基于KZ滤波法的河北省PM2.5和O3浓度不同时间尺度分析研究

大气细粒子和臭氧是影响我国城市空气质量的主要污染物质,其浓度的大小不仅与污染源的排放量有关,气象条件也是影响其浓度分布特征的重要因素.要评估污染物减排措施的效果,有必要将气象条件的影响剥离出来,仅评估排放量的降低对污染物浓度长期变化趋势的影响.本文使用KZ(Kolmogorov-Zurbenko)滤波方法对河北省石家庄、保定、张家口三市2013—2017年PM_(2.5)和O_3逐日浓度时间序列进行分解,并使用同期地面气象观测数据对各时间序列进行逐步回归分析,将经过KZ滤波后的长期序列与经逐步回归后的结果的差值再次进行滤波处理,得到去除气象影响的污染物浓度长期变化趋势,该浓度仅与污染物的排放量有关.结果表明,因污染源排放的影响,河北省三市大气PM_(2.5)浓度在研究年内除在2017年初略有上升以外,其余季节均呈下降趋势.河北省三市大气O_3浓度在研究年内均有波动上升趋势.气象条件对PM_(2.5)浓度长期变化趋势的影响大于O_3.

Study on different time scales of PM2.5 and O3 concentrations in Hebei Province based on KZ filter

Atmospheric fine particles and ozone are the main pollutants that affect air quality of cities in China. Their concentrations and distributions are influenced by both emissions from pollution sources and meteorological conditions. In order to evaluate the effectiveness of measures taken to reduce air pollution, it is necessary to subtract meteorological effect from the original time series of air pollutant. The long-term trend produced only by reduction of emissions can thus be analyzed. In this study, Kolmogorov-Zurbenko (KZ) filter was used to decompose concentrations of PM_2.5 and O₃ into three components during the period of 2013-2017 in Shijiazhuang, Baoding and Zhangjiakou in Hebei Province. Stepwise regression analysis and residual analysis were used to obtain the meteorological adjusted time series of pollutant. Our results revealed that the emission of PM_2.5 showed a downward trend in three cities in Hebei Province during the studied years due to the influence of anthropogenic emissions, except for the early days in 2017. The concentration of O₃ fluctuated upward during the study period. The effect of meteorological conditions was greater for the long-term variation trend of PM_2.5 than that of O₃.