Identification and Analysis of Sets Variables for of Municipal Waste Management Modelling

Abstract

Due to the large quantities of municipal waste generated, their harmful effects on the environment should be minimized. The rationalization of waste management is therefore necessary to achieve a more sustainable development system. In order to support the decision-making process for municipal waste management, this document focuses on developing models for practical use by local authorities in forecasting and managing the size of waste stream in their area. This action, because of its specificity, is a difficult task, especially because of the systemic changes made and the territorial differentiation and changes in the living level of the population. The work presents studies conducted in 2479 municipalities for which mass accumulation index forecasts were developed, using selected methods based on readily available input variables that have not yet been used (structure municipalities and typology of municipalities by scope of influence). The studies confirmed the hypothesis that the amount of municipal waste collected from households depends both on the administrative type of the municipality and on the factors related to the location and socioeconomic function of the area. The inclusion of localization and socioeconomic factors, which so far were not used to model the municipal waste stream, allowed for the reduction of the prediction error of this indicator. Relevant waste stream forecasts will allow local governments to achieve more effectively the objective of sustainable waste management and thus reduce their environmental impact. The achievement of this objective will be possible not only through the preparation of infrastructure to serve the projected waste volumes; it will also identify the waste management areas where the municipal waste reception process is inadequate. Thus, it will help to eliminate illegal processing and the landfill of waste. Keywords: municipal waste; sustainable waste management; ecological modelling; forecasting the amount of waste; limiting the impact of waste on the environment

Selection of a Multicriteria Method for Selecting Independent Variables for Forecasting the Energy Potential of Municipal Waste—A Case Study in Poland

“…Research on forecasts of solid waste generation has been conducted for the purposes of municipal waste management planning at various levels, including national [3,4], regional [6], as well as in households in rural and urban areas [5,7]. The most commonly used indicators for estimating the mass and composition of generated waste rely on publicly available statistical data or information provided by municipalities, such as [8][9][10][11][12][13][14][15][16][17][18][19]: socioeconomic factors, including economic development and residents' incomes, industrial and commercial activities, tourism, municipality size, land-use structure, urbanization level, technical equipment in households, demographics and population density, as well as waste collection systems, social awareness, and environmental education.…”

“…Therefore, the science of feature selection, also known as variable selection or attribute selection, is necessary for the effective identification of features for predicting the municipal waste accumulation indicator. Statistical methods, such as linear regression models [21], multiple regression [8], rough set theory [22], multidimensional gray models [23], and artificial neural networks [5,[24][25][26], are primarily used for forecasting the accumulation of municipal waste. Studies have shown that the selection of a forecasting method, which serves as the basis for waste management planning in each area, should consider a range of significant features and factors that influence the forecast's quality.…”

“…Municipal waste management planning requires obtaining reliable data on waste generation, the factors influencing waste quantity, and credible forecasts of accumulated waste quantities within a specific time horizon. The selection of appropriate variables for modeling municipal waste flow is crucial for effective analysis, forecasting, and waste management planning [5]. Suitable variables allow for a better understanding of factors influencing waste generation, improving analysis efficiency, considering data availability, and enabling result interpretation within the context of reality.…”

Assessing the Connections between COVID-19 and Waste Management in Brazil

“…It was noticed that there were decentralized decisions about the functioning of the waste management sector during the pandemic [51]. This could be due to the fact that the amount of municipal households' waste depends both on the administrative type of the municipality and on the factors related to the location and socioeconomic characteristics of the citizens living in the area [52].…”

“…It is also necessary to consider the specificity of the municipality, the population density, the use intensive of energy, etc. [52].…”