Bibliographic Details
| Title: |
Indoor Residence Times of Semivolatile Organic Compounds: Model Estimation and Field Evaluation. |
| Authors: |
Hyeong-Moo Shin1 hmshin@ucdavis.edu, McKone, Thomas E.2, Tulve, Nicolle S.3, Clifton, Matthew S.3, Bennett, Deborah H.1 |
| Source: |
Environmental Science & Technology. 1/15/2013, Vol. 47 Issue 2, p859-867. 9p. |
| Subjects: |
Indoor air pollution research, Semivolatile organic compounds analysis, Dust, Air analysis, Fugacity, Chlorpyrifos, Mathematical models |
| Geographic Terms: |
United States |
| Abstract: |
Indoor residence times of semivolatile organic compounds (SVOCs) are a major and mostly unavailable input for residential exposure assessment. We calculated residence times for a suite of SVOCs using a fugacity model applied to residential environments. Residence times depend on both the mass distribution of the compound between the "mobile phase" (air and dust particles settled on the carpet) and the "non-mobile phase" (carpet fibers and pad) and the removal rates resulting from air exchange and cleaning. We estimated dust removal rates from cleaning processes using an indoor-particle mass-balance model. Chemical properties determine both the mass distribution and relative importance of the two removal pathways, resulting in different residence times among compounds. We conducted a field study after chlorpyrifos was phased out for indoor use in the United States in 2001 to determine the decreases in chlorpyrifos air concentrations over a one-year period. A measured average decrease of 18% in chlorpyrifos air concentrations indicates the residence time of chlorpyrifos is expected to be 6.9 years and compares well with model predictions. The estimates from this study provide the opportunity to make more reliable estimates of SVOCs exposure in the indoor residential environment. [ABSTRACT FROM AUTHOR] |
|
Copyright of Environmental Science & Technology is the property of American Chemical Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Engineering Source |