Modelling micropollutant fate in sewer systems – A new systematic approach to support conceptual model construction based on in-sewer hydraulic retention time

Research output: Contribution to journalJournal article – Annual report year: 2019Researchpeer-review

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Conceptual sewer models are useful tools to assess the fate of micropollutants (MPs) in integrated wastewater systems. However, the definition of their model structure is highly subjective, and obtaining a realistic simulation of the in-sewer hydraulic retention time (HRT) is a major challenge without detailed hydrodynamic information or with limited measurements from the sewer network. This study presents an objective approach for defining the structure of conceptual sewer models in view of modelling MP fate in large urban catchments. The proposed approach relies on GIS-based information and a Gaussian mixture model to identify the model optimal structure, providing a multi-catchment conceptual model that accounts for HRT variability across urban catchment. This approach was tested in a catchment located in a highly urbanized Italian city and it was compared against a traditional single-catchment conceptual model (using a single average HRT) for the fate assessment of reactive MPs. Results showed that the multi-catchment model allows for a successful simulation of dry weather flow patterns and for an improved simulation of MP fate compared to the classical single-catchment model. Specifically, results suggested that a multi-catchment model should be preferred for (i) degradable MPs with half-life lower than the average HRT of the catchment and (ii) MPs undergoing formation from other compounds (e.g. human metabolites); or (iii) assessing MP loads entering the wastewater treatment plant from point sources, depending on their location in the catchment. Overall, the proposed approach is expected to ease the building of conceptual sewer models, allowing to properly account for HRT distribution and consequently improving MP fate estimation.

Original languageEnglish
JournalJournal of Environmental Management
Volume246
Pages (from-to)141-149
ISSN0301-4797
DOIs
Publication statusPublished - 2019
CitationsWeb of Science® Times Cited: No match on DOI

    Research areas

  • Cluster analysis, Emerging contaminants, Geographical information system, Sewer system modelling, Wastewater-based epidemiology

ID: 183364136