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Bioconcentration partitioning models

Methylmercury partitions strongly into the lipid-rich tissues of fish hence, it becomes highly bioconcentrated. Assume the BCF for fish is 106 liters/kg (i.e., assume an equilibrium partitioning model is an acceptable approximation to the real world). What fraction of the methylmercury in a lake would actually be in fish tissue, if the lake had a volume of 106 m3 and contained a metric ton (1000 kg) of fish ... [Pg.189]

Noegrohati, S., Hammers, W.E. (1992) Regression models for octanol-water partition coefficients, and for bioconcentration in fish. Toxicol. Environ. Chem. 34, 155-173. [Pg.912]

Chiou chose glyceryl trioleate (triolein) as model lipid because of its similarity to triglycerides which are abundant in organisms [109], Triolein is also a bulk lipid and the good correlation with the bioconcentration factor is restricted to neutral compounds of moderate hydrophobicity. No attempts were made to measure partitioning of ionogenic compounds with the glyceryl trioleate-water partition system. [Pg.218]

The dominant transport process from water is volatilization. Based on mathematical models developed by the EPA, the half-life for M-hexane in bodies of water with any degree of turbulent mixing (e.g., rivers) would be less than 3 hours. For standing bodies of water (e.g., small ponds), a half-life no longer than one week (6.8 days) is estimated (ASTER 1995 EPA 1987a). Based on the log octanol/water partition coefficient (i.e., log[Kow]) and the estimated log sorption coefficient (i.e., log[Koc]) (see Table 3-2), ii-hexane is not expected to become concentrated in biota (Swann et al. 1983). A calculated bioconcentration factor (BCF) of 453 for a fathead minnow (ASTER 1995) further suggests a low potential for -hcxanc to bioconcentrate or bioaccumulate in trophic food chains. [Pg.191]

The ability to predict the behavior of a chemical substance in a biological or environmental system largely depends on knowledge of the physical-chemical properties and reactivity of that compound or closely related compounds. Chemical properties frequently used in environmental assessment include melting/boiling temperature, vapor pressure, various partition coefficients, water solubility, Henry s Law constant, sorption coefficient, bioconcentration factor, and diffusion properties. Reactivities by processes such as biodegradation, hydrolysis, photolysis, and oxidation/reduction are also critical determinants of environmental fate and such information may be needed for modeling. Unfortunately, measured values often are not available and, even if they are, the reported values may be inconsistent or of doubtful validity. In this situation it may be appropriate or even essential to use estimation methods. [Pg.5]

Evidence for the validity of the hydrophobicity model of bioconcentration is provided by correlations of it with the octanol-water partition coefficient, Km, using n-octanol as a surrogate for fish lipid tissue. The measurement of Kow consists of determining the concentration of a hydrophobic contaminant in water-immiscible n-oclanol relative to water with which it is in equilibrium. Typical Kow values range from 10 to 107, corresponding to BCF values of 1 to 106. Such Kow/BCF correlations have proven to be reasonably accurate when narrowly defined for a specified class of compounds, most commonly poorly metabolized organohalides. Major inconsistencies appear when attempts are made to extrapolate from one class of contaminants to another. [Pg.123]

Although there is a strong negative correlation between partition coefficient and aqueous solubility (Hansch et al., 1968 Chiou et al., 1977), and a strong positive correlation between % and molecular volume (Dearden et al., 1988), the use of the partial least squares (PLS) method in this study allows the simultaneous use of intercorrelated descriptors. Nevertheless, the use of four descriptors to model the bioconcentration factor of only 11 compounds contravenes the Topliss and Costello (1972) rule, and renders the QSAR of dubious validity. [Pg.348]

Dimitrov, S.D., Mekenyan, O.G., and Walker, J.D., Non-linear modelling of bioconcentration using partition coefficients for narcotic chemicals, SAR QSAR Environ. Res., 13, 177-184, 2002. [Pg.356]

The availability of reliable measurements or estimates of water solubility, octanol-water partition coefficient, bioconcentration factor, rate constants and the like allows one to make qualitative judgements or, through the use of mathematical simulation models such as EPA s EXAMS (19), quantitative calculations of environmental distribution and persistence. In the qualitative use, Swann and coworkers (20) classified chemical mobility in soil based upon reversed-phase HPLC retention data which in turn is related to S. The approximate water solubility equivalents in this first-estimate classification, with chemical examples, are in Table II. This classification holds for chemicals whose primary adsorption in soil is to organic matter, and excludes those chemicals (such as paraquat) which bind ionically to the soil mineral fraction. A recent tabulation of pesticides found in groundwater had 11 entries, 8 of which represented compounds with water solubilities in excess of 200 ppm with the remaining three falling in the range of 3.5 to 52 ppm (21). [Pg.96]

The concept of bioconcentration is derived from that of distribution coefficients in physical chemistry in these, the equilibrium concentrations of a compound distributed between two phases are measured, for example, between water and a water-immiscible solvent such as hexane. If partitioning were a passive reaction, direct physicochemical measurements of the partition between an aquatic phase and a suitable model for the biological membrane would be possible. It would therefore be attractive to measure distribution coefficients in a chemically defined system and to seek a correlation between the values found and those obtained by direct measurements in biota. [Pg.138]

The importance of lipids in bioconcentration is emphasized several times in this chapter, and various devices have been explored to take this into account. Experiments using liposomes prepared with L-a-dipalmitoyl and L-a-dio-leylphosphatidylcholine, and membranes prepared from Rhodobacter sphaeroides were therefore studied in an attempt to produce more realistic models of the lipid phase in partition experiments (Escher and Schwartzen-bach 1996). The system was evaluated using a number of phenols of varying pKa and log Kow values, and it was shown that both systems provided good models for all species of phenolic compounds. An extremely important observation that has wide implications for ecotoxicology emerged not only the neutral phenols partitioned into the liposomes but also the anionic species. [Pg.140]

Various predictive models have been proposed to estimate BCFs for organic compounds based on their hydrophobicity as represented by their n-octanol/water partition coefficient (Kow) [15], Explosive compounds are weakly hydrophobic (low Kow values) and therefore BCFs predicted using these models should be low [3,6,17]. The equation derived by Meylan et al. [15] for nonionic compounds in the log Kow range of 1 to 7 (log BCF = 0.86 log Kow - 0.39) was used to calculate predicted BCFs for explosives and related compounds (Table 6.2) for empirically derived BCF values reported in Table 6.1. Comparison of predicted and empirically derived BCFs revealed that most explosives and related compounds bioconcentrate in aquatic... [Pg.138]

Indeed, OCPs, once released into the environment, are distributed into various environmental compartments (e.g., water, soil, and biota) as a result of complex physical, chemical, and biological processes. In order to perform appropriate exposure and risk assessment analyses, multimedia models of pollutant partitioning in the environment have been developed. Properties which are at the base of such a partitioning are water solubility (WS), octanol-water partition coefficient (Ko ), soil adsorption (K ), and bioconcentration factors (BCFs) in aquatic organisms, following these four equilibriums ... [Pg.804]


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See also in sourсe #XX -- [ Pg.157 ]

See also in sourсe #XX -- [ Pg.177 ]




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