Fate model estimation

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. 

Output from the soil erosion, pesticide fate, and economics submodels may not be needed for ET landfill cover evaluation and design they can be disregarded without affecting other components of the model estimate. 

From these data, aquatic fate models construct outputs delineating exposure, fate, and persistence of the compound. In general, exposure can be determined as a time-course of chemical concentrations, as ultimate (steady-state) concentration distributions, or as statistical summaries of computed time-series. Fate of chemicals may mean either the distribution of the chemical among subsystems (e.g., fraction captured by benthic sediments), or a fractionation among transformation processes. The latter data can be used in sensitivity analyses to determine relative needs for accuracy and precision in chemical measurements. Persistence of the compound can be estimated from the time constants of the response of the system to chemical loadings. 

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. 

Because the significance of exposure has only been considered over the past few years, there is not as wide a selection of exposure models available as that for fate models. The latter have been applied for several decades to the calculation of ambient exposure levels compared with some standard values. Papers illustrative of human exposure assessments in this symposium include one on airborne pollutant exposure assessments by Anderson (2), a generic approach to estimating exposure in risk studies by Fiksel (5), and a derivation of pollutant limit values in soil or water based on acceptable doses to humans by Rosenblatt, Small and Kainz (6). 

In this symposium a comprehensive overview of the risk estimation step and its relationship to the output of multimedia fate models is given in the paper by Fiksel (5). Examples of the application of and linkage among the various techniques are also presented in that paper. 

Parameters for which measured values are not clearly defined or readily available are often determined through calibration with observed data. In watershed chemical fate modeling, calibration has traditionally been associated with hydrologic parameters (e.g., erodibility coefficients, scour and deposition rates) because the required flow and sediment data are often available. Although initial parameter values can always be estimated, calibration is usually recommended to account for local and spatial variations. 

This gives an example of fate modeling in which the risks of an insect growth inhibitor, CGA-72662, in aquatic environments were assessed using a combination of the SWRRB and EXAMS mathematical models.. Runoff of CGA-72662 from agricultural watersheds was estimated using the SWRRB model. The runoff data were then used to estimate the loading of CGA-72662 into the EXAMS model for aquatic environments. EXAMS was used to estimate the maximum concentrations of CGA-72662 that would occur in various compartments of the defined ponds and lakes. The maximum expected environmental concentrations of CGA-72662 in water were then compared with acute and chronic toxicity data for CGA-72662 in fish and aquatic invertebrates in order to establish a safety factor for CGA-72662 in aquatic environments. 

The purpose of an Exposure Route and Receptor Analysis is to provide methods for estimating individual and population exposure. The results of this step combined with the output of the fate models serve as primary input to the exposure estimation step. Unlike the other analytic steps, the data prepared in this step are not necessarily pollutant-specific. The two discrete components of this analysis are (1) selection of algorithms for estimating individual intake levels of pollutants for each exposure pathway and (2) determination of the regional distribution of study area receptor populations and the temporal factors and behavioral patterns influencing this distribution. 

For a limited number of exposure pathways (primarily inhalation of air in the vicinity of sources), pollutant fate and distribution models have been adapted to estimate population exposure. Examples of such models include the SAI and SRI methodologies developed for EPA s Office of Air Quality Planning and Standards (1,2), the NAAQS Exposure Model (3), and the GEMS approach developed for EPA s Office of Toxic Substances (4). In most cases, however, fate model output will serve as an independent input to an exposure estimate. 

Because an assessment of this detail can be very difficult and costly to perform, however, (especially if it requires the use of complex fate models), exposure estimates may be limited to average seasonal conditions (e.g., summer — low flow — low rainfall, etc.) and to specific "worst case" meteorological or hydrological conditions for that area (e.g., inversion conditions, 7 day-10 year low flow). 

Particularly in the last two examples, fate models provide a useful tool not only for estimating concentrations, but also for tracing back the relative contributions of various sources to total exposure. 

The Qwasi model estimate the fate of a chemical in a water system (lake, river, etc.) consisting of water, bottom and suspended sediments, and air. The model is... 

Wania F, McLachlan MS (2001) Estimating the influence of forests on the overall fate of semivolatile organic compounds using a multimedia fate model. Environ Sci Technol 35(3) 582-590... 

When the rates of sorption or desorption processes are known, environmental fate modeling can provide an educated estimate and prediction on the accessibility and bioavailability of a target pollutant to a specific transport mechanism in the environment. Hence, the present chapter is an attempt to assess fate (i.e., in terms of pollutant mobility using predictive sorption or desorption coefficients) as well as effects (i. e., in terms of bioavailability) of various pollutants and to correlate these observations for development of predictive relationships. 

Objectives Optimize biological activity of drugs Find new active lead compounds Characteristics Response in isolated systems Effects are specific and well defined Specific mechanism of action Receptor is known in most cases Techniques Hansch Approach Multivariate Analysis Computerized molecular modeling Estimate rates of fate processes Analyze Processes Whole organism response Net effects (mortality growth, etc.) Specific nonspecific mechanisms Receptor unknown in most cases Hansch Approach Multivariate Analysis Molecular modeling not applied... 

Table 1.1 is a portion of the 196-compound data base used in a fate model to estimate volatile emissions, concentrations of toxic compounds in sludges, and... 

In fact, physiologically based pharmacokinetic models are similar to environmental fate models. In both cases we divide a complicated system into simpler compartments, estimate the rate of transfer between the compartments, and estimate the rate of transformation within each compartment. The obvious difference is that environmental systems are inherently much more complex because they have more routes of entry, more compartments, more variables (each with a greater range of values), and a lack of control over these variables for systematic study. The discussion that follows is a general overview of the transport and transformation of toxicants in the environment in the context of developing qualitative and quantitative models of these processes. 

Because exposure occurs where receptors co-occur with or contact stressors in the environment, characterizing the spatial and temporal distribution of a stressor is a necessary precursor to estimating exposure. The stressor s spatial and temporal distribution in the environment is described by evaluating the pathways that stressors take from the source as well as the formation and subsequent distribution of secondary stressors. For chemical stressors, the evaluation of pathways usually follows the type of transport and fate modeling described in Chapter 27. Some physical stressors such as sedimentation also can be modeled, but other physical stressors require no modeling because they eliminate entire ecosystems or portions of them, such as when a wetland is filled, a resource is harvested, or an area is flooded. 

Figure 1.1 The continuum of multimedia fate models available for estimating overall persistence (Pov) and potential for long-range transport of chemicals (Redrawn from OECD [2004]).

I inear Free-energy reactions have been applied to the reactions of many contaminants in natural waters, and they are especially useful in implementing simple transport and fate models for organic chemicals. If experimental values of iale constants are not available and if they can be estimated by LFERs, the applicability of such models can be extended. Hydrolysis reactions have received ihe most attention in developing LFERs for organic contaminants. In most... 

Estimation of the Main Exposure Routes by Environmental Fate Modeling... 

J. Dressel, C. Beigel, Estimation of standardized transformation rates of a pesticide and its four soil metabolites from field dissipation studies for use in environmental fate modeling, Proc. BCPC Conference - Weeds 119-126 (2001). 

Using annual emission surveys and trajectory calculations, the concentration, deposition, and transboundary flux of sulphur compounds will be continuously estimated in order to evaluate the atmospheric transport and fate of sulphur dioxide. The model estimates will be compared with the dally measurements at the monitoring stations. 

Two basic approaches to environmental exposure estimation can be identified monitoring and fate modeling. Although the techniques associated with both approaches are different, they share some goals ... 

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