Multifunctional Ecological Footprint Analysis for assessing eco-efficiency: a case study of fruit production systems in Northern Italy

Abstract

Sustainable farming in the fruit production systems of the Piemonte Region of Northern Italy was examined using a multifunctional Ecological Footprint based method. The analysis is based on the quantification of four different ecological footprint applications related to different functional units:tons of product, nutrient content in the fruit produced, hectare of crop and 1000 € of revenue. Of the major fruit production in the region, apricot and nectarine show the best overall performance from an ecological and economic point of view. This result is mainly due to the low input requirements of the cultivation processes, combined with a good product mass and the high market value of the fruit.Kiwifruit production had the worst overall ranking due to the high requirement of agronomical inputs and a low market value of the final product. The problems and the key aspects of a multifunctional assessment are discussed from a methodological point of view. Results highlight that standard Ecological Footprint Analysis alone would not allowed to evaluate the complete environmental profile of the different production systems.

Life Cycle Based Evaluation of Environmental and Economic Impacts of Agricultural Productions in the Mediterranean Area

“…Results on apple cultivation are consistent with those found in other LCA studies of conventional apple orchards (0.06-0.09 kg CO2eq./kg of product) [52,53].…”

Principles Guiding Practice: A Case Study Analysis of the Principles of Sustainable Agriculture for Diverse Farms

“…Although comparative case studies are used in many sciences (Smerdon, Cook, Cook, & Seager, 2015;Zimmermann, Aurich, Graziano, & Fuertes, 2014), there is not a large body of literature about sustainable agriculture that uses the case study design. However, there are some studies that extend beyond description to comparison and explanation, which was our objective (Bisht et al, 2014;Boogaard, Oosting & Bock, 2008;Cerutti, Beccaro, Bagliani, Donno, & Bounous, 2013;Crivits & Paredis, 2013;Davies-Jones, 2011;Girard, Magda, Nosedaz & Sarandon, 2015).…”

Using eco-efficiency as an indicator for sustainable urban development: A case study of Chinese provincial capital cities

“…To date, the applications of eco-efficiency have included products (Cerutti et al, 2013;Quariguasi-Frota-Neto and Bloemhof-Ruwaard, 2012), enterprises (Fernández-Viñé et al, 2013;Hahn et al, 2010) and industry sections (Oggioni et al, 2011;Wang et al, 2011). It was recently extended to a regional scale (Kielenniva et al, 2012;Yu et al, 2013) in an attempt to develop the potential of individual regions.…”

“…The first class is the single-ratio model of 'economic output/environmental impact', which has been widely accepted and aggregates different environmental emissions into one score using life cycle analysis. The single-ratio model is easy to understand and communicate and is mainly used for the eco-efficiency analysis of product (Cerutti et al, 2013) and technology (Burchart-Korol et al, 2013). The second class substitutes the numerator with other composite indicators representing the ecological performance of the system, such as emergy indicators (Li et al, 2011), ecological footprint indicators (Cerutti et al, 2013) and material flow analysis indicators (Seppälä et al, 2005).…”

“…The single-ratio model is easy to understand and communicate and is mainly used for the eco-efficiency analysis of product (Cerutti et al, 2013) and technology (Burchart-Korol et al, 2013). The second class substitutes the numerator with other composite indicators representing the ecological performance of the system, such as emergy indicators (Li et al, 2011), ecological footprint indicators (Cerutti et al, 2013) and material flow analysis indicators (Seppälä et al, 2005). The third class uses models to calculate eco-efficiency; some of the key methods of aggregation employed are principal components analysis (Jollands et al, 2004), factor analysis (Singh et al, 2012) and positive matrix factorisation (Wu et al, 2012).…”