Brown Kendra I, Graham Katherine E, Soller Jeffrey A, Boehm Alexandria B
Department of Civil and Environmental Engineering, Environmental Engineering and Science, Stanford University, 94305-4020, USA.
Environ Sci Process Impacts. 2017 Dec 13;19(12):1528-1541. doi: 10.1039/c7em00316a.
Beaches often receive fecal contamination from more than one source. Human sources include untreated sewage as well as treated wastewater effluent, and animal sources include wildlife such as gulls. Different contamination sources are expected to pose different health risks to swimmers. Genetic microbial source tracking (MST) markers can be used to detect bacteria that are associated with different animal sources, but the health risks associated with a mixture of MST markers are unknown. This study presents a method for predicting these health risks, using human- and gull-associated markers as an example. Quantitative Microbial Risk Assessment (QMRA) is conducted with MST markers as indicators. We find that risks associated with exposure to a specific concentration of a human-associated MST marker (HF) are greater if the HF source is untreated sewage rather than treated wastewater effluent. We also provide a risk-based threshold of HF from untreated sewage at a beach, to stay below a predicted illness risk of 3 per 100 swimmers, that is a function of gull-associated MST marker (CAT) concentration.
海滩常常受到不止一个来源的粪便污染。人类来源包括未经处理的污水以及经过处理的废水排放，动物来源包括海鸥等野生动物。不同的污染源预计会给游泳者带来不同的健康风险。基因微生物源追踪（MST）标记可用于检测与不同动物来源相关的细菌，但与MST标记混合物相关的健康风险尚不清楚。本研究以与人类和海鸥相关的标记为例，提出了一种预测这些健康风险的方法。以MST标记为指标进行定量微生物风险评估（QMRA）。我们发现，如果人类相关的MST标记（HF）的来源是未经处理的污水而非经过处理的废水排放，那么接触特定浓度的该标记所带来的风险会更大。我们还给出了海滩上未经处理污水中HF的基于风险的阈值，以使每100名游泳者的预测患病风险保持在3以下，该阈值是与海鸥相关的MST标记（CAT）浓度的函数。
