Literature DB >> 29376649

Determining Biodegradation Kinetics of Hydrocarbons at Low Concentrations: Covering 5 and 9 Orders of Magnitude of Kow and Kaw.

Heidi Birch1, Rikke Hammershøj1, Philipp Mayer1.   

Abstract

A partitioning-based experimental platform was developed and applied to determine primary biodegradation kinetics of 53 hydrocarbons at ng/L to μg/L concentrations covering C8-C20, 11 structural classes, and several orders of magnitude in hydrophobicity and volatility: (1) Passive dosing from a loaded silicone donor was used to set the concentration of each hydrocarbon in mixture stock solutions; (2) these solutions were combined with environmental water samples in gastight auto sampler vials for 1-100 days incubation, and (3) automated solid phase microextraction (SPME) coupled to GC-MS was applied directly on these test systems for measuring primary biodegradation relative to abiotic controls. First order biodegradation kinetics were obtained for 40 hydrocarbons in activated sludge filtrate, 18 in seawater, and 21 in lake water. Water phase half-lives in seawater and lake water were poorly related to hydrophobicity and volatility but were, with a few exceptions, within a factor of 10 or shorter than BioHCwin predictions. The most persistent hydrocarbons, 1,1,4,4,6-pentamethyldecalin, perhydropyrene, 1,2,3,6,7,8-hexahydropyrene, and 2,2,4,4,6,8,8-heptamethylnonane, showed limited or inconsistent degradation in all three environmental media. This biodegradation approach can cover a large chemical space at low substrate concentrations, which makes it highly suited for optimizing predictive models for environmental biodegradation.

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Year:  2018        PMID: 29376649     DOI: 10.1021/acs.est.7b05624

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  2 in total

1.  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

Review 2.  Improving the Environmental Risk Assessment of Substances of Unknown or Variable Composition, Complex Reaction Products, or Biological Materials.

Authors:  Daniel Salvito; Marc Fernandez; Karen Jenner; Delina Y Lyon; Joop de Knecht; Philipp Mayer; Matthew MacLeod; Karen Eisenreich; Pim Leonards; Romanas Cesnaitis; Miriam León-Paumen; Michelle Embry; Sandrine E Déglin
Journal:  Environ Toxicol Chem       Date:  2020-09-16       Impact factor: 3.742

  2 in total

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