Chapter 3
CART Screening Level Analysis of Persistence: A Case Study 1
Deborah H. Bennett , Thomas E. McKone1,2, and W . E. Kastenberg
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Environmental Energy Technologies Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 School of Public Health and Department of Nuclear Engineering, University of California at Berkeley, Berkeley, CA 94720
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For the thousands of chemicals continuously released into the environment, it is desirable to make prospective assessments of those likely to be persistent. Persistent chemicals will remain in the environment a long time. Based on specific criteria for persistence, a binary logic tree can be developed to classify a chemical as "persistent" or "non-persistent" based on the chemical's properties. In this approach, the classification is based on the results of a standardized multimedia model. Thus, the classifications are more comprehensive for multimedia pollutants than classification using single media half-lives. A case study using twenty-six chemicals for three modes of entry into a unit world environment compares the characteristic time calculated from the multimedia model to the classification resulting from the tree.
Introduction Some chemical pollutants released into the environment are rapidly degraded while others persist for years or even decades. Those that persist can have higher environmental concentrations per unit release and are removed more slowly from the environment after use has ceased. Many persistent chemicals partition into multiple environmental media. Because persistent chemicals pose a greater potential concern
© 2 0 0 1 American Chemical Society
In Persistent, Bioaccumulative, and Toxic Chemicals II; Lipnick, R., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2000.
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30 per unit release than non-persistent pollutants, there is a need for simple but reliable methods for identifying potentially persistent pollutants. It is desirable to create screening level qualifications to determine which chemicals are likely to be non-persistent and which may persist (1,2). The ability to assess large numbers of chemicals provides a distinct regulatory advantage by eliminating the need to assess persistence by running a complex model for each chemical under consideration. If a chemical is classified as "non-persistent" using a screening method, we eliminate the need for further analysis. If a chemical is classified as persistent, it would likely undergo a more thorough evaluation before deciding i f the use of the chemical should be restricted. Ideally, the screening method should minimize both false negatives (preventing the use of persistent chemicals) and false positives (minimizing the need for a higher level evaluations). To provide a more robust screening method for classifying chemicals as persistent or non-persistent, we use multi-media assessments, without requiring extensive modeling and data for each chemical. To do this, we link the results of a simple multimedia model to a classification system, in this case: Classification and Regression Tree (CART) (3). A multi-media model is more effective than a single medium model if the chemical partitions among multiple media. A classification approach is linked to the model because modeling the persistence of numerous new and existing chemicals would be a major undertaking. The results of simple models can be used with Monte Carlo simulations as tools to develop effective strategies to classify chemicals without requiring an explicit simulation for each chemical. We develop a classification tree for each of three modes of entry into the environment. These trees are used to classify twenty-six chemicals as persistent or non-persistent. We compare the classifications to the characteristic time calculated by a multimedia model. The results of this analysis give us an idea about the effectiveness of C A R T and the limits on the precision of the method.
Methods Multimedia Model We use a closed unit world system to approximate the actual distribution of environmental media found across the earth as presented in Figure 1 (4). The model uses fugacity principles, a common approach for describing partitioning in multimedia systems (5, 6). The fugacity capacities (the chemical concentration per unit chemical fugacity) and dimensions for each compartment of the evaluation unit are listed in Table 1 (4, 6-9). The chemical exchange rates between compartments are based on both chemical properties and landscape properties and are defined as inventory-based mass transfer coefficients, " T " values, which can be found in Bennett et al., along with landscape property values used in the calculation (10). We have chosen to use a steady state mass distribution because it accounts for the shift from equilibrium resulting from the source and advective processes, while retaining sufficient simplicity to complete calculations in a tractable form, such as a spreadsheet (7).
In Persistent, Bioaccumulative, and Toxic Chemicals II; Lipnick, R., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2000.
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Figure 1 : Configuration of the unit world environmental model.
Table 1; Fugacity Capacities and Model Dimensions Fugacity Capacity, Air; Z =Z +Z a
IfTm>T,
air
\ Z
ap
=-^
a i r
0.17X&4 TfTm
