Download - Formation, evolution and modeling of trihalomethanes in the drinking water of a town: II. In the distribution system

~ Pergamon PII: S0043-1354(96)00335-1

Wat. Res. Vol. 31, No. 6, pp. 1299-1308, 1997 © 1997 Elsevier Science Ltd

All rights reserved. Printed in Great Britain 0043-1354/97 $17.00 + 0.00

FORMATION, EVOLUTION AND M O D E L I N G OF T R I H A L O M E T H A N E S IN THE D R I N K I N G WATER OF A TOWN: I. AT THE MUNICIPAL

T R E A T M E N T UTILITIES

R A F A E L J. G A R C I A - V I L L A N O V A t*, CESAR G A R C I A 1, J. A L F O N S O G O M E Z 1, M. PAZ G A R C I A ~ and R A M O N A R D A N U Y 2

~Departamento de Quimica Analitica, Nutrici6n y Bromatologia and 2Departamento de Matematica Pura y Aplicada, Facultad de Farmacia, Universidad de Salamanca, Avda. Campo Charro, s/n 37007

Salamanca, Spain

(First received October 1994; accepted in revised form October 1996)

Abstract--Taking samples at eight points chosen from two conventional water treatment plants for the city of Salamanca, the formation and evolution of THM levels were studied on 11 different dates. The values obtained were correlated statistically with the following parameters: concentration of humic acids (only raw water), pre- and postchlorination dosages, UV absorbance (UV-254), pH and temperature. No statistical correlation was observed either with the humic acids content or with the organic matter measured as UV-254. A correlation was only found with the prechlorination dosage in the clarifiers of the old plant. However, in both plants there was a correlation with the postchlorination dosage although this was not very patent owing to the impossibility of knowing the contribution of each parameter at one of the sampling sites where postchlorination and pH correction are performed simultaneously. A clear linear correlation (r = 0.4345, P = 0.0001) was observed with temperature. Using stepwise regression (ANCOVA) a mathematical function was obtained (R=0.8066, P=0.0001) that relates the concentration of chloroform with temperature and the sampling points. From this it is deduced that both pH and temperature increase this concentration, although for each pH value all the In CHCl3 (/~g/l) vs temperature curves showed a maximum (To = 18.97°C), after which chloroform levels decrease sharply. On attempting to quantify the contribution of the rest of the parameters studied here concerning the levels of THMs, it may be inferred that others should be considered, such as the design, the dimensions and the exploitation of the water treatment plants studied. © 1997 Elsevier Science Ltd.

Key words---trihalomethane modeling, trihalomethane formation, chlorination by-products, disinfection by-products, chloroform in drinking water, haloforms, drinking water treatment plants

INTRODUCTION

In 1976 the U.S. National Cancer Institute published a report linking chloroform to cancer in laboratory animals. Two years previously, Rook (1974) and Bellar and Lichtenberg (1974), separately, were the first to report on tile occurrence of this compound in chlorinated drinking water. During the ensuing years water research on this topic gained importance and as a result either the widespread occurrence (USEPA, 1978; Fawell and Hunt, 1988) or the high content (Ventura and Riviera, 1985) of chloroform and three other halogenated methane species (bromodichloromethane, chlorodibromomethane and bromoform) were reported in chlorinated drinking water.

The scientific literature has also addressed the occurrence of many other groups of compounds as a result o f the reaction of the natural organic matter of

*Author to whom all correspondence should be addressed.

water with disinfectant chemical reagents, as a result of which a long and varied list of disinfection by-products (DBPs)- -many of which might be teratogenic, mutagenic and/or carcinogenic--has been compiled (Fawell and Hunt, 1988; Horth, 1989; Holborn, 1990; Kronberg et al., 1991) in which the trihalomethanes (THMs) are only the tip of the iceberg (Klein, 1990).

The concern of the national and supranational health authorities has resulted either in recommen- dations or regulations about the maximum levels of several groups of DPBs (EEC, 1980; USEPA, 1988; WHO, 1992) and has prompted studies on the reaction mechanisms and conditions involved and, furthermore, on developing kinetic computer models to simulate the formation of DBPs during water treatment, for both their control and minimization.

The information on the reaction mechanism of the formation of T H M s is still limited, although it is

1299

1300 R.J. Garcia-Villanova et al.

generally recognized that four factors would be involved in their formation: the chlorine-to-precursor molar ratio, pH, temperature and reaction time.

(1) THM formation is strongly dependent upon the chlorine concentration (Kavanough et al . , 1980; Peters et al. , 1980). However, there is some disagreement regarding the quantitative relations between chlorine concentrations and the rate of THMs production. Most investigators have found a linear relationship between chlorine consumption and the production of THMs with a reaction order

greater or equal to unity (Kavanough et al. , 1980; Trussel and Umphres, 1978). Despite this, it is also possible that the reaction order might change during the course of the reaction (Kavanough et al. , 1980).

(2) The formation of THMs also increases strongly with increasing amounts of soluble organic matter, following a first-order reaction. In naturally occur- ring water, this organic matter usually consists of humic substances (Trussel and Umphres, 1978; Babcock and Singer, 1979). Although fulvic acid accounts for over 90% of the aqueous humics in

Raw water NEW PLANT OLD PLANT (river Tormes)

R

N I. CI2 gas (prechl°rinatiOn) i

[ Clarifier Clarilier

g~ I Fn g= 1 + c,o L_

(poslchlodn~ion) I I Na()H I j I.

I Postchlodnated I p.

i Fe

F AM

Distribution s/s'tam

Fig. 1. Schematic outline of the water treatment processes in the old and new water utilities of Salamanca, with indication (O) of the sampling and measuring points. R: raw water; Cp: clarified pulsator water (old plant); Ca: clarified accelator water (old pianO; Fo: filtered water in the old plant; Cn: clarified water (new plant); Fn: filtered water in the new plant; Fc: filtered chlorinated and pH corrected water (new plant);

M: mixed water (from old and new plants).

THM evolution and modeling: I. At the utilities

Table 1. Operation data for the two water treatment plants, x indicates the mean dosage during the period of study. The postchlorination dosage at the new plant is expressed kg/m -~ of chlorine, but it actually represents the sum of CI., + CIO: in approximately equimolar amounts

Old New

Flow (l/s) 400 600 Cl., or CIO2 dosage (kg/m 3)

(x) Prechlorinafion 2.15 2.67 (x) Postchlorination 0.98 1.67

Treatment process time (h) 2 2

many water sources, Babcock and Singer found that relative contributions to the formation of THMs by the humic fraction is greater than that of the fulvic fraction since the. former substances react more readily with chlorine.

(3) Increased pH values lead to increases in THMs formation (Stevens et al., 1976; Onodera et al., 1987 and 1989), three-fold increases being reported in the reaction rate per unit of pH (Kavanough et al., 1980). The lower the pH, the higher non-ionized HCIO form of hypochlorous acid is found, thus increasing its reaction rate with the humic matter. However, THM yields depend rather on the last step of the THM reaction pathway, which is base-catalyzed as with the haloform reaction (Simmon and Tardiff, 1978). These findings have also been reported by other authors (Peters et al., 1980; Sandier, 1977). According to Adin et al. (1991), the acidic functional groups of humic matter are not ionized, leading to the aggregation of molecules due to Van der Waals forces. This phenomenon is also associated with folding of the huraic molecules, leaving fewer sites available for attack by chlorine (Trehy and Bieber, 1980), thereby red'acing THM production.

(4) In studies on the effect of temperature on THMs formation, an Arrhenius-type dependence has been found between the rate constant and temperature, with activation energies ranging from 10-20 kJ mol -~ (Kohei et al., 1983; Peters et al., 1980) to below l0 kJ mol -~ (Kavanough et al., 1980; Stevens et al., 1976). Accordingly, a higher rate of THM formation should be expected with increasing water temperatures although, on the other hand, the volatility of

15,0 ~ • C~oroform

12,0-, [ ] Dfd,lorobromomethane

9 ,0- .

6,0-

3,0 -

0,0 Ca Cp Fo Cn Fn Fc M

Sampling points

Fig. 2. Nature and mean concentrations of THMs found in seven sampling points of the two plants (old and new).

16,0

.

13,0-

10,0 -

7,0-

1301

Fig. compounds (chloroform and dichlorobromomethane, mean value, as TTHM) for each plant during the sampling period.

these compounds should account for their partial remotion in open systems, as will be discussed below.

(5) A fifth factor involved in the process would be the bromide concentration, which affects both the rate of formation and yield of THMs. During chlorination, bromide is oxidized to bromine which in turn reacts more readily than chlorine with organic precursors to form mainly brominated THMs (Stevens et al., 1976; Rook et al., 1978).

The U.S. Water Quality Division Disinfectant Committee (1992) reported a survey on 186 U.S. water utilities and compared current disinfection practice, introduced to reduce THM formation, with those operating in the late 1970s. Most changes in the treatment process took into account the above considerations and the main ones were reported to be: alteration of both the point of application and the dosage of chlorine used; a reduction in pH during coagulation to improve this and to add ammonia, or a shift to another preoxidant or final disinfectant. Changes involving major infrastructure investment, such as GAC contactors or ozone had not been widely adopted.

Studies on the simulation of THMs formation have been based on two approaches: namely, the development of kinetic and mathematical models. With respect to the former (kinetic) the study conducted by Amy et al. (1987) was based on a large

3O,O

T('C) ~ ( ~ L )

20,0

10,0

0,0

F'mished water

I I I I

0 4 6 S 10 12 Sample

Fig. 4. Evolution of temperature and TTHM (chloroform + dichlorobromomethane) for the finished water (point M) during the period of study (February through to

July).

TrHM • New plant D Old plant f f ~

Cp, Cn Fo. Fn Sampling points

3. Evolution of the two measurable (>D.L.)

1302 R. J. Garcia-Villanova et al.

Table 2. AN COVA test for dependence of production of chloroform on both temperature and sampling point

Variable Coefficient Std Error t -value Probability Constant 4.056751 T 0.290559 0.064890 4.477746 0.0001 Ca -3.564824 0.785285 4.539526 0.0001 Fc 3.564824 0.785285 4.539526 0.0001 n = 77; R = 0.604563; F = 21.31332; P < 0.0001; (~Snedecor).

number of different water samples, a large number of observations with extensive testing conditions and a wide range of parameter types and values. These authors studied laboratory chlorination of nine samples of natural water from various locations throughout the United States by spiking with several bromide concentrations and adjusting to several different temperatures and pH values prior to chlorination. A mathematical equation was obtained for total trihalomethane (TTHM) production as a function of the DOC (dissolved organic carbon), DUV-254 (UV absorbance at 254 nm of dissolved matter), the chlorine dosage, bromide concentration, pH, temperature and reaction time. However, the applicability of this equation to all kinds of treated water was later reported to be limited (Harrington et al., 1992). Another kinetic model was proposed by Adin et al. (1991); this suggested that a multi-step reaction occurs between chlorine and humic matter, affording an equation which enables one to predict the concentration of THMs as a function of the precursor and chlorine concentrations and of the reaction rate. This equation also includes the values of four reaction constants of the overall multi-step reaction calculated at 20°C and pH 8 for that system (water from Lake Kinneret, Israel). The experimental and calculated values were successfully correlated (r 2 = 0.9) for this water sample.

Numerous studies have used linear regression techniques to correlate the THMs formation potential with the TOC and UV-254, but although the results point to good correlations, general use of the regressions should be restricted because they do not include parameters such as chlorine dosage, pH, temperature and time. An ambitious computer program was compiled by Harrington et al. (1992) to simulate DBP formation, the removal of natural organic matter, organic water quality changes and disinfectant decay in water treatment processes. The authors took data from many bench-scale, pilot and full-scale studies in the United States which used alum or ferric chloride coagulation, floculation, clarification and filtration. They obtained equations that were unable to simulate the formation of THMs, the removal of TOC and UV-254 by alum

coagulation and changes in alkalinity and pH. When the modeled simulations were compared with the limited set of measured values, a slight tendency to underpredict finished-water pH and DOC (by 4 and 7%, respectively), but a higher tendency to underpredict TTHM by 20-30% were observed.

The development of a performant method (Garcia et al., 1992) for the determination of 16 volatile haloorganic hydrocarbon DBPs (including the four THMs) enabled us, with a certain degree of accuracy, to conduct a follow-up of the levels of these compounds during the drinking water treatment process in the city of Salamanca, Spain. These results are statistically compared with selected parameters with a view to assessing their influence at each sampling point along the processes. An empirical mathematical model is proposed for predicting THM formation, measured as chloroform.

EXPERIMENTAL

Determination o f halogenated hydrocarbons

Sixteen halogenated hydrocarbons (Chem Service, Inc.; Analytical Standard Stockroom), many of them potential DBPs, were assayed by a method developed by us and reported elsewhere (Garcia et al., 1992). The method is based on a single liquid-liquid extraction with n-pentane (Merck, pro analysi) performed, always without head-space, in the sampling vial itself and then analysis by gas chromatography using a semicapillary column and an electron-capture detector. The compounds assayed were:

Methylene chloride l,l-Dichloroethane Chloroform (D.L.: 0.9/tg/l) Carbon tetrachloride 1,2-Dichloroethane Trichloroethylene 1,2-Dichloropropane Bromodichloromethane (D.L.: 0.4/tg/1) 2-Chloroethylvinylether cis- 1,3-Dichloropropene trans- 1,3-Dichloropropene 1,1,2-Trichloroethane trans- 1,3-Dichloropropene 1,1,2-Trichloroethane Chlorodibromomethane (D.L.: 0.4/tg/1) Tetrachloroethylene Bromoform (D.L.: 0.9 ~g/1) 1,1,2,2-Tetrachloroethane.

Table 3. Correlation values (r) between humic acid amount in raw water (H.A.-R.) and chloroform (CHCh) production in Cp, Ca, Fo, Cn, Fn and Fc

CHCh-Cp CHCh-Ca CHCh-Fo CHCI3-Cn CHCh-Fn CHC13-Fc H.A.-R. -0.057409 -0.146466 -0.525603 -0.015292 -0.135176 -0.111601

Tab

le 4

. O

ld p

lant

(F

ebru

ary

to

July

199

1):

oper

atio

n an

d m

easu

red

dat

a at

the

poi

nts

B,

Ca,

Cp

and

Fo;

tem

per

atu

re a

nd h

umic

aci

ds a

re g

iven

onl

y fo

r ra

w w

ater

(R

).

Th

e pr

e- a

nd p

ostc

hlor

inat

ion

dosa

ge d

ata

for

sam

plin

gs 1

0 an

d

11 w

ere

not

avai

labl

e

Chl

orin

atio

n do

sage

(g

C12

/m 3)

B

C

a C

p F

o

T

Hu

mic

aci

d C

HC

13

CH

Ch

C

HC

I3

Sam

plin

g P

rech

lor.

P

ostc

hlor

. (<

'C)

(mg/

I)

pH

U

V-2

54

pH

U

V-2

54

(/~g

/l)

pH

U

V-2

54

(/tg

/l)

pH

U

V-2

54

(/~

g/l)

1 1.

457

0.72

7 6.

0 0.

20

7.85

0.

092

6.70

0.

022

2.7

6.40

0.

022

2.7

6.40

0.

020

2.7

2 1.

599

0.77

9 4.

5 0.

40

7.35

0.

180

6.60

0.

038

1.4

6.41

0.

038

1.9

6.60

0.

034

1.9

3 1.

818

1.09

0 9.

5 0.

31

7.40

0.

130

6.70

0.

122

4.5

6.60

0.

044

5.4

6.40

0.

031

6.2

4 2.

393

1.10

4 9.

5 0.

52

7.20

0.

223

6.20

0.

035

3.9

5.20

0.

035

5.2

6.60

0.

031

5.1

5 2.

840

1.36

3 13

.0

0.34

7.

60

0.12

0 6.

80

0.02

8 7.

8 6.

70

0.02

8 8.

5 6.

70

0.03

8 10

.6

6 2.

945

0.92

0 15

.0

0.18

7.

35

0.12

0 6.

20

0.02

7 5.

4 6.

20

0.02

7 7.

0 6.

30

0.03

0 6.

5 7

2.11

4 0.

845

24.0

N

.D.

6.90

0.

079

6.70

0.

043

6.2

6.00

0.

052

6.8

6.60

0.

045

12.7

8

2.02

0 0.

808

22.0

0.

22

7.20

0.

127

6.90

0.

046

6.9

6.20

0.

038

7.5

6.40

0.

035

7.5

9 2.

181

1.16

3 21

.0

0.38

6.

70

0.14

2 5.

50

0.02

5 4.

1 5.

50

0.02

6 7.

1 5.

00

0.02

0 6.

0 10

--

23

.5

0.30

6.

70

0.09

0 5.

75

0.01

6 3.

0 5.

75

0.01

8 9.

5 6.

00

0.02

0 5.

4 11

--

26

.0

0.02

7.

60

0.13

9 5.

50

0.01

4 2.

0 5.

00

0.01

1 4.

5 6.

30

0.01

7 7.

1

Tab

le 5

. N

ew p

lant

(F

ebru

ary

to

July

199

1):

op

erat

ion

an

d m

easu

red

dat

a at

the

poi

nts

B,

Cn,

Fn

an

d F

c; t

emp

erat

ure

and

hum

ic a

cids

are

giv

en o

nly

for

raw

wat

er (

R)

Chl

orin

atio

n do

sage

(g

Cl~

/m 3)

B

C

n F

n F

c

T

Hu

mic

aci

d C

HC

I3

CH

Cb

C

HC

I3

Sam

plin

g P

rech

lor.

P

ostc

hlor

.*

(°C

) (m

g/l)

p

H

UV

-254

p

H

UV

-254

(/

tg/l

) p

H

UV

-254

(/

tg/l

) p

H

UV

-254

(/

~g/

l)

o o o g _~.

1 1.

819

1.01

8 6.

0 0.

20

7.85

0.

092

6.65

0.

041

5.1

6.65

0.

029

6.0

8.50

0.

033

7.8

2 2.

678

1.50

0 4.

5 0.

40

7.35

0.

180

6.35

0.

038

4.3

6.40

0.

032

3.6

7.60

0.

041

4.0

3 2.

142

1.85

7 9.

5 0.

31

7.40

0.

130

6.45

0.

047

9.1

6.40

0.

038

11.3

7.

60

0.04

2 11

.1

4 3.

489

1.85

7 9.

5 0.

52

7.20

0.

223

6.00

0.

038

6.9

5.50

0.

025

5.2

7.30

0.

029

6.9

5 2.

285

1.50

0 13

.0

0.34

7.

60

0.12

0 6.

70

0.02

9 12

.2

6.80

0.

029

13.9

7.

40

0.03

9 13

.9

6 2.

285

1.42

8 15

.0

0.18

7.

35

0.12

0 6.

65

0.03

8 5.

1 6.

70

0.03

8 6.

1 7.

60

0.05

4 7.

3 7

2.42

8 1.

571

24.0

N

.D.

6.90

0.

079

6.50

0.

040

11.6

6.

60

0.04

0 12

.8

7.50

0.

035

12.7

8

2.42

8 1.

928

22.0

0.

22

7.20

0.

127

6.40

0.

041

17.6

6.

40

0.04

3 15

.8

8.50

0.

066

17.5

9

3.71

4 2.

571

21.0

0.

38

6.70

0.

142

5.00

0.

020

14.7

5.

00

0.02

1 14

.4

7.80

0.

034

25.2

10

3.

156

1.55

9 23

.5

0.30

6.

70

0.09

0 5.

50

0.02

8 8.

4 5.

50

0.02

8 5.

6 8.

00

0.05

7 9.

8 11

2.

923

1.58

6 26

.0

0.02

7.

60

0.13

9 6.

70

0.02

7 6.

0 5.

50

0.01

5 5.

8 8.

00

0.03

6 13

.7

*The

se v

alue

s re

pres

ent

the

sum

of

C12

+ C

IO2

add

ed i

n an

app

roxi

mat

ely

equ

imo

lar

amo

un

t (s

ynth

esis

of

CIO

2 by

exc

ess

of

C12

ov

er N

aCIO

2).

U,


Table 6. Correlation between prechlorination dosage and chloroform formation in the new (Cn and Fn) and old plants (Ca, Cp, Fo)

Cn Fn Ca Cp Fo Corr. values (r) 0.154783 -0.074499 0.650840 0.756646 0.526069 Probability 0.6495 0.8277 0.0576 0.0183 0.1457

None of these compounds appeared in any of the samples studied except the four THMs, for which the detection limits are given in parentheses. Precision, expressed as standard deviation (S), ranged from 0.32 #g/1 (for CHCh) to 0.78 #g/1 (for CHBr3) and, as variation coefficient (V.C.), from 8.7 to 18.0%, respectively. The average total time for the analysis of each sample was 45 min.

The calibration curve for the analysis of humic acids was made from a commercial standard (Janssen Chimica; Humic acid sodium salt) and not by any of the isolation methods found in literature. Consequently, the values given in the text should not be considered as absolute, but relative and their interest lies in the comparison among the different samples.

Treatment plants The source for the water supply of the city of Salamanca

is the River Tormes. At the time of this study, the water was being treated at two plants (old and new) working in parallel, according to the diagram outlined in Fig. 1. The old plant had three up-flow solids contact clarifiers (one "pulsator" and two "accelerator" types) and six rapid sand filters. The new plant in its first phase had one rectangular pulsator type clarifier and two rapid sand filters.

The operational data are summarized in Table 1. Chlorination is always performed to free chlorine.

Another treatment plant operates on the left bank of the river. Because its catchment is different and the population served is much smaller, it was not considered in this study.

Sampling period and points Analysis and measurement of all the above indicated

parameters were made for 11 sampling dates every 2 weeks, from February to July 1991. Analyses of halogenated hydrocarbons were made for two replicate samples. The sampling and measuring points were eight along the treatment plants, as indicated in Fig. 1. Three representative clarifiers were selected, two from the old plant and one from the new plant.

Computer programs Two Macintosh version programs were employed for the

statistical treatment of data and mathematical modeling; Stat-View 4.0 and SPSS (statistical package for social sciences).

Parameters measured

Parameter Technique

pH* Temperature* UV-254"* Spectrophotometry at 254 nm, with 10 mm

optical path quartz cells. Humic acids** Precipitation by acetic acid and separation

at the water-isoamilic alcohol interphase, after addition of it; filtration, washing with ethanol; redissolution in sodium hydroxide solution and spectrophotometry at 580 nm (Suess, 1982).

Free/total Ch* Colorimetry with DPD at 515 nm (HACH, DR 100 colorimeter apparatus)

CIO2"* Colorimetry with DPD at 515 nm (APHA- AWWA-WPCF, 1989)

*Field measurement. **Laboratory measurement.

RESULTS AND DISCUSSION

A total of 88 analyses was performed. None of the 16 halogenated hydrocarbons was found in the raw water samples (point R, Fig. 1). However, in all the samples (77) f rom the other points bo th chloroform and b romodich lo romethane were found, while ch io rod ib romomethane was present in 76 samples. An unidentified compound appeared on 18 occasions, bu t presumably at low concentra t ions except on the first sampling date. Wi th large differences, the major compound was chloroform, followed much fur ther behind by b romodich lo romethane ; chlorodibromomethane almost always appeared at levels below the detect ion limit of the method ( < 0.4 pg/1). Figure 2 shows the mean concentra t ions of the three T H M s found at each point of the plants.

It may be seen tha t the amount s of chloroform and of ch lo rod ib romomethane formed were higher at all points of the new plant (Cn, Fn and Fc) with respect to the old plant (Ca, Cp and Fo) (Fig. 3).

Since chloroform was always found to be by far the major compound , it was decided to use its values for s tudying the correlat ion with other parameters as an indicator for the format ion of THMs.

Effect of temperature

A certain parallelism can be seen (Fig. 4) between T T H M and the tempera ture parameters , with f luctuat ion due to different causes, as will be discussed below.

A global regression analysis made with all the data measured for chloroform and tempera ture (n = 77) gave a linear correlat ion (r --- 0.434513, P = 0.0001) for the whole system. In order to determine the points of bo th plants at which this correla t ion was best

LrV.254 " 0 , 1 7 5 "

0,14o-" 0,I05"

0,070 ="

0,035-

15,0 •

12 o OLg/L)

" 9 , 0

" 6 ,0

- 3 , 0

I-. u R Ca Cp Fo M F¢ F n C n R

Sampling points

Fig. 5. Evolution of UV-254 and measurable TTHM during the treatment process in the old and new plants• Arrows indicate the "direction" of the treatment in each plant from R (raw water) to M (mixture of finished water); dotted lines

indicate treatment in parallel.

0 , 0 0 6 0 , 0


Table 7. Friedman test for UV-254, obtained when including point Table 9. Friedman test for comparing pH in Ca, R (Column 1) and when deleting point R (Column 2) Cp and Cn

Column 1 Column 2 D.F. 2 D.F. 6 5 No. of groups 3 No. of groups 7 6 No. of cases 11 No. of cases 11 11 Chi corrected for ties 8.75 Chi corrected for ties 33.18408 10.672043 P = 0.0126

P = 0.0001 P = 0.0583 Mean rank Mean Std dev.

fitted, a multiple regression test was employed. It was concluded that the points Ca and Fc were those at which the dependence of chloroform production on temperature were smaller and higher, respectively, as compared with the other five points. The A N C O V A test confirmed these findings (Table 2).

Effect of concentration of humic acids

The method employed only allows the measurement of humic acids in raw water since at the seven ensuing points their low concentrations prevented their measurement.

A correlation between their contents in raw water (point R) and chloroform production in the seven following points was assayed (Table 3). For n = 11, the correlation would be significant if Irl > 0.6021 ( P > 0.05), such that none of the points was significant.

Influence of the prechlorination dosage and UV-254 parameters

As reported above, Figs 2 and 3 reveals at first glance a lower formation of T T H M in the clarifiers of the old plant (Ca and Cp) with respect to the new one (Cn); this can be attributed to two factors that, although individually of little importance, could act in an additive fashion:

(1) The chlorination dosages are slightly higher in the new plant (Table 5) than in the old one (Table 4).

(2) According to the UV-254 values, at first sight the process of decantation-fil tration seems to be more efficient in the old plant than in the new one.

In an analysis of these two factors: (1) A correlation test was performed with the

prechlorination values given by the plant operators (shown in Tables 4 and 5) for the production of chloroform either at Cn or Fn (new plant) and at Ca, Cp and Fo (old plant) (Table 6). For n = 11, the correlations would be significant if Irl _> 0.6021, such that it can be deduced that there was not significant correlation for the new plant. In the case of the old plant, a clear correlation was only observed at Cp (P < 0.05) and a less clear one at Ca (P = 0.0576), although owing to the low number of cases it is not possible to confirm this since for n- - -9 the correlations are significant if [r] > 0.6666; at Fo, no correlation was observed.

pH-Ca 2.68 6.32 0.53 pH-Cp 1.55 6.00 0.57 pH-Cn 1.77 6.26 0.55

1305

The lack of fitting observed between the prechlorination dosage and chloroform production at the new plant could be due to the different dimensions and design of the clarifiers which are shallower and wider. This could lead to a more irregular evaporation of the chloroform and of free chlorine and the photochem- ical destruction of chlorine (Nowell and Hoigne, 1992).

(2) Figure 5 shows the evolution of the T T H M contents against the UV-254 values in both plants.

It may be seen that it is in the clarifiers where the highest amounts of T T H M are produced, especially in those of the new plant (Cn) (see Fig. 5). F rom Tables 4 and 5 the following UV-254 values may be deduced for the three clarifiers studied:

Ca = 0.029 + 0.012; Cp = 0.31 + 0.012 and Cn = 0.034 + 0.009. These values seem to point to slightly higher values for Cn, although they are subject to a lower standard deviation. To determine whether the differences in UV-254 among the seven points of both plants (before mixing, point M) were significant, the A N O V A test was used. Significant differences were seen among the seven points (P < 0.0001), such that it was decided to determine where the differences lay using the Fisher PLSD test for an A N O V A test for repeated measures and by non-parametric analysis of variance (Friedman test, Table 8).

Neither of the tests revealed significant differences in the UV-254 values among any of the points with the exception of R. Thus, only the raw water (R) was found to have higher values of UV-254; the values of Ca, Cp and Cn could not be distinguished. Accordingly, neither is it possible to use this parameter to account for the greater amount of chloroform found in the clarifiers of the new plant.

Effect of the postchlorination dosage

Owing to the lack of an available sampling point in the old plant, the effect of the postchlorination dosage was studied at point Fc of the new plant. The maximum concentrations of chloroform and

Table 8. Correlation values (r) between chloroform content in Fc and the indicated parameters

Prechlor. pH-Fn pH-Fc A pH (Fn - Fc) Postchlor. CHCI~-Fc 0.360793 -0.411460 0.203536 0.448150 0.746977


Table 10. Ordinary ANOVA test for comparing differences of chloroform production between the three clarifiers

Comparison Mean diff. Fisher PLSD CHCh-Ca vs CHCb-Cp -1.654545 1.864072 CHCb-Ca vs CHCh-Cn - 4 . 8 2 7 2 7 3 1.864072" CHCh-Cp vs CHCI~-Cn - 3 . 1 7 2 7 2 7 1.864072" F-test between groups: 15.07 (P < 0.0001). *Significant at 95%.

chlorodibromomethane were found at this point (Figs 2, 3 and 5). As may be seen in Fig. 1, at this point a correction of the pH is also carried out, bringing it to a value of 7.7 + 0.26 (Table 3) to compensate the pH of 6.3 + 0.34 (Table 2) coming from the old plant. Finally, a finished water pH (point M) of 7.3 _ 0.42 is obtained.

Since the factors of prechlorination and pH are generally reported also to affect the production of chloroform, it was decided to introduce the following variables (Table 8) for the study of correlation: prechlorination dosage (at Cn), pH (at Fn), pH (at Fc), ApH (from Fn to Fc) and, finally, the postchlorination dosage (at Fc). For n = 11, the correlation would be significant if Irl >0.6021 (P < 0.05) such that only a correlation with the postchlorination dosage was deduced. On performing step-wise regression, pH (rpartial = 0.5104) appears as a second variable, although with a low degree of significance (P = 0.1317) because of the low differences in pH between dates (x = 7.71; s = 0.26).

Accordingly, in statistical terms the postchlorination dosage appears as a clear factor in the production of chloroform, although the impossibility of separating and conducting independent studies on the ApH and chlorination dosage factors tends to mask this finding.

Effect o f pH

Study of the above parameters still fails to explain the lower production of chloroform observed in the clarifiers of the old plant (Ca and Cp) as compared with those of the new one (Cn). To see whether pH might be involved in this, an initial attempt was made to discover whether there were significant differences between the pH values of the clarifiers. First, the

Table 11. Friedman test for comparing differences of chloroform content in Ca, Cp and Cn D.F. 2 No. of groups 3 No. of cases I 1 Chi corrected for ties 14.55814

P = 0.0007 CHCh-Cn Mean rank Mean Std dev. CHCb-Ca 2.05 1.14 4.35 CHCh-Cp 2.34 2.14 6.01 CHCb-Cn 4.35 2.73 9.18

ordinary A N O V A test was applied, but this did not reveal significant differences among the pH values (P = 0.0873) in the three clarifiers. The non-parametric Friedman test was also applied (Table 9) which did reveal some statistical differences (P = 0.0126), showing that from date to date the pH values at Ca are slightly greater than those found at Cp.

Following this, the ordinary A N O V A test (Table 10) and the non-parametric Friedman test (Table 11) were applied to see whether the differences in the formation of chloroform at Ca, Cp and Cn were significant.

Neither the ordinary A N O V A test (P < 0.0001) nor the non-parametric Friedman test revealed significant differences in the levels of chloroform between Ca and Cp but there was a significant difference between these at Cn, where they were higher (PLSD Fisher test, smallest significant difference). As a result, the study reveals a lower production of T H M s at the old plant; however it is unable to account for the greater production of T H M s in the new plant through the observation of pH either in the clarifiers or at point Fc because in the latter case of the impossibility of differentiating this factor from the postchlorination rate, although its effect seems probable.

A mathematical model

After observing the dependence of the chloroform concentration on temperature, possibly on pH and on the sampling point in both plants, step-wise regression functions aimed at relating these factors

Table 12. ANCOVA test for chloroform content with variables T 3, T 4, pH 2 and sampling points (Ca, Cn and Fn)

n R R 2 Adj. R-' RMS residual 77 0.806581352 0.650573477 0.625965976 0.358529663

D.F. Sum squares Mean square F-test

Regression 5 16.992176896 3.398435379 26.438014207 Residual 71 9.126589843 0.128543519 P = 0.0001 Total 76 26.118766739 Variable Coefficient B Std error t -value Probability

Constant 0.34830371 T 3 0.000588564 0.000072479 8.120507311 0.0001 T 4 -0.000023273 0.000003051 7.626997868 0.0001 pH 2 0.023692526 0.003896286 6.080797882 0.0001 Ca --0.539253717 0.088636658 6.083867916 0.0001 Cn 0.29286354 0.089043203 3.289005012 0.0016 Fn 0.246390177 0.088551115 2.782462734 0.0069

~" 4 .

:=

0

-1,


6 ~ 5 ~

! I 5 10 15 2 0 25 ~ [ 0

Te

-2,

Fig. 6. Graphic plot of In CHCI3 (#g/l) vs temperature (T) at the indicated pH values. T,: critical temperature.

were obtained. The variables resulting from these assays were as follows: In CHC13 (/~g/l), T 3, T 4, p W and sampling point (Ca, Cn and Fn) that were subjected to covariance analysis A N C O V A (Table 12). Since chloroform values are subjected to an analytical error with an S = 0.32 and a V.C. = 8.7%, their In function,; will be affected by a standard deviation (S) of 0.087 whose error should be accumulated to the error of the fitting, thus obtaining the overall error.

Thus, a linear model fitting with the following mathematical expression was obtained:

In CHCI3 (#g/l) =: ct + fl3T 3 + f14 T4 + ypH 2 + 6~ + e

and the overall mathematical equation with the best fit to all the experimental data is."

In CHC13 (/~g/l)= 0.34830371 + 0.000588564T 3

-- 0.000023273T 4 + 0.02369252pH 2 + 6~ + e

in which & is:

-0.539253717 :in Ca +0.292863540 :in Cn +0.246390177 :in Fn +0.000000000 :in the rest of the points

and e is a random error with a zero average and a standard deviation of S(e) = 0.3689, pooled from two components (Sa.a~y~ca~ = 0.087 and S,, = 0.3585).

The graphic plot of In CHCI3 (gg/i) vs T at several pH values affords the curves shown in Fig. 6, in which

1307

3,5 . . . . . . . . . . . . .

"~ II

0'5 / . , k /

O! . . . . . . . . . . 0 0,5 1 1,5 2 2,5 3 3,5

Fitted values

Fig. 7. Plot of tlhe observed vs fitted values (from mathematical model of the treatment plants) for In CHCI3

(ug/l).

a maximum is seen for a temperature value, referred to here as critical temperature To:

7", = - 3f13/4fl, = 18.97°C.

A plot of the observed vs the fitted values for In CHCI3 (/tg/l) is shown in Fig. 7, for which a correlation coefficient of 0.8066 is obtained.

CONCLUSION

None of the parameters studied, with the exception of temperature, could be clearly correlated with the concentration of T H M s in the system studied. However, it was possible to compile a predictive mathematical model that includes pH and temperature for each of the sampling points with excellent fitting (Table 12). The increasing values of pH and temperature lead to a higher production of THMs; however, as from a given value ( T = 18.97°C), temperature dramatically reduces T H M levels. This could be accounted for in terms of a shift in the extent of two phenomena: temperature increases the rate of formation up to Te, at which the rate of removal of THMs, most likely owing to their volatility, becomes higher than their formation rate.

On attempting to quantify the contribution of the rest of the parameters studied here concerning the levels of THMs, it may be inferred that others should be considered, such as the design, the dimensions and the exploitation of the water treatment plants studied.

Acknowledgements--This paper is based on the Doctoral Thesis work of M. P. Garcia de Tiedra. The authors would like to thank the Regional Government (Junta de Castilla-Le6n) for its financial support, the municipal operators of the City of Salamanca and, especially, Mrs M. J. Sierra for the typing and computer-generated design of many of the tables and figures.

R E F E R E N C E S

Adin A., Katzhendler J., Alkaslassy D. and Rav-Acha CH. (1991) Trihalomethane formation in chlorinated drinking water: a kinetic model. Wat. Res. 25, 797-805.

Amy G. L., Chadik P. A. and Chowdhury Z. K. (1987) Developing models for predicting trihalomethane formation potential and kinetics. J. Am. Wat. Works Assoc. 79(2), 89-96.

APHA-AWWA-WPCF (1989) Standard Methods for the Examination o f Water and Wastewater, 17th edn, pp. 79-80 (Edited by Clescery L. S., Greenberg A. E. and Trussel R. K.). Washington, D.C.

Babcock D. B. and Singer P. C. (1977) Chlorination and coagulation of humic and fulvic acids. Proc. 97th Ann. A W W A Conf. Paper 16-6.

Bellar T. A., Lichtenberg J. J. and Kroner R. C. (1974) Occurrence of organohalides in chlorinated drinking water. J. Am. Wat. Works Assoc. 66, 703-706.

EEC (1980) Directiva del Consejo de 15 de Julio de 1980 relativa a la calidad de las aguas destinadas al consumo humano 80/778/CEE. Diario Oficial de las Comunidades Europeas, no. L229/11.

Fawell J. K. and Hunt S. (1988) Chloroform and trihalomethanes. In Environmental Toxicology: Organic Pollutants, Chapters 1 and 2, pp. 15-36. Ellis Horworth Ltd, Chichester, West Sussex.

1308 R.J. Garcia-Villanova et al.

Garcia C., G-Tiedra P., Ruano A., Grmez J. A. and Garcia-Villanova R. J. (1992) Evaluation of the liquid-liquid extraction technique and application to the determination of volatile halo-organic compounds. J. Chromatogr. 605, 251-255.

Garcia C., G-Tiedra P., Ruano A., Grmez J. A. and Garcia-Villanova R. J. (1992) Volatile halo-organic compounds in treated waters of the province of Salamanca (Spain). European Water Pollution Control 2(4), 46-49.

Harrington G. W., Chowdhury Z. K. and Owen D. M. (1992) Developing a computer model to simulate DBP formation during water treatment. J. Am. Wat. Works Assoc. 84(11), 78-87.

Holbom B. (1990) Mutagenic compounds in chlorinated pulp bleaching waters and drinking waters. In Complex Mixtures and Cancer Risk (Edited by Vainio H., Sorsa M. and McMichael A. J.). Lyon International Agency for Research on Cancer, IARC.

Horth H. (1989) Identification of mutagens in drinking water. Aqua 38, 80-100.

Kavanough M. C., Trussell A. R., Cromer J. and Trussell R. R. (1980) An empirical Kinetic model of THM formation: applications to meet the proposed THM standards. J. Am. War. Works Assoc. 72, 578-582.

Klein S. (1990) Bildung von organohalogenverbindungen bei der wasserchlorung. Z. Gesamte Hyg. 36, 532-535.

Kohey V., Hiroshi W. and Takao T. (1983) Empirical rate equation for THM formation with chlorination of humic substances in water. Water Res. 17, 1797-1802.

Kronberg L., Christman R. F., Singh R. and Ball L. M. (1991 ) Identification of oxidized and reduced forms of the strong bacterial mutagen (z)-2-chloro-3-(dichloromethyl)- 4-oxobutenoic acid (MX) in extracts of chlorine-treated water. Environ. Sci. Technol. 25, 99-104.

National Cancer Institute Report on Carcinogenesis (1976) Bioassay of Chloroform Carcinogenesis Program, Div. of Cancer Cause and Prevention, Bethesda, MD.

Nowell L. H. and Hoigne J. (1992) Photolysis of aqueous chlorine at sunlight and ultraviolet wavelengths. Water Res. 26, 593-598.

Onodera S., Nishikawa T. and Suzuki S. (1987) Chemical changes in chlorinated water. XIV. Characterization and determination of halogenated organics formed during chlorination of water from the Tama River. J. Chromatogr. 409, 259 270.

Onodera S., Nishikawa T., Igarashi K., Nishimura A. and Suzuki S. (1989) Chemical changes of organic compounds in chlorinated water. XV. The concentrations and compositions of halogenated organics formed during chlorination of water from the Tama River. Eisei Kagaku 35, 9-18.

Peters C. J., Young R. J. and Perry R. (1980) Factors influencing the formation of haloforms in the chlorination of humic materials. Envir. Sci. Technol. 14, 1391-1395.

Ram N. M. (1986) Experimental significance of trace organic contaminants in drinking water supplies. In Organic Carcinogens in Drinking Water, p. 7. Wiley Interscience, New York.

Rook J. J. (1974) Formation of haloforms during chlorination of natural waters. Water Treat. Exam. 23, 234-243.

Rook J. J., Grass A. A., Van der Heijden J. (1978) Bromide oxidation and organic substitution in water treatment. J. Environ. Sci. Hlth AI3, 91-116.

Sandier R. (1977) Untersuchungen sur buildung von organischen chlorrerbindungen bei der chlorung humin- saurehaltiger wasser. Thesis, Engler-Bunte Institute, University of Karlsruhe.

Simmon V. F. and Tardiff R. G. (1978) The mutagenic activity of halogenated compounds found in chlorinated drinking water. In Water Chlorination: Environmental Impact and Health Effects (Edited by Jolley R. L., Gorcher H. and Hamilton D. H.), Vol. 2, pp. 417-432. Ann Arbor Science, Ann Arbor, MI.

Stevens A. A., Slocum C. J., Seeger D. R. and Robeck C. B. (1976) Measurement of THM and precursor concentration changes. J. Am. Wat. Works Assoc. 68, 546-554.

Suess H. J. (1982) Examination of Water for Pollution Control, Vol. 2, pp. 471-476. World Health Organization Regional Office for Europe, Copenhagen.

Trehy M. L. and Bieber T. S. (1980) Effect of commonly used water treatment processes on the formation of THM. Proc. AWWA Ann. Conf. 1980, pp. 125-138.

Trussell R. R. and Umphres M. D. (1978) The formation of trihalomethanes. J. Am. Water Works Assoc. 70, 604-612.

USEPA (1978) The National Organics Monitoring Survey, Cincinnati, OH.

USEPA Drinking Water (1988) Substitution of contaminants and drinking water priority list of additional substances which may require regulation under the Safe Drinking Water Act. Fed. Reg. 53(14), 1892.

Ventura F. and Rivera J. (1985) Factors influencing the high content of brominated trihalomethanes in Barcelona's water supply (Spain). Bull. Environ. Contam. Toxicol. 35, 73 81.

Water Quality Division Disinfection Committee (1992) Survey of water utility disinfection practices. J. Am. Wat. Works Assoc. 84, 121-128.

WHO (1992) Revision of the WHO guidelines for drinking water quality. Report of the final task group meeting. Geneva (limited distribution document).