Calculation and Evaluation Methodology of Transport Energy Consumption and Carbon Emissions: A Case Study of Jiangsu Province

2014 ◽  
Vol 962-965 ◽  
pp. 1293-1302 ◽  
Author(s):  
Bin Ouyang ◽  
Zhen Hua Feng ◽  
Qing Hua Bi
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Energy Intensity ◽  
Jiangsu Province ◽  
Policy Implications ◽  
System Structure ◽  
Evaluation Methodology ◽  
Carbon Intensity ◽  
Low Carbon ◽  
Carbon Transport

The calculation methodology of transport carbon emissions, based on the methodology recommended by Intergovernmental Panel on Climate Change (IPCC) and the energy consumption statistics of provincial transport industry in China, is proposed. By using the methodology, the energy consumption and carbon emissions of highway, waterway and urban passenger transport from 2005 to 2012 of Jiangsu Province are calculated and evaluated. And the developing trends and main features from the perspectives of the total amount of transport energy consumption and carbon emissions, the proportional of both various energy types and various transport modes in the energy consumption, the energy intensity and carbon dioxide intensity, are systematically analyzed. Finally, some policy implications of low-carbon transport development were conclusively put forward, including reducing energy intensity and carbon intensity as the core focus, the highway transport as the breakthrough point, optimizing the integrated transport system structure and developing of public transport in priority as the strategic orientation, developing clean and low-carbon energy as an important way, etc. The research methodology and results can provide references for decision-making and management of the relevant provinces and cities on low-carbon transport development.

An Analysis on Carbon Emissions and Energy Efficiency of Small Heavy Industrial Enterprises in Shanghai

2013 ◽  
Vol 869-870 ◽  
pp. 997-1000
Author(s):  
Jing Jing Zhang ◽  
Jian Cheng Kang ◽  
Hao Zhang
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Carbon Emissions ◽  
Energy Intensity ◽  
Correlation Coefficients ◽  
Carbon Intensity ◽  
Small Enterprises ◽  
Growth Trend ◽  
Positive Correlation ◽  
Industrial Enterprises

Based on the energy consumption and the output value data of the 6 small heavy industrial enterprises during 2007-2011 in Shanghai, we calculated comprehensive energy consumption, carbon emissions, carbon intensity and energy intensity of these enterprises. It been found that the comprehensive energy consumption and the carbon emissions of the 6 small enterprises are in a fluctuating growth trend but the energy intensity and the carbon intensity show a trend of fluctuating downward. The energy intensity and the carbon intensity of the small enterprises are much larger than the average of the two whole industries in Shanghai. We analyzed the correlation coefficients between the output value and the energy consumption as well as between the output value and the carbon emissions. The results show that the comprehensive energy consumption and the carbon emissions have positive correlation as well as the carbon emissions and the output value.

scholarly journals Countermeasures and suggestions regarding the development of low carbon transport

2020 ◽  
Vol 194 ◽  
pp. 04001
Author(s):  
Jianfang Zong ◽  
Liang Sun ◽  
Huiting Guo ◽  
Fei Fang
Keyword(s):  
Energy Consumption ◽  
Greenhouse Gas ◽  
Future Development ◽  
Carbon Emissions ◽  
Present Status ◽  
Urban Transport ◽  
Low Carbon ◽  
Transport Industry ◽  
Countermeasures And Suggestions ◽  
Carbon Transport

The transport industry is the main sector of China’s energy consumption, while the urban transport is the main way of China’s carbon emissions. Therefore, the development of low carbon transport is not only the significant way to mitigate greenhouse gas emissions, but also the inevitable trend for future development of transport industry. This paper introduces the present status and fundamental connotation, characteristics and implementation path of low carbon transport. On such basis, this paper illustrates the international experiences of low carbon transport, and analyzes the main problems existing in the development of urban low carbon transport in China. This paper also provides the countermeasures and suggestions regarding the development of low carbon transport in China.

scholarly journals Influencing Factors and Scenario Forecasts of Carbon Emissions of the Chinese Power Industry: Based on a Generalized Divisia Index Model and Monte Carlo Simulation

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2398 ◽  
Author(s):  
Lin Zhu ◽  
Lichun He ◽  
Peipei Shang ◽  
Yingchun Zhang ◽  
Xiaojun Ma
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Energy Intensity ◽  
Power Industry ◽  
Emissions Reduction ◽  
Low Carbon ◽  
Maximum Probability ◽  
Index Model ◽  
Carbon Emissions Reduction ◽  
Probability Range

The power industry is the industry with the most direct uses of fossil fuels in China and is one of China’s main carbon industries. A comprehensive and accurate analysis of the impacts of carbon emissions by the power industry can reveal the potential for carbon emissions reductions in the power industry to achieve China’s emissions reduction targets. The main contribution of this paper is the use of a Generalized Divisia Index Model for the first time to factorize the change of carbon emissions in China’s power industry from 2000 to 2015, and gives full consideration to the influence of the economy, population, and energy consumption on the carbon emissions. At the same time, the Monte Carlo method is first used to predict the carbon emissions of the power industry from 2017 to 2030 under three different scenarios. The results show that the output scale is the most important factor leading to an increase in carbon emissions in China’s power industry from 2000 to 2015, followed by the energy consumption scale and population size. Energy intensity levels have always promoted carbon emissions reduction in the power industry, where energy intensity and carbon intensity effects of energy consumption have great potential to mitigate carbon levels. By setting the main factors affecting carbon emissions in the future three scenarios, this paper predicts the carbon emissions of China’s power industry from 2017 to 2030. Under the baseline scenario, the maximum probability range of the potential annual growth rate of carbon emissions by the power industry in China from 2017 to 2030 is 1.9–2.2%. Under the low carbon scenario and technological breakthrough scenario, carbon emissions in China’s power industry continue to decline from 2017 to 2030. The maximum probability range of the potential annual drop rate are measured at 1.6–2.1% and 1.9–2.4%, respectively. The results of this study show that China’s power industry still has great potential to reduce carbon emissions. In the future, the development of carbon emissions reduction in the power industry should focus on the innovation and development of energy saving and emissions reduction technology on the premise of further optimizing the energy structure and adhering to the low-carbon road.

An Optimal Model for Low-Carbon Urban Agglomeration Based on Energy Structure Reduction under Uncertainty

2012 ◽  
Vol 599 ◽  
pp. 211-215
Author(s):  
Lun Wang ◽  
Zhao Sun ◽  
Jing Ya Wen ◽  
Zhuang Li ◽  
Wen Jin Zhao ◽  
...  
Keyword(s):  
Regional Planning ◽  
Energy Intensity ◽  
Greenhouse Gas Emission ◽  
Urban Agglomeration ◽  
Carbon Intensity ◽  
Energy Structure ◽  
Low Carbon ◽  
Optimal Model ◽  
The Sustainable Development

This paper developed an optimal model of low-carbon urban agglomeration on the base of energy structure under uncertainty. The case study shows that the carbon intensity was decreased by [32.19, 41.20] (%) and energy intensity was reduced by [34.08, 43.19] (%) compared with those in 2010; meanwhile, the carbon intensity and energy intensity in the core area was reduced by [50.88, 54.11] (%) and [51.24, 54.57] (%) respectively, compared with those in 2010. The optimized scheme could not only meet the requirements of 12th Five-Year Planning Outline of Controlling Greenhouse Gas Emission, but also complied with the requirements of regional planning targets. The established model also provided more decision-making space for the sustainable development of low-carbon urban agglomeration.

Carbon Emission of Mining Industry’s Energy Consumption in Heilongjiang Province

2015 ◽  
Vol 1092-1093 ◽  
pp. 1597-1600
Author(s):  
Zhong Hua Wang ◽  
Xin Ye Chen
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Industrial Structure ◽  
Mining Industry ◽  
Calculation Model ◽  
Energy Utilization ◽  
Utilization Efficiency ◽  
Heilongjiang Province ◽  
Low Carbon

The need to reduce carbon emission in Heilongjiang Province of China is urgent challenge facing sustainable development. This paper aims to make explicit the problem-solving of carbon emission to find low carbon emission ways. According to domestic and foreign literatures on estimating and calculating carbon emissions and by integrating calculation methods of carbon emissions, it was not possible to consider all of the many contributions to carbon emissions. Calculation model of carbon emissions suitable to this paper is selected. The carbon emissions of energy consumption in mining industry are estimated and calculated from 2005 to 2012, and the characteristics of carbon emission are analyzed at the provincial level. It makes the point that carbon emissions of energy consumption in mining industry can be reduced when we attempt to alter energy consumption structure, adjust industrial structure and improve energy utilization efficiency.

Influencing Factors and Decoupling Analysis of Carbon Emissions in China's Manufacturing Industry

2021 ◽  
Author(s):  
baoling jin ◽  
ying Han
Keyword(s):  
Carbon Emissions ◽  
Manufacturing Industry ◽  
Energy Intensity ◽  
Value Added ◽  
Carbon Intensity ◽  
Energy Structure ◽  
Investment Efficiency ◽  
Fixed Asset ◽  
Carbon Productivity ◽  
Fixed Asset Investment

Abstract The manufacturing industry directly reflects national productivity, and it is also an industry with serious carbon emissions, which has attracted wide attention. This study decomposes the influential factors on carbon emissions in China’s manufacturing industry from 1995 to 2018 into industry value added (IVA), energy consumption (E), fixed asset investment (FAI), carbon productivity (CP), energy structure (EC), energy intensity (EI), investment carbon intensity (ICI) and investment efficiency (IE) by Generalized Divisia Index Model (GDIM). The decoupling analysis is carried out to investigate the decoupling states of the manufacturing industry under the pressure of "low carbon" and "economy.” Considering the technological heterogeneity, we study the influential factors and decoupling status of the light industry and the heavy industry. The results show that: (1) Carbon emissions of the manufacturing industry present an upward trend, and the heavy industry is the main contributor. (2) Fixed asset investment (FAI), industry value added (IVA) are the driving forces of carbon emissions. Investment carbon intensity (ICI), carbon productivity (CP), investment efficiency (IE), and energy intensity (EI) have inhibitory effects. The impact of the energy consumption (E) and energy structure (EC) are fluctuating. (3) The decoupling state of the manufacturing industry has improved. Fixed asset investment (FAI), industry value added (IVA) hinder the decoupling; carbon productivity (CP), investment carbon intensity (ICI), investment efficiency (IE), and energy intensity (EI) promote the decoupling.

Analysis of Hubei Province Industry’s Carbon Emissions Based on the LMDI

2014 ◽  
Vol 675-677 ◽  
pp. 1865-1868 ◽  
Author(s):  
Han Li ◽  
Lin Wu
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Hubei Province ◽  
Hunan Province ◽  
Carbon Intensity ◽  
Logarithmic Mean ◽  
Coal Consumption ◽  
Industrial Carbon ◽  
Industrial Energy ◽  
Industrial Energy Consumption

LMDI (Logarithmic Mean Divisia Index) was used to estimates the carbon emission of industrial energy consumption in Hunan Province with collected data on industrial energy consumption in 2000-2012. The results showed that carbon emissions of industrial energy consumption present the overall upward trend in Hubei Province, where the carbon emissions of coal consumption are the main factors, this shows that the industry of Hubei is extensive development withhigh energy consumption. In addition, industrial carbon intensity has a fluctuated downward trend in 2011-2012; this shows that Hubei province has made ​​a positive change on control carbon emissions of energy consumption.

scholarly journals Analysis of total carbon emission of the logistics industry in Guangdong and solutions to emission reduction

2021 ◽  
Vol 245 ◽  
pp. 01020
Author(s):  
Aixia Xu ◽  
Xiaoyong Yang
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Energy Utilization ◽  
Total Carbon ◽  
Utilization Rate ◽  
Low Carbon ◽  
Logistics Industry ◽  
Direct Energy ◽  
Reduce Emissions

The input-output method is employed in this study to measure the total carbon emission of the logistics industry in Guangdong. The findings revealed that the carbon emission of direct energy consumption of the logistics industry in Guangdong is far above the actual carbon emissions, the second and third industries play a significant role in carbon emission of indirect energy consumption in the logistics industry in Guangdong. To reduce energy consumption and carbon emissions in Guangdong, it is not only important to control the carbon emissions in the logistics industry, but strengthen carbon emission detection in relevant industries, improve the energy utilization rate and reduce emissions in other industries, and move towards low-carbon sustainable development.

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.

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