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      기후인자와 관련된 동아시아 봄과 가을 PM 2.5 농도 이해 = Understanding PM 2.5 Concentration Associated with Climate Indicators in Spring and Fall over East Asia

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      https://www.riss.kr/link?id=A108766468

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      다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

      Due to the adverse impacts of PM 2.5, particulate matter less than 2.5µg/m 3 , understanding their concentration mechanisms related to atmospheric processes is crucial. Various types of aerosol emission and meteorological conditions are the dominant factors of changing PM 2.5 concentration in the atmosphere. Therefore PM 2.5 emission has been controlled and its relationship with meteorological conditions has been actively researched. In this study, we identify the spatial patterns of high and low concentrations of PM 2.5 obtained from MERR A2 and investigate how PM 2.5 differences are associated with climate indicators, such as precipitation and vertical velocity, over the East Asia region in spring and fall. The results of Empirical Orthogonal Function (EOF) analysis show that most high concentration appears over inland east China from 2000-2013 in both spring and fall. Our results indicate that a combination of a strong downward vertical velocity, less precipitation, and cyclonic circulation at 850hPa interrupting PM 2.5 moving towards the downwind region, influences on high concentration over the PM 2.5 source region in spring. Similar to spring, less precipitation and downward vertical velocity pattern with weaker intensity appears in the fall with high PM 2.5. In the case of low PM 2.5, both spring and fall show more precipitation and a relatively strong upward vertical velocity. This work indicates that different meteorological conditions, particularly precipitation and vertical velocity, are associated with PM 2.5 concentration over the source region in spring and fall.
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      Due to the adverse impacts of PM 2.5, particulate matter less than 2.5µg/m 3 , understanding their concentration mechanisms related to atmospheric processes is crucial. Various types of aerosol emission and meteorological conditions are the dominant ...

      Due to the adverse impacts of PM 2.5, particulate matter less than 2.5µg/m 3 , understanding their concentration mechanisms related to atmospheric processes is crucial. Various types of aerosol emission and meteorological conditions are the dominant factors of changing PM 2.5 concentration in the atmosphere. Therefore PM 2.5 emission has been controlled and its relationship with meteorological conditions has been actively researched. In this study, we identify the spatial patterns of high and low concentrations of PM 2.5 obtained from MERR A2 and investigate how PM 2.5 differences are associated with climate indicators, such as precipitation and vertical velocity, over the East Asia region in spring and fall. The results of Empirical Orthogonal Function (EOF) analysis show that most high concentration appears over inland east China from 2000-2013 in both spring and fall. Our results indicate that a combination of a strong downward vertical velocity, less precipitation, and cyclonic circulation at 850hPa interrupting PM 2.5 moving towards the downwind region, influences on high concentration over the PM 2.5 source region in spring. Similar to spring, less precipitation and downward vertical velocity pattern with weaker intensity appears in the fall with high PM 2.5. In the case of low PM 2.5, both spring and fall show more precipitation and a relatively strong upward vertical velocity. This work indicates that different meteorological conditions, particularly precipitation and vertical velocity, are associated with PM 2.5 concentration over the source region in spring and fall.

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      참고문헌 (Reference)

      1 이수철, "일본의 미세먼지 대책과 미세먼지 저감을 위한 한중일 협력" 한국환경경제학회 26 (26): 57-83, 2017

      2 전병일, "부산지역 최근 4년간(2015∼2018년) PM10과 PM2.5농도의 시·공간적 변화 특성" 한국환경과학회 29 (29): 749-760, 2020

      3 최효 ; 이미숙, "고비사막에서 황사의 유입 전, 후의 강릉시에서 매 시각별 PM10, PM2.5, PM1농도에 영향을 미치는 대기경계층과 상관관계 예측" 기후연구소 7 (7): 30-54, 2012

      4 "https://www.air.go.kr/"

      5 "https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/FAQ/"

      6 Bai, D., "Variations and possible causes of the December PM2.5 in Eastern China during 2000-2020" 11 : 1134940-, 2023

      7 Park, S., "Understanding influences of convective transport and removal processes on aerosol vertical distribution" 42 (42): 10-438, 2015

      8 Tian, L., "The scavenging process and physical removing mechanism of pollutant aerosols by different precipitation intensities" 30 (30): 279-291, 2019

      9 Randles, C. A., "The MERRA-2 aerosol reanalysis, 1980 onward. Part I: system description and data assimilation evaluation" 30 (30): 6823-6850, 2017

      10 Dee, D. P., "The ERA‐Interim reanalysis:configuration and performance of the data assimilation system" 137 (137): 553-597, 2011

      1 이수철, "일본의 미세먼지 대책과 미세먼지 저감을 위한 한중일 협력" 한국환경경제학회 26 (26): 57-83, 2017

      2 전병일, "부산지역 최근 4년간(2015∼2018년) PM10과 PM2.5농도의 시·공간적 변화 특성" 한국환경과학회 29 (29): 749-760, 2020

      3 최효 ; 이미숙, "고비사막에서 황사의 유입 전, 후의 강릉시에서 매 시각별 PM10, PM2.5, PM1농도에 영향을 미치는 대기경계층과 상관관계 예측" 기후연구소 7 (7): 30-54, 2012

      4 "https://www.air.go.kr/"

      5 "https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/FAQ/"

      6 Bai, D., "Variations and possible causes of the December PM2.5 in Eastern China during 2000-2020" 11 : 1134940-, 2023

      7 Park, S., "Understanding influences of convective transport and removal processes on aerosol vertical distribution" 42 (42): 10-438, 2015

      8 Tian, L., "The scavenging process and physical removing mechanism of pollutant aerosols by different precipitation intensities" 30 (30): 279-291, 2019

      9 Randles, C. A., "The MERRA-2 aerosol reanalysis, 1980 onward. Part I: system description and data assimilation evaluation" 30 (30): 6823-6850, 2017

      10 Dee, D. P., "The ERA‐Interim reanalysis:configuration and performance of the data assimilation system" 137 (137): 553-597, 2011

      11 Hersbach, H., "The ERA5 global reanalysis" 146 (146): 1999-2049, 2020

      12 Gao, J., "Temporal-spatial characteristics and source apportionment of PM2.5 as well as its associated chemical species in the Beijing-Tianjin-Hebei region of China" 233 : 714-724, 2018

      13 Ryu, Y. H., "Recent decreasing trends in surface PM2.5 over East Asia in the winter-spring season: different responses to emissions and meteorology between upwind and downwind regions" 21 (21): 200654-, 2021

      14 Ma, J., "PM2.5concentration distribution patterns and influencing meteorological factors in the central and eastern China during 1980-2018" 311 : 127565-, 2021

      15 He, Q., "Longterm variation of satellite-based PM2.5 and influence factors over East China" 8 (8): 11764-, 2018

      16 Hu, W., "Importance of regional PM2.5 transport and precipitation washout in heavy air pollution in the Twain-Hu Basin over Central China: observational analysis and WRF-Chem simulation" 758 : 143710-, 2021

      17 Colarco, P. R., "Impact of radiatively interactive dust aerosols in the NASA GEOS‐5climate model: sensitivity to dust particle shape and refractive index" 119 (119): 753-786, 2014

      18 Ye, H., "High-normal blood pressure (prehypertension) is associated with PM2.5 exposure in young adults" 29 (29): 40701-40710, 2022

      19 Qi, L., "Effects of meteorology changes on inter-annual variations of aerosol optical depth and surface PM2.5 in China—Implications for PM2.5 remote sensing" 14 (14): 2762-, 2022

      20 Wang, J., "Effects of meteorological conditions on PM2.5 concentrations in Nagasaki, Japan" 12 (12): 9089-9101, 2015

      21 Feng, Y., "Defending blue sky in China: effectiveness of the “Air Pollution Prevention and Control Action Plan” on air quality improvements from 2013 to 2017" 252 : 109603-, 2019

      22 Han, C., "Decrease in ambient fine particulate matter during COVID-19 crisis and corresponding health benefits in Seoul, Korea" 17 (17): 5279-, 2020

      23 Xing, Q., "Characteristics of PM2.5and PM10 Spatio-temporal distribution and influencing meteorological conditions in Beijing" 13 (13): 1120-, 2022

      24 Xiao, Q., "Changes in spatial patterns of PM2.5pollution in China 2000-2018: impact of clean air policies" 141 : 105776-, 2020

      25 Diehl, T., "Anthropogenic, biomass burning, and volcanic emissions of black carbon, organic carbon, and SO2 from 1980 to 2010 for hindcast model experiments" 12 (12): 24895-24954, 2012

      26 Hwang, S. H., "Ambient endotoxin and chemical pollutant (PM10, PM2.5, and O3) levels in South Korea" 19 (19): 786-793, 2019

      27 Zhou, Y., "A modeling study of the impact of crop residue burning on PM2.5 concentration in Beijing and Tianjin during a severe autumn haze event" 18 (18): 1558-1572, 2018

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