Philip Dickemann

2024

Providing reliable data on carbon emissions is a challenge for every company involved in mandatory and voluntary sustainability reporting. Business customers concerned with their own carbon balance are increasingly pushing for low-carbon products. However, existing methods to determine product carbon footprints (PCFs) are time-intensive and imprecise. This paper explores the applicability of a “carbon machine hour rate” to determine PCFs within a vast modular product portfolio. The case study at a large international producer of drive-technology highlights that machine specific emission factors significantly improve the accuracy of emissions data compared to LCI databases. The method reduces the manual effort by integrating existing data, such as the bill of materials and work plan, from the company’s ERP system. The proposed solution accounts for direct and several indirect sources of CO2 emissions at the product-level, and calls for the implementation of carbon footprint features into ERP systems.