• Environmental Analysis Health and Toxicology
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• 제13권1_2호
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• pp.27-31
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• 1998

Motor vehicle exhaust is the major cause to the air contamination in Seoul. It includes many toxic chemicals to human health such as aidehyde, PAHs, benzene, xylene, toluene, benzo[a]pyrene, nickel, arsenic and cadmium in gasoline exhaust and formaldehyde, PAHs, 1,3-butadiene, benzene and particulate matter in diesel exhaust. Some chemicals out of them are classified as a human carcinogen. Many large diesel vehicles such as buses and trucks are drivened frequently in Seoul so that the air in Seoul is seriously contaminated by diesel exhaust, especially particulate matter. The amounts of particulate matter from large diesel vehicles may be estimated to be more than 50% of small dust in Seoul. The particles of particulate matter are coated with many toxic chemicals and some of these are considered as a human carcinogen. The cancer risk has to be throughly managed because the population density of Seoul is very high. Government should list hazardous air pollutants in Seoul, assess the exposure of people to toxic pollutants, especially carcinogens and manage human health risk.

• 한국입자에어로졸학회지
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• 제16권1호
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• pp.9-17
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• 2020

The characteristics of particulate matter made from daily cooking at a Korean residential apartment house with three dwellers had been investigated for about 3 months. All data were recorded by an optical particle counter every minute at the kitchen. Types of cooking such as boiling, frying, and grilling that performed in the house were listed. Boiling only was used in 32% cases among total 234 meals. Frying and grilling were 14% and 11%, respectively. From an initial indoor particulate matter smaller than 10 ㎛ in diameter, the increases due to cooking are reported by size. In case of boiling, PM at 1-10 ㎛ size and under 1 ㎛ size little increased. Normally, particles from oil or combustion in a process of frying or grilling increased indoor PM. In a case of grilling, particle mass concentration in a region of 1-10 ㎛ in diameter increased as much as 295 ㎍/㎥. Mass concentration of particles smaller than 1 ㎛ increased as much as 33 ㎍/㎥.

• 한국독성학회:학술대회논문집
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• 한국독성학회 2003년도 추계학술대회
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• pp.153-153
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• 2003

It has been reported that exposure to particulate matter is linked to increase lung cancer risk. Recently it is confirmed that diesel exhaust particulate matter (DEP), which derives from diesel powered vehicles, is contributed as a major pollutant in urban air-borne particulate matter.(omitted)

• Communications for Statistical Applications and Methods
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• 제25권6호
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• pp.619-631
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• 2018

Functional data analysis continues to attract interest because advances in technology across many fields have increasingly permitted measurements to be made from continuous processes on a discretized scale. Particulate matter is among the most harmful air pollutants affecting public health and the environment, and levels of PM10 (particles less than 10 micrometers in diameter) for regions of California remain among the highest in the United States. The relatively high frequency of particulate matter sampling enables us to regard the data as functional data. In this work, we investigate the dominant modes of variation of PM10 using functional data analysis methodologies. Our analysis provides insight into the underlying data structure of PM10, and it captures the size and temporal variation of this underlying data structure. In addition, our study shows that certain aspects of size and temporal variation of the underlying PM10 structure are associated with changes in large-scale climate indices that quantify variations of sea surface temperature and atmospheric circulation patterns.

• Fisheries and Aquatic Sciences
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• 제27권2호
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• pp.111-121
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• 2024

Particulate matter (PM) is a mixture of microscopic solid inhalable particles including airborne liquid droplets, and it is implicated with several diseases. The eye does not have a protective barrier among the human organs, consequently it get directly exposed to environmental substances such as PM. The scarcity of treatments for damage to the eyesight and the vision and eye structure being closely related to the structure and function of the central nervous system highlights the cruciality of novel therapeutics. In this study was conducted using in vivo zebrafish vertebrate model which is a useful model due to the conserved genes between human. We found that protective effect of Octopus minor extract against particulate matter-induced adverse effects on eye development in zebrafish (Danio rerio) embryos by regulating antioxidant and anti-inflammatory mRNA expression.

• 한국대기환경학회:학술대회논문집
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• 한국대기환경학회 2006년도 추계학술대회 논문집
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• pp.169-170
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• 2006

• Elastomers and Composites
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• 제58권4호
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• pp.161-172
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• 2023

Because particulate matter has emerged as a major contributor to air pollution, the tire industry has conducted studies to reduce particulate matters from tires by improving tire performance. In this study, we compared the conventional blending method, in which rubber, filler, and additives are mixed simultaneously, to the Y-blending method, in which masterbatches are blended. We manufactured carbon black (CB)-filled natural rubber (NR)/butadiene rubber (BR) blend and silica-filled epoxidized NR/BR blend compounds to compare the effects of the two blending methods on the physical properties of the compounds and the amount of particulate matter generated. The Y-blending method provided uniform filler distribution in the heterogeneous rubber matrix, improved processability, and exhibited low rolling resistance. This method also improved physical properties owing to the excellent filler-rubber interaction. The results obtained from measuring the generation of particulate matter indicated that, the Y-blending method reduced PM_2.5 particulate matter generation from the CB-filled and silica-filled compounds by 38% and 60%, and that of PM₁₀ by 29% and 67%, respectively. This confirmed the excellence of the Y-blending method regarding the physical properties of truck bus radial tire tread compounds and reduced particulate matter generated.

• 한국환경독성학회:학술대회논문집
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• 한국환경독성학회 2003년도 춘계학술대회
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• pp.195-195
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• 2003

It is well known that diesel exhaust particulate matter contains mutagenic PAHs, such as benzo[${\alpha}$]pyrene, benz[${\alpha}$]anthracene, chrysene, etc. Therefore it is suspected that these chemicals act on estrogen receptor and reveal endocrine-disrupting effects. Recent attention has focused on causative chemicals of endocrine-disrupting effects. We examined the estrogenic activity of respirable diesel exhaust particulate matter derived from diesel powered vehicle. PM2.5 diesel exhaust of vehicle was collected using a high volume sampler equipped with a cascade impactor. Diesel exhaust samples were fractionated according to EPA methods. The presence of estrogenic and antiestrogenic chemicals in PM 2.5 diesel exhaust was determined using E-screen assay. To quantitatively assess the estrogenic and antiestrogenic activities in diesel exhaust particulate matter, estradiol equivalent concentration (bio-EEQ) was calculated by comparing the concentration response curve of the sample with those of the estrogen calibration curve. Weak estrogenic activities and strong antiestrogenic activities were detected in the crude extract and moderately polar fractions. Higher antiestrogenic potency was observed with higher EROD activities in aliphatic and aromatic compounds fraction. In conclusion, estrogenic/antiestrogenic-like activities were present in diesel exhaust particulate matter. However, the health consequences of this observation was unknown, the presence of these activities may contribute to and exacerbate adverse health effect evoked by diesel exhaust particulate matter.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2018년도 추계학술대회
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• pp.620-622
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• 2018

미세먼지에 대한 인체 영향에 관한 사회적 관심이 높아짐에 따라 미세먼지 예측 알고리즘의 필요성이 증가되었다. 많은 연구에서 기상 데이터를 이용하여 통계 모델링 및 기계 학습 기법 기반 예측 모델이 제안되었으나, 해당 모델의 환경 및 세부조건을 정확히 설정하기는 어렵다. 또한 국내 기상 측정소 데이터의 경우 누락된 데이터가 존재하여 새로운 예측 모델을 설계해야 할 필요성이 있다. 본 논문에서는 미세먼지 예측을 위한 선행 연구로서 다층 퍼셉트론 신경망을 활용하여 미세먼지 예측을 수행한다. 이를 위해 측정소 3곳의 기상 데이터를 기반으로 예측 모델을 설계, 실제 데이터와의 비교를 통해 미세먼지 예측을 위한 알고리즘의 적합성을 평가한다.

• 디지털융복합연구
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• 제17권8호
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• pp.471-479
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• 2019

본 연구는 미세먼지 예방행동의도에 영향을 미치는 결정요인을 탐색하는 것을 목적으로 했다. 280명의 대학생들을 대상으로 한 설문조사 결과, 미세먼지에 대한 지각된 민감성과 지각된 장애는 예방행동의도에 통계적으로 유의한 영향을 미치지 못하였다. 그러나 미세먼지에 대한 지각된 심각성과 지각된 이익, 주관적 규범과 자기효능감은 예방행동의도에 통계적으로 유의한 긍정적 영향을 미치는 것으로 나타났다. 본 연구 결과를 통해 대학생들의 미세먼지 예방행동의도를 높이기 위해서는 지각된 심각성과 지각된 이익, 주관적 규범과 자기효능감을 높일 수 있는 커뮤니케이션 전략이 요구되며, 향후 미세먼지와 같은 환경위험에 대한 예방행동을 설명하는데 있어 일정 부분 기여할 것으로 판단된다.