생활시간조사 자료를 활용한 인구집단별 국소환경 초미세먼지(PM2.5) 노출 및 기여율 평가
Assessing PM2.5 Exposure and Contribution Rates by Cluster Microenvironments via a Time-Use Survey
2
조회
0
다운로드
1
인용
0
참고문헌
키워드
초록
Background: People spend 80~90% of their day indoors, with only 10~20% of their time spent outdoors. Evaluating exposure accurately requires assessments based on an individual’s time-activity pattern. Objectives: The purpose of this study is to evaluate the exposure and contribution rates of PM2.5 by microenvironment, identify related exposure factors, and suggest management measures and priorities. Methods: This study analyzed the time-activity patterns of 3,984 weekday respondents in Seoul using data from the 2014 Time-Use Survey by Statistics Korea. The respondents were clustered, and occupational groups were estimated by conducting a frequency analysis of sociodemographic factors. Location data was collected at 10-minute intervals, followed by exposure scenario construction and active simulations. When calculating the exposure and contribution rates of PM2.5, the Korean exposure factors handbook was used to account for inhalation rates. Results: Most of the indoor microenvironments where people spend their time are residential. Students spend the most time indoors at 22.7 hours per day, followed by senior citizens at 22.5 hours, office workers at 22.0 hours, and stay-at-home parents at 21.8 hours. Although people spend little time in spaces such as outdoors, in transportation, and other indoor microenvironments, higher PM2.5 concentrations significantly increase the contribution rates. Among all clusters, even though cluster 10 (office workers) and cluster 2 (night security workers) spend relatively little time in other indoor microenvironments, such as Korean barbecue restaurants and pubs, they were included in the scenarios, resulting in higher exposure concentrations and contribution rates. Conclusions: The analysis of PM2.5 exposure contribution rates by microenvironment revealed that the highest exposure occurred in the ‘other indoor’ category, with Korean barbecue restaurants showing the highest concentration levels among them. Based on the PM2.5 exposure contribution rates in the microenvironments, this study suggests priority locations and population groups for targeted management.
Abstract
Background: People spend 80~90% of their day indoors, with only 10~20% of their time spent outdoors. Evaluating exposure accurately requires assessments based on an individual’s time-activity pattern. Objectives: The purpose of this study is to evaluate the exposure and contribution rates of PM2.5 by microenvironment, identify related exposure factors, and suggest management measures and priorities. Methods: This study analyzed the time-activity patterns of 3,984 weekday respondents in Seoul using data from the 2014 Time-Use Survey by Statistics Korea. The respondents were clustered, and occupational groups were estimated by conducting a frequency analysis of sociodemographic factors. Location data was collected at 10-minute intervals, followed by exposure scenario construction and active simulations. When calculating the exposure and contribution rates of PM2.5, the Korean exposure factors handbook was used to account for inhalation rates. Results: Most of the indoor microenvironments where people spend their time are residential. Students spend the most time indoors at 22.7 hours per day, followed by senior citizens at 22.5 hours, office workers at 22.0 hours, and stay-at-home parents at 21.8 hours. Although people spend little time in spaces such as outdoors, in transportation, and other indoor microenvironments, higher PM2.5 concentrations significantly increase the contribution rates. Among all clusters, even though cluster 10 (office workers) and cluster 2 (night security workers) spend relatively little time in other indoor microenvironments, such as Korean barbecue restaurants and pubs, they were included in the scenarios, resulting in higher exposure concentrations and contribution rates. Conclusions: The analysis of PM2.5 exposure contribution rates by microenvironment revealed that the highest exposure occurred in the ‘other indoor’ category, with Korean barbecue restaurants showing the highest concentration levels among them. Based on the PM2.5 exposure contribution rates in the microenvironments, this study suggests priority locations and population groups for targeted management.
참고문헌 (57)
- Kim D, "Evaluation of population exposures to PM2.5 before and after the outbreak of COVID-19", J Environ Health Sci, 47(6), pp.521~529 (2021)
- Atkinson RW, "Fine particle components and health-a systematic review and meta-analysis of epidemiological time series studies of daily mortality and hospital admissions", J Expo Sci Environ Epidemiol, 25(2), pp.208~214 (2015)
- "Health effects of particulate matter: policy implications for countries in eastern Europe, Caucasus and central Asia"[URL]
- Kim OH., "Effects of the particulate matter(PM10ㆍPM2.5) on domestic tourism demand: evidence from the Korea National Tourism Survey", Int J Tour Hosp Res, 35(5), pp.131~144 (2021)
- Kyung SY, "Adverse health effects of particulate matter", J Korean Med Assoc, 60(5), pp.391~398 (2017)
- Choi HJ, "The effect of fine dust risk perception on indoor and outdoor tourists : focusing on planned behavior theory(TPB)", J Korea Entertain Ind Assoc, 17(8), pp.25~37 (2023)
- Kim TY, "Design of fine dust monitoring system based on the internet of things", J Korea Inst Inf Electron Commun Technol, 15(1), pp.14~26 (2022)
- Ma CJ, "A study on the air pollution status and health effects in Tokyo", J Korean Soc Atmos Environ, 39(4), pp.469~477 (2023)
- Yoon YH, "Analyses of the current market trend and research status of indoor air quality control to develop an electrostatic force-based dust control technique", J Korea Acad Ind Coop Soc, 14(12), pp.6610~6617 (2013)
- Yoon H, "Microenvironmental time-activity patterns of weekday and weekend on Korean adults", J Odor Indoor Environ, 16(2), pp.182~186 (2017)
- Sim SH, "Characterization and assessment of indoor air quality in newly constructed apartments-volatile organic compounds and formaldehyde-", J Environ Health Sci, 32(4), pp.275~281 (2006)
- Park SE, "Health risk of indoor radon in schools", Korean J Environ Educ, 12(2), pp.81~90 (1999)
- He C, "Contribution from indoor sources to particle number and mass concentrations in residential houses", Atmos Environ, 38(21), pp.3405~3415 (2004)
- Quackenboss JJ, "Exposure assessment approaches to evaluate respiratory health effects of particulate matter and nitrogen dioxide", J Expo Anal Environ Epidemiol, 1(1), pp.83~107 (1991)
- Kim H, "Seasonal variations of human exposure to residential fine particles (PM2.5) and particle-associated polycyclic aromatic hydrocarbons in Chuncheon", J Envrion Toxicol, 21(1), pp.57~69 (2006)
- Choi C, "Evaluation of particulate matter (PM2.5) reduction through greenwalls in classrooms", J Environ Health Sci, 49(4), pp.183~189 (2023)
- Lee B, "Measurement of time", location for personal exposure assessment of air pollutants, 2016, pp.42(5), 314~323
- Ott WR, "Human exposure assessment : the birth of a new science", J Expo Anal Environ Epidemiol, 5(4), pp.449~472 (1995)
- Schwab M, "Activity patterns applied to pollutant exposure assessment : data from a personal monitoring study in Los Angeles", Toxicol Ind Health, 6(6), pp.517~532 (1990)
- Jung SW, "Comparison of exposure estimation methods on air pollution of residents of industrial complexes", J Environ Sci Int, 22(2), pp.151~161 (2013)
- Guak S, "Review of exposure assessment methodology for future directions", J Environ Health Sci, 48(3), pp.131~137 (2022)
- Kim EK, "The analysis of the structure of time use of aged", J Korean stud, 17, pp.145~175 (2002)
- "American time use survey"[URL]
- "Time use servey (TUS)"[URL]
- "Outline of the 2021 survey on time use and leisure activities"[URL]
- Shon AL, "Characteristics and development of Time Use Survey", Korean Assoc Surv Res, 1(1), pp.135~148 (2000)
- Noy D, "The assessment of personal exposure to nitrogen dioxide in epidemiological studies", Atmos Environ. Part A. General Topics, 24(12), pp.2903~2909 (1990)
- Lee SW, "Classification of time activity pattern of urban population by season", master, pp.2017
- Park EO, "Job Statisfaction comparison between gender and the influencing factors on job satisfaction", Korean J Occup Health Nurs, 10(2), pp.131~141 (2001)
- Lee S, "Seasonal differences in determinants of time location patterns in an urban population : a large population-based study in Korea", Int J Environ Res Public Health, 14(7), pp.672~ (2017)
- Kim D, "Measurement of PM2.5 concentrations and comparison of affecting factors in residential houses in summer and autumn", J Environ Health Sci, 50(1), pp.16~24 (2024)
- Jenkins RA, "Development and application of protocols for the determination of response of realtime particle monitors to common indoor aerosols", J Air Waste Manag Assoc, 54(2), pp.229~241 (2004)
- Lizana J, "Contribution of indoor microenvironments to the daily inhaled dose of air pollutants in children. The importance of bedrooms", Build Environ, 183, pp.107188~ (2020)
- Korean exposure factors handbook, "National Institute of Environment Research(NIER)", NIER, ~, pp.NIER-GP2019-037 (2019)
- Korean exposure factors handbook for children, "National Institute of Environment Research (NIER)", NIER, ~, pp.NIER-GP2019-038 (2019)
- Bae S, "Health effects of particulate matter", J Korean Med Assoc, 61(12), pp.749~755 (2018)
- Yang WH, "Time-activity pattern of students and indoor air quality of school", J Korean Inst Educ Facil, 21(6), pp.17~22 (2014)
- Tran VV, "Indoor air pollution, related human diseases, and recent trends in the control and improvement of indoor air quality", Int J Environ Res Public Health, 17(8), pp.2927~ (2020)
- Han MS, "Reconsideration on leisure education", J Sport Leis Stud, 54(1), pp.661~673 (2013)
- Park SH, "A study on participation in leisure activities and social development among high school students", Korean J Sports Sci, 10(2), pp.85~93 (2001)
- Kim MS, "A longitudinal study on children’s time use change and the quality of life", Korean Soc Child Welf, 71(1), pp.61~92 (2022)
- Song MJ, "A study on the concept and type of integration senior center-focusing on the development of the network of leisure welfare facilities for the elderly", J Archit Inst Korea Plan Des, 35(9), pp.57~64 (2019)
- Seok J, "A study of factors affecting use intention of untact medical diagnosis and consultation services", J Korea Contents Assoc, 20(12), pp.180~197 (2020)
- Son WB, "An exploratory research on affecting factors of commute time in the metropolitan area of Korea", GRI Rev, 21(2), pp.97~116 (2019)
- Lee HS, "Assessment of time activity pattern for workers", J Korean Soc Occup Environ Hyg, 20(2), pp.102~110 (2010)
- Lim S, "Personal exposures to PM2.5 and their relationships with microenvironmental concentrations", Atmos Environ, 47, pp.407~412 (2012)
- Lee SC, "Indoor air quality at restaurants with different styles of cooking in metropolitan Hong Kong", Sci Total Environ, 279(1-3), pp.181~193 (2001)
- Jang SJ, "Legal policy trends and issues of biomass burning management in air pollution sources of Republic of Korea", Environ Law Policy, 31(2), pp.1~35 (2023)
- Min JH, "Concentration distribution characteristics of PM2.5 and PM10, and health risk assessment for BaP at different types of restaurants", J Environ, 15(1), pp.33~40 (2022)
- Li T, "Household concentrations and personal exposure of PM2.5 among urban residents using different cooking fuels", Sci Total Environ, 548-549, pp.6~12 (2016)
- Siddiqui AR, "Indoor carbon monoxide and PM2.5 concentrations by cooking fuels in Pakistan", Indoor Air, 19(1), pp.75~82 (2009)
- Brauer M, "Assessment of particulate concentrations from domestic biomass combustion in rural Mexico", Environ Sci Technol, 30(1), pp.104~109 (1996)
- Wan MP, "Ultrafine particles, and PM2.5 generated from cooking in homes", Atmos Environ, 45(34), pp.6141~6148 (2011)
- Xue Y, "Association between cooking oil fume exposure and lung cancer among Chinese nonsmoking women : a meta-analysis", Onco Targets Ther, 9, pp.2987~2992 (2016)
- Shi Y, "Construction and evaluation of hourly average indoor PM2.5 concentration prediction models based on multiple types of places", Front Public Health, 11, pp.1213453~ (2023)
- Hou W, "Systematically quantifying the dynamic characteristics of PM2.5 in multiple indoor environments in a plateau city: implication for internal contribution", Environ Int, 186, pp.108641~ (2024)
- Brown KW, "Concentrations of PM2.5 mass and components in residential and non-residential indoor microenvironments:the sources and composition of particulate exposures study", J Expo Sci Environ Epidemiol, 22(2), pp.161~172 (2012)