Intensive use of asphalt generates pollutants into the atmosphere which are harmful to the environment and worrying for occupational health. The application of asphalt products leads to emissions of significant concentrations of polycyclic aromatic hydrocarbons (PAHs) and particulate matter (PM) to the atmosphere. This paper aims to assess the pollutant emissions into the atmosphere in real conditions of asphalt paving through sampling and quantification of PM, Black Carbon (BC) and PAHs in fine particulate fraction and PAHs in gas phase. Concentration intervals of PM1.0, PM2.5, BC1.0 and BC2.5 found during a highway reconstruction in Londrina/PR were respectively 5.6-20.5; 6.3-24.2; 2.0-6.8 and 1.8-6.5 µg m-3. During asphalt surfacing at the same city’s central bus station, the concentration intervals were 15.1-75.1; 19.7-150; 5.1-14.6 and 4.9-16.2 µg m-3 for PM1.0, PM2.5, BC1.0 and BC2.5, respectively. PAHs in the gas and PM fractions were found in both situations with higher concentrations in the gas phase. The results of this work can provide useful information to society in order to improve practices and promote lower environmental impact and health protection.

The present study aims to quantify black carbon (BC), particulate matter (PM1.0 and PM2.5, particles with diameter ≤ 1.0 and 2.5 µm, respectively) levels and their variability during the combustion of biodiesel/diesel blends used in heavy-duty vehicles. The samplings were conducted in the years 2014, 2016 and 2017 inside a semi closed bus station, a direct source of emission from engines burning blends of B5 to B8 biodiesel/diesel. Diesel engines using B5 and B6 presented a high contribution of BC in PM1.0 fraction representing 95 and 98% in mass, respectively. Results obtained from engines fueled with B7 and B8 diesel blends showed about 47% BC mass contribution in fine PM. The ratio PM1.0/PM2.5 remained relatively constant showing that the fine PM mass did not change significantly. Those measurements are important to follow the behavior of the addition of biodiesel in the diesel fuel as well as to help indicate a fingerprint of BC and PM2.5 concentrations in biodiesel increase.

In order to study the emission of vapor-phase polycyclic aromatic hydrocarbons (PAHs) by light-duty vehicles burning gasoline and ethanol blends, air samplings were performed at a parking lot in Londrina, PR, Brazil. The samples were obtained during the summer and winter 2012. The semi-volatile PAHs were collected using a cartridge packed with XAD-2 resin, extracted under sonication and subsequently analyzed by liquid chromatograph equipped with fluorescence and photodiode array detectors. Acenapthene (ACE) appears as the most abundant PAH, followed by acenapthylene (ACY) (summer) and fluorene (FLU) (winter). From the total PAHs analyzed (83.5 ng m−3 in winter and 574 ng m−3 in summer), low molecular weight PAHs (LM-PAHs) corresponded to 93%. The PAH source fingerprint identified in this study was obtained from local and identified sources, and the fluoranthene (FLT) / (FLT + pyrene (PYR)) and anthracene (ANT) / (ANT + phenanthrene (PHE)) ratios corresponding to 0.94 and 0.46, respectively, were characteristic of gasoline and ethanol blend emission.

The quality of biodiesel is extremely important for its commercialization and use; oxidation of biodiesel is a critical factor because it decreases the fuel storage time. A commercial biodiesel was mixed with synthetic antioxidants, according to a simplex-centroid experimental mixture design, and its stability was evaluated through induction period and activation energy. In all trials, addition of antioxidants increased activation energy in the mixtures containing tertiary butylhydroquinone (TBHQ). When a mixture containing 50% TBHQ and 50% butylated hydroxyanisole was used, synergistic effect was observed, and the major activation energy obtained was 104.43 kJ mol-1.

Vinte variedades de soja (Glycine max), quatorze convencionais e seis variedades transgênicas (RR) foram analisadas quanto ao teor de proteína, ácido fítico, teor de óleo, fitosteróis, cinzas, minerais e ácidos graxos que foram tabelados e apresentados à rede neural do tipo perceptron de múltiplas camadas para a classificação e identificação quanto a região de plantio e quanto a variedade convencional ou transgênica. A rede neural utilizada classificou e testou corretamente 100% das amostras cultivadas por região. Para o banco de dados contendo informações sobre sojas transgênicas e convencionais foi obtido um desempenho de 94,43% no treinamento da rede, 83,30% no teste e 100% na validação.

Twenty soybean (Glycine max) varieties, 14 conventional and 6 transgenic varieties were analyzed for protein content, phytic acid, oil content, phytosterols, ash, minerals and fatty acids. The data were tabled and presented to the multilayer perceptron neural network for classification and identification of their planting region and whether they were a conventional or transgenic. The neural network used correctly classified and tested 100% of the samples cultivated per region. For the data bank containing information on transgenic and conventional soybean, a performance of 94.43% was obtained in the training of the neural network, 83.30% in the test and 100% in the validation.