• Korean Journal of Remote Sensing
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• v.36 no.2_1
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• pp.121-137
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• 2020

Data from the Ozone Monitoring Instrument (OMI) satellite and national emission inventories were used in this study to analyze air quality in East Asia and estimate the impact of domestic and foreign emissions on South Korea's air quality, based on which future emissions were predicted. The concentration trends of nitrogen dioxide (NO₂) and sulfur dioxide (SO₂) in East Asia from 2005 to 2015 showed that both substances were highest in North East China (NEC), followed by South East China (SEC) and Seoul Metropolitan Area (SMA). The average SO₂ concentration was 1.63 times higher in NEC than in SMA. Analysis on the ratios of NO₂/SO₂ and NO_x/SO_x provides an indirect picture of the effect of transboundary air pollutants on atmospheric composition in Korea. The concentration ratio of NO₂/SO₂ in all study areas peaked in 2013 and SMA's emission ratio of NO_x/SO_x increased in 2015 by over 22% from 2013. Despite the reduction in domestic emissions, the concentration-to-emission ratios (NO₂/NO_x, SO₂/SO_x) rose gradually, which implies that other factors besides domestic emissions (e.g., foreign sources, lifetime, etc.) influence air quality in SMA. We estimated future emissions of NO_x and SO_x in SMA to be 296.2 and 39.0 ktons in 2025 and 284.4 and 33.8 ktons in 2035, respectively. Application of the inter-comparison techniques of this study to the data from the Geostationary Environment Monitoring Instrument (GEMS) is expected to provide concrete information which can be used to improve national emission inventories and figure out factors and sources that affect domestic air quality.

• Environmental and Resource Economics Review
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• v.29 no.1
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• pp.23-45
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• 2020

The rapid economic growth has brought tremendous pressure on the environment and caused severe air pollution in China. This study empirically examines causes of air pollution in China. Panel-corrected standard errors procedure (PCSE) was used to analyze major determinants of increasing or reducing emissions of sulfur dioxide (SO₂) and nitrogen oxides (NO_X) in 30 Chinese provinces. The estimation results show that SO₂ emission is mitigated as per capita regional GDP increases, but the relation between emission of NO_X and per capita regional GDP is found to have an inverse N-shaped curve, which implies that emission of NO_X is ultimately expected to decline with economic growth. As for increasing factors of air pollutants, electricity consumption is a significant common source of SO₂ and NO_X emissions. Moreover, the results show that increment of coal consumption significantly affects emission of SO₂ while increase of natural gas consumption reduce emission of SO₂. On the other side, investment in energy industry, and investment on treatment of waste gases are determinants of mitigating emissions of SO₂, but have no impact on NO_X. Consumption of diesel, truck ratio and number of vehicles increase emission of NO_X. Meanwhile, higher precipitation rate is a common determinant of mitigating emissions of SO₂ and NO_X. Policy implications are suggested in the conclusion.

• Journal of environmental and Sanitary engineering
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• v.10 no.3
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• pp.131-138
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• 1995

As the energy consumption increases continuously, the emission amount of air pollutants is growing, and after all it can influence the global environment as welt as the regional atmosphere. So, the clean energy which emits less air pollutants should be developed and widely used to reduce emission of pollutants. Electricity, known for clean energy in the side of consumption, is not actually clean in the process of generation. Electric power is generated using fossil fuels which produce acidic gases like $SO_{2}$, $NO_{x}$, etc. The emission rates of $SO_{2}$, $NO_{x}$, $CO_{2}$ are 2g,0.78g and 1 l0g per electric power generating Ikwh. If one light(60 watt bulb) be turned off at each house for a month electricity will be saved about 1.Skillion kwh a year. This is almost the same as 4,170 tons of $SO_{2}$ and $NO_{x}$. As a result the economization of electricity will be one of the effective strategy to reduce the air pollution and to keep our life clean and comfortable.

• Journal of Environmental Science International
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• v.20 no.5
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• pp.599-610
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• 2011

Emission of air pollutants such as nitrogen oxides ($NO_x$), hydrocarbons (HC), $SO_2$, and particulate matter (PM) and $CO_2$ from ship during 2009 in Busan port was estimated based on activity-based method. The significant fraction (> 50%) of ship emission resulted from container and general cargo ships. Emission at port operation mode was the most dominant compared to at sea and maneuvering modes. Emission at North port was the largest source of air pollutants among ports. The magnitudes of air pollutants $NO_x$, $SO_2$, HC, $CO_2$, and PM in Busan port were $8.7{\times}10^3$, $8.23{\times}10^3$, $0.35{\times}10^3$, $4.86{\times}10^6$, and $0.67{\times}10^3$ ton/yr, respectively. The ratio of $NO_x$ to VOC is about 25. Our ship emission estimate is 2 times higher than that in CAPSS emission inventory.

• Journal of Korean Society for Atmospheric Environment
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• v.25 no.5
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• pp.410-419
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• 2009

Generally, air pollutant emission at workplace is estimated by two methods: indirect methods using emission factors and direct methods based on CEMS (Continuous Emission Monitoring System). CAPSS (Clean Air Policy Support System) is a representative indirect method and the national air pollutant database of Korea. However, characteristics of some workplaces may create a gap between CAPSS and CEMS data. For improving of emission data accuracy, emission data of CEMS (named CleanSYS) equipped at 138 target workplaces were compared with those of CAPSS. As a result, $SO_x$ and $PM_{10}$ emission levels obtained by CAPSS were lower than those of CleanSYS. $SO_x$ and $PM_{10}$emission ratios were 61.5% and 71.2% lower respectively, showing the biggest gaps. On the other hand, $NO_x$ emission of CAPSS was higher by 10.4%. $SO_x$ showed the biggest difference in 'Energy industry combustion' and $NO_x$ did in 'Production Process' within the SCC category. $PM_{10}$ presented a large gap in 'Manufacturing industry combustion.' The differences in $SO_x$ between the two systems occurred because some large-size facilities lack pollution controllers or efficient pollution controllers. Based on this study, CAPSS emission database of Korea will improve accuracy through adopting CEMS emission system, which enables more efficient national atmospheric policies and workplace management.

• Particle and aerosol research
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• v.17 no.3
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• pp.55-69
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• 2021

Chungnam region accounts for the largest SO_X (22.8%) emission with the second-largest NO_X (10.8%) emission in Korea due to the integration of many large industrial sources including a steel mill, coal-fired power plants, and petrochemical complex. Air pollutants emitted by large industrial sources can cause harmful problems to humans and the environment. Thus, it is necessary to understand dispersion patterns of air pollutants from large industrial sources in Chungnam to characterize atmospheric contamination in Chungnam and the surrounding area. In this study, seasonal atmospheric dispersion characteristics for SO_X, NO_X, and PM2.5 from ten major point sources in Chungnam were evaluated using HYSPLIT 4 model, and their contributions to SO₂, NO₂ concentrations in the regions near the source areas were estimated. The predictions of the HYSPLIT 4 model show a seasonal different dispersion pattern, in which air pollutants were dispersed toward the southeast in winter while, northeast in summer. In summer, due to weaker wind speed, air pollutants concentrations were higher than in winter, and they were dispersed to the metropolitan area. The local emissions of air pollutants in Taean area had a greater influence on the ambient SO₂ and NO₂ concentrations at Taean, whereas SO_X and NO_X emissions from large sources located at Seosan showed relatevely little effect on the ambient ambient SO₂ and NO₂ concentrations at Seosan.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.4
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• pp.351-360
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• 2017

In this study, we developed emission factors from solid-fuel fired combustors. In order to increase the reliability of emission factors, we conducted a joint research with the Institute of Health and Environment. As a result, PM average concentration was $8.19mg/m^3$. $SO_2$ and $NO_x$ were respectively 8.46 ppm, 50.64 ppm. Hazardous air pollutants such as Cr, Pb and Hg were detected in trace amounts continuously for 2 years in some solid-fuel fired combustors. The emission factors for the three kinds of PM, $SO_x$, $NO_x$ were developed based on the measurement data. For the PM emission factors, that of SRF was 15.93 g/kg and that of Bio-SRF was 14.18 g/kg. Compared with those of US. EPA, emission factors of this study showed the results of low values. $SO_x$ emission factors were 4.42 g/kg for SRF and 1.39 g/kg for Bio-SRF. $NO_x$ emission factors were 13.21 g/kg and 4.43 g/kg, respectively. Through the results of this study, we would support atmospheric administration policies such as the emission factor notification revision.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.4
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• pp.543-550
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• 1998

From the power plant in a steel plant, environment pollutants such as $SO_x$, $NO_x$, CO and $CO_2$ are emitted by combustion reactions of the fuels which are by-product gases, oil and liquefied natural gas(LNG). To reduce the amounts of the pollutants, it is important to build a predictive model for the emission of the pollutants. In this paper, model that predict the amounts of generated pollutants for the used fuel is developed by using Gibbs free energy minimization method[1] with the temperature correction technique. For some data set, the calculation results from this model are compared with the real emission amounts of $SO_x$, $NO_x$, and the result of the calculation by both ASPEN PLUS which is a commercial simulation software. This model shows good results and can be applied to other power plants.

• Journal of the Korean Applied Science and Technology
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• v.31 no.1
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• pp.159-166
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• 2014

In recent years, researchers have put a considerable effort to decrease the emission of harmful gaseous pollutants to the atmosphere. In order to remove simultaneously $SO_2$ and $NO_X$ from the flue gas of small and medium-sized ship, we designed minimal wet scrubber inside a compact multistage modular system. In this study we proceed experiment of elemental technology at each stage of the scrubber. The each stage is oxidation of NO which is the main component of $NO_X$, and removal of $SO_2$, respectively. $NaClO_2$ was used to oxidize NO gas, and NaOH was used to remove $SO_2$ gas. The maximum NO conversion efficiency and the $SO_2$ removal efficiency are both indicate 100%.

• Journal of Environmental Science International
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• v.12 no.1
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• pp.23-34
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• 2003

Urban air quality is usually worse than that of rural counterpart. The contrasting atmospheric properties seem to be direct result of different urban-rural air pollutant emission. Hence, the emission estimation of air pollutants plays an important role to the atmospheric environmental management. The main purpose of this study is to find out the temporal and spatial distribution of air pollutant emission in Daegu area. For the study, the Daegu statistical yearbook and data of waste facilities and the report on traffic survey issued by Daegu metropolitan city and the statistical yearbook on the road capacity issued by the ministry of construction and transportation are used. Each item for the emission estimation is $SO_2$, CO, HC, $NO_x$, PM-10 from point, line and area source. The result were as follow; (1) The air pollutants with the highest amount of emission from the emission source is CO followed by $NO_x$, $SO_2$, PM-10, HC in descending order of magnitude. (2) The annually totaled air pollutant emission consists of 81%(73,185 ton/year) of line, 11%(9,589% ton/year) of area and 8%(7,445 ton/year) of point source in Daegu. Air polluant emission was mainly due to line sources. (3) High-emission of the air pollutants of line source appeared ariond Bukgu, Dalseonggun, Dongu and Seogu ; the areas with highway networks.