Evaluation of tectonically enhanced radon in fault zones by quantification of the radon activity index.

This work highlights the importance of the Geogenic Radon Potential (GRP) component originated by degassing processes in fault zones. This Tectonically Enhanced Radon (TER) can increase radon concentration in soil gas and the inflow of radon in the buildings (Indoor Radon Concentrations, IRC). Although tectonically related radon enhancement is known in areas characterised by active faults, few studies have investigated radon migration processes in non-active fault zones. The Pusteria Valley (Bolzano, north-eastern Italy) represents an ideal geological setting to study the role of a non-seismic fault system in enhancing the geogenic radon. Here, most of the municipalities are characterised by high IRC. We performed soil gas surveys in three of these municipalities located along a wide section of the non-seismic Pusteria fault system characterised by a dense network of faults and fractures. Results highlight the presence of high Rn concentrations (up to 800 kBq·m-3) with anisotropic spatial patterns oriented along the main strike of the fault system. We calculated a Radon Activity Index (RAI) along north-south profiles across the Pusteria fault system and found that TER is linked to high fault geochemical activities. This evidence confirms that TER constitutes a significant component of GRP also along non-seismic faults.

Apportioning PM1 in a contrasting receptor site in the Mediterranean region: Aerosol sources with an updated sulfur speciation.

A multi-parametric experimental campaign was performed in Agri Valley (Basilicata, southern Italy) from July 2017 to January 2018. The investigated area, though basically rural and devoted to agricultural activities, hosts a huge on-shore oil reservoir, i.e. Centro Olio Val d'Agri (COVA), bringing substantial environmental modifications and impacts to the district landscape. Daily concentrations of PM1 aerosol samples, Equivalent Black Carbon and number size distributions were evaluated. Chemical aerosol speciation based on elemental and ion analyses were carried out and source apportionment by Positive Matrix Factorization (PMF) was applied to reconstruct PM1 source profile. The most significant emission sources found are torches from the oil treatment facility (37 % w/w), an unresolved factor constituted by soil resuspension, Saharan dust, and biomass burning (24 % w/w), ammonium sulphate (23 % w/w), emissions from the oil desulfurization (Claus process) (13 % w/w), and traffic + road dust (3 % w/w). SEM analysis on PM1 single particles allowed to confirm the finding from PMF including the occurrence of elemental sulfur associated with the Claus process. The novelty of the present study consists in the identification of this latter fingerprint.

The assessment of local geological factors for the construction of a Geogenic Radon Potential map using regression kriging. A case study from the Euganean Hills volcanic district (Italy).

The assessment of potential radon-hazardous environments is nowadays a critical issue in planning, monitoring, and developing appropriate mitigation strategies. Although some geological structures (e.g., fault systems) and other geological factors (e.g., radionuclide content, soil organic or rock weathering) can locally affect the radon occurrence, at the basis of a good implementation of radon-safe systems, optimized modelling at territorial scale is required. The use of spatial regression models, adequately combining different types of predictors, represents an invaluable tool to identify the relationships between radon and its controlling factors as well as to construct Geogenic Radon Potential (GRP) maps of an area. In this work, two GRP maps were developed based on field measurements of soil gas radon and thoron concentrations and gamma spectrometry of soil and rock samples of the Euganean Hills (northern Italy) district. A predictive model of radon concentration in soil gas was reconstructed taking into account the relationships among the soil gas radon and seven predictors: terrestrial gamma dose radiation (TGDR), thoron (220Rn), fault density (FD), soil permeability (PERM), digital terrain model (SLOPE), moisture index (TMI), heat load index (HLI). These predictors allowed to elaborate local spatial models by using the Empirical Bayesian Regression Kriging (EBRK) in order to find the best combination and define the GRP of the Euganean Hills area. A second GRP map based on the Neznal approach (GRPNEZ) has been modelled using the TGDR and 220Rn, as predictors of radon concentration, and FD as predictor of soil permeability. Then, the two GRP maps have been compared. Results highlight that the radon potential is mainly driven by the bedrock type but the presence of fault systems and topographic features play a key role in radon migration in the subsoil and its exhalation at the soil/atmosphere boundary.

Chemiluminescent fingerprints from airborne particulate matter: A luminol-based assay for the characterization of oxidative potential with kinetical implications.

In this study, a new chemiluminescent method based on the dependence of luminol light emission induced by free radicals in airborne particulate matter (PM) is proposed as a screening assay for the rapid characterization of samples from different sources based on their redox properties. This parameter is considered critical for assessing particulate matter toxicity and its impacts on human health. We propose a cell-free, luminescent assay to evaluate the redox potential of particulate matter directly on the filters employed to collect it. A joint chemometric approach based on Principal Component Analysis and Hotelling Analysis was applied to quickly sort out ambient particulate samples with a significantly different light emission profile caused by Luminol reaction. Based on Spearman correlation analysis, the association of the samples light emission intensity with their chemical composition and emission sources was attempted. The overall methodology was tested with certified reference materials and applied to two series of particulate matter samples previously subjected to thorough chemical speciation and subsequent source apportionment. The results show the effectiveness of the luminescent method, allowing the quick assessment of particulate matter oxidative potential, but providing further evidence on the complexity of the oxidative potential determination in this kind of samples. The chemometric processing of the whole dataset clearly highlights the distinct behavior among the two series of samples, the certificate standard reference materials, and the blank controls, supporting the suitability of the approach.

Particulate matter emission sources and meteorological parameters combine to shape the airborne bacteria communities in the Ligurian coast, Italy.

Aim of the present study is to explore how the chemical composition of particulate matter (PM) and meteorological conditions combine in shaping the air microbiome in Savona (Italy), a medium-size, heavily inhabited urban settlement, hosting a wide range of industrial activities. In particular, the air microbiome and PM10 were monitored over six months in 2012. During that time, the air microbiome was highly dynamic, fluctuating between different compositional states, likely resulting from the aerosolization of different microbiomes emission sources. According to our findings, this dynamic process depends on the combination of local meteorological parameters and particle emission sources, which may affect the prevalent aerosolized microbiomes, thus representing further fundamental tools for source apportionment in a holistic approach encompassing chemical as well as microbiological pollution. In particular, we showed that, in the investigated area, industrial emissions and winds blowing from the inlands combine with an airborne microbiome which include faecal microbiomes components, suggesting multiple citizens' exposure to both chemicals and microorganisms of faecal origin, as related to landscape exploitation and population density. In conclusion, our findings support the need to include monitoring of the air microbiome compositional structure as a relevant factor for the final assessment of local air quality.

Deposition processes over complex topographies: Experimental data meets atmospheric modeling.

The present paper describes the assessment of the atmospheric deposition processes in a basin valley through a multidisciplinary approach based on the data collected within an extensive physico-chemical characterization of the soils, combined with the local meteorology. Surface soil cores were collected on a NNW-SSE transect across the Terni basin (Central Italy), between the Monti Martani and the Monti Sabini chains (956 m a.s.l.), featuring the heavily polluted urban and industrial enclave of Terni on its bottom. Airborne radiotracers, namely 210Pb and 137Cs, have been used to highlight atmospheric deposition. We observed an increased deposition flux of 210Pb and 137Cs at sites located at the highest altitudes, and the associated concentration profiles in soil allowed to evaluate the role of atmospheric deposition. We also obtained a comprehensive dataset of stable anthropogenic pollutants of atmospheric origin that showed heterogeneity along the transect. The behavior has been explained by the local characteristic of the soil, by seeder-feeder processes promoted by the atmospheric circulation, and was reconciled with the concentration profile of radiotracers by factor analysis. Finally, the substantial impact of the local industrial activities on soil profiles and the role of the planetary boundary layer has been discussed and supported by simulations employing a Lagrangian dispersion model.

How to Get the Best from Low-Cost Particulate Matter Sensors: Guidelines and Practical Recommendations.

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.

ATR-FTIR Spectroscopy, a New Non-Destructive Approach for the Quantitative Determination of Biogenic Silica in Marine Sediments.

Biogenic silica is the major component of the external skeleton of marine micro-organisms, such as diatoms, which, after the organisms death, settle down onto the seabed. These micro-organisms are involved in the CO2 cycle because they remove it from the atmosphere through photosynthesis. The biogenic silica content in marine sediments, therefore, is an indicator of primary productivity in present and past epochs, which is useful to study the CO2 trends. Quantification of biosilica in sediments is traditionally carried out by wet chemistry followed by spectrophotometry, a time-consuming analytical method that, besides being destructive, is affected by a strong risk of analytical biases owing to the dissolution of other silicatic components in the mineral matrix. In the present work, the biosilica content was directly evaluated in sediment samples, without chemically altering them, by attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy. Quantification was performed by combining the multivariate standard addition method (MSAM) with the net analyte signal (NAS) procedure to solve the strong matrix effect of sediment samples. Twenty-one sediment samples from a sediment core and one reference standard sample were analyzed, and the results (extrapolated concentrations) were found to be comparable to those obtained by the traditional wet method, thus demonstrating the feasibility of the ATR-FTIR-MSAM-NAS approach as an alternative method for the quantification of biosilica. Future developments will cover in depth investigation on biosilica from other biogenic sources, the extension of the method to sediments of other provenance, and the use higher resolution IR spectrometers.

A Quick and Efficient Non-Targeted Screening Test for Saffron Authentication: Application of Chemometrics to Gas-Chromatographic Data.

Saffron is one of the most adulterated food products all over the world because of its high market prize. Therefore, a non-targeted approach based on the combination of headspace flash gas-chromatography with flame ionization detection (HS-GC-FID) and chemometrics was tested and evaluated to check adulteration of this spice with two of the principal plant-derived adulterants: turmeric (Curcuma longa L.) and marigold (Calendula officinalis L.). Chemometric models were carried out through both linear discriminant analysis (LDA) and partial least squares discriminant analysis (PLS-DA) from the gas-chromatographic data. These models were also validated by cross validation (CV) and external validation, which were performed by testing both models on pure spices and artificial mixtures capable of simulating adulterations of saffron with the two adulterants examined. These models gave back satisfactory results. Indeed, both models showed functional internal and external prediction ability. The achieved results point out that the method based on a combination of chemometrics with gas-chromatography may provide a rapid and low-cost screening method for the authentication of saffron.