Media & Research

Unveiling the drivers of atmospheric methane variability in Iran: A 20-year exploration using spatiotemporal modeling and machine learning

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Spatial  and temporal variability in atmospheric methane (XCH4) across Iran is influenced by meteorological factors rather  than anthropogenic sources. This 20-year study using satellite data and  machine learning identified high XCH4 in central and southern Iran, peaking  in summer. Key drivers include land surface temperature, wind speed, and soil  moisture, with vegetation cover showing a negative correlation. Understanding  these factors is crucial for methane reduction strategies.