Cooding AOD-MAX-SUM: Dust Dynamics and Air Quality in Khuzestan, Iran (2018-2022)
by Alireza Yousefi Kebriya·Updated 1mo ago
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Description
From 2018 to 2022, this dataset analyzes dust dynamics in Khuzestan Province, Iran, using satellite-derived Aerosol Optical Depth (AOD) and Aerosol Absorption Index (AAI), ground-based PM₂.₅ and PM₁₀ measurements, HYSPLIT trajectory modeling, wind rose analysis, and wetland assessments. It was authored by Alireza Yousefi Kebriya and shared on figshare under a CC-BY-4.0 license. The study finds strong correlations between satellite and ground data and links dust peaks to drought, wetland shrinkage, and transboundary inflows.
Use Cases
Modeling dust source contributions and pathways based on HYSPLIT trajectory clustering and WPSCF/WCWT mapping.
Correlating satellite-derived Aerosol Optical Depth with ground-level PM₂.₅ and PM₁₀ concentrations for air quality validation.
Assessing the impact of wetland area and water level changes on local dust suppression and aerosol levels.
Identifying temporal patterns in dust events linked to hydrological states (healthy, transitional, critical) and drought periods.
Strengths
Includes multi-year temporal coverage from 2018 to 2022.
Integrates multiple data sources: satellite AOD/AAI, ground PM measurements, trajectory modeling, and wetland assessments.
Reports strong statistical correlations, such as R²=0.79 between AOD and PM₂.₅ and R²=0.78 between wetland area and AOD.
Provides specific quantified ranges for key variables, including PM₂.₅ (12–750 µg/m³) and AOD-Max (3.2–3.9).
Limitations
Column-level documentation is absent; field semantics must be inferred after download.
Row count is unknown, which may limit suitability assessment.
The dataset is very small (4.0 KB), suggesting it may contain summary results or a description rather than the full underlying raw data.