Recent Challenges in Data Acquisition for Scope 3 Activities in Germany: A Case Study at a Scientific Institute Operating a Production Line

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:This study offers a methodological approach for automating Scope 3 data collection and sensitivity analysis of emission factors, useful for carbon accounting research.

🏢実務担当者:Companies can leverage existing MES/ERP systems to automate emission data collection, as demonstrated in this case, reducing reliance on external service providers.

🏛政策担当者:The paper highlights the difficulties SMEs face in Scope 3 reporting, suggesting policy support for data infrastructure and standardized emission factors.

The German industrial and energy sectors accounted for over 52% of national greenhouse gas emissions in 2024. This is influenced both by an ongoing demand for fossil fuels and the usage of emission-intensive raw and processed materials. With the current European directive on corporate sustainability reporting, a push is being made for companies to publish annual emission reports. However, as per a study conducted by the authors, small and medium-sized companies have difficulties accurately calculating emissions across their supply chain without relying on external service providers. As a scientific institute with a real production facility for metal machining, the ETA (Energy Technologies and Applications) Factory bridges the gap between academia and manufacturing enterprises. The authors have used this disposition to calculate scope 1–3 emissions for the factory as per the Greenhouse Gas Protocol across three years, while progressively attempting to automate data collection for all scopes. CO2e emissions for the years 2022–2024 were 86.3 tCO2e, 146.9 tCO2e, and 86.1 tCO2e, respectively. Emission categories were assessed in terms of relevance to the institute and subsequently used to analyze the emission activities of the factory. The highest contributor to emissions was electricity purchasing for 2022 and 2024, along with business travel for 2023. Within scope 3, the emissions produced by business travel showed the highest impact across all years, followed by either energy-related activities or purchased goods. The sensitivity of CO2e factors was also investigated, showing discrepancies between 25% and 130% for the utilized CO2e factor for steel. Automation of data collection benefits largely from implemented manufacturing systems, such as manufacturing execution systems or enterprise resource planning systems.

• semanticscholar https://doi.org/10.3390/environments13050270first seen 2026-05-17 07:38:40 · last seen 2026-05-20 05:23:53