The development and evaluation of a portable polyethylene biogas reactor

Document Type : Research Paper


Department of Biosystems Engineering, Ferdowsi University of Mashhad, Mashhad, Iran


Several factors can influence the process of biogas production. The type of reactor is one of the key factors that influence biogas production. Therefore, the aim of this study was to construct a portable horizontal polyethylene-based biogas reactor. In addition, the performance of the developed biogas reactor was tested through digestion of cow manure. The experiments were carried out in Mashhad, Iran, during June–July 2016. Biogas production was studied over a span of 58 days’ hydraulic retention time. Artificial neural network (ANN) models were used to predict the production of biogas based on temperature and pH. The Levenberg–Marquardt learning algorithm was employed to develop the best model. The obtained biogas productivity was 0.27 m3 kgVS-1, indicating that the developed biogas reactor was optimum to convert the substrate into biogas. The ANN results highlighted that the best developed model consisted of an input layer with two input variables, one hidden layer with 15 neurons, and one output layer with the correlation coefficient of 0.90. Overall, it was concluded that the ANN models can be employed to prognosticate biogas production using a portable polyethylene biogas reactor.


[1]  Ahmadi-Pirlou M., Ebrahimi-Nik M., Khojastehpour M., Ebrahimi S.H., Mesophilic co-Digestion of Municipal Solid Waste and Sewage Sludge: Effect of Mixing Ratio, Total Solids, and Alkaline Pretreatment, International Biodeterioration & Biodegradation, (2017) 125: 97-104.
[2] Anozie A.N, Layokun S.K, Okeke C.U., An Evaluation of a Batch Pilot-Scale Digester for Gas Production from Agricultural Wastes, Energy Sources (2005) 27(14):1301-1311.
[3] Bacenetti J, Sala C, Fusi A, Fiala M., Agricultural Anaerobic Digestion Plants, What LCA Studies Pointed out and What Can be Done to Make Them more Environmentally Sustainable, Applied Energy (2016) 179:669-686.
[4] Bond T., Templeton M.R., History and Future of Domestic Biogas Plants in the Developing World, Energy for Sustainable Development (2011) 5(4):347-354.
[5] Cheng S., Li Z., Mang, H.P., Huba E.M., Gao R., Wang X., Development and Application of Prefabricated Biogas Digesters in Developing Countries, Renewable and Sustainable Energy Reviews (2014) 34:387-400.
[6] Chmielewski A.G., Berbec A., Zalewski M., Dobrowolski A., Hydraulic Mixing Modeling in Reactor for Biogas Production, Chemical and Process Engineering (2012) 33(4):621-628.
[7] Comino E., Rosso M., Riggio V., Development of a Pilot Scale Anaerobic Digester for Biogas Production from Cow Manure and Whey Mix, Bioresource Technology (2009) 100(21):5072-5078.
[8] D’Agostino R.B., Tests for the Normal Distribution, Goodness-of-fit Techniques, (1986) 68: p.576,
[9] EurObserv’E.R., 15th Annual Overview Barometer ( (2015).
[10] Fayyazi S., Abbaspour-Fard M.H., Rohani A., Monadjemi S.A., Sadrnia H., Identification and Classification of Three Iranian Rice Varieties in Mixed Bulks Using Image Processing and MLP Neural Network. International Journal of Food Engineering (2017) 13(5). DOI: 10.1515/ijfe-2016-0121
[11] Ghalhari G.F., Mayvaneh F., Effect of Air Temperature and Universal Thermal Climate Index on Respiratory Diseases Mortality in Mashhad, Iran. Archives of Iranian Medicine (2016) 19(9):618 – 624.
[12] Hajihassani M., Armaghani D.J., Marto A., Mohamad E.T., Ground Vibration Prediction in Quarry Blasting through an Artificial Neural Network Optimized by Imperialist Competitive Algorithm, Bulletin of Engineering Geology and the Environment (2015) 74(3): 873-886.
[13] Holubar P., Zani L., Hager M., Froschl W., Radak Z., Braun R., Start up and Recovery of a Biogas-Reactor Using Hierarchial Neural Network-Based Control Tool, Journal of Chemical Technology and Biotechnology (2003) 78:847–54.
[14] Islam M.N., Report on Biogas Programme of China, Dacca: Bangladesh University of Engineering and Technology (1979).
[15] Jayakody K.P.K., Menikpura S.N.M., Basnayake B.F.A., Weerasekara R., Development and Evaluation of Hydrolytic/Acidogenic First Stage Anaerobic Reactor for Treating Municipal Solid Waste in Developing Countries, In Proceedings of international conference on sustainable solid waste management, Chennai, India (2007): 363-369.
[16] Kana E.G., Oloke J.K., Lateef A., Adesiyan M.O., Modeling and Optimization of Biogas Production on Saw Dust and other co-Substrates Using Artificial Neural Network and Genetic Algorithm, Renewable Energy (2012) 46:276-281.
[17] Kanat G, Saral A., Estimation of Biogas Production Rate in a Thermophilic UASB Reactor Using Artificial Neural Networks, Environmental Modeling & Assessment (2009) 14(5):607-614.
[18] Kaparaju P., Serrano M., Angelidaki I., Effect of Reactor Configuration on Biogas Production from Wheat Straw Hydrolysate, Bioresource Technology (2009) 100(24): 6317-6323.
[19] Kim E., Lee D.H., Won S., Ahn H., Evaluation of Optimum Moisture Content for Composting of Beef Manure and Bedding Material Mixtures Using Oxygen Uptake Measurement. Asian-Australasian journal of animal sciences (2016) 29(5): 753-758.
[20] Kral I., Piringer G., Saylor M.K., Gronauer A., Bauer A., Environmental Effects of Steam Explosion Pretreatment on Biogas from Maize—Case Study of a 500-kw Austrian Biogas Facility, BioEnergy Research (2015) 9(1): 198–207.
[21] Mahanty B., Zafar M., Park H.S., Characterization of co-Digestion of Industrial Sludges for Biogas Production by Artificial Neural Network and Statistical Regression Models, Environmental Technology (2013) 34(13-14):2145-2153.
[22] Moog F.A., Avilla H.F., Agpaoa E.V., Valenzuela F.G., Concepcion F.C., Promotion and Utilization of Polyethylene Biodigester in Smallhold Farming Systems in the Philippines, Livestock Research for Rural Development (1997) 9(2).
[23] Mosaedi A., Sough M.G., Sadeghi S.H., Mooshakhian Y., Bannayan M., Sensitivity Analysis of Monthly Reference Crop Evapotranspiration Trends in Iran: a Qualitative Approach, Theoretical and Applied Climatology (2016) 1-17.
[24] Mushtaq K., Zaidi A.A., Askari S.J., Design and Performance Analysis of Floating Dome Type portable Biogas Plant for Domestic use in Pakistan, Sustainable Energy Technologies and Assessments (2016)14:21-25.
[25] Negri M., Bacenetti J., Manfredini A., Lovarelli D., Maggiore T.M., Fiala M., Bocchi S., Evaluation of Methane Production from Maize Silage by Harvest of Different Plant Portions, Biomass and Bioenergy (2014) 67:339-346.
[26] Ozkaya B., Demir A., Bilgili M.S., Neural Network Prediction Model for the Methane Fraction in Biogas from Field-Scale Landfill Bioreactors, Environmental Modelling & Software (2007) 22(6):815-822.
[27] Qdais H.A., Hani K.B., Shatnawi, N., Modeling and Optimization of Biogas Production from a Waste Digester Using Artificial Neural Network and Genetic Algorithm, Resources, Conservation and Recycling (2010) 54(6):359-363.
[28] Rajendran K., Aslanzadeh S., Johansson F., Taherzadeh M.J., Experimental and Economical Evaluation of a Novel Biogas Digester, Energy Conversion and Management (2013) 74:183-191.
[29] Rajendran K., Aslanzadeh S., Taherzadeh M.J., Household Biogas Digesters—A Review, Energies (2012) 5(8):2911-2942.
[30] Rohani A., Abbaspour-Fard M.H., Abdolahpour S., Prediction of Tractor Repair and Maintenance Costs Using Artificial Neural Network, Expert Systems with Applications (2011) 38(7):8999-9007.
[31] Saeidirad M.H., Rohani A., Zarifneshat S., Predictions of Viscoelastic behavior of Pomegranate using Artificial Neural Network and Maxwell Model, Computers and Electronics in Agriculture (2013) 31:98:1-7.
[32] Sanaei-Moghadam A., Abbaspour-Fard M.H., Aghel H., Aghkhani M.H., Abedini-Torghabeh J., Enhancement of Biogas Production by co-Digestion of Potato Pulp with Cow Manure in a CSTR System. Applied Biochemistry and Biotechnology (2014) 173(7):1858-1869.
[33] Soltanali H., Nikkhah A., Rohani A. Energy Audit of Iranian Kiwifruit Production Using Intelligent Systems, Energy (2017) 139: 646-654.
[34] Standard Methods for the Examination of Water and Wastewater (APHA, AWWA and WEF), 18th edition (1992).
[35] Stoddard I., Communal Polyethylene Biogas Systems, Experiences from on-farm Research in rural West Java (2010).
[36] Surendra K.C., Takara D., Jasinski J., Kumar Khanal S., Household Anaerobic Digester for Bioenergy Production in Developing Countries, Opportunities and Challenges. Environmental Technology (2013) 34(13-14):1671-1689.
[37] Taheri-Rad A., Khojastehpour M., Rohani A., Khoramdel S., Nikkhah, A., Energy Flow Modeling and Predicting the Yield of Iranian Paddy Cultivars Using Artificial Neural Networks, Energy (2017) 135: 405–412.
[38] Taki M., Ajabshirchia Y., Ranjbar S.F., Rohani A., Matloobi M., Heat Transfer and MLP Neural Network Models to Predict inside Environment Variables and Energy Lost in a Semi-Solar Greenhouse, Energy and Buildings (2016) 110:314–329.
[39] Taylor C., Hassan M., Ali S., Integrated Portable Biogas Systems for Managing Organic Waste, In Presentation at the 4th WSEAS International Conference on Energy Planning, Energy Saving, Environmental Education (EPESE’10) and 4th WSEAS International Conference on Renewable Energy Sources (RES ‘10) (2010).
[40] USCC. TMECC, 4.11A. Test Methods for the Examination of Composting and Compost, US Composting Coincil. Ronkonkonma, NY, USA (2002).
[41] Yousuf A., Iqbal S.A., Sarker N.C., Hasan M.N., Sarker M.S.H., Optimization and Fabrication of a Portable Biogas Reactor, Journal of Chemical Engineering (2014) 27(2):36-40.
[42] Zeynali R., Khojastehpour M., Ebrahimi-Nik M., Effect of Ultrasonic Pre-Treatment on Biogas Yield and Specific Energy in Anaerobic Digestion of Fruit and Vegetable Wholesale Market Wastes, Sustainable Environment Research (2017) 27(6):259-264.