Estimate of China's energy carbon emissions peak and analysis on electric power carbon emissions

China's energy consumption in the building sector: A life cycle approach

Transport energy consumption and saving in China

China's energy consumption: A perspective from Divisia aggregation approach

This research focuses on two main lines: national energy supply and demand security under the goals of carbon peak and carbon neutrality, as well as national energy green and low-carbon development. The research conducts quantitative prediction on the total demand and energy structure of national fossil energy under low-carbon transformation goals, providing reference for the country to implement green and low-carbon energy transformation and build a new energy system. Based on the national energy security and carbon peak and carbon neutrality strategic objectives, this study uses grey relational analysis to conduct multi-factor analysis and innovatively builds a fossil energy development potential prediction model under the "dual carbon" goal constraints. Three scenarios of robust-sustainable transformation, active-CCUS technology breakthrough, and radical-renewable energy technology breakthrough are designed to analyze the energy development paths under different scenarios, outlining the national energy development path and defining the quantitative targets for the fossil energy development phase. Through multiple model calculations, it is found that in the three scenarios, China's primary energy consumption will peak around 2030, with a peak value of approximately 5.99-6.01 billion tons of standard coal. The total energy consumption demand will slowly decline from 2030 to 2040, and maintain basic stability from 2040 to 2060. In the three scenarios of robust, positive and radical, China's energy consumption in 2030 is respectively 6.01, 5.99 and 6.01 billion tons of standard coal, of which non-fossil energy accounts for 24.9%, 27.0% and 28.3% respectively. By 2060, China's energy consumption will be approximately 5.63, 5.8, and 5.87 billion tons of standard coal, with non-fossil energy accounting for 73.6%, 80.0%, and 85.2% respectively. In response to the challenges facing the adjustment of the national energy supply and demand structure, this research has proposed corresponding development strategies from the three aspects of policy system, industrial layout, and technological innovation. The research results of this project have strong forward-looking, strategic and guiding significance, providing a theoretical basis for the country's energy transformation and development under the background of carbon peak and carbon neutrality, with significant comprehensive benefits.

Can China achieve its carbon intensity target by 2020 while sustaining economic growth?

China's primary policy lever for carbon emission reduction is shifting from an ‘energy dual control’ system – focused on limiting total volume and intensity of energy consumption – to a ‘carbon dual control’ framework. However, the broader impacts of this policy shift on the energy system, carbon emissions, and the economy remain uncertain. This study develops linear programming models to maximize economic growth while accounting for energy demand and sectoral growth, comparing the impacts of this policy shift on China's energy consumption, carbon emissions, and economic performance. Results show that carbon ‘dual control’ more effectively optimizes the energy structure and encourages the development of natural gas and non-fossil energy, while reducing energy costs and supporting economic growth, especially in the secondary sector. Targeting carbon emissions instead of energy consumption alone lowers the risk of higher-than-expected carbon peaks or failing to peak. China is still in a transitional phase, with carbon intensity targets in place and energy ‘dual control’ being refined – particularly by excluding non-fossil energy and energy used as raw material from total consumption. While this helps ease energy constraints and support growth, it may increase emissions and delay peaking if not properly managed. To support this shift, policymakers should strengthen inter-agency coordination, gradually phase out the energy consumption limits, and enhance carbon governance capacity. Key actions include tightening coal regulations, scaling up clean energy investment, improving energy efficiency, accelerating industrial transformation, and advancing international cooperation on carbon cap management.

China's energy consumption and economic activity at the regional level

To improve the statistical indicators for road transport energy consumption and accurately analyze its energy consumption level of China, the article analyzes energy statistics scope, indicators, vehicle classification and energy consumption proportion of road transport in China, the United States, Britain and Japan. The horizontal and vertical comparison methods are used to propose differences in energy consumption statistics between China and developed countries and to put forward the trends of China's energy consumption for road transport. Studies have shown as follows: the scope of China's road transport energy consumption statistics has differences from the international accepted patterns; at present, energy consumption statistical indicators for China lack the conveying efficiency of transport vecicle; the proportion of China's energy consumption for road transport to the total society is far lower than that of foreign countries, but it can be rapidly increased in the future.

Energy consumption is one of main reasons for global warming and highly correlated with economic development. As the largest energy consumer worldwide, China has entered a new economic development model—the “new normal.” This study aims to explore the pattern shift in China's energy consumption growth in this new development phase. We use structural decomposition analysis and environmentally extended input‐output analysis to decompose China's energy consumption changes during 2005–2012 into five factors: population, efficiency, production structure, consumption patterns, and consumption volume. During the period of the global financial crisis, the energy consumption generated by China's exports dropped, while the energy consumption generated by capital formation grew rapidly. Over three quarters of China's energy consumption growth was caused by capital formation during 2007–2010. This growth is mainly because of China's economic stimulus measures in response to the global recession, with a focus on infrastructure construction. In the new normal, the strongest factors offsetting China's energy consumption have been shifting from efficiency gains to structural changes. Efficiency gains were the strongest factor offsetting China's energy consumption in traditional development model and offset 42% of energy consumption between 2005 and 2010 by keeping other driving forces constant. Since 2010, however, their effects offsetting energy have become weak. The production structure and consumption patterns both drove China's energy consumption growth in the traditional development model and drove energy consumption growth by 31% and 12% between 2005 and 2010, respectively. Since 2010, however, both factors have started to offset China's energy consumption.

Since China's reform and opening, with the rapid development of the heavy manufacturing and high energy consumption industry, energy consumption also increases significantly. However, in the energy consumption process, out-dated technology lead to high energy consumption of the unit GDP and the environmental pollution, which have directly influenced the sustainable development of China's energy consumption, economy and society. In order to ensure China's energy consumption, economic and social sustainable development, we should put more technology into the energy consumption to realize the changes towards tech-intensive China's energy consumption and the goal of China's 11th Five-Year Plan that average energy consumption per unit GDP decline 20%. Therefore, on the basis of analyzing the actuality of China's energy consumption per unit GDP and technology advance, first the paper sums up 14 indexes which impact China's technology advance and sets up a comprehensive assessment system on China's technology advance; second it uses gray correlation analysis to select the key technology indexes which have an important impact on China's energy consumption constitution, and builds a multiple linear regression model for analyzing the connection between technology advance and China's energy consumption; Finally it uses GM (1.1) gray prediction model to select the optimum technology inputs decision-making which can realize the goal of China's 11th Five-Year Plan that average energy consumption per unit GDP decline 20%, in order to provide theoretical support for the relevant departments. (4 pages)

Analysis and forecast of China's energy consumption structure

What drive the changes in China's energy consumption and intensity during 12th Five-Year Plan period?

Based on the grey correlation model and Group-AHP, with the data of China's primary energy consumption varieties, such as coal, petroleum, natural gas and non-thermal power (wind power, hydropower, nuclear power) and the environmental data of the same period, such as industrial wastewater, industrial sulfur dioxide, industrial dust, industrial smoke and industrial solid waste, this paper obtains the results of a single association and integrated evaluation of China's energy consumption structure versus environment, and the comprehensive environmental effects of China's energy consumption structure. The results show that the coal energy has the greatest relational grade versus the environmental indicators, and its comprehensive relational grade is also the largest among the consumption structure versus five pollutant emissions.

The development of society is highly dependent on energy. However, the extensive use of power causes global problems such as resource exhaustion and climate warming. China and India are typical fast-growing developing countries whose economic advancement relies on traditional energy consumption. To realize the vision of sustainable development for these states, it is necessary to study the nations' economic efficiency of power use. Based on the analysis of energy consumption and gross domestic product trends in China and India from 1990 to 2019, this paper discusses the changes in the energy consumption index per unit of gross domestic product. The authors concluded that the power consumption in China and India is mainly concentrated in the industry, residential, and transport sectors. Divided by resource types, the energy consumed by China comes primarily from coal, oil products, and electricity, while the power consumed by India is mainly from coal, oil products, biofuels and waste. Since both countries mostly use coal and oil products which belong to fossil fuels, they emit large amounts of carbon dioxide, endangering the environment quality. Given this, China and India should focus on green power development. China's total energy consumption is much larger than India's, and China's gross domestic product is much larger than India's. However, China's energy consumption per unit of gross domestic product is less than India's. The higher the energy consumption per unit of gross domestic product is, the higher the dependence of economic development on energy is. The authors' suggestions are to develop non-fossil energy sources and adjust the energy mix, recycle solid wastes, and encourage carbon trading, climate investment and financing in the states to reach sustainable development targets.

Accurately predicting energy consumption and carbon emission is important for China to make energy and carbon emission policy formulation more scientific and to achieve the goal of carbon peak before 2030 and carbon neutrality before 2060. Since energy demand is affected by numerous complex factors, it is hard to capture the dynamically developing rules of energy consumption comprehensively. Therefore, a novel two-layer decomposition-ensemble forecasting approach that was optimized by an improved particle swarm optimization algorithm based on simulation anneal and position disturbance strategy (IPSO) was proposed. Firstly, trend decomposition (TD) was utilized to break energy consumption time series down into a trend and a non-trend subseries. Then, empirical mode decomposition (EMD) was adopted to break the non-trend subseries down into several intrinsic mode functions (IMFs) and a residuum subseries. Subsequently, the aforementioned trend subseries, intrinsic mode functions, and residuum series were respectively modeled for prediction. The trend subseries was predicted using the multivariate linear regression model (MLR), which was optimized using IPSO. Both IMFs and residuum series were predicted using long short-term memory (LSTM). Finally, the final prediction of energy consumption was obtained by integrating the forecasting results of these subseries. According to China's energy consumption empirical analysis, the proposed IPSO-MLR-LSTM forecasting model based on the two-layer decomposition-ensemble approach using TD-EMD combined the advantages of TD, EMD, IPSO, and LSTM, which could comprehensively extract the developing rules of energy consumption by implementing a deeper decomposition strategy. Therefore, it is feasible and effective to apply the proposed forecasting model for energy consumption prediction. Finally, the energy consumption and carbon emissions of China under different energy consumption structure, economic growth, population, energy efficiency, and household energy consumption per capita scenarios in 2021-2035 were predicted. Then, some relevant policies and suggestions were put forward based on the forecasting results.