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用于评估化学物质排放、归宿、危害、暴露和风险的化学性质数据的检索、选择和评估。

Retrieval, Selection, and Evaluation of Chemical Property Data for Assessments of Chemical Emissions, Fate, Hazard, Exposure, and Risks.

作者信息

Li Li, Zhang Zhizhen, Men Yujie, Baskaran Sivani, Sangion Alessandro, Wang Shenghong, Arnot Jon A, Wania Frank

机构信息

School of Public Health, University of Nevada Reno, Reno, Nevada 89557, United States.

Department of Chemical & Environmental Engineering, University of California Riverside, Riverside, California 92521, United States.

出版信息

ACS Environ Au. 2022 Jul 19;2(5):376-395. doi: 10.1021/acsenvironau.2c00010. eCollection 2022 Sep 21.

Abstract

Reliable chemical property data are the key to defensible and unbiased assessments of chemical emissions, fate, hazard, exposure, and risks. However, the retrieval, evaluation, and use of reliable chemical property data can often be a formidable challenge for chemical assessors and model users. This comprehensive review provides practical guidance for use of chemical property data in chemical assessments. We assemble available sources for obtaining experimentally derived and in silico predicted property data; we also elaborate strategies for evaluating and curating the obtained property data. We demonstrate that both experimentally derived and in silico predicted property data can be subject to considerable uncertainty and variability. Chemical assessors are encouraged to use property data derived through the harmonization of multiple carefully selected experimental data if a sufficient number of reliable laboratory measurements is available or through the consensus consolidation of predictions from multiple in silico tools if the data pool from laboratory measurements is not adequate.

摘要

可靠的化学性质数据是对化学物质排放、归宿、危害、暴露和风险进行合理且无偏差评估的关键。然而,对于化学评估人员和模型使用者而言,检索、评估和使用可靠的化学性质数据往往是一项艰巨的挑战。本全面综述为在化学评估中使用化学性质数据提供了实用指南。我们汇总了获取实验得出的数据和计算机模拟预测的性质数据的可用来源;还阐述了评估和整理所获性质数据的策略。我们证明,实验得出的数据和计算机模拟预测的性质数据都可能存在相当大的不确定性和变异性。如果有足够数量的可靠实验室测量数据,鼓励化学评估人员使用通过协调多个精心挑选的实验数据得出的性质数据;如果实验室测量的数据池不足,则鼓励使用通过整合多个计算机模拟工具的预测结果达成的共识得出的性质数据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c5c/10125307/5618c51ea210/vg2c00010_0001.jpg

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