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Air pollution exhibits significant spatial spillover effects, complicating and challenging regional governance models. This study innovatively applied and optimized a statistics-based complex network method in atmospheric environmental field. The methodology was enhanced through improvements in edge weighting and threshold calculations, leading to the development of an advanced pollutant transport network model. This model integrates pollution, meteorological, and geographical data, thereby comprehensively revealing the dynamic characteristics of PM2.5 and O3 transport among various cities in China. Research findings indicated that, throughout the year, the O3 transport network surpassed the PM2.5 network in edge count, average degree, and average weighted degree, showcasing a higher network density, broader city connections, and greater transmission strength. Particularly during the warm period, these characteristics of the O3 network were more pronounced, showcasing significant transport potential. Furthermore, the model successfully identified key influential cities in different periods; it also provided detailed descriptions of the interprovincial spillover flux and pathways of PM2.5 and O3 across various time scales. It pinpointed major pollution spillover and receiving provinces, with primary spillover pathways concentrated in crucial areas such as the Beijing-Tianjin-Hebei (BTH) region and its surrounding areas, the Yangtze River Delta, and the Fen-Wei Plain. Building on this, the model divided the O3, PM2.5, and synergistic pollution transmission regions in China into 6, 7, and 8 zones, respectively, based on network weights and the Girvan Newman (GN) algorithm. Such division offers novel perspectives and strategies for regional joint prevention and control. The validity of the model was further corroborated by source analysis results from the WRF-CAMx model in the BTH area. Overall, this research provides valuable insights for local and regional atmospheric pollution control strategies. Additionally, it offers a robust analytical tool for research in the field of atmospheric pollution.

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O3 pollution in China has worsened sharply in recent years, and O3 formation sensitivity (OFS) in many regions have gradually changed, with eastern China as the most typical region. This study constructed the transport networks of O3 and NO2 in different seasons from 2017 to 2020. The transport trends and the clustering formation patterns were summarized by analyzing the topological characteristics of the transport networks, and the patterns of OFS changes were diagnosed by analyzing the satellite remote sensing data. Based on that, the main clusters that each province or city belongs to in different pollutant transport networks were summarized and proposals for the inter-regional joint prevention and control were put forward. As the results showed, O3 transport activity was most active in spring and summer and least active in winter, while NO2 transport activity was most active in autumn and winter and least active in summer. OFS in summer mainly consisted of transitional regimes and NOx-limited regimes, while that in other seasons was mainly VOC-limited regimes. Notably, there was a significant upward trend in the proportion of transitional regimes and NOx-limited regimes in spring, autumn, and winter. For regions showing NOx-limited regime, areas with higher out-weighted degrees in the NO2 transport network should focus on controlling local NOx emissions, such as central regions in summer. For regions showing VOC-limited regime, areas with higher out-weighted degrees in the O3 transport network should focus on controlling local VOCs emissions, such as central and south-central regions in summer. For regions that belong to the same cluster and present the same OFS in each specific season, regional cooperative emission reduction strategies should be established to block important transmission paths and weaken regional pollution consistency.

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The eastern China presented the most serious O3 pollution and increasingly prominent regional characteristics. To understand the transport characteristics of O3 and its precursors and identify their potential relationships are of great guiding significance for interregional joint prevention and control. In this study, the annual and seasonal transport networks of O3 and its precursors (NO2 and CO) during 2017-2021 were constructed by applying the complex network method to air quality observations. And the key spatial clusters, the spillover paths and the potential links among pollutants were comprehensively analyzed based on the topological characteristic analysis of the established air pollutant transport networks. As the results showed, O3 pollution in the eastern China was affected by active regional transports of O3 and its precursors. Regional transports of O3, NO2, and CO were more prominent in autumn and showed high synchronization. The regional transport of precursors, especially NOx, was an important cause of regional O3 pollution. Air pollutant transport characteristics varied with seasons and regions, which demonstrating the importance of regulating seasonal and regional differentiated joint prevention and control strategies, especially for NOx. The results of this study can provide science-based guidance for the regional cooperative control of O3 pollution in the eastern China, and the application of complex networks can also provide a new methodological perspective for the study of air pollution transmission.

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Inter-provincial trade can bring "emission leakage", and consequently influence the air quality and public health. However, there has been a lack of systematic research on air pollution and public health related to emission leakage embodied in inter-provincial trade of China. Here, we systematically evaluated for the first time the influence of emission leakage on national air pollution and related premature deaths in 2012 of China. Unexpected opposite influences of emission leakage on emission and air quality/public health were discovered. Emission leakage embodied in inter-provincial trade in 2012 of China led to an increase of 1.4 % to 4.8 % in national air pollutant emissions, but a decrease of 1.5 % (-0.8 µg·m-3) in population-weighted concentration of PM2.5, while avoiding 1.1 % (-1.4 × 104 people) of premature deaths. Therefore, to reveal the intrinsic mechanism of this opposite influences, we proposed two coefficients, the Concentration per unit primary PM2.5 emission (CPE, unit: µg·m-3/t) and the Death per unit primary PM2.5 emission (DPE, unit: people/t), to characterize the response of air quality and health to emission leakage embodied in inter-provincial trade. Statistical analysis indicated that both the above coefficients showed significant negative correlation (P < 0.05) with provincial PM2.5 emissions changes. The findings offer a means of adjustment and its related evaluation parameters for the emission transfer caused by inter-provincial trade, thereby contributing to further improvement environmental and health benefits through inter-provincial trade.

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Increasingly prominent pollution levels and strong regional characteristics of O3, especially in economically developed eastern China, called for a regional cooperation strategy based on transport quantification. This study adopted the complex networks to construct the O3 Transport Network (OTN) to explore characteristics in eastern China in the summer of 2017 and 2021, whose results were afterward verified with spatial source apportionment results simulated with WRF-CMAQ-ISAM. As OTN suggested, O3 transport showed stronger and faster characteristics in eastern China in 2021 than in 2017, judging from changes in the network density, number of connections, transport ranges, and transport paths. Among all cluster communities, inland Shandong was the most important O3 transport hub, the Central Community was the largest community, and the Southern Community showed the closest inter-city transport relationships. In- and out-weighted degrees in OTN showed relatively superior consistency with the transport matrix obtained with WRF-CMAQ-ISAM, and can be explained by wind fields. Generally, O3 pollution in the whole eastern China showed more frequent intra-regional transport and more strengthened inter-city correlations in 2021 than in 2017, meanwhile, northerly and southerly cities exhibited strengthening and weakening trends in O3 transport, respectively. Despite the completely different principles of complex networks and air quality models, their results were mutually verifiable. This study presented a comprehensive understanding of O3 transport in eastern China for further formulation of regional collaborative strategies and provided the methodological verification for applying complex networks in the atmospheric environment field.

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This study aimed to establish the emission factors and the emission inventory of agricultural machinery in Beijing in 2017 under real-world operation. The emissions of typical harvesters, tractors, agricultural transport vehicles, and farm construction machinery under real-world operation were tested by a portable emission measurement system. The results showed that different operation modes have a greater impact on the tailpipe emissions of agricultural machinery. The CO, NOx, HC, and PM emissions were relatively stable when the engine is idling and moving compared to when the excavator is performing actual work. According to the classification and emission standards of various types of machinery, a relatively perfect emission factor system of agricultural machinery in Beijing was established, which can provide reference and support for relevant research and management decisions. According to the emission factors of agricultural machinery and fuel consumption in Beijing, the emissions of CO, NOx, HC, and PM in 2017 were 2566.60, 1239.29, 563.08, and 538.32 t, respectively. The total pollutants of transport machinery, tractors, and combined harvester accounted for 98%, 95%, 95%, and 98% of the total concentrations of CO, NOx, HC, and PM, respectively. Therefore, transport machinery, tractor, and combined harvester should be the key control objects in the reduction of agricultural machinery pollution.