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Techno-economic and georeferenced analysis of forestry residues-based Fischer-Tropsch diesel with carbon capture in Brazil

Abstract This study aims to identify the potential for the deployment of diesel biofuel production based on forestry residues conversion through Fischer-Tropsch synthesis in Brazil. It develops a technical and economic analysis to estimate in what extension (georeferenced analysis) and at what costs (process analysis) can this biomass-based diesel contribute to the Brazilian diesel supply, and to the reduction of greenhouse gas emissions. Findings indicate the annual techno-economic potential of 80.3 PJ (considering the use of eucalyptus and pine residues), mostly concentrated in the South, Midwest and Southeast regions of the country. Overall, 21 production hotspots were identified, allowing the deployment of 27 facilities across the country. A clear advantage of this fuel production route is the fact that the carbon capture and storage can be intrinsic to the process, leading to negative CO2 emissions of the fuel production chain. Total mitigation potential is nearly 25 MtCO2 yearly. Furthermore, while still not cost-competitive without ambitious climate and energy policies in place, the forestry residue-based diesel can contribute to the reduction of the country's dependency on imports, resulting in positive impacts on the Brazilian trade balance.
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).45 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
