Achieving waste recovery goals in the medium/long term: Eco-efficiency analysis in a Brazilian city by using the LCA approach

Abstract

The aim of this study was to analyse how to ensure that medium- and long-term waste recovery goals can be achieved in Brazilian cities, based on the incorporation of viable and accessible technology. The identification of the strengths of the Brazilian cities with better (dry and wet) waste recovery rates allowed different strategies to be proposed for Jo ̃ao Pessoa (the city selected as a case study). Those strategies were based on the improvement of (1) the selective collection of the recyclable dry waste fraction, (2) the material recovery facility to increase the recovery of recyclable dry waste fraction to be recycled and/or wet waste fraction to be composted, and finally (3) the working conditions of waste workers. A combination of these improvement strategies at two different levels of implementation (partial and total) allowed the definition of 14 alternative scenarios, which were analysed from an eco-efficiency perspective (environmental vs. economic). After analysing the evolution over time of the alternative scenarios proposed, the proposal that was finally selected was based on the initial implementation of a mechanical biological and composting facility capable of handling up to 50% of the mixed municipal solid waste collected by 2023 with a material recovery efficiency of 30%. From there, the efficiency of the mechanical biological and composting facility should increase up to 60% to achieve the waste recovery goals by 2034 (management of 60% of the mixed waste collected). This rate has not yet been reached in any of the Brazilian mechanical biological and composting facilities analysed, so the reduction in the amount of waste generated and the increase in the selective separation of waste at source are identified as key elements to be able to fulfil the long-term goals. The approach used in the case study provides guidelines for application in other geographical contexts.