emerging waterborne pathogensweb.iitd.ernet.in/~arunku/files/cel795_y13/removal...also used on two...

102 MAY 2004 | JOURNAL AWWA • 96:5 | PEER-REVIEWED | XAGORARAKI ET AL

Removal of emergingwaterborne pathogens

and pathogen indicatorsBY PILOT-SCALE CONVENTIONAL TREATMENT

The goal of this project was to evaluate the removal of emerging pathogens and pathogen

indicators by pilot-scale coagulation, flocculation, sedimentation, and granular media

filtration. The emerging pathogens included Cryptosporidium parvum oocysts, Encephalitozoon

intestinalis spores, Escherichia coli O157:H7, and Aeromonas hydrophila. Bacteriophage MS2

and turbidity were used as pathogen indicators. This work revealed that some emerging

pathogens were removed much more effectively than others. A. hydrophila was removed more

effectively than C. parvum, and E. intestinalis spores and E. coli O157:H7 were the least

effectively removed. For the water tested in this study, the results suggest that a change in

filter effluent turbidity requirements from 0.5 to 0.3 ntu would not achieve a significant

improvement in the reliability of pathogen removal. However, by setting filter effluent turbidity

goals below 0.2 ntu, significant improvements in microbiological quality could be obtained.

In general, the pilot-plant data suggest that good removal of both turbidity and natural

organic matter (NOM) decreases the risk of achieving poor emerging pathogen removal. In

other words, optimizing the coagulation process for reduction of turbidity and NOM would

improve removal of emerging pathogens.

BY IRENE XAGORARAKI,

GREGORY W. HARRINGTON,

PRAPAKORN ASSAVASILAVASUKUL,

AND JON H. STANDRIDGE

n the 1980s and 1990s, the waterborne pathogens Giardia and Cryp-tosporidium emerged, significantly altering drinking water policies andtreatment practices (USEPA, 1989; USEPA, 1994; USEPA, 1998). Onthe basis of this experience, it is appropriate to ask whether other organ-isms could emerge, spurring even more alterations in policy and practice.

The ease of genetic mutation of microbes, combined with changes in humanbehavior, landscape and climate alterations, developing technologies, and increasedtravel, allows new microbial pathogens to emerge (Ebel & Spielman, 1998; Roseet al, 2000). The drinking water industry can expect to see an increase in the num-ber of identified waterborne pathogens as analytical, epidemiological, and clin-ical methods continue to improve. Continued development of watersheds is also

I

xenobiotics/emerging issues

2003 © American Water Works Association

XAGORARAKI ET AL | PEER-REVIEWED | 96 :5 • JOURNAL AWWA | MAY 2004 103

likely to contribute to an increase in thenumber of identified waterbornepathogens. Because medical treatmentsare largely ineffective for the diseasescaused by some of the emergingpathogens, these diseases can becomelife threatening for immunosuppressedindividuals. As a result, public healthstrategies must emphasize preventionrather than medical treatment. The effi-ciency of the conventional treatmentbarrier approach to drinking water treat-ment will play a critical role in this pre-ventive effort.

Several researchers have studied theremoval of emerging pathogens in theconventional water treatment process(coagulation, flocculation, sedimenta-tion, and filtration). Pilot-scale treat-ment studies with two waters in thewestern United States showed that whentreatment conditions were optimized forturbidity and particle removal, conven-tional treatment could obtain 2.7–5.9log removal of Cryptosporidium oocysts(Patania et al, 1995). In a pilot-scalestudy in Utah, Cryptosporidium oocystremoval ranged from 1.9 to 4.0 logs(Nieminski & Ongerth, 1995). AnotherUtah study was designed to evaluateCryptosporidium oocyst removal in afull-scale treatment plant that was notdelivering water to customers. In thiscase, removals ranged from 1.9 to 2.8logs (Nieminski & Ongerth, 1995). Twodifferent pilot plants reported approxi-mately 3- and 5-log removal of Cryp-tosporidium oocysts under optimal operating conditions(Huck et al, 2002). In another study, Cryptosporidiumoocyst removals >5 logs were reported when coagula-tion was optimized (Dugan et al, 2001).

Conventional treatment has also achieved 3.6–5.7-logremoval of Entamoeba histolytica cysts, 1.5–3.5-logremoval of Giardia cysts, 1.7–3.0-log removal of coliformbacteria, 0.85-log removal of naturally occurring bacterialspores, and 2.0–3.2-log removal of poliovirus (Rice et al,1996; Ongerth & Pecoraro, 1995; Nieminski & Ongerth,1995; Horn et al, 1988; Rao et al, 1988; Logsdon et al,1985; Logsdon et al, 1981; Guy et al, 1977; Robeck et al,1964; Robeck et al, 1962; Spector et al, 1934). Using alumcoagulation, flocculation, and sedimentation followed byferric chloride coagulation, flocculation, sedimentation,and granular media filtration, Chang et al (1958) achieved3.0-log removal of Coxsackie virus.

The performance of the conventional process to removepathogens depends on numerous factors including source

water quality, chemical pretreatment conditions (e.g.,coagulant dose and pH), filtration rate, bed depth, and fil-ter media types. The objective of this work was to com-pare the removal of several emerging pathogens andpathogen indicators, such as turbidity and bacteriophageMS2, in pilot-scale conventional treatment.

METHODSPilot-scale experiments. Pilot-scale experiments were

performed to determine the removal of four live emergingpathogens by coagulation, flocculation, clarification, andfiltration. These experiments included protozoa (C. parvumoocysts and Encephalitozoan intestinalis spores), bacteria(E. coli and Aeromonas hydrophila), and an indicatorvirus (bacteriophage MS2).

To investigate the effects of various source water qual-ity, pretreatment, and filtration conditions on waterbornepathogen removal by conventional treatment, seven pilot-scale challenge experiments were conducted. In each

FIGURE 1 GGeenneerraall ffllooww ddiiaaggrraamm ffoorr tthhee UUnniivveerrssiittyy ooff WWiissccoonnssiinn––MMaaddiissoonnppiilloott--ssccaallee ddrriinnkkiinngg wwaatteerr ttrreeaattmmeenntt ppllaanntt

Constant-head tank

Rapidmix

Alum

Flocculation

Sedimentation

Pump

Settling tubes

Rapidmix

Pathogen cocktail

Constant-head tank

Pump

LakeMendota

Drain

Granular media filtration

Constant-head tank

Rapidmix

Rapidmix

Alum

Focculation

Sedimentation

Pump

Settling tubes

Pathogen cocktail

Drain

Granular media filtration

= Sampling locations



experiment, the raw water was spiked with a “cocktail”that contained sufficiently large concentrations of thefour pathogens and the one indicator virus to ensure pre-cise enumeration in the treated water. Using this cock-tail facilitated direct comparison of pathogen removals andavoided the need for comparing removals among watersamples of varying quality. The design of the experimentsincluded duplicate treatment trains so that the uncer-tainty associated with experimental procedures andpathogen assays could be measured.

On two occasions, the pilot plant was used to evaluatethe effect of alternative loading rates on the performanceof ripened granular-media filters. This experiment wasrun twice to determine whether results varied as a resultof seasonal water quality changes. The pilot plant wasalso used on two occasions to evaluate the effect of filterrun time on the performance of dual-media filters operatedat 4 gpm/sq ft (3 mm/s). As with the previous experiment,this test was run twice to evaluate seasonal effects. Pilot-scale tests were performed to evaluate alternative filtermedia on two separate dates. An evaluation of coagulationpH was combined with the second evaluation of alterna-tive filter media. For this experiment, alum coagulation wasperformed at ambient pH in one treatment train and at alower pH in the other treatment train. The last experi-ment was designed to evaluate the influence of a rawwater turbidity spike on treatment performance. A detaileddescription of the results from each experiment can befound elsewhere (Harrington et al, 2003; Harrington et al,2001). This article gives an overview of results obtainedfrom all seven experiments. Data from all experimentswere grouped together and analyzed to indicate generaltrends in pathogen removal during conventional treat-

ment. Pathogen removal data represent overall removalthrough sedimentation and filtration.

Pilot plant setup and operation. The continuous-flowpilot-scale experiments were run at the University ofWisconsin’s pilot-scale treatment facility. The pilot plantreceived raw water from Lake Mendota in Madison,Wis., and included two parallel treatment trains (Fig-ure 1), each being operated at 1 gpm (0.06 L/s). Rawwater was pumped to a constant-head reservoir andflowed by gravity through two rapid-mix tanks, threeflocculation chambers, and one sedimentation basin oneach train. Each rapid-mix tank was operated with a 1-min nominal detention time and an estimated velocitygradient of 750 s–1. Pathogen cocktail was fed to thefirst rapid-mix chamber and alum was fed to the secondrapid-mix chamber. Each flocculation chamber was oper-ated with a nominal detention time of 10 min for a totalflocculation time of 30 min. Estimated velocity gradientswere 70 s–1, 40 s–1, and 10 s–1 for the first, second, andthird flocculation chambers, respectively. Water was dis-tributed to each flocculation chamber and to the sedi-mentation basin through a perforated wall. The sedi-mentation basin, which included a tube settler module,had a nominal detention time of approximately 2 h.The overflow rate of the sedimentation basin was esti-mated to be 70 gpd/sq ft (0.03 mm/s). For each treatmenttrain, settled water was pumped to a constant-head tankand then flowed by gravity to a rack of four granular-media filter columns. Each filter column was constructedof clear polyvinylchloride with a diameter of 3 in. (8cm) and a height of 10 ft (3 m). A constant filtration ratewas maintained by pumping the filter effluent at thedesired flow rate.

Pathogen Average Concentration

Cryptosporidium parvum 1 × 105 oocysts/L

Encephalitozoan intestinalis 2 × 105 spores/L

Aeromonas hydrophila 2 × 107 cfu/L

Escherichia coli 6 × 107 cfu/L

Bacteriophage MS2 5 × 107 pfu/L

TABLE 1 AAvveerraaggee ppaatthhooggeenn ccoonncceennttrraattiioonnss iinn ffiirrssttrraappiidd--mmiixx ttaannkk

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Aerom

onas

hyd

rophila MS2

Crypto

sporid

ium

par

vum

Encephali

tozo

an

inte

stin

alis

Escher

ichia

coli 0

157:

H7

Mea

n L

og

Rem

ova

lError bars show the standard deviation of replicate treatment basins.

FIGURE 2 MMeeaann lloogg rreemmoovvaall ooff wwaatteerrbboorrnnee mmiiccrroobbeessiinn aallll 4466 ppiilloott--ssccaallee ffiilltteerr eefffflluueenntt ssaammpplleess



One day before a pathogen challenge run, the rapid-mix tanks, flocculation chambers, and sedimentationbasins were drained, and solids were flushed to the san-itary sewer. The alum dose for each pilot-scale test wasdetermined by a series of jar test experiments performedapproximately 12 h before the pilot-scale experiment.The selected alum dose was based on optimal turbidityremoval in sedimentation. After cleaning, the pilot-scalesystem was brought back online without pathogen feedand allowed to run overnight with the selected alum dose.

On the day of the experiment, feeding of the pathogencocktail was initiated at the desired time. The cocktailwas composed of approximately 10 to 15 parts LakeMendota water and 1 part stock pathogen suspension. Forthe entire set of pilot-scale experiments, Table 1 gives theaverage pathogen concentrations in the first rapid-mixtank. Figure 1 shows the sampling locations.

The cocktail was continuously fed to each pilot trainat a flow rate of 5 mL/min from a 20-L (5-gal) high-den-sity polyethylene container. The container was placed ina cooler with ice packs to help maintain the stability of thepathogen cocktail. A mixing system maintained a uni-form suspension of pathogens within the container. Thisallowed for a uniform feed concentration of pathogensthroughout the length of the experiment.

On the basis of tracer study results, the filter effluentwas presumed to be at steady state 5 h after pathogenfeed was initiated (Harrington et al, 2001). At the end ofthe 5-h period, all filters were backwashed and simulta-neously placed back online after backwashing was com-plete. Filter effluent turbidities were monitored every 5 minfor 3 h after the filters were placed back online. Filteredwater and settled water samples were collected forpathogen analysis after this 3-h period. These samplinglocations are also shown in Figure 1.

Turbidity. Turbidity was measured with a turbidime-ter1 in accordance with method 2130 B (Standard Meth-ods, 1996). The turbidimeter was calibrated monthlythroughout the project with primary standard formazin

suspensions (hydrazine sulfate and hexamethylenetetramine2) and before every experiment with secondarystandards.3

UV254 absorbance. Ultraviolet (UV) absorbance wasmeasured at 254 mm wavelength with a spectropho-tometer,4 in accordance with method 5910 B (StandardMethods, 1996).

Purification and propagation of microorganisms. C. par-vum oocysts were purchased from a supplier.5 The oocystswere recovered from infected calf feces by ether extraction(Bukhari & Smith 1995) followed by discontinuoussucrose and isopycnic percoll gradient centrifugation(Arrowood & Sterling 1987). Fresh feces from infectedcalves were suspended into cold reverse osmosis (RO)–grade water and sieved through a coarse stainless-steelscreen to remove fecal solids. Approximately 300 mL ofscreened fecal matter was then supplemented with 100 mLcold ethyl ether and shaken well in a 500-mL centrifugebottle. Samples were then centrifuged at 1,000 × g for15 min at 4oC. The fecal plug and residual ether wereaspirated and discarded, and oocysts in the pellet weretransferred to 50-cc polypropylene centrifuge tubes andwashed serially with phosphate-buffered saline (PBS) tofurther clarify the preparations. Approximately 20 mLof washed oocysts were then underlaid with 10 mL dilutedSheather’s solution and centrifuged at 500 × g for 10 min.Oocysts were collected from the interface, washed severaltimes with PBS, centrifuged at 500 × g for 10 min, sup-plemented with 1,000 U penicillin G and 1,000 mg strep-tomycin sulfate and reserved at 4oC until the day of use.On the day of each experimental trial, oocysts were cen-trifuged at 2,000 × g and resuspended in RO water towash away residual antibiotics.

E. intestinalis spores were obtained from a duodenalisolate6 and were propagated to high titer in either rab-bit kidney cells (RK-13) or dog kidney–derived cells(MDCK). Following preliminary evaluations, the RK-13cell line was adopted for large-scale spore productionbecause of the comparative efficiency of spore expres-

UV Turbidity EscherichiaCorrelated Effluent Effluent Removal Removal Cryptosporidium Encephalitozoan Aeromonas coliParameters UV Turbidity % % parvum intestinalis hydrophila 0157:H7

Effluent turbidity 0.52

UV—% removal –0.85 –0.47

Turbidity—% removal –0.51 –0.61 0.48

Cryptosporidium parvum –0.38 –0.65 0.33 0.42

Encephalitozoan intestinalis –0.23 0.19 –0.50 0.44 0.86

Aeromonas hydrophila –0.82 0.70 –0.65 0.64 0.50 0.31

Escherchia coli –0.49 0.38 –0.42 0.39 0.38 0.19 0.72

Bacteriophage MS2 –0.81 0.67 –0.53 0.75 0.55 0.51 0.76 0.52

TABLE 2 CCoorrrreellaattiioonn mmaattrriixx ffoorr ffiilltteerreedd wwaatteerr ppaatthhooggeenn rreemmoovvaallss aanndd ffiilltteerreedd wwaatteerr ttuurrbbiiddiittyy aanndd UUVV aabbssoorrbbaannccee



sion in this cell line. Mycoplasma-free cells7 were grownto confluency in 225-cm2 flasks8 and maintained inmedium9 containing 10% fetal calf serum,10 100 U/mLpenicillin G, and 100 µg/mL streptomycin sulfate. Cellswere incubated at 37oC in a humidified 5% carbon diox-ide (CO2) environment. Spores were harvested frominfected cultures weekly following the second week ofinfection. Medium from each flask was decanted and

centrifuged at 2,500 × g for 20 min in250-mL polypropylene bottles. Thesupernatant was discarded, and pel-leted spores were resuspended in asmall volume of PBS. A portion of eachresuspended pellet was added to freshmaintenance medium, which was thenreturned to each culture flask. Har-vested preparations were supplementedwith antibiotics and reserved at 4oCuntil the day of use.

E. coli 0157:H711 was obtained andpropagated through a single subcul-ture in trypticase soy broth (TSB).12

Log-phase bacterial cultures were sup-plemented with glycerol (20% vol/vol),divided into 1.0-mL aliquots and pre-served at –80oC. Approximately 14 hbefore each experiment, aliquots werethawed and introduced into a series ofshaker flasks containing 40–1,500 mLof TSB. Flasks were mounted onto ashaker platform and incubated at35oC. Following overnight incubation,bacterial cultures were transferred into250-mL polypropylene centrifuge bot-tles and centrifuged at 2,500 × g for20 min. Following centrifugation, thesupernatant was discarded and sedi-mented bacteria were washed by re-suspending the pellets in RO waterand centrifuging a second time. Pel-lets were resuspended in a small vol-ume of RO water.

Isolates of A. hydrophila were ob-tained from natural waters that hadbeen screened for coliform and E. colibacteria and propagated to log-phaselevels through a single subculture inTSB. Aliquots from the mother culturewere supplemented with glycerol andcryopreserved; this was also done for E.coli 0157:H7.

Bacteriophage MS213 was propa-gated by the double agar layer (DAL)technique (Adams 1959). Bacterio-phages were inoculated into borosili-cate glass tubes containing 5 mL

0.75% nutrient agar medium and 80 µL log-phase E.coli C3000.14 Mixed samples were then poured over 100mm (3.94 in.) bottom agar plates containing 15 mL of2.3% nutrient agar medium15 supplemented with 0.5%sodium chloride, and plates were incubated overnight at37oC. The uppermost soft agar layer was recovered fromplates exhibiting confluent bacterial lysis and resuspendedin 5 mL of PBS per plate. To separate the crude viruses

FIGURE 3 CCrryyppttoossppoorriiddiiuumm ppaarrvvuumm ooooccyysstt rreemmoovvaall iinn ddiiffffeerreenntt ffiilltteerr eefffflluueennttttuurrbbiiddiittyy rraannggeess

MaximumMinimum

25–75% Median

Filter Effluent Turbidity Range—ntu

Lo

g R

emo

val

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

n = 5

n = 5n = 4

n = 7

n = 17

n = 8

< 0.2 0.2–0.3 0.3–0.4 0.4–0.6 0.6–0.7 > 0.7

FIGURE 4 AAeerroommoonnaass hhyyddrroopphhiillaa rreemmoovvaall iinn ddiiffffeerreenntt ffiilltteerr eefffflluueennttttuurrbbiiddiittyy rraannggeess

MaximumMinimum

25–75% Median


Lo

g R

emo

val

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

n = 5n = 5

n = 4n = 7

n = 17n = 8

< 0.2 0.2–0.3 0.3–0.4 0.4–0.6 0.6–0.7 > 0.7



from the cell lysate, pooled sampleswere supplemented with equal volumesof chloroform, homogenized for 60 s,and centrifuged at 5,000×g for 15 min.The virus-containing supernatant wasdecanted and reserved at 4oC.

Enumeration of microorganisms. C.parvum oocysts and E. intestinalis sporeswere enumerated by flow cytometry andin some cases by epifluorescencemicroscopy. Aliquots (50 mL) from eachsample volume were introduced intopolypropylene centrifuge tubes16 andcentrifuged at 2,500 × g for 20 min. Thesupernatant was aspirated and pelletswere resuspended in 300–500-µL vol-umes. One hundred microlitres of eachsample was withdrawn and introducedinto 12 × 100 mm polypropylene tubes,and was supplemented with normal goatserum17 and blocked overnight at 4oC.Samples were then stained with eithermonoclonal antibody against C. par-vum18 or polyclonal antibody against E.intestinalis19 that had been previouslyconjugated with fluorescein isothio-cyanate (FITC).

After being stained, samples were seeded with either1,000 or 5,000 beads20 and subjected to flow cytom-etry assay21 using an air-cooled helium–neon excita-tion laser. Oocysts and spores were identified and enu-merated as a function of their forward-light-scatterand side-scatter properties in combination with thefluorescent characteristics specific for each lot of mi-croorganisms. The concentration of each microorgan-ism was expressed per microlitre of sample based on thenumber of seeded fluorescent calibration beads thatwere recovered. Absolute sample concentrations werethen corrected to reflect the original sample volumeand expressed as oocysts per microlitre or spores permicrolitre.

For those samples in which the distinction betweenoocyst or spore signal and background noise was unclear,slides were prepared and samples were examined manu-ally under epifluorescence optics at 400× magnification inan fluorescence microscope.22

Bacterial reductions were quantified according to thespread-plate technique with selective agar specific foreach microorganism. For E. coli and A. hydrophila, 100mm plastic petri dishes were prepared with two types ofagar.23 Aliquots (100 mL) of serial tenfold dilutions wereintroduced onto the agar surface and spread uniformlywith sterile stainless-steel rods. Plates were incubated for18 to 24 h at 35oC. Transparent/light pink colonies againsta red agar background were scored as E. coli. ForAeromonas, bright yellow colonies against the blue agar

background were counted. Plates were prepared in trip-licate for each dilution.

Bacteriophage MS2 concentrations were determinedusing the DAL infectivity method (Adams 1959) in 100mm (3.94 in.) plastic petri dishes, as was done during pro-duction of bacterial virus stocks. Top agar tubes were sup-plemented with 100 µL of each sample dilution and 100 µLof log-phase E. coli C300013 host cells. Tubes were mixedthoroughly and poured over nutrient bottom agar plates.After the top agar medium hardened, plates were incubatedat 37oC overnight and plaques were counted. Sample dilu-tions were plated in triplicate with virus concentrationsexpressed as mean plaque-forming units per microlitre.

Tukey’s test. Tukey’s test was used to compare the meanremovals of all pathogens with one another. This test usesa pooled variance as one criterion for determining whethertwo means are significantly different from each other.Tukey’s test is considered to be a conservative indicatorof differences in mean values (Wynne, 1982).

Box plots. The log removal data were analyzed graph-ically using box plots, which show the minimum, maxi-mum, median, 25th percentile, and 75th percentileremoval for each emerging pathogen. The box plots werecreated with statistical software.24

RESULTS AND DISCUSSIONOverall results. In all, 46 filtered water samples were col-

lected for pathogen analysis during these pilot-scale exper-iments. The samples were collected under a range of treat-

FIGURE 5 BBaacctteerriioopphhaaggee MMSS22 rreemmoovvaall iinn ddiiffffeerreenntt ffiilltteerr eefffflluueenntt ttuurrbbiiddiittyyrraannggeess

MaximumMinimum

25–75% Median


Lo

g R

emo

val

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

n = 5n = 5

n = 4n = 7n = 17

n = 8

< 0.2 0.2–0.3 0.3–0.4 0.4–0.6 0.6–0.7 > 0.7



ment conditions, and some samples did not necessarilyreflect optimal treatment performance. Figure 2 showsthe mean log removal of all test pathogens in these 46samples. Error bars in this figure illustrate the standarddeviations that were calculated from duplicate experi-ments. The figure shows that A. hydrophila was thepathogen with the best removal and E. coli was thepathogen with the worst removal.

Tukey’s test was run at a 95% con-fidence level to determine which meanswere significantly different from theothers. This test demonstrated that A.hydrophila was the most readily re-moved microorganism with a mean logremoval of 2.5. E. coli was the mostpoorly removed waterborne pathogenwith a mean log removal of 0.7. Themean log removal of E. intestinalisspores (1.2 logs) was significantly bet-ter than the mean log removal of E.coli but significantly poorer than themean log removal of A. hydrophila (2.5logs) and bacteriophage MS2 (1.8 logs).However, no statistically significant dif-ference was found between the meanlog removal of E. intestinalis sporesand the mean log removal of C.parvum oocysts (1.6 logs). Tukey’s testshowed no significant differencesbetween the mean log removals of C.parvum oocysts and bacteriophageMS2. The results show that E. coli andE. intestinalis spores were significantlymore difficult to remove than C.parvum oocysts (the microbe currentlyreceiving the most research and regu-latory attention).

There are no clear explanations forthe observed ranking of removals forthe different pathogens. In general, theremoval of particles from drinkingwater is driven by the size, shape, andsurface charge of the particles. Thepathogens used in this study have arange of sizes, differing approximatelythree orders of magnitude from virusesto protozoa (Harrington et al, 2001).Hydrodynamic theory suggests that 1-µm particles are the most difficult toremove in granular media filtration.This might explain the poor removal ofE. intestinalis spores and E. coliO157:H7, both of which have thesame approximate size of 1 µm. How-ever, even though A. hydrophila is sim-ilar in size, it was the most readily

removed pathogen. Furthermore, pathogens passingthrough granular media filters may be associated withalum floc particles, and the size of these floc particleswould be the important factor in determining removal.

Surface charge characteristics have been studied foronly a few waterborne pathogens. Most are considered tohave negative charge at pH values typically encounteredin drinking water treatment (Lytle et al, 1999). The high

FIGURE 6 CCrryyppttoossppoorriiddiiuumm ppaarrvvuumm ooooccyysstt rreemmoovvaall ffoorr ddiiffffeerreenntt ffiilltteerreefffflluueenntt ttuurrbbiiddiittyy lliimmiittss

Turbidity Limit—ntu

Lo

g R

emo

val

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

n = 46n = 41n = 35n = 32n = 25

n = 8

MaximumMinimum

25–75% Median

< 0.2 0.3 0.4 0.5 0.7 All data

FIGURE 7 AAeerroommoonnaass hhyyddrroopphhiillaa rreemmoovvaall ffoorr ddiiffffeerreenntt ffiilltteerr eefffflluueennttttuurrbbiiddiittyy lliimmiittss


Lo

g R

emo

val

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

<0.2 <0.3 <0.4 <0.5 <0.7 All data

n = 46n = 41n = 35n = 32n = 25

n = 8

MaximumMinimum

25–75% Median



level of A. hydrophila removal may berelated to its relatively high pH of zerocharge. Isoelectric focusing results forA. hydrophila suggest that these bac-terial cells had a near-neutral surfacecharge before coagulant addition (Har-rington et al, 2001). However, elec-trophoretic mobility measurementsshowed that the C. parvum oocysts alsohad a near-neutral surface charge beforecoagulant addition (Harrington et al,2001). Therefore the observed order ofpathogen removals cannot be explainedat this time. As with particle size, thepathogens may be associated with flocparticles having significantly differentsurface charge characteristics.

In this study, the removal of C. par-vum oocysts ranged from 0.3 to 2.6logs with a mean of 1.6 logs. Theseremovals were less than those observedin previous studies at other locations(see the introduction to this article).The reason for the differences betweenthis study and the others is unknown,but differences in oocyst properties, oocyst concentra-tions, water sources, and treatment plant design couldbe responsible. For example, this study used live oocystsrather than formalin-inactivated oocysts, and investigatorshave shown that formalin inactivation can produce sig-nificant differences in oocyst properties (Brush et al, 1998;Xagoraraki, 2001).

Correlations between pathogen removals. Correlationanalyses were performed to determine if the removal ofone pathogen was a good indicator of the removal ofanother pathogen or surrogate. Table 2 gives the results.One of the strongest correlation coefficients (R = 0.86)was for the relationship between the removal of C.parvum oocysts and the removal of E. intestinalis spores.For all other pathogens, the analyses showed poor cor-relations between removals of the different pathogens.

Turbidity as an indicator for pathogen removal. Similarresults were obtained for percent turbidity removal andfilter effluent turbidity. The results did not show anystrong correlation between these parameters and theremoval of pathogens. The results agree with Nieminski& Ongerth (1995), who found a poor correlation (R2 =0.55) between oocyst removal and turbidity removal.Also, Plummer et al (1995) did not find a strong corre-lation between the log removal of oocysts and the percentreduction of turbidity by dissolved air flotation. Theauthors reported that only about 50% of the variation inoocyst removal could be explained by these parameters.

Analyses using box plots were performed as an alter-native way of evaluating whether there was any rela-tionship between filter effluent turbidity and pathogen

removals. The box plots present the minimum, 25th per-centile, median, 75th percentile, and maximum removalsfor each pathogen at a specific filter effluent turbidityrange. Figures 3–5 show representative box plots for aprotozoan (C. parvum), a bacterium (A. hydrophila), anda virus (bacteriophage MS2).

Figure 3 shows that the median Cryptosporidium oocystremoval was best when filter effluent turbidities were <0.2ntu and worst when filter effluent turbidities were >0.7 ntu.When filter effluent turbidities were in the 0.2–0.3, 0.3–0.4,0.4–0.6, and 0.6–0.7 ntu ranges, the range of removals var-ied widely from the maximum removal to the minimumremoval. Under the conditions in which filter effluent tur-bidities were less than 0.2 ntu, the median removal wasmaximized and the range of removals was minimized.Figures 4 and 5 show that the median A. hydrophila andbacteriophage MS2 removals were maximized under theconditions wherein filter effluent turbidities were less than0.2 ntu. The same trends were observed for all pathogens,revealing that the best and most reliable pathogen removalswere observed when filter effluent turbidities were lessthan 0.2 ntu.

Figures 6–8 show the same data from a regulatoryperspective. These figures depict the removals that wouldbe observed if the treatment system used in this studywas required to meet alternative filter effluent turbidityrequirements. For example, when the treatment plantwas meeting a filter effluent turbidity standard of 0.5ntu, oocyst removals varied from 1.2 to 2.6 logs (Figure6). However, when the treatment plant was meeting afilter effluent turbidity standard of 0.2 ntu, oocyst

FIGURE 8 BBaacctteerriioopphhaaggee MMSS22 rreemmoovvaall ffoorr ddiiffffeerreenntt ffiilltteerr eefffflluueenntt ttuurrbbiiddiittyylliimmiittss


Lo

g R

emo

val

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0n = 8

<0.2 <0.3 <0.4 <0.5 <0.7 All data

n = 46n = 41n = 35n = 32n = 25

MaximumMinimum

25–75% Median



removals varied from 1.8 to 2.3 logs. Figure 6 shows thata decreasing filter effluent turbidity standard produced nochange in the median and the maximum values of Cryp-tosporidium oocyst removal in this study. However, thefigure also illustrates that more stringent turbidity stan-dards produced an increase in the minimum log removals,

maximizing the reliability of the pilotplant to remove Cryptosporidium atall times.

Figure 6 shows that for those sam-ples having a filter effluent turbidity<0.2 ntu, the removal of C. parvumoocysts was at least 1.8 logs. In otherwords, when the pilot plant achieveda filtered water turbidity of <0.2 ntu,the minimum C. parvum oocyst re-moval was 1.8 logs. The minimum C.parvum oocyst removal of all sampleswas 0.3 log. Similar results were ob-tained for the other pathogens, withFigures 7 and 8 showing representa-tive results for A. hydrophila and bac-teriophage MS2, respectively. Whenthe pilot plant achieved filter effluentturbidities <0.2 ntu, the removals ofE. intestinalis, A. hydrophila, E. coli,and bacteriophage MS2 were at least1.3 logs, 3.2 logs, 0.9 log, and 2.5logs, respectively.

The relationship between filtereffluent turbidities and pathogen re-movals is also illustrated in Figures9–11. These figures show the 10thpercentile removal versus filter efflu-ent turbidity standards for all the pro-tozoans, bacteria, and viruses thatwere evaluated in this study. Pataniaet al (1995) published a similar typeof analysis. The 10th percentile datawere selected to show pathogenremovals that were achieved 90% ofthe time for a given turbidity stan-dard. This provides a measure of reli-ability in treatment plant perfor-mance. The figures show that the10th percentile removal for allpathogens increased once filter efflu-ent turbidities reached a level of 0.2ntu, improving the reliability of theprocess to remove pathogens. In allcases, the best reliability for pathogenremoval was observed when the pilotplant achieved filter effluent turbidi-ties <0.2 ntu.

The results given in Figures 6–8clearly show that the reliability of

pathogen removal increased with more stringent turbid-ity standards. The US Environmental Protection Agencyrecently implemented a change in the filter effluent tur-bidity standard from 0.5 to 0.3 ntu (USEPA, 1998). Theresults from this study show that this change would notsignificantly improve pathogen control for this pilot-scale

FIGURE 9 EEffffeecctt ooff ttuurrbbiiddiittyy ssttaannddaarrdd oonn 1100tthh ppeerrcceennttiillee rreemmoovvaallssooff pprroottoozzooaann ppaatthhooggeennss

0.0

0.5

1.0

1.5

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0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6

Filtered Water Turbidity Limit—ntu

10th

Per

cen

tile

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Cryptosporidium parvum

Encephalitozoan intestinalis

FIGURE 10 EEffffeecctt ooff ttuurrbbiiddiittyy ssttaannddaarrdd oonn 1100tthh ppeerrcceennttiillee rreemmoovvaallssooff bbaacctteerriiaall ppaatthhooggeennss

0.0

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Aeromonas hydrophila

Escherichia coli 0157:H7

FIGURE 11 EEffffeecctt ooff ttuurrbbiiddiittyy ssttaannddaarrdd oonn 1100tthh ppeerrcceennttiillee rreemmoovvaallssooff vviirraall ppaatthhooggeennss

0.0

0.5

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1.5

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0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6


10th

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treatment system. On the other hand, achange in the filter effluent turbidityrequirement to 0.2 ntu would signifi-cantly improve the reliability of the con-ventional process for removing water-borne pathogens.

UV absorbance as an indicator forpathogen removal. Correlation analyseswere also performed to determine if thepercent removal of UV absorbance andfilter effluent UV absorbance were goodindicators for the removal of pathogens.The results did not show any strong cor-relations between these parameters andthe removal of pathogens. The resultsagree with Plummer et al (1995), whodid not find a strong correlation betweenthe log removal of oocysts and percentreduction of UV254 or dissolved organiccarbon by dissolved-air flotation. Theauthors reported that only about 50% ofthe variation in oocyst removal couldbe explained by these parameters.

Box-plot analyses were performedfor different filter effluent UV ab-sorbance values. Figure 12 shows anexample for C. parvum oocysts. Thefigure shows the median oocyst removaldid not change when filter effluent UVabsorbance decreased. However, theminimum oocyst removal was maxi-mized when filter effluent UV ab-sorbance was <0.05 cm–1. Similar re-sults were observed for all pathogensin this study. The analyses showed thatwhen the pilot plant was able to achievea filter effluent UV absorbance <0.05cm–1, the removals of C. parvumoocysts, E. intestinalis spores, A.hydrophila, E. coli, and bacteriophageMS2 were at least 1.8, 1.3, 3.2, 0.9,and 2.5 logs, respectively. These mini-mum removals were identical to theminimum removals observed when thepilot plant achieved filter effluent tur-bidities <0.2 ntu, as discussed previ-ously. Therefore, the best emergingpathogen removals were observed whenthe pilot plant achieved filter effluent turbidities <0.2 ntuand when the pilot plant achieved filter effluent UVabsorbance <0.05 cm–1.

Aluminum dose to raw water UV absorbance as an indicatorfor pathogen removal. Coagulant dose is often consideredto be the most important parameter in removal of water-borne pathogens by the combined sequence of coagulation,flocculation, sedimentation, and granular media filtration

(Ongerth & Pecoraro, 1995; Logsdon et al, 1981; Robecket al, 1964; Spector et al, 1934). Also, practical experiencein the treatment of natural water has shown that the coag-ulant dose depends mostly on natural organic matter(NOM) concentration and not on turbidity (White et al,1997). In this study, analyses were performed to demon-strate the combined effect of coagulant dose and sourcewater NOM concentration. An example of the analysis is

FIGURE 12 CCrryyppttoossppoorriiddiiuumm ppaarrvvuumm ooooccyysstt rreemmoovvaall aatt ddiiffffeerreenntt ffiilltteerreefffflluueenntt UUVV aabbssoorrbbaannccee vvaalluueess

Ultraviolet absorbance—1/cm

Lo

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em

oval

0.0

0.5

1.0

1.5

2.0

2.5

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<0.05 <0.06 <0.07 All data

n = 46n = 32n = 19

n = 7

MaximumMinimum

25–75% Median

FIGURE 13 CCrryyppttoossppoorriiddiiuumm ppaarrvvuumm ooooccyysstt rreemmoovvaall aatt ddiiffffeerreenntt aalluummiinnuummddoossee ttoo rraaww wwaatteerr UUVV aabbssoorrbbaannccee rraattiiooss

Aluminum/Ultraviolet Absorbance—mg × cm/L

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30–50 50–70 70–90 >90

n = 11 n = 18n = 3

n = 14

MaximumMinimum

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given in Figure 13, which shows a box plot of Cryp-tosporidium oocyst removals for different ratios of alu-minum dose to raw water UV absorbance (in milligramstimes centimeter per litre). The figure shows that the mosteffective C. parvum oocyst removals were observed whenthe aluminum dose to UV absorbance ratio was >70 mg× cm/L. Similar results were observed for E. intestinalisspores, A. hydrophila, and bacteriophage MS2.

The analyses showed that when the aluminum-dose-to-UV-absorbance ratio was >70 mg × cm/L, the removalof C. parvum oocysts was at least 1.7 logs. When thealuminum-dose-to-UV-absorbance ratio ranged from 70to 90 mg × cm/L, the removals of E. intestinalis and bac-teriophage MS2 were at least 1.4 and 2.9 logs, respec-tively. When the aluminum-dose-to-UV-absorbance ratiowas >90 mg × cm/L, the removal of A. hydrophila was atleast 3 logs. These removals were very similar to the min-imum removals observed when the pilot plant achieved fil-ter effluent turbidities <0.2 ntu and filter effluentabsorbance values <0.05 cm–1. For E. coli, no obvioustrend was seen between removal and the ratio of alumdose to UV absorbance.

CONCLUSIONSFor the specific water and the treatment conditions eval-

uated, one of the most significant conclusions from thiswork is that some emerging pathogens were removed muchmore effectively than others. For example, A. hydrophilawas more effectively removed than the other pathogensstudied. E. intestinalis spores and E. coli were more poorlyremoved than C. parvum oocysts and the other pathogensexamined in this study. Currently, the C. parvum microbeis receiving the most research and regulatory attention.On the basis of the results of this work, however, there is

a significant need to further characterize the occurrence,removal, and inactivation of E. intestinalis spores and E.coli in a variety of water supplies. In addition to E. intesti-nalis spores, the spores of other microsporidian speciesshould also receive increased attention.

The data indicate that the minimum level of pathogenremoval increased as filter effluent turbidities decreasedbelow 0.2 ntu. Similarly, the results showed that the min-imum level of pathogen removal increased when the efflu-ent water had a UV absorbance <0.05 cm–1. Additionally,for the specific water tested in this study, the ratio ofalum dose to raw water UV absorbance played a role inpathogen removal. In most cases, high aluminum doseto raw water UV absorbance ratios (>70 mg × cm/L) pro-duced higher pathogen removals.

The results suggest that a change in filter effluent tur-bidity requirements from 0.5 to 0.3 ntu would not sig-nificantly improve the reliability of pathogen control.However, by setting filter effluent turbidity goals below0.2 ntu, significant improvements in microbiological qual-ity could be obtained.

The pilot-plant data suggest that good removal of bothturbidity and NOM (as measured by UV absorbance)decreases the risk of achieving poor emerging pathogenremoval. In other words, optimizing the coagulationprocess based on removal of turbidity and NOM wouldimprove the reliability of the process for achieving higheremerging pathogen removals.

ACKNOWLEDGMENTUniversity of Wisconsin–Madison grants were used

to purchase pilot-plant equipment for the pilot-scalephase of the project. The F.B. Leopold Company(Zelionople, Pa.) provided crushed anthracite filter

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medium, and Best Sand (Chardon, Ohio) and the NorthernGravel Company (Muscatine, Iowa) donated filter sandand support gravel, respectively. The Oak Creek Water andSewer Utility (Oak Creek, Wis.) contributed garnet sand, sil-ica sand, and crushed anthracite for trimedia filtration stud-ies. Jim Buchholtz, Chris Bone, and Andrew Harris weresubstantially involved in the installation and startup of thepilot-plant facilities, and Andrew Harris and Kristine Hahnassisted with the pilot-scale experiments. Throughout theproject, David A. Battigelli provided laboratory supportand consultation, and Brad Argue, Rebecca Hoffman, Eliz-abeth Weisshaar, and David Polchert furnished additionallaboratory support. Nanette Kelsey in the University ofWisconsin–Madison’s Department of Civil and Environ-mental Engineering provided secretarial support. Theauthors also thank Kathryn Martin, the AWWA ResearchFoundation (AWWARF) project manager, and the mem-bers of the project advisory committee for their supportand suggestions throughout the project. Members of theproject advisory committee were Gene Koontz of GannettFleming (Harrisburgh, Pa.), Rick Sakaji of the CaliforniaDepartment of Health Services (Berkeley), and Stanley Statesof the Pittsburgh (Pa.) Water and Sewer Authority.

ABOUT THE AUTHORS:Irene Xagoraraki25 is a postdoctoralresearch associate in the Department ofCivil and Environmental Engineeringat the University of Wisconsin–Madi-son, 1415 Engineering Drive, Madi-son, WI, 53706; e-mail [email protected]. She has a BS degree in

environmental studies from the University of the Aegean,Lesvos, Greece, and MS and PhD degrees in environ-

mental engineering from the University of Wisconsin–Madison. Gregory W. Harrington is an associate profes-sor in the Department of Civil and Environmental Engi-neering at the University of Wisconsin-Madison, andPrapakorn Assavasilavasukul is a research assistant in thesame department. Jon H. Standridge is a managingmicrobiologist with the Wisconsin State Laboratory ofHygiene in Madison.

FOOTNOTES1Model 2100N, Hach Co., Loveland, Colo.2Sigma Chemical Co., St. Louis, Mo.3Gelex standards, Hach Co., Loveland, Colo.4Model DR/4000U, Hach Co., Loveland, Colo.5Pat Mason, Pleasant Hill Farms in Troy, Idaho6ATCC No. 50603, American Type Culture Collection, Rockville, Md.7ATCC No. CCL-37, American Type Culture Collection, Rockville, Md.8Corning, Inc., Corning, N.Y.9Roswell Park Memorial Institute, Gibco, Grand Island, N.Y.10Hyclone Laboratories, Detroit, Mich.11ATCC No. O157:H7, American Type Culture Collection, Rockville, Md.12Difco Laboratories, Detroit, Mich.13ATCC No. 15597-B1, American Type Culture Collection, Rockville, Md.14ATCC No. 15597, American Type Culture Collection, Rockville, Md.15Difco Laboratories, Detroit, Mich.16Corning, Inc., Corning, N.Y.17Sigma Chemical Co, St. Louis, Mo.18Cellabs, Brookvale, NSW, Australia19Waterborne, Inc., New Orleans, La.20FlowCountTM, Beckman-Coulter, Fullerton, Calif.21Epics XL, Beckman-Coulter, Fullerton, Calif.22Olympus BX-50, Olympus, Melville, N.Y.23MacConkey-sorbitol, Difco Laboratories, Detroit, Mich.; Aeromas

agar, Sigma Aldrich, St. Louis, Mo.24Statistica, StatSoft, Tulsa, Okla.25To whom correspondence should be addressed

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