1. Estimation of High-Resolution PM 2.5 over the Indo-Gangetic Plain by Fusion of Satellite Data, Meteorology, and Land Use Variables.
- Author
-
Mhawish A, Banerjee T, Sorek-Hamer M, Bilal M, Lyapustin AI, Chatfield R, and Broday DM
- Subjects
- Aerosols analysis, Asia, Environmental Monitoring, Meteorology, Particulate Matter analysis, Air Pollutants analysis, Air Pollution analysis
- Abstract
Very high spatially resolved satellite-derived ground-level concentrations of particulate matter with an aerodynamic diameter of less than 2.5 μm (PM
2.5 ) have multiple potential applications, especially in air quality modeling and epidemiological and climatological research. Satellite-derived aerosol optical depth (AOD) and columnar water vapor (CWV), meteorological parameters, and land use data were used as variables within the framework of a linear mixed effect model (LME) and a random forest (RF) model to predict daily ground-level concentrations of PM2.5 at 1 km × 1 km grid resolution across the Indo-Gangetic Plain (IGP) in South Asia. The RF model exhibited superior performance and higher accuracy compared with the LME model, with better cross-validated explained variance ( R2 = 0.87) and lower relative prediction error (RPE = 24.5%). The RF model revealed improved performance metrics for increasing averaging periods, from daily to weekly, monthly, seasonal, and annual means, which supported its use in estimating PM2.5 exposure metrics across the IGP at varying temporal scales (i.e., both short and long terms). The RF-based PM2.5 levels over the middle and lower IGP, with the annual mean exceeding 110 μg/m2.5 levels over the middle and lower IGP, with the annual mean exceeding 110 μg/m3 concentrations of >170 μg/m2.5 concentrations of >170 μg/m3 .- Published
- 2020
- Full Text
- View/download PDF