Analysis on the Influencing Factors of PM2.5Concentrations in Chinese Cities

2nd International Symposium on Resource Exploration and Environmental Science

生态环境科学

Zhou, Hao^1 ; Zhu, Bingxiang^2

National Research Center of Cultural Industries, Central China Normal University, Hubei Province, Wuhan, China^1

School of Electrical Engineering, Wuhan University, Hubei Province, Wuhan, China^2

关键词: Correlation coefficient method;    Influencing Factors;    Multivariate regression models;    PM2.5 concentration;    Policy suggestions;    Regression model;    Statistical significance test;    Stepwise regression method;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/170/3/032064/pdf
DOI  :  10.1088/1755-1315/170/3/032064

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Recently, haze weather has become a common phenomenon in large cities. PM2.5 usually refers to fine particulate matter with a diameter less than 2.5 micrometres, which is considered to be the "culprit" of haze weather. Modern society develops at a high speed, a series of economic and social activities are bound to discharge a large amount of PM2.5. Once it goes beyond air endurance, with unstable weather factors, it is easy to appear a wide range of haze. Based on data from 31 provincial capitals and municipalities directly under the central government, main reasons for the concentrations of PM2.5 in major cities were studied. The related factors were choosing to establish a multivariate regression model, MATLAB software was used as an instrument. The correlation coefficient method and stepwise regression method were used to eliminate redundant variables. By carrying out economic significance test and statistical significance test, the revised accurate model results were achieved. Finally, according to the results of the model, feasible ways to reduce PM2.5 concentrations are obtained, which provide policy suggestions for reducing haze and improving air conditions in China.