Exploring Spatial and Temporal Dynamics of Red Sea Air Quality through Multivariate Analysis, Trajectories, and Satellite Observations

Abstract

The Red Sea, a significant ecoregion and vital marine transportation route, has experienced a consistent rise in air pollution in recent years. Hence, it is imperative to assess the spatial and temporal distribution of air quality parameters across the Red Sea and identify temporal trends. This study concentrates on utilizing multiple satellite observations to gather diverse meteorological data and vertical tropospheric columns of aerosols and trace gases, encompassing carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3). Furthermore, the study employs the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to analyze the backward trajectory of air mass movement, aiding in the identification of significant sources of air pollutants. A principal component analysis (PCA) with varimax rotation is applied to explore the relationship and co-variance between the aerosol index (AI), trace gas concentrations, and meteorological data. The investigation reveals seasonal and regional patterns in the tropospheric columns of trace gases and AI over the Red Sea. The correlation analysis indicates medium-to-low positive correlations (0.2 < r < 0.6) between air pollutants (NO2, SO2, and O3) and meteorological parameters, while negative correlations (−0.3 < r < −0.7) are observed between O3, aerosol index, and wind speed. The results from the HYSPLIT model unveil long-range trajectory patterns. Despite inherent limitations in satellite observations compared to in situ measurements, this study provides an encompassing view of air pollution across the Red Sea, offering valuable insights for future researchers and policymakers.