As decentralized water reuse continues to gain popularity, risk-based treatment guidance is increasingly sought for the protection of public health. However, efforts to evaluate pathogen risks and log-reduction requirements have been hindered by an incomplete understanding of pathogen occurrence and densities in locally-collected wastewaters (i.e., from decentralized collection systems). Of particular interest is the potentially high enteric pathogen concentration in small systems with an active infected excreter, but generally lower frequency of pathogen occurrences in smaller systems compared to those with several hundred contributors. Such variability, coupled with low concentrations in many source streams (e.g., sink, shower/bath, and laundry waters), has limited direct measurement of pathogens. This study presents an approach to modeling pathogen concentrations in variously sized greywater and combined wastewater collection systems based on epidemiological pathogen incidence rates, user population size, and fecal loadings to various residential wastewater sources. Pathogen infections were modeled within various population sizes (5-, 100-, and 1,000-person) for seven reference pathogens (viruses: adenoviruses, Norovirus, and Rotavirus; bacteria: Campylobacter and Salmonella spp.; and protozoa: Cryptosporidium and Giardia spp.) on each day of 10,000 possible years, accounting for intermittent infection and overlap of infection periods within the population. Fecal contamination of fresh greywaters from bathroom sinks, showers/baths, and laundry, as well as combined greywater and local combined wastewater (i.e., including toilets), was modeled based on reported fecal indicators in the various sources. Simulated daily infections and models of fecal contamination were coupled with pathogen shedding characteristics to generate distributions of pathogen densities in the various waters. The predicted frequency of pathogen occurrences in local wastewaters was generally low due to low infection incidence within small cohort groups, but increased with collection scale (population size) and infection incidence rate (e.g., Norovirus). When pathogens did occur, a decrease in concentrations from 5- to 100- and from 100- to 1,000-person systems was observed; nonetheless, overall mean concentrations (i.e., including non-occurrences) remained the same due to the increased number of occurrences. This highlights value of the model for characterizing scaling effects over averaging methods, which overestimate the frequency of pathogen occurrence in small systems while underestimating concentration peaks that likely drive risk periods. Results of this work will inform development of risk-based pathogen reduction requirements for decentralized water reuse.

随着分散式水回用的不断普及，人们越来越多地寻求基于风险的处理指南来保护公众健康。然而，由于对当地收集的废水（即来自分散的收集系统）中病原体的出现和密度的不完全了解，评估病原体风险和对数减少要求的努力受到阻碍。特别令人感兴趣的是，在具有活跃的受感染排泄物的小型系统中，肠道病原体浓度可能很高，但与具有数百个贡献者的系统相比，较小的系统中病原体出现的频率通常较低。这种变异性，加上许多源流（例如水槽、淋浴/浴缸和洗衣水）中的低浓度，限制了病原体的直接测量。本研究提出了一种根据流行病学病原体发病率、用户人口规模和各种住宅废水源的粪便负荷对不同规模的灰水和组合废水收集系统中的病原体浓度进行建模的方法。在不同人口规模（5、100 和 1,000 人）内对七种参考病原体（病毒：腺病毒、诺如病毒和轮状病毒；细菌：弯曲杆菌和沙门氏菌；原生动物：隐孢子虫和贾第鞭毛虫）进行了病原体感染建模。 ）在 10,000 个可能年中的每一天，考虑到人群中的间歇性感染和感染期重叠。浴室水槽、淋浴/浴缸和洗衣房的新鲜灰水以及混合灰水和当地混合废水（即，包括厕所）的粪便污染是根据报告的各种来源的粪便指标进行建模的。模拟的日常感染和粪便污染模型与病原体脱落特征相结合，生成不同水域中病原体密度的分布。由于小群体内感染发生率较低，预测当地废水中病原体出现的频率通常较低，但随着收集规模（种群规模）和感染发生率（例如诺如病毒）的增加而增加。当病原体确实出现时，观察到浓度从 5 人减少到 100 人，以及从 100 人减少到 1,000 人系统；尽管如此，总体平均浓度（即，包括未发生的情况）由于发生次数的增加而保持不变。这凸显了该模型在表征尺度效应方面相对于平均方法的价值，平均方法高估了小型系统中病原体出现的频率，同时低估了可能驱动风险期的浓度峰值。这项工作的结果将为分散式水回用制定基于风险的病原体减少要求提供信息。