A LIDAR-Compatible, Multichannel Raman Spectrometer for Remote Sensing of Water Temperature

The design and operation of a custom-built LIDAR-compatible, four-channel Raman spectrometer integrated to a 532 nm pulsed laser is presented. The multichannel design allowed for simultaneous collection of Raman photons at two spectral regions identified as highly sensitive to changes in water tempe...

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Main Authors: Andréa de Lima Ribeiro, Christopher Artlett, Helen Pask
Format: Article
Language:English
Published: MDPI AG 2019-07-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/19/13/2933
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spelling doaj-e143e8abc40d4b5b9e112308125cad002020-11-24T21:31:46ZengMDPI AGSensors1424-82202019-07-011913293310.3390/s19132933s19132933A LIDAR-Compatible, Multichannel Raman Spectrometer for Remote Sensing of Water TemperatureAndréa de Lima Ribeiro0Christopher Artlett1Helen Pask2MQ Photonics Research Centre, Department of Physics and Astronomy, Macquarie University, Sydney 2109, AustraliaMQ Photonics Research Centre, Department of Physics and Astronomy, Macquarie University, Sydney 2109, AustraliaMQ Photonics Research Centre, Department of Physics and Astronomy, Macquarie University, Sydney 2109, AustraliaThe design and operation of a custom-built LIDAR-compatible, four-channel Raman spectrometer integrated to a 532 nm pulsed laser is presented. The multichannel design allowed for simultaneous collection of Raman photons at two spectral regions identified as highly sensitive to changes in water temperature. For each of these spectral bands, the signals having polarization parallel to (∥) and perpendicular to (⟂), the excitation polarization were collected. Four independent temperature markers were calculated from the Raman signals: two-colour(∥), two-colour(⟂), depolarization(A) and depolarization(B). A total of sixteen datasets were analysed for one ultrapure (Milli-Q) and three samples of natural water. Temperature accuracies of ±0.4 °C−±0.8 °C were achieved using the two-colour(∥) marker. When multiple linear regression models were constructed (linear combination) utilizing all simultaneously acquired temperature markers, improved accuracies of ±0.3 °C−±0.7 °C were achieved.https://www.mdpi.com/1424-8220/19/13/2933Raman spectroscopyremote sensingwatertemperaturenatural watersLIDAR
collection DOAJ
language English
format Article
sources DOAJ
author Andréa de Lima Ribeiro
Christopher Artlett
Helen Pask
spellingShingle Andréa de Lima Ribeiro
Christopher Artlett
Helen Pask
A LIDAR-Compatible, Multichannel Raman Spectrometer for Remote Sensing of Water Temperature
Sensors
Raman spectroscopy
remote sensing
water
temperature
natural waters
LIDAR
author_facet Andréa de Lima Ribeiro
Christopher Artlett
Helen Pask
author_sort Andréa de Lima Ribeiro
title A LIDAR-Compatible, Multichannel Raman Spectrometer for Remote Sensing of Water Temperature
title_short A LIDAR-Compatible, Multichannel Raman Spectrometer for Remote Sensing of Water Temperature
title_full A LIDAR-Compatible, Multichannel Raman Spectrometer for Remote Sensing of Water Temperature
title_fullStr A LIDAR-Compatible, Multichannel Raman Spectrometer for Remote Sensing of Water Temperature
title_full_unstemmed A LIDAR-Compatible, Multichannel Raman Spectrometer for Remote Sensing of Water Temperature
title_sort lidar-compatible, multichannel raman spectrometer for remote sensing of water temperature
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2019-07-01
description The design and operation of a custom-built LIDAR-compatible, four-channel Raman spectrometer integrated to a 532 nm pulsed laser is presented. The multichannel design allowed for simultaneous collection of Raman photons at two spectral regions identified as highly sensitive to changes in water temperature. For each of these spectral bands, the signals having polarization parallel to (∥) and perpendicular to (⟂), the excitation polarization were collected. Four independent temperature markers were calculated from the Raman signals: two-colour(∥), two-colour(⟂), depolarization(A) and depolarization(B). A total of sixteen datasets were analysed for one ultrapure (Milli-Q) and three samples of natural water. Temperature accuracies of ±0.4 °C−±0.8 °C were achieved using the two-colour(∥) marker. When multiple linear regression models were constructed (linear combination) utilizing all simultaneously acquired temperature markers, improved accuracies of ±0.3 °C−±0.7 °C were achieved.
topic Raman spectroscopy
remote sensing
water
temperature
natural waters
LIDAR
url https://www.mdpi.com/1424-8220/19/13/2933
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