Impact of Land-Use Pattern on Particulate Matter Pollution in a Mega-City in India

Urbanization is an inevitable attribute associated with modern civilization and development. However, rapid urbanization has led to increase in particulate matter (PM2.5) pollution in several Indian cities. Here, we study Bengaluru, where the city has expanded by 62% from 2001 (457 km2) to 2019 (741 km2), and consequently the PM2.5 is mostly above the limit (40 ug/m3), except for the monsoon season. As the high ambient PM2.5 concentration has an adverse effect on public health, monitoring PM2.5 is key for air quality management. However, the sparse and non-uniform distribution of air quality monitoring stations (AQMSs) poses a hindrance in assessing the air quality in Bengaluru. Therefore, the present study uses satellite-derived aerosol optical depth (AOD), land use, and road density maps together with meteorological parameters to model spatio-temporal PM2.5 levels in Bengaluru using general linear mixed effects regression (GLME) model. The chosen predictors explain about 62% variance in PM2.5. When tenfold cross-validation was performed, relative root mean square error (rRMSE) and relative mean bias error (rMBE) are 37.42% and 19.174%, respectively.