Department of Geography & Environmental Studies, Toronto Metropolitan University, Canada.
Department of Geography & Environmental Studies, Toronto Metropolitan University, Canada; Department of Earth and Planetary Sciences, McGill University, Canada.
Sci Total Environ. 2024 Jul 1;932:172917. doi: 10.1016/j.scitotenv.2024.172917. Epub 2024 May 1.
PMMoV has been widely used to normalize the concentration of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA, influenza, and respiratory syncytial virus (RSV) to account for variations in the fecal content of wastewater. PMMoV is also used as an internal RNA recovery control for wastewater-based epidemiology (WBE) tests. While potentially useful for the interpretation of WBE data, previous studies have suggested that PMMoV concentration can be affected by various physico-chemical characteristics of wastewater. There is also the possibility that laboratory methods, particularly the variability in centrifugation steps to remove supernatant from pellets can cause PMMoV variability. The goal of this study is to improve our understanding of the main drivers of PMMoV variability by assessing the relationship between PMMoV concentration, the physico-chemical characteristics of wastewater, and the methodological approach for concentrating wastewater samples. We analyzed 24-hour composite wastewater samples collected from the influent stream of three wastewater treatment plants (WWTPs) located in the City of Toronto, Ontario, Canada. Samples were collected 3 to 5 times per week starting from the beginning of March 2021 to mid-July 2023. The influent flow rate was used to partition the data into wet and dry weather conditions. Physico-chemical characteristics (e.g., total suspended solids (TSS), biological oxygen demand (BOD), alkalinity, electrical conductivity (EC), and ammonia (NH)) of the raw wastewater were measured, and PMMoV was quantified. Spatial and temporal variability of PMMoV was observed throughout the study period. PMMoV concentration was significantly higher during dry weather conditions. Multiple linear regression analysis demonstrates that the number and type of physico-chemical parameters that drive PMMoV variability are site-specific, but overall BOD and alkalinity were the most important predictors. Differences in PMMoV concentration for a single WWTP between two different laboratory methods, along with a weak correlation between pellet mass and TSS using one method may indicate that differences in sample concentration and subjective subsampling bias could alter viral recovery and introduce variability to the data.
PMMoV 已被广泛用于标准化严重急性呼吸综合征冠状病毒 2 (SARS-CoV-2) RNA、流感和呼吸道合胞病毒 (RSV) 的浓度,以解释废水粪便含量的变化。PMMoV 也被用作基于废水的流行病学 (WBE) 测试的内部 RNA 回收对照。虽然它对 WBE 数据的解释可能有用,但以前的研究表明,PMMoV 浓度可能受到废水各种理化特性的影响。此外,实验室方法,特别是离心步骤去除沉淀上清液的差异,也可能导致 PMMoV 变化。本研究的目的是通过评估 PMMoV 浓度、废水理化特性和浓缩废水样品的方法学方法之间的关系,提高我们对 PMMoV 变异性主要驱动因素的理解。我们分析了 2021 年 3 月初至 2023 年 7 月中旬期间从加拿大安大略省多伦多市的三个污水处理厂 (WWTP) 的进水流中收集的 24 小时复合废水样品。每周收集 3 到 5 次样品。进水流量用于将数据分为湿天和干天条件。测量了原废水的理化特性(例如总悬浮固体 (TSS)、生化需氧量 (BOD)、碱度、电导率 (EC) 和氨 (NH)),并定量了 PMMoV。整个研究期间都观察到 PMMoV 的时空变异性。在干天条件下,PMMoV 浓度显著更高。多元线性回归分析表明,驱动 PMMoV 变异性的理化参数的数量和类型因地点而异,但 BOD 和碱度总体上是最重要的预测因子。单个 WWTP 在两种不同实验室方法之间的 PMMoV 浓度差异,以及一种方法中沉淀质量与 TSS 之间的弱相关性,可能表明样品浓度差异和主观亚采样偏差会改变病毒回收率,并为数据引入变异性。