Environ. Sci. Technol. 2005, 39, 5407-5413
Simple Method for Quantifying Microbiologically Assisted Chloramine Decay in Drinking Water A R U M U G A M S A T H A S I V A N , * ,† IAN FISHER,‡ AND GEORGE KASTL‡ Asset Management and Sustainability Divisions, Sydney Water Corporation, 115-123 Bathurst Street, Sydney, New South Wales 2000, Australia
In a chloraminated drinking water distribution system, monochloramine decays due to chemical and microbiological reactions. For modeling and operational control purposes, it is necessary to know the relative contribution of each type of reaction, but there was no method to quantify these contributions separately. A simple method was developed to do so. It compares monochloramine decay rates of processed (0.2 µm filtered or microbiologically inhibited by adding 100 µg of silver/L as silver nitrate) and unprocessed samples under controlled temperature conditions. The term microbial decay factor (Fm) was defined and derived from this method, to characterize the relative contribution of microbiologically assisted monochloramine decay to the total monochloramine decay observed in bulk water. Fm is the ratio between microbiologically assisted monochloramine decay and chemical decay of a given water sample measured at 20 °C. One possible use of the method is illustrated, where a service reservoir’s bulk and inlet waters were sampled twice and analyzed for both the traditional indicators and the microbial decay factor. The microbial decay factor values alone indicated that more microbiologically assisted monochloramine decay was occurring in one bulk water than the other. In contrast, traditional nitrification indicators failed to show any difference. Further analysis showed that the microbial decay factor is more sensitive and that it alone can provide an early warning.
Introduction Many drinking water distribution systems have long residence times of a week or more. (Mono)chloramine is often used in such systems as a secondary disinfectant instead of chlorine, to maintain a longer lasting residual and to reduce the formation of chlorinated disinfection byproducts (DBPs) (12). However, the stability of monochloramine presents some additional challenges for water utilities. In addition to autodecomposition of monochloramine, and its direct chemical reaction with waterborne constituents, nitrification accelerates monochloramine decay and promotes bacterial regrowth. A survey (3) of U.S. water utilities indicated that nitrification may occur in 63% of those utilities that use monochloramine. * Corresponding author present address: Asset Management, Sydney Water Corporation, P.O. Box 73, West Ryde, NSW 2114, Australia; phone: +612-98006732; fax: +612-98006896; e-mail:
[email protected]. † Asset Management Division. ‡ Sustainability Division. 10.1021/es048300u CCC: $30.25 Published on Web 06/15/2005
2005 American Chemical Society
Nitrification is a two-step microbiological process: ammonia is initially oxidized to nitrite by ammonia oxidizing bacteria (AOB), and nitrite is then oxidized to nitrate by nitrite oxidizing bacteria (NOB). In a chloraminated system, ammonia is added to water (before, after, or simultaneously with the addition of chlorine) to form monochloramine. Nitrification occurs in chloraminated systems over a wide pH range (from 6.5 to 10.0) and preferentially at temperatures above 15 °C (4). However, it can also occur in colder water (5). Growth rates of nitrifiers are controlled by the concentration of substrate (i.e., ammonia for AOB), temperature, pH, light, and oxygen concentration (6). Typical of most chemolithotrophs, nitrifying bacteria grow slowly, with generation times ranging from 8 h to several days (6). In addition to nitrification, nitrifying bacteria can secrete organic compounds that stimulate the growth of bacteria detected by heterotrophic plate count (HPC) (6). Some strains of nitrifying bacteria can incorporate organic compounds (acetate, formate, glucose, and yeast extract), which increase their growth rates and cell yields (6). Recognizing the major role of nitrifying bacteria in microbiologically accelerated monochloramine decay, nitrifying bacteria (AOB), or their effects, are traditionally monitored by the water industry to understand the status of the acceleration of monochloramine decay (7, 8). Since the monitoring of nitrifying bacteria is complicated, timeconsuming, and inefficient, the direct monitoring and quantifying of nitrifiers are not recommended for most utilities (8). Instead, parameters such as monochloramine residual concentrations, ammonia, nitrite, nitrate, and HPC are used as surrogates for nitrifying bacteria. However, these parametersdonotdirectlyshowbyhowmuchthemonochloramine decay is microbiologically assisted. The surrogates do not indicate the actual levels of nitrifying bacteria. In a study that involved sampling over an 18 month period from nine locations including reservoirs (4) reported poor correlations of nitrite, monochloramine, and ammonia to AOB concentrations for all except one of the waters studied. A recent study (9) reported varying levels and species of NOB in different chloraminated distribution system waters. NOB and reaction with monochloramine convert variable amounts of nitrite to nitrate, making the concentration of nitrite unpredictable. As the ambient level of nitrate is usually more than an order of magnitude greater than the nitrite level, it is not possible to use the change in nitrate level as an estimate of the amount of nitrite converted. Even if it were possible to count the various species responsible for nitrification, their direct role and their relative contribution to monochloramine decay (the parameter of most concern) are not well-known. Therefore, traditional indicators often provide misleading information on the extent of nitrification and the impact of all forms of microbiological activity on monochloramine decay. Further, under low temperature conditions, due to the minimal activity of nitrifying bacteria and other microorganisms that could degrade monochloramine, appreciable changes in traditional parameters may not be noticeable, even though there is a large enough population of such microorganisms present to significantly impact monochloramine residuals at higher temperatures. When the temperature does subsequently increase, these microorganisms can rapidly decay monochloramine, resulting in lower monochloramine concentrations, which will further expedite the monochloramine loss and, in turn, the growth of nitrifiers. At this stage, the problem would be difficult for most utilities to eradicate or even control. The only options left are to VOL. 39, NO. 14, 2005 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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breakpoint chlorinate or to dump the water. It would be far better if a method were available to detect the problem (especially in winter or early spring), before the start of the cycle of monochloramine loss and microbial (including nitrifiers) growth, which will accelerate during the summer months. If the component of microbiologically assisted decay could be measured separately from the total bulk water decay, monochloramine residuals could be better managed within distribution systems. For example, utility operators would be able to measure the effectiveness of any intervention. If the intervention is intended to decrease the activity of microorganisms, they will be able to measure the microbial component of decay before and after the intervention is implemented. If chemical decay is too high, then it can be addressed separately, usually with quite different types of intervention. Additionally, when accelerated monochloramine loss is observed in the system, it is often difficult to distinguish whether it is due to bulk water reactions or wall associated reactions (biofilm, corrosion, etc.). This issue also cannot be directly resolved by measuring traditional nitrification indicators. In summary, it would be beneficial for water utilities to have a simple method that directly quantifies the microbial component of monochloramine decay and separates bulk water reactions from wall reactions. It would be advantageous if this measurement could also provide early warning of a latent nitrification problem and an estimate of the expected residual in summer. This paper presents a simple method that would allow water utilities to quantitatively separate the microbial component of monochloramine decay from the total decay. It can also provide the desirable early warning and prediction of summer residuals. Further, direct measurement of chemical and microbiological components would lead to more targeted management of monochloramine decay.
Method Development Monochloramine decay in a chloraminated water sample from a distribution system can be divided into two components: decay due to chemical reactions and decay due to microbial activity. Chemical decay depends on the chlorineto-ammonia ratio, temperature, total organic carbon (TOC), pH, nitrite, or other agents present in water (10-13). In addition to dissolved agents, both dead microbial cells and abiotic particles suspended in water may also affect monochloramine decay. First-order reaction kinetics is commonly used in describing monochloramine decay in bulk water, although a more complicated model was recently proposed (13). In the method developed here, however, first-order reaction kinetics is used to characterize all decay rates. All experiments were carried out at 20 °C. The integrated form is given by eq 1.
CNH2Cl ) CNH2Cl,0 exp(-kSt)
(1)
where CNH2Cl,0 is the initial monochloramine concentration in mg/L (i.e., at t ) 0), CNH2Cl is the monochloramine concentration in mg/L, kS is the first-order decay coefficient of sample S at 20 °C, and t is elapsed time in hours. An experimental protocol has been designed (Figure 1) to determine the microbiologically assisted monochloramine decay. In this protocol, each water sample is processed in two ways before its monochloramine decay characteristics are determined, along with the characteristics of the unprocessed sample. Inhibition (by addition of 100 µg of silver/L as silver nitrate) and filtration (through 0.2 µm sterile filter paper under pressure) are used to separate (a) the activity of microbiological agents (that accelerate monochloramine 5408
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FIGURE 1. Experimental protocol for determining microbial decay factor and the impact of water contents (dissolved, particulate, microbes, and inhibited microbes) on monochloramine decay. Solid lines show the protocol for determination of microbial decay factor. Dotted lines show an augmented protocol to differentiate further (if necessary) the impact on the monochloramine decay of the inhibitor itself and any interactions between it and the water contents. decay) and (b) the effect of abiotic particles and inhibited microbes from (c) the total monochloramine decay observed in the unprocessed sample. It has been reported (4) that ammonia-oxidizing bacteria (AOB) are Gram-negative, rodshaped bacteria, 0.8 × 1.2 µm in size. Consequently, they (in addition to other microorganisms, especially bacteria and larger organisms) should be effectively removed by a 0.2 µm filter. The following assumptions are made regarding the effect of filtration and inhibition and details on checking these assumptions are provided next. (i) Filtering through 0.2 µm pores removes only the effect of microbiological agents, including nitrifying bacteria, and the effect of abiotic particles on monochloramine decay. (ii) Inhibition suppresses only the accelerated decay of monochloramine caused by microbiological activity, including that of nitrifying bacteria. The constituents that affect monochloramine decay in processed and unprocessed samples are presented in Table 1. The previous assumptions imply that the decay in the filtered sample (FS) at a given time after processing is due only to dissolved substances. The decay in the inhibited sample (IS) after the same elapsed time is due to the reaction with both dissolved substances and particulates. Particulates include both abiotic particles and inactivated microbes. Consequently, the decay due to particulates is (IS - FS). The total decay in the unprocessed sample (US) after the same elapsed time is due to the reaction of monochloramine with all three componentssdissolved substances, particulates, and (active) microbes (including nitrifiers). Consequently, the decay due to active microbes is (US - IS). To generalize the results for all elapsed times, and to ensure that they were less influenced by any single data point,
TABLE 1. Water Sample Processing and Resulting Solid Contents that May Affect Monochloramine Decay, under Assumptionsa treatment
decay coefficient
contents in water during decay test
unprocessed (US) filtered (FS) inhibited (IS)
ktotal kF kI
dissolvedb + particulates + active microbes (including nitrifiers) dissolvedb dissolvedb + particulates (abiotic particles and inhibited microbes)
a Inhibitor is assumed to only inhibit microbes, and filtration removes both particulates and all microbes. b Dissolved substances operationally defined as passing through a 0.2 µm filter.
TABLE 2. Water Sample Processing and Resulting Contents that May Affect Monochloramine Decay, under More Complex Assumptions treatment
decay coefficients
unprocessed (US) filtered (FS) inhibited (IS)
ktotal kF kI
filtered + inhibited (F + I)
kF+I
a
contents in water during decay tests + particulates + active microbes (including nitrifiers) dissolveda dissolveda + particulates (abiotic particles and inhibited microbes) + inhibitor + inhibitor interaction with dissolved and particulates dissolveda + inhibitor + inhibitor interaction with dissolved dissolveda
Dissolved substances operationally defined as passing through a 0.2 µm filter.
results from decay tests were first characterized by the firstorder decay coefficient. The decay coefficients derived from FS, IS, and US are given in Table 1 as kF, kI, and ktotal, respectively. Provided that the previous assumptions regarding filtration and inhibition hold, then kI represents the chemical decay (kC) only. If the difference between kI and kF is negligible, then kF can also be used as kC. This would imply that abiotic particulates and inhibited microbes have a negligible impact on monochloramine decay. The difference between chemical decay (kC) and total decay (ktotal) is attributable to microbiological agents including nitrifiers. The difference is defined as the microbial decay coefficient and is denoted as km.
km ) ktotal - kC
(2)
While it is important to quantify km, it is rather difficult to judge its significance in isolation. To provide a point of reference, the term microbial decay factor (Fm) is introduced, which is the ratio between the microbial decay coefficient (km) and the chemical decay coefficient (kC), that is
Fm )
km kC
(3)
This can be interpreted directly as the ratio of the decay rate due to microbiological agents relative to the chemical decay rate at any time, in the original (unprocessed) water, as all decay tests conform to the exponential decay model (i.e., each decay rate is equal to the product of the respective decay coefficient and the current (monochloramine) concentration). In the original sample, the monochloramine concentration driving both microbiological and chemical decay is identical. Consequently, at any time
Dm kmCNH2Cl ) ) Fm DC kCCNH2Cl
(4)
where Dm is the microbiologically assisted monochloramine decay rate in the original sample (mg/L/h) and DC is the chemical decay rate in the original sample (mg/L/h). The total decay rate occurring in the sample at a given time (DT) is the sum of chemical (DC) and microbiological (Dm) decay rates. From eqs 2-4, it is apparent that, in the absence of microbiologically assisted monochloramine decay, the value
of km should be zero; hence, Fm should be zero. This is the theoretical minimum value for the microbial decay coefficient and the microbial decay factor. These values increase as the impact of microorganisms (including nitrifying bacteria) on monochloramine decay increases. Confirmation that the Main Contribution to Accelerated Monochloramine Decay Is from Microbes Including Nitrifiers. It may be that the previous assumptions made regarding filtration and inhibition do not hold for all waters. Specifically, when inhibitor is added to a sample, the inhibitor itself (In) may have an effect on the monochloramine decay. There may also be interactions between inhibitor and dissolved substances (In + D) or (abiotic) particulates (In + P) that affect subsequent monochloramine decay. Table 2 shows this fuller scheme of decay components. Then, the decay in the inhibited sample (IS) is not only decay due to dissolved substances, particulates, and inhibited microbes, as described previously, but also the additional decay due to the effects just listed. Then, the difference between decay in the unprocessed sample (US) and IS is the decay due to microbial activity and particulates, reduced by In, In + D, and In + P. An additional experiment is included in the Materials and Methods to allow further differentiation of these components of monochloramine decay. This experiment follows the augmented protocol shown in Figure 1 as dotted lines, which is similar to that used for the determination of the microbial decay factor, except that inhibitor is added to a third filtered subsample. Its decay coefficient is denoted as kF+I. If kI, kF, and kF+I are the same, all the additional effects described previously are negligible, as is the effect of particulates. If they are not equal, then the additional experiment can be used to identify the sum of the decay components (In + [In + D]). This sum is obtained from the difference between kF+I and kF. The difference between kI and kF+I would be due to the particulate effect on decay (P + [In + P]). In all the experiments conducted so far, no significant differences have been found between kI, kF, and kF+I. Consequently, conducting the additional experiment is not recommended, unless kI and kF are found to be different.
Materials and Methods Experimental Protocol for Determining Microbial Decay Factor. Determining the microbial decay factor involves four major steps so that the effect of microbiological agents can be quantified: sample preparation, incubation, monitoring monochloramine decay, and determining decay rate coefVOL. 39, NO. 14, 2005 / ENVIRONMENTAL SCIENCE & TECHNOLOGY
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ficients. Sample preparation involves splitting the sample into three subsamples. The first subsample is not processed at all, the second is inhibited, and the third is filtered. All three subsamples are then subjected to incubation at a constant temperature of 20 °C. After following this procedure, it is possible to identify whether decay is due to microbiological agents, particulates, or chemical decay. The protocol involves the following steps: if the monochloramine residual is less than 0.8 mg/L, monochloramine was added to boost the residual to 1.0 mg/L. The sample was divided into three subsamples. The first subsample was not processed, and inhibitor (silver nitrate) was added to a second water subsample to obtain 100µg of silver/L. A third water subsample was pressure-filtered through a 0.2 µm pre-washed (with MilliQ ultrapure water) sterile membrane (polycarbonate). All subsamples were incubated in duplicate, in dark conditions at 20 °C, and the monochloramine decay for all subsamples was monitored by measuring monochloramine residual concentrations daily for a period of 1-2 weeks. Initially, when the monochloramine residual decays faster, more frequent measurements were needed. Monochloramine decay experiments were terminated when the total chlorine residual in the unprocessed sample reached 0.5 mg/L. First-order monochloramine decay coefficients (kF, kI, ktotal) were determined, and 95% confidence intervals for each subsample by exponential regression. Monochloramine decay coefficients of the inhibited and filtered subsamples were compared; if they did not agree within experimental error, the difference was due to abiotic particles and inhibited microbes (and, the augmented protocol given as dotted lines in Figure 1 could be used to further partition the coefficients). The microbial decay coefficient (km) was calculated as the difference between that of the unprocessed subsample (ktotal) and that of the inhibited (kI) (or filtered (kF)) subsamples. The microbial decay factor Fm was determined (using eq 3). As a confirmation of the presence of nitrification, ammonia and nitrite concentrations were recorded for each sample at the beginning and end of the experimental period. Ammonia was measured using flow injection analysis (14). The error of the measurement was estimated. At low levels (less than 0.010 mg of N/L), a nitrite measurement had the standard error of (0.002 µg/L, while the ammonia measurement had a standard error of 15%. Monochloramine concentrations were measured using the DPD colorimetric method (14). Sydney Water System from Where Samples Were Collected. Sydney Water Corporation supplies water to about 4 million customers. The Prospect water filtration plant (WFP) is the major plant treating almost 90% of the 1700 megaliters of water delivered per day. Water mainly from Warragamba Dam is treated by coagulation/ flocculation/direct filtration, followed by chlorination and ammoniation. The pH and DOC of finished water are about 8.0 and 3.5 mg/L, respectively. Chlorine is applied for primary disinfection. The turbidity of the treated water is less than 0.1 NTU. In the finished water, the monochloramine concentration is about 1.5 mg/L and a chlorine/NH3-N ratio of 4.8 is maintained. Reservoir A is a large service reservoir, the first in a chain of 23 and located about 10 km downstream of Prospect WFP. It has a common inlet and outlet, a full supply level of 13 m, and is operated as a balancing tank.
Results and Discussion Determination of Chemical Decay and Microbial Decay Factor. The results from the experiments on two water samples collected from a chloraminated distribution system supplied by reservoir A in Sydney, Australia, are given in Figures 2 and 3 and Tables 3 and 4. Table 3 shows the water quality results at the time of sample collection. Figure 2 shows 5410
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FIGURE 2. Chlorine decay characteristics for end-of-system sample. Diamond, triangle, and cross symbols are data points for unprocessed, inhibited, and filtered subsamples, respectively.
FIGURE 3. Chlorine decay characteristics of water collected from the inlet to the first reservoir in the distribution system. Diamond, triangle, and cross symbols are data points for unprocessed, inhibited, and filtered subsamples, respectively.
TABLE 3. Water Quality of Samples at Time of Collection sample initial temperature total ammonia-N Cl/N nitrite-N (°C) Cl2 (mg/L) ratio (mg/L) end of system inlet to reservoir A
18.2 17.1
0.89 1.47
0.27 0.32
3.3 4.6
0.005 0.001
TABLE 4. First-Order Decay Coefficients Calculated from Experimental Results in Figures 2 and 3 sample
experimental conditions
end of system
unprocessed inhibited filtered filtered +inhibited inlet to reservoir A unprocessed inhibited filtered a
first-order decay coefficients ( c.i.a (h-1)
R2
0.0028 ( 0.00023 0.0017 ( 0.00014 0.0018 ( 0.00016 0.0017 ( 0.00017 0.0021 ( 0.00022 0.0019 ( 0.00025 0.0020 ( 0.00016
0.99 0.99 0.99 0.99 0.98 0.99 0.98
95% confidence interval.
the results of monochloramine decay tests (performed at 20 °C) for a sample collected from the end of the distribution system. Figure 3 shows the results for a sample collected from the inlet to reservoir A. Table 4 shows the first-order decay coefficients and statistics for both samples. Ammonia levels were analyzed initially and after 500 h. In the unprocessed subsample, after 500 h, the ammonia level decreased from 0.28 to 0.03 mg of N/L, whereas it only decreased to 0.25, 0.24, and 0.25 mg of N/L in the inhibited, filtered, and filtered + inhibited samples, respectively. The experimental error of ammonia measurement was 15% of the measurement. The change in the processed subsamples is within experimental error (i.e., ammonia had decreased in the unprocessed subsample but not decreased in the processed subsamples). In 500 h, the nitrite levels have
FIGURE 4. Monochloramine decay profile of processed end-ofsystem subsamples. Triangle, cross, and cross symbols are data points for inhibited, filtered, and filtered + inhibited subsamples, respectively. changed from 0.005 to 0.20 mg of N/L in the unprocessed samples and to below detection level in the processed samples. These results indicated that the processing had eliminated the microorganisms (including nitrifiers) and hence their impact on monochloramine decay. From Table 4, ktotal, kI, kF, and kF+I are, respectively, 0.0028, 0.0017, 0.0018, and 0.0017 h-1 for the sample collected from the end of the distribution system. The proportion of variance (R2) explained by fitting the data from each subsample listed in Table 4 with the first-order exponential decay equation was always better than 0.98, indicating an excellent fit of that model to the data. Similar goodness of fit to decay in numerous other samples has been obtained, provided the tests were performed at a constant temperature. The assumption of first-order decay is therefore valid for all the samples included in this paper. The differences between kI, kF, and kF+I are only 0.0001 h-1, and in terms of the monochloramine residual at any given time, they are only 0.03 mg/L apart. Their similarity is emphasized by the decay profiles shown in Figure 4. The difference between any two decay coefficients is smaller than the 95% confidence interval. After 500 h, ammonia in filtered and filtered + inhibited samples was 0.24 and 0.25 mg of N/L. The error in ammonia measurement was 15%. Adding inhibitor to the filtered sample therefore did not significantly affect the monochloramine decay or ammonia usage of that sample. Consequently, additional partitioning of decay due to the additional components is not possible in this case, and the simple assumptions made in the Method Development are valid. From the discussion in the Methods Development, chemical decay kC is the same as the inhibited sample decay coefficient (kI) of 0.0017 h-1. The filtered water decay coefficient (kF) is 0.0018 h-1. The 95% confidence intervals for filtered and inhibited subsamples are (0.00016 and (0.00014 h-1, respectively. Within the accuracy of monochloramine measurement, the difference of 0.0001 h-1 (between inhibited and filtered subsamples) is therefore not significant. This implies that abiotic particulates and inhibited microbes have a negligible impact on monochloramine decay in this sample. The microbial decay coefficient, km (from eq 2), is calculated as
km ) 0.0028 - 0.0017 ) 0.0011 h-1 The microbial decay factor, Fm (from eq 5), is calculated as
Fm ) 0.0011/0.0017 ) 0.6 Similar calculations can be made for the sample collected from the inlet of the reservoir. However, the differences between any two subsamples are within the 95% confidence
interval of the first-order decay coefficient of filtered, inhibited, or unprocessed subsamples (as shown in Table 4). Therefore, Fm is zero within experimental error and need not be calculated for the inlet water sample. Ammonia in all subsamples decreased from 0.32 to 0.27 mg of N/L in the unprocessed subsamples, as compared to 0.28 in the processed (filtered and inhibited) samples. The maximum change in ammonia nitrogen is only 16%. This is very close to the experimental error. These results indicated that there was no detectable activity of nitrifiers (especially AOB). Results for both ammonia and microbial decay factor indicate that there was no detectable microbial (including nitrifier) activity in the inlet sample (in terms of accelerating monochloramine decay and in decaying ammonia), and Fm was zero within experimental error. Traditional indicators for nitrification such as monochloramine residuals, ammonia, nitrite and nitrate levels, and heterotrophic plate counts, while useful, do not directly indicate how much monochloramine decay is attributable to microbial activity (including nitrifiers). The microbial decay factor method is based on straightforward partitioning of various contributions to monochloramine decay. In all cases tested, it quantified the contributions of microbiological activity and chemical reactions in bulk water without the need for measuring ammonia, nitrite, or nitrate. The microbiological decay factor is defined as the ratio between the extra microbial decay and the chemical decay. From the previous results and other experimental results obtained so far, both filtration and inhibition with silver nitrate were found to be capable of eliminating the microbiological effect on monochloramine decay. An augmented protocol was devised to cover more complex cases. If inhibition consistently produced similar results to filtration, as in all our experiments so far, the method would become less tedious, and the filtration step could be eliminated. The accuracy of Fm determination depends on the accuracy of the monochloramine measurement. Status of Nitrification of a Sydney Reservoir. Reservoir A was also selected to illustrate the wider application of the method. Reservoir A, which is a balance reservoir, is known to undergo nitrification in most summers. Water samples were collected in winter 2002 and 2003, before and after the operational change (decreased retention time by increasing throughput) that improved the nitrification situation. Before the operational change, the reservoir had a residence time of 6.5 days in winter 2002 and 9 days in summer 2002. The operational change introduced in winter 2003 reduced the reservoir residence time to 3.5 days in both winter and following summer. All samples were analyzed for the traditional indicators, as well as for the parameters from which the microbial decay factor is calculated. The usefulness of the results to predict monochloramine residuals in the subsequent season was evaluated. Tables 5 and 6, respectively, provide some of the traditional data, as well as the data related to the microbial decay factor, which were collected in both winters. Traditional Approach. From Table 5, nitrite in bulk water was 0.003 mg of N/L in winter (August) for both 2002 and 2003. The experimental standard error of the measurement is (0.002 mg of N/L. Sufficient monochloramine residual (1.20 mg/L in winter 2002 and 1.30 mg/L in winter 2003) and low nitrite levels existed in both samples. With the traditional approach, one would conclude that there was very little nitrifier activity in the samples; hence, no action was needed in winter. The temperature of the samples was 12.9 °C in 2002 and 13.5 °C in 2003. If the reservoir nitrite levels (0.003 mg of N/L) are interpreted with temperature and compared with the inlet nitrite levels (
