3.1.2. The Spatial Heterogeneity of Temporal Variations

Although PM2.5 concentrations in the study area have been decreasing on the whole, they express different temporal regulations in various areas. As shown in Figure S2, Beijing, Tianjin, and most cities in Hebei and Henan Provinces decreased from 2015 to 2019, while a few cities showed different patterns. The average concentrations in Hebei Province and Henan Province also had the same patterns as most of the cities under their jurisdictions. However, the patterns of cities in Shanxi Province and Shandong Province were quite different from the others. To be more specific, PM2.5 concentrations in Shanxi Province first went up but then decreased, and reached their highest level in 2017, presenting an inverted U-shaped trend. In Shandong Province, it first went down, and then it went up, reaching the lowest level in 2018 and showing a U-shaped trend. The patterns of most cities in the two provinces were consistent with their corresponding provinces. This heterogeneity may be related to differences in economic development, environmental protection policies, geographical differences, and other factors between the different provinces. The regions with the highest PM2.5 concentration in 2015 were Beijing and Henan Provinces, and Henan Province exhibited the highest PM2.5 concentration for the period of 2016–2019. After five years of decline, Beijing ranked last among the four provinces and two municipalities in 2019.

Specific to the urban level, the discrepancies in the reduction rates among different regions were more obvious, as shown in Figure S3. Specifically, BJ, BD, LF, DZ, and LC exhibited the highest reduction rate if more than 40%. Those of TY, YQ, JC, YC, and LFF were slightly less than 10%. The former was mainly concentrated in the Beijing– Tianjin–Hebei region, while the latter was under the jurisdiction of Shanxi Province. To further explore the differences in temporal variations, we plotted the PDFs of PM2.5 in each province or municipality from 2015 to 2019, as shown in Figure 3. To facilitate comparison, we divided the study area into the Beijing–Tianjin–Hebei region and its surrounding regions (Shandong, Hebei, Shanxi Province). In 2015, the PDFs of each province varied greatly. Shanxi Province had the highest peak value, while Beijing had the lowest. Although the concentration ranges of the two peak areas were similar, the occurrence probability of high PM2.5 concentration in Beijing was high, indicating that Beijing was prone to PM2.5 pollution events. On the whole, the peaks in the Beijing–Tianjin–Hebei region were lower, while those

in the surrounding region were higher, indicating that PM2.5 pollution in the Beijing–Tianjin– Hebei region was more serious than in its surrounding areas. From the temporal point of view, the curve variation of the Beijing–Tianjin–Hebei region is very significant, especially in terms of BJ. The Shandong, Henan, and Shanxi regions also showed a trend of pollution alleviation. It is worth noting that the PDFs curve of Henan Province was always at the bottom, indicating that it had higher PM2.5 pollution. After five years of improvement, the PDFs curves of the six regions showed a tendency to gradually coincide. Until 2019, the curves were quite similar, showing that the spatial differences of PM2.5 concentration were narrowing, which is similar to the research results of Jiang, He, and Zhou [22].
