Spatial correlation of PM2.5 pollution in Beijing-Tianjin-Hebei and surrounding cities based on complex networks and their motif
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摘要:
近年来，随着污染治理和生态环境保护力度的加大，京津冀区域生态环境质量持续改善，但是以PM2.5为特征污染物的大气污染问题仍然不容小觑。选取了2015年1月1日—2022年11月30日京津冀及周边31个城市的PM2.5浓度数据，结合引力模型与皮尔逊相关指数，构建了京津冀及周边城市PM2.5污染的空间关联网络，并对该网络的整体特征与模体季节变化进行了统计分析。结果表明：邢台、石家庄、邯郸3个城市的度值、中介中心性、接近中心性均排名前3，它们在该网络中处于核心位置，与多个城市存在较强的PM2.5污染空间关联，对于控制PM2.5污染的空间溢出具有较为重要的作用；模体的四季关联网络密度和平均度相差不大，但均较高，各城市间的PM2.5存在较强的空间关联，其中在冬季网络密度最高，石家庄、邢台、衡水在模体四季关联网络中起着重要作用。对于在京津冀及周边城市PM2.5污染空间关联网络中处于核心位置的城市，在加强自身PM2.5治理的同时，应制定政策减弱其对相邻城市PM2.5污染的空间溢出效应；根据不同季节模体的关联情况，制定相应的协同治理政策，加强对这些模体城市PM2.5污染的协同治理，同时减弱它们之间的PM2.5污染空间关联与溢出效应。
Abstract:In recent years, with the increase of pollution control and ecological environmental protection, the quality of the ecological environment in Beijing-Tianjin-Hebei region has continued to improve, but the problem of air pollution with PM2.5 characteristics should not be underestimated. PM2.5 data of 31 cities in Beijing-Tianjin-Hebei and surrounding areas from January 1, 2015 to November 30, 2022 were selected, combined with the gravity model and Pearson correlation index, to construct a spatial correlation network of PM2.5 pollution in Beijing-Tianjin-Hebei and surrounding cities, and the overall characteristics of the network and the seasonal changes of the motif were analyzed statistically. The results showed that Xingtai, Shijiazhuang and Handan ranked top 3 in degree value, betweenness centrality and closeness centrality. They were at the core of the network and had strong spatial correlation with PM2.5 pollution in multiple cities, which played an important role in controlling the spatial spillover of PM2.5 pollution. The density and average degree of the four seasons correlation network of the motif were not different, but both were high. There was a strong spatial correlation between PM2.5 among cities, and the network density was the highest in winter. Shijiazhuang, Xingtai and Hengshui played an important role in the four seasons correlation network of the motif. For the cities in the core position of the spatial correlation network of PM2.5 pollution in Beijing-Tianjin-Hebei and surrounding cities, while strengthening their own PM2.5 control, policies should be formulated to reduce the spatial spillover effect of PM2.5 pollution on neighboring cities. According to the correlation of the motif in different seasons, corresponding collaborative governance policies should be formulated to strengthen the collaborative governance of urban PM2.5 pollution of the motif, while weakening the spatial correlation and spillover effect of PM2.5 pollution between them.
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Key words:
- Beijing-Tianjin-Hebei /
- PM2.5 /
- motif /
- collaborative governance
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图 2 2015—2022年京津冀地区PM2.5的皮尔逊相关系数热力图
Figure 2. Pearson correlation coefficient heat diagram of PM2.5 in Beijing-Tianjin-Hebei region from 2015 to 2022
图 3 京津冀及周边城市PM2.5污染空间关联社会网络
Figure 3. Social network related to PM2.5 pollution space of cities in Beijing-Tianjin-Hebei and surrounding areas
图 4 京津冀及周边城市度值排序
Figure 4. Degree value ranking of cities in Beijing-Tianjin-Hebei and surrounding areas
图 5 京津冀及周边城市接近中心性与中介中心性
Figure 5. Closeness centrality and betweenness centrality of cities in Beijing-Tianjin-Hebei and surrounding areas
图 6 京津冀及周边城市模块化与子群展示
Figure 6. Modular and subgroup display of cities in Beijing-Tianjin-Hebei and surrounding areas
表 1 季节关联网络的平均度和图密度
Table 1. Average degree and graph density of seasonal correlation network
季节 春季 夏季 秋季 冬季 平均度 12.120 13.533 12.774 13.484 图密度 0.416 0.407 0.426 0.449 
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