Exposure estimation calculations

Migration data submitted for exposure estimates. Calculated versus Experimental. Calculated amount using Mt = 2C< (Dp t/ir)0-5 and 1.55 g/cm2 food to package surface. 

When, as is often the case, dietary exposure estimates calculated with tolerances or MRLs exceed acceptable toxicity limits, revised dietary exposure estimates may be calculated using residues derived from field trials. For chronic dietary exposure, the mean field trial residue is used in the US, and the median residue (STMR - Supervised Trials Median Residue) is used in the EU. In addition, as shown m the NESTI calculation, the high residue from field trials can be substituted for the tolerance or MRL value. 

NESTI calculations were calculated using the procedures discussed in section 2.4.1 above. The results of these calculations are shown in Table 3. As seen in Table 3, all dietary exposure estimates calculated using the NESTI methodology, except for peppers. 

Assessments of risks associated with the use of chlorpyrifos insecticide products for workers have been made. The assessments are based on the results of field studies conducted in citrus groves, a Christmas tree farm, cauliflower and tomato fields, and greenhouses that utilized both passive dosimetry and biomonitoring techniques to determine exposure. The biomonitoring results likely provide the best estimate of absorbed dose of chlorpyrifos, and these have been compared to the acute and chronic no observed effect levels (NOELs) for chlorpyrifos. Standard margin-of-exposure (MOE) calculations using the geometric mean of the data are performed however, probability (Student s f-test) and distributional (Monte Carlo simulation) analyses are deemed to provide more realistic evaluations of exposure and risk to the exposed population. 

The internal dose of propoxur was measured by assessing the total amount of 2-isopropoxyphenol (IPP) excreted in the urine, collected over a period of 24 hr from the start of exposure, and described in detail in previous studies (Brouwer et al., 1993 Meuling et al., 1991). Volunteer kinetics studies revealed a one-to-one relationship of absorbed propoxur and excreted IPP on a mole basis. Based on the results by Machemer et al. (1982), a pulmonary retention of 40% was used to calculate the relative contribution of the respiratory exposure to the internal exposure. To estimate the contribution of the dermal exposure, the calculated respiratory portion was subtracted from the total amount of IPP excreted in urine. 

Another case of multimedia fate modeling may be exemplified by human inhalation exposure estimates for PCB spills. The spill size is estimated considering both spread and soil infiltration. Volatilization calculations were carried out to get transfer rates into the air compartment. Finally, plume calculations using local meteorological statistics produced ambient concentration patterns which can be subsequently folded together with population distributions to obtain exposures. 

A worktable that can be used to calculate a cumulative exposure estimate on a site-specific basis is provided in Table 2. To use the table, environmental levels for outdoor air, indoor air, food, water, soil, and dust are needed. In the absence of such data (as may be encountered during health assessment activities), default values can be used. In most situations, default values will be background levels unless data are available to indicate otherwise. Based on the U.S. Food and Drug Administration s (FDA s) Total Diet Study data, lead intake from food for infants and toddlers is about 5 pg/day (Bolger et al. 1991). In some cases, a missing value can be estimated from a known value. For example, EPA (1986) has suggested that indoor air can be considered 0.03 x the level of outdoor air. Suggested default values are listed in Table 3. 

For calculation of the waste life stage s contribution to the release of the substance at regional scale, a standard model of a European region with about 20 million inhabitants and defined parameters (e.g., size, volume of water, soil, sediments and biota, etc.) is used details are given in Chapter R.16 Environmental Exposure Estimation [21]. 

The Office of Toxic Substances has assembled a team of multi-disciplined scientists to review each of these PMNs and assess the potential risks to human health and the environment posed by commercial manufacture and sale. These assessments are based upon limited firm data on the specific chemical, comparison with structurally similar chemicals of known toxicity, plus estimates of exposure from calculations of the potential number of people involved in manufacturing and processing operations and in consumer use. Most PMNs contain elementary data on physical and chemical properties and obvious acute health effect such as skin... 

Conditions of intended use. The GRAS status is determined, in part, based on the intended conditions of use of the flavoring substance through the calculation of a possible average daily intake (PADI) and a per capita exposure estimate. 

Measurement of dietary exposure to pesticides has historically relied upon deterministic methods that assign finite values to both the pesticide residue level and the food consumption estimates to yield a point estimate of exposure. The calculations are relatively simple, but consideration needs to be given to the accuracy of the assumptions concerning residue level and food consumption. 

The EDI of phthalates in China, Germany, Taiwan, and US populations are shown in Table 7. The calculation was based on phthalate metabolite (primary and secondary) concentrations, the model of David [137] and the excretion fractions according to various authors [23,28,143,144]. DEHP median values are very close or clearly exceed the TDIs and RfD values (Table 4). The median values for the rest of PAEs are below levels determined to be safe for daily exposures estimated by the US (RfD), the EU and Japan (TDI) (Table 4). However, the upper percentiles of DBP and DEHP urinary metabolite concentrations suggested that for some people, these daily phthalate intakes might be substantially higher than previously assumed and exceed the RfD and TDIs. 

The POD is used as the starting point for subsequent extrapolations and analyses. For linear extrapolation, the POD is used to calculate a slope factor, and for nonlinear extrapolation the POD is used in the calculation of a Reference Dose (RfD) or Reference Concentration (RfC). In a risk characterization, the POD is part of the determination of an MOE, defined as the ratio of the POD over an exposure estimate (MOE = POD/Exposure). 

If a nonlinear dose-response function has been determined, it can be used with the expected exposure to estimate a risk. If an RfD or RfC is calculated, the hazard can be expressed as a Hazard Quotient (HQ), defined as the ratio of an exposure estimate over the RfD or RfC, i.e., HQ = Exposure/(RfD or RfC). 

Exposure should normally be understood as external exposure, which can be defined as the amount of substance ingested, the total amount in contact with the skin (which can be calculated from exposure estimates expressed as mg/cm or mg/cm ), or either the amount inhaled or the concentration of the substance in the atmosphere, as appropriate. In cases where a comparison needs to be made with systemic effects data (e.g., when inhalation or dermal toxicity values are lacking or when exposures due to more than one exposure route need to be combined) the total body burden has to be estimated. Since the assessment of the amount that is absorbed after ingestion, by inhalation or by the skin is usually done in the effects assessment (section on toxicokinetics), this calculation of the total body burden is often placed in the section on risk characterization. 

These are estimates of dietary exposure to inorganic contaminants for individuals who eat average amounts of food (i.e. mean consumers) and those who eat more than average (i.e. upper range (97.5th percentile) consumers) and are based on consumption data from the UK National Adult Dietary Survey (NADS).4 They are calculated using the mean upper bound concentrations of specific contaminants in each food group and the consumption data from the NADS. Consumer exposure estimates are less suitable for following trends in exposure than population estimates as they are based on consumption data from the NADS which was carried out only once in 1986 and 1987 and is not updated... 

Some aspects of degree of concern currently can be considered in a quantitative evaluation. For example, EPA considers human and animal data in the process of calculating the RfD, and these data are used as the critical effect when they indicate that developmental effects are the most sensitive endpoints. When a complete database is not available, a database UF is recommended to account for inadequate or missing data. The dose-response nature of the data is considered to an extent in the RfD process, especially when the BMD approach is used to model data and to estimate a low level of response however, there is no approach for including concerns about the slope of the dose-response curve. Because concerns about the slope of the dose-response curve are related to some extent to human exposure estimates, this issue must be considered in risk characterization. (If the MOE is small and the slope of the dose-response curve is very steep, there could be residual uncertainties that must be dealt with to account for the concern that even a small increase in exposure could result in a marked increase in response.) On the other hand, a very shallow slope could be a concern even with a large MOE, because definition of the true biological threshold will be more difficult and an additional factor might be needed to ensure that the RfD is below that threshold. 

The models and methods used for purposes of estimating potential residential exposure (and absorbed dose) continue to be refined and validated as new monitoring studies become available. The goal is to simulate actual exposure conditions as closely as possible. The following sections present an example of a simplistic screening-level exposure assessment calculation for a consumer product, followed by a discussion of how more refined, probability-based or uncertainty analysis methods can be used. Screening-level methods typically include conservative bias in the form of default assumptions that are used in the absence of directly relevant and robust exposure monitoring data and other information. These methods can be used to predict potential exposure. However, it... 

In tliis step, the exposure assessor calculates clicmical-specific exposures for each exposure pathway identified la step 2. As described in the last chapter, e.xposure estimates arc c.xprcsscd in terms of the mass of substance in contact with the body per unit body weight per unit lime (e.g., mg chemical per kg body weight per day, also e.xpressed as mg/kg-day). Tlicse exposure estimates are termed intakes (for tlie purposes of tliis tc.xt) and represent tlie normalized exposure rate. Several terms common in other EPA documents and tlie literature are equivalent or related to intake arc provided below. 

When calculating chronic dietary exposure, the deterministic models use point values for both food consumption and residue concentration, thereby yielding a point estimate of dietary exposure. In the US, the initial chronic dietary exposure estimate is the Theoretical Maximum Residue Contribution (TMRC) and is analogous to the Theoretical Maximum Daily Intake (TMDI) used to estimate chronic dietary exposure in the EU. Both the TMRC and the TMDI are relatively conservative estimates of dietary expostire. The TMRC is calculated as the product of the mean consumption value and the US pesticide tolerance [6]. In the EU, the TMDI is calculated as the product of the mean consumption value and the Maximum Residue Limit (MRL) [7]. The objective of both calculations is essentially identical to calculate an estimate of the central tendency of the dietary exposure. Both calculated values use the central tendency dietary exposure estimate as the estimate of chronic (long-term) dietary exposure and calculate it using mean consumption data and the maximum residue permitted on the commodity. 

Two assessments were conducted using the US procedures with the UK food consun tion database and the DEEM-UK m model, in which a total dietary exposure estimate is calculated for all four foods at the same time. When 100% of the crop was assumed to be treated (so that probabilistic sampling was fixim the residue distributions), the resulting exposure estimates resulted in unacceptable estimates of risk. When percent crop treated was included in the assessment, the probabilistic assessment resulted in acceptable risk levels for all four commodities at the same time. 

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