Factors Affecting the Transport of Pathogens & Pathogen Surrogates in Saturated Porous Media: Implications for Natural & Engineered Drinking Water Filters
Bibliographic record
Abstract
Three tiers of bench-scale experiments were conducted to evaluate the use of laboratory column \ninvestigations for studying the transport and removal of pathogenic microorganisms (i.e. disease causing \nviruses, bacteria and protozoa) and pathogen-surrogates (i.e. (bio)colloids) in saturated porous media \n(filtration). These experiments were used to explore the effects of individual and concurrent factors on the \ntransport and removal of a suite of (bio)colloids at a range of environmentally relevant conditions typical \nof natural riverbank filtration and engineered drinking water filters. Several bench-scale column designs \nwere investigated to elucidate laboratory-scale column size factors that may affect reproducibility of \n(bio)colloid passage through granular media filtration. The physical and chemical factors investigated for \ntheir individual and concurrent effects on the transport of a suite of (bio)colloids included: media grain \nsize, media uniformity coefficient, ionic strength, and the presence of natural organic matter. The suite of \npathogens and (bio)colloids utilized in this study included PR772 bacteriophage, Escherichia coli RS2g \nbacteria, Salmonella typhimurium bacterial pathogen, and two sizes of fluorescent polycarbonate \nmicrospheres (1.1 μm and 4.5 μm). In addition to S. typhimurium, pathogenic bacterial strains of E. coli \nand Pseudomonas aeruginosa were isolated and used in an experiment to investigate the effects of \nbacterial exposure to different environmental water matrices (impacted by various land-uses) on the \ntransport of pathogenic bacteria. Additionally, the effects of bacterial exposure to the different water \nmatrices on cell size and surface EPS composition of the suite of bacterial pathogens were investigated. \nPathogen and (bio)colloid removal was assessed for the three experiments by plotting breakthrough \ncurves and/or removal value from each trial, followed by ANOVA to determine the statistical \nsignificance of the effect of each parameter studied on (bio)colloid removal. The outcomes of this work \nhave several implications for the use of bench-scale column studies in (bio)colloid transport \ninvestigations to improve the understanding of natural and engineered filter performance. \nLaboratory bench-scale experiments using replicate glass columns proved to be a useful tool in \ninvestigating factors that affect (bio)colloid transport in saturated porous media. In contrasts to common \nrecommendations for experimental design (e.g., column diameter (D) to collector diameter (d) ratio > 50), \ncolumn and collector media designs with D/d between 15 and 116 did not have a significant effect on the \nreproducibility and removal of a suite of (bio)colloids in transport investigations using varying ionic \nstrengths and flow velocities representative of natural subsurface environments. Accordingly, small scale \ncolumn studies of (bio)colloid removal by filtration that are conducted at D/d < 50 should not be \nuniversally disregarded because of wall effects concerns. \niv \nObservations of (bio)colloid removal by granular media filtration were generally consistent with colloid \nfiltration theory. Grain size, ionic strength and the presence of natural organic matter significantly \naffected the removal of a suite of (bio)colloids at values representative of natural field conditions. \nInteraction effects were also identified between the chemical factors of ionic strength and natural organic \nmatter, as well as between physical media characteristics of grain size and uniformity coefficient. These \nresults suggest that synergistic effects within physical and chemical factors known to effect pathogen \ntransport in saturated porous media should be considered when assessing pilot- and full-scale filter \nperformance demonstrations. \nDifferences in removal between the suite of bacterial pathogens investigated at conditions representative \nof subsurface filtration were small (<0.5 log), suggesting that nuances between the removal of various \nstrains of bacteria that are present at the micro-scale may not be substantial at the macro- or field-scale. \nThe effects of bacterial EPS on (bio)colloid transport may be more important in environments with \nprofuse biofilm formation (unlike the “clean-bed” environments used in this study). Established and \nstandardised methods for EPS extraction and characterization for a range of applications are necessary to \nimprove our understanding of bacterial EPS production, and the effects of these compounds in a range of \nsaturated porous media environments. A conceptual model was developed to encompass the current state \nof knowledge on bacterial EPS effects on bacterial removal and the results presented herein.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".