Welcome to Francis Academic Press

Academic Journal of Business & Management, 2022, 4(6); doi: 10.25236/AJBM.2022.040610.

Analysis of Influencing Factors of Haze in Zhengzhou Based on Linear Regression

Author(s)

Yifan Gao

Corresponding Author:
Yifan Gao
Affiliation(s)

Shanghai University, Shanghai, China

Abstract

In recent years, various regions in China have been plagued by smog problems, and Zhengzhou, as the capital city of Henan, has a particularly prominent smog problem than other cities due to climate and economic development. In the past two years, smog pollution has improved slightly, but smog still plagues our lives. This paper analyses the changes in haze pollution in Zhengzhou in the past five years, draws the main reasons for the changes in haze pollution. Principal component analysis and regression analysis were used to establish a regression model of the influencing factors of haze in Zhengzhou. The results show that pollutant emissions and coal consumption have the most obvious impact on the degree of haze pollution in different years, and reasonable suggestions are put forward based on the current situation of haze pollution in Zhengzhou and the existing governance policies.

Keywords

Haze; Zhengzhou City; Principal Component Analysis; Linear Regression

Cite This Paper

Yifan Gao. Analysis of Influencing Factors of Haze in Zhengzhou Based on Linear Regression. Academic Journal of Business & Management (2022) Vol. 4, Issue 6: 59-65. https://doi.org/10.25236/AJBM.2022.040610.

References

[1] Cai F. (2017) Study on the impact of industrial structure on haze in Beijing-Tianjin-Hebei region [D]. Northwestern University. 

[2] Huang B.B. (2019) An analysis of the causes, hazards and management measures of haze in Luohe City[J]. Agricultural disaster research, 9(04): 113-114.

[3] Li L., Sun Y.X. (2015) Analysis and research on haze environment based on mean-valued principal component analysis [J]. Computer Application Research, 32(05): 1373-1375.

[4] Li Y.Y., Wang L.H. (2018) Grey correlation variance analysis of PM2.5 drivers in Beijing-Tianjin-Hebei region [J]. China Development, 18(04): 13-25.

[5] Lu N., Zhou J.B., Li Z.G., Wang Y.T., Jin W. (2015) Causes of haze in China and countermeasures for its management [J]. Hebei Industrial Science and Technology, 32(04): 371-376. 

[6] Meng Z.G., Yue X.N., Wang D., Yuan Z.H. (2015) Analysis of urban haze causation model based on multilayer regression [J]. Journal of Shenyang University (Natural Science Edition), 27(02): 139-142.

[7] Xie Q.J., Lu Y.L., Zhu J.M., Zhou J.B., (2017).Research on the quantitative levy of haze tax based on fuzzy comprehensive evaluation [J]. Journal of Huaiyin Normal College (Natural Science Edition), 16(02): 113-118.

[8] Yao, X.J., Li, Y.W., Liu, M.Z. (2014) Characteristics and formation mechanism of a winter haze–fog episode in Tianjin, China [J]. Atmospheric Environment, 98.

[9] Yan, S.Q., Zhu B., Kang H.Q. (2019) Long-Term Fog Variation and Its Impact Factors Over Polluted Regions of East China [J]. Journal of Geophysical Research: Atmospheres, 124(3).