{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:24:42Z","timestamp":1760243082393,"version":"build-2065373602"},"reference-count":48,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2015,6,17]],"date-time":"2015-06-17T00:00:00Z","timestamp":1434499200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Satellite remote sensing offers an effective approach to estimate indicators of air quality on a large scale. It is critically significant for air quality monitoring in areas experiencing rapid urbanization and consequently severe air pollution, like the Pearl River Delta (PRD) in China. This paper starts with examining ground observations of particulate matter (PM) and the relationship between PM10 (particles smaller than 10 \u03bcm) and aerosol optical thickness (AOT) by analyzing observations on the sampling sites in the PRD. A linear regression (R2 = 0.51) is carried out using MODIS-derived 500 m-resolution AOT and PM10 concentration from monitoring stations. Data of atmospheric boundary layer (ABL) height and relative humidity are used to make vertical and humidity corrections on AOT. Results after correction show higher correlations (R2 = 0.55) between extinction coefficient and PM10. However, coarse spatial resolution of meteorological data affects the smoothness of retrieved maps, which suggests high-resolution and accurate meteorological data are critical to increase retrieval accuracy of PM. Finally, the model provides the spatial distribution maps of instantaneous and yearly average PM10 over the PRD. It is proved that observed PM10 is more relevant to yearly mean AOT than instantaneous values.<\/jats:p>","DOI":"10.3390\/rs70607914","type":"journal-article","created":{"date-parts":[[2015,6,17]],"date-time":"2015-06-17T11:19:34Z","timestamp":1434539974000},"page":"7914-7937","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Retrieval of High-Resolution Atmospheric Particulate Matter Concentrations from Satellite-Based Aerosol Optical Thickness over the Pearl River Delta Area, China"],"prefix":"10.3390","volume":"7","author":[{"given":"Lili","family":"Li","sequence":"first","affiliation":[{"name":"State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry,  Chinese Academy of Sciences, Guangzhou 510640, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Jingxue","family":"Yang","sequence":"additional","affiliation":[{"name":"Guangdong Research Institute of Water Resources and Hydropower, Guangzhou 510365, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4164-9677","authenticated-orcid":false,"given":"Yunpeng","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry,  Chinese Academy of Sciences, Guangzhou 510640, China"}]}],"member":"1968","published-online":{"date-parts":[[2015,6,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2229","DOI":"10.1175\/1520-0477(1999)080<2229:RSOTAF>2.0.CO;2","article-title":"Remote sensing of tropospheric aerosols from space: Past, present and future","volume":"80","author":"King","year":"1999","journal-title":"Bull. 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