954 resultados para Coal combustion


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An investigation of the potential environmental and health impacts in the immediate aftermath of one of the largest coal ash spills in U.S. history at the Tennessee Valley Authority (TVA) Kingston coal-burning power plant has revealed three major findings. First the surface release of coal ash with high levels of toxic elements (As = 75 mg/kg; Hg = 150 microg/kg) and radioactivity (226Ra + 228Ra = 8 pCi/g) to the environment has the potential to generate resuspended ambient fine particles (< 10 microm) containing these toxics into the atmosphere that may pose a health risk to local communities. Second, leaching of contaminants from the coal ash caused contamination of surface waters in areas of restricted water exchange, but only trace levels were found in the downstream Emory and Clinch Rivers due to river dilution. Third, the accumulation of Hg- and As-rich coal ash in river sediments has the potential to have an impact on the ecological system in the downstream rivers by fish poisoning and methylmercury formation in anaerobic river sediments.

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Selenium (Se) is a micronutrient necessary for the function of a variety of important enzymes; Se also exhibits a narrow range in concentrations between essentiality and toxicity. Oviparous vertebrates such as birds and fish are especially sensitive to Se toxicity, which causes reproductive impairment and defects in embryo development. Selenium occurs naturally in the Earth's crust, but it can be mobilized by a variety of anthropogenic activities, including agricultural practices, coal burning, and mining.

Mountaintop removal/valley fill (MTR/VF) coal mining is a form of surface mining found throughout central Appalachia in the United States that involves blasting off the tops of mountains to access underlying coal seams. Spoil rock from the mountain is placed into adjacent valleys, forming valley fills, which bury stream headwaters and negatively impact surface water quality. This research focused on the biological impacts of Se leached from MTR/VF coal mining operations located around the Mud River, West Virginia.

In order to assess the status of Se in a lotic (flowing) system such as the Mud River, surface water, insects, and fish samples including creek chub (Semotilus atromaculatus) and green sunfish (Lepomis cyanellus) were collected from a mining impacted site as well as from a reference site not impacted by mining. Analysis of samples from the mined site showed increased conductivity and Se in the surface waters compared to the reference site in addition to increased concentrations of Se in insects and fish. Histological analysis of mined site fish gills showed a lack of normal parasites, suggesting parasite populations may be disrupted due to poor water quality. X-ray absorption near edge spectroscopy techniques were used to determine the speciation of Se in insect and creek chub samples. Insects contained approximately 40-50% inorganic Se (selenate and selenite) and 50-60% organic Se (Se-methionine and Se-cystine) while fish tissues contained lower proportions of inorganic Se than insects, instead having higher proportions of organic Se in the forms of methyl-Se-cysteine, Se-cystine, and Se-methionine.

Otoliths, calcified inner ear structures, were also collected from Mud River creek chubs and green sunfish and analyzed for Se content using laser ablation inductively couple mass spectrometry (LA-ICP-MS). Significant differences were found between the two species of fish, based on the concentrations of otolith Se. Green sunfish otoliths from all sites contained background or low concentrations of otolith Se (< 1 µg/g) that were not significantly different between mined and unmined sites. In contrast creek chub otoliths from the historically mined site contained much higher (≥ 5 µg/g, up to approximately 68 µg/g) concentrations of Se than for the same species in the unmined site or for the green sunfish. Otolith Se concentrations were related to muscle Se concentrations for creek chubs (R2 = 0.54, p = 0.0002 for the last 20% of the otolith Se versus muscle Se) while no relationship was observed for green sunfish.

Additional experiments using biofilms grown in the Mud River showed increased Se in mined site biofilms compared to the reference site. When we fed fathead minnows (Pimephales promelas) on these biofilms in the laboratory they accumulated higher concentrations of Se in liver and ovary tissues compared to fathead minnows fed on reference site biofilms. No differences in Se accumulation were found in muscle from either treatment group. Biofilms were also centrifuged and separated into filamentous green algae and the remaining diatom fraction. The majority of Se was found in the diatom fraction with only about 1/3rd of total biofilm Se concentration present in the filamentous green algae fraction

Finally, zebrafish (Danio rerio) embryos were exposed to aqueous Se in the form of selenate, selenite, and L-selenomethionine in an attempt to determine if oxidative stress plays a role in selenium embryo toxicity. Selenate and selenite exposure did not induce embryo deformities (lordosis and craniofacial malformation). L-selenomethionine, however, induced significantly higher deformity rates at 100 µg/L compared to controls. Antioxidant rescue of L-selenomethionime induced deformities was attempted in embryos using N-acetylcysteine (NAC). Pretreatment with NAC significantly reduced deformities in the zebrafish embryos secondarily treated with L-selenomethionine, suggesting that oxidative stress may play a role in Se toxicity. Selenite exposure also induced a 6.6-fold increase in glutathione-S-transferase pi class 2 gene expression, which is involved in xenobiotic transformation. No changes in gene expression were observed for selenate or L-selenomethionine-exposed embryos.

The findings in this dissertation contribute to the understanding of how Se bioaccumulates in a lotic system and is transferred through a simulated foodweb in addition to further exploring oxidative stress as a potential mechanism for Se-induced embryo toxicity. Future studies should continue to pursue the role of oxidative stress and other mechanisms in Se toxicity and the biotransformation of Se in aquatic ecosystems.

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In this paper, we present some early work concerned with the development of a simple solid fuel combustion model incorporated within a Computational Fluid Dynamics (CFD) framework. The model is intended for use in engineering applications of fire field modeling and represents an extension of this technique to situations involving the combustion of solid cellulosic fuels. A simple solid fuel combustion model consisting of a thermal pyrolysis model, a six flux radiation model and an eddy-dissipation model for gaseous combustion have been developed and implemented within the CFD code CFDS-FLOW3D. The model is briefly described and demonstrated through two applications involving fire spread in a compartment with a plywood lined ceiling. The two scenarios considered involve a fire in an open and closed compartment. The model is shown to be able to qualitatively predict behaviors similar to "flashover"—in the case of the open room—and "backdraft"— in the case of the initially closed room.

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An integrated fire spread model is presented in this study including several sub-models representing different phenomena of gaseous and solid combustion. The integrated model comprises of the following sub-models: a gaseous combustion model, a thermal radiation model that includes the effects of soot, and a pyrolysis model for charring combustible solids. The interaction of the gaseous and solid phases are linked together through the boundary conditions of the governing equations for the flow domain and the solid region respectively. The integrated model is used to simulate a fire spread experiment conducted in a half-scale test compartment. Good qualitative and reasonable quantitative agreement is achieved between the experiment and numerical predictions.

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The increasing volumes of municipal solid waste produced worldwide are encouraging the development of processes to reduce the environmental impact of this waste stream. Combustion technology can facilitate volume reduction of up to 90%, with the inorganic contaminants being captured in furnace bottom ash, and fly ash/APC residues. The disposal or reuse of these residues is however governed by the potential release of constituent contaminants into the environment. Accelerated carbonation has been shown to have a potential for improving the chemical stability and leaching behaviour of both bottom ash and fly ash/APC residues. However, the efficacy of carbonation depends on whether the method of gas application is direct or indirect. Also important are the mineralogy, chemistry and physical properties of the fresh ash, the carbonation reaction conditions such as temperature, contact time, CO2 partial pressure and relative humidity. This paper reviews the main issues pertaining to the application of accelerated carbonation to municipal waste combustion residues to elucidate the potential benefits on the stabilization of such residues and for reducing CO2 emissions. In particular, the modification of ash properties that occur upon carbonation and the CO2 sequestration potential possible under different conditions are discussed. Although accelerated carbonation is a developing technology, it could be introduced in new incinerator facilities as a "finishing step" for both ash treatment and reduction of CO2 emissions.

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Hollow, black reticulate ‘microfossils’ of unknown affinity found in Ordovician to late Cretaceous sediments from North America, Europe and Australia were given the name Linotolypa by Eisenack in 1962. In 1978, he recognised that they were pseudo-microfossils consisting of asphalt, and noted that their structure resembled that of soap bubbles formed in agitated suspensions. These objects are well known as a component of the particles caught from the air by pollen and spore traps at the present day. They are correctly termed ‘cenospheres’ and are formed from coal and possibly pitch and fuel oil by incomplete combustion. If their presence were to be confirmed in Palaeozoic sediments, this would provide important new evidence for the occurrence of fire in the geological record and of the history of levels of O2 in the atmosphere.

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This paper presents a statistical-based fault diagnosis scheme for application to internal combustion engines. The scheme relies on an identified model that describes the relationships between a set of recorded engine variables using principal component analysis (PCA). Since combustion cycles are complex in nature and produce nonlinear relationships between the recorded engine variables, the paper proposes the use of nonlinear PCA (NLPCA). The paper further justifies the use of NLPCA by comparing the model accuracy of the NLPCA model with that of a linear PCA model. A new nonlinear variable reconstruction algorithm and bivariate scatter plots are proposed for fault isolation, following the application of NLPCA. The proposed technique allows the diagnosis of different fault types under steady-state operating conditions. More precisely, nonlinear variable reconstruction can remove the fault signature from the recorded engine data, which allows the identification and isolation of the root cause of abnormal engine behaviour. The paper shows that this can lead to (i) an enhanced identification of potential root causes of abnormal events and (ii) the masking of faulty sensor readings. The effectiveness of the enhanced NLPCA based monitoring scheme is illustrated by its application to a sensor fault and a process fault. The sensor fault relates to a drift in the fuel flow reading, whilst the process fault relates to a partial blockage of the intercooler. These faults are introduced to a Volkswagen TDI 1.9 Litre diesel engine mounted on an experimental engine test bench facility.

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In this paper NOx emissions modelling for real-time operation and control of a 200 MWe coal-fired power generation plant is studied. Three model types are compared. For the first model the fundamentals governing the NOx formation mechanisms and a system identification technique are used to develop a grey-box model. Then a linear AutoRegressive model with eXogenous inputs (ARX) model and a non-linear ARX model (NARX) are built. Operation plant data is used for modelling and validation. Model cross-validation tests show that the developed grey-box model is able to consistently produce better overall long-term prediction performance than the other two models.