• Environmental and Resource Economics Review
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• v.23 no.3
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• pp.473-496
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• 2014

This paper intends to test the non-linear relationship between $CO_2$ emissions and income by employing cointegration model of the time-varying income elasticity. We select France, UK, Italy, Japan, US, China, India, Mexico and Korea and use non-parametric time series analysis on each country in order to estimate its own effect of income on $CO_2$ emission. The main results indicate that the $CO_2$ emission-income elasticities vary over time and the income elasticities of the Annex I countries tend to be higher in absolute terms than those of developing countries. In addition, we find that emission-income elasticities decrease for Annex I countries over time, whereas those for developing countries increase.

• Journal of Korean Society of Transportation
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• v.33 no.5
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• pp.449-460
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• 2015

The reliability of air quality evaluation results for green transportation could be improved by applying correct emission factors. Unlike previous studies, which estimated emission factors that focused on vehicles in laboratory experiments, this study investigates emission factors according to road types and time using real driving data. The real driving data was collected using a Portable Activity Monitoring System (PAMS) according to road types and time, which it compared and analyzed fuel consumption from collected data. The result of the study shows that fuel consumption on national highway is 17.33% higher than the fuel consumption on expressway. In addition, the average fuel consumption of peak time is 4.7% higher than that of non-peak time for 22.5km/h. The difference in fuel consumption for road types and time is verified using ANOCOVA and MANOVA. As a result, the hypothesis of this study - that fuel consumption differs according to road types and time, even if the travel speed is the same - has proved valid. It also suggests correction factor of emission factors by using the difference in fuel consumption. It is highly expected that this study can improve the reliability of emissions from mobile pollution sources.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.61-67
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• 2004

It is needed for one to design the better models estimating emission and then with the real time data, make the monitoring system simulating emission rate because of having built the basement of accepting real-time traffic information in ITS projects. The objective of the study is to develop the monitoring system visualizing air pollution to a certain place. It is based on the estimated emission from the patterns of individual vehicles and the changes of traffic flow. For constructing simulator, we loaded referring algorithm in actuality program and simulates the traffic flow movement in a microscopic viewpoint. The simulator is able to express not only the movement of each car but also to visualize processing the emission and diffusion of the air pollutant by computer program. Not only expresses the simulation process the angle of vision but it also cutting down environment expenses and improving the traffic impact assessment and the traffic impact assessment.

• Journal of the Economic Geographical Society of Korea
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• v.16 no.2
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• pp.149-166
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• 2013

The purpose of this study is to analyze the regional disparity and its determinants of $CO_2$ emission from the residential energy consumption in China. This study examines factors that affect the $CO_2$ emission per capita using the panel model. The panel model was set by a balanced panel data for 30 provinces and for the period of 2006~2011. $CO_2$ emission per capita is used as the dependent variable and characteristics of the household and regional physical environmental factors are selected as the explanatory variables. The important findings can be summarized as follows. $CO_2$ emission per capita is influenced by the ratio of the graduate students, household size, the ratio of the old-aged, female economic participation rate. High residential density is negatively affected on $CO_2$ emission. The findings suggest that the effect of policies reducing $CO_2$ emission per capita may vary by characteristics of the household, energy sources and regional climate. The results of this empirical study give some implications to reduce the residential energy consumption in the era of climate change.

• Proceedings of the KIEE Conference
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• 2007.11b
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• pp.214-216
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• 2007

Post 2012 기후변화협약 체제의 토래 및 강화되는 기후변화협약으로 인해 우리나라의 온실가스 의무감축이 확실하게 예견되고 있는 현 시점에서 우리나라의 온실가스 감축이행을 위한 대응책의 필요성이 증가하고 있다. 특히 발전부문은 우리나라의 온실가스 배출의 약 30%를 차지하고 있으며, 경제성장에 따라 온실가스 배출량이 빠른 속도로 증가하고 있으므로 Post 2012 기후변화협약 체제의 대응책이 보다 필요하다. 본 연구에서는 향후 발전부문에 온실가스 감축의무가 부담될 것을 고려하여 온실가스 배출량 제약 및 배출권거래제를 고려한 설비계획을 도출하고자 한다. 현재 우리나라의 전원 개발계획에서 사용되고 있는 전산모형(WASP, POWERSYM 등)은 온실가스 배출량 제약 및 배출권거래제를 고려하지 못하므로 MEFISET 모형을 이용하여 이를 고려하고자 한다. 그러나 MEFISET 모형은 설비예비력 제약조건을 통해 공급신뢰도를 만족하고 있다. 이러한 설비계획 결과는 공급신뢰도 기준 을 만족시키기 위해 과도한 설비계획 결과를 도출한다. 따라서 본 연구에서는 이를 보완하기 위해 Visual C를 통해 구현한 LOLP 프로그램을 통해 공급신뢰도 기준을 만족시키기 위한 적정 설비예비력을 추정하고자 한다.

• Spatial Information Research
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• v.6 no.1
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• pp.65-76
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• 1998

Air contaminant density must be inferred exactly to manage air pollution. Each land use of air pollution source is duplicated in the existing air contaminant distribution because the resolution of the land use map is low. The purpose of this study is to understand how the land use map is used to determine effectively in the distribution calculation of the emission volume and the inference of air contaminant density, as it is made in a high resolution. The major findings are as follows : In this study, as to making a high resolution($28.5m{\times}28.5m$) map of land use with GIS, each air pollution source is not duplicated spatially and land use can be reflected effectively. In Seoul, each air contaminant density was inferred (using a TCM-2 model) with the existing distribution map of emission volume, whose resolution is $1km{\times}1km$, and the new distribution map of emission volume, whose resolution is $28.5km{\times}28.5km$. According to the result, the inference value of the new distribution map was more similar to the actual value of an automatic survey network.

• Journal of Environmental Policy
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• v.9 no.4
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• pp.53-76
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• 2010

This paper attempts to estimate and compare environmental Kuznets curves (EKC) for$CO_2$ emissions of five regions constituting South Korea. For this, panel data of $CO_2$ emission for these regions are constucted for the period 1990 - 2007. Close inter-dependency among these five regions is considered by using a seemingly unrelated regression (SUR) model. In addition to real per-capita income, price index of energy sources and population dens ity are included as control variables. Results of estimates show the robust existence of EKC's in all these regions. EKC turning points of five regions range between 13.7 and 21.6 million Korean Won, showing a large variation. This difference among regions should be conisidered for the effective implementation of policies targeting the reduction of $CO_2$ emmission. In addition, the increase of energy price is found help reduce the $CO_2$ emmision while the rise of population density seems to lead to the increase of $CO_2$ emission.

• Journal of Korea Port Economic Association
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• v.31 no.4
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• pp.133-150
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• 2015

This study estimates greenhouse and noxious gas emissions caused by cargo-handling equipment at the Port of Incheon in 2013 by applying the NONROAD Model (U.S. EPA). The port emitted 838.4 tons of NOx and 82,747 tons of CO2. The estimates are 2.4 times higher for NOx and 1.3 times higher for CO2 than those of the Port of Los Angeles. Emissions from general cargo-handling equipment are five times more than those from container cargo-handling equipment. Among the three ports comprising the Port of Incheon, the emissions at the North Port, which handles raw materials for industry are relatively higher than those at the other ports. Compared to the study conducted by Chang et al. (2013, 2014), this study finds that CO2 and NOx emissions per cargo-handling equipment are 10 times higher than the corresponding amounts per ship.

• Environmental and Resource Economics Review
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• v.19 no.4
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• pp.875-896
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• 2010

Using the difference in differences (DID) estimation method, this paper analyzes the effect of European Union's Emission Trading Scheme (EU ETS) on the reduction of per capita $CO_2$ emission among the twenty five participating countries. For this, the panel dataset of forty two European countries for the period 1990~2007 is constructed. Special attention is paid to the bias of the standard errors in the DID estimation due to the presence of serial correlation in the error terms. The results shows quite a robust effect of EU ETS on the reduction of per capita $CO_2$ emission among the participating countries regardless of the calculation methods of standard errors. The results also shows that the increased implicit tax rate on energy has a robust effect on the reduction of per capita $CO_2$ emission. On the contrary, the estimation results regarding the effects of per capita GDP and population density on the per capita $CO_2$ emission seem inconsistent. In particular, the environmental Kuznets curve is not statistically supported with the use of robust standard errors.

• Journal of the Economic Geographical Society of Korea
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• v.24 no.4
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• pp.400-410
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• 2021

This study analyzed the determinants of carbon dioxide emissions through the expanded STIRPAT model using panel data from 16 metropolitan cities and provinces in Korea from 2000 to 2019. After testing cross-sectional dependence and coefficient heterogeneity of panel data, we performed analysis using MG, CCEMG, and AMG estimation methods reflected these characteristics. The results of analysis using the AMG estimation method are as follows. The coefficients of income, population, and energy intensity were statistically significant with a positive sign, but urbanization was statistically insignificant. Reduction of carbon dioxide emissions in Korea can be achieved through an increase in energy efficiency and sustainable economic growth. It is necessary to establish a policy that can contribute to sustainable economic growth by inducing productivity improvement through technology innovation reducing carbon dioxide emissions in the long-term as well as building a low-carbon society through active development of carbon dioxide reduction technology.