LBNL Report Number
Carbon forestry mitigation potential estimates at the global level are limited by the absence or simplicity of national level estimates, and similarly national-level estimates are limited by absence of regional-level estimates. The present study aims to estimate the mitigation potential for a large diverse country such as India, based on the GTAP global land classification system of agro-ecological zones (AEZs), as well the Indian AEZ system. The study also estimates the implications of carbon price incentive (US$50 and $100) on mitigation potential in the short-, medium-, and long-term, since afforestation and reforestation (A&R) is constrained by lack of investment and financial incentives. The mitigation potential for short and long rotation plantations and natural regeneration was estimated using the GCOMAP global forest model for two land area scenarios. One scenario included only wastelands (29 Mha), and the second enhanced area scenario, included wastelands plus long fallow and marginal croplands (54 Mha). Under the $100 carbon price case, significant additional area (3.6 Mha under the waste land scenario and 6.4 Mha under the enhanced area scenario) and carbon mitigation is gained in the short-term (2025) compared to the baseline when using the GTAP land classification system. The area brought under A&R increases by 85 to 100% for the $100 carbon price compared to $50 carbon price in the short-term, indicating the effectiveness of higher carbon price incentives, especially in the short-term. A comparison of estimates of mitigation potential using GTAP and Indian AEZ land classification systems showed that in the short-term, 35% additional C-stock gain is achieved in the $100 carbon price case in the enhanced area scenario of the Indian AEZ system. This difference highlights the role of the land classification system adopted in estimation of aggregate mitigation potential estimates, particularly in the short-term. Uncertainty involved in the estimates of national level mitigation potential needs to be reduced, by generating reliable estimates of carbon stock gain and losses, and cost and benefit data, for land use sector mitigation options at a scale disaggregated enough to be relevant for national mitigation planning.