Arid regions are a major source of mineral dust aerosol. Transport from these sources can have a great impact on aerosol climatology in distant regions. In order to assess the impact of dust on climate we must understand how dust properties change after long distance transport from sources. This study addresses the changes in columnar aerosol properties when mineral dust outbreaks from western Africa arrive over the eastern Caribbean after transport across the Atlantic Ocean, a transit of 5–7 days. We use data from the NASA Aerosol Robotic Network (AERONET) located at five Caribbean and two western Africa sites to characterize changes in columnar aerosol properties: aerosol optical depth (AOD), size distribution, single scattering albedo, and refractive indexes. We first characterized the local aerosol climatology at each site and then using air mass back trajectories we identified those days when trajectories over Caribbean sites back-tracked to western Africa. Over the period 1996–2014 we identify 3174 days, an average of 167 days per year, when the air mass over the Caribbean sites could be linked to at least one of the two western Africa sites. For 1162 of these days, AOD data are available for the Caribbean sites as well as for the corresponding western Africa sites about 5–7 days earlier, when the air mass passed over these sites. We identified dust outbreaks as those air masses yielding AOD ≥ 0.2 and an Ångström exponent below 0.6. On this basis of the total 1162 days, 484 meet the criteria for mineral dust outbreaks. We observe that the AOD at 440 nm decreases by about 0.16 or 30 % during transport. The volume particle size distribution shows a similar decrease in the volume concentration, mainly in the coarse mode. The single scattering albedo, refractive indexes, and asymmetry factor remain unchanged. The difference in the effective radius over western Africa sites with respect to Caribbean sites ranges between 0 and −0.3 µm. Finally we conclude that in about half of the cases only non-spherical dust particles are present in the atmosphere over the western Africa and Caribbean sites, while in the other cases dust particles were mixed with other types of aerosol particles.

Over the last decades, the impact of mineral dust from African deserts on human health and climate has been of great interest to the scientific community. In this paper, the climatological analysis of dusty events of the past 20 years in the Caribbean area has been performed using a particulate approach. The focus is made on June 2020 extreme event dubbed “Godzilla”. To carry out this study, different types of data were used (ground-based, satellites, model, and soundings) on several sites in the Caribbean islands. First, the magnitude of June 2020 event was clearly highlighted using satellite imagery. During the peak of this event, the value of particulate matter with an aerodynamic diameter of less than 10 μ$\mathsf{\mu }$m ($PM10$) reached a value 9 times greater than the threshold recommended by the World Health Organization in one day. Thereafter, the $PM10$, the aerosol optical depth, and the volume particle size distribution analyses exhibited their maximum values for June 2020. We also highlighted the exceptional characteristics of the Saharan air layer in terms of thickness and wind speed for this period. Finally, our results showed that the more the proportion of particulate matter with an aerodynamic diameter of less than 2.5 μ$\mathsf{\mu }$m ($PM2.5$) in $PM10$ increases, the more the influence of sea salt aerosols is significant.

Atmospheric aerosols significantly impact air quality, human health, and regional climate, with regions like the Caribbean Basin affected by various aerosol types, including marine, anthropogenic, and desert dust particles. This study utilizes Agglomerative Hierarchical Clustering (AHC) to analyze more than a decade of Aerosol Robotic Network (AERONET) data (2007–2023) from four Caribbean islands: Barbados, Guadeloupe, Puerto Rico, and Cuba. We examined sixteen physical parameters, including Aerosol Optical Depth (AOD), Angstrom Exponent (AE), and Volume Particle Size Distribution (VPSD), to identify distinct aerosol regimes and groups of daily measurements displaying similar aerosol optical properties. The originality of this work lies in the significant number of parameters considered to achieve a classification free of arbitrary orientation. The clustering method identified specific periods and aerosol characteristics, revealing seasonal patterns of background marine aerosols and Saharan dust events. By referring to existing research and using analysis tools such as VPSD and AE versus AOD representation, we aimed to define value ranges of physical parameters attributable to marine, dust, and mixed aerosols in the Caribbean region. The results underscore the diversity of aerosol sources and their seasonal variations across the Caribbean, providing critical insights for improving regional air quality management. This classification approach integrates comprehensive aerosol properties and is reinforced by the analysis of atmospheric circulation using the HYSPLIT model. These findings not only advance the characterization of aerosol regimes but also contribute to sustainable air quality management practices by providing actionable data to mitigate the adverse health and environmental impacts of aerosols.

The Caribbean basin is a geographical area with a high prevalence of asthma due to mineral dust. As such, it is crucial to analyze the dynamic behavior of particulate pollutants in this region. The aim of this study was to investigate the relationships between particulate matter with aerodynamic diameters less than or equal to 2.5 and 10 μm (PM2.5 and PM10) using Hilbert–Huang transform (HHT)-based approaches, including the time-dependent intrinsic correlation (TDIC) and time-dependent intrinsic cross-correlation (TDICC) frames. The study utilized datasets from Puerto Rico from between 2007 and 2010 to demonstrate the relationships between two primary particulate matter concentration datasets of air pollution across multiple time scales. The method first decomposes both time series using improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) to obtain the periodic scales. The Hilbert spectral analysis identified two dominant peaks at a weekly scale for both PM types. High amplitude contributions were sustained for long and continuous time periods at seasonal to intra-seasonal scales, with similar trends in spectral amplitude observed for both types of PM except for monthly and intra-seasonal scales of six months. The TDIC method was used to analyze the resulting modes with similar periodic scales, revealing the strongest and most stable correlation pattern at quarterly and annual cycles. Subsequently, lagged correlations at each time scale were analyzed using the TDICC method. For high-frequency PM10 intrinsic mode functions (IMFs) less than a seasonal scale, the value of the IMF at a given time scale was found to be dependent on multiple antecedent values of PM2.5. However, from the quarterly scale onward, the correlation pattern of the PM2.5-PM10 relationship was stable, and IMFs of PM10 at these scales could be modeled by the lag 1 IMF of PM2.5. These results demonstrate that PM2.5 and PM10 concentrations are dynamically linked during the passage of African dust storms.