A Review on the CO2 Emission Reduction Scheme and Countermeasures in China’s Energy and Power Industry under the Background of Carbon Peak

To reach the peak of carbon emission in China, the energy and power industry has the most arduous task and the heaviest responsibility. It should not only ensure efficient economic development, but also complete the arduous task of energy conservation and emission reduction. It is the main force in helping reach the peak of carbon emission. Taking the achievement of carbon peak in China’s power industry as the research object, this paper utilizes time series analyses to establish CO2 emission prediction models for China and its power industry under two scenarios: with and without a carbon peak target. The paper analyzes the current status of achieving carbon peak in China’s power industry and puts a forward CO2 emission reduction scheme for China and its power industry in the future. On this basis, countermeasures for China’s power industry to deal with carbon peak are explored.

Quo Vadis? Carbon Peak and Emission Network for China in the Post-Pandemic Era

China’s carbon peak greatly impacts global climate targets. Limited studies have comprehensively analyzed the influence of the COVID-19 pandemic, changing emission network, and recent carbon intensity (CI) reduction on the carbon peak and the corresponding mitigation implications. Using a unique dataset at different levels, we project China’s CO2 emission by 2035 and analyze the time, volume, driver patterns, complex emission network, and policy implications of China’s carbon peak in the post- pandemic era. We develop an ensemble time-series model with machine learning approaches as the projection benchmark, and show that China’s carbon peak will be achieved by 2021–2026 with > 80% probability. Most Chinese cities and counties have not achieved carbon peaks response to the priority-peak policy and the current implementation of CI reduction should thus be strengthened. While there is a "trade off" between the application of carbon emission reduction technology and economic recovery in the post-pandemic era, a close cooperation of interprovincial CO2 emission is also warranted.

The Prediction of Carbon Emission Information in Yangtze River Economic Zone by Deep Learning

This study aimed to respond to the national “carbon peak” mid-and long-term policy plan, comprehensively promote energy conservation and emission reduction, and accurately manage and predict carbon emissions. Firstly, the proposed method analyzes the Yangtze River Economic Belt as well as its “carbon peak” and carbon emissions. Secondly, a support vector regression (SVR) machine prediction model is proposed for the carbon emission information prediction of the Yangtze River Economic Zone. This experiment uses a long short-term memory neural network (LSTM) to train the model and realize the experiment’s prediction of carbon emissions. Finally, this study obtained the fitting results of the prediction model and the training model, as well as the prediction results of the prediction model. Information indicators such as the scale of industry investment, labor efficiency output, and carbon emission intensity that affect carbon emissions in the “Yangtze River Economic Belt” basin can be used to accurately predict the carbon emissions information under this model. Therefore, the experiment shows that the SVR model for solving complex nonlinear problems can achieve a relatively excellent prediction effect under the training of LSTM. The deep learning model adopted herein realized the accurate prediction of carbon emission information in the Yangtze River Economic Zone and expanded the application space of deep learning. It provides a reference for the model in related fields of carbon emission information prediction, which has certain reference significance.

Innovation of Talent Training Mode for Undergraduates Majored in Energy Under the “Carbon Neutralization” Target

In September 22, 2020, Xi Jinping said at the seventy-fifth general debate of the UN General Assembly that China will enhance the national independent contribution, and strive to achieve the peak of carbon dioxide emissions by 2030, and strive to achieve carbon neutralization by 2060. Under the goal of carbon peak and carbon neutralization, the implementation of carbon emission reduction is an important strategy for China to achieve green and low-carbon development, but also faces major challenges “The Fourteenth Five Year Plan” Period is an important window period for scientific and technological innovation to realize the transformation of carbon dioxide emission growth rate. Only with the support of scientific and technological innovation can China be expected to achieve the goal of carbon peak and carbon neutralization on schedule. This paper attempts to study how to innovate the energy undergraduate talent training mode under the goal of “carbon neutral” from the aspects of the current situation of talent training, the analysis of talent training objectives, and the path analysis of talent training mode innovation.

Challenges for China to achieve carbon neutrality and carbon peak goals: Beijing case study

China has set a goal to achieve peak CO2 emissions before 2030 and carbon neutrality by 2060. To achieve the goals of carbon peak and carbon neutrality, China needs to address the challenge of the large and still growing CO2 emission base. This paper investigated the energy consumption and CO2 emission in Beijing from 2020–2035 based on the energy elasticity coefficient and contribution value of the sub-energy increment (CVSI) method. Beijing is one of the first cities in China to propose the "carbon peak” target as of 2020. From 2020 Beijing will strive to achieve the goal of carbon neutrality. The results show that in 2035 the CO2 emission in Beijing may drop to 50% of 2020. This decline would be affected by economic growth, energy efficiency and the proportion of renewable energy use. Beijing’s energy supply mainly comes from outside the region. Therefore, for Beijing, in addition to increasing the proportion of renewable energy sources outside the region, its own energy acceptance also needs to be strengthened, including strengthening energy storage construction, actively researching and promoting carbon capture and utilization of gas-fired units, which are effective ways to achieve carbon neutrality target.

Carbon Neutral Roadmap of Commercial Building Operations by Mid-Century: Lessons from China

Carbon neutrality has positive impacts on people, nature and the economy, and buildings represent the “last mile” sector in the transition to carbon neutrality. Carbon neutrality is characterized by the decarbonization of operations and maintenance, in addition to zero emissions in electricity and other industry sectors. Taking China’s commercial buildings as an example, this study is the first to perform an extensive data analysis for a step-wise carbon neutral roadmap of building operations via the analysis of a dynamic emission scenario. The results reveal that the carbon emissions abatement of commercial building operations from 2001 to 2018 was 1460.85 (±574.61) mega-tons of carbon dioxide (Mt CO2). The carbon emissions of commercial building operations will peak in the year 2039 (±5) at 1364.31 (±258.70) Mt, with emission factors and energy intensity being the main factors influencing the carbon peak. To move toward carbon neutral status, an additional 169.73 Mt CO2 needs to be cut by 2060, and the low emission path toward carbon neutrality will lead to the realization of the carbon peak of commercial buildings in 2024, with total emissions of 921.71 Mt. It is believed that cutting emissions from the operation of buildings in China will require a multi-sectoral synergistic strategy. It is suggested that government, residents, enterprises, and other stakeholders must better appreciate the challenges to achieve a substantial carbon reduction and the need for urgent action in the building sector in order to achieve carbon neutrality.

Carbon emission factor decomposition and carbon peak prediction based on multi-objective decision and information fusion processing

Global warming caused by excessive carbon dioxide emissions has seriously threatened the sustainable development of human society. How to reduce carbon dioxide emissions has become a common problem faced by the international community. This article aims to study the decomposition of carbon emission factors and the prediction of carbon peaks from the perspective of multi-objective decision-making and information fusion processing. The sample collection method and statistical analysis method are used to collect samples and simplify the algorithm. A collection experiment of carbon emission factors based on the industry of City A is designed. The experimental data collection takes into account the conversion of coal and oil products into standard coal and carbon dioxide the resulting emissions impact. The experimental results in this paper show that the simulated and real values of my country’s petroleum carbon emissions have both increased from 2000 to 2015, and the decline will be controlled in 2017. Both the simulated value and the real value of my country's coal carbon emissions have been on the rise from 2000 to 2015, and the decline will be controlled in 2017. The carbon emissions of coal are far greater than those of petroleum. The research on carbon emission factor decomposition and carbon peak prediction based on multi-objective decision-making and information fusion processing has been completed well. The research results can be used for industrial carbon emission factor decomposition and carbon peak prediction in other cities across the country.