从1980年到2012年在中国中部和东部重建高质量的地面层臭氧记录
Jinghui Ma1,2,3, Yihong Wei4, Zhongqi Yu5,6
1Shanghai Typhoon Institute, Shanghai Meteorological Service, Shanghai, 200030, China.
Scientific data
|December 15, 2025
概括
研究人员使用机器学习模型为中国中东地区 (1980-2012) 创建了一个新的臭氧数据集. 这些数据揭示了气候变化和排放导致的臭氧水平上升,这对空气质量管理至关重要.
科学领域:
- 大气化学和空气质量
- 环境科学 环境科学
- 气候变化研究 气候变化研究
背景情况:
- 表面臭氧 (O3) 对公众健康和生态系统产生重大影响.
- 对于中国中东部 (CEC),2013年之前的臭氧数据有限,这阻碍了长期分析.
- 解决这一数据缺口对于了解历史臭氧污染趋势至关重要.
研究的目的:
- 构建一个高分辨率的日常臭氧度数据集为CEC跨越1980-2012年.
- 分析长期臭氧趋势并确定该地区的关键驱动因素.
- 为未来的空气质量和气候变化研究提供必要的基线数据.
主要方法:
- 采用了一个光梯度增强机 (LightGBM,LGBM) 模型.
- 使用多源数据集进行数据重建.
- 使用十倍交叉验证 (2013-2023) 验证该模型,具有高相关系数 (R2>0.8) 和低RMSE (7.5-7.9μg·m−3).
主要成果:
- 重建了一个区域平均臭氧度为87.6μg·m-3的数据集,显示了南北梯度.
- 确定每年臭氧含量显著增加,为0.14μg·m−3 yr−1 (p < 0.01).
- 臭氧的升高归因于全球变暖 (0.32°C十年-1),工业扩张和城市化的协同作用.
结论:
- 用LightGBM重建的数据集提供了特殊的稳定性 (年间变化率<5%).
- 为量化多十年臭氧污染与气候相互作用提供了关键的基线数据.
- 为区域空气质量管理战略和未来环境政策制定提供信息.
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