从1970年到2024年全球每日CO2排放量
Tao Li1, Lixing Wang1, Zihan Qiu2
1Department of Earth System Science, Tsinghua University, Beijing, 100084, China.
Scientific data
|February 24, 2026
概括
极端温度事件需要每日二氧化碳 (CO2) 排放数据. 本研究使用高频活动和机器学习构建了从1970年到2024年的长期每日二氧化碳数据集,填补了关键数据缺口.
科学领域:
- 环境科学 环境科学
- 气候科学 气候科学
- 数据科学数据科学数据科学
背景情况:
- 在全球范围内,极端温度事件的频率正在增加.
- 每日二氧化碳 (CO2) 排放数据对于影响评估至关重要,但仅可从2019年开始获得.
- 对于历史的每日二氧化碳排放,存在很大的数据差距.
研究的目的:
- 创建一个全面的,长期的每日二氧化碳排放数据集,涵盖1970-2024年.
- 为了能够详细分析极端温度事件对二氧化碳排放的影响.
- 使用化学运输模型提高碳流量估计的准确性.
主要方法:
- 编制了超过200万次近实时观测 (电力,交通,天然气,工业) 从2019-2024.
- 通过使用高频活动数据,开发了2019-2024年每日二氧化碳排放数据集.
- 应用机器学习和学位日方法,将每月排放量 (1970-2018) 分解为每天的排放量.
主要成果:
- 从1970年到2024年为14个国家/地区生成了全球每日二氧化碳排放数据集.
- 该数据集涵盖了四个主要部门:电力,工业,住宅和运输 (包括航空).
- 合并的数据集为排放分析提供了前所未有的时间分辨率.
结论:
- 新的长期每日二氧化碳排放数据集解决了对气候影响研究的关键需求.
- 这一数据集将增强对极端温度对排放的影响的理解.
- 改进的排放数据将完善碳流逆转模型和气候变化评估.
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