• Journal of Service Research and Studies
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• v.10 no.1
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• pp.55-67
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• 2020

Fine dust has recently become one of the greatest concerns of Korean people and has been a target of considerable efforts by governments and local governments. In the academic world, many researches have been carried out in relation to fine dust, but the research on the economic field has been relatively few. So we wanted to know how fine dust affects the economy. Big data of PM10 concentration for fine dust and fine dust theme stock price were collected for five years from 2013 to 2017. Regression analysis was performed using the linear regression model, the generalized least squares method. As a result, the change in the fine dust concentration was found to have a effect on the related theme stocks' price. When the fine dust concentration increased compared to the previous day, the fine dust theme stocks' price also showed a tendency to increase. Also, according to the analysis of stock price change from 2013 to 2017 based on fine dust theme stocks, companies with large regression coefficients were changed every year. Among them, the regression coefficients of Monalisa were repeatedly high in 2014, 2015, 2017, Samil Pharmaceutical in 2015, 2016 and 2017, and Welcron in 2016 and 2017, and the companies were judged to be sensitive to the concentration of fine dust. The companies that responded the most in the past 5 years were Wokong, Welcron, Dongsung Pharmaceutical, Samil Pharmaceutical, and Monalisa. If PM2.5 measurement data are accumulated enough, it would be meaningful to compare and analyze PM2.5 concentration with independent variables. In this study, only the fine dust concentration is used as an independent variable. However, it is expected that a more clear and well-explained result can be found by adding appropriate additional variables to increase the explanatory power.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.140-145
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• 2022

In an advanced modern society, among air pollutants caused by urban industrialization and public transportation, fine dust flows into indoors from the outdoors. The fine dust meter used indoors provides limited information and measures the pollution level differently, so there is a problem that users cannot monitor and monitor the data they want. To solve this problem, in this paper, indoor air quality data fine dust and ultra-fine dust (PM1.0, PM2.5, PM10), VOC (Volatile Organic Compounds) and PIR (Passive Infrared Sensor) are used to measure fine dust. and a monitoring system were designed and implemented. We propose a fine dust meter and monitoring system that is installed in a designated area to measure fine dust in real time, collects, stores, and visualizes data through App Engine of Google Cloud Platform and provides it to users.

• Communications for Statistical Applications and Methods
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• v.30 no.5
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• pp.517-530
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• 2023

Recent studies revealed that fine dust in ambient air may cause various health problems such as respiratory diseases and cancer. To prevent the toxic effects of fine dust, it is important to predict the concentration of fine dust in advance and to identify factors that are closely related to fine dust. In this study, we developed a Bayesian network model for predicting PM10 concentration in Seoul, Korea, and visualized the relationship between important factors. The network was trained by using air quality and meteorological data collected in Seoul between 2018 and 2021. The study results showed that current PM10 concentration, season, carbon monoxide (CO) were the top 3 effective factors in 24 hours ahead prediction of PM10 concentration in Seoul, and that there were interactive effects.

• The Journal of Bigdata
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• v.2 no.1
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• pp.17-26
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• 2017

The gradual desertification in Northeastern China brought about by the industrial development and global warming, has affected the Korean peninsula as evident by the ultrafine dust geographically and seasonally. People with severe respiratory problems, senior citizens and the infants are susceptible to the ill effects of fine dust which could prove fatal to them. Hence, we need to study the root cause of fine dust emergence and the correlation verification between fine dust and its side effects. This study firstly analyzed clean and contaminated areas classified by industrial elements. We utilized air, weather and industrial data in the area. Next, we detected a change of fine dust in terms of weather and climate. We analyzed correlation of air and weather by influence from domestic and neighboring country. The result indicated that China is the culprit of the emergence of fine dust predicament. Consequently, we can prove that fine dust ($PM_{10}$) and ultrafine dust ($PM_{2.5}$) could arise from geographical, seasonal, and pollutant elements. Therefore, we propose the optimum to make countermeasures about fine dust in terms of industry, topography, population and living residence.

• Journal of Environmental Science International
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• v.29 no.5
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• pp.445-455
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• 2020

Fine dust is one of the most critical environmental issues in Korea, and the government recognizes the need to establish customized reduction policies based on regional characteristics. Several studies on air pollutants investigate whether factories affect the distribution of fine dust in a particular region. However, understanding the impact of the entire industry sector requires further investigation. This study identifies the impacts of industrial characteristics on fine dust levels of 141 municipalities across Korea in 2016. A total of 23 variables were used, of which 12 referred to industries and 11 to general characteristics of each city. Due to the high correlation between independent variables, partial least squares (PLS) regression models were used. The analysis identified 14 significant variables for PM10 and 13 for PM2.5. Therefore, the results suggest that local industrial characteristics can significantly influence fine dust levels and provide suggestions for establishing customized reduction policies based on local characteristics.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.30-37
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• 2022

Because fine dust (PM10) has a close effect on the environment, fine dust generated in the climate and living environment has a bad effect on the human body. In this study, the LSTM model was applied to predict and analyze the effect of fine dust on Gwangju Metropolitan City in Korea. This paper uses prediction values of input variables selected through correlation analysis to confirm fine dust prediction performance. In this paper, data from the Gwangju Metropolitan City area were collected to measure fine dust. The collection period is one year's worth of data was used from january to December of 2021, and the test data was conducted using three-month data from January to March of 2022. As a result of this study, in the as a result of predicting fine dust (PH10) and ultrafine dust (PH2.5) using the LSTM model, the RMSE was 4.61 and the test result value was as low as 4.37. This reason is judged to be the result of the contents of the one-year sample.

• Land and Housing Review
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• v.12 no.3
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• pp.39-50
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• 2021

This research aims to provide guidelines with the appropriate type of smart bus stop to reduce the concentration of fine dust. To this end, we divided smart bus stops into two types: closed and open bus stops. The estimated reduction effect was compared and analysed by measuring the estimated PM₁₀ and the estimated PM_2.5 at five locations inside and outside a smart bus stop located in Gangnam gu, Seoul. The effect of reducing the amount of the fine dust concentration in external space was insignificant for both types of bus stops. The different effect of reducing the concentration of the amount between in internal space was relatively significant: the fine dust concentration was 26.0 ㎍/m³ for PM₁₀ and 20.2 ㎍/m³ for PM_2.5 at open-type bus stops; whilst was 2.4 ㎍/m³ for PM₁₀ and 1.8 ㎍/m³ for PM_2.5 at closed type bus stops. Based on the findings, a closed type bus stop is recommended when considering the cost of reducing fine dust. In addition, due to the ineffectiveness of reducing the amount of fine dust from the outside of the bus stop, additional provision of smart bus stops is required particularly in locations where demand exceeds the capacity of the inside. A clear definition of smart bus stop and it's minimum standard should also be considered.

• Journal of KIBIM
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• v.12 no.4
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• pp.104-115
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• 2022

Fine Dust in Korea has been classified as a social disaster since 2019 due to continuous increase in concentration of Particulate Matter 10(PM 10) and PM 2.5. The fine dust issue has negative physical and mental impacts, especially on vulnerable population including children and the elderly. Seoul metropolitan government have installed fine dust shelters since 2019. However, there is a lack of research that evaluates spatiotemporal distribution of these facilities. Therefore, the first aim of this study is to find the relationship between PM levels and dust scattering construction sites, or air pollutant emission sites through in depth spatial analyses. The second purpose is to analyze the spatial distribution of PM shelters in Seoul, and to evaluate the location efficiency of them. Kernel density, krigging, and network analyses were conducted, and floating population was considered instead of census data for this research. The reults of network analysis based on the road system showed that Yangcheon-gu, Songpa-gu, Seongbuk-gu, and Dobong-gu were found to need additional fine dust shelters. Also, the results from analyzing the floating population that includes children and the elderly showed that Songpa-gu, Seodaemun-gu, Gangdong-gu, Seocho-gu, and Dongdaemun-gu need more placements of find dust shelters. The results of this study are expected to provide implications for urban planners to enhance find dust shelter placement in urban areas, and vulnerable population issues would be considered in many ways.

• Journal of Environmental Science International
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• v.26 no.6
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• pp.751-765
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• 2017

This research investigates the characteristics of meteorological variation and fine particles ($PM_{10}$ and $PM_{2.5}$) for case related to the haze occurrence (Asian dust, long range transport, stationary) in Busan. Haze occurrence day was 559 days for 20 years (from 1996 to 2015), haze occurrence frequency was 82 days (14.7%) in March, followed by 67 days (12.0%) in February and 56 days (10.0%) in May. Asian dust occurred most frequently in spring and least in winter, whereas haze occurrence frequency was 31.5% in spring, 29.7% in winter, 21.1% in fall, and 17.7% in summer. $PM_{10}$ concentration was highest in the occurrence of Asian dust, followed by haze and haze + mist, whereas $PM_{2.5}$ concentration was highest in the occurrence of haze. These results indicate that understanding the relation between meteorological phenomena and fine particle concentration can provide insight into establishing a strategy to control urban air quality.

• Korean Journal of Agricultural Science
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• v.50 no.4
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• pp.917-925
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• 2023

Efforts for developing the domestic horse industry in South Korea are evident through the various national policies. Proper management of stables for ensuring the health of horses is essential to sustain the growing equine industry. This study aimed to measure the fine dust emissions in stables based on the type and quantity of bedding used for horses, for establishing guidelines pertaining to bedding use in stables. The stables accommodated 12 horses. Sawdust, wood shavings, wood pellet, and straw were chosen as treatments. Three different quantities (approximately 3, 6, and 9 cm in height) were applied for each type. Fine dust measurements were carried out at three time points, with each measuring period lasting for approximately three weeks. Measurements included PM2.5 and PM10 fine dust levels. The initial analysis revealed that, sawdust with 9 cm bedding had the highest dust levels; approximately 54.6 ㎍/m³, for PM2.5 and 95.3 ㎍/m³, for PM10. Sawdust bedding at the highest quantity (9 cm) exhibited significantly higher initial fine dust emissions. These findings suggest that bedding materials with smaller particle size, such as sawdust and wood shavings, tend to produce finer dust. Initially, the fine dust emissions decreased in all bedding types and quantities, possibly due to the increased moisture content of bedding owing to horse manure production. However, emissions increased subsequently due to ammonia production.