Addressing uncertainty in emissions and emissions reductions from deforestation and forest degradation taking into account natural variability and measurement capabilities: Case study for Panama and Zambia

Background/Question/Methods

Uncertainty in emissions and emission changes estimates constitutes an unresolved issue for a future international climate agreement. Uncertainty can be addressed ‘upstream’ through improvements in the technologies or techniques used to measure, report, and verify (MRV) emission reductions, or ‘downstream’ through the application of discount factors to more uncertain reductions. In the context of Reducing Emissions from Deforestation and forest Degradation (REDD+), we provide a diagnosis of the main sources of error to greenhouse gas estimation from land-cover change and overall error using Monte Carlo analysis, working with data from Panama, in Central America, and from Zambia, in Southern Africa. For Zambia, using new approaches in statistical modelling, we look at factors explaining the spatial variation in carbon stocks using national forest inventory, including species composition, environmental factors and land uses. For Panama, we look at the effects of forest monitoring improvements on reductions in uncertainty. We also test five downstream proposals for discounting uncertainty of the potential credits received for reducing emissions. We compare the potential compensation received for these emission reductions to the cost of alternative upstream investments in forest monitoring capabilities. 

Results/Conclusions

First, we find that upstream empirical improvements can noticeably reduce the overall uncertainty in emission reductions. Furthermore, the costs of upstream investments in empirical research for improved forest monitoring are relatively low compared to the potential benefits from carbon payments; they would allow Panama to receive higher financial compensation from more certain emission reductions. When uncertainty is discounted downstream, we find that the degree of conservativeness applied downstream has a major influence on both overall creditable emission reductions and on incentives for upstream forest monitoring improvements. Of the five downstream approaches that we analyze, only the Conservativeness Approach and the Risk Charge Approach provided consistent financial incentives to reduce uncertainty upstream. We provide policy relevant inputs for those countries to reduce uncertainty in estimates, taking into account natural variability and measurement errors. More generally, we provide recommendations on approaches to be used to address uncertainty in the REDD+ context.