Optimization of phthalic acid batch biodegradation and the use of modified Richards model for modelling degradation

International Biodeterioration & Biodegradation 53 (2004) 57 – 63

www.elsevier.com/locate/ibiod

Optimization of phthalic acid batch biodegradation and the use of modi&ed Richards model for modelling degradation Yanzhen Fana , Yingying Wanga , Pei-Yuan Qianb , Ji-Dong Gua; c;∗ a Laboratory

of Environmental Toxicology, Department of Ecology & Biodiversity, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, PR China b Department of Biology, Hong Kong University of Science and Technology, Clearwater Bay, Kowloon, Hong Kong SAR, PR China c The Swire Institute of Marine Science, The University of Hong Kong, Shek O, Cape d’Aguilar, Hong Kong SAR, PR China Received 3 June 2003; received in revised form 18 September 2003; accepted 1 October 2003

Abstract Microbial degradation of phthalic acid was investigated using cultures of aerobic bacteria enriched from a sewage sludge. The Gompertz function and the Richards function were modi&ed and compared to describe the phthalic acid (PA) degradation process, and both models successfully &tted the biomass growth curve when PA was used as the sole source of growth controlling substrate. However, the modi&ed Richards model was superior in describing the depletion curve of PA. The additional parameter, m, in the modi&ed Richards model may be corresponding to the relative importance of the substrate consumption for maintenance. Based on the maximum degradation rates calculated using the modi&ed Richards model, the optimal degradation conditions were determined by an orthogonal test for environmental factors including initial pH, C:N:P ratio and salt concentrations of the culture medium. More than 99% of PA at an initial concentration of 4000 mg l−1 was degraded within 5 days under the optimized condition: namely initial pH 6.0, C:N:P=100:5:1, and NaCl concentration 10 g l−1 . Our results suggest that both substrate depletion and microbial biomass formation can be modelled and predicted using the modi&ed Richards model and the limitation factor of phthalic acid degradation is the initial pH of the culture. ? 2003 Elsevier Ltd. All rights reserved. Keywords: Aerobic; Degradation; Gompertz model; Phthalic acid; Richards model

1. Introduction Phthalates are synthetic organic compounds widely used as additives in plastic manufacturing and moulding to improve mechanical properties of the plastic resin, particularly Dexibility (ECETOC, 1988; Giam et al., 1984; Nilsson, 1994). However, in order to provide the required Dexibility, the phthalate plasticizer is not bound covalently to the resin and is able to migrate into the environment (Nilsson, 1994). Due to the global utilization of plasticized plastics in large quantities, phthalates have been detected in every environment in which they have been sought (Giam et al., 1984). Some phthalates and their degradation intermediates are suspected to cause cancer and kidney damage and have been listed as priority pollutants by the US ∗

Corresponding author. Department of Ecology & Biodiversity, The University of Hong Kong, 3S-11 Kadoorie BSB, Pokfulam Road, Hong Kong. Tel.: +86-852-2299-0605; fax: +86-852-2517-6082. E-mail address: [email protected] (J.-D. Gu). 0964-8305/$ - see front matter ? 2003 Elsevier Ltd. All rights reserved. doi:10.1016/j.ibiod.2003.10.001

Environmental Protection Agency (US EPA, 1992). Known as endocrine-disrupting chemicals, some phthalates may also interfere with the reproductive system and development of animals and humans (Allsopp et al., 1997; Gray et al., 1999; Jobling et al., 1995). Microbial degradation is believed to be the principal route for complete mineralization of phthalate in natural environments (Staples et al., 1997). Although considerable research has been conducted on the biodegradation of phthalates including the molecular biology of degradative genes and organization in bacteria over the last decade (Chang and Zylstra, 1998; Kleerebezem et al., 1999; Roslev et al., 1998; Stahl and Pessen, 1953; Sugatt et al., 1984; Wang et al., 1996), those studies dealt mainly with the biodegradability of diMerent phthalates by microorganisms from diverse habitats and the pathways of degradation. Few studies have been focused on the inDuence of environmental factors on the degradation rate of phthalate. For a better understanding of the degradation process and its optimization, a model containing information on

58

Y. Fan et al. / International Biodeterioration & Biodegradation 53 (2004) 57 – 63

Nomenclature A e m Rm S S0 t

asymptotic phase constant (2.718281828) shape parameter maximum substrate consumption (mg l−1 d −1 ) substrate concentration (mg l−1 ) initial substrate concentration (mg l−1 ) incubation time (d)

R2 RSS rate

degradation and microbial growth may provide insight to the processes involved. In batch reactor, bacterial growth often shows a sigmoidal curve with a beginning phase in which the speci&c growth rate starts at a value of zero and then accelerates to a maximal value (m ) in a certain period of time, resulting in a lag time ( ). After that, an asymptote (A) is reached in a &nal phase in which the rate decreases and eventually reaches zero (Zwietering et al., 1990). These kind of sigmoidal curves can be &tted by diMerent mathematical functions, such as monomolecular, von BertalanMy, Gompertz and logistic (McCallum and Dixon, 1990). A major development in the analysis of growth curves has been the generalization of these sigmoid growths to a single function, i.e. the Richards function (Richards, 1959; McCallum and Dixon, 1990). On the other hand, the modi&ed Gompertz model was also successfully used to describe the growth data of Lactobacillus plantarum (Zwietering et al., 1990). Although the linear relationship lies between the bacterial growth rate and the single growth-controlling substrate utilization rate (Monod, 1949), there was no report on modelling the substrate utilization process using the Gompertz or Richards equation. Therefore, the objectives of this study were (1) to evaluate the suitability of the Gompertz and Richards functions in modelling the phthalic acid (PA) degradation process, and (2) to investigate the eMects of environmental factors on the degradation rate of phthalic acid. 2. Materials and methods 2.1. Microorganisms and culture conditions The initial start up culture was prepared by adding 10 ml activated sludge from a local wastewater treatment plant to 200 ml of mineral salt medium with phthalic acid as the sole source of carbon and energy in a 250 ml Erlenmeyer Dask. Except for those used in the orthogonal test, the mineral salt medium consisted of the following nutrients (mg l−1 ): (NH4 )2 SO4 1000, KH2 PO4 800, K2 HPO4 200, MgSO4 · 7H2 O 500, FeSO4 10, CaCl2 50, NiSO4 32, Na2 BO7 · H2 O 7.2, (NH4 )6 Mo7 O24 · H2 O 14.4, ZnCl2 23, CoCl2 · H2 O 21, CuCl2 · 2H2 O 10 and MnCl2 · 4H2 O 30, and

X Y

m

correlation coeOcient residual sum of squares (mg2 l−2 for depletion curve) biomass concentration yield coeOcient (l mg−1 ) lag phase time (d) maximum biomass growth rate (d −1 )

the initial pH of the culture medium was adjusted to 7:0±0:1 using H2 SO4 or NaOH. The Dasks were incubated in an INNOVA 4340 incubator shaker (New Brunswick Scienti&c, New Jersey) kept in the dark at 150 rpm and 30:0 ± 0:5◦ C. The PA-degrading consortium was obtained by transferring weekly (approximately) on the basis of depletion (more than 85%) of the substrate compound, and 40 ml of the culture was transferred to a new Dask containing 160 ml of freshly made mineral salt medium and a gradually increasing concentration of PA. Each of the cultures was transferred more than 20 times prior to being used in the subsequent biodegradation tests reported here. All biodegradation experiments were conducted in triplicate. Periodically, samples (2 ml) of culture were withdrawn aseptically from Dasks by syringe and stored frozen (−20◦ C) in a glass vial until analyzed. Sterile controls were prepared by autoclaving for 20 min on three successive days before introduction of the substrate through a 0.2-m-pore-size membrane <er &tted to a syringe (Pall Gelman Laboratory, Ann Arbor, Michigan). 2.2. Orthogonal test Orthogonal-test design was based on the principle of statistical mathematics and the tests were arranged scienti&cally to solve multiple-factor optimization requirements with reduced numbers of tests conducted. The inDuence of environmental factors, speci&cally pH, C:N ratio, C:P ratio and NaCl concentration, on the degradation rate of PA was optimized by an orthogonal test as shown in Table 1. The initial concentration of PA was 1000 mg l−1 . 2.3. Analysis of substrate chemicals In preparation of samples for PA analysis by HPLC, thawed culture samples from PA degradation experiments were centrifuged and <ered through 0.22-m-pore-size PVDF Acrodisc Minispike (Pall Gelman Laboratory, Ann Arbor, Michigan) syringe <ers respectively. The &rst &ve drops were discarded to avoid the inDuence of phthalates or metabolites adsorption onto membranes. Samples were chromatographed on an Agilent 1100 series HPLC system

Y. Fan et al. / International Biodeterioration & Biodegradation 53 (2004) 57 – 63 Table 1 Factorial design of the orthogonal experiment

Level

A pH

B C:N

C C:P

D NaCl (g l−1 )

1 2 3 4

4 5 6 7

2 10 20 200

2 50 100 500

0 0.3 10 30

(Agilent Technologies, Hewlett-Packard, California) consisting of a quaternary low-pressure degasser, a quaternary high-pressure pump, a model 7725i manual sample injector with a 20 l sample loop, and diode array and multiple wavelength detectors. Separation of parent compounds and metabolites was accomplished by using a 4:6 × 150 mm Eclipse 5-m XDB-C8 reversed-phase liquid chromatography column (Agilent Technologies). The mobile phase for separation of PA consisted of a mixture of methanol– 0:02 mol l−1 H3 PO4 (pH 3.0) (25:75, v/v). PA was quanti&ed by the external standards method at wavelength of 280 nm. The calibration curve was linear in the range of 1–1000 mg l−1 (n = 7; R2 = 0:9999). The microbial biomass was determined by optical density measurements at 600 nm (OD600 ) spectrophotometrically using an UV 1201 (Shimadzu Co., Kyoto, Japan). The culture was mixed intensively before sampling if Docs were observed. The samples were diluted when OD600 value was greater than 0.4. 2.4. Model development Many models were developed to describe the bacterial growth curve (Schepers et al., 2000; Richards, 1959). Among them, the Gompertz model (Eq. (1)) was found to be the most suitable model to &t the growth data based on Lactobacillus plantarum and easy to use (Zwietering et al., 1990):
 e  m X = A exp −exp ( − t) + 1 (1) A Since growth is a result of catabolic and anabolic enzymatic activities, these processes, i.e. substrate utilization or growth-associated product formation, can also be quantitatively described on the basis of growth models (KovRarovRa-kovar and Egli, 1998). According to Monod (1949), the relationship between the bacterial growth rate (dX=dt) and the utilization rate (dS=dt) of single growth-controlling substrate (such as PA) is linear: Y =−

dX ; dS

(2)

where Y corresponds to the yield coeOcient. The abiotic degradation of PA can be negligible in this situation; i.e. ds=dt = 0 when X0 = 0. Therefore, the

cumulative PA degradation can be de&ned as  t  t X dS dX=Y dt = dt = S0 − S = − dt dt Y 0 0 and combining Eqs. (1) and (3):    (m =Y )e A S0 − S = exp −exp ( − t) + 1 Y (A=Y )

59

(3)

(4)

The term A=Y can be replaced by the term S0 , de&ned as the PA degradation potential, which equals the initial concentration of PA, while m =Y can be de&ned as the maximum PA degradation rate (Rm ). Therefore, Eq. (4) can be expressed as     Rm e S = S0 1 − exp −exp ( − t) + 1 : (5) S0 There are three parameters (A, m and ) in the Gompertz model. But the number of parameters in Eq. (5) is only 2 (Rm and ) since the S0 is known. In some situations, the Richards model is more suitable for describing the bacterial growth curve (Schepers et al., 2000). The Richards function includes a parameter, m, which describes the shape of familiar three-parameter functions, such as the monomolecular (m = 1), von BertalanMy (m = 2=3), Gompertz (m → 1) and logistic (m = 2), as well as other sigmoid functions (McCallum and Dixon, 1990). To describe the degradation of a substrate in the same way as mentioned above, the Richards function can be rewritten as S = S0 {1 − {1 + (m − 1)em   1=(1−m)

m m=(m−1) × exp m ( − t) S0

(6)

2.5. Data analysis The above nonlinear equations were used to &t the PA degradation and biomass accumulation data using nonlinear least-squares regression method. All data analysis was performed using Matlab 6.0 with Optimization Toolbox 2.1 (The MathWorks Inc., 2000). This method minimized the residual sum of squares (RSS) using Levenberg–Marquardt algorithm which has been successfully tested on a large number of nonlinear problems and has proved to be more robust than the Gauss–Newton method and iteratively more eOcient than an unconstrained method. The R-square value (R2 ) and the residual sum of squares (RSS) were used to discriminate among models. 3. Results and discussion 3.1. Modelling of PA degradation The experimental and simulation results of a typical PA degradation curve and biomass growth curve by the modi&ed Gompertz model and the modi&ed Richards model are

60

Y. Fan et al. / International Biodeterioration & Biodegradation 53 (2004) 57 – 63 2800

1200 0.8

800

0.6

600 0.4

400 0.2

200

0

0

0

1

2

3

4

5

6

Concentration of PA,mg/l

2400

OD 600

PA Concentration, mg/l

1000

2000

1600

1200

800

400

Time, d 0

Fig. 1. The &tting of bacterial growth and phthalic acid (PA) degradation to experimental data using the modi&ed Gompertz model and the modi&ed Richards model. ◦, PA concentration;
, microbial population (OD600 ). The solid lines and the dotted lines apply to the results of Richards model and the Gompertz model, respectively.

illustrated in Fig. 1. The calculated parameter values and their R2 , RSS (residual of sum of squares) are listed in Table 2. For the bacterial growth curve, both the modi&ed Gompertz model and the modi&ed Richards model &tted the experiment data very well. The R2 values were the same (0.9996) and very close to 1. The RSS values were also nearly equal. And the calculated parameter values, i.e.

; m and A, were also quite similar. With three parameters, the Gompertz model was good enough to &t the sigmoidal growth curve. There was no need to use the four-parameter Richards function since the three-parameter Gompertz model is simpler and therefore easier to use. Moreover, the three-parameter model is more stable because the parameters are less correlated. However, PA degradation curves demonstrate that the Richards model &tted the experimental data better than the Gompertz model (Fig. 1 and Table 2). The RSS value of the Richards model was less than 1=6 of that of the Gompertz model. The R2 value of the Richards model (0.9997) was higher than that of the Gompertz model (0.9982). More PA degradation experiments with initial PA concentration ranged from 330 to 2640 mg l−1 were conducted to investigate the availability of the modi&ed Richards model in &tting the PA depletion curve and the microbiological

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

Time, d Fig. 2. The &tting of phthalic acid (PA) degradation to experimental data using the modi&ed Gompertz model and the modi&ed Richards model. ◦, PA concentration;
, PA concentration of sterile control. The solid lines and the dotted lines apply to the results of Richards model and the Gompertz model, respectively.

meaning of the additional parameter, m. Variation between replicated runs was very little except for the observable diMerences in initial lag-time. Fig. 2 illustrates the representative experimental data and the &tting results of these degradation curves by the modi&ed Gompertz model and the modi&ed Richards model. The calculated parameter values and their R2 , RSS values are summarized in Table 3. Fig. 2 shows that the modi&ed Richards model simulates the experimental data much better than the modi&ed Gompertz model does. The conclusion is based on the RSS and R2 values presented in Table 3. The RSS values of the modi&ed Richards model were clearly less than that of the modi&ed Gompertz model, showing a better &t of the data with the model. Further, all R2 values of the Richards model were higher than that of the Gompertz model. The &tting of tens of PA degradation curves led to one conclusion, i.e. that the Richards model was better than the Gompertz model in &tting the degradation curve of a single growth-controlling substrate. The diMerence in performance between the Gompertz model and the Richards model in &tting the bacterial growth curve and the PA degradation curve indicates that the relationship between the bacterial growth rate (dX=dt) and the utilization rate (dS=dt) of a single growth-controlling

Table 2 Comparison of the calculated parameter values and their R2 , RSS from the Gompertz model and the Richards model

Model

(d)

Rm =m

A

R2

RSS

Gompertz degradation Richards degradation Gompertz growth Richards growth

2.52 2.56 2.03 2.03

664 639 0.527 0.527

— — 0.810 0.808

0.9982 0.9997 0.9996 0.9996

9:74 × 103 1:46 × 103 1:07 × 10−3 1:06 × 10−3

Y. Fan et al. / International Biodeterioration & Biodegradation 53 (2004) 57 – 63

61

Table 3 Comparison of the calculated parameter values and their R2 , RSS from the Gompertz model and the Richards model at diMerent initial PA concentration

PA concentration (mg l−1 ) 330 660 900 1270 1920 2640

Model

Rm (mg l−1 d −1 )

(d)

RSS (mg2 l−2 )

R2

m

Richards Gompertz Richards Gompertz Richards Gompertz Richards Gompertz Richards Gompertz Richards Gompertz

1724 1730 2421 2428 1909 2022 1963 2026 2130 2131 2615 2697

0.522 0.517 0.561 0.555 0.472 0.466 0.519 0.500 0.596 0.551 0.705 0.668

61 344 1525 2989 7183 11991 17617 36265 67111 119390 61980 207780

0.9999 0.9991 0.9991 0.9986 0.9979 0.9966 0.9974 0.9948 0.9958 0.9924 0.9987 0.9948

1.72 — 1.70 — 1.98 — 2.25 — 2.47 — 2.31 —

substrate (such as PA) is not ideally linear. Microorganisms consume substrates even when no apparent growth can be observed for maintenance of the bacterial population (KovRarovRa-kovar and Egli, 1998; McCarty, 1999). The consumed substrates can be divided into two parts, one part for physiological growth and the other part for maintenance (or balancing the decay of cell number). The &rst part of the utilization rate of a single growth-controlling substrate is linear to the bacterial growth rate, while the second part may be speci&c to individual species of microorganism and the physiological conditions. For this reason, the original Monod equation was modi&ed by introducing the maintenance term and expressed as the threshold substrate concentration or maintenance rate to account for this biological characteristic (KovRarovRa-kovar and Egli, 1998). Furthermore, a bacterial population in batch culture is not homogeneous in terms of their physiological development which can result in signi&cant diMerences in the lag-time, degradation rate and also the bioactivity in the culture between replicated experiments. The Gompertz model does not comprise a parameter for the substrate consumed for maintenance. It &ts the &rst half of the PA degradation curves very well (Fig. 2). This may result from the fact that the substrate consumed for maintenance can be negligible at the beginning of degradation when the biomass is relatively low. But it cannot be negligible any more at the last part of degradation, resulting in the simulated curves always being higher than the experimental data. The strength of Richards function is that it includes a parameter, m, which can change the shape of sigmoidal functions to include the substrate consumption for maintenance. The value of m may indicate the relative importance of the substrate consumption for maintenance. The value increases with initial concentration of PA (Table 3). The value of m is less than 2 when the initial concentration of PA is less than 1000 mg l−1 and the corresponding biomass is also low. More substrate is consumed for maintenance when biomass is higher, which results in a higher m value. This parameter may enable the sigmoidal function to include the substrate consumption for maintenance; as a re-

Table 4 Results of orthogonal testsa

Test no. A pH

B C:N

C C:P

D NaCl (g l−1 )

(d)

Rm (mg l−1 d −1 )

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

1 2 3 4 2 1 4 3 3 4 1 2 4 3 2 1

1 2 3 4 3 4 1 2 3 4 2 1 2 1 4 3

¿7 ¿7 ¿7 ¿7 1.8 ¿7 2.0 ¿7 1.6 1.1 0.2 ¿7 1.2 0.3 2.6 ¿7

0 0 0 0 984 0 157 0 1125 631 1578 0 305 1438 640 0

1 1 1 1 2 2 2 2 3 3 3 3 4 4 4 4

a Refer to Table 1 for the test concentrations and conditions of A, B, C and D in this table.

sult, the Richard model performed better than the Gompertz model in describing the PA degradation. 3.2. Optimizing condition for degradation All of the 16 orthogonal tests were conducted simultaneously under the same conditions other than those speci&ed in Table 1. Both the lag time ( ) and the maximum degradation rate (Rm ) of each test were subsequently calculated according to the Richards model. Only Rm was considered in optimization of these factors because lag time is less important from an engineering point of view. Based on the analytical data obtained in Table 4, further results were calculated and illustrated in Fig. 3. The highest degradation rate was achieved when the initial pH was at 6, the C:N ratio was 2:1 or 20:1, the C:P ratio was 100:1, and NaCl concentration was 10 g l−1 . Then C:N ratio of 20:1 was chosen because less nitrogen was economically preferable in an actual wastewater treatment system. The optimal degradation

Y. Fan et al. / International Biodeterioration & Biodegradation 53 (2004) 57 – 63 4000

4000

3000

3000

Rm, mg/l/d

Rm, mg/l/d

62

2000 1000

2000 1000 0

0 3

4

5

6

7

8

pH

1

4000

3000

3000

1000

10

100

1000 0

1000

C:P

(c)

1000

2000

0 1

100

C:N

4000

2000

10

(b)

Rm, mg/l/d

Rm, mg/l/d

(a)

0

10

(d)

20

30

40

NaCl,g/L

Fig. 3. The inDuence of pH (a), C:N ratio (b), C:P ratio (c) and NaCl concentration (d) on phthalic acid (PA) degradation by the acclimated aerobic culture of microorganisms enriched from activated sludge.

9

pH

8 7 6 5 0

1

2

3

4

5

6

Time, d Fig. 4. Changes of pH during phthalic acid (PA) degradation at two initial pH values by the acclimated aerobic culture of microorganisms enriched from activated sludge. , initial pH 6.0;
, initial pH 7.0.

condition was determined as A3 B3 C3 D3 when all levels of the four factors were considered (Table 1). Under optimal conditions, more than 99% PA was degraded in 5 days at an initial concentration of 4000 mg l−1 . To our knowledge, this is the &rst report on degradation of PA at such a high concentration in a short period of time. The optimum initial pH was 6 rather than 7 may suggest that the pH of the culture medium tended to increase as phthalic acid was depleted from the medium due to degradation. Fig. 4 shows that the &nal pH could reach approximately 8.5 in the PA degradation process with an initial pH 7. In comparison, the &nal pH was about neutral when the initial pH was set at 6 (Fig. 4). Although PA was degraded quickly at near neutral condition, degradation was not detectable at pH 4.0. In a typical aerobic wastewater treatment process, the optimal BOD5 =N=P ratio is approximately 100:5:1 according to Bene&eld and Randall (1980). Table 4 shows that our optimized C:N/P ratio was calculated to be 100:5:1 for PA degradation suggesting that little nitrogen and phosphorus were needed in our degradation system. Considering a

typical aerobic wastewater treatment system, the theoretical BOD5 =C ratio for PA should be 2. It is clear that a small quantity of nitrogen is suOcient for complete PA degradation because the N can be recycled while carbon is oxidized. Although the degradation rate did not change much when the C:N ratio increased from 2:1 to 100:1, no degradation was detected at a C:N ratio of 200:1. In terms of the metabolic importance to microbial cells, phosphorus seems to be a less important factor than nitrogen. At a C:P ratio of as high as 500:1, PA was still degraded to some extent, though signi&cantly slower. Salt concentration is important in maintaining the osmotic pressure of bacterial cells, but inhibition may result from too high or too low a concentration. At a NaCl concentration of 30 g l−1 , severe inhibition of the microbial degradation processes was observed due to osmotic stress (Kincannon and Gaudy, 1966). Table 4 shows that moderate salt concentration (10 g l−1 ) was preferred for PA degradation while NaCl concentration as high as that of seawater (30 g l−1 ) showed inhibitory eMects. In Fig. 3, the variance in Rm shows the range over which the maximum PA degradation rate changed with levels for each factor. The higher the variance value, the greater the inDuence of the factor on the degradation process, and the more important is the factor. It is clear that the variance of Rm follows pH ¿ C : N ¿ C : P ¿ NaCl concentration (Fig. 3). Thus, pH is the most important and sensitive factor in the test, followed by C:N ratio and C:P ratio, and NaCl concentration is ranked the least important. 4. Conclusion Both the Richards and the Gompertz models successfully described the biomass growth curve with PA as the single

Y. Fan et al. / International Biodeterioration & Biodegradation 53 (2004) 57 – 63

growth controlling substrate. The modi&ed Richards model could &t the degradation curve of PA better than the modi&ed Gompertz model. Based on the maximum PA degradation rate calculated using the modi&ed Richards model, the orthogonal optimization test of PA degradation condition indicated that pH was the most important factor in the degradation process, followed by C:N ratio, C:P ratio, and NaCl concentration. Acknowledgements Research was supported by Hong Kong Innovative Technology Fund (ITS/276/00) and RGC Central Allocation grant (CA00/01.Sco1). Additional &nancial support was from industrial partnership with Peako Engineering Co. and Kou Hing Hong Scienti&c Supplies. We thank the technical support of Jessie Lai. Any opinions, &ndings, conclusions or recommendations expressed in this publication do not reDect the view of the Government of the Hong Kong Administrative Region, the Innovation and Technology Commission or the vetting committees for the Innovation and Technology Fund. References Allsopp, M., Santillo, D., Johnston, P., 1997. Poisoning the future: impacts of endocrine-disrupting chemicals on wildlife and human health. Greenpeace International, The Netherlands. Bene&eld, L.D., Randall, C.W., 1980. Biological process design for wastewater treatment. Prentice-Hall, Englewood CliMs, NJ. Chang, H.-K., Zylstra, G.J., 1998. Novel organization of the genes for phthalate degradation from Burkholderia cepacia DBO1. Journal of Bacteriology 180, 6529–6537. ECETOC, 1988. Concentrations of industrial organic chemicals measured in the environments: the inDuence of physiochemical properties. Tonnage and use pattern. ECETOC Technical Report No. 29. Giam, C.S., Atlas, E., Powers, M.A., Leonard Jr., J.E., 1984. Phthalate esters. In: Hutzinger, O. (Ed.), Anthropogenic Compounds, SpringerVerlag, Berlin, pp. 67–142. Gray, L.E., Wolf, C., Lambright, C., Mann, P., Price, M., Cooper, R.L., Ostby, J., 1999. Administration of potentially antiandrogenic pesticides (procymidone, linuron, iprodione, chlozolinate, p; p -DDE, and ketonazole) and toxic substances (dibutyl- and diethylhexyl phthalate, PCB 169, and ethane dimethane sulphonate) during sexual diMerentiation produces diverse pro&les of reproductive malformations in the male rat. Toxicology and Industrial Health 15, 94–118.

63

Jobling, S., Reynolds, T., White, R., Parker, M.G., Sumpter, J.P., 1995. A variety of environmentally persistent chemicals, including some phthalate plasticizers, are weakly estrogenic. Environmental Health Perspectives 103 (Suppl. 7), 582–587. Kincannon, D.F., Gaudy, A.F., 1966. Some eMects of high salt concentration on activated sludge. Journal of Water Pollution Control Federation 38, 1148–1159. Kleerebezem, R., HulshoM Pol, L.W., Lettinga, G., 1999. Anaerobic degradation of phthalate isomers by methanogenic consortia. Applied and Environmental Microbiology 65, 1152–1160. KovRarovRa-kovar, K., Egli, T., 1998. Growth kinetics of suspended microbial cells: from single-substrate-control growth to mixed-substrate kinetics. Microbiology and Molecular Biology Reviews 62, 646–666. McCallum, D.A., Dixon, P.M., 1990. Reducing bias in estimates of the Richards growth function shape parameter. Growth, Development and Aging 54, 135–141. McCarty, P.L., 1999. Novel biological removal of hazardous chemicals at trace levels. In: Chen, G., Huang, J.-C. (Eds.), Proceedings of the International Symposium on Development of Innovative Water and Wastewater Treatment Technologies for the 21st Century. Hong Kong University of Science and Technology, Hong Kong, pp. 5–19. Monod, J., 1949. The growth of bacterial cultures. Annual Review of Microbiology 3, 371–394. Nilsson, C., 1994. Phthalate acid esters used as plastic additives— comparisons of toxicological eMects. Swedish National Chemicals Inspectorate, Brussels. Richards, F.J., 1959. A Dexible growth function for empirical use. Journal of Experimental Botany 10, 290–300. Roslev, P., Madsen, P.L., Thyme, J.B., Henriksen, K., 1998. Degradation of phthalate and di-(2-ethylhexyl) phthalate by indigenous and inoculated microorganisms in sludge-amended soil. Applied and Environmental Microbiology 64, 4711–4719. Schepers, A.W., Thibault, J., Lacroix, C., 2000. Comparison of simple neural networks and nonlinear regression models for descriptive modeling of Lactobacillus helveticus growth in pH-controlled batch cultures. Enzymes and Microbial Technology 26, 431–445. Stahl, W.H., Pessen, H., 1953. The microbial degradation of plasticizers. Applied Microbiology 1, 30–35. Staples, C.A., Peterson, D.R., Parkerton, T.F., Adams, W.J., 1997. The environmental fate of phthalate esters: a literature review. Chemosphere 35, 667–749. Sugatt, R.H., O’Grady, D.P., Banerjee, S., Howard, P.H., Gledhill, W.E., 1984. Shake Dask biodegradation of 14 commercial phthalate esters. Applied and Environmental Microbiology 47, 601–606. The MathWorks Inc., 2000. Optimization Toolbox User’s Guide, Version 2.1. The MathWorks, Inc. Natick, MA. US EPA, 1992. Code of Federal Regulations, 40 CFR, Part 136. Wang, J., Liu, P., Qian, Y., 1996. Biodegradation of phthalic acid esters by an acclimated activated sludge. Environmental International 22, 737–774. Zwietering, M.H., Jongenburger, I., Rombouts, F.M., van’t Riet, K., 1990. Modeling of the bacterial growth curve. Applied and Environmental Microbiology 56, 1875–1881.