The decision‐making landscape to maximize the use of sustainable biomass resources, and achieve long‐term environmental and socioeconomic benefits, is complex with a high level of uncertainty in biomass supply and… Click to show full abstract
The decision‐making landscape to maximize the use of sustainable biomass resources, and achieve long‐term environmental and socioeconomic benefits, is complex with a high level of uncertainty in biomass supply and logistics, technical and economic performance of the biorefinery routes, lifecycle performance of the finished products, and other sustainability criteria. Numerous decision‐making support models have been developed but these models usually assess only a few specific aspects of technology, regulations, economic, environment, and society. Decision‐making support models with a limited capability to capture environmental and socioeconomic performance of the biorefining pathways are not able to identify the best available biorefining routes. This study reviews and discusses recent progress on the harmonization, standardization, and integration of the existing decision‐making support models that aim to improve the comparability of the results of these models when different pathways are being assessed and align the decisions made at the strategic, tactical and operational levels. With the growing number of climate‐change policies and greenhouse gas (GHG) emission reduction targets, national and international efforts to harmonize the input databases, the model assumptions and system boundaries, and the integration of the existing models have been increasing. However, the deployment of the integrated frameworks among the bioeconomy stakeholders that are capable of evaluating and identifying the promising biorefining routes with significant economic, social and environmental benefits is still not a common practice. This study proposes an integrated decision‐making support framework to identify cost‐competitive, low‐carbon fuel production pathways that are technically viable and can potentially provide maximum GHG emission reduction.
               
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