CO2 reduction from transportation is exerting significant effects on global CO2 reduction. This industry contributes 23.96% of global CO2 emissions. In this research, an ecological network input–output interval fuzzy linear programming (EIFP) method is developed to clarify CO2 reduction responsibilities and depict transfer relationships of transportation. This method integrates input–output analysis (IOA), inexact rough interval fuzzy linear programming (IRFLP) and ecological network analysis (ENA) into a general framework. The proposed method is employed for calculating inter-provincial CO2 transfer under different situations in 30 provinces of China and further supporting the formulation of regional reduction policies. Results demonstrate that transportation energy demand of Beijing is dependent on imports, which indirectly increases CO2 reduction pressure in energy supply areas. Therefore, CO2 reduction responsibility should be traced to source and included in emission reduction plan of energy demand areas. In inter-provincial CO2 transfer relationships of natural gas, positive relationships account for a higher proportion; therefore, it is feasible to consider raising the proportion of natural gas in the future development direction of transportation. The achievements of this paper can provide scientific references for decision makers to formulate CO2 reduction policies in transportation.

The transfer of carbon dioxide (CO2) implied in inter-sectoral trade is significantly affecting the process of reducing CO2 emissions in China. This phenomenon also affects Zhejiang Province, which has the top five GDP in China. In this study, a universal modeling system is developed to clarify CO2 emission reduction responsibilities and visualize relationships of each pair of transfers in Zhejiang Province. The system includes “three modules”, namely input-output module, CO2 emission factor module and ecological network module. The proposed modelling system is employed for sectors of Zhejiang province. Research results demonstrate that industry should assume more responsibility for emission reduction; the existing development models of various industries need to be further adjusted. Achievements of this research will provide a scientific reference and a strong basis for decision-makers to formulate reasonable emission reduction policies in Zhejiang Province.