Assessing methodological consistency of forest carbon quantification in REDD+ projects in the Brazilian Amazon

REDD+ projects play a central role in climate mitigation, particularly in the Brazilian Amazon, where deforestation remains a major source of greenhouse gas emissions. Despite their relevance, concerns persist regarding the methodological consistency of carbon quantification approaches adopted across projects. Here, we evaluated the methodological consistency of 35 REDD+ projects developed under Verra's Verified Carbon Standard (VCS) in the Brazilian Amazon, focusing on carbon stock estimation. We examined the inclusion of carbon pools, data levels adopted, primary data sources, carbon fraction values, post-deforestation land-use classes, and key forest inventory parameters. We observed a strong focus on mandatory woody carbon pools, with limited inclusion of additional pools such as dead wood and wood products (∼30% of projects) and litter, non-woody biomass, and soil organic carbon (each in fewer than 6% of projects). Secondary data sources are widely used, especially for above- and below-ground woody biomass, a pattern largely driven by the predominance of VM0015 projects (24 of 35) relying on national or global default datasets. Carbon fraction values were predominantly based on IPCC defaults, with limited adoption of regionally derived estimates. Post-deforestation scenarios were characterized by simplified land-use classes, frequently supported by Tier 1 or Tier 2 data. Among the 17 projects that conducted forest inventories, we observed convergence toward common methodological choices, including minimum diameter thresholds of 10–15 cm, plot sizes around 0.25 ha or 1 ha, and a small number of well-established allometric equations. Our results reveal considerable heterogeneity in methodological choices alongside high standardization in key parameters, highlighting the need for clearer guidance, increased field-based data, and greater regionalization of parameters to strengthen the environmental integrity of REDD+ projects in the Amazon.