Journal of Environmental Health Sciences (한국환경보건학회지)

Korean Society of Environmental Health (한국환경보건학회)
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Assessing PM2.5 Exposure and Contribution Rates by Cluster Microenvironments via a Time-Use Survey

생활시간조사 자료를 활용한 인구집단별 국소환경 초미세먼지(PM2.5) 노출 및 기여율 평가

  • Sanghoon Lee (Department of Health and Safety, Daegu Catholic University) ;
  • Youngtae Choe (Department of Health and Safety, Daegu Catholic University) ;
  • Daehwan Kim (Department of Health and Safety, Daegu Catholic University) ;
  • Jihun Shin (Department of Health and Safety Management, Songwon University) ;
  • Kyunghwa Sung (Center of Environmental Health Monitoring, Daegu Catholic University) ;
  • Jeong Kim (EILAP Co., Ltd.) ;
  • Gihong Min (Department of Health and Safety, Daegu Catholic University) ;
  • Wonho Yang (Department of Health and Safety, Daegu Catholic University)
  • 이상훈 (대구가톨릭대학교 보건안전학과) ;
  • 최영태 (대구가톨릭대학교 보건안전학과) ;
  • 김대환 (대구가톨릭대학교 보건안전학과) ;
  • 신지훈 (송원대학교 보건안전관리학과) ;
  • 성경화 (대구가톨릭대학교 환경보건모니터링센터) ;
  • 김정 ((주)이아이랩) ;
  • 민기홍 (대구가톨릭대학교 보건안전학과) ;
  • 양원호 (대구가톨릭대학교 보건안전학과)
  • Received : 2024.08.20
  • Accepted : 2024.09.12
  • Published : 2024.10.31
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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.

Keywords

Acknowledgement

본 연구는 환경부 환경산업기술원의 환경성질환예측평가기술개발 사업(과제번호: RS-2021-KE001349) 수행 중 작성되었으며 이에 감사드립니다.

References

  1. Kim D, Min G, Choe Y, Shin J, Woo J, Kim D, et al. Evaluation of population exposures to PM2.5 before and after the outbreak of COVID-19. J Environ Health Sci. 2021; 47(6): 521-529. 
  2. Atkinson RW, Mills IC, Walton HA, Anderson HR. 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. 2015; 25(2): 208-214. 
  3. World Health Organization (WHO). Health effects of particulate matter: policy implications for countries in eastern Europe, Caucasus and central Asia. Available: https://iris.who.int/handle/10665/344854 [accessed 30 July 2024]. 
  4. Kim OH. Effects of the particulate matter(PM10.PM2.5) on domestic tourism demand: evidence from the Korea National Tourism Survey. Int J Tour Hosp Res. 2021; 35(5): 131-144. 
  5. Kyung SY, Jeong SH. Adverse health effects of particulate matter. J Korean Med Assoc. 2017; 60(5): 391-398. 
  6. 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. 2023; 17(8): 25-37. 
  7. Kim TY. Design of fine dust monitoring system based on the internet of things. J Korea Inst Inf Electron Commun Technol. 2022; 15(1): 14-26. 
  8. Ma CJ, Kang GU. A study on the air pollution status and health effects in Tokyo. J Korean Soc Atmos Environ. 2023; 39(4): 469-477. 
  9. Yoon YH, Joo JC, Ahn HS, Nam SH. 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. 2013; 14(12): 6610-6617. 
  10. Yoon H, Shuai JF, Kim T, Seo J, Jung D, Ryu H, et al. Microenvironmental time-activity patterns of weekday and weekend on Korean adults. J Odor Indoor Environ. 2017; 16(2): 182-186. 
  11. Sim SH, Kim YS. Characterization and assessment of indoor air quality in newly constructed apartments-volatile organic compounds and formaldehyde-. J Environ Health Sci. 2006; 32(4): 275-281. 
  12. Park SE, Kim JY, Shin DC. Health risk of indoor radon in schools. Korean J Environ Educ. 1999; 12(2): 81-90. 
  13. He C, Morawska L, Hitchins J, Gilbert D. Contribution from indoor sources to particle number and mass concentrations in residential houses. Atmos Environ. 2004; 38(21): 3405-3415. 
  14. Quackenboss JJ, Krzyzanowski M, Lebowitz MD. Exposure assessment approaches to evaluate respiratory health effects of particulate matter and nitrogen dioxide. J Expo Anal Environ Epidemiol. 1991; 1(1): 83-107. 
  15. Kim H, Jung KM. Seasonal variations of human exposure to residential fine particles (PM2.5) and particle-associated polycyclic aromatic hydrocarbons in Chuncheon. J Envrion Toxicol. 2006; 21(1): 57-69. 
  16. Choi C, Yang H, Kim H, Kwon H. Evaluation of particulate matter (PM2.5) reduction through greenwalls in classrooms. J Environ Health Sci. 2023; 49(4): 183-189. 
  17. Lee B, Ban H, Jang Y, Lee K. Measurement of time/location for personal exposure assessment of air pollutants. J Environ Health Sci. 2016; 42(5): 314-323. 
  18. Ott WR. Human exposure assessment: the birth of a new science. J Expo Anal Environ Epidemiol. 1995; 5(4): 449-472. 
  19. Schwab M, Colome SD, Spengler JD, Ryan PB, Billick IH. Activity patterns applied to pollutant exposure assessment: data from a personal monitoring study in Los Angeles. Toxicol Ind Health. 1990; 6(6): 517-532. 
  20. Jung SW, Cho YS, Yang WH, Son BS. Comparison of exposure estimation methods on air pollution of residents of industrial complexes. J Environ Sci Int. 2013; 22(2): 151-161. 
  21. Guak S, Lee K. Review of exposure assessment methodology for future directions. J Environ Health Sci. 2022; 48(3): 131-137. 
  22. Kim EK, Kim ER. The analysis of the structure of time use of aged. J Korean stud. 2002; 17: 145-175. 
  23. U.S. Bureau of Labor Statistics. American time use survey. Available: https://www.bls.gov/tus/ [accessed 30 July 2024]. 
  24. Statistics Canada. Time use servey (TUS). Available: https://www.statcan.gc.ca/en/survey/household/4503 [accessed 30 July 2024]. 
  25. Statistics Bureau of Japan. Outline of the 2021 survey on time use and leisure activities. Available: https://www.stat.go.jp/english/data/shakai/2021/gaiyo.htm [accessed 30 July 2024]. 
  26. Shon AL. Characteristics and development of Time Use Survey. Korean Assoc Surv Res. 2000; 1(1): 135-148. 
  27. Noy D, Brunekreef B, Boleij JSM, Houthuijs D, De Koning R. The assessment of personal exposure to nitrogen dioxide in epidemiological studies. Atmos Environ. Part A. General Topics. 1990; 24(12): 2903-2909. 
  28. Lee SW. Classification of time activity pattern of urban population by season [master's]. [Seoul]: Graduate School of Seoul National University; 2017. 
  29. Park EO. Job Statisfaction comparison between gender and the influencing factors on job satisfaction. Korean J Occup Health Nurs. 2001; 10(2): 131-141. 
  30. Lee S, Lee K. 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. 2017; 14(7): 672. 
  31. Kim D, Min G, Shin J, Choe Y, Choi K, Sim SH, et al. Measurement of PM2.5 concentrations and comparison of affecting factors in residential houses in summer and autumn. J Environ Health Sci. 2024; 50(1): 16-24. 
  32. Jenkins RA, Ilgner RH, Tomkins BA, Peters DW. Development and application of protocols for the determination of response of real-time particle monitors to common indoor aerosols. J Air Waste Manag Assoc. 2004; 54(2): 229-241. 
  33. Lizana J, Almeida SM, Serrano-Jimenez A, Becerra JA, Gil-Baez M, Barrios-Padura A, et al. Contribution of indoor microenvironments to the daily inhaled dose of air pollutants in children. The importance of bedrooms. Build Environ. 2020; 183: 107188. 
  34. National Institute of Environment Research (NIER). Korean exposure factors handbook. Incheon: NIER; 2019 Oct. Report No.: NIER-GP2019-037. 
  35. National Institute of Environment Research (NIER). Korean exposure factors handbook for children. Incheon: NIER; 2019 Nov. Report No.: NIER-GP2019-038. 
  36. Bae S, Hong YC. Health effects of particulate matter. J Korean Med Assoc. 2018; 61(12): 749-755. 
  37. Yang WH. Time-activity pattern of students and indoor air quality of school. J Korean Inst Educ Facil. 2014; 21(6): 17-22. 
  38. Tran VV, Park D, Lee YC. Indoor air pollution, related human diseases, and recent trends in the control and improvement of indoor air quality. Int J Environ Res Public Health. 2020; 17(8): 2927. 
  39. Han MS, Kim M. Reconsideration on leisure education. J Sport Leis Stud. 2013; 54(1): 661-673. 
  40. Park SH. A study on participation in leisure activities and social development among high school students. Korean J Sports Sci. 2001; 10(2): 85-93. 
  41. Kim MS, Bae HO. A longitudinal study on children's time use change and the quality of life. Korean Soc Child Welf. 2022; 71(1): 61-92. 
  42. Song MJ, Lee HW. 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. 2019; 35(9): 57-64. 
  43. Seok J. A study of factors affecting use intention of untact medical diagnosis and consultation services. J Korea Contents Assoc. 2020; 20(12): 180-197. 
  44. Son WB, Jang JM. An exploratory research on affecting factors of commute time in the metropolitan area of Korea. GRI Rev. 2019; 21(2): 97-116. 
  45. Lee HS, Woo BL, Hwang MY, Park CH, Yu SD, Yang WH. Assessment of time activity pattern for workers. J Korean Soc Occup Environ Hyg. 2010; 20(2): 102-110. 
  46. Lim S, Kim J, Kim T, Lee K, Yang W, Jun S, et al. Personal exposures to PM2.5 and their relationships with microenvironmental concentrations. Atmos Environ. 2012; 47: 407-412. 
  47. Lee SC, Li WM, Chan LY. Indoor air quality at restaurants with different styles of cooking in metropolitan Hong Kong. Sci Total Environ. 2001; 279(1-3): 181-193. 
  48. Jang SJ. Legal policy trends and issues of biomass burning management in air pollution sources of Republic of Korea. Environ Law Policy. 2023; 31(2): 1-35. 
  49. Min JH, Hur MY, Kim H. Concentration distribution characteristics of PM2.5 and PM10, and health risk assessment for BaP at different types of restaurants. J Environ. 2022; 15(1): 33-40. 
  50. Li T, Cao S, Fan D, Zhang Y, Wang B, Zhao X, et al. Household concentrations and personal exposure of PM2.5 among urban residents using different cooking fuels. Sci Total Environ. 2016; 548-549: 6-12. 
  51. Siddiqui AR, Lee K, Bennett D, Yang X, Brown KH, Bhutta ZA, et al. Indoor carbon monoxide and PM2.5 concentrations by cooking fuels in Pakistan. Indoor Air. 2009; 19(1): 75-82. 
  52. Brauer M, Bartlett K, Regalado-Pineda J, Perez-Padilla R. Assessment of particulate concentrations from domestic biomass combustion in rural Mexico. Environ Sci Technol. 1996; 30(1): 104-109. 
  53. Wan MP, Wu CL, Sze To GN, Chan TC, Chao CYH. Ultrafine particles, and PM2.5 generated from cooking in homes. Atmos Environ. 2011; 45(34): 6141-6148. 
  54. Xue Y, Jiang Y, Jin S, Li Y. Association between cooking oil fume exposure and lung cancer among Chinese nonsmoking women: a meta-analysis. Onco Targets Ther. 2016; 9: 2987-2992. 
  55. Shi Y, Du Z, Zhang J, Han F, Chen F, Wang D, et al. Construction and evaluation of hourly average indoor PM2.5 concentration prediction models based on multiple types of places. Front Public Health. 2023; 11: 1213453. 
  56. Hou W, Wang J, Hu R, Chen Y, Shi J, Lin X, et al. Systematically quantifying the dynamic characteristics of PM2.5 in multiple indoor environments in a plateau city: implication for internal contribution. Environ Int. 2024; 186: 108641. 
  57. Brown KW, Sarnat JA, Koutrakis P. 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. 2012; 22(2): 161-172.