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中国农学通报 ›› 2015, Vol. 31 ›› Issue (36): 176-183.doi: 10.11924/j.issn.1000-6850.casb15040065

所属专题: 农业气象

• 资源 环境 生态 土壤 气象 • 上一篇    下一篇

临汾市雾霾天气的分析和研究

徐晋峰1,2,李丽萍1,李 敏3,公芙萍4,赵俊平4,崔雪莲5   

  1. (1南京信息工程大学,南京 210000;2山西省朔州市朔城区气象局,山西朔州 036000;3民航青海空管分局,西宁 810000;4山西省临汾市气象局,山西临汾 041000 5山西省临汾市曲沃县气象局,山西曲沃 043400)
  • 收稿日期:2015-04-08 修回日期:2015-08-18 接受日期:2015-09-25 出版日期:2015-12-30 发布日期:2015-12-30
  • 通讯作者: 公芙萍
  • 基金资助:
    无基金

Analysis of Fog and Haze Weather in Linfen City

Xu Jinfeng1,2, Li Liping1, Li Min3, Gong Fuping4, Zhao Junping4, Cui Xuelian5   

  1. (1Nanjing University of Information Science & Technology, Nanjing 210000;2Shuocheng Meteorological Bureau of Shuozhou City, Shuozhou Shanxi 036000;3Qinhai Branch of the Civil Aviation ATC, Xining 8100004Linfen Meteorology Bureau, Linfen Shanxi 0410005Meteorology Bureau of Quwo, Quwo Shanxi 043400)
  • Received:2015-04-08 Revised:2015-08-18 Accepted:2015-09-25 Online:2015-12-30 Published:2015-12-30

摘要: 为了进一步提高对临汾市雾霾的预测以及防治效果,从而避免、减轻雾霾天气对人类造成的交通、健康等危害。根据临汾市2013年11月—2014年3月自动气象站对PM1.0、PM2.5、PM10、能见度、相对湿度、气温等的观测资料,利用临汾市1954—2014年12—3月的降水日数和静风日数的统计资料,利用数理统计、线性拟合、多元回归等方法,分析临汾市秋冬季雾霾与天气气象要素之间的关联。结果表明:风速、气压、气温都会对空气的能见度产生影响,其中风速的影响最大,风速每增大1 m/s,能见度增加3.3 km;气温、相对湿度、风速、能见度均与PM2.5呈负相关,风速与PM2.5浓度值的负相关程度最大,风速每增大1 m/s,PM2.5的浓度值减少65.2 μg/m3;静风日数以0.98 d/10 a的速率减少,而降水日数以 0.07d /10 a的速率减少。

关键词: 单叶省藤, 单叶省藤, 组织培养, 生根

Abstract: The paper aims to further improve the haze prediction and control in Linfen City, to avoid and reduce the traffic and health hazards caused by haze weather. According to the observation data of PM1.0, PM2.5 and PM10, visibility, relative humidity and temperature from November 2013 to March 2014 recorded by the automatic meteorological station in Linfen City, the authors used data of rainy days and no wind days from December to March during 1954-2014, the mathematical statistics, linear fitting and multivariate regression method, to analyze the relationship between fog haze and meteorological factors in autumn and winter in Linfen City. The results showed that the wind speed, air pressure and temperature would affect the air visibility, wind speed had the biggest influence, wind speed increased per 1 m/s, visibility increased 3.3 km; temperature, relative humidity, wind speed and visibility were negatively correlated to PM2.5, wind speed and PM2.5 level had the biggest negative correlation degree, wind speed increased per 1 m/s, PM2.5 reduced 65.2 μg/m3; no wind days were reducing at a rate of about 0.98 d/10 a, and rainy days were reducing at a rate of about 0.07 d/10 a.

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