Assessing the Environmental Performance of Municipal Solid Waste Collection: A New Predictive LCA Model

Alba Bala, Marco Raugei, Carlos Afonso Teixeira, Alberto Fernández, Francisco Pan-Montojo and Pere Fullana-i-Palmer
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Alba Bala: UNESCO Chair in Life Cycle and Climate Change, Escola Superior de Comerç Internacional (UPF), Passeig Pujades, 1, 08003 Barcelona, Spain
Marco Raugei: School of Engineering, Computing and Mathematics, Oxford Brookes University, Wheatley Campus, Wheatley OX33 1HX, UK
Carlos Afonso Teixeira: Centre for the Research and Technology of Agro-Environmental and Biological Sciences, University of Trás-os-Montes and Alto Douro, Quinta de Prados, 5000-801 Vila Real, Portugal
Alberto Fernández: Ecoembalajes España, S.A., Calle de Cardenal Marcelo Spínola 14/2ª planta, 28016 Madrid, Spain
Francisco Pan-Montojo: Circular Economy and Waste Advisor, 10 Azagador, Las Rozas de Madrid, 28232 Madrid, Spain
Pere Fullana-i-Palmer: UNESCO Chair in Life Cycle and Climate Change, Escola Superior de Comerç Internacional (UPF), Passeig Pujades, 1, 08003 Barcelona, Spain

Sustainability, 2021, vol. 13, issue 11, 1-17

Abstract: Most existing life cycle assessment models of waste management have so far underplayed the importance of the waste collection phase, addressing it only in a simplified fashion, either by requesting the total amount of fuel used as a direct user input or by calculating it based on a set of input parameters and fixed diesel consumption factors. However, if the main purpose of the study is to improve the efficiency of the collection system itself, a more detailed analysis of the collection phase is required, avoiding oversimplified and potentially misleading conclusions. The new LCA collection model presented here relies on a large number of parameters (number and type of containers, collection frequency, distances for the various legs of transport, etc.) and allows the detailed predictive analysis of alternative collection scenarios. The results of applying this newly developed model to a number of experimental case studies in Portugal are analyzed, discussed, and compared to those produced by a selection of pre-existing, more simplified models such as ORWARE and MSW-DST. The new model is confirmed as being the most accurate and, importantly, as the only one capable of predicting the consequences of a range of possible changes in the collection parameters.

Keywords: LCA; waste management; waste collection; predictive model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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