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2015~2021年青藏高原地表臭氧时空变化及驱动因素分析
摘要点击 835  全文点击 147  投稿时间:2023-08-04  修订日期:2023-10-01
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中文关键词  青藏高原  地表臭氧(O3  时空特征  KZ滤波  气象影响
英文关键词  Qinghai-Xizang Plateau  surface ozone (O3  spatial-temporal characteristics  KZ filter  meteorological influence
作者单位E-mail
刘晓咏 信阳师范大学地理科学学院, 信阳 464000
信阳师范大学河南省水土环境污染协同防治重点实验室, 信阳 464000 
xyliu_liuxy@163.com 
颜俊 信阳师范大学地理科学学院, 信阳 464000  
刘航 中国科学院大气物理研究所大气边界层物理和大气化学国家重点实验室, 北京 100029  
牛继强 信阳师范大学地理科学学院, 信阳 464000
信阳师范大学河南省水土环境污染协同防治重点实验室, 信阳 464000 
 
闫军辉 信阳师范大学地理科学学院, 信阳 464000
信阳师范大学河南省水土环境污染协同防治重点实验室, 信阳 464000 
 
苏方成 郑州大学化学学院, 郑州 450001  
中文摘要
      基于青藏高原12个城市2015~2021年的大气污染监测数据和气象数据,分析了青藏高原地表臭氧(O3)时空分布格局. 采用KZ滤波将O3-8h原始序列分解为不同时间尺度的分量,并利用气象变量的多元线性回归定量地分离出气象和排放的影响. 结果表明,2015~2021年青藏高原12个城市地表ρ(O3-8h)均值为78.7~156.7 μg·m-3,O3浓度超标率(国家二级标准)为0.7%~1.5%. O3-8h月浓度变化呈单峰倒“V”型和多峰“M”型,浓度峰值出现在4~7月,谷值多出现在7月、 9月和12月. 经KZ滤波分解的O3-8h短期、季节和长期分量对12个城市O3-8h原始序列总方差的贡献率分别为29.6%、 51.4%和9.1%. 从整个区域看,2015~2017年气象条件对青藏高原O3降低不利,使得O3-8h长期分量升高0.2~2.1 μg·m-3. 2018~2021年气象有利于O3浓度降低,导致O3-8h长期分量降低0.4~1.1 μg·m-3. 气象条件增加了阿里、拉萨、那曲、林芝、昌都、海西和西宁的O3-8h长期分量,其平均贡献率为30.1%. 气象条件降低了日喀则和果洛的O3-8h长期分量,贡献率分别为359.0%和56.5%. 阿里、日喀则、那曲、海西和西宁O3-8h长期分量的上升可能是由于PM2.5长期分量快速下降[4.04 μg·(m3·a)-1]导致.
英文摘要
      The spatial-temporal distribution pattern of surface O3 over the Qinghai-Xizang Plateau (QXP) was analyzed based on air quality monitoring data and meteorological data from 12 cities on the QXP from 2015 to 2021. Kolmogorov-Zurbenko (KZ) filtering was employed to separate the original O3-8h series into components at different time scales. Then, multiple linear regression of meteorological variables was used to quantitatively isolate the effects of meteorology and emissions. The results revealed that the annual mass concentrations of surface O3-8h from 2015 to 2021 in 12 cities over the QXP ranged from 78.7 to 156.7 μg·m-3, and the exceedance rates of O3 mass concentrations (National Air Quality Standard of grade II) ranged from 0.7%-1.5%. The monthly O3-8h mass concentration displayed a single-peak inverted “V”-shape and a multi-peak “M”-shape. The maximum monthly concentration of O3 occurred in April to July, and valleys occurred in July, September, and December. The short-term, seasonal, and long-term components of O3-8hdecomposed by KZ filtering contributed 29.6%, 51.4%, and 9.1% to the total variance in the original O3 sequence in 12 cities, respectively. From the whole region, the meteorological conditions were unfavorable for O3 reduction on the QXP from 2015 to 2017, which made the long-term component of O3 increase by 0.2-2.1 μg·m-3. The meteorological conditions were favorable for O3-8h reduction from 2018 to 2021, which led to the long-term component of O3-8h decrease by 0.4-1.1 μg·m-3. The meteorological conditions increased the long-term component of O3-8h in Ngari, Lhasa, Naqu, Nyingchi, Qamdo, Haixi, and Xining, with an average contribution of 30.1%. The meteorological conditions decreased the long-term component of O3-8h in Shigatse and Golog, with contributions of 359.0% and 56.5%, respectively. The increase in the long-term component of O3-8h in Ngari, Shigatse, Nagqu, Haixi, and Xining could be due to the rapid decrease in the long-term component of PM2.5 (4.04 μg·(m3·a)-1).

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