Evaluation of the Export of Fecal Contamination from Roadside Green Infrastructure

Journal of Sustainable Water in the Built Environment(2023)

引用 1|浏览13
暂无评分
摘要
Fecal contamination in stormwater runoff is a leading contributor of waterbody impairment in the US, and green infrastructure (GI) has demonstrated variable performance in its mitigation. Therefore, there is a need for studies that use robust sampling methods to quantify concentration and load reductions as well as evaluate export of fecal contamination with respect to other water quality constituents. The objective of this study was to characterize the performance of various types of GI systems in mitigating fecal contamination [measured as Escherichia coli (EC)] in highway stormwater runoff. This study was conducted at a field site on Lorton Road in Fairfax County, Virginia, where a bioretention, bioswale, compost-amended grass channel and a grass channel were instrumented for 2 years in all seasons for flow-weighted composite sampling and volume monitoring. The bioretention effectively reduced EC concentration and loading from a relatively high inflow concentration [1,120 most probable number (MPN)/100 mL]. The swales, however, consistently increased EC concentration from their relatively low average inflow concentration of 58 MPN/100 mL but had no significant impact on mass load. For all GI systems, outflow concentrations were regularly above recreational water quality standards. Regression analyses indicated that average daily temperature, dissolved organic carbon, total dissolved nitrogen, and chloride were significantly correlated with the log-transformed EC concentrations exiting the GI systems. We conclude that EC export is prevalent in varying degrees in the studied GI systems such that the bioretention reduces its presence, whereas the swales often increase its presence. This study provides insight into environmental factors and common stormwater quality constituents that are correlated with the export of fecal contamination from GI. DOI: 10.1061/JSWBAY.0001002. (c) 2022 American Society of Civil Engineers.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要