Well-To-Wheel LCI data for fossil and renewable fuels on the Swedish market

Report, 2013

The purpose of this project has been to gather and compile the best available environmental data for vehicle fuels on the Swedish market, for use in environmental assessments, such as LCA etc. The main deliverable is a database, published by f3 and also distributed by CPM - Swedish Life Cycle Center. Life cycle inventory data (LCI-data) for well-to-tank (production of the fuel) as well as tank-to-wheel (combustion of the fuel in a vehicle) have been gathered from different available LCA studies and other sources. No LCA modelling has been carried out in the project except for some minor calculations in some cases. The fuels studied are fuels used in heavy duty vehicles (trucks and buses) and data sets for the following fuels are published in the database; ED95, Fossil diesel, RME, HVO, biogas and natural gas. The reference unit for the reported LCI-data is 1 MJ fuel. When assessing the impact from using different fuels in vehicles, the consumption of the fuel needs to be considered in addition to the environmental data for the fuel. Note that the fuel consumption in heavy duty vehicles can differ widely due to other factors than the fuel type, namely vehicle type and driving conditions. The actual figures are presented in the database and not in the report. However, an illustration of the results for the fuel data sets based on global warming potentials [g CO2-eq/MJ fuel] is presented. For well-to-tank, there are for most fuels two different scenarios; allocation and system expansion. For fossil diesel and natural gas there is only one scenario. The different scenarios published are the scenarios available in the original data sources. For well-to-tank, the biofuels ED95, RME and HVO show a larger impact than the fossil diesel. Biogas, regardless of the production process, shows a similar impact as the natural gas. For tank-to-wheel, two data sets for each fuel are presented; Euro V and Euro VI engine. The data sets differ concerning the emissions of methane (CH4), nitrogen oxides (NOx), non-methane volatile organic compounds (NMVOC) and particles (PM), while emissions of fossil carbon dioxide (CO2), carbon monoxide (CO), nitrous oxide (N2O) and sulphur dioxide (SO2) are the same irrespective of Euro class. For the biofuels biogas and HVO, the fossil carbon dioxide (CO2) is assumed to be zero. The global warming impact however is not zero, since there are small emissions of the other greenhouse gases (CH4 and N2O). For RME a very small part (1 of 19 carbon atoms) in the fuel is of fossil origin, which means that some fossil CO2 is generated as well. For ED95 the fossil CO2 comes from the components (not from the ethanol). All biofuels have a global warming impact of less than 10 grams of CO2-eq/MJ, while the fossil fuels vary between 60-75 grams of CO2-eq/MJ. For most bio fuels, the total well-to-wheel impact is much lower than for the corresponding fossil fuels. The impact from ED95 and RME is less than 40% of the impact from diesel. The biogases (no allocation) show an impact of between 10-30% of the impact from natural gas. If considering the system expansion from the use of biogases, the savings from biogas will be even higher. The only biofuel showing an impact within in the same range as the corresponding fossil fuel is HVO from palm oil, which has more or less the same impact as diesel has. The HVO from rape-seed oil is however significantly lower (40%) compared to fossil diesel. General conclusions *) The choice of methodology (e.g. energy allocation or no allocation versus system expansion) can have large influence on the LCI results (data). *) The choices of the alternative material and/or energy which are assumed to replace the generated by-products and/or energy are of large importance. *) For ED95 and RME there are small differences between the two scenarios energy allocation and system expansion. *) For the biogases, it is the opposite situation. The system expansion results in much lower values (often even negative). This is an expected result since the corresponding “allocation” scenario, allocates the entire impact to the biogas.