Climate Scenarios in the Automotive Sector : A Comprehensive Analysis and Selection Framework
Year: 2024
Type: dissertation
Abstract: Climate change is the most fundamental challenge for industries today, including the automotive sector. To push the necessary transformation, the European Union has adopted the Corporate Sustainability Reporting Directive, in line with the Paris Agreement 1.5°C target. It mandates companies to conduct an indepth climate scenario analysis, highlighting the need of selecting feasible scenarios. The present thesis aimed to identify the most relevant climate scenarios for the automotive industry to provide recommendations. An analysis of ratings identified climate scenarios applied in the automotive sector. The most pertinent organisations for scenario development are the Intergovernmental Panel on Climate Change (IPCC), the International Energy Agency (IEA), the International Renewable Energy Agency (IRENA), and the Network for Greening the Financial System (NGFS). Based on an extensive literature review, criteria for selecting feasible criteria were identified, and scenarios from these organisations, aligned with the 1.5°C target, were rated against these criteria. Two case studies determined the weighting of the criteria to account for an internal stakeholder perspective (Volkswagen Group) and an external perspective (Greenpeace). The results demonstrate that four scenarios – the IEA Net Zero Emissions 2050, IPCC's Illustrative Mitigation Pathways Ren and LD, and IRENA's 1.5 Pathway – have the largest overlap from both viewpoints. Net Zero Emissions 2050 and IMP-Ren scenarios rank highest. A sensitivity analysis confirmed the robustness of the methodology and findings. Adopting these recommended scenarios positions manufacturers as leaders in the transition towards a low-carbon economy and sustainable mobility solutions, mitigating risks and driving innovation.
Author: Kramer, Okka
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7036735173