37 resultados para Organic Soils

em Doria (National Library of Finland DSpace Services) - National Library of Finland, Finland


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Electrokinetics has emerged as a potential technique for in situ soil remediation and especially unique because of the ability to work in low permeability soil. In electrokinetic remediation, non-polar contaminants like most organic compounds are transported primarily by electroosmosis, thus the process is effective only if the contaminants are soluble in pore fluid. Therefore, enhancement is needed to improve mobility of these hydrophobic compounds, which tend to adsorb strongly to the soil. On the other hand, as a novel and rapidly growing science, the applications of ultrasound in environmental technology hold a promising future. Compared to conventional methods, ultrasonication can bring several benefits such as environmental friendliness (no toxic chemical are used or produced), low cost, and compact instrumentation. It also can be applied onsite. Ultrasonic energy applied into contaminated soils can increase desorption and mobilization of contaminants and porosity and permeability of soil through developing of cavitation. The research investigated the coupling effect of the combination of these two techniques, electrokinetics and ultrasonication, in persistent organic pollutant removal from contaminated low permeability clayey soil (with kaolin as a model medium). The preliminary study checked feasibility of ultrasonic treatment of kaolin highly contaminated by persistent organic pollutants (POPs). The laboratory experiments were conducted in various conditions (moisture, frequency, power, duration time, initial concentration) to examine the effects of these parameters on the treatment process. Experimental results showed that ultrasonication has a potential to remove POPs, although the removal efficiencies were not high with short duration time. The study also suggested intermittent ultrasonication over longer time as an effective means to increase the removal efficiencies. Then, experiments were conducted to compare the performances among electrokinetic process alone and electrokinetic processes combined with surfactant addition and mainly with ultrasonication, in designed cylinders (with filtercloth separating central part and electrolyte parts) and in open pans. Combined electrokinetic and ultrasonic treatment did prove positive coupling effect compared to each single process alone, though the level of enhancement is not very significant. The assistance of ultrasound in electrokinetic remediation can help reduce POPs from clayey soil by improving the mobility of hydrophobic organic compounds and degrading these contaminants through pyrolysis and oxidation. Ultrasonication also sustains higher current and increases electroosmotic flow. Initial contaminant concentration is an essential input parameter that can affect the removal effectiveness.

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Acid sulfate (a.s.) soils constitute a major environmental issue. Severe ecological damage results from the considerable amounts of acidity and metals leached by these soils in the recipient watercourses. As even small hot spots may affect large areas of coastal waters, mapping represents a fundamental step in the management and mitigation of a.s. soil environmental risks (i.e. to target strategic areas). Traditional mapping in the field is time-consuming and therefore expensive. Additional more cost-effective techniques have, thus, to be developed in order to narrow down and define in detail the areas of interest. The primary aim of this thesis was to assess different spatial modeling techniques for a.s. soil mapping, and the characterization of soil properties relevant for a.s. soil environmental risk management, using all available data: soil and water samples, as well as datalayers (e.g. geological and geophysical). Different spatial modeling techniques were applied at catchment or regional scale. Two artificial neural networks were assessed on the Sirppujoki River catchment (c. 440 km2) located in southwestern Finland, while fuzzy logic was assessed on several areas along the Finnish coast. Quaternary geology, aerogeophysics and slope data (derived from a digital elevation model) were utilized as evidential datalayers. The methods also required the use of point datasets (i.e. soil profiles corresponding to known a.s. or non-a.s. soil occurrences) for training and/or validation within the modeling processes. Applying these methods, various maps were generated: probability maps for a.s. soil occurrence, as well as predictive maps for different soil properties (sulfur content, organic matter content and critical sulfide depth). The two assessed artificial neural networks (ANNs) demonstrated good classification abilities for a.s. soil probability mapping at catchment scale. Slightly better results were achieved using a Radial Basis Function (RBF) -based ANN than a Radial Basis Functional Link Net (RBFLN) method, narrowing down more accurately the most probable areas for a.s. soil occurrence and defining more properly the least probable areas. The RBF-based ANN also demonstrated promising results for the characterization of different soil properties in the most probable a.s. soil areas at catchment scale. Since a.s. soil areas constitute highly productive lands for agricultural purpose, the combination of a probability map with more specific soil property predictive maps offers a valuable toolset to more precisely target strategic areas for subsequent environmental risk management. Notably, the use of laser scanning (i.e. Light Detection And Ranging, LiDAR) data enabled a more precise definition of a.s. soil probability areas, as well as the soil property modeling classes for sulfur content and the critical sulfide depth. Given suitable training/validation points, ANNs can be trained to yield a more precise modeling of the occurrence of a.s. soils and their properties. By contrast, fuzzy logic represents a simple, fast and objective alternative to carry out preliminary surveys, at catchment or regional scale, in areas offering a limited amount of data. This method enables delimiting and prioritizing the most probable areas for a.s soil occurrence, which can be particularly useful in the field. Being easily transferable from area to area, fuzzy logic modeling can be carried out at regional scale. Mapping at this scale would be extremely time-consuming through manual assessment. The use of spatial modeling techniques enables the creation of valid and comparable maps, which represents an important development within the a.s. soil mapping process. The a.s. soil mapping was also assessed using water chemistry data for 24 different catchments along the Finnish coast (in all, covering c. 21,300 km2) which were mapped with different methods (i.e. conventional mapping, fuzzy logic and an artificial neural network). Two a.s. soil related indicators measured in the river water (sulfate content and sulfate/chloride ratio) were compared to the extent of the most probable areas for a.s. soils in the surveyed catchments. High sulfate contents and sulfate/chloride ratios measured in most of the rivers demonstrated the presence of a.s. soils in the corresponding catchments. The calculated extent of the most probable a.s. soil areas is supported by independent data on water chemistry, suggesting that the a.s. soil probability maps created with different methods are reliable and comparable.

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Tiivistelmä: TDR-mittausten kalibrointi viljeltyjen turvemaiden kosteuden mittaamiseen

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Selostus: Suomen happamien sulfaattimaiden kansainvälinen luokittelu

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Selostus: Haihtuvien orgaanisten yhdisteiden muodostuminen kuivikkeissa

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Tiivistelmä: Metsitettyjen turvepeltojen maan fysikaaliset ominaisuudet

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Selostus: Kasvien raskasmetallien otto ilmasta ja saastuneesta maasta

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