• Journal of Korean Society for Atmospheric Environment
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• v.28 no.4
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• pp.466-476
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• 2012

This study calculated monthly and sectoral (for industry, energy industry, transport, residential, commercial and public sectors) greenhouse gas (GHG) emissions of Seoul, Korea from 1999 until 2009 with following the IPCC 2006 Guideline for National Greenhouse Gas Inventories through an analysis on available monthly data of fossil fuel and electricity consumption for the period. The time series analysis showed that GHG emissions had significant cyclical pattern season by season with the highest peak in August and the lowest peak in January throughout the period. The analysis on monthly and sectoral energy consumption showed that residential, commercial and public sectors had emitted about 65% of total GHG emissions of Seoul and had consumed more energy in winter for heating. About 30% GHG of Seoul was emitted from transport sector but its monthly energy consumption showed irregular pattern and it consumed 80% petroleum (in 2009) of Seoul. Hopefully together with further study on this subject, it is expected that this study can be used as basic data for various research regarding Greenhouse gas baseline emission, energy consumption pattern and estimation for future GHG emission of Seoul.

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.5
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• pp.537-544
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• 2015

The effects of the modification of hybrid vehicle components on diesel exhaust emissions were investigated in this study. We examined the changes in exhaust emissions and the fuel consumption (FC) caused by the modification of generator (alternator) and motors. Exhaust emissions such as black carbon (BC), HC, $NO_X$ and $CO_2$ were measured not only in idle state but also on an actual urban road as well as on a chassis dynamometer. BC, $NO_X$ and HC emissions increased by 95%, 27% and 34% respectively when the generator charged the battery in the idle condition. BC and FC decreased in hybrid mode on the actual urban road partly because the motors were used to assist the diesel engine. In addition, the decreases in exhaust emissions and FC were also evident in the hybrid mode when the vehicle was tested on the chassis dynamometer.

• Korean System Dynamics Review
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• v.10 no.2
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• pp.53-79
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• 2009

The main purpose of this study is to find what steps are needed for a system for CO2 emissions trading to be formulated as government policy, using System Thinking approach. First, this paper analyzed Korean newspapers to consider the social issue regarding CO2 emissions trading. There were more articles related to international issues than domestic ones before 2008. This trend, however, became reversed from January 2008, which means that consideration of CO2 emissions trading has been discussed as a domestic social issue from 2008. Second, it analyzed speeches by former president Roh Moo-Hyun and current president Lee Myung-bak. In particularly, President Lee Myung-bak declared "Low Carbon and Green Growth" as a new growth engine and a Korea's vision of the future national development. Third, it examined which government agencies, including departments and committees, are pursuing policies regarding climate change, global warming, and CO2 emissions trading. Most policy has originated in the Ministry of Environment, although policy alternatives have been proposed in other agencies including the Ministry of Knowledge Economy. The study concludes that the political consideration has played a major role in the policy agenda-setting process of the CO2 emissions trading in Korea.

• Environmental Engineering Research
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• v.22 no.3
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• pp.302-311
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• 2017

Nowadays, with the burgeoning development of economy, $CO_2$ emissions increase rapidly in China. It has become a common concern to seek effective methods to forecast $CO_2$ emissions and put forward the targeted reduction measures. This paper proposes a novel hybrid model combined principal component analysis (PCA) with regularized extreme learning machine (RELM) to make $CO_2$ emissions prediction based on the data from 1978 to 2014 in China. First eleven variables are selected on the basis of Pearson coefficient test. Partial autocorrelation function (PACF) is utilized to determine the lag phases of historical $CO_2$ emissions so as to improve the rationality of input selection. Then PCA is employed to reduce the dimensionality of the influential factors. Finally RELM is applied to forecast $CO_2$ emissions. According to the modeling results, the proposed model outperforms a single RELM model, extreme learning machine (ELM), back propagation neural network (BPNN), GM(1,1) and Logistic model in terms of errors. Moreover, it can be clearly seen that ELM-based approaches save more computing time than BPNN. Therefore the developed model is a promising technique in terms of forecasting accuracy and computing efficiency for $CO_2$ emission prediction.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.2
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• pp.190-202
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• 2012

Emissions of air pollutants and greenhouse gases (GHGs) by aircraft at the Gimhae International Airport (GIA) were investigated using the Emissions and Dispersion Modeling System (EDMS) version 5.1.3. The number of Landing and Take-Off (LTO) at the GIA for aircraft B737 was dominant, accounting for more than 60% of the total LTOs. For air pollutant emissions, CO was the most dominant pollutant by aircraft, followed by $NO_x$, VOCs, $SO_x$, etc. The emissions of CO, $NO_x$, and VOCs in 2009 (and 2010) at the GIA were 974 (968), 447 (433), 118 (122) ton/yr, respectively. The emissions of GHGs such as $CO_2$, $CH_4$, and $N_2O$ in 2009 (and 2010) were 110,795 (111,114), -0.157 (-0.151), and 1,989 (1,998) ton/yr, respectively. The negative number in $CH_4$ emission represents the consumption of atmospheric $CH_4$ in the engine. In addition, the emissions of most air pollutants (except for $PM_{10}$) and GHGs were estimated to be high in Taxi-Out and Climb-Out modes.

• Journal of ILASS-Korea
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• v.14 no.1
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• pp.28-33
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• 2009

This paper presents the performance and emissions characteristics of a small spark-ignited 2-stroke gasoline and LPG engine. The engine used in this paper is a single cylinder, two-stroke, air-cooled SI engine for brush cutter. We measured the rpm, torque, fuel consumption and HC, CO, NOx emissions in associated with the dynamometer load at WOT. The results showed that as engine revolution speed decreased, the excess air ratio of gasoline engine kept going about 0.9 and that of LPG engine increased 0.83 to 1.05. Torque and power of gasoline engine was higher than LPG engine. In exhaust emissions, HC emissions of gasoline engine was lower than LPG engine. In low speed area, CO emissions of LPG engine was lower than gasoline engine. Both gasoline engine and LPG engine emitted little NOx emissions.

• Asian Journal of Business Environment
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• v.10 no.4
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• pp.21-27
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• 2020

Purpose: The present study examines the effects of tourism on carbon dioxide emissions for selected South Asian economies over the time from 1995 to 2016. Research design, data and methodology: The present study is an annual time series analysis of tourism and CO2 emissions. The data is taken from World Development Indicators, an official data bank of World Bank. The study sample covers four South Asian countries, namely Bangladesh, India, Pakistan, Sri Lanka and Nepal. The empirical analysis is conducted by employing Pedroni panel cointegration, Fully Modified OLS, and Dynamic OLS approaches of estimation. Results: Tourism significantly increases environmental degradation in selected South Asian economies. The empirical estimated results indicate, that 1 % increase in tourism related activities leads to 0.16 % increase in CO2 emissions. In addition energy consumption and GDP are also causing an upsurge in CO2 emissions in the selected panel of South Asian economies. As the empirical results indicate that 1% increase in GDP stimulates carbon dioxide emissions by 0.23%. Conclusion: In order to protect the environment, the study emphasizes that sustainable tourism practices need to be promoted in the selected South Asian countries. Policy implication and provided and discussed.

• Journal of Korea Multimedia Society
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• v.18 no.7
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• pp.886-894
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• 2015

In this paper, we conduct sensitivity analysis of parameters used for inverse modeling in order to estimate the PM₁₀ emissions from the 16 areas in East Asia accurately. Parameters used in sensitivity analysis are R, the observational error covariance matrix, and B, a priori (background) error covariance matrix. In previous studies, it was used with the predetermined parameter empirically. Such a method, however, has difficulties in estimating an accurate emissions. Therefore, an automatically determining method for the most suitable value of R and B with an error measurement criteria and posteriori emissions accuracy is required. We determined the parameters through a sensitivity analysis, and improved the accuracy of posteriori emissions estimation. Inverse modeling methods used in the emissions estimation are pseudo inverse, NNLS (Nonnegative Least Square), and BA(Bayesian Approach). Pseudo inverse has a small error, but has negative values of emissions. In order to resolve the problem, NNLS is used. It has a unrealistic emissions, too. The problems are resolved with BA(Bayesian Approach). We showed the effectiveness and the accuracy of three methods through case studies.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.6
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• pp.108-116
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• 2002

The diesel engine is one of the most effective transport options available in all sizes and covering a wide range of applications. But, many researchers developing the diesel engine are facing tough challenges in view of the increasingly lower emissions standards. Thus, this study will explore the possible fuel additive technology to further reduce the emissions from the IDI diesel engine. The purpose of this study is to investigate the effects of oxygenated fuels on the exhaust emissions and to attain a better trade-off relation between smoke and NOx in four cylinder diesel engine. Experiments were conducted with oxygenated fuels as an effective way to improve the combustion efficiency. Some of oxygenated fuel(Diglyme and DEE) were added to the conventional diesel fuel which had no an oxygen content. Also, EGR was adopted for reducing NOx without any strong adverse effects on other exhaust emissions. This study concluded that exhaust emissions in diesel engine could be reduced by adding the oxygenated fuels which had lower boiling point, and the combustion efficiency was also improved as the oxygen content in fuel increased.

• Environmental Engineering Research
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• v.22 no.2
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• pp.175-185
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• 2017

As the energy and environmental problems are increasingly severe, researches about carbon dioxide emissions has aroused widespread concern. The accurate prediction of carbon dioxide emissions is essential for carbon emissions controlling. In this paper, we analyze the relationship between carbon dioxide emissions and influencing factors in a comprehensive way through correlation analysis and regression analysis, achieving the effective screening of key factors from 16 preliminary selected factors including GDP, total population, total energy consumption, power generation, steel production coal consumption, private owned automobile quantity, etc. Then fruit fly algorithm is used to optimize the parameters of least squares support vector machine. And the optimized model is used for prediction, overcoming the blindness of parameter selection in least squares support vector machine and maximizing the training speed and global searching ability accordingly. The results show that the prediction accuracy of carbon dioxide emissions is improved effectively. Besides, we conclude economic and environmental policy implications on the basis of analysis and calculation.