Vulsini Volcanic district in Northern Latium (Central Italy) is characterized by high natural radiation background resulting from the high concentrations of uranium, thorium and potassium in the volcanic products. In order to estimate the radon radiation risk, a series of soil gas radon measurements were carried out in Bolsena, the principal urban settlement in this area NE of Rome. Soil gas radon concentration ranges between 7 and 176 kBq/m³ indicating a large degree of variability in the NORM content and behavior of the parent soil material related in particular to the occurrence of two different lithologies. Soil gas radon mapping confirmed the existence of two different areas: one along the shoreline of the Bolsena lake, characterized by low soil radon level, due to a prevailing alluvial lithology; another close to the Bolsena village with high soil radon level due to the presence of the high radioactive volcanic rocks of the Vulsini volcanic district. Radon risk assessment, based on soil gas radon and permeability data, results in a map where the alluvial area is characterized by a probability to be an area with high Radon Index lower than 20 %, while probabilities higher than 30 % and also above 50 % are found close to the Bolsena village.

The Mediterranean basin represents a hot spot area for short-term O3 distribution and anthropogenic contributions to it. This is why we analysed in this work the surface O3 variability observed at Mt. Cimone WMO/GAW global station (CMN, 44°12′ N, 10°42′ E, 2165 m a.s.l., Italy) from 1991 to 2011. The measurements performed at this mountain observatory represent the longest surface O3 record at a baseline site in the Mediterranean basin.Monthly O3 averages at CMN show a typical seasonal cycle characterised by a winter minimum and a spring – summer maxima. The shape of the mean annual variation of O3 is well comparable with those observed at other four baseline sites in the Alps and in the Mediterranean region: Jungfraujoch – Swiss Alps, Sonnblick – Austrian Alps, Mt. Krvavec– Slovenia and Giordan Lightouse – Island of Gozo, Malta. In general, O3 levels at CMN show higher values during warm months, which is likely to be related both to vertical transport of polluted air-masses at regional and continental scales and to enhanced photochemistry.Here, we also investigate the influence of specific atmospheric processes (i.e. the occurrence of heat-waves, North Atlantic Oscillation, thermal transport of air-masses from the regional PBL and stratospheric intrusions) in affecting O3 variability at CMN.Overall, a significant positive (95% confidence level) linear trend in monthly O3 mole fraction was observed over the period 1991–2011 (0.21 ± 0.10 nmol/molyr−1) while no trend (-0.02 ± 0.12 nmol/molyr−1) was detected for the 1996–2011, when measurements were carried out by an homogeneous experimental set-up. On a seasonal basis, a positive trend has been observed for 1996–2011 (0.34 ± 0.32 nmol/molyr−1) only for spring. Significant decreases of the seasonal O3 growth-rates have been detected at CMN during 1991–2011 from winter to spring and only for summer during 1996–2011

Low-cost sensors based on the optical particle counter (OPC) are increasingly being used to collect particulate matter (PM) data at high space and time resolution. In spite of their huge explorative potential, practical guidelines and recommendations for their use are still limited. In this work, we outline a few best practices for the optimal use of PM low-cost sensors based on the results of an intensive field campaign performed in Bologna (44°30′ N, 11°21′ E; Italy) under different weather conditions. Briefly, the performances of a series of sensors were evaluated against a calibrated mainstream OPC with a heated inlet, using a robust approach based on a suite of statistical indexes capable of evaluating both correlations and biases in respect to the reference sensor. Our results show that the sensor performance is sensibly affected by both time resolution and weather with biases maximized at high time resolution and high relative humidity. Optimization of PM data obtained is therefore achievable by lowering time resolution and applying suitable correction factors for hygroscopic growth based on the inherent particle size distribution.