• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.5
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• pp.1981-1987
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• 2013

$CO_2$ emissions of vehicles vary with vehicle's speeds. In addition, the speeds vary with road type, location, time and traffic volume. In this paper, the section in which a large quantity of $CO_2$ emissions per vehicle is exhausted is determined and analyzed with principal component analysis(PCA). In results of analysis, the principal components analysis were divided into two principal components. It had been identified that the main component was the time zone one which is able to explain each components' role. The first principal component could explain the role of a major component on $CO_2$ emissions per vehicle in the early morning and afternoon hour, respectively. The second principal component could explain the role of the component on $CO_2$ emissions per vehicle in the morning and afternoon peak hours, respectively. Therefore, the section in which a large quantity of $CO_2$ emissions per vehicle could be deterimined by PCA scores.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.3
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• pp.289-294
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• 2020

The study of environmental pollution plays an important role in controlling emissions in the production activities of FDI enterprises as well as export goods. Vietnam is a country with a large proportion of FDI contribution and high export value. Therefore, there should be studies to assess the actual effects of FDI and the openness of the economy (trade) on the environment. Therefore, the authors conduct research on the role of FDI and trade on environmental quality in Vietnam. With data collected from 1990 to 2018 (from the period of Vietnam's economy opening up) through the ARDL (Autoregressive Distributed Lag) model, the results show that FDI has a positive impact on CO2 emissions in the short term but has no impact on the long-term (In this study, CO2 is considered to represent environmental quality). The trade has a positive impact on CO2 emissions in both the short term and long term. The results of the study show the actual shortcomings of FDI as well as production activities in the export enterprises in Vietnam. From the results of this research, the author also provides the causes and remedies to control of CO2 emissions from two activities of foreign direct investment and trade.

• New & Renewable Energy
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• v.6 no.3
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• pp.13-21
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• 2010

This paper analyzes the factors of renewable energy consumption in Korea, China and Japan. We consider renewable energy consumption per capita as dependent variable, GDP per capita, $CO_2$ emissions per capita and real oil prices as independent variables. To analyze this model, this paper uses three econometric methods such as OLS, fixed effect model and panel GLS, utilizing data from 1990 to 2006 in Korea, China and Japan. According to the results by OLS for each country, an increase in GDP per capita or $CO_2$ emissions per capita or oil prices leads to an increase in renewable energy consumption. According to the results by fixed effect model, an increase in GDP per capita or $CO_2$ emissions per capita leads to an increase in renewable energy consumption. And real oil prices do not have a significant impacts on this model. According to the results by panel GLS, an increase in real GDP per capita as a proxy of income leads to an increase renewable energy consumption. And both $CO_2$ emissions per capita and real oil prices do not correlated closely with renewable energy consumption. Thus oil is not substituted to renewable energy in Northeast asian countries.

• Environmental Engineering Research
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• v.23 no.1
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• pp.107-113
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• 2018

Air quality and pollution have recently become a major concern; vehicle emissions significantly pollute the air, especially in large and crowded cities. There are various factors that affect vehicle emissions; this research aims to find the most influential factors affecting $CO_2$ and $NO_x$ emissions using Adaptive Neural Fuzzy Inference System (ANFIS) as well as a systematic approach. The modified ANFIS (MANFIS) was developed to enhance modelling and Root Mean Square Error was used to evaluate the model performance. The results show that percentages of $CO_2$ from trucks represent the best input combination to model. While for $NO_x$ modelling, the best pair combination is the vehicle delay and percentage of heavy trucks. However, the final MANFIS structure involves two inputs, three membership functions and nine rules. For $CO_2$ modelling the triangular membership function is the best, while for $NO_x$ the membership function is two-sided Gaussian.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.79-80
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• 2023

After the Second Industrial Revolution, as global warming caused by environmental issues has intensified, the CO₂ emissions from the cement industry have become an urgent challenge. Therefore, this study aimed to reduce and utilize CO₂ emissions by using CO₂-reducing Calcium Silicate Cement.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.2
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• pp.37-43
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• 2014

Exhaust emissions were studied as a function of gasoline olefin composition in two vehicles-MPI and GDi engine equipped vehicles. Three different gasolines were tested which varied in olefin contents-12, 16 and 20 vol%. Exhaust emissions in two vehicles were affected by changes in gasoline olefin composition. Responses to changes in olefins were similar in both vehicles : reducing olefins lowered emissions of NOx and CO. Measured exhaust emissions included total hydrocarbons (THC), oxides of nitrogen (NOx), carbon monooxide(CO), carbon dioxide($CO_2$), formaldehyde, benzene, toluene, xylene, 1,3-butadiene and acetylene.

• 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 Korean Society of Transportation
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• v.32 no.4
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• pp.303-314
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• 2014

This study develops a $CO_2$ emissions estimation method, which considers different O/D travel patterns and through traffic volumes, in different regions for $CO_2$ emissions management in the field of transportation. In the research, O/D and network data provided by the Korea Transport Database (KTDB) Center are used as basic data. The results show that the total emission was similar to the Metropolitan's total emission which was estimated by KTDB (2009). With the analysis focusing on Gyeonggi-do, the results show that $CO_2$ emission from through traffic volumes was greater than $CO_2$ emissions of the Intra-Regional in southern regions; By contrast, $CO_2$ emissions of the Intra-Regional was greater than that from through traffic volumes in northern regions. Therefore, the $CO_2$ emissions management needs to be segregated into local government and nation with each travel pattern.

• Journal of Environmental Science International
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• v.16 no.3
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• pp.287-297
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• 2007

Increasing carbon dioxide emissions from fossil fuel use and land-use change has been perturbing the balanced global carbon cycle and changing the carbon distribution among the atmosphere, the terrestrial biosphere, the soil, and the ocean. SGCM(Simple Global Carbon Model) was used to simulate global carbon cycle for the IPCC emissions scenarios, which was six future carbon dioxide emissions from fossil fuel use and land-use change set by IPCC(Intergovernmental Panel on Climate Change). Atmospheric $CO_2$ concentrations for four scenarios were simulated to continuously increase to $600{\sim}1050ppm$ by the year 2100, while those for the other two scenarios to stabilize at $400{\sim}600ppm$. The characteristics of these two $CO_2$-stabilized scenarios are to suppress emissions below $12{\sim}13$ Gt C/yr by tile year 2050 and then to decrease emissions up to 5 Gt C/yr by the year 2100, which is lower than the current emissions of $6.3{\pm}0.4$ Gt C/yr. The amount of carbon in the atmosphere was simulated to continuously increase for four scenarios, while to increase by the year $2050{\sim}2070$ and then decrease by the year 2100 for the other two scenarios which were $CO_2$-stabilized scenarios. Even though the six emission scenarios showed different simulation results, overall patterns were such similar that the amount of carbon was in the terrestrial biosphere to decrease first several decades and then increase, while in the soil and the ocean to continuously increase. The ratio of carbon partitioning to tile atmosphere for the accumulated total emissions was higher for tile emission scenario having higher atmospheric $CO_2$, however that was decreasing as time elapsed. The terrestrial biosphere and the soil showed reverse pattern to the atmosphere.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.247-253
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• 2023

As climate change problem has recently become serious, studies are being conducted to identify carbon dioxide (CO₂) emission dynamics based on satellite data to reduce emissions. It is also very important to analyze spatial patterns by estimating and mapping CO₂ emissions dynamic. Therefore, in this study, CO₂ emissions in the Korean Peninsula from 2013 to 2020 were estimated and mapped. To spatially estimate and map emissions, we use the enhanced vegetation index adjusted nighttime light index, an index that combines nighttime light (NTL) and vegetation index, to map both areas where NTL is observed and areas where NTL is not observed. In order to spatially estimate and map CO₂ emissions, the total annual emissions of the Korean Peninsula were calculated, resulting in an increase of 11% from 2013 to 2017 and a decrease of 13% from 2017 to 2020. As a result of the mapping, it was confirmed that the spatial pattern of CO₂ emissions in the Korean Peninsula were concentrated in urban areas. After being divided into 17 regions, which included the downtown area, the metropolitan area accounted for roughly 40% of CO₂ emissions in the Korean Peninsula. The region that exhibited the most significant change from 2013 to 2020 was Sejong City, showing a 96% increase.