Title
Economic optimization for a dual-feedstock lignocellulosic-based sustainable biofuel supply chain considering greenhouse gas emission and soil carbon stock
Author
Zhang, B.
Guo, C.
Lin, T.
Faaij, A.P.C.
Publication year
2022
Abstract
Environmental factors, including greenhouse gas (GHG) emissions and soil organic carbon (SOC), should be considered when building a sustainable biofuel supply chain. This work developed a three-step optimization approach integrating a geographical information system-based mixed-integer linear programming model to economically optimize the biofuel supply chain on the premise of meeting certain GHG emission criteria. The biomass supply grid cell was considered first, based on a maximum level of GHG emissions, prior to economic optimization. The optimization simultaneously considered dual-feedstock sourcing, selection between distributed and centralized configurations, and the impact of maintaining SOC balance in agricultural soil on biomass availability. The applicability of the modeling approach was demonstrated through a case study that optimized a dual-feedstock renewable jet fuel supply chain via a gasification-Fischer–Tropsch (gasification-FT) conversion pathway in 2050 under three biomass availability scenarios. The case study results show that the differences in procurement costs and GHG emissions between energy crops and agricultural residues have a large impact on the layout of the supply chain. The supply-chain configuration tends to be more centralized with large-scale biorefineries when a supply region has an intensive and centralized distribution of biomass resources. The cost-supply curves demonstrated the technical potential of biofuels that could be obtained at a certain level of cost. Additionally, sensitivity analysis shows that the GHG emission credit from producing extra electricity during the gasification-FT process will be significantly reduced with a rising share of renewable electricity generation in the future.
Subject
Biofuel supply chain optimization
GHG emission
Lignocellulosic biomass
Mixed integer linear programming
Soil organic carbon
Sustainable
Energy Efficiency
Energy / Geological Survey Netherlands
To reference this document use:
http://resolver.tudelft.nl/uuid:743cdb80-ff09-4d3f-af3b-e3ba855634ea
DOI
https://doi.org/10.1002/bbb.2347
TNO identifier
980796
Publisher
John Wiley and Sons Ltd
ISSN
1932-104X
Source
Biofuels, Bioproducts and Biorefining, 16 (16), 653-670
Document type
article