Wastewater-Based Epidemiological Engineering—Modeling Illicit Drug Biomarker Fate in Sewer Systems as a Means To Back-Calculate Urban Chemical Consumption Rates

Research output: Chapter in Book/Report/Conference proceedingBook chapter – Annual report year: 2019Researchpeer-review

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In this chapter, we present the Activated Sludge Model for Xenobiotics (ASM-X), which offers the largest systematic and consistent database to predict illicit drug and pharmaceutical biomarker fate in wastewater conveyed in sewer pipes. ASM-X was originally developed for predicting the removal of trace organic pharmaceutical chemical pollutants (micropollutants), notably antibiotics in biological wastewater treatment. Here, we present the identification of simulation models in the ASM-X framework for illicit biomarker transformation, physicochemical partitioning onto particulate matter, and diffusive transport in biofilms. Model parameters were estimated using experimental data obtained with in-sewer biocatalytic environments represented by suspended solids and biofilm. A systematic methodology for inferring reliable estimates of unique parameter sets in tandem with chemical transformation pathways was developed using Bayesian optimization. This is a method that can be generalized to any other chemodynamics problems focusing on quantifying chemical biotransformation using external prior metabolic information. The method developed can offer a platform to promote a more effective interaction between analytical chemists and modelers to develop smart experimental designs conducive to effective model development. Additionally, the identification method developed can be used in conjunction with optimal experimental designs to effectively identify model structures and parameters.
Original languageEnglish
Title of host publicationWastewater-Based Epidemiology: Estimation of Community Consumption of Drugs and Diets
EditorsBikram Subedi, Daniel A. Burgard, Bommanna G. Loganathan
PublisherAmerican Chemical Society
Publication date2019
Pages99-115
Chapter5
ISBN (Print)9780841234413
ISBN (Electronic)9780841234406
DOIs
Publication statusPublished - 2019
SeriesA C S Symposium Series
Volume1319
ISSN0097-6156
CitationsWeb of Science® Times Cited: No match on DOI

ID: 185301158