NSF Convergence Accelerator Track L: UAV-assisted dual-comb spectroscopic detection, localization, and quantification of multiple atmospheric trace-gas emissions

Detecting chemical gas plumes is important for monitoring air quality. This project addresses the challenging problem of detecting, localizing, and quantifying gas emissions and detecting sources. The novel chemical sensing technology developed under this research project will provide a three-dimensional (3D) localization of airborne chemicals, creating maps to address a broad variety of trace-gas sensing applications of high societal importance.

Applications include the monitoring of health-threatening gas (e.g. from landfills, wastewater treatment plants, agriculture, or other industries), monitoring of farming environments to enrich yield, measuring exposure to toxic air pollution in communities located near industrial zones, or real-time assessment of disaster zones to provide actionable information to first responders. In addition to the technological and commercial impact, the project represents a unique mixture of fundamental physics, engineering, applied mathematics, and optics, and it will provide training for students at every level of educational ladder, thus contributing strongly to the development of a broadly-trained and globally competitive STEM workforce in the US.

To address the challenging problem of detecting, localizing and quantifying gas plumes of multiple volatile chemicals, an innovative laser sensing technology platform that offers 3D spatial concentration mapping will be developed. This technology will employ a novel dual-comb spectroscopic (DCS) sensor system based on chip-scale semiconductor quantum cascade laser frequency combs (QCL-FCs) operating in the mid-infrared molecular fingerprint spectral region.

These new laser sources provide both broadband mid-infrared coverage required for multi-species detection, and ultra‐high spectral resolution that enables high chemical selectivity. The QCL-DCS system will be configured into a retroreflector-based optical remote sensing system integrated with novel robotic capabilities provided by lightweight unmanned aerial vehicles (UAVs), and it will be coupled with advanced atmospheric fluid dynamics models to synergistically provide a powerful sensing platform that enables 3D tomographic localization of multiple chemical sources over large areas.

Ultimately, the proposed UAV-assisted QCL-DCS sensing platform will be optimized for rapid deployments and will achieve cost-efficiency via scalable semiconductor manufacturing and large deployment footprints, offering qualities that are highly desired in both commercial and government sectors.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.