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7 Models, Methods, and Data
Pages 106-143

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From page 106...
... The degree of confidence that one can place in a risk assessment depends on the reliability of the models chosen and their input parameters (i.e., variables) and on how well the boundaries of uncertainty have been quantified for the input parameters, for the models as a whole, and for the entire risk-assessment process.
From page 107...
... EMISSION CHARACTERIZATION As described in Chapter 3, emissions are characterized on the basis of emission factors, material balance, engineering calculations, established Environmental Protection Agency (EPA) protocols, and measurement.
From page 108...
... for fugitive emissions from a valve. The screening value is determined by measuring the hydrocarbons em~tted by a piece of equipment (in this case, a valve in gas service)
From page 109...
... Similar results were obtained from other possible emission points. The facilities in this SOCMI study could reduce the estimate of their emissions by 29-99% by determining plant-specific emission factors, indicating the difficulties in using industry-wide average to represent specific plant behavior.
From page 110...
... should be considered an indicator of the accuracy and precision of a given factor used to estimate emissions from a large number of sources." The uncertainty in the estimates is such that EPA is not comfortable with the A-E system and is developing a new qualitative system to indicate uncertainty. EPA is attempting to generate estimation factors for hazardous air pollutants industry by industry, but it is still hesitant to ascribe any sort of uncertainty to emission factors.
From page 111...
... There have been efforts to increase the scientific justification of estimates of emissions from storage tanks: the American Petroleum Institute has developed data that have been used for developing the estimation method shown in the multiplicative form described above. The question then arises as to how to approach emission estimates in exposure assessments and risk assessments.
From page 112...
... It is focusing on adding data, rather than evaluating its basic approach the use of a descriptive model, instead of a model based on processes, for emission estimation. It appears from the examples given above that the uncertainties in emissions can dominate an exposure assessment and that a concerted effort to improve emission estimation could serve to substantially reduce the uncertainty in many risk estimates.
From page 113...
... Even where sampling is used, a large background of technique and experience allows complex estimation and other kinds of modeling to proceed without the large uncertainties inherent in, for example, extrapolation from high to low doses of toxic agents or from rodents to humans. Population data are almost always affected to some degree by nonsampling error (bias)
From page 114...
... Air-Quality Model Evaluation Air-quality models are powerful tools for relating pollutant emissions to ambient air quality. Most air-quality models used in assessing exposure to toxic air pollutants have been extensively evaluated with specific data sets, and their underlying mathematical formulations have been critically reviewed.
From page 115...
... Model evaluation can also add insight as to whether a tool is "conservative" or the opposite, and it can provide a quantitative estimate of uncertainty. Of particular concern are the more demanding applications of models, such as in areas of complex terrain (e.g., hills, valleys, mountains, and over water)
From page 116...
... · The variation of peak concentration values with atmospheric stability and distance predicted by the Gaussian models did not match the pattern of observed peak values. · One of the first-order closure models performed better than the Gaussian models in estimating peak concentration as a function of meteorological characteristics, but its predictive capacity was poorer than desirable for detailed risk assessments, and it systematically overpredicted the distance to the maximal concentrations.
From page 117...
... Thus, there has been some effort to validate the exposure models developed for research purposes. There have been no systematic attempts, however, to validate either of the exposure models used for regulatory purposes, the Human Exposure Model (HEM)
From page 118...
... in its exposure assessments. Exposure models, such as NEM and SHAPE, have been developed to account for personal activity.
From page 119...
... The predictive accuracy and uncertainty associated with the use of the HEM should be clearly stated with each exposure assessment. The underlying assumption that the calculated exposure estimate is a conservative one should be reaffirmed; if not, alternative models whose performance has been demonstrated to be superior should be used in exposure assessment.
From page 120...
... tobacco smoke in laboratory animals. Recent advances in the understanding of basic mechanisms of carcinogenesis, often very similar in laboratory animals and humans, lend credibility to a relationship between animal carcinogenesis and human carcinogenesis, particularly when mutagenicity is involved (OSTP, 1985; Barbacid, 1986; Bishop, 1987~; in other cases, advances in the understanding of species-specific mechanisms of carcinogenesis do not support a relationship between humans and specific laboratory animals studied to date (Ellwein and Cohen, 1992~.
From page 121...
... . Studies of the genetic, biochemical, hormonal, and other factors that determine development of such tumors might improve the validity of human risk assessments based on animal studies, and should be pursued more vigorously.
From page 122...
... As currently estimated by EPA, potency is a statistical upper bound on the slope of the linear portion of a dose-response curve at low doses as calculated with a mathematical dose-response model. The unit cancer risk is based on potency and is an upper-bound estimate of the probability of cancer development due to continuous lifetime exposure to one unit of carcinogen.
From page 123...
... A statistical upper bound on the slope of the low-dose linear portion of the curve is considered to represent an upper bound on a chemical's carcinogenic potency. The multistage model is based on a theory of carcinogenic mechanism proposed in the early 1950s by Armitage and Doll.
From page 124...
... The models would then depict more accurately the dose-response relationship at the low doses that are of concern to regulators, but are too low for toxic effects to be directly observed in whole animal studies or, often, any feasible human studies. The challenge can be illustrated by examining the simplified mechanistic assumptions that are included in the multistage model used by EPA in light of new understanding of mechanisms, which is not included in that model.
From page 125...
... Thus, use of a two-stage pharmacodynamic model might predict low-dose risks that are lower or higher than those predicted by the linearized multistage model. Successful use of biologically based models in the risk assessment process will require a greater variety and amount of information on and understanding of carcinogenic mechanisms than is typically available for most chemicals.
From page 126...
... The EPA classification scheme is intended to provide information on hazard not to provide information about potential human risk; the latter cannot be assessed without the additional evaluation of dose-response and exposure information. The assignment of evidence to a class is intended by EPA only to suggest how convinced we should be that a substance poses a carcinogenic hazard to people.
From page 127...
... Although EPA includes a strength-of-evidence classification with each risk characterization, there is no clear indication of whether and how the classification influences ultimate agency decision-making. Evaluation of EPA Practice Does EPA's approach accurately portray the state of knowledge regarding human carcinogenic hazard?
From page 128...
... Moreover, it is impossible to capture in any simple categorization scheme the completeness and complexity of the information that supports scientific judgments about the nature of a human carcinogenic hazard and the conditions under which it can exist. The quality, nature, and extent of such information vary greatly among carcinogens, and it is not an exaggeration to state that every substance is unique with respect to the scientific evidence bearing on its hazards.
From page 129...
... As already noted, however, the committee believes that the current EPA categorization scheme is inadequate. Substantial improvements could be made if the scheme incorporated not only "strength-of-evidence" information, but also some of the information we have called for in the narrative description.
From page 130...
... · Evidence of carcinogenicity in either human or animal studies (strength of evidence varies; see Step 2) · Scientific information available to show that there are limitations in the conditions under which carcinogenicity might be expressed, owing to questions about the relevance to humans of the animal models or results or relevance of the conditions of exposure (route, dose, timing, duration, etc.)
From page 131...
... Although the committee recommends that any categorization scheme adopted by EPA include the elements associated with the above example, it also recognizes that there might be other ways to capture and express the same information. Some members suggested, for example, that substances listed as carcinogens simply be accompanied by a set of codes that specify both the strength of supporting evidence and the conditions and limitations, if any, that might pertain to the interpretation of that evidence (e.g., an asterisk next to a chemical might mean "assumed to be carcinogenic in humans only when inhaled"~.
From page 132...
... Evaluation of EPA Practice The methodology now used by EPA to regulate human exposure to noncarcinogens is in a state of flux. That used by EPA in the past was not sufficiently rigorous.
From page 133...
... As a consequence, the use of pharmacokinetic models to provide inputs to dose-response models reduces the uncertainty associated with the dose parameter and can result in more accurate estimates of potential cancer risks in humans. The relationship between administered and delivered doses often differs among individuals: because of such differences, some people might be acutely sensitive and others insensitive to the same administered dose.
From page 134...
... Use of a particular pharmacokinetic model for methylene chloride in cancer risk assessment reduces human risk estimates for exposure to methylene chloride in drinking water by a factor of 50-210, compared with estimates derived by conventional linear extrapolation and body surface-area conversions (Andersen et al., 1987~. Other analyses show different results (Portier and Kaplan, 1989~.
From page 135...
... Using EPA's pharmacokinetic model for tetrachloroethylene and cancer bioassay data in mice, they found that human cancer risk estimates varied by a factor of about 10,000, depending on the dose surrogate used. Interestingly, the estimates bracketed that obtained in the absence of any pharrnacokinetic transformation of dose as shown in Table 7-2.
From page 136...
... Accurate prediction of delivered and biologically active doses requires comprehensive, physiologically based computer models of those linked processes. Because the science of pharmacokinetics aims to replace general assumptions with a more refined model based on the specific relationship between administered and delivered or biologically active doses, its use in risk assessment will help to reduce the uncertainties in the process and the related bias in risk estimation.
From page 137...
... FINDINGS AND RECOMMENDATIONS The following is a compilation of findings and recommendations related to evaluation of methods, data, and models for risk assessment. Predictive Accuracy and Uncertainty of Models Various methods and models are available to EPA and other organizations for conducting emission characterization, exposure assessment, and toxicity assessments.
From page 138...
... Uncertainry EPA does not adequately evaluate the uncertainty in the emission estimates used in risk assessments. · Because of the wide variety of processes and differing maintenance of those sources, EPA should develop guidelines for the estimation and reporting of uncertainty in emission estimates; these guidelines may depend on the level of risk assessment.
From page 139...
... Population Data EPA has not previously used population activity, population mobility, and demographics in modeling exposure to hazardous air pollutants and has not adequately evaluated the effects of assuming that the population of a census enumeration district is all at the location of the district' s population center. · EPA should use population-activity models in exposure assessments when there is reason to believe that the exposure estimate might be inaccurate (e.g., as indicated by monitoring data)
From page 140...
... The HEM construct will not provide accurate estimates of exposure in specific locations and for specific sources and contaminants where conditions do not match the simplified exposure and dispersion-model assumptions inherent in the standard HEM components. · EPA should provide a statement on the predictive accuracy and uncertainty associated with the use of the HEM in each exposure assessment.
From page 141...
... EPA and NIP are encouraged to explore the use of alternative species to test the hypothesis that results obtained in mice and rats are relevant to human carcinogenesis, the use of younger animals when unique sensitivity might exist for specific chemicals, and the age-dependent effects of exposure. EPA typically extrapolates data from laboratory animals to humans by assuming that the delivered dose is proportional to the administered dose, as a default option.
From page 142...
... Classification of Evidence of Carcinogenicity EPA's narrative descriptions of the evidence of carcinogenic hazards are appropriate, but a simple classification scheme is also needed for decision-making purposes. The current EPA classification scheme does not capture information regarding the relevance to humans of animal data, any limitations regarding the applicability of observations, or any limitations regarding the range of carcinogenicity outside the range of observation.
From page 143...
... However, uncertainty about the potency estimate should be described as recommended in Chapter 9. Although EPA routinely cites available human evidence, it does not always rigorously compare the quantitative risk-assessment model based on rodent data with available information on molecular mechanisms of carcinogenesis or with available human evidence from epidemiological studies.


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