• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.1
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• pp.61-70
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• 2014

South Korea is under pressure to reduce $CO_2$ emissions because of expanding request for reducing $CO_2$ emissions. In many industry sectors, $CO_2$ emissions were analyzed to reduce $CO_2$ emissions. But little effort in researching agricultural sector has been undertaken because it is recognized as environmentally friendly industry. The object of this research is to estimate $CO_2$ emissions of crops and analysis on correlation between $CO_2$ emissions and production, acreage of crops. In this study, environmental input-output analysis was used to estimate $CO_2$ emissions of agricultural sector and spearman correlation coefficient was used to analysis on correlation between $CO_2$ emissions and statics like production and acreage. As a result, rice, barley, pulses and horticultural specialities had correlation with acreage and correlation coefficients of these crops were 0.800~0.933. Regression equations about $CO_2$ emissions and acreage of rice, barley, pulses and horticultural specialities was made and $R^2$ of these equations were 0.615~0.929. Using equations, $CO_2$ emissions of rice, barley, pulses and horticultural specialities can be estimated with acreage.

• Nuclear Engineering and Technology
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• v.54 no.4
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• pp.1312-1320
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• 2022

The earlier studies have analyzed theoretical links between nuclear energy and carbon dioxide (CO₂) emissions concerning territorial (or production-based) emissions. Here using the latest available dataset, this study explores the impacts of nuclear energy on production-based and consumption-based CO₂ emission in the era of globalization for the Organization for Economic Co-operation and Development (OECD) countries. The Driscoll-Kraay regression method reveals that nuclear energy is beneficial for the reduction of production-based CO₂ emissions. However, it is revealed that nuclear energy does not reduce consumption-based CO₂ emissions that are traded internationally and hence not comprised in conventional production-based emissions (territory) inventories. Globalization tends to reduce both production-based and demand-based carbon emissions. Finally, Environmental Kuznets Curve (EKC) is validated for both kinds of CO₂ emissions. The findings may deliver practical policy implications related to nuclear energy and CO₂ emissions for selected countries.

• Journal of Climate Change Research
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• v.8 no.4
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• pp.357-367
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• 2017

Electricity generation in Korea mainly depends on thermal power and nuclear power. Especially the coal power has led to the increase in $CO_2$ emissions. This paper intends to analyze the current status of $CO_2$ emissions from electricity generation in Korea during the period 1990~2016, and apply the logarithmic mean Divisia index (LMDI) technique to find the nature of the factors influencing the changes in $CO_2$ emissions. The main results as follows: first, $CO_2$ emission from electricity generation has increased by $165.9MtCO_2$ during the period of analysis. Coal products is the main fuel type for thermal power generation, which accounts about 73% $CO_2$ emissions from electricity generation. Secondly, the increase of real GDP is the most important contributor to increase $CO_2$ emissions from electricity generation. The carbon intensity and the electricity intensity also affected the increase in $CO_2$ emission, but the energy intensity effect and the dependency of thermal power effect play the dominant role in decreasing $CO_2$ emissions.

• Nuclear Engineering and Technology
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• v.56 no.7
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• pp.2480-2488
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• 2024

Pakistan is a developing country whose maximum amount of mixed energy is provided by electricity, oil, coal, and gas. The study objective is to analyze the six major social factors to describe the significance of nuclear energy and CO₂ emissions at the decisive point coming from income, trade, energy, and urbanization. This study has tried to analyze the impact of different factors (i.e., fossil energy, GDP per capita, overall population, urban population, and merchandise trade) on Pakistan's CO₂ emissions using the extended STRIPAT model from 1986 to 2021. Ridge regression has been applied to analyze the parameters due to the multicollinearity problem in the data. The results show that (i) all the factors show significant results on carbon emissions; (ii) population and energy factors are the huge contributors to raising CO₂ emissions by 0.15% and 0.16%; however, merchandise and GDP per capita are the least contributing factors by 0.12% and 0.13% due to import/export and income level in Pakistan, and (iii) nuclear energy and substitute overall show a prominent and growing impact on CO₂ emissions by 0.16% and 0.15% in Pakistan. Finally, empirical results have wider applications for energy-saving, energy substitution, capital investment, and CO₂ emissions mitigation policies in developing countries. Moreover, by investigating renewable energy technologies and renewable energy sources, insights are provided on future CO₂ emissions reduction.

• Journal of Korea Trade
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• v.26 no.8
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• pp.21-36
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• 2022

Purpose - Carbon emission standards are based on the "production-based carbon emissions" generated by the production of goods in the relevant country which were the existing measurement methods. However, can such carbon emissions measurement standards be established international? For example, some of the goods produced in developing countries are produced for the demand of developed countries. The method of measuring carbon emission based on the final demand of a certain country is called "consumption-based carbon emissions." This study compares productionand consumption-based CO₂ emissions according to economic growth in ninety-three countries categorized by income level. Design/methodology - Our empirical model considers the difference between production- and consumption-based CO₂ emissions according to economic growth. Also, our model investigated whether the EKC hypothesis in most of the previous studies that had been based on production-based emissions was also established in the consumption-based emission model. Considering the continuous characteristics of CO₂, we utilized the generalized method of moments (GMM), specifically a system GMM econometric technique because CO₂ in the previous period can affect CO₂ in the present period. Findings - Our main findings can be summarized as follows: The results show that for the consumption-based CO₂ emissions model, CO₂ continuously increases as economic growth increases in the upper-middle income countries. The inverted U-shaped result was found in the case of the production-based model. However, in the lower-income countries, an inverted-U shape in which CO₂ emissions decrease at some point as the economy grows in the production-based model does not appear. On the other hand, in the consumption-based model, an inverted U-shaped result was obtained when estimating with system-GMM. Additionally, the proportion of manufacturing, energy imports, and energy consumption had an effect on both the production- and the consumption-based model regardless of the group's CO₂ emissions. On the basis of such assessments, policymakers need to consider not only production- but also consumption-based options. Originality/value - Previous studies have mainly focused on production-based CO₂ emissions, with most of them revolving around economic growth or the effect of various social and economic factors on CO₂ emissions. However, this study considers the relationship with economic growth using consumption-based emissions as a dependent variable by classifying ninety-three countries by income level.

• Journal of Environmental Policy
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• v.12 no.3
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• pp.97-122
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• 2013

The ARDL(Autoregressive Distributed Lag) method is employed analyzes the long-run equilibrium relationships among environmental pollution($CO_2$ emissions) per capita, income levels per capita, and energy consumption per capita. The error correction model is employed to analyze the short-term effects of income and energy consumption on $CO_2$ emissions. The Toda-Yammamoto method is employed for causal analysis among the three variables. The results show that income levels, energy consumption, and $CO_2$ emissions are cointegrated. We found the N type relationship between income and $CO_2$ emissions. Long-term elasticities of income and energy consumption with respect to $CO_2$ emission were greater than their short-term elasticities. There were a bilateral causality between energy consumption and $CO_2$ emissions. There was a unilateral causality from $CO_2$ emissions to income and from energy consumption to income not vice versa. Energy consumption can be an important variable to contribute to forecasting $CO_2$ emissions.

• Environmental and Resource Economics Review
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• v.30 no.2
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• pp.299-323
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• 2021

This study investigated the impact of information and communication technology (ICT), trade openness, financial development, and economic growth on CO₂ emissions in Korea from 1990 to 2016. The cointegration relationship of the variables was confirmed by an autoregressive distributed lag (ARDL) bounds test. In the long-run, economic growth was statistically significant factor in the increase in CO₂ emissions, while other factors, as well as ICT, did not significant factors in the changes in CO₂ emissions. In the long-run, a link between economic growth and CO₂ emissions has been confirmed, but other factors, including ICT, have not been able to confirm the link between CO₂ emissions in the long-run. Meanwhile, in the short-run, economic growth and ICT increased CO₂ emissions, and financial development led to a decrease in CO₂ emissions. Trade openness did not have a significant effect on CO₂ emissions in the short-run as in the long-run. In particular, ICT did not contribute to the reduction of CO₂ emissions in the short-run as well as the long-run. In order to induce CO₂ mitigation through ICT, the development and deployment of technology that efficiently save energy by using ICT should be further promoted.

• Environmental Engineering Research
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• v.21 no.1
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• pp.74-83
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• 2016

The purpose of this study is to identify the driven factors affecting the changes in energy-related $CO_2$ emissions in Hebei Province of China from 1995 to 2013. This study confirmed that energy-related $CO_2$ emissions are correlated with the population, urbanization level, economic development degree, industry structure, foreign trade degree, technology level and energy proportion through an improved STIRPAT model. A reasonable and more reliable outcome of STIRPAT model can be obtained with the introducing of the Ridge Regression, which shows that population is the most important factor for $CO_2$ emissions in Hebei with the coefficient 2.4528. Rely on these discussions about affect abilities of each driven factors, we conclude several proposals to arrive targets for reductions in Hebei's energy-related $CO_2$ emissions. The method improved and relative policy advance improved pointing at empirical results also can be applied by other province to make study about driven factors of the growth of carbon emissions.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1017-1024
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• 2010

Under the Kyoto Protocol many countries have been requested to participate in emissions trading with the assigned $CO_2$ emissions. In this environment, it is inevitable to change the system and market operation in deregulated power systems, and then ensuring safety margin is becoming more important for balancing system security, economy and $CO_2$ emissions. Nowadays, available transfer capability (ATC) is a key index of the remaining capability of a transmission system for future transactions. This paper presents a novel approach to the ATC evaluation with $CO_2$ emissions using multi-objective particle swarm optimization (MOPSO) technique. This technique evolves a multi-objective version of PSO by proposing redefinition of global best and local best individuals in multi-objective optimization domain. The optimal power flow (OPF) method using MOPSO is suggested to solve multi-objective functions including fuel cost and $CO_2$ emissions simultaneously. To show its efficiency and effectiveness, the results of the proposed method is comprehensively realized by a comparison with the ATC which is not including $CO_2$ emissions for the IEEE 30-bus system, and is found to be quite promising.

• Environmental Engineering Research
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• v.21 no.1
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• pp.91-98
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• 2016

Along with China's increasing share in global total $CO_2$ emissions, there is a necessity for China to shoulder large emission-mitigating responsibility. The appropriate allocation of $CO_2$ emission quotas can build up a solid foundation for future emissions trading. In views of originality, an optimized approach to determine $CO_2$ emissions allocation efficiency based on the zero sum gains data envelopment analysis (ZSG-DEA) method is proposed. This paper uses a non-radial ZSG-DEA model to allocate $CO_2$ emissions between different Chinese provinces by 2020 and treats $CO_2$ as the undesirable output variable. Through the calculation of efficiency allocation amounts of provincial $CO_2$ emissions, all provinces are on the ZSG-DEA efficiency frontier. The allocation results indicate that the cumulative optimal amounts of $CO_2$ emissions in 2020 were higher than the actual amounts in 13 provinces, and lower in other 17 provinces, and show that different provinces have to shoulder different mitigation burdens in terms of emission reduction.