Wastewater-Based Epidemiological Engineering - Modeling Illicit Drug Biomarker Fate in Sewer Systems as a Means to Back-Calculate Urban Chemical Consumption Rates: Modelling illicit drug biomarker fate in sewer systems as a means to back-calculate urban chemical consumption rates

Benedek Gy Plosz, Pedram Ramin

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

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
Subtitle of host publicationEstimation of Community Consumption of Drugs and Diets
EditorsBikram Subedi, Daniel A. Burgard, Bommanna G. Loganathan
PublisherAmerican Chemical Society
Chapter5
Pages99-115
Number of pages17
ISBN (Electronic)780841234406
ISBN (Print)9780841234413
DOIs
Publication statusPublished - 1 Jan 2019

Publication series

NameACS Symposium Series
Volume1319
ISSN (Print)0097-6156
ISSN (Electronic)1947-5918

ASJC Scopus subject areas

  • Chemistry(all)
  • Chemical Engineering(all)

Cite this

Plosz, B. G., & Ramin, P. (2019). Wastewater-Based Epidemiological Engineering - Modeling Illicit Drug Biomarker Fate in Sewer Systems as a Means to Back-Calculate Urban Chemical Consumption Rates: Modelling illicit drug biomarker fate in sewer systems as a means to back-calculate urban chemical consumption rates. In B. Subedi, D. A. Burgard, & B. G. Loganathan (Eds.), Wastewater-Based Epidemiology: Estimation of Community Consumption of Drugs and Diets (pp. 99-115). (ACS Symposium Series; Vol. 1319). American Chemical Society. https://doi.org/10.1021/bk-2019-1319.ch005

Wastewater-Based Epidemiological Engineering - Modeling Illicit Drug Biomarker Fate in Sewer Systems as a Means to Back-Calculate Urban Chemical Consumption Rates : Modelling illicit drug biomarker fate in sewer systems as a means to back-calculate urban chemical consumption rates. / Plosz, Benedek Gy; Ramin, Pedram.

Wastewater-Based Epidemiology: Estimation of Community Consumption of Drugs and Diets. ed. / Bikram Subedi; Daniel A. Burgard; Bommanna G. Loganathan. American Chemical Society, 2019. p. 99-115 (ACS Symposium Series; Vol. 1319).

Research output: Chapter in Book/Report/Conference proceedingChapter

Plosz, BG & Ramin, P 2019, Wastewater-Based Epidemiological Engineering - Modeling Illicit Drug Biomarker Fate in Sewer Systems as a Means to Back-Calculate Urban Chemical Consumption Rates: Modelling illicit drug biomarker fate in sewer systems as a means to back-calculate urban chemical consumption rates. in B Subedi, DA Burgard & BG Loganathan (eds), Wastewater-Based Epidemiology: Estimation of Community Consumption of Drugs and Diets. ACS Symposium Series, vol. 1319, American Chemical Society, pp. 99-115. https://doi.org/10.1021/bk-2019-1319.ch005
Plosz, Benedek Gy ; Ramin, Pedram. / Wastewater-Based Epidemiological Engineering - Modeling Illicit Drug Biomarker Fate in Sewer Systems as a Means to Back-Calculate Urban Chemical Consumption Rates : Modelling illicit drug biomarker fate in sewer systems as a means to back-calculate urban chemical consumption rates. Wastewater-Based Epidemiology: Estimation of Community Consumption of Drugs and Diets. editor / Bikram Subedi ; Daniel A. Burgard ; Bommanna G. Loganathan. American Chemical Society, 2019. pp. 99-115 (ACS Symposium Series).
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abstract = "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.",
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