Adapting SimpleTreat for simulating behaviour of chemical substances during industrial sewage treatment

Struijs, Jeroen N.; Meent, Dik van de; Schowanek, Diederik; Buchholz, H.; Patoux, R.; Wolf, T.; Austin, Thomas; Tolls, Johannes; Leeuwen, Cornelis van; Galay-Burgos, Malyka

doi:10.1016/j.chemosphere.2016.06.063

Cited by 16 publications

(8 citation statements)

References 4 publications

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“…Such properties of chemicals are used in standard process-based models to estimate REs of chemicals in WWTPs 12 . One example is the SimpleTreat model 13 , which is widely-used in regulatory risk assessment to predict REs of chemicals in activated sludge WWTPs under standard operating conditions 14 .…”

Section: Introductionmentioning

confidence: 99%

Quantifying variability in removal efficiencies of chemicals in activated sludge wastewater treatment plants – a meta-analytical approach

Douziech

Conesa

Benítez‐López

et al. 2018

Environ. Sci.: Processes Impacts

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Large variations in removal efficiencies (REs) of chemicals have been reported for monitoring studies of activated sludge wastewater treatment plants (WWTPs). In this work, we conducted a meta-analysis on REs (1539 data points) for a set of 209 chemicals consisting of fragrances, surfactants, and pharmaceuticals in order to assess the drivers of the variability relating to inherent properties of the chemicals and operational parameters of activated sludge WWTPs. For a reduced dataset (n = 542), we developed a mixed-effect model (meta-regression) to explore the observed variability in REs for the chemicals using three chemical specific factors and four WWTP-related parameters. The overall removal efficiency of the set of chemicals was 82.1% (95% CI 75.2-87.1%, N = 1539). Our model accounted for 17% of the total variability in REs, while the process-based model SimpleTreat did not perform better than the average of the measured REs. We identified that, after accounting for other factors potentially influencing RE, readily biodegradable compounds were better removed than non-readily biodegradable ones. Further, we showed that REs increased with increasing sludge retention times (SRTs), especially for non-readily biodegradable compounds. Finally, our model highlighted a decrease in RE with increasing K. The counterintuitive relationship to K stresses the need for a better understanding of electrochemical interactions influencing the RE of ionisable chemicals. In addition, we highlighted the need to improve the modelling of chemicals that undergo deconjugation when predicting RE. Our meta-analysis represents a first step in better explaining the observed variability in measured REs of chemicals. It can be of particular help to prioritize the improvements required in existing process-based models to predict removal efficiencies of chemicals in WWTPs.

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Section: Introductionmentioning

confidence: 99%

Quantifying variability in removal efficiencies of chemicals in activated sludge wastewater treatment plants – a meta-analytical approach

Douziech

Conesa

Benítez‐López

et al. 2018

Environ. Sci.: Processes Impacts

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“…Mathematical models for assessing the fate of TOrCs in wastewater treatment are effective tools for process design, optimization of existing processes, or augmentation using tertiary treatment processes for improved effluent quality (Clouzot et al, 2013). Several modeling frameworks such as ASTREAT (McAvoy et al, 1999), TOXCHEM+ (Melcer et al, 1999), WATER9 (U.S. EPA, 2001), and SimpleTreat (Struijs et al, 2016) have been developed to predict the removal of organic compounds in conventional activated sludge (CAS) systems. The ASM-X model has also been developed to include an anoxic process for denitrifying systems (Plosz et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Biotransformation and sorption of trace organic compounds in biological nutrient removal treatment systems

Lakshminarasimman

Quiñones

Vanderford

et al. 2018

Science of The Total Environment

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This study determined biotransformation rates (k) and sorption-distribution coefficients (K) for a select group of trace organic compounds (TOrCs) in anaerobic, anoxic, and aerobic activated sludge collected from two different biological nutrient removal (BNR) treatment systems located in Nevada (NV) and Ohio (OH) in the United States (US). The NV and OH facilities operated at solids retention times (SRTs) of 8 and 23 days, respectively. Using microwave-assisted extraction, the biotransformation rates of the chosen TOrCs were measured in the total mixed liquor. Sulfamethoxazole, trimethoprim, and atenolol biotransformed in all three redox regimes irrespective of the activated sludge source. The biotransformation of N, N-diethyl-3-methylbenzamide (DEET), triclosan, and benzotriazole was observed in aerobic activated sludge from both treatment plants; however, anoxic biotransformation of these three compounds was seen only in anoxic activated sludge from NV. Carbamazepine was recalcitrant in all three redox regimes and both sources of activated sludge. Atenolol and DEET had greater biotransformation rates in activated sludge with a higher SRT (23 days), while trimethoprim had a higher biotransformation rate in activated sludge with a lower SRT (8 days). The remaining compounds did not show any dependence on SRT. Lyophilized, heat inactivated sludge solids were used to determine the sorption-distribution coefficients. Triclosan was the most sorptive compound followed by carbamazepine, sulfamethoxazole, DEET, and benzotriazole. The sorption-distribution coefficients were similar across redox conditions and sludge sources. The biotransformation rates and sorption-distribution coefficients determined in this study can be used to improve fate prediction of the target TOrCs in BNR treatment systems.

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“…Specifically, SimpleBoxTreat4Solutions was constructed as a simplified (spatially and temporally invariable) version of the spatially explicit model for European water bodies as created for the European Union project SOLUTIONS (Brack et al 2015; Van Gils et al 2019, 2020). It is a combination of the emission estimation model just described with the environmental fate simulation models SimpleBox Ver 4 (Hollander et al 2016) and SimpleTreat Ver 4 (Struijs et al 2016; Lautz et al 2017), and a further simplification to a 3‐compartment (air/water/soil) version as applied in the KnowSEC decision support system developed at the German Federal Environment Agency (UBA; Striffler and Wassermann 2015). We used integrated emission + exposure modeling to test the usefulness and plausibility of the outcomes of the emission model.…”

Section: Methodsmentioning

confidence: 99%

Screening‐Level Estimates of Environmental Release Rates, Predicted Exposures, and Toxic Pressures of Currently Used Chemicals

Meent

Zwart

Posthuma

2020

Enviro Toxic and Chemistry

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We describe a procedure to quantify emissions of chemicals for environmental protection, assessment, and management purposes. The procedure uses production and use volumes from registration dossiers and combines these with Specific Environmental Release Category data. The procedure was applied in a case study. Emission estimations were made for chemicals registered under the European Union chemicals regulations for industrial chemicals (Registration, Evaluation, Authorisation and Restriction of Chemicals [REACH]) and for the active ingredients of medicines and crop protection products. Emissions themselves cannot be validated. Instead, emission estimates were followed by multimedia fate modeling and mixture toxic pressure modeling to arrive at predicted environmental concentrations (PECs) and toxic pressures for a typical European water body at steady state, which were compared with other such data. The results show that screening‐level assessments could be performed, and yielded estimates of emissions, PECs, and mixture toxic pressures of chemicals used in Europe. Steady‐state PECs agreed fairly well with measured concentrations. The mixture toxic pressure at steady state suggests the presence of effects in aquatic species assemblages, whereby few compounds dominate the predicted impact. The study shows that our screening‐level emission estimation procedure is sufficiently accurate and precise to serve as a basis for assessment of chemical pollution in aquatic ecosystems at the scale of river catchments. Given a recognized societal need to develop methods for realistic, cumulative exposures, the emission assessment procedure can assist in the prioritization of chemicals in safety policies (such as the European Union REACH regulation), where “possibility to be used safely” needs to be demonstrated, and environmental quality policies (such as the European Union Water Framework Directive), where “good environmental quality” needs to be reached. Environ Toxicol Chem 2020;39:1839–1851. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

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Adapting SimpleTreat for simulating behaviour of chemical substances during industrial sewage treatment

Cited by 16 publications

References 4 publications

Quantifying variability in removal efficiencies of chemicals in activated sludge wastewater treatment plants – a meta-analytical approach

Quantifying variability in removal efficiencies of chemicals in activated sludge wastewater treatment plants – a meta-analytical approach

Biotransformation and sorption of trace organic compounds in biological nutrient removal treatment systems

Screening‐Level Estimates of Environmental Release Rates, Predicted Exposures, and Toxic Pressures of Currently Used Chemicals

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