Investigation of a Raman scattering spectral model for seawater containing a composite salt solute

Dong Bao; Dengxin Hua; Hao Qi; Jun Wang

doi:10.1364/OE.450250

1. Introduction

Salinity is an important physical parameter in oceanography and is also a significant dynamic parameter connecting the global water cycle and ocean circulation. Oceans dominate the global water cycle, 85% of evaporation and 77% of precipitation occurs at the ocean-atmosphere interface [1,2]. The main source of precipitation on land is also transported by the atmosphere from the ocean [3]. The salinity of the ocean plays an important role in the global water cycle. To analyze the impact of ocean salinity on water cycle, it is necessary to obtain not only the surface salinity of the ocean, but also to consider the vertical distribution of salinity [4,5]. The seasonal variation in salinity is closely related to extreme climate phenomena such as El Niño and hurricanes. Changes in salinity also influence the distribution of marine organisms. Therefore, monitoring ocean salinity is extremely important for biological research, climate simulation, weather forecasting, and hurricane path prediction [6]. In recent years, remote sensing, including satellite and laser remote sensing, has become an effective means of detecting ocean salinity [7]. Vine [8], Lagerloef [9], Reul [10], and Bao [11] used the European Space Agency’s Soil Moisture and Ocean Salinity (SMOS) satellite and NASA's Satelite de Aplicaciones Cienrificas-D (SAC-D) satellite detection data to obtain values of ocean salinity. However, satellite remote sensing can only obtain the temperature and salinity of the ocean’s surface layer. To meet the need of high-resolution, rapid, and continuous profile monitoring of salinity in oceanography, a method for detecting salinity of ocean using laser remote sensing is proposed. Temperature and salinity can alter the Raman spectra of seawater [12], and both these physical parameters produce subtle but distinct changes in the Raman stretching band. With the variation pattern of vibrational Raman spectra with salinity, Artlett [13] and Dolenko et al. [14] used Raman spectroscopy to detect the salinity of natural water, and established the relationship between Raman spectra and salinity at constant temperatures. Moghaddasl [15] and Kagi [16] investigated the relationship between the Raman spectra of fluid inclusions and salinity using laser remote sensing methods. Burikov et al. [17] used a neural network algorithm to achieve the inversion of seawater salinity by measuring Raman spectra at different salinities. Current methods for measuring ocean salinity are based on the monotropic function between Raman spectra and ocean salinity, while the effect of ocean temperature, which influences the measurement of salinity, is neglected. The theoretical studies for salinity detection by Raman spectra mainly focused on solution containing a single solute [18–20]. In ocean salinity detection research, NaCl solution is mainly used as the research target; however, seawater is a mixed solution composed of multiple solutes. Using a solution containing a single solute as the research target will also affect the accuracy of the detected relationship between Raman spectra and salinity. Raman spectra are correlated with seawater temperature and salinity, and their intensities are affected by the solute. Therefore, this method cannot accurately reflect the relationship between the Raman spectra, temperature, and salinity of seawater.

To achieve accurate detection of salinity, Raman spectra were obtained at different temperatures and salinities in this study. Combined with the Raman spectra of composite solute solutions. A quantitative function model of the Raman spectra, temperature, and salinity of seawater was established. Raman spectral intensity is affected by the temperature and salinity; hence, the intensity of the low-frequency Raman spectra decreases with increasing salinity, whereas the intensity of the high-frequency spectra increases with increasing salinity. Moreover, the low- and high-frequency area ratio of Raman spectra has a quantitative relationship with temperature and salinity. Therefore, the Raman spectra, salinity, and temperature model for active remote sensing of the ocean can be obtained. This research will provide reliable data for the study of global climates and ecosystems and improve the accuracy of marine disaster warnings and marine weather forecasting. The exploration and analysis of marine data for the economy, efficient and sustainable development, and the utilization of marine resources has a high research value and significant social benefits.

2. Theory

Raman scattering is a light scattering phenomenon caused by molecular or lattice vibrations in solids. In the entire 4π solid angle range, the total vibrational Raman scattering cross-section σ_mn for the transition n←m of a single molecule in all directions is [21]

(1)$${\sigma _{mn}} = \frac{{{I_{mn}}}}{{{I_0}}} = \frac{{{2^3}\pi }}{{{3^2}{\varepsilon _0}^2}}{v_0}{({v_0} - {v_{mn}})^3}gf(T){\left|{\sum\limits_{\rho \sigma } {{\alpha_{\rho \sigma }}({v_0})} } \right|^2},$$

where I_mn is the Raman scattering intensity of the n←m vibrational transition, I₀ and v₀ are the incident excitation beam intensity and frequency, respectively, v_mn represents the vibrational frequency of the Raman mode, g is the factor degeneracy of the initial state m, f(T) is the Boltzmann weight coefficient of the initial state heat distribution, and α_ρσ is the ρ, σth(ρ, σ=x, y, z) component of the Raman polarizability of molecules in all directions at the excitation frequency.

At 90°, Raman scattering measurements were obtained from a solution in which the incident light was polarized perpendicular to the scattering plane; both the parallel and perpendicular scattering polarizations were also collected. The differential Raman scattering cross-section equation is as follows [22]:

(2)$$\sigma ( \nu ) = \frac{{{\pi ^2}}}{{\textrm{45} \times \varepsilon _0^2}}{b^2}g\frac{{L({\nu _0}){{({{\nu_0} - {\nu_{mn}}} )}^4}}}{{1 - \textrm{exp} ( - hc{v_{mn}}/kT)}}[{45{{({\alpha_{}^{\prime}} )}^2} + 7{{({\gamma_{}^{\prime}} )}^2}} ],$$

where b is the zero amplitude, b = (h/8π²cv_mn)^1/2, α′² is the isotropy of the polarizability tensor, γ′² is the anisotropy of the polarizability tensor, h is the Planck constant, c is the speed of light, k is the Boltzmann constant, T is the absolute temperature, and L(v₀) is the local field correction for the condensed phase sample, which specifies the increased electric field amplitude in the sample over that which would be present in the gas phase. Its expression is as follows:

(3)$$L({v_0}) = ({n_s}/{n_0}){(n_s^2 + 2)^2}{(n_0^2 + 2)^2}/81,$$

where n_s and n₀ are the refractive indices of the samples at (v₀-v_mn) and v₀, respectively.

According to Eqs. (2) and (3), the Raman scattering cross-section is a function of temperature, excitation frequency, and solution concentration (related to salinity). However, owing to the unknown mechanism behind the seawater Raman spectra dependence on temperature and salinity, the quantitative representation of the Raman spectra of mixed solutions can be obtained using the polarizability theory. The area A of Raman spectra in the finite wavenumber range for the case of Stokes scattering is given by the following equation [23]:

(4)$$A \propto \int\limits_{{v_1}}^{{v_2}} {{I_{{v_0}}}\sigma (v)} \eta \Omega dv\textrm{ = }\int\limits_{{v_1}}^{{v_2}} {{I_{{v_0}}}} \sigma (v)N(V)\Omega dv,$$

where I_v₀ is the laser irradiance on the sample, σ(v) is the Raman scattering cross section, η is the molar density, N(V) is the number of molecules of a certain species in the scattering volume V, and Ω is the solid angle of the collected Raman scattering.

Research has shown that variations in Raman spectral intensity at low and high frequencies are correlated with temperature and salinity variations in seawater. Therefore, the relationship between Raman spectra, temperature, and salinity is usually established using the area ratio of the low- and high-frequency parts of Raman spectra. The low frequency aspect of Raman spectra is the vibration containing hydrogen bonds (HB), and the high frequency aspect is the vibration containing non-hydrogen bonds (NHB). According to the polarizability theory, Raman spectra are related to temperature and salinity through the following equation:

(5)$$\ln (\frac{{{A_{HB}}}}{{{A_{NHB}}}}) \propto f(S,t)\textrm{ = }n(S,T,\lambda )\frac{{\int\limits_{{v_1}}^{{v_2}} {{I_v}\sigma (v)\frac{{{W_i}}}{{{M_i}}}\Omega {e^t}dv} }}{{\int\limits_{{v_2}}^{{v_3}} {{I_v}\sigma (v)\frac{{{W_i}}}{{{M_i}}}\Omega {e^t}dv} }},$$

where A_HB and A_NHB are the low-frequency and high-frequency areas of Raman spectra, respectively, n(S, T, λ) is the refractive index of ocean, W_i is the mass fraction of species i in the solution, and M_i is the molar mass.

The refractive index n(S, T, λ) of ocean is related to its temperature and salinity as follows [24]:

(6)$$n(S,t,\lambda ) = {n_0} + S({n_1}t + {n_2}{t^2} + {n_3}{t^3}) + {n_4}{t^2} + \frac{{{n_{^5}} + {n_6}S + {n_7}t}}{\lambda } + \frac{{{n_8}}}{{{\lambda ^2}}} + \frac{{{n_9}}}{{{\lambda ^3}}},$$

where, the coefficient n_i is the system constant.

According to Eq. (5), to model the relationship between the Raman spectra, temperature, and salinity of seawater, Raman spectra must be obtained in different environments. Therefore, this study adopted experimental methods to detect Raman spectra at different temperatures and salinities.

3. Experiment

Seawater is a mixed solution containing complex chemical compositions, which mainly consist of anions and cations such as Cl^-, SO4^2-, Na⁺, K⁺, Mg²⁺, and Ca²⁺. Therefore, to investigate this composite multiple-solute solution, this study first considered solutions containing a single solute as the target; hence, NaCl, MgCl₂, Na₂SO₄, and MgSO₄ solutions with different salinities were prepared. Second, mixed solutions composed of NaCl-MgCl₂, NaCl-Na₂SO₄, Na₂SO₄-MgSO₄, and Na₂SO₄-MgCl₂-NaCl were prepared. Finally, the relationship between the Raman spectra of solutions containing a single solute and mixed solutions was obtained. Synthetic seawater was formulated according to the method proposed by Lyman and Fleming [25] and used to verify the relationship. Deionized water was used to prepare the solution, and an analytical reagent that required no further purification was chosen as the solute. To reduce the attenuation of incident light in seawater, a 532 nm Nd:YAG pulsed laser was used as the light source. The signal detection path was co-linear with the excitation, that is, a 180° backward scattering Raman signal was collected. Furthermore, a Princeton Instruments SP2500I spectrometer was used to detect Raman spectra, and the spectral data were smoothed using the Savitzky–Golay algorithm to reduce noise. To reduce experimental error, each sample was collected three times under the same conditions. Also, each sample with different salinities was maintained at a constant temperature using temperature control equipment to bring the water samples into thermal equilibrium.

4. Results and discussion

4.1 Raman spectra of water at different temperatures

The stretching vibration Raman spectra of pure water at room temperature can be decomposed into four modes of the re-emission process: 3250 cm⁻¹, 3425 cm⁻¹, 3530 cm⁻¹, and 3625 cm⁻¹. The corresponding redistribution function of the Raman spectra is given by [26]

(7)$${I_R} = k\sum\limits_{i = 1}^4 {{a_i}} \times \textrm{exp} \left[ {\frac{{{{({{{10}^7}/{\lambda_E} - {{10}^7}/{\lambda_R} - \Delta {v_i}} )}^2}}}{{2\sigma_i^2}}} \right],$$

where, k, a_i, △v_i, and σ_i are system constants.

Using Eq. (7), Raman spectra of pure water at different temperatures were obtained, which are shown in Fig. 1(a). The Raman spectra of water were observed in the range from 2800 to 3800 cm⁻¹. The intensity of the low-frequency areas of the Raman spectra decreased with increasing temperature, while the intensity of the high-frequency areas increased with increasing temperature.

Fig. 1. (a) Raman spectra of pure water at different temperatures; (b) relationship between the low- and high-frequency area ratio of Raman spectra and temperature.

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To quantitatively establish relationship between Raman spectra and temperature, the spectra were divided into two parts at the position of the maximum peak. The areas of low and high frequencies (A_HB and A_NHB) were calculated separately, and the relationship between temperature and Raman spectra was established using the results, as presented in Fig. 1(b). With the increase in temperature, the area ratio of the low- and high-frequency gradually decreased. The relationship between the area ratio of the low- and high-frequency of Raman spectra and temperature was approximately linear. Therefore, according to the results in Fig. 1(b), the relationship between Raman spectra and temperature can be obtained by using the Taylor expansion method on Eq. (5). The Raman spectra as a function of temperature is given by the following equation:

(8)$$\begin{aligned} \ln (\frac{{{A_{HB}}}}{{{A_{NHB}}}}) &= n(S,T,\lambda )[f({t_0}) + {f^{\prime}}({t_0})(t - {t_0}) + \frac{1}{2}{f^{^{\prime\prime}}}({t_0}){(t - {t_0})^2}]\\ &= n({S,t,\lambda } )({\gamma + \alpha t + \beta {t^2}} ), \end{aligned}$$

where α, β, and γ are functions related to the salinity of seawater. To accurately solve these three parameters, it is necessary to use the quantitative relationship between Raman spectra and salinity in seawater.

4.2 Raman spectra of solutions at different salinities

The salinity of seawater varies depending on the latitudinal position of the sea area, with an average value of 35‰. Therefore, the salinity of the prepared solution in this study ranged from 29.12‰ to 42.8‰. Because seawater contains complex solutes. Therefore, the study first used solutions containing a single solute as the research target. The effect of different ions in the solution on the intensity of the spectra was investigated by comparing the Raman spectra of solutions containing a single solute. Figures 2(a)–2(d) show the Raman spectra of four solutions containing a single solute of NaCl, MgCl₂, Na₂SO₄, and MgSO₄, respectively. According to the detection results, the intensities of both the low and high frequencies of the spectra varied with varying salinity for solutions of the same solute. However, for solutions containing different single solutes, differences were observed in the low- and high-frequency variations at the same salinity using Raman difference spectroscopy.

Fig. 2. Raman spectra of solutions containing a single solute. (a) NaCl solution; (b) MgCl₂ solution; (c) Na₂SO₄ solution; (d) MgSO₄ solution.

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Figure 3(a) shows the Raman difference spectroscopy results for solutions containing different single solutes at the same salinity. By comparing the results for solutions containing the same cation but different anions, the Raman spectra of the salt solutions containing chloride ions as the anion were shown to have a larger variation in intensity than the salt solutions containing sulfate ions as the anion. By comparing the results for solutions containing the same anion but different cations, the Raman spectra of the solution containing the magnesium ion cation were shown to have a large variation in intensity, whereas the Raman spectra of the solution containing the sodium ion cation exhibited a small variation in intensity. Therefore, the four solutions containing different solutes at the same salinity affected the intensity of the Raman spectra in the following order of strength: MgCl₂> NaCl > MgSO₄> Na₂SO₄. According to the differences between Raman spectra, the effect of the MgCl₂ solution on the spectral intensity was 1.5 times that of the NaCl solution, the effect of the MgSO₄ solution on the spectral intensity was 0.2 times that of the NaCl solution, and the effect of the Na₂SO₄ solution on the spectral intensity was 0.13 times that of the NaCl solution.

Fig. 3. (a) Raman difference spectroscopy results for solutions containing a single solute; (b) the relationship between the low- and high-frequency area ratio and salinity of the Raman spectra of solutions containing a single solute.

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The Raman spectra were affected by salinity, and the intensities of both the low and high frequencies varied. Therefore, the ratio of the low and high frequencies of Raman spectra can be used to quantitatively establish the relationship between Raman spectra and salinity. The relationship between the Raman spectra and the salinity of the solutions is shown in Fig. 3(b). A quantitative function was observed between the low- and high-frequency area ratio of the Raman spectra and salinity of solutions containing a single solute, while solutions containing different solutes exhibited a varying quantitative relationship between the low- and high-frequency area ratio of Raman spectra and salinity.

The detection results for solutions containing a single solute showed that there was a quantitative function between the area ratio of the low and high frequencies of Raman spectra and salinity. However, the obtained relationship varied for different solutes. Therefore, the influence of solutes on Raman spectra must also be considered in the detection of ocean salinity using Raman spectroscopy. In this study, a mixed solution containing two or three solutes was used as an example to investigate the relationship between the Raman spectra of the mixed solution and the solution containing a single solute. The relationship between the Raman spectra of the single solute solutions and that of seawater was obtained, and Fig. 4 shows the Raman spectra of the mixed solutions at different salinities. For mixed solutions, the intensity of both the low and high frequencies of the spectra varied with varying salinity. For mixed solutions containing different solutes, differences were also observed in the low- and high-frequency intensity variations using Raman difference spectroscopy.

Fig. 4. Raman spectra of different solute mixtures. (a) NaCl-MgCl₂ solution; (b) NaCl-Na₂SO₄ solution; (c) Na₂SO₄-MgSO₄ solution; (d) Na₂SO₄-MgCl₂-NaCl solution.

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Figure 5(a) shows the results of Raman difference spectroscopy on the mixed solutions at the same salinity. The mixed solutions consisting of different solutes at the same salinity affected the Raman spectral intensity in the following order of strength: MgCl₂-NaCl > NaCl-Na₂SO₄> MgCl₂-NaCl-Na₂SO₄> Na₂SO₄-MgSO₄. When the anion contained in the solution was a chloride ion, a greater effect was observed on the intensity of the Raman spectra than in the case of a sulfate ion. By analyzing the differences between Raman spectra at the same salinity, the effect of the NaCl-Na₂SO₄ solution on the intensity of Raman spectra was found to be 10.2 times greater than that of the Na₂SO₄-MgSO₄ solution. Therefore, the effect of anionic chloride ions on the intensity of Raman spectra was more than ten times greater than the effect of cationic magnesium ions. In summary, when the effect of solutes on the Raman spectra of seawater was investigated, salt solutions containing chloride ions were primarily targeted, followed by salt solutions containing sulfate ions, and finally the effect of cations on Raman spectra was considered.

Fig. 5. (a) Raman difference spectroscopy of mixed solutions; (b) relationship between the low- and high-frequency area ratio of Raman spectra and salinity of mixed solutions.

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The relationship between the Raman spectra of the mixed solutions and salinity is shown in Fig. 5(b), which reveals that the Raman spectra of mixed solutions with low- and high-frequency area ratios were quantitatively related as a function of salinity. However, for mixed solutions containing different solutes, the quantitative relationship between the low- and high-frequency area ratios of the Raman spectra and salinity differed.

By investigating the relationship between the Raman spectra of solutions containing a single solute and mixed solutions, it was found that the area ratios of mixed solution Raman spectra at low and high frequencies could be obtained from the results of multiple solutions containing a single solute. Therefore, this method could also be used for seawater containing complex solutes. By detecting the Raman spectra of multiple solutions containing a single solute at different salinities, the low- and high-frequency area ratios of the Raman spectra of seawater at different salinities were obtained. The relationship between the Raman spectra of seawater and solutions containing a single solute is given by the following equation:

(9)$$\begin{array}{c} \ln {(\frac{{{A_{HB}}}}{{{A_{NHB}}}})_{\textrm{sea}}} \approx (\ln {(\frac{{{A_{HB}}}}{{{A_{NHB}}}})_{\textrm{NaCl}}} + \frac{{{q_{\textrm{MgC}{\textrm{l}_\textrm{2}}}}}}{{{q_{\textrm{NaCl}}}}}\ln {(\frac{{{A_{HB}}}}{{{A_{NHB}}}})_{\textrm{MgC}{\textrm{l}_\textrm{2}}}} + \frac{{{q_{\textrm{MgS}{\textrm{O}_4}}}}}{{{q_{\textrm{NaCl}}}}}\ln {(\frac{{{A_{HB}}}}{{{A_{NHB}}}})_{\textrm{MgS}{\textrm{O}_\textrm{4}}}}\\ + \frac{{{q_{{\textrm{K}_\textrm{2}}\textrm{S}{\textrm{O}_\textrm{4}}}}}}{{{q_{\textrm{NaCl}}}}}\ln {(\frac{{{A_{HB}}}}{{{A_{NHB}}}})_{{\textrm{K}_\textrm{2}}\textrm{S}{\textrm{O}_\textrm{4}}}} + \frac{{{q_{\textrm{CaC}{\textrm{l}_\textrm{2}}}}}}{{{q_{\textrm{NaCl}}}}}\ln {(\frac{{{A_{HB}}}}{{{A_{NHB}}}})_{\textrm{CaC}{\textrm{l}_\textrm{2}}}} \ldots )/m, \end{array}$$

where q is the scale factor and m is the number of solutions containing a single solute. The expression for q is

(10)$$q = \frac{{\Delta \cdot {I_0}}}{{{\delta _0} \cdot {I_d}}},$$

where Δ is the frequency shift of Raman spectra, I₀ is the Raman spectral intensity, δ₀ is the half-height full width of Raman spectra, and I_d is the difference between the maximum and minimum values of Raman difference spectroscopy.

By combining Eq. (8) with the results of the detected Raman spectra, the quantitative relationship between the low- and high-frequency area ratio of the Raman spectra of seawater and salinity can be obtained. Using the least-squares fitting method, the coefficients α, β, and γ in Eq. (7) can be calculated by combining the relationship between the Raman spectra of seawater and salinity. The expressions for the coefficients α, β, and γ are as follows:

(11)$$\alpha ={-} 0.003939 - 5.417 \times {10^{ - 5}}S + 4.876 \times {10^{ - 7}}{S^2},$$

(12)$$\beta = 4.356 \times {10^{ - 7}} + 4.876 \times {10^{\textrm{ - }7}}S,$$

(13)$$\gamma = 0.5097 - 0.002182S + 3.736 \times {10^{ - 6}}{S^2} - 3.098 \times {10^{ - 8}}{S^3}.$$

Because the area ratio of the low- and high-frequency parts of Raman spectra are negatively correlated with temperature and salinity. Therefore, by introducing the coefficients α, β, and γ into Eq. (7), the quantitative relationship between the Raman spectra of seawater and the temperature and salinity can be obtained. Using this relationship, the area ratios of the low and high frequencies of the obtained Raman spectra were calculated as a function of temperature and salinity, as shown in Fig. 6. The low- and high-frequency area ratio of the Raman spectra decreased with an increase in salinity and temperature. When the seawater temperature is known, accurate salinity can be obtained by detecting the Raman spectra of ocean.

Fig. 6. Relationship between the temperature, salinity, and Raman spectra of seawater.

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To verify the model of the Raman spectra, temperature and salinity relationship of seawater, samples of seawater at different salinities were prepared using artificial sea salt. The detected Raman spectra are shown in Fig. 7. The low-frequency intensity of the seawater Raman spectra decreased with increasing salinity; however, the high-frequency intensity increased with increasing salinity.

Fig. 7. Raman spectra of seawater at different salinities.

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The quantitative relationship between Raman spectra and salinity can be obtained based on the detection results of the seawater Raman spectra. The low- and high-frequency area ratios of the Raman spectra were substituted into Eq. (7) to invert the seawater salinity. The experimental results (dots) and the results of the inversion using the model (line) are shown in Figs. 8(a) and 8(b). Because the model results were obtained by theoretical, and the experimental results were obtained by instrument detection. Therefore, there are differences between them.

Fig. 8. Relationship between Raman spectra of seawater and salinity.

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4.3 Error analysis

The Raman spectra of seawater are correlated with temperature and salinity, and both temperature and salinity variations can affect the detection results. The model error of the Raman spectra, temperature and salinity of seawater is given by the following equation:

(14)$$\delta \ln (\frac{{{A_{HB}}}}{{{A_{NHB}}}})\textrm{ = [(}\frac{{\partial \ln (\frac{{{A_{HB}}}}{{{A_{NHB}}}})}}{{\partial T}}\delta T{\textrm{)}^2}\textrm{ + (}\frac{{\partial \ln (\frac{{{A_{HB}}}}{{{A_{NHB}}}})}}{{\partial S}}\delta S{\textrm{)}^2}{\textrm{]}^{1/2}}.$$

In the Raman spectra experiment for seawater, the temperature control accuracy was ±0.2 °C. The influence of the temperature error on the low- and high-frequency area ratios of the Raman spectra is presented in Fig. 9. Figure 9(a) shows the experimental results and theoretical values of the low- and high-frequency area ratio of the Raman spectra at different temperatures; the theoretical values agreed with the experimental results. Figure 9(b) shows the error between the experimental and theoretical values; the error caused by the temperature error on the low- and high-frequency area ratio of the Raman spectra was less than 0.001.

Fig. 9. (a) Theoretical values and experimental results of the low- and high-frequency area ratio of the Raman spectra at different temperatures; (b) the error in temperature caused the difference between the theoretical and experimental values of the low- and high-frequency area ratio of the Raman spectra.

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Furthermore, salinity errors can also affect Raman spectra detection results. The salinity accuracy of the prepared solution in the experiment was ±0.2 ‰. The influence of salinity error on the low- and high-frequency area ratios of the Raman spectra is presented in Fig. 10. Figure 10(a) shows the experimental results and theoretical values of the low- and high-frequency area ratio of the Raman spectra at different salinities; the theoretical values agreed with the experimental results. Figure 10(b) shows the error between the experimental results and theoretical values at different salinities; the error caused by salinity error on the low- and high-frequency area ratio of the Raman spectra was less than 0.003.

Fig. 10. (a) Theoretical values and experimental results of low- and high-frequency area ratio of the Raman spectra at different salinities; (b) the error in salinity caused the difference between the theoretical and experimental values of the low- and high-frequency area ratio of the Raman spectra.

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In practical remote sensing applications, the changes of temperature and salinity are the influencing factors to the Raman spectra of seawater. Therefore, the temperature of ocean is required for remote sensing salinity. Ocean temperature can be detected by using Brillouin scattering [27–29]. Its principle is that both temperature and salinity affect the velocity of sound, and the Brillouin frequency shift is related to the velocity of sound within the medium. The results showed that the maximum error is about ±0.16 °C for the inversion of ocean temperature with assumed salinity. The influence of the Brillouin lidar detection of seawater temperature for the low- and high-frequency area ratio of the Raman spectra is presented in Fig. 11. Figure 11(a) shows the experimental results and theoretical values of the low- and high-frequency area ratio of the Raman spectra at different temperatures; the theoretical values agreed with the experimental results. Figure 11(b) shows the error between the experimental and theoretical values; the error caused by the temperature of ocean remote sensing for the low- and high-frequency area ratio of the Raman spectra was less than 8.3×10⁻⁴.

Fig. 11. (a) Theoretical values and experimental results of low- and high-frequency area ratio of the Raman spectra at different temperatures; (b) the error caused by the temperature of ocean remote sensing for the low- and high-frequency area ratio of the Raman spectra.

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5. Conclusion

To realize the high-precision inversion of seawater salinity using Raman spectroscopy, this paper proposed a quantitative Raman spectra, temperature, and salinity function model for seawater using the Raman spectra of seawater with different temperatures and salinities combined with the Raman spectra of composite solute solutions. Raman spectra of solutions containing a single solute and mixed solutions were detected, and the effect of solutions containing different solutes on the Raman spectra was analyzed. Based on the relationship between the Raman spectra of solutions containing a single solute and mixed solutions, the relationship between the Raman spectra of seawater containing complex solutes and solutions containing a single solute was deduced. The intensity variation of the low- and high-frequency areas of Raman spectra correlated with temperature and salinity. Therefore, the area ratio of the Raman spectra at low and high frequencies was used to model the quantitative relationship between temperature and salinity. The model can be used to accurately invert the salinity of seawater when the seawater temperature is known. Experiments were conducted to validate the model using the Raman spectra of seawater at different salinities, and the results showed that the model calculations were consistent with the experimental results. The model provides reliable data for remote sensing of ocean salinity, offers data support for the research of global climates and ecosystems, and will improve the accuracy of marine environments, marine disaster warnings, and marine meteorological forecasting. However, in practical remote sensing applications, the changes of temperature and salinity are the influencing factors to the Raman spectra of seawater. Therefore, it is difficult to achieve high accuracy inversion of ocean salinity or temperature using either Raman spectroscopy or Brillouin scattering individually. To achieve high precision remote sensing of ocean salinity, the data of Brillouin frequency shift and Raman spectra can be fused. Ocean water content will also significantly impact the detection results, such as colored dissolved organic matter (CDOM), solid organic matter and particulates. To reduce the impact on salinity detection, these parameters can also be detected using a filter system in lidar detection.

Funding

National Natural Science Foundation of China (41875034).

Acknowledgments

Statistical support was provided by Hao Qi. Writing assistance was provided by Jun Wang and Dengxin Hua. The detection experiment was conducted by Dong Bao.

Disclosures

The authors declare no conflicts of interest.

Data availability

Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

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Investigation of a Raman scattering spectral model for seawater containing a composite salt solute

Abstract

1. Introduction

2. Theory

3. Experiment

4. Results and discussion

4.1 Raman spectra of water at different temperatures

4.2 Raman spectra of solutions at different salinities

4.3 Error analysis

5. Conclusion

Funding

Acknowledgments

Disclosures

Data availability

References

Data availability

Cited By

Figures (11)

Equations (14)

Optics Express