China's transportation sector carbon dioxide emissions efficiency and its influencing factors based on the EBM DEA model with undesirable outputs and Spatial Durbin model

Energy ◽  
2021 ◽  
pp. 121934
Author(s):  
Pengjun Zhao ◽  
Liangen Zeng ◽  
Peilin Li ◽  
Hai-yan Lu ◽  
Haoyu Hu ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Influencing Factors ◽  
Carbon Dioxide Emissions ◽  
Undesirable Outputs ◽  
Spatial Durbin Model ◽  
Dea Model ◽  
Transportation Sector

scholarly journals Estimation of Carbon Dioxide from Transportation Sector Based on Urban Data Availability

2019 ◽  
Vol 14 (3) ◽  
pp. 411-420
Author(s):  
Abdu Fadli Assomadi ◽  
Rachmat Boedisantoso ◽  
Agus Slamet ◽  
Arie Dipareza Syafei ◽  
Joni Hermana
Keyword(s):  
Carbon Dioxide ◽  
Developing Countries ◽  
Standard Error ◽  
Calculation Method ◽  
Carbon Dioxide Emissions ◽  
Data Availability ◽  
Alternative Methods ◽  
Calculation Methods ◽  
Intergovernmental Panel ◽  
Transportation Sector

One source of potential carbon dioxides in most developing countries is the transportation sector. The calculation of carbon dioxides is therefore, important as a part of policy making on carbon management in the region. The Intergovernmental Panel on Climate Change (IPCC) calculation method which were often used require large and complete data. This is a problematic for developing countries due to the availability of data are not in accordance or sufficient with the IPCC method. This study examined the alternative calculation methods that are tailored to the available data in most developing countries. Two alternative methods are proposed for calculating carbon dioxide emissions; the first method is based on data of the number and types of vehicles, and the second method is based on the data and the length of the road class. The results show that both alternative methods are reliable to estimate specific emission factor (SEF) and emission estimates that are close to the IPCC calculation methods. The alternative of second method provides results that are closer to the IPCC calculation method with the correlation value of 0.997 and the standard error of 2.8 ton CO2/years, as compared to the results of alternative first method (correlation value of 0.990 and the standard error of 4.7 ton CO2/years).

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.

Influencing Factors Analysis of Carbon Dioxide Emissions of Liaoning Power Consumption Based on Kaya Model

2013 ◽  
Vol 779-780 ◽  
pp. 1476-1481 ◽  
Author(s):  
Chang He Jiang ◽  
Wen Ru Zang ◽  
Lei Lei Hu
Keyword(s):  
Carbon Dioxide ◽  
Power Consumption ◽  
Influencing Factors ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Liaoning Province ◽  
Low Carbon ◽  
Low Carbon Economy ◽  
Carbon Reduction ◽  
Industry Investment

In order to achieve the carbon reduction targets committed by China, Liaoning Province must take the way of low-carbon economy. Based on the related Statistical Yearbook data, applying the IPCC carbon emissions equation and Kaya model, this paper analyses the influencing factors of the carbon dioxide emissions produced from the power consumption of Liaoning Province. and then put forward some suggestion on reducing carbon emissions. The results show that Liaoning Province can achieve the goal, but unit GDP CO2 emissions reduction is mainly due tothe investment expansion of the second industry and construction industry investment expansion. As a result, it puts forward some suggestions.

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