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基于计算机预测的集成工作流程来扩展优先多环芳烃化合物列表。

An Integrated Workflow Assisted by In Silico Predictions To Expand the List of Priority Polycyclic Aromatic Compounds.

机构信息

State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.

University of Chinese Academy of Sciences, Beijing 100049, China.

出版信息

Environ Sci Technol. 2023 Dec 12;57(49):20854-20863. doi: 10.1021/acs.est.3c07087. Epub 2023 Nov 27.

DOI:10.1021/acs.est.3c07087
PMID:38010983
Abstract

The limited information in existing mass spectral libraries hinders an accurate understanding of the composition, behavior, and toxicity of organic pollutants. In this study, a total of 350 polycyclic aromatic compounds (PACs) in 9 categories were successfully identified in fine particulate matter by gas chromatography high resolution mass spectrometry. Using mass spectra and retention indexes predicted by in silico tools as complementary information, the scope of chemical identification was efficiently expanded by 27%. In addition, quantitative structure-activity relationship models provided toxicity data for over 70% of PACs, facilitating a comprehensive health risk assessment. On the basis of extensive identification, the cumulative noncarcinogenic risk of PACs warranted attention. Meanwhile, the carcinogenic risk of 53 individual analogues was noteworthy. These findings suggest that there is a pressing need for an updated list of priority PACs for routine monitoring and toxicological research since legacy polycyclic aromatic hydrocarbons (PAHs) contributed modestly to the overall abundance (18%) and carcinogenic risk (8%). A toxicological priority index approach was applied for relative chemical ranking considering the environmental occurrence, fate, toxicity, and analytical availability. A list of 39 priority analogues was compiled, which predominantly consisted of high-molecular-weight PAHs and alkyl derivatives. These priority PACs further enhanced source interpretation, and the highest carcinogenic risk was attributed to coal combustion.

摘要

现有的质谱文库信息有限,这阻碍了对有机污染物的组成、行为和毒性的准确理解。在这项研究中,通过气相色谱高分辨率质谱法成功鉴定了细颗粒物中 9 类共 350 种多环芳烃(PACs)。利用计算机工具预测的质谱和保留指数作为补充信息,化学鉴定的范围有效扩大了 27%。此外,定量构效关系模型为超过 70%的 PACs 提供了毒性数据,有助于进行全面的健康风险评估。在广泛鉴定的基础上,需要关注 PACs 的累积非致癌风险。同时,53 种单体类似物的致癌风险值得关注。这些发现表明,由于传统多环芳烃(PAHs)对总丰度(18%)和致癌风险(8%)的贡献不大,因此迫切需要更新优先 PACs 清单,以便进行常规监测和毒理学研究。采用毒性优先指数方法,根据环境发生、归宿、毒性和分析可用性对化学物质进行相对排名。编制了一份包含 39 种优先类似物的清单,这些类似物主要由高分子量 PAHs 和烷基衍生物组成。这些优先 PACs 进一步增强了对来源的解释,最高的致癌风险归因于煤炭燃烧。

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