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 (PM2.5 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 PM2.5 and PM10 were statistically significant (p < 0.1) only for winter. The accuracy of the derived map for PM2.5 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.
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Acknowledgements
The authors sincerely also acknowledge the mission scientist and principal investigator of MODIS MAIAC AOD product (MCD19A2) and land cover product (MCD12Q1) for making the data available used in the present study. Utilization of different climatological data (e.g., wind speed, specific humidity, temperature) and CPCB-based ground observations (PM2.5, PM10) is also sincerely acknowledged. We also acknowledge the Google Earth Engine and Climate Engine for providing cloud-based computing facilities. The authors thank the anonymous reviewers for their constructive and valuable comments and suggestions.
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This research was supported by the Council of Scientific and Industrial Research (CSIR), New Delhi, grant no. 24(0352)/18/EMR-II.
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PK: Conceptualization, Methodology, Validation, Data curation, Writing—review and editing, Visualization. AKR: Conceptualization, Methodology, Software, Validation, Formal analysis, Data curation, Writing—original draft, Visualization. AKG: Conceptualization, Methodology, Validation, Formal analysis, Writing—review and editing, Visualization, Supervision, Project administration. All authors have read and approved the final version of the manuscript for publication.
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Kumar, P., Ranjan, A.K. & Gorai, A.K. Investigations on Aerosol and Particulate Matter Dynamics During 2001–2021 Using Satellite, In Situ, and Reanalysis Datasets over the Mining-Dominated State Odisha, India. Aerosol Sci Eng 8, 87–107 (2024). https://doi.org/10.1007/s41810-023-00208-2
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DOI: https://doi.org/10.1007/s41810-023-00208-2