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影响北京夏季O3污染的O3前体物浓度及天气条件分析
引用本文:刘玉彻,徐敬,王淑凤,孟昭阳.影响北京夏季O3污染的O3前体物浓度及天气条件分析[J].气象与环境学报,2006,22(6):34-37.
作者姓名:刘玉彻  徐敬  王淑凤  孟昭阳
作者单位:1.中国气象局沈阳大气环境研究所 沈阳110016;2.北京市气象局 北京100022;3.中国气象科学研究院 北京100081
基金项目:中国环境科学研究院区域大气污染物总量控制技术与示范研究(2003BA614A-03)资助
摘    要:根据2003年北京夏季近地面大气光化学污染物观测资料,对中国气象局培训中心(代表站)O3超标日浓度、O3前体物浓度、不同天气条件下O3浓度分布特征等进行分析。结果表明:中国北京夏季NO2,NO,CO的浓度特征与日本神奈川县相似,白天(16:00以前)如果NO2/NO超过29,则容易出现O3超标;VOC浓度的高低影响O3浓度;当处于暖湿气流控制,地面为小风或静风、气温较高、湿度较大的多云天气时,易出现O3超标情况。这些污染物发生的特点和规律对北京大气光化学污染的研究和防治具有借鉴意义。

关 键 词:大气污染物  O  O前体物  天气条件  特征分析  
收稿时间:2006-08-30
修稿时间:2006-08-302006-11-15

Analysis of ozone precursor concentration and its weather conditions in summer in Beijing
LIU Yuche,XU Jing,WANG Shufeng,MENG Zhaoyang.Analysis of ozone precursor concentration and its weather conditions in summer in Beijing[J].Journal of Meteorology and Environment,2006,22(6):34-37.
Authors:LIU Yuche  XU Jing  WANG Shufeng  MENG Zhaoyang
Institution:1.Institute of Atmospheric Environment;CMA;Shenyang 110016;2.Beijing MeteorologicalBureau;Beijing 100022;3.the Chinese Academy of Metrological sciences;CMA;Beijing 100081
Abstract:Based on surface atmospheric photochemistry concentration observation data in summer of 2003 in Beijing observation station,ozone concentration of exceeding standard day,ozone precursor concentration and the distribution characteristics of ozone concentration in different weather conditions were analyzed.The results indicated that the characteristics of NO_2 concentration and NO concentration as well as CO concentration were similar to that of Kanagawa in Japan.If the value of NO_2/NO was beyond 29,ozone concentration exceeded the standard easily.Ozone concentration could be influenced by VOC concentration.Under the conditions of warm and wet current control,faint ground wind or calm and cloudy weather with high humidity,ozone concentration exceeded the standard easily,too.All these were significant to research and prevention of atmospheric photochemistry pollution.
Keywords:Atmosphere pollution  Ozone  Ozone precursor  Weather condition  Characteristic analysis
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