RESUMEN

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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RESUMEN

With the continuous abatement of industries and vehicles in the past years in China, the comprehensive understanding and scientific control of non-road construction equipment (NRCE) may play an important role in alleviating PM2.5 and O3 pollution in the next stage. In this study, the emission rates of CO, HC, NOx, PM2.5, CO2 and the component profiles of HC and PM2.5 from 3 loaders, 8 excavators and 4 forklifts under different operating conditions were tested for a systematic representation of NRCE emission characteristics. With the fusion of field tests, construction land types and population distributions, the NRCE emission inventory with a 0.1° × 0.1° resolution in nationwide and with a 0.01° × 0.01° resolution in Beijing-Tianjin-Hebei region (BTH) were established. The sample testing results suggested prominent differences in instantaneous emission rates and the composition characteristics among different equipment and under different operating modes. Generally, for NRCE, the dominant components are OC and EC for PM2.5, and HC and olefin for OVOC. Especially, the proportion of olefins in idling mode is much higher than that in working mode. The measurement-based emission factors of various equipment exceeded the Stage III standard to varying degrees. The high-resolution emission inventory suggested that highly developed central and eastern areas, represented by BTH, showed the most prominent emissions in China. This study is a systematic representations of China's NRCE emissions, and the NRCE emission inventory establishment method with multiple data fusion has important methodological reference value for other emission sources.