A total of 2400 samples of commercial Brazilian C gasoline were collected over a 6-month period from different gas stations in the São Paulo state, Brazil, and analysed with respect to 12 physicochemical parameters according to regulation 309 of the Brazilian Government Petroleum, Natural Gas and Biofuels Agency (ANP). The percentages (v/v) of hydrocarbons (olefins, aromatics and saturated) were also determined. Hierarchical cluster analysis (HCA) was employed to select 150 representative samples that exhibited least similarity on the basis of their physicochemical parameters and hydrocarbon compositions. The chromatographic profiles of the selected samples were measured by gas chromatography with flame ionisation detection and analysed using soft independent modelling of class analogy (SIMCA) method in order to create a classification scheme to identify conform gasolines according to ANP 309 regulation. Following the optimisation of the SIMCA algorithm, it was possible to classify correctly 96% of the commercial gasoline samples present in the training set of 100. In order to check the quality of the model, an external group of 50 gasoline samples (the prediction set) were analysed and the developed SIMCA model classified 94% of these correctly. The developed chemometric method is recommended for screening commercial gasoline quality and detection of potential adulteration.
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http://dx.doi.org/10.1016/j.aca.2007.02.049 | DOI Listing |
J Environ Qual
December 2024
Departamento de Solos, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
Although ecosystem management and restoration are known to enhance carbon storage, limited knowledge of ecosystem-specific soil organic carbon (SOC) stocks and processes hinders the development of climate-ready, biodiversity-focused policies. Baseline SOC stocks data for specific ecosystems is essential. This paper aims to: (i) examine SOC stock variability across major grassy ecosystems in Brazil and (ii) discuss data limitations and applications.
View Article and Find Full Text PDFBiol Trace Elem Res
December 2024
Laboratory of Toxicology (LATOX), Department of Analysis, Faculty of Pharmacy, Federal University of Rio Grande do Sul, Rua São Luis 150-Anexo II, Santa Cecília, Porto Alegre, RS, CEP: 90610-000, Brazil.
Occupational exposure to pollutants may cause health-damaging effects in humans. Genotoxicity assays can be used to detect the toxic effects of pollutants. In the present study, we evaluated genetic damage in three populations occupationally exposed to benzene, pyrenes, and agrochemicals and assessed the possible influence of titanium (Ti) co-exposure.
View Article and Find Full Text PDFChem Biodivers
December 2024
Laboratório de Química dos Produtos Naturais, Universidade do Estado do Pará, Belém, Pará, Brazil.
Alpinia nutans (L.) Roscoe (Zingiberaceae) is used in folk medicine as an antiviral, anti-inflammatory, and antioxidant. This study aimed to evaluate the seasonality effects on the yield, chemical composition, antioxidant capacity, and anti-Candida activity of the A.
View Article and Find Full Text PDFInt J Med Inform
December 2024
Division of Thoracic Surgery, Instituto do Coracao do Hospital das Clinicas HCFMUSP da Faculdade de Medicina da Universidade de Sao Paulo, Brazil.
Objective: The patient's journey to the medical center for an outpatient visit can often mean hours of travel in their vehicle, leading to increased expenses and greater carbon dioxide (CO2) emissions into the environment. The study demonstrates the estimated carbon emission and cost savings associated with a telemedicine program dedicated to patients with tracheal disease in the Brazilian public health system.
Methods: Cross-sectional study of telemedicine visits for patients with tracheal disease referred to a public academic hospital between August 1, 2020, and December 30, 2023.
J Environ Manage
December 2024
Department of Animal Science, School of Agricultural and Veterinary Sciences, Sao Paulo State University (UNESP), SP, Brazil.
There is an important gap in how variations in herbivore dung composition affect GHG emissions on pastures, especially due to differences in dry matter (DM) and nitrogen contents. Oversimplifications can compromise the accuracy of mitigation strategies. This study aims to address this gap by investigating how the chemical composition of dung from different species influences GHG emissions in pasture systems.
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