Hotspot mapping and risk prediction of fluoride in natural waters across the Tibetan Plateau
Intake of high fluoride concentrations through water affects up to 1 billion people worldwide, and the Tibetan Plateau (TP) is one of the most severely affected areas. Knowledge regarding the high fluoride risk areas, the driving factors, and at-risk populations on the TP remains fragmented. We coll...
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Veröffentlicht in: | Journal of hazardous materials 2024-03, Vol.465, p.133510-133510, Article 133510 |
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creator | Yang, Yi Zhang, Ru Deji, Yangzong Li, Yonghua |
description | Intake of high fluoride concentrations through water affects up to 1 billion people worldwide, and the Tibetan Plateau (TP) is one of the most severely affected areas. Knowledge regarding the high fluoride risk areas, the driving factors, and at-risk populations on the TP remains fragmented. We collected 1581 natural water samples from the TP to model surface water and groundwater fluoride hazard maps using machine learning. The geomean concentrations of surface water and groundwater were 0.26 mg/L and 0.92 mg/L, respectively. Surface water fluoride hazard hotspots were concentrated in the north-central region; high fluoride risk areas of groundwater were mainly concentrated in the southern TP. Hazard maps showed a maximum estimate of 15% of the total population in the TP (approximately 1.47 million people) at risk, and 500,000 people considered the most reasonable estimate. Critical environment driving factors were identified, in which climate condition was taken for the vital one. Under the moderate climate change scenario (SSP2.45) for 2089–2099, the high fluoride risk change rate differed inside the TP (surface water −24%−55% and groundwater −56%−50%), and the overall risk increased in natural waters throughout the TP, particularly in the southeastern TP.
[Display omitted]
●First large-scale water fluoride monitoring was conducted in Tibetan Plateau (TP).●High-resolution maps of fluoride in natural waters across the TP were generated.●Future water fluoride risks under SSP2.45 were clarified by the random forest model.●Climate change will lead to an overall increase in the risk of water fluoride on TP.●High fluoride risk areas were identified, and at-risk population were estimated. |
doi_str_mv | 10.1016/j.jhazmat.2024.133510 |
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[Display omitted]
●First large-scale water fluoride monitoring was conducted in Tibetan Plateau (TP).●High-resolution maps of fluoride in natural waters across the TP were generated.●Future water fluoride risks under SSP2.45 were clarified by the random forest model.●Climate change will lead to an overall increase in the risk of water fluoride on TP.●High fluoride risk areas were identified, and at-risk population were estimated.</description><identifier>ISSN: 0304-3894</identifier><identifier>EISSN: 1873-3336</identifier><identifier>DOI: 10.1016/j.jhazmat.2024.133510</identifier><identifier>PMID: 38219577</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>China ; climate change ; climatic factors ; Fluoride ; groundwater ; Machine learning ; Natural waters ; people ; Prediction ; risk ; surface water ; The Tibetan Plateau</subject><ispartof>Journal of hazardous materials, 2024-03, Vol.465, p.133510-133510, Article 133510</ispartof><rights>2024 Elsevier B.V.</rights><rights>Copyright © 2024 Elsevier B.V. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c398t-6241b3c88e4abd7fe53e81d65e83217342fbac780dadf3730a1c9fc037785cd23</citedby><cites>FETCH-LOGICAL-c398t-6241b3c88e4abd7fe53e81d65e83217342fbac780dadf3730a1c9fc037785cd23</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0304389424000888$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/38219577$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Yang, Yi</creatorcontrib><creatorcontrib>Zhang, Ru</creatorcontrib><creatorcontrib>Deji, Yangzong</creatorcontrib><creatorcontrib>Li, Yonghua</creatorcontrib><title>Hotspot mapping and risk prediction of fluoride in natural waters across the Tibetan Plateau</title><title>Journal of hazardous materials</title><addtitle>J Hazard Mater</addtitle><description>Intake of high fluoride concentrations through water affects up to 1 billion people worldwide, and the Tibetan Plateau (TP) is one of the most severely affected areas. Knowledge regarding the high fluoride risk areas, the driving factors, and at-risk populations on the TP remains fragmented. We collected 1581 natural water samples from the TP to model surface water and groundwater fluoride hazard maps using machine learning. The geomean concentrations of surface water and groundwater were 0.26 mg/L and 0.92 mg/L, respectively. Surface water fluoride hazard hotspots were concentrated in the north-central region; high fluoride risk areas of groundwater were mainly concentrated in the southern TP. Hazard maps showed a maximum estimate of 15% of the total population in the TP (approximately 1.47 million people) at risk, and 500,000 people considered the most reasonable estimate. Critical environment driving factors were identified, in which climate condition was taken for the vital one. Under the moderate climate change scenario (SSP2.45) for 2089–2099, the high fluoride risk change rate differed inside the TP (surface water −24%−55% and groundwater −56%−50%), and the overall risk increased in natural waters throughout the TP, particularly in the southeastern TP.
[Display omitted]
●First large-scale water fluoride monitoring was conducted in Tibetan Plateau (TP).●High-resolution maps of fluoride in natural waters across the TP were generated.●Future water fluoride risks under SSP2.45 were clarified by the random forest model.●Climate change will lead to an overall increase in the risk of water fluoride on TP.●High fluoride risk areas were identified, and at-risk population were estimated.</description><subject>China</subject><subject>climate change</subject><subject>climatic factors</subject><subject>Fluoride</subject><subject>groundwater</subject><subject>Machine learning</subject><subject>Natural waters</subject><subject>people</subject><subject>Prediction</subject><subject>risk</subject><subject>surface water</subject><subject>The Tibetan Plateau</subject><issn>0304-3894</issn><issn>1873-3336</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNqFkUFv1DAQhS0Eokvbn9DKRy5ZbE8cO6cKVYUiVYJDuSFZjj2h3iZxsB1Q-fVk2YVrT3OY783TvEfIBWdbznjzbrfdPdjfoy1bwUS95QCSsxdkw7WCCgCal2TDgNUV6LY-IW9y3jHGuJL1a3ICWvBWKrUh325jyXMsdLTzHKbv1E6eppAf6ZzQB1dCnGjsaT8sMQWPNEx0smVJdqC_bMGUqXUp5kzLA9L70GGxE_0yrCu7nJFXvR0ynh_nKfn64eb--ra6-_zx0_X7u8pBq0vViJp34LTG2nZe9SgBNfeNRA2CK6hF31mnNPPW96CAWe7a3jFQSkvnBZySt4e7c4o_FszFjCE7HAY7YVyyAS6hEVo08CwqWl4L2Qi-R-UB_ftfwt7MKYw2PRnOzL4DszPHDsy-A3PoYNVdHi2WbkT_X_Uv9BW4OgC4ZvIzYDLZBZzcmndCV4yP4RmLPxxHmsU</recordid><startdate>20240305</startdate><enddate>20240305</enddate><creator>Yang, Yi</creator><creator>Zhang, Ru</creator><creator>Deji, Yangzong</creator><creator>Li, Yonghua</creator><general>Elsevier B.V</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7S9</scope><scope>L.6</scope></search><sort><creationdate>20240305</creationdate><title>Hotspot mapping and risk prediction of fluoride in natural waters across the Tibetan Plateau</title><author>Yang, Yi ; Zhang, Ru ; Deji, Yangzong ; Li, Yonghua</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c398t-6241b3c88e4abd7fe53e81d65e83217342fbac780dadf3730a1c9fc037785cd23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>China</topic><topic>climate change</topic><topic>climatic factors</topic><topic>Fluoride</topic><topic>groundwater</topic><topic>Machine learning</topic><topic>Natural waters</topic><topic>people</topic><topic>Prediction</topic><topic>risk</topic><topic>surface water</topic><topic>The Tibetan Plateau</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yang, Yi</creatorcontrib><creatorcontrib>Zhang, Ru</creatorcontrib><creatorcontrib>Deji, Yangzong</creatorcontrib><creatorcontrib>Li, Yonghua</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>Journal of hazardous materials</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yang, Yi</au><au>Zhang, Ru</au><au>Deji, Yangzong</au><au>Li, Yonghua</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Hotspot mapping and risk prediction of fluoride in natural waters across the Tibetan Plateau</atitle><jtitle>Journal of hazardous materials</jtitle><addtitle>J Hazard Mater</addtitle><date>2024-03-05</date><risdate>2024</risdate><volume>465</volume><spage>133510</spage><epage>133510</epage><pages>133510-133510</pages><artnum>133510</artnum><issn>0304-3894</issn><eissn>1873-3336</eissn><abstract>Intake of high fluoride concentrations through water affects up to 1 billion people worldwide, and the Tibetan Plateau (TP) is one of the most severely affected areas. Knowledge regarding the high fluoride risk areas, the driving factors, and at-risk populations on the TP remains fragmented. We collected 1581 natural water samples from the TP to model surface water and groundwater fluoride hazard maps using machine learning. The geomean concentrations of surface water and groundwater were 0.26 mg/L and 0.92 mg/L, respectively. Surface water fluoride hazard hotspots were concentrated in the north-central region; high fluoride risk areas of groundwater were mainly concentrated in the southern TP. Hazard maps showed a maximum estimate of 15% of the total population in the TP (approximately 1.47 million people) at risk, and 500,000 people considered the most reasonable estimate. Critical environment driving factors were identified, in which climate condition was taken for the vital one. Under the moderate climate change scenario (SSP2.45) for 2089–2099, the high fluoride risk change rate differed inside the TP (surface water −24%−55% and groundwater −56%−50%), and the overall risk increased in natural waters throughout the TP, particularly in the southeastern TP.
[Display omitted]
●First large-scale water fluoride monitoring was conducted in Tibetan Plateau (TP).●High-resolution maps of fluoride in natural waters across the TP were generated.●Future water fluoride risks under SSP2.45 were clarified by the random forest model.●Climate change will lead to an overall increase in the risk of water fluoride on TP.●High fluoride risk areas were identified, and at-risk population were estimated.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>38219577</pmid><doi>10.1016/j.jhazmat.2024.133510</doi><tpages>1</tpages></addata></record> |
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subjects | China climate change climatic factors Fluoride groundwater Machine learning Natural waters people Prediction risk surface water The Tibetan Plateau |
title | Hotspot mapping and risk prediction of fluoride in natural waters across the Tibetan Plateau |
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