Estimating the opportunity costs of reducing carbon dioxide emissions via avoided deforestation, using integrated assessment modelling

Estimates show that, in recent years, deforestation and forest degradation accounted for about 17% of global greenhouse gas emissions. The implementation of REDD (Reducing Emissions from Deforestation and Forest Degradation in Developing Countries) is suggested to provide substantial emission reductions at low costs, although cost estimates show large uncertainty. Cost estimates can differ, as they depend on the approach chosen, for example: giving an economic stimulus to entire countries, taking landowners as actors in a REDD framework, or starting from protecting carbon-rich areas. This last approach was chosen for this analysis. Proper calculation of the economic cost requires an integrated modelling approach involving biophysical impact calculations and their associated economic effects. To date, only a few global modelling studies have applied such an approach. In modelling REDD measures, the actual implementation of REDD can take many forms, with implications for the results. This study assumes that non-Annex I countries will protect carbon-rich areas against deforestation, and therefore will refrain from using these areas as agricultural land. The opportunity costs of reducing deforestation within the framework of REDD were assessed using an integrated economic and land-use modelling approach comprising the global economic LEITAP model and the biophysical IMAGE model. One of the main methodological challenges is the representation of land use and the possibility to convert woodlands land into agricultural land. We endogenised the availability of agricultural land by introducing a flexible land supply curve, and represented the implementation of REDD policies as a reduction in the maximum amount of unmanaged land that potentially would be available for conversion to agriculture, in various regions in the world. In a series of model experiments, carbon-rich areas in non-Annex I countries were protected from deforestation. In each consecutive scenario the protected area was increased, starting off with the most carbon rich lands, worldwide systematically working down to areas with less carbon storage. The associated opportunity costs, expressed in terms of GDP reduction, were calculated with the economic LEITAP model. The resulting net reduction in carbon dioxide emissions from land-use change was calculated with the IMAGE model. From the sequence of experiments, marginal cost curves were constructed, relating carbon dioxide emission reductions to the opportunity costs. The results showed that globally a maximum of around 2.5 Gt carbon dioxide emissions could be avoided, annually. However, regional differences in opportunity costs are large and were found to range from about 0 to 3.2 USD per tonne carbon dioxide in Africa, 2 to 9 USD in South America and Central America, and 20 to 60 USD in Southeast Asia. These results are comparable to other studies that have calculated these costs, in terms of both opportunity costs and the regional distribution of emissions reduction