A mathematical model for removal of human pathogenic viruses and bacteria by slow sand filtration under variable operational conditions

Schijven, Jack; Berg, Harold van den; Colin, Michel; Dullemont, Yolanda; Hijnen, W.A.M.; Magic-Knezev, Aleksandra; Oorthuizen, Wim A.; Wubbels, G. H.

doi:10.1016/j.watres.2013.02.027

Cited by 37 publications

(35 citation statements)

References 30 publications

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“…Although heavy metal and nutrient removal efficiencies are low [12], Schijven [13] reported that suspended solids (SS), turbidity, biochemical oxygen demand (BOI), and fecal coliforms are effectively removed by slow sand filtration.…”

Section: Introductionmentioning

confidence: 99%

Experimental Study of Factors that Affect Iron and Manganese Removal in Slow Sand Filters and Identification of Responsible Microbial Species

Demır¹

2016

Pol. J. Environ. Stud.

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This paper presents the results of DNA-based molecular analyses of the microbial community responsible for biological iron (Fe) and manganese (Mn) removal in slow sand filters (SSF). A lab-scale SSF was operated in 55-day sets under different operating conditions in order to evaluate long-term performance of the filter. The concentrations of Fe and Mn in synthetic feed water were increased from 1 mg/L to 2 mg/L at two different filtration rates (0.1 and 0.3 m/h). Daily samples were taken from influent and effluent for turbidity and Fe-Mn concentration measurements. 90-95% removal efficiencies were achieved with very low effluent concentrations. PCR-DGGE analyses were performed on samples, and Gallionella, Leptothrix, Crenothrix, and Hyphomicrobium were identified as the main microbial strains responsible for iron and manganese oxidation in SSF. Results also revealed that microbial activity was the main mechanism for Fe and Mn removal in the early stages of operation.

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Section: Introductionmentioning

confidence: 99%

Experimental Study of Factors that Affect Iron and Manganese Removal in Slow Sand Filters and Identification of Responsible Microbial Species

Demır¹

2016

Pol. J. Environ. Stud.

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“…In brief, the Slow Sand Filtration Process Model by Schijven et al (2013) is cited here: 1 0, , , , , 0 0…”

Section: Methodsmentioning

confidence: 99%

“…Based on the results of thirteen such pilot plant experiments that were conducted under various operational conditions, Schijven et al (2013) developed a Slow Sand Filtration Process Model that can be used to predict removal of bacteriophage MS2 and of E. coli by slow sand filtration as a function of temperature, grain size, filtration rate and the age of the Schmutzdecke. The latter is a biologically active slime layer that gradually develops on top of a sand filter.…”

Section: Chapter 18mentioning

confidence: 99%

Progress in Slow Sand and Alternative Biofiltration Processes

Nakamoto¹,

Graham²,

Collins³

et al. 2014

wio

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“…This takes place in the Schmutzdecke (dirt layer) that develops in the top soil as a result of successive deposition of organic waste, plankton and microbes, such as protozoa, bacteria, rotifers, bacteriaphages, and fungi; particularly, the bacterivores protozoa ciliate have large effect on decay (Ellis and Wood, 1985;Puigagut et al, 2007;Stott et al, 2003). The Schmutzdecke can improve in attenuation capacity with time (Schijven et al, 2013), and the effect of predation increases with higher temperatures (Ellis and Wood, 1985). Moreover, in subsurface-flow constructed wetlands the removal of E. coli can be enhanced in the presence of vegetation, since plants compete with bacteria for nutrients, and some plants produce secondary metabolites with antibacterial properties (García et al, 2010).…”

Section: Inactivation Increases With Predation Temperature Uv Lightmentioning

confidence: 99%

Water Transport, Retention, and Survival ofEscherichia coliin Unsaturated Porous Media: A Comprehensive Review of Processes, Models, and Factors

Engström

Thunvik

Kulabako

et al. 2014

Critical Reviews in Environmental Science and Technology

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The vadose zone can function as both a filter and a passage for bacteria. This review evaluates when and why either effect will apply based on available literature. It summarizes theories and experimental research that address the related, underlying bacterial attenuation processes, the applied macro-scale modeling approaches, and the influencing factors -including the cell, soil, solution and system characteristics. Results point to that the relative importance of each removal mechanism depends on the moisture content and the solution ionic strength. The limitations of available modeling approaches are discussed. It remains unclear in which contexts these are reliable for predictions. The temporal first-order kinetic Escherichia coli ( E. coli) removal coefficient ranges three orders of magnitude, from 10 −4 to 10 −1 /min. Results suggest that this rate depends on the pore-water velocity. Spatial filtration of E. coli increases with slower flow and higher collector surface heterogeneity. It could be insignificant in the case of heavy and sudden infiltration and subsequent transport in preferential flow paths, induced, for example, by plant roots or cracks in clayey soils. Future research 2 E. Engström et al. thus needs to address transport as an effect of extreme weather events such as droughts and subsequent floods.

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A mathematical model for removal of human pathogenic viruses and bacteria by slow sand filtration under variable operational conditions

Cited by 37 publications

References 30 publications

Experimental Study of Factors that Affect Iron and Manganese Removal in Slow Sand Filters and Identification of Responsible Microbial Species

Experimental Study of Factors that Affect Iron and Manganese Removal in Slow Sand Filters and Identification of Responsible Microbial Species

Progress in Slow Sand and Alternative Biofiltration Processes

Water Transport, Retention, and Survival ofEscherichia coliin Unsaturated Porous Media: A Comprehensive Review of Processes, Models, and Factors

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