• Journal of Climate Change Research
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• v.8 no.2
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• pp.145-151
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• 2017

Korea's energy consumption has been constantly increasing. Final energy consumption was increased by anannual average of 2.9% compared to 2010. The consumption of all energy sources except for its oil was increased during the same time. While electric demand has increased coal consumption increased rapidly. Therefore, calorfic value and carbon emission factor development can improve the quality of Korea's greenhouse gas inventory. Calorific value is the amount of heat generated while burning coal. Caloric value is one of the most important factors in the development of carbon emission factors. Calorific value is used as the basis for the analysis of the various energy statistics. This study has calculated the sub-bituminous coal's calorfic value by the data received from domestic coal-fired power plants. Calorofic value's trend analysis period is the year of 2011~2015. Through analyzing the carbon content it was calculated the carbon emission factor. The sub-bituminous coal's uncertainty analysis was performed using a Monte Carlo simulation.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.3
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• pp.269-277
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• 2019

Since 2020, according to the International Convention for the Prevention of Pollution from Ships (MARPOL) amended in 2016, each Administration shall transfer the annual fuel consumption of its registered ships of 5,000 gross tonnage and above to the International Maritime Organization (IMO) after verifying them. The Administration needs stacks of materials, which must not be manipulated by ship companies, including the Engine log book and also bears an administrative burden to verify them by May every year. This study considers using the Automatic Identification System (AIS), mandatory navigational equipment, as an objective and efficient tool among several verification methods. Calculating fuel consumption using a ship's speed in AIS information based on the theory of a relationship between ship speed and fuel consumption was reported in several examples of relevant literature. After pre-filtering by excluding AIS records which had speed errors from the raw data of five domestic cargo vessels, fuel consumptions calculated using Excel software were compared to actual bunker consumptions presented by ship companies. The former consumptions ranged from 96 to 123 percent of the actual bunker consumptions. The difference between two consumptions could be narrowed to within 20 percent if the fuel consumptions for boilers were deducted from the actual bunker consumption. Although further study should be carried out for more accurate calculation methods depending on the burning efficiency of the engine, the propulsion efficiency of the ship, displacement and sea conditions, this method of calculating annual fuel consumption according to the difference between two consumptions is considered to be one of the most useful tools to verify bunker consumption.

• Asian Journal of Atmospheric Environment
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• v.8 no.3
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• pp.126-139
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• 2014

In order to estimate the influence of sources on $PM_{2.5}$ in the industrial area of Japan, we carried out a source analysis using chemical component data of $PM_{2.5}$. $PM_{2.5}$ samples were collected intermittently at an industrial area in Japan from July 2010 to November 2012. Water soluble ions ($Cl^-$, $NO_3{^-}$, $SO{_4}^{2-}$, $Na^+$,$NH_4{^+}$, $K^+$, $Mg^{2+}$, $Ca^{2+}$), elements (Al, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, As, Cd, Sb, Pb), and carbonaceous species (OC, EC) of the $PM_{2.5}$ (a total of 198 samples) were analyzed. Positive Matrix Factorization (PMF) model was applied to the data of those chemical components to identify the source of $PM_{2.5}$. At this observation site, nine factors were extracted. The major contributors of $PM_{2.5}$ were secondary sulfate 1, in which loading factors of $SO{_4}^{2-}$ and $NH_4{^+}$ were large (percentage source contribution: 20.9%), traffic, in which loading factors of OC (organic carbon) and EC (elemental carbon) were large (20.8%), secondary sulfate 2, in which loading factors of K and $SO{_4}^{2-}$ were large (8.0%), steel mills (7.8%), secondary chloride and nitrate (7.0%), soil (5.0%), heavy oil combustion (3.8%), sea salt (3.8%), and coal combustion (2.3%). The conditional probability function (CPF) and the potential source contribution function (PSCF) were carried out to examine the influence of a regional source and a broad-based source, respectively. CPF results supported local source influences such as steel mills, sea salt, traffic, coal combustion, and heavy oil combustion. PSCF results suggested that ships in the East China Sea, an industrial area of the east coastal region of China, and an active volcano in the Kyushu region of Japan were potential regional sources of secondary sulfate 1. Secondary sulfate 2 was affected by the burning of biomass fields and by coal combustion in Chinese urban areas such as Beijing, Hebei, and western Inner Mongolia. Source characterization using continuous data from one site showed a potential source representing fossil fuel combustion is affected both by regional and broad-based sources.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.5
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• pp.538-555
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• 2012

The purpose of this study was to understand $PM_{2.5}$ chemical characteristics on the Suwon/Yongin area and further to quantitatively estimate $PM_{2.5}$ source contributions. The $PM_{2.5}$ sampling was carried out by a high-volume air sampler at the Kyung Hee University-Global Campus from November, 2010 to October, 2011. The 40 chemical species were then analyzed by using ICP-AES(Ag, Ba, Cr, Cu, Fe, Mn, Ni, Pb, Si, Ti, V and Zn), IC ($Na^+$, $K^+$, $NH_4{^+}$, $Mg^{2+}$, $Ca^{2+}$, $NO_3{^-}$, ${SO_4}^{2-}$ and $Cl^-$), DRI/OGC (OC1, OC2, OC3, OC4, OP, EC1, EC2 and EC3) and GC-FID (acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, benzo[a]anthracene, benzo[b]fluoranthene, benzo[a] pyrene, indeno[1,2,3-cd] pyrene, benzo[g,h,i]perylene and dibenzo[a,h,]anthracene). When applying PMF model after performing proper data treatment, a total of 10 sources was identified and their contributions were quantitatively estimated. The average contribution to $PM_{2.5}$ emitted from each source was determined as follows; 26.3% from secondary aerosol source, 15.5% from soil and road dust emission, 15.3% from vehicle emission, 15.3% from illegal biomass burning, 12.2% from incineration, 7.2% from oil combustion source, 4.9% from industrial related source, and finally 3.2% from coal combustion source. In this study we used the ratios of PAHs concentration as markers to double check whether the sources were reasonably classified or not. Finally we provided basic information on the major $PM_{2.5}$ sources in order to improve the air quality in the study area.

• Journal of Korean Society for Atmospheric Environment
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• v.20 no.4
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• pp.555-569
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• 2004

Size -segregated measurements of aerosol composition using 8-stage DRUM impactor are used to determine the transport of natural and anthropogenic aerosols at Gosan site from 29 March to 30 May in 2002. Separation of ambient aerosols by DRUM impactor offers many Advantages over other standard filtration techniques. Some of the most important advantages are the ability to segregate into details by particle tire, to better preserve chemical integrity since the air stream doesn＇t pars through the deposit, to collect samples as a function of time, and to have a wide variety of impaction surfaces available to match analytical needs. Although the transport of Yellow sand is a well-known phenomenon in springtime, the result of measurement shows that not only soil dust but also anthropogenic aerosols, including sulfur, enriched trace metals such as Pb, Ni, Zn. Cu, Cr, As, Se, Br, are transported to Gosan in springtime. This study combines the size- and time-resolved aerosol composition measurements with isentropic, backward air-mass trajectories in order to identify some potential source regions of anthropogenic aerosols. As a result, during the NYS period, the average concentration of PM$_{10}$ was 46$\mu\textrm{g}$/㎥, Si, Al. S, Fe, Cl, K, Ca were higher than 1,000 ng/㎥ and Ti was about 100 ng/㎥. The concentrations of Zn, Mn, Cu. Pb, Br, Rb, V, Cr, Ni. At, Se ranged between 1 and 70 ng/㎥. More than 50% typical soil elements, tuck as Al, Si, Fe, Cd. Ti, Cr, Cu, Br. were distributed in a coarse particle range(5.0-12${\mu}{\textrm}{m}$). In other hand, anthropogenic pollutants, luck as S, N, Vi, were mainly distributed in a fine particle range (0.09-0.56${\mu}{\textrm}{m}$). During the YS period, PM$_{10}$ increased about 8 times than NYS period, and main soil elements, such as Al, Si, S, K, V, Mn, Fe also doubled in coarse particle range (1.15-12${\mu}{\textrm}{m}$). But Zn, As, Pb, Cu and Se, which distributed in the time aerosols (0.09-0.56${\mu}{\textrm}{m}$), were on the same level with or decreased than NYS period. Finally. except the YS Period, coarse particles (2.5-12${\mu}{\textrm}{m}$) are inferred to be influenced by soil, coal combustion, waste incineration, ferrous and nonferrous sources through similar pathways with Yellow Sand. But fine particles have different sources, such as coal combustion, gasoline vehicle, biomass burning, oil or coal combustion, nonferrous and ferrous metal sources, which are transported from China, Korea peninsula and local sources.ces.

• Journal of Korean Society for Atmospheric Environment
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• v.25 no.4
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• pp.275-288
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• 2009

The Korean government strengthened the environmental polices to manage and enhance Metropolitan Area air quality, and also has enforced "Special Act on Seoul Metropolitan Air Quality Improvement (SASMAQI)" issued in Dec. 2004. Recently government expanded the Seoul Metropolitan Air Quality Management District (SMAQMD) to the outskirts satellite cities of Seoul area through the "Revised Law Draft of SASMAQI". The SMAQMD has been alloted the allowable emission loads to the local governments on the basis of the carrying $PM_{10}$ capacity. However, in order to establish the effective air quality control strategy for $PM_{10}$, it is necessary to understand the corresponding sources which have a potential to directly impact ambient $PM_{10}$ concentration. To deal with the situations, many receptor methodologies have been developed to identify the origins of pollutants and to determine the contributions of sources of interests. The objective of this study was to extensively identify $PM_{10}$ sources and to estimate their contributions at the metropolitan area. $PM_{10}$ samples were simultaneously collected at the 3 semi-industrialized local cities in the Seoul metropolitan area such as Hwasung-si, Paju-si, and Icheon-si sites from April 15 to May 31, 2007. The samples collected on the teflon membrane filter by one $PM_{10}$ cyclone sampler were analyzed for trace metals and soluble ions and samples on the quartz fiber filter by another sampler were analyzed for OC and EC. Source apportionment study was then performed by using a positive matrix factorization (PMF) receptor model. A total of 6 sources were identified and their contributions were estimated in each monitoring site. Contribution results on Hwasung, Paju, and Icheon sites were as follows: 33%, 27%, and 27% from soil source, 26%, 26%, and 21% from secondary aerosol source, 11%, 11%, and 12% from biomass burning, 12%, 6%, and 5% from sea salt, 7%, 15%, and 19% from industrial related source, and finally 11%, 15%, and 16% from mobile and oil complex source, respectively. This study provides information on the major sources affecting air quality in the receptor sites and thus it will help to manage the ambient air quality in the metropolitan area by establishing reasonable control strategies, especially for the anthropogenic emission sources.

• Journal of the Korean Applied Science and Technology
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• v.35 no.3
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• pp.667-675
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• 2018

Increasing emissions regulations and demand of high-efficiency cars that travels a lot of distance with less fuel, there is growing interest in Energy Consumption Efficiency. Korean energy consumption efficiency compute combined Fuel Economy by driven city & highway driving mode and present final Energy Consumption Efficiency as using 5-cycle correction formula. Energy consumption efficiency is computed Carbon-balance-method, when used burning fuel play a key role in vehicle performance & Energy Consumption Efficiency. In Korea, vehicle fuel is circulate by Petroleum and Petroleum Alternative Business Act, there is property difference in quality standard because petroleum sector's refine method or type of crude oil. It does not appear a big difference according to fuel, because it sets steady quality standard, it may affect the performance of automobile. Thus, in research We purchase a few diesel fuel which circulated in the market in summer season though directly-managed-gas station by petroleum sector, resolve property each of fuel, we compute Fuel Economy each of them. We analyze into change depend on applying for property as nowadays utilizing Energy Consumption Efficiency calculating formula of gasoline and diesel fuel. As result, Density each of sample fuel has a maximum difference roughly 0.9%, net heat value each of sample fuel has difference 1.6%, result of current Energy Consumption Efficiency each of sample fuel has a difference roughly 1% at city drive mode, 1.4% at highway drive mode. Result of use gasoline calculator formula shows less 6% result than nowadays utilizing Energy Consumption Efficiency calculating formula, each of sample's Energy Consumption Efficiency shows maximum roughly 1.4% result in city & highway drive mode.