[1] We measured the absorption properties of phytoplankton, nonalgal particles (NAP), and colored dissolved organic matter (CDOM) at about 350 stations in various coastal waters around Europe including the English Channel, Adriatic Sea, Baltic Sea, Mediterranean Sea, and North Sea. For comparison, we also collected data in the open ocean waters of North Atlantic. The exponential slope of the CDOM absorption spectrum varied within a narrow range around 0.0176 nm−1 (SD = 0.0020 nm−1). When data from all the regions were considered altogether, the relationship between phytoplankton absorption and chlorophyll concentration was generally similar to the one previously established for open oceanic waters. Our coastal data, however, show that significant departures from the general trend may occur due to peculiar pigment composition and cell size. In some coastal areas, high phaeopigment concentrations gave rise to especially high blue-to-red ratio of phytoplankton absorption. The NAP absorption covaried with the particle dry weight. Most absorption spectra of these particles were well described by an exponential function with a slope averaging 0.0123 nm−1 (SD = 0.0013 nm−1). In some highly turbid waters, the spectra exhibited a signature possibly associated with iron oxides. In the Baltic Sea, NAP absorption systematically showed lower values at wavelengths shorter than 440 nm than predicted from the fitted exponential function. Overall, the variability in the absorption properties of European coastal waters showed some consistent patterns despite the high diversity of the examined waters. Distinct features were identified in the phytoplankton and NAP components. An absorption budget is presented and parameterizations are proposed.

https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2001JC000882

Variations in the light absorption coefficients of phytoplankton, nonalgal particles, and dissolved organic matter in coastal waters around Europe

Quantification of quality parameters of inland and near shore waters by means of remote sensing has encountered varying degrees of success in spite of the high variability of the parameters under consideration and limitations of remote sensors themselves. This paper com- prehensively evaluates the quantification of four types of water quality parameters: inorganic sediment particles, phytoplankton pigments, coloured dissolved organic material and Secchi disk depth. It concentrates on quantification requirements, as well as the options in selecting the most appropriate sensor data for the purpose. Relevant factors, such as quantification imple- mentation and validation of the quantified results are also extensively discussed. This review reveals that the relationship between in situ samples and their corresponding remotely sensed data can be linear or nonlinear, but are nearly always site-specific. The quantification has been attempted from terrestrial satellite data largely for suspended sediments and chlorophyll con- centrations. The quantification has been implemented through integration of remotely sensed imagery data, in situ water samples and ancillary data in a geographic information system (GIS). The introduction of GIS makes the quantification feasible for more variables at an increasingly higher accuracy. Affected by the number and quality of in situ samples, accuracy of quantifica- tion has been reported in different ways and varies widely.

Quantification of shallow water quality parameters by means of remote sensing

Modelling the impact of the Scheldt and Rhine/Meuse plumes on the salinity distribution in Belgian waters (southern North Sea)

Effect of humic substances on the iron speciation in natural waters by CLE/CSV

Terrestrial dissolved organic matter distribution in the North Sea

Regional and seasonal differences in light absorption by yellow substance in the Southern Bight of the North Sea

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Roderick E Warnock

Author Tools

Chat about Author

Papers

Regional and seasonal differences in light absorption by yellow substance in the Southern Bight of the North Sea