Environ. Sci. Technol. 1992, 26, 1627-1635
Impact of Chlorophenols and Chloroanilines on the Kinetics of Acetoclastic Methanogenesis Chrlstlan Davles-Venn,+ James C. Young,*,$and Henry H. Tabak5
Engineering Science, Inc., Fairfax, Virginia 22030, Department of Civil Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, and U.S. Environmental Protection Agency, Cincinnati, Ohio 45268 Bench-scale tests were conducted to assess the impact of monochlorophenols and monochloroanilines on the kinetics of acetoclastic methanogenesis. The procedure involved adding toxicant at two to three concentrations to cultures transferred from an acetate-enriched seed culture reactor. A control without toxicant was included as a basis for comparison. Unacclimated cultures were used to minimize the biodegradation of the toxic organic chemicals during the test. A finite-difference, nonlinear, least-squares algorithm was used to estimate kinetic parameters by obtaining a best fit of the experimental data to the classical Monod growth and substrate utilization model. Resulting kinetic coefficients revealed substantial changes in both the maximum rate of acetate conversion, k, and the half-velocity coefficient, K,, when both chlorophenols and chloroanilines were used. Therefore, mixed inhibition was occurring.
Introduction Anaerobic microbial reactions have received increased attention over the past decade as a potential means of degrading complex organic chemicals. This attention has resulted in significant advances in identifying the principal microorganisms involved in the anaerobic degradation process, unraveling the complex degradative pathways used by these microorganisms, and demonstrating the potential for anaerobic degradation of a large number of anthropogenic compounds. Despite these advances, there is limited information regarding the impact of toxic organic chemicals on the kinetics of the degradation of other organic substrates and a lack of definition of the various chemical, physical, and biological factors that may influence the nature and extent of the inhibitory effects. Such knowledge is essential for predicting the impact of toxic chemicals on anaerobic wastewater treatment processes and preventing inefficient treatment or potentially costly upset of treatment plant operations. To address the need for better definition of toxicant/ substrate interactions, bench-scale tests were conducted to assess the impact of toxic organic chemicals on the kinetics of acetoclastic methanogenesis and to relate the effects to the classification and molecular structure of the toxicants (I). Teats conducted to date by other researchers have used cultures obtained from different sources and grown under a variety of environmental conditions, making comparison of test results very difficult. Therefore, a second objective of the present study was to provide a controlled culture growth environment and uniform test procedures to minimize experimental error and to serve as a basic protocol for future tests. The test approach forms a part of a broader multilevel protocol designed to provide a consistent means of assessing the fate and effect of toxic organic chemicals in anaerobic processes (2). t Engineering Science, Inc.
* Pennsylvania State University.
US.Environmental Protection Agency.
0013-936X/92/0926-1627$03.00/0
Anaerobic Reactions Anaerobic treatment reactions involve four main stages of biodegradation (3). In the first stage, hydrolysis of complex organic materials produces soluble products. Fermentation of the hydrolysis products forms fatty acids, alcohols, carbon dioxide, and hydrogen. In the third, or acetogenesis stage, the fermentation products are converted further into hydrogen, carbon dioxide, and acetate. Finally, the fourth stage involves two physiologically different groups of methane-forming bacteria: acetoclastic methanogens decarboxylate acetate to form methane and carbon dioxide while hydrogenotrophic methanogens produce methane from the reduction of carbon dioxide with hydrogen. In view of the complexity of anaerobic reactions, we have adopted the approach of dividing the anaerobic biotransformation sequences into specific reactions that can be isolated and studied separately and in a stepwise manner, working from simple and known reactions toward the more complex situations. Consequently, the study described in this paper concentrates specifically on the acetoclastic methanogenesis reaction. Subsequent test programs expand the assessment of toxic effects to include acetogenic reactions (2, 4). Experimental Program Experimental Design. The experimental program consisted of two phases. Batch screening tests (2) were used in phase I to select the concentration levels of toxicants-representing low, intermediate, and moderately high toxicity-to be used for kinetics testing. The phase I procedure was based on conventional batch anaerobic toxicity assay (ATA) techniques ( 5 6 ) . A second series of batch tests was then conducted in phase I1 to assess the effect of the toxicant on the rate of acetate conversion at different toxicant levels and initial acetate concentrations. Batch bioassay techniques were employed because they are relatively simple and can be performed within 12-48 h, thereby minimizing major shifts in the microbial population during tests. Acetate-enriched seed cultures of 12-L volume were grown in 13-L glass vessels maintained at 35 "C and operated at a 20-day solids retention time (0.05 day-l dilution rate). Complete mixing was provided by using magnet stirring units. These reactors were initially seeded using cultures obtained from a municipal anaerobic sludge digester and then were operated for over 90 days prior to use for testing. These seed culture reactors were fed one time per day on a draw-and-fill basis at an organic loading rate of 0.938 g of acetic acid L-' day-', using acetate as the sole organic substrate. The nutrient/mineral/ buffer medium listed in Table I was used in the seed culture reactors as well as in all cultures transferred to serum bottles. Unacclimated cultures were used to minimize the biodegradation of the toxic organic chemicals throughout the duration of the test. Steady-state conditions were indicated when daily gas production rate and biomass concentration were within the quality control limits of 760 f
0 1992 American Chemical Society
Environ. Sci. Technol., Vol. 26, No. 8, 1992
1627
Table I. Formulation of the Nutrient/Mineral/Buffer Medium Used in Test Cultures concn in test culture (mg/L) KzHPOI KHZPO,
1750 1350
concn in test culture (mg/L)
Nutrients NazS04 NH4Cl
Table 111. Experimental Setup for Phase I1 Kinetic Tests no. of test reactors 1 1 3
150° 530
1
6000
CaCl2-2H20 MgC12.6H20 FeC12.4H,0 MnClZ.4Hz0 H3J303 ZnCl, a
Minerals 150 CUCl, 200 Na2Mo04. 20 2H20 0.50 CoC12.6HzO 0.25 NiCl2-6H20 0.25 NazSe04
0.15 0.05 2.50 0.25 0.25
150 mg/L Na2S04in the NMB medium provides 5 mg of SO:-
L-' day-' to the culture reactors. Table 11. Toxicant and Acetate Concentration Used in Phase I1 Kinetic Tests run series 1 2 3 4 5 6
toxicant
toxicant concns ( m u L)
2-chlorophenol 0, 300, 600 3-chlorophenol 0, 100, 300 4-chlorophenol 0, 50, 100, 300 2-chloroaniline 0, 200,400, 800 3-chloroaniline 0, 200, 400, 800 4-chloroaniline 0, 100, 200, 300
init acetate concns (mg of HAC/L) 469, 938 469, 938 375, 656,938 375, 656, 938 375, 656, 938 469, 938
90 mL L-l day-' and 530 f 64 mg/L, respectively. The procedure for each test phase involved transferring 400 mL of seed culture under anaerobic conditions to each of a number of 500-mL serum bottles which had previously been flushed with a mixture of 70% nitrogen and 30% carbon dioxide. Prior to the start of the test, the cultures were stabilized over a period of 3-4 days by daily removal of 5% of the mixed liquor from each serum bottle and addition of an equal volume of stock acetate substrate (17.9 mL of acetic acid/L). The test temperature was maintained at a constant 35 "C, and the serum bottles were thoroughly mixed using magnet stirring devices. Gas production was monitored manually using syringes or by means of an automatic anaerobic respirometer to verify activity of the transferred cultures (7). The test cultures were selected from among the serum bottles that consistently produced the expected amount of gas as indicated above for the seed culture reactor. This approach ensured the use of cultures having essentially the same characteristics from test to test. Six compounds representing isomeric series of chlorosubstituted phenols and chloro-substituted anilines were selected for testing (Table 11) because they are commonly encountered in industrial wmtestreams and present concerns regarding their toxic effects on the environment. The experimental setup for the phase I1 tests is summarized in Table 111. A test control reactor consisting of seed culture plus acetic acid but without toxicant provided baseline kinetic parameters. An abiotic control was included to determine if acetate conversion was affected by nonbiological reactions (such as adsorption and volatilization) that must be accounted for in the test measurements. Abiotic conditions were accomplished by inhibiting the growth of the seed culture using 100 mg of HgC12/L. Three test reactors were spiked with toxic organic chemicals and operated at the same environmental conditions 1828
function test control abiotic control test reactors test duplicate
toxicant dnnn
Buffer NaHCO,
materials added seed + acetate seed + acetate + HgCl, seed + acetate + toxicant at three dose levels seed + acetate + duplicate
Envlron. Sci. Technol., Vol. 26, No. 8, 1992
as the control. A test duplicate was used to assess repeatability between test replicates. Samples (10 mL) were removed from each serum bottle at close time intervals for up to 24 h, transferred to sealed, septum-capped vials containing two drops of 8 g/L mercuric chloride for sample preservation, and centrifuged (G = 5125) for 30 min. Aliquots (5 mL) of supernatant were then transferred to clean 5-mL septum-capped vials containing one drop of concentrated sulfuric acid to adjust the pH to Kso
(3)
k C ko
K, = K,,
(4)
k C ko
K, C K,o
(5)
noncompetitive uncompetitive mixed
K, > K,o (6) where k,ko are the maximum specific substrate conversion rate in the presence and absence of inhibitory substances, respectively and K,, Ksoare the half-velocity coefficients in the presence and absence of inhibitory substances, respectively. Most inhibition models then consist of modifications of eq 1 as follows:
k C ko
k = k,[k*] Ks = K,o[K,*l
(7)
(8)
where k* and K,* are inhibition terms. A number of equations have been proposed for describing these k* and K,* terms but none has been shown to fit all toxic situations (12).As indicated in subsequent sections, our data seemed to follow the traditional linear relationship based on enzyme reactions (13), or
k* = [ l + I / k ; ] - l
(9)
K,* = [ l + I/K,i]
(10)
where ki and KSiare inhibition coefficients and I is the toxicant concentration. The procedure for determining values for the inhibition coefficients involved first estimating values of ko and Ks0 for the control reactors and k and K, for each toxicant test reactor using a finite-difference, nonlinear, least-squares method to fit eqs 1and 2 to batch test data (I). The model solution required input of initial estimates for k and K,, which were then varied, followed by using a two-dimensional grid search until the residual sums of squares of the differences between the experimentally measured and estimated substrate concentrations were minimized (1,10). To reduce the errors associated with multiparameter estimation from a single data set (14),only k and K, were considered as unknowns. Values of Y (0.40 mg of biomass/mg of acetate conversion) and Kd (8.024/day) for acetate-enriched cultures were obtained from measurements made on the seed culture reactors and verified by published data obtained under conditions similar to those of our study (9, 15,16). The acetoclastic methanogen biomass concentration, Mo, was 482 mg/L, which represented 91% of the total biomass concentration of 530 mg/L* Values of k and K , obtained from the above modeling procedure were then entered into the linear form of the inhibition terms expressed by eqs 9 and 10 to provide best-fit estimates for kiand Ksi. This two-level modeling approach was adopted to reduce the errors commonly associated with attempts to estimate a large number of variables simultaneously (10,11, 17). One of the factors that must be taken into consideration in the modeling of substrate conversion data from batch tests is the sensitivity of the model to the number and distribution of data points in different regions of the substrate conversion curves. Typically, k is most sensitive to the accuracy of the data collected at high substrate concentrations (see Figure 1). A sufficient number of points must be collected at low substrate concentrations, where K, is most sensitive to the accuracy and number of data points obtained. Also, the influence of biomass decay must be considered if long time periods are required for substrate conversion (14,15,18).
Results (a) Phase I. The results of phase I prescreening tests are presented in Figure 2 for the six chemicals studied. These graphs show gas production for each test reactor expressed as a percentage of the cumulative amount of gas produced by the control at the end of the incubation period. Corrections for gas produced in the seed blank were applied to all test reactors. Chlorophenols. The chlorophenols exhibited distinctly different toxic effects on gas production (Figure 2A-C). Figure 2A shows that 2-chlorophenol (2-CP) was only slightly toxic at the 100 mg/L level but showed gradually increasing inhibitory effects as the concentration was increased to 1000 mg/L. Gas production was essentially completely inhibited at 1000 mg of 2-CP/L, and 50% inhibition occurred at -600 mg/L. There was no evidence of recovery throughout the 24-h test period. On the basis of these results, 300 and 600 mg/L 2-chlorophenol concentrations were selected for phase I1 tests. The toxicity of 3-chlorophenol (3-CP) increased steadily with increases in concentration, but a dramatic change occurred between 300 and 600 mg/L (Figure 2B). At 600 mg/L and above, 3-chlorophenol was highly toxic and caused gas production to essentially cease. From these results, 100 and 300 mg of 3-CP/L concentrations were selected for phase I1 tests. Inhibition of gas production Environ. Sci. Technol., Vol. 26, No. 8, 1992
1629
-
120
2-CHLOROPHENOL
100 c
p-
8 80
L
w
n- 60
s2 a
40
i;;l
20
Y
A
rr
120
3-CHLOROPHENOL
t 50 q / L 4 a 0
40
x
'
20
w
nq/L 3 4 2 300 r q / L 3-cp xx) q / L 3cp
w
I
w
'
6w m/L 3 4 2
_-
/ryuuuyII
0
0
nq/L 4€P
nq/L 4 e xx) mg/L 4 e Kx r q / l 4 e
a
I]
D
2-CHLOROANILINE
E
3-CHLOROANILINE
i
4-CHLOROANILINE
F
a0
Kx)
80
80 t
MI
0
x
'
40
0
50 r q / L 243
w
rq/L 2 - 3
MI
2w nq/L 2ul Mo rq/L 2 4 Bw r q / L 243
40
m
20
5
0
IO
15
20
I 25
C.
80
t
0
4-CHLOROPHENOL
yx)
60
acxlrq/L 2cp
120
8
0
0
Xi
20
30
40
50
60
M
0
TIME, hours
TIME, hours
20
xi
40
TIME, hours
50
Figure 2. Relative gas production measured during phase I screening tests.
Table IV. Estimated Kinetic Coefficients, k and K , , for Various Concentrations of Acetate and Chlorophenols 2-Chlorophenol So = 938 mg/L HAC
tox conc (mg/L) 0
300 600
k (h-l)
Ka (mg/L)
0.2162 0.1059 0.0665
54.1 37.0 86.4
So = 469 mg/L HAC k (h-l) K, (mg/L)
combined data k (h-l) K , (mg/L)
0.2445 0.1146 0.0757
0.2166 0.1089 0.0682
69.3 71.3 111.3
51.0 55.3 96.0
3-Chlorophenol tox conc (mg/L) 0 100 300
So = 938 mg/L HAC k (h-l) K , (mg/L)
So = 469 mg/L HAC k (h-9 K, h / L )
combined data k (h-l) K, (mg/L)
0.2174 0.1457 0.1116
0.2456 0.1432 0.1204
0.2170 0.1505 0.1115
50.4 53.4 152.8
73.7 62.0 172.7
48.0 76.1 151.6
4-Chlorophenol tox conc (mg/L) 0 50 100 300
So = 938 mg/L HAC k (h-') Ka (mg/L)
0.2150 0.2013 0.1810 0.1413
45.6 65.8 119.0 206.6
k
0.2224 0.2132 0.1926 0.1685
0.2534 0.2187 0.2123 0.1828
57.4 78.0 144.3 317.3
by 4-chlorophenol (4-CP) increased at concentrations up to 300 mg/L with some evidence of recovery at the 300 mg/L level, as indicated by the increased gas production after a lag period of -5 h (Figure 2C). A t 600 mg of 4-CP/L, gas production was totally inhibited. Consequently, 50, 100, and 300 mg of 4-CA/L concentrations were selected for testing in phase 11. In all cases, test duplicates showed very close and consistent agreement between test duplicates as demonstrated by the almost identical gas production curves. Chloroanilines. The chloroanilines exhibited patterns of toxic effects on gas production similar to those caused by the chlorophenols except at relatively higher toxicant concentrations (Figure 2D-F). Only a modest increase in toxicity occurred at 2-chloroaniline (2-CA) concentrations up to 800 mg/L, while 3-chloroaniline (3-CA) showed a relative gas production of 70% up to the 1600 mg/L level. 1630 Environ. Sci. Technol., Vol. 26, No. 8, 1992
So = 375 mg/L HAC
So = 656 mg/L HAC k (h-') K. (mg/L)
W1)
Ka (mg/L)
68.5 80.6 178.5 359.2
combined data k W1) K, (mg/L) 0.2163 0.2044 0.1845 0.1503
47.9 73.3 131.5 259.2
On the basis of these results, 200, 400, and 800 mg/L toxicant concentrations were selected for these two compounds for phase I1 tests. Inhibition of gas production by 4-chloroaniline (4-CA) showed a pattern of recovery at the 200-800 mg/L toxicant concentration range so that 100, 200, and 300 mg/L concentrations were selected for phase I1 tests. (b) Phase 11. Initial substrate concentrations used in phase I1 were varied from 375 to 938 mg/L acetate (as acetic acid) to provide some overlap of the substrate uptake curves obtained with each level of initial substrate concentration. Typical results when 3-chloroaniline and 4chlorophenol were used are shown in Figures 3 and 4, respectively. Data from individual tests (symbols) are shown graphically in the left-hand segments of these figures along with the computer-simulated acetate concentrations (lines) representing the best fit of the measured
XXMl
I
k
0 mg/L 3-CHLOROANILINE
A
800
I
-
700
0 ~ / 3-CHLOROANILINE l 600
$
B
800-
2
2m d 8
400
W k
a
!j200 0
800 2
2600 d 8
200 mg/L 3-CHLOROANILINE
t\
84
s
200
0
0
0
m 2
2 600
200 w/l 3-CHLOROANILINE
h
4
400
800
20
15
=q \ 200L 800
W
5
M
5
0
10
'6
20
25
30
400 mg/l 3-CHLOROANILINE
400 g / L 3-CHLOROANILINE
t\
5
F 600
F
9-
d 8 400 s
so08
W
5
200 0
0
5
'0
15
20
25
30
35
40 700
xxx)
,"""
800 w/l 3-CHLOROANILINE
800 mg/L 3-CHLOROANILINE
H
800 2
2m G 8
400
c a
g
o MEASURED - CALCULATED
w
W
2
5 200 a
200 0
0 0
'0
20
30
40
50
60
70
TIME, hours
0
' 0 2 0 3 0 4 0 5 0 6 0 7 0 TIME, hours
Flgure 3. Kinetic test results showlng separate acetate utilization and biomass production at initial substrate concentrations of 938, 656, and 375 mg/L acetate and 200,400, and 800 mg/L 3chloroanillne (left-hand segments). Segments on the right side show the correspondlngcomposite curves. Symbols represent measured data; lines represent results of least-squares modeling.
data. The kinetic parameters, k and K,, estimated from all test sets are listed in Tables IV and V. The biomass concentrations indicated in Figures 3 and 4 were calculated using eq 2. Variations in the values of the kinetic coefficients, k and K,, between individual tests are due in part to the sensitive nature of the model in different regions of the substrate uptake curve (see Figure 1). Since the progression of the reactions could not be determined precisely in advance, it was not possible to always obtain sufficient numbers of measurements in the low-concentration regions of the reaction. Also the volume of culture typically used in the batch bioassay tests limited the quantity and frequency of samples that could be withdrawn for analysis. Therefore, the distribution of the experimentally measured
points along the substrate uptake curve could significantly affect the accuracy of the estimated kinetic coefficients. To address this problem, we adopted the approach of combining the data obtained from tests conducted at various initial substrate concentrations for each toxicant concentration. The procedure used to combine the data points was as follows: a calculated curve was fit to the data obtained at the highest level of initial acetate concentration. The time required to degrade the acetate to the next lower initial acetate concentration was determined from the fitted curve to the nearest 0.6 min of reaction time (2'1 in Figure 3A). The time value associated with this point on the higher concentration curve was then added to the actual measured times for the data points obtained in the Environ. Sci. Technol., Vol. 26, No. 8, 1992
1831
1000
700
800
600
1
-2600
4
1000
5 d
so08
8
3
400
W
L?
!j 200
400
\\
0
S0=375mg/L M C
I
15
20
0 0
M
5
Y
800 J
2 600
4 8
400
MEASURED
IW
- CALCULATED
i25 200 0
300
0
5
M
15
20
Kxx)
50 mg/L 4-CHLOROPHENOL 800 1
2 600 $2
8
400
W
s
5
200 0
0
M
5
15
20
5
0
700
xxw)
l
600
3
800 -1
2- P
600
500
8
H
400
400
200
Y Jw ..
0
M
5
15
25
20
~~
100 mg/L 4-CHLOROPHENOL E
0
20
15 ~
100 m g / L 4-CHLOROPHENOL
800
M
xxw)
k
8
z2
Mx)
400
W
I
t
'r
k
MEASURED
200 0
50
0
40
0
20
30
EN 800 1
2 600 4 8
400
W
I< -
!j 200 0
0
5
10
15 20 25 TIME, hours
30
35
M
20 TIME, hours
30
40
Flgure 4. Kinetic test results showing separate acetate utilization and biomass production at inltial substrate concentrations of 938, 656, and 375 mg/L acetate and 50, 100, and 300 mg/L khlorophenol (left-hand segments). Segments on the right side show the corresponding composite curves. Symbols represent measured data; lines represent the results of least-squares modeling.
reactor receiving the lower acetate dose. This procedure was repeated for the third initial acetate concentration (T2 in Figure 3A). The time shift allowed the data from the two or three individual tests with each chemical to be treated as if they were produced from the same reaction. The graph segments on the right side of Figures 3 and 4 illustrate the combined acetate concentration curves obtained from the respective individual test reactors. In view of the sensitivity of estimates of the kinetic coefficients to So, the initial added acetate concentration was used in the model instead of the initial measured concentration. The data sets shown in Figures 3 and 4 indicate clearly that, as the toxicant concentration was increased, the rate of acetate utilization decreased. The relative effect of the toxicant was manifested in a decrease in the value of k or 1632
Envlron. Sci. Technol., Vol. 26, No. 8, 1992
an increase in the value of K, (Tables IV and V). Generally, k and K,for the combined data fell within the range of values estimated using data from individual tests (Tables IV and V). However, the statistical variation was much less when the combined data sets were used (Table VI) * The procedure used to combine individual substrate curves assumes that the change in biomass concentration in the test reactor receiving the higher substrate dose is negligible over the time interval corresponding to the time shift between the individual tests. Because of the low biomass yield in high-rate batch tests relative to the starting biomass concentration, we considered the small error in combining data sets to be much less than the error associated with the small number of data points in the k-
Table V. Estimated Kinetic Coefficients, k and K,, for Various Concentrations of Acetate and Chloroanilines
2-Chloroaniline So = 938 mg/L HAC K , (mg/L)
tox conc (mg/L)
k (h-')
0.2145 0.1711 0.1210 0.0753
0
200 400 800
So = 656 mg/L HAC K , (mg/L)
0.2773 0.1310 0.1146 0.0814
48.0 81.0 104.3 91.7
So = 375 mg/L HAC K , (mg/L)
k (h-')
combined data K , (mg/L)
k (h-')
138.7 6.3 76.7 131.3
0.2549 0.1933 0.1149 0.0760
k (h-')
84.6 85.7 91.3 112.7
0.2175 0.1644 0.1214 0.0786
55.5 68.7 109.3 122.7
3-Chloroaniline So = 938 mg/L HAC K , (mg/L)
tox conc (mg/L)
k (h-I)
0 200 400 800
0.2056 0.1616 0.1267 0.0812
31.1 60.3 125.3 228.3
So = 665 mg/L HAC
k (h-')
K , (mg/L)
0.2512 0.1571 0.1012 0.0786
105.2 57.0 50.0 246.3
So = 375 mg/L HAC k (h-9 K , (mg/L)
k (h-')
0.2241 0.1532 0.0974 0.0638
0.2130 0.1629 0.1212 0.0795
combined data K , (mg/L)
41.9 33.7 73.0 165.3
48.6 65.9 116.1 227.6
4-Chloroaniline So = 938 mg/L HAC tox conc K.3 (mg/L) k (h-') (mg/L) 0 100
So = 469 mg/L HAC
300 240
K,
K,
k (h-') (mg/L) k (h-') (mg/L) 0.2410 0.1729
33.1 60.4
0.2069 0.1868
combined data
1
57.7 35.6
0.2066 0.1885
So 469 mg/L HAC
K,
K,
tox conc (mg/L) k (h-'1
29.1 69.6
200 300
A
P
So = 938 mg/L HAC
0.1611 0.1327
(mg/L) 81.5 155.3
combined data
K.3
k (h-9 (mg/L) k (h-9 (mg/L) 0.1659 0.1208
87.0 111.9
0.1606 0.1253
80.1 116.3
B
15 12
2-CHLOROPHENOL t 3-CHLOROPHENOL O 4-CHLOROPHENOL
c $
9
22
'1.6
0
5
0 ' 0
250
O
2-CHLOROPHENOL 3-CHLOROPHENOL 4-CHLOROPHENOL
0
100
200 300 400 500 TOXlCANT COW., rng/L
600
I
700
0
200
400 600 TOXICANT CONC., mg/L
800
1000
I
200 150 \ 2
d
100 50
t 3-CHLOROANILINE O 4-CHLOROANILINE
0
200
400 600 TOXICAM CONC., mg/L
800
1000
O L 0
200
400 600 TOXICAM CONC., mg/L
800
1000
Figure 5. Summary of test results showing the effect of chlorophenol and chloroaniline on k and K, on acetate conversion.
or Ks-sensitive areas of the individual substrate uptake reactions. Inhibition Type. The estimated kinetic coefficients determined from the above analysis, and summarized in Tables IV and V, were substituted into the linear form of eqs 9 and 10; the resulting relationship is shown graphically in Figure 5, and values of kiand Ksiare listed in Table VI. The inhibition coefficients for both the chlorophenols and chloroanilines appear to conform best to the mixed inhibition model with k decreasing and Ks increasing as the toxicant concentration increases. However, the relative changes in K,for the 2-chloro isomers were substantially
lower than those in k, indicating the predominance of noncompetitive inhibition mechanisms. The 4-chloro isomers seemed to show a greater effect on K, than on k (Figure 5A and C). Discussion The main benefit of assessing inhibitory effects of toxic chemicals lies in the potential for using the data to predict inhibitory effects based on chemical classification and functionality. Competitive versus noncompetitive inhibitory effeds for metal ions generally have been associated with ionic charge and molecular weights (29). Inhibition Envlron. Sci. Technol., Vol. 26, No. 8, 1992
1633
Table VI. Summary of Kinetic and Inhibition Coefficients kinetic coeff for control samples
toxicant test series
inhibitn coeff ki KSi indv av combn indv av combn (h-l) (mg/L)
ko 0-l)
K ~ o(mg/L)
2-CP 3-CP 4-CP 2-CA 3-CA 4-CA
0.2304 0.2315 0.2303 0.2489 0.2270 0.2240
0.2166 0.2170 0.2163 0.2175 0.2130 0.2066
61.7 62.1 57.2 90.4 59.4 45.4
51.0 48.0 47.9 55.5 48.6 29.1
av SD
cv (%)
0.2320 0.0087 3.8
0.2145 0.0042 1.95
62.7 14.9 23.8
46.7 9.1 19.5
indv av indv SD indv CV (%)
0.2327 0.0213 9.2
267 318 679 416 440 439
599 130 67 657 143 121
64.0 28.4 44.5
of methane formation has been correlated to the functional groups of petrochemicals in unacclimated methanogenic cultures (20). Other general interactions between structure and biodegradation characteristics of different types of complex organic chemicals have been identified (21-24). While these qualitative observations are important, they do not provide information on the effects of toxic organic chemicals on the kinetics of cosubstrate transformations. However, good correlation between aerobic biodegradation rates and the Randic index has been reported (25). Major potential benefits will arise if similar, yet more comprehensive, relationships can be derived between organic chemical structure and the effect of toxicants on the kinetics of anaerobic reactions. In the present study, the toxic effects were clearly related to the molecular structure of the toxicants in each isomeric series. Results of tests with both the chlorophenols and chloroanilines showed that the toxic effect increased in relation to the position of the substituted chlorine group on the benzene ring with 4-chlorophenol > 3-chlorophenol > 2-chlorophenol and 4-chloroaniline > 3-chloroaniline > 2-chloroaniline. However, the chlorophenols exhibited a relatively greater degree of toxicity per unit concentration than did the chloroanilines. The values of ko and K,, were remarkably constant for the combined data for the six control tests (see Tables IV-VI) with a coefficient of variability of 1.95% for ko and 19.5% for Ks0(Table VI). The variation was much greater when the data for the individual tests were modeled. In this case, the coefficients of variability were 9.2% for ko and 44.5% for Kso. These results clearly show the benefit of using the compiting procedure for the tests conducted. The procedure described above for conducting anaerobic toxicity testa is expected to provide a consistent basis for tests designed to determine the relative effects of toxic organic chemicals on the acetoclastic methanogenesis reaction. Subsequent tests in ethanol-enriched reactors produced essentially the same kinetic and inhibition coefficients as reported in Tables IV-VI for inhibition of acetoclastic methanogenesis by chlorophenols and chloroaniline (4). Therefore, while the coefficients may not be truly intrinsic, that is, unaffected by method of system operation or the presence of extraneous materials such as inactive solids or other toxicants, the results should be essentially the same from test to test and among analysts. The method of using acetoclastic methanogen biomass in the substrate uptake and biological growth equations, rather than total biomass, is expected to correct for differences that might arise if measurements are made at different solids retention times. 1634 Environ. Scl. Technol., Vol, 26, No. 8, 1992
Conclusions Based on the results of tests described in this paper, the following conclusions could be drawn: (1)Different toxicant concentrations caused significant changes in the kinetic coefficients, k and K,, for the acetoclastic methanogenesis, reaction with the chlorophenols showing relatively greater toxic effects per unit concentration than the chloroanilines. Initial acetate concentration had no effect on the values of the baseline kinetic coefficients for acetate conversion. (2) Both chlorophenols and chloroanilines exhibited mixed inhibition. (3) The relative toxicity of the chlorophenols and chloroanilines to acetoclastic methanogenesis increased as the position of the substituted chlorine group changed from the ortho to the meta to the para position on the benzene ring. This relationship was more pronounced with values of K , than with values of k. Registry NO.2-CP, 95-57-8; 3-CP, 108-43-0;4-CP, 106-48-9; 2-CA, 95-51-2; 3-CA, 108-42-9; 4-CA, 106-47-8.
Literature Cited (1) Davies-Venn, C. Ph.D. Dissertation, University of Arkansas at Fayetteville, 1989. (2) Young, J. C.; Tabak, H. H. Multi-Leuel Protocol for Assessing the Fate and Effect of Toxic Organic Chemicals in Anaerobic Processes; Final report for Project R814488; Risk Reduction Engineering Laboratory, U S . Environmental Protection Agency, Cincinnati, OH, 1991. (3) Wilkie, A.; Colleran, E. In Anaerobic Treatment of Zndustrial Wastes; Report ANL/CNSV-TM-188; Argonne National Laboratory, Argonne, IL, 1988; pp 37-50. (4) Kim, I. S. Ph.D. Dissertation, University of Arkansas a t Fayetteville, 1991. (5) Owen, W. F.; Stuckey, D. C.; Healy, J. B., Jr.; Young, L. Y.; McCarty, P. L. Water Res. 1979, 13,485-492. (6) Johnson, L. D.; Young, J. C. J.-Water Pollut. Control Fed. 1983,55, 1441-1449. (7) Young, J. C.; Kuss, M. L.; Nelson, M. A. In Waste Treatment Technology: Bioremediation; Air and Waste Management Association: Pittsburgh, PA, 1991, Vol. 11, Paper No. 91-20.1. (8) Struigs, J.; Rogers, J. E. Appl. Enuiron. Microbiol. 1989, 55,2527-2531. (9) Lawrence, L.; McCarty, P. L. J. Sanit. Eng. Diu., Am. SOC. Ciu. Eng. 1970, 96, 757-778. (10) Volskay, V. T., Jr.; Grady, C. P. L., Jr. J.-Water Pollut. Control Fed. 1988,60, 1850-1856. (11) Grady, C. P. L., Jr. J. Enuiron. Eng. 1991, 116, 805-816. (12) Han, K.; Levenspiel, 0. Biotechnol. Bioeng. 1988, 32, 430-437. (13) Segel, I. M. Enzyme Kinetics: Behavior and Analysis of Rapid Equilibrium and Steady-State Enzyme Systems; John Wiley and Sons: New York, 1975. (14) Andrews, G. F. Biotechnol. Bioengin. 1984,26, 824-825. (15) Montgomery, M. S. Ph.D. Dissertation, Stanford university, Stanford, CA, 1984. (16) Smith, D. P.; McCarty, P. L. Biotechnol. Bioeng. 1989,34, 39-48. (17) Robinson, J. A.; Tiedje, J. M. Appl. Enuiron. Microbiol. 1983,45, 1453-1459. (18) Wang, X. M.S. Thesis, Clemson University, Clemson, SC, 1988. (19) Hartmann, L.; Laubenberger, G. J. Sunit. Eng. Diu., Am. SOC. Ciu. Eng. 1968, 94, SA2, 247-254. (20) Chou, W. L.; Speece, R. E.; Siddiqi, R. H.; McKeon, K. hog. Water Technol. 1978,10, 545-557. (21) Lyman, W. J.; Reehl, W. F.; Rosenblatt, D. H. Handbook of Chemical Property Estimation of Methods: Environmental Behavior of Organic Compounds; McGraw-Hill Book Co.: New York, 1982; Chapter 9. (22) Paris, D. F.; Wolfe, N. L.; Steen, W. C. Appl. Enuiron. Microbiol. 1982, 44, 153-158.
Environ. Sei. Technol. 1992,26,1635-1638
Paris, D. F.; Wolfe, N. L.; Steen, W. C.; Buaghman, G. L. Appl. Environ. Microbiol. 1983, 45, 1153-1155. Paris, D. F.; Wolfe, N. L.; Steen, W. C. Appl. Environ. Microbiol. 1984, 47, 7-11. Bishop, D. F. EPA Research on Treatability and Toxicity in Municipal Wastewater Treatment Plants. Presented at the Wastewater Pretreatment and Toxicity Control Workshop sponsored by the University of Wisconsin, Milwaukee, WI, 1987.
Received for review December 18, 1991. Revised manuscript
received April 6, 1992. Accepted April 28, 1992. The research work described in this paper was supported in part by the U S . Environmental Protection Agency through Cooperative Agreement R814488, in part by the University of Arkansas, Fayetteville, and in part by The Pennsylvania State University, University Park. This paper has not been subjected to the agency's peer and administrative review and therefore does not necessarily reflect the views of the Agency and no official endorsement should be inferred. The work was conducted while C.D.-V. and J.C.Y. were Graduate Research Assistant and Professor of Civil Engineering, respectively, at the University of Arkansas.
Chemical Fractionation of Particulate Extracts from Diesel Vehicle Exhaust: Distribution of Ligands for the Dioxin Receptor Grant Mason' and Jan-Ake Gustafsson
Department of Medical Nutrition, Karolinska Institute, Huddinge Hospital, F60, Novum, S-14 1 86 Huddinge, Sweden Roger N. Westerholm and Hang LI
Department of Analytical Chemistry, Arrhenlus Laboratory, Stockholm University, S-I06 9 1 Stockholm, Sweden Diesel vehicle emission particulates were collected using a cyclone sampler. A solvent extract made from the particulate material was fractionated on the basis of polarity into five fractions (I-V), Fractions I and I1 were further subfractionated (1-1 and -2, 11-1 to 11-7). The amounts of 28 polycyclic aromatic compounds present in the extract and its fractions were measured. The ability of each fraction to compete with 2,3,7,&tetrachloro[1,63H]dibenzo-p-dioxin (dioxin) for its receptor was determined. The majority of dioxin receptor binding activity was seen in the primary fractions I1 and 111. These fractions contain those polycyclic aromatic compounds of a size and polarity expected of good dioxin receptor ligands. With respect to the subfractions of fraction 11,greater than 90% of the polycyclic aromatics occurred in subfractions 11-1to 11-4 while the greatest dioxin receptor binding activity was seen in 11-5 and 11-6. Although these latter fractions contain polycyclic hydrocarbons that would be expected to be good dioxin receptor ligands, it is not known if the amounts of known ligands present would be sufficient to account for the observed receptor binding. H
Introduction Bound to particles from diesel exhaust is a complex mixture of compounds. In mammalian tissues metabolic activation of these compounds to more chemically reactive species is a key step in the sequence of events leading to genotoxicity and carcinogenicity. With regard to polycyclic aromatic compounds (PACs), two cytochrome P450 isozymes, cytochromes P450IA1 and -1A2, preferentially catalyze this activation and are known generally as aryl hydrocarbon hydroxylase (A") (I). One of the most commonly studied biological effects of the PACs and related compounds is their ability to induce the activity of cytochrome P450IA1 (1,2).A number of studies have now shown that these compounds induce cytochrome P450IA1 through initial binding to the receptor which specifically binds 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD, dioxin), the dioxin or Ah receptor
* Present address: Department of Biochemistry, University of Leicester, Leicester LE1 7RH, Great Britain. 0013-936X/92/0926-1635$03.00/0
(3,4). Following binding of ligand, the receptor undergoes an "activation" step as a result of which it acquires an increased affinity for the cell nucleus. Following translocation to the nucleus, the receptor-ligand complex appears to interact with specific sites to alter the transcriptional rates of target genes including that of cytochrome P450IA1 (46) Affinity for the dioxin receptor has been shown to correlate with A" inducing ability (3, 7-9). We have shown that particulate extracts can induce AHH in the cell line H4IIE and that this induction correlates with receptor affinity (10). Receptor binding has been shown to be of importance in the initiation of a variety of toxic effects of these compounds, including, for example, embryotoxicity, tumor promotion, and cellular hyperplasia and differentiation (reviewed in ref 3). Thus, binding to the dioxin receptor provides a measure of toxic potential for these compounds. The concentrations of known ligands among the PACs has been suggested to account for only a minor fraction of the observed dioxin receptor binding elicited by particulate extracts (11, 12). Unknown compounds must, therefore, be responsible for the major part of the binding. We, thus, undertook the present study to gain some information as to which compounds or types of compounds are responsible for the observed dioxin receptor binding elicited by diesel exhaust extracts.
Experimental Section Materials. 2,3,7,8-Tetra~hlor0[1,6-~H]dibenzo-p-dioxin and 2,3,7,8-tetrachlorodibenzofuranwere purchased from Chemsyn Science Laboratories (Lenexa, KS). Hydroxylapatite was purchased from Bio-Rad Laboratories (Richmond, CA). All other reagents were of analytical grade purchased from standard sources. Particulate Material. F o r chemical and biological characterizations of particulate exhaust emissions, vehicles are normally run on a chassis dynamometer and the exhausts diluted in a dilution tunnel prior sampling (12,13). However, in order to obtain larger amounts of particulate material from light-duty diesel vehicles, particulate material was collected using a cyclone particulate separator, which is situated before the fan in the CVS system used (Horiba CVS system, Horiba Inc.), which meets U.S.
@ 1992 American Chemical Society
Environ. Sci. Technol., Vol. 26, No. 8, 1992
1685
