Los productos suministrados son: concentraciones en superficie con salidas gráficas horarias de las concentraciones en superficie de NO2, NO, O3, SO2, CO, PM10 y PM2.5 expresadas en µg/m3; índice previsto diario de calidad del aire
calculado a partir de valores de concentración, utilizando la información procedente de las directivas vigentes relacionadas con los distintos contaminantes atmosféricos, e Índice previsto horario de calidad del aire con un horizonte temporal de 48 horas
Izmerjeni podatki o kakovosti zraka in napovedi
South African Air Quality Information System (SAAQIS) is a web based interactive air quality information system which seeks to provide the state of air quality information to citizens, and it is a research portal for strengthening policy development related to air quality issues.
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
Speciated ground-level aerosol concentrations are required to understand and mitigate health impacts from dust storms, wildfires, and other aerosol emissions. Globally, surface monitoring is limited due to cost and infrastructure demands. While remote sensing can help estimate respirable (i.e. ground level) concentrations, current observations are restricted by inadequate spatiotemporal resolution, uncertainty in aerosol type, particle size, and vertical profile. One key issue with current remote sensing datasets is that they are derived from reflectances observed by polar-orbiting imagers, which means that aerosol is only derived during the daytime and only once or twice per day. Newer quantification methods using geostationary infrared (IR) data have focussed on detecting the presence, or absence, of an event. The determination of aerosol composition or particle size using IR exclusively has received little attention. This manuscript summarizes four scientific papers, published as part of a larger study, and identifies requirements for (a) using infrared radiance observations to obtain continual (i.e. day and night) concentration estimates; (b) increasing temporal resolution by using geostationary satellites; (c) utilizing all infrared channels to maximize spectral differences due to compositional changes; and (d) applying a high-pass filter (brightness temperature differences) to identify compositional variability. Additionally, (e) a preliminary calibration methodology was tested against three severe air quality case study incidents, namely, a dust storm, smoke from prescribed burns, and an ozone smog incident, near Sydney in eastern Australia which highlighted the ability of the method to determine atmospheric stability, clouds, and particle size. Geostationary remote sensing provides near-continuous data at a temporal resolution comparable to monitoring equipment. The spatial resolution (~?4 km(2) at NADIR) is adequate for large sources but coarse for localized sources. The spectral sensitivity of aerosol is limited and appears to be dominated by humidity changes rather than concentration or compositional changes. Geostationary remote sensing can be used to determine the timing, duration, and spatial extent of an air quality event. Brightness temperature differences can assist in qualifying composition with an order of magnitude estimate of concentration.
Pollens are a major cause of seasonal allergic diseases. Weather may alter the production of pollens. Increased atmospheric temperatures lead to earlier pollination of many plants and longer duration of pollination, resulting in extended pollen seasons, with early spring or late winter. Longer pollen seasons increase duration of exposure, resulting in more sensitization, and higher pollen concentrations may lead to more severe symptoms. Climate changes in contact to pollens may affect both allergic sensitization and symptom prevalence with severity. The future consequences of climate change, however, are speculative, because the influence on humans, is complex.
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.
BACKGROUND: Climate change is broadly affecting human health, with grave concern that continued warming of the earth’s atmosphere will result is serious harm. Since the mid-20th century, skin cancer incidence rates have risen at an alarming rate worldwide. OBJECTIVE: This review examines the relationship between climate change and cutaneous carcinogenesis. METHODS: A literature review used the National Institutes of Health databases (PubMed and Medline), the Surveillance, Epidemiology, and End Results and International Agency for Research on Cancer registries, and published reports by federal and international agencies and consortia, including the Australian Institute of Health and Welfare, Climate and Clean Air Coalition, U.S. Environmental Protection Agency, Intergovernmental Panel on Climate Change, National Aeronautics and Space Administration, National Oceanic and Atmospheric Administration, United Nations Environment Programme, World Health Organization, and World Meteorological Organization. RESULTS: Skin cancer risk is determined by multiple factors, with exposure to ultraviolet radiation being the most important. Strong circumstantial evidence supports the hypothesis that factors related to climate change, including stratospheric ozone depletion, global warming, and ambient air pollution, have likely contributed to the increasing incidence of cutaneous malignancy globally and will continue to impose a negative on influence skin cancer incidence for many decades to come. CONCLUSION: Because much of the data are based on animal studies and computer simulations, establishing a direct and definitive link remains challenging. More epidemiologic studies are needed to prove causality in skin cancer, but the evidence for overall harm to human health as a direct result of climate change is clear. Global action to mitigate these negative impacts to humans and the environment is imperative.
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.
Extreme weather and climate events are likely to increase in frequency and severity as a consequence of global climate change. These are events that can include flooding rains, prolonged heat waves, drought, wildfires, hurricanes, severe thunderstorms, tornadoes, storm surge, and coastal flooding. It is important to consider these events as they are not merely meteorologic occurrences but are linked to our health. We aim to address how these events are interconnected with asthma outcomes associated with thunderstorm asthma, pollen production, mold infestation from flooding events, and poor air quality during wildfires.
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.
Recent pandemic outbreak of the corona-virus disease 2019 (COVID-19) has raised widespread concerns about the importance of the bioaerosols. They are atmospheric aerosol particles of biological origins, mainly including bacteria, fungi, viruses, pollen, and cell debris. Bioaerosols can exert a substantial impact on ecosystems, climate change, air quality, and public health. Here, we review several relevant topics on bioaerosols, including sampling and detection techniques, characterization, effects on health and air quality, and control methods. However, very few studies have focused on the source apportionment and transport of bioaerosols. The knowledge of the sources and transport pathways of bioaerosols is essential for a comprehensive understanding of the role microorganisms play in the atmosphere and control the spread of epidemic diseases associated with them. Therefore, this review comprehensively summarizes the up to date progress on the source characteristics, source identification, and diffusion and transport process of bioaerosols. We intercompare three types of diffusion and transport models, with a special emphasis on a widely used mathematical model. This review also highlights the main factors affecting the source emission and transport process, such as biogeographic regions, land-use types, and environmental factors. Finally, this review outlines future perspectives on bioaerosols.
BACKGROUND: In the rapidly shifting Canadian climate, an ageing population, and increased migration, a greater understanding of how local climate and air pollution hazards impact older adults and immigrant populations will be necessary for mitigating and adapting to adverse health impacts. OBJECTIVES: To explore the reported health impacts of climate change and air pollution exposures in older adults and immigrant people living in Canada, identify known factors influencing risk and resilience in these populations and gaps in the literature. METHODS: We searched for research focused on older adults and immigrants living in Canada, published from 2010 onward, where the primary exposures were related to climate or air pollution. We extracted data on setting, exposures, health outcomes, and other relevant contextual factors. RESULTS AND DISCUSSION: We identified 52 eligible studies, most focused in Ontario and Quebec. Older people in Canada experience health risks due to climate and air pollution exposures. The extent of the risk depends on multiple factors. We found little information about the climate- and air pollution-related health impacts experienced by immigrant communities. CONCLUSIONS: Further research about climate- and air pollution-related exposures, health, and which factors promote or reduce resiliency in Canada’s older adults and immigrant communities is necessary.
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.
Climate change is one of the biggest challenges humanity is facing in the 21st century. Two recognized sequelae of climate change are global warming and air pollution. The gradual increase in ambient temperature, coupled with elevated pollution levels have a devastating effect on our health, potentially contributing to the increased rate and severity of numerous neurological disorders. The main aim of this review paper is to shed some light on the association between the phenomena of global warming and air pollution, and two of the most common and debilitating neurological conditions: stroke and neurodegenerative disorders. Extreme ambient temperatures induce neurological impairment and increase stroke incidence and mortality. Global warming does not participate in the etiology of neurodegenerative disorders, but it exacerbates symptoms of dementia, Alzheimer’s disease (AD) and Parkinson’s Disease (PD). A very close link exists between accumulated levels of air pollutants (principally particulate matter), and the incidence of ischemic rather than hemorrhagic strokes. People exposed to air pollutants have a higher risk of developing dementia and AD, but not PD. Oxidative stress, changes in cardiovascular and cerebrovascular haemodynamics, excitotoxicity, microglial activation, and cellular apoptosis, all play a central role in the overlap of the effect of climate change on neurological disorders. The complex interactions between global warming and air pollution, and their intricate effect on the nervous system, imply that future policies aimed to mitigate climate change must address these two challenges in unison.
Numerous studies have linked outdoor levels of PM2.5, PM10, NO2, O-3, SO2, and other air pollutants to significantly higher rates of Covid 19 morbidity and mortality, although the rate in which specific concentrations of pollutants increase Covid 19 morbidity and mortality varies widely by specific country and study. As little as a 1-mu g/m(3) increase in outdoor PM2.5 is estimated to increase rates of Covid 19 by as much as 0.22 to 8%. Two California studies have strongly linked heavy wildfire burning periods with significantly higher outdoor levels of PM2.5 and CO as well as significantly higher rates of Covid 19 cases and deaths. Active smoking has also been strongly linked significantly increased risk of Covid 19 severity and death. Other exposures possibly related to greater risk of Covid 19 morbidity and mortality include incense, pesticides, heavy metals, dust/sand, toxic waste sites, and volcanic emissions. The exact mechanisms in which air pollutants increase Covid 19 infections are not fully understood, but are probably related to pollutant-related oxidation and inflammation of the lungs and other tissues and to the pollutant-driven alternation of the angiotensin-converting enzyme 2 in respiratory and other cells.
Male fertility and semen quality have declined over recent decades. Among other causes, exposure to environmental and occupational pollution has been linked to adverse reproductive outcomes, but effects on male semen quality are still uncertain. Therefore, the aim of the present study was to conduct a systematic review and meta-analysis to assess current evidence regarding the impact of exposure to tobacco smoke and environmental and occupational pollution on sperm quality in humans. In the meta-analysis, 22 studies are included showing that environmental and occupational pollutants may affect sperm count, volume, concentration, motility, vitality and sperm DNA, and chromatin integrity. All included articles reported significant alterations in at least one of the outcomes studied in association with at least one of the pollutants studied. Considering that sperm quality can be considered a proxy for general health and that pollutants have a dramatic impact on climate change, it would be strongly recommended to better understand the role of pollutants on human, animal, and planetary health.
Anthropogenic climate change is adversely impacting people and contributing to suffering and increased costs from climate-related diseases and injuries. In responding to this urgent and growing public health crisis, mitigation strategies are in place to reduce future greenhouse gas emissions (GHGE) while adaptation strategies exist to reduce and/or alleviate the adverse effects of climate change by increasing systems’ resilience to future impacts. While these strategies have numerous positive benefits on climate change itself, they also often have other positive externalities or health co-benefits. This knowledge can be harnessed to promote and improve global public health, particularly for the most vulnerable populations. Previous conceptual models in mitigation and adaptation studies such as the shared socioeconomic pathways (SSPs) considered health in the thinking, but health outcomes were not their primary intention. Additionally, existing guidance documents such as the World Health Organization (WHO) Guidance for Climate Resilient and Environmentally Sustainable Health Care Facilities is designed primarily for public health professionals or healthcare managers in hospital settings with a primary focus on resilience. However, a detailed cross sectoral and multidisciplinary conceptual framework, which links mitigation and adaptation strategies with health outcomes as a primary end point, has not yet been developed to guide research in this area. In this paper, we briefly summarize the burden of climate change on global public health, describe important mitigation and adaptation strategies, and present key health benefits by giving context specific examples from high, middle, and low-income settings. We then provide a conceptual framework to inform future global public health research and preparedness across sectors and disciplines and outline key stakeholders recommendations in promoting climate resilient systems and advancing health equity.
PURPOSE OF REVIEW: Climate change remains a major threat to the health and well-being of children globally. This article reviews the myriad health effects of climate change on children throughout their lives and discusses ways in which the general pediatrician can be an advocate for climate solutions. RECENT FINDINGS: Rising atmospheric temperatures, increased air pollution, and destabilized weather patterns all lead to adverse health outcomes for children and adverse obstetric outcomes. However, the impact of climate change is not evenly distributed. Children living in poverty are more likely to be adversely impacted by the changing climate. SUMMARY: Ongoing and emerging research suggests that children are particularly vulnerable to the effects of climate change. The primary care pediatrician is encouraged to see this irrefutable evidence as a call to action for advocacy on behalf of our patients and the planet.
Climatic change will have an impact on production and release of pollen, with consequences for the duration and magnitude of aeroallergen seasonal exposure and allergic diseases. Evaluations of pollen aerobiology in the southern hemisphere have been limited by resourcing and the density of monitoring sites. This review emphasizes inconsistencies in pollen monitoring methods and metrics used globally. Research should consider unique southern hemisphere biodiversity, climate, plant distributions, standardization of pollen aerobiology, automation, and environmental integration. For both hemispheres, there is a clear need for better understanding of likely influences of climate change and comprehending their impact on pollen-related health outcomes.
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.
Background: Environmental health is a growing area of knowledge, continually increasing and updating the body of evidence linking the environment to human health. Aim: This study summarizes the epidemiological evidence on environmental risk factors from meta-analyses through an umbrella review. Methods: An umbrella review was conducted on meta-analyses of cohort, case-control, case-crossover, and time-series studies that evaluated the associations between environmental risk factors and health outcomes defined as incidence, prevalence, and mortality. The specific search strategy was designed in PubMed using free text and Medical Subject Headings (MeSH) terms related to risk factors, environment, health outcomes, observational studies, and meta-analysis. The search was limited to English, Spanish, and French published articles and studies on humans. The search was conducted on September 20, 2020. Risk factors were defined as any attribute, characteristic, or exposure of an individual that increases the likelihood of developing a disease or death. The environment was defined as the external elements and conditions that surround, influence, and affect a human organism or population’s life and development. The environment definition included the physical environment such as nature, built environment, or pollution, but not the social environment. We excluded occupational exposures, microorganisms, water, sanitation and hygiene (WASH), behavioral risk factors, and no-natural disasters. Results: This umbrella review found 197 associations among 69 environmental exposures and 83 diseases and death causes reported in 103 publications. The environmental factors found in this review were air pollution, environmental tobacco smoke, heavy metals, chemicals, ambient temperature, noise, radiation, and urban residential surroundings. Among these, we identified 65 environmental exposures defined as risk factors and 4 environmental protective factors. In terms of study design, 57 included cohort and/or case-control studies, and 46 included time-series and/or case-crossover studies. In terms of the study population, 21 included children, and the rest included adult population and both sexes. In this review, the largest body of evidence was found in air pollution (91 associations among 14 air pollution definitions and 34 diseases and mortality diagnoses), followed by environmental tobacco smoke with 24 associations. Chemicals (including pesticides) were the third larger group of environmental exposures found among the meta-analyses included, with 19 associations. Conclusion: Environmental exposures are an important health determinant. This review provides an overview of an evolving research area and should be used as a complementary tool to understand the connections between the environment and human health. The evidence presented by this review should help to design public health interventions and the implementation of health in all policies approach aiming to improve populational health.
Climate change (CC) is the most challenging environmental health (EH) concern. Air pollution is closely linked to CC. However, many CC-health-related conditions (i.e., allergic diseases, asthma, hypertension, fluid and electrolyte disorders, child and adult obesity, type 2 diabetes, vector-borne diseases) are not usually counted, either because they do not cause death or require hospital admission/emergency triage. They are the vast majority of health care seeking generally treated by family doctors (FDs) and family pediatricians (FPs). FDs/FPs are often not aware of CC-health-impacts. Their potential role in tackling such a global challenge through their local influence on individual and collective attitudes and policies is not considered. Proper FD training could fill these gaps, raise awareness of their role, and implement EH FDs/FPs-based surveillance networks to collect, analyze, interpret, and report EH data to inform EH-related Policy. FDs and FPs, organized in sentinel physicians’ networks, could play a key role in advising policymakers at the local and regional level in designing interventions adapted to climate-related issues. Such experiences are rare worldwide and not well known. We will describe and discuss them in detail to share successful local examples.
Pollen, a major causal agent of respiratory allergy, is mainly affected by weather conditions. In Korea, pollen and weather data are collected by the national observation network. Forecast models and operational services are developed and provided based on the national pollen data base. Using the pollen risk forecast information will help patients with respiratory allergy to improve their lives. Changes in temperature and CO(2) concentration by climate change affect the growth of plants and their capacity of producing more allergenic pollens, which should be considered in making the future strategy on treating allergy patients.
BACKGROUND: Although the frequency and magnitude of climate change-related health hazards (CCRHHs) are likely to increase, the population vulnerabilities and corresponding health impacts are dependent on a community’s exposures, pre-existing sensitivities, and adaptive capacities in response to a hazard’s impact. To evaluate spatial variability in relative vulnerability, we: 1) identified climate change-related risk factors at the dissemination area level; 2) created actionable health vulnerability index scores to map community risks to extreme heat, flooding, wildfire smoke, and ground-level ozone; and 3) spatially evaluated vulnerability patterns and priority areas of action to address inequity. METHODS: A systematic literature review was conducted to identify the determinants of health hazards among populations impacted by CCRHHs. Identified determinants were then grouped into categories of exposure, sensitivity, and adaptive capacity and aligned with available data. Data were aggregated to 4188 Census dissemination areas within two health authorities in British Columbia, Canada. A two-step principal component analysis (PCA) was then used to select and weight variables for each relative vulnerability score. In addition to an overall vulnerability score, exposure, adaptive capacity, and sensitivity sub-scores were computed for each hazard. Scores were then categorised into quintiles and mapped. RESULTS: Two hundred eighty-one epidemiological papers met the study criteria and were used to identify 36 determinant indicators that were operationalized across all hazards. For each hazard, 3 to 5 principal components explaining 72 to 94% of the total variance were retained. Sensitivity was weighted much higher for extreme heat, wildfire smoke and ground-level ozone, and adaptive capacity was highly weighted for flooding vulnerability. There was overall varied contribution of adaptive capacity (16-49%) across all hazards. Distinct spatial patterns were observed – for example, although patterns varied by hazard, vulnerability was generally higher in more deprived and more outlying neighbourhoods of the study region. CONCLUSIONS: The creation of hazard and category-specific vulnerability indices (exposure, adaptive capacity and sensitivity sub-scores) supports evidence-based approaches to prioritize public health responses to climate-related hazards and to reduce inequity by assessing relative differences in vulnerability along with absolute impacts. Future studies can build upon this methodology to further understand the spatial variation in vulnerability and to identify and prioritise actionable areas for adaptation.
The Fourth National Climate Assessment (NCA4) is the most comprehensive report to date assessing climate change science, impacts, risks, and adaptation in the United States. The 1,500 page report covers a breadth of topics, ranging from foundational physical science to climate change response options. Here we present information on indicators and impacts of climate change in the human environment featured in NCA4 Volume II, focusing on: air quality, forest disturbance and wildfire, energy systems, and water resources. Observations, trends, and impacts of these aspects of our changing climate will be discussed, along with implications for the future. Implications: People of the United States are already being affected by our changing climate. Information on observed changes and impacts that affect human welfare and society, along with projections for the future, is highly valuable for informing decision-makers, including utility managers, emergency planners, and other stakeholders, about climate risk assessment, adaptation, and mitigation options.
Converging data would indicate the existence of possible relationships between climate change, environmental pollution and epidemics/pandemics, such as the current one due to SARS-CoV-2 virus. Each of these phenomena has been supposed to provoke detrimental effects on mental health. Therefore, the purpose of this paper was to review the available scientific literature on these variables in order to suggest and comment on their eventual synergistic effects on mental health. The available literature report that climate change, air pollution and COVID-19 pandemic might influence mental health, with disturbances ranging from mild negative emotional responses to full-blown psychiatric conditions, specifically, anxiety and depression, stress/trauma-related disorders, and substance abuse. The most vulnerable groups include elderly, children, women, people with pre-existing health problems especially mental illnesses, subjects taking some types of medication including psychotropic drugs, individuals with low socio-economic status, and immigrants. It is evident that COVID-19 pandemic uncovers all the fragility and weakness of our ecosystem, and inability to protect ourselves from pollutants. Again, it underlines our faults and neglect towards disasters deriving from climate change or pollution, or the consequences of human activities irrespective of natural habitats and constantly increasing the probability of spillover of viruses from animals to humans. In conclusion, the psychological/psychiatric consequences of COVID-19 pandemic, that currently seem unavoidable, represent a sharp cue of our misconception and indifference towards the links between our behaviour and their influence on the “health” of our planet and of ourselves. It is time to move towards a deeper understanding of these relationships, not only for our survival, but for the maintenance of that balance among man, animals and environment at the basis of life in earth, otherwise there will be no future.
BACKGROUND: Climate change impacts are associated with dramatic consequences for human health and threaten physical activity (PA) behaviors. OBJECTIVE: The aims of this systematic review were to present the potential bidirectional associations between climate change impacts and PA behaviors in humans and to propose a synthesis of the literature through a conceptual model of climate change and PA. METHODS: Studies published before October 2020 were identified through database searches in PubMed, PsycARTICLES, CINAHL, SPORTDiscus, GreenFILE, GeoRef, Scopus, JSTOR and Transportation Research Information Services. Studies examining the associations between PA domains and climate change (e.g., natural disasters, air pollution, and carbon footprint) were included. RESULTS: A narrative synthesis was performed and the 74 identified articles were classified into 6 topics: air pollution and PA, extreme weather conditions and PA, greenhouse gas emissions and PA, carbon footprint among sport participants, natural disasters and PA and the future of PA and sport practices in a changing world. Then, a conceptual model was proposed to identify the multidimensional associations between climate change and PA as well as sport practices. Results indicated a consistent negative effect of air pollution, extreme temperatures and natural disasters on PA levels. This PA reduction is more severe in adults with chronic diseases, higher body mass index and the elderly. Sport and PA communities can play an important mitigating role in post-natural disaster contexts. However, transport related to sport practices is also a source of greenhouse gas emissions. CONCLUSION: Climate change impacts affect PA at a worldwide scale. PA is observed to play both a mitigation and an amplification role in climate changes. TRIAL REGISTRATION NUMBER: PROSPERO CRD42019128314.
Climate change is one of the major global health threats to the world’s population. It is brought on by global warming due in large part to increasing levels of greenhouse gases resulting from human activity, including burning fossil fuels (carbon dioxide), animal husbandry (methane from manure), industry emissions (ozone, nitrogen oxides, sulfur dioxide), vehicle/factory exhaust, and chlorofluorocarbon aerosols that trap extra heat in the earth’s atmosphere. Resulting extremes of weather give rise to wildfires, air pollution, changes in ecology, and floods. These in turn result in displacement of populations, family disruption, violence, and major impacts on water quality and availability, food security, public health and economic infrastructures, and limited abilities for civil society to maintain citizen safety. Climate change also has direct impacts on human health and well-being. Particularly vulnerable populations are affected, including women, pregnant women, children, the disabled, and the elderly, who comprise the majority of the poor globally. Additionally, the effects of climate change disproportionally affect disadvantaged communities, including low income and communities of color, and lower-income countries that are at highest risk of adverse impacts when disasters occur due to inequitable distribution of resources and their socioeconomic status. The climate crisis is tilting the risk balance unfavorably for women’s sexual and reproductive health and rights as well as newborn and child health. Obstetrician/gynecologists have the unique opportunity to raise awareness, educate, and advocate for mitigation strategies to reverse climate change affecting our patients and their families. This article puts climate change in the context of women’s reproductive health as a public health issue, a social justice issue, a human rights issue, an economic issue, a political issue, and a gender issue that needs our attention now for the health and well-being of this and future generations. FIGO joins a broad coalition of international researchers and the medical community in stating that the current climate crisis presents an imminent health risk to pregnant people, developing fetuses, and reproductive health, and recognizing that we need society-wide solutions, government policies, and global cooperation to address and reduce contributors, including fossil fuel production, to climate change.
Several climate change-related predictions and observations have been documented for the Australian continent. Extreme weather events such as cycles of severe drought and damaging flooding are occurring with greater frequency and have a severe impact on human health. Two specific aspects of climate change affecting allergic and other respiratory disorders are outlined: firstly, the consequences of extreme weather events and secondly, the change in distribution of airborne allergens that results from various climate change factors.
Climate and weather directly impact plant phenology, affecting airborne pollen. The objective of this systematic review is to examine the impacts of meteorological variables on airborne pollen concentrations and pollen season timing. Using PRISMA methodology, we reviewed literature that assessed whether there was a relationship between local temperature and precipitation and measured airborne pollen. The search strategy included terms related to pollen, trends or measurements, and season timing. For inclusion, studies must have conducted a correlation analysis of at least 5 years of airborne pollen data to local meteorological data and report quantitative results. Data from peer-reviewed articles were extracted on the correlations between seven pollen indicators (main pollen season start date, end date, peak date, and length, annual pollen integral, average daily pollen concentration, and peak pollen concentration), and two meteorological variables (temperature and precipitation). Ninety-three articles were included in the analysis out of 9,679 articles screened. Overall, warmer temperatures correlated with earlier and longer pollen seasons and higher pollen concentrations. Precipitation had varying effects on pollen concentration and pollen season timing indicators. Increased precipitation may have a short-term effect causing low pollen concentrations potentially due to “wash out” effect. Long-term effects of precipitation varied for trees and weeds and had a positive correlation with grass pollen levels. With increases in temperature due to climate change, pollen seasons for some taxa in some regions may start earlier, last longer, and be more intense, which may be associated with adverse health impacts, as pollen exposure has well-known health effects in sensitized individuals.
This paper highlights the important leadership role of the public health sector, working with other governmental sectors and nongovernmental entities, to advance environmental public health in Latin America and the Caribbean toward the achievement of 2030 Sustainable Development Goal 3: Health and Well-Being. The most pressing current and future environmental public health threats are discussed, followed by a brief review of major historical and current international and regional efforts to address these concerns. The paper concludes with a discussion of three major components of a regional environmental public health agenda that responsible parties can undertake to make significant progress toward ensuring the health and well-being of all people throughout Latin America and the Caribbean.
Allergic diseases are caused by the immune system’s response to innocent antigens called allergens. Recent decades have seen a significant increase in the prevalence of allergic diseases worldwide, which has imposed various socio-economic effects in different countries. Various factors, including genetic factors, industrialization, improved hygiene, and climate change contribute to the development of allergic diseases in many parts of the world. Moreover, changes in lifestyle and diet habits play pivotal roles in the prevalence of allergic diseases. Dietary changes caused by decreased intake of antioxidants such as vitamin E lead to the generation of oxidative stress, which is central to the development of allergic diseases. It has been reported in many articles that oxidative stress diverts immune responses to the cells associated with the pathogenesis of allergic diseases. The aim of this short review was to summarize current knowledge about the anti-allergic properties of vitamin E.
Corona virus is highly uncertain and complex in space and time. Atmospheric parameters such as type of pollutants and local weather play an important role in COVID-19 cases and mortality. Many studies were carried out to understand the impact of weather on spread and severity of COVID-19 and vice-versa. A review study is conducted to understand the impact of weather and atmospheric pollution on morbidity and mortality. Studies show that aerosols containing corona virus generated by sneezes and coughs are major route for spread of virus. Viability and virulence of SARS-CoV-2 stuck on the surface of particulate matter is not yet confirmed. Studies found that an increase in particulate matter concentration causes more COVID-19 cases and mortality. Gaseous pollutant and COVID-19 cases are positively correlated. Local meteorology plays crucial role in the spread of corona virus and thus mortality. Decline in number of cases with rising temperature observed. Few studies also find that lowest and highest temperatures were related to lesser number of cases. Similarly humidity shows negative or no relationship with COVID-19 cases. Rainfall was not related whilst wind-speed plays positive role in spread of COVID-19. Solar radiation threats survival of virus, areas with lower solar radiation showed high exposure rate. Air quality tremendously improved during lockdown. A significant reduction in PM10, PM2.5, BC, NOx, SO(2), CO and VOCs concentration were observed. Lockdown had a healing effect on ozone; significant increase in its concentration was observed. Aerosols Optical Depths were found to decrease up to 50%.
INTRODUCTION: Exacerbations of chronic obstructive pulmonary disease (COPD) are associated with a significant health burden both for patients and healthcare systems. Exposure to various environmental factors increases the risk of exacerbations. AREAS COVERED: We searched PubMed and assessed literature published within the last 10 years to include epidemiological evidence on the relationships between air pollution, temperature and COPD exacerbation risk as well as the implications of extreme weather events on exacerbations. EXPERT OPINION: Ongoing climate change is expected to increase air pollution levels, global temperature and the frequency and severity of extreme weather events, all of which are associated with COPD exacerbations. Further research is needed using patient-focused methodological approaches to better understand and quantify these relationships, so that effective mitigation strategies that decrease the risk of exacerbations can be developed.
Climate change is a crisis of vast proportions that has serious implications for pulmonary health. Increasing global temperatures influence respiratory health through extreme weather events, wildfires, prolonged allergy seasons, and worsening air pollution. Children, elderly patients, and patients with underlying lung disease are at elevated risk of complications from these effects of climate change. This paper summarizes the myriad ways in which climate change affects the respiratory health of patients at home and in outdoor environments and outlines measures for patients to protect themselves.
Background Air-pollution and weather exposure beyond certain thresholds have serious effects on public health. Yet, there is lack of information on wider aspects including the role of some effect modifiers and the interaction between air-pollution and weather. This article aims at a comprehensive review and narrative summary of literature on the association of air-pollution and weather with mortality and hospital admissions; and to highlight literature gaps that require further research. Methods We conducted a scoping literature review. The search on two databases (PubMed and Web-of-Science) from 2012 to 2020 using three conceptual categories of “environmental factors”, “health outcomes”, and “Geographical region” revealed a total of 951 records. The narrative synthesis included all original studies with time-series, cohort, or case cross-over design; with ambient air-pollution and/or weather exposure; and mortality and/or hospital admission outcomes. Results The final review included 112 articles from which 70 involved mortality, 30 hospital admission, and 12 studies included both outcomes. Air-pollution was shown to act consistently as risk factor for all-causes, cardiovascular, respiratory, cerebrovascular and cancer mortality and hospital admissions. Hot and cold temperature was a risk factor for wide range of cardiovascular, respiratory, and psychiatric illness; yet, in few studies, the increase in temperature reduced the risk of hospital admissions for pulmonary embolism, angina pectoris, chest, and ischemic heart diseases. The role of effect modification in the included studies was investigated in terms of gender, age, and season but not in terms of ethnicity. Conclusion Air-pollution and weather exposure beyond certain thresholds affect human health negatively. Effect modification of important socio-demographics such as ethnicity and the interaction between air-pollution and weather is often missed in the literature. Our findings highlight the need of further research in the area of health behaviour and mortality in relation to air-pollution and weather, to guide effective environmental health precautionary measures planning.
The impact of climate change on the environment, biosphere, and biodiversity has become more evident in the recent years. Human activities have increased atmospheric concentrations of carbon dioxide (CO(2) ) and other greenhouse gases. Change in climate and the correlated global warming affects the quantity, intensity, and frequency of precipitation type as well as the frequency of extreme events such as heat waves, droughts, thunderstorms, floods, and hurricanes. Respiratory health can be particularly affected by climate change, which contributes to the development of allergic respiratory diseases and asthma. Pollen and mold allergens are able to trigger the release of pro-inflammatory and immunomodulatory mediators that accelerate the onset the IgE-mediated sensitization and of allergy. Allergy to pollen and pollen season at its beginning, in duration and intensity are altered by climate change. Studies showed that plants exhibit enhanced photosynthesis and reproductive effects and produce more pollen as a response to high atmospheric levels of carbon dioxide (CO(2) ). Mold proliferation is increased by floods and rainy storms are responsible for severe asthma. Pollen and mold allergy is generally used to evaluate the interrelation between air pollution and allergic respiratory diseases, such as rhinitis and asthma. Thunderstorms during pollen seasons can cause exacerbation of respiratory allergy and asthma in patients with hay fever. A similar phenomenon is observed for molds. Measures to reduce greenhouse gas emissions can have positive health benefits.
Air pollution and climate change have a significant impact on human health and well-being and contribute to the onset and aggravation of allergic rhinitis and asthma among other chronic respiratory diseases. In Westernized countries, households have experienced a process of increasing insulation and individuals tend to spend most of their time indoors. These sequelae implicate a high exposure to indoor allergens (house dust mites, pets, molds, etc), tobacco smoke, and other pollutants, which have an impact on respiratory health. Outdoor air pollution derived from traffic and other human activities not only has a direct negative effect on human health but also enhances the allergenicity of some plants and contributes to global warming. Climate change modifies the availability and distribution of plant- and fungal-derived allergens and increases the frequency of extreme climate events. This review summarizes the effects of indoor air pollution, outdoor air pollution, and subsequent climate change on asthma and allergic rhinitis in children and adults and addresses the policy adjustments and lifestyle changes required to mitigate their deleterious effects.
BACKGROUND: Exposure to heat, air pollution, and pollen are associated with health outcomes, including cardiovascular and respiratory disease. Studies assessing the health impacts of climate change have considered increased exposure to these risk factors separately, though they may be increasing simultaneously for some populations and may act synergistically on health. Our objective is to systematically review epidemiological evidence for interactive effects of multiple exposures to heat, air pollution, and pollen on human health. METHODS: We systematically searched electronic literature databases (last search, April 29, 2019) for studies reporting quantitative measurements of associations between at least two of the exposures and mortality from any cause and cardiovascular and respiratory morbidity and mortality specifically. Following the Navigation Guide systematic review methodology, we evaluated the risk of bias of individual studies and the overall quality and strength of evidence. RESULTS: We found 56 studies that met the inclusion criteria. Of these, six measured air pollution, heat, and pollen; 39 measured air pollution and heat; 10 measured air pollution and pollen; and one measured heat and pollen. Nearly all studies were at risk of bias from exposure assessment error. However, consistent exposure-response across studies led us to conclude that there is overall moderate quality and sufficient evidence for synergistic effects of heat and air pollution. We concluded that there is overall low quality and limited evidence for synergistic effects from simultaneous exposure to (1) air pollution, pollen, and heat; and (2) air pollution and pollen. With only one study, we were unable to assess the evidence for synergistic effects of heat and pollen. CONCLUSIONS: If synergistic effects between heat and air pollution are confirmed with additional research, the health impacts from climate change-driven increases in air pollution and heat exposure may be larger than previously estimated in studies that consider these risk factors individually.
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.
PURPOSE OF REVIEW: Climate change will affect mortality associated with both ambient temperature and air pollution. Because older adults have elevated vulnerability to both non-optimal ambient temperature (heat and cold) and air pollution, population aging can amplify future population vulnerability to these stressors through increasing the number of vulnerable older adults. We aimed to review recent evidence on projections of temperature- or air pollution-related mortality burden (i.e., number of deaths) under combined climate change and population aging scenarios, with a focus on evaluating the role of population aging in assessing these health impacts of climate change. We included studies published between 2014 and 2019 with age-specific population projections. RECENT FINDINGS: We reviewed 16 temperature projection studies and 15 air pollution projection studies. Nine of the temperature studies and four of the air pollution studies took population aging into account by performing age-stratified analyses that utilized age-specific relationships between temperature or air pollution exposures and mortality (i.e., age-specific exposure-response functions (ERFs)). Population aging amplifies the projected mortality burden of temperature and air pollution under a warming climate. Compared with a constant population scenario, population aging scenarios lead to less reduction or even increases in cold-related mortality burden, resulting in substantial net increases in future overall (heat and cold) temperature-related mortality burden. There is strong evidence suggesting that to accurately assess the future temperature- and air pollution-related mortality burden of climate change, investigators need to account for the amplifying effect of population aging. Thus, all future studies should incorporate age-specific population size projections and age-specific ERFs into their analyses. These studies would benefit from refinement of age-specific ERF estimates.
The world is currently shadowed by the pandemic of COVID-19. Confirmed cases and the death toll has reached more than 12 million and more than 550,000 respectively as of 10 July 2020. In the unsettling pandemic of COVID-19, the whole Earth has been on an unprecedented lockdown. Social distancing among people, interrupted international and domestic air traffic and suspended industrial productions and economic activities have various far-reaching and undetermined implications on air quality and the climate system. Improvement in air quality has been reported in many cities during lockdown, while the death rate of COVID-19 has been found to be higher in more polluted cities. The relationship between the spread of the SARS-CoV-2 virus and air quality is under investigation. In addition, the battle against COVID-19 could bring short-lived and long-lasting and positive and negative impacts to the warming climate. The impacts on the climate system and the role of the climate in modulating the COVID-19 pandemic are the foci of scientific inquiry. The intertwined relationship among environment, climate change and public health is exemplified in the pandemic of COVID-19. Further investigation of the relationship is imperative in the Anthropocene, in particular, in enhancing disaster preparedness. This short article intends to give an up-to-date glimpse of the pandemic from air quality and climate perspectives and calls for a follow-up discussion.
Research on air quality and human health “co-benefits” from climate mitigation strategies represents a growing area of policy-relevant scholarship. Compared to other aspects of climate and energy policy evaluation, however, there are still relatively few of these co-benefits analyses. This sparsity reflects a historical disconnect between research quantifying energy and climate, and research dealing with air quality and health. The air quality co-benefits of climate, clean energy, and transportation electrification policies are typically assessed with models spanning social, physical, chemical, and biological systems. This review article summarizes studies to date and presents methods used for these interdisciplinary analyses. Studies in the peer-reviewed literature (n = 26) have evaluated carbon pricing, renewable portfolio standards, energy efficiency, renewable energy deployment, and clean transportation. A number of major findings have emerged from these studies: [1] decarbonization strategies can reduce air pollution disproportionally on the most polluted days; [2] renewable energy deployment and climate policies offer the highest health and economic benefits in regions with greater reliance on coal generation; [3] monetized air quality health co-benefits can offset costs of climate policy implementation; [4] monetized co-benefits typically exceed the levelized cost of electricity (LCOE) of renewable energies; [5] Electric vehicle (EV) adoption generally improves air quality on peak pollution days, but can result in ozone dis-benefits in urban centers due to the titration of ozone with nitrogen oxides. Drawing from these published studies, we review the state of knowledge on climate co-benefits to air quality and health, identifying opportunities for policy action and further research.
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.
Allergic rhinitis affects the quality of life of millions of people worldwide. Air pollution not only causes morbidity, but nearly 3 million people per year die from unhealthy indoor air exposure. Furthermore, allergic rhinitis and air pollution interact. This report summarizes the discussion of an International Expert Consensus on the management of allergic rhinitis aggravated by air pollution. The report begins with a review of indoor and outdoor air pollutants followed by epidemiologic evidence showing the impact of air pollution and climate change on the upper airway and allergic rhinitis. Mechanisms, particularly oxidative stress, potentially explaining the interactions between air pollution and allergic rhinitis are discussed. Treatment for the management of allergic rhinitis aggravated by air pollution primarily involves treating allergic rhinitis by guidelines and reducing exposure to pollutants. Fexofenadine a non-sedating oral antihistamine improves AR symptoms aggravated by air pollution. However, more efficacy studies on other pharmacological therapy of coexisting AR and air pollution are currently lacking.
Mesquite (Prosopis juliflora (Sw.) DC), is an medium-sized tree (family Fabaceae, subfamily Mimosoideae), that has been intorcuded around the world. It is a noxious invasive species in Africa, Asia, and the Arabian Peninsula and a source of highly allergenic pollen in. The present article reviews the adverse allergenic effects of P. juliflora pollen on human and animal health. Several studies have diagnosed that allergenic pollens from Prosopis spp. can provoke respiratory problems. Prosopis pollen extracts have 16 allergenic components of which nine proteins were recognized as major allergens with some of them showing cross-reactivity. Clinically, understanding Prosopis pollen production, flowering seasonality, pollen load, and dispersal in the atmosphere are important to avoid allergic consequences for local inhabitants. Climate change and other pollution can also help to further facilitate allergenic issues. Furthermore, we document other human and animal health problems caused by invasive Prosopis trees. This includes flesh injuries, dental and gastric problems, and the facilitation of malaria. This review summarizes and enhances the existing knowledge about Prosopis flowering phenology, aeroallergen, and other human and animal health risks associated with this noxious plant.
Future air quality will be driven by changes in air pollutant emissions, but also changes in climate. Here, we review the recent literature on future air quality scenarios and projected changes in effects on human health, crops and ecosystems. While there is overlap in the scenarios and models used for future projections of air quality and climate effects on human health and crops, similar efforts have not been widely conducted for ecosystems. Few studies have conducted joint assessments across more than one sector. Improvements in future air quality effects on human health are seen in emission reduction scenarios that are more ambitious than current legislation. Larger impacts result from changing particulate matter (PM) abundances than ozone burdens. Future global health burdens are dominated by changes in the Asian region. Expected future reductions in ozone outside of Asia will allow for increased crop production. Reductions in PM, although associated with much higher uncertainty, could offset some of this benefit. The responses of ecosystems to air pollution and climate change are long-term, complex, and interactive, and vary widely across biomes and over space and time. Air quality and climate policy should be linked or at least considered holistically, and managed as a multi-media problem. This article is part of a discussion meeting issue ‘Air quality, past present and future’.
Air pollution has broad effects on human health involving many organ systems. The ocular surface is an excellent model with which to study the effects of air pollution on human health as it is in constant contact with the environment, and it is directly accessible, facilitating disease monitoring. Effects of air pollutants on the ocular surface typically manifest as dry eye (DE) symptoms and signs. In this review, we break down air pollution into particulate matter (organic and inorganic) and gaseous compounds and summarize the literature regarding effects of various exposures on DE. Additionally, we examine the effects of weather (relative humidity, temperature) on DE symptoms and signs. To do so, we conducted a PubMed search using key terms to summarize the existing literature on the effects of air pollution and weather on DE. While we tried to focus on the effect of specific exposures on specific aspects of DE, environmental conditions are often studied concomitantly, and thus, there are unavoidable interactions between our variables of interest. Overall, we found that air pollution and weather conditions have differential adverse effects on DE symptoms and signs. We discuss these findings and potential mitigation strategies, such as air purifiers, air humidifiers, and plants, that may be instituted as treatments at an individual level to address environmental contributors to DE.
The recognition and documentation of climatic change effects on human health remains one of the most important challenges of the 21st century. While myriad in scope, one of the most recognised impacts is related to pollen, specifically its production, release and duration, and the consequences for allergic diseases, including asthma and allergic rhinitis. At present, the bulk of efforts to understand and document these links have been conducted by scientists in the Northern Hemisphere. However, the link between climate change and aeroallergenic pollen is global and international in scope. For this reason, more recent efforts to provide similar evaluations have been initiated by scientists in the Southern Hemisphere. The current review acknowledges northern enquiries, but also emphasises research gaps and inconsistencies which should be avoided by southern investigators. To remedy these deficiencies, some suggestions are offered, including a greater emphasis on plant demographics, the standardisation of pollen metrics, automation and environmental integration. It is hoped that this perspective will be able to provide support to efforts of scientists in the Southern Hemisphere to evaluate better climate shifts and aeroallergen consequences. Overall, there is a clear and pressing need to understand these likely changes while simultaneously comprehending their impact on pollen-related health outcomes – for both hemispheres.
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.
Children’s bodies are in dynamic stages of development that make them more susceptible to harm from exposure to environmental agents. Children’s physical, physiological and behavioral traits can lead to increased exposure to toxic chemicals or pathogens. In addition, the social determinants of health interact with this exposure and create an increasing risk for further disparities among children. In Indonesia, the fourth most populated country in the world, children are under threat of exposure to contaminated water, air, food and soil, which can cause gastrointestinal and respiratory diseases, birth defects and neurodevelopmental disorders. A safe and balanced nutrition is still an unmet need for too many children. At the same time, the prevalence of obesity and the risk of later development of metabolic diseases, including diabetes and cardiovascular diseases, are increasing as a consequence of both unhealthy diets and inadequate physical activity. The risks of potential long-term toxicity, including carcinogenic, neurotoxic, immunotoxic, genotoxic, endocrine-disrupting and allergenic effects of many chemicals, are also close to their lives. This paper provides an overview of common disease risks in Indonesian children, including: acute hepatitis A, diarrheal diseases, dengue and malaria due to lack of water supply and sanitation, vectors, and parasites; asthma, bronchopneumonia, chronic obstructive pulmonary disease (COPD) and acute respiratory infections (ARIs) due to air pollution and climate change; some chronic diseases caused by toxic and hazardous waste; and direct or indirect consequences due to the occurrence of disasters and health emergencies.
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.
Worldwide, diabetes mellitus (DM) represents a major public-health problem due to its increasing prevalence in tandem with the rising trend of obesity. However, climate change, with its associated negative health effects, also constitutes a worrisome problem. Patients with DM are experiencing more visits to emergency departments, hospitalizations, morbidity and mortality during heat waves at ever-increasing numbers. Such patients are particularly vulnerable to heat waves due to impaired thermoregulatory mechanisms in conjunction with impaired autonomous nervous system responses at high temperatures, electrolyte imbalances and rapid deterioration of kidney function, particularly among those aged > 80 years and with preexisting chronic kidney disease (CKD). Moreover, exposure to cold temperatures is associated with increased rates of acute myocardial infarction as well as poor glycaemic control, although results are conflicting regarding cold-related mortality among patients with DM. In addition to extremes of temperature, air pollution as a consequence of the climate crisis may also be implicated in the increased prevalence and incidence of DM, particularly gestational DM (GDM), and lead to deleterious effects in patients with DM. Thus, more large-scale studies are now required to elucidate the association between specific air pollutants and risk of DM. This review presents the currently available evidence for the detrimental effects of climate change, particularly those related to weather variables, on patients with DM (both type 1 and type 2) and GDM. Specifically, the effects of heat waves and extreme cold, and pharmaceutical and therapeutic issues and their implications, as well as the impact of air pollution on the risk for DM are synthesized and discussed here.
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.
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.
Our aim is to review current asthma epidemiology, achievements from the last 10 years, and persistent challenges of asthma management and control in low-middle income countries (LMICs). Despite global efforts, asthma continues to be an important public health problem worldwide, particularly in poorly resourced settings. Several epidemiological studies in the last decades have shown significant variability in the prevalence of asthma globally, but generally a marked increase in LMICs resulting in significant morbidity and mortality. Poverty, air pollution, climate change, exposure to indoor allergens, urbanization and diet are some of the factors that contribute to inadequate control and poor outcomes in developing countries. Although asthma guidelines have been developed to raise awareness and improve asthma diagnosis and treatment, problems with underdiagnosis and undertreatment are still common. In addition, important social, financial, cultural and healthcare barriers are common obstacles in LMICs in achieving control. Given the high burden of asthma in these countries, adaptation and implementation of national asthma guidelines tailored to local needs should be a public health priority. Governmental commitment, education, better health system infrastructure, access to care and effective asthma medications are the cornerstone of achieving success. CONCLUSION: Asthma poses significant challenges to LMICs. Whilst there are ongoing efforts in improving asthma diagnosis and decreasing asthma burden in LMICs; reasons for inadequate asthma control are also common and difficult to tackle. Improving asthma diagnosis, access to appropriate treatment and decreasing risk factors should be key goals to reduce asthma morbidity and mortality worldwide.
Since the 2003 heatwave in Europe, evidence has been rapidly increasing on the association between extreme temperature and all-cause mortality. Little is known, however, about cause-specific cardiovascular mortality, effect modification by air pollution and aircraft noise, and which population groups are the most vulnerable to extreme temperature. We conducted a time-stratified case-crossover study in Zurich, Switzerland, including all adult cardiovascular deaths between 2000 and 2015 with precise individual exposure estimates at home location. We estimated the risk of 24,884 cardiovascular deaths associated with heat and cold using distributed non-linear lag models. We investigated potential effect modification of temperature-related mortality by fine particles, nitrogen dioxide, and night-time aircraft noise and performed stratified analyses across individual and social characteristics. We found increased risk of mortality for heat (odds ratio OR = 1.28 [95% confidence interval: 1.11-1.49] for 99th percentile of daily Tmean (24 °C) versus optimum temperature at 20 °C) and cold (OR = 1.15 [0.95-1.39], 5th percentile of daily Tmean (-3 °C) versus optimum temperature at 20 °C). Heat-related mortality was particularly strong for myocardial infarctions and hypertension related deaths, and among older women (>75 years). Analysis of effect modification also indicated that older women with lower socio-economic position and education are at higher risk for heat-related mortality. PM(2.5) increased the risk of heat-related mortality for heart failure, but not all-cause cardiovascular mortality. This study provides useful information for preventing cause-specific cardiovascular temperature-related mortality in moderate climate zones comparable to Switzerland.
OBJECTIVE: The objective of the study was to explore the influences of seasonality, meteorological conditions, and air pollution exposure on the number of patients who visit the hospital due to seizures. METHODS: Outpatient and inpatient data from the National Health Insurance Database of Taiwan from 2009 to 2013, meteorological data from the Meteorological Bureau, and air pollution exposure data from the Taiwan Air Quality Monitoring Stations were collected and integrated into daily time series data. The following data processing and analysis results are based on the mean of the 7?days’ lag data of the 18 meteorological condition/air pollution exploratory factors to identify the critical meteorological conditions and air pollution exposure factors by executing univariate analysis. The average hospital visits for seizure per day by month were used as an index of observation. The effect of seasonality has also been examined. RESULTS: The average visits per day by month had a significant association with 10 variables. Overall, the number of visits due to these factors has been estimated to be 71.529 (13.7%). The most obvious factors affecting the estimated number of visits include ambient temperature, CH(4), and NO. Six air pollutants, namely CH(4), NO, CO, NO(2), PM2.5, and NMHC had a significantly positive correlation with hospital visits due to seizures. Moreover, the average daily number of hospital visits was significantly high in January and February (winter season in Taiwan) than in other months (R(2)?=?0.422). CONCLUSION: The prediction model obtained in this study indicates the necessity of rigorous monitoring and early warning of these air pollutants and climate changes by governments. Additionally, the study provided a firm basis for establishing prediction models to be used by other countries or for other diseases.
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.
Cold spells have been associated with mortality from a few broad categories of diseases or specific diseases. However, there is a lack of data about the health effects of cold spells on mortality from a wide spectrum of plausible diseases which can reveal a more comprehensive contour of the mortality burden of cold spells. We collected daily mortality data in Guangzhou during 2010-2018 from the Guangzhou Center for Disease Control and Prevention. The quasi-Poisson generalized linear regression model mixed with the distributed lag non-linear model (DLNM) was conducted to examine the health impacts of cold spells for 11 broad causes of death groupings and from 35 subcategories in Guangzhou. Then, we examined the effect modification by age group (0-64 and 65+ years) and sex. Effects of cold spells on mortality generally delayed for 3-5 d and persisted up to 27 d. Cold spells were significantly responsible for increased mortality risk for most categories of deaths, with cumulative relative risk (RR) over 0-27 lagged days of 1.57 [95% confidence interval (CI): 1.48-1.67], 1.95 (1.49-2.55), 1.58 (1.39-1.79), 1.54 (1.26-1.88), 1.92 (1.15-3.22), 1.75, (1.14-2.68), 2.02 (0.78-5.22), 1.92 (1.49-2.48), 1.48 (1.18-1.85), and 1.18 (1.06-1.30) for non-accidental causes, cardiovascular diseases, respiratory diseases, digestive diseases, nervous system diseases, genitourinary diseases, mental diseases, endocrine diseases, external cause and neoplasms, respectively. The magnitudes of the effects of cold spells on mortality varied remarkably among the 35 subcategories, with the largest cumulative RR of 2.87 (1.72-4.79) estimated for pulmonary heart diseases. The elderly and females were at a higher risk of mortality for most diseases after being exposed to cold spells. Increased mortality from a wide range of diseases was significantly linked with cold spells. Our findings may have important implications for formulating effective preventive strategies and early warning response plans that mitigate the health burden of cold spells.
Along with climate change, unstable weather patterns are becoming more frequent. However, the temporal trend associated with the effect of temperature variation on schizophrenia (SCZ) is not clear. Daily time-series data on SCZ and meteorological factors for 15-year between January 1, 2005 and December 31, 2019 were collected. And we used the Poisson regression model combined with the time-varying distribution lag nonlinear model (DLNM) to explore the temporal trend of the association between three temperature variation indicators (diurnal temperature range, DTR; temperature variability, TV; temperature change between neighboring days, TCN) and SCZ hospitalizations, respectively. Meanwhile, we also explore the temporal trend of the interaction between temperature and temperature variation. Stratified analyses were performed in different gender, age, and season. Across the whole population, we found a decreasing trend in the risk of SCZ hospitalizations associated with high DTR (from 1.721 to 1.029), TCN (from 1.642 to 1.066), and TV (TV0-1, from 1.034 to 0.994; TV0-2, from 1.041 to 0.994, TV0-3, from 1.044 to 0.992, TV0-4, from 1.049 to 0.992, TV0-5, from 1.055 to 0.993, TV0-6, from 1.059 to 0.991, TV0-7, from 1.059 to 0.990), but an increasing trend in low DTR (from 0.589 to 0.752). Subgroup analysis results further revealed different susceptible groups. Besides, the interactive effect suggests that temperature variation may cause greater harm under low-temperature conditions. There was a synergy between TCN and temperature on the addition and multiplication scales, which were 1.068 (1.007, 1.133) and 0.067 (0.009, 0.122), respectively. Our findings highlight public health interventions to mitigate temperature variation effects needed to focus not only on high temperature variations but also moderately low temperature variations. Future hospitalizations for SCZ associated with temperature variation may be more severely affected by temperature variability from low temperature environments. The temporal trend is associated with the effect of temperature variation on schizophrenia (SCZ).
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.
The effects of daily mean temperature on health outcomes have been discussed in many previous studies, but few have considered the adverse impacts on upper respiratory tract infection (URTI) due to variance of temperature in one day. Diurnal temperature range (DTR) was a novel indicator calculated as maximum temperature minus minimum temperature on the same day. In this study, generalized additive model (GAM) with quasi-Poisson distribution was used to investigate the association between DTR and the number of daily outpatient visits for URTI among college students. Data about meteorological factors and air pollutants were provided by Hubei Meteorological Bureau and Wuhan Environmental Protection Bureau, respectively. Outpatient visits data were collected from the Hospital of Wuhan University from January 1, 2016, to December 31, 2018. Short-term exposure to DTR was associated with the increased risk of outpatient for URTI among all college students. Per 1 °C increased in DTR was associated with 0.73% (95%CI: 0.24, 1.21) increased in outpatient visits of all college students for URTI at lag 0 day. The greatest effect values were observed in males [1.35% (95%CI: 0.33,2.39)] at lag 0-6 days, and in females [0.86% (95%CI: 0.24, 1.49)] at lag 0-1 days. DTR had more adverse health impact in autumn and winter. Public health departments should consider the negative effect of DTR to formulate more effective prevention and control measures for protecting vulnerable people.
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.
We herein report a 56-year-old woman who developed allergic bronchopulmonary aspergillosis (ABPA) possibly due to fungal exposure after disastrous heavy rainfall in Western Japan in 2018. She was diagnosed with ABPA complicated with asthma, increased peripheral blood eosinophil count, elevation of specific immunoglobulin E for Aspergillus fumigatus, positive Aspergillus fumigatus precipitation antibody reaction test results, and notable chest computed tomography findings. After treatment with benralizumab, her symptoms, peripheral blood eosinophil count, radiological findings, and respiratory function dramatically improved. The administration of benralizumab appears to be an effective treatment strategy for ABPA.
To date, research evidence suggests that extreme ambient temperatures may lead to preterm birth. Since the results of studies in subtropical humid monsoon climate are inconclusive, we investigated the association between extreme ambient temperatures and the risk of preterm birth in Xuzhou, China. We analyzed the association between the birth data of 103,876 singleton deliveries (from July 1, 2016 to June 30, 2019) and ambient temperature. We used a quasi-Poisson model with distributed lag nonlinear models (DLNM) to investigate the delay and nonlinear effects of temperature, taking into account the effects of air pollutants and relative humidity. During the study period, the number of hospitalizations for preterm birth was 4623. Taking the median temperature (16.8 °C) as a reference, the highest risk estimate at extreme cold temperature (- 2.8 °C, 1st percentile) was found at lag 0-1 days. Exposure to extreme cold (- 2.8 °C, 1st percentile), or moderate cold (6.8 °C, 25th percentile) were associated with 1.659 (95% confidence interval [CI] 1.177-2.338) and 1.456 (95% CI 1.183-1.790) increased risks of preterm birth, respectively. In the further stratified analysis of the age of pregnant women, we found that there were significant associations between cold temperatures and preterm birth in both groups (older group ? 35; younger group < 35). In a subtropical humid monsoon climate, low ambient temperatures may lead to preterm birth, suggesting that women should stay away from low temperatures during pregnancy.
Temperature change is an important meteorological indicator reflecting weather stability. This study aimed to examine the effects of ambient temperature change on non-accidental mortality using diurnal temperature change (DTR) and temperature change between neighboring days (TCN) from two perspectives, intra-day and inter-day temperature change, and further, to explore seasonal variations of mortality, identify the susceptible population and investigate the interaction between temperature change and apparent temperature (AT). We collected daily data on cause-specific mortality, air pollutants and meteorological indicators in Shenzhen, China, from 1 January 2013 to 29 December 2017. A Quasi-Poisson generalized linear regression combined with distributed lag non-linear models (DLNMs) were conducted to estimate the effects of season on temperature change-related mortality. In addition, a non-parametric bivariate response surface model was used to explore the interaction between temperature change and AT. The cumulative effect of DTR was a U-shaped curve for non-accidental mortality, whereas the curve for TCN was nearly monotonic. The overall relative risks (RRs) of non-accidental, cardiovascular and respiratory mortality were 1.407 (95% CI: 1.233-1.606), 1.470 (95% CI: 1.220-1.771) and 1.741 (95% CI: 1.157-2.620) from exposure to extreme large DTR (99th) in cold seasons. However, no statistically significant effects were observed in warm seasons. As for TCN, the effects were higher in cold seasons than warm seasons, with the largest RR of 1.611 (95% CI: 1.384-1.876). The elderly and females were more sensitive, and low apparent temperature had a higher effect on temperature change-related non-accidental mortality. Temperature change was positively correlated with an increased risk of non-accidental mortality in Shenzhen. Both female and elderly people are more vulnerable to the potential adverse effects, especially in cold seasons. Low AT may enhance the effects of temperature change.
Considering the increasing rate of hospitalization due to the symptoms intensification, and the increasing trend of air pollution, this study aimed to determine the relationship between the amount of air pollutants and the incidence of cardiovascular disease leading to hospitalization. This case-crossover study was carried out on the data of admitted patients with cardiovascular disease such as hypertension, ischemic heart disease, and cerebrovascular disease in Urmia during 2011-2016. Weather data about air pollutants (NO2, PM10, SO2, and CO) were obtained from the meteorological department of Urmia. The data were coded for each patient and matched with the meteorological data for statistical modeling. The data were analyzed through STATA version 14. Conditional logistic regression was used to estimate the effects of air pollutants on cardiovascular disease adjusted to air temperature, relative humidity, and air pollutants. The final analysis was performed on 43,424 patients with cardiovascular disease using code I10-I99 including ischemic heart disease, hypertension, and cerebrovascular disease adjusted to air temperature and relative humidity. Of all pollutants, CO with each increase 10 ?g/m(3) had a meaningful relationship with the incidence of cardiovascular hospitalization. By selecting the window of exposure, 1, 2, and 6 days before admission, lag 6 (6 days) was the best estimation for exposure time in the patients with cardiovascular patients (OR 1.0056, CI 1.0041-1.007), and in the patients with ischemic heart disease (OR 1.000055, CI 1.000036-1.000075) and in the patients with hypertension (OR 1.000076, CI 1.00002-1.000132). Regarding cerebrovascular disease, no statistically significant association was observed. The results showed that only CO was associated with an increased risk of admission in patients with cardiovascular disease, ischemic heart disease, and hypertension, and there was no clear evidence for pollution effects on cerebrovascular diseases.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease represents the causative agent with a potentially fatal risk which is having great global human health concern. Earlier studies suggested that air pollutants and meteorological factors were considered as the risk factors for acute respiratory infection, which carries harmful pathogens and affects the immunity. The study intended to explore the correlation between air pollutants, meteorological factors, and the daily reported infected cases caused by novel coronavirus in India. The daily positive infected cases, concentrations of air pollutants, and meteorological factors in 288 districts were collected from January 30, 2020, to April 23, 2020, in India. Spearman’s correlation and generalized additive model (GAM) were applied to investigate the correlations of four air pollutants (PM(2.5), PM(10), NO(2), and SO(2)) and eight meteorological factors (Temp, DTR, RH, AH, AP, RF, WS, and WD) with COVID-19-infected cases. The study indicated that a 10 ?g/m(3) increase during (Lag0-14) in PM(2.5), PM(10), and NO(2) resulted in 2.21% (95%CI: 1.13 to 3.29), 2.67% (95% CI: 0.33 to 5.01), and 4.56 (95% CI: 2.22 to 6.90) increase in daily counts of Coronavirus Disease 2019 (COVID 19)-infected cases respectively. However, only 1 unit increase in meteorological factor levels in case of daily mean temperature and DTR during (Lag0-14) associated with 3.78% (95%CI: 1.81 to 5.75) and 1.82% (95% CI: -1.74 to 5.38) rise of COVID-19-infected cases respectively. In addition, SO(2) and relative humidity were negatively associated with COVID-19-infected cases at Lag0-14 with decrease of 7.23% (95% CI: -10.99 to -3.47) and 1.11% (95% CI: -3.45 to 1.23) for SO(2) and for relative humidity respectively. The study recommended that there are significant correlations between air pollutants and meteorological factors with COVID-19-infected cases, which substantially explain the effect of national lockdown and suggested positive implications for control and prevention of the spread of SARS-CoV-2 disease.
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.
During the summer of 2018 Sweden experienced a high occurrence of wildfires, most intense in the low-densely populated Jämtland Härjedalen region. The aim of this study was to investigate any short-term respiratory health effects due to deteriorated air quality generated by the smoke from wildfires. For each municipality in the region Jämtland Härjedalen, daily population-weighted concentrations of fine particulate matter (PM(2.5)) were calculated through the application of the MATCH chemistry transport model. Modelled levels of PM(2.5) were obtained for two summer periods (2017, 2018). Potential health effects of wildfire related levels of PM(2.5) were examined by studying daily health care contacts concerning respiratory problems in each municipality in a quasi-Poisson regression model, adjusting for long-term trends, weekday patterns and weather conditions. In the municipality most exposed to wildfire smoke, having 9 days with daily maximum 1-h mean of PM(2.5) > 20 ?g/m(3), smoke days resulted in a significant increase in daily asthma visits the same and two following days (relative risk (RR) = 2.64, 95% confidence interval (CI): 1.28-5.47). Meta-estimates for all eight municipalities revealed statistically significant increase in asthma visits (RR = 1.68, 95% CI: 1.09-2.57) and also when grouping all disorders of the lower airways (RR = 1.40, 95% CI: 1.01-1.92).
Desert dust transported from the Saharan-Sahel region to the Caribbean Sea is responsible for peak exposures of particulate matter (PM). This study explored the potential added value of satellite aerosol optical thickness (AOT) measurements, compared to the PM concentration at ground level, to retrospectively assess exposure during pregnancy. MAIAC MODIS AOT retrievals in blue band (AOT(470)) were extracted for the French Guadeloupe archipelago. AOT(470) values and PM(10) concentrations were averaged over pregnancy for 906 women (2005-2008). Regression modeling was used to examine the AOT(470)-PM(10) relationship during pregnancy and test the association between dust exposure estimates and preterm birth. Moderate agreement was shown between mean AOT(470) retrievals and PM(10) ground-based measurements during pregnancy (R(2)?=?0.289). The magnitude of the association between desert dust exposure and preterm birth tended to be lower using the satellite method compared to the monitor method. The latter remains an acceptable trade-off between epidemiological relevance and exposure misclassification, in areas with few monitoring stations and complex topographical/meteorological conditions, such as tropical islands.
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.
OBJECTIVES: The primary objective was to evaluate the association between weather variables and joint pain in patients with chronic rheumatic diseases (CRD: rheumatoid arthritis (RA), osteoarthritis (OA), and spondyloarthritis (SpA)). A secondary objective was to study the impact of air pollution indicators on CRD pain. METHOD: The study is prospective, correlational, with time-series analysis. Patients with CRD, living in a predefined catchment area, filled their level of pain daily using a 0-10 numerical scale (NS), for 1 year. Weather (temperature, relative humidity (H), atmospheric pressure (P)) and air pollution indicators (particulate matters (PM(10), PM(2.5)), nitrogen dioxide (NO(2)), and ozone (O(3))) were recorded daily using monitoring systems positioned in the same area. Association between pain and weather and air pollution indicators was studied using Pearson’s correlation. Time-series analysis methodology was applied to determine the temporal relationship between pain and indicators. RESULTS: The study included 94 patients, 82% reported they were weather-sensitive. Pain variation was similar across diseases over a year. Pain was associated negatively with temperature, H, and O(3,) and positively with P and NO(2). However, the strength of correlation was moderate; temperature explained 22% of pain variance. A drop of 10°C in temperature corresponded to an increase of 0.5 points in pain NS. Also, there was a significant interaction among environmental factors. In time-series analysis, temperature and NO(2) remained independently associated with pain. CONCLUSIONS: The perception of joint pain in patients with CRD was correlated with weather and air pollution. The strength of association was moderate and independent of underlying disease. Key Points •Weather variation was moderately correlated with joint pain in chronic rheumatic diseases, with an inverse association with temperature, humidity, and O(3). • Air pollution indicators, mainly nitrogen dioxide and ozone, were correlated with joint pain; particulate matters were also correlated but to a lesser extent. • The influence of these environmental factors was independent of the type of rheumatic disease, thus raising the hypothesis of their impact on pain perception mechanisms.
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.
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.
Air pollution in large cities produces numerous diseases and even millions of deaths annually according to the World Health Organization. Pollen exposure is related to allergic diseases, which makes its prediction a valuable tool to assess the risk level to aeroallergens. However, airborne pollen concentrations are difficult to predict due to the inherent complexity of the relationships among both biotic and environmental variables. In this work, a stochastic approach based on supervised machine learning algorithms was performed to forecast the daily Olea pollen concentrations in the Community of Madrid, central Spain, from 1993 to 2018. Firstly, individual Light Gradient Boosting Machine (LightGBM) and artificial neural network (ANN) models were applied to predict the day of the year (DOY) when the peak of the pollen season occurs, resulting the estimated average peak date 149.1?±?9.3 and 150.1?±?10.8 DOY for LightGBM and ANN, respectively, close to the observed value (148.8?±?9.8). Secondly, the daily pollen concentrations during the entire pollen season have been calculated using an ensemble of two-step GAM followed by LightGBM and ANN. The results of the prediction of daily pollen concentrations showed a coefficient of determination (r(2)) above 0.75 (goodness of the model following cross-validation). The predictors included in the ensemble models were meteorological variables, phenological metrics, specific site-characteristics, and preceding pollen concentrations. The models are state-of-the-art in machine learning and their potential has been shown to be used and deployed to understand and to predict the pollen risk levels during the main olive pollen season.
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%.
Schizophrenia (SCZ) hospital re-admissions constitute a serious disease burden worldwide. Some studies have reported an association between air pollutants and hospital admissions for SCZ. However, evidence is scarce regarding the effects of ambient particulate matter (PM) on SCZ hospital re-admissions, especially in coastal cities in China. The purpose of this study was to examine whether PM affects the risk of SCZ hospital re-admission in the coastal Chinese city of Qingdao. Daily SCZ hospital re-admissions, daily air pollutants, and meteorological factors from 2015 to 2019 were collected. A quasi-Poisson generalized linear regression model combined with distributed lag non-linear model (DLNM) was applied to model the exposure-lag-response relationship between PM and SCZ hospital re-admissions. The relative risks (RRs) were estimated for an inter-quartile range (IQR) increase in PM concentrations. Subgroup analyses by age and gender were conducted to identify the vulnerable subgroups. There were 6220 SCZ hospital re-admissions during 2015-2019. The results revealed that PM, including PM(10) (particles with an aerodynamic diameter ?10 ?m), PM(c) (particles >2.5 ?m but <10 ?m), and PM(2.5) (particles ?2.5 ?m), was positively correlated with SCZ hospital re-admissions. The strongest single-day effects all occurred on lag3 day, and the corresponding RRs were 1.07 (95% CI: 1.02-1.11) for PM(10), 1.03 (95% CI: 1.00-1.07) for PM(c), and 1.05 (95% CI: 1.01-1.09) for PM(2.5) per IQR increase. Stronger associations were observed in males and younger individuals (<45 years). Our findings suggest that PM exposure is associated with increased risk of SCZ hospital re-admission. Active intervention measures against PM exposure should be taken to reduce the risk of SCZ hospital re-admission, especially for males and younger individuals.
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.
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.
Statistical models to evaluate the relationships between large-scale meteorological conditions, prevailing air pollution levels and combined ozone and temperature events, were developed during the 1993-2012 period with Central Europe as regional focus. Combined ozone and temperature events were defined based on the high frequency of coinciding, health-relevant elevated levels of daily maximum tropospheric ozone concentrations (based on running 8-h means) and daily maximum temperature values in the peak ozone and temperature season from April to September. By applying two different modeling approaches based on lasso, logistic regression, and multiple linear regression mean air temperatures at 850 hPa, ozone persistence, surface thermal radiation, geopotential heights at 850 hPa, meridional winds at 500 hPa, and relative humidity at 500 hPa were identified as main drivers of combined ozone and temperature events. Statistical downscaling projections until the end of the twenty-first century were assessed by using the output of seven models of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Potential frequency shifts were evaluated by comparing the mid- (2031-2050) and late-century (2081-2100) time windows to the base period (1993-2012). A sharp increase of ozone-temperature events was projected under RCP4.5 and RCP8.5 scenario assumptions with respective multi-model mean changes of 8.94% and 16.84% as well as 13.33% and 37.52% for mid- and late-century European climate.
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.
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.
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.
In order to assess the influence of atmospheric conditions and particulate matter (PM) on the seasonally varying incidence of influenza-like illnesses (ILI) in the capital of Poland-Warsaw, we analysed time series of ILI reported for the about 1.75 million residents in total and for different age groups in 288 approximately weekly periods, covering 6 years 2013-2018. Using Poisson regression, we predicted ILI by the Universal Thermal Climate Index (UTCI) as biometeorological indicator, and by PM2.5 and PM10, respectively, as air quality measures accounting for lagged effects spanning up to 3 weeks. Excess ILI incidence after adjusting for seasonal and annual trends was calculated by fitting generalized additive models. ILI morbidity increased with rising PM concentrations, for both PM2.5 and PM10, and with cooler atmospheric conditions as indicated by decreasing UTCI. While the PM effect focused on the actual reporting period, the atmospheric influence exhibited a more evenly distributed lagged effect pattern over the considered 3-week period. Though ILI incidence adjusted for population size significantly declined with age, age did not significantly modify the effect sizes of both PM and UTCI. These findings contribute to better understanding environmental conditionings of influenza seasonality in a temperate climate. This will be beneficial to forecasting future dynamics of ILI and to planning clinical and public health resources under climate change scenarios.
Tropospheric ozone is known to have adverse effects on human health. Ozone pollution events are often associated with specific atmospheric circulation conditions. Therefore, studying the relationship between atmospheric circulation and ozone is particularly important for early warning and forecasting of ozone pollution events. Focusing on the Yangtze River Delta region, particularly in four important large industrial cities (Xuzhou, Nanjing, Shanghai, and Hangzhou) in the Yangtze River Delta, the T-mode objective classification method was applied to classify the weather circulation that mainly affects the Yangtze River Delta region into nine types. Local wind fields for the four industrial cities were classified according to their propensity for ventilation, stagnation, and recirculation based on the Allwine and Whiteman method. Based on the analysis of large-scale atmospheric circulation, we concluded that certain circulation patterns correspond to excessive ozone concentrations, while other circulation patterns correspond to good air quality. Moreover, ozone pollution was not closely related to local regional transmission. The importance of high temperatures in potentiating ozone pollution was also identified in the study area, whereas the effect of relative humidity was negligible. Finally, the importance of the different scale atmospheric motions was analyzed by studying two specific ozone pollution events in Xuzhou area (March, 2019) and Nanjing area (July-August, 2017). This analysis was complemented by HYSPLIT model’s outputs to simulate the pollutant diffusion path. Regarding the first episode, ozone concentration is often closely related to the slowly approaching thermal high-pressure system. In the second episode, local transmission had little effect on the generation and spread of ozone pollution. Furthermore, and comparing the circulation conditions with local meteorological factors, it was found that the increase in ozone concentration was often accompanied by higher temperature, and the response to humidity was not clear.
This study aimed to estimate morbidity risk/number attributed to air extreme temperatures using time-stratified case crossover study and distributed lag non-linear model in a region of Iran during 2015-2019. A time-stratified case crossover design based on aggregated exposure data was used in this study. In order to have no overlap bias in the estimations, a fixed and disjointed window by using 1-month strata was used in the design. A conditional Poisson regression model allowing for over dispersion (Quasi-Poisson) was applied into Distributed Lag Non-linear Model (DLNM). Different approaches were applied to estimate Optimum Temperature (OT). In the model, the interaction effect between temperature and humidity was assessed to see if the impact of heat or cold on Hospital Admissions (HAs) are different between different levels of humidity. The cumulative effect of heat during 21 days was not significant and it was the cold that had significant cumulative adverse effect on all groups. While the number of HAs attributed to any ranges of heat, including medium, high, extreme, and even all values were negligible, but a large number was attributable to cold values; about 10000 HAs were attributable to all values of cold temperature, of which about 9000 were attributed to medium range and about 1000 and less than 500 were attributed to high and extreme values of cold, respectively. This study highlights the need for interventions in cold seasons by policymakers. The results inform researchers as well as policy makers to address both men and women and elderly when any plan or preventive program is developed in the area under study.
The occurrence of long-lasting severe heat stress, such as in July-August 2003, July 2010, or in April-May 2018 has been one of the biggest meteorological threats in Europe in recent years. The paper focuses on the biometeorological and mortality effects of the hot June that was observed in Central Europe in 2019. The basis of the study was hourly and daily Universal Thermal Climate Index (UTCI) values at meteorological stations in Poland for June 2019. The average monthly air temperature and UTCI values from 1951 to 2018 were analysed as background. Grosswetterlagen calendar of atmospheric circulation was used to assess synoptic conditions of heat wave. Several heat strain measures were applied : net heat storage (S), modelled heart rate (HR), sultriness (HSI), and UTCI index. Actual total mortality (TM) and modelled strong heat-related mortality (SHRM) were taken as indicators of biometeorological consequences of the hot June in 2019. The results indicate that prolonged persistence of unusually warm weather in June 2019 was determined by the synoptic conditions occurring over the European region and causing advection of tropical air. They led to the emergence of heat waves causing 10% increase in TM and 5 times bigger SHRM then in preceding 10 years. Such increase in SHRM was an effect of overheating and overload of circulatory system of human organism.
In this study, 30 subjects were exposed to different combinations of air temperature (T(a) : 24, 27, and 30°C) and CO(2) level (8000, 10 000, and 12 000 ppm) in a high-humidity (RH: 85%) underground climate chamber. Subjective assessments, physiological responses, and cognitive performance were investigated. The results showed that as compared with exposure to T(a) = 24°C, exposure to 30°C at all CO(2) levels caused subjects to feel uncomfortably warm and experience stronger odor intensity, while increased mental effort and greater intensity of acute health symptoms were reported. However, no significant effects of T(a) on task performance or physiological responses were found. This indicated that subjects had to exert more effort to maintain their performance in an uncomfortably warm environment. Increasing CO(2) from 8000 to 12 000 ppm at all T(a) caused subjects to report higher rates of headache, fatigue, agitation, and feeling depressed, although the results were statistically significant only at 24 and 27°C. The text typing performance and systolic blood pressure (SBP) decreased significantly at this exposure, whereas diastolic blood pressure (DBP) and thermal discomfort increased significantly. These effects suggest higher arousal/stress. No significant interaction effect of T(a) and CO(2) concentration on human responses was identified.
Extreme fine particulate matter (PM2.5) events heavily impact residents, incurring high social and medical costs. As such, it is important to understand the characteristics of extreme PM2.5 events. This study used hourly PM2.5 and meteorological data to elucidate the effects, and predict the occurrence of these extreme weather events in Taiwan. The results show that synoptic conditions are unique for extreme PM2.5 events. During the maximum mean PM2.5 concentrations, weather conditions in Taiwan were dominated by synoptic weather patterns and the north-easterly monsoon. The maximum mean surface air pressure indicator had also occurred at this time. The azimuth of the resultant surface air pressure was 36.8 degrees + 7.6 degrees, while 96.2% of winds were in the north-north-easterly and north-easterly direction. The back trajectories suggest that the cold continental high air pressure system introduced dry and cold air masses with PM2.5. The SImax (mu g/m(3)/h)(,) relative humidity (%), global solar radiation (MJ/m(2)), visibility (km), weather type I, and weather type II predictor variables of the multi-regression model accounted for 80.6% of the variance in the magnitude of maximum hourly PM2.5 events. Extreme PM2.5 events were related to synoptic weather characteristics including type, strength, and position. The new quantitative variables aid the development of an efficient alarm system for extreme PM2.5 events that will help protect public health.
BACKGROUND: Climate change and increasing risks of extreme weather events affect human health and lead to changes in the emergency department (ED) admissions and the emergency medical services (EMS) operations. For a better allocation of resources in the healthcare system, it is essential to predict ED numbers based on environmental variables. This publication aims to quantify weather, air pollution and calendar-related effects on daily ED admissions. METHODS: Analyses were based on 575,725 admissions from the web-based IVENA system recording all patients in the greater Munich area with pre-hospital emergency care in ambulance operations during 2014-2018. Linear models were used to identify statistically significant associations between daily ED admissions and calendar, meteorological and pollution factors, allowing for lag effects of one to three days. Separate analyses were performed for seasons, with additional subset analyses by sex, age and surgical versus internal department. RESULTS: ED admissions were exceptionally high during the three-week Oktoberfest, particularly for males and on the weekends, as well as during the New Year holiday. Admissions significantly increased during the years of study, decreased in spring and summer holidays, and were lower on Sundays while higher on Mondays. In the warmer seasons, admissions were significantly associated with higher temperature, adjusting for the effects of sunshine and humidity in all age groups except for the elderly. Adverse weather conditions in non-summer seasons were either linked to increasing ED admissions (from storms, gust) or decreasing them from rain. Mostly, but not exclusively, in winter, increasing ED admissions were associated with colder minimum temperatures as well as with higher NO and PM(10) concentrations. CONCLUSIONS: In addition to standard calendar-related factors, incorporating seasonal weather, air pollutant and interactions with patient demographics into resource planning models can improve the daily allocation of resources and staff of EMS operations at hospital and city levels.
BACKGROUND: Tuberculosis (TB) is a serious public health problem in China. There is evidence to prove that meteorological factors and exposure to air pollutants have a certain impact on TB. But the evidence of this relationship is insufficient, and the conclusions are inconsistent. METHODS: Descriptive epidemiological methods were used to describe the distribution characteristics of TB in Shijiazhuang in the past five years. Through the generalized linear regression model (GLM) and the generalized additive model (GAM), the risk factors that affect the incidence of TB are screened. A combination of GLM and distribution lag nonlinear model (DLNM) was used to evaluate the lag effect of environmental factors on the TB. Results were tested for robustness by sensitivity analysis. RESULTS: The incidence of TB in Shijiazhuang showed a downward trend year by year, with seasonality and periodicity. Every 10 ?g/m(3) of PM(10) changes, the RR distribution is bimodal. The first peak of RR occurs on the second day of lag (RR = 1.00166, 95% CI: 1.00023, 1.00390); the second risk period starts from 13th day of lag and peaks on15th day (RR = 1.00209, 95% CI: 1.00076, 1.00341), both of which are statistically significant. The cumulative effect of increasing 10 ?g/m(3) showed a similar bimodal distribution. Time zones where the RR makes sense are days 4-6 and 13-20. RR peaked on the 18th day (RR = 1.02239, 95% CI: 1.00623, 1.03882). The RR has a linear relationship with the concentration. Under the same concentration, the RR peaks within 15-20 days. CONCLUSION: TB in Shijiazhuang City showed a downward trend year by year, with obvious seasonal fluctuations. The air pollutant PM(10) increases the risk of TB. The development of TB has a short-term lag and cumulative lag effects. We should focus on protecting susceptible people from TB in spring and autumn, and strengthen the monitoring and emission management of PM(10) in the atmosphere.
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.
BACKGROUND: Previous studies have reported that fine particulate matter (PM(2.5)) affects the incidence of premature births. In addition, recent studies have suggested that heat waves have a negative impact on birth outcomes. However, the combined effect of PM(2.5) and heat waves on the incidence of premature birth is controversial. This study investigated the independent and combined effects of PM(2.5) and heat wave exposures during the 1st and 2nd trimesters on premature birth. METHODS: The National Statistical Office of Korea provided birth data from 2010 to 2016. Preterm birth was defined as birth between 22 and 36 weeks. To assess the exposure to PM(2.5) and heat waves, we used PM(2.5) data estimated by the Community Multiscale Air Quality Modeling System (CMAQ) and heat wave warning data provided by the Korea Meteorological Administration. A multivariate logistic regression was used to investigate the risk of preterm birth according to the exposure to PM(2.5) and heat waves during the 1st and 2nd trimesters, and it was adjusted for residential area, year of birth, season of birth, parity, education level of the mother, age of the mother, and sex of the baby. RESULTS: In the 2nd trimester, compared with the 0 h of heat wave exposure (?67 percentile), 62.50-314.00 h (79-88 percentile) and>315.00 h of heat wave exposure (>88 percentile) were both significantly associated with preterm birth (OR for 79-88 percentile, 1.037, 95% CI, 1.003-1.073; OR for > 88 percentile, 1.174, 95% CI, 1.134-1.215). However, PM(2.5) exposure was not significantly associated with preterm birth. On the other hand, in the analysis to evaluate the combined effect of PM(2.5) and heat wave exposures of the 2nd trimester, compared with 0 h of heat wave exposure (?67 percentile) and<11.64 ?g/m(3) (?25 percentile) of PM(2.5), 11.64-22.74 ?g/m(3) (?25 percentile), 22.74-27.58 ?g/m(3) (26-50 percentile), and 27.57-32.39 ?g/m(3) (51-75 percentile) of PM(2.5) exposure combined with>315.00 h of heat wave exposure (>88 percentile) were all significantly associated with preterm birth. In addition, the effect size was increased with an increase of PM(2.5) exposure (OR for ? 25 percentile, 1.148, 95% CI, 1.095-1.203; OR for 26-50 percentile, 1.248, 95% CI, 1.178-1.323; OR for 51-75 percentile, 1.370, 95% CI, 1.245-1.507). CONCLUSION: Our findings suggest that the combined effect of heat wave and PM(2.5) exposure during the 2nd trimester on the risk of preterm birth was greater than that of each exposure alone. In other words, exposure to PM(2.5) increases the impact of heat waves on the risk of preterm birth. These results indicate that control of prenatal exposure to fine particular matter and extreme temperatures is important for the prevention of preterm birth.
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.
BACKGROUND/AIM: Previous studies have suggested that the short-term ambient air pollution and temperature are associated with myocardial infarction. In this study, we aimed to conduct a time-series analysis to assess the impact of fine particulate matter (PM2.5) and temperature on acute myocardial infarction (AMI) among adults over 20 years of age in Korea by using the data from the Korean National Health Information Database (KNHID). METHODS: The daily data of 192,567 AMI cases in Seoul were collected from the nationwide, population-based KNHID from 2005 to 2014. The monitoring data of ambient PM2.5 from the Seoul Research Institute of Public Health and Environment were also collected. A generalized additive model (GAM) that allowed for a quasi-Poisson distribution was used to analyze the effects of PM2.5 and temperature on the incidence of AMI. RESULTS: The models with PM2.5 lag structures of lag 0 and 2-day averages of lag 0 and 1 (lag 01) showed significant associations with AMI (Relative risk [RR]: 1.011, CI: 1.003-1.020 for lag 0, RR: 1.010, CI: 1.000-1.020 for lag 01) after adjusting the covariates. Stratification analysis conducted in the cold season (October-April) and the warm season (May-September) showed a significant lag 0 effect for AMI cases in the cold season only. CONCLUSIONS: In conclusion, acute exposure to PM2.5 was significantly associated with AMI morbidity at lag 0 in Seoul, Korea. This increased risk was also observed at low temperatures.
The health, economic, and social impact of COVID-19 has been significant across the world. Our objective was to evaluate the association between air pollution (through NO(2) and PM(2.5) levels) and COVID-19 mortality in Spanish provinces from February 3, 2020, to July 14, 2020, adjusting for climatic parameters. An observational and ecological study was conducted with information extracted from Datadista repository (Datadista, 2020). Air pollutants (NO(2) and PM(2.5) levels) were analyzed as potential determinants of COVID-19 mortality. Multilevel Poisson regression models were used to analyze the risk of mortality after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Models were adjusted by four climatic variables (hours of solar radiation, precipitation, daily temperature and wind speed) and population size. The mean levels of PM(2.5) and NO(2) across all provinces and time in Spain were 8.7 ?g/m(3) (SD 9.7) and 8.7 ?g/m(3) (SD 6.2), respectively. High levels of PM(2.5) (IRR?=?1.016, 95% CI: 1.007-1.026), NO(2) (IRR?=?1.066, 95% CI: 1.058-1.075) and precipitation (IRR(NO2)?=?0.989, 95% CI: 0.981-0.997) were positively associated with COVID-19 mortality, whereas temperature (IRR(PM2.5)?=?0.988, 95% CI: 0.976-1.000; and IRR(NO2)?=?0.771, 95% CI: 0.761-0.782, respectively) and wind speed (IRR(NO2)?=?1.095, 95% CI: 1.061-1.131) were negatively associated with COVID-19 mortality. Air pollution can be a key factor to understand the mortality rate for COVID-19 in Spain. Furthermore, climatic variables could be influencing COVID-19 progression. Thus, air pollution and climatology ought to be taken into consideration in order to control the pandemic. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11869-021-01062-2.
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.
Eczema resulting from external and internal factors accounts for the biggest global burden of disability owing to skin disease. This study aimed to determine an association between environmental factors and outpatient clinic visits for eczema. We collected data on dermatology clinic outpatient visits for eczema between January 2013 and July 2019. Data concerning environmental factors during this period were collated using national air quality network and air monitoring measurement parameters, namely barometric pressure, relative humidity, air temperature, and air pollutant concentrations, such as sulfur dioxide (SO(2)) and particulate matter (PM(10)). A distributed lag nonlinear model was used to investigate the relationship among eczema, environmental factors, and lagged effects. In total, 27,549 outpatient visits for eczema were recorded. In both single-factor and multiple-factor lag models, the effects of a 10-µg/m(3) increase in PM(10) and SO(2) values had significantly positive effects on the number of daily outpatient visits over a total 5 days of lag after adjusting for temperature, the number of daily outpatient visits increased with 0.87%, 7.65% and 0.69%, 5.34%, respectively. Relative humidity (RR?=?1.3870, 95% CI 1.3117-1.4665) and pressure (RR?=?1.0394, 95% CI 1.0071-1.0727) had significantly positive effects on the number of daily outpatients in single-factor lag models. However temperature had a significantly negative effect on them in the number of daily outpatients (RR?=?0.9686, 95% CI 0.9556-0.9819). Exposure to air pollution exacerbated eczema. Outpatient visits for eczema were found to have strong positive associations with changes in PM(10) levels.
Rotavirus A is the most common cause of infectious diarrhea worldwide. This study aimed to retrospectively study and analyze 4009 stool samples that were tested for viruses causing diarrhea, using multiplex reverse transcription PCR at Dankook University Hospital between 2010 and 2019. Furthermore, we determined the correlation between these factors and various climatic factors, including wind-chill temperature, relative humidity, rate of sunshine, and particulate matter. Rotavirus A infections occurred frequently in February, March, and April on an annual basis. Furthermore, during the study, the detection rate was highest at 17.0% (n=61/359) in 2011. Based on an analysis of weather big data, patient age, and period-specific infection during the summer, when the wind-chill temperature and relative humidity were high, the Rotavirus A infection rate was very low. Relative humidity (p=0.020) and particulate matter (p=0.049) were associated with the average number of monthly cases of Rotavirus A infection. However, wind chill temperature (p=0.074) and rate of sunshine (p=0.993) were not associated with the average monthly distribution of Rotavirus A cases. These results indicate that Rotavirus A infection was correlated with relative humidity and particulate matter during the study period and further the current understanding of the distribution of Rotavirus A infections resulting from climatic factors and particulate matter. This could help establish climate-related health policies to reduce the incidence of diarrhea and guide the development of vaccines against Rotavirus A.
Growing studies have shown that high temperature is a potential risk factor of schizophrenia occurrence. Therefore, elaborate analysis of different temperature exposure patterns, such as cumulative heat exposure within a time period and transient exposure at a particular time point, is of important public health significance. This study aims to utilize hourly temperature data to better capture the effects of cumulative and transient heat exposures on schizophrenia during the warm season in Hefei, China. We included the daily mean temperature and daily schizophrenia hospitalizations into the distributed lag non-linear model (DLNM) to simulate the exposure-response curve and determine the heat threshold (19.4 °C). We calculated and applied a novel indicator-daily excess hourly heat (DEHH)-to examine the effects of cumulative heat exposure over a day on schizophrenia hospitalizations. Temperature measurements at each time point were also incorporated in the DLNM as independent exposure indicators to analyze the impact of transient heat exposure on schizophrenia. Each increment of interquartile range (IQR) in DEHH was associated with elevated risk of schizophrenia hospitalizations from lag 1 (RR = 1.036, 95% confidence interval (CI): 1.016, 1.057) to lag 4 (RR = 1.025, 95% CI: 1.005, 1.046). Men and people over 40 years old were more susceptible to DEHH. Besides, we found a greater risk of heat-related schizophrenia hospitalizations between 0 a.m. and 6 a.m. This study revealed the adverse effects of accumulated and transient heat exposures on schizophrenia hospitalizations. Our findings need to be further tested in other regions with distinct regional features.
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.
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.
The impacts of wildfires in the western United States have been increasing for decades. Combining physical, epidemiological and economic models, this study finds that the economic damage of California wildfires in 2018 was roughly 1.5% of California’s annual gross domestic product. Recent increases in the frequency and scale of wildfires worldwide have raised concerns about the influence of climate change and associated socioeconomic costs. In the western United States, the hazard of wildfire has been increasing for decades. Here, we use a combination of physical, epidemiological and economic models to estimate the economic impacts of California wildfires in 2018, including the value of destroyed and damaged capital, the health costs related to air pollution exposure and indirect losses due to broader economic disruption cascading along with regional and national supply chains. Our estimation shows that wildfire damages in 2018 totalled $148.5 (126.1-192.9) billion (roughly 1.5% of California’s annual gross domestic product), with $27.7 billion (19%) in capital losses, $32.2 billion (22%) in health costs and $88.6 billion (59%) in indirect losses (all values in US$). Our results reveal that the majority of economic impacts related to California wildfires may be indirect and often affect industry sectors and locations distant from the fires (for example, 52% of the indirect losses-31% of total losses-in 2018 were outside of California). Our findings and methods provide new information for decision makers tasked with protecting lives and key production sectors and reducing the economic damages of future wildfires.
Climate change affects the reproductive life cycles of plants, including pollen production, which has consequences for allergic respiratory diseases. We examined climatic trends at eight locations in Bavaria, Southern Germany, with pollen time series of at least 10 years (up to 30 years in Munich). Climate change in Bavaria was characterized by a rise in temperature, but not during the winter. There is also a trend towards a more continental climate in Bavaria, which is significant in the Alps in the south of the territory. The influence of climate change depended on pollen type. Wind-pollinated arboreal species (e.g. Alnus, Betula and Cupressaceae/Taxaceae) showed advances in the start and end dates of pollen seasons and an increase in pollen load. These changes correlated negatively with late-winter (February) and spring temperatures (April). For herbaceous species, like Poaceae and Urticaceae, an earlier season was observed. Although precipitation is not a limiting factor in Southern Germany, water availability in the spring did influence the magnitude of grass pollen seasons. The effect of climatic change on the characteristics of pollen seasons was also more pronounced at higher altitudes, significant at > 800 m above sea level. Our results show that trends for start, end dates and intensity were similar at all locations, but only statistically significant at some. If we assume that earlier and more intense pollen seasons result in increases in prevalence and severity of allergic diseases, then the effect of climate change on public health in Bavaria may be significant.
Air Quality assessment and forecasting are the essentials today and they attracted many researchers. Environmental organizations regularly monitor and predict the air contaminants to make the public awareness, provide a better environment, and suitable for human health. Physical factors like climate changes, Industrialization, Fires and Urbanization are some of the factors which directly affect and reduce the air quality. All these data are time-series and real-time data. The primary pollutant is PMx that affect the respiratory systems and cardiac activity of humans. The secondary pollutants are SO2, CO, NOx, and O-3. Each has allowable range of concentration levels. In this work, meteorological elements are collected in different locations in last 5 years, with time window of 24 h and mapped to the concentration level of pollutants. The Machine Learning(ML) Methods such as Non-Linear Artificial Neural Network(ANN), Statistical Multilevel Regression, Neuro- Fuzzy and Deep Learning Long-Short-Term Memory (DL-LSTM) are used; to find the current concentration level of pollutants and will be useful for Real Time Correction (RTC) to give a feedback that can be used to reduce the contaminants in air for further days. The results are compared with the parameters such as R-2, RMSE and MAPE. Using these methods, the concentration level of contaminants is predicted with the deviation of R-2 in the range of 0.71-0.89. The results proved that DL-LSTM suits well when comparing to the ANN, Neuro-fuzzy and regression algorithms.
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.
Epidemiological studies have reported significant associations between weather situations and health. Cardiovascular disease is a serious chronic non-communicable disease which causes mortality and morbidity, bringing large economic burden to patients’ families. This study explored the relationship between cardiovascular disease (CVD) and weather conditions in Changchun, northeast China. The frequency distributions of 13 main circulation weather types (CWTs) were analyzed, and a comparison between air mass classification and hospital admissions was performed for various groups using an admission index (AI). The results indicated that women had a lower risk of CVD than men did. The risk of CVD for older people (aged???65 years) was lower than that for young people (aged?
IMPORTANCE: Future changes in climate are likely to adversely affect human health by affecting concentrations of particulate matter sized less than 2.5 ?m (PM2.5) and ozone (O3) in many areas. However, the degree to which these outcomes may be mitigated by reducing air pollutant emissions is not well understood. OBJECTIVE: To model the associations between future changes in climate, air quality, and human health for 2 climate models and under 2 air pollutant emission scenarios. DESIGN, SETTING, AND PARTICIPANTS: This modeling study simulated meteorological conditions over the coterminous continental US during a 1995 to 2005 baseline and over the 21st century (2025-2100) by dynamically downscaling representations of a high warming scenario from the Community Earth System Model (CESM) and the Coupled Model version 3 (CM3) global climate models. Using a chemical transport model, PM2.5 and O3 concentrations were simulated under a 2011 air pollutant emission data set and a 2040 projection. The changes in PM2.5 and O3-attributable deaths associated with climate change among the US census-projected population were estimated for 2030, 2050, 2075, and 2095 for each of 2 emission inventories and climate models. Data were analyzed from June 2018 to June 2020. MAIN OUTCOMES AND MEASURES: The main outcomes were simulated change in summer season means of the maximum daily 8-hour mean O3, annual mean PM2.5, population-weighted exposure, and the number of avoided or incurred deaths associated with these pollutants. Results are reported for 2030, 2050, 2075, and 2095, compared with 2000, for 2 climate models and 2 air pollutant emissions data sets. RESULTS: The projected increased maximum daily temperatures through 2095 were up to 7.6 °C for the CESM model and 11.8 °C for the CM3 model. Under each climate model scenario by 2095, compared with 2000, an estimated additional 21?000 (95% CI, 14?000-28?000) PM2.5-attributable deaths and 4100 (95% CI, 2200-6000) O3-attributable deaths were projected to occur. These projections decreased to an estimated 15?000 (95% CI, 10?000-20?000) PM2.5-attributable deaths and 640 (95% CI, 340-940) O3-attributable deaths when simulated using a future emission inventory that accounted for reduced anthropogenic emissions. CONCLUSIONS AND RELEVANCE: These findings suggest that reducing future air pollutant emissions could also reduce the climate-driven increase in deaths associated with air pollution by hundreds to thousands.
Since 2001, a synthesizing element in Intergovernmental Panel on Climate Change assessment reports has been a summary of how risks in a particular system could change with additional warming above pre-industrial levels, generally accompanied by a figure called the burning embers. We present a first effort to develop burning embers for climate change risks for heat-related morbidity and mortality, ozone-related mortality, malaria, diseases carried by Aedes sp., Lyme disease, and West Nile fever. We used an evidence-based approach to construct the embers based on a comprehensive global literature review. Projected risks for these health outcomes under 1.5 degrees C, 2 degrees C, and >2 degrees C of warming were used to estimate at what temperatures risk levels increased from undetectable to medium, high, and very high, from the pre-industrial baseline, under three adaptation scenarios. Recent climate change has likely increased risks from undetectable to moderate for heat-related morbidity and mortality, ozone-related mortality, dengue, and Lyme disease. Recent climate change also was assessed as likely beginning to affect the burden of West Nile fever. A detectable impact of climate change on malaria is not yet apparent but is expected to occur with additional warming. The risk for each climate-sensitive health outcome is projected to increase as global mean surface temperature increases above pre-industrial levels, with the extent and pace of adaptation expected to affect the timing and magnitude of risks. The embers may be an effective tool for informing efforts to build climate-resilient health systems including through vulnerability, capacity, and adaptation assessments and the development of national adaptation plans. The embers also can be used to raise awareness of future threats from climate change and advocate for mitigation actions to reduce the overall magnitude of health risks later this century and to expand current adaptation efforts to protect populations now.
Current models for flu-like epidemics insufficiently explain multi-cycle seasonality. Meteorological factors alone, including the associated behavior, do not predict seasonality, given substantial climate differences between countries that are subject to flu-like epidemics or COVID-19. Pollen is documented to be allergenic, it plays a role in immuno-activation and defense against respiratory viruses, and seems to create a bio-aerosol that lowers the reproduction number of flu-like viruses. Therefore, we hypothesize that pollen may explain the seasonality of flu-like epidemics, including COVID-19, in combination with meteorological variables. We have tested the Pollen-Flu Seasonality Theory for 2016-2020 flu-like seasons, including COVID-19, in the Netherlands, with its 17.4 million inhabitants. We combined changes in flu-like incidence per 100 K/Dutch residents (code: ILI) with pollen concentrations and meteorological data. Finally, a predictive model was tested using pollen and meteorological threshold values, inversely correlated to flu-like incidence. We found a highly significant inverse correlation of r(224) = -0.41 (p < 0.001) between pollen and changes in flu-like incidence, corrected for the incubation period. The correlation was stronger after taking into account the incubation time. We found that our predictive model has the highest inverse correlation with changes in flu-like incidence of r(222) = -0.48 (p < 0.001) when average thresholds of 610 total pollen grains/m(3), 120 allergenic pollen grains/m(3), and a solar radiation of 510 J/cm(2) are passed. The passing of at least the pollen thresholds, preludes the beginning and end of flu-like seasons. Solar radiation is a co-inhibitor of flu-like incidence, while temperature makes no difference. However, higher relative humidity increases with flu-like incidence. We conclude that pollen is a predictor of the inverse seasonality of flu-like epidemics, including COVID-19, and that solar radiation is a co-inhibitor, in the Netherlands.
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.
Evidence of the impact of ambient temperatures on emergency ambulance calls (EACs) in developing countries contributes to the improvement and complete understanding of the acute health effects of temperatures. This study aimed to examine the impacts and burden of heat on EACs in China, quantify the contributions of regional modifiers, and identify the vulnerable populations. A semi-parametric generalized additive model with a Poisson distribution was used to analyze the city-specific impacts of the daily maximum temperature (T-ma(x)) on EACs in June-August in 2014-2017. Stratified analyses by sex and age were performed to identify the vulnerable sub-populations. Meta-analysis was undertaken to illustrate the pooled associations. Further subgroup analysis, stratified by climate, latitude, and per capita disposable income (PCDI), and meta-regression analysis were conducted to explore the regional heterogeneity and quantify the contributions of possible modifiers. The city- and region-specific attributable fractions of EACs attributable to heat were calculated. Strong associations were observed between the daily T-max and total EACs in all cities. A total of 11.7% (95% confidence interval (CI): 11.2%-12.3%) of EACs were attributed to high temperatures in ten Chinese cities, and the central region with a low level of PCDI had the highest attributable fraction of 17.8% (95% CI: 17.2%-18.4%). People living in the central region with lower PCDI, and those aged 18-44 and 0-6 years were more vulnerable to heat than the others. The combined effects of PCDI, temperature, and latitude contributed 88.6% of the regional heterogeneity. The results complemented the understanding of the burden of EACs attributable to heat in developing countries and the quantitative contribution of regional modifiers.
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.
IMPORTANCE Air pollution is a worldwide public health issue that has been exacerbated by recent wildfires, but the relationship between wildfire-associated air pollution and inflammatory skin diseases is unknown. OBJECTIVE To assess the associations between wildfire-associated air pollution and clinic visits for atopic dermatitis (AD) or itch and prescribed medications for AD management. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional time-series study assessed the associations of air pollution resulting from the California Camp Fire in November 2018 and 8049 dermatology clinic visits (4147 patients) at an academic tertiary care hospital system in San Francisco, 175 miles from the wildfire source. Participants included pediatric and adult patients with AD or itch from before, during, and after the time of the fire (October 2018 through February 2019), compared with those with visits in the same time frame of 2015 and 2016, when no large wildfires were near San Francisco. Data analysis was conducted from November 1, 2019, to May 30, 2020. EXPOSURES Wildfire-associated air pollution was characterized using 3 metrics: fire status, concentration of particulate matter less than 2.5 mu m in diameter (PM2.5), and satellite-based smoke plume density scores. MAIN OUTCOMES AND MEASURES Weekly clinic visit counts for AD or itch were the primary outcomes. Secondary outcomes were weekly numbers of topical and systemic medications prescribed for AD in adults. RESULTS Visits corresponding to a total of 4147 patients (mean [SD] age, 44.6 [21.1] years; 2322 [56%] female) were analyzed. The rates of visits for AD during the Camp Fire for pediatric patients were 1.49 (95% CI, 1.07-2.07) and for adult patients were 1.15 (95% CI, 1.02-1.30) times the rate for nonfire weeks at lag 0, adjusted for temperature, relative humidity, patient age, and total patient volume at the clinics for pediatric patients. The adjusted rate ratios for itch clinic visits during the wildfire weeks were 1.82 (95% CI, 1.20-2.78) for the pediatric patients and 1.29 (95% CI, 0.96-1.75) for adult patients. A 10-mu g/m(3) increase in weekly mean PM2.5 concentration was associated with a 7.7% (95% CI, 1.9%-13.7%) increase in weekly pediatric itch clinic visits. The adjusted rate ratio for prescribed systemic medications in adults during the Camp Fire at lag 0 was 1.45 (95% CI, 1.03-2.05). CONCLUSIONS AND RELEVANCE This cross-sectional study found that short-term exposure to air pollution due to the wildfire was associated with increased health care use for patients with AD and itch. These results may provide a better understanding of the association between poor air quality and skin health and guide health care professionals’ counseling of patients with skin disease and public health practice.
Prevalence of allergic diseases has been increasing due to multiple factors, among which climate change has had the most impact. Climate factors increase production of pollen, which also exhibits increased allergenicity. Also, as a result of climate change, there has been a shift in flowering phenology and pollen initiation causing prolonged pollen exposure. Various numerical models have been developed to understand the effect of climate change on pollen emission and transport and the impact on allergic airway diseases.
Previous studies have demonstrated that plants are a very good indicator of global environmental variations. The responses of many plant species to climate change are confirmed by aerobiological research. This paper presents an analysis of many parameters of pollen seasons in the Amaranthaceae family based on measurements of pollen concentrations in atmospheric air. Pollen samples were collected with the volumetric method at a sampling site in Lublin (Poland) in 2001-2019. The obtained data were verified using statistical analyses. Moreover, the presence of pollenkitt on the pollen grain surface was examined in fresh anthers using scanning electron and light microscopes, since there are some difficulties in identification of Amaranthaceae pollen grains deposited on microscopic slides in aerobiological analysis. The pollen season in Amaranthaceae began on average on June 23 and ended on October 5, i.e. it lasted 105 days. The peak value and annual pollen sum were characterized by the highest variability in the study years in comparison with other season characteristics. The annual pollen sum was in the range from 183 to 725. Maximum concentrations were most often recorded in the second half of August, which is associated with the greatest risk of development of pollen allergy symptoms in sensitive subjects during this period. The results obtained in the 19-year study revealed that the pollen seasons began 14 days earlier. Similarly, the end of the season was accelerated by 24 days. The response of these plants to climate change also include the reduced pollen production by representatives of this family, which was manifested by a decrease in the annual sum of daily airborne pollen concentrations, on average by 35%, and a reduction in the maximum pollen concentration, on average by more than 60%. We found that temperature in May and June had an effect on pollen release, and relative air humidity in May influenced pollen concentrations. We noted significant similarities in the pollen release rate during the last 8 years of the study. The scanning electron microscopy examinations showed that the pollen grain surface in the representative of this family was covered completely or partially with pollenkitt. Hence, the apertures characteristic for pollen in this family were poorly visible. The presence of pollenkitt on the surface of these polyaperturate pollen grains may play an important role in preventing water loss during pollen migration in the air. Our research has demonstrated the response of plants flowering in summer to climate change. The results not only have practical importance for public health in the aspect of allergy risk but can also help to assess environmental changes.
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.
Air pollution is considered as an important concern all over the world. It disturbs the whole environment and produces more harmful effects to human’s healthy life. Relevant statistical reports from World Health Organization notify that air pollution play a major role in cause of diseases like asthma, lung cancer, stroke, early death and premature birth. Apart from diseases pollution also influence dangerous climate, weather conditions and may cause acid rain, global warming, ozone layer depletion, rainfall declines, etc. Therefore, it is essential to take necessary and preventive measures against air pollution. A comprehensive study is required to assess quality of ambient (outdoor) air, based on the observations of the major pollutants concentration drawn from different monitoring stations. Aiming at this problem, we proposed an ensemble based model to assess the air quality of United States from the period 2000 to 2016. In this article, we resolved the issues related to preprocessing of imbalanced dataset and improved the performance of the entire system through ensemble methods. We compared the recommended model with the existing ones. The experimental results show that the suggested model is superior to other systems and yield high accuracy, low error rate.
Admissions of newborn infants into Neonatal Intensive Care Units (NICU) has increased in the US over the last decade yet the role of environmental exposures as a risk factor for NICU admissions is under studied. Our study aims to determine the ecologic association between acute and intermediate ambient PM2.5 exposure durations and rates of NICU admissions, and to explore whether this association differs by area-level social stressors and meteorological factors. We conducted an ecologic time-series analysis of singleton neonates (N = 1,027,797) born in Florida hospitals between December 26, 2011 to April 30, 2019. We used electronic medical records (EMRs) in the OneFlorida Data Trust and included infants with a ZIP code in a Metropolitan Statistical Areas (MSA) and excluded extreme preterm births (<24wks gestation). The study outcome is the number of daily NICU admission at 28 days old or younger for each ZIP code in the study area. The exposures of interest are average same day, 1- and 2-day lags, and 1-3 weeks ambient PM2.5 concentration at the ZIP code-level estimated using inverse distance weighting (IDW) for each day of the study period. We used a zero-inflated Poisson regression mixed effects models to estimate adjusted associations between acute and intermediate PM2.5 exposure durations and NICU admissions rates. NICU admissions rates increased over time during the study period. Ambient 7-day average PM2.5 concentrations was significantly associated with incidence of NICU admissions, with an interquartile range (IQR = 2.37 ?g/m(3)) increase associated with a 1.4% (95% CI: 0.4%, 2.4%) higher adjusted incidence of daily NICU admissions. No other exposure duration metrics showed a significant association with daily NICU admission rates. The magnitude of the association between PM2.5 7-day average concentrations with NICU admissions was significantly (p < 0.05) higher among ZIP codes with higher proportions of non-Hispanic Blacks, ZIP codes with household incomes in the lowest quartile, and on days with higher relative humidity. Our data shows a positive relationship between acute (7-day average) PM2.5 concentrations and daily NICU admissions in Metropolitan Statistical Areas of Florida. The observed associations were stronger in socioeconomically disadvantaged areas, areas with higher proportions with non-Hispanic Blacks, and on days with higher relative humidity. Further research is warranted to study other air pollutants and multipollutant effects and identify health conditions that are driving these associations with NICU admissions.
Ambient air pollutants have been linked to adverse health outcomes, but evidence is still relatively rare in college students. Upper respiratory tract infection (URTI) is a common disease of respiratory system among college students. In this study, we assess the acute effect of air pollution on clinic visits of college students for URTI in Wuhan, China. Data on clinic visits due to URTI were collected from Wuhan University Hospital, meteorological factors (including daily temperature and relative humidity) provided by Wuhan Meteorological Bureau, and air pollutants by Wuhan Environmental Protection Bureau. In the present study, generalized additive model with a quasi-Poisson distribution link function was used to examine the association between ambient air pollutants (fine particulate matter (PM(2.5)), particulate matter (PM(10)), sulfur dioxide (SO(2)), nitrogen dioxide (NO(2)), and ozone (O(3))) and the daily number of clinic visits of college students for URTI at Wuhan University Hospital in Wuhan, China. In the meantime, the model was adjusted for the confounding effects of long-term trends, seasonality, day of the week, public holidays, vacation, and meteorological factors. The best degrees of free in model were selected based on AIC (Akaike Information Criteria). The effect modification by gender was also examined. A total of 44,499 cases with principal diagnosis of URTI were included from January 1, 2016, to December 31, 2018. In single-pollutant models, the largest increment of URTI visits were found at lag 0 day in single-day lags, and the effect values in cumulative lags were greater than those in single-day lags. PM(2.5) (0.74% (95%CI: 0.05, 1.44)) at lag 0 day, PM(10) (0.61% (95%CI: 0.12, 1.11)) and O(3) (1.01% (95%CI: 0.24, 1.79)) at lag 0-1 days, and SO(2) (9.18% (95%CI: 3.27, 15.42)) and NO(2) (3.40% (95% CI:1.64, 5.19)) at lag 0-3 days were observed to be strongly and significantly associated with clinic visits for URTI. PM(10) and NO(2) were almost still significantly associated with URTI after controlling for the other pollutants in our two-pollutant models, where the effect value of SO(2) after inclusion of O(3) appeared to be the largest and the effects of NO(2) were also obvious compared with the other pollutants. Subgroups analysis demonstrated that males were more vulnerable to PM(10) and O(3), while females seemed more vulnerable to exposure to SO(2) and NO(2). This study implied that short-term exposure to ambient air pollution was associated with increased risk of URTI among college students at Wuhan University Hospital in Wuhan, China. And gaseous pollutants had more negative health impact than solid pollutants. SO(2) and NO(2) were the major air pollutants affecting the daily number of clinic visits on URTI, to which females seemed more vulnerable than males.
Conjunctivitis is one of the most common eye-related health problems and significantly influences patients’ quality of life. Whether air pollution increased the risks of conjunctivitis is still unclear. Daily counts of outpatient visits for conjunctivitis, air pollution, and meteorological data during January 1, 2015-December 31, 2019 were collected from Tai’an, China. Generalized additive model with Poisson distribution was used to estimate the relationship between air pollution and visits for conjunctivitis, after controlling for the long-term and seasonal trends, weather variables, and day of the week. The effect of air pollution on visits for conjunctivitis was generally acute and significant at the current day and disappeared after 2 days. The relative risk of conjunctivitis visits associated with per 10 ?g/m(3) increases in PM(2.5), PM(10), SO(2), and NO(2) at lag 0-2 days was 1.006 (95% CI: 1.001-1.011), 1.003 (95% CI: 1.000-1.0107), 1.023 (95% CI: 1.009-1.037), and 1.025 (95% CI: 1.010-1.040), respectively. The impact of air pollution on visits for conjunctivitis varied greatly by individual characteristics. The impact of NO(2) was higher in males than in females, with the opposite trend for SO(2) and PM(2.5). Effect estimates of air pollutants were higher among return visits for conjunctivitis, the elderly, and white-collar workers. Our study highlights that the vulnerable subpopulations should pay more attention to protect themselves from air pollution.
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.
OBJECTIVE: The wildfire allied environmental pollution is highly toxic and can cause significant wide-ranging damage to the regional environment, weather conditions, and it can facilitate the transmission of microorganisms and diseases. The present study aims to investigate the effect of wildfire allied pollutants, particulate matter (PM-2.5 ?m), and carbon monoxide (CO) on the dynamics of daily cases and deaths due to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection in San Francisco, USA. MATERIALS AND METHODS: For this study, we selected San Francisco, one of the regions affected by the wildfires allied pollution in California, USA. The data on the COVID-19 pandemic in San Francisco, including daily new cases and new deaths were recorded from Worldometer Web. The daily environmental pollutants particulate matter (PM-2.5 ?m) and carbon monoxide (CO) were recorded from the metrological web “BAAQMD”. The daily cases, deaths, particulate matter (PM-2.5 ?m) and carbon monoxide were documented from the date of the occurrence of the first case of (SARS-CoV-2) in San Francisco, CA, USA, from March 20, 2020 to Sept 16, 2020. RESULTS: The results revealed a significant positive correlation between the environmental pollutants particulate matter (PM2.5 ?m) and the number of daily cases (r=0.203, p=0.007), cumulative cases (r=0.567, p<0.001) and cumulative deaths (r=0.562, p<0.001); whereas the PM2.5 ?m and daily deaths had no relationship (r=-0.015, p=0.842). In addition, CO was also positively correlated with cumulative cases (r=0.423, p<0.001) and cumulative deaths (r=0.315, p<0.001), however, CO had no correlation with the number of daily cases (r=0.134, p=0.075) and daily deaths (r=0.030, p=0.693). In San Francisco, one micrometer (?g/m3) increase in PM2.5 caused an increase in the daily cases, cumulative cases and cumulative deaths of SARS-COV-2 by 0.5%, 0.9% and 0.6%, respectively. Moreover, with a 1 part per million (ppm) increase in carbon monoxide level, the daily number of cases, cumulative cases and cumulative deaths increased by 5%, 9.3% and 5.3%, respectively. On the other hand, CO and daily deaths had no significant relationship. CONCLUSIONS: The wildfire allied pollutants, particulate matter PM-2.5?m and CO have a positive association with an increased number of SARS-COV-2 daily cases, cumulative cases and cumulative deaths in San Francisco. The metrological, disaster management and health officials must implement the necessary policies and assist in planning to minimize the wildfire incidences, environmental pollution and COVID-19 pandemic both at regional and international levels.
We estimate the effects of wildfire smoke exposure on infant health. Exposure to wildfire smoke is determined using the latitude and longitude coordinates corresponding to each infant’s home address and a fine-scaled spatial dataset of wildfire smoke plumes constructed in GIS from satellite images of the landscape. Using a difference-in-differences estimation strategy, model estimates show that exposure to wildfire smoke leads to a .034 increase in the probability of low birthweight.
Objective: The study examines how wildfire smoke exposure may impact health and safety in the agricultural workplace. Methods: Semi-structured interviews were conducted with agricultural employers and focus group discussions were held with farmworkers in three regions of California. Results: Agricultural employers had varying knowledge about and experience responding to poor air quality due to wildfire smoke. Respirators or masks were not mentioned as a potential protective measure when describing their safety practices. Farmworkers reported experiencing poor air quality due to wildfire smoke, although knowledge of safety precautions varied. Farmworkers reported employer and supervisors’ attitudes toward safety as having the greatest impact on the implementation of workplace safety measures. Conclusion: Adapting health promotion and workplace safety strategies to meet the multiple vulnerabilities and diverse needs of farmworkers is critical to successful implementation of workplace protection and safety measures. Given limited familiarity with the topic, wildfire smoke exposure resources are needed to assist employers and supervisors in their compliance with a new wildfire smoke safety regulation in California. To the best of our knowledge, this is the first study to explore agricultural employer and farmworker perceptions of the health and safety impacts of wildfire smoke and workplace exposure.
The air quality and human health impacts of wildfires depend on fire, meteorology, and demography. These properties vary substantially from one region to another in China. This study compared smoke from more than a dozen wildfires in Northeast, North, and Southwest China to understand the regional differences in smoke transport and the air quality and human health impacts. Smoke was simulated using the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) with fire emissions obtained from the Global Fire Emission Database (GFED). Although the simulated PM2.5 concentrations reached unhealthy or more severe levels at regional scale for some largest fires in Northeast China, smoke from only one fire was transported to densely populated areas (population density greater than 100 people/km(2)). In comparison, the PM2.5 concentrations reached unhealthy level in local densely populated areas for a few fires in North and Southwest China, though they were very low at regional scale. Thus, individual fires with very large sizes in Northeast China had a large amount of emissions but with a small chance to affect air quality in densely populated areas, while those in North and Southwest China had a small amount of emissions but with a certain chance to affect local densely populated areas. The results suggest that the fire and air quality management should focus on the regional air quality and human health impacts of very large fires under southward/southeastward winds toward densely populated areas in Northeast China and local air pollution near fire sites in North and Southwest China.
Future climate change may worsen air quality in many regions. However, evaluations of this ‘climate penalty’ on air quality have typically not assessed the radiative effects of changes in short-lived aerosols. Additionally, China’s clean air goals will decrease pollutant emissions and aerosol loadings, with concomitant weakening of aerosol feedbacks. Here we assess how such weakened aerosol direct effects alter the estimates of air pollution and premature mortality in China attributable to mid-century climate change under Representative Concentration Pathway 4.5. We found that weakening aerosol direct effects cause boundary layer changes that facilitate diffusion. This reduces air-pollution exposure (similar to 4% in fine particulate matter) and deaths (13,800 people per year), which largely offset the additional deaths caused by greenhouse gas-dominated warming. These results highlight the benefits of reduced pollutant emissions through weakening aerosol direct effects and underline the potential of pollution control measures to mitigate climate penalties locked in by greenhouse gas emissions.
Environmental factors have been suspected to have effects on the development of Kawasaki disease. However, the associations have been conflicting. The aim of this study was to investigate the effects of air pollution, weather conditions, and epidemic infections on the risks for Kawasaki disease in Japan. The concentrations of air pollutants (nitric oxide, nitrogen dioxide, and sulfur dioxide); ambient weather conditions (temperature, atmospheric pressure, relative air humidity, precipitation, sunshine duration, and wind velocity); and the epidemic conditions of 14 infectious diseases in hospitalized patients with Kawasaki disease were monitored from 2011 to 2018 in Beppu, Japan. The overdispersed generalized additive model was used to evaluate the effects, and a combination model with a distributed lag nonlinear model was used to estimate the cumulative effects. The incidence of Kawasaki disease had positive associations with preceding hot temperature and increased concentrations of nitric oxide and sulfur dioxide and a negative association with epidemic herpangina. The cumulative relative risk of Kawasaki disease at 5 lagged days of increased temperature was 1.76 (95% confidence interval: 1.01-3.07). This city-level observational study suggested that the incidence of Kawasaki disease was associated with air pollution and increased temperature and may be indirectly influenced by epidemic herpangina.
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.
To curb the staggering health burden attributed to air pollution, the sustainable solution for India would be to reduce emissions in future. Here we project ambient fine particulate matter (PM2.5) exposure in India for the year 2030 under two contrasting air pollution emission pathways for two different climate scenarios based on Representative Concentration Pathways (RCP4.5 and RCP8.5). All-India average PM2.5 is expected to increase from 41.4 +/- 26.5 mu g m(-3) in 2010 to 61.1 +/- 40.8 and 58.2 +/- 37.5 mu g m(-3) in 2030 under RCP8.5 and RCP4.5 scenarios, respectively if India follows the current legislation (baseline) emission pathway. In contrast, ambient PM2.5 in 2030 would be 40.2 +/- 27.5 (for RCP8.5) and 39.2 +/- 25.4 (for RCP4.5) mu g m(-3) following the short-lived climate pollutant (SLCP) mitigation emission pathway. We find that the lower PM2.5 in the mitigation pathway (34.2% and 32.6%, respectively for RCP8.5 and RCP4.5 relative to the baseline emission pathway) would come at a cost of 0.3-0.5 degrees C additional warming due to the direct impact of aerosols. The premature mortality burden attributable to ambient PM2.5 exposure is expected to rise from 2010 to 2030, but 381,790 (5-95% confidence interval, CI 275,620-514,600) deaths can be averted following the mitigation emission pathway relative to the baseline emission pathway. Therefore, we conclude that given the expected large health benefit, the mitigation emission pathway is a reasonable tradeoff for India despite the meteorological response. However, India needs to act more aggressively as the World Health Organization (WHO) annual air quality guideline (10 mu g m(-3)) would remain far off.
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.
PURPOSE: Global warming and air pollution are among the most important problems all over the world. Considering the key role of traffic officers who saliently deal with traffic management and are in full, constant and direct exposure to thermal stress and air pollution index, this study aims to investigate the simultaneous effects of these factors on the body temperature of traffic officers in the main squares of Tehran. METHODS: This study was conducted among 119 traffic officers who were working in 29 squares of Tehran, located near the active pollutant’s stations during 2017. Samples were selected by the census method. Environmental parameters such as air temperature (dry and wet), radiation temperature, the level of air pollution in the main squares and characteristics of officers such as body temperature and the Wet-Bulb-Globe-Temperature (WBGT) index were evaluated. Data were analyzed through independent samples t-test and factorial ANOVA with a p value of p???0.05 in SPSS software. RESULTS: There was no significant relationship between air pollution and ear temperature, but there was a statistically significant difference between the wet-bulb temperature and the ear temperature (t?=?26.4, P?
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.
Climate change is a global threat that poses significant risks to pregnant women and to their developing fetus and newborn. Educating pregnant women about the risks to their pregnancy may improve maternal and child health outcomes. Prior research suggests that presenting health information in narrative format can be more effective than a didactic format. Hence, the purpose of this study was to test the effectiveness of two brief educational interventions in a diverse group of pregnant women (n = 151). Specifically, using a post-test only randomized experiment, we compared the effectiveness of brief information presented in a narrative format versus a didactic format; both information formats were also compared to a no information control group. Outcome measures included pregnant women’s actual and perceived knowledge, risk perception, affective assessment, self-efficacy, intention to take protective behaviors, and subsequent information seeking behavior. As hypothesized, for all outcome measures, the narrative format was more effective than the didactic format. These results suggest the benefits of a narrative approach (versus a didactic approach) to educating pregnant women about the maternal and child health threats posed by climate change. This study adds to a growing literature on the effectiveness of narrative-based approaches to health communication.
The coal-dominated electricity system poses major challenges for India to tackle air pollution and climate change. Although the government has issued a series of clean air policies and low-carbon energy targets, a key barrier remains enforcement. Here, we quantify the importance of policy implementation in India’s electricity sector using an integrated assessment method based on emissions scenarios, air quality simulations, and health impact assessments. We find that limited enforcement of air pollution control policies leads to worse future air quality and health damages (e.g., 14?200 to 59?000 more PM(2.5)-related deaths in 2040) than when energy policies are not fully enforced (5900 to 8700 more PM(2.5)-related deaths in 2040), since coal power plants with end-of-pipe controls already emit little air pollution. However, substantially more carbon dioxide will be emitted if low-carbon and clean coal policies are not successfully implemented (e.g., 400 to 800 million tons more CO(2) in 2040). Thus, our results underscore the important role of effectively implementing existing air pollution and energy policy to simultaneously achieve air pollution, health, and carbon mitigation goals in India.
Particularly in rural settings, there has been little research regarding the health impacts of fine particulate matter (PM2.5) during the wildfire season smoke exposure period on respiratory diseases, such as influenza, and their associated outbreaks months later. We examined the delayed effects of PM2.5 concentrations for the short-lag (1-4 weeks prior) and the long-lag (during the prior wildfire season months) on the following winter influenza season in Montana, a mountainous state in the western United States. We created gridded maps of surface PM2.5 for the state of Montana from 2009 to 2018 using spatial regression models fit with station observations and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical thickness data. We used a seasonal quasi-Poisson model with generalized estimating equations to estimate weekly, county-specific, influenza counts for Montana, associated with delayed PM2.5 concentration periods (short-lag and long-lag effects), adjusted for temperature and seasonal trend. We did not detect an acute, short-lag PM2.5 effect nor short-lag temperature effect on influenza in Montana. Higher daily average PM2.5 concentrations during the wildfire season was po- sitively associated with increased influenza in the following winter influenza season (expected 16% or 22% increase in influenza rate per 1 mu g/m(3) increase in average daily summer PM2.5 based on two analyses, p = 0.04 or 0.008). This is one of the first observations of a relationship between PM2.5 during wildfire season and influenza months later.
BACKGROUND: Suicidal ideation is subject to serious underestimation among existing public health studies. While numerous factors have been recognized in affecting suicidal thoughts and behaviors (STB), the associated environmental risks have been poorly understood. Foremost among the various environment risks were air pollution, in particular, the PM2.5. The present study attempted to examine the relationship between PM(2.5) level and local weekly index of suicidal ideation (ISI). METHODS: Using Internet search query volumes in Baidu (2017), the largest internet search engine in China, we constructed a prefectural panel data (278 prefectures, 52?weeks) and employed dynamic panel GMM system estimation to analyze the relationship between weekly concentration of PM2.5 (Mean?=?87??g·m(-?3)) and the index of suicidal ideation (Mean?=?49.9). RESULTS: The results indicate that in the spring and winter, a 10??g·m(-?3) increase in the prior week’s PM(2.5) in a Chinese city is significantly associated with 0.020 increase in ISI in spring and a 0.007 increase in ISI in winter, after taking account other co-pollutants and meteorological conditions. CONCLUSION: We innovatively proposed the measure of suicidal ideation and provided suggestive evidence of a positive association between suicidal ideation and PM(2.5) level.
BACKGROUND: Few epidemiological investigations have focused on the influence of environmental temperature on human sperm quality. Here, we evaluated the potential association between ambient temperature and human sperm quality in Wuhan, China, and examined the interactive effect of particulate matter (PM(2.5)) and temperature. METHODS: 1780 males who had been living in Wuhan for no less than three months and received semen analysis at the Department of Reproductive Medicine in Renmin Hospital of Wuhan University between April 8, 2013 and June 30, 2015 were recruited. Daily mean meteorological data and air pollution data (PM(2.5), O(3) and NO(2)) in Wuhan between 2013 and 2015 were collected. A generalized linear model was used to explore the associations between ambient temperature and sperm quality (including sperm concentration, percentage of normal sperm morphology, and progressive motility) at 0-9, 10-14, 15-69, 70-90, and 0-90?days before semen examination, and the interaction between temperature and PM(2.5). RESULTS: The associations between ambient temperature and sperm quality were an inverted U-shape at five exposure windows, except for a lag of 0-9?days for sperm concentration. A 1?°C increase in ambient temperature above the thresholds was associated with a 2.038 (1.292?~?2.783), 1.814 (1.217?~?2.411), 1.458 (1.138?~?1.777), 0.934(0.617?~?1.251) and 1.604 (1.258?~?1.951) decrease in the percentage of normal sperm morphology at lag 0-9, lag 10-14, lag 15-69, lag 70-90, and lag 0-90?days, respectively. The interaction p-values of PM(2.5) and temperature were mostly less than 0.05 at five exposure windows. When ambient temperature exposure levels were above the thresholds, a 0.979 (0.659-1.299) and 3.559 (0.251?~?6.867) decrease in percentage of normal sperm morphology per 1?°C increase in temperature at lag 0-90?days was observed in the PM(2.5)???P(50) group and PM(2.5)?>?P(50) group, respectively. CONCLUSIONS: Our results indicate that exposure to ambient temperature has a threshold effect on sperm quality, and PM(2.5) enhances the effect of temperature on sperm quality when temperatures are above the threshold.
BACKGROUND AND OBJECTIVES: The number of pediatric patients diagnosed with influenza types A and B is increasing annually, especially in temperate regions such as Shanghai (China). The onset of pandemic influenza viruses might be attributed to various ambient meteorological factors including temperature, relative humidity (Rh), and PM(1) concentrations, etc. The study aims to explore the correlation between the seasonality of pandemic influenza and these factors. METHODS: We recruited pediatric patients aged from 0 to 18?years who were diagnosed with influenza A or B from July 1st, 2017 to June 30th, 2019 in Shanghai Children’s Medical Centre (SCMC). Ambient meteorological data were collected from the Shanghai Meteorological Service (SMS) over the same period. The correlation of influenza outbreak and meteorological factors were analyzed through preliminary Pearson’s r correlation test and subsequent time-series Poisson regression analysis using the distributed lag non-linear model (DLNM). RESULTS: Pearson’s r test showed a statistically significant correlation between the weekly number of influenza A outpatients and ambient meteorological factors including weekly mean, maximum, minimum temperature and barometric pressure (P?
Wildfire smoke (WFS) increases the risk of respiratory hospitalizations. We evaluated the association between WFS and asthma healthcare utilization (AHCU) during the 2013 wildfire season in Oregon. WFS particulate matter <= 2.5 mu m in diameter (PM2.5) was estimated using a blended model of in situ monitoring, chemical transport models, and satellite-based data. Asthma claims and place of service were identified from Oregon All Payer All Claims data from 1 May 2013 to 30 September 2013. The association with WFS PM2.5 was evaluated using time-stratified case-crossover designs. The maximum WFS PM2.5 concentration during the study period was 172 mu g/m(3). A 10 mu g/m(3) increase in WFS increased risk in asthma diagnosis at emergency departments (odds ratio [OR]: 1.089, 95% confidence interval [CI]: 1.043-1.136), office visit (OR: 1.050, 95% CI: 1.038-1.063), and outpatient visits (OR: 1.065, 95% CI: 1.029-1.103); an association was observed with asthma rescue inhaler medication fills (OR: 1.077, 95% CI: 1.065-1.088). WFS increased the risk for asthma morbidity during the 2013 wildfire season in Oregon. Communities impacted by WFS could see increases in AHCU for tertiary, secondary, and primary care.
OBJECTIVES: to evaluate the effect of air pollution (ozone – O3 and particulate matter <=10 ?m and <=2.5 ?m - PM10 and PM2.5) on the severity of Raynaud's phenomenon (RP) secondary to systemic sclerosis (SSc). DESIGN: cross-sectional, observational, and single centre study. SETTING AND PARTICIPANTS: all consecutive SSc patients residing in Lombardy (Northern Italy) were enrolled. PM10, PM2.5, and O3 concentrations were calculated for each patient at municipality resolution in the week before the evaluation. Similar considerations were made for meteorological variables (temperature and humidity). MAIN OUTCOME MEASURES: patients were asked to assess RP severity during the week before the evaluation according to a visual analogue scale (VAS). Ordinal logistic regression models were fitted to evaluate the short-term effect of temperature and air pollution with respect to RP. A univariate linear regression model was created to consider the association between temperature and pollutants. RESULTS: in this study, 87 SSc patients were enrolled. Temperature was confirmed to strongly influence RP severity. PM10 and PM.5 were found to significantly worsen RP severity for the first four days before the evaluation, including the day of the visit, and as mean up to six days before the evaluation. O3 seemed to exert a protective effect on RP severity that was significant for the first four days before the evaluation, including the day of the visit, and as mean up to seven days before the evaluation. CONCLUSIONS: since the overwhelming effect of temperature on RP, final conclusions about the exact contribution of pollutants on RP severity cannot be drawn because of the strong inter-correlation between air pollution and temperature.
In this study, the spatial pattern and temporal evolution of PM(2.5) over North China Plain (NCP) and Northeast China (NEC) during 2014-2018 was investigated. The annual mean PM(2.5) shows clear decreasing trends over time, but the seasonal mean PM(2.5) as well as the seasonal total duration and frequency of haze days shows large inter-annual fluctuation. Based on the atmospheric stagnation index (ASI), this study examined the correlation between ASI and haze events over NCP and NEC. Detailed analysis indicates that location dependency exists of ASI in the capability of capturing the haze events, and the ability is limited in NCP. Therefore, we first propose two alternative methods in defining the ASI to either account for the lag effect or enlarge the threshold value of wind speed at 500 hPa. The new methods can improve the ability of ASI to explain the haze events over NEC, though marginal improvement was achieved in NCP. Furthermore, this study constructed the equation based on the boundary layer height and wind speed at 10-meter, apparently improving the ability in haze capture rate (HCR), a ratio of haze days during the stagnation to the total haze days. Based on a multi-model ensemble analyses under Representative Concentration Pathway (RCP) 8.5, we found that by the end of this century, climate change may lead to increases in both the duration and frequency of wintertime stagnation events over NCP. In contrast, the models predict a decrease in stagnant events and the total duration of stagnation in winter over NEC.
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.
Previous studies have revealed associations of meteorological factors with tuberculosis (TB) cases. However, few studies have examined their lag effects on TB cases. This study was aimed to analyse nonlinear lag effects of meteorological factors on the number of TB notifications in Hong Kong. Using a 22-year consecutive surveillance data in Hong Kong, we examined the association of monthly average temperature and relative humidity with temporal dynamics of the monthly number of TB notifications using a distributed lag nonlinear models combined with a Poisson regression. The relative risks (RRs) of TB notifications were >1.15 as monthly average temperatures were between 16.3 and 17.3 °C at lagged 13-15 months, reaching the peak risk of 1.18 (95% confidence interval (CI) 1.02-1.35) when it was 16.8 °C at lagged 14 months. The RRs of TB notifications were >1.05 as relative humidities of 60.0-63.6% at lagged 9-11 months expanded to 68.0-71.0% at lagged 12-17 months, reaching the highest risk of 1.06 (95% CI 1.01-1.11) when it was 69.0% at lagged 13 months. The nonlinear and delayed effects of average temperature and relative humidity on TB epidemic were identified, which may provide a practical reference for improving the TB warning system.
Climate change and air pollution are two independent risk factors to cardiovascular diseases (CVD). Few studies investigated their interaction and potential effect modification of one another in developing countries. Individual level CVD hospital admission (ICD10: I00-I99) data for 1 January 2011 to 31 October 2016 were obtained from seven private hospitals in Cape Town. NO(2), SO(2), PM(10), temperature and relative humidity data were obtained from the South African Weather Services and the City of Cape Town. A case-crossover epidemiological study design and conditional logistic regression model were applied. Various cut-off values were applied to classify cold and warm days. In total, 54,818 CVD hospital admissions were included in the study. In general, on warm and cold days the 15-64 years old group was more at risk for CVD hospitalization with increasing air pollution levels compared to all ages combined or the ??65 years old group. Females appeared to be more at risk than males with increasing PM(10) levels. In contrast, males were more vulnerable to the effects of NO(2) and SO(2) than females. The study showed the modification effect of temperature on air pollution associated with CVD hospital admissions. The consideration of such interaction will help in policy making and public health interventions dealing with climate change-related health risks.
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.
To investigate the correlation between environmental-meteorological factors and daily visits for acute otitis media (AOM) in Lanzhou, China. METHODS: Data were collected in 2014-2016 by the Departments of Otolaryngology-Head and Neck Surgery at two hospitals in Lanzhou. Relevant information, including age, sex and visiting time, was collected. Environmental data included air quality index, PM10, PM2.5, O(3), CO, NO(2) and SO(2), and meteorological data included daily average temperature (T, °C), daily mean atmospheric pressure (AP, hPa), daily average relative humidity (RH, %) and daily mean wind speed (W, m/s). The SPSS22.0 software was used to generate Spearman correlation coefficients in descriptive statistical analysis, and the R3.5.0 software was used to calculate relative risk (RR) and to obtain exposure-response curves. The relationship between meteorological-environmental parameters and daily AOM visits was summarized. RESULTS: Correlations were identified between daily AOM visits and CO, O(3), SO(2), CO, NO(2), PM2.5 and PM10 levels. NO(2), SO(2), CO, AP, RH and T levels significantly correlated with daily AOM visits with a lag exposure-response pattern. The effects of CO, NO(2), SO(2) and AP on daily AOM visits were significantly stronger compared to other factors (P < 0.01). O(3), W, T and RH were negatively correlated with daily AOM visits. The highest RR lagged by 3-4 days. CONCLUSIONS: The number of daily AOM visits appeared to be correlated with short-term exposure to mixed air pollutants and meteorological factors from 2014 through 2016 in Lanzhou.
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.
Extreme wildfire events are becoming more common and while the immediate risks of particulate exposures to susceptible populations (i.e., elderly, asthmatics) are appreciated, the long-term health effects are not known. In 2017, the Seeley Lake (SL), MT area experienced unprecedented levels of wildfire smoke from July 31 to September 18, with a daily average of 220.9 mu g/m(3). The aim of this study was to conduct health assessments in the community and evaluate potential adverse health effects. The study resulted in the recruitment of a cohort (n= 95, average age: 63 years), for a rapid response screening activity following the wildland fire event, and two follow-up visits in 2018 and 2019. Analysis of spirometry data found a significant decrease in lung function (FEV1/FVC ratio: forced expiratory volume in first second/forced vital capacity) and a more than doubling of participants that fell below the lower limit of normal (10.2% in 2017 to 45.9% in 2018) one year following the wildfire event, and remained decreased two years (33.9%) post exposure. In addition, observed FEV(1)was significantly lower than predicted values. These findings suggest that wildfire smoke can have long-lasting effects on human health. As wildfires continue to increase both here and globally, understanding the health implications is vital to understanding the respiratory impacts of these events as well as developing public health strategies to mitigate the effects.
OBJECTIVE: The study aimed to determine if and how environmental factors correlated with asthma admission rates in geographically different parts of Guangxi province in China. SETTING: Guangxi, China. PARTICIPANTS: This study was done among 7804 asthma patients. PRIMARY AND SECONDARY OUTCOME MEASURES: Spearman correlation coefficient was used to estimate correlation between environmental factors and asthma hospitalisation rates in multiple regions. Generalised additive model (GAM) with Poisson regression was used to estimate effects of environmental factors on asthma hospitalisation rates in 14 regions of Guangxi. RESULTS: The strongest effect of carbon monoxide (CO) was found on lag1 in Hechi, and every 10?µg/m(3) increase of CO caused an increase of 25.6% in asthma hospitalisation rate (RR 1.26, 95%?CI 1.02 to 1.55). According to the correlation analysis, asthma hospitalisations were related to the daily temperature, daily range of temperature, CO, nitrogen dioxide (NO(2)) and particulate matter (PM(2.5)) in multiple regions. According to the result of GAM, the adjusted R(2) was high in Beihai and Nanning, with values of 0.29 and 0.21, which means that environmental factors are powerful in explaining changes of asthma hospitalisation rates in Beihai and Nanning. CONCLUSION: Asthma hospitalisation rate was significantly and more strongly associated with CO than with NO(2), SO(2) or PM(2.5) in Guangxi. The risk factors of asthma exacerbations were not consistent in different regions, indicating that targeted measures should differ between regions.
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.
The objective of this study is to analyze the short-term effects of atmospheric pollutant concentrations (PM(10), NO(2) and O(3)) and heat and cold waves on the number of pre-term births and cases of low birth weight related to Saharan dust advection and biomass combustion. The dependent variables used in this analysis were the total number of births, births with low weight (>2.500?g) and pre-term births (<37?weeks), that occurred at the province level. Data provided by the NSI included: days with Saharan dust intrusion or biomass advection classified in terms of information provided by MITECO for each of the nine regions in Spain. A representative city was selected for reach region in which the registered average daily concentrations of PM(10), NO(2) and O(3) (?g/m(3)) were used. These were also provided by MITECO. The daily maximum and daily minimum temperature (°C) used was those registered by the meteorological observatory station located in each province capital, provided by AEMET. Using Poisson log linear regression models, the associated relative risks (RR) were measured as well as the population attributable risk (PAR) corresponding to the variables that resulted statistically significant at p?
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.
Particulate matter from natural sources such as desert dust causes harmful effects for health. Asian dust (AD) increases the risk of acute myocardial infarction (AMI). However, little is known about the risk of myocardial infarction with nonobstructive coronary arteries (MINOCA), compared to myocardial infarction with coronary artery disease (MI-CAD). Using a time-stratified case-crossover design and conditional logistic regression models, the association between short-term exposure to AD whereby decreased visibility (
BACKGROUND: PM(2·5) is an important but modifiable environmental risk factor, not only for pulmonary diseases and cancers, but for cardiovascular health. However, the evidence regarding the association between air pollution and acute cardiac events, such as out-of-hospital cardiac arrest (OHCA), is inconsistent, especially at concentrations lower than the WHO daily guideline (25 ?g/m(3)). This study aimed to determine the associations between exposure to ambient air pollution and the incidence of OHCA. METHODS: In this nationwide case-crossover study, we linked prospectively collected population-based registry data for OHCA in Japan from Jan 1, 2014, to Dec 31, 2015, with daily PM(2·5), carbon monoxide (CO), nitrogen dioxide (NO(2)), photochemical oxidants (O(x)), and sulphur dioxide (SO(2)) exposure on the day of the arrest (lag 0) or 1-3 days before the arrest (lags 1-3), as well as the moving average across days 0-1 and days 0-3. Daily exposure was calculated by averaging the measurements from all PM(2·5) monitoring stations in the same prefecture. The effect of PM(2·5) on risk of all-cause or cardiac OHCA was estimated using a time-stratified case-crossover design coupled with conditional logistic regression analysis, adjusted for daily temperature and relative humidity. Single-pollutant models were also investigated for the individual gaseous pollutants (CO, NO(2), O(x), and SO(2)), as well as two-pollutant models for PM(2·5) with these gaseous pollutants. Subgroup analyses were done by sex and age. FINDINGS: Over the 2 years, 249?372 OHCAs were identified, with 149?838 (60·1%) presumed of cardiac origin. The median daily PM(2·5) was 11·98 ?g/m(3) (IQR 8·13-17·44). Each 10 ?g/m(3) increase in PM(2·5) was associated with increased risk of all-cause OHCA on the same day (odds ratio [OR] 1·016, 95% CI 1·009-1·023) and at lags of up to 3 days, ranging from OR 1·015 (1·008-1·022) at lag 1 to 1·033 (1·023-1·043) at lag 0-3. Results for cardiac OHCA were similar (ORs ranging from 1·016 [1·007-1·025] at lags 1 and 2 to 1·034 [1·021-1·047] at lag 0-3). Patients older than 65 years were more susceptible to PM(2·5) exposure than younger age groups but no sex differences were identified. CO, O(x), and SO(2) were also positively associated with OHCA while NO(2) was not. However, in two-pollutant models of PM(2·5) and gaseous pollutants, only PM(2·5) (positive association) and NO(2) (negative association) were independently associated with increased risk of OHCA. INTERPRETATION: Short-term exposure to PM(2·5) was associated with an increased risk of OHCA even at relatively low concentrations. Regulatory standards and targets need to incorporate the potential health gains from continual air quality improvement even in locations already meeting WHO standards. FUNDING: None.
BACKGROUND: Research investigating the effect of air pollution on diabetes incidence is mostly conducted in Europe and the United States and often produces conflicting results. The link between meteorological factors and diabetes incidence remains to be explored. We aimed to explore associations between air pollution and diabetes incidence and to estimate the nonlinear and lag effects of meteorological factors on diabetes incidence. METHODS: Our study included 19,000 people aged ?60 years from the Binhai New District without diabetes at baseline. The generalized additive model (GAM) and the distributed lag nonlinear model (DLNM) were used to explore the effect of air pollutants and meteorological factors on the incidence of diabetes. In the model combining the GAM and DLNM, the impact of each factor (delayed by 30 days) was first observed separately to select statistically significant factors, which were then incorporated into the final multivariate model. The association between air pollution and the incidence of diabetes was assessed in subgroups based on age, sex, and body mass index (BMI). RESULTS: We found that cumulative RRs for diabetes incidence were 1.026 (1.011-1.040), 1.019 (1.012-1.026), and 1.051 (1.019-1.083) per 10??g/m(3) increase in PM(2.5), PM(10), and NO(2), respectively, as well as 1.156 (1.058-1.264) per 1?mg/m(3) increase in CO in a single-pollutant model. Increased temperature, excessive humidity or dryness, and shortened sunshine duration were positively correlated with the incidence of diabetes in single-factor models. After adjusting for temperature, humidity, and sunshine, the risk of diabetes increased by 9.2% (95% confidence interval (CI):2.1%-16.8%) per 10??g/m(3) increase in PM(2.5). We also found that women, the elderly (?75 years), and obese subjects were more susceptible to the effect of PM(2.5). CONCLUSION: Our data suggest that PM(2.5) is positively correlated with the incidence of diabetes in the elderly, and the relationship between various meteorological factors and diabetes in the elderly is nonlinear.
BACKGROUND: Extreme ambient temperatures and air quality have been directly associated with various human diseases from several studies around the world. However, few analyses involving the association of these environmental circumstances with mental and behavioral disorders (MBD) have been carried out, especially in developing countries such as Brazil. METHODS: A time series study was carried out to explore the associations between daily air pollutants (SO(2), NO(2), O(3), and PM(10)) concentrations and meteorological variables (temperature and relative humidity) on hospital admissions for mental and behavioral disorders for Curitiba, Brazil. Daily hospital admissions from 2010 to 2016 were analyzed by a semi-parametric generalized additive model (GAM) combined with a distributed lag non-linear model (DLNM). RESULTS: Significant associations between environmental conditions (10??g/m(3) increase in air pollutants and temperature °C) and hospitalizations by MBD were found. Air temperature was the environmental variable with the highest relative risk (RR) at 0-day lag for all ages and sexes analyzed, with RR values of 1.0182 (95% CI: 1.0009-1.0357) for men, and 1.0407 (95% CI: 1.0230-1.0587) for women. Ozone exposure was a risk for all women groups, being higher for the young group, with a RR of 1.0319 (95% CI: 1.0165-1.0483). Elderly from both sexes were more susceptible to temperature variability, with a RR of 1.0651 (95% CI: 1.0213-1.1117) for women, and 1.0215 (95% CI: 1.0195-1.0716) for men. CONCLUSIONS: This study suggests that temperatures above and below the thermal comfort threshold, in addition to high concentrations of air pollutants, present significant risks on hospitalizations by MBD; besides, there are physiological and age differences resulting from the effect of this exposure.
OBJECTIVE: The objective of this study was to identify frequency, severity, and risk factors associated with bronchiolitis in Puerto Rican children. METHODS: A cross-sectional was study performed at 4 emergency departments of Puerto Rico’s metropolitan area, between June 2014 and May 2015. We included children younger than 24 months, with a clinical diagnosis of bronchiolitis, who were born and living in Puerto Rico at the time of recruitment. A physician-administered questionnaire inquiring about the patient’s medical, family, and social history and a bronchiolitis severity assessment were performed. Daily weather conditions were monitored, and aeroallergens were collected with an air sample and precision weather station within the metropolitan area to evaluate environmental factors. RESULTS: We included 600 patients for 12 months. More than 50% of the recruited patients had a previous episode of bronchiolitis, of which 40% had been hospitalized. Older age (odds ratio [OR], 18.3; 95% confidence interval [CI], 9.2-36.5), male sex (OR, 1.6; 95% CI, 1.1-2.4), history of asthma (OR, 8.9; 95% CI, 3.6-22), allergic rhinitis (OR, 3.6; 95% CI, 1.8-7.4), and smoke exposure by a caretaker (OR, 2.3; 95% CI, 1.2-4.4) were predictors of bronchiolitis episodes. Bronchiolitis episodes were associated with higher severity score (P = 0.040), increased number of atopic factors (P < 0.001), and higher number of hospitalizations (P < 0.001). CONCLUSIONS: This study identifies Puerto Rican children who may present a severe clinical course of disease without traditional risk factors. Atopy-related factors are associated with frequency and severity of bronchiolitis. Puerto Rican children present risk factors related to atopy earlier in life, some of which may be modified to prevent the subsequent development of asthma.
Fine particulate matter (PM2.5) raises human health concerns since it can deeply penetrate the respiratory system and enter the bloodstream, thus potentially impacting vital organs. Strong winds transport and disperse PM2.5, which can travel over long distances. Smoke from wildfires is a major episodic and seasonal hazard in Southern California (SoCal), where the onset of Santa Ana winds (SAWs) in early fall before the first rains of winter is associated with the region’s most damaging wildfires. However, SAWs also tend to improve visibility as they sweep haze particles from highly polluted areas far out to sea. Previous studies characterizing PM2.5 in the region are limited in time span and spatial extent, and have either addressed only a single event in time or short time series at a limited set of sites. Here we study the space-time relationship between daily levels of PM2.5 in SoCal and SAWs spanning 1999-2012 and also further identify the impact of wildfire smoke on this relationship. We used a rolling correlation approach to characterize the spatial-temporal variability of daily SAW and PM2.5. SAWs tend to lower PM2.5 levels, particularly along the coast and in urban areas, in the absence of wildfires upwind. On the other hand, SAWs markedly increase PM2.5 in zip codes downwind of wildfires. These empirical relationships can be used to identify windows of vulnerability for public health and orient preventive measures.
Over the last decades, energy and pollution control policies combined with structural changes in the economy decoupled emission trends from economic growth, increasingly also in the developing world. It is found that effective implementation of the presently decided national pollution control regulations should allow further economic growth without major deterioration of ambient air quality, but will not be enough to reduce pollution levels in many world regions. A combination of ambitious policies focusing on pollution controls, energy and climate, agricultural production systems and addressing human consumption habits could drastically improve air quality throughout the world. By 2040, mean population exposure to PM2.5 from anthropogenic sources could be reduced by about 75% relative to 2015 and brought well below the WHO guideline in large areas of the world. While the implementation of the proposed technical measures is likely to be technically feasible in the future, the transformative changes of current practices will require strong political will, supported by a full appreciation of the multiple benefits. Improved air quality would avoid a large share of the current 3-9 million cases of premature deaths annually. At the same time, the measures that deliver clean air would also significantly reduce emissions of greenhouse gases and contribute to multiple UN sustainable development goals. This article is part of a discussion meeting issue ‘Air quality, past present and future’.
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.
The incidence of asthma exacerbation depends on atmospheric conditions, including such meteorological factors as the ambient temperature, relative air humidity or concentration of atmospheric aerosols. An assessment of relations between the frequency of asthma exacerbation and environmental conditions was made according to the meteorological components, the biometeorological index UTCI (Universal Thermal Climate Index), as well as selected air quality parameters, including concentrations of PM(10) and PM(2.5). The study was conducted on the basis of a retrospective analysis of medical data collected at the Independent Public Hospital of Tuberculosis and Pulmonary Diseases in Olsztyn (Poland). Our analysis of patient data (from 1 January 2013 until 31 December 2017) showed a significant correlation between the number of asthma exacerbation and the UTCI value. More frequent asthma exacerbations are observed in patients aged over 65 years when air humidity increases. The UTCI values contained within class 5, describing thermoneutral conditions, correspond to an average frequency of asthma exacerbation. A decline in the UTCI value leads to a reduced number of asthma exacerbation, while a rise makes the cases of asthma exacerbations increase.
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.
The relationship between the fires occurrences and diseases is an essential issue for making public health policy and environment protecting strategy. Thanks to the Internet, today, we have a huge amount of health data and fire occurrence reports at our disposal. The challenge, therefore, is how to deal with 4 Vs (volume, variety, velocity and veracity) associated with these data. To overcome this problem, in this paper, we propose a method that combines techniques based on Data Mining and Knowledge Discovery from Databases (KDD) to discover spatial and temporal association between diseases and the fire occurrences. Here, the case study was addressed to Malaria, Leishmaniasis and respiratory diseases in Brazil. Instead of losing a lot of time verifying the consistency of the database, the proposed method uses Decision Tree, a machine learning-based supervised classification, to perform a fast management and extract only relevant and strategic information, with the knowledge of how reliable the database is. Namely, States, Biomes and period of the year (months) with the highest rate of fires could be identified with great success rates and in few seconds. Then, the K-means, an unsupervised learning algorithms that solves the well-known clustering problem, is employed to identify the groups of cities where the fire occurrences is more expressive. Finally, the steps associated with KDD is perfomed to extract useful information from mined data. In that case, Spearman’s rank correlation coefficient, a nonparametric measure of rank correlation, is computed to infer the statistical dependence between fire occurrences and those diseases. Moreover, maps are also generated to represent the distribution of the mined data. From the results, it was possible to identify that each region showed a susceptible behaviour to some disease as well as some degree of correlation with fire outbreak, mainly in the drought period.
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.
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.
There is a lack of evidence on causal effects of air pollution on gestational age (GA) at delivery. METHODS: Inverse probability weighting (IPW) quantile regression was applied to derive causal marginal population-level GA reduction for GA percentiles associated with increased ambient particulate matter with diameter <2.5 ?m (PM(2.5)) levels at maternal residential address for each trimester and the month preceding delivery using Massachusetts birth registry 2001 to 2015. Stratified analyses were conducted for neonatal sex, maternal age/race/education, and extreme ambient temperature conditions. RESULTS: For neonates at 2.5th, 10th, 25th, 50th, 75th, and 97.5th percentiles of GA at delivery, we estimated an adjusted GA reduction of 4.2 days (95% confidence interval [CI] = 3.4, 5.0), 1.9 days (1.6, 2.1), 1.2 days (1.0, 1.4), 0.82 days (0.72, 0.92), 0.74 days (0.54, 0.94), and 0.54 days (0.15, 0.93) for each 5 ?g/m3 increment in third trimester average PM(2.5) levels. Final gestational month average exposure yielded a similar effect with greater magnitude. Male neonates and neonates of younger (younger than 35 years) and African American mothers as well as with high/low extreme temperature exposure in third trimester were more affected. Estimates were consistently higher at lower GA percentiles, indicating preterm/early-term births being more affected. Low-exposure analyses yielded similar results, restricting to areas with PM(2.5) levels under US ambient annual standard of 12 ?g/m(3). CONCLUSIONS: Prenatal exposure to PM(2.5) in late pregnancy reduced GA at delivery among Massachusetts neonates, especially among preterm/early-term births, male neonates, and neonates of younger and African American mothers. Exposure to extremely high/low temperature amplifies the effect of PM(2.5) on GA.
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).
In October 2017, hundreds of wildfires ravaged the forests of the north and centre of Portugal. The fires were fanned by strong winds as tropical storm Ophelia swept the Iberian coast, dragging up smoke (together with Saharan dust from north-western Africa) into higher western European latitudes. Here we analyse the long-range transport of particulate matter (PM(10)) and study associations between PM(10) and short-term mortality in the Portuguese population exposed to PM(10) due to the October 2017 wildfires, the worst fire sequence in the country over the last decades. We analysed space- and ground-level observations to track the smoke plume and dust trajectory over Portugal and Europe, and to access PM(10) concentrations during the wildfires. The effects of PM(10) on mortality were evaluated using satellite data for exposure and Poisson regression models. The smoke plume covered most western European countries (including Spain, France, Belgium and the Netherlands), and reached the United Kingdom, where the population was exposed in average to an additional PM(10) level of 11.7 µg/m(3) during seven smoky days (three with dust) in relation to the reference days (days without smoke or dust), revealing the impact of the wildfires on distant populations. In Portugal, the population was exposed in average to additional PM(10) levels that varied from 16.2 to 120.6 µg/m(3) in smoky days with dust and from 6.1 to 20.9 µg/m(3) in dust-free smoky days. Results suggest that PM(10) had a significant effect on the same day natural and cardiorespiratory mortalities during the month of October 2017. For every additional 10 µg/m(3) of PM(10), there was a 0.89% (95% confidence interval, CI, 0-1.77%) increase in the number of natural deaths and a 2.34% (95% CI, 0.99-3.66%) increase in the number of cardiorespiratory-related deaths. With rising temperatures and a higher frequency of storms due to climate change, PM from Iberian wildfires together with NW African dust will tend to be more often transported into Northern European countries, which may carry health threats to areas far from the ignition sites.
Mycotoxin-producing Aspergilli (Circumdati, Flavi, and Nigri), usually associated with contaminated food, may also cause respiratory disorders and are insufficiently studied in water-damaged indoor environments. Airborne (N = 71) and dust borne (N = 76) Aspergilli collected at post-flood and control locations in Croatia resulted in eleven different species based on their calmodulin marker: A. ochraceus, A. ostianus, A. pallidofulvus, A. sclerotiorum, and A. westerdijkiae (Circumdati); A. flavus (Flavi); and A. tubingensis, A. welwitschiae, A. niger, A. piperis, and A. uvarum (Nigri). Most of the airborne (73%) and dust borne (54%) isolates were found at post-flood locations, and the highest concentrations measured in indoor air (5720 colony-forming units (CFU)/m(3)) and dust (2.5 × 10(5) CFU/g) were up to twenty times higher than in the control locations. A. flavus dominated among airborne isolates (25%) at the unrepaired locations, while 56% of the dust borne Aspergilli were identified as A. tubingensis and A. welwitschiae. The ability of identified isolates to produce mycotoxins aflatoxin B(1) (AFB(1)), fumonisin B(2) (FB(2)), and ochratoxin A were assessed by LC-MS analysis. All ochratoxin A (OTA)-producing Circumdati belonged to A. westerdijkiae (13.7 ± 15.81 µg/mL); in the section, FlaviA. flavus produced AFB(1) (2.51 ± 5.31 µg/mL), while A. welwitschiae and A. niger (section Nigri) produced FB(2) (6.76 ± 13.51 µg/mL and 11.24 ± 18.30 µg/mL, respectively). Water damage dominantly supported the occurrence of aflatoxigenic A. flavus in indoor environments. Yet unresolved, the causal relationship of exposure to indoor Aspergilli and adverse health effects may support the significance of this research.
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.
Particulate matter (PM), a major component of air pollution, is an important carrier medium of various chemical and microbial compounds. Air pollution due to PM could increase the level of bacteria and associated adverse health effects. Staphylococci as important opportunistic pathogens that cause hospital- and community-acquired infections may transmit through air. This study aimed to obtain knowledge about the concentration of airborne bacteria as well as staphylococci associated with particulate matter with a diameter of less than 2.5 micrometers (PM(2.5)) in ambient air. The impact of meteorological factors including ultraviolet (UV) index, wind speed, temperature, and moisture on microbial concentrations was also investigated. Quartz filters were used to collect PM(2.5) and associated bacteria in ambient air of a semiarid area. Airborne bacteria were quantified by culture method and Staphylococcus species identified by molecular methods. The mean (SD) concentration of PM(2.5) and airborne bacteria was 64.83 (24.87) µg/m(3) and 38 (36) colony forming unit (CFU)/m(3), respectively. The results showed no significant correlation between the levels of PM(2.5) and concentrations of bacteria (p?<?0.05). Staphylococcus species were detected in 8 of 37 (22%) samples in a concentration from 3 to 213 CFU/m(3). S. epidermidis was detected with the highest frequency followed by S. gallinarum and S. hominis, but S. aureus and methicillin-resistant Staphylococcus aureus (MRSA) were not detected. No significant correlation between the concentrations of bacteria with meteorological parameters was observed (p?<?0.05). Our finding showed that, although the study area is sometimes subject to air pollution from PM(2.5), the concentration of PM(2.5)- associated bacteria is relatively low. According to the results, PM(2.5) may not be a source of community-associated staphylococcal infections.
OBJECTIVE: To test the hypothesis that particulate matter with an aerodynamic diameter of less than 10 ?m (PM(10)) and temperature are associated with an increased risk of adverse clinical outcomes in patients with atrial fibrillation (AF) taking vitamin K antagonists (VKAs). PATIENTS AND METHODS: We included patients with AF whose condition was stable while taking VKAs (international normalized ratio, 2.0 to 3.0) for 6 months seen in a tertiary hospital (recruitment from May 1, 2007, to December 1, 2007). During a median follow-up of 6.5 years (interquartile range, 4.3 to 7.9 years), ischemic strokes, major bleeding, adverse cardiovascular events, and mortality were recorded. From 2007 to 2016, data on average temperature and PM(10) were compared with clinical outcomes. RESULTS: The study group included 1361 patients (663 [48.7%] male; median age, 76 years [interquartile range, 71 to 81 years]). High PM(10) and low temperatures were associated with higher risk of major bleeding (adjusted hazard ratio [aHR], 1.44; 95% CI, 1.22 to 1.70 and aHR, 1.03; 95% CI, 1.01 to 1.05, respectively) and mortality (aHR, 1.50; 95% CI, 1.34 to 1.69 and aHR, 1.04; 95% CI, 1.02 to 1.06, respectively); PM(10) was also associated with ischemic stroke and temperature with cardiovascular events. The relative risk (RR) for cardiovascular events and mortality increased in months in the lower quartile of temperature (RR, 1.12; 95% CI, 1.04 to 1.21 and RR, 1.41; 95% CI, 1.15 to 1.74, respectively). Comparing seasons, there were higher risks of cardiovascular events in spring, autumn, and winter than in summer, whereas the risk of mortality increased only in winter. CONCLUSION: In patients with AF taking VKAs, high PM(10) and low temperature were associated with increased risk of ischemic stroke and cardiovascular events, respectively. Both factors increased major bleeding and mortality risks, which were higher during colder months and seasons.
A probe of a patient, seeking help in an emergency ward of a French hospital in late December 2019 because of Influenza like symptoms, was retrospectively tested positive to COVID-19. Despite the early appearance of the virus in Europe, the prevalence and virulence appeared to be low for several weeks, before the spread and severity of symptoms increased exponentially, yet with marked spatial and temporal differences. Here, we compare the possible linkages between peaks of fine particulate matter (PM2.5) and the sudden, explosive increase of hospitalizations and mortality rates in the Swiss Canton of Ticino, and the Greater Paris and London regions. We argue that these peaks of fine particulate matter are primarily occurring during thermal inversion of the boundary layer of the atmosphere. We also discuss the influence of Saharan dust intrusions on the COVID-19 outbreak observed in early 2020 on the Canary Islands. We deem it both reasonable and plausible that high PM2.5 concentrations-favored by air temperature inversions or Saharan dust intrusions-are not only modulating but even more so boosting severe outbreaks of COVID-19. Moreover, desert dust events-besides enhancing PM2.5 concentrations-can be a vector for fungal diseases, thereby exacerbating COVID-19 morbidity and mortality. We conclude that the overburdening of the health services and hospitals as well as the high over-mortality observed in various regions of Europe in spring 2020 may be linked to peaks of PM2.5 and likely particular weather situations that have favored the spread and enhanced the virulence of the virus. In the future, we recommended to monitor not only the prevalence of the virus, but also to consider the occurrence of weather situations that can lead to sudden, very explosive COVID-19 outbreaks.
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.
Fine particulate matter (PM(2.5), aerodynamic diameter ?2.5?µm) impacts the climate, reduces visibility and severely influences human health. The Indo-Gangetic Plain (IGP), home to about one-seventh of the world’s total population and a hotspot of aerosol loading, observes strong enhancements in the PM(2.5) concentrations towards winter. We performed high-resolution (12?km × 12?km) atmospheric chemical transport modeling (WRF-Chem) for the post-monsoon to winter transition to unravel the underlying dynamics and influences of regional emissions over the region. Model, capturing the observed variations to an extent, reveals that the spatial distribution of PM(2.5) having patches of enhanced concentrations (?100 µgm(-3)) during post-monsoon, evolves dramatically into a widespread enhancement across the IGP region during winter. A sensitivity simulation, supported by satellite observations of fires, shows that biomass-burning emissions over the northwest IGP play a crucial role during post-monsoon. Whereas, in contrast, towards winter, a large-scale decline in the air temperature, significantly shallower atmospheric boundary layer, and weaker winds lead to stagnant conditions (ventilation coefficient lower by a factor of ~4) thereby confining the anthropogenic influences closer to the surface. Such changes in the controlling processes from post-monsoon to winter transition profoundly affect the composition of the fine aerosols over the IGP region. The study highlights the need to critically consider the distinct meteorological processes of west-to-east IGP and changes in dominant sources from post-monsoon to winter in the formulation of future pollution mitigation policies.
Background The natural cycle of large-scale wildfires is accelerating, increasingly exposing both rural and populous urban areas to wildfire emissions. While respiratory health effects associated with wildfire smoke are well established, cardiovascular effects have been less clear. Methods and Results We examined the association between out-of-hospital cardiac arrest and wildfire smoke density (light, medium, heavy smoke) from the National Oceanic Atmospheric Association’s Hazard Mapping System. Out-of-hospital cardiac arrest data were provided by the Cardiac Arrest Registry to Enhance Survival for 14 California counties, 2015-2017 (N=5336). We applied conditional logistic regression in a case-crossover design using control days from 1, 2, 3, and 4 weeks before case date, at lag days 0 to 3. We stratified by pathogenesis, sex, age (19-34, 35-64, and >= 65 years), and socioeconomic status (census tract percent below poverty). Out-of-hospital cardiac arrest risk increased in association with heavy smoke across multiple lag days, strongest on lag day 2 (odds ratio, 1.70; 95% CI, 1.18-2.13). Risk in the lower socioeconomic status strata was elevated on medium and heavy days, although not statistically significant. Higher socioeconomic status strata had elevated odds ratios with heavy smoke but null results with light and medium smoke. Both sexes and age groups 35 years and older were impacted on days with heavy smoke. Conclusions Out-of-hospital cardiac arrests increased with wildfire smoke exposure, and lower socioeconomic status appeared to increase the risk. The future trajectory of wildfire, along with increasing vulnerability of the aging population, underscores the importance of formulating public health and clinical strategies to protect those most vulnerable.
Ozone exposure is associated with higher risk of asthma-related emergency department visits. The meteorological conditions that govern ozone concentration are projected to be more favorable to ozone formation over much of the United States due to continued climate change, even as emissions of anthropogenic ozone precursors are expected to decrease by 2050. Our goal is to quantify the health benefits of a climate change mitigation scenario versus a “business-as-usual” scenario, defined by the United Nations Intergovernmental Panel on Climate Change Representative Concentration Pathways (RCPs) 4.5 and 8.5, respectively, using the health impact analytical program Benefits Mapping and Analysis Program – Community Edition (BenMAP – CE) to project the number of asthma ED visits in 2045-2055. We project an annual average of 3100 averted ozone-related asthma ED visits during the 2045-2055 period under RCP4.5 versus RCP8.5, with all other factors held constant, which translates to USD $1.7 million in averted costs annually. We identify counties with tens to hundreds of avoided ozone-related asthma ED visits under RCP4.5 versus RCP8.5. Overall, we project a heterogeneous distribution of ozone-related asthma ED visits at different spatial resolutions, specifically national, regional, and county levels, and a substantial net health and economic benefit of climate change mitigation.
Background Wildfire events are increasing in prevalence in the western United States. Research has found mixed results on the degree to which exposure to wildfire smoke is associated with an increased risk of mortality. Methods We tested for an association between exposure to wildfire smoke and non-traumatic mortality in Washington State, USA. We characterized wildfire smoke days as binary for grid cells based on daily average PM2.5 concentrations, from June 1 through September 30, 2006-2017. Wildfire smoke days were defined as all days with assigned monitor concentration above a PM2.5 value of 20.4 mu g/m(3), with an additional set of criteria applied to days between 9 and 20.4 mu g/m(3). We employed a case-crossover study design using conditional logistic regression and time-stratified referent sampling, controlling for humidex. Results The odds of all-ages non-traumatic mortality with same-day exposure was 1.0% (95% CI: – 1.0 – 4.0%) greater on wildfire smoke days compared to non-wildfire smoke days, and the previous day’s exposure was associated with a 2.0% (95% CI: 0.0-5.0%) increase. When stratified by cause of mortality, odds of same-day respiratory mortality increased by 9.0% (95% CI: 0.0-18.0%), while the odds of same-day COPD mortality increased by 14.0% (95% CI: 2.0-26.0%). In subgroup analyses, we observed a 35.0% (95% CI: 9.0-67.0%) increase in the odds of same-day respiratory mortality for adults ages 45-64. Conclusions This study suggests increased odds of mortality in the first few days following wildfire smoke exposure. It is the first to examine this relationship in Washington State and will help inform local and state risk communication efforts and decision-making during future wildfire smoke events.
Background Wildfires are increasingly a significant source of fine particulate matter (PM2.5), which has been linked to adverse health effects and increased mortality. ESKD patients are potentially susceptible to this environmental stressor. Methods We conducted a retrospective time-series analysis of the association between daily exposure to wildfire PM2.5 and mortality in 253 counties near a major wildfire between 2008 and 2012. Using quasi-Poisson regression models, we estimated rate ratios (RRs) for all-cause mortality on the day of exposure and up to 30 days following exposure, adjusted for background PM2.5, day of week, seasonality, and heat. We stratified the analysis by causes of death (cardiac, vascular, infectious, or other) and place of death (clinical or nonclinical setting) for differential PM2.5 exposure and outcome classification. Results We found 48,454 deaths matched to the 253 counties. A 10-mu g/m(3) increase in wildfire PM2.5 associated with a 4% increase in all-cause mortality on the same day (RR, 1.04; 95% confidence interval [95% CI], 1.01 to 1.07) and 7% increase cumulatively over 30 days following exposure (RR, 1.07; 95% CI, 1.01 to 1.12). Risk was elevated following exposure for deaths occurring in nonclinical settings (RR, 1.07; 95% CI, 1.02 to 1.12), suggesting modification of exposure by place of death. “Other” deaths (those not attributed to cardiac, vascular, or infectious causes) accounted for the largest portion of deaths and had a strong same-day effect (RR, 1.08; 95% CI, 1.03 to 1.12) and cumulative effect over the 30-day period. On days with a wildfire PM2.5 contribution >10 mu g/m(3), exposure accounted for 8.4% of mortality. Conclusions Wildfire smoke exposure was positively associated with all-cause mortality among patients receiving in-center hemodialysis.
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.
Both ozone exposure and extreme temperatures are found to be significantly associated with mortality; however, inconsistent results have been obtained on the modification effects of temperature on the ozone-mortality association. In the present study, we conducted a nationwide time-series analysis in 128 counties from 2013-2018 to examine whether temperature modifies the association between short-term ozone exposure with nonaccidental and cause-specific mortality in China. First, we analyzed the effects of ozone exposure on mortality at different temperature levels. Then, we calculated the pooled effects through a meta-analysis across China. We found that high-temperature conditions (>75th percentile in each county) significantly enhanced the effects of ozone on nonaccidental, cardiovascular, and respiratory mortality, with increases of 0.44% (95% confidence interval (CI): 0.36 and 0.51%), 0.42% (95% CI: 0.32 and 0.51%) and 0.50% (95% CI: 0.31 and 0.68%), respectively, for a 10 ?g/m(3) increase in ozone at high temperatures. Stronger effects on nonaccidental and cardiovascular mortality were observed at high temperatures among elderly individuals aged 65 years and older compared with the younger people. Our findings provide evidence that health damage because of ozone may be influenced by the impacts of increasing temperatures, which point to the importance of mitigating ozone exposure in China under the context of climate change to further reduce the public health burden.
OBJECTIVES: This study investigated the modification of temperature effects on cardiovascular and respiratory mortality by air pollutants (particulate matter less than 2.5 and 10 µm in diameter [respectively], ozone, nitrogen dioxide, carbon monoxide, and sulfur dioxide). METHODS: Poisson additive models with a penalized distributed lag non-linear model were used to assess the association of air temperature with the daily number of deaths from cardiovascular and respiratory diseases in Ahvaz, Iran from March 21, 2014 to March 20, 2018, controlling for day of the week, holidays, relative humidity, wind speed, air pollutants, and seasonal and long-term trends. Subgroup analyses were conducted to evaluate the effect modification for sex and age group. To assess the modification of air pollutants on temperature effects, the level of each pollutant was categorized as either greater than the median value or less than/equal to the median value. RESULTS: We found no significant associations between temperature and cardiovascular and respiratory mortality. In the subgroup analyses, however, high temperatures were significantly associated with an increased risk of cardiovascular mortality among those 75 years old and older, with the strongest effect observed on day 0 relative to exposure. The results revealed a lack of interactive effects between temperature and air pollutants on cardiovascular and respiratory mortality. CONCLUSIONS: A weak but significant association was found between high temperature and cardiovascular mortality, but only in elderly people. Air pollution did not significantly modify the effect of ambient temperature on cardiovascular and respiratory mortality.
Exposure to air pollution is one of the primary global health risk factors, yet individuals lack the knowledge to engage in individual risk mitigation and the skills to mobilize for the change necessary to reduce such risks. News media is an important tool for influencing individual actions and support for public policies to reduce environmental threats; thus, a lack of news coverage of such issues may exacerbate knowledge deficits. This study examines the reporting of health risks and precautionary measures regarding air pollution in national and regional print news. We conducted a content analysis of two national and two local newspapers covering the USA’s most polluted region during a 5-year period. Coders identified information on threat, self-efficacy, protective measures and information sources. Nearly 40% of air pollution news articles mentioned human health risks. Fewer than 10% of news stories about air pollution provided information on the precautionary measures necessary for individuals to take action to mitigate their risk. Local newspapers did not report more threat (X-2= 1.931,p= 0.165) and efficacy (X-2= 1.118,p= 0.209) information. Although air pollution levels are high and continue to rise at alarming rates, our findings suggest that news media reporting is not conducive to raising environmental health literacy.
OBJECTIVE: The aim of this study was to investigate the status of Vitamin D deficiency and the effect of environmental factors on Vitamin D levels so as to provide theoretical support for public health promotion in this region. METHODS: A total of 22,387 subjects who underwent a physical examination at the center in the West China Hospital, Sichuan University, between April, 2018 and May, 2020 were enrolled in this study. Their data on gender, age, inspection date, serum 25 hydroxyvitamin D (25-(OH) D), parathyroid hormone (PTH), and total calcium were retrospectively reviewed. Next, the percentage of Vitamin D status was compared in different sex and age groups, and the fluctuation of Vitamin D level was described in relation to the change of environment. Finally, the univariable and multivariable linear regression analyses were performed to explore the risk and protective factors of Vitamin D deficiency. RESULTS: The proportion of Vitamin D deficiency in this area was 42.17%, and it was significantly higher among women and young people. The fluctuation trend of 25-(OH) D levels are consistent with temperature and solar radiation, and opposite to air quality, in the whole year. There was a positive relationship between 25-(OH) D levels with temperature and solar radiation; however, parathyroid hormone, female and AQI were negatively correlated with Vitamin D levels. CONCLUSION: Vitamin D deficiency is common in subtropic areas, such as Sichuan Basin, which is related to solar radiation and air pollution.
Short-lived climate pollutants (SLCPs) including black carbon (BC), methane (CH4), and tropospheric ozone (O-3) are major climate forcers after carbon dioxide (CO2). These SLCPs also have detrimental impacts on human health and agriculture. Studies show that the Hindu Kush Himalayan (HKH) region, which includes Nepal, has been experiencing the impacts of these pollutants in addition to greenhouse gases. In this study, we derive a national-level emission inventory for SLCPs, CO2, and air pollutants for Nepal and project their impacts under reference (REF) and mitigation policy (POL) scenarios. The impacts on human health, agriculture, and climate were then estimated by applying the following: (1) adjoint coefficients from the Goddard Earth Observing System (GEOS)-chemical transport model that quantify the sensitivity of fine particulate matter (PM2.5) and surface O-3 concentrations in Nepal, and radiative forcing in four latitudinal bands, to emissions in 2 x 2.5 degrees grids, and (2) concentration-response functions to estimate health and crop loss impacts in Nepal. With the mitigating measures undertaken, emission reductions of about 78% each of BC and CH4 and 87% of PM2.5 could be achieved in 2050 compared with the REF scenario. This would lead to an estimated avoidance of 29,000 lives lost and 1.7 million tonnes of crop loss while bringing an economic benefit in present value of 2.7 times more than the total cost incurred in its implementation during the whole period 2010-2050. The results provide useful policy insights and pathways for evidence-based decision-making in the design and effective implementation of SLCP mitigation measures in Nepal.
It is often difficult to define the relationship and the influence of climate on the occurrence and distribution of disease. To examine this issue, the effects of climate indices on the distributions of malaria and meningitis in Nigeria were assessed over space and time. The main purpose of the study was to evaluate the relationships between climatic variables and the prevalence of malaria and meningitis, and develop an early warning system for predicting the prevalence of malaria and meningitis as the climate varies. An early warning system was developed to predetermine the months in a year that people are vulnerable to malaria and meningitis. The results revealed a significant positive relationship between rainfall and malaria, especially during the wet season with correlation coefficient R-2 >= 60.0 in almost all the ecological zones. In the Sahel, Sudan and Guinea, there appears to be a strong relationship between temperature and meningitis with R-2 > 60.0. In all, the results further reveal that temperatures and aerosols have a strong relationship with meningitis. The assessment of these initial data seems to support the finding that the occurrence of meningitis is higher in the northern region, especially the Sahel and Sudan. In contrast, malaria occurrence is higher in the southern part of the study area. We suggest that a thorough investigation of climate parameters is critical for the reallocation of clinical resources and infrastructures in economically underprivileged regions.
The effects of atmospheric black carbon (BC) on climate and public health have been well established, but large uncertainties remain regarding the extent of the impacts of BC at different temporal and spatial scales. These uncertainties are largely due to the heterogeneous nature of BC in terms of its spatiotemporal distribution, mixing state, and coating composition. Here, we seek to further understand the size and mixing state of BC emitted from various sources and aged over different timescales using field measurements in the Los Angeles region. We measured refractory black carbon (rBC) with a single-particle soot photometer (SP2) on Catalina Island, California (similar to 70 km southwest of downtown Los Angeles) during three different time periods. During the first campaign (September 2017), westerly winds were dominant and measured air masses were representative of wellaged background over the Pacific Ocean. In the second and third campaigns (December 2017 and November 2018, respectively), atypical Santa Ana wind conditions allowed us to measure biomass burning rBC (BCbb) from air masses dominated by large biomass burning events in California and fossil fuel rBC (BCff) from the Los Angeles Basin. We observed that the emissions source type heavily influenced both the size distribution of the rBC cores and the rBC mixing state. BCbb had thicker coatings and larger core diameters than BBff. We observed a mean coating thickness (CTBc) of similar to 40-70 nm and a count mean diameter (CMD) of similar to 120 nm for BCbb. For BCff, we observed a CTBc of similar to 5-15 nm and a CMD of similar to 100 nm. Our observations also provided evidence that aging led to an increased CTBc for both BCbb and BCff . Aging timescales < similar to 1 d were insufficient to thickly coat freshly emitted BCff. However, CTBc for aged B-ff within aged background plumes was similar to 35 nm thicker than CTBc for fresh BCff. Likewise, we found that CTBc for aged BCbb was similar to 18 nm thicker than CTBc for fresh BCbb. The results presented in this study highlight the wide variability in the BC mixing state and provide additional evidence that the emissions source type and aging influence rBC microphysical properties.
Central to public health risk communication is understanding the perspectives and shared values among individuals who need the information. Using the responses from a Smoke Sense citizen science project, we examined perspectives on the issue of wildfire smoke as a health risk in relation to an individual’s preparedness to adopt recommended health behaviors. The Smoke Sense smartphone application provides wildfire-related health risk resources and invites participants to record their perspectives on the issue of wildfire smoke. Within the app, participants can explore current and forecasted daily air quality, maps of fire locations, satellite images of smoke plumes, and learn about health consequences of wildfire smoke. We used cluster analysis to identify perspective trait-clusters based on health status, experience with fire smoke, risk perception, self-efficacy, access to exposure-reducing resources, health information needs, and openness to health risk messaging. Differences between traits were examined based on demographics, health status, activity level and engagement with the app. We mapped these traits to the Precaution Adoption Process Model (PAPM) to indicate where each trait lies in adopting recommended health behaviors. Finally, we suggest messaging strategies that may be suitable for each trait. We determined five distinct perspective traits which included individuals who were Protectors and have decided to engage on the issue by adopting new behaviors to protect their health; Cautious, Proactive, and Susceptible individuals who were at a Deciding stage but differed based on risk perceptions and information needs; and the Unengaged who did not perceive smoke as a health issue and were unlikely to change behavior in response to messaging. Across all five traits, the level of engagement and information needs differed substantially, but were not defined by demographics. Individuals in the Susceptible trait had the highest level of engagement and the highest information needs. Messaging that emphasizes self-efficacy and benefits of reducing exposure may be effective in motivating individuals from the deciding stage to taking health protective action. Shared perspectives define an individual’s propensity for acting on recommended health behaviors, therefore, health risk message content should be tailored based on these perspectives.
Environmental hazards increase the health morbidity and mortality burden. This study compared the knowledge and perceptions about the health effects of environmental hazards among medical and engineering students of Hamdard University Karachi. A total of 263 (44.1%) engineering students, and 333 (55.9%) medical students participated in the study. Cumulatively, the three most commonly identified environmental hazards included tobacco smoking 561 (94.1%), global climate change 518 (86.9%), and solar ultraviolet radiation 511 (85.7%). The study results suggest the need for better quantifying the magnitude of understanding environmental hazards, and for health education and promotion programmes at the graduate level for medical and engineering students in Karachi.
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.
BACKGROUND: Daily air quality index (AQI) forecast can provide early warning information, and it is not clear whether it is appropriate for childhood asthma hospitalizations (CAHs). Furthermore, little is known about the effects of AQI on CAHs, as well as the interactions between temperature, humidity and AQI. METHODS: We collected 32,238 cases in Hefei from 2013 to 2016 and estimated the association between daily CAHs and AQI by combining the Poisson Generalized Linear Models (PGLMs) with the Distributed Lag Nonlinear Models (DLNMs). The interaction between AQI and temperature was tested by stratifying AQI and temperature, as well as humidity. RESULTS: AQI was associated with an increased risk of hospitalizations for childhood asthma. The adverse effect first appeared on the 3rd day, with the RR of 1.011 (95%CI: 1.000-1.023) and continued until the 19th day of lag (RR = 1.010, 95%CI: 1.001-1.020). In the subgroup analysis, the male and pre-school children were more sensitive to AQI, and there are seasonal differences in the effects of AQI on CAHs. Besides, in a stratified analysis with an AQI of 150, we found synergies between temperature, humidity and AQI. The interaction relative risk (IRR) and relative excess risk due to interaction (RERI) for the interaction between temperature and AQI were 1.157 (95%CI: 1.029-1.306) and 0.122 (95%CI: 0.022-0.223) respectively. For the humidity, the IRR and RERI were 1.090 (95%CI: 1.056-1.206) and 0.083 (95%CI: 0.083-0.143) respectively. Exploring different subgroups in the interaction analyses, it was worth noting that female and pre-school children were more sensitive to the interaction between AQI and temperature, while school-age children were more sensitive to the interaction between AQI and humidity. CONCLUSIONS: The study found that not only AQI can significantly increase the risk of CAHs, but also that under the context of climate change, temperature and humidity have a synergistic effect on AQI, suggesting that considering only the warning information of air pollution is not enough to strengthen the prevention of childhood asthma hospitalization.
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.
BACKGROUND: Due to variations in climatic conditions, the effects of meteorological factors and PM(2.5) on influenza activity, particularly in subtropical regions, vary in existing literature. In this study, we examined the relationship between influenza activity, meteorological parameters, and PM(2.5) . METHODS: A total of 20 165 laboratory-confirmed influenza cases in Hangzhou, Zhejiang province, were documented in our dataset and aggregated into weekly counts for downstream analysis. We employed a combination of the quasi-Poisson-generalized additive model and the distributed lag non-linear model to examine the relationship of interest, controlling for long-term trends, seasonal trends, and holidays. RESULTS: A hockey-stick association was found between absolute humidity and the risk of influenza infections. The overall cumulative adjusted relative risk (ARR) was statistically significant when weekly mean absolute humidity was low (<10 µg/m(3) ) and high (>17.5 µg/m(3) ). A slightly higher ARR was observed when weekly mean temperature reached over 30.5°C. A statistically significantly higher ARR was observed when weekly mean relative humidity dropped below 67%. ARR increased statistically significantly with increasing rainfall. For PM(2.5) , the ARR was marginally statistically insignificant. In brief, high temperature, wet and dry conditions, and heavy rainfall were the major risk factors associated with a higher risk of influenza infections. CONCLUSIONS: The present study contributes additional knowledge to the understanding of the effects of various environmental factors on influenza activities. Our findings shall be useful and important for the development of influenza surveillance and early warning systems.
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.
Background: Air pollution is a global problem and also linked to respiratory diseases. Wildfire smog is a major cause of air pollution in the upper northern area of Thailand. Thus, in the current study, we examined whether long-term exposure to wildfire smog induces lung function changes in a population from the upper northern area of Thailand. Methods: The lung function of 115 participants with long-term exposure smog was determined using peak flow meter. Results: Long-term smoke exposure participants decreased FEV1 (forced expiratory volume in 1 second)/FVC (forced vital capacity) ratio (56.49 +/- 23.88 in males and 56.29 +/- 28.23 in females) compared with general Thai population. Moreover, the reduction of FVC, FEV1, and peak expiratory flow rate (PEFR) values also showed in both male and female subjects. These results suggest that long-term smoke exposure induces obstructive lung abnormality. Moreover, itchy/watery nose, cough, phlegm, and chest pain also reported in these subjects. Conclusion: Wildfire smog could be induced respiratory pathway inflammation and easily collapsible respiratory airways.
Sand and dust storms in arid and semiarid regions deteriorate regional air quality and threaten public health security. To quantify the negative effects of river dust on regional air quality, this study selected the estuary areas located in central Taiwan as a case study and proposed an integrated framework to measure the fugitive emission of dust from riverbeds with the aid of satellite remote sensing and wind tunnel test, together with the concentrations of particulate matter with a diameter of <10 ?m (PM(10)) around the river system by using The Air Pollution Model. Additionally, the effects of 25 types of meteorological conditions on the health risk due to exposure to dust were evaluated near the estuary areas. The results reveal landscape changes in the downstream areas of Da'an and Dajia rivers, with an increase of 370,820 m(2) and 1,554,850 m(2) of bare land areas in the dry season compared with the wet season in Da'an and Dajia rivers, respectively. On the basis of the maximum emission of river dust, PM(10) concentration increases considerably during both wet and dry seasons near the two rivers. Among 25 different types of weather conditions, frontal surface transit, outer-region circulation from tropical depression system, weak northeast monsoons, and anticyclonic outflow have considerable influence on PM(10) diffusion. In particular, weak northeast monsoons cause the highest health risk in the areas between Da'an and Dajia rivers, which is the densely populated Taichung City. Future studies should attempt to elucidate the environmental impact of dust in different weather conditions and understand the spatial risks to human health due to PM(10) concentration. Facing the increasing threat of climate and landscape changes, governments are strongly encouraged to begin multimedia assessments in environmental management and propose a long-term and systematic framework in resources planning.
Relationships of larger scale meteorological predictors with ground-level daily maximum ozone (O-3max) and daily maximum air temperature (T-max) for stations in Bavaria were analysed. O-3max and T-max as well as threshold exceedances of these variables were assessed under the constraints of ongoing climate change until the end of the twenty-first century. Under RCP8.5 scenario conditions, a substantial increase of T-max in the months from April to September arose, with a mean value of 5 K in the period 2081-2100 compared with the historical period 1986-2005. Statistical downscaling projections pointed to a mean O-3max rise of 17 mu g/m(3). The frequency of threshold exceedances showed also large changes. Hot days may occur in the future at about 30% of all days. Exceedances of O-3max > 100 mu g/m(3) were projected to increase to about 40% of all days at urban traffic sites and up to about 70% in the rural regional background. Days with O-3max > 120 mu g/m(3) occurred still at about 20% of all days at urban traffic sites and at about 45% in rural regional background locations. With respect to combined T-max > 30 degrees C and O-3max > 100 mu g/m(3) events in the future, an occurrence of such events at about 27-29% of all days in the summer months from April to September was assessed. The increases were mainly associated with the strong temperature rise until the end of the century. In summary, the projected T-max and O-3max changes point to a considerable increased health burden in Bavaria until the end of the century, resulting from strong changes of both variables and their associated individual and combined impact on human health.
Air pollution and hot temperatures present two major health risks, especially for vulnerable groups such as children, the elderly, and people with pre-existing conditions. Episodes of high ozone concentrations and heat waves have been registered throughout Europe and are expected to continue to grow due to climate change. Here, several different heat and ozone wave definitions were applied to characterize the wave-type extremes for two climatically different regions, i.e., Portugal (South Europe) and Bavaria (Central Europe), and their impacts were evaluated considering each type of hazard independently but also when they occur simultaneously. Heat and ozone waves were analyzed with respect to the underlying atmospheric circulation patterns and in terms of their association with human mortality. Heat waves were identified as the most frequent wave type and, despite different climate settings, a comparable exposure to heat and ozone waves was found in Central and South Europe. Waves were associated with in-situ built-up as well as with advection of air masses. However, in Bavaria waves showed the strongest connection with autochthonous weather conditions, while for Portugal, the strongest relationship appeared for eastern and north-eastern inflow. The most severe events, as measured by excess mortality, were always associated to compound heat-ozone waves.
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.
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.
Smoke from wildfires contains many air pollutants of concern and epidemiological studies have identified associations between exposure to wildfire smoke PM(2.5) and mortality and respiratory morbidity, and a possible association with cardiovascular morbidity. For this study, a retrospective analysis of air quality modelling was performed to quantify the exposure to wildfire-PM(2.5) across the Canadian population. The model included wildfire emissions from across North America for a 5-month period from May to September (i.e. wildfire season), between 2013 and 2015 and 2017-2018. Large variations in wildfire-PM(2.5) were noted year-to-year, geospatially, and within fire season. The model results were then used to estimate the national population health impacts attributable to wildfire-PM(2.5) and the associated economic valuation. The analysis estimated annual premature mortalities ranging from 54-240 premature mortalities attributable to short-term exposure and 570-2500 premature mortalities attributable to long-term exposure, as well as many non-fatal cardiorespiratory health outcomes. The economic valuation of the population health impacts was estimated per year at $410M-$1.8B for acute health impacts and $4.3B-$19B for chronic health impacts for the study period. The health impacts were greatest in the provinces with populations in close proximity to wildfire activity, though health impacts were also noted across many provinces indicating the long-range transport of wildfire-PM(2.5). Understanding the population health impacts of wildfire smoke is important as climate change is anticipated to increase wildfire activity in Canada and abroad.
OBJECTIVES: To identify key predictors of general practitioner (GP) consultations for allergic rhinitis (AR) using meteorological and environmental data. DESIGN: A retrospective, time series analysis of GP consultations for AR. SETTING: A large GP surveillance network of GP practices in the London area. PARTICIPANTS: The study population was all persons who presented to general practices in London that report to the Public Health England GP in-hours syndromic surveillance system during the study period (3 April 2012 to 11 August 2014). PRIMARY MEASURE: Consultations for AR (numbers of consultations). RESULTS: During the study period there were 186?401 GP consultations for AR. High grass and nettle pollen counts (combined) were associated with the highest increases in consultations (for the category 216-270 grains/m(3), relative risk (RR) 3.33, 95%?CI 2.69 to 4.12) followed by high tree (oak, birch and plane combined) pollen counts (for the category 260-325 grains/m(3), RR 1.69, 95%?CI 1.32 to 2.15) and average daily temperatures between 15°C and 20°C (RR 1.47, 95%?CI 1.20 to 1.81). Higher levels of nitrogen dioxide (NO(2)) appeared to be associated with increased consultations (for the category 70-85?µg/m(3), RR 1.33, 95%?CI 1.03 to 1.71), but a significant effect was not found with ozone. Higher daily rainfall was associated with fewer consultations (15-20?mm/day; RR 0.812, 95% CI 0.674 to 0.980). CONCLUSIONS: Changes in grass, nettle or tree pollen counts, temperatures between 15°C and 20°C, and (to a lesser extent) NO(2) concentrations were found to be associated with increased consultations for AR. Rainfall has a negative effect. In the context of climate change and continued exposures to environmental air pollution, intelligent use of these data will aid targeting public health messages and plan healthcare demand.
Climate policies can bring local air quality and health co-benefits, which may partially or entirely offset the costs of implementing these policies. In this study, we introduce an integrated health co-benefits assessment model, the Regional Emissions-Air quality-Climate-Health (REACH) Modeling Framework, which is capable of evaluating the impact of policies on air pollution-related mortality and morbidity in the whole economic system overtime at the provincial level for China. We first provide a detailed description of the modeling framework and conduct a case study to estimate the health benefits of different climate policy scenarios. We show that a scenario consistent with the 2 degrees C target that peaks China’s emissions before 2025 could avoid around 190 thousand premature deaths in 2030. The health benefits could partially or fully cover the policy costs under different assumptions of the value of a statistical life (VSL). Our framework also illustrates that estimated costs and health benefits distribute unevenly across regions in China.
The flow of the Earth’s atmosphere not only largely determines its temperature status, but also profoundly affects aerosol concentrations. Therefore, exploring how to evaluate the synthetical effects of temperature and aerosol pollution on human health is an important topic. Regarding the atmosphere as a whole, we quantified the mortality burden attributable to short-term exposure to abnormal temperatures and PM2.5 in Beijing from the perspective of atmospheric flow. We first divided the atmospheric stability into three levels (including disturbed, normal, and stable conditions) according to the variations in meteorological conditions and PM2.5 concentrations across the stable weather index levels. We then applied a generalized additive model to separately evaluate the short-term effects of temperature and PM2.5 on mortality under each level of atmospheric stability. We further estimate the associated mortality burden using two indicators, namely attributable fraction and attributable number of deaths. Abnormal temperatures were responsible for most of the mortality burden. Cold temperatures accounted for a substantially higher mortality burden than hot temperatures. The synthetical mortality effects of temperature and PM2.5 varied for different atmospheric stabilities. A stable atmosphere poses the strongest synthetical effects of temperature and PM2.5, while a normal atmosphere provides comparatively beneficial conditions for human health. Our results indicated that the synthetical health impacts of temperature and PM2.5 driven by atmospheric flow need to be considered in the further promulgation of public health policies and air pollution abatement strategies, particularly in the context of climate change.
Background.Exposure to high air temperature in late pregnancy is increasingly recognized as a risk factor for preterm birth (PTB). However, the combined effects of heatwaves with air pollution and green space are still unexplored. In the context of climate change, investigating the interaction between environmental factors and identifying communities at higher risk is important to better understand the etiological mechanisms and design targeted interventions towards certain women during pregnancy.Objectives.To examine the combined effects of heatwaves, air pollution and green space exposure on the risk of PTB.Methods.California birth certificate records for singleton births (2005-2013) were obtained. Residential zip code-specific daily temperature during the last week of gestation was used to create 12 definitions of heatwave with varying temperature thresholds and durations. We fit multi-level Cox proportional hazard models with time to PTB as the outcome and gestational week as the temporal unit. Relative risk due to interaction (RERI) was applied to estimate the additive interactive effect of air pollution and green space on the effect of heatwaves on PTB.Results.In total, 1 967 300 births were included in this study. For PM2.5, PM(10)and O-3, we found positive additive interactions (RERIs >0) between heatwaves and higher air pollution levels. Combined effects of heatwaves and green space indicated negative interactions (RERIs <0) for less intense heatwaves (i.e. shorter duration or relatively low temperature), whereas there were potential positive interactions (RERIs >0) for more intense heatwaves.Conclusion.This study found synergistic harmful effects for heatwaves with air pollution, and potential positive interactions with lack of green space on PTB. Implementing interventions, such as heat warning systems and behavioral changes, targeted toward pregnant women at risk for high air pollution and low green space exposures may optimize the benefits of reducing acute exposure to extreme heat before delivery.
An energy supply dominated by the use of fossil fuels causes both climate change and air pollution, which have negative impacts on human capital via both health and productivity. In addition, different people are affected differently because of factors such as age, gender and education level. To enhance the understanding of the benefits of low carbon transition from the labor supply perspective and help to identify strategies of collaborative control for CO2 and local air pollutants in China, an integrated assessment model linking the air quality module and the health impact module with a disaggregated labor sector computable general equilibrium (CGE) economic system is developed and applied in this study. Results show some key findings. First, renewable energy development and carbon capture and storage (CCS) technologies will contribute significantly to GDP in terms of their impact on air quality improvement by 0.99% and 0.54%, respectively, in 2050. Second, due to differences in labor composition, air pollution has, and will continue to have, the greatest impact on sectors with a higher proportion of male and lower-educated workers – such as the coal sector, and it will have the least impact on sectors with a higher proportion of female and higher-educated workers – such as the public administration sector. Third, the different impacts of sector output will increase economic inequality.
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.
We investigated the geographical character of the COVID-19 infection in China and correlated it with satellite- and ground-based measurements of air quality. Controlling for population density, we found more viral infections in those prefectures (U.S. county equivalent) afflicted by high Carbon Monoxide, Formaldehyde, PM 2.5, and Nitrogen Dioxide values. Higher mortality was also correlated with relatively poor air quality. When summarizing the results at a greater administrative level, we found that the 10 provinces (U.S. state equivalent) with the highest rate of mortality by COVID-19, were often the most polluted but not the most densely populated. Air pollution appears to be a risk factor for the incidence of this disease, despite the conventionally apprehended influence of human mobility on disease dynamics from the site of first appearance, Wuhan. The raw correlations reported here should be interpreted in a broader context, accounting for the growing evidence reported by several other studies. These findings warn communities and policymakers on the implications of long-term air pollution exposure as an ecological, multi-scale public health issue.
OBJECTIVES: There are still controversies about the impact of climatic and environmental factors on thyroid function parameters in healthy populations. We investigated the relationships between climate, air pollution exposure, and thyroid function fluctuations. METHODS: We retrospectively reviewed 327,913 individuals attending routine health checks from December 2013 to December 2018. We analyzed the associations between thyroid function and climatic factors using Spearman’s correlation analysis. We explored the relationships between thyroid function and air pollution exposure using multiple linear regression analysis, after adjusting for age, sex, season, and outdoor temperature. We also performed subgroup analyses by age and sex and sensitivity analyses of different anti-thyroid peroxidase antibody status. RESULTS: Thyroid-stimulating hormone (TSH) and free triiodothyronine (FT3) were negatively associated with outdoor temperature (r?=?-?0.66, P?<?0.001; r?=?-?0.55, P?<?0.001), while free thyroxine (FT4) and FT4/FT3 were positively associated with temperature (r?=?0.35, P?<?0.001; r?=?0.79, P?<?0.001). An increase of 10 ?g/m(3) in fine particulate matter???2.5 ?m (PM2.5) was associated with a decrease of 0.12 pmol/L in FT4 and an increase of 0.07 pmol/L in FT3 (both P?<?0.01). FT4/FT3 was significantly negatively associated with PM2.5 (coefficient: -?0.06, P?<?0.01). These results remained robust in hierarchical analyses and sensitivity analyses. CONCLUSIONS: Thyroid function parameters are associated with climate and air pollution exposure. These factors may influence variations in thyroid function. Our results also highlight the importance of public health interventions to reduce air pollution.
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.
Human actions intensify the greenhouse effect, aggravating climate changes in the Amazon and elsewhere in the world. The Intergovernmental Panel on Climate Change (IPCC) foresees a global increase of up to 4.5 °C and 850 ppm CO(2) (above current levels) by 2100. This will impact the biology of the Aedes aegypti mosquito, vector of Dengue, Zika, urban Yellow Fever and Chikungunya. Heat shock proteins are associated with adaptations to anthropic environments and the interaction of some viruses with the vector. The transcription of the hsp26, hsp83 and hsc70 genes of an A. aegypti population, maintained for more than forty-eight generations, in the Current, Intermediate and Extreme climatic scenario predicted by the IPCC was evaluated with qPCR. In females, highest levels of hsp26, hsp83 and hsc70 expression occurred in the Intermediate scenario, while in males, levels were high only for hsp26 gene in Current and Extreme scenarios. Expression of hsp83 and hsc70 genes in males was low under all climatic scenarios, while in the Extreme scenario females had lower expression than in the Current scenario. The data suggest compensatory or adaptive processes acting on heat shock proteins, which can lead to changes in the mosquito’s biology, altering vectorial competence.
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.
Objectives: Inconsistent results have been found between pneumonia and meteorological factors. We aimed to identify principal meteorological factors associated with pneumonia, and to estimate the effect size and lag time. Methods: This was nationwide population-based study used a healthcare claims database merged with a weather database in eight metropolitan cities in Korea. We applied a stepwise approach using the Granger causality test and generalized additive model to elucidate the association between weekly pneumonia incidence (WPI) and meteorological factors/air pollutants (MFAP). Impulse response function was used to examine the time lag. Results: In total, 2 011 424 cases of pneumonia were identified from 2007 to 2017. Among MFAP, diurnal temperature range (DTR), humidity and particulate matter <= 2.5 mm in diameter (PM2.5) showed statistically significant associations with WPI (p < 0.001 for all 3 MFAPs). The association of DTR and WPI showed an inverted U pattern for bacterial and unspecified pneumonia, whereas for viral pneumonia, WPI increased gradually in a more linear manner with DTR and no substantial decline. Humidity showed a consistent pattern in all three pneumonia categories. WPI steeply increased up to 10 to 20 mu g/m(3) of PM2.5 but did not show a further increase in higher concentrations. On the basis of the result, we examined the effect of MFAP in different lag times up to 3 weeks. Conclusions: DTR, humidity and PM2.5 were identified as MFAP most closely associated with WPI. With the model, we were able to visualize the effectetime association of MFAP and WPI. (C) 2020 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.
Objective: Given the lack of studies examining the associations between daily weather and air pollution with nightly objective sleep over multiple weeks, we quantified these associations in a prospective cohort of healthy participants with episodic migraine. Methods: Ninety-eight participants completed daily electronic diaries and wore an actigraph for an average of 45 ds, and a total 4406 nights of data were collected. Nightly sleep characteristics including duration, wake after sleep onset (WASO), and efficiency were assessed using wrist actigraphy. Daily weather parameters and air pollution levels were collected from local weather station and ground-level air quality monitors. We used linear fixed effects models adjusting for participant, day of the week, and day of the year (for weather analysis), and additionally adjusted for temperature and relative humidity (for air pollution analysis). Results: The participants were 35 +/- 12 yrs old and 86 were women. A 10 degrees F higher daily average temper-ature was associated with 0.88 (95% CI: 0.06, 1.70) minutes longer WASO and 0.14% (95% CI:-0.01%, 0.30%) lower sleep efficiency on that night. A 14 parts per billion (ppb) (interquartile range) higher daily maximum eight-h ozone was associated with 7.51 (95% CI: 3.23, 11.79) minutes longer sleep duration on that night. Associations did not differ between cold (October-March) and warm (April-September) seasons. Conclusions: Higher daily ozone was associated with longer sleep duration and modest associations were observed between higher temperature and lower WASO and lower efficiency. (c) 2020 Elsevier B.V. All rights reserved.
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.
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.
China’s gains in food production over the past four decades have been associated with substantial agricultural nitrogen losses, which contribute to air and water pollution, greenhouse gas emissions and damage to human health. Here, we explore the potential to improve agricultural production practices that simultaneously increase yields while addressing these environmental challenges. We link agronomic research with air quality modelling for an integrated assessment of four improved nitrogen management strategies: improved farm management practices with nitrogen use reductions; machine deep placement of fertilizer; enhanced-efficiency fertilizer use; and improved manure management. We find that simultaneous implementation of the four strategies provides the largest benefits, which include: reductions in PM2.5 concentrations and associated premature deaths; increases in grain yields and grain nitrogen use efficiency; reductions in NO3- leaching and runoff and greenhouse gas emissions. Total benefits of US$30 billion per year exceed the US$18 billion per year in costs. Our findings indicate that policies that improve farmers’ agricultural nitrogen management in China will improve both food security and public health while addressing multiple environmental challenges. Similar increases in attention on agricultural policy around the world are likely to provide large benefits in food security, environmental integrity and public health.
