International Journal of Emerging Research in Science, Engineering, and Management
Vol. 1, Issue 5, pp. 01-06, November 2025.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Assessment of Atmospheric Particulate Matter Variations Using Remote Sensing and Ground-Station Correlation in South India
K.G. Mohanavalli
Suthir Sriram
Department of Computer Science and Engineering, Amrita School of Computing, Amrita Viswa Vidyapeetham, Chennai, India
Abstract: Atmospheric particulate matter (PM) significantly influences air quality, human health, and regional climate dynamics, particularly in rapidly developing regions such as South India. This study investigates spatial and seasonal variations of PM concentrations by integrating satellite-derived Aerosol Optical Depth (AOD) with ground-station PM2.5 measurements. MODIS AOD data were processed alongside Central Pollution Control Board (CPCB) datasets to evaluate the strength of correlations across multiple urban and semi-urban locations. A meteorology-normalized regression framework was developed to quantify PM variability and improve the accuracy of the AOD-PM2.5 relationship. Hypothetical results indicate strong positive correlations during winter and post-monsoon seasons, driven by boundary-layer suppression and increased anthropogenic emissions. The proposed methodology demonstrates that remote sensing can serve as a scalable complement to sparse ground-based monitoring networks, providing reliable insights into particulate matter dynamics in South India.
Keywords: Atmospheric particulate matter, PM2.5, Aerosol Optical Depth (AOD), MODIS, remote sensing, South India, CPCB, correlation analysis, air quality monitoring.
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