(258b) Designing Resilient Biorefineries Under Policy and Technology Uncertainty: A Scenario-Based Systems Approach

Achieving climate mitigation targets requires coordinated advances in both policy and technology^{1, 2}. Scientists continue to develop low-carbon systems—such as electric vehicles, renewable energy, and sustainable manufacturing—while policymakers implement carbon pricing mechanisms and emissions regulations to steer decarbonization. However, the future evolution of these technologies and policies is deeply uncertain and often diverges from assumptions used in infrastructure planning. This uncertainty challenges the design of long-lived systems, such as biorefineries, that must remain viable across a wide range of future scenarios.

This work develops a multi-period, superstructure-based optimization framework for biorefinery design and capacity expansion under long-term uncertainty. Environmental performance is assessed with prospective life cycle assessment (LCA), leveraging premise, a tool that updates the background database (ecoinvent) with projections from integrated assessment models (IAMs)³. These models simulate interactions between the global economy, energy systems, and climate policy under different Shared Socioeconomic Pathways (SSPs)—plausible narratives of how society and technology may evolve. To model economic performance over time, capital costs are adjusted using the Chemical Engineering Plant Cost Index (CEPCI), which tracks inflation and investment cost trends in the chemical process industry, while operating costs are projected using commodity price forecasts. These adjustments allow the model to reflect realistic cost fluctuations across future scenarios.

The process superstructure includes a diverse portfolio of technologies for producing commodity and specialty chemicals, drop-in fuels, and carbon capture and utilization. Two carbon pricing mechanisms—carbon tax and cap-and-trade—are incorporated with time-dependent policy trajectories. A bi-objective optimization using the ε-constraint method evaluates trade-offs between net present value and cumulative carbon emissions. The scenario-based framework tests multiple combinations of Shared Socioeconomic Pathways (SSPs) alongside varying carbon price trajectories and emissions caps, capturing a wide range of plausible policy and technology futures. By embedding dynamic environmental and economic assumptions into this framework, the model identifies biorefinery strategies that remain economically and environmentally robust across divergent long-term scenarios. The results emphasize the importance of flexible, forward-looking planning in sustainable process systems design.

References:

(1) Popp, D. Environmental policy and innovation: a decade of research. 2019.

(2) Fawzy, S.; Osman, A. I.; Doran, J.; Rooney, D. W. Strategies for mitigation of climate change: a review. Environmental Chemistry Letters 2020, 18, 2069-2094.

(3) Sacchi, R.; Terlouw, T.; Siala, K.; Dirnaichner, A.; Bauer, C.; Cox, B.; Mutel, C. L.; Daioglou, V.; Luderer, G. PRospective EnvironMental Impact asSEment (premise): A streamlined approach to producing databases for prospective life cycle assessment using integrated assessment models. Renewable and Sustainable Energy Reviews 2022/05/01, 160. DOI: 10.1016/j.rser.2022.112311.