Western Collaborative Innovation Research Center for Energy Economy and Regional Development, Xi'an University of Finance and Economics, Xi'an, 710100, China.
Environ Sci Pollut Res Int. 2023 Jun;30(27):70541-70557. doi: 10.1007/s11356-023-27434-y. Epub 2023 May 6.
In this paper, we empirically study the spatial association network of PM and the factors influencing those correlations using the gravity model, social network analysis (SNA), and the quadratic assignment procedure (QAP) based on data from the Beijing-Tianjin-Hebei urban agglomeration (BTHUA) in China from 2005 to 2018. We draw the following conclusions. First, the spatial association network of PM exhibits relatively typical network structure characteristics: the network density and network correlations are highly sensitive to efforts to control air pollution, and there are obvious spatial correlations within the network. Second, cities in the center of the BTHUA have large network centrality values, while cities in the peripheral region have small centrality values. Tianjin is a core city in the network, and the spillover effect of PM pollution in Shijiazhuang and Hengshui is the most noticeable. Third, the 14 cities can be divided into four plates, with each plate having obvious geographical location characteristics and linkage effects. The cities in the association network are divided into three tiers. Beijing, Tianjin, and Shijiazhuang are located in the first tier, and a considerable number of PM connections are completed through these cities. Fourth, differences in geographical distance and urbanization are the main drivers of the spatial correlations of PM. The greater the urbanization differences, the more likely the generation of PM links is, while the opposite is true for differences in geographical distance.
本文运用引力模型、社会网络分析（SNA）和二次分配程序（QAP），基于 2005-2018 年中国京津冀城市群的观测数据，实证研究了 PM 的空间关联网络及其关联因素。主要结论如下：第一，PM 的空间关联网络具有较为典型的网络结构特征：网络密度和网络关联度对空气污染控制的努力高度敏感，网络内部存在明显的空间关联。第二，京津冀城市群中心城市的网络中心度值较大，而外围城市的中心度值较小。天津是网络的核心城市，石家庄和衡水的 PM 污染溢出效应最为显著。第三，14 个城市可分为四个板块，每个板块具有明显的地理位置特征和联动效应。关联网络中的城市分为三个层次，北京、天津和石家庄位于第一层次，通过这些城市完成了相当数量的 PM 联系。第四，地理距离和城市化水平的差异是 PM 空间关联的主要驱动因素。城市化水平差异越大，PM 联系产生的可能性就越大，而地理距离的差异则相反。
