Transportation Research Part D 13 (2008) 315–322

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Transportation Research Part D

journal homepage: www.elsevier .com/ locate/ t rd

Use of ecological footprinting to explore alternative transport policyscenarios in an Irish city-region

David Browne a,*, Bernadette O’Regan b, Richard Moles c

a Department of Transport, 44 Kildare Street, Dublin 2, Irelandb Centre for Environmental Research, Foundation Building, University of Limerick, Castletroy, Irelandc Chemical and Environmental Sciences Department, University of Limerick, Castletroy, Ireland

a r t i c l e i n f o

Keywords:Ecological footprinting

Sustainable travelSpatial planningScenario analysisSustainable urban development

1361-9209/$ - see front matter � 2008 Elsevier Ltddoi:10.1016/j.trd.2008.03.009

* Corresponding author.E-mail address: davidbrowne@transport.ie (D. Br

a b s t r a c t

The objective of this paper is to compare the ecological footprint for travel-commuting pat-terns for the residents of an Irish city-region, that is Limerick city-region, in 1996 and 2002.Scenario building, based on ecological footprint analysis, is used to estimate the impact ofdifferent policy choices for 2010. The optimal policy mix for sustainable travel is proposedand consists of a mix of reduced demand through travel demand measures, better spatialplanning and technological improvements in fuel economy.

� 2008 Elsevier Ltd. All rights reserved.

1. Introduction

The concept of sustainable travel and transport is embedded in the broader concept of sustainable development, whichrelates to maintaining or improving the quality of human life and variety of social opportunities within the natural con-straints and limits of the global ecosystem. According to the 1997 Irish Sustainable Development Strategy, sustainable trans-port (Department of Environment and Local Government, 1997):

� Helps to preserve the natural environment by minimising emissions of pollutants and careful land use planning to addressthe impact of transport infrastructure.

� Reduces environmental impacts and contributes to economic prosperity and development by maximising transportefficiency.

� Enhances social well-being by providing access and mobility to urban and rural populations and by reducing health risksand noise nuisance.

The Organisation for Economic Cooperation and Development (2004) defines an environmentally sustainable transportsystem as ‘‘one where transportation does not endanger public health or ecosystems and meets needs for access consistentwith use of renewable resources below their rates of regeneration and use of non-renewable resources below the rates ofdevelopment of renewable substitutes”. Thus, a sustainable transport system should improve quality of life and ease ofaccess or mobility for all individuals; internalise the negative impacts of transport through appropriate pricing mechanisms;preserve natural resources for future generations through the development of renewable fuels, maintenance and enhancement

. All rights reserved.

owne).

316 D. Browne et al. / Transportation Research Part D 13 (2008) 315–322

of biodiversity and reduction of emissions; and enhance economic competitiveness and support a knowledge economy(Gudmundsson and Hojer, 1996).

More recently the concept of sustainable travel has emerged to focus on individual behaviour and smarter choices ratherthan just on the provision of physical infrastructure or transport systems. It ostensibly involves encouraging people to makeinformed choices about the way they travel and the consequences of those choices on their health and the environment. Theobjective of this paper is to use the ecological footprint (EF) to assess travel-commuting patterns in an Irish city-region in1996 and 2002 and to develop a range of policy scenarios that offer potential measures to reduce the environmental impactof commuting.

2. Ecological footprint analysis

The EF may be defined as the ‘‘total area of productive land and water required continuously to produce all the resourcesconsumed and to assimilate all the wastes produced by a defined population, regardless of where that land is located” (Reesand Wackernagel, 1996). It aims to determine ‘‘to what extent human load is within the present regenerative capacity of thebiosphere or natural capital interest” (Haberl et al., 2001).

An EF is an aggregate measure of the land footprint required to produce natural resources and support infrastructure, andthe carbon footprint or land required to sequester the carbon emissions generated in production, transport, and waste assim-ilation. The carbon footprint is estimated by calculating the embodied energy associated with consumption using energyanalysis, that is the amount of energy consumed during the full life cycle of extraction, production, delivery and disposalof a specified good or service and subsequent conversion into CO2-equivalents (Brown and Herendeen, 1996).

The carbon footprint component of an aggregate EF may be calculated using energy analysis, that uses either processanalysis or input–output (IO) analysis, or a hybrid life cycle assessment (LCA) approach that combines process and IO anal-ysis (Lave et al., 1995; Nishimura et al., 1996). In process analysis, the energy requirements and GHG emissions of the mainprocesses are assessed within the context of a system boundary with impacts across the full life cycle being considered usingbottom-up data (Benders et al., 2001). IO analysis is a top-down macroeconomic technique, which uses sectoral monetarytransactions matrices describing complex interdependencies of industries to trace resource requirements and pollutant re-leases throughout the whole economy (Lenzen and Treloar, 2002).

The basic EF is an additive model of different land uses, which are mutually exclusive uses of bioproductive areas. Theseland areas are then normalised to give standardised units of biologically productive area, termed global hectare (Gha), bymultiplying them by equivalence and yield factors, thus allowing for construction of a consumption-land use matrix (Monf-reda et al., 2004). The inputs for EF analysis include the land area required to produce resources and assimilate wastes asso-ciated with material and product consumption, land area required for use of services and infrastructure such as housing andtransport, land area appropriated for carbon sequestration, and yield and equivalence factor ratios.

The strengths of EF analysis are that it is conceptually simple and allows for comprehensive and comparative analyses; itprovides an effective heuristic tool; it promotes discussion on the ecological consequences of increasing consumption pat-terns; and it may be used to monitor progress towards closing the sustainability gap by use in a time-series (Van den Berghand Verbruggen, 1999; Van Vuuren and Smeets, 2000; McDonald and Patterson, 2004). However, it also has a number of sig-nificant weaknesses as a sustainability metric tool (Van den Bergh and Verbruggen, 1999; Senbel et al., 2003).

The EF is regarded as a measure of sustainability because it assesses the utilisation of the environment in physical termsand compares the extent of resource use with resource availability. Thus, it may be used to measure the size of the physicaleconomy as well as demonstrating ‘overshoot’ or ecological deficit, which is the amount that resource requirements exceedbioavailability (Haberl et al., 2001).

3. Results

The population of Limerick City and its environs is taken as a case study. The region is the primary urban centre in theMid-West region in the Republic of Ireland and its population increased by 10% from 1996 to 2002 to 86,998 in 2002 (CentralStatistics Office, 2003).

The carbon footprint of daily personal travel is defined as

ðFEþ UFÞ=CS � EF ð1Þ

where FE is the fuel emissions (gCO2 per vehicle-kilometre), UF is an uplift factor, defined as the energy required for man-ufacturing and maintenance (gCO2 per vehicle-kilometre), CS is the carbon sequestration (tonnes Carbon per hectare perannum), and EF is the equivalence factor of 1.38 for energy land.

The land footprint is

ðARI � EF � VRSÞ=TDT ð2Þ

where ARI is the area of road infrastructure or land required for transportation (hectare), EF is the equivalence factor of 2.19for built environment and road infrastructure, VRS is vehicle road share (%), and TDT is the total distance travelled (vehicle-kilometres).

D. Browne et al. / Transportation Research Part D 13 (2008) 315–322 317

Total EF is

Table 1Daily p

FootBicycleBusTrainMotorcMotor cOther/n

Total

Table 2PrivateHeritag

Alfa RoAudiBMWChrysleCitroenDaewooDaihatsFiatFordHondaHyundaIsuzuJaguarKiaLexusMazdaMercedMitsubNissanOpelPeugeoRenaultRoverSaabSeatSkodaSubaruSuzukiToyotaVolkswVolvoOthers

Total

ðCFþ LFÞ=AVOR ð3Þ

where CF is the carbon footprint (Gha per vehicle-kilometre), LF is the land footprint (Gha per vehicle-kilometre), and AVORis the average vehicle occupancy rate.

Daily passenger-miles are found by multiplying the number of people by the median of each distance band for each modeof travel to work, school or college for persons aged 5 and over and were then converted to passenger-kilometre (Table 1)(Central Statistics Office, 1998, 2003). Modal split is estimated the percentage of passenger-miles for each mode relative tototal passenger-miles. Comparing the figures in the table with national data, passenger-kilometres in the region grew less;the national average passenger-kilometre from 2.8 per capita in 1996 to 3.9 per capita in 2002 (Central Statistics Office,2004).

Table 2 offers information on the number of private cars licensed in Limerick city and its environs and the average CO2

emissions per make and model. Passenger-kilometre per make of car was estimated by applying the percentage of carslicensed per model to daily passenger-kilometre. Table 3 shows the CO2 emissions per make of car for 1996 and 2002 based

assenger-miles and percentage modal travel in Limerick city and its environs, 1996 and 2002 (Central Statistics Office, 1998, 2003)

1996 daily passenger-miles 1996 modal split (%) 2002 daily passenger-miles 2002 modal split (%)

24,564 13.6 25,584 11.35986 3.3 3892 1.723,053 12.7 20,572 9.1977 0.5 1377 0.6

ycle 936 0.5 2068 0.9ar 117,315 64.8 165,361 73.2ot stated 8211 4.5 6911 3.1

181,040 – 225,765 –

cars licensed in Limerick city and its environs in 1996 and 2002 and emissions associated with car model (gCO2/km) (Department of the Environment,e and Local Government, 2003, 2004)

1996 1996% 2002 2002% Average CO2 emissions (g/km)

meo 32 0.15 142 0.49 203.7298 1.44 376 1.31 205.4233 1.12 486 1.68 232.4

r 5 0.02 28 0.1 239.2243 1.17 446 1.54 157– – 261 0.9 206.4

u 216 1.04 120 0.42 155.1380 1.83 1239 4.29 157.54316 20.8 4232 14.64 170.9510 2.46 813 2.81 186.4

i 116 0.56 890 3.08 19128 0.14 11 0.04 275.3– – 29 0.1 245.3– – 24 0.08 193.7– – 18 0.06 259.3611 2.9 630 2.18 199.8

es Benz 270 1.3 548 1.9 223.3ishi 511 2.46 612 2.12 211.8

2357 11.35 2728 9.44 191.91909 9.19 3072 10.63 164.6

t 857 4.13 1120 3.88 167.8898 4.32 1755 6.07 174.7359 1.73 624 2.16 197.161 0.29 153 0.53 197.1137 0.66 366 1.27 168.275 0.36 380 1.32 169.272 0.35 62 0.22 208.9150 0.72 256 0.89 175.53682 17.73 4306 14.9 180.7

agen 1211 5.83 2591 9 171.3468 2.25 388 1.3 214.2760 3.66 195 0.7 263.1

20,765 – 28,901 198.7

Table 3Emissions estimated from daily passenger-kilometre and modal split (gCO2)

1996 passenger-kilometre 1996 CO2 emissions (g) 2002 passenger-kilometre 2002 CO2 emissions (g)

Alfa Romeo 291 59,218 1306.7 266,131Audi 2709 556,561 3486.2 716,170BMW 2118 492,205 4470.9 1,038,834Chrysler 45 10,839 266.1 63,659Citroen 2,209 346,870 4098.3 643,523Daewoo – – 2395.1 494,236Daihatsu 1964 304,539 1104.4 171,294Fiat 3455 544,128 11,416.6 1,798,007Ford 39,242 6,705,623 38,960.3 6,657,534Honda 4637 864,439 7478 1,394,100Hyundai 1055 201,578 8196.6 1,565,544Isuzu 255 70,164 101.1 27,839Jaguar – – 266.1 65,2745Kia – – 212.9 41,247Lexus – – 165 42,782Mazda 5551 1,109,190 5801.5 1,159,307Mercedes Benz 2454 547,999 5056.3 1,128,945Mitsubishi 4644 983,710 5641.8 1,194,954Nissan 21,429 4,111,676 25,122 4,820,347Opel 17,351 2,856,734 28,288.8 4,657,693Peugeot 7792 1,307,448 10,312.2 1,730,393Renault 8156 1,424,688 16,153.6 2,821,682Rover 3266 643,829 5748.2 1,133,081Saab 555 109,406 1410.5 278,006Seat 1246 209,543 3369.1 566,559Skoda 682 115,289 3499.5 591,956Subaru 655 136,828 572.2 119,500Suzuki 1363 239,193 2357.8 413,740Toyota 33,478 6,050,859 39,652.2 7,166,859Volkswagen 11,011 1,886,300 23,857.9 4,087,208Volvo 4248 909,718 3566 763,681Others 6910 1,817,721 1796.3 472,534

Total 188,798 34,616,292 266,122 48,092,630

318 D. Browne et al. / Transportation Research Part D 13 (2008) 315–322

on the product of average CO2 emissions per car manufacturer per kilometre and passenger-kilometre per car make. Thus,daily CO2 emissions were estimated to have increased from 437 g per Limerick resident in 1996 to 553 in 2002.

The uplift factor is estimated as 45% of the emissions associated with 1 passenger-kilometre, including 15% for energyrequired for vehicle maintenance and 30% for construction and maintenance of road infrastructure (Birch et al., 2004).CO2 emissions were 183 g per passenger-kilometre in 1996 and 181 g per passenger-kilometre in 2002. Thus, the uplift fac-tor was 83 g CO2 per passenger-kilometre in 1996 and 81 g CO2 in 2002.

Average car occupancy rates for urban travel in Ireland are 1.45 and urban travel occupancy rate of buses is 35 (Goodbody,2000). The average percentage of heavy commercial vehicles (HCV) on roads, as shown in Table 4, is used to estimate per-centage road share of other vehicles. The area of the Irish road network was 84,950 ha in 1996 and 85,009 in 2002 (NationalRoads Authority, 2003; Directorate-General for Energy and Transport (DG-TREN), 2005; Highways Agency, 2005).

The average number of vehicle-kilometre travelled by car is 19,864 km per annum (National Roads Authority, 2003) andthe number of private cars licensed in 1996 was 1,057,383 increasing in 2002 to 1,447,908 and car-kilometres 21 bn in 1996and 28.8 bn in 2002 (Department of the Environment, Heritage and Local Government, 2003). Table 5 shows the car road-hectare per car-kilometre for 1996 and 2002. The 1996 EF for daily car personal transport by Limerick residents is estimatedto be 0.000021 Gha per passenger-kilometre. The 2002 EF for daily car personal transport is 0.00002 Gha per passenger-kilo-metre. Car passenger-kilometre travelled by Limerick residents per day were 2.4 per capita in 1996 and 3.1 per capita in2002. Thus, the carbon footprint for personal car travel for 1996 was estimated to be 0.0147 Gha per capita. The carbon

Table 4Average heavy commercial vehicle (HCV)% road share on Limerick access roads, 1996 and 2002 (National Roads Authority, 2003)

1996 HCV (% of road share) 2002 HCV (% of road share)

N7 14.5 12.1N18 11.7 8.4N20 11.7 7.8N24 16.1 10.5N69 11.3 8.4

Average 13.1 9.4

Table 5Car-road hectare, 1996 and 2002

1996 2002

Road share of vehicles other than HCV (%) 86.9 90.6Ratio of car passenger-kilometre to bus passenger-kilometre 84% 89%Car road share 0.73 0.81Car road hectare 62,039 68,483Bus road hectare 11,817 8516

Car road-hectare per Car-kilometre 0.000003 0.0000024

D. Browne et al. / Transportation Research Part D 13 (2008) 315–322 319

footprint for personal car travel for 2002 was estimated to be 0.0185 Gha per capita and the annual EF for car travel was0.0184 Gha per capita in 1996.

The EF was also calculated for other forms of travel including bus, motorcycle, train and cycling. The conversion factor forbus travel in Northern Ireland was calculated to be 0.000019 Gha per passenger-kilometre (George and Dias, 2005) and thiswas used for Limerick personal bus use, as local settlement-specific data were not available for both years. Daily passenger-miles by bus were 23,053 in 1996 and 20,572 in 2002 from Small Area Population Statistics data (Table 1). Thus, annual pas-senger-kilometre by bus were 13,540,912 and 12,083,803 in 1996 and 2002, respectively, and annual passenger-kilometreper capita Limerick resident were 171.1 and 138.9 giving an EF of bus travel was 0.0033 Gha per capita in 1996 and0.0026 Gha 2002.

A conversion factor of 0.0000207 Gha per passenger-kilometre was adopted for motorcycles (Barrett and Scott, 2001).Daily passenger-miles by motorcycle were 936 in 1996 and 2068 in 2002 from Small Area Population Statistics date. Annualpassenger-kilometre were 549,801 and 1,214,796 and the annual passenger-kilometre per capita Limerick resident were6.95 in 1996 and 13.96 in 2002. Therefore, the EF of motorcycle travel was 0.00014 Gha per capita in 1996 and0.00029 Gha in 2002.

The conversion factor for train travel is estimated at 0.000023 Gha per passenger-kilometre (George and Dias, 2005). Thiswas used for Limerick personal rail use, as local settlement-specific data were not available for both 1996 and 2002. Daily pas-senger-miles by train were 977 in 1996 and 1377 in 2002 from SAPS data. Thus, annual passenger-kilometre by train were573,884 in 1996 and 809,077 in 2002 and annual passenger-kilometre per capita Limerick resident were 7.25 in 1996 and9.3 in 2002. Therefore, the EF of train travel was 0.00017 Gha per capita in 1996 and 0.00021 Gha per capita in 2002.

The energy required for maintenance and manufacture of bicycles is 0.06 MJ/km, which equates to 0.0048 kg of CO2 perkm (Barrett et al., 2001). Daily passenger-miles by cycling were 5986 in 1996 and 3892 in 2002 from SAPS data. Annual pas-senger-kilometre were 3,516,144 in 1996 and 2,286,045 in 2002 and annual passenger-kilometre per capita Limerick resi-dent were 44.4 in 1996 rising to 26.3 in 2002 resulting in CO2 emissions associated with cycling were 0.213 kg per capitain 1996 and 0.126 kg per capita in 2002. Assuming a sequestration rate of 6 tonnes of carbon per hectare, a stoichiometricratio of (12/44) for carbon to CO2 and an equivalence factor of 1.38, this gives an EF of 0.000013 Gha per capita in 1996 and0.0000079 Gha in 2002.

The EF for passenger transport per capita Limerick resident increased by 14% between 1996 and 2002. Fig. 1 shows the EFper transport mode for 1996 and 2002 in Gha per capita. The percentage of car travel increased from 83% in 1996 to 88% in2002, while that by bus fell from 15% to 10%.

4. Transport policy scenario analysis

4.1. Scenario 1 – Business as Usual (BAU)

CO2 emissions per passenger-kilometre fell from 183 g in 1996 to 181 g in 2002 and are estimated to be 177 g in 2010 dueto BAU vehicle efficiency improvements. Road area is estimated to be 85,122 hectare in 2010 and car road-hectare are esti-mated to be 68,575. Private cars licensed in 2010 are predicted to be 1,955,725 and car-kilometre are estimated to be slightlyover 38,848 million giving 0.000001765 road-hectare per kilometre. The 2010 daily EF for car personal transport, under theBusiness as Usual (BAU) scenario, is 0.0000188 Gha per passenger-kilometre, The EF for bus travel is predicted to fall to0.0018 Gha per capita by 2010 and for motorcycle travel is predicted to increase to 0.00048 Gha per capita. The EF for traintravel is predicted to increase to 0.000275 Gha per capita and daily cycling passenger-kilometre to fall to 0.00002 Gha percapita in 2010. Thus under the EF under a BAU scenario, the EF will increase by 30% over the 2002 figure to 0.0326 Ghaper capita in 2010.

4.2. Scenario 2 – Business as Usual (BAU) with increased car occupancy

Taking the algorithm for estimated EF for 2010 and, assuming increased car occupancy of three persons per vehicle, a con-version factor of 0.0000174 Gha per daily passenger-kilometre was calculated. Assuming daily passenger-kilometre are 4.3per capita, this gives an annual EF for car travel of 0.0273 Gha per capita and a predicted decrease in EF of 8% to 0.03 Gha percapita by 2010.

0

0.005

0.01

0.015

0.02

0.025

0.03

Car Bus Motorcycle Train Cycling Total

Gha

per

Cap

ita

1996 2002

Fig. 1. EF of personal travel per mode of transport, 1996 and 2002 (Gha per capita).

320 D. Browne et al. / Transportation Research Part D 13 (2008) 315–322

4.3. Scenario 3 – increased engine efficiency to 140 g CO2/km

The 2010 EF for car personal transport for emissions at 140 g CO2/km is estimated to be 0.0000154 Gha per passenger-kilometre. Assuming again that daily passenger-kilometre are 4.3 per capita, this gives daily emissions of 602 g per Limerickresident or 57,614 kg, based on an estimated population of 95,704 in 2010. The annual EF for car travel is thus 0.0242 Ghaper capita leading to a decrease of 18% compared to the BAU scenario for 2010.

4.4. Scenario 4 – reduction of 2002 car passenger-kilometres per capita by 20%

This scenario assumes a reduction of 20% of 2002 car passenger-kilometre per capita by 2010. CO2 emissions per passen-ger-kilometre fell from 183 g in 1996 to 181 g in 2002 and are estimated to be 177 g in 2010 due to vehicle efficiencyimprovements. The 2010 daily EF for car personal transport is, therefore, estimated to be 0.0000188 Gha per passenger-kilo-metre and the EF for car travel is estimated to be 0.017 Gha per capita in 2010; a decrease of 23% from the 2002 EF for cartravel. The EF is predicted to be 0.0196 Gha per capita in 2010, assuming there was a modal shift of 20% from car to walkingdue to better spatial planning and integration of investment with land use planning.

4.5. Scenario 5 – reduction of 2002 car passenger-kilometres per capita by 10% and increased engine efficiency to 120 g CO2/km

Here we assume a reduction of 10% in car passenger-kilometre per capita between 2002 and 2010 and increased engineefficiency to an average of 120 g CO2/km for new passenger cars based on the proposed European Union legislative target of130 g/km to be achieved though improvements in engine technology and an additional 10 g/km through supply-orientedmeasures include air-conditioning systems, tyre pressure monitoring systems, standards for the rolling resistance of tyres,gear shift indicators, fuel-efficiency progress in light-commercial vehicles and sustainable biofuels (European Commission,2007). The scenario is predicated on fuel economy standards, which are not likely to be introduced until 2012, and theassumption that full fleet replacement will have taken place. The EF per passenger-kilometre in 2010 for emissions at120 g CO2/km is 0.0000136 Gha. The 2010 daily EF for car personal transport is, therefore, predicted to be 0.0000188 Ghaper passenger-kilometre and the EF for car travel is predicted to be 0.0138 Gha per capita in 2010. The EF is predicted tobe 0.0164 Gha per capita in 2010, assuming there is a modal shift of 10% from car to non-motorised forms of transport, withno additional environmental impact, and increased engine efficiency.

4.6. Scenario 6 – biofuels substitution of 5.75% for transport fuels

Estimates of reduction of GHG emissions from production and combustion of biofuels compared to fossil fuels per averagekilometre are given in Table 6, based on energy consumed over the life cycle or ‘well to wheel’. CO2 emissions per passenger-kilometre fell from 183 g in 1996 to 181 g in 2002 and are predicted to be 177 g in 2010 due to BAU vehicle efficiencyimprovements.

Table 6Percentage reduction of GHG emissions of various biofuel feedstocks compared to fossil fuels (International Energy Agency 2003)

Biofuel feedstock and conversion process Percentage reduction

Ethanol from corn 38Ethanol from wheat 29Ethanol from sugar beet 41Ethanol from wood 51Ethanol from grass 71Ethanol from straw crop residue 82Ethanol from hay 68Biodiesel from rapeseed 38Biodiesel from soybeans 53Diesel from biomass through gasification and Fischer–Tropsch synthesis 108Diesel from biomass through pyrolysis 64Dimethyl ether (DME) from biomass through gasification 89Reduction and compressed natural gas from biomass through gasification 83

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

1996 2002 Scenario 12010

Scenario 22010

Scenario 32010

Scenario 42010

Scenario 52010

Scenario 62010

Eco

logi

cal F

ootp

rint

(G

ha p

er C

apita

)

Fig. 2. Comparison of per capita EF (Gha per capita).

D. Browne et al. / Transportation Research Part D 13 (2008) 315–322 321

Assuming substitution of 5.75% of fossil fuels for transport on a ‘neat fuel comparison basis’ by biodiesel from rapeseedfeedstock, this gives emissions of 173 g CO2 per passenger-kilometre based on a 38% reduction of the life cycle GHG emis-sions associated with the 5.75% of the biodiesel blend.1 The 2010 EF for car personal transport per passenger-kilometre, basedon these assumptions is 0.0000184 Gha implying EF for car travel of 0.0289 Gha per capita.

5. Conclusions

This paper used the EF to explore different policy scenarios for travel-commuting patterns in an Irish city-region. It wasfound that the EF for passenger transport per capita Limerick resident increased by 14% from 0.022 Gha per capita in 1996 to0.025 Gha per capita in 2002. Fig. 2 provides a comparative analysis of per capita EF under each scenario we examined and itmay be seen that Scenario 1, the BAU scenario, has the highest EF. Scenario 5, which involves a reduction of 2002 car pas-senger-kilometre per capita by 10% and increased engine efficiency to 120 g CO2/km, has the lowest EF and may be regardedas the optimal scenario.

Although increasing fuel economy and substitution of alternative or renewable fuels certainly have the potential to re-duce greenhouse gas emissions from the transport sector, a long-term sustainable transport system necessitates a paradigmshift towards ‘smarter travel’ and more efficient use of the physical system which requires a reduction in overall demand. In

1 It is also based on the European Union’s ‘Biofuels Directive’ (Directive 2003/30/EC), requiring all EU Member States substitute 5.75% of transport fossil fuelswith renewable fuels derived from ‘biogenic material’ by 2010.

322 D. Browne et al. / Transportation Research Part D 13 (2008) 315–322

addition, reducing use of the private car and/or considering switch of transport mode has other benefits such as reduced con-gestion, lower obesity levels, increased safety, and lower localised air pollution. The results of the scenario analysis show thatreduced demand and technological improvements in fuel economy are the optimal policy mix, which indicates that no onepolicy strategy is a panacea for sustainable transport.

Acknowledgements

The authors wish to gratefully acknowledge the funding assistance, awarded by the Irish Research Council for Science,Engineering and Technology under the Embark Initiative of the Irish National Development Plan 2000–2006.

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