• 한국환경과학회지
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• 제31권12호
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• pp.999-1012
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• 2022

To investigate the reason for the spatial difference in PM_2.5 (Particulate Matter, < 2.5 ㎛) concentration despite a similar synoptic pattern, a synoptic analysis was performed. The data used for this study were the daily average PM_2.5 concentration and meteorological data observed from 2016 to 2020 in Busan and Seoul metropolitan areas. Synoptic pressure patterns associated with high PM_2.5 concentration episodes (greater than 35 ㎍/m³) were analyzed using K-means cluster analysis, based on the 900 hPa geopotential height of NCEP (National Centers for Environmental Prediction) FNL (Final analysis) data. The analysis identified three sub-groups related to high concentrations occurring only in Busan and Seoul metropolitan areas. Although the synoptic patterns of high PM_2.5 concentration episodes that occur independently in Busan and Seoul metropolitan areas were similar, there was a difference in the intensity of pressure gradient and its direction, which tends to be an important factor determining the movement time of pollutants. The spatial difference in PM_2.5 concentration in the Korean Peninsula is due to the difference and direction of the atmospheric pressure gradient that develops from southwest to northeast direction.

• 대한원격탐사학회지
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• 제31권4호
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• pp.347-351
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• 2015

Sea ice is a key parameter for understanding the climate change in cryosphere. In this study, we investigated the correlation with the factors that influenced change of the sea ice extent. We used the Sea Ice Concentration (SIC) from Ocean and Sea Ice Satellite Application Facility (OSI-SAF), and surface albedo provided by The Satellite Application Facility on Climate Monitoring (CM SAF). We converted the same temporal and spatial resolution of the data and detected the sea ice using SIC data. We performed the relationship analysis between SIC and sea ice albedo. As a result, we found they have a strong positive correlation. We performed the linear regression between SIC and sea ice albedo, and found they have high-level coefficient of determination. It shows using either SIC or sea ice albedo is possible to estimate the sea ice products.

• The Journal of Asian Finance, Economics and Business
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• 제4권2호
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• pp.37-44
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• 2017

This research is devoted to the development of methods general and standard methodological approaches and approbation those for the evaluation of economic potential and level of concentration of the regions of Kazakhstan. This paper presents the results of development of the authors on the selection and justification of the methodological approaches for quantitative evaluation of the economic potential (the degree of territorial differentiation of the profile) and concentration of regions. In this study, we used scientific methods: method of analysis the main trends of economic development, and method of evaluation of concentration of the region. Based on the analysis of foreign techniques developed and tested methodical approaches to the assessment of the economic potential (index and coefficient methods). Proposed methodological approaches to the assessment profile of the territory and developed a system of indicators, which includes an aggregated index of spatial concentration, which accurately reflects the concentration of production in the region. This study shows the results of the analysis of the potential regional disparities and trends of economic development of Kazakhstan. By using, the proposed methodology shows the possibility of their use; we calculated the indicators of integrated assessment of the economic potential and indicators of spatial concentration.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• 제4권1호
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• pp.11-23
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• 2000

Photochemical air quality models are essential tools in predicting future air quality and assessing air pollution control strategies. To evaluate air quality using a photochemical air quality model, emission inventories are important inputs to these models. Since most emission inventories are provided at a county-level, these emission inventories need to be geographically allocated to the computational grid cells of the model prior to running the model. The conventional method for the spatial allocation of these emissions uses "spatial surrogate indicators", such as population for mobile source emissions and county area for biogenic source emissions. In order to examine the applicability of such approximations, more detailed spatial surrogate indicators were developed using Geographic Information System(GIS) tools to improve the spatial allocation of mobile and boigenic source emissions, The proposed spatial surrogate indicators appear to be more appropriate than conventional spatial surrogate indicators in allocating mobile and biogenic source emissions. However, they did not provide a substantial improvement in predicting ground-level ozone(O3) concentrations. As for the carbon monoxide(CO) concentration predictions, certain differences between the conventional and new spatial allocation methods were found, yet a detailed model performance evaluation was prevented due to a lack of sufficient observed data. The use of the developed spatial surrogate indicators led to higher O3 and CO concentration estimates in the biogenic source emission allocation than in the mobile source emission allocation.llocation.

• 한국환경과학회지
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• 제13권1호
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• pp.27-36
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• 2004

Present study analyzed the temporal and spatial characteristics of PM10 pollution in Metropolitan Daegu area based on air pollution monitoring station data and measurements of PM10 concentrations in background area in order to provide essential data for efficient PM10 pollution management. The significant variation of spatial and temporal PM10 concentrations in Daegu area was observed during the study years. The highest maximum PM10 concentration(332 $\mu\textrm{g}$/㎥), average concentration(88 $\mu\textrm{g}$/㎥) and frequency exceeding PM10 daily standard(150 $\mu\textrm{g}$/㎥) were all observed in Namsandong located near a major roadway. The hourly and weekly variations of PM10 concentrations had different pattern for the measurement sites. The monthly and seasonal concentrations exhibited a notable characteristic： the maximum concentration was obtained in spring season, most likely due to Yellow sand effects. Furthermore, this temporal variation of PM10 pollution varied with study site. Meanwhile, the PM10 values measured at the monitoring site, Manchondong, were comparable with those of a control site. The average PM10 concentration ranged from 23 $\mu\textrm{g}$/㎥ to 115 $\mu\textrm{g}$/㎥ with a mean value of 53 $\mu\textrm{g}$/㎥ in the former site and from 22 $\mu\textrm{g}$/㎥ to 91 $\mu\textrm{g}$/㎥ with a mean value of 45 $\mu\textrm{g}$/㎥ in the latter site.

• Asian Journal of Atmospheric Environment
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• 제11권3호
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• pp.194-201
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• 2017

This study investigates the factors that affect China's air pollution using city-level panel data and spatial econometric models. We address three air pollutants ($PM_{10}$, $SO_2$, and $NO_2$) present in 30 cities in China between 2004-2012 using global OLS and spatial models. To develop the spatial econometric analysis, we create a spatial weights matrix to define spatial patterns based on two neighborhood criteria - the queen contiguity and k nearest neighbors. The results show that the estimated coefficients are relatively consistent across different spatial weight criteria. The OLS models indicate that the effect of green spaces is statistically significant in decreasing the concentrations of all air pollutants. In the $PM_{10}$ and $SO_2$ analyses, the OLS models find that the number of buses and population density are also positively related to a reduction in the concentration of air pollutants. In addition, an increase in the temperature and the presence of secondary industries increase $SO_2$ and $NO_2$ concentrations, respectively. All spatial models capture a positive and significant effect of green spaces on reducing the concentration of each air pollutant. Our results suggest that green spaces in cities should receive priority consideration in local planning aimed at sustainable development. Furthermore, policymakers need to be able to discern the differences among pollutants when establishing environmental policies.

• Spatial Information Research
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• 제21권5호
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• pp.15-22
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• 2013

본 연구는 동북아시아 지역의 이산화탄소 분포와 식생지수의 상관성 규명을 목적으로 한다. 이를 위해 지리가중치 분석기법을 활용하여 GOSAT 이산화탄소 측정자료와 MODIS 식생지수에 대해 다중공간회귀 분석을 시행하였다. 그 결과 이산화탄소와 식생지수 사이에는 전체적인 (-)의 상관관계가 나타나고 있음을 확인할 수 있었다. 공간적 자기상관성 측정을 위한 Global Morans'I지수와 Anselin Local Morans'I 통계 분석 결과에서는 이산화탄소는 일정한 군집성을 보이며 분포하고 있는 것으로 나타나났다. 이러한 결과는 산림파괴와 같은 개발 활동이 이산화탄소의 배출에 영향을 미쳐 일정한 군집을 형성하게 된 것으로 추정된다. 그러나 이산화탄소의 분포는 인위적 배출원과 식생의 호흡, 해양의 배출과 흡수 등의 다양한 요인과 결부되어 달라지기 때문에 이산화탄소 분포에 개입되는 다양한 변수와 상관성을 평가하는 후속연구가 필요할 것으로 사료된다.

• 한국분무공학회지
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• 제4권4호
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• pp.1-8
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• 1999

The concentration and spatial distribution of vapor phases in DI (Direct Injection) gasoline spray were measured quantitatively by exciplex fluorescence method. Fluorobenzene and DEMA (diethylmethylamine) in a solution of hexane were used as the exciplex-forming dopants. The fluorescence intensity of vapor phase were obtained by ICCD camera with the appropriate filter The relationship between fluorescence intensity and vapor concentration was induced fer the purpose of a quantitative analysis. The 2-D vapor/liquid images of fuel spray were captured under the evaporation condition, and the spatial distribution of vapor concentration was obtained. The spatial distribution of liquid phase had hollow-cone shape. And the vapor phase was widely distributed in the whole spray. The behavior of vapor phase was significantly affected by second flow such as entrainment, vortex, while that of liquid phase was scarcely affected.

• Journal of Korea Trade
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• 제25권5호
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• pp.93-109
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• 2021

Purpose - The logistics industry is often featured by its location relevance and industrial concentration. Industrial concentration is conducive to the effective transmission of information by reducing transaction costs and improving transaction efficiency, thus promoting the development of trade. The main purpose of this paper is to measure the spatial total factor productivity and location quotient of the logistics industry in Korea, and to study the impact of the logistics industry efficiency and agglomeration effect on import and export trade in Korea. Design/methodology - First, used the spatial stochastic frontier method to measure the spatial total factor productivity of the logistics industry in Korea, this serves as the efficiency index of the logistics industry in various regions of Korea. Second, calculated the location quotient (LQ) of the logistics industry to measure the industry's concentration degree. Third, employed a spatial econometric model to analyze the impacts of factors such as the efficiency and concentration levels of the logistics industry on import and export trade in Korea. Findings - This study's main findings can be summarized as follows: this study found that the overall efficiency of the logistics industry in Korea needs to be improved, even though it showed an upward trend in all regions of the country; Moreover, the agglomeration level of Korea's logistics industry needs to be improved; Finally, the positive spatial correlation and industrial agglomeration effect of Korea's logistics industry had a positive impact on the country's import and export trade. Originality/value - This study is innovative in terms of research perspective and methods. Most of the previous studies have measured the development level of the logistics industry using the logistics performance index (LPI), Fewer studies have assessed through the spatial total factor productivity and location quotient of the logistics industry in Korea to measure the efficiency index of the logistics industry in various regions of Korea and concentration degree, as well as there was almost no study on the impact of logistics industry efficiency and agglomeration effect on import and export trade in Korea. This study addresses this limitation by analyzing the impacts of the efficiency and agglomeration effect of the logistics industry on import and export trade in Korea.

• 한국환경복원기술학회지
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• 제25권1호
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• pp.41-55
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• 2022

Social interest in the fine particulate matter has increased significantly since the 2010s, and various efforts have been made to reduce it through environmental plans and policies. To support such environmental planning, in this study, spatial cluster characteristics of fine particulate matter (PM2.5) concentrations were analyzed in the metropolitan area to identify high-risk areas spatially, and the correlation with local environmental characteristics was also confirmed. The PM2.5 concentration for the recent 5 years (2016-2020) was targeted, and representative spatial statistical methods Getis-Ord Gi^* and Local Moran's I were applied. As a result of the analysis, the cluster form was different in Getis-Ord Gi^* and Local Moran's I, but they show high similarity in direction, therefore complementary results could be obtained. In the high concentration period, the hotspot concentration of the Getis-Ord Gi* method increased, but in Local Moran's I, the HH region, the high concentration cluster, showed a decreasing trend. Hotspots of the Getis-Ord Gi^* technique were prominent in the Pyeongtaek-Hwaseong and Yeoju-Icheon regions, and the HH cluster of Local Moran's I was located in the southwest, and the LL cluster was located in the northeast. As in the case of the metropolitan area, in the results of Seoul, there was a phenomenon of division between the northeast and southwest regions. The PM2.5 concentration showed a high correlation with the elevation, vegetation greenness and the industrial area ratio. During the high concentration period, the relation with vegetation greenness increased, and the elevation and industrial area ratio increased in the case of the annual average. This suggests that the function of vegetation can be maximized at a high concentration period, and the influence of topography and industrial areas is large on average. This characteristic was also confirmed in the basic statistics for each major cluster. The spatial clustering characteristics of PM2.5 can be considered in the national land and environmental plan at the metropolitan level. In particular, it will be effective to utilize the clustering characteristics based on the annual average concentration, which contributes to domestic emissions.