Search

As the main energy consumption and emission area, carbon emission reduction for industrial parks is a pivotal target for China. In this study, a multi-objective optimization model was established to quantitatively develop low-carbon development strategies for industrial parks that simultaneously considers land productivity, energy structure and efficiency, carbon emissions, and industrial structure optimization. A Monte Carlo method was adopted to investigate the uncertainties associated with emission-reduction technologies and economic development. A study on an industrial park showed that with the implementation of a series of fossil energy-saving measures, the percentage of clean energy in the park is projected to reach 62.6–72.2 %, while the percentage of output from energy-intensive enterprises relative to the total output of the industrial park decreases from 3.78 % in the baseline year to 1.74–3.29 %, and carbon emissions are projected to decrease by 69–85.4 % relative to the benchmarking scenario. This implies that the model developed in this study is effective and can serve as a roadmap for designing industrial parks to realize low-carbon development. • A multi-objective optimization model is used to achieve low-carbon industrial park. • The model integrates energy system management and industrial structure adjustment. • A Monte Carlo method was adopted to investigate uncertainties associated the. • Model. • An applied study showed the effective of the model. [ABSTRACT FROM AUTHOR]

The application of Hybrid Electric Wheel Loaders (HEWL) represents an attractive option for future industrial development. In order to reduce the equivalent fuel consumption and extend the lifetime of the battery, a real time whale optimal algorithm and general regression neural network (WOA-GRNN) based hierarchical model predictive control (WG-MPC) energy management strategy for HEWL is proposed. The structure of the WG-MPC consists of three layers, namely, the prediction layer, the economic layer and the control layer. In the prediction layer, a prediction model based on WOA-GRNN is proposed for the complex demand power prediction. In the economic layer, the equivalent diesel cost, diesel generator operation cost, the lifetime cost of the diesel generator and the battery pack are considered. The control layer is designed based on improved MPC. Through the simulation analysis, the proposed WOA-GRNN prediction model achieves the best prediction accuracy compared with the traditional prediction methods. Compared with FT-MPC and ECMS, the total economic cost of WG-MPC is reduced by 3.42% and 5.12%, respectively. The simulation results demonstrate that the proposed WG-MPC strategy has good control performance, high computational efficiency, low equivalent diesel consumption, longer battery lifetime and good use cost economy, which is of great significance for practical applications. • A real time EMS based on WG-MPC is proposed for hybrid electric wheel loaders. • A novel prediction model based on WOA-GRNN is proposed. • An actual economic cost model of HEWL is established. • The control function combines the economy optimization with control performance is developed. • The good economic performance and control performance of the proposed EMS is verified under real driving condition. [ABSTRACT FROM AUTHOR]

In the belief that no country in the world can develop without a strong industrial sector, African leaders have consistently stressed the importance of industrialization for sustainable development. Despite the benefits of industrialization, Africa remains the least industrialized region in the world. Moreover, this is the region where the problem of energy poverty is most acute, with the lowest levels of access to and consumption of electricity. Thus, this study analyzes the effect of energy poverty on industrialization in a sample of 44 African countries. Using the two-step system Generalized Method of Moments, empirical results resilient to a set of robustness checks consistently show that reducing energy poverty is a necessary condition for the industrialization of African countries. Through a mediation analysis, this study identifies human capital and income as some channels through which the reduction of energy poverty favors the industrialization of African countries. The conclusions of this study have the main implication of inviting African decision-makers to improve the effectiveness of the various national and sub-regional initiatives aimed at guaranteeing access to clean, reliable, and modern energy for all in order to foster the industrialization of African economies. • The study analyzes the effect of energy poverty on industrialization in 44 African countries. • Static and dynamic panel estimation techniques are used. • Results suggest that energy poverty impedes industrialization. • Human capital, and income are some transmission channels. [ABSTRACT FROM AUTHOR]

Trade flows between provinces have led to the transfer of embodied carbon emissions. Therefore, when formulating carbon emission reduction policies for a province, it's necessary to consider the carbon emissions implied in trade. In this study, we established an interprovincial carbon flow analysis framework based on multi-regional input-output model, and we used China's 1997, 2002, 2007, and 2012 input-output data to make an empirical research of Hebei Province. The findings are as follows. Firstly, from 1997 to 2012, the embodied carbon emissions' net outflow of Hebei increased by 244.26 Mt, the number of the provinces that net inflowed carbon from Hebei increased from 18 to 22, and they extended from eastern coastal provinces and southern China to most parts of the country. Secondly, technological level and trade demand are the main factors affecting carbon emissions' net outflow, contributing −108.45 Mt and 352.71 Mt, respectively. On this basis, we developed a relationship model of the net outflow of carbon emission and commodity value to optimize the industrial development. Different from previous studies, our research has penetrated into every industry and every related province. We not only calculated the commodity transfer and embodied carbon transfer between Hebei Province and other provinces, and balanced the advantages and disadvantages of trade between key industries and provinces, then gave specific solutions and optimization measures, which has stronger practical meaning and guiding significance. • From 1997 to 2012, the embodied carbon's net outflow of Hebei increased by 244 Mt. • The number of target provinces has increased and spread across the country. • Technical level and trade demand are the main factors affecting carbon's outflow. • The net outflow is mainly concentrated in three industries. • Trade relations with other provinces need to be adjusted. [ABSTRACT FROM AUTHOR]

This paper examines the asymmetric impact of oil price, economic growth, financial development, and industrialization on oil consumption in Tunisia, using the Nonlinear Autoregressive Distributed Lag (NARDL) model over the period 1980–2020. The NARDL bound testing approach confirms the presence of a cointegrating relationship between oil demand and its determinants. The results show that oil demand is income elastic and price inelastic. In the long run, the impact of increased and decreased financial development on oil consumption is found positive and negative, respectively. The findings also highlight that a positive (negative) shock to industrialization decreases (increases) energy consumption. The study of symmetrical causality supports the feedback hypothesis between growth and consumption. However, the asymmetric causality analysis shows that only negative shocks to economic growth have impacts on oil demand. The Tunisian economic model could be oriented in such a way as to support economic activity and implement energy saving policies. Finally, the implications of the different findings are discussed and key recommendations for policymakers are also provided. • The demand for oil is income elastic and price inelastic. • There is a positive relationship between financial development and oil consumption. • There is a negative relationship between industrialization and oil demand. • Only negative shocks to economic growth impact on oil demand. [ABSTRACT FROM AUTHOR]

Abstract The current study discusses the linear and non-linear relationship between trade, and non-renewable and renewable energy consumption using data of 72 countries extending from 1990 to 2012. Our empirical models integrate some additional variables which affect the above-mentioned relationship such as GDP, CO 2 emissions, domestic resources abundance, and some interaction terms. The innovation of the paper is not only to compare between developed and developing countries but also between industrialized countries and non-industrialized ones by integrating some dummy variables into the models. The empirical results demonstrate that trade and energy consumption (renewable or non-renewable) have a mutually reinforcing linear relationship. Moreover, the validity of non-linear relationships is accepted only in the case of the impact of non-renewable on trade. This latter follows an inverted U-shape form in the case of developed and industrialized countries while a U-Shape one in the case of developing and non-industrialized countries. In addition, the findings indicate a positive contribution of GDP, capital, and labor on trade and energy consumption. However, CO 2 emissions and natural resource have positive impacts on trade and non-renewable energy while negative effect on renewable energy. It implies that policy makers should develop appropriate policies to profit from trade and energy consumption. Highlights • We investigate the linear and non-linear relationship between energy consumption (renewable or non-renewable), and trade. • We focus in developed versus developing countries and industrialized versus non-industrialized ones from 1990 to 2012. • We use GMM dynamic panel data models. • We state bidirectional linear links between trade and renewable energy consumption. • We obtain a non-linear impact of trade on non-renewable energy consumption against a linear effect in the opposite sense. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to investigate the dynamic long run relationship between CO 2 emissions, economic growth, financial development, trade openness, industrialization, urbanization, coal and noncarbohydrate energy consumption within the framework of environmental Kuznets curve (EKC) for Turkey over the period 1971–2014. The two main contributions of this study are that the EKC hypothesis has been examined by separating trade openness and final energy consumption into import-export and coal-noncarbohydrate energy consumption respectively. The findings of the autoregressive disturbed lag bounds testing approach showed that economic growth, coal consumption, financial development, import, industrialization and urbanization had a positive impact on CO 2 emissions, while export and noncarbohydrate energy consumption decreased CO 2 emission in the long run. Moreover, the study supported the EKC hypothesis, which suggests an inverted U-shaped relationship between per capita income and CO 2 emissions. The turning point obtained from long run regression was found to be approximately $14360 that outside of the sample period. Finally, these important findings indicate that noncarbohydrate energy consumption and export can be a solution to reduce environmental pollution, and Turkey's CO 2 emissions will begin to decline when the country reaches the per capita income level at the turning point in the coming years. [ABSTRACT FROM AUTHOR]

This study empirically explored the nexus of wind energy (with regards to the effect of the drought), industrial-economic development, and emitted CO 2 in 41 World's top countries in wind energy consumption from 1997 to 2018. Cross-sectional augmented distributed lag estimators (CS-DL, CS-ARDL, CCE-P) and newly updated estimation packages to effectively assess the relationships between variables. Our results are the following: First, severe droughts were not a significant matter in wind energy, and consuming wind energy reasonably contributes to reducing emitted CO 2 , while industrial and economic development positively promotes CO 2 emissions in sampled countries. Second, industrial development significantly promotes economic growth, while wind energy use has an insignificant positive effect on economic growth. Moreover, wind energy negatively affects industrial development. Third, two-way directional causal relationships were noted between CO 2 and other covariates, this hypothesis was also noted between industrial development and economic growth and wind energy use. We, therefore, suggested policy implications to reduce CO 2 across the globe and country-specific and consider the positive effect of wind energy on growth. • Wind energy-industrial-economic development-CO 2 nexus investigated for 25 years. • Most recent estimators employed in 41 top global consumers of wind energy. • Wind energy use negatively affects CO 2 , while positively affecting growth. • Industrial and economic growth positively affects CO 2. [ABSTRACT FROM AUTHOR]

The application of fuel cell hybrid construction equipment (FCHCE) represents an attractive option for future industrial development. Construction equipment has highly repetitive modes of operation, which can be used for predictive control. However, the loads usually change markedly and frequently, leading to adverse scenarios for energy management. In this paper, we focus on alleviating this problem by presenting a predictive energy management strategy based on a model predictive control (MPC) framework for FCHCE. The supervisory-level energy management objectives are to respond to rapid variations in the load of the construction equipment while minimizing the fuel consumption, improving fuel cell durability, and maintaining the state of charge (SoC) of supercapacitors within the allowable bounds. To improve the performance and practicality of the predictive controllers, we present two power demand prediction methodologies based on Markov chains and neural networks. Simulations are carried out on the representative driving cycles of a wheel loader. Simulation results validate the feasibility and effectiveness of the proposed MPC. Neural network model made better predictions than the Markov chain model, which is preferable when modeling comprehensive driving cycles. [ABSTRACT FROM AUTHOR]

We develop a theoretical framework to study energy-biased technical change considering capital, labor and energy as inputs. The framework involves a first order condition estimation of elasticity and technical change parameters for a three factor-nested Constant Elasticity of Substitution (CES) function. Technical change parameters, elasticities and time derivatives of marginal products are combined to compute technical change bias. Conceptually, we introduce total bias in order to estimate the direction without requiring a direct comparison with another factor. For Chinese industries from 1990 to 2012, the optimal structure is capital and energy to be combined at the composite level and then with labor to form total output. Technical change is found to be unambiguously energy biased, it increases in every year, and the bias is predominately away from labor. The results show that Chinese industrialization was fuelled by fossil fuels and energy-intensive technologies. Nonetheless, the growth rate of energy-biased technical change decreased during the 2000s that may result from more energy efficient development. [ABSTRACT FROM AUTHOR]

This work aims to build a comprehensive biomass torrefaction model, which can provide a wide range of information essential for industrialization and commercialization of the process. Norwegian forest residue (birch branches) was chosen as feedstock. The model is capable of presenting detailed distributions of main and by-products from the torrefaction process. In addition, important fuel properties (ultimate analysis and heating value) of the main solid product after torrefaction can be predicted. The model is validated and simulation results show good agreement with available experimental data in the literature. Reduction in mass and energy yields as well as improvement in heating value of torrefied biomass with increasing torrefaction temperature are observed. Trends for carbon, oxygen and hydrogen contents are also consistent with other experimental works. Moreover, overall energy consumption and process energy efficiency can be estimated from the model. It reveals that drying accounts for 76–80% of the total heat demand. Furthermore, the process energy efficiency reduces with increasing temperature, thus torrefaction at high temperatures is not advisable. More importantly, process optimization shows that optimal conditions for torrefaction of birch branches are 30 min holding time and a temperature between 275 and 278 °C. [ABSTRACT FROM AUTHOR]

Increasing energy demand triggered by industrialization has led to high carbon dioxide (CO 2 ) emission into the environment, causes rise in earth temperature resulting in global warming. Therefore, there is urgent need to develop a cost effective methods and materials for its sequestration from point source and reduce its impact on the environment. This paper reviewed the recent development in functionalized composites for CO 2 capture. The composites can help to develop more efficient technologies and cost effective materials for CO 2 capture in view of the exponential growing demand for energy. Myriad of researchers have focused interest on the development of novel materials to trap CO 2 using solid sorbents that appear promising. The composite adsorbents have superficial properties in terms of surface area, pore characteristic, adsorption capacity and stability at high temperature. The superior properties can be achieved by surface modification via activation or functionalization. The study revealed that functionalized composites provides superficial properties in terms of surface area, microporosity and high adsorption capacity for CO 2 sequestration. However, the development of carbon based composite derived from lignocellulose biomass and understanding the mechanism and kinetics of CO 2 onto functionalized composite have been graced with few research and needs to be explored further. [ABSTRACT FROM AUTHOR]

In March 2014 China announced its long awaited plan for managing the migration of the rural population into already overcrowded urban areas. The so called “new style” of urbanization has potentially important implications for China's energy use. However, the relationship between urbanization and energy intensity is not straight-forward. This papers investigates the direct and indirect impacts of urbanization on the intensity of energy use in China using a balanced panel of 30 provinces for the period 1995 to 2012. Using recently developed mean group estimation techniques it is found that the direct impact of urbanization on energy intensity is generally positive while the indirect impact measured through four different channels (construction, industrial upgrading, transportation and changing lifestyles) tends to be negative. On average, a one percentage point increase in urbanization leads to an increase in energy intensity of between 0.753 and 1.473% for electricity and coal intensity respectively. The construction channel tends to be the most significant indirect pathway. The transportation and industrial upgrading channels are significant but only under certain circumstances. The results also highlight the difference between formal and informal urbanization as well as the importance of province heterogeneity. The implication is that future national targets should be implemented with care. [ABSTRACT FROM AUTHOR]

This present study is the first attempt to analyze the synergy between primary energy consumption, economic growth, natural resources, quality of government, financial development, and gross capital formation in the panel data of 30 developing countries from 1990 to 2017. For this purpose, the study employed pooled regression, fixed effects, random effects, and the heterogeneous panel Dumitrescu-Hurlin causation procedure. Our findings confirm that primary energy consumption, gross capital formation, financial development, and quality of government positively impact economic growth. The heterogeneous panel causality test confirms the feedback effect hypothesis in the connection between primary energy consumption and other factors including economic growth. These results offer new insights into policy implications for the developing countries being studied. [Display omitted] • The relationship between primary energy consumption and economic growth in a multivariate framework is investigated. • The panel data consisting of 30 developing countries for the period of 1990–2017 is employed. • Regression analysis and panel Dumitrescu-Hurlin causation methods are utilized. • Primary energy consumption increased economic growth and economic growth increased energy consumption. • Bidirectional causality exists between primary energy consumption and GDP. [ABSTRACT FROM AUTHOR]

A deeper understanding of the decoupling status between carbon emissions and industrial growth as well as its influencing factors is very important in implementing targeted polices. This study applies decoupling analysis, index decomposition analysis, and attribution analysis to achieve three goals. First, the study explores the decoupling relationship between industrial growth and carbon emissions in Taiwan. Second, the factors influencing changes in industrial carbon intensity are explored. Finally, the contributions of industrial sub-sectors to each factor are analyzed. The results indicate that Taiwan's industrial growth and carbon emissions experienced a negative decoupling from 2007 to 2009 and a decoupling from 2009 to 2013. Energy intensity effect plays the dominant role in promoting decoupling, and both energy structure effect and industrial structure effect negatively impact decoupling. The chemical materials , electrical and electronic machinery and basic metal industries sub-sectors are primarily responsible for the energy intensity effect. Energy-intensive industries are the main contributors to the increase in energy structure and industrial structure effects. The study suggests that the Taiwanese government should establish targeted carbon reduction measures at sub-sector level. Adjusting the energy structure and industrial structure is also urgently required to promote the decoupling of carbon emissions from industrial growth. [ABSTRACT FROM AUTHOR]

The market-oriented reforms boost economic take-off in China, but the lag of the factor market still leads to many disadvantages where the factor market distortion is a stylized fact. There is rarely direct evidence showing whether market-oriented reform can spur industrial green development (IGD) although the industrial sector is the main battlefield of market-oriented reform. Herein this study integrates labor, capital, and energy into a unified research framework and investigates the impact of market-oriented reforms in different fields on IGD from the perspective of factor market distortion. The results from China's 30 provinces show that the distortions in the capital market and energy market play a significantly negative role in IGD while the impact of labor market distortion on IGD is not statistically significant. Further calculation shows that the growth potential of the national IGD level is 10.117% and 2.291% per year under the ideal condition of eliminating the market distortions of capital and energy, and the growth potential in central and western China is greater than that in eastern China. It is encouraging that increasing investment in R&D and pollution control will weaken the inhibitory effect. Of note, the inhibition effects are significantly heterogeneous and asymmetric across quantiles where capital market distortion shows a relatively weaker inhibitory effect in areas already in the late stage of industrialization. However, an interesting finding is that the negative effect of energy market distortion is the weakest in areas in the mid-industrialization stage, where government regulation should not be completely abandoned. The findings help shed important insights into the ongoing debate regarding the role of market-oriented reform in the high-quality development of the industrial sector in emerging economies. • Investigate the impact of market-oriented reforms on IGD. • The market distortions in capital and energy play a negative role in IGD. • The negative role show heterogeneity across quantiles. • Investment in R&D and pollution abatement play a negative regulatory role. • The loss gap of IGD level is further calculated. [ABSTRACT FROM AUTHOR]

Renewable energy is one of the key clean production pathways to achieve the global energy transition and combat climate change. This research is aimed to investigate the impact of changes in social structure, economic structure, demographic structure, and trade structure on per capita renewable energy consumption. Four threshold panel regression models are developed using the updated data of 116 countries. In these models, social structure, economic structure, demographic structure, and trade structure are set as both explanatory variables and threshold variables, whereas per capita renewable energy consumption is set as the explained variable. These models verify the existence of the threshold (1% confidence level), which indicates that there is a non-linear relationship between social-, economic-, demographic- and trade-structure changes and renewable energy consumption. Changes in the social structure (urbanization level) promote per capita renewable energy consumption, and when it crosses the threshold, this promotion effect become more significant. Changes in the economic structure (industrialization level) inhibits the growth of per capita renewable energy consumption. However, as industrialization level rises above the threshold, this inhibition is weakening. Changes in the demographic structure (population aging) and trade structure (trade openness) contributes to the growth of per capita renewable energy consumption. Moreover, after the demographic structure and trade structure cross the threshold value, this promotion strengthened. The above findings provide theoretical support for policymakers to formulate energy and population policies. [Display omitted] • Explanatory variables are also threshold variables in these four panel threshold models. • Social structural change (urbanization level) contributes to renewable energy consumption. • The early stage of industrialization is not conducive to the development of renewable energy. • Aging of population contributes renewable energy consumption. • Free trade benefits to the renewable energy development. [ABSTRACT FROM AUTHOR]

A cursory look at South Africa's energy data reveals that, energy intensity has consistently declined for the past two decades. The logical question that ensues is; what might have contributed to this phenomenon? The current study aims to investigate how different phenomena have contributed to the decline in South Africa's energy intensity. The study also tests for structural effects in the model parameters. The result showed that the de-industrialisation since 1980 and the changes in trade structure in favour of more imports have contributed significantly to the decline in energy intensity, in South Africa. Also, the current industry composition has induced technological transfer via FDI (Foreign direct inflows) and this has contributed to the decline in energy intensity levels, in South Africa. The individual effect analyses showed that each of the predictors shared significant amount of variance with the regression effect. Finally, there are significant structural effects in the parameters, and this has rendered the effects of regressors asymmetric. [ABSTRACT FROM AUTHOR]

Energy efficiency and renewable energy are considered to be two indispensable solutions to control GHG (greenhouse gas) emissions. Moreover, industrialization is at the center of discussions on the roles of countries to reduce CO 2 emissions. However, the literature is underprovided to understand the long run contribution of energy efficiency, renewable energy and industrial composition in reducing GHG emissions at the macro level. In this study, we differentiate the effects of economic activity, energy efficiency, economic structure and use of renewable energy resources on CO 2 emissions. We develop energy efficiency indices for thirty six countries for the period of 1971–2009 and use a CCE (common correlated effects) estimator model that is consistent under heterogeneity and cross-sectional dependence. We find a positive significant effect of energy efficiency on CO 2 emissions in the long-run. Similarly, substituting renewable energy for non-renewable energy reduces CO 2 emissions in the long-run. Our results ensure widely discussed roles of energy efficiency and renewable energy in curbing CO 2 emissions. Furthermore, the scale of economic activity measured by real income and industrialization have significant positive effect on CO 2 emissions. [ABSTRACT FROM AUTHOR]

Increasing economic activities and rapid demographic changes in a number of African countries may have consequential effects on environmental quality. In this paper, a multi-region input–output modeling framework is used to show that except Egypt, Nigeria, Tunisia, South Africa, Zimbabwe and the Rest of North Africa, all other African countries/regions are net-importers of embodied emissions. With respect to the emission-intensive and trade exposed sectors, however, only Egypt, Mozambique, South Africa and Zimbabwe are rather net-exporters of embodied emissions. Secondly, panel regression techniques that allow cross-section dependence are used to investigate the determinants of CO 2 emissions in Africa. The estimated elasticities for per capita income and energy intensity are positive, statistically significant and robust for both low- and middle-income African countries. The most active segment of the labor force (percentage of the population between age 14 and 64) and industrialization exert significant positive effects on CO 2 emissions in middle income countries while the impact of urbanization, population and trade openness appears generally insignificant across income groups. The differential impacts of both economic and demographic variables on CO 2 emissions may have implications for the design and implementation of development and climate protection policies. [ABSTRACT FROM AUTHOR]

The bottleneck of China's industrial carbon efficiency improvement is that the contribution of carbon emission technology is less than that of energy technology, and that of neutral technology is less than that of capital-based technology. The key to breaking through this bottleneck is to clarify how heterogeneous technological progress enhances carbon efficiency through industrial structural upgrading. The effects of four levels of technological progress on carbon efficiency under two technical classifications based on technology sources and carbon emission processes from energy consumption are studied by using the DEA method. The suitable choice of the path of technological progress to promoting China's industrial carbon efficiency is provided accordingly. The panel data model is used to deeply investigate the effects of these four levels of technological progress on industrial carbon efficiency in China's 30 provincial industries. The main results are as follows: First, in terms of direct effects, progress in energy technology is more conducive to improving carbon efficiency than progress in carbon emission technology, and progress in neutral technology is more effective in improving carbon efficiency than progress in capital-embodied technology. Second, in terms of indirect effects, progress in capital-embodied technology is effective in upgrading industrial structures and enhancing carbon efficiency; and, through green upgrading of industrial structures, progress in energy technology has a positive and significant impact on carbon efficiency. Third, the level of industrial development and government environmental governance have a positive impact on carbon efficiency, and the energy structure has a negative impact on carbon efficiency. • Different technologies impact carbon efficiency through different paths. • NT and CET promote industrial structure grading and carbon efficiency. • Industrial structure grading promotes ET and CT progress. • Promoted by industrial structure grading promotes carbon efficiency. • ET and CT progress promotes carbon efficiency. [ABSTRACT FROM AUTHOR]

As issues concerning the environment and energy security have become extremely serious, investment in technological research and the development of China's industrial sector has been markedly increasing in an effort to control energy consumption. Energy rebound effects may offset the effects of the energy saved as a result of technological advancement. The present study assessed 30 provinces in China from 2001 to 2017 and analysed the relationship between the heterogeneous technological progress rates and energy productivity of China's industrial sector. This study also assesses the energy rebound effect of China's industrial sector using elasticity analysis. The energy rebound effect in China's industrial sector was significant. Furthermore, the energy rebound effect serves as a regional characteristic of progressive growth from the eastern, central and western regions in China. Moreover, an increasing variation with time was observed in the energy rebound effect of most provinces, indicating that China's industrial development is still ridden with the rough developmental pattern in the sample interval. Finally, according to the characteristics of the energy rebound effect of China's industrial sector, possible explanations and related policy recommendations have been provided from the perspective of energy market reforms and environmental regulations. • Technological advances in China were assessed for technological progress. • Elasticity analysis was used to measure the rebound effect of energy consumption. • Short- and long-term and regional differences were considered. • Energy conservation should be encouraged along with market-oriented reform. [ABSTRACT FROM AUTHOR]

Several trial productions of natural gas hydrate (NGH) on onshore and offshore reservoirs have been implemented, signaling the start of the stage of technology development for its industrial exploitation. Several methods for NGH exploitation have been proposed, but none of them has been verified applicable to the commercial exploitation of NGH. The applicability of a technology to NGH exploitation is subject to the evaluation of its economic potential, but unfortunately few relevant studies have been conducted. In this research, each exploitation technology for NGH is evaluated for its economic potential as referring to the break-even production rate with energy return on investment (EROI) analysis. Sensitivity analysis is also performed to specify the effect of each key factor, such as gas production rate, gas-water ratio, efficiency of thermal stimulation, injection-production ratio for the methods of chemical injection or CO 2 replacement, on the standard EROI. The results obtained indicate that depressurization is the most promising method, because on it the lowest critical production rate would be required for commercial exploitation of NGH, ranging from 0.16 to 0.25 million m3/day/well. Comparing with other unconventional oil and gas, the commercial exploitation of NGH still relies on further technological breakthroughs, especially those for the improvement of production rate. [Display omitted] • Economic evaluation of hydrate exploitation technology is conducted on EROI. • The break-even production rate of each production technology is estimated. • Sensitivity analyses of the key factors on standard EROI are carried out. • Depressurization is most promising for the exploitation of natural gas hydrate. • The EROI of hydrate exploitation is compared with other energy resources. [ABSTRACT FROM AUTHOR]

This paper contributes insights on differences in observed rates of substitution for fossil fuels across countries as measured by changes in the energy mix. If some countries are relatively slower in substituting for fossil fuels, climate change will be addressed less successfully. This paper specifically investigates the role of industrialisation and state-related institutions in the speed of energy substitution in 19 European countries from years 2011–2018 using panel data econometric methods, and has three main results. This paper finds evidence that (1) higher industrialisation levels in the economy increase the speed of energy substitution; (2) that changes in industrialisation levels, not the levels themselves, decrease the speed of energy substitution, but state-related institutions in support of green energy policy weaken this effect; and that (3) higher degrees of state control of the electricity sector slows down energy substitution, but state-related institutions in support of green energy policy likewise weaken this effect. These findings imply that higher industrialisation levels require more energy in absolute terms, implying greater energy portfolio diversification in order to satisfy such energy demand, and that a faster energy substitution can result from a more liberalised electricity sector. • A study on 19 European countries from years 2011–2018 using panel data. • Changes in industrialisation levels decelerates energy substitution. • More state control of the electricity sector decelerates energy substitution. • State-related institutions supporting green energy policies weaken these effects. • Higher industrialisation levels themselves however accelerate energy substitution. [ABSTRACT FROM AUTHOR]

As an effective means to alleviate the contradiction between energy and economy, industrial restructuring has gradually received widespread international attention. A two-stage optimization method is constructed from evaluation index system to multi-objective optimization model by taking industrial structure adjustment as the research object. In order that the adjustment of industrial structure is closer to the actual situation, an adjustment-rate-based multi-objective optimization model is also proposed by introducing an objective of minimum adjustment of industrial structure. China is selected as our case study. Results show that the 9.57 % of industrial adjustment, will lead to the increase of economic objective by 6.66 %, and the decrease of energy consumption by 5.36 %, which meets China's current high-quality development requirements. Meanwhile, a grouping proposal is established for each sector based on the range of industrial scale adjustment in comprehensive preference. By comparing the optimization effect of different groups of sectors after energy efficiency improvement, the priority of energy efficiency improvement was identified. In addition, the uncertainty of slack variable is discussed to ensure the accuracy of the model, and conclude that the Chinese government should improve the diversity of energy import. The above conclusions can provide useful references for the development of industrial restructuring plans. [Display omitted] • EIS provides qualitative judgment for constraints setting. • ARMOM is proposed for more efficient industrial adjustment. • All sectors are classified based on the adjustment range. • Decreasing the energy intensity of DP has the best effect. • Effects of uncertainty in the slack variable are discussed. [ABSTRACT FROM AUTHOR]

The importance of manufacturing as a main determinant of economic growth has been explored extensively in the literature considering manufacturing as the engine of economic growth. In our study, a new database covering 117 countries for 1995–2017 containing four indicators, namely manufacturing value added share in GDP, growth of GDP, manufacturing energy intensity, and UNIDO's Competitive Industrial Performance score is constructed. Relying on this dataset and the Granger causality tests the paper investigates the effect of economic growth, energy intensity and the competitiveness index on manufacturing value added. Applying adequate econometric methods the effect of this set of variables on the relative importance of manufacturing in the economy as a whole measured by the share of MVA in GDP (MVAsh) is analyzed. An inverted U shape is verified with different turning points between static and dynamic analyses in the full sample, as well as in industrialized countries and emerging and developing countries separately, with turning points all within samples. Energy intensity has negative effect in most of the cases while CIP has positive effect with high magnitudes. The rate of adjustment is high. • We estimate the adjustment rate and main indicators effect on manufacturing sector. • Static and dynamic panel specifications are proposed modelling MVA share and growth. • We explore energy intensity effect on selected indicators of industrial development. • We use for first time in such specifications manufacturing energy intensity. • UNIDO's Competitive Industrial Performance score is used for the first time. [ABSTRACT FROM AUTHOR]

The inconsistency of growth rate in industrial and its electricity consumption in China has attracted the global attention. This study uses a novel quantile-on-quantile approach to reveal the complicated and seemly inconsistent relationship between China's industrial growth and its electricity consumption from 1995 to 2017. Empirical results show: (1) generally, a positive correlation exists between industrial growth and its electricity consumption. However, the strength of that correlation depends highly on the level of industrial electricity consumption and industrial development, thereby causing variations in the relationships at different periods and regions. (2) During the middle period of industrialization, a strong relationship is observed. Then, it gradually weakened with the steady growth of industry and high electricity consumption. (3) From a regional perspective, the positive correlation in eastern China changed from strong to weak, while a "high-low-high" trend transpired in northeastern China. The relationship was stable in central China during the sample period. (4) The main reason for the above results is the different characteristics of the industrial transfer and industrial structure upgrading across regions. • Industrial growth positively correlated with electricity consumption. • The strength of that correlation depends highly on the level of industrialization. • The correlation is heterogeneous across regions. • Industrial transfer and industrial structure upgrading paly an important role. [ABSTRACT FROM AUTHOR]

This study investigates the determinants of the energy consumption by integrating the influence of shadow economy through the STIRPAT framework for 115 economies over the period 1991–2014. We apply the system-GMM estimations for our dynamic panel data to examine the determinants of the energy consumption under three aspects: the level, the intensity, and the sustainability (renewable energy). The major contribution of this article is to use the STIRPAT framework to provide a holistic analysis of the determinants of the energy consumption. In this context, our key contribution is to study the influence of shadow economy on the level of energy through the lens of several common drivers of energy consumption (including income level, urbanization, industrialization in line with recent uncovered factors as trade openness and FDI) that we recruit as explanatory variables. Our main explanatory variable is the ratio of shadow economy to GDP collecting from recent study of Medina and Schneider (2018). The combined analysis of the effect of shadow economy and the drivers of energy offer significant contributions to the existing literature. Our global sample shows that a higher informal sector induces a higher level, a higher intensity, and a higher renewable energy use. A major contribution of our article is to identify a significant difference in the nature of informal sectors and its relationships with official sectors, energy consumption and environmental quality across the income levels. Our holistic study in the STIRPAT framework allows us to identify additional interesting findings related to the determinants of the energy consumption and to provide some key recommendations to policy-makers on this matter. • A higher informal economy induces a higher level, intensity and renewable energy use. • Urbanization surprisingly reduces the level and intensity of energy use. • It suggested to combine environmental policy with measures to reduce shadow economy. [ABSTRACT FROM AUTHOR]

To improve the ecological efficiency (eco-efficiency) of industrial production and promote its sustainable development, we present a data-driven method for evaluating and optimizing the eco-efficiency of industrial production system. The data of industrial production system are collected and processed in a unified dimension from the perspective of emergy, then the eco-efficiency evaluation model of industrial production system is constructed to realize the quantitative evaluation, the correlation between various factors and eco-efficiency is analysed, and a date driven eco-efficiency optimization decision is built to improve eco-efficiency and production benefits in industrial production. In the application to an example in a manufacturing enterprise, the method identifies opportunity for reducing resource consumption by 8.3% and waste discharge by 6.7%, enhancing the eco-efficiency by 13.8% and production benefit by 8.1%. This paper provides theoretical and methodological support for the evaluation and optimization of eco-efficiency of industrial production system, and also provides theoretical basis for the sustainable development of industrial production. • Ecological efficiency of industrial production considering the economic, social and environmental benefits. • Constructing a data-driven eco-efficiency model of industrial production system. • Analysing various factors related to the eco-efficiency. • Illustrating the measurable, evaluable and optimized eco-efficiency mechanism of industrial production system. [ABSTRACT FROM AUTHOR]

We diagnose CO 2 emission changes and determine the driving mechanisms and spatial spillover effect worldwide using spatial econometric techniques embedded within energy trade in the period 2000–2014. We focus on fossil fuel import, taking it as the medium through which to examine the spatial spillover effect on CO 2 emissions, and compare the spatial influence between developed and developing countries. We propose different hypotheses considering the magnitude of spatial influence through fossil fuel trade between developed countries, between developing countries, and between developed and developing countries. These hypotheses are manifested in the multiple spatial econometric model. Results revealed general heterogeneity of CO 2 emissions among different countries alongside fluctuations and wavy increments in the analyzed groups of countries. However, the convergence of emissions was predictable because the growth rate of CO 2 emissions was low in countries with high levels of CO 2 emission and converged rapidly with that of developed countries. The spatial autocorrelation phenomenon and spatial spillover effects generated from energy trade have previously only been verified worldwide rather than solely in developed countries or developing countries. Urbanization, industrial development, deforestation and GDP growth all drive the increase in CO 2 emissions whereas renewable energy options can help to mitigate emission increases. • We embed fossil fuel trade into the spatial relations to identify the spatial effect. • We differentiate the spatial relations among the developed and developing countries. • Fossil fuel trade helps to generate spatial interactions in global CO 2 emission. • Developed countries play an influential role in the spatial relations. [ABSTRACT FROM AUTHOR]