SBIR/STTR Research Award

Black Carbon and UV Particulate Matter, Multi-gas, Multi-pollutant Sensor Platform

Award identifier 0dd2ba3e8ec4bb5871d9482768d59f2d15d25d1dde41f3332ad14c249421ed97Awarding agency Environmental Protection Agency

Award amount

$299,919

Program and phase

SBIR · Phase II

Award year

2020

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Environmental Protection Agency
Branch
Not reported
Recipient company
MICROAETH CORPORATION
Proposal award date
2020-06-01
Contract end date
2022-05-31
UEI
NVFHWSQWBC69
Solicitation number
68HERC20R0005
Topic code
19-NCER-P2

Research abstract

As wildfires are increasing in prevalence and intensity there is a need for miniaturized, lower cost, and easily portable air sensor systems that provide accurate information to air quality and public health managers, communities, and researchers, so that the public can be protected and timely decisions can be made. Fixed site measurement stations are large and expensive. More dense networks of small low-cost sensors are needed to better protect public health. PM2.5 is an accepted standard for particulate matter (PM) measurements, but PM2.5 mass measurements alone cannot identify sources in-situ. In near-source biomass and wildfire impacted regions, Black Carbon and Organic Carbon are a significant portion of PM and are major contributors to the PM2.5 burden in the air. Black Carbon has been identified as one of the key constituents of PM2.5 and likely a causal agent of respiratory and cardiovascular disease. Diesel particulate matter, a known carcinogen and a significant source in urban areas, impacts health around the world. Low-cost PM sensors use a light scattering measurement technique which cannot detect particles below 0.5-1.0 micron (0.3 micron at best) in diameter and thus do not detect much of the emissions from fresh diesel combustion. This means that low-cost sensors and networks are likely not collecting any data related to fresh DPM and for PM in these small size fractions. Detecting toxic sub-micron diesel particulate matter and fine I ultra-fine particles from other sources is important in understanding health and providing accurate mass concentration data. Combining low cost PM sensors with AethLabs microAeth® Aethalometer® technology and advanced multi-sensor calibration algorithms using artificial intelligence techniques has significant advantages over the existing sensor platforms that are currently available. We have developed a proof-of-concept prototype sensor platform with sensor devices that integrate an optical particle counter with PM1. PM2.5, PM10 measurements, Black Carbon and CO2 sensors. The eventual commercialized device and the supporting cloud based data system has applications not just in wild land fire applications but in emerging smart city and community monitoringapplications. We estimate an opportunity in the United States for state and local agency sensor monitoring networks of between 20,000 and 350,000 sensors. Assuming that the USA might account for½ of the total market. we believe that the global addressable market is between 60,000 and 1,060,000 sensors valued between $30MM to $530MM depending on the final configuration and price of the final commercialized device.

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

2 SBIR/STTR records share this UEI (2019–2020). Reported award amounts total $399,472. Reported amounts are not federal obligations.

Phases: Phase II, Phase I

Agencies: Environmental Protection Agency

Agency intelligence

Environmental Protection Agency

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.