• Title, Summary, Keyword: Particulate matter

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Health effects of particulate matter (미세먼지의 건강영향)

  • Bae, Sanghyuk;Hong, Yun-Chul
    • Journal of the Korean Medical Association
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    • v.61 no.12
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    • pp.749-755
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    • 2018
  • Particulate matter is an air pollutant emitted from both natural and anthropogenic sources, and its adverse health effects have been well documented in time-series analyses and cohort studies. The effect size of particulate matter exposure-a roughly 0.5% increase in mortality for each $10{\mu}g/m^3$ increment of short-term exposure to particulate matter with aerodynamic diameter ${\leq}10{\mu}m$ and approximately a 10% increase for each $10{\mu}g/m^3$ increment of long-term exposure to particulate matter with aerodynamic diameter ${\leq}2.5{\mu}m$-is small compared to other risk factors, but the exposure is involuntary and affects the entire population, which makes particulate matter pollution an important public health issue. The World Health Organization and Korean government have both established guidelines for particulate matter concentrations, but the Korean guideline is less stringent than that of the World Health Organization. The annual mean concentration of particulate matter in Korea is decreasing, but the trend seems to be slowing. In addition to policy efforts to reduce particulate matter emission, personal approaches such as the use of face masks and air purifiers have been recommended. Personal approaches may not solve the fundamental problem, but can provide temporary mitigation until efforts to reduce emission make progress.

A Particulate Matter Sensor with Groove Electrode for Real-Time Diesel Engine On-Board Diagnostics

  • Kim, S.;Kim, Y.;Lee, J.;Lim, S.;Min, K.;Chun, K.
    • Journal of Sensor Science and Technology
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    • v.22 no.3
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    • pp.191-196
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    • 2013
  • A particulate matter sensor fabricated by MEMS process is proposed. It is developed to accommodate Euro6 on-board diagnostics regulation for diesel automobile. In the regulation, emission of diesel particulate matter is restricted to 9 mg/km. Particulate matter sensor is designed to use induced charges by charged particulate matter. To increase sensitivity of the sensor, groove is formed on sensor surface because wider surface area generates more induced charges. Sensitivity of the sensor is measured 10.6 mV/(mg/km) and the sensor shows good linearity up to 15.7 mg/km. Also its minimum detectable range is about 0.25 mg/km. It is suitable to detect failure of a diesel particulate filter which should filter particulate matter more than 9 mg/km. For removing accumulated particulate matter on the sensor which can disturb normal operation, platinum heater is designed on the backside of the sensor. The developed sensor can sense very low amount of particulate matter from exhaust gas in real-time with good linearity.

Particulate Matter Prediction Model using Artificial Neural Network (인공 신경망을 이용한 미세먼지 예측 모델)

  • Jung, Yong-jin;Cho, Kyoung-woo;Kang, Chul-gyu;Oh, Chang-heon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • pp.623-625
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    • 2018
  • As the issue of particulate matter spreads, services for providing particulate matter information in real time are increasing. However, when a sensor node for collecting particulate matter is defective, a corresponding service may not be provided. To solve these problems, it is necessary to predict and deduce particulate matter. In this paper, a particulate matter prediction model is designed using artificial neural network algorithm based on past particulate matter and meteorological data to predict particulate matter. Also, the prediction results are compared by learning the input data of the model in the design stage.

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Particulate Matter AQI Index Prediction using Multi-Layer Perceptron Network (다층 퍼셉트론 신경망을 이용한 미세먼지 AQI 지수 예측)

  • Cho, Kyoung-woo;Lee, Jong-sung;Oh, Chang-heon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • pp.540-542
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    • 2019
  • With many announcements on air pollution and human effects from particulate matters, particulate matter forecasts are attracting a lot of public attention. As a result, various efforts have been made to increase the accuracy of particulate matter forecasting by using statistical modeling and machine learning technique. In this paper, the particulate matter AQI index prediction is performed using the multilayer perceptron neural network for particulate matter prediction. For this purpose, a prediction model is designed by using the meteorological factors and particulate matter concentration values commonly used in a number of studies, and the accuracy of the particulate matter AQI prediction is compared.

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The Relationships between Particulate Matter Risk Perception, Knowledge, and Health Promoting Behaviors among College Students (대학생의 미세먼지 위험에 대한 인식, 지식, 관리행위에 대한 지각된 장애와 건강 관리행위의 관계)

  • Park, Eunsun;Oh, Hyun-Jung;Kim, Sue-Hyon;Min, Ari
    • Journal of Korean Biological Nursing Science
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    • v.20 no.1
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    • pp.20-29
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    • 2018
  • Purpose: This study aimed to determine the relationships between particulate matter risk perception, knowledge, and perceived barriers and health-promoting behaviors among college students. Methods: Data for this cross-sectional study were collected from September 1 to 30, 2017. The study sample consisted of 85 students from a university, Seoul. Students not living in the Seoul metropolitan area during the spring 2017 semester were excluded from participation. Pearson's correlation coefficient was used to identify relationships among study variables. Results: A significant positive correlation existed between particulate matter risk perception and health-promoting behaviors related to particulate matter (r= .51, p< .001). Among the risk perception subdomains, attention (r= .47, p< .001) and health effect (r= .55, p< .001) showed strong positive relationships with health-promoting behaviors. No significant relationships were found between knowledge (r= .12, p= .288) or perceived barriers (r= -.12, p= .264) and health-promoting behaviors related to particulate matter. Conclusion: Based on the study results, strategies for enhancing particulate matter risk perception are needed to increase the level of health-promoting behaviors related to particulate matter among college students.

Assessment and Estimation of Particulate Matter Formation Potential and Respiratory Effects from Air Emission Matters in Industrial Sectors and Cities/Regions (국내 산업 및 시도별 대기오염물질 배출량자료를 이용한 미세먼지 형성 가능성 및 인체 호흡기 영향 평가추정)

  • Kim, Junbeum
    • Journal of Korean Society of Environmental Engineers
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    • v.39 no.4
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    • pp.220-228
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    • 2017
  • Since the fine particulate matters occurred from mainly combustion in industry and road transport effect to human respiratory health, the interest and importance are getting increased. In 2013, the World Health Organization (WHO) concluded that outdoor air pollution is carcinogenic to humans, with the particulate matter component ($PM_{10}$ and $PM_{2.5}$) of air pollution most closely associated with increased cancer incidence, especially cancer of the lung. Therefore, many researches have been studied in the quantification and data development of fine particulate matters. Currently, the Ministry of Environment and cities/regions are developing the fine particulate matter data and air emission information. Particularly just $PM_{10}$ and $PM_{2.5}$ data is used in the fine particulate matters warning and alert. The data of NOx, SOx, $NH_3$, which have the particulate matter formation potential are not well considered. Also, the researches related with particulate matter formation potential and respiratory effects by industrial sectors and cities/regions are not conducted well. Therefore, the purpose of this study is to evaluate and calculate particulate matter formation potential and respiratory effects in 11 industrial sectors and cities using NOx, SOx, $PM_{10}$, $NH_3$ data (developed by Ministry of Environment and National Institute of Environmental Research) in 2001 and 2013. The results of this study will be provided the particulate matter formation potential and respiratory effects and will be used for future the fine particulate matter researches.

Non-linearity Mitigation Method of Particulate Matter using Machine Learning Clustering Algorithms (기계학습 군집 알고리즘을 이용한 미세먼지 비선형성 완화방안)

  • Lee, Sang-gwon;Cho, Kyoung-woo;Oh, Chang-heon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • pp.341-343
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    • 2019
  • As the generation of high concentration particulate matter increases, much attention is focused on the prediction of particulate matter. Particulate matter refers to particulate matter less than $10{\mu}m$ diameter in the atmosphere and is affected by weather changes such as temperature, relative humidity and wind speed. Therefore, various studies have been conducted to analyze the correlation with weather information for particulate matter prediction. However, the nonlinear time series distribution of particulate matter increases the complexity of the prediction model and can lead to inaccurate predictions. In this paper, we try to mitigate the nonlinear characteristics of particulate matter by using cluster algorithm and classification algorithm of machine learning. The machine learning algorithms used are agglomerative clustering, density-based spatial clustering of applications with noise(DBSCAN).

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Characteristics of Particulate Matter Generated during the Operation of a Small Directly Fired Coffee Roaster (소형 직화식 커피 로스터 이용 시 발생하는 미세먼지 특성 연구)

  • Yu, Da Eun;Kim, Seung Won
    • Journal of Korean Society of Occupational and Environmental Hygiene
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    • v.30 no.2
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    • pp.236-248
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    • 2020
  • Objectives: The purpose of this study was to evaluate the concentrations of particulate matter generated during coffee roasting and to study various factors affecting the concentrations. Methods: Differences in concentration levels were investigated based on various factors to understand the emission rates of particulate matter over time and to compare the mass and number concentrations according to their size. Sampling was performed in closed laboratories without the operation of air conditioning or ventilation. Optical Particle Sizer(OPS) was used as a measuring device. An OPS measures using a light-scattering method. Sampling was performed for sixty minutes at one-minute intervals. The background concentration was measured for about 30 minutes before starting of coffee roasting. The concentrations of particulate matter generated during coffee roasting were monitored until roasted coffee beans were removed from the roaster and cooled down. Several factors affecting the concentrations of particulate matter were investigated, which includes the origins of green beans, the roasting level, and the input amount of green beans. Results: The results of this study may be summarized as follows: 1) There was no difference in particulate matter concentration levels by the origin of the green beans, but a statistically significant difference in concentration levels by roasting level and the input amount of green beans; The higher the roasting level, the higher was the particulate matter concentration. The more green beans we put in the roaster, the higher were the concentrations; 2) The PM10 mass concentrations increased over time. The average concentration after roasting was higher than the average concentration during roasting; 3) In the distribution of mass and number concentration by particle diameter, the majority of particles was below 2.5 ㎛. Conclusions: Persons who work in roastery cafes can be exposed to high concentrations of particulate matter. Therefore, personal exposure and risk assessment should be conducted for roastery cafe workers.

Effects of Regular Inspection Facility Standards Improvement on Particulate Matter (PM10) Emissions (정기검사 시설기준 개선이 입자상물질(PM10) 배출에 미치는 영향)

  • Choi, Soungkyu;Kim, Yongdal;Lee, Jaeyoung;Kim, Hogyeong;Noh, Kiseong;Park, Jungsoo
    • Journal of Auto-vehicle Safety Association
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    • v.11 no.1
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    • pp.36-39
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    • 2019
  • The particulate matter that was emitted always come up by atmospheric environmental problem. Running on the road vehicles must have regular inspection at regular period and make sure the emissions of exhaust gases exceed the legal standards. Emission test for the atmospheric environment, but it is not free from the particulate matter. Currently, emission test of vehicle inspection is divided into regular inspection and close inspection. Regular inspection and close inspection differ not only the method of emission test, but also the facility standards that must have for this inspection. According to the "Regulations on the Implementation of Comprehensive vehicle Inspection, etc.", close inspection must have trapping device that is trap particulate matter by emission test to vehicle. However, regular inspection is different. Regular inspection do not specify any criteria for trapping facilities. Therefore, this study is confirm how to prevent the emission of particulate matter to the atmosphere during the year when mandatory trapping facilities are required to trapped particulate matter in the regular inspection.

The Possibility of Managing Diseases Caused by Particulate Matter(PM10) with Chinese and Korean Medicines - Emphasis on Medical Prevention and Treatment - (미세먼지(霧霾)가 발생하는 질병과 중의학, 한의학의 관리가능성 - 예방과 치료를 중심으로-)

  • Koh, WonJoon;Ahn, JeongHoon;Lee, Sundong
    • Journal of Society of Preventive Korean Medicine
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    • v.22 no.1
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    • pp.69-80
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    • 2018
  • Objectives : This paper examines the effects of Particulate Matter on human bodies and the possibility of treating them with Chinese or Korean medicines. Methods : This paper categorizes the diseases caused by Particulate Matter, as well as the causes, pathology, prevention methods, and effectiveness of treatments by Chinese and Korean medicines. Based on these results, it analyzes whether such diseases can be managed by Chinese and Korean medicine. Results : Particulate Matter is known to affect respiratory organs, skin, circulatory system, nervous system, gestational diabetes, and other parts of the human body. While studies show evidence that treatments by Chinese and Korean medicines can reduce symptoms of some diseases and improve bodily functions that are damaged by Particulate Matter, there is no statistically significant evidence that they can provide fundamental treatments nor treat irreversible damages. Conclusion : Currently, there is no definite evidence that Chinese and Korean medicine can treat symptoms and diseases caused by Particulate Matter. Therefore, some Korean medicine doctors' arguments that Korean medicine is effective in treating such diseases are problematic, and thus, there is a need for much research in this field.