RESUMO
Understanding greenhouse gas mitigation potential of the U.S. agriculture and forest sectors is critical for evaluating potential pathways to limit global average temperatures from rising more than 2° C. Using the FASOMGHG model, parameterized to reflect varying conditions across shared socioeconomic pathways, we project the greenhouse gas mitigation potential from U.S. agriculture and forestry across a range of carbon price scenarios. Under a moderate price scenario ($20 per ton CO2 with a 3% annual growth rate), cumulative mitigation potential over 2015-2055 varies substantially across SSPs, from 8.3 to 17.7 GtCO2e. Carbon sequestration in forests contributes the majority, 64-71%, of total mitigation across both sectors. We show that under a high income and population growth scenario over 60% of the total projected increase in forest carbon is driven by growth in demand for forest products, while mitigation incentives result in the remainder. This research sheds light on the interactions between alternative socioeconomic narratives and mitigation policy incentives which can help prioritize outreach, investment, and targeted policies for reducing emissions from and storing more carbon in these land use systems.
RESUMO
The Forestry and Agriculture Sector Optimization Model with Greenhouse Gases (FASOMGHG) has historically relied on regional average costs of land conversion to simulate land use change across cropland, pasture, rangeland, and forestry. This assumption limits the accuracy of the land conversion estimates by not recognizing spatial heterogeneity in land quality and conversion costs. Using data from Nielsen et al. (2014), we obtained the afforestation cost per county, then estimated nonparametric regional marginal cost functions for land converting to forestry. These afforestation costs were then incorporated into FASOMGHG. Three different assumptions for land moving into the forest sector (constant average conversion cost, static rising marginal costs, and dynamic rising marginal cost) were run in order to assess the implications of alternative land conversion cost assumptions on key outcomes, such as projected forest area and cropland use, carbon sequestration, and forest product output.
RESUMO
The United States has recently set ambitious national goals for greenhouse gas (GHG) reductions over the coming decades. A portion of these reductions are based on expected sequestration and storage contributions from land use, land use change, and forestry (LULUCF). Significant uncertainty exists in future forest markets and thus the potential LULUCF contribution to US GHG reduction goals. This study seeks to inform the discussion by modeling US forest GHG accounts per different simulated demand scenarios across a grid of over 130,000 USDA Forest Service Forest Inventory and Analysis (FIA) forestland plots over the conterminous United States. This spatially disaggregated future supply is based on empirical yield functions for log volume, biomass and carbon. Demand data is based on a spatial database of over 2300 forest product manufacturing facilities representing 11 intermediate and 13 final solid and pulpwood products. Transportation costs are derived from fuel prices and the locations of FIA plot from which a log is harvested and mill or port destination. Trade between mills in intermediate products such as sawmill residues or planer shavings is also captured within the model formulation. The resulting partial spatial equilibrium model of the US forest sector is solved annually for the period 2015-2035 with demand shifted by energy prices and macroeconomic indicators from the US EIA's Annual Energy Outlook for a Reference, Low Economic Growth, and High Economic Growth case. For each macroeconomic scenario simulated, figures showing historic and scenario-specific live tree carnon emissions and sequestration are generated. Maps of the spatial allocation of both forest harvesting and related carbon fluxes are presented at the National level and detail is given for both regions and ownerships.
