采出水
流出物
环境化学
毒物
毒性
污染物
环境科学
污染
水力压裂
化学
生物
环境工程
生态学
古生物学
有机化学
作者
Fan Wu,Zhimin Zhou,Shaoqiong Zhang,Fei Cheng,Yujun Tong,Liang Li,Biao Zhang,Xiangying Zeng,Huizhen Li,Dali Wang,Zhiqiang Yu,Jing You
出处
期刊:Water Research
[Elsevier]
日期:2023-08-01
卷期号:241: 120170-120170
被引量:6
标识
DOI:10.1016/j.watres.2023.120170
摘要
Hydraulic fracturing flowback and produced water (HF-FPW) from shale gas extraction processes is a highly complex medium with potential threats to the environment. Current research on ecological risks of FPW in China is limited, and the link between major components of FPW and their toxicological effects on freshwater organisms is largely unknown. By integrating chemical and biological analyses, toxicity identification evaluation (TIE) was used to reveal causality between toxicity and contaminants, potentially disentangling the complex toxicological nature of FPW. Here, FPW from different shale gas wells, treated FPW effluent, and a leachate from HF sludge were collected from southwest China, and TIE was applied to obtain a comprehensive toxicity evaluation in freshwater organisms. Our results showed that FPW from the same geographic zone could cause significantly different toxicity. Salinity, solid phase particulates, and organic contaminants were identified as the main contributors to the toxicity of FPW. In addition to water chemistry, internal alkanes, PAHs, and HF additives (e.g., biocides and surfactants) were quantified in exposed embryonic fish by target and non-target tissue analyses. The treated FPW failed to mitigate the toxicity associated with organic contaminants. Transcriptomic results illustrated that organic compounds induced toxicity pathways in FPW-exposed embryonic zebrafish. Similar zebrafish gene ontologies were affected between treated and untreated FPW, again confirming that sewage treatment did not effectively remove organic chemicals from FPW. Thus, zebrafish transcriptome analyses revealed organic toxicant-induced adverse outcome pathways and served as evidence for TIE confirmation in complex mixtures under data-poor scenarios.
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