A model library for dynamic transport and fate of micropollutants in integrated urban wastewater and stormwater systems

Vezzaro, Luca; Benedetti, Lorenzo; Gevaert, Veerle; Keyser, Webbey De; Verdonck, Frederik; Baets, Bernard De; Nopens, Ingmar; Cloutier, Frédéric; Vanrolleghem, Peter A.; Mikkelsen, Peter Steen

doi:10.1016/j.envsoft.2013.11.010

Cited by 39 publications

(24 citation statements)

References 40 publications

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“…SimpleTreat and multimedia models in general require limited input (steady-state emission rate and physico-biochemical characteristics of the substances assessed) and are indicated for generic fate/exposure assessments (Struijs, 1996;Keller, 2006). Mass-or concentrationbased process models (Joss et al, 2006), also implemented as extension of traditional activated sludge models (Pl osz et al, 2010(Pl osz et al, , 2012Vezzaro et al, 2014), represent an alternative approach for assessing the fate in WWTPs. These models are usually dynamic and allow for correlating elimination of trace chemicals with conventional WWTP processes (e.g., by describing biotransformation as a cometabolic process).…”

Section: Introductionmentioning

confidence: 99%

From consumption to harvest: Environmental fate prediction of excreted ionizable trace organic chemicals

2015

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Section: Introductionmentioning

confidence: 99%

From consumption to harvest: Environmental fate prediction of excreted ionizable trace organic chemicals

2015

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“…These models are used as decision support tools to help understand the underlying mechanisms of micropollutant fate in the WWTP, and thus they provide a prediction of the efficiency of different treatment technologies (Lindblom et al 2006;Snip et al 2014;Vezzaro et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Generation of synthetic influent data to perform (micro)pollutant wastewater treatment modelling studies

Snip

Flores-Alsina

Aymerich

et al. 2016

Science of The Total Environment

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The use of process models to simulate the fate of micropollutants in wastewater treatment plants is constantly growing. However, due to the high workload and cost of measuring campaigns, many simulation studies lack sufficiently long time series representing realistic wastewater influent dynamics. In this paper, the feasibility of the Benchmark Simulation Model No. 2 (BSM2) influent generator is tested to create realistic dynamic influent (micro)pollutant disturbance scenarios. The presented set of models is adjusted to describe the occurrence of three pharmaceutical compounds and one of each of its metabolites with samples taken every 2-4h: the anti-inflammatory drug ibuprofen (IBU), the antibiotic sulfamethoxazole (SMX) and the psychoactive carbamazepine (CMZ). Information about type of excretion and total consumption rates forms the basis for creating the data-defined profiles used to generate the dynamic time series. In addition, the traditional influent characteristics such as flow rate, ammonium, particulate chemical oxygen demand and temperature are also modelled using the same framework with high frequency data. The calibration is performed semi-automatically with two different methods depending on data availability. The 'traditional' variables are calibrated with the Bootstrap method while the pharmaceutical loads are estimated with a least squares approach. The simulation results demonstrate that the BSM2 influent generator can describe the dynamics of both traditional variables and pharmaceuticals. Lastly, the study is complemented with: 1) the generation of longer time series for IBU following the same catchment principles; 2) the study of the impact of in-sewer SMX biotransformation when estimating the average daily load; and, 3) a critical discussion of the results, and the future opportunities of the presented approach balancing model structure/calibration procedure complexity versus predictive capabilities.

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“…Carbon footprint [29] Stakeholder preferences [30] Thorough ecosystem [31] Rapid ecosystem [32] X Flext (DayWater) [33] SWMPT [34] X BMP MCA [35] BMP DSM [36] Project choice [37] MCA/cost [38] X X SWITCH BMP DSS [39] SUDS potential [40] X X X X X SUSTAIN [41] UHRU [42] X X X LIDRA [43] STEPL [44] X X X X X MCA&CBA [45] X X X X Flood Risk CBA [46] X X X SUDSLOC [47] When going through our search results we focused more on water quantity issues than water quality, and hence tools that focus on water quality were omitted. For examples of tools with specific focus on water quality issues, see e.g., [12][13][14]. We also omitted tools that focus on the broader issue of integrated urban water management, although some of these tools include functionality that is similar to the categories defined here; for examples of such tools see e.g., [15][16][17][18].…”

Section: Categorization Based On Questions Addressed By the Toolsmentioning

confidence: 99%

A Mapping of Tools for Informing Water Sensitive Urban Design Planning Decisions—Questions, Aspects and Context Sensitivity

Lerer

Arnbjerg‐Nielsen

Mikkelsen

2015

Water

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Water Sensitive Urban Design (WSUD) poses new challenges for decision makers compared with traditional stormwater management, e.g., because WSUD offers a larger selection of measures and because many measures are multifunctional. These challenges have motivated the development of many decision support tools. This review shows that the tools differ in terms of the types of questions they can assist in answering. We identified three main groups: "How Much"-tools, "Where"-tools and "Which"-tools. The "How Much"-tools can further be grouped into tools quantifying hydraulic impacts, hydrologic impacts, water quality impacts, non-flow-related impacts and economic impacts. Additionally, the tools differ in terms of how many aspects of water they address, from those focused only on bio-physical aspects to those attempting to find the best WSUD based on multiple criteria. Finally, we suggest that variability among the tools can partly be explained by variability in local context including conditions such as type of existing stormwater systems, groundwater conditions and legislative frameworks.

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A model library for dynamic transport and fate of micropollutants in integrated urban wastewater and stormwater systems

Cited by 39 publications

References 40 publications

From consumption to harvest: Environmental fate prediction of excreted ionizable trace organic chemicals

From consumption to harvest: Environmental fate prediction of excreted ionizable trace organic chemicals

Generation of synthetic influent data to perform (micro)pollutant wastewater treatment modelling studies

A Mapping of Tools for Informing Water Sensitive Urban Design Planning Decisions—Questions, Aspects and Context Sensitivity

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