• 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.

• Environmental and Resource Economics Review
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• v.28 no.3
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• pp.327-354
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• 2019

In this paper, we conducted panel data analysis considering spatial correlation between regions, which were not considered in previous papers in analyzing the causes of fine dust concentration in Korea. Many existing researchers implicitly assume the independence of the effects of incomes and other explanatory variables of adjoining countries(or regions). Using panel data on fine dust concentration, this paper has established that existing EKC can be established even when considering the spatial correlation of the region, and when these effects are not taken into account, it can be underestimated or overestimated on the effects and causes of fine dust concentration.

• Journal of the Korean Institute of Rural Architecture
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• v.25 no.4
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• pp.9-16
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• 2023

In this study, the status and characteristics of fine dust and its impact on neighboring areas were investigated to proactively respond to the government's environmental regulations expected in the future and to minimize the damage by the fine dust generated at construction waste intermediate treatment plants. In addition, since there are no such plants that can affect the surroundings with no houses or other waste treatment sites nearby, an independently located construction waste intermediate treatment plant was selected to compare the characteristics of fine dust with that from the construction waste intermediate treatment sites located in the downtown area. The conclusions of the study are as follows. (1) The measurement results of PM10 at 4 points in the plant showed that the location where the crushing facility was operating had an elevated level of fine dust at 80㎍/m³ on average and a maximum of 124㎍/m³, and the level rose to 110㎍/m³ at points where vehicles frequent. (2) The PM2.5 measurement results inside the plant showed that the average concentration of the reference point was 16㎍/m³ and the maximum value was 20㎍/m³, which was distributed within the management standard. (3) It was found that the average concentration of PM10 in the nearby area ranged from 28 to 38㎍/m³, which was similar to or lower than 36㎍/m³ of the reference point. Therefore, the concentration of the fine dust generated in the plant had a negligible effect on the increase in concentration of fine dust in nearby areas. (4) The heavy metal contents were measured from the filter paper collected from the plant. The PM10 was found to be about 14 to 26ng/m³, and PM 2.5 was 25 to 28ng/m³, which was the average of domestic atmospheric concentrations. (5) The SEM-EDX analysis results showed that the PM10 contained Si and O around 40% similarly for both. The SiO2, a component of silica occupied the most and C was present as CaCO3, which was assumed to be a limestone component. The remaining components included NaO, Al2O3, and CaO as trace oxides. (6) The SEM-EDX analysis results showed that the PM 2.5 contained 5 to 7% of Cl, which is a chlorine ion, and a small amount of K was detected at 2.51% in the sample from the shutdown plant.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.97-101
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• 2022

In this paper, we propose a method of measuring Fine dust in images using K-means and Sobel-mask based edge detection techniques using CCTV. The proposed algorithm collects images using a CCTV camera and designates an image range through a region of interest. When clustering is completed by applying the K-means algorithm, outline is detected through Sobel-mask, edge strength is measured, and the concentration of fine dust is determined based on the measured data. The proposed method extracts the contour of the mountain range using the characteristics of Sobel-mask, which has an advantage in diagonal measurement, and shows the difference in detection according to the concentration of fine dust as an experimental result.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.506-512
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• 2018

The fine dust generated in the home and restaurant business occupies a low ratio of about 4% of the total fine dust emissions. However, at the foodservice business, the rate of change of the pollutant concentration is very high, so that the temporary fine dust concentration can be measured up to 60 times. The pollutants generated from non-industrial combustion plants consist of particulate fine dust and gaseous organic compounds. To remove these pollutants, cleaning dust collection system, which is an effective system for simultaneous removal of gaseous and particulate matter, is applied. This is a method of increasing the probability of diffusion capture of the Brownian motion by pressurized liquid injection method using the atomizing nozzle. The dust removal efficiency of the fine dust collecting system was analyzed by nozzle spraying air pressure condition and angle using the manufactured fine dust removing system. As a result, it was confirmed that the efficiency of removal of fine dust and gaseous organic compounds was more than 90%. The developed system is expected to be highly usable in the future because it can remove particulate dust from the existing plant hood system without any installation cost.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.139-149
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• 2019

As of 2018, a large amount of Chinese fine dust is flowing into Korea in westerlies. However, the amount of fine dust generated in Korea can not be ignored. Even 52% of the causes of fine dust are domestic factors. Especially in Seoul, where the population is densely populated, the dust levels are high enough to be comparable to other regions. In Seoul, the dust levels are different from each other district. In order to understand the difference of fine dust generation by distinction, it is judged based on the highest traffic volume among the causes of fine dust generation in Seoul. Comparing the traffic volume and the fine dust concentration in 2017, it is possible to know the effect of traffic volume actually, how much it affects.

• Journal of the Korean Society of Clothing and Textiles
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• v.44 no.3
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• pp.516-538
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• 2020

The present study investigated regional and sex differences in knowledge, perception, cognition and behavior of fine-dust protective masks for periods of high concentration of fine dust in Korea. A total of 2,012 adults from seven provinces responded to the questionnaire. The results (all p<.05) showed that 78% of respondents considered pollution from China to be the greatest contributor of fine dust. Seoul and Gyeonggi residents more frequently checked fine dust forecasts than other provinces and consulted their smartphone applications to do so more than other residents. Jeju, Gwangwon, and Jeonla residents had less knowledge of KF 80, 94, and 99 masks than residents of other provinces. Gwangwon and Jeju residents had less trust in the effectiveness of protective masks than other residents. Females perceived themselves as unhealthier respiratory, more frequently checked the concentration of fine dust, trusted more the effectiveness of masks, and more frequently wore masks, compared to male respondents. Those who self-identified their respiratory function as poor, more frequently checked fine dust forecasting, and had greater knowledge of masks, which resulted in greater trust in the protective function of masks, and finally had higher wear frequency of masks for days with high concentrations of fine dust.

• Journal of Energy Engineering
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• v.29 no.2
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• pp.23-29
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• 2020

In this study, the last 10 years of news data on fine dust was collected and 80 topics are selected through LDA analysis. As a result, weather-related information made up the main words for the topic, and we can see that fine dust becomes a big issue below 10 degrees Celsius. The frequency of exposure to the media and the maximum concentration of fine dust are correlated with positive. Topics related to fine dust reduction measures and the government's comprehensive measures over the past decade, topics related to products such as air purifiers related to fine dust, topics related to policies protecting vulnerable people from fine dust, and topics on fine dust reduction through R&D were found to be major topics. Measures against fine dust as a social issue can be seen to be closely related to the government's policy.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.1
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• pp.92-111
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• 2021

As fine dust negatively affects disease, industry and economy, the people are sensitive to fine dust. Therefore, if the occurrence of fine dust can be predicted, countermeasures can be prepared in advance, which can be helpful for life and economy. Fine dust is affected by the weather and the degree of concentration of fine dust emission sources. The industrial sector has the largest amount of fine dust emissions, and in industrial complexes, factories emit a lot of fine dust as fine dust emission sources. This study targets regions with old industrial complexes in local cities. The purpose of this study is to explore the factors that cause fine dust and develop a predictive model that can predict the occurrence of fine dust. weather data and fine dust data were used, and variables that influence the generation of fine dust were extracted through multiple regression analysis. Based on the results of multiple regression analysis, a model with high predictive power was extracted by learning with a machine learning regression learner model. The performance of the model was confirmed using test data. As a result, the models with high predictive power were linear regression model, Gaussian process regression model, and support vector machine. The proportion of training data and predictive power were not proportional. In addition, the average value of the difference between the predicted value and the measured value was not large, but when the measured value was high, the predictive power was decreased. The results of this study can be developed as a more systematic and precise fine dust prediction service by combining meteorological data and urban big data through local government data hubs. Lastly, it will be an opportunity to promote the development of smart industrial complexes.

• Journal of Environmental Science International
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• v.22 no.6
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• pp.651-666
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• 2013

This study introduces a novel approach to the differentiation of two phenomena, Asian Dust and haze, which are extremely difficult to distinguish based solely on comparisons of PM10 concentration, through use of the Optical Particle Counter (OPC), which simultaneously generates PM10, PM2.5 and PM1.0 concentration. In the case of Asian Dust, PM10 concentration rose to the exclusion of PM2.5 and PM1.0 concentration. The relative ratios of PM2.5 and PM1.0 concentration versus PM10 concentration were below 40%, which is consistent with the conclusion that Asian Dust, as a prime example of the coarse-particle phenomenon, only impacts PM10 concentration, not PM2.5 and PM1.0 concentration. In contrast, PM10, PM2.5 and PM1.0 concentration simultaneously increased with haze. The relative ratios of PM2.5 and PM1.0 concentration versus PM10 concentration were generally above 70%. In this case, PM1.0 concentration varies because a haze event consists of secondary aerosol in the fine-mode, and the relative ratios of PM10 and PM2.5 concentration remain intact as these values already subsume PM1.0 concentration. The sequential shift of the peaks in PM10, PM2.5 and PM1.0 concentrations also serve to individually track the transport of coarse-mode versus fine-mode aerosols. The distinction in the relative ratios of PM2.5 and PM1.0 concentration versus PM10 concentration in an Asian Dust versus a haze event, when collected on a national or global scale using OPC monitoring networks, provides realistic information on outbreaks and transport of Asian Dust and haze.