Linking an Economic and a Life-cycle Analysis Biophysical Model
to Support Agricultural Greenhouse Gas Mitigation Policy

Vera Eory, Michael MacLeod, Shailesh Shrestha, David Roberts

Guest Editors: Martin Banse, Floor Brouwer, Ruslana Rachel Palatnik and Franz Sinabell
Published: 01.09.2014  〉 Volume 63 (2014), Number 3, 133-142  〉 Resort: Articles 
Submitted: N. A.   〉 Feedback to authors after first review: N. A.   〉 Accepted: N. A.

ABSTRACT

Greenhouse gas (GHG) mitigation is one of the main challenges facing agriculture, exacerbated by the increasing demand for food, in particular for livestock products. Production expansion needs to be accompanied by reductions in the GHG emission intensity of agricultural products, if significant increases in emissions are to be avoided. Suggested farm management changes often have systemic effects on farm, therefore their investigation requires a whole farm approach. At the same time, changes in GHG emissions arising offfarm in food supply chains (pre- or post-farm) can also occur as a consequence of these management changes. A modelling framework that quantifies the whole-farm, life-cycle effects of GHG mitigation measures on emissions and farm finances has been developed. It is demonstrated via a case study of sexed semen on Scottish dairy farms. The results show that using sexed semen on dairy farms might be a costeffective way to reduce emissions from cattle production by increasing the amount of lower emission intensity ‘dairy beef’ produced. It is concluded that a modelling framework combining a GHG life cycle analysis model and an economic model is a useful tool to help designing targeted agri-environmental policies at regional and national levels. It has the flexibility to model a wide variety of farm types, locations and management changes, and the LCA-approach adopted helps to ensure that GHG emission leakage does not occur in the supply chain.

CONTACT AUTHOR
VERA EORY
Research Division, SRUC, West Mains Road
Edinburgh, EH9 3JG, UK
e-mail: vera.eory@sruc.ac.uk
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