Analyzing Temporal Aerosol Distribution over Pakistan Using MODIS Data and Their Socio-Economic Impacts

In this investigation, we analyze the long-term determinants of aerosol pollution utilizing nationally accessible data from Pakistan on a provincial scale, spanning the years 2000 to 2022. This study employs aerosol optical depth (AOD) data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) as a proxy indicator for particulate matter present in the atmosphere. It integrates satellite-derived environmental data with socio-economic and meteorological variables, including GDP per capita, levels of industrialization, population density, temperature, precipitation, and wind direction, to furnish a comprehensive assessment of both anthropogenic and natural influences on aerosol dispersion. Furthermore, the CS-ARDL model, accompanied by tests for cross-sectional dependence, slope heterogeneity, and cointegration, is utilized within the analysis. Additionally, it elucidates both long-term and short-term relationships among the variables under consideration. The findings of this research reveal that AOD is significantly influenced by economic growth, industrial output, and population density. This underscores the detrimental implications of Pakistan's developmental trajectory on environmental quality. Nevertheless, there exists a mitigating effect of variables such as precipitation and temperature, which serve as significant meteorological determinants of aerosol concentration. Conversely, wind direction emerges as a prominent spatial factor, potentially attributable to the translocation of pollutants across various regions. Furthermore, resistance analyses conducted on generalized method of moments (GMM) regression reveal that the findings exhibit a remarkable degree of consistency. This research addresses a notable deficiency in the empirical literature concerning the correlation between environmental degradation in developing nations and remote sensing data through the application of econometric modeling. Additionally, the study offers pertinent policy recommendations for decision-makers, as it underscores the imperative for regionally adaptive, seasonally responsive, and environmentally sustainable development and planning practices. In this context, it provides an evidence-based foundation for the formulation of substantiated air quality management strategies and sustainable development measures to be implemented throughout Pakistan.