基于时间序列分解的京津冀区域PM2.5和O3空间分布特征

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O₃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O₃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O₃，春、夏季PM_2.5和O₃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O₃浓度的贡献最大. PM_2.5的季节分量、短期分量以及O₃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O₃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O₃浓度的演变趋势...

Spatial Distribution Characteristics of PM2.5 and O3 in Beijing-Tianjin-Hebei Region Based on Time Series Decomposition

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 O₃ at different time scales is helpful to formulate scientific and effective pollution prevention and control measures. Here, the concentrations of PM_2.5 and O₃ 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 O₃. There was a positive correlation between PM_2.5 and O₃ 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 O₃ 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 O₃, 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 O₃ 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 O₃ 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 O₃ 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 O₃ concentration in Tangshan was the highest.