SBIR/STTR Research Award

Multispectral Sensor for Chemical Composition Analysis of Ultrafine Aerosols in Air Quality Assessment

Award identifier 152ed21ec03b551e081a7ed49e7be8bed05838eb83a3604cad182af4f0f1d2d9Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$259,573

Program and phase

STTR · Phase I

Award year

2022

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
SPECTREE INC.
Proposal award date
2022-09-13
Contract end date
2023-08-31
UEI
N4LLBMPLDKL8
Solicitation number
PA21-262
Topic code
143

Research abstract

Project SummaryWe propose developing and validating a novel platform technology that combines the collection and chemical analysis of ultrafine particles using an in-situ multispectral technique. The sample, collected directly onto the analysis substrate, is analyzed via excitation-emission matrix (EEM) spectroscopy. This approach will be validated against laboratory combustion-generated aerosols, such as diesel exhaust, wood smoke, tobacco smoke, and against a mixture of environmental pollutants. Within the respiratory tract, particle size determines the region of deposition and tissue uptake; the chemistry of the particle also affects solubility and determines the potential for biochemical reaction with tissues and cells. There is a growing awareness that exposure scenarios are very complex, consisting of time-varying concentrations and chemical composition over a broad range of particle sizes. Long-term exposure to air pollution has also been linked to increased mortality rates for infectious diseases, including COVID-19. The proposed research addresses the need for improved personal exposure assessment and characterization of ultrafine particles in the environment. Low-cost, miniaturized exposure monitoring devices can shed insight into the relationships between exposure to pollutants and health impact. Source apportioned measurements of PM concentration with high temporal and spatial resolution can facilitate the implementation of optimal air pollution mitigation strategies. The anticipated outcome of this project is the development of a miniaturized spectroscopic sensor that provides an analysis of the chemical composition of combustion-generated ultrafine particles, which both reflects the particle sources and determines their toxic potential. The machine-learning algorithms will enable the deconvolution of the complex spectra and identification of the PM source from the EEM analysis. The broader applications of the technology are environmental and regulatory monitoring, personal exposure assessment for the consumer market, and epidemiological studies.Project NarrativeExposure to complex environmental agents, such as ultrafine particulate matter derived from combustion sources and engineered nanomaterials, is not well understood. The toxic potential of inhaled particles is dependent on their size and chemical composition, and current solutions for personal exposure monitoring are expensive. This proposed effort addresses the need for a better individual exposure assessment, specifically, quantification of the health impact of ultrafine particles, and will facilitate optimal selection and implementation of air pollution control strategies.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

4 SBIR/STTR records share this UEI (2022–2026). Reported award amounts total $2,535,330. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Health and Human Services, Department of Defense

Agency intelligence

Department of Health and Human Services

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