The development of a natural gas-fired tri-generation power plant (520 MW Combined Cycle Gas Turbines + 58 MW Tri-generation) in the Republic of San Marino, a small independent country in Northern Italy, is under assessment. This work investigates the impact of atmospheric emissions of NO_x by the plant, under the Italian and European regulatory framework. The impact assessment was performed by the means of the Aria Industry package, including the 3D Lagrangian stochastic particle dispersion model SPRAY, the diagnostic meteorological model SWIFT, and the turbulence model SURFPRO (Aria Technologies, France, and Arianet, Italy). The Republic of San Marino is almost completely mountainous, 10 km west of the Adriatic Sea and affected by land-sea breeze circulation. SPRAY is suitable for simulations under non-homogenous and non-stationary conditions, over a complex topography. The emission scenario included both a worst-case meteorological condition and three 10-day periods representative of typical atmospheric conditions for 2014. The simulated NO_x concentrations were compared with the regulatory air quality limits. Notwithstanding the high emission rate, the simulation showed a spatially confined environmental impact, with only a single NO_x peak at ground where the plume hits the hillside of the Mount Titano (749 m a.s.l.), 5 km west of the future power plant.

The Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5.1 Aerosol Optical Depth (AOD) data retrieved at 0.55 μm with spatial resolution of 10 km (MYD04) and the new 1 km Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm from MODIS is investigated in this work. We focus on evaluating the ability of these two products to characterize the spatial distribution of aerosols within urban areas. This is done through the comparison with PM₁₀ measurements from 126 of the Italian Regional Agency for Environmental Protection (ARPA) ground monitoring stations during 2012. The Po Valley area (northern Italy) was chosen as the study domain since urban air pollution is one of the most important concerns in this region. Population and industrial activities are located within a large number of urban areas within the valley. We find that the annual correlations between PM₁₀ and AOD are R² = 0.90 and R² = 0.62 for MYD04 and for MAIAC respectively. When the depth of the planetary boundary layer (PBL) is used to normalize the AOD, we find a significant improvement in the PM–AOD correlation. The introduction of the PBL information is needed for AOD to capture the seasonal cycle of the observed PM₁₀ over the Po valley and significantly improves the PM vs. AOD relationship, leading to a correlation of R² = 0.98 for both retrievals when they are normalized by the PBL depth. The results show that the normalized MAIAC retrieval provides a higher resolution depiction of the AOD within the Po Valley and performs as well in a statistical sense as the normalized standard MODIS retrieval for the same days and locations.