• 제목/요약/키워드: fine particle concentration

검색결과 343건 처리시간 0.031초

서울시 초미세먼지 질량농도 저감을 위한 입자 내 이온성분 최적감축방법 예측 (Estimation of Optimum PM2.5 Ionic Concentration Control Strategy for Reducing Fine Particle Mass Concentrations in Seoul)

  • 김정연;이지원;김용표
    • 한국입자에어로졸학회지
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    • 제6권4호
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    • pp.151-164
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    • 2010
  • Inorganic ions and water are major components of ambient fine particles. Water content in fine particles is mainly determined by ambient meteorological conditions and the concentrations of hygroscopic species such as inorganic ions. Thus, to reduce fine particle mass concentration, it is important to accurately estimate the relationship between water content and the concentration of ions in fine particles. Water content in fine particles in Seoul are estimated by using a gas/particle equilibrium model to understand the characteristics of fine particle mass concentration. In addition, sensitivity of fine particle mass concentration to the changes of particulate ionic species (sulfate, nitrate, and ammonium) is estimated. It was found that water content in Seoul is mostly determined by the concentrations of the hygroscopic ionic species, especially, sulfate and ammonium, and ambient relative humidity.

태풍 우사기와 나리 통과 후 부산지역 미세먼지 농도의 급상승에 관한 연구 (Sudden rise of fine particle concentration after Typhoon USAGI and NARI passage in Busan)

  • 전병일
    • 환경영향평가
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    • 제20권4호
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    • pp.557-564
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    • 2011
  • This study was conducted to investigate the sudden rise of fine particle concentration after the passage of typhoon USAGI and NARI in Busan. Nocturnal inversion layer was formed at atmospheric boundary layer and wind direction changed from southerly wind to northeasterly wind after USAGI passed through Busan. Fine particle concentration in Busan rapidly increased by subsidence of air pollutants released from sources and dust transported from in the vicinity of industrial regions. Wind direction changed from northeasterly wind to southeasterly wind, wind velocity increased and lower atmosphere became extremely unstable after NARI passed through Busan. $PM_{10}$ concentration of Busan increased sharply because of surface dust dispersed by strong wind. Fine particle concentration generally decreases by precipitation and wind after typhoon passes through. However, the concentration can also go up not only by subsidence and transportation in nocturnal inversion layer but also by surface dust which temporarily occurs by strong wind.

부산 도심지역 기습 폭우 후 형성된 도로면 토사의 재비산에 의한 미세먼지 농도 상승 (Concentration Rise of Fine Particle according to Resuspended Dust from Paved Roads after Sudden Heavy Rain in Busan)

  • 전병일
    • 한국환경과학회지
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    • 제25권5호
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    • pp.705-713
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    • 2016
  • This study investigates the concentration sudden rise in fine particle according to resuspended dust from paved roads after sudden heavy rain in Busan on August 25, 2015. The localized torrential rainfall in Busan area occurred as tropical airmass flow from the south and polar airmass flow from north merged. Orographic effect of Mt. Geumjeong enforced rainfall and it amounted to maximum 80 mm/hr at Dongrae and Geumjeong region in Busan. This heavy rain induced flood and landslide in Busan and the nearby areas. The sudden heavy rain moved soil and gravel from mountainous region, which deposited on paved roads and near roadside. These matters on road suspended by an automobile transit, and increased fine particle concentration of air. In addition outdoor fine particle of high concentration flowed in indoor by shoes, cloths and air circulation.

2022년 5월 31일 발생한 밀양산불이 인근 도시 지역의 미세먼지 농도에 미치는 영향 (Effect of May 31, 2022 Miryang Forest Fire on Fine Particle Concentration in Nearby Urban Areas)

  • 전병일
    • 한국환경과학회지
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    • 제32권1호
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    • pp.37-46
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    • 2023
  • This study investigated the effect of May 31, 2022 Miryang wildfire on fine particle concentrations in Busan and Gimhae, which are neighboring urban areas. In addition, fine particle characteristics and air pollution concentrations were investigated in Miryang, where haze occurred. The Miryang city wildfire that occurred on May 31, 2022, at 0925 LST, was driven by strong north winds and increased fine particle concentrations in Dongsangdong and Jangyoodong, Gimhae City, which are approximately 35 km to the southeast and south, respectively, of the wildfire occurrence site. Furthermore, the fine particle concentration in Myeongjidong, which is approximately 50 km south-southeast of the wildfire site, exhibited a temporary increase at 1400 LST owing to the effects of wildfire smoke. On the morning of June 1, the day after the fire, the Miryang area had very bad visibility because of the smoke from the fire. Therefore the PM10 and PM2.5 concentrations in Naeildong, 3 km south of the wildfire site, were 276 ㎍/㎥ and 222 ㎍/㎥, respectively, at 1200 LST. In addition, the gases O3, CO, and SO2 showed high concentrations at the time of haze generation. This study provides insights into policy making in response to the rapid increase in fine dust when wildfire occurs near cities.

서울시 대기중 유기오염물질의 농도와 돌연변이원성에 대한 연구 (Atmospheric concentration and mutagenicity of organic pollutants of suspended particulate in Seoul)

  • 신동천;정용;문영한;노재훈
    • Journal of Preventive Medicine and Public Health
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    • 제23권1호
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    • pp.43-56
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    • 1990
  • To evaluate the difference of concentration and mutagenicity of organic pollutants between residential and traffic area of Seoul, air samples were collected in Bulkwang (residential) and Shinchon (traffic) area. Samples were analyzed to measure the concentration of extractable organic matters (EOM) and their subfractions and mutagenicities were tested using Salmonella typhimurium TA 98. The concentrations of polycyclic aromatic hydrocarbons (PAHs) were also measured by gas-chromatography and compared between two areas. The results were as follows ; 1. While the concentration of total suspended particulate (TSP) in residential area was below the environmental standard in annual average, the concentration in traffic area was above the standard and was up to its maximum $256{\mu}g/m^3$ in November. The difference of TSP concentrations in both areas of each month was statistically significant (P<0.05). 2. The concentration of fine particle in traffic area was significantly higher compare to that in residential area and showed statistically significant monthly difference in both areas (P<0.05). The proportion of concentration of fine particle to TSP was 55-68%. 3. Mean concentrations of EOM in residential and traffic areas were $4.3{\mu}g/m^3\;and\;5.3{\mu}g/m^3$ respectively. The proportion of amount of EOM from fine particle to EOM from TSP was 70-88%. 4. While the percentage of polar neutral organic compounds (POCN) of fine particle in Bulkwang's sample was higher compare to Shinchon's sample, the percentage of aliphatic compounds of fine particle in Shinchon's sample was higher compare to Bulkwang's sample. The percentages of PAH fraction were as low as 6-10% in both areas. 5. The mutagenic activity of nit concentration of organic matters extracted from fine particle was higher compare to that of coarse particle and was increased when metabolically activated with S9. Mutagenicities with metabolic activation calculated by unit air volume were significantly different between residential and traffic area, $17\;revertants/m^3$\;and\;22\;revertants/m^3$ respectively. 6. The concentrations of benzo(a)pyrene in fine particle of traffic and residential areas were $3.10ng/m^3\;and\;2.02ng/m^3$ respectively. Sixteen PAHs were higher in samples of traffic area compare to residential area and also concentrations of PAHs in fine particle were higher compare to coarse particle.

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1994년 수도권 지역에서의 시정과 미세 입자상물질 화학조성과의 관계해석 (Chemical Composition of Fine Aerosol Associated with Visibility Degradation in Seoul Metropolitan Area in 1994)

  • 한진석;김병곤;김신도
    • 한국대기환경학회지
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    • 제12권4호
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    • pp.377-387
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    • 1996
  • This study was carried out to monitor the visibility including measurement and analysis of the various parameters such as particle size distribution, chemical composition, and meteorotical conditions to understand the characteristics and causes of this phenomenon. According to the analysis of intensive sampling, $SO_4^{2-}, NO-3^-, Cl^-, NH_4^+$ ion concentration increased together with the mass concentration around 1 $\mu$m in the case of low visibility. $(NH_4)_2SO_4, NH_4NO_3$, and $NH_4Cl$ were thought to be the major components of fine particles. The statistical analysis showed that the scattering effect of particle was 81.2%, the absorption effect was 14.9%. Therefore, these effects were the major factors to reduce the visibility. In conclusion, the visibility was reduced by the fine particle of sulfate (18.6%), nitrate (14.2%), organic carbon (10.8%), element carbon (25.8%), and residual (24.8%) during this study.

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大氣浮游粒子狀物質中 Benzo(a) pyrene 濃度에 關한 硏究 (Studies on Benzo(a) pyrene Concentrations in Atmospheric Particulate Matters)

  • 손동헌;허문영;남궁용
    • 한국대기환경학회지
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    • 제3권2호
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    • pp.11-17
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    • 1987
  • Atmospheric particulate matter (A.P.M.) was collected on quartz fiber filters from March 1985 to February 1986 at Chung-Ang University according to particle size using Andersen high-volume air smapler, and benzo (a) pyrene concentration in these particulates were analyzed by high performance liquid chromatography. The annual arithmetic mean concentration of A.P.M. was 115.50$\mug/m^3$. The annual arithmetic mean concentrations of coarse particles and fine particles in A.P.M. were 52.54$\mum/m^3$ and 62.96$\mum/m^3$ respectively. THe annual arithmetic mean concentration of benzo(a)pyrene in A.P.M. was 1.44$ng/m^3$. THe annual arithmetic mean concentrations of benzo(a)pyrene in coarse particles and fine particles were 0.05 $ng/m^3$ and 1.39 $ng/m^3$ respectively. Thus, the concentration of benzo(a)pyrene showed maldistribution of 96.53% in fine particle. A.P.M. showed wide fluctuation according to the season. The concentration of A.P.M. was lowest in summer and high in spring and winter. Coarse and fine particle concentrations in A.P.M. were highest in spring and winter, respectively. The concentrations of benzo(a)pyrene was highest in winter and lowest in summer. The concentrations of benzo(a)pyrene in fine and coarse particles were highest in winter and spring, respectively.

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Vertical Change in Extinction and Atmospheric Particle Size in the Boundary Layers over Beijing: Balloon-borne Measurement

  • Chen, Bin;Shi, Guang-Yu;Yamada, Maromu;Zhang, Dai-Zhou;Hayashi, Masahiko;Iwasaka, Yasunobu
    • Asian Journal of Atmospheric Environment
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    • 제4권3호
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    • pp.141-149
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    • 2010
  • Aerosol size and number concentration were observed in the atmospheric boundary layer over Beijing (from near the ground to 1,200 m) on March 15 (a clear day) and 16 (a dusty day), 2005. The results were further compared with lidar measurements in order to understand the dependency of extinction on the particle size distribution and their vertical changes. The boundary layer atmosphere was composed of several sub-layers, and a dry air layer appeared between 400 and 1,000 m under the influence of dust event. In this dry air layer, the concentration of the fine-mode particles (diameter smaller than $1.0\;{\mu}m$) was slightly lower than the value on the clear day, while the concentration of coarse-mode particles (diameter larger than $1.0\;{\mu}m$) was remarkably higher than that on the clear day. This situation was attributed to the inflow of an air mass containing large amounts of Asian dust particles and a smaller amount of fine-mode particles. The results strongly suggest that the fine-mode particles affect light extinction even in the dusty atmosphere. However, quantitatively the relation between extinction and particle concentration is not satisfied under the dusty atmospheric conditions since laser beam attenuates in the atmosphere with high concentration of particles. Laser beam attenuation effect becomes larger in the relation between extinction and coarse particle content comparing the relation between extinction and fine particle content. To clarify this problem technically, future in situ measurements such as balloon-borne lidar are suggested. Here extinction was measured at 532 nm wavelength. Measurements of extinction at other wavelengths are desired in the future.

풍화잔적토의 유동특성에 대한 연구 (Particle Transport of Residual Soils)

  • 이인모;박광준
    • 한국지반공학회지:지반
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    • 제13권5호
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    • pp.155-168
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    • 1997
  • 흙 세립자의 이탈 및 유동은 지반공학이나 지반환경공학적인 관점에서 매우 중요한 현상 중의 하나이다. 특히 지반환경공학적인 견지에서 보면 세림자가 입자유동을 하기 전에 오염물질을 흡착하기 때문에, 오염물질 정화의 방편으로 이용될 수 있다. 본 논문에서는 한국에 가장 편재해 있는 화강풍화토의 입자유동특성을 실내시험에 의해 파악하였다. 실험에 사용된 시료는 대표적인 잔류토라 할 수 있는 서을 신내동, 포이동 및 경북 안동의 시료 각각에 대하여 흐름에 대한 지반특성 치등을 측정하였다. 풍화잔적토에서의 세립분 유동특성에 가장 큰 영향을 미차는 인자는 세립자의 함량과 초기간극률 그리고 입도분포로 나타났고 입자가 이탈되기 시작하는 한계속도는 200번체 통과량에 비례 하여 감소하는 경향을 보였다. 이탈률의 변화율은 간극률에 비례하여 증가함을 보였으며 입도분 포가불량하고200번체 통과량이 적은 시료에서의 입자이탈량이 가장 크게 나타났다. 또한 실험결과를 토대로 단계별 입자유동현상을 표현하는 기본방정식을 모델링하고 유한차분법을 이용하여 해를구하므로써 흐름이 발생하는 지반구조물에서 입자유동현상이 미치는 영향을 파악할 수 있는 토대를 마련하였다.

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Domain Adaptation 방법을 이용한 기계학습 기반의 미세먼지 농도 예측 (Machine Learning-based Estimation of the Concentration of Fine Particulate Matter Using Domain Adaptation Method)

  • 강태천;강행봉
    • 한국멀티미디어학회논문지
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    • 제20권8호
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    • pp.1208-1215
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    • 2017
  • Recently, people's attention and worries about fine particulate matter have been increasing. Due to the construction and maintenance costs, there are insufficient air quality monitoring stations. As a result, people have limited information about the concentration of fine particulate matter, depending on the location. Studies have been undertaken to estimate the fine particle concentrations in areas without a measurement station. Yet there are limitations in that the estimate cannot take account of other factors that affect the concentration of fine particle. In order to solve these problems, we propose a framework for estimating the concentration of fine particulate matter of a specific area using meteorological data and traffic data. Since there are more grids without a monitor station than grids with a monitor station, we used a domain adversarial neural network based on the domain adaptation method. The features extracted from meteorological data and traffic data are learned in the network, and the air quality index of the corresponding area is then predicted by the generated model. Experimental results demonstrate that the proposed method performs better as the number of source data increases than the method using conditional random fields.