{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T01:03:39Z","timestamp":1773191019058,"version":"3.50.1"},"reference-count":38,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2022,7,14]],"date-time":"2022-07-14T00:00:00Z","timestamp":1657756800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Natural Science Foundation of Hunan Province","award":["2021JJ40022"],"award-info":[{"award-number":["2021JJ40022"]}]},{"name":"Natural Science Foundation of Hunan Province","award":["19B107"],"award-info":[{"award-number":["19B107"]}]},{"name":"Natural Science Foundation of Hunan Province","award":["41871317"],"award-info":[{"award-number":["41871317"]}]},{"name":"Research Foundation of Education Bureau of Hunan Province, China","award":["2021JJ40022"],"award-info":[{"award-number":["2021JJ40022"]}]},{"name":"Research Foundation of Education Bureau of Hunan Province, China","award":["19B107"],"award-info":[{"award-number":["19B107"]}]},{"name":"Research Foundation of Education Bureau of Hunan Province, China","award":["41871317"],"award-info":[{"award-number":["41871317"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2021JJ40022"],"award-info":[{"award-number":["2021JJ40022"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["19B107"],"award-info":[{"award-number":["19B107"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41871317"],"award-info":[{"award-number":["41871317"]}],"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>Fine particulate matter (PM2.5), which can cause adverse human health effects, has been proven as the first air pollutant in China. In situ observations with ground-level monitoring and satellite-based concentrations have been used to analyze the variations in PM2.5. However, variation analyses based on these two kinds of measurement have mainly focused on the concentration itself and ignored the effects on the population. Therefore, this study not only investigated these two kinds of measurements, but also performed weighted population analyses to study the variations in PM2.5. Firstly, daily models of timely structure adaptive modeling (TSAM) were constructed to simulate satellite-derived PM2.5 levels from January 2013 to December 2016. Secondly, population-weighted concentrations were calculated based on TSAM-derived PM2.5 surfaces. Finally, observed, TSAM-derived, and population-weighted concentrations were used to analyze the variations in PM2.5. The results showed the different importance of various input parameters; AOD had the highest rank. Additionally, TSAM models demonstrated good performance, fitting R ranging from 0.86 to 0.91, and validating R from 0.82 to 0.89. According to the air quality standard in China, TSAM-derived PM2.5 showed that the increase in area lower than Level II was 29.03% and the increase in population was only 14.81%. This indicates that the air quality exhibited an overall improvement in spatial perspective, but some areas with high population density showed a relatively low improvement due to uneven distributions in China. The population-weighted PM2.5 concentration could better represent the health threats of air pollutants compared with in situ observations.<\/jats:p>","DOI":"10.3390\/rs14143381","type":"journal-article","created":{"date-parts":[[2022,7,14]],"date-time":"2022-07-14T00:12:40Z","timestamp":1657757560000},"page":"3381","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Analysis of PM2.5 Variations Based on Observed, Satellite-Derived, and Population-Weighted Concentrations"],"prefix":"10.3390","volume":"14","author":[{"given":"Xin","family":"Fang","sequence":"first","affiliation":[{"name":"School of Municipal and Geomatics Engineering, Hunan City University, Yiyang 413000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6238-1820","authenticated-orcid":false,"given":"Shenxin","family":"Li","sequence":"additional","affiliation":[{"name":"School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"}]},{"given":"Liwei","family":"Xiong","sequence":"additional","affiliation":[{"name":"School of Municipal and Geomatics Engineering, Hunan City University, Yiyang 413000, China"}]},{"given":"Bin","family":"Zou","sequence":"additional","affiliation":[{"name":"School of Geosciences and Info-Physics, Central South University, Changsha 410083, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1345","DOI":"10.1016\/S0140-6736(17)32366-8","article-title":"Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990\u20132016: A systematic analysis for the Global Burden of Disease Study 2016","volume":"390","author":"Emmanuela","year":"2017","journal-title":"Lancet"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1038\/nature15371","article-title":"The contribution of outdoor air pollution sources to premature mortality on a global scale","volume":"525","author":"Lelieveld","year":"2017","journal-title":"Nature"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"117002","DOI":"10.1289\/EHP1673","article-title":"Long-term fine particulate matter exposure and nonaccidental and cause-specific mortality in a large national cohort of Chinese men","volume":"125","author":"Yin","year":"2017","journal-title":"Environ. 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