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Natural disinfection of wastewater in marine outfall fields
PII: S0043-1354(99)00209-2
Wat. Res. Vol. 34, No. 3, pp. 743±750, 2000 # 2000 Elsevier Science Ltd. All rights reserved Printed in Great Britain 0043-1354/00/$ - see front matter
www.elsevier.com/locate/watres
NATURAL DISINFECTION OF WASTEWATER IN MARINE OUTFALL FIELDS LEI YANG1*M, WEN-SHI CHANG1 and MONG-NA LO HUANG2{ 1
Department of Marine Environment and Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan, Republic of China and 2Department of Applied Mathematics, National Sun Yat-sen University, Kaohsiung, Taiwan, Republic of China (First received 1 October 1998; accepted in revised form 1 May 1999)
AbstractÐIn this study the natural disinfection eects of marine environment on wastewater without the process of chlorination before being discharged into the ocean through submarine outfall pipes were investigated. The eects of four natural factors, including light intensity, salinity, volumetric mixing ratio of seawater to wastewater and the existence of predators, to the disinfection of wastewater in marine environment were examined. Under the condition that with or without the existence of predatory microorganisms in wastewater, experiments are performed based on rotatable central composite designs with dierent factor level combinations of the three factors mentioned above. Under each factor level combinations, the numbers of E.coli are measured at the beginning of each experiment and every half hour later on for two hours. Then through statistical analysis, it was found that both light intensity and salinity have signi®cant eects to the die-o rate constant with or without the existence of predators. The eects of the three environment factors can explain a larger portion (about 90%) of the variations exhibiting in the estimated die-o rate constants in the case of without the existence of predators than that (about 50%) for the case with the existence of predators, which indicates that there may be random eects of predatory microorganisms in wastewater causing more variations in the die-o rate constants. Furthermore, through paired t-test, it also indicates that the dieo rate constants for with the existence of predators is signi®cantly larger than that for without the existence of predators. Finally, for the primarily treated sewage from Kaohsiung, Taiwan, by natural disinfection it is estimated that it takes about 100 min during the daytime and 196 min during the nighttime to reach the national guideline concentration of E. coli (1000 cfu/100 ml) of Taiwan in marine environment. # 2000 Elsevier Science Ltd. All rights reserved Key wordsÐocean outfall, natural disinfection, marine environment, light intensity, salinity, rotatable central composite design, Chick's law, E. coli
INTRODUCTION
Ocean disposal is the most original way to treat the wastes generated from man, through which the wastes are diluted by a vast quantity of seawater in the ocean. Until now, ocean disposal is still one of the feasible ways to treat human waste. Most of the large cities located in coastal areas worldwide prefer to discharge their sewage into the ocean through marine outfall systems for convenient and economic reasons (Brook, 1987; Yang, 1995). However, the discharge of untreated or partially treated wastewater into the ocean may result in contamination of the marine environment with pathogenic organisms. Disinfection of the wastewater is consequently *Author to whom all correspondence should be addressed. Tel.: +86-7-525200, extn. 5068; fax: +86-7-5255068; e-mail: [email protected] { E-mail: [email protected] 743
necessary before it is discharged into the ocean, especially in those areas used for recreation and mariculture. Among the chemical disinfectants usually used in disinfection of wastewater chlorine (Cl2) is the most common, due to its characteristics of eectiveness and economics. However, from manufacture through transport and storage to ®nal use, chlorine always poses a continuous threat to operators and the environment. In addition, a variety of halogenated organic compounds, such as trihalomethanes (THMs), halogenated acetic acids (HAAs) and halophenols (HPs), may be formed during chlorination, which may contaminate the marine environment when they are discharged along with the chlorinated wastewater into the ocean through marine outfall pipes (Ali and Riley, 1989; Kristiansen et al., 1994; Kristiansen et al., 1996; Ram et al., 1990). Much research has identi®ed some of these organic halogens which are toxic and/or potentially carcino-
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genic for human health and aquatic life (Blatchley et al., 1997; Brungs, 1973; Bull et al., 1990; Kool et al., 1982; Meier et al., 1987). Although both ozone (O3) and UV light could be used instead of chlorine in disinfection of wastewater, to prevent the formation of hazardous chlorinated organic compounds, they are costly in operation and maintenance. In addition, ozone at concentrations as low as 0.03 g/m3, is a threat to the health of operators and the environment when it escapes from water during the disinfection operation (Acher et al., 1997; Erb, 1982). Therefore, if the wastewater could be discharged directly into the ocean through submarine outfall systems and disinfected naturally in the marine environment instead of traditional chemical disinfection, two bene®ts would be achieved: (1) cutting down expenses for capitalization, operation and maintenance, and (2) decreasing the hazardous potential to human health and aquatic life. Actually, in the marine environment the natural disinfection eects on wastewater were reported to be controlled by some environmental factors such as dilution, dispersion, solar radiation, salinity, temperature, pH values, presence of toxic substances, competition for nutrients and depredation in several studies (McFeters and Stuart, 1972; Ayres, 1977; Anderson et al., 1979; McCambridge and McMeekin, 1981; Scheuerman et al., 1988; ElSharkawi et al., 1989; Solic and Krstulovic, 1992). It has been found that solar radiation exerts a great in¯uence on bacteria causing their mortality in seawater at much higher rates compared to that of other environmental factors concerned (Alkan et al. (1995)). In addition, the factor of dilution of wastewater by seawater is also important to the eect of disinfection due to its in¯uence on the salinity of seawater and amounts of suspended solids and predators in wastewater, all of which aect the disinfection eects on wastewater. As to the factor of temperature, except in deep ocean, the temperature changes in seawater are insigni®cant in coastal areas, where most of the wastewater from land is discharged. In addition, in the Alkan et al. (1995) study using statistical analyses, it was found that temperature was not a signi®cant parameter for disinfection in the marine environment. Thus, the objective of this study is to investigate the disinfection eects of the factors of light intensity, salinity, volumetric mixing ratio of wastewater and seawater, and the existence of predators in the marine environment on wastewater evaluated by measuring the die-o rate of E. coli, which are regarded as an important indicator of faecal pollution in the marine environment. The feasibility of natural disinfection of wastewater in the marine environment for ocean outfall systems without the process of chlorination may thereby be assessed.
MATERIALS AND METHODS
Preparation of batch test solutions Seawater. In this study, arti®cial seawater was used to run the batch disinfection tests. The receipt of preparing the arti®cial seawater with salinity of 35- was as follows: NaCl 31 g, MgSO4.7H2O 10 g, NaHCO3 0.05 g and deionized (DI) water 1 l. Before being used in the tests, the arti®cial seawater was ®rst sterilized by using an autoclave (P. SELECTA WIKA) at 1208C for 15 min. Wastewater. In this study, the wastewater was taken from the campus sewage treatment plant of National Sun Yat-sen University (NSYSU). The samples were taken by using sterile sampling bags and then sent back to the laboratory immediately to run the tests. If the tests were those without the existence of predators, the samples were autoclaved (1208C for 15 min), ®rst for sterilization and then used in the experiments. The sewage samples were analyzed for their BOD values for each test run. Bacterial stock solution. The test organisms (E. coli JM109) were inoculated from the Microbiology Laboratory of NSYSU into the sterilized Luria±Bertani broth solution and then cultured at 358C for 24 h. After being cultured, the concentrations of the bacteria were in the range of about 107±108 cfu/100 ml. Experimental equipment Equipment employed for the batch tests consisted of a 3-l ¯ask, a magnetic agitator and a sunlight simulator (high-pressure metal halide lamp, Philips, HPI-T, 400 W). This set of equipment was put in a dark room and the light intensity was controlled by adjusting the distance between the lamp and the surface of test solution inside the ¯ask, which was put on the magnetic agitator to keep the solution mixed during the tests. The light intensity (Lux, lumen/m2) was measured and controlled by a light meter (TES Electrical Corp., TES-132). The temperature of the mixed liquor was measured in each test run by a thermometer. Experimental design In this study, the controlled conditions were composed by the four environmental factors: light intensity; salinity; volumetric mixing ratio; and under the condition either with or without the existence of predatory microorganisms in wastewater. Although the factors of temperature T and organic matter concentration BOD in the wastewater would also aect the fate of microorganisms, the temperature T was highly correlated to light intensity L (with a sample correlation coecient, r = 0.9501 in our experiments) and volumetric mixing ratio of seawater to wastewater R was highly correlated with the inverse of the factor of organic matter concentration 1/BOD (with a sample correlation coecient, r = 0.9864 in our experiments). The stronger the light intensity is radiated into the water, the higher the water temperature is achieved. On the other hand, the higher the seawater and wastewater ratio is controlled in the mixed sample, the lower the organic matter concentration is achieved due to the eect of dilution. Therefore either factor from these two sets of factors can be used as a controlled level in the experiments. In this study, we selected light intensity and seawater and wastewater ratio instead of temperature and organic matter concentration as controlled factors, respectively. A rotatable central composite design was employed to investigate the eects of the factors mentioned above. The rotatable central composite design with m factors (m = 3) may be subdivided into three parts. 1. The 2 m points with either high (1) or low (ÿ1) level in each coordinate constitute a 2 m factorial. 2. The 2 m extra points, one at either extreme of each fac-
Natural disinfection of wastewater in ocean tor and at the center of all other factors, are included to form a central composite design. 3. Some points are added at the center to give roughly equal precision for the predicted values of the responses within a circle of radius 1, where for m = 3 six center points are added. A preliminary step in any experiment of this type is to set up the relations between the coded levels and the original level scales of the factor. In our study original levels of the controlled factors in the tests are as shown in Table 1, where the ®ve levels are coded as ÿ1.682, ÿ1, 0, 1, 1.682, respectively. As under the condition that either with or without the existence of predators, for a central composite design with m = 3 factors, there are 20 test runs, therefore, we have a total of 40 test runs, and within each central composite design the order of running the experiment under the factor level combinations is completely random. The advantage of a rotatable central composite design over the fractional or complete three-leveled factorial is in the reduction of the number of treatment combinations required to estimate the squared terms in a second-order model. For more details about rotatable central composite designs, see Box and Draper (1987), and Cochran and Cox (1992). Experimental procedure The test ¯ask was ®rst ®lled with the mixed liquor of arti®cial seawater and sewage with a mixing ratio designed previously. If the test was run for the condition without the existence of predators, the mixed liquor would be sterilized before being added into the ¯ask, and vice versa. A quantity of E. coli cultured stock solution was added to the ¯ask, in which the concentration of the bacteria was controlled in a range of about 107±108 cfu/100 ml. Meanwhile the light intensity was setup to a number as requested in the experimental design by using the light meter mentioned previously. Samples were taken by using sterilized pipettes and collected in sterile sampling bags from the ¯ask. The initial samples were taken at time zero just before exposure to the light and were followed by subsequent samples with a time interval of 30 min. Then we analyzed the collected samples for bacterial counts immediately using the method of membrane ®ltration in Standard Methods (APHA et al., 1992). It was usually assumed that the number of bacteria remaining after contact time t follows the equation derived from the Chick law: Nt N0 eÿkt , where t = contact time, Nt=number of bacteria remaining after contact time and N0=number of bacteria at time zero. The die-o rate constant (k, minÿ1) of E. coli under each combination of controlled environmental conditions designed can be expressed as the slope of the line with log Nt =N0 against time t without an intercept, i.e. log Nt ÿ log N0 ÿkt: Although all numbers of bacteria counted in the experiments are with random errors, under each combination of controlled environmental conditions we consider the following model: log Yt a ÿ kt Et ,
t 0, . . . , n,
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where Yt is the observed number of bacteria counts at time t, n is the observed time span, a, k are unknown parameters, E'ts are uncorrelated random errors with expectation 0 and common unknown variance s 2. The values of a, k and s 2 all need to be estimated. Later the estimated values of k are used to investigate the eects of the environmental conditions. The relationships between the k values and the environmental factors considered in this study are analyzed statistically, and two multiple regression equations for conditions with and without the existence of predators are then obtained, which are also used to predict the die-o rates of E. coli controlled under a special condition in the marine environment.
RESULTS AND DISCUSSION
Evaluation of the die-o rate of E. coli Estimated die-o rate constants (k ) of E. coli under each controlled environmental condition for both tests with and without the existence of predators are summarized in Table 2 where it can be seen that when it is with the existence of predators, the two largest values of k are 0.087273 minÿ1 in test No. 17 and 0.044930 minÿ1 in test No. 15, which are controlled under the conditions of light intensity L = 50,000 lux, salinity S = 40-, volumetric mixing ratio of seawater to sewage R:1=50:1 for test No. 17, and L = 100,000 lux, S = 20- and R:1=50:1 for test No. 15. Note that in these two cases it is either under the highest salinity level with the other two conditions under middle levels, or under the highest light intensity level with the other two conditions under middle levels. Similarly when it is without the existence of predators, the two largest values of k are 0.02269 minÿ1 under L = 79,730 lux, S = 31.89-, R:1=80:1 in test No. 5 and 0.01778 minÿ1 under condition described above in test No. 15. In the ®rst case it seems to have all the favorable conditions to have larger dieo rate, relative high light intensity, salinity, and seawater level. In the second case it again has the highest light intensity level. About the minimum value of k, in test No. 8 the estimated k values with or without the existence of predators are both negative, which seem to be in con¯ict to the usual understanding that the number of counts of bacteria should be decreasing, i.e. k should be positive. A possible explanation is that in test No. 8, both light intensity and salinity are in relatively low levels, where similar phenomena appear for test No. 4, i.e. the values of k are positive, but are the second or the third smallest, with or without the existence of predators, respectively. The second smallest
Table 1. Levels of factors controlled in the batch tests Factors Light intensity (lux) Salinity (-) Volumetric mixing ratio of seawater to wastewater (R:1) Existence of predators
Levels 0 0 1:1 Yes
20,270 8.11 20:1 No
50,000 20 50:1
79,730 31.89 80:1
100,000 40 100:1
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Lei Yang et al. Table 2. Results of E. coli die-o rate constants (k ) in varying experimental conditions
Test No.
Light intensity (lux)
Salinity (-)
Mixing ratio (R )
Mixed liquor temperature (8C)
Mixed liquor BOD (mg/l)
Die-o rate with existence of predator
Without existence of predator (k, minÿ1)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
79,730 20,270 79,730 20,270 79,730 20,270 79,730 20,270 50,000 50,000 50,000 50,000 50,000 50,000 100,000 0 50,000 50,000 50,000 50,000
31.89 31.89 8.11 8.11 31.89 31.89 8.11 8.11 20 20 20 20 20 20 20 20 40 0 20 20
20 20 20 20 80 80 80 80 50 50 50 50 50 50 50 50 50 50 01 100
27 20 28 21 28 19 29 23 25 25 26 24 25 25 31 16 26 24 25 26
14.2 14.6 15.0 13.4 4.2 3.8 4.3 4.0 6.0 5.3 5.7 6.4 6.1 6.0 6.0 5.8 6.3 6.2 138.0 2.8
0.040159 0.010535 0.004254 0.001847 0.022258 0.013122 0.012140 ÿ0.004673 0.033454 0.027612 0.005932 0.005756 0.019341 0.018604 0.044930 0.005380 0.087273 0.001958 0.005343 0.010155
0.013228 0.006345 0.008164 0.001755 0.022693 0.001254 0.012984 ÿ0.000436 0.003621 0.006105 0.007903 0.006600 0.006599 0.006856 0.017780 0.001024 0.005722 0.003993 0.006128 0.004605
value of k without the existence of predators appeared in test No. 16, where L = 0 lux, S = 20-, and R:1=50:1, i.e. the light intensity is under the lowest level possible in this study. Regarding the environmental factor of depredation, it was found that in some cases the k values estimated in the systems with predators existing are three to ®ve times larger than the values estimated in the systems without predators existing, others are quite close and comparable, which in turn implies there is larger variation for the k values estimated in the systems with predators existing. This also indicates that the mechanisms for the systems with predators existing are more complicated than that without predators existing. In the following Sections the relationships between the k values and the environmental factors with or without the existence of predators are investigated. As discussed above, in test No. 8 with both light intensity and salinity under relatively low levels, the estimated values of k are negative, which might be re¯ecting the real situation or might be due to experimental errors. Also it is noted that in test No. 8 and without the existence of predators, the simple linear model is ®tted with r 2=0.0212 and has a very insigni®cant disinfection eect on E. coli as the time elapsed within the ®rst two hours. Similarly for data set in test No. 4 (which are obtained under the same light intensity and salinity levels as in test No. 8) with the existence of predators, it is noted that although the estimated values of k are positive, the simple linear model is ®tted with only r 2=0.2084 which is not as signi®cant as in the other test runs ®tted with r 2 being at least 0.75. So in this work we have removed the estimated k values for data sets in test No. 8, and in the statistical analysis of test No. 4 hereafter.
Results of statistical analyses Plots of estimated die-o rates vs environmental factors. The relationship between the k value and each environmental factor used in the tests can be observed ®rst through plots of the average of estimated die-o rates at each factor level as shown in Fig. 1. As seen from Fig. 1, the estimated values of k are generally increased proportional to light intensity and salinity for both with and without the existence of predators. However, the positive relationships between the k values and mixing ratio are not as clearly shown for either with or without predators existing in the systems. The reason might be the same as that mentioned previously, i.e. the concentrations of SS in sewage were changed in each test. Response surface models. Under the condition with or without the existence of predators, two response surface models with the form: kp b0
i1
bi x i
X 1Ri
kpÿ b0ÿ
3 X
3 X i1
1Ri
i1
bii x 2i
bij x i x j Z ,
biÿ x i
X
3 X
3 X i1
biiÿ x 2i
bijÿ x i x j Zÿ ,
where fbi , bii , bij g1Ri
Natural disinfection of wastewater in ocean
Fig. 1. Plots of average k values vs light intensity, salinity and volumetric mixing ratio.
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Lei Yang et al.
Z+, Zÿ are the random experimental errors with expectation 0, are built respectively. In each model there are 18 sets of data. The ®nal response surface models are obtained through stepwise regression and the results are presented in Tables 3 and 4. Results of stepwise regression. From Tables 3 and 4, both light intensity and salinity have signi®cant eects to the die-o rate constants with or without the existence of predators. The mixing ratio of seawater to wastewater has an eect on the die-o rate constant through interaction with light intensity in the case of without the existence of predators. In the case of with the existence of predators the eect of salinity is more signi®cant to k than that of light intensity. However, in the case of without the existence of predators, the eect of light intensity is more signi®cant to k than that of salinity. Also from the model ®tting correlation coecient r 2 for the two models, the model for without the existence of predators has a much better ®tting with r 2=0.8959 than that with the existence of predators of r 2=0.5045. That is, without the existence of predatory microorganisms in wastewater, the eects of the three environmental factors can explain a larger portion (about 90%) of the variations exhibiting in the estimated die-o rate constants, but when it is with the existence of predatory microorganisms in wastewater, only 50% of the variations exhibiting in the estimated die-o rate constants can be explained by the eects of the three environmental factors. This is due perhaps to the random eects of the existence of predatory microorganisms in wastewater causing more variations in the die-o rate constants, which cannot be explained through the three environmental factors. In addition, predators may also be aected by the environmental factors of light intensity and salinity. Analysis of variance. From analysis of variance results presented in Tables 3 and 4, the two pure error estimates are obtained by computing the variances of the die-o rates for the six center points (tests 9±14 with identical test conditions). These
give some idea about the values of experimental errors for those tests with or without the existence of predators. It is clear that the experimental errors for the k values with or without the existence of predators are dierent by a magnitude of order 2, which is consistent with results for the mean estimates of k with a dierence with a magnitude of order 1. The sum of squares of the lack of ®t is obtained by subtracting the sum of squares of the pure error from that of the error term. Then the lack of ®t tests is performed to test if the response regression models for the two cases are acceptable. Since the lack of ®t tests give P-values 0.1662 and 0.1557 respectively for the two models, the null hypothesis that the model is adequate is accepted for both models under signi®cance level 0.05. Paired comparison of the die-o rate constants. Now we present estimates of the dierence of the die-o rates with or without the existence of predators, and test if the dierence is statistically signi®cant at 0.05. To avoid confounding eects of the environmental factors in performing the statistical test for the dierence of the k values, we used paired t-test, i.e. under each test condition combination, let kd kp ÿ kpÿ , then perform the usual t-test for variable kd : The results are presented in Table 5. As seen from Table 5, the P-value for the paired t-test is 0.0185, from which it is clear that there is a signi®cant dierence in the k values for the two cases at signi®cance level 0.05. Also, it may be computed that the 95% con®dence interval of kd is (0.0023923, 0.0227863), which means that it is estimated that for the k values in the two cases, with 95% con®dence, the dierence is at least 0.0023923, but no more than 0.0227863. Application of study According to the design criteria of ocean outfall systems, the volumetric mixing ratio of seawater and wastewater should be at least larger than 100:1 when the wastewater plume is raised up to the surface of sea (Grace, 1978). The light intensity of the
Table 3. Results of stepwise regression of die-o rate constant k^p vs light intensity (L ), salinity (S ), and mixing ratio (R ) with existence of predatorsa Variable
Parameter estimate
Standard error
F
P>F
Constant x1 x2
0.01740451 0.01038149 0.01708094
0.00379709 0.00474327 0.00474327
21.01 4.79 12.97
0.0004 0.0449 0.0026
DF Analysis of variance Regression Error Lack of ®t Pure error Total a 2
2 15 10 5 17
r =0.5045; x1=(L ÿ 50,000)/29730, x2=(S ÿ 20)/11.89.
Sum of squares
Mean square
F
P>F
0.00378096 0.00371370 0.00308600 0.00062770 0.00749466
0.00189048 0.00024758 0.00030860 0.00012554
7.64
0.0052
2.46
0.1662
Natural disinfection of wastewater in ocean
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Table 4. Results of stepwise regression of die-o rate constants k^pÿ vs light intensity (L ), salinity (S ), and mixing ratio (R ) without existence of predatorsa Variable
Parameter estimate
Standard error
F
P>F
Constant x1 x2 x 21 x 1 x3
0.00609537 0.00568561 0.00185080 0.00144177 0.00323067
0.00060097 0.00061931 0.00061931 0.00054112 0.00083683
102.87 84.28 8.93 7.10 14.90
0.0001 0.0001 0.0105 0.0195 0.0020
Analysis of variance Regression Error Lack of ®t Pure error Total
DF
Sum of squares
4 13 8 5 17
0.00047008 0.00005462 0.00004232 0.00001230 0.00052470
Mean square 0.00011752 0.00000420 0.00000529 0.00000205
F
P>F
27.97
0.0001
2.58
0.1557
a 2
r =0.8959; x1=(L ÿ 50,000)/29,730, x2=(S ÿ 20)/11.89, x3=(R ÿ 50)/30.
sun tested on a sunny day in July 1996, has a range between 100,000 and 86 lux from 13:00 to 18:00 h in Kaohsiung, Taiwan. The average light intensity was thus about 60,000 lux. The salinity of seawater was approximately 35- after the mixing ratio of seawater and wastewater was reached 100:1. Meanwhile, there were predators existing in both sewage and seawater. Therefore, we used the light intensity of 60,000 lux and salinity 35- to substitute into the estimated response surface model with the existence of predators to predict the die-o rate (k value) of E. coli, as well as the disinfection eects on the sewage in Kaohsiung discharged into the marine environment under such natural conditions and the predicted value of k is 0.0424 minÿ1. Then the time required for disinfection could be estimated by substituting 0.0424 into the equation derived from Chick's law mentioned previously. The value of T90, which is the time required for 90% die-o of bacterial cells, is estimated to be about 55 min under the light intensity of 60,000 lux and salinity at 35-. In addition, the average number of E. coli in the primarily treated sewage from Kaohsiung was reported to be about 6,700,000 cfu/100 ml. According to the general design criteria of ocean outfall systems that sewage is diluted at least 100 times on the surface of sea, then the number of the bacteria is decreased to 67,000 cfu/100 ml when the sewage plume is raised up to the surface of seawater. Hence, the time required to reach the number of 1000 cfu/100 ml, which is the guideline number of E. coli for high quality seawater in Taiwan, is estimated to be about 100 min in the marine environment during the daytime. For the
nighttime, following the same steps, except that light intensity was changed from 60,000 to 0 lux, it is estimated about 196 min to reach the guideline number of E. coli in marine environment. In summary, the eects of natural disinfection on wastewater in marine environment under high light intensity and salinity are signi®cant. Hence, using the natural factors in the marine environment instead of traditional chlorination for disinfection of wastewater, is feasible for the sewage ocean outfall systems in Kaohsiung, where over 10 months are sunny days in a year. It is estimated that by using this alternative method for disinfecton of sewage, at least US$4 million per year spent in operation and maintenance fees in the sewage treatment plant of Kaohsiung can be saved, which at present uses the method of electrolyzing seawater for disinfection.
CONCLUSIONS
According to statistical analysis on the die-o rate constants (k ) of E. coli performed in this study, the natural environmental factors of light intensity and salinity in the marine environment exhibits signi®cant disinfection eects on wastewater discharged into the ocean through submarine outfall systems. In addition, the existence of predators in both wastewater and seawater shows positive disinfection eects on E. coli in marine environment. Two response surface models corresponding to the cases with or without predators are established:
Table 5. Comparison of the k values with or without the existence of predators Mean 0.0125893
Standard error
T
P >j T j
0.0048327
2.6050
0.0185
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Lei Yang et al.
k^p ÿ2:8787 10ÿ2 3:4919 10ÿ7 L 1:4365 10ÿ3 S, and k^pÿ 6:5537 10ÿ3 ÿ 1:5299 10ÿ7 L 1:5566 10ÿ4 S ÿ 1:8111 10ÿ4 R 1:6312 10ÿ12 L2 3:6222 10ÿ9 LR, where k^p is the estimated die-o rate constant of E. coli for condition with predators existing (minÿ1), k^pÿ is the estimated die-o rate constant of E. coli for conditions without predators existing (minÿ1), L is the light intensity (lux), S is the salinity (-), and R is the volumetric mixing ratio (seawater:wastewater). Generally, according to Chick's law, the time required to decrease the number of E. coli in sewage (6,700,000 cfu/100 ml on average) to 1000 cfu/100 ml (upper limit for the high quality seawater in Taiwan) in an ocean outfall system designed with a volumetric mixing ratio of seawater and sewage of 100:1 only needs about 100 and 196 min for daytime and nighttime respectively under the 35- salinity level and average light intensities of 60,000 and 0 during daytime and nighttime respectively with the existence of predators. Therefore, it is feasible that the primarily treated wastewater could be discharged directly into the marine environment with high light intensity and salinity by ocean outfall systems without going through the process of chemical disinfection (chlorination), which may save expenses spent on operation and maintenance as well as decreasing the hazardous potential of chlorine to human health and aquatic life in the marine environment. REFERENCES
Acher A., Fischer E., Turnheim R. and Manor Y. (1997) Ecologically friendly wastewater disinfection techniques. Wat. Res. 31, 1398±1404. Ali M. Y. and Riley J. P. (1989) The production of brominated methanes in desalination plants in Kuwait. Wat. Res. 23, 1099±1106. Alkan U., Elliott D. J. and Evison L. M. (1995) Survival of enteric bacteria in relation to simulated solar radiation and other environmental factors in marine waters. Wat. Res. 29, 2071±2081. Anderson I. C., Rhodes M. and Kator H. (1979) Sublethal stress in Escherichia coli: a function of salinity. Appl. Environ. Microbiol. 38, 1147±1152. APHA, AWWA and WEF (1992) Standard Methods for the Examination of Water and Wastewater, 18th ed. American Public Health Association, Washington, DC. Ayres P. A. (1977) Coliphages in sewage and the marine environment. In Aquatic Microbiology, eds F. A. Skinner and J. M. Shewan, pp. 275±298. Academic Press, New York. Blatchley III E. R., Hunt B. A., Duggirala R. D.,
Thompson J. E., Zhao J., Halaby T., Cowger R. L., Straub C. M. and Alleman J. E. (1997) Eects of disinfectants on wastewater euent toxicity. Wat. Res. 31, 1581±1588. Box G. E. P. and Draper N. R. (1987) Empirical ModelBuilding and Response Surfaces. Wiley, New York. Brook N. H. (1987) Evaluation of key issues and alternative strategies. In Proceedings of the Marine Outfall Symposium (I), Taipei, Taiwan, pp. 1±52. Brungs W. A. (1973) Eects of residual chlorine on aquatic life. J. Wat. Pollut. Control Fed. 45, 2180±2189. Bull R. J., Gerba C. and Trussel R. R. (1990) Evaluation of the health risks associated with disinfection. Crit. Rev. Environ. Control. 20, 77±113. Cochran W. G. and Cox G. M. (1992) Experimental Designs, 2nd ed. Wiley, New York. El-Sharkawi F., El-Attar L., Gawad A. A. and Molazem S. (1989) Some environmental factors aecting survival of fecal pathogens and indicator organisms in seawater. Wat. Sci. Technol. 21, 115±120. Erb F. (1982) Toxicity of ozone. In Ozonation Manual for Water and Wastewater Treatment, ed. W. Masschelein, pp. 197±199. Wiley, New York. Grace R. A. (1978) The technical aspects of outfall design. In Marine Outfall Systems: Planning, Design, and Construction. Prentice-Hall Inc, NJ, pp. 339±421. Kool H. J., van Kreijl C. F., de Greef E. and van Kronen H. J. (1982) Presence, introduction and removal of mutagenic activity during the preparation of drinking water in The Netherlands. Environ. Health Perspect. 46, 207±211. Kristiansen N. K., Froshaug M., Aune K. T., Becher G. and Lundanes E. (1994) Identi®cation of halogenated compounds in chlorinated seawater and drinking water produced oshore using n-pentane and open-loop stripping technique. Environ. Sci. Technol. 28, 1169±1173. Kristiansen N. K., Aune K. T., Froshaug M., Becher G. and Lundanes E. (1996) Determination of halogenated acetic acids in chlorinated sea water and drinking water produced oshore. Wat. Res. 30, 2155±2159. McCambridge J. and McMeekin T. A. (1981) Eect of solar radiation and predacious microorganisms on survival of faecal and other bacteria. Appl. Environ. Microbiol. 41, 1083±1087. McFeters G. A. and Stuart D. G. (1972) Survival of coliform bacteria in natural waters: ®eld and laboratory studies with membrane ®lter chambers. Appl. Environ. Microbiol. 24, 805±811. Meier J. R., Knohl R. B., Coleman W. E., Ringhand H. P., Munch J. W., Kaylor W. H., Streicher R. P. and Kop¯er F. C. (1987) Studies on the petent bacterial mutagen 3-chloro-4-(dichloromethyl)-5-hydroxy-2(5H)furanone: aqueous stability, XAD recovery and analytical determination in drinking water and in chlorinated humic acid solutions. Mutat. Res. 189, 363±369. Ram N. M., Mussalli Y. G. and Chow W. (1990) Total trihaolmethane formation during targeted and conventional chlorination of seawater for biofouling control. J. Wat. Pollut. Control Fed. 62, 789±795. Scheuerman P. R., Schmidt J. P. and Alexander M. (1988) Factors aecting the survival and growth of bacteria introduced into lade water. Arch. Microbiol. 150, 320± 325. Solic M. and Krstulovic N. (1992) Separate and combined eects of solar radiation, temperature, salinity, and pH on the survival of faecal coliforms in seawater. Mar. Poll. Bull. 24, 411±416. Yang L. (1995) Review of marine outfall systems in Taiwan. Wat. Sci. Technol. 31, 257±264.
Wat. Res. Vol. 34, No. 3, pp. 743±750, 2000 # 2000 Elsevier Science Ltd. All rights reserved Printed in Great Britain 0043-1354/00/$ - see front matter
www.elsevier.com/locate/watres
NATURAL DISINFECTION OF WASTEWATER IN MARINE OUTFALL FIELDS LEI YANG1*M, WEN-SHI CHANG1 and MONG-NA LO HUANG2{ 1
Department of Marine Environment and Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan, Republic of China and 2Department of Applied Mathematics, National Sun Yat-sen University, Kaohsiung, Taiwan, Republic of China (First received 1 October 1998; accepted in revised form 1 May 1999)
AbstractÐIn this study the natural disinfection eects of marine environment on wastewater without the process of chlorination before being discharged into the ocean through submarine outfall pipes were investigated. The eects of four natural factors, including light intensity, salinity, volumetric mixing ratio of seawater to wastewater and the existence of predators, to the disinfection of wastewater in marine environment were examined. Under the condition that with or without the existence of predatory microorganisms in wastewater, experiments are performed based on rotatable central composite designs with dierent factor level combinations of the three factors mentioned above. Under each factor level combinations, the numbers of E.coli are measured at the beginning of each experiment and every half hour later on for two hours. Then through statistical analysis, it was found that both light intensity and salinity have signi®cant eects to the die-o rate constant with or without the existence of predators. The eects of the three environment factors can explain a larger portion (about 90%) of the variations exhibiting in the estimated die-o rate constants in the case of without the existence of predators than that (about 50%) for the case with the existence of predators, which indicates that there may be random eects of predatory microorganisms in wastewater causing more variations in the die-o rate constants. Furthermore, through paired t-test, it also indicates that the dieo rate constants for with the existence of predators is signi®cantly larger than that for without the existence of predators. Finally, for the primarily treated sewage from Kaohsiung, Taiwan, by natural disinfection it is estimated that it takes about 100 min during the daytime and 196 min during the nighttime to reach the national guideline concentration of E. coli (1000 cfu/100 ml) of Taiwan in marine environment. # 2000 Elsevier Science Ltd. All rights reserved Key wordsÐocean outfall, natural disinfection, marine environment, light intensity, salinity, rotatable central composite design, Chick's law, E. coli
INTRODUCTION
Ocean disposal is the most original way to treat the wastes generated from man, through which the wastes are diluted by a vast quantity of seawater in the ocean. Until now, ocean disposal is still one of the feasible ways to treat human waste. Most of the large cities located in coastal areas worldwide prefer to discharge their sewage into the ocean through marine outfall systems for convenient and economic reasons (Brook, 1987; Yang, 1995). However, the discharge of untreated or partially treated wastewater into the ocean may result in contamination of the marine environment with pathogenic organisms. Disinfection of the wastewater is consequently *Author to whom all correspondence should be addressed. Tel.: +86-7-525200, extn. 5068; fax: +86-7-5255068; e-mail: [email protected] { E-mail: [email protected] 743
necessary before it is discharged into the ocean, especially in those areas used for recreation and mariculture. Among the chemical disinfectants usually used in disinfection of wastewater chlorine (Cl2) is the most common, due to its characteristics of eectiveness and economics. However, from manufacture through transport and storage to ®nal use, chlorine always poses a continuous threat to operators and the environment. In addition, a variety of halogenated organic compounds, such as trihalomethanes (THMs), halogenated acetic acids (HAAs) and halophenols (HPs), may be formed during chlorination, which may contaminate the marine environment when they are discharged along with the chlorinated wastewater into the ocean through marine outfall pipes (Ali and Riley, 1989; Kristiansen et al., 1994; Kristiansen et al., 1996; Ram et al., 1990). Much research has identi®ed some of these organic halogens which are toxic and/or potentially carcino-
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Lei Yang et al.
genic for human health and aquatic life (Blatchley et al., 1997; Brungs, 1973; Bull et al., 1990; Kool et al., 1982; Meier et al., 1987). Although both ozone (O3) and UV light could be used instead of chlorine in disinfection of wastewater, to prevent the formation of hazardous chlorinated organic compounds, they are costly in operation and maintenance. In addition, ozone at concentrations as low as 0.03 g/m3, is a threat to the health of operators and the environment when it escapes from water during the disinfection operation (Acher et al., 1997; Erb, 1982). Therefore, if the wastewater could be discharged directly into the ocean through submarine outfall systems and disinfected naturally in the marine environment instead of traditional chemical disinfection, two bene®ts would be achieved: (1) cutting down expenses for capitalization, operation and maintenance, and (2) decreasing the hazardous potential to human health and aquatic life. Actually, in the marine environment the natural disinfection eects on wastewater were reported to be controlled by some environmental factors such as dilution, dispersion, solar radiation, salinity, temperature, pH values, presence of toxic substances, competition for nutrients and depredation in several studies (McFeters and Stuart, 1972; Ayres, 1977; Anderson et al., 1979; McCambridge and McMeekin, 1981; Scheuerman et al., 1988; ElSharkawi et al., 1989; Solic and Krstulovic, 1992). It has been found that solar radiation exerts a great in¯uence on bacteria causing their mortality in seawater at much higher rates compared to that of other environmental factors concerned (Alkan et al. (1995)). In addition, the factor of dilution of wastewater by seawater is also important to the eect of disinfection due to its in¯uence on the salinity of seawater and amounts of suspended solids and predators in wastewater, all of which aect the disinfection eects on wastewater. As to the factor of temperature, except in deep ocean, the temperature changes in seawater are insigni®cant in coastal areas, where most of the wastewater from land is discharged. In addition, in the Alkan et al. (1995) study using statistical analyses, it was found that temperature was not a signi®cant parameter for disinfection in the marine environment. Thus, the objective of this study is to investigate the disinfection eects of the factors of light intensity, salinity, volumetric mixing ratio of wastewater and seawater, and the existence of predators in the marine environment on wastewater evaluated by measuring the die-o rate of E. coli, which are regarded as an important indicator of faecal pollution in the marine environment. The feasibility of natural disinfection of wastewater in the marine environment for ocean outfall systems without the process of chlorination may thereby be assessed.
MATERIALS AND METHODS
Preparation of batch test solutions Seawater. In this study, arti®cial seawater was used to run the batch disinfection tests. The receipt of preparing the arti®cial seawater with salinity of 35- was as follows: NaCl 31 g, MgSO4.7H2O 10 g, NaHCO3 0.05 g and deionized (DI) water 1 l. Before being used in the tests, the arti®cial seawater was ®rst sterilized by using an autoclave (P. SELECTA WIKA) at 1208C for 15 min. Wastewater. In this study, the wastewater was taken from the campus sewage treatment plant of National Sun Yat-sen University (NSYSU). The samples were taken by using sterile sampling bags and then sent back to the laboratory immediately to run the tests. If the tests were those without the existence of predators, the samples were autoclaved (1208C for 15 min), ®rst for sterilization and then used in the experiments. The sewage samples were analyzed for their BOD values for each test run. Bacterial stock solution. The test organisms (E. coli JM109) were inoculated from the Microbiology Laboratory of NSYSU into the sterilized Luria±Bertani broth solution and then cultured at 358C for 24 h. After being cultured, the concentrations of the bacteria were in the range of about 107±108 cfu/100 ml. Experimental equipment Equipment employed for the batch tests consisted of a 3-l ¯ask, a magnetic agitator and a sunlight simulator (high-pressure metal halide lamp, Philips, HPI-T, 400 W). This set of equipment was put in a dark room and the light intensity was controlled by adjusting the distance between the lamp and the surface of test solution inside the ¯ask, which was put on the magnetic agitator to keep the solution mixed during the tests. The light intensity (Lux, lumen/m2) was measured and controlled by a light meter (TES Electrical Corp., TES-132). The temperature of the mixed liquor was measured in each test run by a thermometer. Experimental design In this study, the controlled conditions were composed by the four environmental factors: light intensity; salinity; volumetric mixing ratio; and under the condition either with or without the existence of predatory microorganisms in wastewater. Although the factors of temperature T and organic matter concentration BOD in the wastewater would also aect the fate of microorganisms, the temperature T was highly correlated to light intensity L (with a sample correlation coecient, r = 0.9501 in our experiments) and volumetric mixing ratio of seawater to wastewater R was highly correlated with the inverse of the factor of organic matter concentration 1/BOD (with a sample correlation coecient, r = 0.9864 in our experiments). The stronger the light intensity is radiated into the water, the higher the water temperature is achieved. On the other hand, the higher the seawater and wastewater ratio is controlled in the mixed sample, the lower the organic matter concentration is achieved due to the eect of dilution. Therefore either factor from these two sets of factors can be used as a controlled level in the experiments. In this study, we selected light intensity and seawater and wastewater ratio instead of temperature and organic matter concentration as controlled factors, respectively. A rotatable central composite design was employed to investigate the eects of the factors mentioned above. The rotatable central composite design with m factors (m = 3) may be subdivided into three parts. 1. The 2 m points with either high (1) or low (ÿ1) level in each coordinate constitute a 2 m factorial. 2. The 2 m extra points, one at either extreme of each fac-
Natural disinfection of wastewater in ocean tor and at the center of all other factors, are included to form a central composite design. 3. Some points are added at the center to give roughly equal precision for the predicted values of the responses within a circle of radius 1, where for m = 3 six center points are added. A preliminary step in any experiment of this type is to set up the relations between the coded levels and the original level scales of the factor. In our study original levels of the controlled factors in the tests are as shown in Table 1, where the ®ve levels are coded as ÿ1.682, ÿ1, 0, 1, 1.682, respectively. As under the condition that either with or without the existence of predators, for a central composite design with m = 3 factors, there are 20 test runs, therefore, we have a total of 40 test runs, and within each central composite design the order of running the experiment under the factor level combinations is completely random. The advantage of a rotatable central composite design over the fractional or complete three-leveled factorial is in the reduction of the number of treatment combinations required to estimate the squared terms in a second-order model. For more details about rotatable central composite designs, see Box and Draper (1987), and Cochran and Cox (1992). Experimental procedure The test ¯ask was ®rst ®lled with the mixed liquor of arti®cial seawater and sewage with a mixing ratio designed previously. If the test was run for the condition without the existence of predators, the mixed liquor would be sterilized before being added into the ¯ask, and vice versa. A quantity of E. coli cultured stock solution was added to the ¯ask, in which the concentration of the bacteria was controlled in a range of about 107±108 cfu/100 ml. Meanwhile the light intensity was setup to a number as requested in the experimental design by using the light meter mentioned previously. Samples were taken by using sterilized pipettes and collected in sterile sampling bags from the ¯ask. The initial samples were taken at time zero just before exposure to the light and were followed by subsequent samples with a time interval of 30 min. Then we analyzed the collected samples for bacterial counts immediately using the method of membrane ®ltration in Standard Methods (APHA et al., 1992). It was usually assumed that the number of bacteria remaining after contact time t follows the equation derived from the Chick law: Nt N0 eÿkt , where t = contact time, Nt=number of bacteria remaining after contact time and N0=number of bacteria at time zero. The die-o rate constant (k, minÿ1) of E. coli under each combination of controlled environmental conditions designed can be expressed as the slope of the line with log Nt =N0 against time t without an intercept, i.e. log Nt ÿ log N0 ÿkt: Although all numbers of bacteria counted in the experiments are with random errors, under each combination of controlled environmental conditions we consider the following model: log Yt a ÿ kt Et ,
t 0, . . . , n,
745
where Yt is the observed number of bacteria counts at time t, n is the observed time span, a, k are unknown parameters, E'ts are uncorrelated random errors with expectation 0 and common unknown variance s 2. The values of a, k and s 2 all need to be estimated. Later the estimated values of k are used to investigate the eects of the environmental conditions. The relationships between the k values and the environmental factors considered in this study are analyzed statistically, and two multiple regression equations for conditions with and without the existence of predators are then obtained, which are also used to predict the die-o rates of E. coli controlled under a special condition in the marine environment.
RESULTS AND DISCUSSION
Evaluation of the die-o rate of E. coli Estimated die-o rate constants (k ) of E. coli under each controlled environmental condition for both tests with and without the existence of predators are summarized in Table 2 where it can be seen that when it is with the existence of predators, the two largest values of k are 0.087273 minÿ1 in test No. 17 and 0.044930 minÿ1 in test No. 15, which are controlled under the conditions of light intensity L = 50,000 lux, salinity S = 40-, volumetric mixing ratio of seawater to sewage R:1=50:1 for test No. 17, and L = 100,000 lux, S = 20- and R:1=50:1 for test No. 15. Note that in these two cases it is either under the highest salinity level with the other two conditions under middle levels, or under the highest light intensity level with the other two conditions under middle levels. Similarly when it is without the existence of predators, the two largest values of k are 0.02269 minÿ1 under L = 79,730 lux, S = 31.89-, R:1=80:1 in test No. 5 and 0.01778 minÿ1 under condition described above in test No. 15. In the ®rst case it seems to have all the favorable conditions to have larger dieo rate, relative high light intensity, salinity, and seawater level. In the second case it again has the highest light intensity level. About the minimum value of k, in test No. 8 the estimated k values with or without the existence of predators are both negative, which seem to be in con¯ict to the usual understanding that the number of counts of bacteria should be decreasing, i.e. k should be positive. A possible explanation is that in test No. 8, both light intensity and salinity are in relatively low levels, where similar phenomena appear for test No. 4, i.e. the values of k are positive, but are the second or the third smallest, with or without the existence of predators, respectively. The second smallest
Table 1. Levels of factors controlled in the batch tests Factors Light intensity (lux) Salinity (-) Volumetric mixing ratio of seawater to wastewater (R:1) Existence of predators
Levels 0 0 1:1 Yes
20,270 8.11 20:1 No
50,000 20 50:1
79,730 31.89 80:1
100,000 40 100:1
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Lei Yang et al. Table 2. Results of E. coli die-o rate constants (k ) in varying experimental conditions
Test No.
Light intensity (lux)
Salinity (-)
Mixing ratio (R )
Mixed liquor temperature (8C)
Mixed liquor BOD (mg/l)
Die-o rate with existence of predator
Without existence of predator (k, minÿ1)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
79,730 20,270 79,730 20,270 79,730 20,270 79,730 20,270 50,000 50,000 50,000 50,000 50,000 50,000 100,000 0 50,000 50,000 50,000 50,000
31.89 31.89 8.11 8.11 31.89 31.89 8.11 8.11 20 20 20 20 20 20 20 20 40 0 20 20
20 20 20 20 80 80 80 80 50 50 50 50 50 50 50 50 50 50 01 100
27 20 28 21 28 19 29 23 25 25 26 24 25 25 31 16 26 24 25 26
14.2 14.6 15.0 13.4 4.2 3.8 4.3 4.0 6.0 5.3 5.7 6.4 6.1 6.0 6.0 5.8 6.3 6.2 138.0 2.8
0.040159 0.010535 0.004254 0.001847 0.022258 0.013122 0.012140 ÿ0.004673 0.033454 0.027612 0.005932 0.005756 0.019341 0.018604 0.044930 0.005380 0.087273 0.001958 0.005343 0.010155
0.013228 0.006345 0.008164 0.001755 0.022693 0.001254 0.012984 ÿ0.000436 0.003621 0.006105 0.007903 0.006600 0.006599 0.006856 0.017780 0.001024 0.005722 0.003993 0.006128 0.004605
value of k without the existence of predators appeared in test No. 16, where L = 0 lux, S = 20-, and R:1=50:1, i.e. the light intensity is under the lowest level possible in this study. Regarding the environmental factor of depredation, it was found that in some cases the k values estimated in the systems with predators existing are three to ®ve times larger than the values estimated in the systems without predators existing, others are quite close and comparable, which in turn implies there is larger variation for the k values estimated in the systems with predators existing. This also indicates that the mechanisms for the systems with predators existing are more complicated than that without predators existing. In the following Sections the relationships between the k values and the environmental factors with or without the existence of predators are investigated. As discussed above, in test No. 8 with both light intensity and salinity under relatively low levels, the estimated values of k are negative, which might be re¯ecting the real situation or might be due to experimental errors. Also it is noted that in test No. 8 and without the existence of predators, the simple linear model is ®tted with r 2=0.0212 and has a very insigni®cant disinfection eect on E. coli as the time elapsed within the ®rst two hours. Similarly for data set in test No. 4 (which are obtained under the same light intensity and salinity levels as in test No. 8) with the existence of predators, it is noted that although the estimated values of k are positive, the simple linear model is ®tted with only r 2=0.2084 which is not as signi®cant as in the other test runs ®tted with r 2 being at least 0.75. So in this work we have removed the estimated k values for data sets in test No. 8, and in the statistical analysis of test No. 4 hereafter.
Results of statistical analyses Plots of estimated die-o rates vs environmental factors. The relationship between the k value and each environmental factor used in the tests can be observed ®rst through plots of the average of estimated die-o rates at each factor level as shown in Fig. 1. As seen from Fig. 1, the estimated values of k are generally increased proportional to light intensity and salinity for both with and without the existence of predators. However, the positive relationships between the k values and mixing ratio are not as clearly shown for either with or without predators existing in the systems. The reason might be the same as that mentioned previously, i.e. the concentrations of SS in sewage were changed in each test. Response surface models. Under the condition with or without the existence of predators, two response surface models with the form: kp b0
i1
bi x i
X 1Ri
kpÿ b0ÿ
3 X
3 X i1
1Ri
i1
bii x 2i
bij x i x j Z ,
biÿ x i
X
3 X
3 X i1
biiÿ x 2i
bijÿ x i x j Zÿ ,
where fbi , bii , bij g1Ri
Natural disinfection of wastewater in ocean
Fig. 1. Plots of average k values vs light intensity, salinity and volumetric mixing ratio.
747
748
Lei Yang et al.
Z+, Zÿ are the random experimental errors with expectation 0, are built respectively. In each model there are 18 sets of data. The ®nal response surface models are obtained through stepwise regression and the results are presented in Tables 3 and 4. Results of stepwise regression. From Tables 3 and 4, both light intensity and salinity have signi®cant eects to the die-o rate constants with or without the existence of predators. The mixing ratio of seawater to wastewater has an eect on the die-o rate constant through interaction with light intensity in the case of without the existence of predators. In the case of with the existence of predators the eect of salinity is more signi®cant to k than that of light intensity. However, in the case of without the existence of predators, the eect of light intensity is more signi®cant to k than that of salinity. Also from the model ®tting correlation coecient r 2 for the two models, the model for without the existence of predators has a much better ®tting with r 2=0.8959 than that with the existence of predators of r 2=0.5045. That is, without the existence of predatory microorganisms in wastewater, the eects of the three environmental factors can explain a larger portion (about 90%) of the variations exhibiting in the estimated die-o rate constants, but when it is with the existence of predatory microorganisms in wastewater, only 50% of the variations exhibiting in the estimated die-o rate constants can be explained by the eects of the three environmental factors. This is due perhaps to the random eects of the existence of predatory microorganisms in wastewater causing more variations in the die-o rate constants, which cannot be explained through the three environmental factors. In addition, predators may also be aected by the environmental factors of light intensity and salinity. Analysis of variance. From analysis of variance results presented in Tables 3 and 4, the two pure error estimates are obtained by computing the variances of the die-o rates for the six center points (tests 9±14 with identical test conditions). These
give some idea about the values of experimental errors for those tests with or without the existence of predators. It is clear that the experimental errors for the k values with or without the existence of predators are dierent by a magnitude of order 2, which is consistent with results for the mean estimates of k with a dierence with a magnitude of order 1. The sum of squares of the lack of ®t is obtained by subtracting the sum of squares of the pure error from that of the error term. Then the lack of ®t tests is performed to test if the response regression models for the two cases are acceptable. Since the lack of ®t tests give P-values 0.1662 and 0.1557 respectively for the two models, the null hypothesis that the model is adequate is accepted for both models under signi®cance level 0.05. Paired comparison of the die-o rate constants. Now we present estimates of the dierence of the die-o rates with or without the existence of predators, and test if the dierence is statistically signi®cant at 0.05. To avoid confounding eects of the environmental factors in performing the statistical test for the dierence of the k values, we used paired t-test, i.e. under each test condition combination, let kd kp ÿ kpÿ , then perform the usual t-test for variable kd : The results are presented in Table 5. As seen from Table 5, the P-value for the paired t-test is 0.0185, from which it is clear that there is a signi®cant dierence in the k values for the two cases at signi®cance level 0.05. Also, it may be computed that the 95% con®dence interval of kd is (0.0023923, 0.0227863), which means that it is estimated that for the k values in the two cases, with 95% con®dence, the dierence is at least 0.0023923, but no more than 0.0227863. Application of study According to the design criteria of ocean outfall systems, the volumetric mixing ratio of seawater and wastewater should be at least larger than 100:1 when the wastewater plume is raised up to the surface of sea (Grace, 1978). The light intensity of the
Table 3. Results of stepwise regression of die-o rate constant k^p vs light intensity (L ), salinity (S ), and mixing ratio (R ) with existence of predatorsa Variable
Parameter estimate
Standard error
F
P>F
Constant x1 x2
0.01740451 0.01038149 0.01708094
0.00379709 0.00474327 0.00474327
21.01 4.79 12.97
0.0004 0.0449 0.0026
DF Analysis of variance Regression Error Lack of ®t Pure error Total a 2
2 15 10 5 17
r =0.5045; x1=(L ÿ 50,000)/29730, x2=(S ÿ 20)/11.89.
Sum of squares
Mean square
F
P>F
0.00378096 0.00371370 0.00308600 0.00062770 0.00749466
0.00189048 0.00024758 0.00030860 0.00012554
7.64
0.0052
2.46
0.1662
Natural disinfection of wastewater in ocean
749
Table 4. Results of stepwise regression of die-o rate constants k^pÿ vs light intensity (L ), salinity (S ), and mixing ratio (R ) without existence of predatorsa Variable
Parameter estimate
Standard error
F
P>F
Constant x1 x2 x 21 x 1 x3
0.00609537 0.00568561 0.00185080 0.00144177 0.00323067
0.00060097 0.00061931 0.00061931 0.00054112 0.00083683
102.87 84.28 8.93 7.10 14.90
0.0001 0.0001 0.0105 0.0195 0.0020
Analysis of variance Regression Error Lack of ®t Pure error Total
DF
Sum of squares
4 13 8 5 17
0.00047008 0.00005462 0.00004232 0.00001230 0.00052470
Mean square 0.00011752 0.00000420 0.00000529 0.00000205
F
P>F
27.97
0.0001
2.58
0.1557
a 2
r =0.8959; x1=(L ÿ 50,000)/29,730, x2=(S ÿ 20)/11.89, x3=(R ÿ 50)/30.
sun tested on a sunny day in July 1996, has a range between 100,000 and 86 lux from 13:00 to 18:00 h in Kaohsiung, Taiwan. The average light intensity was thus about 60,000 lux. The salinity of seawater was approximately 35- after the mixing ratio of seawater and wastewater was reached 100:1. Meanwhile, there were predators existing in both sewage and seawater. Therefore, we used the light intensity of 60,000 lux and salinity 35- to substitute into the estimated response surface model with the existence of predators to predict the die-o rate (k value) of E. coli, as well as the disinfection eects on the sewage in Kaohsiung discharged into the marine environment under such natural conditions and the predicted value of k is 0.0424 minÿ1. Then the time required for disinfection could be estimated by substituting 0.0424 into the equation derived from Chick's law mentioned previously. The value of T90, which is the time required for 90% die-o of bacterial cells, is estimated to be about 55 min under the light intensity of 60,000 lux and salinity at 35-. In addition, the average number of E. coli in the primarily treated sewage from Kaohsiung was reported to be about 6,700,000 cfu/100 ml. According to the general design criteria of ocean outfall systems that sewage is diluted at least 100 times on the surface of sea, then the number of the bacteria is decreased to 67,000 cfu/100 ml when the sewage plume is raised up to the surface of seawater. Hence, the time required to reach the number of 1000 cfu/100 ml, which is the guideline number of E. coli for high quality seawater in Taiwan, is estimated to be about 100 min in the marine environment during the daytime. For the
nighttime, following the same steps, except that light intensity was changed from 60,000 to 0 lux, it is estimated about 196 min to reach the guideline number of E. coli in marine environment. In summary, the eects of natural disinfection on wastewater in marine environment under high light intensity and salinity are signi®cant. Hence, using the natural factors in the marine environment instead of traditional chlorination for disinfection of wastewater, is feasible for the sewage ocean outfall systems in Kaohsiung, where over 10 months are sunny days in a year. It is estimated that by using this alternative method for disinfecton of sewage, at least US$4 million per year spent in operation and maintenance fees in the sewage treatment plant of Kaohsiung can be saved, which at present uses the method of electrolyzing seawater for disinfection.
CONCLUSIONS
According to statistical analysis on the die-o rate constants (k ) of E. coli performed in this study, the natural environmental factors of light intensity and salinity in the marine environment exhibits signi®cant disinfection eects on wastewater discharged into the ocean through submarine outfall systems. In addition, the existence of predators in both wastewater and seawater shows positive disinfection eects on E. coli in marine environment. Two response surface models corresponding to the cases with or without predators are established:
Table 5. Comparison of the k values with or without the existence of predators Mean 0.0125893
Standard error
T
P >j T j
0.0048327
2.6050
0.0185
750
Lei Yang et al.
k^p ÿ2:8787 10ÿ2 3:4919 10ÿ7 L 1:4365 10ÿ3 S, and k^pÿ 6:5537 10ÿ3 ÿ 1:5299 10ÿ7 L 1:5566 10ÿ4 S ÿ 1:8111 10ÿ4 R 1:6312 10ÿ12 L2 3:6222 10ÿ9 LR, where k^p is the estimated die-o rate constant of E. coli for condition with predators existing (minÿ1), k^pÿ is the estimated die-o rate constant of E. coli for conditions without predators existing (minÿ1), L is the light intensity (lux), S is the salinity (-), and R is the volumetric mixing ratio (seawater:wastewater). Generally, according to Chick's law, the time required to decrease the number of E. coli in sewage (6,700,000 cfu/100 ml on average) to 1000 cfu/100 ml (upper limit for the high quality seawater in Taiwan) in an ocean outfall system designed with a volumetric mixing ratio of seawater and sewage of 100:1 only needs about 100 and 196 min for daytime and nighttime respectively under the 35- salinity level and average light intensities of 60,000 and 0 during daytime and nighttime respectively with the existence of predators. Therefore, it is feasible that the primarily treated wastewater could be discharged directly into the marine environment with high light intensity and salinity by ocean outfall systems without going through the process of chemical disinfection (chlorination), which may save expenses spent on operation and maintenance as well as decreasing the hazardous potential of chlorine to human health and aquatic life in the marine environment. REFERENCES
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