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 The Driving Factors of Carbon Emissions in China’s Transportation Sector: A Spatial Analysis

2021 ◽  
Vol 9 ◽  
Author(s):  
Xingbo Xu ◽  
Haicheng Xu
Keyword(s):  
Industrial Structure ◽  
Driving Factors ◽  
Direct Effects ◽  
Urbanization Level ◽  
Per Capita Gdp ◽  
Activity Intensity ◽  
Transportation Sector ◽  
Technological Level ◽  
Per Capita ◽  
Transportation Activity

Studies on the CO2 emissions from the transportation sector in China are increasing, but their findings are inconclusive. The main reason is that the spatial correlation of CO2 emissions from the regional transportation sector has been ignored in examinations of the driving factors of CO2 emissions from this sector. In this paper, new emission factors are adopted to calculate the CO2 emission levels from the transportation sector in Chinese provinces. By fully considering the spatial correlation of regional CO2 emissions and based on a two-way Durbin model incorporating both spatial and temporal fixed effects, the driving factors of CO2 emissions from the transportation sector in China are studied. The CO2 and spatial regression results for the transportation sector in China suggest the following: 1) Most of the regions with the highest CO2 emissions from the Chinese transportation sector are located on the east coast; they have gradually expanded over time to include the central and western regions. 2) The CO2 emissions from the transportation sector are higher in South China than in North China, and the regions with higher CO2 emissions have gradually shifted from north to south. 3) Transportation activity intensity, urbanization level, technological level, industrial structure and per capita GDP greatly impact CO2 emissions from the transportation sector in each province of China. Among these factors, transportation activity intensity, urbanization level, and per capita GDP exert not only direct effects but also indirect effects, whereas technological level and industrial structure exert only direct effects.

scholarly journals Study on Influencing Factors of Carbon Emissions from Energy Consumption of Shandong Province of China from 1995 to 2012

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Jiekun Song ◽  
Qing Song ◽  
Dong Zhang ◽  
Youyou Lu ◽  
Long Luan
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Industrial Structure ◽  
Shandong Province ◽  
Stirpat Model ◽  
Per Capita Gdp ◽  
Consumption Structure ◽  
Per Capita ◽  
The Impact ◽  
Consumption Intensity

Carbon emissions from energy consumption of Shandong province from 1995 to 2012 are calculated. Three zero-residual decomposition models (LMDI, MRCI and Shapley value models) are introduced for decomposing carbon emissions. Based on the results, Kendall coordination coefficient method is employed for testing their compatibility, and an optimal weighted combination decomposition model is constructed for improving the objectivity of decomposition. STIRPAT model is applied to evaluate the impact of each factor on carbon emissions. The results show that, using 1995 as the base year, the cumulative effects of population, per capita GDP, energy consumption intensity, and energy consumption structure of Shandong province in 2012 are positive, while the cumulative effect of industrial structure is negative. Per capita GDP is the largest driver of the increasing carbon emissions and has a great impact on carbon emissions; energy consumption intensity is a weak driver and has certain impact on carbon emissions; population plays a weak driving role, but it has the most significant impact on carbon emissions; energy consumption structure is a weak driver of the increasing carbon emissions and has a weak impact on carbon emissions; industrial structure has played a weak inhibitory role, and its impact on carbon emissions is great.

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.

Study on the Relationship between the Economics and Environment of Puyang City Based on Environmental Kuznets Curve

2013 ◽  
Vol 807-809 ◽  
pp. 773-782
Author(s):  
Qing Song Li ◽  
Kai Kang ◽  
Jia Wei Zhu ◽  
Qing Xiang Meng ◽  
Su Jun Deng
Keyword(s):  
Environmental Kuznets Curve ◽  
Industrial Structure ◽  
Kuznets Curve ◽  
Environmental Index ◽  
Per Capita Gdp ◽  
Sulfur Dioxide Emissions ◽  
Per Capita ◽  
Spss Software ◽  
Set Up ◽  
The Relationship

The study set up the model of per capita GDP and the environmental index based on the Environmental Kuznets Curve (EKC) with the support of SPSS software and the 2003-2011 economics and environment data of Puyang City. And the result shows that the environmental Kuznets Curve (EKC) of industrial wastewater discharge and industrial sulfur dioxide emissions both display inverted U-shape; and just across the turning point, the discharge present downward trend with the increasing of per capita GDP; while the EKC of industrial fumes emissions display positive U-shape, and its emission present upward trend first and then downward with the increasing of per capita GDP. It shows that the environmental problems of Puyang City has partly improved, but has not been fully restrained. The main reasons are unreasonable industrial structure, single dominated industy and relatively low investment on environmental improvement.

Exploration of the Development of Schemes to Achieve a District-Aggregate Energy-Intensity Goal - Taking the 12th Five-Year Period Energy Intensity Goal of Daxing District, Beijing as a Study Case

2014 ◽  
Vol 962-965 ◽  
pp. 1455-1460
Author(s):  
Xiang Qian Li ◽  
Li Juan Yang ◽  
Ling Ling Chen
Keyword(s):  
Energy Consumption ◽  
Gross Domestic Product ◽  
Energy Intensity ◽  
Industrial Structure ◽  
Energy Losses ◽  
Residential Energy ◽  
Initial Value ◽  
Study Case ◽  
Per Capita

The paper explored how to develop schemes to achieve a district’s energy consumption per gross domestic product (ECPGDP) target. It first analysed the available measures regarding the reduction of ECPGDP. These measures include optimising the industrial structure, reducing the energy intensity of different industries, reducing the per capita residential energy consumption, and reducing the energy losses. Next, the procedure and methods of developing schemes to achieve the target ECPGDP were proposed. The procedure contains five steps: determine the target ECPGDP, predicting the initial value of the ECPGDP, analysing the availability of different measures of reducing the ECPGDP, forming the schemes of achieving the target, and summarising the proposed schemes. Finally, the paper considered the 12th Five-Year period ECPGDP target of Daxing District, Beijing as a study case. In the case study, four quantitative schemes to achieve the target ECPGDP were considered.

scholarly journals Economic Activity and Pollution:The case of Indonesia 1967-2013

2017 ◽  
Vol 18 (2) ◽  
pp. 239 ◽  
Author(s):  
Mohammad Rofiuddin ◽  
Tito Aditya Perdana ◽  
Nugroho SBM
Keyword(s):  
Linear Regression ◽  
Environmental Pollution ◽  
Co2 Emissions ◽  
Significant Influence ◽  
Economic Activity ◽  
Quadratic Equation ◽  
Gdp Per Capita ◽  
Per Capita Gdp ◽  
Curve Method ◽  
Per Capita

Increased economic activity accompanied with environmental pollution. The objective of the study was to analyze the effect of per capita GDP on CO2 emissions and to prove the hypothesis of the Kuznets environment curve. Method for analyzing data by using multiple linear regression with quadratic equation. The results show that GDP per capita has a positive and significant influence on CO2 emissions, as well as the square GDP per capita has a negative and significant influence on CO2 emissions, so the Kuznets Environment Curve's hypothesis can be proven.

scholarly journals ENVIRONMENTAL KUZNETS CURVE HYPOTHESIS IN SELECTED EU COUNTRIES: KYOTO EFFECT

2019 ◽  
Vol 2 (2) ◽  
pp. 134-139
Author(s):  
​Cuma Bozkurt ◽  
İlyas Okumuş
Keyword(s):  
Energy Consumption ◽  
Environmental Pollution ◽  
Co2 Emissions ◽  
Trade Openness ◽  
Gdp Growth ◽  
Ekc Hypothesis ◽  
Eu Countries ◽  
Dummy Variable ◽  
Real Gdp ◽  
Per Capita

The purposes of this study is to investigate the relationship between per capita CO2 emissions, per capita energy consumption, per capita real GDP, the squares of per capita real GDP, trade openness and Kyoto dummies in selected 20 EU countries over the periods from 1991 to 2013 in order to analyze the connection between environmental pollution and Kyoto Protocol using Environmental Kuznets Curve (EKC) framework. According to EKC hypothesis, there is an inverted-U shape relation between environmental pollution and economic growth. Generally, the relationship between environmental pollution, per capita GDP and energy consumption has been analyzed for testing EKC hypothesis. In this study, it is used dummy variable to analyze the effects of Kyoto protocol on environmental degradation in the context of EKC hypothesis model. The dummy variable indicates Kyoto Protocol agreement year 2005. The results show that there is long run cointegration relationship between CO2, energy consumption, GDP growth, and the squares of GDP growth, trade openness and Kyoto dummy variable. Energy consumption and GDP growth increase the level of CO2 emissions. On the contrary, Kyoto dummy variable de­creases CO2 emissions in EU countries. In addition, the results reveal that the squares of per capita real GDP and trade openness rate are statistically insignificant. As a result of analysis, the inverted-U shape EKC hypothesis is invalid in these EU countries over the periods from 1991 to 2013.

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%.

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 Financial Market Development and Pollution Nexus in Saudi Arabia: Asymmetrical Analysis

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3462 ◽  
Author(s):  
Haider Mahmood ◽  
Abdullatif Alrasheed ◽  
Maham Furqan
Keyword(s):  
Saudi Arabia ◽  
Energy Consumption ◽  
Co2 Emissions ◽  
Financial Market ◽  
Market Development ◽  
Kuznets Curve ◽  
Long Run ◽  
Short Run ◽  
Per Capita ◽  
Financial Market Development

The study is aimed to scrutinize the presence of Environmental Kuznets Curve (EKC) hypothesis in Saudi Arabia by analyzing a period of 1971–2014. Asymmetrical impacts of Financial Market Development (FMD) and energy consumption per capita have also been tested on CO2 emissions per capita. The estimates buoyed the long and short-run relationships in the hypothesized model, and EKC is found to be true in terms of the relationship between income and pollution. Asymmetrical effects of FMD in the long run and asymmetrical effects of energy consumption per capita in the long and short run are presented on the CO2 emissions per capita. A decreasing FMD is found responsible for environmental degradation, and decreasing energy consumption per capita is found helpful in controlling CO2 emissions. The tested effect of the financial crisis is found insignificant on CO2 emissions.

Sign in / Sign up

Export Citation Format

Share Document