Estimating the economic potential for agricultural soil carbon sequestration in the Central United States using an aggregate econometric-process simulation model

Abstract

The purpose of this paper is to develop and apply a new method to assess economic potential for agricultural greenhouse gas mitigation. This method uses secondary economic data and conventional econometric production models, combined with estimates of soil carbon stocks derived from biophysical simulation models such as Century, to construct economic simulation models that estimate economic potential for carbon sequestration. Using this method, simulations for the central United States show that reduction in fallow and conservation tillage adoption in the wheat-pasture system could generate up to about 1.7 million MgC/yr, whereas increased adoption of conservation tillage in the corn–soy–feed system could generate up to about 6.2 million MgC/yr at a price of $200/MgC. About half of this potential could be achieved at relatively low carbon prices (in the range of $50 per ton). The model used in this analysis produced estimates of economic potential for soil carbon sequestration potential similar to results produced by much more data-intensive, field-scale models, suggesting that this simpler, aggregate modeling approach can produce credible estimates of soil carbon sequestration potential. Carbon rates were found to vary substantially over the region. Using average carbon rates for the region, the model produced carbon sequestration estimates within about 10% of those based on county-specific carbon rates, suggesting that effects of spatial heterogeneity in carbon rates may average out over a large region such as the central United States. However, the average carbon rates produced large prediction errors for individual counties, showing that estimates of carbon rates do need to be matched to the spatial scale of analysis. Transaction costs were found to have a potentially important impact on soil carbon supply at low carbon prices, particularly when carbon rates are low, but this effect diminishes as carbon prices increase.