Deep mining of reported emerging contaminants in China's surface water in the past decade: Exposure, ecological effects and risk assessment
•Deep mining strategy was developed to identify reported ECs in China over a decade.•A multilevel risk characterization method was developed to reveal the risk status.•Database was built with exposure and effect information for all the ECs.•We found acceptable individual risk but unacceptable multis...
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Veröffentlicht in: | Water research (Oxford) 2023-09, Vol.243, p.120318-120318, Article 120318 |
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creator | Guo, Jing Tu, Keng Chou, Liben Zhang, Ying Wei, Si Zhang, Xiaowei Yu, Hongxia Shi, Wei |
description | •Deep mining strategy was developed to identify reported ECs in China over a decade.•A multilevel risk characterization method was developed to reveal the risk status.•Database was built with exposure and effect information for all the ECs.•We found acceptable individual risk but unacceptable multisubstance risk.•Twenty provinces, 24 contaminants and 9 endpoints were prioritized for management.
The identification and management of high-risk contaminants have raised great concern from governments. Facing the growing amount of data on the occurrence of emerging contaminants (ECs) in surface water, a deep mining and quality control strategy was developed to integrate data on all reported ECs in Chinese surface water over the past decade, and an exposure and effect database was further built. In addition, multilevel risk characterization was carried out to prioritize high-risk areas, contaminants and endpoints. A total of 1038 ECs, mainly pharmaceutical and personal care products (PPCPs) and industrial chemicals, were curated, with concentrations ranging from 0.02 pg/L to 533 µg/L. For individual risk, all the provinces had acceptable risks except for Henan, which was characterized with a medium chronic risk. Nine ECs, including 4-nonylphenol and estrone, dominated individual risks. Conversely, for multisubstance risk, 76.20% and 73.87% of aquatic organisms were affected acutely and chronically at the national level, with acute and chronic risks exceeding the safety threshold of 5% in 11 and 19 provinces, respectively. Nineteen ECs, including sitosterol and chyfluthrin, dominated the multisubstance risk. In addition, 9 MoAs mainly inducing electron transfer inhibition, neurotoxicity and narcosis toxicity are high-risk endpoints. The study revealed the ecological risk status and key risk entities of Chinese surface waters, which provided the latest data to support the control of ECs in China.
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doi_str_mv | 10.1016/j.watres.2023.120318 |
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The identification and management of high-risk contaminants have raised great concern from governments. Facing the growing amount of data on the occurrence of emerging contaminants (ECs) in surface water, a deep mining and quality control strategy was developed to integrate data on all reported ECs in Chinese surface water over the past decade, and an exposure and effect database was further built. In addition, multilevel risk characterization was carried out to prioritize high-risk areas, contaminants and endpoints. A total of 1038 ECs, mainly pharmaceutical and personal care products (PPCPs) and industrial chemicals, were curated, with concentrations ranging from 0.02 pg/L to 533 µg/L. For individual risk, all the provinces had acceptable risks except for Henan, which was characterized with a medium chronic risk. Nine ECs, including 4-nonylphenol and estrone, dominated individual risks. Conversely, for multisubstance risk, 76.20% and 73.87% of aquatic organisms were affected acutely and chronically at the national level, with acute and chronic risks exceeding the safety threshold of 5% in 11 and 19 provinces, respectively. Nineteen ECs, including sitosterol and chyfluthrin, dominated the multisubstance risk. In addition, 9 MoAs mainly inducing electron transfer inhibition, neurotoxicity and narcosis toxicity are high-risk endpoints. The study revealed the ecological risk status and key risk entities of Chinese surface waters, which provided the latest data to support the control of ECs in China.
[Display omitted]</description><identifier>ISSN: 0043-1354</identifier><identifier>EISSN: 1879-2448</identifier><identifier>DOI: 10.1016/j.watres.2023.120318</identifier><identifier>PMID: 37453404</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>China's surface waters ; Data mining ; Ecological risk ; Emerging contaminants ; High-risk entities</subject><ispartof>Water research (Oxford), 2023-09, Vol.243, p.120318-120318, Article 120318</ispartof><rights>2023</rights><rights>Copyright © 2023. Published by Elsevier Ltd.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c362t-c01b9104da91e5f3876273ac85898fc79782d69013d52ffb0eb81429b0f481d3</citedby><cites>FETCH-LOGICAL-c362t-c01b9104da91e5f3876273ac85898fc79782d69013d52ffb0eb81429b0f481d3</cites><orcidid>0000-0002-3963-0400 ; 0000-0001-8974-9963</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0043135423007546$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37453404$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Guo, Jing</creatorcontrib><creatorcontrib>Tu, Keng</creatorcontrib><creatorcontrib>Chou, Liben</creatorcontrib><creatorcontrib>Zhang, Ying</creatorcontrib><creatorcontrib>Wei, Si</creatorcontrib><creatorcontrib>Zhang, Xiaowei</creatorcontrib><creatorcontrib>Yu, Hongxia</creatorcontrib><creatorcontrib>Shi, Wei</creatorcontrib><title>Deep mining of reported emerging contaminants in China's surface water in the past decade: Exposure, ecological effects and risk assessment</title><title>Water research (Oxford)</title><addtitle>Water Res</addtitle><description>•Deep mining strategy was developed to identify reported ECs in China over a decade.•A multilevel risk characterization method was developed to reveal the risk status.•Database was built with exposure and effect information for all the ECs.•We found acceptable individual risk but unacceptable multisubstance risk.•Twenty provinces, 24 contaminants and 9 endpoints were prioritized for management.
The identification and management of high-risk contaminants have raised great concern from governments. Facing the growing amount of data on the occurrence of emerging contaminants (ECs) in surface water, a deep mining and quality control strategy was developed to integrate data on all reported ECs in Chinese surface water over the past decade, and an exposure and effect database was further built. In addition, multilevel risk characterization was carried out to prioritize high-risk areas, contaminants and endpoints. A total of 1038 ECs, mainly pharmaceutical and personal care products (PPCPs) and industrial chemicals, were curated, with concentrations ranging from 0.02 pg/L to 533 µg/L. For individual risk, all the provinces had acceptable risks except for Henan, which was characterized with a medium chronic risk. Nine ECs, including 4-nonylphenol and estrone, dominated individual risks. Conversely, for multisubstance risk, 76.20% and 73.87% of aquatic organisms were affected acutely and chronically at the national level, with acute and chronic risks exceeding the safety threshold of 5% in 11 and 19 provinces, respectively. Nineteen ECs, including sitosterol and chyfluthrin, dominated the multisubstance risk. In addition, 9 MoAs mainly inducing electron transfer inhibition, neurotoxicity and narcosis toxicity are high-risk endpoints. The study revealed the ecological risk status and key risk entities of Chinese surface waters, which provided the latest data to support the control of ECs in China.
[Display omitted]</description><subject>China's surface waters</subject><subject>Data mining</subject><subject>Ecological risk</subject><subject>Emerging contaminants</subject><subject>High-risk entities</subject><issn>0043-1354</issn><issn>1879-2448</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp9kcmO1DAQhi0EYpqBN0DINziQxls6NoeRUDMs0khc5m45drnHTRIHV5rlGXhp3MrAkVOVqr5af0Kec7bljO_eHLc_3FIAt4IJueWCSa4fkA3XnWmEUvoh2TCmZMNlqy7IE8QjY0wIaR6TC9mpViqmNuT3e4CZjmlK04HmSAvMuSwQKIxQDuegz9PiKuCmBWma6P6u-i-R4qlE54HWLaCcE8sd0NnhQgN4F-Atvf4550rBawo-D_mQvBsoxAi-dnJToCXhV-oQAXGEaXlKHkU3IDy7t5fk9sP17f5Tc_Pl4-f9u5vGy51YGs94bzhTwRkObZS624lOOq9bbXT0nem0CDvDuAytiLFn0GuuhOlZVJoHeUlerW3nkr-dABc7JvQwDG6CfEIrtNSiVZ0xFVUr6ktGLBDtXNLoyi_LmT2rYI92VcGeVbCrCrXsxf2EUz9C-Ff09-0VuFoBqGd-T1As-gSTh5BK_Y4NOf1_wh-Pvpvm</recordid><startdate>20230901</startdate><enddate>20230901</enddate><creator>Guo, Jing</creator><creator>Tu, Keng</creator><creator>Chou, Liben</creator><creator>Zhang, Ying</creator><creator>Wei, Si</creator><creator>Zhang, Xiaowei</creator><creator>Yu, Hongxia</creator><creator>Shi, Wei</creator><general>Elsevier Ltd</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-3963-0400</orcidid><orcidid>https://orcid.org/0000-0001-8974-9963</orcidid></search><sort><creationdate>20230901</creationdate><title>Deep mining of reported emerging contaminants in China's surface water in the past decade: Exposure, ecological effects and risk assessment</title><author>Guo, Jing ; Tu, Keng ; Chou, Liben ; Zhang, Ying ; Wei, Si ; Zhang, Xiaowei ; Yu, Hongxia ; Shi, Wei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c362t-c01b9104da91e5f3876273ac85898fc79782d69013d52ffb0eb81429b0f481d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>China's surface waters</topic><topic>Data mining</topic><topic>Ecological risk</topic><topic>Emerging contaminants</topic><topic>High-risk entities</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Guo, Jing</creatorcontrib><creatorcontrib>Tu, Keng</creatorcontrib><creatorcontrib>Chou, Liben</creatorcontrib><creatorcontrib>Zhang, Ying</creatorcontrib><creatorcontrib>Wei, Si</creatorcontrib><creatorcontrib>Zhang, Xiaowei</creatorcontrib><creatorcontrib>Yu, Hongxia</creatorcontrib><creatorcontrib>Shi, Wei</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Water research (Oxford)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Guo, Jing</au><au>Tu, Keng</au><au>Chou, Liben</au><au>Zhang, Ying</au><au>Wei, Si</au><au>Zhang, Xiaowei</au><au>Yu, Hongxia</au><au>Shi, Wei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Deep mining of reported emerging contaminants in China's surface water in the past decade: Exposure, ecological effects and risk assessment</atitle><jtitle>Water research (Oxford)</jtitle><addtitle>Water Res</addtitle><date>2023-09-01</date><risdate>2023</risdate><volume>243</volume><spage>120318</spage><epage>120318</epage><pages>120318-120318</pages><artnum>120318</artnum><issn>0043-1354</issn><eissn>1879-2448</eissn><abstract>•Deep mining strategy was developed to identify reported ECs in China over a decade.•A multilevel risk characterization method was developed to reveal the risk status.•Database was built with exposure and effect information for all the ECs.•We found acceptable individual risk but unacceptable multisubstance risk.•Twenty provinces, 24 contaminants and 9 endpoints were prioritized for management.
The identification and management of high-risk contaminants have raised great concern from governments. Facing the growing amount of data on the occurrence of emerging contaminants (ECs) in surface water, a deep mining and quality control strategy was developed to integrate data on all reported ECs in Chinese surface water over the past decade, and an exposure and effect database was further built. In addition, multilevel risk characterization was carried out to prioritize high-risk areas, contaminants and endpoints. A total of 1038 ECs, mainly pharmaceutical and personal care products (PPCPs) and industrial chemicals, were curated, with concentrations ranging from 0.02 pg/L to 533 µg/L. For individual risk, all the provinces had acceptable risks except for Henan, which was characterized with a medium chronic risk. Nine ECs, including 4-nonylphenol and estrone, dominated individual risks. Conversely, for multisubstance risk, 76.20% and 73.87% of aquatic organisms were affected acutely and chronically at the national level, with acute and chronic risks exceeding the safety threshold of 5% in 11 and 19 provinces, respectively. Nineteen ECs, including sitosterol and chyfluthrin, dominated the multisubstance risk. In addition, 9 MoAs mainly inducing electron transfer inhibition, neurotoxicity and narcosis toxicity are high-risk endpoints. The study revealed the ecological risk status and key risk entities of Chinese surface waters, which provided the latest data to support the control of ECs in China.
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subjects | China's surface waters Data mining Ecological risk Emerging contaminants High-risk entities |
title | Deep mining of reported emerging contaminants in China's surface water in the past decade: Exposure, ecological effects and risk assessment |
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