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Since General Secretary Xi Jinping pledged the "30·60" targets to the world, the importance of pollution reduction and carbon reduction has become increasingly prominent. The previous focus on the pollution reduction effects of emission trading systems, while overlooking their carbon reduction impacts, as well as the limitations of research methods and scope, is no longer suitable for the needs of the new era. Therefore, this paper constructs a CGE model to study the synergistic effects, simulating the synergistic emission reduction effects of sulfur dioxide emission trading policies, and comes to the following conclusions: After the implementation of the sulfur dioxide emission trading mechanism, under different sulfur price scenarios, the synergistic reduction amounts of SO 2 and CO 2 vary greatly. As the sulfur price increases, the reduction amount becomes larger. In the five sulfur price scenarios set in this paper, the maximum reduction of SO 2 can reach about 111,400 tons, and the maximum for CO 2 is about 399 million tons. The CO 2 reduction rate is approximately 1.0767 times that of SO 2. This indicates that the sulfur dioxide emission trading policy is a very effective path for synergistic pollution and carbon reduction, with good reduction effects. In addition, sulfur dioxide emission trading will reduce the consumption of fossil energy, decrease industry output, raise product prices, cause GDP loss, and lead to reduced social welfare to varying degrees. [ABSTRACT FROM AUTHOR]

The OECD community consumes excessive amounts of raw materials and materials, which leads to pollution and increases the material footprint. The material footprint is directly linked to the Sustainable Development Goals (SDGs)-8 and 12. The main reason for the material footprint is the usage of fossil fuels, and the dependence of OECD countries on fossil fuels continues to this day. By expanding renewable energy utilization due to rising energy security risk, a community can take steps to improve ecological quality and reduce its material footprint. In this context, the paper focuses to examine the impact of energy security, green innovation, economic policy stringency and income on the fossil fuel material footprint for 24 OECD countries over the period 1995–2018. To this end, the paper uses the Augmented Mean Group (AMG) method and novel Half Panel Jackknife (HPJ) causality and estimation approach. The study adds value to existing knowledge by empirically testing the determinants of fossil fuel material footprint for OECD countries for the first time using the novel HPJ approach. The results of the AMG show that increasing energy security risk index reduces the material footprint, while green innovation and economic policy stringency have no impact on environmental degradation. The environmental Kuznets curve (EKC) in the form of an inverted U and an inverted N are valid for OECD countries. The HPJ approach also illustrates that there is a causality from green innovation and energy security risk to material footprint, and innovation and risk are support footprint reduction. Based on these results, the study recommends that OECD policymakers pay attention to ensuring energy security to reduce the material footprint by expanding renewable resources and allocate more economic resources to green innovations with higher returns, considering the validity of the EKC. [Display omitted] • Applies second-generation panel data methods. • Investigates the fossil fuel material footprint for 24 OECD countries. • The EKC hypothesis holds for the fossil fuel material footprint of OECD countries. • Green innovation and energy security risk reduce fossil fuel material footprint. • Increasing risks and technological development contribute to SDGs 8 and 12. [ABSTRACT FROM AUTHOR]

Most economists focus on how a market system determines the consumption of resources, but the Chinese government controls its energy demand and succeeds to save energy. It is intriguing to ask about how the Chinese government reduces firms' (fossil) fuel consumption. To the best of our knowledge, this paper contributes by offering a first attempt to show how government intervention determines a firm's fuel-saving incentive. With evidence from China, this paper first documents that a firm's fuel intensity significantly constrains its profitability. In particular, the constraint effect is robust to potential endogeneity bias. Moreover, we confirm that the constraint effect of fuel intensity on profitability is larger for firms when the burden, intensity or capacity of a local government to intervene for ambient air quality is great than when the interventional burden, intensity or capacity is small. Thus, these findings offer application for fuel-saving intervention in a developing country. [ABSTRACT FROM AUTHOR]

This paper presents the outcome of an extensive research that ultimately proposes a dynamic quasi comprehensive model to assess the carbon footprint of fossil fuel electrical energy. The key parameters and their respective effects have been fully considered. Such key parameters include plant type, fuel type, fuel transportation, emissions for fuel extraction and processing, within-facility power consumption at the power plant, degradation rate, site ambient conditions, and losses related to transmission and distribution. The proposed model has two significant features. The first feature considers a framework that generates a dynamic model. The time span in the dynamic framework is flexible and can vary from 1 s to the entire functional life of a power plant. The second feature of the model (representing its comprehensiveness) considers the aforementioned nine key parameters, holistically and simultaneously. Applying the proposed model across a wide range of circumstances leads to the estimation of the quantitative effect of each parameter. This shows the priority of order that the parameters should be given when designing a low-emission fossil-fuel power plant. Among the different standard cases of plant designs discussed in this paper, combined-cycle power plants running on natural gas have the minimum carbon footprint. Hence, the power plant and fuel types have the greatest effect on carbon footprint per unit of generated electrical power. Moreover, other mentioned parameters demonstrate significant effect on the results in this research work. The variation of parameters from least to most can result in a four-fold increase in carbon footprint. [ABSTRACT FROM AUTHOR]

Excessive energy consumption and carbon dioxide emissions are long lasting issues and need continuous research to improve efficiency evaluation and performance monitoring of economies. The static and dynamic aspects of efficiency need to be dealt with simultaneously to thoroughly analyze the performance of economies. This paper aims at conducting a static and dynamic analysis of energy and CO 2 emissions efficiency of major economies. In this paper, we applied slacks based model of Tone (2001) with the treatment of undesirable output in objective function and constraint assuming free disposability of undesirable output and built a dashboard. The results can be summarized by saying that the larger economies with intensive production strategy, larger secondary industry, and weaker carbon tax laws are more likely to be inefficient. China, India, and Russia have the greatest potential for improvement in both energy efficiency and carbon dioxide emissions efficiency. The suggested dashboard has the ability to dig out the potential for efficiency improvement of countries like the USA, which mostly appear at the efficient frontier with other techniques. Concluding it can be suggested that economies in lower ranks of dashboard need stricter policy measures to cut energy consumption, carbon dioxide emissions and encourage a shift from fossil fuels to other renewable resources of energy. [ABSTRACT FROM AUTHOR]

This study aims to elucidate the profound implications of industrial transformation and upgrading in mitigating dependence on fossil fuels, which holds paramount significance in shaping energy transition strategies—an aspect that is currently missing in existing studies. Leveraging data spanning from 2000 to 2020, encompassing fossil energy consumption and economic development, this paper developed a second-order classification model as a new measure of energy elasticity. Comparing regional variations in fossil energy resilience, an in-depth analysis was conducted on four representative provinces to understand the evolution of their fossil energy consumption structures over time. Correlation analysis was employed to reveal the impact of industrial structures on the reduction of fossil energy dependence. The results indicate distinct spatial variations in the energy transition effect, with the southwest inland region retaining a pronounced reliance on fossil energy sources. However, approximately 80% of the provinces have made substantial progress in reducing fossil energy dependence from 2000 to 2020. Notably, the financial sector and the accommodation and catering industry contribute positively to mitigating fossil energy dependence, while the industrial sector exhibits the opposite effect. Urban agglomeration planning attributes the uneven regional energy transition to the delineation of urban industrial functions. Suggestions for narrowing the energy transition gap include measuring the sustainability of the industrial chain from a life-cycle perspective, avoiding the singular functional division of cities, and developing systematic policies. In the catering industry, adopting alternative cooking energy and implementing the conversion and recycling of catering waste can help prevent risks. This study underscores the positive role of the accommodation and catering industry in the energy transition, along with its potential risks. The study also makes efforts toward advancing the application of the widely used energy elasticity assessment method. [Display omitted] • A second-order classification model is developed as a widely used energy elasticity assessment method. • 80% of China's provinces have successfully reduced their reliance on fossil fuels. • The financial sector and the accommodation and catering sector play pivotal roles in diminishing reliance on fossil fuels. • In the forthcoming years, the catering industry has the potential to engender a reliance on fossil fuels. [ABSTRACT FROM AUTHOR]

This research investigates the relationship between greenhouse gas (GHG) emissions and energy production and consumption patterns in 122 countries over the period from 1990 to 2020. Particular attention is paid to the role of different types of energy, including renewable, hydro and nuclear energy, as well as oil, gas and coal, in shaping GHG emissions. Unlike previous studies, the paper analyzes the full range of energy resources and focuses on different quantiles of data using the quantile-quantile regression (QQR) method. The results of this approach are compared with traditional quantile regression (QR) to assess its validity. Among the findings of this study are: (1) different parts of the energy mix have a heterogeneous impact on GHG emissions in different quantiles; (2) energy consumption patterns play a more significant role in shaping GHG emissions than production patterns; (3) increasing production and consumption of fossil fuels does not necessarily increase GHG emissions; (4) similarly, the development of renewable energy sources is not always accompanied by a reduction in GHG emissions. Our general conclusion is that existing climate policy requires significant diversification to not be focused only on renewable energy, which impact on GHG emissions is not as homogeneous as it usually considered, and which cannot solve the problem of raising emissions solely. Instead of this, it could be more rational to focus on the searching the ways of hydrocarbon industries sustainable development and support them in this journey, especially in the field of Scope 2 and Scope 3 operations management. • Impact of energy consumption and production on GHG emissions were analyzed for 122 countries in 1990–2020. • Quantile and Quantile-on-Quantile regression were used to catch the specifics of energy consumption and production patterns. • Two temporal breakpoints (1999/2000 and 2009/2010) were introduced to catch shifts in variables dependencies. • The influence of fossil fuels on GHG emissions is not homogeneous as it usually considered, the same is fare for renewables. • A promising option to reduce GHG emissions is carbon capture, utilization and storage (CCUS). [ABSTRACT FROM AUTHOR]

The fossil energy and the carbon market are closely connected, but few articles have applied the Granger causality method on quantiles to explore the bi-directional causality between carbon prices and fossil fuels. Most articles use conditional mean regression models to test linear Granger causality, but are unable to assess tail causality or nonlinear causality. In order to accomplish the objective of studying the interaction of carbon and fossil energy markets at different quartiles, we use the method of Granger causality at quartiles, which allows us to assess median and tail causality and to gain insights into how carbon and traditional fossil energy markets interact under different market conditions. This paper analyzes the causal relationships between carbon prices and coal, oil, and gas from June 1, 2015 to October 31, 2022 across all quantiles. We find no indication of Granger-causality from carbon to oil and gas at the middle quantile. However, at the lower and upper quantiles, we discover the causal relationship between changes in carbon prices and traditional energy prices. The asymmetric two-way causal relationship between the carbon market and the fossil energy market has prompted the government to carry out differentiated management, as well as to improve energy efficiency. • We study the bi-causality between coal, oil, gas markets and carbon market. • We test for Granger-causality for each quantile of the distribution. • The negative correlation between carbon prices and fossil energy prices under mean reversion analysis is unreliable. • The impact of carbon taxes on oil prices varies widely across different quantiles. • We make demands on governments to develop energy policies. [ABSTRACT FROM AUTHOR]

Abstract: The belief that it is possible to have a perpetual “economic growth” based on fossil energy has been challenged since the 1970s. However, only in the last decade is this issue re-emerging once again because of the predicaments of climate change and peak oil. Many, finally start to perceive that an “economic degrowth” entailing a downscaling of the current size and pattern of socio-economic systems seem unavoidable. In this paper we analyze the implications, the feasibility and the desirability of possible trajectories of downscaling from an energetic perspective. The quantitative analysis is based on the methodological approach of societal metabolism, and it provides a dynamic accounting of the profile of energy flows required and consumed by societies in relation the expression of a given set of societal functions. This analysis makes it possible to check two types of constraints: external constraints (supply and sink side limits for the whole) and internal constraints (the feasibility of energy budget of the various parts of the society expressing the required functions). The analysis of the metabolic pattern of a sample of developed countries is used to discuss possible implications of: (i) demographic changes; (ii) the declining supply of net energy sources, and (iii) the effects of the Jevons'' Paradox. Within such an analysis, a few assumptions and recipes of the degrowth movement seem problematic: (i) population is and will remain as a relevant variable to be considered; (ii) the proposed reduction in working hours seem to be impractical unless a major catastrophe will reset current civilization to pre-industrial standards; and (iii) voluntary reduction of personal energy consumption, even if a welcome adjustment, alone will not solve the existing problems. In the final part of the paper, future energetic road maps are questioned within the realm of post-normal science. Can we “plan” degrowth? If we are serious about the need of doing “something completely different”, societies will have to learn how to deliberate under uncertainty within the realms of flexible management and stop planning for either growth or degrowth. Moreover, before suggesting policies, it would be wise first to try to understand the option space. [Copyright &y& Elsevier]

Despite the positive momentum achieved by the renewable energy sector in recent years, there are substantial challenges that need the attention of the global community, and one of the more pressing issues is dealing with the deleterious external costs of power generation. One of the parameters to compare costs of energy across various technologies is levelised cost of energy (LCOE), but it has been conventional practice to neglect the external costs in estimating the LCOE of power generation technologies. Furthermore, as LCOE is a critical indicator for policy and decision makers, there is a need to juxtapose actual costs of renewable and conventional power generation technologies. This research paper attempts to internalise some of these external and GHG emission costs across various power generation and storage technologies in all the G20 countries, as they account for 85% of global power consumption. As future investment decisions are largely influenced by costs, estimates in this research prove renewables and storage to be far cheaper than fossil and nuclear sources by 2030, even without considering external costs. The myth that renewables are ‘way too expensive’ has been debunked repeatedly, and the cost decline of wind and solar photovoltaic (PV) technologies have outpaced most industry expectations. The results of this research not only substantiate this trend, but also statistically display that all the G20 countries have the opportunity to decrease their energy costs significantly, between now and 2030. Renewable energy technologies offer the lowest LCOE ranges across G20 countries in 2030. Utility-scale solar PV generally shows the lowest values ranging from 16 to 117 €/MWh el and onshore wind LCOE range is from 16 to 90 €/MWh el . Rooftop solar PV generally offers the next lowest LCOE ranging from 31 to 126 €/MWh el , followed by LCOE of offshore wind power ranging from 64 to 135 €/MWh el . Solar PV and battery systems are highly competitive on an LCOE basis at utility-scale ranging from 21 to 165 €/MWh el and at residential scale from 40 to 204 €/MWh el . The G20, as well as other countries, can continue to develop their economies in a sustainable manner, along with substantial co-benefits in adjacent policy fields such as higher national welfare, better health of citizens, lower respective health costs and improved energy security. [ABSTRACT FROM AUTHOR]

Reliable energy statistics serve as the foundation and starting point for understanding the climate policies of any country. As the most comprehensive sources of energy data for China, China Energy Statistics Yearbooks (ESY), published by the National Bureau of Statistics (NBS), underwent three major revisions since 2005. This paper analyzes how these three major revisions correspond to data on China's energy use from 1996 to 2012, and theirs impacts on CO 2 emissions, emission intensity and the share of non-fossil energy in total energy consumption, which are key indicators of China's climate policies. Some notable changes include CO 2 emissions for 2012, which increased by 594 Million tons – a figure equivalent to South Korea's annual emissions, which implies that China's emissions at peak level will be higher than previous estimation. Meanwhile, revised emission intensity data show a higher amount and lower decreasing rate, which means that China's achievements in decreasing emission intensity during 2005–2012 have been overestimated, while future difficulties for achieving the goal of 40–45% reduction will be greater. On the share of non-fossil fuel energy in China's total energy mix, the adjustments increased the indicator by 1.26%, reflecting the fact that China's effort in developing non-fossil energy had been underestimated. Discrepancies in reported scattered coal in different statistics versions are the main contributors to these changes. To further enhance the reliability of its energy statistics, and thereby its climate policies, China should remove incentives for misreporting through legal means, and make the technical system for data collection more comprehensive and accurate, with particular emphasis on scattered coal. [ABSTRACT FROM AUTHOR]

The reduction of CO 2 by moving from fossil to renewable energy sources is currently high on the agenda of many governments. Simultaneously these governments are also forcing the reduction of energy consumption. The primary focus of these agendas is on mobility, building, and industrial sectors. For the latter, energy-efficient shop floors and machining processes assist the reduction of energy consumption. Previous research has focused on energy-efficient machining strategies during machining processes. However, an energy-efficient start-up of these machines or their spindle axis start-up has been neglected until now. This paper focuses on this neglected issue by comparing the energy-efficiency, production time, and cost-efficiency of the CNC (computer numeric control) machine by varying the power input at the spindle axis. This is done by analysing the high-frequency data (500 H z) of the machine from machining operations that is retrieved via the edge device. Concepts of data analytics and especially EDA (exploratory data analytics) were used to interactively visualize the inter-dependencies and develop results. It is shown that optimized reduction of spindle power input value leads to both: peak power smoothing from 20kW to 10kW and lowering of overall energy consumption by approximately 1.4%. Moreover, the costs and production time are marginally affected (0.518% and 0.523% respectively) by this optimized reduction of spindle power input value. Thus, this paper highlights a novel method from data acquisition to process improvement towards energy-efficient and sustainable machining. [Display omitted] • Energy-efficient machining via innovative technique of data acquisition and analysis. • Sustainable peak smoothing for spindle operations. • Utilization of high-frequency machine data for enhancement of process. [ABSTRACT FROM AUTHOR]

Climate change, environmental problems and consequent ecological damages due to excessive consumption of resources and to the continuing human population growth of more than 80,000,000 net increase per year, have damaged and continue to accelerate the devastation of numerous ecosystems. These changes have brought significant harm to humans and are imposing high costs on societal maintenance and development. In that context, low/no-fossil carbon transformations and improved material’s and energy efficiency are crucial elements for reconciling human activities with sustainable societal development, which is built upon vibrant and sustainable ecosystems. The urgently needed changes are bound to be difficult to make due to the perceived contradictions between low/no-fossil-carbon systems and sustainable and economically vibrant societies. This Special Volume (SV) is comprised of thirty-three articles, which mainly focus on investigations of low/no-fossil carbon transformations in countries, regions, industries and enterprises. Some authors provided insights of ways to proceed based upon new research and development (R&D), evaluations of specific low/no-fossil carbon technologies and lessons learned from policy simulations and analyses of potential post-fossil carbon societies. This SV introductory article contains an overview of the content of the articles divided into five topics: (a) low/no-fossil carbon transformations within industrial sectors, (b) regional planning and low/no-fossil carbon developments, (c) multi-regional, low/no-fossil carbon economies, (d) specific low-fossil carbon technologies, and (e) low/no-fossil carbon policy results. Given the extensive coverage of low/no-fossil carbon transformations, the papers on mechanisms and pathways are clearly the most important contributions of this SV. The researchers focused broadly on ways to address two objectives: (a) To characterize the main factors catalyzing high-fossil carbon development and (b) To accelerate the transition to low/no fossil carbon societies. Some authors focused upon new, low/no-fossil carbon development and planning in different countries and regions, while others focused upon ways to make changes within energy-intensive industries. Additionally, some authors reported on progress in the evaluation of the effectiveness of specific low/no-fossil-carbon technologies and in the design and implementation of low/no-fossil carbon policies. The findings and recommendations of the authors are positive and encouraging. However, it is clear, that there are many additional research, policy and educational challenges, which must be solved, to establish and support systems to guide and to monitor the transformations to sustainable, equitable, livable, low/post-fossil carbon societies. Much work remains but the wisdom in the articles in this SV will help societies make the needed transitions. [ABSTRACT FROM AUTHOR]

The construction sector contributes to 8% of carbon dioxide emissions, most of them caused by clinker production: in recent years, the efforts to reduce environmental impacts are growing. This paper investigates the environmental performances of clinker production and the factors driving emissions. For this purpose, the environmental impacts of 41 different grey clinkers produced in Italy from 2016 to 2021 certified by a third party according to the European standard EN 15804 have been assessed. Three input datasets (i.e., energy consumption, raw materials, and transport) have been investigated to identify the most significant variables that affected the environmental impact categories in the period 2016–2020: a stepwise regression allowed the identification of the optimal predictors to be included in the multiple regression models. The most significant variables are pet coke, fossil fuels, natural raw materials, and lorry transport. The identified models have been validated having regard to 2021 data. Therefore, for each impact category, multiple positive and negative dependencies which bear an effect on the environmental results have been quantified. The output provides proven quantitative results that can support cement producers to develop low-impacting clinker recipes. [ABSTRACT FROM AUTHOR]

Strengthening the implementation of environmental regulation is one of the key measures to prevent further energy depletion and environmental deterioration. This paper focuses on complicated relation between environmental regulation and fossil energy consumption. We theoretically identified the direct and indirect paths of environmental regulation that affect fossil energy consumption and analyzed the relationship between the two. To identify the indirect impact of environmental regulation on fossil energy consumption, we incorporated three types of technology (e.g., production technology, pollution abatement technology, and backstop technology) into our model. On the theoretical basis, we then evaluated the impact of environmental regulation on fossil energy consumption in China by applying both non-spatial models and spatial econometric models. In the direct path, energy-saving effect of environmental regulation in China is dynamic and yields complex results from the “Green Paradox” and “compliance cost”. As for indirect effects, we find that current environmental regulations have promoted technological progress in production to induce energy savings but failed to drive technological advancements in pollution abatement and backstop to guarantee a sustainable energy development. Based on the findings, some corresponding policy implications are provided. [ABSTRACT FROM AUTHOR]

Much theoretical and empirical research has verified the non-linear and uncertain relationships between carbon emissions and economic growth. To forecast the carbon emissions from fossil energy consumption, this paper introduces the power exponential term of the relevant variables as exogenous variables into a multivariable grey model. Under the target of minimisation of the mean absolute percentage error, two non-linear programming models are constructed to solve the unknown parameters of the non-linear grey multivariable model. In addition, to enhance the adaptability of the grey model to large sample sizes, we divide the data of Chinese gross domestic product and carbon emissions from fossil energy consumption of 1953–2013 into 15 stages. The empirical results show that the non-linear grey multivariable model can reflect the mechanism of the non-linear effects of gross domestic product on carbon emissions from fossil energy consumption, and has higher forecast accuracy than the traditional grey model and the autoregressive integrated moving average models. In three schemes – economic growth at low, medium, and high, speeds – we use the non-linear grey model to quantify future Chinese carbon emissions from fossil energy consumption from 2014 to 2020, and the predicted results can provide the basis for energy planning and the formulation of environmental policy. [ABSTRACT FROM AUTHOR]

It is clear that an increase in gases, due to fossil energy consumption, in the atmosphere has been causing greenhouse effect influencing the world's temperature. The effect of renewable usage, on the other hand, on global warming is not very clear. For instance, the influence of wind energy usage on Greenhouse Gas (GHG) has been a controversial research topic for the last two-three decades. Throughout some empirical analyses, some researches reached no evidence that wind can reduce global warming, as some other researches observed that the wind has proven to have a positive impact on environmental quality by lowering CO 2 emissions. This paper, on the other hand, reveals that wind usage can influence GHG positively or negatively at different time periods. By observing the monthly period 1989:1–2017:8, this paper examines the effect of wind energy usage on GHG emissions for the variables of wind energy consumption, coal consumption, natural gas consumption, other renewable energy consumption, and total energy consumption interrelated carbon dioxide (CO 2) emissions. This research launches the methodology of Morlet wavelet coherence analysis allowing a researcher to conduct the analyses of variables in both time and frequency dimensions. The research also performed Monte Carlo simulations with 1000, 2500, 5000 and 10000 replications to reach significant outputs. The paper, therefore, (a) observes whether there exists causality between the variables within the whole sample and all sub-samples together with other interrelated control variables, (b) monitors the significant causalities (co-movements) at different time frequencies, (c) hence, determines the potential influence of wind energy usage on CO 2 emissions at different time periods corresponding to different time frequencies. This paper eventually detects three significant emergent outcomes. The first outcome is that the increase in CO 2 led to enlarged use of wind energy for the periods 1999, 2001–2002, and 2015–2017. The second outcome is that wind energy consumption diminished the CO 2 emissions for the period 2015–2017. The 1st and 2nd outputs are obtained at 5% significance level. The third outcome is that the wind power turbines intensified the emissions during the periods 1991–2004 (at10% significance) and 1999–2002 (at 5% significance) in the US. This research later suggests therefore that policy makers consider the consumption of wind energy to reduce CO 2 emissions. • Observes the impact of wind energy power consumption on CO 2 emissions in the US. • Employs wavelet coherency and partial wavelet coherency analyses. • Reveals that wind power consumption contributes to CO 2 emissions for the period 1991-2005. • Yields that wind power consumption diminishes CO 2 emissions after 2015 in the US. [ABSTRACT FROM AUTHOR]

Since the combustion of fossil fuel became the largest contributing factor of greenhouse gas emissions in China, the growth of energy consumption caused by urbanization has led to significant increase in carbon emissions. Applying both the carbon-emissions-coefficient and the sector-energy-consumption method, we predicted the energy consumption and carbon emissions, explored the characteristics of energy consumption and carbon emissions in different urbanization stages, and analyzed the energy crisis in Shandong which is a typical province in China. The results indicate that in 2015 and 2020, the total primary energy consumption will be 1.57 times and 1.85 times higher than that of in 2009, and the carbon emissions are estimated to be 1.48 times and 1.67 times respectively. The urbanization has distinct positive effects on energy consumption and carbon emissions, and the influence is more obvious in the intermediate-stage than in the early-stage. From a policy perspective, this paper could provide valuable information for planners and decision makers to formulate feasible and practical polices with a view to optimize energy structure and mitigate carbon emissions. [ABSTRACT FROM AUTHOR]

All economies need energy for growth, particularly emerging ones with continued demand for fossil fuels that move them to unconventional energy sources such as heavy oil. However, the presence of large quantities of heteroatoms -sulfur, nitrogen, oxygen, and metals – in heavy oil is a major contributor to environmental pollution during the combustion phase. This requires the crude and residue to be upgraded and fractionated within tight specifications. Hot compressed water (HCW), at or beyond the critical point (374 °C, 22.1 MPa), has emerged as a highly promising environmentally benign and efficient method for heavy oil upgrading to replace conventional toxic solvents. The synergistic effect of HCW with energy generated from renewable sources is a new avenue into a cleaner carbon energy system for fuel production with the benefits of reduced energy consumption and lower carbon dioxide emission. This paper provides a comprehensive review in multi-scale which underlines the recent evolution and the challenges in this field. In addition, the critical factors and emerging gaps influencing the heavy oil upgrading in HCW are appended. Eventually, a set of suggestions for integrating renewable energy technologies with heavy oil upgrading in HCW and future perspective has been reported. [Display omitted] • The synergistic effect between HCW and heavy oil as a cleaner carbon conversion system is reviewed. • A comprehensive view in multi-scale which underlines the recent evolution and the challenges in this field. • Critical factors and emerging gaps influencing the heavy oil upgrading in HCW are appended. • A logical integration of renewable technologies with carbon-based energy conversion system in HCW is suggested. • Possible research suggestions and directions on this field have been proposed. [ABSTRACT FROM AUTHOR]

Biofuel manufacturing from renewable biomass through a smart manufacturing system is an important alternative to fossil fuels, which helps to decrease dependability on conventional fuel and decrease carbon emanations. By utilizing efficient labors, smart machines, and minimized energy utilization, the conventional biofuel manufacturing framework can be converted into a smart sustainable manufacturing framework. The existing conventional fuel demand can be replaced by biofuel. This study efforts to make pure biofuel with less amount of carbon emanations and energy utilization through a smart multi-type biofuel manufacturing framework, where the demand of the biofuel is selling price dependent. The different energy costs including air handling cost, lighting cost are calculated in this work-in-process inventory. The carbon emissions cost is included in every stage of this model. A variable demand has introduced for the maximization of profit. To reduce energy consumption and carbon emissions, a two-stage inspection cost with a variable manufacturing rate is taken to make the manufacturing process flexible such that the amount of impure biofuel is minimized. Although a random manufacturing rate is applied through a smart manufacturing system, still impure biofuel is manufactured. The impure biofuel is remanufactured again through refining just after the well-planned manufacturing ends. In this model, the multi-delivery technique is used such that a fixed amount of biofuel of n segments of the pure biofuel is transported to market places at predetermined intervals at the time of delivery frame. The classical optimization technique is used for continuous and differentiable variables and the mixed integer programming technique is utilized for discrete variables to maximize the total profit globally. To validate the model's usefulness, four numerical observations are studied. It is shown that by utilizing the said procedure, the percentage of impure biofuel can be decreased truly through the minimized energy consumption. The graphical representation and the sensitivity experiment show the impact of every parameter with the whole cost of the research paper. Numerical results assist to get the maximum profit and the optimum selling price of biofuel globally in a sustainable smart multi-type biofuel manufacturing system. [Display omitted] [ABSTRACT FROM AUTHOR]

Abstract: This paper focuses on growth feasibility in an era of increasing scarcity of fossil fuels. A stylised dynamic model illustrates the implications of investing in smooth technological progress in the field of renewable energy. Positive rates of GDP growth sustained by fossil fuels entail, on the one hand, more income available for R&D in renewable energy sources, and on the other, an acceleration of the exhaustible resource depletion time. Our model explores such a trade-off and highlights the danger of high growth rates. Policies should target low growth rates, stimulate investment in alternative energy sources and discourage consumption growth. [Copyright &y& Elsevier]

Abstract: This paper examines the energy and carbon balance of two residential house alternatives; a typical wood frame home using more conventional materials (brick cladding, vinyl windows, asphalt shingles, and fibreglass insulation) and a similar wood frame house that also maximizes wood use throughout (cedar shingles and siding, wood windows, and cellulose insulation) in place of the more typical materials used – a wood-intensive house. Carbon emission and fossil fuel consumption balances were established for the two homes based on the cumulative total of three subsystems: (1) forest harvesting and regeneration; (2) cradle-to-gate product manufacturing, construction, and replacement effects over a 100-year service life; and (3) end-of-life effects – landfilling with methane capture and combustion or recovery of biomass for energy production. The net carbon balance of the wood-intensive house showed a complete offset of the manufacturing emissions by the credit given to the system for forest re-growth. Including landfill methane emissions, the wood-intensive life cycle yielded 20tons of CO2e emissions compared to 72tons for the typical house. The wood-intensive home''s life cycle also consumed only 45% of the fossil fuels used in the typical house. Diverting wood materials from the landfill at the end of life improved the life cycle balances of both the typical and wood-intensive houses. The carbon balance of the wood-intensive house was 5.2tons of CO2e permanently removed from the atmosphere (a net carbon sink) as compared to 63.4 of total CO2e emissions for the typical house. Substitution of wood fuel for natural gas and coal in electricity production led to a net energy balance of the wood-intensive house that was nearly neutral, 87.1GJ energy use, 88% lower than the scenario in which the materials were landfilled. Allocating biomass generation and carbon sequestration in the forest on an economic basis as opposed to a mass basis significantly improves the life cycle balances of both houses. Employing an economic allocation method to the forest leads to 3–5 times greater carbon sequestration and fossil fuel substitution attributable to the house, which is doubled in forestry regimes that remove stumps and slash as fuel. Thus, wood use has the potential to create a significantly negative carbon footprint for a house up to the point of occupancy and even offset a portion of heating and cooling energy use and carbon emissions; the wood-intensive house is energy and carbon neutral for 34–68 years in Ottawa and has the potential to be a net carbon sink and energy producer in a more temperate climate like San Francisco. [Copyright &y& Elsevier]

Generation of electricity comes with the emission of toxic gases into the atmosphere by the fossil fueled generators. Along with the promotion in the utilization of renewable energy sources (RES), it is also the duty of the power engineers to arrive at a compromised solution such that less emission of toxic gases occurs with economic generation of electricity. This paper proposes a balanced trade-off method for solving environment constrained economic dispatch (ECED) problems. A novel comparative analysis is performed among proposed ECED method with existing price-penalty-factor (PPF) and fractional programming (FP) methods for solving combined economic emission dispatch (CEED) problems on a 3-unit dynamic test system to sort out the method, which yields a better trade off solution between generation cost and pollutants emitted. An algorithm, following the hunting strategy of wolves, is improvised by incorporating strategies from population-based sine-cosine algorithm along with position updating methods of crows to form a robust hybrid algorithm, which was used as the optimization tool for the study. Involvement of RES diminished the generation cost to 5.5% for both economic dispatch and PPF based CEED, and 6.5% decrease in emission of pollutants was observed due to the same. The generation cost and amount of emitted pollutants, evaluated using proposed ECED approach, were much closer to the economic dispatch and emission dispatch values respectively compared to PPF based and FP based CEED solution. Furthermore, statistical analysis endorses the superiority of the proposed hybrid optimizer over other algorithms presented in the state-of-art literature. • Three different types of CEED methods are studied. • Subject test system is a 3-units RES integrated microgrid system. • Comparative analysis among the generation costs and pollutants emitted is performed. • A novel HMGWO algorithm was proposed as the optimization tool for the study. [ABSTRACT FROM AUTHOR]

The recent historical increase in energy-related CO 2 emissions globally have put the United States of America's (USA) transportation sector in the spotlight, courtesy of the significantly high pollutant emissions from this particular sector. Taking a cue from this, this paper follows sustainable development goals of the United Nations, and investigates the impact of biomass energy consumption, fossil fuel energy consumption, and economic growth (GDP) on carbon dioxide (CO 2) emissions in the transportation sector of the USA. In doing so, this study also employs the Gregory-Hansen cointegration, Hatemi-J cointegration, cointegration regression (FMOLS, DOLS, and CCR), and Spectral Breitung-Candelon causality test for the period between 1981Q1 and 2019Q4. The findings reveal that (i) a significant nonlinear cointegration among the environmental quality determinants is observed, using the threshold cointegration test. This test determines the structural breaks endogenously and combines two cointegration tests, namely the Gregory-Hansen Cointegration and Hatemi-J Cointegration tests; (ii) while the use of biomass energy consumption and real GDP have a negative effect on CO 2 emissions in the transportation sector, the rising fossil fuel energy consumption is associated with increasing the CO 2 emissions that are stemming from the transportation sector; (iii) in the long-run, biomass energy consumption, fossil fuel energy consumption, and real GDP cause CO 2 emissions to stem from the transportation sector in the USA at different frequency levels. In general, the current study offers policy insights for the transportation sector of the USA and other similar economies that replicate the same conditions. Image 1 • We explore the driving forces of CO 2 emissions in the transport sector for the USA. • We employ advanced time series econometric techniques for empirical analysis. • Biomass energy and real GDP help to mitigate CO 2 emissions in the transport sector. • Fossil fuel energy has a positive impact on CO 2 emissions in the transport sector. • All variables have a causative relationship with CO 2 emissions in the long-run. [ABSTRACT FROM AUTHOR]

The pollution of fossil fuels uses and low efficiency performance of energy systems are the main issues which threaten the environment and cause extra cost. Many solutions are presented and the one which is performed in this study is using energy hub which is composed of several parts. Sub energy hub and combined cooling, heating and power combining with the renewable energies such as wind turbine and photovoltaic are the component parts of this novel energy hub. The optimum flow of energy plus using energy storage devices brings coordination and reliability to the system. The model proposed is multi-objective and the goal is to investigate the effects of accomplishment real-time based demand response program in reducing operation cost and CO 2 emission. The mathematical methods like compromise programming and fuzzy approach are implemented to gain the Pareto solutions and obtain trade-off between economic and environmental performances. Two cases which are investigated in this paper are without and with demand response program. The linear model with mixed-integer programming is implemented in general algebraic modeling system to solve the proposed model. The comparison results illustrate that the operation cost and CO 2 emission is decreased 4.05% and 1.52% respectively due to demand response program. • CCHP based microgrid in the presence of renewable energies is considered. • The environmental issue is considered as bi-objective model. • Compromise programming and fuzzy approach are used to solve the proposed model. • Real-time demand response program is applied to reduce operation cost and emission. [ABSTRACT FROM AUTHOR]

Livestock production systems, such as dairy farming, are one of the most important contributors to resource use and if not managed well, it can be environmentally detrimental. Iranian livestock sector faces a variety of the challenges such as high costs of energy and environmental legislations as well as an increasing demand for dairy products to respond the growing population. This paper aims to contribute to the discussion on technical efficiency as a key indicator of energy use within dairy farming systems. A Window Data Envelopment Analysis (W-DEA) with energy use as inputs and milk production as output was modelled with data from 25 provinces during the last 22 years (1994–2016) in Iran. In addition, the Slack-Based Model (SBM) was used to compare the radial DEA model with non-radial SBM, both in a dynamic environment (window analysis). The average efficiency score of Iranian dairy farming production system was estimated at approximately 0.85. Through the years, three provinces including Zanjan, Ardabil and Hormozgan had the highest technical efficiencies. Window analysis represented that provinces are distinctive in terms of their technical efficiencies and energy consumption over the years. Applying the SBM model improved the accuracy of the estimated efficiency scores compared to the radial (DEA) model. Further analysis represented a significant difference between the technical efficiency of different milk production levels. Provinces that produced higher volumes of milk had lower technical efficiencies. Based on the results it can be concluded that there is a substantial space for upgrading the technical efficiency of dairy farming in Iran by improving resource use efficiency which leads to an optimized energy consumption. It is recommended to reform Iranian livestock farming policies by applying mechanized systems, optimal strategies for water, electricity and fossil fuel consumption, use of renewable energy and better feed management while enhancing milk productivity and technical efficiency. In this respect, it is suggested that policy makers consider different indicators such as energy use efficiency and environmental impacts when allocating subsidies and resources to different provinces and farms. • Iranian dairy farming was assessed for the technical efficiency over 22 years. • Efficiency of 25 provinces were identified using window data envelopment analysis. • The average efficiency score of dairy farming was approximately 0.85. • We propose improvement of resource management in order to minimize energy use. • Milk production was found as an effective factor on efficiency of provinces. [ABSTRACT FROM AUTHOR]

This review deals with organic Rankine cycle powered by geothermal resource which is one favorable substitute for conventional fossil energy. Organic Rankine cycle power plants are suitable for utilization of low-temperature energy sources (low grade energy) such as geothermal resource having low temperature (below 150 ᵒC). The applications of organic Rankine cycle for electricity production from geothermal energy resource was reviewed first, where the choice of geothermal energy resources and organic fluids was discussed for different ORC configurations and operating conditions. Hybrid optimization approaches for the purpose of maintaining long term performance of enhanced geothermal system reservoirs were also summarized. Furthermore, an in-depth review of energy and exergy efficiencies of ORCs was conducted. Key factors that influence the energy and energy efficiencies of organic Rankine cycle were discussed in detail. Then, the economic indexes such as electricity production cost and levelized cost of electricity for different organic Rankine cycle configurations were compared with other conventional power generation systems to examine the commercialization of the Organic Rankine cycle. Finally, life cycle assessment that evaluates the whole life performance of geothermal organic Rankine cycle energy systems was reviewed. The Environmental impacts of geothermal ORC were also considered. Compared with other review papers on geothermal organic Rankine cycle s, the present review provides the latest materials for more systematically surveying the geothermal organic Rankine cycle, which will be a valuable source of guidance and directions for engineers and researchers in this field. [ABSTRACT FROM AUTHOR]

One major drawback of climate change agreements including the recent 21st Conference of the Parties is focusing mainly on countries or regions with very high contribution to global emission rise but neglecting potential emitters. With Sub-Saharan Africa (SSA) been one such potential region, this paper applies the extended Kaya Identity Decomposition to investigate the dynamic impact of energy-related driving factors on carbon dioxide (CO 2) emissions and its future trend in SSA. Employing the Autoregressive distributed lag model analysis for the period 1980 to 2014 reveals carbon intensity and "transition from biomass to fossil fuel energy" as the major long run and short run drivers of CO 2 emissions increase respectively while "potential of penetration of clean energy in the energy consumption mix" is the only driver of both short and long run CO 2 emissions decrease. Energy intensity and per capita GDP (supported by substantial household self-consumption of fuel) weakly and positively impact CO 2 emissions in SSA. The dynamic forecasting analysis reveals possible low carbon energy path towards 2030. We propose transport sector energy efficiency improvement, use of natural gas and renewables to improve the region's high energy poverty, improvement of household-self consumption paying attention to cleaner and safer energy and others. • Transition from biomass to petroleum fuel hinder low carbon development in the short run in SSA. • Carbon intensity is the major long run cause of increase in CO 2 emissions in SSA. • Clean energy potential is main promotor of low carbon development in SSA. • Energy intensity and per capital GDP weakly promote CO 2 emissions in SSA. • Significant emission reduction potential exists for SSA towards 2030. [ABSTRACT FROM AUTHOR]

Despite the global context, only 6% of Australia's total energy consumption was derived from renewables, while 86.3% of electricity was generated from fossil fuels. However, this trend has been disrupted by the recent decommissioning and closure of a fleet of ageing coal power plants, along with the country's international commitments to reduce fossil fuel emissions. Currently, Australia is at a crucial stage of its transition to renewable energy adoption. With the purpose of providing an updated depiction of renewable energy, related policy and the way ahead in the Australian context, this research paper presents a systematic review of contemporary literature from the perspectives of energy potential, utilisation and policy incentives. The research analysed a total of 118 documents using an interpretivist epistemological lens; emergent findings offer an evidence-based, lucid account of advancements in the renewable energy market. Polynomial regression analysis is also conducted on secondary data obtained from the literature to predict trends in the electricity generated by different sources of renewable energy. The work also identifies several areas that require attention, including: (1) the most recent time-varying feed-in tariffs (TV FiTs) which offer the innate potential to alter consumer attitudes toward power usage at peak times, thereby improving grid security; (2) the increasingly popular integration of waste-to-energy with other sources of renewable energy emerges as a viable complementary solution to meet energy demands; (3) the increasing utilisation of subsidised geothermal energy installations which are set to rise exponentially in the future; and (4) the use of Public Private Partnerships (PPP) for developing renewable energy generation infrastructure and how this investment may facilitate the national transition to renewable energy adoption. This research contributes to the existing body of knowledge by raising awareness of the current state of renewable energy in Australia, along with proposing pragmatic recommendations for overcoming any challenges posed. As a comprehensive reference, this study provides practitioners and policymakers with thorough, reliable and collated information on Australia's current renewable energy position. [ABSTRACT FROM AUTHOR]

Coal direct chemical looping hydrogen generation (CDCLHG) is a promising technology to convert coal into high purity hydrogen. Cradle-to-grave life cycle greenhouse gas (GHG) emissions and primary fossil energy consumption (PFEC) analysis are developed to study the CDCLHG process in this paper. The results show that the total GHG emissions and PFEC of the CDCLHG process are 9.54 kg eq. CO 2 /kg H 2 and 312.02 MJ/kg H 2 , respectively. The CDCLHG stage is the largest GHG emissions stage and the largest PFEC stage. The total GHG emissions of the CDCLHG process is larger than the ash agglomerating fluidized bed (AFB) gasification process, whereas the total PFEC of the CDCLHG process is smaller than the AFB gasification process. In addition, the sensitivity analysis demonstrates that GHG emissions of the CDCLHG stage are sensitive to reducer temperature, reducer pressure and n F e 2 O 3 to n C . • Cradle-to-grave life cycle analysis is carried out to the CDCLHG process. • The total GHG emissions of the CDCLHG process are 9.54 kg eq. CO 2 /kg H 2. • The PFEC of the CDCLHG stage is 283.61 MJ/kg H 2. • The PFEC of the CDCLHG process is smaller than the AFB gasification process. [ABSTRACT FROM AUTHOR]

Selective fermentation of reducing sugars in cane juice harnesses the advantageous productivity of high-yielding sugarcane cultivars for increasing products from limited arable land. Without this technology, the altered compositions of cane juice often lead to additional environmental impacts due to increased consumption of externally supplied energy and compensated yield of sugar. In this paper, the effects of coordinated transition of sugarcane farming and sugar milling on the yield of final products, energy consumption, operability in the crystallization process, and economic feasibility were analyzed in simulation across various sugarcane cultivars. An integrated sugarcane farming and sugar milling process model (SugaNol) was extended from a previous work to consistently balance mass and energy considering the characteristics of the selective fermentation technology. A case study demonstrated that the coordinated introduction of selective fermentation with the high-yielding cultivar enhanced sugar production by 8.5% and ethanol production by 17.9%, improved operability in the crystallization process, and lead to a cleaner production by achieving above without consuming additional fossil fuels, although the market price of ethanol should be under 95 JPY L−1 for profitability. Furthermore, the specific characteristics of cultivars to make selective fermentation economically feasible are presented as a guideline for future cultivar development. Image 1 • A process model of combined sugar and ethanol production was developed. • The model can consider agricultural options and selective fermentation technology. • A set of options expects increases in sugar by 8.5% and ethanol by 17.9%. • Busy operation could be avoided even if bad-quality sugarcane is fed. • The request to cultivar development could be visualized through modeling. [ABSTRACT FROM AUTHOR]