Sustainability efficiency of climate change and global disasters based on greenhouse gas emissions from the parallel production sectors - A modified dynamic parallel three-stage network DEA model.

This study employed dynamic three-stage network data envelopment analysis (DEA), considering parallel production in the agricultural and industrial sectors, to assess the impact of greenhouse gas emissions on the climate change and natural disaster stages. The results revealed the following: (1) The dynamic overall efficiencies of more countries are decreasing than are increasing. The seven countries with the poorest overall efficiency ranking (Myanmar, Vietnam, Thailand, Bangladesh, the Philippines, Pakistan, and India) are mostly located in Southeast Asia. (2) The number of countries that maintained low efficiency over the long term is greater than those that retained high efficiency over the long term. Myanmar, Mexico, India, the Philippines, Thailand, and Vietnam maintained efficiency scores below 0.5, whereas South Korea, Japan, China, and New Zealand maintained efficiency scores above 0.8. (3) More than one-third of countries exhibited declines in efficiency over time, and half were European countries. Less than one-third of countries maintained their efficiency, and less than one-third of countries gradually improved. (4) Approximately half of the countries' efficiency scores were lower than the global average. The efficiency scores of the industrial sector exhibited a greater room for improvement on the input factors than did those of the agricultural sector. (5) Total factor energy efficiency analysis revealed that methane emissions and CO2 emissions have a similar level but large room for improvement across countries. Improving input factors in the production stage can ultimately mitigate inefficiencies in the climate change and natural disaster stages. There are still other important factors related to climate change, such as sea surface temperature, forest areas, or air pollution indicators, that could be considered in future research. The occurrence of global disasters could also be discussed in groups according to the region where the countries are located in the future.

Energy performance of European countries by considering the role of forest.

This paper applies the modified undesirable dynamic data envelopment analysis (DEA) model by considering the role of forest carbon sinks to evaluate European countries' carbon dioxide (CO2) emissions and productivity efficiency. Taking population and energy consumption as input variables, gross domestic product (GDP) as the desirable input, CO2 as the undesirable output, and fixed assets as an inter-temporal carry-out input variable, our results suggest considering the fixed amount of the forest carbon sinks significantly affects efficiency rankings. The overall efficiency rankings for Ireland, Austria, Italy, Germany, Spain, and Belgium look to be overrated, while those of Finland, France, and Netherlands are apparently underrated. In terms of Total-Factor Efficiency analysis, countries with the best performance in efficiency ranking are Denmark, Luxembourg, Norway, Sweden, and the UK, thanks to their long-term effort at addressing the impact of forest carbon sinks and the effect of CO2 emissions on efficiency.

New Energy Development and Pollution Emissions in China.

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.

Urban energy environment efficiency in China: Based on dynamic meta-frontier slack-based measures.

Rapid economic growth in China has resulted in a significant increase in particulate matter (PM2.5) and sulfur dioxide (SO2), the reduction of which has become a primary government focus. However, as the energy consumption and air pollutant emissions in Chinese cities have very significant regional characteristics, individual governance measures are necessary. This study used 2013 to 2016 energy consumption data from 31 Chinese cities to evaluate the dynamic efficiency of the urban environments. Labor, fixed assets, and energy consumption were taken as the inputs, gross domestic product (GDP) was taken as the output, and particulate matter (PM2.5) and sulfur dioxide (SO2) were taken as the carry-over variable indicators. Using a meta-frontier dynamic DEA model, the 31 cities were classified into high-income and upper-middle-income cities, the overall 2013-2016 energy consumption and air pollutant efficiency scores were analyzed, and improvements and changes were recommended to increase the efficiencies. Large differences were found in the energy consumption and air pollution emissions efficiency scores and the needed improvements, with the hig-income cities performing better overall than the upper-middle-income cities. While there have been some significant improvements in SO2 emissions, PM2.5 improvements have been far slower. Therefore, in most cities, more control measures are needed to control PM2.5 emissions. However, in addition to improving PM2.5 in the upper-middle-income cities, SO2treatments are also needed. Implications: There are big differences in the expectation of improvement of the two pollutants in all cities. In many Western cities, the expectation of PM2.5 improvement in the past years has not been reduced, but has been expanding. This shows that the central government has unified the air pollution control policies and the existing air pollution control measures formulated and implemented by the local governments.