A near-real time daily European Power Consumption and Carbon Intensity Dataset (ECON-PowerCI)
文献类型：期刊论文
| 作者 | Zhang, Shujie4; Zhao, Wenli5,6,7,8; Zhu, Biqing9; Yan, Chunhua10; Song, Xuanren11; Jiang, Hou1; Fang, Jianing5; Ciais, Philippe12; Xuan, Ning4; Gentine, Pierre5 |
| 刊名 | SCIENTIFIC DATA
 |
| 出版日期 | 2025-10-27 |
| 卷号 | 12期号:1页码:1693 |
| DOI | 10.1038/s41597-025-05978-7 |
| 产权排序 | 9 |
| 文献子类 | Article |
| 英文摘要 | 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. |
| URL标识 | 查看原文 |
| WOS关键词 | CLIMATE-CHANGE ; IMPACTS ; COUNTRIES ; PHASE |
| WOS研究方向 | Science & Technology - Other Topics |
| 语种 | 英语 |
| WOS记录号 | WOS:001603536600003 |
| 出版者 | NATURE PORTFOLIO |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/217688]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 通讯作者 | Zhao, Wenli; Qiu, Guo Yu |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China; 2.Tsinghua Univ, Beijing, Peoples R China 3.Stanford Univ, Stanford Doerr Sch Sustainabil, Stanford, CA USA; 4.Peking Univ, Sch Environm & Energy, Shenzhen, Peoples R China; 5.Columbia Univ, New York, NY 10027 USA; 6.Max Planck Inst Biogeochem, Jena, Germany; 7.ELLIS Jena Unit, Jena, Germany; 8.Max Planck Caltech Carnegie Columbia MC3 Ctr, New York, NY 10027 USA; 9.Int Inst Appl Syst Anal IIASA, Vienna, Austria; 10.Sun Yat Sen Univ, Shenzhen, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Zhang, Shujie,Zhao, Wenli,Zhu, Biqing,et al. A near-real time daily European Power Consumption and Carbon Intensity Dataset (ECON-PowerCI)[J]. SCIENTIFIC DATA,2025,12(1):1693. |
| APA | Zhang, Shujie.,Zhao, Wenli.,Zhu, Biqing.,Yan, Chunhua.,Song, Xuanren.,...&Qiu, Guo Yu.(2025).A near-real time daily European Power Consumption and Carbon Intensity Dataset (ECON-PowerCI).SCIENTIFIC DATA,12(1),1693. |
| MLA | Zhang, Shujie,et al."A near-real time daily European Power Consumption and Carbon Intensity Dataset (ECON-PowerCI)".SCIENTIFIC DATA 12.1(2025):1693. |
入库方式： OAI收割
来源：地理科学与资源研究所
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