A multi-dimensional KPI framework for evaluating urban mobility scenarios: Integrating air quality, climate, and equity metrics across three metropolitan areas

Evaluating urban mobility scenarios typically relies on single-metric assessments—CO2 reductions, modal shares, or air quality indices—that fail to capture trade-offs between environmental effectiveness, social equity, and policy feasibility. A scenario delivering maximum emission cuts may exacerbate inequalities; one prioritising accessibility may underperform on climate targets. Decision-makers need multi-dimensional frameworks that make these trade-offs explicit and comparable across contexts.

We present the Key Performance Indicator (KPI) framework developed within IMTECC (Integrated Multimodal Traffic Emissions Climate and Cities), a Sino-European collaboration funded by ANR, Innovation Fund Denmark, and NSFC, involving LISA-CNRS, University of Copenhagen, Aarhus University, Zhejiang University, and the Municipality of Copenhagen. The framework structures scenario evaluation across six pillars and fourteen sub-dimensions:

• Climate & Pollution: emission reductions, net-zero pathway alignment, public health impacts 
• Society & Lifestyles: behavioural shifts, inequality trends 
• Mobility & Transport: pricing and incentives, multimodality, infrastructure upgrades 
• Technology & Innovation: low-emission vehicle penetration, ITS optimisation 
• Governance & Policy: master plan integration, low-emission zone implementation 
• Territorial: urban typology coherence, innovation cluster development 

This structure enables systematic cross-city comparison between Paris (OLYMPUS-CHIMERE platform), Copenhagen (COMPASS transport model), and Hangzhou, despite differences in modelling approaches and local policy contexts.

For the Paris metropolitan area, four scenarios at the 2035 horizon are evaluated against this KPI matrix:
• Scenario A (Reference): Baseline trajectory. 
• Scenario B (Densification): 220,000 inhabitants and 140,000 jobs relocated within 800m of Grand Paris Express stations. 
• Scenario C (LEZ + Electrification): 50% electric vehicle target with reinforced emission standards. 
• Scenario E1 (Progressive LEZ + Equity): Gradual implementation with social support for vulnerable households.

The KPI matrix reveals differentiated scenario profiles. Scenario C scores highest on climate & pollution indicators (emission reductions, net-zero alignment) but neutral on inequality trends. Scenario B shows balanced performance across territorial coherence, multimodality, and master plan integration. Scenario E1 achieves the strongest score on inequality trends while maintaining moderate climate performance—demonstrating that equity need not be sacrificed for environmental ambition.

Cross-pillar analysis exposes synergies and tensions: scenarios combining electrification with densification (B+C hybrid) could maximise both climate and territorial scores, while pure technology-push approaches (C alone) leave behavioural and equity dimensions unaddressed. A composite sustainability index weighting GHG emissions, travel times, population exposure, exposure inequalities, and non-fossil energy share is proposed to support multi-criteria decision-making. This KPI-based approach, aligned with the Integrated Urban System framework promoted by the World Meteorological Organization, offers a replicable methodology for evidence-based urban climate governance.