A structured methodology to understand municipal waste generation at local level with minimized effort: development...

Area of Science:

• Environmental Science
• Waste Management
• Statistical Analysis

Background:

• Effective municipal solid waste (MSW) management requires understanding waste generation patterns.
• Optimizing collection services and implementing Pay-As-You-Throw (PAYT) systems depend on accurate waste data.

Purpose of the Study:

• To develop and apply a statistical methodology for identifying distinct household waste generation patterns.
• To differentiate weekly and seasonal (monthly) variations in MSW generation.
• To inform the design of efficient waste sampling campaigns for pilot PAYT implementation.

Main Methods:

• Utilized standard statistical methods including ANOVA, non-parametric tests, and cluster analysis.
• Applied the methodology to analyze MSW collection records from a Portuguese neighborhood.
• Identified statistically distinct clusters for daily and monthly waste generation.

Main Results:

• Discovered statistically significant differences in MSW generation across days of the week and months.
• Identified three clusters for weekly generation (high, medium, low) and two for monthly generation (high, low).
• Enabled the design of a customized, efficient waste sampling campaign, reducing fieldwork.

Conclusions:

• The statistical methodology effectively identifies distinct MSW generation patterns at weekly and monthly scales.
• Customized sampling based on identified patterns leads to more efficient data collection.
• This systematic approach is adaptable and valuable for waste management planning and PAYT implementation.