Coal-based thermal power generation has long been the main source of power generation in the mainland of China. The efficiency of power generation is an important factor that determines the energy conservation and emission reduction as well as the sustainable development of the power industry in China. By comparing the regional differences of 30 provinces in the mainland from 2013 to 2017, this study uses the Super-DDF model and the TFEE to comprehensively evaluate the energy efficiency of thermal power generation. Empirical results: Overall efficiency: eastern efficiency (1.181) is the highest, followed by western (0.956), central (0.951) and northeastern (0.926). Total factor energy efficiency: eastern efficiency (0.923) is the highest, followed by western (0.754), central (0.742) and northeastern (0.710). The government and power industry managers should fully consider the regional differences in the field of thermal power generation when formulating policies so as to improve the power efficiency and promote the green development of power industry in China. Based on the analysis results, although the coal-fired power industry is more mature than other alternative energy industries, the expansion of thermal power generation cannot be considered if CO₂ emissions are to be reduced. Additionally, the market share and competitiveness of the local power industry can be increased based on the different conditions of the resource endowments of each region.

This research employs the modified undesirable slack-based measure dynamic exogenous data envelopment analysis model to evaluate the construction industry efficiency in 30 provinces of China from 2006 to 2017. It considers the differences in urbanization levels in three (east, central, west) regions and evaluates the profitability, resource allocation, energy consumption, and carbon emission efficiency of the construction industry. The results are as follows. First, the construction industry efficiency is the best in the east, followed by the central region, and lowest in the west. Second, the changing trends in this industry's efficiency are widespread across the nation's regions. The highest point of efficiency in the east region is at the beginning of the research period, but it then declines. The efficiency value of the central region reaches its peak around 2012 and then falls. The west region experiences increasing efficiency year-by-year until peaking in 2017. Third, depending on the degree of urbanization, its effects are also diverse. Therefore, the China government must examine the degree of urbanization to avoid environmental problems brought by urbanization that can bring about a drop in efficiency of the construction industry.

In this study, the Group of 20 (G20; excluding EU economies) were selected as the research objects, and the dynamic network slacks-based model (SBM) was used to evaluate the impact of carbon dioxide (CO₂) emissions and forested area on the efficiency and productivity of the industrial and agricultural sectors from 2011 to 2015. Empirical results showed that: (1) The efficiency of the industrial sector was superior to that of the agricultural sector among the G20 countries. Argentina, Australia, Indonesia, Saudi Arabia, South Africa, Turkey, the UK, and the US maintained the best industrial sector efficiency values, falling on the efficiency boundary, whereas Argentina, Brazil, Canada, France, Indonesia, South Korea, Russia, and the US had the best agricultural sector efficiency values. (2) Argentina, Indonesia, and the US had the best overall efficiency value of G20 countries. Saudi Arabia (0.0303), China (0.2721), and the UK (0.2809) had the lowest efficiency values. (3) Only France and Germany had higher than average total factor productivity, while Indonesia and Saudi Arabia had declining industrial and agricultural sector productivity. (4) The proportion of forested area (546.02%) was the most important variable to be improved due to the influence of desert topography, followed by the proportion of agricultural output values (60.86%) and the proportion of industrial output values (38.02%) in some countries.

According to the October 2021 Glasgow Climate Agreement reaffirming the cooling goals of the Paris Agreement and the Glasgow Leaders Declaration on Forests and Land Use, this research applies the Super-D-DDF model to non-oriented variable returns to scale to evaluate the Organization for Economic Cooperation and Development (OECD) and China (38 countries in total), collect important production and energy variables from 2016 to 2020, and measure the total efficiency of energy dynamics and its changes during COVID-19. The empirical results are as follows. (1) Comparing energy efficiency from 2016 to 2018 and 2019 to 2020 (during COVID-19), we find that most countries (22 countries) changed from high efficiency to low efficiency, showing a decrease in energy efficiency. (2) The emissions of carbon dioxide in China in 2020 are close to the sum of OECD carbon dioxide emissions, highlighting that the energy policy in China should be adjusted appropriately. (3) From 2016 to 2020, the forest area of various countries has a significant impact on overall energy efficiency performance. In line with the United Nations’ policy goals, countries should adjust forest protection policies to effectively reduce carbon emissions.