PM2.5浓度影响因素的主成分回归分析

Principal component regression analysis of influencing factors of PM2.5 concentration

选取全国31个城市,对空气中细颗粒物(PM 2.5)浓度的影响因素进行分析。为处理自变量之间存在的共线性,选用主成分回归。确定主成分的个数,将原自变量的主成分代替原自变量进行回归分析。总结出造成空气中细颗粒物(PM 2.5)浓度上升的因素分为两方面,直接因素中二氧化氮浓度和间接因素中汽车数量。

For 31 cities across the country, the influential factors to concentration of air fine particulate matter （PM 2. 5） are analyzed. Principal component regression is selected to process the collinearityamong the independent variables. We choose the number of principal components and replace the original variables with principal component with regression analysis. It comes to a conclusion that the reasons for increase of PM 2.5 are the following, increase of NO2 concentrations and the number of cars.