We employ the WRF-Chem model to study summertime air pollution, the intense photochemical activity and their impact on air quality over the eastern Mediterranean. We utilize three nested domains with horizontal resolutions of 80, 16 and 4 km, with the finest grid focusing on the island of Cyprus, where the CYPHEX campaign took place in July 2014. Anthropogenic emissions are based on the EDGAR HTAP global emission inventory, while dust and biogenic emissions are calculated online. Three simulations utilizing the CBMZ-MOSAIC, MOZART-MOSAIC, and RADM2-MADE/SORGAM gas-phase and aerosol mechanisms are performed. The results are compared with measurements from a dense observational network of 14 ground stations in Cyprus. The model simulates T_2 m, P_surf, and WD_10 m accurately, with minor differences in WS_10 m between model and observations at coastal and mountainous stations attributed to limitations in the representation of the complex topography in the model. It is shown that the south-eastern part of Cyprus is mostly affected by emissions from within the island, under the dominant (60 %) westerly flow during summertime. Clean maritime air from the Mediterranean can reduce concentrations of local air pollutants over the region during westerlies. Ozone concentrations are overestimated by all three mechanisms (9 % ≤ NMB ≤ 23 %) with the smaller mean bias (4.25 ppbV) obtained by the RADM2-MADE/SORGAM mechanism. Differences in ozone concentrations can be attributed to the VOC treatment by the three mechanisms. The diurnal variability of pollution and ozone precursors is not captured (hourly correlation coefficients for O₃ ≤ 0.29). This might be attributed to the underestimation of NO_x concentrations by local emissions by up to 50 %. For the fine particulate matter (PM_2.5), the lowest mean bias (9 µg m⁻³) is obtained with the RADM2-MADE/SORGAM mechanism, with overestimates in sulfate and ammonium aerosols. Overestimation of sulfate aerosols by this mechanism may be linked to the SO₂ oxidation in clouds. The MOSAIC aerosol mechanism overestimates PM_2.5 concentrations by up to 22 µg m⁻³ due to a more pronounced dust component compared to the other two mechanisms, mostly influenced by the dust inflow from the global model. We conclude that all three mechanisms are very sensitive to boundary conditions from the global model for both gas-phase and aerosol pollutants, in particular dust and ozone.

We describe and evaluate a high-resolution real-time air quality forecast system over the Eastern Mediterranean, based on a regional, online coupled atmospheric chemistry and aerosol model. The Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) is used to perform daily, 3 d forecasts of regulated pollutants (NO₂, O₃, PM_2.5) over the Eastern Mediterranean, applying three nested domains with horizontal resolutions of 50, 10 and 2 km, the latter focusing on Cyprus. Natural (dust, sea-salt, biogenic) emissions are calculated online, while anthropogenic emissions are based on the Emissions Database for Global Atmospheric Research – Hemispheric Transport of Air Pollution (EDGAR-HTAP) global emission inventory. A high spatial (1 km) and temporal (hourly) anthropogenic emission inventory is used for the island of Cyprus in the innermost domain. The model skill in forecasting the concentrations of atmospheric pollutants is evaluated using measurements from a network of nine ground stations in Cyprus and compared with the forecasting skill of the EU Copernicus Atmosphere Monitoring Service (CAMS). The forecast of surface temperature, pressure, and wind speed is found to be accurate, with minor discrepancies between the modelled and observed 10 m wind speed at mountainous and coastal sites attributed to the limited representation of the complex topography of Cyprus. Compared to CAMS, the WRF-Chem model predicts with higher accuracy the NO₂ mixing ratios at the residential site with a normalized mean bias (NMB) of 7 % during winter and −44 % during summer, whereas the corresponding biases for CAMS are −81 % and −84 %. Due to the high temporal resolution of the anthropogenic emission inventory, the WRF-Chem model captures more accurately the diurnal profiles of NO₂ and O₃ mixing ratios at the residential site. Background PM_2.5 concentrations influenced by long-range transport are overestimated by the WRF-Chem model during winter (NMB = 54 %), whereas the corresponding NMB for CAMS is 11 %. Our results support the adoption of regional, online coupled air quality models over chemical transport models for real-time air quality forecasts.

We describe and evaluate a high-resolution real-time air quality forecast system over the Eastern Mediterranean, based on a regional, on-line coupled atmospheric chemistry and aerosol model. The WRF/Chem model is used to perform daily, 3-day forecasts of regulated pollutants NO₂, O₃, PM2.5 over the Eastern Mediterranean, with three nested domains with horizontal resolutions of 50 km, 10 km and 2 km, focusing on Cyprus. Natural (dust, sea-salt, biogenic) emissions are calculated online, while anthropogenic emissions are based on the EDGAR-HTAP global emission inventory. A high spatial (1 km) and temporal (hourly) anthropogenic emission inventory is used for the island of Cyprus in the innermost domain. The model skill in forecasting the concentrations of atmospheric pollutants is evaluated using measurements from a network of nine ground stations in Cyprus and compared with the forecast skill of the EU Copernicus Atmosphere Monitoring Service – CAMS. The forecast of surface temperature, pressure, and wind speed is found to be accurate, with minor discrepancies between the modelled and observed 10 m wind speed at mountainous and coastal sites attributed to the limited representation of the complex topography of Cyprus. Compared to CAMS, the WRF/Chem model predicts with higher accuracy the NO₂ mixing ratios at the residential site with a normalized mean bias of 7 % during winter and −44 % during summer, whereas the corresponding biases for CAMS are −81 % and −84 %. Due to the high temporal resolution of the anthropogenic emission inventory, the WRF/Chem model captures more accurately the diurnal profiles of NO₂ and O₃ mixing ratios at the residential site. Background PM2.5 concentrations influenced by long-range transport are overestimated by the WRF/Chem model during winter NMB = 54 % whereas the corresponding NMB for CAMS is 11 %. Our results support the adoption of regional, on-line coupled air quality models over chemical transport models for real-time air quality forecasts.

As many large metropolitan areas have pledged for a rapid decrease of their greenhouse gas emissions through ambitious climate mitigation policies, the need for rapid and robust quantification methods became more pressing. At the global scale, the scarcity of satellite carbon dioxide (CO₂) observations remains the major roadblock to producing independent city-scale CO₂ emissions estimates from atmospheric data, except for a handful of cities benefiting from a dense network of ground-based CO₂ sensors. In this study, we quantify the potential of assimilating indirect measurements from spaceborne sensors (here nitrogen dioxide – NO₂) to constrain fossil fuel CO₂ emissions, relying on the co-emission of these two species during combustion. We developed a modeling framework using a NO_x-aerosol chemistry transport model (WRF-Chem) and performed simulations of NO₂ and CO₂ over the Middle-East, an area known for its large cities, its frequent clear sky conditions and a fairly constant albedo from its desertic land. We first demonstrate the importance of production/destruction processes impacting NO₂ lifetime at short and long distances from the source, suggesting that simplified approaches may be impacted by large errors. In comparison to TROPOMI satellite observations, the simulated NO₂ plumes from emissions inventories (EDGAR) revealed large misattribution of NO₂ emissions at fine scales, hence an uncertain disaggregation of national emissions to single point sources in the industrial and energy sectors in the EDGAR inventory. We further studied the relationship between NO₂ and CO₂ during summer and winter seasons by simulating the enhancement ratios (δNO₂:δXCO₂) in plumes produced by cities and point sources We found that the enhancement ratios are consistent with the observed ratios derived from the ESA TROPOMI (NO₂) and NASA OCO-3 missions (XCO₂). We conclude here that the spatial misattribution of NO₂ emissions parallels the misattribution of CO₂ emissions, and that improved NO₂ inventories could therefore be used to improve the monitoring of CO₂ emissions at sub-national scales in current global inventories when a sufficiently-large amount of NO₂ satellite measurements are available.