to vulnerability grouping i.e. a ward prone to flooding may not be perceived as equally vulnerable. A strong correlation of 73.5% validated this fact. For obtaining a holistic picture, the top-down approach from experts was tallied with its bottom-up counterpart of citizen’s observation. The knowledge will help in making focused policies and prioritize funds for development planning, that are critical for cities of developing countries which lack resources to tackle the growing wrath of urban floods.
Air pollution and the urban heat island effect are consistently linked to numerous respiratory and heat-related illnesses. Additionally, these stressors disproportionately impact low-income and historically marginalized communities due to their proximity to emissions sources, lack of access to green space, and exposure to other adverse environmental conditions. Here, we use relatively low-cost stationary sensors to analyze PM2.5 and temperature data throughout the city of Richmond, Virginia, on the ten hottest days of 2019. For both hourly means within the ten hottest days of 2019 and daily means for the entire record for the year, the temperature was found to exhibit a positive correlation with PM2.5. Analysis of hourly means on the ten hottest days yielded a diurnal pattern in which PM2.5 levels peaked in the early morning and reached their minima in the mid-afternoon. Spatially, sites exhibiting higher temperatures consistently had higher PM2.5 readings, with vulnerable communities in the east end and more intensely developed parts of the city experiencing significantly higher temperatures and PM2.5 concentrations than the suburban neighborhoods in the west end. These findings suggest an uneven distribution of air pollution in Richmond during extreme heat events that are similar in pattern but less pronounced than the temperature differences during these events, although further investigation is required to verify the extent of this relationship. As other studies have found both of these environmental stressors to correlate with the distribution of green space and other land-use factors in cities, innovative and sustainable planning decisions are crucial to the mitigation of these issues of inequity going forward.
BACKGROUND: Sedentary behavior is a worldwide public health concern. There is consistent and growing evidence linking sedentary behavior to mortality and morbidity. Early monitoring and assessment of environmental factors associated with sedentary behaviors at a young age are important initial steps for understanding children’s sedentary time and identifying pertinent interventions. OBJECTIVE: This study examines the association between daily temperature (maximum, mean, minimum, and diurnal variation) and all-day sedentary time among 4-6 year old children in Mexico City (n = 559) from the year 2013 to 2015. METHODS: We developed a spatiotemporally resolved hybrid satellite-based land use regression temperature model and calculated percent daily sedentary time from aggregating 10-second epoch vertical counts captured by accelerometers that participants wore for one week. We modeled generalized additive models (GAMs), one for each temperature type as a covariate (maximum, mean, minimum, and diurnal variation). All GAMs included percent all-day sedentary time as the outcome and participant-level random intercepts to account for repeated measures of sedentary time. Our models were adjusted for demographic factors and environmental exposures. RESULTS: Daily maximum temperature, mean temperature, and diurnal variation have significant negative linear relationships with all-day sedentary time (p<0.01). There is no significant association between daily minimum temperature and all-day sedentary time. Children have on average 0.26% less daily sedentary time (approximately 2.2 minutes) for each 1°C increase in ambient maximum temperature (range 7.1-30.2°C), 0.27% less daily sedentary time (approximately 2.3 minutes) for each 1°C increase in ambient mean temperature (range 4.3-22.2°C), and 0.23% less daily sedentary time (approximately 2.0 minutes) for each 1°C increase in diurnal variation (range 3.0-21.6°C). CONCLUSIONS: These results are contrary to our hypothesis in which we expected a curvilinear relationship between temperature (maximum, mean, minimum, and diurnal variation) and sedentary time. Our findings suggest that temperature is an important environmental factor that influences children’s sedentary behavior.
Following a distinct summer heat wave, nine autochthonous cases of West Nile fever and West Nile neuroinvasive disease, including one fatality, were observed in Leipzig, Germany, in August and September 2020. Phylogenetic analysis demonstrated close relationships in viruses from humans, animals and mosquitos in eastern Germany, obtained during the preceding 2 years. The described large cluster of autochthonous West Nile virus infections in Germany indicates endemic seasonal circulation of lineage 2 viruses in the area.
BACKGROUND: Despite the substantial role indoor exposure has played in heat wave-related mortality, few epidemiological studies have examined the health effects of exposure to indoor heat. As a result, knowledge gaps regarding indoor heat-health thresholds, vulnerability, and adaptive capacity persist. OBJECTIVE: We evaluated the role of indoor heat exposure on mortality and morbidity among the elderly ( ? 65?years of age) in Houston, Texas. METHODS: Mortality and emergency hospital admission data were obtained through the Texas Department of State Health Services. Summer indoor heat exposure was modeled at the U.S. Census block group (CBG) level using building energy models, outdoor weather data, and building characteristic data. Indoor heat-health associations were examined using time-stratified case-crossover models, controlling for temporal trends and meteorology, and matching on CBG of residence, year, month, and weekday of the adverse health event. Separate models were fitted for three indoor exposure metrics, for individual lag days 0-6, and for 3-d moving averages (lag 0-2). Effect measure modification was explored via stratification on individual- and area-level vulnerability factors. RESULTS: We estimated positive associations between short-term changes in indoor heat exposure and cause-specific mortality and morbidity [e.g., circulatory deaths, odds ratio per?5°C?increase = 1.16 (95% CI: 1.03, 1.30)]. Associations were generally positive for earlier lag periods and weaker across later lag periods. Stratified analyses suggest stronger associations between indoor heat and emergency hospital admissions among African Americans compared with Whites. DISCUSSION: Findings suggest excess mortality among certain elderly populations in Houston who are likely exposed to high indoor heat. We developed a novel methodology to estimate indoor heat exposure that can be adapted to other U.S. LOCATIONS: In locations with high air conditioning prevalence, simplified modeling approaches may adequately account for indoor heat exposure in vulnerable neighborhoods. Accounting for indoor heat exposure may improve the estimation of the total impact of heat on health. https://doi.org/10.1289/EHP6340.
This paper describes the development of a scenario-based approach that couples 2D hydrodynamic modeling with Geographic Information System (GIS) network analysis to assess the vulnerability of emergency services to surface water flooding at a large city scale. The method is demonstrated for Emergency Medical Service and Fire & Rescue Service in the city of Shanghai, China. Considering four representative traffic conditions, accessibility in terms of service area, response time, and population coverage within specified timeframes (8-, 12-, and 15-minute for Emergency Medical Service and 5-, 10-, and 15-minute for Fire & Rescue Service) is quantified and mapped under normal as well as pluvial flood scenarios of various magnitudes (5-, 20-, and 100-year return periods). Results show that the performance of operational responses largely depends on the functioning of transportation system, dramatically decreasing from unobstructed to congested traffic. Surface water flooding is found to result in limited (i.e. site-specific) but nonlinear impacts on the city-wide emergency service provisions. The results provide detailed information for optimizing the distribution of emergency stations and developing strategic contingency planning for vulnerable populations and facilities.
Urban heat islands are an increasing concern even in small- to medium-sized cities, although these areas are still understudied especially in terms of the economic feasibility of adaptation options. This paper uses adaptation scenarios produced by an urban climate model as inputs to a social cost-benefit analysis in three small- to medium-sized cities in Austria: Modling, Klagenfurt, and Salzburg. The adaptation scenarios, which consider measures such as increasing the reflectivity of different sealed surfaces (referred to as the White City scenario) as well as greening measures (i.e. the Green City scenario), show decreases in the number of hot days (T-max >= 30 degrees C) when implemented. Benefits include reductions in heat-related mortality, which are modeled based on trends of daily mortality and climate data, reduced morbidity, productivity loss, and numerous urban ecosystem services. The results demonstrate favorable benefit-cost ratios of a combination of measures (White and Green City) of 1.27, 1.36, and 2.68 for Modling, Klagenfurt, and Salzburg, respectively, indicating positive economic grounds for supporting policies in line with the adaptation scenarios. Furthermore, results of the Green City vs. White City showed higher benefits for the combined and Green City scenarios despite higher costs for each of the cities.
OBJECTIVES: We examine the public health response to an unprecedented multiple mortality event in bats following an extreme heat event. The main public health risk associated with the event and the environmental clean-up was potential human infection with Australian bat lyssavirus. We also consider the public health implications as we enter an age of climate change, vulnerability and unexpected events. Type of service: The Tropical Public Health Service of Far North Queensland worked collaboratively with the local council to coordinate a practical public health and health protection response to a mass mortality event in bats in late 2018. METHODS: A coordinated response was instigated to remove thousands of decaying bat corpses from residential areas. This occurred alongside a health education campaign advising the public to avoid handling bats. RESULTS: The combined efforts were successful; those requiring vaccination and post-exposure prophylaxis were treated appropriately and owing to a successful campaign, exposures were minimised. However, significant issues with misinformation and social media messaging were noted, alongside amateur bat carers handling sick and injured bats inappropriately, compounding the challenge for public health services. This mass mortality event has implications regarding the preparation for and management of other unexpected public health crises related to climate change. LESSONS LEARNT: It is vital that areas populated with bats be prepared for extreme heat events (EHEs). Public health units need to be prepared for the unexpected events of climate change, advocate for a ‘one health’ approach to public health, and work with local and national governments to become ‘climate ready’.
With the ultrahigh-speed, large-scale development of tourism and the increasing frequency, intensity, and scope of extreme natural hazards in the context of climate warming, tourism has entered a high-risk era. Based on the central urban area within the outer ring of Shanghai as the research area and the tourism attraction as the research object, this paper takes the flood scenario simulation combined with GIS network analysis to evaluate the spatial accessibility of the emergency response of urban key public service departments (120) under current and future river flood scenarios in different return periods. The results of the study show that, (1) under the current and future flood scenarios, the submergence range is mainly distributed within 2 similar to 3 km along the banks of the Huangpu River, and it tends to increase from north to south; (2) there are 6, 9, and 21 tourism attractions in the emergency blind area under the once-in-a-century floods in 2010, 2030, and 2050 and 98, 105, and 112 tourism attractions in the emergency blind area under the once-in-a-millennium floods in 2010, 2030, and 2050, respectively; (3) in the flood scene, local road traffic in the inundation area is interrupted by water, and 120 first aid cannot get or be delayed to some tourist attraction (blind area); and (4) in 2030, under the normal and flooding scenarios, 120 first aid in the downtown area of Shanghai has the fastest route to tourism attractions according to the speed of S1, S2, S3, and S4. The flooding intensity (range and water depth), road traffic conditions (vehicle flow speed), and the number and location of key public service departments jointly determine the service scope and response time of medical emergency in urban floods. Since the flood control area of the central city in Shanghai is mainly distributed in the 2 similar to 3 km area on both banks of the Huangpu River, the impact of flood on the emergency medical service in the entire central city is limited, mainly in some hospitals in the riverside area, where 120 emergency vehicles are unable or delayed to reach some tourism attractions. The research indicates that the quantitative assessment method of spatial accessibility of the emergency response under flood scenario simulation has important scientific value and practical significance, which can provide decision-making basis for emergency management of tourism in China’s urban flood disaster.
Background: A growing number of cities, including Greater London, have set ambitious targets, including detailed policies and implementation plans, to reach global goals on sustainability, health, and climate change. Here we present a tool for a rapid assessment of the magnitude of impact of specific policy initiatives to reach these targets. The decision-support tool simultaneously quantifies the environmental and health impacts of specified selected policies. Methods: The ‘Cities Rapid Assessment Framework for Transformation (CRAFT)’ tool was applied to Greater London. CRAFT quantifies the effects of ten environmental policies on changes in (1) greenhouse gas (GHG) emissions, (2) exposures to environmental hazards, (3) travel-related physical activity, and (4) mortality (the number of attributable deaths avoided in one typical year). Publicly available data and epidemiological evidence were used to make rapid quantitative estimates of these effects based on proportional reductions in GHG emissions and environmental exposures from current baseline levels and to compute the mortality impacts. Results: The CRAFT tool estimates that, of roughly 50,000 annual deaths in Greater London, the modelled hazards (PM (2.5) (from indoor and outdoor sources), outdoor NO (2), indoor radon, cold, overheating) and low travel-related physical activity are responsible for approximately 10,000 premature environment-related deaths. Implementing the selected polices could reduce the annual mortality number by about 20% (~1,900 deaths) by 2050. The majority of these deaths (1,700) may be avoided through increased uptake in active travel. Thus, out of ten environmental policies, the ‘active travel’ policy provides the greatest health benefit. Also, implementing the ten policies results in a GHG reduction of around 90%. Conclusions: The CRAFT tool quantifies the effects of city policies on reducing GHG emissions, decreasing environmental health hazards, and improving public health. The tool has potential value for policy makers through providing quantitative estimates of health impacts to support and prioritise policy options.
