Novel Insights into Atmospheric Methane Variability and Climatic Drivers in Eastern Saudi Arabia Using TROPOMI/Sentinel 5P Observations

Methane (CH₄​) is a critical atmospheric trace gas and a potent greenhouse gas contributing to global warming, yet its relationship with climate variables remains underexplored, particularly in eastern Saudi Arabia, which hosts over 70% of the country’s oil fields. This study presents the first comprehensive evaluation of the spatiotemporal variability of CH₄​ and its climatic drivers in eastern Saudi Arabia, using novel TROPOMI (Tropospheric Monitoring Instrument)/Sentinel-5P data and innovative approaches applied over the period from 2019 to 2024. Google Earth Engine (GEE)-based analysis shows significant annual and seasonal changes, with CH₄​ concentrations increasing from 1892 ppb to 1927 ppb. Seasonal patterns show maximum concentrations in summer and autumn and minimum concentrations in winter and spring. ArcGIS-based spatial trend analysis indicates an area-averaged increase of 5.61 ppb per year across the majority of the examined regions. These spatiotemporal variabilities are driven by anthropogenic factors (e.g., oil and gas activities, urbanization, and agriculture) and natural climatic factors (e.g., wetlands, soil activity, and changing climate variables). Emission sources are validated using the Global Fuel Exploitation Inventory (GFEIv2) dataset. Geographically Weighted Regression (GWR) modelling is adopted to understand the spatial-scale connections between CH₄ and climate variables. The results, with a model fit R² of 0.85, reveal that CH₄​ is negatively correlated with temperature, solar radiation, and precipitation, but positively correlated with humidity and wind speed. For instance, in 2023, the mean correlation coefficient between CH₄​ and temperature was -3.89, indicating that CH₄ concentrations decreased by 3.89 ppb across most of the studied areas per year for each unit increase in temperature. This decrease may be attributed to accelerated oxidative processes at higher temperatures, as the eastern region of Saudi Arabia is known for its consistently high temperatures. To assess the degree of importance of these connections, the Random Forest model is employed, outperforming statistical models with an R² of 0.75 and an RMSE of 2.79 ppb. The findings highlight that temperature and incoming solar radiation have the highest importance, followed by humidity, wind speed, and precipitation, in driving CH₄ variability. These results provide valuable insights to guide future research efforts across the Middle East and support policymakers in developing effective strategies for monitoring and managing atmospheric methane.