M. Sieranen, Helena Hilander, H. Haimi, Timo Larsson, Anna Kuokkanen, A. Mikola
{"title":"Seasonality of nitrous oxide emissions at six full-scale wastewater treatment plants","authors":"M. Sieranen, Helena Hilander, H. Haimi, Timo Larsson, Anna Kuokkanen, A. Mikola","doi":"10.2166/wst.2023.420","DOIUrl":"https://doi.org/10.2166/wst.2023.420","url":null,"abstract":"Nitrous oxide (N2O) is an ozone-depleting greenhouse gas that contributes significantly to the carbon footprint of a wastewater treatment plant (WWTP). Plant-specific measurement campaigns are required to reliably quantify the emission level that has been found to significantly vary between WWTPs. In this study, the N2O emissions were quantified from five full-scale WWTPs during 4- to 19-day measurement campaigns conducted under both cold period conditions (water temperature below 12 °C) and warm period conditions (water temperature from 12 to 20 °C). The measurement data were studied alongside long-term monitoring data from a sixth WWTP. The calculated emission factors (EFs) varied from near 0 to 1.8% relative to the influent total nitrogen load. The results confirmed a significant seasonality of N2O emissions as well as a notable variation between WWTPs in the emission level, which a single fixed EF cannot represent. Wastewater temperature was one explanatory factor for the emission seasonality. Both low and high emissions were measured from denitrifying–nitrifying activated sludge (AS) processes, while the emissions from only nitrifying AS processes were consistently high. Nitrite (NO2-) at the end of the aerobic zones of the AS process was linked to the variability in N2O emissions during the cold period.","PeriodicalId":505935,"journal":{"name":"Water Science & Technology","volume":"26 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139162564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ania Morvannou, Matthieu Dufresne, M. Gromaire, Stéphane Troesch, N. Forquet
{"title":"Sizing efficient underdrains for treatment wetlands","authors":"Ania Morvannou, Matthieu Dufresne, M. Gromaire, Stéphane Troesch, N. Forquet","doi":"10.2166/wst.2023.417","DOIUrl":"https://doi.org/10.2166/wst.2023.417","url":null,"abstract":"Treatment wetlands are recognized as an effective technology for mitigating the impacts of urban runoff. However, there is no consensus on the design guidelines, and the effects of some design features, such as the underdrain system, remain unexplored. A simple analog model has been developed to mimic the underdrain network (when operating at saturation) and to evaluate the spatial heterogeneity of the flow entering it. The model has been applied to a treatment wetland in the Paris area and shows that the underdrain network was largely undersized, likely causing an uneven distribution of infiltrating flow along the length of the treatment wetland. It was also shown that this analog model can be used for optimization purposes and that it is important to use conservative values of the rugosity coefficient when designing an underdrain network.","PeriodicalId":505935,"journal":{"name":"Water Science & Technology","volume":"30 30","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139166071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. Therrien, Mathew Thomson, Eugen-Sorin Sion, Ivan Lee, T. Maere, Niels Nicolaï, Douglas G. Manuel, Peter A. Vanrolleghem
{"title":"A comprehensive, open-source data model for wastewater-based epidemiology","authors":"J. Therrien, Mathew Thomson, Eugen-Sorin Sion, Ivan Lee, T. Maere, Niels Nicolaï, Douglas G. Manuel, Peter A. Vanrolleghem","doi":"10.2166/wst.2023.409","DOIUrl":"https://doi.org/10.2166/wst.2023.409","url":null,"abstract":"The recent SARS-COV-2 pandemic has sparked the adoption of wastewater-based epidemiology (WBE) as a low-cost way to monitor the health of populations. In parallel, the pandemic has encouraged researchers to openly share their data to serve the public better and accelerate science. However, environmental surveillance data is highly dependent on context and is difficult to interpret meaningfully across sites. This paper presents the second iteration of the Public Health Environmental Surveillance Open Data Model (PHES-ODM), an open-source dictionary and set of data tools to enhance the interoperability of environmental surveillance data and enable the storage of contextual (meta)data. The data model describes how to store environmental surveillance program data, metadata about measurements taken on various specimens (water, air, surfaces, sites, populations) and data about measurement protocols. The model provides software tools that support the collection and use of PHES-ODM formatted data, including performing PCR calculations and data validation, recording data into input templates, generating wide tables for analysis, and producing SQL database definitions. Fully open-source and already adopted by institutions in Canada, the European Union, and other countries, the PHES-ODM provides a path forward for creating robust, interoperable, open datasets for environmental public health surveillance for SARS-CoV-2 and beyond.","PeriodicalId":505935,"journal":{"name":"Water Science & Technology","volume":"199 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139173298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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