长江
中国
流出物
环境科学
地表水
环境化学
分布(数学)
水资源管理
环境工程
水文学(农业)
地理
化学
地质学
考古
数学
岩土工程
数学分析
作者
Xiao‐Min Xiong,Haifeng Zhang,Rongmao Wang,Zhao Tang,Min Yang
出处
期刊:ACS ES&T water
[American Chemical Society]
日期:2024-05-01
卷期号:4 (5): 2300-2308
标识
DOI:10.1021/acsestwater.4c00169
摘要
Polycyclic aromatic compounds (PACs) are widely present in aquatic environments and have attracted considerable attention because of their potential carcinogenicity, teratogenicity, and mutagenicity. However, compared with that of the 16 Environmental Protection Agency (EPA) polycyclic aromatic hydrocarbons (PAHs), information on the occurrence and ecological risks of other PACs is scarce. In this study, a liquid–liquid extraction coupled gas chromatography–tandem mass spectrometry method was established for the simultaneous analysis of 80 PACs, including 23 parent PAHs (PPAHs) and 12 alkylated, 10 oxygenated, 8 nitrated, 18 halogenated, and 9 heterocyclic PAHs, in 15 surface water and 7 industrial effluent samples collected from the upper reaches of Yangtze River. The average concentration of total PACs in surface water was 1106.4 ng/L, with ΣHPAH (974.2 ng/L) > ΣPPAH (55.6 ng/L) > ΣAPAH (48.1 ng/L) > ΣNPAH (16.8 ng/L) > ΣOPAH (10.9 ng/L) > ΣXPAH (0.8 ng/L). The average concentration of total PACs in industrial effluent was 373 ng/L with ΣHPAH (294.1 ng/L) > ΣPPAH (37.2 ng/L) > ΣAPAH (23 ng/L) > ΣOPAH (10.9 ng/L) > ΣOPAH (6.7 ng/L) > ΣXPAH (1.1 ng/L). Notably, indole concentrations up to 6466.9 and 1616.6 ng/L were detected in surface water and industrial effluent, respectively. Ecological risk assessment using the risk quotient (RQ) showed that all surface water samples exhibited high risks (RQ > 1), mainly derived from indole, 1,4-naphthoquinone, and PPAHs with high ring numbers. Additionally, 4 surface water samples exhibited medium to high risks, and 10 exhibited low to medium risks based on the total toxicity equivalent (TEQcarc) evaluation, with the main contribution from benzo[a]pyrene. The results of this study would provide valuable data to comprehensively assess the exposure levels and risks of PACs.
科研通智能强力驱动
Strongly Powered by AbleSci AI