Laser Driver and Analysis Circuitry Development for Quartz-Enhanced Photoacoustic Spectroscopy of NO2 for IoT Purpose

Alexander Kerschhofer, Philipp Breitegger, Alexander Bergmann

    Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review

    Abstract

    The rising effort to track local air pollution measurements require low-cost air quality sensors that provide good accuracy, long-term stability and possibly Internet of Things (IoT) connectivity. To provide such a solution and avoid cost-intensive equipment the development of a low-cost environmental sensor system was started. To measure the pollutant NO2, a quartz-enhanced photoacoustic spectroscopy (QEPAS) setup was established. A pulsed 450 nm laser diode excites NO2 molecules due to its strong absorption at this wavelength and causes a vibrational-translational relaxation, which results in an acoustic wave. The acoustic wave is detected by a quartz tuning fork (QTF) which generates a weak electrical signal proportional to the NO2 concentration. To realize this at low cost, a laser driver and an analysis circuit including a lock-in amplifier and analog-to-digital conversion were developed. We present first results, which proof the functionality of the circuitry compared to a more expensive laboratory setup.
    Original languageEnglish
    Title of host publicationLaser Driver and Analysis Circuitry Development for Quartz-Enhanced Photoacoustic Spectroscopy of NO2 for IoT Purpose
    Pages1-5
    Volume2
    Edition13
    DOIs
    Publication statusPublished - 22 Nov 2018

    Publication series

    NameProceedings
    PublisherMDPI AG
    ISSN (Print)2504-3900

    Keywords

    • air pollution
    • dds
    • internet of things
    • laser driver
    • lock in amplifier
    • measurement
    • photoacoustic spectroscopy

    Fingerprint

    Dive into the research topics of 'Laser Driver and Analysis Circuitry Development for Quartz-Enhanced Photoacoustic Spectroscopy of NO2 for IoT Purpose'. Together they form a unique fingerprint.

    Cite this