{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T21:13:13Z","timestamp":1774127593709,"version":"3.50.1"},"reference-count":38,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2016,2,26]],"date-time":"2016-02-26T00:00:00Z","timestamp":1456444800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41275128, 41375063 and 41206163"],"award-info":[{"award-number":["41275128, 41375063 and 41206163"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>High spatial resolution estimating of exposure to particulate matter 2.5 (PM2.5) is currently very limited in China. This study uses the newly released nationwide, hourly PM2.5 concentrations to create a nationwide, geographically weighted regression (GWR) model to estimate ground-level PM2.5 concentrations in China. A3 km resolution aerosol optical depth (AOD) product from MODIS is used as the primary predictor. Fire emissions detected by MODIS fire count were considered in the model development process. Additionally, meteorological features were used as covariates in the model to improve the estimation of ground-level PM2.5 concentrations. The model performed well and explained 81% of the daily PM2.5 concentration variations in model predictions, and the cross validations R2 is 0.79. The cross-validated root mean squared error (RMSE) of the model was 18.6 \u03bcg\/m3.Annual PM2.5 concentrations retrieved by the MODIS 3 km AOD product indicated that most of the residential community areas exceeded the new annual Chinese PM2.5 National Standard level 2. Estimated high-resolution national-scale daily PM2.5 maps are useful to identify severe air pollution episodes and determine health risk assessments. These results suggest that this approach is useful for estimating large-scale ground-level PM2.5 distributions, especially for regions without PM monitoring sites.<\/jats:p>","DOI":"10.3390\/rs8030184","type":"journal-article","created":{"date-parts":[[2016,2,26]],"date-time":"2016-02-26T10:23:39Z","timestamp":1456482219000},"page":"184","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":133,"title":["National-Scale Estimates of Ground-Level PM2.5 Concentration in China Using Geographically Weighted Regression Based on 3 km Resolution MODIS AOD"],"prefix":"10.3390","volume":"8","author":[{"given":"Wei","family":"You","sequence":"first","affiliation":[{"name":"Institute of Meteorology and Oceanography, PLA University of Science and Technology, Nanjing 211101, China"}]},{"given":"Zengliang","family":"Zang","sequence":"additional","affiliation":[{"name":"Institute of Meteorology and Oceanography, PLA University of Science and Technology, Nanjing 211101, China"}]},{"given":"Lifeng","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Meteorology and Oceanography, PLA University of Science and Technology, Nanjing 211101, China"}]},{"given":"Yi","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Meteorology and Oceanography, PLA University of Science and Technology, Nanjing 211101, China"}]},{"given":"Xiaobin","family":"Pan","sequence":"additional","affiliation":[{"name":"Institute of Meteorology and Oceanography, PLA University of Science and Technology, Nanjing 211101, China"}]},{"given":"Weiqi","family":"Wang","sequence":"additional","affiliation":[{"name":"Institute of Meteorology and Oceanography, PLA University of Science and Technology, Nanjing 211101, China"}]}],"member":"1968","published-online":{"date-parts":[[2016,2,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1038\/nature01091","article-title":"A satellite view of aerosols in the climate system","volume":"419","author":"Kaufman","year":"2002","journal-title":"Nature"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1132","DOI":"10.1001\/jama.287.9.1132","article-title":"Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution","volume":"287","author":"Pope","year":"2002","journal-title":"JAMA"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"965","DOI":"10.1289\/ehp.1104660","article-title":"Chronic exposure to fine particles and mortality: An extended follow-up of the Harvard six cities study from 1974 to 2009","volume":"120","author":"Lepeule","year":"2012","journal-title":"Environ. 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