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Contaminant populations

To understand these processes and correlate residue profiles with specific toxic responses required congener-specific methods of analysis and complex statistical techniques (principal component analysis). Using these techniques, it was established that eggs of Forster s terns of two colonies differed significantly in PCB composition (Schwartz and Stalling 1991). Similar techniques were used to identify various PCB-contaminated populations of harbor seals (Phoca vitulina) in Denmark (Storr-Hansen and Spliid 1993). [Pg.1318]

County Towns Wells Contaminated Population Served... [Pg.508]

Breast fed infants represent a population with daily exposure to dioxins and related chemicals. This population may have an increased theoretical risk for PCDD and PCDF induced cancer and other dioxin induced illnesses. This is especially true for contaminated populations in the south of Vietnam. However, the theoretical risk is based on an extrapolation from animal models and varies considerably on the model chosen. We do not know whether there will actually be an increased cancer incidence at these levels of contamination. [Pg.172]

Practically, the method first requires an estimate of average numbers of microorganisms on items. The contaminant population is assumed to respond to radiation in the same way as the standard but arbitrary" distribution. [Pg.78]

The region between the two sets of coordinates is called the dose window" (Fig. 4). The response to radiation within the dose window is assumed to be exponential, and therefore a D q can be calculated. The dose required to achieve an SAL of 10 is then derived from the 10 dose plus as many calculated values as are required to achieve the target. The B2 method therefore recognizes that there may be two components to radiation sensitivities of a contaminant population a sensitive portion that is addressed through determination of the actual 10 - SAL dose and a more resistant tail" population than is accounted for by extrapolation. [Pg.80]

Some observations seem to indicate that this is probably true for red wines with normal pH levels (3.4-3.5), containing 2.0-2.5% free SO2 in active, molecular form (Volume 1, Section 8.3.1, Table 8.2). When pH reaches 3.8, there is only 1% active, molecular SO2 left, raising the concern that 30 mg/1 would be insufficient to eliminate contaminant populations. [Pg.253]

It has been stated [413] that in Clay Lake, which lies within this water system, the mercury concentration is about twenty times as great as that found in relatively uncontaminated waters in the area. D Itri and D Itri [414] have reported that where mercury is a fresh-water contaminant, populations (such as the 0jibway Indians of Ontario) which depend on fish or shellfish as a major food source, carry clinically dangerous levels of mercury in the blood. [Pg.195]

Unrestricted calculations often incorporate a spin annihilation step, which removes a large percentage of the spin contamination from the wave function. This helps minimize spin contamination but does not completely prevent it. The final value of (,S y is always the best check on the amount of spin contamination present. In the Gaussian program, the option iop(5/14=2) tells the program to use the annihilated wave function to produce the population analysis. [Pg.228]

Resistance to antimicrobial agents is of concern as it is well known that bacterial resistance to antibiotics can develop. Many bacteria already derive some nonspecific resistance to biocides through morphological features such as thek cell wall. Bacterial populations present as part of a biofilm have achieved additional resistance owkig to the more complex and thicker nature of the biofilm. A system contaminated with a biofilm population can requke several orders of magnitude more chlorine to achieve control than unassociated bacteria of the same species. A second type of resistance is attributed to chemical deactivation of the biocide. This deactivation resistance to the strong oxidising biocides probably will not occur (27). [Pg.97]

Figures 16-3 through 16-5 present the decision network for screening contaminant fate in air, surface water, ground water, and biota. Pathways must be further evaluated to determine the likelihood of population exposure. Figures 16-3 through 16-5 present the decision network for screening contaminant fate in air, surface water, ground water, and biota. Pathways must be further evaluated to determine the likelihood of population exposure.

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See also in sourсe #XX -- [ Pg.234 ]




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