Modelagem da geração de resíduos sólidos urbanos através de regressão geograficamente ponderada: um estudo de caso no estado de Goiás e Distrito Federal

Abstract

The study conducted an in-depth investigation into the generation of municipal solid waste (MSW) in the state of Goiás and the Federal District, taking as a reference the increasing complexity of urbanization processes and the challenges associated with contemporary environmental management. Starting from the recognition that waste production constitutes a socio-spatially heterogeneous phenomenon, the research aimed to understand how socioeconomic, demographic, educational, and environmental variables relate to waste generation patterns, considering their unequal distribution across the territory. For this purpose, recent official data were used, covering variables such as population density, literacy rate, average household size, GDP per capita, number of formal jobs, in addition to climatic factors, all integrated into georeferenced databases. The modeling was conducted in two stages: initially, multiple linear regression (OLS) was applied to identify significant variables and assess multicollinearity issues; subsequently, geographically weighted regression (GWR) was employed, a technique capable of revealing the spatial non-stationarity of parameters and providing more precise local estimates. The results demonstrated the superior performance of GWR, which explained approximately 99% of the variability in waste generation, surpassing the global model and confirming the pertinence of the spatial approach. The analysis revealed distinct regional patterns: in the metropolitan areas of Goiânia and Brasília, population density and household size were strongly related to the intensification of waste production; in the Brasília metropolitan fringe, migratory flows and large families played a relevant role; in contrast, in rural regions, adherence to traditional reuse practices and a weaker impact of demographic growth on waste generation were observed. A particularly significant finding was the inverse relationship between GDP per capita and MSW production in several municipalities, reflecting agro-export economies that elevate economic indicators without necessarily increasing urban consumption. However, the variable that stood out the most was the number of formal jobs (EMPFOR), which showed a universally positive correlation with waste generation in all municipalities, indicating that job formalization, by increasing disposable income, translates into greater consumption and disposal regardless of location. This finding reinforces that economic development and employment growth must progress in harmony with environmental mitigation strategies to avoid overloading collection and treatment systems. From a methodological standpoint, the research highlights the importance of analytical instruments capable of capturing territorial heterogeneities, while at the applied level, it emphasizes the need for regional policies adapted to local specificities, articulating economic development and sustainability. In this sense, the findings provide strategic inputs for public managers while also broadening the academic debate on the use of advanced spatial models for solid waste management in complex and unequal realities.