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Assessment of Air Quality through Multiple Air Quality Index Models – A Comparative Study

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
It is important to indicate air quality level in metropolitan areas as it is harmful to public health. Air quality index (AQI) is a useful tool to convert air quality pollutants concentrations into a single number representing air quality level. There are many air quality index models in the literature to represent air quality level. Two models were selected to assess the air quality in Mosul city. The first model utilizes the highest sub-index depending on USEPA pollutants standards. The second model includes the weights of all pollutants in the model as an aggregated air quality index (AAQI) model. Air quality concentrations were collected using a fixed monitoring station located in the courtyard of the public library for a year. The results illustrate that the values of aggregated Air quality index model were higher than those of the USEPA model. Air quality category "Moderate" was dominant in winter and spring for the two models. In contrast, the category "Unhealthy for sensitive group" was dominant in summer and autumn. Furthermore, the category "Unhealthy" appeared only with aggregated model in autumn. The contribution of air pollutants in AQI can be ranked as PM10, SO2, NO2, CO and O3 from higher to lower. The study concluded that the AAQI is comprehensive and more workable in environmental management.
Rocznik
Strony
110--116
Opis fizyczny
Bibliogr. 21 poz., rys., tab.
Twórcy
  • Mosul University, Environmental Research Center, Mosul, Iraq
Bibliografia
  • 1. Bishoi B., Prakash A., Jain V. 2009. A comparative study of air quality index based on factor analysis and US-EPA methods for an urban environment. Aerosol and Air Quality Research, 9, 1–17.
  • 2. EPA (United States Environmental Protection Agency) 2009. Technical assistance document for reporting of daily air quality-the air quality index (AQI). EPA-454/B-09-001. U.S. Environmental Protection Agency, North Carolina.
  • 3. Eugene K.C., John J., Zunckel M. 2007. A novel air pollution index based on the relative risk of daily mortality associated with short-term exposure to common air pollutants. Atmospheric Environment, 41(38), 8442–8454.
  • 4. Hu J., Ying Q., Wang Y., Zhang H. 2015. Characterizing multi-pollutant air pollution in China: comparison of three air quality indices. Environment International, 84, 17–25.
  • 5. Kampa M., Castanas E. 2008. Human health effects of air pollution. Environmental Pollution, 151, 362–367.
  • 6. Kyrkilis G., Chaloulakou A., Kassomenos P.A. 2007. Development of an aggregate Air Quality Index for an urban Mediterranean agglomeration: relation to potential health effects. Environment International, 33, 670–676.
  • 7. Li Y., Tang Y., Fan Z., Zhou H., Yang Z. 2018. Assessment and comparison of three different air quality indices in China. Environmental Engineering Research, 23(1), 21–27.
  • 8. Mirabelli M.C., Ebelt S., Damon S.A. 2020. Air Quality Index and air quality awareness among adults in the United States. Environmental Research, 183, 109185.
  • 9. Oakes M., Baxter L., Long T.C. 2014. Evaluating the application of multi-pollutant exposure metrics in air pollution health studies. Environment International, 69, 90–99.
  • 10. Olvera-García M.´A., Carbajal-Hern´andez J.J., S´anchez-Fern´andez L.P., Hern´andez- Bautista I. 2016. Air quality assessment using a weighted Fuzzy Inference System. Ecological Inference, 33, 57–74.
  • 11. Pineiro G., Perelmanb S., Guerschmanb J.P., Parueloa J.M. 2008. How to evaluate models: Observed vs. predicted or predicted vs. observed? Ecological Modelling, 216, 316–322.
  • 12. Plaia A., Ruggieri M. 2011. Air quality indices: A review. Reviews in Environmental Science and Biotechnology, 10, 165–170.
  • 13. Ruggieri M., Plaia A. 2012. An aggregate AQI: comparing different standardizations and introducing a variability index. Science of the Total Environment, 420, 263–272.
  • 14. Sahbeni G., Nagy G., Gurgenidze T. 2019. Examination of Air Quality Indexes (AQIs) Role in Urban Air Quality Assessment. Asian Journal of Applied Science and Technology, 3(1), 130–142.
  • 15. Shah D.P., Patel P. 2021. A comparison between national air quality index, India and composite air quality index for Ahmedabad, India. Environmental Challenges, 5, 100356.
  • 16. Shihab A.S. 2021. Assessment of Ambient Air Quality of Mosul City/Iraq Via Air Quality Index. Journal of Ecological Engineering, 22(10), 241–250.
  • 17. Shihab A.S., Al-Jarrah O.A.I. 2015. The levels of ozone and nitrogen oxides and its relationship with metrological factors. Al-Rafidain Engineering Journal, 23(4), 98–109. [in Arabic]
  • 18. Shihab A.S., Fadhil M.N., Jumaa O.K 2010. Distribution of dustfall in selected sites in Mosul city and around it/ Iraq. Tishreen University Journal for Scientific Researches and Studies, Engineering Series, 32(6), 191–203.
  • 19. Shihab A.S., Taha A.T. 2014. Suspended particulate levels in the left bank residential areas of Mosul city and its relation with some metrological factors. Al-Rafidain Engineering Journal, 22(3), 158–164. [in Arabic]
  • 20. Stieb D.M., Burnett R.T., Smith-Doiron M., Brion O., Shin H.H., Economou V. 2008. A new multi-pollutant, No-threshold air quality health index based on short-term associations observed in daily time-series analyses. J. of Air & Waste Management Association, 58, 435–450.
  • 21. Zhang X.P., Lin M.H. 2020. Comparison between two air quality index systems in study of urban air pollution in China and its socio-economic determinants. Journal of University of Chinese Academy of Sciences, 37(1), 39–50.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-c19c93fe-b5fd-4f78-9f5d-3dbac0b741cd
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