E s t i m a t i o n of t h e r e m o v a l of o r g a n i c pr ior i ty p o l l u t a n t s b y t h e p o w d e r e d a c t i v a t e d

c a r b o n t r e a t m e n t p r o c e s s Gerald J. O'Brien

ABSTRACT: Federal guidelines have been issued that regulate the aqueous discharge concentrations of priority pollutants for the organic chemicals, plastics, and synthetic fibers industries. Insufficient data existed in the literature to allow estimations of the removal of priority pollutants by a wastewater treatment plant (WWTP). The removals of 18 problem organic priority pollutants were measured in five parallel, aerated, con­tinuous, mixed reactors. The influent to the laboratory pilot plants was primary effluent from an industrial 1.75 m3/s (40 Mg/d) WWTP at Du Pont's Chambers Works in Deepwater, N. J. This plant utilizes powdered activated carbon in combination with activated sludge (PACT® Process) in the aeration tanks.

The kinetic coefficients that characterize removal by biodegradation, powdered activated carbon adsorption, and air-stripping were obtained from the pilot-plant data, and a steady-state model was used to predict priority pollutant removals. Good agreement was obtained,"with the exception of three compounds that were batch discharged from the process sources, which invalidated the steady-state assumption. The model was used to design a second stage PACT unit and to determine source control requirements. The model also can be used to estimate the relative im­portance of the three removal mechanisms in order to adjust WWTP operating conditions to enhance the removal of specific compounds. Water Environ. Res., 64, 877 (1992).

KEYWORDS: activated sludge, biodegradation, carbon adsorption, chemical industry, model, organic chemicals, priority pollutants.

EPA has issued guidelines that limit the discharge concentra­tions of 57 organic priority pollutants from the organic chemicals, plastics, and synthetic fibers industries to parts per billion levels. The guidelines for 36 of those compounds were incorporated into the Chambers Works site's NJDEPS permit in June 1991. A knowledge of the factors influencing the removal of each pol­lutant in the wastewater was necessary to design new WWTP facilities for removal of these compounds, and to set source re­duction goals where the limits could not be met by the WWTP.

The Chambers Works WWTP previously consisted of two treatment stages. The wastewater is neutralized and suspended solids are removed in the first stage. Dissolved organics are re­moved by activated sludge mixed with powdered activated sludge (PACT® process) in three, 15 140-m3 (4-mil. gal) aeration tanks. The wastewater is then clarified and the PACT solids are recycled. This paper will discuss the formulation of a kinetic model that was used to design a tertiary stage for the 1.75 m 3/s (40 Mg/d) WWTP in order to improve the removal of those compounds that would have exceeded the permit limits. The kinetic model

was based upon an experimental study of the mechanisms for pollutant removal.

L i t e r a t u r e S u r v e y

An earlier paper (O'Brien et al, 1990) showed that the re­moval of priority pollutants could be enhanced by increased temperature, sludge age, powdered activated carbon (PAC) ad­dition, and by the addition of a second aeration stage. An em­pirical relationship was used to predict the performance of the second stage from pilot plant and full-scale data. However, it did not allow an assessment of the magnitude of the effect of each parameter upon the removal of each problem pollutant, and the data were limited by the large number of effluent con­centrations that were below detection limits. A quantitative as­sessment of the removal under different operating conditions was required to determine the maximum allowable influent concentrations that would not exceed the discharge limits.

Most modeling efforts have focused on gross measures of pol­lutant concentration such as five-day biochemical oxygen de­mand (BOD 5) and chemical oxygen demand (COD). More re­cent studies have addressed specific priority pollutants in the activated sludge process, but a consensus has not been reached on a model acceptable for design purposes. Few models address the PACT process, which incorporates PAC into the activated sludge process, and those that do primarily focus on BOD and COD measurements. Garcia-Orozco and Eckenfelder (1986) compared the removal of 4,6-dinitro-ortho-cresol in a synthetic wastewater for the activated sludge and PACT processes, but the model requires experiments at several sludge ages to evaluate the coefficients. A comprehensive study of both the activated sludge and PACT processes was done by Weber and Jones (1986) for several of the compounds of interest with a synthetic feed, but the PACT process was not modeled.

M o d e l

The model used in this study was a modified form of the equation formulated by earlier investigators for activated sludge systems (Stover and Kincannon, 1983; Blackburn et al, 1984; and Blackburn, 1987). The aeration tank was considered to be a perfectly mixed reactor, which assumed that the concentration in the aeration tank was uniform and identical to the effluent concentration. Lithium chloride tracer studies in the WWTP aeration tanks validated this assumption. The effluent and in­fluent concentrations can be related through a material balance.

N o v e m b e r / D e c e m b e r 1992 877

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( l a )

At steady state, the accumulation term is zero:

(1b)

Where

F = flow rate, K = kinetic coefficient, S = concentration, Sc = aeration tank P A C concentration,

t = time, V = aeration tank volume, and X = biomass concentrations in aeration tank.

Subscripts

A = adsorption, B = biodegradation, e = effluent, i = influent, and s = stripping.

From a solids material balance.

Substituting and rearranging.

(2)

(3)

Where

Cc = influent P A C concentration, θC = solids retention time (sludge age), and θN = hydraulic retention time (V/F).

A s s u m p t i o n s i n M o d e l

The model lumps adsorption by the bacteria into the biode-gradion coefficient, and assumes that biodegradation is first order in both substrate and biomass concentration. The Monod equa­tion reduces to this form at low substrate concentrations. Co-metabolism and toxic effects were ignored. The removal of each priority pollutant was assumed to be proportional to the total biomass present. The biomass concentration in the aeration tank was obtained from measurements of the concentrations of pow­dered activated carbon and primary clarifier overflow suspended solids in the influent and the total measured mixed liquor sus­pended solids ( M L S S ) in the aeration tank.

From equation 2:

(4)

(2a)

(2b)

(5)

Where

Cp = primary solids carryover in the influent to the aeration tank, and

Sp = primary solids concentration in the aeration tank.

Adsorption on P A C was initially assumed to follow the Freundlich isotherm and to be proportional to the concentration of P A C in the aeration tank. Experimentally, it was shown that adsorption was a linear, rather than an exponential, function of substrate concentration at the low concentrations studied. Son-theimer et al (1988) also indicates that adsorption is linear at low substrate concentrations. Weber and Jones (1986) found that adsorption was proportional to the P A C concentration in the influent, but in this study a better empirical fit was obtained with the P A C concentration in the aeration tank. Stripping was assumed to be proportional to the concentration of the pollutant in the aeration tank (Blackburn et al, 1984, and Blackburn, 1987).

The kinetic coefficients were assumed initially to be indepen­dent of the composition and concentration of the wastewater and of interactions between mechanisms. It was found that the adsorption and biodegradation coefficients were not independent for those compounds that biodegraded. The synergistic effect was lumped into the adsorption coefficient for predictive pur­poses.

The steady-state assumption required that the influent, W W T P operating parameters, and vessel volumes be constant with time. In this study, the influent concentration and com­position were continuously changing due to the varied sources of the site's waste streams. However, a dynamic model would have required on-line analyzers to continuously determine the concentration of each compound in the influent and effluent, or frequent sampling. A steady-state model was used because the technology was not available for continuous analyses of this complex waste stream, and the analytical resources to collect and analyze a large number of grab samples were not available.

M e t h o d s a n d M a t e r i a l s

The aeration section of each pilot plant was 7.5 L and was separated from the 2.0-L internal clarifier by a baffle. A i r entered through sparging stones at 0.5 L/minute to four of the pilot-plant aeration tanks but at 1.0 L/minute to the fifth pilot plant which was operated to obtain a D O concentration comparable to the W W T P . A mixer was used in each aeration tank to keep the solids in suspension. The tanks were covered to minimize bacterial inoculation between units, but the covers were not air­tight. The primary effluent from the W W T P , which varied con­tinuously in composition and concentrations, was spiked with a mixture of twelve pollutants in a dilute, ethylene glycol solution. This served as the influent to four of the pilot plants. The fifth pilot plant received the unspiked W W T P primary effluent. The W W T P primary effluent was continuously fed from the W W T P clarifier overflow. The spike solution was prepared weekly to minimize volatilization and biodegradation in the hold tank, and was fed continuously. The hold tank, feed lines, and mix tank were continuously chilled to minimize volatilization. Floating covers reduced volatilization from the hold tank and mix tank. A schematic of the apparatus is shown in Figure 1.

W a t e r E n v i r o n m e n t R e s e a r c h , Vo lume 64, Number 7 878

O'Br ien

F i g u r e 1 — C o n t i n u o u s - f l o w p i l o t p l a n t s .

The four pilot plants which received the spiked feed were operated at a constant temperature (20°C), hydraulic retention time (approximately 8 hours), and sludge age (20 days). The fifth pilot plant mirrored the operation of the WWTP, whose temperature, sludge age, retention time, and other operating conditions varied with time. Nonvolatile compound concentra­tions were analyzed by a contract laboratory by gas chromatog­raphy/mass spectrometry (GC/MS) after extraction of 24-hour composite samples. Grab samples were analyzed for the volatile compounds because the open composite samples lost a significant amount of the volatiles. Grab samples were analyzed in-house by purge-and-trap G C / M S following EPA protocol.

D e t e r m i n a t i o n o f t h e K i n e t i c C o e f f i c i e n t s

The four pilot plants that received the spiked feed were used to determine the kinetic coefficients and the efficacy of the model. The aeration tank of pilot plant 44R, the "stripper" unit, con­tained no PAC or biota. The spiked wastewater flowed through the unit and air was sparged to determine the stripping coefficient (Ks). A mixer was also used so that conditions were similar to the other pilot plants that required agitation to suspend the solids. The unit was cleaned weekly to preclude bacterial formation. The general material balance (equation 3) for this unit reduces to:

Si = Se( 1+KSθN) (6)

A plot of influent versus effluent concentration enabled the determination of Ks from the slope of the regression line fitted through the data and the origin. Figure 2 illustrates the calcu-lational procedure for methylene chloride. The stripping coef­ficients agreed for most compounds, within experimental error, with those calculated from Blackburn's correlation (1987):

Ks = 6.18 X 10- 5 (Q/F)H C

1 0 4 5 (7)

Where

Ks = stripping coefficient, h _ 1 ; Q = air flow, L/hour;

-i o

qT IT)

d c o

O c Qi 3 H—

c

E f f l u e n t C o n e , " 4 4 R " , U G / L

F i g u r e 2 — D e t e r m i n a t i o n o f s t r i p p i n g c o e f f i c i e n t s : m e t h ­

y l e n e c h l o r i d e .

V = aeration tank volume, L; and Hc = Henry's Law coefficient, torr • L/mole.

The stripping coefficients are listed in Table 1. Pilot plant 22B, the "biounit," was operated under identical

conditions as the "stripper unit" except the aeration tank con­tained bacteria from the WWTP. The biounit was run for several months prior to data collection to remove all traces of PAC, which was verified by a solids analysis. Equation 3 for the biounit reduces to:

Si = Se( 1 + KSθN +KBXθN) (8)

A plot of influent versus effluent concentration enabled the determination of KB from the slope of the regression line, since Ks and θN were known, and X was obtained from Equation 5. Figure 3 illustrates the procedure for methylene chloride.

T a b l e 1 — K i n e t i c c o e f f i c i e n t s f r o m p i l o t - p l a n t s t u d i e s a t

2 0 ° C .

KB X 1 0 s L K'A X 1 0 5 L

C o m p o u n d K 8 , h o u r 1 m g . h m g - h

1,2-Dichloroethane 0.31 1.3 10.2

Chloroethane 1.67 2.8 26 .3

Ch loromethane 1.51 10.2 48.5

Chloroform 1.00 2.8 10.0

Methylene chlor ide 0.60 2.6 9.8

Ch lorobenzene 0.80 1.2 47.1

Toluene 1.50 4.2 200

Ethyl benzene 1.36 3.8 53.2

Xylenes 0.76 3.7 8.7

Benzene 1.30 9.9 50

1,2-Dichlorobenzene 0.60 0.3 27

Phenol 0 15.0 400

4-Nitrophenol 0 0.1 216

2-Nitrophenol 0 0.7 197

2,4-Dinitrotoluene 0 1.9 200

2,6-Dinitrotoluene 0 0.4 10.5

Ni t robenzene 0.01 3.1 500

Naphthalene 0.20 2.7 57.7

4,6-Dinitro-o-cresol 0 2.1 6.1

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mJ o r> CL (/) 10

6 c o

O

c o 3 c

Effluent Cone, "22B", UG/L

F i g u r e 3 — D e t e r m i n a t i o n o f b i o d e g r a d a t i o n c o e f f i c i e n t :

m e t h y l e n e c h l o r i d e .

5

<0 o O

6 c o o c cd 3

UJ

Influent Cone, "5SP", UG/L

F i g u r e 4 — D e t e r m i n a t i o n o f a d s o r p t i o n c o e f f i c i e n t : m e t h ­

y l e n e c h l o r i d e .

The KB values were much lower than reported in the literature (Stover and Kincannon, 1983). Possible reasons for the order of magnitude differences include differences in substrate con­centrations, substrate composition, the biota composition and concentration, the toxicity of the wastewater, and experimental methodology. For example, the model assumes that the removal of each compound is proportional to the total biomass. The specific compounds under study each comprised only 0.02-2% of the total organics present, while in Stover and Kincannon's 1983 study, the specific compounds were a far larger percentage of the influent. Also, the wastewater composition bore no re­semblance to the synthetic feed used by Stover and Kincannon and differences in biodegradation rates are to be expected. Based upon prior experience, the removals of BOD and DOC (dissolved organic carbon) were typical of a laboratory biounit receiving Chambers Works wastewater (89% and 62%, respectively), which indicated the biounit performed normally.

Pilot plant G06, the PAC unit, was operated similarly to the biounit except PAC was added instead of biomass to seed the reactor. PAC was added at 100 mg/L concentration to the in­fluent stream. Steady state was considered to be achieved when both the MLSS and the removal of total organics were constant. This unit was treated with formaldehyde to kill bacteria when the oxygen uptake started to increase. Equation 3 can be rewritten as:

Se = Si (9) 1 + K s θ N + KACcθc

A regression line was fitted to a plot of effluent versus influent concentration and KA was determined from equation 9 as shown in Figure 4.

The kinetic coefficients were used in equation 3 to predict the effluent concentrations of pilot plant G04, the PACT unit, that contained both PAC and bacteria. The predicted effluent con­centrations were greater than the actual data for the biodegrad­able compounds, apparently due to a synergism between the bacteria and the PAC. It is speculated that biodegradation was inhibited in the biounit by toxins in the wastewater, that were adsorbed on the PAC in the PACT unit. Modified adsorption coefficients were obtained from the slope of the PACT unit data plots, the Ks and KB values previously obtained, and equation

3 (see Figure 5). Hence, any synergism and errors in Ks and KB

were lumped into the modified adsorption coefficient, K'A. The values obtained from the PACT unit were the same as those obtained from the PACT unit for several of the chlorinated vol­atile compounds, presumably because they are relatively non­biodegradable. Where insufficient data existed, WWTP data were used to estimate K'A. The kinetic coefficients are summarized in Table 1. Table 2 compares the average removal for the PACT unit versus the model predictions based upon K'A values. Good agreement is not proof of the efficacy of the model, since some of the K'A values were obtained from the PACT unit data.

M o d e l , W W T P , a n d " T r a c k e r " C o m p a r i s o n

The fifth pilot plant, the "tracker," was run at the WWTP operating conditions except for the air-flow rate to aeration vol­ume ratio (Q/V). The sludge age, retention time, temperature, and PAC addition were changed the day after a change in the WWTP conditions (average values were 29 days, 10 hours, 13-36°C, and 68 mg/L, respectively). The stripping coefficients were corrected for the difference in air-flow rate and average values were used for sludge age, feed rate, and PAC concentration in equation 3. The change in the kinetic coefficients with tem-

3

6 c o o c (d 3 Hi

Influent Cone, "5SP", UG/L

F i g u r e 5 — D e t e r m i n a t i o n o f a d s o r p t i o n c o e f f i c i e n t w i t h

b a c t e r i a l s y n e r g i s m : m e t h y l e n e c h l o r i d e .

W a t e r E n v i r o n m e n t R e s e a r c h , Vo lume 64, Number 7 880

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T a b l e 2 — P r e d i c t i o n o f r e m o v a l s f o r P A C T ® p i l o t p l a n t

" G Q 4 . "

C o m p o u n d P r e d i c t e d

% r e m o v a l A c t u a l " G 0 4 "

% r e m o v a l

1,2-Dichloroethane 89.5 85.9

Chloroethane 96.6 96.6

Ch lo romethane 97.8 98.9

Ch loro form 93.9 93.0

Methy lene chlor ide 92.2 92.2

Ch lo robenzene 96.8 96.8

Toluene 99.1 97.6

Ethyl benzene 97.6 91.6

Xylenes 93.1 90.2

Benzene 97.7 — 1,2-Dichlorobenzene 94.8 97.8

Phenol 99.5 — 4-Nitrophenol 99.1 — 2-Nitrophenol 99.0 90.8

2,4-Dinitrotoluene 99.0 99.0

2,6-Dinitrotoluene 84.4 79.4

N i t robenzene 99.6 99.3

Naphtha lene 96.9 90.0

4,6-Dinitro-o-cresol 82 .4 81.2

perature changes was unknown, hence no corrections were made to the coefficients originally determined at 20 °C. The influent to the tracker was not spiked, so there were few data points for those nonvolatile compounds which were highly removed. The predicted removal and the data averages in Table 3 agreed within one standard deviation, with the exception of dichloroethane, chloroform, and methylene chloride. The principal waste streams which contained these three compounds were discharged to the WWTP by batch, rather than continuously, and the standard deviations for these compounds were two to three times the average influent concentrations.

T a b l e 3 — P r e d i c t i o n o f r e m o v a l s f o r t r a c k e r ( " 4 6 Z " ) p i l o t

p l a n t .

C o m p o u n d P r e d i c t e d

% r e m o v a l A c t u a l " 4 6 Z "

% r e m o v a l

1,2-Dichloroethane 89.7 97.7

Chloroethane 96.9 97.5

Ch lo romethane 97.8 96.8

Ch loro form 94.3 87.6

Methy lene chlor ide 92.5 85.9

Ch lo robenzene 96 .9 96.5

Toluene 99.1 97.8

Ethyl benzene 97.6 97.5

Xylenes 93.4 96.3

Benzene 97.7 97.6

1,2-Dichlorobenzene 95.0 99.2

Phenol 99.5 > 9 9 . 0

4-Ni t rophenol 99 .0 99.5

2-Nitrophenol 98.9 90.6

2,4-Dinitrotoluene 99 .0 97.2

2,6-Dinitrotoluene 84 .0 92.4

N i t robenzene 99.6 99.9

Naphtha lene 96 .9 > 9 7 . 0

4,6-Dinitro-o-cresol 80.6 83.0

The effluent concentrations from the tracker were less than the WWTP values for the volatile compounds, despite the fact that the operating conditions were almost identical. (Sludge age averaged 23 days, temperature ranged from 13 to 36°C, hydraulic retention time averaged 10.5 hours, and PAC averaged 63 mg/ L for the WWTP.) The reason was that the Q/ V was greater for the tracker and, therefore, more stripping was occurring. Equa­tion 7 was used to calculate Ks values for the WWTP from the pilot-plant values and the Q/ V ratios. The WWTP Ks values were 25% of the tracker values. Table 4 compares the model predictions with the WWTP averages over the same time periods (1 / 1 to 3 / 8 / 90 and 8 / 2 3 to 10 / 18 / 90). Agreement in removal efficiency was generally within one standard deviation, again with the exception of the three multichlorinated aliphatics. The predicted effluent concentration for many of the compounds was close to the measured averaged value (Table 4 ) . Note that at low concentrations (high removals), small absolute differences between measured and predicted values caused large changes in the concentration ratio ("scale-up factor" in Table 4 ) .

D i s c u s s i o n o f E r r o r i n P r e d i c t i v e M o d e l

Composite or grab samples, while perfectly adequate for steady-state operation, are not representative of unsteady-state behavior. Grab samples represent only a snapshot in time, while composites are time-averaged samples. A further complexity in obtaining a representative sample for unsteady-state operation is introduced by the holdup volume of the WWTP even for compounds which are not removed. Figure 6 illustrates that plugflow in the WWTP will require the effluent sample collection time to be offset from the influent sample by the detention time. Mixing in the WWTP not only requires an additional offset, but precludes obtaining an effluent sample that is 100% represen­tative of the influent due to the mixing of the influent with the

T a b l e 4 — M o d e l

r e m o v a l s .

p r e d i c t i o n v e r s u s W W T P a v e r a g e

C o m p o u n d P r e d i c t e d

% r e m o v a l A c t u a l W W T P

% r e m o v a l S c a l e - u p

f a c t o r a

1,2-Dichloroethane 83.7 57.5 2.61

Chloroethane 93.9 93.4 1.07

Chloromethane 96.5 96 .3 1.05

Chloroform 88.7 71.1 2.55

Methylene chloride 86.9 62.8 2.83

Chlorobenzene 95.1 94.9 1.02

Toluene 98.7 97.2 2.13

Ethyl benzene 96.1 95.9 1.03

Xylenes 88.0 87.1 1.07

Benzene 96.4 90.5 2.66

1,2-Dichlorobenzene 91.8 95.3 0.57

Phenol 99.3 99.9 0.10

4-Nitrophenol 98.7 98.7 1.00

2-Nitrophenol 98.6 98.6 1.00

2,4-Dinitrotoluene 98.6 98.7 0.93

2,6-Dinitrotoluene 79.7 79.6 1.01

Ni t robenzene 99.4 99.7 0.48

Naphthalene 95.7 95.7 1.01

4,6-Dinitro-o-cresol 77.4 76.8 1.03

a The scale-up factor is the ratio of the average measured effluent con­

centrat ion to the pred ic ted effluent concent ra t ion.

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tank contents. The disparity between the shapes of the influent and effluent concentration profiles in Figure 6 was due to the mixing characteristics of the hypothetical WWTP. No removal by biodegradation, stripping, or adsorption was assumed in this hypothetical illustration.

Despite the limitations of the model, the predictions of re­moval efficiencies were adequate except for the three, multichlo-rinated volatile compounds. Namkung and Rittmann (1987) also experienced aberrant behavior of chloroform and methylene chloride in their study of the Calumet WWTP. In the present study, the batch discharge of these compounds, which invalidates the steady-state assumption, was the source of the prediction errors. Work in progress with a dynamic model, which will be the subject of a future paper, has shown that the effluent con­centration profile can be predicted from the kinetic coefficients in Table 1.

S c a l e - u p

The ratio of the actual average WWTP effluent concentration to the predicted value for each compound in Table 4 was used to correct the model. The scale-up factors were expressed as fractional removals and used to predict tertiary-stage removals as follows:

but,

(10)

(11)

(12)

Tertiary stage:

(13)

(14)

Where

C = concentration, R = fraction removed, and f = scale-up factor.

Subscripts

0 = influent, 1 = first-stage PACT effluent (secondary),

2 = second-stage PACT effluent (tertiary), a = actual data, and

m = calculated from model.

The tertiary model prediction was obtained from a steady-state material balance analogous to equation 1, which led to an equation similar to equation 3:

(15)

and

(16)

The WWTP tertiary removals were predicted from equation 14 in conjunction with the model (equation 15) and the scale-up factors (equation 12). The tacit assumption was that the first and second stage of PACT would have the same scale-up factors and kinetic coefficients.

D e s i g n o f t h e T e r t i a r y S t a g e

The tertiary stage was sized for priority pollutant removal based upon the model predictions and scale-up factors along with economic and operating constraints. Sludge age, aeration tank volume, PAC concentration, and temperature were oper­ating parameters that could be increased to maximize removal. Economic constraints limited the size of the aeration tank, PAC addition, and temperature control. Operating constraints, such as foaming and settling, limited the sludge age and the amount of PAC. Cost of removal had to be balanced versus source re­duction. The variability of the data was an important consid­eration in determination of influent limits. Removals were not constant due to changes in temperature, waste composition, sampling, analytical errors, and other factors. Statistical methods were used in conjunction with the equations developed and the

T a b l e 5 — E f f e c t o f a c t i v a t e d s l u d g e a n d P A C T p r o c e s s e s

i n s u p p r e s s i n g s t r i p p i n g ( b a s e d o n m o d e l ) .

% S t r i p , a c t i v a t e d

% S t r i p , s l u d g e % S t r i p , P A C T C o m p o u n d s t r i p o n l y p r o c e s s p r o c e s s

1,2-Dichloroethane 45 31 13

Chloroethane 81 61 27

Chloromethane 80 35 14

Chloroform 72 49 3 0

Methylene chlor ide 61 37 21

Ch lorobenzene 68 55 10

Toluene 80 52 5

Ethyl benzene 78 52 14

Xylenes 67 38 24

Benzene 77 32 12

1,2-Dichlorobenzene 61 57 13

Phenol 0 0 0

4-Nitrophenol 0 0 0

2-Nitrophenol 0 0 0

2,4-Dinitrotoluene 0 0 0

2,6-Dinitrotoluene 0 0 0

Ni t robenzene 3 1 0

Naphthalene 34 17 2

4,6-Dinitro-o-cresol 0 0 0

W a t e r E n v i r o n m e n t R e s e a r c h , Vo lume 64, Number 7

F i g u r e 6 — S a m p l i n g p r o b l e m s i n t r o d u c e d w i t h u n s t e a d y -

s t a t e o p e r a t i o n .

8 8 2

Co

nc

en

tra

tio

n

T i m e , H o u r s

U n s t e a d y S t a t e

O'Brien

T a b l e 6 — T o t a l r e m o v a l s b y a e r a t i o n , a c t i v a t e d s l u d g e ,

a n d P A C T p r o c e s s e s ( b a s e d o n m o d e l ) .

C o m p o u n d S t r i p p i n g A c t i v a t e d s l u d g e PACT®

1,2-Dichloroethane 45 62 84 Chloroethane 81 86 94 Chloromethane 80 91 96 Chloro form 72 81 89 Methylene chlor ide 61 76 87 Chlorobenzene 68 74 95 Toluene 80 87 99 Ethyl benzene 78 86 96 Xylenes 67 81 88 Benzene 77 91 96 1,2-Dichlorobenzene 61 64 92 Phenol 0 90 99 4-Nitrophenol 0 8 99 2-Nitrophenol 0 29 99 2,4-Dinitrotoluene 0 54 99 2,6-Dinitrotoluene 0 21 80 Ni t robenzene 3 66 99 Naphtha lene 34 69 96 4,6-Dinitro-o-cresol 0 57 77

discharge limits to determine the influent limits for the WWTP. Compounds whose concentrations could have exceeded the limits were reduced at their sources.

R e m o v a l s b y M e c h a n i s m s

The fractional removals by each mechanism for the first PACT stage are from equation lb:

Stripping: Rs= KsdNSe/Si (17)

Biodegradation: RB = KBXθNSe/Si (18)

Adsorption: RA = KAθcCcSe/Si (19)

It has been observed (Weber and Jones, 1986, and Dietrich et al, 1988) that stripping is suppressed in the PACT process due to the PAC. This is due to the additional reduction in effluent concentration by adsorption, which reduces the stripping rate (equation 17). Equation 17 in combination with equations 3, 6, and 8 allows the calculation of the stripping that occurs in a PACT unit, an activated sludge unit, or in the absence of both PAC and biomass. Table 5 shows the suppression of stripping for each case as estimated from the model without the scale-up factors. The effect of activated sludge kinetics in reducing strip­ping by a similar calculational procedure has been shown pre­viously (Blackburn, 1987, and Namkung and Rittmann, 1987). However, stripping was a more important mechanism in this study than observed by these investigators because of the reduced biodegradation rates with Chambers Works wastewater in the absence of PAC. Table 6 shows the total removals for these processes as estimated from the model without scale-up factors.

C o n c l u s i o n s

A steady-state model based upon pilot-plant data was sur­prisingly effective in predicting the removal of priority pollutants bya 1.75 m 3/s(40Mg/d) industrial WWTP that used the PACT process. The prediction of three multichlorinated aliphatic com­pounds was unsatisfactory due to batch discharge from the pro­cess sources which invalidated the steady-state assumption. The model was corrected for scale-up and used to size a second-stage, PACT, aeration tank and predict performance.

Stripping, biodegradation, and adsorption rates were found to be linear with substrate concentration. Stripping coefficients agreed with Blackburn's correlation within experimental error. The model shows that the competing kinetics of both biodeg­radation and carbon adsorption reduce the amount of volatiles which are stripped. However, stripping was a more important mechanism than previous studies had indicated.

A c k n o w l e d g m e n t s

Credits. The author would like to thank Dr. Robert A. Reich, Du Pont, and Professor C. P. Leslie Grady, Clemson University, for valuable comments; H. Ron Raleigh and Dennis S. Zawadzki, Du Pont, for operating the pilot plants; and Susan M . Solek and Terry J. Quinto, Du Pont, for G C / M S analyses.

Author. Gerald J. O'Brien is a Senior Engineering Associate with E. I. Du Pont de Nemours and Company. Correspondence should be addressed to him at Jackson Laboratory, Chambers Works, Deepwater, N . J. 08023.

Submitted for publication May 21, 1991; revised manuscript submitted April 13, 1992; accepted for publication May 26, 1992. The deadline for discussions of this paper is March 15, 1993. Discussions should be submitted to the Executive Editor. The authors will be invited to prepare a single Closure for all discus­sions received before that date.

R e f e r e n c e s

Blackburn, J. W., et al. (1984) Prediction of the Fates of Organic Chem­icals in a Biological Treatment Process—An Overview. Environ. Prog, 3, 3, 163.

Blackburn, J. W. (1987) Prediction of the Fates of Organic Chemicals in a Biological Treatment System. Environ. Prog., 6, 4, 217.

Dietrich, M. J., et al. (1988) Removal of Pollutants from Dilute Waste­water by the PACT® Treatment Process. Environ. Prog., 7, 2, 143.

Garcia-Orozco, J. H., and Eckenfelder, W. W. (1986) Modeling and performance of the activated sludge-PAC process in the presence of 4,6-dinitro-o-cresol. J. Water Pollut. Control Fed., 58, 320.

Namkung, E., and Rittmann, B. E. (1987) Estimating volatile organic compound emissions from publicly owned treatment works. J. Wa­ter Pollut. Control Fed., 59, 670.

O'Brien, G. J., et al. (1990) Carbon Columns vs. the PACT® Process for Priority Pollutant Removal. Water Environ. Technoi, 2, 9, 72.

Sontheimer, H., et al. (1988) Activated Carbon for Water Treatment. Distributed in U.S.A. by AWWA Research Foundation, Denver Colo., 119.

Stover, E. L., and Kincannon, D. F. (1983) Biological treatability of specific organic compounds found in chemical industry wastes. J. Water Pollut. Control Fed., 55, 97.

Weber, W. J., and Jones, B. E. (1986) Toxic Substance Removal in Activated Carbon and PAC Treatment Systems. EPA-600/2-86/ 045, Accession No. PB86-182425, U. S. EPA, Washington, D. C.

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