title: Generation of synthetic influent data to perform (micro)pollutant wastewater treatment modelling studies.
abstract: 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.
authors.affiliation: CAPEC-PROCESS Research Center, Department of Chemical and Biochemical Engineering, Technical University of Denmark, Building 229, DK-2800 Kgs. Lyngby, Denmark.
authors.forename: L J P
authors.initials: LJP
authors.lastname: Snip
authors.affiliation: CAPEC-PROCESS Research Center, Department of Chemical and Biochemical Engineering, Technical University of Denmark, Building 229, DK-2800 Kgs. Lyngby, Denmark.
authors.forename: X
authors.initials: X
authors.lastname: Flores-Alsina
authors.affiliation: ICRA, Catalan Institute for Water Research, Scientific and Technological Park of the University of Girona, Emili Grahit, 101, E-17003 Girona, Spain.
authors.forename: I
authors.initials: I
authors.lastname: Aymerich
authors.affiliation: ICRA, Catalan Institute for Water Research, Scientific and Technological Park of the University of Girona, Emili Grahit, 101, E-17003 Girona, Spain.
authors.forename: S
authors.initials: S
authors.lastname: Rodríguez-Mozaz
authors.affiliation: ICRA, Catalan Institute for Water Research, Scientific and Technological Park of the University of Girona, Emili Grahit, 101, E-17003 Girona, Spain; Water and Soil Quality Research Group, Department of Environmental Chemistry, IDAEA-CSIC, Jordi Girona 18-26, 08034 Barcelona, Spain.
authors.forename: D
authors.initials: D
authors.lastname: Barceló
authors.affiliation: Urban Water Engineering (UWE) Section, Department of Environmental Engineering, Technical University of Denmark, Building 115, DK-2800 Kgs. Lyngby, Denmark.
authors.forename: B G
authors.initials: BG
authors.lastname: Plósz
authors.affiliation: ICRA, Catalan Institute for Water Research, Scientific and Technological Park of the University of Girona, Emili Grahit, 101, E-17003 Girona, Spain.
authors.forename: Ll
authors.initials: L
authors.lastname: Corominas
authors.affiliation: ICRA, Catalan Institute for Water Research, Scientific and Technological Park of the University of Girona, Emili Grahit, 101, E-17003 Girona, Spain; LEQUIA, Institute of the Environment, University of Girona, E17071 Girona, Spain.
authors.forename: I
authors.initials: I
authors.lastname: Rodriguez-Roda
authors.affiliation: Division of Industrial Electrical Engineering and Automation (IEA), Department of Biomedical Engineering (BME), Lund University, Box 118, SE-221 00 Lund, Sweden.
authors.forename: U
authors.initials: U
authors.lastname: Jeppsson
authors.affiliation: CAPEC-PROCESS Research Center, Department of Chemical and Biochemical Engineering, Technical University of Denmark, Building 229, DK-2800 Kgs. Lyngby, Denmark. Electronic address: kvg@kt.dtu.dk.
authors.forename: K V
authors.initials: KV
authors.lastname: Gernaey
mesh_terms: D000890:Anti-Infective Agents / Q000032:analysis; D000894:Anti-Inflammatory Agents, Non-Steroidal / Q000032:analysis; D018692:Antimanic Agents / Q000032:analysis; D002220:Carbamazepine / Q000032:analysis; D007052:Ibuprofen / Q000032:analysis; D008962:Models, Theoretical; D013420:Sulfamethoxazole / Q000032:analysis; D014865:Waste Disposal, Fluid / Q000379:methods*; D014874:Water Pollutants, Chemical / Q000032:analysis*
chemical_list: D000890:Anti-Infective Agents; D000894:Anti-Inflammatory Agents, Non-Steroidal; D018692:Antimanic Agents; D014874:Water Pollutants, Chemical; D002220:Carbamazepine; D013420:Sulfamethoxazole; D007052:Ibuprofen
keywords: BSM2 influent generator; Calibration; Micropollutant occurrence; Trace chemicals; Xenobiotics