Final Report: Black Carbon and UV Particulate Matter, Multi-gas, Multi-pollutantSensor Platform
EPA Contract Number:
Black Carbon and UV Particulate Matter, Multi-gas, Multi-pollutantSensor Platform
MicroAeth Corporation dba AethLabs
May 1, 2019 through
October 31, 2019
Small Business Innovation Research (SBIR) - Phase I (2019)
Small Business Innovation Research (SBIR)
Small Business Innovation Research (SBIR): Phase 1 (2019)
SBIR - Air
As forest fires are increasing in prevalence and intensity there is a need for miniaturized, lower cost, and easily portable air sensors that provide information to first responders, air quality and public health managers, and communities, so that informed, timely decisions can be made. PM2.5 is an accepted standard for particulate matter (PM) measurements, but PM2.5 mass measurements cannot identify sources without analyzing samples in the laboratory. In near-source biomass and wildland fire environments, Black Carbon (BC) and Organic Carbon are a significant portion of PM and are major contributors to the PM2.5 burden in the air. BC has been identified as one of the key constituents of PM2.5 likely a causal agent of respiratory and cardiovascular disease. Carbonaceous particles, a byproduct of combustion, do not estimate total PM2.5 therefore an instrument that measures BC, UVPM, PM1, PM2.5, PM10, particle size and count, calculates BC / PM2.5 ratios and distinguishes between wood/biomass smoke and diesel emissions, has clear advantages. This project integrates the AethLabs microAeth MA350, additional PM and CO2 sensors and evaluates additional, CO, Ozone and NO2 sensors. Together these sensors can help to measure a variety of important pollutants and also discriminate between biomass and traffic emissions and between smoldering vs. flaming combustion emissions and determine their contribution to total PM2.5 mass.
The research objectives of this project are to investigate commercial feasibility of a Black Carbon and UV Particulate Matter, Multi-gas, Multi-pollutant Sensor Platform and to develop a new sensor platform capable of integrating different sensors depending on application requirements, and implement a data management and visualization system. For this project, we aimed to integrate PM and CO2 sensors with AethLabs' microAeth MA350 Black Carbon monitor. A prototype system was developed produced in prototype form and additional sensors researched and selected for future prototyping and testing.
The proof-of-concept prototype was compared to functional requirements and prototype specifications as informed by expert / customer feedback through key opinion leader interviews. A new data system has been implemented with a new website for the new sensor platform. End-to-end data collection and wireless transmission to the server has been tested over WiFi and cellular connections. Various wireless networking technologies were evaluated before finalizing a short list of technologies to implement depending on application requirements.
Through expert customer and key opinion leader interviews we have gained more insight into market opportunities and have defined a basic plan for releasing new products to meet the demands of various applications. We proposed multiple product variants to ensure wider commercial feasibility of the equipment while still enabling measurements in proximity to wildfires. We have made connections for future demonstrations, testing and field evaluations. The feedback from interviews and other market research stressed the value of other product applications over the wildfire source application. A Black Carbon and UV Particulate Matter, Multi-gas, Multi-pollutant Sensor Platform was developed and demonstrated. A data management and visualization system with data transmission over wireless was implemented and tested. Market analysis was carried out with key-opinion leader interviews, the result of which has directed our commercialization plan with a focus towards different application targets.
SBIR Phase II:
Black Carbon and UV Particulate Matter, Multi-gas, Multi-pollutant Sensor Platform