Predictions of Potential Human Health and Ecological Risks from

Predictions of Potential Human Health and Ecological Risks from Power Plant Discharges of Total Residual Chlorine and Chloroform into Rivers. William ...
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Environ. Sci. Technol. 1998, 32, 2162-2171

Predictions of Potential Human Health and Ecological Risks from Power Plant Discharges of Total Residual Chlorine and Chloroform into Rivers WILLIAM B. MILLS,* CHRISTINE S. LEW, AND JOHN Y. LOH Tetra Tech, Inc., Applied Research and Development Division, 3746 Mt. Diablo Blvd., Suite 300, Lafayette, California 94549

Low levels of chlorine residual and the trihalomethane chloroform can be released from power plant discharges and enter natural surface water bodies. Such effluents may pose potential human health and ecological risks. To evaluate these risks, a model was developed and applied to a time-variable release of these constituents into a river. The release pattern and dose are typical of power plants. In situ formation of chloroform is also simulated. The model is applicable to situations where chloroform is the dominant trihalomethane. Therefore, the model is limited to water with low background bromide ion concentrations (approximately 50 µg/L or less). For the scenario evaluated, predicted total residual chlorine levels, expressed in terms of a hazard quotient for the protection of aquatic organisms, are above EPA criteria at locations to within approximately 5 km downstream of the discharge; excess lifetime risk to an individual exposed to predicted levels of chloroform in the river range from 5 × 10-7 to above 10-6, a degree of risk that is close to levels of concern to regulatory agencies. Background. Since the mid-1970s, it has been documented (1-3) that trihalomethanes form as a result of the chlorination of natural waters. Trihalomethanes (chloroform, dichlorobromomethane, dibromochloromethane, and bromoform) are possible human carcinogens as characterized in the Integrated Risk Information System (IRIS) (4) and pose a potential threat to human health. Using cancer slope factor information from IRIS, the concentrations of trihalomethanes in drinking water that would cause excess lifetime cancer risks that range from 10-6 to 10-4 are shown in Table 1. Exposure pathways are limited to domestic uses of drinking and showering. All exposure information used in the calculation is included in Table 1 and is consistent with Environmental Protection Agency (EPA) guidelines. As shown in the table, individual trihalomethane concentrations on the order of 0.1-10 µg/L can produce 10-6-10-4 excess lifetime cancer risks. In 1979, a maximum contaminant level (MCL) was established for total trihalomethanes at 100 µg/L (5). In 1994, a rule was proposed to reduce the MCL for total trihalomethanes to 80 µg/L (6). Recently, the U.S. EPA proposed new, more strict, water quality criteria for trihalomethanes to protect human health in a rule proposed for the * To whom all correspondence should be addressed. Phone: 925283-3771; fax: 925-283-0780; e-mail: [email protected]. 2162

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state of California. The rule’s intention is to fulfill the requirements of the Clean Water Act of the state. Currently, the state of California is without numeric water quality criteria for many priority toxic pollutants, as required by the Clean Water Act (7). The concentrations proposed are 5.7 µg/L (chloroform), 0.56 µg/L (dichlorobromomethane), 0.41 µg/L (chlorodibromomethane), and 4.3 µg/L (bromoform). The criteria in the Federal Register are based on a risk level of 10-6 via the ingestion pathway, and the concentrations in Table 1 differ because both ingestion and showering pathways are considered. This paper focuses on the single trihalomethane chloroform, which is the dominant trihalomethane in water with low background levels of bromide, typical of the waterways on which many power plants are located. When chlorinated effluents are discharged to surface water, both residual chlorine and chloroform may be present in the effluent. Since excessive chlorine residuals adversely impact aquatic organisms, such discharges potentially affect both human health and aquatic organisms. Once the chlorine-containing effluents have been discharged, chloroform may also form in situ, thus potentially exacerbating human health risks. The purpose of this paper is to document the development and application of a framework to model both chlorine residuals and the trihalomethane chloroform in rivers. Discussion of Relevant Studies. To control biofouling of heat exchangers in once-through cooling power plants, approximately 90% of such plants chlorinate cooling water on a periodic basis (as compared to a continuous basis for water and wastewater treatment). Typically, chlorine is dosed at 1-2 mg/L for 20-30 min two or three times daily. However, chlorine application patterns may vary (8). To minimize chlorine residuals in once-through cooling systems, chlorinated effluent from one group of condensers may be diluted with nonchlorinated effluent from the remaining condensers, or targeted chlorination may be practiced (9). For cooling tower applications, chlorine residuals are often less than those from once-through cooling systems (typically 0.2 mg/L). In a study on chlorination of cooling water in nuclear power plants, total residual chlorine in discharged water ranged from 0.1 to 1.0 mg/L (10). Review of Previous Modeling Studies. A number of researchers have simulated the transport of chlorine residuals through drinking water systems (11-14) and in rivers (15, 16). Models to predict trihalomethane formation in water distribution systems have also been developed (17-23). Also, models to predict the trihalomethane formation potential (TTHMFP) in drinking water supplies have been developed, based on transport models that simulate precursors and assume the ambient water is later chlorinated (24-28). However, the models that predict TTHMFP do not simulate the actual formation of trihalomethanes in natural systems; they only simulate the potential formation of trihalomethanes once the river water is withdrawn and treated with chlorine. In contrast, the model developed here predicts actual levels of the trihalomethane chloroform in rivers at the site where chlorine residuals have been discharged. Conceptual Model for Power Plant Discharges and in Situ Chloroform Formation. The conceptual model of the release and fate of total residual chlorine and chloroform is shown in Figure 1. The effluent total residual chlorine and chloroform concentrations are depicted as variable over time. The time-variable releases shown here are typical of power plant discharges, where periodic dosing of condensers is a normal practice. S0013-936X(97)00209-5 CCC: $15.00

 1998 American Chemical Society Published on Web 06/04/1998

TABLE 1. Concentrations of Trihalomethanes in Drinking Water That Produce Excess Lifetime Cancer Risks from 10-6 to 10-4 for the Exposure Scenario Shown, and Water Quality Criteria for Total Residual Chlorine concentration (µg/L) such that lifetime cancer risk is chemical

10-6

10-5

10-4

chloroform bromodichloromethane dibromochloromethane bromoform

0.15 0.16 0.8 8.5

1.5 1.6 8 85

15 16 80 850

water quality criterion (µg/L) 4 day average

1 h average

11

19

total residual chlorine input data for exposure scenario

adult

child

body weight (kg) exposure duration (years) ingestion of drinking water ingestion rate (L/day) exposure frequency (days/year) dermal contact while showering skin surface area (cm2) exposure time (h/day) exposure frequency (days/year) ingestion while showering ingestion rate (L/day) exposure frequency (days/year) inhalation while showering water discharge rate (L/min) vol of shower (m3) residence time in shower (min) inhalation rate (m3/h) exposure time (h/day) exposure frequency (days/year)

70 24

15 6

2 350

1 350

23 000 0.25 350

7600 0.25 350

0.05 350

0.05 350

10 2 20 0.6 0.25 350

10 2 20 0.6 0.25 350

chemical parameters

dibromochloromethane

chloroform

bromodichloromethane

bromoform

skin permeability constant (cm/h) chemical transfer efficiency oral slope factora (mg/kg/day)-1 inhalation slope factora (mg/kg/day)-1

0.0039 0 0.084 0.084

0.13 0.56 0.0061 0.081

0.0058 0.58 0.062 0.062

0.0026 0 0.0079 0.0039

a

Source of slope factors, ref 4.

The model assumes that discharge characteristics are known (i.e., the model does not calculate the chlorine residual in the effluent, relying instead on monitoring data), and the responses (i.e., concentrations and risks) are calculated for specified exposure point locations downstream. In-stream formation of chloroform is also simulated. The kinetic framework developed for total residual chlorine decay and trihalomethane formation is shown in Figure 2. Due to the speed of the reactions, equilibrium is assumed to exist between HOCl, CL2(aq), OCl-, and the chloramines. Firstorder rates are assumed for the formation and decay of the trihalomethanes, volatilization of HOCl and Cl2(aq), and decay of trihalomethanes. The rates shown are composite rates representing all relevant processes including volatilization, which is an important loss mechanism for the trihalomethanes. Stoichiometric coefficients are employed to predict the yield of the breakdown products (such as chloroform) for each relevant pathway. A detailed presentation of the chemical relationships and methods for solving the resulting systems of equations is presented in the Appendix. Releases are typically along the side of one river bank so that lateral concentration gradients exist in the river. Vertical concentration gradients are ignored as vertical mixing is assumed to be faster than lateral mixing and is essentially complete at exposure locations. Since human health risks from exposure to chloroform are carcinogenic and are typically based on as many as 30

years of exposure, the river flow rate that is appropriate to use for predictions of human health risks is the harmonic mean flow, QHM (29). For ecological risks, however, exposure durations that can produce an adverse effect from total residual chlorine is much shorter. Therefore, low-flow conditions, such as the 7 day consecutive flow that reoccurs once every 10 years, Q7-10, are more appropriate for ecological risk screening. Uncertainties of the model input data may be accommodated using the Monte Carlo technique (30). Input data that can be treated as random variables include chlorine residual decay rates, stoichiometric yield ratios, and formation rates. However, for the research reported in this paper, all analyses were performed deterministically. To develop the input required for this model, the databases developed by Amy et al. (18) and Krasner et al. (22) were reviewed. Since the focus of this paper is freshwater with low bromide ion concentration, the portions of those databases with water samples containing less than 50 µg/L of background bromide were extracted. At those low bromide concentrations, chloroform compressed most of the total trihalomethane concentrations. At higher bromide ion concentrations, a larger fraction of the total trihalomethane contained brominated compounds. Therefore, the present model is applicable to water with low bromide ion concentrations (50 mg/L or less). Also from the Amy et al. (18) data set, stoichiometric chloroform formation coefficients were calculated. Since VOL. 32, NO. 14, 1998 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 1. Total residual chlorine and chloroform time and spatial variability that result from periodic doses of total residual chlorine and chloroform.

FIGURE 2. Kinetic framework for total residual chlorine and trihalomethane formation. some of the conditions in the database were not typical of many rivers; a subset of the data was selected that more closely corresponds to natural conditions (5.0 e pH e 8.5; 5 µg/L e bromide ion < 50 µg/L; 1.1 mg/L < TOC < 5 mg/L; 0.0 mg/L e ammonia nitrogen < 0.63 mg/L). The mean of 2164

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the calculated stoichiometric coefficients is 6.2 × 10-3. Thus, for a given river, or even similar rivers, the stoichiometric formation coefficient could be treated as a random variable, perhaps uniformly distributed about 6.2 × 10-3, with a range of approximately 3 × 10-3 to 1.1 × 10-2 (the range calculated

Approach for Calculating Human Health and Ecological Risks. Human health risks are predicted using standard EPA protocols and are consistent with Risk Assessment Guidance for Superfund (33). The total lifetime carcinogenic risk (RCT) is given by all pathways all chemicals

RCT )

∑ i

∑

(CDIij × SFij)

(3)

j

where CDIij is the chronic daily intake over pathway i for chemical j average over 70 years (mg/kg/day), and SFij is the slope factor over pathway i for chemical j (kg day/mg). This formulation assumes that (1) carcinogenic risks from multiple chemicals are additive and no consideration is given for type of cancer and (2) equal weights are given to different classes of carcinogens. A screening approach to ecological risk calculations is used. Risks to aquatic organisms are evaluated for each chemical in terms of the hazard quotient, which is defined by

HQi )

FIGURE 3. Decay of chlorine residual and formation of chloroform in California aqueduct headwaters (26). (The decay rates and formation rates are all assumed to be first order and were calculated by fitting the curve that predicts the rate of decay, or formation, to the observed data. The observed data are shown by the data points; the model predictions are shown by the lines.) from the data of Amy et al.). The approach of using a stoichiometric formation coefficient should be used only within the range of natural conditions outlined above. The complexities of trihalomethane formation, under more general conditions, are discussed by Amy et al. (18) and Krasner et al. (22). As a comparison, stoichiometric yields were calculated from raw data provided from the earlier work of McGuire et al. (31). An illustration of the data from that study to predict chlorine residual decay and chloroform formation rates compared with predictions is shown in Figure 3. For the eight water samples selected, the stoichiometric yield coefficients were remarkably consistent for chloroform (5.0 × 10-3 to 8.8 × 10-3 mol/mol). Definition of Chlorine Residual. The purpose of the chlorine residual analysis is, first, to predict the fate of total residual chlorine, free residual chlorine, and chloramines in rivers and, second, to provide the precursor chlorine residual needed in trihalomethane formation. The definitions of free residual chlorine (FRC) and total residual chlorine (TRC) are

FRC ) 2[Cl2] + [HOCl] + [OCl-]

(1)

TRC ) FRC + [NH2Cl] + 2[NHCl2] + 3[NCl3]

(2)

where [Cl2] is the dissolved concentration of chlorine; [HOCl] is the concentration of hypochlorous acid; [OCl-] is the concentration of hypochlorite ion; [NH2Cl] is the concentration of monochloramine; [NHCl2] is the concentration of dichloramine; and [NCl3] is the concentration of trichloramine. Typically, the concentration of free chlorine, [Cl2], is negligible in eq 1, and the concentration of trichloramine, [NCl3], is negligible in eq 2 (32). The relationships between the chemical species in eqs 1 and 2 are based on chemical reactions illustrated in Figure 2 and detailed in the Appendix.

CWi WQi

(4)

where CWi is the concentration of chemical i in river water (mg/L) and WQi is the water quality criterion for freshwater organisms for chemical i (mg/L). Application and Discussion. The model was applied to a power plant discharge scenario. A power plant was selected with a generating capacity of 350 MW, which is in the median generating capacity size class. The power plant is located along a river approximately 140 m wide and 1.5 m deep when the flow rate is 32 m3/s. Daily stream flow data for this river was downloaded from the USGS Surface-Water Data Retrieval Site on the Internet (http://h2o.usgs.gov/swr/). The Q7-10 and harmonic mean flows were calculated for the entire period of record (1927-1993) to be 30.9 and 87.1 m3/s, respectively. The chlorine release scenario involves a daily 2 h release. A total residual chlorine concentration of 1.0 mg/L is released into 14.9 m3/s of cooling water. This represents a typical release scenario (8). For the scenario, the chloroform concentration in the effluent is 5 µg/L. The discharge to the river was modeled as input through a diffuser 10 m in length beginning at the edge of the river and oriented perpendicular to the flow. The remaining input parameters are based on the sources discussed previously (4, 30). Results from the modeling effort include predictions of total residual chlorine and chloroform in the river. The Q7-10, representative of low-flow conditions, was used to generate results for total residual chlorine. All results are presented along the same shoreline of the river as the diffuser. Figure 4a presents the total residual chlorine hazard quotients in the river versus time for locations 1000 and 5000 m downstream of the discharge along the near-shore with respect to the discharge. The daily pulse release is apparent by a peak on each day. The hazard quotients, based on the 1 h criteria shown previously in Table 1, are well above unity, and indicate a potential ecological concern with chlorine residual. Carcinogenic human health risks from exposure to chloroform in river water were also evaluated for the common pathways of inhalation, ingestion, and dermal contact. For exposure from showering, ingestion, crop irrigation, and swimming, an individual was assumed to use domestic water that contained the same chloroform concentrations as the river water (i.e., the water is untreated). The harmonic mean flow rate was used for human health risk prediction. Human health risks were evaluated for a typical individual and high-end exposed individual, consistent with EPA VOL. 32, NO. 14, 1998 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 4. River concentration versus time. guidelines. For the scenario used here, risks were calculated deterministically as the effort to evaluate risks as a random variable for a time-variable discharge on personal computers would be too great. Exposure parameters that differed for the typically and high-end exposed individual are body weight, exposure duration, tap water ingestion rate, skin

surface area, shower duration, skin surface area for soil exposure, and soil adherence factor. Values for the remaining exposure parameters are U.S. EPA default values. More information on the specific values of the exposure parameters is provided in Lew et al. (34). Risks were predicted for a location 1000 m downstream of the discharge and are based on the assumption that the modeled release pattern is repeated for the entire exposure duration. Concentrations averaged over the period of exposure were used for the risk calculations. Risks for the typical individual were estimated to be 6.0 × 10-7, and risks for the high-end exposed individual were estimated to be 1.4 × 10-6 (excess lifetime cancer risks) at the end of the exposure periods. A risk of 10-6 is generally considered a level of concern. The total risks to the two individuals over time are shown in Figure 5. The risk to the typical individual accumulates more slowly over time than does the risk to the high-end exposed individual due to differences in exposure factors. The risk to the typical individual stops increasing after 15 years while the risk to the high-end individual continues to increase for another 25 years, due to differences in exposure durations for these two individuals. The slopes of both lines change at 6 years because for the first 6 years the risk to the child is simulated and for all subsequent time the risk to the adult is simulated. Approximately 95% of the risk is incurred via inhalation of volatilized chloroform while showering; ingestion of water contributes approximately 2% and the other pathways contribute only slightly to the risk. The chloroform concentration versus time from which the risks were generated is shown in Figure 4b. Peak concentrations at 1000 m and along the near shore are on the order of 2.6 µg/L. This concentration is well below the typical concentration of 21 µg/L found in potable water (1); nevertheless, when compared to concentrations that can produce 10-6 excess lifetime cancer risks (see Table 1), this concentration is significant. A sensitivity analysis was performed to evaluate the input data most important in effecting changes in exposure point concentrations. The results of these analyses are shown in Table 2. Two scenarios were examined: scenarios 1a and

FIGURE 5. Predicted total excess lifetime cancer risk from exposure to chloroform. 2166

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TABLE 2. Sensitivity Analysis Results Scenario 1a: Example Application in Paper, Except Chloroform Concentration in Discharge is 0.0 µg/L perturbed variables value endpointa value % change from base case stoichiometric yield of chloroform (-) 1/4 base 1/2 base base 2 base 4 base chloroform formation rate (1/day) 1/4 base 1/2 base base 2 base 4 base duration of release (h) 1/4 base 1/2 base base 2 base 4 base chloroform decay rates (1/day) 1/4 base 1/2 base base 2 base 4 base

0.002 0.004 0.008 0.016 0.032

0.000 08 0.000 15 0.000 30 0.000 61 0.001 22

-75% -50% 0% 100% 300%

0.225 0.45 0.9 1.8 3.6

0.000 08 0.000 15 0.000 30 0.000 61 0.001 22

-75% -50% 0% 100% 300%

30 60 120 240 480 0.0015 0.003 0.006 0.012 0.024

0.0003 0.0003 0.0003 0.0003 0.0003 0.0003 0.0003 0.0003 0.0003 0.0003

Scenario 1b: Example Application with Chlorine in Discharge ) 5 µg/L perturbed variables value endpointa value stoichiometric yield of chloroform (-) 1/4 base 1/2 base base 2 base 4 base chloroform formation rate (1/day) 1/4 base 1/2 base base 2 base 4 base duration of release (h) 1/4 base 1/2 base base 2 base 4 base chloroform decay rates (1/day) 1/4 base 1/2 base base 2 base 4 base

perturbed variablesb

a

-0.010% -0.0068% 0% 0.014% 0.042%

0.225 0.45 0.9 1.8 3.6

2.2107 2.2107 2.2109 2.2112 2.2118

-0.010% -0.0068% 0% 0.014% 0.042%

2.2109 2.2109 2.2109 2.2109 2.2109 2.2112 2.2111 2.2109 2.2105 2.2098

Scenario 2: Same as Scenario 1b value endpointc value

body weight (kg)

Peak chloroform concentration at receptor point (µg/L).

0.42 1.3 2 2.7 3.8 0.055 0.11 0.243 0.333 40 70 100 130 b

% change from base case

2.2107 2.2107 2.2109 2.2112 2.2118

0.0015 0.003 0.006 0.012 0.024

time spent in shower (h)

0.0062% 0.0043% 0% -0.0082% -0.025%

0.002 0.004 0.008 0.016 0.032

30 60 120 240 480

drinking water ingestion rate (1/day)

0% 0% 0% 0% 0%

1.125 × 10-6 1.129 × 10-6 1.133 × 10-6 1.136 × 10-6 1.142 × 10-6 7 × 10-7 8.266 × 10-7 1.133 × 10-6 1.340 × 10-6 2.015 × 10-6 1.385 × 10-6 9.970 × 10-7 1.340 × 10-6

0% 0% 0% 0% 0% -0.013% -0.0086% 0% -0.016% -0.05%

% change from base case -0.72% -0.32% 0% 0.32% 0.82% -38% -27% 0% 18% 78% 22% 0% -12%

Variables shown are for adult. c Human Health Risk at end of exposure period.

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1b, where the endpoint is peak chloroform concentration at the receptor location. These two scenarios differ from each other only in the discharge chloroform concentration: scenario 1a assumes no chloroform is in the discharge; scenario 1b assumes 5 µg/L of chloroform is in the discharge. Scenario 2 is the same as scenario 1b except the endpoint is human health risk. For scenarios 1a and 1b, variables perturbed are stoichiometric yield of chloroform, chloroform formation rate, chloroform decay rate, and duration of release. For scenario 1a, the results are most sensitive to stoichiometric yield and formation rate and least sensitive to the duration of release and chloroform decay rates. For scenario 1b, all sensitivities are diminished, because the concentration of chloroform in the effluent is a dominant factor that controls the peak concentration. In scenario 2, where risk is the endpoint evaluated, the time spent in the shower and body weight are most significant. The drinking water ingestion rate, however, is not important, since the risks are driven by showering, not water ingestion. Complete model validation has not been completed (i.e., the model’s capability to predict observed in situ chloroform data of the resolution needed to compare against the predictions in Figure 5b was not attempted). Historically, researchers have been much more concerned with the formation of chloroform after river water is withdrawn, dosed with chlorine, and distributed for drinking water purposes. Much less concern has existed regarding in situ formation of chloroform from low-chlorine residuals of the type examined here; therefore, data to validate the model is not yet available. However, this work shows that, from both a human health point of view and ecological health point of view, the release of low levels of chlorine residuals deserves attention. Although model validation was not accomplished, an extensive review of the historical data on chloroform formation from data sets produced by McGuire et al. (31), Amy et al. (18), and Krasner et al. (22) show that the kinetic approach developed here for chloroform formation is a plausible one.

Chlorine can also react with inorganic constituents in the water column. For the analysis here, the reaction with ammonia is considered to dominate; reduced species such as Fe(II) and Mn(II) are assumed to be negligible in oxygenated surface waters. Dissolved ammonia and hypochlorous acid react to produce monochloramine:

HOCl + NH3 T NH2Cl + H2O KN1 ) 10+9.56 at 25 °C

where KN1 is the equilibrium constant for eq A-3 at 25 °C. The monochloramine then reacts with hypochlorous acid to produce dichloramine:

NH2Cl + HOCl T NHCl2 + H2O KN2 ) 10-6.12 at 25 °C

Appendix

CTRC )

Ka[HOCl] 2[HOCl][H+][Cl-] + [HOCl] + + Kh H+ [NH3][HOCl]KN1 + [NH3][HOCl]2KN1KN2 (A-5)

where CTRC is the concentration of total residual chlorine. On the basis of the equilibrium relationships embodied in eqs A-1-A-4, eq A-5 can be written in terms of [HOCl] as follows:

{

Kh ) 4 × 10

at 25 °C

(A-1)

where Kh is the equilibrium constant for this disproportionation reaction. Hypochlorous acid is a weak acid that dissociates as follows:

2168

9

-1

(A-6)

Typically [NH3(aq)][HOCl]KN1KN2 , 1 (typical orders of magnitude estimates are 10-7-10-6), so that eq A-7 can be written as follows:

{

1+

CTRC +

}

-

Ka 2[H ][Cl ] + + + [NH3(aq)]KN1 Kh [H ] (A-7)

The interaction between the species of chlorine is shown in Figure 2. Also shown is the pathway for trihalomethane formation. Assuming two-dimensional concentration distributions, the transport equation for total residual chlorine is:

{

-CTRC{RCl2[2kv(Cl

2

γ1 ) Cl2

+

2 2k8γCl ] 2

}

(A-2)

ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 32, NO. 14, 1998

1 + RHOCl[k6γHOCl +

2 3 4 5 6 kvHOClγHOCl + k14γHOCl + k24γHOCl + k34γHOCl + k44γHOCl ]+ 1 2 + k29γNH ]} (A-8) ROClk7γOCl + RNH2Cl[k19γNH 2Cl 2Cl

) -kTRCCTRC

HOCl T H+ + OClpKa ) 7.5 at 25 °C

}

[NH3(aq)][HOCl]KN1KN2

∂CTRC ∂CTRC ∂2CTRC ∂2CTRC +  ) + u∞ - y x ∂t ∂x ∂y2 ∂x2

Cl2 + H2O T HOCl + H+ + Cl-4

Ka 2[H+][Cl-] + + + [NH3(aq)]KN1 + Kh [H ]

[HOCl] ) CTRC 1 +

[HOCl] )

This appendix contains the mathematical details embodied in the model to predict chlorine residual and chloroform formulation in rivers. The kinetic framework that shows the environmental chemistry considerations in the model is shown in Figure 2. The chemical and mathematical details are shown below. The first-order rate constants include volatilization, an important process for chloroform. Elemental chlorine, Cl2, reacts with water where one atom is oxidized to Cl(+1) and one atom is reduced to Cl(-1):

(A-4)

where KN2 is the equilibrium constant for eq A-4 at 25 °C. Temperatures other than 25 °C can be accommodated as described in Lietzke (35). All of the above reactions are rapid (36), and therefore equilibrium is assumed. The trichloramine reaction is not shown and is neglected in the following analyses. The total residual chlorine is then expressed in terms of [HOCl] by using equilibrium relationships:

Acknowledgments We are grateful to Christine Davis, Patti Heath, Phoebe McClure, Cuong Pham, and Mary Porcella for their help in preparing this paper. We also thank the anonymous reviewers who provided many constructive comments, and who helped to focus the scope of the paper.

(A-3)

(A-9)

where u∞ is the cross-sectionally averaged river velocity; x and y are the longitudinal and lateral dispersion coefficients;

FIGURE 6. Definition of release scenario. rate constants and stoichiometric coefficients are depicted in Figure 2; kTRC is the coefficient of CTRC on the right-hand side of eq A-8; RCl2, RHOCl, ROCl, and RNH2Cl are equilibrium relationships between Cl2(aq), HOCl, OCl-, NH2Cl, and TRC, respectively, based on eqs A-1-A-5, and x and y are distances down the river and across the river, respectively. The last term in eq A-6 was neglected in eq A-9, as it is small (discussed previously). As discussed in numerous references (e.g., ref 36), organochlorine compounds, such as chloroform, can be formed from HOCl in the presence of reactive organic matter. As an example, the mass transport equation for chloroform is given by

∂[CHCl3]T ∂ + u∞ [CHCl3]T ) ∂t ∂x 2

x

∂ [CHCl3]T 2

∂x

CTRC(x, y, t ) 0) ) 0

∂ [CHCl3]T

3 k14(γHOCl )[HOCl]

2

∂CTRC ∂CTRC (x, y ) 0, t) ) (x, y ) W, t) ) 0 (A-12) ∂y ∂y (3) The discharge concentration is time-variable and is given by the following equation:

{

CTRC(x ) 0, y, t) ) C0(t)

+

∂y

1 -[CHCl3]Tk11e

(A-10)

where k111e ) k111 /(1 + KP(CHCl3)S) and [CHCl3]T is the total (dissolved plus adsorbed) concentration of chloroform; S is the suspended sediment concentration, and kPCHCl3 is the aqueous-sediment partition coefficient for chloroform. Solution of Equations. The total residual chlorine mass transport equation is solved subject to the following conditions:

(A-11)

(2) Zero flux of total residual chlorine occurs across either bank of the river:

0

2

+ y

(1) At the initiation of the discharge, the river is free of total residual chlorine:

0

y < hD hD < y < WD + hD

(A-13)

WD + hD < y < W

where the distances h, WD, and W are shown in Figure 6a. The release of total residual chlorine is assumed to continue for a period of ∆ton and is followed by a period of ∆toff where release does not occur. This pattern is then assumed to continue (see Figure 6b). On the basis of these assumptions and application of integral transforms (37), the solution to the total residual chlorine transport equation with specified auxiliary conditions is VOL. 32, NO. 14, 1998 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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CTRC(x, y, t) ) 4Co 3/2

π

∞

×

∑

m)1

2WDCo N-1

∑∫

Wxπ

{

UL

i)0

(

exp

u∞x

-

2x

ko u2

)

- u2 du +

1

[sin(ψm[hD + WD]) - sin(ψmhD)] × m

N-1

cos(ψmhD)

Uui

∑∫

{

Uui

exp

ULi

i)0

u∞x

-

km

2x

u2

}}

- u2 du

(A-14)

where

{

Co )

RMCl , when chlorine is discharged WD (QR - Qd) + Qw + Qd W 0, otherwise x ULi ) (t - toni)-1/2 2xx Uui )

x 2xx

(t - toffi)-1/2

toni ) i(∆toff + ∆ton) toffi ) toni + ∆ton km )

(

)

u∞2 x2 + kTRC + ψm2y 4x 4x

ko )

(

)

u∞ 2 x2 + kTRC 4x 4x

and CTRC is the total residual chlorine concentration; WD is the width of diffuser; W is the width of river; N is the number of chlorine releases; t is the time since beginning of initial release; ∆ton is the duration of each chlorine release; ∆toff is the duration between each chlorine release; u∞ is the river velocity; x is the distance downstream from discharge; x is the longitudinal eddy diffusion coefficient; ψm is the summation constant defined by mπ/W; hD is the distance of diffuser from shore; u is the integrand; kTRC is the decay rate of total residual chlorine; y is the transverse eddy diffusion coefficient; MCl is the mass release of chlorine; R is the ratio of mass of chlorine released to river to mass chlorine injected into condenser; QR is the river flow rate; Qd is the flow diverted to condenser; and Qw is the discharge flow rate. The integrals are solved using a Gauss-Legendre quadrature iteration scheme with a user-specified number of integration points. The trihalomethane in the river is from two sources: in situ formation and the discharge. The solution is also found by using integral transforms and is not shown. The same initial and boundary conditions, eqs A-11A-13, are also used for trihalomethane simulation. At present, the only trihalomethane simulated is chloroform (the predominant trihalomethane in potable waters with low bromide concentration).

Glossary CTRC hD ki kij kTRC 2170

concentration of total residual chlorine distance from shoreline to nearest edge of diffuser equilibrium constants first order rate constants decay rate of TRC 9

ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 32, NO. 14, 1998

MCl mass release of chlorine N number of chlorine releases Q 7 - 1 0 7-day consecutive low flow with a return period of 10 years flow diverted to condenser Qd QHM harmonic mean flow rate QR river flow rate discharge flow rate Qw t time since beginning of initial release duration of release of TRC ∆ton duration between TRC releases ∆toff u integrand cross-sectionally averaged river velocity u∞ W width of river width of diffuser WD x distance downstream of discharge y distance across the river R ratio of mass of chlorine released to river to mass of chlorine injected into condenser equilibrium relationship between Cl2 and TRC RCl2 R H O C l equilibrium relationship between HOCl and TRC equilibrium relationship between OCl and TRC ROCl RNH2Cl equilibrium relationship between NH2Cl and TRC x longitudinal dispersion coefficient lateral dispersion coefficient y stoichiometric coefficients γik ψm summation constant defined by mπ/W

Literature Cited (1) Symons, J. M.; Bellar, T. A.; Carswell, J. K.; DeMarco, J.; Kropp, K. L.; Robeck, G. G.; Seeger, D. R.; Slocum, C. J.; Smith, B. L.; Stevens, A. A. National Organics Reconnaissance Survey for Halogenated Organics. J. Am. Water Works Assoc. 1975, 67, 634647. (2) Rook, J. J. Formation of Haloforms During Chlorination of Natural Waters. Water Treatment Examination 1974, 23 (2), 234-243. (3) Bellar, T. A.; Lichtenberg, J. J.; Kroner, R. C. The Occurrence of Organohalides in Chlorinated Drinking Water. J. Am. Water Works Assoc. 1974, 66 (22), 703-706. (4) U.S. Environmental Protection Agency. Integrated Risk Information System (IRIS). Office of Research and Development, 1997. (5) Fed. Regis. 1979, 44 (231), 68624. (6) Fed. Regis. 1994, 59 (145), 38670. (7) Fed. Regis. 1997, 62 (150), 42195-42196. (8) Lockheed Ocean Science Laboratories. Biofouling Control Assessment - A Preliminary Data Base Analysis; Prepared for Electric Power Research Institute, Palo Alto, CA, 1982. (9) Stone and Webster Engineering Corporation. Condenser Targeted Chlorination Demonstration at Brayton Point Station-Unit 2; Prepared for Electric Power Research Institute, Palo Alto, CA, 1991. (10) Bean, R. M. Organohalogen Products from Chlorination of Cooling Water at Nuclear Power Stations; Pacific Northwest National Laboratory: Richland, WA, 1982. (11) Clark, R. M.; Grayman, W. M.; Goodrich, J. A.; Deininger, R. A.; Skov, K. Measuring and Modeling Chlorine Propagation in Water Distribution Systems. J. Water Resour. Plan. and Mgmt. 1994, 120 (6), 871-887. (12) Zhang, G. R.; Kiene, L.; Wable, O.; Chan, U. S.; Duquet, J. P. Modeling of Chlorine Residual in the Water Distribution Network of Macao. Environ. Technol. 1992, 13, 937-946. (13) Biswas, P.; Lu, C.; Clark, R. M. A Model for Chlorine Concentration Decay in Pipes. Water Res. 1993, 27 (12), 1715-1784.

(14) Rossman, L. A.; Clark, R. M.; Grayman, W. M. Modeling Chlorine Residuals in Drinking Water Distribution Systems. J. Environ. Eng. 1994, 120 (4), 803-820. (15) Heinemann, T. J.; Lee, G. F.; James, R. A.; Newbry, B. W. Summary of Studies on Modeling Persistence of Domestic Wastewater Chlorine in Colorado Front Range Rivers. Water Chlorination: Environmental Impact and Health Effects, Vol. III; Ann Arbor Science: Ann Arbor, MI, 1983. (16) Milne, G. D.; Stanley, S. J.; Smith, D. W. Residual Chlorine Decay in a Broad Shallow River. Water Res. 1993, 27 (6), 993-1001. (17) Vasconcelos, J. J.; Rossman, L. A.; Grayman, W. M.; Boulos, P. F.; Clark, R. M. Kinetics of Chlorine Decay. J. Am. Water Works Assoc. 1997, 89 (7), 54. (18) Amy, G. L.; Chadik, Z. K.; Chowdhury, Z. K. Developing Models for Predicting Trihalomethane Formation Potential and Kinetics. J. Am. Water Works Assoc. 1987, 79 (7), 89-97. (19) Chowdhury, Z. K.; Amy, G. L.; Siddiqui, M. Modeling Effects of Bromide Ion Concentration on the Formation of Brominated Trihalomethanes. J. Environ. Health Res. 1991, 2, 33-40. (20) Harrington, G. W.; Chowdhury, Z. K.; Owen, D. M. A Computer Model to Simulate Organics Removal and Trihalomethane Formation. Proc. 1991 AWWA Annu. Conf. Philadelphia, PA, 1991; pp 589-624. (21) Harrington, G. W.; Chowdhury, Z. K.; Owen, D. M. Developing a Computer Model to Simulate DBP Formation During Water Treatment. J. Am. Water Works Assoc. 1992, 84 (11), 78-87. (22) Krasner, S. W.; Sclimenti, M. J.; Means, E. G. Quality Degradation: Implications for DBP Formation. J. Am. Water Works Assoc. 1994, 86 (6), 34-47. (23) Koch, B.; Krasner, S. W.; Sclimenti, M. J.; Schimpff, W. K. Predicting the Formation of DBPs by the Simulated Distribution System. J. Am. Water Works Assoc. 1991, 83 (10), 62-70. (24) Hutton, P. H.; Chung, F. I. Simulating THM Formation Potential in Sacramento Delta: Part I. J. Water Resour. Plan. Mgmt. ASCE, 1992, 118 (5), 513-529. (25) Hutton, P. H.; Chung, F. I. Simulating THM Formation Potential in Sacramento Delta: Part II. J. Water Resour. Plan. Mgmt. ASCE, 1992, 118 (5), 530-542. (26) Hutton, P. H.; Chung, F. I. Bromine Distribution Factors in THM Formation. J. Water Resour. Plan. Mgmt. ASCE, 1994, 120 (1), 1-16. (27) Hutton, P. H.; Chung, F. I. Correlating Trihalomethane Data. J. Environ. Eng. ASCE, 1994, 120 (1), 219-241.

(28) Canale, R. P.; Chapra, S. C.; Amy, G. A.; Edwards, M. A. Trihalomethane Precursor Model for Lake Youngs, Washington. J. Water Resour. Plan. Mgmt. ASCE, 1997, Sept/Oct, 259265. (29) Rossman, L. A. Design Stream Flows Based on Harmonic Means. J. Hydraul. Eng. 1990, 116 (7), 946-950. (30) Lew, C. S.; Mills, W. B.; MacNeil, A.; Liu, S.; Gherini, S. RIVRISK: A Model to Assess Potential Human Health Risks from Power Plant Discharges into Rivers. Proceedings from the Fifth International Conference on Development and Application of Computer Techniques to Environmental Studies; Computational Mechanics Publications, Southampton, U.K. (31) McGuire, M. J.; Shepherd, B. M.; Davis, M. K. Surface Water Supply Trace Organics Survey. Phase I Maximum Trihalomethane Potential. The Metropolitan Water District of Southern California, Water Quality Branch, Water Quality Laboratory Report, 1980. (32) Stumm, W.; Morgan, J. J. Aquatic Chemistry: Chemical Equilibrium and Rates in Natural Waters; John Wiley & Sons: New York, 1996. (33) U.S. Environmental Protection Agency. Risk Assessment Guidance for Superfund. Human Health Evaluation Manual Part A; EPA/540/1-89/002, 1989. (34) Lew, C. S.; Mills, W. B.; Wilkinson, K. J.; Gherini, S. A. RIVRISK: A Model to Assess Potential Human Health and Ecological Risks from Chemical and Thermal Releases into Rivers. J. Water, Air, Soil Pollut. 1996, 90 (1/2); Kluver Academic Publishers. Dordrecht, Netherlands. (35) Lietzke, M. H. A kinetic model for predicting the composition of chlorinated water discharged from power plant cooling systems. Water Chlorination, Environmental Impact and Health Effects, Vol. I; Ann Arbor Science, 1978. (36) Stumm, W.; Morgan, J. J. Aquatic Chemistry: Chemical Equilibrium and Rates in Natural Waters; John Wiley & Sons: New York, 1996. (37) Sneddon, I. N. The Use of Integral Transforms; McGraw-Hill Book Company, 1972.

Received for review March 10, 1997. Revised manuscript received April 27, 1998. Accepted April 27, 1998. ES970209L

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