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China is the top emitter of greenhouse gases in the world. Pulp and paper industry is one of eight the strictly regulated industries about carbon emission in China. However, estimates of carbon emissions from China's pulp and paper industry have been suffered from remarkable uncertainty. It is summarized that is aroused by the inaccuracy of factors evaluating energy consumption, and the huge gap between the calculation standards for assessing energy consumption in the production process and the actual level recorded in the factories. This paper re-evaluated the carbon emission of China's pulp and paper industry from the perspective of life cycle assessment, and applied more accurate emission factors, taking account of the actual energy consumption of the production process in factories, to estimate the actual carbon emissions in maximum. It is found that the national standards about the energy consumption quota of China's pulp and paper industry is no longer applicable, and the actual energy consumption regulated in the production process is far better than the advanced level given by the national standards. The greenhouse gas emission have been seriously overestimated approximately 12.00%–56.17% by international organizations. • Life Cycle Analysis of the China's pulp and paper Industry is conducted thoroughly. • The pulp flow of China's pulp and paper Industry is analyzed. • Energy regulated in factory is far better than the national standards' required. • Carbon emissions of China's pulp and paper Industry are overestimated. [ABSTRACT FROM AUTHOR]

Direct air capture, an emerging technology, captures carbon dioxide from the atmosphere and has initiated global demonstrations, highlighting the need for comprehensive operational understanding and effective planning methods. To this end, the paper delves into an in-depth analysis of the operational traits of direct air capture and formulates strategic optimization methods. Firstly, this paper analyzes the operational characteristics of direct air capture, examines the operational mechanisms and energy flow interactions of absorption-based and adsorption-based direct air capture, and reviews the current status of engineering demonstrations of direct air capture technology, highlighting the current technological bottlenecks in project applications. Subsequently, the paper proposes a planning and optimization model for direct air capture loads, incorporating subsidy mechanisms, and develops a dual-layer optimization model aimed at minimizing investment and operational costs. Finally, the effectiveness of the modeling and planning methods proposed in this paper is validated through numerical analysis. Furthermore, the reduction potential of direct air capture is analyzed in conjunction with the theory of carbon emissions flow in the power system. This research aims to provide valuable insights and practical recommendations for the design and demonstration of direct air capture projects. • Direct air capture requires green electricity. • Fixed cost subsidies best support direct air capture due to high initial costs. • Absorption-based direct air capture cuts carbon emissions better than adsorption. [ABSTRACT FROM AUTHOR]

With rising global temperatures and complex environmental changes, it has become particularly important to reduce carbon emissions and promote clean energy transition, while energy transition in rural areas is difficult. Environmental regulation, as an important policy enforcement tool, plays an important role in protecting the environment, but its impact and mechanism on the energy consumption transition of rural residents are not clear. In this regard, this paper analyses the impact of environmental regulations on the energy consumption transition of rural residents in 30 provinces in China, using provincial panel data from 2005 to 2021. The main conclusions are as follows: (1) Environmental regulation can significantly promote the transition of rural residents' clean energy consumption, and the mechanism of action shows that environmental regulation can influence the transition of rural residents' energy consumption through the spread of environmental knowledge, technological progress, and the enhancement of residents' health awareness. (2) Heterogeneity analyses showed that the results of the impact of environmental regulations on the rural residents' energy consumption transition differ by geographic region, level of energy consumption, and temperature. This paper hopes to provide experiences and insights for effectively promoting energy consumption transition and upgrading and alleviating energy poverty in rural areas of China. • The energy consumption transition of rural residents in China's provinces is analyzed. • The impact of environmental regulations on rural residents' energy consumption transition is analyzed. • The mechanism of environmental regulation on rural residents' energy consumption transition is revealed. • Heterogeneity results based on the relationship between the two in different scenarios are further assessed. [ABSTRACT FROM AUTHOR]

China's carbon neutrality target requires early carbon decoupling of economic growth. Utilizing the input-output and programming technique, we investigate the carbon mitigation potential of industrial restructuring along with the substitution of non-fossil energy for electric production. Given the constraints of manufacturing stabilization and employment volatility magnitude, this paper finds that industrial restructuring can mitigate carbon emissions by 7.47 %. Besides, non-fossil energy substitution in electric production can strengthen the inhibiting effect, reducing carbon emissions from 7.47 % (currently about 31.5 % for non-fossil power generation) to 28.99 % (about 80 % in the future). This paper also simulates several scenarios for growth rates and estimates the prospective carbon reduction for the fourteenth Five-Year Plan in China. We indicate that the rising share of non-fossil energy is the linchpin to reducing energy-related carbon emissions, which can achieve absolute decoupling if the share of non-fossil energy in power generation reaches 67.1 % under different growth scenarios. This paper argues that carbon-based performance indicators, e.g., carbon intensity and carbon emissions, are more appropriate for local bureaucrats than energy-based ones. We provide valuable implications for the carbon decoupling path. • This paper combines the input-output technique and programming model. • Industrial restructuring can mitigate carbon emissions by 7.47 %. • Non-fossil energy substitution can further amplify the emission reduction effect. • The rising share of non-fossil fuels is the linchpin to achieving absolute decoupling. [ABSTRACT FROM AUTHOR]

With the development of the energy and carbon markets, it has become a trend for multiple virtual power plants (MVPP) that aggregate distributed resources from different regions to participate in market trading through cooperative operation. In order to study the energy-carbon interactions between VPPs and the supply-demand interactions for MVPP and users, this paper introduces a load aggregator (LA) and establishes a cooperative alliance consisting of MVPP and LA. Firstly, a carbon emission allowance allocation and transaction mechanism for MVPP is proposed based on the modified Shapley value method, which considers the impact of energy interactions within the alliance on the carbon emissions. Then, a cooperation model for the MVPP-LA alliance is established based on Nash bargaining theory, and it is decomposed into two subproblems of the maximal alliance benefits and the optimal benefit distribution. In terms of benefit distribution, this paper modifies the bargaining mechanism based on the contribution of each VPP to the alliance benefit. A dynamic penalty factor-based alternating direction method of multipliers (DP-ADMM) is used to solve the two subproblems in a distributed manner. Finally, the validity of the proposed trading mechanism, allocation method and solution algorithm are verified through several cases. • A contribution-based bargaining model is proposed for a fair benefit distribution. • A modified CEA allocation mechanism for MVPP cooperation is proposed. • A combined carbon trading mechanism is developed. • A DP-ADMM is adopted to solve the cooperation problem. [ABSTRACT FROM AUTHOR]

Integrated energy system plays a crucial role in achieving low carbon emissions while supplying multiple loads. As the energy Internet continues to evolve, integrated energy system, acting as a cell-level prosumer, exhibits intricate coupling characteristics between multiple energy flows and carbon flows. This paper presents a flexible planning method based on a unified energy-carbon coupled operation model. It can realize blank-paper planning under multiple energy-carbon flow constraints, that is, jointly optimize equipment configuration and capacity size from scratch. The proposed method combines clustering algorithms and Latin hypercube sampling to generate the operational scenarios for renewable resources and energy loads, enhancing the representativeness and reliability of planning solutions. The results demonstrate that the proposed method can effectively meet the requirements of electricity, cooling and heat loads under different seasonal scenarios. Furthermore, it elucidates the corresponding carbon emission distribution across distinct energy flows of the planned system. Compared with the conventional fixed equipment connected planning method, the more flexible blank-paper planning method can achieve annual economic cost savings of about 7.5 % and reduce annual carbon emissions by 6.7 %. • A unified multi-energy-carbon flows operating-planning model is constructed. • A blank-paper planning for equipment configuration and capacity size is implemented. • An operating scenarios is selected to improve the reliability of planning solutions. [ABSTRACT FROM AUTHOR]

Against the backdrop of addressing the dual challenges of tightening energy constraints and carbon emission reduction, this paper, building upon the construction of an urban-level Energy Trilemma Index, employs a Difference-in-Differences (DID) model to assess the impact of carbon emission right trading policy (CERTP) on the energy trilemma (ET). Key findings include: Firstly, compared to non-pilot areas, the ET in CERTP pilot areas decreased by 1.86 %; the policy's impact persists and is even greater in the long term, reaching 2.84 %. Secondly, CERTP stimulates green technological innovation, improves energy consumption structures, and alleviates ET levels. Furthermore, the study shows that CERTP, as a market-driven energy-environmental strategy, is further enhanced by the regulatory effects of marketization and government intervention. Lastly, the policy's impact is more pronounced in eastern China, resource-based cities, regions with stringent environmental regulations, and areas with high carbon prices. Based on these findings, the paper proposes a series of policy insights, not only aiding in understanding the causal relationship between CERTP and ET but also providing valuable references for designing carbon trading mechanisms to address ET. Importantly, the conclusions offer beneficial guidance for China's energy structure optimization, ensuring energy security and sustainable development goals. [Display omitted] • The energy trilemma index levels of Chinese cities have been calculated. • The impact of carbon emission right trading policy on China's energy trilemma has been analyzed, with a discussion on the short-term and long-term policy effects. • Two intermediary channels through which carbon emission right trading policy mitigates the energy trilemma have been discussed: green technological innovation and the energy consumption structure. • The positive moderating effects of marketization levels and government intervention have been analyzed. • The inhibitory effect of carbon emission right trading policy on the energy trilemma is more pronounced in regions with high carbon prices, in eastern China, resource-based cities, and areas with strict environmental regulations. [ABSTRACT FROM AUTHOR]

Waste-to-energy (WTE) is a technology that converts inexhaustible waste into electricity, thus significantly alleviating energy crisis. Integrating hydrogen storage into WTE provides an effective way to store and utilize surplus electricity from WTE on-site (by producing hydrogen). Additionally, integrating power-to-gas (P2G) into WTE provides an effective way to reduce CO 2 emission from WTE on-site (by producing natural gas). To this end, a novel waste-driven renewable energy system (WRES), which is consisted of WTE, hydrogen storage, and P2G, has been proposed. However, the uncertain waste supply and electrical load markedly interfere with WRES operation. Meanwhile, when WTE, hydrogen storage, and P2G belong to different agents, the collaborative benefit from WRES operation should be rationally allocated among agents for system sustainability. This paper endeavors to achieve WRES scheduling and collaborative benefit allocation for WTE, hydrogen storage, and P2G under uncertainties. Firstly, a temporal relevance based distributionally robust optimization model is proposed for WRES scheduling under uncertainties, in which the possible range of the joint distribution for uncertainties is depicted by data covariance matrices involved ambiguity set. Secondly, collaborative benefit is allocated according to WTE, hydrogen storage, and P2G contributions, in which Gauss-Legendre quadrature formula is integrated with Aumann-Shapley value method to reduce calculation complexity. Finally, simulation results show that 1) the proposed scheduling model guarantees the economic and stable operation of WRES under uncertainties. 2) after considering the temporal relevance, WRES operation benefit is 8.35 % higher, which indicates that the proposed scheduling model has superiority in decision conservatism by introducing temporal relevance to remove impractical distributions in ambiguity set. 3) the proposed allocation model rationally distributes the collaborative benefit according to contributions, and presents lower calculation complexity, e.g., the calculation time is 95.52 % lower than the Shapely value method. This paper provides policy insights to promote widespread application and sustainable operation of WRES. • Collaborative scheduling and benefit allocation are studied for WRES. • Temporal relevance based DRO model is proposed for collaborative scheduling. • Aumann-Shapley value method plus Gauss-Legendre quadrature for benefit allocating. • The proposed scheduling model can reduce conservatism and resist uncertainty. • The proposed allocation model can reduce calculation complexity and keep fairness. [ABSTRACT FROM AUTHOR]

Reducing carbon emissions is a crucial way to achieve sustainable development. Whether the digital economy helps or makes it harder to cut emissions is a matter of debate. This paper proposes a new digital economy index based on the entropy weight method. The two-way fixed effect panel model is used to analyze the data of 30 provinces in China from 2011 to 2021. The results suggest that (1) The digital economy can significantly reduce carbon emissions. (2) Improving energy efficiency and promoting energy structure transformation are two essential mechanisms for carbon reduction in the digital economy. (3) There is heterogeneity in the impact of the digital economy on carbon emissions. The digital economy significantly reduces carbon emissions from coal but does not significantly impact carbon emissions from other sources. Moreover, the emission reduction effect of the digital economy is related to regional energy endowment, intelligent manufacturing level, and industrial agglomeration level. This paper provides new empirical evidence for clarifying the relationship between the digital economy and carbon emissions and provides policy implications for promoting the realization of carbon neutrality goals. • The digital economy can significantly reduce carbon emissions. • Energy efficiency and energy structure are two essential mechanisms. • The emission reduction effects of the digital economy vary by region. • The effect is related to intelligent manufacturing and industrial agglomeration. [ABSTRACT FROM AUTHOR]

Under the trend of global carbon neutrality, the integrated energy system with the characteristics of multi-energy scheduling and gradient utilizing will be widely constructed and applied in the future energy market. For the construction of energy systems in emerging building complex, this paper analyzes the load probability characteristics of regional building complex at the planning stage, and conducts an aggregation analysis of its multiple uncertainties, and obtains the conclusion that the load factor at time t obeys the normal distribution. In order to formulate this uncertainty, this paper combines the case study with the scenario analysis method containing scenario generation and reduction to transform the stochastic programming model into several deterministic models and analyses the discrepancies of the optimization results under different objectives and different load variances. The results show that after considering load-side uncertainty, the total system capacity increases by 7 %, the total investment under the minimum investment objective by 4 %, and the carbon emission under the minimum carbon emission objective by 3 %. In addition, the system needs to pay 32.8 % of the total investment increment to obtain 80 % carbon reduction when adopting carbon emissions as the objective. • Mechanism of IES load uncertainty is illustrated. • Scenario analysis is applied to obtain an easy-to-follow MILP model. • The incremental investment due to uncertainty intensity is calculated. [ABSTRACT FROM AUTHOR]

To achieve a win-win situation among multiple stakeholders within the integrated energy system, this paper proposes a low-carbon scheduling research of integrated energy system based on Stackelberg game under sharing mode. Firstly, an operation framework of integrated energy system based on leader-follower game was established, and a model of integrated energy system operator and user coalition was established considering carbon trading mechanism. Secondly, bi-directional long short-term memory is used to predict the travel data of electric vehicles, and a schedulable capacity model for electric vehicle cluster as shared energy storage was established. Then, an energy trading optimization model based on leader-follower game was constructed for integrated energy system operator and user coalition, and an improved Shapley value is adopted to realize cost allocation within user coalition. Finally, based on the demonstration project of Sino-Singapore Tianjin Eco-City is selected as the research object to make example analysis. The calculation results show this paper can achieve a reasonable benefit allocation among multiple participants, reduce carbon emissions of integrated energy system, and increase renewable energy accommodation capacity. The relevant achievements are a preliminary exploration for an effective mode of sharing economy in integrated energy system. • A low-carbon scheduling strategy of integrated energy system considers Stackelberg game under sharing mode. • A stepped carbon trading mechanism is introduced in the energy price decision of integrated energy system operator. • Bi-LSTM algorithm was used to predict EV cluster data, and Minkowski sum theory was used to get its schedulable capacity. • Everyone in user coalition participants in cooperative game, Individual cost can be allocated by improved Shapley value. • Dichotomy method is used to solve leader-follower game, example uses pilot project of Sino-Singapore Tianjin Eco-city. [ABSTRACT FROM AUTHOR]

Wood drying is one of the most energy-intensive processes in lumber production, and most wood drying kilns rely on combustion for the process heating. Heat pumps are a promising technology for electrifying industrial heating processes, including wood drying. However, the application of heat pumps has been limited, largely due to the long-established popularity and cost-effectiveness of combustion-based technologies. While previous reviews have covered wood drying technologies more generally, this paper aims to bridge the gap between the wood drying and heat pump fields that have largely been investigated separately. This paper reviews the current wood drying process, including standard operating procedures, wood properties, and conventional drying kilns. Then, the current state-of-the-art heat pump wood drying technologies are reviewed, including heat pump cycle options, energy recovery, refrigerant selection, component enhancement, controls, and renewable energy integration. Additionally, other electrically driven technologies that can be combined with heat pumps to improve the efficiency and control of wood drying systems are reviewed. As the electrification of wood drying can significantly reduce global carbon emissions, this review article is a strong foundation for developing innovative systems and components for heat pump wood drying. • Provide an in-depth review of the wood drying industry and standard procedures. • Conduct a review of heat pump dryers in the lumber and related industries. • Discuss advanced heat pump design considerations relevant to wood drying. • Present a robust perspective on future research needs for heat pump wood dryers. [ABSTRACT FROM AUTHOR]

Integrated Energy Systems (IES) play a pivotal role in achieving carbon peak and carbon neutrality goals. However, previous research in IES operation has mainly focused on energy flow constraints, neglecting the impacts of renewable energy output, energy prices, carbon emission, and storage status. To bridge this gap, this paper proposes a Comprehensive Self-Adaptive (CSA) operation strategy as a key component of our two-tier synergistic optimization method, optimizing an IES integrated with Concentrated Photovoltaic/Thermal systems. In the upper-tier capacity configuration, the proposed method considers the full life-cycle carbon emissions of equipment. In the lower-tier operational strategy optimization, the CSA operation strategy automatically adjusts energy generation, utilization, and storage by comprehensively evaluating hourly operating costs, hourly carbon emissions, and hourly storage benefits. Compared to traditional operation strategies and other adaptive methods, the newly developed strategy consistently demonstrates superior performance. When contrasted with separate energy systems, IES operating under the CSA operation strategy markedly stands out, achieving a cost savings rate of 25.87 %, a CO2 reduction rate of 61.54 %, and an electricity matching ratio of 91.24 %. Additionally, the paper explores the performance of the CSA operation strategy across various regions, confirming its feasibility and generalizability under diverse load and irradiance conditions. • An integrated energy system combines CPV/T, ORC, and multi-dimensional energy storage solutions. • A CSA operation strategy holistically assesses costs, carbon emissions, and storage benefits during operation. • A two-tier synergistic optimization method simultaneously addresses capacity configuration and operational strategy. • Comparative studies in various regions to validate the feasibility and generalizability of the CSA strategy and CPV/T-IES. [ABSTRACT FROM AUTHOR]

Dynamic simulation is a powerful tool for accurately evaluating the thermal demands of buildings and assessing the impact of energy refurbishment actions on their final consumption. Conversely, semi-stationary models are widely adopted in commercial applications for its simplified approach, which reduce calculation times, resulting in standardized results showing a certain deviation with respect to the real energy This paper presents the energy and economic comparison between the dynamic simulation and semi-stationary approaches for the calculation of primary energy demand of residential buildings. The semi-stationary method, used by the legislation to calculate the buildings energy label, is based on an energy performance parameter, not representative of the real energy demand. Conversely, an approach based on dynamic simulation provides a more reliable estimation of the primary energy demand. The main novelty of this paper is to numerically prove that the energy and economic savings calculated by means of software based on the current legislation may be overestimated. In this work, the dynamic simulation of the building-plant system is performed by TRaNsient SYstem Simulation (TRNSYS) program. Each building apartment is divided in thermal zones, where the internal heat gains are defined in detail. The semi-stationary simulation of the building-plant system is performed according to the Italian standard UNI TS 11300. The models allow one to evaluate the yearly primary energy demand, along with the energy bill and CO 2 emissions. A specific case study is developed for a residential building located in Naples (Italy). The models are used to calculate the building energy demand for several scenarios, considering different thermal transmittances of the building elements. The results show that the semi-stationary method overestimates of primary energy saving, equal to 64.7 %, with respect to the one calculated with the dynamic approach, equal to 43.2 %. • Semi-stationary and dynamic simulations were compared for residential buildings. • Critical evaluation of energy and economic savings due to the building refurbishment. • Primary energy savings of 65 % and 43 % by semi-stationary and dynamic simulation. • Dynamic simulation is needed within the legal frame of energy efficient buildings. [ABSTRACT FROM AUTHOR]

Faced with the difficult but urgent task of reducing carbon emission intensity, considering urban agglomeration as a fundamental spatial unit for this purpose has become increasingly important. However, as a long-standing and pivotal phenomenon in the development of urban agglomerations, the potential role of spatial functional division in urban agglomerations in reducing carbon emission intensity has been largely overlooked. To fill this gap, this paper explores the relationship between spatial functional division in urban agglomerations and carbon emission intensity, relying on a dataset of 19 urban agglomerations in China. The main results reveal an inverted U-shaped relationship between spatial functional division in urban agglomerations and carbon emission intensity. Spatial functional division in urban agglomerations increases carbon emission intensity in the initial stage; once it reaches a turning point, spatial functional division in urban agglomerations can reduce carbon emission intensity. This conclusion remains robust after conducting various robustness checks and addressing endogeneity concerns. This paper identifies productivity enhancement as an underlying mechanism that shapes this relationship. Moreover, the relationship between spatial functional division in urban agglomerations and carbon emission intensity exhibits heterogeneity based on function types and urban types. These findings emphasize that spatial functional division in urban agglomerations plays a unique role in reducing carbon emission intensity, which offers a new strategy for reducing carbon emission intensity from an individual city level to an entire urban agglomeration level. • An inverted U-shaped relationship exists between SFD and CEI. • Productivity enhancement derived from SFD is a crucial influencing mechanism. • Function types and urban types influence the relationship between SFD and CEI. • Improving SFD adds a novel urban agglomeration-level strategy to reduce CEI. [ABSTRACT FROM AUTHOR]

The energy sector prioritizes innovative clean energy production. This research explores a versatile hybrid solar-biomass trigeneration system, integrating organic Rankine cycle (ORC), a heat pump, and a proton exchange membrane electrolyser. Sustainable and adaptable, it produces electricity, heating, and hydrogen for Indian paper and pulp industries. The study assesses the system's thermodynamic, economic, and environmental feasibility. Initially, parametric analysis and first layer multi-objective optimization (MOO) are performed to select the efficient working fluid and operating temperatures. Benzene outperforms other fluids, achieving an energy utilization ratio (EUR) of 0.27 and exergy efficiency of 75 %. A typical heat requirement of 250 kW for processing 150 kg of paper necessitates collector areas of 3500 m2 and 4500 m2 in Aurangabad and Tiruchirappalli, respectively, and biomass waste of 0.05 kg/s. The combined system performance during day time and night time operation was studied by altering the critical solar radiation, ambient temperature and biomass waste flow rate. The second layer MOO revealed an optimum EUR of 0.25 and exergy efficiency of 9 % at the lowest cost of 33 $/h for biomass waste operation. In comparison to the conventional electricity-powered system, the proposed system would reduce CO 2 emissions by 90 kg/h to 270 kg/h. [Display omitted] • Solar and biomass waste powered systems proposed for paper and pulp applications. • ORC integrated heat pump system for heating, electricity, and green H 2 generation. • Collector area and biomass flow rate are designed for daily paper output of 300 kg. • Benzene is an efficient working fluid, produced 815 kW of heat and 3 kg/h of H 2. • The recommended system reduced CO 2 emissions by 90 kg/h to 270 kg/h. [ABSTRACT FROM AUTHOR]

Growing demand for electricity due to economic development contributes to increased greenhouse gas production, especially CO 2. However, emissions can be limited by enhancing the efficiency of primary energy conversion, such as integrating geothermal energy into coal-fired power plants. Therefore, this paper proposes replacing conventional feed-water heaters with geothermal preheaters to create a hybridized system. This study was based on a numerical model validated at a selected Polish power unit. The model was subsequently calibrated for off-design conditions to facilitate partial load analysis. The obtained characteristics outperformed those of the non-hybrid unit, generating over 18 MW of electric power output. Such an improvement could potentially boost the unit's net efficiency by more than 2.6 %. This enhancement is significant as power units typically operate under part load for approximately 90 % of the time, hence the need to evaluate the performance characteristics of hybridized units in those states. Furthermore, the research outlines the potential decrease in the plant's CO 2 emission factor, with reductions reaching up to 6.5 % under off-design conditions. Based on a gap analysis of the existing literature, this paper's comprehensive partial load evaluation serves as a new addition to research on hybridized systems. • An in-depth analysis of feed-water heaters operation is performed. • Turbine performance calculations for both design and off-design states is validated. • The comprehensive study of hybridized systems integrates three major factors. • Hybrid geothermal-fossil power cycle is vital for specific CO 2 emissions reduction. [ABSTRACT FROM AUTHOR]

To identify the influence of digital transformation on energy consumption, this paper introduces digitalization and energy elements into the multi-sector energy efficiency analysis model. Furthermore, this paper empirically tests the influence of digital transformation on energy efficiency from the micro level. The results show that the digital transformation indeed improves the enterprises energy efficiency, in which enterprises with higher energy efficiency are more affected. The improvement effect of digital transformation on enterprise energy efficiency continues to increase over time. In comparison, digital transformation shows more effective improvement effect on energy efficiency in enterprises that substantive transformation priority, with same group and maturity stage. Mechanism analysis shows that digital transformation can improve the energy efficiency of enterprises by reducing costs, increasing income, improving production efficiency and promoting technological innovation. In addition, the digital inclusive finance, government subsidies, intellectual property protection and service industry opening show positive regulatory effects. This paper proposes that, with the goal of peak carbon dioxide emissions and carbon neutrality, enterprises should actively increase digital investment and strengthen digital management of energy utilization. [Display omitted] • Digital transformation indeed improves the enterprises energy efficiency. • The promotion effect of digital transformation increases over time. • Digital transformation drives efficiency improvement and technological innovation. • Digital transformation contributes to cost reduction and benefit increase. [ABSTRACT FROM AUTHOR]

Carbon emission flow is an effective tool to obtain carbon emission distribution in power systems, which can guide the active carbon reductions of consumers through proper incentive schemes. With the increasing penetration of renewable energy, the existing single-valued carbon emission flow model based on deterministic forecasted power outputs cannot describe the impacts of renewable energy uncertainties on carbon flows. Therefore, this paper mainly focuses on the assessment of the probabilistic carbon emission flow through the power systems considering the impacts of load and renewable energy uncertainties. In this paper, the probabilistic carbon emission flow (PCEF) is innovatively proposed. With the PCEF, consumers can make better energy use plans considering their own risk appetites for carbon emission payment. Firstly, the impact factors of the PCEF are modeled, including load and renewable energy uncertainties and integrated carbon intensity of thermal plants. The uncertainties of load, wind power and photovoltaics are modeled based on a p-box method while the uncertainty of hydropower is modeled based on the multi-state model. Besides, the integrated carbon intensity model of thermal plants are proposed considering the carbon intensity variations during the operating, start-up, and shut-down stages. Furthermore, the probabilistic carbon emission evaluation framework is proposed to assess the probabilistic carbon distribution. In this framework, novel probabilistic carbon indices are defined to precisely characterize the carbon emission situation with probabilistic representations. A solution method based on an adaptive interval point estimation (AIPEM) algorithm is proposed to efficiently solve the developed evaluation problem. Tests on an IEEE-30 node system, and a real provincial power system in China validate the effectiveness and application of the proposed model. The results showed that the PCEF can be a useful tool for obtaining the probabilistic representation of carbon emission flow and guiding the consumers' active carbon reduction in power systems. • Probabilistic carbon emission flow is proposed considering multiple uncertainties. • Integrated carbon intensity model for thermal plants is developed. • A p-box model is used to describe the uncertainties of load and renewable energy. • PCEF can help consumers balance the cost and carbon risk when making decisions. [ABSTRACT FROM AUTHOR]

This paper establishes a multi-objective optimization model for railway heavy-haul trains, focusing on reducing carbon emissions and improving transport efficiency. The model integrates optimization of the route and the vehicle load rate, significantly reducing carbon emissions and enhancing transport efficiency. It addresses the challenges and characteristics of heavy-haul trains, introducing multi-objective optimization problems related to transport carbon emissions and efficiency. Using a pigeon-inspired optimization algorithm, the model considers joint constraints between carbon emissions and transport efficiency objectives. To overcome challenges in multi-objective transportation problems, the paper proposes a forward-learning pigeon-inspired optimization algorithm based on a surrogate-assisted model. This approach calculates the quality of the candidate solution using a surrogate model, reducing time costs. The algorithm employs a forward-learning strategy to enhance learning from non-dominant solutions. Experimental validation with benchmark functions confirms the effectiveness of the model and offers optimized solutions. The proposed method reduces carbon emissions while maintaining transport efficiency, contributing innovative ideas for the development of sustainable heavy-duty trains. [Display omitted] • A model is build for carbon emissions reduction and transport efficiency enhancement. • The model combines route and load rate optimization. • The model achieves carbon emission reductions while improving transport efficiency. • A novel meta-heuristic algorithm for solving the railway heavy-haul trains model. • The proposed algorithm introduces fresh insights for railway heavy-haul trains. [ABSTRACT FROM AUTHOR]

To attain China's target of carbon neutrality by 2060, the implementation of the Energy Consumption Trading (ECT) system serves as an effective approach to improve energy efficiency and mitigate CO 2 emissions. Nevertheless, it is crucial to consider not only the importance of carbon reduction effect caused by ECT system but also the associated cost. Therefore, this paper applies the spatial difference-in-differences (SDID) model to assess the direct and spillover impacts of the ECT policy on the carbon abatement cost, which is measured by shadow price of CO 2 emissions and calculated using SBM-DEA model. Panel data encompassing 279 Chinese cities from 2010 to 2019 are employed for analysis, with additional insights provided through heterogeneity and mechanism analyses. The results show that ECT policy increases the local carbon abatement cost in pilot cities but decreases the cost of surrounding cities. Meanwhile, such a declination effect in neighboring cities with a spatial attenuation boundary of 1000 km. The heterogeneity analysis suggests that the implementation of ECT policy leads to an increase in the carbon abatement cost in cities located in non-Eastern Coastal regions, cities with abundant natural resources and cities with small populations. The mechanism analysis indicates that the ECT policy implementation facilitates the improvement of green technology in the neighboring cities of the pilot project, consequently lowering the carbon abatement cost. Besides, this policy also results in a decrease in the carbon intensity of the pilot cities. Owing to the U-shaped association between carbon intensity and the carbon abatement cost, the policy implementation stimulates an increase in the cost within the pilot cities. • This paper estimates the carbon abatement cost (MAC) using SBM-DEA method. • The SDID model is used to investigate the impacts of ECT policy on carbon MAC. • We test whether green technology and carbon intensity are mediating variables. • ECT policy increases the carbon MAC in pilot cities through carbon intensity. • ECT policy lowers the carbon MAC of adjacent cities through the green technology. [ABSTRACT FROM AUTHOR]

The carbon neutrality agenda requires that carbon lock-in enters an endgame. A well-developed energy system, which is secure, equitable, and sustainable is paramount to getting rid of carbon lock-in and realizing decarbonization. We carry out systematic research to empirically study the possible carbon lock-in reduction effect of energy trilemma based on the instrumental variable-generalized method of moment (IV-GMM) model. We also detect heterogeneous effects in terms of geographical locations and endowments of capital, as well as the impact mechanisms. Moreover, this paper highlights the mediating and threshold role of environmental regulation. We thus get the following conclusions. (1) The paper's primary findings underscore that the continuous increase of energy trilemma exacerbates carbon lock-in and hampers the process of decarbonization; (2) Energy trilemma has a higher stimulating effect on carbon lock-in in provinces that lie in the central region and that have a comparatively low level of physical, social, and human capital; (3) Energy trilemma can also indirectly aggravate carbon lock-in by inhibiting technology innovation and exacerbating carbon emissions intensity; (4) The interaction of environmental regulation and energy trilemma can alleviate the energy trilemma - carbon lock-in nexus, and environmental regulation also shows a significant threshold effect. • We investigate the impact of the energy trilemma on carbon lock-in. • Energy trilemma eradication is an effective way to realize the carbon lock-in endgame. • The nexus between energy trilemma and carbon lock-in is more prominent in provinces with high capital endowments. • Environmental regulation shows significant mediating and threshold effects. • The exacerbate carbon lock-in effect of energy trilemma depends on technology and intensity effect. [ABSTRACT FROM AUTHOR]

Transition to carbon-neutral energy generation is a reality, and great efforts are being made in this direction in the last years. Ammonia is a promising carbon-free fuel, and it can be used as a gas turbine fuel in existing power generation cycles without significant modification. This paper considers various aspects of the use of ammonia as a gas turbine fuel: it provides a review of existing ammonia-fired gas turbines and conducts a study of the prospective technology of using ammonia via thermochemical transformation into hydrogen-rich gas. Moreover, this paper considers on-board hydrogen production technology via thermochemical ammonia transformation. The ammonia fired chemically recuperated gas turbine is analyzed for which the thermal efficiency can be increased up to 5%–7% comparing to traditional gas turbines. Moreover, hydrogen-rich fuel with a hydrogen mole fraction up to 75% is used as a fuel, leading to more stable combustion with lower NO x emission up to 6–10 ppm. Additionally, an approach to on-board hydrogen production from ammonia via the utilization of solar energy is investigated. It is shown that solar energy can replace up to 25% of heat obtained via ammonia combustion. The paper discusses future perspectives in investigations for ammonia-fired gas turbines with on-board ammonia transformation. • Ammonia as a gas turbine fuel with zero CO 2 emission. • NH 3 containing blends show the better combustion and emission performances when pure NH 3. • Thermochemical ammonia transformation as an on-board hydrogen production system is considered. • Use of exhaust gas for ammonia decomposition leads to an increase in efficiency up to 7%. • Use of solar energy for ammonia decomposition can decrease the ammonia consumption up to 25%. [ABSTRACT FROM AUTHOR]

The specific CO 2 production of fuels has commonly been expressed empirically in terms of kg CO2 (kWh)−1. No specifications regarding combustion conditions, transformation technology used, and efficiency are usually presented in detail. In this paper, however, we propose replacing this approach by the use of rigorous chemical engineering calculations based on the composition and the combustion conditions of the fuels. The MS EXCEL program, which is provided as supplementary material to this paper, calculates the specific CO 2 production considering energy losses, adiabatic flame temperature, calorific value and heat of fuel combustion, flue gas temperature, energy losses through flue gas, slag, and the overall energy efficiency of the whole energy conversion process. Results are presented for three fuel groups: coal, hydrocarbons, and renewable fuels. The calculated results are compared with the literature data. A benefit of our approach is that the procedure can be generalized for any fuel of known composition and for different types of combustion-based energy transformation. • Techno-economic energy strategies require accurate knowledge of CO 2 emissions. • The attached chemical engineering program in EXCEL provides the necessary data. • Fuel type and combustion conditions affect CO 2 emission per kWh. • The overall efficiency of various energy production processes was calculated. • The estimated and observed overall efficiencies are in good agreement. [ABSTRACT FROM AUTHOR]

Industrial chain structure optimization and digital transformation are crucial factors for achieving carbon emission reduction goals. Based on China's non-competitive input-output tables, this paper constructed industrial chain panel data using the structural path analysis method. We explored the influence of industrial chain division (ICD) on CO 2 emission intensity through panel fixed effects model, and examined the moderating effect of digitization. The research found that: (1) The ICD can significantly reduce CO 2 emission intensity, the results are robust after some endogeneity tests. (2) The emission reduction effect brought by ICD will be more obvious in high-stage, high-energy consumption, and high-intelligence industrial chains. There is still room to improve the emission reduction brought by the division network effect. (3) Digitization plays a positive moderating role on this effect. Furthermore, digital manufacturing and digital services exhibit heterogeneity in various types of industrial chains. (4) The ICD can reduce carbon emission intensity through pathways such as intelligent transformation, technological innovation, and energy efficiency, and digitization has positively moderated these impact pathways. Based on research results, targeted policy suggestions are provided for optimizing industrial chain structure and promoting digital transformation. • This paper constructed industrial chain carbon emission intensity panel data. • This paper assessed the industrial chain digitization by digital intermediate input. • This paper constructed industrial chain synergistic division (ICSD) index. • This paper explored the influence of ICSD on CO 2 emission intensity. • Digitization plays a positive moderating role on carbon emission reduction effect. [ABSTRACT FROM AUTHOR]

The transportation sector is deemed one of the primary sources of energy consumption and greenhouse gases throughout the world. To realise and design sustainable transport, it is imperative to comprehend relationships and evaluate interactions among a set of variables, which may influence transport energy consumption and CO 2 emissions. Unlike recent published papers, this study strives to achieve a balance between machine learning (ML) model accuracy and model interpretability using the Shapley additive explanation (SHAP) method for forecasting the energy consumption and CO 2 emissions in the UK's transportation sector. To this end, this paper proposes an interpretable multi-stage forecasting framework to simultaneously maximise the ML model accuracy and determine the relationship between the predictions and the influential variables by revealing the contribution of each variable to the predictions. For the UK's transportation sector, the experimental results indicate that road carbon intensity is found to be the most contributing variable to both energy consumption and CO 2 emissions predictions. Unlike other studies, population and GDP per capita are found to be uninfluential variables. The proposed multi-stage forecasting framework may assist policymakers in making more informed energy decisions and establishing more accurate investment. • An interpretable multi-stage forecasting framework is proposed. • The drivers of energy consumption and CO2 emissions in UK's transport sector are identified. • A comprehensive comparison between different machine learning models is carried out. • The impacts of feature selection methods on machine learning models are investigated. [ABSTRACT FROM AUTHOR]

It is increasing crucial to improve the sustainable use rate of energy and contribute to carbon neutrality and environmental footprints reduction. This work features cutting-edge selected extended papers and developments that were presented at the 25th Conference on Process Integration, Modelling and Optimization for Energy Saving and Pollution Reduction, held on 5–8 September 2022 in Bol, Croatia. More than 400 papers were accepted and presented at this conference. Out of these papers, the 45 contributions in this Virtual Special Issue represent a selection of the most cutting-edge developments in the topic of the Sustainable Use of Energy Contributes to Carbon Emissions Neutrality and Environmental footprint reduction. This paper provides a review of these contributions and above, and groups them into four research themes: (1) Energy Conversion, Storage, Recovery and Efficiency Improvement, (2) Energy Management, Planning and Optimization, (3) Energy, Environment and Economy, and (4) Heat Transfer, Heat Pumps and Heat Convection. [ABSTRACT FROM AUTHOR]

In this paper, 41 prefecture level cities in the Yangtze River Delta (YRD) are selected as the research objects. Based on the semantic mining model, the policy data information from three dimensions namely national, provincial and municipal levels is integrated to build data-driven multiple scenarios. Then the long short-term memory neural network optimized by particle swarm optimization (PSO-LSTM) is further used to predict the peaking time of the YRD urban agglomeration under multiple scenarios. The results show that the YRD urban agglomeration as a whole can achieve carbon peaking on time under all three simulation paths, but the peaking situation of specific cities within the region will be significantly different due to differentiated policy orientations. Under the business as usual scenario, some cities in the north of the region cannot achieve carbon peaking by 2030. Under the stable growth scenario, more cities cannot achieve carbon peaking on time. However, under the low carbon scenario, all cities within the region can achieve carbon peaking by 2030. Therefore, when exploring effective carbon peaking paths, adopting more stringent policies and measures to limit carbon emissions can help achieve the regional carbon peaking goal earlier, ensure that all cities within the region can achieve carbon peaking on time, and can also narrow the gap between cities within the region in terms of peaking time. This paper explores a new scenario analysis parameter setting and carbon emission prediction method, which overcomes the subjectivity of current scenario analysis research in parameter setting to a certain extent, and also provides a scientific reference for predicting the diversified development trend of carbon emission. • The semantic mining method is used to determine the scenario parameters. • PSO-LSTM is used to improve the accuracy of carbon emission prediction. • Multiple scenarios of carbon emission development trends. • Differentiated emission reduction paths for cities. [ABSTRACT FROM AUTHOR]

To reduce the greenhouse gas emissions of the transport sector, synthetic fuels based on CO 2 and H 2 are one viable option. This paper evaluates the integration of a Fischer Tropsch process into a pulp mill to improve efficiency and to lower CO 2 emissions. Different syngas preparation technologies, plant sizes, and gas loop designs are considered. The processes were simulated with a chemical process simulation software to retrieve mass and energy balances. Based on the simulations, the processes are evaluated regarding economics, CO 2 emissions, and efficiency indicators. The Power-to-Fuel efficiency reaches almost 40 % for closed loop configuration with reverse water gas shift reactor for carbon monoxide production. For the open loop configuration the efficiency is tremendously lower. In closed loop configurations, the carbon efficiency reaches 80 %. The levelized cost of syncrude ranges from 3.28 to 7.69 €/kg. The most important impact on syncrude price comes from electricity price, investment cost, and efficiency of water electrolysis. Integrating the Fischer Tropsch process into the pulp mill shows advantages in terms of Power-to-Fuel efficiency and CO 2 emissions but not necessarily in terms of economics. • Integration in terms of mass and energy exchange between pulp mill and Fischer Tropsch process. • Investigation of different plant sizes, syngas preparation routes and gas loop designs of the Fischer Tropsch process. • Levelized cost of syncrude ranges from 3.28 to 7.96 €/kg. • Beneficial effects of the integration into the pulp mill: CO 2 emissions and Power-to-Fuel efficiency. [ABSTRACT FROM AUTHOR]

The current single energy storage approach and market incentives do not fully exploit the potential of diverse energy storage methods and market incentives. Additionally, the traditional operation method often results in a poor alignment between energy supply and demand. Moreover, the conventional solution algorithm struggles to address complex problem-solving involving multiple variables. To address these issues, this paper proposes an improved carbon-neutral energy system (ICNES). Firstly, ICNES enhances residual energy utilization by implementing dual-layer residual power and heat treatment. Secondly, to enhance the effectiveness of market incentives, ICNES incorporates an improved approach that combines a dual-layer carbon capture drive, step carbon penalty, carbon reward, and green certificate trading. Thirdly, to improve the supply–demand matching, ICNES introduces a dynamic hybrid operation approach (DFHL). Finally, the paper proposes a honey badger-pattern search algorithm (HB-PSA) to optimize the configuration of ICNES for the DFHL multivariate scenario. Results indicate that compared to conventional carbon-neutral energy systems, ICNES reduces annual operating costs by 6.686%, CO 2 emissions by 9.538%, primary energy consumption by 12.826%, and energy waste rate by 17.465%. Furthermore, HB-PSA increases the optimization rate from 48.693% to 53.88% of the local optimum. • Dual-layer residual electric and residual heat treatment system is proposed. • Dual-layer carbon treatment for carbon neutrality and carbon profitability. • Carbon markets and green certificate are used in carbon-neutral energy system. • Dynamic hybrid operation to improve the matching of supply and demand. • A honey badger-pattern search algorithm is proposed for solving. [ABSTRACT FROM AUTHOR]

Zero-energy buildings usually achieve annual net-zero energy balance by generating electricity using on-site renewable energies and interconnecting with the power grid. However, the impact of energy mismatch problem in zero-energy buildings design on the grid is often overlooked, which potentially compromises grid's stability. To address this issue, this paper presents an optimization design method based on "grid-friendly interaction" which optimizes the energy system of zero-energy buildings to ensure better alignment between the building's electricity purchase/sale and grid demand. In this study, an indicator of "grid-friendly interaction", which represents the ratio of the net building friendly interaction power to the total annual interaction power, is firstly established to guide buildings in improving their interaction with the grid. Next, the energy supply, demand, and storage schemes of renewable energy systems in the zero-energy building are iteratively adjusted to achieve the best match with grid's expectations. This optimization design method was applied to a practical case in Hong Kong. Results show that, compared to the benchmark building, the optimal system design scheme increases grid friendliness by 83 %, reduces carbon dioxide emissions by 77 %, but also incurs a total cost increase of 180 %. The optimization design method proposed in this paper can effectively mitigate the impact of zero-energy buildings on the power grid, fostering enhanced interplay between the building structures and the grid. The study significantly contributes to the advancement of exploring the potential for energy flexibility in zero-energy buildings, which is of great significance for the safe and stable operation of future grids. The purpose of this study is to explore the energy flexibility potential of zero-energy buildings, which is of great significance for the safe and stable operation of future grids. • A novel indicator that reflects the degree of friendly interaction is proposed. • An optimization design method based on "grid-friendly interaction" is presented. • Single-objective and multi-objective optimization are applied respectively to ZCB. • It is of great significance for the safe and stable operation of future grids. [ABSTRACT FROM AUTHOR]

Electricity cross-subsidy policies have long been criticized for they involve subsidizing households by charging above-cost prices in industrial sectors. This paper examines the environmental and economic impacts of phasing out cross-subsidy in electricity prices in the context of China's Carbon Peaking and Neutrality goals by exploiting a large panel data from 2012 to 2020. We first adopt a price-gap approach to calculate the scale of negative cross-subsidy in China and different sectors. Next, we estimate the electricity demand price elasticity of high-, medium-, and low-emission industries to evaluate how the cross-subsidy affects electricity consumption, carbon emissions, and the output value. Finally, with the 2020 scenario as our baseline, we simulate three distinct policy change Schemes and evaluate the environmental and economic effects of phasing out electricity cross-subsidy in China. We find that if policy makers do not consider the emission levels of different industries when implementing cross-subsidy removal, great environmental harm will be caused. We also find that the potential burden on households of electricity cross-subsidy removal is likely to be relatively small at all implementation stages. This study provides timely policy implications for the ongoing electricity system reform in China. • This paper examines the environmental and economic impacts of phasing out cross-subsidy in electricity prices in the context of China's Carbon Peaking and Neutrality goals. • We find that if policymakers do not consider the emission levels of different industries in cross-subsidy removal, it will lead to large carbon emissions but small output in average. • If the cross-subsidy is fully borne by high-emission industries, the optimal Scheme is to reduce the cross-subsidy by approximately 50%–70% to obtain more economic output and less carbon emissions. • If high-emission bear twice as much cross-subsidy as the medium-emission industries, the carbon reduction and economic output will be maximised at 10%–30% of cross-subsidy removal. • We also find that the potential burden on households is relatively small at all implementation stages. [ABSTRACT FROM AUTHOR]

Whether renewable energy consumption is beneficial to reducing CO 2 emission intensity and carbon emissions in the context of the goal of "carbon peak and carbon neutrality" in China. To prove this conjecture, considering the spatial spillover effect of carbon dioxide, this paper adopts the spatial Dubin model for empirical analysis based on the panel data of China's 30 provinces over the period 2002–2019. This study explores the CO 2 intensity mitigation effect of China's renewable energy consumption and further investigates the mediation role of technological innovation, industrial structure upgrading and optimization, and energy efficiency in the nexus between renewable energy consumption and carbon intensity. The main findings present that: (1) China's carbon emission intensity is characterized by significant spatial correlation; (2) Renewable energy consumption can significantly reduce carbon intensity and per capita carbon emissions; (3) The mediation effect of renewable energy consumption in reducing carbon emission intensity is to promote technological innovation and industrial structure upgrading, as well as improve energy efficiency. Based on the conclusions, this paper offers several policy implications for governments to reduce CO 2 emission intensity. • The impact of renewable energy consumption on CO 2 emission intensity is explored. • Renewable energy consumption can reduce carbon emission intensity and per capita carbon emissions. • Renewable energy consumption reduces CO 2 intensity through the spatial mediation effect. [ABSTRACT FROM AUTHOR]

For energy conservation, emission reduction and sustainable development, China launched the New Energy Demonstration City Program (NEDC) to try a more decentralized energy governance structure. Based on the theoretical framework between NEDC and carbon emissions, this paper tests its policy impact and mechanism. The results show that NEDC can significantly reduce carbon emissions by about 15.34%. The policy effects of NEDC are characterized by time lag and increasing intensification. NEDC has a stronger effect on reducing carbon emissions in western cities and non-resource-based cities. NEDC can reduce carbon emissions through industrial structure effect, environmental decentralization and information technology effect. NEDC has a synergistic emission reduction effect, which can reduce about 20.39% of nitrogen oxides (NOx) and 18.70% of sulfur dioxide (SO 2). NEDC has policy spillover effect, which can not only reduce the carbon emissions of pilot cities, but also reduce the carbon emissions of neighbouring cities. The space emission reduction effect of NEDC is better within 400 km. Finally, this paper puts forward policy recommendations to strengthen decentralized energy governance to reduce carbon emissions. • NEDC can reduce carbon emissions, which has the characteristics of hysteresis. • Central cities and non-resource-based cities have greater policy effects. • Industry, environmental decentralization, and technology are policy paths. • NEDC has synergistic emission reduction effect, which can reduce NOx and SO 2. • NEDC has spillover effect when the distance is not more than 400 km. [ABSTRACT FROM AUTHOR]

The coordinated operation and management of energy and carbon emissions in an integrated energy system (IES) can effectively promote overall energy efficiency and reduce carbon emissions. However, allocating carbon emission responsibilities between transmission-level integrated energy system (TIES) and regional integrated energy system (RIES) is difficult. On the basis of carbon emission flow theory, a model for allocating carbon emission responsibility for IES is developed in this paper. Moreover, the Shapley value method is adopted to obtain the carbon emissions responsibility intervals at the RIES. A dynamic tiered carbon pricing methodology is proposed for the RIES on the basis of equitable carbon emission responsibility intervals. In addition, a bilevel coordinated operation model that imposes carbon price to more fully excavate the low-carbon benefits obtained from operating an IES is proposed. The upper-level model, namely, the TIES, explores the optimal low-carbon schedule for energy networks by imposing fixed carbon price on the energy production costs. The lower-level model, namely, the RIES, investigates the optimal low-carbon energy supply scheme of multienergy coupling equipment and imposes dynamic tiered carbon pricing to adjust the amount of electricity and natural gas consumed. After the whole bilevel model is solved iteratively, equilibrium is reached. Case studies verify the potential and efficacy of the proposed bilevel model, demonstrating superior effectiveness in reducing carbon emissions compared with existing methods. • A carbon emission responsibility allocation model for Transmission-level multiple-energy systems (TMESs) and Distribution-level multiple-energy systems (DMESs) is proposed. • A carbon emission responsibility intervals model for DMESs is developed using the Shapely value method. In addition, a dynamic tiered carbon pricing methodology is proposed for DMESs based on equitable responsibility intervals of carbon emission. • A bilevel coordinated optimization model that incorporates carbon prices is developed to investigate MESs' low-carbon benefits under the proposed carbon emission responsibility allocation model of MESs. [ABSTRACT FROM AUTHOR]

This paper uses a multi-energy complementary system composed of thermal, wind, photovoltaic power generation, and electric energy storage units to participate in four market mechanisms and construct the optimal scheduling model of these trading mechanisms. These four mechanisms are carbon emission trading, green certificate trading, these two trading that are not joint, and joint. Under the latter two mechanisms, the excess carbon emissions of the system can be reduced to 9258t, and the utilization rate of renewable energy can reach 100 %. However, the operating costs under the fourth mechanism are 9695.80 $ lower than the third one because 5947 pieces of green certificates are converted into carbon emission rights. When the carbon price rises, the cost of the fourth mechanism increases slower than that of the third mechanism. The conversion volume of green certificates increases from 5947 to 10947, and the cost difference between the two increases to 67558.33 $. When green certificate prices rise, the cost under the fourth trading mechanism decreases faster. As that cost steadily declines, the carbon emission rights are converted into 907 green certificates, and the cost difference between this and the third mechanism increases to 4695.52 $. • A new trading mechanism combining carbon emission trading with green certificate trading. • Green certificates can be converted into carbon emission rights to participate indirectly in the carbon emission market. • Volumes entering both markets are reallocated to cope with price fluctuations. • High renewable energy utilization and low carbon emissions can be achieved. • The operating cost of the responsible entity is reduced. [ABSTRACT FROM AUTHOR]

As a mature technology for utilizing surplus exhaust pressure energy, turbo-compounding can significantly redistribute multigrade waste heat in marine two-stroke engines. This paper aims to provide a comprehensive thermodynamic study and design criteria for the combined organic Rankine cycle (ORC) and turbo-compounding system. Firstly, the turbo-compounding system applied to the 6EX340 two-stroke engine and ORC systems designed with double-source and three-source configurations are described. The thermodynamic performance of ORC systems using four working fluids is then analyzed, followed by a thermodynamic and environmental assessment of various combined systems. The results show that utilizing the power turbine bypass results in an additional 10.5 % increase in exhaust energy at the rated condition, while the scavenging air waste energy decreases by around 26.4 % compared to the base engine. For the base engine, the three-source ORC using R245ca shows the greatest potential with a 5.4 % improvement in fuel economy, a CO 2 emissions reduction of 579.7 t, and a payback period of 7.4 years. Further combined with a power turbine, the double-source ORC using toluene as the working fluid outperforms the three-source ORC, resulting in a 9.3 % improvement in fuel economy, a CO 2 emission reduction of 950.6 t, and a payback period of 4 years. • The influence of the power turbine bypass on the waste energy distribution was quantified. • Thermodynamic performance of the organic Rankine cycle system recovering multigrade waste heat was investigated. • Fuel-saving potential of different combined cycle power plants was studied. • The design criteria for the combined system was provided. [ABSTRACT FROM AUTHOR]

The extensive use of non-renewable energy sources in agriculture and associated unsustainable practices have contributed greatly to climate change issues. Africa's lack of green initiatives has exacerbated environmental pollution in the last decade. In that regard, this study investigates the transformative impact of green investment on carbon emissions in agriculture fueled by dependency on non-renewable energy use in the sector. It utilizes advanced econometric techniques, including dynamic ordinary least squares, fully modified ordinary least squares, and the causality tests to conduct a rigorous analysis. The findings reveal a concerning rise in agricultural pollution via crop and livestock production. However, green investment is found to have a positive impact on carbon dioxide emissions, hence a potent tool for significantly reducing carbon emissions. The causality analysis unveils a bidirectional causal relationship between green investment and agricultural pollution and a unidirectional causality between green investment and carbon emissions, shedding light on the complex interplay between these variables. Also, non-renewable energy is found to increase carbon emissions in the region. The outcomes of this research contribute valuable insights and lay a foundation for future research and policymakers to enhance the future of agricultural research and sustainability. It also offers a roadmap for developing effective policies that balance the immediate needs of the agricultural sector with the imperative of long-term environmental sustainability. Finally, it has a global significance on the relevance of green initiatives to boost sustainable agriculture and reduce pollution. • Non-renewable energy use has exacerbated agricultural pollution in West Africa. • The mechanism of green investments, energy use, and CO 2 emissions is assessed. • An increase in Green investment helps to reduce agricultural pollution. • The paper provides valuable insights into environmental pollution mitigation. [ABSTRACT FROM AUTHOR]

More than 130 countries and regions have put forward various climate goals, which makes carbon-oriented energy system planning a heated topic. However, these planning studies do not consider the carbon fixation role played by forest carbon sinks (FCSs). To take advantage of the carbon fixation role of FCSs, this paper will develop a carbon-cycle integrated energy hub (CC-EH) model to quantify the economic advantages of FCSs in planning a zero-carbon energy system, where energy flow and carbon flow are both analyzed. A total planning and operating costs minimization with the constraints of CO 2 emissions is proposed as a mixed integer nonlinear programming (MINLP) optimization model and the overall problem is solved based on commercial solver. The proposed model is validated by case studies on six medium to large-size cities in different geographical locations in China. Results indicate that the typical cities in China can fulfill their carbon-neutral commitments by 2060. Throughout the entire planning period, FCSs can offset up to 55.31 % of the total carbon dioxide emissions from urban energy systems. Besides, FCSs achieved by forestation will help the energy system to reduce up to 36 % of the planning cost compared to the case without using FCSs. [Display omitted] • Forest carbon sink (FCS) is modeled considering CO 2 absorption and biomass growth. • FCS is applied to planning through a carbon-cycle integrated energy hub (CC-EH) model. • Coupling of energy system operation and FCS process on an hourly scale is realized. • A power function is introduced to characterize the transition path, and determine the optimal capacity of the CC-EH. • Typical cities in China are taken for case studies to analyze the impact of FCSs on the carbon neutral. [ABSTRACT FROM AUTHOR]

Seaports are significant energy consumers and sources of carbon emissions within the maritime industry. To address this problem, an energy hub (EH) can be established as an intensive energy interconnection center. This paper proposes a carbon emission flow (CEF) model based on the energy hub in seaport, which monitors the carbon emissions generated by the internal energy conversion unit operating within the hub. Additionally, a carbon integrated energy pricing strategy based on non-cooperative game theory is proposed. Based on duality theory and gradient descent method, an iterative algorithm is designed to seek the global optimal solution satisfying the Nash equilibrium point. The aim of the strategy is to encourage seaport energy consumers to adjust their energy consumption strategy according to the optimal benefits and reduce carbon emissions. A comparative study of three different strategy cases are conducted to evaluate the effectiveness of the proposed strategy. Numerical simulation results show the reduction of the total energy consumption and carbon emissions of the system, which is conducive to realizing the low-carbon operation of the seaport energy system. • The carbon emission flow in seaport energy hub is integrated into the pricing model. • A non-cooperative game theory is used to determine the energy price. • An iterative algorithm is developed to search for the Nash equilibrium solution. • A novel carbon energy integrated pricing strategy for consumers is proposed. • The total energy consumption and carbon emissions of the system are reduced. [ABSTRACT FROM AUTHOR]

Due to the imperative to reduce carbon emissions, NH 3 -H 2 mixed combustion has garnered significant attention. However, the knowledge of the reaction kinetics of NH 3 -H 2 -O 2 mixtures at the molecular level remains limited. In this paper, the reactive force-field (ReaxFF) method was employed to study the microscale reaction kinetics of the NH 3 -H 2 -O 2 mixture with varying hydrogen ratios (HR). The results of the microcanonical ensemble simulations indicated that the addition of H 2 significantly increased the combustion performance of NH 3. However, H 2 did not change the two primary reaction paths of NH 3 oxidation (NH 3 → N 2 H 2 → N 2 and NH 3 → NO → N 2). The addition H 2 not only led to a shift in the initiation reactions from NH 3 -O 2 to H 2 -O 2 reactions, but also notably enhanced the concentration of HO 2 and OH radicals (e.g., O 2 + H 2 → HO 2 + H), which accelerated the extraction of H from N x H y and subsequently facilitated the immediate formation of N 2. Furthermore, the ignition delay decreased from 120 ps to 40 ps, and the activation energies decreased from 295.46 kJ/mol to 162.12 kJ/mol as HR increased from 0 to 0.3 under the equivalence ratio of 0.4. These key findings can guide the development of clean NH₃ combustion technology. • Reaction kinetics of NH 3 -H 2 combustion were conducted by ReaxFF-MD. • In NH 3 -H 2 -O 2 systems, H 2 -O 2 reactions were the main initiation reactions. • The addition of H 2 did not significantly alter the oxidation path of NH 3. • H 2 introduced more radicals such as HO 2 and OH to promote NH 3 oxidation. • The addition of H 2 reduced the ignition delay and activation energy. [ABSTRACT FROM AUTHOR]

The industrial sector contributes significant environmental impact due to greenhouse gas (GHG) emissions. It is necessary to investigate the energy flow from resources, and the possibilities for lowering energy use through energy management. Energy modeling and visualization have been identified as effective and powerful methods for investigating energy-saving potential and improving energy efficiency. In this study, the Sankey diagram-based decision support tool is designed and developed to illustrate the energy flow and the potential for energy savings from various processes in different industrial sectors. The tool is developed in Python and presented as a web-based dashboard, making it accessible to various users. The web-based Sankey diagram tool allows the user to comprehend the present state of energy consumption, costs, and CO2 emissions, as well as the potential for enhancing system flexibility and efficiency in the industry. The opportunities for heat recovery, renewable energy sources, and energy storage technologies are discussed as an assumed case study in 4 specific scenarios. Finally, the findings validate the significance of energy-efficient solutions in industry utilizing the proposed tool. This underscores the importance of adopting sustainable practices within industries, ultimately contributing to the enhancement of the sector's overall sustainability and resilience. • The paper aims to describe the design and development of a web-based decision support tool using Sankey diagrams to visualize and optimize energy flow. • The tool, created in Python, is accessible to engineers and non-engineers via a user-friendly web interface. • Allows users to easily modify parameters and scenarios to explore various energy-saving opportunities. • Demonstrates potential for substantial reductions in CO 2 emission and energy costs through renewable energy, energy storage, and heat recovery utilization. • Evaluated through a case study with four scenarios, highlighting significant efficiency improvements. • Enhances understanding of energy consumption and sustainability in industrial processes. [ABSTRACT FROM AUTHOR]

A regional integrated energy system (RIES) guarantees the fulfillment of a diversified load demand of users by coordinating all types of energy equipment and is a two-layer optimal scheduling method that takes into consideration the flexibility of the characteristics of the combined heat and power (CHP) system is proposed in this paper. First, the thermoelectric output characteristics of hydrogen fuel cell (HFC) and CHP units are analyzed to establish an energy equipment model that takes into consideration the variability of the operating conditions. Subsequently, a two-layer optimal scheduling model of the RIES is established, where the upper layer takes into consideration the operating costs, carbon emission penalties, and renewable energy consumption capacity to determine the strategy for allocating the energy flow, and the lower layer considers the energy efficiency as the optimization objective to determine the output modes of the HFC and CHP units. Finally, an adaptive closed-loop control strategy is used to avoid the continuous startup and shutdown of the CHP unit. The simulation results show that the proposed method can effectively reduce operating costs and carbon emissions, improve energy efficiency and renewable energy consumption, and promote the efficient utilization of integrated energy resources. • A variable operating condition model of a RIES was established. • A scheduling strategy based on flexible characteristics of CHP system was proposed. • An adaptive closed-loop control method was used to coordinate the operating states. • The optimized operation of regional integrated energy system was realized. • Results were implemented to verify the effectiveness of the scheduling method. [ABSTRACT FROM AUTHOR]

Focusing on large thermal power plants in China, we examine the causal effect of carbon emission trading scheme (CETS) on their carbon emission efficiency. Using the staggered installation of CETS pilots as a natural experiment, we show that carbon emission trading significantly improves power plants' carbon efficiency. Specifically, the CETS leads to a 6.9 % increase in carbon efficiency. The carbon efficiency growth effects are stronger for plants that are not state-owned, large in scale, or plants located in regions with high level of marketization. Moreover, the improvement in carbon efficiency mainly comes from the reduction in carbon emission, not the improvement in power generation level. The mechanism analysis indicates that the implementation of CETS increases the number of granted patents by as much as 23 %, which provides supporting evidence for the Porter hypothesis. • The causal effect of carbon emission trading scheme on carbon emission efficiency is investigated at plant-level. • The carbon emission trading scheme is conducive to increasing carbon efficiency by 6.9 %. • Carbon emission trading scheme has a significant heterogeneous effect on carbon efficiency. • This paper provides supporting evidence for the Porter hypothesis. [ABSTRACT FROM AUTHOR]

As the development and use of offshore islands increase, so do the diversity of their energy needs, the cost of utilising the mainland for resource replenishment, and the instability of island energy systems. To address this challenge, this paper introduces an innovative system integrating fossil and renewable energy tailored for these islands, considering seasonal variations and external energy fluctuations. Leveraging a P-graph, an optimisation framework is designed to assess different optimised solutions. A comprehensive analysis is also performed to compare the solutions, while sensitivity assessments evaluate factors including electricity and gas price fluctuations, renewable energy availability, and natural gas demand. Additionally, the carbon emissions resulting from different power generation scenarios are visually represented and thoroughly analysed. The results support two key findings: 1) the cost of combined energy supply is lowest when wind energy accounts for 59 % of the total energy, mainland grid connection accounts for 3 %, fossil fuel energy accounts for 28 %, and natural gas accounts for 10 % of the energy mix; and 2) the price of electricity and natural gas supplied to the islands and the variability in the energy sources of wind and natural gas can significantly affect the cost of the energy system. • Use the P-graph approach to provide optimal and near-optimal solutions. • Integrate electricity and gas systems in one energy network. • The integration enhances the stability of the island energy system. • Calculates carbon emissions of the island energy system. • Sensitivity analysis is used to support practical applications. [ABSTRACT FROM AUTHOR]

The increase in the share of renewable energy sources in the integrated energy system (IES) has led to the bidirectional flow of electricity and carbon in the transmission and distribution network, which has increased dispatch complexity. To address these issues, this paper proposes an optimal scheduling method for IES considering the seasonal carbon trading mechanism and electricity-carbon quota sharing method. First, an energy hub model of the integrated electric-heat-carbon energy system was established, with the introduction of carbon flow. Then, a seasonal carbon trading mechanism that considers the characteristics of carbon emissions in each period of the system is proposed, and the ladder-type carbon price model and carbon quota allocation method are optimized. Moreover, to fully utilize the interaction between electricity and carbon to achieve low-carbon economic dispatch, a dual time-scale electricity-carbon quota sharing method is proposed. Finally, the effectiveness of the proposed method is verified by the case studies. The results show that the scheduling method considering seasonal carbon trading mechanism and electricity-carbon quota energy sharing can optimize the allocation of resources such as electricity and carbon quota among the systems, and reduce the cost of the system by 6.04 % and carbon emission by 4.27 %. • Dispatch method considers the long-term energy storage properties of hydrogen. • A seasonal carbon trading mechanism is proposed. • An electricity-carbon quota dual time scale energy sharing mechanism is proposed. • The low carbon and economy of the model are proved. [ABSTRACT FROM AUTHOR]

In this paper, a novel hydrogen-doping X-type rotary engine (XRE) using dual-ignitors is proposed to improve its high-altitude performance. Firstly, the effects of hydrogen doping fraction and operation altitude on the combustion, thermodynamic and environmental performance of XRE are revealed by establishing CFD model. Furthermore, the novel dual-ignition strategy using different ignition intervals is raised based on the eddy distribution characteristics. Finally, the comprehensive performance of the dual-ignition strategies is analyzed by comparing with the traditional single-ignition strategy under high-altitude conditions. The results show that the thermal efficiency increases firstly and then drops with the increasing hydrogen doping fraction. When hydrogen doping fraction increase by 6 %, the NO x emission increases by 2.9 times at 0 km altitude, while it increases by 4.2 times at 6 km altitude. Auxiliary ignitor arranged at back side can generate backward flame and promote combustion. At 0 km altitude, the thermal efficiency of dual-ignition reaches the maximum of 0.330, which is 3.12 % higher than that of single-ignition. However, the synchronous dual-ignition is the best strategy at high-altitude, in which the thermal efficiency is improved by 2.59 % and CO 2 emission is reduced by 3.99 % compared with the asynchronous ignition using an interval of 10 °EA. • A novel hydrogen-doping X-type rotary engine (XRE) using dual-ignitors is proposed. • Effects of hydrogen on the high-altitude performance of novel XRE are investigated. • Dual-ignition strategy of XRE is raised based on eddy distribution characteristics. • Performance differences of XRE using single-ignitor and dual-ignitors are revealed. [ABSTRACT FROM AUTHOR]

As a fundamental policy instrument for facilitating the profound transformation of China's energy sector, the carbon decoupling effect of the energy consumption permit trading scheme (ECPTS) is a crucial issue to be evaluated. This paper aimed to explore the carbon decoupling effect and mechanisms of China's ECPTS by utilizing the difference-in-differences (DID) estimator. The findings indicated that the ECPTS significantly enhanced the degree of carbon decoupling, and the dynamic effect tended to gradually expand this decoupling effect. This conclusion holds even after conducting several robustness tests. Moreover, heterogeneity is observed in the carbon decoupling effect of the ECPTS, with regions characterized by higher levels of economic development, lower carbon emissions, and higher resource endowments exhibiting more pronounced decoupling effects. Furthermore, the mechanism analysis revealed that the ECPTS primarily improves carbon decoupling through the optimization of the energy mix and the reduction of the energy use scale. Conversely, the role of industrial structure and technological innovation has yet to fully manifest. Consequently, it is imperative to continue promoting and refining the construction of the ECPTS market. Additionally, stimulating investment in optimizing industrial structures and fostering technological innovation, along with the formulation of regionally tailored policy measures, may propel the carbon decoupling effect of ECPTSs. • The carbon decoupling effects of ECPTSs are explored. • The ECPTS significantly enhanced China's carbon decoupling. • There is regional heterogeneity in the carbon decoupling effect of the ECPTS. • The ECPTS improves carbon decoupling through optimizing energy mix and reducing energy consumption. • The conclusions can provide empirical supports and policy recommendations for Chinas ECPTS. [ABSTRACT FROM AUTHOR]

The coupling of renewable energy electrolysis for hydrogen production and methanol synthesis can not only reduce CO 2 emissions, but also achieve on-site consumption of renewable electricity. In this paper, an integrated system of solid oxide electrolysis cell (SOEC) with CO 2 to methanol (SOEC-CO 2 tM) is studied: (1) The energy-intensive SOEC is combined with the intense exothermic CO 2 tM, (2) the heat of the system is redistributed to energy realize cascade utilization and electrification transformation of public works to further improve energy efficiency, (3) multi-dimensional techno-economic assessments are performed to reveal the development potential. The results show that the carbon utilization and carbon emissions of the new process are better controlled. The energy efficiency of the SOEC-CO 2 tM process after electrification transformation is also higher than that of traditional methanol synthesis processes. The production cost of methanol is currently higher than the market price, which does not give the SOEC-CO 2 tM process a competitive advantage. However, when considering carbon taxes and changes in raw material costs and renewable electricity prices, the future cost of the SOEC-CO 2 tM process can be comparable to or even more favorable than other processes. Through the research and analysis, we aim to explore the potential integration of SOEC and CO 2 tM process. [Display omitted] • Energy integration realizes the energy cascade utilization and electrification further improves the energy efficiency. • Calculate and analyze system technical superiority and economic feasibility. • The process achieves 87.87 % carbon element utilization rate and 62.59 % energy efficiency. • The minimum carbon emissions of the new process are 0.193 kg CO 2 /kg MeOH. • The process offers significant economic benefits with green electricity priced at 0.014 USD/kWh. [ABSTRACT FROM AUTHOR]

As a major institutional innovation of China's environmental governance system, weather the Central Environmental Protection Inspection (CEPI) can reduce carbon intensity is still unclear. This research takes 18,728 company-year sample observations of Chinese industrial A-share listed companies from 2009 to 2020 as the research object (CSMAR and CNRDS databases are used). Multi-period Differences-in-Differences model approach is employed to investigate the mechanisms through which the CEPI affects carbon intensity governance in industrial enterprises, the heterogeneous effects of CEPI are explored at macro, meso and micro levels. CEPI reduces the carbon dioxide emissions of industrial enterprises by 0.028 tons per 10,000 yuan of output value, CEPI achieves carbon intensity governance effect by incentivizing companies to enhance the quantity and the quality of green technological innovation. High level of public environmental oversight and industry competition, as well as nature of state-owned enterprises facilitate the CEPI's role in promoting the reduction of enterprise carbon intensity. The findings provide practical insights for driving green technological innovation among enterprises. Some policy implications are proposed. CEPI should be regulated to strengthen the environmental governance responsibilities of local governments and incentivize industrial enterprises to improve the quantity and quality of green technological innovation and reduce carbon intensity. [Display omitted] • Pioneering CEPI's research on the governance of carbon intensity of industrial enterprises. • A mediation model is introduced to analyze the governance pathway of CEPI policy. • Examining CEPI's impact on both the quantity and quality of green technology innovation. • In this paper we conduct heterogeneous analyses at macro, meso, and micro levels. [ABSTRACT FROM AUTHOR]