• 한국대기환경학회지
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• 제22권5호
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• pp.564-573
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• 2006

This study was performed to examine the effect of particulate matter less than 10 ${\mu}m$ in diameter($PM_{10}$) on respiratory-related admission in Seoul, 1999. Daily counts of respiratory-related admission were analyzed by generalized additive model with adjustment for effects of air temperature, humidity, and day of the week as confounders in a nonparametric approach. The results follow associations between $PM_{10}$ and asthma, acute upper respiratory disease, acute lower respiratory disease, pneumonia, and chronic respiratory disease. The relative risks were 1.30(95% CI=1.14$\sim$1.50) for pneumonia, 1.18(95% CI=1.01$\sim$1.37) for acute lower respiratory disease in less than 15 years, respectively. The relative risks were 1.85(95% CI=1.22$\sim$2.81) for acute lower respiratory disease, 1.28(95% CI=1.04$\sim$1.57) for asthma, 1.25(95% CI=1.01$\sim$1.54) for pneumonia and 1.19(95% CI=1.01$\sim$1.41) for acute upper respiratory disease in 15 to 64 years, respectively The relative risks were 1.54(95% CI=1.15$\sim$2.08) for asthma, 1.38(95% CI=1.06$\sim$l.80) for chronic respiratory disease in more than 65 years, respectively. The study showed that $PM_{10}$ was considerably affects daily counts of respiratory-related admission in Seoul, 1999 Statistically significant associations were mostly found in the adult group like If to 64 years. The highly relative risks come out in the elderly.

• 청정기술
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• 제26권4호
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• pp.293-303
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• 2020

세계보건기구에 따르면 대기오염은 건강에 대한 주요 위험원으로 대기오염으로 인해 매년 약 700만 명의 조기 사망이 발생하고 있다. 이산화황(SO2)은 대표적인 대기오염물질로 황 성분이 포함된 연료의 연소에서 다량 발생한다. SO2 발생량을 감소시키기 위해서는 대형 연소 환경에서 이를 실시간으로 정밀하게 측정하고 측정 값을 바탕으로 저감 설비를 최적화하는 과정이 필요하다. 이 논문에서는 미세먼지 전구물질인 SO2의 농도를 측정하기 위해 파장 가변형 다이오드 레이저 흡수 분광법 중 파장 변조 분광법을 이용하였다. 광원으로는 7.6 ㎛ 양자 폭포 레이저를 사용하였고 7623.7 ~ 7626.0 nm 사이의 64개 다중 광흡수선으로 SO2 농도 측정이 가능함을 증명하였다. 실험은 1 atm, 296 K에서 28, 76 m multi-pass cell을 사용하여 수행되었다. SO2 농도는 고농도(1000 ~ 5000 ppm)와 저농도(10 ppm 이하)로 두 종류로 실험 하였다. 추가적으로 가스 셀 외에 레이저가 지나가는 경로에 질소를 채워 대기 중의 H2O가 SO2 측정에 미치는 영향을 확인하였다. SO2는 3 ppm까지 측정하였고 측정된 SO2 농도는 전기 화학식 센서와 NDIR 센서 측정 결과와 비교되었다.

• 한국환경보건학회지
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• 제48권2호
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• pp.66-74
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• 2022

Background: The health effects of particulate matter (PM_2.5) bonded with various harmful chemicals differ based on their composition, so investigating and managing their concentrations and composition is vital for long-term management. As industrial complexes emit considerable quantities of pollutants, higher PM_2.5 concentrations and chemical component effects are expected than in other places. Objectives: We investigated the concentration distribution ratios of PM_2.5 chemical components to provide basic data to inform future major emissions control and PM_2.5 reduction measures in industrial complexes. Methods: We monitored five sites near the Ansan and Siheung industrial complexes from August 2020 to July 2021. Samples were collected and analyzed twice per week in spring/winter and once per week in summer/autumn according to the National Institute of Environmental Research in the Ministry of Environments' Air Pollution Monitoring Network Installation and Operation Guidelines. We investigated and compared composition ratios of 29 ions, carbon, and elemental components in PM_2.5. Results: The analysis of PM_2.5 components at the five sites revealed that ion components accounted for the greatest total mass at approximately 50% while carbon components and elemental components contributed 23~28% and 8~10%, respectively. Among the ionic components, NO₃^- occupies the greatest proportion. OC occupies the greatest proportion of the carbon components and sulphur occupies the greatest proportion of elemental components. Conclusions: This study investigated the concentration distribution ratios of PM_2.5 chemical components in industrial complexes. We believe these results provide basic chemical component concentration ratio data for establishing future air management policies and plans for the Ansan and Siheung industrial complexes.

• 한국산업보건학회지
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• 제33권2호
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• pp.171-187
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• 2023

Objectives: Aircraft cabin cleaning work is characterized by being performed within a limited time in a narrow and enclosed space. The objective of this study was to evaluate the exposure levels to dust, ultra fine dust(PM2.5) and black carbon(BC) among aircraft cabin cleaners. Methods: Active personal air sampling for respirable dust(n=73) and BC(n=47) was conducted during quick transit cleaning(cabin general and vacuum-specific) and seat cover replacement and total dust and PM2.5 were area-air-sampled as well. Also, size distribution of particle was identified with the cleaning workers targeted. Dusts were collected with PVC filters using gravimetric analysis. The concentration of PM2.5 and the particle size distribution were measured with real-time direct reading portable equipment using light scattering analysis. The concentration of BC was measured by aethalometer(filter-based real-time light absorption analysis instrument). Results: The geometric mean of respirable dust was the highest at vacuum cleaning as 74.4 ㎍/m³, following by replacing seat covers as 49.3 ㎍/m³ and cabin general cleaning as 47.8 ㎍/m³ . The arithmetic mean of PM2.5 was 4.83 ~ 9.89 ㎍/m³ inside the cabin, and 28.5~44.5 ㎍/m³ outside the cabin(from bus and outdoor waiting space). From size distribution, PM_2.5/PM₁₀ ratio was 0.54 at quick transit cleaning and 0.41 at replacing seat covers. The average concentration of BC was 2~7 ㎍/m³, showing a high correlation with the PM2.5 concentration. Conclusions: The hazards concentration levels of aircraft cabin cleaners were very similar to those of roadside outdoor workers. As the main source of pollution is estimated to be diesel vehicles operating at airports, and it is necessary to replace older vehicles, strengthen pollutant emission control regulations, and introduce electric vehicles. In addition, it is necessary to provide as part of airport-inftastructure a stable standby waiting space for aircraft cabin cleaners and introduce a systematic safety and health management system for all workers in the aviation industry.

• 생명과학회지
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• 제32권4호
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• pp.310-317
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• 2022

최근 인체에 유해한 요인으로 대기오염의 주성분인 미세먼지에 대한 관심이 증가하고 있다. 특히 직경이 2.5 ㎛ 미만인 PM_2.5는 인간의 폐 상피세포에서 자가포식을 동반한 산화적 스트레스를 유발하는 것으로 알려져 있다. 그러나 PM_2.5가 산화적 스트레스 하에서 자가포식을 증가시키는지와 이 과정이 ROS 의존적인지에 대한 연구는 충분하지 않은 실정이다. 본 연구에서는 PM_2.5가 인간 폐 상피 A594 세포에서 ROS 생성을 통해 자가포식을 촉진하는지를 조사하였다. 우리의 결과에 의하면, PM_2.5와 H₂O₂를 함께 처리한 세포에서는 각각이 단독 처리된 세포에 비하여 세포 생존력이 유의적으로 감소하였으며, 이는 전체 및 미토콘드리아 ROS 생성의 증가와 관련이 있었다. 또한, PM_2.5와 H₂O₂의 동시 처리는 Cyto-ID 염색을 통해 확인된 바와 같이 자가포식 유도의 증가와 LC3, p62 및 beclin 1과 같은 자가포식 바이오 마커 단백질의 발현을 증가시켰다. 그러나 NAC의 전처리에 의하여 ROS의 생성을 인위적으로 차단하였을 경우, PM_2.5와 H₂O₂의 동시 처리에 의한 세포 생존율의 감소와 자가포식 유도는 현저하게 억제되었다. 따라서, PM_2.5에 의해 유도된 ROS 생성이 A549 세포에서 자가포식 유도에 중요한 역할을 할 것으로 추측되며, 이는 PM_2.5에 의해 유도될 수 있는 폐 기능 손상이 산화적 스트레스 하에서 더욱 증가할 수 있음을 의미한다.

• 환경위생공학
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• 제24권4호
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• pp.1-26
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• 2009

We conclude the following with air pollution data measured from city measurement net administered and managed in Gwangju for the last 7 years from January in 2001 to December in 2007. In addition, some major statistics governed by Gwangju city and data administered by Gwangju as national official statistics obtained by estimating the amount of national air pollutant emission from National Institute of Environmental Research were used. The results are as follows ; 1. The distribution by main managements of air emission factory is the following ; Gwangju City Hall(67.8%) > Gwangsan District Office(13.6%) > Buk District Office(9.8%) > Seo District Office(5.5%) > Nam District Office(3.0%) > Dong District Office(0.3%) and the distribution by districts of air emission factory ; Buk District(32.8%) > Gwangsan District(22.4%) > Seo District(21.8%) > Nam District(14.9%) > Dong District(8.1%). That by types(Year 2004~2007 average) is also following ; Type 5(45.2%) > Type 4(40.7%) > Type 3(8.6%) > Type 2(3.2%) > Type 1(2.2%) and the most of them are small size of factory, Type 4 and 5. 2. The distribution by districts of the number of car registrations is the following ; Buk District(32.8%) > Gwangsan District(22.4%) > Seo District(21.8%) > Nam District(14.9%) > Dong District(8.1%) and the distribution by use of car fuel in 2001 ; Gasoline(56.3%) > Diesel(30.3%) > LPG(13.4%) > etc.(0.2%). In 2007, there was no ranking change ; Gasoline(47.8%) > Diesel(35.6%) > LPG(16.2%) >etc.(0.4%). The number of gasoline cars increased slightly, but that of diesel and LPG cars increased remarkably. 3. The distribution by items of the amount of air pollutant emission in Gwangju is the following; CO(36.7%) > NOx(32.7%) > VOC(26.7%) > SOx(2.3%) > PM-10(1.5%). The amount of CO and NOx, which are generally generated from cars, is very large percentage among them. 4. The distribution by mean of air pollutant emission(SOx, NOx, CO, VOC, PM-10) of each county for 5 years(2001~2005) is the following ; Buk District(31.0%) > Gwangsan District(28.2%) > Seo District(20.4%) > Nam District(12.5%) > Dong District(7.9%). The amount of air pollutant emission in Buk District, which has the most population, car registrations, and air pollutant emission businesses, was the highest. On the other hand, that of air pollutant emission in Dong District, which has the least population, car registrations, and air pollutant emission businesses, was the least. 5. The average rates of SOx for 5 years(2001~2005) in Gwangju is the following ; Non industrial combustion(59.5%) > Combustion in manufacturing industry(20.4%) > Road transportation(11.4%) > Non-road transportation(3.8%) > Waste disposal(3.7%) > Production process(1.1%). And the distribution of average amount of SOx emission of each county is shown as Gwangsan District(33.3%) > Buk District(28.0%) > Seo District(19.3%) > Nam District(10.2%) > Dong District(9.1%). 6. The distribution of the amount of NOx emission in Gwangju is shown as Road transportation(59.1%) > Non-road transportation(18.9%) > Non industrial combustion(13.3%) > Combustion in manufacturing industry(6.9%) > Waste disposal(1.6%) > Production process(0.1%). And the distribution of the amount of NOx emission from each county is the following ; Buk District(30.7%) > Gwangsan District(28.8%) > Seo District(20.5%) > Nam District(12.2%) > Dong District(7.8%). 7. The distribution of the amount of carbon monoxide emission in Gwangju is shown as Road transportation(82.0%) > Non industrial combustion(10.6%) > Non-road transportation(5.4%) > Combustion in manufacturing industry(1.7%) > Waste disposal(0.3%). And the distribution of the amount of carbon monoxide emission from each county is the following ; Buk District(33.0%) > Seo District(22.3%) > Gwangsan District(21.3%) > Nam District(14.3%) > Dong District(9.1%). 8. The distribution of the amount of Volatile Organic Compound emission in Gwangju is shown as Solvent utilization(69.5%) > Road transportation(19.8%) > Energy storage & transport(4.4%) > Non-road transportation(2.8%) > Waste disposal(2.4%) > Non industrial combustion(0.5%) > Production process(0.4%) > Combustion in manufacturing industry(0.3%). And the distribution of the amount of Volatile Organic Compound emission from each county is the following ; Gwangsan District(36.8%) > Buk District(28.7%) > Seo District(17.8%) > Nam District(10.4%) > Dong District(6.3%). 9. The distribution of the amount of minute dust emission in Gwangju is shown as Road transportation(76.7%) > Non-road transportation(16.3%) > Non industrial combustion(6.1%) > Combustion in manufacturing industry(0.7%) > Waste disposal(0.2%) > Production process(0.1%). And the distribution of the amount of minute dust emission from each county is the following ; Buk District(32.8%) > Gwangsan District(26.0%) > Seo District(19.5%) > Nam District(13.2%) > Dong District(8.5%). 10. According to the major source of emission of each items, that of oxides of sulfur is Non industrial combustion, heating of residence, business and agriculture and stockbreeding. And that of NOx, carbon monoxide, minute dust is Road transportation, emission of cars and two-wheeled vehicles. Also, that of VOC is Solvent utilization emission facilities due to Solvent utilization. 11. The concentration of sulfurous acid gas has been 0.004ppm since 2001 and there has not been no concentration change year by year. It is considered that the use of sulfurous acid gas is now reaching to the stabilization stage. This is found by the facts that the use of fuel is steadily changing from solid or liquid fuel to low sulfur liquid fuel containing very little amount of sulfur element or gas, so that nearly no change in concentration has been shown regularly. 12. Concerning changes of the concentration of throughout time, the concentration of NO has been shown relatively higher than that of $NO_2$ between 6AM~1PM and the concentration of $NO_2$ higher during the other time. The concentration of NOx(NO, $NO_2$) has been relatively high during weekday evenings. This result shows that there is correlation between the concentration of NOx and car traffics as we can see the Road transportation which accounts for 59.1% among the amount of NOx emission. 13. 49.1~61.2% of PM-10 shows PM-2.5 concerning the relationship between PM-10 and PM-2.5 and PM-2.5 among dust accounts for 45.4%~44.5% of PM-10 during March and April which is the lowest rates. This proves that particles of yellow sand that are bigger than the size $2.5\;{\mu}m$ are sent more than those that are smaller from China. This result shows that particles smaller than $2.5\;{\mu}m$ among dust exist much during July~August and December~January and 76.7% of minute dust is proved to be road transportation in Gwangju.

• Asian Journal of Atmospheric Environment
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• 제8권1호
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• pp.35-47
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• 2014

The purpose of the study is to evaluate the pollution level (gaseous and particle phase) in the public facilities for the PAHs, non-regulated materials, forecast the risk level by the health risk assessment (HRA) and propose the guideline level. PAH assessments through sampling of particulate matter of diameter < 2.5 ${\mu}m$ ($PM_{2.5}$). The user and worker exposure scenario for the PAHs consists of 24-hour exposure scenario (WIES) assuming the worst case and the normal exposure scenario (MIES) based on the survey. This study investigated 20 PAH substances selected out of 32 substances known to be carcinogenic or potentially carcinogenic. The risk assessment applies major toxic equivalency factor (TEF) proposed from existing studies and estaimates individual Excess Cancer Risk (ECR). The study assesses the fine dusts ($PM_{2.5}$) and the exposure levels of the gaseous and particle PAH materials for 6 spots in each 8 facility, e.g. underground subway stations, child-care facilities, elderly care facilities, super market, indoor parking lot, terminal waiting room, internet caf$\acute{e}$ (PC-rooms), movie theater. For internet caf$\acute{e}$ (PC-rooms) in particular, that marks the highest $PM_{2.5}$ concentration and the average concentration of 10 spots (2 spots for each cafe) is 73.3 ${\mu}g/m^3$ (range: 6.8-185.2 ${\mu}g/m^3$). The high level of $PM_{2.5}$ seen in internet cafes was likely due to indoor smoking in most cases. For the gaseous PAHs, the detection frequency for 4-5 rings shows high and the elements with 6 rings shows low frequency. For the particle PAHs, the detection frequency for 2-3 rings shows low and the elements with 6 rings show high frequency. As a result, it is investigated that the most important PAHs are the naphthalene, acenaphthene and phenanthrene from the study of Kim et al. (2013) and this annual study. The health risk assessment demonstrates that each facility shows the level of $10^{-6}-10^{-4}$. Considering standards and local source of pollution levels, it is judged that the management standard of the benzo (a)pyrene, one of the PAHs, shall be managed with the range of 0.5-1.2 $ng/m^3$. Smoking and ventilation were considered as the most important PAHs exposure associated with public facility $PM_{2.5}$. This study only estimated for inhalation health risk of PAHs and focused on the associated cancer risk, while multiple measurements would be necessary for public health and policy.

• 생태와환경
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• 제38권3호통권113호
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• pp.372-381
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• 2005

본 연구는 PAC를 응집제로 사용한 가압부상법에 의한 부영양저수지의 수질과 퇴적물의 개선효과를 평가하기 수행되었다. 얕은 부영양 저수지에 설치한 mesocosm에서 (가로 ${\times}$ 세로 ${\times}$ 높이: 6 ${\times}$ 6 ${\times}$ 3 m), 입자성물질과 용존성물질의 변화와 노즐에 의한 퇴적물 교란 전 ${\cdot}$ 후의 퇴적물로부터 인용출률을 조사하였다. 부유물질 (SS)과 휘발성고형물의 제거효율은 각각 54.4 ${\sim}$ 71.2%와 57.3 ${\sim}$ 78.5%였다. 총인과 엽록소 a 농도는 제거효율은 각각 73.5 ${\sim}$ 91.5%, 53.7 ${\sim}$ 97.8% 였다. 생화학적 산소요구량은 86% 이상의 제거효율을 나타냈으나 화학적 산소요구량의 제거효율은 28.9 ${\sim}$ 62.8%로 낮았다. 조류의 성장에 쉽게 이용될 수 있는 용존무기인 (DIP)과 용존총인은 각각 34.1 ${\sim}$ 88.2%와 61.8 ${\sim}$ 87.6%의 제거효율을 나타냈다. 퇴적물 부상분리 전 호기적 조건과 혐기적 조건의 산소 환경에서 용존무기인 용출율은 각각 0.821 mg $m^{-2}$$day^{-1}$과 2.270 mg $m^{-2}$$day^{-1}$이였다. 반면에 부상분리 후에는 각각0.684 mg $m^{-2}$$day^{-1}$와 1.760 mg $m^{-2}$$day^{-1}$로 호기적 조건에서는 17%, 혐기적 조건에서는 23%정도의 감소효과를 나타냈다. 용존총인 용출율 또한 가압부상 후에 호기적 조건과 혐기적 조건에서 각각 33% (5.62 ${\to}$ 3.78 mg $m^{-2}$$day^{-1}$)와 20% (6.23 ${\to}$ 4.99 mg $m^{-2}$$day^{-1}$)의 감소가 나타났다. 이러한 결과들은 가압부상시 수체 내 입자상물질의 제거 뿐만 아니라 퇴적물로 부터의 인용출이 억제되므로 얕은 부영양 저수지의 수질개선을 위한 효과적인 대안이 될 수 있음을 제시한다.

• 대한교통학회지
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• 제34권5호
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• pp.377-393
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• 2016

차량배출가스는 대기오염을 유발하는 주요 요인인 것으로 알려져 있으며, 배출가스 감소를 위한 다양한 정책수립 및 기술개발이 활발히 진행 중이다. 이에 본 연구는 차량의 배출가스 중 호흡기 질환에 특히 유해한 것으로 알려진 질소산화물($NO_x$)과 초미세먼지($PM_{2.5}$)를 대상으로 시공간적 배출량의 패턴을 분석하고 교통기반 공공보건 증진 방안을 제시하였다. 서울외곽순환고속도로를 공간적 분석범위로 설정하고 2015년 1월부터 6월 사이에 수집된 속도와 교통량 자료를 기반으로 배출계수를 이용하여 거시적 모형을 통한 차량배출가스 발생 총량을 추정하였다. 추정된 배출가스 자료에 군집분석을 적용하여 차량배출가스 수준(Level of Vehicle Emission)을 정의하였으며, 평일 차량배출가스 발생량의 물질별 시간대별 공간별 패턴을 분석하였다. 이를 바탕으로 교통기반 공공보건 정책방안을 교통계획 및 교통시설물, 공공보건 정보, 교통운영 및 관리 측면으로 나누어 제시하였다. 본 연구에서 제시한 차량배출가스 분석방향 및 전략은 공공보건 정책 마련에 기여할 것으로 판단된다.

• 환경영향평가
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• 제27권6호
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• pp.717-726
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• 2018

미세먼지는 대기오염 중 심각한 질병을 야기할 수 있는 대기오염 원인물질이다. 이에 대부분의 연구는 위성영상을 활용하거나 모델링 기법을 이용하여 지역적 미세먼지 분포경향을 분석하였다. 하지만 측정소값을 기준으로 공간보간기법을 적용하여 분석하는 방법은 국내에서 부족한 실정이다. 본 연구에서는 서울시 39개의 미세먼지 측정망을 기준으로 2018년도 서울시의 1월, 2월, 3월, 4월 $PM_{10}$과 $PM_{2.5}$의 월별 공간적인 분포 변이를 분석하였다. 또한 본 연구를 통해 얻어진 분포도를 기반으로 $PM_{10}$과 $PM_{2.5}$의 차이값을 보여주는 분포도를 제작하였으며, $PM_{10}$의 배출량이 많은 지역과 $PM_{2.5}$의 배출량이 많은 지역을 선정하였다. 또한 $PM_{10}$과 $PM_{2.5}$의 분포를 비율로 계산하여 분포지도를 제작함으로 각 지역별 $PM_{10}$과 $PM_{2.5}$의 상호관계를 확인하였다. 본 연구는 공간분석 기법을 통하여 서울시 $PM_{10}$과 $PM_{2.5}$를 분석하는 공간적 분포변이 결과를 해석하였다. 본 연구의 결과 $PM_{10}$은 도로변 측정소에 높은 측정값을 나타내는 것을 확인할 수 있었다.