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Transformation environmental fate models

In fact, physiologically based pharmacokinetic models are similar to environmental fate models. In both cases we divide a complicated system into simpler compartments, estimate the rate of transfer between the compartments, and estimate the rate of transformation within each compartment. The obvious difference is that environmental systems are inherently much more complex because they have more routes of entry, more compartments, more variables (each with a greater range of values), and a lack of control over these variables for systematic study. The discussion that follows is a general overview of the transport and transformation of toxicants in the environment in the context of developing qualitative and quantitative models of these processes. [Pg.480]

Environmental Fate Models for Transformation Products An Overview. . 124... [Pg.121]

J. Dressel, C. Beigel, Estimation of standardized transformation rates of a pesticide and its four soil metabolites from field dissipation studies for use in environmental fate modeling, Proc. BCPC Conference - Weeds 119-126 (2001). [Pg.79]

Simple models are used to Identify the dominant fate or transport path of a material near the terrestrial-atmospheric Interface. The models are based on partitioning and fugacity concepts as well as first-order transformation kinetics and second-order transport kinetics. Along with a consideration of the chemical and biological transformations, this approach determines if the material is likely to volatilize rapidly, leach downward, or move up and down in the soil profile in response to precipitation and evapotranspiration. This determination can be useful for preliminary risk assessments or for choosing the appropriate more complete terrestrial and atmospheric models for a study of environmental fate. The models are illustrated using a set of pesticides with widely different behavior patterns. [Pg.197]

The modified terrestrial-aquatic model ecosystem described here has been found to be a useful tool in studying the environmental fate of drugs and related residues present in animal excreta used as manure. The operation of the ecosystem is relatively simple and yet it allows one to study the complex metabolic transformations of a drug or related residues in its various components. Especially interesting is the study of the degradation of a compound in the soil in the presence of microorganisms found in the animal excreta. This information is important since it eventually determines whether a compound and/ or its metabolites will bioaccumulate in the various elements of the environment. [Pg.194]

The goals of this section are to introduce methods of modeling chemical movement within and between environment compartments, to define specific translocation and transformation processes, to provide a basic understanding of the association among chemical structure, physicochemical properties, and susceptibility to specific translocation and transformation processes, and to provide methods of accessing and estimating physicochemical properties and environmental fate of chemicals. [Pg.226]

We have developed a number of multi-media models based on our (Higinal idea, and validated their predictability for evaluating environmental fate and exposure [2-9]. In our models, it is assumed that the environment consists of phases which are composed of several homogenous compartments. Also, the models assume that rates of intraphase transfer processes are faster than those of interphase transfer, transport and transformation processes (local equilibrium). [Pg.91]

Environmental Fate. Zinc partitions to the air, water, and soil (Callahan et al. 1979 Guy and Chakrabarti 1976 Houba et al. 1983 Pita and Hyne 1975). Zinc occurs in the environment mainly in the +2 oxidation state (Lindsey 1979). Adsorption is the dominant fate of zinc, resulting in enrichment of zinc in suspended and bed sediments (Callahan et al. 1979). The mobility of zinc in soil has been characterized (Base and Sharp 1983 Bergkvist et al. 1989 EPA 1980d Hermann and Neumann-Mahikau 1985 Kalbasi et al. 1978 Saeed and Fox 1977 Tyler and McBride 1982). No estimate for the atmospheric lifetime of zinc is available. Development of pertinent data on the atmospheric processes important for zinc speciation in the atmosphere would be helpful. Development of this information would permit construction of a comprehensive model for the transport and interaction of zinc not only in air but in other media as well. Transformation in air and water can occur as a result of changes in chemical speciation (Anderson et al. 1988 Callahan et al. 1979 EPA 1980d Stokinger 1981). Data that describe the transformation processes for zinc in soil or the fate of zinc in soil are needed. A model of zinc flux from all environmental compartments would be useful for providing information on the overall environmental fate of zinc. [Pg.132]

It is often difficult to comprehend how a particular environmental chemical behaves in the environment given the multitude of information on its distribution, transport, and transformation characteristics. The various fate processes interact and compete with each other in complex and sometimes not very intuitive ways. Especially when a quantitative understanding of environmental fate is required, the available information is therefore often synthesized in conceptual and mathematical models. [Pg.259]

Environmental hazard model, transport, transformation, fate, accumulation, persistence, contaminants, cluster analysis, structure-activity relationships. [Pg.26]

Fate and exposure analyses. The multimedia transport and transformation model is a dynamic model that can be used to assess time-varying concentrations of contaminants that are placed in soil layers at a time-zero concentration or contaminants released continuously to air, soil, or water. This model is used for determining the distribution of a chemical in the environmental compartments. An overview of the partitioning among the liquid, solid and/or gas phases of individual compartments is presented in Fig. 7. The exposure model encompasses... [Pg.60]

There are many areas into which environmental organic chemistry and environmental engineering can advance as a result of developments in various analytical techniques. All of this information will provide a much clearer picture on the chemodynamics of organic compounds, their biodegradation residues, and transformation products. Information such as this is important for modeling the fate and transport of organic compounds in the environment. [Pg.89]

Chemical transport and transformation have been a part of environmental science and engineering for decades. Air pollutant plume dispersion modeling and surface water quality stream modeling are mature elements of EC, commonly termed chemical fate and... [Pg.892]

A well-documented example of this approach is a study of the fate of the pesticide, chlorpyrifos, in a pond in Missouri (87 reviewed by Branson, 75). The conceptual model includes rate constants for each of the transport and transformation processes affecting the final concentrations of chlorpyrifos in the water, the sediment, and the fish. The rate constant for evaporation from water is estimated from data on vapor pressure, solubility, and molecular weight (for techniques, see 33, 68, 71). The remaining rate constants for the pond model are derived from laboratory studies. When validated by sampling in a pond, the predicted and environmentally measured concentrations of chlorpyrifos showed close agreement (75). [Pg.375]

The activity measures in environmental sciences concern ecotoxicological effects as well as fate- and exposure-related parameters such as partitioning between the water, air and soil phases, or degradation/transformation. Because of the different nature of these endpoints, different techniques may be appropriate for the respective structure-activity analyses. Nevertheless, whichever sophisticated method is applied, it has to be stressed repeatedly that the basis of any QSAR modelling is the experimental data, and that their quality (i.e. variability) determines the reliability and soundness of the derived models. [Pg.11]


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