{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T07:11:39Z","timestamp":1784963499913,"version":"3.55.0"},"reference-count":55,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2022,4,2]],"date-time":"2022-04-02T00:00:00Z","timestamp":1648857600000},"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":["41907192"],"award-info":[{"award-number":["41907192"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Civil Aerospace Pre-research Project","award":["D040102"],"award-info":[{"award-number":["D040102"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Particulate matter (PM2.5) is a significant public health concern in China, and the Chinese government has implemented a series of laws, policies, regulations, and standards to improve air quality. This study documents the changes in PM2.5 and evaluates the effects of industrial transformation and clean air policies on PM2.5 levels in urban and suburban areas of China\u2019s three largest urban agglomerations, Beijing\u2013Tianjin\u2013Hebei (BTH), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD) based on a new degree of urbanization classification method. We used high-resolution PM2.5 concentration and population datasets to quantify the differences in PM2.5 concentrations in urban and suburban areas of these three urban agglomerations. From 2000 to 2020, the urban areas have expanded while the suburban areas have shrunk. PM2.5 concentrations in urban areas were approximately 32, 10, and 7 \u03bcg\/m3 higher than those in suburban areas from 2000 to 2020 in BTH, YRD, and PRD, respectively. Since 2013, the PM2.5 concentrations in the urban regions of BTH, YRD, and PRD have declined at average annual rates of 7.30, 5.50, and 5.03 \u03bcg\/m3\/year, respectively, while PM2.5 concentrations in suburban areas have declined at average annual rates of 3.11, 4.23 and 4.69 \u03bcg\/m3\/year, respectively. By 2018, all of the urban and suburban areas of BTH, YRD, and PRD satisfied their specific targets in the Air Pollution and Control Action Plan. By 2020, the PM2.5 declines of BTH, YRD, and PRD exceeded the targets by two, three, and four times, respectively. However, the PM2.5 exposure risks in urban areas are 10\u201320 times higher than those in suburban areas. China will need to implement more robust air pollution mitigation policies to achieve the World Health Organization\u2019s Air Quality Guideline (WHO-AQG) and reduce long-term PM2.5 exposure health risks.<\/jats:p>","DOI":"10.3390\/rs14071716","type":"journal-article","created":{"date-parts":[[2022,4,3]],"date-time":"2022-04-03T06:04:01Z","timestamp":1648965841000},"page":"1716","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Changes in Long-Term PM2.5 Pollution in the Urban and Suburban Areas of China\u2019s Three Largest Urban Agglomerations from 2000 to 2020"],"prefix":"10.3390","volume":"14","author":[{"given":"Lili","family":"Zhang","sequence":"first","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"Zhongke Langfang Institute of Spatial Information Applications, Langfang 065001, China"},{"name":"State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4434-1726","authenticated-orcid":false,"given":"Na","family":"Zhao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8762-1878","authenticated-orcid":false,"given":"Wenhao","family":"Zhang","sequence":"additional","affiliation":[{"name":"North China Institute of Aerospace Engineering, Langfang 065000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5969-0729","authenticated-orcid":false,"given":"John P.","family":"Wilson","sequence":"additional","affiliation":[{"name":"Spatial Sciences Institute, Dornsife College of Letters, Arts, and Sciences, University of Southern California, Los Angeles, CA 90089, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,2]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization (2018). Burden of Disease from Ambient Air Pollution for 2016, World Health Organization."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1038\/sj.jea.7500465","article-title":"PM source apportionment and health effects. 3. Investigation of inter-method variations in associations between estimated source contributions of PM2. 5 and daily mortality in Phoenix, AZ","volume":"16","author":"Mar","year":"2006","journal-title":"J. Expo. Sci. Environ. Epidemiol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"eaav4707","DOI":"10.1126\/sciadv.aav4707","article-title":"Clean air for some: Unintended spillover effects of regional air pollution policies","volume":"5","author":"Fang","year":"2019","journal-title":"Sci. Adv."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.envint.2011.03.003","article-title":"Ambient air pollution, climate change, and population health in China","volume":"42","author":"Kan","year":"2012","journal-title":"Environ. Int."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1186\/1476-069X-12-43","article-title":"Long-term air pollution exposure and cardio- respiratory mortality: A review","volume":"12","author":"Hoek","year":"2013","journal-title":"Environ. Health"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1659","DOI":"10.1016\/S0140-6736(16)31679-8","article-title":"Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990\u20132015: A systematic analysis for the Global Burden of Disease Study 2015","volume":"388","author":"Forouzanfar","year":"2017","journal-title":"Lancet"},{"key":"ref_7","unstructured":"State Council of People\u2019s Republic of China (2013). The Air Pollution Prevention and Control Action Plan 2013, State Council of People\u2019s Republic of China. (In Chinese)."},{"key":"ref_8","unstructured":"State Council of People\u2019s Republic of China (2016). The Thirtieth Five-Year Plan for Ecological Environment Protection, State Council of People\u2019s Republic of China. (In Chinese)."},{"key":"ref_9","first-page":"225","article-title":"Evolution of the spatiotemporal pattern of PM2","volume":"183","author":"Yan","year":"2018","journal-title":"5 concentrations in China\u2013A case study from the Beijing-Tianjin-Hebei region. Atmos. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1436","DOI":"10.1016\/j.jclepro.2017.07.210","article-title":"Inter-regional and sectoral linkage analysis of air pollution in Beijing\u2013Tianjin\u2013Hebei (Jing-Jin-Ji) urban agglomeration of China","volume":"165","author":"Wang","year":"2017","journal-title":"J. Clean. Prod."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"11031","DOI":"10.5194\/acp-19-11031-2019","article-title":"Fine particulate matter (PM2.5) trends in China, 2013\u20132018: Separating contributions from anthropogenic emissions and meteorology","volume":"19","author":"Zhai","year":"2019","journal-title":"Atmos. Chem. Phys."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.jclepro.2018.03.290","article-title":"Direct and spillover effects of urbanization on PM2.5 concentrations in China\u2019s top three urban agglomerations","volume":"190","author":"Du","year":"2018","journal-title":"J. Clean. Prod."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Fang, C., and Yu, D. (2016). China\u2019s New Urbanization: Developmental Paths, Blueprints and Patterns, Springer.","DOI":"10.1007\/978-3-662-49448-6"},{"key":"ref_14","unstructured":"State Council of People\u2019s Republic of China (2014). New National Urbanization Plan (2014\u20132020), State Council of People\u2019s Republic of China. (In Chinese)."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1038\/509158a","article-title":"Society: Realizing China\u2019s Urban Dream","volume":"509","author":"Bai","year":"2014","journal-title":"Nature"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"426","DOI":"10.1016\/j.partic.2009.09.003","article-title":"Aerosol pollution in China: Present and future impact on environment","volume":"7","author":"Tie","year":"2009","journal-title":"Particuology"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"5685","DOI":"10.5194\/acp-13-5685-2013","article-title":"Analysis of a winter regional haze event and its formation mechanism in the North China Plain","volume":"13","author":"Zhao","year":"2013","journal-title":"Atmos. Chem. Phys."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.atmosenv.2016.08.060","article-title":"Characteristics of PM2.5 concentrations across Beijing during 2013\u20132015","volume":"145","author":"Batterman","year":"2016","journal-title":"Atmos. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/j.atmosenv.2015.08.040","article-title":"Diurnal, weekly and monthly spatial variations of air pollutants and air quality of Beijing","volume":"119","author":"Chen","year":"2015","journal-title":"Atmos. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Wu, J., Xie, W., Li, W., and Li, J. (2015). Effects of Urban Landscape Pattern on PM2.5 Pollution\u2014A Beijing Case Study. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0142449"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"23604","DOI":"10.1038\/srep23604","article-title":"Fine particulate (PM2.5) dynamics during rapid urbanization in Beijing, 1973\u20132013","volume":"6","author":"Han","year":"2016","journal-title":"Sci. Rep."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"362","DOI":"10.1016\/j.atmosenv.2015.08.053","article-title":"Long-term trend and spatiotemporal variations of haze over China by satellite observations from 1979 to 2013","volume":"119","author":"Zhang","year":"2015","journal-title":"Atmos. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"842","DOI":"10.5094\/APR.2015.093","article-title":"Characterizing spatial distribution and temporal variation of PM10 and PM2.5 mass concentrations in an urban area of Southwest China","volume":"6","author":"Huang","year":"2015","journal-title":"Atmos. Pollut. Res."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"13585","DOI":"10.5194\/acp-15-13585-2015","article-title":"Spatial and temporal variations of the concentrations of PM10, PM2.5 and PM1 in China","volume":"15","author":"Wang","year":"2015","journal-title":"Atmos. Chem. Phys."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"13431","DOI":"10.1021\/acs.est.5b03614","article-title":"Spatiotemporal Characterization of Ambient PM2.5 Concentrations in Shandong Province (China)","volume":"49","author":"Yang","year":"2015","journal-title":"Environ. Sci. Technol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"13161","DOI":"10.1021\/acs.est.7b03468","article-title":"Visibility-based PM2.5 concentrations in China: 1957\u20131964 and 1973\u20132014","volume":"51","author":"Liu","year":"2017","journal-title":"Environ. Sci. Technol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.envpol.2014.07.022","article-title":"Impact of urbanization level on urban air quality: A case of fine particles (PM2.5) in Chinese cities","volume":"194","author":"Han","year":"2014","journal-title":"Environ. Pollut."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.envpol.2015.06.038","article-title":"City as a major source area of fine particulate (PM2.5) in China","volume":"206","author":"Han","year":"2015","journal-title":"Environ. Pollut."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"14884","DOI":"10.1038\/srep14884","article-title":"Fine particulate matter (PM2.5) in China at a city level","volume":"5","author":"Zhang","year":"2015","journal-title":"Sci. Rep."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"9665","DOI":"10.1007\/s11356-014-2996-3","article-title":"Spatiotemporal distribution and short-term trends of particulate matter concentration over China, 2006\u20132010","volume":"21","author":"Yao","year":"2014","journal-title":"Environ. Sci. Pollut. Res."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"e2020GL091160","DOI":"10.1029\/2020GL091160","article-title":"Quantifying CO2 Uptakes Over Oceans Using LIDAR: A Tentative Experiment in Bohai Bay","volume":"48","author":"Shi","year":"2021","journal-title":"Geophys. Res. Lett."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"140879","DOI":"10.1016\/j.scitotenv.2020.140879","article-title":"Response of major air pollutants to COVID-19 lockdowns in China","volume":"743","author":"Pei","year":"2020","journal-title":"Sci. Total Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.atmosres.2017.08.023","article-title":"Temporal and spatial analyses of particulate matter (PM10 and PM2.5) and its relationship with meteorological parameters over an urban city in northeast China","volume":"198","author":"Li","year":"2017","journal-title":"Atmos. Res."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Lou, C.-R., Liu, H.-Y., Li, Y.-F., and Li, Y.-L. (2016). Socioeconomic Drivers of PM2.5 in the Accumulation Phase of Air Pollution Episodes in the Yangtze River Delta of China. Int. J. Environ. Res. Public Health, 13.","DOI":"10.3390\/ijerph13100928"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.atmosenv.2007.09.003","article-title":"Air pollution in mega cities in China","volume":"42","author":"Chan","year":"2008","journal-title":"Atmos. Environ."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1016\/j.atmosenv.2013.05.029","article-title":"Characterization of parameters influencing the spatio-temporal variability of urban particle number size distributions in four European cities","volume":"77","author":"Birmili","year":"2013","journal-title":"Atmos. Environ."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2893","DOI":"10.1016\/j.atmosenv.2009.03.009","article-title":"Seasonal and diurnal variations of ambient PM2.5 concentration in urban and rural environments in Beijing","volume":"43","author":"Zhao","year":"2009","journal-title":"Atmos. Environ."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Lin, C., Lau, A.K.H., Li, Y., Fung, J.C.H., Li, C., Lu, X., and Li, Z. (2018). Difference in PM2.5 Variations between Urban and Rural Areas over Eastern China from 2001 to 2015. Atmosphere, 9.","DOI":"10.3390\/atmos9080312"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"103312","DOI":"10.1016\/j.jue.2020.103312","article-title":"Applying the Degree of Urbanisation to the globe: A new harmonised definition reveals a different picture of global urbanisation","volume":"125","author":"Dijkstra","year":"2021","journal-title":"J. Urban Econ."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"105862","DOI":"10.1016\/j.envint.2020.105862","article-title":"The changing PM2.5 dynamics of global megacities based on long-term remotely sensed observations","volume":"142","author":"Zhang","year":"2020","journal-title":"Environ. Int."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"3273","DOI":"10.5194\/acp-20-3273-2020","article-title":"Improved 1 km resolution PM2.5 estimates across China using enhanced space\u2013time extremely randomized trees","volume":"20","author":"Wei","year":"2020","journal-title":"Atmos. Chem. Phys."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"112136","DOI":"10.1016\/j.rse.2020.112136","article-title":"Reconstructing 1-km-resolution high-quality PM2. 5 data records from 2000 to 2018 in China: Spatiotemporal variations and policy implications","volume":"252","author":"Wei","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_43","unstructured":"Center for International Earth Science Information Network\u2014CIESIN\u2014Columbia University (2016). Documentation for the Gridded Population of the World, Version 4 (GPWv4), NASA Socioeconomic Data and Applications Center (SEDAC). Available online: https:\/\/sedac.ciesin.columbia.edu\/data\/collection\/gpw-v4\/documentation."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"226","DOI":"10.1080\/23754931.2015.1014272","article-title":"Taking advantage of the improved availability of census data: A first look at the gridded population of the world, version 4","volume":"1","author":"MacManus","year":"2015","journal-title":"Pap. Appl. Geogr."},{"key":"ref_45","unstructured":"ESRI (2021, March 04). Performing Sensitivity Analysis. Available online: http:\/\/webhelp.esri.com\/arcgisdesktop\/9.2\/index.cfm?TopicName=Performing_sensitivity_analysis."},{"key":"ref_46","first-page":"1","article-title":"Spatial-temporal pattern of population exposure risk to PM2.5 in China","volume":"40","author":"Zhang","year":"2020","journal-title":"China Environ. Sci."},{"key":"ref_47","first-page":"1","article-title":"A harmonised definition of cities and rural areas: The new degree of urbanisation. European Comission Directorate-General for Regional and Urban Policy","volume":"1","author":"Dijkstra","year":"2014","journal-title":"Reg. Work. Pap."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"756","DOI":"10.1016\/j.scib.2019.04.024","article-title":"40-Year (1978\u20132017) human settlement changes in China reflected by impervious surfaces from satellite remote sensing","volume":"64","author":"Gong","year":"2019","journal-title":"Sci. Bull."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"105776","DOI":"10.1016\/j.envint.2020.105776","article-title":"Changes in spatial patterns of PM2.5 pollution in China 2000\u20132018: Impact of clean air policies","volume":"141","author":"Xiao","year":"2020","journal-title":"Environ. Int."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/j.rse.2014.03.004","article-title":"A cluster-based method to map urban area from DMSP\/OLS nightlights","volume":"147","author":"Zhou","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Wang, S., Sun, P., Sun, F., Jiang, S., Zhang, Z., and Wei, G. (2021). The Direct and Spillover Effect of Multi-Dimensional Urbanization on PM2.5 Concentrations: A Case Study from the Chengdu-Chongqing Urban Agglomeration in China. Int. J. Environ. Res. Public. Health., 18.","DOI":"10.3390\/ijerph182010609"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"6861","DOI":"10.5194\/acp-19-6861-2019","article-title":"Effects of air pollution control policies on PM2.5 pollution improvement in China from 2005 to 2017: A satellite-based perspective","volume":"19","author":"Ma","year":"2019","journal-title":"Atmos. Chem. Phys."},{"key":"ref_53","unstructured":"State Council of People\u2019s Republic of China (2017). Guidelines on Promoting the Relocation and Transformation of Hazardous Chemical Production Enterprises in Densely Populated Areas, State Council of People\u2019s Republic of China. (In Chinese)."},{"key":"ref_54","unstructured":"World Health Organization, and WHO European Centre for Environment (2021). W.E.C.F. Environment. WHO Global Air Quality Guidelines: Particulate Matter (PM2.5 and PM10), Ozone, Nitrogen Dioxide, Sulfur Dioxide and Carbon Monoxide, World Health Organization."},{"key":"ref_55","unstructured":"World Health Organization (2006). Air Quality Guidelines: Global Update 2005: Particulate Matter, Ozone, Nitrogen Dioxide, and Sulfur Dioxide, World Health Organization."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/7\/1716\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:48:51Z","timestamp":1760136531000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/7\/1716"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,2]]},"references-count":55,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2022,4]]}},"alternative-id":["rs14071716"],"URL":"https:\/\/doi.org\/10.3390\/rs14071716","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4,2]]}}}