Techno-Economic Analysis of Biogas Production from Slaughterhouse Biowastes, in Mekelle City, Tigray, Ethiopia

Techno-Economic Analysis of Biogas Production from Slaughterhouse Biowastes, in Mekelle City, Tigray, Ethiopia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Techno-Economic Analysis of Biogas Production from Slaughterhouse Biowastes, in Mekelle City, Tigray, Ethiopia Fentahun Abebaw Belete, Goitom Gebreyohannes Berhe, Tesfaldet Gebregerges Gebreegziabher, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3795026/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The utilization of biomass energy such as biogas is currently getting a growing interest by researchers and the final destination of the process is its overall cost, and the profit gained. This study aims on the production of biogas from slaughterhouse biowastes (blood, manure, and rumen content) at optimal conditions, clean-up it and evaluate its feasibility. Calcium oxide and steel wool were used to remove CO 2 and H 2 S respectively. The methane content of raw biogas and upgraded biogas are 67.20% 0.435% and 82.458% 0.503% respectively. The major fertilizing values (nitrogen, phosphorus, and potassium) content of the digestate were recorded 11,573.00, 392.40, and 426.85 mg/kg respectively. From the economic analysis, urnover ratio, rate of return on investment, payback period, and the production capacity (%) at the break-even point were estimated as 0.22, 12.63%, 4.08 years, and 16.67% respectively. Moreover, a positive value for the net present value (NPV) ($2,949,848.99), as well as 40.37% of the discount cash flow rate of return was obtained. The profitability analysis results indicate that the biogas production process is feasible and acceptable. Physical sciences/Engineering/Chemical engineering Physical sciences/Engineering/Energy infrastructure Anaerobic digestion Biogas Digestate Fertilizing values Methane Slaughterhouse biowastes Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. INTRODUCTION The fast-growing of world population, urbanization, and industrial development, the discharge of wastes from different sources are increasing from time to time. The growing dearth of petroleum and coal, deforestation of jungles for cooking and heating purposes, and problems related to the emission of greenhouse gases such as uncontrolled methane (CH 4 ), carbon dioxide (CO 2 ), hydrogen sulfide (H 2 S), and other trace gases lead to the global warming of the Earth’s surface (Genet et al., 2018 ). Hence, to ameliorate the worsening impacts of global warming, recent research undertakings are geared towards finding alternate energy from renewable sources in a sustainable manner. There are numerous types of renewable energy sources available including hydropower, wind energy, solar energy, ocean wave power, and biomass energy. The utilization of these renewable energy sources is limited for various reasons. However, the energy obtained from biomass wastes has a multitude of benefits (Peiris, 2016 ). Besides, its paramount importance in alleviating the problem related to energy supply, it is a waste treatment process furnishing nutrients for agricultural production. Biomass energy, which can substitute for fossil fuel applications with minor upgrading methods, is a significant natural and renewable carbon resource (Peiris, 2016 ). For the sustainable development of the world, renewable biomass waste materials from agriculture, industries, and domestic waste sources should be converted to useful energy forms like bio-hydrogen, biogas, bio-alcohols, etc., through waste-to-energy routes (Kothari et al., 2010 ). Organic and inorganic industrial wastes can easily pollute the environment and can cause serious health problems in the world especially in developing countries like Ethiopia. The majority of these organic wastes are generated from the agro-food industries such as slaughterhouses, meat processing companies, dairy companies, and others industries (US EPA, 2004 ). Biogas as its name suggests is the production of gas from biodegradable materials. It is a combustible gas mainly composed of methane which can be used as cooking fuel, natural gas or to produce electricity by combustion (Kunal et al., 2017 ). Biogas comprises 60–65% CH 4 , 35–40% CO 2 , 0.5-1.0% H 2 S and the rest is water vapor, etc. (Bamboriya, 2012 ). Even if Ethiopia is among methane emitter countries and slaughterhouse biowastes are good sources of biogas production, sufficient consideration of slaughterhouse wastes has not yet been given. Biogas significantly reduces the bulky consumption of fossil fuel and reduces the deforestation of forests that can be used for cooking and heating purposes (Genet et al., 2018 ). Bases on the author’s observation on the study area, the main problems related to most slaughterhouses in developing countries are the production of large amounts of solid and liquid wastes and the absence of waste treatment plants. These problems were also observed in Ethiopia-based slaughterhouses including in the slaughterhouse owned by Abergelle International Livestock Development (AILD) Plc located in the Tigray Regional State. Treating the slaughterhouse biowaste via the anaerobic route can provide energy and organic fertilizers. Detail technical and economic analysis of the treatment plant was not carried out before. The slaughterhouse owned by AILD Plc. located in Mekelle, Tigray, Ethiopia is operating without a waste treatment plant for both solid and liquid wastes. According to the enterprise data, about 9,575,228 kg of untreated slaughterhouse wastes, including manure, blood, and rumen content (RC) are generated annually. Hence, to overcome energy crisis, deforestation of plants, environmental pollution, and global warming; efficient, cost-effective, and environmentally friendly treatment methods such as biogas technology is required. Up to our knowledge there is no any study on techno-Economic Analysis of Biogas Production from Slaughterhouse Biowastes at AILD Plc. The aim of this study is to investigate the techno-economic analysis of biogas production from slaughterhouse biowastes. Specifically it includes characterize the raw materials, produce and upgrade biogas at the laboratory by considering optimal operating parameters from existing literature (optimum feed ratios, optimum temperature value, and optimum pH value), determine the composition (CH 4 , CO 2, and H 2 S) of raw biogas and purified biogas experimentally, determine the nutrient quality (nitrogen, phosphorus, and potassium) of the digestate by-product experimentally, and analyze the economic feasibility of biogas production from slaughterhouse biowastes (manure, blood, and RC) by considering important equipment required for purification and compression at an industrial scale. 2. MATERIALS AND METHODOLOGY 2.1. Study Area The slaughterhouse biowastes was provided by AILD located in Mekelle, Tigrai, Ethiopia and the location of the enterprise is shown in Fig. 1 . It is located in Semien sub-city (Gebeyehu et al., 2018 ). This enterprise produces many organic wastes, including manure, blood, and RC and waste water from the slaughterhouse. All the wastes directly dispose with the environment without any treatment which was often washed and discharged to the environment. 2.2. Materials and Equipment Freshly voided slaughterhouse biowastes (manure, blood, and rumen content) was collected. The physical and chemical composition such as proximate and ultimate analysis of each feedstock was analyzed. The biowastes to water ratio was 1:1. The inoculum used was bio-slurry, which contains active microbes essential for the AD process, collected at Desta Alcohol and Liquor Factory, Mekelle, Tigray, Ethiopia. The percentage of inoculum for anaerobic fermentation of the organic waste was 20% of the volume of the feed sample. The inoculum had a pH, TSS, TDS, and COD of 7.4, 18000 ppm, 37500 ppm, and 75000 ppm, respectively. The major equipment and instruments used were electronic balance to measure the weight of samples and a product. Multiparameter (multi 3410) and COD multimeter were used to measure the BOD and COD content of raw materials. pH meter was used to measure the pH of the mixed feed (blood, manure, RC, and water) and the pH of each sample. A 3 L of the plastic jar was used as an anaerobic digester and a water bath was used as a source of heat for the digestion process. An oven was used to remove the moisture of each sample to estimate the moisture content of the feeds and the samples were burnt in a furnace to determine the ash content of the samples. A small plastic balloon was used to collect the final purified biogas. A flame photometer (SP-FP6450) was used to evaluate the trace amounts of potassium in a digestate/compost by-product. UV-Vis spectrophotometer (UV-6300PC) was used to determine the nitrogen, phosphorus, and sulfur in the samples and the digestate. Orsat apparatus and Tutwiler apparatus were used to determine the CO 2 and H 2 S content of the biogas. 2.3. Method of Biogas Production According to Kothari et al., ( 2010 ), the production of biogas through AD offers significant advantages over others due to less biomass sludge, successful in treating wet wastes of less than 40% dry matter, it is more effective pathogen removal. Due to these reasons, AD is preferable. According to Genet et al., ( 2018 ), the optimum feedstock percentage are 20% blood, 20% manure, and 60% rumen content. Before the digestion stage, the sanitation stage was occured for the reactor to remove pathogens by heating or sterilization it at 60 \(℃\) . The slaughterhouse biowastes (blood, RC, and manure) and water were fed to the digester at a 1:1 ratio where the total volume was 2 liters with a space volume of 1 litter and the reaction was occurred in it and biogas as well as digestate by-product was produced. The optimal operating conditions such as feed ratios, pH value, and temperature was determined based on Genet et al., ( 2018 ). 2.4. Estimation of the Composition of Raw Biogas Biogas is a mixture of methane (CH 4 ), carbon dioxide (CO 2 ), hydrogen sulfide (H 2 S), and traces of water vapor (Nallamothu et al., 2013 ). The composition of biogas was determined at Desta Alcohol and Liquor Factory, Mekelle, Ethiopia. The composition of CO 2 , v/v% was estimated using the Orsat apparatus. Again, the composition of H 2 S, v/v% was determined using the Tutwiler apparatus. Finally, the composition of methane was estimated from the composition of CO 2 and H 2 S. 2.5. Methods of Biogas Upgrading According to (Ray et al., 2016 ), chemical adsorption was used to upgrade/purify biogas using calcium oxide (to remove CO 2 ), and steel wool (to remove H 2 S). Since impurities, reduce the heating capacity of biogas and they are also a health problem, their concentration should be reduced. The raw biogas was first passed through a CO 2 separation unit that contains limestone crystals in it to reduce the concentration of CO 2 . CO 2 was reacting with CaO and produce calcium carbonate (CaCO 3 ). Once the concentration of CO 2 is reduced, the biogas was passed through the H 2 S separation unit, which contains iron oxide in the form of oxidized steel wool or iron turning, to reduce the concentration of H 2 S in the biogas. When the biogas comes in contact with this steel wool, H 2 S was converted into elemental sulfur, and biogas that has higher CH 4 content was produced. 2.6. Estimation of the Composition and Volume of Upgraded Biogas To estimate the composition of the upgraded biogas, the same procedures and apparatus was used as raw biogas. The volume of the upgraded biogas was estimated by determining its mass and density. The mass of the upgraded biogas was determined by weighing the balloon that contains an upgraded biogas and the balloon (free of the biogas). The mass was then the difference between the two masses. 2.7. Determination of Fertilizing Values of the Digestate The major fertilizing values of the digestate i.e. Nitrogen (N), Phosphorus (P), and potassium (K) were estimated by the Department of Geology, Mekelle University, Tigrai, Ethiopia. The trace amounts of potassium were determined in a direct reading type of flame photometer at a wavelength of 766.5 nm and a slit width of 2 nm. Nitrogen (N) and Phosphorus (P) was determined using the UV-Vis spectrophotometer at a wavelength of 570 and 400 nm, respectively with a path length of 1 cm for both elements. The results of the major fertilizing values (N, P, and K) of the digestate were estimated in mg per kg of digestate. 2.8. Techno-Economic Assessments Calculation of capital investment costs, operational costs, and profitability analysis are the main economic evaluations. An order-of-magnitude estimate (ratio estimate) or predesign method was used and the economic analysis was estimated according to the purchased equipment cost, which was evaluated using Aspen plus v11 based on the capacity and construction materials of the unit operations. 2.8.1. Capital Investment Costs It is the sum of fixed capital investment costs and working capital. The fixed capital investment cost is again the sum of direct and indirect costs. Direct costs denote the capital necessary for the installed process equipment with all auxiliaries that are needed for the direct operation process. Indirect costs are costs that are required for construction overhead and for all plant components that are not directly related to the process operation. The description of each parameter was also taken from the techno-economic analysis of a similar study (Xie & Willquist, 2016 ). Working capital for an industrial plant consists of the total amount of money invested in raw materials and supplies carried in stock, finished products in stock and semi-finished products in the process of being manufactured, and accounts receivable. The ratio of working capital to total capital investment varies with different companies, but most chemical plants use an initial working capital amounting to 10 to 20 percent of the fixed capital investment (Tsagkari et al., 2015 ). The economic evaluation was calculated using EXCEL spreadsheet. 2.8.2. Operating Costs It is an expense cost related to the operation of the biogas plant and selling of the products and byproducts. The description of each parameter was also taken from the techno-economic analysis of a similar study (Xie & Willquist, 2016 ). 2.8.3. Analysis of Profitability According to (Hunpinyo et al., 2013 ), the most common methods used for profitability evaluation are turnover ratio, rate of return on investment (ROI), payback period (PBP), break-even analysis, net present value (NPV), and discounted cash flow rate of return based on full-life performance. Therefore, in this study, the profitability analysis was estimated using these methods. According to Perez Garcia, ( 2014 ), the average biogas plant-life (n) is 15 years and the straight-line method was used to evaluate depreciation at the end of each year. The following formulas were used to calcite the profitability analysis. Turnover Ratio = \(\frac{\text{G}\text{r}\text{o}\text{s}\text{s} \text{A}\text{n}\text{n}\text{u}\text{a}\text{l} \text{S}\text{a}\text{l}\text{e}\text{s}}{\text{F}\text{i}\text{x}\text{e}\text{d} \text{C}\text{a}\text{p}\text{i}\text{t}\text{a}\text{l} \text{I}\text{n}\text{v}\text{e}\text{s}\text{t}\text{m}\text{e}\text{n}\text{t}}\) (1) ROI = \(\frac{\text{N}\text{e}\text{t} \text{P}\text{r}\text{o}\text{f}\text{i}\text{t}}{\text{T}\text{o}\text{t}\text{a}\text{l} \text{C}\text{a}\text{p}\text{i}\text{t}\text{a}\text{l} \text{I}\text{n}\text{v}\text{e}\text{s}\text{t}\text{m}\text{e}\text{n}\text{t}}\) *100% (2) PBP = \(\frac{\text{T}\text{o}\text{t}\text{a}\text{l} \text{f}\text{i}\text{x}\text{e}\text{d} \text{c}\text{a}\text{p}\text{i}\text{t}\text{a}\text{l} \text{i}\text{n}\text{v}\text{e}\text{s}\text{m}\text{e}\text{n}\text{t} - \text{S}\text{a}\text{l}\text{v}\text{a}\text{g}\text{e} \text{v}\text{a}\text{l}\text{u}\text{e}}{\text{N}\text{e}\text{t} \text{p}\text{r}\text{o}\text{f}\text{i}\text{t} + \text{D}\text{e}\text{p}\text{r}\text{i}\text{c}\text{i}\text{t}\text{i}\text{o}\text{n}}\) (2) Break-Even Point (BEP) Analysis At the break-even point, the total operating costs are equal to the annual revenue earned. i.e Total operating cost (TOC) = Total Annual sales Again; \(\text{T}\text{O}\text{C} = \text{F}\text{i}\text{x}\text{e}\text{d} \text{c}\text{h}\text{a}\text{r}\text{g}\text{e} \left(\text{F}\text{C}\right) + \text{G}\text{e}\text{n}\text{e}\text{r}\text{a}\text{l} \text{E}\text{x}\text{p}\text{e}\text{n}\text{s}\text{e}\text{s} \left(\text{G}\text{E}\right) + \text{D}\text{i}\text{r}\text{e}\text{c}\text{t} \text{P}\text{r}\text{o}\text{d}\text{u}\text{c}\text{t}\text{i}\text{o}\text{n} \text{C}\text{o}\text{s}\text{t} \left(\text{D}\text{P}\text{C}\right)\) $$\text{F}\text{C} + \text{G}\text{E} + \text{D}\text{P}\text{C} = \text{T}\text{o}\text{t}\text{a}\text{l} \text{A}\text{n}\text{n}\text{u}\text{a}\text{l} \text{S}\text{a}\text{l}\text{e}\text{s}$$ 4 After estimating production capacity at the break-even point using the above equation, the percentage at the break-even point was calculated using the following equation. The biogas production is acceptable for the percentage of break-even point less than the plant operating capacity. BEP, % = \(\frac{\text{P}\text{r}\text{o}\text{d}\text{u}\text{c}\text{t}\text{i}\text{o}\text{n} \text{c}\text{a}\text{p}\text{a}\text{c}\text{i}\text{t}\text{y} \text{a}\text{t} \text{B}\text{E}\text{P}}{\text{A}\text{n}\text{n}\text{u}\text{a}\text{l} \text{b}\text{i}\text{o}\text{g}\text{a}\text{s} \text{p}\text{r}\text{o}\text{d}\text{u}\text{c}\text{t}\text{i}\text{o}\text{n}+\text{A}\text{n}\text{n}\text{u}\text{a}\text{l} \text{c}\text{o}\text{m}\text{p}\text{o}\text{s}\text{t} \text{p}\text{r}\text{o}\text{d}\text{u}\text{c}\text{t}\text{i}\text{o}\text{n}}\) (5) NPV = \(\sum _{1}^{\text{n}}{\left(1+\text{i}\right)}^{-\text{n}}\left(\text{N}\text{P}\text{j}+\text{D}\text{j}+\text{R}\text{e}\text{c}\text{j}\right)-\text{T}\text{C}\text{I}\) (6) Where, i = the discount rate, n = lifetime of the plant, NPj = net profit, Dj = depreciation, Recj = recovery value, and TCI = Total capital investment $$\text{R}\text{e}\text{c}\text{j} = \text{S}\text{a}\text{l}\text{v}\text{a}\text{g}\text{e} \text{v}\text{a}\text{l}\text{u}\text{e} + \text{W}\text{o}\text{r}\text{k}\text{i}\text{n}\text{g} \text{c}\text{a}\text{p}\text{i}\text{t}\text{a}\text{l}$$ 7 Discount Cash Flow Rate of Return (DCFR) The method of approach for a profitability evaluation by discounted cash flow takes into account the time value of money and is based on the amount of the investment that is unreturned at the end of each year during the estimated life of the project. It was estimated by making the NPV zero and determining the discount rate. An excel solver was used for this study to evaluate the discount cash flow rate of return. $$\sum _{1}^{\text{n}}{\left(1+\text{i}\right)}^{-\text{n}}\left(\text{N}\text{P}\text{j}+\text{D}\text{j}+\text{R}\text{e}\text{c}\text{j}\right)-\text{T}\text{C}\text{I}=0$$ 8 3. RESULT AND DISCUSSION In these results, immediate and final analysis, composition of biogas and its valorization effect, main fertilizer value of the waste and economic analysis were performed. The results are discussed below. 3.1. Proximate and Ultimate Analysis of Raw Materials As shown in Table 1 , the proximate and ultimate analysis of manure, blood, and RC were determined separately. BOD, COD, and all the ultimate analyses was done on a wet basis and most of the parameters of this study have the same values as Genet et al., ( 2018 ). According to Genet et al., ( 2018 ), the proximate and ultimate analysis are depends on several factors such as the age of the animal, type of food, type of on-site sanitation system, and way of the sampling method. These results indicate that the raw materials, especially manure, and RC are suitable for biogas production due to their high organic matter content. Table 1 The proximate and ultimate analysis of raw materials Parameters Results of the Study Manure RC Blood Moisture, % 81.75 79.20 85.35 Ash, % 18.08 19.71 17.06 Volatile Matter, % of TS 81.92 87.50 82.94 Fixed Carbon, % 14.20 15.86 11.54 Total Solids, % 18.25 20.80 14.65 pH 8.10 7.40 8.20 COD, mg. l − 1 2,741.00 3,028 1,062.00 BOD, mg. l − 1 1,482.00 1,561.00 526.00 Carbon, % 31.30 29.68 14.01 Nitrogen, % 2.145 3.178 1.562 Sulfur, % 0.82 0.92 0.39 Organic content, % 53.21 50.5 23.8 3.2. Composition and Upgrading Efficiency of Biogas 3.2.1. Composition and Volume of Biogas The average composition (v/v%) of the raw biogas was recorded as 67.2, 32.0, and 0.8% of CH 4 , CO 2 , and H 2 S, respectively (Fig. 2 ). This is due to the high organic content in raw materials especially manure (53.21%) and RC (50.5%). According to Andrade et al., ( 2016 ), biogas production is influenced by feedstock properties; animal species; energetic, protein & fiber content in the diet; digestibility; physiologic stage; age; animal production systems; and environmental conditions. As shown in Fig. 3 , the average contents of upgraded methane, carbon dioxide, and hydrogen sulfide contents were recorded as 82.458, 17.5, and 0.042% respectively. The upgrading process was performed at room temperature. Methane content can be increased by increasing the contact time and the temperature of the CO 2 and H 2 S scrubbers. Therefore, the upgraded biogas has a higher calorific value than the raw biogas due to its high CH 4 content. 3.2.2. Upgrading Efficiency of the Produced Biogas The upgrading efficiency of biogas was estimated by determining the composition of raw biogas and upgraded biogas. From the biogas production experiments, an average 22.29 g of raw biogas (67.2% CH 4 , 32% CO 2 , and 0.8% H 2 S) was obtained at the reactor outlet from a total of 1 kg of mixed feed (manure, blood, and RC). Therefore, the masses of CH 4 , CO 2 , and H 2 S are 14.98 g, 7.133 g and 0.178 g respectively. After upgrading, an average of 17.07 g of upgraded biogas (82.458% CH 4 , 17.5% CO 2 , and 0.042% H 2 S) was obtained experimentally. Then the masses of CH 4 , CO 2 , and H 2 S are 14.076 g, 2.987 g and 7.169*10 − 3 g respectively. From this result, 95.9% of H 2 S was removed from the biogas. 3.3. Energy Potential of the Upgraded Biogas The average volume of upgraded biogas recorded was 0.0192 m 3 /1 kg of feed. The determination of the calorific value of the purified biogas containing 82.458% of methane is based on the calorific value of biomethane. According to ANDRITZ GROUP, ( 2013 ), the calorific value of biomethane is 35.9 MJ/m 3 and this value is equivalent to 9.97 KWh/m 3 . On those bases, the calorific value of upgraded biogas (82.458% of CH 4 ) is 29.6 MJ/m 3 . Here again, the energy equivalent of the produced upgraded biogas is 8.22 KWh/m 3 . Finally, the upgraded/purified biogas was collected in a small plastic balloon as shown in Fig. 4 . 3.4. Fertilizing Values and Amount of the Digestate As shown in Table 2 , the main fertilizer values (N, P, and K) of the digestate/slurry were determined separately based on a weight basis. According to Pagés et al., ( 2015 ), the composition of animal waste varies slightly, depending on many factors such as weather conditions, animal breed, age, and the quantity/quality of the food. The study results were estimated based on a wet weight basis and the digestate can be used as a fertilizer supplement. Table 2 Main fertilizing values (N, P, and K) of the digestate Nutrients Results, mg/Kg (wet weight basis) Results (% of wet weight basis) Nitrogen (N) 11,573.00 1.16 Phosphorus (P) 392.41 0.039 Potassium (K) 426.85 0.045 Figure 5 shows the digestate by product after the production of biogas that can be used as an organic fertilizer due to is high fertilizing values (N, P, and K) content. 3.5. Economic Analysis Table 3 shows the capacity and the cost of the main unit operations for the production and purification of biogas. The capacity and cost of each unit operations was generated from Aspen Plus v11 based on the availability of the feedstock. Table 3 The capacity and cost of the main unit operations, generated from Aspen plus v11 S.N Equipment Construction Material Capacity Price ( $ ) 1 Agitated mix reactor Carbon steel 31.031 m 3 209,300 2 CO 2 scrubber Carbon steel 2.4 m 3 17,300 3 H 2 S scrubber Carbon steel 0.6 m 3 9,800 4 Compressor 110.60 hp 228,500 Total purchased equipment cost including 8% contingency 502,092 3.5.1. Capital Investment Costs Table 4 elaborates the findings of the capital investment cost following the procedures on section 2.8.1. The description of each parameter was also taken from the techno-economic analysis of a similar study (Xie & Willquist, 2016 ). The results showed that the total capital investment cost, which is the sum of fixed capital investment (FCI) and working capital (WC), was estimated as $ 2,124,853.34. Table 4 General summary of cost estimation for total capital investment cost Parameters Description Total Cost ( $ ) Direct Costs Equipment Cost (EC) 100% of EC 502,092.00 Equipment installation 25% of EC 125,523.00 Instrumentation and control 20% of EC 100,418.40 Electrical equipment and installation 11% of EC 55,230.12 Process piping 68% of EC 341,422.56 Buildings including services 18% of EC 90,376.56 Service facilities 30% of EC 150,627.60 Total Direct Cost (TDC) 1,365,690.24 Indirect Costs Engineering and Supervision 33% of EC 165,690.36 Construction expenses 41% of EC 205,857.72 Contractor’s fee 22% of EC 110,460.24 Total Indirect Cost (TIC) 482,008.32 Fixed capital investment (FCI) TDC + TIC 1,847,698.56 Working capital (WC) 15% FCI 277,154.784 Total Capital Investment, TCI FCI + WC 2,124,853.34 3.5.2. Operating Costs Table 5 describes the findings of the operating cost following the procedures on section 2.8.1. The description of each parameter was also taken from the techno-economic analysis of a similar study (Xie & Willquist, 2016 ). The results showed that the total operating cost; which is the sum of fixed charges, direct production cost, and general expenses, was estimated as $ 440,702.37. Table 5 General summary of cost estimation for the total operating cost Parameters Description Total Cost (ETB) Fixed Charges Depreciation 10% of FCI 184,769.86 Local taxes 1% of FCI 18,476.98 Insurance 1% of FCI 18,476.98 Total Fixed Charge (TFC) 221,722.97 Direct Production Cost Maintenance (M) 3% of FCI 55,430.96 Operating Labor (OL) 15% of TOC 66,105.36 Supervision (S) 15% of OL 9,915.80 Utility 5% of TOC 22,035.12 Operating supplies 15% of M 8,314.64 Laboratory charges 15% of OL 9,915.80 Plant overhead 15% of (M + OL + S) 19,717.82 Total Direct Production Cost (TDPC) 191,435.50 General Expenses Administrative cost 15% of OL 9,915.80 Distribution and marketing cost 2% of TOC 8,814.05 Research and development cost 2% of TOC 8,814.05 Total General Expenses (TGE) 27,543.9 Total Operating Cost (TOC) TFC + TDPC + TGE 440,702.37 3.5.3. Analysis of Profitability According to (Hunpinyo et al., 2013 ), the most commonly used methods to evaluate profitability are turnover ratio, rate of return on investment (ROI), payback period (PBP), break-even analysis, net present value (NPV), and discounted cash flow rate of return based on full-life performance. Therefore, in this study, cost-effectiveness analysis was estimated using these methods as shown in Table 6 . The value of the discount rate was estimated using Excel software. Table 6 Comparison of profitability analysis of this study and other similar studies Parameters This Study (Pratima & Bhakta, 2015 ) (Raj et al., 2023 ) (Hublin et al., 2014 ) Turnover Ratio 0.22 n.d n.d n.d Return on Investment, % 12.63 16.23 11.3 7.1 Payback Period (PBP), year 4.08 5.3 9.2 9.9 Break-Even Point Analysis,% 16.67 n.d n.d n.d Net present value $ 2,949,848.99 629,646.26 NRs 135,701.00 € 183,047.00 € Discount Cash Flow Rate of Return, % 40.37 n.d n.d n.d Where; n.d is to mean not determined Profitability parameters depend on several factors. These include operating parameters, feedstock composition, economic analysis method, direct and indirect costs, operating costs, biogas selling price, and compost selling price. These factors make a slight difference for the profitability parameters of this study to vary slightly from the results reported by (Pratima & Bhakta, 2015 ), (Raj et al., 2023 ), and (Hublin et al., 2014 ). 4. CONCLUSION This study was intended to evaluate the techno-economic of biogas produced by three different sources, namely, manure, RC, and blood and it’s upgraded. The techno-economics evaluation was estimated based on the final experimental outputs. The characteristics of manure, RC, and blood were investigated in detail comparatively and the results indicate that the raw materials, especially manure, and rumen content are suitable for biogas production due to its organic content. The methane content of raw biogas and upgraded biogas are 67.20% 0.435% and 82.458% 0.503% respectively.The energy potential of the upgraded biogas was estimated as 29.6 MJ/m 3 , which is equivalent to 8.22 KWh/m 3 . The major fertilizing values (nitrogen, phosphorus, and potassium) content of the digestate were estimated using a UV-Vis spectrophotometer (for Nitrogen and Phosphorus) and flame photometer (for potassium). Experimental results for nitrogen, phosphorus, and potassium were scored 11,573, 392.4, and 426.85 mg/kg, respectively, based on a wet weight basis, and the digestate can be used as a fertilizer supplement. An order-of-magnitude estimate (ratio estimate) or predesign method, which uses the purchased equipment costs, was used to estimate the capital investment cost of the biogas plant. From this, the turnover ratio, rate of return on investment, payback period and the production capacity (%) at the break-even point were estimated as 0.22, 12.63%, 4.08 years, and 16.67%, respectively. Additionally, a positive value for the net present value (NPV) ($2,949,848.99) was obtained, as well as a 40.37% discounted cash flow rate of return. The result of the business show that the biogas production process is feasible and acceptable.. Generally, from the profitability point of view, the biogas production and upgrading process is feasible and acceptable. Declarations Authors’ Contributions FAB, GGB, TGG conceived the problem of the study. All authors prepared research proposals and developed the design of the experiments as well as prepared the first draft of the manuscript, reviewed and approved the manuscript for submission. Funding This study was supported by Mekelle University, PO Box 231, Mekelle, Ethiopia through Grant No.: PG/MSc/EiTM/MU-NMBU/25/2019 Availability of data The data sets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing Interests The authors declare no competing interests. References Andrade, W. R., Xavier, C. A. N., Coca, F. O. C. G., Arruda, L. D. O., & Santos, T. M. B. (2016). Biogas production from ruminant and monogastric animal manure co-digested with manipueira. Archivos de Zootecnia , 65 (251), 375–380. https://doi.org/10.21071/az.v65i251.699 ANDRITZ GROUP. (2013). BIOgas – An important renewable energy source. WBA Fact Sheet , May , 7. Bamboriya, M. . (2012). Biogas Bottling in India. Akshya Urja , 5 (5), 41–43. Gebeyehu, B., Kebede, E., Kifleyohannes, T., Abebe, N., & Kumar, N. (2018). Prevalence of calf coccidiosis in Mekelle, northern Ethiopia. Ethiopian Veterinary Journal , 22 (2), 1. https://doi.org/10.4314/evj.v22i2.1 Genet, T., Birhanu, A., & Solomon, K. (2018). Optimization of bio gas production from slaughterhouse wastes. African Journal of Environmental Science and Technology , 12 (8), 283–295. https://doi.org/10.5897/ajest2017.2456 Hublin, A., Schneider, D. R., & Džodan, J. (2014). Utilization of biogas produced by anaerobic digestion of agro-industrial waste: Energy, economic and environmental effects. Waste Management and Research , 32 (7), 626–633. https://doi.org/10.1177/0734242X14539789 Hunpinyo, P., Narataruksa, P., Tungkamani, S., Pana-Suppamassadu, K., & Chollacoop, N. (2013). Evaluation of techno-economic feasibility biomass-to-energy by using ASPEN Plus®: A case study of Thailand. Energy Procedia , 42 (November 2013), 640–649. https://doi.org/10.1016/j.egypro.2013.11.066 Kothari, R., Tyagi, V. V., & Pathak, A. (2010). Waste-to-energy: A way from renewable energy sources to sustainable development. In Renewable and Sustainable Energy Reviews (Vol. 14, Issue 9, pp. 3164–3170). Elsevier Ltd. https://doi.org/10.1016/j.rser.2010.05.005 Kunal, A., Prashanth, B., Ghosh, A., & Hemanth, G. (2017). A Review on production of Biogas from Slaughter house waste and poultry litter. International Research Journal of Engineering and Technology(IRJET) , 4 (4), 2188–2192. Nallamothu, R. B., Teferra, A., & Rao, P. B. V. A. (2013). Biogas Purification, Compression and Bottling. Global Journal of Engineering, Design & Technology , 2 (6), 34–38. Pagés, J., Jhosané, D., & Díaz, P. (2015). Biogas From Slaughterhouse Waste . Peiris, A. P. T. S. (2016). Feasibility Study of Production of Bio Methane from Bio Wastes in Sri Lanka and Develop Cost Model for the Production Process . Perez Garcia, A. (2014). Techno-economic feasibility study of a small-scale biogas plant for treating market waste in the city of El Alto . Independen , 67. Pratima, K. ., & Bhakta, B. . (2015). Production Of Biogas From Slaughterhouse Waste In Lalitpur Sub-metropolitan City. IOE Graduate Conference , 143–149. https://doi.org/10.1016/j.indcrop.2023.116758 Raj, R., Kumar Singh, D., & Vachan Tirkey, J. (2023). Performance simulation and optimization of SI engine fueled with peach biomass-based producer gas and propane blend. Thermal Science and Engineering Progress , 41 , 101816. https://doi.org/10.1016/j.tsep.2023.101816 Ray, N. H. S., Mohanty, M. K., & Mohanty, R. C. (2016). Biogas compression and storage system for cooking applications in rural households. International Journal of Renewable Energy Research , 6 (2), 594–598. https://doi.org/10.20508/ijrer.v6i2.3449.g6823 Tsagkari, M., Couturier, J. L., Dubois, J. L., & Kokossis, A. (2015). Heuristics for Capital Cost Estimation: a Case Study on Biorefinery Processes. 10th National Congress of Chemical Engineering , August , 9. US EPA. (2004). Effluent Limitations Guidelines and Standards for the Meat and Poultry Products Industry Point Source Category . Xie, Y., & Willquist, K. (2016). Techno-Economic Analysis of Biomethane Production With . December . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3795026","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":264518492,"identity":"fff2c928-0ed7-4bea-bf6a-7024a8592c84","order_by":0,"name":"Fentahun Abebaw Belete","email":"","orcid":"","institution":"Ethiopian Institute of Technology-Mekelle, Mekelle University","correspondingAuthor":false,"prefix":"","firstName":"Fentahun","middleName":"Abebaw","lastName":"Belete","suffix":""},{"id":264518493,"identity":"ffe4b3bc-d219-4bdc-a473-fcc334d12e8b","order_by":1,"name":"Goitom Gebreyohannes Berhe","email":"data:image/png;base64,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","orcid":"","institution":"Mekelle University","correspondingAuthor":true,"prefix":"","firstName":"Goitom","middleName":"Gebreyohannes","lastName":"Berhe","suffix":""},{"id":264518494,"identity":"3ff00e43-96bf-48aa-8bb1-b2f3af38f00c","order_by":2,"name":"Tesfaldet Gebregerges Gebreegziabher","email":"","orcid":"","institution":"Tigray Institute of Policy Studies (TIPS)","correspondingAuthor":false,"prefix":"","firstName":"Tesfaldet","middleName":"Gebregerges","lastName":"Gebreegziabher","suffix":""},{"id":264518495,"identity":"8388cf5e-825f-4aed-9b54-42ff6d7a0db3","order_by":3,"name":"Asmelash Gebrekidan Mekonen","email":"","orcid":"","institution":"Ethiopian Institute of Technology-Mekelle, Mekelle University","correspondingAuthor":false,"prefix":"","firstName":"Asmelash","middleName":"Gebrekidan","lastName":"Mekonen","suffix":""},{"id":264518496,"identity":"6846af73-ca3d-4c88-9fb4-274f8c8adebf","order_by":4,"name":"Brhanu Teka Gebrezgabher","email":"","orcid":"","institution":"Ethiopian Institute of Technology-Mekelle, Mekelle University","correspondingAuthor":false,"prefix":"","firstName":"Brhanu","middleName":"Teka","lastName":"Gebrezgabher","suffix":""}],"badges":[],"createdAt":"2023-12-23 05:44:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3795026/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3795026/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49049571,"identity":"adad3ae6-e17b-4e62-ba90-8ca57bbb2b92","added_by":"auto","created_at":"2024-01-02 08:51:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":172345,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of the study area (Gebeyehu et al., 2018)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3795026/v1/480cd6e02a49612b6bcb97a2.png"},{"id":49049570,"identity":"f27915ef-24da-421d-af4a-53a4ff4b1daa","added_by":"auto","created_at":"2024-01-02 08:51:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":10177,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of the study area (Gebeyehu et al., 2018)\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3795026/v1/9cf0929f536c97a9be9ceb2c.png"},{"id":49049574,"identity":"7056a20c-13ae-43b3-81e6-5cfde617c22a","added_by":"auto","created_at":"2024-01-02 08:51:07","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":18842,"visible":true,"origin":"","legend":"\u003cp\u003eThe main biogas composition of the final product\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3795026/v1/5094bf946bb9484dd2f0a07a.png"},{"id":49049573,"identity":"c145ef0a-9249-4548-825a-82c0a6d0c821","added_by":"auto","created_at":"2024-01-02 08:51:06","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":149855,"visible":true,"origin":"","legend":"\u003cp\u003eAn upgraded biogas collected in the plastic ballon\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-3795026/v1/a0ce886f85b9b80971cb740d.png"},{"id":49049572,"identity":"695ba288-e0d1-4c5f-ada8-e1152a0e62ef","added_by":"auto","created_at":"2024-01-02 08:51:06","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":137898,"visible":true,"origin":"","legend":"\u003cp\u003eThe digestate by-product after biogas production\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-3795026/v1/35579eb2d05172f706d99346.png"},{"id":53845068,"identity":"4709e620-7796-44f4-a7c1-e6b6f6c54548","added_by":"auto","created_at":"2024-04-01 08:22:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1115539,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3795026/v1/8fed816e-7194-448d-8b9d-63e770a4d13b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Techno-Economic Analysis of Biogas Production from Slaughterhouse Biowastes, in Mekelle City, Tigray, Ethiopia","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eThe fast-growing of world population, urbanization, and industrial development, the discharge of wastes from different sources are increasing from time to time. The growing dearth of petroleum and coal, deforestation of jungles for cooking and heating purposes, and problems related to the emission of greenhouse gases such as uncontrolled methane (CH\u003csub\u003e4\u003c/sub\u003e), carbon dioxide (CO\u003csub\u003e2\u003c/sub\u003e), hydrogen sulfide (H\u003csub\u003e2\u003c/sub\u003eS), and other trace gases lead to the global warming of the Earth\u0026rsquo;s surface (Genet et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Hence, to ameliorate the worsening impacts of global warming, recent research undertakings are geared towards finding alternate energy from renewable sources in a sustainable manner.\u003c/p\u003e \u003cp\u003eThere are numerous types of renewable energy sources available including hydropower, wind energy, solar energy, ocean wave power, and biomass energy. The utilization of these renewable energy sources is limited for various reasons. However, the energy obtained from biomass wastes has a multitude of benefits (Peiris, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Besides, its paramount importance in alleviating the problem related to energy supply, it is a waste treatment process furnishing nutrients for agricultural production. Biomass energy, which can substitute for fossil fuel applications with minor upgrading methods, is a significant natural and renewable carbon resource (Peiris, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). For the sustainable development of the world, renewable biomass waste materials from agriculture, industries, and domestic waste sources should be converted to useful energy forms like bio-hydrogen, biogas, bio-alcohols, etc., through waste-to-energy routes (Kothari et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Organic and inorganic industrial wastes can easily pollute the environment and can cause serious health problems in the world especially in developing countries like Ethiopia. The majority of these organic wastes are generated from the agro-food industries such as slaughterhouses, meat processing companies, dairy companies, and others industries (US EPA, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBiogas as its name suggests is the production of gas from biodegradable materials. It is a combustible gas mainly composed of methane which can be used as cooking fuel, natural gas or to produce electricity by combustion (Kunal et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Biogas comprises 60\u0026ndash;65% CH\u003csub\u003e4\u003c/sub\u003e, 35\u0026ndash;40% CO\u003csub\u003e2\u003c/sub\u003e, 0.5-1.0% H\u003csub\u003e2\u003c/sub\u003eS and the rest is water vapor, etc. (Bamboriya, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Even if Ethiopia is among methane emitter countries and slaughterhouse biowastes are good sources of biogas production, sufficient consideration of slaughterhouse wastes has not yet been given. Biogas significantly reduces the bulky consumption of fossil fuel and reduces the deforestation of forests that can be used for cooking and heating purposes (Genet et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBases on the author\u0026rsquo;s observation on the study area, the main problems related to most slaughterhouses in developing countries are the production of large amounts of solid and liquid wastes and the absence of waste treatment plants. These problems were also observed in Ethiopia-based slaughterhouses including in the slaughterhouse owned by Abergelle International Livestock Development (AILD) Plc located in the Tigray Regional State. Treating the slaughterhouse biowaste via the anaerobic route can provide energy and organic fertilizers. Detail technical and economic analysis of the treatment plant was not carried out before. The slaughterhouse owned by AILD Plc. located in Mekelle, Tigray, Ethiopia is operating without a waste treatment plant for both solid and liquid wastes. According to the enterprise data, about 9,575,228 kg of untreated slaughterhouse wastes, including manure, blood, and rumen content (RC) are generated annually. Hence, to overcome energy crisis, deforestation of plants, environmental pollution, and global warming; efficient, cost-effective, and environmentally friendly treatment methods such as biogas technology is required.\u003c/p\u003e \u003cp\u003eUp to our knowledge there is no any study on techno-Economic Analysis of Biogas Production from Slaughterhouse Biowastes at AILD Plc. The aim of this study is to investigate the techno-economic analysis of biogas production from slaughterhouse biowastes. Specifically it includes characterize the raw materials, produce and upgrade biogas at the laboratory by considering optimal operating parameters from existing literature (optimum feed ratios, optimum temperature value, and optimum pH value), determine the composition (CH\u003csub\u003e4\u003c/sub\u003e, CO\u003csub\u003e2,\u003c/sub\u003e and H\u003csub\u003e2\u003c/sub\u003eS) of raw biogas and purified biogas experimentally, determine the nutrient quality (nitrogen, phosphorus, and potassium) of the digestate by-product experimentally, and analyze the economic feasibility of biogas production from slaughterhouse biowastes (manure, blood, and RC) by considering important equipment required for purification and compression at an industrial scale.\u003c/p\u003e"},{"header":"2. MATERIALS AND METHODOLOGY","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study Area\u003c/h2\u003e \u003cp\u003eThe slaughterhouse biowastes was provided by AILD located in Mekelle, Tigrai, Ethiopia and the location of the enterprise is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. It is located in Semien sub-city (Gebeyehu et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This enterprise produces many organic wastes, including manure, blood, and RC and waste water from the slaughterhouse. All the wastes directly dispose with the environment without any treatment which was often washed and discharged to the environment.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Materials and Equipment\u003c/h2\u003e \u003cp\u003eFreshly voided slaughterhouse biowastes (manure, blood, and rumen content) was collected. The physical and chemical composition such as proximate and ultimate analysis of each feedstock was analyzed. The biowastes to water ratio was 1:1. The inoculum used was bio-slurry, which contains active microbes essential for the AD process, collected at Desta Alcohol and Liquor Factory, Mekelle, Tigray, Ethiopia. The percentage of inoculum for anaerobic fermentation of the organic waste was 20% of the volume of the feed sample. The inoculum had a pH, TSS, TDS, and COD of 7.4, 18000 ppm, 37500 ppm, and 75000 ppm, respectively.\u003c/p\u003e \u003cp\u003eThe major equipment and instruments used were electronic balance to measure the weight of samples and a product. Multiparameter (multi 3410) and COD multimeter were used to measure the BOD and COD content of raw materials. pH meter was used to measure the pH of the mixed feed (blood, manure, RC, and water) and the pH of each sample. A 3 L of the plastic jar was used as an anaerobic digester and a water bath was used as a source of heat for the digestion process. An oven was used to remove the moisture of each sample to estimate the moisture content of the feeds and the samples were burnt in a furnace to determine the ash content of the samples. A small plastic balloon was used to collect the final purified biogas. A flame photometer (SP-FP6450) was used to evaluate the trace amounts of potassium in a digestate/compost by-product. UV-Vis spectrophotometer (UV-6300PC) was used to determine the nitrogen, phosphorus, and sulfur in the samples and the digestate. Orsat apparatus and Tutwiler apparatus were used to determine the CO\u003csub\u003e2\u003c/sub\u003e and H\u003csub\u003e2\u003c/sub\u003eS content of the biogas.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Method of Biogas Production\u003c/h2\u003e \u003cp\u003eAccording to Kothari et al., (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), the production of biogas through AD offers significant advantages over others due to less biomass sludge, successful in treating wet wastes of less than 40% dry matter, it is more effective pathogen removal. Due to these reasons, AD is preferable. According to Genet et al., (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), the optimum feedstock percentage are 20% blood, 20% manure, and 60% rumen content.\u003c/p\u003e \u003cp\u003eBefore the digestion stage, the sanitation stage was occured for the reactor to remove pathogens by heating or sterilization it at 60\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(℃\\)\u003c/span\u003e\u003c/span\u003e. The slaughterhouse biowastes (blood, RC, and manure) and water were fed to the digester at a 1:1 ratio where the total volume was 2 liters with a space volume of 1 litter and the reaction was occurred in it and biogas as well as digestate by-product was produced. The optimal operating conditions such as feed ratios, pH value, and temperature was determined based on Genet et al., (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Estimation of the Composition of Raw Biogas\u003c/h2\u003e \u003cp\u003eBiogas is a mixture of methane (CH\u003csub\u003e4\u003c/sub\u003e), carbon dioxide (CO\u003csub\u003e2\u003c/sub\u003e), hydrogen sulfide (H\u003csub\u003e2\u003c/sub\u003eS), and traces of water vapor (Nallamothu et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The composition of biogas was determined at Desta Alcohol and Liquor Factory, Mekelle, Ethiopia. The composition of CO\u003csub\u003e2\u003c/sub\u003e, v/v% was estimated using the Orsat apparatus. Again, the composition of H\u003csub\u003e2\u003c/sub\u003eS, v/v% was determined using the Tutwiler apparatus. Finally, the composition of methane was estimated from the composition of CO\u003csub\u003e2\u003c/sub\u003e and H\u003csub\u003e2\u003c/sub\u003eS.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Methods of Biogas Upgrading\u003c/h2\u003e \u003cp\u003eAccording to (Ray et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), chemical adsorption was used to upgrade/purify biogas using calcium oxide (to remove CO\u003csub\u003e2\u003c/sub\u003e), and steel wool (to remove H\u003csub\u003e2\u003c/sub\u003eS).\u003c/p\u003e \u003cp\u003eSince impurities, reduce the heating capacity of biogas and they are also a health problem, their concentration should be reduced. The raw biogas was first passed through a CO\u003csub\u003e2\u003c/sub\u003e separation unit that contains limestone crystals in it to reduce the concentration of CO\u003csub\u003e2\u003c/sub\u003e. CO\u003csub\u003e2\u003c/sub\u003e was reacting with CaO and produce calcium carbonate (CaCO\u003csub\u003e3\u003c/sub\u003e). Once the concentration of CO\u003csub\u003e2\u003c/sub\u003e is reduced, the biogas was passed through the H\u003csub\u003e2\u003c/sub\u003eS separation unit, which contains iron oxide in the form of oxidized steel wool or iron turning, to reduce the concentration of H\u003csub\u003e2\u003c/sub\u003eS in the biogas. When the biogas comes in contact with this steel wool, H\u003csub\u003e2\u003c/sub\u003eS was converted into elemental sulfur, and biogas that has higher CH\u003csub\u003e4\u003c/sub\u003e content was produced.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Estimation of the Composition and Volume of Upgraded Biogas\u003c/h2\u003e \u003cp\u003eTo estimate the composition of the upgraded biogas, the same procedures and apparatus was used as raw biogas. The volume of the upgraded biogas was estimated by determining its mass and density. The mass of the upgraded biogas was determined by weighing the balloon that contains an upgraded biogas and the balloon (free of the biogas). The mass was then the difference between the two masses.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7. Determination of Fertilizing Values of the Digestate\u003c/h2\u003e \u003cp\u003eThe major fertilizing values of the digestate i.e. Nitrogen (N), Phosphorus (P), and potassium (K) were estimated by the Department of Geology, Mekelle University, Tigrai, Ethiopia. The trace amounts of potassium were determined in a direct reading type of flame photometer at a wavelength of 766.5 nm and a slit width of 2 nm. Nitrogen (N) and Phosphorus (P) was determined using the UV-Vis spectrophotometer at a wavelength of 570 and 400 nm, respectively with a path length of 1 cm for both elements. The results of the major fertilizing values (N, P, and K) of the digestate were estimated in mg per kg of digestate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8. Techno-Economic Assessments\u003c/h2\u003e \u003cp\u003eCalculation of capital investment costs, operational costs, and profitability analysis are the main economic evaluations. An order-of-magnitude estimate (ratio estimate) or predesign method was used and the economic analysis was estimated according to the purchased equipment cost, which was evaluated using Aspen plus v11 based on the capacity and construction materials of the unit operations.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e2.8.1. Capital Investment Costs\u003c/h2\u003e \u003cp\u003eIt is the sum of fixed capital investment costs and working capital. The fixed capital investment cost is again the sum of direct and indirect costs. Direct costs denote the capital necessary for the installed process equipment with all auxiliaries that are needed for the direct operation process. Indirect costs are costs that are required for construction overhead and for all plant components that are not directly related to the process operation. The description of each parameter was also taken from the techno-economic analysis of a similar study (Xie \u0026amp; Willquist, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWorking capital for an industrial plant consists of the total amount of money invested in raw materials and supplies carried in stock, finished products in stock and semi-finished products in the process of being manufactured, and accounts receivable. The ratio of working capital to total capital investment varies with different companies, but most chemical plants use an initial working capital amounting to 10 to 20 percent of the fixed capital investment (Tsagkari et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The economic evaluation was calculated using EXCEL spreadsheet.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e2.8.2. Operating Costs\u003c/h2\u003e \u003cp\u003eIt is an expense cost related to the operation of the biogas plant and selling of the products and byproducts. The description of each parameter was also taken from the techno-economic analysis of a similar study (Xie \u0026amp; Willquist, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e2.8.3. Analysis of Profitability\u003c/h2\u003e \u003cp\u003eAccording to (Hunpinyo et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), the most common methods used for profitability evaluation are turnover ratio, rate of return on investment (ROI), payback period (PBP), break-even analysis, net present value (NPV), and discounted cash flow rate of return based on full-life performance. Therefore, in this study, the profitability analysis was estimated using these methods. According to Perez Garcia, (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), the average biogas plant-life (n) is 15 years and the straight-line method was used to evaluate depreciation at the end of each year.\u003c/p\u003e \u003cp\u003eThe following formulas were used to calcite the profitability analysis.\u003c/p\u003e \u003cp\u003eTurnover Ratio = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{\\text{G}\\text{r}\\text{o}\\text{s}\\text{s} \\text{A}\\text{n}\\text{n}\\text{u}\\text{a}\\text{l} \\text{S}\\text{a}\\text{l}\\text{e}\\text{s}}{\\text{F}\\text{i}\\text{x}\\text{e}\\text{d} \\text{C}\\text{a}\\text{p}\\text{i}\\text{t}\\text{a}\\text{l} \\text{I}\\text{n}\\text{v}\\text{e}\\text{s}\\text{t}\\text{m}\\text{e}\\text{n}\\text{t}}\\)\u003c/span\u003e\u003c/span\u003e (1)\u003c/p\u003e \u003cp\u003eROI = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{\\text{N}\\text{e}\\text{t} \\text{P}\\text{r}\\text{o}\\text{f}\\text{i}\\text{t}}{\\text{T}\\text{o}\\text{t}\\text{a}\\text{l} \\text{C}\\text{a}\\text{p}\\text{i}\\text{t}\\text{a}\\text{l} \\text{I}\\text{n}\\text{v}\\text{e}\\text{s}\\text{t}\\text{m}\\text{e}\\text{n}\\text{t}}\\)\u003c/span\u003e\u003c/span\u003e*100% (2)\u003c/p\u003e \u003cp\u003ePBP = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{\\text{T}\\text{o}\\text{t}\\text{a}\\text{l} \\text{f}\\text{i}\\text{x}\\text{e}\\text{d} \\text{c}\\text{a}\\text{p}\\text{i}\\text{t}\\text{a}\\text{l} \\text{i}\\text{n}\\text{v}\\text{e}\\text{s}\\text{m}\\text{e}\\text{n}\\text{t} - \\text{S}\\text{a}\\text{l}\\text{v}\\text{a}\\text{g}\\text{e} \\text{v}\\text{a}\\text{l}\\text{u}\\text{e}}{\\text{N}\\text{e}\\text{t} \\text{p}\\text{r}\\text{o}\\text{f}\\text{i}\\text{t} + \\text{D}\\text{e}\\text{p}\\text{r}\\text{i}\\text{c}\\text{i}\\text{t}\\text{i}\\text{o}\\text{n}}\\)\u003c/span\u003e\u003c/span\u003e (2)\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eBreak-Even Point (BEP) Analysis\u003c/strong\u003e \u003cp\u003eAt the break-even point, the total operating costs are equal to the annual revenue earned. i.e Total operating cost (TOC)\u0026thinsp;=\u0026thinsp;Total Annual sales\u003c/p\u003e \u003c/p\u003e \u003cp\u003eAgain;\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\text{T}\\text{O}\\text{C} = \\text{F}\\text{i}\\text{x}\\text{e}\\text{d} \\text{c}\\text{h}\\text{a}\\text{r}\\text{g}\\text{e} \\left(\\text{F}\\text{C}\\right) + \\text{G}\\text{e}\\text{n}\\text{e}\\text{r}\\text{a}\\text{l} \\text{E}\\text{x}\\text{p}\\text{e}\\text{n}\\text{s}\\text{e}\\text{s} \\left(\\text{G}\\text{E}\\right) + \\text{D}\\text{i}\\text{r}\\text{e}\\text{c}\\text{t} \\text{P}\\text{r}\\text{o}\\text{d}\\text{u}\\text{c}\\text{t}\\text{i}\\text{o}\\text{n} \\text{C}\\text{o}\\text{s}\\text{t} \\left(\\text{D}\\text{P}\\text{C}\\right)\\)\u003c/span\u003e\u003c/span\u003e\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\text{F}\\text{C} + \\text{G}\\text{E} + \\text{D}\\text{P}\\text{C} = \\text{T}\\text{o}\\text{t}\\text{a}\\text{l} \\text{A}\\text{n}\\text{n}\\text{u}\\text{a}\\text{l} \\text{S}\\text{a}\\text{l}\\text{e}\\text{s}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e4\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eAfter estimating production capacity at the break-even point using the above equation, the percentage at the break-even point was calculated using the following equation. The biogas production is acceptable for the percentage of break-even point less than the plant operating capacity.\u003c/p\u003e \u003cp\u003eBEP, % = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{\\text{P}\\text{r}\\text{o}\\text{d}\\text{u}\\text{c}\\text{t}\\text{i}\\text{o}\\text{n} \\text{c}\\text{a}\\text{p}\\text{a}\\text{c}\\text{i}\\text{t}\\text{y} \\text{a}\\text{t} \\text{B}\\text{E}\\text{P}}{\\text{A}\\text{n}\\text{n}\\text{u}\\text{a}\\text{l} \\text{b}\\text{i}\\text{o}\\text{g}\\text{a}\\text{s} \\text{p}\\text{r}\\text{o}\\text{d}\\text{u}\\text{c}\\text{t}\\text{i}\\text{o}\\text{n}+\\text{A}\\text{n}\\text{n}\\text{u}\\text{a}\\text{l} \\text{c}\\text{o}\\text{m}\\text{p}\\text{o}\\text{s}\\text{t} \\text{p}\\text{r}\\text{o}\\text{d}\\text{u}\\text{c}\\text{t}\\text{i}\\text{o}\\text{n}}\\)\u003c/span\u003e\u003c/span\u003e (5)\u003c/p\u003e \u003cp\u003eNPV = \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\sum _{1}^{\\text{n}}{\\left(1+\\text{i}\\right)}^{-\\text{n}}\\left(\\text{N}\\text{P}\\text{j}+\\text{D}\\text{j}+\\text{R}\\text{e}\\text{c}\\text{j}\\right)-\\text{T}\\text{C}\\text{I}\\)\u003c/span\u003e\u003c/span\u003e (6)\u003c/p\u003e \u003cp\u003eWhere, i\u0026thinsp;=\u0026thinsp;the discount rate, n\u0026thinsp;=\u0026thinsp;lifetime of the plant, NPj\u0026thinsp;=\u0026thinsp;net profit, Dj\u0026thinsp;=\u0026thinsp;depreciation,\u003c/p\u003e \u003cp\u003eRecj\u0026thinsp;=\u0026thinsp;recovery value, and TCI\u0026thinsp;=\u0026thinsp;Total capital investment\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\text{R}\\text{e}\\text{c}\\text{j} = \\text{S}\\text{a}\\text{l}\\text{v}\\text{a}\\text{g}\\text{e} \\text{v}\\text{a}\\text{l}\\text{u}\\text{e} + \\text{W}\\text{o}\\text{r}\\text{k}\\text{i}\\text{n}\\text{g} \\text{c}\\text{a}\\text{p}\\text{i}\\text{t}\\text{a}\\text{l}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e7\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eDiscount Cash Flow Rate of Return (DCFR)\u003c/strong\u003e \u003cp\u003eThe method of approach for a profitability evaluation by discounted cash flow takes into account the time value of money and is based on the amount of the investment that is unreturned at the end of each year during the estimated life of the project. It was estimated by making the NPV zero and determining the discount rate. An excel solver was used for this study to evaluate the discount cash flow rate of return.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv id=\"Equ3\" class=\"Equation\"\u003e \u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$$\\sum _{1}^{\\text{n}}{\\left(1+\\text{i}\\right)}^{-\\text{n}}\\left(\\text{N}\\text{P}\\text{j}+\\text{D}\\text{j}+\\text{R}\\text{e}\\text{c}\\text{j}\\right)-\\text{T}\\text{C}\\text{I}=0$$\u003c/div\u003e \u003cdiv class=\"EquationNumber\"\u003e8\u003c/div\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3. RESULT AND DISCUSSION","content":"\u003cp\u003eIn these results, immediate and final analysis, composition of biogas and its valorization effect, main fertilizer value of the waste and economic analysis were performed. The results are discussed below.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Proximate and Ultimate Analysis of Raw Materials\u003c/h2\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the proximate and ultimate analysis of manure, blood, and RC were determined separately. BOD, COD, and all the ultimate analyses was done on a wet basis and most of the parameters of this study have the same values as Genet et al., (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). According to Genet et al., (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), the proximate and ultimate analysis are depends on several factors such as the age of the animal, type of food, type of on-site sanitation system, and way of the sampling method. These results indicate that the raw materials, especially manure, and RC are suitable for biogas production due to their high organic matter content.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe proximate and ultimate analysis of raw materials\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eResults of the Study\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eManure\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eRC\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eBlood\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoisture, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e81.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e85.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsh, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVolatile Matter, % of TS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e81.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e82.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFixed Carbon, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Solids, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOD, mg. l\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,741.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,062.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBOD, mg. l\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,482.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,561.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e526.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbon, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNitrogen, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.562\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSulfur, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrganic content, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Composition and Upgrading Efficiency of Biogas\u003c/h2\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e3.2.1. Composition and Volume of Biogas\u003c/h2\u003e \u003cp\u003eThe average composition (v/v%) of the raw biogas was recorded as 67.2, 32.0, and 0.8% of CH\u003csub\u003e4\u003c/sub\u003e, CO\u003csub\u003e2\u003c/sub\u003e, and H\u003csub\u003e2\u003c/sub\u003eS, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This is due to the high organic content in raw materials especially manure (53.21%) and RC (50.5%). According to Andrade et al., (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), biogas production is influenced by feedstock properties; animal species; energetic, protein \u0026amp; fiber content in the diet; digestibility; physiologic stage; age; animal production systems; and environmental conditions.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the average contents of upgraded methane, carbon dioxide, and hydrogen sulfide contents were recorded as 82.458, 17.5, and 0.042% respectively. The upgrading process was performed at room temperature. Methane content can be increased by increasing the contact time and the temperature of the CO\u003csub\u003e2\u003c/sub\u003e and H\u003csub\u003e2\u003c/sub\u003eS scrubbers. Therefore, the upgraded biogas has a higher calorific value than the raw biogas due to its high CH\u003csub\u003e4\u003c/sub\u003e content.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e3.2.2. Upgrading Efficiency of the Produced Biogas\u003c/h2\u003e \u003cp\u003eThe upgrading efficiency of biogas was estimated by determining the composition of raw biogas and upgraded biogas. From the biogas production experiments, an average 22.29 g of raw biogas (67.2% CH\u003csub\u003e4\u003c/sub\u003e, 32% CO\u003csub\u003e2\u003c/sub\u003e, and 0.8% H\u003csub\u003e2\u003c/sub\u003eS) was obtained at the reactor outlet from a total of 1 kg of mixed feed (manure, blood, and RC). Therefore, the masses of CH\u003csub\u003e4\u003c/sub\u003e, CO\u003csub\u003e2\u003c/sub\u003e, and H\u003csub\u003e2\u003c/sub\u003eS are 14.98 g, 7.133 g and 0.178 g respectively.\u003c/p\u003e \u003cp\u003eAfter upgrading, an average of 17.07 g of upgraded biogas (82.458% CH\u003csub\u003e4\u003c/sub\u003e, 17.5% CO\u003csub\u003e2\u003c/sub\u003e, and 0.042% H\u003csub\u003e2\u003c/sub\u003eS) was obtained experimentally. Then the masses of CH\u003csub\u003e4\u003c/sub\u003e, CO\u003csub\u003e2\u003c/sub\u003e, and H\u003csub\u003e2\u003c/sub\u003eS are 14.076 g, 2.987 g and 7.169*10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e g respectively. From this result, 95.9% of H\u003csub\u003e2\u003c/sub\u003eS was removed from the biogas.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Energy Potential of the Upgraded Biogas\u003c/h2\u003e \u003cp\u003eThe average volume of upgraded biogas recorded was 0.0192 m\u003csup\u003e3\u003c/sup\u003e/1 kg of feed. The determination of the calorific value of the purified biogas containing 82.458% of methane is based on the calorific value of biomethane. According to ANDRITZ GROUP, (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), the calorific value of biomethane is 35.9 MJ/m\u003csup\u003e3\u003c/sup\u003e and this value is equivalent to 9.97 KWh/m\u003csup\u003e3\u003c/sup\u003e. On those bases, the calorific value of upgraded biogas (82.458% of CH\u003csub\u003e4\u003c/sub\u003e) is 29.6 MJ/m\u003csup\u003e3\u003c/sup\u003e. Here again, the energy equivalent of the produced upgraded biogas is 8.22 KWh/m\u003csup\u003e3\u003c/sup\u003e. Finally, the upgraded/purified biogas was collected in a small plastic balloon as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Fertilizing Values and Amount of the Digestate\u003c/h2\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the main fertilizer values (N, P, and K) of the digestate/slurry were determined separately based on a weight basis. According to Pag\u0026eacute;s et al., (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), the composition of animal waste varies slightly, depending on many factors such as weather conditions, animal breed, age, and the quantity/quality of the food. The study results were estimated based on a wet weight basis and the digestate can be used as a fertilizer supplement.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMain fertilizing values (N, P, and K) of the digestate\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNutrients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResults, mg/Kg (wet weight basis)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eResults (% of wet weight basis)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNitrogen (N)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11,573.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhosphorus (P)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e392.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePotassium (K)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e426.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the digestate by product after the production of biogas that can be used as an organic fertilizer due to is high fertilizing values (N, P, and K) content.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Economic Analysis\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the capacity and the cost of the main unit operations for the production and purification of biogas. The capacity and cost of each unit operations was generated from Aspen Plus v11 based on the availability of the feedstock.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe capacity and cost of the main unit operations, generated from Aspen plus v11\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS.N\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEquipment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eConstruction Material\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCapacity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePrice (\u003cspan\u003e$\u003c/span\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAgitated mix reactor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCarbon steel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.031 m\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e209,300\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCO\u003csub\u003e2\u003c/sub\u003e scrubber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCarbon steel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.4 m\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17,300\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eH\u003csub\u003e2\u003c/sub\u003eS scrubber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCarbon steel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6 m\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9,800\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCompressor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e110.60 hp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e228,500\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eTotal purchased equipment cost including 8% contingency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e502,092\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec22\" class=\"Section3\"\u003e \u003ch2\u003e3.5.1. Capital Investment Costs\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e elaborates the findings of the capital investment cost following the procedures on section 2.8.1. The description of each parameter was also taken from the techno-economic analysis of a similar study (Xie \u0026amp; Willquist, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The results showed that the total capital investment cost, which is the sum of fixed capital investment (FCI) and working capital (WC), was estimated as \u003cspan\u003e$\u003c/span\u003e2,124,853.34.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGeneral summary of cost estimation for total capital investment cost\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal Cost (\u003cspan\u003e$\u003c/span\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eDirect Costs\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEquipment Cost (EC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100% of EC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e502,092.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEquipment installation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25% of EC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e125,523.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstrumentation and control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20% of EC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100,418.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElectrical equipment and installation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11% of EC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55,230.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProcess piping\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68% of EC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e341,422.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuildings including services\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18% of EC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90,376.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eService facilities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30% of EC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e150,627.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTotal Direct Cost (TDC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,365,690.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eIndirect Costs\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEngineering and Supervision\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33% of EC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e165,690.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConstruction expenses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41% of EC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e205,857.72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eContractor\u0026rsquo;s fee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22% of EC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110,460.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTotal Indirect Cost (TIC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e482,008.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFixed capital investment (FCI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTDC\u0026thinsp;+\u0026thinsp;TIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,847,698.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWorking capital (WC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15% FCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e277,154.784\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Capital Investment, TCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFCI\u0026thinsp;+\u0026thinsp;WC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,124,853.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003e3.5.2. Operating Costs\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e describes the findings of the operating cost following the procedures on section 2.8.1. The description of each parameter was also taken from the techno-economic analysis of a similar study (Xie \u0026amp; Willquist, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The results showed that the total operating cost; which is the sum of fixed charges, direct production cost, and general expenses, was estimated as \u003cspan\u003e$\u003c/span\u003e440,702.37.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGeneral summary of cost estimation for the total operating cost\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal Cost (ETB)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eFixed Charges\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepreciation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10% of FCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e184,769.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocal taxes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1% of FCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18,476.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1% of FCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18,476.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTotal Fixed Charge (TFC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e221,722.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eDirect Production Cost\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaintenance (M)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3% of FCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55,430.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOperating Labor (OL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15% of TOC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66,105.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSupervision (S)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15% of OL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9,915.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUtility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5% of TOC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22,035.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOperating supplies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15% of M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8,314.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaboratory charges\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15% of OL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9,915.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlant overhead\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15% of (M\u0026thinsp;+\u0026thinsp;OL\u0026thinsp;+\u0026thinsp;S)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19,717.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTotal Direct Production Cost (TDPC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e191,435.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eGeneral Expenses\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdministrative cost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15% of OL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9,915.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistribution and marketing cost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2% of TOC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8,814.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResearch and development cost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2% of TOC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8,814.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTotal General Expenses (TGE)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27,543.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Operating Cost (TOC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTFC\u0026thinsp;+\u0026thinsp;TDPC\u0026thinsp;+\u0026thinsp;TGE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e440,702.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section3\"\u003e \u003ch2\u003e3.5.3. Analysis of Profitability\u003c/h2\u003e \u003cp\u003eAccording to (Hunpinyo et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), the most commonly used methods to evaluate profitability are turnover ratio, rate of return on investment (ROI), payback period (PBP), break-even analysis, net present value (NPV), and discounted cash flow rate of return based on full-life performance. Therefore, in this study, cost-effectiveness analysis was estimated using these methods as shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. The value of the discount rate was estimated using Excel software.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of profitability analysis of this study and other similar studies\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThis Study\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Pratima \u0026amp; Bhakta, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015\u003c/span\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(Raj et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(Hublin et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2014\u003c/span\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTurnover Ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en.d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003en.d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003en.d\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReturn on Investment, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePayback Period (PBP), year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBreak-Even Point Analysis,%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en.d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003en.d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003en.d\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNet present value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e2,949,848.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e629,646.26 NRs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e135,701.00 \u0026euro;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e183,047.00 \u0026euro;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiscount Cash Flow Rate of Return, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en.d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003en.d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003en.d\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eWhere; n.d is to mean not determined\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eProfitability parameters depend on several factors. These include operating parameters, feedstock composition, economic analysis method, direct and indirect costs, operating costs, biogas selling price, and compost selling price. These factors make a slight difference for the profitability parameters of this study to vary slightly from the results reported by (Pratima \u0026amp; Bhakta, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), (Raj et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and (Hublin et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. CONCLUSION","content":"\u003cp\u003eThis study was intended to evaluate the techno-economic of biogas produced by three different sources, namely, manure, RC, and blood and it’s upgraded. The techno-economics evaluation was estimated based on the final experimental outputs. The characteristics of manure, RC, and blood were investigated in detail comparatively and the results indicate that the raw materials, especially manure, and rumen content are suitable for biogas production due to\u0026nbsp;its\u0026nbsp;organic content.\u0026nbsp;The methane content of raw biogas and upgraded biogas are 67.20%\u0026nbsp;\u0026nbsp;\u0026nbsp;0.435% and 82.458%\u0026nbsp;\u0026nbsp;\u0026nbsp;0.503% respectively.The energy potential of the upgraded biogas was estimated as\u0026nbsp;29.6 MJ/m\u003csup\u003e3\u003c/sup\u003e, which is equivalent to 8.22 KWh/m\u003csup\u003e3\u003c/sup\u003e. The major fertilizing values (nitrogen, phosphorus, and potassium) content of the digestate were estimated using a UV-Vis spectrophotometer (for Nitrogen and Phosphorus) and flame photometer (for potassium). Experimental results for nitrogen, phosphorus, and potassium were scored 11,573, 392.4, and 426.85 mg/kg, respectively, based on a wet weight basis, and the digestate can be used as a fertilizer supplement. An order-of-magnitude estimate (ratio estimate) or predesign method, which uses the purchased equipment costs, was used to estimate the capital investment cost of the biogas plant. From this, the turnover ratio, rate of return on investment, payback period and the production capacity (%) at the break-even point were estimated as 0.22, 12.63%, 4.08 years, and 16.67%, respectively. Additionally, a positive value for the net present value (NPV) ($2,949,848.99) was obtained, as well as a 40.37% discounted cash flow rate of return. The result of the business show that the biogas production process is feasible and acceptable.. Generally, from the profitability point of view, the biogas production and upgrading process is feasible and acceptable.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFAB, GGB, TGG conceived the problem of the study. All authors prepared research proposals and developed the design of the experiments as well as prepared the first draft of the manuscript, reviewed and approved the manuscript for submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by Mekelle University, PO Box 231, Mekelle, Ethiopia through Grant No.: PG/MSc/EiTM/MU-NMBU/25/2019\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data sets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAndrade, W. R., Xavier, C. A. N., Coca, F. O. C. G., Arruda, L. D. O., \u0026amp; Santos, T. M. B. (2016). Biogas production from ruminant and monogastric animal manure co-digested with manipueira. \u003cem\u003eArchivos de Zootecnia\u003c/em\u003e, \u003cem\u003e65\u003c/em\u003e(251), 375\u0026ndash;380. https://doi.org/10.21071/az.v65i251.699\u003c/li\u003e\n \u003cli\u003eANDRITZ GROUP. (2013). BIOgas \u0026ndash; An important renewable energy source. \u003cem\u003eWBA Fact Sheet\u003c/em\u003e, \u003cem\u003eMay\u003c/em\u003e, 7.\u003c/li\u003e\n \u003cli\u003eBamboriya, M. . (2012). Biogas Bottling in India. \u003cem\u003eAkshya Urja\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e(5), 41\u0026ndash;43.\u003c/li\u003e\n \u003cli\u003eGebeyehu, B., Kebede, E., Kifleyohannes, T., Abebe, N., \u0026amp; Kumar, N. (2018). Prevalence of calf coccidiosis in Mekelle, northern Ethiopia. \u003cem\u003eEthiopian Veterinary Journal\u003c/em\u003e, \u003cem\u003e22\u003c/em\u003e(2), 1. https://doi.org/10.4314/evj.v22i2.1\u003c/li\u003e\n \u003cli\u003eGenet, T., Birhanu, A., \u0026amp; Solomon, K. (2018). Optimization of bio gas production from slaughterhouse wastes. \u003cem\u003eAfrican Journal of Environmental Science and Technology\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(8), 283\u0026ndash;295. https://doi.org/10.5897/ajest2017.2456\u003c/li\u003e\n \u003cli\u003eHublin, A., Schneider, D. R., \u0026amp; Džodan, J. (2014). Utilization of biogas produced by anaerobic digestion of agro-industrial waste: Energy, economic and environmental effects. \u003cem\u003eWaste Management and Research\u003c/em\u003e, \u003cem\u003e32\u003c/em\u003e(7), 626\u0026ndash;633. https://doi.org/10.1177/0734242X14539789\u003c/li\u003e\n \u003cli\u003eHunpinyo, P., Narataruksa, P., Tungkamani, S., Pana-Suppamassadu, K., \u0026amp; Chollacoop, N. (2013). Evaluation of techno-economic feasibility biomass-to-energy by using ASPEN Plus\u0026reg;: A case study of Thailand. \u003cem\u003eEnergy Procedia\u003c/em\u003e, \u003cem\u003e42\u003c/em\u003e(November 2013), 640\u0026ndash;649. https://doi.org/10.1016/j.egypro.2013.11.066\u003c/li\u003e\n \u003cli\u003eKothari, R., Tyagi, V. V., \u0026amp; Pathak, A. (2010). Waste-to-energy: A way from renewable energy sources to sustainable development. In \u003cem\u003eRenewable and Sustainable Energy Reviews\u003c/em\u003e (Vol. 14, Issue 9, pp. 3164\u0026ndash;3170). Elsevier Ltd. https://doi.org/10.1016/j.rser.2010.05.005\u003c/li\u003e\n \u003cli\u003eKunal, A., Prashanth, B., Ghosh, A., \u0026amp; Hemanth, G. (2017). A Review on production of Biogas from Slaughter house waste and poultry litter. \u003cem\u003eInternational Research Journal of Engineering and Technology(IRJET)\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e(4), 2188\u0026ndash;2192.\u003c/li\u003e\n \u003cli\u003eNallamothu, R. B., Teferra, A., \u0026amp; Rao, P. B. V. A. (2013). Biogas Purification, Compression and Bottling. \u003cem\u003eGlobal Journal of Engineering, Design \u0026amp; Technology\u003c/em\u003e, \u003cem\u003e2\u003c/em\u003e(6), 34\u0026ndash;38.\u003c/li\u003e\n \u003cli\u003ePag\u0026eacute;s, J., Jhosan\u0026eacute;, D., \u0026amp; D\u0026iacute;az, P. (2015). \u003cem\u003eBiogas From Slaughterhouse Waste\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003ePeiris, A. P. T. S. (2016). \u003cem\u003eFeasibility Study of Production of Bio Methane from Bio Wastes in Sri Lanka and Develop Cost Model for the Production Process\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003ePerez Garcia, A. (2014). \u003cem\u003eTechno-economic feasibility study of a small-scale biogas plant for treating market waste in the city of El Alto\u003c/em\u003e. \u003cem\u003eIndependen\u003c/em\u003e, 67.\u003c/li\u003e\n \u003cli\u003ePratima, K. ., \u0026amp; Bhakta, B. . (2015). Production Of Biogas From Slaughterhouse Waste In Lalitpur Sub-metropolitan City. \u003cem\u003eIOE Graduate Conference\u003c/em\u003e, 143\u0026ndash;149. https://doi.org/10.1016/j.indcrop.2023.116758\u003c/li\u003e\n \u003cli\u003eRaj, R., Kumar Singh, D., \u0026amp; Vachan Tirkey, J. (2023). Performance simulation and optimization of SI engine fueled with peach biomass-based producer gas and propane blend. \u003cem\u003eThermal Science and Engineering Progress\u003c/em\u003e, \u003cem\u003e41\u003c/em\u003e, 101816. https://doi.org/10.1016/j.tsep.2023.101816\u003c/li\u003e\n \u003cli\u003eRay, N. H. S., Mohanty, M. K., \u0026amp; Mohanty, R. C. (2016). Biogas compression and storage system for cooking applications in rural households. \u003cem\u003eInternational Journal of Renewable Energy Research\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e(2), 594\u0026ndash;598. https://doi.org/10.20508/ijrer.v6i2.3449.g6823\u003c/li\u003e\n \u003cli\u003eTsagkari, M., Couturier, J. L., Dubois, J. L., \u0026amp; Kokossis, A. (2015). Heuristics for Capital Cost Estimation: a Case Study on Biorefinery Processes. \u003cem\u003e10th National Congress of Chemical Engineering\u003c/em\u003e, \u003cem\u003eAugust\u003c/em\u003e, 9.\u003c/li\u003e\n \u003cli\u003eUS EPA. (2004). \u003cem\u003eEffluent Limitations Guidelines and Standards for the Meat and Poultry Products Industry Point Source Category\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003eXie, Y., \u0026amp; Willquist, K. (2016). \u003cem\u003eTechno-Economic Analysis of Biomethane Production With\u003c/em\u003e. \u003cem\u003eDecember\u003c/em\u003e.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Anaerobic digestion, Biogas, Digestate, Fertilizing values, Methane, Slaughterhouse biowastes","lastPublishedDoi":"10.21203/rs.3.rs-3795026/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3795026/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003eThe utilization of biomass energy such as biogas is currently getting a growing interest by researchers and the final destination of the process is its overall cost, and the profit gained. This study aims on the production of biogas from slaughterhouse biowastes (blood, manure, and rumen content) at optimal conditions, clean-up it and evaluate its feasibility. Calcium oxide and steel wool were used to remove CO\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e and H\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eS respectively.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe methane content of raw biogas and upgraded biogas are 67.20% \u0026nbsp;0.435% and 82.458% \u0026nbsp;0.503% respectively. The major fertilizing values (nitrogen, phosphorus, and potassium) content of the digestate were recorded 11,573.00, 392.40, and 426.85 mg/kg respectively. From the economic analysis, urnover ratio, rate of return on investment, payback period, and the production capacity (%) at the break-even point were estimated as 0.22, 12.63%, 4.08 years, and 16.67% respectively. Moreover, a positive value for the net present value (NPV) ($2,949,848.99), as well as 40.37% of the discount cash flow rate of return was obtained. The profitability analysis results indicate that the biogas production process is feasible and acceptable.\u003c/em\u003e\u003c/p\u003e","manuscriptTitle":"Techno-Economic Analysis of Biogas Production from Slaughterhouse Biowastes, in Mekelle City, Tigray, Ethiopia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-02 08:51:02","doi":"10.21203/rs.3.rs-3795026/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"606ff660-c4db-462c-9169-b0cc790e73c0","owner":[],"postedDate":"January 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":27877400,"name":"Physical sciences/Engineering/Chemical engineering"},{"id":27877401,"name":"Physical sciences/Engineering/Energy infrastructure"}],"tags":[],"updatedAt":"2024-04-01T08:14:26+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-02 08:51:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3795026","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3795026","identity":"rs-3795026","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}