Identifying Candidate Persistent, Mobile, and Toxic (PMT) and Very Persistent and Very Mobile (vPvM) Substances in Shale Gas Drilling Fluids by Combining Nontarget Analysis and Machine Learning Model
文献类型：期刊论文
| 作者 | Wang, Ziwei1,2,3; Han, Min1,2,3; Jin, Biao1,2,3
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| 刊名 | ENVIRONMENTAL SCIENCE & TECHNOLOGY LETTERS
 |
| 出版日期 | 2024-01-22 |
| 卷号 | 11期号:2页码:114-121 |
| 关键词 | drilling fluids organic pollutants groundwater machine learning causal inference |
| ISSN号 | 2328-8930 |
| DOI | 10.1021/acs.estlett.3c00943 |
| 英文摘要 | Shale gas extraction has raised environmental concerns on regional water resources. Horizontal drilling is a process in which drilling fluids containing complex organic and inorganic chemicals are intensively applied. Accidental spill and improper disposal of drilling fluids and related wastes might pose risks to surrounding groundwater environment. Given regional ground water quality, persistent, mobile, and toxic (PMT) and very persistent and very mobile (vPvM) substances should be of particular attention. However, recent research rarely focused on chemical compositions of drilling fluids, and the harmful PMT/vPvM substances in drilling fluids remain unknown. In this study, we utilized a nontarget screening strategy to detect and identify the organic compounds in drilling fluids collected in southwest China. Specifically, a total number of 371 compounds were detected in drilling fluids, and the main fraction of the compounds was alicyclic compounds. Later, an original machine learning model developed by us was applied to identify the candidate PMT/vPvM substances among the detected organic compounds. Our study identified 29 candidate PMT/vPvM substances, thus providing a list of prioritized substances for early warning and risk assessment of regional groundwater contamination. |
| WOS研究方向 | Engineering ; Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:001162084500001 |
| 源URL | [http://ir.gig.ac.cn/handle/344008/76285]  |
| 专题 | 有机地球化学国家重点实验室 |
| 通讯作者 | Jin, Biao |
| 作者单位 | 1.CAS Ctr Excellence Deep Earth Sci, Guangzhou 510640, Peoples R China 2.Univ Chinese Acad Sci, Beijing 10069, Peoples R China 3.Chinese Acad Sci, State Key Lab Organ Geochem, Guangzhou Inst Geochem, Guangzhou 510640, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Ziwei,Han, Min,Jin, Biao. Identifying Candidate Persistent, Mobile, and Toxic (PMT) and Very Persistent and Very Mobile (vPvM) Substances in Shale Gas Drilling Fluids by Combining Nontarget Analysis and Machine Learning Model[J]. ENVIRONMENTAL SCIENCE & TECHNOLOGY LETTERS,2024,11(2):114-121. |
| APA | Wang, Ziwei,Han, Min,&Jin, Biao.(2024).Identifying Candidate Persistent, Mobile, and Toxic (PMT) and Very Persistent and Very Mobile (vPvM) Substances in Shale Gas Drilling Fluids by Combining Nontarget Analysis and Machine Learning Model.ENVIRONMENTAL SCIENCE & TECHNOLOGY LETTERS,11(2),114-121. |
| MLA | Wang, Ziwei,et al."Identifying Candidate Persistent, Mobile, and Toxic (PMT) and Very Persistent and Very Mobile (vPvM) Substances in Shale Gas Drilling Fluids by Combining Nontarget Analysis and Machine Learning Model".ENVIRONMENTAL SCIENCE & TECHNOLOGY LETTERS 11.2(2024):114-121. |
入库方式： OAI收割
来源：广州地球化学研究所
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