A hybrid approach for integrating micro-satellite images and sensors network-based ground measurements using deep learning for high-resolution prediction of fine particulate matter (PM2.5) over an indian city, lucknow
Jain V, Mukherjee A, Banerjee S, Madhwal S, Bergin M, Bhave P, Carlson D, Jiang Z, Zheng T, Rai P, Tripathi S. A hybrid approach for integrating micro-satellite images and sensors network-based ground measurements using deep learning for high-resolution prediction of fine particulate matter (PM2.5) over an indian city, lucknow. Atmospheric Environment 2024, 338: 120798. DOI: 10.1016/j.atmosenv.2024.120798.Peer-Reviewed Original ResearchFine particulate matterGround-based measurementsPM2.5 concentrationsParticulate matterPredictions of fine particulate matterPrediction mapsAmbient air quality monitoring networkImpact of fine particulate matterAir quality monitoring networkSources of PM2.5Estimate PM2.5 concentrationsPM2.5 exposure assessmentGround measurementsQuality monitoring networkDeterminants of PM2.5Satellite-based estimatesDaily PM2.5High-resolution predictionPM2.5Monitoring networkLowest root mean square errorHuman healthPost-monsoonExposure assessmentRoot mean square error