Understand the local and regional contributions on air pollution from the view of human health impacts
* PM 2.5-related deaths were estimated to be 227 thousand in BTH & surrounding regions. * Local emissions contribute more to PM 2.5-related deaths than PM 2.5 concentration. * Local controls are underestimated if only considering its impacts on concentrations. * Rural residents suffer larger imp...
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| Veröffentlicht in: | Frontiers of environmental science & engineering 2021-10, Vol.15 (5), p.88, Article 88 |
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| creator | Jiang, Yueqi Xing, Jia Wang, Shuxiao Chang, Xing Liu, Shuchang Shi, Aijun Liu, Baoxian Sahu, Shovan Kumar |
| description | * PM 2.5-related deaths were estimated to be 227 thousand in BTH & surrounding regions. * Local emissions contribute more to PM 2.5-related deaths than PM 2.5 concentration. * Local controls are underestimated if only considering its impacts on concentrations. * Rural residents suffer larger impacts of regional transport than urban residents. * Reducing regional transport benefits in mitigating environmental inequality.
The source-receptor matrix of PM 2.5 concentration from local and regional sources in the Beijing-Tianjin-Hebei (BTH) and surrounding provinces has been created in previous studies. However, because the spatial distribution of concentration does not necessarily match with that of the population, such concentration-based source-receptor matrix may not fully reflect the importance of pollutant control effectiveness in reducing the PM 2.5-related health impacts. To demonstrate that, we study the source-receptor matrix of the PM 2.5-related deaths instead, with inclusion of the spatial correlations between the concentrations and the population. The advanced source apportionment numerical model combined with the integrated exposure-response functions is used for BTH and surrounding regions in 2017. We observed that the relative contribution to PM 2.5-related deaths of local emissions was 0.75% to 20.77% larger than that of PM 2.5 concentrations. Such results address the importance of local emissions control for reducing health impacts of PM 2.5 particularly for local residents. Contribution of regional transport to PM 2.5-related deaths in rural area was 22% larger than that in urban area due to the spatial pattern of regional transport which was more related to the rural population. This resulted in an environmental inequality in the sense that people staying in rural area with access to less educational resources are subjected to higher impacts from regional transport as compared with their more resourceful and knowledgeable urban compatriots. An unexpected benefit from the multi-regional joint controls is suggested for its effectiveness in reducing the regional transport of PM 2.5 pollution thus mitigating the associated environmental inequality. |
| doi_str_mv | 10.1007/s11783-020-1382-2 |
| format | Article |
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The source-receptor matrix of PM 2.5 concentration from local and regional sources in the Beijing-Tianjin-Hebei (BTH) and surrounding provinces has been created in previous studies. However, because the spatial distribution of concentration does not necessarily match with that of the population, such concentration-based source-receptor matrix may not fully reflect the importance of pollutant control effectiveness in reducing the PM 2.5-related health impacts. To demonstrate that, we study the source-receptor matrix of the PM 2.5-related deaths instead, with inclusion of the spatial correlations between the concentrations and the population. The advanced source apportionment numerical model combined with the integrated exposure-response functions is used for BTH and surrounding regions in 2017. We observed that the relative contribution to PM 2.5-related deaths of local emissions was 0.75% to 20.77% larger than that of PM 2.5 concentrations. Such results address the importance of local emissions control for reducing health impacts of PM 2.5 particularly for local residents. Contribution of regional transport to PM 2.5-related deaths in rural area was 22% larger than that in urban area due to the spatial pattern of regional transport which was more related to the rural population. This resulted in an environmental inequality in the sense that people staying in rural area with access to less educational resources are subjected to higher impacts from regional transport as compared with their more resourceful and knowledgeable urban compatriots. An unexpected benefit from the multi-regional joint controls is suggested for its effectiveness in reducing the regional transport of PM 2.5 pollution thus mitigating the associated environmental inequality.</description><identifier>ISSN: 2095-2201</identifier><identifier>EISSN: 2095-221X</identifier><identifier>DOI: 10.1007/s11783-020-1382-2</identifier><language>eng</language><publisher>Beijing: Higher Education Press</publisher><subject>Air pollution ; Dose-response effects ; Earth and Environmental Science ; Effectiveness ; Emissions control ; Environment ; Environmental inequality ; Fatalities ; Health impact ; Local emissions ; Mathematical models ; Numerical models ; Particulate matter ; PM 2.5 ; Pollution control ; Pollution dispersion ; Receptors ; Regional transport ; Research Article ; Response functions ; Rural areas ; Rural populations ; Spatial distribution ; Urban areas</subject><ispartof>Frontiers of environmental science & engineering, 2021-10, Vol.15 (5), p.88, Article 88</ispartof><rights>Copyright reserved, 2020, Higher Education Press</rights><rights>Higher Education Press 2020</rights><rights>Higher Education Press 2020.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c431t-1461bcd6703c2ee6f73d583f769467a4a3d6f4ea7c8f1de846be1f3b86e1a7803</citedby><cites>FETCH-LOGICAL-c431t-1461bcd6703c2ee6f73d583f769467a4a3d6f4ea7c8f1de846be1f3b86e1a7803</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11783-020-1382-2$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2918744793?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,776,780,21367,27901,27902,33721,41464,42533,43781,51294</link.rule.ids></links><search><creatorcontrib>Jiang, Yueqi</creatorcontrib><creatorcontrib>Xing, Jia</creatorcontrib><creatorcontrib>Wang, Shuxiao</creatorcontrib><creatorcontrib>Chang, Xing</creatorcontrib><creatorcontrib>Liu, Shuchang</creatorcontrib><creatorcontrib>Shi, Aijun</creatorcontrib><creatorcontrib>Liu, Baoxian</creatorcontrib><creatorcontrib>Sahu, Shovan Kumar</creatorcontrib><title>Understand the local and regional contributions on air pollution from the view of human health impacts</title><title>Frontiers of environmental science & engineering</title><addtitle>Front. Environ. Sci. Eng</addtitle><description>* PM 2.5-related deaths were estimated to be 227 thousand in BTH & surrounding regions. * Local emissions contribute more to PM 2.5-related deaths than PM 2.5 concentration. * Local controls are underestimated if only considering its impacts on concentrations. * Rural residents suffer larger impacts of regional transport than urban residents. * Reducing regional transport benefits in mitigating environmental inequality.
The source-receptor matrix of PM 2.5 concentration from local and regional sources in the Beijing-Tianjin-Hebei (BTH) and surrounding provinces has been created in previous studies. However, because the spatial distribution of concentration does not necessarily match with that of the population, such concentration-based source-receptor matrix may not fully reflect the importance of pollutant control effectiveness in reducing the PM 2.5-related health impacts. To demonstrate that, we study the source-receptor matrix of the PM 2.5-related deaths instead, with inclusion of the spatial correlations between the concentrations and the population. The advanced source apportionment numerical model combined with the integrated exposure-response functions is used for BTH and surrounding regions in 2017. We observed that the relative contribution to PM 2.5-related deaths of local emissions was 0.75% to 20.77% larger than that of PM 2.5 concentrations. Such results address the importance of local emissions control for reducing health impacts of PM 2.5 particularly for local residents. Contribution of regional transport to PM 2.5-related deaths in rural area was 22% larger than that in urban area due to the spatial pattern of regional transport which was more related to the rural population. This resulted in an environmental inequality in the sense that people staying in rural area with access to less educational resources are subjected to higher impacts from regional transport as compared with their more resourceful and knowledgeable urban compatriots. An unexpected benefit from the multi-regional joint controls is suggested for its effectiveness in reducing the regional transport of PM 2.5 pollution thus mitigating the associated environmental inequality.</description><subject>Air pollution</subject><subject>Dose-response effects</subject><subject>Earth and Environmental Science</subject><subject>Effectiveness</subject><subject>Emissions control</subject><subject>Environment</subject><subject>Environmental inequality</subject><subject>Fatalities</subject><subject>Health impact</subject><subject>Local emissions</subject><subject>Mathematical models</subject><subject>Numerical models</subject><subject>Particulate matter</subject><subject>PM 2.5</subject><subject>Pollution control</subject><subject>Pollution dispersion</subject><subject>Receptors</subject><subject>Regional transport</subject><subject>Research Article</subject><subject>Response functions</subject><subject>Rural areas</subject><subject>Rural populations</subject><subject>Spatial distribution</subject><subject>Urban areas</subject><issn>2095-2201</issn><issn>2095-221X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp9kF1LwzAUhosoOOZ-gHcBr6s5SdZklzL8goE3DrwLaXuydnRNTTLFf2-2it4tN8kb3ufAebLsGugtUCrvAoBUPKeM5sAVy9lZNmF0Mc8Zg_fzvzeFy2wWwpamo5QAxSeZXfc1-hBNX5PYIOlcZTpySB43retTqFwffVvuY4qBuJ6Y1pPBdd3xh1jvdkf0s8Uv4ixp9jvTkwZNFxvS7gZTxXCVXVjTBZz93tNs_fjwtnzOV69PL8v7VV4JDjEHUUBZ1YWkvGKIhZW8nituZbEQhTTC8LqwAo2slIUalShKBMtLVSAYqSifZjfj3MG7jz2GqLdu79MWQbMFKCmEXPDUgrFVeReCR6sH3-6M_9ZA9cGoHo3qZFQfjGqWGDYyIXX7Dfr_yacgNUJNu2nQYz14DEEnZX1sk_YT6A-okYvb</recordid><startdate>20211001</startdate><enddate>20211001</enddate><creator>Jiang, Yueqi</creator><creator>Xing, Jia</creator><creator>Wang, Shuxiao</creator><creator>Chang, Xing</creator><creator>Liu, Shuchang</creator><creator>Shi, Aijun</creator><creator>Liu, Baoxian</creator><creator>Sahu, Shovan Kumar</creator><general>Higher Education Press</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PATMY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope></search><sort><creationdate>20211001</creationdate><title>Understand the local and regional contributions on air pollution from the view of human health impacts</title><author>Jiang, Yueqi ; Xing, Jia ; Wang, Shuxiao ; Chang, Xing ; Liu, Shuchang ; Shi, Aijun ; Liu, Baoxian ; Sahu, Shovan Kumar</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c431t-1461bcd6703c2ee6f73d583f769467a4a3d6f4ea7c8f1de846be1f3b86e1a7803</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Air pollution</topic><topic>Dose-response effects</topic><topic>Earth and Environmental Science</topic><topic>Effectiveness</topic><topic>Emissions control</topic><topic>Environment</topic><topic>Environmental inequality</topic><topic>Fatalities</topic><topic>Health impact</topic><topic>Local emissions</topic><topic>Mathematical models</topic><topic>Numerical models</topic><topic>Particulate matter</topic><topic>PM 2.5</topic><topic>Pollution control</topic><topic>Pollution dispersion</topic><topic>Receptors</topic><topic>Regional transport</topic><topic>Research Article</topic><topic>Response functions</topic><topic>Rural areas</topic><topic>Rural populations</topic><topic>Spatial distribution</topic><topic>Urban areas</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jiang, Yueqi</creatorcontrib><creatorcontrib>Xing, Jia</creatorcontrib><creatorcontrib>Wang, Shuxiao</creatorcontrib><creatorcontrib>Chang, Xing</creatorcontrib><creatorcontrib>Liu, Shuchang</creatorcontrib><creatorcontrib>Shi, Aijun</creatorcontrib><creatorcontrib>Liu, Baoxian</creatorcontrib><creatorcontrib>Sahu, Shovan Kumar</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Engineering Database</collection><collection>Environmental Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering collection</collection><collection>Environmental Science Collection</collection><jtitle>Frontiers of environmental science & engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jiang, Yueqi</au><au>Xing, Jia</au><au>Wang, Shuxiao</au><au>Chang, Xing</au><au>Liu, Shuchang</au><au>Shi, Aijun</au><au>Liu, Baoxian</au><au>Sahu, Shovan Kumar</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Understand the local and regional contributions on air pollution from the view of human health impacts</atitle><jtitle>Frontiers of environmental science & engineering</jtitle><stitle>Front. Environ. Sci. Eng</stitle><date>2021-10-01</date><risdate>2021</risdate><volume>15</volume><issue>5</issue><spage>88</spage><pages>88-</pages><artnum>88</artnum><issn>2095-2201</issn><eissn>2095-221X</eissn><abstract>* PM 2.5-related deaths were estimated to be 227 thousand in BTH & surrounding regions. * Local emissions contribute more to PM 2.5-related deaths than PM 2.5 concentration. * Local controls are underestimated if only considering its impacts on concentrations. * Rural residents suffer larger impacts of regional transport than urban residents. * Reducing regional transport benefits in mitigating environmental inequality.
The source-receptor matrix of PM 2.5 concentration from local and regional sources in the Beijing-Tianjin-Hebei (BTH) and surrounding provinces has been created in previous studies. However, because the spatial distribution of concentration does not necessarily match with that of the population, such concentration-based source-receptor matrix may not fully reflect the importance of pollutant control effectiveness in reducing the PM 2.5-related health impacts. To demonstrate that, we study the source-receptor matrix of the PM 2.5-related deaths instead, with inclusion of the spatial correlations between the concentrations and the population. The advanced source apportionment numerical model combined with the integrated exposure-response functions is used for BTH and surrounding regions in 2017. We observed that the relative contribution to PM 2.5-related deaths of local emissions was 0.75% to 20.77% larger than that of PM 2.5 concentrations. Such results address the importance of local emissions control for reducing health impacts of PM 2.5 particularly for local residents. Contribution of regional transport to PM 2.5-related deaths in rural area was 22% larger than that in urban area due to the spatial pattern of regional transport which was more related to the rural population. This resulted in an environmental inequality in the sense that people staying in rural area with access to less educational resources are subjected to higher impacts from regional transport as compared with their more resourceful and knowledgeable urban compatriots. An unexpected benefit from the multi-regional joint controls is suggested for its effectiveness in reducing the regional transport of PM 2.5 pollution thus mitigating the associated environmental inequality.</abstract><cop>Beijing</cop><pub>Higher Education Press</pub><doi>10.1007/s11783-020-1382-2</doi></addata></record> |
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| subjects | Air pollution Dose-response effects Earth and Environmental Science Effectiveness Emissions control Environment Environmental inequality Fatalities Health impact Local emissions Mathematical models Numerical models Particulate matter PM 2.5 Pollution control Pollution dispersion Receptors Regional transport Research Article Response functions Rural areas Rural populations Spatial distribution Urban areas |
| title | Understand the local and regional contributions on air pollution from the view of human health impacts |
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