Abstract
Background: Fine particulate matter (PM <2.5µm), key air pollution indicator, affects not just health but also climate and vice versa. Identifying its drivers in megacities is vital for designing interventions. Few studies have explored the variations in PM2.5 and its causes across time and location, including climate and socioeconomic factors.
Method: We adopted a geographically and temporally weighted regression model (GTWR) to explore the direction and strength of the influences of climate change and socioeconomic variables on the concentration of PM2.5 in one of the highest polluted megacities (Lahore), covering the period 1998 to 2020.
Result: Lahore's PM2.5 concentration jumped from an average of 63.4 to 87.5 µg/m3 over 23 years. Among climatic factors, higher windspeed has a strong negative effect (coefficient range: -0.75 to -0.25) and humidity has moderate variable negative to no influence (coefficient range: -0.5 to 0.0) on PM2.5 in the city. Temperature and rainfall had a small mixed (positive and negative) influence, depending on specific locations in the city on PM2.5 (coefficient range: -0.25 to 0.25). Low winter windspeed was the key driver of increased PM2.5. Among socioeconomic factors, road density overall positive association (coefficient range: 0.9 to 0.7), land use has positive and negative association (coefficient range: 0.9 to -0.9), population density primarily has positive association (-0.4 to 0.9), FDI has positive association (coefficient range: 0.7 to 0.9) and GDP has positive association (coefficient range: 0.5 to 0.8) with PM2.5.
Conclusion: Lahore's rising PM2.5 is linked to local emissions due to socioeconomic factors, urban changes, and climatic factors over 23 years. Climate change and socioeconomic factors like windspeed, GDP, and population density all play a role. This model can explain historical and spatial PM2.5 drivers, aiding in designing solutions for Lahore.