Environmental Science and Pollution Research

, Volume 26, Issue 11, pp 10941–10950 | Cite as

Prediction of O3 in the respiratory system of children using the artificial neural network model and with selection of input based on gamma test, Ahvaz, Iran

  • Zeinab Ghaedrahmat
  • Mehdi Vosoughi
  • Yaser Tahmasebi BirganiEmail author
  • Abdolkazem NeisiEmail author
  • Gholamreza Goudarzi
  • Afshin Takdastan
Research Article


In recent years, concerns over the issue of air pollution have increased as one of the significant environmental and health problems. Air pollutants can be toxic or harmful to the life of plants, animals, and humans. Contrast to primary pollutants, ozone is a secondary pollutant that is produced by the reaction between primary precursors in the atmosphere. The average of air pollutant data was compiled for the purpose of analyzing their correlation with the pulmonary function of students and the FENO biomarker from the air pollutants of the Environmental Protection Agency. According to the average of 3 days, the concentration of ozone in the (S3) region was higher than the other regions, and this level was significantly different from the ANOVA test (p < 0.05). The results of artificial neural network modeling for three particular combinations in the cold season, two hidden layers with 9 and 12 neurons, with R2 = 0.859 and in the warm season, layer with 13 neurons, with R2 = 0.74, showed the best performance.


O3 Gamma test ANN model Respiratory system Children Ahvaz 



  1. Al-Gburi MA, Jonasson J-E, Nilsson M (2015) Using artificial neural networks to predict the restraint in concrete culverts at early age. SEI 25(3):258–265Google Scholar
  2. Asagha, Nkoro E, Udo SO (2012) Predicting global solar radiation using gamma test and local linear regression data models in Bauchi, Nigeria. IJSR 3(358):1375–1381Google Scholar
  3. Biancofiore F, Verdecchia M, Di Carlo P et al (2015) Analysis of surface ozone using a recurrent neural network. Sci Total Environ 514:379–387CrossRefGoogle Scholar
  4. da Silva IN, Spatti DH, Flauzino RA, Liboni LHB, dos Reis Alves SF (2017) Artificial neural network architectures and training processes artificial neural networks. Springer, Berlin, pp 21–28Google Scholar
  5. Daryanoosh M, Goudarzi G, Rashidi R et al (2017) Risk of morbidity attributed to ambient PM10 in the western cities of Iran. Toxin Rev:1–6Google Scholar
  6. Durrant PJ (2001) winGamma: A non-linear data analysis and modelling tool with applications to flood prediction. Unpublished PhD thesis, Department of Computer Science, Cardiff University, Wales, UKGoogle Scholar
  7. Emad S, Malay C (2011) The use of artificial neural network (ANN) form modeling, simulation and prediction of advanced oxidation process performance in recalcitrant wastewater treatment, artificial neural networks—application. Dr. chi Leung Patrick Hui (ed), ISBN: 978-953-307-188-6, InTech,
  8. Epton MJ, Dawson RD, Brooks WM, Kingham S, Aberkane T, Cavanagh JAE, Frampton CM, Hewitt T, Cook JM, McLeod S, McCartin F, Trought K, Brown L (2008) The effect of ambient air pollution on respiratory health of school children: a panel study. Environ Health 7(1):16CrossRefGoogle Scholar
  9. Evans D, Jones AJ (2008) Non-parametric estimation of residual moments and covariance. In: Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 2008, vol 464. The Royal Society, London, pp 2831–2846Google Scholar
  10. Faris H, Alkasassbeh M, Rodan A (2014) Artificial neural networks for surface ozone prediction: models and analysis. Pol J Environ Stud 23(2)Google Scholar
  11. Friedman JH, Bentley JM, Finkel RA (1977) An olgorithm for finding best matches in logarithmitic expected time. TOMS 3(3):200–226Google Scholar
  12. Gauderman WJ, Avol E, Gilliland F, Vora H, Thomas D, Berhane K, McConnell R, Kuenzli N, Lurmann F, Rappaport E, Margolis H, Bates D, Peters J (2004) The effect of air pollution on lung development from 10 to 18 years of age. N Engl J Med 351(11):1057–1067CrossRefGoogle Scholar
  13. Goudarzi G, Geravandi S, Foruozandeh H, Babaei AA, Alavi N, Niri MV, Khodayar MJ, Salmanzadeh S, Mohammadi MJ (2015) Cardiovascular and respiratory mortality attributed to ground-level ozone in Ahvaz, Iran. Environ Monit Assess 187(8):487CrossRefGoogle Scholar
  14. Hashemzadeh B, Idani E, Goudarzi G, et al. (2016) Effects of PM2. 5 and NO2 on the 8-isoprostane and lung function indices of FVC and FEV1 in students of Ahvaz city, Iran. Saudi J Biol Sci.
  15. Jansen KL, Larson TV, Koenig JQ, Mar TF, Fields C, Stewart J, Lippmann M (2005) Associations between health effects and particulate matter and black carbon in subjects with respiratory disease. Environ Health Perspect 113(12):1741–1746CrossRefGoogle Scholar
  16. Jones AJ, Tsui A, De Oliveira A (2002) Neural models of arbitrary chaotic systems: construction and the role of time delayed feedback in control and synchronization. Complex Int 9(2002)Google Scholar
  17. Lane C, Knight D, Burgess S, Franklin P, Horak F, Legg J, Moeller A, Stick S (2004) Epithelial inducible nitric oxide synthase activity is the major determinant of nitric oxide concentration in exhaled breath. Thorax 59(9):757–760CrossRefGoogle Scholar
  18. Luna A, Paredes M, de Oliveira G, Corrêa S (2014) Prediction of ozone concentration in tropospheric levels using artificial neural networks and support vector machine at Rio de Janeiro, Brazil. Atmos Environ 98:98–104CrossRefGoogle Scholar
  19. Marletta MA, Yoon PS, Iyengar R, Leaf CD, Wishnok JS (1988) Macrophage oxidation of L-arginine to nitrite and nitrate: nitric oxide is an intermediate. Biochem 27(24):8706–8711CrossRefGoogle Scholar
  20. Naimabadi A, Ghadiri A, Idani E, Babaei AA, Alavi N, Shirmardi M, Khodadadi A, Marzouni MB, Ankali KA, Rouhizadeh A, Goudarzi G (2016) Chemical composition of PM10 and its in vitro toxicological impacts on lung cells during the middle eastern dust (MED) storms in Ahvaz, Iran. Environ Pollut 211:316–324CrossRefGoogle Scholar
  21. Neisi A, Vosoughi M, Idani E, Goudarzi G, Takdastan A, Babaei AA, Ankali KA, Hazrati S, Shoshtari MH, Mirr I, Maleki H (2017a) Comparison of normal and dusty day impacts on fractional exhaled nitric oxide and lung function in healthy children in Ahvaz, Iran. ESPR 24(13):12360–12371Google Scholar
  22. Neisi A, Vosoughi M, Shirmardi M et al (2017b) Concentration of air pollutants as toxic matter in urban and rural areas of Ahvaz. Toxin Rev:1–8Google Scholar
  23. Pope CA III (2007) Mortality effects of longer term exposures to fine particulate air pollution: review of recent epidemiological evidence. Inhal Toxicol 19(sup1):33–38CrossRefGoogle Scholar
  24. Remesan R, Shamim M, Han D (2008) Model data selection using gamma test for daily solar radiation estimation. Hydrol Proced 22(21):4301–4309CrossRefGoogle Scholar
  25. Ricciardolo FL, Di Stefano A, Sabatini F, Folkerts G (2006) Reactive nitrogen species in the respiratory tract. Eur J Pharmacol 533(1–3):240–252CrossRefGoogle Scholar
  26. Sartor F, Snacken R, Demuth C, Walckiers D (1995) Temperature, ambient ozone levels, and mortality during summer, 1994, in Belgium. Environ Res 70(2):105–113CrossRefGoogle Scholar
  27. Sheffield M, Mabry S, Thibeault DW, Truog WE (2006) Pulmonary nitric oxide synthases and nitrotyrosine: findings during lung development and in chronic lung disease of prematurity. PEDS 118(3):1056–1064CrossRefGoogle Scholar
  28. Souza A, Aristones F, Goncalves F (2015) Modeling of surface and weather effects ozone concentration using neural networks in west Center of Brazil. J Climate Weather Forecast 3(1):4Google Scholar
  29. Tamas W, Notton G, Paoli C, Voyant C, Nivet M-L, Balu A (2014) Urban ozone concentration forecasting with artificial neural network in Corsica. MMCE 10(1):29–37Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Zeinab Ghaedrahmat
    • 1
    • 2
  • Mehdi Vosoughi
    • 3
  • Yaser Tahmasebi Birgani
    • 1
    • 2
    Email author
  • Abdolkazem Neisi
    • 1
    • 2
    Email author
  • Gholamreza Goudarzi
    • 1
    • 2
  • Afshin Takdastan
    • 1
    • 2
  1. 1.Department of Environmental Health Engineering, Student Research Committee Ahvaz Jundishapur University of Medical SciencesAhvazIran
  2. 2.Environmental Technologies Research CenterAhvaz Jundishapur University of Medical SciencesAhvazIran
  3. 3.Department of Environmental Health Engineering, School of HealthArdabil University of Medical SciencesArdabilIran

Personalised recommendations