Energy Structure Adjustment Research Articles

Inter-annual variability of wintertime PM2.5 chemical composition in Xi'an, China: Evidences of changing source emissions

Chemical characteristics of PM2.5 in Xi'an in wintertime of 2006, 2008, and 2010 were investigated. Markers of OC2, EC1, and NO3−/SO42− ratio were calculated to investigate the changes in PM2.5 emission sources over the 5-year period. Positive matrix factorization (PMF) model was used to identify and quantify the main sources of PM2.5 and their contributions. The results showed that coal combustion, motor vehicular emissions, fugitive dust, and secondary inorganic aerosol accounted for more than 80% of PM2.5 mass. The importance of these major sources to the PM2.5 mass varied yearly: coal combustion was the largest contributor (31.2%±5.2%), followed by secondary inorganic aerosol (20.9%±5.2%) and motor vehicular emissions (19.3%±4.8%) in 2006; the order was still coal combustion emissions (27.6%±3.4%), secondary inorganic aerosol (23.2%±6.9%), and motor vehicular emissions (20.9%±4.6%) in 2008; while coal combustion emission further decreased (24.1%±3.1%) with fugitive dust (19.4%±5.5%) increasing in 2010. The changes in PM2.5 chemical compositions and source contributions can be attributed to the social and economic developments in Xi'an, China, including energy structure adjustment, energy consumption, the expansion of civil vehicles, and the increase of urban construction activities.

Sustainable Development of Geothermal Industry in China: An Overview

With a wide distribution, large reserves, low cost, sustainable energy use and environmental protection and other unparalleled advantages, geothermal energy resources is important for China’s energy structure adjustment, energy conservation and environment improvement. Currently, geothermal utilization in China is still in its infancy, and Sustainable Development of the geothermal industry is also having a lot of problems. In this paper, the current research on sustainable development of geothermal industry focuses on two aspects: 1. the current situation of geothermal industry development and existing problems, 2. the current situation of sustainable development of the geothermal industry. On the basis of the review, some suggestions for further study on the sustainable development of geothermal industry are put forward.

An externality evaluation model for hydropower projects: A case study of the Three Gorges Project

Hydropower has become an important method for relieving energy tensions and facilitating energy structure adjustments in China. However, the development of hydropower has been restricted due to issues related to migration, ecology, and benefit sharing. The key is to establish a reasonable and scientifically based benefit sharing system that considers all input and output factors in a project's life cycle. Most of the studies performed in this field to date have focused on the direct costs and benefits of hydropower projects; however, the systematic identification and integral assessment of externalities is seriously lacking. Therefore, this paper 1) identifies a hydropower project's externalities using the Externality Theory based on analysis of input and output factors; 2) chooses or designs a specific calculation method for each externality and subsequently establishes an externality evaluation model for hydropower projects; and 3) calculates and analyses the externalities of the TGP (Three Gorges Project). The results show that the TGP has several considerable positive externalities, whose monetary value is approximately five times that of the negative externalities. Additionally, there are so many externalities that should not be ignored that it is necessary to include externalities in the evaluation of hydropower projects. These results lay a foundation for establishing a scientific and reasonable benefit-sharing system and provide the public with important and quantitative information to objectively understand the TGP.

Development of an integrated optimization method for analyzing effect of energy conversion efficiency under uncertainty – A case study of Bayingolin Mongol Autonomous Prefecture, China

In this study, a superiority–inferiority full-infinite mixed-integer programming (SFMP) method is developed for analyzing the effect of energy conversion efficiency under uncertainty. SFMP can effectively tackle uncertainties expressed as fuzzy sets, crisp intervals and functional intervals, it also can directly reflect relationships among multiple fuzzy sets through varying superiority and inferiority degrees with a high computational efficiency. Then the developed SFMP is applied to a real case of planning energy system for Bayingolin Mongol Autonomous Prefecture, where multiple scenarios related to different energy-conversion efficiency are concerned. Results for energy processing, energy conversion, capacity expansion, pollutant emission and system cost have been generated. It is proved that SFMP is an effective approach to deal with the uncertainties in energy systems with interactive and uncertain characteristics. A variety of uncertainties existed in energy conversion processes and impact factors could affect the modeling result. Results show that improvement of energy-conversion efficiency can effectively facilitate reducing energy resources consumption, optimizing energy generation pattern, decreasing capacity expansion, as well as mitigating pollutant emissions. Results also reveal that, for the study area, electric power has a highest energy saving potential among heating, oil processing, coal washing and refining. Results can help decision makers to generate desired alternatives that can facilitate policy enactment of conversion efficiency improvement and adjustment of regional energy structure under uncertainty.

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

In 2009, the Chinese government announced its carbon intensity target for 2020. Can China achieve this carbon intensity while sustaining economic growth? To address this essential issue, the contributions of this study lie in three aspects. First, we quantitatively capture the relationship between China's economic growth and energy consumption using the cointegration theory, and predict China's energy consumption by 2020 according to different economic growth targets. Second, we forecast China's energy structure in 2020 using compositional data and ARIMA models under different scenarios. Third, we deduce China's CO2 emission and carbon intensity in 2020. Furthermore, we investigate whether (or not) China can realize the carbon intensity target in premise of ensuring economic growth, and evaluate the contribution of the energy structure's adjustment to meeting this target. Finally, we put forward some relevant policy implications for achieving China's carbon intensity target.

Decomposition analysis on influence factors of direct household energy‐related carbon emission in Guangdong province—Based on extended Kaya identity

The decomposition quantitative model of household energy‐related carbon emission in Guangdong is established based on the extended Kaya identity with the Logarithmic Mean Divisia Index (LMDI) method; influence factors of household energy‐related carbon emission are decomposed into eight factors, energy price, average consumption propensity, and urban–rural structure of population included in the model. Results show that total direct household energy‐related carbon emission in Guangdong province show increasing trend from 1995 to 2012. Oil and electric power consumption are two main source of household carbon emission. Results of decomposition show that resident's living standard has the largest contribution to the increase of carbon emission, which is the first promoting factor to household energy‐related carbon emission, followed by energy use level. Energy price has the largest contribution to the reduction of carbon emission, which is the first inhibiting factor, followed by average consumption propensity. Guangdong can realize household energy‐related carbon mitigation effectively by the following four measures, namely (1) Adjust energy structure, especially energy structure of power generation, enhances the proportion of nuclear power, (2) Improve energy price mechanism, (3) Optimize urban–rural structure of population, (4) Drive application of home intelligent energy management technology, to realize automatic home energy‐saving control. © 2015 American Institute of Chemical Engineers Environ Prog, 35: 298–307, 2016

Probe into the Strategies of Regional Energy-Saving and Emission-Reduction Based on the Energy Consumption Structure Evolution

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.

Analysis of energy efficiency and carbon dioxide reduction in the Chinese pulp and paper industry

Pulp and paper production, an energy-intensive process, is among the main light industries contributing to energy saving and pollution emission reduction in China. The improvement of energy efficiency is essential for energy consumption and sustainable development. This study analyzes the negative factors in the pulp and paper sector by calculating energy efficiency from the lengthways time and investigating the gap between China and foreign countries through a horizontal comparison. Accordingly, energy efficiency has increased in the Chinese pulp and paper industry with years of efforts, but its transformation remains unclear. Furthermore, the energy-saving potential, energy cost saving, and carbon dioxide emission reduction in the pulp and paper industry are evaluated according to the Twelfth Five-year Plan (2011–2015). The results show that the pulp and paper industry has further capabilities for energy-saving and carbon dioxide emission reduction by improving energy efficiency in China, resulting in great economic benefit. In brief, new technology and energy structure adjustment are long-term strategies for energy conversation, with changes in the scale of mills expected to provide huge opportunities to improve energy efficiency in China within a short period.

CO2 emissions and mitigation potential of the Chinese manufacturing industry

Energy-related CO2 emissions of the Chinese manufacturing industry are critically important for China and for the entire world. This study addresses the historical trajectory and features of CO2 emissions in the Chinese manufacturing industry, investigates the influencing factors of CO2 emission changes utilizing the logarithmic mean Divisia index (LMDI) method, and explores the mitigation potential based on scenario analyses. The results show the following: (1) CO2 emissions experienced spectacular but unsteady growth during the 1993–2011 period, although CO2 emissions intensity presented a downward trend; (2) the coal-dominant emissions structure was subject to an electricity-dominant emissions structure; (3) the smelting and pressing of ferrous metals (C32), manufacture of raw chemical materials and chemical products (C26) and manufacture of non-metallic mineral products (C31) were the top three sectors, combining to account for approximately 60% of total emissions; (4) the economic scale was the major driving factor and energy intensity was the most important diminishing factor of CO2 emissions, and the effects of the emission coefficient, energy structure and economic structure were minuscule; and (5) CO2 emissions mitigation in the future will mainly depend on drops in energy intensity, declines in emission coefficient of electricity and upgrades in economic structure – their additive effects on CO2 emissions reductions will be 5412 Mt in 2020. However, energy structure adjustment with the proportion of electricity increasing is not beneficial in terms of CO2 emissions reductions, because of electricity's high emission factor.

Environmental and Economic Optimization Model for Electric System Planning in Ningxia, China: Inexact Stochastic Risk-Aversion Programming Approach

The main goal of this paper is to provide a novel risk aversion model for long-term electric power system planning from the manager’s perspective with the consideration of various uncertainties. In the proposed method, interval parameter programming and two-stage stochastic programming are integrated to deal with the technical, economics, and policy uncertainties. Moreover, downside risk theory is introduced to balance the trade-off between the profit and risk according to the decision-maker’s risk aversion attitude. To verify the effectiveness and practical application of this approach, an inexact stochastic risk aversion model is developed for regional electric system planning and management in Ningxia Hui Autonomous Region, China. The series of solutions provide the decision-maker with the optimal investment strategy and operation management under different future emission reduction scenarios and risk-aversion levels. The results indicated that pollution control devices are still the main measures to achieve the current mitigation goal and the adjustment of generation structure would play an important role in the future cleaner electricity system with the stricter environmental policy. In addition, the model can be used for generating decision alternatives and helping decision-makers identify desired energy structure adjustment and pollutants/carbon mitigation abatement policies under various economic and system-reliability constraints.

Correlation Study on Energy Consumption and Economic Sustainable Development of Liaoning

As one of old northeast industrial base, Liaoning province, whose economic growth depends largely on energy consumption, which is not conducive to sustainable economic development. According to the GDP and energy statistical data of Liaoning in 1988~2012, we use the correlation analysis and regression analysis of statistical methods to research the relationship between energy consumption and economic growth,then getting the correlation coefficient and regression models.Through analyzing results and combining with real situation of Liaoning, we put forward suggestions from the following seven aspects, they are improving energy efficiency, accelerating energy marketization, adjusting energy structure, optimizing industrial structure, developing circular economy, enhancing energy-saving ideas and establishing strategic alliances to promote energy and economic sustainable development.

An Empirical Research on the Relationship between Environmental Quality and Energy Consumption in China

The relationship between environmental quality and energy consumption has become more and more important. This paper firstly develops the index for China’s comprehensive environmental quality evaluation, and employs spss17.0 to conduct factorial analysis and comprehensive analysis on the condition of China’s comprehensive environmental quality between 1995 and 2012. By using Eviews6.0 to build a regression model for China’s environmental quality and energy consumption and exercising stationary test and Granger causality test, this paper also affirms the co-integration relationship between environmental quality and energy consumption in China. Among all energy sources, coal consumption has the closest relationship with environmental quality, and oil and natural gas consumptions are in the 2nd and 3rd place. In the last part, this paper proposes countermeasures and suggestions like optimizing industrial structure, adjusting energy structure and improving technologies in energy utilization.

Dynamic Research on Residents Consumption and Power Consumption of Harbin Using GM(1,1) Model

The modern city development and improvement of residents’ consumption level have strong dependence on power consumption. In the important period of the optimization of energy structure adjustment and residents’ consumption structure upgrade, the article carried out the correlation analysis of Harbin city residents’ consumption and power consumption, discussed the corresponding relation of them, and forecasts the residents’ consumption and power consumption based on GM(1,1) model. It also put forward suggestions that included reasonably limit consumption, effectively energy saving, focused on the development of new energy, and to promote economic development.

Adjust Energy Structure, Promoting Chinese Environmental Protection

With the sustained and rapid development of Chinese economy, the energy issue has become a constraining "bottleneck" in economic and social development. Therefore, optimization of energy structure is an inevitable trend. In this paper, through the contrast of China and the other countries energy structure and environmental conditions, we think Chinese adjustment of energy structure is still have large space and environment protection efforts need to be strengthened. At last we puts forward some suggestions about promoting environmental protection and reducing carbon emissions.

Impacts of Electricity Price Reform on Energy and Residents’ Life in China

Electricity price reform aims at improving resource allocation and energy saving. In this paper, The latest input-output data and price affect partial-closed model are used to measure the impacts of electricity price reform for the whole society, energy industry and the residents con- sumptions. The results indicate that electricity price reform had limited impacts on GDP and resi- dents’ consumption, and the impacts on mining industryand energy industry are more significant than others. The policy certainly achieved the aim to adjust energy structure and promoted the co -ordinated development of urban and rural economy.

Carbon and air pollutants constrained energy planning for clean power generation with a robust optimization model—A case study of Jining City, China

In this study, a multistage inexact stochastic robust model was developed for regional energy system management in Jining City, China. Three scenarios about the electric power structure adjustment, clean power generation, and the emission reduction target are designed. Methods of interval parameter programming (IPP), stochastic robust optimization (SRO), and multistage stochastic programming (MSP) were incorporated into the developed model to tackle uncertainties described by interval values and probability distributions. The results indicated that the model can provide an effective linkage between conflicting economic cost and the system stability, and different power demand levels correspond to different electricity generation schemes with varied system cost and system-failure risk. The net system cost, power generation schemes, exported electricity, and captured CO2 amount were analyzed. The results indicated that the power generation by traditional technology would be decreased with the improvement of regional energy structure adjustment and environmental protection request. The modeling results are valuable for supporting the adjustment or justification of the existing power generation schemes within a complicated energy system under uncertainty.

Regional disaggregation of China's national carbon intensity reduction target by reduction pathway analysis

Chinese government announced it is going to reduce carbon intensity in 2020 by 40 to 45% when compared with 2005 levels. One question for how to accomplish this is how to disaggregate national target to provincial level. This study employed a regional disaggregation approach based on a series of principles. Analysis of the carbon intensity revealed three main approaches to reduce CO2 are energy structure adjustment, technical improvement and energy substitution. We proposed a disaggregation model from the view of reduction approaches. Through the data collection and analysis of provinces from 2005 to 2010, a regional disaggregation scheme is carried out in which the national carbon intensity reduction target during the 12th Five-Year Plan was set at 17%. The calculated regional targets were then compared with official published data. The results showed that this method could be useful for disaggregation of the target to the provincial level.

Dynamic simulation of China’s carbon emission reduction potential by 2020

Along with the rapid economic development of China, carbon dioxide (CO $$_{2}$$ ) emissions will inevitable rise in the future. This will happen even though the Chinese government has made a series of attempts to constrain the CO $$_{2}$$ -emissions, and is committed to reduce its CO $$_{2}$$ -emissions per unit of gross domestic product (GDP) by 40–45 % (1,045–1,140 tons/million dollars) by 2020 from 2005 levels. However, according to estimates the total amount of CO $$_{2}$$ -emissions will grow to more than 13 billion tons, and the carbon intensity will be twice of the world average. In order to improve this situation, this research study will construct a comprehensive dynamic simulation model to forecast China’s CO $$_{2}$$ -emissions and GDP development under different energy structure adjustment plans and carbon intensity constraints from 2008 to 2020. In addition, find out the trade-off between Chinese carbon intensity reduction and economic development. The comprehensive model we constructed includes a CO $$_{2}$$ -emissions model, an energy balance model, and a socio-economic model. Through a dynamic simulation analysis established by LINGO programming, this study provides the proper carbon intensity that China can achieve under the current situation, lie 1,040 tons/million dollars in 2020 (a 45 % reduction compared with the situation in 2005), while the CO $$_{2}$$ -emissions will be 12.51 billion tons, the proportion of non-fossil energy 15 %, and the average annual increase in GDP 9 %. This research provides an effective method to estimate the interaction between economic growth and CO $$_{2}$$ -emissions reduction, with alternative energy utilization in the future.

Analysis of CO2emissions peak: China’s objective and strategy

Establishing positive and urgent targets for CO2 reduction and emission peak, and promoting energy conservation and energy structure adjustment are among the strategies to address global climate change and CO2 emissions reduction. They are also means to break through the constraints of domestic resources and environment, and internal needs, to achieve sustainable development. Generally speaking, a country's CO2 emission peak appears after achieving urbanization and industrialization. By then, connotative economic growth will appear, GDP will grow slowly, energy consumption elasticity will decrease, and energy consumption growth will slow down – dependent mainly on new and renewable energies. Fossil fuel consumption will not increase further. When CO2 emission reaches its peak, the annual reduction rate of CO2 intensity of GDP is greater than GDP annual growth rate; and the annual reduction rate of CO2 intensity of energy use is greater than the annual growth rate of energy consumption. Therefore, three important approaches to promotion of CO2 emission peak can be concluded: maintaining reasonable control of GDP growth, strengthening energy conservation to significantly reduce the GDP energy intensity, and optimizing the energy mix to reduce the CO2 intensity of energy use. By around 2030, China will basically have completed its rapid development phase of industrialization and urbanization. Connotative economic growth will appear with the acceleration of industrial structure adjustment. The target of GDP energy intensity will still be to maintain an average annual reduction of 3% or higher. The proportion of non-fossil fuels will reach 20–25%, and the aim will be to maintain an average annual growth rate of 6–8%. The total annual energy demand growth of 1.5% will be satisfied by the newly increased supply of non-fossil fuels. The annual decline in CO2 intensity of GDP will reach 4.5% or higher, which is compatible with an average annual GDP growth rate of approximately 4.5% in order to reach CO2 emission peak. This corresponds to the level of China's potential economic growth. Achieving CO2 emission peak will not impose a rigid constraint on economic development, but rather promote economic development and accelerate the transformation of green, low-carbon development. The CO2 emission peak can be controlled with a cap of 11 billion tons, which means that CO2 emission will increase by less than 50% compared with 2010. The per capita emission peak will be controlled at a level of less than 8 tons, which is lower than the 9.5 tons in the EU and Japan and much lower than the 20 tons in the US, future economic and social development faces many uncertainties in achieving the CO2 emission peak discussed above. It depends on current and future strategies and policies, as well as the pace and strength of economic transformation, innovation, and new energy technologies. If the economic transformation pattern fails to meet expectations, the time required to reach CO2 emission peak would be delayed and the peak level would be higher than expected. Therefore, we need to coordinate thoughts and ideas and deploy these in advance; to highlight the strategic position of low-carbon development and its priorities; to enact mid- to long-term energy development strategies; and to establish and improve a system of laws, regulations, and policies as well as an implementation mechanism for green, low-carbon development. Oriented by positive and urgent CO2 reduction and peak targets, the government would form a reversed mechanism to promote economic transformation and embark on the path of green, low-carbon development as soon as possible.

Smart Grid and its Application

Smart grid could meet the electricity demand against the rapid development of economy and society. The idea to implement smart grid is fully in accordance with the energy developing strategy and it will exert far-reaching impact on the adjustment of energy structure, the sustainable development of society as well as low-carbon economy. Currently, smart grid has attracted wide attention around the world and major countries in the world have been carrying out related researches. This paper describes the background and basic concepts of the smart grid, and takes the United States, European Union and China for example to introduce the development characteristics and typical projects. Besides, this paper analyzes and compares the smart grid in U.S., E.U. and China and gives related suggestions on the key issues of the development of smart grid in China.