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China’s rapid economic growth is accompanied by increasing energy consumption and severe environmental problems. As sustainable development can only be achieved by reducing energy intensity, new energy and renewable energy investment, as well as improving traditional energy efficiency, is becoming increasingly important. However, past energy efficiency assessments using data envelopment analysis (DEA) models mostly focused on radial and non-radial DEA model analyses. However, traditional radial DEA models ignore non-radial slacks when evaluating efficiency values, and non-radial DEA models ignore the same proportionality as radial DEA when evaluating efficiency value slacks. To balance the radial and non-radial model characteristics and consider undesirable output, this study combines a modified Epsilou-based measure (EBM) DEA and undesirable output and proposes a modified undesirable EBM DEA model to analyze the efficiency of China’s new and traditional energy sources. The empirical results found that (1) most new energy investment in most municipalities/provinces rapidly grew from 2013 to 2016; (2) as the annual efficiency score was only 1 in Beijing, Inner Mongolia, Shanghai, and Tianjin, the other 26 municipalities/provinces need significant improvements; (3) traditional energy efficiency scores were higher than new energy efficiency; and (4) NO₂ efficiencies are slightly better than CO₂ and SO₂ efficiencies. Full article

The Yangtze River Economic Belt (YREB) is one of the most important areas for the economic growth of China, but rapid development has caused tremendous damage to the energy and ecological environments of the region. Very few studies have compared the carbon emissions of YREB with that of non-YREB and furthermore, have not considered regional differences and radial or non-radial characteristics in their analysis. This paper thus selects the energy consumption data of 19 provinces and cities in YREB and 19 provinces and cities in non-YREB from 2013 to 2016, constructs the modified meta-frontier Epsilou-based measure (EBM) data envelopment analysis (DEA) model and adds an undesirable factor, energy consumption, and CO₂ emission efficiency of each province and city of the two regions. The results are as follows. (1) China’s provinces and cities have different energy efficiency scores in energy consumption, economic growth, and CO₂ emissions. The regional ranks and technology gaps of five provinces and cities in non-YREB and of four provinces and cities in YREB exhibit a decline. Overall, the ranks and technology gaps of the provinces and cities in YREB are significantly lower than those in non-YREB, meaning that there is greater room for efficiency improvement in the latter region. (2) The gross domestic product (GDP) and CO₂ efficiency values of non-YREB provinces present great differences, especially the CO₂ efficiency value that ranges from 0.2 to 1, while their values in YREB are more balanced with little difference between provinces and cities. Thus, YREB is more coordinated in terms of energy savings and air pollutant reduction. (3) Some cities with good economic development such as Beijing, Shanghai, and Tianjin have regional and technology gap values of one, indicating that they not only target economic growth but also address energy savings and air pollutant reduction. The regional rank and technology gap values of some underdeveloped provinces such as Neimenggu, Ningxia, and Qinghai are also one. Finally, this research proposes countermeasures and recommendations to both areas. Full article