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[PM_2.5-O₃的特征和影响因素在宝市的双高组合污染]

Shuai-Long He¹, Chuan-da Wang¹, Shui-Yuan Cheng¹

¹Beijing Key Laboratory of Regional Air Pollution Control, College of Environmental Science and Engineering, Beijing University of Technology, Beijing 100124, China.

Huan jing ke xue= Huanjing kexue

|December 19, 2025

概括

宝市的空气质量受到细颗粒物 (PM2.5) 和臭氧 (O3) 的影响. 虽然PM2.5水平下降,但O3波动,污染在流行后反弹. 协调的控制策略对于改进至关重要.

科学领域:

环境科学环境科学
大气化学大气化学
空气质量管理管理空气质量

背景情况:

细颗粒物 (PM2.5) 和臭氧 (O3) 对宝市的空气质量构成重大挑战.
了解这些污染物的时空动态和来源对于有效的缓解至关重要.
以前的研究可能没有完全捕捉到该地区PM2.5和O3的季节性变化和气象影响.

研究的目的:

为了调查PM2.5和O3污染的时空变化在宝市从2017年到2022年.
确定影响PM2.5和O3度的关键气象和化学因素.
分析PM2.5和O3的污染源,包括当地排放和跨境运输.

主要方法:

使用的污染物度和宝市 (2017-2022) 的气象数据.
使用随机森林模型来确定影响因素.
应用逆向轨迹集群分析和WRF-CAMx模型用于源分配和模拟.

主要成果:

PM2.5度呈现下降趋势,而O3水平波动,在2022年流行后观察到反弹.
冬季的PM2.5污染达到峰值,夏季的O3,春季的复合污染受到湿度,CO,NO2,太阳辐射和温度的影响.
PM2.5-O3污染主要是由本地排放造成的,而来自河北和河南省周边地区的重要贡献.

结论:

季节性和特定条件的控制策略是必要的,以有效地管理巴的空气质量.
考虑到气象条件和区域运输,对PM2.5和O3的协调控制至关重要.
建议加强污染预测,早期预警系统以及联合区域预防和控制工作.

关键词:

在O3中,O3是O3的.对于PM2.5来说,这是一个很好的例子.在WRF-CAMx中使用WRF.复合污染复合污染复合污染随机的森林随机的森林区域运输区域运输区域运输

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