A complex network analysis of heavy air pollution transport in NW China's urban agglomerations

Urban agglomerations in arid and semi-arid regions face severe environmental challenges, When the Air Quality Index (AQI) exceeds 200, it is defined as severe pollution. To analyze the spatiotemporal characteristics of air pollution and interactions between cities in such regions, this study constructed a pollutant transport network for heavy air pollution episodes from 2015 to 2024 in typical northwestern Chinese urban agglomerations. These included the Ningxia Yellow River, Guanzhong Plain and Lanzhou-Xining urban agglomerations, and the network was constructed based on complex network theory. When defining edge weights, the model incorporated pollutant concentration correlation coefficients, wind direction, and geographical factors, overcoming the limitations of traditional single-correlation methods and providing a more realistic representation of pollutant transport processes. Furthermore, two distinct pollution episodes were examined to show that the model accurately reflects the impact of wind on the transport of pollution between cities. The results show that 89 heavy pollution episodes occurred during this period, lasting 1-10 days, primarily in winter and spring, with PM_2.5 and PM₁₀ as the dominant pollutants and a decreasing annual trend in pollution levels. Strong correlations between pollutants in different cities were primarily observed when the inter-city distance was within 200 km, the altitudes of the cities were between 1000 and 1500 m, and their altitude difference was less than 500 m. Based on the PageRank algorithm, Yinchuan and Wuzhong in the Ningxia Yellow River Urban Agglomeration were identified as key pollution transport hubs: Yinchuan was dominated by SO₂ (PR = 2.4297) and CO (PR = 2.3883), while Wuzhong was mainly affected by PM_2.5 (PR = 1.9642), PM₁₀ (PR = 1.9014), O₃ (PR = 2.1329), and NO₂ (PR = 1.7413). Under northwesterly winds exceeding 2 m/s, pollution in Wuzhong was exacerbated by upwind Yinchuan. Louvain community detection revealed that the Guanzhong Plain is prone to complex pollution, the Ningxia Yellow River urban agglomeration frequently experiences concomitant SO₂ and O₃ pollution, and the Lanzhou-Xining urban agglomeration had lower pollution frequency, with only Haidong exhibiting high-frequency CO pollution. By integrating complex network analysis with multi-source geographic and meteorological data, this study offers a novel framework for identifying critical pollution transport hubs and transmission pathways in arid and semi-arid urban agglomerations. The findings provide actionable insights for targeted emission controls, cross-city collaborative governance, and sustainable urban development in similar regions globally.