Long-term trends and climatic drivers of air pollution in a coastal urbanizing district of south India: Insights from Thrissur (2000-2023)

Abstract

Air pollution is a leading cause of premature deaths globally. Despite this, local studies integrating long-term trends in pollutants and climatic influences remain limited. This is particularly evident in the growing urbanization in tropical regions, such as the Thrissur district in Kerala. This study has examined the evolution of particulate matter (PM) in Thrissur, India, over the last two decades (2000-2023), to determine the relative impacts of weakening atmospheric ventilation and land-use fragmentation. Multi-source satellite reanalysis (Modern-Era Retrospective analysis for Research and Applications, version 2; 0.5 degrees spatial resolution) with high-resolution land cover data (European Space Agency WorldCover, 10 m) was used to analyze meteorological forcings. Long-term trends were quantified using the Mann-Kendall test, and non-linear source attribution was performed using a random forest regression model (R-2 > 0.65). The random forest results were validated against multiple linear regression results to distinguish between non-linear convective forcings and linear climatological trends. Geometric centroid partitioning was applied spatially to quantify the north-south 'source-sink' gradient. The analysis revealed significant climatological discrepancies: increasing trends in fine PM (PM2.5) and black carbon coincided with a concurrent decline in surface wind speeds (Sen's slope is-0.525 units yr(-1), p < 0.01). The study found a reduction in the natural ventilation ('atmospheric stilling'), thus amplifying the retention of local emissions. The geometric partitioning exposed a clear contrast, with the northern 'source' region (urban/ industrial) consistently displaying higher concentrations than the southern 'ecological sink' regions. The findings underscore the pressing need for combined pollution control paired with climate adaptation strategies. This evidence-based study informs policymakers aiming for effective air quality management that combines stricter emissions controls with climate adaptation strategies.