12 research outputs found
Internalized protozoan (oo)cysts in granular filtration: a quantitative risk analysis in drinking water
Predation and transport of persistent pathogens in GAC and slow sand filters: A threat to drinking water safety?
Do internalized pathogens inside higher organisms pose a significant microbial risk in drinking water?
Predation and transport of persistent pathogens in GAC and slow sand filters : a threat to drinking water safety?
Role of predation in transport of fecal bacteria and protozoan (oo)cysts in water treatment
Preliminary study on the occurrence and risk arising from bacteria internalized in zooplankton in drinking water
A mathematical model for removal of human pathogenic viruses and bacteria by slow sand filtration under variable operational conditions
Slow sand filtration (SSF) in drinking water production removes pathogenic microorganisms,
but detection limits and variable operational conditions complicate assessment of removal
efficiency. Therefore, amodel was developed to predict removal ofhuman pathogenic viruses
and bacteria as a function of the operational conditions. Pilot plant experiments were conducted,
in which bacteriophage MS2 and Escherichia coli WR1 were seeded as model microorganisms
for pathogenic viruses and bacteria onto the filters under various temperatures,
flowrates, grain sizes and ages of the Schmutzdecke.Removal of MS2 was 0.082e3.3 log10 and
that of E. coli WR1 0.94e4.5 log10 by attachment to the sand grains and additionally by processes
in theSchmutzdecke. Thecontribution of theSchmutzdecke to the removal ofMS2and
E. coliWR1increased with its ageing, with sticking efficiency and temperature, decreased with
grain size, and was modelled as a logistic growth function with scale factor f0 and rate coefficient
f1. Sticking efficiencies were found to be microorganism and filter specific, but the
values of f0 and f1 were independent of microorganism and filter. Cross-validation showed
that the model can be used to predict log removal of MS2 and ECWR1 within 0.6 log. Within
the range of operational conditions, themodel shows that removal of microorganismsis most
sensitive to changes in temperature and age of the Schmutzdecke
A mathematical model for removal of human pathogenic viruses and bacteria by slow sand filtration under variable operational conditions
Slow sand filtration (SSF) in drinking water production removes pathogenic microorganisms,
but detection limits and variable operational conditions complicate assessment of removal
efficiency. Therefore, amodel was developed to predict removal ofhuman pathogenic viruses
and bacteria as a function of the operational conditions. Pilot plant experiments were conducted,
in which bacteriophage MS2 and Escherichia coli WR1 were seeded as model microorganisms
for pathogenic viruses and bacteria onto the filters under various temperatures,
flowrates, grain sizes and ages of the Schmutzdecke.Removal of MS2 was 0.082e3.3 log10 and
that of E. coli WR1 0.94e4.5 log10 by attachment to the sand grains and additionally by processes
in theSchmutzdecke. Thecontribution of theSchmutzdecke to the removal ofMS2and
E. coliWR1increased with its ageing, with sticking efficiency and temperature, decreased with
grain size, and was modelled as a logistic growth function with scale factor f0 and rate coefficient
f1. Sticking efficiencies were found to be microorganism and filter specific, but the
values of f0 and f1 were independent of microorganism and filter. Cross-validation showed
that the model can be used to predict log removal of MS2 and ECWR1 within 0.6 log. Within
the range of operational conditions, themodel shows that removal of microorganismsis most
sensitive to changes in temperature and age of the Schmutzdecke