The Regression Models of PM2.5 and Other Air Pollutants in Wuhan

Ling Na Li; Xiao Ping Gong; Lin Cheng Dai; Xiao Hong Zhan

doi:10.4028/www.scientific.net/AMR.864-867.1356

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 864-867The Regression Models of PM2.5 and Other Air...

The Regression Models of PM2.5 and Other Air Pollutants in Wuhan

Abstract:

In this study PM2.5 and other five air pollutants (i.e. SO₂, NO₂, PM10, CO, and O₃) have been analyzed by using statistical methods. Two different regression models were established quantitatively in this paper to find out the factors and causes of PM2.5 and were compared by using the partial data from January 1 to August 26, 2013, which is obtained from Wuhan Environmental Protection Bureau. The results indicate that the correlation coefficients of PM2.5 and other four air pollutants CO, SO₂, NO₂, and PM10 are all over 0.7, which shows significant linear correlations, and regression models were proved illustrious and accurate by testing and contrast.

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Periodical:

Advanced Materials Research (Volumes 864-867)

Pages:

1356-1359

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.864-867.1356

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Online since:

December 2013

Authors:

Ling Na Li*, Xiao Ping Gong, Lin Cheng Dai, Xiao Hong Zhan

Keywords:

Air Pollution, Correlation Analysis, Factors and Causes, PM2.5, Regression Model

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* - Corresponding Author

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