基于时间序列分解的京津冀区域PM_(2.5)和O_(3)空间分布特征

Spatial Distribution Characteristics of PM_(2.5) and O_(3) in Beijing-Tianjin-Hebei Region Based on Time Series Decomposition

京津冀区域大气污染分布呈现明显的空间差异,厘清不同时间尺度下PM_(2.5)和O_(3)浓度分布有助于制定科学有效的污染防控措施.采用STL方法分解PM_(2.5)和O_(3)浓度,获取长期分量、季节分量和短期分量,研究其变化趋势与空间分布特征.结果表明,2017~2021年京津冀区域PM_(2.5)浓度下降幅度高于O_(3),春、夏季PM_(2.5)和O_(3)浓度呈正相关,秋、冬季呈现负相关,短期分量和季节分量分别对PM_(2.5)和O_(3)浓度的贡献最大.PM_(2.5)的季节分量、短期分量以及O_(3)的长期分量和短期分量均存在2个主成分,对应河北省中南部和京津冀区域北部,在不同时间尺度上京津冀区域PM_(2.5)和O_(3)均存在次区域分布.与原始序列相比,长期分量能够更好地反映PM_(2.5)和O_(3)浓度的演变趋势;季节分量和短期分量的标准差可用于衡量各城市PM_(2.5)和O_(3)浓度波动情况,太行山前各城市PM_(2.5)浓度季节分量和短期分量标准差较高,唐山的O_(3)浓度短期分量的标准差最高.

Notably,clear spatial differences occur in the distribution of air pollution among cities in the Beijing-Tianjin-Hebei(BTH)Region.Clarifying the concentration distribution of PM_(2.5) and O_(3) at different time scales is helpful to formulate scientific and effective pollution prevention and control measures.Here,the concentrations of PM_(2.5) and O_(3) were decomposed using a seasonal-trend decomposition procedure based on the loess(STL)method;their long-term,seasonal,and short-term components were obtained;and their temporal and spatial distribution characteristics were studied.The results showed that the decrease in PM_(2.5) concentration in the BTH Region from 2017 to 2021 was higher than that of O_(3).There was a positive correlation between PM_(2.5) and O_(3) concentrations in spring and summer and a negative correlation in autumn and winter.The short-term component and seasonal component had the greatest contribution to PM_(2.5) and O_(3) concentrations,respectively.There were two principal components in the seasonal and short-term components of PM_(2.5) and the long-term and short-term components of O_(3),corresponding to the central and southern part of Hebei Province and the northern part of the BTH Region.Sub-regional distribution of PM_(2.5) and O_(3) in the BTH Region at different time scales were found.Compared with that in the original series,the long-term component could better reflect the evolution trend of PM_(2.5) and O_(3) concentrations,and the standard deviation(SD)of the seasonal component and short-term component could be used to measure the fluctuation in PM_(2.5) and O_(3) concentrations in various cities.The SD of the seasonal and short-term components of the PM_(2.5) concentration in every city in front of Taihang Mountain was higher,and the SD of the short-term component of the O_(3) concentration in Tangshan was the highest.