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The experimental determination of reliable biodegradation rates for mono-aromatics towards evaluating QSBR models.
- Source :
-
Water research [Water Res] 2019 Sep 01; Vol. 160, pp. 278-287. Date of Electronic Publication: 2019 May 24. - Publication Year :
- 2019
-
Abstract
- Quantitative Structure Biodegradation Relationships (QSBRs) are a tool to predict the biodegradability of chemicals. The objective of this work was to generate reliable biodegradation data for mono-aromatic chemicals in order to evaluate and verify previously developed QSBRs models. A robust biodegradation test method was developed to estimate specific substrate utilization rates, which were used as a proxy for biodegradation rates of chemicals in pure culture. Five representative mono-aromatic chemicals were selected that spanned a wide range of biodegradability. Aerobic biodegradation experiments were performed for each chemical in batch reactors seeded with known degraders. Chemical removal, degrader growth and CO <subscript>2</subscript> production were monitored over time. Experimental data were interpreted using a full carbon mass balance model, and Monod kinetic parameters (Y, K <subscript>s</subscript> , q <subscript>max</subscript> and μ <subscript>max</subscript> ) for each chemical were determined. In addition, stoichiometric equations for aerobic mineralization of the test chemicals were developed. The theoretically estimated biomass and CO <subscript>2</subscript> yields were similar to those experimentally observed; 35% (s.d ± 8%) of the recovered substrate carbon was converted to biomass, and 65% (s.d ± 8%) was mineralised to CO <subscript>2</subscript> . Significant correlations were observed between the experimentally determined specific substrate utilization rates, as represented by q <subscript>max</subscript> and q <subscript>max</subscript> /K <subscript>s</subscript> , at high and low substrate concentrations, respectively, and the first order biodegradation rate constants predicted by a previous QSBR study. Similarly, the correlation between q <subscript>max</subscript> and selected molecular descriptors characterizing the chemicals structure in a previous QSBR study was also significant. These results suggest that QSBR models can be reliable and robust in prioritising chemical half-lives for regulatory screening purposes.<br /> (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)
- Subjects :
- Biodegradation, Environmental
Biomass
Kinetics
Carbon
Subjects
Details
- Language :
- English
- ISSN :
- 1879-2448
- Volume :
- 160
- Database :
- MEDLINE
- Journal :
- Water research
- Publication Type :
- Academic Journal
- Accession number :
- 31154125
- Full Text :
- https://doi.org/10.1016/j.watres.2019.05.075