Journal of Atmospheric and Environmental Optics ›› 2016, Vol. 11 ›› Issue (4): 249-257.

• 论文 • Previous Articles     Next Articles

Analysis of Regional Characteristics and Long-Term Variations of Visibility in China

WANG Wei 1, 2, WANG Xiquan1, WANG Zifa1, GE Baozhu1, YAN Pingzhong1, YANG Ting1   

  1. ( 1 State Kay Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China 
    2 University of Chinese Academy of Sciences, Beijing 100049, China )
  • Received:2015-06-04 Revised:2015-06-09 Online:2016-07-28 Published:2016-07-15
  • Contact: 王威,(1985-),男,吉林通化人, 博士研究生。主要从事灰霾预报预警及其成因研究。 E-mail:wwangwwei@gmail.com

Abstract:

An analysis of visibility in China from 1980 to 2008 was conducted based on 29 years’ data that was collected from over 350 meteorological observation stations. In order to find out the trends and influencing factors of visibility from different areas, grid-based population density was also used to classify different types of stations. Results show that visibility decreased steadily after 1980, especially in Eastern China. This kind of decrease usually happened in areas that have high population density and relative humidity (RH). The amplitude and frequency of visibility decline have a good relativity with the population that surrounded the observational station. However, results of Northwest China shows an increase in regional visibility, especially in the areas with a relatively low RH and low population, such as Inner Mongolia and Xinjiang. This might be caused by the decrease in frequency and intensity of sand storm in recent years. The decrease of visibility in South China is the most significant, which might be caused by economical production activities. The regional correlations of visibility between different observational sites showed an obvious increase in Northern and Eastern China, which reflects the aggravation of regional pollution in these areas.

Key words: visibility, population density, dust; multiple linear regression, regional pollution

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