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• Decoupling of GDP from all energy sources under multiple principles are examined. • World economy achieved weak energy decoupling in most years during 2000–2011. • World economy coupled with coal use and tended to couple with cleaner energy use. • None of studied economies achieved long-term GDP-embodied energy decoupling. • Decoupling delusions occurred when only considering direct and total energy use. Decoupling indicators are widely used to understand links between economic growth and energy use. However, traditional decoupling analyses mostly focus on domestic energy consumption (i.e., the production-based principle) and neglect off-site energy use across global supply chains to satisfy an economy's final consumption (i.e., the consumption-based principle). Moreover, analyses for total primary energy conceal an economy's preference for different energy sources. Therefore, this paper evaluates decoupling states of GDP from all types of primary energy use under consumption-based principle, for world economy and eight typical economies during 2000–2011. Regarding total primary energy, world economy witnessed weak decoupling in most years, and most economies studied (e.g., USA, Japan and China) achieved decoupling initially but performed negative decoupling finally. For EU, USA, Japan, Russia and India, production-based decoupling performances were generally better than consumption-based ones. Decoupling phenomena detected under production-based principle even became coupling or negative decoupling under consumption-based principle in some cases. As for each energy source, world economy decoupled from oil use, but still coupled with coal use, and gradually showed a trend to couple with natural gas and renewables use. Different energy sources showed distinct decoupling degrees from GDP, affected by individual embodied energy requirement structure. This paper uncovers potential energy decoupling delusions to deepen the understanding of relationships between energy use and economic growth. [ABSTRACT FROM AUTHOR]

Energy plays a vital part in stimulating economic progress, and the shift towards a cleaner energy system is highly significant for ensuring the sustainable development of the economy. China's energy structure urgently needs to be transitioned. The fast advancement and implementation of artificial intelligence (AI) has provided a new and important tool for promoting the transition of energy structure. So, what is the relationship between the application of artificial intelligence and the transition of the energy structure? This research introduces artificial intelligence into the energy sector, focusing on the relationship between artificial intelligence and energy transition. Since nonlinear models are better able to study the complex effects and phase differences of artificial intelligence. Using China's provincial panel data spanning from 2006 to 2019, this study employs nonlinear modeling to explore the stage differences in the process of AI in facilitating energy structure transformation. This paper derives the following findings based on empirical research. First, there is a U-shaped relationship between artificial intelligence and the transition of energy structure. Specifically, before the inflection point, the initial application of artificial intelligence, artificial intelligence may adversely impact energy transition. When the inflection point is passed, AI will help facilitate the energy transition. Second, the U-shaped relationship between AI and energy transition is more pronounced in coastal and non-resource-based regions. Third, energy intensity, government investment in science and technology, and informatization will moderate the U-shaped relationship between artificial intelligence and energy transition, changing the steepness of the original U-shaped relationship and even reversing it. Hence, it is imperative to effectively utilize the technological benefits of artificial intelligence through the development patterns and distinctive features of different regions, thereby facilitating the smooth transition of the energy structure. [Display omitted] • The role of artificial intelligence in the energy transition process is studied. • Stage differences in the role of AI are analyzed. • The nonlinear relationship between AI and energy transition is investigated. • Provide insights into the factors affecting the relationship between AI and energy transition. • This research helps the government to advance the energy structure transition. [ABSTRACT FROM AUTHOR]

Highlights • A nonlinear relationship between industrial agglomeration and energy efficiency. • A threshold effect exists when industrial agglomeration affects energy efficiency. • When agglomeration degree is less 1.3865, it will promote energy efficiency. • Future policy for energy efficiency in China's textile industry is suggested. Abstract Based on provincial panel data on the textile industry in China, this paper calculates the total-factor energy efficiency of this industry as the dependent variable. Additionally, based on linear panel analysis of the relationship between industrial agglomeration and energy efficiency, in-depth analysis of the industry is performed at different industrial agglomeration levels. The paper identifies different impacts of industrial agglomeration on energy efficiency, uses the threshold regression model to extend the research to a nonlinear framework, and constructs a double threshold regression model in which the threshold of the textile industry agglomeration level serves as the threshold variable. The results show, first, a threshold effect occurs when industrial agglomeration affects total-factor energy efficiency. Second, a significant positive correlation exists among the degree of economic development, energy prices, research and development investment (R&D), enterprise scale, and total factor energy efficiency of the textile industry. Third, a non-linear relationship exists between industrial agglomeration and energy efficiency in the industry. When industrial agglomeration is low, promoting it improves energy efficiency. However, when industrial agglomeration reaches a certain level, agglomeration and energy efficiency show a negative relationship. Finally, based on the empirical results, ways of improving energy efficiency in the industry are suggested. [ABSTRACT FROM AUTHOR]

This paper investigates the long run dynamics of economic growth and biomass consumption nexus by applying dynamic panel analyses for 51 Sub-Sahara African countries for 1980–2009 period. The results show that economic growth is affected by biomass consumption, openness and population significantly and positively in African countries. GDP elasticity with respect to biomass consumption is close to unity and the elasticities of GDP in terms of openness are found statistically significant (between 0.259 and 0.348). According to homogeneous variance structure, one percent increase in variables of biomass, openness and population will lead GDP to increase by 1.818%, 0.269% and 0.676%, respectively. However, according to estimations from heterogeneous variance structure indicate that one percent increase in biomass, openness and population variables will cause GDP to increase by 0.820%, 0.259% and 0.811%, respectively. In conclusion, this paper finds significant effect of biomass consumption on GDP in 51 Africa countries. [ABSTRACT FROM AUTHOR]

Electrical power generation is changing dramatically across the world because of the need to reduce greenhouse gas emissions and to introduce mixed energy sources. The power network faces great challenges in transmission and distribution to meet demand with unpredictable daily and seasonal variations. Electrical Energy Storage (EES) is recognized as underpinning technologies to have great potential in meeting these challenges, whereby energy is stored in a certain state, according to the technology used, and is converted to electrical energy when needed. However, the wide variety of options and complex characteristic matrices make it difficult to appraise a specific EES technology for a particular application. This paper intends to mitigate this problem by providing a comprehensive and clear picture of the state-of-the-art technologies available, and where they would be suited for integration into a power generation and distribution system. The paper starts with an overview of the operation principles, technical and economic performance features and the current research and development of important EES technologies, sorted into six main categories based on the types of energy stored. Following this, a comprehensive comparison and an application potential analysis of the reviewed technologies are presented. [ABSTRACT FROM AUTHOR]

• Energy security in the EU countries was assessed from two different perspectives. • A new integrated approach based on MCDM methods was used for the assessment. • The level of energy security of EU countries varies and depends on the assessment perspective. • RES-based countries have a high level of energy security. • EU policies need to target decarbonization and increase energy independence. The subject of this article concerns a crucial issue of energy security in the European Union countries, especially during the war in Ukraine. The paper presents the results of a study aimed at assessing the level of energy security of EU-27 countries from two perspectives (for two variants of analysis). The first variant assesses the level of energy security of EU-27 countries, which is derived from a traditional approach related to the availability of energy sources at affordable prices (energy and economic factors). The second variant assesses the level of energy security from the perspective of sustainable development, the so-called sustainable energy security, which, in addition to energy and economic factors, also takes into account environmental and social factors. The multi-criteria nature of the subject matter undertaken determined the adoption of methodology based on Multiple-criteria decision-making methods (MCDM) for the study. Also, the author's integrated approach based on indicator weighting methods and MCDM methods was used. The CRiteria Importance Through Intercriteria Correlation (CRITIC) and standard deviation (SD) methods were utilized to determine indicator weights, and the Grey relational analysis (GRA) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods were used for the core part of the research. Based on the proposed research methodology and the results, rankings of the studied countries were created for the two analyzed variants and the levels of energy security were specified. The research was carried out for an 11-year period between 2010 and 2020. The results showed that the level of energy security for some EU countries depends on the assessment variant. Regardless of the assessment variant, the high level of energy security was found in the Scandinavian countries. It is reasonable to use the presented results when developing a new EU energy and climate strategy, which seems absolutely necessary in the new geopolitical situation that has now emerged in the region. The article should also be regarded as a voice in the discussion on the choice of direction and pace of economic transformation in the context of building a sustainable knowledge-based economy and climate neutrality in Europe. [ABSTRACT FROM AUTHOR]

• The impact of economic growth pressure on energy efficiency improvement is discussed. • Economic growth pressure has hindered the improvement of energy efficiency. • Heterogeneity effects exist in individual dimension and temporal dimension. Economic growth target management has been a typical feature of Chinese governments at all levels for a long time in the past decades. Based on a panel data of 188 Chinese cities, this paper examines the impact of pressure brought by economic growth target on energy efficiency improvement. The results suggest that economic growth pressure has hindered the improvement of energy efficiency. For every unit of increase in economic growth pressure, the improvement indicator of energy efficiency will decrease by 3.3%. This finding is robust, after replacing explained variables and core explanatory variables, no substantial changes are found. Sub-sample regression confirms the existence of heterogeneity effects in individual dimension and temporal dimension. Finally, by summarizing existing studies, this paper finds that the investment imbalance effect, the hindrance effect on industrial structure upgrading, and the crowding-out effect on innovation are three important ways for economic growth pressure to restrain the improvement of energy efficiency. Our findings are helpful to understand the role of the government's economic growth target management in resource allocation and energy utilization and provide a certain practical reference for China to promote high-quality economic development. [ABSTRACT FROM AUTHOR]

Highlights • Methods to assess an energy rebound effect are reviewed. • Our new approach to assess rebound effect considers the factors of production. • Energy rebound effect in Korea is investigated. • The estimation result of our model is more plausible than one of previous model. Abstract Our paper presents a new approach to estimating the macroeconomic growth energy rebound effect. Utilizing data envelopment analysis, our suggested methodology, unlike the standard macroeconomic growth rebound effect estimation, considers other factors of production. Through an output-oriented data envelopment analysis, optimal economic growth is derived considering all factors of production. The difference between the optimal economic growth and actual economic growth represents information on energy overspending. This overspent energy directly equates to the macroeconomic growth energy rebound effect. For the empirical case study, time-series data of economic growth and factors of production, demonstrated by energy supply, capital stocks, and labor force, are collected for the period of 1971 to 2012 in Korea. While the energy rebound effect results using the standard approach to estimating macroeconomic growth energy rebound effect are in the vicinity of 100%, our empirical results show that there is a 1% rebound effect in most of the years. Our method is plausible since our results show that the energy rebound effect is high when the economy is in recession or energy prices are shocked. That is, energy, one of the factors of production, is wasted from an economic viewpoint, which is consistent with the definition of energy rebound effect. [ABSTRACT FROM AUTHOR]

Highlights • The impact of oil price uncertainty on economic growth in OECD countries is studied. • Taking a historic perspective, the sample covers a 144-year period starting in 1870. • The negative impact of uncertainty is more severe for oil producing countries. • A smaller impact is recorded in the post-World War II subsample period. • Reasons for declining impact of oil price uncertainty are proposed. Abstract This paper uses a number of different panel data estimators, including fixed effects, bias-corrected least squares dummy variables (LSDVC), generalised methods of moments (GMM), feasible generalised least squares (FGLS), and random coefficients (RC) to analyse the impact of real oil price volatility on the growth in real GDP for 17 member countries of the Organisation for Economic Co-operation and Development (OECD), over a 144-year time period from 1870 to 2013. The main finding of the study is that oil price volatility has a negative and statistically significant impact on economic growth of the OECD countries in the sample. In addition, when allowing for slope heterogeneity, oil-producing countries are significantly negatively impacted by oil price uncertainty, most notably Norway and Canada. [ABSTRACT FROM AUTHOR]

Highlights • India's emissions and intensity are driven by private consumption, followed by investment and exports. • India's emission increase comes from final demand and production structure changes. • India's increase of household indirect emissions mainly comes from per capita income increase. • India's aggregate embodied intensity by final demand category all increased. • India's aggregate embodied intensity changes mainly determine by production structure changes. Abstract India is the second largest developing country and fourth largest carbon emitter in the world. It has registered the rapid economic growth (7–9%) in the last decade. However, both its total carbon emissions and emission intensity (CO 2 emissions per GDP) kept increasing during period 2007–2013. There are few studies using input-output (I-O) analysis for India's energy/emissions in the literature. This paper tries to fill in the gap by using I-O framework to study India's total emissions and intensity changes and its driving forces with the latest data available and newly proposed techniques. The results show that India's carbon emission were mainly driven by private consumption (50–55%), followed by investment (25–26%) and exports (14–19%). During period 2007/08–2013/14, India's total emissions increased by 56.6%, where total final demand change resulted in emissions increasing and the shift of demand from raw material industry to high-value added manufacturing industry helped to reduce the emissions. When measuring India's relative emission efficiency, its aggregate embodied intensity (AEI) indicator in aggregate was mainly determined by private consumption (47–49%), followed by investment (23–24%) and exports (15–18%). From 2007/08 to 2013/14, the AEI values in aggregate and by final demand category all increased except the AEI of inventory change, mainly caused by production structure change. The emission efficiency improvements helped to reduce India's total emissions and carbon intensity, but the contributions were small. The policy implications of our findings are also discussed. [ABSTRACT FROM AUTHOR]

Highlights • A new framework of energy and water systems on island has been proposed. • Water demand and renewable energy potential of the Maldives are estimated. • Feasibility analysis of renewable energy-driven island was done in the Maldives. • It is possible for the Maldives to be a “zero input” system as to energy & water. Abstract Water and energy supply systems are essential parts of the infrastructure on islands. For small islands that are far from continents, water shortage is usually the main constraint on economic and social development. In order to maintain island water security, desalination plants are built to supply fresh water. The plants need a great deal of energy, which increases demand for energy and the cost of transportation. Thus, it is necessary to design a new island system driven by renewable energy. This study investigated the existing type of water and energy supply systems in some typical islands of the world, and analyzed their advantages and disadvantages. The energy supply systems can be classified into three categories: imported conventional energy supply system (ICESS); imported conventional energy & renewable energy supply system (ICE&RESS); and integrated energy supply system (IESS). Water supply systems can also be classified into three categories: imported water supply system (ImWSS); imported water and unconventional water supply system (IW&UWSS); and integrated water supply system (InWSS). The nexus of energy and water is very complicated on islands. This paper presents a framework for an interconnected energy and water system on an island. The new framework reveals a roadmap from “full input of energy & water (FIEW)” through “semi-input of energy & water (SIEW)” to “zero input of energy & water (ZIEW)”, which leads an island's energy and water resources to become gradually independent from the mainland. The new framework also reduces transportation costs and carbon emissions. The proposed framework is applied to the Maldives to aid design of a renewable energy-driven water supply system. The characteristics and mutual adaptability of three types of renewable energy (solar, wind, and biomass energy) and water supply systems is discussed. The results show that a ZIEW system can be realized in the Maldives with a reduction in the cost of renewable energy. ZIEW system has great potential for application in island regions in the future. [ABSTRACT FROM AUTHOR]

The Chinese government has committed to reduce its carbon dioxide emissions per unit gross domestic product by 60–65% from 2005 levels by 2030. In order to achieve this commitment, various measures should be taken. Due to the complex relationship between carbon emission and economic development, it is critical to quantify the impacts of different measures. Under such a circumstance, this paper is to identify the effects of carbon tax on the sectoral competitiveness in Shanghai by 2030 under unequal imposition of carbon tax between Shanghai and the rest of China by using a two-region dynamic computable general equilibrium (CGE) model. Research results show that different carbon tax rates in different regions would affect GDP of Shanghai and the outcomes are different under different scenarios. In general, a lower carbon tax rate can lead to a higher output and these output changes could further influence the sectoral competitiveness. Under the tax44 scenario, sectors such as agriculture, textile, transport equipment, and electronics are the winners in Shanghai, with outputs increased by 2.02%, 1.47%, 1.08% and 3.05%, respectively; while food production, petrol oil, chemicals and non-metal are the losers, with outputs decreased by 2.02%, 0.87%, 0.03% and 2.39%, respectively. This study also reveals that price and scale effects are the key factors influencing the changes of sectoral outputs. Such findings provide useful insights to those policy makers to allocate appropriate carbon reduction targets to different regions. [ABSTRACT FROM AUTHOR]

This paper attempts to explore the effect of energy construction adjustment on the energy-saving and emission-reduction (ESER) dynamical evolution system. Based on the nonlinear dynamics theory, the dynamic behavior of the novel system is discussed. The quantitative coefficients of the actual system are identified with the aid of genetic algorithm-back propagation neural network. Scenario analysis results show that, energy construction adjustment could effectively control energy intensity. To clarify this further, an example of 4D ESER system with new energy constraints is demonstrated. Investigation results show that, government control can effectively control energy intensity, while brings inhibiting impact on economic growth and people’s livelihood. Economic investment is the key variable affecting energy construction adjustment and ESER, the ESER system will crash when the investment is too low. Energy construction adjustment could effectively reduce energy intensity. However, the ESER system will also crash if the development of energy construction adjustment is too fast. The interesting thing is that the ESER system should be pulled back to steady state as the investment getting bigger. Energy intensity could be controlled in expected range by taking adequate measures. Full use of the role of energy structure adjustment should be made to promote the development of new energy, while government control is used only when necessary. [ABSTRACT FROM AUTHOR]

Regional imbalance in development is amongst the most important challenges for China. As the country’s leading economic engines, three major economic circles representing 6.5% of the national land territory contributed to more than 2/5 of national gross domestic product (GDP). This paper focuses on the impact of these three growth poles in China’s regional development, particularly for their embodied energy uses in light of multi-regional input-output analysis. Significantly, the three developed areas generated huge demands for embodied energy, 1237.52 Mtce and 40.1% of the total domestic supply in 2010, but far from self-sufficient. In Yangtze-River-Delta , Pearl-River-Delta and Jing-Jin-Ji , 93.1%, 85.1% and 63.4% of their embodied energy uses respectively can be traced back to the energy-supply provinces such as Shanxi, Inner Mongolia and Shaanxi and other trade partners. Over a half of the national interregional transfers of embodied energy via domestic trade were induced by the three economic circles’ final demand, largely resulted from their large-scale infrastructure construction, upgraded consumption structures, high export dependency and ongoing urbanization process. The results indicate that demand-driven embodied energy is a comprehensive indicator to reflect the real energy use patterns of developed regions or megacities and reveal their industrial positions in domestic and even global supply chains. Understanding the temporal and spatial energy transition along with regional development from consumption-based insights is a vital step toward appropriately targeted policy making for the nationwide energy saving and emission reduction. [ABSTRACT FROM AUTHOR]

As a fundamental approach to assess active management and decision-making challenges in large state-owned energy companies (e.g., sustainability, social responsibility, economic growth, and shareholder value), this paper presents a methodological approach, based on a real case study, for integrating real options analysis into multicriteria analysis in order to evaluate and holistically rank a portfolio of multiple firms’ projects. While real options analysis adds value to the projects by hedging uncertainty and valuing flexibility in the decision-making process, multicriteria analysis allows ranking the projects through an Aggregate Quality function that synthesizes economic and social impacts such as gross domestic product and employment. The proposed approach divides the decision-making problem into three main areas that consider aspects related to decision makers’ preferences ( behavioral area ), data analysis ( analytical area ), and projects’ rankings ( multicriteria analysis methods ) based on the use of Preference Ranking Organization Methods for Enrichment Evaluations (PROMETHEE). A case example involving a portfolio of projects in state-owned energy companies discusses the benefits of the proposed methodology. [ABSTRACT FROM AUTHOR]

This paper attempts to explore carbon tax pilot in Yangtze River Delta (YRD) urban agglomerations based on a novel energy-saving and emission-reduction (ESER) system with carbon tax constraints, which has not yet been discussed in present literature. A novel carbon tax attractor is achieved through the discussion of the dynamic behavior of the new system. Based on the genetic algorithm-back propagation neural network, the quantitative coefficients of the actual system are identified. The scenario analysis results show that, under the same tax rate and constraint conditions, the ESER system in YRD urban agglomerations is superior to the average case in China, in which the impacts on economic growth are almost the same. The former’s energy intensity is lower and the shock resistance is stronger. It is found that economic property of YRD urban agglomerations is the main cause for the ESER system of YRD urban agglomerations being superior. In the current YRD urban agglomerations’ ESER system, energy intensity cannot be adjusted to an ideal level by commercialization management and government control; however, it is under effective control of carbon tax incentives. Therefore, strengthening the economic property of YRD urban agglomerations and effective utilization of carbon tax incentives could perfectly control energy intensity, without obvious potential negative impact on economic growth. [ABSTRACT FROM AUTHOR]

Islands are facing considerable challenges in meeting their energy needs in a sustainable, affordable and reliable way. The present paper develops an integrated approach to economically assess initiatives that can transform island power systems into smart ones. Single and multi-action initiatives fostering the deployment of renewable energy sources (RES), energy storage systems (ESS), demand-side management (DSM), and electric vehicle (EV) are considered. An hourly unit commitment on a weekly basis is proposed to assess the impact of the initiatives on the system operation costs of five prototype island power systems, which have been identified by applying clustering techniques to a set of sixty islands power systems. The different investment costs of the initiatives are accounted for determining their corresponding internal rate of return (IRR) through their lifetime. The economic assessment of single and multi-action initiatives for five prototype islands representing sixty island power systems quantifies which initiatives are most suitable for which type of island power system. The assessment shows that islands of different sizes and features require different initiatives. Larger islands tend to DSM initiatives, whereas smaller islands tend to RES initiatives. Multi-action initiatives achieve highest system operation cost reduction, whereas single action initiatives yield to highest IRR. [ABSTRACT FROM AUTHOR]

Rapid urbanization and the expansion of metropolitan areas have resulted in severe demands on water and energy resources, which threaten the sustainability of the urban economy and environment. In this paper, an input–output model and linkage analysis are used to detect the synergetic effects of water and energy consumption and interactions among economic sectors. Beijing is chosen as a case study to investigate the water–energy nexus and the water and energy importing and exporting functions of major economic sectors. The results reveal that the agriculture and food processing sectors are major virtual water suppliers, while petroleum and natural gas processing, and electricity production sectors are major embodied energy suppliers. These energy suppliers mainly import intermediate products to satisfy the final demand of Beijing, thus transferring resources pressure to other regions. With rapid urbanization, the real estate industry sector chain has become an important water–energy nexus node and resources transfer node. The real estate sector needs large amounts of virtual water and embodied energy resource inputs to continue its production and thereby promote the growth of logistical industries. The transportation sector was also found to be important energy consumer and energy transfer node. In addition, the services sector, contributing one fourth of Beijing’s total GDP, is a key water–energy nexus node because it consumes considerable amounts of both virtual water and embodied energy resources to support its production pattern. [ABSTRACT FROM AUTHOR]

The United Nations agenda for sustainable development by the year 2030 proposes 17 sustainable development goals which include access to affordable, reliable and clean energy, sustained economic growth with full productive employment and, urgent action to mitigate environmental degradation. Planning for sustainable development requires integrating conflicting criteria on economy, energy, environment and social aspects. In this paper, we introduce a Weighted Goal Programming model involving criteria on the economic development (GDP), the electricity consumption, the greenhouse gas emissions, and the total number of employees to determine optimal labor allocation across various economic sectors. The proposed model is validated with data from the six members of the Gulf Cooperation Council (namely Bahrain, Kuwait, Oman, Qatar, Saudi Arabia and the United Arab Emirates). The results of the model aim to provide empirical evidence and insights to decision makers and policy analysts in developing optimal strategies able to simultaneously satisfy energy demand, economic growth, labor development and reduction in greenhouse gas emissions to achieve sustainability targets by the year 2030. [ABSTRACT FROM AUTHOR]

Along with rapid development of economy, urbanization and industrialization in China, the transportation sector especially road transport accounts for the quickest growth of energy consumption and greenhouse gas (GHG) emissions across the country. This paper selects four representative cities (Beijing, Shanghai, Guangzhou, and Chongqing) in the north, east, south, and west of China as targets of case study. It predicts future motor vehicle population in various cities using the Gompertz Model, and predicts and analyzes fuel consumption and GHG emissions of different types of motor vehicles in the case cities by 2035. The results indicate that besides gasoline and diesel, in the future uses of various types of vehicle fuels will follow different patterns among these four cities due to diverse resources endowment, economic strength, technology levels and geographical features. Based on predicted vehicle population and fuel consumption, it is found that from 2013 to 2035, GHG emissions from tank to wheel (TTW) and well to wheel (WTW) in all cities will continuously increase yet at different rates. If there is no interference from new policies, around 2020 Chongqing is expected to replace Beijing as the city with the highest volume of GHG emissions of vehicles among four case study cities. Therefore, the four cities especially Chongqing need urgently to develop or adjust low-carbon policies in road transportation sector, in order to achieve China’s future greenhouse gas reduction targets. Some policy implications to reduce GHG emissions of the road transportation sectors of the case cities are suggested based on the analysis results. [ABSTRACT FROM AUTHOR]

The so-called post-China countries (PC-16́s), distinguished by low wages and high economic growth, will replace China as the “world’s factory”. The aim of this paper is to assess the effect of these changes on global CO 2 emissions pathways. To achieve this, a counterfactual is proposed wherein China’s trade with the rest of the world is replaced by the PC-16’s trade in a global multiregional input–output context. The emissions savings realized by trade replacement are significant in those scenarios where the current pattern of trade is maintained (−13% on emissions traded and −3.5% on global emissions) and in scenarios where enterprises relocate their production directly or indirectly to the most environmentally efficient countries (ranging from −15.2% to −18.2% on emissions embodied in trade). Nevertheless, the potential savings drop considerably (ranging from −1.5% to −7.1%) if companies and host countries take advantage of cheaper, but more polluting means of production and do not internalize the externalities. Through changes in international trade, there is a possibility of reducing emissions, which have to be included in international, multilateral and bilateral agreements to mitigate climate change if we do not want to lose the opportunities these changes present. [ABSTRACT FROM AUTHOR]

• Constructing a new welfare function considering economy, equity and ecology. • Optimizing carbon emission pathways from multiple perspectives. • Focusing on the emission pathways in China achieving the ambitious targets. With the increasing climate warming, reducing carbon emissions has gradually become a consensus around the world. However, the process of carbon emission reduction will inevitably lead to the transformation of economic structure, industrial structure and energy structure, which will bring huge changes in economic output, employment and other aspects, thus affecting the overall social welfare and equity. Therefore, it is particularly important for each country to determine a scientific and effective carbon emission pathway which take into account both social development and climate targets. As the largest carbon emitter, China has put forward the targets of carbon peak and carbon neutrality. In this regard, the corresponding carbon emission reduction scenarios are designed according to the new situation of China's emission reduction in this paper, firstly. Furthermore, under the premise of maximizing social welfare, an optimization model which integrating economic growth-equity-environment is developed to determine China's emission pathways under different scenarios from 2020 to 2050. Besides quantitatively showing the future total amount and peak value of carbon emissions under different scenarios, the results can also identify its evolution pathway over time. Therein, the peak under most scenarios will concentrate in 2025–2030, which is about 10.7 to 11.8 billion tons. With the increasingly stringent constraints on carbon emission reduction, the cost of emission reduction will increase correspondingly, but the overall social welfare will increase slightly. Finally, our findings provide practical guidance on achieving carbon emission reduction and enlightenments on policymaking. [ABSTRACT FROM AUTHOR]

Facing serious energy constraints and environmental challenges, policy makers in China have set up clear targets to reduce energy intensity in order to secure a sustainable economic growth; however, it is unclear in theory what the determining forces are. The empirical evidence, although intensively discussed in the literature, also remain divided in opinion. This paper contributes to the existing literature full of heated debates using a Bayesian averaging approach to identify robust determinants of energy intensity in China. Using provincial level data, key contributors that help explain the level of energy intensity across China are found. By ranking the relative importance of explanatory variables according to their posterior inclusion probabilities, this study can also offer support to policy makers in designing intensity reduction policies. It is suggested that policies should focus on those robust and relatively more important factors such as fiscal expenditure, infrastructure and economic structure. [ABSTRACT FROM AUTHOR]

Due to fast rising energy demand, Southeast Asia has become a larger energy consumer and bigger player in global energy markets. Energy security and environmental emissions reduction have become higher priorities to ensure energy supply at affordable costs, for continued economic growth and development. To address these issues renewable energy plays a vital role in the long-term future for sustainable development. This paper estimates and analyzes the renewable energy potential in the energy mix in two Southeast Asian countries, Indonesia and Thailand. The LEAP energy model is used to develop different renewable energy policy scenarios from base year 2010 to 2050. The results of the simulation show that a large proportion of electricity must be produced by renewables by 2050 if full potential of renewables is to be exploited. In this case, 81% and 88% of CO 2 emissions are reduced in Indonesia and Thailand respectively. In implementing renewables at large scale in both these countries the cost of production increases substantially. [ABSTRACT FROM AUTHOR]

Coal comprises 70% of primary energy sources and 80% of electricity generation in China. This paper investigates the coal consumption–economic growth nexus in an integrated demand–supply framework over the period from 1978 to 2010. We incorporate the role of coal technology to explain the growth process. Using the Autoregressive Distributed Lag bounds testing approach, we find improvement in the coal-to-electricity efficiency indicator, a proxy for coal technology, causing almost a 35% increase in real GDP in the long run. The Toda–Yamamoto causality test indicates unidirectional causality from coal consumption to economic growth, feedback effects both for coal-to-electricity efficiency indicator to economic growth and coal demand and openness to coal consumption. For a robustness check, we forecast the validity of the causal relationships beyond the sample horizon using the generalised forecast error variance decomposition method. Our analysis suggests that improving overall efficiency in coal sector will continue to play a significant role in maintaining sustainable growth in China in the long run. [ABSTRACT FROM AUTHOR]

The current mode of economic development in China is typified by high growth, high energy consumption, and high pollution characteristics and this has caused great stress on both energy consumption and the environment. This paper focuses on a historical analysis of China’s energy, environmental, and economic (‘E3’) efficiency and the sources of E3 productivity growth therein. A developed slacks-based measure is utilized to evaluate the performance of E3 efficiency and decompose the performance fluctuations into three components: energy, economy, and environmental efficiency fluctuations. By applying a method based on global data envelopment analysis, we also analyze the key factors responsible for the change in E3 productivity during 2002–11 from the point of view of technical progress, production scale, and management level. The results show that China performs well on the economic front, while the energy and environmental performances are not optimistic. Fortunately, energy and environmental efficiency have gradually improved in recent years. Further analysis shows that the trend in E3 productivity in China has begun to follow an ascending path. Technical progress is the most powerful contributor to China’s E3 productivity growth, while falling scale and management efficiency are the two main obstacles preventing improvement in E3 productivity. [ABSTRACT FROM AUTHOR]

With fast economic development, industrialization and urbanization, China faces increasing pressures on carbon emission reduction, and especially on air pollutants (SO 2 , NOx, PM) reduction, particularly the notorious haze issue caused by air pollution in recent years. Pursuing co-benefits is an effective approach to simultaneously respond to both carbon and air pollutant problems. In this paper, the AIM/CGE (Asia–Pacific Integrated Assessment Model/Computational General Equilibrium) model and GAINS (Greenhouse Gas and Air Pollution Interactions and Synergies)-China model are combined together to project future CO 2 and air pollutants emissions in China, as well as reduction costs and co-benefit effects. Considering implementation of carbon mitigation policy and air pollutant mitigation technologies, four scenarios (S1, S2, S3 and S4) are analyzed. Results indicate that by implementing both carbon and air pollutant mitigation (S4), CO 2 emission per GDP can be reduced by 41% by 2020, compared with the 2005 level, and SO 2 , NOx and PM2.5 emissions would change by a factor 0.8, 1.26 and 1.0 of the 2005 level, respectively in 2030. The real co-benefits of emission reductions (S2 minus S4) for SO 2 , NOx and PM2.5 are 2.4 Mt, 2.1 Mt and 0.3 Mt in 2020, and the corresponding cost reduction co-benefits are 4, 0.11, and 0.8 billion €, respectively. Provincial disparity analysis reveals that regions with higher co-benefits are those with higher GDP such as Guangdong, Shandong and Jiangsu, energy production bases such as Inner Mongolia and Shanxi, low coal quality provinces such as Sichuan (for SO 2 ), and industrial base provinces such as Liaoning. Cost-effectiveness is finally discussed for policy implications, which suggests that investment in less developed western regions is more cost-effective and easier in reducing CO 2 or air pollutant emissions than in developed eastern regions. [ABSTRACT FROM AUTHOR]

India’s recent macro-economic and structural changes are transforming the economy and bringing significant changes to energy demand behaviour. Life-style and consumption behaviour are evolving rapidly due to accelerated economic growth in recent times. The population structure is changing, thereby offering the country with the potential to reap the population dividend. The country is also urbanising rapidly, and the fast-growing middle class segment of the population is fuelling consumerism by mimicking international life-styles. These changes are likely to have significant implications for energy demand in the future, particularly in the residential sector. Using the end-use approach of demand analysis, this paper analyses how residential energy demand is likely to evolve as a consequence of India’s transformation and finds that by 2030, India’s commercial energy demand in the residential sector can quadruple in the high scenario compared to the demand in 2010. Demand for modern fuels like electricity and liquefied petroleum gas is likely to grow at a faster rate. However, there is a window of opportunity to better manage the evolution of residential demand in India through energy efficiency improvement. [ABSTRACT FROM AUTHOR]

Recently, significant reserves of natural gas have been identified in Mozambique and Tanzania. These resources may support a pathway to both economic growth and a low-carbon future. This natural gas could be used locally for a host of different applications such as cooking, power generation, transportation and fertilizer production. The aim of this paper is to investigate how the potential future demand for natural gas across sectors and countries might impact the economic viability of an investment in a new regional transmission and distribution gas network in Eastern and Southern Africa. We analyze the economic viability by using future demand and pricing data inferred for biomass, charcoal, LPG and liquid fuels currently being used in the continent. The investment and transmission costs are assessed for various scenarios of transmission pipeline networks. Then, a detailed analysis for a gas transmission network across eight Eastern African countries is presented. Results suggest that the development of a regional gas pipeline network within the continent is an attractive investment (based on internal regional demand as well as co-benefits to economy, environment and health) that can complement LNG export, which is the dominant market option being considered to enable the large upstream investments. [ABSTRACT FROM AUTHOR]

This paper disaggregates energy consumption and GDP data according to end-use to analyze a broad number of developed and developing countries grouped in panels by similar characteristics. Panel long-run causality is assessed with a relatively under-utilized approach recommend by Canning and Pedroni (2008) [1]. We examine (i) reduced form production function models for both the industry and service/commercial sectors, where aggregate energy consumption is expected to cause aggregate output; and (ii) reduced form demand models, where income is expected to cause (separately) per capita residential electricity consumption and per capita gasoline consumption. We uncover for 12 different panels a set of super-consistent causality findings across two demand models that income “Granger-causes” per capita consumption. By contrast, the results from the production function models suggest that a different modeling framework is required to glean new, useful insights. [ABSTRACT FROM AUTHOR]

With rapid economic growth, China is facing tremendous pressures of emission–reduction and serious income inequality issues. The existing research is concerned with the relationships between income inequality and CO 2 emissions in recent years, but little attention has been paid to the regional differences in China. This paper investigated the impact of income and its inequality on CO 2 emissions at the national and regional levels using the panel data from 1995 to 2010 in China. The empirical results show that income growth increases China’s CO 2 emissions. The effects of income growth on CO 2 emissions vary across regions. Further, the impact of income inequality on CO 2 emissions in the Eastern region is greater than that in the Western region. This research reveals that a more equitable income distribution may help control CO 2 emissions in developing China, and there is a win–win situation of income redistribution and emission–reduction. Our findings merit particular attention from policy makers in China. [ABSTRACT FROM AUTHOR]

• The paper introduces an index to measure the progress towards meeting the industry-related targets of the 2030 Agenda. • The SDG-9 index benchmarks industrial performance while preserving the environment and promoting inclusiveness. • The final ranking compares performance of 128 economies over the period 2000–2016. • Economic growth should be accompanied by technological changes and efficient use of natural resources. This article introduces the SDG-9 index as a measure of country progress towards achieving industry-related targets of Sustainable Development Goal 9 (SDG-9). The SDG-9 index represents a comprehensive but straightforward approach to assess the extent to which countries have industrialized while promoting social inclusiveness and minimizing natural resource use and environmental impacts. The selection of indicators is based on the global indicator framework for the Goals and targets of the 2030 Agenda adopted by the United Nations General Assembly. The resulting SDG-9 index benchmarks inclusive and sustainable industrial development in 128 economies over the period 2000–2016. In general, industrialized economies outperform other countries, with the top five leading the 2016 ranking being Ireland, Germany, the Republic of Korea, Switzerland and Japan. The calculated scores of the SDG-9 index can show in which dimensions countries represent the leaders or lag behind other economies. Thus, the SDG-9 index forms a valuable tool for policy makers and analysts. [ABSTRACT FROM AUTHOR]

• We explore whether each of the 30 Chinese provinces will peak emissions by 2030. • We combine STIRPAT models and scenario analyses to predict emissions trajectories. • 26 provinces are likely to peak emissions under at least one scenario, but 4 are not. • Peaking time and cumulative emissions are considered in seeking optimal peaking path. • Provincial results in aggregate show China may peak in 2028–2040 and 2030 is optimal. China has pledged in its Nationally Determined Contributions (NDCs) that its carbon emissions will peak no later than 2030. However, the varying carbon emissions trajectories of individual provinces make it difficult to determine whether China can fulfill this ambitious goal on time. To bring transparency and clarity to this core issue, this paper explores for the first time whether and how all the 30 Chinese provinces will peak their energy-related emissions in future by developing a set of extended STIRPAT models that investigate the driving forces behind each province and integrating the estimates into scenario analysis for peaking simulation. We observe that, despite continued economic growth, 26 provinces are highly likely to reach peak emissions under at least one scenario, whereas the remaining are not. We find it interesting that the earliest peaking scenarios may not be the best option for those provinces whose cumulative carbon emissions are estimated to be considerably large. To ensure a viable reaching of China's peak emissions, much more attention should be paid to seeking for the most appropriate emissions trajectory to peak at the subnational level with relatively low cumulative value. Provincial results in aggregate show that China may peak emissions in the period 2028–2040, with cumulative emissions ranging from 403,607 Mt CO 2 (corresponding to peaking in 2030) to 456,191 Mt CO 2 (corresponding to peaking in 2038), while 2030 would be the optimal year for the country to peak because of the lowest cumulative carbon emissions. Our findings only provide a deeper understanding of China's potential peaking paths by province, but also assist policy makers in better prediction and evaluation of possible emissions trajectory for other nations and the whole world from a bottom-up perspective, and therefore could be of global significance. [ABSTRACT FROM AUTHOR]

• A new method, open system network effectiveness analysis, is introduced. • Two performance metrics, effectiveness of utilization and conversion are developed. • Effectiveness measures the ability of a city to maximize the resource available. • The case study of Singapore shows the trajectory of effectiveness for 2005–2014. Cities have evolved as centers of economic growth and often described as open systems where the intake of resources is heavily dependent on flows imported from the external environment. The question is, how much of the resource available in cities is effectively utilized? In response, this paper develops an ecological-thermodynamic approach to assess the ability of a system to make full use of the resources available and reduce the demand for new resources. In this work, open system network effectiveness analysis is introduced as a novel assessment method to investigate the cities' producer and consumer behaviors by studying the resource flow connections and the interactions between the socio-economic sectors. Investigation on the urban flows network evaluates the ability of the system to utilize the resource imported through the effectiveness of utilization indicator and the ability to convert the resource imported to useful products through the effectiveness of conversion indicator. The effectiveness indicators, utilization and conversion, represent the consumption and production characteristics of the system respectively. This is tested through a case study conducted for Singapore city over the time period 2005–2014. The effectiveness results show that the city, on average, has utilized 45% of the maximum extractable usefulness from the resources imported throughout the years, with the lowest effectiveness, 39%, and the highest effectiveness, 50%, in the years 2007 and 2014 respectively. The trajectory of effectiveness results throughout the years suggests a trade-off relationship between the producers and consumers to balance the production and consumption of resources in the city. [ABSTRACT FROM AUTHOR]

• Convergence in energy efficiency of BRI counties and its factors are studied. • Energy efficiency along BRI experienced an increasing trend except 2009 and 2010. • BRI countries with low TFEE are catching up with countries with high TFEE. • High-income & Eastern Europe and West Asia countries have faster catch-up rate. The Belt and Road Initiative (BRI) has raised concern that it may involve an extensive economic growth pattern at a higher cost of energy and the environment, and China is making a great effort to construct a green BRI, which may improve the general energy efficiency of BRI countries. Therefore, it is important to investigate whether backward countries with low energy efficiency are catching up with frontier countries or falling behind. In response, this paper adopts DEA to calculate the total-factor energy efficiency (TFEE) of the BRI countries, and investigates heterogeneous beta-convergence in energy efficiency of BRI counties and its factors. The results indicate that: (1) except for 2009 and 2010, the TFEE along the BRI experienced an increasing trend due to the global finance crisis; (2) BRI countries with low TFEE are catching up with countries with high TFEE, and more significantly when the TFEE growth rate is greater; (3) the TFEE converges at a faster rate in high-income BRI countries and Eastern Europe and West Asia countries; and (4) inadequate innovation ability and a weak R&D absorption capacity may decelerate the energy efficiency convergence rate of BRI countries, especially those with low-income. [ABSTRACT FROM AUTHOR]