Impurities threshold values

The (+)-enantiomer, main constituent of cold-pressed citrus peel oils, has a remarkably low odor threshold value of lOppb in water (Buttery et al., 1969b). This figure has been corrected to 200ppb for the (7 )-(+)-isomer and 500 ppb for the (S)-(—)-isomer, the error being due to impurities, very important for these low values (Buttery, 1999). Ahmed et al. (1978) estimated a probable odor threshold of 60 ppb and flavor threshold of 210ppb, but these were measured on a sample 96.5% pure. 

The purity requirement imposed on synthetic aroma substances is very high. The purification steps usually used are not only needed to meet the stringent legal requirements (i. e. beyond any doubt safe and harmless to health), but also to remove undesirable contaminating aroma compounds. For example, menthol has a phenolic off-flavor note even in the presence of only 0.01% thymol as an impurity. This is not surprising since the odor threshold value of thymol is lower than that of 1 (—)-menthol by a factor of 450. 

For a commercial cell, containing 45 lb caibon, and rated at 700 cfm air at an operating efficiency of about 95%, the service life in hours (t) is calculated to be 4.35 x 10 S/MC. Constants of some important atmospheric odorants for use in this equation are given in Table 12-34. The table also gives calculated values for service life based on a concentration of impurity equal to the odor-threshold value. Additional odor-threshold concentration values are given by Wark and Warner (1976). Data obtained on the adsorption of contaminants from air streams in which they are present in low ppm concentrations indicate that generally reported retentivities represent maximum values (Stankovich, 1969). Appreciably lower capacities can be expected when contaminants are present in concentrations near the odor threshold. 

The percolation model, which can be applied to any disordered system, is used for an explanation of the charge transfer in semiconductors with various potential barriers [4, 14]. The percolation threshold is realized when the minimum molar concentration of the other phase is sufficient for the creation of an infinite impurity cluster. The classical percolation model deals with the percolation ways and is not concerned with the lifetime of the carriers. In real systems the lifetime defines the charge transfer distance and maximum value of the possible jumps. Dynamic percolation theory deals with such case. The nonlinear percolation model can be applied when the statistical disorder of the system leads to the dependence of the system s parameters on the electrical field strength. 

In a previous paper of the authors on metal-free and Zn-phthalocyanines45 an overestimated value for

photoelectron emission at photon energies below the sharp threshold, attributed to impurities. This was corrected in later work. 

Calcium carbonate is listed as a food additive and nut considered a toxic material. The exposure lo dusl is regulated and a Threshold Limit Value-Time-Weighted Average (TLV-TWA) of 10 mg/m1 is set. Both natural ground and precipitated calcium carbonates can contain low levels of impurities that are regulated. 

If compounds with very low odor thresholds and very small concentrations contribute to a material s odor their detection can be very challenging, especially when only applying routine emission measurements like GC—MS. Such compounds will easily be overlooked, for their detection GC—O can often be the only choice, but so far this method is seldom used in material analysis. Instead concentrations determined by emission measurements are compared with published odor thresholds to decide whether a compound might contribute to the odor or not. One problem is that published odor thresholds can differ quite a lot, even by several orders of magnitude (van Gemert, 2003). The value depends on the method and the panel but also on the purity of the compound used for threshold determination (if small impurities of a substance with a low odor threshold were present in a sample the odor threshold determined would have been too low ). Many factors influence odor threshold determination, therefore many published values are questionable and they are hard to rely on. Some authors (Knudsen et al., 1999 Wolkoff, 1999 Wolkoff et al., 2006) assume that many of the odor thresholds reported in the literature are actually much lower, because if they compare concentrations of compounds emitted and measured with odor thresholds published,... 

Additionally, the incident impurity ions in a fusion device will be multiply charged, e.g., a charge state of 4 can be assumed for Be, C, O, and even higher values for W ions. This will result in increased acceleration of the ions in the sheath potential such that the most probable energies for multiply charged ions in a divertor plasma with Te = 10 eV will be around 200 eV, i.e., well above the threshold energy. 

Among the rare earth elements, cerium is an exception. The impurity of CeV04 NPs prepared under high alkaline conditions was Ce02, rather than cerium hydroxides, because Ce(OH)3 was prone for dehydration and oxidation. Chen s)mthesized CeV04 NPs from NH4VO3 and Ce(N03)3 in hydrothermal reactions with different pH (ranging from 9 to 14). The pH value of 12 was shown to be the upper threshold for pure vanadate NPs (Chen 2006). 

Simple peak purity analysis is relatively accurate when the impurity is present at significant concentration levels but, as the level of impurity diminishes, its impact on the target analyte spectrum becomes subtler and may require more sophisticated techniques. For this, statistical software routines are available for automated spectral comparisons. In these cases, peak purity determination and analysis of spectral differences are achieved using vector analysis algorithms. The more similar the spectra are, the closer the value is to 0.0° the more spectrally different they are, the larger the value. All the spectral data points across the peak are analyzed the data are converted into vectors, compared, and graphically plotted so that the results can be visualized. These software routines provide both numerical results and graphical representations such as similarity and threshold curves. 

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