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According to the Intergovernmental Panel on Climate Change (IPCC), in 2010 the transport sector was responsible for 23% of the total energy-related CO 2 emissions (6.7 GtCO 2 ) worldwide. Policy makers in Luxembourg are well-aware of the challenges and are setting ambitious objectives at country level for the mid and long term. However, a framework to assess environmental impacts from a life cycle perspective on the scale of transport policy scenarios, rather than individual vehicles, is lacking. We present a novel framework linking activity-based modeling with life cycle assessment (LCA) and a proof-of-concept case study for the French cross-border commuters working in Luxembourg. Our framework allows for the evaluation of specific policies formulated on the trip level as well as aggregated evaluation of environmental impacts from a life cycle perspective. The results of our proof-of-concept-based case study suggest that only a combination of: (1) policy measures improving the speed and coverage of the public transport system; (2) policy measures fostering electric mobility; and (3) external factors such as de-carbonizing the electricity mix will allow to counteract the expected increase in impacts due to the increase of mobility needs of the growing commuting population in the long term.

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The urgency of tackling global environmental issues calls for radical technological and behavioral changes. New prospective (or ex ante) methods are needed to assess the impacts of these changes. Prospective life cycle assessment (LCA) can contribute by detailed analysis of environmental consequences. A new stream of research has taken up the challenge to create prospective life cycle inventory (LCI) databases, building on projections of integrated assessment models to describe future changes in technology use and their underlying environmental performance. The present work extends on this by addressing the research question on how to project life cycle impact assessment methods for water scarcity consistent with prospective LCI modeling. Water scarcity characterization factors are projected from 2010–2050 using the AWARE method, based on SSP‐RCP scenario results of the integrated assessment model IMAGE. This work is coupled with prospective LCI databases, where electricity datasets are adapted based on the energy component of IMAGE for the same scenario. Based on this, an LCA case study of water desalination for the steel industry in Spain is presented. The resulting regional characterization factors show that some regions (i.e., the Iberian Peninsula) could experience an increase in water scarcity in the future. Results of the case study show how this can lead to trade‐offs between climate change and water scarcity impacts and how disregarding such trends could lead to biased assessments. The relevance and limitations are finally discussed, highlighting further research needs, such as the temporalization of the impacts.