• Journal of IKEEE
• /
• v.24 no.4
• /
• pp.1136-1140
• /
• 2020

As air pollution caused by fine dust becomes serious, interest in the spread of fine dust and prediction of air quality is increasing. The causes of fine dust are very diverse, and some fine dust naturally occurs through forest fires and yellow dust, but most of them are known to be caused by air pollutants from burning fossil fuels such as petroleum and coal or from automobile exhaust gas. In this paper, the CALPUFF model recommended by the US EPA is used, and CALPUFF diffusion modeling is performed by generating a wind field through the CALMET model as a meteorological preprocessing program that generates a three-dimensional wind field, which is a meteorological element required by CALPUFF. Through this, we propose a fine dust diffusion modeling and air quality prediction system that reflects complex topography.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2020.06a
• /
• pp.68-69
• /
• 2020

Recently, the problem of air pollution is drawing attention as a social problem worldwide. Particularly, fine dust is the biggest issue among air pollutants, and it is analyzed that fine dust is generated from air pollutants such as burning fossil fuels such as petroleum or coal, or exhaust gases from automobiles. In addition, yellow dust originating from China adjacent to Korea flows into the Korean Peninsula in a western wind, causing the concentration of fine dust to deteriorate. Fine dust is a harmful substance to the human body such as asthma or respiratory disease, and awareness of the risk is also increasing to a degree designated as a primary carcinogen. In this study, as a method for improving the indoor air quality, the Properties of the matrix according to the mixing ratio of powdered activated carbon based on blast furnace slag are reviewed. The flexural strength and compressive strength were measured, and a fine dust concentration measurement experiment will be conducted later.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.16 no.2
• /
• pp.271-278
• /
• 2021

This paper is a study on the implementation of smart filter system that recognizes the external environment and automatically removes pollutants according to pollution level. Recently, the occurrence of various pollutants in indoor and outdoor space has adversely affected the human body. Especially, various fine dust generated in the atmosphere becomes worse in closed residential space or office space. Although air pollution can be temporary lowered through ventilation, it is difficult to respond to fine dust changes in real time, and such problems become serious in the space where many people reside, such as at home or industry. Therefore, it is necessary to measure the pollution level of fine dust inside the residential space in real time and to reduce the pollution of indoor ventilation through automatic ventilation with the outside. To improve these problems, this paper proposes the implementation of smart filter system for external environment recognition. The structure of smart filter system that automatically measures air quality inside and outside, removes pollutants, implements the function, and confirms the operability by manufacturing prototypes. Finally, the effectiveness of the smart filter system for solving fine dust problems was examined.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2018.11a
• /
• pp.89-90
• /
• 2018

In recent years, harmful substances and fine dust in the air are caused by respiratory and cardiovascular diseases through various mechanisms when they are introduced into the human body through respiration, thereby exacerbating human health and causing cancer by prolonged exposure do. In order to prevent such fine dust from being introduced into the room and to improve indoor air quality, improvement of air quality has attracted attention. Among indoor air pollutants, fine dust and CO₂ are pollutants that are directly affected by indoor number and activity. The purpose of this study is to evaluate the basic performance of cement matrix using photosynthetic bacteria as a basic study of fine dust and CO₂ adsorption type matrix to suppress indoor air pollution and improve air quality.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.14 no.4
• /
• pp.328-337
• /
• 2021

Air pollution, which is a class 1 carcinogen, such as asbestos and benzene, is the cause of various diseases. The spread of ultra-air pollution is one of the important causes of the spread of the corona virus. This paper analyzes and predicts fine dust and ultra-air pollution from 2015 to 2019 based on weather data such as average temperature, precipitation, and average wind speed in Seoul and atmospheric environment data such as SO2, NO2, and O3. Linear regression, SVM, and ensemble models among machine learning models were compared and analyzed to predict fine dust by grasping and analyzing the status of air pollution and ultra-air pollution by season and month. In addition, important features(attributes) that affect the generation of fine dust and ultra-air pollution are identified. The highest ultra-air pollution was found in March, and the lowest ultra-air pollution was observed from August to September. In the case of meteorological data, the data that has the most influence on ultra-air pollution is average temperature, and in the case of meteorological data and atmospheric environment data, NO2 has the greatest effect on ultra-air pollution generation.

• Particle and aerosol research
• /
• v.18 no.4
• /
• pp.137-145
• /
• 2022

As many studies on the harmfulness of fine dust have been reported, awareness of its seriousness is spreading. Recently, interest in indoor air quality as well as air pollution is increasing, and research on measures to block fine dust flowing into the room from the outside is being conducted. The clothing company is launching functional clothing to prevent fine dust attached to clothing from entering the room through outdoor activities. However, it is difficult to confirm whether there is actually fine-dust blocking performance, and there is no evaluation standard. In this study, the contamination rate caused by fine dust was quantitatively compared through image processing after contamination of the outer fabric for 4 types of commercially available functional clothing with fine-dust blocking effect. The difference in particle contamination according to the material of the outer fabric was analyzed by comparing the surface resistance, and it was found that the higher the surface resistance of the outer fabric material, the more fine dust was attached. The analysis method of this study is expected to be able to quantitatively compare and evaluate the fine-dust blocking performance of functional clothing.

• Applied Science and Convergence Technology
• /
• v.26 no.6
• /
• pp.218-222
• /
• 2017

This study was conducted to remove $NO_x$, which is the main cause of fine dust and air pollution as well as acid rain. $NO_x$ was tested using 3% NO (diluted in He) as a simulated gas. Experiments were sequentially carried out by oxidizing NO to $NO_2$ and absorbing $NO_2$. Especially, we focused on the changes of NO oxidation according to both oxidant ($NaClO_2$) concentration change (1~10 M) and oxidant pH change (pH = 1~5) by adding HCl. In addition, we tried to suggest a method to improve $NO_2$ absorption by conducting $NO_2$ reduction reaction with reducing agent (NaOH) concentration (40~60%). It was found that NO removal efficiency increased as both concentration of oxidant and flow rate of NO gas increased, and NO decreased more effectively as the pH of hydrochloric acid added to the oxidant was lower. The $NO_2$ adsorption was also better with increasing NaOH concentration, but the NO removal efficiency was ~20% lower than that of the selective NO reduction. Indeed, this experimental method is expected to be a new method that can be applied to the capture and removal of fine dust caused by air pollution because it is a method that can easily remove NO gas by a simple device without expensive giant equipment.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.15 no.1
• /
• pp.125-132
• /
• 2020

Due to the rapidly increasing number of cars and power generation, environmental pollution caused by fine dust is becoming a serious social problem. Especially fine dust becomes an important issue nowadays. More than 50 countries are suffering from fine dust above the recommended level, and each affected country is studying the measures to reduce fine dust and minimize its occurrence. However, at present, it is difficult to collect fine dust data from the various points with fixed fine dust acquisition drones, and also to collect accurate data due to the influence of rotating blades even in the existing drone method. In this paper, we propose a method for collecting fine dust using drones and a sensing parts architecture and show its effectiveness.

• Smart Media Journal
• /
• v.7 no.3
• /
• pp.22-28
• /
• 2018

Air pollution problems in Korea are gradually becoming a higher concern due to various reasons such as fine dust, causing anxiety among people with regard to their health. Although various studies have been carried out on the relationship between the influence of fine dust and a certain disease, they are mostly focusing on the analyzation that fine dust is related to specific illnesses such as respiratory and cardiovascular diseases, hypertension and diabetes. In this paper, we utilize the public data of medical history information to extract ten medical care subjects with the highest number of monthly care in 2016, and analyze the relation of fine dust with certain medical subjects using Pearson correlation coefficient. We also subdivide and analyze the correlation between fine dust and the medical subjects according to their gender and age. Middle-aged Female group with the strongest positive correlation between fine dust and the medical subjects is analyzed with the correlation from 2011 to 2015, with its relevance coefficient extracted by regression analysis in order to predict the correlation with the medical subjects according to the fine dust concentration.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.24 no.6
• /
• pp.119-128
• /
• 2020

An ultrasonic multiple scattering simulation using cross-section of fine dust particles were proposed. These days, along with awareness of air pollution, social interest in fine dust is increasing. In the construction field, awareness of fine dust is increasing, and research on preparing various countermeasures is underway. The light scattering method fine dust meter currently in use is affected by environmental factors such as relative humidity, and reliability problems in terms of accuracy are continuously reported. However, the transmission of ultrasonic waves can directly reflect the physical change of the medium based on the mechanical wave. Using these advantages of ultrasonic waves, fine dust measurement simulation was performed using the scattering cross section and ultrasonic multiple scattering theory. The shape data of the fine dust particles were collected using a SEM (Scanning Electron Microscope), and a cross-section according to the fine dust particles was derived through numerical analysis. As a result of signal processing, the error for the number density corresponding to each cross-section is minimum 19, maximum 3455.