Accurate estimation of microbial concentrations is necessary to inform many important environmental science and public health decisions and regulations. Critically, widespread misconceptions about laboratory-reported microbial non-detects have led to their erroneous description and handling as “censored” values. This ultimately compromises their interpretation and undermines efforts to describe and model microbial concentrations accurately. Herein, these misconceptions are dispelled by (1) discussing the critical differences between discrete microbial observations and continuous data acquired using analytical chemistry methodologies and (2) demonstrating the bias introduced by statistical approaches tailored for chemistry data and misapplied to discrete microbial data. Notably, these approaches especially preclude the accurate representation of low concentrations and those estimated using microbial methods with low or variable analytical recovery, which can be expected to result in non-detects. Techniques that account for the probabilistic relationship between observed data and underlying microbial concentrations have been widely demonstrated, and their necessity for handling non-detects (in a way which is consistent with the handling of positive observations) is underscored herein. Habitual reporting of raw microbial observations and sample sizes is proposed to facilitate accurate estimation and analysis of microbial concentrations.
Characterization of surface water - groundwater interaction in riverbank filtration (RBF) systems is of decisive importance to drinking water utilities due to the increasing microbial and chemical contamination of surface waters. These interactions are commonly assessed by monitoring changes in chemical water quality, but this might not be indicative for microbial contamination. The hydrological dynamics of the infiltrating river can influence these interactions, but seasonal temperature fluctuations and the supply of oxygen and nutrients from the surface water can also play a role. In order to understand the interaction between surface water and groundwater in a highly dynamic RBF system of a large river, bacterial abundance, biomass and carbon production as well as standard chemical parameters were analyzed during a 20 month period under different hydrological conditions. In the investigated RBF system, groundwater table changes exhibited striking dynamics even though flow velocities were rather low under regular discharge conditions. Bacterial abundance, biomass, and bacterial carbon production decreased significantly from the river towards the drinking water abstraction well. The cell size distribution changed from a higher proportion of large cells in the river, towards a higher proportion of small cells in the groundwater. Although biomass and bacterial abundance were correlated to water temperatures and several other chemical parameters in the river, such correlations were not present in the groundwater. In contrast, the dynamics of the bacterial groundwater community was predominantly governed by the hydrogeological dynamics. Especially during flood events, large riverine bacteria infiltrated further into the aquifer compared to average discharge conditions. With such information at hand, drinking water utilities are able to improve their water abstraction strategies and react quicker to changing hydrological conditions in the RBF system.
Aquifer microbial water quality evaluations are often performed by collecting groundwater samples from monitoring wells. While samples collected from continuously pumped sources are seldom disputed as representative of the aquifer, natural biofilm present in the vicinity of well screens may introduce unwanted microbial artefacts in monitoring wells that are only periodically sampled. The need for well water purging to obtain samples void of these artefacts has been widely recognized. However, purging methods are not standardized; many approaches presume that physico‐chemical water quality stability achieved through the removal of 3 to 5 well volumes is indicative of the stability of target analytes. Using a data set collected from a shallow unconfined aquifer in Southern Ontario, Canada, the need for using dedicated approaches that account for the time‐dependent nature of microbial water quality changes was demonstrated. Specifically, the utility of adenosine triphosphate (ATP) as a rapid, field‐ready biochemical indicator of microbial water quality stability was investigated. This work shows that ATP concentrations reflect time‐limited (bio)colloid transport processes that are consistent with other microbial water quality parameters monitored, but different from commonly measured physical and chemical water quality indicators of well purging adequacy. ATP concentrations occasionally fluctuated even after 3 or 4 h of purging, indicating that microbial artefacts attributable to biofilms in the vicinity of the well screen can still persist. The recurrence of characteristic ATP patterns in each well was systematically examined through the novel application of dynamic time warping (DTW), a nonparametric time series analysis approach. These patterns are believed to be linked with seasonal hydrogeological conditions, which warrant consideration in the design and interpretation of subsurface microbial water quality investigations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.