Agricultural mitigation of greenhouse gases (GHG), via carbon sequestration and ag source emission reductions has been favorably regarded as a policy option for a variety of reasons: low cost, existing technology, ancillary environmental benefits and incentives for sustainable agriculture and rural development.  However, ag mitigation options have been slow to gain acceptance in current voluntary GHG offset markets as well as compliance systems (e.g. state and regional programs in the US, EU emissions trading system).  The primary barriers facing implementation of ag mitigation options in the US are related to effective quantification and accounting procedures.  Agricultural GHG emissions and C sequestration are challenging for a variety of reasons: emissions/removals are highly dispersed and variable in space and time, direct measurement methods are costly, technologically advanced and/or can have a low signal to noise ratio, and transaction costs, reporting and verification are potentially costly due to the large number of individual actors involved. 

While a variety of approaches for quantification and accounting systems of various emission/removal source categories have been proposed (e.g., broad-based emission factors vs direct measurement, regional performance standards vs ‘project-specific’ baselines), we suggest that farm-specific quantification and accounting approaches, based on farmer self-reporting and monitoring and sample-based verification procedures provide a robust approach for implementing agricultural mitigation programs.  Farm-scale quantification and self-reporting could provide efficient mitigation while streamlining monitoring, verification and other transactional functions in a networked environment.  A key to this approach are methods that are simple to use (without specialized training) but which can still capture fine-scale effects on GHG emissions associated with local climate and soil conditions and farm-specific land use history and current management.  

We review and characterize several farm- and field-level GHG estimation tools that are available or are under development, primarily in the US and in Europe.  We compare key features among systems including ease-of-use, comprehensiveness, scale and level of detail, quantification and uncertainty estimation.   Scenarios for different management systems and emission sources are presented and emission estimates from the different quantification tools are compared to results from relevant field experiments.