Decarbonisation Index (DCI): an LCA-based key performance indicator for the automotive industry

Purpose Road vehicles cause considerable amounts of CO 2 e emissions over their life cycle. Original equipment manufacturers (OEMs) report CO 2 e emissions of past years on corporate level according to the Greenhouse Gas (GHG) Protocol and produce vehicle LCAs to identify GHG hotspots on the product...

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Bibliographic Details
Published in:The international journal of life cycle assessment 2024-04, Vol.29 (4), p.557-577
Main Authors: Neef, Mara, Dettmer, Tina, Bäuml, Georg, Schebek, Liselotte
Format: Article
Language:English
Subjects:
Automobile industry
Automobiles
Business metrics
Carbon Footpprinting
Company structure
Decarbonization
Earth and Environmental Science
Ecological footprint
Emissions
Environment
Environmental Chemistry
Environmental Economics
Environmental Engineering/Biotechnology
Greenhouse effect
Greenhouse gases
Life cycles
Modelling
Monte Carlo simulation
OEM
Powertrain
Renewable energy sources
Steering
Supply chains
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Summary:Purpose Road vehicles cause considerable amounts of CO 2 e emissions over their life cycle. Original equipment manufacturers (OEMs) report CO 2 e emissions of past years on corporate level according to the Greenhouse Gas (GHG) Protocol and produce vehicle LCAs to identify GHG hotspots on the product-level. However, no approach to combine this past and future orientation of emissions modelling on fleet and product level yet exists. We demonstrate that this research gap is closed by using the “Decarbonisation Index” (DCI). Methods We identify the missing elements of OEMs’ absolute emissions reporting and vehicle LCAs to develop a resource-efficient, dynamic and modular key performance indicator (KPI) addressing both past and future scope 1–3 GHG emissions of OEMs. We assess in how far other existing approaches such as the Organisational LCA (O-LCA), the Organisation Environmental Footprint (OEF) and modular LCA can be used to develop these missing elements in a holistic modelling approach. After the derivation of the DCI, we provide a list of modelling options and data sources showing that the DCI can serve different means of an OEM, from a rough estimate of emissions to a basis for a detailed decarbonisation steering model involving several brands and departments. Results and discussion In the case study, we compute a 2015 and 2035 DCI (in t CO 2 e per vehicle) by using the basic DCI calculation model and publicly available data of the Volkswagen Group as well as data derived from publicly available scenarios. We demonstrate that even with this simplistic approach, the DCI delivers meaningful results indicating the core measures for an OEM’s decarbonisation programme: an electrified fleet with renewable energy sources being used throughout the supply chain and use phase. A Monte Carlo simulation of the 2015 results demonstrate the DCI’s robustness regarding the identification of core measures but also its dependency on changing (external or internal) methodological requirements. Conclusions The DCI can be used by OEMs regardless of their company structure, powertrain portfolio or market coverage to monitor past emissions and model future emissions. The DCI combines the product-level of the vehicle LCA with the fleet-level necessary to develop a decarbonisation strategy. Its modular approach facilitates the use of generic LCA data or supplier-specific data on component level. Incrementally incorporating supplier-specific data is crucial to calculate the effe
ISSN:0948-3349
1614-7502
DOI:10.1007/s11367-023-02247-w