Assessing and prioritizing challenges facing bioenergy supply chain in Norway: A Delphi-AHP method

Assessing and prioritizing challenges facing bioenergy supply chain in Norway: A Delphi-AHP method

Zahir Barahmand Marianne S. Eikeland

Department of Process, Energy and Environmental Technology, University of South-Eastern Norway

Page: 
310 - 330
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DOI: 
https://doi.org/10.2495/EQ-V7-N4-310-330
Received: 
N/A
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Accepted: 
N/A
| | Citation

© 2022 IIETA. This article is published by IIETA and is licensed under the CC BY 4.0 license (http://creativecommons.org/licenses/by/4.0/).

OPEN ACCESS

Abstract: 

Norway is leading the share of renewable energy in Europe by almost 75%. However, the share of bioenergy in Norway’s energy supply is insignificant. Bioenergy, the most common type of renewable energy, generates more energy than all other forms. This fact demonstrates the value of bioenergy, which will play an increasingly important part in the future energy mix. There are different biomass resources such as agricultural crop residues, forestry, wood processing residues, algae, dedicated energy crops, and municipal and wet organic waste. Biofuel markets in Norway are relatively immature. In past decades, bioenergy consumption in Norway ranged between 4% and 6% of the total primary energy supply. Norway has experienced a gradual increase in total energy supply of biofuels and wastes, and it has almost doubled since 1990, which is 80 petajoule in 2020. However, various barriers are hindering the development of the biomass industry. The present study aims to identify and classify Norway’s biomass supply chain challenges and prioritize them using the Delphi-Analytic Hierarchy Process (AHP) method. Based on a comprehensive literature review, 42 challenges were recognized and classified into seven major categories. Then, a Delphi technique is used to define and choose the main challenges in the context of Norway through an expert panel. Finally, 4 main categories, 9 sub-categories, and 37 challenge indicators related to Norway’s biomass industry were selected. Moreover, the AHP method is employed to determine the weight of the challenges using a geometric mean approach. The results show that ‘high investment cost’, ‘Greenhouse Gas (GHG) emission’, ‘minor differences between the energy prices achievable for the sales of heat and electricity’, and ‘small market size’ were the most critical challenge indicators.

Keywords: 

AHP, barriers, biomass, bioenergy supply chain, Delphi

  References

[1] Ma, L., Yu, J. & Zhang, L., An analysis on barriers to biomass and bioenergy development in rural China using intuitionistic fuzzy cognitive map. Energies, 12(9), Art. no. 9, 2019. https://doi.org/10.3390/en12091598

[2] Mukeshimana, M. C., Zhao, Z.-Y., Ahmad, M. & Irfan, M., Analysis on barriers to biogas dissemination in Rwanda: AHP approach. Renewable Energy, 163, pp. 1127–1137, 2021. https://doi.org/10.1016/j.renene.2020.09.051

[3] Rosillo-Calle, F. & Hall, D. O., Biomass energy, forests and global warming. Energy Policy, 20(2), pp. 124–136, 1992. https://doi.org/10.1016/0301-4215(92)90106-C

[4] Sansaniwal, S. K., Pal, K., Rosen, M. A. & Tyagi, S. K., Recent advances in the development of biomass gasification technology: A comprehensive review. Renewable and Sustainable Energy Reviews, 72, pp. 363–384, 2017. https://doi.org/10.1016/j.rser.2017.01.038

[5] Campbell, R. M., Anderson, N. M., Daugaard, D. E. & Naughton, H. T., Technoeco-nomic and policy drivers of project performance for bioenergy alternatives using bio-mass from beetle-killed trees. Energies, 11(2), Art. no. 2, 2018. https://doi.org/10.3390/en11020293

[6] Directive (EU) 2018/2001, vol. 328. 2018. http://data.europa.eu/eli/dir/2018/2001/oj/eng, Accessed on: 04 March 2022.

[7] Scarlat, N., Dallemand, J.-F., Skjelhaugen, O. J., Asplund, D. & Nesheim, L., An overview of the biomass resource potential of Norway for bioenergy use. Renewable and Sustainable Energy Reviews, 15(7), pp. 3388–3398, 2011. https://doi.org/10.1016/j.rser.2011.04.028

[8] Ranta, T., Laihanen, M. & Karhunen, A., Development of the bioenergy as a part of renewable energy in the Nordic Countries: A comparative analysis. Journal of Sustainable Bioenergy Systems, 10(3), Art. no. 3, 2020. https://doi.org/10.4236/jsbs.2020.103008

[9] Nakada, S., Saygin, D. & Gielen, D., Global bioenergy supply and demand projections: A working paper for REmap 2030, IRENA, 2014. https://www.irena.org/publications/2014/Sep/Global-Bioenergy-Supply-and-Demand-Projections-A-working-paper-for-REmap-2030. Accessed on: 04 March 2022.

[10] Biller, P., Hydrothermal liquefaction of aquatic feedstocks. Direct Thermochemical Liquefaction for Energy Applications, Ed. L. Rosendahl, Woodhead Publishing, pp. 101–125, 2018. https://doi.org/10.1016/B978-0-08-101029-7.00003-5

[11] Bioenergy Europe factsheet, Biomass for energy - Agricultural residues & energy crops, Bionergy Europe, 2019.

[12] Zahraee, S. M., Shiwakoti, N. & Stasinopoulos, P., Biomass supply chain environmental and socio-economic analysis: 40-Years comprehensive review of methods, decision issues, sustainability challenges, and the way forward. Biomass and Bioenergy, 142, p. 105777, 2020. https://doi.org/10.1016/j.biombioe.2020.105777

[13] Forestry, Government.no, 2014. https://www.regjeringen.no/en/topics/food-fisheriesand-agriculture/skogbruk/innsikt/skogbruk/id2009516/. Accessed on: 04 March 2022.

[14] Galera Lindblom, P. & Rasmussen, R. O., Bioenergy and Regional Development in the Nordic Countries. Nordregio, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:norden:org:diva-170. Accessed on: 04 March 2022.

[15] Granlund, L. L., Eltun, R., Hohle, E. E., Nesheim, L., Waalen, W. & Åssveen, M., Biodiesel fra norske jordbruksvekster (Biodiesel from Norwegian agricultural crops). Bioforsk, 2010. https://nibio.brage.unit.no/nibio-xmlui/handle/11250/2460467. Accessed 

on: 04 March 2022.

[16] Knudsen, J. & Haug, J., Increasing the sustainable use of biomass in Norway. Assessment of the policy framework for more industrial use of seaweed, SINTEF Energy Research, TR A7472, 2015.

[17] Yadav, Y. S. & Yadav, Y. K., Biomass supply chain management: Perspectives and challenges. Proceedings of the First International Conference on Recent Advances in Bioenergy Research, New Delhi, pp. 267–281, 2016. https://doi.org/10.1007/978-81-322-2773-1_20

[18] Beamon, B. M., Supply chain design and analysis: Models and methods. International Journal of Production Economics, 55(3), pp. 281–294, 1998. https://doi.org/10.1016/S0925-5273(98)00079-6

[19] Simchi-Levi, D., Kaminsky, P. & Simchi-Levi, E., Designing and Managing the Supply Chain: Concepts, Strategies, and Cases w/CD-ROM Package, Book plus CD-Rom edi-tion. Boston: McGraw-Hill/Irwin, 1999.

[20] Fiedler, P., Lange, M. & Schultze, M., Supply logistics for the industrialized use of bio-mass - principles and planning approach. 2007 International Symposium on Logistics and Industrial Informatics, pp. 41–46, 2007. https://doi.org/10.1109/LINDI.2007.4343510

[21] IEA Bioenergy, Bioenergy policies and status of implementation - Morway (2018 update), IEA Bioenergy, 2018.

[22] Norway - Countries & Regions, IEA. https://www.iea.org/countries/norway. Accessed on: 05 March 2022.

[23] Forbord, M., Vik, J. & Hillring, B. G., Development of local and regional forest based bioenergy in Norway – supply networks, financial support and political commitment. Biomass and Bioenergy, 47, pp. 164–176, 2012. https://doi.org/10.1016/j.biombioe.2012.09.045

[24] Irfan, M., Elavarasan, R. M., Ahmad, M., Mohsin, M., Dagar, V. & Hao, Y., Priori-tizing and overcoming biomass energy barriers: Application of AHP and G-TOPSISapproaches. Technological Forecasting and Social Change, 177, p. 121524, 2022. https://doi.org/10.1016/j.techfore.2022.121524

[25] Tseng, M.-L., Ardaniah, V., Sujanto, R. Y., Fujii, M. & Lim, M. K., Multicriteria assess-ment of renewable energy sources under uncertainty: Barriers to adoption. Technological Forecasting and Social Change, 171, p. 120937, 2021. https://doi.org/10.1016/j.techfore.2021.120937

[26] Ghimire, L. P. & Kim, Y., An analysis on barriers to renewable energy development in the context of Nepal using AHP. Renewable Energy, 129, pp. 446–456, 2018.

[27] Solangi, Y. A., Longsheng, C. & Shah, S. A. A., Assessing and overcoming the renewable energy barriers for sustainable development in Pakistan: An integrated AHP and fuzzy TOPSIS approach. Renewable Energy, 173, pp. 209–222, 2021.

[28] Numata, M., Sugiyama, M. & Mogi, G., Barrier analysis for the deployment of renewable-based mini-grids in Myanmar using the Analytic Hierarchy Process (AHP). Energies, 13(6), Art. no. 6, 2020. https://doi.org/10.3390/en13061400

[29] Rupf, G. V., Bahri, P. A., de Boer, K. & McHenry, M. P., Barriers and opportunities of biogas dissemination in Sub-Saharan Africa and lessons learned from Rwanda, Tan-zania, China, India, and Nepal. Renewable and Sustainable Energy Reviews, 52, pp. 468–476, 2015.

[30] Cavicchi, B., The burden of sustainability: Limits to sustainable bioenergy development in Norway. Energy Policy, 119, pp. 585–599, 2018. https://doi.org/10.1016/j.enpol.2018.05.015

[31] Yu, H., Román, E. & Solvang, W. D., A Value Chain Analysis for Bioenergy Production from Biomass and Biodegradable Waste: A Case Study in Northern Norway, IntechO-pen, 2017. https://doi.org/10.5772/intechopen.72346

[32] Hummel, J. M., Bridges, J. F. P. & IJzerman, M. J., Group decision making with the analytic hierarchy process in benefit-risk assessment: A tutorial. Patient, 7(2), pp. 129–140, 2014. https://doi.org/10.1007/s40271-014-0050-7

[33] Steurer, J., The Delphi method: an efficient procedure to generate knowledge. Skeletal Radiology, 40(8), pp. 959–961, 2011. https://doi.org/10.1007/s00256-011-1145-z

[34] Saaty, T. L., How to make a decision: The analytic hierarchy process. European Journal of Operational Research, 48(1), pp. 9–26, 1990. https://doi.org/10.1016/0377-2217(90)90057-I

[35] Franek, J. & Kresta, A., Judgment scales and consistency measure in AHP. Proce-dia Economics and Finance, 12, pp. 164–173, 2014. https://doi.org/10.1016/S2212-5671(14)00332-3

[36] Krejčí, J. & Stoklasa, J., Aggregation in the analytic hierarchy process: Why weighted geometric mean should be used instead of weighted arithmetic mean. Expert Systems with Applications, 114, pp. 97–106, 2018. https://doi.org/10.1016/j.eswa.2018.06.060

[37] Sultana, A., Kumar, A. & Harfield, D., Development of agri-pellet production cost and optimum size. Bioresource Technology, 101(14), pp. 5609–5621, 2010. https://doi.org/10.1016/j.biortech.2010.02.011

[38] Caputo, A. C., Palumbo, M., Pelagagge, P. M. & Scacchia, F., Economics of biomass energy utilization in combustion and gasification plants: effects of logistic variables. Biomass and Bioenergy, 28(1), pp. 35–51, 2005. https://doi.org/10.1016/j.biom-bioe.2004.04.009

[39] Balan, V., Current challenges in commercially producing biofuels from lignocellu-losic biomass, ISRN Biotechnology, 2014, p. 463074, 2014. https://doi.org/10.1155/2014/463074

[40] McKendry, P., Energy production from biomass (part 1): overview of biomass. Bio-resource Technology, 83(1), pp. 37–46, 2002. https://doi.org/10.1016/S0960-8524(01)00118-3

[41] Barahmand, Z. & Eikeland, M. S., A scoping review on environmental, economic, and social impacts of the gasification processes. Environments, 9(7), Art. no. 7, 2022. https://doi.org/10.3390/environments9070092

[42] Norway tightens its biofuel policy stifling the use of palm oil. https://www.regnskog.no/en/news/norway-tightens-its-biofuel-policy-stifling-the-use-of-palm-oil. Accessed on: 20 August 2022.

[43] Toth, W. & Vacik, H., A comprehensive uncertainty analysis of the analytic hierarchy process methodology applied in the context of environmental decision making. Journal of Multi-Criteria Decision Analysis, 25(5–6), pp. 142–161, 2018. https://doi.org/10.1002/mcda.1648

[44] Eskandari, H. & Rabelo, L., Handling uncertainty in the analytic hierarchy process: a stochastic approach. International Journal of Information Technology & Decision Making, 06(1), pp. 177–189, 2007. https://doi.org/10.1142/S0219622007002356

[45] Saaty, T. L. & Vargas, L. G., Uncertainty and rank order in the analytic hierarchy pro-cess. European Journal of Operational Research, 32(1), pp. 107–117, 1987. https://doi.org/10.1016/0377-2217(87)90275-X

[46] Yaraghi, N., Tabesh, P., Guan, P. & Zhuang, J., Comparison of AHP and Monte Carlo AHP under different levels of uncertainty. IEEE Transactions on Engineering Manage-ment, 62(1), pp. 122–132, 2015. https://doi.org/10.1109/TEM.2014.2360082

[47] Hsu, T.-H. & Pan, F. F. C., Application of Monte Carlo AHP in ranking dental quality attributes. Expert Systems with Applications, 36(2), Part 1, pp. 2310–2316, 2009. https://doi.org/10.1016/j.eswa.2007.12.023

[48] Carmone, F. J., Kara, A. & Zanakis, S. H., A Monte Carlo investigation of incomplete pair-wise comparison matrices in AHP. European Journal of Operational Research, 102(3), pp. 538–553, 1997. https://doi.org/10.1016/S0377-2217(96)00250-0

[49] Zhu, J., Wang, E. & Sun, W., Application of Monte Carlo AHP in ranking coastal tour-ism environmental carrying capacity factors. Asia Pacific Journal of Tourism Research, 24(7), pp. 644–657, 2019. https://doi.org/10.1080/10941665.2019.1611610

[50] Serrano-Gomez, L. & Munoz-Hernandez, J. I., Monte Carlo approach to fuzzy AHP risk analysis in renewable energy construction projects. PLoS One, 14(6), e0215943, 2019. https://doi.org/10.1371/journal.pone.0215943

[51] Ataei, M., Shahsavany, H. & Mikaeil, R., Monte Carlo Analytic Hierarchy Process (MAHP) approach to selection of optimum mining method. International Journal of Mining Science and Technology, 23(4), pp. 573–578, 2013. https://doi.org/10.1016/j.ijmst.2013.07.017

[52] Liu, Y., Eckert, C. M. & Earl, C., A review of fuzzy AHP methods for decision-making with subjective judgements. Expert Systems with Applications, 161, p. 113738, 2020. https://doi.org/10.1016/j.eswa.2020.113738

[53] Wang, Y.-M., Luo, Y. & Hua, Z., On the extent analysis method for fuzzy AHP and its applications. European Journal of Operational Research, 186(2), pp. 735–747, 2008. https://doi.org/10.1016/j.ejor.2007.01.050

[54] Kahraman, C., Cebeci, U. & Ulukan, Z., Multi-criteria supplier selection using fuzzy AHP. Logistics Information Management, 16(6), pp. 382–394, 2003. https://doi.org/10.1108/09576050310503367

[55] Pan, N.-F., Fuzzy AHP approach for selecting the suitable bridge construction method. Automation in Construction, 17(8), pp. 958–965, 2008. https://doi.org/10.1016/j.autcon.2008.03.005

[56] Zhu, K.-J., Jing, Y. & Chang, D.-Y., A discussion on extent analysis method and applications of fuzzy AHP. European Journal of Operational Research, 116(2), pp. 450–456, 1999. https://doi.org/10.1016/S0377-2217(98)00331-2

[57] Chen, J.-F., Hsieh, H.-N. & Do, Q. H., Evaluating teaching performance based on fuzzy AHP and comprehensive evaluation approach. Applied Soft Computing, 28, pp. 100–108, 2015. https://doi.org/10.1016/j.asoc.2014.11.050