摘要
利用回归分析和相关性分析研究气象因素对长沙PM_(2.5)、PM_(10)浓度影响的季节性差异。研究表明:(1)春季,与PM_(2.5)、PM_(10)浓度相关系数最大的气象因子分别为日降水量、日最高气温;夏季均为日最大风速;秋季均为日平均相对湿度;冬季为日降水量、日最高气温。(2)秋季气象因素与PM_(2.5)多元回归分析R^2(P<0.01)最大,为0.269;春季次之,R^2为0.159;春、冬季较低,R^2<0.1;秋季气象因素与PM_(10)多元回归分析R^2(P<0.01)最大,为0.572;春、夏、秋季,R^2分别为0.258、0.265、0.252。本结果揭示了不同季节气象条件影响PM_(2.5)、PM_(10)浓度的差异程度,利于提高城市PM10、PM_(2.5)预测的精度水平。
In this paper, regression analysis and correlation analysis were used to study the seasonal differences of meteorological factors on PM2.5 and PM10 concentrations in Changsha. The results showed that： （ 1 ） In spring the weathering factors that had largest correlation coefficient of PM2.5 and PM10 concentration, are daily precipitation and daily maximum temperature, in summer is maximum wind speed, in autumn is daily average relative humidity, in winter were daily precipitation and maximum daily temperature. ; （2） In autumn, R^2 （P 〈0. 01 ） of meteorological factors and PM2.5 regression analysis was largest, 0. 269. R^2 was 0. 159 in summer, spring and winter were lower R^2 〈 0. 1. R^2 （P 〈 0. 01 ） of meteorological factors and PM10 multiple regression analysis, in autumn was largest, 0. 572. In spring, summer, autumn, R^2 were 0. 258, 0. 265, 0. 252, respectively. The results showed that the meteorological conditions affect the PM2.5 and PM10 concentrations in different seasons, which improved the accuracy of prediction of PM10 and PM2.5.
出处
《四川环境》
2017年第4期103-108,共6页
Sichuan Environment
