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Development and validation of improved PM2.5 models for public health applications using remotely sensed aerosol and meteorological data

Authors :
Erica Burrows
William L. Crosson
Mohammad Z. Al-Hamdan
Muhammad Barik
Shane Coffield
Breanna Crane
Source :
Environmental Monitoring and Assessment. 191
Publication Year :
2019
Publisher :
Springer Science and Business Media LLC, 2019.

Abstract

In this study, Moderate Resolution Imaging Spectrometer (MODIS) satellite measurements of aerosol optical depth (AOD) from different retrieval algorithms have been correlated with ground measurements of fine particulate matter less than 2.5 μm (PM2.5). Several MODIS AOD products from different satellites (Aqua vs. Terra), retrieval algorithms (Dark Target vs. Deep Blue), collections (5.1 vs. 6), and spatial resolutions (10 km vs. 3 km) for cities in the Western, Midwestern, and Southeastern USA have been evaluated. We developed and validated PM2.5 prediction models using remotely sensed AOD data. These models were further improved by incorporating meteorological variables (temperature, relative humidity, precipitation, wind gust, and wind direction) from the North American Land Data Assimilation System Phase 2 (NLDAS-2). Adding these meteorological data significantly improved the simulation quality of all the PM2.5 models, especially in the Western USA. Temperature, relative humidity, and wind gust were significant meteorological variables throughout the year in the Western USA. Wind speed was the most significant meteorological variable for the cold season while for the warm season, temperature was the most prominent one in the Midwestern and Southeastern USA. Using this satellite-derived PM2.5 data can improve the spatial coverage, especially in areas where PM2.5 ground monitors are lacking, and studying the connections between PM2.5 and public health concerns including respiratory and cardiovascular diseases in the USA can be further advanced.

Details

ISSN :
15732959 and 01676369
Volume :
191
Database :
OpenAIRE
Journal :
Environmental Monitoring and Assessment
Accession number :
edsair.doi...........94dadc9909902d9efa22d2b100599b78
Full Text :
https://doi.org/10.1007/s10661-019-7414-3