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The urgent need to address climate change has led to global efforts towards achieving carbon neutrality. However, it is crucial to recognize the existence of carbon inequity, where certain regions or communities bear a disproportionate burden of carbon emissions compared to others. This paper explores the concept of carbon inequity and highlights the importance of considering driving factors in the pursuit of just energy transition. By examining the socioeconomic, environmental, and policy-related factors that contribute to carbon emissions, a comprehensive understanding of the underlying causes of carbon inequity is gained. The study emphasizes the need to address systemic issues such as economic development patterns, industrial structures, energy consumption habits, and social inequalities that perpetuate carbon inequity. It further discusses the significance of collaborative and inclusive approaches to carbon reduction, focusing on bridging the gap between regions with high and low carbon emissions. Policy implications are derived to guide decision-makers in formulating effective strategies for achieving carbon neutrality while ensuring equity and fairness. By considering both the overarching goal of carbon neutrality and the distributional aspects of carbon emissions, a more holistic and equitable approach can be adopted to accelerate the transition to a sustainable and low-carbon future. • It is crucial to recognize the existence of carbon inequity to address climate change. • This paper explores the concept and importance of carbon inequity of just energy transition. • Policy implications are derived to guide decision-makers while ensuring equity and fairness. [ABSTRACT FROM AUTHOR]

The intensification of global climate change has led to a widespread consensus on carbon reduction, with the power industry being the principal contributor to carbon emissions necessitating an inevitable transition of its energy structure. Concomitantly, the escalating frequency of natural disasters caused by extreme weather presents formidable challenges to both secure power supply and the low-carbon transition of the power system. To fulfill the developmental requirements of a low-carbon power system and address the carbon emission risks imposed by natural disasters, this paper proposes a bi-level model for generation expansion planning (GEP) that incorporates constraints on the carbon emission trajectory and the influence of natural disasters. The planning-level model optimizes investment costs of various generation technologies and energy storage (ES), as well as the overall operational expenses over the planning period, with an objective to minimize them. It incorporates carbon emission trajectory constraints and policy constraints, such as carbon peaking, carbon neutrality and renewable energy (RE) penetration rates, in order to optimize the planning installed capacity of power sources. The operational-level model aims to minimize typical daily operating costs while also simulating power unit outputs in routine and disaster scenarios. A case study is conducted in a disaster-prone province in southern China to analyze the power generation expansion planning and the trajectory of carbon emissions from 2020 to 2060 under different scenarios. The simulation results show that compared to thermal power, the planning scheme mainly focused on RE with ES is better suited to achieve the goal of a low-carbon transition of the power grid. Moreover, after considering natural disasters, the cost and carbon emissions of power system planning are higher, and the risk of carbon emissions increases with the severity of disasters. • A multi-time scale bi-level low-carbon GEP model is proposed. • Natural disaster scenarios and low-carbon policy constraints are considered in the GEP model. • Carbon emission trajectory of the planned power system is estimated and introduced as a constraint into the GEP model. • Evaluation indicators that comprehensively consider low-carbon performance and economic feasibility are proposed. [ABSTRACT FROM AUTHOR]

Treating carbon emission rights as tradable commodities is a major institutional innovation in the carbon market's response to climate change. The level of carbon emissions from production activities is inextricably linked to climate policy adjustments. Thus, this article applies wavelet-based quantile-on-quantile regression to study the impact of climate policy uncertainty (CPU) on the carbon trading price (CTP) in the European Union Emissions Trading System (EU ETS). Short-term results show a mixed effect of CPU on CTP. In the medium to long term, there is a positive correlation between the two at the high quantiles of CPU. The results are supported by the theoretical mechanisms of CPU on CTP. The CTP represents the economic cost of carbon emissions, which can significantly influence the level of carbon emissions and is critical to achieving carbon neutrality. Governments should strive to reduce CPU and manage market expectations to minimise the impact of CPU on CTP. In addition, this paper can also inspire carbon market participants to help them make sound and scientific investment decisions. • Apply wavelet-based quantile-on-quantile regression to study the effect of CPU on the CTP. • The CPU is at different quantiles and time frequencies, the link between CPU and CTP is dynamic • The results are supported by the theoretical mechanisms of CPU on CTP. • The CTP can significantly influence the level of carbon emissions and is critical to achieving carbon neutrality. • Governments should strive to reduce CPU and manage market expectations to minimise the impact of CPU on CTP. [ABSTRACT FROM AUTHOR]

• Forecasting-test framework for long-term power system planning. • Coal-fired generators can be completely withdrawn from the power system by 2060. • China's power capacity mix will transition to wind and solar generators dominated. • Biomass and gas-fired generators will take on the role of reserved generators. • The timing of achieving China's zero-coal power system may be advanced or delayed. Facing the challenges of climate deterioration, environmental pollution, and energy shortages, China has put forward the goals of "carbon dioxide peaking and carbon neutrality", and the electricity sector will be the key area and the main direction of carbon emissions reduction. To prospect China's power system and explore the potential for establishing China's zero-coal power system in the future, this paper proposes a forecasting-test framework for long-term power system planning. We predict, evaluate, and analyze China's power system from 2025 to 2060 using the proposed forecasting-test framework. During this process, the power capacity mix and the electricity generation mix of China's power system will gradually transition from coal-fired generators dominated to wind and solar generators dominated. Moreover, the roles of different generators and energy storages are illustrated through the seasonal comparison and sensitivity analysis of the installed capacity of generators. The results indicate that coal-fired generators can be completely withdrawn from the power system, confirming the feasibility and possibility of achieving China's zero-coal power system by 2060. Although the timing may be advanced or delayed in different scenarios, achieving China's zero-coal power system will require exercising nationwide planning and making joint efforts of various sectors from now on. [ABSTRACT FROM AUTHOR]

This study explores the impact of political uncertainty on sustainable urban development by examining carbon emission trading systems (ETS) in four major markets in China (Beijing, Shanghai, Guangdong, and Hubei) from 2014 to 2022. As an alternative to carbon taxes, carbon ETS markets have become increasingly popular due to their success in reducing greenhouse gas emissions. However, their effectiveness is often hindered by political instability and uncertainty. Utilising logistic regression and AR(1)-GARCH estimations, we identify a negative relationship between political uncertainty and carbon trading volume. Our study also reveals significant variations in the responses of these markets to political uncertainty. The paper contributes to the understanding of how ETS markets operate in a complex and constantly changing political environment. We suggest that policymakers need to consider the impact of political uncertainty on carbon trading when designing and implementing urban policies that promote sustainable development. Additionally, our research contributes to the development of urban policies that can be effectively implemented in both developed and developing regions. • Local government official turnovers are used as the measurement of political uncertainty. • Daily transaction data from four carbon ETS markets (Beijing, Shanghai, Hubei and Guangdong) in China • Considered the probability and proportion of zero transaction day • Logistic regression and AR(1)-GARCH estimations • A negative relationship between political uncertainty and carbon transaction volume [ABSTRACT FROM AUTHOR]

How to achieve the "double carbon" goal in energy systems has been the concern of governments. Integrated energy system (IES) is affected by climate change during his operation, in order to study the impact of climate change on IES and achieve the "double carbon" goal in energy systems, this paper proposes an integrated machine learning(IML) to forecast the long-term load, then investigates IES costs and carbon emissions in relation to climate, followed by the establishment of carbon peak energy system(CPES) and carbon neutral energy system(CNES), finally the honey badger algorithm is used to optimize the configuration of CPES and CNES. The results show that: IML can accurately make load forecasts. Under climate change, changes in load reduce the cost and carbon emissions of IES, and changes in equipment efficiency increase the cost and carbon emissions of IES. When both are considered, the cost and carbon emissions of IES increase by 1.18% and 0.92% per decade respectively. The costs of CPES and CNES increase by 0.93% and 1% respectively for every 10 years earlier than the year of achievement. To meet China's "double carbon" goal, CPES and CNES need to increase their costs by 1.97% and 2% respectively. • Integrated machine learning proposed for long-term load forecasting. • Studied the impact of system equipment efficiency and load with climate change. • Proposing carbon peaking energy system to achieve the carbon peak goal. • Proposed carbon-neutral energy system to achieve carbon neutrality goal. • The increased costs of achieving carbon peak and carbon neutral were studied. [ABSTRACT FROM AUTHOR]

Recent times have witnessed an increasing number of countries and private firms pledging carbon neutrality by mid-century. Whilst representing a significant improvement in intentions to tackle climate change, such pledges lack substance and structure. For instance, individual pledges lack coordination and aggregation among peers, while strategies and measures to achieve ambitious targets are largely absent. Moreover, current disagreements obstructing progress in international climate change negotiations further undermine the reliability of carbon neutrality objectives. Effective international policies are needed to foster aggregate mitigation ambitions and the creation of adequate supporting mechanisms. This theoretical paper describes a governance innovation aimed at overcoming such shortfalls and disagreements through a unifying yet customizable pathway towards carbon neutrality. It does so by first outlining a political governance framework based on a climate club interpretation of Article 6 of the Paris Agreement. Secondly, it proposes carbon emission mitigation effort sharing on a per capita basis to ensure efficiency, equity and political feasibility. Thirdly, this paper describes how the supply of certified mitigations of carbon emissions required to satisfy effort sharing-based demand can be assetized as carbon credits by operationalizing Article 6 as a joint certification mechanism. The resulting governance architecture for managing demand and supply of mitigations shifts efforts to tackle climate change from a 'problem-driven' cost approach to 'opportunity-driven' value creation pathways towards carbon neutrality. • Climate clubs enable operationalisation of article 6 of the Paris Agreement. • Effort-sharing on a per capita basis ensures a fair target distribution. • A joint certification mechanism mirrors effort-sharing in a climate club. • The resulting architecture provides a pathway towards carbon neutrality. [ABSTRACT FROM AUTHOR]

Anthropogenic CO 2 emissions are one of the principal driving forces of climate change. Climate change leads to systematic changes of ecosystems that cause significant impacts on species interactions, ecosystem processes, and result in profound socio-economic consequences. While carbon offsetting of terrestrial forests and their monetary value are well accepted, the carbon offsetting potential and value of coastal and marine ecosystems (Blue Carbon, BC) remains excluded from the international carbon accounting framework. In this study, we estimated the carbon offsetting value of kelp forests (Ecklonia radiata) against urchin barrens (dominated by crustose coralline algae) using the standing stock biomass as a metric. We propose that standing stock biomass is a crucial next step in introducing BC to the general carbon offsetting framework. Our approach is informed by long-term ecological research conducted in a marine reserve, which highlights the potential of utilizing trophic cascades to limit the dominance of urchin barrens in shallow coastal habitats. We found that the value of carbon standing stock in current kelp forests with reforestation in the Hauraki Gulf Marine Park (HGMP) is worth up to $NZ 7.9 million, based on 2021 carbon market pricing in New Zealand. This simple step towards realizing the value of marine conservation and its multiple benefits to society highlights the missed opportunities when policy and plans do not align with ecology and economics. Including the ocean's contributions to carbon storage is a critical step in using monetization techniques to overcome climate change challenges. Monetizing the carbon offsetting value of kelp forests contributes to establishing funding mechanisms to attract diverse investments in marine ecosystem restoration while providing ecological benefits in ocean governance. • This paper draws attention to the missed opportunity of including kelp forest in the current carbon offsetting framework. • The CO 2 stored in kelp standing stock biomass could be worth up to NZD 7.9 million (2021, with reforestration) in the Hauraki Gulf Marine Park. • Monetizing the carbon storage value of kelp contributes to the establishment of funding mechanisms to attract investments as a nature-based solution to climate change. [ABSTRACT FROM AUTHOR]

Carbon emission trading mechanism is an important market-based instrument to address global climate change. The auction ratio and price of carbon emission allowances (CEA) are cores of the carbon emission trading mechanism. What combination of CEA auction ratio and auction price is most conducive to carbon emission reduction for emission control enterprises? There are still relatively few studies conducted on this issue, and there is no clear answer from the views of theory and practice. In this paper, the AIM/Enduse model was used to analyze the changes and differences of installed power capacity, power supply, energy consumption and carbon emissions in the Guangdong-Hong Kong-Macao Great Bay Area (GBA) with different combinations of CEA auction ratios and prices. Moreover, the best pathway of energy transition was explored in the power industry of the GBA, and the best combination of CEA auction ratios and prices was identified in the GBA. The results show that: (1)The carbon emission constraint starts to work only when the auction ratio of CEA is increased to 50% and the auction price is increased to 60 CNY/ton (Scenario p 3). When the auction ratio of CEA is 100% and the auction price reaches 120 CNY/ton (Scenario p 5), a low-carbon transition of the power sector in the GBA can be achieved. (2) Under scenario p 5 , the total cost of power transition rises and then falls. And the cost of carbon in the power sector increases exponentially as the auction ratio of CEA and the auction price rise. However, the growth in the cost of power supply is relatively flat, which shows that appropriate carbon trading mechanism can improve the economic benefits of power sectors. With the increase of installed capacity of clean low-carbon energy generation and power supply, as well as the decrease of local power cost in the GBA, the proportion of outsourcing power can be appropriately reduced in the future, with an aim to reduce the external dependence of electricity to ensure the security of energy supply. In the end, it suggests that cities in the GBA should give full play to their regional advantages and establish a unified carbon emission trading market in the GBA as soon as possible. This study provides a theoretical basis for the supplementation and improvement of China's carbon emission trading mechanism. • What is the best combinations of CEA auction ratios and auction prices in the GBA? This paper gives a clear answer. • The best transition pathway of the power industry under technological progress and carbon trading policy was suggested. • With the decrease of local power cost, the proportion of outsourcing power can be appropriately reduced in the future. • Provides a theoretical basis for the supplementation and improvement of China's carbon emission trading mechanism. [ABSTRACT FROM AUTHOR]

• This paper analyzes China's challenges toward carbon neutrality (CN) by 2060. • Currently, up to 85% of China's energy consumption relies on fossil fuels. • China's zero-carbon technologies and economy are not yet sufficient for CN. • Thus, we propose a three-stage/four-step strategy for China to achieve CN. • This paper also presents seven suggestions to foster China's green transition. In response to climate change, the Chinese government has set a clear goal to reach its carbon peak by 2030 and achieve carbon neutrality by 2060, endeavoring to gradually realize net-zero carbon dioxide (CO 2) emissions. This paper explores the concept of carbon neutrality and makes a comparative analysis of the gap between China, the European Union, and the United States vis-à-vis carbon neutrality based on international data. The main challenges China faces in its progress toward carbon neutrality are the following: first, China's energy consumption and CO 2 emissions continue to increase, while its carbon peak has not yet been reached; second, carbon emission reduction in China is an arduous process, as the transition period allowed for the country to transition from its carbon peak to carbon neutrality is shorter than that of developed countries; third, China remains reliant on high-carbon fossil energy, with high energy consumption and low energy utilization efficiency; fourth, China's low level of economic development, compared with those of the EU, the US, or other developed countries, makes it relatively weak to withstand economic risks; and fifth, China's low-carbon and zero-carbon technologies are not mature. Therefore, this paper posits a three-stage/four-step strategy as well as seven specific suggestions that could benefit China's progress toward carbon neutrality. [ABSTRACT FROM AUTHOR]

For making earlier realization on peak carbon dioxide emissions and carbon neutrality, hydropower development in countries all over the world can effectively reduce the Greenhouse Gas (GHG) emissions and solve the problem of global climate change. This paper proposes a novel Optimized initial condition and Seasonal division based Grey Seasonal Variation Index (OSGSVI) model to accurately predict the hydropower generation in some countries. Firstly, for enhancing the fitting accuracy, the initial condition is optimized based on the weighted average methods and the data grouping with OSVI is utilized by seasonal divisions. Secondly, an OSGSVI model is established coupled optimization on both optimized initial conditions and seasonal divisions. Thirdly, the Whale Optimized Algorithm (WOA) is employed to determine estimated parameters to further enhance the fitting accuracy for the hydropower generation. Finally, the experimental results of the prediction study show that three error measure values are all the smallest in all the fitting results and the MAPE values are converged before 30 iterations by utilizing our proposed model when compared with a set of baseline prediction models. It demonstrates the superiority of our proposed model over the others on the fitting accuracy with fast-convergence for the hydropower generation in these selected countries. • An OSGSVI model is proposed to accurately predict the hydropower generation. • The model uses the seasonal data grouping and OGSVI to enhance the predictive accuracy. • The WOA is proposed to further improve the predictive accuracy. [ABSTRACT FROM AUTHOR]

As the climate is warming up and climate disasters occur more frequently, China's carbon peak and carbon neutrality targets are gaining attention, with provinces starting to set carbon peak targets and constantly exploring low carbon economic development opportunities. However, the existing evaluation index system mainly focuses on low carbon cities and green cities, and there is no evaluation index system for carbon peak and carbon neutrality. This study adopts a combination of theoretical and empirical research and draws on domestic and international research results to construct the first index system for evaluating China's provincial carbon peak and carbon neutrality. The evaluation index system includes 18 indicators from three dimensions: climate ambition, low carbon status, and emissions trends. Using this index system, we calculated the carbon peak and carbon neutrality indices of 30 Chinese provinces. Further, the 30 provinces were classified into six categories, and corresponding policy recommendations for achieving the "Dual carbon" targets were put forward. The evaluation index system constructed in this paper can provide a reference for future carbon peak and carbon neutrality assessments. By disclosing the integrated index of each province, we hope to effectively curb the increasing local carbon emissions; avert inaction in areas with good natural endowments; and motivate the advancement of the latter, to boost the implementation of the "Dual carbon" targets coherently for the whole country. [Display omitted] • An integrated evaluation system on China's Provincial "Dual carbon" was proposed. • 30 provinces in mainland China were ranked based on the integrated index. • 6 groups were classified to show provincial differences on dual carbon performance. • Policy recommendations to fulfill China's climate commitment were put forward. [ABSTRACT FROM AUTHOR]

• Constructing a new welfare function considering economy, equity and ecology. • Optimizing carbon emission pathways from multiple perspectives. • Focusing on the emission pathways in China achieving the ambitious targets. With the increasing climate warming, reducing carbon emissions has gradually become a consensus around the world. However, the process of carbon emission reduction will inevitably lead to the transformation of economic structure, industrial structure and energy structure, which will bring huge changes in economic output, employment and other aspects, thus affecting the overall social welfare and equity. Therefore, it is particularly important for each country to determine a scientific and effective carbon emission pathway which take into account both social development and climate targets. As the largest carbon emitter, China has put forward the targets of carbon peak and carbon neutrality. In this regard, the corresponding carbon emission reduction scenarios are designed according to the new situation of China's emission reduction in this paper, firstly. Furthermore, under the premise of maximizing social welfare, an optimization model which integrating economic growth-equity-environment is developed to determine China's emission pathways under different scenarios from 2020 to 2050. Besides quantitatively showing the future total amount and peak value of carbon emissions under different scenarios, the results can also identify its evolution pathway over time. Therein, the peak under most scenarios will concentrate in 2025–2030, which is about 10.7 to 11.8 billion tons. With the increasingly stringent constraints on carbon emission reduction, the cost of emission reduction will increase correspondingly, but the overall social welfare will increase slightly. Finally, our findings provide practical guidance on achieving carbon emission reduction and enlightenments on policymaking. [ABSTRACT FROM AUTHOR]

Bioenergy is considered a promising alternative to achieve carbon neutrality and emission reduction. There is a debate over the role of bioenergy in climate change mitigation because of carbon emissions from the production and utilization of biofuels. Recently, studies on emissions of biogenic volatile organic compounds (BVOCs) have substantially increased as they have a significant impact on human health and climate change due to large emissions and high reactivity. A scientometric analysis of 2895 journal papers during 1991 and 2020 related to BVOC emissions from the Web of Science Core Collection was conducted by CiteSpace and Carrot2. Results showed that three main knowledge domains were BVOC emissions and drivers, BVOCs and their oxidation products in biosphere-atmosphere exchange, and soil BVOCs in plant-microbe interactions during the period under study. Generally, the relationships between plant BVOC emissions and environmental variables (e.g., temperature, drought, light solar radiation, humidity, availability of nutrients, carbon dioxide, ozone, etc.) can be investigated by measurement techniques (i.e., chamber) or models (i.e., Model of Emissions of Gases and Aerosols from Nature). Soils could work as both the sink and source of BVOCs through various processes that are affected by soil temperatures, pH, organic matter, and moisture. Anthropogenic activities might affect the emission of BVOCs and promote the formation of BVOC-derived pollutants (e.g., ozone, particles, etc.). Incorporating BVOC emissions and their relationships with pollutants, biomass, and energy into environmental management and decision-making is a promising direction. [Display omitted] • A scientometric analysis was conducted on the research evolution of BVOC emissions. • Ten clusters generated by CiteSpace were logically reclassified into three hotspots. • MEGAN is the most frequently empirical model for BVOC emission assessment. • BVOC-derived pollutants like SOA are likely affected by anthropogenic activities. • Soils in terrestrial ecosystems can act as both the source and sink of BVOCs. [ABSTRACT FROM AUTHOR]