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This paper explores the role of electricity in the transition to renewable energy to mitigate climate change. A systematic literature review with the Scopus database identified 92 papers relevant to the renewable electricity transition. A PESTLE (Political, Economic, Sociological, Technological, Legal, and Environmental) review of the papers provided a multidisciplinary analysis. The Paris Agreement created a global movement for carbon neutrality to address the threats of climate change, calling for a transition to renewable electricity to lead the way and expand into new sectors and regions. Although smaller renewable technologies are ramping up, complexities thwarting the transition include locked-in assets, high upfront costs, variability of solar and wind energy, infrastructure, difficulty in decarbonizing transportation and industry, material resource constraints, and fossil fuel support. This research found that renewables are not replacing fossil fuels to date but adding further energy demands, so that greenhouse gas emissions rose in 2021 despite an increased renewable electricity share. Without a major shift in the trillions of dollars of subsidies and investment away from fossil fuels to renewables, catastrophic climate change is predicted. This paper found that the Paris Agreement's commitment to net-zero carbon and the transition to renewable electricity are undermined by record-high levels of subsidies and financing for fossil fuel industry expansion. Transitioning to a climate-neutral economy requires an investment away from fossil fuels into renewable energy ecosystems. Renewable electricity provides possibilities to realize sustainable development goals, climate stabilization, job creation, a green economy, and energy security with careful planning. [ABSTRACT FROM AUTHOR]

In recent years, the amount of the photovoltaic (PV) system has been rapidly increasing from the viewpoint of carbon neutral. There are concerns about voltage rises and grid congestion in the electrical distribution network because of large‐scale PV increases. In order to address these issues, we focused on the control of water supply pumps in the water distribution system, which is infrastructure equipment for consumers. By controlling the start/stop of the water pump, it is expected to contribute to the power distribution system by increasing Demand Response (DR) and reduce CO2 emission from the electricity used by the pump. In this paper, with the aim of constructing an optimal operation planning method for water pumps that can evaluate DR and CO2 reduction effects, the optimal operation plan is formulated as a mixed integer linear programming problem. We numerical evaluated impact of water pump operation for CO2 emission and electrical distribution network. © 2023 The Authors. IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

China has made remarkable achievements in reducing carbon emissions in recent years. However, there is still much reduction room before achieving carbon neutrality. In Beijing, the capital of China, it is a strategic choice to respond to global climate change by promoting green and low-carbon development. This paper calculates the carbon dioxide emissions of key industries in Beijing and analyzes the temporal evolution trend of carbon emissions. Carbon dioxide emissions in Beijing before 2030 are predicted based on the grey prediction GM (1,1) and BP neural network model. The effects of factors of carbon dioxide emissions are discussed using the threshold regression model under different economic conditions. The results show that energy consumption intensity, GDP per capita, and the ownership of civil cars have a positive impact on carbon dioxide emissions, while the number of permanent residents and urban green space areas have a negative impact on carbon dioxide emissions. These findings of carbon emission prediction and influencing factors contribute to carbon reduction path design. Related policy implications on carbon emission reduction are put forward from the aspects of promoting industrial upgrading, accelerating the construction of advanced economic structures, optimizing transportation structures, and strengthening green building development. [ABSTRACT FROM AUTHOR]

To achieve carbon peak targets, realize carbon neutrality vision, and tackle global climate change, China must improve the carbon emission performance at the city level. Based on the carbon emission performance of 191 prefecture-level cities in China from 1997 to 2017, this paper analyses the evolution characteristics of urban carbon emission performance from three aspects: the overall spatial and temporal evolution, the differences according to both region and city size, and the differences among clusters categorized by carbon emission performance at the city level. This paper also reveals the impact of the social and economic transition on China's carbon emission performance. The results show that: (1) The overall level of carbon emission performance of Chinese cities is low, and there is a downward trend during the study period. The differences in carbon emission performance among cities are convergent, but there is a wide gap between high and low values. (2) The carbon emission performance of cities in eastern coastal areas is higher than that in non-coastal areas cities. Large urban agglomerations and economically developed regions, such as provincial capitals, are the agglomeration areas of high urban carbon emission performance values. (3) The carbon emission performance level of cities with similar sizes will converge. At the same time, such changes will enhance the differences among carbon emission performances at the city level within the same region. (4) Cities that belong to high urban carbon emission performance clusters are mainly distributed in the eastern region. Such cities are classified into large cities, supercities, and megacities. Compared with low urban carbon emission performance clusters, cities in high urban carbon emission performance clusters show a higher proportion in the medium-high level and high level of carbon emission performance. Moreover, cities in high urban carbon emission performance clusters are more likely to improve theirurban carbon emission performance. (5) The economic agglomeration effect, industrial structure adjustment and carbon intensity reduction have a significant impact on improving urban carbon emission performance. Population agglomeration has an incremental effect, and the anticipated benefits of environmental regulation have yet to be fully realized. The impacts of different clusters and different regions are variable. Finally, this paper advances policy enlightenment according to its research findings. [ABSTRACT FROM AUTHOR]

In the global context, countries must reduce carbon dioxide emissions to "net zero" by 2050 to limit global warming to 1.5 °C above pre-industrial levels. China's Nationally Determined Contributions (NDCs) are to peak carbon dioxide emissions by 2030 and achieve the carbon neutrality target by 2060. To monitor the achievements of the NDCs, establishing an annual-based accounting mechanism is necessary to record the carbon stocks in China, especially for Blue Carbon. The paper aims to present China's first national-scale systematic Blue Carbon accounting for mangroves, salt marshes, and seagrasses, covering the accounting subjects of physical and monetary assets, as well as relevant indicators for investors. It focuses on the design of the accounting method and system, the selection of data categories applied to this system, and the application of China's Blue Carbon accounting based on this accounting system. Taking Blue Carbon accounting as a starting point, this paper analyses the restoration prospects of these ecosystems and their application potential for NDCs in China compared with the terrestrial ecosystems. The results indicate that mangroves are the most cost-effective type of ecosystem, even compared to terrestrial forests. Thus, the paper provides policymakers with a new perspective on the decision-making of carbon sequestration relevant decisions, aiming to promote the monitoring, restoration, and expansion of China's coastal blue carbon ecosystem through the establishment of a sound Blue Carbon accounting system, and to help achieve the carbon neutrality goal in China's NDCs through regular and systematic monitoring of its national Blue Carbon inventories. • China's coastal blue carbon ecosystems are carbon sources rather than carbon sinks. • Mangroves are the most cost-effective coastal blue carbon ecosystem compared to salt marshes and seagrass beds. • The Blue Carbon of mangroves is more cost-effective than the Green Carbon of terrestrial forests when meeting China's Nationally Determined Contributions target of increasing forest stocks. • Establishing guidelines for Blue Carbon data requirements will lay a scientific foundation for formulating strategies and policies to cope with global climate change. [ABSTRACT FROM AUTHOR]

Carbon neutrality is becoming an important development goal for regions and countries around the world. Land-use cover/change (LUCC), especially urban growth, as a major source of carbon emissions, has been extensively studied to support carbon-neutral planning. However, studies have typically used methods of small-scale urban growth simulation to model urban agglomeration growth to assist in carbon-neutral planning, ignoring the significant characteristics of the process to achieve carbon neutrality: large-scale and long-term. This paper proposes a framework to model large-scale and long-term urban growth, which couples a quantity module and a spatial module to model the quantity and spatial allocation of urban land, respectively. This framework integrates the inertia of historical land-use change, the driving effects of the urbanization law (S-curve), and the traction of the urban agglomeration network to model the long-term quantity change of urban land. Moreover, it couples a partitioned modeling framework, spatially heterogeneous rules derived by geographically weighted regression (GWR), and quantified land-use planning orientations to build a cellular automata (CA) model to accurately allocate the urbanized cells in a large-scale spatial domain. Taking the Guangdong–Hong Kong–Macao Greater Bay Area (GHMGBA) as an example, the proposed framework is calibrated by the urban growth from 2000 to 2010 and validated by that from 2010 to 2020. The figure of merit (FoM) of the results simulated by the framework is 0.2926, and the simulated results are also assessed by some evidence, which both confirm the good performance of the framework to model large-scale and long-term urban growth. Coupling with the coefficients proposed by the Intergovernmental Panel on Climate Change (IPCC), this framework is used to project the carbon emissions caused by urban growth in the GHMGBA from 2020 to 2050. The results indicate that Guangzhou, Foshan, Huizhou, and Jiangmen are under great pressure to achieve the carbon-neutral targets in the future, while Hong Kong, Macao, Shenzhen, and Zhuhai are relatively easy to bring up to the standard. This research contributes to the ability of land-use models to simulate large-scale and long-term urban growth to predict carbon emissions and to support the carbon-neutral planning of the GHMGBA. [ABSTRACT FROM AUTHOR]

China's declaration to the international community to peak CO2 emissions before 2030 and achieve carbon neutrality before 2060 is of great significance in advancing the objectives of the Paris Agreement, and has a positive and far-reaching impact on China's high-quality development. This paper expounds on responsibilities and ambitions in tackling climate change, analyzes the high-quality development opportunities brought about by CO2 emissions peak and carbon neutrality, and discusses the net zero carbon emissions transformation in the new era of ecological civilization. This paper is of the view that development towards net zero carbon emissions provides a new impetus for building a Beautiful China, and promoting ecological civilization and green development. The essence of carbon neutrality should be correctly understood so that the world will work together to improve climate resilience. China should also deepen the understanding of the principles and methodologies of climate change economics. [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]

To avoid the potential adverse impacts of climate change from global warming, it is suggested that the target of net zero emissions should be reached by this mid-century. Thailand is aiming to achieve carbon neutrality by 2050. Since electricity generation is one of the largest producers of carbon dioxide emission, the associated emissions must be greatly reduced to achieve the targets mentioned above. Thus, new generation expansion plans must be well developed. This paper discusses the development of generation expansion plans considering Thailand's latest policies along with enhancement of the existing multi-period linear programming model, allowing new electricity generation technologies having low emissions, e.g., solar PV with battery and hydrogen blending in natural gas, to be integrated into generation expansion planning. Then, four generation expansion plans with different levels of hydrogen blending in natural gas are proposed and discussed. It is found that Thailand can achieve carbon neutrality by 2050 by promoting more use of renewable energy altogether with trade-off between land for solar PV installation and amount of hydrogen blended in natural gas. The lesson learned from this study provides crucial information about possible pathways to achieve carbon neutrality in the electricity sector for policy makers in other countries. [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]

With global climate change becoming increasingly serious, carbon neutrality, a key strategy to mitigate climate change, has attracted widespread attention. However, due to the multidisciplinary and complexity of carbon neutrality studies, as well as the diversification of research content, a comprehensive review and systematic synthesis of which is quite limited. In this paper, a bibliometric analysis on the topic of carbon neutrality is conducted to reveal the research progress from a quantitative and visual perspective and describe the evolution of research hotspots. The results show that carbon neutrality research is abundant at both the macro and micro levels. Low carbon development is the premise of carbon neutrality, and emission reduction and carbon sinks are the basis of carbon neutrality. The degree of research varies significantly in different countries, with China dominating in the number of publications, followed by the USA and the UK. The realization of carbon neutrality cannot be fully achieved by one single perspective and requires a comprehensive and systematic analysis of technology, economy, and society. Carbon neutrality is a technology-driven process guided by policy. Economically, carbon taxes and carbon markets are two important market mechanisms for reducing carbon emissions. Technically, researches of negative carbon technologies and renewable energy are growing rapidly. Carbon market, carbon negative technology, circular economy, and green energy will become the focus of future research. This paper helps scholars to understand the overall state of carbon neutrality research and provides a historical reference for future research. • The evolution of carbon neutrality research is identified by a bibliometric method. • Visualizes research status and outlines research foci, frontiers and prospects. • Retrieve 5271 articles published over 25 years in SCIE and SSCI databases. • Carbon neutrality is a technology-driven process guided by policy. • Circular economy and carbon markets are new areas of carbon neutrality research. [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]

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]

As a major carbon dioxide-emitting country, China set carbon trading market to reduce enterprise carbon emissions through the rational allocation of carbon quotas among different enterprises and regions. The market has also conducted a preliminary exploration for the country to achieve carbon dioxide emissions peak in 2030 and carbon neutrality in 2060 while actively addressing the challenges of global climate change. This study analysed the emission reduction effect of China's carbon trading pilot policy, especially the role of carbon quota and carbon trading price. The analysis used county-level panel data from 1997 to 2017, regarded the implementation of the carbon trading pilot policy as a quasi-natural experiment, and used the difference-in-differences method. The results showed that, first, the policy implementation not only reduced regional carbon emissions but also inhibited carbon dioxide emissions per capita, with long-term effects. Second, the carbon emission reduction effect brought by the carbon pilot policy showed significant heterogeneous results with the different degrees of regional carbon emissions and environmental supervision. The effect was greater in areas with higher carbon emission density and stronger legal supervision. Third, the difference in carbon quota allocations resulted in different emission reduction effects, among which the historical method had the strongest effect. The carbon quota price and number of enterprises participating carbon trading market were the key factors affecting carbon emission reduction. • This paper investigates the impact of carbon emission trading market on the carbon reduction. • China provides an excellent "Quasi-natural Experiment" for assessing the role of carbon emission trading market in environmental management. • It is found that policy implementation has significantly reduced various types of carbon emissions, and this reduction effect is long-term. • Stimulating the vitality of the carbon market and expanding the supply and demand of carbon quotas are the main ways to achieve carbon emission reduction. [ABSTRACT FROM AUTHOR]

Carbon emissions play a crucial role in inducing global warming and climate change. Accurate and stable carbon emissions forecasting is beneficial for formulating emissions reduction schemes and achieving carbon neutrality as early as possible. Although previous studies have concentrated on employing one or several methods for carbon emissions forecasting, the improvement in forecasting performance is limited because they ignore the importance of objectively selecting the models and the necessity of interval forecasting. In this paper, a novel ensemble prediction system, composed of data decomposition, model selection, phase space reconstruction, ensemble point prediction, and interval prediction, is proposed to conduct both point and interval predictions, which has been proven to be effective in prompting carbon emissions forecasting accuracy and stability. According to the empirical results, the mean MAPE results of our proposed forecasting strategy in point prediction are 1.1102% (in Dataset A) and 1.1382% (in Dataset B), and the mean CWC values in the interval forecasting are 0.3512 and 0.1572, respectively. Thus, the proposed forecasting system improves the forecasting performance relative to other models considerably, which can provide meaningful references for policymakers. • An ensemble forecasting system is developed for carbon management. • Comprehensive indicator is proposed to determine the best predictor adaptively. • Optimal distribution and reduction coefficient are used for interval forecasting. • Multi-objective tangent search algorithm is proposed for interval forecasting. [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]