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      실시간 저가형 측정기를 활용한 미소환경에서의 개인 PM2.5 노출 특성 = Personal exposure characteristics of PM2.5 by microenvironment using real-time and low-cost monitors

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      https://www.riss.kr/link?id=A109275846

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      다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

      This study investigated the characteristics of personal PM2.5 exposure among 109 participants residing in Seoul over a two-month period, from February 2024 to April 2024. The participants were categorized into four sub-populations, and personal exposure to PM2.5 was assessed using portable monitors, GPS, and time-activity diaries. To understand the time-activity patterns, the daily occupancy rate for different microenvironments was calculated. Additionally, daily PM2.5 exposure contribution and integrated exposure were quantified. A time series analysis was conducted to identify differences in time-activity patterns and PM2.5 exposure among the sub-populations. ANOVA analysis indicated statistically significant differences in PM2.5 concentrations across populations and microenvironments (p<0.05). However, post-hoc analysis revealed specific microenvironments within certain sub-populations where PM2.5 concentration differences were not significant (p>0.05). All sub-populations spent more than 90% of their time indoors, and the results for exposure contribution and integrated exposure indicated that the home, which had the highest occupancy rate, was the most significant contributor to PM2.5 exposure. This study is expected to serve as foundational data for future indoor air quality management and the development of personalized strategies for reducing PM2.5 exposure.
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      This study investigated the characteristics of personal PM2.5 exposure among 109 participants residing in Seoul over a two-month period, from February 2024 to April 2024. The participants were categorized into four sub-populations, and personal exposu...

      This study investigated the characteristics of personal PM2.5 exposure among 109 participants residing in Seoul over a two-month period, from February 2024 to April 2024. The participants were categorized into four sub-populations, and personal exposure to PM2.5 was assessed using portable monitors, GPS, and time-activity diaries. To understand the time-activity patterns, the daily occupancy rate for different microenvironments was calculated. Additionally, daily PM2.5 exposure contribution and integrated exposure were quantified. A time series analysis was conducted to identify differences in time-activity patterns and PM2.5 exposure among the sub-populations. ANOVA analysis indicated statistically significant differences in PM2.5 concentrations across populations and microenvironments (p<0.05). However, post-hoc analysis revealed specific microenvironments within certain sub-populations where PM2.5 concentration differences were not significant (p>0.05). All sub-populations spent more than 90% of their time indoors, and the results for exposure contribution and integrated exposure indicated that the home, which had the highest occupancy rate, was the most significant contributor to PM2.5 exposure. This study is expected to serve as foundational data for future indoor air quality management and the development of personalized strategies for reducing PM2.5 exposure.

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      참고문헌 (Reference)

      1 Burki, T., "WHO introduces ambitious new air quality guidelines" 398 (398): 1117-, 2021

      2 Xue, J., "Understanding variability in time spent in selected locations for 7–12-year old children" 14 (14): 222-233, 2004

      3 Bhangar, S., "Ultrafine particle concentrations and exposures in seven residences in northern California" 21 (21): 132-144, 2011

      4 Buonanno, G., "Tracheobronchial and alveolar dose of submicrometer particles for different population age groups in Italy" 45 (45): 6216-6224, 2011

      5 Shen, H., "Temporal and spatial variation of PM2. 5 in indoor air monitored by low-cost sensors" 770 : 145304-, 2021

      6 Querol, X., "Spatial and temporal variations in airborne particulate matter(PM10 and PM2. 5)across Spain 1999–2005" 42 (42): 3964-3979, 2008

      7 Li, Z., "Sources, health effects and control strategies of indoor fine particulate matter(PM2. 5) : A review" 586 : 610-622, 2017

      8 National Institute of Environmental Research, "Research for personal exposure assessment by time activity patterns on a nation"

      9 박신영 ; 장혁 ; 권재민 ; 조용성 ; 이철민, "Proposal for concentration calibration method for field evaluation of particulate matter monitors based on light scattering using decision tree techniques" 22 (22): 314-327, 2023

      10 Krutmann, J., "Pollution and skin : from epidemiological and mechanistic studies to clinical implications" 76 (76): 163-168, 2014

      1 Burki, T., "WHO introduces ambitious new air quality guidelines" 398 (398): 1117-, 2021

      2 Xue, J., "Understanding variability in time spent in selected locations for 7–12-year old children" 14 (14): 222-233, 2004

      3 Bhangar, S., "Ultrafine particle concentrations and exposures in seven residences in northern California" 21 (21): 132-144, 2011

      4 Buonanno, G., "Tracheobronchial and alveolar dose of submicrometer particles for different population age groups in Italy" 45 (45): 6216-6224, 2011

      5 Shen, H., "Temporal and spatial variation of PM2. 5 in indoor air monitored by low-cost sensors" 770 : 145304-, 2021

      6 Querol, X., "Spatial and temporal variations in airborne particulate matter(PM10 and PM2. 5)across Spain 1999–2005" 42 (42): 3964-3979, 2008

      7 Li, Z., "Sources, health effects and control strategies of indoor fine particulate matter(PM2. 5) : A review" 586 : 610-622, 2017

      8 National Institute of Environmental Research, "Research for personal exposure assessment by time activity patterns on a nation"

      9 박신영 ; 장혁 ; 권재민 ; 조용성 ; 이철민, "Proposal for concentration calibration method for field evaluation of particulate matter monitors based on light scattering using decision tree techniques" 22 (22): 314-327, 2023

      10 Krutmann, J., "Pollution and skin : from epidemiological and mechanistic studies to clinical implications" 76 (76): 163-168, 2014

      11 Broich, A. V., "Personal monitoring of exposure to particulate matter with a high temporal resolution" 19 : 2959-2972, 2012

      12 Rojas-Bracho, L., "Personal exposures to particles and their relationships with personal activities for chronic obstructive pulmonary disease patients living in Boston" 54 (54): 207-217, 2004

      13 Menon, J. S., "Personal exposure to fine particulate matter concentrations in central business district of a tropical coastal city" 68 (68): 415-429, 2018

      14 Gentzke, A. S., "Peer Reviewed : Exposure to Secondhand Smoke and Secondhand E-Cigarette Aerosol Among Middle and High School Students" 16 : 2019

      15 World Health Organization, "Monitoring ambient air quality for health impact assessment"

      16 Hsu, W. T., "Model development and validation of personal exposure to PM2. 5 among urban elders" 316 : 120538-, 2023

      17 윤효정 ; 솨이 지엔페이 ; 김탁수 ; 서정관 ; 정다영 ; 류현수 ; 양원호, "Microenvironmental time activity patterns of weekday and weekend on korean adults" 16 (16): 182-186, 2017

      18 양원호 ; 이기영 ; 박경화 ; 윤충식 ; 손부순 ; 전준민 ; 이현수 ; 최욱희 ; 유승도 ; 한진석, "Microenvironmental time activity patterns of weekday and weekend on korean" 6 (6): 267-274, 2009

      19 Van Poppel, M., "Methodology for setup and data processing of mobile air quality measurements to assess the spatial variability of concentrations in urban environments" 183 : 224-233, 2013

      20 Hong, G. H., "Longterm evaluation and calibration of three types of low-cost PM2. 5 sensors at different air quality monitoring stations" 157 : 105829-, 2021

      21 김도헌 ; 신동민 ; 황정호, "Laboratory/Field evaluation and calibration method of low-cost PM sensor for indoor PM2. 5, PM10 measurement" 18 (18): 109-127, 2022

      22 National Institute of Environmental Research, "Korean exposure factors handbook"

      23 Du, X., "Intake fraction of PM2. 5 and NOX from vehicle emissions in Beijing based on personal exposure data" 233-243, 2012

      24 Baxter, L. K., "Influence of human activity patterns, particle composition, and residential air exchange rates on modeled distributions of PM2.5 exposure compared with centralsite monitoring data" 23 (23): 241-247, 2013

      25 박신영 ; 윤단기 ; 장혁 ; 윤성원 ; 이철민, "Indoor PM2. 5 concentration distribution and health risk assessment according to the implementation of a seasonal management system" 49 (49): 218-227, 2023

      26 Lee, K., "In-vehicle exposures to particulate matter and black carbon" 60 (60): 130-136, 2010

      27 Díaz, R. V., "Health risk by inhalation of PM2. 5 in the metropolitan zone of the City of Mexico" 72 (72): 866-871, 2009

      28 Pope III, C. A., "Health effects of fine particulate air pollution : lines that connect" 56 (56): 709-742, 2006

      29 Ilenič, A., "Fine particulate matter(PM2. 5)exposure assessment among active daily commuters to induce behaviour change to reduce air pollution" 912 : 169117-, 2024

      30 박진현 ; 양원호 ; 양소영 ; 박윤경 ; 류현수 ; 김은채 ; 최영태 ; 허정 ; 조만수, "Exposure and risk assessment of benzene and PM10 for sub-populations using Monte-Carlo simulations" 45 (45): 247-257, 2019

      31 Zikova, N., "Evaluation of new low-cost particle monitors for PM2. 5 concentrations measurements" 105 : 24-34, 2017

      32 박승식 ; 류준호 ; 정시원 ; 김광련 ; 박후경, "Evaluation of measurement reliability of light-scattering PM2. 5 monitor applied with referenced-channel calibration technology" 38 : 341-353, 2022

      33 배현주, "Effects of short-term exposure to PM10 and PM2. 5 on mortality in seoul" 40 (40): 346-354, 2014

      34 유승도 ; 차정훈 ; 김대선 ; 이종태, "Effects of fine particles on pulmonary function of elementary school children in Ulsan" 33 (33): 365-371, 2007

      35 황윤형 ; 이기영 ; 윤충식 ; 양원호 ; 유승도 ; 김근배, "Determination of similar exposure groups using weekday time activity patterns of urban populations" 42 (42): 353-364, 2016

      36 Bekö, G., "Contribution of various microenvironments to the daily personal exposure to ultrafine particles : Personal monitoring coupled with GPS tracking" 110 : 122-129, 2015

      37 Hoek, G., "Concentration response functions for ultrafine particles and all-cause mortality and hospital admissions : results of a European expert panel elicitation" 44 (44): 476-482, 2010

      38 Cunha-Lopes, I., "Children's exposure to sized-fractioned particulate matter and black carbon in an urban environment" 155 : 187-194, 2019

      39 Faria, T., "Children's exposure and dose assessment to particulate matter in Lisbon" 171 : 106666-, 2020

      40 Colbeck, I., "Characteristics of indoor/outdoor particulate pollution in urban and rural residential environment of Pakistan" 20 (20): 40-51, 2010

      41 Mcbride, S. J., "Bayesian hierarchical modeling of cardiac response to particulate matter exposure" 21 (21): 74-91, 2011

      42 Yang, F., "Assessment of personal integrated exposure to fine particulate matter of urban residents in Hong Kong" 69 (69): 47-57, 2019

      43 Park, J., "Assessment of PM2. 5population exposure of a community using sensor-based air monitoring instruments and similar time-activity groups" 11 (11): 1971-1981, 2020

      44 Morawska, L., "Airborne particles in indoor environment of homes, schools, offices and aged care facilities : The main routes of exposure" 108 : 75-83, 2017

      45 Ong, H., "Air pollution and child obesity : Assessing the feasibility of measuring personal PM2. 5 exposures and behaviours related to BMI in preschool-aged children in China" 16 : 100149-, 2019

      46 Song, S., "Acute health effects of urban fine and ultrafine particles on children with atopic dermatitis" 111 (111): 394-399, 2011

      47 Hussein, T., "Activity pattern of a selected group of school occupants and their family members in Helsinki—Finland" 425 : 289-292, 2012

      48 Bae, H. J., "A study on children's environmental disease due to PM2. 5" Korea Environment Institute 9 : 847-933, 2014

      49 Buonanno, G., "A comparison of submicrometer particle dose between Australian and Italian people" 169 : 183-189, 2012

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