Exposure concentration, calculation

The calculations that yield the occupational exposure concentration from the individual analytical values... 

Calculation of the occupational exposure concentration (OEC) depends on the type of OEL. For example, when the limit value has been set as an eight-hour time-weighted average, the cumulative exposure for an eight-hour work shift should be computed as follows ... 

In this step, the assessor qiuuitifies tlie magnitude, frequency and duration of exposure for each patliway identified in Step 2. Tliis step is most often conducted in two stages estimation of exposure concentrations and calculation of intakes. The later estimation is considered in Step 4. In tliis part of step 3. the exposure assessor determines the concentration of chemicals tliat will be contacted over the exposure period. E.xposure concentrations are estimated using monitoring data and/or chemical transport and environmental fate models. Modeling may be used to estimate future chemical concentrations in media tliat are currently contaminated or tliat may become contaminated, and current concentrations in media and/or at locations for which tliere are no monitoring data. The bulk of the material in tliis chapter is concerned witli tliis step. 

EUSES. In EUSES 2.0 steady-state exposure concentrations at the regional, continental, and global scales are calculated for all environmental compartments (air, water, soil, sediment, and air) using the multi-media fate model SimpleBox 3.0. 

For gases and vapors, exposure concentrations are traditionally expressed in parts per million (ppm). The calculation for the ppm of a gas or vapor in an air sample is based on Avogadro s Law, which states that Equal volumes contain equal numbers of molecules under the same temperature and pressure. In other words, under standard temperature and pressure (STP), one gram-molecular weight (mole) of any gas under a pressure of one atmosphere (equivalent to the height of 760 mm mercury) and a temperature of 273 K has the same number of molecules and occupies the same volume of 22.4 liters. However, under ambient conditions, the volume of 22.4 liters has to be corrected to a larger volume based on Charles Law, which states that at constant pressure the volume of gas varies directly with the absolute temperature. Thus, at a room temperature of 25° C, one mole of a gas occupies a volume of 24.5 liters. 

The principal application of PBPK models is in the prediction of the target tissue dose of the toxic parent chemical or its reactive metabolite. Use of the target tissue dose of the toxic moiety of a chemical in risk assessment calculations provides a better basis of relating to the observed toxic effects than the external or exposure concentration of the parent chemical. Because PBPK models facilitate the prediction of target tissue dose for various exposure scenarios, routes, doses, and species, they can help reduce the uncertainty associated with the conventional extrapolation approaches. Direct application of modeling includes... 

Environmental risk assessment of substances is nowadays based on an evaluation of exposure pathways and concentrations on the one hand and identification and selection of sensitive endpoints on the other. The concept is operationalised by comparing real or estimated (predicted) exposure concentrations (PEC) with calculated no-effect concentrations (NEC or PNEC, predicted NEC). The comparison can be made by calculating the quotient of exposure and no-effect concentration. If the quotient is less than one, then the substance poses no significant risk to the environment. If the quotient is greater than one, the substance may pose a risk, and further action is required, e.g. a more thorough analysis of probability and magnitude of effects will be carried out. 

Exposure Levels in Environmental Media. Several studies are available documenting bromomethane concentrations in ambient air (Brodzinsky and Singh 1983 Harsch and Rasmussen 1977), but data for bromomethane in water are rare. Bromomethane has been analyzed for, but rarely detected, in foods (Daft 1987, 1988, 1989). Human exposure levels of bromomethane by inhalation of urban air have been calculated (Singh et al. 1981b). However, these levels are based on monitoring data more than 10 years old. Since urban air concentrations of bromomethane may have decreased due to reduced emissions from automobiles, exposure levels calculated from past data should be taken as an upper limit, and new levels calculated from current monitoring data would be useful. 

It is also noted that there is overlap in the individual UFs and that the application of five UFs of ten for the chronic reference value (yielding a total UF of 100,000) is inappropriate. In fact, in cases where maximum uncertainty exists in all five areas, it is unlikely that the database is sufficient to derive a reference value. Uncertainty in four areas may also indicate that the database is insufficient to derive a reference value. In the case of the RfC, the maximum UF would be 3,000, whereas the maximum would be 10,000 for the RfD. This is because the derivation of RfCs and RfDs has evolved somewhat differently. The RfC methodology (US-EPA 1994) recommends dividing the interspecies UF in half, one-half (10° ) each for toxicokinetic and toxicodynamic considerations, and it includes a Dosimetric Adjustment Factor (D AF, represents a multiplicative factor used to adjust an observed exposure concentration in a particular laboratory species to an exposure concentration for humans that would be associated with the same delivered dose) to account for toxicokinetic differences in calculating the Human Equivalent Concentration (HEC), thus reducing the interspecies UF to 3 for toxicodynamic issues. RfDs, however, do not incorporate a DAF for deriving a Human Equivalent Dose (HED), and the interspecies UF of 10 is typically applied, see also Section 5.3.4. It is recommended to limit the total UF applied for any particular chemical to no more than 3000, for both RfDs and RfCs, and avoiding the derivation of a reference value that involves application of the full 10-fold UF in four or more areas of extrapolation. 

The likely range of the intersex indicator (ISI) for L. littorea was also calculated based on the dose-response relationship for L. littorea as published by Oehlmann (2002) and the spatial distribution of water concentrations. The range of possible ISI values from the 5 and 95 percentile of the exposure concentration distributions were calculated applying Formula 1. 

Figure 3 Correspondence between ecological risk expressed as the Potentially Affected Fraction of species (PAF) and the calculated ISI level corresponding to the 95th percentile exposure concentration in Dutch harbours.

To check the correspondence between the maximum ISI levels that can be expected in a harbour and the ecological risk, PAF values have been plotted against the calculated ISI value corresponding to the 95 percentile of the exposure concentration distribution (Figure 3). The 95 percentile was chosen because this value corresponds to the most polluted part of the harbour or water body corresponding to a maximum ISI value that might be encountered during... 

Risk assessments for anionic surfactants are obtained by comparing environmental exposure concentrations to effect levels (the quotient method). A protection factor that reflects the environmental safety of the material is calculated by dividing the exposure level by the effect concentration. If the protection factor is greater than 1, the material is deemed safe. Although this approach to assessing risk yields a numerical value that could be interpreted as the relative safety of a compound, comparisons of protection factors for different compounds should be avoided. The risk assessment for each material must be considered separately because of differences in chemical properties and differences in the database used to obtain the protection factor. In addition, the degree of uncertainty in the exposure and effect... 

If, during the bioconcentration test, the chemical concentrations in the organism and water reach steady-state, the bioconcentration factor can be calculated from the steady-state concentrations in the organism (CB) and the water (Cw) as CB/ Cw. However, when steady-state is not achieved during the test because the test was conducted for an insufficiently long period of time or because exposure concentrations were variable during the test, the derivation of the BCF and the rate constant for chemical uptake and elimination require a more specific method of data analysis. 

SimpleBox was created as a research tool in environmental risk assessment. Simple-Box (Brandes et al. 1996) is implemented in the regulatory European Union System for the Evaluation of Substances (EUSES) models (Vermeire et al. 1997) that are used for risk assessment of new and existing chemicals. Dedicated SimpleBox 1.0 applications have been used for integrating environmental quality criteria for air, water, and soil in The Netherlands. Spreadsheet versions of SimpleBox 2.0 are used for multi-media chemical fate modeling by scientists at universities and research institutes in various countries. SimpleBox models exposure concentrations in the environmental media. In addition to exposure concentrations, SimpleBox provides output at the level of toxic pressure on ecosystems by calculating potentially affected fractions (PAF) on the basis of species sensitivity distribution (SSD) calculus (see Chapter 4). 

Besides meeting its assumptions, other problems in the application of SSD in risk assessment to extrapolate from the population level to the community level also exist. First, when use is made of databases (such as ECOTOX USEPA 2001) from which it is difficult to check the validity of the data, one does not know what is modeled. In practice, a combination of differences between laboratories, between endpoints, between test durations, between test conditions, between genotypes, between phenotypes, and eventually between species is modeled. Another issue is the ambiguous integration of SSD with exposure distribution to calculate risk (Verdonck et al. 2003). They showed that, in order to be able to set threshold levels using probabilistic risk assessment and interpret the risk associated with a given exposure concentration distribution and SSD, the spatial and temporal interpretations of the exposure concentration distribution must be known. 

RDDR is a multiplicative factor used to adjust an observed inhalation particulate exposure concentration of an animal to the predicted inhalation particulate exposure concentration for a human based on a MMAD of 0.28 pm and a geometric standard deviation of 1.63, lung effects (TH or thoracic region) RDDR calculated to be 2.1576 using Table H-l (EPA, 1990—older version of inhalation dosimetry methodology used to calculate RDDR because MMAD <0.5 pm, so cannot use the EPA, 1994 program). 

The toxic pressure of each of the compounds in a mixture is calculated using the species sensitivity distribution (SSD) concept. In this concept, laboratory toxicity data for various species are collected from a database, for example, the USEPA s Ecotox database (USEPA 2005) or the RIVM e-toxBase (Wintersen et al. 2004), and compiled for each compound. A statistical distribution of these data, called the SSD, is derived. Each SSD describes the relationship between exposure concentration (X) and toxic pressure (Y), whereby the latter is expressed as the probably affected fraction (PAF, %) per compound (Posthuma et al. 2002). Depending on the test endpoint chosen for deriving SSDs, there is the option to derive chronic and acute toxic pressures, based on SSDN0ECs and SSDEC50s, respectively. 

Tier 1 involves the application of a simplified form of CA. It boils down to calculating the ratio between the exposure concentration of each component and a point estimate from its concentration-effect curve (e.g., the EC10, EC50, or NOEC), and the summation of these ratios. The human variant of this approach is the HI, and... 

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