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苏州市区灰霾现象形成的气象条件分析
引用本文:邹强,姚玉刚,林惠娟.苏州市区灰霾现象形成的气象条件分析[J].中国环境监测,2014,30(1):37-42.
作者姓名:邹强  姚玉刚  林惠娟
作者单位:苏州市环境监测中心站, 江苏 苏州 215004;苏州市环境监测中心站, 江苏 苏州 215004;苏州市气象局, 江苏 苏州 215131
基金项目:苏州市科技支撑计划(社会发展)“苏州市区复合污染监测、评价与预警关键技术应用研究”(SS201232)
摘    要:随着社会和经济的快速发展,灰霾现象的发生有逐渐上升趋势,严重影响城市形象和群众的身心健康。苏州市的灰霾现象发生频率1—2月最高,7—8月最低。通过寻找形成灰霾现象的主要气象控制因子,有助于判别不同气象条件在灰霾天气形成中的作用。采用基于因子分析的主成分提取方法,将6个气象因子观测资料整合为3个主成分,并逐一揭示4个典型季节各主成分的支配因子在灰霾天气形成中的作用。结果表明,热量条件是影响1—2月、4—5月和7—8月霾日形成的主要气象条件。动力条件是10—11月霾日形成的主要气象条件,水分条件影响相对较弱,仅起辅助作用。

关 键 词:苏州  灰霾形成  气象条件  主成分分析
收稿时间:2012/7/15 0:00:00
修稿时间:2012/11/22 0:00:00

The Analysis of Meteorological Conditions on Haze Formation in Suzhou City
ZOU Qiang,YAO Yu-gang and LIN Hui-juan.The Analysis of Meteorological Conditions on Haze Formation in Suzhou City[J].Environmental Monitoring in China,2014,30(1):37-42.
Authors:ZOU Qiang  YAO Yu-gang and LIN Hui-juan
Institution:Suzhou Environmental Monitor Centre, Suzhou 215004, China;Suzhou Environmental Monitor Centre, Suzhou 215004, China;Suzhou Meteorology Bureau, Suzhou 215131, China
Abstract:With the rapid development of society and economy, the haze phenomenon occurs gradually rising trend, and seriously affected city image and peoples healthy. Haze frequency of Suzhou city occurred in January-February was the highest and July-August lowest. To differentiate the effect of different weather conditions on haze formation days, weather factors were collected and analyzed in Suzhou city. By using principal components extraction method, six meteorological factors were integrated into three principal components and the contributions of each principal component to the forming of haze days were analyzed in four different time scales. Results show that heat conditions play an important role in Jan-Feb (winter), Apr-May (spring) and Jul-Aug (summer), while dynamic condition is more important in Oct-Nov (autumn) on the forming of haze days. Water condition shows relatively weak influence which only plays a supplementary role in different time scales.
Keywords:Suzhou  haze formation  meteorological conditions  PCA analysis
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