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合肥市霾天气变化特征及其影响因子
引用本文:张浩,石春娥,邱明燕,谢伟.合肥市霾天气变化特征及其影响因子[J].环境科学学报,2010,30(4):714-721.
作者姓名:张浩  石春娥  邱明燕  谢伟
作者单位:1. 南京大学大气科学学院,南京,210093;安徽省气象科学研究所,安徽省大气科学与卫星遥感重点实验室,合肥,230031
2. 安徽省气象科学研究所,安徽省大气科学与卫星遥感重点实验室,合肥,230031
3. 安徽省大气探测技术保障中心,合肥,230031
基金项目:国家自然科学基金资助项目(No. 40675002,40775010)
摘    要:分别应用费希尔最优分割法和后向轨迹-聚类分析的方法分析了1965~2005年间合肥霾天气的气候变化特征,以及合肥霾天气发生频率与不同高度输送条件的关系.同时应用2001~2005年的资料分析了合肥霾的月、季分布特征及其与地面气象要素的关系.合肥各月平均霾日数呈W型分布,1月最多,8月最少,秋冬两季占全年霾日数的70%以上.41年来霾日数总体呈上升趋势,期间发生了3次跃变,分别在1978、1992和2005年,与我国社会经济发展的各个阶段相一致.霾的发生频率与边界层中上部气团来向关系不大,但与其移动速度关系密切.近地面不同来向的气团对应霾的发生频率明显不同,霾易于出现的气团在春、夏、冬季主要来自偏东方向,秋季主要为本地气团以及来自偏北方向的气团.小风、高湿和偏东风是产生霾的有利条件.随着空气污染加重,霾的出现频率升高,当空气质量为中度污染时,霾的出现频率达到75%;高质量浓度的PM10并不意味着有霾出现,反之亦然.

关 键 词:  费希尔最优分割法  后向轨迹  聚类分析  气候跃变  影响因子
收稿时间:7/6/2009 12:00:00 AM
修稿时间:2009/11/3 0:00:00

Long-term variation of haze phenomena in Hefei and its impact factors
ZHANG Hao,SHI Chun''e,QIU Mingyan and XIE Wei.Long-term variation of haze phenomena in Hefei and its impact factors[J].Acta Scientiae Circumstantiae,2010,30(4):714-721.
Authors:ZHANG Hao  SHI Chun'e  QIU Mingyan and XIE Wei
Institution:1. School of Atmospheric Science, Nanjing University, Nanjing 210093; 2. Anhui Institute of Meteorological Sciences, Key Laboratory of Atmospheric Science and Satellite Remote Sensing, Hefei 230031,Anhui Institute of Meteorological Sciences, Key Laboratory of Atmospheric Science and Satellite Remote Sensing, Hefei 230031,Anhui Institute of Meteorological Sciences, Key Laboratory of Atmospheric Science and Satellite Remote Sensing, Hefei 230031 and Anhui Atmospheric Detection Center, Hefei 230031
Abstract:The Fisher optimum separation method was used to analyze the hazy days and associated climate jumps in Hefei during the period from 1965 to 2005 and back-trajectory-cluster analysis was used to determine the effects of transport patterns at different heights on haze frequency. The monthly variation of hazy days and their relationships with surface meteorological parameters are analyzed with data from 2001 to 2005. The monthly variation of the hazy days shows a "W" pattern,with maxima in January,June and November,and minima in April and August. The number of hazy days in autumn and winter accounts for more than 70% of the annual hazy days. During those forty-one years,annual hazy days kept increasing with 3 climate jumps,which occurred in 1978,1992,2005,corresponding to different stages of Chinese economic development. The haze occurrence has little relationship with the direction of the back trajectory in the upper atmospheric boundary layer (ABL) (1000 m); however,it has close relationship with the direction of air mass in the lower ABLand with the length of the trajectory in the upper ABL. The air masses in the lower ABLwith the highest haze occurrence are mainly from east in spring,summer and winter,and local,and north in autumn. The light wind,high humidity and easterly wind at the ground level are conducive to occurrence of haze. With the increase of PM10 concentration,the frequency of haze increases. The frequency of haze occurrence reaches 75% when the air quality is medium polluted. However,high PM10 concentration does not always mean haze nor vice versa.
Keywords:haze  Fisher optimum separation method  back-trajectory  cluster analysis  climate jump  influencing factors
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