This study provides an overview of the atmospheric drivers of climate change over Greece (Eastern Mediterranean), focusing on greenhouse gases (GHG: carbon dioxide, CO₂; methane, CH₄; etc.). CO₂ in Greece is mostly produced by energy production, followed by transport, construction, and industry. Waste management is the largest anthropogenic source of methane, accounting for 47% of total CH₄ emissions, surpassing emissions from the agricultural sector in 2017, while the energy sector accounts for the remaining 10.5%. In situ simultaneous observations of GHG concentrations in Greece conducted at three sites with different topologies (urban background; Athens, regional background; Finokalia and free troposphere; and Helmos) during the last 5 years (2019–2023) showed increasing trends of the order of 2.2 ppm·yr⁻¹ and ~15 ppb·yr⁻¹ for CO₂ and CH₄, respectively, in line with the global trends. These increasing trends were found from both ground-based and satellite-based remote-sensing observations. Finally, during the lockdown period due to the COVID-19 global pandemic, a 58% reduction in CO₂ levels was observed in the urban background site of Athens after subtracting the regional background levels from Finokalia, while the respective reduction in CH₄ was of only the order of 15%, highlighting differences in emission sources.

The Eastern Mediterranean experiences a rapid acceleration of climate warming mainly due to the continuous growth of greenhouse gases (GHG) in the atmosphere. Carbon dioxide (CO2) is a key contributor to the human-induced greenhouse effect due to its long lifetime and high atmospheric concentrations. With its levels continuing to rise, the need to mitigate its emissions is of utmost importance. Towards this direction, atmospheric models are used to assess the influence of emissions on atmospheric composition. Emission fields used in models, called bottom-up emission inventories, provide information on the amounts and the distribution of the emitted pollutants. However, these emissions are coupled with large uncertainties at small spatiotemporal scales. Therefore, optimization of these emission estimates is needed to increase accuracy and thus support the identification of targets for emission reduction. In this study, we are optimizing the anthropogenic emissions of CO2 over Greece by using the data assimilation system CTDAS-WRF (Carbon Tracker Data Assimilation Shell) that uses an Ensemble Kalman filter data assimilation method. As a forward model, we use WRF-CHEM with the GHG mechanism that allows passive tracer transport of CO2. The sum of emissions from all different anthropogenic sectors from the CAMS anthropogenic emission inventory (CAMS-GLOB-ANT 5.3) is used as input to the model, in addition to biogenic (VPRM) and biomass burning emissions (FINN 2.5). The simulations are then compared to in-situ, FTIR and satellite observations of CO2 that have been assimilated by CTDAS. The differences between the observations and the simulations are assumed to be only due to the uncertainty of the anthropogenic emissions. Therefore, our system is optimizing only these emissions. Preliminary results show the largest underestimates by the bottom-up inventories over the city of Athens.

Methane (CH4) is the second most abundant anthropogenic greenhouse gas after CO2. Emissions from the Eastern Mediterranean and Middle East (EMME) are important, as the region hosts a large share of global oil and gas production and thus offers significant mitigation potential. We use TROPOMI satellite observations in combination with the Lagrangian transport model FLEXPART and the inversion framework FLEXINVERT+ to estimate CH4 emissions in the EMME region for 2020. We perform sensitivity experiments to address methodological challenges and better quantify emission uncertainties. Our inversions show robust downward corrections of emissions around the Persian Gulf relative to the EDGAR v8.0 inventory, consistent with the recently released EDGAR_2025_GHG dataset, yielding total emissions of 22.4 (±1.9) Tg yr−1 in the EMME region. At the national scale, we derive emissions of 4.6 (±0.4), 3.6 (±1.1), 3.5 (±0.8), 2.8 (±0.4), and 1.9 (±0.4) Tg yr−1 CH4 for Iran, Saudi Arabia, Turkey, Iraq, and Egypt, respectively. While many countries in the region appear to substantially underestimate their emissions, Greece, subject to mandatory reporting requirements, reports emissions comparable to our inversion estimates. Our results suggest a decrease in emissions in the EMME region during 2020, coinciding with reduced oil demand during the COVID-19 epidemic. Our satellite-based inversions provide robust constraints in regions with strong emission signals and good observational coverage (e.g. Iran, Iraq), while other regions show greater sensitivity to uncertainty settings and prior estimates. Our sensitivity analyses highlight the importance of baseline optimization and its associated uncertainty.

Methane (CH₄) is the second most abundant anthropogenic greenhouse gas after CO₂. Emissions from the Eastern Mediterranean and Middle East (EMME) are important, as the region hosts a large share of global oil and gas production and thus offers significant mitigation potential. We use TROPOMI satellite observations in combination with the Lagrangian transport model FLEXPART and the inversion framework FLEXINVERT+ to estimate CH₄ emissions in the EMME region for 2020. We perform sensitivity experiments to address methodological challenges and better quantify emission uncertainties. Our inversions show robust downward corrections of emissions around the Persian Gulf relative to the EDGAR v8.0 inventory, consistent with the recently released EDGAR_2025_GHG dataset, yielding total emissions of 22.4 (±1.9) Tg yr⁻¹ in the EMME region. At the national scale, we derive emissions of 4.6 (±0.4), 3.6 (±1.1), 3.5 (±0.8), 2.8 (±0.4), and 1.9 (±0.4) Tg yr⁻¹ CH₄ for Iran, Saudi Arabia, Turkey, Iraq, and Egypt, respectively. While many countries in the region appear to substantially underestimate their emissions, Greece, subject to mandatory reporting requirements, reports emissions comparable to our inversion estimates. Our results suggest a decrease in emissions in the EMME region during 2020, coinciding with reduced oil demand during the COVID-19 epidemic. Our satellite-based inversions provide robust constraints in regions with strong emission signals and good observational coverage (e.g. Iran, Iraq), while other regions show greater sensitivity to uncertainty settings and prior estimates. Our sensitivity analyses highlight the importance of baseline optimization and its associated uncertainty.