[Analysis of Spatial and Temporal Evolution of Carbon Emission Productivity in Provincial Transportation Industry]

This research takes the transportation industries of 30 provinces in China as the research object. Based on the SBM super-efficiency model, the total-factor carbon-emission productivity of the transportation industry from 2010 to 2021 was measured. Dynamic analysis was carried out by combining the Malmquist-Luenberger index model and kernel density estimation. Meanwhile, the Theil index method and the coefficient of variation were used to study its regional differences. The spatial and temporal evolution characteristics and driving mechanisms were systematically explored with the help of the spatial geographically weighted regression model. The research results showed that: ① In terms of time series, from 2010 to 2021, the carbon-emission productivity of the transportation industry in the whole country and the eastern, central, and western regions showed a fluctuating upward trend, with average annual growth rates of 5.41%, 7.54%, 4.90%, and 4.79%, respectively. Technological progress and pure technical efficiency were the main driving factors. The increase in the carbon-emission productivity of the transportation industry in the eastern region was greater than the national level, while the increases in the central and western regions were less than the national level. ② In terms of spatial distribution, there were obvious regional differences in the carbon-emission productivity of China's transportation industry. Overall, it showed a spatial distribution characteristic of "high in the east and low in the west, " with "medium-low values as the main and high values as the supplement." The relative differences shown by the average value of the coefficient of variation from large to small were those of the eastern region, western region, and central region in turn. The relative difference in the carbon-emission productivity of the eastern region showed a narrowing trend, while the relative differences in the central and western regions showed an expanding trend. ③ The kernel density analysis showed that the carbon-emission productivity in the eastern region was concentrated in the medium-low level, the central region showed a broad single-peak and strong heterogeneity, and the western region showed polarization. ④ The spatial geographically weighted regression analysis revealed the heterogeneity of driving factors: Labor input continuously promoted positively in the West, and its effect strengthened in the later stage in the East; the impact of investment showed a dynamic evolution of "negative-dominated to positive-expansion, " and the regional gap gradually narrowed; and the inhibitory effect of energy intensity was stronger in the east than in the west.