High levels of sewage contamination released from urban areas after storm events: A quantitative survey with sewage specific bacterial indicators

Background Past studies have demonstrated an association between waterborne disease and heavy precipitation, and climate change is predicted to increase the frequency of these types of intense storm events in some parts of the United States. In this study, we examined the linkage between rainfall and sewage contamination of urban waterways and quantified the amount of sewage released from a major urban area under different hydrologic conditions to identify conditions that increase human risk of exposure to sewage. Methods and findings Rain events and low-flow periods were intensively sampled to quantify loads of sewage based on two genetic markers for human-associated indicator bacteria (human Bacteroides and Lachnospiraceae). Samples were collected at a Lake Michigan estuary and at three river locations immediately upstream. Concentrations of indicators were analyzed using quantitative polymerase chain reaction (qPCR), and loads were calculated from streamflow data collected at each location. Human-associated indicators were found during periods of low flow, and loads increased one to two orders of magnitude during rain events from stormwater discharges contaminated with sewage. Combined sewer overflow (CSO) events increased concentrations and loads of human-associated indicators an order of magnitude greater than heavy rainfall events without CSO influence. Human-associated indicator yields (load per km2 of land per day) were related to the degree of urbanization in each watershed. Contamination in surface waters were at levels above the acceptable risk for recreational use. Further, evidence of sewage exfiltration from pipes threatens drinking water distribution systems and source water. While this study clearly demonstrates widespread sewage contamination released from urban areas, a limitation of this study is understanding human exposure and illness rates, which are dependent on multiple factors, and gaps in our knowledge of the ultimate health outcomes. Conclusions With the prediction of more intense rain events in certain regions due to climate change, sewer overflows and contamination from failing sewer infrastructure may increase, resulting in increases in waterborne pathogen burdens in waterways. These findings quantify hazards in exposure pathways from rain events and illustrate the additional stress that climate change may have on urban water systems. This information could be used to prioritize efforts to invest in failing sewer infrastructure and create appropriate goals to address the health concerns posed by sewage contamination from urban areas.

areas. The Milwaukee estuary site was at the USGS station at Jones Island water reclamation facility in Milwaukee, Wisconsin (USGS station number 04087170). The MKE River sampler was housed within an MMSD real-time water quality station beneath the Cherry Street Bridge in Milwaukee, WI. The MN River sampler was housed within the USGS monitoring station on 16 th Street in Milwaukee, WI (USGS station number 04087142). The KK River sampler was housed within the USGS monitoring station on 11 th and Harrison Streets in Milwaukee, WI (USGS station number 04087159).

Flow data retrieval
River streamflow was retrieved from USGS continuous monitoring stations on the KK River at 11 th Street (USGS station number 04087159), the MN River at Wauwatosa, WI (USGS station number 04087120), and the MKE River at Milwaukee, WI (USGS station number 04087000), which are represented in S2 Table. MN River at Wauwatosa, WI streamflow measurements were multiplied by a drainage area ratio correction of 1.0976 and MKE River at Milwaukee, WI streamflow measurements were multiplied by a drainage area ratio correction of 1.0117 to

qPCR analysis
For qPCR, standard curves were run with DNA serially diluted from 1.5x10 6 to 1.5x10 1 copies per reaction and standards were run in triplicate. HB, Lachno2, and ruminant assay slopes, intercepts, and efficiency are shown in S3 Table for all storm events and 400 mL was filtered for low flow samples. The limit of reliable quantification was determined to be 15 copies per reaction, or 225 CN/100 mL. Therefore, any samples with positive amplification, but were below 15 copies were reported as below the limit of quantification (BLQ).

Rainfall data retrieval
For the majority of events, average one-hour rainfall accumulation was computed for each watershed-defined area using radar-indicated rainfall models, retrieved from the National Weather Service North-Central River Forecast Center (National Weather Service, 2015). For events during which rainfall amounts from the National Weather Service were missing, the Thiessen polygon method was used in ESRI ArcGIS® to determine weights that were placed on MMSD rain gauges in each watershed. Rainfall depths from each rain gauge within each watershed were multiplied by their respective weights and these values were summed to compute average hourly rainfall depths across each watershed.

Complications to load and mass balance computations in a freshwater estuary
Although samples were collected in the KK, MN, and MKE Rivers and the Milwaukee estuary during nearly the same time periods, due to the complexity of the Milwaukee estuary, S3 determining a mass balance between the sewage loads measured in the rivers and the loads measured in the estuary is more complicated than simply adding up the loads from the three rivers and expecting it to be equal to loads measured in the estuary. Because of the proximity of the Milwaukee estuary to Lake Michigan, there is a significant amount of backflow which dilutes the concentrations measured in the samples collected in this study. The sampling location in the Milwaukee estuary is upstream of where the effluent from the Jones Island water reclamation facility is discharged, yet backflow could cause some of this effluent to flow upstream and potentially contribute to the concentrations measured in the estuary. Another issue is the distance between each sampling locations on the rivers and the sampling location in the estuary. Each of the rivers has a different velocity, effecting the travel time between the river monitoring sites and the estuary monitoring site. The bacteria we are measuring in the rivers may degrade or settle into the sediment before reaching the estuary, and likewise, bacteria can be re-suspended from the sediment into the water column. Settling could be significant due to the slowing of velocity in the estuary where the channels cross sections are much larger, and water surface slopes decrease due to influence from Lake Michigan. Additionally, samples are collected in the estuary from a relatively shallow intake of approximately two meters below the surface, meaning there is a potential for bacteria to be settled further down in the water column before reaching our sampling point. Finally, additional contributions from the urban areas located between the sampling locations on the rivers and in the estuary were not accounted for; however, for most events the sum of the loads from the three rivers were greater than the load in the estuary, suggesting settling and dilution outweighs these additional contributions.