Drivers of civil aviation emissions in China: Considering spatial heterogeneity and interdependence

Abstract

CO₂ and NO_x emissions from aviation transportation are critical components of overall transportation-related emissions, significantly impacting both climate and air quality. To implement more targeted and effective measures for mitigating emissions in this sector, it is essential to conduct empirical analyses that deepen our understanding of the factors influencing aviation emissions. Previous studies have predominantly focused on emissions from the entire transportation sector, with limited research specifically addressing aviation emissions. Notably, past research has often overlooked the existence of spatial autocorrelation patterns in aviation emissions. Here, we developed a civil aviation emission inventory at the provincial scale for China using a bottom-up approach based on daily flight schedules from 2012 to 2019. By utilizing the STIRPAT and spatial Durbin models, we identified key factors affecting civil aviation CO₂ and NO_x emissions and assessed their spatial effects at the provincial level in China. Spatial-temporal analysis revealed distinct patterns and spatial non-stationarity in CO₂ and NO_x emissions from civil aviation. The results also highlighted that GDP, per capita GDP, the transportation price index, and per capita consumption expenditure positively drive. The results emphasize the importance of close collaboration among different provinces to effectively decarbonize and reduce pollution in the civil aviation sector given the significant observed spatial dependencies. These findings provide valuable insights for policymakers in formulating strategies to reduce aviation emissions and understanding the influence of different socioeconomic activities on emissions.