Journal article
A systematic model identification method for chemical transformation pathways – the case of heroin biomarkers in wastewater
Department of Environmental Engineering, Technical University of Denmark1
Water Technologies, Department of Environmental Engineering, Technical University of Denmark2
Department of Chemical and Biochemical Engineering, Technical University of Denmark3
CAPEC-PROCESS, Department of Chemical and Biochemical Engineering, Technical University of Denmark4
Environmental Chemistry, Department of Environmental Engineering, Technical University of Denmark5
Water Resources Engineering, Department of Environmental Engineering, Technical University of Denmark6
This study presents a novel statistical approach for identifying sequenced chemical transformation pathways in combination with reaction kinetics models. The proposed method relies on sound uncertainty propagation by considering parameter ranges and associated probability distribution obtained at any given transformation pathway levels as priors for parameter estimation at any subsequent transformation levels.
The method was applied to calibrate a model predicting the transformation in untreated wastewater of six biomarkers, excreted following human metabolism of heroin and codeine. The method developed was compared to parameter estimation methods commonly encountered in literature (i.e., estimation of all parameters at the same time and parameter estimation with fix values for upstream parameters) by assessing the model prediction accuracy, parameter identifiability and uncertainty analysis.
Results obtained suggest that the method developed has the potential to outperform conventional approaches in terms of prediction accuracy, transformation pathway identification and parameter identifiability. This method can be used in conjunction with optimal experimental designs to effectively identify model structures and parameters.
This method can also offer a platform to promote a closer interaction between analytical chemists and modellers to identify models for biochemical transformation pathways, being a prominent example for the emerging field of wastewater-based epidemiology.
Language: | English |
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Publisher: | Nature Publishing Group UK |
Year: | 2017 |
Pages: | 9390 |
ISSN: | 20452322 |
Types: | Journal article |
DOI: | 10.1038/s41598-017-09313-y |
ORCIDs: | Ramin, Pedram , Valverde Pérez, Borja , Polesel, Fabio and Locatelli, Luca |