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This paper examines the relationships between the marginal abatement costs ( MAC) of greenhouse gas ( GHG) emissions on dairy farms and factors such as herd size, milk yield and available farm labour, on the one hand, and prices, GHG indicators and GHG reduction levels, on the other. A two-stage Heckman procedure is used to estimate these relationships from a systematically designed set of simulations with a highly detailed mixed integer bio-economic farm-level model. The resulting meta-models are then used to analyse how MAC vary across farm-level conditions and GHG measures. We find that simpler GHG indicators lead to significantly higher MAC, and that MAC strongly increase beyond a 1-5% emission reduction, depending on farm attributes and the chosen indicator. MAC decrease rapidly with increasing farm size, but the effect levels off beyond a herd size of 40 cows. As expected, the main factors driving gross margins per dairy cow also significantly influence mitigation costs. Our results indicate high variability of MAC on real life farms. In contrast to time consuming simulations with the complex mixed integer bio-economic programming model, the meta-models allow the distribution of MAC in a farm population to be efficiently derived and thus could be used to upscale to regional or sector level. [ABSTRACT FROM AUTHOR]

There is broad debate about including agriculture in greenhouse gas (GHG) reduction efforts such as the European Emissions Trading Scheme. Since most agricultural GHG emissions originate from non-point sources, they cannot be directly measured, and therefore have to be derived by calculation schemes (indicators). We designed five such GHG indicators for dairy farms and analyzed the trade-offs between their feasibility, measurement accuracy, and level of induced abatement costs. Analyses of induced abatement costs and calculation accuracy are based on emission reduction simulations with a highly-detailed single-farm optimization model. Feasibility is discussed in a qualitative manner. Our results indicate that the trade-offs depend on both farm characteristics and the targeted reduction level. In particular, the advantages of detailed indicators decrease for higher abatement levels. Only the least feasible indicator led to abatement costs that would result in emission efforts at given prices in the European Emissions Trading Scheme, although with a rather small potential. Our results thus suggest little potential for including dairy production into market-based reduction policies. [ABSTRACT FROM AUTHOR]

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