Ultra-broadband infrared gas sensor for pollution detection: the TRIAGE project. (10th June 2021)

• Record Type: Journal Article
• Authors: Napier, Bruce; Bang, Ole; Markos, Christos; Moselund, Peter; Huot, Laurent; Harren, Frans J M; Khodabakhsh, Amir; Martin, Hans; Briano, Floria Ottonello; Balet, Laurent; Lecomte, Steve; Petersen, Christian R; Israelsen, Niels; Bastviken, David; Gålfalk, Magnus; Kubiszyn, Łukasz; Warzybok, Piotr
• Is Part Of: JPhys photonics. Volume 3:Number 3(2021)
• Publication Date: 2021-06-10
• Subjects: trace gas detection -- supercontinuum source -- spectroscopy -- mid-infrared -- deep learning algorithms -- big data repositories; Photonics -- Periodicals; 621.365
• DOI: 10.1088/2515-7647/ac0542
• Languages: English
• ISSNs: 2515-7647

Abstract

Abstract: Air pollution is one of the largest risk factors for disease or premature death globally, yet current portable monitoring technology cannot provide adequate protection at a local community level. Within the TRIAGE project, a smart, compact and cost-effective air quality sensor network will be developed for the hyperspectral detection of gases which are relevant for atmospheric pollution monitoring or dangerous for human health. The sensor is based on a mid-infrared supercontinuum source, providing ultra-bright emission across the 2–10 µ m wavelength region. Within this spectral range, harmful gaseous species can be detected with high sensitivity and selectivity. The spectroscopic sensor, which includes a novel multi-pass cell and detector, enables a smart robust photonic sensing system for real-time detection. With built-in chemometric analysis and cloud connection, the sensor will feed advanced deep-learning algorithms for various analyses, ranging from long-term continental trends in air pollution to urgent local warnings and alerts. Community-based distributed pollution sensing tests will be verified on municipal building rooftops and local transport platforms.