Modelling the Effect of COVID-19 Lockdown on Air Pollution in Makkah Saudi Arabia with a Supervised Machine Learning Approach.

To reduce the spread of COVID-19, lockdowns were implemented in almost every single country in the world including Saudi Arabia. In this paper, the effect of COVID-19 lockdown on O3, NO2, and PM10 in Makkah was analysed using air quality and meteorology data from five sites. Two approaches were employed: (a) comparing raw measured concentrations for the lockdown period in 2019 and 2020; and (b) comparing weather-corrected concentrations estimated by the machine learning approach with observed concentrations during the lockdown period. According to the first approach, the average levels of PM10 and NO2 decreased by 12% and 58.66%, respectively, whereas the levels of O3 increased by 68.67%. According to the second approach, O3 levels increased by 21.96%, while the levels of NO2 and PM10 decreased by 13.40% and 9.66%, respectively. The machine learning approach after removing the effect of changes in weather conditions demonstrated relatively less reductions in the levels of NO2 and PM10 and a smaller increase in the levels of O3. This showed the importance of adjusting air pollutant levels for meteorological conditions. O3 levels increased due to its inverse correlation with NO2, which decreased during the lockdown period.

Source Apportionment of Atmospheric PM10 in Makkah Saudi Arabia by Modelling Its Ion and Trace Element Contents with Positive Matrix Factorization and Generalised Additive Model.

In this paper, the emission sources of PM10 are characterised by analysing its trace elements (TE) and ions contents. PM10 samples were collected for a year (2019-2020) at five sites and analysed. PM10 speciated data were analysed using graphical visualization, correlation analysis, generalised additive model (GAM), and positive matrix factorization (PMF). Annual average PM10 concentrations (µg/m3) were 304.68 ± 155.56 at Aziziyah, 219.59 ± 87.29 at Misfalah, 173.90 ± 103.08 at Abdeyah, 168.81 ± 82.50 at Askan, and 157.60 ± 80.10 at Sanaiyah in Makkah, which exceeded WHO (15 µg/m3), USEPA (50 µg/m3), and the Saudi Arabia national (80 µg/m3) annual air quality standards. A GAM model was developed using PM10 as a response and ions and TEs as predictors. Among the predictors Mg, Ca, Cr, Al, and Pb were highly significant (p < 0.01), Se, Cl, and NO2 were significant (p < 0.05), and PO4 and SO4 were significant (p < 0.1). The model showed R-squared (adj) 0.85 and deviance explained 88.1%. PMF identified four main emission sources of PM10 in Makkah: (1) Road traffic emissions (explained 51% variance); (2) Industrial emissions and mineral dust (explained 27.5% variance); (3) Restaurant and dwelling emissions (explained 13.6% variance); and (4) Fossil fuel combustion (explained 7.9% variance).

Assessment of supplied water quality during mass gatherings in arid environments.

Mass gathering events commonly encounter environmental challenges that necessitate assurance of water quality and food security. The current outbreak of the coronavirus disease 2019 (COVID-19) call for maintaining safe drinking water supply and providing assessment tools of drinking water quality to avoid contamination in water sources or distribution networks. Arid environmental conditions also add more stress on supplied water to mass gathering events. Herein, we assess the quality of the water supply (desalinated 95% and groundwater 5%) in Makkah city, Saudi Arabia during a mass gathering event in 2019 (9.6 million people) for religious purposes. Fifty five samples were randomly collected from nine different districts of Makkah city, analyzed for TDS, turbidity, pH, EC, free Cl2, Al, Cd, Pb, Cr, F, major ions, coliform and E.coli bacteria and were finally used to estimate the water quality index (WQI). Major ions, trace elements and heavy metals analyses show values below permissible limits in most of the samples, while a few samples show slightly higher values. No bacterial count found in any sample. WQI values of all fifty-five samples were below 50 and were identified as "excellent water". The WQI variations could be attributed to the distribution network conditions rather than a direct impact of adding groundwater with uncontrolled chemical composition. The use of WQI to report the quality of water during mass gathering events to governmental authorities has been proved to be beneficial and should be applied for further mass gathering events worldwide.