Theoretical Assessment of Agro-Waste for Biogas Production Based on Novel Methodology Related to Biochemical Potential

Abstract

Agricultural and waste biomasses present viable solutions for utilization in the energy sector, achieving sustainable and long-term transformation into energy and fuel. However, it is important to carefully evaluate the competing applications for these feedstocks, considering both short- and long-term stability. Biomass for biogas production in agriculture and waste management is used due to its availability and ease of handling. Considering everything mentioned, evaluating the most suitable raw materials for biogas production is crucial for meeting sustainability criteria and promoting biomass as an energy source. In this paper, an examination of different biomass sources as possible feedstock to produce biogas by applying a theoretical approach to the proximate and final analysis results of those materials is presented. Based on data from the raw material analysis, the theoretical biochemical methane potential (TBMP) for the considered samples was calculated. Furthermore, the mass and energy balance for the case study biogas plant was also performed. According to the obtained results, the considered feedstocks show the validity of their use for biogas production considering the fulfillment of the raw material minimum quantity, mandatory residue arrangement, and achieving higher efficiency of the energy conversion process.

1. Introduction

Globally, enormous amounts of agricultural and waste biomasses are produced, offering significant potential for conversion into biofuels through various processes. Technical, socioeconomic, and environmental issues and constraints are discussed to assist stakeholders, energy managers, and decision makers in the sustainable and renewable energy sectors in considering agricultural biomass for energy production on a greater scale [1,2]. Rapid industrialization and environmental pollution have led numerous researchers to examine various sources of biomass used as a raw material to produce biogas. The production of biogas from agricultural biomass plays a crucial role in Europe’s energy transition, offering a promising solution for the energy industry for achieving a sustainable and long-term shift towards energy and/or fuel generation. The biogas sector is transitioning to a new model, where organic waste, agricultural byproducts, and sequential crops are used as primary feedstock, and biogas is upgraded to bio-methane which can have various applications (transportation, chemical manufacturing, heat generation, etc.).

The economic viability, substrate efficiency, and environmental factors of several biogas production substrates, including garbage, sewage sludge, straw, wood, bovine manure, pig manure, chicken manure, and maize silage, were evaluated and compared [3]. According to the researchers, pig dung is the best raw material for Latvian biogas generation, followed by poultry manure. According to most research, anaerobic digestion (AD) is a highly efficient alternative technology that combines biofuel production with sustainable waste management, offering both environmental and economic benefits [4,5,6]. Agricultural biomass fruits and vegetable wastes were used in a process of anaerobic digestion [4] to analyze the cost of production. In a simulated project created using SuperPro Designer software version 8.5, the concentration of methane was increased to 95% (v/v) after purification, while the biogas produced contained 55% (v/v) methane from a total of 936.8 m³/h. The technique was able to reduce the initial COD by more than 60% (chemical oxygen demand). The economic analysis of the study also showed that the profit margin was achieved. The authors of the study [5] provided a summary of the process of producing biogas from lignocellulosic waste and demonstrated that various lignocellulosic sources, including manure or fruit and vegetable wastes, can be utilized to produce biogas. Given the low cost of accessible feedstocks, the variety of applications of biogas, and the potential to increase AD control and efficiency, more investments in AD are expected to achieve greater success. The suitability of several grain straw pellets for anaerobic digestion was examined, along with the corresponding untreated straw [6]. Tests of both pelletized and unpelletized straws were conducted to assess the biochemical methane potential (BMP) and the chemical-physical properties. Pelletizing increased the methane yield from 274 to 286 NL CH4/kg VS. Due to their higher C/N ratios, straw pellets and straw, in general, can be effectively co-digested with nitrogen-rich materials.

Interest in producing biogas from lignocellulosic biomass through anaerobic digestion has grown, as methane is one of the primary byproducts. Algae and aquatic plants present a promising, efficient, and sustainable option for biogas production, delivering high methane yields. An additional advantage is that they can be obtained from wastewater treatment processes and therefore they can be applied to the biorefinery concept [7].

Biogas and ethanol can be produced from lignocellulosic raw materials such as winter rye straw, oilseed rape straw, and bean straw [8]. It was demonstrated that wet oxidation pretreatment was essential for ethanol production from all raw materials, but only winter rye straw produced higher biogas yields. However, biogas productivity needs to be optimized from winter rye straw, oilseed rape straw, and bean straw to increase gas production levels. With the proper selection of local crops, biomass production appears promising for supplying society with resources for energy production. Additionally, autumn tree leaves could potentially be utilized as a feedstock for biogas production [9]. Three scenarios were used in this study to assess the usage of tree leaves from Berlin parks: the pretreatment of leaves before biogas production, composting (business as usual scenario), and biogas production. To estimate greenhouse gas emissions and the potential for energy generation for several scenarios, the BIORIM (Biological Resource Utilization Impacts) model was employed, taking into consideration the location and capacity of an existing agricultural biogas plant. In terms of greenhouse gas emissions, the comparison showed that the scenarios involving biogas performed better (−140.1 kg of CO₂ eq per ton of leaves for biogas and −167.4 kg of CO₂ eq for pretreatment before biogas). The lowest net emissions and highest energy production per ton of feedstock was obtained by pretreated leaves. Using tree leaves as a feedstock for biogas presents an opportunity to reduce the need for fossil fuels and decrease the need for importing electricity into urban energy grids. In recent research [10], the authors examined the effects of a mechanical pretreatment on the methane yield of giant reed stems and wheat straw. According to the authors, pretreated giant reed stems produced more biogas than 212 Nm³/t of volatile solids, which is a 137% increase over the raw material. Additionally, pretreated straw produced a cumulative methane yield of 250.3 Nm³/t, which is a 49.1% increase over the feedstock. The results of this study [10] indicate that the pretreatment investigated could be effectively applied to enhance methane production efficiency in anaerobic digesters. Numerous studies conducted on full-scale biogas plants using mechanical pretreatments have shown that the results of BMP tests provide a reliable prediction of actual biogas production. In recent years, significant advancements in science and technology related to thermochemical biomass conversion have been made, where incineration, gasification, pyrolysis, and catalysis [11,12,13] conversion are among the best available thermochemical technologies. Catalytic pyrolysis technology can be used to convert agricultural biomass into energy-producing high-quality renewable fuels [11]. The obtained biogas has high yields and stability and it was shown that the production of biogas via catalytic pyrolysis is environmentally friendly and economically feasible for clean energy production. Hazelnut shells are highly promising as combustion fuel because, during high-temperature pyrolysis, they produce a larger proportion of gaseous products, especially hydrogen, which significantly enhances their energy density compared to other systems. Using simultaneous thermal analysis and mass spectrometry, the slow pyrolysis properties of feedstocks made from agricultural residues (corn brakes, wheat straw, and hazelnut shells) were examined [12]. It has been determined that hydrothermal carbonization is a very efficient thermochemical method for converting biomass into multifunctional products, such as the carbon-rich substance hydrochar, from wet and wasted biomass [13]. The hydrothermal carbonization (HTC) of waste biomass produces hydrochar with excellent potential as a biofuel. HTC was performed on maize cobs, paulownia leaves, and olive pomace to assess their potential for future usage as an alternative energy source. The objective was to investigate how the process temperature affected the composition and properties of the generated hydrochars. According to the results, all samples of hydrochar yields dramatically decline as the temperature rises. However, it has been known for long that biomass’s inorganic content (ash) has a significant impact on the thermochemical conversion process [14]. The commercial implementation of large-scale biomass thermochemical conversion faces obstacles from cost-efficient and efficient remediation technologies of inorganic pollutants. The first and most crucial step in processing biomass is pretreatment, which increases the effectiveness of handling, processing, and conversion. Inorganic pollutants can be effectively removed using pretreatment procedures to reduce concentration limits.

Securing deposits and the need for alternative feedstocks are growing since the number of biogas plants has increased. Animal wastes (manures and slurries), lignocellulosic biomasses, energy and sequence crops and silages, and agricultural co-products are the primary inputs for agricultural biogas plants. It is essential to gain a better understanding of key chemical properties (such as organic matter, fibers, proteins, elemental analysis, and C/N ratio), along with assessing the biochemical methane potential to assist industrial and biogas operators. Another crucial factor is the feedstock’s C/N ratio, which needs to be between 20 and 30 for an effective anaerobic digestion process [15]. The composition of fibers (cellulose, hemicellulose, and lignin) and proteins is crucial as it impacts the final biodegradability of the substrates. Finally, elemental analysis data (C, H, N, S, and O) is very important because it enables the determination of both theoretical chemical oxygen demand (COD) and theoretical methane potential, according to the Buswell equation. In addition to chemical properties, the biochemical methane potential (BMP) tests are crucial for determining the methane potential. The biochemical methane potential enables the laboratory-scale measurement of the maximum methane production from the digestion of a single substrate. In recent years, numerous national and international inter-laboratory studies have been conducted to refine the protocol and define good practices [16,17].

To establish a material balance for evaluating the quality of the produced biogas, in this paper, the theoretical analysis of the possibility of using various raw materials for biogas production is presented. The evaluation of various raw materials was determined using the theoretical biochemical methane potential (TBMP) criterion, which is an indicator of the yield and quality of biogas, where commonly used raw materials will be considered to obtain the highest quality of biogas. In this manuscript, the key improvements, in comparison to already published studies that deal with this approach, are related to involve the content of volatiles in calculations of TBMP and highlight the differences between the TBPM and the theoretical biochemical potential of biogas (TBPB), which includes all other gasses (CO₂, NH₃, and H₂S, besides CH₄) in the biochemical transformation of raw material. This may be crucial for enhancing the forecast of biogas yield from various feedstocks that are likely to produce those gasses. Furthermore, in this study, mass and energy balances were created for the biogas plant case study to analyze the energy efficiency justification of different biomass feedstocks for biogas production.

2. Materials and Methods

The potential for biogas production was analyzed for ten different biomass feedstocks, which are considered as waste material from the agricultural industry and industrial processes. The selection of the potential raw materials was carried out to achieve sustainable production in biogas plants, in regions with little development of the biomass market and limited availability of biogas feedstocks [18]. In this study, the following materials were examined as a raw material for biogas production: poultry litter, pig manure, corn cob, grape pomace, corn stover, sewage sludge (dried), black liquor, soybean oil cake, MSW organic wet fraction, and brewery spent grains. For the selected materials, the data of proximate and ultimate analysis as well as low heating value (LHV) were acquired from the literature to perform the proposed methodology. The data of proximate analysis are necessary for the application of the methodology proposed in this study, and include the values of moisture (M), ash (A), and volatile content (Vg) as well as the content of fixed carbon (C_fix) in the biomass material. Also, the low heating value (LHV) is important information for further energy efficiency assessments. Furthermore, the chemical composition of the raw material must be determined to apply molar balancing, within the proposed model, to a particular feedstock. The elements that the model considers are carbon (C), hydrogen (H), oxygen (O), nitrogen (N), and sulfur (S). The values and relative ratios of these components can be derived from determined values from the ultimate analysis of the considered raw materials.

To obtain the reliable and uniform set of data for all considered biomass materials, the data were taken from the Phyllis database [19]. The data of LHV, proximate and ultimate analysis, and the Phyllis database identifier for each considered raw material for biogas production are given in Table 1.

The Calculation of the Theoretical Biochemical Methane Potential (TBMP)

According to different authors, a methodology for the calculation of the theoretical biochemical methane potential (TBMP) of the biogas feedstocks is based on data of ultimate analysis of the considered biomass material [20]. By this approach, numerous simplifications were made to establish the material’s TBMP, which allows researchers to make it more complex [20]. The following assumptions were commonly adopted to significantly decrease the calculation time:

• Constant temperature and perfect mixing.

• Ideal bacterial conditions, meaning full digestion.

• Input waste consists of only C, H, O, N and S.

• Products of reaction include only CH₄, CO₂, NH₃ and H₂S.

• No accumulation of ashes.

Based on the provided assumptions and Boyle’s formula (modified Buswell equation), which includes the nitrogen and sulfur content, the following equation can be established:

(1)${\mathrm{C}}_{\mathrm{a}}{\mathrm{H}}_{\mathrm{b}}{\mathrm{N}}_{\mathrm{c}}{\mathrm{S}}_{\mathrm{d}}{\mathrm{O}}_{\mathrm{e}}+n_{H_{2}O}{\mathrm{H}}_2\mathrm{O}\to n_{C{H}_4}{\mathrm{CH}}_4+n_{C{O}_2}{\mathrm{CO}}_2+n_{N{H}_3}{\mathrm{NH}}_3+n_{H_{2}S}{\mathrm{H}}_2\mathrm{S}$

Based on the molar balances for each element in Equation (1), the number of moles for the reactants and products of the reaction could be calculated as follows:

(2)$n_{C{H}_4}={\displaystyle \frac{1}{2}}a-{\displaystyle \frac{1}{4}}e+{\displaystyle \frac{1}{8}}b-{\displaystyle \frac{3}{8}}c-{\displaystyle \frac{1}{4}}d$

(3)$n_{C{O}_2}={\displaystyle \frac{1}{2}}a+{\displaystyle \frac{1}{4}}e-{\displaystyle \frac{1}{8}}b+{\displaystyle \frac{3}{8}}c+{\displaystyle \frac{1}{4}}d$

(4)$n_{N{H}_3}=c$

(5)$n_{H_{2}S}=d$

(6)$n_{H_{2}O}=a-{\displaystyle \frac{1}{2}}e+{\displaystyle \frac{3}{4}}c+{\displaystyle \frac{1}{2}}d-{\displaystyle \frac{1}{4}}d$

According to the balanced number of moles, the Boyle’s approach proposes that a material’s theoretical biochemical methane potential (TBMP) can be determined by the following equation:

(7)$TBMP={\displaystyle \frac{22.4\cdot \left(\frac{a}{2}+\frac{b}{8}-\frac{c}{4}-\frac{3d}{8}-\frac{e}{4}\right)}{12.017a+1.0079b+15.999c+14.0067d+32.065e}}$

The overall amount of biogas produced in the digester is impacted by the previously defined assumptions. Since the hypothetical potential of a complete reaction will not be attained, the limiting factor (f) should be utilized, in order to produce accurate results and to eliminate the disparity between the amount of biogas that is predicted and that which is actually produced. By application of the limitation factor, the adjusted value of TBMP is calculated according to the formula:

(8)$TBM{P}_{adj}=TBMP\cdot f$

The previous adjustment performed by the application of Equation (8) is necessary due to the fact that anaerobic digestion reactions are incomplete. In this approach, the reduction in large discrepancies in the performed calculations was achieved by using the limiting factor which considers aspects like the presence of toxins, inadequate mixing, the establishment of microbial populations, the complexity of lignin structure, and other process condition effects (pH, temperature, and redox). All of these are encouraged in the framework of mathematical manipulation, as cited by Almomani and Bhosale [21]. The development of a model that considers all potential outcomes and has several factors would be challenging and outside the purview of small-scale biogas producing activities from farmers. To convert the gas produced under (unrealistic) ideal conditions into the gas produced under real ones, a value of 80% is utilized for f [21].

The calculated TBMP data give the maximum possible theoretical potential of biogas production from the considered raw material and do not consider the characteristics of the real plant, nor possible losses during the process. In this sense, the calculated TBMP value cannot be used to determine the actual capacity of the biogas plant but can be used to assess the potential of the raw material for production, i.e., in comparison with other raw materials used for biogas production.

To further improve the actual methodology, with the adoption of all of the previously defined assumptions, and based on number of moles for the reactants and products of the reaction from Equations (2)–(6), the theoretical composition of the biogas from the considered raw material could be calculated by the following equations:

(9)$y_{C{H}_4}={\displaystyle \frac{n_{C{H}_4}}{n_{C{H}_4}+n_{C{O}_2}+n_{N{H}_3}+n_{H_{2}S}}}$

(10)$y_{C{O}_2}={\displaystyle \frac{n_{C{O}_2}}{n_{C{H}_4}+n_{C{O}_2}+n_{N{H}_3}+n_{H_{2}S}}}$

(11)$y_{N{H}_3}={\displaystyle \frac{n_{N{H}_3}}{n_{C{H}_4}+n_{C{O}_2}+n_{N{H}_3}+n_{H_{2}S}}}$

(12)$y_{H_{2}S}={\displaystyle \frac{n_{H_{2}S}}{n_{C{H}_4}+n_{C{O}_2}+n_{N{H}_3}+n_{H_{2}S}}}$

where y_i/kmol kmol⁻¹ and n_i/kmol represent the mole fraction and number of moles for each component (considered gas) in the analysis.

Based on the composition, the biogas thermophysical characteristics and LHV are calculated according to the following series of equations:

(13)$M_{biogas}=y_{C{H}_4}\cdot M_{C{H}_4}+y_{C{O}_2}\cdot M_{C{O}_2}+y_{N{H}_3}\cdot M_{N{H}_3}+y_{H_{2}S}\cdot M_{H_{2}S}$

(14)${\rho }_{biogas}={\rho }_{C{H}_4}\cdot M_{C{H}_4}+{\rho }_{C{O}_2}\cdot M_{C{O}_2}+{\rho }_{N{H}_3}\cdot M_{N{H}_3}+{\rho }_{H_{2}S}\cdot M_{H_{2}S}$

(15)$LH{V}_{biogas}=y_{C{H}_4}\cdot LH{V}_{C{H}_4}+y_{N{H}_3}\cdot LH{V}_{N{H}_3}+y_{H_{2}S}\cdot LH{V}_{H_{2}S}$

where M_i/kg kmol⁻¹, ρ_i/kg m⁻³, and LHV_i/MJ kg⁻¹ represent the molar mass, density, and low heating value of each component. Taking into consideration the theoretical number of moles for methane and the content of volatiles in the specific feedstock, the theoretical biochemical potential of methane (TBPM) in this study is calculated according to the formula:

(16)$TBPM={\displaystyle \frac{n_{C{H}_4}\cdot 22.4}{g_{VG}}}\cdot 100$

where g_VG is the mass fraction of volatile content based on the proximate analysis data. Furthermore, to perform mass and energy balancing for the case study of the biogas plant, the theoretical biochemical potential of biogas (TBPB) could be determined as:

(17)$TBPB={\displaystyle \frac{\left(n_{C{H}_4}+n_{C{O}_2}+n_{N{H}_3}+n_{H_{2}S}\right)\cdot 22.4}{g_{VG}}}\cdot 100$

According to TBPB, the mass fraction of biogas in the base raw material could be calculated as:

(18)$g_{biogas}=TBPB\cdot {\rho }_{biogas}\cdot {10}^{-3}$

where ρ_biogas/kg m⁻³ represents the density of the produced biogas.

The specific amount of the process water (APW) required for the biogas production is calculated as follows:

(19)$APW={\displaystyle \frac{\left(n_{H_{2}O}\cdot 18.01-g_M\right)\cdot {10}^6}{998.2}}$

where g_M is the mass fraction of moisture for the considered feedstock based on the proximate analysis.

For the case study of the biogas plant, a capacity (P) of 200 kW is considered in the further analysis. Based on the adopted product capacity, the amount of feedstock for biogas production is calculated according to the formula:

(20)$B_{feedstock}={\displaystyle \frac{P}{LH{V}_{biogas}\cdot g_{biogas}}}\cdot 3.6$

while the volume flow of the process water is:

(21)$B_{water}=APW\cdot B_{feedstock}$

Based on the obtained flows, for the case study of the biogas plant, the mass balances for 24 h plant operation (in tons) are calculated according to the following equations:

(22)$m_{feedstock}=B_{feedstock}\cdot 24$

(23)$m_{processwater}=B_{water}\cdot 24\cdot {10}^{-3}$

(24)$m_{rawmaterial}=m_{feedstock}+m_{processwater}$

(25)$m_{biogas}=g_{biogas}\cdot m_{feedstock}$

(26)$m_{sludge}=m_{feedstock}-m_{biogas}$

(27)$m_{solid}=m_{sludge}\cdot \left(1-g_M-g_{VG}\right)$

(28)$m_{wastewater}=m_{sludge}-m_{solid}$

The volume of produced biogas for 24 h of the operation of the biogas plant is calculated according to the following equation:

(29)$V_{biogas}={\displaystyle \frac{m_{biogas}}{{\rho }_{biogas}}}\cdot {10}^3$

To assess the energy efficiency of the biogas production plant, the energy input/output efficiency (EEIO) for the considered feedstocks is determined as the ratio of energy output (produced biogas) and energy input (used feedstock) in the biogas plant based on the following equation:

(30)$EEIO={\displaystyle \frac{V_{biogas}\cdot LH{V}_{biogas}}{m_{feedstock}\cdot LH{V}_{feedstock}}}\cdot 100$

According to the provided Equations, a schematic overview of the proposed methodology is shown in Figure 1.

3. Results and Discussions

The selection of the biomass samples was made to include the main categories of the biomass, which shows the potential for utilization in biogas plants.

According to the data presented in Table 1, it can be concluded that the moisture content of all considered biomass samples is within the range of 1.88% up to 16.69 wt. %. The lowest value for the moisture content is for corn cob. which is in accordance with the literature data for this type of biomass [22], and it is highly related to the phase of the biomass production and utilization. Corn cobs are generated through the agricultural production process of maize and belong to the waste material which can be utilized in the energy sector as a residue from agricultural production. Additionally, the highest content of moisture is determined in a municipal solid waste sample, considered as a raw material for the biogas plant, which is mainly composed of the organic waste material with a higher content of water in it. The moisture content of the biogas feedstock is important since it directly determines the amount of water which should be included in the technological process.

Furthermore, to achieve a higher amount of methane yield, the important data of proximate and ultimate analysis are related to carbon and hydrogen content as well as the content of volatiles in the raw material. According to these criteria, the grape pomace and brewery spent grain samples have a high potential for methane production as a key component of the biogas product. Regarding the energy input, the highest LHV among all considered samples is found int the two samples mentioned above, and this is expected due to the presented data.

According to the methodology provided in the previous section, the calculations of the biogas composition for all considered biomass feedstocks are presented in Figure 2. This is performed to assess the selection of the raw materials for efficient and sustainable biogas production.

The data presented in Figure 2 confirm the earlier statement regarding the selection of the raw materials which have the highest potential for methane yield. As can be seen in Figure 2d,j for the grape pomace and brewery spent grains, the methane yield amounts to 51.74% vol and 51.11% vol, respectively. However, the highest yield can be noticed for the black liquor and MSW organic wet fraction samples (Figure 2g,i), but this is a consequence of the application of the total molar balancing of elements. This refers to the fact that all atoms of carbon and hydrogen in feedstocks are considered to be utilized for methane formation. However, for those two samples, the content of volatiles is noticeably lower (42.4 and 44.48 wt. %, according to Table 1) and that will lead to the conclusion that the real yield of gaseous methane could be much lower than it is expected to be due to molar balancing. In that sense, the proposed methodology for the determination of the TBPM must take the content of the volatiles into consideration, and that is what was proposed by introducing Equation (16) in the previous section. Furthermore, in order to perform the material balance of the biogas production process, the total amount of biogas is represented as TBPB (given by Equation (17)), and it will be used for further analysis of the biogas plant operation. The results of TBPM and TBPB for all considered feedstocks for biogas production are presented in Figure 3.

By analyzing the results presented in Figure 3, it can be seen that grape pomace has the highest values of TBPM and TBPB among all considered raw materials due to the ratio of carbon, hydrogen, and volatile content. Also, it can be noticed that samples like black liquor and MSW organic wet fraction, the methane content of which shows the highest values in biogas composition (by material balancing) (Figure 2), have lower values of TBPM and TBPB than sewage sludge and pig manure, for example. That issue is mainly due to the lower content of volatiles in the raw sample. By this approach, the TBPM values do not need the adjustment factor (f) presented in Equation (8), and the adjustment is automatically performed by including the content of volatiles for the considered sample. That is the primary explanation for the significant discrepancies between the TBPM values estimated using the suggested methodology and those from the literature, TBPM_adj [20]. TBPM_adj accounts for the complete transformation of carbon and hydrogen into CH₄ without examining the volatility of the molecules to which they are linked. Furthermore, the formation of other gasses (such as CO₂, NH₃, and H₂S) is not included in the analysis of TBPM_adj. Because of that, the values of TBPM and TBPB calculated by the approach presented in this manuscript are much closer to the real operational values of biogas yield in the plant operation according to the literature [23].

The determination of the chemical composition of the produced biogas, however, should be corrected by the volatile content, as shown above, and should be used for the assessment of the energy yield in the production of biogas as fuel for further energy production. In that sense, according to the theoretical chemical composition presented in Figure 2, and by application of Equation (15) from the previous section, the theoretical LHVs of the produced biogas from all considered raw materials are presented in Figure 4. Figure 4 logically shows the highest values for the samples where the theoretical amounts of methane are higher. However, for some samples (for example, sewage sludge), the higher theoretical LHVs are a consequence of the higher amount of ammonia in the biogas composition, which has a non-negligible LHV (13.6 MJ/m³), according to the literature [24].

Furthermore, in order to analyze the efficiency of the biogas plant operation, the mass balance for the case study, a biogas plant of 200 kW capacity and for a 24 h operation, was performed. The methodology is presented by a set of equations labeled as Equations (22)–(28). The masses of feedstock and process water as the input and biogas, waste water, and solid residue as the output of the process are considered in order to establish the mass balance of the case study (biogas plant operation) for all considered raw materials. The results of all these analyses are given in Figure 5.

By analyzing the presented results, it could be concluded that the lowest amount of feedstock for defined capacity plant is for the sample grape pomace as a raw material. On the other hand, the lowest amount of process water necessary for the plant operation is for the sample MSW organic wet fraction and it is due to the highest content of moisture in the considered sample.

Furthermore, soybean oil cake produces the highest amount of waste water (7.02 t) and black liquor and corn stover produce the highest content of solid residue (2.87 t and 2.72 t, respectively). This could be explained with the highest content of ash and fixed carbon which those two samples have, according to Table 1. Based on the adopted case study’s biogas plant operational data, the soybean oil cake sample produces the highest mass of biogas (1.31 t), and that is also to be expected due to Figure 4 and the lowest theoretical LHV of biogas produced from the actual sample. The overall mass balance based on the theoretical approach could provide the ratios of the amounts for different feedstocks and that is especially important for the planning of new biogas plants in order to fulfill the logistics requirements [25].

The final analysis in this study is presented in Figure 6 and considers the determination of the total volume of produced biogas, as adopted for the case study of biogas plant data, the mass of utilized feedstock, and the energy input/output (EEIO), as defined by Equation (30).

According to the results presented in Figure 6, it could be concluded that the black liquor sample has the best energy input/output efficiency ratio and it is the only one close to 30%. All other samples show low EEIO (below 20%) due to the high amount of utilized feedstock, with relatively high LHV of raw material, for producing a relatively small volume of biogas with higher LHVs than an initial raw material. However, this analysis does not include the efficiency of the biochemical transformation as well as energy consumption for the raw material pretreatment (drying and size reduction). Also, by this analysis, it could be shown that the soybean oil cake and pig manure samples produce the largest volume of the biogas, but according to the previous analysis, with lower quality and with poor EEIO. This is also an important issue regarding the selection of the raw materials and the possible utilization of the produced biogas. It is important to note that many types of the organic waste considered in this study have other uses beyond their use for anaerobic digestion. For example, sewage sludge can be spread on land, agricultural wastes can be burned to produce energy, manure can be spread on land providing significant contents of nitrogen, phosphorus, and potassium, and the organic portion of MSW can be turned into compost. Each of these alternative uses of organic waste has its own advantages and disadvantages, and the optimal use of the waste will be determined by local conditions. However, it is not the aim of this paper to compare anaerobic digestion with other technologies for waste valorization, as shown in studies that use the economic return of different technologies with different raw materials [26]. It is worth observing that anaerobic digestion can be often used in conjunction with, rather than as an alternative to, other valorization technologies. The presented analysis may allow researchers to achieve the full potential of anaerobic digestion for methane production which is deduced from the proposed methodology, and this can be summarized through important items such as (a) the identification of operating conditions that maximize methane yield for various feedstocks, (b) progress on the anaerobic digestion of lignocellulosic biomass, and (c) the optimization and maximization of methane yield tailored to the considered feedstocks for full-scale biogas plants.

4. Conclusions

According to the proposed methodology including selected raw materials for efficient and sustainable biogas production, the performed analysis could provide the following advantages:

• The theoretical biochemical potential of methane (TBPM) should include the content of the volatile matter as data for the proximate analysis of raw material, to avoid using a “universal” adjusting factor independent of the used feedstock and to provide more realistic data for real biogas plant operational yield.

• The application of theoretical molar balance for the considered feedstocks in this study shows that the highest quality of biogas with a high LHV could be achieved if it was produced from the black liquor sample (20.595 MJ/m³). However, by considering the TBPM and TBPB values calculated for the considered samples, the optimal quality/amount ratio should be achieved with the grape pomace sample.

• The traditionally used raw materials for biogas production, poultry litter and pig manure samples, show that quality expressed by the LHV is in inverse proportion to the amount expressed by the TBPM and TBPB. Poultry litter has a higher LHV but lower TBPM and TBPB values than the pig manure sample. This issue is mainly related to lignocellulosic content, and the content of protein, phosphorus, potassium, and nitrogen in the raw material.

• The establishment of the mass balance of the adopted case study biogas plant data shows that the amount of feedstock and the required process water are highly dependent of the proximate and ultimate analysis of the raw material. Furthermore, the amount of wastewater and solid residue should be considered for all considered feedstocks, because they represent a significant amount in the product of the considered process.

• The performed assessment derived from the proposed theoretical approach and the energy input/output values show that the energy efficiency of biogas production could be increased since biochemical conversion is a highly energy-demanding process.

This study outlines a theoretical approach that relies on fundamental balances to assess the potential use of various biomass feedstocks as raw materials for biogas plants. Future work will involve validation studies on real biogas plants, incorporating operational parameters and uncertainty analysis into the methodology [27] to enhance prediction accuracy.

Author Contributions

Conceptualization: M.B., B.J. and N.M.; Methodology: N.M.; Formal analysis and investigation: M.B.; Writing—original draft preparation: B.J. and N.M.; Writing—review and editing: M.B. and N.M.; Funding acquisition: N.M.; Resources: N.M.; Supervision: M.B. and N.M. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

Data will be made available on request.

Acknowledgments

The authors would like to acknowledge the financial support of the Ministry of Education, Science and Technological Development of the Republic of Serbia, under contract numbers 451–03-65/2024–03/200105 and 451–03-66/2024–03/200017.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Footnotes

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Figures and Table

Figure 1. The schematic overview of the proposed methodology.

Figure 2. The theoretical biogas composition for considered feedstocks presented as radar graphs (a)-Poultry litter, (b)-Pig manure, (c)-Corn cob, (d)-Grape pomace, (e)-Corn stover, (f)-Sewage sludge, (g)-Black liquor, (h)-Soybean oil cake, (i)-MSW organic wet fraction, (j)-Brewery spent grains.

Figure 2. The theoretical biogas composition for considered feedstocks presented as radar graphs (a)-Poultry litter, (b)-Pig manure, (c)-Corn cob, (d)-Grape pomace, (e)-Corn stover, (f)-Sewage sludge, (g)-Black liquor, (h)-Soybean oil cake, (i)-MSW organic wet fraction, (j)-Brewery spent grains.

Figure 3. Calculated values of TBPB and TBPM for all considered feedstocks compared with the literature data for TBPMadj (Achinas et al., 2016 [20]).

Figure 4. The low heating value (LHV) of the biogas produced from the considered feedstocks.

Figure 5. Mass balance of biogas plant operation for considered feedstocks, represented by Sankey flow charts (a)-Poultry litter, (b)-Pig manure, (c)-Corn cob, (d)-Grape pomace, (e)-Corn stover, (f)-Sewage sludge, (g)-Black liquor, (h)-Soybean oil cake, (i)-MSW organic wet fraction, (j)-Brewery spent grains.

Figure 5. Mass balance of biogas plant operation for considered feedstocks, represented by Sankey flow charts (a)-Poultry litter, (b)-Pig manure, (c)-Corn cob, (d)-Grape pomace, (e)-Corn stover, (f)-Sewage sludge, (g)-Black liquor, (h)-Soybean oil cake, (i)-MSW organic wet fraction, (j)-Brewery spent grains.

Figure 6. Amount of produced biogas and utilized feedstock with assessed energy input/output efficiency (EEIO).

Table 1

Proximate and ultimate analysis data from Phyllis database for considered feedstocks [19].

Phyllis	Biomass	M	A	V g	C fix	C	H	N	S	O *	LHV
ID	Sample					% wt.					MJ/kg
#3621	Poultry litter	9.71	12.91	62.84	14.54	38.7	4.99	3.56	0.58	29.55	14.93
#1715	Pig manure	12.7	13.27	54.91	19.12	38.12	3.65	2.16	0.42	29.68	14.47
#2791	Corn cob	1.88	3.06	76.7	18.36	45.64	5.57	0.46	0.08	43.31	15.05
#1485	Grape pomace	9.81	3.79	67.1	19.3	49.55	5.26	1.88	0.19	29.52	18.27
#890	Corn stover	5.90	20.3	60.13	13.67	35.57	4.55	0.61	0.08	32.99	12.50
#2877	Sewage sludge	7.61	24.16	58.67	9.56	36.36	5.25	5.51	1.06	20.05	15.09
#1394	Black liquor	9.40	36.42	42.4	11.78	26.46	3.99	0.13	4.44	19.16	9.00
#2848	Soybean oil cake	9.50	6.3	69.28	14.92	35.11	5.2	6.01	0.00	37.88	13.93
#3199	MSW organic wet fraction	16.69	30.07	44.48	8.76	28.69	3.47	1.41	0.8	18.87	11.61
#3578	Brewery spent grains	6.6	3.55	75.39	14.46	45.64	6.38	3.44	0.035	34.35	18.46

* Calculated by the difference.

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