Uncertainty Quantification
Effective beginning 5/20/2025: Please note this site is under review and content may change.
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- Recommended Citations
Breidt, F. J., and S.M. Ogle. 2024. Chapter 8: Uncertainty quantification of greenhouse gas emissions. In Hanson, W.L., C. Itle, K. Edquist. (eds.). Quantifying greenhouse gas fluxes in agriculture and forestry: Methods for entity-scale inventory. Technical Bulletin Number 1939, 2nd edition. Washington, DC: U.S. Department of Agriculture, Office of the Chief Economist.
Chapter 8: Uncertainty Quantification for Entity-Scale Greenhouse Gas Emissions
If greenhouse gas (GHG) emissions were measured at the entity scale, the only uncertainty would be due to the measurement process. In nearly all cases, the emissions are instead estimated by calculation methods. These methods vary in complexity, but all are functions of activity data inputs and emission factors.
The simplest way to predict the GHG emissions from a single source at the entity scale is to multiply a known entity-scale activity data input by an entity-scale emission factor or set of factors. This is possible with some methods in this report; in those cases, the uncertainty in emission factors can be quantified and is provided in the description of the method. Examples include liming and carbon dioxide (CO2) emissions, indirect soil nitrous oxide (N2O) emissions, and non-CO2 emissions from field burning of agricultural residues.
The most complex methods described in this report involve models with many parameters that represent biogeochemical processes; for these methods, it is not feasible to derive uncertainty in the individual parameters. Uncertainty is instead quantified based on comparisons of model-based predictions to field measurements. Examples include cropland and grassland soil carbon stock changes and direct soil N2O emissions, which are predicted with the DayCent ecosystem model.
