Spatial Effects of Transportation Carbon Emission Intensity Based on SDM Model: A Case Study in East China

By collecting the research data from seven provinces in East China from 2003 to 2019, a spatial Durbin model (SDM) is established to study the spatial effects of carbon emission intensity in East China. Then the analysis of transport carbon intensity, grey correlation degree and spatial autocorrelation test are further examined. The results show that the transportation carbon emission intensity has a significant spatial effect among provinces in East China. The proportion of tertiary industry and population density has a negative spatial direct effect on transportation carbon emission intensity. Passenger turnover, urban public vehicles and highway mileage have a positive spatial direct effect on transportation carbon emission intensity. The urbanization rate has an insignificant spatial direct effect on transportation carbon emission intensity. Passenger turnover and highway mileage have a positive spatial spillover effect on carbon emission intensity. In contrast, the proportion of the tertiary industry, population density, urbanization rate and urban public vehicles have no significant spatial spillover effect on carbon emission intensity.