Brazil nut oil is highly valued in the food, cosmetic, chemical, and pharmaceutical industries, as well as other sectors of the economy. This work aims to use the Fourier transform infrared (FTIR) technique associated with partial least squares regression (PLSR) and principal component analysis (PCA) to demonstrate that these methods can be used in a prior and rapid analysis in quality control. Natural oils were extracted and stored for chemical analysis. PCA presented two groups regarding the state of degradation, subdivided into super-degraded and partially degraded groups in 99.88% of the explained variance. The applied PLS reported an acidity index (AI) prediction model with root mean square error of calibration (RMSEC) = 1.8564, root mean square error of cross-validation (REMSECV) = 4.2641, root mean square error of prediction (RMSEP) = 2.1491, R²_cal (calibration correlation coefficient) equal to 0.9679, R²_val (validation correlation coefficient) equal to 0.8474, and R²_pred (prediction correlation coefficient) equal to 0, 8468. The peroxide index (PI) prediction model showed RMSEC = 0.0005, REMSECV = 0.0016, RMSEP = 0.00079, calibration R² equal to 0.9670, cross-validation R² equal to 0.7149, and R² of prediction equal to 0.9099. The physical–chemical analyses identified that five samples fit in the food sector and the others fit in other sectors of the economy. In this way, the preliminary monitoring of the state of degradation was reported, and the prediction models of the peroxide and acidity indexes in Brazil nut oil for quality control were determined.

The Amazon suffers from the occurrence of mining along its hydrographic routes, which releases toxic substances into the aquatic environment. The objective of this study was to evaluate the risk of contamination by As and Hg that indigenous peoples are exposed to through the consumption of fish in an area impacted by mining activity in the basin of the Curuá and Baú Rivers, Altamira-PA. In total, 55 fish specimens and 30 surface water samples were collected. The decomposition of the fish samples was done by wet method with the use of nitric acid, hydrogen peroxide, and microwaves. The quantification of total mercury (THg) and total arsenic (TAs) was carried out by inductively coupled plasma optical emission spectrometry with vapor generation (VG-ICP OES). The methodology proposed by the U.S. Environmental Protection Agency was used. The results showed that TAs presents safe levels; however, THg presents a sample with levels up to (4.6 µg g-1), exceeding the permitted levels (1 µg g-1). The risk assessment shows that only the consumption of fish, linked to Hg, represents the existence of deleterious risks to indigenous peoples (hazard quotient (HQ)) > 1). Bioaccumulation factor (BAF) in fish represents a risk to indigenous people, because of the Hg’s presence. The study identified that illegal mining activities are responsible for Hg pollution in the Baú and Curuá Rivers. The fish species analyzed can be used as bioindicators of Hg in the rivers, which is relevant for making environmental and public health policy decisions.

Este estudo avaliou a influência da sazonalidade e da profundidade nos parâmetros físico-químicos do rio Curuá-Una, na área da Usina Hidrelétrica de Curuá-Una, entre março de 2015 e janeiro de 2016. Foram realizadas quatro campanhas de amostragem em oito estações, abrangendo quatro períodos sazonais e três profundidades da coluna d'água, com análises estatísticas univariadas (ANOVA de dois fatores) e multivariadas (PCA). Os resultados indicaram que a sazonalidade foi o principal fator de variação, influenciando significativamente a maioria dos parâmetros, especialmente aqueles relacionados à entrada de material particulado, nutrientes e condições redox, enquanto a profundidade exerceu um efeito limitado. A análise multivariada confirmou a separação entre os períodos sazonais e revelou relativa homogeneidade vertical, demonstrando que a dinâmica hidrológica regional controla predominantemente a qualidade da água no sistema estudado.

Os reservatórios por sua vez são estimados para equilíbrio ambiental. Os mapas isoteóricos ajudam a visualizar mudanças na qualidade da água nos reservatórios e são ferramentas úteis para monitorar parâmetros. O objetivo deste trabalho foi avaliar a utilização de mapas geoestatísticos como ferramenta de gestão da qualidade da água utilizada na avaliação sazonal e temporal dos parâmetros: cloreto, condutividade elétrica, temperatura e sólidos totais dissolvidos na área da Usina Hidrelétrica de Tucuruí. Os dados foram avaliados em relação à estatística descritiva, ao teste e à garantia. Os mapas isotérmicos foram construídos utilizando o software Surfer 13 para interpolar a distribuição espacial dos dados. A sazonalidade influenciou todos os parâmetros estudados, revelando-se um fator importante na alteração da qualidade da água. A pesquisa mostrou que a qualidade da água do rio Tocantins é influenciada pela agricultura, principal atividade humana na área de estudo. Mapas geoestatísticos são importantes ferramentas de gestão da qualidade da água e podem ser utilizados em grandes áreas, como reservatórios de hidrelétricas na Amazônia.

The El Niño phenomenon in the Amazon is associated with extreme drought and lower atmospheric humidity, leading to environmental disturbances, such as wildfires and decreased river levels. An exceptionally intense El Niño occurred between 2015 and 2016, reaching historic magnitudes. This study evaluated its influence on water quality parameters in the Curuá‐Una Hydroelectric Power Plant reservoir, located near Santarém, Pará, in the Brazilian Amazon. Data from 2012, used as a baseline, were compared with those obtained in 2015, during the event. The 2012 dataset was provided by the company responsible for reservoir monitoring, whereas water samples in 2012 were collected at eight stations during both rainy and dry seasons. Results highlighted significant differences in most water quality parameters, particularly lower pH, phosphate, and ammonium concentrations, together with higher total dissolved solids (TDSs) and chlorophyll a during the 2015 dry season. Principal component analysis revealed distinct seasonal patterns, with higher phosphate contributions in the rainy season and greater influence of TDSs, chloride, chlorophyll a, phosphate, and ammonium in the dry season. These findings suggest that the 2015 El Niño drought was associated with marked changes in water quality, particularly during the dry season, highlighting the sensitivity of Amazonian reservoirs to extreme climatic events.

This study evaluated the water quality of artesian wells and effluents generated in cassava processing in a rural area of Bragança, Pará, with emphasis on physicochemical parameters, multielement composition, and cyanogenic compounds. The well water presented specific nonconformities, highlighting pH values below the recommended level and high concentrations of residual chlorine. Although cyanide was not detected in the groundwater, the effluents presented concentrations of total and free cyanide above legal limits, mainly in the pressing water and in the washing and fermentation tanks, indicating an environmental risk associated with the inadequate disposal of these residues. Regarding the multielement analysis, boron and copper enrichment was observed in the well water, and high concentrations of manganese and nickel were found in the effluents, exceeding the limits established by Brazilian environmental legislation. The multivariate analysis revealed distinct physicochemical profiles between the well water and the effluents, with temperature, dissolved oxygen, and pH being the main factors responsible for the differentiation between the matrices. The results indicate the need for improvements in the management and treatment systems of cassava processing effluents, aiming at protecting water resources and reducing potential environmental and human health risks.