Impact and Health Effects”,Vol. 2, Jolley, R. L., et al., Eds., Ann Arbor Science Publishers, Ann Arbor, Mich., 1978, pp 29-48. (18) Rockwell, A., Larson, R. A., in “Water Chlorination: Environmental Impact and Health Effects”, Vol. 2, Jolley, R. L., et al., Eds., Ann Arbor Science Publishers, Ann Arbor, Mich., 1978, pp 6774.
(19) Larson, R. A., Rockwell, A., Enuiron. Sci. Technol., 13, 325 (1979).
(20) Bellas, T. A,, Lichtenberg, J. J.,J . A m . Water Works Assoc., 66, 739-44 (1974). (21) Hus, R. Y., Shimizu, Y., Chesapeake Sci., 18, 129 (1977). Receiced for rei’ieu August 20, 2979. Accepted 1’Vorember 8, 1979. T h i s research is supported in part by E P A Research Grant 1Vo. R804490 f r o m the Municipal Enuironmentai Research Laborator), ( A l a n A . Steuens, Project Officer). This paper is E S E No. 569.
Temporal Variations in Trihalomethane Content of Drinking Water Virginia L. Smith’, kina Cechl*, James H. Brown2, and Gregory F. Bogdan’ Department of Environmental Sciences, The University of Texas Health Science Center at Houston, School of Public Health,
P.O. Box 20186, Houston, Tex. 77025, and the Department of Pediatrics, The University of Texas Medical School at Houston, Houston, Tex. 77025
T h e 24-h variations in concentration of total trihalomethanes, chloroform, dichlorobromomethane, dibromochloromethane, and bromoform in drinking water were assessed in a dynamic system using a solvent-extraction electron-capture gas chromatographic procedure. Measurements were made every 4 h for a 1-week period. Spectral analysis and replicate harmonic regression were used to evaluate temporal patterns in fluctuations of trihalornethanes. Data indicate that for reliable monitoring of trihalomethane concentrations in drinking water, time of sampling is an important factor, inasmuch as both within the 24-h and day-to-day samples, variations were found to be present. T h e United States Environmental Protection Agency has proposed regulations of maximum contaminant levels for total trihalomethanes ( T T H M s ) in public drinking water a t 100 ppb ( I ) . Monitoring under this proposed regulation would require multiple measurements of trihalomethane concentrations, a t least quarterly, for all systems serving more than 10 000 people. Trihalomethane concentration measurements a t specific sites within the distribution system have also been decreed to assure that samples are representative of the water supplied at the consumers’ taps. This proposed regulation further specified collection of two samples for analysis at each site-one for immediate analysis and a second sample to be held a t room temperature for 7 days to permit completion of the halogenation reaction forming trihalomethanes. These requirements imply a recognition t h a t spatial and temporal variations in trihalomethane concentrations are anticipated, but to date there is limited experimental verification of the significance of these factors, particularly in dynamic flowing systems. This communication is the first of a series presenting experimental data confirming the importance of temporal and spatial aspects in environmental monitoring of drinking water. Here we concentrate on the evaluation of temporal patterns in trihalomethane concentrations in drinking water from a system drawing primarily from surface water.
Methods Trihalomethane concentrations were measured every 4 h for 7 days a t a site within the University of Texas Health Science Center. This site is representative of a moderate size The University of Texas Health Science Center at Houston. The University of Texas Medical School at Houston. 190
Environmental Science & Technology
office building housing a population of approximately 750 during working hours and minimally staffed a t night. Nearby hospitals and laboratories use water throughout the 24 h. This site was chosen because: Water distributed within the Houston Medical Center is of surface origin, derived from the San Jacinto River via Lake Houston. This water has been found previously to contain comparatively high concentrations of trihalomethanes. San Jacinto River water is distributed within the City of Houston from a single treatment plant, situated on the eastern side, to approximately 50% of Houston residents. At the present population of 1.75 million, this amounts to nearly 900 000 people. The Medical Center is located approximately 15 km from the water treatment plant. Building security and other facilities allowed the investigators to remain on site for the duration of the study, including nocturnal sampling hours. T h e laboratory measurements could be performed immediately, eliminating sample transport time as a source of variation. Samples were drawn during the week of November 10-17, 1978,at10a.m.,2p.m.,6p.m.,10p.m.,2a.m.,and6a.m.each day from a constantly flowing tap, and analyses were carried out without delay. Fresh standards were prepared and used a t each sampling time. Trihalomethane concentrations (CHClj, CHC12Br, CHCIBri, CHBrl) were assayed using the extractive technique of Glaze and co-workers (2) with electron-capture gas chromatographic determination as adapted in these laboratories. Free residual chlorine was measured by the o-tolidine method ( 3 ) ;p H was measured colorimetrically using phenol red 1. In order to identify sources of variation in concentration of TTHMs, a time series analysis was performed in the following stepwise manner: First, temporal patterns in each of the variables were evaluated separately using lagged autocorrelation and spectral analyses ( 4 , 5 ) in order to detect a potential 24-h cycle, weekly trend, or any other systematic feature and distinguish it from purely random fluctuations. Second, temporal patterns of the individual variables were compared, and the possibility of phase differences between variables was studied by lagged cross-correlation. T h e significance of temporal patterns and the strengths of associations between the variables were tested using procedures originally developed by Tukey (6) and extended by Box and Jenkins ( 7 ) . Further effort was made to approximate mathematically
0013-936X/80/0914-0190$01 .OO/O
@ 1980 American Chemical Society
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Figure 1. Concentrations of total trihalomethanes in drinking water and the ambient conditions in the river basin of origin
the 24-h fluctuations in the concentration of trihalomethanes by a cosine model using the Bliss method of the replicate periodic regression combined with the analysis of variance ( 8 , 9).
Res u 1t s Figure 1 shows concentrations of total trihalomethanes ( T T H M s ) in drinking water over the study periods. For reference, information is also provided (upper part of Figure 1) on ambient environmental conditions in the river basin from which water is derived. During the period of study, air temperature ranged from 7 to 28 "C, with daily peaks in tne early afternoon and the lowest in the early morning hours. Trace amounts of rainfall were reported twice during the study, on Saturday and Thursday. The amplitude of fluctuation in the stages of Lake Houston during this period was 4 cm, with the highest stage reported on the first day of the study and the lowest on the last. There was a slight rise in the stage of the lake corresponding to the second period of rainfall. Data on stages of Lake Houston were obtained from the United States Geological Survey a t Houston. Data on air temperature and precipitation b e r e obtained from the National Weather Bureau's weather station a t Houston Intercontinental Airport. Figure 2 displays the variation in concentration of the individual trihalomethanes. It is apparent that there is a wide variation in total trihalomethane concentrations, from 69 ppb to nearly its double, 132 ppb, and, moreover, there appears to be a periodic rise and fall in these concentrations. The highest levels were observed daily near 10 a.m.; the lowest were observed in the nocturnal hours, between 10 p.m. and 2 a.m. Rapid changes in concentrations were found to occur, by as much as 30 to 40 ppb within 4 h. T h e average concentration of total trihaloinethanes was 98.5 ppb, with the highest level observed on Saturday morning and the lowest on Tuesday evening. The 24-h average concentrations ranged from 116 pph o n Saturday to 86 ppb on Monday. Weekday mean con-
centrations were 94 ppb, while the average trihalomethane concentrations over the weekend, Saturday and Sunday, were 116 and 101 ppb, respectively. Chloroform was the principal trihalomethane measured; its concentration paralleled that of the total trihalomethanes. T h e highest value was on Saturday a t midday, 80 ppb, and lowest on Monday night/Tuesday morning, 33 ppb. T h e Saturday mean daily concentration was 69 ppb, while the Monday mean daily concentration was 44 ppb. T h e weekday average was 49 ppb, while the weekend mean concentration was 56 ppb. Dichlorobromomethane concentration roughly paralleled that of chloroform; however, the maximum concentration was observed on Friday and late Wednesday rather than Saturday. T h e mean concentration was 20 ppb with a range of 13 to 28 ppb. Dibromochloromethane and bromoform concentrations were 11to 31 ppb, averaging 20 ppb, and 4 to 17 ppb, with an average of 8.7 ppb, respectively. T h e pattern was distinctly different for the brominated methanes with maxima occurring near the end of the week as opposed to weekend maxima seen in the predominantly chlorinated compounds. Concurrent measurements of p H and chlorine both showed rather small fluctuations. Free residual chlorine ranged from nondetectable to trace quantities, while p H varied from 7.6 to 7.9 (Figure 3). This figure indicates that pH and free residual chlorine contribute minimally to the wide variability seen in total trihalomethane concentrations. In some instances there even appears to be a phase reversal in that high values of p H and chlorine accompany low trihalomethane concentrations, while elevated trihalomethane levels coincide with lower p H and chlorine. These apparently anomalous results should be considered in their true perspective. Le.: (a) T h e measurement of free residual chlorine was near the detectable limit, where the dependability of the reading would be expected to be the lowest. (b) The variation in acidity was maximally only 0.3 of a p H unit. (c) T h e sampling site is at least 15 km from the treatment plant; thus, it is anticipated that the effects of these small fluctuations might be partially obscured by the long travel time from the water Volume 14, Number 2, February 1980
191
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treatment plant to the point of measurement. Temperature variations in t a p water were measured during a portion of the study (Figure 4). Although little variation was expected, water temperature was found to fluctuate from 25 to 38 “C. Temperature generally peaked during the early 192
Environmental Science & Technology
morning hours, while lower values were observed a t night. The lag between water temperature a t the tap and air temperature a t the source is due t o a difference in conductivity between water and air, and also reflects travel time of a half day or more from the water treatment plant to the sampling site. Figure 5 presents the autocorrelation curves derived for studied variables. T h e autocorrelation measures similarity of a time series with a delayed version of itself. I t is always maximal a t lag zero and in the case of a random series is expected to rapidly decay to zero a t the introduction of a time shift between the series and its image. Such a pattern was found for CHClBr2 and for the p H series, suggesting random fluctuations unrelated to time. For the series of free residual chlorine, there was a noticeable rebound in the coefficient of correlation to positive values when the time shift approached 24 h. This suggests some repetitions in fluctuation of content of free residual chlorine over a 24-h interval. T h e autocorrelations for T T H M s , CHC13, CHCl*Br, and CHBr:j suggested a different pattern. For these time series, the coefficient of correlation remained high a t nonzero lags. Such lagged autocorrelation suggests a trendlike persistence in the fluctuation of trihalomethanes. This persistence is highly significant statistically as revealed by the next step of the data evaluation. I t is also noteworthy t h a t for all trihalomethanes, except for CHBr:], the coefficient of correlation rose as lags approached 24 h, again suggesting some daily cyclic repetition. T h e spectra shown in Figure 6 represent a partitioning of the overall variance in the data to show the contribution of fluctuations over various lengths of time. If there were no prominent temporal patterns in the data set, all fluctuations over any length of time would be contributing equally and the resultant spectra would be rectangular in shape. T h e examination of Figure 6 suggests t h a t CHClBrZ, p H , and free residual chlorine had such random spectra (upper and lower 95% confidence limits of the reference random spectra are shown). However. for T T H M s , CHCl:I, CHC12Br, and CHBrx, the contribution of the fluctuations over the period longer than 24 h was significantly higher than expected of randomly occurring events. T h e variation in this range of time accounted for about 60% of a total. T h e lagged cross-correlation analysis provided the means for measuring temporal associations of T T H M s with specific trihalomethanes and with other water characteristics. The curves on Figure 7 are formed by sets of computed cross-correlation values displayed against corresponding time shifts
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(both positive and negative) of each studied series with respect to the series of TTHMs. T h e right-hand portion of the graphs, corresponding t o negative time shifts, gives the cross-correlation of T T H M s on moment n with a given specific compound on moment n - h , or h measurements earlier. T h e portion of the curve on the left-hand side of the graphs represents t h e cross-correlation of T T H M s on moment n and of specific compound on moment n h . T h e lagged cross-correlation curve of T T H M s and CHC13 was very symmetric. T h e highest correlation, R = 0.87, was at lag zero, or for simultaneous readings. Most other coeffi-
+
cients of correlation were positive and there was a secondary rise a t 24-h shifts, both backward and forward, which suggests t h a t the 24-h cyclic repetitions, although not exceptionally strong. tend t o be common to these series. A very similar pattern was found for T T H M s correlation with CHC12Br. The coefficient of simultaneous correlation was equal to 0.82. For T T H M s and CHClBr2, this coefficient was 0.57 and still statistically significant ( p < 0.05). An entirely different picture was seen for lagged correlation between T T H M s and CHBr3. T h e coefficient of simultaneous correlation was equal to -0.1 and all other correlation coefVolume
14, Number 2,
February 1980 193
Table 1. Analysis of Variance of the Total lTHMs Concentrationa source of variation
df
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6 2 3 12 18
3 367.2381 1846.0476 373.2143 1501.6190 2 308.2857
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561.2063 923.0238 124.4048 125.1349 128.2381
4.3763 7.6093 0.9701 0.9758
(6, 18) (2, 1.99) (3, 18) (12, 18)
72.6273 177.6425
0.5663 1.3853
(6, 18) (6, 18)
a Fundamental harmonics with period of 24 h is fitted to replicate days (methodology after Bliss, ref 8). Statistically significant ( p < 0.05) variation between replicatedays.
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curve, derived in such a way, and its mean, amplitude, and phase are shown in Figure 8. I t follows from this figure and from the analysis of variance in Table I that this average curve, when fitted t o each of the 7 replicate days, did not show substantial discrepancy in the amplitude or in phase. Such an average curve, however, was not strong enough to account for a statistically significant amount of variance (some 20% of the total variance about the mean). Significant variation ( p < 0.05) was found to exist, however, between replicates or in mean values of 24-h periods.
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iron.Health Persp., 24, 209 (1978). (13) Laxen, D. P. H., Harrison, R. M., Water Res., 11, l ( l 9 7 7 ) . (14) Stevens, A. A,, Slocum, C. J., Seeger, D. R., Robeck, G. G., “The Environmental Impact of Water Chlorination”, Oak Ridge National Laboratory, Oak Ridge, Tenn., 1976.
Literature Cited (1) Fed Regzst , 43 (No. 28) (Feb 9, 1978). ( 2 ) Keith, “Identification and Analysis of Organic Pollutants in Water”, Ann Arbor Science Publishers, Ann Arbor, Mich., 1976, p 105.
Receiced f o r rerieu, May 8 , 1979. Accepted Noisember 9, 1979. T h i s incestigation was supported in part by Grant X o , 1 ROl CA24138-01, aii,arded by t h e National Cancer Institute, D H E W , t o Irina Cech, Ph.D. (principal inuestigator).
Photolysis of Pentachlorophenol-Treated Wood. Chlorinated Dibenzo-p-dioxin Formation Lester L. Lamparski” and Rudolph H. Stehl Analytical Laboratories, Dow Chemical U.S.A., Midland, Mich. 48640
Robert L. Johnson Designed Products Department, Dow Chemical U.S.A., Midland, Mich. 48640
Laboratory studies have been conducted to determine the effect of sunlight on the concentrations of pentachlorophenol ( P C P ) and chlorinated dibenzo-p-dioxins (CDDs) in wood treated with PCP. Wood samples were treated with technical P C P , Dowicide EC-7 antimicrobial, and purified PCP. Irradiation experiments were designed using either artificial sunlamps or natural sunlight. P C P determinations were made by flame ionization gas chromatography, and dioxin determinations were made by electron-capture gas chromatography and gas chromatography-mass spectrometry. Photolytic condensation of P C P to form octachlorodibenzo-p-dioxin (OCDD) was observed on a wood substrate. This effect was greatly reduced by the addition of a hydrocarbon oil (example: P - 9 oil). OCDD concentrations in photolyzed wood samples ranged from 4 pg/g of P C P for Dowicide EC-7 and purified P C P to -1500 pg/g of technical P C P when both were stabilized with hydrocarbon oil. Data on the distribution of CDDs as a function of depth are also presented. Pentachlorophenol (PCP),which is commonly used as a wood preservative, can contain chlorinated dibenzo-p-dioxins (CDDs) as impurities ( I ) .Technical P C P has been reported t o contain chlorodiphenyl ethers, chlorodibenzo-p-dioxins, 196
Environmental Science & Technology
chlorodibenzofurans, and hydroxychlorodiphenyl ethers; the octachlorodibenzo-p-dioxin (OCDD) content of technical P C P is typically 500-1500 ppm (2). Purified P C P Dowicide EC-7 (trademark of T h e Dow Chemical Co.) contains much lower levels of these impurities. Specification levels of hexachlorodibenzo-p-dioxins (HxCDD) and OCDD are 1 and 30 ppm, respectively ( 1 ) . Although a wide variety of CDDs have been reported in the environment (3-5) from a variety of both natural and synthetic sources, little information exists to allow identification of the routes for occurrence of these compounds in the environment. Thermal stresses, both combustive and pyrolytic, have been reported to produce CDDs. T h e photolytic condensation of chlorophenols has been widely studied. Irradiation of aqueous solutions of 2,4-dichlorophenol and 2,4,5-trichlorophenol gave little reaction unless a sensitizer such as riboflavin was present. Reaction products were chlorophenoxyphenols and chlorodihydroxybiphenyls (6). In these studies CDDs could not be detected in the reaction products by electron-capture gas chromatography (EC-GC). In alkaline aqueous solutions, however, the condensation of P C P to form OCDD proceeds quite readily ( 7 , R ) . Also, photolysis of OCDD has been shown to yield a variety of CDDs of decreasing chlorine content (9-1 1). Recently, because of concern over the formation of CDDs
0013-936X/80/0914-0196$01.00/0
@ 1980 American Chemical Society
