大气污染与雾霾天气已严重危害公众健康,影响了社会与经济的正常秩序。基于向量自回归(VAR)模型,综合运用广义脉冲响应函数和方差分解方法,利用西安市2013年1月1日-2014年12月31日空气质量和气象因素的相关数据,分析PM2.5与其影响因素动态关系,探讨其它大气污染物和气象因素对PM2.5的影响作用。实证研究表明:西安市PM2.5与其影响因素构成的动态系统是稳定的;一氧化碳、二氧化硫、臭氧和气温的正向变动会引起PM2.5浓度增加,风速和降水量的正向变动则会引起PM2.5浓度降低。建议将综合治理与专项治理措施相结合,保持政策持续性和协调性。
Air pollution and smog are the serious harms to public health and has affected the social and economic order. Based on the vector auto- regressive( VAR) model,we analyzed the dynamic relationship between the PM2.5and its influence factors,investigated the effect of other kinds of air pollutants and meteorological factors on the PM2.5by using the methods of generalized impulse response function,variance decomposition analysis and the related daily data from January 1,2013 to December 31,2014 in Xi'an city to the empirical study. The results show that the dynamic system that composed of PM2.5and its influence factors was stable; the increase of carbon monoxide,sulfur dioxide,ozone and the weather led to the increase of PM2.5concentration while the increase of the wind speed and the amount of precipitation resulted in the decrease of PPM2.5concentration. It is suggested that comprehensive air pollution governance should combine with special governance,and keep policy sustainable and harmonious.