2018
DOI: 10.1016/j.resconrec.2018.07.024
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Material flow analysis as a support tool for multi-criteria analysis in solid waste management decision-making

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Cited by 54 publications
(23 citation statements)
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“…Various types of models were used-regression [19,20], stochastic [21,22] or with the use of artificial neural networks [23,24], often with good results, close to reality. The use of mathematical modeling also allows for effective planning of waste management systems and assessment of the impact of changes in input parameters on the functioning of the system as a whole [25][26][27][28][29][30][31][32][33][34][35][36]. It has proved particularly useful in recent years in connection with the implementation of the circular economy concept [37][38][39][40][41][42][43][44][45][46][47][48][49][50][51][52][53].…”
Section: Introductionmentioning
confidence: 99%
“…Various types of models were used-regression [19,20], stochastic [21,22] or with the use of artificial neural networks [23,24], often with good results, close to reality. The use of mathematical modeling also allows for effective planning of waste management systems and assessment of the impact of changes in input parameters on the functioning of the system as a whole [25][26][27][28][29][30][31][32][33][34][35][36]. It has proved particularly useful in recent years in connection with the implementation of the circular economy concept [37][38][39][40][41][42][43][44][45][46][47][48][49][50][51][52][53].…”
Section: Introductionmentioning
confidence: 99%
“…When the collection coverage is 100%, the total amount of waste generated equals the total amount of waste collected. Makarichi et al (2018) Recycling rate…”
Section: Discussionmentioning
confidence: 99%
“…Actors of this informal waste activity are scavengers, scrap dealers, small-scale enterprises, large-scale enterprises, grinders and manufactures. Each region has a collection system that ends up producing recycled plastic ore (Makarichi et al, 2018).…”
Section: Discussionmentioning
confidence: 99%