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Atmospheric Particulate Matter (PM) is a pollutant with diverse origins, exhibiting varying chemical compositions, and undergoes several molecular transformations in the atmosphere. In this study, PM samples (PM2.5, PM10 and TSP) were collected in five Brazilian cities (Camboriú-SC; Catalão-GO; Florianópolis-SC; Limeira-SP and Novo Hamburgo-RS) during the four seasons of the year. Analysis of Variance (ANOVA) was used to evaluate the differences between each city and season in PM concentration. PM10 average concentrations were higher in the city of Limeira, compared to the other (ANOVA p-values and Tukey's test). Moreover, Tukey's test demonstrated differences between the average PM10 concentrations in summer and winter. Regarding TSP and PM2.5, Tukey's test showed differences between winter and warm seasons (spring and summer). Moreover, polar compounds from the samples collected in the summer (February) and winter (August) periods were analyzed (Ultra-High-Performance Liquid Chromatography coupled to a Quadrupole Time-of-Flight Mass Spectrometer) following a non-targeted approach and annotated. This is the first study to carry out this type of analysis in these five Brazilian cities. Despite the differences in PM concentrations, profiles of polar organic compounds, showed similarities between samples/and, in general, the same compounds were present, albeit with different intensities. The annotated compounds are associated with vehicle emissions and plastics, which are considered important global air polluters. Therefore, there is an urgent necessity for comprehensive studies aimed at investigating the non-targeted compounds existing in the atmosphere. Such research can provide invaluable insights to policymakers, enabling them to formulate effective guidelines and policies to mitigate particulate matter concentration and enhance overall air quality.

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The extensive use of medicinal herbs to traditionally treat disease persists for generations, and scientific evidence on plant-derived extracts has indicated their numerous biological activities. The Bauhinia, popular known as cow's paw ("pata de vaca"), with more than 60 native species, are extensively used in Brazilian popular medicine for the control of diabetes. Therefore, in 2009, B. forficata, B. variegata and/or B. affinis were included in the Brazilian National List of Medicinal Plants of Interest to SUS (RENISUS - Brazil). In this context, this work reports the results of the chemical differentiation of B. forficata, B. variegata, B. longifolia, and B. affinis using liquid chromatography coupled to high-resolution mass spectrometry and unsupervised chemometric tools. Chromatographic conditions were optimized by using the design of experiments (DoE) and chromatographic knowledge. Furthermore, the chemical profile of the studied species was analyzed by principal component analysis (PCA) and hierarchical cluster analysis that differentiated the four species of Bauhinia, and 55 compounds were also inferred by MS2 experiments, some of them for the first time in B. affinis. In this manner, this work provides important information that could be used in quality control, development of new pharmaceuticals, and food products based on Bauhinia leaves, as well as to explain ethnomedicinal properties, pharmacological and toxicological actions.

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The present study aims to develop a fast and simple method for the determination of potassium (K), magnesium (Mg) and phosphor (P) in bean seed samples employing a data fusion strategy in the low-level with laser-induced breakdown spectroscopy (LIBS) and wavelength dispersive X-ray fluorescence (WDXRF) techniques combined with direct solid sample analysis. Univariate and multivariate (multiple linear regression, MLR) calibration and leave-one-out cross validation strategies were evaluated to build the calibration models correlated with reference values obtained by inductively coupled plasma optical emission spectrometry (ICP OES) after microwave-assisted acid digestion. The proposed calibration models for WDXRF and LIBS were tested using 14 samples, where the best results were obtained using the data fusion of both techniques. The standard error of cross validation (SECV) obtained were: 0.12% for K, 0.019% for Mg and 0.10% for P, and the trueness ranged between 89 and 124% for K, 82 to 125% for Mg and 73 to 128% for P. These values showed a good accuracy, precise and robustness of the method and a greater reliability of the results. In addition, the predicted concentrations ranged from 0.97 to 1.55% for K, 0.14 to 0.28% for Mg, and 0.27 to 0.82% for P.

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A wide range of anthropogenic activities have caused various problems to the aquatic environment, leading to economic, social, and environmental losses. The use of materials for the recovery of water quality is very important due to the water scarcity scenario present in different parts of the world. The use of sawdust as an organic adsorbent for P removal in eutrophic environments attempts to address both water quality preservation and possible application of the organic adsorbent as fertilizer for agricultural practices. This use will result in important contributions to the water and food security. In this work, we performed laboratory experiments to study P adsorption and to evaluate possible adsorption of metals and emerging contaminants by sawdust. The experiments were carried out in 36 microcosms (glass jars), using 50% of the flasks as treatments (containing bags with sawdust) and the rest of the flasks as control (water and sediment without sawdust). For future application of sawdust as a fertilizer it is important to be aware of the presence of possible pathogenic microorganisms, thus the presence of helminth eggs was determined in the sawdust. The results showed the tendency of P adsorption by the biosorbent; maximum adsorption occurred at 214 d (41 µg P g-1 ), after the P desorption occurred. No helminth eggs or emerging contaminants and toxic metal were detected in the sawdust after its use as biosorbent, providing an important subsidy regarding the use of the biosorbent as soil fertilizer. Integr Environ Assess Manag 2019;00:1-12. © 2019 SETAC.

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Models using near-infrared spectroscopy (NIRS) were constructed based on physical-mechanical tests to determine the quality of cattle leather. The following official parameters were used, considering the industry requirements: tensile strength (TS), percentage elongation (%E), tear strength (TT), and double hole tear strength (DHS). Classification models were constructed with the use of k-nearest neighbor (kNN), soft independent modeling of class analogy (SIMCA), and partial least squares-discriminant analysis (PLS-DA). The evaluated figures of merit, accuracy, sensitivity, and specificity presented results between 85% and 93%, and the false alarm rates from 9% to 14%. The model with lowest validation percentage (92%) was kNN, and the highest was PLS-DA (100%). For TS, lower values were obtained, from 52% for kNN and 74% for SIMCA. The other parameters %E, TT, and DHS presented hit rates between 87 and 100%. The abilities of the models were similar, showing they can be used to predict the quality of cattle leather.

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Eutrophication is considered a global environmental problem that causes economic and biodiversity loss. Together with excess phosphorus in some aquatic environments, there is the depletion of phosphate rock deposits, which can directly affect fertilizer production and therefore global food security. Thus, the present work aimed to study a new remediation technique for eutrophic environments that enables the recovery of these environments through phosphorus adsorption in sawdust, creating the possibility to apply the phosphorus-enriched material as an agricultural fertilizer. The study was conducted in 36 microcosm flasks with water and sediment samples from a eutrophic reservoir in Ibirité/MG. The experiment was carried out using 18 control flasks and 18 others as treatment, consisting of water and eutrophic environment sediment and, additionally, two bags, containing 10 g of sawdust in each bag. The phosphorus adsorption on sawdust was more intense after 49 days of immersion in the microcosm, and reductions of 90% in the concentration of reactive soluble phosphorus were observed in the water column of the microcosm treatment at 159 days of the experiment. Based on the results, it can be concluded that, although the phosphorus concentration adsorbed on sawdust (16.2 µg g-1) is considered low, the use of the biosorbent is a particularly promising technique for remediation of eutrophic environments, as well as the possible reuse of the adsorbed phosphorus as a fertilizer in agriculture.

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Application of a refined procedure of experimental design and chemometric analysis to improve the production of curvularin-related polyketides by a marine-derived Penicillium sp. DRF2 resulted in the isolation and identification of cyclothiocurvularins 6-8 and cyclosulfoxicurvularins 10 and 11, novel curvularins condensed with a mercaptolactate residue. Two additional new curvularins, 3 and 4, are also reported. The structures of the sulfur-bearing curvularins were unambiguously established by analysis of spectroscopic data and by X-ray diffraction analysis. Analysis of stable isotope feeding experiments with [U-(13)C3(15)N]-l-cysteine confirmed the presence of the 2-hydroxy-3-mercaptopropanoic acid residue in 6-8 and the oxidized sulfoxide in 10 and 11. Cyclothiocurvularins A (6) and B (7) are formed by spontaneous reaction between 10,11-dehydrocurvularin (2) and mercaptopyruvate (12) obtained by transamination of cysteine. High ratios of [U-(13)C3(15)N]-l-cysteine incorporation into cyclothiocurvularin B (7), the isolation of two diastereomers of cyclothiocurvularins, the lack of cytotoxicity of cyclothiocurvularin B (7) and its methyl ester (8), and the spontaneous formation of cyclothiocurvularins from 10,11-dehydrocurvularin and mercaptopyruvate provide evidence that the formation of cyclothiocurvularins may well correspond to a 10,11-dehydrocurvularin detoxification process by Penicillium sp. DRF2.

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In an attempt to classify sugarcane spirits according to their geographic region of origin, chemical data for 24 analytes were evaluated in 50 cachaças produced using a similar procedure in selected regions of Brazil: São Paulo - SP (15), Minas Gerais - MG (11), Rio de Janeiro - RJ (11), Paraiba -PB (9), and Ceará - CE (4). Multivariate analysis was applied to the analytical results, and the predictive abilities of different classification methods were evaluated. Principal component analysis identified five groups, and chemical similarities were observed between MG and SP samples and between RJ and PB samples. CE samples presented a distinct chemical profile. Among the samples, partial linear square discriminant analysis (PLS-DA) classified 50.2% of the samples correctly, K-nearest neighbor (KNN) 86%, and soft independent modeling of class analogy (SIMCA) 56.2%. Therefore, in this proof of concept demonstration, the proposed approach based on chemical data satisfactorily predicted the cachaças' geographic origins.

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Because of their short life span and high production and consumption rates, mobile phones are one of the contributors to WEEE (waste electrical and electronic equipment) growth in many countries. If incorrectly managed, the hazardous materials used in the assembly of these devices can pollute the environment and pose dangers for workers involved in the recycling of these materials. In this study, 144 polymer fragments originating from 50 broken or obsolete mobile phones were analyzed via laser-induced breakdown spectroscopy (LIBS) without previous treatment. The coated polymers were mainly characterized by the presence of Ag, whereas the uncoated polymers were related to the presence of Al, K, Na, Si and Ti. Classification models were proposed using black and white polymers separately in order to identify the manufacturer and origin using KNN (K-nearest neighbor), SIMCA (Soft Independent Modeling of Class Analogy) and PLS-DA (Partial Least Squares for Discriminant Analysis). For the black polymers the percentage of correct predictions was, in average, 58% taking into consideration the models for manufacturer and origin identification. In the case of white polymers, the percentage of correct predictions ranged from 72.8% (PLS-DA) to 100% (KNN).

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In this study, laser-induced breakdown spectroscopy (LIBS) was combined with chemometric strategies (PCA, Principal Component Analysis) and scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS) to investigate the metal composition of a printed circuit board (PCB) sample from a mobile phone. Scanning electron microscopy-EDS was used for two main reasons: it was possible at the same time to visualize the sample surface, craters (made by the laser pulses) and also the chemical composition of the samples. A 30 mm×40 mm area of the mobile phone PCB sample, which was manufactured in 2011, was investigated. In this case, a matrix with 30 rows and 40 columns (1200 points) was analyzed, and 10 pulses were performed at each point. A total of 12,000 emission spectra were recorded in the wavelength range from 186 to 1040 nm. After an initial exploratory investigation using PCA, 18 emission lines were selected (representing the elements Al, Au, Ba, Ca, Co, Cu, Fe, K, Li, Mg, Mn, Na, Ni, Sb, Si, Sn, Ti and Zn) and then normalized by the relative intensities, and a new PCA was calculated with the autoscaled data. For example, Au and Si were mainly observed in the superficial electrical contacts and in the bulk of the PCB, respectively. A second sample (a mouse PCB) was also analyzed and Pb (emission lines 357.273, 363.956, 368.346, 373.994 and 405.780 nm) was identified in the solders. In addition, this element was determined using FAAS (flame atomic absorption spectrometry) and the Pb concentration was around 25% (w/w). This study opens the possibility for improved recycling processes and the chemical investigation of solid samples measuring a few millimeters in dimension without sample preparation.