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Probabilistic intake modelling

Probabilistic exposure models attempt to provide inputs to exposure models by representing variability or uncertainty via frequency or probability distributions. Probabilistic methods can be used in the exposure assessment because pertinent variables (e.g., concentration, intake rate, exposure duration, and body weight) have been identified, their distributions can be observed, and the formula for combining the variables to estimate the exposure is well defined. [Pg.341]

Probabilistic modelling works by taking a random sample from the distribution of additive levels for a given food and combining it with a random sample from the distribution of food consumption for that food. This sampling is repeated several thousand times until a smooth intake distribution curve is produced. [Pg.74]

Probabilistic modelling has been widely applied for determining acute intakes of pesticide residues. The method works well because for any randomly selected individual, the level of pesticide residue in a given food item is a... [Pg.74]

When the EPA considered exposures to insecticide residues in the home they identified at least six possible sources and routes these are given in Table 2.6. Their original approach apportioned the acceptable daily intake (ADI) between the various routes but it soon became clear that this was unrealistic because an individual was unlikely to be exposed via all routes on any one day. The EPA s present strategy is to develop an approach called micro-exposure event modelling. Micro-exposure event modelling is based on statistical data on the frequencies and levels of contamination of food, water, etc. and on behavioural information about the frequency of use of lawn/pet/timber treatments, etc. The combined data are assembled in a probabilistic model called LIFELINE which is able to predict the frequency and level of exposure to a group of hypothetical individuals over their lifetime.12 The model is also able to take account of the relative proportions of different types of accommodation, the incidence of pet ownership or any other data that will affect real levels of exposure. The output from the LIFELINE model allows the exposures of individuals in a population to be modelled over any interval from a single occasion to a lifetime. [Pg.34]

To address these questions, an exposure assessment should begin with a definition of the assessment objective (section 2.2.1). From this follows the need to define and evaluate the conceptual exposure model (section 2.2.2). The goal of the conceptual model is to establish exposure links via exposure pathways to exposure routes and relative magnitude of uptake or intake by different exposure routes. These questions are discussed in more detail in section 5.4 with respect to interpretation of the results of a probabilistic exposure assessment. [Pg.6]

One problem encountered when assessing exposure of human populations to contaminated land is spatial heterogeneity of pollution. To overcome this problem, Gay and Korre (2006) propose the combinations of spatial statistical methods for mapping soil concentrations, and probabilistic human health risk assessment methods. They applied geostatistical methods to map As concentrations in soil. Subsequently, an age-stratified human population was mapped across the contaminated area, and the intake of As by individuals was calculated using a modified version of the Contaminated Land Exposure Assessment (CLEA) model. This approach allowed a... [Pg.32]


See other pages where Probabilistic intake modelling is mentioned: [Pg.74]    [Pg.26]    [Pg.74]    [Pg.26]    [Pg.123]    [Pg.253]    [Pg.74]    [Pg.256]    [Pg.190]    [Pg.26]    [Pg.26]    [Pg.143]    [Pg.147]    [Pg.69]    [Pg.100]    [Pg.330]   


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