China Energy Statistical Yearbook Research Articles

Exploring the Carbon Footprint of Energy Consumption in Shanxi Province Based on the Tapio Decoupling and Grey BP Neural Network Model

This paper focuses on analyzing the carbon footprint of energy consumption in Shanxi Province, China. It utilizes data from sources such as the 'China Energy Statistical Yearbook' (2001-2022), the China Carbon Accounting Database, and the 'Shanxi Statistical Yearbook' for an exploratory analysis of energy consumption and the province's economy. The study calculates the carbon footprint of energy consumption in Shanxi Province and employs the LMDI model to identify influencing factors. Additionally, it uses the Tapio decoupling model to assess the relationship between these factors and economic development. To forecast the carbon footprint from 2022 to 2026, a grey BP neural network prediction model is applied, demonstrating improved accuracy compared to BP and grey models, with MAE and RMSE values of 2.44 and 10.91.

Evaluation of Sustainability for Coal Consumption Using a Multiattribute Decision-Making Model

The study of coal consumption has become a focus of academic attention due to ecological and environmental concerns. This study proposed a method to evaluate sustainability for coal consumption by using a multiple-attribute decision-making (MADM) model. The data used are from the China Statistical Yearbook and the China Energy Statistical Yearbook over the years. The MADM model consists of attributes (standards), their importance weights, and alternatives. The comprehensive evaluation system for the sustainability of coal consumption, which was composed of four first-grade indicators including coal strength (CS), energy dependency (ED), social development level (SL), and population size (PS) and their corresponding 20 second-grade indicators, was included in the MADM model as attributes (standards). The importance weight of the attributes was determined by the entropy weight method (EWM) and the analytic hierarchy process (AHP), while the comprehensive evaluation of the sustainability of coal consumption in China over the years was considered as an alternative. The evaluation indices of four first-grade indicators were obtained through multiobjective optimization, and then through the weights and evaluation indices of the four first-grade indicators, multiobjective optimization was carried out for the overall objective of the comprehensive evaluation of the sustainability of coal consumption over the years, and the comprehensive evaluation indices of the sustainable development of coal consumption over the years were obtained. The results show that China’s coal consumption is sustainable, with the composite assessment index rising from 0.058 in 2011 to 0.837 in 2021, an increase of 13.4 times.

Analysis of financial support efficiency and influencing factors of listed seed companies from the perspective of energy consumption and carbon emissions.

The seed industry has a prominent role in strengthening ecological stability and national food security as it provides the basic ground for agriculture sector. In the current research, the effectiveness of financial support provided to listed seed enterprises and its influencing factors from the perspectives of energy consumption and carbon emissions are examined using a three-stage DEA-Tobit model. The dataset for the underlined study variables mainly comes from the financial data published by 32 listed seed enterprises and the China Energy Statistical Yearbook from 2016 to 2021. In order to make the results more accurate, the influence of external environmental factors such as economic development level, total energy consumption, and total carbon emission on listed seed enterprises are excluded. The results revealed that the mean value of financial support efficiency of listed seed enterprises increased significantly after excluding the influence of external environmental and random factors. External environmental factors such as regional energy consumption and carbon dioxide emission played an important role in the process of the financial system supporting the development of listed seed enterprises. The development of some listed seed enterprises with high financial support efficiency came at the cost of high local carbon dioxide emission and high energy consumption. Internal factors such as operating profit, equity concentration, financial structure, and enterprise size are the key intra-firm factors that affect the efficiency of financial support for listed seed enterprises. Thus, it is suggested that enterprises must pay attention to the environmental performance to reach a win-win situation in reducing and improving the energy consumption and financial performance, respectively. Similarly, the improvement of energy use efficiency through endogenous and external innovation should be prioritized to achieve sustainable economic development.

The Impact of Public Transportation on Carbon Emissions—From the Perspective of Energy Consumption

Background: Transportation has become the second-largest source of global carbon emissions. Promoting low-carbon development by means of public transport and green travel and analyzing the mechanism and path of the carbon emissions reduction effect of public transport have become key to reducing carbon emissions in the transportation field and achieving “carbon peak and carbon neutrality”. Methods: The data from 30 provinces (2010–2019) were extracted from China Emission Accounts and Datasets (CEADs), China Energy Statistical Yearbook, China Statistical Yearbook, and China Automobile Statistical Yearbook. The two-way fixed-effect model was used to explore the carbon emissions reduction effect of public transport development level. The mediating-effect model was used to verify the transmission role of energy consumption in the carbon emissions reduction effect of public transport development level. Results: The study suggests that the public transport development level and CO2 emissions are negatively correlated, showing an “Inverted U-shaped” curve relationship. Energy consumption is the transmission path of the carbon emissions reduction effect of public transport development level. The public transport development level adjusts the energy consumption structure through the traffic substitution effect, energy input optimization effect, and industrial structure optimization effect and then acts on carbon emissions. Moreover, the contribution rate of energy consumption is about 4.22%. In addition, regional heterogeneity is present in the transmission path of the carbon emissions reduction effect of public transport development level based on energy consumption. The carbon emissions reduction effect of public transport development level is more significant in the central and western regions than the eastern and northeast regions of China. Conclusion: The transmission mechanism of energy consumption in the carbon emissions reduction effect of public transport is worthy of attention. To promote low-carbon and circular development in the transportation sector, it is urgent to accelerate the green upgrading of transportation infrastructure, promote the low-carbon transformation of energy production and consumption, promote carbon emissions reduction in public transport, and strengthen the linkage regulation between effective government and an effective market.

Urban residential energy switching in China between 1980 and 2014 prevents 2.2 million premature deaths

Urban residential energy switching in China between 1980 and 2014 prevents 2.2 million premature deaths

Total Factor Energy Efficiency Measurement in the Provinces of China Along the ‘Belt and Road’

Energy is an important element of a regional economic development strategy. According to the China Energy Statistical Yearbook and the China Statistical Yearbook, the proportion of energy efficiency in the provinces along the Belt and Road (BR the eastern region is restricted by technical efficiency issues, and the northeast and western regions are restricted by issues relating to technological progress.

Long-Term Cointegration Relationship between China’s Wind Power Development and Carbon Emissions

Faced with the deterioration of the environment and resource shortages, countries have turned their attention to renewable energy and have actively researched and applied renewable energy. At present, a large number of studies have shown that renewable energy can effectively improve the environment and control the reduction of resources. However, there are few studies on how renewable energy improves the environment through its influencing factors. Therefore, this paper mainly analyses the relationship between wind energy and carbon emissions in renewable energy and uses Chinese data as an example for the case analysis. Based on the model and test methods, this paper uses the 1990–2018 data from the China Energy Statistical Yearbook to study and analyse the correlation between wind energy and carbon emissions and finally gives suggestions for wind energy development based on environmental improvements.

Air pollutant emission from the underestimated households' coal consumption source in China.

In order to improve the regional air quality, many control strategies have been developed by Chinese government for reducing air pollutant emission from power plants, industrial and transport sources during the past decade. However, little attention has been paid to residential combustion sources. To fill the knowledge gap, a series of surveys were carried out to investigate the residential energy use in Beijing-Tianjin-Hebei (BTH) region during the period of 2013-2014. Study shows that the actual average amount of residential coal consumption is over 0.7tyr-1 per capita in 2013, which is much higher than that of 0.15tyr-1 per capita reported in the 2014 China Energy Statistical Yearbook (CESY). Combining the investigated activities data with the best available emission factors (EFs), bottom-up method was used to evaluate the potential air pollutant emissions from residential coal combustion in BTH region in 2013. The results indicate that Baoding is the top contributor to the whole BTH region and accounts for approximately 15% of the regional residential emissions in 2013. The spatial pattern of air pollutants shows that high emissions locate in the southeast, along the Yanshan and Taihang Mountains, where much more rural people live and coal combustion is prevalent in winter. The future emission scenario at the end of the 13th Five Year Plan (in 2020) was also predicted based on the policy guidance for the residential coal consumptions in the BTH region. The scenario analysis indicates that air pollutant emissions will drop substantially around 90% because more strict rules will be made for reducing the residential coal consumption. With combined survey information and statistical data, the uncertainty of the emission inventory which was established in this study for the residential sector in the BTH region is reduced and the emission inventory is more reliable for air quality decision making.

Carbon emission and its decoupling research of transportation in Jiangsu Province

Transportation in Jiangsu province has been developed rapidly. However, the development was accompanied with a large amount of energy consumption and carbon emissions. Combined with the coefficient in 2006 Intergovernmental Panel on Climate Change (IPCC) guidelines for national greenhouse gas inventories and China's calorific value, this article calculated the carbon emission coefficient of usual energy covered by Jiangsu Statistical Yearbook (JSY) in detail. Based on this, carbon emission of transportation in Jiangsu Province from 1995 to 2012 was easily estimated. And from the result which appears clearly that the construction of energy consumption was changed in 2011. According to China Electricity Power Yearbook (CEPY) and China Energy Statistical Yearbook (CESY), carbon emission caused by electricity power indirectly could be estimated. With the help of Tapio model, this paper conducted a research on decoupling relationship between economic growth and carbon emission of transportation in Jiangsu Province with consideration of electricity. The results show that the amount of carbon emission by electric power is significant, which makes no difference on the overall decoupling states with an obvious periodical characteristic of Weak Decoupling (Expansive Coupling)-Expansive Negative Decoupling-Weak Decoupling. Transportation has made great achievements on reducing pollution and carbon emission in Jiangsu Province since the Eleventh Five-Year Plan, and would be better on low-carbon development in potential. However, there is still a large step to realize low-carbon transportation in reality.

Coal, oil, or clean energy: Which contributes most to the low energy efficiency in China?

The lack of energy efficiency in China is always of interest. This paper builds a total-factor energy efficiency framework which contains coal energy, oil energy, and clean energy, which emits fewer pollutants into the atmosphere when used. We study the “China Statistical Yearbook” and the “China Energy Statistical Yearbook” to identify which type of energy contributes most to low energy efficiency in China. Our conclusion is that the total-factor energy efficiency (TFEE) in China has been at a relatively low level without any significant improvement from 1998 to 2010. The efficiencies of coal and oil energy have improved moderately, while there is no obvious improvement in the efficiency of clean energy. Despite the moderately improved efficiency of coal energy, its relatively low level contributes most to the overall energy inefficiency because it is the main fuel used in China. Further, the lack of improvements in the efficiency of clean energy makes it another area of policy interest.

Index decomposition analysis of residential energy consumption in China: 2002–2010

Residential energy consumption in China increased dramatically over the period of 2002–2010. In this paper, we undertake a decomposition analysis of changes in energy use by Chinese households for five energy-using activities: space heating/cooling, cooking, lighting and electric appliances. We investigate to what extent changes in energy use are due to changes from appliances and to change in floor space, population and energy mix. Our decomposition analysis is based on the logarithmic mean Divisia index technique using data from the China statistical yearbook and China energy statistical yearbook in the period of 2002–2010. According to our results, the increase in energy-using appliances is the biggest contributor to the increase of residential energy consumption during 2002–2010 but the effect declines over time, due to energy efficiency improvements in those appliances. The second most important contributor is floor space per capita, which increased with 28%. Of the four factors, population is the most stable factor and energy mix is the least important factor. We predicted electricity use, with the help of regression-based predictions for ownership of appliances and the energy efficiency of appliances. We found that electricity use will continue to rise despite a gradual saturation of demand.

Research on Spatial and Temporal Distribution of Primary Energy in China

Based on statistics from China Energy Statistical Yearbook, this paper studied basic reserves, production and consumption, spatial and temporal distribution of primary energy in 30 provinces of China by geographic information system. Result shows that primary energy resource is limited and unevenly distributed, mainly concentrates in part of northwest and northeast regions. China produced and consumed about 50% of the world coal in 2009, and imported more than 50% of crude oil from international market to meet the demand. Consumption of nuclear power and hydro power are increased year by year, yet still lower than developed countries, production and consumption of per capita of energy increased to 2.06 tce and 2.30 tce. Biomass resources are aboundant in China, with energy potential of as high as 1.17 Btce in 2030, which can be used as an important energy supplement. It is of great significance to promote the utilization of biomass energy for sustainable energy supply of China.