[HTML][HTML] Identification of influencing municipal characteristics regarding household waste generation and their forecasting ability in Biscay

I Oribe-Garcia, O Kamara-Esteban, C Martin… - Waste management, 2015 - Elsevier
I Oribe-Garcia, O Kamara-Esteban, C Martin, AM Macarulla-Arenaza, A Alonso-Vicario
Waste management, 2015Elsevier
The planning of waste management strategies needs tools to support decisions at all stages
of the process. Accurate quantification of the waste to be generated is essential for both the
daily management (short-term) and proper design of facilities (long-term). Designing without
rigorous knowledge may have serious economic and environmental consequences. The
present works aims at identifying relevant socio-economic features of municipalities
regarding Household Waste (HW) generation by means of factor models. Factor models face …
Abstract
The planning of waste management strategies needs tools to support decisions at all stages of the process. Accurate quantification of the waste to be generated is essential for both the daily management (short-term) and proper design of facilities (long-term). Designing without rigorous knowledge may have serious economic and environmental consequences. The present works aims at identifying relevant socio-economic features of municipalities regarding Household Waste (HW) generation by means of factor models. Factor models face two main drawbacks, data collection and identifying relevant explanatory variables within a heterogeneous group. Grouping similar characteristics observations within a group may favour the deduction of more robust models. The methodology followed has been tested with Biscay Province because it stands out for having very different municipalities ranging from very rural to urban ones. Two main models are developed, one for the overall province and a second one after clustering the municipalities. The results prove that relating municipalities with specific characteristics, improves the results in a very heterogeneous situation. The methodology has identified urban morphology, tourism activity, level of education and economic situation as the most influencing characteristics in HW generation.
Elsevier
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