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

- Clarifying electricity loss in chp 2.1 -updated conclusions

Åsgeir Helland

1

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

2

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.

3

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.

4

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

Country

EcoInvent 2.0 CO2 g/kWh

IEA (2007) CO2 g/kWh

Norway 31 7

Western European Grid 490 346

(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

5

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

6

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

production

g/kWh

Zebra

UDC

g/km

Zebra

MUDC

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

7

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

8

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).

9

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.

10

Car Model Engine

capacity cc,

Trans-

mission

Fuel

consumption

extra urban

cycle

(l/100 km)

Fuel

consumption

urban cycle

(l/100 km)

Fuel

consumption

mixed cycle

(l/100 km)

Gasoline

Smart fortwo coupe (50 bhp)

698, SM6 4 6 4,7

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

Table 5: Fuel consumption according to driving cycle. (Source: www.vcacarfueldata.org.uk)

11

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-

mission

CO2 emissions

well-to-tank

urban cycle

(g/km)

CO2 emissions

tank-to-wheel

urban cycle

(g/km)

CO2 emission

well-to-wheel

urban cycle

(g/km)

Gasoline

Toyota Prius 1497, E-CVT 24 120 144 Peugot 107 998, M5/A5 26 132 158 Smart fortwo coupe

(50 bhp) 698, SM6 29 144 173

Mini

Cooper

R55 Clubman 1598, M6 34 170 204

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

(109.5 bhp) 1896, M5 29 181 210

12

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.

13

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

Fossil fuel car Th!nk City

Norway

Th!nk City

Switzerland

Th!nk City

UK

Th!nk City

Netherlands

Model CO2 CO2 %

Reduction

CO2 %

Reduction

CO2 %

Reduction

CO2 %

Reduction g/km g/km g/km g/km g/km

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 %

14

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

Norway

Th!nk City

Switzerland

Th!nk City

UK

Th!nk City

Netherlands

Model CO2 CO2 %

Reduction

CO2 %

Reduction

CO2 %

Reduction

CO2 %

Reduction g/km g/km g/km g/km g/km

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 %

15

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 temp

Start up time

Start up effect

Maintenance effect

Heater usage 30 min

Heater usage 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.

16

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

for selected cities

Oslo, Stockholm

Copenhagen, Paris, Zurich

London, 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

for selected cities

Oslo, Stockholm

Copenhagen, Paris, Zurich

London, Paris

17

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 Petrol

Litre/Start 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

18

Table 13: Average well-to-wheel CO2 emissions (g/km) during typical winter conditions for selected vehicles driving 30 min UDC.

Temperature Toyota

Prius

Peugot

107

Smart for

two

Nissan

Micra

Fiat G.

Punto

Mini

Cooper

Peugot

206

VW

Beetle

Fiat

Panda

Citroen

C1

BMW

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).

Temperature Toyota

Prius

Peugot

107

Smart for

two

Nissan

Micra

Fiat G.

Punto

Mini

Cooper

Peugot

206

VW

Beetle

Fiat

Panda

Citroen

C1

BMW

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

19

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

Norway

Th!nk City

Nordic Grid

Th!nk City

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 %

20

Table 16: Percentage reduction in CO2 emissions comparing Th!nk City with fossil fuelled cars under typical winter conditions, 60 min driving (30 min UDC + 30min MUDC).

Fossil fuel car Th!nk City

Norway

Th!nk City

Nordic Grid

Th!nk City

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 -93,2 % -94,5 % -95,1 % -95,0 % -62,6 % -69,0 % -72,0 % -73,8 % 7,5 % -10,3 % -18,9 % -24,1 %

Peugot 107 -93,6 % -94,9 % -95,5 % -95,4 % -65,0 % -71,2 % -74,0 % -75,7 % 0,6 % -16,7 % -24,7 % -29,6 %

Smart fortwo -93,9 % -95,1 % -95,7 % -95,6 % -66,5 % -72,4 % -75,2 % -76,7 % -3,7 % -20,2 % -28,0 % -32,7 %

Mini Cooper R55 -94,8 % -95,8 % -96,3 % -96,2 % -71,2 % -76,2 % -78,6 % -80,0 % -17,3 % -31,2 % -38,0 % -42,2 %

Nissan Micra -95,0 % -96,0 % -96,4 % -96,4 % -72,6 % -77,4 % -79,7 % -81,1 % -21,4 % -34,7 % -41,1 % -45,4 %

Fiat Grande Punto

-95,0 % -96,0 % -96,5 % -95,8 % -72,8 % -77,5 % -79,9 % -77,8 % -21,8 % -35,0 % -41,7 % -35,9 %

Diesel

Citroen C1 -93,7 % -94,8 % -95,5 % -95,4 % -65,2 % -71,0 % -74,0 % -75,7 % 0,0 % -16,1 % -24,7 % -29,6 %

Peugot 206 -93,9 % -95,0 % -95,6 % -95,5 % -66,3 % -71,9 % -74,8 % -76,4 % -3,1 % -18,8 % -27,0 % -31,8 %

Fiat Panda -93,9 % -95,0 % -95,6 % -95,5 % -66,3 % -71,9 % -74,8 % -76,4 % -3,1 % -18,8 % -27,0 % -31,8 %

BMW E81 -94,0 % -95,1 % -95,7 % -95,7 % -67,1 % -72,6 % -75,5 % -77,0 % -5,4 % -20,7 % -28,8 % -33,5 %

VW Beetle -95,0 % -95,9 % -96,4 % -96,4 % -72,5 % -77,2 % -79,6 % -80,9 % -21,0 % -34,0 % -40,8 % -44,8 %

21

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.

22

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

Electricity

Norway

Th!nk City

Electricity

Switzerland

Th!nk City

Electricity

UK

Th!nk City

Electricity

The Netherlands

Th!nk City

Electricity

Hard Coal*

Model Normal

CO2

g/km

RushHour

CO2

g/km

CO2

g/km

%

Reduction

CO2

g/km

%

Reduction

CO2

g/km

%

Reduction

CO2

g/km

%

Reduction

CO2

g/km

%

Reduction

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 R55

204 269 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 Punto

216 285 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 %

23

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).

24

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

25

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.

26

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.

27

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.

28

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

capacity

cc

Transmission CO2

Emissions

g/km

Fuel

consumption

(l/100km)

Emission

factor

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 50 bhp

698 SM6 113 4,7 2,40

Mini Cooper

R55 Clubman

1598 M6 132 5,5 2,40

BMW X3 Series E83

2497 M6 224 9,3 2,41

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.

29

Annex II: Nordic Winter – Example of calculation sheet 5 degrees Celsius

UDC 30 min

Model Toyota Prius

Peugot 107

Smart for two

Nissan Micra

Fiat G. Punto

Mini Cooper

Peugot 206

VW Beetle

Fiat Panda

Citroen C1

BMW 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 Prius

Peugot 107

Smart for two

Nissan Micra

Fiat G. Punto

Mini Cooper

Peugot 206

VW Beetle

Fiat Panda

Citroen C1

BMW 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