994 resultados para Trace Organic-chemicals
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Trace organic chemicals include a range of compounds which, due to a combination of their physico-chemical properties and toxicological implications, have been described as a serious threat to the biotic environment. A global treaty to regulate the manufacture and release of some of the most persistent trace chemicals has been promulgated and signed. The marine environment is an important sink for many trace chemicals, some of which accumulate in the marine food chain and in particular in marine mammals. With respect to the global distribution of trace organic chemicals, the levels of organohalogen compounds in the Southern Hemisphere are comparatively lower for a given environmental compartment and latitude compared to the Northern Hemisphere. A debate is currently evolving about the toxicity of alternative halogen substitutions such as bromine instead of chlorine and also of mixed halogen substitution. Recently a series of potentially natural bioaccumulative and persistent organohalogen chemicals have been found in marine mammals and turtles at levels in excess of those of anthropogenic trace organochlorines including PCBs and DDE. Little is known about the sources, behaviour and effects of natural trace organic chemicals. This manuscript presents an overview on the occurrence of trace organic chemicals in different compartments of the aquatic environment. Important knowledge gaps with regards to trace chemicals in the marine environment are presented. Crown Copyright (C) 2002 Published by Elsevier Science Ltd. All rights reserved.
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In life cycle impact assessment (LCIA) models, the sorption of the ionic fraction of dissociating organic chemicals is not adequately modeled because conventional non-polar partitioning models are applied. Therefore, high uncertainties are expected when modeling the mobility, as well as the bioavailability for uptake by exposed biota and degradation, of dissociating organic chemicals. Alternative regressions that account for the ionized fraction of a molecule to estimate fate parameters were applied to the USEtox model. The most sensitive model parameters in the estimation of ecotoxicological characterization factors (CFs) of micropollutants were evaluated by Monte Carlo analysis in both the default USEtox model and the alternative approach. Negligible differences of CFs values and 95% confidence limits between the two approaches were estimated for direct emissions to the freshwater compartment; however the default USEtox model overestimates CFs and the 95% confidence limits of basic compounds up to three orders and four orders of magnitude, respectively, relatively to the alternative approach for emissions to the agricultural soil compartment. For three emission scenarios, LCIA results show that the default USEtox model overestimates freshwater ecotoxicity impacts for the emission scenarios to agricultural soil by one order of magnitude, and larger confidence limits were estimated, relatively to the alternative approach.
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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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An expert elicitation exercise was undertaken to determine those components and processes that are most important for modeling plant uptake of organic chemicals. The state of our knowledge of these processes was also assessed. This semi-quantitative analysis allowed the construction of an idealized model with seven compartments; soil bulk, soil water, roots, stem, leaves, fruit, and air. Three main areas were identified further research: 1) the uptake of organic chemicals by fruit; 2) the internal transfer of organic chemicals between plant structures (e.g., stem and leaves); and 3) the transfer via the soil-air-plant pathway. Until new data becomes available to quantify these processes, it is proposed that an equilibrium partitioning approach is used between plant components other than fruit or that models consist of both an edible and inedible compartment.
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Plant uptake of organic chemicals is an important process when considering the risks associated with land contamination, the role of vegetation in the global cycling of persistent organic pollutants, and the potential for industrial discharges to contaminate the food chain. There have been some significant advances in our understanding of the processes of plant uptake of organic chemicals in recent years; most notably there is now a better understanding of the air to plant transfer pathway, which may be significant for a number of industrial chemicals. This review identifies the key processes involved in the plant uptake of organic chemicals including those for which there is currently little information, e.g., plant lipid content and plant metabolism. One of the principal findings is that although a number of predictive models exist using established relationships, these require further validation if they are to be considered sufficiently robust for the purposes of contaminated land risk assessment or for prediction of the global cycling of persistent organic pollutants. Finally, a number of processes are identified which should be the focus of future research
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The soil−air−plant pathway is potentially important in the vegetative accumulation of organic pollutants from contaminated soils. While a number of qualitative frameworks exist for the prediction of plant accumulation of organic chemicals by this pathway, there are few quantitative models that incorporate this pathway. The aim of the present study was to produce a model that included this pathway and could quantify its contribution to the total plant contamination for a range of organic pollutants. A new model was developed from three submodels for the processes controlling plant contamination via this pathway: aerial deposition, soil volatilization, and systemic translocation. Using the combined model, the soil−air−plant pathway was predicted to account for a significant proportion of the total shoot contamination for those compounds with log KOA > 9 and log KAW < −3. For those pollutants with log KOA < 9 and log KAW > −3 there was a higher deposition of pollutant via the soil−air−plant pathway than for those chemicals with log KOA > 9 and log KAW < −3, but this was an insignificant proportion of the total shoot contamination because of the higher mobility of these compounds via the soil−root−shoot pathway. The incorporation of the soil−air−plant pathway into the plant uptake model did not significantly improve the prediction of the contamination of vegetation from polluted soils when compared across a range of studies. This was a result of the high variability between the experimental studies where the bioconcentration factors varied by 2 orders of magnitude at an equivalent log KOA. One potential reason for this is the background air concentration of the pollutants under study. It was found background air concentrations would dominate those from soil volatilization in many situations unless there was a soil hot spot of contamination, i.e., >100 mg kg−1.
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Binding of hydrophobic chemicals to colloids such as proteins or lipids is difficult to measure using classical microdialysis methods due to low aqueous concentrations, adsorption to dialysis membranes and test vessels, and slow kinetics of equilibration. Here, we employed a three-phase partitioning system where silicone (polydimethylsiloxane, PDMS) serves as a third phase to determine partitioning between water and colloids and acts at the same time as a dosing device for hydrophobic chemicals. The applicability of this method was demonstrated with bovine serum albumin (BSA). Measured binding constants (K(BSAw)) for chlorpyrifos, methoxychlor, nonylphenol, and pyrene were in good agreement with an established quantitative structure-activity relationship (QSAR). A fifth compound, fluoxypyr-methyl-heptyl ester, was excluded from the analysis because of apparent abiotic degradation. The PDMS depletion method was then used to determine partition coefficients for test chemicals in rainbow trout (Oncorhynchus mykiss) liver S9 fractions (K(S9w)) and blood plasma (K(bloodw)). Measured K(S9w) and K(bloodw) values were consistent with predictions obtained using a mass-balance model that employs the octanol-water partition coefficient (K(ow)) as a surrogate for lipid partitioning and K(BSAw) to represent protein binding. For each compound, K(bloodw) was substantially greater than K(S9w), primarily because blood contains more lipid than liver S9 fractions (1.84% of wet weight vs 0.051%). Measured liver S9 and blood plasma binding parameters were subsequently implemented in an in vitro to in vivo extrapolation model to link the in vitro liver S9 metabolic degradation assay to in vivo metabolism in fish. Apparent volumes of distribution (V(d)) calculated from the experimental data were similar to literature estimates. However, the calculated binding ratios (f(u)) used to relate in vitro metabolic clearance to clearance by the intact liver were 10 to 100 times lower than values used in previous modeling efforts. Bioconcentration factors (BCF) predicted using the experimental binding data were substantially higher than the predicted values obtained in earlier studies and correlated poorly with measured BCF values in fish. One possible explanation for this finding is that chemicals bound to proteins can desorb rapidly and thus contribute to metabolic turnover of the chemicals. This hypothesis remains to be investigated in future studies, ideally with chemicals of higher hydrophobicity.
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The objective of this dissertation was to design and implement strategies for assessment of exposures to organic chemicals used in the production of a styrene-butadiene polymer at the Texas Plastics Company (TPC). Linear statistical retrospective exposure models, univariate and multivariate, were developed based on the validation of historical industrial hygiene monitoring data collected by industrial hygienists at TPC, and additional current industrial hygiene monitoring data collected for the purposes of this study. The current monitoring data served several purposes. First, it provided information on current exposure data, in the form of unbiased estimates of mean exposure to organic chemicals for each job title included. Second, it provided information on homogeneity of exposure within each job title, through the use of a carefully designed sampling scheme which addressed variability of exposure both between and within job titles. Third, it permitted the investigation of how well current exposure data can serve as an evaluation tool for retrospective exposure estimation. Finally, this dissertation investigated the simultaneous evaluation of exposure to several chemicals, as well as the use of values below detection limits in a multivariate linear statistical model of exposures. ^
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Mode of access: Internet.
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Includes bibliographical references and indexes.
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Vols. issued as its TC publications.
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Mode of access: Internet.
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"HWRIC RR-057."