The following discussion provides guidance on approaches for assessing uncertainty associated with estimates of biomass carbon for each tier method.
The sources of uncertainty when using the Tier 1 method include the degree of accuracy in land area estimates (see Chapter 3) and in the default biomass carbon increment and loss rates. Uncertainty is likely to be low (<10%) for estimates of area under different cropping systems since most countries annually estimate cropland area using reliable methods. A published compilation of research on carbon stocks in agroforestry systems was used to derive the default data provided in Table 5.1 (Schroeder, 1994). While defaults were derived from multiple studies, their associated uncertainty ranges were not included in the publication. Therefore, a default uncertainty level of +75% of the parameter value has been assigned based on expert judgement. This information can be used, with a measure of uncertainty in area estimates from Chapter 3 of this Report, to assess the uncertainty in estimates of carbon emissions and removals in Cropland biomass using the Tier 1 methodology. Guidance on uncertainty analysis is given in Volume 1, Chapter 3.
The Tier 2 method will reduce overall uncertainty because country-specific emission and removal factors rates should provide more accurate estimates of carbon increment and loss for crop systems and climatic regions within national boundaries. It is good practice to calculate error estimates (i.e., standard deviations, standard error, or ranges) for country-specific carbon increment rates and to use these variables in a basic uncertainty assessment. It is good practice for countries to assess error ranges in country-specific coefficients and compare them to those of default carbon accumulation coefficients. If country-specific rates have equal or greater error ranges than default coefficients, then it is good practice to use a Tier 1 approach and to further refine country-specific rates with more field measurements.
Tier 2 approaches may also use finer resolution activity data, such as area estimates for different climatic regions or for specific cropping systems within national boundaries. The finer-resolution data will further reduce uncertainty levels when associated with biomass carbon increment factors defined for those finer-scale land bases (e.g., when area of coffee plantations is multiplied by a coffee plantation coefficient, rather than by a generic agroforestry default).
Tier 3 approaches will provide the greatest level of certainty relative to Tiers 1 and 2 approaches. It is good practice to calculate standard deviations, standard errors, or ranges for all country-defined biomass increment and loss rates. It is good practice for countries to develop probability density functions for model parameters to use in Monte Carlo simulations. The uncertainty, particularly with respect to area estimates, is likely to be less or absent for cropping systems.
Was this article helpful?
Your Alternative Fuel Solution for Saving Money, Reducing Oil Dependency, and Helping the Planet. Ethanol is an alternative to gasoline. The use of ethanol has been demonstrated to reduce greenhouse emissions slightly as compared to gasoline. Through this ebook, you are going to learn what you will need to know why choosing an alternative fuel may benefit you and your future.