A near-real time daily European Power Consumption and Carbon Intensity Dataset (ECON-PowerCI)
We present a near-real-time daily European Consumption-based Power Carbon Intensity Dataset (ECON-PowerCI), developed from the CarbonMonitor power production dataset for Europe. Spanning from January 2015 to December 2024, the dataset encompasses 35 European countries, with daily updates and a one-day latency. ECON-PowerCI provides consumption-based power carbon intensity at the national level, accounting for cross-border electricity net imports in the country of consumption. By integrating ENTSO-E (The European Network of Transmission System Operators for Electricity) data, ECON-PowerCI enables comprehensive analysis of carbon intensity trends shaped by cross-border transmissions, extreme weather events, and disruptions like the COVID-19 pandemic and geopolitical conflicts. This dataset facilitates in-depth study of the effect of cross-border electricity flows on national carbon footprints, providing insights for energy policy and climate resilience. The dataset also holds extensive research potential for power-related analyses and policy-making in Europe's interconnected power systems.
Authors
- Xuanren Song (ORCID: https://orcid.org/0000-0001-9075-2895)
- Steven J. Davis (ORCID: https://orcid.org/0000-0002-9338-0844)
- Guo Yu Qiu (ORCID: https://orcid.org/0000-0002-1845-6976)
- Biqing Zhu (ORCID: https://orcid.org/0000-0001-9360-6797)
- Pierre Gentine (ORCID: https://orcid.org/0000-0002-0845-8345)
- Philippe Ciais (ORCID: https://orcid.org/0000-0001-8560-4943)
- Chunhua Yan (ORCID: https://orcid.org/0000-0002-8142-4280)
- Wenli Zhao (ORCID: https://orcid.org/0000-0001-6152-1692)
- Zhu Liu (ORCID: https://orcid.org/0000-0002-8968-7050)
- Jianing Fang (ORCID: https://orcid.org/0000-0002-1642-5797)
- Xuan Ning (ORCID: https://orcid.org/0000-0003-1459-2847)
- Shujie Zhang (ORCID: https://orcid.org/0000-0002-9109-8917)
- Hou Jiang (ORCID: https://orcid.org/0000-0002-5087-3446)
Institutions
- International Institute for Applied Systems Analysis (AT)
- Sun Yat-sen University (CN)
- Chinese Academy of Sciences (CN)
- Peking University (CN)
- Jena Bioscience (Germany) (DE)
- Laboratoire des Sciences du Climat et de l'Environnement (FR)
- Botswana Geoscience Institute (BW)
- Stanford Medicine (US)
- Max Planck Institute for Biogeochemistry (DE)
- Institute of Geographic Sciences and Natural Resources Research (CN)
- Max Planck Graduate Center (DE)
- Monash University (AU)
- Columbia University (US)
- Stanford University (US)
- Tsinghua University (CN)
Publication Details
- Journal
- Scientific Data
- Published
- 2025-10-27
- DOI
- https://doi.org/10.1038/s41597-025-05978-7
- Citations
- 1
- Primary Topic
- Integrated Energy Systems Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.73
Funders
- California Institute of Technology