18 resultados para organic classification


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The use of chemicals and chemical derivatives in agriculture and industry has contributed to their accumulation and persistence in the environment. Persistent organic pollutants (POPs) are among the environmental pollutants of most concern since, when improperly handled and disposed, they can persist in the environment, bioaccumulate through the food web, and may create serious public health and environmental problems. Development of an effective degradation process has become an area of intense research. The physical/chemical methods employed, such as volatilization, evaporation, photooxidation, adsorption, or hydrolysis, are not always effective, are very expensive, and, sometimes, lead to generation/disposal of other contaminants. Biodegradation is one of the major mechanisms by which organic contaminants are transformed, immobilized, or mineralized in the environment. A clear understanding of the major processes that affect the interactions between organic contaminants, microorganisms, and environmental matrix is, thus, important for determining persistence of the compounds, for predicting in situ transformation rates, and for developing site remediation. Information on their risks and impact and occurrence in the different environmental matrices is also important, in order to attenuate their impact and apply the appropriate remediation process. This chapter provides information on the fate of pesticides and polycyclic aromatic hydrocarbons (PAHs), their impact, bioavailability, and biodegradation. © Springer Science+Business Media Dordrecht 2014.

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Dissertação de mestrado em Bioengenharia

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Natural mineral waters (still), effervescent natural mineral waters (sparkling) and aromatized waters with fruit-flavors (still or sparkling) are an emerging market. In this work, the capability of a potentiometric electronic tongue, comprised with lipid polymeric membranes, to quantitatively estimate routinely quality physicochemical parameters (pH and conductivity) as well as to qualitatively classify water samples according to the type of water was evaluated. The study showed that a linear discriminant model, based on 21 sensors selected by the simulated annealing algorithm, could correctly classify 100 % of the water samples (leave-one out cross-validation). This potential was further demonstrated by applying a repeated K-fold cross-validation (guaranteeing that at least 15 % of independent samples were only used for internal-validation) for which 96 % of correct classifications were attained. The satisfactory recognition performance of the E-tongue could be attributed to the pH, conductivity, sugars and organic acids contents of the studied waters, which turned out in significant differences of sweetness perception indexes and total acid flavor. Moreover, the E-tongue combined with multivariate linear regression models, based on sub-sets of sensors selected by the simulated annealing algorithm, could accurately estimate waters pH (25 sensors: R 2 equal to 0.99 and 0.97 for leave-one-out or repeated K-folds cross-validation) and conductivity (23 sensors: R 2 equal to 0.997 and 0.99 for leave-one-out or repeated K-folds cross-validation). So, the overall satisfactory results achieved, allow envisaging a potential future application of electronic tongue devices for bottled water analysis and classification.