• 제목/요약/키워드: Particulate matter 2.5

검색결과 606건 처리시간 0.138초

새만금 간척지 지역 공기 중 암모니아 농도의 연간 분포 (Annual Distribution of Atmospheric Ammonia Concentration in Saemangum Reclaimed Land Area)

  • 홍성창;김민욱;김진호
    • 한국환경농학회지
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    • 제40권4호
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    • pp.330-334
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    • 2021
  • BACKGROUND: More recently, it has been shown that atmospheric ammonia (NH3) plays a primary role in the formation of secondary particulate matter by reacting with the acidic species, e.g. SO2, NOx, to form PM2.5 aerosols in the atmosphere. The Jeonbuk region is an area with high concentration of particulate matter. Due to environmental changes in the Saemangeum reclaimed land with an area of 219 km2, it is necessary to evaluate the impact of the particulate matter and atmospheric ammonia in the Jeonbuk region. METHODS AND RESULTS: Atmospheric ammonia concentrations were measured from June 2020 to May 2021 using a passive sampler and CRDS analyzer. Seasonal and annual atmospheric ammonia concentration measured using passive sampler was significantly lower in Jangjado (background concentration), and the concentration ranged from 11.4 ㎍/m3 to 18.2 ㎍/m3. Atmospheric ammonia concentrations in Buan, Gimje, Gunsan, and Wanju regions did not show a significant difference, although there was a slight seasonal difference. The maximum atmospheric ammonia concentration measured using the CRDS analyzer installed in the IAMS near the Saemangeum reclaimed land was 51.5 ㎍/m3 in autumn, 48.0 ㎍/m3 in summer, 37.6 ㎍/m3 in winter, and 32.7 ㎍/m3 in spring. The minimum concentration was 4.9 ㎍/m3 in spring, 4.2 ㎍/m3 in summer, and 3.5 ㎍/m3 in autumn and winter. The annual average concentration was 14.6 ㎍/m3. CONCLUSION(S): Long term monitoring of atmospheric ammonia in agricultural areas is required to evaluate the formation of fine particulate matter and its impact on the environment. In addition, continuous technology development is needed to reduce ammonia emitted from farmland.

국내 지역별 미세먼지 농도 리스크 분석 (Regional Analysis of Particulate Matter Concentration Risk in South Korea)

  • 오장욱;임태진
    • 한국안전학회지
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    • 제32권5호
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    • pp.157-167
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    • 2017
  • Millions of People die every year from diseases caused by exposure to outdoor air pollution. Especially, one of the most severe types of air pollution is fine particulate matter (PM10, PM2.5). South Korea also has been suffered from severe PM. This paper analyzes regional risks induced by PM10 and PM2.5 that have affected domestic area of Korea during 2014~2016.3Q. We investigated daily maxima of PM10 and PM2.5 data observed on 284 stations in South Korea, and found extremely high outlier. We employed extreme value distributions to fit the PM10 and PM2.5 data, but a single distribution did not fit the data well. For theses reasons, we implemented extreme mixture models such as the generalized Pareto distribution(GPD) with the normal, the gamma, the Weibull and the log-normal, respectively. Next, we divided the whole area into 16 regions and analyzed characteristics of PM risks by developing the FN-curves. Finally, we estimated 1-month, 1-quater, half year, 1-year and 3-years period return levels, respectively. The severity rankings of PM10 and PM2.5 concentration turned out to be different from region to region. The capital area revealed the worst PM risk in all seasons. The reason for high PM risk even in the yellow dust free season (Jun. ~ Sep.) can be inferred from the concentration of factories in this area. Gwangju showed the highest return level of PM2.5, even if the return level of PM10 was relatively low. This phenomenon implies that we should investigate chemical mechanisms for making PM2.5 in the vicinity of Gwangju area. On the other hand, Gyeongbuk and Ulsan exposed relatively high PM10 risk and low PM2.5 risk. This indicates that the management policy of PM risk in the west side should be different from that in the east side. The results of this research may provide insights for managing regional risks induced by PM10 and PM2.5 in South Korea.

Therapeutic Effects of (+)-Afzelechin on Particulate Matter-Induced Pulmonary Injury

  • Sanghee Cho;Yun Jin Park;Jong-Sup Bae
    • Biomolecules & Therapeutics
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    • 제32권1호
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    • pp.162-169
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    • 2024
  • Particulate matter (PM) constitutes a hazardous blend of organic and inorganic particles that poses health risks. Inhalation of fine airborne PM with a diameter of ≤ 2.5 ㎛ (PM2.5) can lead to significant lung impairments. (+)-afzelechin (AZC), a natural compound sourced from Bergenia ligulata, boasts a range of attributes, including antioxidant, antimicrobial, anticancer, and cardiovascular effects. However, knowledge about the therapeutic potential of AZC for patients with PM2.5-induced lung injuries remains limited. Thus, in this study, we investigated the protective attributes of AZC against lung damage caused by PM2.5 exposure. AZC was administered to the mice 30 min after intratracheal instillation of PM2.5. Various parameters, such as changes in lung tissue wet/dry (W/D) weight ratio, total protein/total cell ratio, lymphocyte counts, levels of inflammatory cytokines in bronchoalveolar lavage fluid (BALF), vascular permeability, and histology, were evaluated in mice exposed to PM2.5. Data demonstrated that AZC mitigated lung damage, reduced W/D weight ratio, and curbed hyperpermeability induced by PM2.5 exposure. Furthermore, AZC effectively lowered plasma levels of inflammatory cytokines produced by PM2.5 exposure. It reduced the total protein concentration in BALF and successfully alleviated PM2.5-induced lymphocytosis. Additionally, AZC substantially diminished the expression levels of Toll-like receptors 4 (TLR4), MyD88, and autophagy-related proteins LC3 II and Beclin 1. In contrast, it elevated the protein phosphorylation of the mammalian target of rapamycin (mTOR). Consequently, the anti-inflammatory attribute of AZC positions it as a promising therapeutic agent for mitigating PM2.5-induced lung injuries by modulating the TLR4-MyD88 and mTOR-autophagy pathways.

딥러닝 알고리즘 기반의 초미세먼지(PM2.5) 예측 성능 비교 분석 (Comparison and analysis of prediction performance of fine particulate matter(PM2.5) based on deep learning algorithm)

  • 김영희;장관종
    • 융합정보논문지
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    • 제11권3호
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    • pp.7-13
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    • 2021
  • 본 연구는 딥러닝(Deep Learning) 알고리즘 GAN 모델을 기반으로 초미세먼지(PM2.5) 인공지능 예측시스템을 개발한다. 실험 데이터는 시계열 축으로 생성된 온도, 습도, 풍속, 기압의 기상변화와 SO2, CO, O3, NO2, PM10와 같은 대기오염물질 농도와 밀접한 관련이 있다. 데이터 특성상, 현재시간 농도가 이전시간 농도에 영향을 받기 때문에 반복지도학습(Recursive Supervised Learning) 예측 모델을 적용하였다. 기존 모델인 CNN, LSTM의 정확도(Accuracy)를 비교분석을 위해 관측값(Observation Value)과 예측값(Prediction Value)간의 차이를 분석하고 시각화했다. 성능분석 결과 제안하는 GAN이 LSTM 대비 평가항목 RMSE, MAPE, IOA에서 각각 15.8%, 10.9%, 5.5%로 향상된 것을 확인하였다.

미세먼지 포집장치 개발을 위한 관성충돌 프리필터 유동 전산해석 (CFD Analysis of the Inertial Impaction Pre-Filter for a Particulate Matter Collecting Device)

  • 경대승;황대성
    • 토지주택연구
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    • 제10권2호
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    • pp.53-58
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    • 2019
  • Particulate matter (PM) is designated as a group 1 carcinogen by the International Agency for Research on Cancer (IARC) of the World Health Organization (WHO). In South Korea, the health threat caused by PM is the most serious level internationally. Therefore, in order to solve the urban PM problem, it is important to develop the technology that can control PM efficiently. In this study, CFD(Computational Fluid Dynamics) simulation was performed for PM pre-filter (type 1-3 with different PM collecting room) to develop a high-efficiency PM collecting device. The complex flow field and the local flow phenomenon inside the PM collecting device were understood with CFD simulation by changing the shape and size of the pre-filter. The PM removal performance can be described with flow rate through the device and PM removal efficiency. The type-1 pre-filter with 5x5 size collecting room was confirmed to have the highest efficiency. Based on the analysis results, the optimal type of pre-filter could be developed and it would be applied as an element technology included in the PM collecting device.

초미세 크기의 마른 안개 생성과 이를 이용한 미세먼지 제거 연구 (Experimental study on the generation of ultrafine-sized dry fog and removal of particulate matter)

  • 김기웅
    • 한국가시화정보학회지
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    • 제22권1호
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    • pp.34-39
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    • 2024
  • With the fine particulate matter (PM) poses a serious threat to public health and the environment. The ultrafine PM in particular can cause serious problems. This study investigates the effectiveness of a submicron dry fog system in removing fine PM. Two methods are used to create fine dust particles: burning incense and utilizing an aerosol generator. Results indicate that the dry fog system effectively removes fine dust particles, with a removal efficiency of up to 81.9% for PM10 and 61.9% for PM2.5 after 30 minutes of operation. The dry fog, characterized by a mean size of approximately 1.5 ㎛, exhibits superior performance in comparison to traditional water spraying methods, attributed to reduced water consumption and increased contact probability between water droplets and dust particles. Furthermore, experiments with uniform-sized particles which sizes are 1 ㎛ and 2 ㎛ demonstrate the system's capability in removing ultrafine PM. The proposed submicron dry fog system shows promise for mitigating fine dust pollution in various industrial settings, offering advantages such as energy consumption and enhanced safety for workers and equipment.

Niacinamide Protects Skin Cells from Oxidative Stress Induced by Particulate Matter

  • Zhen, Ao Xuan;Piao, Mei Jing;Kang, Kyoung Ah;Fernando, Pincha Devage Sameera Madushan;Kang, Hee Kyoung;Koh, Young Sang;Yi, Joo Mi;Hyun, Jin Won
    • Biomolecules & Therapeutics
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    • 제27권6호
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    • pp.562-569
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    • 2019
  • Niacinamide (NIA) is a water-soluble vitamin that is widely used in the treatment of skin diseases. Moreover, NIA displays antioxidant effects and helps repair damaged DNA. Recent studies showed that particulate matter 2.5 ($PM_{2.5}$) induced reactive oxygen species (ROS), causing disruption of DNA, lipids, and protein, mitochondrial depolarization, and apoptosis of skin keratinocytes. Here, we investigated the protective effects of NIA on $PM_{2.5}$-induced oxidative stress in human HaCaT keratinocytes. We found that NIA could inhibit the ROS generation induced by $PM_{2.5}$, as well block the $PM_{2.5}$-induced oxidation of molecules, such as lipids, proteins, and DNA. Furthermore, NIA alleviated $PM_{2.5}$-induced accumulation of cellular $Ca^{2+}$, which caused cell membrane depolarization and apoptosis, and reduced the number of apoptotic cells. Collectively, the findings show that NIA can protect keratinocytes from $PM_{2.5}$-induced oxidative stress and cell damage.

규칙기반 초미세먼지 상태 추론 (Particulate Matter (PM2.5) State Inference by Rule Induction)

  • 최락현;강원석;손창식
    • 대한임베디드공학회논문지
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    • 제13권4호
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    • pp.179-185
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    • 2018
  • Particulate Matter (PM2.5) has various adverse effects on health. Climate and industry activity and traffic volume are the main causes, especially in urban area. In order to construct an effective forecasting system, many measurement systems are required, but it is impossible in reality. Therefore, in this study, we propose a method to infer PM2.5 condition by using rule induction technique. The experimental results showed a classification accuracy of 71%.

Chemical Properties and Source Profiles of Particulate Matter Collected on an Underground Subway Platform

  • Ma, Chang-Jin;Lee, Kyoung-Bin;Kim, Shin-Do;Sera, Koichiro
    • Asian Journal of Atmospheric Environment
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    • 제9권2호
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    • pp.165-172
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    • 2015
  • Under a very tough situation that there has been increasing concern to the air quality in underground subway spaces, this study set sights on the thorough estimation of the chemical properties and source apportionment of particulate matter (PM) collected on an underground subway platform by a cooperative approach of semi-bulk and single particle analyses. The size-resolved PMs were intensively collected on the platform of Miasageori station on the Seoul Subway Line-4, and then, they were semibulkily analyzed by a PIXE and the TOR$^{(R)}$ method, and individually analyzed by a SEM-EDX. Overwhelmingly enriched iron was a notable feature of elemental concentration of $PM_{2.5}$. Source classification of iron in $PM_{10-2.5}$ and $PM_{2.5}$ performed along with their elemental concentrations, indicates that the railway originated iron accounts for 95.71% and 66.39% of total iron in $PM_{10-2.5}$ and $PM_{2.5}$, respectively. Via a stoichiometric categorization, $Fe_2O_3$, $CaAl_2Si_2O_8$, $Al_2O_3$, and $CaCO_3$ show more than 85% abundance ratio in individual coarse particles. The result of theoretical estimation of the subway derived organic carbon ($OC_{Subway}$) suggests that $OC_{Subway}$ in $PM_1$ and $PM_{2.5-1}$ account for 75.86% and 51.88% of total organic carbon, respectively.

Impact of Dust Transported from China on Air Quality in Korea -Characteristics of PM2.5 Concentrations and Metallic Elements in Asan and Seoul, Korea

  • Yang, Won-Ho;Son, Bu-Soon;Breysse, Patrick;Chung, Tae-Woong
    • 한국환경보건학회지
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    • 제33권6호
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    • pp.479-487
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    • 2007
  • [ $PM_{2.5}$ ], particulate matter less than 2.5 um in a diameter, can penetrate deeply into the lungs. Exposure to $PM_{2.5}$ has been associated with increased hospital visits for respiratory aliments as well as increase mortality. $PM_{2.5}$ is a byproduct of combustion processes and as such has a complex composition including a variety of metallic elements, inorganic and organic compounds as well as biogenic materials (microorganisms, proteins, etc). In this study, the average concentrations of fine particulates $PM_{2.5}$ have been measured simultaneously in Asan and Seoul, Korea, by using particulate matter portable sampler from September 2001 to August 2002. Sample collection filters were analyzed by ICP-OES to determine the concentrations of metallic elements (As, Ni, Fe, Cr, Cd, Cu, Pb, Zn, Si). Annual mean $PM_{2.5}$ concentrations in Asan and Seoul were 37.70 and $45.83\;{\mu}g/m^3$, respectively. The highest concentrations of $PM_{2.5}$ were found in spring season in both cities and the concentrations of measured metallic elements except As in Asan were higher than those in Seoul, suggesting that yellow dust in spring could affect $PM_{2.5}$ concentrations in Asan rather than Seoul. The correlation coefficients of Pb and Zn were 0.343 for Asan and 0.813 for Seoul during non-yellow dust condition, suggesting that Pb and Zn were influenced with the same sources. The correlation coefficients between Si and Fe in the fine particulate mode were 0.999 (Asan) and 0.998 (Seoul) during yellow dust condition. It was suggested that these two elements were impacted by soil-related transport from China during the yellow dust storm condition.