Multi-objective inexact optimization of the biomass supply chain from an energy-land-carbon nexus perspective
Z-Q. Fang, Mengmeng Wang, Ling Ji, Yulei Xie, Jiliang Zhen
Abstract
• A biomass supply chain is investigated from an energy-land-carbon nexus perspective. • A holistic framework is developed for synergetic planning of bioenergy and marginal lands. • Multi-criteria and multi-objective tradeoffs are considered for sustainable development. • Developing marginal lands is beneficial for biomass energy supply and local job creation. It is attractive and advantageous to utilize marginal land to support regional biomass energy development and improve energy security. In this study, an integrated and comprehensive decision-making framework is proposed to support the strategic planning and tactical management of regional biomass supply networks from an energy-land-carbon nexus perspective. It combines a multi-objective fuzzy chance-constraint programming model with spatial analysis of marginal land and multi-criteria assessment of biorefinery sites. The model is verified through a case study of a major agricultural region, Shandong Province in China. Local agricultural residues remain a key feedstock for bioethanol production. The results highlight the importance of considering the multi-objective tradeoffs and the intricate resource and environmental nexus for stakeholders to achieve sustainability in real practice. A cost-minimization objective drives the construction of large-scale biomass plants to enhance efficiency. An emissions-minimization goal favors smaller, decentralized plants to reduce transport distances and improve local land use. Maximizing social welfare promotes marginal land development, creating more employment opportunities. Decision-makers' management goals, risk preferences, and external fluctuations significantly influence the spatial planning of bioethanol supply chains, marginal land utilization, and operational strategies. Overall, the proposed methodology offers decision-makers an effective tool for achieving optimal decisions while accounting for complex system interdependencies, conflicting objectives, and uncertainties.