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, PM 10 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 PM 10 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 (NO 2 ), sulphur dioxide (SO 2 ) and lag_PM 10 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 PM 10 concentrations. Predicted and observed PM 10 concentrations are compared, and several metrics, including the coefficients of determination (R 2 = 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 PM 10 concentrations. Traffic related air pollutants showed a weak association with PM 10 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.

The main objective of this study is to investigate temperature trend and distribution over 29 years period (1985 to 2013) in Makkah, Saudi Arabia, the holiest city for all Muslims. Monthly mean, maximum, and minimum temperature levels and their trends are investigated using Regression analysis and Theil-Sen nonparametric test. Also, trends in deviations from the reference period (1985-2013) are analyzed. The results showed that the number of hot days and nights increased annually by 1.5966 and 1.832, respectively, while the number of cold nights decreased annually by 0.4054 nights. Both Regression analysis and Theil-Sen test demonstrated positive trends in mean, minimum and maximum temperature levels. Trends are determined for various seasons and months of the year. The annual mean of daily mean, maximum and minimum temperature increased by 0.0398˚C, 0.0552˚C, 0.0398˚C per year, respectively. The minimum value of monthly mean temperature (Tmmean = 23.98˚C) was found in January, whereas the maximum value of the mean temperature (Tmmean= 35.95˚C) was found in July. Maximum value of monthly mean of daily maximum temperature (Tmmax = 43.88˚C) was found in June and minimum (30.54˚C) in January. The monthly mean of the daily minimum temperature (Tmmin) varied between a minimum of 18.82˚C in January and a maximum of 29.59˚C in August. From the above analysis it can be concluded that Makkah is suffering from a considerable warming temperature trend which is confirmed by the Theil-Sen non-parametric test and there is potentially an increasing medical risk from heat waves that will be more intense. This requires specific attention toward: the energy demands for extra cooling, water resources, draughts, and medical preparedness by the decision makers in order to minimize these risks to residents, pilgrims who gather annually to perform hajj rituals and other visitors.