Investigations on Aerosol and Particulate Matter Dynamics During 2001–2021 Using Satellite, In Situ, and Reanalysis Datasets over the Mining-Dominated State Odisha, India

Abstract

Investigating the aerosols and particulate matter (PM) dynamics in mining and industrial-dominated regions holds profound significance for understanding air quality, environmental dynamics, and human health. The present study investigates aerosols and PM dynamics in the mining-dominated state Odisha, India. The Moderate Resolution Imaging Spectroradiometer (MODIS)-based Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol product was used to analyze the long-term (2001–2021) annual and seasonal trends using Theil–Sen's slope test. Before trend analysis, MODIS-based AOD was also evaluated with the ground-based observations in the opencast mine site. Furthermore, the multiple regression models were developed to estimate the seasonal spatial distribution of particulate matter (PM_2.5 and PM₁₀) using MODIS-based AOD, ground-based PM, and reanalysis weather datasets. The key findings of the study showed that MODIS-based AOD was moderately correlated with ground-based AOD at daily (r = 0.42, p < 0.01) and monthly (r = 0.60, p < 0.1) time scale with considerable RMSE (0.29 and 0.19, respectively) and MAE (0.22 and 0.15, respectively). The long-term (2001 to 2021) AOD trends analysis exhibited a significantly increasing annual AOD trend (0.047 units/year) over the entire Odisha state. The seasonal trend analysis showed that winter (December–January–February) has the utmost increasing AOD trend (0.056 units/year), followed by the pre-monsoon (March–April–May) (0.055 units/year) and post-monsoon (September–October–November) (0.031 units/year). Besides, the multiple-regression-based models to estimate the seasonal mean spatial distributions of PM_2.5 and PM₁₀ were statistically significant (p < 0.1) only for winter. The accuracy of the derived map for PM_2.5 estimation was relatively better than the PM₁₀ with low RMSE (16.28 µg/m³) and MAE (13.71 µg/m³) values compared to CPCB-based observations. The study's findings contribute to our understanding of regional aerosol and PM dynamics, with potential implications for policy and air quality management in mining and industrial-dominated regions.