Factors Influencing Spatiotemporal Variability of NO2 Concentration in Urban Area: A GIS and Remote Sensing-Based Approach

Abstract

The growing global attention on urban air quality underscores the need to understand the spatial and temporal dynamics of nitrogen dioxide (NO2), especially in cities like Dhaka (Gazipur), Bangladesh, known for having some of the world's poorest air quality. The present study utilizes the Tropospheric Monitoring Instrument (TROPOMI) on the Sentinel-5P (S5P) satellite and Google Earth Engine (GEE) to analyse NO2 concentrations in Gazipur, Bangladesh, from 2019 to 2022. Utilizing S5P TROPOMI data, we investigate the correlations between NO2 levels and various environmental factors, including land surface temperature (LST), normalized difference vegetation index (NDVI), land use and land cover (LULC), population density, road density, settlement density, and industry density. Our results reveal significant seasonal variations, with peak NO2 levels during pre-monsoon and post-monsoon periods and the lowest levels during monsoon seasons. The study demonstrates a positive correlation between NO2 concentrations and LST, road density, settlement density, and industrial density, and a negative correlation with NDVI. These findings underscore the detrimental impact of rapid urbanization and deforestation on air quality. Through linear regression analysis, we highlight the influence of these environmental factors on NO2 levels, providing a comprehensive understanding of the urban pollution dynamics in a rapidly growing city. This research offers critical insights for policymakers and urban planners, advocating for enhanced green infrastructure, stringent emission controls, and sustainable urban development strategies to mitigate air pollution in Gazipur. Our methodological approach and findings contribute to the broader discourse on urban air quality management in developing countries.