Header

UZH-Logo

Maintenance Infos

Comparison of Small Molecule Biotransformation Half-Lives between Activated Sludge and Soil: Opportunities for Read-Across?


Fenner, Kathrin; Screpanti, Claudio; Renold, Peter; Rouchdi, Marwa; Vogler, Bernadette; Rich, Stephanie (2020). Comparison of Small Molecule Biotransformation Half-Lives between Activated Sludge and Soil: Opportunities for Read-Across? Environmental Science & Technology, 54(6):3148-3158.

Abstract

Compartment-specific degradation half-lives are essential pieces of information in the regulatory risk assessment of synthetic chemicals. However, their measurement according to regulatory testing guidelines is laborious and costly. Despite the obvious ecological and economic benefits of knowing environmental degradability as early as possible, its consideration in the early phases of rational chemical design is therefore challenging. Here, we explore the possibility to use half-lives determined in highly time- and work-efficient biotransformation experiments with activated sludge and mixtures of chemicals to predict soil half-lives from regulatory simulation studies. We experimentally determined half-lives for 52 structurally diverse agrochemical active ingredients in batch reactors with three concentrations of the same activated sludge. We then developed bi- and multivariate models for predicting half-lives in soil by regressing the experimentally determined half-lives in activated sludge against average soil half-lives of the same chemicals extracted from regulatory data. The models differed in how we accounted for sorption-related bioavailability differences in soil and activated sludge. The best-performing models exhibited good coefficients of determination (R2 of around 0.8) and low average errors (<factor of 3 in half-life predictions) and were robust in cross-validation. From a practical perspective, these results suggest that it may indeed be possible to read across from half-lives determined in highly efficient biotransformation experiments in activated sludge to soil half-lives, which are obtained from much more work- and resource-intense regulatory studies, and that these predictions are clearly superior to predictions based on the output of BIOWIN, a publicly available quantitative structure-biodegradation relationship (QSBR) model. From a theoretical perspective, these results suggest that soil and activated sludge microbial communities, although certainly different in terms of taxonomic composition, may be functionally similar with respect to the enzymatic transformation of environmentally relevant concentrations of a diverse range of chemical compounds.

Abstract

Compartment-specific degradation half-lives are essential pieces of information in the regulatory risk assessment of synthetic chemicals. However, their measurement according to regulatory testing guidelines is laborious and costly. Despite the obvious ecological and economic benefits of knowing environmental degradability as early as possible, its consideration in the early phases of rational chemical design is therefore challenging. Here, we explore the possibility to use half-lives determined in highly time- and work-efficient biotransformation experiments with activated sludge and mixtures of chemicals to predict soil half-lives from regulatory simulation studies. We experimentally determined half-lives for 52 structurally diverse agrochemical active ingredients in batch reactors with three concentrations of the same activated sludge. We then developed bi- and multivariate models for predicting half-lives in soil by regressing the experimentally determined half-lives in activated sludge against average soil half-lives of the same chemicals extracted from regulatory data. The models differed in how we accounted for sorption-related bioavailability differences in soil and activated sludge. The best-performing models exhibited good coefficients of determination (R2 of around 0.8) and low average errors (<factor of 3 in half-life predictions) and were robust in cross-validation. From a practical perspective, these results suggest that it may indeed be possible to read across from half-lives determined in highly efficient biotransformation experiments in activated sludge to soil half-lives, which are obtained from much more work- and resource-intense regulatory studies, and that these predictions are clearly superior to predictions based on the output of BIOWIN, a publicly available quantitative structure-biodegradation relationship (QSBR) model. From a theoretical perspective, these results suggest that soil and activated sludge microbial communities, although certainly different in terms of taxonomic composition, may be functionally similar with respect to the enzymatic transformation of environmentally relevant concentrations of a diverse range of chemical compounds.

Statistics

Citations

Dimensions.ai Metrics
19 citations in Web of Science®
18 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

52 downloads since deposited on 05 Feb 2021
17 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Department of Chemistry
Dewey Decimal Classification:540 Chemistry
Scopus Subject Areas:Physical Sciences > General Chemistry
Physical Sciences > Environmental Chemistry
Uncontrolled Keywords:General Chemistry, Environmental Chemistry
Language:English
Date:17 March 2020
Deposited On:05 Feb 2021 08:14
Last Modified:25 Nov 2023 02:47
Publisher:American Chemical Society (ACS)
ISSN:0013-936X
Additional Information:This document is the Accepted Manuscript version of a Published Work that appeared in final form in Environmental Science & Technology, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://pubs.acs.org/doi/abs/10.1021/acs.est.9b05104
OA Status:Green
Publisher DOI:https://doi.org/10.1021/acs.est.9b05104
Project Information:
  • : FunderFP7
  • : Grant ID614768
  • : Project TitlePRODUCTS - Predicting environment-specific biotransformation of chemical contaminants
  • Content: Accepted Version