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시내버스 실내공기질 IAQ 종합지수 개발

Development of IAQ Index for Indoor Air Quality in City Buses

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Objectives: This study developed an index for the indoor air quality management of city buses to allow the provision of indoor air quality information to city bus users. Methods: Nine city buses in Seoul were measured for PM10, PM2.5, CO2, temperature, and relative humidity through IoT sensors. Big data collected through the sensors was analyzed to identify indoor air quality on city buses and graded through the index. Results: As a result of dividing the measured city bus data into five grades through the IAQ index, PM10 was rated “good” for 30.4% of the total measured values, and 9.2% were rated “risky”. For PM2.5, 67.7 percent were rated “good” and 0.4 percent were rated “risky”. For CO2, 0.9% were ‘good’ and 1.1% were ‘risky’. The results of the classification through the IAQ index for city buses showed that the impact of good, normal, sensitive, bad, and dangerous were 2.7, 38.8, 46.0, 12.4, and 0.1%, respectively. According to the analysis by measurement area, Seocho-gu, Gangnam-gu, Seongdong-gu, Gwangjin-gu, and Dobong-gu are “normal” and other areas (Seodaemoon-gu, Jongno-gu, Yongsan-gu, Jung-gu, Seongbuk-gu, Dongdaemun-gu, Junggye-gu, Gangbuk-gu, and Nowon-gu) are all rated “sensitive”. Conclusions: When analyzing cases where PM10 and CO2 indices are in the “bad” zone, the concentration is generally found to increase during rush hour, during which there are a large number of passengers. It is expected that indoor air quality management in vehicles will be necessary during rush hour.

Abstract

Objectives: This study developed an index for the indoor air quality management of city buses to allow the provision of indoor air quality information to city bus users. Methods: Nine city buses in Seoul were measured for PM10, PM2.5, CO2, temperature, and relative humidity through IoT sensors. Big data collected through the sensors was analyzed to identify indoor air quality on city buses and graded through the index. Results: As a result of dividing the measured city bus data into five grades through the IAQ index, PM10 was rated “good” for 30.4% of the total measured values, and 9.2% were rated “risky”. For PM2.5, 67.7 percent were rated “good” and 0.4 percent were rated “risky”. For CO2, 0.9% were ‘good’ and 1.1% were ‘risky’. The results of the classification through the IAQ index for city buses showed that the impact of good, normal, sensitive, bad, and dangerous were 2.7, 38.8, 46.0, 12.4, and 0.1%, respectively. According to the analysis by measurement area, Seocho-gu, Gangnam-gu, Seongdong-gu, Gwangjin-gu, and Dobong-gu are “normal” and other areas (Seodaemoon-gu, Jongno-gu, Yongsan-gu, Jung-gu, Seongbuk-gu, Dongdaemun-gu, Junggye-gu, Gangbuk-gu, and Nowon-gu) are all rated “sensitive”. Conclusions: When analyzing cases where PM10 and CO2 indices are in the “bad” zone, the concentration is generally found to increase during rush hour, during which there are a large number of passengers. It is expected that indoor air quality management in vehicles will be necessary during rush hour.

참고문헌 (21)

  1. Kim YS, "Measurements of Carcinogenic Air Pollutants in Seoul Metropolitan Subway Stations", Journal of Environmental Health Sciences, 20(1), pp.19~27 (1994)
  2. 배현주, "서울시 미세먼지(PM10)와 초미세먼지(PM2.5)의 단기노출로 인한 사망영향", 한국환경보건학회지, 40(5), pp.346~354 (2014), 한국환경보건학회[DOI]
  3. "Amendment by Other ACT. ACT. Act No.728, 27 December 2017"[URL]
  4. Cetin M, "Measuring the Impact of Selected Plants on Indoor CO2 Concentrations", Pol. J. Environ. Stud, 25(3), pp.973~979 (2016)
  5. Oh GS, "Impact of Indoor CO Concentration on Work Performance", Journal of The Architectural Institute of Korea Planing &Design, 30(1), pp.385~386 (2020)
  6. "Public transport distribution rate" (2019)[URL]
  7. "The current status of public transportation in Seoul"[URL]
  8. "Purpose of public transportation"[URL]
  9. Marques G, "An Internet of Things-Based Environmental Quality Management System to Supervise the Indoor Laboratory Conditions", Appl. Sci, 9(3), pp.438~ (2019)
  10. Marques, G, "An indoor monitoring system for ambient assisted living based on internet of things architecture", Int. J. Environ. Res. Public Health, 13(11), pp.1152~ (2016)
  11. World Health Organization (WHO), "WHO Air quality guidelines for particulate metter, ozone, nitrogen dioxide and sulfur dioxide", ~ (2000)
  12. United States Environmental Protection Agency (US EPA), "Technical Assistance Document for the Reporting of Daily Air Quality – the Air Quality Index", ~ (2018)
  13. 김호현, "대중교통 관리 대상(지하철, 열차, 버스) 내 규제물질 분포 특성", 실내환경 및 냄새 학회지, 18(3), pp.218~227 (2019), 한국냄새환경학회[DOI]
  14. 안선민, "대중교통수단 중 시외버스 객실 내 유해물질 특성", 실내환경 및 냄새 학회지, 17(3), pp.199~206 (2018), 한국냄새환경학회[DOI]
  15. 신임철, "대중교통수단의 실내공기질 실태에 관한 연구", 실내환경 및 냄새 학회지, 9(2), pp.107~117 (2010), 한국냄새환경학회
  16. Ho-Hyun Kim, "Characteristics of exposure and health risk air pollutants in public buses in Korea", Environmental Science and Pollution Research, 27(29), pp.37087~37098 (2020), Springer Science and Business Media LLC[DOI]
  17. A study on the Management of Indoor Air Quality of Intercity Buses, "Ministry of Environment (ME)", 1~157 (2015)
  18. A advanced project to manage indoor air quality of express buses during running, "Ministry of Environment (ME)", 1~88 (2012)
  19. Ministry of Environment (ME), "Investigation and Management method of Indoor Air Quality by means of public transport, etc", 1~204 (2006)
  20. 김광욱, "시내버스 이용자의 서비스만족 영향요인에 관한 연구", 대한토목학회 논문집D, 32(3), pp.213~222 (2012), 대한토목학회[DOI]

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