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China, the world's largest developing country, faces a severe water shortage. As the government has set a goal of limiting water use to 7000 × 108 m3 by 2035, how to control the increase in water use will be a thorny issue for China. Unbalanced and uncoordinated regional socio-economic development is an important feature of China. Research on the interaction between provincial water use will help to optimize the rational allocation of water resources and control of water use. In this paper, SNA (social network analysis) method is first used to explore the characteristics of social network relationship between inter-provincial water use, construct a two-stage model of SNA–LMDI, and decompose the driving factors of inter-provincial water use evolution. We found the following points. (1) From 2000 to 2018, the spatial correlation network structure of water use is tending to be stable, and the stability and risk resistance of the whole network are enhanced. (2) From different angles to quantify the centricity analysis, can be found that eastern provinces located right in the heart of water network, obviously larger impact on water resources utilization in other provinces, Shanghai and Beijing is located in the former two, and central and western provinces in the edge position. (3) The national water use spatial correlation network can be divided into four blocks, net beneficial block, bidirectional spillover block, brokers block, and net spillover block. (4) Technological progress and industrial structure adjustment were the primary and secondary factors inhibiting the increase of total water use, while income increase was the main factor promoting the increase of total water use, population scale expansion had a weak role in promoting the increase of total water use. Some policy implications are put forward related to our research conclusions. [ABSTRACT FROM AUTHOR]

In a low-carbon economic environment, China's thermal power industry has developed at a rapid speed. Faced with significant development bottlenecks, however, promoting energy conservation and technological innovation has become the current goals of the country's thermal power industry. Taking into account the heterogeneity of production technology, we utilize panel data of 23 listed thermal power companies in the Shanghai and Shenzhen stock markets from 2010 to 2015 as samples and divide them into large, medium, and small groups according to company size. Based on a meta-frontier function and the non-radial data envelopment analysis method, we evaluate the performance of energy-saving and emissions reduction in the thermal power industry when considering slack variables of energy input and undesirable output. The empirical study's results show that the mean energy-saving and emissions reduction performance in this power industry is generally low and exhibits significant differences under different frontiers. The performance of energy-saving and emissions reduction from high to low is small, large, and medium-size groups. The small-size group seems to obtain the industry-leading level production technology. Moreover, the technology gap and insufficient management are the primary sources of the total performance loss. [ABSTRACT FROM AUTHOR]

The growth in the world economy has resulted in an increase in environmental pollution and ecological destruction in many parts of the world. In particular, economic development in mainland China in recent years has seen a massive rise in environmental pollution such as particulate matter (PM2.5), sulfur dioxide (SO2), and nitrogen oxides (NO2) in many cities; as a result, there has been an increased focus on air pollution and carbon dioxide emission control in recent years. This study used 2013–2017 energy consumption data from 31 cities in China to examine overall and specific efficiencies, for which employees, fixed assets, and energy consumption were taken as the input indicators, and gross domestic product (GDP) and the PM2.5, SO2, and NO2 levels as the output indicators. It was found that from 2013 to 2017, only four cities (Beijing, Guangzhou, Nanning, and Shanghai) had total efficiency scores of 1, with all other cities needing efficiency improvements. The efficiency scores for the different pollutants varied widely, with the NO2 efficiencies being generally higher with less improvement needed, while the SO2 and PM2.5 efficiencies required significantly greater governance measures. [ABSTRACT FROM AUTHOR]

Over the past few decades, China's rapid economic, energy, and industrial developments have caused serious environmental damage. However, as there are large resource, energy use, economic, and environmental damage differences across Chinese regions, the Chinese government is seeking to reduce city pollution across the country. Most previous analyses have only looked at these issues on a single level; for example, the impact of environmental pollution on health, or energy and environmental efficiency analyses, but there have been few studies that have conducted overall analyses. Further, many of the methods that have been used in previous research have employed one-stage radial or non-radial analyses without considering regional differences. Therefore, this paper developed a meta undesirable two-stage EBM DEA model to analyze the energy, environment, health, and media communication efficiencies in 31 Chinese cities, from which it was found that the productivity efficiency in most cities was better than the health treatment efficiencies, the GDP and fixed asset efficiency improvements were small, the air quality index (AQI) and CO2 efficiencies varied widely between the cities, media report and governance inputs were generally inefficient, the birth rate efficiencies were better than the respiratory disease efficiencies, and the technical gap was best in Guangzhou, Shanghai, and Lhasa. Also, it found that high-income cities have a higher technology gap than upper middle–income cities, and media reports efficiency have a high correlation with respiratory diseases and CO2. [ABSTRACT FROM AUTHOR]