Importance of reversible attachment in predicting E. coli transport in saturated aquifers from column experiments

Abstract

Drinking water wells indiscriminatingly placed adjacent to fecal contaminated surface water represents a significant but difficult to quantify health risk. Here we seek to understand mechanisms that limit the contamination extent by scaling up bacterial transport results from the laboratory to the field in a well constrained setting. Three pulses of E. coli originating during the early monsoon from a freshly excavated pond receiving latrine effluent in Bangladesh were monitored in 6 wells and modeled with a two-dimensional (2-D) flow and transport model conditioned with measured hydraulic heads. The modeling was performed assuming three different modes of interaction of E. coli with aquifer sands: 1) irreversible attachment only (best-fit ki=7.6 day-1); 2) reversible attachment only (ka=10.5 and kd=0.2 day-1); and 3) a combination of reversible and irreversible modes of attachment (ka=60, kd=7.6, ki=5.2 day-1). Only the third approach adequately reproduced the observed temporal and spatial distribution of E. coli, including a 4-log10 lateral removal distance of ∼9 m. In saturated column experiments, carried out using aquifer sand from the field site, a combination of reversible and irreversible attachment was also required to reproduce the observed breakthrough curves and E. coli retention profiles within the laboratory columns. Applying the laboratory-measured kinetic parameters to the 2-D calibrated flow model of the field site underestimates the observed 4-log10 lateral removal distance by less than a factor of two. This is promising for predicting field scale transport from laboratory experiments.

Mimicking filtration and transport of rotavirus and adenovirus in sand media using DNA-labeled, protein-coated silica nanoparticles

“…Understanding of the attachment-detachment kinetics has important implication in risk assessment. Detachment is considered a major reason for the widespread microbial contamination of some shallow groundwater and allows microbial contaminants to move much further into an aquifer (Feighery et al, 2013;Knappett et al, 2014). A constantly slow release of viruses from previously attached in the porous media will lengthen the contamination duration, and a sudden release of microbial contaminants due to a change of hydraulic conditions (e.g.…”

“…It is well documented that attenuation and transport of particles in porous media is controlled by attachment-detachment kinetics, and attachment can be reversible and irreversible (Murphy and Ginn, 2000). Assuming there are two kinetic attachment sites (one reversible and other irreversible) with equal-sized populations (Knappett et al, 2014), particle data were simulated using a two-site attachment-detachment kinetic model (Schijven et al, 2002):…”

Effect of Low Energy Waves on the Accumulation and Transport of Fecal Indicator Bacteria in Sand and Pore Water at Freshwater Beaches

“…The first-order die-off rate coefficient μ dec for FIB was estimated based on an average value determined from microcosm experiments conducted using foreshore sand from Burlington Beach . Given die-off rates for both FIB in water and sediment often have similar ranges [ O (0.01–1) L/d], − the same μ dec was assumed for FIB in the aqueous phase and those attached to sand. The FIB concentration in the terrestrial groundwater ( Q t ) was zero based on negligible FIB detected in the landward groundwater at each site (Figure S2).…”

Making Steppingstones out of Stumbling Blocks: A Bayesian Model Evidence Estimator with Application to Groundwater Transport Model Selection

“…Breakthrough curves are curves of concentrations measured at an observation point downstream from a source plotted against time. Least square regression methods are generally used for fitting breakthrough curves of column experiments and tracer tests with subsurface transport models [84][85][86][87][88][89][90][91][92][93][94][95][96]. Subsequently, model weight calculation and ranking of multiple candidate models are carried out using an approximate semi-analytical solution [85,87], which indirectly accounts for model complexity as previously discussed.…”