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
收藏NIAID Data Ecosystem2026-05-01 收录
下载链接:
https://figshare.com/articles/dataset/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/25043310
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资源简介:
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.
创建时间:
2024-01-22



