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Energy development in industrial parks promotes both industrial and inter-park economies. However, as the number of industrial parks increases and the economic level of the parks rises, energy consumption is also increasing rapidly. The rapid expansion of inter-park trading markets is accompanied by a surge in carbon emissions, making industrial parks increasingly significant contributors to carbon emissions within the industrial sector. In response to this environmental challenge, this paper proposes an integrated trading approach within industrial parks that considers carbon constraints. By implementing a spot trading method for surplus industrial energy, the goal is to mitigate the carbon emission pressure within these parks. Firstly, the paper conducts an analysis of the characteristics of combined heat and power units in industrial parks. It introduces an integrated analysis method within the target region, consolidating information from various park units to enhance flexibility in energy utilization. Secondly, an energy storage model is established. This model efficiently leverages energy storage capacity to balance fluctuations in energy supply and demand within industrial parks, thereby alleviating carbon emission pressure. Finally, the study and analysis of an industrial park in Liaoning Province were conducted using the Yalmip + Gurobi commercial software on the MATLAB platform. Compared with the traditional industrial park, the carbon dioxide emission of the industrial park is reduced by 91.49t, and the energy cost is saved by 11.2 million RMB. Numerical results from instances indicate that this method surpasses traditional trading approaches, aligning with the rigorous standards of scientific research. • An energy storage model is proposed to address the shortage of energy storage in waste heat trading in industrial parks. • A coordinated scheduling program is presented to reduce energy scheduling imbalances between multiple campuses. • The carbon-constrained energy storage device is integrated to improve the decarbonization capacity. [ABSTRACT FROM AUTHOR]

This research addresses the critical necessity for energy-efficient solutions in port operations. The primary objective of this paper is to introduce and assess the viability of an innovative infrastructure termed Underground Reefer Container Storage (URCS) devised to mitigate the significant and increasing energy demand posed by reefer containers in ports. This study employs a discrete-event simulation (DES) model to evaluate the feasibility, environmental implications, and cost-effectiveness of three distinctive URCS infrastructure designs. These designs are compared against conventional storage methods to ascertain their capacity for minimizing energy usage and greenhouse gas emissions. The analysis reveals that the best scenario for a specific case study involves a multi-block layout comprising two underground yards, capable of accommodating 39% of the overall refrigerated container capacity at a port. This layout cuts CO 2 emissions by 61% from the 2.704 GWh/year energy used by refrigerated containers, yielding around 1.4 million USD/year cost savings. Further analyses using weighted searches to prioritize URCS container slotting led to shorter container dwell times at ports, rendering energy savings 23% higher than in similar unplanned settings. Moreover, this study presents URCS as an eco-friendly alternative for port-based reefer container storage, offering practical alignment with sustainability goals and regulations. The innovative design and its successful application provide holistic insights, paving the way for enhanced port energy management and environmental care. In addition, the implementation of URCS has the potential to reshape port procedures, yielding economic and ecological benefits. This initiative contributes to diminishing the carbon footprint of ports, aligning with global endeavors towards greener and more responsible practices. [Display omitted] • Conventional stacking at ports consumes high energy for reefer containers, risking the cold chain. • Underground reefer container storage (URCS) reduces heat exchange by storing reefers in a colder underground deposit. • Multi-level block storage is preferred in URCS, according to a multi-criteria assessment. • Simulation recommends energy savings with proper stacking in multi-level block storage. • URCS enables environmentally responsible port operations, improving standards feasibly. [ABSTRACT FROM AUTHOR]

With the increasing number of integrated energy system (IES) construction, a multi-agent system group composed of multiple IESs would be formed in a certain region. Moreover, complex uncertainties gradually existed in the IES which affect the system optimal situation and optimization results. In order to take full use of each agent's advantages and improve the performance of the whole region under uncertainty, this paper focuses on the multiple energy types' interaction of multi-agent IESs within the region to realize the stable operation, economic and environmental improvement of each agent and the whole region. To this aim, a multi-objective multiple energy types' multi-agent interactive optimization model considering energy demand and renewable energy output uncertainties was built. The model was based on Nash bargaining cooperative game theory and took economy, flexibility and carbon emission as objectives. Moreover, energy interaction scheduling and its corresponding price can be optimized through the model. The results of non-cooperative operation mode without interaction and cooperative operation mode with interaction were compared to analyze the superiority of interaction from the cost, carbon emission and flexibility aspects. The overall regional carbon emission and the economic cost has been reduced by 13.84% and 9.94%, for each IES, the carbon emission and economic cost could reduce by up to 41.5% and 44.5%. Moreover, the flexibility of the IES was correspondingly increased by nearly 47%. These results denoted that after multi-agent interaction, not only the overall region's energy, economic and environmental performance are improved, but also that of each agent are significantly improved. In addition, different energy types among multiple agents could be effectively used and regional joint energy storage is realized, improving the region flexibility level and resilience. • A multi-objective integrated energy systems interaction model is established. • The interaction model considers multiple energy types and uncertainties. • The model can improve economy and flexibility of each system agent and the region. [ABSTRACT FROM AUTHOR]

Sustainability pertains to the interplay between environmental, economic, and social systems at varying scales. In transportation systems, vehicles use different fuels to fulfill their energy requirements. However these fuels emit green house gases that pollute the environment. Taking into account this fact, the present paper delves into the investigation of a multi-objective multi-item fixed cost solid transportation problem with various driving styles. Also, three types of fuels are incorporated in the proposed model. The primary focus of this paper is to maximize profit by reducing breakage of the items along with reducing carbon emission and time of transportation. In real-life situations, the parameters of multi-objective multi-item fixed cost solid transportation problem may not be tackled crisply. Hence triangular intuitionistic fuzzy numbers are introduced in the proposed model. The score function is employed to convert intuitionistic fuzzy problem to deterministic one. Thereafter, a methodology is developed to solve the proposed model involving different driving styles and is extended to consider the optimistic, pessimistic, and mixed view of the decision maker. Comparisons are made among the compromise solutions that are derived from different approaches and are shown by various charts and graphs. A case study is included to illustrate the applicability and validity of the proposed methodology. • A sustainable multi-objective 4DTP with multiple items and fixed charge is modeled. • Three types of fuels: diesel, petrol and CNG are incorporated in the proposed model. • Driving style is included to analyze the fuel consumption and breakability of items. • The decision-maker's optimistic, pessimistic, and mixed viewpoints are discussed. [ABSTRACT FROM AUTHOR]

Developing green materials for infrastructure construction is of vital importance for sustainable development. Limestone calcined clay cement (LC3) is an appropriate alternative for the reduction of CO 2 emissions and resource consumption in the cement industry. Recycled concrete aggregate (RCA), seawater and sea sand are potentially advantageous from a sustainability perspective, especially in coastal regions. Fiber-reinforced polymer (FRP) bars with excellent corrosion resistance are ideal alternative materials for steel bars in a corrosive environment. In this paper, a new type of green concrete structure incorporating LC3, seawater, sea sand, RCA, and FRP bars was investigated, and the performance was assessed to verify the considerable sustainable advantages while considering life cycle cost and environmental impacts. The results showed that the proposed LC3 concrete exhibited lower environmental impacts: compared with traditional concrete, and the CO 2 and energy consumption of LC3 concrete were reduced by 32%–41.7% and 23.3%–28%, respectively. Although the initial cost was higher for LC3 and CFRP bars, this disadvantage could be offset by their longer service life and lower maintenance costs during their life cycle. Compared with traditional RC structures, the total cost, CO 2 and energy consumption in the life cycle were reduced by 39%, 30.5%–65.4%, and 18.5%–58.9% for the LC3 concrete structure, respectively. In contrast to the life cycle cost, the LC3 replacement ratio had a negative effect on the environmental indices for the LC3 concrete and structure. Considering the promising advantages in economy and environmental impact, the proposed LC3 concrete and structure provides an effective approach for the sustainable development of the construction industry. • A type of green concrete structure incorporating LC3, seawater, sea sand, RCA, and FRP bars. • LC3 concrete exhibits lower environmental impacts, decreased as the LC3 replacement ratio increases. • LC3 concrete structure shows excellent environmental and economic advantages. [ABSTRACT FROM AUTHOR]

The concept of NZEB (Nearly Zero Energy Building) has a promising share to fulfill the future of sustainable development goals. However, exploiting renewable-based THESs (Trigeneration Hybrid Energy Systems) for providing the energetic demands of the building sector needs further attention. In this regard, the present paper proposes a sustainable THES driven by a biogas-fueled gas engine. The bottoming systems comprise absorption/electrical chillers (AC and EC), organic Rankine cycle (ORC), solar collector (PTC), and an auxiliary boiler. A detailed sustainability evaluation framework (technical and eco-environment) is derived to approve the performance of the THES. Within this procedure, the best working fluid of the ORC is firstly selected and then the sensitivity of the system performance to the design variables is assessed by a comprehensive parametric study. To make the derived framework more applicable, a case study building is considered and the proposed THES is sized to meet its electricity, heating, and cooling energies. The analyses proved that R123 shows the best techno-economic performance among six investigated ORC working fluids. The parametric study illustrated that the highest and lowest sensitivity of the THES's performance is related to the outlet temperatures of EC condenser and AC evaporator. Furthermore, the energy, exergy, and economic efficiencies of the THES for the case study building are 61.78%, 25.24%, and 44.77%. In this condition, discounted payback period is 7 years, demonstrating the feasibility of this proposal. The maximum CO 2 emission is released in November, with a total electricity generation of 320 MWh. [Display omitted] • Renewable-based hybrid system is introduced to produce cold, heat, and power. • Comprehensive sensitivity analysis is done to assess impact of some decision variables. • A case study building is considered to boost NZEB concept based on the proposed system. • Energy efficiency and payback period is 61.78% and 7 years for the case study building. • Using renewables in energy systems to reduce fossil fuel share has great significance. [ABSTRACT FROM AUTHOR]

Energy efficiency and carbon mitigation are important issues in modern energy systems research. Considering the couplings between energy and carbon, this paper investigates a carbon-embedded energy coordination problem in a park-level integrated energy system (PIES). Firstly, based on energy hub, a multilateral interactive transaction framework is introduced, consisting of energy hub operator (EHO), building users with photovoltaics, and an electric vehicle (EV) charging agent. Secondly, a time-varying carbon emission measurement model for the outsourced electricity is designed, taking into account the dynamic composition of the supply-side generators. Based on the time-varying carbon factor and virtual carbon emission flow, an energy-carbon pricing strategy is proposed to balance the carbon responsibility among different participants. Then, a multi-agent interactive trading model in the PIES is constructed, where the energy consumption plans of building users and EVs are guided by the dynamic energy-carbon integrated prices. Through the iterative interaction among different agents, the optimal trading results are finally obtained. Simulation results illustrate the effectiveness of the proposed energy-carbon integrated pricing method in reducing carbon emissions and promoting energy sharing. • A carbon-embedded multilateral energy interaction mechanism in a PIES is discussed. • A time-varying carbon emission measurement model is established. • An energy-carbon integrated pricing strategy based on the dynamic carbon factor and virtual carbon emission flow is designed. • The impacts of energy-carbon integrated pricing on the scheduling of the PIES and carbon emission are investigated. [ABSTRACT FROM AUTHOR]

Transnational power cooperation contributes to promoting the large-scale use of renewable energies in Asia, but how to develop the structure of power transmission network deserves careful investigation. This paper thoroughly investigates the structure of power investment and transmission network in China and neighbouring countries, aiming to promote the large-scale use of renewable energies around Asia. Various power-generation and power-transmission technologies are considered in detail, and transnational power interconnection risk cost and carbon emission cost are embedded into a bottom-up optimization model. The future power-generation structures and networks installed under various policy scenarios are analysed in detail, and the corresponding economic, carbon emission reduction and renewable energy consumption benefits are evaluated. The results show that power transmission between China's internal regions and neighbouring countries can save $56.7 billion for the entire power system through the large-scale grid integration of renewable energy. The installed capacities of wind power, solar power, and hydropower renewable energy power generation could be increased by 141 GW, 163 GW, and 58 GW, respectively. The construction of transnational transmission lines from Central Asia to Northwest China, Mongolia to North China, the Russian Far East to Northeast China, and Northeast China to South Korea could effectively promote the utilization of renewable energy in the Russian Far East, Mongolia and Central Asia and further reduce carbon emissions in China, Japan and South Korea. • It examines how to construct a power investment and transmission network in Asia. • Various technologies, risks and costs are considered based on bottom-up model. • Huge benefits exist for power transmission between China and neighbouring countries. • Various power-generation structures and networks installed are analysed in detail. • Suggestions about power investment and transmission are given for Asian countries. [ABSTRACT FROM AUTHOR]

The increasing contribution of refrigeration systems to global warming has led to widespread demand for low global warming potential (GWP) refrigerants as alternatives. This paper proposed a comprehensive environmental assessment method for evaluating the carbon footprint of units charged with low-GWP refrigeration. Experimental and numerical studies were used to investigate the carbon footprint impact of using alternative refrigerants at different ambient temperatures in China. Initially, the model was validated through experimental case studies on the use stage of cold storage units. Subsequently, a comparison was made between the cooling capacity (CC) and energy efficiency ratio (EER) of cold storage units charged with different refrigerants. Additionally, the impact of alternative refrigerants in the use stage was analyzed by numerical calculations, and the adaptability of the cold storage unit to the ambient temperature and the national energy structure was also studied. The results indicate that among the four stages of the cold storage unit, the use stage is the hotspot of carbon footprint due to the large amount of energy consumption and the existence of refrigerant leakage and other behaviors. Utilizing low-GWP alternative refrigerants could significantly reduce the carbon footprint of the cold storage units' use stage by 10.56%–16.39%, thereby lowering the whole stage carbon footprint. Furthermore, the ambient temperature and national energy structure could also effectively reduce the carbon footprint of cold storage units' whole stage by 1%–27.17%. Furthermore, after adopting low GWP refrigerants, the life-cycle cost (LCC) of the units have also decreased by 6.1%–12%. Taking into account both environmental impact and economic considerations, it is recommended to directly replace R404A with R448A in the units in regions where the average ambient temperature is above 15 °C. • A carbon footprint evaluation model for the units was established. • Influencing factors of carbon footprint are studied numerically and experimentally. • By GHG assessments, the optimal refrigerant and external conditions were determined. • Alternative refrigerants reduce carbon emissions for cold storage units by 8.8%–24.92%. [ABSTRACT FROM AUTHOR]

Carbon peaking and carbon neutrality goals are proposed by the Chinese government, which aims to reach the highest level of CO 2 emissions by 2030 and achieve carbon neutrality by 2060. It is of great significance to accelerate green production and lead high-quality development. Energy carbon emissions account for 88% of total CO 2 emissions, while forest carbon sequestration account for 80% of China's terrestrial ecosystems. In this paper, we analyzed the spatial and temporal evolutions of industrial energy consumption carbon emissions and forest carbon sequestration of Hubei Province, then demonstrated the offsetting effect of forest carbon sequestration on the industrial CO 2 emissions. Our results documented energy carbon emissions and forest carbon sequestration in Hubei Province both increased from 2000 to 2020, with the growth rates of 4.9423 Mt/yr and 0.28015 Mt/yr. Forest carbon sequestration could offset energy carbon emissions before 2005, while the offsetting effect was weak due to the continuous increase in industrial energy consumption after 2005. Significant spatial heterogeneity was observed in both energy carbon emissions and forest carbon sequestration. Wuhan had the biggest carbon emission with annual average carbon emission of about 20.046 Mt, while Enshi had the biggest carbon sequestration with annual average forest carbon sequestration of about 14.411 Mt. Spatial autocorrelation between energy carbon emissions and forest carbon sequestration was significant in Hubei Province in the past two decades. Our findings provided evidence that local-scale forest carbon sequestration could offset carbon emissions caused by industrial energy consumption at a certain extent, helping to draw up the scientific energy-saving and emissions-reducing measures. [Display omitted] [ABSTRACT FROM AUTHOR]

Meeting energy needs and ensuring ecological sustainability are important tasks for policymakers. In particular, changing the energy mix used in daily electricity generation can have a major effect on ecological conditions, and this is a previously neglected research topic. Therefore, this paper aims to investigate the influence of daily electricity generation from nuclear power and renewables on the achievement of carbon neutrality targets in the four largest nuclear power countries (i.e., the U.S., China, France, and Russia). The study applies the wavelet-transform coherence (WTC), quantile-on-quantile regression (QQR), and Granger causality in quantiles (GCQ) approaches for the period from January 2, 2019 to December 29, 2022. The outcomes present that electricity generation from nuclear energy reduces carbon (CO 2) emissions only in Russia, while hydropower generation does not contribute to CO 2 emission reduction in any country. Solar electricity generation decreases CO 2 emissions in different quantiles in the U.S. and Russia, while electricity generation from wind power reduces CO 2 emissions in the U.S. and France. The empirical outcomes also reveal that expanding solar, wind, and nuclear power in the energy mix can enhance the potential of the U.S., France, and Russia to achieve carbon neutrality and secure a sustainable future. However, China is using nuclear and renewables inefficiently regarding carbon neutrality. Therefore, the empirical evidence for China is highly controversial compared to former studies. [Display omitted] • The study examines renewable and nuclear electricity effect on carbon neutrality. • The study focuses on top four major nuclear power countries. • The study applies nonlinear approaches by using high-frequency (daily) data. • Renewable and nuclear electricity have time, frequency, & quantile-varying effect. • The best electricity source change according to each country. [ABSTRACT FROM AUTHOR]

The metallurgy industry plays a very important role in China's economic growth. Due to its energy concentration, the energy consumption of the industry accounts for a large proportion of China's total energy consumption, and thus contributes to carbon emissions. Whether the metallurgy industry can successfully reduce emissions is related to the future of China's carbon emissions targets. In this paper, the logarithmic mean Divisia index model is used to analyze the change in China's carbon dioxide emissions from 1991 to 2014. The empirical results show that there are three main factors affecting the carbon dioxide emissions of China's metallurgy industry. The three factors are labor productivity, energy intensity and industry size. In addition, we further analyzed the deep motivation of carbon dioxide emissions in the industry, and calculated the future emission reduction potentials. Lastly, according to the empirical results, the paper proposes policy recommendations for the future emission reduction of China's metallurgy industry. [ABSTRACT FROM AUTHOR]

The paper aims at investigation of the nexus between Industry 4.0 (I4.0) and environmental sustainability in addition to exploring the long-run and short-run effects of Industry 4.0 on CO 2 emissions. For this end, energy consumption, internet and communication technology (ICT) exports, research and development (R&D), artificial intelligence (AI), ICT technology patents and bitcoin are taken as control variables of Industry 4.0 for a panel of 9 countries that contribute to 62% of the total CO 2 emissions in the world. For this purpose, the paper follows two approaches. First, the paper proposes utilization of AI and ICT technology patents, technology-related R&Ds and ICT exports as variables of I4.0 in addition to investigating the effects of economic growth, energy consumption and bitcoin. Second, to control structural changes and nonlinearity in the cointegrating relations and existence of degenerate cointegration, Fourier panel bootstrap autoregressive distributed lag model (FPBARDL) is utilized. Afterwards, FPBARDL based long, short and strong causality analyses are conducted. The empirical findings revealed positive impacts of all I4.0-related variables on emissions in the long-run. Though I4.0 related AI and ICT innovation has no direct effect in the short-run, its effects are determined through increased energy consumption towards emissions. The strong positive effects of energy consumption and positive effects of economic growth, ICT exports and R&D are observed both in the short and long-run. In addition to positive impacts of I4.0 on environment, the findings favor insufficiency of policies focusing on lowering emissions in I4.0 context.Policy recommendations include strong commitment to energy efficiency and renewable energies and trade policies with environmental concerns. [ABSTRACT FROM AUTHOR]

Excessive energy-related carbon emission intensity will lead to deterioration of environmental quality and hinder green economic growth. This paper proposes a novel self-adaptive fractional order grey generalized Verhulst model (SAFGGVM) to predict energy-related carbon emission intensity in China, America, India, Russia, and Japan with nonlinear and complex characteristics effectively. Firstly, self-adaptive fractional order and dynamic background value coefficient are introduced to capture the nonlinear evolutionary trends. Subsequently, the optimal nonlinear parameters are determined using Grey Wolf Optimization algorithm through comprehensive comparison. Furthermore, the flexibility of SAFGGVM is verified by presenting its relevance to existing models. Finally, the validity, applicability, and robustness of SAFGGVM are confirmed by comparing with two machine learning models and four grey prediction models. The empirical results exhibit that the overall precision of SAFGGVM model significantly prevails over the others in five cases, with MAPE values less than 6% in both the simulation and prediction intervals. The out-of-sample forecast results indicate that the energy-related carbon emission intensity of five countries will fall into 5.7024, 1.6030, 7.3668, 8.1633, 2.0399 tons/10,000 USD by 2025, and the decreasing rate of developing countries tends to catch up with, or even exceed, developed countries. Projection results can serve as a reference point for countries to achieve green and sustainable development. • A novel self-adaptive grey generalized Verhulst model is proposed. • Energy-related carbon emission intensity (ECEI) of five countries is predicted. • Optimal nonlinear parameters are determined by Grey Wolf Optimization algorithm. • The novel model is superior to other competing models in accuracy and roubutness. • Decline rate of ECEI in developing countries will catch up with developed countries. [ABSTRACT FROM AUTHOR]

The construction industry is one of the most energy-intensive industries in China, which contributes to high carbon emissions and hinders efforts to reduce the emissions. The high energy consumption and emission have seriously constrained the growth of low carbon economy in China's construction industry. And reducing the carbon emission from construction industry (CECI) has become the key to sustainable development and the achievement of "double carbon target". The paper firstly decomposes the main influencing factors and calculates their effects by LMDI model. Then, the Tapio decoupling index is used to explore the decoupling relationship between carbon emissions and economic output. Finally, the spatial-temporal evolution of carbon emissions is analyzed through spatial autocorrelation theory. The results show that the carbon emissions from construction industry are highly increased by the construction employment rate (EM), and may be reduced by the energy intensity (EI) and carbon emission efficiency (CI). And the regions with better decoupling status are the eastern and central regions, which have relatively developed construction industry. Moreover, the spatial-temporal characteristic of carbon emissions is "high in the east and low in the west, high in the south and low in the north," showing obviously regional differences. [Display omitted] • Factors about production technology are taken into account, reflecting the characteristics of the construction industry. • Developed regions have better decoupling potential and more responsibility for CO 2. • The spatial distribution is "high in the east and low in the west, high in the south and low in the north". • The provinces in a region have similar decoupling status and carbon emission distribution. [ABSTRACT FROM AUTHOR]

Energy Internet (EI) is typically characterized by digitalization and clean energy that seeks to revolutionize the energy system and reduce carbon emissions. Even though several scholars conclude that EI accelerates the clean energy transition of energy system, since the controversial relationship between digitalization and energy consumption in academia, current studies on the carbon emission reduction advantages of the EI are still in dispute. This paper employs the effect of EI's construction on the carbon emission peak goal of China's energy system based on the system dynamics model and different scenarios. The simulation results find that: (1) the construction of the EI could enable China's energy system to meet the carbon reduction commitment in 2028, with a carbon emission peak of 11.61 billion tons; (2) As digitalization and clean energy become more extensively employed, rising energy demand is satisfied by the manner of consuming low-carbon electricity energy. This is thought to be the primary factor that could promote China to achieve the carbon peak goal earlier than expected; (3) The advancement of digitalization has further promoted the decoupling of China's economic growth from carbon emissions. It is projected that China's energy system will still achieve the carbon peak goal by 2030 when the expected annual GDP growth rate is increased to 6.32%, 5.75%, and 4.6% for the years 2020–2025, 2026–2030, and 2031–2035, respectively. These findings might provide a new perspective for quantitative research on the environmental outcomes of the EI and the relationship between environmental improvement and economic growth. [ABSTRACT FROM AUTHOR]

There is no one-size-fits-all solution for global energy sustainability. It is affected by a country's policies, resources, financing opportunities, the attention given to it, and the degree to which other pressing issues, such as poverty and access to power, are addressed in each country. This paper used 28 indicators to assess a country's energy sustainability. These indicators ranged from CO 2 per capita emissions to the share of electricity production from wind. The indicators were adjusted so that the lower values were more sustainable. 31 countries were selected. Kohonen's self-organizing maps were used to present this 28-dimensional model in a 2D map. This algorithm is a type of artificial neural network trained by unsupervised learning. Eight clusters of countries were found through the analysis using the four-light traffic panel, where green is the most sustainable, followed by blue, yellow, and red. The closeness on the map does not guarantee that two countries will be in the same cluster. Three color matches and closeness were the criteria for the creation of clusters. The energy transition from the map's lower to upper sides is plainly visible. Red clusters make up the lower side, while green clusters make up the top. One blue cluster and two yellow clusters are located between them. The algorithm converged in the 133rd iteration; the quantization error reached 0 and the topological error reached a value of 25. This method can be used to visualize how far or close a country is to the best achievers. It shows which parameters can or should be improved and what the world trend is. If there is a trend, cost-effective solutions are frequently present. [ABSTRACT FROM AUTHOR]

The growing demand for private vehicles associated with the rise in the number of middle-income consumers in Indonesia has led to an enormous energy demand and high-level CO 2 emissions. In order to increase the sustainability in the transportation sector, the Indonesian government has given special attention to electric vehicles as key future solutions to achieve clean and green transport and to improve energy supply security. This paper aims to investigate public perception in relation to the adoption of electric motorcycles (EMs) in Indonesia. We conduct a survey involving 514 participants and find that only 36% of participants agree to adopt EMs as their next motorcycle, and 40% are still in doubt (i.e. neutral). To identify factors influencing EMs adoption, we expand the Theory of Planned Behaviour (TPB) model and analyse the data collected using Partial-Least Squares Structural Equation Modelling (PLS-SEM). The findings show that an adequate perception of EMs, environmental benefits, economic benefits, and incentive policies positively affect the attitude toward the adoption of EMs, which reinforce the results of the previous studies. However, perceived cost and perceived risks appear to be insignificantly influential in our study. Furthermore, factors related to high-behavioural control and support from relatives and closest people are shown to significantly affect the adoption of EMs. This paper also presents the acceptable price range of EMs and the optimal price point (OPP) for segments differentiated by monthly income. All these findings provide valuable insights for the different stakeholders interested in enhancing the adoption of EMs in Indonesia. [ABSTRACT FROM AUTHOR]

Taiwan's per capita carbon emissions ranks first in Asia. Whether Taiwan's current "2025 Non-Nuclear Homeland" energy transition policy can achieve the goal of greenhouse gas reduction is an issue that needs to be studied urgently. On the basis of studying the status quo of energy supply and demand and carbon emissions in Taiwan, this paper first uses an econometric model to predict Taiwan's energy demand from 2021 to 2030, and then uses a Markov chain model to predict its energy structure changes and CO 2 emission trends under different scenarios, and evaluates the impact of its energy transition policies on carbon emission reduction goals. On this basis, by comparing the carbon trading markets on both sides of the Taiwan strait, the feasibility of and obstacles to the cross-strait cooperation in the carbon trading market are discussed in depth, and the opportunities for future cross-strait cooperation in the carbon trading market are proposed innovatively. The empirical results of this paper show that the carbon emissions in 2025 under the energy transition policy will be reduced by 59.8–61.1 million tons compared with those without planning constraints, but compared with the carbon reduction target (a reduction of 124.8–133 million tons), there is still a long way to go. The contribution potential of the annual carbon emission reduction target is only 45.9%–47.9%, and the contribution potential in 2030 is 57.2%–60.1%. The current "2025 Non-Nuclear Homeland" policy is not in line with Taiwan's current reality, and it is difficult to achieve the expected carbon reduction goal. In order to realize the energy transition in Taiwan in the future, it is necessary to make overall planning of energy policies, explore the cross-strait power cooperation model, and gradually try to build a cross-strait carbon trading market. [ABSTRACT FROM AUTHOR]

The growing demand for private vehicles associated with the rise in the number of middle-income consumers in Indonesia has led to an enormous energy demand and high-level CO 2 emissions. In order to increase the sustainability in the transportation sector, the Indonesian government has given special attention to electric vehicles as key future solutions to achieve clean and green transport and to improve energy supply security. This paper aims to investigate public perception in relation to the adoption of electric motorcycles (EMs) in Indonesia. We conduct a survey involving 514 participants and find that only 36% of participants agree to adopt EMs as their next motorcycle, and 40% are still in doubt (i.e. neutral). To identify factors influencing EMs adoption, we expand the Theory of Planned Behaviour (TPB) model and analyse the data collected using Partial-Least Squares Structural Equation Modelling (PLS-SEM). The findings show that an adequate perception of EMs, environmental benefits, economic benefits, and incentive policies positively affect the attitude toward the adoption of EMs, which reinforce the results of the previous studies. However, perceived cost and perceived risks appear to be insignificantly influential in our study. Furthermore, factors related to high-behavioural control and support from relatives and closest people are shown to significantly affect the adoption of EMs. This paper also presents the acceptable price range of EMs and the optimal price point (OPP) for segments differentiated by monthly income. All these findings provide valuable insights for the different stakeholders interested in enhancing the adoption of EMs in Indonesia. [ABSTRACT FROM AUTHOR]

Global warming, climate change, and resource depletion have forced us to reconsider energy usage and efficiencies over the last few decades. Residential and commercial buildings are both large energy consumers, so improving energy and material usage efficiency in this sector is a common research topic. According to a recent study, the Building Sector (BS) accounts for 40% of greenhouse gas emissions. The primary objective of this paper is to examine and assess the potential of Renewable Energy Systems (RES) and their combinations for enhancing energy efficiency in the BS. Specifically, the focus will be on converting low energy-efficient buildings into highly efficient ones. The potential of the RES and their combinations for the BS is evaluated based on payback durations, energy generation, and reduction of CO 2 emissions. The optimization flow charts for the RES, feasibility studies, commercialization road maps of energy storage systems and the necessity of control mechanisms for enhancing RES efficiency were discussed. Additionally, the technology drawbacks are discussed, along with various innovative techniques recommended to direct future study in this area. Finally, this article assists the audience clear idea in the selection of the right combination of potential RES based on different conditions to achieve deep decarbonization in BSs. • Buildings sector (BS) responsible for 40% of GHG emissions. • Study assesses potential of Renewable Energy System (RES) in BS. • RES evaluated on payback, energy generation, and CO 2 reduction. • Optimization, feasibility and commercialization studies were discussed. • Article recommends right RES combinations for deep decarbonization in BS. [ABSTRACT FROM AUTHOR]

To perform better future trend prediction for an economy-energy-environment (3E) system and address the shortcomings of traditional multivariate grey models, this paper introduces a spatial correlation term into the multivariate discrete grey model, thus creating the SLDGM(1,n) model, and improves the final calculation of the model according to the priority of new information. The validity of the SLDGM(1,n) model is assessed using data from the 3E system in North China, and the SLDGM(1,n) model is applied to predict the future trends of the 3E system in North China. The following conclusions are obtained. First, the introduction of the spatial correlation term and the improvement of the final calculation method are reasonable; the prediction accuracy of the multivariate grey model is improved, and multiple systems are modeled simultaneously. Second, the SLDGM(1,n) model calculates the spatial spillover effect, and according to the simulation results for North China from 2010 to 2019, Hebei's energy consumption and carbon emissions are subject to the largest influence from other provinces, while its economic development level is subject to the smallest influence, and the carbon emissions of Shanxi and Inner Mongolia are subject to a negative spatial influence effect. Third, the prediction results indicate that under the effect of spatial correlation, the energy consumption of all five provinces in North China will continue to rise; the carbon emissions of Beijing will gradually decline while the carbon emissions of the other four provinces will all gradually rise, and the per capita GDP of the five provinces is expected to increase by more than 50% by 2025. [ABSTRACT FROM AUTHOR]

The Yangtze River Delta region is one of the key areas of energy transition for China's carbon neutrality. The pathways to carbon neutrality are diverse in the regional level due to the different conditions on the energy supply and demand side. How to construct comprehensive assessment index system and evaluate regional pathways to carbon neutrality is an urgent problem to be solved. To fill this gap, this paper evaluates the carbon neutrality pathways of supply-side and demand-side coordination in the Yangtze River Delta region using the Low Emissions Analysis Platform with five scenarios (64 sub-scenarios): Business as usual, energy intensity decrease, energy structure reform, power supply technology innovation and policies mix. The simulation results indicate that: (1) 22 of the 64 sub-scenarios can achieve carbon neutrality by 2060. (2) In energy intensity decrease scenario, an annual 6% reduction in energy intensity could achieve carbon neutrality before 2060. (3) The policies mix scenario can lead to 21 sub-scenarios with pathways to achieve carbon neutrality when the average annual energy intensity decreases by 4% or more. Additionally, the end-use sectors electrification level should reach 64.19% at least by 2060. (4) There can be 14 sub-scenarios to achieve zero carbon emissions in the power plant sector, but annual energy intensity should be reduced by at least 4%. Applying Analytic Hierarchy Process analysis, the article evaluated the 22 sub-scenarios with the index of regional pathways to carbon neutrality. The result shows that the mixed policies of energy intensity reduction, energy structure reformation and power technology innovation can promote the coordination of supply-side and demand-side. This study can provide reference for policymakers to formulate effective policies to realize carbon neutrality. • The coordination of energy supply and energy demand is assessed. • A model with five scenarios (64 sub-scenarios) is developed for carbon neutrality. • Energy intensity drops by 4% or more can lead to multiple carbon neutral pathways. • A comprehensive assessment index of regional carbon neutral pathways is developed. [ABSTRACT FROM AUTHOR]

At present, carbon emissions reduction is a very important challenge all over the world. Improvement of human capital helps to reduce carbon emissions. This paper studies the long- and short-term effects of human capital on carbon emissions in Pakistan from 1971 to 2014. We employ an autoregressive distributed lag model and the vector error correction model to analyze the co-integration and direction of causalities between human capital and carbon emissions, respectively. Results show that a significant long-term relationship exists between human capital and carbon emissions. Improvement of human capital will reduce carbon emissions without decreasing economic growth. Granger causality test results describe the bidirectional causality that exists between human capital and carbon emissions in the long term and no causality in the short term. Human capital and economic growth have feedback effects in the long term and no effect in the short term. The results of this study show that improvement in human capital through education will help carbon emissions reduction in the long term. This study will help policymakers devise a comprehensive strategy to reduce carbon emissions through improvement of human capital. [ABSTRACT FROM AUTHOR]

Greenhouse gas (GHG) emissions cause climate changes, and their impact on the environment continues to increase. As a result, there is an urgent need to accelerate efforts to reduce GHG emissions. In industry, the majority of the current methods of reducing GHG emissions depend on technical enhancements of the facility and equipment. These methods focus on local optimization for carbon emission reduction in enterprises and may require additional time, money and effort for satisfactory implementation. Unlike technical approaches that focus on the equipment, this paper proposes an approach that combines carbon footprint analysis and production planning. The carbon footprint of the entire company’s operational process can be analyzed systematically using this approach. Subsequently, carbon emissions can be reduced significantly through production planning and optimization. To test the effectiveness of the proposed approach, a pharmaceutical enterprise is employed as an example. A production planning model is constructed based on the energy consumption analysis of different units and equipment. Using this model, the carbon emissions of the enterprise can be analyzed, and the corresponding production plan can be developed. To determine the optimal solution, a hybrid discrete particle swarm algorithm is developed and tested based on real data collected from the pharmaceutical enterprise. The experimental results demonstrate that the proposed novel approach is effective and carbon emissions of the enterprise can be reduced by an average of 6.77%, or a reduction in CO 2 emissions of 610.2 tons per year. [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]

In this paper, an integrated process for coproduction of methanol (122500 k g h), desalinated water (40.56 m 3 h), and oxygen (13420 N m 3 h) using landfill gas upgrading is presented. The process embraces negative carbon dioxide (CO 2) emission framework, high thermodynamic efficiency, and low product cost. The proposed process consists of nine subsystems, which are utilized for heat recovery in addition to production of electricity and desalinated water. Results showed that the total energy and exergy efficiencies of the trigeneration system are 59.19% and 48%, respectively. According to the conducted analysis, the total exergy destruction rate equals 973291 kW in which the biogas upgrading unit has an 80% contribution. In addition, it is demonstrated that the combustor of the biogas upgrading unit is responsible for 57.96% of the total exergy destruction rate. Moreover, the sensitivity analysis illustrates that the increase in the H 2 C O 2 ratio is an important factor in increasing the carbon efficiency and total energy efficiency, and decreasing the CO 2 emission. From the environmental perspective, it is deduced that the total net emission of the proposed process is −0.6773 k g C O 2 k g M e O H , which is significantly lower than other methanol production technologies. Economic analysis is performed for the integrated structure and its results showed that the total annual cost and methanol production cost rate are 124,660,373 $ and 0.124 $ k g , respectively. This value is 91.68% lower than the renewable methanol production technology. • Simulation of a novel trigeneration model based on landfill gas upgrading. • Methanol, oxygen, and desalinated water production through nine integrated cycles. • 4E analysis along with a sensitivity analysis. • Negative carbon dioxide emission is found at −0.6773 k g C O 2 k g M e O H . • Total annual cost and methanol production cost rate are 124,660,373 USD and 0.124 $ k g . [ABSTRACT FROM AUTHOR]

With the rise of renewable energy sources (RES) due to detrimental impacts of climate change, the potential for clean energy sources such as hydrogen has gained attention. The development of various technologies, such power-to-gas (P2G) and hydrogen-based energy systems (HES), enables the integration of these systems with conventional ones in this task. This approach will help improve efficiency and resolve the substantial carbon emission problem on the demand and supply sides. This paper focuses on using hydrogen as a primary source of energy and uses wind turbine (WT) and Photovoltaic (PV) as RES. Hot- and chilled water storages besides a HTS are implemented to improve energy efficiency. Upstream grid and hydrogen markets are connected to this system to compensate for the energy deficiency in some periods. P2G functions as a carbon recycling system by reducing carbon emissions and generating extra heat from its chemical reaction for end-users. The proposed hydrogen-based energy system combined with Power-to-gas (HES-P2G) is based on stochastic programming, and takes into account various uncertainties. The nonlinearity in some restrictions is converted using the piecewise linearization technique. The epsilon-constraint method is used as a multi-objective optimization to achieve both economic and environmental goals. The fuzzy satisfying technique is used to obtain a trade-off solution between two objectives. The numerical results show the impacts of using P2G in HES in reducing carbon emission and operating cost. The current HES can significantly reduce carbon emissions; however, using P2G influences environmentally and economically. P2G will thereby cut carbon emissions by 14.2% and operating expenses by 11.7%. [Display omitted] • Multi-objective optimization of a hydrogen-based renewable penetrated multi energy system. • Investigating the impacts of carbon capture system on recycling the carbon emission of system. • Using the scenario-based approach for uncertainty modeling of stochastic resources and loads. • Using the fuzzy-based method for satisfying the objectives and obtaining an optimum point. [ABSTRACT FROM AUTHOR]

Cap-and-trade and carbon tax are the two main policies to reduce carbon emissions. Different from the previous literature and practice, this paper examines the production and transportation outsourcing problems of a two-echelon supply chain under the cap-and-trade policy and joint cap-and-trade and carbon tax policy. Enterprise operations are divided into the order stage and transportation outsourcing decision stage. In the order stage, the retailer sets his order schedule for the manufacturing plant for fulfillment, and in the transportation outsourcing decision stage, the manufacturer decides the optimal freight volume based on energy consumption. Furthermore, we construct a basic model without a carbon policy and two extended models with carbon policies and the optimal solutions of the models are solved. Numerical examples are provided, and the three models are compared. The results indicate that the extended model with carbon policies is more beneficial for emissions reduction, and the effect of emissions reduction gradually becomes smooth as the carbon price increases; the joint cap-and-trade and carbon tax policy is more effective for emissions reduction, especially when the carbon price is lower. These findings will be helpful to policy makers and managers. [ABSTRACT FROM AUTHOR]

This paper examines the asymmetric and long-run effect of energy productivity on the quality of the environment in Finland. Finland, as one of the Nordic countries, is a major contributor to the global drive to achieve decarbonization by 2050. In effect, this study seeks to contribute to the strides by querying the extent to which shocks in energy productivity make or mar the sustainability of the Finland environment from 1990:Q1 to 2019:Q4. The other impacts of financial development, economic growth, and trade openness are considered in the model estimated by using the novel hidden panel cointegration and nonlinear autoregressive distributed lag (NARDL) methodology. The results reveal a significant asymmetric equilibrium cointegration relationship among the variables over long-run time horizons; energy productivity utilization enhances the quality of the environment in Finland over the long run while trade openness, financial development, and economic growth contribute to environmental degradation in Finland in the long term. In particular, a 1% positive and negative fluctuation in energy productivity lowers carbon emissions by 1.79442% and 0.84799% in the long term. Whereas 1% change in trade openness, financial development, and economic growth trigger CO 2 emissions (CO 2 E) by 1.15298%, 0.271365%, and 2.93402% in Finland's economies. The results of the frequency domain causality model corroborate the NARDL results. On the basis of these empirical findings, this study suggests that policymakers in Finland should consider the asymmetric behavior among these variables in setting their trade, environmental, growth, and energy policies. [Display omitted] • The effect of energy productivity on environmental degradation in Finland is examined. • Nonlinear ARDL, Fourier ADL cointegration and frequnecy domain causality tests are employed. • Energy productivity leads to lower environmental degradation in Finland. • Energy productivity causes environmental sustainability at different frequencies. [ABSTRACT FROM AUTHOR]

Machine learning (ML) has been shown to bypass key limitations of traditional methods (i.e., physical testing and numerical simulations) and hence presents itself as an attractive technology in engineering. While the integration of ML brings exciting opportunities, it also introduces unique challenges. One such challenge is related to the heavy reliance of ML on large datasets and computing facilities – for algorithm development, training, deployment, and storage. To realize Green ML (GML), this paper argues that ML users are to be cognizant of the hidden costs of energy consumption and subsequent carbon emissions arising from ML modeling, and hence they are ethically bound to apply ML responsibly. In this pursuit, a series of simple and exotic ML algorithms are examined, and their performance on a relatively large dataset (∼8000 observations) is documented on five fronts; predictive performance, model size, training time, energy consumption, and generatedcarbon emissions. In addition, this work also examines the influence of algorithmic architecture, processing language, number of features, as well as dataset size on model predictivity and energy consumption. Findings from this investigation infer that a 23–99% reduction in energy consumption and carbon emissions can be attained (while maintaining a comparable level of accuracy) by adopting simple as opposed to exotic ML models. The same findings have also led to the development of two new metrics that can tie the predictivity (i.e., level of accuracy) to the amount of energy consumed per algorithm. These metrics can be used to compare model performance in a similar manner to that traditionally used to assess the accuracy of ML predictions, thereby integrating energy-based awareness as a key dimension for model comparison. [ABSTRACT FROM AUTHOR]

In the fight against global climate change, improving energy efficiency and reducing related emissions are critical to mitigating sustainability issues such as global warming. In this regard, technological progress is known to improve energy efficiency and reduce related emissions. However, previous sustainability studies on Africa have paid less attention to energy and emission efficiency convergence among countries, along with the contribution of technological progress to the continent's sustainability. Accordingly, this paper develops a novel framework that assesses energy and emission efficiency convergence, gauges technology inequality, identifies the barriers to technology diffusion, and explores the factors influencing energy and emission efficiency convergence in Africa. The proposed framework incorporates Data Envelopment Analysis (DEA), several economic convergence concepts, a K-means clustering model, the concept of efficiency Gini coefficient, and a group-based inequality decomposition method. We empirically covered 39 African countries from 2006 to 2018. The results show that African countries are, on average, 71.1% energy efficient and 65.3% CO 2 emission efficient, leaving more room for energy saving and emissions reduction. Second, there is strong evidence of convergence in energy and emission efficiencies in Africa. Third, despite the observed convergence process, there is significant heterogeneity between two research groups (i.e., low-and high-efficiency groups of countries) in terms of energy and emission efficiencies, with persistent technology inequality suggesting a lower contribution of environmental technological advancements to the continent's sustainability. Furthermore, cross-group inequality is the primary barrier to technology diffusion. Fourth, regional cooperation accelerates the convergence process in the two efficiency indicators. While economic development, industrial structure, and renewable energy consumption (REC) tend to favor energy and emission efficiency growth, rising foreign direct investment (FDI) and energy prices have a negative impact. Meanwhile, the effects of energy prices, FDI, and REC on emission efficiency are insignificant. Based on our findings, we discussed policy implications to promote energy and emission efficiency convergence and narrow environmental technology gaps. • Convergence in Total-factor energy and emission efficiency in Africa is explored. • Technology inequality across African countries is measured. • There is strong evidence of convergence in TFEE and TFCEE in Africa. • A persistent technology inequality is found among African countries. • Cross-group efficiency inequality is the main barrier to technology diffusion. [ABSTRACT FROM AUTHOR]

Global warming is a serious problem presently faced by human society, and CO 2 is a major concern as a greenhouse gas (GHG), especially as the amount of atmospheric CO 2 has been steadily increasing in recent years. Multi-depot model of vehicle routing has sparked widespread interest among researchers as an effective means of reducing cost comprising carbon emissions, fuel consumption, vehicles rental, and driver salaries. In this paper, we developed an improved adaptive large neighborhood search (ALNS) algorithm to efficiently solve large-scale instances of the multi-depot green vehicle routing problem with time windows (MDGVRPTW), based on the characteristics of the multi-depot model, and the formulation of carbon emissions from customers. For the destroy operation, three problem-specific destroy operators that took advantage of the structure of the multi-depot model and the calculation formula of carbon emissions, were deliberately tailored for the MDGVRPTW. The operators could rapidly remove customers causing significant carbon emissions, which enabled these customers to be better positioned in future repair operations. For the repair operation, a noise-greedy repair operator was proposed to enhance the diversification capabilities of the ALNS. Additionally, two methods for speeding up the repair process were proposed to improve computational time. Computational experiments revealed that the proposed ALNS algorithm exhibited a significant improvement in calculation speed and accuracy compared with existing algorithms. • Multi-depot green VRPTW (MDGVRPTW) to reduce emissions and economic cost is studied. • Improved adaptive large neighborhood search (ALNS) is devised for larger-scale MDGVRPTW. • Three novel destroy operators and two speeding-up repair methods are developed. • Accuracy is improved by 17.94% on average compared to classic ALNS. [ABSTRACT FROM AUTHOR]

Hydrogen-rich gas and steam are widely regarded to be of great potential to mitigate CO 2 emissions in iron ore sintering, these gases can regulate heat distribution in the sintering machines by replacing fossil fuels. However, most sintering machines only use one of the gases as the injecting medium, the potential of this technology has not been developed. In this paper, a multiple gaseous medium injection method contained natural gas and steam was experimentally investigated to solving this problem. Sintering tests were arranged to study the appropriate scheme of coupling injection and its influence on the sintering process, and the flue gas analyzer was used to detect the composition of the sintering flue gas in real time. Better sintering indexes were achieved by injecting the above two gaseous medium when the coke breeze ratio is unchanged, the results show that when 0.8 vol% natural gas is injected into the 4–14min, 0.15 vol% steam is injected into the 10–14 min, and 0.25 vol% steam is injected into the 15–18 min of sintering, the sintering yield increases by 2.42%, and the tumbler index increases by 2.72%. Under the above parameters, the coke breeze ratio can be reduced by 12.99%, the average NOx emissions decreased by 19.5%, and the average CO emissions decreased by 36.96% in the coupling injection interval (4–18min). After calculating the amount of coke breeze and natural gas in the optimal coupling injection sintering, CO 2 emissions decreased by 7.66%, about 17.15 kg/t -sinter. Moreover, the PFR model was used to simulate the associated gas phase reaction after coupling injection which shows H 2 O significantly reduced CO emissions and change the reduction pathway of NO. Generally, sintering fuel consumption and greenhouse gas emissions have also been reduced, providing theoretical support for the change of iron ore sintering energy structure. [Display omitted] • Natural gas and steam coupling injection in iron ore sintering for the first time. • The energy structure is optimized to partial replace fossil fuel with gas-based fuel. • The heat distribution and sintering speed after coupling injecting are analyzed. • PFR model shows the NO reduction pathway will change when steam is present. • CO 2 emission can be reduced by 91400 t/year with coupling injection sintering. [ABSTRACT FROM AUTHOR]

Nowadays, China's economy and energy structure are deeply adjusting to the direction of low-carbonization and non-carbonization with unprecedented efforts. This paper considered carbon emissions and energy endowments, adopted SBM-Undesirable model and spatial Durbin model to calculate the energy efficiency of 30 provinces and municipalities in China from 2015 to 2019 and analyze the direct effect, indirect effect and total effect on energy efficiency of 7 variables. Empirical results show that: Energy efficiency has spatial positive correlation and agglomeration characteristics; The main influencing factor of China's energy efficiency is energy consumption structure; Regions with strong energy endowment bear the environmental pollution cost of energy consumption areas in China; Environment Kuznets Curve (EKC) exists in China, but different provinces and municipalities are distributed in disparate stages; Research and development (R&D) investment only affects local energy efficiency, and has no spillover effect on surrounding areas in China; Foreign direct investment (FDI) has negative impacts on China's energy efficiency, and there is a phenomenon of pollution paradise. The valuable conclusions obtained in this study deepens the insights about the influencing factors of China's energy efficiency under the constraints of carbon emission and energy endowment. Energy efficiency has spatial positive correlation and agglomeration characteristics; The main influencing factor of China's energy efficiency is energy consumption structure; Regions with strong energy endowment bear the environmental pollution cost of energy consumption areas in China; Environment Kuznets Curve (EKC) exists in China, but different provinces and municipalities are distributed in disparate stages; Research and development (R&D) investment only affects local energy efficiency, and has no spillover effect on surrounding areas in China; Foreign direct investment (FDI) has negative impacts on China's energy efficiency, and there is a phenomenon of pollution paradise. [Display omitted] • Energy efficiency has spatial positive correlation and agglomeration characteristics. • Energy consumption structure mainly affects energy efficiency. • Environment Kuznets Curve exists in China. • "Pollution paradise hypothesis" exists in foreign direct investment. • Environmental pollution is transferred to surrounding provinces through resource trades. [ABSTRACT FROM AUTHOR]

Production of mature oil fields emits significant amount of CO 2 related to circulation and handling of large volumes of gas and water. This can be reduced either by (1) using a low-carbon energy source and/or (2) reducing the volumes of the non-hydrocarbon produced/injected fluids. This paper describes how improved oil recovery techniques can be designed to reduce CO 2 intensity (kgCO 2 /bbl oil) of oil production by efficient use of the injectants. It is shown that CO 2 emissions associated with injection of chemicals is strongly influenced by water cut at the start of the project, extent of the water cut reduction, and chemical utilization factor defined as the volume of produced oil per mass or volume of the injectant. As an example, for the oil field considered in this study, 3–8% reduction in water cut can result in 50–80% reduction in its CO 2 intensity. In addition to the incremental oil production with lower CO 2 intensity, the earlier implementation of enhanced oil recovery methods can extend the lifetime of the mature fields if carbon emission cut-offs are applied. In case of CO 2 enhanced oil recovery (EOR), the large storage potential for CO 2 can significantly reduce the overall CO 2 emissions of oil, albeit at a large energetic cost. For CO 2 EOR using CO 2 captured from gas power plants, improving the utilization factor from 2 bbl/tCO 2 to 4 bbl/tCO 2 can reduce the CO 2 intensity of the produced oil from 120 kgCO 2 /bbl to 80 kgCO 2 /bbl (33% reduction). [Display omitted] • Improved oil recovery methods can lead to cleaner production of oil. • Efficient utilization of injectants is key to reduce CO 2 emissions from operations. • CO 2 enhanced oil recovery reduces total CO 2 intensity of oil by 80%. • Cleaner production of hydrocarbon fields extends their lifetime. • Earlier implementation of EOR techniques lowers overall CO 2 footprint of fields. [ABSTRACT FROM AUTHOR]

Compressed air systems have a high energy transfer capacity. They are widely used in the manufacturing industry due to being clean, dependable, and simple-to-use. On the other hand, these systems are among the most significant energy consumers in the manufacturing sector because they are inefficient with high electricity usage and high CO 2 emissions. As a result, all kinds of the energy efficiency enhancements in these systems promote cleaner production by lowering total energy consumption and CO 2 emissions in factories. In this paper, the energy-saving potential and carbon emissions of Compressed Air Systems are investigated using data from in-situ energy audits. A simple set of equations is proposed to calculate the mass flow rate of air leakage. The sound intensity (dB) obtained from ultrasonic flow measurements were used as the input of the equation set. Furthermore, two new Energy Performance Indicators have been proposed to guide energy audit evaluation and continuous monitoring of the energy efficiency of Compressed Air Systems in industrial facilities. The new evaluation criteria "Specific Compressed Air Savings" and "Specific Leakage Savings" provide a comparison tool to help decision-makers with their compressed air system investment decisions. Using the "Specific Compressed Air Savings" and "Specific Leak Savings" parameters, the analysis method is demonstrated for an example industrial plant. The facility's specific compressed air and leakage savings are calculated as 0.0067 TOE/ton and 0.0035 TOE/ton, respectively. [ABSTRACT FROM AUTHOR]

Ammonia is a very important chemical industry product. It has a wide range of applications in refrigeration, energy, and fertilizers, and 80% of ammonia is used as a nitrogen fertilizer. China mainly produces ammonia and urea from coal gasification, which leads to difficult CO 2 capture and high energy consumption. This study proposed a new process for the production of ammonia and urea by coal direct chemical looping hydrogen production process (CDCLTU). The coal direct chemical looping hydrogen production replaces the air separation unit and water gas conversion unit of the traditional coal-to-urea process (CTU), which effectively separates and captures CO 2 and significantly reduces the energy consumption. A model of the CDCLTU was established using Aspen Plus. Parameter optimization, technoeconomic, and environmental analysis were conducted through simulations. The results showed that CDCLTU could completely replace the air separation system that the CTU relies on. Compared with the traditional process, the utilization rate of C increased from 53.46% to 67.95% in the new process. The energy consumption of CO 2 separation and capture was reduced by 97.04%. The CDCLH had a 79.7% energy efficiency in the hydrogen production process and 99% capture rate of CO 2. The total capital investment was dropped by 41%, unit urea production cost dropped by 12.1%, and the payback period dropped from 7.5 to 3.5 years. This paper provides a new direction for clean and efficient utilization of coal resources. [Display omitted] • Proposed a novel coal-to-urea process by chemical looping technology. • Conducted main parameters optimization and performance analysis for the new process. • The new process reduced 97.04% energy consumption of CO 2 separation and capture. • Production cost of the new process is 12.1% lower than that of the conventional process. • The new process achieved 67.95% C utilization rate and 1.39 t/t lower CO 2 emission. [ABSTRACT FROM AUTHOR]

This study uses annual data to detect the nexus between urbanization, energy use, and carbon emissions in a panel of Association of Southeast Asian Nations (ASEAN) countries spanning the period 1980–2009. The study contributes to the increasing empirical literature by investigating the effects of urbanization and detecting causal links between the variables. Results from the Pedroni panel cointegration tests show evidence for the existence of a long-term equilibrium relationship between urbanization, energy use, and carbon emissions for the ASEAN countries. Using the panel fully modified ordinary least squares technique, the effect of urbanization on carbon emissions is further revealed; i.e., a 1% rise in urban population results in a 0.20% increase in carbon emissions. Unilateral short-run causal relationships from urbanization to energy use and from urbanization to carbon emissions have been found by Granger causality tests. Also, the results clearly indicate that in the long term, urbanization together with energy use Granger causes carbon emissions. The paper concludes with main findings and provides recommendations toward rational planning of urban development and energy-efficiency improvement strategies for the ASEAN countries. [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]

The non-metallic minerals industry is the third-largest industrial energy consumer, and it constitutes around 7% of global CO 2 emissions due to the high energy intensity of production processes. Although the substantial improvement of the energy efficiency of this industry in the EU observed since 1995, the energy intensity of this sector is still relatively high. To reach the goals of the Paris Agreement, it is necessary to implement further steps towards the decarbonization of this sector. Previous works do not provide information about research trends in this field or the current development of technologies. To fill this gap, the following research questions have been asked: (Q1) which decarbonization measures are already applied or under development in the non-metallic minerals sector?; (Q2) which of these measures might bring breakthrough to this sector?; (Q3) what is the impact of these measures on costs, energy consumption and GHG emissions? To this end, this paper performs a systematic literature review of GHG emission mitigation options of the non-metallic minerals industry by screening 2964 articles and performing an in-depth analysis of 48 full-text relevant articles following the PRISMA approach. The results show that the carbon capture, utilization and storage (CCUS) is the most popular research topic and has the highest decarbonization potential for the industry (up to 60%). However, more research is needed for the full-scale implementation. Further lowering the clinker to cement ratio to at least 75% is also of major importance, however, it is a mature technology, and not much research is required in this field. Despite the relatively low representation in scientific literature, heat electrification is an unavoidable direction for the industry in the long term, resulting from the global shift towards sustainable energy from renewables. The article also sets directions for future research, especially in terms of further development of the most promising technologies and on the industry transition pathways that would be legally adopted at the international level. • The non-metallic minerals industry constitutes around 7% of global CO 2 emissions. • A systematic literature review of GHG emission mitigation options of the industry. • 2964 articles screened and 48 full-text articles analyzed. • CCS is the most discussed mitigation option, yet not ready for commercialization. • Heat electrification is an unavoidable direction, resulting from the climate policy. [ABSTRACT FROM AUTHOR]

Achieving the peak of carbon dioxide (CO 2) emissions requires a large amount of green and low-carbon investment. Whether the green finance system can efficiently support the capital need for achieving the CO 2 emissions target in the context of the COVID-19 epidemic is a matter of concern. This paper constructs a system dynamics model (SD model) to illustrate the quantitative relationship between the green finance system and CO 2 emissions and introduce the COVID-19 epidemic as a variable to analyze ten simulation scenarios regarding the carbon emissions commitment realization under different green finance and economic growth status. It is shown that: (1) Regardless of the impact of COVID-19, China can meet its commitment by reaching its CO 2 emissions peak in 2030 and realizing a 20% non-fossil energy proportion in 2025; (2) Under the impact of the epidemic, the goal can not be obtained in all energy consumption scenarios when the government expenditure on the environment is low. The target year of reaching CO 2 emissions peak becomes 2033, 2037, and 2040. The results indicate that reducing government expenditure on environment protection makes the CO 2 emissions peak target less likely to be achieved within a given time frame. We also concluded with important policy implications according to the result of the simulations. Overall, this study makes a reference for other economies and researchers to quantitatively predict the interaction relationship between the green finance system and CO 2 emissions in the context of COVID-19, which provides policymakers with insights into a joint power of energy consumption upgrading and green capital guidance. • Providing empirical studies regarding the mechanism of the inhibitory effect of green finance on CO 2 emissions. • Using systems dynamics model to address the missing data problem. • Making solid suggestions under COVID-19 Epidemic. • Building the relationship between the green finance system and CO 2 emissions and making forecasts for "3060" mission result. [ABSTRACT FROM AUTHOR]

Low carbon manufacturing is of growing importance due to the severity of energy shortage and increasing energy costs, as well as a series of environmental problems, i.e., climate change and global warming. This paper investigates the potential of process parameter optimization to minimize carbon emissions during machine processing. A process model of CNC machining is first presented to scope the system boundaries for energy footprint and process efficiency. A multi-objective optimization model is then proposed to explore the impact of cutting speed and feed rate on carbon emissions and processing time. The benefit of the approach is illustrated through a case study of a CNC cylindrical turning process. [ABSTRACT FROM AUTHOR]

The increasing energy and material consumption associated with global economic growth has resulted in the need for more severe efforts at mitigating global climate change. The iron and steel industry consumes 8% of energy and emits 7% of total CO 2 globally. China's iron and steel industry contributes to 15% of that country's total CO 2 emissions. Therefore, there is an urgent need to explore the possibility of net zero emissions in the iron and steel industry in China to meet China's goal of carbon neutrality before 2060. In the study presented in this paper, the MESSAGEix–China iron and steel model was developed by integrating the process-based technology of the sector into the IIASA's MESSAGEix framework to explore zero CO 2 emission pathways and their associated impacts on resources, energy, and water in China's iron and steel industry up to 2100. We found that there are multiple pathways to achieving zero CO 2 emissions in the Chinese iron and steel industry by the end of the 21st century. More specifically, in all the pathways developed in this study, CO 2 emissions decreased significantly between 2030 and 2060 due to the rapid application of 100% scrap-based Electric Arc Furnaces (EAFs) and hydrogen-based Direct Reduced Iron (DRI)-EAFs steel-making technologies. However, by 2060, there will still be 70–360 Mt of CO 2 emissions from China's iron and steel industry; consequently, carbon sink or negative emission technologies are required to offset this and achieve the country's carbon neutrality goal. Furthermore, technologies for achieving zero emissions differ widely in terms of their impacts on the consumption of materials and energy. Compared to the electric (ELE) scenarios, 25–40% of extra iron ore is consumed in the current and new national policy (NPS) scenarios and the DRI scenarios, but 25–220% of scrap is required. At the same time, 20–150% more energy will be saved in the ELE scenarios than in the NPS and DRI scenarios. Finally, we recommend that policy makers design a cross-cutting strategy to achieve zero CO 2 emissions and enhance efforts for material recycling and the provision of clean energy and water. • There are multiple pathways to achieving net zero emissions in China's iron and steel industry. • Steel outputs are essential for reducing CO 2 emissions and conserving materials, energy, and water. • Hydrogen-based DRI and 100% scrap-EAFs technologies are key to achieving zero emissions. • CO 2 mitigation measures have limited impacts on water consumption. [ABSTRACT FROM AUTHOR]

Residential and commercial buildings consume around 40% of the total energy of the world. The building sector is also responsible for 30% of the global greenhouse gas emissions. There is an urgent need to assess the environmental carbon footprint (CFP) of global building industry. This study reviews the related studies and calculates the CFP of a residential building constructed in Turkey by considering the type of construction materials, energy consumption habits, maintenance and demolition stages in a 50 year of life cycle. The CFP of a common type of residential building constructed in Turkey found to be 48.87 kgCO 2 eq/m2/year. The CFP of structural elements used during the construction phase has been calculated to be 6.94 kgCO 2 eq/m2/year, which is about 14.21% of the total footprint. It is investigated that; the operational stage is the foremost contributor, representing 64.11% of CFP. The CO 2 emissions have been decreased by 38.05% by the implementation of basic methods. Unlike other studies, this paper revealed that the CFP from transportation of habitants is 6.5% more than the construction stage contributing 15.13% of overall emissions. The comparative studies of constructions in different countries show that CFP significantly depend on the behavioral factors of citizens of a country and the system boundaries selected. The results exposed that the effects of transportation should not be disregarded in the future studies. [Display omitted] • The total life cycle CFP of the building found to be 48.87 kgCO 2 eq/m2/year. • The CFP of construction materials is calculated to be 6.94 kgCO 2 eq/m2/year. • CFP from transportation of habitants is 6.5% more than the construction stage contributing 15.13% of overall emissions. • The daily energy use of the habitants is the main contributor to the CFP, representing the 64.11% of CFP. • The CFP of the building has been decreased by 38.05% by the implementation of low-carbon strategies. [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]

Advance cooling/lubrication (lubricooling) approaches are getting fame in industry and academia due to their excellent performance. A significant amount of work has been conducted to investigate the effect of various lubricooling approaches on the machinability of the hardened steel. However, sustainability-based performance evaluation of lubricooling assisted machining is missing. Thus, this paper presents 3E-based (Energy, Economics, Environment) analysis to compare the performance of various lubricooling approaches. Initially, preliminary experiments were performed to achieve optimal flow rates of various cutting fluids used in Minimum Quantity Lubrication (MQL), cryogenic cooling, and conventional emulsion (Flood) approaches. Later, optimal flow rates were used to achieve equal cutting-tool life under all machining environments. Results showed that with the same tool life method (STLM), Cryogenic-MQL(CryoMQL) could withstand aggressive cutting speeds and produce the highest productivity among all lubricooling approaches. In addition, it yielded 50% lower-priced specific production cost as compared to dry machining. However, 44.3% more specific-CO 2 emitted in CryoMQL as compared with dry machining. In summary, the hybrid CryoMQL assisted machining process is sustainable economically but not environmentally. The outcomes of the present study provide useful information, and it can help machinist to enhance the process performance. [Display omitted] • Holistic sustainability assessment of hard machining. • New holistic models for energy consumption, CO 2 emission, and cost. • Determining optimal flow rate of cooling/lubrication approaches. • Comparison of energy-conscious advanced lubricooling technologies. • Proposed CryoMQL yielded 50% lower price products. [ABSTRACT FROM AUTHOR]

Increasing energy demand and the rising levels of greenhouse gas emissions have increased the necessity of bioenergy and sustainable energy generation. The sustainable bioenergy supply chain is the key to produce sustainable biofuel. This paper points to render an optimization model for planning a versatile and dependable biomass-to-bioenergy sustainable supply chain network in which crop residuals from several agricultural sectors, multi-transportation disruption modes, multi-biorefineries, multi-biogas plants, and multi-market centers are investigated for two bioenergy sources, namely biofuel and biogas. For this reason, supply chain cost optimization, emissions of feedstock transport, processing, and distributing end biofuel to respective markets are utilized. The multi-setup-multi-delivery (MSMD) concept is incorporated and lead time crashing cost is applied to minimize the lead time in this model. The carbon emission costs at all steps and the variable production rate for the production of bioenergy are included within the model. Finally, one small-scale data and another large-scale data of six agricultural areas, four biorefineries, four biogas plants, and six markets are considered to validate the model's usefulness. The model's goal is to show bioenergy's effect to make a sustainable supply chain of biofuel and biogas. The numerical results reveal that the cost of bioenergy production contributed 54.12%, a major extent of the whole cost in biorefinery and biogas plants. The transportation segment is the preeminent initiator of carbon emissions with 83.33% in the entire carbon emission within the whole supply chain. Although, transportation cost contributed 33.09% of the total cost, the multi setup-delivery-multi-delivery policy minimized the whole supply chain cost. The results provide a systematic guideline for developing a sustainable biofuel supply-chain by minimizing cost, various aspects of transportation logistics, and multi-model alternatives under reduced energy effects. • Energy demand and two approaches of biofuel and biogas production are evaluated. • Reduction of the supply chain network's total cost. • Optimizing allocation of the appropriate quantity of residual biomass and biofuel. • Reducing energy consumption by using variable production rate. • An intelligent logistics system with multi-disruption is addressed. [ABSTRACT FROM AUTHOR]

There are many measures for decarbonisation of maritime transport, however only a few of such measures have been applied in practice. The method for the assessment of the potential energy savings due to the application of antifouling coatings with lower roughness in terms of decrease in fuel consumption and consequently greenhouse emission is proposed within this paper. Using the proposed method, detailed analysis of the potential benefits of the application of antifouling coatings with lower roughness in terms of fuel savings and greenhouse emission reduction is performed for the first time. In addition, an economic analysis related to the implementation of this technical energy-saving measure is carried out. This study quantifies the fuel savings and carbon dioxide emission reduction that can be attained by applying antifouling coatings with lower roughness on the example of crude oil and bulk carriers. The results have shown that 138 t of fuel can be saved per route with a decrease in carbon dioxide emission up to 430 t for the investigated crude oil carrier. Furthermore, 20.4 t of fuel can be saved per route with a decrease in carbon dioxide emission up to 63.6 t for the investigated bulk carrier. In addition, the return on investment related to the application of antifouling coatings with lower roughness varied approximately from 1.5 to 3 years, which is lower than the usual dry-dock period. Based on these findings, it has been shown that antifouling coatings with lower roughness can be applied even for ships sailing at a lower speed, and that notable savings in fuel consumption and carbon dioxide emission can be attained. • A new method for the assessment of potential energy savings is presented. • Energy savings related to the application of AF coatings are quantified. • Significant savings in FOC and CO 2 emission are identified even at lower speeds. • The return on investment varied approximately from 1.5 to 3 years. [ABSTRACT FROM AUTHOR]