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Multi-level stratification of territories for waste composition analysis
Radovan Šomplák1, Miloš Kopa2, Marek Omelka2
1Institute of Process Engineering, Faculty of Mechanical Engineering, Brno University of Technology, Brno, Czech Republic.
Journal of Environmental Management
|June 26, 2022
Summary
This study introduces a new method for estimating municipal waste composition by grouping similar municipalities. This approach reduces the number of required analyses, making waste management planning more cost-effective and accurate at regional and national levels.
Area of Science:
- Environmental Science
- Waste Management
- Statistical Modeling
Background:
- Accurate waste composition data is crucial for effective waste management decision-making.
- Existing methods for estimating municipal waste composition often lack regional and national scope and efficient area selection.
- Cost-efficiency and accuracy are key challenges in waste analysis planning.
Purpose of the Study:
- To present a novel multi-level stratification method for selecting representative municipalities for waste composition analysis.
- To reduce the number of necessary waste observations while maintaining accuracy at regional or state levels.
- To provide a cost-effective framework for estimating waste composition applicable globally.
Main Methods:
- Utilizes multi-level stratification to group similar municipalities.
- Combines expert knowledge with statistical methods, including cluster analysis.
- Employs socio-economic and waste-related parameters for stratification and selection.
Main Results:
- Demonstrates a method for selecting representative municipalities, exemplified by 10 sites in the Czech Republic.
- The proposed method enables accurate waste composition estimation for larger territories.
- Estimated cost for analyzing 10 representative municipalities in the Czech Republic is approximately 72,000 euros.
Conclusions:
- The presented method offers a statistically sound and cost-effective approach to waste composition analysis.
- This methodology supports sustainable waste management by improving data accuracy and reducing costs.
- The generalizable method can be adapted for waste analysis planning in any country worldwide.
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