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The performance evaluation of hybrid anaerobic baffled reactor for treatment of PVA-containing desizing wastewater
Desalination 271 (2011) 287–294
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Desalination j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / d e s a l
The performance evaluation of hybrid anaerobic baffled reactor for treatment of PVA-containing desizing wastewater Liu Rongrong a,b,⁎, Lu Xujie c, Tian Qing b, Yang Bo b, Chen Jihua b a b c
Department of Environmental Science & Engineering, Yangzhou Vocational College of Environment and Resources, Yangzhou, PR China Department of Environmental Science & Engineering, DongHua University, 2999 North Renmin Road, Songjiang district, Shanghai 201620, PR China School of Chemical and Environmental Engineering, Jianghan University, Wuhan 430056, PR China
a r t i c l e
i n f o
Article history: Received 8 October 2010 Received in revised form 20 December 2010 Accepted 20 December 2010 Available online 26 January 2011 Keywords: Desizing wastewater Granular sludge Hybrid anaerobic baffled reactor Polyvinyl alcohol Volatile fatty acid
a b s t r a c t Polyvinyl alcohol (PVA)-containing desizing wastewater discharged from final textile wastewater has a great impact on the environment. In the paper, an improved lab-scale hybrid anaerobic baffled reactor (HABR) was developed to treat desizing wastewater. Under optimum condition (alkalinity of influent 500 mg/L, effluent recycle ratio of 94 times influent rate and hydraulic retention time of 5 d), the system demonstrated a good performance of COD and PVA removal efficiencies (around 42.0% and 18.0% respectively) and the average concentration of alkalinity in the effluent was around 700 mg/L and pH value was above 6.8. Microbial selection and zoning are encouraged inside the HABR. The improved lab-scale HABR proved to be a suitable technology for desizing wastewater treatment. © 2011 Elsevier B.V. All rights reserved.
1. Introduction Polyvinyl alcohol (PVA), a water soluble synthetic polymer prepared by the hydrolysis of polyvinyl acetate, is widely used in the warp sizing process in textile industry due to its excellent film strength, flexibility, wearability, adhesiveness and chemical durability. In 2004, about 125 thousand tons of PVA were consumed in textile sizing agent industry in China. The PVA-containing desizing wastewater generated from desizing step contributes approximately 50% of the organic load in the total textile wastewater [1,2]. As a common refractory organic matter, 1 g of PVA is an equivalent of 0.016-g 5-d biochemical oxygen demand (BOD5) or 1.6 g chemical oxygen demand (COD). The ratio of BOD5 to COD is low to 0.01, indicating the poor biodegradability [3]. Therefore, the desizing wastewaters require adequate and sufficient treatment before being allowed to be discharged into surface waters. Various treatment methods such as special microorganisms and enzymes, biological activated sludge process, activated carbon adsorption, chemical oxidation by ozone, or a combination of UV radiation and ozone and H2O2, wet oxidation, etc. are being used to treat desizing wastewaters [4]. However, the treatment costs are very high and fullscale treatment processes are still impractical. In order to comply with the stringent COD discharge standard and requirement of energy saving and emission reduction in textile industry, anaerobic process becomes ⁎ Corresponding author. Yangzhou Vocational College of Environment and Resources, 33 South Runyang Road, Hanjiang district, Yangzhou 225127, PR China. Tel.: +86 514 87432017; fax: +86 514 87436688. E-mail address: [email protected] (L. Rongrong). 0011-9164/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.desal.2010.12.044
attractive for treatment of PVA-containing wastewater. This process takes advantages of microorganisms involved in the anaerobic process and their strong tolerance to high concentration inhibitory organic matters and unfavorable environmental stresses. A detailed investigation of the anaerobic biodegradability of PVA was carried out by Matsumura et al., and the result showed that over 60% of PVA was biodegraded as determined by TOC after 4 months of incubation [5]. In contrast with the above investigations, PVA was found to show only minor degradation, ranging between 0% and 12% in 77 d, in anaerobic tests using digestion sludge according to ISO and ASTM standard procedures [6]. As one of the high-rate anaerobic reactors, anaerobic baffled reactor (ABR) has several advantages such as simple design, low energy consumption, high stability for shocking and loading, and high treatment efficiency [7]. The significant advantage of the ABR is its ability to separate acidogenesis and methanogenesis longitudinally down the reactor [7–9]. This can permit different bacterial population to dominate each compartment, acidification predominating in the first compartment section and methanogenesis dominant in the subsequent section [7,9,10]. As a promising system for industrial wastewater treatment, the ABR was extensively used in the treatment of palm oil mill effluent wastewater [11], swine wastewater [12], synthetic tannery wastewater containing sulfate and chromium (III) [7], pulp and paper mill black liquors [13], whisky distillery wastewater [14], landfill leachate [15], domestic wastewater [16], sulfate-containing wastewater [17], nitrogencontaining wastewater [18], soybean protein processing wastewater [19] and also heavy oil produced water with high concentrations of salt and
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poor nutrient [20]. However, limited study on treating PVA-containing desizing wastewater using ABR was observed in the literature. Therefore, it is essential to evaluate the feasibility of a lab-scale ABR on treatment of PVA-containing desizing wastewater. Many developments have focused on ABR design and operation that can enhance both the efficiency and reliability of the technology. The main objective of the efficient ABR design must be high retention time of bacterial cells with very little loss of bacteria from the bioreactor, taking into consideration the slow growth rate of many anaerobic microorganisms, particularly methanogenics. In order to produce high-rate designs, enhance the bacterial activity together with good mixture to ensure a high rate of contact between the cells and their substrate [21], a modification was achieved by increasing the height of hybrid anaerobic baffled reactor (HABR) in this study, which increased the ability of entrapping microbe-rich small particles in the reactor. In addition, proper effluent recycle was also applied. This work has also provided an understanding of the relationship between operational conditions, reactor design, and the formation of granular sludge. The purpose of this study was to evaluate the performance of improved HABR for treatment of desizing wastewater. The performance of reactor during start-up, optimization of operation parameters and its potential to treat PVA-containing desizing wastewater were investigated.
The reactor was operated under mesophilic conditions (32 ± 1 °C). The influent was adjusted using a variable speed peristaltic pump (Model BT-001, Zhixin, China). Industrial peristaltic pump (Model PP6, SCMI, China) was used to control effluent recycle ratio to the reactor. 2.2. Wastewater characteristics The feed used in this study was real desizing wastewater which was collected from a dying and finishing plant at Chuzhou in Anhui, China. The composition of the raw wastewater was as follows: COD 10,000–13,520 mg/L, alkalinity (as CaCO3) 10,000–17,000 mg/L, BOD5 1500–2192 mg/L, PVA 1000–3000 mg/L, and suspended solid (SS) 5000–7056 mg/L, pH 12–14. 2.3. Inoculated sludge The HABR was inoculated with anaerobic granular sludge taken from an anaerobic digester of a sewage treatment plant in Yixing, China. Characteristics of inoculated sludge were: average particle size 3–5 mm, sedimentation velocity 23.40 ± 0.60 m/h, total suspended solid (TSS) 16.05 ± 0.40 g/L, volatile suspended solid (VSS) 12.02 ± 0.30 g/L, and VSS/TSS 72.85 ± 1.82%. 2.4. Experimental design
2. Materials and methods 2.1. Configuration of HABR The HABR had a dimension of 15 cm wide, 62 cm long and 100 cm high. It was constructed from Perspex, with a valid volume of 79.05 L. The reactor was divided into four equal compartments (compartments 1, 2, 3 and 4), which incorporated a solids settling chamber after its final compartment. Between the compartments there was a 5.5 cm wide recycle chamber in which inner recycle occurred from it to the first compartment. The compartment was equipped with sampling ports that allowed biological solids, gas and liquid samples to be withdrawn. The produced gas was collected via portholes on the top of the reactor and volume was determined using the gas–water displacement technique. Fig. 1 shows a schematic diagram of the HABR.
This experiment was divided into 3 parts: 1) the prompt start-up of HABR, 2) optimization of the operation parameters of HABR, and 3) examination of the performance of HABR under steady condition. The HABR was operated at HRT 168 h during start-up. The pH of influent was corrected to between 6.5 and 8.0 and the alkalinity was adjusted purposely higher. The initial influent COD was maintained at about 1800 mg/L up to a loading rate of 0.26 kg COD/m3 d; thereafter, increases in organic loading rate (OLR) from 0.26 to 1.92 kg COD/m3 d were mainly achieved by increasing the feed concentration to a COD of 135,200 mg/L. After the HABR achieved a prompt start-up, an orthogonal experiment of three factors at three different levels for optimization of the operation parameters of HABR was carried out at three given HRT (3, 5 and 7 d), influent alkalinity (500, 800, 1000 mg/L) and effluent recycle ratio (94, 156, 219). After the orthogonal experiment was completed, the study on the performance of HABR under steady condition was carried out, and the HABR went through the experimental conditions as given in Table 1. 2.5. Hydrodynamic flow characteristics Residence time distribution (RTD) studies were carried out to analyze the hydrodynamics of the reactor at HRTs of 3, 5 and 7 d at three different effluent recycle ratio (94, 156, 219) by adding a pulse of an inert tracer (lithium chloride) to the reactor at a concentration of 5.5 mg Lit/L of reactor volume. Samples were taken from the outlet of the reactor for at least 3 HRTs after the addition of the pulse and were analyzed for lithium concentration by using a microprocessor based flame photometer (model TMF 45, Toshniwal, India). Effluent samples were collected at regular intervals of 2 h. 2.6. Analytical methods
Fig. 1. Schematic diagram of a hybrid anaerobic baffled reactor. 1. Feed tank; 2. Peristaltic pump; 3. Influent; 4. Supernatant sampling port; 5. Temperature regulator; 6. Biogas holder; 7. Effluent; 8. Wastewater recycle; 9. Industrial peristaltic pumps; 10. Sludge sampling port.
The performance of the HABR was evaluated by determination of parameters COD, pH of the influent and effluent of each compartment according to standard methods [22], while available alkalinity was determined by direct titration method [23]. PVA was measured at 690 nm in spectrophotometer (Model DR 2800, HACH, USA). Biogas composition (CH4, CO2 and N2) was determined using gas chromatography with a flame thermal conductivity detector by MULTIGAS
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Table 1 Summary of reactor operating condition. Operation stage
Operation days (d)
HRT (d)
Nominal influent COD concentration (mg/L)
Nominal OLR (kgCOD/m3 d)
Nominal influent pH
Nominal influent alkalinity (mg/L)
Nominal effluent recycle ratio (R)
Start-up
1–10 11–20 21–30 31–40 41–50 51–60 61–81 82–102 103–123 124–138 139–153 154–168 169–177 178–186 187–195 196–315
7 7 7 7 7 7 7 7 7 5 5 5 3 3 3 5
1800 3600 4000 6000 9000 13,520 13,520 13,520 13,520 13,520 13,520 13,520 13,520 13,520 13,520 13,520
0.26 0.52 0.57 0.87 1.28 1.92 1.92 1.92 1.92 2.69 2.69 2.69 4.48 4.48 4.48 2.69
8 7.5 7.9 7.4 7.5 7.8 5.5 6.5 7.2 7.2 6.5 5.5 5.5 7.2 6.5 5.5
500 510 550 600 650 700 500 1000 2000 2000 1000 500 500 2000 1000 500
156 156 156 156 156 156 156 94 219 94 156 219 94 156 219 94
Optimization of operation parameters
Stable condition
analyzer Model MX2100 (OLDHAM, France). The compositions of the biogas were analyzed when the reactors reached steady-state condition. Mean and the standard deviation value of experimental data were calculated with duplicate samples. Sludge samples were taken from each compartment of the reactor after the start-up and stable operation of 120 d and the biomass was examined by SEM. Samples were first fixed for 4 h at room temperature with 2.5% (w/v) glutaraldehyde in Sorenson phosphate buffer, and dehydrated through a graded series of water–ethanol mixtures (10%, 25%, 50%, 75%, 90%, 100%). The samples were brought to equilibrium in each mixture for 10 min and finally dried by the frozen drying method before sputter-coating with gold particles. The samples were then examined in a scanning electron microscope (Model JSM-5600LV, Shimazu, JAP). Micrographs were produced at magnifications between 10× and 10,000×.
influent rate and HRT 5 d. The results indicated that: 1) the reactor achieved a prompt start-up; 2) orthogonal experiment was suitable for optimization of the operation parameters of HABR; 3) the reactor was operated stably under optimum condition; and 4) the reactor had good potential to treat real desizing PVA-containing wastewater.
3. Results and discussion 3.1. COD and PVA removal The COD and PVA concentrations during various operational conditions for the entire length of the study are shown in Fig. 2. In this experiment, start-up of reactor lasted for approximately 60 d for biomass acclimatization. COD removal efficiencies were in the range of 45.0–80.1% within 60 d of start-up, while PVA removal efficiencies were in the range of 18.0–50.0%. Due to inoculated granular sludge, it shortened the acclimatization period by sustaining high microbial activity. Within 135 d of the orthogonal experiment for optimization of the operation parameters of HABR, each trial was replicated three times to obtain suitable precision. COD removal observed was around 17.5–41.8%. The best performance was observed with an influent alkalinity 2000 mg/L, effluent recycle ratio of 94 times influent rate and HRT 5 d. PVA removal observed was around 7.0–20.9%. The best performance was observed with an influent alkalinity 500 mg/L, effluent recycle ratio of 94 times influent rate and HRT 5 d. The results indicated that higher alkalinity favored the removal of COD, but inhibited the biodegradation of PVA. It was inferred that higher alkalinity may inhibit proliferation of methanogenic bacteria and result in forming crystals, which wrapped the granules and prevented the further biodegradation of PVA. Under optimum condition, COD removal observed was around 42.0%, while PVA removal observed was around 18.0%. The PVA removal efficiency obtained with the reactor type used is much better than the efficiencies reported in the literature with other types of reactor [6]. The phase lasted 120 d with alkalinity of influent 500 mg/L, effluent recycle ratio of 94 times
Fig. 2. Concentrations variation and removal efficiencies of (A) COD and (B) PVA over time.
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Table 2 Factors and levels of an orthogonal design (A and B are the respective codes for each factor). Levels
1 2 3
Factors A [Alkalinity of influent (mg/L)]
B [Effluent recycle ratio (R)]
C [HRT (d)]
500 1000 2000
94 156 219
3 5 7
Table 4 ANOVA results for COD removal rate in the OA9 (34) matrix. Source
SS⁎
df a
MSa
F
F0.95(2,2)
F0.99(2,2)
A B C Error Total
61.717 240.762 368.148 2.377 673.004
2 2 2 2 8
30.859 120.381 184.074 1.189
FA = 25.964 FB = 101.288 FC = 154.879
19.0 19.0 19.0
99.0 99.0 99.0
a
,a
SS⁎—sum of squares, df—degrees of freedom, MS—mean squares.
Table 5 ANOVA results for PVA removal rate in the OA9 (34) matrix.
3.2. Orthogonal experiment design Taguchi's optimization technique is a unique and powerful optimization discipline that allows optimization with minimum number of experiments [24]. In this work, the effect of three important factors including alkalinity of influent, effluent recycle ratio, HRT and each factor at three levels were studied using Taguchi's method. The used level setting values of the main factors (A–C) and the OA9 (34) matrix employed to assign the considered factors are shown in Tables 2 and 3, respectively. It is noteworthy that the mean of COD, PVA removal rate and theirs (X, X 1j, X 2j, X 3j and Y, Y 1j, Y 2j, Y 3j) for each factor at different levels was also calculated respectively (Table 3). OA9 orthogonal array scheme was adapted, which needs 9 experiments to complete the optimization process; however, all of the trials were replicated three times to obtain suitable precision. In the proposed method, no interaction between the variables was found in the matrix and the focus was placed on the main effects of the three most important factors. ANalysis Of VAriance (ANOVA) between groups was used to assess the orthogonal array design results. The results of the sums of squares (SS) for different variables were calculated (Table 3). The error estimation of the experiments was calculated and used in ANOVA. The dummy column was assigned in OA9 (34) matrix as error column. The COD and PVA removal ANOVA results (Tables 4 and 5) showed that the most important factor contributing to the COD and PVA removal efficiency was factor C (HRT) followed by factor B (effluent recycle ratio) and lastly, factor A (influent alkalinity). Based on the COD removal ANOVA results, the optimum condition was A3B1C2, while based on the PVA removal ANOVA results, the optimum condition was A1B1C2. By comprehensively comparing experimental data and considering cost, A1B1C2 was chosen as the optimum condition, that is, influent alkalinity 500 mg/L, effluent recycle ratio of 94 times influent rate and HRT 5 d.
,a
Source
SS*
df a
MSa
F
F0.95(2,2)
F0.99(2,2)
A B C Error Total
21.660 73.319 136.867 0.66 232.506
2 2 2 2 8
10.830 36.660 68.434 0.330
FA = 32.968 FB = 111.597 FC = 208.321
19.0 19.0 19.0
99.0 99.0 99.0
a
SS⁎—sum of squares, df—degrees of freedom, MS—mean squares.
Fig. 3. Variation of pH and alkalinity over time.
3.3. pH and alkalinity Proper pH value and alkalinity are of key importance for the stable operation of HABR. The pH levels and alkalinity concentrations at
Table 3 The OA9 (34) matrix for optimization of the operation parameters of HABR. Column no. Exp. no.
Factor A
Factor B
Factor C
Error column
1 2 3 4 5 6 7 8 9 X 1j X 2j X 3j ST Y 1j Y 2j Y 3j ST′
1 1 1 2 2 2 3 3 3 31.700 26.897 32.980 61.717 16.007 12.291 13.464 21.660
1 2 3 1 2 3 1 2 3 36.673 28.297 25.607 240.762 17.770 13.049 10.943 73.319
1 2 3 2 3 1 3 1 2 29.410 38.857 23.310 368.148 13.090 19.057 9.614 136.867
1 2 3 3 1 2 2 3 1 30.773 30.993 29.810 2.377 13.888 14.266 13.607 0.66
COD removal rate (%)
PVA removal rate (%)
37.98 38.27 18.85 41.66 17.70 21.33 33.38 28.92 36.64 X = 30.526
18.994 20.618 8.410 20.963 7.080 8.829 13.352 11.448 15.591
ST = 673.004 Y = 13.921
ST′ = 232.506
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various operational conditions are shown in Fig. 3. During the startup, the pH of influent varied between 6.5 and 8.0 and alkalinity was adjusted deliberately higher (pH b 8.2), with a general increase in pH levels and alkalinity concentrations in the final effluent. Higher alkalinity applied during start-up period provided buffering in the reactor to prevent the souring of the reactor and sped up formation of granular sludge. Within 135 d of the orthogonal experiment, the pH
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levels and alkalinity concentrations varied under various operational conditions, while with an increase in the final effluent. Within 120 d of the optimum condition, the pH of influent was around 5.5 and alkalinity was 500 mg/L; however, the pH in the final effluent remained greater than 6.8 throughout the experimental study and alkalinity around 700 mg/L. At the same time, due to adoption of effluent recycle, pH and alkalinity in four compartments remained at a stable level. The pH in the first compartment remained greater than 6.5 throughout the experimental study. Within the acidogenic dominant zone of an anaerobic system, the low pH levels play a vital role in microbial selection [25–27]. In this study, the relatively high pH values in front compartments showed that the HABR configuration stimulated production of intermediate products in front compartments favorable to the methanogenic zone. It has been reported that the reactor design is of key importance for the selection of microbial populations within the system [28]. As stated above, souring of the reactor did not occur during the whole operation period. It was indicated that pH value and alkalinity were important parameters to measure the stability of the reactor. When the reactor was operated efficiently, effluent pH and alkalinity were relatively stable. 3.4. Gas production and composition The total biogas produced and the degree of waste stabilization, performance of an anaerobic system should also be measured in terms of an observed methane yield, the amount of methane generated per kilogram of COD removed. Initially arrangements were designed to collect the biogas separately from four compartments. Because some fraction of the gas produced solubilized in reactor effluent and escaped from being collected, cumulative gas production was low (Fig. 4A). Methane content in the biogas at different HRTs varied from 60% to 72% and the remaining was assumed as carbon dioxide. Increasing loading by lowering HRTs generally increases biogas production, our data (Fig. 4B, C) also illustrate that effluent recycle could augment biogas production as well. Increasing effluent recycle ratio has the effects similar to a decrease in HRT in a way that the microorganisms inside the reactor would expose to the higher hydraulic and organic loadings. The system at the HRT 5 d had the highest observed methane yield averaged at 0.30 L CH4/g COD removed of HABR (Fig. 4A), but approximately 14% less than theoretical value of 0.35 L CH4/g COD removed. Observed methane yield refers only to the fraction of COD removed that is effectively converted to methane. However, other parts of COD may have been removed through other means such as solid accumulated in the reactor, part of the VFA adsorbed on to the sludge, or precipitation of some compounds within the reactor [29]. 3.5. Residence time distribution studies Tracer studies were carried out at 3, 5 and 7 d HRTs at three different effluent recycle ratio. In order to compare the flow patterns
Table 6 Results of the residence time distribution studies.
Fig. 4. Biogas production (A) and gas percentage of HABR (B) at different OLRs and (C) with different effluent recycle ratio.
HRT (d)
Effluent recycle ratio
Dead space (%)
Dispersion number
7 7 7 5 5 5 3 3 3
94 156 219 94 156 219 94 156 219
14.2 12.5 9.9 13.0 10.3 9.2 12.5 9.0 8.5
0.100 0.111 0.113 0.105 0.115 0.132 0.111 0.133 0.138
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at different HRTs, normalized (dimensionless) time and concentration have been used.
Normalized time ðθÞ =
time ðhÞ HRT ðhÞ
ð1Þ
Normalized concentration
ðC Þ =
Measured concentration ðmg = LÞ Initial concentration ðmg = LÞ ð2Þ
From typical C-curves (C vs. θ) mean and the variance of the curve and finally the dead space in the reactor were calculated using a
Fig. 5. Scanning electron micrographs showing different types of bacteria in granular sludge from compartments 1 to 4, respectively. (A–D) Appearance of granules in each compartment after start-up; (E–H) cells from granule surface in each compartment after start-up; (I–K) SEM photomicrographs of granules from compartment 3 of HABR after stable operation; (I) dissected granule; (J) rod-shaped cells from granule surface; (K) filamentous cells from granule core.
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Fig. 5 (continued).
model. The cut-off point for the tail was taken at θ = 2. The area under the curve between θ = 0 and θ = 2 represented the fraction of tracer recovered within two residence times, while the total area under the C-curve is unity. 2
∫ x ⋅ f ðxÞdx Normalized mean μ α =
0
ð3Þ
2
∫ f ðxÞdx 0 2
∫ ðx−μ α Þf ðxÞdx 2
Variance σ =
0
ð4Þ
2
∫ f ðxÞdx 0
Dead space was calculated according to the following relation: Dead space fraction
Vd = 1 − να μ α V
ð5Þ
where Vd is the volume of dead space in the reactor (m3), V is the theoretical working volume of the reactor (m3), and μa is the fraction of tracer recovered within 2 residence times (i.e. area under the curve between θ = 0 and θ = 2). The standard deviation was used to find the dispersion number 2
2
D = uL of the reactor σ = 2ðD = uLÞ − 2ðD=uLÞ
D = uL
1−e
ð6Þ
where D is the longitudinal dispersion coefficient m2/s, u is the fluid velocity m/s, and L is the length of the reactor m [30]. The calculated results are summarized in Table 6. The dead space ranged from 8.5% to 14.2%. Dead space consists of both hydraulic and biological dead spaces. Hydraulic dead space is a function of the flow
rate and the number of compartments in the ABR and the biological dead space is a function of the biomass concentration and activity [31]. An increase in the (hydraulic) dead space was expected with a decrease in HRT while creating less (biological) dead space. However, no direct correlation between hydraulic dead space and HRTs could be drawn. Dispersion number was found to be lowest (0.100) at maximum HRT of 7 d at effluent recycle ratio of 94 times influent rate. It increased from 0.100 to 0.138, with decrease in HRT from 7 to 3 d. A large dispersion number (D/uL → ∞) shows a perfectly mixed system, whereas a small dispersion number (D/uL → 0) relates to a plug flow system, with D/uL = 0.02 being defined as an intermediate and D/uL = 0.2 as large degree of dispersion [31,32]. Based on the tracer studies carried out at different HRTs at three different effluent recycle ratio, it was observed that the flow pattern within the HABR remains intermediate between plug and perfectly mixed flows, closer to plug flow than completely mixed flow. 3.6. Microbial population distribution in the reactor The granular sludge can be observed in four compartments during the experiments. After 60 d of reactor start-up, the granules had compact structure and naturally occurring cavities on the surface, as illustrated in Fig. 5A–D. SEM photomicrographs showed that all granules had a heterogeneous bacterial population and the dominant cells in each compartment of the HABR appeared to have different morphologies. SEM images of the sludge from compartments 1 to 4 of the HABR are given in Fig. 5A–K, respectively. Different bacterial morphologies were observed within the HABR after the start-up of experiment. All granules examined were composed of various types of bacteria including bacilli, cocci and filaments. The granules in the initial compartments of the reactor were mainly composed of short rod-shaped and filamentous bacteria, as illustrated in Fig. 5E–H. Compartment 2 had no preponderant bacteria. The morphotype observed were bacilli and cocci, maybe they were similar to methanogenic bacteria. In compartment 3 of the reactor, granules were dominated presumably by Methanococcus and
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Methanobacterium. In compartment 4 of the reactor, the preponderant bacteria were similar to Methanobrevibacter. This result showed that microbial selection and zoning are encouraged inside the HABR [9,10]. Sludge samples were also taken from compartment 3 of HABR after stable operation of 120 d. Furthermore, there appeared to be a stratified structure to the bacterial genera present within the granules in compartment 3. This was observed when manually dissected granules were inspected for differences between the outside layer and deep section of the granule, as shown in Fig. 5I–K. The sectioned granules revealed that the bacteria in the deep centre of the granules were morphologically different from those at the surface. It appeared that a considerable part of the granule interior consisted of filamentous bacteria, while the outer layer mainly comprised rodshaped bacteria. Some researchers have concluded that clusters of Methanosaeta cells are the precursor nuclei during granule formation [33]. However, our observations indicate that the predominance of filamentous bacteria in a granule interior probably arises after a discrete internal microenvironment has established which provides a selective growth advantage for methanogens present in the granule interior, but not at the initial stage of granule formation, as predicted by multi-layer modeling [34]. 4. Conclusion The following conclusions about the HABR were drawn in this paper: a. The lab-scale HABR was able to treat PVA-containing desizing wastewater successfully. Under stable condition, the COD and PVA removal efficiencies were around 42.0% and 18.0% respectively. The optimum condition was chosen as alkalinity of influent 500 mg/L, effluent recycle ratio of 94 times influent rate and HRT 5 d. b. Proper pH and alkalinity were of key importance for the stable operation of HABR. c. The flow pattern within the reactors showed an intermediate behaviour between plug flow and ideally mixed flow. d. Methane content in the biogas at different HRTs varied from 60% to 72% and effluent recycle could augment biogas production. All the above indicated the improved lab-scale HABR proved to be a suitable technology for desizing wastewater treatment. Acknowledgments We thank Zhongde Company for offering the anaerobic granular sludge used in this study. This work was supported by the Innovation Foundation of Donghua University for Ph.D. candidates (BC200828) and the Key Subject Construction Item of Shanghai City (B064). References [1] H. Feitkenhauer, Anaerobic digestion of desizing wastewater: influence of pretreatment and anionic surfactant on degradation and intermediate accumulation, Enzyme Microb. Technol. 33 (2003) 250–258. [2] W. Hickmann, Environmental aspects of textile processing, J. Soc. Dyers Colorist 109 (1993) 32–37. [3] H. Yu, G. Gu, L. Song, Degradation of polyvinyl alcohol in sequencing batch reactors, Environ. Sci. Technol. 17 (1996) 1261–1267. [4] P. Kumar, B. Prasad, I.M. Mishra, S. Chand, Catalytic thermal treatment of desizing wastewaters, J. Hazard. Mater. 149 (1) (2007) 26–34. [5] S. Matsumura, H. Kurita, H. Shimokobe, Anaerobic biodegradability of polyvinyl alcohol, Biotechnol. Lett. 15 (1993) 749–754.
[6] S. Gartiser, M. Wallrabenstein, G. Stiene, Assessment of several test methods for the determination of the anaerobic biodegradability of polymers, J. Environ. Polym. Degrad. 6 (1998) 159–173. [7] W.P. Barber, D.C. Stuckey, The use of the anaerobic baffled reactor (ABR) for wastewater treatment: a review, Water Res. 33 (1999) 1559–1578. [8] J. Plumb, J. Bell, D.C. Stuckey, Microbial populations associated with treatment of an industrial dye effluent in an anaerobic baffled reactor, Appl. Environ. Microbiol. 67 (2001) 3226–3235. [9] S. Uyanik, P.J. Sallis, G.K. Anderson, The effect of polymer addition on granulation in an anaerobic baffled reactor (ABR). Part 1: process performance, Water Res. 36 (2002) 933–943. [10] S. Uyanik, P.J. Sallis, G.K. Anderson, The effect of polymer addition on granulation in an anaerobic baffled reactor (ABR). Part 2: compartmentalization of bacterial populations, Water Res. 36 (2002) 944–955. [11] T. Setiadi, L. Husaini, A. Djajadiningrat, Palm oil mill effluent treatment by anaerobic baffled reactors: recycle effects and biokinetic parameters, Water Sci. Technol. 34 (1996) 59–66. [12] R. Boopathy, Biological treatment of swine waste using anaerobic baffled reactors, Bioresour. Technol. 64 (1998) 1–6. [13] R. Grover, S.S. Marwaha, J.F. Kennedy, Studies on the use of an anaerobic baffled reactor for the continuous anaerobic digestion of pulp and paper mill black liquors, Process Biochem. 34 (1999) 653–657. [14] J.C. Akunna, M. Clark, Performance of a granular-bed anaerobic baffled reactor (GRABBR) treating whisky distillery wastewater, Bioresour. Technol. 74 (2000) 257–261. [15] B. Wang, Y. Shen, Performance of an anaerobic baffled reactor (ABR) as a hydrolysis-acidogenesis unit in treating landfill leachate mixed with municipal sewage, Water Sci. Technol. 42 (2000) 115–121. [16] P. Dama, J. Bell, K.M. Faxon, C.J. Brouckaert, T. Huany, C.A. Buckley, Pilot scale study of an anaerobic baffled reactor for the treatment of domestic wastewater, Water Sci. Technol. 26 (2002) 263–270. [17] M. Vossoughi, M. Shakeri, I. Alemzadeh, Performance of anaerobic baffled reactor treating synthetic wastewater influenced by decreasing COD/SO4 ratios, Chem. Eng. Process. 42 (2003) 811–816. [18] I. Bodik, K. Kratochvil, E. Gasparikova, M. Hutnan, Nitrogen removal in an anaerobic baffled reactor with aerobic post-treatment, Bioresour. Technol. 86 (2003) 79–84. [19] G.F. Zhu, J.Z. Li, P. Wu, H.Z. Jin, Z. Wang, The performance and phase separated characteristics of an anaerobic baffled reactor treating soybean protein processing wastewater, Bioresour. Technol. 99 (2008) 8027–8033. [20] G.D. Ji, T.H. Sun, J.R. Ni, J.J. Tong, Anaerobic baffled reactor (ABR) for treating heavy oil produced water with high concentrations of salt and poor nutrient, Bioresour. Technol. 100 (2009) 1108–1114. [21] M. Faisal, H. Unno, Kinetic analysis of palm oil mill wastewater treatment by a modified anaerobic baffled reactor, Biochem. Eng. J. 9 (2001) 25–31. [22] APHA, AWWA, WEF, Standard methods for the examination of water and wastewater, 21th ed.Springer, Berlin, 2005. [23] R. Dilallo, O.E. Alberton, Volatile acids by direct titration, J. Water Pollut. Control Fed. 33 (1961) 356–365. [24] R.K. Roy, A Primer on the Taguchi Method, VNR Publishers, New York, 1990. [25] B. Inanc, S. Matsui, S. Ide, Propionic acid accumulation and controlling factors in anaerobic treatment of carbohydrate: effects of H2 and pH, Water Sci. Technol. 34 (1996) 317–325. [26] N. Azbar, P. Ursillo, R.E. Speece, Effect of process configuration and substrate complexity on the performance of anaerobic processes, Water Res. 35 (2001) 817–829. [27] J.I. Horiuchi, T. Shimizu, K. Tada, T. Kanno, M. Kobayashi, Selective production of organic acids in anaerobic acid reactor by pH control, Bioresour. Technol. 82 (2002) 209–213. [28] R.E. Speece, M. Duran, G. Demirer, H. Zhang, T. DiStefano, The role of process configuration in the performance of anaerobic systems, Water Sci. Technol. 36 (1997) 539–547. [29] M.A. Pereira, M. Mota, M.M. Alves, Operation of an anaerobic filter and an EGSB reactor for the treatment of an oleic acid-based effluent: influence of inoculum quality, Process Biochem. 37 (2002) 1025–1031. [30] G.V.T. Gopala Krishna, P. Kumar, P. Kumar, Treatment of low-strength soluble wastewater using an anaerobic baffled reactor (ABR), J. Environ. Manage. 1 (2009) 166–176. [31] A. Grobicki, D.C. Stuckey, Hydrodynamic characteristics of the anaerobic baffled reactor, Water Res. 26 (3) (1992) 371–378. [32] O. Levenspiel, Chemical Reaction Engineering, third ed.Wiley, New York, 1999. [33] W.M. Wiegant, The “spaghetti theory” on anaerobic sludge formation, or the inevitability of granulation, Proceedings of the GASMAT Workshop, Lunteren, The Netherlands, 1987, pp. 146–152. [34] Y. Arcand, C. Chavarie, S.R. Guiot, Dynamic modeling of the populationdistribution in the anaerobic granular biofilm, Water Sci. Technol. 30 (1994) 63–73.
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Desalination j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / d e s a l
The performance evaluation of hybrid anaerobic baffled reactor for treatment of PVA-containing desizing wastewater Liu Rongrong a,b,⁎, Lu Xujie c, Tian Qing b, Yang Bo b, Chen Jihua b a b c
Department of Environmental Science & Engineering, Yangzhou Vocational College of Environment and Resources, Yangzhou, PR China Department of Environmental Science & Engineering, DongHua University, 2999 North Renmin Road, Songjiang district, Shanghai 201620, PR China School of Chemical and Environmental Engineering, Jianghan University, Wuhan 430056, PR China
a r t i c l e
i n f o
Article history: Received 8 October 2010 Received in revised form 20 December 2010 Accepted 20 December 2010 Available online 26 January 2011 Keywords: Desizing wastewater Granular sludge Hybrid anaerobic baffled reactor Polyvinyl alcohol Volatile fatty acid
a b s t r a c t Polyvinyl alcohol (PVA)-containing desizing wastewater discharged from final textile wastewater has a great impact on the environment. In the paper, an improved lab-scale hybrid anaerobic baffled reactor (HABR) was developed to treat desizing wastewater. Under optimum condition (alkalinity of influent 500 mg/L, effluent recycle ratio of 94 times influent rate and hydraulic retention time of 5 d), the system demonstrated a good performance of COD and PVA removal efficiencies (around 42.0% and 18.0% respectively) and the average concentration of alkalinity in the effluent was around 700 mg/L and pH value was above 6.8. Microbial selection and zoning are encouraged inside the HABR. The improved lab-scale HABR proved to be a suitable technology for desizing wastewater treatment. © 2011 Elsevier B.V. All rights reserved.
1. Introduction Polyvinyl alcohol (PVA), a water soluble synthetic polymer prepared by the hydrolysis of polyvinyl acetate, is widely used in the warp sizing process in textile industry due to its excellent film strength, flexibility, wearability, adhesiveness and chemical durability. In 2004, about 125 thousand tons of PVA were consumed in textile sizing agent industry in China. The PVA-containing desizing wastewater generated from desizing step contributes approximately 50% of the organic load in the total textile wastewater [1,2]. As a common refractory organic matter, 1 g of PVA is an equivalent of 0.016-g 5-d biochemical oxygen demand (BOD5) or 1.6 g chemical oxygen demand (COD). The ratio of BOD5 to COD is low to 0.01, indicating the poor biodegradability [3]. Therefore, the desizing wastewaters require adequate and sufficient treatment before being allowed to be discharged into surface waters. Various treatment methods such as special microorganisms and enzymes, biological activated sludge process, activated carbon adsorption, chemical oxidation by ozone, or a combination of UV radiation and ozone and H2O2, wet oxidation, etc. are being used to treat desizing wastewaters [4]. However, the treatment costs are very high and fullscale treatment processes are still impractical. In order to comply with the stringent COD discharge standard and requirement of energy saving and emission reduction in textile industry, anaerobic process becomes ⁎ Corresponding author. Yangzhou Vocational College of Environment and Resources, 33 South Runyang Road, Hanjiang district, Yangzhou 225127, PR China. Tel.: +86 514 87432017; fax: +86 514 87436688. E-mail address: [email protected] (L. Rongrong). 0011-9164/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.desal.2010.12.044
attractive for treatment of PVA-containing wastewater. This process takes advantages of microorganisms involved in the anaerobic process and their strong tolerance to high concentration inhibitory organic matters and unfavorable environmental stresses. A detailed investigation of the anaerobic biodegradability of PVA was carried out by Matsumura et al., and the result showed that over 60% of PVA was biodegraded as determined by TOC after 4 months of incubation [5]. In contrast with the above investigations, PVA was found to show only minor degradation, ranging between 0% and 12% in 77 d, in anaerobic tests using digestion sludge according to ISO and ASTM standard procedures [6]. As one of the high-rate anaerobic reactors, anaerobic baffled reactor (ABR) has several advantages such as simple design, low energy consumption, high stability for shocking and loading, and high treatment efficiency [7]. The significant advantage of the ABR is its ability to separate acidogenesis and methanogenesis longitudinally down the reactor [7–9]. This can permit different bacterial population to dominate each compartment, acidification predominating in the first compartment section and methanogenesis dominant in the subsequent section [7,9,10]. As a promising system for industrial wastewater treatment, the ABR was extensively used in the treatment of palm oil mill effluent wastewater [11], swine wastewater [12], synthetic tannery wastewater containing sulfate and chromium (III) [7], pulp and paper mill black liquors [13], whisky distillery wastewater [14], landfill leachate [15], domestic wastewater [16], sulfate-containing wastewater [17], nitrogencontaining wastewater [18], soybean protein processing wastewater [19] and also heavy oil produced water with high concentrations of salt and
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poor nutrient [20]. However, limited study on treating PVA-containing desizing wastewater using ABR was observed in the literature. Therefore, it is essential to evaluate the feasibility of a lab-scale ABR on treatment of PVA-containing desizing wastewater. Many developments have focused on ABR design and operation that can enhance both the efficiency and reliability of the technology. The main objective of the efficient ABR design must be high retention time of bacterial cells with very little loss of bacteria from the bioreactor, taking into consideration the slow growth rate of many anaerobic microorganisms, particularly methanogenics. In order to produce high-rate designs, enhance the bacterial activity together with good mixture to ensure a high rate of contact between the cells and their substrate [21], a modification was achieved by increasing the height of hybrid anaerobic baffled reactor (HABR) in this study, which increased the ability of entrapping microbe-rich small particles in the reactor. In addition, proper effluent recycle was also applied. This work has also provided an understanding of the relationship between operational conditions, reactor design, and the formation of granular sludge. The purpose of this study was to evaluate the performance of improved HABR for treatment of desizing wastewater. The performance of reactor during start-up, optimization of operation parameters and its potential to treat PVA-containing desizing wastewater were investigated.
The reactor was operated under mesophilic conditions (32 ± 1 °C). The influent was adjusted using a variable speed peristaltic pump (Model BT-001, Zhixin, China). Industrial peristaltic pump (Model PP6, SCMI, China) was used to control effluent recycle ratio to the reactor. 2.2. Wastewater characteristics The feed used in this study was real desizing wastewater which was collected from a dying and finishing plant at Chuzhou in Anhui, China. The composition of the raw wastewater was as follows: COD 10,000–13,520 mg/L, alkalinity (as CaCO3) 10,000–17,000 mg/L, BOD5 1500–2192 mg/L, PVA 1000–3000 mg/L, and suspended solid (SS) 5000–7056 mg/L, pH 12–14. 2.3. Inoculated sludge The HABR was inoculated with anaerobic granular sludge taken from an anaerobic digester of a sewage treatment plant in Yixing, China. Characteristics of inoculated sludge were: average particle size 3–5 mm, sedimentation velocity 23.40 ± 0.60 m/h, total suspended solid (TSS) 16.05 ± 0.40 g/L, volatile suspended solid (VSS) 12.02 ± 0.30 g/L, and VSS/TSS 72.85 ± 1.82%. 2.4. Experimental design
2. Materials and methods 2.1. Configuration of HABR The HABR had a dimension of 15 cm wide, 62 cm long and 100 cm high. It was constructed from Perspex, with a valid volume of 79.05 L. The reactor was divided into four equal compartments (compartments 1, 2, 3 and 4), which incorporated a solids settling chamber after its final compartment. Between the compartments there was a 5.5 cm wide recycle chamber in which inner recycle occurred from it to the first compartment. The compartment was equipped with sampling ports that allowed biological solids, gas and liquid samples to be withdrawn. The produced gas was collected via portholes on the top of the reactor and volume was determined using the gas–water displacement technique. Fig. 1 shows a schematic diagram of the HABR.
This experiment was divided into 3 parts: 1) the prompt start-up of HABR, 2) optimization of the operation parameters of HABR, and 3) examination of the performance of HABR under steady condition. The HABR was operated at HRT 168 h during start-up. The pH of influent was corrected to between 6.5 and 8.0 and the alkalinity was adjusted purposely higher. The initial influent COD was maintained at about 1800 mg/L up to a loading rate of 0.26 kg COD/m3 d; thereafter, increases in organic loading rate (OLR) from 0.26 to 1.92 kg COD/m3 d were mainly achieved by increasing the feed concentration to a COD of 135,200 mg/L. After the HABR achieved a prompt start-up, an orthogonal experiment of three factors at three different levels for optimization of the operation parameters of HABR was carried out at three given HRT (3, 5 and 7 d), influent alkalinity (500, 800, 1000 mg/L) and effluent recycle ratio (94, 156, 219). After the orthogonal experiment was completed, the study on the performance of HABR under steady condition was carried out, and the HABR went through the experimental conditions as given in Table 1. 2.5. Hydrodynamic flow characteristics Residence time distribution (RTD) studies were carried out to analyze the hydrodynamics of the reactor at HRTs of 3, 5 and 7 d at three different effluent recycle ratio (94, 156, 219) by adding a pulse of an inert tracer (lithium chloride) to the reactor at a concentration of 5.5 mg Lit/L of reactor volume. Samples were taken from the outlet of the reactor for at least 3 HRTs after the addition of the pulse and were analyzed for lithium concentration by using a microprocessor based flame photometer (model TMF 45, Toshniwal, India). Effluent samples were collected at regular intervals of 2 h. 2.6. Analytical methods
Fig. 1. Schematic diagram of a hybrid anaerobic baffled reactor. 1. Feed tank; 2. Peristaltic pump; 3. Influent; 4. Supernatant sampling port; 5. Temperature regulator; 6. Biogas holder; 7. Effluent; 8. Wastewater recycle; 9. Industrial peristaltic pumps; 10. Sludge sampling port.
The performance of the HABR was evaluated by determination of parameters COD, pH of the influent and effluent of each compartment according to standard methods [22], while available alkalinity was determined by direct titration method [23]. PVA was measured at 690 nm in spectrophotometer (Model DR 2800, HACH, USA). Biogas composition (CH4, CO2 and N2) was determined using gas chromatography with a flame thermal conductivity detector by MULTIGAS
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Table 1 Summary of reactor operating condition. Operation stage
Operation days (d)
HRT (d)
Nominal influent COD concentration (mg/L)
Nominal OLR (kgCOD/m3 d)
Nominal influent pH
Nominal influent alkalinity (mg/L)
Nominal effluent recycle ratio (R)
Start-up
1–10 11–20 21–30 31–40 41–50 51–60 61–81 82–102 103–123 124–138 139–153 154–168 169–177 178–186 187–195 196–315
7 7 7 7 7 7 7 7 7 5 5 5 3 3 3 5
1800 3600 4000 6000 9000 13,520 13,520 13,520 13,520 13,520 13,520 13,520 13,520 13,520 13,520 13,520
0.26 0.52 0.57 0.87 1.28 1.92 1.92 1.92 1.92 2.69 2.69 2.69 4.48 4.48 4.48 2.69
8 7.5 7.9 7.4 7.5 7.8 5.5 6.5 7.2 7.2 6.5 5.5 5.5 7.2 6.5 5.5
500 510 550 600 650 700 500 1000 2000 2000 1000 500 500 2000 1000 500
156 156 156 156 156 156 156 94 219 94 156 219 94 156 219 94
Optimization of operation parameters
Stable condition
analyzer Model MX2100 (OLDHAM, France). The compositions of the biogas were analyzed when the reactors reached steady-state condition. Mean and the standard deviation value of experimental data were calculated with duplicate samples. Sludge samples were taken from each compartment of the reactor after the start-up and stable operation of 120 d and the biomass was examined by SEM. Samples were first fixed for 4 h at room temperature with 2.5% (w/v) glutaraldehyde in Sorenson phosphate buffer, and dehydrated through a graded series of water–ethanol mixtures (10%, 25%, 50%, 75%, 90%, 100%). The samples were brought to equilibrium in each mixture for 10 min and finally dried by the frozen drying method before sputter-coating with gold particles. The samples were then examined in a scanning electron microscope (Model JSM-5600LV, Shimazu, JAP). Micrographs were produced at magnifications between 10× and 10,000×.
influent rate and HRT 5 d. The results indicated that: 1) the reactor achieved a prompt start-up; 2) orthogonal experiment was suitable for optimization of the operation parameters of HABR; 3) the reactor was operated stably under optimum condition; and 4) the reactor had good potential to treat real desizing PVA-containing wastewater.
3. Results and discussion 3.1. COD and PVA removal The COD and PVA concentrations during various operational conditions for the entire length of the study are shown in Fig. 2. In this experiment, start-up of reactor lasted for approximately 60 d for biomass acclimatization. COD removal efficiencies were in the range of 45.0–80.1% within 60 d of start-up, while PVA removal efficiencies were in the range of 18.0–50.0%. Due to inoculated granular sludge, it shortened the acclimatization period by sustaining high microbial activity. Within 135 d of the orthogonal experiment for optimization of the operation parameters of HABR, each trial was replicated three times to obtain suitable precision. COD removal observed was around 17.5–41.8%. The best performance was observed with an influent alkalinity 2000 mg/L, effluent recycle ratio of 94 times influent rate and HRT 5 d. PVA removal observed was around 7.0–20.9%. The best performance was observed with an influent alkalinity 500 mg/L, effluent recycle ratio of 94 times influent rate and HRT 5 d. The results indicated that higher alkalinity favored the removal of COD, but inhibited the biodegradation of PVA. It was inferred that higher alkalinity may inhibit proliferation of methanogenic bacteria and result in forming crystals, which wrapped the granules and prevented the further biodegradation of PVA. Under optimum condition, COD removal observed was around 42.0%, while PVA removal observed was around 18.0%. The PVA removal efficiency obtained with the reactor type used is much better than the efficiencies reported in the literature with other types of reactor [6]. The phase lasted 120 d with alkalinity of influent 500 mg/L, effluent recycle ratio of 94 times
Fig. 2. Concentrations variation and removal efficiencies of (A) COD and (B) PVA over time.
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Table 2 Factors and levels of an orthogonal design (A and B are the respective codes for each factor). Levels
1 2 3
Factors A [Alkalinity of influent (mg/L)]
B [Effluent recycle ratio (R)]
C [HRT (d)]
500 1000 2000
94 156 219
3 5 7
Table 4 ANOVA results for COD removal rate in the OA9 (34) matrix. Source
SS⁎
df a
MSa
F
F0.95(2,2)
F0.99(2,2)
A B C Error Total
61.717 240.762 368.148 2.377 673.004
2 2 2 2 8
30.859 120.381 184.074 1.189
FA = 25.964 FB = 101.288 FC = 154.879
19.0 19.0 19.0
99.0 99.0 99.0
a
,a
SS⁎—sum of squares, df—degrees of freedom, MS—mean squares.
Table 5 ANOVA results for PVA removal rate in the OA9 (34) matrix.
3.2. Orthogonal experiment design Taguchi's optimization technique is a unique and powerful optimization discipline that allows optimization with minimum number of experiments [24]. In this work, the effect of three important factors including alkalinity of influent, effluent recycle ratio, HRT and each factor at three levels were studied using Taguchi's method. The used level setting values of the main factors (A–C) and the OA9 (34) matrix employed to assign the considered factors are shown in Tables 2 and 3, respectively. It is noteworthy that the mean of COD, PVA removal rate and theirs (X, X 1j, X 2j, X 3j and Y, Y 1j, Y 2j, Y 3j) for each factor at different levels was also calculated respectively (Table 3). OA9 orthogonal array scheme was adapted, which needs 9 experiments to complete the optimization process; however, all of the trials were replicated three times to obtain suitable precision. In the proposed method, no interaction between the variables was found in the matrix and the focus was placed on the main effects of the three most important factors. ANalysis Of VAriance (ANOVA) between groups was used to assess the orthogonal array design results. The results of the sums of squares (SS) for different variables were calculated (Table 3). The error estimation of the experiments was calculated and used in ANOVA. The dummy column was assigned in OA9 (34) matrix as error column. The COD and PVA removal ANOVA results (Tables 4 and 5) showed that the most important factor contributing to the COD and PVA removal efficiency was factor C (HRT) followed by factor B (effluent recycle ratio) and lastly, factor A (influent alkalinity). Based on the COD removal ANOVA results, the optimum condition was A3B1C2, while based on the PVA removal ANOVA results, the optimum condition was A1B1C2. By comprehensively comparing experimental data and considering cost, A1B1C2 was chosen as the optimum condition, that is, influent alkalinity 500 mg/L, effluent recycle ratio of 94 times influent rate and HRT 5 d.
,a
Source
SS*
df a
MSa
F
F0.95(2,2)
F0.99(2,2)
A B C Error Total
21.660 73.319 136.867 0.66 232.506
2 2 2 2 8
10.830 36.660 68.434 0.330
FA = 32.968 FB = 111.597 FC = 208.321
19.0 19.0 19.0
99.0 99.0 99.0
a
SS⁎—sum of squares, df—degrees of freedom, MS—mean squares.
Fig. 3. Variation of pH and alkalinity over time.
3.3. pH and alkalinity Proper pH value and alkalinity are of key importance for the stable operation of HABR. The pH levels and alkalinity concentrations at
Table 3 The OA9 (34) matrix for optimization of the operation parameters of HABR. Column no. Exp. no.
Factor A
Factor B
Factor C
Error column
1 2 3 4 5 6 7 8 9 X 1j X 2j X 3j ST Y 1j Y 2j Y 3j ST′
1 1 1 2 2 2 3 3 3 31.700 26.897 32.980 61.717 16.007 12.291 13.464 21.660
1 2 3 1 2 3 1 2 3 36.673 28.297 25.607 240.762 17.770 13.049 10.943 73.319
1 2 3 2 3 1 3 1 2 29.410 38.857 23.310 368.148 13.090 19.057 9.614 136.867
1 2 3 3 1 2 2 3 1 30.773 30.993 29.810 2.377 13.888 14.266 13.607 0.66
COD removal rate (%)
PVA removal rate (%)
37.98 38.27 18.85 41.66 17.70 21.33 33.38 28.92 36.64 X = 30.526
18.994 20.618 8.410 20.963 7.080 8.829 13.352 11.448 15.591
ST = 673.004 Y = 13.921
ST′ = 232.506
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various operational conditions are shown in Fig. 3. During the startup, the pH of influent varied between 6.5 and 8.0 and alkalinity was adjusted deliberately higher (pH b 8.2), with a general increase in pH levels and alkalinity concentrations in the final effluent. Higher alkalinity applied during start-up period provided buffering in the reactor to prevent the souring of the reactor and sped up formation of granular sludge. Within 135 d of the orthogonal experiment, the pH
291
levels and alkalinity concentrations varied under various operational conditions, while with an increase in the final effluent. Within 120 d of the optimum condition, the pH of influent was around 5.5 and alkalinity was 500 mg/L; however, the pH in the final effluent remained greater than 6.8 throughout the experimental study and alkalinity around 700 mg/L. At the same time, due to adoption of effluent recycle, pH and alkalinity in four compartments remained at a stable level. The pH in the first compartment remained greater than 6.5 throughout the experimental study. Within the acidogenic dominant zone of an anaerobic system, the low pH levels play a vital role in microbial selection [25–27]. In this study, the relatively high pH values in front compartments showed that the HABR configuration stimulated production of intermediate products in front compartments favorable to the methanogenic zone. It has been reported that the reactor design is of key importance for the selection of microbial populations within the system [28]. As stated above, souring of the reactor did not occur during the whole operation period. It was indicated that pH value and alkalinity were important parameters to measure the stability of the reactor. When the reactor was operated efficiently, effluent pH and alkalinity were relatively stable. 3.4. Gas production and composition The total biogas produced and the degree of waste stabilization, performance of an anaerobic system should also be measured in terms of an observed methane yield, the amount of methane generated per kilogram of COD removed. Initially arrangements were designed to collect the biogas separately from four compartments. Because some fraction of the gas produced solubilized in reactor effluent and escaped from being collected, cumulative gas production was low (Fig. 4A). Methane content in the biogas at different HRTs varied from 60% to 72% and the remaining was assumed as carbon dioxide. Increasing loading by lowering HRTs generally increases biogas production, our data (Fig. 4B, C) also illustrate that effluent recycle could augment biogas production as well. Increasing effluent recycle ratio has the effects similar to a decrease in HRT in a way that the microorganisms inside the reactor would expose to the higher hydraulic and organic loadings. The system at the HRT 5 d had the highest observed methane yield averaged at 0.30 L CH4/g COD removed of HABR (Fig. 4A), but approximately 14% less than theoretical value of 0.35 L CH4/g COD removed. Observed methane yield refers only to the fraction of COD removed that is effectively converted to methane. However, other parts of COD may have been removed through other means such as solid accumulated in the reactor, part of the VFA adsorbed on to the sludge, or precipitation of some compounds within the reactor [29]. 3.5. Residence time distribution studies Tracer studies were carried out at 3, 5 and 7 d HRTs at three different effluent recycle ratio. In order to compare the flow patterns
Table 6 Results of the residence time distribution studies.
Fig. 4. Biogas production (A) and gas percentage of HABR (B) at different OLRs and (C) with different effluent recycle ratio.
HRT (d)
Effluent recycle ratio
Dead space (%)
Dispersion number
7 7 7 5 5 5 3 3 3
94 156 219 94 156 219 94 156 219
14.2 12.5 9.9 13.0 10.3 9.2 12.5 9.0 8.5
0.100 0.111 0.113 0.105 0.115 0.132 0.111 0.133 0.138
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at different HRTs, normalized (dimensionless) time and concentration have been used.
Normalized time ðθÞ =
time ðhÞ HRT ðhÞ
ð1Þ
Normalized concentration
ðC Þ =
Measured concentration ðmg = LÞ Initial concentration ðmg = LÞ ð2Þ
From typical C-curves (C vs. θ) mean and the variance of the curve and finally the dead space in the reactor were calculated using a
Fig. 5. Scanning electron micrographs showing different types of bacteria in granular sludge from compartments 1 to 4, respectively. (A–D) Appearance of granules in each compartment after start-up; (E–H) cells from granule surface in each compartment after start-up; (I–K) SEM photomicrographs of granules from compartment 3 of HABR after stable operation; (I) dissected granule; (J) rod-shaped cells from granule surface; (K) filamentous cells from granule core.
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293
Fig. 5 (continued).
model. The cut-off point for the tail was taken at θ = 2. The area under the curve between θ = 0 and θ = 2 represented the fraction of tracer recovered within two residence times, while the total area under the C-curve is unity. 2
∫ x ⋅ f ðxÞdx Normalized mean μ α =
0
ð3Þ
2
∫ f ðxÞdx 0 2
∫ ðx−μ α Þf ðxÞdx 2
Variance σ =
0
ð4Þ
2
∫ f ðxÞdx 0
Dead space was calculated according to the following relation: Dead space fraction
Vd = 1 − να μ α V
ð5Þ
where Vd is the volume of dead space in the reactor (m3), V is the theoretical working volume of the reactor (m3), and μa is the fraction of tracer recovered within 2 residence times (i.e. area under the curve between θ = 0 and θ = 2). The standard deviation was used to find the dispersion number 2
2
D = uL of the reactor σ = 2ðD = uLÞ − 2ðD=uLÞ
D = uL
1−e
ð6Þ
where D is the longitudinal dispersion coefficient m2/s, u is the fluid velocity m/s, and L is the length of the reactor m [30]. The calculated results are summarized in Table 6. The dead space ranged from 8.5% to 14.2%. Dead space consists of both hydraulic and biological dead spaces. Hydraulic dead space is a function of the flow
rate and the number of compartments in the ABR and the biological dead space is a function of the biomass concentration and activity [31]. An increase in the (hydraulic) dead space was expected with a decrease in HRT while creating less (biological) dead space. However, no direct correlation between hydraulic dead space and HRTs could be drawn. Dispersion number was found to be lowest (0.100) at maximum HRT of 7 d at effluent recycle ratio of 94 times influent rate. It increased from 0.100 to 0.138, with decrease in HRT from 7 to 3 d. A large dispersion number (D/uL → ∞) shows a perfectly mixed system, whereas a small dispersion number (D/uL → 0) relates to a plug flow system, with D/uL = 0.02 being defined as an intermediate and D/uL = 0.2 as large degree of dispersion [31,32]. Based on the tracer studies carried out at different HRTs at three different effluent recycle ratio, it was observed that the flow pattern within the HABR remains intermediate between plug and perfectly mixed flows, closer to plug flow than completely mixed flow. 3.6. Microbial population distribution in the reactor The granular sludge can be observed in four compartments during the experiments. After 60 d of reactor start-up, the granules had compact structure and naturally occurring cavities on the surface, as illustrated in Fig. 5A–D. SEM photomicrographs showed that all granules had a heterogeneous bacterial population and the dominant cells in each compartment of the HABR appeared to have different morphologies. SEM images of the sludge from compartments 1 to 4 of the HABR are given in Fig. 5A–K, respectively. Different bacterial morphologies were observed within the HABR after the start-up of experiment. All granules examined were composed of various types of bacteria including bacilli, cocci and filaments. The granules in the initial compartments of the reactor were mainly composed of short rod-shaped and filamentous bacteria, as illustrated in Fig. 5E–H. Compartment 2 had no preponderant bacteria. The morphotype observed were bacilli and cocci, maybe they were similar to methanogenic bacteria. In compartment 3 of the reactor, granules were dominated presumably by Methanococcus and
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Methanobacterium. In compartment 4 of the reactor, the preponderant bacteria were similar to Methanobrevibacter. This result showed that microbial selection and zoning are encouraged inside the HABR [9,10]. Sludge samples were also taken from compartment 3 of HABR after stable operation of 120 d. Furthermore, there appeared to be a stratified structure to the bacterial genera present within the granules in compartment 3. This was observed when manually dissected granules were inspected for differences between the outside layer and deep section of the granule, as shown in Fig. 5I–K. The sectioned granules revealed that the bacteria in the deep centre of the granules were morphologically different from those at the surface. It appeared that a considerable part of the granule interior consisted of filamentous bacteria, while the outer layer mainly comprised rodshaped bacteria. Some researchers have concluded that clusters of Methanosaeta cells are the precursor nuclei during granule formation [33]. However, our observations indicate that the predominance of filamentous bacteria in a granule interior probably arises after a discrete internal microenvironment has established which provides a selective growth advantage for methanogens present in the granule interior, but not at the initial stage of granule formation, as predicted by multi-layer modeling [34]. 4. Conclusion The following conclusions about the HABR were drawn in this paper: a. The lab-scale HABR was able to treat PVA-containing desizing wastewater successfully. Under stable condition, the COD and PVA removal efficiencies were around 42.0% and 18.0% respectively. The optimum condition was chosen as alkalinity of influent 500 mg/L, effluent recycle ratio of 94 times influent rate and HRT 5 d. b. Proper pH and alkalinity were of key importance for the stable operation of HABR. c. The flow pattern within the reactors showed an intermediate behaviour between plug flow and ideally mixed flow. d. Methane content in the biogas at different HRTs varied from 60% to 72% and effluent recycle could augment biogas production. All the above indicated the improved lab-scale HABR proved to be a suitable technology for desizing wastewater treatment. Acknowledgments We thank Zhongde Company for offering the anaerobic granular sludge used in this study. This work was supported by the Innovation Foundation of Donghua University for Ph.D. candidates (BC200828) and the Key Subject Construction Item of Shanghai City (B064). References [1] H. Feitkenhauer, Anaerobic digestion of desizing wastewater: influence of pretreatment and anionic surfactant on degradation and intermediate accumulation, Enzyme Microb. Technol. 33 (2003) 250–258. [2] W. Hickmann, Environmental aspects of textile processing, J. Soc. Dyers Colorist 109 (1993) 32–37. [3] H. Yu, G. Gu, L. Song, Degradation of polyvinyl alcohol in sequencing batch reactors, Environ. Sci. Technol. 17 (1996) 1261–1267. [4] P. Kumar, B. Prasad, I.M. Mishra, S. Chand, Catalytic thermal treatment of desizing wastewaters, J. Hazard. Mater. 149 (1) (2007) 26–34. [5] S. Matsumura, H. Kurita, H. Shimokobe, Anaerobic biodegradability of polyvinyl alcohol, Biotechnol. Lett. 15 (1993) 749–754.
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