Extrapolation methods, lifetime

In the present discussion it is tacitly assumed that the thermal analysis technique identifies the proper life-determining reaction and that the detailed chemistry and physics of the various failure mechanisms is as assumed, in order to allow us to concentrate on the kinetics and the precision of the chosen extrapolation methods. The safest lifetime prediction is necessarily the one with the shortest extrapolation — in other words, the test made under conditions close to those the material experiences in service. 

The site-specific investigation confirms the hazards defined in the national building codes at the regional level. The investigation is carried out within a 20 km radius of the site. This radius may be smaller if the area is not populated and possible causes of events do not exist. Data record length and extrapolation methods are the same as for hazard category 1. The facility s lifetime is compatible with the projected population growth around the site. 

The following example is based on a risk assessment of di(2-ethylhexyl) phthalate (DEHP) performed by Arthur D. Little. The experimental dose-response data upon which the extrapolation is based are presented in Table II. DEHP was shown to produce a statistically significant increase in hepatocellular carcinoma when added to the diet of laboratory mice (14). Equivalent human doses were calculated using the methods described earlier, and the response was then extrapolated downward using each of the three models selected. The results of this extrapolation are shown in Table III for a range of human exposure levels from ten micrograms to one hundred milligrams per day. The risk is expressed as the number of excess lifetime cancers expected per million exposed population. 

Estimates of exposure levels posing minimal risk to humans (MRLs) have been made, where data were believed reliable, for the most sensitive noncancer end point for each exposure duration. MRLs include adjustments to reflect human variability and, where appropriate, the uncertainty of extrapolating from laboratory animal data to humans. Although methods have been established to derive these levels (Barnes et al. 1987 EPA 1989a), uncertainties are associated with the techniques. Furthermore, ATSDR acknowledges additional uncertainties inherent in the application of these procedures to derive less than lifetime MRLs. As an example, acute inhalation MRLs may not be protective for health effects that are delayed in development or are acquired following repeated acute insults, such as hypersensitivity reactions, asthma, or chronic bronchitis. As these kinds of health effects data become available and methods to assess levels of significant human exposure improve, these MRLs will be revised. 

In animal experiments exposures can be carefully controlled, and dose-response curves can be formally estimated. Extrapolating such information to the human situation is often done for regulatory purposes. There are several models for estimating a lifetime cancer risk in humans based on extrapolation from animal data. These models, however, are premised on empirically unverified assumptions that limit their usefulness for quantitative purposes. While quantitative cancer risk assessment is widely used, it is by no means universally accepted. Using different models, one can arrive at estimates of potential cancer incidence in humans that vary by several orders of magnitude for a given level of exposure. Such variations make it rather difficult to place confidence intervals around benefits estimations for regulatory purposes. Furthermore, low dose risk estimation methods have not been developed for chronic health effects other than cancer. The... 

There are many circumstances in which the only information we can develop on toxic hazards and dose-response relationships derives from experiments on laboratory animals. The example of the food additive, presented in the opening pages, is just one of many circumstances in which condition A involves animal toxicology data, and condition B involves a human population, almost always exposed at small fractions of the dose used in animals, and sometimes exposed for much larger fractions of their lifetime than the animals, and even by different routes. Extrapolations under these circumstances should cause individuals trained in the rigors of the scientific method to seek some form of psychological counsel, or, better yet, to return to the laboratory. 

Prior knowledge of the behaviour of a proposed intermediate under a particular set of reaction conditions is often available and facilitates experimental design. For example, species which are transient under one set of conditions (solvent, temperature) may be stable under others, and then observable by conventional methods. Similar considerations apply to structural variation, which may stabilise charge or unusual valence states. Systematic studies of the effects of variation of conditions, or of structural variation on reactivity, often permit useful extrapolation to behaviour of a proposed intermediate under the conditions in question. Importantly, if extrapolations of this kind indicate that a proposed intermediate would have a lifetime of less than 10 13 s under a particular set of reaction conditions, then that proposal must be re-evaluated. Either the mechanism involving the proposed intermediate is fundamentally flawed, or the bonding changes involved in its formation and destruction are actually concerted. 

S/S, S/L, and S/G interfaces of many types occur in most solar devices, often with several in close proximity. To extrapolate from short-term laboratory behavior to 30-year lifetimes requires an atomic-level mechanistic understanding of the degradation processes occurring at interfaces. The latter, in turn, require using state-of-the-art methods of microcharacterization that yield structural, chemical, or electronic information with a lateral spatial resolution approaching atomic dimensions (14). 

EPA has used cancer risk data from human epidemiological studies to derive risk factors associated with oral exposure to benzene. Oral dose levels associated with specific carcinogenic risks have been extrapolated the risk value of 2.7x 10"2 for lifetime inhalation exposure to 1 ppm was converted to a slope factor of 2.9/10"2 for oral exposure of 1 mg/kg/day, assuming identical levels of absorption of benzene following both routes of exposure. Using the method described by EPA (IRIS 1996), the drinking water levels associated with individual upper-bound estimates of 10"4, 10"5, 10"6, and 10"7 have been calculated to be lxlO 1, lxlO"2, lxlO"3, and lxlO"4 mg/L, respectively, which are equivalent to dose levels of 3x 10"3,... 

Two different approaches for lifetime prediction are presented. The underlying lifetime limiting processes have been identified in two cases. Mathematical expressions of chemical/physical relevance were used for the lifetime predictions for PE hot-water pipes and cables insulated with plasticized PVC. Accelerated testing, extrapolation and validation of the extrapolation by assessment of the remaining lifetime of objects aged during service conditions for 25 years were successfully applied to cables insulated with chlorosulfonated polyethylene. Polyolefin pipes exposed to chlorinated water showed a very complex deterioration scenario and it was only possible to find a method suitable for predicting the time for the depletion of the stabilizer system. 

Lifetime predictions of polymeric products can be performed in at least two principally different ways. The preferred method is to reveal the underlying chemical and physical changes of the material in the real-life situation. Expected lifetimes are typically 10-100 years, which imply the use of accelerated testing to reveal the kinetics of the deterioration processes. Furthermore, the kinetics has to be expressed in a convenient mathematical language of physical/chemical relevance to permit extrapolation to the real-life conditions. In some instances, even though the basic mechanisms are known, the data available are not sufficient to express the results in equations with reliably determined physical/chemical parameters. In such cases, a semi-empirical approach may be very useful. The other approach, which may be referred to as empirical, uses data obtained by accelerated testing typically at several elevated temperatures and establishes a temperatures trend of the shift factor. The extrapolation to service conditions is based on the actual parameters in the shift function (e.g. the Arrhenius equation) obtained from the accelerated test data. The validity of such extrapolation needs to be checked by independent measurements. One possible method is to test objects that have been in service for many years and to assess their remaining lifetime. 

Boltzmann constant. The effective path length of the collision cell is X, while T and p are the temperature and the pressure of the reactant gas, respectively. Pressure dependent cross section data were plotted and then extrapolated to zero pressure using the method of Armentrout and coworkers [44]. The reaction rate coefficients, which are dependent on the lifetime of the ion molecule complex, were calculated and converted to an expression for the phenomenological rate coefficient [44] by (14.2). 

The existing methods available for scientifically defensible risk characterization are not yet ideal since each step has an associated uncertainty resulting from data limitation and incomplete knowledge on exact mechanism of action of the toxic chemical on the human body. For noncancer end points, safety factors or uncertainty factors are applied since these effects are assumed to have a threshold below which no adverse effect is expected to be observed. US EPA has used the concept of a reference concentration (RfC) to estimate acceptable daily human exposure from HAPs. The RfC was adapted for inhalation studies based on a reference dose (RfD) method previously used for oral exposure assessment. The derivation of the RfC differs from that for the RfD in the use of dosimetric adjustment to extrapolate the exposure concentration for animals to a human equivalent concentration. Both are estimates, with uncertainty spaiming perhaps an order of magnitude, of a daily exposure to the human population, including sensitive subgroups, which would be without appreciable risk of deleterious effects over a lifetime. 

Many chemical risks such as those of chloroform in drinking water, are calculated, not measured - that is, they are based not only on scientific data, but also on various sets of assumptions and extrapolation models that, while scientifically plausible (they fall within the bounds of acceptable biological theory), have not been subjected to empirical study and verification. Indeed, the results of most risk assessments - whether expressed as an estimate of extra cancer risk or an ADI - are scientific hypotheses that are not generally testable with any practicable epidemiological method. There is, for example, no practical means to test whether chloroform residues in chlorinated drinking water increase lifetime cancer risk in humans by 8 in 1000000, as hypothesized above. The tools of epidemiology are enormously strained, indeed, when called upon to detect the relatively low risks associated with most environmental chemicals. Without such a test, these risks remain unverified. 

Suitable models have to be developed so as to extrapolate from the experimental results to nominal real-life conditions by calculating the age-acceleration factor that relates the lifetime under experimental stress to the in-use lifetime. As with reliability functions, various models that apply to the different age-acceleration methods are described in the literature [1, 9]... 

In addition to the graphic approach for toxicity data and the verification of uncertainty factors, other areas are under study such as route-to-route conversion, high-dose to low-dose extrapolation, approaches to assess the health risk from less-than-lifetime exposures, and refinement of risk assessment approaches for chemical mixtures. All of these areas represent progress in the methods used for risk assessment of single chemicals and chemical mixtures. With the new risk assessment guidelines currently being developed, the U.S. EPA can move forward to better and more consistent health risk assessments. 

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