removal of soft deposits from the distribution system

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Water Research 38 (2004) 601610

Removal of soft deposits from the distribution system

improves the drinking water quality

Markku J. Lehtolaa,*, Tarja K. Nissinenb, Ilkka T. Miettinena,Pertti J. Martikainenc, Terttu Vartiainenb,c

aLaboratory of Environmental Microbiology, National Public Health Institute, P.O. Box 95, Kuopio 70701, FinlandbLaboratory of Chemistry, National Public Health Institute, P.O. Box 95, Kuopio 70701, Finland

cDepartment of Environmental Sciences, Bioteknia 2, University of Kuopio, P.O. Box 1627, Kuopio 70211, Finland

Received 20 September 2002; received in revised form 23 October 2003; accepted 30 October 2003

Abstract

Deterioration in drinking water quality in distribution networks represents a problem in drinking water distribution.

These can be an increase in microbial numbers, an elevated concentration of iron or increased turbidity, all of which

affect taste, odor and color in the drinking water. We studied if pipe cleaning would improve the drinking water quality

in pipelines. Cleaning was arranged by flushing the pipes with compressed air and water. The numbers of bacteria and

the concentrations of iron and turbidity in drinking water were highest at 9 p.m., when the water consumption was

highest. Soft deposits inside the pipeline were occasionally released to bulk water, increasing the concentrations of iron,

bacteria, microbially available organic carbon and phosphorus in drinking water. The cleaning of the pipeline decreased

the diurnal variation in drinking water quality. With respect to iron, only short-term positive effects were obtained.

However, removing of the nutrient-rich soft deposits did decrease the microbial growth in the distribution systemduring summer when there were favorable warm temperatures for microbial growth. No Norwalk-like viruses or

coliform bacteria were detected in the soft deposits, in contrast to the high numbers of heterotrophic bacteria.

r 2003 Elsevier Ltd. All rights reserved.

Keywords: Drinking water; Distribution system; Bacteria; Nutrient; Iron; Pipe cleaning; Biofilm

1. Introduction

The quality of drinking water leaving from water-

works usually meets the standards for chemical andmicrobiological quality. However, there are often

microbiological and chemical changes which deteriorate

the water quality within the distribution networks. Iron

pipes are commonly used in drinking water distribution

systems. Iron corrosion products may cause taste andcolor in the drinking water and may can also induce a

chemical decay of the residual chlorine [1,2].

In a drinking water distribution system, the number of

microbes in water generally increases [3]. Detachment of

bacteria from biofilms has accounted for most of the

planktonic cells present in drinking water [4]. Soft

deposits and biofilms in drinking water pipelines have

been found to consist mostly of bacteria, including

pathogenic microbes, which can also be present in

drinking water distribution networks [3,5,6].

Finnish waterworks generally clean the pipelines,

because of taste, odor and color problems. In old iron

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Abbreviations: AOC, Assimilable organic carbon; AOCpotential,

Assimilable organic carbon analyzed with addition of inorganic

nutrients; CFU/ml, Colony forming units per milliliter; FTU,

Formazine turbidity unit; HPC, Heterotrophic plate counts;

MAP, Microbially available phosphorus; NLV, Norwalk-like

virus; NOX, Spirillum NOX bacteria strain; P17, Pseudomonas

fluorescens P17 bacteria strain; TOC, Total organic carbon

*Corresponding author. Tel.: +358-17-201371; fax: +358-

17-201155.

E-mail address:[email protected] (M.J. Lehtola).

0043-1354/$- see front matterr 2003 Elsevier Ltd. All rights reserved.

doi:10.1016/j.watres.2003.10.054


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pipes the content of iron in drinking water can exceed

the indicator parameter value of 200 mg/l laid down in

the council directive 98/83/EC adopted by the council of

the European Union [7]. When there are cases of

waterborne disease outbreaks in Finland, one of the

recommended procedures, in addition to chlorination, is

flushing or pipeline internal gauging (pigging) of thecontaminated parts of the distribution networks [8].

However, cleaning of the pipes is expensive and usually

only some problematic parts of the distribution network

are cleaned, not the whole distribution network.

Data from waterworks have revealed that there is a

high diurnal variation in the consumption of drinking

water. Here we have studied if there is also a diurnal

variation in the drinking water quality, and whether pipe

cleaning would improve the drinking water quality.

Furthermore, the possible occurrence of coliform

bacteria or Norwalk-like viruses (NLV) in the soft

deposits was studied.

2. Materials and methods

2.1. The waterworks and the distribution system

The studied waterworks purified drinking water from

lake water using chemical coagulation with ferric sulfate

and rapid sand filtration. Water pH was adjusted by

liming and water was disinfected with chlorine gas

before distribution. One third of the water was treated

with activated carbon. The waterworks distributed

drinking water for 25,000 individuals.

The part of the distribution system that was studied

was located at a distance of 6 km from the waterworks

with a retention time of about 1 day. The total length of

the distribution system was 171 km. The pipeline was

built in 1966 and had never been mechanically cleaned

after its construction. The pipes were made of cast iron

(inner diameter 150 mm). In the studied area, the water

was consumed by private houses and ramifications in

pipes were about equal, pipes were not dead ends. Water

samples were taken from fire hydrants which were

flushed for 35 min before sampling. Samples were taken

from a common sampling point representing thebeginning of both the cleaned pipeline and the reference

line (A in Fig. 1) and from sampling points after the

cleaned part of the pipeline (B in Fig. 1) as well as from

the end of the uncleaned reference pipeline (C in Fig. 1).

The length of both the cleaned and reference pipelines

was 850 m. The pipeline cleaning was done by com-

pressed air-water flushing, i.e. compressed air and water

pulses were passed through the pipeline. Compressed air

and water were drawn into the pipeline through the fire

hydrants. The water flow during cleaning was turbulent,

and the flow rate of water pulses inside the pipeline was

312m/s. It took about 1 h to clean the pipe.

2.2. Sampling

Weekly water sampling was carried out for 3 weeks

during the same working day of the week (Tuesday

Wednesday). Samples for heterotrophic plate counts

(HPC), iron and total number of bacteria were taken five

times and those for microbially available phosphorus

(MAP) and assimilable organic carbon (AOCpotential)

three times during each sampling day. Sampling times

were chosen to represent the lowest and highest con-

sumption periods. The first 3-week sampling period ended

1 week before the pipeline cleaning (at AprilMay). Two

days after the cleaning (May), water samples were taken

three times every second day. The last 3-week sampling

period was done 3 months after the cleaning (August).

Soft deposit samples were collected during the

compressed airwater flushing. Samples were collected

at the beginning of the cleaning when the thickest

deposits were coming from the pipe.

2.3. Glassware

Glassware was washed with phosphate-free detergent

(Deconex; Borer Chemie AG, Zuchwil, Switzerland).

After immersion in 2% HCl solution for 2 h they were

rinsed with deionized water (Millipore, Molsheim,

France) and finally heated for 6 h at 550C. This

procedure was done to remove all phosphorus and

carbon residuals from the glassware.

2.4. Organic carbon

Total organic carbon (TOC) was analyzed by a high

temperature combustion method with a Shimadzu 5000

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A

B

C

Fig. 1. Layout of the cleaned part of the distribution system.Dashed line (from A to B) is cleaned pipeline and solid line

(from A to C) is the reference pipeline.

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TOC analyser (Kyoto, Japan). Assimilable organic

carbon (AOC) was analyzed by a modification [9] of

the Van der Kooij [10] method. The modification

included addition of inorganic nutrients to ensure that

only the AOC content restricted microbial growth in

phosphorus limited waters, i.e. AOC was measured as

AOCpotential [9]. Growth ofPseudomonas fluorescens wascalculated to correspond to acetate equivalents and

Spirillum NOX to oxalate equivalents.

2.5. Phosphorus

Total phosphorus (total P) was analyzed by the

ascorbic acid method according to the Finnish standards

(SFS, 3026) [11]. Absorbance was measured spectro-

photometrically (Shimadzu UV-1601, Australia) at

880 nm wavelength using a 5 cm light path. Microbially

available phosphorus (MAP) was analyzed by a

bioassay where the maximum growth of P. fluorescensP17 (ATCC 49642) in sterilized water samples was

related to the phosphorus concentration [12]. Inorganic

salts (except phosphorus) and sodium acetate were

added to the water to ensure that the growth of test

bacteria was limited solely by phosphorus. The max-

imum microbial cell production (CFU/ml) was con-

verted to the phosphorus concentration using the

empirical yield factor of 3.73 108 CFU/mg PO4P [12].

Turbidity was analyzed with a Hach Ratio Turbidi-

meter, Model 18900, temporal variation was analyzed in

the sampling point B. The iron concentration was

analyzed spectrophotometrically with Swan Analytical

Instruments (AG CH-8616 Riedikon/Uster) Chematest

20 spectrophotometer. Oxycon Fe reagent (Spectro-

quant 14761 Merck, Dramstad) was used to determine

dissolved iron as described in the manual. The content

of free chlorine was analyzed with Palintest Micro 1000

chlorometer (UK), the test being based on the DPD

method. DPD No.1 test tablets (Palintest, UK) were

used in the test.

2.6. Microbial numbers

The total number of bacteria in drinking water was

analyzed by an acridine orange direct counting methodbased on the method of Hobbie et al. [13]. Bacteria were

counted with an Olympus BH-2 epifluorescence micro-

scope (Olympus Optical co., Tokyo, Japan) using an

eyepiece micrometer (Graticules Ltd., Tonbridge, UK).

Heterotrophic bacteria (HPC) were analyzed by a

spread plating method on R2A-agar (Difco) [14].

R2A-agar plates were incubated for 7 days at 22C

before colony counting. Total coliforms in drinking

water were analyzed according to the Finnish standard

[15] by a membrane filtration method using LesEndo

agar (Difco). Water samples of 100 ml were filtered

through Millipore HA membrane filter with a pore size

of 0.45mm (Millipore Co., Bedford, USA). The plates

were incubated 24 h at 37C before colony counting.

Soft deposit samples collected during the pipe

cleaning were analyzed for total coliforms and Nor-

walk-like viruses. For total coliforms, 2 ml of the deposit

was filtered on the membrane and analyzed as water

samples. For viral analysis, the RNA was extracted fromthe deposits and the presence of NLVs was detected by

RT-PCR and hybridization as described for stool

samples in Maunula et al. [16].

2.7. Statistical analyses

Pearson correlation coefficients were calculated with

SPSS version of 10.1.3 (SPSS Inc.) and Excel 97

(Microsoft) programs. Statistical differences were tested

with one-way analysis of variance and Tukeys multiple

comparison test (significance level ap0:05) and inde-

pendent samples T-test, analyses were done by SPSS forWindows version 10.1.3 program (SPSS Inc.).

3. Results

The quality of drinking water leaving the waterworks

is presented in Table 1. The temperature of the raw

water increased in the summer, which affected the water

quality, demanding an increase in the required chlorine

dose (Table 1).

There was a diurnal variation in the consumption of

the drinking water in the studied network. Fig. 2 shows

an example of the water flow during 1 day. The variation

in diurnal consumption was also similar on the other

days. Drinking water consumption was highest at 9 p.m.

and lowest at 4 a.m. The maximum water flow in the

studied area was approximately 28.7 m3/h and minimum

14.6m3/h. Five daily water samples were taken, repre-

senting different consumption periods (Fig. 2). The

sampling times were at 4 a.m., 7 a.m., 1 p.m., 6 p.m. and

9 p.m. (Fig 2). AOC and MAP were analyzed from the

samples taken at 1 p.m., 9 p.m. and 4 a.m.

No coliform bacteria or Norwalk-like viruses were

found from the soft deposits collected during the pipe

cleaning. Coliform bacteria (not Esherichia coli) wereonly recovered once from the drinking water samples.

This positive sample was taken three months after the

pipe cleaning from the reference pipeline. The average

number of heterotrophic bacteria in soft deposits was

217,100719,400 CFU/ml (n 4).

3.1. Water quality in pipeline before cleaning

Water consumption rate affected the water quality in

the distribution network. The concentration of iron and

turbidity of drinking water was highest at 9 p.m. (A1, B1

and C1 in Fig. 3, B1 in Fig. 4). The differences in iron

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concentrations were statistically significant only at the

sampling point B (po0:05) (Fig. 3). Turbidity was

analyzed only at sampling point B, where differences

were significant (po0:01; except at 7 a.m.) (B1 in Fig. 4).

At other sampling points, especially at the reference

point C, there was a great variation in the iron

concentrations (C1 in Fig. 3). There were no significant

changes in the numbers of heterotrophic bacteria at

different sampling times (Fig. 5). The number of total

bacteria was highest at 9 p.m. (Fig. 6).

When comparing the water quality at sampling pointsB and C, there were no differences in microbiological

parameters, but at C the content of iron (p 0:01) and

content of AOC (p 0:05) were higher (Table 2).

3.2. Effect of pipe cleaning on the water quality

One week after the cleaning, there were differences in

water quality between the sampling point B and

reference point C with the concentrations of MAP,

HPC and total number of bacteria being significantly

higher at the reference point C (Table 2). The difference

in microbial numbers was caused more by the deteriora-

tion of the water quality in reference point C than anyimprovement in the water quality at sampling point B.

In the cleaned pipeline, the content of MAP decreased

below the level of the water leaving the waterworks.

After cleaning at sampling point B, there was no

longer any detectable diurnal variation in the water

quality (B2 in Figs. 36). At reference point C, the

content of iron was highest at 9 p.m. (p 0:05 for

6 p.m.), as were the numbers of bacteria, i.e. the diurnal

variation was similar to that before cleaning (C2 in Figs.

3, 5 and 6).

Three months after the pipe cleaning, the water

temperature increased during summer in waterworks

up to 18.5C, and in the distribution network up to

12.2C (at B) and 15.1C (at C) (Table 2). This increase

in the temperature was reflected by an increase in the

microbial numbers in distribution network. However,

the increase in HPC was significantly higher at reference

sampling point C than at cleaned sampling point B

(Table 2, Fig. 2). There also was an increase in the total

bacteria at both sampling points, however, more at

sampling point C (Table 2). On average there were no

changes in the content of iron at sampling point B, but

at sampling point C the content of iron increased up to

the level prevailing during the first sampling period

(Table 2, Fig. 3). The concentrations of iron, HPC andtotal bacteria were highest at 9 p.m. (B3 and C3 in

Figs. 46).

3.3. Relationships between physical, chemical and

microbiological water parameters

In all data, HPC correlated positively with water

temperature (r 0:74; p 0:000; n 87), total bacteria

(r 0:36; p 0:000; n 135), turbidity (r 0:53;

p 0:000; n 60) and content of iron (r 0:42; p

0:000; n 135), and negatively with the content of

chlorine (r

0:

34;

p

0:

000;

n

121). The content of

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time

04:00 07:00 13:00 18:00 21:00

waterflow

21m

3/h

Fig. 2. Diurnal fluctuation in water flow in the studied area.

Table 1

Characteristics of water leaving waterworks (average7standard deviation, n 3)

Before cleaning 1 week after the cleaning 3 months after the cleaning

Temperature (C) 3.771.3 7.470.2 18.570.6

Chlorine (mg/l) 0.3470.02 0.4270.09 0.5870.01

Iron (mg/l) 0.0970.03 0.0570.02 0.0170.00Turbidity (FTU) 0.1670.01 0.1170.01 0.1070.05

HPC (CFU/ml) 577 14724 26736

Total bacteria/ml 64400728200 71400711600 77500712700

Total P (mg/l) 272 170 o1

MAP (mg/l) 0.2270.04 0.3170.09 0.1970.10

TOC (mg/l) 2.070.1 1.970.1 2.270.2

AOCpotential (mg/l) 104715 8974 8871

Symbols: AOCpotential: assimilable organic carbon analyzed with addition of inorganic nutrients, MAP: microbially available

phosphorus, TOC: total organic carbon.



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iron correlated with turbidity (r 0:83; p 0:000;

n 62), MAP (r 0:45; p 0:000; n 80) and AOC

(r 0:42; p 0:000; n 80) and total bacteria

(r 0:33; p 0:000; n 135).

3.4. The effect of soft deposits on drinking water quality

The data was divided into the periods with high or

low content of iron in the water. In all data, 10% of

samples had iron concentrations over 0.40 mg/l. In this

data the iron concentrations correlated with AOC

(r 0:73; p 0:007; n 12), total bacteria (r 0:69; p

0:004; n 15) and MAP (r 0:63; p 0:027; n 12)

(Fig. 7). In these samples the contents of MAP (0.41 mg/l,

p 0:001), AOC (125 mg/l, p 0:207), HPC (4545CFU/

ml, p 0:017) and the total number of bacteria (110,000

bacteria/ml, p 0:086) were on average higher than in

the samples with the iron content of 0.40 mg/l or less

(MAP 0.26mg/l, AOC 84 mg/l, HPC 1374CFU/ml, total

number of bacteria 85,600 bacteria/ml).

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Fig. 3. Diurnal variations in the concentrations of iron in drinking water taken from different sampling sites. A1, B1, C1: beforecleaning, A2, B2, C2: one week after cleaning, A3, B3, C3: three months after cleaning. Time is shown in the legend.

Fig. 4. Diurnal variations in water turbidity in the cleaned pipeline. B1: before cleaning, B2: one week after cleaning, B3: three months

after cleaning. Time is shown in the legend.



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4. Discussion

In Finnish waterworks, an increase in the iron content

and the turbidity of drinking water are the most

common reasons for initiation of pipeline cleaning.

They are also the main reasons for consumer com-

plaints. Since it is an expensive technique, pipe cleaning

is restricted to only the real problem parts of the

distribution system.

Since there are seasonal changes in water quality, we

also used a reference pipeline in our study to control for

the natural changes in water quality. However, some

differences were noted in the studied pipelines. AOC and

iron concentrations were higher in the reference line, and

temperature was also slightly higher in the reference

pipeline.

Before cleaning, the water quality was lowest at

9 p.m., when the water consumption was also highest.

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Fig 5. Diurnal variations in the number of heterotrophic plate counts in drinking water taken from different sampling sites. A1, B1,

C1: before cleaning, A2, B2, C2: one week after cleaning, A3, B3, C3: three months after cleaning. Time is shown in the legend.

Fig 6. Diurnal variations in total number of bacteria in drinking water taken from different sampling sites. A1, B1, C1: before

cleaning, A2, B2, C2: one week after cleaning, A3, B3, C3: three months after cleaning. Time is shown in the legend.



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The differences were not always statistically significant,

as a result of occasional peaks in the parameters studied.

However, we observed that the peaks were more

frequent at 9 p.m. The peaks may have originated from

old soft deposits in pipelines being disturbed by the

maximal flow rate of water.

When we started this study, we presumed that the

increase in the content of iron and turbidity in water

would be attributable to the release of soft deposits into

bulk water. During the study we detected several iron

peaks in the drinking water with a simultaneous increase

in the concentrations of nutrients and bacteria, the most

extensive increase being in the HPC and MAP concen-

trations. The concentrations of MAP and AOC were on

average more than 50% higher during the iron peak

episode (iron >0.40mg/l). During these high iron

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Table 2

Water quality in the studied pipelines before and after the cleaning of the pipelines (average7standard deviation, n 5)

Before cleaning 1 week after 3 months after

B1 C1 B2 C2 B3 C3

Temperature n.a. n.a. 5.570.3 6.870.4 12.270.5 15.170.4

Chlorine (mg/l) 0.0870.02 0.0870.05 0.0570.02 0.0570.01 0.0470.01 0.0370.02

Iron (mg/l) 0.1570.06 0.4670.45 0.1370.02 0.2270.24 0.1570.15 0.4070.34

Turbidity (FTU) 0.3070.09 0.2870.04 0.3070.05 0.4070.16 0.5770.52 0.3870.07

TOC (mg/l) 2.771.2 2.971.7 1.870.1 1.870.1 2.070.1 2.170.1

AOCpotential (mg/l) 72729 1957179 72717 97740 91739 79738

Total P (mg/l) 473 573 170 273 070 170

MAP (mg/l) 0.2870.14 0.4370.26 0.2470.06 0.3570.14 0.2070.09 0.2370.12

HPC (CFU/ml) 5657189 5657736 4607148 11437596 29367838 632073299

Total bacteria/ml 81600735100 72000736600 78500721800 101900731900 95000731800 102200736600

Symbols: AOCpotential: assimilable organic carbon analyzed with addition of inorganic nutrients, HPC: heterotrophic plate counts

MAP: microbially available phosphorus, n.a.: not analyzed, TOC: total organic carbon.

Statistical significance between cleaned pipeline and reference pipeline po0:05; po0:01; po0:001:

Fig. 7. Relationships of iron and AOC (a), MAP (b) and total bacteria (c) during the iron peak episode (concentration of iron in water

>0.40mg/l)



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episodes, the content of iron correlated strongly with

AOC, MAP and number of bacteria, which indicates

that the release of soft deposits did affect the water

quality. Previous studies have shown that soft deposits

contain high amounts of iron, organic matter, phos-

phorus and microbial biomass [3,17]. Also, we found

high numbers of bacteria in deposits collected duringcompressed airwater flushing, but we did not analyze

the chemical composition of the deposits. However, our

results show that soft deposits are able to release

microbially available organic carbon and phosphorus

into bulk water when the water flow rate changed.

Immediately after cleaning, the content of MAP

decreased below the level in the waterworks, which

shows that during distribution MAP had accumulated in

the pipelines.

The compounds usually found in iron corrosion scales

are goethite (a-FeOOH), lepidocrocite (g-FeOOH) and

magnetite (Fe3O4) [18]. Phosphorus is known to reactwith iron and to form FeOOHPO4 complexes and

FePO4, but these compounds are redox sensitive and can

release phosphorus under anoxic conditions [1921]. The

chemistry of phosphorus and iron may represent one

reason for the MAP accumulation in the distribution

system. Also, Power and Nagy [22] noted an increase in

the content of phosphorus in their studied drinking

water distribution system. There is a risk that this iron

bound phosphorus is released in a bioavailable form

under anoxic conditions or when water flow changes and

thus enhance microbial growth. Previously it was found

that in phosphorus limited waters, even a very minor

increase in the phosphorus concentration can strongly

increase microbial growth [23,24]. In previous studies we

have shown that microbial growth in drinking water

produced in the waterworks studied is limited by

phosphorus.

It is noteworthy that in the cleaned pipeline there was

no observable diurnal variation in the iron concentra-

tion, in contrast to the uncleaned line. Microbial growth

decreased significantly immediately after cleaning. Dur-

ing the summer, the concentration of heterotrophic

bacteria in drinking water increased 5 times higher in the

cleaned pipeline and was 11 times higher in the

uncleaned pipeline, from the concentrations beforecleaning (Table 2, Fig. 5). Three months after the pipe

cleaning other improvements in water quality were

minor.

In this study we found that the increase in tempera-

ture during the summer affected strongly the microbial

quality of drinking water. Also, Niquette et al. [25]

found that the biomass in drinking water was highest in

summer when the water temperature increased. Part of

the difference in microbial numbers between the cleaned

and reference pipelines can be explained by the slight

difference (13C) in water temperature between these

pipelines. Another, probably more important reason for

the difference in microbial numbers after the cleaning is

the removal of nutrient rich deposits, which may have

decreased the potential growth of microbes in the

distribution system. The increase in temperature also

decreased the content of free residual chlorine. Water-

works try to eliminate this problem by increasing the

chlorine dose, but the doses are generally not highenough to prevent the microbial growth throughout the

entire networks. LeChevallier et al. [26] found that even

a free chlorine concentration as high as 4 mg/l was not

enough to eliminate biofilm microbes on iron pipes.

Drinking water quality in the studied area is affected

not only by the pipeline just before the sampling point,

but also the distribution network (6 km) before the

studied area. Release of the soft deposits to drinking

water requires continuous dissolving/accumulation of

iron, sedimentation of organic matter and growth/

accumulation of microbial biomass on the inner surface

of pipelines. Several factors can affect the formation ofbiofilms and deposition of particulate matter in dis-

tribution system. The formation of biofilms is affected

by microbial nutrients, pipe materials, disinfectants,

microbial quality of water and hydraulic regime

[1,27,28]. Gauthier et al. [17] listed the origins of

particulate matter in a distribution network: incomplete

removal of particles in the waterworks, release of fine

material from treatment filters, precipitation of metal

oxides or calcium carbonates, post-flocculation, biolo-

gical activity and corrosion. Previously it was found that

after pipe cleaning, new deposits developed rapidly

inside the pipeline. In that study, 1 year after cleaning,

the microbial numbers in new deposits were almost

equal with those in old deposits which had developed

over decades [3]. Also our study showed that the

improving effect of the pipe cleaning seemed to be fairly

transient, especially for the concentration of iron and

turbidity. This is probably due to the rapid growth of

new deposits.

Development of new soft deposits may be affected by

the possible release of the deposits from the pipeline

before the cleaned area and would be slower if the entire

distribution network were cleaned. Usually soft deposits

accumulate in certain parts of the distribution system

(low flow at night, dead-ends, reservoirs) [17]. Cleaningis not the only solution for elimination of sediments

from the distribution system, e.g. improving of water

hydraulics may decrease the accumulation of soft

deposits. Cleaning of the pipeline would be necessary

especially in cases of contamination of drinking water.

We also studied the soft deposits for presence of

Norwalk-like viruses (NLV) and coliform bacteria. In

previous studies, high concentrations of coliforms have

been reported to be present in old deposits in drinking

water pipelines [3,5]. In Finland, most of the identified

waterborne epidemics in 19981999 were attributable to

caliciviruses (NLV) [8]. There are some concerns that

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biofilms may have a potential to harbor enteric viruses

[6]. In this study we found no coliform bacteria or NLV

in the soft deposits. It should be noted that no

waterborne disease epidemics have occurred in the

geographical areas studied.

5. Conclusions

We found that in old distribution networks, the water

consumption rate could affect the water quality.

Concentrations of iron, bacteria and turbidity in

drinking water were highest at 9 p.m., when the water

consumption was also highest. This may be the reason

for the release of soft deposits in the pipeline. The

release of soft deposits into drinking water increased the

concentrations of iron, MAP and AOC, indicating that

these deposits are reservoirs for microbial nutrients.

Cleaning of the pipeline decreased the diurnal variationin drinking water quality and decreased the microbial

growth in the distribution system. No NLV or coliform

bacteria were found in the soft deposits.

Acknowledgements

This study was supported by National Technology

Agency (TEKES), project number 40230/01. We give

special thanks to the staff of the Laboratory of

Environmental Microbiology in the National Public

Health Institute and in the studied waterworks. We alsowant to thank Carl-Henrik von Bonsdorff and Leena

Maunula in University of Helsinki, Haartman Institute

for virus analyses.

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