The AOPII Cost-effectiveness Study Part III: The Transport Base Case. Annex B.8 Spain

Transcription

1 The AOPII Cost-effectiveness Study Annex B.8 Spain Draft Final report Presented to Working 7 August 1999 by The European Commission, Standard & Poor s DRI and KULeuven

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3 Contents 1. INTRODUCTION GENERAL ASSUMPTIONS TRAFFIC COSTS AND PRICES MOTOR VEHICLE STOCK FUELS EMISSIONS FROM ROAD TRAFFIC SELECTED SOURCES...26 APPENDIX 1: OTHER TRANSPORT INDICATORS...28 APPENDIX 2: AVERAGE EMISSION FACTORS...32 APPENDIX 3: EMISSION REDUCTION CONTRIBUTIONS...33 European Commission --Standard & Poor s DRI KULeuven, August

4 Tables and Charts Table 1: Macroeconomic indicators, Spain...3 Table 2: Total traffic demand by mode for Spain and Madrid (Mvkm)...5 Table 3: passenger traffic demand by mode for Spain and Madrid (Mpkm)...5 Table 4: Freight traffic demand by mode for Spain (Mtkm)...5 Table 5: Annual traffic demand growth for all modes...6 Table 6: Annual traffic demand growth for all passenger modes...6 Table 7: Annual Traffic demand growth for all freight modes...6 Chart 1: Modal shares for Spanish passenger transport (pkm based)...7 Table 8: Modal shares in Spain for passenger traffic (based on pkm)...7 Chart 2: Modal shares in Spain for freight transport (based on tkm)...7 Table 9: Modal shares for Spanish freight traffic (based on tkm)...8 Table 10: Average load factors, Spain...8 Table 11: Average vehicle purchase cost components, 1996 (98 )...10 Table 12: Average annual driving costs (excl. fuel), 1996 (98 )...11 Table 13: Average fuel price components, 1996 (98 )...11 Table 14: The lifetime driving costs by vehicle category (98 ECU/vkm)...12 Table 15: Growth rate of the lifetime driving cost for Spain...12 Table 16: Vehicle stocks in Spain...13 Chart 3: Age structure of the car stock for Spain, Chart 4: Age structure of the truck stock for Spain, Table 17: Average vehicle age for Spain...15 Chart 5: Fuel consumption profiles for Spain...16 Table 18: Auto-Oil II base case fuel specifications Spain...17 Figure 1: Road transport emission indices for Spain (1995=100)...18 Table 19: Road transport emission indices for Spain (part A)...19 Table 20: Road transport emission indices for Spain (part B)...19 Table 21: Road transport emissions indices for Spain (part C)...20 Table 22: Total emission levels for Spain (tonnes)...20 Table 23: Emissions by vehicle category for Spain (tonnes)...21 Chart 6: Total CO emissions by vehicle category for Spain (tonnes)...22 Chart 7: Total NOx emissions by vehicle category for Spain (tonnes)...22 Chart 8: Total VOC emissions by vehicle category for Spain (tonnes)...23 Chart 9: Total Benzene emissions by vehicle category for Spain (tonnes)...23 Chart 10: Total PM 10 emissions by vehicle category for Spain (tonnes)...24 Chart 11: Total CO2 emissions by vehicle category for Spain (tonnes)...24 Chart 12: Total SO2 emissions by vehicle category for Spain (tonnes)...25 Table 24: Emissions from passenger cars by fuel class for Spain (tonnes)...26 Chart 13: Traffic demand compared to GDP (1990 = 1), Spain...28 Table 25: Other transport indicators for Spain --absolute levels...29 Table 26: Other transport indicators for Spain -- growth rates...29 Chart 14: Traffic demand (in vkm, pkm and tkm per capita), Spain...29 Chart 15: Traffic demand (in vkm and pkm per capita), Madrid...30 Table 27: Vehicle stock per capita in Spain...31 Chart 16: Average annual mileage per vehicle (thousand km), Spain...30 Table 28: Average Emission factors across all modes, Spain (g/km)...32 Chart 17: Emission reduction contributions for NOx...33 Chart 18: Emission reduction contributions for PM Chart 19: Emission reduction contributions for VOC European Commission, Standard & Poor s DRI KULeuven, August 1999

5 1. Introduction This annex presents the Auto Oil II transport base case for Spain as an addendum to Part III of the AOPII Cost-effectiveness study. The latter contains an executive summary and a cross-country overview of the AOPII transport base case as well as some background information and important comments related to the methodology and data collection process. It forms an integral part of this annex. This annex includes key assumptions and selected indicators related to traffic demand, costs and prices, vehicle stocks, fuel consumption and fuel quality specifications, and emissions from road transport. The complete data set is also available in a spreadsheet, which can be obtained on demand. All comments and questions should be addressed to Thomas Verheye (thomas.verheye@dg11.cec.be). 2. General assumptions The main macro-economic assumptions used to construct this base case are presented in Table 1. 1 Historical values up to 1995 of the main macroeconomic indicators have been obtained from Spain National Statistical Office, up to The values used from 1996 to 2020, are consistently taken from the Energy 2020 forecast prepared by DGXVII (i.e., the pre-kyoto reference scenario), throughout the AOPII transport base case. Throughout the study, a discount rate of 4% has been used, corresponding to the long-term real interest rate. Data for Madrid came from different sources, and we had to use a different definition of Madrid. A number of data for Madrid however, correspond to a region which includes about 4.6 million inhabitants. This corresponds to a large part of the Comunidad de Madrid (Almendra Central, Periferia Urbana and Corona Metropolitana, excluding the Corona regional). Population in other urban areas of Spain has also been estimated based on UN data, Compendium of Human Settlement Statistics. TABLE 1: MACROECONOMIC INDICATORS, SPAIN Macroeconomic indicators Average annual compound growth rates Region Concept Spain GDP, 98 ECU 1.3% 3.1% 2.9% 2.8% 2.4% 2.2% Spain Inflation 5.2% 2.9% 2.6% 2.4% 2.2% 2.0% Annual average Region Concept Spain Ecu per peseta Spain Population Madrid Population The Auto Oil II base case has been constructed in 1998, based on data then available, such as the Pre-Kyoto scenario from DGXVII. No reference is made to the euro, which did not exist before December 31, Economic concepts such as GDP are thus defined in constant 1998 ECU. As a consequence, the exchange rate between the national currencies and the ECU differ slightly from the conversion rates to the euro. European Commission --Standard & Poor s DRI KULeuven, August

6 A number of other indicators were calculated ex-post to verify the overall consistency of the base case assumptions and data. These are presented in Appendix Traffic In this section, we describe the traffic demand scenarios that were built based on historical data published by statistical organisations and on forecasts received from transport authorities. We discuss the key facts and the assumptions taken to complement existing data. For the period 1990 to 1996, traffic data for Spain has been mainly obtained from two publications from the Ministerio de Fomento, Transport and Communications 1996, and the Statistical yearbook, Detailed information on traffic in vehicle-kilometre and in passenger-kilometre or tonne-kilometre is published in these publications, from which we could derive load factors. However, the detailed information we collected on traffic in Spain was mainly for the State and Regions networks. We had to take account of traffic on smaller roads (from the Diputationes and Ayutamentos) by applying a correction factor of 1.62, which we computed based on the data available for those networks (for 1990 and 1991 only). We did not apply this factor to moped and motorcycle traffic, as this would imply a annual mileage of about 20,000 km per year for these vehicles. The current values, at about 13,000 km per year, are already very high when compared to other European countries. No forecast was available for Spain. We thus assumed that the growth rate of non-urban passenger traffic (in passenger-kilometre) would be equal to the growth rate of consumer income, multiplied a correction factor. This correction factor, the income elasticity, is proportional to the inverse of income per capita, and has been calibrated on Dutch data, for which detailed information was available. This implies that, assuming the same growth of consumer income, traffic growth will be lower in countries with high revenue per inhabitant than in a country with low revenue per inhabitant. For nonurban freight traffic, we simply assumed that it would grow at the same rate as GDP. Urban traffic was assumed to grow at half the rate of non-bran traffic Whenever Spanish statistics did not provide a breakdown of transport modes as detailed as the categories of Tremove (i.e. the split between small and large cars, and between small and large trucks), we attributed to each sub-category a share of traffic proportional to the number of vehicles (from the vehicle stock data) and the average annual mileage (taken from MEET deliverable 21). Non-motorised transport was assumed to amount to 3% of total car passenger transport. Key results for the traffic demand scenarios are presented in the tables below, including traffic demand levels, growth rates, modal shares, and load factors. Table 2 shows the trends in traffic demand for Spain and the Madrid region, expressed in vehicle-kilometres for all modes. Trends expressed in passengerkilometres are shown in Table 3. The data for freight transport, expressed in tonnes-kilometres are shown in Table 4. 4 European Commission, Standard & Poor s DRI KULeuven, August 1999

7 TABLE 2: TOTAL TRAFFIC DEMAND BY MODE FOR SPAIN AND MADRID (MVKM) Traffic demand in million vehicle-kilometre Region Mode Spain Total 200, , , , , , ,518 Spain Buses & coaches 2,478 4,249 4,624 5,362 6,089 6,703 7,275 Spain Cars 146, , , , , , ,418 Spain Train & metro Spain Trucks 39,157 48,433 55,802 62,779 70,481 77,797 85,264 Spain Motorcycles 11,379 12,199 11,590 12,644 13,625 14,417 15,130 Spain Non-motorised 1,342 1,556 1,741 1,886 2,018 2,124 2,219 Region Mode Madrid Total 11,845 13,757 15,041 16,261 17,413 18,361 19,226 Madrid Buses & coaches Madrid Cars 7,308 8,475 9,485 10,271 10,994 11,571 12,085 Madrid Train & metro Madrid Trucks 2,418 3,015 3,355 3,607 3,869 4,106 4,337 Madrid Motorcycles 1,700 1,823 1,721 1,864 1,995 2,100 2,193 Madrid Non-motorised TABLE 3: PASSENGER TRAFFIC DEMAND BY MODE FOR SPAIN AND MADRID (MPKM) Traffic demand in million passenger-kilometre Region Mode Spain Total 375, , , , , , ,884 Spain Buses & coaches 41,722 60,671 65,941 76,463 86,824 95, ,744 Spain Cars 295, , , , , , ,743 Spain Train & metro 25,791 26,232 29,784 33,303 36,681 39,479 42,048 Spain Motorcycles 11,379 12,199 11,590 12,644 13,625 14,417 15,130 Spain Non-motorised 1,342 1,556 1,741 1,886 2,018 2,124 2,219 Region Mode Madrid Total 28,428 31,687 34,103 36,929 39,527 41,602 43,452 Madrid Buses & coaches 2,980 2,336 2,385 2,582 2,764 2,909 3,038 Madrid Cars 14,788 17,091 19,108 20,691 22,147 23,310 24,346 Madrid Train & metro 8,740 10,183 10,605 11,484 12,291 12,937 13,512 Madrid Motorcycles 1,700 1,823 1,721 1,864 1,995 2,100 2,193 Madrid Non-motorised TABLE 4: FREIGHT TRAFFIC DEMAND BY MODE FOR SPAIN (MTKM) Traffic demand in million tonne-kilometre Region Mode Spain Total 256, , , , , , ,619 Spain Trucks 245, , , , , , ,343 Spain Train & metro 11,613 10,013 11,577 13,362 15,363 17,289 19,276 Spain Waterways The average annual compound growth rates of traffic demand for all modes are presented in Table 5. The growth rates for passenger transport are shown in Table 6. The same data for freight transport are shown in Table 7. European Commission --Standard & Poor s DRI KULeuven, August

8 TABLE 5: ANNUAL TRAFFIC DEMAND GROWTH FOR ALL MODES Traffic demand in vehicle-kilometre, average annual compound growth Region Mode Spain Total 3.3% 3.0% 2.6% 2.3% 1.8% 1.6% Spain Buses & coaches 11.4% 1.7% 3.0% 2.6% 1.9% 1.7% Spain Cars 3.0% 3.3% 2.8% 2.4% 1.8% 1.5% Spain Train & metro -1.3% 2.8% 2.5% 2.4% 1.9% 1.7% Spain Trucks 4.3% 2.9% 2.4% 2.3% 2.0% 1.8% Spain Motorcycles 1.4% -1.0% 1.8% 1.5% 1.1% 1.0% Spain Non-motorised 3.0% 2.3% 1.6% 1.4% 1.0% 0.9% Region Mode Madrid Total 3.0% 1.8% 1.6% 1.4% 1.1% 0.9% Madrid Buses & coaches -1.6% 0.4% 1.6% 1.4% 1.0% 0.9% Madrid Cars 3.0% 2.3% 1.6% 1.4% 1.0% 0.9% Madrid Train & metro 2.6% 0.9% 1.6% 1.4% 1.0% 0.9% Madrid Trucks 4.5% 2.2% 1.5% 1.4% 1.2% 1.1% Madrid Motorcycles 1.4% -1.1% 1.6% 1.4% 1.0% 0.9% Madrid Non-motorised 3.0% 2.3% 1.6% 1.4% 1.0% 0.9% TABLE 6: ANNUAL TRAFFIC DEMAND GROWTH FOR ALL PASSENGER MODES Traffic demand in passenger-kilometre, average annual compound growth Region Mode Spain Total 3.3% 2.9% 2.7% 2.4% 1.8% 1.5% Spain Buses & coaches 7.8% 1.7% 3.0% 2.6% 1.9% 1.7% Spain Cars 2.9% 3.3% 2.8% 2.4% 1.8% 1.5% Spain Train & metro 0.3% 2.6% 2.3% 2.0% 1.5% 1.3% Spain Motorcycles 1.4% -1.0% 1.8% 1.5% 1.1% 1.0% Spain Non-motorised 3.0% 2.3% 1.6% 1.4% 1.0% 0.9% Region Mode Madrid Total 2.2% 1.5% 1.6% 1.4% 1.0% 0.9% Madrid Buses & coaches -4.8% 0.4% 1.6% 1.4% 1.0% 0.9% Madrid Cars 2.9% 2.3% 1.6% 1.4% 1.0% 0.9% Madrid Train & metro 3.1% 0.8% 1.6% 1.4% 1.0% 0.9% Madrid Motorcycles 1.4% -1.1% 1.6% 1.4% 1.0% 0.9% Madrid Non-motorised 3.0% 2.3% 1.6% 1.4% 1.0% 0.9% TABLE 7: ANNUAL TRAFFIC DEMAND GROWTH FOR ALL FREIGHT MODES Traffic demand in tonne-kilometre, average annual compound growth Region Mode Spain Total 3.6% 2.9% 2.6% 2.5% 2.1% 2.0% Spain Trucks 3.9% 2.9% 2.6% 2.5% 2.1% 2.0% Spain Train & metro -2.9% 2.9% 2.9% 2.8% 2.4% 2.2% Spain Waterways Modal shares for passenger transport demand in Spain and Madrid are shown in Chart 1 and in Table 8. The chart clearly shows the predominance of road transport demand, at about 90% of all passenger kilometres in Spain. Modal shares remain constant over the forecast period. In large cities, such as Madrid, public transport represents a more important share of passenger traffic than the country average. Only about 55% of traffic is generated by cars in Madrid, against almost 80% in the whole country on average (see Table 8). 6 European Commission, Standard & Poor s DRI KULeuven, August 1999

9 CHART 1: MODAL SHARES FOR SPANISH PASSENGER TRANSPORT (PKM BASED) 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Spain 1995 Spain 2010 Madrid 1995 Madrid 2010 Buses & coaches Cars Train & metro Other TABLE 8: MODAL SHARES IN SPAIN FOR PASSENGER TRAFFIC (BASED ON PKM) Modal shares in Spain and Madrid - passenger traffic Region Mode Spain Buses & coaches 11% 14% 13% 13% 13% 13% 13% Spain Cars 79% 77% 79% 79% 79% 79% 79% Spain Train & metro 7% 6% 6% 6% 6% 6% 5% Spain Other 3% 3% 3% 2% 2% 2% 2% Madrid Buses & coaches 10% 7% 7% 7% 7% 7% 7% Madrid Cars 52% 54% 56% 56% 56% 56% 56% Madrid Train & metro 31% 32% 31% 31% 31% 31% 31% Madrid Other 7% 7% 6% 6% 6% 6% 6% Modal shares for freight transport demand in Spain are shown in Chart 2 and in Table 9,based on figures in tkm. Trucks account for about 97% of freight transport in Spain, compared to about 3% for freight trains. We have assumed waterways freight transport to be negligible. CHART 2: MODAL SHARES IN SPAIN FOR FREIGHT TRANSPORT (BASED ON TKM) 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Trucks Trains Waterways European Commission --Standard & Poor s DRI KULeuven, August

10 TABLE 9: MODAL SHARES FOR SPANISH FREIGHT TRAFFIC (BASED ON TKM) Modal shares in Spain - freight traffic Region Mode Spain Trucks 95% 97% 97% 97% 97% 97% 97% Spain Trains 5% 3% 3% 3% 3% 3% 3% Spain Waterways 0% 0% 0% 0% 0% 0% 0% We further distributed traffic demand for each transport mode over peak and off-peak periods. The breakdown between peak and off-peak traffic was not supplied by our sources. For each transport mode, we assumed the same split between peak and off-peak period as in Great Britain, where detailed information is available. Traffic is also divided in traffic by inhabitants and traffic by commuters. We generally assumed that commuters account for 12% of urban traffic, based on a TRENEN case study on London. However, considering the results of other TRENEN case studies, we proposed to use a value of 20% (close to a European average) in the final base case. For the non-urban areas, no such split is considered. Selected average load factors computed for the Spanish base case are presented in Table 10. Load factors have usually been computed for each transport mode as the ratio of traffic in passenger kilometre or tonne-kilometre to traffic in vehicle-kilometre. In the case of trucks, thus, load factors represent an average over all sizes of trucks, from 3.5T to over 40T, which corresponds to an average capacity use of 40% to 50% in each category. TABLE 10: AVERAGE LOAD FACTORS, SPAIN Average load factors (in passenger or tonne per vehicle) Region Mode Spain Buses & coaches Spain Cars Spain Train & metro Spain Trucks (T/veh.) Spain Trains, freight (T/veh.) Spain Waterways (T/veh.) Madrid Buses & coaches Madrid Cars Madrid Train & metro Historical load factors were directly computed from the data obtained from the Ministerio de Fomento. Load factors were assumed to be constant after There is a small variation in passenger train load factors. For freight trains and barges, we used constant load factors of, respectively, tonnes/vehicle and 350 tonnes/vehicle. The data on freight train load factors comes from the Belgian Rail Road Company (NMBS/SNCB), Statistisch Jaarboek 1990, since no Spanish data was available. The data on load factors of barges comes from the Belgian Statistical Institute (NIS/INS), Binnenscheepvaart Load factors for passenger cars and public transport are also differentiated between peak and off-peak. As no information was available on this split, we assumed that the ratio of peak load factor to total load factor was the same in Spain as in Great Britain. Off-peak load factors were then computed as the residual. 8 European Commission, Standard & Poor s DRI KULeuven, August 1999

11 4. Costs and prices The cost and price data included in the road-transport base case are used to calculate generalised prices (and changes thereof) for each transport mode. The generalised price is calculated per transport mode as the sum of three elements, i.e. resource costs (including vehicle purchase, maintenance, insurance and fuel cost, excluding taxes), taxes or subsidies, and travel time costs (including waiting and walking time for public transport). The latter is discussed in Part II of the AOPII cost-effectiveness study report. Cost and price data used in the base case scenario are expressed in constant 1998 ECU 2. Prices are stable over the forecast horizon following the assumption that most prices would grow at the same pace as inflation after Selected data and assumptions are presented below. A number of cost components are used to compute the life time driving cost which is an important parameter used in the integrated policy simulation model. Lifetime driving costs are computed as the sum of all costs incurred annually in the exercise of driving, plus an annuity of the purchase cost. The annual driving cost per vehicle consists of the fuel cost, the car insurance, the circulation tax and the repair and maintenance costs. Table 11 provides an illustration of the vehicle purchase cost components contained in the base case for the year Vehicle prices were computed for a reference year on a sample of vehicles in each category, and then converted in constant 1998 ECU. Vehicle prices are catalogue prices, and exclude any discount. As we have assumed that vehicle prices change at the same pace as inflation, the real price of vehicles is constant (except in the early nineties, following a change in VAT and in registration tax). The purchase price of a medium diesel car is lower than the price of a gasoline medium car. Although this seems to be counter-intuitive, this is explained by the fact that we consider car categories based on a fixed engine capacity (for example between 1.4 and 2.0 litres) following the COPERT II methodology. Indeed, for equal cylinder capacities, diesel cars are less expensive than gasoline cars (contrary to the results you would obtain when comparing diesel cars to gasoline cars with a lower cylinder capacity in order to have similar functionality, for example a gasoline engine of 1400cc compared to a 1600 or 1700cc diesel engine). 2 See footnote on the euro at the beginning of this chapter. European Commission --Standard & Poor s DRI KULeuven, August

12 TABLE 11: AVERAGE VEHICLE PURCHASE COST COMPONENTS, 1996 (98 ) Vehicle Categories Average purchase price, excl. taxes Average sales tax (VAT) Average registration tax Average purchase price, incl. taxes Small gasoline car, <1400cc Medium gasoline car, 1400cc-2000cc Large gasoline car, >2000cc Medium diesel car, <2000cc Large diesel car, >2000cc LPG car LDV gasoline LDV diesel HDV gasoline HDV diesel, 3.5T-7.5T HDV diesel, 7.5T -16T HDV diesel, 16T-32T HDV diesel, >32T Moto, two strokes, <50cc Moto, two strokes, <50cc Moto, four strokes, 50cc-250cc Moto, four strokes, 250cc -750cc Moto, four strokes, >750cc Tax data and forecast assumptions were obtained from the AOPII Working Group on Fiscal Instruments (WG6) chaired by DGXXI and from the DRI Automotive group. Following advice from WG6, we have generally assumed that the tax rate (expressed in ECU) grows at the same pace as inflation in the base case. When expressed in constant 1998 ECU, effective tax rates are thus constant over the forecast period. Table 12 provides an illustration for the year of 1996 of other annual driving costs contained in the base case. As discussed, these include the fuel cost, the car insurance, the circulation tax and the repair and maintenance costs. The fuel cost is not shown here. It is calculated as a function of the fuel price (discussed below) and the fuel consumption (discussed in detail in Part II of the Costeffectiveness study report). 10 European Commission, Standard & Poor s DRI KULeuven, August 1999

13 TABLE 12: AVERAGE ANNUAL DRIVING COSTS (EXCL. FUEL), 1996 (98 ) Average annual Average annual insurance Average annual maintenance Vehicle Categories costs circulation tax cost Small gasoline car, <1400cc Medium gasoline car, 1400cc-2000cc Large gasoline car, >2000cc Medium diesel car, <2000cc Large diesel car, >2000cc LPG car LDV gasoline LDV diesel HDV gasoline HDV diesel, 3.5T-7.5T HDV diesel, 7.5T -16T HDV diesel, 16T-32T HDV diesel, >32T Moto, two strokes, <50cc Moto, two strokes, <50cc Moto, four strokes, 50cc-250cc Moto, four strokes, 250cc -750cc Moto, four strokes, >750cc Insurance costs for cars were estimated from surveys published by BEUC (1997). On average, they represent 4.4% of the purchase value of the car. For motorcycles, we have assumed that insurance costs represent 6% of the purchase value in real terms, and for trucks 1.5%. Maintenance costs are a function of the vehicle age (Table 11 shows average values by way of illustration). Table 13 provides an illustration of the fuel price components for the year Fuel prices from 1990 through 1997 were obtained from the Commission s Energy Directorate. We assumed that future fuel prices increase at the same pace as inflation. LPG prices were estimated on the basis of European fuel price & tax survey, from ENGVA. TABLE 13: AVERAGE FUEL PRICE COMPONENTS, 1996 (98 ) Fuel Type Average purchase price per litre, excl. taxes Average tax per litre Average purchase price per litre, incl. taxes Gasoline, leaded 0,235 0,523 0,758 Gasoline, Euro-super 98 0,235 0,483 0,718 Diesel 0,223 0,359 0,582 LPG 0,199 0,224 0,423 Table 14 shows the lifetime driving costs per vehicle which are computed as the sum of all costs incurred annually in the exercise of driving, plus an annuity of the purchase cost. Table 15 shows the average annual compound growth rate of the lifetime driving costs computed in the base case. The annual driving cost per vehicle consists of the fuel cost, the car insurance, the circulation tax and the repair and maintenance costs. The purchase cost is European Commission --Standard & Poor s DRI KULeuven, August

14 converted to annualised values by computing the equivalent annuities over the lifetime of the vehicle. In 1995, for example, the average lifetime of cars was about 14 years in Spain. TABLE 14: THE LIFETIME DRIVING COSTS BY VEHICLE CATEGORY (98 ECU/VKM) Lifetime annual driving cost, 98 ECU / vkm Region Mode Spain Small gasoline car Spain Medium gasoline car Spain Large gasoline car Spain Medium diesel car Spain Large diesel car Spain LPG cars Spain LCV, gasoline Spain LCV, diesel D Spain HDV, gasoline Spain HDV, T Spain HDV, T Spain HDV, 16-32T Spain HDV, >32T Spain Mopeds & motos, <50cc Spain Motos, 2 str., > 50cc Spain Motos, 4 str., cc Spain Motos, 4 str., cc Spain Motos, 4 str., >750cc TABLE 15: GROWTH RATE OF THE LIFETIME DRIVING COST FOR SPAIN Lifetime annual driving cost, annual compound growth rate Region Mode Spain Small gasoline car -3.4% -0.2% -0.3% -0.5% -0.5% -0.2% Spain Medium gasoline car -1.5% 0.3% 0.0% -0.2% -0.4% -0.3% Spain Large gasoline car -1.3% 0.4% -0.1% -0.4% -0.4% -0.2% Spain Medium diesel car -2.4% 0.2% -0.2% -0.4% -0.2% -0.1% Spain Large diesel car -2.2% 0.3% -0.1% -0.2% -0.2% -0.1% Spain LPG cars Spain LCV, gasoline 0.9% -0.3% -0.1% -0.4% -0.3% -0.2% Spain LCV, diesel D 0.6% 0.2% 0.0% -0.1% -0.2% -0.1% Spain HDV, gasoline Spain HDV, T -1.8% -2.3% 0.0% -0.1% -0.1% -0.1% Spain HDV, T -1.5% -0.7% -0.1% -0.3% -0.3% -0.3% Spain HDV, 16-32T -1.2% 0.4% -0.2% -0.3% -0.4% -0.5% Spain HDV, >32T -1.1% 0.3% -0.2% -0.4% -0.5% -0.5% Spain Mopeds & motos, <50cc 0.0% 0.6% -1.2% -1.3% -1.0% 0.0% Spain Motos, 2 str., > 50cc Spain Motos, 4 str., cc -0.3% 2.4% 0.0% -0.2% -0.5% -0.2% Spain Motos, 4 str., cc -0.2% 2.0% -0.3% -0.5% -0.3% -0.2% Spain Motos, 4 str., >750cc -0.5% 2.0% -0.5% -0.4% -0.3% -0.2% 5. Motor vehicle stock Historical stock data for motor vehicles were obtained from Standard & Poor s DRI Automotive Group which regularly collects stock data from national sources across Europe, as well as from other sources, such as industry associations. In the case of Spain, we kept the age profile of the DRI data, but used total figures published by the Ministerio de Fomento. 12 European Commission, Standard & Poor s DRI KULeuven, August 1999

15 The forecast of vehicle stocks described here were computed using the transport model TREMOVE. 3 The major assumption is that future market shares of the various sub-categories only depend on changes in the relative driving cost (thus including the cost of fuel). Details on the methodology and assumptions used in TREMOVE are provided in Part II of the AOPII Costeffectiveness study. Total vehicle stocks for Spain are shown in Table 16. Spain has a medium penetration level of diesel cars amounting to 17.5% of the car stock in 1995, remaining stable over the forecast (compared to 15% in Europe on average in 1995 and up to 18% in 2005). There are few LPG cars in Spain. TABLE 16: VEHICLE STOCKS IN SPAIN Vehicle stock (thousands) Region Mode Spain Buses & coaches Spain Cars, gasoline 10,037 9,851 10,635 12,036 13,559 14,937 16,199 Spain Cars, diesel 2,119 2,092 1,976 2,419 2,695 2,830 2,971 Spain Cars, LPG Spain LGV 1,420 1,979 2,441 2,697 2,974 3,235 3,497 Spain HGV Spain Motorcycles ,044 1,095 The average age structure of the 1995 passenger car stock is shown in Chart 4. The age structure for commercial vehicles is shown in Chart 5. The sales peak during the economic boom of the late eighties is clearly depicted in the charts, with a peak in the age distribution of cars for 6 years old vehicles. The economic slow-down of the early nineties led to lower car sales. This is reflected in the relatively lower number of younger vehicles. The large number of cars in the eldest generation is due to the fact that this category accounts for all vehicles of that age and older. The large number of cars in the category of fifteen year old cars is due to the fact that this category accounts for all vehicles of that age and older. 3 The forecast presented here has been prepared by Standard & Poor s DRI and KU Leuven with assumptions (such as the macroeconomic scenarios) and models specific to the Auto-Oil II programme, with the aim of preparing a reference scenario (thus excluding developments likely to occur after 2000) for the programme. Therefore, they differ from the forecasts published by the Standard & Poor s DRI Automotive Group. European Commission --Standard & Poor s DRI KULeuven, August

16 CHART 3: AGE STRUCTURE OF THE CAR STOCK FOR SPAIN, ,600,000 1,400,000 1,200,000 1,000, , , , , Age of the vehicle, in years Note: The number of vehicles in the rightmost column represents all vehicles registered 16 years ago and before. CHART 4: AGE STRUCTURE OF THE TRUCK STOCK FOR SPAIN, ,000 50,000 40,000 30,000 20,000 10, Age of the vehicle, in years Note: The number of vehicles in the rightmost column represents all vehicles registered 15 years ago and before. Finally, Table 17 shows the evolution of the average age of the vehicle stock in each category. For the purpose of constructing these data, all vehicles older than 15 years have been included in the 15 years old category as only 16 generations are included in the TREMOVE data base. This assumption introduces a small underestimation of the average age of the vehicle stock. 14 European Commission, Standard & Poor s DRI KULeuven, August 1999

17 TABLE 17: AVERAGE VEHICLE AGE FOR SPAIN Average age of vehicles, Spain Vehicle category Small gasoline car Medium gasoline car Large gasoline car Medium diesel car Large diesel car LPG car LCV, gasoline LCV, diesel D HDV, gasoline HDV, T HDV, T HDV, 16-32T HDV, >32T Buses & coaches Mopeds & motos, <50cc Motos, 2 str., > 50cc Motos, 4 str., cc Motos, 4 str., cc Motos, 4 str., >750cc Fuels Fuel consumption is calculated as a function of the vehicle stock and usage following a bottom-up approach as explained in the next Chapter and in Part II of the AOPII cost-effectiveness analysis. Chart 5 shows the general trend in the average fuel consumption profiles for Spain as computed in the base case. 4 4 Fuel consumption data computed in the base case have been subject to limited validation against reported fuel sales by category. Depending on the source and the level of detail available, historical figures showed differences sometimes up to 20%. Following discussions with experts, these differences remained within an acceptable range of uncertainties. Given that the purpose of the exercise is to simulate differences against a predefined base case, further improvements would increase the overall robustness of the base case but not significantly affect the conclusions drawn from scenarios. European Commission --Standard & Poor s DRI KULeuven, August

18 CHART 5: FUEL CONSUMPTION PROFILES FOR SPAIN Diesel Gasoline LPG Table 18 shows the assumptions related to fuel specifications used to construct the AOPII base case scenario for Spain. Following guidance from the AOPII Fuel Quality Working Group (WG3), fuel quality parameters have been assumed equal across all countries considered, except for Finland, which is has a longer tradition with clean fuels. The starting point is the average fuel quality assumed during the first Auto-Oil Programme. Next, estimated market averages rather than minimum specifications were used as proposed by the Fuels Quality Working Group. 16 European Commission, Standard & Poor s DRI KULeuven, August 1999

19 TABLE 18: AUTO-OIL II BASE CASE FUEL SPECIFICATIONS SPAIN Parameter Unit 1996 market AOP 1 Base average ( regulatory ( ) 1999) specification 2000 average market quality ( ) 2005 regulatory specification 2005 average market quality ( ) Gasoline RVP w Kpa RVP s Kpa Trace Lead g/l 0,005 0,005 0,005 0,003 0,005 0,003 E100 % E150 % Aromatics %vol Sulphur ppm Oxigenates %O2 0,6 0,4 2,7 1 2,7 1,5 Olefins %vol Benzene %vol 2,3 2,1 1 0,8 1 0,8 Diesel - Light Duty Density at 15 kg/m Sulphur ppm PCA %vol Distillation range (T95) C Cetane number Diesel - Heavy Duty Density at 15 kg/m Sulphur ppm PCA %vol Distillation range (T95) C Cetane number Source: Gasoline 1996 data from CONCAWE report 5/98, Diesel Data from Paramins winter survey Future data from DG XVII. 7. Emissions from road traffic The computations of emissions are based on the FOREMOVE and COPERT II methodology, as modified, to account for changes in regulated emission limit values and trends in technology. The modifications were discussed and implemented in close co-operation with experts from the AOPII Vehicle Technology and Fuel Quality Working Groups. They include: modified vehicle hot emission factors for Euro II, III and IV vehicles; modified parameters for computing cold start and evaporative emissions; the incorporation of the so-called EPEFE equations to account for changes in fuel specifications. Hence, the AOPII transport base case includes emission factors for current and near future technologies up to 2005/Euro IV (2008/Euro V for trucks). While no further improvements of emission factors for new vehicles are assumed beyond 2005/2008, total emissions will still reduce beyond that date older, more polluting vehicles will be replaced by new cleaner vehicles. The correspondence between technology standards and the vehicle stock, i.e. the first registration year of a new technology vintage, is determined by a vehicle technology matrix. This matrix has been prepared based on information from COPERT II and MEET,deliverable 21. In addition, a number of other parameters required to implement the emission calculation methodology, were taken directly from FOREMOVE scenarios carried-out in the context of AOP I. European Commission --Standard & Poor s DRI KULeuven, August

20 Examples include, average trip length, monthly minimum and maximum temperatures, and Reid vapour pressure. These parameters are constant over the years and are listed in the detailed base case data spreadsheet. Also, the COPERT II methodology did not account for improvements in the fuel efficiency of the vehicles beyond the EURO I vintage, entering the market in the mid-nineties. On the other hand, the pre-kyoto scenario, for example, assumes that fuel efficiency will improve at an annual rate of about 0.9% per year, due to changes in the vehicle stock, in the transport system, (both taken into account in this scenario), and due to technological improvement (not accounted for here). In this base case scenario, following discussions with ACEA and WG7 members, we have assumed that new cars would see improvements of fuel efficiency of 1.3% per year until 2003, 3.5% per year between 2003 and 2008, and 1% per year thereafter. For LDV s, we have assumed that annual gains in fuel efficiency would reach half of those for the passenger cars. For HDV s and trucks, we have assumed that gains in fuel efficiency would amount to 1% per year until 2008, and 0.5% per year thereafter. A detailed discussion of these improvements is provided in Part II of the AOPII Cost-effectiveness study report describing the TREMOVE model. Figure 1 shows the estimated average trends from 1990 through 2020 for selected emissions included in the transport base case as compared to their levels in Related details are shown in the tables and charts that follow. FIGURE 1: ROAD TRANSPORT EMISSION INDICES FOR SPAIN (1995=100) 160% 140% 120% 100% 80% 60% 40% 20% 0% CO NOX VOC Benzene PM-diesel CO2 SO2 The prime focus of the Auto-Oil II Programme is on emissions of carbon monoxide (CO), nitrogen oxides (NOx), diesel particulates (PM10), and volatile organic compounds (VOC). As can be seen from Figure 1, most of these emissions are expected to fall to around 25 percent of the 1995 levels by 18 European Commission, Standard & Poor s DRI KULeuven, August 1999

21 2020 reflecting anticipated emission improvements for new vehicles by about as 75% between the mid-nineties and This is reflected in the progressive decline of average emission factors shown in Appendix 2 (computed ex-post as total emission divided by total mileage). As a result, and despite the continuing growth of traffic demand (at about 2% p.a.), the relative contribution of emissions from road transport will decline significantly between now and As illustrated in Appendix 3, these improvements can be mainly attributed to the significant tightening of environmental limit values for vehicles and fuels during the last decade, including the impact of the so-called AOP I Directives adopted in the fall of 1998 following the outcome of the first European Auto-Oil Programme. Tables 19 shows the data for main pollutants discussed above and shown in Figure 1. 5 TABLE 19: ROAD TRANSPORT EMISSION INDICES FOR SPAIN (PART A) Spain '000 T Index, 1995 = 100% CO % 78% 54% 39% 29% 25% NOX % 82% 61% 40% 30% 26% VOC % 72% 45% 25% 20% 20% NMVOC % 72% 45% 25% 20% 19% Benzene % 54% 32% 19% 15% 14% PM-diesel % 78% 55% 31% 20% 16% In addition to the emissions at the core of the AOP II described above, Table 20 describes future trends of other road transport emissions. Although not at the core of the analysis, it was agreed to calculate emissions of carbon dioxide (CO 2 ), and sulphur dioxide (SO 2 ) to ensure consistency with related environmental programmes (e.g. climate and ozone and acidification strategies) whenever abatement measures affecting several pollutants (in opposite directions) are assessed. TABLE 20: ROAD TRANSPORT EMISSION INDICES FOR SPAIN (PART B) Spain '000 T Index, 1995 = 100% CO % 112% 124% 131% 137% 143% FC % 112% 124% 131% 137% 143% SO % 65% 13% 14% 15% 15% Contrary to the emission profiles of the core pollutants analysed in AOP II, average CO 2 emissions from road transport are expected to continue to increase 5 These tables allow us to link the transport base case emission results, described in this report, with the emission totals and trends for road-transport included in the overall base case for all sectors and described in a separate volume released by WG1. European Commission --Standard & Poor s DRI KULeuven, August

22 to about 140 percent compared to their 1995 levels by This trend closely follows expected average fuel consumption (FC). Because the transport base case also account for the voluntary agreement to reduce CO 2 emissions from cars agreed by the European automobile manufacturers (ACEA), estimates of trends in CO 2 emissions are often lower then what is concluded from similar studies to date. Finally, towards the end of the base case preparation, additional emission estimates for other greenhouse gas and PM emissions were computed to provide additional linking with other analytical programmes. Table 21 shows estimates for methane (CH 4 ) and PM emissions from gasoline vehicles and non-exhaust emissions (e.g. tyre wear and brakes). These estimates are purely indicative and need to be treated with extreme care at this stage as very little is known about their formation, characteristics, and about the impact of recent and near future technology on these emission levels. Indeed, emission factors used for these estimates have received only very limited attention, both the cost-effectiveness analysis and the vehicle and fuel experts, participating in AOP II. TABLE 21: ROAD TRANSPORT EMISSIONS INDICES FOR SPAIN (PART C) Spain '000 T Index, 1995 = 100% CH % 74% 52% 32% 30% 30% PM-gasoline 6 100% 55% 54% 57% 62% 67% PM -non-exhaust 3 100% 120% 139% 157% 173% 188% Total emission levels at five-year intervals are summarised per pollutant in Table 22. Again, the levels for the pollutants indicated in italics are more uncertain then the others as explained above. Table 23 and Charts 6 through 12 show the contribution of the main vehicle categories for each pollutant. Finally, Table 24 provides a further breakdown of passenger car emissions by fuel class. TABLE 22: TOTAL EMISSION LEVELS FOR SPAIN (TONNES) CO NOX VOC NMVOC Benzene PM-diesel CO2 ('000 T) SO CH PM-gasoline PM -non-exhaust European Commission, Standard & Poor s DRI KULeuven, August 1999

23 TABLE 23: EMISSIONS BY VEHICLE CATEGORY FOR SPAIN (TONNES) Emissions by vehicle category, tonnes Region Mode CO emissions Spain Cars Spain LCV Spain HDV Spain Buses Spain Motos Spain Total NOx emissions Spain Cars Spain LCV Spain HDV Spain Buses Spain Motos Spain Total PM emissions Spain Cars Spain LCV Spain HDV Spain Buses Spain Motos Spain Total Benzene emissions Spain Cars Spain LCV Spain HDV Spain Buses Spain Motos Spain Total VOC emissions Spain Cars Spain LCV Spain HDV Spain Buses Spain Motos Spain Total NMVOC emissions Spain Cars Spain LCV Spain HDV Spain Buses Spain Motos Spain Total SO2 emissions Spain Cars Spain LCV Spain HDV Spain Buses Spain Motos Spain Total CO2 emissions (thousand tonnes) Spain Cars Spain LCV Spain HDV Spain Buses Spain Motos Spain Total European Commission --Standard & Poor s DRI KULeuven, August

24 CHART 6: TOTAL CO EMISSIONS BY VEHICLE CATEGORY FOR SPAIN (TONNES) 3,000,000 2,500,000 2,000,000 1,500,000 1,000,000 Motos Buses HDV LCV Cars 500, Motos 139, ,821 95,066 71,476 61,217 49,289 51,390 Buses 7,600 11,201 10,254 9,760 7,744 7,643 8,470 HDV 120, , , , , , ,646 LCV 163, , ,055 52,953 23,937 10,600 8,720 Cars 1,999,690 1,633,423 1,297, , , , ,727 CHART 7: TOTAL NOX EMISSIONS BY VEHICLE CATEGORY FOR SPAIN (TONNES) 600, , , , ,000 Motos Buses HDV LCV Cars 100, Motos Buses 27,813 41,642 34,833 31,124 21,816 17,552 16,030 HDV 202, , , , ,325 99,525 87,875 LCV 19,288 23,500 17,418 11,633 6,956 4,169 3,756 Cars 300, , , ,106 66,905 44,232 36, European Commission, Standard & Poor s DRI KULeuven, August 1999

25 CHART 8: TOTAL VOC EMISSIONS BY VEHICLE CATEGORY FOR SPAIN (TONNES) 600, , , , ,000 Motos Buses HDV LCV Cars 100, Motos 58,778 63,583 44,230 36,842 34,063 30,328 31,883 Buses 2,504 3,988 4,082 4,097 3,483 3,442 2,623 HDV 35,742 41,720 45,241 42,761 37,155 36,527 37,678 LCV 27,613 30,860 18,758 9,520 4,771 2,730 2,689 Cars 364, , , ,460 34,219 19,667 13,594 CHART 9: TOTAL BENZENE EMISSIONS BY VEHICLE CATEGORY FOR SPAIN (TONNES) 20,000 18,000 16,000 14,000 12,000 10,000 8,000 6,000 Motos Buses HDV LCV Cars 4,000 2, Motos 2,440 2,639 1,498 1,155 1, Buses HDV LCV 983 1, Cars 13,025 11,229 5,600 2,854 1, European Commission --Standard & Poor s DRI KULeuven, August