Assessing particulate matter (PM2.5) concentrations and variability across Maharashtra using satellite data and machine learning techniques

Assessing particulate matter (PM2.5) concentrations and variability across Maharashtra using satellite data and machine learning techniques

Abstract Airborne fine particulate matter (PM2.5) is recognized globally as one of the most hazardous air pollutants due to its profound impact on human health, contributing to respiratory and cardiovascular diseases, and increasing the risk of premature mortality. The World Health Organization (WHO...

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Bibliographic Details
Main Authors: Ganesh Machhindra Kunjir, Suvarna Tikle, Sandipan Das, Masud Karim, Sujit Kumar Roy, Uday Chatterjee
Format: Article
Language:English
Published: Springer 2025-04-01
Series:Discover Sustainability
Subjects:
Machine learning
Fine mode aerosol optical depth (FAOD)
Satellite remote sensing
Fine particulate matter (PM2.5)
Online Access:https://doi.org/10.1007/s43621-025-01082-3
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https://doi.org/10.1007/s43621-025-01082-3

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