Wastewater compounds are frequently detected in urban shallow groundwater. Sources include sewage or reclaimed wastewater, but origins are often unknown. In a prior study, wastewater compounds were quantified in waters sampled from shallow groundwater wells in a small coastal California city. Here, we resampled those wells and expanded sample analyses to include sewage- or reclaimed water-specific indicators, i.e. pharmaceutical and personal care product chemicals or disinfection byproducts. Also, we developed a geographic information system (GIS)-based model of sanitary sewer exfiltration probability--combining a published pipe failure model accounting for sewer pipe size, age, materials of construction, with interpolated depths to groundwater--to determine if sewer system attributes relate to wastewater compounds in urban shallow groundwater. Across the wells, groundwater samples contained varying wastewater compounds, including acesulfame, sucralose, bisphenol A, 4-tert-octylphenol, estrone and perfluorobutanesulfonic acid (PFBS). Fecal indicator bacterial concentrations and toxicological bioactivities were less than known benchmarks. However, the reclaimed water in this study was positive for all bioactivity tested. Excluding one well intruded by seawater, the similarity of groundwater to sewage, based on multiple indicators, increased with increasing sanitary sewer exfiltration probability (modeled from infrastructure within ca. 300 m of each well). In the absence of direct exfiltration or defect measurements, sewer exfiltration probabilities modeled from the collection system's physical data can indicate potential locations where urban shallow groundwater is contaminated by sewage.
Twentieth century municipal wastewater infrastructure greatly improved U.S. urban public health and water quality. However, sewer pipes deteriorate, and their accumulated structural defects may release untreated wastewater to the environment via acute breaks or insidious exfiltration. Exfiltrated wastewater constitutes a loss of potentially reusable water and delivers a complex and variable mix of contaminants to urban shallow groundwater. Yet, predicting where deteriorated sewers impinge on shallow groundwater has been challenging. Here we develop and test a spatially explicit model of exfiltration probability based on pipe attributes and groundwater elevation without prior knowledge of exfiltrating defect locations. We find that models of exfiltration probability can predict the probable occurrence in underlying shallow groundwater of established wastewater indicators including the artificial sweetener acesulfame, tryptophan-like fluorescent dissolved organic matter, nitrate, and a stable isotope of water (δO). The strength of the association between exfiltration probability and indicators of wastewater increased when multiple pipe attributes, distance weighting, and groundwater flow direction were considered in the model. The results prove that available sanitary sewer databases and groundwater digital elevation data can be analyzed to predict where pipes are likely leaking and contaminating groundwater. Such understanding could direct sewer infrastructure reinvestment toward water resource protection.
In this study, we explore the use of unsteady transit time distribution (TTD) theory to model solute transport in biofilters, a popular form of nature‐based or “green” storm water infrastructure (GSI). TTD theory has the potential to address many unresolved challenges associated with predicting pollutant fate and transport through these systems, including unsteadiness in the water balance (time‐varying inflows, outflows, and storage), unsteadiness in pollutant loading, time‐dependent reactions, and scale‐up to GSI networks and urban catchments. From a solution to the unsteady age conservation equation under uniform sampling, we derive an explicit expression for solute breakthrough during and after one or more storm events. The solution is calibrated and validated with breakthrough data from 17 simulated storms at a field‐scale biofilter test facility in Southern California, using bromide as a conservative tracer. TTD theory closely reproduces bromide breakthrough concentrations, provided that lateral exchange with the surrounding soil is accounted for. At any given time, according to theory, more than half of the water in storage is from the most recent storm, while the rest is a mixture of penultimate and earlier storms. Thus, key management endpoints, such as the pollutant treatment credit attributable to GSI, are likely to depend on the evolving age distribution of water stored and released by these systems.
In urban areas, untreated stormwater runoff can pollute downstream surface waters. To intercept and treat runoff, low-impact or "green infrastructure" approaches such as biofilters are adopted. Yet actual biofilter pollutant removal is poorly understood; removal is often studied in laboratory columns, with variable removal of viable and culturable microbial cell numbers including pathogens. Here, to assess bacterial pollutant removal in full-scale planted biofilters, stormwater was applied, unspiked or spiked with untreated sewage, in simulated storm events under transient flow conditions during which biofilter influents versus effluents were compared. Based on microbial biomass, sequences of bacterial community genes encoding 16S rRNA, and gene copies of the human fecal marker HF183 and of the Enterococci marker Entero1A, the removal of bacterial pollutants in biofilters was limited. Dominant bacterial taxa were similar for influent versus effluent aqueous samples within each inflow treatment of either spiked or unspiked stormwater. Bacterial pollutants in soil were gradually washed out, albeit incompletely, during simulated storm flushing events. In post-storm biofilter soil cores, retained influent bacteria were concentrated in the top layers (0-10 cm), indicating that the removal of bacterial pollutants was spatially limited to surface soils.To the extent that plant-associated processes are responsible for this spatial pattern, treatment performance might be enhanced by biofilter designs that maximize influent contact with the rhizosphere.
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