• Journal of Preventive Medicine and Public Health
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• 제49권4호
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• pp.205-219
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• 2016

Objectives: No children-specified review and meta-analysis paper about the short-term effect of fine particulate matter ($PM_{2.5}$) on hospital admissions and emergency department visits for asthma has been published. We calculated more precise pooled effect estimates on this topic and evaluated the variation in effect size according to the differences in study characteristics not considered in previous studies. Methods: Two authors each independently searched PubMed and EMBASE for relevant studies in March, 2016. We conducted random effect meta-analyses and mixed-effect meta-regression analyses using retrieved summary effect estimates and 95% confidence intervals (CIs) and some characteristics of selected studies. The Egger's test and funnel plot were used to check publication bias. All analyses were done using R version 3.1.3. Results: We ultimately retrieved 26 time-series and case-crossover design studies about the short-term effect of $PM_{2.5}$ on children's hospital admissions and emergency department visits for asthma. In the primary meta-analysis, children's hospital admissions and emergency department visits for asthma were positively associated with a short-term $10{\mu}g/m^3$ increase in $PM_{2.5}$ (relative risk, 1.048; 95% CI, 1.028 to 1.067; $I^2=95.7%$). We also found different effect coefficients by region; the value in Asia was estimated to be lower than in North America or Europe. Conclusions: We strengthened the evidence on the short-term effect of $PM_{2.5}$ on children's hospital admissions and emergency department visits for asthma. Further studies from other regions outside North America and Europe regions are needed for more generalizable evidence.

• 해양환경안전학회지
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• 제27권6호
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• pp.898-904
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• 2021

본 연구에서는 강화되는 황산화물 및 입자상물질의 배출규제를 만족시키기 위한 후처리장치로 습식전기집진기에 대한 실험적 연구를 수행하였다. 실험을 위해 선박용 중유(HFO, 황함유량 약 2.1%)를 연료로 사용하는 선박용 4행정 디젤엔진(STX-MAN B&W)을 활용하였으며, 연돌에 설치된 습식전기집진기 입/출구에서 측정을 실시하였다. 미세먼지 측정을 위해서는 광학식 계측기(OPA-102) 및 중량농도측정방식(Method 5 Isokinetic Train)을 이용하였으며, 황산화물 계측을 위해서는 FT-IR(DX-4000)을 사용하였다. 엔진부하는 50%, 75%, 100%로 변화시키면서 실험을 실시하였다. 실험 결과로, 엔진부하가 50%에서 100%로 변화함에 따라 미세먼지 저감 효율은 모든 부하 조건에서 94~98% 정도의 높은 저감 효율을 나타내었다. 추가적으로 습식전기집진기 퀜칭존에서 배기가스의 온도를 낮추는 과정 중 세정액에 의한 이산화황(SO₂) 저감을 확인할 수 있었으며, 저감율은 엔진부하에 따라 55%~81%로 확인되었다.

• 대한화장품학회지
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• 제47권1호
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• pp.75-84
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• 2021

본 연구에서는 3 개의 아미노산으로 이루어진 트리펩타이드의 미세먼지에 의한 인간각질형성세포의 손상 억제 효과에 대해 확인하였다. 실험 결과 트리펩타이드 처리 시 미세먼지에 의한 세포 사멸이 억제되어 생존율 증가가 관찰되었으며, aryl hydrocarbon receptor (AhR) 기전 활성이 억제 되어 독성 대사체 생성과 염증반응에 관여하는 하위 인자인 cytochrome P450 family 1 subfamily A member 1 (CYP1A1) 및 cyclooxygenase-2 (COX-2)의 발현이 저해되었다. 또한 미세먼지에 의한 산화적 스트레스 억제 효과를 나타내어 염증성 사이토카인의 발현을 저해하였고, 피부 구성 단백질의 분해를 유도하는 matrix metalloproteinase-1 (MMP-1)의 발현을 저해하였으며, 세포 사멸 인자의 수준을 저해하였다. 이 결과를 종합해 볼 때, 본 연구의 트리펩타이드는 미세먼지에 의한 인간각질형성세포의 사멸 및 주변 피부 조직의 손상을 유도할 수 있는 기전들을 억제하여 보호 효과를 나타내는 것으로 보인다. 트리펩타이드의 이러한 안티폴루션 효과는 신규 기능성 화장품 소재로 응용될 수 있을 것으로 기대된다.

• 한국대기환경학회지
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• 제19권6호
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• pp.789-803
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• 2003

The purpose of this study is to compare the usefulness between Gaussian dispersion model and receptor model with the experimental result of the dispersion tracing of the particulate pollutants from Taean coal-fired power plants. For this purpose, the component analysis of the collected PM 10 samples was performed. In order to trace the pollution sources, factor analysis was done with the result of the component analysis. As a result of the correlativity analysis of the fifteen power plants' profiles offered by US EPA, the correlativity of No.11202 source profile showed highest rate up to 84.5%. Thus it was adopted as proper one and the contribution rate by each pollution source was calculated by Chemical Mass Balance (CMB)-8 model. The contribution rate, which was the effect rate of the power plants on each measuring point, were calculated with a range of 24∼52％ and the standard error was below 0.9 $\mu\textrm{g}$/㎥. This indicates the selection of the source profile was appropriate. Also, the concentrations of each point were calculated by the ISCST3 which is suggested by US EPA as one of the regulatory Gaussian dispersion model. The calculation result showed that the predicted concentration was 50∼58 $\mu\textrm{g}$/㎥, comparing with the measured result of 9∼65 $\mu\textrm{g}$/㎥. It was found that the concentration calculated by ISCST3 was underpredicted. It was thought that the receptor model was more favorable than the Gaussian dispersion model in estimating the effect of the particulate matter on a certain receptive point.

• 한국대기환경학회지
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• 제33권3호
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• pp.233-240
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• 2017

To distinguish between high particulate matter (HPM) and light Asian dust (LAD) events, aerosol optical properties from GOCI were investigated in Seoul from 2014 to 2016. The poor air quality case caused by fine atmospheric particulate matter (i.e., 80<$PM_{10}$<$400{\mu}g/m^3$) is clearly separated from the case of heavy Asian dust that generally shows the $PM_{10}$ concentration more than $400{\mu}g/m^3$. In this study, we have found eight cases for the poor air quality and divided them into the two events(i.e., HPM and LAD). In case of aerosol optical depth (AOD), there was no big difference between two events. However, Angstrom exponent (AE) for HPM events was greater than 1, while that for LAD events less than 1. As a result of comparing aerosol type, non-absorbing fine mode aerosols were dominant for HPM events, but coarse and absorbing coarse mode aerosols for LAD events. Therefore, AE and aerosol type from GOCI can be used to distinguish between two events effectively.

• Environmental Engineering Research
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• 제21권2호
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• pp.121-131
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• 2016

In most African urban areas, Particulate Matters (PM) concentration exceeds by far the WHO limits. In these areas, plants can play a key role in removing particles. In this study, we evaluated three ornamental species (Jatropha interrigima, Ficus benjamina, Barleria prionitis) used in Abidjan (Ivory Coast). Leaf-encapsulated saturation isothermal remnant magnetisation (SIRM) were measured and the relationship between PM captured and leaf wettability were done. The sampling were performed at roadsides and Parks. Firstly, Leaf-encapsulated and total leaf SIRM were quantified and the wettability was determined by drop contact angles (DCA). Secondly, the relationship between leaf SIRM and wettability was found. Results showed that leaf SIRM was two to ten times higher at roadsides than in Parks. Total leaf SIRM was also higher on mature leaves in Main roads suggesting a particle accumulation in leaves over time especially in waxy species (Ficus benjamina). This species encapsulated other than 20% of total leaf SIRM. All tested species were highly-wettable ($40^{\circ}$ < DCA < $90^{\circ}$). Thus, Jatropha interrigima with its leaf trichomes and F. benjamina with its leaf waxes were more wettable. A significantly positive correlation was found between wettability intensity and leaf SIRM.

• Journal of Preventive Medicine and Public Health
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• 제37권4호
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• pp.300-305
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• 2004

Objectives : The exposure to particulate air pollution during the pregnancy has reported to result in adverse pregnancy outcome such as low birth weight, preterm birth, still birth, and intrauterine growth retardation (IUGR). We aim to assess whether prenatal exposure of particulate matter less than 10 (m in diameter ($PM_{10}$) is associated with preterm birth in Seoul, South Korea. Methods : We included 382,100 women who delivered a singleton at 25-42 weeks of gestation between 1998 and 2000. We calculated the average PM10 exposures for each trimester period and month of pregnancy, from the first to the ninth months, based on the birth date and gestational age. We used three different models to evaluate the effect of air pollution on preterm birth; the logistic regression model, the generalized additive logistic regression model, and the proportional hazard model. Results : The monthly analysis using logistic regression model suggested that the risks of preterm birth increase with PM10 exposure between the sixth and ninth months of pregnancy and the highest risk was observed in the seventh month (adjusted odds ratio=1.07, 95% CI=1.01-1.14). We also found the similar results using generalized additive model. In the proportional hazard model, the adjusted odds ratio for preterm births due to PM10 exposure of third trimester was 1.04 (95% CI=0.96-1.13) and PM10 exposure between the seventh month and ninth months of pregnancy was associated with the preterm births. Conclusions : We found that there were consistent results when we applied the three different models. These findings suggest that air pollution exposure during the third trimester pregnancy has an adverse effect on preterm birth in South Korea.

• 한국산학기술학회논문지
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• 제21권4호
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• pp.259-267
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• 2020

본 연구에서는 원하는 시간과 장소에서 데이터 수집이 용이한 드론에 미세먼지 측정 센서를 부착하여 3가지 측정환경인 건설현장, 자연환경(수목원), 주거지역에서 고도(30m, 60m, 90m, 120m, 150m)에 따른 미세먼지 농도를 측정하고 비교하였다. 건설현장 30m 지점의 PM_2.5와 PM₁₀ 측정값은 각각 18.63㎍/㎥, 24.23㎍/㎥, 150m 지점의 PM_2.5와 PM₁₀ 측정값은 각각 10.89㎍/㎥, 10.61㎍/㎥로 고도가 높아질수록 평균 농도가 낮아지는 것으로 나타났다. 자연환경(수목원) 30m 지점의 PM_2.5와 PM₁₀ 측정값은 각각 9.03㎍/㎥, 11.21㎍/㎥, 150m 지점의 PM_2.5와 PM₁₀ 측정값은 각각 3.42㎍/㎥, 3.57㎍/㎥로 고도가 높아질수록 평균 농도가 낮아지는 것으로 나타났으나, 모든 지점의 PM_2.5와 PM₁₀ 측정값은 비슷한 것으로 나타났다. 주거지역 30m 지점의 PM_2.5와 PM₁₀ 측정결과는 각각 10.65㎍/㎥, 12.06㎍/㎥, 150m 지점의 PM_2.5와 PM₁₀의 측정값은 각각 4.24㎍/㎥, 5.17㎍/㎥로 고도가 높아질수록 대체적으로 PM_2.5와 PM₁₀농도가 낮아짐을 확인하였다. 주거지역의 경우 건설현장이나 수목원에 비해 교통량이 많은 도로에 인접해 있어 PM_2.5의 농도가 PM₁₀의 농도보다 높게 나온 것으로 사료된다. 세 대상지 모두 고도가 상승할수록 PM_2.5와 PM₁₀의 농도가 감소하는 추세를 보였다. 또한, 건설현장, 주거지역, 자연환경(수목원) 순으로 PM_2.5와 PM₁₀의 농도가 높은 것으로 확인하였다. 본 연구의 결과는 토지이용별로 미세먼지 농도값을 고도별로 측정하였다는데 의의가 있으며, 지역계획이나 도시계획 등에서 중요한 공간의사결정 기초자료로 활용될 수 있을 것으로 사료된다.

• Journal of Forest and Environmental Science
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• 제33권2호
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• pp.113-121
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• 2017

In flight particulate matter particularly emissions generated by incomplete combustion processes has become a subject of global concern due to the health problems and environmental impacts associated with them. This has compelled most countries to set standards for coarse and fine particles due to their conspicuous impacts on environment and public health. This contribution therefore explores forest fire emissions and how its particulates affects air quality, damage to vegetation, water bodies and biological functions as architects for lung diseases and other degenerative illnesses such as oxidative stress and aging. Soot was collected from simulated forest fire using a clean glass surface and carefully transferred into amber vials for analysis. Volatile components of soot were collected over 10 mL dichloromethane and analyzed using a QTOF Premier-Water Corp Liquid Chromatography hyphenated to a mass selective detector (MSD), and Gas Chromatograph coupled to a mass spectrometer (GC-MS). To characterize the size and surface morphology of soot, a scanning electron microscope (SEM) was used. The characterization of molecular volatiles from simulated forest fire emissions revealed long chain compounds including octadec-9-enoic acid, octadec-6-enoic acid, cyclotetracosane, cyclotetradecane, and a few aromatic hydrocarbons (benzene and naphthalene). Special classes of organics (dibenzo-p-dioxin and 2H-benzopyran) were also detected as minor products. Dibenzo-p-dioxin for instance in chlorinated form is one of the deadliest environmental organic toxins. The average particulate size of emissions using SEM was found to be $11.51{\pm}4.91{\mu}m$. This study has shown that most of the emissions from simulated forest fire fall within $PM_{10}$ particulate size. The molecular by-products of forest fire and particulate emissions may be toxic to both human and natural ecosystems, and are possible precursors for various respiratory ailments and cancers. The burning of a forest by natural disasters or man-made fires results in the destruction of natural habitats and serious air pollution.

• 지능정보연구
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• 제28권1호
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• pp.329-352
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• 2022

미세먼지는 폐나 혈관에 침투해 각종 심장 질환이나 폐암 등의 호흡기 질환을 일으키는 것으로 보고되고 있다. 지하철은 일 평균 천만 명이 이용하는 교통수단으로, 깨끗하고 쾌적한 환경조성이 중요하나 지하터널을 통과하는 지하철의 운행 특성과 터널에 갇힌 미세먼지가 열차 풍으로 인해 지하역사로 이동하는 등의 문제로 지하역사의 미세먼지 오염도는 높은 것으로 나타나고 있다. 환경부와 서울시는 지하역사 공기질 개선대책을 수립하여 다양한 미세먼지 저감 노력을 기울이고 있다. 스마트 공기질 관리 시스템은 공기질 데이터 수집 및 미세먼지 농도를 예측하여 공기질을 관리하는 시스템으로 미세먼지 농도 예측 모델이 중요한 구성 요소이다. 그동안 시계열 데이터 예측에 관한 다양한 연구가 진행되어왔지만, 지하철 역사의 미세먼지 농도 예측과 관련해서는 통계나 순환신경망 기반의 딥러닝 모델 연구에 국한되어 있다. 이에 본 연구에서는 시공간 트랜스포머를 포함한 4개의 트랜스포머 기반 모델을 제안한다. 서울시 지하철 역사의 대합실을 대상으로 한 시간 후의 미세먼지 농도 예측실험을 수행한 결과, 트랜스포머 기반 모델들의 성능이 기존의 ARIMA, LSTM, Seq2Seq 모델들에 비해 우수한 성능을 나타냄을 확인하였다. 트랜스포머 기반 모델 중에서는 시공간 트랜스포머의 성능이 가장 우수하였다. 데이터 기반의 예측을 통하여 운영되는 스마트 공기질 관리 시스템은 미세먼지 예측의 정확도가 향상될수록 더욱더 효과적이고 에너지 효율적으로 운영될 수 있다. 본 연구 결과는 스마트 공기질 관리 시스템의 효율적 운영에 기여할 수 있을 것으로 기대된다.