Index-Based Logistic Modeling: A New Approach to Assessing Biodegradability and Climate Change Mitigation Potential of Soil Pyrogenic Carbons.

We present a new model for predicting long-term microbially-mediated degradation characteristics, and subsequently the carbon sequestration potential, of different pyrogenic organic carbon (pyC) materials in fire-impacted/biochar-amended soils. The model uses the mean relative stability of the pyC material (R₅₀; to that of graphite), a heterogeneity factor (α; describing the distribution of carbon stabilities around the mean) and, an environment-specific kinetic function (β) to estimate the fraction of pyC remaining after a given time, t (in years). Time, t can be on the annual, decadal, centurial and millennial time scales. Testing of the model with data from two independent biochar biodegradation studies (a 1-year and a 5-year) indicated prediction errors on the order of 10-20% compared to measured pyC. In addition to the pyC remaining the model facilitates the 1) simple calculation of the half-life and mean residence time for the pyC material, 2) reconstruction/construction of degradation curves for pyC from different feedstock and, 3) development of refined classification scheme to quantitatively rank (and assign monetary value to) the carbon sequestration potential of different pyC materials. The advantages and limitations of the model will be discussed.