Routes and clustering features of PM2.5 spillover within the Jing-Jin-Ji region at multiple timescales identified using complex network-based methods

As a resource-dependent local economy and heavy industry cluster, the Jing-Jin-Ji region has become China's largest source of air contaminant emissions and experiences frequent pollutant spillovers. integration process. One of the most urgent steps in the integration development process in Jing-Jin-Ji is achieving joint regional air pollution control in the cities comprising the region. Thus, this paper aims to provide a decision-making foundation for the collaborative governance of Jing-Jin-Ji cities with respect to PM2.5. To achieve this goal, spillover networks at multiple timescales were constructed using discrete wavelet transform, the GARCH-BEKK model and complex networks. The results showed that the interaction of the PM2.5 spillover behavior within Jing-Jin-ji is notably strong and that the spillover relationships are normally active for up to approximately one week. The Shijiazhuang and Baoding cities require more control due to their wide PM2.5 spillover range to other cities, such as Beijing and Chengde. Moreover, the PM2.5 spillover routes differ at different timescales. In the short term, the initial cities of spillover routes, e.g., the Cangzhou-Tianjin-Handan-Beijing route, are the critical control cities for the government, and the cities along the routes should take advanced measures to prevent bad air conditions when the former cities have heavy haze days. In addition, the Jing-Jin-Ji cities are divided into two to three clusters, and cities in the same cluster are mostly adjacent to each other. Therefore, the most cost-effective method for achieving joint regional air pollution control in Jing-Jin-Ji cities is to treat the cities in the same clusters as a whole. This study proposes a novel perspective for the regional joint control of air pollution based on complex networks, an approach that can be used to holistically and cost-effectively select areas of collaborative governance. (C) 2018 Elsevier Ltd. All rights reserved.