主办单位:中国气象局沈阳大气环境研究所
国际刊号:ISSN 1673-503X
国内刊号:CN 21-1531/P

气象与环境学报 ›› 2019, Vol. 35 ›› Issue (2): 107-111.doi: 10.3969/j.issn.1673-503X.2019.02.016

• 简报 • 上一篇    

海口市重污染天气潜在源分析研究

张滢滢1,2, 陈明1, 陈丽英1   

  1. 1. 海南省气象服务中心, 海南 海口 570203;
    2. 海南省南海气象防灾减灾重点实验室, 海南 海口 570203
  • 收稿日期:2017-09-22 修回日期:2018-01-19 出版日期:2019-04-30 发布日期:2019-04-30
  • 作者简介:张滢滢,女,1986年生,工程师,主要从事专业气象服务工作,E-mail:evazhang928@163.com
  • 基金资助:

    海南省气象局青年基金项目(HN2013MS19)资助。

Potential source analysis of heavy pollution weather in Haikou

ZHANG Ying-ying1,2, CHEN Ming1, CHEN Li-ying1   

  1. 1. Hainan meteorological service center, Haikou 570203, China;
    2. Key Laboratory of South China Sea Meteorological Disaster Prevention and Mitigation of Hainan Province, Haikou 570203, China
  • Received:2017-09-22 Revised:2018-01-19 Online:2019-04-30 Published:2019-04-30

摘要:

在进入冬半年后,海口市受弱冷空气或较强下沉气流控制时,易出现污染天气,对2013—2015年当年10月至翌年1月的气团轨迹进行了聚类分析、潜在源贡献因子分析(Potential Source Contribution Function,PSCF)和重轨迹分析(Concentration Weighted trajectory,CWT),结果表明:在污染时段内,海口大多受到来自中国华南和华东的东北向气流影响。PSCF和CWT分析表明,广东、福建、江西的大部分地区,以及湖南东部、广西东部等地区,是对海口地区污染天气污染物浓度的潜在贡献大值区。在进行预报时,可参考主要天气影响系统,和一些关键区域的外源影响以及本地污染的堆积情况。

关键词: 空气质量, 气象要素, 聚类分析, PSCF, CWT

Abstract:

After entering the winter half year,pollution weather of Haikou is easily caused by the weak cold air or downdraft.Using cluster analysis,PSCF and CWT methods,the potential source of heavy pollution weather from October to January during 2013-2015 was analyzed.The result shows that Haikou's air quality is mainly influenced by the northeast air stream from south china and east china during the studied period.The analysis results of PSCF and CWT methods indicate that the most areas of Guangdong,Fujian and Jiangxi province as well as the east of Hunan and Guangxi province are potential areas contributing pollutant for the pollution weather of Haikou.In addition,the main weather system causing air pollution,the exotic impacting from the key area and the accumulation condition of local pollutant should be considered in pollution forecast.

Key words: Air quality, Meteorological elements, Cluster analysis, PSCF, CWT

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