Article pubs.acs.org/EF
Antagonistic Effects on the Methane Yield of Liquid Hot-Water Pretreated Press Mud Fractions Co-digested with Vinasse Lisbet Mailin López González,*,† Ileana Pereda Reyes,‡ Osvaldo Romero Romero,† Jörn Budde,§ Monika Heiermann,§ and Han Vervaeren∥ †
Centro de Estudios de Energía y Procesos Industriales (CEEPI), Universidad de Sancti Spíritus “José Martí Pérez” (UNISS), Avenida de los Mártires 360, 60100 Sancti Spíritus, Cuba ‡ Centro de Estudio de Ingeniería de Procesos (CIPRO), Instituto Superior Politécnico “José Antonio Echeverría” (Cujae), Calle 114, No. 11901 e/Rotonda y Ciclovía, Marianao, 19390 La Habana, Cuba § Leibniz Institute for Agricultural Engineering Potsdam-Bornim, Max-Eyth-Allee 100, 14469 Potsdam, Germany ∥ Laboratory of Industrial Water and Eco-technology (LIWET), Faculty of Bioscience Engineering, Ghent University Campus Kortrijk, Graaf Karel de Goedelaan 5, B-8500 Kortrijk, Belgium ABSTRACT: Sugar cane press mud pretreated by liquid hot water was separated into a liquid fraction and a solid fraction. These fractions were blended with vinasse in different proportions, according to a three-factor mixture design, to evaluate their synergetic and antagonistic effects on the methane yield. The biochemical methane potential was determined in batch assays under mesophilic conditions (37 ± 1 °C). The highest methane production rates were obtained for a mixture of 33% chemical oxygen demand (COD) vinasse and 67% COD liquid fraction of press mud and for sheer vinasse (73 and 84 N mL CH4 g−1 CODfed day−1). The maximum methane yield was found for the pure liquid fraction with a value of 369 N mL CH4 g−1 CODfed. For most mixtures examined, antagonistic effects were found, with significant differences when mixing vinasse and the liquid fraction. solids press mud);9 and for the UASB reactor, press mud was soaked for 4 h with water or sewage at ratios of 1:7.5, 1:10, and 1:12.5 and the filtrate was used in the feeding.10 Doing so, only a low organic fraction from the raw press mud was used. On the other hand, thermal pretreatment application increases the solubilization of organic matter with positive impact on the performance of the anaerobic digestion process. Previous studies demonstrated that thermal pretreatment of sugar cane press mud improves the biodegradability of this substrate.2 Similar results were obtained in the organic matter solubilization of pig and cattle manure and sunflower oil cake.11−13 Thermal pretreatment leads to a distinct separation of solids and liquids. Thus, two different fractions were obtained: a liquid and a solid. A separated anaerobic digestion of the two fractions is accompanied by significant differences in the kinetics of the hydrolytic/acidogenic and methanogenic stages.12,14,15 These results are still not investigated in the case of thermally pretreated sugar cane press mud. Focusing on overall efficiency, it is important to characterize these fractions because they might require different process regimes in anaerobic digestion or even point out which conversion strategies should be considered. Being a liquid residue obtained after the ethanol fermentation and removal of ethanol from molasses, V is also a byproduct of sugar cane processing. Its co-digestion with press mud should be considered for CSTR, PF reactor, or UASB reactor. V is generated in volumes between 9 and 14 L for each liter of ethanol
1. INTRODUCTION Sugar-distillery complexes, integrating the production of cane sugar and ethanol, constitute one of the key industries that generate large quantities and high-strength streams. Among them, vinasse (V) and press mud are considered the main residues generated, whose current management practices may cause serious environmental problems.1 Sugar cane press mud is a semi-solid material containing fiber, crude protein, sugar, wax, fat, and ash.2,3 It arises in large quantities (30−40 kg ton−1 of crushed cane) containing a considerable amount of organic matter [157 g kg−1 as chemical oxygen demand (COD)]4 as well as micronutrients, such as nitrogen, phosphorus, potassium, calcium, iron, magnesium, manganese, and zinc.3,5 In sugar-producing countries, it is a general practice to spread press mud on the field as fertilizer, either as raw material or after composting. The high temperature of the residue (65 °C), the long period of natural decomposition,6 the nitrogen immobilization, and the phytotoxicity7 are disadvantages when applied as raw material. According to the characteristics mentioned, press mud is a potential source for anaerobic digestion. Previous studies were focused on biogas8,9 and biohydrogen production.10 As a semisolid material (20−27% total solids on fresh matter), press mud cannot be fermented unless water or some liquid waste is added. Digestions were carried out in a continuous stirred tank reactor (CSTR), a plug flow (PF) reactor, and an upflow anaerobic sludge blanket (UASB) reactor, according to the solids fed. The CSTR was tested using a press mud/water ratio of 1:4;8 the PF reactor was fed with sugar production wastewater as a cosubstrate at a ratio of 15.6:1 (grams of wastewater/grams of total © XXXX American Chemical Society
Received: June 18, 2015 Revised: October 11, 2015
A
DOI: 10.1021/acs.energyfuels.5b01369 Energy Fuels XXXX, XXX, XXX−XXX
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Energy & Fuels obtained.1,16 It is characterized by a pH between 3.5 and 5, a dark brown color, and a COD ranging between 50 and 150 g L−1.16 Because of its high nutrient and organic matter contents, V is used for irrigation and fertilization.1 Nevertheless, the permanent application of high volumes of V on soil leads to excessive nitrogen and potassium concentrations, because they are the main chemical components of this residue.16,17 The anaerobic treatment of V prior to its disposal in the environment offers an alternative to the current practices and could simultaneously increase the digestibility of press mud. In this study, press mud fractions (liquid and/or solid) as obtained by liquid hot-water (LHW) pretreatment were tested for methane yield and combined effects (synergetic, antagonistic, or neutral) in co-digestion with V, using a simplex lattice mixture design. Therefore, it was screened if the co-digestion of two major byproducts from sugar cane processing could be a novel process route for the industry.
Table 1. Mixture Compositions for the Experimental Setups Investigated during Batch Co-digestion Sets
2. MATERIALS AND METHODS
Assuming that the measured response was dependent upon the relative proportions of the components in the mixture, linear to cubic models were used for the analysis of the design.18 All four models (linear, quadratic, full cubic, and special cubic) were fitted to the response variable by regression analysis with analysis of variance (ANOVA). The significance of the regression models was evaluated at a 5% significance level (p values ≤ 0.05), and pooled standard deviations were used to assess the size of experimental errors. The hypothesis that the selected model is adequate to describe the experimental data (p values ≥ 0.05) was verified by the lack-of-fit test. MINITAB Release 14.12.0 software package was used for analyzing the results. 2.4. Analytical Methods. COD, DM, ODM, and pH were determined according to standard methods.19 The COD analysis was carried out by standard closed reflux, colorimetric method 5220 D.19 Volatile fatty acids (VFAs) (acetic acid, propionic acid, butyric acid, valeric acid, and isovaleric acid) were determined by gas chromatography (GC) applying a previously published method.5 Total nitrogen (TN) was determined by the Kjeldahl method. Proteins were calculated from the TN content, using a conversion factor of 6.25. Gallic acid, hydroxymethylfurfural (HMF), furfural, vanillic acid, syringic acid, p-coumaric acid, and ferulic acid were analyzed by highperformance liquid chromatography (HPLC) Agilent 1100 Series, equipped with a diode array detector Agilent 1200 Series. The analysis was performed with an Inertsil ODS column, an injection volume of 5 μL, and a flow rate of 1 mL/min in a gradient run using 1% (v/v) acetic acid in distilled water and 1% (v/v) acetic acid in methanol as the mobile phase. The biogas composition was analyzed using GC (Agilent 6890, Germany) equipped with a thermal conductivity detector (TCD) and PoraBond Q capillary column (25 m length × 530 μm internal diameter × 0.70 μm particle size), with split/splitless inlet in split mode at 280 °C. Helium was the carrier gas at a constant flow of 39.8 mL min−1 and a split ratio = 10:1. Oven initial temperature was 60 °C, with a T ramp of 110 °C/min to 280 °C and held for 2 min. Detector T = 250 °C. 2.5. Anaerobic Digestion: Biochemical Methane Potential Test. Anaerobic digestion experiments for determining methane potentials were carried out in accordance with VDI 4630.20 The temperature was set to 37.5 °C. Schott bottles (500 mL) with four port lids were used as reactors. Each reactor received an appropriate amount of mixture and 200 g of inoculum, keeping a CODsubstrate/VSinoculum ratio of 0.5. One of the ports was connected to a graduated cylinder filled with acidified water at pH 2, to measure the cumulative biogas production by liquid displacement. From a second lid port with a septum, headspace gas samples from each bottle were collected (5 mL pressure-tight syringe) and analyzed by GC. The digestate collected from an anaerobic digestion plant (Inagro vzw, Belgium) fed with swine manure and maize silage was used as inoculum after 1 week of degassing. The inoculum applied contained 6.0% DM with 65.9% ODM on a dry matter basis. The VFA/alkalinity
mixing ratiosa
tb cb + t b
(1)
rs(t ) = ymax
bc bt b − 1 (c b + t b)2
(2)
y(t ) = ymax (1 − e−kt )
mixtures
substrate (g)
V
LF
SF
V LF SF V67/LF0/SF33 V67/LF33/SF0 V33/LF0/SF67 V33/LF67/SF0 V33/LF33/SF33 V0/LF67/SF33 V0/LF33/SF67
67.8 87.9 19.4 51.7 74.6 35.5 81.2 58.4 42.2 65.1
100 0 0 66.6 66.6 33.3 33.3 33.3 0 0
0 100 0 0 33.3 0 66.6 33.3 66.6 33.3
0 0 100 33.3 0 66.6 0 33.3 33.3 66.6
a
Expressed as the COD proportion for each component added in the mixture. bAmount of individual substrate mixture added in each batch.
2.1. Materials. Fresh press mud and V were provided from “Melanio Hernández” Sugar Mill (Sancti Spiritus, Cuba) during the 2013 harvest. Press mud was air-dried and stored in plastic bags at 4 °C until use. Dry press mud contained 90.5 and 72.2% of dry matter (DM) and organic dry matter (ODM), respectively. V (5.6% of DM and 4.1% of ODM, on fresh matter) was collected, cooled, and kept at −20 °C. 2.2. Pretreatment Conditions. The LHW pretreatment assay on press mud was conducted in a 600 mL mini reactor system, model number 4568 (Parr Instruments, Moline, IL).13 The best experimental conditions for press mud pretreatment by LHW (150 °C and 20 min) were determined in a previous study2 and used in the current work. A press mud sample of 100 g was mixed with 500 g of deionized water with a liquid/solid ratio of 5.5. An amount of 450 g of the mixture was fed to the reactor, heated to 150 °C, and kept at that temperature for 20 min under constant agitation at a stirring speed of 350 rpm. After completing the pretreatment time, the heater was removed and the reactor was cooled to less than 50 °C by immersing it into room-temperature water. The pretreated press mud slurry was taken out of the reactor and stored in containers at 4 °C. The assays were carried out in duplicate. Afterward, pretreated slurries were separated in their respective fractions, liquid fraction (LF) and solid fraction (SF), by centrifugation at 6000 rpm for 30 min. Resulting fractions and V were used in the preparation of different mixtures according to a simplex-lattice design explained in section 2.3. 2.3. Mixture Design. A simplex-lattice design was employed for the present study. The design consists of pure components and mixtures of two and three components according to Table 1. The basis used for the design was the COD fraction contributed by each component to the mixture. The designed experiments were replicated 3 times. The response variables were maximum methane yield ymax (N mL CH4 g−1 CODfed) and the methane production rate rs(t) (N mL CH4 g−1 CODfed day−1), determined by fitting the experimental data to the Hill model (eqs 1 and 2, respectively). The kinetic parameter k was estimated by the Roediger model (eq 3)
y(t ) = ymax
b
(3) −1
where y(t) is the cumulative methane yield (N mL CH4 g CODfed), ymax is the maximum methane yield (N mL CH4 g−1 CODfed), rs(t) is the methane production rate (N mL CH4 g−1 CODfed day−1), k is the kinetic constant (day−1), b and c are equation coefficients, and t is the time in days. B
DOI: 10.1021/acs.energyfuels.5b01369 Energy Fuels XXXX, XXX, XXX−XXX
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Energy & Fuels Table 2. Chemical Composition of LF and SF from Pretreated Sugarcane Press Mud and V
a
component
units
LF
SF
V
COD TN pH DM ODM acetic acid furfural HMF gallic acid vanillic acid syringic acid p-coumaric acid ferulic acid Ca K Mg Mn Na Zn
g kg−1 g kg−1
52.6 ± 0.8 0.03 ± 0.0 4.9 ± 0.05 3.0 ± 0.0 80.0 ± 0.0 576.7 ± 11.1 8.6 ± 0.4 56.6 ± 6.9 10.7 ± 2.8 3.9 ± 0.4 4.8 ± 0.1 52.6 ± 0.8 3.8 ± 0.4 4.1 ± 0.06 1.4 ± 0.01 0.7 ± 0.00 NDb 0.35 ± 0.00 ND
204.1 ± 0.9 15.5 ± 0.0 5.2 ± 0.06 20.7 ± 0.2 79.8 ± 0.6 NAa NA NA NA NA NA NA NA 3.4 ± 0.02 0.4 ± 0.00 0.4 ± 0.00 0.1 ± 0.00 0.23 ± 0.00 0.03 ± 0.00
58.3 ± 0.4 0.6 ± 0.0 3.9 ± 0.02 5.6 ± 0.0 73.5 ± 0.1 2805.1 ± 0.4 4.2 ± 0.1 5.4 ± 0.1 17.3 ± 0.2 30.9 ± 0.3 32.4 ± 0.2 2.6 ± 0.2 6.3 ± 0.3 3.3 ± 0.01 7.4 ± 0.04 0.9 ± 0.00 ND 0.22 ± 0.00 ND
% FM % DM mg L−1 mg L−1 mg L−1 mg L−1 mg L−1 mg L−1 mg L−1 mg L−1 % DM % DM % DM % DM % DM % DM
NA = not analyzed. bND = not detected.
ratio was 0.27. A total of 11 batch assays, including the inoculum (blank reactor), were performed in triplicate. Each trial was conducted for 30 days. Reactors were shaken manually once a day. The gas pressure was calculated according to the liquid column height and subtracted from the atmospheric pressure before standardization (273 K and 101.29 kPa). Methane yields are given in N mL CH4 g−1 CODfed.
Table 3. ANOVA for the Linear, Quadratic, Special Cubic, and Full Cubic Models response variable
sum of squared
standard error
degree of freedom
R2 (%)
Radj2 (%)
34.17
29.30
0.00 0.00
87.58
84.99
0.00 0.00
89.73
88.09
0.00 0.00
95.60
94.68
0.00 0.29
p value
Linear
3. RESULTS AND DISCUSSION 3.1. Characterization of Substrates. All of the substrate components were analyzed for DM, ODM, pH, VFA, TN, COD, furans, and phenolic compounds (Table 2). The DM content for the mixture components varied between 3.0 and 20.7% for the LF and SF, respectively. Dependent upon their composition, the DM content of mixtures ranged between 3.7% (V33/LF67/SF0) and 11.1% (V33/LF0/SF67). Highest proportions of fiber (mainly lignin and cellulose), proteins (96.8 g kg−1), and lipids (waxes and fats) were contained in the SF, according to the remaining fraction after pretreatment and soluble fraction separation. Those components can result in a slower methane production and a lower hydrolysis rate.21,22 The pH was between 3.9 and 5.2 for all of the mixtures, but after adding the inoculum, it was between 7.3 and 7.6 before digestion. These values were within the operational range between 6.5 and 8.5 previously reported for optimal anaerobic digestion conditions.23 The total nitrogen content in the SF was higher (15.5 g kg−1) in comparison to V and LF and similar to that contained in the raw press mud.2 The content of phenolic acids was below the inhibitory values for anaerobic digestion.24 However, higher values have been reported for V.25 The metal composition in the mixtures, according to their content in the feedstock, is given mainly by Ca > K > Mg > Na. 3.2. Model Fitting and Regression Analysis. The ANOVA results of the four models are presented in Table 3. Standard error of regression was calculated as a measure of model fitting regression and ANOVA. The linear model is statistically significant (p < 0.05) but with a low Radj2 (0.29) and a high lack of fit, indicating a poor prediction. The addition of two- and three-component interactions for the quadratic and cubic models significantly improves the fit. The
regression lack of fit pure error
22831 41654 2324
regression lack of fit pure error
35680 5974 2324
regression lack of fit pure error
2336 4538 2324
regression lack of fit pure error
3920 617 2324
40
2 7 20 Quadratic 18 3 4 20 Special Cubic 16 1 5 20 Full Cubic 11 1 4 20
analysis of the Radj2 values reveals that both cubic and quadratic models have high fits (Radj2 > 0.85). It means that pure components and binary mixtures explain a minimum of about 85% of the variability in the response, while another 3% is explained by introducing a ternary interaction term, and 12% of the remaining variability is unexplained. After application of the criteria of minimum standard error for regression and high Radj2, the full cubic model was found to be superior according to a p value higher than 0.05 (0.29) in the lack-of-fit test and a maximum Radj2 = 0.95, leaving only 5% of the variability unexplained. According to the significance of each coefficient determined by p values for the full cubic model, all pure components contribute positively to the methane yield (Table 4). The pure component LF has the highest positive coefficient of 369, indicating the largest influence on the methane yield. The quadratic terms of the full cubic model show an antagonistic effect for all mixtures. This effect is highly significant C
DOI: 10.1021/acs.energyfuels.5b01369 Energy Fuels XXXX, XXX, XXX−XXX
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Energy & Fuels
are comparable concerning their methane yields (Table 5). When V is not present, biodegradability is increased from SF to LF. Therefore, the optimal value for the methane yield is obtained for the pure component LF, with 370.7 N mL CH4 g−1 CODfed. 3.3. Mixture Effects on the Methane Yield and Methane Production Rate. Table 5 summarizes the predicted methane yield as well as the experimental values obtained in terms of ymax. The ymax value varies from 249 N mL CH4 g−1 CODfed (SF) to 369 N mL CH4 g−1 CODfed (LF) for pure components. The methane yield obtained for the LF in batch anaerobic digestion tests is slightly higher than the theoretical value of 350 N mL CH4 g−1 CODfed, which could be due to the so-called autolysis of the sludge. Some microorganisms could have died because of the feast−famine regime (batch regime), the presence of toxic intermediates or compounds (e.g., because of pretreatment), or other unknown effects, creating extra COD release compared to the control variant fed only with inoculum. Thus, the high methane yield attained for the LF may include a surplus methane production from inoculum. The methane yield of the LF of press mud is 48% higher than that obtained from the SF. This result was expected because more complex substances difficult to degrade, such as waxes, fats, cellulose, and some lignin, remained in the SF. On the contrary, easily degradable and very well hydrolyzed components (hydrolyzable fat and carbohydrate components), unavailable without press mud pretreatment, could be part of the LF of thermally pretreated press mud. Similar results were obtained for the LF and SF of sunflower oil cake hydrothermally pretreated at 150 °C for 4 h. In that case, the methane yield of the LF resulted in 122% of the increment compared to the methane yield of the SF.12 In the case of V, the ymax obtained is 271 N mL CH4 g−1 CODfed. Similar ymax values of 250 and 263 N mL CH4 g−1 CODfed were previously reported by refs 17 and 26. The low ymax from V has been attributed to the presence of complex recalcitrant compounds called melanoidines,27 high potassium levels, and high sulfate concentrations and its reduction to sulfide during the fermentation.16,28 The maximum methane yields range from 217 to 335 N mL CH4 g−1 CODfed for the different mixtures. Even though the DM varied from 5.1 to 7.3% (w/w), it is generally accepted that wet anaerobic digestion has a good performance with 8% of total solids.29 Therefore, the methane yield was not affected as a result
Table 4. Calculated Regression Coefficients, Standard Errors, and Statistical Significances Obtained from the Full Cubic Model Predicting Methane Yields before Fitting of the Model coefficient
estimate
standard error
p value
βLF βSF βV βLF_SF βLF_V βSF_V βLF_SF_V δLF_V (LF−V) δLF_SF (LF−SF) δSF_V (SF−V)
369 249 271 −2 −416 −21 −767 −344 80 −109
6 6 6 28 28 25 202 62 62 62
0.940 0.000 0.457 0.001 0.000 0.213 0.097
for the mixture of LF and V (p = 0.000) with a coefficient βLF_V of −416 and insignificant for the mixtures of LF and SF (p = 0.940) and SF and V (p = 0.457). The cubic terms indicate an antagonistic influence on the methane yield for the coefficient βLF_SF_V (−767), followed by δLF_V (LF−V) (−344). Both coefficients show a highly significant interaction with p values of 0.001 and 0.000, respectively. The cubic terms δLF_SF (LF−SF) and δSF_V (SF−V) have either synergetic (80) or antagonistic (−109) effects but are insignificant according to p values of 0.213 and 0.097, respectively (Table 4). Clearly, both in quadratic and cubic terms, the combination of V with LF is negative regarding the methane yield, although both contribute to COD removal and show positive methane yields when digested separately. The full cubic model was calculated again without the nonsignificant coefficients. The result is given as follows (eq 4): yCH = 370.7x LF + 247.8xSF + 266.4x V − 410.0x LFx V 4
− 817.6x LFxSFx V − 357.2x LFx V(x LF − x V )
(4)
On the basis of eq 4, methane production of different mixtures can be predicted. The results can be graphically displayed using a triangular surface response method. A triaxial diagram as a graphical representation of the blends of substrates considered in the current study is given in Figure 1. It is observed that the LF yields the highest production. Lower methane yields were observed closer to the V triangle corner, demonstrating the antagonistic effect of V. There is also an antagonistic effect in mixing SF and V, but this is less obvious because both SF and V
Figure 1. (A) Three-dimensional mixture surface and (B) contour plot for methane yields (yCH4) obtained from the fitted model. D
DOI: 10.1021/acs.energyfuels.5b01369 Energy Fuels XXXX, XXX, XXX−XXX
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Energy & Fuels
Table 5. Experimental and Predicted Methane Yields, Kinetic Constants, and Methane Production Rates for the Different Mixturesa yCH4,predicted (N mL CH4 g−1 CODfed) mixtures
ymax (N mL CH4 g−1 CODfed)
b
c
k (day−1)
rs(t) (N mL CH4 g−1 CODfed)
V LF SF V67/LF0/SF33 V67/LF33/SF0 V33/LF0/SF67 V33/LF67/SF0 V33/LF33/SF33 V0/LF67/SF33 V0/LF33/SF67
271 ± 20 de 369 ± 21 a 249 ± 11 f 255 ± 6 ef 237 ± 5 fg 254 ± 6 ef 218 ± 12 gh 217 ± 6 h 335 ± 6 b 283 ± 9 cd
266 371 248 260 301 260 336 295 330 289
266 371 248 260 240 260 214 219 330 289
0.38 a 0.24 c 0.18 d 0.33 b 0.34 b 0.21 d 0.39 a 0.33 b 0.31 b 0.25 c
84 a 57 e 38 f 66 c 68 c 45 d 73 b 63 d 57 e 54 e
a Letters indicate significant difference (p < 0.05) as tested with Duncan’s test. bMethane yields obtained by the first linear part of the full cubic model (no synergistic or antagonistic interactions). cMethane yields obtained by the full cubic model (taking into account synergistic or antagonistic interactions).
of the solid content in the reactors but the bioavailability of the carbon source. In addition, some interactions in two- and threecomponent mixtures had a significant antagonistic effect on the methane yield, as proven in section 3.2. The assessment of the antagonistic effect on the methane yield is carried out comparing two predicted yCH4 values: one referring to the linear effects solely (yCH4,predicted) and the second including the square and cubic terms of the full cubic model (yCH4,predicted) (Table 5). The methane yields obtained experimentally are comparable to the predicted methane yields in the case of the mixtures without V and the mixtures without LF. When V and LF are present, the linear prediction fails, according to the high antagonistic effect found for their interaction. The methane yields obtained from batch anaerobic digestion tests are 20, 36, and 25% lower for V67/LF33/SF0, V33/LF67/SF0, and V33/LF33/ SF33, respectively, than the attained methane yields considering an additive behavior. It is well-known that V biodegradability is not higher than 50%, taking into account the biochemical oxygen demand (BOD)/ COD ratio.16 As previously mentioned, V contains high amounts of melanoidines as well as phenolic compounds among other components possibly inhibitory to microorganisms. These components, if mixed with pretreated LF or SF, might have reached a concentration that could have affected the biomethanation process. Consequently, the addition of V to pretreated press mud or LF should not be considered a good option for biogas production. With regard to reaction kinetics, the values for k ranged from 0.18 to 0.39 day−1. For SF and mixtures with a high portion of SF (V33/LF0/SF67 and V0/LF33/SF67), k values lower than 0.26 day−1 are attained. Higher methane production rates are observed for V and most of its blends when compared to pure SF and LF, with rs(t) values higher than those of SF and LF (Figure 2). The highest methane production rate is achieved for V33/LF67/SF0 and V (73 and 84 N mL CH4 g−1 CODfed day−1, respectively). With regard to LF, a high concentration of more biodegradable components present in the hydrolyzed components could bring a rapid production of VFAs, affecting the methane production rate.30 On the contrary, because the less biodegradable fraction was retained in the SF, the lowest rs(t) (38 N mL CH4 g−1 CODfed day−1) was found for that component.
Figure 2. Cumulative methane yield corresponding to different mixture compositions in batch assays and curves from the Hill model: (▲) V, (◆) SF, (●) LF, (+) V67/LF0/SF33, (×) V67/LF33/SF0, (◇) V33/LF0/ SF67, (○) V33/LF67/SF0, (■) V33/LF33/SF33, (□) V0/LF67/SF33, and (-) V0/LF33/SF67.
4. CONCLUSION A lattice simplex design was used to conceptualize the experiment for the co-digestion of V with LF and SF from thermally pretreated press mud. The highest methane yield was obtained for the pure LF with a value of 369 N mL CH4 g−1 CODfed, that is 48% higher compared to that of SF. For most mixtures examined, antagonistic effects were found with significant differences when V and LF are mixed. Consequently, the co-digestion of V and the LF of LHW pretreated press mud is not considered a good option for liquid stream treatment at the sugar industry. A better understanding of the nature of this antagonistic effect could help to avert this effect or even turn it into a synergetic effect. Therefore, future research clearly offers interesting challenges that could lead to efficient and environmentally friendly process options for the sugar cane industry.
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Corresponding Author
*Telephone: +53-41-327724. E-mail:
[email protected]. E
DOI: 10.1021/acs.energyfuels.5b01369 Energy Fuels XXXX, XXX, XXX−XXX
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Energy & Fuels Notes
(17) España-Gamboa, E. I.; Mijangos-Cortés, J. O.; Hernández-Zárate, G.; Maldonado, J. A. D.; Alzate-Gaviria, L. M. Methane production by treating vinasses from hydrous ethanol using a modified UASB reactor. Biotechnol. Biofuels 2012, 5 (82), 82. (18) Cornell, J. A. Experiments with Mixtures: Designs, Models and the Analysis of Mixture Data, 3rd ed.; John Wiley & Sons: Hoboken, NJ, 2002. (19) American Public Health Association (APHA). Standard Methods for the Examination of Water and Wastewater, 20th ed.; APHA: Washington, D.C., 1998. (20) Verein Deutscher Ingenieure (VDI). VDI 4630, Fermentation of Organic Materials. Characterisation of the Substrates, Sampling, Collection of Material Data, Fermentation Tests. Handbuch Energietechnik; Beuth Verlag GmbH: Berlin, Germany, 2006. (21) Batstone, D. J.; Jensen, P. D. Anaerobic processes. In Treatise on Water Science; Wilderer, P., Ed.; Elsevier B.V.: Amsterdam, Netherlands, 2010; Chapter 97, pp 615−638. (22) Zheng, Y.; Zhao, J.; Xu, F.; Li, Y. Pretreatment of lignocellulosic biomass for enhanced biogas production. Prog. Energy Combust. Sci. 2014, 42, 35−53. (23) Weiland, P. Biogas production: current state and perspectives. Appl. Microbiol. Biotechnol. 2010, 85, 849−860. (24) Monlau, F.; Trably, E.; Barakat, A.; Quemeneur, M.; Steyer, J. P.; Carrère, H. Do by-products of thermochemical treatment of lignocellulosic materials inhibit anaerobic mixed cultures? Overview of recent findings. Proceedings of the 13th World Congress on Anaerobic Digestion: Recovering (bio) Resources for the World; Santiago de Compostela, Spain, June 25−28, 2013. (25) Wilkie, A. C.; Riedesel, K. J.; Owens, J. M. Stillage characterization and anaerobic treatment of ethanol stillage from conventional and cellulosic feedstocks. Biomass Bioenergy 2000, 19, 63−102. (26) Siles, A.; García-García, I.; Martín, A.; Martín, M. A. Integrated ozonation and biomethanization treatments of vinasse derived from ethanol manufacturing. J. Hazard. Mater. 2011, 188 (1−3), 247−253. (27) Chandra, R.; Bharagava, R. N.; Rai, V. Melanoidins as major colourant in sugarcane molasses based distillery effluent and its degradation. Bioresour. Technol. 2008, 99, 4648−4660. (28) Barrera, E. L.; Spanjers, H.; Romero, O.; Rosa, E.; Dewulf, J. Characterization of the sulfate reduction process in the anaerobic digestion of a very high strength and sulfate rich vinasse. Chem. Eng. J. 2014, 248, 383−393. (29) Weiland, P. Biogas production: current state and perspectives. Appl. Microbiol. Biotechnol. 2010, 85 (4), 849−860. (30) Xie, S.; Frost, J. P.; Lawlor, P. G.; Wu, G.; Zhan, X. Effects of thermo-chemical pre-treatment of grass silage on methane production by anaerobic digestion. Bioresour. Technol. 2011, 102 (19), 8748−8755.
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS This research was supported by the VLIR-UOS Project entitled “Biogas Production from Waste from Local Food, Wood and Sugarcane Industries for Increasing Self-Sufficiency of Energy in Sancti Spiritus, Cuba”. The authors thank Anka Thoma from Leibniz-Institute for Agricultural Engineering Potsdam-Bornim, Germany, because of her technical assistance for the LHW press mud pretreatment assays.
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DOI: 10.1021/acs.energyfuels.5b01369 Energy Fuels XXXX, XXX, XXX−XXX
