用深度学习预测欧盟减排趋势，发现2030目标将差35%。
Europe's Climate Ambition Under Scrutiny: Evidence from Deep Learning Emission Projections
- 基于历史数据推演各行业碳排放趋势，不假设政策加速。
- 2030年欧盟碳排放将比目标高出35%，缺6.2亿吨。
- 交通领域进展缓慢，占总排放超三分之一，需重点干预。
欧盟承诺到2030年将温室气体排放较1990年水平降低55%，但当前趋势是否可达目标尚不确定。本文利用深度学习对欧盟27国截至2023年的高分辨率社会经济与部门数据进行分析，基于现有趋势预测各部门二氧化碳排放路径，未假设政策节奏或效力在未来发生超出历史数据反映的变化。预测显示，欧盟27国排放量将超出2030年目标35%（相当于6.2亿吨二氧化碳缺口），仅少数国家处于符合承诺的轨迹上。尽管电力部门因可再生能源转型实现目标一致减排，但交通领域进展微弱，到2030年将贡献超过三分之一的总排放，反映出成员国间普遍存在的结构性惯性，而非地理集中滞后。研究结果表明，亟需采取重大额外措施弥合欧洲气候雄心与实施之间的差距，并呼吁建立更新的能源信息体系。
原文摘要 · Abstract (English)
The European Union has committed to reducing greenhouse gas emissions 55% below 1990 levels by 2030, but whether current trends are compatible with this ambition remains uncertain. We apply deep learning to high-resolution socioeconomic and sectoral data across EU27 member states till 2023 to project sectoral CO$_2$ trajectories under current trends, extrapolating observed sectoral momentum without assuming changes in the pace or effectiveness of the policy environment beyond what is already reflected in historical data. We project that EU27 emissions will exceed the 2030 target by 35% (620 Mt CO$_2$ shortfall), with only a small minority of countries on trajectories consistent with the bloc's commitments. While the Power sector achieves target-consistent reductions driven by the renewable transition, Mobility shows minimal progress and accounts for over a third of total emissions by 2030, reflecting a structural inertia across member states rather than geographically concentrated lag. Our findings indicate that substantial additional intervention is required to close Europe's ambition-implementation gap, and call for establishing up-to-date energy information in Europe.
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