Literature DB >> 33930635

Predictive modelling as a tool for effective municipal waste management policy at different territorial levels.

Martin Rosecký1, Radovan Šomplák2, Jan Slavík3, Jiří Kalina4, Gabriela Bulková5, Josef Bednář6.   

Abstract

Nowadays, the European municipal waste management policy based on the circular economy paradigm demands the closing of material and financial loops at all territorial levels of public administration. The effective planning of treatment capacities (especially sorting plants, recycling, and energy recovery facilities) and municipal waste management policy requires an accurate prognosis of municipal waste generation, and therefore, the knowledge of behavioral, socio-economic, and demographic factors influencing the waste management (and recycling) behavior of households, and other municipal waste producers. To enable public bodies at different territorial levels to undertake an effective action resulting in circular economy we evaluated various factors influencing the generation of municipal waste fractions at regional, micro-regional and municipal level in the Czech Republic. Principal components were used as input for traditional models (multivariable linear regression, generalized linear model) as well as tree-based machine learning models (regression trees, random forest, gradient boosted regression trees). Study results suggest that the linear regression model usually offers a good trade-off between model accuracy and interpretability. When the most important goal of the prediction is supposed to be accuracy, the random forest is generally the best choice. The quality of developed models depends mostly on the chosen territorial level and municipal waste fraction. The performance of these models deteriorates significantly for lower territorial levels because of worse data quality and bigger variability. Only the age structure seems to be important across territorial levels and municipal waste fractions. Nevertheless, also other factors are of high significance in explaining the generation of municipal waste fractions at different territorial levels (e.g. number of economic subjects, expenditures, population density and the level of education). Therefore, there is not one single effective public policy dealing with circular economy strategy that fits all territorial levels. Public representatives should focus on policies effective at specific territorial level. However, performance of the models is poor for lower territorial levels (municipality and micro-regions). Thus, results for municipalities and micro-regions are weak and should be treated as such.
Copyright © 2021 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Machine learning; Municipal waste generation; Public policy; Regression modelling; Socio-economic factors; Territorial levels

Year:  2021        PMID: 33930635     DOI: 10.1016/j.jenvman.2021.112584

Source DB:  PubMed          Journal:  J Environ Manage        ISSN: 0301-4797            Impact factor:   6.789


  2 in total

1.  Design and development of smart Internet of Things-based solid waste management system using computer vision.

Authors:  Senthil Sivakumar Mookkaiah; Gurumekala Thangavelu; Rahul Hebbar; Nipun Haldar; Hargovind Singh
Journal:  Environ Sci Pollut Res Int       Date:  2022-04-27       Impact factor: 5.190

2.  Quantitative Evaluation of Waste Separation Management Policies in the Yangtze River Delta Based on the PMC Index Model.

Authors:  Fang Liu; Zhi Liu
Journal:  Int J Environ Res Public Health       Date:  2022-03-23       Impact factor: 3.390

  2 in total

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