Determination of the absorption coefficient of chromophoric dissolved organic matter from underway spectrophotometry

CFSA-AGD: An accurate crosstalk fluorescence spectroscopic decomposition method for identifying and quantifying FDOMs in aquatic environments

Fluorescent substances exist in various aquatic environments and other environmental media. It is a critical task to identify the components accurately and quantify their contents precisely. Based on the Crosstalk Fluorescence Spectroscopy Analysis (CFSA) model, a fluorescence spectroscopic decomposition using the Alternating Gradient Descent (AGD) algorithm is developed. By reducing the residual error of the model through alternating iterations, the CFSA-AGD method achieves unsupervised model training and automatic spectroscopic decomposition without extra experimental operations such as dilution or absorbance measurement, exempting from tedious modeling process. The objectives of this work are to validate that the CFSA-AGD method can comprehensively address the decomposition of fluorescence spectral crosstalk. Furthermore, the novel method is applied to the spectroscopic decomposition of natural FDOMs in aquatic environments as a standard tool. The spectral data analyzing the performance of this method is verified and compared with the conventional methods through the experiment on standard samples. The results indicate that CFSA-AGD has higher spectroscopic decomposition accuracy and gives more abundant information on the characteristic spectra with less residual error than parallel factor analysis. This means that the fluorescence spectra of natural FDOMs can be decomposed into the characteristic fluorescence emission spectra of single components with higher accuracy and the characteristic fluorescence absorption spectra that cannot be obtained by the conventional methods. Meanwhile, it improves the analytical precision of the contents (from R² ≥ 0.9778 to R² ≥ 0.9920) and reduces the ultimate residual error by two orders of magnitude (from 1.42 × 10^-1 to 4.68 × 10^-3) when the method is used to estimate the measured fluorescence spectra.

Drivers of spectral optical scattering by particles in the upper 500 m of the Atlantic Ocean

Optical models have been proposed to relate spectral variations in the beam attenuation (c_p) and optical backscattering (b_bp) coefficients to marine particle size distributions (PSDs). However, due to limited PSD data, particularly in the open ocean, optically derived PSDs suffer from large uncertainties and we have a poor empirical understanding of the drivers of spectral c_p and b_bp coefficients. Here we evaluated PSD optical proxies and investigated their drivers by analyzing an unprecedented dataset of co-located PSDs, phytoplankton abundances and optical measurements collected across the upper 500 m of the Atlantic Ocean. The spectral slope of c_p was correlated (r>0.59) with the slope of the PSD only for particles with diameters >1 µm and also with eukaryotic phytoplankton concentrations. No significant relationships between PSDs and the spectral slope of b_bp were observed. In the upper 200 m, the b_bp spectral slope was correlated to the light absorption by particles (a_p; r<-0.54) and to the ratio of cyanobacteria to eukaryotic phytoplankton. This latter correlation was likely the consequence of the strong relationship we observed between a_p and the concentration of eukaryotic phytoplankton (r=0.83).

Satellite Ocean Colour: Current Status and Future Perspective

Spectrally resolved water-leaving radiances (ocean colour) and inferred chlorophyll concentration are key to studying phytoplankton dynamics at seasonal and interannual scales, for a better understanding of the role of phytoplankton in marine biogeochemistry; the global carbon cycle; and the response of marine ecosystems to climate variability, change and feedback processes. Ocean colour data also have a critical role in operational observation systems monitoring coastal eutrophication, harmful algal blooms, and sediment plumes. The contiguous ocean-colour record reached 21 years in 2018; however, it is comprised of a number of one-off missions such that creating a consistent time-series of ocean-colour data requires merging of the individual sensors (including MERIS, Aqua-MODIS, SeaWiFS, VIIRS, and OLCI) with differing sensor characteristics, without introducing artefacts. By contrast, the next decade will see consistent observations from operational ocean colour series with sensors of similar design and with a replacement strategy. Also, by 2029 the record will start to be of sufficient duration to discriminate climate change impacts from natural variability, at least in some regions. This paper describes the current status and future prospects in the field of ocean colour focusing on large to medium resolution observations of oceans and coastal seas. It reviews the user requirements in terms of products and uncertainty characteristics and then describes features of current and future satellite ocean-colour sensors, both operational and innovative. The key role of in situ validation and calibration is highlighted as are ground segments that process the data received from the ocean-colour sensors and deliver analysis-ready products to end-users. Example applications of the ocean-colour data are presented, focusing on the climate data record and operational applications including water quality and assimilation into numerical models. Current capacity building and training activities pertinent to ocean colour are described and finally a summary of future perspectives is provided.

Retrieval of Phytoplankton Pigments from Underway Spectrophotometry in the Fram Strait

Phytoplankton in the ocean are extremely diverse. The abundance of various intracellular pigments are often used to study phytoplankton physiology and ecology, and identify and quantify different phytoplankton groups. In this study, phytoplankton absorption spectra ( a p h ( λ ) ) derived from underway flow-through AC-S measurements in the Fram Strait are combined with phytoplankton pigment measurements analyzed by high-performance liquid chromatography (HPLC) to evaluate the retrieval of various pigment concentrations at high spatial resolution. The performances of two approaches, Gaussian decomposition and the matrix inversion technique are investigated and compared. Our study is the first to apply the matrix inversion technique to underway spectrophotometry data. We find that Gaussian decomposition provides good estimates (median absolute percentage error, MPE 21–34%) of total chlorophyll-a (TChl-a), total chlorophyll-b (TChl-b), the combination of chlorophyll-c1 and -c2 (Chl-c1/2), photoprotective (PPC) and photosynthetic carotenoids (PSC). This method outperformed one of the matrix inversion algorithms, i.e., singular value decomposition combined with non-negative least squares (SVD-NNLS), in retrieving TChl-b, Chl-c1/2, PSC, and PPC. However, SVD-NNLS enables robust retrievals of specific carotenoids (MPE 37–65%), i.e., fucoxanthin, diadinoxanthin and 19 ′ -hexanoyloxyfucoxanthin, which is currently not accomplished by Gaussian decomposition. More robust predictions are obtained using the Gaussian decomposition method when the observed a p h ( λ ) is normalized by the package effect index at 675 nm. The latter is determined as a function of “packaged” a p h ( 675 ) and TChl-a concentration, which shows potential for improving pigment retrieval accuracy by the combined use of a p h ( λ ) and TChl-a concentration data. To generate robust estimation statistics for the matrix inversion technique, we combine leave-one-out cross-validation with data perturbations. We find that both approaches provide useful information on pigment distributions, and hence, phytoplankton community composition indicators, at a spatial resolution much finer than that can be achieved with discrete samples.

Low-Cost Automatic Sensor for in Situ Colorimetric Detection of Phosphate and Nitrite in Agricultural Water

This study proposed a low-cost sensor for in situ automatic monitoring of phosphate and nitrite in agricultural water environments, involving a series of "Fish-Bite" reservoirs, multiple reagent capsules, and a colorimetric sensor. The Fish-Bite reservoir is an alternative to the pumps, valves, and filters that are widely used for water sample collection and also offers a closed cell for chromogenic reactions afterward. Up to two capsules can be embedded in each reservoir to support chromogenic reactions that use two different reagents in sequence. From the results of calibration tests in the laboratory, the limit of detection was found to be approximately 0.01 mg/L for both phosphate and nitrite, with a linear range of 0.01-1.00 mg/L for phosphate and 0.01-0.20 mg/L for nitrite. Furthermore, an in situ experiment was successfully carried out in an irrigation canal beside farmland to demonstrate the practicability and robustness of the device. The averaged concentrations of phosphate and nitrite were 0.0113 mg/L and 0.0383 mg/L, respectively. The relative deviations were 20.2% and 11.7%, respectively, referred to results obtained by using the standard spectrophotometric methods. With the advantages of being robust, fast, and low cost, this in situ device is promising for the formation of agricultural sensor networks.

MERIS observations of phytoplankton phenology in the Baltic Sea

The historical data from the MEdium Resolution Imaging Spectrometer (MERIS) is an invaluable archive for studying global waters from inland lakes to open oceans. Although the MERIS sensor ceased to operate in April 2012, the data capacities are now re-established through the recently launched Sentinel-3 Ocean and Land Colour Instrument (OLCI). The development of a consistent time series for investigating phytoplankton phenology features is crucial if the potential of MERIS and OLCI data is to be fully exploited for inland water monitoring. This study presents a time series of phytoplankton abundance and bloom spatial extent for the highly eutrophic inland water of the Baltic Sea using the 10-year MERIS archive (2002-2011) and a chlorophyll-a based Summed Positive Peaks (SPP) algorithm. A gradient approach in conjunction with the histogram analysis was used to determine a global threshold from the entire collection of SPP images for identifying phytoplankton blooms. This allows spatio-temporal dynamics of daily bloom coverage, timing, phytoplankton abundance and spatial extent to be investigated for each Baltic basin. Furthermore, a number of meteorological and hydrological variables, including spring excess phosphate, summer sea surface temperature and photosynthetically active radiation, were explored using boosted regression trees and generalised additive models to understand the ecological response of phytoplankton assemblages to environmental perturbations and potential predictor variables of summer blooms. The results indicate that the surface layer excess phosphate available in February and March had paramount importance over all other variables considered in governing summer bloom abundance in the major Baltic basins. This finding allows new insights into the development of early warning systems for summer phytoplankton blooms in the Baltic Sea and elsewhere.

Underway spectrophotometry in the Fram Strait (European Arctic Ocean): a highly resolved chlorophyll a data source for complementing satellite ocean color

Satellite remote sensing of chlorophyll a concentration (Chl-a) in the Arctic Ocean is spatially and temporally limited and needs to be supplemented and validated with substantial volumes of in situ observations. Here, we evaluated the capability of obtaining highly resolved in situ surface Chl-a using underway spectrophotometry operated during two summer cruises in 2015 and 2016 in the Fram Strait. Results showed that Chl-a measured using high pressure liquid chromatography (HPLC) was well related (R2 = 0.90) to the collocated particulate absorption line height at 676 nm obtained from the underway spectrophotometry system. This enabled continuous surface Chl-a estimation along the cruise tracks. When used to validate Chl-a operational products as well as to assess the Chl-a algorithms of the aqua moderate resolution imaging spectroradiometer (MODIS-A) and Sentinel-3 Ocean Land Color Imager (OLCI) Level 2 Chl-a operational products, and from OLCI Level 2 products processed with Polymer atmospheric correction algorithm (version 4.1), the underway spectrophotometry based Chl-a data sets proved to be a much more sufficient data source by generating over one order of magnitude more match-ups than those obtained from discrete water samples. Overall, the band ratio (OCI, OC4) Chl-a operational products from MODIS-A and OLCI as well as OLCI C2RCC products showed acceptable results. The OLCI Polymer standard output provided the most reliable Chl-a estimates, and nearly as good results were obtained from the OCI algorithm with Polymer atmospheric correction method. This work confirms the great advantage of the underway spectrophotometry in enlarging in situ Chl-a data sets for the Fram Strait and improving satellite Chl-a validation and Chl-a algorithm assessment over discrete water sample analysis in the laboratory.