The Regression Analysis between the Meteorological Synthetic Index Sequence and PM2.5 Concentration


Adapting daily meteorological data provided by China International Exchange Station, and using principal component analysis of meteorological index for dimension reduction comprehensive, the regression analysis model between PM2.5 and comprehensive index is established, by making use of Eviews time series modeling of the comprehensive principal component, finally puts forward opinions and suggestions aim at the regression analysis results of using artificial rainfall to ease haze.

Share and Cite:

Liang, W. , Zhang, Z. , Gao, J. , Li, W. , Liu, X. , Bai, L. and Gui, Y. (2015) The Regression Analysis between the Meteorological Synthetic Index Sequence and PM2.5 Concentration. Applied Mathematics, 6, 1913-1917. doi: 10.4236/am.2015.611168.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] He, T. (2013) The Artificial Rainfall to Ease Haze in Wuhan, Contribute but Not Go on for Long Guangzhou Daily.
[2] Mei, P.Y. (2006) The Influence of Stable Weather Conditions on the Quality of the Environment in Tianjin. Urban Environment and Urban Ecology, 19, 37-49.
[3] Xu, W., Gan, Q.H. and Tang, Q. (2008) The Climate Characteristics and the Influencing Factors of Shantou Haze in 1951-2006. Meteorological and Environmental Newspapers, 24, 42-45.
[4] Wuhan Environmental Monitoring Center (2015) Environmental Quality Bulletin.
[5] (2014) China Meteorological Science Data Sharing Service Network, the Daily Data of Climate of Chinese International Exchange Station.
[6] Jolliffe, I.T. (2014) Principal Component Analysis.
[7] Mayer, J. (2005) Adaptive Random Testing by Bisection with Restriction. Springer, Berlin, 231-256.
[8] Liu, S.S. (2014) The Cloud Is Not Be Able to Rain. The Shijiazhuang Air Quality in the First “Severe” in June. Yanzhao Metropolis Net.

Copyright © 2022 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.