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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]

Deep decarbonization aims to achieve the profound transformation of energy systems through steeply reducing carbon intensity in all sectors of the economy, which is the only way to achieve the goals of reaching peak carbon emissions and carbon neutrality. It is of great practical significance for China to clarify the research themes and identify the research evolution trend of deep decarbonization. We first analyzed the connotation and characteristics of deep decarbonization, based on which we deeply read the related academic literature and the frontier reports issued by international organizations and research institutions to make a systematic review of relevant research themes. Moreover, based on the identification results of research hotspots and research frontiers of deep decarbonization obtained by bibliometric analysis, we analyzed the evolution trend of deep decarbonization research. The research found that: ① Deep decarbonization is essentially to promote the deployment of carbon reduction, zero carbon, and negative carbon technologies to achieve the transition of the entire energy system from a high carbon emission type to a net-zero emission type through technological, social, and economic policy paths. Compared with normal decarbonization, the characteristics of coverage and path planning determine that deep decarbonization is a more advanced decarbonizing process. ② The research themes of deep decarbonization mainly fall into four categories: challenges faced by deep decarbonization, technological paths of deep decarbonization, policy research oriented to deep decarbonization, and cost and benefit evaluation of deep decarbonization. ③ The evolutionary trend of deep decarbonization research can be divided into two stages. In the initial stage (2015-2018), the framework, including subdivided research fields and research frontiers of deep decarbonization research, was initially formed. In the rapid development stage (2019-2021), more detailed emerging research topics were emerging in the field of deep decarbonization research, and scholars began to turn to new research perspectives. Finally, the implications of deep decarbonization research for China were proposed: In terms of research perspective, deep decarbonization research should be expanded to the micro-subject level and to research on issues such as decarbonization of the corporate value chain and corporate decarbonization potential assessment with an interdisciplinary perspective. In terms of research methods and paradigms, multidisciplinary research methods should be used to better develop comprehensive models supporting accurate decision-making. New paradigms such as big data, machine learning, and simulation can be explored in deep decarbonization research. In terms of research content, this paper suggests the expansion of the current research boundary of deep decarbonization through studying the incentive mechanisms, investment and financing mechanisms, identification of emerging technologies, construction of technology systems, and establishment of cost-benefit evaluation frameworks, models and methods. [ABSTRACT FROM AUTHOR]

The process of carbon neutrality does have economic costs; however, few studies have measured the cost and the economic neutral opportunities. This paper uses a dynamic computable general equilibrium (CGE) model to simulate China's carbon neutrality path from 2020 to 2060 and analyzes its economic impact. This paper innovatively adjusts the CGE modeling technology and simulates the boundary of the Porter hypothesis on the premise of economic neutrality. The results show that the carbon neutrality target may reduce the annual GDP growth rate by about 0.8% in 2020–2060. To make the carbon pricing method under the carbon neutrality framework meet the strong version of the Porter hypothesis (or economic neutrality), China must increase its annual total factor productivity by 0.56–0.57% in 2020–2060; this is hard to achieve. In addition, the study finds that China's 2030 carbon target has little impact on the economy, but the achievement of the 2060 carbon neutrality target will have a significant effect. Therefore, the paper believes that the key to carbon neutrality lies in the coexistence of technological innovation and carbon pricing to ensure that we can cope with global warming with the lowest cost and resistance. [ABSTRACT FROM AUTHOR]

China has committed to peak carbon emissions by 2030 and become carbon neutral by 2060. Hebei, as a major energy province in China, has more challenging carbon peaking and carbon neutrality targets. Based on the extended STIRPAT model, this paper evaluates the time to peak carbon and post-peak carbon trend changes in Hebei province under different scenarios from 2020 to 2060. Based on the support vector machine model with particle swarm optimization, this paper evaluates the carbon neutral pathways under different scenarios in Hebei province from 2020 to 2060 in terms of forests, croplands, wetlands, grasslands and Carbon Capture, Utilization and Storage (CCUS). The results show that a monotonically flat trend without inflection point, a single-inflection-point plateau-period trend and a multi-inflection-point inverted U-wave trend occur after carbon peaks. Hebei Province can achieve carbon neutrality by 2060 under the policy scenario and the enhanced scenario, and the enhanced scenario is better. Comparing with existing studies, the innovation of this paper is to design different trends of changes after carbon peak, combining carbon absorption and carbon emission, and providing more diversified development paths for carbon neutral strategies through a more integrated perspective and multi-scenario comprehensive analysis. Therefore, In the future, Hebei Province should establish a platform for carbon emissions monitoring and carbon footprint assessment, and set up an early warning and assessment mechanism for carbon peaking, so as to prevent a rebound trend in carbon emissions after peaking. At the same time, it should introduce and develop carbon capture and conversion technologies and promote the low-carbon transformation of the industrial and energy sectors, thereby forcing the early realization of peak carbon. Pay attention to the role of forestry resources in carbon neutrality, increase carbon sink resources such as forests and wetlands, promote the development of CCUS, and enhance the implementation of the policy. [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]

Process-related carbon emissions, which cannot be completely eliminated by the improvement of processes and energy structure, are recognized as an enormous challenge for in-depth decarbonization. To accelerate the achievement of carbon neutrality, the concept of 'artificial carbon cycle' is proposed based on the integrated system of process-related carbon emissions from high-emitting industries and CCU technology as a potential pathway towards a sustainable future. This paper conducts a systematic review on the integrated system with the case of China, which is the largest carbon-emitting and manufacturing country, to provide a clearer and more meaningful analysis. Multi-index assessment was used to organize the literature and draw the useful conclusion. Based on literature review, the high-quality carbon sources, reasonable carbon capture approaches and promising chemical products were identified and analyzed. Then the potential and practicability of the integrated system was further summarized and analyzed. Finally, key factors of future development including technology improvement, green hydrogen, clean energy and industrial cooperation were stressed to provide a theoretical reference for future researchers and policy makers. • Demonstration on the rationality and importance of applying CCU technology on process-based carbon emissions. • Multi-index assessment on adoptable carbon sources, possible pathways of carbon capture and carbon conversion. • Analysis on the potential and practicability of the integrated system to accelerate carbon neutrality. [ABSTRACT FROM AUTHOR]

• The influencing factors of carbon prices in China's carbon market are analysed. • The influencing factors and historical data are combined to predict the carbon price. • The EEMD-BP-ELM model and the CHINAGEM-E model are constructed and combined. Carbon price is one of the core indicators of the carbon market. Making accurate predictions of carbon prices based on insight into the volatility characteristics of the carbon market will not only provide a scientific basis for investors and regulators to make decisions and greatly promote emission reduction, but also effectively promote the healthy development of the carbon financial market. Based on the historical carbon price data of the national carbon market, this paper constructs the EEMD-BP-ELM model to predict the high and low frequency components of China's future carbon price. On this basis, according to China's goal of peaking carbon emissions before 2030 and achieving carbon neutrality before 2060, the CHINAGEM-E model is used to predict the trend component of the carbon price under the baseline and the 2060 carbon neutral scenarios. Finally, the trend component is combined with the high and low frequency components to obtain the price range from 2022 to 2060. We find that under the baseline scenario, China's carbon price range in 2060 is [343, 785] CNY/tCO2, while under the 2060 carbon neutral scenario, this price range is [1543, 3531] CNY/tCO2. [ABSTRACT FROM AUTHOR]