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Validation of the UPAS+: A filter-based air sampler coupled with a suite of real-time sensors

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 2R44ES024041-04
Agency Tracking Number: R44ES024041
Amount: $2,809,469.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: R
Solicitation Number: ES20-016
Timeline
Solicitation Year: 2020
Award Year: 2021
Award Start Date (Proposal Award Date): 2021-09-21
Award End Date (Contract End Date): 2024-08-31
Small Business Information
320 East Vine, Suite 221
Fort Collins, CO 80524
United States
DUNS: 078845198
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 DANIEL MILLERLIONBERG
 (970) 818-7520
 danlionberg@accsensors.com
Business Contact
 CHARLES HENRY
Phone: (970) 491-2852
Email: chemdoc98@gmail.com
Research Institution
N/A
Abstract

Particulate matter air pollution is a major contributor to the global burden of disease and the leading
environmental risk factor for premature morbidity and mortality on the planet. Human exposure to particulate air
pollution is largely estimated using data from stationary outdoor monitors installed in heavily populated areas.
These data might not reflect exposures in rural communities or vulnerable subpopulations. Further, there is
evidence that these data do not capture the unique exposure of a given individual, who likely spends most of
their time indoors and transitions between multiple locations (e.g., home, work) throughout the day. Therefore,
a need exists to improve our understanding of how the timing and magnitude of human exposure to particulate
air pollution relates to specific sources as well as individual behaviors or tasks.
The goal of this SBIR Phase IIB project is to improve our ability to assess human exposure to PM (and
subsequent health outcomes) by coupling a real-time sensor with a filter-based sampler (for in-situ gravimetric
validation) in a small, lightweight, quiet, wearable device. This coupling will improve our ability to estimate time-
and location-resolved PM exposure for outdoor, indoor, and personal exposure monitoring. To help users
harness the data from this device, we will develop data analysis and visualization software using a popular,
open-source platform (the R Statistical Software Project). To validate device performance and to evaluate its
usefulness to the research and environmental justice communities, we propose a field demonstration in rural
and urban communities in the San Joaquin Valley of California—an area known to suffer from high levels of fine
(PM2.5) and coarse (PM10) particulate matter pollution.

* Information listed above is at the time of submission. *

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