Material flow analysis (MFA) was applied to study the process of biogas production from switchgrass using a mid-temperature (35 ± 1 °C) batch anaerobic digestion process. The flow distributions of energy and material, including carbon (C) and nitrogen (N), were analyzed, as were the material and energy conversion efficiencies. The results showed that biogas and CH4 production were 268.80 and 135.31 NmL×gVS-1 added, respectively, and the average CH4 content in biogas was 50.34%. Based on the MFA of the anaerobic digestion process, 30.6%, 3.6%, and 65.8% of C was converted into biogas, biogas slurry, and biogas residue, respectively; and 11.7% and 88.3% of N was converted into biogas slurry and biogas residue, respectively. The conversion efficiencies of the material and energy from switchgrass to biogas were 36.1% and 30.1%. Because of the low conversion efficiencies of matter and energy during biogas production, it is necessary to strengthen the secondary use of the fermentation residue. This study provides a basis for the optimization of the anaerobic digestion process and efficient utilization of resources and energy of energy-grass.
Analysis of Biogas Produced from Switchgrass by Anaerobic Digestion
Hongzhi Niu,a,b Xiaoying Kong,a,* Lianhua Li,a Yongming Sun,a,* Zhenhong Yuan,a and Xianyou Zhou a,b
Material flow analysis (MFA) was applied to study the process of biogas production from switchgrass using a mid-temperature (35 ± 1 °C) batch anaerobic digestion process. The flow distributions of energy and material, including carbon (C) and nitrogen (N), were analyzed, as were the material and energy conversion efficiencies. The results showed that biogas and CH4 production were 268.80 and 135.31 NmLgVS-1 added, respectively, and the average CH4 content in biogas was 50.34%. Based on the MFA of the anaerobic digestion process, 30.6%, 3.6%, and 65.8% of C was converted into biogas, biogas slurry, and biogas residue, respectively; and 11.7% and 88.3% of N was converted into biogas slurry and biogas residue, respectively. The conversion efficiencies of the material and energy from switchgrass to biogas were 36.1% and 30.1%. Because of the low conversion efficiencies of matter and energy during biogas production, it is necessary to strengthen the secondary use of the fermentation residue. This study provides a basis for the optimization of the anaerobic digestion process and efficient utilization of resources and energy of energy-grass.
Keywords: Switchgrass; Anaerobic digestion; Biogas; Methane; Material flow analysis
Contact information: a: Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, CAS, Key Laboratory of Renewable Energy, Guangzhou 510640, Guangdong China; b: University of China Academy of Sciences, Beijing 100049, China;
* Corresponding author: email@example.com, firstname.lastname@example.org
Energy crops may become a sustainable alternative to the use of fossil fuels and a more environmentally friendly energy source in the future. Various perennial grasses have been studied and identiﬁed as promising energy crops, such as Miscanthus (Clifton-Brown et al.2004; Toma et al. 2011; Jurado et al. 2013), reed canarygrass (Massé et al. 2011), and switchgrass (Ahn et al. 2010; Massé et al. 2011; Jin et al. 2012 El-Mashad 2013). Switchgrass, a C4 grass, is considered a more promising energy crop than many other grasses because of its efﬁcient photosynthetic pathway. Switchgrass has additional advantages, such as superior aboveground biomass yield across a wide geographical range, adaptability to marginal quality land, and low requirements for water, energy, and nutrients. Moreover, switchgrass roots can enhance the structural stability of soil (Massé et al. 2010; Hu and Ragauskas 2011).
Anaerobic digestion is a biological method for the conversion of organic wastes into stable products for land applications with reduced environmental impacts (Ahn et al. 2010). Methane produced by anaerobic digestion may be a signiﬁcant energy source for the generation of heat and power. Biomethanation of switchgrass is becoming a more common practice, e.g., anaerobic digestion of switchgrass harvested at different stages (Massé et al. 2010) and co-digestion of animal manure–switchgrass mixture (Ahn et al. 2010). The use of switchgrass for biogas has several potential benefits, including greater biogas production using codigestion with animal or human waste, as well as providing an interim market for energy crops producing ethanol and supplemental “tipping fee” revenue, which could enhance the economics and widespread adoption of switchgrass anaerobic digestion.
Material flow analysis (MFA) is a systematic assessment of the flows and stocks of materials within a defined system (Brunner and Rechberger 2004). MFA connects the flows and sinks of a material, making it a useful decision-making support tool for the management of resources, waste, and the environment (Huang et al. 2012). In recent decades, MFA has become widely used in many fields, including process control (Chen et al. 2012; Fang et al. 2012), waste and wastewater treatment (Aparcana et al. 2013, Chen et al. 2013), and resource conservation and recovery (Cha et al. 2013; Arena and Di Gregorio 2014).
It has been debated in previous articles whether the production of biogas or bioethanol for a given material is the best use (Papa et al.2015). Much research on the anaerobic digestion of switchgrass has been performed, but the flow distribution of material and energy in the anaerobic digestion process has not been clearly explained. In this study, MFA was used to analyze the process of using switchgrass to produce biogas via mid-temperature (35 ± 1 °C) batch anaerobic digestion. The flow distributions of materials, energy, carbon (C), and nitrogen (N) were presented and discussed. Based on the MFA results, some suggestions on improving efficiency of resource and biogas productivity were proposed.
Switchgrass provided by the Beijing University of Chemical Technology was dried, crushed, and sieved (20 mesh, < 0.85 mm). The inoculum was trained long-term in a mesophilic anaerobic fermentation tank in Biomass Bio-chemical Conversion Laboratory of GuangZhou Institute of Energy Conversion, Chinese Academy of Sciences (short for GIEC-BBC, CAS).
Digester setup and operation
Lab-scale digesters were arranged, as shown in Fig. 1. Briefly, 2500-mL Büchner flasks (BA) with one sampling opening were filled with inoculum and switchgrass mix (12:1 m/m, 8% TS), while nitrogen was used to remove the air in the flasks. Water baths were controlled at 35 ± 1 °C, and the digesters were stirred manually twice a day. The experiments were stopped after 44 d when the daily biogas productions were less than 1.5 mL∙gVS-1 added∙d-1 for a period of more than 5 d. The fermentation residues in BA were filtered and the solid residues were dried at 60 °C, while the filtrate (biogas slurry) was stored at -20 °C.
Biogas generated from bottle A was collected in bottle B and measured with saturated NaCl solution displace method. Biogas production was measured daily by measuring the volume of the solution in Bottle C with a graduated cylinder. All tests were run in duplicate.
Fig. 1. Lab-scale setup for anaerobic digestion. Bottle A: anaerobic reactor; Bottle B: biogas collector; Bottle C: solution collector; Tube A: biogas-guide tube; Tube B: solution-guide tube; Valve A was used for biogas sampling; Valve B for biogas metering.
Methods of Analysis
Composition analyses of switchgrass and biogas residue were performed in triplicate. Total solids (TS) and volatile solids (VS) were assessed at 105 and 550 °C, respectively. Cellulose (CL), hemicellulose (HCL), and lignin (LG) were measured according to the National Renewable Energy Laboratory’s (NREL) laboratory analytical procedures (LAPs). The carbon (C) and nitrogen (N) contents of switchgrass and biogas residue were measured using a Vario EL cube analyzer (Elementar, Germany), while the total inorganic carbon (TIC), total carbon (TC), and total nitrogen (TN) of the inoculum and biogas slurry were measured using a Vario TOC analyzer (Elementar, Germany).
Gross heat of combustion (GHC)
The GHCs of switchgrass and biogas residue were determined using an oxygen bomb calorimeter (C 2000, IKA, Germany), with an initial oxygen pressure of 5.0 MPa (50 atm) and a final temperature of 20 to 25 °C. Benzoic acid was used for calibration.
Biogas analysis was conducted at 120 °C using a GC-2014 gas chromatograph (Shimadzu, Japan) equipped with a TCD detector. A Porapak Q column, maintained at 50 °C, was used with an argon gas ﬂow rate of 30 mLmin-1 and a retention time of 5 min. Calibration of the instrument to a standard biogas (5% N2, 60% CH4, 35% CO2) was conducted weekly.
Gas production was calculated as the ratio of the total gas yield over the mass of the volatile solids added to the reactor (VSadded, assuming that VSadded = VSswitchgrass in this experiment), and expressed as mLgVS-1 added. Gas production was normalized and reported (273 K, 1 atm) as mL per g of the added volatile solids (NmLgVS-1 added). Daily gas production (DGP) and cumulative gas production (CGP) were expressed as NmLgVS-1 addedd-1 and NmLgVS-1 added, respectively.
Material flow analysis (MFA)
The MFA was performed as described by Brunner and Rechberger (2004). In the current study, the systematic assessment object was the experimental anaerobic fermentation process of biogas produced with switchgrass. Substance flow analysis software (STAN 2.5) was applied to establish the MFA system model, and an algorithm (IAL-IMPL 2013) was created to optimize the experimental data to ensure the conservation of matter (Smith and Tan 2013; Rechberger et al.2014). Graphical renderings of MFA results were prepared using the e!Sankey 3.2 flow chart designer.
RESULTS AND DISCUSSION
Anaerobic Digestion of Switchgrass
The physicochemical properties of the inoculum, switchgrass, biogas slurry, and biogas residue are shown in Table 1. The TIC, TC, and TOC (TC-TIC) in the inoculum (0.750, 1.055, and 0.305 g/L, respectively) were slightly lower than those recovered from the biogas slurry (0.894, 1.399, and 0.505 g/L, respectively), while the TN content in the inoculum (0.71 g/L) was higher than that of biogas slurry (0.12 g/L). Some of the degraded organic matters in the biogas slurry were not converted into biogas because of their low concentrations. The majority of N in the inoculum was recovered from the biogas slurry. The biogas slurry with high content of N element not only could be used as inoculum to adjust C/N rate of anaerobic digestive substrates, but also applied as plant nutrient solution to realize the recycling of resources. The GHC, VS, and the relative contents of CL, HCL, and C in the biogas residue were lower than those in switchgrass, while the relative contents of LG and N were greater than those in switchgrass.
Table 1. Component Analysis of Inoculum, Switchgrass, Biogas Slurry, and Biogas Residue
*C(N) = TC(TN)/liquid, liquid =1.03 g/mL, §Assume GHCInoculum = GHCBiogas slurry = GHCBiogas residue.
Some components of switchgrass, such as cellulose, hemicellulose, and other organic matters, were efficiently degraded and transformed into biogas, while LG and N were degraded less efficiently, which resulted in a relative increase in the content of these elements. In the biogas residue, the concentration of LG was higher than CL and HCL, indicating the formation of biogas. The majority of N in the biogas residue originated from the inoculum. During the anaerobic fermentation process, the removal rates of TS, VS, CL, HCL, LG, C, and N elements were 43.75%, 49.74%, 51.08%, 49.17%, 7.41%, 36.00%, and 15.83%, respectively. Degradation rate of CL and HCL had important effects on biogas production in anaerobic digestion (Surendra 2015).
Biogas Production from Switchgrass
In the anaerobic digestion process (during which switchgrass produced biogas), the CH4 volume in biogas reached up to 62.32% on day 9 (denoted as d), and then decreased and stabilized between 53% and 56%. The production of biogas and CH4 are shown in Fig. 2. The highest peak of daily gas production appeared on d 4, where daily gas productions of biogas and CH4 were 20.25 and 10.29 NmL∙gVS-1added∙d-1. The CGP of biogas and CH4 were 268.80 and 135.31 NmL∙gVS-1 added, respectively, and the average CH4 content was 50.34%; 80% of the cumulative gas production was reached within the first 22 to 23 days. Barbanti et al. (2014) reported that the highest CH4 DGP was 7.0 NmL∙gVS-1 added∙d-1 at d 10, but the CGP was 216 NmL∙gVS-1 added at d 58. Jin et al. (2014) reported the results of batch digestion studies for ammonia-pretreated switchgrass, where the CH4 DGP was approximately 160 mL∙gVS-1 for 21 days. The main reason for the differences in gas production was the composition of the raw material, especially the lignocellulose content, which can change at different localities and stages of growth.
Fig. 2. Production of biogas and CH4 during anaerobic digestion
MFA model of the anaerobic digestion process
Based on the lab-scale anaerobic digestion process of biogas produced from switchgrass, a model of an open MFA system was established, as shown in Fig. 3. An experimental cycle (EC) was defined as the system time boundary, while the system space boundary was simplified to include only the anaerobic digestion process. With the aid of the model, the flow distribution of materials for different levels were analyzed. The levels of inoculum, switchgrass, biogas, biogas slurry, and biogas residue, the amounts of C and N (substance flow analysis, SFA) and the level of chemical energy fixed in goods (energy flow analysis, EFA) were tracked and analyzed.
Fig. 3. Material flow analysis system model for switchgrass producing biogas
SFA of Anaerobic Digestion Process
The objects subjected to SFA (shown in Table 2) were the flow distributions of C and N. The densities of both the inoculum and biogas residues (liquid) were approximately 1.03 g∙mL-1, while the biogas density (biogas) was approximately 1.34 g∙L-1, calculated at CO2 49.7% and CH4 50.3%. The SFA data were logged and optimized in the MFA model, and the results were shown as a Sankey diagram in Fig. 4.
Fig. 4. Substance flow analysis of switchgrass producing biogas
Table 2. Substance Flow Analysis of the Anaerobic Digestion Process
* C(N)conc= TC(TN)/liquid; § mbiogas= TVbiogas × biogas, Cconc= Mc/Vm/biogas, Vm=22.4 L/mol, MC= 12 g/mol, Nbiogas was ignored; ¶ Substance Flow = Mass Flow × Substance Concentration.
SFA results showed that (1) 36.1% of the raw material of switchgrass was degraded to be transformed into biogas; (2) 30.6% C of switchgrass was degraded to be transformed into biogas in the form of CH4 and CO2, while approximately 3.6% and 65.8% flowed into biogas slurry and biogas residue, respectively; and (3) very little N from the switchgrass was degraded to be transformed into biogas, while 11.7% and 88.3% flowed into biogas slurry and biogas residue, respectively. It is clear that the switchgrass-producing biogas had lower material conversion efficiency after batch anaerobic fermentation. Over 60% of the C and 80% of the N in switchgrass were still stored in fermentation residue, especially within the biogas residue. The rational development of fermentation residues for solid and liquid organic fertilizers may improve the material conversion efficiency of resources, and it also can decrease environmental pollution.
EFA of Anaerobic Digestion Process
EFA data are shown in Table 3. It was assumed that energy contained within the liquid parts of the inoculum and biogas slurry could be ignored, while the GHC of the solid parts were same and equal to the biogas residue. The EFA data were logged and optimized in the MFA model, and the results are shown as a Sankey diagram in Fig. 5.
Table 3. Energy Flow Analysis of the Anaerobic Digestion Process
* Assume: GHCInoculum(TS) = GHCbiogas slurry (TS) = GHCbiogas residue; § GHCbiogas = 20~25 kJ/L, average = 22.5 kJ/L, Energy Densitybiogas= GHCbiogas/biogas; ¶ Energy density = TS × GHC; ♯ Energy flow = Mass flow × Energy Density.
Fig. 5. Energy flow analysis of switchgrass producing biogas
EFA results showed that the energy in raw material was transformed into biogas, biogas slurry, and biogas residue. Only about 30.1% energy in switchgrass was transformed into biogas, and about 57.3% energy still was stored in biogas residue. It is also clear that the switchgrass-producing biogas had lower energy conversion efficiency by anaerobic fermentation. It is important to pay attention to the energy recycling of biogas residues.
- Switchgrass producing biogas had a lower material and energy conversion efficiency. More than half of C, N, and energy were still stored in the fermentation residue, especially in the biogas residue.
- In the batch anaerobic fermentation process for biogas produced from switchgrass, cumulative gas productions of biogas and CH4 were 268.80 and 135.31 NmL∙gVS-1 added, and the average CH4 content was 50.34%.
- The MFA revealed that the rates of C flowing into biogas, biogas slurry, and biogas residue were 30.6%, 3.6%, and 65.8%, respectively; while the rates of N that separately flowed into the biogas slurry and biogas residue were 11.7% and 88.3%.
- When the amount of N in the biogas was ignored, the material and energy conversion efficiency of the fermentation process were 36.05% and 30.1%, respectively.
This research was supported by grants from the National High Technology Research and Development Program (2012AA101802) and Key Deployment Program of CAS (KGZD-EW-304-1).
Ahn, H. K., Smith, M. C., Kondrad, S. L., and White, J. W. (2010). “Evaluation of biogas production potential by dry anaerobic digestion of switchgrass-animal manure mixtures,” Applied Biochemistry and Biotechnology 160(4), 965-975. DOI: 10.1007/s12010-009-8624-x
Aparcana, S., Salhofer, S., and Linzner, R. (2013). “Material flow analysis of formal and informal household waste recycling systems in developing countries. Case studies from Peru,” Waste Management33(3), 774-775. DOI: 10.1016/j.wasman.2013.01.009
Arena, U., and Di Gregorio, F. (2014). “A waste management planning based on substance flow analysis,” Resources Conservation and Recycling 85(4), 54-66. DOI: 10.1016/j.resconrec.2013.05.008
Barbanti, L., Di Girolarno, G., Grigatti, M., Bertin, L., and Ciavatta, C. (2014). “Anaerobic digestion of annual and multi-annual biomass crops,” Industrial Crops and Products 56, 137-144. DOI: 10.1016/j.indcrop.2014.03.002
Brunner, P. H., and Rechberger, H. (2004). Practical Handbook for Material Flow Analysis, CRC Press, Boca Raton, FL. DOI: 10.1201/9780203507209.fmatt
Cha, K., Son, M., Matsuno, Y., Fthenakis, V., and Hur, T. (2013). “Substance flow analysis of cadmium in Korea,” Resources Conservation and Recycling 71(2), 31-39. DOI: 10.1016/j.resconrec.2012.11.005
Chen, H. W., Hsu, C. H., and Hong, G. B. (2012). “The case study of energy flow analysis and strategy in pulp and paper industry,” Energy Policy 43(4), 448-455. DOI: 10.1016/j.enpol.2012.01.037
Chen, P. C., Su, H. J., and Ma, H. W. (2013). “Trace anthropogenic arsenic in Taiwan-substance flow analysis as a tool for environmental risk management,” Journal of Cleaner Production 53(8), 13-21. DOI: 10.1016/j.jclepro.2011.10.041
Clifton-Brown, J. C., Stampfl, P. F., and Jones, M. B. (2004). “Miscanthus biomass production for energy in Europe and its potential contribution to decreasing fossil fuel carbon emissions,” Global Change Biology 10(4), 509-518 DOI: 10.1111/j.1529-8817.2003.00749.x
El-Mashad, H. M. (2013). “Kinetics of methane production from the codigestion of switchgrass and Spirulina platensis algae,” Bioresource Technology 132, 305-312. DOI: 10.1016/j.biortech.2012.12.183
Fang, M., Cao, M. L., Li, Y., and Li, Y. (2012). “Material flow analysis on cement industry,” Advanced Materials Research 512-515, 3042-3046. DOI: 10.4028/www.scientific.net/AMR.512-515.3042
Hu, Z. J., and Ragauskas, A. J. (2011). “Hydrothermal pretreatment of switchgrass,” Industrial and Engineering Chemistry Research50(8), 4225-4230. DOI: 10.1021/ie101886d
Huang, C. L., Vause, J., Ma, H. W., and Yu, C. P. (2012). “Using material/substance flow analysis to support sustainable development assessment: A literature review and outlook,” Resources Conservation and Recycling 68(11), 104-116. DOI: 10.1016/j.resconrec.2012.08.012
Jin, G., Bierma, T., and Walker, P. M. (2012). “Biogas production from switchgrass under experimental conditions simulating U.S. digester operations,” Journal of Environmental Science and Health Part A 47(3), 470-478. DOI: 10.1080/10934529.2012.646150
Jin, G., Bierma, T., and Walker, P. M. (2014). “Low-heat, mild alkaline pretreatment of switchgrass for anaerobic digestion,” Journal of Environmental Science and Health Part A 49(5), 565-574. DOI: 10.1080/10934529.2014.859453
Jurado, E., Gavala, H. N., and Skiadas, I. V. (2013). “Enhancement of methane yield from wheat straw, miscanthus and willow using aqueous ammonia soaking,” Environmental Technology 34(13-14), 2069-2075. DOI: 10.1080/09593330.2013.826701
Massé, D., Gilbert, Y., Savoie, P., Bélanger, G., Parent, G., and Babineau, D. (2010). “Methane yield from switchgrass harvested at different stages of development in Eastern Canada,” Bioresource Technology 101(24), 9536-9541. DOI: 10.1016/j.biortech.2010.07.018
Massé, D., Gilbert, Y., Savoie, P., Bélanger, G., Parent, G., and Babineau, D. (2011). “Methane yield from switchgrass and reed canarygrass grown in Eastern Canada,” Bioresource Technology102(22), 10286-10292. DOI: 10.1016/j.biortech.2011.08.087
Papa, G., Rodriguez, S., George, A., Schievano, A., Orzi, V., Sale, K. L. and Simmons, B. A. (2015). “Comparison of different pretreatments for the production of bioethanol and biomethane from corn stover and switchgrass,” Bioresource Technology 183, 101-110. DOI: 10.1016/j.biortech.2015.01.121
Rechberger, H., Cencic, O., and Fruhwirth, R. (2014). “Uncertainty in material flow analysis,” Journal of Industrial Ecology 18(2), 159-160. DOI: 10.1111/jiec.12087
Smith, J. M., and Tan, B. (2013). Handbook of Stochastic Models and Analysis of Manufacturing System Operations, Springer, New York.
Surendra, K. C. (2015). “Effects of crop maturity and size reduction on digestibility and methane yield of dedicated energy crop,” Bioresource Technology 178, 187–193. DOI: 10.1016/j.biortech.2014.09.055
Toma, Y., Fernandez, F. G., Sato, S., Izumi, M., Hatano, R., Yamada, T., Nishiwaki, A., Bollero, G., and Stewart, J. R. (2011). “Carbon budget and methane and nitrous oxide emissions over the growing season in a Miscanthus sinensis grassland in Tomakomai, Hokkaido, Japan,” GCB Bioenergy 3(2), 116-134. DOI: 10.1111/j.1757-1707.2010.01070
Article submitted: March 26, 2015; Peer review completed: June 10, 2015; Revised version received and accepted: July 3, 2015; Published: September 4, 2015.