Biogeosciences
Biogeosciences
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Articles | Volume 22, issue 15
Articles | Volume 22, issue 15
https://doi.org/10.5194/bg-22-3769-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-22-3769-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 22, issue 15
Research article
 | 
05 Aug 2025
Research article |  | 05 Aug 2025

Improved understanding of nitrate trends, eutrophication indicators, and risk areas using machine learning

Deep S. Banerjee and Jozef Skákala

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Short summary
Nitrate is a crucial nutrient in oceans, whose excess can trigger uncontrolled algae growth that damages marine ecosystems. We used machine learning to generate skilled, gap-free, bi-decadal surface nitrate data from sparse observations, revealing areas on the North-West European Shelf that are more vulnerable to excess algae growth if nutrient pollution occurs. We also looked at bi-decadal trends in coastal nitrate and the impact of winter nitrate on spring phytoplankton blooms.
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