Recommended Citation
August 1, 2015.
Abstract
The Chemical Mixture Methodology (CMM) is used by the Department of Energy (DOE), its contractors, and other private and public organizations for emergency response planning. CMM assesses the potential health impacts on individuals that would result from exposure to an airborne mixture of hazardous chemicals. Health Code Numbers (HCNs) are assigned to each chemical based on the human organs targeted by exposure. In the current CMM, only the top 10 HCNs ranked by severity are included in each CMM analysis. This project focuses on assessing what happens when doubling the potential number of HCNs for each chemical that could be used in each CMM analysis. A total of 361 chemicals were used in our testing (the entire CMM database contains over 3000 chemicals). A set of 127 representative mixtures were prepared for our analysis. Three different concentration distributions (called “ideal”, “realistic”, and “same”) were used for each test mixture, providing us with a total of 381 test cases. CMM results were compared for all 381 test cases using both the 10-HCN approach and the 20-HCN approach. Only a slight difference was observed between the 10- and 20-HCN approaches. This slight difference suggests that the top 10-HCNs give good representation of the potential toxic health effects. This also indicates that it is impractical to incorporate the 20-HCN approach in a future version of the CMM. Therefore, effort should be directed to other aspects of the CMM development such as refining the nervous system effects or respiratory irritant effects in the near future.
Mentor
Xiao-Ying Yu
Lab site
Pacific Northwest National Laboratory (PNNL)
Funding Acknowledgement
This material is based upon work supported by the S.D. Bechtel, Jr. Foundation and by the National Science Foundation under Grant No. 0952013. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the S.D. Bechtel, Jr. Foundation or the National Science Foundation. This project has also been made possible with support of the National Marine Sanctuary Foundation. The STAR program is administered by the Cal Poly Center for Excellence in Science and Mathematics Education (CESaME) on behalf of the California State University (CSU).
URL: https://digitalcommons.calpoly.edu/star/316