Journal article
Transformation and Sorption of Illicit Drug Biomarkers in Sewer Biofilms
Department of Environmental Engineering1
Process and Systems Engineering Center (PROSYS), Department of Chemical and Biochemical Engineering2
P.O. Box 1072, 3430 BB Nieuwegein3
Institute for Biodiversity and Ecosystem Dynamics4
Department of Chemical Engineering5
In-sewer transformation of drug biomarkers (excreted parent drugs and metabolites) can be influenced by the presence of biomass in suspended form as well as attached to sewer walls (biofilms). Biofilms are likely the most abundant and biologically active biomass fraction in sewers. In this study, 16 drug biomarkers were selected, including the parent forms and the major human metabolites of mephedrone, methadone, cocaine, heroin, codeine, and tetrahydrocannabinol (THC).
Transformation and sorption of these substances were assessed in targeted batch experiments using laboratory-scale biofilm reactors operated under aerobic and anaerobic conditions. A one-dimensional model was developed to simulate diffusive transport, abiotic and biotic transformation, and partitioning of drug biomarkers.
Model calibration to experimental results allowed estimating biotransformation rate constants in sewer biofilms, which were compared to those obtained for suspended biomass. Our results suggest that sewer biofilms can enhance the biotransformation kinetics of most selected compounds. Through scenario simulations, we demonstrated that the estimation of biotransformation rate constants in biofilm can be significantly biased if the boundary layer thickness is not accurately estimated.
This study complements our previous investigation on the transformation and sorption of drug biomarkers in the presence of only suspended biomass in untreated sewage. A better understanding of the role of sewer biofilmsalso relative to the in-sewer suspended solidsand improved prediction of associated fate processes can result in more accurate estimation of daily drug consumption in urban areas in wastewater-based epidemiological assessments.
Language: | English |
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Publisher: | American Chemical Society |
Year: | 2017 |
Pages: | 10572-10584 |
ISSN: | 15205851 and 0013936x |
Types: | Journal article |
DOI: | 10.1021/acs.est.6b06277 |