Canada Research Chair in Source Water Protection, Polytechnique Montréal, Civil, Geological and Mining Engineering Department, P.O. Box 6079, Station Centre-Ville, Montréal H3C 3A7, Québec, Canada; NSERC Industrial Chair on Drinking Water, Polytechnique Montréal, Civil, Geological and Mining Engineering Department, P.O. Box 6079, Station Centre-Ville, Montréal H3C 3A7, Québec, Canada.
Modelling Surface Water Limited, Toronto, Canada.
Sci Total Environ. 2019 Nov 25;693:133567. doi: 10.1016/j.scitotenv.2019.07.373. Epub 2019 Jul 23.
The aim of this study was to assess the variability of microbial risk associated with drinking water under various contaminant loading conditions in a drinking water source. For this purpose, a probabilistic-deterministic approach was applied to estimate the loadings of Cryptosporidium, Giardia, and Escherichia coli (E. coli) from fecal contamination sources during both dry and wet weather conditions. The relative importance of loads originating from various fecal contamination sources was also determined by a probabilistic approach. This study demonstrates that water resource recovery facilities were the dominant source of Giardia, yet rivers were more important with regards to Cryptosporidium. Estimated loadings were used as input to a three-dimensional hydrodynamic model of Lake Ontario; the fate and transport of microbial organisms were simulated at the influent of a drinking water intake. Discharge-based hydrodynamic modelling results were compared to observed concentrations. Simulated probability distributions of concentrations at the intake were used as an input to a quantitative microbial risk assessment (QMRA) model such that the variability of microbial risk in the context of drinking water could be examined. Depending on wind and currents, higher levels of fecal contamination reached the intake during wet weather loading scenarios. Probability distribution functions of Cryptosporidium, Giardia and E. coli concentrations at the intake were significantly higher during wet weather conditions when compared to dry conditions (p < 0.05). For all contaminants studied, the QMRA model showed a higher risk during wet weather (over 1 order of magnitude) compared to dry weather conditions. When considering sewage by-pass scenarios, risks remained below 2.7 × 10 person day for Giardia and E. coli O157:H7. Limited data were available for Cryptosporidium in by-pass effluents and the risk is unknown; hence it is critical to obtain reliable loading data for the riskiest scenarios, such as those associated with water resource recovery facility by-passes.
本研究旨在评估在饮用水源中各种污染物负荷条件下与饮用水相关的微生物风险的变异性。为此，应用概率-确定性方法来估算在干湿条件下，粪便污染源中隐孢子虫、贾第鞭毛虫和大肠杆菌（E. coli）的负荷。还通过概率方法确定了来自各种粪便污染源的负荷的相对重要性。本研究表明，水资源回收设施是贾第鞭毛虫的主要来源，但对于隐孢子虫而言，河流更为重要。估算的负荷被用作安大略湖三维水动力模型的输入；在饮用水入口处模拟微生物的命运和运输。基于排放的水动力模型结果与观测浓度进行比较。进水口处的浓度模拟概率分布用作定量微生物风险评估 (QMRA) 模型的输入，以便可以检查饮用水背景下微生物风险的变异性。根据风和水流的情况，在湿天气负荷情况下，更多的粪便污染到达进水口。与干天气条件相比，进水口处隐孢子虫、贾第鞭毛虫和大肠杆菌浓度的概率分布函数在湿天气条件下显着更高（p <0.05）。对于所有研究的污染物，与干天气条件相比，QMRA 模型在湿天气条件下显示出更高的风险（超过 1 个数量级）。考虑到污水旁路情况，对于贾第鞭毛虫和大肠杆菌 O157：H7，风险仍然低于 2.7×10 人天。旁路污水中隐孢子虫的数据有限，风险未知；因此，对于风险最大的情况（例如与水资源回收设施旁路相关的情况）获取可靠的负荷数据至关重要。
