Strategies to Reduce Uncertainties from the Best Available Physicochemical Parameters Used for Modeling Novel Organophosphate Esters across Multimedia Environments

Organophosphate esters (OPEs) raise growing environmental and human health concerns globally. However, numerous novel OPEs lack data on physicochemical properties, which are essential for assessing environmental fate, exposure, and risks. This study predicted water solubility (<i>S</i><sub>w</sub>), vapor pressure (<i>V</i><sub>p</sub>), octanol-water partition coefficient (<i>K</i><sub>ow</sub>), and octanol-air partition coefficient (<i>K</i><sub>oa</sub>) at 25 °C for 46 novel OPEs by identifying optimal <i>in silico</i> tools and establishing prediction strategies based on molecular weights (MWs). Prediction discrepancies between <i>in silico</i> tools increased with MWs and structural complexity. Method evaluations for compounds with MWs > 450 g/mol suggest that COSMOtherm is advantageous in predicting <i>S</i><sub>w</sub> and <i>V</i><sub>p</sub> for alkyl-OPEs, while SPARC is better for predicting <i>V</i><sub>p</sub> for aryl- and halogenated-OPEs. For compounds with MWs > 500 g/mol, COSMOtherm and SPARC are recommended for <i>K</i><sub>ow</sub> and <i>K</i><sub>oa</sub> prediction, respectively. For smaller OPEs, average values from the top three of COSMOtherm, SPARC, EPI Suite, and OPERA, ranked by validation on traditional flame retardants, are recommended. Using improper software could cause deviations in multimedia distribution and overall persistence in the environment by up to 83 and 350%, respectively. The present data and prediction strategy are useful to enhance the reliability of environmental fate, exposure, and risk assessments of various OPEs and emerging contaminants.

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Publication Details

Journal
Environmental Science & Technology
Published
2025-03-19
DOI
https://doi.org/10.1021/acs.est.4c11028
Citations
6
Primary Topic
Green IT and Sustainability
Type
article
Field-Weighted Citation Impact
4.38

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article

Strategies to Reduce Uncertainties from the Best Available Physicochemical Parameters Used for Modeling Novel Organophosphate Esters across Multimedia Environments

Shuyang Li, Kevin C. Jones, Ying Zhu, Rongcan Chen et al.
6 citations
Environmental Science & Technology
Green IT and Sustainability
4.38
article

Strategies to Reduce Uncertainties from the Best Available Physicochemical Parameters Used for Modeling Novel Organophosphate Esters across Multimedia Environments

Shuyang Li, Kevin C. Jones, Ying Zhu, Rongcan Chen, Yong Geng, Chen Wang, Jianxin Ge, Xianming Zhang, Changyue Xing
article en
6 citations

Abstract

Organophosphate esters (OPEs) raise growing environmental and human health concerns globally. However, numerous novel OPEs lack data on physicochemical properties, which are essential for assessing environmental fate, exposure, and risks. This study predicted water solubility (<i>S</i><sub>w</sub>), vapor pressure (<i>V</i><sub>p</sub>), octanol-water partition coefficient (<i>K</i><sub>ow</sub>), and octanol-air partition coefficient (<i>K</i><sub>oa</sub>) at 25 °C for 46 novel OPEs by identifying optimal <i>in silico</i> tools and establishing prediction strategies based on molecular weights (MWs). Prediction discrepancies between <i>in silico</i> tools increased with MWs and structural complexity. Method evaluations for compounds with MWs > 450 g/mol suggest that COSMOtherm is advantageous in predicting <i>S</i><sub>w</sub> and <i>V</i><sub>p</sub> for alkyl-OPEs, while SPARC is better for predicting <i>V</i><sub>p</sub> for aryl- and halogenated-OPEs. For compounds with MWs > 500 g/mol, COSMOtherm and SPARC are recommended for <i>K</i><sub>ow</sub> and <i>K</i><sub>oa</sub> prediction, respectively. For smaller OPEs, average values from the top three of COSMOtherm, SPARC, EPI Suite, and OPERA, ranked by validation on traditional flame retardants, are recommended. Using improper software could cause deviations in multimedia distribution and overall persistence in the environment by up to 83 and 350%, respectively. The present data and prediction strategy are useful to enhance the reliability of environmental fate, exposure, and risk assessments of various OPEs and emerging contaminants.

Environmental Science & TechnologyVol. 59(12)
Shanghai Jiao Tong University (CN), Ministry of Ecology and Environment (CN), Southern University of Science and Technology (CN), Impact Assessment (US), Early Warning (United States) (US), Concordia University (CA), Lancaster University (GB)
National Natural Science Foundation of China, Science and Technology Commission of Shanghai Municipality, Shanghai Jiao Tong University
Openalex Percentile: Top 6%
Green IT and Sustainability
4.38
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