New approach to remote sensing of temperature and salinity in natural water samples

Artlett, Christopher; Pask, Helen M.

doi:10.1364/oe.25.002840

Cited by 25 publications

(14 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Raman spectroscopy has proven to be an effective technique for determining water temperature in the laboratory with high accuracies of up to ±0.1 °C and ±0.5 °C using two-colour or depolarization markers, respectively [11,24]. The reports in [23,25,26] propose the possibility of measuring subsurface water temperature using Raman spectroscopy in combination with LIDAR methods, collecting time-resolved Raman signals in channels selected by optical filters. This is the ultimate goal of our research project.…”

Section: Introductionmentioning

confidence: 99%

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

Ribeiro

Artlett

Pask

2019

Sensors

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionmentioning

confidence: 99%

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

Ribeiro

Artlett

Pask

2019

Sensors

View full text Add to dashboard Cite

show abstract

“…Artlett and Pask have shown that both temperature and chlorinity significantly affect changes in Raman parameter dependent variables. 40 Therefore, the chlorinity calibration model should fully consider temperature and chlorinity. Accounting for the changes in chlorinity due to phase separation and water/rock reactions, 41,42 the chlorinity and temperature ranges for this study were set at 0-3.0 mol/ kg NaCl and 0-300 C, respectively, which cover the chlorinity and temperature levels of most hydrothermal fluids.…”

Section: Building the Chlorinity Calibration Modelmentioning

confidence: 99%

A Piecewise Model for In Situ Raman Measurement of the Chlorinity of Deep-Sea High-Temperature Hydrothermal Fluids

Zhang

et al. 2021

Appl Spectrosc

View full text Add to dashboard Cite

The chlorinity of deep-sea hydrothermal fluids, representing one of the crucial deep-sea hydrothermal indicators, indicates the degree of deep phase separation of hydrothermal fluids and water/rock reactions. However, accurately measuring the chlorinity of high-temperature hydrothermal fluids is still a significant challenge. In this paper, a piecewise chlorinity model to measure the chlorinity of high-temperature hydrothermal fluids was developed based on the OH stretching band of water, exhibiting an accuracy of 96.20%. The peak position, peak area ratio and F value were selected to establish the chlorinity piecewise calibration model within the temperature ranges of 0-50Â°C, 50-200Â°C and 200-300Â°C. Compared with that of the chlorinity calibration model built based on a single parameter, the accuracy of this piecewise model increased by approximately 4.83-12.33%. This chlorinity calibration model was applied to determine the concentrations of Cl for high-temperature hydrothermal fluids in the Okinawa Trough hydrothermal field.

show abstract

“…According to simulations performed by Artlett and Pask (2015) for ultrapure (Reverse-Osmosis) water, an optimum trade-off between Raman signals strength and RMSTEs would be obtained for acquisition channels with spectral widths of around 200 cm −1 . Optimum spectral positions for such channels were explored using simulations in Artlett and Pask (2017), with the "low shift" channel central position at 3,200 cm −1 and the "high shift" channel central position at 3,600 cm −1 . The availability of commercial Band Pass filters within these conditions is extremely limited, therefore the differences between spectral widths for channels collecting signals in the blue (254 and 136 cm −1 ) TABLE 3 | RMSTEs (± • C), sensitivities (% change/ • C), and absolute percentage errors in markers (%) for natural water sample analyzed by two-color and depolarisation markers.…”

Section: Considering the Relative Merits Of Spectrometers Using Blue mentioning

confidence: 99%

Remote Sensing of Natural Waters Using a Multichannel, Lidar-Compatible Raman Spectrometer and Blue Excitation

Ribeiro

Pask

2020

Front. Mar. Sci.

View full text Add to dashboard Cite

The design and operation of a custom-built LIDAR-compatible, four-channel Raman spectrometer integrated to a 473 nm pulsed laser is presented. The multichannel design allowed for simultaneous collection of Raman photons at spectral regions identified as highly sensitive to changes in water temperature. Four independent temperature markers were calculated for ultrapure (Milli-Q) and natural water samples [two-color(||), two-color(⊥), depolarisation(A), and depolarisation(B)]. Temperature accuracies of up to ±0.5 • C were achieved for both water types when predicted by two-color(||) markers. Multiple linear regression models were constructed considering all simultaneously acquired temperature markers, resulting in improved accuracies of up to ±0.2 • C. The potential benefits of blue laser excitation in relation to avoiding overlap between the Raman signal and fluorescence by chlorophyll-a are discussed, along with the higher Raman returns anticipated compared to the more-conventional green laser excitation.

show abstract

New approach to remote sensing of temperature and salinity in natural water samples

Cited by 25 publications

References 11 publications

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

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

A Piecewise Model for In Situ Raman Measurement of the Chlorinity of Deep-Sea High-Temperature Hydrothermal Fluids

Remote Sensing of Natural Waters Using a Multichannel, Lidar-Compatible Raman Spectrometer and Blue Excitation

Contact Info

Product

Resources

About