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In this paper we investigate the market size of all materials and products presently produced from (organic) carbon and we present a method to estimate the intrinsic recycling potential of these materials/chemicals as a function of their respective applications. The method is based on the expert assessment of a number of variables that are important within the different application categories and markets of the carbon-based materials/chemicals. Applying the method, the paper presents the recycling potential of all carbon-based products. Following, an estimation of the amount of new products that can be produced each year through recycling of discarded products is presented and the amount of carbon that needs to come from other sustainable sources to fulfil our demand for new products is calculated. We distinguish nine different categories of (organic) carbon-based materials/chemicals: plastics, textile fibres, thermoset resins, rubbers, surfactants, solvents, fine chemicals, paper/board and wood products. Within these nine categories the most important materials/chemicals types were taken into account. Fossil-based and bio-based materials/chemicals were assessed separately. For each of the materials/chemicals types, the market size in terms of mass (Mt) was calculated for the main applications in which they are applied. Next, for all materials/chemicals types in these applications, the maximum recycling potential, in case mechanical or physical recycling methods are applied, was assessed, using an expert panel. Also, inevitable leakage of materials/chemicals in the different applications was assessed. Finally, the amount of feedstock coming from recycling streams that may be made available for chemical recycling or carbon capture and utilisation technologies was derived. From this, the magnitude of carbon-based materials/chemicals that need to be replaced each year by other renewable feedstock than recycled content in terms of Mton carbon was calculated. The analysis is relevant in view of implementation of a circular economy and reuse and recycling of materials, to combat depletion of raw materials. Next, it is relevant in view of phasing out fossil-feedstock to combat climate change. Our analysis indicates that the recycling potential of carbon-based materials and products through mechanical or physical methods lies around 50%, even in a system that is fully optimised for recycling. Chemical recycling and carbon capture and utilisation may provide another 25% of the renewable-carbon feedstock needed, but they generally require far more energy and other inputs to produce new materials and chemicals than the mechanical and physical recycling methods. The remaining demand for renewable-carbon feedstock thus needs to come from either biomass or CO 2 through carbon capture and utilisation technologies. Based on our findings, we argue that the composition of our present carbon-based products pool needs to be redesigned on a fundamental molecular level, towards material types that contain more oxygen. Carbon-based materials that contain more oxygen generally can be recycled more efficiently, and are also easier to produce from the alternative feedstocks biomass and CO 2 through CCU. [ABSTRACT FROM AUTHOR]

Promoting green hydrogen has emerged as a pivotal discourse in the contemporary energy landscape, driven by pressing environmental concerns and the quest for sustainable energy solutions. This paper delves into the multifaceted domain of C -Suite issues about green hydrogen, encompassing both technological advancements and policy considerations. The question of whether green hydrogen is poised to become the focal point of the upcoming energy race is explored through an extensive analysis of its potential as a clean and versatile energy carrier. The transition from conventional fossil fuels to green hydrogen is considered a fundamental shift in energy paradigms, with far-reaching implications for global energy markets. The paper provides a comprehensive overview of state-of-the-art green hydrogen technologies, including fuel cells, photocatalysts, photo electrocatalysts, and hydrogen panels. In tandem with technological advancements, the role of policy and strategy in fostering the development of green hydrogen energy assumes paramount significance. The paper elucidates the critical interplay between government policies, market dynamics, and corporate strategies in shaping the green hydrogen landscape. It delves into policy mechanisms such as subsidies, carbon pricing, and renewable energy mandates, shedding light on their potential to incentivize the production and adoption of green hydrogen. This paper offers a nuanced exploration of C -Suite issues surrounding green hydrogen, painting a comprehensive picture of the technological and policy considerations that underpin its emergence as a transformative energy source. As the global community grapples with the imperatives of climate change mitigation and the pursuit of sustainable energy solutions, understanding these issues becomes imperative for executives, policymakers, and stakeholders alike. [Display omitted] • The latest advancements in photo electrocatalysts and fuel cell technologies are reviewed. • The storage and transportation within the realm of green hydrogen energy were discussed. • Policy and strategy for fostering the development of green energy are proposed. [ABSTRACT FROM AUTHOR]

This paper looks into the crucial macroeconomic feedback mechanisms emerging from the interplay among the goods market, the labor market, the financial sector, and monetary policy, particularly in the context of transitioning towards a climate-neutral economy. The investment decisions of firms, pivotal in this interaction, can trigger feedback loops with potentially destabilizing effects, underscoring the critical role of investment within the complex interplay of market and sector dynamics in the macroeconomy. Governmental intervention is highlighted as a key factor in steering the green transition while preserving economic stability. A carbon tax on fossil fuel consumption is proposed as a primary tool for facilitating this green transition. Our investigation employs a disequilibrium model of monetary growth, a la Keynes-Metzler-Goodwin (KMG), incorporating a portfolio perspective across three asset markets - money, bonds, and stocks. This framework allows for an in-depth analysis of how a carbon tax influences real production, inflation, and inequality during the transition. Our findings indicate that imposing a carbon tax on production does not markedly disrupt economic stability, as long as the carbon pricing and its growth rate remain within low bounds. [ABSTRACT FROM AUTHOR]

Green hydrogen, produced from renewable electricity, can be transported long distances in multiple mediums. In this paper, a Techno-economic model is proposed to show the economic viability of global green hydrogen transport along 15 major regional routes such as Australia to Asia and Europe for the first time. A Monte Carlo-based technique is presented to assess the levelised cost of green hydrogen for different regions for the next 30 years. Depending on the specific route, green hydrogen can be transported in different forms, including ammonia, Liquid Organic Hydrogen Carrier (LOHC), Hydrogen Slush, compressed or liquefied hydrogen, etc. form and using different modes including shipping, truck, train, and pipeline. A linear programming analysis has been conducted for different regions, showing that among the global projected 300Mt of green hydrogen demand in 2050, 85% will need to be transported between regions to achieve the most economically optimal distribution. • Techno-economic analysis of green H 2 export via 15 worldwide regional trade routes. • Export model includes H2 generation, conversion, transport, and carbon prices. • In 2030, North America will be the largest exporter, followed by Australia. • Higher carbon prices allow for rapid growth in the green hydrogen industry. • Shipping is the most likely and cheapest H 2 export mode for distant transport. [ABSTRACT FROM AUTHOR]

With the high proportion of renewable energy connected to the grid, the problem of insufficient flexibility in the power system has emerged. Renewable energy and controllable distributed resources can be aggregated and managed through virtual power plants, reducing the need for flexibility to a certain extent. Although building new energy storage systems can compensate for the lack of flexibility, it requires high initial investment costs. To address this, this paper proposes a lease mechanism for coal-fired units based on the combination of carbon credits and prices, providing the right to use coal-fired units for virtual power plants. Subsequently, different demand response strategies are utilized to control the controllable loads of various users, thereby providing certain controllable resources for the virtual power plant. Additionally, to ensure the optimal decision-making of the virtual power plant operator, a cost model accurately describing the capacity degradation state of the energy storage system is adopted. Moreover, a multi-time scale scheduling strategy of virtual power plant is implemented to fully utilize controllable resources of different time scales, effectively dealing with the power imbalance caused by multiple uncertainties. The results show that utilizing the leasing mechanism of coal-fired units and employing demand response strategies from different users can provide flexibility to the virtual power plant. The accuracy of the capacity degradation model used by the operator significantly impacts the optimality of the scheduling plan. • The scheduling model of VPP consider capacity degradation of ESSs, carbon trading, and DR strategies. • A lease mechanism for coal-fired units based on the combination of carbon credits and prices is proposed. • This paper proposes ISBDR strategies for reduceable loads. • The ESSs capacity degradation model adopted takes into account DOD and SOC. • A multi-time scale scheduling strategy of VPP is adopted to deal with multiple uncertainties. [ABSTRACT FROM AUTHOR]

• Vessel train in ocean shipping offers environmental and economic benefits. • Multi-scenario analysis reveals diverse applications of vessel train. • Case study from Yangshan Port to Port of Piraeus showcases the potentials of vessel train. • Sensitivity analysis emphasizes dependence of vessel train on shipping productivity. This paper introduces the concept of vessel train, a new mode in maritime transport offering both environmental and economic advantages. The study provides a framework for analyzing the economic feasibility of vessel train in ocean shipping, focusing on four different scenarios to evaluate its impact on navigation speed and productivity for both round-trip and year-long operations. Using the container ship route from Yangshan Port to the Port of Piraeus as a case study, the research compares vessel train with traditional shipping methods by categorizing shipping costs. It also includes a sensitivity analysis considering factors like route length, frictional resistance reduction, and variations in the container freight index, fuel prices, and carbon tax rates. The findings indicate that vessel train can reduce transportation costs and fuel emissions. The paper concludes that vessel train could significantly contribute to a competitive and sustainable future in shipping. [ABSTRACT FROM AUTHOR]

The mitigation of climate change requires that agricultural development would proceed in accordance with green and sustainable practices. This implies that economic performance should be improved while minimizing the impact on the environment. One way to assess the underlying costs of sustainable agricultural development, and to model the relationship between the environment and the economy in general, is to use the carbon shadow price (CSP). In this paper, we utilize a by-production model within a non-parametric framework to estimate the agricultural CSP from 1997 to 2020 in 31 provinces of China. The patterns of the agricultural CSP are unveiled through kernel density analysis and convergence tests. Additionally, this paper constructs a comprehensive agricultural informatization indicator using the entropy method. We then empirically investigate its influence on agricultural CSP. The results reveal that China's agricultural CSP has demonstrated consistent growth over the past two decades which suggests serious improvement in environmental performance. Furthermore, the CSP show cross-province variation, albeit with conditional β convergence. Our empirical findings indicate that agricultural information technology contributes to an increase in CSP, thereby indicating its positive role on the green growth of agriculture in China. [ABSTRACT FROM AUTHOR]

• Taking carbon in RIES as energy flow, which is equivalent to electricity-heat-gas to ensure the carbon quota requirements of the system. • Proposing a new demand-side response mechanism to meet the purpose of reducing carbon emissions. • Scheduling RIES with comprehensive consideration of economy and low carbon. • Proposing a new RIES ladder carbon price trading mechanism to match the purpose of demand side management. Effective mitigation and reduction of carbon emissions is consistently underscored in Regional Integrated Energy Systems (RIES), aligning with the goals of carbon-neutralization. However, the inherent trade-off between carbon emissions reduction and economic operation is an obvious challenge not only in power systems but especially in the coupled electricity-gas-heat energy systems. This paper develops a bi-level low-carbon optimal scheduling model, highlighting reliable operation and the balance of supply and demand of RIESs with demand-response uncertainty. In this paper we firstly redefined the carbon emission of a RIES as a carbon flow and proposed a reward and punishment carbon trading mechanism based on the ladder carbon price. Secondly, we designed an incentive-based demand-side response policy within the subsystem encompassing electricity, gas, and heat. Concurrently, the probability density distribution functions of transferable, replaceable, and interruptible loads are computed separately. Based on the above, the deviation of the load reduction and the actual load is recalculated to delimit the constraint of the demand-side response. Finally, the mechanism of carbon trading and the demand-response is leveraged to address the economic scheduling incorporating operation cost, carbon transaction cost, imbalance costs of supply and demand, and load loss. Simulations demonstrated in the paper prove that the optimal solution with demand-response uncertain may effectively increase the economic performance and reduce carbon emissions of a RIES. [ABSTRACT FROM AUTHOR]

Australia has significant offshore wind resources that can support ever-increasing power demand and hence provide a long-term contribution to the net-zero target by 2050. Although some offshore wind farm projects are proposed in Australia, the industry is not mature enough to justify the benefits and display economic opportunities. More specifically, the techno-economic analysis of offshore wind energy has not been systematically mapped in Australia. Therefore, the investigation of the spatial variation of technical feasibility and economic potential of offshore wind is vital to identify the potential regions and to develop strategies for future offshore wind farm developments in Australia. This paper presents detailed mappings of the techno-economic potential of offshore wind energy in Victoria-Tasmania's exclusive economic zone. Offshore wind energy resources are assessed in the paper in terms of energy availability and variability and the feasibility of various offshore wind technologies is investigated, including turbines, foundation types and transmission topologies. In addition, the high-fidelity life-cycle cost models and two innovative evaluation matrices are developed to assess the economic potential of offshore energy farms in South-eastern Australia. The impact of local power system regulation costs and future carbon prices on the viability of offshore wind is also investigated in this paper. It is concluded that the detailed mapping approach and analysis in the paper can provide a systematic tool for industry partners, investors and policymakers at the pre-planning stage of developing offshore renewable energy systems. • The technical feasibility of offshore wind is mapped under various constraints. • The novel LACE and high-fidelity LCC assessment models are developed. • The techno-economic potential is systemically mapped in South-eastern Australia. • The impacts of electricity market regulation and future carbon prices are studied. [ABSTRACT FROM AUTHOR]

Combined heat and power is an inevitable trend in the development of waste-to-power industry. Many waste incineration power generation projects that have already put into operation in China are waiting for transition and upgrading to combined heat and power projects. From a growth option perspective, this paper considers the irreversible process and uncertainty in economic benefits, introduces carbon emission trading mechanism and develops the growth option theory to design the expansion decision making model of waste-to-energy combined heat and power projects, so as to obtain the project value and find the optimal expansion timing. In this paper, a case study is carried out on the expansion decision making of a waste-to-energy combined heat and power project in Shandong Province in China. And two scenarios with specific and flexible expansion times are developed from European and American options separately, as European options require investors to expand at a certain time but American options not. The results indicate that 1) real option approach successfully improves the project value through considering uncertainty, and American option can achieve the optimal expansion time, 2) under the carbon emission trading mechanism, the carbon price affects the expansion index, which has a positive effect on the project value, 3) the linear nature of the income and cost expansion index can help investors make judgments on expansion investments. The effectiveness of the case study implies the practicality of the expansion option method for similar projects to reach dual carbon targets in cost and benefit analysis. • Real option approach is applied in energy transition in WTECHP projects. • European and American options are proposed for certain and flexible decision times. • Expansion time and triggers of WTECHP are incorporated into life cycle management. • CCER is introduced as an environmental element to evaluate expansion decision making. [ABSTRACT FROM AUTHOR]

Carbon trading market is a central policy tool for promoting cleaner enterprises' energy consumption and investment behaviors. It is crucial for enterprises to establish a green and low-carbon development model by clarifying carbon trading impact mechanism on enterprise behaviors and the interactive relationship between entities in the carbon market. China's contract-based carbon market is still in the development stage, the impact of the mainstream allowance mechanism and government regulation on enterprises' energy behaviors has yet to be determined. In view of this, this paper describes mathematical mechanisms of the influence of carbon prices and carbon quotas on enterprises' energy consumption and investment, and the evolutionary game model of government-enterprise behaviors is constructed, the evolution process and appropriate strategies of enterprises' energy behaviors in the development of the carbon market are discussed. This paper uses real data of China carbon market to simulate the model, it is found that strategies such as relaxation of carbon quotas and carbon subsidies dynamization are needed during the initial development of the market. In the mature stage of the carbon market, strategies are needed to increase the proportion of government carbon revenue and reduce its regulatory cost. The higher the initial willingness of government-enterprise, the better the effect of strategies and the constraints of public willingness. The model and results have theoretical implications for enterprises' energy transformation and government regulation, and provide a reference for the development of China's carbon market. • Constructed benefit-cost analytical framework for enterprises' energy behaviors. • Described mechanisms of carbon trading affecting enterprises' energy behaviors. • Constructed government-enterprise behaviors model by the evolutionary game theory. • Found new conclusions of enterprises' energy behaviors under the carbon market. [ABSTRACT FROM AUTHOR]

This study investigates the carbon compensation mechanism as a tool to promote coordinated economic and environmental development in China's Jing-Jin-Ji region (Beijing, Tianjin, and Hebei). A novel approach for calculating carbon compensation cost that integrate emission responsibility as well as carbon abatement cost through a bi-level programming model is proposed. Shared producer and consumer responsibility is established for carbon emissions under the multi-regional input-output model. Marginal abatement costs of Beijing, Tianjin, and Hebei are further calculated through the input-output and linear programming method. Results highlight that the emission responsibility allocation method significantly affects the inter-regional carbon compensation amount. The production-based approach leads to a 77% reduction of carbon compensation amount from Beijing to Hebei, and a 170% overestimation from Tianjin to Hebei compared with the shared responsibility approach in 2060. The optimal carbon compensation unit cost ranges from 1539 to 6438 yuan/ton when the carbon reduction ratio ranges from 10% to 20%. Beijing would compensate Hebei 3.56 and 29.74 billion yuan for achieving 10% and 20% emission reduction, respectively. Similarly, Tianjin's compensation for Hebei would be 0.23 and 1.87 billion yuan in the two scenarios. Results further show that implementing the proposed carbon compensation mechanism can reduce total abatement cost by 43% and 84% in Jing-Jin-Ji under the two scenarios. The methods and results of this paper could help inform future carbon compensation implementation in China and other countries. • Develop a bi-level programming model to determine optimal carbon compensation cost. • Consider emission responsibility and carbon abatement cost in Jing-Jin-Ji. • Resulting mechanism reduces abatement cost by 43% for 10% emission reduction. • Production-based allocation underestimates carbon compensation amount by 62%. • Optimal carbon compensation unit cost changes with marginal abatement cost. [ABSTRACT FROM AUTHOR]

Meeting the goal of reaching zero emissions by 2050 requires profound changes in the production of bulk materials, cement and concrete. For construction sector, this transition is also dependent on the evolution of demand, stemming from changes in the population structure and practice in structural design. Many timelines have been produced suggesting pathways to zero emissions, but none have looked at the required investment level, or the feasibility of transition looking at the level of single plants being shut, transformed or built within a single country. In this paper, we have looked at transition pathways in the United Kingdom as a function of the available funding and the possible emergence of transformative technologies. We find that trade is a necessary component of the transition, allowing for continued construction while the production apparatus is upgraded. Our results further suggest that the current level of investment is consistent with today's carbon price but falls short of what is necessary to achieve net zero by 2050. Finally we find that pathways assuming that CCS will be available at scale are particularly susceptible to overshoot their emissions target if the technological deployment fails to materialise. This is because they combine heavy investments, immature technology and concentrated risk. [Display omitted] [ABSTRACT FROM AUTHOR]

Interval-valued time series (ITS) has been widely concerned by the academic community due to its outstanding performance in dealing with the uncertainty of systems. Numerous ITS forecasting studies have emerged, while the most popular method is based on "divide and conquer". For ITS analysis, bivariate empirical mode decomposition (BEMD) is currently the main tool that can simultaneously consider the interrelationships between the upper and lower limits. The concern is that, like empirical mode decomposition (EMD), BEMD suffers from mode mixing and end-point effects, which leads to unsatisfactory results of decomposition. In this paper, a bivariate ensemble empirical mode decomposition (BEEMD) method is proposed and applied to ITS forecasting, which aims at alleviating the problems mentioned above. At the same time, dynamic time warping (DTW) is used to quantize and analyze the mode mixing. Then, the effects of complex-valued signal constructions on ITS forecasting are discussed. To overcome the uncertainty and instability that may arise from a single prediction method, an optimal prediction based on the model pool is designed for sub-modes, and the final result can be obtained by simple addition. Using carbon prices, West Texas Intermediate (WTI) crude oil prices, and short-term loads, as the research objects, the results indicate that BEEMD is effective in avoiding mode mixing in BEMD, the complex-valued signal construction based on center and radius method (CRM) is more conducive to forecasting and optimal prediction can further improve forecasting accuracy. [ABSTRACT FROM AUTHOR]

Transportation is a major cause of energy consumption and emissions which can be reduced by optimizing routings and using alternative modes of transport. This paper relates to the strategic design of multimodal transportation networks. It presents a general model of green vehicle routing problems that supports strategic decision-making by identifying optimal solutions and provides data on costs and emissions. Three general linear programming models were developed that optimize multimodal distribution networks that could be applied in many industries. Model I evaluates carbon emissions; model II assesses carbon emissions and capacity constraints; and model III establishes total costs including transportation, handling, storage, fuel and carbon costs. Thailand is the third largest world sugar exporter in the world and is piloting carbon pricing, which will affect energy intensive industries, including the sugar industry. The models are applied using data obtained from a collaborating company. The research contributed to practice by informing managerial decisions relating to the export of sugar from the factory. This included evaluating the possible use of a dry port with rail connections, which could reduce transportation and carbon costs by 54.3 % and facilitate the building of another factory to increase exports. • LP models optimized outbound logistics networks with multiple modes of transport. • Minimized CO 2 emissions and total costs including transportation and carbon costs. • Modelling multimodal distribution networks including road, water, rail and dry port. • Used real data and supported strategic decision making for a Thai sugar company. • Provides a comprehensive review of LP models for optimizing distribution network. [ABSTRACT FROM AUTHOR]

System modelling efforts have shown that carbon capture is a key technology to enable a cost-effective reduction of hard-to-abate emissions in energy-intensive industries. The CO 2 that is captured can either be utilised (CCU), or stored with carbon capture and storage (CCS). This paper examines the implications of both European carbon pricing mechanisms (ETS I & ETS II) on the level-playing field between CCS and CCU investments. Our contribution is threefold. First, we develop an equilibrium model that enables us to mimic market outcomes under different regulatory conditions. With a numerical case study applied to a fuel production chain, the model confirms that the current ETS regulation can have an adverse effect on CCU uptake. Especially with zero or low ETS II prices a lock-in effect can occur on CCS, potentially prolonging conventional refinery activities. Second, we propose an alternative approach to better integrate CCUS into the EU ETS. Results show that this approach maintains the level-playing field between CCU and CCS, regardless of any carbon price differentials. That results in a closer to Pareto optimal outcome in terms of welfare and emission abatement. Third, we present an analytic analysis to express the CCUS trade-off from a theoretical point of view. This provides generalised and concrete insights into how EU ETS influences the profitability and likelihood of CCUS. Our results help policymakers to gain a better understanding of the impact of ETS regulations on decarbonisation efforts in the industry. [ABSTRACT FROM AUTHOR]

Distributed photovoltaic energy storage systems (DPVES) offer a proactive means of harnessing green energy to drive the decarbonization efforts of China's manufacturing sector. Capacity planning for these systems in manufacturing enterprises requires additional consideration such as carbon price and load management. This paper proposed a triple-layer optimization model for DPVES capacity configuration in the manufacturing sector using a chemical fibre manufacturing enterprise for demonstration. Refined photovoltaic generation and energy storage lifetime models were used. Beyond the considerations of electricity prices and meteorological conditions, we further studied the influence of carbon price and user load management on system capacity configuration and associated economic feasibility. Firstly, without considering carbon, minimizing user costs requires maximizing PV capacity up to the area limit while adjusting the ES to its optimal capacity and power. The optimal DPVES annually reduces the grid electricity consumption and carbon emissions, resulting in a 12.73% annual cost reduction. When considering the costs of carbon emissions, the carbon reduction contributed by DPVES can reduce the annual costs, making the whole system more economically feasible. However, the presence of substantial carbon emissions costs diminishes the economic feasibility of the ES, leading to a reduction of 24.51% in the optimal capacity configuration. Finally, user load management can further reduce system costs because it replaces some of the functions of energy storage. This results in a decrease of over 39% in the optimal energy storage capacity and a further reduction in related costs. Additionally, we found that load management by enterprises is more effective during the low carbon price than the high carbon price, implying that companies should implement load management as soon as possible. • Established a triple-layer optimization model for capacity configuration of distributed photovoltaic energy storage systems • The annual cost can be reduced by about 12.73% through capacity and power configuration optimziation • High carbon prices may reduce the economic viability of the energy storage system, causing reduction in its optimal capacity • Load management can further reduce the energy storage capacity demand by 39%, bringing economic benefits especially in low carbon prices [ABSTRACT FROM AUTHOR]

Carbon price prediction serves as a market indicator and economic driver, facilitating the adoption of more environmentally friendly production methods to achieve the emission reduction targets outlined in the Paris Agreement. In recent years, time series analysis and decomposition techniques have been widely applied to carbon price forecasting. However, few researchers have considered the issue of data feature drift caused by real-time decomposition. Specifically, as the sample size increases, data features undergo changes, rendering the trained models unable to fit the new data. This paper explains the underlying reasons for this phenomenon from new perspectives and proposes a novel paradigm that replaces the intrinsic mode function with a single-step fuzzy particle. This new paradigm corrects the issue of data feature drift and concentrates noise into a completely new sequence during the preprocessing stage. In the subsequent processing steps, the loss of correlation between the sequence and time lag, as well as the sequence and carbon prices, is addressed through multi-information association. This paradigm hybrid model can be applied to deterministic and interval multi-step predictions. Experimental results on the datasets from Guangdong and Hubei demonstrate that the proposed model outperforms other comparative models, achieving better predictive results than existing decomposition-based forecasting models. In the case of Guangdong, the normalized root mean square error (NRMSE%) for one-step, three-step, and five-step deterministic predictions are 2.18%, 2.51%, and 2.89%, respectively. The average interval score (AIS) for interval predictions are −0.357 and − 0.2375, respectively. • Provide new perspectives on the data feature drift caused by real-time decomposition. • Propose a novel paradigm to address the practical challenges of real-time decomposition. • Multi-information association solves the problem of correlation loss in traditional decomposition techniques. • This paradigm can be combined with secondary decomposition and applied to deterministic and interval multi-step prediction. [ABSTRACT FROM AUTHOR]

• Proposed BECCS deployment criteria are based on socio-enviro-economic objectives. • Life cycle emissions and carbon abatement costs are calculated. • Some of the BECCS pathways are less likely to achieve net negative emissions. • Balancing between socioeconomic aspects such as local job creation opportunities, cost, feedstock supply chain disruptions, and emission reduction targets is discussed. Countries are considering different options to achieve net zero emissions including Bioenergy with carbon capture and storage (BECCS), which is the process of capturing and storing CO 2 from processes that use bioenergy to produce heat, electricity, or biofuels. However, this technology faces sustainability concerns and possesses complex value chains of its emissions. Adding further to this complexity, the literature indicates two opposing views with respect to the potential of BECCS in terms of being able (or unable) to achieve negative emissions. Hence, this paper analyzes in detail a wide range of BECCS pathways in terms of their ability to achieve negative emissions along with their associated costs. Out of seven assessed pathways, our analysis shows that corn to ethanol and biomethane production from maize BECCS pathway in the USA, biomethane production from wet manure in Europe, and baling of straw pellets with trans-Atlantic shipment can achieve negative emissions at a cost of 50, 108, 159, and 232 dollars per ton of CO 2 ($/tCO 2) respectively. Other technologies like poplar pellets, forest residue, and agricultural residue with trans-Atlantic shipment are not able to achieve negative emissions. [ABSTRACT FROM AUTHOR]

As an important initiative of climate action, REDD+ has been increasingly discussed in global policy arena. But delay in wider scale yet full-fledged implementation and its poor performance have raised suspects and pushed REDD+ toward in a long line of "conservation fad". In this paper, we have discussed the following ten questions to REDD+: (1) Does REDD+ address major causes of deforestation? (2) Does REDD+ contribute to global emissions reduction? (3) Does REDD+ recognize the inherent capacity of local people to manage their forests? (4) Does REDD+ respect the rights of indigenous people and local communities? (5) Does REDD+ justify the local governance and countries' sovereignty? (6) Does REDD+ ensure the transparency in program design and architecture? (7) Does REDD+ give credits to the carbon sequestering communities? (8) Does REDD+ supply sufficient reasons to justify the current carbon price? (9) Does REDD+ achieve climate goals through the voluntary carbon markets? and (10) Does REDD+ ensure sustainability of the ongoing projects? While discussing the questions, we have referred to global environmental issues of deforestation, emissions, transparency, decentralized governance, indigenous and local communities, voluntary carbon market, price effect, and other various contemporary sustainability issues. We argue that REDD+ could be a low-hanging fruit and act as a complimentary action to achieve its climate goal if it can address the issues raised under those ten questions. • We have raised and discussed ten important issues for REDD+ to be successful • REDD+ is popularly discussed yet highly debated conservation initiative • Forest centric activities would be inadequate for achieve climate goals through REDD+ • Voluntary carbon market is a challenge for successful REDD+ institutions • REDD+ should secure resource ownership and management authorship of locals [ABSTRACT FROM AUTHOR]

Microgrid is a promising way to integrate renewable distributed generation into the electric power sector, which has received widespread attention. In this paper, a uniform capacity-constrained optimization model under different power purchase and sale price contracts is developed to explore the optimal green investment strategy for grid-connected microgrid (GCM) with three configuration types. The impact of renewable energy source endowment and incentive policy is focused when macrogrid's generators emit more pollution than GCM's non-renewable generators, such as in China and India. The results show that: (1) GCM with renewable generation can only be invested in a site with relatively abundant renewable endowment; (2) carbon tax effectively promotes the deployment of GCM with renewable generation and achieves carbon emission abatement, but excessive carbon tax cannot incentive investment in the most desired GCM type; (3) a subsidy trap is found under feed-in tariff (FIT) subsidy, which implies that the fade-out or exit of FIT subsidy is beneficial for microgrid's healthy development; (4) and the comparisons under different price contracts emphasize the importance of macrogrid providing non-discriminatory access to feed-in and feed-out services to microgrid. • Investment strategy is explored for grid-connected microgrid (GCM) with three types. • Renewable source endowment and incentive policy determine the investment for GCM. • Excessive carbon tax cannot incentive investment in the most desired renewable GCM. • The fade-out or exit of FIT subsidy is beneficial for healthy GCM deployment due to the subsidy trap. • Emphasizing the importance of macrogrid providing non-discriminatory services to GCM. [ABSTRACT FROM AUTHOR]

The shipping industry must delineate feasible switching pathways of emission reduction technologies for vessels if it wants to meet the emission reduction targets set forth by the International Maritime Organization (IMO). This paper introduces a programming model integrating power systems, alternative fuels, and air emission control measures to decarbonize bulk vessel operations. The model captures the uncertainty in fuel prices and carbon emission prices. Reliable decision-making schemes are generated using interval quadratic programming. The results reveal that power systems will switch from mono-fuel internal combustion engines (MF ICE) to dual-fuel internal combustion engines (DF ICE). Traditional fossil fuels will progressively give way to carbon-neutral alternatives. The combination of air emission control measures will markedly reduce emissions. • Combining emission reduction technologies for four types of bulk vessels. • Selection of power systems, alternative fuels and air emission control measures. • Reliable schemes with the aid of interval programming and recourse actions. • Decarbonization technology pathways for bulk vessels across diverse scenarios. [ABSTRACT FROM AUTHOR]

• A CGE model elaborately depicting six CCS technologies was developed. • Impacts of four CCS incentive scenarios on decarbonization pathways were simulated. • CCS can sequester 960 ∼ 1,604 MtCO 2 annually in China by 2060 with policy incentives. • CCS incentives can reduce China's future primary energy demand by 7.7 ∼ 17.4 %. • CCS incentives can increase GDP by 5.64 ∼ 6.59 % compared to no policy scenario. Carbon capture and storage (CCS) technology, considered as a pivotal tool in mitigating climate change within the fossil energy system, particularly in China, has experienced slower development than expected. The exploration of direct incentive policies to facilitate its growth remains relatively underdeveloped. This study developed a hybrid dynamic computable general equilibrium (CGE) model to simulate the substantial impacts of CCS incentive policies on China within the context of carbon neutrality target. Two potential incentive policies, carbon emission trading system (ETS) and 45Q tax credit, were simulated, with different sectoral coverage. The results indicate that CCS technologies can reduce carbon emissions by 960 ∼ 1,604 MtCO 2 annually by 2060 through the strategic implementation of these incentive policies. The 45Q tax credit demonstrates its effectiveness in promoting early-stage research and development (R&D) and demonstration of CCS, while the ETS policy facilitates the commercial development of CCS in the later stage of development. By 2060, the implementation of CCS incentive policies could potentially result in 7.7 ∼ 17.4 % reduction in China's primary energy consumption, 71.2 ∼ 82.7 % decrease in the carbon price of ETS and 5.64 ∼ 6.59 % increase in the GDP compared with the no-policy scenario. In addition, the sectoral output in various sectors and the welfare of urban and rural households also increase. This paper provides an important reference for the realization of China's carbon neutrality goal and the model framework can be applied to other countries. [ABSTRACT FROM AUTHOR]

Multi-energy systems with carbon capture system (CCS) and power to gas (P2G) can reduce carbon emissions while increasing the consumption of renewable energy. This paper proposed a long-term equilibrium including electricity, gas and carbon markets to study the price effect of the system and its impact on the carbon-gas- electricity sector. The simulation results indicate that the main impact of the system on the electricity sector is to reduce energy curtailment and provide flexible resource for the electric system. P2G used an excess of 22.21 TWh of renewable energy, while CCS used 2.65 TWh of electricity to operate the capture system. The multi-energy system will reduce the market clearing price in the gas market (the annual average gas price decreased from 276.90 to 276.30 yuan/MWh). However, the partial transfer of flexibility to the electricity sector may increase cost in the gas industry, which in turn will be transferred back to the electricity sector again. In addition, through the operation of multi-energy system, carbon elements will circulate in the three sectors. CCS will become a carbon price-maker when electricity scarcity and carbon quota tightening, and increase carbon prices, which will increase the utilization hours of CCS and P2G and their profitability. • A carbon-gas-electricity market coupling model is proposed. • The multi-energy system will reduce the market clearing price in the gas market. • The partial transfer of flexibility may increase cost in the gas industry • CCS will become a carbon price-maker when electricity scarcity. [ABSTRACT FROM AUTHOR]

Equilibrium capacity expansion is an effective tool to help regulators predict the generation evolution of power systems by analyzing the decision-making of generation companies (Gencos). With the development of carbon markets (CMs) and electricity markets (EMs), Gencos' decisions in these two markets (encompassing investment and bidding decisions related to carbon emission allowances and electricity) are deeply intertwined through market clearing results. However, existing studies mainly focus on equilibrium capacity expansion with fixed carbon prices and usually ignore the realistic clearing process of CMs, which cannot simulate Gencos' coupled decision-making and accurately predict generation evolution under the CMs and EMs. This paper proposes a two-level equilibrium capacity expansion model for power systems which considers the coupled decisions of Gencos between CMs and EMs. At the upper level, multiple Gencos' coupled decision models are proposed based on their interaction with market clearing results. At the lower levels, CMs and EMs are respectively cleared to determine the varying carbon and electricity prices. Furthermore, the developed equilibrium capacity expansion model is reformulated as an equilibrium problem with equilibrium constraints (EPEC), which is solved by a diagonalization-based solution procedure. Finally, a provincial power system of southeast China is used to validate the performance of the proposed framework. The results illustrate that under CMs and EMs, non-fossil energy would account for 81.3% of total capacity and 73.88% of total generation in 2050. Compared to the existing model using fixed carbon prices, the consideration of realistic carbon market clearing will promote the installation of renewable energies and improve social welfare. The proposed model can provide beneficial references for regulators to perceive the evolution of power systems in CMs and EMs. • A two-level equilibrium capacity expansion model for power systems is proposed. • A novel coupled decision model for Gencos in CMs and EMs is developed. • The proposed model is solved by a diagonalization based solution procedure. • The results can guide the transition of power systems under the CMs and EMs. [ABSTRACT FROM AUTHOR]

Achieving carbon neutrality is probably one of the most important challenges of the 21st century for our societies. Part of the solution to this challenge is to leverage renewable energies. However, these energy sources are often located far away from places that need the energy, and their availability is intermittent, which makes them challenging to work with. In this paper, we build upon the concept of Remote Renewable Energy Hubs (RREHs), which are hubs located at remote places with abundant renewable energy sources whose purpose is to produce carbon-neutral synthetic fuels. More precisely, we model and study the Energy Supply Chain (ESC) that would be required to provide a constant source of carbon-neutral synthetic methane, also called e-NG (electric Natural Gas) or e-methane (electric methane), in Belgium from an RREH located in Morocco. To be carbon neutral, a synthetic fuel has to be produced from existing carbon dioxide (CO 2) that needs to be captured using either Direct Air Capture (DAC) or Post Combustion Carbon Capture (PCCC). In this work, we detail the impact of three different carbon sourcing configurations on the price of the e-methane delivered in Belgium. Our results show that sourcing CO 2 through a combination of DAC and PCCC is more cost-effective, resulting in a cost of 146 €/MWh for e-methane delivered in Belgium, as opposed to relying solely on DAC, which leads to a cost of 158 €/MWh. Moreover, these scenarios are compared to a scenario where CO 2 is captured in Morocco from a CO 2 emitting asset that allow to deliver e-methane for a cost of 136 €/MWh. • Model energy supply chain from Morocco to Belgium for electric methane; • Explore three CO2 sources for electric methane synthesis; • Analyse the pros and cons of each CO2 source on price and energy efficiency. [ABSTRACT FROM AUTHOR]

This study assesses alternative energy technologies (i.e., PV and battery systems, electric heat pumps, hybrid gas heating with solar thermal energy) in terms of profitability and CO 2 emissions, for the case of two simulated typical households living in detached houses in Germany. Under the status-quo regulatory framework, the energy transition in the heating sector is fostered through grants for replacing old heating systems, whereas PV generation is fostered by feed-in tariffs and indirect subsidies for self-consumption. This study considers an alternative regulatory scenario with a more market-oriented approach, finding that a CO 2 -oriented reform of energy surcharges and taxes, as well as a reform of network charges, can support a more cost-efficient energy transition in the residential sector. The paper concludes with a discussion of the consistency, cost efficiency and effectiveness of past and current policies underpinning the energy transition in the residential sector. • Assessment of home energy systems across 2 households and 2 regulatory scenarios. • Consideration of PV, batteries, heat pumps and hybrid gas-solar heating systems. • Comparison of subsidies and flat energy tariffs vs. cost-reflective, dynamic tariffs. • Market-oriented approach incentivizes far more cost-efficient CO 2 emission reduction. • The German residential energy sector needs a consistent regulatory framework. [ABSTRACT FROM AUTHOR]

[Display omitted] • It analyzes the feasibility of achieving net zero emission in the Chinese power sector by 2050 and the required policy measures. • It is essential to foster the concurrent development of renewable energy, energy storage, and demand response technologies. • The carbon pricing mechanism with exponential growth is more suitable. • Referring to the European offshore wind power investment model is beneficial for the development of offshore wind power in China. The low-carbon transition in China's power sector plays a crucial role in the mitigation of climate change worldwide, and increasing renewable energy penetration rate is widely recognized as the key approach to decarbonize this sector. This paper proposes a renewable energy penetration model to examine the feasibility for net zero emission by 2050 in China's power sector taking into account of economic and social development. It also evaluates the impacts of carbon pricing and financial incentives on renewable energy penetration and carbon emissions. The results indicate that along with economic development, China's electricity demand will continue to grow, but at a gradually slowing rate. It is possible for the power sector to achieve net zero emission by 2050 while meeting this growing electricity demand, with a renewable energy penetration rate of 75%. To ensure the achievement of the goal, we recommend setting the carbon price with the current market price as the baseline and increasing it annually by a relative increment index of 10%. Furthermore, given the high initial cost and late start of offshore wind power, we suggest incorporating associated grid connection cost into the transmission and distribution price to ensure the comprehensive and healthy development of renewable energy. [ABSTRACT FROM AUTHOR]

Carbon market is the most effective market tool for carbon emission reduction. China, the largest carbon emitter in the world, established the national carbon market in 2021, covering over 2000 key units in the power sector. Therefore, the forecasting of carbon price has profound implications for environmental and energy policies. In this paper, two traditional econometric model and three kinds of machine learning (ML) algorithms are used to predict carbon returns in the Chinese carbon trading market based on carefully selected predictors. Among all forecasting models, the Random Forest (RF) has the best forecasting performance, followed by some GARCH models using various factors. Compared with the traditional benchmark of ARMA model, the BP neural network (BP) and the GA improved BP method (GA-BP) are less competitive in predicting carbon returns in China because of their large forecasting errors. According to the optimal model, social attention to the carbon market, the international crude oil returns and the overall performance of the stock market are the most important predictors. The findings are robust to the change in the sample set. Overall, the ML approach shows an advantage in forecasting carbon returns, but the selection of predictors is also important. • Machine learning and econometric models are used to forecast carbon returns in China. • The selection of predictors is based on economic analysis. • The Random Forest (RF) outperforms the other ML and econometric methods. • The energy market is extremely important for predicting carbon returns. • Social concerns and stock market performance improve forecasting accuracy. [ABSTRACT FROM AUTHOR]

The socio-political processes that influence the acceptance of climate policies play a crucial role in shaping mitigation strategies. In this paper, we explore the interplay between social and political dynamics and their impact on climate policy support. Using a simplified model of the social and political system, we aim to uncover ways to enhance public support for climate change mitigation measures. Several factors come into play when considering policy support, including social norms, self-efficacy, social learning, and income. By examining climate mitigation policies and accounting for shifting and inherent preferences, we shed light on how individuals contribute to processes of social change. Through simulations, we find that even minimal peer pressure has a positive and significant impact on individuals' inclination towards green behaviours, regardless of whether regressive or progressive policies are implemented. Additionally, assuming uniform self-efficacy across society leads to an overestimation of society's acceptance of green policies. Our results highlight the importance of nurturing existing skills or developing new ones. Finally, our findings reveal that regional heterogeneity matters for climate policy acceptance. [ABSTRACT FROM AUTHOR]

Decarbonization is currently an urgent issue for the international shipping industry. The maritime Emission Trading Scheme (METS) is an effective measure, while the utilization of the Arctic Northeast Passage (NEP) and carriers' profit-driven reactions may affect its effectiveness. Thus, this paper proposed an optimization model to investigate the carrier's economic viability and the CO 2 emission under METS for the SCR/NEP-combined liner shipping service. Various METS scenarios are set based on 1) geographical scope (GS), 2) free emission quota percentage (FEQP), and 3) carbon price (CP). Results show that METS would guarantee a short-term CO 2 emission reduction within the GS, but the volume of overall CO 2 emission in some scenarios would be even larger. In individual cases, METS positively affects the carrier's economic viability. METS disincentivizes carriers to use the NEP, especially when it is implemented in the Arctic area or with high pricing. For carriers, the main countermeasure to cope with METS is slow steaming in the GS. Some valuable insights for policymakers designing METS: it is not the case that the higher the value of GS/FEQP/CP, the better the overall CO 2 emission reduction effect. A moderate GS and CP may be appropriate for balancing carriers' economic benefits and emission reduction efficiency, in whole or in part. FEQP can be set relatively low at the start of METS and raised gradually to motivate the carriers in emission control. [ABSTRACT FROM AUTHOR]

Promoting the trading of blue carbon generated by marine ranching (MR) is essential for China to achieve its carbon peaking and carbon neutrality goals. As blue carbon trading develops, it remains uncertain whether it can promote the transformation of marine ranching firm (MRF) from traditional fishery aquaculture-type MR (FAMR) to more eco-friendly conservation-type MR (CMR). This paper constructs a game model involving MRF and the government to explore the impact of blue carbon trading on the transformation of MRF' production modes by considering carbon asset renting, carbon cap-and-trade, government subsidies, and green investment, which is of great significance in managing coastal marine and aquatic organisms, as well as promoting sustainable development of the marine economy. Research shows that the price and demand of FAMR products are solely influenced by carbon cap-and-trade. The introduction of carbon rents will increase the incentive for MRF to choose CMR, and this incentive is further enhanced when government subsidies are provided. Concurrently, green investment and MRF's profit have an inverted-U relationship. Both government subsidies and blue carbon trading will increase blue carbon. Although this policy will also increase MRF's carbon emissions, the carbon surplus generated by MRF will be higher than without subsidies. • A game model considering MRF, and government was developed. • Carbon asset renting can lead MRF to choose greener CMR production mode. • MRF is more willing to provide green investments when subsidy is offered. • MRF's green investment volume has an inverted-U relationship with profits. • Government subsidies and blue carbon trading can increase carbon surpluses. [ABSTRACT FROM AUTHOR]

Carbon trading, one of the key policy instruments for reducing carbon emissions, can significantly contribute to the government's goal of achieving "peak carbon" and "carbon neutrality". Thus, under pressure from the government to implement carbon trading policies, enterprises often seek new low-carbon production technologies or business models. Meanwhile, outsourcing remanufacturing is often considered an effective means of promoting carbon reduction. Therefore, based on an outsourced remanufacturing model, we investigated the impact of carbon trading on the manufacturing/remanufacturing supply chain (SC) by constructing a game model involving an original equipment manufacturer (OEM) and an outsourced remanufacturer (OR) under decentralized versus centralized decision-making conditions. Furthermore, we designed a coordination mechanism to address the loss of benefits for the overall SC under decentralized decision-making conditions. We drew the following conclusions: (1) Whether in a decentralized or centralized decision-making model, there is a feasibility boundary condition when a government implements the carbon trading policy. Namely, the policy fails when the carbon trading price is greater than a certain threshold. (2) The decentralized decision-making approach reduces the sales of remanufactured goods and the recycling rate for used goods compared to the centralized decision-making paradigm, resulting in a marginal loss of profit. And, as the price of carbon trading rises, carbon trading regulations tend to expand the room for coordination of interests in the decentralized decision-making paradigm. (3) A single cost-sharing contract, while increasing revenues for OEM and SC, reduces revenues for OR. Profit-sharing contracts and fixed-cost contracts increase OEM and OR revenues, but overall SC profits are still lower than in the centralized decision-making model. Therefore, this paper combines revenue-sharing, cost-sharing, and fixed-fee outsourcing contracts to effectively achieve SC coordination. [ABSTRACT FROM AUTHOR]

In order to probe collaborative environmental governance (CEG) in China's "1 + N" policy framework for carbon peak and carbon neutrality, this paper applies the Actor-network theory (ANT) as an analytical framework to explore carbon reduction policy coordination. We then model ANT's relations with an evolutionary game theory (EGT) model to examine the evolutionarily stable strategies in CO 2 emission reduction by various actors including the central government, local governments, commercial banks, and polluting enterprises. Our objective is to examine policy coordination as the key enabler for governing success via an ANT-based mechanism design in China's institutional context. Combining the strength of ANT with a four-party EGT model, we investigate how to improve policy coordination to mobilize the actor-network for promoting CEG. Simulations are conducted to examine the effectiveness of policy coordination involving multiple policy instruments for controlling carbon emissions. The central government fulfills leadership in translating the interests of other actors and shaping the desired collaborative network. Without proper coordination, environmental policies may counteract each other. Government transfers and subsidies have direct impacts, but in the long run enhanced competitiveness and profitability of enterprises represent the intrinsic key to CEG success. From a methodology perspective, policy simulation in an EGT framework represents a novel addition to the research toolbox that expands ANT. [ABSTRACT FROM AUTHOR]

As an efficient technique to manage massive distributed energy resources (DER), the virtual power plant (VPP) can leverage the aggregated flexibility to enhance the economy and security of the system. However, few efforts have been reported on the carbon emission reduction benefit of the VPP. In this paper, a novel incentive mechanism for low-carbon demand response is designed, which is based on dynamic pricing and carbon intensity. Considering the uncertainty of renewable energy output characterized by the chance-constrained approach, a coordinated optimization model in the joint day-ahead energy, reserve and carbon market for the VPP operator and flexible consumers is proposed, including the pre-dispatch model, the energy storage systems (ESSs) incorporated carbon emission flow calculation model, and the bi-level final-dispatch model. Numerical simulations of both small-scale and large-scale cases demonstrate that the proposed low-carbon dispatch strategy can boost the payoff of the VPP operator, reduce carbon emissions in the joint energy-reserve-carbon market, and improve the robustness of the power system against uncertainty. • Low-carbon demand response (DR) to fully utilize the potential of the demand side. • Carbon emission flow model integrating energy storage systems. • Chance constrained approach to compensate for the uncertainties based on the versatile distribution. • The VPP engages in the joint energy-reserve-carbon market considering renewable energy uncertainties. [ABSTRACT FROM AUTHOR]

Due to the proliferation of distributed renewable energy, bidirectional electricity and carbon interaction appears in the coordinated transmission and distribution network and increases complexity in entities' decision-making. To address the issues, this paper develops a hierarchical market framework integrated with electricity and carbon trading. Specifically, an electricity market which combines locational marginal price (LMP) and peer-to-peer (P2P) trading is established considering transmission and distribution coordination. Meanwhile, based on carbon emission flow and P2P trading, a hierarchical coordinated carbon market is also designed to precisely measure and price carbon responsibility and contribution from prosumers. In addition, a hierarchical distributed algorithm is developed to clear the proposed market with privacy protection. Numerical results authenticate the necessity for transmission and distribution coordination, benefits of distribution electricity P2P trading as well as superiority in carbon measurement and pricing method. • An LMP-based electricity P2P market is designed for transmission and distribution network. • A systematic method is proposed to precisely price prosumers' carbon responsibility and contribution. • A hierarchical distributed algorithm is proposed to clear the P2P market under TSO-DSO-prosumer coordination. [ABSTRACT FROM AUTHOR]

Hydrogen produced from renewables-fuelled electrolysis has the potential to provide deep decarbonisation for sectors that are the most difficult to decarbonise, but the intermittency of renewable sources may result in low electrolyser utilisation and, consequently, high costs. This study determines the greenhouse gas (GHG) emissions and levelised cost of hydrogen (LCOH) associated with blending wind electricity with the grid to increase electrolyser utilisation. A novel cost model was developed to determine the production performance, costs and embodied CO 2 emissions of an electrolyser with hybrid fuel supply (wind and grid) considering dynamic load constraints of alkaline (ALK) and Proton exchange membrane (PEM) electrolysers and using high-resolution historical weather data to determine wind production profiles in two case study regions: northern (Bayannur) and southern (Pingtan) China. The results show that using 52% of grid electricity in an ALK electrolyser in Bayannur reduces LCOH by 11%, increasing hydrogen production by 74% but with 17.4 kg CO 2 / kg H 2 generated in CO 2 emissions. When a carbon price is accounted for, the optimal electrolyser utilisation is reduced to 40%, with the LCE 44% reduced. Emissions of 9.8 kg CO 2 /kg H 2 are lower than for stream methane reforming with carbon capture. In Southern China (Pingtan), LCOH is higher than Bayanur because of the high electricity cost. The economic benefits of increasing grid power depend primarily on the total CAPEX cost, grid power cost, and carbon tax. By altering the carbon tax, the optimal blend of wind/ grid differs. The grid contribution to the optimal blend diminishes as a carbon tax approaches 35 USD/ t CO 2. • This paper analyses the value of adding grid electricity to a pure wind-powered H 2 production plant. • The LCOH and CO 2 life-cycle emissions are obtained for Alkaline and PEM electrolysers. • We are introducing the novel ICOH metric to optimise the trade-off of LCOH and CO 2 emission on H 2 production. • Using only 52% of grid electricity in an ALK electrolyser, H 2 production can increase by 75%. [ABSTRACT FROM AUTHOR]

The sustained growth of global aviation emissions has highlighted the urgent need for using Sustainable Aviation Fuels (SAFs) to replace traditional aviation fuels to mitigate emissions. SAFs can potentially reduce greenhouse gas emissions by 50%–90% compared to conventional jet fuels. This paper collected aviation emissions data from South American routes between 2019 and 2021, and the GWP100 method was used to convert CH 4 and N 2 O emissions into CO 2 equivalents. Additionally, emissions from the South American route between 2023 and 2070 were predicted, as well as the amount of subsidy required to promote the use of SAFs under four different scenarios. The result shows that adopting SAFs could reduce approximately 69.3 million to 113.53 million tons of CO 2 -equivalent emissions in South America by 2070. However, the South American aviation industry will likely embrace using SAFs only if the carbon trading price exceeds 0.273 times the difference between SAFs and jet fuel prices. • This study calculates the emission reduction effects under four scenarios. • The GWP100 method is used to convert non-CO 2 emissions into CO 2 equivalent emissions. • SAFs can reduce 69.3–113.53 million tons of CO 2 -equivalent emissions by 2070. • Using SAFs is profitable when carbon price exceeds 0.273 times SAFs-kerosene price gap. • Using SAFs earlier will increase subsidies by $3.65–4.56 billion every five years. [ABSTRACT FROM AUTHOR]

As the financialization of carbon emission right, developing effective carbon asset trading strategy is important for both investors and regulators. Traditional trading strategy based on technical analysis is hardly profitable due to high complexity inherent in carbon markets. In order to increase investment returns and reduce risk in carbon market, this paper introduces PSO-VMD-DRL, an innovative carbon asset trading strategy that integrates signal decomposition technology and deep reinforcement learning (DRL). Firstly, the carbon price is decomposed into multiple components by variational mode decomposition (VMD) optimized through particle swarm optimization (PSO) to extract frequency features and reduce noise. Then state representation of the environment (state space) is constructed based on the components and transaction data. Finally, deep reinforcement learning (PPO, A2C, DDPG) are performed separately based on state space to learn optimal trading strategy. Empirical studies based on the data from carbon markets of Hubei and Guangzhou validate that PSO-VMD-DRL can adapt to carbon asset with the better profitability and risk resistance. The PSO-VMD-DRL outperform the other comparison strategies with superiority in all evaluation indices, achieving annual return of 21.39%, 17.67%, 25.50% and 46.34%, 44.55%, 43.03% in carbon market of Hubei and Guangzhou. [ABSTRACT FROM AUTHOR]

As the massive carbon emissions from the power system, the shift of the power system to low-carbon becomes inevitable. In this context, this paper proposes a Stackelberg game approach to develop the operational strategy of energy hubs, which considers the reward and punishment ladder carbon trading mechanism and the coupling of electrothermal demand. To avoid the fixed carbon price in the past and the neglect of the incentive space for carbon trading, a ladder carbon trading mechanism of rewards and punishments is introduced to effectively depict carbon trading costs. The electrothermal coupling of the demand side is incorporated into the Stackelberg game model, and the flexible consumption model of users participating in the integrated demand response is established. The above model is solved by combining heuristic algorithm with solver CPLEX, which can solve the data privacy leakage problem of both parties. Simulation results show that the strategy can bring economic benefits to energy hub operators and users. Carbon emissions across the system were reduced by 14.4 %. Users with electric heating equipment can fully improve the electric load and heat load adjustment level, and improve their economic benefits by 2.4 % at the cost of a 3.2 % increase in carbon emissions. • Consider influence of demand-side electrothermal coupling on carbon emission. • Reward-punishment ladder carbon trading increases economic benefits by 16 %. • Using energy flexibly increases benefits by 2.4 % and carbon emissions by 3.2 %. • The proposed game model is more appropriate for future energy pricing strategies. • The solution method can better protect the data privacy of both parties. [ABSTRACT FROM AUTHOR]

With the development of low-carbon energy, the use of thermal and hydropower units for regulation in the power system dominated by new energy (PSDNE) is decreasing. Electric buses (EBs) are expected to become the primary dispatching objects in this context. Accurately evaluation EB's response capability (RC) is vital for the scheduling operation of the PSDNE. However, current evaluation methods for EB's RC are relatively crude, lacking detailed and quantifiable measures. This paper proposes a novel multi-dimensional evaluation method to provide the aforementioned RCs. The EB operational schedule revise model considering traffic and temperature is proposed to obtain more accurate EB charging load by revise arrival charging time and remaining battery energy. The proposed EB charging model considering carbon emissions contributes to revealing the impact of various charging modes, such as low-carbon and electricity price, on the Eb's RC. The EB multi-dimensional evaluation model is established to obtain quantified and detailed RCs to support the operation of NEDPS. These capabilities include fast response within various periods, sustained response over extended durations, and remaining RC after executing scheduling instructions. Finally, using the actual data from an EB station of a city in China, the effectiveness of the proposed evaluation model is verified. [Display omitted] • The impact mechanisms of traffic and temperature on the EB's RC are revealed. • The accuracy of the revised EB's operating schedule is greatly enhanced. • The impact mechanisms of carbon emissions reduction on the EB's RC are revealed. • The EB's RC under different charging modes is quantitatively evaluated. • The fast RC, sustained RC, and remaining RC of the EB are quantitatively evaluated. [ABSTRACT FROM AUTHOR]

Under the background that China will achieve the goal of carbon neutrality by 2060, analyzing the impact of carbon neutral target constraints on the welfare of urban and rural residents is an important part of the design of a carbon emission reduction policy mechanism, in this paper, the dynamic recursive CGE(Computable general equilibrium) model is used to simulate the changes in welfare level, income consumption, and CO2 emissions of residents and their urban-rural heterogeneity under the policy of imposing a carbon tax on the fossil energy industry from 2022 to 2060. The results show that: compared with the BAU scenario, by 2060, first the income and consumption of residents will decrease slightly. Second, the target constraint of carbon neutrality makes the equivalent variation and compensate variation of urban and rural residents' welfare decrease slightly, and the equivalent variation and compensate variation of urban residents decrease more than those of rural residents. The following conclusions are drawn: first, the carbon-neutral target constraint makes the welfare of urban and rural residents decline slightly, but it will not have a strong impact on residents' income and consumption. Second, this constraint has a greater impact on the income, consumption and savings of urban residents than those of rural residents. [Display omitted] • A five-layer nested dynamic recursive CGE model is established to analyze residents' welfare. • Carbon taxes are incorporated into production decisions as a policy cost for energy companies. • The heterogeneity of the impact of carbon tax policy constraints on the welfare of urban and rural residents was analyzed. • The government needs to improve the intensive and diversified energy supply in rural areas to reduce the urban-rural gap. [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]

With the deterioration of natural resources and the aggravation of environmental pollution, there is a growing imperative to implement industrial green reform through green technology investment (GTI). This paper constructs a nonlinear dual-objective function by drawing on the theory of two-sided matching under the carbon trading regulation, aiming to examine GTI selection decisions made by two oligarchic manufacturers (i.e., oligarchs) and a monopoly supplier (i.e., supplier). The supplier offers multiple green technologies, while oligarchs rack their brains to buy green technologies in an attempt to exploit their social, economic and environmental potentials. Available technologies vary in terms of their environmental efficiency and cost. Then, a two-sided matching mechanism is constructed to explore the availability of stable matchings and examine the impacts of the carbon price and green improvement coefficient on GTI, product pricing decisions and profits within a competitive environment. Finally, a Monte-Carlo experiment is designed to analyze the impact of uncertain market risks on supplier's decisions. The results show that there is a two-sided matching mechanism that enables oligarchs and suppliers to obtain stable matching solution sets. Higher carbon prices lead to higher product prices, lower market demand, and improved environmental performance. Product price and market demand are positively correlated with investment volumes of oligarchs themselves and negatively correlated with those of their competitors. Investment risk has a certain negative impact on suppliers' profitability. [ABSTRACT FROM AUTHOR]

Sustainable Aviation Fuels (SAFs) are considered one of the potential ways for airlines to reduce emissions. However, African airlines may need more support using SAFs in underdeveloped regions. This paper calculates the carbon emissions from the international routes in Africa from 2019 to 2021 through the Modified Fuel Percentage Method (MFPM) and the ICAO standard method. The error rate is about 4.10%. Then, we predict the carbon emissions for each route and airline under different epidemic recovery paths and analyze the potential subsidies, the impact of SAFs price adjustment, and carbon trading price changes. It can be found that the more extensive the overall carbon emission base, the higher the cost of using SAFs. In addition, the higher the SAFs mixing ratio, the more the cost will increase. The average subsidy to promote SAFs will be 3492.82–3784.74 million dollars at a 50% mixed ratio. By 2025, if only the carbon price is not lower than 12.84 times the current price, or the SAF price is 1.412 times lower than the current aviation kerosene price, the African airlines may promote the SAFs. • Cost-benefit analysis of Sustainable Aviation Fuels (SAFs) in Africa aviation industry is done. • The average subsidy to promote SAFs will be 3492.82–3784.74 million dollars at a 50% mixed ratio. • Only the carbon price is not lower than 12.84 times, or the SAF price is 1.412 times lower, the African airlines may promote the SAFs. [ABSTRACT FROM AUTHOR]