Upconversion detector for range-resolved DIAL measurement of atmospheric CH4

Lichun Meng et al., Optics Express 26, pp. 3850 – 3860 (2018)
Enhancing the detectivity of an upconversion single-photon detector by spatial filtering of upconverted parametric fluorescence using NLIR technology as in Optics Express, 2018

Remote monitoring of atmospheric methane (CH₄) with MIDWAVE Spectrometer

We demonstrate a robust, compact, portable and efficient upconversion detector (UCD) for a differential absorption lidar (DIAL) system designed for range-resolved methane (CH4) atmospheric sensing. The UCD is built on an intracavity pump system that mixes a 1064 nm pump laser with the lidar backscatter signal at 1646 nm in a 25-mm long periodically poled lithium niobate crystal. The upconverted signal at 646 nm is detected by a photomultiplier tube (PMT). The UCD with a noise equivalent power around 127 fW/Hz1/2 outperforms a conventional InGaAs based avalanche photodetector when both are used for DIAL measurements. Using the UCD, CH4 DIAL measurements have been performed yielding differential absorption optical depths with relative errors of less than 11% at ranges between 3 km and 9 km.

Explore Spectroscopy news with NLIR

Would you like to learn more?

Are you interested in performing environmental analysis with mid-infrared spectroscopy to monitor pollution and emissions? Discover how NLIR’s mid-infrared spectrometers can enable your research as well as industrial application.

Related News

Development of Mid-Infrared Absorption Spectroscopy for Gemstone Analysis as in Gemstone Analysis by Spectroscopy and Microscopy, Volume II, 2023

Development of mid-infrared absorption spectroscopy for gemstone analysis

Wang Z, Takahashi H., Minerals 13, no. 5: 625, (2023)
More information
Time-resolved mid-infrared photoluminescence spectroscopy of an undoped InAs substrate using NLIR spectrometer as featured in Applied Physics Letters

Time-resolved mid-infrared photoluminescence spectroscopy of an undoped InAs substrate

Hisashi Sumikura et al., Applied Physics Letter 124, 052105 (2024)
More information
Accurate Characterization of Mixed Plastic Waste Using Machine Learning and Fast Infrared Spectroscopy using NLIR technology as in ASC Sustainable Chemistry & Engineering, 2021

Accurate characterization of mixed plastic waste using machine learning and fast infrared spectroscopy

Stas Zinchik et al., ACS Sustainable Chemistry & Engineering 9, pp. 14143-14151 (2021)
More information

Related Scientific Research

Stay up-to-date

Sign up to our newsletter to stay up to date with the latest NLIR news!

RD engineer interested in the latest mid-infrared spectrometer news