The application of economic instruments to GHG emissions from dairy farms needs to rely on GHG indicators as actual emissions are impossible or extremely costly to measure. The choice of indicator impacts chosen abatement options, related costs and GHG actually emitted. A tool to quantify these relations is proposed which at its core consists of a highly detailed, mixed-integer dynamic programming model template able to cover a wide range of dairy farm characteristics and promising indicators. It allows deriving and comparing marginal abatement costs of GHGs emission for different farm types and indicators, informing the policy process about promising indicators, abatement strategies and related abatement and measurement costs.