Usos de indicadores socioeconômicos e índices de reciclagem nas estimativas das vidas úteis de aterros sanitários por meio de regressão linear

Abstract

The most common methodologies used to estimate the useful lives of landfills in environmental impact studies (EIA-RIMAs) disregard possible influences of socioeconomic factors in the generation of MSW, which may generate inaccuracies. The methodology used in the EIA-RIMAs of the Sanitary Landfill of Brasília (ASB) and the Sanitary Landfill of Guarulhos (ASG) estimated the useful lives of the landfills considering the number of solid RSU generated year after year in the Federal District and Guarulhos, did not consider the influences of socioeconomic factors and recycling rates. The objective of this work was to create different estimates for the amount of MSW to be disposed in the two landfills and the consequent useful lives using linear regression and based on recycling rates and socioeconomic indicators of the study sites. Thus, it is possible to compare the estimates generated in this dissertation with the estimates of useful lives generated in the EIA-RIMAs in question. The indicators chosen for this research were: GDP, population, consumption of electricity and water. Pearson correlation analyzes were performed to find out which indicators most influence the generation of RSU at the study sites. Based on the four indicators used in the research, twelve equations were created for each landfill by means of linear regression to estimate the MSW quantities. However, only one equation was chosen for each landfill, which was selected according to statistical parameters of linear regression. Pearson's correlations showed that the indicators that most influence the MSW in the Federal District are: electricity consumed (0.995), GDP (0.991), population (0.971) and water consumption (0.879). In the case of Guarulhos, the indicators are: GDP (0.962), electricity consumed (0.908), water consumption (0.856) and population (0.695). The best equation for the ASB was composed by the indicators consumed and water consumption, and the best equation for the ASG was composed by only one indicator (GDP). With the equations chosen for the two landfills, different projections of the MSW quantities were created according to recycling rates for the study sites. When comparing the minimum and maximum useful lives obtained in this work with the useful life values ​​obtained in the EIA-RIMAs addressed, the differences were considerable: BSA (minimum difference of 2 years and 4 months and maximum difference of 3 years and 3 months ); ASG (minimum difference of 1 year and 8 months and maximum difference of 2 years and 10 months), which may lead to the licensing of new areas ahead of schedule and unexpected costs.