{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T06:15:06Z","timestamp":1763705706427,"version":"build-2065373602"},"reference-count":39,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2019,11,13]],"date-time":"2019-11-13T00:00:00Z","timestamp":1573603200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Science and Technology Plan Project of Guangdong Province of China","award":["2017A050506003"],"award-info":[{"award-number":["2017A050506003"]}]},{"name":"NSFC\/RGC","award":["N_HKUST631\/05"],"award-info":[{"award-number":["N_HKUST631\/05"]}]},{"name":"the Fok Ying Tung Graduate School","award":["NRC06\/07.SC01"],"award-info":[{"award-number":["NRC06\/07.SC01"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The Greater Bay Area (GBA) of China is experiencing a high level of exposure to outdoor PM2.5 pollution. The variations in the exposure level are determined by spatiotemporal variations in the PM2.5 concentration and population. To better guide public policies that aim to reduce the population exposure level, it is essential to explicitly decompose and assess the impacts of different factors. This study took advantage of high-resolution satellite observations to characterize the long-term variations in population exposure to outdoor PM2.5 for cities in the GBA region during the three most-recent Five-Year Plan (FYP) periods (2001\u20132015). A new decomposition method was then used to assess the impact of PM2.5 variations and demographic changes on the exposure variation. Within the decomposition framework, an index of pollution-population-coincidence\u2013induced PM2.5 exposure (PPCE) was introduced to characterize the interaction of PM2.5 and the population distribution. The results showed that the 15-year average PPCE levels in all cities were positive (e.g., 6 \u00b5g\/m3 in Guangzhou), suggesting that unfavorable city planning had led to people dwelling in polluted areas. An analyses of the spatial differences in PM2.5 changes showed that urban areas experienced a greater decrease in PM2.5 concentration than did rural areas in most cities during the 11th (2006\u20132010) and 12th (2011\u20132015) FYP periods. These spatial differences in PM2.5 changes reduced the PPCE levels of these cities and thus reduced the exposure levels (by as much as -0.58 \u00b5g\/m3\/year). The population migration resulting from rapid urbanization, however, increased the PPCE and exposure levels (by as much as 0.18 \u00b5g\/m3\/year) in most cities during the three FYP periods considered. Dongguan was a special case in that the demographic change reduced the exposure level because of its rapid development of residential areas in cleaner regions adjacent to Shenzhen. The exposure levels in all cities remained high because of the high mean PM2.5 concentrations and their positive PPCE. To better protect public health, control efforts should target densely populated areas and city planning should locate more people in cleaner areas.<\/jats:p>","DOI":"10.3390\/rs11222646","type":"journal-article","created":{"date-parts":[[2019,11,13]],"date-time":"2019-11-13T09:11:27Z","timestamp":1573636287000},"page":"2646","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Decomposing the Long-term Variation in Population Exposure to Outdoor PM2.5 in the Greater Bay Area of China Using Satellite Observations"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2326-7889","authenticated-orcid":false,"given":"Changqing","family":"Lin","sequence":"first","affiliation":[{"name":"Division of Environment and Sustainability, the Hong Kong University of Science and Technology, Hong Kong, China"},{"name":"Department of Civil and Environmental Engineering, the Hong Kong University of Science and Technology, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3802-828X","authenticated-orcid":false,"given":"Alexis K. H.","family":"Lau","sequence":"additional","affiliation":[{"name":"Division of Environment and Sustainability, the Hong Kong University of Science and Technology, Hong Kong, China"},{"name":"Department of Civil and Environmental Engineering, the Hong Kong University of Science and Technology, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jimmy C. H.","family":"Fung","sequence":"additional","affiliation":[{"name":"Division of Environment and Sustainability, the Hong Kong University of Science and Technology, Hong Kong, China"},{"name":"Department of Mathematics, the Hong Kong University of Science and Technology, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qianshan","family":"He","sequence":"additional","affiliation":[{"name":"Shanghai Meteorological Service, Shanghai 200030, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Ma","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, the Hong Kong University of Science and Technology, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0962-9855","authenticated-orcid":false,"given":"Xingcheng","family":"Lu","sequence":"additional","affiliation":[{"name":"Division of Environment and Sustainability, the Hong Kong University of Science and Technology, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiyuan","family":"Li","sequence":"additional","affiliation":[{"name":"Division of Environment and Sustainability, the Hong Kong University of Science and Technology, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8860-1916","authenticated-orcid":false,"given":"Chengcai","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Renguang","family":"Zuo","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Geological Processes and Mineral Resources, China University of Geosciences, Wuhan 430074, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andromeda H. S.","family":"Wong","sequence":"additional","affiliation":[{"name":"Division of Environment and Sustainability, the Hong Kong University of Science and Technology, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,11,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"669","DOI":"10.1161\/HYPERTENSIONAHA.119.13212","article-title":"Dynamic Changes in Long-Term Exposure to Ambient Particulate Matter and Incidence of Hypertension in Adults","volume":"74","author":"Bo","year":"2019","journal-title":"Hypertension"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"107002","DOI":"10.1289\/EHP3304","article-title":"Long-Term Exposure to Ambient Fine Particulate Matter and Chronic Kidney Disease: A Cohort Study","volume":"126","author":"Chan","year":"2018","journal-title":"Environ. Health Perspect."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"e114","DOI":"10.1016\/S2542-5196(18)30028-7","article-title":"Effect of long-term exposure to fine particulate matter on lung function decline and risk of chronic obstructive pulmonary disease in Taiwan: A longitudinal, cohort study","volume":"2","author":"Guo","year":"2018","journal-title":"Lancet Planet. Health"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"759","DOI":"10.1007\/s00125-019-4825-1","article-title":"Long-term exposure to ambient fine particulate matter (PM2.5) and incident type 2 diabetes: A longitudinal cohort study","volume":"62","author":"Lao","year":"2019","journal-title":"Diabetologia"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"432","DOI":"10.1016\/j.envpol.2018.04.123","article-title":"Long-term exposure to ambient particulate matter (PM2.5) is associated with platelet counts in adults","volume":"240","author":"Zhang","year":"2018","journal-title":"Environ. Pollut."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"8057","DOI":"10.1021\/acs.est.5b01236","article-title":"Addressing Global Mortality from Ambient PM2.5","volume":"49","author":"Apte","year":"2015","journal-title":"Environ. Sci. Technol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.atmosenv.2013.03.012","article-title":"Science\u2013policy interplay: Air quality management in the Pearl River Delta region and Hong Kong","volume":"76","author":"Zhong","year":"2013","journal-title":"Atmos. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.envint.2018.07.042","article-title":"Population-weighted exposure to PM2.5 pollution in China: An integrated approach","volume":"120","author":"Aunan","year":"2018","journal-title":"Environ. Int."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"652","DOI":"10.1021\/es2025752","article-title":"Exposure Assessment for Estimation of the Global Burden of Disease Attributable to Outdoor Air Pollution","volume":"46","author":"Brauer","year":"2012","journal-title":"Environ. Sci. Technol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1029\/2018GH000169","article-title":"Premature Mortality Due to PM2.5 Over India: Effect of Atmospheric Transport and Anthropogenic Emissions","volume":"3","author":"David","year":"2019","journal-title":"GeoHealth"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1289\/ehp.1408646","article-title":"Use of satellite observations for long-term exposure assessment of global concentrations of fine particulate matter","volume":"123","author":"Martin","year":"2015","journal-title":"Environ. Health Perspect."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1125","DOI":"10.1016\/j.envpol.2019.01.056","article-title":"Satellite-derived PM2.5 concentration trends over Eastern China from 1998 to 2016: Relationships to emissions and meteorological parameters","volume":"247","author":"Gui","year":"2019","journal-title":"Environ. Pollut."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1016\/j.jenvman.2018.12.060","article-title":"Health benefit assessment of PM2.5 reduction in Pearl River Delta region of China using a model-monitor data fusion approach","volume":"233","author":"Li","year":"2019","journal-title":"J. Environ. Manag."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1016\/j.envint.2018.11.075","article-title":"Spatiotemporal continuous estimates of PM2.5 concentrations in China, 2000\u20132016: A machine learning method with inputs from satellites, chemical transport model, and ground observations","volume":"123","author":"Xue","year":"2019","journal-title":"Environ. Int."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"105111","DOI":"10.1016\/j.envint.2019.105111","article-title":"Transition in source contributions of PM2.5 exposure and associated premature mortality in China during 2005\u20132015","volume":"132","author":"Zheng","year":"2019","journal-title":"Environ. Int."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"9592","DOI":"10.1073\/pnas.1803222115","article-title":"Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter","volume":"115","author":"Burnett","year":"2018","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.rse.2016.03.023","article-title":"Estimation of long-term population exposure to PM2.5 for dense urban areas using 1-km MODIS data","volume":"179","author":"Lin","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.atmosenv.2012.10.062","article-title":"Emission trends and source characteristics of SO2, NOx, PM10 and VOCs in the Pearl River Delta region from 2000 to 2009","volume":"76","author":"Lu","year":"2013","journal-title":"Atmos. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1289\/ehp.1409481","article-title":"Satellite-Based Spatiotemporal Trends in PM2.5 Concentrations: China, 2004\u20132013","volume":"124","author":"Ma","year":"2016","journal-title":"Environ. Health Perspect."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2355","DOI":"10.4209\/aaqr.2017.11.0437","article-title":"15-Year PM2.5 Trends in the Pearl River Delta Region and Hong Kong from Satellite Observation","volume":"18","author":"Lin","year":"2018","journal-title":"Aerosol Air Qual. Res."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Lin, C., Lau, A.K.H., Lu, X., Fung, J.C.H., Li, Z., Li, C., and Wong, A.H.S. (2018). Assessing Effect of Targeting Reduction of PM2.5 Concentration on Human Exposure and Health Burden in Hong Kong Using Satellite Observation. Remote Sens., 10.","DOI":"10.3390\/rs10122064"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Lin, C.Q., Lau, A.K.H., Li, Y., Fung, J.C.H., Li, C.C., Lu, X.C., and Li, Z.Y. (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_23","doi-asserted-by":"crossref","first-page":"426","DOI":"10.1016\/j.scitotenv.2017.01.027","article-title":"Particulate matter pollution over China and the effects of control policies","volume":"584\u2013585","author":"Wang","year":"2017","journal-title":"Sci. Total Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2990","DOI":"10.1021\/acs.est.8b06358","article-title":"Assessing the Effect of the Long-Term Variations in Aerosol Characteristics on Satellite Remote Sensing of PM2.5 Using an Observation-Based Model","volume":"53","author":"Lin","year":"2019","journal-title":"Environ. Sci. Technol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/j.atmosenv.2016.06.012","article-title":"Assessment of satellite-based aerosol optical depth using continuous lidar observation","volume":"140","author":"Lin","year":"2016","journal-title":"Atmos. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"11670","DOI":"10.1021\/acs.est.5b02776","article-title":"Assessing Long-Term Trend of Particulate Matter Pollution in the Pearl River Delta Region Using Satellite Remote Sensing","volume":"49","author":"Li","year":"2015","journal-title":"Environ. Sci. Technol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2650","DOI":"10.1109\/TGRS.2005.856627","article-title":"Retrieval, validation, and application of the 1-km aerosol optical depth from MODIS measurements over Hong Kong","volume":"43","author":"Li","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1016\/j.rse.2014.09.015","article-title":"Using satellite remote sensing data to estimate the high-resolution distribution of ground-level PM2.5","volume":"156","author":"Lin","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1016\/j.atmosenv.2018.02.045","article-title":"High-resolution satellite remote sensing of provincial PM2.5 trends in China from 2001 to 2015","volume":"180","author":"Lin","year":"2018","journal-title":"Atmos. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1016\/j.rse.2015.05.016","article-title":"Estimating long-term PM2.5 concentrations in China using satellite-based aerosol optical depth and a chemical transport model","volume":"166","author":"Geng","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.rse.2015.12.008","article-title":"Spatiotemporal patterns of remotely sensed PM2.5 concentration in China from 1999 to 2011","volume":"174","author":"Peng","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"847","DOI":"10.1289\/ehp.0901623","article-title":"Global estimates of ambient fine particulate matter concentrations from satellite-based aerosol optical depth: Development and application","volume":"118","author":"Martin","year":"2010","journal-title":"Environ. Health Perspect."},{"key":"ref_33","unstructured":"OECD (2012). Redefining \u201cUrban\u201d: A New Way to Measure Metropolitan Areas, OECD Publishing."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1016\/j.scitotenv.2017.02.029","article-title":"Sources, health effects and control strategies of indoor fine particulate matter (PM2.5): A review","volume":"586","author":"Li","year":"2017","journal-title":"Sci. Total Environ."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"113136","DOI":"10.1016\/j.envpol.2019.113136","article-title":"A feasible experimental framework for field calibration of portable light-scattering aerosol monitors: Case of TSI DustTrak","volume":"255","author":"Li","year":"2019","journal-title":"Environ. Pollut."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1016\/j.envpol.2017.05.039","article-title":"Characterization of PM2.5 exposure concentration in transport microenvironments using portable monitors","volume":"228","author":"Li","year":"2017","journal-title":"Environ. Pollut."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1016\/j.atmosenv.2013.02.033","article-title":"Systematic evaluation of ozone control policies using an Ozone Source Apportionment method","volume":"76","author":"Li","year":"2013","journal-title":"Atmos. Environ."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/j.envpol.2016.01.056","article-title":"Source apportionment and health effect of NOx over the Pearl River Delta region in southern China","volume":"212","author":"Lu","year":"2016","journal-title":"Environ. Pollut."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/j.atmosenv.2013.04.074","article-title":"Reductions in sulfur pollution in the Pearl River Delta region, China: Assessing the effectiveness of emission controls","volume":"76","author":"Wang","year":"2013","journal-title":"Atmos. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/22\/2646\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:33:59Z","timestamp":1760189639000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/22\/2646"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,13]]},"references-count":39,"journal-issue":{"issue":"22","published-online":{"date-parts":[[2019,11]]}},"alternative-id":["rs11222646"],"URL":"https:\/\/doi.org\/10.3390\/rs11222646","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2019,11,13]]}}}