• Title/Summary/Keyword: South Korean $PM_{2.5}$

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

  • Oh, Jang Wook;Lim, Tea Jin
    • Journal of the Korean Society of Safety
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    • v.32 no.5
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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.

Evaluation of the Effectiveness of Emission Control Measures to Improve PM2.5 Concentration in South Korea (미세먼지 농도 개선을 위한 배출량 저감대책 효과 분석)

  • Kim, Eunhye;Bae, Changhan;Yoo, Chul;Kim, Byeong-Uk;Kim, Hyun Cheol;Kim, Soontae
    • Journal of Korean Society for Atmospheric Environment
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    • v.34 no.3
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    • pp.469-485
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    • 2018
  • On September 26, 2017, South Korean government has established the Particulate Matter Comprehensive Plan to improve Korean air quality by 2022, which aims to reduce annual mean surface $PM_{2.5}$ concentration to $18{\mu}g/m^3$. This study demonstrates quantitative assessment of predicted $PM_{2.5}$ concentrations over 17 South Korean regions with the enforcement of the comprehensive plan. We utilize the Community Multi-scale Air Quality (CMAQ) modeling system with CAPSS 2013 and CREATE 2015 emissions inventories. Simulations are conducted for 2015 with the base emissions and the planned emissions, and impacts from model biases are minimized using the RRF (Relative Response Factor). With effective emission reduction scenario suggested by the comprehensive plan, the model demonstrates that the surface $PM_{2.5}$ concentration may decrease by $6{\mu}g/m^3$ ($23{\mu}g/m^3{\rightarrow}17{\mu}g/m^3$) and $7{\mu}g/m^3$ ($25{\mu}g/m^3{\rightarrow}18{\mu}g/m^3$) for Seoul and South Korea, respectively. The number of high $PM_{2.5}$ days(daily mean>$25{\mu}g/m^3$) also decreases from 21 days to 4 days.

Study on the spatial distribution and aggregation characteristics of fisheries resources in the East Sea, West Sea and South Sea of the South Korea in spring and autumn using a hydroacoustic method (음향을 이용한 춘계와 추계에 우리나라 동서남해의 수산자원의 공간적인 분포 및 군집특성 조사)

  • PARK, Junseong;HWANG, Kangseok;PARK, Junsu;KANG, Myounghee
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.54 no.2
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    • pp.146-156
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    • 2018
  • Acoustic surveys were conducted in the seas surround the South Korea (South Sea A, South Sea B (waters around the Jeju Island), West Sea and East Sea) in spring and autumn in 2016. First, the vertical and horizontal distributions of fisheries resources animals were examined. In most cases vertical acoustic biomass was high in surface water and mid-water layers other than South Sea A in autumn and West Sea. The highest vertical acoustic biomass showed at the depth of 70-80 m in the South Sea A in spring ($274.4m^2/nmi^2$) and the lowest one was 10-20 m in the West Sea in autumn ($0.4m^2/nmi^2$). With regard to the horizontal distributions of fisheries resources animals, in the South Sea A, the acoustic biomass was high in eastern and central part of the South Sea and the northeast of Jeju Island ($505.4-4099.1m^2/nmi^2$) in spring while it was high in eastern South Sea and the coastal water of Yeosu in autumn ($1046.9-2958.3m^2/nmi^2$). In the South Sea B, the acoustic biomass was occurred high in the southern and western seas of Jeju Island in spring ($201.0-1444.9m^2/nmi^2$) and in the southern of Jeju Island in autumn ($203.7-1440.9m^2/nmi^2$). On the other hand, the West Sea showed very low acoustic biomass in spring (average NASC of $1.1m^2/nmi^2$), yet high acoustic biomass in the vicinity of 37 N in autumn ($562.6-3764.2m^2/nmi^2$). The East Sea had high acoustic biomass in the coastal seas of Busan, Ulsan and Pohang in spring ($258.7{\sim}976.4m^2/nmi^2$) and of Goseong, Gangneung, Donghae, Pohang and Busan in autumn ($267.3-1196.3m^2/nmi^2$). During survey periods, fish schools were observed only in the South Sea A and the East Sea in spring and the West Sea in autumn. Fish schools in the South Sea A in spring were small size ($333.2{\pm}763.2m^2$) but had a strong $S_V$ ($-49.5{\pm}5.3dB$). In the East Sea, fish schools in spring had low $S_V$ ($-60.5{\pm}14.5dB$) yet had large sizes ($537.9{\pm}1111.5m^2$) and were distributed in the deep water depth ($83.5{\pm}33.5m$). Fish schools in the West Sea in autumn had strong $S_V$ ($-49.6{\pm}7.4dB$) and large sizes ($507.1{\pm}941.8m^2$). It was the first time for three seas surrounded South Korea to be conducted by acoustic surveys to understand the distribution and aggregation characteristics of fisheries resources animals. The results of this study would be beneficially used for planning a future survey combined acoustic method and mid-water trawling, particularly deciding a survey location, a time period, and a targeting water depth.

PM2.5 Source Apportionment Analysis to Investigate Contributions of the Major Source Areas in the Southeastern Region of South Korea (동남지역 주요 배출지역의 PM2.5 기여도 분석)

  • Ju, Hyeji;Bae, Changhan;Kim, Byeong-Uk;Kim, Hyun Cheol;Yoo, Chul;Kim, Soontae
    • Journal of Korean Society for Atmospheric Environment
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    • v.34 no.4
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    • pp.517-533
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    • 2018
  • We utilize the CAMx (Comprehensive Air Quality Model with eXtensions) system and the PSAT (Particulate Source Apportionment Technology) diagnostic tool to determine the $PM_{2.5}$ concentration and to perform its source apportionment in the southeastern region of South Korea. For a year-long simulation, eight local authorities in the region such as Pohang, Daegu, Gyeongju, Ulsan, Busan-Gimhae, Gosung-Changwon, Hadong, and all remaining areas in Gyeongsangnam-do, are selected as source areas based on the emission rates of $NO_x$, $SO_x$, VOC, and primary PM in CAPSS (Clean Air Policy Support System) 2013 emissions inventory. The CAMx-PSAT simulation shows that Pohang has the highest $PM_{2.5}$ self-contribution rate (25%), followed by Hadong (15%) and Busan-Gimhae (14%). With the exception of Pohang, which has intense fugitive dust emissions, other authorities are strongly affected by emissions from their neighboring areas. This may be measured as much as 1 to 2 times higher than that of the self-contribution rate. Based on these estimations, we conclude that the efficiency of emission reduction measures to mitigate $PM_{2.5}$ concentrations in the southeastern region of South Korea can be maximized when the efforts of local or regional emission controls are combined with those from neighboring regions. A comprehensive control policy planning based on the collaboration between neighboring jurisdictional boundaries is required.

Assessment of PM2.5 and Black Carbon Concentrations among Street Vendors: Focusing on Cooking Stalls (거리 가판대에서의 초미세먼지(PM2.5)와 블랙 카본(BC)의 농도평가: 조리 가판대를 중심으로)

  • Minjung, Kim;Jiyun, Shin;Jiwon, Jeong;Sueun, Choi;Kiyoung, Lee
    • Journal of Environmental Health Sciences
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    • v.48 no.6
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    • pp.291-297
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    • 2022
  • Background: PM2.5 and black carbon (BC) can be generated from cooking and from vehicle operation. Street vendors may be exposed to PM2.5 and BC due to their proximity both to roads and to cooking activities. Objectives: The objectives of this study were to evaluate the PM2.5 and BC concentrations in cooking stalls and to determine the effects of cooking activity and of types of cooking. Methods: Indoor and outdoor PM2.5 and BC concentrations, temperature, and relative humidity were measured in 32 stalls in April and May 2022. Behavioral factors such as the presence of cooking activity and types of cooking were observed. Student's T-test was performed using the difference of indoor and outdoor PM2.5 and BC concentrations to compare the effects of cooking activity and to compare types of cooking. Results: One-hour averages of the difference in indoor and outdoor PM2.5 concentrations for cooking stalls and non-cooking stalls were 9.7±15.7 ㎍/m3 (n=22) and -0.5±0.4 ㎍/m3 (n=10), respectively. The difference in indoor and outdoor PM2.5 concentrations in cooking stalls was significantly higher than in non-cooking stalls (p<0.05). The indoor PM2.5 concentration for stalls for Chinese pancakes and teokbokki exceeded the standards for indoor air quality in South Korea (50 ㎍/m3 ). The indoor PM2.5 concentration for Korean pancake stalls exceeded the standards for outdoor air quality in South Korea (35 ㎍/m3 for 24 hours). Conclusions: The PM2.5 concentrations in stalls with cooking activity was significantly higher than those in stalls without cooking activity. Some stalls with certain types of foods exceeded standards for indoor and outdoor air quality in South Korea. Better management of indoor air quality in stalls with cooking activities is necessary.

Estimation of ambient PM10 and PM2.5 concentrations in Seoul, South Korea, using empirical models based on MODIS and Landsat 8 OLI imagery

  • Lee, Peter Sang-Hoon;Park, Jincheol;Seo, Jung-young
    • Korean Journal of Agricultural Science
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    • v.47 no.1
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    • pp.59-66
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    • 2020
  • Particulate matter (PM) is regarded as a major threat to public health and safety in urban areas. Despite a variety of efforts to systemically monitor the distribution of PM, the limited amount of sampling sites may not provide sufficient coverage over the areas where the monitoring stations are not located in close proximity. This study examined the capacity of using remotely sensed data to estimate the PM10 and PM2.5 concentrations in Seoul, South Korea. Multiple linear regression models were developed using the multispectral band data from the Moderate-resolution imaging spectro-radiometer equipped on Terra (MODIS) and Operational Land Imager equipped on Landsat 8 (Landsat 8) and meteorological parameters. Compared to MODIS-derived models (r2 = 0.25 for PM10, r2 = 0.30 for PM2.5), the Landsat 8-derived models showed improved model reliabilities (r2 = 0.17 to 0.57 for PM10, r2 = 0.47 to 0.71 for PM2.5). Landsat 8 model-derived PM concentration and ground-truth PM measurements were cross-validated to each other to examine the capability of the models for estimating the PM concentration. The modeled PM concentrations showed a stronger correlation to PM10 (r = 0.41 to 0.75) than to PM2.5 (r = 0.14 to 0.82). Overall, the results indicate that Landsat 8-derived models were more suitable in estimating the PM concentrations. Despite the day-to-day fluctuation in the model reliability, several models showed strong correspondences of the modeled PM concentrations to the PM measurements.

Analysis of Q Values on the Crust of the Kimcheon and Mokpo Regions, South Korea (남한 김천.목포 일대 지각의 Q 값 분석)

  • Do, Ji-Young;Lee, Yoon-Joong;Kyung, Jai-Bok
    • Journal of the Korean earth science society
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    • v.27 no.4
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    • pp.475-485
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    • 2006
  • The physical properties of the central and southwestern crust of South Korea were estimated by comparing values of ${Q_P}^{-1}\;and\;{Q_S}^{-1}$ in the Kimcheon and Mokpo areas. In order to get ${Q_P}^{-1}\;and\;{Q_S}^{-1}$ values, seismic data were collected from two stations of the KIGAM network (KMC and MUN) and four stations of the KMA network (CPN, KUC, MOP, and WAN). An extended coda-normalization method was applied to these data. Estimates of ${Q_P}^{-1}\;and\;{Q_S}^{-1}$ show variations depending on frequency. As frequencies vary from 3 Hz to 24 Hz, the estimates decrease from $(1.4{\pm}3.9){\times}10^{-3}\;to\;(2.3{\pm}3.5){\times}10^{-4}\;for\;{Q_P}^{-1}\;and\;(1.8{\pm}1.3){\times}10^{-3}\;to\;(1.9{\pm}1.5){\times}10^{-4}\;for\;{Q_S}^{-1}$ in central South Korea, and $(5.9{\pm}4.8){\times}10^{-3}\;to\;(2.2{\pm}3.8){\times}10^{-4}\;for\;{Q_P}^{-1}\;and\;(0.5{\pm}2.8){\times}10^{-3}\;to\;(1.8{\pm}1.6){\times}10^{-4}\;for\;{Q_S}^{-1}$ in southwestern South Korea. According that a frequency-dependent power law is applied to the data, the best fits of ${Q_P}^{-1}\;and\;{Q_S}^{-1}\;are\;0.003f^{-0.49}\;and\;0.005f^{-1.03}$ in central South Korea, and $0.026f^{-1.47}$ and $0.001f^{-0.49}$ in southwestern South Korea, respectively. These values almost correspond to those of seismically stable regions although ${Q_P}^{-1}$ values of southwestern South Korea are a little high due to lack of data used.

Analysis on the Characteristics of PM10 Variation over South Korea from 2010 to 2014 using WRF-CMAQ: Focusing on the Analysis of Meteorological Factors (기상-대기질 모델을 활용한 2010~2014년 우리나라 PM10 변동 특성 분석: 기상 요인을 중심으로)

  • Nam, Ki-Pyo;Lee, Dae-Gyun;Park, Ji-Hoon
    • Journal of Environmental Impact Assessment
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    • v.27 no.5
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    • pp.509-520
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    • 2018
  • The impact of meteorological condition on surface $PM_{10}$ concentrations in South Korea was quantitatively simulated from 2010 to 2014 using WRF (ver.3.8.1) and CMAQ (5.0.2) model. The result showed that seasonal standard deviations of PM10 induced by change of weather conditions were $4.8{\mu}g/m^3$, $1.7{\mu}g/m^3$, $1.7{\mu}g/m^3$, $4.2{\mu}g/m^3$ for spring, summer, autumn and winter compared to 2010, respectively, with the annual mean standard deviation of about $2.6{\mu}g/m^3$. The results of 18 regions in South Korea showed standard deviation of more than $1{\mu}g/m^3$ in all regions and more than $2{\mu}g/m^3$ in Seoul, Northern Gyeonggi, Southern Southern Gyeonggi, Western Gangwon and Northern Chungcheong in South Korea.

Contributions of Emissions and Atmospheric Physical and Chemical Processes to High PM2.5 Concentrations on Jeju Island During Spring 2018 (2018년 봄철 제주지역 고농도 PM2.5에 대한 배출량 및 물리·화학적 공정 기여도 분석)

  • Baek, Joo-Yeol;Song, Sang-Keun;Han, Seung-Beom;Cho, Seong-Bin
    • Journal of Environmental Science International
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    • v.31 no.7
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    • pp.637-652
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    • 2022
  • In this study, the contributions of emissions (foreign and domestic) and atmospheric physical and chemical processes to PM2.5 concentrations were evaluated during a high PM2.5 episode (March 24-26, 2018) observed on the Jeju Island in the spring of 2018. These analyses were performed using the community multi-scale air quality (CMAQ) modeling system using the brute-force method and integrated process rate (IPR) analysis, respectively. The contributions of domestic emissions from South Korea (41-45%) to PM2.5 on the Jeju Island were lower than those (81-89%) of long-range transport (LRT) from China. The substantial contribution of LRT was also confirmed in conjunction with the air mass trajectory analysis, indicating that the frequency of airflow from China (58-62% of all trajectories) was higher than from other regions (28-32%) (e.g., South Korea). These results imply that compared to domestic emissions, emissions from China have a stronger impact than domestic emissions on the high PM2.5 concentrations in the study area. From the IPR analysis, horizontal transport contributed substantially to PM2.5 concentrations were dominant in most of the areas of the Jeju Island during the high PM2.5 episode, while the aerosol process and vertical transport in the southern areas largely contributed to higher PM2.5 concentrations.

PM2.5 Simulations for the Seoul Metropolitan Area: (V) Estimation of North Korean Emission Contribution (수도권 초미세먼지 농도모사: (V) 북한 배출량 영향 추정)

  • Bae, Minah;Kim, Hyun Cheol;Kim, Byeong-Uk;Kim, Soontae
    • Journal of Korean Society for Atmospheric Environment
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    • v.34 no.2
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    • pp.294-305
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    • 2018
  • Quantitative assessment on the impact from North Korean emissions to surface particulate matter(PM) concentration in the Seoul Metropolitan Area (SMA), South Korea is conducted using a 3-dimensional chemistry transport model. Transboundary transport of air pollutants and their precursors are important to understand regional air quality in East Asian countries. As North Korea locates in the middle of main transport pathways of Chinese pollutants, quantifiable estimation of its impact is essential for policy making in South Korean air quality management. In this study, the Community Multiscale Air Quality Modeling System is utilized to simulate regional air quality and its sensitivity, using the Comprehensive Regional Emissions inventory for Atmospheric Transport Experiment 2015 and the Clean Air Policy Support System 2013 emissions inventories for North and South Korea, respectively. Contributions were estimated by a brute force method, perturbing 50% of North and South Korean emissions. Simulations demonstrate that North Korean emissions contribute $3.89{\mu}g/m^3$ of annual surface PM concentrations in the SMA, which accounts 14.7% of the region's average. Impacts are dominant in nitrate and organic carbon (OC) concentrations, attributing almost 40% of SMA OC concentration during January and February. Clear seasonal variations are also found in North Korean emissions contribution to South Korea (and vice versa) due to seasonal characteristics of synoptic weather, especially by the change of seasonal flow patterns.