Predicting Dissolved Black Carbon Concentration From Chromophoric Dissolved Organic Matter Along the Land‐Ocean Continuum

Abstract Dissolved black carbon (DBC) plays a key role in global carbon cycle and pollutant transport. However, the time‐consuming and labor‐intensive chemical analysis limits its spatiotemporal resolution. Here, we developed models to predict DBC from chromophoric dissolved organic matter (CDOM) measurements across the land‐to‐ocean continuum. We found that the mean ratio of DBC to light absorbance at 254 nm ( a 254 ) changed <20% among different environments. However, a single‐wavelength model is inadequate for precise prediction due to microbial production of CDOM. Incorporating longer wavelengths using multiple linear regression improves model performance. Random Forest Regression using the full spectral range performed even better at all environments, including the open ocean, achieving a root mean square logarithmic error of <0.15, median symmetric accuracy of <10%, and R 2 of >0.85. This study demonstrates the feasibility of using CDOM to predict DBC concentrations and highlights the potential for in situ monitoring and remote sensing applications.

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Publication Details

Journal
Geophysical Research Letters
Published
2025-11-20
DOI
https://doi.org/10.1029/2025gl119009
Citations
1
Primary Topic
Marine and coastal ecosystems
Type
article
Field-Weighted Citation Impact
1.79

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article

Predicting Dissolved Black Carbon Concentration From Chromophoric Dissolved Organic Matter Along the Land‐Ocean Continuum

Ding He, Shuh‐Ji Kao, Lifeng Peng, Weifeng Yang et al.
1 citations
Geophysical Research Letters
Marine and coastal ecosystems
1.79
article

Predicting Dissolved Black Carbon Concentration From Chromophoric Dissolved Organic Matter Along the Land‐Ocean Continuum

Ding He, Shuh‐Ji Kao, Lifeng Peng, Weifeng Yang, Xiaoqian Zhan, Jutta Niggemann, Thorsten Dittmar, Shuwen Li, Julian Merder, Hongyan Bao, Weiqiang Zhao, Yuanbi Yi, Penghui Li, Ziming Fang, Keyuan Li
article en
1 citations

Abstract

Abstract Dissolved black carbon (DBC) plays a key role in global carbon cycle and pollutant transport. However, the time‐consuming and labor‐intensive chemical analysis limits its spatiotemporal resolution. Here, we developed models to predict DBC from chromophoric dissolved organic matter (CDOM) measurements across the land‐to‐ocean continuum. We found that the mean ratio of DBC to light absorbance at 254 nm ( a 254 ) changed <20% among different environments. However, a single‐wavelength model is inadequate for precise prediction due to microbial production of CDOM. Incorporating longer wavelengths using multiple linear regression improves model performance. Random Forest Regression using the full spectral range performed even better at all environments, including the open ocean, achieving a root mean square logarithmic error of <0.15, median symmetric accuracy of <10%, and R 2 of >0.85. This study demonstrates the feasibility of using CDOM to predict DBC concentrations and highlights the potential for in situ monitoring and remote sensing applications.

Geophysical Research LettersVol. 52(22)
Carl von Ossietzky Universität Oldenburg (DE), Sun Yat-sen University (CN), City University of Hong Kong (HK), Xiamen University (CN), Carnegie Institution for Science (US), Hong Kong University of Science and Technology (HK), Hainan University (CN), Helmholtz Institute for Functional Marine Biodiversity (DE), Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (CN), Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (CN)
Alexander von Humboldt-Stiftung, National Key Research and Development Program of China
Openalex Percentile: Top 12%
Marine and coastal ecosystems
1.79
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