Variability and Trends of PM<sub>2.5</sub> Across Different Climatic Zones in Saudi Arabia: A Spatiotemporal Analysis

Variability and Trends of PM<sub>2.5</sub> Across Different Climatic Zones in Saudi Arabia: A Spatiotemporal Analysis

Atmospheric fine particles (PM<sub>2.5</sub>) pose significant health risks by penetrating deep into the lungs and causing respiratory and cardiovascular issues. In Saudi Arabia, high PM<sub>2.5</sub> levels are driven by its geographic location and extreme climate. Therefore...

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Main Authors: Said Munir, Muhammad H. Siddiqui, Turki M. A. Habeebullah, Arjan O. Zamreeq, Norah E. Al-Zahrani, Alaa A. Khalil, M. Nazrul Islam, Abdalla A. Baligh, Muhammad Ismail, Saud Z. Al-Boqami
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Atmosphere
Subjects:
fine particulate matter (PM<sub>2.5</sub>)
spatial and temporal trends
air quality
MERRA-2 reanalysis
satellite-derived data
Saudi Arabia
Online Access:https://www.mdpi.com/2073-4433/16/4/463
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Summary:Atmospheric fine particles (PM<sub>2.5</sub>) pose significant health risks by penetrating deep into the lungs and causing respiratory and cardiovascular issues. In Saudi Arabia, high PM<sub>2.5</sub> levels are driven by its geographic location and extreme climate. Therefore, analysis of PM<sub>2.5</sub> spatiotemporal variability is crucial for understanding its causes, impacts, and effective management. This study analyzed MERRA-2 reanalysis PM<sub>2.5</sub> data for 23 years (2001–2023). MERRA-2 data were validated with in situ observations in terms of several statistical metrics, including RMSE, FAC2, MAE, and Correlation Coefficient. The results revealed a significant spatial variation in PM<sub>2.5</sub> levels, with higher concentrations observed in the eastern and southeastern regions and lower concentrations observed in the western and northwestern regions, a trend confirmed by ground-level observations. Employing the robust Theil–Sen technique, temporal trends in PM<sub>2.5</sub> concentrations indicated an overall decreasing trend over the study period. At most sites, PM<sub>2.5</sub> levels increased until 2010 and then started decreasing, probably due to government interventions for reducing emissions, combating desertification, and enhancing tree plantations. Non-linear modeling provided a more accurate representation of complex trends compared to simple linear models. The findings underscore the need for continued national and regional efforts to mitigate PM<sub>2.5</sub> pollution by addressing its emission sources.
ISSN:2073-4433

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