Impact of fluorescence on Raman remote sensing of temperature in natural water samples.

Andréa De Lima Ribeiro,Helen Pask,Caro Derkenne,Penelope A Ajani,Christopher Artlett

doi:10.1364/oe.27.022339

Andréa De Lima Ribeiro, Helen Pask + Show 3 more

Open Access

https://doi.org/10.1364/oe.27.022339

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Abstract

A comprehensive investigation into the impact of spectral baseline on temperature prediction in natural marine water samples by Raman spectroscopy is presented. The origin of baseline signals is investigated using principal component analysis and phytoplankton cultures in laboratory experiments. Results indicate that fluorescence from photosynthetic pigments and dissolved organic matter may overlap with the Raman peak for 532 nm excitation and compromise the accuracy of temperature predictions. Two methods of spectral baseline correction in natural waters are evaluated: a traditional tilted baseline correction and a new correction by temperature marker values, with accuracies as high as ± 0.2°C being achieved in both cases.

Highlights

The use of Raman spectroscopy to predict water temperature was first proposed in [1,2] and the potential for extending this to determine depth-resolved temperature profiles using LIDAR methods was investigated in [3,4]
In 2015, we reported our first work in this field, harnessing these advances to obtain high quality Raman spectra, using statistical methods to identify the spectral parameters most sensitive to temperature change, and systematically predicting the accuracy with which temperature could be predicted by means of a temperature marker
In this case the temperature marker was the ratio of Raman signal intensities at two particular frequencies within the broad Raman band associated with OH stretching [8]

Summary

Introduction

The use of Raman spectroscopy to predict water temperature was first proposed in [1,2] and the potential for extending this to determine depth-resolved temperature profiles using LIDAR methods was investigated in [3,4] The applications for such knowledge are extensive, and include making predictions about underwater communication, validating hydrologic and climate change models, and obtaining habitat information. In 2015, we reported our first work in this field, harnessing these advances to obtain high quality Raman spectra, using statistical methods to identify the spectral parameters most sensitive to temperature change, and systematically predicting the accuracy with which temperature could be predicted by means of a temperature marker. That was a first step towards optical instrumentation for vertically profiling water temperature in natural environments

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Discussion

Conclusion