• 제목/요약/키워드: 초미세먼지(PM-2.5)

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국소환경 모델을 이용한 초미세먼지(PM2.5) 노출 기여율 평가 (Evaluation of PM2.5 Exposure Contribution Using a Microenvironmental Model)

  • 신지훈;최영태;김동준;민기홍;우재민;김동준;신정현;조만수;성경화;이종대;양원호
    • 한국환경보건학회지
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    • 제48권2호
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    • pp.59-65
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    • 2022
  • Background: Since people move through microenvironments rather than staying in one place, they may be exposed to both indoor and outdoor PM2.5 concentrations. Objectives: The aim of this study was to assess the exposure level of each sub-population group and evaluate the contribution rate of the major microenvironments. Methods: Exposure scenarios for sub-population groups were constructed on the basis of a 2019 Time-Use survey and the previous literature. A total of five population groups were classified and researchers wearing MicroPEM simulated monitoring PM2.5 exposure concentrations in real-time over three days. The exposure contribution for each microenvironment were evaluated by multiplying the inhalation rate and the PM2.5 exposure concentration levels. Results: Mean PM2.5 concentrations were 33.0 ㎍/m3 and 22.5 ㎍/m3 in Guro-gu and Wonju, respectively. When the exposure was calculated considering each inhalation rate and concentration, the home showed the highest exposure contribution rate for PM2.5. As for preschool children, it was 90.8% in Guro-gu, 94.1% in Wonju. For students it was 65.3% and 67.3%. For housewives it was 98.2% and 95.8%, and 59.5% and 91.7% for office workers. Both regions had higher exposure to PM2.5 among the elderly compared to other populations, and their PM2.5 exposure contribution rates were 98.3% and 94.1% at home for Guro-gu and Wonju, respectively. Conclusions: The exposure contribution rate could be dependent on time spent in microenvironments. Notably, the contribution rate of exposure to PM2.5 at home was the highest because most people spend the longest time at home. Therefore, microenvironments such as home with a higher contribution rate of exposure to PM2.5 could be managed to upgrade public health.

부스팅 기반 기계학습기법을 이용한 지상 미세먼지 농도 산출 (Estimation of Ground-level PM10 and PM2.5 Concentrations Using Boosting-based Machine Learning from Satellite and Numerical Weather Prediction Data)

  • 박서희;김미애;임정호
    • 대한원격탐사학회지
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    • 제37권2호
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    • pp.321-335
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    • 2021
  • 미세먼지 (PM10) 및 초미세먼지 (PM2.5)는 인체에 흡수 가능하여 호흡기 질환 및 심장 질환과 같이 인체건강에 악영향을 미치며, 심각할 경우 조기 사망에 영향을 줄 수 있다. 전 세계적으로 현장관측기반의 모니터링을 수행하고 있지만 미 관측지역에 대한 대기질 분포의 공간적인 한계점이 존재하여 보다 광범위한 지역에 대한 지속적이고 정확한 모니터링이 필요한 상황이다. 위성기반 에어로졸 정보를 사용함으로써 이러한 현장 관측자료의 한계점을 극복할 수 있다. 따라서 본 연구에서는 다양한 위성 및 모델자료를 활용하여 2019년도에 대해 한 시간 단위의 지상 PM10 및 PM2.5 농도를 추정하였다. GOCI 위성의 관측영역을 포함하는 동아시아 지역에 대해 트리 기반 앙상블 방법을 사용하는 Boosting 기법인 GBRTs (Gradient Boosted Regression Trees)와 LightGBM (Light Gradient Boosting Machine)을 활용하여 모델을 구축하였다. 또한, 기상변수 및 토지피복변수의 사용유무에 따른 모델의 성능을 비교하기 위해 두 가지 festure set으로 나누어 테스트하였다. 두 기법 모두 주요 변수인 AOD (Aerosol Optical Depth), SSA (Single Scattering Albedo), DEM (Digital Eelevation Model), DOY (Day of Year), HOD (Hour of Day)와 기상변수 및 토지피복변수를 함께 사용한 Feature set 1을 사용하였을 때 높은 정확도를 보였다. Feature set 1에 대해 GBRT 모델이 LightGBM에 비해서약 10%의 정확도 향상을 보였다. 가장 정확도가 높았던 기상 및 지표면 변수를 포함한 Feature set1을 사용한 GBRT기반 모델을 최종모델로 선정하였으며 (PM10: R2 = 0.82 nRMSE = 34.9%, PM2.5: R2 = 0.75 nRMSE = 35.6%), 계절별 및 연평균 PM10 및 PM2.5 농도에 대한 공간적인 분포를 확인해본 결과, 현장관측자료와 비슷한 공간 분포를 보였으며, 국가별 농도 분포와 계절에 따른 시계열 농도 패턴을 잘 모의하였다.

인자분석을 이용한 광주지역 초미세먼지(PM2.5)의 특성 연구 (Characteristics of PM2.5 in Gwangju Evaluated by Factor Analysis)

  • 이세행;이경석;윤상훈;양윤철;박지영;배석진;이대행
    • 한국환경과학회지
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    • 제28권4호
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    • pp.413-422
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    • 2019
  • The objective of this study was to estimate the trends of air quality in the study area by analyzing monthly and seasonal concentration trends obtained from sampled data. To this aim, the mass concentrations of $PM_{2.5}$ in the air were analyzed, as well as those of metals, ions, and total carbon within the $PM_{2.5}$. The mean concentration of $PM_{2.5}$ was $22.7{\mu}g/m^3$. The mass composition of $PM_{2.5}$ was as follows: 31.1% of ionic species, 2.2% of metallic species, and 26.7% of carbonic species (EC and OC). Ionic species, especially sulfate, ammonium, and nitrate, were the most abundant in the $PM_{2.5}$ and exhibited a high correlation coefficient with the mass concentration of $PM_{2.5}$. Seasonal variations of $PM_{2.5}$ showed a similar pattern to those of ionic and metallic species, with high concentrations during winter and spring. $PM_{2.5}$ also had a high correlation with the ionic species $NO_3{^-}$ and $NH_4{^+}$. In addition, $NH_4{^+}$ was highly correlated with $NO_3{^-}$. Through factor analysis, we identified four controlling factors, and determined the pollution sources using the United States Environmental Protection Agency(U.S. EPA) pollution profile. The first factor, accounting for 19.1% of $PM_{2.5}$ was attributed to motor vehicles and heating-related sources: the second factor indicated industry-related sources and secondary particles, and the other factors indicated soil, industry-related and marine sources. However, the pollution profile used in this study may be somewhat different from the actual situation in Korea, since it was obtained from US EPA. Therefore, to more accurately estimate the pollutants present in the air, a pollution profile for Korea should be produced.

인구 유동에 따른 서울시 대기 중 초미세먼지 농도 변화 요인 분석 및 노출평가 (Analysis and Exposure Assessment of Factors That Affect the Concentration of Ambient PM2.5 in Seoul Based on Population Movement)

  • 우재민;신지훈;민기홍;김동준;성경화;조만수;우병열;양원호
    • 한국환경보건학회지
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    • 제50권1호
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    • pp.6-15
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    • 2024
  • Background: People's activities have been restricted due to the COVID-19 pandemic. These changes in activity patterns may lead to a decrease in fine particulate matter (PM2.5) concentrations. Additionally, the level of population exposure to PM2.5 may be changed. Objectives: This study aimed to analyze the impact of population movement and meteorological factors on the distribution of PM2.5 concentrations before and after the outbreak of COVID-19. Methods: The study area was Guro-gu in Seoul. The research period was selected as January to March 2020, a period of significant population movement changes caused by COVID-19. The evaluation of the dynamic population was conducted by calculating the absolute difference in population numbers between consecutive hours and comparing them to determine the daily average. Ambient PM2.5 concentrations were estimated for each grid using ordinary kriging in Python. For the population exposure assessment, the population-weighted average concentration was calculated by determining the indoor to outdoor population for each grid and applying the indoor to outdoor ratio to the ambient PM2.5 concentration. To assess the factors influencing changes in the ambient PM2.5 concentration, a statistical analysis was conducted, incorporating population mobility and meteorological factors. Results: Through statistical analysis, the correlation between ambient PM2.5 concentration and population movement was positive on both weekends and weekdays (r=0.71, r=0.266). The results confirmed that most of the relationships were positive, suggesting that a decrease in human activity can lead to a decrease in PM2.5 concentrations. In addition, when population-weighted concentration averages were calculated and the exposure level of the population group was compared before and after the COVID-19 outbreak, the proportion of people exceeding the air quality standard decreased by approximately 15.5%. Conclusions: Human activities can impact ambient concentrations of PM2.5, potentially altering the levels of PM2.5 exposure in the population.

서울시 구로구에서 COVID-19 발생 전·후 초미세먼지(PM2.5) 농도 변화에 따른 인구집단 노출평가 (Evaluation of Population Exposures to PM2.5 before and after the Outbreak of COVID-19)

  • 김동준;민기홍;최영태;신준섭;우재민;김동준;신정현;조만수;성경화;최윤형;이채관;최길용;양원호
    • 한국환경보건학회지
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    • 제47권6호
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    • pp.521-529
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    • 2021
  • Background: The coronavirus disease (COVID-19) has caused changes in human activity, and these changes may possibly increase or decrease exposure to fine dust (PM2.5). Therefore, it is necessary to evaluate the exposure to PM2.5 in relation to the outbreak of COVID-19. Objectives: The purpose of this study was to compare and evaluate the exposure to PM2.5 concentrations by the variation of dynamic populations before and after the outbreak of COVID-19. Methods: This study evaluated exposure to PM2.5 concentrations by changes in the dynamic population distribution in Guro-gu, Seoul, before and after the outbreak of COVID-19 between Jan and Feb, 2020. Gurogu was divided into 2,204 scale standard grids of 100 m×100 m. Hourly PM2.5 concentrations were modeled by the inverse distance weight method using 24 sensor-based air monitoring instruments. Hourly dynamic population distribution was evaluated according to gender and age using mobile phone network data and time-activity patterns. Results: Compared to before, the population exposure to PM2.5 decreased after the outbreak of COVID-19. The concentration of PM2.5 after the outbreak of COVID-19 decreased by about 41% on average. The variation of dynamic population before and after the outbreak of COVID-19 decreased by about 18% on average. Conclusions: Comparing before and after the outbreak of COVID-19, the population exposures to PM2.5 decreased by about 40%. This can be explained to suggest that changes in people's activity patterns due to the outbreak of COVID-19 resulted in a decrease in exposure to PM2.5.

항공기 기내 청소노동자의 분진, 초미세먼지(PM2.5) 및 블랙카본 노출수준 평가 (Exposure Assessment of Dust, Ultra Fine Dust(Particulate Matter 2.5, PM2.5) and Black Carbon among Aircraft Cabin Cleaners)

  • 박현희;김세동;김성호;박승현
    • 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, PM2.5/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.

고농도 초미세먼지 출현 시 발전소 주변 대기 입자 성장 및 화학조성 특성 (Characteristics of Particle Growth and Chemical Composition of High Concentrated Ultra Fine Dusts (PM2.5) in the Air around the Power Plant)

  • 강수지;성진호;엄용석;천성남
    • KEPCO Journal on Electric Power and Energy
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    • 제8권2호
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    • pp.103-110
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    • 2022
  • Ultrafine Particle number and size distributions were simultaneously measured at rural area around the power plant in Dangjin, South Korea. New Particle formation and growth events were frequently observed during January, 2021 and classified based on their strength and persistence as well as the variation in geometric mean diameter(GMD) on January 12, 21 and 17. In this study, we investigated mechanisms of new particle growth based on measurements using a high resolution time of flight aerosol mass spectrometer(HR-ToF-AMS) and a scanning mobility particle sizer(SMPS). On Event days(Jan 12 and 21), the total average growth rate was found to be 8.46 nm/h~24.76 nm/hr. These growth rate are comparable to those reported for other urban and rural sites in South Korea using different method. Comparing to the Non-Event day(Jan 17), New Particle Growth mostly occurred when solar radiation is peaked and relative humidity is low in daytime, moreover enhanced under the condition of higher precusors, NO2 (39.9 vs 6.2ppb), VOCs(129.5 vs 84.6ppb), NH3(11 vs 4.7ppb). The HR-ToF-AMS PM1.0 composition shows Organic and Ammoniated nitrate were dominant species effected by emission source in domestic. On the other hand, The Fraction of Ammoniated sulfate was calculated to be approximately 16% and 31% when air quality is inflow from China. Longer term studies are needed to help resolve the relative contributions of each precusor species on new particle growth characteristics.

가습 주기에 따른 벽면형 식물바이오필터의 토양 수분 안정화 및 실내공기질 정화 (Stabilizing Soil Moisture and Indoor Air Quality Purification in a Wall-typed Botanical Biofiltration System Controlled by Humidifying Cycle)

  • 이창희;최봄;천만영
    • 원예과학기술지
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    • 제33권4호
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    • pp.605-617
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    • 2015
  • 본 연구의 최종 목표는 실내의 공간과 식물바이오필터의 규모에 따라 실내공기 오염물질을 정화할 수 있는 식물 녹화와 자동관수 그리고 생물학적 여과 기능을 통합한 식물바이오필터 시스템의 개발이다. 본 연구는 가습 주기에 따른 벽면형(수직형) 식물바이오필터내 공기 흐름의 특성에 대한 안정성과 미세먼지 제거율을 비교하고, 이 식물바이오필터에 의한 휘발성 유기화합물의 제거율을 조사하기 위해 수행하였다. 본 실험에 사용된 식물바이오필터는 실내 공간 활용에 적합하도록 물펌프, 물탱크, 송풍기, 가습장치, 그리고 다층구조의 식물 식재 공간을 일체형으로 설계하였다. 실험 결과, 물펌프에 의해 작동하는 세 가지 다른 가습 주기 처리에 관계없이 식물바이오필터의 상대습도, 온도, 그리고 토양 수분 함량은 안정된 값을 나타내었다. 토양 수분 함량은 모든 가습 주기 처리에서 27.1-29.7%의 범위에서 안정적으로 유지하였으며, 특히 15분 작동 45분 작동 중지의 가습 주기를 120시간 동안 처리하여 $29.0{\pm}0.2%$의 평균 토양 수분 함량을 유지하면서 가장 수평적인 일차회귀식(y = 0.0008x + 29.09)을 보여주었다. 가습 주기에 따라 식물바이오필터를 통과한 미세먼지(PM10)와 초미세먼지(PM2.5) 입자 수에 대한 제거율(RE)은 각각 82.7-89.7%와 65.4-73.0% 범위에 있었고, PM10의 무게에 대한 RE는 58.1-78.9%의 범위에 있었다. 식물바이오필터를 통과한 자일렌, 에틸벤젠, 총 휘발성 유기화합물, 톨루엔의 RE는 71.3-75.5%의 범위에 있었으나, 벤젠과 포름알데히드의 RE는 각각 39.7%와 44.9%로 나타났다. 따라서 실내식물을 식재할 수 있는 본 벽면형 식물바이오필터는 실내 공기 정화에 매우 효과가 있는 것으로 확인하였다.

새만금간척지 지역 대기 중 초미세먼지 (PM2.5) 오염 특성 평가 (Characteristics of Fine Particulate Matter (PM2.5) in the Atmosphere of Saemangum Reclaimed Land Area)

  • 송지한;김정수;홍성창;김진호
    • 한국농공학회논문집
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    • 제64권3호
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    • pp.25-32
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    • 2022
  • To understand the distribution characteristics of PM2.5 concentration in the Saemangeum Reclamation Area and nearby areas, three points of the background area, the occurrence area, and the affected area were selected and samples were collected for each season. The chemical composition was determined. As a result of analyzing the chemical composition contained in PM2.5, NO3- (7.2 ㎍/m3), SO42- (4.3 ㎍/m3), NH4+ (4.3 ㎍/m3), OC (2.5 ㎍/m3), Si (1.3 ㎍/m3) m3) and EC (0.5 ㎍/m3) seemed to be the main components, and NO3-, SO42-, NH4+, which are components that form secondary particles, occupied a large proportion. The composition ratio of PM2.5 was investigated in the order of ion component (56.8%) > Unknown (27.4%) > carbon component (11.8%) > heavy metal component (4.0%). During the PM2.5 high concentration case days, the ionic component accounted for 90.7% during atmospheric stagnation cases, whereas the chemical composition ratio was in the order of ionic component (51.7%) > heavy metal component (41.5%) > carbon component (6.8%) during yellow dust cases. It was found that the characteristic of PM2.5 in the Saemangeum reclaimed land and surrounding areas is mainly influenced by outside (domestic and overseas) throughout the year. Ion components accounted for the largest portion of PM2.5 components in this area, but there were few sources of SOx and NOx emission in the Seamangeum area, which are precursors for secondary particle formation. Therefore, it is judged that most of these are generated and influenced as a secondary reaction in the atmosphere from the outside.

광주 지역에서 2018년 1월 측정한 초미세먼지의 오염 특성 (Pollution characteristics of PM2.5 observed during January 2018 in Gwangju)

  • 유근혜;박승식;정선아;조미라;장유운;임용재;김영성
    • 한국입자에어로졸학회지
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    • 제15권3호
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    • pp.91-104
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    • 2019
  • In this study, hourly measurements of $PM_{2.5}$ and its major chemical constituents such as organic and elemental carbon (OC and EC), and ionic species were made between January 15 and February 10, 2018 at the air pollution intensive monitering station in Gwangju. In addition, 24-hr integrated $PM_{2.5}$ samples were collected at the same site and analyzed for OC, EC, water-soluble OC (WSOC), humic-like substance (HULIS), and ionic species. Over the whole study period, the organic aerosols (=$1.6{\times}OC$) and $NO_3{^-}$ concentrations contributed 26.6% and 21.0% to $PM_{2.5}$, respectively. OC and EC concentrations were mainly attributed to traffic emissions with some contribution from biomass burning emissions. Moreover, strong correlations of OC with WSOC, HULIS, and $NO_3{^-}$ suggest that some of the organic aerosols were likely formed through atmospheric oxidation processes of hydrocarbon compounds from traffic emissions. For the period between January 18 and 22 when $PM_{2.5}$ pollution episode occurred, concentrations of three secondary ionic species ($=SO{_4}^{2-}+NO_3{^-}+NH_4{^+}$) and organic matter contributed on average 50.8 and 20.1% of $PM_{2.5}$, respectively, with the highest contribution from $NO_3{^-}$. Synoptic charts, air mass backward trajectories, and local meteorological conditions supported that high $PM_{2.5}$ pollution was resulted from long-range transport of haze particles lingering over northeastern China, accumulation of local emissions, and local production of secondary aerosols. During the $PM_{2.5}$ pollution episode, enhanced $SO{_4}^{2-}$ was more due to the long-range transport of aerosol particles from China rather than local secondary production from $SO_2$. Increasing rate in $NO_3{^-}$ was substantially greater than $NO_2$ and $SO{_4}^{2-}$ increasing rates, suggesting that the increased concentration of $NO_3{^-}$ during the pollution episode was attributed to enhanced formation of local $NO_3{^-}$ through heterogenous reactions of $NO_2$, rather than impact by long-range transportation from China.