Seasonal AOD analysis based on AERONET observations in North and West Africa over 2010–2019
Published in Earth & Environment
This study presents a comprehensive characterization of aerosols across selected Eurafrican stations over a decade (2010–2019), utilizing Aerosol Optical Depth (AOD) and Angstrom Exponent (AE) data from the surface-based AERONET Version 3, Level 2 dataset. The main objective is to understand the spatial and seasonal variability of aerosols and their relationship with regional meteorological patterns, with particular focus on how different aerosol types dominate across varied geographic and climatic regions.
Four stations were selected for analysis, representing both eastern and western parts of the Eurafrican domain: Cairo_EMA_2 (Egypt) and Tamanrasset_INM (Algeria) in the east, and IER Cinzana (Mali) and Cape Verde in the west. To ensure accurate and reliable comparisons across sites, the AOD data were first detrended to remove inherent seasonal trends. Validated AOD and AE values were then employed to classify aerosol types and assess their seasonal behavior, providing insight into the dominant aerosol sources and their temporal dynamics.
Aerosol Type Classification and Key Findings
The results confirm that Saharan dust is the dominant aerosol type at the eastern stations of Cairo and Tamanrasset. This is evidenced by AOD values less than 1 and AE values less than 1, which indicate the prevalence of large, coarse particles typical of desert dust. In contrast, the western stations of IER Cinzana and Cape Verde display both AOD and AE values greater than 1, signifying finer aerosol particles. These finer particles are likely influenced by sources such as biomass burning and anthropogenic pollution, which are common in these regions.
Seasonal analysis further revealed that the monsoon season is the period of highest dust activity. Conversely, the winter season exhibited lower AOD values at the eastern stations, highlighting the strong seasonal influence of regional meteorological cycles on aerosol loading and type. The seasonal cycles show that the monsoon not only drives dust transport but also affects aerosol optical properties through changes in humidity, wind patterns, and atmospheric mixing.
Linear regression analysis between AOD and AE was conducted for the various sites. At Tamanrasset_INM, an inverse relationship was observed, with AE mean and standard deviation of approximately 0.01 ± 0.28, supporting the dominance of dust aerosols driven by strong surface winds. This inverse coupling between AE and AOD is significant because fine-mode aerosols generally have AE > 1, while coarse-mode aerosols show AE < 1. The root mean square error (RMSE) and mean absolute error (MAE) for regression fits were low, indicating good agreement and reliable characterization of aerosol optical properties.
Detrending of AOD time series was necessary to separate seasonal variations from longer-term trends. Seasonal patterns can otherwise mask relative changes in aerosol loading. This approach enables a more precise understanding of aerosol behavior over time and across regions.
Seasonal cycles were examined in detail, classifying data into winter, premonsoon, monsoon, and postmonsoon periods, which collectively represent about 25% of the dataset. The study found that AOD spectral dominance begins in the premonsoon and extends through the monsoon season, with characteristic dust loading. AE values during this period ranged from 0.22 to 0.33, all below 1, further confirming the coarse dust particle presence.
Winter was characterized by drier local conditions, with AE values peaking at 0.33 and showing typical dust aerosol peaks in AOD. These results emphasize the key role that local meteorology and atmospheric chemistry play in influencing aerosol concentrations. For instance, low-pressure regions tend to have higher AOD loading due to enhanced aerosol uplift and transport.
The inverse correlation between AE and AOD was again confirmed for Cairo_EMA_2, with seasonal variations clearly indicating that different aerosol types dominate at different times of the year. Winter spectral means showed negative deviations in AOD and AE, consistent with dust dominance, whereas premonsoon periods exhibited more varied aerosol properties.
The spatial trends highlight the asymmetric AOD variations, particularly pronounced in the eastern region after detrending. This asymmetry may result from additional aerosol types such as black carbon or other absorbing aerosols contributing to the optical depth.
The comprehensive decadal analysis across the Eurafrican stations revealed distinct regimes of aerosol sources and types, including dust, biomass burning, and urban pollution, each with unique optical and physical-chemical properties. These sources are affected by long-range transport and seasonality, demonstrating the complex nature of aerosol dynamics in the region.
The findings provide a clearer understanding of the spatial heterogeneity and seasonal shifts in aerosol properties across Eurafrican regions. Saharan dust remains the principal aerosol type in eastern stations, while western stations show more influence from finer aerosols related to biomass burning and human activities. The study confirms the monsoon season as a major driver for dust transport and highlights how meteorological cycles shape aerosol characteristics.
The study link is here: Recent study in aerosol distribution
Follow the Topic
-
Discover Environment
This is a transdisciplinary, open-access journal that provides a leading platform for the rapid dissemination of knowledge and advances covering the research and innovation that is taking place across the environmental sector.
Related Collections
With Collections, you can get published faster and increase your visibility.
Environmental Pollutants: Origins, Pathways, Impacts, and Sustainable Solutions
Pollution is a critical threat to ecosystems, human health, and the planet’s future. From industrial waste in China to microplastics in the Mediterranean and PFAS contamination in the U.S., pollutants spread across air, water, and soil, harming wildlife and communities worldwide. Understanding how these contaminants move, transform, and impact the environment is key to designing effective solutions.
This collection brings together cutting-edge research on pollution sources, environmental behavior, risks, and innovative cleanup strategies—covering everything from heavy metals in mining regions to pharmaceutical waste in urban waterways. We highlight advances in environmental science, green technology, and policy to tackle both long-standing and emerging threats like e-waste and AI-driven monitoring. The topics include, but are not limited to, the following:
• Pollution Origins: Industrial, agricultural, and urban sources, including legacy and emerging contaminants.
• Environmental Pathways: How pollutants travel through air, water, soil, and food chains.
• Risks and Impacts: Effects on biodiversity and human health, from local hotspots to global crises.
• Cleanup and Prevention: Nature-based solutions (like wetland restoration) and high-tech innovations (such as catalytic oxidation).
• Policy and Tools: Smart regulations, predictive modeling, and new detection methods.
This Collection supports and amplifies research related to: SDG 11
Keywords:PFAS, Heavy metals, Microplastics, Emerging Contaminants, Emission sources, Environmental forensics, Ecological indicators, Pollution sources, Contaminant transport, Ecological risk assessment, Pollutant fate and transformation, Bioaccumulation, Ecological restoration, Remediation technologies, Sustainable pollution management
Publishing Model: Open Access
Deadline: May 01, 2026
Socio-ecological Systems and Climate Resilience
Climate change poses a significant threat to both biophysical systems and societal communities. Climate resilience is embedded within socio-ecological systems (SES), where social actors and the ecological units they manage are interdependent as part of their livelihoods. Achieving climate resilience requires adjustments to social structures, political and economic systems, power dynamics, worldviews, cultures, values, and ideologies in order to create a sustainable, climate-resilient society. Additionally, there is a need to bridge emerging technology (e.g., AI) with social innovation to enhance the capacity for real-time, data-driven decision-making, foster community-resilient responses to climate impacts, and ultimately reshape climate adaptation policies and practices.
The Collection invites the submission of interdisciplinary and policy-oriented research with innovative systems approaches and emerging methodologies for decision-making and co-designing climate solutions. We encourage contributions from a wide range of fields, including environmental science, sociology, human geography, environmental economics, environmental public health and public policy, etc. We seek research that focuses on the interconnectedness between human societies and natural ecological systems, the impacts of climate change on human well-being, community adaptive capacity, innovative governance solutions, knowledge co-production (with an emphasis on local and indigenous knowledge for climate adaptation), climate equity, local and global collaboration efforts, and the role of technology and education in enhancing climate resilience.
Manuscripts presenting empirical studies, theoretical frameworks, policy analysis, and case studies that contribute both to theoretical advancements and practical applications are encouraged.
Keywords:Socio-Ecological Resilience, Climate Governance, Technological And Social Innovation, Indigenous Knowledge Systems, Sustainability Transition, Human And Ecological Well-Being
Publishing Model: Open Access
Deadline: Dec 30, 2025
Please sign in or register for FREE
If you are a registered user on Research Communities by Springer Nature, please sign in