Analysis of crystalline phases in airborne particulate matter by two-dimensional X-ray diffraction (XRD2)

First data analysis about possible COVID-19 virus airborne diffusion due to air particulate matter (PM): The case of Lombardy (Italy)

The severe cases of COVID-19 infections in Italy, and notably in Lombardy (mainly in Brescia and Bergamo areas), registered at the beginning of March 2020, occurred after a period of PM10 pollution, that exceeded the concentration of 50 μg/m3 (the attention limit) for several days. The two events were supposed to be correlated, also based on the limited information available about the new virus. Despite that clear indications about the role of particulate matter (PM) in the virus mechanism dispersion cannot be found in literature, some researchers supposed that PM can act as virus carrier, promoting its diffusion through the air. This paper, for the first time, analyses the PM10 situation in Lombardy (from 10th February to March 27, 2020), several days before the sanitary emergency explosion. The data of the detected infection cases are reported and discussed parallelly. As a comparison, the situation of Piedmont, located near to the Lombardy is also presented. Data are reported for Brescia, Bergamo, Cremona, Lodi, Milano, Monza-Brianza, Pavia (Lombardy), Alessandria, Vercelli, Novara, Biella, Asti, and Torino (Piedmont). The results show that it is not possible to conclude that COVID-19 diffusion mechanism also occurs through the air, by using PM10 as a carrier. In particular, it is shown that Piedmont cities, presenting lower detected infections cases in comparison to Brescia and Bergamo in the investigated period, had most sever PM10 pollution events in comparison to Lombardy cities. This first study may serve as a reference to better understand and predict the factors affecting the COVID-19 diffusion and transmission routes, focusing on the role of air particulate matter in the atmosphere.

Uncommon chemical species in PM2.5 and PM10 and its potential use as industrial and vehicular markers for source apportionment studies

Chemical characterization of PM_2.5 and PM₁₀ is important to identify potential compounds that induce biological responses that translate into cardio-respiratory health problems. This study shows the reliability of the use of crystalline phases, identified in samples from receptor sites, as source markers, helping researchers to infer the main sources of air pollution, even without the use of receptor models. PM_2.5 and PM₁₀ samples were collected at two sites in an urban industrialized region located at southeast of Brazil and analyzed by Synchrotron X-ray Diffraction to identify crystalline compounds. Results show 5 PM₁₀ and PM_2.5 species not previously reported in the literature. We propose reaction mechanisms for these species and identify specific sources for each crystalline phase found: BaTiO₃ was found in PM₁₀ receptor samples and proved to be a vehicular marker formed during brake action; maghemite (γ-Fe₂O₃), pyracmonite [(NH₄)₃Fe(SO₄)₃], ammonium perchlorate (NH₃OHClO₄) and potassium ferrate (K₂Fe₂O₄) were found in PM_2.5 proved to be markers of industrial activities. The crystalline phases found in PM samples from receptor sites and the mechanisms of reactions showed the reliability of the use of crystalline phases as source markers in the identification of potential sources of air pollution without misinterpretation of the likely source.

Air quality and PM10-associated poly-aromatic hydrocarbons around the railway traffic area: statistical and air mass trajectory approaches

Diesel engine railway traffic causes atmosphere pollution due to the exhaust emission which may be harmful to the passengers as well as workers. In this study, the air quality and PM₁₀ concentrations were evaluated around a railway station in Northeast India where trains are operated with diesel engines. The gaseous pollutant (e.g. SO₂, NO₂, and NH₃) was collected and measured by using ultraviolet-visible spectroscopy. The advanced level characterizations of the PM10 samples were carried out by using ion chromatography, Fourier-transform infrared, X-ray diffraction, inductively coupled plasma optical emission spectrometry , X-ray photoelectron spectroscopy, field-emission scanning electron microscopy with energy-dispersive spectroscopy, and high-resolution transmission electron microscopy with energy-dispersive spectroscopy techniques to know their possible environmental contaminants. High-performance liquid chromatography technique was used to determine the concentration of polycyclic aromatic hydrocarbons to estimate the possible atmospheric pollution level caused by the rail traffic in the enclosure. The average PM₁₀ concentration was found to be 262.11 µg m^-3 (maximum 24 hour) which indicates poor air quality (AQI category) around the rail traffic. The statistical and air mass trajectory analysis was also done to know their mutual correlation and source apportionment. This study will modify traditional studies where only models are used to simulate the origins.

Airborne particulate matter (PM) filter analysis and modeling by total reflection X-ray fluorescence (TXRF) and X-ray standing wave (XSW)

This work is presented as an improvement of a recently introduced method for airborne particulate matter (PM) filter analysis [1]. X-ray standing wave (XSW) and total reflection X-ray fluorescence (TXRF) were performed with a new dedicated laboratory instrumentation. The main advantage of performing both XSW and TXRF, is the possibility to distinguish the nature of the sample: if it is a small droplet dry residue, a thin film like or a bulk sample. Another advantage is related to the possibility to select the angle of total reflection to make TXRF measurements. Finally, the possibility to switch the X-ray source allows to measure with more accuracy lighter and heavier elements (with a change in X-ray anode, for example from Mo to Cu). The aim of the present study is to lay the theoretical foundation of the new proposed method for airborne PM filters quantitative analysis improving the accuracy and efficiency of quantification by means of an external standard. The theoretical model presented and discussed demonstrated that airborne PM filters can be considered as thin layers. A set of reference samples is prepared in laboratory and used to obtain a calibration curve. Our results demonstrate that the proposed method for quantitative analysis of air PM filters is affordable and reliable without the necessity to digest filters to obtain quantitative chemical analysis, and that the use of XSW improve the accuracy of TXRF analysis.

Total reflection X-ray fluorescence (TXRF) for direct analysis of aerosol particle samples

Atmospheric aerosol particles have a great impact on the environment and on human health. Routine analysis of the particles usually involves only the mass determination. However, chemical composition and phases provide fundamental information about the particles' origins and can help to prevent health risks. For example, these particles may contain heavy metals such as Pb, Ni and Cd, which can adversely affect human health. In this work, filter samples were collected in Brescia, an industrial town located in Northern Italy. In order to identify the chemical composition and the phases of the atmospheric aerosols, the samples were analysed by means of total reflection X-ray fluorescence (TXRF) spectrometry with a laboratory instrument and X-ray microdiffraction at Synchrotron Daresbury Laboratories, Warrington (Cheshire, UK). The results are discussed and correlated to identify possible pollution sources. The novelty of this analytical approach is that filter samples for TXRF were analysed directly and did not require chemical pretreatment to leach elements from the aerosol particulates. The results of this study clearly show that TXRF is a powerful technique for the analysis of atmospheric aerosols on 'as-received' filters, thereby leaving samples intact and unaltered for possible subsequent analyses by other methods. In addition, the low detection limits for many elements (low ng/cm2) indicate that this method may hold promise in various application fields, such as nanotechnology.

Analysis of settled dust with X-ray Fluorescence for exposure assessment of metals in the province of Brescia, Italy

Ferroalloy industries have been active for more than a century in the province of Brescia, Northern Italy. Air emission and water discharge have contaminated the environment in the surroundings of four plants with several metals including manganese. The presence of manganese in this region is especially interesting, because of the observed relationship between manganese exposure and Parkinsonism in a previous epidemiological survey. The aim of this study was represented by an initial screening of metal exposure in this area, using a geographic information system. X-ray fluorescence (XRF) was applied to identify heavy metals in deposited dust samples, collected in representative residential households throughout the province. The results were interpreted through a systematic mapping of all municipal districts of the Brescia province. A more frequent distribution of manganese and other metals was observed in the municipalities where the plants were located and differences in the geochemical and anthropogenic origin of metals were discussed, according to the point sources.