by-products, chloroform in drinking water, haloforms, drinking water treatment plants ... plant); Fn: filtered water in the new plant; Fc: filtered chlorinated and pH ...
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Pergamon PII: S0043-1354(96)00335-1
Wat. Res. Vol. 31, No. 6, pp. 1299-1308, 1997 © 1997 ElsevierScienceLtd All rights reserved. Printed in Great Britain 0043-1354/97 $17.00 + 0.00
FORMATION, EVOLUTION AND MODELING OF T R I H A L O M E T H A N E S IN T H E D R I N K I N G W A T E R OF A TOWN: I. AT T H E M U N I C I P A L 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*, C E S A R 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, R o o k (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 ( D B P s ) - - m a n y 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 recommendations or regulations about the maximum levels of several groups of DPBs (EEC, 1980; U S E P A , 1988; W H O , 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
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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 occurring 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 (river Tormes)
OLD PLANT
NEW PLANT
R
N
[
I. CI2 gas (prechl°rinatiOn) i
Clarifier
Clarilier
g~
I g=
1
Fn + c,o L_
(poslchlodn~ion)jI
I Na()H I.
I
I Postchlodnated I
p.
i F
Fe
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 indicatesthe meandosageduringthe periodof study. The postchlorinationdosage at the new plant is expressedkg/m-~of chlorine,but it actuallyrepresentsthe sum of CI.,+ CIO:in approximatelyequimolaramounts
Flow (l/s) Cl., or CIO2dosage (kg/m3) (x) Prechlorinafion (x) Postchlorination Treatment process time (h)
Old
New
400
600
2.15 0.98 2
2.67 1.67 2
16,0
.
1301 TrHM
• New plant
D Oldplant
f
f
~
13,0-
10,0
-
7,0-
Cp,Cn
Fo.Fn Samplingpoints
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
Fig. 3. Evolution of the two measurable (>D.L.) 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 F'mishedwater
3O,O
T('C) ~(~L)
15,0
~
• C~oroform 12,0-,
[ ] Dfd,lorobromomethane
20,0
9,0.
10,0
6,03,0 -
0,0 0
0,0 Ca
Cp
Fo
Cn
Fn Fc M Samplingpoints
Fig. 2. Nature and mean concentrations of THMs found in seven sampling points of the two plants (old and new).
I
I
I
4
6
S
I
10 Sample
12
Fig. 4. Evolution of temperature and TTHM (chloroform + dichlorobromomethane) for the finished water (point M) during the period of study (February through to July).
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R. J. Garcia-Villanova et al.
Table2. ANCOVAtest for dependenceof productionof chloroformon both temperature and samplingpoint Variable Coefficient Std Error t - v a l u e 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. Correlationvalues(r) betweenhumicacid amount in raw water (H.A.-R.)and chloroform(CHCh) productionin 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
1.457 1.599 1.818 2.393 2.840 2.945 2.114 2.020 2.181 ---
Prechlor.
0.727 0.779 1.090 1.104 1.363 0.920 0.845 0.808 1.163
Postchlor. 6.0 4.5 9.5 9.5 13.0 15.0 24.0 22.0 21.0 23.5 26.0
0.20 0.40 0.31 0.52 0.34 0.18 N.D. 0.22 0.38 0.30 0.02
T Humic acid (
