U.S. Department of EnergyOffice of Scientific and Technical Information
Data to Accompany: PM2.5 is insufficient to explain personal PAH exposure
Abstract
Fine particulate matter (PM2.5) air quality index (AQI) data from outdoor stationary monitors and Hazard Mapping System (HMS) smoke density data from satellites are often used as proxies for personal chemical exposure. Silicone wristbands can quantify more individualized exposure data than stationary air monitors or smoke satellites. However, it is not understood how these proxy measurements compare to chemical data measured from wristbands. We hypothesized that predictive models for personal chemical exposure would be significantly improved by expanding beyond stationary PM2.5 AQI data or satellite HMS data to also include environmental and behavioral information. In Eugene, Oregon, participants wore daily wristbands, carried a phone that recorded locations, and answered daily questionnaires for a seven-day period in multiple seasons. We gathered publicly available daily PM2.5 AQI data and HMS data. We analyzed wristbands for 94 organic chemicals, including 53 polycyclic aromatic hydrocarbons (PAHs). Wristband chemical detections and concentrations, behavioral variables (e.g., time spent indoors), and environmental conditions (e.g., PM2.5 AQI) significantly differed between seasons. Machine learning models were fit to predict personal chemical exposure using PM2.5 AQI only, HMS only, and a multivariate feature set including PM2.5 AQI, HMS, and other environmental and behavioral information. On average, the multivariate models increasedmore »
- Publication Date:
- DOE Contract Number:
- AC05-76RL01830
- Research Org.:
- Pacific Northwest National Laboratory 2
- Sponsoring Org.:
- DOE
- OSTI Identifier:
- 2229512
- DOI:
- https://doi.org/10.25584/2229512
Citation Formats
Bramer, Lisa M, Dixon, Holly M, Rohlman, Diana, Scott, Richard P, Miller, Rachel L, Kincl, Laurel, Herbstman, Julie B, Waters, Katrina M, and Anderson, Kim A. Data to Accompany: PM2.5 is insufficient to explain personal PAH exposure. United States: N. p., 2023.
Web. doi:10.25584/2229512.
Bramer, Lisa M, Dixon, Holly M, Rohlman, Diana, Scott, Richard P, Miller, Rachel L, Kincl, Laurel, Herbstman, Julie B, Waters, Katrina M, & Anderson, Kim A. Data to Accompany: PM2.5 is insufficient to explain personal PAH exposure. United States. doi:https://doi.org/10.25584/2229512
Bramer, Lisa M, Dixon, Holly M, Rohlman, Diana, Scott, Richard P, Miller, Rachel L, Kincl, Laurel, Herbstman, Julie B, Waters, Katrina M, and Anderson, Kim A. 2023.
"Data to Accompany: PM2.5 is insufficient to explain personal PAH exposure". United States. doi:https://doi.org/10.25584/2229512. https://www.osti.gov/servlets/purl/2229512. Pub date:Mon Nov 27 04:00:00 UTC 2023
@article{osti_2229512,
title = {Data to Accompany: PM2.5 is insufficient to explain personal PAH exposure},
author = {Bramer, Lisa M and Dixon, Holly M and Rohlman, Diana and Scott, Richard P and Miller, Rachel L and Kincl, Laurel and Herbstman, Julie B and Waters, Katrina M and Anderson, Kim A},
abstractNote = {Fine particulate matter (PM2.5) air quality index (AQI) data from outdoor stationary monitors and Hazard Mapping System (HMS) smoke density data from satellites are often used as proxies for personal chemical exposure. Silicone wristbands can quantify more individualized exposure data than stationary air monitors or smoke satellites. However, it is not understood how these proxy measurements compare to chemical data measured from wristbands. We hypothesized that predictive models for personal chemical exposure would be significantly improved by expanding beyond stationary PM2.5 AQI data or satellite HMS data to also include environmental and behavioral information. In Eugene, Oregon, participants wore daily wristbands, carried a phone that recorded locations, and answered daily questionnaires for a seven-day period in multiple seasons. We gathered publicly available daily PM2.5 AQI data and HMS data. We analyzed wristbands for 94 organic chemicals, including 53 polycyclic aromatic hydrocarbons (PAHs). Wristband chemical detections and concentrations, behavioral variables (e.g., time spent indoors), and environmental conditions (e.g., PM2.5 AQI) significantly differed between seasons. Machine learning models were fit to predict personal chemical exposure using PM2.5 AQI only, HMS only, and a multivariate feature set including PM2.5 AQI, HMS, and other environmental and behavioral information. On average, the multivariate models increased predictive accuracy by approximately 70% compared to either the AQI model or the HMS model for all chemicals modeled. This study provides evidence that PM2.5 AQI data alone or HMS data alone is insufficient to explain personal chemical exposures. Our results identify additional key predictors of personal chemical exposure.},
doi = {10.25584/2229512},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Nov 27 04:00:00 UTC 2023},
month = {Mon Nov 27 04:00:00 UTC 2023}
}