A Novel Composite Index for the Development of Decentralized Food Production, Food Loss, and Waste Management Policies: A Water-Climate-Food Nexus Approach

• Main Authors: Daniel Hoehn, María Margallo, Jara Laso, Israel Ruiz-Salmón, Laura Batlle-Bayer, Alba Bala, Pere Fullana-i-Palmer, Rubén Aldaco
• Format: Article
• Language: English
• Published: MDPI AG 2021-03-01
• Series: Sustainability
• Subjects: sustainable development goals; food waste; composite index; water-climate-food nexus
• Online Access: https://www.mdpi.com/2071-1050/13/5/2839

The United Nations has adopted 17 sustainable development goals for 2030 with environmental sustainability being one of the main pillars. A key point to address this pillar is the proper management of waste generation. Within the broad spectrum of waste types, food loss and waste is produced worldwide in large quantities. In this framework, the development of composite indexes is recommended to measure the level of compliance of any context with Sustainable Development Goals. This work presents a novel composite index for food loss and waste generation and management systems, the so-called sustainable development goals-food (SDG-Food) index, aiming to determine the level of compliance of any concrete national, regional, or local context regarding five different sustainable development goals with a water-climate-food nexus thinking. The pilot case study of Spain is presented by analyzing the environmental performance between 2015 and 2040 in a context of (i) compliance and (ii) non-compliance with the Paris Agreement targets. Additionally, four different diets are assessed. Results suggested a numerical index score of 13.79, highlighting the categories of eggs, cereals, meat, and vegetables, and the stages of agricultural production and consumption, as the furthers ones for compliance with the five SDG assessed. Moreover, the scenario of compliance with the Paris agreement targets presented better values for all stages, and a vegan diet was highlighted as the one with the best index score.