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Open AccessArticle

Clean Technologies in Agriculture—How to Prioritise Measures?

1
Institute of Natural Resource Sciences, Zurich University of Applied Sciences, 8820 Wädenswil, Switzerland
2
Former Student at Institute of Natural Resource Sciences, Zurich University of Applied Sciences, 8820 Wädenswil, Switzerland
*
Author to whom correspondence should be addressed.
Sustainability 2017, 9(8), 1303; https://doi.org/10.3390/su9081303
Received: 19 May 2017 / Revised: 14 July 2017 / Accepted: 21 July 2017 / Published: 26 July 2017
(This article belongs to the Special Issue 6th World Sustainability Forum - Selected Papers)
As agriculture continues to be under pressure due to its negative environmental impacts, resource-efficiency and the use of clean technologies gain importance. Meanwhile, there is an abundance of technological solutions that help “clean” agriculture’s hotspots, either by reducing inputs, by producing renewable energy or by protecting ecosystems. Decisions about clean technologies remain difficult due to the variety of options, difficulties in cost-benefit calculations, and potential trade-offs in sustainability. We therefore addressed the issue of decision-making regarding clean technologies in agriculture. A multi-criteria decision analysis (MCDA) was used to rank the most sustainable technologies. Evaluation of 17 selected clean technologies was based on literature information and expert opinion. Wireless sensor irrigation networks, frequency converters for vacuum pumps and stable air conditioning, PV electricity and drip irrigation were the five technologies with the highest sustainability scores, outperforming the 12 other clean technologies. When all sustainability dimensions and criteria were equally weighted, PV electricity was superseded by variable speed drive technology for irrigation in the top five. This paper shows that MCDAs are a useful method for choosing between sustainable clean technology options. By applying different weighting, the MCDA can reflect the priorities of the decision maker and provide customised results. View Full-Text
Keywords: clean technologies; MCDA; analytic hierarchy process; agriculture clean technologies; MCDA; analytic hierarchy process; agriculture
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MDPI and ACS Style

Scharfy, D.; Boccali, N.; Stucki, M. Clean Technologies in Agriculture—How to Prioritise Measures? Sustainability 2017, 9, 1303. https://doi.org/10.3390/su9081303

AMA Style

Scharfy D, Boccali N, Stucki M. Clean Technologies in Agriculture—How to Prioritise Measures? Sustainability. 2017; 9(8):1303. https://doi.org/10.3390/su9081303

Chicago/Turabian Style

Scharfy, Deborah; Boccali, Norman; Stucki, Matthias. 2017. "Clean Technologies in Agriculture—How to Prioritise Measures?" Sustainability 9, no. 8: 1303. https://doi.org/10.3390/su9081303

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