SBIR/STTR Award attributes
TECHNICAL ABSTRACT: In this Small Business Innovative Research (SBIR) program, Nikira Labs Inc. proposes to miniaturize the patented, open-path cavity ringdown spectroscopy (CRDS) analyzer developed by the National Oceanic and Atmospheric Administration (NOAA). The resulting instrument will be used to measure the optical properties of aerosols aboard Unmanned Aerial Systems (UASs) in highly humidified area, dust storms, and other poorly characterized regions. This data will be used by researchers in the NOAA Earth System Research Laboratory Chemical Sciences Division (ESRL CSD) to better constrain aerosol rad iative forcing estimations, thus improving climate models and the understanding of global climate change. In Phase I, Nikira Labs Inc. will fabricate a prototype, open-path CRDS instrument that includes a miniaturized, high-finesse optical cavity, fiber-coupled laser(s) and detector, and associated electronics for data control, acquisition, analysis, and reporting. The system will be extensively laboratory tested to determine its analytical performance by measuring both Rayleigh and aerosol scattering, before being deployed to measure ambient, outdoor air in an urban environment. Subsequently, the instrument will be deployed aboard a drone to empirically gauge its robustness and ability to perform airborne measurements. Finally, the Phase I results will be used to design a Phase II prototype.SUMMARY OF ANTICIPATED RESULTS: If the SBIR program is successful, Nikira Labs Inc. will have developed a very compact, openpath cavity ringdown system capable of measuring aerosol optical extinction and trace gases in unmanned aerial systems (UASs). This instrument will then be used to measure the optical properties of aerosols in highly humidified area (e.g. near clouds), dust storms, and other poorly characterized regions. This data will be used by researchers in the NOAA Earth System Research Laboratory Chemical Sciences Division (ESRL CSD) to better constrain aerosol radiative forcing estimations, thus improving climate models and the understanding of global climate change.
