(258g) Optimized Scaling of Biomass-Based Carbon Dioxide Removal Systems

Carbon Dioxide Removal (CDR) has been identified as a strategy for lowering net global greenhouse gas emissions in economic sectors that are challenging to decarbonize.^[1] CDR technologies can broadly be classified into direct and indirect methods. Direct technologies rely on chemical reactions or physical adsorption processes and have a high energy demand because of the thermodynamic challenges associated with capturing a dilute stream of CO₂ from air.^[2] As a result these technologies need to be powered by renewable sources and present a high-cost barrier to large-scale deployment, in order to achieve a net reduction in atmospheric CO₂.^[3] In contrast, indirect CDR technologies leverage the natural ability of plants to remove CO₂ from air by photosynthesis. Utilizing biomass-derived residues requires overcoming logistical challenges associated with collecting, transporting, and processing these low-density residues to improve process economics and net CO₂ captured across the supply chain.^[4]

In this work, we focused on four CDR technologies that convert biomass to carbonaceous residues or char using pyrolysis.^[5] A general mass and energy balance was developed to explore a range of different operating conditions to quantify the yield and composition of the char generated, the energy required by the process, and the net CO₂ captured by the process. This balance was integrated with pre-processing, transportation, and post-processing requirements, such as burial, by using a Mixed Integer Linear Programming (MILP) model to determine the size and location of facilities. This model was applied as a case study in Minnesota for utilizing forest-based logging residues as CDR input. Two different scale-up strategies were compared: (i) a single large centralized facility, and (ii) many smaller distributed facilities. The annual cost of operation and annual CO₂ removal for different scenarios was calculated to identify trade-offs associated with system decisions. Furthermore, the sensitivity of model parameters including the quality of incoming biomass and economic values of inputs and outputs was evaluated to demonstrate opportunities for these technologies to be competitively deployed and remove atmospheric CO₂ at the required scales.

[1] A. Usadi, M. Higgins, and B. Mignone, "President's Page: Emerging CO₂ removal options require geoscience skills," The Leading Edge 43, (2024).

[2] J. K. Soeherman, A. J. Jones, and P. J. Dauenhauer. “Overcoming the entropy penalty of direct air capture for efficient gigatonne removal of carbon dioxide”. In: ACS Engineering Au, 3, 2, (2023).

[3] K.Z. House, A.C. Baclig, M. Ranjan, E.A. van Nierop, J. Wilcox, and H.J. Herzog. “Economic and energetic analysis of capturing CO2 from ambient air”. In: Proceedings of the National Academy of Sciences, 108, (2011).

[4] W. A. Marvin, L. D. Schmidt, and P. Daoutidis. “Biorefinery Location and Technology Selection Through Supply Chain Optimization”. In: Industrial & Engineering Chemistry Research, 52 (2013)

[5] D. Neves, H. Thunman, A. Matos, L. Tarehlho, and A. Gomez-Barea. “Characterization and prediction of biomass pyrolysis products”. In: Progress in Energy and Combustion Science, 37, (2017).