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上海市一次重雾霾过程的天气特征及成因分析
引用本文:王静,施润和,李龙,张璐.上海市一次重雾霾过程的天气特征及成因分析[J].环境科学学报,2015,35(5):1537-1546.
作者姓名:王静  施润和  李龙  张璐
作者单位:华东师范大学地理信息科学教育部重点实验室,上海200241;华东师范大学环境遥感与数据同化联合实验室,上海200241
基金项目:上海市科委重点支撑项目(No.13231203804);国家自然科学基金(No.41201358);地理信息科学教育部重点实验室主任基金
摘    要:2013年11月30日至12月9日上海地区出现入冬以来一次最严重的持续性雾霾天气过程,严重影响了该地区人们的生活健康.本文借助空气质量数据、地面气象要素、卫星遥感数据并结合后向轨迹模式反映了此次重污染过程的污染特征及其成因.结果表明,污染期间,PM2.5与PM10小时浓度变化趋势基本一致,高浓度值出现在早晚8时左右,主要是由该时段的逆温现象造成的;来自西北方向污染物的远距离输送影响了本地空气质量状况,气团在不同高度层做下沉运动,造成大气层结稳定;该地区在西北方向的弱高压控制下,地面风速较小,能见度低,天气条件静稳,不利于污染物扩散,造成持续性重污染事件;卫星遥感数据显示此次污染为区域性污染.

关 键 词:雾霾  天气形势  MODIS  AOD  上海
收稿时间:2014/7/12 0:00:00
修稿时间:2014/11/2 0:00:00

Characteristics and formation mechanism of a heavy air pollution episode in Shanghai
WANG Jing,SHI Runhe,LI Long and ZHANG Lu.Characteristics and formation mechanism of a heavy air pollution episode in Shanghai[J].Acta Scientiae Circumstantiae,2015,35(5):1537-1546.
Authors:WANG Jing  SHI Runhe  LI Long and ZHANG Lu
Institution:1. Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241;2. Joint Laboratory for Environmental Remote Sensing and Data Assimilation, ECNU and CEODE, Shanghai 200241;1. Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241;2. Joint Laboratory for Environmental Remote Sensing and Data Assimilation, ECNU and CEODE, Shanghai 200241;1. Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241;2. Joint Laboratory for Environmental Remote Sensing and Data Assimilation, ECNU and CEODE, Shanghai 200241;1. Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241;2. Joint Laboratory for Environmental Remote Sensing and Data Assimilation, ECNU and CEODE, Shanghai 200241
Abstract:The air pollution episode from 30 November to 9 December, 2013 was the most serious one since the winter began in Shanghai. This had seriously threatened the life and health of local citizen. To analyze the characteristics and formation mechanisms of this episode, the air quality data, ground meteorological data and satellite remote sensing data were collected over the period and the backward trajectories method was used. The results showed that hourly variation trend of PM2.5 and PM10 concentrations were similar, and higher values were generally detected in the morning and evening, probably due to the temperature inversion over those periods; The long-distance transport of particulate matter from Northwest China influenced local air quality, whereas atmosphere layers could be more stable because air mass went down within layers. In addition, the weak high pressure dominated Shanghai, consequently, the surface wind was weak, visibility was low, and synoptic pattern was relatively stable. This was not good for the air pollutant dispersion, leading to the long-lasting heavy air pollution episode. Our results retrieved from satellite remote sensing found that this episode was not local, as the same pollution event was observed in many cities in the Yangtze River Delta.
Keywords:haze  synoptic pattern  MODIS AOD  Shanghai
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