967 resultados para Soil Pollution--Analysis


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Spatial analysis and fuzzy classification techniques were used to estimate the spatial distributions of heavy metals in soil. The work was applied to soils in a coastal region that is characterized by intense urban occupation and large numbers of different industries. Concentrations of heavy metals were determined using geostatistical techniques and classes of risk were defined using fuzzy classification. The resulting prediction mappings identify the locations of high concentrations of Pb, Zn, Ni, and Cu in topsoils of the study area. The maps show that areas of high pollution of Ni and Cu are located at the northeast, where there is a predominance of industrial and agricultural activities; Pb and Zn also occur in high concentrations in the northeast, but the maps also show significant concentrations of Pb and Zn in other areas, mainly in the central and southeastern parts, where there are urban leisure activities and trade centers. Maps were also prepared showing levels of pollution risk. These maps show that (1) Cu presents a large pollution risk in the north-northwest, midwest, and southeast sectors, (2) Pb represents a moderate risk in most areas, (3) Zn generally exhibits low risk, and (4) Ni represents either low risk or no risk in the studied area. This study shows that combining geostatistics with fuzzy theory can provide results that offer insight into risk assessment for environmental pollution.

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Soil and subsoil pollution is not only significant in terms of environmental loss, but also a matter of environmental and public health. Solid, liquid and gaseous residues are the major soil contamination agents. They originate from urban conglomerates and industrial areas in which it is impossible to emphasize the chemical, petrochemical and textile industry; thermoelectric, mining, and ironmaster activities. The contamination process can thus be defined as a compound addition to soil, from what qualitative and or quantitative manners can modify soil's natural characteristics and use, producing baneful and deteriorative effects on human health. Studies have shown that human exposition to high concentration of some heavy metals found on soil can cause serious health problems, such as pulmonary or kidney complications, liver and nervous system harm, allergy, and the chronic exposition that leads to death. The present study searches for the correlation among soil contamination, done through a geochemical baseline survey of an industrial contamination area on the shoreline of Sao Paulo state. The study will be conducted by spatial analysis using Geographical Information Systems for mapping and regression analysis. The used data are 123 soil samples of percentage concentration of heavy metals. They were sampled and spatially distributed by geostatistics methods. To verify if there is a relation between heavy metals soil pollution and morbidity an executed correlation and regression analysis will be done using the pollution registers as the independent variables and morbidity as dependable variables. It is expected, by the end of the study, to identify the areas relation between heavy metals soil pollution and morbidity, moreover to be able to provide assistance in terms of new methodologies that could facilitate soil pollution control programs and public health planning. © 2010 WIT Press.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The problems caused by the residual effluents of wine distilleries for alcohol production are well known. The effluent effects in soil and groundwater are being researched in an area with sugar cane culture which receives, yearly, vinasse by dispersion. Samples are being collected from the soil, the groundwater and the existing creeks in the area. Four sub-areas are being monitored separately with a vinasse application of 300 m 3/ha year. Experimentation periods in each area have been 0, 5, 10 and 15 years. In the unsaturated zone, samples are being collected at depths of 25, 75 and 150 cm. The chemical analyses include macro and micro nutrients, organic matter and pH. Physical analyses give the soil water retention, hydraulic conductivity and soil particle distribution. These measurements permit the evaluation of nitrogen absorption and fertility changes of the soil. A tendency for the maintenance of soil fertility can be observed but with an elevation of nitrate concentration in groundwater.

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Biodiesel production has received considerable attention in the recent past as a nonpolluting fuel. However, this assertion has been based on its biodegradability and reduction in exhaust emissions. Assessments of water and soil biodiesel pollution are still limited. Spill simulation with biodiesel and their diesel blends in soils were carried out, aiming at analyzing their cytotoxic and genotoxic potentials. While the cytotoxicity observed may be related to diesel contaminants, the genotoxic and mutagenic effects can be ascribed to biodiesel pollutants. Thus, taking into account that our data stressed harmful effects on organisms exposed to biodiesel-polluted soils, the designation of this biofuel as an environmental-friendly fuel should be carefully reviewed to assure environmental quality. (C) 2011 Elsevier B.V. All rights reserved.

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A reduction in the numbers of macroinvertebrates present in soil may have a negative effect on soil structure, infiltration rates, and gas exchanges. Soil pollution by metal is known to have a detrimental effect on soil macrofauna. The aim of the present study was to evaluate (1) direct and indirect effects of soil pollution on soil macroinvertebrate bioturbation and (2) effects of the two macroinvertebrate communities found in a polluted and a nonpolluted area (one supposed sensitive, the other tolerant to metals) on burrow systems parameters. Macroinvertebrate porosity was studied using X-ray tomography. Three-dimensional reconstructions and characterisation of the burrow system were obtained using image analysis. Results showed that metal pollution principally affected the spatial distribution of macropores (more macropores were found near the soil surface) and the shape of the burrow system (branching rate was higher in the polluted soil), whereas soil macroinvertebrate composition principally affects burrow density parameters (the number of burrows was higher for the sensitive macroinvertebrate community).

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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"January 15, 1957."

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Urban rainfall-runoff residuals contain metals such as Cr, Zn, Cu, As, Pb and Cd and are thus reasonable candidates for treatment using Portland cement-based solidification-stabilization (S/S). This research is a study of S/S of urban storm water runoff solid residuals in Portland cement with quicklime and sodium bentonite additives. The solidified residuals were analyzed after 28 days of hydration time using X-ray powder diffraction (XRD) and solid-state Si-29 nuclear magnetic resonance (NMR) spectroscopy. X-ray diffraction (XRD) results indicate that the main cement hydration products are ettringite, calcium hydroxide and hydrated calcium silicates. Zinc hydroxide and lead and zinc silicates are also present due to the reactions of the waste compounds with the cement and its hydration products. Si-29 NMR analysis shows that the coarse fraction of the waste apparently does not interfere with cement hydration, but the fine fraction retards silica polymerization.

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Phytotoxicity and transfer of potentially toxic elements, such as cadmium (Cd) or barium (Ba), depend on the availability of these elements in soils and on the plant species exposed to them. With this study, we aimed to evaluate the effect of Cd and Ba application rates on yields of pea (Pisum sativum L.), sorghum (Sorghum bicolor L.), soybean (Glycine max L.), and maize (Zea mays L.) grown under greenhouse conditions in an Oxisol and an Entisol with contrasting physical and chemical properties, and to correlate the amount taken up by plants with extractants commonly used in routine soil analysis, along with transfer coefficients (Bioconcentration Factor and Transfer Factor) in different parts of the plants. Plants were harvested at flowering stage and measured for yield and Cd or Ba concentrations in leaves, stems, and roots. The amount of Cd accumulated in the plants was satisfactorily evaluated by both DTPA and Mehlich-3 (M-3). Mehlich-3 did not relate to Ba accumulated in plants, suggesting it should not be used to predict Ba availability. The transfer coefficients were specific to soils and plants and are therefore not recommended for direct use in risk assessment models without taking soil properties and group of plants into account.

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Spatial data analysis mapping and visualization is of great importance in various fields: environment, pollution, natural hazards and risks, epidemiology, spatial econometrics, etc. A basic task of spatial mapping is to make predictions based on some empirical data (measurements). A number of state-of-the-art methods can be used for the task: deterministic interpolations, methods of geostatistics: the family of kriging estimators (Deutsch and Journel, 1997), machine learning algorithms such as artificial neural networks (ANN) of different architectures, hybrid ANN-geostatistics models (Kanevski and Maignan, 2004; Kanevski et al., 1996), etc. All the methods mentioned above can be used for solving the problem of spatial data mapping. Environmental empirical data are always contaminated/corrupted by noise, and often with noise of unknown nature. That's one of the reasons why deterministic models can be inconsistent, since they treat the measurements as values of some unknown function that should be interpolated. Kriging estimators treat the measurements as the realization of some spatial randomn process. To obtain the estimation with kriging one has to model the spatial structure of the data: spatial correlation function or (semi-)variogram. This task can be complicated if there is not sufficient number of measurements and variogram is sensitive to outliers and extremes. ANN is a powerful tool, but it also suffers from the number of reasons. of a special type ? multiplayer perceptrons ? are often used as a detrending tool in hybrid (ANN+geostatistics) models (Kanevski and Maignank, 2004). Therefore, development and adaptation of the method that would be nonlinear and robust to noise in measurements, would deal with the small empirical datasets and which has solid mathematical background is of great importance. The present paper deals with such model, based on Statistical Learning Theory (SLT) - Support Vector Regression. SLT is a general mathematical framework devoted to the problem of estimation of the dependencies from empirical data (Hastie et al, 2004; Vapnik, 1998). SLT models for classification - Support Vector Machines - have shown good results on different machine learning tasks. The results of SVM classification of spatial data are also promising (Kanevski et al, 2002). The properties of SVM for regression - Support Vector Regression (SVR) are less studied. First results of the application of SVR for spatial mapping of physical quantities were obtained by the authorsin for mapping of medium porosity (Kanevski et al, 1999), and for mapping of radioactively contaminated territories (Kanevski and Canu, 2000). The present paper is devoted to further understanding of the properties of SVR model for spatial data analysis and mapping. Detailed description of the SVR theory can be found in (Cristianini and Shawe-Taylor, 2000; Smola, 1996) and basic equations for the nonlinear modeling are given in section 2. Section 3 discusses the application of SVR for spatial data mapping on the real case study - soil pollution by Cs137 radionuclide. Section 4 discusses the properties of the modelapplied to noised data or data with outliers.

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The applicability of supercritical fluid extraction (SFE) in pesticide multiresidue analysis (organohalogen, organonitrogen, organophosphorus, and pyrethroid) in soil samples was investigated. Fortification experiments were conducted to test the conventional extraction (solid-liquid) and to optimize the extraction procedure in SFE by varying the CO2 Modifier, temperature, extraction time, and pressure. The best efficiency was achieved at 400 bar using methanol as modifier at 60 degreesC. For the SFE method, C-18 cartridges were used for the cleanup. The analytical screening was performed by gas chromatography equipped with electron-capture detection (ECD). Recoveries for the majority of pesticides from spiked samples of soil at different residence times were 1, 20, and 40 days at the fortification level of 0.04-0.10 mg/kg ranging from 70 to 97% for both methods. The detection limits found were <0.01 mg/kg for ECD, and the confirmation of pesticide identity was performed by gas chromatography-mass spectrometry in a selected-ion monitoring mode. Multiresidue methods were applied in real soil samples, and the results of the methods developed were compared.

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Diplopods feed organic matter in decomposition; however, some environmental factors can promote changes in tissues of these animals. Sewage sludge has been applied for recuperation of physical structure of degraded soil. This work analyzed the influence of the sludge from a city of So Paulo in the midgut of the diplopod Rhinocricus padbergi. After the exposition to sludge, the midgut was prepared for histological and ultra-structural analyses. After 1 week of exposition, there were various glycoprotein globules in the fat body, which appeared, ultrastructurally, little electron dense. In the animals exposed for 2 weeks, there was an intensive renovation of the epithelium with the invasion of regenerative cells, which was observed in the histological and ultra-structural analyses. These data showed that the sludge present various substances that were very hazardous for these animals; more studies were necessary before the application of this in agriculture.

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With the development of the textile industry, there has been a demand for dye removal from contaminated effluents. In recent years, attention has been directed toward various natural solid materials that are capable of removing pollutants from contaminated water at low cost. One such material is sugarcane bagasse. The aim of the present study was to evaluate adsorption of the dye Acid Violet Alizarin N with different concentrations of sugarcane bagasse and granulometry in agitated systems at different pH. The most promising data (achieved with pH 2.5) was analyzed with both Freundlich and Langmuir isotherms equations. The model that better fits dye adsorption interaction into sugarcane bagasse is Freundlich equation, and thus the multilayer model. Moreover, a smaller bagasse granulometry led to greater dye adsorption. The best treatment was achieved with a granulometry value lower than 0.21 mm at pH 2.50, in which the total removal was estimated at a concentration of 16.25 mg mL(-1). Hence, sugarcane bagasse proves to be very attractive for dye removal from textile effluents.