Nikos Gialesakis

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.

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.

The great importance of educating the next generation of citizens in climate change drivers, impacts as well as mitigation and adaptation measures has been highlighted by many international entities like the IPCC and the European Union. Additionally, many research groups have indicated the importance of incorporating real world data in teaching about climate change. This can take the form of educational tools that are aimed at data exploitation and visualization. One initiative exploring the creation of such tools is the Erasmus + project CLIMADEMY. In CLIMADEMY a video game was developed in the Unity engine which implemented real world data (from the NOAA database) for three greenhouse gasses concentrations (CH4, CO2, N2O) as well as the concentrations of scattering and absorbing aerosols. The video game’s primary function is to calculate the planet’s average temperature by 2100 based on the radiative forcing equations of the IPCC and the five aforementioned parameters. Additionally, the game is able to process which RCP scenario the word will be in based on these five parameters. The game is highly interactive, with students able to choose if these parameters will be based on an established database or if they want to explore other RCP scenarios. Furthermore, the game allows students to input custom values for CH4, CO2, N2O and aerosols in order to observe the average temperature of the planet in 2100 as well as the RCP scenario these values lead to. Τhe open source approach, gives students the chance to modify the game and include further features according to the specific educational needs. Finally, the educational value of this game is complemented by its user interface which, due to Unity’s capabilities as an engine, has vibrant colors and themes making the game aesthetically pleasing and interesting.

Black Carbon (BC) aerosol is a major short-lived climate forcer which plays a significant role in both atmospheric warming and air quality. BC is emitted during incomplete combustion during fossil fuel combustion, biomass burning and domestic heating but its emission fluxes estimate remains uncertain. The accurate representation of BC fluxes and its atmospheric fate in climate models is crucial for understanding BC contribution to climate change. This study aims to optimize the total BC emissions, using as starting point the emission inventories provided by CMIP6 for both anthropogenic and biomass burning sources. For this, a data assimilation global 3-d modeling system was used together with filter and aethalometer measurements of BC worldwide. The assimilation system used is the forward chemistry and transport model TM5-MP combined with the Carbon Tracker Data Assimilation Shell (CTDAS) that utilizes an Ensemble Kalman filter data assimilation method. The TM5-MP model simulates atmospheric chemistry and aerosol microphysics using the M7 module in the global atmosphere driven by ERA-5 meteorology and running with a 2ox3o horizontal resolution and 25 hybrid levels up to 0.1 hPa. The efficiency of the optimisation method is evaluated by comparing the forward simulations with the aerosol optical depth observations from the AERONET network before and after the emission optimization.

Over the past decades, air pollution mitigation measures have been applied extensively in Europe with a direct impact on the particulate matter (PM) load and composition. The Mediterranean atmospheric aerosol burden is not only characterized by emissions from anthropogenic sources but is also strongly influenced by the arid areas of North Africa and the Middle East, the marine environment, and atmospheric transformation. Here, we analyse data from various databases to investigate the evolution of unregulated particulate pollutants, namely ultrafine particles (UFP), desert dust (DD) and black carbon (BC) in the Eastern Mediterranean region over the last 20 years. Ground-based (AERONET) and satellite-based (MODIS/Terra) remote sensing observations, reanalysis products (MERRA-2) and in-situ observations (Finokalia environmental research station - finokalia.chemistry.uoc.gr) were used to investigate the variability and the trends of atmospheric aerosols.A decrease in the AOT was observed during the studied period, which was also reflected in the ground-based PM10 measurements. In addition to the decrease in sulfate content observed as a result of EU regulations, the AOT of dust was found to be decreasing as well. At the same time a statistically significant increase in the Ångström exponent was observed for all datasets, suggesting that the overall size of aerosols in the eastern Mediterranean is decreasing. Ground-based measurements of submicron atmospheric aerosol number concentrations showed an increase in total aerosol number, which was more pronounced for the UFP. At the same time, an increase in the absorption coefficient of aerosol particles was observed, indicating an increase in the BC content, which could contribute to the increase in UFP concentrations. Overall, it was found that despite the apparent decrease in aerosol constituents in terms of particulate matter due to the regulations applied in Europe over the last decades, pollutants such as BC and UFP, which are hazardous to human health and may influence climate at the regional scale, appear to be increasing and new approaches are required for effective clean air strategies.

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.

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.