980 resultados para cleaning of contaminated soil


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Agricultural reuse of treated sewage effluent (TSE) is an environmental and economic practice; however, little is known about its effects on the characteristics and microbial function in tropical soils. The effect of surplus irrigation of a pasture with TSE, in a period of 18 months, was investigated, considering the effect of 0% surplus irrigation with TSE as a control. In addition, the experiment consisted of three surplus treatments (25%, 50%, and 100% excess) and a nonirrigated pasture area (SE) to compare the soil microbial community level physiological profiles, using the Biolog method. The TSE application increased the average substrate consumption of the soil microbial community, based on the kinetic parameters of the average well color development curve fitting. There were no significant differences between the levels of surplus irrigation treatments. Surplus TSE pasture irrigation caused minor increases in the physiological status of the soil microbial community but no detectable damage to the pasture or soil.

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This study investigated the ionic speciation of reclaimed urban wastewater (RWW), and the impact of increasing RWW irrigation rates on soil properties and plant nutrition under field conditions. Most RWW elements (>66%) are readily available as NH(4)(+), Ca(2+), Mg(2+), K(+), SO(4)(2-), Cl(-), H(3)BO(3), Mn(2+) and Zn(2+), but in imbalanced proportion for plant nutrition. Lead, Cd, Cr and Al in RWW are mostly bounded with DOM or OH. Irrigation with RWW decreased soil acidity, which is beneficial to the acidic tropical soil. Although RWW irrigation builds exchangeable Na(+) up, the excessive Na(+) was leached out of the soil profile after a rainy summer season (>400 mm). Benefits of the disposal of RWW to the soil under tropical conditions were discussed, however, the over irrigation with RWW (>100% of crop evapotranspiration) led to a nutritional imbalance, accumulating S and leading to a plant deficiency of P and K. (C) 2011 Elsevier B.V. All rights reserved.

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Humic substances (HS) from salt marsh soils were characterized and the relationships among HS composition and some geochemical factors were analysed. For this, three salt marshes with the same vegetation cover (Juncus maritimus), but with different geochemical characteristics, were selected. The qualitative characterization of the soil humic acids and fulvic acids was carried out by elemental analysis, FTIR spectroscopy, fluorescence spectroscopy and VACP/MAS (13)C NMR spectroscopy. HS from salt marsh soils under sea rush (Juncus maritimus) displayed some shared characteristics such as low degree of humification, low aromatic content and high proportion of labile compounds, mainly polysaccharides and proteins. However, although the three salt marsh soils under study were covered by the same type of vegetation, the HS showed some important differences. HS composition was found to be determined not only by the nature of the original organic material, but also by environmental factors such as soil texture, redox conditions and tidal influence. In general. an increase in the humification process appeared to be related to aerobic conditions and predominance of sand in the mineral fraction of the soil, while the preservation of labile organic compounds may be associated with low redox potential values and fine soil texture. (C) 2008 Elsevier Ltd. All rights reserved.

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Study of surface electric charges of soil colloids helps in understanding the physicochemical phenomena that influence the capacity of retaining nutrients and their availability to plants. The structural charge (sigma(0), (min)), the variable charge (sigma(q, min)), and the organic matter (OM) charge (sigma(total) (OM)) of 12 tropical soils with contrasting mineralogies were evaluated based on the difference of selectivity for Cs(+) and Li(+) between the functional ionizable surfaces groups and the mineral 2:1 siloxane surface. Soils were divided into three groups: G1, soils with a predominance of kaolinite and gibbsite in the clay fraction; G2, soils with hydroxy-interlayered 2:1 minerals; and G3, soils with smectite but without hydroxy-interlayered 2:1 minerals. The Cs absorption method was efficient for detecting the charge components in tropical soils. The mineral structural charge contributed 11% and 16%, 28% and 31%, and 52% and 59% of total soil charge of A and B horizons of soils from groups G 1, G2, and G3, respectively. On the other hand, OM contributed 53% and 37%, 48% and 41%, and 21% and 20% of total charge for the same samples, respectively, In highly weathered soils of group G I and, to a lesser extent, in soils in group G2, surface charges depended mainly on their variable components, resulting from the OM (sigma(toal) (OM)), as well as from imperfections found in 1:1 minerals (sigma(q, min)). The importance of OM in determining the magnitude of electric charges in humid tropical soils is highlighted.

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Previously known only from the southern United States, hosta petiole rot recently appeared in the northern United States. Sclerotium rolfsii var. delphinii is believed to be the predominant petiole rot pathogen in the northern United States, whereas S. rolfsii is most prevalent in the southern United States. In order to test the hypothesis that different tolerance to climate extremes affects the geographic distribution of these fungi, the survival of S. rolfsii and S. rolfsii var. delphinii in the northern and southeastern United States was investigated. At each of four locations, nylon screen bags containing sclerotia were placed on the surface of bare soil and at 20-cm depth. Sclerotia were recovered six times from November 2005 to July 2006 in North Dakota and Iowa, and from December 2005 to August 2006 in North Carolina and Georgia. Survival was estimated by quantifying percentage of sclerotium survival on carrot agar. Sclerotia of S. rolfsii var. delphinii survived until at least late July in all four states. In contrast, no S. rolfsii sclerotia survived until June in North Dakota or Iowa, whereas 18.5% survived until August in North Carolina and 10.3% survived in Georgia. The results suggest that inability to tolerate low temperature extremes limits the northern range of S. rolfsii.

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Listeria monocytogenes is a bacterial pathogen that represents a serious threat during pregnancy and several cases of listeriosis have been linked to the consumption of contaminated foods worldwide. In Brazil, there is no report of foodborne listeriosis, despite some sporadic cases of infection by this bacterium occur. In general in our country, there is no awareness of medical personnel to instruct moms-to-be to avoid high risk foods. In the present study, a total of 141 samples were surveyed for the presence of Listeria spp., including cervicovaginal samples of patients, foods and home refrigerators. No clinical sample was positive for Listeria spp., but it was isolated from two refrigerators. L. monocytogenes was detected in two food samples out of five positive ones for Listeria spp. In conclusion, it was shown the presence of contaminated food items at home level and the lack of information on the risks of listeriosis, indicating the need of implementation of food safety education programs. (C) 2007 Elsevier Ltd. All rights reserved.

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Despite the increasing prevalence of salinity world-wide, the measurement of exchangeable cation concentrations in saline soils remains problematic. Two soil types (Mollisol and Vertisol) were equilibrated with a range of sodium adsorption ratio (SAR) solutions at various ionic strengths. The concentrations of exchangeable cations were then determined using several different types of methods, and the measured exchangeable cation concentrations compared to reference values. At low ionic strength (low salinity), the concentration of exchangeable cations can be accurately estimated from the total soil extractable cations. In saline soils, however, the presence of soluble salts in the soil solution precludes the use of this method. Leaching of the soil with a pre-wash solution (such as alcohol) was found to effectively remove the soluble salts from the soil, thus allowing the accurate measurement of the effective cation exchange capacity (ECEC). However, the dilution associated with this pre-washing increased the exchangeable Ca concentrations while simultaneously decreasing exchangeable Na. In contrast, when calculated as the difference between the total extractable cations and the soil solution cations, good correlations were found between the calculated exchangeable cation concentrations and the reference values for both Na (Mollisol: y=0.873x and Vertisol: y=0.960x) and Ca (Mollisol: y=0.901x and Vertisol: y=1.05x). Therefore, for soils with a soil solution ionic strength greater than 50 mM (electrical conductivity of 4 dS/m) (in which exchangeable cation concentrations are overestimated by the assumption they can be estimated as the total extractable cations), concentrations can be calculated as the difference between total extractable cations and soluble cations.

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To simulate cropping systems, crop models must not only give reliable predictions of yield across a wide range of environmental conditions, they must also quantify water and nutrient use well, so that the status of the soil at maturity is a good representation of the starting conditions for the next cropping sequence. To assess the suitability for this task a range of crop models, currently used in Australia, were tested. The models differed in their design objectives, complexity and structure and were (i) tested on diverse, independent data sets from a wide range of environments and (ii) model components were further evaluated with one detailed data set from a semi-arid environment. All models were coded into the cropping systems shell APSIM, which provides a common soil water and nitrogen balance. Crop development was input, thus differences between simulations were caused entirely by difference in simulating crop growth. Under nitrogen non-limiting conditions between 73 and 85% of the observed kernel yield variation across environments was explained by the models. This ranged from 51 to 77% under varying nitrogen supply. Water and nitrogen effects on leaf area index were predicted poorly by all models resulting in erroneous predictions of dry matter accumulation and water use. When measured light interception was used as input, most models improved in their prediction of dry matter and yield. This test highlighted a range of compensating errors in all modelling approaches. Time course and final amount of water extraction was simulated well by two models, while others left up to 25% of potentially available soil water in the profile. Kernel nitrogen percentage was predicted poorly by all models due to its sensitivity to small dry matter changes. Yield and dry matter could be estimated adequately for a range of environmental conditions using the general concepts of radiation use efficiency and transpiration efficiency. However, leaf area and kernel nitrogen dynamics need to be improved to achieve better estimates of water and nitrogen use if such models are to be use to evaluate cropping systems. (C) 1998 Elsevier Science B.V.

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Nitrogen relations of natural and disturbed tropical plant communities in northern Australia (Kakadu National Park) were studied. Plant and soil N characteristics suggested that differences in N source utilisation occur at community and species level. Leaf and xylem sap N concentrations of plants in different communities were correlated with the availability of inorganic soil N (NH4+ and NO3-). In general, rates of leaf NO3- assimilation were low. Even in communities with a higher N status, including deciduous monsoon forest, disturbed wetland, and a revegetated mine waste rock dump, levels of leaf nitrate reductase, xylem and leaf NO3 levels were considerably lower than those that have been reported for eutrophic communities. Although NO3- assimilation in escarpment and eucalypt woodlands, and wetland, was generally low, within these communities there was a suite of species that exhibited a greater capacity for NO3- assimilation. These high-NO3- species were mainly annuals, resprouting herbs or deciduous trees that had leaves with high N contents. Ficus, a high-NO3- species, was associated with soil exhibiting higher rates of net mineralisation and net nitrification. Low-NO3- species were evergreen perennials with low leaf N concentrations. A third group of plants, which assimilated NO3- (albeit at lower rates than the high-NO3- species), and had high-N leaves, were leguminous species. Acacia species, common in woodlands, had the highest leaf N contents of all woody species. Acacia species appeared to have the greatest potential to utilise the entire spectrum of available N sources. This versatility in N source utilisation may be important in relation to their high tissue N status and comparatively short life cycle. Differences in N utilisation are discussed in the context of species life strategies and mycorrhizal associations.

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Multiple sampling is widely used in vadose zone percolation experiments to investigate the extent in which soil structure heterogeneities influence the spatial and temporal distributions of water and solutes. In this note, a simple, robust, mathematical model, based on the beta-statistical distribution, is proposed as a method of quantifying the magnitude of heterogeneity in such experiments. The model relies on fitting two parameters, alpha and zeta to the cumulative elution curves generated in multiple-sample percolation experiments. The model does not require knowledge of the soil structure. A homogeneous or uniform distribution of a solute and/or soil-water is indicated by alpha = zeta = 1, Using these parameters, a heterogeneity index (HI) is defined as root 3 times the ratio of the standard deviation and mean. Uniform or homogeneous flow of water or solutes is indicated by HI = 1 and heterogeneity is indicated by HI > 1. A large value for this index may indicate preferential flow. The heterogeneity index relies only on knowledge of the elution curves generated from multiple sample percolation experiments and is, therefore, easily calculated. The index may also be used to describe and compare the differences in solute and soil-water percolation from different experiments. The use of this index is discussed for several different leaching experiments. (C) 1999 Elsevier Science B.V. All rights reserved.

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We assembled a globally-derived data set for site-averaged foliar delta(15)N, the delta(15)N of whole surface mineral soil and corresponding site factors (mean annual rainfall and temperature, latitude, altitude and soil pH). The delta(15)N of whole soil was related to all of the site variables (including foliar delta(15)N) except altitude and, when regressed on latitude and rainfall, provided the best model of these data, accounting for 49% of the variation in whole soil delta(15)N. As single linear regressions, site-averaged foliar delta(15)N was more strongly related to rainfall than was whole soil delta(15)N. A smaller data set showed similar, negative correlations between whole soil delta(15)N, site-averaged foliar delta(15)N and soil moisture variations during a single growing season. The negative correlation between water availability (measured here by rainfall and temperature) and soil or plant delta(15)N fails at the landscape scale, where wet spots are delta(15)N-enriched relative to their drier surroundings. Here we present global and seasonal data, postulate a proximate mechanism for the overall relationship between water availability and ecosystem delta(15)N and, newly, a mechanism accounting for the highly delta(15)N-depleted values found in the foliage and soils of many wet/cold ecosystems. These hypotheses are complemented by documentation of the present gaps in knowledge, suggesting lines of research which will provide new insights into terrestrial N-cycling. Our conclusions are consistent with those of Austin and Vitousek (1998) that foliar (and soil) delta(15)N appear to be related to the residence time of whole ecosystem N.

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This field study was a combined chemical and biological investigation of the relative effects of using dispersants to treat oil spills impacting mangrove habitats. The aim of the chemistry was to determine whether dispersant affected the short- or long-term composition of a medium range crude oil (Gippsland) stranded in a tropical mangrove environment in Queensland, Australia. Sediment cores from three replicate plots of each treatment (oil only and oil plus dispersant) were analyzed for total hydrocarbons and for individual molecular markers (alkanes, aromatics, triterpanes, and steranes). Sediments were collected at 2 days, then 1, 7, 13 and 22 months post-spill. Over this time, oil in the six treated plots decreased exponentially from 36.6 +/- 16.5 to 1.2 +/- 0.8 mg/g dry wt. There was no statistical difference in initial oil concentrations, penetration of oil to depth, or in the rates of oil dissipation between oiled or dispersed oil plots. At 13 months, alkanes were >50% degraded, aromatics were similar to 30% degraded based upon ratios of labile to resistant markers. However, there was no change in the triterpane or sterane biomarker signatures of the retained oil. This is of general forensic interest for pollution events. The predominant removal processes were evaporation (less than or equal to 27%) and dissolution (greater than or equal to 56%), with a lag-phase of 1 month before the start of significant microbial degradation (less than or equal to 7%). The most resistant fraction of the oil that remained after 7 months (the higher molecular weight hydrocarbons) correlated with the initial total organic carbon content of the soil. Removal rate in the Queensland mangroves was significantly faster than that observed in the Caribbean and was related to tidal flushing. (C) 1999 Elsevier Science Ltd. All rights reserved.

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The movement of chemicals through the soil to the groundwater or discharged to surface waters represents a degradation of these resources. In many cases, serious human and stock health implications are associated with this form of pollution. The chemicals of interest include nutrients, pesticides, salts, and industrial wastes. Recent studies have shown that current models and methods do not adequately describe the leaching of nutrients through soil, often underestimating the risk of groundwater contamination by surface-applied chemicals, and overestimating the concentration of resident solutes. This inaccuracy results primarily from ignoring soil structure and nonequilibrium between soil constituents, water, and solutes. A multiple sample percolation system (MSPS), consisting of 25 individual collection wells, was constructed to study the effects of localized soil heterogeneities on the transport of nutrients (NO3-, Cl-, PO43-) in the vadose zone of an agricultural soil predominantly dominated by clay. Very significant variations in drainage patterns across a small spatial scale were observed tone-way ANOVA, p < 0.001) indicating considerable heterogeneity in water flow patterns and nutrient leaching. Using data collected from the multiple sample percolation experiments, this paper compares the performance of two mathematical models for predicting solute transport, the advective-dispersion model with a reaction term (ADR), and a two-region preferential flow model (TRM) suitable for modelling nonequilibrium transport. These results have implications for modelling solute transport and predicting nutrient loading on a larger scale. (C) 2001 Elsevier Science Ltd. All rights reserved.

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Axial X-ray Computed tomography (CT) scanning provides a convenient means of recording the three-dimensional form of soil structure. The technique has been used for nearly two decades, but initial development has concentrated on qualitative description of images. More recently, increasing effort has been put into quantifying the geometry and topology of macropores likely to contribute to preferential now in soils. Here we describe a novel technique for tracing connected macropores in the CT scans. After object extraction, three-dimensional mathematical morphological filters are applied to quantify the reconstructed structure. These filters consist of sequences of so-called erosions and/or dilations of a 32-face structuring element to describe object distances and volumes of influence. The tracing and quantification methodologies were tested on a set of undisturbed soil cores collected in a Swiss pre-alpine meadow, where a new earthworm species (Aporrectodea nocturna) was accidentally introduced. Given the reduced number of samples analysed in this study, the results presented only illustrate the potential of the method to reconstruct and quantify macropores. Our results suggest that the introduction of the new species induced very limited chance to the soil structured for example, no difference in total macropore length or mean diameter was observed. However. in the zone colonised by, the new species. individual macropores tended to have a longer average length. be more vertical and be further apart at some depth. Overall, the approach proved well suited to the analysis of the three-dimensional architecture of macropores. It provides a framework for the analysis of complex structures, which are less satisfactorily observed and described using 2D imaging. (C) 2002 Elsevier Science B.V. All rights reserved.

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The principle of using induction rules based on spatial environmental data to model a soil map has previously been demonstrated Whilst the general pattern of classes of large spatial extent and those with close association with geology were delineated small classes and the detailed spatial pattern of the map were less well rendered Here we examine several strategies to improve the quality of the soil map models generated by rule induction Terrain attributes that are better suited to landscape description at a resolution of 250 m are introduced as predictors of soil type A map sampling strategy is developed Classification error is reduced by using boosting rather than cross validation to improve the model Further the benefit of incorporating the local spatial context for each environmental variable into the rule induction is examined The best model was achieved by sampling in proportion to the spatial extent of the mapped classes boosting the decision trees and using spatial contextual information extracted from the environmental variables.