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Multi-level system modelling of the resource-food-bioenergy nexus in the global south

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  • Guo, Miao
  • van Dam, Koen H.
  • Touhami, Noura Ouazzani
  • Nguyen, Remy
  • Delval, Florent
  • Jamieson, Craig
  • Shah, Nilay

Abstract

To meet the demands for resources, food and energy, especially in fast developing countries in the Global South, new infrastructure investments, technologies and supply chains are required. It is essential to manage a transition that minimises the impacts on global environmental degradation while benefits local socio-economic development. Food-bioenergy integration optimising natural capital resources and considering wider environmental and socio-economic sustainability offers a way forward. This study presents an integrative approach enabling whole systems modelling to address the interlinkage and interaction of resource-food-bioenergy systems and optimise supply chains considering poly-centric decision spaces. Life cycle sustainability assessment, optimisation, agent-based modelling and simulation were coupled to build an integrated systems modelling framework applicable to the resource-food-bioenergy nexus. The model building blocks are described before their applications in three case studies addressing agricultural residues and macro-fungi in the Philippines, sugar cane biorefineries in South Africa, and Nipa palm biofuel in Thailand. Our case studies revealed the great potential of untapped biomass including agricultural waste and non-food biomass grown on marginal lands. Two value chain integration case studies – i.e. straw-fungi-energy in Philippines and sugar-energy in Africa – have been suggested as sustainable solutions to recover waste as value-added products to meet food and energy security. Case studies highlight how an integrative modelling framework can be applied to address multi-level questions, taking into account decision-making at different levels, which contribute to an overall sustainability goal.

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  • Guo, Miao & van Dam, Koen H. & Touhami, Noura Ouazzani & Nguyen, Remy & Delval, Florent & Jamieson, Craig & Shah, Nilay, 2020. "Multi-level system modelling of the resource-food-bioenergy nexus in the global south," Energy, Elsevier, vol. 197(C).
    • Handle: RePEc:eee:energy:v:197:y:2020:i:c:s0360544220303030
    DOI: 10.1016/j.energy.2020.117196
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    as
    1. Lingling Wang & Tsunemi Watanabe, 2016. "A Stackelberg Game Theoretic Analysis of Incentive Effects under Perceived Risk for China’s Straw-Based Power Plant Supply Chain," Energies, MDPI, vol. 9(6), pages 1-20, June.
    2. Shu, Kesheng & Schneider, Uwe A. & Scheffran, Jürgen, 2017. "Optimizing the bioenergy industry infrastructure: Transportation networks and bioenergy plant locations," Applied Energy, Elsevier, vol. 192(C), pages 247-261.
    3. Moncada, J.A. & Junginger, M. & Lukszo, Z. & Faaij, A. & Weijnen, M., 2017. "Exploring path dependence, policy interactions, and actor behavior in the German biodiesel supply chain," Applied Energy, Elsevier, vol. 195(C), pages 370-381.
    4. Yazan, Devrim Murat & Fraccascia, Luca & Mes, Martijn & Zijm, Henk, 2018. "Cooperation in manure-based biogas production networks: An agent-based modeling approach," Applied Energy, Elsevier, vol. 212(C), pages 820-833.
    5. Stummer, Christian & Kiesling, Elmar & Günther, Markus & Vetschera, Rudolf, 2015. "Innovation diffusion of repeat purchase products in a competitive market: An agent-based simulation approach," European Journal of Operational Research, Elsevier, vol. 245(1), pages 157-167.
    6. Aghbashlo, Mortaza & Mandegari, Mohsen & Tabatabaei, Meisam & Farzad, Somayeh & Mojarab Soufiyan, Mohamad & Görgens, Johann F., 2018. "Exergy analysis of a lignocellulosic-based biorefinery annexed to a sugarcane mill for simultaneous lactic acid and electricity production," Energy, Elsevier, vol. 149(C), pages 623-638.
    7. Cobuloglu, Halil I. & Büyüktahtakın, İ. Esra, 2015. "Food vs. biofuel: An optimization approach to the spatio-temporal analysis of land-use competition and environmental impacts," Applied Energy, Elsevier, vol. 140(C), pages 418-434.
    8. Utomo, Dhanan Sarwo & Onggo, Bhakti Stephan & Eldridge, Stephen, 2018. "Applications of agent-based modelling and simulation in the agri-food supply chains," European Journal of Operational Research, Elsevier, vol. 269(3), pages 794-805.
    9. Huang, Shiyang & Hu, Guiping & Chennault, Carrie & Su, Liu & Brandes, Elke & Heaton, Emily & Schulte, Lisa & Wang, Lizhi & Tyndall, John, 2016. "Agent-based modeling of bioenergy crop adoption and farmer decision-making," Energy, Elsevier, vol. 115(P1), pages 1188-1201.
    10. Trivedi, Abhinav & Verma, Amit Ranjan & Kaur, Supreet & Jha, Bhaskar & Vijay, Vandit & Chandra, Ram & Vijay, Virendra Kumar & Subbarao, P.M.V. & Tiwari, Ratnesh & Hariprasad, P. & Prasad, Rajendra, 2017. "Sustainable bio-energy production models for eradicating open field burning of paddy straw in Punjab, India," Energy, Elsevier, vol. 127(C), pages 310-317.
    11. Bhattacharyya, Subhes C., 2006. "Energy access problem of the poor in India: Is rural electrification a remedy?," Energy Policy, Elsevier, vol. 34(18), pages 3387-3397, December.
    12. Guillem, E.E. & Murray-Rust, D. & Robinson, D.T. & Barnes, A. & Rounsevell, M.D.A., 2015. "Modelling farmer decision-making to anticipate tradeoffs between provisioning ecosystem services and biodiversity," Agricultural Systems, Elsevier, vol. 137(C), pages 12-23.
    13. Kesheng Shu & Uwe A. Schneider & Jürgen Scheffran, 2015. "Bioenergy and Food Supply: A Spatial-Agent Dynamic Model of Agricultural Land Use for Jiangsu Province in China," Energies, MDPI, vol. 8(11), pages 1-24, November.
    14. Pradhan, Anup & Mbohwa, Charles, 2014. "Development of biofuels in South Africa: Challenges and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 1089-1100.
    15. Bridge, Gavin & Bouzarovski, Stefan & Bradshaw, Michael & Eyre, Nick, 2013. "Geographies of energy transition: Space, place and the low-carbon economy," Energy Policy, Elsevier, vol. 53(C), pages 331-340.
    16. Shafie, S.M. & Masjuki, H.H. & Mahlia, T.M.I., 2014. "Life cycle assessment of rice straw-based power generation in Malaysia," Energy, Elsevier, vol. 70(C), pages 401-410.
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    7. Marco Pastori & Angel Udias & Luigi Cattaneo & Magda Moner-Girona & Awa Niang & Cesar Carmona-Moreno, 2021. "Bioenergy Potential of Crop Residues in the Senegal River Basin: A Cropland–Energy–Water-Environment Nexus Approach," Sustainability, MDPI, vol. 13(19), pages 1-23, October.
    8. You, Chanhee & Han, Seulki & Kim, Jiyong, 2021. "Integrative design of the optimal biorefinery and bioethanol supply chain under the water-energy-food-land (WEFL) nexus framework," Energy, Elsevier, vol. 228(C).
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