Abstract

Life cycle-based studies endorse public transport to cause lower environmental pressures compared to a private car. However, a private car can cause lower environmental pressure when a public vehicle (bus or train) runs on a lower occupancy during an off-peak hour. This fact should be the basis for a more profound debate regarding public versus private transport. Many transport interventions are striving to reduce the number of car transports. To reach this goal, passengers need attractive alternatives to their reduced number of car travels (i.e., attractive public transport). This study aimed to develop a model allowing us to estimate potential environmental gains by changing travel behavior. A passenger travel model was developed based on life cycle inventories (LCI) of different travel modes to calculate environmental footprints. The model was applied in an intervention of public transport through temporary free public transport. The intervention was successful in significantly reducing the number of car transports (12%). However, total passenger kilometer travelled (PKT) increased substantially more, mainly by bus, but also train, bicycle and walking. The total energy, carbon and nitrogen oxide footprints were slightly increased after the intervention. If the commuters were assumed to travel during peak hours or the number of public transports were not affected by the increased number of commuters, the overall environmental footprints decreased. Our conclusions are that transport interventions are very complex. They may result in desired changes, but also in altered travel behavior, increasing overall impact. Thus, a very broad evaluation of all transport modes as well as potential positive social influences of the transport intervention will be necessary.

Highlights

  • Climate change is considered one of the greatest global challenges that we are currently facing

  • EFc,i represents environmental footprints of a commuter where i represents indicator for environmental footprint, PKTC stands for passenger kilometer travelled by a commuter, EFd represents environmental footprint of an inventory for default parameter settings of the model, j represents each travel mode, k represents inventories related to vehicle manufacturing and maintenance, l represents inventories related to vehicle operation and infrastructure, O represents occupancy where d stands for default parameter values of the model, and LS represents life span of a vehicle

  • The Excel-based passenger travel model, which was developed for the present study, allows a user to calculate environmental footprints in a life cycle perspective for the user’s travel behavior

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Summary

Introduction

Climate change is considered one of the greatest global challenges that we are currently facing. The car-related emissions could decrease even further by shifting mode from private cars to public transport according to a recent study [8]. Various kinds of initiatives and interventions have been studied to assess modal shifts from car travel to public transport as well as to understand behavioral/psychological mechanisms for such changes [14,15,16,17,18]. A comparison of different travel modes in a life cycle perspective in the literature demonstrates that public transport has lower environmental pressures compared to those of a private car [22,23]. The present study attempts to develop a life cycle assessment-based passenger travel model (PTM) that can assess intervention effects or change of an individual passenger, company, institute, city or even country. Tehnitsawl-eoffiulcdiecnrteatrtaevaelb.eTttheer uprnodjeecrtstraunndsiningcoofohpoewratiinotnerbveetnwtieoennsScearnvibcee dReessieganrecdh Cfoernmteror(eCTenFe) ragtyK/eanrvlsitraodnmUennivtaelr-seiftfyicaienndt Dtreapvaerl.tmTehnetporfoSjeucsttariunnasblienDceovoepleorpamtioenntb, eEtnwveireonnSmeervnitcael SRceiseenacrechandCeEnntgeirne(eCrTinFg) (aStEEKDa)rlasttaKdTHUnRiovyearlsiItnystiatnudte oDfeTpeacrhtmnoelnotgyoSf toScukshtaoilnma,balendDceovllealbooprmateionnt, wEnitvhirtownomreengtioalnaSlcipeunbcleicatnrdanEsnpgoirnt eperroivnigde(SrsEEinDt)haetsKouTtHh aRnodywaleIsntsotfitSuwteeodfenT.echnology Stockholm, and collaboration with two regional public transport providers in the south and west of Sweden

Aims and Objectives Aims and Objectives
Temporary Free Public Transport Intervention
Results
Transport Mode Model
Conclusions
Full Text
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