The Contaminant Candidate List (CCL) classification process involves three major stages. The first stage was to
identify a large number of chemicals that are in or have the potential to be present in
drinking water, or have demonstrated or potential adverse health effects. The second
stage was to narrow the pool of candidates by developing screening criteria, which takes
into account both the occurrence and adverse health effects data at a level of concern, to a
Preliminary CCL (PCCL). The third stage of the process involves classifying
contaminants on the PCCL to develop the CCL.
In order to classify contaminants for the CCL, a variety of approaches need to be
considered in developing a process to classify contaminants. The selected approach
would be used to classify the chemicals on the PCCL, chemicals that have already been
pre-screened from a larger number of chemicals. The general approaches for
consideration are rule-based, prototype classification (algorithm), expert process or some
combination. The general approaches for consideration have some similarities and
unique differences that may be important in making a decision. For example, the
prototype classification approach requires the use of a training and validation data set.
Whereas, the other approaches may make use of a training and validation data set but not
require it. Additionally, each of these general categories of approaches includes a variety
of related approaches with more specific differences that may be relevant to the process
as the details of the available data in the PCCL are determined.
The selected approach will need to classify the chemicals on the basis of the
available occurrence and health effects data and information in the PCCL. The data used
to classify will also be consistent with the types of data used to screen the larger number
of chemicals to develop the PCCL. More specifically, the data elements that represent
occurrence and health effects are combined into five attributes. Potency and Severity
represent the health effects and Prevalence, Magnitude and Persistence-Mobility
represent the occurrence. Potency is represented by data elements such as: the lowest
observed adverse effect levels (LOAEL), lethal dose (LD50, LDlo), and carcinogenicity
values. Severity represents the adverse health effect caused by chemical, based on the
potency data element used. Prevalence is represented by data elements such as:
percentage of detects in finished water, number of states released (production and release
data). Magnitude is represented by data elements such as: concentration in finished
water, pounds produced (production data) and pounds released (Toxic Release
Inventory). Persistence and Mobility is represented by data elements such as: half-life,
biodegradation rate and solubility. A method (Attribute Scoring Protocols) is being
developed to create a numerical value for each of these attributes on the same basis, in
order to classify chemicals on the PCCL using the selected approach in a consistent
manner. Includes abstract only.
| Edition : | Vol. - No. |
| File Size : | 1
file
, 76 KB |
| Note : | This product is unavailable in Ukraine, Russia, Belarus |
| Number of Pages : | 1 |
| Published : | 11/01/2005 |
