Model systems environmental fate

GEMS (1986) Graphical Exposure Modeling System. FAP, Fate Atmospheric Pollution. Data Base, Office of Toxic Substances. U.S. Environmental Protection Agency. 

In a continuous model river test system it can be shown that after passage through a sewage treatment plant ester sulfonates have no significant influence on the qualitative and quantitative composition of the biocenosis of a receiving water [113]. All the investigations into the environmental fate of a-sulfo fatty acid esters demonstrate that aquatic toxicity is alleviated by their fast ultimate biodegradability, which allows them to be classified as environmentally compatible. 

In the past few years a variety of workshops and symposia have been held on the subjects of model verification, field validation, field testing, etc. of mathematical models for the fate and transport of chemicals in various environmental media. Following a decade of extensive model development in this area, the emphasis has clearly shifted to answering the questions "How good are these models ", "How well do they represent natural systems ", and "Can they be used for management and regulatory decision-making "... 

Additionally, the integration of geographic information system (GIS) with analytical data is an effective procedure in addressing the problem of spatial and temporal variability of the different parameters involved in the environmental fate of chemicals. Based on accurate local estimations, GIS-based models would then also allow deriving realistic and representative spatially averaged regional PECs. Table 4 shows some studies that have used GIS-based methodologies to perform a site-specific risk assessment of PECs in different exposed ecosystems. 

The characteristics of the applied models have been described in detail in the chapters Environmental Fate Models [50] and A Revision of Current Models for Environmental and Human Health Impact and Risk Assessment for Application to Emerging Chemicals [49] and only a brief overview is given here. Since each model has its own approach (i.e., QWASI is focused on the aquatic system), the combined results are expected to give a wider view with in-depth analyses for different aspects compared to just one model with its special characteristics. 

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. 

The ability to predict the behavior of a chemical substance in a biological or environmental system largely depends on knowledge of the physical-chemical properties and reactivity of that compound or closely related compounds. Chemical properties frequently used in environmental assessment include melting/boiling temperature, vapor pressure, various partition coefficients, water solubility, Henry s Law constant, sorption coefficient, bioconcentration factor, and diffusion properties. Reactivities by processes such as biodegradation, hydrolysis, photolysis, and oxidation/reduction are also critical determinants of environmental fate and such information may be needed for modeling. Unfortunately, measured values often are not available and, even if they are, the reported values may be inconsistent or of doubtful validity. In this situation it may be appropriate or even essential to use estimation methods. 

Many environmental fate processes, such as the degradation of pollutant chemicals, are not usefully modeled as equilibrium chemistry problems because the rate of the reaction is more important to quantify than the final composition of the system. For example, even though it may be known that at equilibrium a certain chemical will be fully degraded, it is crucial to know whether degradation will take seconds, years, or perhaps centuries. 

Data Structures. Inspection of the unit simulation equation (Equation 7) indicates the kinds of input data required by aquatic fate codes. These data can be classified as chemical, environmental, and loading data sets. The chemical data set , which are composed of the chemical reactivity and speciation data, can be developed from laboratory investigations. The environmental data, representing the driving forces that constrain the expression of chemical properties in real systems, can be obtained from site-specific limnological field investigations or as summary data sets developed from literature surveys. Allochthonous chemical loadings can be developed as worst-case estimates, via the outputs of terrestrial models, or, when appropriate, via direct field measurement. 

In summary then, one should analyze the problem at systems level prior to model selection based on entry characteristics and environmental dynamics of the pollutant. Experience suggests that it is better to rely on intuition and a few calculations than to construct a formal logical decision tree for guiding this process. Often, the compartment screening models are helpful at this stage. Characterization of the sources, the environment and the fate properties is an essential prerequisite to any procedure. 

Its capability to conduct full-chain risk assessment on a common system, which allows for linking the simulation of chemical fate in the environmental media, multiple pathways of exposure and the detailed analysis for multiple effects in different target tissues in human body (by PBPK models). 

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