[2018 - 2022年北京市PM2.5污染事件时空变化、气象条件及区域运输特征]。

Q2 Environmental Science
Yuan-Xi Guo, Bao-Xian Liu, Yun-Ting Li, Xiu-E Shen, Shu-Xiao Wang, Qian Song, Chen Chen, Feng Sun, Yang Chen, Rui-Wen Sun, Qian Li, De-Jia Yin, Yue-Qi Jiang, Zhao-Xin Dong
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引用次数: 0

摘要

基于PM2.5监测资料、气象观测资料和CMAQ-ISAM空气质量模型,分析了2018 - 2022年北京市108次PM2.5污染事件的时空变化、气象条件和区域运输特征。结果表明:PM2.5污染事件发生频次、平均浓度和峰值浓度均呈显著下降趋势,且中、重度污染事件的下降程度明显大于轻污染事件。从季节上看,PM2.5污染事件在夏季基本消失,而在其他季节则较为严重。从日变化曲线看,重污染事件期间PM2.5浓度从白天到前半夜明显下降,后半夜下降不明显。近5年PM2.5污染事件平均浓度呈现东南高西北低的趋势,其中北京经济技术开发区最高,延庆区最低。从空间演变的角度看,2018 - 2022年各区平均浓度显著下降,下降幅度为13 ~ 31 μg·m-3,下降幅度为11% ~ 25%;各区发生频率也显著下降,下降幅度为35 ~ 52 d,下降幅度为56% ~ 68%。平均风速、平均相对湿度和西北风频次是影响北京PM2.5浓度的三个最重要气象因子。污染日平均风速为1.6 m·s-1,平均相对湿度为62.4%,西北风频率为3%。大部分污染事件始于北京东部和北京南部。与全市相比,东南边境站PM2.5污染事件发生时间平均提前12 h,南边境站、西南边境站和东部边境站PM2.5污染事件发生时间平均提前10、8和5 h。在北京PM2.5污染事件中,当地贡献为34%,交通贡献为66%。在邻近省份中,河北的贡献最大,达到33%。从城市来看,保定、廊坊、天津、唐山对北京PM2.5污染事件的影响最为突出,分别占贡献率的9%、6%、5%和5%。在运输路径方面,东南路径贡献了24%,西南路径贡献了23%。政府必须建立区域联防联控机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
[Spatio-temporal Variation, Meteorological Condition, and Regional Transport Characteristics of PM2.5 Pollution Events in Beijing from 2018 to 2022].

Based on PM2.5 monitoring data, meteorological observation data, and a CMAQ-ISAM air quality model, the spatio-temporal variation, meteorological conditions, and regional transport characteristics of 108 PM2.5 pollution events in Beijing from 2018 to 2022 were analyzed. The results showed that the frequency, the mean concentration, and the peak concentration of PM2.5 pollution events demonstrated a significant decrease and the decrease degree of moderate and heavy pollution events was significantly larger than that of light pollution events. From the seasonal perspective, the PM2.5 pollution events nearly disappeared in summer, however, were severe in other seasons. According to the diurnal variation curves, PM2.5 concentration during heavy pollution events decreased significantly from daytime to the first half of night and did not decrease notably in the second half of the night. In the past five years, the mean concentration of PM2.5 pollution events was higher in the southeast and lower in the northwest, with the highest in the Beijing Economic and Technological Development Area and the lowest in Yanqing District. From the perspective of spatial evolution, the mean concentration in all districts significantly decreased from 2018 to 2022, with a decrease range of 13-31 μg·m-3 and a decrease percentage of 11%-25%; the frequency in all districts also decreased significantly, with a decrease range of 35-52 days and a decrease percentage of 56%-68%. The mean wind speed, mean relative humidity, and northwest wind frequency were the three most important meteorological factors that had an impact on PM2.5 concentration in Beijing. For polluted days, the mean wind speed was 1.6 m·s-1, the mean relative humidity was 62.4%, and the frequency of northwest wind was 3%. Most of the pollution events began from Eastern Beijing and Southern Beijing. Compared to those throughout the whole city, PM2.5 pollution events usually occurred 12 hours earlier at the southeast border station and 10, 8, and 5 hours earlier at the southern, southwest, and eastern border stations, respectively. During PM2.5 pollution events in Beijing, the local contribution was 34%, and the transport contribution was 66%. Out of all nearby provinces, Hebei had the biggest contribution of 33%. With regard to cities, Baoding, Langfang, Tianjin, and Tangshan had the most prominent impact on Beijing's PM2.5 pollution events, accounting for 9%, 6%, 5%, and 5% of the contribution, respectively. When it comes to transport pathways, the southeast pathway contributed 24% and the southwest pathway contributed 23%. The government must establish a regional joint prevention and control mechanism.

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来源期刊
环境科学
环境科学 Environmental Science-Environmental Science (all)
CiteScore
4.40
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