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This study reports the results of an experimental research project carried out in Bologna, a midsize town in central Po valley, with the aim at characterizing local aerosol chemistry and tracking the main source emissions of airborne particulate matter. Chemical speciation based upon ions, trace elements, and carbonaceous matter is discussed on the basis of seasonal variation and enrichment factors. For the first time, source apportionment was achieved at this location using two widely used receptor models (principal component analysis/multi-linear regression analysis (PCA/MLRA) and positive matrix factorization (PMF)). Four main aerosol sources were identified by PCA/MLRA and interpreted as: resuspended particulate and a pseudo-marine factor (winter street management), both related to the coarse fraction, plus mixed combustions and secondary aerosol largely associated to traffic and long-lived species typical of the fine fraction. The PMF model resolved six main aerosol sources, interpreted as: mineral dust, road dust, traffic, secondary aerosol, biomass burning and again a pseudo-marine factor. Source apportionment results from both models are in good agreement providing a 30 and a 33% by weight respectively for PCA-MLRA and PMF for the coarse fraction and 70% (PCA-MLRA) and 67% (PMF) for the fine fraction. The episodic influence of Saharan dust transport on PM10 exceedances in Bologna was identified and discussed in term of meteorological framework, composition, and quantitative contribution.

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.

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.

Considerations for evaluating green infrastructure impacts in microscale and macroscale air pollution dispersion models.