Abstract
Four receptor-oriented source apportionment models were evaluated by applying them to simulated personal exposure data for select volatile organic compounds (VOCs) that were generated by Monte Carlo sampling from known source contributions and profiles. The exposure sources modeled are environmental tobacco smoke, paint emissions, cleaning and/or pesticide products, gasoline vapors, automobile exhaust, and wastewater treatment plant emissions. The receptor models analyzed are chemical mass balance, principal component analysis/absolute principal component scores, positive matrix factorization (PMF), and graphical ratio analysis for composition estimates/source apportionment by factors with explicit restriction, incorporated in the UNMIX model. All models identified only the major contributors to total exposure concentrations. PMF extracted factor profiles that most closely represented the major sources used to generate the simulated data. None of the models were able to distinguish between sources with similar chemical profiles. Sources that contributed <5% to the average total VOC exposure were not identified. (Author)
Miller, Shelly L;
Anderson, Melissa J;
Daly, Eileen P;
Milford, Jana B
[1]
- Colorado Univ., Dept. of Mechanical Engineering, Boulder, CO (United States)
Citation Formats
Miller, Shelly L, Anderson, Melissa J, Daly, Eileen P, and Milford, Jana B.
Source apportionment of exposures to volatile organic compounds. 1: Evaluation of receptor models using simulated exposure data.
United Kingdom: N. p.,
2002.
Web.
doi:10.1016/S1352-2310(02)00279-0.
Miller, Shelly L, Anderson, Melissa J, Daly, Eileen P, & Milford, Jana B.
Source apportionment of exposures to volatile organic compounds. 1: Evaluation of receptor models using simulated exposure data.
United Kingdom.
https://doi.org/10.1016/S1352-2310(02)00279-0
Miller, Shelly L, Anderson, Melissa J, Daly, Eileen P, and Milford, Jana B.
2002.
"Source apportionment of exposures to volatile organic compounds. 1: Evaluation of receptor models using simulated exposure data."
United Kingdom.
https://doi.org/10.1016/S1352-2310(02)00279-0.
@misc{etde_20282987,
title = {Source apportionment of exposures to volatile organic compounds. 1: Evaluation of receptor models using simulated exposure data}
author = {Miller, Shelly L, Anderson, Melissa J, Daly, Eileen P, and Milford, Jana B}
abstractNote = {Four receptor-oriented source apportionment models were evaluated by applying them to simulated personal exposure data for select volatile organic compounds (VOCs) that were generated by Monte Carlo sampling from known source contributions and profiles. The exposure sources modeled are environmental tobacco smoke, paint emissions, cleaning and/or pesticide products, gasoline vapors, automobile exhaust, and wastewater treatment plant emissions. The receptor models analyzed are chemical mass balance, principal component analysis/absolute principal component scores, positive matrix factorization (PMF), and graphical ratio analysis for composition estimates/source apportionment by factors with explicit restriction, incorporated in the UNMIX model. All models identified only the major contributors to total exposure concentrations. PMF extracted factor profiles that most closely represented the major sources used to generate the simulated data. None of the models were able to distinguish between sources with similar chemical profiles. Sources that contributed <5% to the average total VOC exposure were not identified. (Author)}
doi = {10.1016/S1352-2310(02)00279-0}
journal = []
issue = {22}
volume = {36}
journal type = {AC}
place = {United Kingdom}
year = {2002}
month = {Aug}
}
title = {Source apportionment of exposures to volatile organic compounds. 1: Evaluation of receptor models using simulated exposure data}
author = {Miller, Shelly L, Anderson, Melissa J, Daly, Eileen P, and Milford, Jana B}
abstractNote = {Four receptor-oriented source apportionment models were evaluated by applying them to simulated personal exposure data for select volatile organic compounds (VOCs) that were generated by Monte Carlo sampling from known source contributions and profiles. The exposure sources modeled are environmental tobacco smoke, paint emissions, cleaning and/or pesticide products, gasoline vapors, automobile exhaust, and wastewater treatment plant emissions. The receptor models analyzed are chemical mass balance, principal component analysis/absolute principal component scores, positive matrix factorization (PMF), and graphical ratio analysis for composition estimates/source apportionment by factors with explicit restriction, incorporated in the UNMIX model. All models identified only the major contributors to total exposure concentrations. PMF extracted factor profiles that most closely represented the major sources used to generate the simulated data. None of the models were able to distinguish between sources with similar chemical profiles. Sources that contributed <5% to the average total VOC exposure were not identified. (Author)}
doi = {10.1016/S1352-2310(02)00279-0}
journal = []
issue = {22}
volume = {36}
journal type = {AC}
place = {United Kingdom}
year = {2002}
month = {Aug}
}