Connecting blue-green infrastructure elements to reduce combined sewer overflows.

By infiltrating and retaining stormwater, Blue-Green Infrastructure (BGI) can help to reduce Combined Sewer Overflows (CSOs), one of the main causes of urban water pollution. Several studies have evaluated the ability of individual BGI types to reduce CSOs; however, the effect of combining these elements, likely to occur in reality, has not yet been thoroughly evaluated. Moreover, the CSO volume reduction potential of relevant components of the urban drainage system, such as detention ponds, has not been quantified using hydrological models. This study presents a systematic way to assess the potential of BGI combinations to mitigate CSO discharge in a catchment near Zurich (Switzerland). Sixty BGI combinations, including four BGI elements (bioretention cells, permeable pavement, green roofs, and detention ponds) and four different implementation rates (25%, 50%, 75%, and 100% of the available sewer catchment area) are evaluated for four runoff routing schemes. Results reveal that BGI combinations can provide substantial CSO volume reductions; however, combinations including detention ponds can potentially increase CSO frequency, due to runoff prolongation. When runoff from upstream areas is routed to the BGI, the CSO discharge reductions from combinations of BGI elements differ from the cumulative CSO discharge reductions achieved by individual BGI types, indicating that the sum of effects from individual BGI types cannot accurately predict CSO discharge in combined BGI scenarios. Moreover, larger BGI implementation areas are not consistently more cost-effective than small implementation areas, since the additional CSO volume reduction does not outweigh the additional costs. The best-performing BGI combination depends on the desired objective, being CSO volume reduction, CSO frequency reduction or cost-effectiveness. This study emphasizes the importance of BGI combinations and detention ponds in CSO mitigation plans, highlighting their critical factors-BGI types, implementation area, and runoff routing- and offering a novel and systematic approach to develop tailored BGI strategies for urban catchments facing CSO challenges.

The effect of green infrastructure on resilience performance in combined sewer systems under climate change.

Climate change is currently reshaping precipitation patterns, intensifying extremes, and altering runoff dynamics. Particularly susceptible to these impacts are combined sewer systems (CSS), which convey both stormwater and wastewater and can lead to combined sewer overflow (CSO) discharges during heavy rainfall. Green infrastructure (GI) can help mitigate these discharges and enhance system resilience under historical conditions; however, the quantification of its effect on resilience in a future climate remains unknown in the literature. This study employs a modified Global Resilience Analysis (GRA) framework for continuous simulation to quantify the impact of climate change on CSS resilience, particularly CSOs. The study assesses the efficacy of GI interventions (green roofs, permeable pavements, and bioretention cells) under diverse future rainfall scenarios based on EURO-CORDEX regional climate models (2085-2099) and three Representative Concentration Pathways (2.6, 4.5, 8.5 W/m2). The findings underscore a general decline in resilience indices across the future rainfall scenarios considered. Notably, the total yearly CSO discharge volume increases by a range of 145 % to 256 % in response to different rainfall scenarios. While GI proves effective in increasing resilience, it falls short of offsetting the impacts of climate change. Among the GI options assessed, green roofs routed to pervious areas exhibit the highest adaptive capacity, ranging from 9 % to 22 % at a system level, followed by permeable pavements with an adaptation capacity between 7 and 13 %. By linking the effects of future rainfall scenarios on CSO performance, this study contributes to understanding GI's potential as a strategic tool for enhancing urban resilience.

Do baseline assumptions alter the efficacy of green stormwater infrastructure to reduce combined sewer overflows?

Green stormwater infrastructure (GSI) is growing in popularity to reduce combined sewer overflows (CSOs) and hydrologic simulation models are a tool to assess their reduction potential. Given the numerous and interacting water flows that contribute to CSOs, such as evapotranspiration (ET) and groundwater (GW), these models should ideally account for them. However, due to the complexity, simplified models are often used, and it is currently unknown how these assumptions affect estimates of CSOs, GSI effectiveness, and ultimately planning guidance. This study evaluates the effect on estimates of CSOs and GSI effectiveness when different flows and hydrologic processes are neglected. We modified an existing EPA SWMM model of a combined sewer system in Switzerland to include ET, GW, and upstream inflows. Historical rainfall data over 30 years are used to assess volume and duration of CSOs with and without three types of GSI (bioretention basins, permeable pavements and green roofs). Results demonstrate that neglect of certain flows in modelling can alter CSO volumes from -15 % to 40 %. GSI effectiveness also varies considerably, resulting in differences in simulated percent of CSO volume reduced from 8 % to 35 %, depending on the GSI type and modeled flow or process. Representation of GW within models is particularly crucial when infiltrating GSI are present, as CSOs could increase in certain subcatchments due to higher GW levels from increased infiltration. When basing GSI planning decisions on modeled estimates of CSOs, all relevant hydrologic processes should be included to the extent possible, and uncertainty and assumptions should always be considered.

Microbial, holobiont, and Tree of Life eDNA/eRNA for enhanced ecological assessment.

Microbial environmental DNA and RNA (collectively 'eNA') originate from a diverse and abundant array of microbes present in environmental samples. These eNA signals, largely representing whole organisms, serve as a powerful complement to signals derived from fragments or remnants of larger organisms. Integrating microbial data into the toolbox of ecosystem assessments and biotic indices therefore has the potential to transform how we use eNA data to understand biodiversity dynamics and ecosystem functions, and to inform the next generation of environmental monitoring. Incorporating holobiont and Tree of Life approaches into eNA analyses offers further holistic insight into the range of ecological interactions between microbes and other organisms, paving the way for advancing our understanding of, and ultimately manipulating ecosystem properties pertinent to environmental management, conservation, wildlife health, and food production.

Interleukin-6 induces nascent protein synthesis in human dorsal root ganglion nociceptors primarily via MNK-eIF4E signaling.

Plasticity of dorsal root ganglion (DRG) nociceptors in the peripheral nervous system requires new protein synthesis. This plasticity is believed to be responsible for the physiological changes seen in DRG nociceptors in animal models of chronic pain. Experiments in human DRG (hDRG) neurons also support this hypothesis, but a direct observation of nascent protein synthesis in response to a pain promoting substance, like interleukin-6 (IL-6), has not been measured in these neurons. To fill this gap in knowledge, we used acutely prepared human DRG explants from organ donors. These explants provide a physiologically relevant microenvironment, closer to in vivo conditions, allowing for the examination of functional alterations in DRG neurons reflective of human neuropathophysiology. Using this newly developed assay, we demonstrate upregulation of the target of the MNK1/2 kinases, phosphorylated eIF4E (p-eIF4E), and nascently synthesized proteins in a substantial subset of hDRG neurons following exposure to IL-6. To pinpoint the specific molecular mechanisms driving this IL-6-driven increase in nascent proteins, we used the specific MNK1/2 inhibitor eFT508. Treatment with eFT508 resulted in the inhibition of IL-6-induced increases in p-eIF4E and nascent proteins. Additionally, using TRPV1 as a marker for nociceptors, we found that these effects occurred in a large number of human nociceptors. Our findings provide clear evidence that IL-6 drives nascent protein synthesis in human TRPV1+ nociceptors primarily via MNK1/2-eIF4E signaling. The work links animal findings to human nociception, creates a framework for additional hDRG signaling experiments, and substantiates the continued development of MNK inhibitors for pain.