Premature Mortality Associated with Exposure to Outdoor Black Carbon and Its Source Contributions in China. Wang, Y., Li, X., Shi, Z., Huang, L., Li, J., Zhang, H., Ying, Q., Wang, M., Ding, D., Zhang, X., & Hu, J. RESOURCES CONSERVATION AND RECYCLING, ELSEVIER, RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS, JUL, 2021. doi abstract bibtex Epidemiological studies have shown that outdoor black carbon (BC) has higher health risks than other constituents and the total fine particulate matter (PM2.5). In this study, we estimated premature mortality attributed to BC in China in 2013 using a health impact model combined with annual average BC concentrations predicted using the Community Multi-scale Air Quality model. Source contributions to BC from six different source sectors were estimated using the source-oriented method, including residential, industrial, transportation, open burning, power, and other sources. The sensitivity of BC-related premature mortality to emission reductions in different sources was quantified in different regions of China. The results showed that the total all-cause premature mortality related to BC was approximately 1,436,957 (95% CI: 998,746-2,029,210) in China in 2013. Residential, industrial, and transportations sources were the three main sources of BC-induced premature mortality. Central China, Yangtze River Delta, and Sichuan Basin had the highest BC-induced mortality due to a high level of emissions and a dense population. A sensitivity test by assuming the same exposure-response coefficient of BC as the total PM2.5 showed the number of deaths was 265,122 thousand (95% CI: 541,90, 445,943) which can be treated as the lower limit of the BC-related mortality in China. Despite the uncertainties in estimates, it is suggested that reducing BC emissions in China would lead to significant health benefits. Controlling BC from industrial and transportation sources would bring more relative mortality reductions, from a percentage point of view, in most provinces of China.
@article{ WOS:000667309200053,
Author = {Wang, Yiyi and Li, Xun and Shi, Zhihao and Huang, Lin and Li, Jingyi and
Zhang, Hongliang and Ying, Qi and Wang, Meng and Ding, Deping and Zhang,
Xiaoling and Hu, Jianlin},
Title = {{Premature Mortality Associated with Exposure to Outdoor Black Carbon and
Its Source Contributions in China}},
Journal = {{RESOURCES CONSERVATION AND RECYCLING}},
Year = {{2021}},
Volume = {{170}},
Month = {{JUL}},
Abstract = {{Epidemiological studies have shown that outdoor black carbon (BC) has
higher health risks than other constituents and the total fine
particulate matter (PM2.5). In this study, we estimated premature
mortality attributed to BC in China in 2013 using a health impact model
combined with annual average BC concentrations predicted using the
Community Multi-scale Air Quality model. Source contributions to BC from
six different source sectors were estimated using the source-oriented
method, including residential, industrial, transportation, open burning,
power, and other sources. The sensitivity of BC-related premature
mortality to emission reductions in different sources was quantified in
different regions of China. The results showed that the total all-cause
premature mortality related to BC was approximately 1,436,957 (95\% CI:
998,746-2,029,210) in China in 2013. Residential, industrial, and
transportations sources were the three main sources of BC-induced
premature mortality. Central China, Yangtze River Delta, and Sichuan
Basin had the highest BC-induced mortality due to a high level of
emissions and a dense population. A sensitivity test by assuming the
same exposure-response coefficient of BC as the total PM2.5 showed the
number of deaths was 265,122 thousand (95\% CI: 541,90, 445,943) which
can be treated as the lower limit of the BC-related mortality in China.
Despite the uncertainties in estimates, it is suggested that reducing BC
emissions in China would lead to significant health benefits.
Controlling BC from industrial and transportation sources would bring
more relative mortality reductions, from a percentage point of view, in
most provinces of China.}},
Publisher = {{ELSEVIER}},
Address = {{RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Hu, JL (Corresponding Author), Nanjing Univ Informat Sci \& Technol, Jiangsu Collaborat Innovat Ctr Atmospher Environm, Jiangsu Key Lab Atmospher Environm Monitoring \& P, Nanjing 210044, Peoples R China.
Wang, Yiyi; Li, Xun; Shi, Zhihao; Huang, Lin; Li, Jingyi; Hu, Jianlin, Nanjing Univ Informat Sci \& Technol, Jiangsu Collaborat Innovat Ctr Atmospher Environm, Jiangsu Key Lab Atmospher Environm Monitoring \& P, Nanjing 210044, Peoples R China.
Zhang, Hongliang, Fudan Univ, Dept Environm Sci \& Engn, Shanghai 200438, Peoples R China.
Ying, Qi, Texas A\&M Univ, Zachry Dept Civil Engn, College Stn, TX 77843 USA.
Wang, Meng, Univ Buffalo, Sch Publ Hlth \& Hlth Profess, Dept Epidemiol \& Environm Hlth, Buffalo, NY USA.
Wang, Meng, Univ Buffalo, RENEW Inst, Buffalo, NY USA.
Wang, Meng, Univ Washington, Sch Publ Hlth, Dept Environm \& Occupat Hlth Sci, Seattle, WA 98195 USA.
Ding, Deping, Beijing Weather Modificat, Beijing 100089, Peoples R China.
Zhang, Xiaoling, Chengdu Univ Informat Technol, Sch Atmospher Sci, Chengdu 610103, Peoples R China.}},
DOI = {{10.1016/j.resconrec.2021.105620}},
Article-Number = {{105620}},
ISSN = {{0921-3449}},
EISSN = {{1879-0658}},
Keywords = {{premature mortality; black carbon; source contribution; Disaggregation
by province; source contributions; China}},
Keywords-Plus = {{FINE PARTICULATE MATTER; TIME-SERIES; EMISSIONS; APPORTIONMENT;
METAANALYSIS; ADMISSIONS; TRANSPORT; PM2.5}},
Research-Areas = {{Engineering; Environmental Sciences \& Ecology}},
Web-of-Science-Categories = {{Engineering, Environmental; Environmental Sciences}},
Funding-Acknowledgement = {{National Natural Science Foundation of ChinaNational Natural Science
Foundation of China (NSFC) {[}42007187, 41975162]; National Key Research
and Development Program of China {[}2018YFC0213802]}},
Funding-Text = {{This work was supported by the National Natural Science Foundation of
China (Grant No. 42007187, and 41975162); and the National Key Research
and Development Program of China (2018YFC0213802).}},
Number-of-Cited-References = {{29}},
Times-Cited = {{0}},
Usage-Count-Last-180-days = {{9}},
Usage-Count-Since-2013 = {{9}},
Journal-ISO = {{Resour. Conserv. Recycl.}},
Doc-Delivery-Number = {{TA5SQ}},
Unique-ID = {{WOS:000667309200053}},
DA = {{2021-12-02}},
}
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In this study, we estimated premature mortality attributed to BC in China in 2013 using a health impact model combined with annual average BC concentrations predicted using the Community Multi-scale Air Quality model. Source contributions to BC from six different source sectors were estimated using the source-oriented method, including residential, industrial, transportation, open burning, power, and other sources. The sensitivity of BC-related premature mortality to emission reductions in different sources was quantified in different regions of China. The results showed that the total all-cause premature mortality related to BC was approximately 1,436,957 (95% CI: 998,746-2,029,210) in China in 2013. Residential, industrial, and transportations sources were the three main sources of BC-induced premature mortality. Central China, Yangtze River Delta, and Sichuan Basin had the highest BC-induced mortality due to a high level of emissions and a dense population. A sensitivity test by assuming the same exposure-response coefficient of BC as the total PM2.5 showed the number of deaths was 265,122 thousand (95% CI: 541,90, 445,943) which can be treated as the lower limit of the BC-related mortality in China. Despite the uncertainties in estimates, it is suggested that reducing BC emissions in China would lead to significant health benefits. Controlling BC from industrial and transportation sources would bring more relative mortality reductions, from a percentage point of view, in most provinces of China.","publisher":"ELSEVIER","address":"RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS","language":"English","affiliation":"Hu, JL (Corresponding Author), Nanjing Univ Informat Sci & Technol, Jiangsu Collaborat Innovat Ctr Atmospher Environm, Jiangsu Key Lab Atmospher Environm Monitoring & P, Nanjing 210044, Peoples R China. Wang, Yiyi; Li, Xun; Shi, Zhihao; Huang, Lin; Li, Jingyi; Hu, Jianlin, Nanjing Univ Informat Sci & Technol, Jiangsu Collaborat Innovat Ctr Atmospher Environm, Jiangsu Key Lab Atmospher Environm Monitoring & P, Nanjing 210044, Peoples R China. Zhang, Hongliang, Fudan Univ, Dept Environm Sci & Engn, Shanghai 200438, Peoples R China. Ying, Qi, Texas A&M Univ, Zachry Dept Civil Engn, College Stn, TX 77843 USA. Wang, Meng, Univ Buffalo, Sch Publ Hlth & Hlth Profess, Dept Epidemiol & Environm Hlth, Buffalo, NY USA. Wang, Meng, Univ Buffalo, RENEW Inst, Buffalo, NY USA. Wang, Meng, Univ Washington, Sch Publ Hlth, Dept Environm & Occupat Hlth Sci, Seattle, WA 98195 USA. Ding, Deping, Beijing Weather Modificat, Beijing 100089, Peoples R China. Zhang, Xiaoling, Chengdu Univ Informat Technol, Sch Atmospher Sci, Chengdu 610103, Peoples R China.","doi":"10.1016/j.resconrec.2021.105620","article-number":"105620","issn":"0921-3449","eissn":"1879-0658","keywords":"premature mortality; black carbon; source contribution; Disaggregation by province; source contributions; China","keywords-plus":"FINE PARTICULATE MATTER; TIME-SERIES; EMISSIONS; APPORTIONMENT; METAANALYSIS; ADMISSIONS; TRANSPORT; PM2.5","research-areas":"Engineering; Environmental Sciences & Ecology","web-of-science-categories":"Engineering, Environmental; Environmental Sciences","funding-acknowledgement":"National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [42007187, 41975162]; National Key Research and Development Program of China [2018YFC0213802]","funding-text":"This work was supported by the National Natural Science Foundation of China (Grant No. 42007187, and 41975162); and the National Key Research and Development Program of China (2018YFC0213802).","number-of-cited-references":"29","times-cited":"0","usage-count-last-180-days":"9","usage-count-since-2013":"9","journal-iso":"Resour. Conserv. Recycl.","doc-delivery-number":"TA5SQ","unique-id":"WOS:000667309200053","da":"2021-12-02","bibtex":"@article{ WOS:000667309200053,\nAuthor = {Wang, Yiyi and Li, Xun and Shi, Zhihao and Huang, Lin and Li, Jingyi and\n Zhang, Hongliang and Ying, Qi and Wang, Meng and Ding, Deping and Zhang,\n Xiaoling and Hu, Jianlin},\nTitle = {{Premature Mortality Associated with Exposure to Outdoor Black Carbon and\n Its Source Contributions in China}},\nJournal = {{RESOURCES CONSERVATION AND RECYCLING}},\nYear = {{2021}},\nVolume = {{170}},\nMonth = {{JUL}},\nAbstract = {{Epidemiological studies have shown that outdoor black carbon (BC) has\n higher health risks than other constituents and the total fine\n particulate matter (PM2.5). In this study, we estimated premature\n mortality attributed to BC in China in 2013 using a health impact model\n combined with annual average BC concentrations predicted using the\n Community Multi-scale Air Quality model. Source contributions to BC from\n six different source sectors were estimated using the source-oriented\n method, including residential, industrial, transportation, open burning,\n power, and other sources. The sensitivity of BC-related premature\n mortality to emission reductions in different sources was quantified in\n different regions of China. The results showed that the total all-cause\n premature mortality related to BC was approximately 1,436,957 (95\\% CI:\n 998,746-2,029,210) in China in 2013. Residential, industrial, and\n transportations sources were the three main sources of BC-induced\n premature mortality. Central China, Yangtze River Delta, and Sichuan\n Basin had the highest BC-induced mortality due to a high level of\n emissions and a dense population. A sensitivity test by assuming the\n same exposure-response coefficient of BC as the total PM2.5 showed the\n number of deaths was 265,122 thousand (95\\% CI: 541,90, 445,943) which\n can be treated as the lower limit of the BC-related mortality in China.\n Despite the uncertainties in estimates, it is suggested that reducing BC\n emissions in China would lead to significant health benefits.\n Controlling BC from industrial and transportation sources would bring\n more relative mortality reductions, from a percentage point of view, in\n most provinces of China.}},\nPublisher = {{ELSEVIER}},\nAddress = {{RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS}},\nType = {{Article}},\nLanguage = {{English}},\nAffiliation = {{Hu, JL (Corresponding Author), Nanjing Univ Informat Sci \\& Technol, Jiangsu Collaborat Innovat Ctr Atmospher Environm, Jiangsu Key Lab Atmospher Environm Monitoring \\& P, Nanjing 210044, Peoples R China.\n Wang, Yiyi; Li, Xun; Shi, Zhihao; Huang, Lin; Li, Jingyi; Hu, Jianlin, Nanjing Univ Informat Sci \\& Technol, Jiangsu Collaborat Innovat Ctr Atmospher Environm, Jiangsu Key Lab Atmospher Environm Monitoring \\& P, Nanjing 210044, Peoples R China.\n Zhang, Hongliang, Fudan Univ, Dept Environm Sci \\& Engn, Shanghai 200438, Peoples R China.\n Ying, Qi, Texas A\\&M Univ, Zachry Dept Civil Engn, College Stn, TX 77843 USA.\n Wang, Meng, Univ Buffalo, Sch Publ Hlth \\& Hlth Profess, Dept Epidemiol \\& Environm Hlth, Buffalo, NY USA.\n Wang, Meng, Univ Buffalo, RENEW Inst, Buffalo, NY USA.\n Wang, Meng, Univ Washington, Sch Publ Hlth, Dept Environm \\& Occupat Hlth Sci, Seattle, WA 98195 USA.\n Ding, Deping, Beijing Weather Modificat, Beijing 100089, Peoples R China.\n Zhang, Xiaoling, Chengdu Univ Informat Technol, Sch Atmospher Sci, Chengdu 610103, Peoples R China.}},\nDOI = {{10.1016/j.resconrec.2021.105620}},\nArticle-Number = {{105620}},\nISSN = {{0921-3449}},\nEISSN = {{1879-0658}},\nKeywords = {{premature mortality; black carbon; source contribution; Disaggregation\n by province; source contributions; China}},\nKeywords-Plus = {{FINE PARTICULATE MATTER; TIME-SERIES; EMISSIONS; APPORTIONMENT;\n METAANALYSIS; ADMISSIONS; TRANSPORT; PM2.5}},\nResearch-Areas = {{Engineering; Environmental Sciences \\& Ecology}},\nWeb-of-Science-Categories = {{Engineering, Environmental; Environmental Sciences}},\nFunding-Acknowledgement = {{National Natural Science Foundation of ChinaNational Natural Science\n Foundation of China (NSFC) {[}42007187, 41975162]; National Key Research\n and Development Program of China {[}2018YFC0213802]}},\nFunding-Text = {{This work was supported by the National Natural Science Foundation of\n China (Grant No. 42007187, and 41975162); and the National Key Research\n and Development Program of China (2018YFC0213802).}},\nNumber-of-Cited-References = {{29}},\nTimes-Cited = {{0}},\nUsage-Count-Last-180-days = {{9}},\nUsage-Count-Since-2013 = {{9}},\nJournal-ISO = {{Resour. 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