Wastewater-based epidemiology (WBE) has been proven to be a useful tool in monitoring public health-related issues such as drug use, and disease. By sampling wastewater and applying WBE methods, wastewater-detectable pathogens such as viruses can be cheaply and effectively monitored, tracking people who might be missed or under-represented in traditional disease surveillance. There is a gap in current knowledge in combining hydraulic modeling with WBE. Recent literature has also identified a gap in combining machine learning with WBE for the detection of viral outbreaks. In this study, we loosely coupled a physically-based hydraulic model of pathogen introduction and transport with a machine learning model to track and trace the source of a pathogen within a sewer network and to evaluate its usefulness under various conditions. The methodology developed was applied to a hypothetical sewer network for the rapid detection of disease hotspots of the disease caused by the SARS-CoV-2 virus. Results showed that the machine learning model's ability to recognize hotspots is promising, but requires a high time-resolution of monitoring data and is highly sensitive to the sewer system's physical layout and properties such as flow velocity, the pathogen sampling procedure, and the model's boundary conditions. The methodology proposed and developed in this paper opens new possibilities for WBE, suggesting a rapid back-tracing of human-excreted biomarkers based on only sampling at the outlet or other key points, but would require high-frequency, contaminant-specific sensor systems that are not available currently.

The aim of this study was to assess the health risks that may arise from the implementation of greywater reuse and rainwater harvesting for household use, especially for toilet flushing. In addition, the risk of cross connections between these systems and the drinking water system was considered. Quantitative microbial risk assessment (QMRA) is a method that uses mathematical modelling to estimate the risk of infection when exposure to pathogens happens and was used in this study to assess the health risks. The results showed that using rainwater without prior treatment for toilet flushing poses an annual infection risk from L. pneumophila at 0.64 per-person-per-year (pppy) which exceeds the Dutch standard of 10−4 pppy. The use of untreated greywater showed a risk that is below the standard. However, treatment is recommended due to the ability of P. aeruginosa to grow in the reuse system. Moreover, showering and drinking with cross-connected water has a high annual infection risk that exceeds the standard due to contact with Staphylococcus aureus and E. coli O157:H7. Several measures can be implemented to mitigate the risks such as treating the greywater and rainwater with a minimum of 5-log removal, closing the toilet lid while flushing, good design of greywater and rainwater collection systems, and rigorous plumbing installation procedures.

Drinking water distribution networks (DWDNs) have a huge potential for cold thermal energy recovery (TED). TED can provide cooling for buildings and spaces with high cooling requirements as an alternative for traditional cooling, reduce usage of electricity or fossil fuel, and thus TED helps reduce greenhouse gas (GHG) emissions. There is no research on the environmental assessment of TED systems, and no standards are available for the maximum temperature limit (Tmax) after recovery of cold. During cold recovery, the water temperature increases, and water at the customer’s tap may be warmer as a result. Previous research showed that increasing Tmax up to 30 °C is safe in terms of microbiological risks. The present research was carried out to determine what raising Tmax would entail in terms of energy savings, GHG emission reduction and water temperature dynamics during transport. For this purpose, a full-scale TED system in Amsterdam was used as a benchmark, where Tmax is currently set at 15 °C. Tmax was theoretically set at 20, 25 and 30 °C to calculate energy savings and CO2 emission reduction and for water temperature modeling during transport after cold recovery. Results showed that by raising Tmax from the current 15 °C to 20, 25 and 30 °C, the retrievable cooling energy and GHG emission reduction could be increased by 250, 425 and 600%, respectively. The drinking water temperature model predicted that within a distance of 4 km after TED, water temperature resembles that of the surrounding subsurface soil. Hence, a higher Tmax will substantially increase the TED potential of DWDN while keeping the same comfort level at the customer’s tap.

Recovering resources from wastewater systems is increasingly being emphasised. Many technologies exist or are under development for recycling nutrients such as nitrogen and phosphorus from wastewater to agriculture. Planning and design methodologies are needed to identify and deploy the most sustainable solutions in given contexts. For the environmental sustainability dimension, life cycle assessment (LCA) can be used to assess environmental impact potentials of wastewater-based nutrient recycling alternatives, especially nitrogen and phosphorus recycling. This review aims to evaluate how well the LCA methodology has been adapted and applied for assessing opportunities of wastewater-based nutrient recycling in the form of monomineral, multimineral, nutrient solution and organic solid. We reviewed 65 LCA studies that considered nutrient recycling from wastewater for agricultural land application. We synthesised some of their insights and methodological practices, and discussed the future outlook of using LCA for wastewater-based nutrient recycling. In general, more studies suggested positive environmental outcomes from wastewater-based nutrient recycling, especially when chemical inputs are minimised, and source separation of human excreta is achieved. The review shows the need to improve methodological consistency (e.g., multifunctionality, fertiliser offset accounting, contaminant accounting), ensure transparency of inventory and methods, consider uncertainty in comparative LCA context, integrate up-to-date cross-disciplinary knowledge (e.g., agriculture science, soil science) into LCA models, and consider the localised impacts of recycled nutrient products. Many opportunities exist for applying LCA at various scales to support decisions on wastewater-based nutrient recycling – for instance, performing “product perspective” LCA on recycled nutrient products, integrating “process perspective” LCA with other systems approaches for selecting and optimising individual recovery processes, assessing emerging nutrient recovery technologies and integrated resource recovery systems, and conducting systems analysis at city, national and global level.

Reducing water use could impact existing sewer systems but this is not currently well understood. This work describes a new flow and wastewater quality model developed to investigate this impact. SIMDEUM WW® was used to generate stochastic appliance-specific discharge profiles for wastewater flow and concentration, which were fed into InfoWorks® ICM to quantify the impacts within the sewer network. The model was validated using measured field data from a sewer system in Amsterdam serving 418 households. Wastewater concentrations of total suspended solids (TSS), chemical oxygen demand (COD), total Kjeldahl nitrogen (TKN) and total phosphorus (TPH) were sampled on an hourly basis, for one week. The results obtained showed that the InfoWorks® model predicted the mass flow of pollutants well (R-values 0.69, 0.72 and 0.75 for COD, TKN and TPH respectively) but, due to the current lack of a time-varying solids transport model within InfoWorks®, the prediction for wastewater concentration parameters was less reliable. Still, the model was deemed capable of analysing the effects of three water conservation strategies (greywater reuse, rainwater harvesting and water-saving appliances) on flow, nutrient concentrations, and temperature in sewer networks. Results show through a 62% reduction in sewer flow, COD, TKN and TPH concentrations increased by up to 111%, 84% and 75% respectively, offering more favourable conditions for nutrient recovery.

The wastewater chain of Amsterdam offers an opportunity to recover up to 100% of phosphorus per year, versus 47% currently recovered. However, for the stakeholders of Amsterdam (e.g. citizens, business) it remains difficult to scale-up existing solutions for resource recovery. Mainly, due to the limitations of the widelyused methods (e.g. mass flow, life-cycle analysis) to provide holistic assessment of the solutions and the changes they will propagate outside the wastewater chain (e.g. solid waste). In the current study, three existing phosphorus recovery Solutions applied at three scales of Amsterdam (city, neighborhood, house) were analyzed. The study showed that the house scale closed-loop solution has higher positive influence on resilience of the city. Moreover, the DSM indicators could be used to measure resilience of the city and constituent parts, given an influence of a specific Solution. The developed toolkit is applicable for analysis of other resources in the wastewater of Amsterdam.

Life cycle assessment (LCA) is an established methodology to assess the potential environmental impacts of products and processes. We reviewed 49 recent LCA studies (2010-2019) on wastewater nutrient recovery to synthesise some current methodological practices. Their scopes, variations, nutrient recovery accounting, uncertainty and sensitivity management, and future opportunities are discussed. There are many opportunities to improve the current practice such as assessing a broader scope of environmental impacts, improving model and inventory transparency, communicating uncertainties and understanding model sensitivities. While this study focuses on nutrient recovery from wastewater, a lot of the insights are also relevant to other water-related LCA.

Drinking water and fire safety are strongly bonded to each other. Actual drinking water demand and fire flows are both delivered through the same network, and are both devoted to public health and safety. In The Netherlands, the discussion about fire flows supplied by the drinking water networks has drawn fire fighters and drinking water companies together, searching for novel approaches to improve public safety. One of these approaches is the application of residential fire sprinkler systems fed by drinking water. This approach has an impact on the layout of domestic drinking water systems (DDWSs), as extra plumbing is required. This study examined the influence of the added plumbing on quality of both fresh and 10 h stagnant water in two full scale DDWSs: a conventional and an extended system. Overnight stagnation was found to promote copper and zinc leaching from pipes in both DDWSs. Microbial numbers and viability in the stagnant water, measured by heterotrophic plate count (HPC), flow cytometry (FCM) and adenosine tri-phosphate (ATP), depended on the temperature of fresh water, as increased microbial numbers and viability was measured in both DDWSs when the temperature of fresh water was below the observed tipping point (15 °C for the HPC and 17 °C for the FCM and ATP measurements respectively) and vice versa. A high level of similarity between water and biofilm communities, >98% and >70–94% respectively, indicates that the extension of the DDWS did not affect either the microbial quality of fresh drinking water or the biofilm composition.

The wastewater system of Amsterdam offers an opportunity to recover phosphorus, and contribute to circular economy. However, it remains unclear where to intervene in system to maximize recovery and valorisation in a resilient and feasible way. The Design Structure Matrix method was tested to define the system architecture from Food-Water-Energy nexus perspective. Physical, phosphorus, and ownership dependencies between Infrastructure, Stakeholder, Resource and Cleantech domains (elements) of the wastewater system in Amsterdam are analyzed in a Multi-Domain Matrix model. Change Propagation Indicator quantified critical elements, and emergent changes. An Influence Profile unveiled four levels of system leverage: household, neighborhood, city-block, region. The stakeholders can engage into optimizations at each level, to generate individual and shared benefits. Hybrid infrastructure, plug&play solutions and modular approach to cleantech will harness up to 100% of phosphorus available. The method proved to be an effective tool for analysing complexity and engineering resilient solutions for the circular economy.

Domestic drinking water supply systems (DDWSs) are the final step in the delivery of drinking water to consumers. Temperature is one of the rate-controlling parameters for many chemical and microbiological processes and is, therefore, considered as a surrogate parameter for water quality processes. In this study, a mathematical model is presented that predicts temperature dynamics of the drinking water in DDWSs. A full-scale DDWS resembling a conventional system was built and run according to one year of stochastic demands with a time step of 10 s. The drinking water temperature was measured at each point-of-use in the systems and the data-set was used for model validation. The temperature model adequately reproduced the temperature profiles, both in cold and hot water lines, in the full-scale DDWS. The model showed that inlet water temperature and ambient temperature have a large effect on the water temperature in the DDWSs.

The drinking water quality changes during the transport through distribution systems. Domestic drinking water systems (DDWSs), which include the plumbing between the water meter and consumer's taps, are the most critical points in which water quality may be affected. In distribution networks, the drinking water temperature and water residence time are regarded as indicators of the drinking water quality. This paper describes an experimental research on the influence of stagnation time and temperature change on drinking water quality in a full-scale DDWS. Two sets of stagnation experiments, during winter and summer months, with various stagnation intervals (up to 168 h of stagnation) were carried out. Water and biofilms were sampled at two different taps, a kitchen and a shower tap. Results from this study indicate that temperature and water stagnation affect both chemical and microbial quality in DDWSs, whereas microbial parameters in stagnant water appear to be driven by the temperature of fresh water. Biofilm formed in the shower pipe contained more total and intact cells than the kitchen pipe biofilm. Alphaproteobacteria were found to dominate in the shower biofilm (78% of all Proteobacteria), while in the kitchen tap biofilm Alphaproteobacteria, Betaproteobacteria and Gammaproteobacteria were evenly distributed.