Construction of an Improved Air Quality Index: A Case Report

  • Rui ZHAO Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
  • Yibo ZHANG Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
  • Sidai GUO Sichuan Province Cyclic Economy Research Centre, Southwest University of Science and Technology, Mianyang 621010, China

Abstract

Abstract We report a case to provide an improved air quality index (AQI) based upon association between individual health risk and Particulate matter (PM2.5) exposure. A Poisson sampling distribution model was used to quantify the health risk, in which the coefficient of exposure-response was derived from a simple Meta-analysis. The result shows that the old people are the most vulnerable population while exposing to PM2.5, for which they are advised to reduce intensity of their physical activities. It is expected that this study is insightful to create a nexus between air quality information and public communication, which help publics take appropriate actions on health protection.     

References

1. Guan D, Su X, Zhang Q, Peters GP, Liu Z, Lei Y, He K (2014). The socioeconomic drivers of China’s primary PM2.5 emis-sions. Environ Res Lett, 9(2): 024010.
2. Xing YF, Xu YH, Shi MH, Lian YX (2016). The impact of PM2.5 on the human res-piratory system. J Thorac Dis, 8(1): E69-E74.
3. Zhang Q, Qi W, Yao W, Wang M, Chen Y, Zhou Y (2016). Ambient particulate mat-ter (PM2.5/PM10) exposure and emergen-cy department visits for acute myocardial infarction in Chaoyang District, Beijing, China during 2014: a case-crossover study. J Epidemiol, 26(10): 538-545.
4. Xie Y, Bo L, Jiang S, Tian Z, Kan H, Li Y, Song W, Zhao J (2016). Individual PM2.5 exposure is associated with the impair-ment of cardiac autonomic modulation in general residents. Environ Sci Pollut Res Int, 23(10): 10255-10261.
5. Plaia A, Ruggieri M (2011). Air quality indi-ces: a review. Rev Environ Sci Bio/Technol, 10(2): 165-179.
6. Messner MJ, Berger P, Nappier SP (2014). Fractional poisson—a simple dose-response model for human norovirus. Risk Anal, 34(10):1820-1829.
7. World Health Organization (2006). Air quali-ty guidelines: global update 2005: particulate matter, ozone, nitrogen dioxide, and sulfur diox-ide. Geneva: World Health Organization.
8. Vincent JH, Mark D, Miller BG, Armbruster L, Ogden TL (1990). Aerosol inhalability at higher windspeeds. J Aerosol Sci, 21(4): 577-586.
9. Giorgini P, Di Giosia P, Grassi D, Ruben-fire M, D Brook R, Ferri C (2016). Air pollution exposure and blood pressure: an updated review of the literature. Curr Pharm Des, 22(1): 28-51.
10. Sowlat MH, Gharibi H, Yunesian M, Mahmoudi MT, Lotfi S (2011). A novel, fuzzy-based air quality index (FAQI) for air quality assessment. Atmos Environ, 45(12): 2050-2059.
11. Wong TW, San Tam WW, Yu ITS, Lau AKH, Pang SW, Wong AH (2013). De-veloping a risk-based air quality health in-dex. Atmos Environ, 76: 52-58.
12. Li L, Lin GZ, Liu HZ, Guo Y, Ou CQ, Chen PY (2015). Can the Air Pollution Index be used to communicate the health risks of air pollution?. Environ Pollut, 205: 153-160.
13. Sicard P, Lesne O, Alexandre N, Mangin A, Collomp R (2011). Air quality trends and potential health effects–development of an aggregate risk index. Atmos Environ, 45(5): 1145-1153.
Published
2019-07-18
How to Cite
1.
ZHAO R, ZHANG Y, GUO S. Construction of an Improved Air Quality Index: A Case Report. Iran J Public Health. 48(8):1523-1527.
Section
Case Report(s)