Title: Estimating the lifespan of the Brasília Landfill (Brazil) by means of linear regression based on socioeconomic indicators and recycling rates

Authors: Francisco Orlando Holanda Costa Filho; Marisete Dantas De Aquino; Francisco Humberto De Carvalho Júnior

Addresses: Department of Hydraulic and Environmental Engineering, Technology Center, Federal University of Ceará (UFC), Campus do Pici – Bloco 713, Cep: 60440-970, Fortaleza – Ceará, Brazil ' Department of Hydraulic and Environmental Engineering, Technology Center, Federal University of Ceará (UFC), Campus do Pici – Bloco 713, Cep: 60440-970, Fortaleza – Ceará, Brazil ' Department of Hydraulic and Environmental Engineering, Technology Center, Federal University of Ceará (UFC), Campus do Pici – Bloco 713, Cep: 60440-970, Fortaleza – Ceará, Brazil

Abstract: The environmental impact assessment report (EIAR) of the Brasília Landfill (BL) estimated the lifespan of the landfill by considering the MSW to be constant over the years in the Distrito Federal (Brazil). Thus, it did not consider the influences of socioeconomic factors and recycling rates. Therefore, this work had the objective of creating different estimates of MSW to be disposed of in the BL and consequent lifespans using linear regression and based on the recycling rates and socioeconomic indicators. This makes it possible to compare the estimates generated in this study with the estimated lifespan given in the EIAR of the BL. Four indicators were used in the creation of 12 equations by means of linear regression to estimate MSW. However, only one equation was chosen, which was then used to create MSW projections. These projections generated estimates with a minimum difference of 28 months and a maximum difference of 39 months between the lifespans obtained in this research and the lifespan value presented in the EIAR of the BL, which may hamper BL planning in the future.

Keywords: municipal solid waste; MSW; Distrito Federal; environmental impact assessment report; EIAR; Pearson correlation; linear regression; simple regression; multiple regression; landfill; socioeconomic indicators; recycling rates; estimates; Shapiro-Wilk test; trend analysis.

DOI: 10.1504/IJEWM.2021.115380

International Journal of Environment and Waste Management, 2021 Vol.27 No.4, pp.395 - 419

Received: 27 Aug 2019
Accepted: 08 Jan 2020

Published online: 01 Jun 2021 *

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