Forest blue carbon sink accounting: methodological advancements and uncertainty analysis

Abstract

Mangroves, seagrass beds, and salt marshes represent key Blue Carbon Ecosystems (BCEs) that serve as vital carbon sinks, playing a crucial role in climate change mitigation. However, accurately quantifying blue carbon sequestration in these ecosystems remains challenging due to diverse environmental conditions, inconsistent methodologies, and substantial uncertainties. With the increasing urgency of global climate targets, reliable accounting methods are important for shaping policies and integrating blue carbon into carbon markets. In light of current needs, this review examined a range of carbon accounting methods, including isotopic methods, Unmanned Aerial Vehicles (UAVs), Remote Sensing (RS), modeling approaches (e.g., DeNitrification–DeComposition model (DNDC) and climate models), direct measurements (e.g., biomass sampling and eddy covariance), and Machine Learning (ML). Each method offers distinct advantages but also exhibits significant limitations, particularly in terms of cost, scalability, and spatial resolution. Moreover, the variability in carbon burial rates, methane (CH₄) and Nitrous Oxide (N₂O) emissions, and methodological assumptions were the sources of the greatest uncertainty. Although regional initiatives—such as Verra, Japan’s BlueCredit, Australia’s Blue Carbon Accounting Model (BlueCAM), and China’s Ministry of Natural Resources (MNR)—have implemented standardized procedures, a globally consistent framework is still lacking. Current blue carbon accounting methods face considerable uncertainties, mainly due to variations in environmental conditions, measurement techniques and Greenhouse Gas emissions (GHG), which limit their effectiveness in climate mitigation strategies and carbon credit markets. Therefore, future efforts should focus on integrating advanced technologies like RS, ML, and microsubs to harmonize global protocols, and improving ecosystem-specific data. Addressing these methodological gaps and strengthening monitoring frameworks will be pivotal for scaling up the role of BCEs in climate policy and carbon finance.

Keywords

Blue carbon / Modeling technique / Machine learning / UAVs / Coastal wetlands

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