REDD+ projects have long been touted as a climate change solution. However, a UC Berkeley study funded by Carbon Market Watch reveals that only 1 out of every 13 credits represents a real emissions reduction.
The study “Error Log: Exposing the methodological failures of REDD+ forestry projects” concludes that REDD+ is not suitable for carbon offsetting and raises concerns about its impact on local communities and the environment.
What is REDD+
REDD+ stands for “Reducing Emissions from Deforestation and Forest Degradation.” It is an international initiative that incentivizes forest conservation to reduce carbon emissions and combat climate change.
At the end of 2022, there are over 620 individual REDD+ projects and programs implemented globally, backed by international donor organizations, such as the UN-REDD and the World Bank. For the same period, there were over 400 million REDD+ credit issuances, representing a quarter of total credits issued in the market.
Five Main Factors Influencing Carbon Credits
- Baseline Setting: The baseline is the estimated level of carbon emissions that would occur without the project. Accurate baselines are crucial for measuring a project’s effectiveness. The report shows that there’s a staggering 14x overestimation in baseline settings. This means that the highest baseline calculated for a given project was 14 times higher than the lowest, leading to inflated carbon credits.
- Leakage: This refers to the unintended increase in carbon emissions outside the project’s boundary due to its implementation. For example, if a project stops deforestation in one area, the activity might just move to another area. Current methodologies underestimate leakage, with an average rate of just 4.4%, affecting the overall effectiveness of the carbon credits.
- Forest Carbon Accounting: This involves calculating the amount of carbon stored in the forest that the project aims to protect. Overestimation in this area leads to more carbon credits being issued than are actually warranted. The report indicates a 23%-30% overestimation in forest carbon, which includes both aboveground and belowground carbon pools.
- Permanence: This factor considers the long-term viability of storing carbon in forests. Risks like wildfires, pests, and political instability can release stored carbon back into the atmosphere. These risks are often underestimated; for instance, natural risks are underestimated by more than a factor of 10. This affects the long-term credibility of the carbon credits.
- Safeguards: These are measures put in place to protect local communities and the environment from potential harm caused by REDD+ projects. Current VCS (Verified Carbon Standard) safeguards are weak and fall behind “best in class” consideration by international standards. This raises ethical concerns and questions the overall integrity of the projects.
The Baseline Dilemma: A Foundation of Over-Crediting
Baselines set the estimated emissions without the project. The study found that inflated baselines led to over-crediting, with results differing by more than 14x for a given project.
Recommendations:
- Implement Ex-Post Baseline Setting: Real-time data could correct inflated baselines, which are currently overestimated by 14x.
- Transparency is Key: All calculations should be publicly available, given the current lack of transparency.
- Third-Party Involvement: Independent analysts should set baselines, eliminating conflicts of interest.
Leakage: The Silent Saboteur
Leakage increases emissions outside a project’s boundary. The study found that the average leakage rate deducted by REDD+ projects is just 4.4%, far below the prescribed 10%-70%.
Recommendations:
- Standardize Leakage Identification: First and foremost, clearly define areas where deforestation is likely to shift, considering the current 4.4% average leakage rate.
- Tighten Exceptions: Subsequently, establish strict criteria, given that one out of four methodologies fails to include market leakage.
- Global Leakage: Lastly, include international factors, as all four assessed methodologies unfortunately ignore international leakage.
Forest Carbon Accounting: The Numbers Game
Carbon accounting is central to credit issuance. The study found a 23%-30% overestimation in forest carbon content, with belowground carbon overestimated by 61%.
Recommendations:
- Adopt Scientifically-Backed Equations: Use equations based on the latest research, given the current 23%-30% overestimation.
- Open-Source Data: Make all data publicly available, as not one of the 12 assessed projects shared their data.
- Quantify Uncertainty: Clearly communicate the 61% overestimation in belowground carbon.
Permanence: The Long-Term Risk
Permanence ensures long-term carbon storage. The study found that natural risks like wildfires are underestimated by more than a factor of 10.
Recommendations:
- Avoid Offsetting Fossil Fuels: Carbon storage in forests should not offset fossil fuel emissions, given the high risk of release.
- Base Risk on Science: Use scientific evidence, as natural risks are currently underestimated by more than a factor of 10.
- Revise Buffer Contributions: Make buffer pools more robust, given the current underestimation of risks.
Safeguards: The Missing Link
Safeguards protect against harm. The study found that VCS safeguards are less stringent than international standards like the IFC and GCF.
Recommendations:
- International Alignment: Adopt policies that meet or exceed international standards, given the current ambiguity in VCS rules.
- Rigorous Verification: Verification bodies should apply policies strictly, as they currently “rubber-stamp” projects.
- Grievance Mechanisms: Establish a free-of-charge, independent channel for grievances, given the current lack of accountability.
The UC Berkeley study serves as a wake-up call. By implementing its recommendations, we can improve REDD+ projects’ quality, effectiveness, and ethical standing.
The study provides a roadmap for making these projects more aligned with their intended goals, ensuring a meaningful contribution to the fight against climate change.