Methodology for the Life Cycle Assessment of a Car-sharing Service

Abstract: Nowadays, circular economy is becoming more relevant in society. In the context of the automotive industry, we no longer simply work on emissions emitted during the vehicle use phase but rather on the environmental impacts induced during all phases of the vehicle's life cycle (manufacturing, logistics, use, maintenance and end of life). For this purpose, many automakers, including the Group PSA, use life cycle assessment (LCA) to determine these environmental impacts. Also, the economy of sharing is gradually established and follows innovative uses of the car. New mobility systems emerge and compete with the classical system of sales of vehicles. These new uses of the automobile mainly take the form of car-sharing. In the future, it will become essential to evaluate these services from an environmental point of view.Some studies of the use of car-sharing already demonstrate important consequences such as reductions in the number of vehicles and in the number of kilometers traveled but also an increase in the use of other means of transport. However, to my knowledge, there is no LCA-based method to quantify the environmental benefit of the use of a car-sharing service in relation to the use of vehicles for exclusive use by the owner but also which would eco-design these services and the vehicles intended for these services.As part of this six-month project, a LCA approach was implemented to a PSA B2C (business-to-consumers) car-sharing service called “Emov” with a fleet of 500 Citroën C-Zero electric vehicles. The goal was to compare the use of Emov in Madrid, Spain with the urban use of a private Internal Combustion Engine (ICE) vehicle and a battery electric vehicle for one user characterized by its frequency, its average time and its average distance of use over a defined period. Thanks to a modeling of the service on the LCA software Gabi and by controlling over the input parameters related to the Emov service and the parameters related to the user's use of the service (variable parameters), it was therefore possible to show the influence of these parameters on the final results. Furthermore, it was possible to show also in which scenario it was more environmentally beneficial to use the service rather than a private vehicle. For the study, six impact indicators were chosen: the potentials for global warming, photochemical oxidation, air acidification, water eutrophication, resource depletion and primary energy demand.Using Emov’s big data to inform the service parameters and then varying the service user's usage parameters, it was possible to conclude that whatever the user's urban mobility needs, it is more beneficial to use the service than a private ICE vehicle for five of the six impact indicators. Only the acidification potential indicator (SO2 equivalent) is worse when using the service, which can be explained by the manufacture of the batteries of the Emov vehicles.