Enhancing reclaimed water distribution network resilience with cost-effective meshing.

Water Distribution Networks (WDNs) are critical infrastructures that ensure a continuous supply of safe water to homes. In the face of challenges, like water scarcity, establishing resilient networks is imperative, especially in regions vulnerable to water crises. This study evaluates the resilience of network designs through graph theory, including its hydraulic feasibility using EPANET software, an aspect often overlooked. Novel mathematical algorithms, including Resilience by Design (RbD) and Resilience-strengthening (RS) algorithms, provide cost-effective and resilient network designs, even with budget constraints. A novel metric, Water Availability (WA), is introduced to offer a comprehensive measure of network resilience, thereby addressing ongoing discrepancies in resilience evaluation methods. Practical benefits are illustrated through a case study in which a resilient-by-design reclaimed water network is created, and an existing equivalent non-resilient network is improved. The resilient-by-design network demonstrates remarkably better results compared to the equivalent non-resilient design, including up to a 36 % reduction in the probability of service disruptions and a nearly 65 % decrease in the annual average unserved water due to service disruptions. These findings underscore the enormous advantages of a resilience-focused network design approach. When compared to the equivalent non-resilient design, the resilient-by-design network generated effectively safeguards up to a significant 91,700m3 of water from the impacts of water disruption events over a 50-year operational period. In addition, the resilient-by-design WDN solution incurs a subtle decrease in overall costs compared to consuming tap water from the drinking WDN baseline over a 50-year operational period. These findings highlight the cost-effectiveness of the approach, even offering financial benefits. This paper builds on our previous research by expanding its scope to include resilience considerations, providing algorithms that can be easily adapted from reclaimed to drinking WDNs. Ultimately, we contribute to the enhancement of water resource management and infrastructure planning in ever-evolving urban environments.

Applying a Digital Twin and wastewater analysis for robust validation of COVID-19 pandemic forecasts: insights from Catalonia.

Monitoring SARS-CoV-2 spread is challenging due to asymptomatic infections, numerous variants, and population behavior changes from non-pharmaceutical interventions. We developed a Digital Twin model to simulate SARS-CoV-2 evolution in Catalonia. Continuous validation ensures our model's accuracy. Our system uses Catalonia Health Service data to quantify cases, hospitalizations, and healthcare impact. These data may be under-reported due to screening policy changes. To improve our model's reliability, we incorporate data from the Catalan Surveillance Network of SARS-CoV-2 in Sewage (SARSAIGUA). This paper shows how we use sewage data in the Digital Twin validation process to identify discrepancies between model predictions and real-time data. This continuous validation approach enables us to generate long-term forecasts, gain insights into SARS-CoV-2 spread, reassess assumptions, and enhance our understanding of the pandemic's behavior in Catalonia.

Profiling wastewater characteristics in intra-urban catchments using online monitoring stations.

This study aims to investigate the differences in intra-urban catchments with different characteristics through real-time wastewater monitoring. Monitoring stations were installed in three neighbourhoods of Barcelona to measure flow, total chemical oxygen demand (COD), pH, conductivity, temperature, and bisulfide (HS-) for 1 year. Typical wastewater profiles were obtained for weekdays, weekends, and holidays in the summer and winter seasons. The results reveal differences in waking up times and evening routines, commuting behaviour during weekends and holidays, and water consumption. The pollutant profiles contribute to a better understanding of pollution generation in households and catchment activities. Flows and COD correlate well at all stations, but there are differences in conductivity and HS- at the station level. The article concludes by discussing the operational experience of the monitoring stations.

Wastewater-based epidemiology applied at the building-level reveals distinct virome profiles based on the age of the contributing individuals.

BACKGROUND: Human viruses released into the environment can be detected and characterized in wastewater. The study of wastewater virome offers a consolidated perspective on the circulation of viruses within a population. Because the occurrence and severity of viral infections can vary across a person's lifetime, studying the virome in wastewater samples contributed by various demographic segments can provide valuable insights into the prevalence of viral infections within these segments. In our study, targeted enrichment sequencing was employed to characterize the human virome in wastewater at a building-level scale. This was accomplished through passive sampling of wastewater in schools, university settings, and nursing homes in two cities in Catalonia. Additionally, sewage from a large urban wastewater treatment plant was analysed to serve as a reference for examining the collective excreted human virome. RESULTS: The virome obtained from influent wastewater treatment plant samples showcased the combined viral presence from individuals of varying ages, with astroviruses and human bocaviruses being the most prevalent, followed by human adenoviruses, polyomaviruses, and papillomaviruses. Significant variations in the viral profiles were observed among the different types of buildings studied. Mamastrovirus 1 was predominant in school samples, salivirus and human polyomaviruses JC and BK in the university settings while nursing homes showed a more balanced distribution of viral families presenting papillomavirus and picornaviruses and, interestingly, some viruses linked to immunosuppression. CONCLUSIONS: This study shows the utility of building-level wastewater-based epidemiology as an effective tool for monitoring the presence of viruses circulating within specific age groups. It provides valuable insights for public health monitoring and epidemiological studies.

Seamless integration of sewer system topology and tree location data: An algorithm to diagnose the potential impact of tree roots on pipes and propose rearrangement solutions.

Wastewater networks are subject to several threats leading to wastewater leakages and public health hazards. External elements such as natural factors and human activities are common causes of wastewater leakages and require more in-depth analysis. Prevention and rehabilitation work is essential to secure wastewater networks and avoid pipe failures. This work presents a new algorithm that allows for the seamless integration of sewer topology and tree location data to diagnose the potential impact of tree roots on pipes. The algorithm also proposes tree rearrangement options that balance the cost of tree rearrangement with the cost of pipe repair. The paper also showcases a real-world case study in the city of Girona to evaluate the performance of the presented algorithms for a specific case focusing on tree roots as a natural factor. Results show that it is possible to optimally rearrange a number of the trees with the greatest impact, significantly minimizing pipe failures and wastewater leakages (82% risk reduction with only rearranging a 12% of the most impactful trees). The rearrangement solution not only protects the environment and prevents public health hazards, but also achieves a positive economic payback during the operational period of the pipes, saving up to 1.33M€ for a tree rearrangement of 7%. The presented methodology is applicable to other natural or human factors.

ediblecity: an R package to model and estimate the benefits of urban agriculture.

Urban agriculture is gaining attraction to become one of the pillars of the urban ecological transition and to increase food security in an urbanized planet. However, there is a lack of systematic quantification of the benefits provided by urban agriculture solutions. In this paper, we present an R package to estimate several indicators related to benefits of urban agriculture. The goal is to provide a tool for researchers and practitioners interested in the impacts of urban agriculture. The ediblecity package provides functions to calculate 8 indicators: urban heat island, runoff prevention, green areas accessibility, NO 2 sequestration, jobs created in commercial gardens, volunteers involved in community gardens, green per capita and, finally, food production. Moreover, the package also provides a function to generate scenarios with different implementations of urban agriculture. We illustrate the use of the package by comparing three scenarios in a neighborhood of Girona (Spain), which is included in the package as an example dataset. There, we compare scenarios with an increasing amount of urban agriculture solutions. The ediblecity package is open-source software. This allows other R developers to contribute to the package, providing new functionalities or improving the existing ones.

Could we estimate industrial wastewater flows composition using the UN-ISIC classification system?

Although we have extensive datasets on the location and typology of industries, we do not know much on their generated and discharged wastewater. This lack of information compromises the achievement of the sustainable development goals focused on water (Sustainable Development Goal 6) in Europe and globally. Thus, our goal was to assess to which degree the chemical composition of industrial wastewater could be estimated based on the industry's typology according to its International Standard Industrial Classification of All Economic Activities (ISIC) class. We collected wastewater effluent water samples from 60 industrial wastewater effluents (before any wastewater treatment process), accounting for 5 samples each of 12 ISIC classes, analyzed the composition of key contaminants (i.e. European Commission rated priority compounds and watchlist), and statistically assessed the similarities and differences amongst ISIC classes using ordination and random forest analyses. The results showed statistically significant linkages between most ISIC classes and the composition of produced wastewater. Among the analytical parameters measured, the random forest methodology allowed identifying a sub-set particularly relevant for classification or eventual contamination prediction based on ISIC class. This is an important applied research topic with strong management implications to (i) determine pollution emission caps for each individual ISIC class, (ii) define monitoring schemes to sample and analyze industrial wastewater, and (iii) enable predicting pollutant loads discharged in river basins with scarce information. These encouraging results urge us to expand our work into other ISIC classes and water quality parameters to draw a full picture of the relationship between ISIC classes and produced wastewater.

N-Nitrosamines and their precursors in wastewater effluents from selected industries in Spain.

N-nitrosamines (NAs), and N-nitrosodimethylamine (NDMA) in particular, are hazardous disinfection byproducts (DBPs) relevant when wastewater impacts drinking water sources and, in water reuse practices. Our study investigates the concentrations of NDMA and five additional NAs and their precursors in industrial wastewater effluents. Aiming to identify potential differences between industrial typologies, wastewaters from 38 industries belonging to 11 types of the UN International Standard Industrial Classification of All Economic Activities system (ISIC) were analysed. Results show that the presence of most NAs and their precursors cannot be linked to a specific industry type as these were in general very different within the classes. Nevertheless, N-nitrosomethylethylamine (NMEA) and N-nitrosopiperidine (NPIP) as well as precursors for N-nitrosodiethylamine (NDEA), NPIP and N-nitrosodibuthylamine (NDBA) could be rank with different concentrations between ISIC classes (p-value < 0.05). Specific industrial wastewater with notable high concentrations of NAs and their precursors were identified too. The effluents with the highest concentration of NDMA belong to the ISIC C2011 class (Manufacture of basic chemical), while the effluents with the highest concentration of NDMA precursors were from the ISIC C1511 class (Tanning and dressing of leather; dressing and dyeing of fur). Other relevant NAs found were NDEA in ISIC class B0810 (Quarrying of stone, sand, and clay) and ISIC class C2029 (Manufacture of other chemical products).

Optimal design of water reuse networks in cities through decision support tool development and testing.

Water scarcity and droughts are an increasing issue in many parts of the world. In the context of urban water systems, the transition to circularity may imply wastewater treatment and reuse. Planning and assessment of water reuse projects require decision-makers evaluating the cost and benefits of alternative scenarios. Manual or semi-automatic approaches are still common practice for planning both drinking and reclaimed water distribution networks. This work illustrates a decision support tool that, based on open data sources and graph theory coupled to greedy optimization algorithms, is able to automatically compute the optimal reclaimed water network for a given scenario. The tool provides not only the maximum amount of served reclaimed water per unit of invested cost, but also the length and diameters of the pipes required, the location and size of storage tanks, the population served, and the construction costs, i.e., everything under the same architecture. The usefulness of the tool is illustrated in two different but complementary cities in terms of size, density, and topography. The construction cost of the optimal water reclaimed network for a city of approximately 100,000 inhabitants is estimated to be in the range of €0.17-0.22/m3 (for a payback period of 30 years).

Surveillance of SARS-CoV-2 in sewage from buildings housing residents with different vulnerability levels.

During the last three years, various restrictions have been set up to limit the transmission of the Coronavirus Disease (COVID-19). While these rules apply at a large scale (e.g., country-wide level) human-to-human transmission of the virus that causes COVID-19, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), occurs at a small scale. Different preventive policies and testing protocols were implemented in buildings where COVID-19 poses a threat (e.g., elderly residences) or constitutes a disruptive force (e.g., schools). In this study, we sampled sewage from different buildings (a school, a university campus, a university residence, and an elderly residence) that host residents of different levels of vulnerability. Our main goal was to assess the agreement between the SARS-CoV-2 concentration in wastewater and the policies applied in these buildings. All buildings were sampled using passive samplers while 24 h composite samples were also collected from the elderly residence. Results showed that passive samplers performed comparably well to composite samples while being cost-effective to keep track of COVID-19 prevalence. In the elderly residence, the comparison of sampling protocols (passive vs. active) combined with the strict clinical testing allowed us to compare the sensitivities of the two methods. Active sampling was more sensitive than passive sampling, as the former was able to detect a COVID-19 prevalence of 0.4 %, compared to a prevalence of 2.2 % for passive sampling. The number of COVID-19-positive individuals was tracked clinically in all the monitored buildings. More frequent detection of SARS-CoV-2 in wastewater was observed in residential buildings than in non-residential buildings using passive samplers. In all buildings, sewage surveillance can be used to complement COVID-19 clinical testing regimes, as the detection of SARS-CoV-2 in wastewater remained positive even when no COVID-19-positive individuals were reported. Passive sampling is useful for building managers to adapt their COVID-19 mitigation policies.

The Catalan Surveillance Network of SARS-CoV-2 in Sewage: design, implementation, and performance.

Wastewater-based epidemiology has shown to be an efficient tool to track the circulation of SARS-CoV-2 in communities assisted by wastewater treatment plants (WWTPs). The challenge comes when this approach is employed to help Health authorities in their decision-making. Here, we describe the roadmap for the design and deployment of SARSAIGUA, the Catalan Surveillance Network of SARS-CoV-2 in Sewage. The network monitors, weekly or biweekly, 56 WWTPs evenly distributed across the territory and serving 6 M inhabitants (80% of the Catalan population). Each week, samples from 45 WWTPs are collected, analyzed, results reported to Health authorities, and finally published within less than 72 h in an online dashboard ( https://sarsaigua.icra.cat ). After 20 months of monitoring (July 20-March 22), the standardized viral load (gene copies/day) in all the WWTPs monitored fairly matched the cumulative number of COVID-19 cases along the successive pandemic waves, showing a good fit with the diagnosed cases in the served municipalities (Spearman Rho = 0.69). Here we describe the roadmap of the design and deployment of SARSAIGUA while providing several open-access tools for the management and visualization of the surveillance data.

Applicability of an on-line solid-phase extraction liquid chromatography - tandem mass spectrometry for the wastewater-based assessment of human exposure to chemicals from personal care and household products.

Wastewater-based epidemiology (WBE) can be a useful complementary approach to assess human exposure to potentially harmful chemicals, including those from personal care and household products. In this work, a fully automated multiresidue method, based on on-line solid-phase extraction liquid chromatography - tandem mass spectrometry, was developed for the determination of 27 biomarkers of human exposure to selected chemicals from personal care and household products, including parabens, UV filters, phthalates and alternative plasticizers, phosphorous flame retardants/plasticizers (PFRs), and bisphenols. These biomarkers include both the parent compounds and their human metabolites. In addition, two oxidative stress biomarkers, 8-epi-prostaglandin F2α and 4-hydroxy nonenal mercapturic acid, were also considered in the study. The method was carefully optimized to tackle the challenges of analyzing compounds with different physico-chemical properties in a highly complex raw wastewater matrix, while model experiments were performed to investigate filtration losses and analyte stability. The applicability of the developed method was tested by analyzing raw wastewater from four European cities: Antwerp, Brussels (Belgium), Girona (Spain), and Zagreb (Croatia). Twenty-one biomarkers (10 parent compounds and 11 metabolites) were detected in all analyzed wastewater samples. The parent compounds with the highest mass loads were PFRs, parabens, and bisphenol S, while phthalate monoesters were the most prominent metabolites. The mass loads of most compounds were quite similar across cities, but geographic differences were observed for some biomarkers, such as metabolites of phthalates and alternative plasticizers. Exposure was then assessed for seven substances for which quantitative urinary excretion data are known. Our results indicate that safe reference values were exceeded for several contaminants, including butylated phthalates, bisphenol A, and tris(2-butoxyethyl) phosphate, particularly for toddlers. With this relatively simple method, which requires less sample manipulation, it is possible to promptly identify and monitor exposure to harmful chemicals at the population level using the WBE approach.

A framework for model-based assessment of resilience in water resource recovery facilities against power outage.

Current practice to enhance resilience in Water Resource Recovery Facilities (WRRFs) is to ensure redundancy or back-up for most critical equipment (e.g. pumps or blowers). Model-based assessment allows evaluation of different strategies for quantitatively and efficiently enhancing resilience and justifying the allocation of resources. The goal of this study is to provide guidance for the development of tailored deterministic models of full-scale WRRFs. A framework for model-based resilience assessment is proposed that provides guidance on data collection, model selection, model calibration and scenario analysis. The framework is embedded into the Good Modeling Practice (GMP) Unified Protocol, providing a new application for resilience assessment and an initial set of stressors for WRRFs. The usefulness of the framework is illustrated through a resilience assessment of the WRRF of Girona against power outage. Results show that, for the Girona facility, limited energy back-up can cause non-compliance of WRRF discharge limits in the case of a blower power shut-down of 6 h, and around 12 h when the blower shut-down is also combined with a shut-down of the recirculation pumps. The best option to enhance resilience would be increasing the power back-up by 218%, which allows the plant to run with recirculation pumps and blowers at minimum capacity. In such a case, resilience can be further enhanced by manipulating the air supply valves to optimise the air distribution, to balance oxygen needs in each reactor with the overall system pressure. We conclude that, with industry consensus on what is considered an acceptable level of resilience, a framework for resilience assessment would be a useful tool to enhance the resilience of our current water infrastructure. Further research is needed to establish if the permit structure should accommodate levels sof functionality to account for stress events.

Optimal selection of monitoring sites in cities for SARS-CoV-2 surveillance in sewage networks.

Selecting sampling points to monitor traces of SARS-CoV-2 in sewage at the intra-urban scale is no trivial task given the complexity of the networks and the multiple technical, economic and socio-environmental constraints involved. This paper proposes two algorithms for the automatic selection of sampling locations in sewage networks. The first algorithm, is for the optimal selection of a predefined number of sampling locations ensuring maximum coverage of inhabitants and minimum overlapping amongst selected sites (static approach). The second is for establishing a strategy of iterations of sample&analysis to identify patient zero and hot spots of COVID-19 infected inhabitants in cities (dynamic approach). The algorithms are based on graph-theory and are coupled to a greedy optimization algorithm. The usefulness of the algorithms is illustrated in the case study of Girona (NE Iberian Peninsula, 148,504 inhabitants). The results show that the algorithms are able to automatically propose locations for a given number of stations. In the case of Girona, always covering more than 60% of the manholes and with less than 3% of them overlapping amongst stations. Deploying 5, 6 or 7 stations results in more than 80% coverage in manholes and more than 85% of the inhabitants. For the dynamic sensor placement, we demonstrate that assigning infection probabilities to each manhole as a function of the number of inhabitants connected reduces the number of iterations required to detect the zero patient and the hot spot areas.

Climate change impact on EU rivers' dilution capacity and ecological status.

Impacts from urban wastewater treatment plants (WWTP) to receiving riverine surface water bodies (SWBs) depend on the load of contaminants discharged, as well as on their dilution capacity. Yet, climate change impacts on such dilution capacity and ultimately on the SWBs ecological status remain unclear. Here, we assess SWBs dilution capacity across the European continent to identify most vulnerable areas using information from centralized European databases. SWBs´ future dilution factor values are estimated based on representative concentration pathway scenarios impacts on rivers flow, and likely changes in European SWBs´ ecological status foretold. Results show that dilution factor in Europe increases by 5.4% in average. Yet, climate change effects are found to lead to a consistent dilution factor decrease for 11% of the 40074 European SWBs receiving WWTP discharge for the early century. This share reaches 17% for the midcentury period. We estimate that up to 42% of the SWBs receiving WWTP discharges and currently reaching a good ecological status show a 0.7 probability to have their ecological status downgraded due to climate change. Sites more vulnerable are located in the Mediterranean countries. Our findings highlight that climate change mitigation is essential for maintaining good ecological status in European SWBs.

Can source control of pharmaceuticals decrease the investment needs in urban wastewater infrastructure?

The source control of pharmaceuticals involves influencing the everyday consumption volume and compound choice. This paper evaluates how source control contributes to protecting the environmental health and decreasing the investment needs in urban wastewater infrastructure. Different levels of reduction in diclofenac consumption (as recommended by the European Medicines Agency) compensated by equivalent increases in naproxen consumption (a less environmentally harmful compound) are evaluated. The different loads of compounds are fed into a microcontaminant fate and transport model of the Llobregat river basin (Spain) to assess the investment needs in tertiary treatment to reach diclofenac and naproxen concentrations below environmental quality standards. The results show that, despite the implementation of source control measures, tertiary treatment upgrades are still required in every scenario evaluated. Even though source control of pharmaceuticals decreases the investment needs in urban wastewater infrastructure, apparent concentrations reductions (i.e. statistically significant differences relative to the reference situation) are only observed in drastic substitutions of diclofenac by naproxen (a reduction in the total diclofenac consumption by 73% and a corresponding increase in naproxen consumption). The results also show that Spain is on good track with regards to the substitution of diclofenac by naproxen (among the top 5 in Europe), and this paper shows how positive this substitution can be for the environment.

The application of life cycle assessment (LCA) to wastewater treatment: A best practice guide and critical review.

Life cycle assessment (LCA) has been widely applied in the wastewater industry, but inconsistencies in assumptions and methods have made it difficult for researchers and practitioners to synthesize results from across studies. This paper presents a critical review of published LCAs related to municipal wastewater management with a focus on developing systematic guidance for researchers and practitioners to conduct LCA studies to inform planning, design, and optimization of wastewater management and infrastructure (wastewater treatment plants, WWTPs; collection and reuse systems; related treatment technologies and policies), and to support the development of new technologies to advance treatment objectives and the sustainability of wastewater management. The paper guides the reader step by step through LCA methodology to make informed decisions on i) the definition of the goal and scope, ii) the selection of the functional unit and system boundaries, iii) the selection of variables to include and their sources to obtain inventories, iv) the selection of impact assessment methods, and v) the selection of an effective approach for data interpretation and communication to decision-makers.

When the fourth water and digital revolution encountered COVID-19.

The ongoing COVID-19 pandemic is, undeniably, a substantial shock to our civilization which has revealed the value of public services that relate to public health. Ensuring a safe and reliable water supply and maintaining water sanitation has become ever more critical during the pandemic. For this reason, researchers and practitioners have promptly investigated the impact associated with the spread of SARS-CoV-2 on water treatment processes, focusing specifically on water disinfection. However, the COVID-19 pandemic impacts multiple aspects of the urban water sector besides those related to the engineering processes, including sanitary, economic, and social consequences which can have significant effects in the near future. Furthermore, this outbreak appears at a time when the water sector was already experiencing a fourth revolution, transitioning toward the digitalisation of the sector, which redefines the Water-Human-Data Nexus. In this contribution, a product of collaboration between academics and practitioners from water utilities, we delve into the multiple impacts that the pandemic is currently causing and their possible consequences in the future. We show how the digitalisation of the water sector can provide useful approaches and tools to help address the impact of the pandemic. We expect this discussion to contribute not only to current challenges, but also to the conceptualization of new projects and the broader task of ameliorating climate change.

The Fourth-Revolution in the Water Sector Encounters the Digital Revolution.

The so-called fourth revolution in the water sector will encounter the Big data and Artificial Intelligence (AI) revolution. The current data surplus stemming from all types of devices together with the relentless increase in computer capacity is revolutionizing almost all existing sectors, and the water sector will not be an exception. Combining the power of Big data analytics (including AI) with existing and future urban water infrastructure represents a significant untapped opportunity for the operation, maintenance, and rehabilitation of urban water infrastructure to achieve economic and environmental sustainability. However, such progress may catalyze socio-economic changes and cross sector boundaries (e.g., water service, health, business) as the appearance of new needs and business models will influence the job market. Such progress will impact the academic sector as new forms of research based on large amounts of data will be possible, and new research needs will be requested by the technology industrial sector. Research and development enabling new technological approaches and more effective management strategies are needed to ensure that the emerging framework for the water sector will meet future societal needs. The feature further elucidates the complexities and possibilities associated with such collaborations.

Wastewater-based epidemiology to assess human exposure to personal care and household products - A review of biomarkers, analytical methods, and applications.

Humans are nowadays exposed to numerous chemicals in our day-to-day life, including parabens, UV filters, phosphorous flame retardants/plasticizers, bisphenols, phthalates and alternative plasticizers, which can have different adverse effects to human health. Estimating human's exposure to these potentially harmful substances is, therefore, of paramount importance. Human biomonitoring (HBM) is the existing approach to assess exposure to environmental contaminants, which relies on the analysis of specific human biomarkers (parent compounds and/or their metabolic products) in biological matrices from individuals. The main drawback is its implementation, which involves complex cohort studies. A novel approach, wastewater-based epidemiology (WBE), involves estimating exposure from the analysis of biomarkers in sewage (a pooled urine and feces sample of an entire population). One of the key challenges of WBE is the selection of biomarkers which are specific to human metabolism, excreted in sufficient amounts, and stable in sewage. So far, literature data on potential biomarkers for estimating exposure to these chemicals are scattered over numerous pharmacokinetic and HBM studies. Hence, this review provides a list of potential biomarkers of exposure to more than 30 widely used chemicals and report on their urinary excretion rates. Furthermore, the potential and challenges of WBE in this particular field is discussed through the review of pioneer WBE studies, which for the first time explored applicability of this novel approach to assess human exposure to environmental contaminants. In the future, WBE could be potentially applied as an "early warning system", which could promptly identify communities with the highest exposure to environmental contaminants.