Driving on renewables on the prospects for life-cycle based energetic conversion of alternative fuels up to 2050 in EU countries

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2 Driving on renewables on the prospects for life-cycle based energetic conversion of alternative fuels up to 5 in U countries Amela Ajanovic, Gerfried Jungmeier, Martin Beermann and Reinhard Haas nergy economics Group, Vienna University of Technology, Austria Ajanovic@eeg.tuwien.ac.at, Haas@eeg.tuwien.ac.at Joanneum Research Graz, Austria gerfried.jungmeier@joanneum.at, Martin.Beermann@joanneum.at Abstract - The core objective of this paper is to investigate the perspectives of renewable fuels mainly from an energetic life-cycle assessment based point-of-view in a dynamic framework till 5 in comparison to fossil fuels. Finally we analyze how this might impact market prospects from energy economic point-of-view. As renewable fuels we consider various categories of st and nd generation biofuels as well as electricity and hydrogen from renewable energy sources. The most important results of this analysis are: (i) The energetic improvements up to 5 will lead to substantial reduction of energetic losses in the WTT as well as in TTW part of the energy service provision chain;(ii) By 5 the total driving costs of all analysed fuels and powertrains will almost even out; (iii) The major uncertainty remaining regarding BV and FCV is how fast technological learning will take place especially for the battery and the fuel cells. Keywords Biofuels, renewables, energetic performance, economics. Introduction Fuels based on renewable energy are considered as a major environmentally benign alternative to fossil fuels. However, the ecological performance as well as the energetic balance and finally the economic competitiveness are still barriers for a broad market breakthrough of these energy carriers. The core objective of this paper is to investigate the perspectives of renewable fuels mainly from an energetic life-cycle assessment based point-of-view in a dynamic framework till 5 in comparison to fossil fuels. Of specific interest in this context is, that the over-all energetic performance of alternative fuels is split up into a renewable (R) and a fossil (FF) energy part based on a life-cycle assessment approach. As renewable fuels we consider various categories of st and nd generation biofuels as well as electricity and hydrogen from renewable energy. The analysis is conducted for the time period up to 5 and is based on average figures for U-5 countries regarding production of biofuels, conversion of biomass into fuels, electricity and hydrogen from biomass, PV, wind and hydro. We note that up to 5 also fundamental changes in the structure of passenger transport may have taken place. However, these changes are not subject of this paper and do also not influence the results. The only dimension where we have to rely on an external scenario are learning rates used for the final economic analysis. In this economic analysis the relevance of the development of the energetic performance for the future development of the economics of alternative fuels (including CO -taxation) is investigated.. Method of approach Our method of approach is based on scenarios for the development of the energetic performance of conversion efficiencies in the whole energy service mobility providing chain, see Figure. prim WTT f conv WTW fuel car TTW S mobility Figure. WTT and TTW - conversion in the energy service providing chain. Moreover, from energetic point-of-view it is of interest how much fossil respectively renewable energy is used to provide a unit of energy to be used

3 in the car. This is described by the primary energy or feedstock conversion factor f conv.. The over-all energy used per km driven results from conversion efficiency in the WTT- and the TTW-part of the chain and is: WTT WTW TTW () WTT ( fconv ) () TTW FF shff (3) TTW R shr () ( f sh (5) WTT R conv ) R ( f sh (6) WTT FF conv ) FF R LCA R LCA_ CAR RWTW (7) R WTW f conv sh R (8) FF LCA FF LCA_ CAR FFWTW (9) FF WTW f conv sh FF () where: f conv. conversion factor of feedstock (FS) or primary energy into fuel [kwh_fs/kwh_fuel] fuel intensity [kwh_fuel/km] RLCA total renewable energy used [kwh_fs/km] FFLCA total fossil energy used [kwh_fs/km] RLCA _ CAR.renewable energy used for production and scrappage of car FFLCA _ CAR.fossil energy used for production and scrappage of car RWTW total renewable energy used for production of fuel used FFWTW total fossil energy used for production of fuel used sh R.share of renewable energy in WTT-balance sh FF.share of fossil energy in WTT-balance. This work extends the analysis conducted in Ajanovic et al [], Ajanovic et al [], and Ajanovic et al [3]. With respect to the literature the most important analyses are summarized by Panoutsou []. We focus on electricity and hydrogen from RS and the following categories of biofuels: st generation biofuels BD-: biodiesel from rape seed and other oil seeds; B-: bioethanol from wheat and maize; BG: biogas from manure, grass and green maize; nd generation biofuels: BD-: biodiesel from biomass-to liquids (BTL) with Fischer-Tropsch process; B-: bioethanol from lignocellulose; : biogas from synthetic gas from biomass. The final economic analysis is based on: the following increases of energy prices: fossil 3%/year, agricultural feedstocks %/year, biomass and other lignocellulosis based energy carriers %/year, technological learning effects (based on global developments); the introduction of a CO -based tax on fuels. 3. Dynamic energetic Well-to-Tank assessment From the energetic point-of-view it is of course of interest how this performance looks like currently, what will be the range of possible developments and under which conditions will which developments take place. The Figures, 3 and depict how the conversion factor looks like currently and what will be the range of possible developments up to 5. f_conv (kwh_in/kwh_out) B Wheat BD Rape seed BG Green maize FT- B Ligno Fossil kwh/kwh Used at tank:kwh 5 R kwh/kwh B Wheat BD Rape seed BG Green maize FT- B Ligno Figure. The feedstock/fuel conversion factor f conv for an energetic WTT assessment of conventionaland bio-fuels for and 5 (Source: Joanneum Research calculations, [5]) The starting points are depicted in Figure, 3 and on the left-hand side. Figure 3 provides the energetic WTT assessment of the considered conventional fossil fuels and biofuels for. We can see that a major problem of BF- is the relatively high share of fossil energy higher than those of BF- while for BF- the low conversion efficiency and the corresponding high input of renewable feedstocks is the major problem. However, we can also see that up to 5 it is expected that this problem will be relieved but only slightly. The WTT-conversion factor f conv for an energetic WTT assessment of conventional fuels and electricity for and 5 is depicted in Figure 3. This Figure depicts the clear preference for generating electricity from wind or hydro power. Figure depicts the WTT-conversion factor f conv for an energetic WTT assessment of conventional fuels and hydrogen for and 5.

4 f-conv (kwh-in/kwh-out) le-uct Coal le_new NG le_wind/hydro le_wood Fossil kwh/kwh Used at tank: kwh 5 R kwh/kwh le-uct Coal le_new NG le_wind/hydro le_wood Figure 3. WTT-conversion factor f conv for an energetic WTT assessment of conventional fuels and electricity for and 5 (Source: Joanneum Research calculations, [5]) A major perception of Figure 3 and Figure is the high input required for producing electricity or hydrogen from biomass which decreases only slightly up to 5 f-conv (kwh_in/kwh_out) H-NG-Russia H-NG-U-Mix H-RS-Wind/hydro H-RS-Wood Fossil kwh/kwh Used at tank: kwh 5 R kwh/kwh H-NG-Russia H-NG-U-Mix H-RS-Wind/hydro H-RS-Wood Figure. WTT-conversion factor f conv for an energetic WTT assessment of conventional fuels and hydrogen for and 5 (Source: Joanneum Research calculations, [5]) Table. WTT-conversion factor f conv for conventional fuels, biofuels, electricity and hydrogen for FF input R input nergy content Unit kwh/kwh kwh/kwh kwh/unit l Gasol l kg kg...78 l Gasol_equ Biodiesel RM l _equ kg BTL-FT- l _equ l Gasol_equ kg _equ le UCT Coal Mix kwh 3... le New NG kwh.8.. le RS- Wind/Hydro kwh... le RS- Wood kwh H-NG-Russia kg H H-NG-U-Mix kg H H-RS-Wind/Hydro kg H H-RS-Wood kg H Table. WTT-conversion factor f conv for conventional fuels, biofuels, electricity and hydrogen for 5 FF input R input nergy content Unit kwh/kwh kwh/kwh kwh/unit l Gasol l kg...53 kg...78 l Gasol_equ Biodiesel RM l _equ kg BTL-FT- l _equ l Gasol_equ kg _equ le UCT Coal Mix kwh.6.. le New NG kwh... le RS- Wind/Hydro kwh..3. le RS- Wood kwh.6.7. H-NG-Russia kg H H-NG-U-Mix kg H H-RS-Wind/Hydro kg H H-RS-Wood kg H TTW-analysis: Development of fuel intensity Figure 5 shows the development of fuel intensity (), power-specific fuel intensity and power (P) of new vehicles in U-5 from 99 to 9. in Figure 5 and Figure 6 does not reflect the real efficiency improvement because it is distorted by the switch to larger cars. To correct for this we define power-specific fuel intensity P: P (l/ (km kw) ) () P litre gas_equiv P-New (l/km/kw) _New l/km kw-new kw Figure 5. Development of fuel intensity, powerspecific fuel intensity and power (kw) of new vehicles in U-5 from 99 to 9 [6]. P-New kw-new _New. 99= Figure 6. Normalised development (99=) of fuel intensity, power-specific fuel intensity and power of new vehicles in U-5 from 99 to 9 [6] Power (kw)

5 It can clearly be seen from Figure 5 and Figure 6 that the decrease in P from 99 to 9 was virtually twice as high as the decrease of. Figure 7 describes the historical developments of passenger cars fuel intensities and assumptions for development in the scenarios up to 5 (for average car size of 8 kw). Note, that the steepest decrease in fuel intensities took already place before as a first result of the C to improve the efficiency of cars. kwh/km //Biogas -Hybrid /Biogas-Hybrid Flex-Fuel BV FCV Figure 7. Historical developments of passenger cars fuel intensities and assumptions for development in the BAU scenarios up to 5 (for average car size of 8 kw) (Source: [7], [8], [9], []) 5. LCA analysis of car We also consider the energy needed for construction and scrappage of the cars, see equ. (7) and (9). Again we have a term for fossil energy FFLCA _ CAR and a term for renewable energy RLCA _ CAR. 6. Summary: Aggregated WTW-analysis Finally we include the three steps of the analysis presented above in one aggregated picture. Figure 8 depicts the renewable and fossil shares in the whole WTW energy service provision chain for conventional fuels vs biofuels for. We can see that for all biofuels large parts of the total energy balance are attributed to WTT conversion losses. BTL-FT- Biodiesel RM -Hybrid kwh/km FF-WTT-Fuel kwh/km FF-TTW-Fuel kwh/km R-WTT-Fuel kwh/km R-TTW-Fuel kwh/km FF-Car kwh/km R-Car kwh/km Figure 8. Renewable and fossil energy shares in the whole WTW energy service provision chain in for conventional fuels vs biofuels Figure 9 depicts the renewable and fossil energy shares in the whole WTW energy service provision chain for conventional vs biofuels for 5. Compared to due to better fuel intensity the energy balance is improved for virtually all fuels. The improvements in the WTT-part are especially remarkable for biofuels nd generation. The renewable and fossil shares in the whole WTW energy service provision chain for conventional fuels vs fuels in BV and FCV for are depicted in Figure. It can be seen that considering the whole WTW chain the advantage of driving on electric renewables is clearly higher for electricity from wind or hydro than from biomass. In total the advantages of BV and FCV are only rather small. BTL-FT- Biodiesel RM -Hybrid kwh/km FF-WTT-Fuel kwh/km FF-TTW-Fuel kwh/km R-WTT-Fuel kwh/km R-TTW-Fuel kwh/km FF-Car kwh/km R-Car kwh/km Figure 9. Renewable and fossil energy shares in the whole WTW energy service provision chain in 5 for conventional vs biofuels

6 FCV-H-RS-Wood FCV-H-Wind/hydro FCV-H-NG-U-Mix FCV-H-NG-Russia BV RS- Wood BV RS- Wind/Hydro BV New NG BV UCT Coal Mix kwh/km FF-WTT-Fuel kwh/km FF-TTW-Fuel kwh/km R-WTT-Fuel kwh/km R-TTW-Fuel kwh/km FF-Car kwh/km R-Car kwh/km Figure. Renewable and fossil energy shares in the whole WTW energy service provision chain in for conventional fuels vs fuels used in BV and FCV Figure depicts the renewable and fossil energy shares in the whole WTW energy service provision chain for conventional fuels vs fuels in BV and FCV for 5. Compared to FCV show the best improvement of performance mainly due to better fuel intensity. FCV-H-RS-Wood FCV-H-Wind/hydro FCV-H-NG-U-Mix FCV-H-NG-Russia BV RS- Wood BV RS- Wind/Hydro BV New NG BV UCT Coal Mix kwh/km FF-WTT-Fuel kwh/km FF-TTW-Fuel kwh/km R-WTT-Fuel kwh/km R-TTW-Fuel kwh/km FF-Car kwh/km R-Car kwh/km Figure. Renewable and fossil energy shares in the WTW energy service provision chain in 5 for conventional fuels vs fuels used in BV and FCV 7. conomic assessment Of special interest in our analysis is finally how improvements in energetic performance influence economic competitiveness. Figure depicts the fuel costs of the service mobility in. Most expensive are cars driving on BTL, biogas, bioethanol from lignocellulosis because of their high production costs. Next is already a gasoline-powered car mainly due to high excise tax and high fuel intensity. Cheapest fuel cost for driving km show cars using. UR/km 8 6 -Hybrid Biodiesel RM BTL-FT- BV UCT Coal Mix BV New NG BV RS- Wind/Hydro BV RS- Wood FCV-H-NG-Russia FCV-H-NG-U-Mix FCV-H-RS-Wind FCV-H-RS-Wood Fuel costs (excl. Tax) UR/ km xcise tax UR/ km VAT CO-tax Figure. Fuel costs of service mobility in passenger cars in In a scenario with CO -taxes replacing excise taxes in 3 and increasing up to 5 by.5 cent/kgco and year fuel costs for driving are cheapest for electricity from RS. Also costs of hydrogen from RS and become also rather low and are remarkably cheaper than fossil fuels and biofuels, see Figure 3. UR/km 8 6 -Hybrid Biodiesel RM BTL-FT- BV UCT Coal Mix BV New NG BV RS- Wind/Hydro BV RS- Wood FCV-H-NG-Russia FCV-H-NG-U-Mix FCV-H-RS-Wind FCV-H-RS-Wood Fuel costs UR/ km VAT UR/ km xcise tax UR/ km CO-tax UR/ km Figure 3. Fuel costs of service in 5 These advantages of BV and FCV regarding lower fuel costs are more than compensated by higher capital costs in, see Figure. By 5 costs of most cars will even out, see Figure 5. Yet, various diesel cars still remain cheapest, mainly because of more km are driven in these cars and capital costs are distributed to larger distances.

7 FCV-H-RS-Wood FCV-H-RS-Wind FCV-H-NG-U-Mix FCV-H-NG-Russia BV RS- Wood BV RS- Wind/Hydro BV New NG BV UCT Coal Mix BTL-FT- Biodiesel RM -Hybrid UR/km Capital costs UR/ km O&M costs UR/ km Fuel costs UR/ km Figure. Total costs of service mobility in passenger cars in FCV-H-RS-Wood FCV-H-RS-Wind FCV-H-NG-U-Mix FCV-H-NG-Russia BV RS- Wood BV RS- Wind/Hydro BV New NG BV UCT Coal Mix BTL-FT- Biodiesel RM -Hybrid UR/km Capital costs UR/ km O&M costs UR/ km Fuel costs UR/ km Figure 5. Total costs of service mobility in passenger cars in 5 8. Conclusions The major conclusions of this analysis are: The energetic improvements of all powertrains up to 5 will lead to substantial reduction of energetic losses in the WTT as well as in TTW part of the energy service provision chain. However, from our analysis it is likely that more significant improvements take place in the TTW part. For BF- and biomethane significant saving potentials exist in the whole chain. Yet, for all biofuels as well as for the use of biomass for electricity generation and hydrogen production the problem remains that the conversion factor in 5 is still expected to be rather high (between and 3, see Figure, 3 and ). These energetic improvements will lead to the effect that the costs for driving will not increase to the extent that fuel prices increase. However, regarding the expected improvements in in the TTW part it is important to state that savings in over-all fossil energy consumption may not fully be harvested because of service becoming cheaper. So due to the Rebound-effect only 3% compared to calculated 5% maybe saved in the case of conventional vehicles. Finally, the following major uncertainties remain: (i) how soon and to what extent will BV and FCV enter the market; (ii) how fast will technological learning take place especially for the battery and the fuel cells and (iii) how will consumers behavior change with respect to size of cars purchased and with respect to vehicle km driven. 9. Nomenclature BD- biodiesel from rape seed and other oil seeds BD- biodiesel from biomass-to liquids (BTL) with Fischer-Tropsch process B- bioethanol from wheat and maize B- bioethanol from lignocellulose BF- st generation biofuels BF- nd generation biofuels BM biomethane from manure, grass and green maize biogas from synthetic gas from biomass TTW Tank-to-Wheel WTW Well-to-Wheel WTT Well-to-Tank BV Battery electric vehicles FCV Fuel cell vehicles. References []. Ajanovic A., Haas R., conomic Challenges for the Future Relevance of Biofuels in Transport in U- Countries. nergy 35 () []. Ajanovic A., Haas R., The future relevance of alternative energy carriers in Austria. IS-5, June, Denizli, Turkey [3] Ajanovic A., On the Future Relevance of Biofuels for Transport in U-5 Countries, nergy & Sustainability. [] Panoutsou C., leftheriadis J., Nikolaou A., Biomass supply in U7 from to 3, nergy Policy 37 (9) [5] CONCAW: Well-to-Wheels analysis of future automotive fuels and powertrains in the uropean context, WLL-TO-TANK Report APPNDIX, Description and detailed energy and GHG balance of individual pathways, November 8 [6] Ajanovic A. et al, : ALTR-MOTIV. Final Report. [7] C, : Progress report on implementation of the Community s integrated approach to reduce CO emissions from light-duty vehicles,, (COM, 656) [8] Toro F., Jain S., Reitze F., Ajanovic A., Haas R., Furlan S., Wilde H., : State of the art for alternative fuels and alternative automotive technologies, ALTR- MOTIV, D8 [9] CONCAW, 8: Well-to-Wheels analysis of future automotive fuels and powertrains in the uropean context, TANK-to-WHLS Report Version 3, October 8 [] DB, 9: Database CO emissions monitoring: Decision No 753//C of the uropean Parliament and of the Council of June. Database to monitor the average specific emissions of CO from new passenger cars, 9 [] ALTR-MOTIV database: