Literature DB >> 15212896

Comparison of two methods for obtaining degradation half-lives.

Todd Gouin1, Ian Cousins, Don Mackay.   

Abstract

Given the paucity of experimental degradation half-life data for most organic chemicals, there is a compelling incentive to use available estimation software when undertaking assessments of chemical persistence and mass balance modeling studies. In this study, half-life data obtained from estimation software for a set of 233 organic chemicals in air, water, soil and sediments were shown to differ significantly from half-life data listed in handbooks. It is suggested that the widely available and used estimation software, EPIWIN (Estimations Program's Interface for Windows), overestimates the reactivity of persistent organic pollutants (POPs). Reasons for this overestimation are explored. It is concluded that the maximum "default half-life values" used by the EPIWIN software are too short for estimating half-lives of highly persistent chemicals such as PCBs. There is a need for estimation software such as EPIWIN to be more thoroughly calibrated against experimental derived half-life data for a wide range of chemicals, including potential POPs, thus improving their reliability.

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Year:  2004        PMID: 15212896     DOI: 10.1016/j.chemosphere.2004.04.018

Source DB:  PubMed          Journal:  Chemosphere        ISSN: 0045-6535            Impact factor:   7.086


  4 in total

Review 1.  Evaluation of artificial intelligence based models for chemical biodegradability prediction.

Authors:  James R Baker; Dragan Gamberger; James R Mihelcic; Aleksandar Sabljić
Journal:  Molecules       Date:  2004-12-31       Impact factor: 4.411

2.  Multimedia model for polycyclic aromatic hydrocarbons (PAHs) and nitro-PAHs in Lake Michigan.

Authors:  Lei Huang; Stuart A Batterman
Journal:  Environ Sci Technol       Date:  2014-11-19       Impact factor: 9.028

3.  In Silico Screening-Level Prioritization of 8468 Chemicals Produced in OECD Countries to Identify Potential Planetary Boundary Threats.

Authors:  Efstathios Reppas-Chrysovitsinos; Anna Sobek; Matthew MacLeod
Journal:  Bull Environ Contam Toxicol       Date:  2017-12-28       Impact factor: 2.151

4.  Predicting Primary Biodegradation of Petroleum Hydrocarbons in Aquatic Systems: Integrating System and Molecular Structure Parameters using a Novel Machine-Learning Framework.

Authors:  Craig Warren Davis; Louise Camenzuli; Aaron D Redman
Journal:  Environ Toxicol Chem       Date:  2022-04-29       Impact factor: 4.218

  4 in total

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