Article pubs.acs.org/EF
Effect of Feedstock Components on Thermophilic Solid-State Anaerobic Digestion of Yard Trimmings Long Lin,†,‡ Liangcheng Yang,†,§ and Yebo Li*,† †
Department of Food, Agricultural and Biological Engineering, Ohio Agricultural Research and Development Center, The Ohio State University, 1680 Madison Avenue, Wooster, Ohio 44691, United States ‡ Environmental Science Graduate Program, The Ohio State University, 3138A Smith Lab, 174 West 18th, Columbus, Ohio 43210, United States ABSTRACT: Solid-state anaerobic digestion of yard trimmings, composed of wood chips, lawn grass, and maple leaves, was conducted at 22% total solids at 55 °C for 45 days. Results showed digestion of mixed feedstocks generated earlier peaks and more methane than digestion of single components. The favorable peaking time (14 days) and methane yield (143 L/kg of VS) were achieved with equal fractions of the three components, increasing the methane yield by 80−200% compared to digestion of single components. Concentrations of volatile fatty acids and ammonia varied with component ratios and correlated with system performance. While organic components in mixtures were degraded differently, they were mostly degraded within 24 days and agreed with the methane yield. A mixture design model was established to predict the methane yield, and results showed that all interactions were synergistic, with the ternary interaction having the strongest effect. The model was verified using experimental data, which showed good agreement.
1. INTRODUCTION
134 L/kg of VS for branches, indicating that yard trimmings can be a potential feedstock for AD. SS-AD of yard trimmings for methane production can be an option. SS-AD was shown to be more suitable to handle yard trimmings than L-AD because the problems of stratification and floatation of fibrous materials in L-AD can be addressed in SSAD.8 However, mesophilic SS-AD was reported to have relatively low methane yields for wood chips (50 L/kg of VSfeedstock) and leaves (75 L/kg of VSfeedstock) compared to their BMPs.8,9 Moreover, digesting grass alone in SS-AD produced low methane yields because of its high nitrogen content, which causes an overaccumulation of ammonia that inhibits methanogenic activity.6 Mixing the three main components of yard trimmings, i.e., wood chips, leaves, and grass, is of particular interest for thermophilic SS-AD. Because these components have different compositions, mixing them can potentially balance nutrients and reduce inhibition, thereby improving the methane yield. For instance, the carbon to nitrogen (C/N) ratios of grass, leaves, and wood chips were determined to be 14, 36, and 75, respectively,10 while the optimal C/N ratio for AD is 20−30.11 Additionally, SS-AD under thermophilic conditions was reported to be more favorable for degradation of lignocellulosic biomass compared to mesophilic SS-AD.12 However, there are few studies on thermophilic SS-AD of yard trimmings. Furthermore, the regional and seasonal variability in the feedstock components of yard trimmings also emphasizes the need for investigating the ratio of yard trimming components on system performance. Therefore, it is crucial to obtain baseline data and develop models for predicting thermophilic
Renewable energy is in high demand because of the increasing consumption of limited fossil fuels. The U.S. Federal Energy Independence and Security Act of 2007 (EISA) requires an annual supply of 136 billion liters of biofuels by 2022.1 One approach to increase biofuel production is to develop anaerobic digestion (AD), which is an engineered process that decomposes organic wastes to produce biogas using microorganisms, meanwhile, reducing the amount of waste.2,3 Depending upon the total solids (TS) content of the materials being processed, AD can be categorized into liquid anaerobic digestion (L-AD) or solid-state anaerobic digestion (SS-AD). Wastes with high moisture content, such as manure, food waste, and sewage sludge, are usually suitable for L-AD, which operates with less than 15% TS content, while wastes with high solid content, such as lignocellulosic biomass, are preferred for SS-AD, which digests with 15−50% TS content.3 In 2010, SSAD accounted for about 60% of the AD systems installed in Europe for the treatment of municipal solid waste.4 Yard trimmings, also known as garden waste, green waste, or yard waste, including grass, leaves, tree branches, and brush are typical lignocellulosic biomass.5 There were 31 million metric tons of yard trimmings produced in the U.S. in 2012;5 their composition varied from source to source and over the year.6 Handling of yard trimmings is a challenge. In the U.S., more than 50% of yard trimmings were composted, while the rest were landfilled, which might cause environmental pollution.5 Therefore, researchers have been looking for alternative methods to resolve this challenge. Owens and Chynoweth7 studied the anaerobic biodegradability of yard trimmings using a biochemical methane potential (BMP) assay and showed that, under mesophilic temperatures, the BMP was 209 L/kg of volatile solids (VS) for grass, 123 L/kg of VS for leaves, and © XXXX American Chemical Society
Received: February 6, 2015 Revised: May 18, 2015
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DOI: 10.1021/acs.energyfuels.5b00301 Energy Fuels XXXX, XXX, XXX−XXX
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Energy & Fuels
VS, pH, and alkalinity were measured according to Standard Methods Examination of Water and Wastewater.15 Samples for pH and alkalinity measurements were prepared by diluting 5 g of the reactor samples with 50 mL of DI water and then measured by an autotitrator connected with a pH meter (Mettler Toledo, DL22 Food & Beverage Analyzer, Columbus, OH). Total carbon and total nitrogen contents were determined by an elemental analyzer (Elementar Vario Max CNS, Elementar Americas, Mt. Laurel, NJ). Total ammonia nitrogen (TAN), including NH3 and NH4+, was measured on the basis of a modified distillation and titration method16 using 4% boric acid instead of 2% boric acid, with a Kjeldahl Distillation Unit B-324 (Buchi Labortechnik AG, Switzerland) and the autotitrator mentioned above. Total volatile fatty acids (VFAs) (acetic, propionic, isobutyric, butyric, isovaleric, and valeric acids) were measured using a gas chromatograph (GC) system (Shimadzu, 2010PLUS, Columbia, MD) equipped with a 30 m × 0.32 mm × 0.5 μm Stabilwax polar phase column and a flame ionization detector according to methods described by Shi et al.12 Extractives of raw materials and digested materials were measured on the basis of the National Renewable Energy Laboratory (NREL) Analytical Procedure17 using an accelerated solvent extractor (Thermo Scientific, Dionex ASE 350, Bannockburn, IL) and a rocket evaporator (Genevac, Inc., Stone Ridge, NY). Extractive-free samples were used to determine the structural carbohydrates using a two-step acid hydrolysis method.18 Monomeric sugars (glucose, xylose, galactorse, arabinose, and mannose) and cellobiose were analyzed with a high-performance liquid chromatograph (HPLC) system (Shimadzu, LC-20AB, Columbia, MD) equipped with a Bio-Rad Aminex HPX-87P column and a refractive index detector. HPLC grade water was used as the mobile phase at a flow rate of 0.3 mL/min. The temperatures of the column and detector were kept at 60 and 55 °C, respectively. Extractive-free samples were also used to determine total Kjeldahl nitrogen (TKN) with the modified Kjeldahl nitrogen method19 using a Tecator digestor (FOSS, Eden Prairie, MN) with the distillation unit and autotitrator mentioned above. The crude protein content was obtained by multiplying total organic nitrogen (TON = TKN − TAN) by a factor of 6.25.20 The volume of biogas was measured with a drum-type gas meter (Ritter, TG 5, Bochum, Germany), and the composition (CO2, CH4, N2, and O2) was analyzed with a GC system (Agilent, HP 6890, Wilmington, DE) equipped with a 30 m × 0.53 mm × 10 μm RtAlumina BondKCl deactivation column and a thermal conductivity detector. Helium gas was used as a carrier gas at a flow rate of 5.2 mL/ min. The temperature of the detector was kept at 200 °C. 2.5. Statistical and Regression Analyses. Average results and standard errors were reported on the basis of triplicates for each treatment, with one exception. One SS-AD reactor digesting lawn grass alone failed to produce methane and, thus, was not included. Statistical significance was tested using analysis of variance (ANOVA) and Tukey−Kramer honestly significant difference (HSD) with a threshold p value of 0.05. The augmented simplex-lattice mixture design allows for not only an estimation of the linear effects of each component but also the quadratic, cubic, and special quartic synergistic or antagonistic effects among the components.13,14 Independent factors were the proportion of the three components in a mixture, and the response variable was the accumulative methane yield. Five models (linear, quadratic, special cubic, full cubic, and special quartic) were fitted for accumulative methane yield by means of regression methods and analyzed with ANOVA at a threshold p value of 0.05. The linear, quadratic, and special cubic models were defined as the reduced models, while the full cubic model was the complete model. F statistic (eq 1) was used to test the significance of a reduced model by comparing it to the complete model.13 Data analysis was processed using JMP 10.0 software (SAS Institute, Inc., Cary, NC)
SS-AD performance of yard trimmings with varied component ratios. The estimation and optimization of the methane yield from feedstocks containing more than two components can be accomplished by means of a mixture design approach.13 It is a useful statistical tool to predict the response of any mixture as well as to optimize the response, depending upon the proportions of the components in the mixture.13,14 The goal of this study was to understand the effects of the ratio of wood chips, lawn grass, and maple leaves on thermophilic SS-AD system performance. The objectives of this study were to (1) evaluate the influence of the ratio of components on system performance, (2) establish a mixture model to estimate and optimize the methane yield, and (3) investigate the mechanism of synergistic/antagonistic effects of the feedstock components on the methane yield.
2. MATERIALS AND METHODS 2.1. Feedstock and Inoculum. Wood chips, lawn grass, and maple leaves (the three main components of yard trimmings) were collected in November, 2013 from the Ohio Agricultural Research and Development Center campus in Wooster, OH. Upon receipt, these feedstocks were dried at 40 °C for 48 h in a convection oven (Precision Thelco Model 18, Waltham, MA) to a moisture content of less than 10%, and then ground with a hammer mill to pass through a 9 mm screen sieve (Mighty Mac, MacKissic, Inc., Parker Ford, PA), and stored in airtight containers. Effluent from a mesophilic liquid anaerobic digester that processed municipal sewage sludge (KB BioEnergy, Inc., Akron, OH) was used as the inoculum. The inoculum was stored in airtight buckets at 4 °C once received. Prior to use, it was acclimated at 55 °C for 1 week. 2.2. Liquid Anaerobic Digestion. L-AD experiments were conducted to evaluate the methane potential of the three individual components, i.e., wood chips, lawn grass, and maple leaves. Each feedstock was mixed with deionized (DI) water and inoculum to obtain a mixture of 5% TS and a feedstock to effluent (F/E) ratio of 0.5. The mixture was loaded into 1 L glass reactors and incubated on an Innova model 2300 platform shaker (New Brunswick Scientific, Enfild, CT) at 150 rpm for 45 days in a 55 ± 0.3 °C incubator (BioCold Environmental, Inc., Fenton, MO). Triplicate reactors were run for each feedstock. Inoculum without any feedstock addition was used as a control. Biogas generated was collected in 5 L Tedlar gas bags (CEL Scientific, Santa Fe Springs, CA) connected to the outlets of each reactor. Biogas composition and volume were measured when 1−2 L of biogas was collected. 2.3. Solid-State Anaerobic Digestion. A three-component augmented simplex-lattice mixture design was adopted for the SSAD tests. Yard trimmings containing different fractions of the three components were used as the feedstocks. The fraction of each component varied between 0 and 1, and the sum of fractions was 1 (wet weight basis). The mixture design consisted of three treatments of a single component, nine binary mixtures, and four ternary mixtures. All of the experiments were performed in triplicate. Two independent batches of experiments were conducted for the ternary mixture with equal fractions of the three components. For the first batch, at predetermined time intervals (days 6, 12, 24, and 45), reactors were terminated for chemical and compositional analyses. The second batch experiment was used to obtain accumulative methane yields for comparison to model predictions. For each treatment, feedstock, DI water, and inoculum were mixed using a hand-mixer (Black & Decker, 250 W mixer, Towson, MD) to achieve a mixture of 22% TS and a F/ E ratio of 4, which were chosen on the basis of previous results.10 The mixture was loaded into 1 L glass reactors and incubated for up to 45 days in a 55 ± 0.3 °C incubator. Inoculum without any feedstock addition was used as a control. Biogas was collected in 5 L Tedlar gas bags, and the biogas composition and volume were measured every 2− 3 days. 2.4. Analytical Methods. Samples from the reactors were collected at the beginning and end of the 45 day incubation. TS,
F=
(SSR complete − SSR reduced)/r SSEcomplete /(N − p)
(1)
where SSRcomplete is the sum of squares as a result of regression when fitted with the complete model, SSRreduced is sum of squares as a result B
DOI: 10.1021/acs.energyfuels.5b00301 Energy Fuels XXXX, XXX, XXX−XXX
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Energy & Fuels Table 1. Characteristics of Feedstocks and Inoculum
a
parameter
wood chips
lawn grass
maple leaves
effluent
TS (%) VS (%) total carbon (%) total nitrogen (%) C/N ratio pH alkalinity (g of CaCO3/kg) VFAs (g/kg) TAN (g of N/kg) extractives (%)b cellulose (%)b hemicellulose (%)b lignin (%)b crude protein (%)b
88.7 ± 0.0 84.8 ± 1.2 46.4 ± 0.3 0.6 ± 0.0 75.4 ± 2.4 NDa ND ND ND 15.5 ± 0.1 27.5 ± 0.3 15.6 ± 0.1 26.9 ± 0.4 5.4 ± 1.2
94.8 ± 0.1 88.5 ± 0.4 47.8 ± 0.0 3.8 ± 0.0 12.4 ± 0.0 ND ND ND ND 24.9 ± 4.4 23.1 ± 0.8 16.4 ± 0.6 12.1 ± 0.8 17.7 ± 0.3
93.8 ± 0.0 84.5 ± 0.0 46.1 ± 0.3 1.2 ± 0.00 41.1 ± 0.3 ND ND ND ND 29.8 ± 0.2 11.6 ± 0.4 9.9 ± 0.4 24.0 ± 0.2 6.4 ± 0.7
7.7 ± 0.0 4.5 ± 0.0 2.9 ± 0.0 0.5 ± 0.0 5.3 ± 0.0 8.3 ± 0.0 13.0 ± 0.1 2.6 ± 0.2 4.1 ± 0.1 15.6 ± 1.0 2.0 ± 0.0 1.8 ± 0.0 ND 14.8 ± 0.1
ND = not determined. bOn the basis of TS of the sample; the others are based on wet weight of the sample.
of regression when fitted with the reduced model, SSEcomplete is sum of squared errors when fitting with the complete model, r is the difference of the number of terms between complete and reduced models, and (N − p) is the degree of freedom for the errors as a result of fitting the complete model.
lowest content of lignin, produced the highest accumulative methane yield (410 L/kg of VSfeedstock), followed by maple leaves (187 L/kg of VSfeedstock) and wood chips (124 L/kg of VSfeedstock), indicating lawn grass had the highest methane potential among the three components (Figure 1b). Similar to a previous report,9 a significant inverse linear correlation was observed between the methane yield and the lignin content (R2 = 0.99). 3.3. SS-AD of Yard Trimmings with Varied Components. 3.3.1. Methane Yield. SS-AD of each single component of yard trimmings was inhibited, lawn grass in particular, compared to their methane potentials achieved in the L-AD tests. The accumulative methane yields of maple leaves and wood chips from SS-AD were both about 40% of those obtained in L-AD; the methane yield of lawn grass was only 15% of that produced in L-AD (Table 2 and Figure 1b), which confirmed the inhibition during digestion of lawn grass alone in SS-AD.6 Mixing wood chips, lawn grass, and/or maple leaves, including binary and ternary mixtures, improved methane yields (Table 2). Maple leaves and lawn grass played important roles in increasing the methane yield. For instance, when mixing maple leaves with wood chips, the methane yield increased in proportion to the fraction of maple leaves and the mixture with 75% maple leaves displayed a maximum increase of 82% in the methane yield compared to digestion of wood chips alone (Table 2 and Figure 2a). On the other hand, when mixing lawn grass with wood chips, the mixture with 75% lawn grass had the largest increase of 117% in the methane yield over digestion of wood chips alone. Moreover, among all of the binary mixtures, the highest methane yield was obtained from the mixture with 75% maple leaves and 25% lawn grass. Among all of the mixtures, the three highest methane yields (141.9− 147.0 L/kg of VSfeedstock), which were not significantly different from each other (p > 0.05), were achieved at three ternary mixtures with 25−33% wood chips and were 200, 140, and 80% higher than SS-AD of only wood chips, lawn grass, and maple leaves, respectively (Table 2). These results implied the advantage of SS-AD of a yard trimmings mixture over single components. SS-AD of mixtures also advanced methane peaking time, especially for those with wood chips (Table 2). The earliest peaking time (8 days) was achieved from the binary mixtures with wood chips/maple leaves ratios of 75:25 and 50:50. This
3. RESULTS AND DISCUSSION 3.1. Composition of Feedstock and Inoculum. Wood chips, lawn grass, and maple leaves had TS contents of 88.7− 94.8% and VS contents of 84.5−88.5% (Table 1). They had similar contents of total carbon but varied contents of total nitrogen, resulting in C/N ratios that ranged from 12.4 (lawn grass) to 75.4 (wood chips). The effluent had the lowest C/N ratio (5.3). Among the three feedstocks, lawn grass had the highest total nitrogen content (3.8%), while wood chips had the lowest (0.6%). As the F/E ratio was fixed, the C/N ratio of the treatments decreased with an increase in the lawn grass fraction (Table 2). Extractives, cellulose, hemicellulose, lignin, and crude protein are also common components in lignocellulosic biomass. Maple leaves had the highest content of extractives (29.8%, water and ethanol solutes combined; Table 1), which include compounds such as free sugars, oligosaccharides, and organic acids21 and are easily degradable for biogas production.9 Wood chips had the highest content of lignin (26.9%) and holocellulose (43.1%, cellulose and hemicellulose combined), while lawn grass exhibited the lowest content of lignin (12.1%) but a similar content of holocellulose (39.5%). The presence of lignin usually reduces the biodegradability of lignocellulose biomass because of its recalcitrant nature and complex structure.9 As expected, lawn grass had a higher content of crude protein than the other two feedstocks because nitrogen is mainly in the form of organic nitrogen in lignocellulosic biomass.6 3.2. L-AD of the Single Components of Yard Trimmings. L-AD was performed to evaluate the methane potential of the three components of yard trimmings at a low (5%) TS content, because there is less inhibition than in SSAD.22 All L-AD reactors were healthy, with final pH of 8.3−8.4. Lawn grass had a higher daily methane yield throughout the 45 day incubation, followed by maple leaves and wood chips (Figure 1a). There was little methane produced from these three components after day 24. The lignin content has been regarded as a key factor in affecting the biodegradability of lignocellulosic biomass.9,23 Lawn grass, which contained the C
DOI: 10.1021/acs.energyfuels.5b00301 Energy Fuels XXXX, XXX, XXX−XXX
100:0:0 0:100:0 0:0:100 24:76:0 24:0:76 0:25:75 0:75:25 74:26:0 74:0:26 48:52:0 0:50:50 49:0:51 24:26:50 24:51:25 48:26:26 32:34:34
wood chips/lawn grass/maple leaves (on the basis of TS) 18.7 9.5 15.8 10.8 16.4 13.5 10.5 15.0 17.9 12.5 11.8 17.1 14.0 12.2 14.5 13.4
C/N 14 32 14−16 14 12−14 18−21 18−21 8−20 8 10−12 14 8 10, 18 21 10 10−14
peaking time (day)
Fraction of the feedstock component in yard trimmings (%, w/w). bEstimated from the special cubic model.
100:0:0 0:100:0 0:0:100 25:75:0 25:0:75 0:25:75 0:75:25 75:25:0 75:0:25 50:50:0 0:50:50 50:0:50 25:25:50 25:50:25 50:25:25 33:33:33
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
a
wood chips/lawn grass/maple leavesa
number
Table 2. Mixture Design for Reactors and SS-AD Performance
1.7 10.9 1.5 7.6 2.7 7.3 6.5 2.8 2.6 4.6 5.5 2.5 1.7 7.2 2.3 3.0
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
3.2 ± 0.2 2.3 ± 0.5 6.4 ± 0.4 10.1 ± 1.1 7.4 ± 0.6 7.75 ± 1.4 11.0 ± 0.4 3.8 ± 0.2 5.7 ± 0.3 5.6 ± 0.3 5.9 ± 1.7 8.0 ± 0.4 9.3 ± 1.1 12.0 ± 0.5 8.8 ± 1.6 10.9 ± 0.6 48.6 60.5 79.8 105.6 88.3 130.2 106.7 76.8 58.2 74.7 97.2 71.1 141.9 147.0 119.4 143.4
measured
maximum daily CH4 yield (L kg−1 of VSfeedstock day−1)
47.8 70.8 91.7 87.4 80.8 112.2 101.7 75.9 58.8 89.1 115.5 69.8 140.2 142.4 128.1 146.2
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
5.6 7.8 5.6 4.6 4.0 4.6 4.6 4.5 4.0 5.2 5.2 3.3 4.1 4.1 4.1 4.7
predictedb
accumulative CH4 yield (L/kg of VSfeedstock)
Energy & Fuels Article
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DOI: 10.1021/acs.energyfuels.5b00301 Energy Fuels XXXX, XXX, XXX−XXX
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Figure 1. (a) Daily methane yield and (b) effect of the lignin content on accumulative methane yield from L-AD of single components of yard trimmings. Figure 2. (a) Ternary plot of accumulative methane yield from SS-AD and (b) daily methane yield from ternary mixtures.
was likely due to the wood chips having the lowest content of extractives and the highest C/N ratio, which would slow the VFA production and balance the C/N ratio of the mixture, respectively. On the other hand, the presence of lawn grass contributed to relatively late peaking time, with the latest at 21 days (25% wood chips/50% lawn grass/25% maple leaves). This was probably due to the fast hydrolysis of easily degradable materials and the high nitrogen content in lawn grass, which led to overproduction of VFAs and TAN in the initial stage, inhibiting the methanogenesis process. Overall, the SS-AD of yard trimmings mixtures had an average peaking time of 15 days, ranging from 8−21 days, while SS-AD of single components had an average value of 20 days, ranging from 14− 32 days. Because the methane yield and peaking time are both important factors to evaluate system performance, the ternary mixture with equal parts of the three components was considered as the preferable condition in this study. This component ratio achieved the second earliest peaking time and the second highest methane yield, with 82% of the methane produced within 24 days (Figure 2b), while other ternary mixtures either had the earliest peaking time with the lowest methane yield or the highest methane yield with the latest peaking time (Table 2). 3.3.2. Reactor Characteristics. The strong inhibition during SS-AD of lawn grass alone was supported by its reactor characteristics (Table 3). Its high concentrations of final VFAs (23.9 g/kg) and TAN (7.8 g of N/kg) were far above the reported inhibitory levels of 6 g/L for VFAs and 5.6 g of N/L
for TAN.24,25 Additionally, its low C/N ratio (9.5; Table 2) agreed with previous studies that found that low C/N ratios led to high concentrations of ammonia, which hindered SS-AD of lawn grass.6 Moreover, one of the three lawn grass reactors failed to produce methane with an extremely high level of VFAs (35.0 g/kg; data not included), suggesting that SS-AD of lawn grass might have introduced excessive VFA accumulation, which could have caused reactor failure. The concentrations of final VFAs and TAN varied with component ratio and correlated with the methane yield. Increasing the lawn grass fraction tended to cause high concentrations of final TAN and VFAs (Table 3). A proportional relation was observed between the concentration of final TAN and the fraction of lawn grass, while the relationship between the final VFA level and the lawn grass fraction was not clear. The binary mixtures with 50% lawn grass showed the highest concentrations of final VFAs (11.6−13.9 g/ kg) among all mixtures, which were probably responsible for their low methane yields. Conversely, increasing the wood chips fraction was likely to slow the VFA and TAN production and reduce the overall biodegradability of feedstocks because wood chips had the lowest extractives content and the highest lignin content among the three components. For instance, the binary mixture with 75% wood chips and 25% maple leaves had the lowest concentration of final VFAs and the lowest accumulative methane yield. Ternary mixtures, which balanced E
DOI: 10.1021/acs.energyfuels.5b00301 Energy Fuels XXXX, XXX, XXX−XXX
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Energy & Fuels Table 3. Characteristics of Initial and Final Parameters pH number
wood chips/lawn grass/maple leavesa
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
100:0:0 0:100:0 0:0:100 25:75:0 25:0:75 0:25:75 0:75:25 75:25:0 75:0:25 50:50:0 0:50:50 50:0:50 25:25:50 25:50:25 50:25:25 33:33:33
a
initial 7.9 8.4 8.0 8.3 7.8 8.1 8.3 7.8 7.9 8.1 8.2 8.0 8.1 8.2 7.9 7.9
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.0 0.1 0.0 0.0 0.1 0.0
VFAs (g/kg) final 8.4 8.0 8.4 8.1 8.3 8.4 8.2 8.4 8.4 8.3 8.5 8.4 8.4 8.3 8.4 8.4
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.1 0.0 0.0 0.1 0.0 0.1 0.0 0.1 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0
initial 1.3 1.3 1.2 1.5 1.4 1.6 1.3 1.2 1.2 1.0 1.3 1.4 1.2 1.5 1.2 1.4
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.0 0.1 0.2 0.0 0.1 0.5 0.0 0.0 0.2 0.1 0.0 0.1 0.3 0.1 0.1 0.2
alkalinity (g of CaCO3/kg)
final 3.1 23.9 2.7 9.3 2.1 2.7 7.3 3.3 1.5 13.9 11.6 3.6 3.8 6.3 5.0 4.4
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
initial 0.5 3.5 1.1 0.3 0.7 1.1 1.9 1.0 0.4 0.4 0.8 0.2 0.3 1.2 0.3 0.5
10.7 11.5 7.2 10.4 8.3 8.1 10.0 8.7 7.8 10.2 8.2 7.4 8.4 9.4 10.5 9.5
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.0 0.1 0.2 0.2 0.1 0.1 0.2 0.1 0.1 0.3 0.3 0.0 0.1 0.2 0.0 0.0
final 11.1 12.0 11.4 15.0 11.7 15.6 19.4 13.0 9.8 11.9 14.8 11.2 15.1 18.2 14.5 15.4
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
TAN (g of N/kg) initial
0.2 0.1 0.1 0.6 0.1 0.7 0.3 0.2 0.9 0.4 0.2 0.2 0.2 1.0 0.7 0.3
3.8 4.2 3.7 3.9 3.6 3.7 3.7 3.9 3.5 3.7 3.7 3.5 3.6 3.9 4.0 3.7
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.5 0.0 0.1 0.0 0.2 0.1 0.0 0.3 0.0
final 4.2 7.8 4.4 7.5 4.0 4.7 6.8 4.8 4.0 5.8 5.8 3.6 4.5 5.8 5.0 5.0
± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±
0.1 0.3 0.2 0.0 0.1 0.1 0.0 0.1 0.2 0.1 0.1 0.1 0.1 0.1 0.2 0.1
Fraction of feedstock component in yard trimmings (%, w/w).
these reactor characteristics within a suitable range for SS-AD, had final VFAs of 3.8−6.3 g/kg, alkalinity of 14.5−18.2 g of CaCO3/kg, and TAN of 4.5−5.8 g of N/kg (Table 3). The results indicated ternary mixtures reduced the inhibitors that would otherwise be inhibitory in the digestion of single components of yard trimmings, particularly lawn grass. The alleviation of inhibitors enabled SS-AD of yard trimmings to use the high contents of easily biodegradable organics in lawn grass. 3.3.3. Temporal Changes in Reactor Characteristics and Degradation. Changes in reactor characteristics and degradation of organic components during SS-AD of yard trimmings that contained equal fractions of the three feedstocks are shown in Figure 3. The VFA profile increased sharply to reach the peak value during the first 6 days, followed by a gradual decrease, leveling off at about 1/3 of the peak value on day 24 (Figure 3a). The high concentration of VFAs (15.0 g/kg) on day 6 reduced pH and alkalinity. After that, VFAs were consumed, and the pH and alkalinity increased accordingly. TAN barely changed on days 6 and 12 but gradually increased thereafter, with a final value of 5.0 g/kg, which was 37% higher than its initial value. Total nitrogen balance showed that the nitrogen loss was 7.2%, which could have been caused by the NH3 evaporation. The temporal changes in degradation of organic components were different. During the 45 day incubation, the total degradation was 50% for cellulose, 57% for hemicellulose, 30% for crude protein, and not detectable for extractives (Figure 3b). The extractives degraded quickly in the beginning 6 days (28%), causing fast VFA production. In contrast, the degradation of cellulose and hemicellulose increased within days 6−12, which was in agreement with previous studies that hydrolysis of cellulose and hemicellulose was slower than extractives.21 No degradation of protein was observed on day 6, which was probably due to protein synthesis through initial microbial cell growth.12 The degradation increased to 30% at the end of the experiment, which might have been due to the decay of microbes. Thus, the protein in microbes would be degraded to release inorganic N-containing compounds into the digestate. On the other hand, because extractives were defined as water and ethanol solutes, the soluble organics from
Figure 3. (a) Changes in reactor characteristics and (b) changes in degradation of organic components during SS-AD of yard trimmings containing equal fractions of three components. (∗) No detectable degradation.
the decay of microbes would also be measured as extractives, which supported the observation of the final accumulation of extractives. Overall, the results implied that most of the degradation could have been achieved within the 24 day incubation, which was also consistent with the methane yield results. 3.4. Model Fitting and Regression Analysis. The fitting results of all five models are presented in Table 4. The special quartic model had two more degrees of freedom (DF) than the F
DOI: 10.1021/acs.energyfuels.5b00301 Energy Fuels XXXX, XXX, XXX−XXX
Article
Energy & Fuels Table 4. Model Fitting Results and Regression Analysis for the Special Cubic Model model
DF
F value
p value
R2
adjusted R2
linear quadratic special cubic full cubic special quartic
2 5 6 9 8
6.6431 17.8045 38.2591 28.9492 28.0538
0.0031
