Modelling and prediction of the effect of operational parameters on the fate of contaminants of emerging concern in WWTPs.

Wastewater treatment plants (WWTPs) provide a barrier against the discharge of contaminants of emerging concern (CECs) into the environment. The removal of CECs is highly WWTP-specific and the underlying mechanisms are still poorly understood, hampering the optimization of biological treatment steps for their removal. To fill this knowledge gap, we assessed the influence of four operational parameters of activated sludge biological treatment, namely total suspended solids, temperature, pH and redox conditions, on the sorption and biodegradation of four CECs under controlled laboratory conditions. Design of Experiments was used to better address the factors influencing CECs removal and interactions among operational parameters. The derived statistical models showed results in concordance with previous studies and indicated how sorption and biodegradation of the investigated CECs depend on most tested parameters and few of their interactions. The predictions of the developed models have been compared with literature values, indicating how the tested parameters are responsible for most of the variability of sorption, while they could not reliably generalize biodegradation rates. The developed models were also implemented as an extension of a mechanistic biological treatment model, successfully describing the dynamic behaviour of a large-scale WWTP, which was observed during a three-day continuous monitoring campaign. Compared to a traditional modelling approach, the one including the developed models showed on average almost a three-fold uncertainty reduction, favouring its use to aid WWTP managers and regulators for improved assessment of CEC fate and removal. Finally, the models highlighted that, while higher temperatures and solids concentrations generically favoured CECs removal, removal efficiency vary significantly due to operational parameters and no globally optimum conditions for CECs removal exist. The use of these models opens the door to the combined dynamic management of both traditional contaminants and CECs in WWTPs.

A hybrid Neural Network-SEIR model for forecasting intensive care occupancy in Switzerland during COVID-19 epidemics.

Anticipating intensive care unit (ICU) occupancy is critical in supporting decision makers to impose (or relax) measures that mitigate COVID-19 transmission. Mechanistic approaches such as Susceptible-Infected-Recovered (SIR) models have traditionally been used to achieve this objective. However, formulating such models is challenged by the necessity to formulate equations for plausible causal mechanisms between the intensity of COVID-19 transmission and external epidemic drivers such as temperature, and the stringency of non-pharmaceutical interventions. Here, we combined a neural network model (NN) with a Susceptible-Exposed-Infected-Recovered model (SEIR) in a hybrid model and attempted to increase the prediction accuracy of existing models used to forecast ICU occupancy. Between 1st of October, 2020 - 1st of July, 2021, the hybrid model improved performances of the SEIR model at different geographical levels. At a national level, the hybrid model improved, prediction accuracy (i.e., mean absolute error) by 74%. At the cantonal and hospital levels, the reduction on the forecast's mean absolute error were 46% and 50%, respectively. Our findings illustrate those predictions from hybrid model can be used to anticipate occupancy in ICU, and support the decision-making for lifesaving actions such as the transfer of patients and dispatching of medical personnel and ventilators.

Modelling the fate of micropollutants in integrated urban wastewater systems: Extending the applicability to pharmaceuticals.

Pharmaceutical active compounds (PhACs) are a category of micropollutants frequently detected across integrated urban wastewater systems. Existing modelling tools supporting the evaluation of micropollutant fate in such complex systems, such as the IUWS_MP model library (which acronym IUWS stands for Integrated Urban Wastewater System), do not consider fate processes and fractions that are typical for PhACs. This limitation was overcome by extending the existing IUWS_MP model library with new fractions (conjugated metabolites, sequestrated fraction) and processes (consumption-excretion, deconjugation). The performance of the extended library was evaluated for five PhACs (carbamazepine, ibuprofen, diclofenac, paracetamol, furosemide) in two different integrated urban wastewater systems where measurements were available. Despite data uncertainty and the simplicity of the modelling approach, chosen to minimize data requirements, model prediction uncertainty overlapped with the measurements ranges across both systems, stressing the robustness of the proposed modelling approach. Possible applications of the extended IUWS_MP model library are presented, illustrating how this tool can support urban water managers in reducing environmental impacts from PhACs discharges.

A statistical assessment of micropollutants occurrence, time trend, fate and human health risk using left-censored water quality data.

In recent years, the presence of micropollutants in drinking water has become an issue of growing global concern. Due to their low concentrations, monitoring databases are usually rich in censored data (e.g. samples with concentrations reported below the limit of quantification, LOQ) which are typically eliminated or replaced with a value arbitrarily chosen between 0 and LOQ. These conventional methods have some limitations and can lead to erroneous conclusions on: presence of micropollutants in the source water, treatment efficiencies, produced water quality and associated human health risk. In this work, an advanced approach, based on Maximum Likelihood Estimation method for left-censored data (MLELC), was applied on monitoring data of 19 contaminants (metals, volatile organic compounds, pesticides and perfluorinated compounds) in 5362 groundwater (GW) and 12,344 drinking water (DW) samples, collected from 2012 to 2017 in 28 drinking water treatment plants in an urbanized area. This study demonstrates the benefits of MLELC method, especially for high percentages of censored data. Data are used to build statistical distributions which can be effectively used for several applications, such as the time trend evaluation of GW micropollutant concentrations and the estimation of treatment removal efficiency, highlighting the adequacy or the need for an upgrade. Moreover, the MLELC method has been applied to assess the human health risk associated with micropollutants, indicating the high discrepancy in the estimations obtained with conventional methods, whose results do not follow precautionary or sustainability criteria.

Risk assessment of contaminants of emerging concern in the context of wastewater reuse for irrigation: An integrated modelling approach.

Direct reuse of reclaimed wastewater (RWW) in agriculture has recently received increasing attention as a possible solution to water scarcity. The presence of contaminants of emerging concern (CECs) in RWW can be critical, as these chemicals can be uptaken in irrigated crops and eventually ingested during food consumption. In the present study, an integrated model was developed to predict the fate of CECs in water reuse systems where RWW is used for edible crops irrigation. The model was applied to a case study where RWW (originating from a municipal wastewater treatment plant) is discharged into a water channel, with subsequent irrigation of silage maize, rice, wheat and ryegrass. Environmental and human health risks were assessed for 13 CECs, selected based on their chemical and hazard characteristics. Predicted CEC concentrations in the channel showed good agreement with available measurements, indicating potential ecotoxicity of some CECs (estrogens and biocides) due to their limited attenuation. Plant uptake predictions were in good agreement with existing literature data, indicating higher uptake in leaves and roots than fruits. Notably, high uncertainties were shown for weakly acidic CECs, possibly due to degradation in soil and pH variations inside plants. The human health risk due to the ingestion of wheat and rice was assessed using the threshold of toxicological concern and the hazard quotient. Both approaches predicted negligible risk for most CECs, while sulfamethoxazole and 17α-ethinylestradiol exhibited the highest risk for consumers. Alternative scenarios were evaluated to identify possible risk minimization strategies (e.g., adoption of a more efficient irrigation system).

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

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.