全球饮用水中PFAS的空间分布特征、健康风险评价及调控

IF 2.9 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Jinsha Ma, Muzhi Shao, Weiwei Fan, Fengge Chen, Yuantao Hao, Tong Wang, Yongyue Wei
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引用次数: 0

摘要

本研究利用PubMed和Web of Science数据库(2000年1月1日至2025年2月25日)系统评估了全球饮用水中全氟烷基和多氟烷基物质(PFAS)的空间分布、健康风险和监管。在回顾的122项研究中,全氟辛酸(PFOA)和全氟辛烷磺酸(PFOS)受到的研究关注最多(分别在102项和100项研究中检测到),检出率最高(分别为64.69%和60.72%)。其他几种化合物,包括全氟辛烷磺酰胺、全氟丁烷磺酰胺和全氟丙烷磺酸,也显示出较高的检出率,但仍然监管不足,这突出表明需要进一步研究和监管监督。[公式:见文本]浓度最高的三个国家是大韩民国、美国和中国。风险评估表明,全氟己酸、全氟丁酸和全氟丁磺酸构成的健康风险可以忽略不计,而全氟己烷磺酸(PFHxS)、全foa、全氟辛烷磺酸和全氟壬烷酸(PFNA)的健康风险水平呈下降趋势(PFHxS > PFOA > PFOS > PFNA)。监管方法正在从特定化合物的标准转向基于混合物的综合框架,并通过逐步严格的限制得到加强。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Characteristics of Spatial Distribution, Health Risk Assessment, and Regulation of PFAS in Global Drinking Water.

This study systematically evaluated the spatial distribution, health risks, and regulation of per- and polyfluoroalkyl substances (PFAS) in global drinking water using the PubMed and Web of Science databases (January 1, 2000 to February 25, 2025). Among the 122 studies reviewed, perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) received the greatest research attention (detected in 102 and 100 studies, respectively) and showed the highest detection rates (64.69% and 60.72%, respectively). Several other compounds, including perfluorooctane sulfonamide, perfluorobutanesulfonamide, and perfluoropropane sulfonate, also exhibited high detection rates but remain underregulated, underscoring the need for further research and regulatory oversight. The three countries with the highest concentrations of [Formula: see text] were the Republic of Korea, the United States, and China. Risk assessments indicated that perfluorohexanoic acid, perfluorobutanoic acid, and perfluorobutanesulfonic acid posed negligible health risks, while perfluorohexane sulfonic acid (PFHxS), PFOA, PFOS, and perfluorononanoic acid (PFNA) showed descending levels of health risk (PFHxS > PFOA > PFOS > PFNA). Regulatory approaches are shifting from compound-specific standards to integrated mixture-based frameworks, reinforced by progressively stringent limits.

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CiteScore
5.90
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