Département Technologie des procédés

The simulation of wastewater treatment plants allows obtaining predictive results when one needs to understand, evaluate, optimize, or design a plant. However, one of the bottlenecks of simulation feasibility is to obtain reliable and dynamic influent data. This difficulty is even more important when alternative scenarios are considered, such as source-separated streams. The present paper offers an influent generator to simulate scenarios where urine is separated at the source and at a user-specified level of retention. The proposed tool contains several blocks to include different contributions (household and industrial wastewater) and, due to its flexibility, allows the user to easily modify the parameters to fit other case studies. The tool allowed generating dynamic, long-term, and predictive data for both urine and wastewater streams. Also, the extensive set of state variables ensured the generation of influents for different modeling platforms.

The COVID-19 pandemic has severely impacted public health and the worldwide economy. Converging evidence from the current pandemic, previous outbreaks and controlled experiments indicates that SARS-CoVs are present in wastewater for several days, leading to potential health risks via waterborne and aerosolized wastewater pathways. Conventional wastewater treatment provides only partial removal of SARS-CoVs, thus safe disposal or reuse will depend on the efficacy of final disinfection. This underscores the need for a risk assessment and management framework tailored to SARS-CoV-2 transmission via wastewater, including new tools for environmental surveillance, ensuring adequate disinfection as a component of overall COVID-19 pandemic containment.

Sensing nitrite in-situ in wastewater treatment processes could greatly simplify process control, especially during treatment of high-strength nitrogen wastewaters such as digester supernatant or, as in our case, urine. The two technologies available today, i.e. an on-line nitrite analyzer and a spectrophotometric sensor, have strong limitations such as sample preparation, cost of ownership and strong interferences. A promising alternative is the amperometric measurement of nitrite, which we assessed in this study. We investigated the sensor in a urine nitrification reactor and in ex-situ experiments. Based on theoretical calculations as well as a practical approach, we determined that the critical nitrite concentrations for nitrite oxidizing bacteria lie between 12 and 30 mg_N/L at pH 6 to 6.8. Consequently, we decided that the sensor should be able to reliably measure concentrations up to 50 mg_N/L, which is about double the value of the critical nitrite concentration. We found that the influences of various ambient conditions, such as temperature, pH, electric conductivity and aeration rate, in the ranges expected in urine nitrification systems, are negligible. For low nitrite concentrations, as expected in municipal wastewater treatment, the tested amperometric nitrite sensor was not sufficiently sensitive. Nevertheless, the sensor delivered reliable measurements for nitrite concentrations of 5-50 mg_N/L or higher. This means that the amperometric nitrite sensor allows detection of critical nitrite concentrations without difficulty in high-strength nitrogen conversion processes, such as the nitrification of human urine.

Multiple anthropogenic drivers are changing ecosystems globally, with a disproportionate and intensifying impact on freshwater habitats. A major impact of urbanization are inputs from wastewater treatment plants (WWTPs). Initially designed to reduce eutrophication and improve water quality, WWTPs increasingly release a multitude of micropollutants (MPs; i.e., synthetic chemicals) and microbes (including antibiotic‐resistant bacteria) to receiving environments. This pollution may have pervasive impacts on biodiversity and ecosystem services. Viewed through multiple lenses of macroecological and ecotoxicological theory, we combined field, flume, and laboratory experiments to determine the effects of wastewater (WW) on microbial communities and organic‐matter processing using a standardized decomposition assay. First, we conducted a mensurative experiment sampling 60 locations above and below WWTP discharges in 20 Swiss streams. Microbial respiration and decomposition rates were positively influenced by WW inputs via warming and nutrient enrichment, but with a notable exception: WW decreased the activation energy of decomposition, indicating a "slowing" of this fundamental ecosystem process in response to temperature. Second, next‐generation sequencing indicated that microbial community structure below WWTPs was altered, with significant compositional turnover, reduced richness, and evidence of negative MP influences. Third, a series of flume experiments confirmed that although diluted WW generally has positive influences on microbial‐mediated processes, the negative effects of MPs are "masked" by nutrient enrichment. Finally, transplant experiments suggested that WW‐borne microbes enhance decomposition rates. Taken together, our results affirm the multiple stressor paradigm by showing that different aspects of WW (warming, nutrients, microbes, and MPs) jointly influence ecosystem functioning in complex ways. Increased respiration rates below WWTPs potentially generate ecosystem "disservices" via greater carbon evasion from streams and rivers. However, toxic MP effects may fundamentally alter ecological scaling relationships, indicating the need for a rapprochement between ecotoxicological and macroecological perspectives.