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With the objectives of achieving "peak carbon" and "carbon neutrality", accurately quantifying the carbon emissions of road transportation becomes crucial. It is challenging to accurately describe the energy consumption of vehicles at both temporal and spatial scales from a macro perspective. Therefore, focusing on the quantitative model of vehicle micro energy consumption and road meso energy consumption, this paper reviewed and summarized the energy consumption model of road traffic in terms of data collection, quantification accuracy, and scope of application. Based on this analysis, this paper identifies the challenges of the current road traffic energy consumption model. Finally, we look forward to future research directions for studying quantitative models of energy consumption from road transportation. [ABSTRACT FROM AUTHOR]

Carbon price prediction is of great importance to regulators and participants in the carbon trading market. It is the basis for developing policies related to the carbon trading market and stabilizing that market. Considering the numerous factors that influence carbon prices in China, dimensionality reduction is needed to improve the prediction accuracy and efficiency. However, the traditional dimensionality reduction methods fail to fully consider the role of influencing factors, which has certain limitations. In this paper, a new dimensionality reduction method, namely scaled principal component analysis (s-PCA), is employed to improve the prediction accuracy of carbon prices. Firstly, a factor library that influence carbon prices is constructed from three perspectives: technical indicators, financial indicators and commodities indicators. Then, the s-PCA method is used to reduce the dimensionality of factors influencing carbon price. Next, two different methods are used to predict carbon prices, including traditional regression method and Long Short-Term Memory (LSTM) method. Finally, the economic value of the s-PCA method is examined by constructing investment portfolios. The empirical results of the Hubei Emissions Exchange show that the s-PCA model outperforms other competing models both in- and out-of-sample. In addition, the LSTM model could improve the performance of the s-PCA model in carbon price prediction. From a market timing perspective, investors can achieve a greater return and a larger Sharpe ratio using the s-PCA method than using other comparative methods and buy-and-hold strategy. Therefore, the s-PCA method is effective and robust in predicting carbon price. [ABSTRACT FROM AUTHOR]

The scope of this paper is the interpretation of sustainability through the university as a traditionally recognized, value-based institution of knowledge, based on the example of Central and Eastern Europe, Hungary. Its aim is to interpret sustainability from different aspects, using the example of Central and Eastern Europe, including Hungary. For this purpose, the paper reviews the development policy directions of the past period and institutional realizations through public databases. The results of the research show that there are different dynamics and focus in terms of resources and development implementations. From the point of view of sustainability, it represents that the use of resources with different dynamics and focus is a challenge for the institutions. [ABSTRACT FROM AUTHOR]

China's 2060 carbon neutrality target requires coal-fired power generation and coal consumption to shrink dramatically, or to introduce carbon capture, storage and utilization technologies (CCUS). In the provinces which produce a lot of coal and export it to other regions such as Shanxi Province, there are many severe challenges to achieve carbon neutrality goal. This paper constructs a provincial level Computable General Equilibrium Model for Shanxi Province to estimate the impacts on economy based on different decarbonization scenarios in power sector. Through comparison among the quantified scenarios, a sustainable pathway to coal phasing-out is also discussed in this research. The results indicate that in the simple phasing-out of coal thermal power scenario and single deployment of CCUS technology scenario, it will be a shock to GDP due to its coal-reliance economy. In the scenario which utilizes CCUS technologies and coal phasing out in the future, it proves that CCUS will mitigate economic impacts from 2025 to 2050. So, instead of coal phasing out, a sustainable pathway with accelerating change to thermal coal with CCUS is discussed in this research. It found that in this scenario, Shanxi province can keep a lower carbon intensity with a lowest carbon reduction cost of 3.62 k RMB/t. [ABSTRACT FROM AUTHOR]

This paper addresses two interlinked problems in sustainable development and suggests a methodology to resolve them. The first is the reduction of atmospheric greenhouse gas emissions, especially carbon dioxide. The second is the maintenance of biodiversity. Current carbon financing and environmental stewardship mechanisms underwhelm, often diluting intended positive effects. Most existing carbon credits do not have protection after 40 years, placing projects substantially beneath the C02 radiative forcing cycle. This paper presents the 'Balance' approach to sustainable development, including contractual principles ensuring C02 reduction, biodiversity enhancement and financial accountability. We describe two novel measures: a carbon calculator for commercial entities, and a new metric, the Balance Unit, combining biodiversity creation with carbon credits. A case study, spanning over 20 years at the Forest of Marston Vale, is then presented. It finds an increase in tree cover, CO2 sequestration, reduction in agricultural GHG emissions, sulphur dioxide and particulate matter absorption, and annual local economic benefits totalling £UK12.83 million. Expository detail regarding the 'Planting Principles' practised at Marston Vale is also provided. We argue that the Balance methodology, especially the Balance Unit, enables greater measurement reliability and long-term efficacy for maintaining biodiversity and reducing GHG emissions than current carbon financing approaches. [ABSTRACT FROM AUTHOR]

Carbon neutrality is an ambitious goal that has been promulgated to be achieved on or before 2060. However, most of the current energy policies focus more on carbon emission reduction, efficiency and high penetration of renewable energy. Thus, this paper presented a review strategy towards carbon neutrality by presenting the concept of a multi-energy system (MES) in terms of its technologies, configuration, modelling and feasibility as zero-emission equipment. The paper addressed some prominent challenges associated with zero-carbon multienergy systems (ZCMES). Various proven solutions in the extant studies that have been affirmed to alleviate some of these challenges were presented. In the end, we identified and summarised the current research gaps, and the future directions to ensure the feasibility of ZCMES as a primary strategy towards the actualization of carbon neutrality. Hence, this review work serves as a reference for revising the current energy policies to incorporate a carbon neutrality framework. [ABSTRACT FROM AUTHOR]

In this paper, we trace the social and material effects of a carbon verification encounter in Timor-Leste. Foregrounding the relational historicity of these resource materialities, we inquire into the disorientating but potentially generative place-based effects of carbon offsetting. We unpack carbon's elusive and unruly materiality through our participation in a verification event connected to a reforestation and carbon-offsetting program that encourages individuals and organisations from Australia to compensate for their greenhouse gas emissions by purchasing carbon credits from subsistence farmers in Timor-Leste. We interpret this making, or conjuring, of carbon through interactions between technical experts, program managers, staff, and participants over a 4-day audit of the program and, with the benefit of subsequent interviews with farmers, examine how the opacity of the carbon credit's materiality and its measurement leads to community scepticism and demands for greater methodological clarity and oversight. At the same time, we take issue with critics of market-based conservation programs who assert that carbon offsetting leads inevitably to severe adverse impacts for local communities. Activating a generative understanding of the economic logics of 'commodity indigenisation' through attention to the 'cultural biographies' or life cycle of things, we evidence fluid movements: complex socio-natural relations and moral economies that humanise nature to reveal and potentially reconfigure the otherwise alienating effects of carbon commodities and their socio-natural technical complex. [ABSTRACT FROM AUTHOR]

Carbon neutrality is the only way for green low-carbon development. Technological progress is an important starting point for improving energy efficiency. Through scientific and technological innovation, improving energy efficiency is a practical way to achieve the goal of carbon neutralization. Due to the limitation of data and index selection, there is no qualitative analysis of carbon neutrality in this paper. Compared with previous studies, the paper has the following contributions: Firstly, the energy efficiency score of China's provincial level is measured with the DEA method and it is found that the average energy efficiency score of the eastern region is the highest, followed by the western region, and finally the central region. The results also show that the energy efficiency is not in accordance with the economic growth. The regions with higher energy efficiency scores are not always economically developed because of huge energy consumption supporting the economic development. Secondly, the Tobit method is used to study the impact of the reverse technology spillover effect of OFDI on China's energy efficiency. The results show that the spillover effect has a significant positive effect on the improvement of China's energy efficiency, and has a positive impact on the eastern and western regions, but has no significant impact on the western region. Finally, we put forward some policy recommendations to increase energy efficiency to approach carbon neutrality and thus promote green economic development. This paper enriches the content of energy economy, the research method is innovative, and the conclusion is more scientific. [ABSTRACT FROM AUTHOR]

Under the background of "carbon peak and carbon neutrality", the interconnection of multiple regional integrated energy systems has become an important way to coordinate multiple energy sources and save energy and reduce emissions. This paper proposes a low-carbon economic dispatch model for multi-regional integrated energy systems considering the joint demand response mechanism; first, the concept and model of joint demand response are proposed, and on this basis, the energy conversion model between multiple energy forms in the multi-regional integrated energy system is studied; secondly, green certificate trading and carbon trading mechanisms are introduced, and green certificate trading and carbon trading are combined through the green certificate emission reduction mechanism; finally, a low-carbon economic dispatch model is proposed with the goal of minimizing the sum of system energy purchase cost, green certificate trading cost, carbon trading cost and joint demand response compensation cost. The example results show that the introduction of joint demand response mechanism and green certificatecarbon trading mechanism in the multi-regional integrated energy system reduces the total system cost and carbon emissions by 14.03% and 26.04% respectively. [ABSTRACT FROM AUTHOR]

This paper analyzes the theoretical mechanism by which urbanization and consumption structure upgrading exert an impact on carbon emissions in the context of promoting higher quality and efficiency in urbanization, advancing the transition and upgrading of consumption structure, and achieving carbon peaking and carbon neutrality (“dual carbon”) goals. By establishing an extended STIRPAT model and an intermediary model, this paper takes nine prefecture-level cities in Fujian Province from 2011 to 2021 as samples to investigate the effects of urbanization and consumption structure upgrading on carbon emission reduction in Fujian Province, revealing the interrelationship and transmission mechanism among the three. The results of this study show that: (i) The relationship between urbanization and carbon emissions in Fujian Province from 2011 to 2021 shows an inverted U-shaped curve, i.e. urbanization accelerated carbon emissions in the early stage and inhibited carbon emissions in the later stage; (ii) the regional heterogeneity analysis shows that under the current urbanization background, the upgrading of consumption structure in western and southern Fujian can significantly reduce carbon emissions, while the relationship between consumption structure upgrading and carbon emission reduction in eastern Fujian is not significant; (iii) the upgrading of consumption structure can help achieve and promote carbon emission reduction through increasing the proportions of the tertiary industry and immaterial consumption and enhancing the level of culture and education, while exerting little effect on carbon emission reduction through consumption in transportation, communication and health care. [ABSTRACT FROM AUTHOR]

This paper constructs a unique dataset of clean energy and collects firm-level green innovation data that matches it with provinces and cities. Then, this paper executes quasi-natural experiments on green innovation to examine the effects of China's emission trading policy on green innovation. Further, this paper introduces the interactive terms of the pilot time and pilot area dummy variables into the spatial Durbin model (SDM) and spatial dynamic panel model (SDPM) to construct quasi-natural experiments to examine the spatial effect. The findings confirm a negative association between the 'policy treatment effect' and green innovation. The results also indicate a significant negative association between the emissions trading policy and clean energy. Besides, the empirical results reveal a positive correlation between clean energy and green innovation; clean energy promotes green innovation in the region and the surrounding areas. This paper complements existing research and provides empirical evidence and policy implications for developing clean energy, promoting green innovation, and improving the emission trading policy. [ABSTRACT FROM AUTHOR]

As global climate change intensifies, nations around the world are implementing policies aimed at reducing emissions, with carbon-trading mechanisms emerging as a key market-based tool. China has launched carbon-trading markets in several cities, achieving significant trading volumes. Carbon-trading mechanisms encompass cap-and-trade markets and voluntary markets, influenced by various factors, including policy changes, economic conditions, energy prices, and climate fluctuations. The complexity of these factors, coupled with the nonlinear and non-stationary nature of carbon prices, makes forecasting a substantial challenge. This paper proposes a dynamic weight hybrid forecasting model based on a dual sliding window approach, effectively integrating multiple forecasting models such as LSTM, Random Forests, and LASSO. This model facilitates a thorough analysis of the influences of policy, market dynamics, technological advancements, and climatic conditions on carbon pricing. It serves as a potent tool for predicting carbon market price fluctuations and offers valuable decision support to stakeholders in the carbon market, ultimately aiding in the global efforts towards emission reduction and achieving sustainable development goals. [ABSTRACT FROM AUTHOR]

In order to support a low-carbon economy and manage market competition, location–inventory–routing logistics management must play a crucial role to minimize carbon emissions while maximizing customer satisfaction. This paper proposes a bi-objective mixed-integer nonlinear programming model with time window constraints that satisfies the normal distribution of stochastic customer demand. The proposed model aims to find Pareto optimal solutions for total cost minimization and customer satisfaction maximization. An improved non-dominated sorting genetic algorithm II (IMNSGA-II) with an elite strategy is developed to solve the model. The model considers cost factors, ensuring that out-of-stock inventory is not allowed. Factors such as a carbon trading mechanism and random variables to address customer needs are also included. An entropy weight method is used to derive the total cost, which is comprised of fixed costs, transportation costs, inventory costs, punishment costs, and the weight of carbon emissions costs. The IMNSGA-II produces the Pareto optimal solution set, and an entropy–TOPSIS method is used to generate an objective ranking of the solution set for decision-makers. Additionally, a sensitivity analysis is performed to evaluate the influence of carbon pricing on carbon emissions and customer satisfaction. [ABSTRACT FROM AUTHOR]

The traditional centralized optimization method encounters challenges in representing the interaction among multi-agents and cannot consider the interests of each agent. In traditional low-carbon scheduling, the fixed carbon quota trading price can easily cause arbitrage behavior of the trading subject, and the carbon reduction effect is poor. This paper proposes a two-layer dynamic community integrated energy system (CIES) low-carbon collaborative optimization operation method. Firstly, a multi-agent stage feedback carbon trading model is proposed, which calculates carbon trading costs in stages and introduces feedback factors to reduce carbon emissions indirectly. Secondly, a two-layer CIES low-carbon optimal scheduling model is constructed. The upper energy seller (ES) sets energy prices. The lower layer is the combined cooling, heating, and power (CCHP) system and load aggregator (LA), which is responsible for energy output and consumption. The energy supply and consumption are determined according to the ES energy price strategy, which reversely affects the energy quotation. Then, the non-dominated sorting genetic algorithm embedded with quadratic programming is utilized to solve the established scheduling model, which reduces the difficulty and improves the solving efficiency. Finally, the simulation results under the actual CIES example show that compared with the traditional centralized scheduling method, the total carbon emission of the proposed method is reduced by 16.34%, which can improve the income of each subject and make the energy supply lower carbon economy. [ABSTRACT FROM AUTHOR]

To respond to the goal of "carbon peaking and carbon neutrality," reducing carbon emissions in the construction industry is urgent and necessary. A sound profit allocation based on carbon emission reduction is essential to promote low-carbon initiatives implementation by construction supply chain enterprises. In this paper, considering the potential impact of an effective emission reduction scheme (ETS), the Stackelberg game models are established to explore the carbon emission reduction decisions and profit allocation mechanism under decentralized, collaborative and centralized decision-making scenarios between developers and contractors. By conducting a comparative analysis, we obtained insights into the level of enterprises' carbon emission reduction effort, the profit allocation proportion and the impact of ETS. The main findings can be summarized as follows. (1) The proportion of carbon emission reduction profit allocation in the collaborative scenario is higher than that in the decentralized one. (2) For contractors, carbon emission reduction efforts are the highest in the centralized scenario, followed by the collaborative one. For developers, the carbon emission reduction effort is highest in the centralized scenario, but is followed by the decentralized one. When the carbon emission reduction effectiveness of the contractor is greater than a certain level (about 0.52), the carbon emission reduction volume in the collaborative scenario is larger than that in the decentralized scenario. (3) Total profits are most sensitive to carbon trading prices in the centralized scenario, followed by the collaborative scenario. This research provides valuable reference for the government and construction enterprises to promote carbon emission reduction initiatives and low-carbon development in the construction sector. [ABSTRACT FROM AUTHOR]

The digital economy has played a vital role in changing economic and social development patterns and has had a multifaceted impact on carbon neutrality. This paper strives to contribute to the existing research by analyzing the relationship between the digital economy and electricity consumption intensity and providing a comprehensive understanding of the mechanisms that influence the digital economy and energy consumption, particularly focusing on electricity consumption intensity through the construction of a theoretical model. To fulfill this objective, this study introduces the development level of the digital economy into the production function of representative power enterprise, constructs a partial theoretical equilibrium analysis framework, calculates provincial digital economy development indices for Chinese provinces from 2013–2021 using the CRITIC method, and examines the impact of the digital economy on power consumption intensity. The results show that the digital economy can reduce the intensity of power consumption. A unit standard deviation increase in the digital economy development level reduces power consumption intensity by 0.1008 standard deviations. The study also conducts a mechanism analysis with economic growth as the mediating variable, which shows that the digital economy promotes economic growth and reduces electricity consumption intensity. The moderating effect of the digital economy on power consumption is further examined using local government fiscal pressure as the moderating variable. The results show that the impact of the digital economy on reducing power consumption intensity decreases with the increase of government fiscal pressure. This study not only contributes to practical applications but also enhances our comprehension of the interplay between the digital economy and power consumption. On the one hand, the development of the digital economy can reduce power consumption, thus reducing carbon emissions and achieving low-carbon growth. On the other hand, central governments can promote the development of the digital economy by reducing the fiscal pressure on local governments through transfer payments. [ABSTRACT FROM AUTHOR]

CO2 geological utilization and storage (CGUS) is a key technology to achieve carbon neutrality goals. To apply CGUS on a larger scale, the issue of steel corrosion during the process must be addressed to mitigate technological risks. This paper provides an overview of CO2-induced steel corrosion mechanisms and identifies factors that influence corrosion. The impact of CO2 partial pressure, temperature, salinity, pH, impurities, and fluid flow on steel corrosion behavior are also discussed. With the presence of water, the corrosive effect of supercritical CO2 on steel is stronger than that of dissolved CO2 or gaseous CO2. As the temperature increases, the corrosion rate of steel first increases and then decreases. Increasing salinity and decreasing pH lead to an accelerated corrosion rate of steel. Corrosion inhibitors, coatings, and corrosion-resistant alloys are recommended protective measures against CO2-induced corrosion. Compared with coatings, corrosion inhibitors and corrosion-resistant alloys are more commonly used in CGUS projects. Future research directions include further exploration of the mechanisms underlying CO2-induced steel corrosion, clarifying the coupled effects of various environmental factors, and developing corrosion protection technologies under high-pressure and high-concentration CO2 conditions. [ABSTRACT FROM AUTHOR]

The collection of papers in this special issue examines empirical evidence from Asia, Europe, and North America, analyzes how climate change affects the spatial economy, and explores the feasibility of carbon neutrality as a countermeasure to climate change. It begins by discussing the research background, the motivation for emphasizing spatial considerations, and the analysis in climate change studies. Each accepted paper is then elaborated upon regarding topic selection, methodology, and findings. The issue highlights the crucial role of spatial elements in climate studies and aims to inspire further research in this direction. By leveraging regional science and analytical tools, the goal is to develop more effective and equitable policies for carbon abatement. [ABSTRACT FROM AUTHOR]

Land is being degraded rapidly worldwide. United Nations Convention to Combat Desertification in 2015 has invited countries to formulate voluntary targets to achieve Land Degradation Neutrality (LDN). Under the Paris Agreement, a legally binding international treaty adopted in 2015, the world is transitioning toward Carbon Neutrality (CN) with more mitigation actions. This paper intended to review the concepts of land degradation, LDN along with CN emphasizing the degradation types, approaches, models available to analyze, synergies, economic aspects and challenges. The review explores approaches and models available for achieving LDN and CN which are both synergistic, economically efficient and could overcome the common challenges. Land degradation has to focus beyond the traditional definitions to incorporate more persistent and the difficult to restore degradation causes. Such complex land degradation requires specialized LDN approaches. The level of degradation and restoration progress could be analyzed using a variety of modeling approaches including economic models. Approaches for LDN and CN can bring significant synergies for each other. The approach proposed by the present study will provide a logical flow for decision-making while minimizing time and effort and avoiding a piecemeal approach. The approach therefore maximizes the output in relation to the inputs thus enhancing sustainability. [ABSTRACT FROM AUTHOR]

The paper addresses the overlooked interaction between power-to-gas (P2G) devices and carbon capture and storage (CCS) equipment, along with the stepwise carbon trading mechanism in the context of current multi-park integrated energy microgrids (IEMGs). Additionally, it covers the economic and coordinated low-carbon operation issues in multi-park IEMGs under the carbon trading system. It proposes a multi-park IEMG low-carbon operation strategy based on the synchronous Alternating Direction Method of Multipliers (ADMM) algorithm. The algorithm first enables the distribution of cost relationships among multi-park IEMGs. Then, using a method that combines a CCS device with a P2G unit in line with the tiered carbon trading scheme, it expands on the model of single IEMGs managing thermal, electrical, and refrigeration energy. Finally, the comparison of simulation cases proves that the proposed strategy significantly reduces the external energy dependence while keeping the total cost of the users unchanged, and the cost of interaction with the external grid is reduced by 56.64%, the gas cost is reduced by 27.78%, and the carbon emission cost is reduced by 29.54% by joining the stepped carbon trading mechanism. [ABSTRACT FROM AUTHOR]

To promote sustainable economic development in the Belt and Road region of China, reducing carbon emissions is essential. The construction industry is a major contributor to carbon emissions in China. Therefore, studying the dynamic evolution of carbon emissions from the construction industry in this region and its driving factors is of great significance for effectively controlling emissions and achieving China’s carbon peak and carbon neutrality targets. This paper first employs the Slope model, Moran’s I index, and standard deviation ellipse to reveal the spatial-temporal characteristics of carbon emissions from the construction industry, and then applies the geographical detector model to identify the main driving factors of carbon emissions. The results indicate that: (1) From 2006 to 2021, the total carbon emissions showed a fluctuating growth trend, and there were significant differences in emissions among different regions. (2) Carbon emissions in most provinces exhibited a moderate growth trend, and there was significant spatial correlation and aggregation of inter-provincial emissions. Regional carbon emissions from 2006 to 2021 showed a spatial distribution pattern from northeast to southwest, with a weakening trend, and the center of gravity mainly distributed in the east of the region. (3) Labor input, urbanization rate, total output value of the construction industry, degree of opening up, and energy intensity are the main factors influencing the spatial heterogeneity of carbon emissions from the construction industry, and the majority of the interaction types between factors were bivariate enhancement. This study aims to provide theoretical support for policymakers to formulate appropriate policies for building energy conservation and emission reduction. [ABSTRACT FROM AUTHOR]

CO2 capture from coal power plants is an important and necessary solution to realizing carbon neutrality in China, but CCS demonstration deployment in power sector is far behind expectations. Hence, the reduction potential of energy consumption and cost for CCS and its competitiveness to renewable powers are very important to make roadmaps and policies toward carbon neutrality. Unlike the popular recognition that capturing CO2 from flue gases is technically and commercially mature, this paper notes that it has been proved to be technically feasible but far beyond technology maturity and high energy penalty leads to its immaturity and therefore causes high cost. Additionally, the potential energy penalty reduction of capture is investigated thermodynamically, and future CO2 avoidance cost is predicted and compared to renewable power (solar PV and onshore wind power). Results show that energy penalty for CO2 capture can be reduced by 48%-57%. When installation capacity reaches a similar scale to that of solar PV in China (250 GW), CO2 capture cost in coal power plants can be reduced from the current 28-40 US$/ton to 10-20 US$/ton, and efficiency upgrade contributes to 67%-75% in cost reduction for high coal price conditions. In China, CO2 capture in coal power plants can be cost competitive with solar PV and onshore wind power. But it is worth noting that the importance and share of CCS role in CO2 emission reduction is decreasing since renewable power is already well deployed and there is still a lack of large-scale CO2 capture demonstrations in China. Innovative capture technologies with low energy penalties need to be developed to promote CCS. Results in this work can provide informative references for making roadmaps and policies regarding CO2 emission reductions that contribute towards carbon neutrality. [ABSTRACT FROM AUTHOR]

In the quest to achieve "double carbon" goals, the urgency to develop an efficient Integrated Energy System (IES) is paramount. This study introduces a novel approach to IES by refining the conventional Power-to-Gas (P2G) system. The inability of current P2G systems to operate independently has led to the incorporation of hydrogen fuel cells and the detailed investigation of P2G's dual-phase operation, enhancing the integration of renewable energy sources. Additionally, this paper introduces a carbon trading mechanism with a refined penalty–reward scale and a detailed pricing tier for carbon emissions, compelling energy suppliers to reduce their carbon footprint, thereby accelerating the reduction in system-wide emissions. Furthermore, this research proposes a flexible adjustment mechanism for the heat-to-power ratio in cogeneration, significantly enhancing energy utilization efficiency and further promoting conservation and emission reductions. The proposed optimization model in this study focuses on minimizing the total costs, including those associated with carbon trading and renewable energy integration, within the combined P2G-Hydrogen Fuel Cell (HFC) cogeneration system. Employing a bacterial foraging optimization algorithm tailored to this model's characteristics, the study establishes six operational modes for comparative analysis and validation. The results demonstrate a 19.1% reduction in total operating costs and a 22.2% decrease in carbon emissions, confirming the system's efficacy, low carbon footprint, and economic viability. [ABSTRACT FROM AUTHOR]

As global warming intensifies, the world is increasingly concerned about carbon emissions. As an important industry that affects carbon emissions, the air transportation industry takes on the important task of energy saving and emission reduction. For this reason, major airlines have designed or will design different kinds of new-energy aircraft; however, each aircraft has a different scope of application according to its energy source. Biofuels have an obvious carbon emission reduction effect in the whole life cycle, which can offset the drawback of the high pollutant emission of traditional fossil fuels in the preparation and combustion stages. At the same time, a battery has zero emissions in the operating condition, while the low energy density also makes it more applicable to short-range navigation in small aircraft. In this paper, the development direction of a biofuel–electric hybrid aircraft is proposed based on the current development of green aviation, combining the characteristics of biofuel and electric aircraft. [ABSTRACT FROM AUTHOR]

Carbon storage services play an important role in maintaining ecosystem stability. Land use/cover change (LUCC) is the main factor leading to changes in ecosystem carbon storage. Understanding the impact of LUCC on regional carbon storage changes is crucial for protecting regional ecosystems and promoting sustainable socio-economic development. This paper selects Shanxi province as the study area and explores the spatial and temporal evolution characteristics of carbon storage in Shanxi province based on the InVEST model and univariate spatial autocorrelation. The results show that the total carbon storage in Shanxi Province in 2000, 2010, and 2020 is 513.51 × 104 t C, 513.46 × 104 t C, and 509.29 × 104 t C, respectively. High carbon storage areas are distributed in forest and grassland land types, while low carbon storage areas are widely distributed in building land in urban metropolitan areas. Shanxi Province is mainly dominated by farmland, which has decreased by 3448.60 km2 in the past 20 years. Grassland has decreased by 1588.31 km2 and the area of building land has increased by 4205.73 km2. Due to the influence of carbon conversion among different land use types, the total carbon storage loss of Shanxi Province in the past 20 years was 4.21 × 104 t C. The transfer of farmland resulted in an increase in carbon stock of 14.46 × 104 t C. The transfer of grassland resulted in an increase of 17.15 × 104 t C, while the transfer of forest resulted in a decrease of 41.44 × 104 t C. The increase in land use types with low carbon density and the decrease in land use types with high carbon density led to the decrease in carbon storage in Shanxi Province. Furthermore, social factors were more likely to influence the carbon storage than natural factors, and the influence of social factors was often negative. On this basis, regional development countermeasures were proposed for the current situation of carbon storage in Shanxi Province and provide a scientific basis for Shanxi Province to achieve the carbon neutrality target. [ABSTRACT FROM AUTHOR]

Under the background of "dual carbon" strategy, the integration of renewable energy adds volatility to the grid. Relying solely on generation-side resources for regulation is inadequate, necessitating a flexible demand response from diverse demandside resources. This paper employs a physical connection and information exchange between the distribution network and microgrids to leverage the advantages of centralized-distributed optimization. This establishes a coordinated demand response model between the distribution network and microgrids, gradually establishing a new type of distribution network that integrates interconnected grids and microgrids. This also necessitates the analysis of the response characteristics of various load resources within microgrids and the categorization and modeling of loads based on their response speeds. Additionally, a method for evaluating the multi-time scale schedulable capacity of microgrids is proposed. Finally, a coordinated demand response model between the distribution network and microgrids based on the schedulable capacity assessment is established. This model is validated through case studies, demonstrating its effectiveness. The coordinated demand response between distribution networks and microgrids enables them to operate in a collaborative and economically safe manner. [ABSTRACT FROM AUTHOR]

In view of water eutrophication, global energy crisis and the carbon neutrality policies, the ammonia recovery from wastewater with high efficiency and low energy consumption is crucial for preserving the ecological environment and achieving sustainable development. Transmembrane electro-chemisorption (TMECS), which integrates transmembrane chemisorption with electrochemical systems to reduce the addition of chemicals and improve recovery efficiency, is a promising technology for ammonia recovery from wastewater. Accordingly, this paper first reviews the recent advances in TMECS for ammonia recovery from wastewater. In particular, the technology principles, including ammonia stripping by cathodic base, ammonia recovery by TMECS with authigenic acid and base, and ammonia recovery by membrane cathode with in situ cathodic base are elucidated. Couplings of TMECS with other electrochemical systems, including electrodialysis, flow-electrode capacitive deionization, and electrochemical precipitation, are further summarized and compared. Finally, the challenges and prospects of the TMECS technology are addressed. [ABSTRACT FROM AUTHOR]

The "Dual Carbon" initiative is a two-stage carbon reduction goal proposed by China, with significant implications for global climate change mitigation. This article examines the impact of the "Dual Carbon" strategy on China's forestry development and explores how to leverage this strategy to facilitate the transformation and advancement of the forestry sector. Current review indicated that forestry has the advantage of achieving higher emission reduction targets at a low cost. Starting with an overview of the "Dual Carbon" strategy, this paper analyzes the carbon sequestration potential of plants and soil, and the challenges and opportunities faced by forestry development under this framework. Furthermore, we outline implementation pathways for forestry development, aiming to provide insights for the progress of China's forestry sector. Overall, it should be noted that the priority is to vigorously develop timber resources, and we also need to vigorously develop and protect forestry talent with the support of China's policies. By trapping into the carbon storage capabilities and leveraging carbon trading mechanisms of forests, a favorable ecological environment can be created, thus achieving the goal of carbon neutrality. Highlights: • Forest development and its carbon sinks, attributed to plant and soil have the potential in carbon sequestration process, thus helping China achieve carbon neutrality. • The supply of forest products and the balance of economic growth and environmental protection are the key difficulties under the "Dual Carbon" strategy. • Trading forest carbon sinks can boost China's sequestration. [ABSTRACT FROM AUTHOR]

In the context of energy transition and carbon neutrality strategies, distributed renewable energy is widely emerging on the distribution side. However, due to the volatility and randomness characteristics of distributed renewable energy, its full absorption poses a huge challenge to the economy and stable operation of the power grid. Flexible resources on the demand side, represented by air conditioners and electric vehicles, can participate in grid dispatching, improving the economic efficiency and reliability of system operation. To this end, this paper proposes an intraday dispatch strategy for demand-side flexible resources based on two-stage optimization. First, based on a generalized energy storage model, the adjustable flexibility of demand-side flexible resources is modeled. Second, to hinder the uncertainties related with markets and demandside flexible resources, the rolling optimization is adopted for the optimal bidding, thus enabling demand-side flexible resources to participate in the intraday market with low risks of profit losses. Third, based on the bidding decision, real-time dispatch optimization is carried out to cope with the system operation deviation caused by forecast errors. Then, in the real-time control stage, the dispatch instructions are decomposed to the control units to achieve power tracking. Finally, the proposed method is simulated and verified on a test system. The results show that by coordinating the operation of demand-side flexible resources through two-stage optimization, the uncertainties of renewable energy output, market price, etc. Can be effectively overcome, and the economics of system operation can be improved. [ABSTRACT FROM AUTHOR]

Lignin, the most prevalent natural source of polyphenols on Earth, offers substantial possibilities for the conversion into aromatic compounds, which is critical for attaining sustainability and carbon neutrality. The hydrogen-transfer method has garnered significant interest owing to its environmental compatibility and economic viability. The efficacy of this approach is contingent upon the careful selection of catalytic and hydrogen-donating systems that decisively affect the yield and selectivity of the monomeric products resulting from lignin degradation. This paper highlights the hydrogen-transfer technique in lignin refinery, with a specific focus on the influence of hydrogen donors on the depolymerization pathways of lignin. It delineates the correlation between the structure and activity of catalytic hydrogen-transfer arrangements and the gamut of lignin-derived biochemicals, utilizing data from lignin model compounds, separated lignin, and lignocellulosic biomass. Additionally, the paper delves into the advantages and future directions of employing the hydrogentransfer approach for lignin conversion. In essence, this concept investigation illuminates the efficacy of the hydrogen-transfer paradigm in lignin valorization, offering key insights and strategic directives to maximize lignin's value sustainably. [ABSTRACT FROM AUTHOR]

China is transitioning into the digital economy era. The advancement of the digital economy could offer a fresh mechanism to attain carbon peak and carbon neutrality objectives. Applications of the digital economy, such as smart energy management, intelligent transport systems, and digital agricultural technologies, have significantly reduced carbon emissions by optimizing resource use, reducing energy waste, and improving production efficiency. This research does so by devising a theoretical model that looks into the multi-faceted power of the digital economy under a two-sector paradigm. Utilising a panel model, a mediation effect model and a spatial Durbin model to assess the digital economy's power on carbon emissions. This research has determined that the digital economy can significantly diminish carbon emissions, with green tech innovations and industrial transformation being key contributors. The spatial spillover effect was used for the digital economy to aid in lowering carbon emissions in adjacent districts and upgrading better environmental stewardship. The influence of the digital economy has better performance in lowering carbon emissions in mid-western China than in the eastern area. This paper deepens understanding of the drivers of low-carbon growth and the significance, mechanism and regional disparities of the digital economy's effect on reducing carbon emissions. It offers valuable policy insights and guidance for globally achieving digital economy growth, reducing carbon emissions and reaching carbon peak and neutrality goals. [ABSTRACT FROM AUTHOR]

As global climate change becomes increasingly severe, energy technology innovation has become a key means of coping with the climate crisis and realizing green and low-carbon development. However, existing literature rarely examines the effects of carbon emission reduction policies based on the perspective of energy technology progress for both short-term economic fluctuations and long-term equilibrium. This paper introduces the fossil energy technology sector and the renewable energy technology sector into the dynamic stochastic general equilibrium (DSGE) model, and compares the effectiveness of the carbon emission cap policy, the fossil energy technology subsidy policy, and the renewable energy technology subsidy policy under the framework of China's carbon trading market in promoting macroeconomic growth and controlling pollutant emissions. We found that in long-term, the emission reduction effect of the carbon emission cap policy falls short of the other two policies, and subsidizing fossil fuel technologies is more cost-efficient comparatively. The government expenditure shock can all stimulate macroeconomic growth with crowding out of private investment and household consumption, whereas the energy technology research productivity shock leads to a decline in total output and an increase in renewable energy technology demand. In addition, pollutant emissions are pro-cyclical under the impact of total carbon policies and counter-cyclical under the impact of energy technology subsidy policies. This article constructs a multi-technology sectoral dynamic stochastic general equilibrium model, expanding the research perspective and theoretical framework for evaluating carbon emission reduction policies. At the same time, it proves the importance of the government to implement the phased energy technology subsidy policy while implementing the carbon emission cap policy, which provides important enlightenment for the implementation and adjustment of carbon emission reduction policy. [ABSTRACT FROM AUTHOR]

Over the past two decades, the Taiwan government promulgated some regulatory measures and promotional actions on energy efficiency promotion and renewable energy development. In March 2022, the "Taiwan's Pathway to Net-Zero Emissions in 2050" was announced to respond to the Paris Agreement. In order to achieve the goal, the Climate Change Response Act (CCRA) was passed on February 15, 2023, requiring the de-carbonization measures and adaptation strategies. The main aim of this paper was to analyze the changes in GHG emissions and renewable energy supply by using the updated data from the official statistics in connection with the trends of environmental and energy sustainability since 2000. The findings showed that total installed capacity of renewable power (especially in solar power and wind power) showed an amazing increase over the past decade, leading to the inclined GHG emissions and thus supporting the environmental and energy sustainability toward a low-carbon society. Furthermore, this paper summarized the development history and main differences concerning the carbon neutrality policy and legislation in Japan and South Korea. For achieving the staged targets of GHG emissions by 2030 and 2050, this paper finally addressed the technological approaches for achieving carbon neutrality by 2050 in Taiwan, focusing on the transformation of energy and industry, and the policy implications by all levels of government. [ABSTRACT FROM AUTHOR]

This paper studied the characteristics of the carbon emission of an industrial wastewater treatment plant (IWWTP) and a domestic WWTP (DWWTP) located in a high-tech industrial park of Shaanxi Province, China. The results showed that the total carbon emissions of the IWWTP and DWWTP were 10.13 kg/t and 1.84 kg/t in 2020, respectively. Indirect carbon emissions play a dominant role in the total carbon emission of the IWWTP, which accounts for about 97.6% of the total amount. The direct carbon emissions of greenhouse gases (e.g., CH4, N2O) account for about 62% of the total carbon emissions in the DWWTP, followed by the indirect carbon emissions generated by electricity consumption (31.06%) and chemical consumption (6.94%). Additionally, the centralized recycling and re-utilization of the wastewater could achieve 1.06 kg/t and 1.16 kg/t of carbon emission reduction in the IWWTP and DWWTP, respectively, while the carbon emissions of the DWWTP are inversely proportional to the treatment capacity. Therefore, it is of great value to collect and utilize intensively the recycled water to achieve the goal of regional carbon emission reduction and carbon neutralization of WWTPs in industrial parks. [ABSTRACT FROM AUTHOR]

To address the challenges posed by global climate change, developing green energy systems characterized by informatization, digitalization, and intelligence is crucial for achieving carbon neutrality. This article is a research report type paper on water source heat pump (WSHP) energy stations, aiming to use digital twin technology and other information technologies to resolve conflicts between clean energy development and efficient energy utilization. The primary objective of this study is to identify and analyze issues in traditional energy station operations and management systems. Based on this analysis, specific technical solutions are proposed, including pathways for technological research, methodologies, and content. The results provide a comprehensive theoretical framework for the intelligent transformation of energy station systems and essential technical support for the WSHP energy station project in the Hankou Binjiang International Business District. The findings have significant implications for the widespread adoption of WSHP energy stations and the achievement of national carbon neutrality goals. [ABSTRACT FROM AUTHOR]

Recently, there has been an increasing effort to promote energy efficiency, using renewable energies and electric mobility to achieve a more sustainable future and even carbon neutrality by 2050. This paper aims to understand if combining these technologies leads to a win–win solution. For that, the system's characteristics that will be used for the simulation were defined as a residential community consumption scenario with and without electric vehicles charging overnight. The simulation was completed in software, and eight scenarios were tested: high population density/low population density with/without electric mobility and hourly tariff/simple tariff. After these scenarios had been tested, the conclusion was that the low population density and hourly tariff without and with electric mobility were the best two cases economically (in terms of levelized cost of energy, net present costs, and savings) and environmentally, and the worst was high population density with hourly tariff and electric mobility. Other scenarios were then tested, including changes in the load curve, namely a commercial load curve, and changes in the load curve of electric vehicle chargers, mainly daytime charging. The conclusion was that even though the initial hypothesis did not lead to a win–win solution, with changes in the hypothesis, the integration of electric mobility in energy communities might lead to that. [ABSTRACT FROM AUTHOR]

Current studies do not provide a consensus on whether digital technology innovation can reduce enterprise carbon intensity despite the rise of the digital economy. This paper examines the role and influence pathway of digital technology innovation on enterprise carbon intensity using data from A-share listed enterprises in China's manufacturing industry from 2012 to 2021. The findings indicate that (1) digital technology innovation has been found to significantly reduce enterprise carbon intensity, as confirmed by numerous robustness and endogeneity tests. However, its inhibitory effect on carbon intensity shows a marginal decreasing trend. (2) In the heterogeneity analysis, it was found that digital technology innovation significantly reduces the carbon intensity of consuming coal, coke, kerosene, and diesel. From various perspectives, including enterprise, industry, and external environment, there are significant differences in the carbon reduction effects of digital technology innovation. (3) The analysis of impact paths reveals that digital technology innovation can affect enterprise carbon intensity through three paths: improving productivity, enhancing green innovation efficiency, and adjusting energy consumption. (4) Upon further analysis, it was discovered that the spillover effect of digital technology innovation is more pronounced in the industry cohort of enterprises. Additionally, digital technology innovation plays a positive role in enhancing enterprise ESG performance. The paper's findings offer empirical evidence and decision-making references for the government to develop reasonable policies for reducing carbon emissions, promoting green and low-carbon enterprise transformation, and actively and steadily achieving the goal of carbon peaking and carbon neutrality. [ABSTRACT FROM AUTHOR]

There are many barriers to green job expansion in the EU linked to cultural, economic barriers, organizational, political, technological technical, social, and behavioral barriers. The main drivers of green job creation include social norms and rules, governance policies, cultural values, demographic data, socio-economic inclusion, technical, and technological elements, etc. The aim of this paper is to analyze barriers and drivers that can influence green job expansion. The case study on green jobs expansion in the EU is provided based on statistical data from EUROSTAT. The policies and measures aiming to cope with barriers to green job expansion and support drivers of these processes are recommended for EU countries based on research conducted. [ABSTRACT FROM AUTHOR]

To mitigate the impact of greenhouse gas (GHG) and air pollutant emissions, it is of utmost importance to understand where emissions occur. In the real world, atmospheric pollutants are produced by various human activities from point sources (e.g. power plants and industrial facilities) but also from diffuse sources (e.g. residential activities and agriculture). However, as tracking all these single sources of emissions is practically impossible, emission inventories are typically compiled using national-level statistics by sector, which are then downscaled at the grid-cell level using spatial information. In this work, we develop high-spatial-resolution proxies for use in downscaling the national emission totals for all world countries provided by the Emissions Database for Global Atmospheric Research (EDGAR). In particular, in this paper, we present the latest EDGAR v8.0 GHG, which provides readily available emission data at different levels of spatial granularity, obtained from a consistently developed GHG emission database. This has been achieved through the improvement and development of high-resolution spatial proxies that allow for a more precise allocation of emissions over the globe. A key novelty of this work is the potential to analyse subnational GHG emissions over the European territory and also over the United States, China, India, and other high-emitting countries. These data not only meet the needs of atmospheric modellers but can also inform policymakers working in the field of climate change mitigation. For example, the EDGAR GHG emissions at the NUTS 2 level (Nomenclature of Territorial Units for Statistics level 2) over Europe contribute to the development of EU cohesion policies, identifying the progress of each region towards achieving the carbon neutrality target and providing insights into the highest-emitting sectors. The data can be accessed at 10.2905/b54d8149-2864-4fb9-96b9-5fd3a020c224 specifically for EDGAR v8.0 (Crippa et al., 2023a) and 10.2905/D67EEDA8-C03E-4421-95D0-0ADC460B9658 for the subnational dataset (Crippa et al., 2023b). [ABSTRACT FROM AUTHOR]

Enhancing energy efficiency within the building sector is imperative to curbing energy losses, given that this sector alone contributes to over 34% of global energy consumption. Employing a building management system, along with its regular updates, presents a strategic avenue to decrease energy usage, enhance building energy efficiency, and more. Tailored control strategies, aligned with the unique characteristics and usage patterns of each building, are essential for achieving energy savings. This article presents an evaluation of HVAC system efficiency in office buildings, utilizing a data-driven approach coupled with simulations conducted in building performance simulation software. The research explores the control strategy of an office building equipped with a constant air volume HVAC system, featuring a regularly controlled air handling unit. The objective is to boost energy efficiency while striking a balance between occupant comfort and energy consumption. The findings indicate that by analyzing measured data and adjusting the configurable parameters, the energy consumption of buildings can be significantly reduced. The close monitoring of indoor parameters by building operators and making corresponding adjustments to the HVAC system can yield energy savings of up to 16%. Leveraging these insights, this paper suggests integrating data-driven and dynamic simulation methods into building management system models to optimize HVAC systems, enhance energy efficiency, and advance ambitious carbon neutrality objectives. [ABSTRACT FROM AUTHOR]

This study investigates the competitive issues of the newsvendor problem with product substitution under the carbon cap-and-trade system. Building on existing research, this paper introduces the carbon cap-and-trade system under uncertain market demand and considers that the original equipment manufacturer (OEM) can choose to procure raw materials from the contract manufacturer (CM), with both final products being substitutable. Furthermore, we explore the different substitution relationships between OEM and CM products under both pure competitive and co-opetitive modes. For this problem, decision models are developed for various scenarios, and optimal solutions satisfying given conditions are provided. We find that in one-way substitution, under pure competition, an increase in the OEM's (or CM's) green investment and substitution rate only leads to an increase in OEM's (or CM's) yields, while an increase in the OEM's (or CM's) green investment does not necessarily reduce CM's (or OEM's) yields. In the co-opetitive mode, an increase in the substitution rate and green investments of both manufacturers may lead to an increase in the yields of both manufacturers. Furthermore, an increase in carbon trading prices does not necessarily inhibit the manufacturer's yields. Moreover, we find that under the same competition mode, under certain conditions, two-way substitution between OEM and CM can bring better profits to both manufacturers and the entire supply chain. When the two modes are in the same substitution scenario, and the CM cannot substitute for the OEM, the optimal decisions and total supply chain profits of the two modes are equal. Finally, through numerical analysis, we find that neither mode is necessarily optimal when CM can substitute for OEM. Additionally, it is observed that when the same mode is in different substitution scenarios, total supply chain profits may be enhanced in the presence of product substitution. [ABSTRACT FROM AUTHOR]

With the challenge posed by global warming, accurately estimating and managing carbon emissions becomes a key step for businesses, especially power generation companies, to reduce their environmental impact. Optuna–LightGBM–XGBoost, a novel power and carbon emission relationship model that aims to improve the efficiency of carbon emission monitoring and estimation for power generation companies, is proposed in this paper. Deeply exploring the intrinsic link between power production data and carbon emissions, this model paves a new path for "measuring carbon through electricity", in contrast to the emission factor method commonly used in China. Unit data from power generation companies are processed into structured tabular data, and a parallel processing framework is constructed with LightGBM and XGBoost, and optimized with the Optuna algorithm. The multilayer perceptron (MLP) is used to fuse features to enhance prediction accuracy by capturing characters that the individual models cannot detect. Simulation results show that Optuna–LightGBM–XGBoost can achieve better performance compared to existing methods. The mean absolute error (MAE), mean squared error (MSE), mean absolute percentage error (MAPE), and coefficient of determination (R2) of the model are 0.652, 0.939, 0.136, and 0.994, respectively. This not only helps governments and enterprises to develop more scientific and reasonable emission reduction strategies and policies, but also lays a solid foundation for achieving global carbon neutrality goals. [ABSTRACT FROM AUTHOR]

Offshore wind energy entering the grid in coastal areas creates issues with the safe and stable operation of power systems. To control the carbon emission of power systems and increase the proportion of offshore wind consumption, a microgrid optimization model considering offshore wind power and carbon trading is proposed in this paper. To avoid the defect of Particle Swarm Optimization (PSO) falling into the local optimum prematurely, the PSO algorithm is improved by dynamically decreasing inertia weights and chaos factors. Combined with the powerful optimization capability of the genetic algorithm (GA), the improved PSO-GA algorithm is used to solve the model. The simulation results show that the improved algorithm iterates 11 times before the parameters reach the optimal value, with high convergence accuracy. The proposed approach can increase the proportion of offshore wind consumption and ensure the optimal economic performance of the system while reducing the carbon emission. [ABSTRACT FROM AUTHOR]

To achieve the goals of "carbon peaking and carbon neutrality", this paper puts forward the connotation and measurement method for the carbon emission intensity of urban industrial land and conducts an empirical study with the Yangtze River Economic Belt (YREB) as an example. We defined the carbon intensity of urban industrial land as the industrial carbon emissions per unit area of land, which is a spatial mapping of urban industrial economic development and carbon spillover and a key indicator for urban and territorial spatial planning oriented towards the "dual carbon" goal. Findings: The carbon emission density of industrial land in the YREB varied greatly between cities and exhibited significant positive spatial autocorrelation. In addition, the geographical pattern and spatio-temporal evolution model of the urban industrial land carbon emission density had a very complex driving mechanism, and different factors had significant synergistic effects. Therefore, it is suggested that while striving towards the goal of "dual carbon", the government should incorporate the carbon emission density indicator of urban industrial land into the urban and territorial spatial planning system, and based on the threshold of the medium suitable density, they should design differentiated management policies according to concrete urban policies and encourage cooperation among cities to jointly promote carbon emission management of urban industrial land. In policy design, emphasis should also be placed on highlighting the interactive effects of foreign direct investment, fiscal expenditure, and the number of patent authorizations as well as constructing a combination of policies centered around them to better leverage the impacts of globalization, government intervention, and innovation. [ABSTRACT FROM AUTHOR]

The pursuit of economic growth has implications for carbon emissions and climate change. Achieving low carbon development is important for attaining the targets of the sustainable development goals. Africa is often described as a largely import-dependent continent. The continent also requires significant investment in information and communication technologies (ICT) and renewable energy to achieve low-carbon economic growth. However, empirical evidence on the joint impacts of imports of goods and services, clean energy use, ICT, and economic growth on carbon emissions in Africa is scanty and mixed. This paper investigated the impacts of information and communication technologies, renewable energy consumption, import and economic growth on carbon emissions by using rich data on total per capita carbon dioxide (CO2) emissions, economic growth, import of goods and services, renewable energy consumption, fixed telephone subscriptions, mobile cellular subscriptions, and individuals using the internet in Africa (2001 ─ 2020) obtained from the World development indicators (WDI) database. Using the Panel autoregressive distributed lag model (PARDL), we found that mobile cellular subscriptions, and level of economic growth significantly increased per capita CO2 emissions in Africa in the long run while renewable energy consumption and technologies and import of goods and services significantly decreased per capita CO2 emissions in the long run. We conclude that information and communication technologies, level of economic growth, import of goods and services, and renewable energy consumption exert impacts on carbon emissions in Africa. Highlights: Achieving low-carbon development in Africa is possible. This research investigated the impacts of information and communication technologies, renewable energy consumption, import and economic growth on carbon emissions in Africa. This study utilized the Panel autoregressive distributed lag model and panel data from 31 African countries. The results shed new light on the emission reduction potential of renewable energy consumption and import of goods and services. The study also shows that ICTs increase carbon emissions in Africa. This article offers recommendations concerning carbon emissions reduction. [ABSTRACT FROM AUTHOR]

As a world-class urban agglomeration, the Yangtze River Delta urban agglomeration is significant for China's carbon neutrality strategy when calculating the carbon budget and dividing carbon compensation zones. This paper focused on 129 county-level cities in the core area of the Yangtze River Delta urban agglomeration, calculating the carbon budget for 2000–2020 using night-time light data and analyzing the evolution of spatiotemporal patterns. On this basis, a carbon compensation zoning model was constructed using the K-means algorithm; 129 cities were divided into different carbon compensation zones after combining this model with the main functional zones. The results showed that (1) the carbon emissions increased, with overall stabilization after 2012. The distribution of high carbon emission areas evolved from a "core-periphery" pattern into a "Z-shaped" pattern. Ecological carbon sinks showed a continuous decline, with the southern sinks performing better than the northern ones. (2) The carbon budget of the study area showed a deficit, gradually widening and exhibiting an unbalanced spatial distribution characterized by a "high in the south and low in the north" pattern. (3) Eleven types of carbon compensation zones were designated after overlaying the main functional zones. Low-carbon development suggestions were proposed for each zone type. [ABSTRACT FROM AUTHOR]

With breakthroughs in big data, communication networks, artificial intelligence, and other next-generation information technologies, intelligent production methods and digital lifestyles have risen rapidly. Digital economy has become a significant force in promoting regional low-carbon development as a new economic form in the important period of the intersection of digitalization and "carbon peaking and carbon neutrality goals." This paper empirically explores the moderating role and threshold role of human capital in digital economy and regional carbon productivity by systematically measuring digital economy indicators. Research shows that China's digital economy development index is rising annually. However, the development of digital economy varies significantly between different regions. The results of moderating effect showed that human capital accumulation could dramatically strengthen the role of digital economy in promoting regional carbon productivity. The results of the threshold effect showed that human capital plays an important threshold role in the relationship between digital economy and regional carbon productivity. This paper provides a practical reference for exploring power sources, policy design, and path selection of low-carbon development. [ABSTRACT FROM AUTHOR]

In accordance with South Korea's recent 2030 Carbon Neutral Plan, an 8GW offshore wind farm is planned for construction in the South-west Sea. Therefore, it is expected that large-scale wind turbines will be installed, and these turbines must operate stably, even when there are instantaneous voltage fluctuations in the power system. The grid code is described for the low-voltage-ride-through (LVRT) and high-voltage-ride-through (HVRT) functions, and a test facility that can perform both LVRT and HVRT tests is essential. In the case of LVRT/HVRT test facilities developed by the existing RLC (impedance component) method, it may be difficult to test large-scale wind turbines due to problems such as power quality, frequent failures and narrow short-circuit capacity ranges. Therefore, to solve such problems, this paper proposes an LVRT/HVRT test facility of the autotransformer type, which is capable of outputting the desired voltage range by changing the wiring method and tap position. Specifically, in order to implement the test facility of the autotransformer type, which is able to output the desired voltage range by changing the wiring method and tap according to the LVRT/HVRT test status, this paper presents an impedance determination algorithm (two-step layer impedance determination algorithm) of auto-transformer based on the fault-current analysis and operation strategy at a real LVRT/HVRT testing evaluation facility. [ABSTRACT FROM AUTHOR]

This paper investigates the relationship between digital finance and carbon emissions and explores the ecological effects of digital finance. Based on a panel data of 256 cities in China from 2011 to 2018, this paper investigates the impact of digital finance on carbon emissions and its intrinsic mechanisms. First, digital finance significantly suppresses the intensity of regional carbon emission, and the breadth of coverage, depth of use, and degree of digital support of digital finance together curb regional carbon emissions, with the strongest suppressive effect being the breadth of coverage. In addition, the regression results remain significant after a series of robustness tests. Second, it reveals the potential mechanism of digital finance to curb urban carbon emissions. These mechanisms include the three channels: promoting industrial advancement, green technology innovation, and optimizing labor resource allocation. Third, the heterogeneity test finds that the energy saving and emission reduction effects of digital finance are significantly stronger in non-low-carbon pilot cities with low urbanization rates, confirming the emission reduction utility of digital finance development. Therefore, we should take advantage of digital finance to improve the green development of financial services and adopt diverse policy measures according to local conditions to maximize the ecological effects of digital finance on energy saving and emission reduction. In the context of the development strategy of "carbon peaking and carbon neutral," this study has some implications for management in developing a regional green development system supported by digital finance. [ABSTRACT FROM AUTHOR]