scholarly journals Decomposition Analysis and Trend Prediction of CO2 Emissions in China’s Transportation Industry

2020 ◽  
Vol 12 (7) ◽  
pp. 2596
Author(s):  
Ming Meng ◽  
Manyu Li
Keyword(s):  
Co2 Emissions ◽  
Carrying Capacity ◽  
Carbon Dioxide Emissions ◽  
Industrial Structure ◽  
Decomposition Analysis ◽  
Carbon Accounting ◽  
Transportation Industry ◽  
Trend Prediction ◽  
Intensity Effect ◽  
Per Capita

China’s transportation industry has become one of the major industries with rapid growth in CO2 emissions, which has a significant impact in controlling the increase of CO2 emissions. Therefore, it is extremely necessary to use a hybrid trend extrapolation model to project the future carbon dioxide emissions of China. On account of the Intergovernmental Panel on Climate Change (IPCC) inventory method of carbon accounting, this paper applied the Logarithmic Mean Divisia Index (LMDI) model to study the factors affected by CO2 emissions. The affected factors are further subdivided into the scale of employees, per capita carrying capacity, transport intensity, average transportation distance, energy input and output structure, energy intensity and industrial structure. The results are as follows: (1) Per capita carrying capacity is the most important factor to promote the growth of CO2 emissions, while industrial structure is the main reason to inhibit the growth of CO2 emissions; (2) the expansion of the number of employees has played a positive role in the growth of CO2 emissions and the organization and technology management of the transportation industry should be strengthened; (3) comprehensive transportation development strategy can make the transportation intensity effect effectively reduce CO2 emissions; (4) the CO2 emissions of the transportation industry will continue to increase during 2018–2025, with a cumulative value of about 336.11 million tons. The purpose of this study is to provide scientific guidance for the government’s emission reduction measures in the transportation industry. In addition, there are still some deficiencies in the study of its influencing factors in this paper and further improvements are necessary for the subsequent research expansion.

scholarly journals The Regional Inequity of CO2 Emissions per Capita in China

2017 ◽  
Vol 9 (7) ◽  
pp. 228 ◽  
Author(s):  
Ting Liu ◽  
Wenqing Pan
Keyword(s):  
Co2 Emissions ◽  
Emission Reduction ◽  
Co2 Emission ◽  
Energy Intensity ◽  
Industrial Structure ◽  
Theil Index ◽  
Energy Structure ◽  
Co2 Emission Reduction ◽  
Index Method ◽  
Per Capita

This paper combines Theil index method with factor decomposition technique to analyze China eight regions’ inequality of CO2 emissions per capita, and discuss energy structure, energy intensity, industrial structure, and per capita output’s impacts on inequality. This research shows that: (1) The trend of China regional carbon inequality is in the opposite direction to the per capita CO2 emission level. Namely, as the per capita CO2 emission levels rise, regional carbon inequality decreases, and vice versa. (2) Per capita output factor reduces regional carbon inequality, whereas energy structure factor and energy intensity factor increase the inequality. (3) More developed areas can reduce the carbon inequality by improving the energy structure, whereas the divergence of energy intensity in less developed areas has increased to expand the carbon inequity. Thus, when designing CO2 emission reduction targets, policy makers should consider regional differences in economic development level and energy efficiency, and refer to the main influencing factors. At the same time, upgrading industrial structure and upgrading energy technologies should be combined to meet the targets of economic growth and CO2 emission reduction.

scholarly journals Key Factors Influencing the Achievement of Climate Neutrality Targets in the Manufacturing Industry: LMDI Decomposition Analysis

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 8006
Author(s):  
Kristiāna Dolge ◽  
Dagnija Blumberga
Keyword(s):  
Energy Efficiency ◽  
Co2 Emissions ◽  
Manufacturing Industry ◽  
Decomposition Analysis ◽  
Clean Energy ◽  
Industrial Activity ◽  
Intensity Effect ◽  
Wood Processing ◽  
Activity Effect ◽  
The Impact

The manufacturing industry is often caught in the sustainability dilemma between economic growth targets and climate action plans. In this study, a Log-Mean Divisia Index (LMDI) decomposition analysis is applied to investigate how the amount of industrial energy-related CO2 emissions in Latvia has changed in the period from 1995 to 2019. The change in aggregate energy-related CO2 emissions in manufacturing industries is measured by five different factors: the industrial activity effect, structural change effect, energy intensity effect, fuel mix effect, and emission intensity effect. The decomposition analysis results showed that while there has been significant improvement in energy efficiency and decarbonization measures in industry, in recent years, the impact of the improvements has been largely offset by increased industrial activity in energy-intensive sectors such as wood processing and non-metallic mineral production. The results show that energy efficiency measures in industry contribute most to reducing carbon emissions. In the future, additional policies are needed to accelerate the deployment of clean energy and energy efficiency technologies.

scholarly journals Decomposition Analysis of CO2 Emissions for Turkey and Iran over 1990-2010

2014 ◽  
Author(s):  
Hasan Rüstemoğlu ◽  
Sevin Uğural
Keyword(s):  
Co2 Emissions ◽  
Scale Effect ◽  
Energy Intensity ◽  
Decomposition Analysis ◽  
Carbon Intensity ◽  
Composition Effect ◽  
Economic Sectors ◽  
Intensity Effect ◽  
The World ◽  
Laspeyres Index

There exists an important awareness for reduction of CO2 emissions to obtain a sustainable world. Together with this, there is a great deal of interest for decomposition analysis to see the accelerating and decelerating factors of CO2 emissions. The aim of this project is to decompose CO2 emissions in economic sectors for the two superpowers of Middle East, Iran and Turkey, over the time period between 1990 and 2010, for Turkey obtained a rapid growth performance in recent years and Iran which is the energy superpower of the world. Refined Laspeyres Index decomposition method and a consistent data gathered from the World Bank’s and UN’s databases have been used during the analysis. Five main sectors (agriculture, manufacturing, transportation, construction and other service sectors) and four main impacts (scale effect, composition effect, energy intensity effect and carbon intensity effect) have been considered to see the increasing and decreasing factors of CO2 emissions. Various interesting results are observed for both of the countries, for each of the economic sectors. Generally scale effect and energy intensity effect are the dominant impacts for all sectors of both countries. However composition effect and carbon intensity effect are also important contributors for economic activities of these two countries. Overall, our analysis showed that these two countries should pay attention for energy intensity and sustainable economic growth.

scholarly journals The travel-related carbon dioxide emissions of atmospheric researchers

2008 ◽  
Vol 8 (2) ◽  
pp. 7373-7389 ◽  
Author(s):  
A. Stohl
Keyword(s):  
Carbon Dioxide ◽  
Co2 Emissions ◽  
Information Exchange ◽  
Carbon Dioxide Emissions ◽  
Radiative Forcing ◽  
Global Climate ◽  
Air Travel ◽  
Ozone Production ◽  
Per Capita ◽  
Carbon Dioxide Co2

Abstract. Most atmospheric scientists agree that greenhouse gas emissions have already caused significant changes to the global climate system and that these changes will accelerate in the near future. At the same time, atmospheric scientists who – like other scientists – rely on international collaboration and information exchange travel a lot and, thereby, cause substantial emissions of carbon dioxide (CO2). In this paper, the CO2 emissions of the employees working at an atmospheric research institute (the Norwegian Institute for Air Research, NILU) caused by all types of business travel (conference visits, workshops, field campaigns, instrument maintainance, etc.) were calculated for the years 2005–2007. It is estimated that more than 90% of the emissions were caused by air travel, 3% by ground travel and 5% by hotel usage. The travel-related annual emissions were between 1.9 and 2.4 t CO2 per employee or between 3.9 and 5.5 t CO2 per scientist. For comparison, the total annual per capita CO2 emissions are 4.5 t worldwide, 1.2 t for India, 3.8 t for China, 5.9 t for Sweden and 19.1 t for Norway. The travel-related CO2 emissions of a NILU scientist, occurring in 24 days of a year on average, exceed the global average annual per capita emission. Norway's per-capita CO2 emissions are among the highest in the world, mostly because of the emissions from the oil industry. If the emissions per NILU scientist derived in this paper are taken as representative for the average Norwegian researcher, travel by Norwegian scientists would nevertheless account for a substantial 0.2% of Norway's total CO2 emissions. Since most of the travel-related emissions are due to air travel, water vapor emissions, ozone production and contrail formation further increase the relative importance of NILU's travel in terms of radiative forcing.

scholarly journals Effects of Kyoto Protocol on CO2 Emissions: A Five-Country Rolling Regression Analysis

2019 ◽  
Vol 11 (3) ◽  
pp. 744
Author(s):  
Chien-Ho Wang ◽  
Ming-Hui Ko ◽  
Wan-Jiun Chen
Keyword(s):  
Co2 Emissions ◽  
Kyoto Protocol ◽  
Carbon Dioxide Emissions ◽  
Global Financial Crisis ◽  
Turning Points ◽  
Developed Countries ◽  
Heated Debate ◽  
Per Capita ◽  
Rolling Regression ◽  
The Impact

The current study illustrated the time variance of turning points in the relationship between carbon emissions and income to resolve heated debate on the different responsibility to climate change with 1950–2010 data of five development diversity countries—three developed countries (Germany, Italy, and Japan) and one developing country (India) and one newly industrialized economy (Taiwan). The article also examines the impact of the crisis on emission. The time-varying patterns in the turning points on environmental Kuznets curves (EKCs) were observed by a rolling regression technique with 1950–2010 data regarding the per capita CO2 emissions caused by fossil fuel combustion and the incomes of the countries. Several empirical findings were revealed from this analysis. Per capita CO2 emissions commonly decreased with varying magnitudes in the five countries over time. The EKC hypothesis regarding the CO2 emissions is affirmed again in this study. The announcement effects associated with the Kyoto Protocol was evidenced. As indicated by the occurring GDP of the turning point, there is a strong reduction trend in the income level of the turning points right before the years of Kyoto Protocol; and this decreasing trend nearly ended as the Kyoto protocol approached its end, except in Germany, where the occurring income of the turning points continued to have a decreasing trend. Although the global financial crisis had its effects in the world, the impacts on carbon dioxide emissions vary across countries.

Analysis of Impact Factors of China's Carbon Dioxide Emissions

2012 ◽  
Vol 616-618 ◽  
pp. 1111-1114
Author(s):  
Xiao Yu Ma ◽  
Qiang Yi Li ◽  
Adili Tuergong
Keyword(s):  
Carbon Dioxide Emissions ◽  
Industrial Structure ◽  
Positive Impact ◽  
Dynamic Panel Data ◽  
Impact Factors ◽  
Dynamic Panel ◽  
Consumption Structure ◽  
Current Period ◽  
Per Capita ◽  
The Impact

This paper estimates the quantity of CO2 emissions in 30 provinces of China covering the year from 1999 to 2010, combining static and dynamic panel data model.Meanwhile, we use instruments to control the endogeny of the two models, analyzing the impact factors of China's CO2 emissions comprehensively and objectively. The result shows that a inverted U-shaped relationship is found between per capita GDP and CO2 emissions per capita .And it means that the Environmental Kuznets Hypothesis is verified in China.And energy consumption structure, industrial structure and urbanization have a positive impact on China's CO2 emissions. The CO2 emissions of last period have a crucial impact on the emissions of current period.

scholarly journals Relationships between Causal Factors Affecting Future Carbon Dioxide Output from Thailand’s Transportation Sector under the Government’s Sustainability Policy: Expanding the SEM-VECM Model

Resources ◽  
2018 ◽  
Vol 7 (4) ◽  
pp. 81 ◽  
Author(s):  
Pruethsan Sutthichaimethee ◽  
Danupon Ariyasajjakorn
Keyword(s):  
Energy Consumption ◽  
Confidence Interval ◽  
Co2 Emissions ◽  
Direct Effect ◽  
Industrial Structure ◽  
Per Capita Gdp ◽  
Net Exports ◽  
Transportation Sector ◽  
Per Capita ◽  
Urbanization Rate

This research aims to analyze the relationships between causal factors likely to affect future CO2 emissions from the Thai transportation sector by developing the Structural Equation Modeling-Vector Autoregressive Error Correction Mechanism Model (SEM-VECM Model). This model was created to fill information gaps of older models. In addition, the model provides the unique feature of viable model application for different sectors in various contexts. The model revealed all exogenous variables that have direct and indirect influences over changes in CO2 emissions. The variables show a direct effect at a confidence interval of 99%, including per capita GDP (), labor growth (), urbanization rate factor (), industrial structure (), energy consumption (), foreign direct investment (), oil price (), and net exports (). In addition, it was found that every variable in the SEM-VECM model has an indirect effect on changes in CO2 emissions at a confidence interval of 99%. The SEM-VECM model has the ability to adjust to the equilibrium equivalent to 39%. However, it also helps to identify the degree of direct effect that each causal factor has on the others. Specifically, labor growth () had a direct effect on per capita GDP () and energy consumption () at a confidence interval of 99%, while urbanization rate () had a direct effect on per capita GDP (), labor growth (), and net exports () at a confidence interval of 99%. Furthermore, industrial structure () had a direct effect on per capita GDP () at a confidence interval of 99%, whereas energy consumption () had a direct effect on per capita GDP () at a confidence interval of 99%. Foreign direct investment () had a direct effect on per capita GDP () at a confidence interval of 99%, while oil price () had a direct effect on industrial structure (), energy consumption (), and net exports () at a confidence interval of 99%. Lastly, net exports () had a direct effect on per capita GDP () at a confidence interval of 99%. The model eliminates the problem of heteroskedasticity, multicollinearity, and autocorrelation. In addition, it was found that the model is white noise. When the SEM-VECM Model was used for 30-year forecasting (2018–2047), it projected that CO2 emissions would increase steadily by 67.04% (2047/2018) or 123.90 Mt CO2 Eq. by 2047. The performance of the SEM-VECM Model was assessed and produced a mean absolute percentage error (MAPE) of 1.21% and root mean square error (RMSE) of 1.02%. When comparing the performance value with the values of other, older models, the SEM-VECM Model was found to be more effective and useful for future research and policy planning for Thailand’s sustainability goals.

scholarly journals Decoupling and decomposition analysis on the CO2 emissions of tourism industry: A case study of Hainan

2019 ◽  
Vol 118 ◽  
pp. 04042
Author(s):  
Yong Yang ◽  
Junsong Jia ◽  
Chunyan Liu ◽  
Duanqian Mao
Keyword(s):  
Energy Use ◽  
Industrial Structure ◽  
Decomposition Analysis ◽  
Tourism Industry ◽  
Primary Role ◽  
Intensity Effect ◽  
Use Efficiency ◽  
Countermeasures And Suggestions ◽  
Tourism Economy

Currently, little attention was paid to the tourism’s CO2 emission (CE) at province level. Thus, taking Hainan as a case, we computed this province’s CE, and analyzed the relationship between Hainan’s tourism economy and its CE, and the drivers of the CE. The results showed that Hainan’s tourism CE increased rapidly from 99.88×104 t in 2001 to 475.07×104 t in 2015. Particularly, Tourism transport always accounted for the largest proportion of tourism CE (more than 74%). Moreover, Hainan presented a holistic weak decoupling (0.68) during 2001-2015. But the decoupling rate was only 57.14%. Thus, Hainan still has much potential to improve the energy-use efficiency of tourism industry for accelerating the decoupling process. In addition, the effect of population was the dominant driver to promote Hainan’s tourism CE followed by expenditure size effect with the contribution rates of 132.52% and 11.78%, respectively. Whereas energy intensity effect played the most primary role in inhibiting CE followed by industrial structure effect, and their contribution rates were -38.65% and -5.58%, respectively. Last, based on these results above, some reasonable countermeasures and suggestions are proposed.

Decomposition analysis of energy-related CO2 emissions in South Africa

2015 ◽  
Vol 26 (1) ◽  
pp. 67-73 ◽  
Author(s):  
Ming Zhang ◽  
Shuang Dai ◽  
Yan Song
Keyword(s):  
South Africa ◽  
Co2 Emissions ◽  
Co2 Emission ◽  
Driving Forces ◽  
Dominant Role ◽  
Decomposition Analysis ◽  
Structure Effect ◽  
Energy Structure ◽  
Index Method ◽  
Intensity Effect

South Africa has become one of the most developing countries in the world, and its economic growth has occurred along with rising energy-related CO2 emission levels. A deeper understanding of the driving forces governing energy-related CO2 emissions is very important in formulating future policies. The LMDI (Log Mean Divisia Index) method is used to analyse the contribution of the factors which influence energy-related CO2 emissions in South Africa over the period 1993-2011. The main conclusions drawn from the present study may be summarized as follows: the energy intensity effect plays the dominant role in decreasing of CO2 emission, followed by fossil energy structure effect and renewable energy structure effect; the economic activity is a critical factor in the growth of energy-related CO2 emission in South Africa.

scholarly journals Reduction of CO2 Emissions Due to Energy Use in Crete-Greece

2016 ◽  
Vol 6 (1) ◽  
pp. 23 ◽  
Author(s):  
John Vourdoubas
Keyword(s):  
Carbon Dioxide ◽  
Energy Consumption ◽  
Co2 Emissions ◽  
Carbon Dioxide Emissions ◽  
Fossil Fuels ◽  
Energy Use ◽  
Heating Oil ◽  
Per Capita ◽  
Reduction Of Co2 ◽  
Negative Growth

Use of fossil fuels in modern societies results in CO2 emissions which, together with other greenhouse gases in the atmosphere, increase environmental degradation and climate changes. Carbon dioxide emissions in a society are strongly related with energy consumption and economic growth, being influenced also from energy intensity, population growth, crude oil and CO2 prices as well as the composition of energy mix and the percentage of renewable energies in it.The last years in Greece, the severe economic crisis has affected all sectors of the economy, has reduced the available income of the citizens and has changed the consumers’ behavior including the consumption of energy in all the activities. Analysis of the available data in the region of Crete over the period 2007-2013 has shown a significant decrease of energy consumption and CO2 emissions due to energy use by 25.90% compared with the reduction of national G.D.P. per capita over the same period by 25.45% indicating the coupling of those emissions with the negative growth of the economy. Carbon dioxide emissions per capita in Crete in 2013 are estimated at 4.96 tons. Main contributors of those emissions in the same year were electricity generation from fuel and heating oil by 64.85%, heating sector by 3.23% and transportation by 31.92%.

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