• 대한의사협회지
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• 제61권12호
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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.

• 센서학회지
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• 제22권3호
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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.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2018년도 추계학술대회
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• pp.623-625
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• 2018

미세먼지에 대한 이슈가 확산됨에 따라 미세먼지에 대한 정보를 실시간으로 제공하는 서비스가 많아지고 있다. 그러나 미세먼지를 수집하기 위한 센서 노드의 결함이 발생할 경우 해당하는 서비스를 제공하지 못하는 경우가 발생한다. 이러한 문제를 해결하기 위해서는 미세먼지의 예측과 추론이 필요하다. 본 논문에서는 미세먼지를 예측하기 위해 과거의 미세먼지 및 기상 데이터를 기반으로 신경망 알고리즘을 이용하여 미세먼지 예측 모델을 설계한다. 또한 설계된 모델의 입력 데이터를 다양화하여 학습함으로써 예측 결과를 비교한다.

• 한국멀티미디어학회논문지
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• 제24권8호
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• pp.1138-1148
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• 2021

In this study, we developed a 'shared-use mobility'-mounted local particulate matter monitoring terminal technology to measure the actual particulate matter concentration around me. As a mobile terminal device in the form of an IoT sensor platform, it is designed to be separated into a control module and a sensor module to minimize interference between sensors and to consider the optimal observation position of each sensor. As a result of the field test, it was confirmed that particulate matter was locally different depending on time and space even within the same area. In addition, it was confirmed that the concentration of particulate matter in the relevant section differed by up to 100 times compared to the surrounding area due to specific sources of particulate matter such as unpaved roads. In addition, we positively reviewed the applicability of the service in the real-time metaverse environment using this result. Through technological advancement and application of multiple shared-use mobilities, we expect to be able to provide new services for practical smart city air environment monitoring, such as localized particulate matter information, air pollution event information, and identification of causes of particulate matter.

• 한국융합학회논문지
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• 제11권11호
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• pp.393-403
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• 2020

본 연구는 청소년을 대상으로 미세먼지에 대한 지식, 태도 및 행위의 수준을 파악하고 미세먼지 행위에 영향을 미치는 요인을 검증하여 미세먼지 대응에 효과적으로 대처하기 위한 전략 개발의 기초자료로 활용하고자 수행되었다. 서술적 조사연구이며, 연구 대상은 D시 일개 고등학교 학생 218명이었으며, 연구 기간은 2019년 5월이며 2주간 실시되었다. 수집된 자료는 SPSS WIN 18.0 프로그램을 사용하여 t-test, one-way ANOVA, Pearson's correlation coefficient, multiple regression을 분석하였다. 미세먼지 태도(β=0.52, p<.001)가 미세먼지 행위에 유의한 영향을 나타내었으며, 설명력은 31%이었다(F=15.19, p<.001). 미세먼지 교육 경험(β=0.08, p=.157), 부의 학력(β=0.08, p=.288), 모의 학력(β=0.05, p=.463), 미세먼지 지식(β=-0.05, p=.415), 동거 가족(β=-0.09, p=.126), 학교 성적(β=-0.02, p=.710)은 미세먼지 행위에 유의한 영향을 미치지 않았다. 청소년을 위한 미세먼지 행위를 높이기 위한 프로그램 개발 시 미세먼지 태도를 증진시키기 위한 방안 마련이 필요하다.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2023년도 가을학술발표대회논문집
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• pp.201-202
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• 2023

Now, there are many cases where materials are maintained at construction sites or standard construction prices are not in accordance with the applicable regulations, resulting in a lot of fine dust. Therefore, a particulate matter measurement system is applied not only to manage particulate matter at construction sites but also to reduce particulate matter .This study aims to evaluate the applicability of this particulate matter measurement system to the construction site through long-term measurement experiments using a light scattering method particulate matter measurement instrument at the construction site.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2019년도 춘계학술대회
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• pp.540-542
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• 2019

미세먼지로 인한 대기오염 및 인체 영향에 대한 많은 발표로 인해 미세먼지 예보는 많은 대중의 관심을 받고 있다. 이로 인해 통계 모델링 기법과 함께 기계학습 기법을 사용하여 미세먼지 예보 정확도를 올리기 위한 다양한 노력이 수행되고 있다. 본 논문에서는 미세먼지 예측을 위해 다층 퍼셉트론 신경망을 활용한 미세먼지 AQI 지수 예측을 수행한다. 이를 위해 다수의 연구에서 공통적으로 사용된 기상 인자와 미세먼지 농도값을 이용하여 예측 모델을 설계하고 4단계의 미세먼지 AQI 예측 정확도를 비교한다.

• 한국구조물진단유지관리공학회 논문집
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• 제25권5호
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• pp.86-93
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• 2021

미세먼지를 제거하기 위하여 미세먼지 제거 기능성 건설자재가 개발되고 있다. 그러나 미세먼지 제거율 평가 방법 및 기반 시설은 국내에 전무한 실정이다. 따라서 본 연구에서는 입자상 미세먼지 제거 성능을 평가하기 위해 미세먼지 제거율 시험 챔버를 구축하고 입자상 미세먼지 제거율 평가 방법을 제시하는 것을 목적으로 하였다. 결과적으로 건설자재는 미세먼지가 발생하는 환경에서 유효성을 가지기 때문에, 시험 입자 주입 단계 구간를 비교 대상으로 제안하였다. 미세먼지 주입 단계에서 측정한 모든 질량농도값에서 선형 회귀 분석으로 얻어진 기울기값을 상대 비교함으로써 미세먼지 제거율 평가를 제안하였다. 본 방법은 모든 측정값을 대상으로 하고 측정값 변동성에 대한 평가를 결정계수(R²)로 평가할 수 있어서 미세먼지 제거율 결과값의 신뢰성을 확보할 수 있다.

• 한국환경보건학회지
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• 제46권6호
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• pp.719-725
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• 2020

Objectives: With the growth of national interest in fine particulate matter, many complaints about pollutants emitted from air pollution emitting facilities have arisen in recent years. In particular, it is thought that a large volume of particulate pollutants are discharged from workplaces that use Solid Refuse Fuel (SRF). Therefore, particulate contaminants generated from SRF were measured and analyzed in this study in terms of respective particle sizes. Methods: In this study, particulate matter in exhaust gas was measured by applying US EPA method 201a using a cyclone. This method measures Filterable Particulate Matter (FPM), and does not consider the Condensable Particulate Matter (CPM) that forms particles in the atmosphere after being discharged as a gas in the exhaust gas. Results: The mass concentration of Total Suspended Particles (TSP) in the four SRF-using facilities was 1.16 to 11.21 mg/Sm3, indicating a very large concentration deviation of about 10 times. When the fuel input method was the continuous injection type, particulate matter larger than 10 ㎛ diameter showed the highest particle size fraction, followed by particulate matter smaller than 10 ㎛ and larger than 2.5 ㎛, and particulate matter of 2.5 ㎛ or less. Contrary to the continuous injection type, the batch injection type had the smallest particle size fraction of particulate matter larger than 10 ㎛. The overall particulate matter decreased as the operating load factor decreased from 100% to 60% at the batch input type D plant. In addition, as incomplete combustion significantly decreased, the particle size fraction also changed significantly. Both TSP and heavy metals (six items) satisfied the emissions standards. The measured value of the emission factor was 38-99% smaller than the existing emissions factor. Conclusions: In the batch injection facility, the particulate matter decreased as the operating load factor decreased, as did the particle size fraction of the particulate matter. These results will help the selection of effective methods such as reducing the operating load factor instead of adjusting the operating time during emergency reduction measures.

• Journal of Korean Biological Nursing Science
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• 제20권1호
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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.