Think Global AS, "Well-to-wheel analysis of CO2 emissions in the car usage phase Th!nk City vs. Fossil Fuelled Cars," 2010
1. Well-to-wheel analysis of CO2
emissions in the car usage phase.
Th!nk City vs. Fossil Fuelled Cars
Version 1.1
Think Global AS
Version Changes Author
1.0 First Version Åsgeir Helland
1.1 - Added chapter 4.6 on methodology Åsgeir Helland
- Clarifying electricity loss in chp 2.1
-updated conclusions
2. Table of Content:
1. Introduction..................................................................................................................................... 2
2. Electric Vehicles ............................................................................................................................... 4
2.1 Emission Data Electricity Production (well-to-tank) ............................................................... 4
2.2 Technical Specifications Th!nk City (tank-to-wheel) ............................................................... 5
2.3 Carbon Impact Analysis of Th!nk City (well-to-wheel) ............................................................ 6
3. Fossil fuel based vehicles................................................................................................................. 6
3.1 Driving Cycles .......................................................................................................................... 6
3.1.1 Driving cycles and real use fuel consumption. ................................................................ 7
3.2 CO2 Emissions of fossil fuel ..................................................................................................... 8
3.2.1 CO2 Emission in Fuel production (well-to-tank).................................................................. 8
3.2.2 CO2 Emissions per litre fuel combusted (tank-to-wheel) ................................................... 9
3.2.3 CO2 Emission per litre fuel consumed (well-to-wheel) ....................................................... 9
3.3 Fuel consumption of fossil fuelled based vehicles .................................................................. 9
3.4 Carbon Impact Analysis for fossil fuelled cars (well-to-wheel) ............................................. 11
4. Comparing the usage phase of Th!nk City with fossil fuelled cars ............................................ 12
4.1 Urban Driving ........................................................................................................................ 12
4.2 Mixed Driving ........................................................................................................................ 14
4.3 Scenario 1: Nordic Winter ..................................................................................................... 15
4.4 Scenario 2: Rush hour............................................................................................................ 21
4.5 Comparing electric vehicles with alternative transport solutions – Results of a life cycle
screening ........................................................................................................................................... 23
4.6 Discussion on methodology .................................................................................................. 24
5. Conclusions................................................................................................................................ 25
Bibliography........................................................................................................................................... 26
Annex I: Fuel Conversion Factors .......................................................................................................... 28
Annex II: Nordic Winter – Example of calculation sheet 5 degrees Celsius .......................................... 29
1
3. 1. Introduction
Among the many human activities that produce greenhouse gases the use of energy represents by
far the largest source of emissions. As seen in Figure 1, energy accounts for over 80% of the global
anthropogenic greenhouse gases. Since 1870, the annual CO2 emissions from fuel combustion
dramatically increased from near zero to 27.1 Gt CO2 in 2005 (IEA 2007).
Figure 1: Shares of global anthropogenic greenhouse gas emissions (IEA 2007).
Between 1971 and 2005, the combined share of electricity and heat generation and transport shifted
from one-half to two-thirds of global emissions (Figure 2). In 2005, fossil fuels provided over 70% of
the world electricity and heat generation from which coal supplied 39% of the generation (IEA 2007).
While electricity and heat generation draws from various energy sources, the transport sector relies
almost entirely on oil (95% of the energy used for transport came from oil in 2005). CO2 emissions
from oil consumption in most sectors remained nearly steady in absolute terms since 1971 with the
exception of those of transport which more than doubled. Dominated by road traffic, this end-use
sector is the strongest driver of world dependence on oil.
2
4. Figure 2: World CO2 emissions by sector (IEA 2007).
Fossil fuel combustion is the single largest human influence on climate change. World leaders have
recognized the need to address and reduce CO2 emissions from fuel combustion. The two sectors of
electricity and transport are both growing rapidly while representing the bulk of CO2 emissions from
fuel combustion. Improving the energy efficiency and reducing the carbon intensity of both sectors
could significantly diminish their contribution to global climate change.
In light of the global challenges of increasing demands for energy as well as climate change, there has
been an increasing focus on alternative vehicles such as the electric vehicles. Many sceptics argue
that driving electric vehicles will only move the emissions (including CO2) from the sector of
transport to the sector of electricity generation. Proponents argue that due to winning energy
efficiency of an electric vehicle as compared to an internal combustion engine (as a rule of thumb, an
electrical engine often achieve 85-90% energy conversion efficiency, the combustion engine achieves
about 20-25%), the global CO2 balance will be drastically reduced. The objective of this analysis is to
compare the co2 emissions in the usage phase of the electric vehicle Th!nk City with fossil-fuel based
vehicles using life-cycle inventory data. Such an analysis is also called a well-to-wheel analysis.
3
5. 2. Electric Vehicles
2.1 Emission Data Electricity Production (well-to-tank)
The production of electricity generates different amount of CO2 depending on the fuel. The
electricity in Norway originates mostly from hydropower whereas the German electricity mix has an
overweight of fossil fuel based production. In addition, the emissions per kilowatt hour (kWh) may
vary significantly from one year to the next depending on the generation mix of a given year. For
example, Norway produces on average 99% of its own electricity. However, 2004 was a dry year in
which our production was lower than 2005 and consequently the import had to be increased. The
increasingly harmonized electricity grid makes it easy to import as well as export electricity to follow
the market. In 2004, Norway imported 15334 GWh from other countries (mostly Sweden and
Denmark) whereas it exported 3842 GWh (Statistics Norway 2007). In 2005, Norway was a net
exporter of about 12 GWh. This makes it difficult to assume an average of the electricity generation
mix of a given country to a given year.
Electrical power is always partially lost by transmission. This applies to short distances as well as to
cross country high voltage lines. The major component of power loss is due to ohmic losses in the
conductors and is equal to the product of the resistance of the wire and the square of the current.
Transmitting electricity at high voltage reduces the fraction of energy lost. At the substations,
transformers are again used to step the voltage down to a lower voltage for distribution to
commercial and residential users. This procedure creates further power loss.
Table 1: Country specific CO2 emissions in production of one kWh in 2004
EcoInvent 2.0 IEA (2007)
Country CO2 g/kWh CO2 g/kWh
Norway 31 7
346
Western European Grid 490 (OECD Europe)
Germany 600 436
Switzerland 100 24
NORDEL (Nordic grid) 170
United Kingdom 551 486
US Average 711 575
Denmark 510 308
Netherlands 650 440
France 86 78
Description of databases and differences in methodology:
• The Ecoinvent database v2.0 contains international industrial life cycle inventory data on
energy supply, resource extraction, material supply, chemicals, metals, agriculture, waste
management services, and transport services. The publisher is the Ecoinvent Centre, also
known as the Swiss Centre for Life Cycle Inventories and is recognized as the most
comprehensive and up-to-date database on life cycle inventory today. The database takes
into account the international electricity market and consequently the sources of its imports
(Frischknecht, et al. 2007). The electricity mix is calculated by adding the domestic
4
6. production with import. For Norway, the high import creates a higher environmental load
than it would if Norway would consume all its domestic production of hydropower. For
countries importing hydropower from Norway, its environmental load would be
proportionately lower. As we can see in Table 1, the environmental load for Norway is
therefore 77% higher than the IEA method, which does not take electricity trade into
account, while for France which is a net exporter of electricity the difference is only 9%.
• The International Energy Agency (IEA) publishes yearly reports on CO2 Emissions from Fuel
Combustion (IEA 2007). Each country reports their emissions based on the 1996 IPCC
Guidelines for National Greenhouse Gas Inventories. The IEA uses the default emission
factors which are given in the 1996 IPCC Guidelines. In addition to different sources of
information depending on the country in question, the methodology used by the national
bodies providing the data to the IEA may differ. The emissions are calculated based on
domestic production and do not take the electricity trade into account. For countries like
Switzerland which has a considerable trade activity, this do not necessarily reflect the
national grid and thus the end-users’ electricity mix. Furthermore, life cycle inventory data of
electricity production such as construction or fuel transportation as well as power losses, are
not taken into account, which leads to a consistent underreporting of life cycle emissions of
electricity.
Emission Data used in this report
Table 1 shows partly considerable differences for the two datasets in emissions per kWh produced
due to the significant methodological differences in the calculations (from 9 to 77% difference of IEA
data compared to the EcoInvent 2.0 data). It is therefore not possible to compare these two datasets,
but should give a good picture while comparing different countries within the same dataset. In this
report, the dataset of EcoInvent 2.0 is applied in our calculations as we find it important to reflect on
the full life cycle impacts of our product (Frischknecht, et al. 2007).
2.2 Technical Specifications Th!nk City (tank-to-wheel)
Th!nk City is an electric vehicle powered by batteries from independent battery producers. It has
two seats and an optional choice of two rear children seats and weighs 1113 kg including the battery
pack of about 245-260 kg. Total load capacity is 284 kg. Th!nk City’s key requirements independent of
the battery pack are the following:
• Top speed, continuous 100 kph
• Acceleration 0 - 50 kph 6.5 seconds
• Acceleration 0 - 80 kph 16.0 seconds
• Start from stand still at maximum gradient 30 %
• Hill Climb 5% during 120 seconds 90 kph
• Range official European range test 170 km
The range test is essentially the same as the official European Union drive cycle as defined in EU
Directive 80/1268/EEC (as last amended by 2004/3/EC), but the drive cycle cuts and keeps steady
speed at 100 kph whereas the original drive cycle has a maximum speed of 120 kph. The driving
cycle consists of the urban and the extra-urban cycle. See chapter 3.1 for more information on these
driving cycles. The vehicle requires proportionately more energy delivered from the battery at high
speed compared to low speed such as urban driving due to lower drag (air resistance). Therefore, the
5
7. range of city driving reaches as much as 203 km as compared to 170 km for mixed driving. Table 2
gives an overview of Th!nk City driving efficiency per kilometre.
Table 2: Driving efficiency of Th!nk City
Battery Zebra Zebra
Driving Cycle UDC MUDC
Range per load in km 203 170
Full battery load kWh 28,2 28,2
Charging Loss 10 % 10 %
Total charge full battery 31,02 31,02
Resulting kWh/km 0,153 0,182
2.3 Carbon Impact Analysis of Th!nk City (well-to-wheel)
The CO2 emissions per driven kilometre with the Th!nk City is highly dependent on the electricity mix
of the country in question. As we can see in Table 3, the Th!nk City’s CO2 indirect emissions from the
production of electricity ranges from a 5 g/km in Norway (hydropower) to 119 g/km in the
Netherlands (fossil fuel). For Th!nk City, vehicle manufacture and fuel production emissions account
for all life cycle emissions, the vehicle being zero-emission in operation.
Table 3: CO2 Emissions per kilometre driven for Th!nk City.
Country Electricity Zebra Zebra
production UDC MUDC
g/kWh g/km g/km
Norway 31 5 6
France 86 13 16
Switzerland 100 15 18
Nordic Grid 170 26 31
Western European Grid 490 75 89
Denmark 510 78 93
United Kingdom 551 84 101
Germany 600 92 109
Netherlands 650 99 119
3. Fossil fuel based vehicles
3.1 Driving Cycles
The driving cycles are defined in EU Directive 80/1268/EEC (as last amended by 2004/3/EC) which all
cars sold after 1 January 2001 are required to take for type approval.
There are in general two parts: an urban and an extra-urban cycle. The fuel test cycle is the same as
the one used to determine the official exhaust emission classification for the vehicle in question. As a
prerequisite are the cars run-in and driven for at least 3000 kilometres before testing. The urban
driving cycle (UDC) starts by taking the vehicle into the test area where the ambient temperature is
6
8. between 20 ° and 30 °C on a rolling road where the emissions are to be collected from key-on (cold
start). The cycle consists of a series of accelerations, steady speeds, decelerations and idling.
Maximum speed is 50 kph, average speed 19 kph with a distance of 4 km. Immediately after the UDC
starts the extra-urban driving cycle (EUDC) which consists of roughly half-steady speed driving and
the remainder accelerations, decelerations, and some idling. The maximum speed is 120 kph,
average speed 63 kph with a distance of 7km. The mixed fuel consumption figure also called the
mixed driving cycle (MUDC) is the average of the two tests, weighted by the distances covered in
each part. For Th!nk City, the driving cycle as seen in Figure 3, would not exceed 100 kph.
Figure 3: European Driving Cycle (source: www.vca.gov.uk).
3.1.1 Driving cycles and real use fuel consumption.
The driving cycles have the following functional requirements:
• use of summer tires,
• an ambient temperature of 20 to 30 degree C,
• heater is off
• new vehicle/engine
In everyday driving the fuel consumption will often be effectively higher. The driving cycles have
typically low average speed (19kph and 62.6kph) and few, soft accelerations (Statens Vegvesen
2007).
Speed and driving behaviour are important elements in limiting CO2 emissions from road transport.
While each vehicle reaches its optimal fuel economy at a different speed (or range of speeds), gas
mileage usually decreases rapidly at speeds above 90 kph. As a rule of thumb, you can assume that
each 8 kph you drive over 90 kph is like adding an additional 7% to your fuel consumption
(http://www.fueleconomy.gov/feg/driveHabits.shtml). Limiting the maximum speed to 100 kph in for
example Germany would reduce the CO2 emissions by 20-25%, cut traffic casualties almost by half
7
9. and improve traffic flow (Kågeson 2005). However, driving at speeds below 20 kph has considerably
higher fuel consumption than driving at high speeds.
Driving in rush hour, queuing with rapid accelerations, stop-and-go are typical situations for many
city drivers. Driving a vehicle in slow queue has much higher fuel consumption than driving at the
highway in the highest gear. Traffic jams waste a lot of fuel, a study from the city of Brussels of
relatively low-mileage cars found that fuel consumption was 20-45% higher during rush hours
compared to Sundays (De Vlieger, De Keukeleere og Kretzschmar 2000). Compared to driving
constant at 50 kph, driving during rush hours (13.5 kph average speed) doubled CO2 emissions.
Similarly, a traffic simulation of a congested city highway, similar to Oslo which has a lot of
connecting roads and exits, shows a decrease of 38% CO2 emissions by adding an extra lane and thus
increasing the traffic flow and average speed from 32.4 kph to 54.7 kph (Knudsen og Bang 2007).
Consequently, driving continuously in high gears (5.) can lead to considerable fuel savings on flat
roads or low gradient hills.
Using the engine block heater reduces the fuel consumption considerably compared to cold starting
at temperatures below 10 degrees Celsius, especially for petrol cars. Although the European Driving
Cycle includes a cold start, the temperature in the test room is about 20-30 degrees and does not
reflect a winter situation. For a modern car, the reduction for Swedish conditions is slightly more
than 0.1 litres per cold start by using the heater (Hoglund og Ydstedt 1998). Block heaters can
improve overall winter fuel economy by as much as 10 percent.
Using the A/C in small and light vehicles will typically increase the fuel consumption more than using
the A/C in larger vehicle. The colder it is inside the car in comparison to the temperature outside, the
higher the fuel consumption will be. Using the A/C typically increases the fuel consumption by 3-8%
(Statens Vegvesen 2007).
Rolling resistance is an important determinator of fuel consumption and can be defined as the force
required to push a vehicle over the surface it rolls over. It is often estimated, that a change in rolling
resistance of 10 % leads to a change in fuel consumption of 2-3 % (Road Directorate 2004). The
rolling resistance force increases as the speed increases and decreases when the inflation pressure is
raised and that is why it is most important to keep correct tyre pressure, especially in winter. For the
smallest tyres (165/70 R14) the summer tyres has the lowest rolling resistance, but for the wider
tyres, the summer tyres have the highest rolling resistance. Generally the presence of water or snow
on a road increases the rolling resistance and therefore the fuel consumption.
3.2 CO2 Emissions of fossil fuel
3.2.1 CO2 Emission in Fuel production (well-to-tank)
Petrol and diesel are mixtures of liquid hydrocarbons refined from crude petroleum. The production
of these fuels involves extraction, separation of crude oil from other fluids, transport to refineries,
processing (fractional distillation), transport to regional storage locations and distribution to fuel
stations. The results of life cycle analyses shows that, in most cases, the vehicle and fuel production
stages account for around 20% of total lifetime CO2 emissions – the emissions associated with fuel
and vehicle production are roughly equal in magnitude (Camden 2006) (Schweimer og Levin 2000)
(Widmer, Gauch og Zah 2007).
8
10. Different estimations of CO2 emissions from fuel production exist. The estimates vary from 202,6-
478,5 grams per litre for petrol and 235,4-420 grams per litre for diesel (Schweimer og Levin 2000)
(Jungbluth 2007)12 (Lewis 1997)3.
CO2 Emissions for fuel production in this report
EcoInvent 2.0 is the same database as we employed for calculating the CO2 emissions from
electricity production and is considered the most recently updated and comprehensive study of fuel
production processes to our knowledge. It is advantageous when comparing alternatives to apply the
same collection and estimation method and we therefore choose to employ EcoInvent 2.0 which
calculates 478.5 grams per litre for fuel production of petroleum and 420 grams per litre for diesel
regardless of which country in question (Jungbluth, 2007).
3.2.2 CO2 Emissions per litre fuel combusted (tank-to-wheel)
Emission factor in this report
There are various estimations of the CO2 content per litre of fuel. Based on the measurement results
of the type approved vehicles and in line with literature provided in Annex I, the emission factor used
in this report for CO2 emissions are 2.40 and 2.66 kg/l for petroleum and diesel respectively.
3.2.3 CO2 Emission per litre fuel consumed (well-to-wheel)
Table 4: Well-to-wheel emissions per litre fuel consumed (kilograms per litre)
Fuel Production Fuel Combustion Total Emissions
Gasoline 0.48 kg/l 2.40 kg/l 2.88 kg/l
Diesel 0.42 kg/l 2.66 kg/l 3.08 kg/l
3.3 Fuel consumption of fossil fuelled based vehicles
Table 5 gives an overview of different cars and their fuel consumption according to the driving cycles.
It is worth noticing that the diesel car will have about 11% higher CO2 emissions compared with a
petrol car with the same fuel consumption. With other words, a diesel car with fuel consumption of
5,0 l/100km and a petrol car with a consumption of 5,5 l/100km will have roughly the same CO2
emissions. However, the diesel engine is a more effective engine that has lower fuel consumption
and consequently lower CO2 emissions than the gasoline engine.
Vehicle size is also a very important determinator of emissions. Moving down one FISITA passenger
car category typically equates to a reduction in the total life cycle environmental impact of around
12%-16% (Camden 2006). The importance of vehicle size is due to the effect of fuel economy on
vehicle emissions, and also to the fact that higher fuel use requires an increase in fuel production
energy which in turn leads to increased emissions. In addition, the vehicle cycle also contributes to
this correlation – larger vehicles (that tend to have higher fuel use) require more materials and
assembly energy during manufacture.
1
Fuel emissions at regional storage in Europe were estimated to 0,65 kg CO2 per kg petrol and 0,5 kg CO2 per
kg diesel.
2
The weight/volume ratio was estimated for petrol to 0.75l/kg and 0.84l/kg for diesel (Zah, et al. 2007)
3
Fuel emissions in production stage were estimated to 434 grams CO2 per kg petrol and 316.8 grams CO2 per
kg diesel.
9
11. Table 5: Fuel consumption according to driving cycle. (Source: www.vcacarfueldata.org.uk)
Car Model Engine Fuel Fuel Fuel
capacity cc, consumption consumption consumption
Trans- extra urban urban cycle mixed cycle
mission cycle (l/100 km) (l/100 km)
(l/100 km)
Gasoline
Smart fortwo coupe 698, SM6 4 6 4,7
(50 bhp)
Peugot 107 998, M5/A5 4,1 5,5 4,6
Fiat Grande Punto 1242, M5 4,9 7,5 5,9
Nissan Micra 1240, M5 5,1 7,4 5,9
Peugot 206 1360, M5 5 8,9 6,4
Toyota Prius 1497, E-CVT 4,2 5 4,3
Mini Cooper R55 Clubman 1598, M6 4,5 7,1 5,5
BMW X3 Series E83 2497, M6 7,3 12,8 9,3
Diesel
Peugot 206 1398, M5 3,7 5,4 4,3
BMW E81/E82/E87/E88 1995, M6 4 5,4 4,5
VW Beetle (109.5 bhp) 1896, M5 4,6 6,8 5,4
Volvo S40 (2007) 2400, A5 5,5 9,7 7
Citroen C1 1395, M5 3,4 5,3 4,1
Fiat Panda 1248, M5 3,7 5,4 4,3
10
12. 3.4 Carbon Impact Analysis for fossil fuelled cars (well-to-wheel)
Table 6 shows the well-to-wheel emission from fossil fuelled cars. Some readers may note that these
calculated CO2 emissions are higher than the official emissions provided by the car manufacturers.
The reason for this is that the emission estimates provided by the car manufacturer are based on the
standard driving cycles for mixed driving (MUDC) whereas this is an overview of the urban cycle
(UDC). They also do not include the life cycle CO2 emissions associated with fuel production. For
numbers on mixed driving see chapter 4.2.
The well-to-tank emissions are calculated with the fuel needed for driving one kilometre in an urban
cycle based on the car manufacturers own data as seen in Table 5 and multiplied with the CO2
emissions of one litre fuel production documented in chapter 3.2.1. The tank-to-wheel emissions are
calculated based the fuel consumption for the urban cycle (Table 5) multiplied with the CO2
emissions for combusting one litre fuel documented in chapter 3.2.2.
Table 6: Well-to-wheel CO2 fuel emissions of the urban driving cycle.
Car Model cc, Trans- CO2 emissions CO2 emissions CO2 emission
mission well-to-tank tank-to-wheel well-to-wheel
urban cycle urban cycle urban cycle
(g/km) (g/km) (g/km)
Gasoline
Toyota Prius 1497, E-CVT 24 120 144
Peugot 107 998, M5/A5 26 132 158
Smart fortwo coupe 698, SM6 29 144 173
(50 bhp)
Mini R55 Clubman 1598, M6 34 170 204
Cooper
Nissan Micra 1240, M5 35 178 213
Fiat Grande Punto 1242, M5 36 180 216
Diesel
Citroen C1 1395, M5 22 141 163
Peugot 206 1398, M5 23 144 167
Fiat Panda 1248, M5 23 144 167
BMW E81/E82/E87/E88 1995, M6 23 144 167
VW Beetle 1896, M5 29 181 210
(109.5 bhp)
11
13. 4. Comparing the usage phase of Th!nk City with fossil fuelled cars
4.1 Urban Driving
The Th!nk City’s emissions depends on the electricity mix of the country in question. Table 7
compares Th!nk City with fossil fuelled cars and illustrates this fact clearly. We can see that also
compared to a hybrid drive (Toyota Prius), Th!nk City achieves a saving of CO2 emissions ranging
from 31.3% to 96.5% depending on the country in question. This is a considerable saving considering
the vehicle’s lifetime. For example, in the Netherlands, a country which has an overweight of fossil
fuelled electricity generation, Th!nk City saves 7.2 metric tons of CO2 emissions over 160 000km
compared to one of the most fuel efficient fossil fuelled car, the Toyota Prius.
In Europe, the Th!nk City has lower CO2 emissions in its usage phase compared to any fossil fuelled
car regardless of the country’s electricity mix. Choosing a green supplier of electricity for charging the
vehicle reduces the CO2 emissions and is an effective way of reducing the carbon footprint of Th!nk
City considerably.
Other independent well to wheels studies have reached the same conclusion (Widmer, Gauch og Zah
2007). A study by Camden (2006) found that the environmental impact was strongly dependent on
the source of the fuel used, illustrated by the large difference between vehicles recharged using
either average mix or renewable electricity. Camden (2006) further found that in those vehicle
classes where available, the use of battery electric vehicles consistently resulted in the lowest overall
environmental impact.
12
14. Table 7: Well-to-wheel CO2 Emissions comparing Th!nk City with fossil fuelled car altenatives and reduction in CO2 emissions with urban driving cycle
Th!nk City Th!nk City Th!nk City Th!nk City
Fossil fuel car
Norway Switzerland UK Netherlands
CO2 CO2 % CO2 % CO2 % CO2 %
Model
g/km g/km Reduction g/km Reduction g/km Reduction g/km Reduction
Gasoline
Toyota Prius 144 5 -96,5 % 15 -89,6 % 84 -41,7 % 99 -31,3 %
Peugot 107 158 5 -96,8 % 15 -90,5 % 84 -46,8 % 99 -37,3 %
Smart fortwo 173 5 -97,1 % 15 -91,3 % 84 -51,4 % 99 -42,8 %
Mini Cooper R55 204 5 -97,5 % 15 -92,6 % 84 -58,8 % 99 -51,5 %
Nissan Micra 213 5 -97,7 % 15 -93,0 % 84 -60,6 % 99 -53,5 %
Fiat Grande Punto 216 5 -97,7 % 15 -93,1 % 84 -61,1 % 99 -54,2 %
Diesel
Citroen C1 163 5 -96,9 % 15 -90,8 % 84 -48,5 % 99 -39,3 %
Peugot 206 167 5 -97,0 % 15 -91,0 % 84 -49,7 % 99 -40,7 %
Fiat Panda 167 5 -97,0 % 15 -91,0 % 84 -49,7 % 99 -40,7 %
BMW E81 167 5 -97,0 % 15 -91,0 % 84 -49,7 % 99 -40,7 %
VW Beetle 210 5 -97,6 % 15 -92,9 % 84 -60,0 % 99 -52,9 %
13
15. 4.2 Mixed Driving
This scenario compares Th!nk City with other fossil fuelled cars at mixed driving, typical for people driving from sub-urban to urban areas of larger cities
where parts of the journey is taken on highways. This scenario uses the standard MUDC. The CO2 emissions for fossil fuel cars were calculated in the same
way as for urban driving, based on the car manufacturers own numbers for fuel consumption multiplied with the CO2 emissions of one litre fuel consumed.
Table 8: Well-to-wheel CO2 Emissions comparing Th!nk City with fossil fuelled car alternatives and reduction in CO2 emissions with mixed urban driving cycle
Fossil fuelled car Th!nk City Th!nk City Th!nk City Th!nk City
Norway Switzerland UK Netherlands
Model CO2 CO2 % CO2 % CO2 % CO2 %
g/km g/km Reduction g/km Reduction g/km Reduction g/km Reduction
Gasoline
Toyota Prius 125 6 -95,2 % 18 -85,6 % 101 -19,2 % 119 -4,8 %
Peugot 107 128 6 -95,3 % 18 -85,9 % 101 -21,1 % 119 -7,0 %
Smart fortwo 136 6 -95,6 % 18 -86,8 % 101 -25,7 % 119 -12,5 %
Mini Cooper R55 158 6 -96,2 % 18 -88,6 % 101 -36,1 % 119 -24,7 %
Nissan Micra 167 6 -96,4 % 18 -89,2 % 101 -39,5 % 119 -28,7 %
Fiat Grande Punto 167 6 -96,4 % 18 -89,2 % 101 -39,5 % 119 -28,7 %
Diesel
Citroen C1 126 6 -95,2 % 18 -85,7 % 101 -19,8 % 119 -5,6 %
Peugot 206 130 6 -95,4 % 18 -86,2 % 101 -22,3 % 119 -8,5 %
Fiat Panda 132 6 -95,5 % 18 -86,4 % 101 -23,5 % 119 -9,8 %
BMW E81 138 6 -95,7 % 18 -87,0 % 101 -26,8 % 119 -13,8 %
VW Beetle 166 6 -96,4 % 18 -89,2 % 101 -39,2 % 119 -28,3 %
14
16. 4.3 Scenario 1: Nordic Winter
The Nordic winter can be cold and may provide challenges for both driver and vehicle. In this
scenario, we compare various climatic conditions. We assume the usage of the UDC driving 30
minutes as well as a longer drive of 60 minutes composed of 30 minutes UDC and 30 minutes MUDC.
Th!nk City
The electricity consumption for Th!nk City increases in cold conditions. Although Th!nk City has no
cold start implications, using the heater requires electricity and decreases range. However, the use of
the heater is a function of climatic conditions and time and is used to keep a comfortable
temperature in the coupe. In fan position 2, 1 kW to the heater increases air temperature by 16°C.
Table 9 shows estimated heater usage as a function of climatic conditions and usage pattern to
achieve a comfortable temperature in coupe (20-22 degrees) for the average user.
Table 9: Average heater usage at different temperatures
Outside Start up Start up Maintenance Heater usage 30 Heater usage
temp time effect effect min 60 min
5˚C 5 min 4 kw 1 kw 0,75 kwh 1,25 kwh
0˚C 15 min 4 kw 1 kw 1,25 kwh 1,75 kwh
-5˚C 15 min 4 kw 2 kw 1,5 kwh 2,5 kwh
-10˚C 15 min 4 kw 4 kw 2,0 kwh 4,0 kwh
However, the experienced Th!nk City driver knows that extensive use of the heater increases
electricity consumption and decreases total range. By reducing the heater accordingly, he may
achieve a better performance than Table 10 and 11 indicates. The average temperature in selected
cities in January was (www.weather.com): Oslo -7˚C; London 3˚C; Paris 4˚C; Amsterdam 2˚C; Berlin -
1˚C; Stockholm -3˚C, and Zurich -1˚C. With other words, cold Nordic conditions occur rarely in other
cities of Western Europe. Driving Th!nk City without heater at MUDC which has average speed of 34
km/h consumes 6,2 kWh per hour driven and for UDC at 19 km/h consumes 2,9 kWh (see Table 2 for
driving efficiency of Th!nk City). Table 10 and 11 gives an overview of the Th!nk City performance
under various climatic conditions as a function of temperature, heater usage and time.
Th!nk City can also be deliver with an option of electric demist/deice front window. This is the most
energy efficient way of securing visibility and will reduce the load on the heater considerably. It
consumes 364W and 663W for demist and deice respectively.
15
17. Table 10: CO2 emissions per kilometre driven for Th!nk City at winter conditions, 30 min UDC
Temperature -10˚C -5˚C 0˚C 5˚C
Heater 30 min, kwh 2,00 1,50 1,25 0,75
Driving 30 min UDC, kwh 1,45 1,45 1,45 1,45
Total 30 min, kwh 3,45 2,95 2,70 2,20
Battery capacity 30 min 88 % 90 % 90 % 92 %
Average 30 min, kWh/km 0,364 0,311 0,285 0,232
CO2 - Norway g/km 11 10 9 7
CO2 – Nordic Grid g/km 62 53 48 39
CO2 – Western European Grid 178 152 139 114
Average temperature in January Oslo, Copenhagen, London,
for selected cities Stockholm Paris, Zurich Paris
Table 11: CO2 emissions per kilometre driven for Th!nk City at winter conditions, 30 min UDC + 30 min MUDC
Temperature -10˚C -5˚C 0˚C 5˚C
Heater 60 min, kwh 4,00 2,50 1,75 1,25
Driving 30 min, UDC, kwh 1,45 1,45 1,45 1,45
Driving 30 min, MUDC, kwh 3,09 3,09 3,09 3,09
Total 60 min, kwh 8,54 7,04 6,29 5,79
Battery capacity 60 min 70 % 75 % 78 % 79 %
Average 60 min, kWh/km 0,323 0,266 0,238 0,219
CO2 - Norway g/km 10 8 7 7
CO2 – Nordic Grid g/km 55 45 40 37
CO2 – Western European Grid 158 130 116 107
Average temperature in January Oslo, Copenhagen, London,
for selected cities Stockholm Paris, Zurich Paris
16
18. Fossil fuelled vehicle
The engine combustion surfaces and engine oil must be warmed up. The sometimes competing
requirements to provide timely heat to the heater and at the same time to the engine increases fuel
consumption. Some factors such as coolant flow rate affect heater warm-up positively while affecting
engine warm-up negatively. Fuel consumption increases almost linearly as a function of decreasing
temperature, although at very low temperature the amount partially and non-combusted fuel
increases disproportionately while the CO2 emissions stagnate or even decrease (Favez og
Weilenmann 2006). The normal UDC is conducted in a room which on average has about 23˚Celsius,
which does not reflect the Nordic winter conditions. For a category Euro-4 petrol engine and a diesel
engine, one may assume the cold start phase last for about 7 km, or 22 minutes and 15 seconds at 19
km/h average speed (Favez og Weilenmann 2006), which is the same average speed as the UDC.
Based on Favez and Weilenmann (2006), we assume a linear increase of the extra fuel consumption
measured at temperatures at 23˚C, -7˚C and -20˚C which was 0.04, 0.13 and 0.18 litre per start for
petrol and 0.05, 0.14 and 0.20 for diesel respectively (see Table 12). In terms of HC (hydrocarbons), a
modern gasoline car emits in one cold start at 23˚C the same amount as a warm ride of 72 km and at
-20˚C, it emits 14 times more, thus as much as within 1000 km of driving (Empa 2008). In a similar
way, the particulate emissions rise for diesel vehicles when they start at lower temperatures.
Distance is of minor importance when it comes to HC emissions (after one km the majority of cold
start emissions are released), driving short distances should therefore be minimized. As seen in Table
13 and 14, there is a considerable increase in CO2 emissions as a result of increased fuel
consumption. The fuel consumption depends on the outside temperature. For more details on the
calculations for Table 13 and 14, see Annex II.
Table 12: extra fuel consumption at cold starts as a function of temperature. Based on Favez and Weilenmann (2006)
Temperature Litre/Start Litre/Start
Petrol Diesel
5˚C 0,0960 0,1061
0˚C 0,1120 0,1205
-5˚C 0,1279 0,1350
-10˚C 0,1449 0,1583
17
19. Table 13: Average well-to-wheel CO2 emissions (g/km) during typical winter conditions for selected vehicles driving 30 min UDC.
Toyota Peugot Smart for Nissan Fiat G. Mini Peugot VW Fiat Citroen BMW
Temperature
Prius 107 two Micra Punto Cooper 206 Beetle Panda C1 E81
Gasoline Gasoline Gasoline Gasoline Gasoline Gasoline Diesel Diesel Diesel Diesel Diesel
-10˚C 188 202 217 257 260 248 218 261 218 215 218
-5˚C 183 197 211 252 255 243 210 253 210 207 210
0˚C 178 192 207 247 250 238 205 249 205 202 205
5˚C 173 187 202 242 245 233 201 244 201 198 201
Table 14: Average well-to-wheel CO2 emissions (g/km) during typical winter conditions for selected vehicles driving 60 min (30 min UDC + 30 min MUDC).
Toyota Peugot Smart for Nissan Fiat G. Mini Peugot VW Fiat Citroen BMW
Temperature
Prius 107 two Micra Punto Cooper 206 Beetle Panda C1 E81
Gasoline Gasoline Gasoline Gasoline Gasoline Gasoline Diesel Diesel Diesel Diesel Diesel
-10˚C 147 157 164 201 202 191 163 200 163 158 167
-5˚C 145 156 163 199 200 189 160 197 160 155 164
0˚C 143 154 161 197 199 187 159 196 159 154 163
5˚C 141 152 159 196 197 185 157 194 157 152 161
18
20. Comparing fossil fuelled vehicles with Th!nk City
In Table 15 and 16, we see that a country’s electricity mix is an important factor while comparing the CO2 emissions. Th!nk City has a higher electricity
consumption per driven kilometre at lower temperature due to increased use of the heater. Nevertheless, driving a Th!nk City for 30 minutes saves 5-30% in
Western Europe, about 70% CO2 emissions compared to other cars in the Nordic Grid and as much as about 95% in Norway at temperature -10˚C. The Th!nk
City also performs better at lower temperature. For a 60 minute drive and typical winter conditions in Western Europe (-5˚C to 5˚C), Th!nk City has 10-40%
lower emissions than other small cars. At -10˚C in Western Europe, the most fuel efficient fossil fuelled cars performs marginally better at low temperature,
although a car similar to the Nissan Micra does not. This will of course depend on the country in question, e.g., France has considerably lower CO2 emissions
than Germany. One may see that using the heater has a major impact, because the relatively low energy efficiency of the combustion engines creates spill
heat that can be used for the heater while for an electric vehicle this heat has to be created.
Table 15: Percentage reduction in CO2 emissions comparing of Th!nk City with fossil fuelled cars under typical winter conditions, 30 min UDC.
Fossil fuelled car Th!nk City Th!nk City Th!nk City
Norway Nordic Grid Western European Grid
Model -10˚C -5˚C 0˚C 5˚C -10˚C -5˚C 0˚C 5˚C -10˚C -5˚C 0˚C 5˚C
Gasoline
Toyota Prius -94,1 % -94,5 % -94,9 % -96,0 % -67,0 % -71,0 % -73,0 % -77,5 % -5,3 % -16,9 % -21,9 % -34,1 %
Peugot 107 -94,6 % -94,9 % -95,3 % -96,3 % -69,3 % -73,1 % -75,0 % -79,1 % -11,9 % -22,8 % -27,6 % -39,0 %
Smart fortwo -94,9 % -95,3 % -95,7 % -96,5 % -71,4 % -74,9 % -76,8 % -80,7 % -18,0 % -28,0 % -32,9 % -43,6 %
Mini Cooper R55 -95,6 % -95,9 % -96,2 % -97,0 % -75,0 % -78,2 % -79,8 % -83,3 % -28,2 % -37,4 % -41,6 % -51,1 %
Nissan Micra -95,7 % -96,0 % -96,4 % -97,1 % -75,9 % -79,0 % -80,6 % -83,9 % -30,7 % -39,7 % -43,7 % -52,9 %
Fiat Grande Punto -95,8 % -96,1 % -96,4 % -97,1 % -76,2 % -79,2 % -80,8 % -84,1 % -31,5 % -40,4 % -44,4 % -53,5 %
Diesel
Citroen C1 -94,9 % -95,2 % -95,5 % -96,5 % -71,2 % -74,4 % -76,2 % -80,3 % -17,2 % -26,6 % -31,2 % -42,4 %
Peugot 206 -95,0 % -95,2 % -95,6 % -96,5 % -71,6 % -74,8 % -76,6 % -80,6 % -18,3 % -27,6 % -32,2 % -43,3 %
Fiat Panda -95,0 % -95,2 % -95,6 % -96,5 % -71,6 % -74,8 % -76,6 % -80,6 % -18,3 % -27,6 % -32,2 % -43,3 %
BMW E81 -95,0 % -95,2 % -95,6 % -96,5 % -71,6 % -74,8 % -76,6 % -80,6 % -18,3 % -27,6 % -32,2 % -43,3 %
VW Beetle -95,8 % -96,0 % -96,4 % -97,1 % -76,2 % -79,1 % -80,7 % -84,0 % -31,8 % -39,9 % -44,2 % -53,3 %
19
22. 4.4 Scenario 2: Rush hour
For a lot of people living in urban areas, driving in rush hour is part of the daily life. The road typically
takes them from a sub-urban area to a highway for some kilometres and into the city. However,
driving in congested traffic provides challenges for both driver and vehicle. A typical description of
rush hour includes frequent accelerations and braking, low average speed, idling, stop –and-go
situations, and wasted time queuing. We apply the urban driving cycle for this scenario to illustrate
the reduced speed and increase of stop-and-go situations.
Th!nk City
Engine idling of Th!nk City does not require electricity. The electricity used will be for powering other
systems, e.g., lights. Th!nk City also has regenerative braking charging the battery, which is an
advantage in stop-and-go situations. Driving at low speed also increases the range of Th!nk City as
the power needed for moving the vehicle one kilometre increases as speed increases. This is due to
air resistance which grows proportionately to the square of the velocity.
Fossil fuelled vehicle
A study from the city of Brussels of relatively low-mileage cars found that fuel consumption was 20-
45% higher during rush hours compared to Sundays and that compared to driving constant at 50 kph,
driving during rush hours (13.5 kph average speed) doubled CO2 emissions (De Vlieger, De
Keukeleere og Kretzschmar 2000). Similarly, a traffic simulation of a congested city highway with a lot
of connecting roads and exits, shows a decrease of CO2 emissions for new cars (1-5 years) of 32% for
petrol cars and 30% for diesel cars by adding an extra lane and thus increasing the traffic flow and
average speed from 32.4 kph to 54.7 kph (Knudsen og Bang 2007). Such a simulation of conditions
could apply to Oslo during Rush hour. The reduction in CO2 emissions was 38% including all types of
vehicles. The authors noted that the real average speed would be lower because cars were queuing
also to get into and exit the highway. We apply the findings of Knudsen and Bang (2007) of 32% and
30% for newer petrol cars and diesel cars respectively in this scenario. For hybrid vehicle, its
performance in rush hour depends on several external factor such as the engine temperature (the
engine needs to be running until optimal temperature is achieved), the size and charging status of
the battery (how long has the vehicle been driven before queuing), how much time queuing (long
time drains the battery and the petrol engine must start), etc. It is therefore depending on external
influences and we assume that a hybrid vehicle on average uses 20% more petrol during rush hour.
Comparing fossil fuelled vehicles with Th!nk City
Table 17 shows that Th!nk City is ideal for rush hour traffic and provides considerably savings
compared to fossil fuelled vehicles, regardless of electricity mix used to charge the vehicle. This
factor is illustrated by providing an electricity mix generated from only hard coal power stations
which still shows a significant saving potential.
21
23. Table 17: Rush hour comparison of Th!nk City with fossil fuelled car. * For illustration we have provided the generation of electricity from hard coal fired power stations which creates co2
emissions of approximately 1000 g/kwh (Dones, Bauer og Röder 2007)
Fossil fuelled car Th!nk City Th!nk City Th!nk City Th!nk City Th!nk City
Electricity Electricity Electricity Electricity Electricity
Norway Switzerland UK The Netherlands Hard Coal*
Model Normal RushHour CO2 % CO2 % CO2 % CO2 % CO2 %
CO2 CO2 g/km Reduction g/km Reduction g/km Reduction g/km Reduction g/km Reduction
g/km g/km
Gasoline
Toyota Prius 144 173 5 -97,1 % 15 -91,3 % 84 -51,4 % 99 -42,7 % 153 -11,5 %
Peugot 107 158 209 5 -97,6 % 15 -92,8 % 84 -59,7 % 99 -52,5 % 153 -26,6 %
Smart fortwo 173 228 5 -97,8 % 15 -93,4 % 84 -63,2 % 99 -56,6 % 153 -33,0 %
Mini Cooper 204
R55 269 5 -98,1 % 15 -94,4 % 84 -68,8 % 99 -63,2 % 153 -43,2 %
Nissan Micra 213 281 5 -98,2 % 15 -94,7 % 84 -70,1 % 99 -64,8 % 153 -45,6 %
Fiat Grande 216
Punto 285 5 -98,2 % 15 -94,7 % 84 -70,5 % 99 -65,3 % 153 -46,3 %
Diesel
Citroen C1 163 212 5 -97,6 % 15 -92,9 % 84 -60,4 % 99 -53,3 % 153 -27,8 %
Peugot 206 167 217 5 -97,7 % 15 -93,1 % 84 -61,3 % 99 -54,4 % 153 -29,5 %
Fiat Panda 167 217 5 -97,7 % 15 -93,1 % 84 -61,3 % 99 -54,4 % 153 -29,5 %
BMW E81 167 217 5 -97,7 % 15 -93,1 % 84 -61,3 % 99 -54,4 % 153 -29,5 %
VW Beetle 210 273 5 -98,2 % 15 -94,5 % 84 -69,2 % 99 -63,7 % 153 -44,0 %
22
24. 4.5 Comparing electric vehicles with alternative transport solutions –
Results of a life cycle screening
A passenger kilometre [pkm] is defined as the transport of one passenger by a transport service over
one kilometre and can be used as a unit for comparing alternative transport solutions. Figure 4 shows a
comparison of Th!nk City with other transport solutions analysed by Simapro 7 using the database
EcoInvent 2.0, based on data representing Swiss conditions. In relation to other passenger cars, the
manufacturing and fuel production stage accounts for 20% of total life cycle impacts (Camden 2006)
(Schweimer og Levin 2000) (Widmer, Gauch og Zah 2007). Th!nk City has CO2 emissions of 15g/km
using Swiss electricity in its usage phase. Assuming that 20% of the life cycle impacts results from
manufacturing, its life cycle emissions are estimated to 18 g/km. Figure 4 shows that Th!nk City
performs at the same level as other electric solutions for personal transportations, such as the tram or
trolley bus.
Figure 4: Life cycle screening of alternative transport solutions in terms of CO2 emissions (Swiss conditions).
23
25. 4.6 Discussion on methodology
The method of conducting a well-to-wheel analysis is well established. However, its outcome
depends on the sources of information applied. In this chapter a short discussion on the fundamental
sources of information is presented. Following key factors determines the outcome of this well to
wheel analysis:
• Life cycle impacts of electricity g/kwh: The CO2 emission per kilowatt hour at consumer is a key
element for determining the electric vehicles performance. In this report, we have used the
Ecoinvent database calculations which includes e.g., the environmental load of constructing and
maintaining and factors such as power loss while transporting electricity and trading. Other
calculations such as from the International Energy Agency do not include life cycle impacts or
effects on grid mix due to electricity trade. This consequently leads to a lower overall emission
than the Ecoinvent database varying from 9 to 77%. We are therefore conservative in our
estimations.
• Life cycle impacts of fuel combustion per litre: The CO2 emissions per litre fuel consumed is a key
element for determining the fossil fuelled vehicles performance. The CO2 emissions per litre fuel
produced is taken from the Ecoinvent database which includes the life cycle impacts. Other
studies have calculated lower production emissions, but these are older studies which do not
necessary take all life cycle impacts into account. We have used the same source (EcoInvent) as
with electricity production as we consider it important to apply a consistent methodology for
comparison. CO2 emissions in the usage phase are directly related to fuel consumption. As
newer vehicles are cleaner in operation than older vehicles we found it necessary to calculate the
CO2 emissions for 2007 models. This was calculated through the average conversion of fuel to
CO2 emissions based on the car manufacturers’ official test results of fuel consumption and the
related CO2 emissions that are measured with the MUDC (see Annex I). Although every engine
type has a different efficiency, the conversion factor should represent the most updated
emission factor based on fuel consumption.
• Fuel and electricity consumption per kilometre driven: The fuel consumption is taken from the
car manufacturers’ own reported consumption based on the European Driving Cycle tests they
are obliged to take for type approval. The electricity consumption are based on Think’s reported
consume based on the European Driving Cycles. This should ensure an equal basis for
comparison.
• Basis for comparison, the European driving cycles and scenarios: The European Driving Cycles are
defined in EU Directive 80/1268/EEC and all vehicles sold after January 2001 are required to take
these tests for type approval. This should ensure an equal basis for comparison. The scenarios
are all based on the driving cycles as discussed above. For scenario Nordic Winter, the extra
electricity consumption due to heater usage are estimated by Think’s own engineering division
for A/C and is based on the average driver’s need of keeping a comfortable temperature in coupe
as well as high visibility. The extra fuel consumption for fossil fuelled vehicles at various
temperatures is based on measurements from the laboratory of internal combustion engine
research at the Swiss Federal Laboratories for Materials Testing and Research. This research
24
26. group is internationally recognized. For scenario Rush Hour, the Think City estimates are based
on the UDC cycle which is not adjusted in any way, even though range may increase in stop and
go situations for Think City due to low speed and regenerative braking. We therefore believe it to
be a conservative estimate. For petrol or diesel vehicles, the estimates for rush hour from
literature vary from 20-45% higher fuel consumption than off-peak hours. We apply the findings
from a simulation of a large city similar to Oslo conducted in 2007 by SINTEF, which is the largest
independent research organisation in Scandinavia. Several stakeholders, such as politicians and
traffic interest organizations, were on the advisory board for this project. The simulation was
targeted to find out whether emissions would be higher or lower by adjusting the “flow” in the
traffic. The characteristics of rush hour is stop-and-go situations and simulating stop and go
situations compared to good flow in traffic is considered to reflect the difference between rush
hour and off-peak hours satisfactory. There were no estimates of hybrid vehicle performance
available in literature. Its electric performance depends on the historic driving pattern as well as
battery status and capacity. We have assumed 10% lower fuel consumption than the average
fossil fuelled car due to increased use of the electric engine.
5. Conclusions
Although an electric vehicle may contribute to global emissions of CO2 depending on generation of
the electricity, an electric vehicle reduces noise, and eliminates local air pollutions such as nitrogen
oxides (NOx), particle matter, ground level ozone (O3), factors that are key contributors to smog, a
major health hazard in cities. In addition, it is easier to control few but big point sources of emissions
(power stations) than millions of small point sources (cars) in terms of e.g. replacing technology or
targeting environmental policies.
An electric vehicle, such as the Th!nk City, will due to its energy efficiency create a significant
reduction of CO2 emissions compared to fossil fuelled vehicles. For urban driving this reduction
amounts to about 95% in Norway, 90% in Switzerland, 40-60% in the UK and 30-50% in the
Netherlands which has the most fossil fuel intensive electricity mix in Western Europe. The reduction
varies depending on the driving pattern and the traffic conditions. Therefore, driving an electric
vehicle will move the CO2 emissions from the transport sector to the electricity sector, but will
reduce the overall global emissions considerably.
Th!nk City outperforms all other fossil fuelled alternatives under all climatic conditions if charged on
electricity from a renewable source. Purchasing guaranteed green electricity is the most effective
way to ensure a low CO2 emission footprint for the vehicle. Moving from a combustion engine to an
electric engine for vehicles will be a necessary change to reduce the impacts of transport on climate
change. The electrical vehicles environmental benefits are significant.
25
27. Bibliography
Camden. Life Cycle Assessment of Vehicle Fuels and Technologies. London: Ecolane Transport
Consultancy, 2006.
De Vlieger, I, D De Keukeleere, og J.G. Kretzschmar. «Environmental effects of driving behavior and
congestion related to passenger cars.» Atmospheric Environment, 2000: 4649-4655.
Dones, Roberto, Christian Bauer, og Alexander Röder. Kohle. ecoinvent report No. 6-VI. Villigen: Swiss
Centre for Life Cycle Inventories, 2007.
Empa. Real world emission and fuel consumption monitoring. 2008.
http://www.empa.ch/plugin/template/empa/*/39486/---/l=2 (accepted March 12, 2008).
Favez, Jean-Yves, og Martin Weilenmann. «Cold start emissions of passenger cars at different low
ambient temperatures.» 2006.
Frischknecht, Rolf, Matthias Tuchschmid, Mireille Faist-Emmenegger, og ESU-services Ltd. Strommix
und Stromnetz. ecoinvent report No. 6 / Teil XVI. Uster: Swiss Centre for Life Cycle Inventories, 2007.
Hoglund, Paul G, og Anders Ydstedt. «Reduced Air Pollution and Fuel Consumption With Preheated
Car Engines.» Urban transport and the environment for the 21st century. Lisbon, Portugal, 1998.
IEA. CO2 Emissions from Fuel Combustion 1971-2005. Paris: International Energy Agency, 2007.
Jungbluth, N. Erdöl. Ecoinvent report No. 6-IV,. Duebendorf, Switzerland: Swiss Centre for Life Cycle
Inventories,, 2007.
Knudsen, Tore, og Børge Bang. Environmental consequences of better roads. Trondheim: Sintef
Teknologi og Samfunn, 2007.
Kågeson, Per. Reducing CO2 emissions from new cars. Brussels: European Federation for Transport
and Environment, 2005.
Lewis. Fuel and Energy Production Emission Factors. Harwell, UK: AEA Technology, 1997.
POST. Carbon Footprint of Electricity Generation. London: Parliamentary Office of Science and
Technology, 2006.
Road Directorate. Rolling resistance, fuel consumption - a literature review. Roskilde: Road
Directorate, Danish Ministry of Transport, 2004.
Schweimer, Georg W., og Marcel Levin. Life Cycle Inventory for the Golf A4. Wolfsburg, Germany.:
Research, Environment and Transport, Volkswagen AG,, 2000.
Statens Vegvesen. Oversikt over drivstofforbruk og CO2-utslipp for nye personbiler 2006/2007. Oslo:
Statens vegvesen, 2007.
26
28. Statens Vegvesen. Vstøy/Vluft 4.5. Beregning av lokal luftforurensning og støy fra veg. MISA 2002/27.
Oslo: Statens Vegvesen, 2002.
Statistics Norway. Elektrisitetsbalanse etter år/kvartal. 1994-2006. GWh. 2007.
http://www.ssb.no/elektrisitetaar/tab-2007-05-24-14.html (Accessed March 19, 2008).
Widmer, Rolf, Marcel Gauch, og Rainer Zah. «Evaluation and comparison of bio-fuelled mobility with
all-electric solutions using Life Cycle Assessment.» EET-2007 European Ele-Drive Conference. Brussels,
Belgium: May 30- June 01, 2007, 2007.
Zah, Rainer, Heinz Boeni, Marcel Gauch, Roland Hischier, Martin Lehmann, og Patrick Waeger.
Ökobilanz von Energieprodukten: Ökologische Bewertung von Biotreibstoffen. Bern, Switzerland:
Bundesamt fuer Energie BFE, 2007.
27
29. Annex I: Fuel Conversion Factors
The fuel consumption given in Table 18 are obtained from UK Governmental Data
(www.vcacarfueldata.org.uk) and are results of official tests (see driving cycles), which are required
before a model of car can be offered for sale. Therefore are no direct conversion factors given. Table
13 gives an overview of 5 petroleum cars and 5 diesel cars with their measured fuel consumption and
CO2 emissions. The theoretical conversion factor is then calculated and used to provide an average
of CO2 emissions per litre fuel.
Table 18: CO2 Conversion factor fuel combustion. The last row is the calculated conversion factor based on CO2 g/km
divided by fuel consumption l/100km for mixed driving cycle.
Make Model Engine Transmission CO2 Fuel Emission
capacity Emissions consumption factor
cc g/km (l/100km) CO2 kg/l
Gasoline
Toyota Prius 1497 E_CVT 104 4.3 2,41
Peugot 107 998 M5 or A5 109 4,6 2,37
Smart Fortwo 698 SM6 113 4,7 2,40
50 bhp
Mini R55 1598 M6 132 5,5 2,40
Cooper Clubman
BMW X3 Series 2497 M6 224 9,3 2,41
E83
Average Conversion Factor Gasoline 2,40
Diesel
Citroen C1 1395 M5 109 4,1 2,66
BMW E81 1995 A6 144 5,4 2,67
Peugot 207 1560 M5 120 4,5 2,67
VW Beetle 1896 M5 143 5,4 2,65
Volvo V50 1560 M5 132 5,0 2,64
Average Conversion Factor Diesel 2,66
The theoretical conversion factor is also confirmed in literature:
• Klimaløftet, an association of the Norwegian Environmental Ministry, Environmental NGOs
and other organizations, assumes CO2 content per litre of fuel to be 2.3 kg for petrol and 2.6
kg for diesel (www.klimaloftet.no).
• A report from the European Federation for Transport and Environment in Brussels estimated
the amount of CO2 released per 1 litre of petrol and diesel to be 2,36 and 2,6 kg respectively
(Kågeson 2005).
• For the determination of CO2-emissions, EcoInvent v2.0 employs a conversion factor of 3.172
kgCO2/kgFuel for petrol and diesel respectively (Jungbluth 2007). Diesel has a weight/volume
ratio of 0.84kg/l and petrol 0.75kg/l which amounts to CO2 emissions of 2.66kg/l and 2.38kg/l
for diesel and petroleum respectively (Zah, et al. 2007). The final value for the life cycle
inventories is then derived by subtracting the carbon fixed in CO-emissions, but which its
relative contribution is minimal.
28
30. Annex II: Nordic Winter – Example of calculation sheet 5 degrees Celsius
UDC 30 min
Model Toyota Peugot Smart for Nissan Fiat G. Mini Peugot VW Fiat Citroen BMW
Prius 107 two Micra Punto Cooper 206 Beetle Panda C1 E81
Fuel Gasoline Gasoline Gasoline Gasoline Gasoline Gasoline Diesel Diesel Diesel Diesel Diesel
Fuel consumption UDC (l/100km) 5,000 5,5 6 7,4 7,5 7,1 5,4 6,8 5,4 5,3 5,4
Fuel consumption 30 min UDC (l) 0,475 0,523 0,570 0,703 0,713 0,675 0,513 0,646 0,513 0,504 0,513
Cold start litre/start at 5˚C (l) 0,09602 0,09602 0,09602 0,09602 0,09602 0,09602 0,1061 0,1061 0,1061 0,1061 0,1061
Total FC 30 min, 9.5km (l) 0,571 0,619 0,666 0,799 0,809 0,771 0,619 0,752 0,619 0,610 0,619
Well-to-wheel CO2 (g/km) 173 187 202 242 245 233 201 244 201 198 201
UDC 30 min + MUDC 30 min
Model Toyota Peugot Smart Nissan Fiat G. Mini Peugot VW Fiat Citroen BMW
Prius 107 for two Micra Punto Cooper 206 Beetle Panda C1 E81
Fuel Gasoline Gasoline Gasoline Gasoline Gasoline Gasoline Diesel Diesel Diesel Diesel Diesel
Fuel consumption UDC (l/100km) 5,000 5,5 6 7,4 7,5 7,1 5,4 6,8 5,4 5,3 5,4
Fuel Consumpt. MUDC (l/100km) 4,300 4,6 4,7 5,9 5,9 5,5 4,3 5,4 4,3 4,1 4,5
Fuel consumption 30 min, UDC (l) 0,475 0,523 0,570 0,703 0,713 0,675 0,513 0,646 0,513 0,504 0,513
Cold start litre/start at 5˚C (l) 0,09602 0,09602 0,09602 0,09602 0,09602 0,09602 0,1061 0,1061 0,1061 0,1061 0,1061
Fuel Consumpt. 30 min, MUDC (l) 0,731 0,782 0,799 1,003 1,003 0,935 0,731 0,918 0,731 0,697 0,765
Total FC 60 min, 26,5 km 1,302 1,401 1,465 1,802 1,812 1,706 1,350 1,670 1,350 1,307 1,384
Well-to-wheel CO2 (g/km) 141 152 159 196 197 185 157 194 157 152 161
UDC, Average speed km/h 19 19 19 19 19 19 19 19 19 19 19
MUDC, Average speed km/h 34 34 34 34 34 34 34 34 34 34 34
Total Distance travelled km 26,5 26,5 26,5 26,5 26,5 26,5 26,5 26,5 26,5 26,5 26,5
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