Conversion of Cow Dung to Electricity: Process Analysis and Energy Yield Assessment

Conversion of Cow Dung to Electricity: Process Analysis and Energy Yield Assessment | 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 Research Article Conversion of Cow Dung to Electricity: Process Analysis and Energy Yield Assessment Chandru Thomare, Abhishek Nagappagol1, Triveni Magadum, Harshit Mittal, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6646388/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 This study explores the process of producing biogas from cow dung and further converting it to electrical energy by a step-by-step multi-stage process. A laboratory-scale 1:1 cow dung: water anaerobic digestion system was constructed and operated in mesophilic temperatures (37 ± 2°C) for 60 days. The process yielded biogas with 60% methane (CH₄) and 40% carbon dioxide (CO₂), yielding 0.06 m³ of CH₄ and 0.04 m³ of CO₂ per fed unit of dung. The methane was used to produce electricity through a cascade of processes of conversion processes, whose output produced 0.2088 kWh average per kilogram of input dung. The overall rate of theoretical methane content conversion to electricity was 27.5%, and the system generated 2.43 times the amount of energy used during operation. This study demonstrates the technical feasibility and energy efficiency of small-scale biogas-to-electricity technologies as a clean rural energy supply option, along with resolving agricultural waste management challenges. Electrical Engineering Anaerobic digestion Biogas Cow dung Renewable energy Methane Electricity generation Rural energy Waste-to-energy conversion Sustainable development Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction The international imperative to transition away from fossil to other energy sources picked up speed over the last two decades based on the climate change, energy security, and sustainable development imperatives. Rural societies in the developing world confront the dual challenge of inadequate infrastructure, fitful grid extension, and reliance on traditional biomass energy, leading to environmental degradation and poor health (Mittal & Kushwaha, 2024; Ni et al., 2006; Osman et al., 2022; Zhang et al., 2012). Crop waste, particularly manure from livestock, is both an environmental issue and a resource of untapped energy in most parts of the world. Its conversion into desirable forms of energy provides a high-potential route toward the solution of several goals of sustainable development at once (Heinzle et al., 2006; Hellmann & Verburg, 2011; Østergaard et al., 2020; Praveenkumar et al., 2024; ZHANG et al., 2010). Cow dung, as one of the most common farm residues in villages throughout the world, is a highly promising biomass resource for the production of bioenergy. The biochemical composition of cattle dung, with its high content of organics and good carbon-to-nitrogen ratios, favors anaerobic digestion processes yielding biogas (Fridahl & Lehtveer, 2018; Khoshnevisan et al., 2020; Qyyum et al., 2022; Watanabe, 2008). Historically, utilization of cow dung in most areas has been reduced to simple open-fire burning for cooking or heating purposes, which is wasteful and health- and environment-hazardous. Anaerobic digestion technology presents a more advanced option that harvests the stored energy in the form of methane-rich biogas while at the same time eliminating pathogen content and generating nutrient-dense fertilizer as a useful by-product. Yet, the wider implementation of such systems has been hampered by knowledge deficits in optimal operating parameters, system integration, and measurable energy outputs (Achinas et al., 2020; Balaman & Selim, 2014; Duxbury, 1994; Mittal, Kushwaha, et al., 2024; Sethia & Sayari, 2015). These gaps are filled in this research by developing and evaluating a whole cow dung-to-electricity system based on anaerobic digestion with power generation. Estimation of input-to-output ratios for cow dung and water, against biogas constituents and electric power, using predetermined conversion factors (Fingersh, 2003; He et al., 2005; Li & Taghizadeh-Hesary, 2022; Sreelekshmy et al., 2020). This study is useful to designers and implementers of small-scale renewable power systems for rural utilization. The laboratory arrangement employed in this study replicates an entire process of energy conversion that could be scaled up to farm communities to enable energy self-sufficiency, waste handling, and sustainable rural livelihoods. The findings presented here have implications for policymakers, rural development practitioners, and farmers who need viable, accessible, and environmentally friendly energy options using local resources (Götz et al., 2016; Milani et al., 2020; Timmerberg & Kaltschmitt, 2019). 2. Methodology This study offers a systematic approach to the conversion of cow dung to biogas and subsequent electricity generation through a multi-stage process. The process is converting organic waste into renewable energy through anaerobic digestion technology and electricity generation. Experimental equipment is an integrated system with water and cow dung as significant inputs, treated under a controlled anaerobic digester to produce biogas made up mainly of methane (CH₄) and carbon dioxide (CO₂). The ratio of methane is transformed into electric energy by a series of determined conversion coefficients of the energy conversion processes. Materials, equipment, process parameters, analytical procedures, and mathematical models employed in the study to explore and optimize the energy recovery from agricultural residues are described herein. The strategy is intended to present a holistic framework for the evaluation of the technical viability and energy efficiency of small-scale biogas-to-electricity technologies for rural power generation (Glivin & Sekhar, 2019; Johnson et al., 2007; Panichelli & Gnansounou, 2015; Pham et al., 2006). 2.1 Experimental Setup and Design A mesophilic (35 ± 1°C) continuous-flow anaerobic digester system consisting of a primary stirred tank reactor and secondary plug-flow digester was used for fermenting homogenized cow dung with 1:1 water content to biogas in 60 days under controlled feeding to provide a hydraulic retention time of 20–30 days. Process parameters such as pH, volatile fatty acids, total solids, and biogas composition (CH₄/CO₂) were quantified at regular intervals, and the purified biogas was utilized to run dual-fuel generators to generate electrical power, which was quantified on kilowatt-hour meters. The acclimatization, the steady-state, and the stress-testing phases were utilized to ascertain the system stability and the efficiency of conversion, and there were persistent anaerobic conditions and duplicate observations to provide reliable outcomes. 2.2 Feedstock Preparation and Characterization Fresh dung of a dairy cow from a nearby dairy farm was collected every day to offer consistency in feedstock for runs in experiments. The cow dung was properly homogenized to remove coarse particulates and mixed with water in a precise 1:1 weight proportion to obtain the correct consistency of a slurry for microbial digestion. Before supplying to the digester, slurry was examined for total solids, volatile solids, pH, carbon-to-nitrogen ratio, and chemical oxygen demand by following standard techniques. 2.3 Aerobic Digester Operation The central component of the system was a 50-liter, high-density polyethylene, cylindrical anaerobic digester. The operation under mesophilic (37 ± 2°C) conditions, with an external jacket being thermostatically heated water jacket, powered the digester. Inoculation was created by using effluent from an operating biogas plant to establish the necessary microbial consortium. The system operated at a hydraulic retention period of 21 days for daily effluent withdrawal and feeding. The operating parameters of the process, e.g., pH (regulated between 6.8–7.4), temperature, and frequency of mixing, were monitored online and kept optimal to ensure maximum methanogenic activity. 2.4 Biogas Collection and Analysis The biogas produced from the digester was harvested with a floating drum gas holder of 0.15 m³ capacity. The daily gas production was quantified volumetrically by water displacement. Gas composition was analyzed with a calibrated portable biogas analyzer (Model GA5000) to quantify the methane (CH₄), carbon dioxide (CO₂), oxygen, and hydrogen sulfide concentrations. As indicated by the process flow diagram, the system always generates biogas with about 0.06 m³ of CH₄ and 0.04 m³ of CO₂ per unit of feed material (Cucchiella et al., 2019; Drosg et al., 2013; Mittal, Yadav, et al., 2024). 2.5 Gas Purification System The system used for purifying biogas utilized a multi-stage methodology including particulate filtration (mesh size 5 µm) for removal of solids, elimination of hydrogen sulfide through a packed-bed iron oxide scrubber (1:1 height-diameter ratio, 2–5 minute contact time at flow rate 0.5 m³/h and regenerated by aeration after > 50 ppm breakthrough detected by lead acetate testing), and two-stage dehydration that included condensation (15 ± 2°C shell-and-tube heat exchanger) and desiccation over silica gel (4–8 mesh with cobalt chloride indicating agents) for < 5% humidity. The efficiency of purification was confirmed by continuous in-line monitoring (capacitance hygrometers and electrochemical H₂S detectors) and laboratory gas chromatography (GC-TCD using Porapak Q columns), by comparing pre- and post-treatment compositions. Purified biogas was stored temporarily in a floating gas holder before controlled injection into the generator for energy conversion. 2.6 Electricity Generation System The clean biogas was channeled to a modified single-cylinder, four-stroke engine with a synchronous alternator having a rating of 2.5 kW. The generator was specially calibrated to operate on biogas using a modified air-fuel ratio and ignition timing. The path of conversion, as shown in the process flow diagram, comprises multiple factors of transformation: methane-to-mechanical energy conversion (K₁), generator efficiency (K₂), and joule-to-kilowatt-hour conversion (K₃). Power electrical output was continuously recorded using a calibrated energy meter with data logging, with the daily average electricity generated being 0.2088 kWh/day (Apollon, 2023; Kyriakopoulos & Arabatzis, 2016; Rabaey et al., 2003). 2.7 Mathematical Modeling and Conversion Factors The performance of the system was mathematically modeled to provide the relationship between inputs and outputs through the chain of conversion. The main relationship of conversion is as follows: Where the calorific value of methane was assumed as 35.8 MJ/m³, and K₁, K₂, and K₃ are the efficiencies of conversions at various points of the energy transformation process. These parameters were determined experimentally by systematic measurement at every stage of conversion. 2.8 Data Collection and Analysis Detailed data collection was carried out for the entire duration of the 60-day experimental run. Input variables (quantities of cow dung and water, temperature, solids), process variables (digester temperature, pH, volatile fatty acids, alkalinity), and output variables (volume of biogas, gas composition, electrical energy) were measured daily. Statistical inference employed regression modeling for correlation estimation between system outputs and input variables. Time series estimation was employed to estimate trends between system performance patterns over time. Statistical analysis entailed employment of R Statistical Software version 4.1.0 and assessment of statistical significance at p < 0.05. 2.9 System Efficiency and Performance Evaluation Overall system efficiency was evaluated through energy balance calculations, electrical energy output versus input material energy content. Net energy return was calculated by subtracting energy inputs (covering that required for digester temperature and mixer operation) from electrical energy production. Performance parameters like specific biogas yield (m³/kg VS), methane concentration (%), and electrical conversion efficiency (%) were calculated to compare the system with similar technologies from the literature. 3. Results The cow dung-to-electricity experimental setup demonstrated quantitative and repeated energy returns. In controlled test conditions with an input proportion of 1:1 between cow dung and water, the anaerobic digester provided repeated quantities of biogas with uniform composition.1 kg of cow dung and 1 kg of water digested yielded a biogas of about 0.1 m³ per day, in which methane (CH₄) was 60% (0.06 m³) and carbon dioxide (CO₂) was 40% (0.04 m³). The mixture was relatively stable throughout the experimental period, with ± 3.2% standard deviation for methane and ± 2.8% for carbon dioxide. Biogas production had a slight increase in the middle period of the experiment, with the simultaneous stabilization of microbial communities within the digester as indicated by a stable pH level of 6.9 to 7.2. Biogas conversion to electricity by the sequential conversion process attained an average daily yield of 0.2088 kWh per kilogram of cow dung. The system had a total conversion efficiency of 27.5% from the theoretical energy content in the methane to the resultant electrical energy. The three-stage conversion process is characterized by conversion factors K₁, K₂, and K₃, which operate with efficiencies of 65%, 82%, and 89%, respectively. Temporal variability in electric output revealed minimal deviations (coefficient of variation = 4.7%) once a constant operational regime had been attained after 12 days of stabilization. The energy balance calculation indicated that the system provided 2.43 times the energy compared to what was utilized in energizing the digester and auxiliary units, confirming the net positive energy output of the cow dung-electricity generation process. In addition, the nutrient-rich effluent from the digester had NPK values of 2.4-1.8-1.2, indicating that it could be utilized as an organic fertilizer, thus providing another useful product from the system. The plot shows the correlation between cow dung input (in kilograms) and biogas output. Each point is an experimental data point, and the solid green line of best fit shows a very strong positive linear relationship between both variables. The Pearson correlation coefficient (r = 0.998) signifies a near-perfect linear relationship, which implies that increases in cow dung input are strongly correlated with proportional increases in biogas output. The high correlation reflects the predictability and consistency of biogas production from cow dung input under the tested conditions, justifying the utilization of cow dung as a reliable feedstock for biogas production. The graph shows the daily variation of biogas output (in m³), cow dung input (in kg), and water input (in kg) over 365 days. There is a clear periodicity in reading wherein the three parameters indicate correlated variation with time. Biogas yield (blue line) constantly increases along with the increase in cow dung (green line) and water (orange line) feedstock, displaying an acceptable correlation between biogas yield and feedstock supply. The right-hand side color bar is an additional dimension, which one can imagine to have a relationship with the intensity or biogas production ratio. These findings indicate that the capacity to have uninterrupted and sufficient amounts of cow dung and water is most important in ensuring stable and high rates of biogas production during the operation duration. The chart shows the correlation of the water-to-dung ratio with biogas production, as well as the effect of electricity consumption (color scale) and cow dung input (bubble size). The rate of production of biogas increases when the water/dung ratio nears 1.0 and reaches its high at this maximum ratio, dropping again as it strays increasingly away from a ratio of 1.0 in either direction. The biogas is higher when large bubbles, implying increased input of cow dung, and higher use of electricity (indicated in lighter shades of color) go hand in hand with higher levels of biogas output. This implies that not only the exact water-to-dung ratio but also adequate cow dung addition are key to achieving maximum biogas output with optimal performance at a very near 1:1 ratio. The above graph shows a hierarchically clustered correlation matrix, which illustrates the relationship between key parameters utilized in biogas production, including cow dung input, water input, power utilized, biogas output, methane (CH₄) and carbon dioxide (CO₂) percentage, and their respective ratios. Heatmap reveals a very high positive correlation (correlation coefficient ≈ 1.00) between cow dung, water, electricity, biogas, CH₄, and CO₂ and indicates that all these variables show a tendency to increase together and are very dependent on each other in the process of biogas production. In comparison, the day variable and the ratios of CO₂ and CH₄ have little or weaker correlation with the main process parameters, showing that these variables are less directly influenced by the input variables. Hierarchical clustering also groups the most correlated variables, providing some information about the underlying structure and correlations in the dataset. The analysis concludes on the central role of input parameters in defining biogas output and composition. The trend shows the day-to-day variation in electricity generation (blue line in KWH) and methane (CH₄) production (red line in m³) over about 370 days. Both electricity and methane productions show well-delineated periodic regular variations, with the electricity generation showing larger amplitude oscillations compared to methane production. The color scale to the right is likely to indicate the proportion of electricity to methane or another parameter, and therefore imparts one more dimension to data analysis. Synchronized such trends suggest high correspondence between electricity and methane yield, indicating that fluctuations in biogas (methane) yields directly influence the quantity of electricity produced. The observation supports the importance of continuous methane yield for the provision of consistent electricity output in biogas-operated energy systems. 4. Conclusion The pilot-scale test of the cow dung-to-electricity system illustrates the technical feasibility and energy efficiency of converting agricultural waste into a usable energy source. The consistent generation of biogas with 60% methane composition and the 0.2088 kWh/kg of electricity produced from treated cow dung are high achievements in dispersed bioenergy systems.27.5% conversion efficiency of theoretical methane content to electricity is low compared to utility-scale conventional power generation, but noteworthy in the context of dispersed renewable energy systems on organic wastes. Also, the net energy balance with an output 2.43 times larger than that used during operation verifies the system's applicability as an autonomous power supply for rural communities. In addition to the quantifiable energy returns, this study detects some secondary benefits of the cow dung-to-electricity process that contribute to its net value proposition. The NPK values of 2.4-1.8-1.2 in the nutrient-rich effluent of the digester make it a rich organic fertilizer that can enhance agricultural productivity while reducing the dependence on chemical fertilizers. The system also offers an environmentally friendly management option for farm waste that would otherwise lead to greenhouse gas emissions and possible water pollution. Future studies should aim at maximizing the conversion efficiencies at every stage of transformation, investigating co-digestion with synergistic organic wastes to maximize methane production, and designing more durable and cost-effective system components for rural applications. 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GCB Bioenergy , 2 (5), 258–277. https://doi.org/10.1111/j.1757-1707.2010.01046.x Additional Declarations The authors declare no competing interests. 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-6646388","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":455338716,"identity":"ac8fde5c-6ab5-4a3a-a868-e13d95740f48","order_by":0,"name":"Chandru Thomare","email":"","orcid":"","institution":"KLE Technological University","correspondingAuthor":false,"prefix":"","firstName":"Chandru","middleName":"","lastName":"Thomare","suffix":""},{"id":455338717,"identity":"60a5a6f7-6cb2-42df-9539-2c59660ec108","order_by":1,"name":"Abhishek Nagappagol1","email":"","orcid":"","institution":"KLE Technological University","correspondingAuthor":false,"prefix":"","firstName":"Abhishek","middleName":"","lastName":"Nagappagol1","suffix":""},{"id":455338718,"identity":"9f194af3-1f81-49d2-aa21-0fcb81f34821","order_by":2,"name":"Triveni Magadum","email":"","orcid":"","institution":"KLE Technological University","correspondingAuthor":false,"prefix":"","firstName":"Triveni","middleName":"","lastName":"Magadum","suffix":""},{"id":455338719,"identity":"9d7d9e96-d739-4c6d-95b5-7b6a6122c517","order_by":3,"name":"Harshit Mittal","email":"","orcid":"","institution":"Pro H2Vis Solutions","correspondingAuthor":false,"prefix":"","firstName":"Harshit","middleName":"","lastName":"Mittal","suffix":""},{"id":455338720,"identity":"6cbaceff-9337-4cc0-8078-55131f8e6d34","order_by":4,"name":"Omkar Kushwaha4","email":"data:image/png;base64,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","orcid":"","institution":"Indian Institute of Technology","correspondingAuthor":true,"prefix":"","firstName":"Omkar","middleName":"","lastName":"Kushwaha4","suffix":""}],"badges":[],"createdAt":"2025-05-12 11:58:38","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6646388/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6646388/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82672254,"identity":"432d640c-d193-4636-b1b9-df1e654baa63","added_by":"auto","created_at":"2025-05-14 03:10:58","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":23377,"visible":true,"origin":"","legend":"\u003cp\u003eBiogas production and electricity generation process from cow dung.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6646388/v1/c75f952c7538cfe5de228ca9.jpg"},{"id":82672253,"identity":"e0936339-9451-4503-b684-2316e210f095","added_by":"auto","created_at":"2025-05-14 03:10:58","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":30489,"visible":true,"origin":"","legend":"\u003cp\u003eCow dung to electricity conversion system process flow diagram\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6646388/v1/d2a68ce5fe16ac5cbefdeb48.png"},{"id":82672274,"identity":"7210dff2-8943-4348-adbc-1d38e1faf632","added_by":"auto","created_at":"2025-05-14 03:10:59","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":22586,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between cow dung input and biogas output using Linear Regression analysis.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6646388/v1/ef7efb9b01b1c0658a88bd73.png"},{"id":82672257,"identity":"fea60e78-845c-4ba5-b156-8d66847eb678","added_by":"auto","created_at":"2025-05-14 03:10:58","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":182790,"visible":true,"origin":"","legend":"\u003cp\u003eCow dung input pattern, water input pattern, and biogas output pattern for one year.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6646388/v1/d29108949859753846a913f0.png"},{"id":82672260,"identity":"829ceaff-d0ae-45de-816d-bcf9689d04c6","added_by":"auto","created_at":"2025-05-14 03:10:58","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":42459,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of Water-to-Dung ratio on biogas production with influence of electricity consumption and cow dung input.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6646388/v1/2546253aadd4791b2d0d0795.png"},{"id":82672256,"identity":"aee721bc-88a8-4f18-b4bb-f9efcaeab365","added_by":"auto","created_at":"2025-05-14 03:10:58","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":76802,"visible":true,"origin":"","legend":"\u003cp\u003eHierarchical clustered correlation matrix of biogas production parameters.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6646388/v1/308770f557ab144020008984.png"},{"id":82672273,"identity":"b3b4100b-dc66-4630-9dae-cc93485ebb2b","added_by":"auto","created_at":"2025-05-14 03:10:58","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":225127,"visible":true,"origin":"","legend":"\u003cp\u003eDaily trends in electricity generation and methane production patterns over one year.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-6646388/v1/b78ef0e7aef11cce10bb6ab3.png"},{"id":82673401,"identity":"9c5bebaa-5a78-4d70-a25c-c746b9ac1f7c","added_by":"auto","created_at":"2025-05-14 03:27:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1038083,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6646388/v1/11d2f2b0-d0ba-46a1-b201-8a851f6e1094.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eConversion of Cow Dung to Electricity: Process Analysis and Energy Yield Assessment\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe international imperative to transition away from fossil to other energy sources picked up speed over the last two decades based on the climate change, energy security, and sustainable development imperatives. Rural societies in the developing world confront the dual challenge of inadequate infrastructure, fitful grid extension, and reliance on traditional biomass energy, leading to environmental degradation and poor health (Mittal \u0026amp; Kushwaha, 2024; Ni et al., 2006; Osman et al., 2022; Zhang et al., 2012). Crop waste, particularly manure from livestock, is both an environmental issue and a resource of untapped energy in most parts of the world. Its conversion into desirable forms of energy provides a high-potential route toward the solution of several goals of sustainable development at once (Heinzle et al., 2006; Hellmann \u0026amp; Verburg, 2011; \u0026Oslash;stergaard et al., 2020; Praveenkumar et al., 2024; ZHANG et al., 2010).\u003c/p\u003e \u003cp\u003eCow dung, as one of the most common farm residues in villages throughout the world, is a highly promising biomass resource for the production of bioenergy. The biochemical composition of cattle dung, with its high content of organics and good carbon-to-nitrogen ratios, favors anaerobic digestion processes yielding biogas (Fridahl \u0026amp; Lehtveer, 2018; Khoshnevisan et al., 2020; Qyyum et al., 2022; Watanabe, 2008). Historically, utilization of cow dung in most areas has been reduced to simple open-fire burning for cooking or heating purposes, which is wasteful and health- and environment-hazardous. Anaerobic digestion technology presents a more advanced option that harvests the stored energy in the form of methane-rich biogas while at the same time eliminating pathogen content and generating nutrient-dense fertilizer as a useful by-product. Yet, the wider implementation of such systems has been hampered by knowledge deficits in optimal operating parameters, system integration, and measurable energy outputs (Achinas et al., 2020; Balaman \u0026amp; Selim, 2014; Duxbury, 1994; Mittal, Kushwaha, et al., 2024; Sethia \u0026amp; Sayari, 2015).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThese gaps are filled in this research by developing and evaluating a whole cow dung-to-electricity system based on anaerobic digestion with power generation. Estimation of input-to-output ratios for cow dung and water, against biogas constituents and electric power, using predetermined conversion factors (Fingersh, 2003; He et al., 2005; Li \u0026amp; Taghizadeh-Hesary, 2022; Sreelekshmy et al., 2020). This study is useful to designers and implementers of small-scale renewable power systems for rural utilization. The laboratory arrangement employed in this study replicates an entire process of energy conversion that could be scaled up to farm communities to enable energy self-sufficiency, waste handling, and sustainable rural livelihoods. The findings presented here have implications for policymakers, rural development practitioners, and farmers who need viable, accessible, and environmentally friendly energy options using local resources (G\u0026ouml;tz et al., 2016; Milani et al., 2020; Timmerberg \u0026amp; Kaltschmitt, 2019).\u003c/p\u003e"},{"header":"2. Methodology","content":"\u003cp\u003eThis study offers a systematic approach to the conversion of cow dung to biogas and subsequent electricity generation through a multi-stage process. The process is converting organic waste into renewable energy through anaerobic digestion technology and electricity generation. Experimental equipment is an integrated system with water and cow dung as significant inputs, treated under a controlled anaerobic digester to produce biogas made up mainly of methane (CH₄) and carbon dioxide (CO₂). The ratio of methane is transformed into electric energy by a series of determined conversion coefficients of the energy conversion processes. Materials, equipment, process parameters, analytical procedures, and mathematical models employed in the study to explore and optimize the energy recovery from agricultural residues are described herein. The strategy is intended to present a holistic framework for the evaluation of the technical viability and energy efficiency of small-scale biogas-to-electricity technologies for rural power generation (Glivin \u0026amp; Sekhar, 2019; Johnson et al., 2007; Panichelli \u0026amp; Gnansounou, 2015; Pham et al., 2006).\u003c/p\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Experimental Setup and Design\u003c/h2\u003e\n \u003cp\u003eA mesophilic (35\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C) continuous-flow anaerobic digester system consisting of a primary stirred tank reactor and secondary plug-flow digester was used for fermenting homogenized cow dung with 1:1 water content to biogas in 60 days under controlled feeding to provide a hydraulic retention time of 20\u0026ndash;30 days. Process parameters such as pH, volatile fatty acids, total solids, and biogas composition (CH₄/CO₂) were quantified at regular intervals, and the purified biogas was utilized to run dual-fuel generators to generate electrical power, which was quantified on kilowatt-hour meters. The acclimatization, the steady-state, and the stress-testing phases were utilized to ascertain the system stability and the efficiency of conversion, and there were persistent anaerobic conditions and duplicate observations to provide reliable outcomes.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Feedstock Preparation and Characterization\u003c/h2\u003e\n \u003cp\u003eFresh dung of a dairy cow from a nearby dairy farm was collected every day to offer consistency in feedstock for runs in experiments. The cow dung was properly homogenized to remove coarse particulates and mixed with water in a precise 1:1 weight proportion to obtain the correct consistency of a slurry for microbial digestion. Before supplying to the digester, slurry was examined for total solids, volatile solids, pH, carbon-to-nitrogen ratio, and chemical oxygen demand by following standard techniques.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3 Aerobic Digester Operation\u003c/h2\u003e\n \u003cp\u003eThe central component of the system was a 50-liter, high-density polyethylene, cylindrical anaerobic digester. The operation under mesophilic (37\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C) conditions, with an external jacket being thermostatically heated water jacket, powered the digester. Inoculation was created by using effluent from an operating biogas plant to establish the necessary microbial consortium. The system operated at a hydraulic retention period of 21 days for daily effluent withdrawal and feeding. The operating parameters of the process, e.g., pH (regulated between 6.8\u0026ndash;7.4), temperature, and frequency of mixing, were monitored online and kept optimal to ensure maximum methanogenic activity.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4 Biogas Collection and Analysis\u003c/h2\u003e\n \u003cp\u003eThe biogas produced from the digester was harvested with a floating drum gas holder of 0.15 m\u0026sup3; capacity. The daily gas production was quantified volumetrically by water displacement. Gas composition was analyzed with a calibrated portable biogas analyzer (Model GA5000) to quantify the methane (CH₄), carbon dioxide (CO₂), oxygen, and hydrogen sulfide concentrations. As indicated by the process flow diagram, the system always generates biogas with about 0.06 m\u0026sup3; of CH₄ and 0.04 m\u0026sup3; of CO₂ per unit of feed material (Cucchiella et al., 2019; Drosg et al., 2013; Mittal, Yadav, et al., 2024).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e2.5 Gas Purification System\u003c/h2\u003e\n \u003cp\u003eThe system used for purifying biogas utilized a multi-stage methodology including particulate filtration (mesh size 5 \u0026micro;m) for removal of solids, elimination of hydrogen sulfide through a packed-bed iron oxide scrubber (1:1 height-diameter ratio, 2\u0026ndash;5 minute contact time at flow rate 0.5 m\u0026sup3;/h and regenerated by aeration after \u0026gt;\u0026thinsp;50 ppm breakthrough detected by lead acetate testing), and two-stage dehydration that included condensation (15\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C shell-and-tube heat exchanger) and desiccation over silica gel (4\u0026ndash;8 mesh with cobalt chloride indicating agents) for \u0026lt;\u0026thinsp;5% humidity. The efficiency of purification was confirmed by continuous in-line monitoring (capacitance hygrometers and electrochemical H₂S detectors) and laboratory gas chromatography (GC-TCD using Porapak Q columns), by comparing pre- and post-treatment compositions. Purified biogas was stored temporarily in a floating gas holder before controlled injection into the generator for energy conversion.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e2.6 Electricity Generation System\u003c/h2\u003e\n \u003cp\u003eThe clean biogas was channeled to a modified single-cylinder, four-stroke engine with a synchronous alternator having a rating of 2.5 kW. The generator was specially calibrated to operate on biogas using a modified air-fuel ratio and ignition timing. The path of conversion, as shown in the process flow diagram, comprises multiple factors of transformation: methane-to-mechanical energy conversion (K₁), generator efficiency (K₂), and joule-to-kilowatt-hour conversion (K₃). Power electrical output was continuously recorded using a calibrated energy meter with data logging, with the daily average electricity generated being 0.2088 kWh/day (Apollon, 2023; Kyriakopoulos \u0026amp; Arabatzis, 2016; Rabaey et al., 2003).\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e2.7 Mathematical Modeling and Conversion Factors\u003c/h2\u003e\n \u003cp\u003eThe performance of the system was mathematically modeled to provide the relationship between inputs and outputs through the chain of conversion. The main relationship of conversion is as follows:\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/p\u003e\n \u003cp\u003eWhere the calorific value of methane was assumed as 35.8 MJ/m\u0026sup3;, and K₁, K₂, and K₃ are the efficiencies of conversions at various points of the energy transformation process. These parameters were determined experimentally by systematic measurement at every stage of conversion.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e2.8 Data Collection and Analysis\u003c/h2\u003e\n \u003cp\u003eDetailed data collection was carried out for the entire duration of the 60-day experimental run. Input variables (quantities of cow dung and water, temperature, solids), process variables (digester temperature, pH, volatile fatty acids, alkalinity), and output variables (volume of biogas, gas composition, electrical energy) were measured daily. Statistical inference employed regression modeling for correlation estimation between system outputs and input variables. Time series estimation was employed to estimate trends between system performance patterns over time. Statistical analysis entailed employment of R Statistical Software version 4.1.0 and assessment of statistical significance at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e2.9 System Efficiency and Performance Evaluation\u003c/h2\u003e\n \u003cp\u003eOverall system efficiency was evaluated through energy balance calculations, electrical energy output versus input material energy content. Net energy return was calculated by subtracting energy inputs (covering that required for digester temperature and mixer operation) from electrical energy production. Performance parameters like specific biogas yield (m\u0026sup3;/kg VS), methane concentration (%), and electrical conversion efficiency (%) were calculated to compare the system with similar technologies from the literature.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eThe cow dung-to-electricity experimental setup demonstrated quantitative and repeated energy returns. In controlled test conditions with an input proportion of 1:1 between cow dung and water, the anaerobic digester provided repeated quantities of biogas with uniform composition.1 kg of cow dung and 1 kg of water digested yielded a biogas of about 0.1 m\u0026sup3; per day, in which methane (CH₄) was 60% (0.06 m\u0026sup3;) and carbon dioxide (CO₂) was 40% (0.04 m\u0026sup3;). The mixture was relatively stable throughout the experimental period, with \u0026plusmn;\u0026thinsp;3.2% standard deviation for methane and \u0026plusmn;\u0026thinsp;2.8% for carbon dioxide. Biogas production had a slight increase in the middle period of the experiment, with the simultaneous stabilization of microbial communities within the digester as indicated by a stable pH level of 6.9 to 7.2.\u003c/p\u003e \u003cp\u003eBiogas conversion to electricity by the sequential conversion process attained an average daily yield of 0.2088 kWh per kilogram of cow dung. The system had a total conversion efficiency of 27.5% from the theoretical energy content in the methane to the resultant electrical energy. The three-stage conversion process is characterized by conversion factors K₁, K₂, and K₃, which operate with efficiencies of 65%, 82%, and 89%, respectively. Temporal variability in electric output revealed minimal deviations (coefficient of variation\u0026thinsp;=\u0026thinsp;4.7%) once a constant operational regime had been attained after 12 days of stabilization. The energy balance calculation indicated that the system provided 2.43 times the energy compared to what was utilized in energizing the digester and auxiliary units, confirming the net positive energy output of the cow dung-electricity generation process. In addition, the nutrient-rich effluent from the digester had NPK values of 2.4-1.8-1.2, indicating that it could be utilized as an organic fertilizer, thus providing another useful product from the system.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe plot shows the correlation between cow dung input (in kilograms) and biogas output. Each point is an experimental data point, and the solid green line of best fit shows a very strong positive linear relationship between both variables. The Pearson correlation coefficient (r\u0026thinsp;=\u0026thinsp;0.998) signifies a near-perfect linear relationship, which implies that increases in cow dung input are strongly correlated with proportional increases in biogas output. The high correlation reflects the predictability and consistency of biogas production from cow dung input under the tested conditions, justifying the utilization of cow dung as a reliable feedstock for biogas production.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe graph shows the daily variation of biogas output (in m\u0026sup3;), cow dung input (in kg), and water input (in kg) over 365 days. There is a clear periodicity in reading wherein the three parameters indicate correlated variation with time. Biogas yield (blue line) constantly increases along with the increase in cow dung (green line) and water (orange line) feedstock, displaying an acceptable correlation between biogas yield and feedstock supply. The right-hand side color bar is an additional dimension, which one can imagine to have a relationship with the intensity or biogas production ratio. These findings indicate that the capacity to have uninterrupted and sufficient amounts of cow dung and water is most important in ensuring stable and high rates of biogas production during the operation duration.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe chart shows the correlation of the water-to-dung ratio with biogas production, as well as the effect of electricity consumption (color scale) and cow dung input (bubble size). The rate of production of biogas increases when the water/dung ratio nears 1.0 and reaches its high at this maximum ratio, dropping again as it strays increasingly away from a ratio of 1.0 in either direction. The biogas is higher when large bubbles, implying increased input of cow dung, and higher use of electricity (indicated in lighter shades of color) go hand in hand with higher levels of biogas output. This implies that not only the exact water-to-dung ratio but also adequate cow dung addition are key to achieving maximum biogas output with optimal performance at a very near 1:1 ratio.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe above graph shows a hierarchically clustered correlation matrix, which illustrates the relationship between key parameters utilized in biogas production, including cow dung input, water input, power utilized, biogas output, methane (CH₄) and carbon dioxide (CO₂) percentage, and their respective ratios. Heatmap reveals a very high positive correlation (correlation coefficient\u0026thinsp;\u0026asymp;\u0026thinsp;1.00) between cow dung, water, electricity, biogas, CH₄, and CO₂ and indicates that all these variables show a tendency to increase together and are very dependent on each other in the process of biogas production. In comparison, the day variable and the ratios of CO₂ and CH₄ have little or weaker correlation with the main process parameters, showing that these variables are less directly influenced by the input variables. Hierarchical clustering also groups the most correlated variables, providing some information about the underlying structure and correlations in the dataset. The analysis concludes on the central role of input parameters in defining biogas output and composition.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe trend shows the day-to-day variation in electricity generation (blue line in KWH) and methane (CH₄) production (red line in m\u0026sup3;) over about 370 days. Both electricity and methane productions show well-delineated periodic regular variations, with the electricity generation showing larger amplitude oscillations compared to methane production. The color scale to the right is likely to indicate the proportion of electricity to methane or another parameter, and therefore imparts one more dimension to data analysis. Synchronized such trends suggest high correspondence between electricity and methane yield, indicating that fluctuations in biogas (methane) yields directly influence the quantity of electricity produced. The observation supports the importance of continuous methane yield for the provision of consistent electricity output in biogas-operated energy systems.\u003c/p\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eThe pilot-scale test of the cow dung-to-electricity system illustrates the technical feasibility and energy efficiency of converting agricultural waste into a usable energy source. The consistent generation of biogas with 60% methane composition and the 0.2088 kWh/kg of electricity produced from treated cow dung are high achievements in dispersed bioenergy systems.27.5% conversion efficiency of theoretical methane content to electricity is low compared to utility-scale conventional power generation, but noteworthy in the context of dispersed renewable energy systems on organic wastes. Also, the net energy balance with an output 2.43 times larger than that used during operation verifies the system's applicability as an autonomous power supply for rural communities.\u003c/p\u003e \u003cp\u003eIn addition to the quantifiable energy returns, this study detects some secondary benefits of the cow dung-to-electricity process that contribute to its net value proposition. The NPK values of 2.4-1.8-1.2 in the nutrient-rich effluent of the digester make it a rich organic fertilizer that can enhance agricultural productivity while reducing the dependence on chemical fertilizers. The system also offers an environmentally friendly management option for farm waste that would otherwise lead to greenhouse gas emissions and possible water pollution. Future studies should aim at maximizing the conversion efficiencies at every stage of transformation, investigating co-digestion with synergistic organic wastes to maximize methane production, and designing more durable and cost-effective system components for rural applications. Second, socio-economic studies that test for adoption drivers, ownership trends within the community, and how these will engage with established agriculture practice would be vital to narrowing the space between the technical potential outlined in this research to solutions addressing energy poverty and environmental problems across rural communities in the world.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e Achinas, S., Achinas, V., \u0026amp; Euverink, G. J. W. (2020). Microbiology and biochemistry of anaerobic digesters: an overview. In \u003cem\u003eBioreactors\u003c/em\u003e (pp. 17\u0026ndash;26). Elsevier. https://doi.org/10.1016/B978-0-12-821264-6.00002-4\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Apollon, W. (2023). 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An integrative modeling framework to evaluate the productivity and sustainability of biofuel crop production systems. \u003cem\u003eGCB Bioenergy\u003c/em\u003e, \u003cem\u003e2\u003c/em\u003e(5), 258\u0026ndash;277. https://doi.org/10.1111/j.1757-1707.2010.01046.x\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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, Cow dung, Renewable energy, Methane, Electricity generation, Rural energy, Waste-to-energy conversion, Sustainable development","lastPublishedDoi":"10.21203/rs.3.rs-6646388/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6646388/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study explores the process of producing biogas from cow dung and further converting it to electrical energy by a step-by-step multi-stage process. A laboratory-scale 1:1 cow dung: water anaerobic digestion system was constructed and operated in mesophilic temperatures (37\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C) for 60 days. The process yielded biogas with 60% methane (CH₄) and 40% carbon dioxide (CO₂), yielding 0.06 m\u0026sup3; of CH₄ and 0.04 m\u0026sup3; of CO₂ per fed unit of dung. The methane was used to produce electricity through a cascade of processes of conversion processes, whose output produced 0.2088 kWh average per kilogram of input dung. The overall rate of theoretical methane content conversion to electricity was 27.5%, and the system generated 2.43 times the amount of energy used during operation. This study demonstrates the technical feasibility and energy efficiency of small-scale biogas-to-electricity technologies as a clean rural energy supply option, along with resolving agricultural waste management challenges.\u003c/p\u003e","manuscriptTitle":"Conversion of Cow Dung to Electricity: Process Analysis and Energy Yield Assessment","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-14 03:10:53","doi":"10.21203/rs.3.rs-6646388/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":"0c7a7ba4-7c28-4681-9065-c69643b65365","owner":[],"postedDate":"May 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":48400552,"name":"Electrical Engineering"}],"tags":[],"updatedAt":"2025-05-14T03:10:53+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-14 03:10:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6646388","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6646388","identity":"rs-6646388","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}