A study on PM2.5 distribution over China using principal component analyses

Di Chen, Yong Wen Zhang, Xue Xi Tie

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Recently China has been suffering from air pollution. The ministry of environmental protection has been publishing air quality index data since 2013, which has enabled us to better understand the situation of air pollution. We used the PM2.5 data in 2015, to study whether the spatial variation of PM2.5 is local or regional. We combined Correlation analysis with the Principal Component Analysis method, and discovered that the PM2.5 concentration in China can be divided into different modes. For the first mode, most of the country experiences cyclonic growth and falls, which means that there is a nationwide regional trend. The only accident appears in the third season, probably a result of the east Asia summer monsoon. For the second mode, all seasons contributions are close, and there’s no evident cluster formed, attributing to local emission and meteorological conditions. We also compared the mean value of the correlation efficient with the geographical distance for all stations. There’s a double-log relationship as m(x)<x–β in the 1st, 2nd and 4th season, where β equals 0.73 and 1. The equation doesn’t exist on the 3rd season, which means there is some other mechanism. In whole This indicates that the PM2.5 concentration around the country is not local but regional related.

Original languageEnglish
Article number020501
JournalScientia Sinica: Physica, Mechanica et Astronomica
Issue number2
StatePublished - 1 Jan 2017
Externally publishedYes


  • Correlation function
  • PM2.5
  • Principle component analysis

ASJC Scopus subject areas

  • General Physics and Astronomy


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