Systemanalys av biodrivmedel baserade på halm och vall - samproduktion av etanol och bioolja

Large amounts of domestic raw material will be needed for future biofuel production in Sweden. Various grasses and straw are interesting alternatives for ethanol production. In the ethanol production, hydrolysis lignin residual is produced, which does not yet have a well-formulated end-use. HTL is a liquefaction process that can be used to produce bio-oil. In this project we have studied whether hydrolysis lignin residue from ethanol production could be used as raw material in the HTL process. The produced bio-oil can be upgraded together with fossil oil in a conventional refinery and converted into biofuel components. In this system study, biofuel production based on straw and ley grass as raw material have been studied in terms of climate impact, mass flows and economy. Four scenarios were investigated, two with straw as raw material and two with ley grass as raw materi-al. In all scenarios, the raw material was assumed to be used for ethanol production. In two scenarios, lignin residue from ethanol production was sent for incineration. In the other two scenarios, the lignin residue is further processed bio-oil via the HTL process. In all scenarios the climate impact was reduced compared to fossil fuels. Ethanol gives a reduction of 72 – 92% and biofuels from bio-oil a reduction of 64 – 81% compared to the fossil reference. Considering soil carbon however has a large effect on the climate impact; removing straw is a loss of carbon while cultivation of ley grass add carbon to the soil. The cost of producing ethanol was calculated to be between SEK 3 200 – 4 800 per metric ton ethanol. The fuels produced via HTL were estimated to have a production cost between SEK 11 600 – 15 100 per metric ton of fuel. Thus, biofuels from hydrolysis lignin were calculated to be much more expensive than ethanol. This is mainly due to the costs associated with the upgrade of bio-oil. However, results should be carefully interpreted as there is a lack of input data and major uncertainties in the estimations.