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.

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 (CO) emissions and productivity efficiency. Taking population and energy consumption as input variables, gross domestic product (GDP) as the desirable input, CO 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.

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.

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 (PM) and sulfur dioxide (SO), 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.