Pollen grains emitted by urban vegetation are the main primary biological airborne particles (PBAPs) which alter the biological quality of urban air and have a significant impact on human health. This work analyses the interactions which exist between pollen-type PBAPs, meteorological variables, and air pollutants in the urban atmosphere so that the complex relationships and trends in future scenarios of changing environmental conditions can be assessed. For this study, the 1992-2018 pollen data series from the city of Granada (southeast Spain) was used, in which the dynamics of the total pollen as well as the 8 main pollen types (Cupressaceae, Olea, Pinus, Platanus, Poaceae, Populus, Quercus and Urticaceae) were analysed. The trend analysis showed that all except Urticaceae trended upward throughout the series. Spearman's correlations with meteorological variables showed that, in general, the most influential variables on the pollen concentrations were the daily maximum temperature, relative humidity, water vapor pressure, global radiation, and insolation, with different effects on different pollen types. Parallel analysis by neural networks (ANN) confirmed these variables as the predominant ones, especially global radiation. The correlation with atmospheric pollutants revealed that ozone was the pollutant with the highest influence, although some pollen types also showed correlation with NO(2), SO(2), CO and PM(10). The Generalized Linear Models (GLM) between pollen and pollutants also indicated O(3) as the most prominent variable. These results highlight the active role that pollen-type PBAPs have on urban air quality by establishing their interactions with meteorological variables and pollutants, thereby providing information on the behaviour of pollen emissions under changing environmental conditions.