Human Bacteroides and total coliforms as indicators of recent combined sewer overflows and rain events in urban creeks
Combined sewer overflows (CSOs) are a known source of human fecal pollution and human pathogens in urban water bodies, which may present a significant public health threat. To monitor human fecal contamination in water, bacterial fecal indicator organisms (FIOs) are traditionally used. However, because FIOs are not specific to human sources and do not correlate with human pathogens, alternative fecal indicators detected using qPCR are becoming of interest to policymakers. For this reason, this study measured correlations between the number and duration of CSOs and mm of rainfall, concentrations of traditional FIOs and alternative indicators, and the presence of human pathogens in two urban creeks. Samples were collected May–July 2016 and analyzed for concentrations of FIOs (total coliforms and E. coli) using membrane filtration as well as for three alternative fecal indicators (human Bacteroides HF183 marker, human polyomavirus (HPoV), pepper mild mottle virus (PMMoV)) and nine human pathogens using qPCR. Four of the nine pathogens analyzed were detected at these sites including adenovirus, Enterohemorrhagic E. coli, norovirus, and Salmonella. Among all indicators studied, human Bacteroides and total coliforms were significantly correlated with recent CSO and rainfall events, while E. coli, PMMoV, and HPoV did not show consistent significant correlations. Further, human Bacteroides were a more specific indicator, while total coliforms were a more sensitive indicator of CSO and rainfall events. Results may have implications for the use and interpretation of these indicators in future policy or monitoring programs.
Additional publication details
|Publication Subtype||Journal Article|
|Title||Human Bacteroides and total coliforms as indicators of recent combined sewer overflows and rain events in urban creeks|
|Series title||Science of the Total Environment|
|Contributing office(s)||Wisconsin Water Science Center|
|Google Analytic Metrics||Metrics page|