Effective correction of dissolved organic carbon interference in nitrate detection using ultraviolet spectroscopy combined with the equivalent concentration offset method.

Nitrate contamination in water sources poses a substantial environmental and health risk. However, accurate detection of nitrate in water, particularly in the presence of dissolved organic carbon (DOC) interference, remains a significant analytical challenge. This study investigates a novel approach for the reliable detection of nitrate in water samples with varying levels of DOC interference based on the equivalent concentration offset method. The characteristic wavelengths of DOC were determined based on the first-order derivatives, and a nitrate concentration prediction model based on partial least squares (PLS) was established using the absorption spectra of nitrate solutions. Subsequently, the absorption spectra of the nitrate solutions were subtracted from that of the nitrate-DOC mixed solutions to obtain the difference spectra. These difference spectra were introduced into the nitrate prediction model to calculate the equivalent concentration offset values caused by DOC. Finally, a DOC interference correction model was established based on a binary linear regression between the absorbances at the DOC characteristic wavelengths and the DOC-induced equivalent concentration offset values of nitrate. Additionally, a modeling wavelength selection algorithm based on a sliding window was proposed to ensure the accuracy of the nitrate concentration prediction model and the equivalent concentration offset model. The experimental results demonstrated that by correcting the DOC-induced offsets, the relative error of nitrate prediction was reduced from 94.44% to 3.36%, and the root mean square error of prediction was reduced from 1.6108 mg L-1 to 0.1037 mg L-1, which is a significant correction effect. The proposed method applied to predict nitrate concentrations in samples from two different water sources shows a certain degree of comparability with the standard method. It proves that this method can effectively correct the deviations in nitrate measurements caused by DOC and improve the accuracy of nitrate measurement.

Neural network spectral relationship to improve an inherent optical properties data processing system for residual error correction.

The residual error was a critical indicator to measure the data quality of ocean color products, which allows a user to decide the valuable envisioned application of these data. To effectively remove the residual errors from satellite remote sensing reflectance (Rrs) using the inherent optical data processing system (IDAS), we expressed the residual error spectrum as an exponential plus linear function, and then we developed neural network models to derive the corresponding spectral slope coefficients from satellite Rrs data. Coupled with the neural network models-based spectral relationship, the IDAS algorithm (IDASnn) was more effective than an invariant spectral relationship-based IDAS algorithm (IDAScw) in reducing the effects of residual errors in Rrs on IOPs retrieval for our synthetic, field, and Chinese Ocean Color and Temperature Scanner (COCTS) data. Particularly, due to the improved spectral relationship of the residual errors, the IDASnn algorithm provided more accurate and smoother spatiotemporal ocean color product than the IDAScw algorithm for the open ocean. Furthermore, we could monitor the data quality with the IDASnn algorithm, suggesting that the residual error was exceptionally large for COCTS images with low effective coverage. The product effective coverage should be rigorously controlled, or the residual error should be accurately corrected before temporal and spatial analysis of the COCTS data. Our results suggest that an accurate spectral relationship of residual errors is critical to determine how well the IDAS algorithm corrects for residual error.

Scattering direction sampling methods for polarized Monte Carlo simulation of oceanic lidar.

Monte Carlo techniques have been widely applied in polarized light simulation. Based on different preconditions, there are two main types of sampling strategies for scattering direction: one is the scalar sampling method; the others are polarized sampling approaches, including the one- and two-point rejection methods. The polarized simulation of oceanic lidar involves a variety of mediums, and an efficient scattering sampling method is the basis for the coupling simulation of the atmosphere and ocean. To determine the optimal scattering sampling method for oceanic lidar simulation, we developed a polarized Monte Carlo model and simulated Mie scattering, Rayleigh scattering, and Petzold average-particle scattering experiments. This simulation model has been validated by comparison with Ramella-Roman's program [Opt. Express13, 4420 (2005)OPEXFF1094-408710.1364/OPEX.13.004420], with differences in reflectance and transmittance Stokes less than 1% in Mie scattering. The simulation results show these scattering sampling methods differ in runtime, scattering angle distributions, and reflectance and transmittance Stokes. Considering the current simulation accuracy of oceanic lidar, the differences in reflectance and transmittance Stokes are acceptable; thus, the runtime becomes the main evaluation factor. The one-point rejection method and scalar sampling method are preferable for the oceanic lidar polarized simulation. Under complex atmosphere-ocean coupling systems, scalar sampling methods may be a better choice since the calculation process of the sampling is independent of the incident Stokes vector.

Dual wavelength laser Doppler anemometer for simultaneous velocity and particulate size distribution measurements in submarine environments.

An in-situ laser Doppler current probe (LDCP) for the simultaneous measurements of the micro-scale subsurface current speed and the characterizations of micron particles is dedicated in this paper. The LDCP performs as an extension sensor for the state-of-the-art laser Doppler anemometry (LDA). The all-fiber LDCP utilized a compact dual wavelength (491 nm and 532 nm) diode pumped solid state laser as the light source to achieve the simultaneous measurements of the two components of the current speed. Besides its ability for the measurements of the current speed, the LDCP is also capable of obtaining the equivalent spherical size distribution of the suspended particles within small size range. The micro-scale measurement volume formed by two intersecting coherent laser beams makes it possible to accurately estimate the size distribution of the micron suspended particles with high temporal and spatial resolution. With its deployment during the field campaign at Yellow Sea, the LDCP has been experimentally demonstrated as an effective instrument to capture the micro-scale subsurface ocean current speed. The algorithm for retrieving the size distribution of the small suspended particles (2∼7.5µm) has been developed and validated. The combined LDCP system could be applied to the continuous long-term observations of plankton community structure, ocean water optical parameter over a wide range, and useful to elucidate the processes and interactions of the carbon cycles in the upper ocean.

Validation of the polarized Monte Carlo model of shipborne oceanic lidar returns.

The polarized Monte Carlo (PMC) model has been applied to study the backscattering measurement of oceanic lidar. This study proposes a PMC model for shipborne oceanic lidar simulation. This model is validated by the Rayleigh scattering experiment, lidar equation, and in-situ lidar LOOP (Lidar for Ocean Optics Profiler) returns [Opt. Express30, 8927 (2022)10.1364/OE.449554]. The relative errors of the simulated Rayleigh scattering results are less than 0.07%. The maximum mean relative error (MRE) of the simulated single scattering scalar signals and lidar equation results is 30.94%. The maximum MRE of simulated total scattering signals and LOOP returns in parallel and cross channels are 33.29% and 22.37%, respectively, and the maximal MRE of the depolarization ratio is 24.13%. The underwater light field of the laser beam is also simulated to illustrate the process of beam energy spreading. These results prove the validity of the model. Further analyses show that the measured signals of shipborne lidar LOOP are primarily from the particle single scatterings. This model is significant for analyzing the signal contributions from multiple scattering and single scattering.

Shipborne variable-FOV, dual-wavelength, polarized ocean lidar: design and measurements in the Western Pacific.

For the requirement of high-precision vertical profile of the polarization and optical properties of natural seawater, a ship-borne variable-FOV, dual-wavelength, polarized ocean lidar system is designed to obtain the volume linear depolarization ratio (VDR), color ratio and optical parameter profiles of seawater. With the high signal-to-noise ratio, which benefits from the high power (355 nm with 120 mJ, 532 nm with 200 mJ) solid-state laser and a photon counting recorder with a sampling rate of 1 GHz, the attenuated backscattered signal of seawater in the western Pacific campaign reaches to the depth of 50 m, where a plankton layer presents. The receiver of lidar is capable of switching to wide and narrow field of view (FOV), respectively, to obtain the lidar attenuation coefficient Klidar, which is in good agreement with the beam attenuation coefficient of seawater c with a narrow FOV and diffuse attenuation coefficient Kd with a wide FOV. Besides, the Klidar, and the VDR, at two wavelengths of 355 nm and 532 nm are compared to explore the possibility of multi-wavelength of laser application in the ocean lidar. The VDR and the color ratio profiles have a desirable correlation with the in-situ measurement of chlorophyll a (Chla) and chromophoric dissolved organic matter (CDOM) profiles, respectively. With the combination of the Klidar, the VDR and the color ratio profiles, measured in different regions and time periods during the campaign, the multi-wavelength and polarization lidar shows its potential to explore various ocean compositions, such as the ocean particles size shape, the species and vertical migration characteristics of planktons, and the profile distribution of the ocean compositions.

A Turbidity-Compensation Method for Nitrate Measurement Based on Ultraviolet Difference Spectroscopy.

To solve the problem that turbidity in water has a significant effect on the spectra of nitrate and reduces the accuracy of nitrate detection, a turbidity-compensation method for nitrate measurement based on ultraviolet difference spectra is proposed. The effect of turbidity on the absorption spectra of nitrate was studied by using the difference spectra of the mixed solution and a nitrate solution. The results showed that the same turbidity had different effects on the absorbance of different concentrations of nitrate. The change in absorbance due to turbidity decreased with an increase in the nitrate concentration at wavelengths from 200 nm to 230 nm, although this change was constant when the wavelength was greater than 230 nm. On the basis of this characteristic, we combined the residual sum of squares (RSS) and interval partial least squares (iPLS) to select wavelengths of 230-240 nm as the optimal modeling interval. Furthermore, the turbidity-compensation model was established by the linear fitting of the difference spectra of various levels of turbidity. The absorption spectra of the nitrate were extracted by subtracting the turbidity-compensation curve from the original spectra of the water samples, and the nitrate concentration was calculated by using a partial least squares (PLS)-based nitrate-prediction model. The experimental results showed that the average relative error of the nitrate predictions was reduced by 50.33% to 1.33% by the proposed turbidity-compensation method. This indicated that this method can better correct the deviation in nitrate's absorbance caused by turbidity and improve the accuracy of nitrate predictions.

Vicarious calibration of COCTS-HY1C at visible and near-infrared bands for ocean color application.

Remote sensing reflectance obtained from space-borne ocean color sensors is of great importance to carbon cycle and ocean-atmospheric interactions by providing biogeochemical parameters on the global scale using specific algorithms. Vicarious calibration is necessary for obtaining accurate remote sensing reflectance that meets the application demands of atmospheric correction algorithms. For ocean color sensors, vicarious calibration must be done prior to atmospheric correction. The third Chinese Ocean Color and Temperature Scanner (COCTS) aboard the HY1C satellite was launched on September 7, 2018, and it will provide essential ocean color data that will complement those of existing missions. We used field measurements from the Marine Optical Buoy (MOBY) and aerosol information provided by the MODerate Imaging Spectroradiometer (MODIS) aboard the Terra satellite to calculate vicarious calibration coefficients, and we further evaluated the applicability of the established vicarious calibration approach by cross-calibration using MODIS data on the global scale. Finally, the established vicarious calibration coefficients were used to retrieve the aerosol optical depth and remote sensing reflectance, which were compared to Aerosol Robotic Network-Ocean Color (AERONET-OC) data and MODIS-Terra and Ocean and Land Color Instrument (OLCI)-Sentinel-3A operational products. The results show that the vicarious calibration coefficients are relatively stable and reliable for all bands ranging from visible to near-infrared and can be used to obtain accurate high-quality data.

Atmospheric correction of HJ-1 CCD imagery over turbid lake waters.

We have presented an atmospheric correction algorithm for HJ-1 CCD imagery over Lakes Taihu and Chaohu with highly turbid waters. The Rayleigh scattering radiance (Lr) is calculated using the hyperspectral Lr with a wavelength interval 1nm. The hyperspectral Lr is interpolated from Lr in the central wavelengths of MODIS bands, which are converted from the band response-averaged Lr calculated using the Rayleigh look up tables (LUTs) in SeaDAS6.1. The scattering radiance due to aerosol (La) is interpolated from La at MODIS band 869nm, which is derived from MODIS imagery using a shortwave infrared atmospheric correction scheme. The accuracy of the atmospheric correction algorithm is firstly evaluated by comparing the CCD measured remote sensing reflectance (Rrs) with MODIS measurements, which are validated by the in situ data. The CCD measured Rrs is further validated by the in situ data for a total of 30 observation stations within ± 1h time window of satellite overpass and field measurements. The validation shows the mean relative errors about 0.341, 0.259, 0.293 and 0.803 at blue, green, red and near infrared bands.

Spectral variability of sea surface skylight reflectance and its effect on ocean color.

In this study, sea surface skylight spectral reflectance ρ(λ) was retrieved by means of the non-linear spectral optimization method and a bio-optical model. The spectral variability of ρ(λ) was found to be mainly influenced by the uniformity of the incident skylight, and a model is proposed to predict the ρ(λ) spectral dependency based on skylight reflectance at 750 nm. It is demonstrated that using the spectrally variable ρ(λ), rather than a constant, yields an improved agreement between the above-water remote sensing reflectance R(rs)(λ) estimates and concurrent profiling ones. The findings of this study highlight the necessity to re-process the relevant historical above-water data and update ocean color retrieval algorithms accordingly.

Atmospheric correction of satellite ocean color imagery using the ultraviolet wavelength for highly turbid waters.

Instead of the conventionally atmospheric correction algorithms using the near-infrared and shortwave infrared wavelengths, an alternative practical atmospheric correction algorithm using the ultraviolet wavelength for turbid waters (named UV-AC) is proposed for satellite ocean color imagery in the paper. The principle of the algorithm is based on the fact that the water-leaving radiance at ultraviolet wavelengths can be neglected as compared with that at the visible light wavelengths or even near-infrared wavelengths in most cases of highly turbid waters due to the strong absorption by detritus and colored dissolved organic matter. The UV-AC algorithm uses the ultraviolet band to estimate the aerosol scattering radiance empirically, and it does not need any assumption of the water's optical properties. Validations by both of the simulated data and in situ data show that the algorithm is appropriate for the retrieval of the water-leaving radiance in turbid waters. The UV-AC algorithm can be used for all the current satellite ocean color sensors, and it is especially useful for those ocean color sensors lacking the shortwave infrared bands. Moreover, the algorithm can be used for any turbid waters with negligible water-leaving radiance at ultraviolet wavelength. Based on our work, we recommend the future satellite ocean color remote sensors setting the ultraviolet band to perform the atmospheric correction in turbid waters.

[Study on using apparent spectrum to retrieve the inherent optical properties of ocean water].

The inherent optical properties are needed when establishing the semi-analytic model in the ocean color retrieval algorithm. Using the in-situ measurements, a retrieval model for inherent optical properties from remote sensing reflectance was established. The in-situ data measured in the 2003 spring cruise over the Yellow and East China Seas is introduced. The measurement method for remote sensing reflectance, particle backscattering and absorption coefficients are detailed. Based on the bio-optical model, the inherent optical properties were retrieved by optimization of Nelder-Mead simplex. The retrieval results of the absorption and backscattering coefficients for the material other than pure water were compared with the counterpart of the in-situ measurements. The comparison shows that the root-mean-square relative error for the absorption coefficient of materials other than water is less than 33%. The value is 30% for the particle backscattering coefficient. The analysis of the error shows that the retrieval model established in this paper can provide an efficient approach to retrieving the absorption and backscattering coefficients. The retrieval model can provide a reference for the application of remotely sensed data to the research on the bio-optical properties of Yellow and East China Seas.

[Influence of petroleum concentration in water on spectral backscattering coefficient].

The petroleum pollutants mixing proportion experiment and in-situ experiment were carried out in the estuary of Panjin, Liaoning province in May 2008 and August 2009. The optical properties and biochemical properties were measured to get the effect of petroleum concentration in water on backscattering coefficients spectrum. The results show that the power-law index of backscattering coefficient decreases as TSM concentration increases and the relationship of these variables follows logarithm mode. Specific backscattering coefficient's value of 440 to 856 nm is between 0.006 and 0.035 m2 x g(-1) and decreases as wavelength increases. The petroleum mass-specific backscattering coefficients (backscattering coefficients of unit petroleum concentration) decreases with the wavelength increasing and follows power law for petroleum concentration. Petroleum concentration has little effect on the power-law index of backscattering coefficient.