scholarly journals Dynamic Decomposition Analysis and Forecasting of Energy Consumption in Shanxi Province Based on VAR and GM (1, 1) Models

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Herui Cui ◽  
Ruirui Wu ◽  
Tian Zhao
Keyword(s):  
Energy Consumption ◽  
Decomposition Analysis ◽  
Coal Industry ◽  
Shanxi Province ◽  
Response Analysis ◽  
Energy Structure ◽  
Low Carbon ◽  
Stirpat Model ◽  
Urbanization Level ◽  
Green Development

Environmental issues caused by energy consumption have attracted increasing attention recently. Shanxi Province, a typical energy-dominated region in China, has long-term dependency on coal industry generating extensive economic growth, which is detrimental to green development. Distinguished from previous studies ignoring driving factors of energy consumption, this paper establishes a vector autoregression (VAR) model to dynamically identify the drivers of energy consumption based on STIRPAT model in Shanxi Province from 1990 to 2015. It can be obtained from the impulse response analysis that a positive shock in population, GDP, and urbanization level, respectively, positively affect energy consumption, and a positive change in technology negatively affects energy consumption in the long run. The variance decomposition results indicate that fluctuation in energy consumption explained by the innovation of the urbanization level accounts for 23.18%, which plays a prevailing role in increasing energy consumption. Meanwhile, the forecasting results of GM (1,1) model manifest that energy consumption in Shanxi Province generally has an increasing trend from 2016 to 2025. Consequently, Shanxi can achieve green development through optimizing energy structure, promoting the transformation of resource-based cities, and promoting low-carbon technological innovation. This paper can be available for other resource-based regions analogous to Shanxi.

scholarly journals Low-carbon development via greening global value chains: a case study of Belarus

2020 ◽  
Vol 476 (2239) ◽  
pp. 20200024
Author(s):  
Huiqing Wang ◽  
Yixin Hu ◽  
Heran Zheng ◽  
Yuli Shan ◽  
Song Qing ◽  
...  
Keyword(s):  
International Trade ◽  
Energy Consumption ◽  
Carbon Emissions ◽  
Clean Energy ◽  
Global Value Chains ◽  
Value Chains ◽  
Energy Structure ◽  
Low Carbon ◽  
Low Carbon Development ◽  
Plastic Products

The rise of global value chains (GCVs) has seen the transfer of carbon emissions embodied in every step of international trade. Building a coordinated, inclusive and green GCV can be an effective and efficient way to achieve carbon emissions mitigation targets for countries that participate highly in GCVs. In this paper, we first describe the energy consumption as well as the territorial and consumption-based carbon emissions of Belarus and its regions from 2010 to 2017. The results show that Belarus has a relatively clean energy structure with 75% of Belarus' energy consumption coming from imported natural gas. The ‘chemical, rubber and plastic products' sector has expanded significantly over the past few years; its territorial-based emissions increased 10-fold from 2011 to 2014, with the ‘food processing' sector displaying the largest increase in consumption-based emissions. An analysis of regional emissions accounts shows that there is significant regional heterogeneity in Belarus with Mogilev, Gomel and Vitebsk having more energy-intensive manufacturing industries. We then analysed the changes in Belarus' international trade as well as its emission impacts. The results show that Belarus has changed from a net carbon exporter in 2011 to a net carbon importer in 2014. Countries along the Belt and Road Initiative, such as Russia, China, Ukraine, Poland and Kazakhstan, are the main trading partners and carbon emission importers/exporters for Belarus. ‘Construction’ and ‘chemical, rubber and plastic products' are two major emission-importing sectors in Belarus, while ‘electricity' and ‘ferrous metals' are the primary emission-exporting sectors. Possible low-carbon development pathways are discussed for Belarus through the perspectives of global supply and the value chain.

Study on Energy Consumption Prediction and Energy Management in Jilin Province Based on STIRPAT Model

2013 ◽  
Vol 281 ◽  
pp. 542-545 ◽  
Author(s):  
Zhuo Ma ◽  
Wei Liu ◽  
Lei Wang ◽  
Ping Liang Ma ◽  
Yong Xuan Wang ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Jilin Province ◽  
Energy Structure ◽  
Stirpat Model ◽  
The Sustainable Development ◽  
Important Means ◽  
Energy Consumption Prediction ◽  
Consumption Control ◽  
Consumption Prediction

Energy consumption control and energy management are the important guarantee for the sustainable development of economy and society in China. Take Jilin province as an example, we study the methods and practice of energy consumption peak prediction, discuss the control countermeasures of energy consumption peak and study the countermeasures of energy efficiency and energy management. The study shows that, technology advances, industry restructuring and energy structure adjustments are the important means of energy management.

Study on the Transition to Low-Carbon Electricity in Coal Industry in Shandong

2013 ◽  
Vol 734-737 ◽  
pp. 1702-1706
Author(s):  
Zhong Wen Liu ◽  
Bin Gao ◽  
Peng Zhao Gao
Keyword(s):  
Industrial Structure ◽  
Paper Analysis ◽  
Coal Industry ◽  
Shandong Province ◽  
Energy Structure ◽  
Low Carbon ◽  
Coal Technology ◽  
Low Carbon Development ◽  
Mode Of Development ◽  
Economic Growth Mode

Economic development of Shandong province is over-reliance on coal resources, which produces shackles for the development of economy in Shandong. No matter from the current economic growth mode, the structure of energy consumption and current environmental pollution, the development model of economy in Shandong requires the transition to a low-carbon model, and there is an urgent requirement to go low carbon development path. This paper analysis that the energy structure in the presence of low carbon development of coal industry in Shandong province is not coordinated, the industrial structure is irrational, the extensive mode of development has not fundamentally change and there are some achievements in low carbon technology innovation and the development of circular economy. The paper provides the path for transition to low-carbon electricity in coal industry in Shandong through coal production, coal utilization, coal technology of low-carbon transition and other aspects.

Research on the Regional Low-Carbon Industrial Development: A Case of Tianjin Binhai New Area

2011 ◽  
Vol 219-220 ◽  
pp. 250-253 ◽  
Author(s):  
Xiao Ying Cui ◽  
Hui Ming Li ◽  
Lei Wang
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Industrial Development ◽  
Carbon Emission ◽  
Large Scale ◽  
Industrial Structure ◽  
Industrial Sector ◽  
Energy Structure ◽  
Low Carbon ◽  
Tianjin Binhai New Area

Energy consumption induced by industry sector is the main source of carbon emission. So it is important to the policy making that research on the low-carbon industrial development, which is aiming to establish an industry system with low-carbon character. There are four restrictive factors on low-carbon industrial development in Tianjin Binhai New Area of China: the rather large scale of the secondary industry, the heavy industrial structure which strongly caused the increasing energy consumption, the high-carbon energy structure of industrial sector, and the lower industrial energy efficiency which has certain gap compared with other regions. Several countermeasures are proposed to reduce carbon emission induced by industrial sector, such as improving energy efficiency, optimizing energy structure, establishing multiple-access financing mechanism to encourage R&D on low-carbon technology, enhancing the development of low carbon industry, participating in the international cooperation actively, and making strategic plan of low-carbon industrial development.

Calculation of Carbon Dioxide Emission in Nanjing City and its Influencing Factors

2014 ◽  
Vol 665 ◽  
pp. 517-520
Author(s):  
Qiang Zhao ◽  
Xiu Mei Li ◽  
Xiang Yu Cui
Keyword(s):  
Carbon Dioxide ◽  
Energy Consumption ◽  
Influencing Factors ◽  
Carbon Dioxide Emissions ◽  
Carbon Dioxide Emission ◽  
Clean Energy ◽  
Energy Structure ◽  
Low Carbon ◽  
Index Decomposition ◽  
Laspeyres Index

The research estimates the carbon dioxide emissions of energy consumption from 2003 to 2011 using the method in IPCC national greenhouse gases listing guidance, by adopting the method of Kaya identities and Laspeyres index decomposition technique to analyze the influencing factors and the influencing degree. The result shows that the main factors influencing carbon dioxide emissions are energy structure and per capita GDP, and to develop clean energy, to improve energy structure are important choice to reduce the carbon dioxide emissions of energy consumption, realize low carbon in the future. This research provides an important reference to protect the environment and to promote the sustainable development of economy.

scholarly journals Multi-Scenario Analysis of Energy Consumption and Carbon Emissions: The Case of Hebei Province in China

Energies ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 624 ◽  
Author(s):  
Zeng Li ◽  
Jingying Fu ◽  
Gang Lin ◽  
Dong Jiang ◽  
Kun Liu ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Alternative Energy ◽  
Ghg Emissions ◽  
Structure Optimization ◽  
Energy System ◽  
Hebei Province ◽  
Energy Structure ◽  
Reference Scenario ◽  
Low Carbon ◽  
The Impact

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.

scholarly journals Analysis of CO2 Drivers and Emissions Forecast in a Typical Industry-Oriented County: Changxing County, China

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1212 ◽  
Author(s):  
Yao Qian ◽  
Lang Sun ◽  
Quanyi Qiu ◽  
Lina Tang ◽  
Xiaoqi Shang ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Industrial Structure ◽  
Ghg Emissions ◽  
Energy Structure ◽  
Low Carbon ◽  
Stirpat Model ◽  
Carbon Reduction ◽  
Economic Output ◽  
Low Carbon Development ◽  
And Control

Decomposing main drivers of CO2 emissions and predicting the trend of it are the key to promoting low-carbon development for coping with climate change based on controlling GHG emissions. Here, we decomposed six drivers of CO2 emissions in Changxing County using the Logarithmic Mean Divisia Index (LMDI) method. We then constructed a model for CO2 emissions prediction based on a revised version of the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model and used it to simulate energy-related CO2 emissions in five scenarios. Results show that: (1) From 2010 to 2017, the economic output effect was a significant, direct, dominant, and long-term driver of increasing CO2 emissions; (2) The STIRPAT model predicted that energy structure will be the decisive factor restricting total CO2 emissions from 2018 to 2035; (3) Low-carbon development in the electric power sector is the best strategy for Changxing to achieve low-carbon development. Under the tested scenarios, Changxing will likely reach peak total CO2 emissions (17.95 million tons) by 2030. Measures focused on optimizing the overall industrial structure, adjusting the internal industry sector, and optimizing the energy structure can help industry-oriented counties achieve targeted carbon reduction and control, while simultaneously achieving rapid economic development.

Comparative Study on Carbon Emission and Energy Consumption of the Textile Industry in Henan Province

2011 ◽  
Vol 84-85 ◽  
pp. 770-774
Author(s):  
Hong Yan Li
Keyword(s):  
Energy Consumption ◽  
Textile Industry ◽  
Carbon Emission ◽  
Henan Province ◽  
Hunan Province ◽  
Shanxi Province ◽  
Jiangxi Province ◽  
Low Carbon ◽  
Low Carbon Economy ◽  
Great Pressure

Selects 9 industries as the comparison of textile industry, estimates the and the industry's carbon emission amount in China and energy consumption levels in Henan Province in recent years, and compare the energy consumption levels of Henan in 2007 and 2008 with the other central provinces: Hunan Province, Jiangxi Province and Shanxi Province. The results show that: in China, the carbon emission of textile industry is less, but in Henan Province is relatively large. Especially in these two years, there is rapid growth in energy consumption of textile industry, which results in great pressure on the environment. Finally recommend to implement energy saving and realize low-carbon economy.

Influencing Factors Decomposition of the Carbon Emission of Industrial Energy Consumption in Nanning Downtown Based on LMDI

2015 ◽  
Vol 737 ◽  
pp. 925-934 ◽  
Author(s):  
Jing Yang ◽  
Huan Mei Yao ◽  
Meng Lin Qin
Keyword(s):  
Energy Consumption ◽  
Carbon Emission ◽  
Energy Intensity ◽  
Industrial Structure ◽  
Energy Structure ◽  
Driving Factor ◽  
Low Carbon ◽  
Industrial Carbon ◽  
Industrial Energy ◽  
Industrial Energy Consumption

According to IPCC carbon emission calculation instruction, the amount of industrial carbon emission of downtown of Nanning from 2003-2012 is evaluated. With LMDI element decomposition method, the carbon emission of industrial energy consumption in Nanning downtown is decomposed into effect of five aspects such as energy structure, energy intensity, industrial structure, economic scale and population size. It turns out that: the energy structure change can promote the increase of carbon emission. The energy consumption structure should be optimized and the proportion of high-carbon energy consumption should be reduced; The energy intensity is the leading driving factor of carbon emission. The energy efficiency should be further improved to control the increase of carbon emission to some degree; The industrial structure restrains the increase of carbon emission in a great degree. Industrial restructuring should be strengthened and low-carbon industry should be developed; The scale of economy is the main driving factor of the increase of carbon emission. The extensive way of economic growth which depends on the large input of production factors should be changed; The population has a promoting function the increase of carbon emission, while the driving effect is weak, and the growth rate of the population should be strictly controlled.

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