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The study's objective was to identify the main generating sources of particulate matter from the Limeira City (SP), Brazil. Particulate matter collections were carried out at the meteorological station of the Technology Department of Campinas State University by using a sequential filtration sampling system. Using synchrotron radiation total reflection X-ray fluorescence makes it possible to perform quality quantitative analysis of the particulate matter collected during the years 2008 and 2009. Respirable particulate matter's coarse and fine fractions that affect the upper and lower respiratory tract were collected on polycarbonate filters arranged in series. At the Brazilian Synchrotron Light Laboratory, samples were analyzed by synchrotron radiation total reflection X-ray fluorescence after removal from acid. Results indicated that the coarse fraction made the greatest contribution to PM 10 formation. As per the particulate matter composition, 16 elements were found in both fractions: S, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Br, Rb, Sr, Ba, and Pb. The determination of the probable emission sources contributing to the formation of particulate material was possible by applying multivariate statistical analyses, namely principal components analysis and cluster analysis. The primary emission source for the coarse fraction was soil dust, which contributed 57%, followed by 30% from vehicular emissions, and lastly, only 13% from industrial emissions. The primary emission source for the fine fraction was soil dust, which contributed 79%, followed by 13% from vehicular emissions, and lastly, only 8% from industrial emissions. Figure 7. Vehicle emissions profile obtained in the city of Limeira compared with those obtained for the cities of Santiago, Chile, [25] and São Paulo [16] ; the Campinas urban center, Paulinia, and Barão Geraldo [15] ; and with the signature for diesel and gasoline vehicles obtained by Mason. [23] Signature sources of particulate matter pollutants X-Ray Spectrom. 2013, 42, 290-298

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This study aimed to assess the microstructure, chemical composition, and image quality of different photostimulable phosphor plates (PSP). Four PSP systems, Express ® , Digora ® , VistaScan ® , and Apixia, ® were assessed. Five radiographs of a homogeneous acrylic phantom were obtained with the PSP of each system, to acquire a total of 20 images. The images were objectively evaluated for uniformity using mean grey and standard deviation (SD) of their grey values. PSP receptors were analyzed using scanning electron microscopy (SEM) to determine the thickness of the granule layer and the size of the granules. The chemical composition of the PSP receptors was analyzed using total reflection X-ray fluorescence (TXRF). VistaScan showed more uniform and higher density images than the other tested systems (p < 0.05), as well as the lowest SD of grey values (p < 0.05).Regarding the microstructure of the receptors, Digora and VistaScan had thicker granule layers than Express and Apixia, and VistaScan had smaller granules than Digora and Express (p < 0.05). Fourteen chemical elements were detected in the receptors, with barium being the element with the highest concentration in all PSP systems. The microstructure, chemical composition, and image quality varied among all four PSP receptors studied. VistaScan receptors showed the smallest variation in granule size, one of the thickest granule layers, and the most uniform and least noisy images.

The COVID-19 disease was first identified at the end of 2019 and spread rapidly around the world in 2020. Its symptom includes an acute respiratory crisis and the disease has claimed millions of victims. According to the literature, the relationship between COVID-19 transmission, and climatic factors and air pollutants is still unclear. Therefore, studies aiming to clarify this correlation are essential. This study aims to determine the correlation between the number of COVID-19 cases, particulate matter (PM) concentration, and meteorological variables in the city of Limeira, Brazil. The statistical analyses used were a generalized model with gamma distribution, Spearman’s correlation, and cluster analysis, followed by the Mann-Whitney test. The variables included were rainfall, temperature, wind speed, relative humidity, and atmospheric pressure, in addition to social distancing compliance rate, dummy variables for business opening flexibility, and the weekday. The concentration of the coarse inhalable particulate matter (PM10) fraction showed an inverse correlation with relative humidity, rainfall, and pressure. The Total Suspended Particulate matter (TSP) had an inverse correlation with relative humidity, rainfall, weekends, and social distancing compliance rate. A correlation was also found between the number of COVID-19 cases and pressure, PM10, and TSP. Finally, the calculated relative risk showed that the reduction in PM10 concentrations directly affects health, which implies an estimate of almost 13 deaths avoided in Limeira, during the pandemic. The results obtained provide important information as to improving air quality and strategies to contain COVID-19 transmission. Besides, albeit on a small scale, they confirm the relationship between the social distancing compliance rate, PM concentration, and COVID-19 cases.

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