通过使用可解释机器学习,了解中国对排放和气象的空间反应中的臭氧变异性
Xin Zhang1, Wei-Chun Zhang1, Wei Wu2
1College of Resources and Environment, Southwest University, Beibei, Chongqing 400716, China.
iScience
|July 21, 2025
概括
区域臭氧污染控制需要了解臭氧的变化. 这项研究揭示了中国北部的季节性模式和南方的短期变化,主要地区的排放驱动增长放缓和气象影响不同.
科学领域:
- 环境科学 环境科学
- 大气化学 大气化学
背景情况:
- 区域臭氧污染对环境和健康构成重大挑战.
- 了解臭氧因排放和气象反应的变化对于有效的控制策略至关重要.
研究的目的:
- 调查中国大陆的臭氧度的空间变化.
- 分析排放和气象因素对臭氧水平的影响.
- 确定臭氧趋势和驱动因素的区域差异.
主要方法:
- 利用来自中国大陆的监测站 (2016-2023) 的臭氧数据.
- 应用统计方法和可解释的机器学习技术.
- 分析了对排放和气象变量的空间反应.
主要成果:
- 臭氧变化的特点是北方的季节周期和南方的短期波动.
- 排放驱动的臭氧增加已经放缓 (平均趋势为0.41μg/m3 a-1).
- 气象对臭氧的影响在区域上有所不同:在北京-天津-河北和四川盆地下降,在长江三角洲和珍珠河三角洲增加.
结论:
- 温度是中国北部的一个关键因素,而太阳辐射在其他地方占主导地位,具有互动效应.
- 有效的臭氧污染控制需要考虑排放和气象影响的特定区域战略.
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