Prioritizing Local Biomass Resources for Biofuel Production by a Fuzzy Hybrid Decision Making Approach (The Case of Hormozgan Province in Iran)

Document Type : Original Research Paper

Authors

1 Graduate Faculty of Environment, University of Tehran, Tehran, Iran

2 Department of Industrial Engineering, Karaj Branch, Islamic Azad University, Karaj, Iran

Abstract

In recent years, increasing in energy demand and the importance of using energy with minimum green- house gas emission (GHG) leads researchers to study about renewable energy resources such as biomasses. Biomasses can be converted to biofuels by applying the appropriate technologies. In this study, a hybrid group fuzzy multi-criteria decision making (MCDM) approach based on step-wise weight assessment ratio analysis (SWARA), technique for order preference by similarity to ideal Solution (TOPSIS), additive ratio assessment (ARAS), weighted aggregated sum product assessment (WASPAS) and simple additive weighting (SAW) in the fuzzy environment is applied to rank biomasses in the case of Hormozgan province in Iran, because of being a coastal area and the access to different types of first, second and third generation resources of biofuel. After ranking these resources by mentioned methods, two aggregated multi-criteria decision making (MCDM) methods (mean rank method and Copeland method) are employed to prioritize these biomasses.  Results of mean rank show that municipal solid wastes (MSW), fish wastes and microalgae have the minimum average rank, respectively and the results of Copeland method show that MSW, fish wastes and microalgae have the maximum (wins-loses), respectively. So, these biomasses are the most suitable ones in biofuel production in this province.

Keywords

Main Subjects


Abadi, F., Sahebi, I., Arab, A., Alavi, A., & Karachi, H. (2018). Application of best-worst method in evaluation of medical tourism development strategy. Decis. Sci. Lett., 7(1), 77-86.
Alam, F., Date, A., Rasjidin, R., Mobin, S., Moria, H., & Baqui, A. (2012). Biofuel from algae-Is it a viable alternative?. Procedia Eng., 49, 221-227.‏ 
Askarifar, K., Motaffef, Z., & Aazaami, S. (2018). An investment development framework in Iran’s seashores using TOPSIS and best-worst multi-criteria decision-making methods. Decis. Sci. Lett., 7(1), 55-64.
Awasthi, S. K., Kumar, M., Sarsaiya, S., Ahluwalia, V., Chen, H., Kaur, G., ... & Awasthi, M. K. (2022). Multi-criteria research lines on livestock manure biorefinery development towards a circular economy: From the perspective of a life cycle assessment and business models strategies. J. Clean. Prod., 341, 130862.‏
Azadeh, A., Rahimi-Golkhandan, A., & Moghaddam, M. (2014). Location optimization of wind power generation–transmission systems under uncertainty using hierarchical fuzzy DEA: a case study. Renew. Sust. Energ., 30, 877-885.
Azarnivand, A., Hashemi-Madani, F.S., & Banihabib, M.E. (2015). Extended fuzzy analytic hierarchy process approach in water and environmental management (case study: Lake Urmia Basin, Iran). Environ. Earth Sci., 73(1), 13-26.
Azizi, A., Malekmohammadi, B., Jafari, H.R., Nasiri, H., & Parsa, V.A. (2014). Land suitability assessment for wind power plant site selection using ANP-DEMATEL in a GIS environment: case study of Ardabil province, Iran. Environ. Monit. Assess., 186(10), 6695-6709.
Babazadeh, R., Razmi, J., & Pishvaee, M.S. (2016). Sustainable cultivation location optimization of the Jatropha curcas L. under uncertainty: A unified fuzzy data envelopment analysis approach. Measurement 89, 252-260.
Banihabib, M.E., Hashemi, F., Shabestari, M.H. (2017). A framework for sustainable strategic planning of water demand and supply in arid regions. Sustain. Dev., 25 (3), 254–266.
Cuellar-Bermudez, S. P., Garcia-Perez, J. S., Rittmann, B. E., & Parra-Saldivar, R. (2015). Photosynthetic bioenergy utilizing CO2: an approach on flue gases utilization for third generation biofuels. J. Clean. Prod., 98, 53-65.‏
Davoudpour, H., Rezaee, S., & Ashrafi, M. (2012). Developing a framework for renewable technology portfolio selection: A case study at a R&D center. Renew. Sust. Energ., 16(6), 4291-4297.‏
Er Kara, M., & Oktay Fırat, S.Ü. (2018). Supplier risk assessment based on best-worst method and K-means clustering: a case study. Sustainability,10(4), 1066.
Eskandari, M., Homaee, M., & Mahmodi, S. (2012). An integrated multi criteria approach for landfill siting in a conflicting environmental, economical and socio-cultural area. Waste Manage., 32(8), 1528-1538.‏
Fadavi-Ghaffari, M., Azad, A., Shariatzadeh, H., Taghizadeh, G., & Aminizadeh, S. (2017). Translation, cultural adaptation, face and content validity of the Persian version “patient-rated wrist evaluation” (prwe-persian) questionnaire. J. Mod. Rehabil., 51-62.
Firouzi, S., Allahyari, M.S., Isazadeh, M., Nikkhah, A., & Van Haute, S. (2021). Hybrid multi-criteria decision-making approach to select appropriate biomass resources for biofuel production. Sci. Total Environ., 770, 144449.
Ghafari, S., Kaviani, B., Sedaghathoor, S.H., Allahyari, M.S. (2020). Ecological potentials of trees, shrubs and hedge species for urban green spaces by multi criteria decision making. Urban For Urban Green, 55, 126824.
Gholami, Z., Mortazavi, M. S., & Karbassi, A. (2019). Environmental risk assessment of harmful algal blooms case study: Persian Gulf and Oman Sea located at Hormozgan Province, Iran., Hum. ecol. risk assess., 25(1-2), 271-296.‏
Ghorbani, A., Rahimpour, M. R., Ghasemi, Y., & Raeissi, S. (2018). The biodiesel of microalgae as a solution for diesel demand in Iran. Energies, 11(4), 950.‏
Greggio, N., Carlini, C., Contin, A., Soldano, M., & Marazza, D. (2018). Exploitable fish waste and stranded beach debris in the Emilia-Romagna Region (Italy). Waste Manage., 78, 566-575.‏
Kannan, S., Gariepy, Y., & Raghavan, G. V. (2017). Optimization and characterization of hydrochar produced from microwave hydrothermal carbonization of fish waste. Waste Manage., 65, 159-168.‏
Kazaz, A., Er, B., Ulubeyli, S., & Ozdemir, B.E. (2015). Classification of construction firms in Turkey by using miles and snows’ typology. Eng. Econ., 26(2), 204-210.
Kheybari, S., Rezaie, F.M., Naji, S.A., & Najafi, F. (2019). Evaluation of energy production technologies from biomass using analytical hierarchy process: The case of Iran. J. Clean. Prod., 232, 257-265.
Khishtandar, S., Zandieh, M., & Dorri, B. (2017). A multi criteria decision making framework for sustainability assessment of bioenergy production technologies with hesitant fuzzy linguistic term sets: The case of Iran. Renew. Sust. Energ. ,77, 1130-1145.
Lawshe, C.H. (1975). A quantitative approach to content validity. Pers. Psychol., 28(4), 563-575.
Malekmohammadi, B., & Blouchi, L.R.(2014). Ecological risk assessment of wetland ecosystems using multi criteria decision making and geographic information system. Ecol. Indic. 41, 133-144.
Mardani, A., Nilashi, M., Zakuan, N., Loganathan, N., Soheilirad, S., Saman, M. Z. M., & Ibrahim, O. (2017). A systematic review and meta-Analysis of SWARA and WASPAS methods: Theory and applications with recent fuzzy developments. Appl. Soft Comput., 57, 265-292.‏
Mo, W. Y., Man, Y. B., & Wong, M. H. (2018). Use of food waste, fish waste and food processing waste for China’s aquaculture industry: Needs and challenge. 
Sci. Total Environ., 613, 635-643.‏
Mohammadpour, A., Gharehchahi, E., Badeenezhad, A., Parseh, I., Khaksefidi, R., Golaki, M., ... & Giannakis, S. (2022). Nitrate in groundwater resources of Hormozgan province, southern Iran: concentration estimation, distribution and probabilistic health risk assessment using Monte Carlo simulation. Water, 14(4), 564.‏
Mohseni, S., & Pishvaee, M. S. (2016). A robust programming approach towards design and optimization of microalgae-based biofuel supply chain. Comput. Ind. Eng., 100, 58-71.‏
Mostafaeipour, A., Alvandimanesh, M., Najafi, F., & Issakhov, A. (2021). Identifying challenges and barriers for development of solar energy by using fuzzy best-worst method: A case study. Energy, 226, 120355.
Naeini, M. A., Zandieh, M., Najafi, S. E., & Sajadi, S. M. (2020). Analyzing the development of the third-generation biodiesel production from microalgae by a novel hybrid decision-making method: The case of Iran. Energy, 195, 116895.‏
Nagai, T., & Suzuki, N. (2000). Isolation of collagen from fish waste material—skin, bone and fins. Food Chem., 68(3), 277-281.‏
Nosratinia, M., Tofigh, A. A., & Adl, M. (2015). Making Decision Support System for Utilization of Biogas in Iran. J. Renew. Energy Environ., 2(1), 1-5.‏
Rabbani, M., Saravi, N.A., Farrokhi-Asl, H., Lim, S.F.W., & Tahaei, Z. (2018). Developing a sustainable supply chain optimization model for switchgrass-based bioenergy production: a case study. J. Clean. Prod., 200, 827-843.
Ravanipour, M., Bagherzadeh, R., & Mahvi, A. H. (2021). Fish and shrimp waste management at household and market in Bushehr, Iran. J. Mater. Cycles Waste Manag., 23, 1394-1403.‏
Ravanipour, M., Hamidi, A., & Mahvi, A. H. (2021). Microalgae biodiesel: A systematic review in Iran. Renew. Sustain. Energy Rev., 150, 111426.‏
Rezaeiniya, N., Zolfani, S.H., & Zavadskas, E.K. (2012). Greenhouse locating based on ANP-COPRAS-G methods–an empirical study based on Iran. Int. J. Strateg. Prop. Manag., 16(2), 188-200
Sakthivel, G., Ilangkumaran, M. (2015). A hybrid multi-criteria decision making approach of ANP and TOPSIS to evaluate the optimum fuel blend in IC engine. Int. J. Decis. Support Syst., 1 (3), 268–293.
Sankaran, R., Show, P. L., & Chang, J. S. (2016). Biodiesel production using immobilized lipase: feasibility and challenges. Biofuels Bioprod. Biorefining, 10(6), 896-916.‏
Saranya, R., Tamil Selvi, A., Jayapriya, J., & Aravindhan, R. (2020). Synthesis of fat liquor through fish waste valorization, characterization and applications in tannery industry. Waste Biomass Valorization, 11, 6637-6647.‏
Saratale, G. D., Saratale, R. G., Banu, J. R., & Chang, J. S. (2019). Biohydrogen production from renewable biomass resources. In Biohydrogen (pp. 247-277). Elsevier.‏
Shahnazari, A., Rafiee, M., Rohani, A., Nagar, B.B., Ebrahiminik, M.A., & Aghkhani, M.H. (2020). Identification of effective factors to select energy recovery technologies from municipal solid waste using multi-criteria decision making (MCDM): A review of thermochemical technologies. Sustain. Energy Technol. Assess., 40, 100737.
Shokatpour, M.H., Nazari, M.A., & Assad, M.E.H. (2022). Renewable Energy Technology Selection for Iran by Using Multi Criteria Decision Making. (Paper presented in the Advances in Science and Engineering Technology International Conferences (ASET). IEEE).
Sindhu, S., Nehra, V., & Luthra, S. (2017). Solar energy deployment for sustainable future of India: Hybrid SWOC-AHP analysis. Renew. Sust. Energ., 72, 1138-1151.‏
Soleymani, M., Asakereh, A., & Safieddin Ardebili, S.M. (2022). A GIS-based multi-criteria fuzzy approach to select a suitable location for a MSW-based power plant and landfill: a case study, Khuzestan province, Iran. Environ. Monit. Assess., 194(3), 1-20.
Tabatabaei, M., Tohidfar, M., Jouzani, G. S., Safarnejad, M., & Pazouki, M. (2011). Biodiesel production from genetically engineered microalgae: future of bioenergy in Iran. Renew. Sust. Energ., 15(4), 1918-1927.‏
Talaiekhozani, A., Bahrami, S., Hashemi, S. M. J., & Jorfi, S. (2016). Evaluation and analysis of gaseous emission in landfill area and estimation of its pollutants dispersion,(case of Rodan in Hormozgan, Iran). Environ. Health Eng. Manag., 3(3), 143-150.‏
Vafaeipour, M., Zolfani, S.H., Varzandeh, M.H.M., Derakhti, A., & Eshkalag, M.K. ( 2014). Assessment of regions priority for implementation of solar projects in Iran: New application of a hybrid multi-criteria decision making approach. Energy Convers. Manag., 86, 653-663.
Yano, Y., Oikawa, H., & Satomi, M. (2008). Reduction of lipids in fish meal prepared from fish waste by a yeast Yarrowia lipolytica. Int. J. Food Microbiol., 121(3), 302-307.‏
Yazdani-Chamzini, A., Fouladgar, M.M., Zavadskas, E.K., & Moini, S.H.H. (2013). Selecting the optimal renewable energy using multi criteria decision making. J. Bus. Econ. Manag., 14(5), 957-978.
Zolfani, S. H., & Saparauskas, J. (2013). New application of SWARA method in prioritizing sustainability assessment indicators of energy system. Eng. Econ., 24(5), 408-414.‏