Supporting information to. Specific climate impact of. passenger and freight transport

Transcription

1 1 2 3 Supporting information to Specific climate impact of passenger and freight transport 4 Jens Borken-Kleefeld* 1,2, Terje Berntsen 3, Jan Fuglestvedt : IIASA International Institute for Applied Systems Analysis, Schlossplatz 1, 2361 Laxenburg/Austria 7 8 2: formerly: DLR Deutsches Zentrum für Luft- und Raumfahrt e.v. in der Helmholtz-Gesellschaft, Transportation Studies, Rutherfordstr. 2, Berlin/Germany : CICERO Center for International Climate and Environmental Research Oslo, P.O. Box 1129 Blindern, N-0318 Oslo, Norway * Corresponding author: IIASA International Institute for Applied Systems Analysis, Schlossplatz 1, 2361 Laxenburg/Austria. Phone: ++43 (2236) ; fax: ++43 (2236) ; Borken@iiasa.ac.at 15 S1

2 16 SUPPORTING INFORMATION pages containing 2 figures and 12 tables This Supporting Information presents the results of the same calculations for the integrated radiative forcing (irf) as climate metric and for passenger travel time and volume-kilometers as alternative transport measures. Furthermore, a sensitivity on lower road transport emissions is presented there. Finally, the SI contain details on the modeling of the global transport emissions, the impact calculations and on uncertainties. 23 S2

3 GLOBAL CLIMATE IMAPCT FACTORS BY TRANSPORT MODE Fuglestvedt et al. [1] and Berntsen & Fuglestvedt [2] established factors for the integrated radiative forcing (irf) and the mean temperature change (dt) for each compound and each transport mode separately. However the global transport emissions data used for the year 2000 were slightly different. Therefore, each irf and dt factor was scaled with the ratio of the updated emission over old emission, per compound and mode. The effect of changes in emissions of NO x, VOC and CO on ozone formation and the resulting methane lifetime change has been accounted for according to [3] (p.269). This emissions update affects notably road and rail transport: The irf and dt-factors for reduced methane lifetime (subsequent to an increased OH-production) increase by a factor of 3.5, while the factors for OC, direct and indirect SO 2, and BC decrease by 75%, 50% and 25% respectively. The irf and dt factor was then assigned to passenger and freight transport according to the share of passenger and freight transport respectively in total emissions of that compound, as given in SI Table 7. The resulting irf and dt factors are presented in SI Table 1 and SI Table The integrated radiative forcing (irf) is embodied in the Global Warming Potential (GWP) used for comparing long-lived greenhouse gases under the Kyoto-Protocol. All forcings from the year of the emission up to a chosen time horizon are integrated. Equal weight is put on all times between the emission and the time horizon. Here the same time horizons of 20 years, 100 years and 500 years as in the IPCC assessments are used for the irf values. The global mean temperature change (dt) in a chosen target year after the emission is a function of the history of radiative forcings, with less contributions from early and larger contributions from later forcings. This can be represented as an integration of radiative forcing with decreasing weight on forcings with increasing distance back in time [4]. 45 S3

4 SI Table 1: Integrated radiative forcing (irf) of global y2000 emissions from passenger and freight transport modes by compound for various times H after the emission. H = 20 years mw/m 2 x yr CO 2 Ozone CH 4 - lifetime SO 4 dir. SO 4 ind. BC OC CH 4 N 2 O H 2 O Contrails Cirrus net Road F Ship F Aviation F Rail diesel F Rail EL F Road P Ship P Aviation P Rail diesel P Rail EL P Transport F Transport P Transport Sum H = 100 years mw/m 2 x yr CO 2 Ozone CH 4 - lifetime SO 4 dir. SO 4 ind. BC OC CH 4 N 2 O H 2 O Contrails Cirrus net Road F Ship F Aviation F Rail diesel F Rail EL F Road P Ship P Aviation P Rail diesel P Rail EL P Transport F Transport P Transport Sum S4

5 H = 500 years mw/m 2 x yr CO 2 Ozone CH 4 - lifetime SO 4 dir. SO 4 ind. BC OC CH 4 N 2 O H 2 O Contrails Cirrus net Road F Ship F Aviation F Rail diesel F Rail EL F Road P Ship P Aviation P Rail diesel P Rail EL P Transport F Transport P Transport Sum SI Table 2: Mean temperature change of global y2000 emissions from passenger and freight transport modes by compound for various times H after the emission. H = 5 y mk CO 2 Ozone a CH 4 SO 4 dir.+indir BC OC H 2 O Contrails Cirrus net Road F Ship F Aviation F Rail diesel F Rail EL F Road P Ship P Aviation P Rail diesel P Rail EL P Transport F Transport P Transport Sum S5

6 H = 20 y mk CO 2 Ozone a CH 4 SO 4 dir.+indir BC OC H 2 O Contrails Cirrus net Road F Ship F Aviation F Rail diesel F Rail EL F Road P Ship P Aviation P Rail diesel P Rail EL P Transport F Transport P Transport Sum H = 50 y mk CO 2 Ozone a CH 4 SO 4 dir.+indir BC OC H 2 O Contrails Cirrus net Road F Ship F Aviation F Rail diesel F Rail EL F Road P Ship P Aviation P Rail diesel P Rail EL P Transport F Transport P Transport Sum a: Combined dt from emission of CH 4 and reduced lifetime for CH 4 following increased OH production. S6

7 COMPARING THE SPECIFIC CLIMATE IMPACT BY TRANSPORT MODE ALTERNATIVE DENOMINATORS Distance travelled is not the only aspect of passenger travel; travel time is equally important. Indeed, people seem to have a travel time budget of little more than one hour per day on annual average [5, 6]. The time available for an activity appears as primary constraint and the location for this activity is chosen according to the available means of transport. Their average travel speed then determines the range of activities available (cf. SI Table 4), along with the available budget and the travel costs. The speed differences result in very different distances traveled and hence different climate impacts per trip. This is obviously most pronounced for aviation: In the same time, an air trip covers five to ten times the distance of road or rail travel. Hence, the climate impact per passenger hour traveled rises strongly from rail over road to air travel (SI Figure 1a). Road travel has about three times larger climate impact than rail per passenger-hour. As their travel speeds are similar, the impact ratio between road and rail is approximately the same as per passenger-kilometer. Aviation s impact per passenger-hour is about 8 times higher than road transport s hourly impact when concerned with warming after decades. The climate impact increases to 40 to 50 times road s hourly impact in the first years after the trip (and thus it is out of scale in the figure). The specific impact from cars of about 2 to 4 times higher than the impact from two-wheelers because of their higher travel speed. Moved mass between two places might be an adequate measure for products like ore, steel, grain, coal, oil, gravel, sand, etc. These bulk goods dominate the global transport balance in terms of ton-kilometers. Therefore, choosing mass in the denominator results in lower specific climate impacts for the bulk carriers ship and rail. However, air cargo for example is made to weigh as little as possible, and a metric like climate impact per ton-kilometer leads to a higher impact value for this mode. Volume requirements determine in many cases the vehicle size and the number of trips, and hence the total vehicle-kilometers required for the transport. This volume limitation is dominant notably for container transport, but also for refined, finished or semi-finished products like machinery, vehicles, pharmaceuticals, etc. Therefore, the climate impact per volume of cargo and transport distance is used S7

8 here as an alternative measure (SI Figure 1b). One volume of cargo has least climate impact on ship transport, rising over rail and road transport to air transport. Thus, the relative order between the modes stays the same on global average but differences become less pronounced: In the long run, the climate impact of shipping and rail transport is 6 and 2 times, respectively, lower than road transport, while air cargo s impact is up to 3 times higher. Aviation s impact per volume-km rises strongly to a factor 14 and more when concerned with warming in the first years after the emission, due to the high contribution from short-lived compounds. a) Temperature increase per passenger-hour b) Temperature increase per volume-kilometer K per p-hr Car Bus 2Wheel Aviation Rail K per m 3 -km LDT HDT Ship Aviation Rail y 20 y 50 y 5 y 20 y 50 y SI Figure 1: Temperature increase per transport work and mode for various time horizons. Global average values for the year a) Impact per passenger and travel hour. b) Impact per volume and distance transported. Bars represent 1 SD. S8

9 SENSITIVITY OF CLIMATE IMPACT TO LOWER ROAD VEHICLE EMISSIONS For road vehicles a number of important regulations and technical measures that have been implemented since the year 2000 in order to control vehicle exhaust emissions in most regions of the world [7, 8]. Further measures are scheduled for implementation in the next couple of years. These measures will take effect in the fleet much quicker than for the other modes, as fleet renewal is much faster. For this sensitivity we assume that emissions of NO x and particulate matter, including black carbon (BC), as well as hydrocarbons and CO are reduced by 75% per kilometer. Furthermore, measures are being implemented for both to increase the fuel efficiency of the vehicles and to reduce the carboncontents of the fuels, both aimed at lower CO 2 emissions per kilometer [9]. These two measures combined could result in about 20% reduction of CO 2 emissions per kilometer, assumed for the sensitivity calculation here. In consequence both, the short-term climate impact of road travel would decrease relative to the impact of the other modes (cf. SI Figure 2). However, initial differences are so large anyway, that the qualitative ranking is not affected at all: Aviation has by far the biggest climate impact per passenger- and ton-kilometer, followed by cars and light trucks respectively. Moreover, the short-term impact from motorized two-wheelers has decreased more than for cars: Two-wheelers impact has a higher contribution from air pollutants than cars impact and is hence more sensitive to reductions (see also above). For the long-term impact, the ratio of CO 2 emissions is essential: Car travel has slightly improved down to the level of air travel, while relations for freight transport are only slightly affected. In conclusion, reductions of air pollutant emissions from road vehicles affect the ratio of the shortterm specific climate impact notably between two-wheelers and cars, but the ratio between road in general and the other modes remains rather stable. The long-term climate impact is determined by the CO 2 -intensity of the transport; here air and car travel are at a similar level per passenger-kilometer, but aviation has by aviation has a ten to twenty times higher impact per hour traveled. S9

10 6 5 4 a) Climate impact per passenger-kilometer : Low road emissions, increased efficiency irf dt Car 2Wheel Bus Aviation Rail b) Climate impact per ton-kilometer: Low road emissions, increased efficiency irf dt Light truck Heavy truck Ship Aviation Rail y 100 y 500 y 5 y 20 y 50 y y 100 y 500 y 5 y 20 y 50 y SI Figure 2: Specific climate impact in the sensitivity calculation with -70% NO x, BC, CO and HC emissions and -20% CO 2 emissions for road vehicles. Values given for both metric simultaneously, therefore relative to road transport. a) Passenger transport, b) freight transport. GLOBAL TRANSPORT MODELLING Consistent global emission inventories for each transport modes have been developed within the European research project QUANTIFY ( Emissions have been calculated bottom-up and cross-checked with the total fuel consumed by each mode and with transport statistics [10-12]. Road transport is differentiated by five vehicle categories. Emission factors and transport volume data for the year 2000 have been researched specifically for each of the twelve world regions. For cross-checking the specific fuel consumption per vehicle category is given in SI Table 3. The transport volume for the different road vehicles in the twelve world regions is given in SI Table 4. S10

11 SI Table 3: Fuel consumption factors per vehicle category and region used for the modeling [1] Region Fuel consumption Car Car - LDT LDT - HDT HDT - 2/3W Bus - Gasoline Diesel Gasoline Diesel Gasoline Diesel Gasoline Diesel AFR g/km CEC g/km CIS g/km EAS g/km WEU g/km JPN g/km LAM g/km MEA g/km NAM g/km OCN g/km SAS g/km SEA g/km AFR: Africa; CEC: Central and Eastern Europe; CIS: Commonwealth of Independent States; EAS: East Asia; WEU: Western Europe; JPN: Japan; LAM: Latin America; MEA: Middle East; NAM: North America; OCN: Oceania; SAS: South Asia; SEA: South East Asia SI Table 4: Global road vehicle travel volume, passenger and freight transport volume by vehicle category in year 2000 differentiated by region [1] (in decreasing order). Region 2/3W Car Bus 2/3W Car Bus LDT HDT [10 9 km] [10 9 km] [10 9 km] [10 9 pkm] [10 9 pkm] [10 9 pkm] [10 9 tkm] [10 9 tkm] NAM 18 4,287 a b 1965 EU , EAS LAM SEA CIS SAS JPN AFR MEA CEC OCN World a: Including SUVs, vans and pick-ups. b: LDT are defined as vehicles with gross vehicle weight below 3.5 tons. Therefore negligible transport volume in NAM and total freight transport volume included as HDT. AFR: Africa; CEC: Central and Eastern Europe; CIS: Commonwealth of Independent States; EAS: East Asia; WEU: Western Europe; JPN: Japan; LAM: Latin America; MEA: Middle East; NAM: North America; OCN: Oceania; SAS: South Asia; SEA: South East Asia S11

12 Shipping emissions are modeled bottom-up from the global transport data differentiated for fifteen vessel types [2]. Aviation emissions were likewise calculated bottom-up from the global transport data and emission factors specific to aircraft types [3]. The data is differentiated by vehicles and vessels; this allows to assign emissions to passenger and freight transport separately [10, 11]. Rail fuel consumption and emission factors were taken from [1], but SO 2 emissions updated per region. The respective emissions from electricity generation are assigned to electric trains according to their share in electricity consumption in a region. SI Table 5 summarizes the transport volumes used for the emission inventory, SI Table 6 compares the implied global average fuel efficiencies per mode. SI Table 5: Global passenger and freight transport volume for rail diesel and electric traction by region, for aviation and marine shipping globally in the year Passenger transport Freight transport Rail diesel Rail electric Aviation Rail diesel Rail electric Aviation Shipping 10 9 pkm 10 9 pkm 10 9 pkm 10 9 tkm 10 9 tkm 10 9 tkm 10 9 tkm EAS SAS EU CIS JPN CEC NAM SEA AFR LAM MEA OCN World AFR: Africa; CEC: Central and Eastern Europe; CIS: Commonwealth of Independent States; EAS: East Asia; WEU: Western Europe; JPN: Japan; LAM: Latin America; MEA: Middle East; NAM: North America; OCN: Oceania; SAS: South Asia; SEA: South East Asia S12

13 SI Table 6: Implied average fuel efficiency for global passenger and freight transportation by mode in the year 2000 Fuel efficiency Fuel efficiency goe/pkm goe/tkm Car 51 LDT 230 2/3-Wheeler 21 HDT 56 Bus 18 Ship 4 Aircraft 36 Aircraft 343 Train 13 Train 6 goe: g oil equivalents, i.e. converting the different fuels (gasoline, diesel, kerosine, heavy fuel oil, electricity, etc. ) to a common energy unit. Global emissions data for the year 2000 has been used, as presented in SI Table 7. These annual emissions are further distributed on a 1x1 longitude-latitude grid for each mode. Aviation emissions are furthermore differentiated in the vertical dimension by every 2000 feet. These regionally explicit emissions are input to detailed global climate-chemistry models accounting for transport, chemistry and meteorology around the world. SI Table 7: Global exhaust emissions by transport mode in the year 2000, differentiated by passenger (P) and freight (F) transport [10, 11]. Implied changes in ozone and OH concentrations calculated from emissions of NO x, NMHC and CO using [13] Fuel CO 2 CO NO 2 NMHC SO 2 BC OC CH 4 N 2 O do 3 dlnoh Tgoe 1 Tg Tg Tg Tg Tg Tg Tg Tg Tg DU Road F na Shipping F Aviation F n.a n.a. n.a n.a n.a Rail diesel F Rail EL F Road P na Shipping P Aviation P n.a n.a. n.a n.a n.a Rail diesel P Rail EL P Transport F Transport P Transport Sum : Tgoe: Tg oil equivalents S13

14 TRANSPORT WORK Transport work is usually expressed as the product of passenger numbers or tons of cargo transported times their travel or transport distance, called passenger-kilometers (Pkm) and ton-kilometers (tkm) respectively. Global passenger-kilometers are dominated by road transport (80%), followed by air (14%) and rail (6%) (SI Table 8). Road transport s dominance stems from high passenger car transport volumes in industrialized countries and high bus travel in developing countries [10]. Motorized two- and threewheelers are important means of transport notably in Asia. In view of significant differences in use and emissions as well as its overall importance we differentiate road transport by vehicle type in the following. Though passenger turnover in aviation is significantly lower than e.g. in rail travel, the long travel distances result in relatively high transport work. Rail is important for commute in urban areas, i.e. with a high passenger turnover over shorter distances. Global ton-kilometers are dominated by shipping (76%), followed by road and rail transport (12% each). Aviation accounts for about 0.24% of the total global ton-kilometers, used essentially for highvalue goods. Shipping s dominance reflects the high volumes of heavy goods, notably oil, ores, coal, steel, grain as well as containers shipped over long distances between global economic centers in Europe, Asia and North America and primary material sources [14]. Similarly, rail freight is dominated in terms of mass by bulk and relatively low value products, notably building materials, coal, ores and metal scarps, iron and steel, as well as machinery and (semi-)finished products over distances between 500 km and 1500 km [15, 16]. Global road freight transport runs to about 90% on long-haul heavy duty trucks, the remainder in smaller trucks and delivery vans [10]. S14

15 SI Table 8: Global transport work, average travel speed and density of shipment used in this analysis. Passenger travel Transport work pkm km/h Average travel speed Reference Road (urban) to 100 (highway) Cars: wheel: Bus: This work, based on [10] This work, based on [10] Road [17] Ship na -/- Aviation This work, based on [18] and [19] Rail (rural) (intercity) Diesel (rural) (intercity) Electric (light rail) (intercity) (high-speed) this work this work this work Rail [17], [20] Freight transport Transport work Shipment density Reference (average) tkm Kg/m 3 Road this work, based on [10] HDT: 6.41 LDT: this work, based on [10] [17] Ship this work based on [14] Aviation this work Rail this work Diesel: this work Electric: this work Rail [17], [4] S15

16 ALLOCATION OF PASSENGER AND FREIGHT TRANSPORT BY MODE The inventories are differentiated by vehicle types. Thus the respective fuel consumption, emissions and transport work have been allocated to passenger and freight transport as follows: Road: - Passenger transport: All emissions and travel with motorized two- and three-wheelers, busses and passenger cars, as well as 50% of LDT emissions and travel. Half of global total vehicle mileage by light duty vehicles is in North America [15-17]. Hence, the allocation between passenger and freight travel is essentially only relevant there. - Freight transport: All emissions and transports by heavy trucks and 50% of light trucks [15-17]. Marine shipping: - Passenger transport: All emissions and travel by passenger vessels and 50% of RoRo-Ferries, accounting for 8% and 5%, respectively, of total marine fuel consumption [10, 11]. - Freight: All other vessel types, i.e. bulk, container, oil tankers, general cargo, etc. Aviation: - Passenger transport: All emissions from passenger aircraft. Emissions due to cargo loaded on passenger aircraft are subtracted according to the average share of cargo weight to total payload. - Freight transport: All emissions from cargo planes plus emissions due to cargo loaded on passenger aircraft, calculated according to the average share of cargo weight to total payload (calculated from [18] citing ICAO circular 299-AT/129 from 2002). Rail: Global rail transport is dominated by the big networks in the US, the Former Soviet Union, India, China and Europe, followed by important rail travel in Japan. Networks in the first four regions are predominantly diesel traction, with high shares of freight transport. Rail traction in Europe and in Japan is predominantly electrified, with important shares on high speed trains [15-17]. Electrified commuter S16

17 trains run in all regions. There is no unified statistics on the global shares of passenger and freight transport per traction type. Here we assume: - Passenger transport: Two thirds of trains electricity consumption, notably for commuting and highspeed trains, and one third of trains diesel consumption is used for passenger transport. - Freight transport: Two thirds of trains diesel consumption, notably in the big railway countries US, China, India and Russia, and one third of trains electricity consumption is used for freight transport, notably in Europe. UNCERTAINTIES Uncertainties results from both, the climate impact calculations and the estimated transport work per mode. The modeling uncertainties along the impact pathway from emissions over changes in atmospheric concentration to resulting radiative forcing and a temperature change, i.e. the numerator, have been calculated in [1, 2] and are adopted here (cf. SI Table 5). Uncertainties are lowest in the case of long lived gases and very high in case of short-lived species with high radiative forcing (e.g. cirrus, contrails and indirect effects of SO 2 ). Therefore, the overall uncertainty is the smaller the lower the share of short-lived species is for the total climate impact of a mode. For the same reason the relative uncertainty decreases with time, i.e. when the impact of short-lived species decays. In consequence, the resulting overall uncertainty (1 SD) for the absolute climate impact on the time horizons chosen here is in the order of ±35% in the case of road transport, for which the CO 2 contribution dominates. It can be as high as ±100% on the intermediate time scales in the case of aviation, for which the warming by aviation induced contrails and cirrus clouds are highly uncertain. In the case of shipping the uncertainty for the (cooling) impact of sulfate aerosols is strongly skewed such that the lower margin for the total uncertainty is up to a factor of four lower and the upper margin up to 80% higher than the calculated best value. The transport work, i.e. the denominator of the transport specific climate impact, is uncertain in terms of distance traveled on the one hand and the passenger and freight turnover on the other hand. For both S17

18 exist statistics and, importantly, the activity is constrained by the total fuel consumed for each mode. We calculate a 1SD uncertainty between 15% and 30% for each mode in terms of passenger-kilometer or ton-kilometer (cf. SI Table 9 for details). Thus the combined uncertainty of the transport specific climate impact is essentially determined by the uncertainty in the absolute climate impact, for each mode except for road transport (cf. SI Table 10 for details). The uncertainty is between ±30% and ±44% in the case of road transport and one order of magnitude higher in the case of aviation. The uncertainty for shipping is below ±10% on the long time horizons, but can be up to a factor 2 for the short time temperature change. The uncertainty for rail transport is in between these values. Similar uncertainties apply to our impact estimate per passenger-hour and volume-kilometer, as they are based on the same sources. Notwithstanding these significant uncertainties, the qualitative statements derived above remain robust. Our analysis applies to a global, average comparison between the fleets that are actually dominated by long-distance travel. This first analysis could be taken one step further by looking at the future technical and operational potential of the different modes, the load factor as a function of route, time, product, the differing load factors between modes and to differentiate between regions. UNCERTAINTIES IN irf and dt FACTORS The uncertainty in irf and dt has been calculated by [1, 2] for each mode and for various time horizons. We apply the same relative errors to the scaled impacts from passenger and freight transport (SI Table 9). Our scaling of the impacts factors accounts for the changes in emissions relative to the earlier publications. Furthermore, the emission profiles of road freight and passenger transport vary, i.e. the relative shares of the various pollutants. However, carbon dioxide is the dominant contributor within a decade after the emission; by then the emission and impact profiles of passenger and freight transport become similar and hence have the same relative uncertainty. Only for the shorter-term impacts this uncertainty does not match fully. Here, we ignore this mismatch for simplicity. The calculated total uncertainty (1 SD) for the climate impact for the time horizons chosen here is in the order of ±35% in the case of road transport, for which the CO 2 contribution dominates: It can be as high as ±100% on the S18

19 intermediate time scales in the case of aviation, for which the warming by aviation induced contrails and cirrus clouds and the cooling due to an increased CH 4 destruction are highly uncertain; in the case of shipping the uncertainty for the (cooling) impact of sulphate aerosols is strongly skewed such that the lower margin for the total uncertainty is up to a factor of four lower and the upper margin up to 80% higher than the calculated best value. SI Table 9: Uncertainty estimates (±1 SD) used in this paper for the absolute climate impact irf and dt. 5y 5y 20y 20y 50y 50y irf(+) irf(-) dt(+) dt(-) dt(+) dt(-) dt(+) dt(-) % % % % % % % % Road 17% 17% 38% 32% 38% 25% 35% 22% Ship 51% 75% 44% 381% 40% 131% 77% 107% Air 49% 40% 60% 38% 98% 92% 38% 26% Rail 120% 139% 144% 38% 50% 146% 7% 144% Rail D 148% 184% 46% 71% 197% 195% 51% 40% Rail EL 184% 96% 44% 70% 64% 53% 45% 35% UNCERTAINTIES IN TRANSPORT WORK Road For road transport, our calculated vehicle mileage is calibrated to the total fuel consumed in a country/region with an overall uncertainty of about of ±10% [10]. We estimate the uncertainty in the load factor for each vehicle category based on the travel in each world region as follows (cp. SI Table 10): - In countries with good statistics the uncertainty in occupancy for cars is 5%, for mopeds and motorcycles it is 7% and for buses it is 10%. These values have been used for North America, Western Europe and Central and Eastern Europe. In Japan and Oceania we assumed twice that uncertainty. For the rest of the world, three times that uncertainty was assumed. Accounting for differences in transport volume by region and vehicle type, the overall uncertainty in the occupancy rate is 13%. Combined with the uncertainty in travel distance the total uncertainty for passenger-kilometers amounts to 16% on global average. S19

20 - For road freight transport we assume 20% uncertainty in cargo volume, resulting in a combined 22% uncertainty in total ton-kilometers. Aviation: Global transport volumes for aviation are established by the manufacturers, industry associations or the relevant UN body [21-23]. Aviation transport volume is dominated by long-haul. The travel distance as calculated from movements data differs by about 15% (1σ) from the distance calculated from fuel sold for aviation [19]. The passenger load factor is closely monitored and in theory the check-in of every single passenger is verified several times. We assume a counting (and reporting) error of ±1% (1σ). An estimated half of air cargo is transported on regular passenger planes [18]. This value however depends on the average passenger weight assumed. We estimate an uncertainty of ±10% (1σ). Shipping: Transport work and volume by global shipping are summarized in [14, 24]. They do essentially concur and do not provide an uncertainty estimate. However different bottom-up calculations lead to considerable differences with respect to total fuel consumed and hence about the underlying transport distance [25]. Therefore, we assume an uncertainty of 15% about the transport distance and about 15% about the cargo volume. Rail: For rail, we assume about 14% uncertainty in distance, based on the uncertainty in total fuel consumed. Uncertainty in passenger occupancy is estimated at 28%, uncertainty in cargo loads is estimated at 21%. S20

21 SI Table 10: Road passenger transport by world region in 2000 [10, 11]: Vehicle mileage, average occupancy and estimated uncertainty (top regions cumulating 66% or more of transport volume per vehicle category shaded). MTW Car Bus & MTW Car Bus & MTW Car Bus & coach Total coach coach Region 10^6 vkm 10^6 vkm 10^6 vkm Occupancy Occupancy Occupancy 10^6 pkm 10^6 pkm 10^6 pkm 10^6 pkm NAM 18'171 4'286'786 31' (±7%) 1.63 (±5%) 10 (±10%) 23'077 6'987' '542 7'330'081 EU15 138'560 2'573'522 28' (+7%) 1.55 (±5%) 14.5 (±10%) 138'560 3'988' '095 4'538'614 CEC 30' '308 13' (±7%) 1.7 (±5%) 8.5 (±10%) 45' ' ' '500 JPN 111' '400 7' (±14%) 1.5 (±10%) 20 (±20%) 145' ' '000 1'072'930 OCN 3' '866 3' (±14%) 1.3 (±10%) 12 (±20%) 4' '126 39' '630 CIS 54' '948 31' (±21%) 2.5 (±30%) 20 (±30%) 71' ' '183 1'175'153 EAS 320' '118 40' (±21%) 2.3 (±30%) 30 (±30%) 641' '572 1'203'717 2'514'659 SEA 137'908 96'406 43' (±21%) 2.5 (±30%) 20 (±30%) 275' ' '327 1'377'159 SAS 186'295 50'419 29' (±21%) 2.5 (±30%) 20 (±30%) 372' ' '876 1'091'515 LAM 79' '775 50' (±21%) 2 (±30%) 20 (±30%) 119'417 1'021'549 1'005'575 2'146'542 MEA 44' '577 15' (±21%) 2 (±30%) 20 (±30%) 66' ' ' '034 AFR 16' '167 26' (±21%) 2.5 (±30%) 20 (±30%) 32' ' ' '683 World 1.14E E E [1.38 / 2.02] 1.69 [1.56 / 1.81] 19 [14 / 24] 1.94E+06 (±19%) 1.54E+07 (±7%) 6.16E+06 (±27%) 2.35E+07 (±13%) 21

22 Overall, the following uncertainty values (1 SD) for the transport work by mode are used (SI Table 11) SI Table 11: Uncertainty estimate (±1 SD) for global transport distance, passenger occupancy and cargo load factors, and resulting uncertainty in transport work by mode vkm P-occ ton-load Pkm tkm Road 10% 19% 20% 21% 22% Car 10% 15% 18% Bus 5% 27% 27% MTW 15% 26% 30% Air 15% 1% 3% 15% 15% Ship 15% n.a. 15% n.a. 21% Rail 14% 28% 21% 32% 25% Finally, uncertainties in irf- and dt-factors and in transport work are combined, resulting in overall uncertainties for the transport specific climate impact used in this analysis ( SI Table 12). SI Table 12: Resulting uncertainty (±1 SD) for the transport specific climate impact per passengerkilometer and per ton-kilometer for both metrics, all modes and all time horizons considered. mw/(m² x yr) mw/(m² x yr) mw/(m² x yr) mw/(m² x yr) mw/(m² x yr) mw/(m² x yr) irf (+) irf (-) irf (+) irf (-) irf (+) irf (-) 20 y 20 y 100 y 100 y 500 y 500 y Impact of freight transport modes per ton-km LDT 28% 28% 28% 28% 28% 28% HDT 28% 28% 28% 28% 28% 28% Ship 24% 33% 4% 6% 1% 2% Aviation 1299% 1081% 542% 451% 344% 286% Rail 9% 10% 10% 12% 10% 11% Impact of passenger transport modes per p-km Car 30% 31% 31% 32% 31% 32% Bus 12% 12% 13% 13% 14% 14% 2Wheel 42% 42% 28% 28% 21% 21% Ship na na na na na na Aviation 158% 131% 84% 70% 61% 51% Rail 17% 20% 25% 29% 40% 46% mk mk mk mk mk mk dt (+) dt (-) dt (+) dt (-) dt (+) dt (-) 5 y 5 y 20 y 20 y 50 y 50 y 22

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