Energy Consumption and Carbon Emissions: Analysis and Prediction-The Case of Hebei Province in China

Based on the results of SSM, regional natural endowment conditions, the stage of economic development and the industrial structure evolution determine the energy consumption structure, while the changes in total energy consumption determine the changes in amount of carbon emissions. Under the premise of the total energy consumption is determined, the optimization of energy consumption structure will reduce the carbon intensity (emissions per unit of GDP), that is to achieve low-input, low-emission energy, high output, which is the essence of the low carbon economic development model. Hebei Energy consumption is heavily dependent on coal; however, coal utilization efficiency is low and unit energy carbon emissions are huge, therefore, energy structure dominated by carbon-based energy is a long-term constraint of the development of low carbon economy. Energy consumption structure is composed of regional natural endowments, the stage of economic development and industrial structure, and it is difficult to change in the short term.

Excessive carbon emissions from energy consumption seriously restrict China's sustainable development and eco-environmental protection. Although the carbon emissions from the construction industry are less than that of the power, transportation, and manufacturing sectors, the carbon emissions released by the construction industry cannot be ignored due to its extensive development trend of high energy consumption and low efficiency. Based on this, this paper studies energy-related carbon emissions and emissions reduction of China's construction industry from 2007 to 2017 by adopting the input-output analysis method, energy consumption method, and structural decomposition model. The results show that within the sample range: (1) The optimization of the construction industry energy consumption structure has a significant reduction effect on the growth of energy carbon emissions from the construction industry in China, and the reduction effect has shown an increasing trend over time. However, it should be noted that in this sample range, the optimization of energy consumption structure in the construction industry is mainly reflected in the decrease of the proportion of high-carbon energy consumption such as raw coal, while low-carbon energy such as natural gas has not played a significant role. Therefore, the future energy optimization space of China's construction industry is still huge. (2) Energy intensity effect and input structure effect have a positive inhibitory effect on carbon emission growth of the construction industry, and the inhibitory effect of energy intensity effect is stronger than that of input structure effect. It shows that in the sample range, the generalized technological progress and energy efficiency of the construction industry have been better optimized and improved. (3) Except for 2015-2017, the final demand effect in other intervals has a positive effect on the growth of carbon emissions in the construction industry, and the secondary and tertiary industries play a major role in the final demand effect. It shows that the total demand for the construction industry in various industries still maintains a growth trend. This paper provides a theoretical analysis basis and practical guidance for China's construction industry to carry out more accurate and efficient emission reduction from the supply-side energy varieties and demand-side industry level, and further enriches the existing research on carbon emissions of the construction industry from the perspective of input-output analysis.

With the rapid development of economy, energy demand is increasing in Hebei. Therefore, prediction of energy consumption and structure in Hebei province has importance of actual meaning significance. In this paper, total energy, coal, oil and natural gas consumption data are selected in Hebei province between 2001 and 2013. First, energy consumption and structure in Hebei province are analyzed. Second, GM(1,1)forecast model is established. Then, according to the established forecast model, energy consumption and structure between 2014 and 2021 in Hebei province is predicted. Last, related suggestions on energy optimization are put forward. The results are expected to provide important scientific basis for energy utilization and planning in Hebei province. Introduction Grey prediction is a method that can predict the systems containing uncertainties. To find the laws of system changes, original data is generating processed by identifying development trend of dissimilarity degree between system factors. Thus, data sequence with high regularity is generated. And then the corresponding differential equation model is established to predict future development trend of things. GM (1,1) prediction model with a variable and first-order differential is an important model of grey prediction. It is commonly used in energy and environment prediction because this model requires less modeling information, operates easily, forecasts precisely and is easy to test. In this paper, total energy, coal, oil and natural gas consumption data in Hebei province between 2001 and 2013 are selected as original sequence. GM (1, 1) model is constructed to predict energy consumption and structure in following 20 years in Hebei province. It hopes to provide reference and scientific basis for energy development strategy and the establishment of energy planning in Hebei. Analysis of energy consumption and structure in Hebei province The energy data in Hebei province between 2000 and 2012 are from China energy statistical yearbook. In this paper, all the energy consumption data have been converted into standard coal and the unit is ten thousand tons of standard coal. Table one shows the energy consumption and consumption structure in Hebei province. As shown in table 1, the total energy consumption in Hebei province seems to be increasing annually from 2000 to 2012 and its average annual growth rate is 7.95%. However, the speed of total energy consumption growth is different during the period and it has periodic growth characteristic. From the table, we can see that the growth speed is rapid from 2001 to 2007. Energy consumption structure in Hebei province is basically stable in recent years because of restriction on resources endowment and consumption structure of energy relying mainly on coal cannot be changed. Coal accounts for about 90 percent in energy consumption before 2011, but oil, gas and electricity such clean energy consumption occupies 10 percent of the total energy consumption. This shows that there is no variety in energy consumption structure in Hebei province and energy consumption has many defects. It depends heavily on coal which is non-renewable International Conference on Computational Science and Engineering (ICCSE 2015) © 2015. The authors Published by Atlantis Press 34 energy, so the renewable clean energy strengthened the large market demand, and the development of solar energy utilization technology has a broad prospect. Table.1 Energy consumption and consumption structure in Hebei province Year Total energy consumption Coal Oil Natural gas Electric power Total Proportion Total Proportion Total Proportion Total Proportion 2001 11195.71 10181.38 90.94 914.69 8.17 94.04 0.84 5.60 0.05 2002 12114.29 11125.76 91.84 898.88 7.42 84.80 0.70 4.85 0.04 2003 13404.53 12214.21 91.12 1092.47 8.15 93.83 0.70 4.02 0.03 2004 15297.89 14193.38 92.78 992.83 6.49 100.97 0.66 10.71 0.07 2005 17347.79 15810.78 91.14 1389.56 8.01 130.11 0.75 17.35 0.1

For a long time, China’s energy consumption structure is relatively simple, the total amount and scale of coal consumption in Hebei Province ranked the forefront of China, while the carbon emission and energy consumption structure have great relevance, the regional haze problem is serious, energy saving and emission reduction task is arduous. Therefore, the energy consumption structure of Hebei Province needs to be optimized urgently. In this paper, the carbon pinch point method is used to find the minimum clean energy consumption and various fossil energy consumption, which carries on the optimization to the energy structure in Hebei Province.

This paper investigates the development trends and variation characteristics of China’s economy, energy consumption and carbon emissions from 2007 to 2030, and the impacts on China’s economic growth, energy consumption, and carbon emissions under the carbon tax policy scenarios, based on the dynamic computable general equilibrium (CGE) model. The results show that during the simulation period, China’s economy will keep a relatively high growth rate, but the growth rate will slow down under the benchmark scenario. The energy consumption intensity and the carbon emissions intensity per unit of Gross Domestic Product (GDP) will continually decrease. The energy consumption structure and industrial structure will gradually optimize. With the economic growth, the total energy consumption will constantly increase, and the carbon dioxide emissions are still large, and the situation of energy-saving and emission-reduction is still serious. The carbon tax is very important for energy-saving and emission-reduction and energy consumption structure optimization, and the effect of the carbon tax on GDP is small. If the carbon tax could be levied and the enterprise income tax could be reduced at the same time, the dual goals of reducing energy consumption and carbon emissions and increasing the GDP growth can be achieved. Improving the technical progress level of clean power while implementing a carbon tax policy is very meaningful to optimize energy consumption structure and reduce the carbon emissions, but it has some offsetting effect to reduce energy consumption.

In view of the complexity of the energy system and its complex relationship with socio-economic factors, this study adopts the Long-range Energy Alternative Planning (LEAP) model, a technology-based, bottom-up approach, scenario-based analysis, to develop a systematic analysis of the current and future energy consumption, supply and associated Green House Gas (GHG) emissions from 2015 to 2050. The impact of various energy policies on the energy system in Hebei Province was analysed by considering four scenarios: a Reference Scenario (REF), Industrial Structure Optimization Scenario (ISO), Terminal Consumption Structure Optimization Scenario (TOS) and Low-carbon Development Scenario (LCD). By designing strategic policies from the perspective of industrial adjustment, aggressive energy structure policies and measures, such as the ISO and the TOS, and even more aggressive options, such as the LCD, where the percentage of cleaner alternative energy sources has been further increased, it has been indicated that energy consumption will have increased from 321.618 million tonnes of coal equivalent (Mtce) in 2015 to 784.88 Mtce in 2050 in the REF, with a corresponding increase in GHG emissions from 920.56 million metric tonnes (Mt) to 2262.81 Mt. In contrast, the more aggressive policies and strategies involved in the LCD, which combines the ISO with the policy-oriented TOS, can lower energy consumption by 50.82% and CO2 emissions by 64.26%. The results shed light on whether and how these scenarios can shape the energy-carbon emission reduction trajectories and develop the low-carbon pathways in Hebei Province.

This paper uses statistical learning theory and big data analysis to study the energy consumption structure of China from qualitative and quantitative aspects during COVID-19. According to the domestic and foreign scholars’ research on the optimization of energy consumption structure, the carbon emission factor is considered in the optimization of energy consumption structure. Taking the minimum energy consumption cost and carbon dioxide emission as the objective function, the carbon dioxide emission is taken as the objective function, and the total energy consumption and various energy consumption proportions as the constraint conditions, the multi-objective planning method is used to evaluate the energy consumption structure of China. The optimization model of source consumption structure is analyzed, and the medium and long-term energy transformation path and optimization model under low-carbon constraints are studied. Combined with the experimental algorithms related to big data, it is concluded that China’s economic development mainly depends on a large amount of energy consumption during the COVID-19 period. On this basis, some suggestions are put forward to realize the sustainable development of China’s economy and energy.

In recent years, the global greenhouse effect caused by excessive energy-related carbon emissions has attracted more and more attention. In this paper, we studied the dynamic evolution of factors driving China's energy-related CO2 emissions growth from 2007 to 2015 by using energy consumption method and input-output analysis and used the IO-SDA model to decompose the energy carbon emissions. Within the research interval, the results showed that (1) on the energy supply-side, the high carbon energy represented by raw coal was still the main factor to promote the growth of energy-related CO2 emissions. However, the optimization of energy consumption structure is conducive to reducing emissions. Specifically, the high carbon energy represented by raw coal exhibited a downward trend in promoting the increment of energy-related CO2 emissions, while the clean energy represented by natural gas showed an upward trend in promoting the increment of CO2 emissions. It is worth noting that there is still a lot of room for optimization of China’s energy consumption structure to reduce emissions. (2) On the energy demand-side, the final demand effect is the main driving force of the growth of carbon emissions from fossil energy. Among them, the secondary industry plays a major role in the final demand effect. The "high carbonization" of the final product reflects the characteristics of China's high energy input in the process of industrialization. At the same time, since the carbon emission efficiency of the tertiary industry and the primary industry is better than that of the secondary industry, actively optimizing the industrial structure is conducive to slowing down the growth of carbon emission brought by the demand effect. (3) The input structure effect is the main restraining factor for the growth of energy carbon emissions, while the energy intensity effect has a slight driving effect on the growth of energy carbon emissions. The results show that China's "extensive" economic growth model has been effectively reversed, but the optimization of fossil energy utilization efficiency is still not obvious, and there is still a large space to curb carbon emissions by improving fossil energy utilization efficiency in the future.

The impact of energy consumption structure on China’s carbon emissions: Taking the Shannon–Wiener index as a new indicator

Optimization of energy consumption structure based on carbon emission reduction target: A case study in Shandong Province, China

Nowadays, energy consumption has been to be one of the biggest problems in China. It is very important to increase proportion of electric power among the end-use energy market for optimization of end-use energy consumption structure. Research on the status of electrical energy in energy consumption for China is a critical method to improve its development. In this paper, it analyses the electrical energy status in the industry energy consumption from 1995 to 2010. Secondly, status of electrical energy in the final energy consumption has been researched deeply. Finally, it analyses the role of electrical energy in energy consumption according to the curve of data from 1995 to 2010, gives some suggestions for optimization of the energy consumption structure so that save energy.

As the biggest developing country in the world, with sustainable and fast development of economy, the fossil energy consumption and carbon emission increases so quickly that the problem of energy security and carbon emission is more and more prominent In China. Therefore, building the sustainable energy supply system and energy consumption mode is the important guarantee for constructing harmonious society. This paper analyses the status of the gross energy consumption and its structure change in China, and then researches the problems of the energy consumption structure. In the end, the paper puts forward the specific countermeasures on optimizing the energy consumption structure, such as striving to develop new energy, improving the using of energy efficiency, promoting the development of low-carbon economy and so on.

In recent years, the environmental problems caused by excessive carbon emissions from energy sources have become increasingly serious, which not only aggravates the climate change caused by the greenhouse effect but also seriously restricts the sustainable development of Chinese economy. An attempt is made in this paper to use energy consumption method and input-output method to study the carbon emission structure of China's energy system and industry in 2015 from two perspectives, namely China's energy supply side and energy demand side, by taking into account the two factors of energy invest in gross capital formation and export. The results show that neglecting these two factors will lead to underestimation of intermediate use carbon emissions and overestimation of final use carbon emissions. On energy supply side, the carbon emission structure of China's energy system is still dominated by high-carbon energy (raw coal, coke, diesel, and fuel oil, etc.), accounting for more than 70% of total energy carbon emissions; on the contrary, the natural gas such as clean energy accounts for only 3.45% of total energy carbon emissions, indicating that the energy consumption structure optimization and emission reduction gap of China's energy supply side are still substantial. On energy demand side, the final use (direct consumption by residents and government) produces less carbon emissions, while the intermediate use (production by enterprises) produces more than 90% of the total energy carbon emissions. Fossil energy, power sector, heavy industry, chemical industry, and transportation belong to industries with larger carbon emissions and lower carbon emission efficiency, while agriculture, construction, light industry, and service belong to industries with fewer carbon emissions and higher carbon emission efficiency. This means that the optimization of industrial structure is conducive to slowing down the growth of energy carbon emissions on the demand side.

Analysis of urban energy consumption in carbon metabolic processes and its structural attributes: a case study for Beijing

From 1980 to 2012 there were 80% carbon dioxide emission from traditional fossil energy in the world, and the proportion reached 90% in China, which was the top of carbon dioxide emission and energy consumption. In order to release the pressure of short term energy-saving and emission-reduction, as well as implement energy system cleaning in long term, reversing the positive situation of energy structure adjustment and the advancing the continuous evolution of energy consumption structure will be the effective methods. This paper takes Hebei Province and the whole country as the research objects, analyzes the influence of energy consumption structure changes on carbon dioxide emission and the correlation effect between energy consumption structure and carbon dioxide emission intensity by constructing a correlation model between energy consumption structure and carbon dioxide emission intensity, discusses the effective strategies for the regional energy-saving and emission-reduction.