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Coupling a continuous watershed-scale microbial fate and transport model with a stochastic dose-response model to estimate risk of illness in an urban watershed

机译:将连续流域规模的微生物归宿和迁移模型与随机剂量反应模型耦合,以估计城市流域中的疾病风险

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Within the United States, elevated levels of fecal indicator bacteria (FIB) remain the leading cause of surface water-quality impairments requiring formal remediation plans under the federal Clean Water Act's Total Maximum Daily Load (TMDL) program. The sufficiency of compliance with numerical FIB criteria as the targeted end-point of TMDL remediation plans may be questionable given poor correlations between FIB and pathogenic microorganisms and varying degrees of risk associated with exposure to different fecal pollution sources (e.g. human vs animal). The present study linked a watershed-scale FIB fate and transport model with a dose-response model to continuously predict human health risks via quantitative microbial risk assessment (QMRA), for comparison to regulatory benchmarks. This process permitted comparison of risks associated with different fecal pollution sources in an impaired urban watershed in order to identify remediation priorities. Results indicate that total human illness risks were consistently higher than the regulatory benchmark of 36 illnesses/1000 people for the study watershed, even when the predicted FIB levels were in compliance with the Escherichia coli geometric mean standard of 126 CFU/100 mL. Sanitary sewer overflows were associated with the greatest risk of illness. This is of particular concern, given increasing indications that sewer leakage is ubiquitous in urban areas, yet not typically fully accounted for during TMDL development Uncertainty analysis suggested the accuracy of risk estimates would be improved by more detailed knowledge of site-specific pathogen presence and densities. While previous applications of the QMRA process to impaired waterways have mostly focused on single storm events or hypothetical situations, the continuous modeling framework presented in this study could be integrated into long-term water quality management planning, especially the United States' TMDL program, providing greater clarity to watershed stakeholders and decision-makers.
机译:在美国,粪便指示菌(FIB)含量升高仍然是造成地表水水质损害的主要原因,这需要根据联邦《清洁水法》的“每日最大总载水量”(TMDL)计划制定正式的修复计划。鉴于FIB与病原微生物之间的相关性较差,以及与不同粪便污染源(例如人与动物)接触相关的风险程度不同,是否符合FIB数字标准作为TMDL修复计划目标终点的充分性可能会受到质疑。本研究将分水岭规模的FIB命运和运输模型与剂量反应模型联系起来,以通过定量微生物风险评估(QMRA)持续预测人类健康风险,以与监管基准进行比较。通过此过程,可以对受损的城市流域中与不同粪便污染源相关的风险进行比较,以便确定修复的重点。结果表明,即使预测的FIB水平符合126 CFU / 100 mL的大肠杆菌几何平均标准,人类的总疾病风险也始终高于本研究分水岭的36种疾病/ 1000人的监管基准。下水道溢水与患病的最大风险有关。考虑到越来越多的迹象表明下水道渗漏在城市地区无处不在,但在TMDL开发过程中通常无法完全解决,这一点尤其令人担忧。不确定性分析表明,通过更详细地了解特定地点的病原体的存在和密度,可以提高风险估计的准确性。尽管QMRA流程以前在受损水道中的应用主要集中在单个暴风雨事件或假设情况上,但本研究中介绍的连续建模框架可以集成到长期水质管理计划中,尤其是美国的TMDL计划,分水岭的利益相关者和决策者更加清晰。

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