Said Munir , Turki M. Habeebullah, Abdulaziz R. Seroji, Essam A. Morsy, Atef M.F. Mohammed, Waleed Abu Saud, Abdellatif E.A. Abdou, Abdul Hamid Awad

  • The Custodian of the Two Holy Mosques Institute for Hajj and Umrah Research, Umm Al-Qura University, Makkah, P.O. Box 6287, Saudi Arabia

Received: November 14, 2012
Revised: January 15, 2013
Accepted: January 15, 2013
Download Citation: ||https://doi.org/10.4209/aaqr.2012.11.0314  

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Cite this article:
Munir, S., Habeebullah, T.M., Seroji, A.R., Morsy, E.A., Mohammed, A.M., Saud, W.A., Abdou, A.E. and Awad, A.H. (2013). Modeling Particulate Matter Concentrations in Makkah, Applying a Statistical Modeling Approach. Aerosol Air Qual. Res. 13: 901-910. https://doi.org/10.4209/aaqr.2012.11.0314


 

ABSTRACT


Particulate matter originates from a variety of sources in Makkah, Saudi Arabia. Since Makkah is situated in an arid region and is a very busy city due to its religious importance in the Muslim world, PM10 concentrations here exceed the international and national air quality standards set for the protection of human health. The main aim of this paper is to model PM10 concentrations with the aid of meteorological variables (wind speed, wind direction, temperature, and relative humidity) and traffic related air pollutant concentrations (carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO2), sulphur dioxide (SO2) and lag_PM10 concentrations), which are measured at the same location near Al-Haram (the Holy Mosque) in Makkah. A Generalized Additive Model was developed for predicting hourly PM10 concentrations. Predicted and observed PM10 concentrations are compared, and several metrics, including the coefficients of determination (R2 = 0.52), Root Mean Square Error (RMSE = 84), Fractional Bias (FB = –0.22) and Factor of 2 (FAC2 = 0.88), are calculated to assess the performance of the model. The results of these, along with a graphical comparison of the predicted and observed concentrations, show that model is able to perform well. While effects of all the covariates were significant (p-value < 0.01), the meteorological variables, such as temperature and wind speed, seem to be the major controlling factors with regard to PM10 concentrations. Traffic related air pollutants showed a weak association with PM10 concentrations, suggesting road traffic is not the major source of these. No modeling study has been published with regards to air pollution in Makkah and thus this is the first work of this kind. Further work is required to characterize road traffic flow, speed and composition and quantify the contribution of each source, which is part of the ongoing project for managing the air quality in Makkah.


Keywords: Particulate matter; Air pollution; Makkah; Generalized additive model; Saudi Arabia


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