A structured methodology to understand municipal waste generation at local level with minimized effort: development and case study

Fernández-Braña, Álvaro; Sousa, Vítor; Dias-Ferreira, Célia

doi:10.1007/s11356-020-11108-0

Research Article
Published: 21 October 2020

A structured methodology to understand municipal waste generation at local level with minimized effort: development and case study

Álvaro Fernández-Braña ORCID: orcid.org/0000-0002-0351-2664^1,2,
Vítor Sousa³ &
Célia Dias-Ferreira^1,4

Environmental Science and Pollution Research volume 28, pages 12597–12612 (2021)Cite this article

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Abstract

Understanding municipal solid waste (MSW) generation is a key requirement for designing and optimizing MSW collection services. The present contribution proposes a statistical methodology to identify MSW generation patterns from MSW collection records. The methodology aims at finding statistically distinct household waste generation patterns within the days of the week and within months (seasonal variation). It is based on standard statistical methods (ANOVA complemented by non-parametric tests and cluster analysis). The methodology was applied to a Portuguese neighbourhood to assist in the definition of a waste sampling campaign to support the implementation of a pilot PAYT. The results showed the existence of groups with statistically distinct MSW generation patterns both at the weekly and monthly time scales. Three clusters of days of the week, with high, medium and low generation, and two clusters of months, with high and low generation, were identified. These results allowed to design and implement a customized field waste sampling campaign to estimate the MSW generated at the study site with minimal field work. Instead of implementing a homogeneous sampling campaign (equal number of samples for every day of the week and for every month), the samples were collected from the days and months that showed statistically distinct MSW generation pattern. The systematic procedure can be easily adapted to any given location, thus being a useful tool that combines statistical analysis with field collected data.

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Acknowledgements and funding

The authors would like to acknowledge the financial support of LIFE+, the financial instrument of the EU

for the environment, for funding the LIFE PAYT project (LIFE 15/ENV/PT/000609).

Availability of data

The data that support the findings of this study belong to Aveiro city municipal council and are not publicly available. The authors were authorised to use them under license for research purposes, so that data are available from them upon reasonable request and with permission of Aveiro municipal council.

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Affiliations

Research Centre for Natural Resources, Environment and Society (CERNAS), Instituto de Investigação Aplicada (IIA) – Instituto Politécnico de Coimbra (IPC), Coimbra, Portugal
Álvaro Fernández-Braña & Célia Dias-Ferreira
Department of Chemical Engineering, Escola Técnica Superior de Enxeñaría (ETSE) – Universidade de Santiago de Compostela (USC), Santiago de Compostela, Galicia, Spain
Álvaro Fernández-Braña
Civil Engineering Research and Innovation for Sustainability (CERIS), Department of Civil Engineering, Arquitecture and Geo-resources, Instituto Superior Técnico (IST) – Universidade de Lisboa, Lisbon, Portugal
Vítor Sousa
Universidade Aberta, Lisbon, Portugal
Célia Dias-Ferreira

Authors

Álvaro Fernández-Braña
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Vítor Sousa
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Célia Dias-Ferreira
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Contributions

CDF contributed to formulating the initial idea and research goals of the article and supervised the overall development. CDF was also responsible for the acquisition of financial support for the project leading to this publication. AFB obtained the initial datasets; VS designed the statistical procedure and performed the formal analysis. AFB wrote the first draft of the manuscript and coordinated the further revisions, with contributions from all authors. All authors have read and approved the final manuscript submitted.

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Correspondence to Álvaro Fernández-Braña.

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Fernández-Braña, Á., Sousa, V. & Dias-Ferreira, C. A structured methodology to understand municipal waste generation at local level with minimized effort: development and case study. Environ Sci Pollut Res 28, 12597–12612 (2021). https://doi.org/10.1007/s11356-020-11108-0

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Received: 15 May 2020
Accepted: 04 October 2020
Published: 21 October 2020
Issue Date: March 2021
DOI: https://doi.org/10.1007/s11356-020-11108-0

Keywords

Data collection
Experimental design
Waste forecasting
Pattern identification
Sample distribution
Seasonality