Energy Environmental Efficiency Research Articles

Dynamic and network slack-based measure analysis of China’s regional energy and air pollution reduction efficiencies

Abstract China’s rapid development over the past few decades has resulted in significant environmental pollution from CO2, SO2 and NO2 emissions amongst others, all of which can adversely affect human health. However, past efficiency analyses have tended to discuss energy efficiency and environmental efficiency separately, or have discussed ways in which governments can reduce pollution at the source. In other words, previous analyses of China’s energy efficiency have only been focused on one-stage, and very few studies have integrated the environment, government pollution reductions, and economic development in the analysis. Therefore, to fill this research gap, this study examined the first and second-stage energy and air pollution reduction efficiencies in thirty Chinese provinces and municipalities from 2013 to 2016 using a dynamic, network slack-based measure (DNSBM) model, in which labor, fixed assets and energy consumption were the input variables in the first production stage, GDP was the output variable, and CO2, SO2, and NO2 emissions were the link variables, and in the second treatment stage, pollution treatment investment was the input variable, the CO2, SO2, and NO2 emissions reductions were the output variables, and energy consumption/GDP was the carryover variable. It was found that; (1) Beijing, Shanghai, Guizhou, Hainan and Qinghai had the best performances over the 4 years, and Shaanxi, Shandong, Fujian, Jilin, Liaoning and Xinjiang had the worst performances and therefore had the greatest need for improvements; (2) the overall provincial efficiencies were generally relatively low and significant improvements were needed however, there were large differences between the provinces/municipalities; (3) the overall air pollution reduction efficiency governance in the second stage was low, indicating that more effective measures were needed to improve environmental efficiency and that the dynamic developments in government regulations and governance had resulted in a policy implementation lag; and (4) in 21 provinces, the first-stage productivity was significantly higher than the second-stage treatment productivity, indicating that the treatment stage needed to be strengthened.

Building heritage of “Sapienza”: integrated digital tools for the executive project

The originality of the contribution has put in system, for an executive project, digital instruments (different from each other). The methodology has developed aspects of method, tools, skills and results: coordinating tools (Mc4energy©, Tally©), preparing the BIM Execution Plan, identifying the BIM modeler and coordinator, managing the information with Overview and Detailed BIM Use Map. The results of the research, financed in the A.A. 2017-18 by “Sapienza” in synergy with the Energy Plan, benefit the entire community: by implementing digital instruments, more effective methods and databases are produced for the project and the management over time of interventions for energy-environmental efficiency and indoor well-being. The paradigm shift takes place with industry 4.0.

Analysis of Coordinated Development of Energy and Environment in China’s Manufacturing Industry under Environmental Regulation: A Comparative Study of Sub-Industries

In order to explore the impact of environmental regulation on the coordinated development of energy and the environment with the background of governance transition, we propose a three-stage integrated approach and use the panel data of China’s manufacturing industry 27 sub-sectors during the period of 2006–2015. In the first stage, according to the environmental pollution intensity, the manufacturing industry is divided into heavily polluting industry, moderately polluting industry, and lightly polluting industry. The second stage is employed the slacks-based measure (SBM)-undesirable method to study the sub-industries’ green energy-environmental efficiency under different environmental pollution intensities. Besides, the dynamic changes of technical innovation and efficiency among different industries are analyzed through the Malmquist productivity index. For the purpose of investigating the transmission mechanism of the Porter’s hypothesis and exploring the compound effects of environmental regulation and governance transition on green development, in the third stage, we use the panel data analysis to conduct more in-depth research on the relationship between environmental regulation, governance transition, and technical innovation. Results show that the highest average green energy-environmental efficiency is lightly polluting industry, which is 0.52, followed by the heavily polluting industry at 0.40, and the lowest is the moderately polluting industry, which is 0.32. By decomposing total factor productivity, heavily polluting industry is at the forefront of technical innovation. Panel data analysis results indicate that investment in research and development and governance transition could promote the growth of total factor productivity for manufacturing.

Coupling analysis of urbanization and energy-environment efficiency: Evidence from Guangdong province

Rapid urbanization has been accompanied by a series of environmental and energy-related issues. It is essential to better understanding the coupling relation between energy-environment efficiency and urbanization in achieving the goal of sustainable urbanization. In this paper, an index system was firstly established for the measurement of urbanization quality scores based on the four aspects of population, economy, society, and space. We then undertook a slack-based measure data envelopment analysis in order to measure energy-environment efficiency. This allowed us to establish a coupling coordination degree model to investigate the coupling relationship between energy-environment efficiency and urbanization. Our findings include the following: (1) Spatiotemporal diversity was apparent in the estimated urbanization quality scores within the province, with high-values areas mainly being concentrated in the Pearl River Delta; (2) A growth trend was identified in energy-environment efficiency values in western Guangdong and the Pearl River Delta, while in eastern Guangdong energy-environment efficiency followed a downward trend, and it stayed stable at a low level in northern Guangdong. Energy-environment efficiency also displayed significant spatial differentiation; (3) The coupling relationship between the energy-environment efficiency and urbanization of Guangdong throughout the research period went from a low coupling stage to a medium coupling stage. Most cities in Guangdong remained in the moderate and low coupling stages, with the exception of Guangzhou and Shenzhen, which took the lead in entering the highly coupling stage. The findings of this paper are of great implications for government in achieving the coordinated development of energy-environment efficiency and urbanization.

Study into predicted efficiency of the application of hybrid solar collectors to supply energy to multi-apartment buildings

This paper reports a study into efficiency of the application of hybrid solar collectors, which can simultaneously generate both electricity and thermal energy to supply power to multi-storey buildings. The novelty of the work is that efficiency was predicted taking into consideration the dynamics over recent years and by extrapolating trends in prices up to the year2045 inthe market of renewable energy, in contrast to existing approaches that disregard their likely change over the considered period. The results of calculations were used to model a predicted market value of the equipment, taking into consideration a reduction in its price due to the improved technology for manufacturing the collectors, their installation, and operating costs, over a specified period. In this case, the dynamics in the «basic» and «green» tariffs for solar electric and thermal energy were considered. Values for the coefficients of determination have confirmed sufficient adequacy of the derived models. An example has been provided for determining the electric and thermal loading on a multi-apartment building equipped with gas stoves; the proper equipment for a hybrid solar collector has been selected. The structures and procedures have been proposed for connecting a hybrid collector to the systems the supply electricity and heat to the building. The collector’s modules the type of ATMOSFERA F2PV are arranged at the roof of the building, whose electric components are connected, through an inverter, to the inlet-distributor device in a building or to the low-voltage buses at a power substation with a voltage of 10/0.4 kV, which powers the building. A heat-carrier is fed from the collector, through storage capacities, to a thermal unit into the system of hot water supply and heating of the building. The obtained results of the study have made it possible to predict a probable energy efficiency (the amount of saved conventional fuel), economic (net discounted profit) and environmental efficiency (reduction in emissions that contribute to the global climate warming). The payback period has been determined by consistent calculation of net income for each year over the entire period of realization of investments provided the specified trend in market prices does not change. The paper presents the results from calculating the magnitude of investments and income for inhabitants per each apartment in the building from the implementation of the investment project.

Evaluation of Energy-Environment Efficiency of European Transport Sectors: Non-Radial DEA and TOPSIS Approach

Transport is recognized as a major energy consumer and environment pollutant. Recently scholars have paid considerable attention to the evaluation of transport energy and environmental efficiency (EEE). In this paper, the non-radial Data Envelopment Analysis (DEA) model was employed to evaluate EEE on a macro level—i.e., of European road, rail and air sectors. The evaluation was conducted under the joint production framework, which considers energy and non-energy inputs, and desirable and undesirable outputs for the last ten years period. To rank decision-making units and check the aptness of this non-radial DEA model in transport EEE evaluation, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method has been proposed. An empirical study has been conducted for as many European countries as possible, depending on availability of data. Based on the non-radial DEA model, it could be said that the level of EEE is improving for the road sector, while many evaluated countries have low EEE for the rail transport sector. Additionally, results have indicated that the TOPSIS method is more suitable than the non-radial DEA model in transport EEE evaluation and for identification of best practices.

Regional convergence of energy-environmental efficiency: from the perspective of environmental constraints.

This paper conducts a convergence analysis on the energy-environmental efficiency to explore the differences between regions that reflect the implementation effect of the policies on energy-saving and emission reduction. Particularly, for the Yangtze River urban agglomeration, additive model (AM model) is applied to calculate the energy-environmental efficiency, and the convergence model is employed to analyze the heterogeneity and spatial evolution of energy-environmental efficiency. From the results, the energy-environmental efficiency for Suzhou is at a good level; the figures for Wuxi, Yangzhou, and Nantong maintain at medium level; for Zhenjiang, qualified level; and for Nanjing, Changzhou, and Taizhou, poor level. The energy-environmental efficiency of the whole Yangtze River urban agglomeration displays a downward trend of fluctuations. While Nantong reveals a divergent energy-environmental efficiency, Zhenjiang, Changzhou, Wuxi, Yangzhou, and Nanjing Cities generally show a trend of convergence. It was also recognized that the energy-environmental efficiency is gradually decreasing from Southeast to North to Southwest regions. In the past decade, the north region of Yangtze River yielded a divergent development trend, while the southeast and southwest regions appear to have a convergent development trend. In the future, the urban agglomeration needs to promote the coordinated development of the economy and the energy environment, impel the optimization and upgrading of the industrial structure, narrow the regional gap, and adjust the energy consumption habits.

The evaluation of energy–environmental efficiency of China’s industrial sector: based on Super-SBM model

With the process of urbanization and industrialization, a growing attention has been paid to the energy–environmental efficiency in China’s industrial sector. Such researches mainly focused on calculating the efficiency and exploring its driving factors at sectoral, provincial and regional perspectives. In this paper, we proposed to evaluate the energy–environmental efficiency of China’ industrial sector and its driving factors at a dynamic change perspective. Combining super-slack-based measure (Super-SBM) model and Malmquist index, this paper calculated the energy–environmental efficiency of China’s 30 provinces (municipalities and autonomous regions) from 2012 to 2016 and captured its dynamic change. Then we aggregated China’s 30 provinces into three groups based on their relevant dynamic change values, namely high-growth, mid-growth and low-growth groups. Finally, we verified the impact of investment in pollution control on industrial energy–environmental efficiency in different groups. The results showed that: Beijing, Inner Mongolia, Guangdong, Hunan, Tianjin and Shaanxi performed efficiently during the whole study period. Most provinces have improved their energy–environmental efficiency from 2012 to 2016. The decomposition results indicated that the technology change was responsible for the growth of energy–environmental efficiency. Economic development level positively and significantly influenced the energy–environmental efficiency of the industrial sector as a whole and three groups, while pollution control investment had a significantly negative effect on energy–environmental efficiency of high-growth and low-growth groups. This study concluded that all the provinces should pay attention to technology progress and sustainable pollution control investment for improving the energy–environmental efficiency in the long term. Additionally, differentiated strategies to improve energy–environmental efficiency for different provinces and groups should be implemented.

Evaluating the energy-environment efficiency and its determinants in Guangdong using a slack-based measure with environmental undesirable outputs and panel data model

Environmental sustainability has become a significant goal for policymakers and practitioners since increasing environmental degradation owing to anthropogenic activities. Energy-environment efficiency, linked to a progressive reduction in the environmental impacts that may occur throughout their life cycle to levels that should be below or equal the Earth's estimated carrying capacity, is a crucial point for constructing an environment friendly society while maintaining rapid economic growth. Thus, this study combined a slack-based measure (SBM) with environmental impacts as undesirable outputs with spatial analysis techniques to measure energy-environment efficiency of 21 cities in Guangdong and its changing patterns during the period 2006–2016. What and how socioeconomic factors affecting energy-environment efficiency over time and space was further examined using heterogeneous panel data model. Here are the main findings: during the study period, energy-environment efficiency showed apparent spatiotemporal diversity with high values predominantly concentrated in coastal areas, especially in the center area of the Pearl River Delta. Energy-environment efficiency increased continuously in the western Guangdong and the Pearl River Delta, while it of eastern Guangdong showed a decreasing trend and of northern Guangdong remained stable at a low level. The results of the heterogeneous panel data model revealed that technological progress exerted the greatest positive effects on energy-environment efficiency, followed by population density, economic growth. Conversely, Openness was evaluated as an inhibiting factor. Interestingly, this study found that industrial structure demonstrated significant negative correlations with respect to energy-environment efficiency in the Pearl River Delta while it exerted significant positive influence in the peripheral areas of Guangdong. And foreign trade and energy-environment efficiency had a significant positive correlation in the Pearl River Delta, unlike the negative correlation in the peripheral areas of Guangdong. This study's findings hold a helpful reference for both policymakers and practitioners to coordinate the economy, energy and environment and established environment-friendly society in the fast-developed areas like Guangdong.

Multiscale analysis of the environmental impacts of the concrete masonry: from masonry unit to building

Life Cycle Analysis of buildings can be led at various scales: from construction products one by drawing the Environmental Product Declarations according to EN 15804+A1 to building’s one by assessing the environmental performance of the buildings according to EN 15978. The new French Labelling scheme “Energie Positive & Reduction Carbone” has adopted a multi-criteria and multi-stage approach to declare the energy consumptions and environmental efficiency of new buildings. A special focus has been put on Greenhouse gas emissions by defining a set of global threshold and subthreshold values covering the whole life cycle of the building and only the contribution Product and Construction Process stage including equipment. Results of different French cases studies for collective housing buildings and single houses shows a variation of less than 10% of the global emissions of greenhouse gas for buildings of different mode of construction (concrete structure, concrete masonry, clay masonry, wood structure …) having a similar energy efficiency of their thermal envelope. The contribution of concrete masonry units typically ranges from 2.5 to 10% of the total amount of the CO2 emission for the Product and Construction Process stages and consequently less than 5% of the emission for the total life cycle, respectively 4–15% and less than 8% for collective housing buildings. No significative differences of the environmental impact calculated as greenhouse gas emissions at the building’s scale can be observed although the environmental impacts of the different type of concrete masonry units (dense and lightweight aggregates, composite blocks including mineral foam) vary significantly.

Environmental Assessment of European Union Countries

This study utilizes the dynamic data envelopment analysis (DEA) model by considering time to measure the energy environmental efficiency of 28 countries in the European Union (EU) during the period 2006–2013. There are three kinds of variables: input, output, and carry-over. The inputs are labor, capital, and energy consumption (EC). The undesirable outputs are greenhouse gas emissions (GHE) and sulfur oxide (SOx) emissions, and the desirable output variable is gross domestic product (GDP). The carry-over variable is gross capital formation (GCF). The empirical results show that first the dynamic DEA model can measure environment efficiency and provide optimum improvement for inefficient countries, as more than half of the EU countries should improve their environmental efficiency. Second, the average overall scores of the EU countries point out that the better period of performance is from 2009 to 2012. Third, the output variables of GHE, SOx, and GDP exhibit a significant impact on environmental efficiency. Finally, the average value of others is significantly better than high renewable energy utilization (HRE) with the Wilcoxon test. Thus, the EU’s strategy for environmental energy improvement should be to pay attention to the benefits of renewable energy (RE) utilization, reducing greenhouse gas emissions (GHE), and enhancing the development of RE utilization to help achieve the goal of lower GHE.

Environmental protection via optimal global economic restructuring

This research proposes an approach to managing the environmental efficiency of the global economy via the optimal economic restructuring. The objective is to promote an increase in energy-environmental efficiency that supports economic growth constrained by greenhouse gas mitigation and energy conservation. The proposed method suggests the way of structural change in a global economy that the national economies should follow by economic restructuring, international cooperation, and trade. By following the recommended course of action, it becomes possible to increase the energy – environmental efficiency of the global economy as a whole via harmonized modifications in output per capita, use of renewable energy, and decrease in energy- and greenhouse gas emissions intensities. A novel stochastic data envelopment analysis with a perfect object method (SDEA PO) is utilized as a mathematical tool. A system of differential-algebraic equations is derived, leading to the determination of the trajectory of locally optimal structural change.•This study introduces a novel method aimed to guide the optimal economic restructuring of the global economy via economic growth constrained by energy conservation and greenhouse gas mitigation.•The suggested model provides guidance for energy-environmentally friendly economic restructuring of the global economy.

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

ABSTRACTRapid 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.

Fairness of China’s provincial energy environment efficiency evaluation: empirical analysis using a three-stage data envelopment analysis model

China has become the world’s largest carbon emitter since 2007; thus, reducing future emission has become an arduous task. Calculating energy efficiency fairly is paramount for formulating energy policies, given the different development levels of provinces. This study employed a three-stage data envelopment analysis model that considered environmental constraints to evaluate the energy efficiency of China’s 30 provinces in 2015 and redefined traditional energy efficiency as energy environment efficiency which calculated under environmental constraints. Different factors, such as urban development level and industrial structure in relation to energy environment efficiency, were analyzed. Three main results were obtained. First, the average energy environment efficiency in 2015 was only 0.73, which showed that China has roughly 30% capacity for improvement in the future. Second, stochastic frontier analysis demonstrated that the industrial structure, energy consumption structure, and central heating systems exerted negative impacts, and the level of city design and the degree of openness exerted positive effects on energy environment efficiency. Third, capital, manpower, and the extent of industrial concentration in central and western regions should be increased to improve China’s energy environment efficiency.

Energy-environmental efficiency and optimal restructuring of the global economy

The primary objective of this study is to investigate the opportunities for economic restructuring, resulting in an optimal increase in the energy-environmental efficiency of the global economy. A novel stochastic data envelopment analysis with a perfect object method (SDEA PO) constitutes the methodology of the research. We equip SDEA PO with the projected gradient of the efficiency score. We employ the indicators of the gross domestic product (GDP) and carbon dioxide emissions (CO2) as output and undesirable output, respectively, and population and clean energy consumption as input and undesirable input, respectively. By using the SDEA PO, we obtain a group efficiency score for the global economy; the projected gradient identifies the direction of optimal economic restructuring. The indicator-wise components of the projected gradient determine locally optimal changes in the shares of each economy, serving particular goals. We use a factor analysis technique to aggregate them into one factor vector that determines the multicriteria optimal structural change. The factor vector determines the redistribution of the GDP, clean energy consumption, CO2 emissions, and population, leading to the maximum possible increase in the energy-environmental efficiency. The suggested approach may be used as a tool for decision-making in a variety of two-tier economic systems.

Sectoral energy-environmental efficiency and its influencing factors in China: Based on S-U-SBM model and panel regression model

Abstract Energy use is often accompanied with air emissions including SOx, NOx, CO2, etc. It is essential to consider both the energy and environmental performance of various sectors to ensure better policymaking. This study considered air pollution by calculating energy-environmental efficiency (EEE) at the sectoral level. A few studies have previously applied the slack-based measure (SBM) model to multi-sector EEE assessments. Despite the advantages of SBM model, potential improvements have rarely been proposed. Therefore, a super-efficiency SBM model with undesirable outputs (S-U-SBM) was used to evaluate the EEE of 31 sectors in China. The policy implications of improving EEE, in microcosmic (potential improvement) and macroscopic (influencing factors) terms, were considered. The results indicated that for all sectors there was an overall trend of increasing EEE from 1995 to 2009, except for Rent and Other Business Activities, and Health and Social Work. The average annual potential for energy-saving and emission-reducing measures in all sectors was 1.396 × 1017 J and 7.0780 × 107 tons, respectively. Chemicals and Chemical Materials had the highest potential to save energy and reduce emissions. A panel regression indicated that the relationship between EEE and gross output was U-shaped for all industry, but had an inverted-U shape for heavy industry. Sectoral size, technology, and the proportion of energy demand satisfied by coal significantly influenced EEE.

Innovative energy and environmental standards for architecture

The article, in order to identify new models according to which to conceive the future transformation and construction of the environment, starts from the description of current energy and environmental models, beginning with those defined by Reyner Banham on End of the 1960s (conservative, selective, regenerative, bioclimatic model) to identify the characteristics of a new energy model consistent with the current energy-environmental efficiency instances of buildings.

The energy-environment efficiency of road and railway sectors in China: Evidence from the provincial level

The transportation sector, particularly the road and the railway sectors, is an important source of CO2 emissions in China. This study combines the non-radial data envelopment analysis (DEA) model with window analysis to measure the energy-environment efficiency of the road and railway sectors of 30 provinces in China, then uses the Tobit regression model to analyze the factors affecting the energy-environment efficiency. The findings suggest that, first of all, although these two sectors are both with high energy-environment efficiency, there is a higher probability for railway sector to improve its energy-environment efficiency than that of road sector, with the average energy-environment efficiency 0.9307 and 0.9815, respectively. Second, the road sector in eastern China with the highest average energy-environment efficiency, lower in the western region, and lowest in the central region. As for the railway sector, the western region has the highest average energy-environment efficiency, followed by the central and the eastern regions. Third, the relationship between energy-environment efficiency and income level in the road and railway sectors follow the U-shaped and inverted U-shaped curves, respectively.

Quantitative characterization and comprehensive evaluation of regional water resources using the Three Red Lines method

Based on the synergetic development of new industrialization, rapid urbanization and agricultural modernization (IUAM), and from the viewpoint of interactive relationships between water resources and regional population, eco-environment, economy and society, the concepts of water resources intensity (WRI), water environment intensity (WEI), water resources relative efficiency (WRRE) and water environment relative efficiency (WERE) are defined with reference to energy intensity, resources efficiency and environment efficiency theory. On the basis of benchmarking theory, the quantitative characterization and evaluation method of “Three Red Lines” (the upper limit of water resources allocation, the baseline of utilization efficiency of water resources and the upper limit of sewage discharge) is proposed. According to these concepts and models, an empirical analysis of the Three Red Lines of water resources on the Chinese mainland between 2003 and 2012 was carried out. The results showed that total water consumption in eastern, central and western parts of China possesses “club convergence” characteristics, which means these areas have similar internal conditions appeared convergence in the development. Inter-provincial differences in water consumption continue to decrease, but the north–south differentiation characteristics in the eastern and central regions were still relatively obvious, while provincial differences in the eastern part were at a minimum and the central region had the largest. Water Resources Efficiency (WRE) of all four sectors in the Southwest rivers and Huaihe River basins were generally high. Industrial WRRE in the Songhua River, Yangtze River and Pearl River basins, agricultural WRRE in the Songhua River, Yellow River and northwestern river basins and domestic WRRE in the Liaohe River, Yangtze River and Pearl River basins were all low. Eco-environmental WRRE in the southeastern rivers and Yangtze River basins were low but showed an upward trend. Other river basins, except for the Northwestern rivers basin, had high eco-environmental WRRE with a downward trend. Western China, especially the northwestern part, had a low relative intensity of the water environment (WERI) and high integrated water environment management (IWEM) performance, but the relative intensities of the water resources (WRRI) were fairly high, and the comprehensive performance of integrated water resources management (IWRM) in these regions was low. In southern China, especially the southeastern part, the IWEM was fairly high, but the overall IWRM was lower.

International comparisons of energy and environmental efficiency in the road transport sector

The present work provides an international comparison of the energy intensity and the carbon dioxide intensity in road transport for a group of 90 countries over the period 1980–2012. This paper attempts to perform a comparative analysis to find the most appropriate mapping of the energy performance in road transport taking into account the three dimensions of sustainable energy development, namely road transport-related energy consumption, economic growth and carbon dioxide emissions. An important result of the study is the inverse relationship between energy efficiency and environmental efficiency. Through the calculated Theil coefficient, our empirical findings highlight the existence of spatial and temporal disparities between countries. In 2012, Tunisia occupies the 48th and the 38th rank respectively in terms of energy and environmental efficiency. Based on a general index of energy performance in the road transport sector, it is deemed to have a medium–high energy performance by occupying the 34th rank. The study shows the importance of enhancing a number of policies for the road transport system through the joint improvement of the fuel price policy, of the road infrastructure policy and of the fuel-efficient road vehicles policy, in order to maintain sustainable energy road transport.