Title
Potential of life cycle assessment to support environmental decision making at commercial dairy farms
Author
Faculty/Department
Faculty of Sciences. Bioscience Engineering
Publication type
article
Publication
Barking ,
Subject
Biology
Source (journal)
Agricultural systems. - Barking
Volume/pages
131(2014) , p. 105-115
ISSN
0308-521X
ISI
000343955300011
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Abstract
In this paper, we evaluate the potential of life cycle assessment (LCA) to support environmental decision making at commercial dairy farms. To achieve this, we follow a four-step method that allows converting environmental assessment results using LCA into case-specific advice for farmers. This is illustrated in a case-study involving 20 specialized Flemish dairy farms. Calculated LCA indicators are normalized into scores between 0 and 100, whereby a score of 100 is assumed optimal, to allow for a mutual comparison of indicators for different environmental impact categories. Next, major farm and management characteristics affecting environmental performance are identified using multiple regression and correlation analyses. Finally, comparing specific farm and management characteristics with those of best performing farms identifies farm-specific optimization strategies. We conclude that this approach complies with most of the identified critical success factors for the successful implementation of LCA as a decision support system for farmers. Key aspects herein are (i) the flexibility and accessibility of the model, (ii) the use of readily available farm data, (iii) farm advisors being intended model users, (iv) the identification of key farm and management characteristics affecting environmental performance and (v) the organization of discussion sessions involving farmers and farm advisors. However, attention should be paid (i) to provide sufficient training and guidance for farm advisors on the use of the applied LCA model and the interpretation of results, (ii) to evaluate the correctness of the used data and (iii) to keep the model up-to-date according to new scientific insights and knowledge concerning LCA methodology. (C) 2014 Elsevier Ltd. All rights reserved.
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