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Performance and kinetic evaluation of anaerobic moving bed biofilm reactor for treating milk permeate from dairy industry
Bioresource Technology 100 (2009) 5641–5647
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Performance and kinetic evaluation of anaerobic moving bed biofilm reactor for treating milk permeate from dairy industry S. Wang a,b, N. Chandrasekhara Rao b, R. Qiu a,*, R. Moletta b,* a b
School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou 510275, China Optimisation Lab of Environmental Conception and Engineering, Polytech’ Savoie, Savoie University, Le Bourget Du Lac 73376, France
a r t i c l e
i n f o
Article history: Received 25 March 2009 Received in revised form 6 June 2009 Accepted 9 June 2009 Available online 23 July 2009 Keywords: Anaerobic moving bed biofilm reactor (AMBBR) Kinetics Mesophilic Milk permeate
a b s t r a c t High strength milk permeate derived from ultra-filtration based cheese making process was treated in an anaerobic moving bed biofilm reactor (AMBBR) under mesophilic (35 °C) condition. Total chemical oxygen demand (TCOD) removal efficiencies of 86.3–73.2% were achieved at organic loading rates (OLR) of 2.0–20.0 g TCOD L1 d1. A mass balance model gave values of methane yield coefficient (YG/S) and cell maintenance coefficient (km) of 0.341 L CH4 g1 TCODremoved and 0.1808 g TCODremoved g1 VSS d1, respectively. The maximum substrate utilization rate Umax was determined as 89.3 g TCOD L1 d1 by a modified Stover–Kincannon model. Volumetric methane production rates (VMPR) were shown to correlate with the biodegradable TCOD concentration through a Michaelis–Menten type equation. Moreover, based on VMPR and OLR removed from the reactor, the sludge production yield was determined as 0.0794 g VSS g1 TCODremoved. Ó 2009 Elsevier Ltd. All rights reserved.
1. Introduction Cheese industry produces high quantities of whey and milk permeate that represent a major disposal problem. Whey is the liquid that is separated from cheese after the coagulation of milk. It contains proteins (8.4 g L1), lactose (79 g L1), fat (<2.5 g L1) and mineral salts (5.6–8.4 g L1) (Suarez et al., 2006). Milk permeate is obtained when milk is concentrated by means of ultrafiltration process prior to cheese production. Its composition is similar to that of whey except for the negligible amount of proteins that it has. Being similar to whey, milk permeate shows a very high COD (chemical oxygen demand) value (around 55.2 g L1 in this study) due to the presence of lactose, and therefore it cannot be drained without treatment. Anaerobic treatments of dairy wastewaters (mainly whey) in various anaerobic reactors have been reported in many studies (Patel et al., 1999; Ergüder et al., 2001; Mockaitis et al., 2006; Saddoud et al., 2007). However, researchers stated that direct treatment of raw dairy wastewaters was not very reliable because of the very low bicarbonate alkalinity (2.5 g L1 as CaCO3), high COD concentration and rapid acidification tendency (Ergüder et al., 2001; Mockaitis et al., 2006). To solve this problem, a reactor which could retain more biomass for better COD degrada-
* Corresponding authors. Tel.: +86 20 8411 3454; fax: +86 20 8411 3616 (R. Qiu), tel.: +33 4 79 75 87 88 (R. Moletta). E-mail addresses: [email protected] (R. Qiu), [email protected] (R. Moletta). 0960-8524/$ - see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.biortech.2009.06.028
tion as well as provide good internal mixing to avoid reactor acidification is required. The anaerobic moving bed biofilm reactor (AMBBR) used in this study is such a reactor in which bio-carriers are employed and a submerged pump is equipped. AMBBR has been proved to be very reliable because of the high volumetric loading rates that could be applied and strong tolerance to shock loading in treating vinasse and landfill leachate (Chai and Moletta, 2007; Chen et al., 2008). However, its application in dairy wastewater treatment was rare. The only one case reported by Rodgers et al. (2004) showed that, at OLR of 11.6–15.2 g L1 d1 as well as HRT of 0.6–1.0 d, COD removal efficiency was well maintained in a range of 81–89% in the AMBBR used to treat whey wastewater at mesophilic conditions (35 ± 2 °C). It should be noted that the concentration of the whey wastewater used in that case was 9.1– 11.6 g COD L1, which were significantly lower than that of the milk permeate (around 55.2 g COD L1) to be treated in this study. Kinetic analysis is an accepted route for describing the performance of biological treatment systems and for predicting their performance (Yetilmezsoy and Sakar, 2008; Debik and Coskun, 2009). Previously reported kinetic analysis focused on a large range of reactors (anaerobic filter, hybrid column upflow anaerobic fixed bed reactor, UASB, upflow anaerobic packed bed reactor, etc.) and feeding substrates (papermill wastewater, starch wastewater, textile wastewater, saline wastewater, etc.) (Ahn and Forster, 2000; Isßik and Sponza, 2005; Kapdan, 2005; Sandhya and Swaminathan, 2006; Yilmaz et al., 2008). To describe and predict the performance of a bioprocess by determining kinetic constants, various kinetic models such as Monod first order model, Stover–Kincannon model
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and Michaelis–Menten type equation have been successfully developed and efficiently used (Kincannon and Stover, 1982; Ahn and Forster, 2000; Borja et al., 2004a,b). Despite the advantages offered by AMBBR, no kinetic analysis has been reported for substrate utilization and methane production in the bioreactor. Thus, the purpose of this research was to investigate the performance of an anaerobic moving bed biofilm reactor in treating undiluted high strength milk permeate. Kinetic analysis was also carried out to evaluate the bioreactor’s capability.
To start the experiment, the reactor was filled with 10 L seeding sludge, 18 L biofilm carriers and sufficient tap water to make up its working volume. The organic loading rate was implemented in a stepwise fashion from 2.0 to 28.0 g TCOD L1 d1, which corresponded to an HRT decrease from 27.56 to 1.97 d over a 9-month period. Kinetic analysis was carried out based on values obtained from stable performance stage, during which the average value of 4–6 consecutive analyses of each parameter amounts to less than 5% deviation in all cases.
2. Methods
2.5. Analytical techniques
2.1. Wastewater characteristics
Biogas and effluent samples were taken in duplicate and analyzed at least twice a week. Total and soluble COD values were measured by using micro method HACH (Spectrophotometer model: P/N 45600-02) and vials for COD 0–1500 ppm. pH measurements were taken twice per day with a pH meter (Model 2906, Eutech Instruments Ltd., Germany) and a pH probe (G-05992-55, Cole Parmer Instrument Co.). Volatile fatty acids (VFA), total alkalinity (TA), total solids (TS), suspended solids (SS) and volatile suspended solids (VSS) were measured by standard methods (APHA, 1995). Daily biogas production was recorded using digital gas meter (Moletta and Albagnac, 1982). Methane content in the biogas was analyzed by Shimadzu Gas-Chromatopac GC-8A equipped with a thermal conductivity detector and recorder C-R6A. N2 was used as the carrier gas and it had a flow-rate of 15 mL min1. Column temperature was 40 °C and current of the detector was 90 mA.
Detailed information of the milk permeate wastewater is presented in Table 1. Before feeding, urea and NaHCO3 was added (0.5 g L1 and 2.0 g L1, respectively) to provide nitrogen source and alkalinity buffering. Moreover, mineral solution VithaneÒ of 1.0 mL L1 from Biothane Co. was added. In addition, the pH of influent was adjusted to around 7.0 with 2.5 mol L1 NaOH solution. 2.2. Inoculum Anaerobic sludge was collected from a plant-scale UASB reactor which has been treating dairy wastewater for many years. The sludge was with pH of 7.2, total solids (TS) of 57.2 g L1, volatile solids (VS) of 49.8 g L1, suspended solids (SS) of 56.8 g L1 and volatile suspended solids (VSS) of 49.4 g L1.
3. Results and discussion 2.3. Biofilm carriers 3.1. Operational parameters and process stability Polyethylene support called Bioflow 9Ò from Raushert Co. was used as bio-carrier. One such bio-carrier (diameter 10 mm; height 8 mm; density 0.94; specific surface 530 m2 m3) consists of a small cylindrical element with small longitudinal fins that protrude on the outside surface and an internal triangle member that divides the element into three circular sectors. 2.4. Reactor configuration and operation Fig. 1 shows the schematic configuration of the reactor. The reactor of 30.0 L working volume was fabricated with polyethylene material and consisted of a tubular section of 23.8 cm internal diameter and 90.0 cm height. The system was placed in a chamber equipped with air heaters to keep the temperature of the reactor at 35 °C. Bioflow 9Ò was filled in the reactor as bio-carriers, occupying 65% of the working volume. Influent was continuously fed into the reactor bottom through the inlet by a peristaltic pump. A submerged pump (Model 1048, Eheim, Germany) with flow-rate of 480 L h1 was fixed at the bottom of the reactor to generate vertical current for inner mixing of the sludge and wastewater. Table 1 Characteristics of milk permeate wastewater. Parametera pH ORP (mv) TCOD (g L1) SCOD (g L1) TSS (g L1) TDS (g L1)
Value 5.55–6.52 +120 55.20 ± 2.26 51.18 ± 1.60 2.67 ± 0.73 10.83 ± 1.16
Parametera
TA (g L ) VFA (g L1) TN (g L1) TP (g L1) Biodegradability
Value 2.73 ± 0.24 1.82 ± 0.56 0.30–0.40 0.35–0.45 BOD/COD 0.95
a ORP, oxidation reduction potential; COD, chemical oxygen demand; TCOD, total COD; SCOD, soluble COD; TSS, total suspended solids; TDS, total dissolved solids; TA, total alkalinity; VFA, volatile fatty acids; TN, total nitrogen; TP, total phosphorous; BOD, bio-chemical oxygen demand.
Table 2 summarizes the operating results including experimental conditions and effluent parameters from the stable operation stage of the reactor. In the current research, authors used the soluble COD (SCOD) removal rate as criterion of system stability. If the SCOD removal rates were constantly stable above 90%, as well as the average value of 4–6 consecutive analyses of these rates amounted to less than 5% deviation, the reactor was considered stably working and ready for a shorter HRT. It should also be noted that, under lower loading condition (66.5 g TCOD L1 d1), OLR was increased slowly by 0.5–1.0 g L1 d1 each time to avoid any overload risk in the reactor. After this period, the reactor was subjected to faster increases (by 1.5–4.0 g L1 d1 each time) and finally reached the highest OLR of 28.0 g L1 d1. In this way, 16 runs were finished in a 9-month period. For the last four HRT settings, the duration of each HRT period was prolonged (28 d) to ensure good performance in the reactor. This strategy efficiently avoided potential impact of a previous HRT condition on current HRT condition. As seen in Table 2, with HRT decreasing to 2.76 d, the pH remained above the lower limit of optimal range (pH 6.8–7.2) for methanogenic bacteria, with 7.87 and 6.85 as extreme values. However, at lower HRTs of 2.30 and 1.97 d, the pH decreased to 6.73 and 6.63. This was probably due to the acidification of the reactor under mesophilic condition and thus, a further decrease of HRT could reinforce the acidification. The decrease of pH at lower HRTs was concomitant with the accumulation of VFA concentrations (expressed as equivalent acetic acid) in the reactor. According to Table 2, with HRT decreasing to 2.30 d, effluent VFA remained around 2 g L1, with 2.87 and 1.27 g L1 as extreme values. However, when the lowest HRT of 1.97 d was applied, effluent VFA sharply increased to a maximum value of 4.94 g L1, indicating that VFA accumulation occurred. The VFA accumulation is mainly due to the fact that the main
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Fig. 1. Schematic diagram of the lab-scale anaerobic moving bed bioflim reactor (AMBBR).
Table 2 Stable performance results obtained under various experimental conditions in AMBBR.a Run
HRTb
OLR
qCH4
TCOD
SCOD
VFA
Alkalinity
pH
VSS
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
27.56 (14) 22.05 (14) 18.38 (10) 15.75 (10) 12.25 (10) 10.02 (10) 8.48 (10) 6.89 (14) 5.80 (14) 5.01 (14) 4.24 (21) 3.68 (21) 3.24 (28) 2.76 (28) 2.30 (28) 1.97 (28)
2.0 2.5 3.0 3.5 4.5 5.5 6.5 8.0 9.5 11.0 13.0 15.0 17.0 20.0 24.0 28.0
15.00 17.71 20.70 23.57 30.11 36.34 44.62 54.46 65.37 75.32 90.73 105.17 123.03 140.44 159.40 159.90
8.61 8.21 7.55 8.32 9.31 9.84 9.04 9.84 10.32 10.43 12.24 13.15 14.80 14.73 17.57 23.23
0.98 0.86 1.03 1.05 1.14 1.33 1.34 1.39 1.59 1.73 2.31 3.17 3.29 3.64 4.66 8.17
2.42 1.30 1.98 2.40 1.27 1.61 1.93 2.04 1.95 2.74 1.87 1.80 2.09 2.33 2.87 4.94
8.08 6.90 6.61 7.65 6.91 9.41 8.98 7.80 6.50 8.39 8.77 6.48 6.28 5.38 5.10 4.94
7.72 7.87 7.74 7.60 7.55 7.74 7.70 7.41 7.30 7.27 7.24 7.14 7.27 6.85 6.73 6.63
3.61 3.65 4.05 4.83 4.64 4.46 4.09 4.26 4.79 5.22 5.25 5.44 5.71 5.43 5.52 6.83
a HRT, hydraulic retention time (d); OLR, organic loading rate (g TCOD L1 d1); qCH4 , daily methane production (L CH4 d1); TCOD, total chemical oxygen demand (g L1); SCOD, soluble chemical oxygen demand (g L1); VFA, volatile fatty acids (g equiv. acetic acid L1); Alkalinity (g equiv. CaCO3 L1); VSS, volatile suspended solids (g L1). b Values in parentheses are the corresponding duration (unit: d) of each HRT setting.
content of lactose in milk permeate is easily degraded by acidogenic bacteria, which causes acid inhibition to occur owing to the difference between acidogenic and methanogenic rates (Ergüder et al., 2001; Mockaitis et al., 2006). The impact of decreasing HRTs on VFA accumulation was reflected by the steady variability of daily methane production rate at the lowest HRT applied. As shown in Table 2, the increase of daily methane production rate (similar to that recorded at HRT of 2.30 d) stopped at HRT of 1.97 d with a value of 159.90 L CH4 d1. In general, the above-mentioned parameters showed that there is no failure of the biofilm reactor. This was due to the fact that bio-carriers were capable of retaining more attached biomass inside the reactor. Previous research conducted by Borja et al. (2004a,b) proved that a reactor with attached biomass was less affected than the control reactor by VFA accumulation at low HRTs. From Table 2, at HRTs lower than 3.24 d the alkalinity (expressed as equivalent CaCO3) decreased from above 6 to around 5 g L1. However, the buffering capacity inside the reactor was
maintained at a favorable level and contributed to the stability of the system at HRTs ranging from 27.56 d to 3.24 d. This can be attributed to carbonate/bicarbonate buffering mechanism inside the reactor. The carbonate/bicarbonate buffering is produced by the additive of NaHCO3 in the influent and the generation of CO2 that is not completely removed from the reactor as gas (Borja et al., 2004a,b). It guards against possible acidification of the reactor, given a pH optimal to that for methanogenic bacteria for the above range of HRT values. On the other hand, the VFA/alkalinity ratio can be used as a measure of process stability (Borja et al., 2004a,b): when this ratio is less than 0.3–0.4, the process is considered to be operating favorably without acidification risk. As can be observed in Fig. 2a, at HRTs of 27.56–3.24 d, the VFA/alkalinity ratio was always lower than the above-mentioned failure limit value. However, for HRTs lower than 3.24 d (period of 14, 15 and 16), a considerable increase of the VFA/alkalinity ratio was observed (from 0.43 to 1.00) as a result of considerable increase in the VFA concentrations (2.33–
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8.0
1.2
7.8
1.0 0.8
pH
7.4 pH
7.2
0.6
VFA/Alkalinity
7.0
0.4
VFA/Alkalinity
7.6
6.8 0.2
6.6 6.4
0
5
10
15
20
25
30
0.0
HRT (d)
20 y=0.9490x, R2=0.9987
-1
-1
COD removal rate (g l d )
25
15
10
y=0.7750x, R2=0.9904
5
0
3.3. Substrate balance model
TCOD SCOD
0
5
10
15
20 -1
25
and, generally, remained around 77% and 95% when the OLR increased from 2.0 g TCOD L1 d1 to 20.0 g TCOD L1 d1. However, TCOD and SCOD removal efficiencies started to decrease when OLR was raised to 24.0 g TCOD L1 d1 and achieved minimum values of 57.9% and 84.1% at OLR of 28.0 g TCOD L1 d1. Fig. 2b illustrates the TCOD and SCOD removal rates (expressed as the removals of TCOD and SCOD L1 d1) as a function of COD loading rate. Here, TCOD removal rate is a function of OLR (TCOD loading rate), and SCOD removal rate is a function of SCOD loading rate. As it could be found, the rates of TCOD and SCOD removal increased linearly over OLR of 2.0–20.0 g TCOD L1 d1. The slopes of the regression lines of 0.775 for TCOD and 0.949 for SCOD could be obtained. Thus, the overall TCOD and SCOD removal efficiency are 77.5% and 94.9%, respectively, over OLR of 2.0–20.0 g TCOD L1 d1. Previous studies found out that VFA accumulation is easy to occur and thus makes the anaerobic treatment unsteady if undiluted whey is directly fed into the reactor (Malaspina et al., 1996; Ergüder et al., 2001; Mockaitis et al., 2006). However, Ergüder et al. (2001) reported a good treatability of undiluted whey (42.7– 55.1 g COD L1) by UASB at OLR of 22.6–24.6 g COD L1 d1 as well as HRT of 2.1–5.0 d. The COD removal efficiency in their research was steady at 95–97%. This was comparable to the SCOD removal efficiency (94.9%) obtained in our current study.
30
-1
COD loading rate (g l d ) Fig. 2. Variations of operational parameters: (a) VFA/alkalinity ratios (equiv. acetic acid/equiv. CaCO3) and pH values over various HRTs; (b) TCOD and SCOD removal rates against TCOD loading rate (OLR) and SCOD loading rate, respectively.
A substrate balance model examining the TCOD balance of the reactor was conducted based on the following two hypotheses (Borja et al., 2002): (1) the anaerobic reactor is operated under steady state for all the OLRs applied; and (2) the suspended solids in the feeding are readily biodegradable and the volatile suspended solids in the effluent are the only source of the biomass generated. Thus, a reactor COD balance is obtained in the following equation (Borja et al., 2004a,b):
ðTCODÞi ¼ ðSCODÞe þ ðTCODÞbiogas þ ðTCODVSS Þe þ ðTCODÞm ; 4.94 g L1) as well as accompanying decrease in alkalinity (5.38– 4.94 g L1). This increase of the VFA/alkalinity ratio with a decreasing HRT was accompanied by a decrease of pH, which achieved the minimum pH values of 6.63 at HRT of 1.97 d. During the last three runs (period of 14, 15 and 16), the methanogenic bacteria were believed to be affected by the high level VFA/alkalinity ratios (Fig. 2a) since the increases of methane productions were in slower paces and almost stopped in the period of 16 (Table 2). When methane production was divided by total amount of influent TCOD, ratios of methane to substrate (CH4/ TCOD) were found to decrease for period of 14, 15 and 16 in the following order: 0.23, 0.22 and 0.19 L CH4 g1 TCOD. All of these values were smaller than the CH4/TCOD ratio of 0.24 L CH4 g1 TCOD found for period of 13 (VFA/alkalinity = 0.33). Therefore, when VFA/alkalinity ratios were at high level (exceeded the limit of 0.4), methane productions were proved to be inhibited. 3.2. Process efficiency From Tables 1 and 2, the variation of TCOD and SCOD removal efficiencies at respective HRT or OLR could be calculated. TCOD and SCOD removal efficiencies decreased slightly from 86.3% to 81.1% and from 98.3% to 96.6% upon an HRT decrease from 27.56 to 5.01 d. However, for HRTs of and lower than 4.24 d, both TCOD and SCOD removal efficiencies decreased more rapidly from 77.8% to 57.9% and from 95.7% to 84.1%. As such, it could be concluded that the decrease of TCOD removal efficiency with decreasing HRT was more pronounced and fluctuating. On the other hand, both of TCOD and SCOD removal efficiencies decreased slightly
ð1Þ
where (TCOD)i is the influent TCOD, (SCOD)e is the effluent SCOD, (TCOD)biogas is the fraction of (TCOD)i converted into biogas, (TCODVSS)e is the fraction of (TCOD)i converted into biomass and (TCOD)m is the fraction of (TCOD)i consumed for cell maintenance. Eq. (1) can be transformed into the following equation:
qSTi ¼ qSSe þ qCH4 Y S=G þ qðSTe SSe Þ þ km XV;
ð2Þ
where q is the flow-rate (L d1), STi is the influent TCOD concentration (g TCOD L1), STe is the effluent TCOD concentration (g TCOD L1), SSe is the effluent SCOD concentration (g SCOD L1), qCH4 is the daily methane production (L CH4 d1), YS/G is the conversion coefficient of substrate into methane (g TCODremoved L1 CH4), km is the coefficient for cell maintenance (g TCODremoved g1 VSS d1), X is the biomass concentration in the reactor (g VSS L1) and V is the working volume of the reactor (L). Herein, experimental results of all the parameters, except X, are listed in Table 2. In the table, effluent biomass concentrations are given as VSS. However, these values should be adjusted so as to reflect the corresponding total biomass concentrations in the reactor at each OLR level. According to Chai and Moletta (2007), suspended biomass generally occupied 16.6% of the total biomass. Thus, the effluent VSS values in this study should be divided by 0.166 to give values to X. From Eq. (2) the following equation can be obtained:
qðSTi STe Þ ¼ qCH4 Y S=G þ km XV:
ð3Þ
By grouping terms and dividing by the product between the reactor volume V and the biomass concentration X, the following equations can be obtained:
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ðSTi STe Þ=ðHRTÞX ¼ Y S=G ðqCH4 =XVÞ þ km ;
ð4Þ
km ¼ ððSTi STe Þ=HRT Y S=G qCH4 =VÞ=X:
ð5Þ
According to Eq. (4), if the quotient (STi STe)/(HRT)X is plotted against the quotient qCH4 =XV, YS/G is the slope and km is the intercept point of a straight line. As illustrated in Fig. 3, the points fit as a straight line with a small intercept for the reactor and the regression coefficient is 0.99, which strongly supports the validity of the model. From the figure, the values of YG/S, calculated as the inverse of YS/G, and km were obtained. YG/S or methane yield coefficient was found to be 0.341 L CH4 g1 TCODremoved for the reactor. This value was similar to those obtained in the anaerobic digestion process of wastewaters coming from cheese making process (Ergüder et al., 2001). It was also coincident with other methane yield coefficient values reported in the literatures for anaerobic treatments of other food industry wastewaters (Borja et al., 2004a,b). On the other hand, the km value obtained in the reactor was 0.0300 g TCODremoved g1 VSS d1, being comparable to the value of 0.0057 g TCODremoved g1 VSS d1 reported by Rincón et al. (2006). This demonstrates that the maintenance energy needed in AMBBR is of a higher order of magnitude. According to Eq. (5), the high value of km might be ascribed to low value of X, the biomass concentration in the reactor, that was indirectly estimated based on the effluent VSS and previous research result. However, this is practically negligible since it represents a quite small fraction of TCODremoved in any OLR assay. Therefore, it could be concluded that the initial raw substrate is basically consumed in anaerobic methane production and biomass generation processes. 3.4. Maximum substrate utilization rate (Stover–Kincannon model) The Stover–Kincannon model was first proposed for a rotary biological contactor by Kincannon and Stover (1982). The original model assumed that the suspended biomass was negligible in comparison to the attached biomass on the media and thus, the disc surface area of the rotary biological contactor was used to represent the total attached-growth active biomass concentration. However, this cannot be applied to other bioreactors that do not have disc configurations. Ahn and Forster (2000) stated that suspended biomass within the interstitial void spaces of the support media is a significant factor in producing high and stable removal efficiency and therefore, proposed that the volume of the reactor can be used instead of the surface area. Therefore, at steady state, the Stover– Kincannon model would have the form as shown in Eq. (6). Here, the AMBBR was also assumed to operate under steady state for all the OLRs applied.
dS U max ðqSTi =VÞ ¼ : dt K B þ ðqSTi =VÞ This can be linearized as:
1 dS KB V 1 ¼ V=qðSTi STe Þ ¼ : þ dt U max U max qSTi
HRT=ðSTi STe Þ ¼
KB 1 1 þ ; U max U max OLR
ð8Þ
where V is the reactor working volume (L), q is the flow-rate (L d1), STi is the influent TCOD concentration (g TCOD L1), STe is the effluent TCOD concentration (g TCOD L1), KB is a rate constant (g L1 d1), Umax is maximum substrate utilization rate constant (g L1 d1), HRT is the hydraulic retention time (d) and OLR is the organic loading rate (g TCOD L1 d1). Since dS/dt approaches Umax as the organic loading rate qSTi/V approaches infinity in Eq. (7), Umax can be referred as the maximum substrate utilization rate constant. According to Eq. (8), if HRT/(STi STe) is plotted against 1/OLR, KB/Umax is the slope and 1/Umax is the intercept point of a straight line. As plotted in Fig. 4, the points fit a straight line with a small intercept; the regression coefficient (0.99) strongly supports the validity of the linearized Stover–Kincannon model. Thus, it could be concluded that the modified Stover–Kincannon model is capable in describing the performance of mesophilic AMBBR treating milk permeate wastewater in this study. Fig. 4 also predicts values for Umax and KB (89.3 and 102.3 g TCOD L1 d1, respectively) for the reactor. Compared with the maximum OLR of 28.0 g TCOD L1 d1 obtained in this study, the predicted Umax is significantly higher. This indicates that the AMBBR possessed much higher potential in coping with high strength milk permeate. A comparison of the values of Umax and KB obtained by the same modified Stover–Kincannon model for various substrates is shown in Table 3 for mesophilic digesters. As seen in Table 3, the highest values of Umax and KB were obtained for papermill wastewater followed by milk permeate wastewater. A comparison of the values in Table 3 shows that Umax and KB obtained from current work are similar to those obtained with starch based substrate, but significantly higher than those obtained from simulated paper and corrugated papermill wastewaters. The results reported by Ahn and Forster (2000) showed that, in a mesophilic anaerobic filter treating simulated starch wastewater, there was also marked difference between the maximum OLR (17.2 g SCOD L1 d1) and the Umax (49.8 g SCOD L1 d1) predicted by the modified Stover–Kincannon model. The authors stated that this was due to an appreciable
0.8
HRT/(S Ti-STe ) (l d g TCOD)
0.5 0.4
0.6
y=1.1457x+0.0112, R2=0.9993
-1
(ST0-STe)/(HRT)X
ð7Þ
By grouping terms, Eq. (7) has the form:
0.6
0.3 0.2
y=2.9367x+0.0300, R2=0.9902
0.1 0.0 0.00
ð6Þ
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
qCH4/VX Fig. 3. Variation of the quotient of (STi STe)/(HRT)X as a function of the quotient of qCH4 =ðVXÞ.
0.4
0.2
0.0 0.0
0.1
0.2
0.3
0.4
0.5
0.6
1/OLR (l d g-1 TCOD) Fig. 4. Scatter plot of HRT/(STi STe) against 1/OLR for the determination of maximum substrate utilization rate.
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Table 3 Comparison of the kinetic parameters obtained for various substrates and digesters. Substrate source
Type of reactor
Umax (g L1 d1)
KB (g L1 d1)
R2
References
Milk permeate Papermill wastewater Simulated starch wastewater Textile wastewater Simulated textile wastewater Synthetic saline wastewater
AMBBR Anaerobic filter Anaerobic filter Hybrid column upflow anaerobic fixed bed reactor Upflow anaerobic sludge blanket reactor Upflow anaerobic packed bed reactor
89.3 86.21 49.8 31.69 7.5 5.3
102.3 104.15 50.6 45.37 8.2 7.05
0.99 0.99 0.99 0.99 0.99 0.91
This study Yilmaz et al. (2008) Ahn and Forster (2000) Sandhya and Swaminathan (2006) Isßik and Sponza (2005) Kapdan (2005)
deterioration in performance which occurred at the highest OLR. Similarly, such situation also existed in the AMBBR in this study and has been proved by the operational parameters (see Table 2).
18
-1
VMPR (g CH4-TCOD l d )
16
According to Table 2, the volumetric methane production rates (rCH4 ) can be obtained through the expression:
r CH4 ¼ qCH4 =V;
ð9Þ
where qCH4 is the daily methane production (L CH4 d1) and V is the reactor working volume (L). In Eqs. (2)–(5), S denotes the concentration of substrate; however, the experimental method used to determine the substrate concentration (TCOD and SCOD analysis) does not distinguish between biodegradable and non-biodegradable substrate. The experimental values of TCOD given in Table 2 must be corrected by subtracting the fraction of non-biodegradable substrate. According to the method used in Martín et al. (1993), the amount of non-biodegradable substrate could be estimated by plotting ln(TCOD) as a function of 1/(HRT) based on the values listed in Table 2. By the least-squares fitting, an intercept of 7.4 g TCOD L1 (regression coefficient 0.97) was calculated, which corresponds to an infinite HRT. Thus, this can be assumed to be the concentration of non-biodegradable substrate (Martín et al., 1993; Rincón et al., 2006). The observed values of rCH4 plotted as a function of the biodegradable TCOD concentrations (TCODb) are illustrated in Fig. 5. As it can be seen, the observed rCH4 values fit a Michaelis–Menten type kinetic model, which is a hyperbolic function. By using the software SigmaPlot V10.0, the following kinetic equation was obtained:
r CH4 ¼ 9:31TCODb =ð10:91 þ TCODb Þ:
ð10Þ
From Eq. (10) the theoretical r CH4 values could be determined for the reactor used in this study. When the theoretical rCH4 values are plotted against those observed ones, a linear regression line
-1
-1
rCH4 (l CH4 l d )
6
4
y=9.3091x/(10.9064+x), R2=0.9457
2
0
0
2
4
6
8
10
12
14
16
14
-1
3.5. Kinetics of methane production (Michaelis–Menten model)
18
Effluent TCODb (g l-1) Fig. 5. Variation of the volumetric methane production rates ðr CH4 Þ as a function of the biodegradable TCOD (TCODb) concentration in the effluent.
y=0.8881x, R2=0.9878
12 10 8 6 4 2 0
0
2
4
6
8
10
12
14
16
18
OLR removed (g TCOD l-1 d-1) Fig. 6. Volumetric methane production rate (VMPR) as a function of TCODremoved. The slope of the fitted line is the proportional fraction of TCODremoved converted into methane.
with a slope of 0.93 and a regression coefficient of 0.94 were obtained. This suggests that the proposed model is capable of accurately predicting the behavior of the AMBBR for the milk permeate in this study. 3.6. Sludge yield coefficient The production of methane is related to the COD reduction and the remaining portion of the reduced COD is considered as synthesis of biomass (Chen et al., 2008). These can allow us to estimate the sludge yield in anaerobic digestions (Fang et al., 1995; Kwong and Fang, 1996; Timur and Özturk, 1997). Generally, the volume of 1 g methane is 1.4 L at STP (standard temperature and pressure) and is equivalent to 4 g COD. Therefore, the volumetric methane production rate (VMPR) could be calculated from the produced methane volume over the reactor volume and HRT. Fig. 6 shows that the VMPR increases with the TCODremoved at a rate of 0.888 g CH4-TCOD g1 TCODremoved. As an average, 88.8% of the TCODremoved is converted to methane, and the remaining 11.2% is presumably converted to biomass. The COD equivalence of the biomass in reactors is 1.41 g COD g1 VSS (Shin et al., 2001). Consequently, the sludge yield is estimated to be 0.0794 g VSS g1 TCODremoved, which is of the same order of magnitude as those results of 0.050–0.057 g VSS g1 COD removed reported by other researchers based on the same method (Chen et al., 2008; Chui et al., 1994; Shin et al., 2001). However, the calculated sludge yield indicates that a bigger fraction of TCODremoved is required for biomass syntheses in AMMBR digestion of milk permeate under the mesophilic condition in this study. 4. Conclusions The results of this study demonstrate that high strength milk permeate wastewater was easily biodegradable in anaerobic
S. Wang et al. / Bioresource Technology 100 (2009) 5641–5647
moving bed biofilm reactor. The theoretical rates based on kinetic models agreed well with experimental values. The average methane yield coefficient YG/S obtained by a mass balance was 0.341 L CH4 g1 TCODremoved. The maximum substrate utilization rate Umax predicted by Stover–Kincannon was 89.3 g TCOD L1 d1, indicating a potentially higher capacity of the AMBBR. Michaelis–Menten model predicted the methane production quite well with a regression coefficient of 0.94. These confirm that the kinetic models are capable of describing the reactor’s bio-kinetic behavior. Acknowledgements This study was supported by a scholarship funded by the French Ministry of Foreign Affairs (Grant No. 20051725). Financial supports from Guangdong Provincial Natural Science Foundation in Universities (No. 06Z001) and New Century Excellent Talents Program from Ministry of Education of China (No. NCET04-0790) are also sincerely acknowledged. The authors are grateful to Region Rhône Alpes, France for the financial support in EMERGENCE program. References Ahn, J.H., Forster, C.F., 2000. Kinetic analyses of the operation of mesophilic and thermophilic anaerobic filters treating a simulated starch wastewater. Process Biochemistry 36, 19–23. APHA (American Public Health Association), 1995. Standard Methods for the Examination of Water and Wastewater. 19th ed. APHA, Washington, DC. Borja, R., González, E., Raposo, F., Millán, F., Martín, A., 2002. Kinetic analysis of the psychrophilic anaerobic digestion of wastewater derived from the production of proteins from extracted sunflower flour. Journal of Agricultural and Food Chemistry 50, 4628–4633. Borja, R., Rincón, B., Raposo, F., Dominguez, J.R., Millan, F., Martín, A., 2004a. Mesophilic anaerobic digestion in a fluidised-bed reactor of wastewater from the production of protein isolates from chickpea flour. Process Biochemistry 39, 1913–1921. Borja, R., Rincón, B., Raposo, F., Sanchez, E., Martín, A., 2004. Assessment of kinetic parameters for the mesophilic anaerobic biodegradation of two-phase olive pomace. International Biodeterioration and Biodegradation 53, 71–78. Chai, S.L., Moletta, R., 2007. Anaerobic treatment of vinasses by a sequentially mixed moving bed biofilm reactor. Water Science and Technology 56, 1–7. Chen, S., Sun, D., Chung, J.S., 2008. Simultaneous removal of COD and ammonium from landfill leachate using an anaerobic–aerobic moving-bed biofilm reactor system. Waste Management 28, 339–346. Chui, H.K., Fang, H.H.P., Li, Y.Y., 1994. Removal of formate from wastewater by anaerobic process. Journal of Environmental Engineering 120, 1308–1320. Debik, E., Coskun, T., 2009. Use of the Static Granular Bed Reactor (SGBR) with anaerobic sludge to treat poultry slaughterhouse wastewater and kinetic modeling. Bioresource Technology 100, 2777–2782. Ergüder, T.H., Tezel, U., Güven, E., Demirer, G.N., 2001. Anaerobic biotransformation and methane generation potential of cheese whey in batch and UASB reactors. Waste Management 21, 643–650.
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Fang, H.H.P., Chui, H.K., Li, Y.Y., 1995. Effect of degradation kinetics on the microstructure of anaerobic biogranules. Water Science and Technology 32, 165–172. Isßik, M., Sponza, D.T., 2005. Substrate removal kinetics in an upflow anaerobic sludge blanket reactor decolorising simulated textile wastewater. Process Biochemistry 40, 1189–1198. Kapdan, I.K., 2005. Kinetic analysis of dyestuff and COD removal from synthetic wastewater in an anaerobic packed column reactor. Process Biochemistry 40, 2545–2550. Kincannon, D.F., Stover, E.L., 1982. Design methodology for fixed film reaction-RBCs and biological towers. Civil Engineering for Practicing and Design Engineers 107, 24. Kwong, T.S., Fang, H.H.P., 1996. Anaerobic degradation of corn starch in wastewater in two upflow reactors. Journal of Environmental Engineering 122, 9–16. Malaspina, F., Cellamare, C.M., Stante, L., Tilche, A., 1996. Anaerobic treatment of cheese whey with a downflow–upflow hybrid reactor. Bioresource Technology 55, 131–139. Martín, A., Borja, R., Chica, A., 1993. Kinetic study of an anaerobic fluidized bed system used for the purification of fermented olive mill wastewater. Journal of Chemical Technology and Biotechnology 56, 155–162. Mockaitis, G., Ratusznei, S.M., Rodrigues, J.A.D., Zaiat, M., Foresti, E., 2006. Anaerobic whey treatment by a stirred sequencing batch reactor (ASBR): effects of organic loading and supplemented alkalinity. Journal of Environmental Management 79, 198–206. Moletta, R., Albagnac, G., 1982. A gas meter for low rates of gas flow: application to the methane fermentation. Biotechnology Letters 4, 319–322. Patel, P., Patel, C., Madamwar, D., 1999. Anaerobic upflow fixed-film bioreactor for biomethanation of salty cheese whey. Applied Biochemistry and Biotechnology 76, 193–201. Rincón, B., Raposo, F., Domínguez, J.R., Millán, F., Jiménez, A.M., Martín, A., 2006. Kinetic models of an anaerobic bioreactor for restoring wastewater generated by industrial chickpea protein production. International Biodeterioration and Biodegradation 57, 114–120. Rodgers, M., Zhan, X.M., Dolan, B., 2004. Mixing characteristics and whey wastewater treatment of a novel moving anaerobic biofilm reactor. Journal of Environmental Science and Health 39, 2183–2193. Saddoud, A., Hassairi, I., Sayadi, S., 2007. Anaerobic membrane reactor with phase separation for the treatment of cheese whey. Bioresource Technology 98, 2102– 2108. Sandhya, S., Swaminathan, K., 2006. Kinetic analysis of treatment of textile wastewater in hybrid column upflow anaerobic fixed bed reactor. Chemical Engineering Journal 122, 87–92. Shin, H.S., Han, S.K., Song, Y.C., Lee, C.Y., 2001. Performance of UASB reactor treating leachate from acidogenic fermenter in the two-phase anaerobic digestion of food waste. Water Research 35, 3441–3447. Suarez, E., Lobo, A., Alvarez, S., Riera, F.A., Alvarez, R., 2006. Partial demineralization of whey and milk ultrafiltration permeate by nanofiltration at pilot-plant scale. Desalination 198, 274–281. Timur, H., Özturk, I., 1997. Anaerobic treatment of leachate using sequencing batch reactor and hybrid bed filter. Water Science and Technology 36, 501–508. Yetilmezsoy, K., Sakar, S., 2008. Development of empirical models for performance evaluation of UASB reactors treating poultry manure wastewater under different operational conditions. Journal of Hazardous Materials 153, 532–543. Yilmaz, T., Yuceer, A., Basibuyuk, M., 2008. A comparison of the performance of mesophilic and thermophilic anaerobic filters treating papermill wastewater. Bioresource Technology 99, 156–163.
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Bioresource Technology journal homepage: www.elsevier.com/locate/biortech
Performance and kinetic evaluation of anaerobic moving bed biofilm reactor for treating milk permeate from dairy industry S. Wang a,b, N. Chandrasekhara Rao b, R. Qiu a,*, R. Moletta b,* a b
School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou 510275, China Optimisation Lab of Environmental Conception and Engineering, Polytech’ Savoie, Savoie University, Le Bourget Du Lac 73376, France
a r t i c l e
i n f o
Article history: Received 25 March 2009 Received in revised form 6 June 2009 Accepted 9 June 2009 Available online 23 July 2009 Keywords: Anaerobic moving bed biofilm reactor (AMBBR) Kinetics Mesophilic Milk permeate
a b s t r a c t High strength milk permeate derived from ultra-filtration based cheese making process was treated in an anaerobic moving bed biofilm reactor (AMBBR) under mesophilic (35 °C) condition. Total chemical oxygen demand (TCOD) removal efficiencies of 86.3–73.2% were achieved at organic loading rates (OLR) of 2.0–20.0 g TCOD L1 d1. A mass balance model gave values of methane yield coefficient (YG/S) and cell maintenance coefficient (km) of 0.341 L CH4 g1 TCODremoved and 0.1808 g TCODremoved g1 VSS d1, respectively. The maximum substrate utilization rate Umax was determined as 89.3 g TCOD L1 d1 by a modified Stover–Kincannon model. Volumetric methane production rates (VMPR) were shown to correlate with the biodegradable TCOD concentration through a Michaelis–Menten type equation. Moreover, based on VMPR and OLR removed from the reactor, the sludge production yield was determined as 0.0794 g VSS g1 TCODremoved. Ó 2009 Elsevier Ltd. All rights reserved.
1. Introduction Cheese industry produces high quantities of whey and milk permeate that represent a major disposal problem. Whey is the liquid that is separated from cheese after the coagulation of milk. It contains proteins (8.4 g L1), lactose (79 g L1), fat (<2.5 g L1) and mineral salts (5.6–8.4 g L1) (Suarez et al., 2006). Milk permeate is obtained when milk is concentrated by means of ultrafiltration process prior to cheese production. Its composition is similar to that of whey except for the negligible amount of proteins that it has. Being similar to whey, milk permeate shows a very high COD (chemical oxygen demand) value (around 55.2 g L1 in this study) due to the presence of lactose, and therefore it cannot be drained without treatment. Anaerobic treatments of dairy wastewaters (mainly whey) in various anaerobic reactors have been reported in many studies (Patel et al., 1999; Ergüder et al., 2001; Mockaitis et al., 2006; Saddoud et al., 2007). However, researchers stated that direct treatment of raw dairy wastewaters was not very reliable because of the very low bicarbonate alkalinity (2.5 g L1 as CaCO3), high COD concentration and rapid acidification tendency (Ergüder et al., 2001; Mockaitis et al., 2006). To solve this problem, a reactor which could retain more biomass for better COD degrada-
* Corresponding authors. Tel.: +86 20 8411 3454; fax: +86 20 8411 3616 (R. Qiu), tel.: +33 4 79 75 87 88 (R. Moletta). E-mail addresses: [email protected] (R. Qiu), [email protected] (R. Moletta). 0960-8524/$ - see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.biortech.2009.06.028
tion as well as provide good internal mixing to avoid reactor acidification is required. The anaerobic moving bed biofilm reactor (AMBBR) used in this study is such a reactor in which bio-carriers are employed and a submerged pump is equipped. AMBBR has been proved to be very reliable because of the high volumetric loading rates that could be applied and strong tolerance to shock loading in treating vinasse and landfill leachate (Chai and Moletta, 2007; Chen et al., 2008). However, its application in dairy wastewater treatment was rare. The only one case reported by Rodgers et al. (2004) showed that, at OLR of 11.6–15.2 g L1 d1 as well as HRT of 0.6–1.0 d, COD removal efficiency was well maintained in a range of 81–89% in the AMBBR used to treat whey wastewater at mesophilic conditions (35 ± 2 °C). It should be noted that the concentration of the whey wastewater used in that case was 9.1– 11.6 g COD L1, which were significantly lower than that of the milk permeate (around 55.2 g COD L1) to be treated in this study. Kinetic analysis is an accepted route for describing the performance of biological treatment systems and for predicting their performance (Yetilmezsoy and Sakar, 2008; Debik and Coskun, 2009). Previously reported kinetic analysis focused on a large range of reactors (anaerobic filter, hybrid column upflow anaerobic fixed bed reactor, UASB, upflow anaerobic packed bed reactor, etc.) and feeding substrates (papermill wastewater, starch wastewater, textile wastewater, saline wastewater, etc.) (Ahn and Forster, 2000; Isßik and Sponza, 2005; Kapdan, 2005; Sandhya and Swaminathan, 2006; Yilmaz et al., 2008). To describe and predict the performance of a bioprocess by determining kinetic constants, various kinetic models such as Monod first order model, Stover–Kincannon model
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and Michaelis–Menten type equation have been successfully developed and efficiently used (Kincannon and Stover, 1982; Ahn and Forster, 2000; Borja et al., 2004a,b). Despite the advantages offered by AMBBR, no kinetic analysis has been reported for substrate utilization and methane production in the bioreactor. Thus, the purpose of this research was to investigate the performance of an anaerobic moving bed biofilm reactor in treating undiluted high strength milk permeate. Kinetic analysis was also carried out to evaluate the bioreactor’s capability.
To start the experiment, the reactor was filled with 10 L seeding sludge, 18 L biofilm carriers and sufficient tap water to make up its working volume. The organic loading rate was implemented in a stepwise fashion from 2.0 to 28.0 g TCOD L1 d1, which corresponded to an HRT decrease from 27.56 to 1.97 d over a 9-month period. Kinetic analysis was carried out based on values obtained from stable performance stage, during which the average value of 4–6 consecutive analyses of each parameter amounts to less than 5% deviation in all cases.
2. Methods
2.5. Analytical techniques
2.1. Wastewater characteristics
Biogas and effluent samples were taken in duplicate and analyzed at least twice a week. Total and soluble COD values were measured by using micro method HACH (Spectrophotometer model: P/N 45600-02) and vials for COD 0–1500 ppm. pH measurements were taken twice per day with a pH meter (Model 2906, Eutech Instruments Ltd., Germany) and a pH probe (G-05992-55, Cole Parmer Instrument Co.). Volatile fatty acids (VFA), total alkalinity (TA), total solids (TS), suspended solids (SS) and volatile suspended solids (VSS) were measured by standard methods (APHA, 1995). Daily biogas production was recorded using digital gas meter (Moletta and Albagnac, 1982). Methane content in the biogas was analyzed by Shimadzu Gas-Chromatopac GC-8A equipped with a thermal conductivity detector and recorder C-R6A. N2 was used as the carrier gas and it had a flow-rate of 15 mL min1. Column temperature was 40 °C and current of the detector was 90 mA.
Detailed information of the milk permeate wastewater is presented in Table 1. Before feeding, urea and NaHCO3 was added (0.5 g L1 and 2.0 g L1, respectively) to provide nitrogen source and alkalinity buffering. Moreover, mineral solution VithaneÒ of 1.0 mL L1 from Biothane Co. was added. In addition, the pH of influent was adjusted to around 7.0 with 2.5 mol L1 NaOH solution. 2.2. Inoculum Anaerobic sludge was collected from a plant-scale UASB reactor which has been treating dairy wastewater for many years. The sludge was with pH of 7.2, total solids (TS) of 57.2 g L1, volatile solids (VS) of 49.8 g L1, suspended solids (SS) of 56.8 g L1 and volatile suspended solids (VSS) of 49.4 g L1.
3. Results and discussion 2.3. Biofilm carriers 3.1. Operational parameters and process stability Polyethylene support called Bioflow 9Ò from Raushert Co. was used as bio-carrier. One such bio-carrier (diameter 10 mm; height 8 mm; density 0.94; specific surface 530 m2 m3) consists of a small cylindrical element with small longitudinal fins that protrude on the outside surface and an internal triangle member that divides the element into three circular sectors. 2.4. Reactor configuration and operation Fig. 1 shows the schematic configuration of the reactor. The reactor of 30.0 L working volume was fabricated with polyethylene material and consisted of a tubular section of 23.8 cm internal diameter and 90.0 cm height. The system was placed in a chamber equipped with air heaters to keep the temperature of the reactor at 35 °C. Bioflow 9Ò was filled in the reactor as bio-carriers, occupying 65% of the working volume. Influent was continuously fed into the reactor bottom through the inlet by a peristaltic pump. A submerged pump (Model 1048, Eheim, Germany) with flow-rate of 480 L h1 was fixed at the bottom of the reactor to generate vertical current for inner mixing of the sludge and wastewater. Table 1 Characteristics of milk permeate wastewater. Parametera pH ORP (mv) TCOD (g L1) SCOD (g L1) TSS (g L1) TDS (g L1)
Value 5.55–6.52 +120 55.20 ± 2.26 51.18 ± 1.60 2.67 ± 0.73 10.83 ± 1.16
Parametera
TA (g L ) VFA (g L1) TN (g L1) TP (g L1) Biodegradability
Value 2.73 ± 0.24 1.82 ± 0.56 0.30–0.40 0.35–0.45 BOD/COD 0.95
a ORP, oxidation reduction potential; COD, chemical oxygen demand; TCOD, total COD; SCOD, soluble COD; TSS, total suspended solids; TDS, total dissolved solids; TA, total alkalinity; VFA, volatile fatty acids; TN, total nitrogen; TP, total phosphorous; BOD, bio-chemical oxygen demand.
Table 2 summarizes the operating results including experimental conditions and effluent parameters from the stable operation stage of the reactor. In the current research, authors used the soluble COD (SCOD) removal rate as criterion of system stability. If the SCOD removal rates were constantly stable above 90%, as well as the average value of 4–6 consecutive analyses of these rates amounted to less than 5% deviation, the reactor was considered stably working and ready for a shorter HRT. It should also be noted that, under lower loading condition (66.5 g TCOD L1 d1), OLR was increased slowly by 0.5–1.0 g L1 d1 each time to avoid any overload risk in the reactor. After this period, the reactor was subjected to faster increases (by 1.5–4.0 g L1 d1 each time) and finally reached the highest OLR of 28.0 g L1 d1. In this way, 16 runs were finished in a 9-month period. For the last four HRT settings, the duration of each HRT period was prolonged (28 d) to ensure good performance in the reactor. This strategy efficiently avoided potential impact of a previous HRT condition on current HRT condition. As seen in Table 2, with HRT decreasing to 2.76 d, the pH remained above the lower limit of optimal range (pH 6.8–7.2) for methanogenic bacteria, with 7.87 and 6.85 as extreme values. However, at lower HRTs of 2.30 and 1.97 d, the pH decreased to 6.73 and 6.63. This was probably due to the acidification of the reactor under mesophilic condition and thus, a further decrease of HRT could reinforce the acidification. The decrease of pH at lower HRTs was concomitant with the accumulation of VFA concentrations (expressed as equivalent acetic acid) in the reactor. According to Table 2, with HRT decreasing to 2.30 d, effluent VFA remained around 2 g L1, with 2.87 and 1.27 g L1 as extreme values. However, when the lowest HRT of 1.97 d was applied, effluent VFA sharply increased to a maximum value of 4.94 g L1, indicating that VFA accumulation occurred. The VFA accumulation is mainly due to the fact that the main
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Fig. 1. Schematic diagram of the lab-scale anaerobic moving bed bioflim reactor (AMBBR).
Table 2 Stable performance results obtained under various experimental conditions in AMBBR.a Run
HRTb
OLR
qCH4
TCOD
SCOD
VFA
Alkalinity
pH
VSS
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
27.56 (14) 22.05 (14) 18.38 (10) 15.75 (10) 12.25 (10) 10.02 (10) 8.48 (10) 6.89 (14) 5.80 (14) 5.01 (14) 4.24 (21) 3.68 (21) 3.24 (28) 2.76 (28) 2.30 (28) 1.97 (28)
2.0 2.5 3.0 3.5 4.5 5.5 6.5 8.0 9.5 11.0 13.0 15.0 17.0 20.0 24.0 28.0
15.00 17.71 20.70 23.57 30.11 36.34 44.62 54.46 65.37 75.32 90.73 105.17 123.03 140.44 159.40 159.90
8.61 8.21 7.55 8.32 9.31 9.84 9.04 9.84 10.32 10.43 12.24 13.15 14.80 14.73 17.57 23.23
0.98 0.86 1.03 1.05 1.14 1.33 1.34 1.39 1.59 1.73 2.31 3.17 3.29 3.64 4.66 8.17
2.42 1.30 1.98 2.40 1.27 1.61 1.93 2.04 1.95 2.74 1.87 1.80 2.09 2.33 2.87 4.94
8.08 6.90 6.61 7.65 6.91 9.41 8.98 7.80 6.50 8.39 8.77 6.48 6.28 5.38 5.10 4.94
7.72 7.87 7.74 7.60 7.55 7.74 7.70 7.41 7.30 7.27 7.24 7.14 7.27 6.85 6.73 6.63
3.61 3.65 4.05 4.83 4.64 4.46 4.09 4.26 4.79 5.22 5.25 5.44 5.71 5.43 5.52 6.83
a HRT, hydraulic retention time (d); OLR, organic loading rate (g TCOD L1 d1); qCH4 , daily methane production (L CH4 d1); TCOD, total chemical oxygen demand (g L1); SCOD, soluble chemical oxygen demand (g L1); VFA, volatile fatty acids (g equiv. acetic acid L1); Alkalinity (g equiv. CaCO3 L1); VSS, volatile suspended solids (g L1). b Values in parentheses are the corresponding duration (unit: d) of each HRT setting.
content of lactose in milk permeate is easily degraded by acidogenic bacteria, which causes acid inhibition to occur owing to the difference between acidogenic and methanogenic rates (Ergüder et al., 2001; Mockaitis et al., 2006). The impact of decreasing HRTs on VFA accumulation was reflected by the steady variability of daily methane production rate at the lowest HRT applied. As shown in Table 2, the increase of daily methane production rate (similar to that recorded at HRT of 2.30 d) stopped at HRT of 1.97 d with a value of 159.90 L CH4 d1. In general, the above-mentioned parameters showed that there is no failure of the biofilm reactor. This was due to the fact that bio-carriers were capable of retaining more attached biomass inside the reactor. Previous research conducted by Borja et al. (2004a,b) proved that a reactor with attached biomass was less affected than the control reactor by VFA accumulation at low HRTs. From Table 2, at HRTs lower than 3.24 d the alkalinity (expressed as equivalent CaCO3) decreased from above 6 to around 5 g L1. However, the buffering capacity inside the reactor was
maintained at a favorable level and contributed to the stability of the system at HRTs ranging from 27.56 d to 3.24 d. This can be attributed to carbonate/bicarbonate buffering mechanism inside the reactor. The carbonate/bicarbonate buffering is produced by the additive of NaHCO3 in the influent and the generation of CO2 that is not completely removed from the reactor as gas (Borja et al., 2004a,b). It guards against possible acidification of the reactor, given a pH optimal to that for methanogenic bacteria for the above range of HRT values. On the other hand, the VFA/alkalinity ratio can be used as a measure of process stability (Borja et al., 2004a,b): when this ratio is less than 0.3–0.4, the process is considered to be operating favorably without acidification risk. As can be observed in Fig. 2a, at HRTs of 27.56–3.24 d, the VFA/alkalinity ratio was always lower than the above-mentioned failure limit value. However, for HRTs lower than 3.24 d (period of 14, 15 and 16), a considerable increase of the VFA/alkalinity ratio was observed (from 0.43 to 1.00) as a result of considerable increase in the VFA concentrations (2.33–
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8.0
1.2
7.8
1.0 0.8
pH
7.4 pH
7.2
0.6
VFA/Alkalinity
7.0
0.4
VFA/Alkalinity
7.6
6.8 0.2
6.6 6.4
0
5
10
15
20
25
30
0.0
HRT (d)
20 y=0.9490x, R2=0.9987
-1
-1
COD removal rate (g l d )
25
15
10
y=0.7750x, R2=0.9904
5
0
3.3. Substrate balance model
TCOD SCOD
0
5
10
15
20 -1
25
and, generally, remained around 77% and 95% when the OLR increased from 2.0 g TCOD L1 d1 to 20.0 g TCOD L1 d1. However, TCOD and SCOD removal efficiencies started to decrease when OLR was raised to 24.0 g TCOD L1 d1 and achieved minimum values of 57.9% and 84.1% at OLR of 28.0 g TCOD L1 d1. Fig. 2b illustrates the TCOD and SCOD removal rates (expressed as the removals of TCOD and SCOD L1 d1) as a function of COD loading rate. Here, TCOD removal rate is a function of OLR (TCOD loading rate), and SCOD removal rate is a function of SCOD loading rate. As it could be found, the rates of TCOD and SCOD removal increased linearly over OLR of 2.0–20.0 g TCOD L1 d1. The slopes of the regression lines of 0.775 for TCOD and 0.949 for SCOD could be obtained. Thus, the overall TCOD and SCOD removal efficiency are 77.5% and 94.9%, respectively, over OLR of 2.0–20.0 g TCOD L1 d1. Previous studies found out that VFA accumulation is easy to occur and thus makes the anaerobic treatment unsteady if undiluted whey is directly fed into the reactor (Malaspina et al., 1996; Ergüder et al., 2001; Mockaitis et al., 2006). However, Ergüder et al. (2001) reported a good treatability of undiluted whey (42.7– 55.1 g COD L1) by UASB at OLR of 22.6–24.6 g COD L1 d1 as well as HRT of 2.1–5.0 d. The COD removal efficiency in their research was steady at 95–97%. This was comparable to the SCOD removal efficiency (94.9%) obtained in our current study.
30
-1
COD loading rate (g l d ) Fig. 2. Variations of operational parameters: (a) VFA/alkalinity ratios (equiv. acetic acid/equiv. CaCO3) and pH values over various HRTs; (b) TCOD and SCOD removal rates against TCOD loading rate (OLR) and SCOD loading rate, respectively.
A substrate balance model examining the TCOD balance of the reactor was conducted based on the following two hypotheses (Borja et al., 2002): (1) the anaerobic reactor is operated under steady state for all the OLRs applied; and (2) the suspended solids in the feeding are readily biodegradable and the volatile suspended solids in the effluent are the only source of the biomass generated. Thus, a reactor COD balance is obtained in the following equation (Borja et al., 2004a,b):
ðTCODÞi ¼ ðSCODÞe þ ðTCODÞbiogas þ ðTCODVSS Þe þ ðTCODÞm ; 4.94 g L1) as well as accompanying decrease in alkalinity (5.38– 4.94 g L1). This increase of the VFA/alkalinity ratio with a decreasing HRT was accompanied by a decrease of pH, which achieved the minimum pH values of 6.63 at HRT of 1.97 d. During the last three runs (period of 14, 15 and 16), the methanogenic bacteria were believed to be affected by the high level VFA/alkalinity ratios (Fig. 2a) since the increases of methane productions were in slower paces and almost stopped in the period of 16 (Table 2). When methane production was divided by total amount of influent TCOD, ratios of methane to substrate (CH4/ TCOD) were found to decrease for period of 14, 15 and 16 in the following order: 0.23, 0.22 and 0.19 L CH4 g1 TCOD. All of these values were smaller than the CH4/TCOD ratio of 0.24 L CH4 g1 TCOD found for period of 13 (VFA/alkalinity = 0.33). Therefore, when VFA/alkalinity ratios were at high level (exceeded the limit of 0.4), methane productions were proved to be inhibited. 3.2. Process efficiency From Tables 1 and 2, the variation of TCOD and SCOD removal efficiencies at respective HRT or OLR could be calculated. TCOD and SCOD removal efficiencies decreased slightly from 86.3% to 81.1% and from 98.3% to 96.6% upon an HRT decrease from 27.56 to 5.01 d. However, for HRTs of and lower than 4.24 d, both TCOD and SCOD removal efficiencies decreased more rapidly from 77.8% to 57.9% and from 95.7% to 84.1%. As such, it could be concluded that the decrease of TCOD removal efficiency with decreasing HRT was more pronounced and fluctuating. On the other hand, both of TCOD and SCOD removal efficiencies decreased slightly
ð1Þ
where (TCOD)i is the influent TCOD, (SCOD)e is the effluent SCOD, (TCOD)biogas is the fraction of (TCOD)i converted into biogas, (TCODVSS)e is the fraction of (TCOD)i converted into biomass and (TCOD)m is the fraction of (TCOD)i consumed for cell maintenance. Eq. (1) can be transformed into the following equation:
qSTi ¼ qSSe þ qCH4 Y S=G þ qðSTe SSe Þ þ km XV;
ð2Þ
where q is the flow-rate (L d1), STi is the influent TCOD concentration (g TCOD L1), STe is the effluent TCOD concentration (g TCOD L1), SSe is the effluent SCOD concentration (g SCOD L1), qCH4 is the daily methane production (L CH4 d1), YS/G is the conversion coefficient of substrate into methane (g TCODremoved L1 CH4), km is the coefficient for cell maintenance (g TCODremoved g1 VSS d1), X is the biomass concentration in the reactor (g VSS L1) and V is the working volume of the reactor (L). Herein, experimental results of all the parameters, except X, are listed in Table 2. In the table, effluent biomass concentrations are given as VSS. However, these values should be adjusted so as to reflect the corresponding total biomass concentrations in the reactor at each OLR level. According to Chai and Moletta (2007), suspended biomass generally occupied 16.6% of the total biomass. Thus, the effluent VSS values in this study should be divided by 0.166 to give values to X. From Eq. (2) the following equation can be obtained:
qðSTi STe Þ ¼ qCH4 Y S=G þ km XV:
ð3Þ
By grouping terms and dividing by the product between the reactor volume V and the biomass concentration X, the following equations can be obtained:
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ðSTi STe Þ=ðHRTÞX ¼ Y S=G ðqCH4 =XVÞ þ km ;
ð4Þ
km ¼ ððSTi STe Þ=HRT Y S=G qCH4 =VÞ=X:
ð5Þ
According to Eq. (4), if the quotient (STi STe)/(HRT)X is plotted against the quotient qCH4 =XV, YS/G is the slope and km is the intercept point of a straight line. As illustrated in Fig. 3, the points fit as a straight line with a small intercept for the reactor and the regression coefficient is 0.99, which strongly supports the validity of the model. From the figure, the values of YG/S, calculated as the inverse of YS/G, and km were obtained. YG/S or methane yield coefficient was found to be 0.341 L CH4 g1 TCODremoved for the reactor. This value was similar to those obtained in the anaerobic digestion process of wastewaters coming from cheese making process (Ergüder et al., 2001). It was also coincident with other methane yield coefficient values reported in the literatures for anaerobic treatments of other food industry wastewaters (Borja et al., 2004a,b). On the other hand, the km value obtained in the reactor was 0.0300 g TCODremoved g1 VSS d1, being comparable to the value of 0.0057 g TCODremoved g1 VSS d1 reported by Rincón et al. (2006). This demonstrates that the maintenance energy needed in AMBBR is of a higher order of magnitude. According to Eq. (5), the high value of km might be ascribed to low value of X, the biomass concentration in the reactor, that was indirectly estimated based on the effluent VSS and previous research result. However, this is practically negligible since it represents a quite small fraction of TCODremoved in any OLR assay. Therefore, it could be concluded that the initial raw substrate is basically consumed in anaerobic methane production and biomass generation processes. 3.4. Maximum substrate utilization rate (Stover–Kincannon model) The Stover–Kincannon model was first proposed for a rotary biological contactor by Kincannon and Stover (1982). The original model assumed that the suspended biomass was negligible in comparison to the attached biomass on the media and thus, the disc surface area of the rotary biological contactor was used to represent the total attached-growth active biomass concentration. However, this cannot be applied to other bioreactors that do not have disc configurations. Ahn and Forster (2000) stated that suspended biomass within the interstitial void spaces of the support media is a significant factor in producing high and stable removal efficiency and therefore, proposed that the volume of the reactor can be used instead of the surface area. Therefore, at steady state, the Stover– Kincannon model would have the form as shown in Eq. (6). Here, the AMBBR was also assumed to operate under steady state for all the OLRs applied.
dS U max ðqSTi =VÞ ¼ : dt K B þ ðqSTi =VÞ This can be linearized as:
1 dS KB V 1 ¼ V=qðSTi STe Þ ¼ : þ dt U max U max qSTi
HRT=ðSTi STe Þ ¼
KB 1 1 þ ; U max U max OLR
ð8Þ
where V is the reactor working volume (L), q is the flow-rate (L d1), STi is the influent TCOD concentration (g TCOD L1), STe is the effluent TCOD concentration (g TCOD L1), KB is a rate constant (g L1 d1), Umax is maximum substrate utilization rate constant (g L1 d1), HRT is the hydraulic retention time (d) and OLR is the organic loading rate (g TCOD L1 d1). Since dS/dt approaches Umax as the organic loading rate qSTi/V approaches infinity in Eq. (7), Umax can be referred as the maximum substrate utilization rate constant. According to Eq. (8), if HRT/(STi STe) is plotted against 1/OLR, KB/Umax is the slope and 1/Umax is the intercept point of a straight line. As plotted in Fig. 4, the points fit a straight line with a small intercept; the regression coefficient (0.99) strongly supports the validity of the linearized Stover–Kincannon model. Thus, it could be concluded that the modified Stover–Kincannon model is capable in describing the performance of mesophilic AMBBR treating milk permeate wastewater in this study. Fig. 4 also predicts values for Umax and KB (89.3 and 102.3 g TCOD L1 d1, respectively) for the reactor. Compared with the maximum OLR of 28.0 g TCOD L1 d1 obtained in this study, the predicted Umax is significantly higher. This indicates that the AMBBR possessed much higher potential in coping with high strength milk permeate. A comparison of the values of Umax and KB obtained by the same modified Stover–Kincannon model for various substrates is shown in Table 3 for mesophilic digesters. As seen in Table 3, the highest values of Umax and KB were obtained for papermill wastewater followed by milk permeate wastewater. A comparison of the values in Table 3 shows that Umax and KB obtained from current work are similar to those obtained with starch based substrate, but significantly higher than those obtained from simulated paper and corrugated papermill wastewaters. The results reported by Ahn and Forster (2000) showed that, in a mesophilic anaerobic filter treating simulated starch wastewater, there was also marked difference between the maximum OLR (17.2 g SCOD L1 d1) and the Umax (49.8 g SCOD L1 d1) predicted by the modified Stover–Kincannon model. The authors stated that this was due to an appreciable
0.8
HRT/(S Ti-STe ) (l d g TCOD)
0.5 0.4
0.6
y=1.1457x+0.0112, R2=0.9993
-1
(ST0-STe)/(HRT)X
ð7Þ
By grouping terms, Eq. (7) has the form:
0.6
0.3 0.2
y=2.9367x+0.0300, R2=0.9902
0.1 0.0 0.00
ð6Þ
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
0.18
qCH4/VX Fig. 3. Variation of the quotient of (STi STe)/(HRT)X as a function of the quotient of qCH4 =ðVXÞ.
0.4
0.2
0.0 0.0
0.1
0.2
0.3
0.4
0.5
0.6
1/OLR (l d g-1 TCOD) Fig. 4. Scatter plot of HRT/(STi STe) against 1/OLR for the determination of maximum substrate utilization rate.
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Table 3 Comparison of the kinetic parameters obtained for various substrates and digesters. Substrate source
Type of reactor
Umax (g L1 d1)
KB (g L1 d1)
R2
References
Milk permeate Papermill wastewater Simulated starch wastewater Textile wastewater Simulated textile wastewater Synthetic saline wastewater
AMBBR Anaerobic filter Anaerobic filter Hybrid column upflow anaerobic fixed bed reactor Upflow anaerobic sludge blanket reactor Upflow anaerobic packed bed reactor
89.3 86.21 49.8 31.69 7.5 5.3
102.3 104.15 50.6 45.37 8.2 7.05
0.99 0.99 0.99 0.99 0.99 0.91
This study Yilmaz et al. (2008) Ahn and Forster (2000) Sandhya and Swaminathan (2006) Isßik and Sponza (2005) Kapdan (2005)
deterioration in performance which occurred at the highest OLR. Similarly, such situation also existed in the AMBBR in this study and has been proved by the operational parameters (see Table 2).
18
-1
VMPR (g CH4-TCOD l d )
16
According to Table 2, the volumetric methane production rates (rCH4 ) can be obtained through the expression:
r CH4 ¼ qCH4 =V;
ð9Þ
where qCH4 is the daily methane production (L CH4 d1) and V is the reactor working volume (L). In Eqs. (2)–(5), S denotes the concentration of substrate; however, the experimental method used to determine the substrate concentration (TCOD and SCOD analysis) does not distinguish between biodegradable and non-biodegradable substrate. The experimental values of TCOD given in Table 2 must be corrected by subtracting the fraction of non-biodegradable substrate. According to the method used in Martín et al. (1993), the amount of non-biodegradable substrate could be estimated by plotting ln(TCOD) as a function of 1/(HRT) based on the values listed in Table 2. By the least-squares fitting, an intercept of 7.4 g TCOD L1 (regression coefficient 0.97) was calculated, which corresponds to an infinite HRT. Thus, this can be assumed to be the concentration of non-biodegradable substrate (Martín et al., 1993; Rincón et al., 2006). The observed values of rCH4 plotted as a function of the biodegradable TCOD concentrations (TCODb) are illustrated in Fig. 5. As it can be seen, the observed rCH4 values fit a Michaelis–Menten type kinetic model, which is a hyperbolic function. By using the software SigmaPlot V10.0, the following kinetic equation was obtained:
r CH4 ¼ 9:31TCODb =ð10:91 þ TCODb Þ:
ð10Þ
From Eq. (10) the theoretical r CH4 values could be determined for the reactor used in this study. When the theoretical rCH4 values are plotted against those observed ones, a linear regression line
-1
-1
rCH4 (l CH4 l d )
6
4
y=9.3091x/(10.9064+x), R2=0.9457
2
0
0
2
4
6
8
10
12
14
16
14
-1
3.5. Kinetics of methane production (Michaelis–Menten model)
18
Effluent TCODb (g l-1) Fig. 5. Variation of the volumetric methane production rates ðr CH4 Þ as a function of the biodegradable TCOD (TCODb) concentration in the effluent.
y=0.8881x, R2=0.9878
12 10 8 6 4 2 0
0
2
4
6
8
10
12
14
16
18
OLR removed (g TCOD l-1 d-1) Fig. 6. Volumetric methane production rate (VMPR) as a function of TCODremoved. The slope of the fitted line is the proportional fraction of TCODremoved converted into methane.
with a slope of 0.93 and a regression coefficient of 0.94 were obtained. This suggests that the proposed model is capable of accurately predicting the behavior of the AMBBR for the milk permeate in this study. 3.6. Sludge yield coefficient The production of methane is related to the COD reduction and the remaining portion of the reduced COD is considered as synthesis of biomass (Chen et al., 2008). These can allow us to estimate the sludge yield in anaerobic digestions (Fang et al., 1995; Kwong and Fang, 1996; Timur and Özturk, 1997). Generally, the volume of 1 g methane is 1.4 L at STP (standard temperature and pressure) and is equivalent to 4 g COD. Therefore, the volumetric methane production rate (VMPR) could be calculated from the produced methane volume over the reactor volume and HRT. Fig. 6 shows that the VMPR increases with the TCODremoved at a rate of 0.888 g CH4-TCOD g1 TCODremoved. As an average, 88.8% of the TCODremoved is converted to methane, and the remaining 11.2% is presumably converted to biomass. The COD equivalence of the biomass in reactors is 1.41 g COD g1 VSS (Shin et al., 2001). Consequently, the sludge yield is estimated to be 0.0794 g VSS g1 TCODremoved, which is of the same order of magnitude as those results of 0.050–0.057 g VSS g1 COD removed reported by other researchers based on the same method (Chen et al., 2008; Chui et al., 1994; Shin et al., 2001). However, the calculated sludge yield indicates that a bigger fraction of TCODremoved is required for biomass syntheses in AMMBR digestion of milk permeate under the mesophilic condition in this study. 4. Conclusions The results of this study demonstrate that high strength milk permeate wastewater was easily biodegradable in anaerobic
S. Wang et al. / Bioresource Technology 100 (2009) 5641–5647
moving bed biofilm reactor. The theoretical rates based on kinetic models agreed well with experimental values. The average methane yield coefficient YG/S obtained by a mass balance was 0.341 L CH4 g1 TCODremoved. The maximum substrate utilization rate Umax predicted by Stover–Kincannon was 89.3 g TCOD L1 d1, indicating a potentially higher capacity of the AMBBR. Michaelis–Menten model predicted the methane production quite well with a regression coefficient of 0.94. These confirm that the kinetic models are capable of describing the reactor’s bio-kinetic behavior. Acknowledgements This study was supported by a scholarship funded by the French Ministry of Foreign Affairs (Grant No. 20051725). Financial supports from Guangdong Provincial Natural Science Foundation in Universities (No. 06Z001) and New Century Excellent Talents Program from Ministry of Education of China (No. NCET04-0790) are also sincerely acknowledged. The authors are grateful to Region Rhône Alpes, France for the financial support in EMERGENCE program. References Ahn, J.H., Forster, C.F., 2000. Kinetic analyses of the operation of mesophilic and thermophilic anaerobic filters treating a simulated starch wastewater. Process Biochemistry 36, 19–23. APHA (American Public Health Association), 1995. Standard Methods for the Examination of Water and Wastewater. 19th ed. APHA, Washington, DC. Borja, R., González, E., Raposo, F., Millán, F., Martín, A., 2002. Kinetic analysis of the psychrophilic anaerobic digestion of wastewater derived from the production of proteins from extracted sunflower flour. Journal of Agricultural and Food Chemistry 50, 4628–4633. Borja, R., Rincón, B., Raposo, F., Dominguez, J.R., Millan, F., Martín, A., 2004a. Mesophilic anaerobic digestion in a fluidised-bed reactor of wastewater from the production of protein isolates from chickpea flour. Process Biochemistry 39, 1913–1921. Borja, R., Rincón, B., Raposo, F., Sanchez, E., Martín, A., 2004. Assessment of kinetic parameters for the mesophilic anaerobic biodegradation of two-phase olive pomace. International Biodeterioration and Biodegradation 53, 71–78. Chai, S.L., Moletta, R., 2007. Anaerobic treatment of vinasses by a sequentially mixed moving bed biofilm reactor. Water Science and Technology 56, 1–7. Chen, S., Sun, D., Chung, J.S., 2008. Simultaneous removal of COD and ammonium from landfill leachate using an anaerobic–aerobic moving-bed biofilm reactor system. Waste Management 28, 339–346. Chui, H.K., Fang, H.H.P., Li, Y.Y., 1994. Removal of formate from wastewater by anaerobic process. Journal of Environmental Engineering 120, 1308–1320. Debik, E., Coskun, T., 2009. Use of the Static Granular Bed Reactor (SGBR) with anaerobic sludge to treat poultry slaughterhouse wastewater and kinetic modeling. Bioresource Technology 100, 2777–2782. Ergüder, T.H., Tezel, U., Güven, E., Demirer, G.N., 2001. Anaerobic biotransformation and methane generation potential of cheese whey in batch and UASB reactors. Waste Management 21, 643–650.
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