The ICCEE Toolbox. A Holistic Instrument Supporting Energy Efficiency of Cold Food and Beverage Supply Chains

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Abstract

Cold supply chains of food and beverage sectors represent one of the main drivers of the EU total final energy consumption. Within this context, food quality losses, changes in temperature regimes, energy use, environmental burdens, and the economic viability of energy efficiency measures are essential aspects to consider for improving cold supply chains' overall sustainability. This paper presents a dedicated toolbox, developed within the Horizon 2020 project ICCEE, for supporting decision-making and actors to assess energy efficiency path within a specific type of food cold-supply (i.e., meat, fish, milk and cheese products, fruits, and vegetables). More in specific the toolbox offers support for decision-makers to understand and minimize the specific energy consumption, to decrease the overall environmental impact even including non-energy benefit evaluation many times underestimated. The six separated tools merged within a unique toolbox consider different methodological approaches such as: assessment of the whole energy requirements in stock and flows considering the storage impact, the logistics and quality losses over time, implementation of Life Cycle Assessment and Life Cycle costs within the environmental and financial assessment of energy efficiency measures, based on a benchmarking approach. Finally, a specific approach implementing Multi Criteria Analysis was developed on selected key performance indicators such as specific and cumulated energy consumptions, quality losses and environmental burdens (i.e., global warming potential and water scarcity). The latest version of the ICCEE toolbox is available as free downloadable package on the ICCEE website.

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APA

Diaz, F., Romagnoli, F., Neusel, L., Hirzel, S., Paulus, J., Marchi, B., & Zanoni, S. (2022). The ICCEE Toolbox. A Holistic Instrument Supporting Energy Efficiency of Cold Food and Beverage Supply Chains. Environmental and Climate Technologies, 26(1), 428–440. https://doi.org/10.2478/rtuect-2022-0033

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