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<p>Independent evaluations have shown substantial over-issuance of REDD+ (Reducing Emissions from Deforestation and Degradation) credits traded on the voluntary carbon market. We synthesise these evaluations to estimate the additional forest conservation achieved by first-generation REDD+ projects and to identify mechanisms underlying over-crediting. We combine six independent ex post evaluations of avoided deforestation covering 44 REDD+ projects. These evaluations show that most projects reduced deforestation, but that they claimed an aggregate of 10.7 times more avoided deforestation than is justified by independent estimates. This discrepancy is not driven by the choice of forest cover data, but by selection bias in projects’ control areas and modelling approaches. Although recent initiatives that transfer assessment to unconflicted parties and restrict methodological flexibility are critical, they are insufficient. Ex post certification against credible counterfactuals is necessary if carbon markets are to represent causal reductions in&#xa0;deforestation.</p>

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Learning lessons from over-crediting to ensure additionality in forest carbon credits

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月11日

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  • Tom Swinfield,
  • Abby Williams,
  • David Coomes,
  • Michael Dales,
  • Patrick Ferris,
  • Alejandro Guizar-Coutiño,
  • James Hartup,
  • Jody Holland,
  • Sadiq Jaffer,
  • Julia P. G. Jones,
  • Miranda O. K. Lam,
  • Srinivasan Keshav,
  • Anil Madhavapeddy,
  • Eleanor Toye-Scott,
  • Thales A. P. West,
  • Andrew Balmford

摘要

Independent evaluations have shown substantial over-issuance of REDD+ (Reducing Emissions from Deforestation and Degradation) credits traded on the voluntary carbon market. We synthesise these evaluations to estimate the additional forest conservation achieved by first-generation REDD+ projects and to identify mechanisms underlying over-crediting. We combine six independent ex post evaluations of avoided deforestation covering 44 REDD+ projects. These evaluations show that most projects reduced deforestation, but that they claimed an aggregate of 10.7 times more avoided deforestation than is justified by independent estimates. This discrepancy is not driven by the choice of forest cover data, but by selection bias in projects’ control areas and modelling approaches. Although recent initiatives that transfer assessment to unconflicted parties and restrict methodological flexibility are critical, they are insufficient. Ex post certification against credible counterfactuals is necessary if carbon markets are to represent causal reductions in deforestation.