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Sediments in urban drainage systems (UDS) significantly impact their operation, so effective strategies are required to reduce their negative effects. Monitoring sediment accumulation provides valuable insights into sediment characteristics, sediment transport dynamics, and system performance. However, the effectiveness of monitoring systems is limited due to cost constraints and installation challenges. This study describes the development and application of a new system based on temperature dynamics to measure sediment depths in sewer systems. The methodology involves the analysis of temperature time series under dry weather flow conditions to identify harmonic patterns between wastewater and sediment-bed temperatures. These patterns are increasingly attenuated by increasing sediment depth. This study combines a system called MONitoring Temperatures in SEdiments (MONTSE), which integrates a dual-probe heat-pulse (DPHP) method to characterize sediment thermal properties, and a surrogate model, which includes temperature pattern analysis, to estimate sediment depths. Likewise, laboratory-scale experiments were performed to validate the temperature monitoring system and the surrogate model performance. The maximum absolute errors in measured sediment depths were less than 22 mm, and the uncertainty of the system was estimated at ±7.3 mm. Groundbreaking measurements of thermal properties of UDS sediments were also reported. Reliable information on sediment depths and properties was provided, so the system could significantly optimize sewer system operation and cleaning strategies., Validerad;2024;Nivå 2;2024-04-03 (joosat);Full text: CC BY license;Funder: Xunta de Galicia (Consellería de Cultura, Educación e Universidade, ED481B2021-082)

Enhancing sediment accumulation monitoring techniques in sewers will enable a better understanding of the build-up processes to develop improved cleaning strategies. Thermal sensors provide a solution to sediment depth estimation by passively monitoring temperature fluctuations in the wastewater and sediment beds, which allows evaluation of the heat-transfer processes in sewer pipes. This study analyses the influence of the flow conditions on heat-transfer processes at the water-sediment interface during dry weather flow conditions. For this purpose, an experimental campaign was performed by establishing different flow, temperature patterns, and sediment depth conditions in an annular flume, which ensured stable flow and room-temperature conditions. Numerical simulations were also performed to assess the impact of flow conditions on the relationships between sediment depth and harmonic parameters derived from wastewater and sediment-bed temperature patterns. Results show that heat transfer between water and sediment occurred instantaneously for velocities greater than 0.1 m/s, and that sediment depth estimations using temperature-based systems were barely sensitive to velocities between 0.1 and 0.4 m/s. A depth estimation accuracy of +/- 7 mm was achieved. This confirms the ability of using temperature sensors to monitor sediment build-up in sewers under dry weather conditions, without the need for flow monitoring., Validerad;2024;Nivå 2;2024-07-10 (joosat);Funder: Xunta de Galicia (Conselleria de Cultura, Educacion e Universidade) (ED481B-2021-082); Full text license: CC BY 4.0

Over the course of the Corona Virus Disease-19 (COVID-19) pandemic in 2020–2022, monitoring of the severe acute respiratory syndrome coronavirus 2 ribonucleic acid (SARS-CoV-2 RNA) in wastewater has rapidly evolved into a supplementary surveillance instrument for public health. Short term trends (2 weeks) are used as a basis for policy and decision making on measures for dealing with the pandemic. Normalisation is required to account for the dilution rate of the domestic wastewater that can strongly vary due to time- and location-dependent sewer inflow of runoff, industrial discharges and extraneous waters. The standard approach in sewage surveillance is normalisation using flow measurements, although flow based normalisation is not effective in case the wastewater volume sampled does not match the wastewater volume produced. In this paper, two alternative normalisation methods, using electrical conductivity and crAssphage have been studied and compared with the standard approach using flow measurements. For this, a total of 1116 24-h flow-proportional samples have been collected between September 2020 and August 2021 at nine monitoring locations. In addition, 221 stool samples have been analysed to determine the daily crAssphage load per person. Results show that, although crAssphage shedding rates per person vary greatly, on a population-level crAssphage loads per person per day were constant over time and similar for all catchments. Consequently, crAssphage can be used as a quantitative biomarker for populations above 5595 persons. Electrical conductivity is particularly suitable to determine dilution rates relative to dry weather flow concentrations. The overall conclusion is that flow normalisation is necessary to reliably determine short-term trends in virus circulation, and can be enhanced using crAssphage and/or electrical conductivity measurement as a quality check.

An outbreak of SARS-CoV-2 Alpha variant (Pango lineage B.1.1.7) was detected at a primary school (School X) in Lansingerland, the Netherlands, in December 2020. The outbreak was studied retrospectively, and population-based screening was used to assess the extent of virus circulation and decelerate transmission. Cases were SARS-CoV-2 laboratory confirmed and were residents of Lansingerland (November 16th 2020 until February 22th 2021), or had an epidemiological link with School X or neighbouring schools. The SARS-CoV-2 variant was determined using variant PCR or whole genome sequencing. A questionnaire primarily assessed clinical symptoms. A total of 77 Alpha variant cases were found with an epidemiological link to School X, 16 Alpha variant cases linked to the neighbouring schools, and 146 Alpha variant cases among residents of Lansingerland without a link to the schools. The mean number of self-reported symptoms was not significantly different among Alpha variant infected individuals compared to non-Alpha infected individuals. The secondary attack rate (SAR) among Alpha variant exposed individuals in households was 52% higher compared to non-Alpha variant exposed individuals (p = 0.010), with the mean household age, and mean number of children and adults per household as confounders. Sequence analysis of 60 Alpha variant sequences obtained from cases confirmed virus transmission between School X and neighbouring schools, and showed that multiple introductions of the Alpha variant had already taken place in Lansingerland at the time of the study. The alpha variant caused a large outbreak at both locations of School X, and subsequently spread to neighbouring schools, and households. Population-based screening (together with other public health measures) nearly stopped transmission of the outbreak strain, but did not prevent variant replacement in the Lansingerland municipality.