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DE-SC0022366: AerFox: An Adaptive Agile Modular System for Global Aerosol and Trace Gas Measurements

Award Status: Expired
  • Institution: Handix Scientific Inc., Fort Collins, CO
  • UEI: Q171MMKSULT4
  • DUNS: 079964197
  • Most Recent Award Date: 11/01/2022
  • Number of Support Periods: 1
  • PM: McFarlane, Sally
  • Current Budget Period: 02/14/2022 - 11/12/2023
  • Current Project Period: 02/14/2022 - 11/12/2023
  • PI: Rainwater, Bryan
  • Supplement Budget Period: N/A
 

Public Abstract

AerFox: An Adaptive Agile Modular System for Global Aerosol and Trace Gas Measurements—Handix Scientific Inc., 5485 Conestoga Court, Suite 104B, Boulder, CO 80301

Anna Hodshire, Principal Investigator, anna@handixscientific.com

Gavin McMeeking, Business Official, gavin@handixscientific.com

Amount:  $250,000


Our ability to predict the earth’s changing energy balance relies on the accurate representation of trace gas and aerosol sources, sinks, and transport processes. Reliable measurements of atmospheric constituents are a DOE objective and of broader benefit to the public. Current challenges to obtaining reliable ground-based measurements of aerosol and trace gas across the globe include limited ability to adapt in real time to do targeted sampling of specific events, limited power budgets in remote locations, poor-quality data at extremely high or low concentrations, and costs of high-quality instrumentation. To overcome these challenges, we propose to develop and commercialize an adaptive aerosol measurement node which will be a ground-based, lower-cost instrument and modular accessory package that can be deployed singly and in networks and operate autonomously anywhere on the Earth’s surface. The proposed system will include the ability to connect to common aerosol and trace gas instruments, provide aerosol conditioning (including concentration or dilution) to improve data quality, and make adaptive sampling decisions. For the latter, we will develop decision-tree software that can take instrument data or external data sources (e.g., weather data) and make user-specified adaptive sampling decisions. Future commercial applications include use by atmospheric researchers seeking low cost, low power, high performance and easy to use nodes that can interface with common aerosol and trace gas instruments and with externally available data sources.



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