5.0 Qualitative Analysis
5.1 Source/Transport
5.2 Exposure/Impact
5.1 Qualitative Analysis of CCEF Source and Transport Components
Ranking of the models considered a number of factors, which are listed here roughly in decreasing level of importance: (1) whether the model evaluated is on the primary exposure pathway (e.g., inhalation, ingestion, dermal) for the scenario of interest, (2) whether the model recommended for a particular scenario needs to be developed or already exists, (3) the accuracy of the model, and (4) whether the model provides the output and time units needed for downstream components of the CCEF.Determination of the primary exposure pathway depends on the physical/chemical characteristics (e.g., volatility) of the contaminant and the nature of the matrix containing the contaminant (e.g., paint or plastic). Exposure pathway determination also depends on specifics of the scenario, such as age, sex, and habits of exposed individual; physical characteristics of exposure location; or frequency and length of exposure. For some scenarios, the primary exposure pathway is fairly obvious, i.e. inhalation for Scenario 1 and ingestion for Scenario 2. For Scenario 3, the primary exposure pathway is inhalation, but it is not clear whether more benzene and toluene were inhaled from fugitive emissions or as natural constituents of cigarette smoke. For Scenario 4, the primary exposure pathway is not obvious without evaluating actual modeling results, since there are multiple chemicals with different exposure routes.
Table 5.1 Qualitative Ranking of Model Elements for Source and Transport Based on their Relative Contribution to Total Results (highest sensitivity listed first) and Research Need
| Scenario | Source* | Transport* |
|---|---|---|
| 1 | 1. WPEM (walls largest area painted) | 1. Partitioning between vapor and particle phases (gap) |
| 2. IAQX (smaller area wood ceiling) | 2. Dust particle resuspension (gap) | |
| 3. CONTAMW | ||
| 2 | 1. CONSEXPO | 1. CONSEXPO (primary exposure pathway) |
| 2. Partitioning between vapor and particle phases (gap) | ||
| 3. CONTAMW | ||
| 3 | 1. Fugitive Emissions (gap) | 1. Partitioning between vapor and particle phases (gap) |
| 2. PROMISE (less accurate) | Dust particle resuspension (gap) | |
| 3. Cigarette model** (most accurate) | 3. CONTAMW | |
| 4 | 1. Combustion model (gap) | 1. Partitioning between vapor and particle phases (gap) |
| 2. Fueling model (gap) | 2. Dust particle resuspension (gap) | |
| 3. Fuel spill (gap; higher frequency) | 3. CONTAMW | |
| 4. Paint spill (gap; higher frequency) | ||
| 5. PROMISE (input less well known) | ||
| 6. WPEM (input more well known) | ||
| 7. IAQX (less accurate) | ||
| 8. Cigarette model (most accurate) |
* - Primary basis for ranking indicated in parentheses. Gap = no model or algorithm currently identified.
** - Two of the contaminants of interest for Scenario 3 are benzene and toluene, which are natural constituents of cigarette smoke, and is not obvious whether the primary exposure pathway to worker compounding adhesives is inhalation of fugitive emissions or cigarette smoke.
Table 5.1 ranks models or algorithms identified for each scenario. Models are listed in order of those expected to contribute from the most to the least toward results in exposure estimates. Model gaps were included in prioritization and given especially high priority as a research need when they were believed to be a component of the primary exposure pathway. The explicit rules of prioritization used for ranking each of the five factors were listed above.
