Open AccessRetrieval, Selection, and Evaluation of Chemical Property Data for Assessments of Chemical Emissions, Fate, Hazard, Exposure, and Risks
Author(s) -
Li Li,
Zhizhen Zhang,
Yujie Men,
Sivani Baskaran,
Alessandro Sangion,
Shenghong Wang,
Jon A. Arnot,
Frank Wania
Publication year - 2022
Publication title -
acs environmental au
Language(s) - English
Resource type - Journals
ISSN - 2694-2518
DOI - 10.1021/acsenvironau.2c00010
Subject(s) - property (philosophy) , hazard , harmonization , computer science , risk analysis (engineering) , biochemical engineering , data mining , environmental science , engineering , business , chemistry , philosophy , physics , organic chemistry , epistemology , acoustics
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.