Abstract
In China, the transportation sector contributes about 18% of the total carbon emissions. This research contributes to measuring the energy and carbon emission efficiency (ECEE) of regional transportation systems (RTS) in China considering uncertain carbon emissions. A radial chance-constrained data envelopment analysis (DEA) model is developed to estimate the overall efficiency, and a nonradial chance-constrained DEA model is presented to evaluate the pure energy efficiency (PEE) and the pure carbon emission efficiency (PCEE). We prove that the proposed chance-constrained DEA models can effectively address the uncertain carbon emissions when measuring efficiency. We find that most of China’s RTS have low ECEE and the inefficiencies are mainly due to the lower gasoline utilization efficiency and the lower kerosene utilization efficiency. In addition, east China performs better than central China, and central China performs better than west China. In China, the unbalanced regional development of the ECEE in transportation corresponds with the unbalanced regional economic development. We provide some valuable suggestions based on the evaluation of the potential cuts in each kind of energy and the potential decreases in carbon emissions.
Highlights
Since China started economic reforms in 1978, the country has been experiencing rapid economic development [1, 2]
We compare the efficiency scores resulting from model (8) with those resulting from the radial deterministic data envelopment analysis (DEA) model
Discussion and Suggestion. e uncertainty of carbon emissions can significantly affect the results of efficiency evaluation. erefore, decision-makers should take uncertain carbon emissions into account when they measure the performance of regional transportation systems (RTS) [54, 55]. e risk criterion has effects on the results of efficiency evaluation
Summary
Measuring the Energy and Carbon Emission Efficiency of Regional Transportation Systems in China: Chance-Constrained DEA Models. In China, the transportation sector contributes about 18% of the total carbon emissions. Is research contributes to measuring the energy and carbon emission efficiency (ECEE) of regional transportation systems (RTS) in China considering uncertain carbon emissions. A radial chance-constrained data envelopment analysis (DEA) model is developed to estimate the overall efficiency, and a nonradial chance-constrained DEA model is presented to evaluate the pure energy efficiency (PEE) and the pure carbon emission efficiency (PCEE). We prove that the proposed chance-constrained DEA models can effectively address the uncertain carbon emissions when measuring efficiency. In China, the unbalanced regional development of the ECEE in transportation corresponds with the unbalanced regional economic development. We provide some valuable suggestions based on the evaluation of the potential cuts in each kind of energy and the potential decreases in carbon emissions
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
