From the highway to receiving water bodies: identification and simultaneous quantification of small microplastics (< 100 µm) in highway stormwater runoff.

Highway stormwater (HSW) runoff is among the environment's most important sources of microplastics. This study aimed to characterize via vibrational spectroscopy and quantify SMPs (small microplastics < 100 µm) in HSW runoff from a trafficked highway entering a facility equipped with a filtration system and in those flowing out to the receiving water body near agricultural activities. Samples of the inlet runoff (from the highway) and outlet runoff (the discharge into the environment) were collected in different periods to investigate potential seasonal and spatial differences.

Monitoring (micro-)pollutants in wastewater treatment plants: Comparing discharges in wet- and dry-weather.

Municipal wastewater treatment plants (WWTPs) are crucial for maintaining good quality of surface water, limiting environmental pollution. However, during wet-weather events, WWTPs become an important point-source discharge due to the activation of the bypass, which releases a mix of untreated wastewater and stormwater. This work aims to assess how the WWTP discharges (effluent and bypass) impact on the receiving surface water body during dry- and wet-weather, monitoring 78 pollutants (7 conventional pollutants, 19 heavy metals, and 52 micropollutants) in each stream (effluent during dry-weather, effluent and bypass during wet-weather), including the influent in dry-weather for comparison.

Temporal variations in micropollutant inlet concentrations matter when planning the design and compliance assessment of stormwater control measures.

Stormwater Control Measures (SCMs) contribute to reducing micropollutant emissions from separate sewer systems. SCM planning and design are often performed by looking at the hydrological performance. Assessment of pollutant removal and the ability to comply with discharge concentration limits is often simplified due to a lack of data and limited monitoring resources.

Quantification and characterization of additives, plasticizers, and small microplastics (5-100 μm) in highway stormwater runoff.

Highway stormwater (HSW) runoff is a significant pathway for transferring microplastics from land-based sources to the other surrounding environmental compartments. Small microplastics (SMPs, 5-100 μm), additives, plasticizers, natural, and nonplastic synthetic fibers, together with other components of micro-litter (APFs), were assessed in HSW samples via Micro-FTIR; oleo-extraction and purification procedures previously developed were optimized to accomplish this goal. The distribution of SMPs and APFs observed in distinct HSW runoff varied significantly since rainfall events may play a crucial role in the concentration and distribution of these pollutants.

A decade of monitoring micropollutants in urban wet-weather flows: What did we learn?

Urban wet-weather discharges from combined sewer overflows (CSO) and stormwater outlets (SWO) are a potential pathway for micropollutants (trace contaminants) to surface waters, posing a threat to the environment and possible water reuse applications. Despite large efforts to monitor micropollutants in the last decade, the gained information is still limited and scattered. In a metastudy we performed a data-driven analysis of measurements collected at 77 sites (683 events, 297 detected micropollutants) over the last decade to investigate which micropollutants are most relevant in terms of 1) occurrence and 2) potential risk for the aquatic environment, 3) estimate the minimum number of data to be collected in monitoring studies to reliably obtain concentration estimates, and 4) provide recommendations for future monitoring campaigns.

The transition of WRRF models to digital twin applications.

Digital Twins (DTs) are on the rise as innovative, powerful technologies to harness the power of digitalisation in the WRRF sector. The lack of consensus and understanding when it comes to the definition, perceived benefits and technological needs of DTs is hampering their widespread development and application. Transitioning from traditional WRRF modelling practice into DT applications raises a number of important questions: When is a model's predictive power acceptable for a DT? Which modelling frameworks are most suited for DT applications? Which data structures are needed to efficiently feed data to a DT? How do we keep the DT up to date and relevant? Who will be the main users of DTs and how to get them involved? How do DTs push the water sector to evolve? This paper provides an overview of the state-of-the-art, challenges, good practices, development needs and transformative capacity of DTs for WRRF applications.

Classifying pollutant flush signals in stormwater using functional data analysis on TSS MV curves.

Pollution levels in stormwater vary significantly during rain events, with pollutant flushes carrying a major fraction of an event pollutant load in a short period. Understanding these flushes is thus essential for stormwater management. However, current studies mainly focus on describing the first flush or are limited by predetermined flush categories.

Optimal control towards sustainable wastewater treatment plants based on multi-agent reinforcement learning.

Wastewater treatment plants (WWTPs) are designed to eliminate pollutants and alleviate environmental pollution resulting from human activities. However, the construction and operation of WWTPs consume resources, emit greenhouse gases (GHGs) and produce residual sludge, thus require further optimization. WWTPs are complex to control and optimize because of high non-linearity and variation.

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).

Reconstruction of corrupted datasets from ammonium-ISE sensors at WRRFs through merging with daily composite samples.

Long-term, continuous datasets of high quality are important for instrumentation, control, and automation efforts of wastewater resources recovery facility (WRRFs). This study presents a methodology to increase the reliability of measurements from ammonium ion-selective electrodes (ISEs). This is done by correcting corrupted ISE data with a data source that often is available at WRRFs (volume-proportional composite samples).

Evaluating the performance of a simple phenomenological model for online forecasting of ammonium concentrations at WWTP inlets.

A simple model for online forecasting of ammonium (NH ) concentrations in sewer systems is proposed. The forecast model utilizes a simple representation of daily NH profiles and the dilution approach combined with information from online NH and flow sensors. The method utilizes an ensemble approach based on past observations to create model prediction bounds.

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.

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.

Towards model predictive control: online predictions of ammonium and nitrate removal by using a stochastic ASM.

Online model predictive control (MPC) of water resource recovery facilities (WRRFs) requires simple and fast models to improve the operation of energy-demanding processes, such as aeration for nitrogen removal. Selected elements of the activated sludge model number 1 modelling framework for ammonium and nitrate removal were included in discretely observed stochastic differential equations in which online data are assimilated to update the model states. This allows us to produce model-based predictions including uncertainty in real time while it also reduces the number of parameters compared to many detailed models.

Pollution levels of stormwater discharges and resulting environmental impacts.

Stormwater carries pollutants that potentially cause negative environmental impacts to receiving water bodies, which can be quantified using life cycle impact assessment (LCIA). We compiled a list of 20 metals, almost 300 organic compounds, and nutrients potentially present in stormwater, and measured concentrations reported in literature. We calculated mean pollutant concentrations, which we then translated to generic impacts per litre of stormwater discharged, using existing LCIA characterisation factors.

Revisiting conceptual stormwater quality models by reconstructing virtual state variables.

This work proposes a Bayesian non-informative reconstruction of virtual state variables in the representation of stormwater total suspended solids pollutographs by the traditional wash-off models, based on 255 rainfall events measured in a 185 ha French urban catchment. Results from event-based analyses revealed the missing representation of an essential process in the traditional rating curve (RC) model (simplest wash-off model) for 56% of the rainfall events. The unsatisfactory performances of the RC model are found to be not necessarily linked to antecedent dry weather conditions, as assumed by a great number of accumulation/wash-off models.

Effect of climate change on stormwater runoff characteristics and treatment efficiencies of stormwater retention ponds: a case study from Denmark using TSS and Cu as indicator pollutants.

This study investigated the potential effect of climate changes on stormwater pollution runoff characteristics and the treatment efficiency of a stormwater retention pond in a 95 ha catchment in Denmark. An integrated dynamic stormwater runoff quality and treatment model was used to simulate two scenarios: one representing the current climate and another representing a future climate scenario with increased intensity of extreme rainfall events and longer dry weather periods. 100-year long high-resolution rainfall time series downscaled from regional climate model projections were used as input.

Urban drainage models--simplifying uncertainty analysis for practitioners.

There is increasing awareness about uncertainties in the modelling of urban drainage systems and, as such, many new methods for uncertainty analyses have been developed. Despite this, all available methods have limitations which restrict their widespread application among practitioners. Here, a modified Monte-Carlo based method is presented that reduces the subjectivity inherent in typical uncertainty approaches (e.

Velocity dependent passive sampling for monitoring of micropollutants in dynamic stormwater discharges.

Micropollutant monitoring in stormwater discharges is challenging because of the diversity of sources and thus large number of pollutants found in stormwater. This is further complicated by the dynamics in runoff flows and the large number of discharge points. Most passive samplers are nonideal for sampling such systems because they sample in a time-integrative manner.

Modelling and monitoring of integrated urban wastewater systems: review on status and perspectives.

While the general principles and modelling approaches for integrated management/modelling of urban water systems already present a decade ago still hold, in recent years aspects like model interfacing and wastewater treatment plant (WWTP) influent generation as complements to sewer modelling have been investigated and several new or improved systems analysis methods have become available. New/improved software tools coupled with the current high computational capacity have enabled the application of integrated modelling to several practical cases, and advancements in monitoring water quantity and quality have been substantial and now allow the collecting of data in sufficient quality and quantity to permit using integrated models for real-time applications too. Further developments are warranted in the field of data quality assurance and efficient maintenance.

Model-based monitoring of stormwater runoff quality.

Monitoring of micropollutants (MP) in stormwater is essential to evaluate the impacts of stormwater on the receiving aquatic environment. The aim of this study was to investigate how different strategies for monitoring of stormwater quality (combining a model with field sampling) affect the information obtained about MP discharged from the monitored system. A dynamic stormwater quality model was calibrated using MP data collected by automatic volume-proportional sampling and passive sampling in a storm drainage system on the outskirts of Copenhagen (Denmark) and a 10-year rain series was used to find annual average (AA) and maximum event mean concentrations.

Comparison of different uncertainty techniques in urban stormwater quantity and quality modelling.

Urban drainage models are important tools used by both practitioners and scientists in the field of stormwater management. These models are often conceptual and usually require calibration using local datasets. The quantification of the uncertainty associated with the models is a must, although it is rarely practiced.

Modelling the fate of organic micropollutants in stormwater ponds.

Urban water managers need to estimate the potential removal of organic micropollutants (MP) in stormwater treatment systems to support MP pollution control strategies. This study documents how the potential removal of organic MP in stormwater treatment systems can be quantified by using multimedia models. The fate of four different MP in a stormwater retention pond was simulated by applying two steady-state multimedia fate models (EPI Suite and SimpleBox) commonly applied in chemical risk assessment and a dynamic multimedia fate model (Stormwater Treatment Unit Model for Micro Pollutants--STUMP).