Implementation of two-phase modeling of hydrogen sulfide in fresh market's combined sewers in Rat Burana, Bangkok.

Hydrogen sulfide (H2S) is one of the sewer gases commonly found in wastewater collection systems. This anaerobic degradation product causes issues, ranging from odor nuisances and health hazards to pipe corrosion. Several studies have provided an understanding of H2S formation mechanism, including simulations of H2S emissions in sewers, especially in pressurized systems. However, the present models necessitate a large amount of data due to the complexity of the H2S processes and common routine-monitoring water quality parameters may not fit the requirements. This study aims to simulate the fate and transport of H2S in both air and water phases in combined sewers, with a realization of practicableness of the application. The study case is centered around a fresh market in Bangkok, where the sewers are commonly plagued with garbage-related issues. These challenges pose difficulties for site monitoring across various aspects, necessitating the application of unconventional methods. On-site hydrodynamics, wastewater quality, and H2S gas concentration data were monitored on hourly and daily bases. It was found that the sulfides in the combined sewerage were correlated with sewage quality, e.g., COD, sulfate (SO42-), and pH concentrations in particular. The model results were in an acceptable range of accuracy (R2 = 0.63; NSE = 0.52; RMSE = 1.18) after being calibrated with the measured hydrogen sulfide gas concentration. The results lead to the conclusion that the simplified model is practical and remains effective even in sewers with untraditional conditions. This could hold promise as a fundamental tool in shaping effective H2S mitigation strategies.

Machine Learning for Detecting Virus Infection Hotspots Via Wastewater-Based Epidemiology: The Case of SARS-CoV-2 RNA.

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.

Making the ecosystem services approach operational: A case study application to the Aarhus River, Denmark.

The ecosystem services (ESS) approach seeks to identify and characterize links between ecosystems and human welfare. The DESSIN ESS evaluation framework is a novel methodology that has been developed to operationalize ecosystem service assessment, with a focus on urban freshwater settings. This paper describes an application of the framework to a retrospective case study in Aarhus, Denmark, which was used to test the framework and make suggestions for improvement. River restoration and wastewater management measures enhanced ecosystem state and the provision and use of purification and recreation ESS for selected beneficiaries, including increased economic values. Feedback from this case study suggests a missing link between science-based ESS approaches, which often have a normative basis in ecosystem status, and the real-world provision and use of ESS in urban settings. In the urban context, many ESS result from a combination of human and ecosystem inputs, and the human inputs can often be significant. Quantifying ESS provision and use therefore requires understanding how ecosystem and human inputs work together to make contributions to human welfare.

Modelling the impact of retention-detention units on sewer surcharge and peak and annual runoff reduction.

Stormwater management using water sensitive urban design is expected to be part of future drainage systems. This paper aims to model the combination of local retention units, such as soakaways, with subsurface detention units. Soakaways are employed to reduce (by storage and infiltration) peak and volume stormwater runoff; however, large retention volumes are required for a significant peak reduction. Peak runoff can therefore be handled by combining detention units with soakaways. This paper models the impact of retrofitting retention-detention units for an existing urbanized catchment in Denmark. The impact of retrofitting a retention-detention unit of 3.3 m³/100 m² (volume/impervious area) was simulated for a small catchment in Copenhagen using MIKE URBAN. The retention-detention unit was shown to prevent flooding from the sewer for a 10-year rainfall event. Statistical analysis of continuous simulations covering 22 years showed that annual stormwater runoff was reduced by 68-87%, and that the retention volume was on average 53% full at the beginning of rain events. The effect of different retention-detention volume combinations was simulated, and results showed that allocating 20-40% of a soakaway volume to detention would significantly increase peak runoff reduction with a small reduction in the annual runoff.

Integration of research advances in modelling and monitoring in support of WFD river basin management planning in the context of climate change.

The integration of scientific knowledge about possible climate change impacts on water resources has a direct implication on the way water policies are being implemented and evolving. This is particularly true regarding various technical steps embedded into the EU Water Framework Directive river basin management planning, such as risk characterisation, monitoring, design and implementation of action programmes and evaluation of the "good status" objective achievements (in 2015). The need to incorporate climate change considerations into the implementation of EU water policy is currently discussed with a wide range of experts and stakeholders at EU level. Research trends are also on-going, striving to support policy developments and examining how scientific findings and recommendations could be best taken on board by policy-makers and water managers within the forthcoming years. This paper provides a snapshot of policy discussions about climate change in the context of the WFD river basin management planning and specific advancements of related EU-funded research projects. Perspectives for strengthening links among the scientific and policy-making communities in this area are also highlighted.