2008～2017年北京市PM2.5周期性变化特征与影响机制

利用Morlet小波方法分析北京市2008~2017年PM_2.5资料，结果表明，北京市PM_2.5浓度存在显著的日变化、周变化、以及季节和年变化周期性特征，并且秋冬季的周期性特征显著高于春夏季.结合气象资料，包括水平风速、大气边界层高度、以及大气稳定度指数等，分析PM_2.5不同周期性变化对应的主要影响机制表明：大气边界层过程是PM_2.5日变化的主要影响机制，导致PM_2.5浓度白天低、夜间高.秋冬季PM_2.5日变化幅度高于春夏季；天气过程是PM_2.5周变化的主要机制，PM_2.5浓度与天气变化过程带来的风速变化和边界层高度呈强反相关关系；PM_2.5的季节变化与大气扩散能力的季节变化密切相关，秋冬季减弱的大气扩散能力加速了PM_2.5在近地面累积，春夏季则相反.

Multi-time scale variations of the PM2.5 in Beijing and its key mechanisms during 2008 to 2017

The variation of PM_2.5 concentration during 2008 to 2017 in Beijing urban area was investigated collectively using the Morlet wavelet method to understand the multi-time scale oscillations of PM_2.5. PM_2.5 in Beijing owned clear temporal variations(on diurnal, week, to seasonal timescales), especially in autumn and winter. Further analyses of wind, planetary boundary layer(PBL),and air stagnation index(ASI) revealed the mechanisms that affect multi-scale temporal oscillations of the PM_2.5. The analyses indicated: the diurnal PM_2.5 variation was closely related to boundary layer process with high concentration at nighttime and low concentration at daytime. The diurnal variations of PM_2.5 in autumn and winter was higher than that in spring and summer; the weekly PM_2.5 variation was closely related to synoptic process, and the PM_2.5 concentration was anti-correlated to wind speed and PBL height; the seasonal variation of PM_2.5 was caused dominantly by the seasonal variation of atmospheric diffusion capacity with high concentration in autumn and winter and low concentration in summer and spring.