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Energy productivity is a key indicator to evaluate energy efficiency. However, few researchers focus on China’s energy productivity at the city level or its spatial patterns. The aim of this paper is to investigate the determinants and spatial character of changes to China’s energy productivity at the city level. The change in energy productivity is decomposed using a distance function approach, and its spatial character is identified through exploratory spatial data analysis, based on data from 248 cities between 2010 and 2014. The study revealed that China’s overall energy productivity exhibited a downward trend caused primarily by the effects of technological and technical efficiency changes at the city level. Additionally, significant spatial autocorrelation existed in energy productivity, although most cities did not show significant spatial clustering. Based on the above results, we provide relevant suggestions for policymakers. [ABSTRACT FROM AUTHOR]

Eco-efficiency is of great significance in facilitating a region’s sustainable development. However, there are some inconsistencies among the concepts and also relationships of eco-efficiency and its relevant efficiencies in recent studies. This paper integrates eco-efficiency and three related-efficiencies (economic efficiency, energy efficiency, and environmental efficiencies) into a total-factor analysis framework, regarding them as composite eco-efficiency indicators. Employing a new data envelopment analysis approach, named Meta-US-SBM, which considers meta-frontier, undesirable outputs, super efficiency, and slacks simultaneously, the measure system of these four efficiencies is established. An empirical study is conducted using Chinese provincial data from 2001 to 2014. Results indicate that, overall, the regional economic efficiency is better than other related efficiency indicators. Furthermore, different provinces are adopting different development modes, as denoted by significant heterogeneity among eco-efficiency indicators. [ABSTRACT FROM AUTHOR]

• Assessing the Environmental Performance of china's Three Urban Agglomerations. • Using the dynamic DEA model based on the input–output perspective. • The total environmental efficiency exhibits a wave-like development trend. • PM2.5 is the best unexpected output after strict prevention from 2013 to 2017. • Industrial smoke and dust emissions need to strengthen management in the future. As a special form of a cluster city, urban agglomeration has become an important platform to support national economic growth and to participate in international competition and cooperation, but it faces severe environmental problems. This research thus selects panel data of 60 cities in the Beijing-Tianjin-Hebei urban agglomeration (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) from 2013 to 2017. Based on the input–output perspective, labor and energy consumption per GDP are selected as input indicators, GDP, PM2.5, SO 2 , industrial smoke and dust emissions, and wastewater discharged as output indicators, and fixed assets as a carry-over variable in the dynamic DEA model to evaluate and analyze the environmental efficiencies of these three urban agglomerations. Findings show that their total environmental efficiency exhibits a wave-like development trend, and that the total efficiency score of BTH is better than that of PRD and YRD. From the viewpoint of a sub-efficiency index, PM2.5 is the lowest in unexpected output, where its average five-year efficiency score is 0.9847, while the average score of industrial smoke and dust emissions efficiency is the lowest at 0.6199. Finally, this paper offers suggestions for different problems facing the three urban agglomerations. [ABSTRACT FROM AUTHOR]