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Statistical methods and regression analysis of stratospheric ozone and meteorological variables in Isfahan

Author

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  • Hassanzadeh, S.
  • Hosseinibalam, F.
  • Omidvari, M.

Abstract

Data of seven meteorological variables (relative humidity, wet temperature, dry temperature, maximum temperature, minimum temperature, ground temperature and sun radiation time) and ozone values have been used for statistical analysis. Meteorological variables and ozone values were analyzed using both multiple linear regression and principal component methods. Data for the period 1999–2004 are analyzed jointly using both methods. For all periods, temperature dependent variables were highly correlated, but were all negatively correlated with relative humidity. Multiple regression analysis was used to fit the meteorological variables using the meteorological variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to obtain subsets of the predictor variables to be included in the linear regression model of the meteorological variables. In 1999, 2001 and 2002 one of the meteorological variables was weakly influenced predominantly by the ozone concentrations. However, the model did not predict that the meteorological variables for the year 2000 were not influenced predominantly by the ozone concentrations that point to variation in sun radiation. This could be due to other factors that were not explicitly considered in this study.

Suggested Citation

  • Hassanzadeh, S. & Hosseinibalam, F. & Omidvari, M., 2008. "Statistical methods and regression analysis of stratospheric ozone and meteorological variables in Isfahan," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(10), pages 2317-2327.
  • Handle: RePEc:eee:phsmap:v:387:y:2008:i:10:p:2317-2327
    DOI: 10.1016/j.physa.2007.12.016
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    Cited by:

    1. Madhvi Rana & Susheel K. Mittal & Gufran Beig, 2021. "Assessment and prediction of surface ozone in Northwest Indo-Gangetic Plains using ensemble approach," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(4), pages 5715-5738, April.
    2. NurIzzah M. Hashim & Norazian Mohamed Noor & Ahmad Zia Ul-Saufie & Andrei Victor Sandu & Petrica Vizureanu & György Deák & Marwan Kheimi, 2022. "Forecasting Daytime Ground-Level Ozone Concentration in Urbanized Areas of Malaysia Using Predictive Models," Sustainability, MDPI, vol. 14(13), pages 1-23, June.

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