Particle size analysis of municipal solid waste for treatment process modeling

Area of Science:

• Environmental Engineering
• Waste Management Science
• Process Engineering

Background:

• Municipal solid waste (MSW) processing relies on physical properties like particle size.
• Accurate particle size distribution (PSD) expressions are crucial for MSW process modeling but are often unavailable.
• Existing models lack sufficient representation for diverse MSW components.

Purpose of the Study:

• To identify the most representative PSD expression for household and construction and demolition (C&D) waste streams.
• To develop a reliable PSD model for mixed MSW to enhance process simulation and design.
• To validate PSD model parameters for various MSW material categories.

Main Methods:

• Analysis of characterization data for household and C&D wastes.
• Comparison of Rosin-Rammler, log-normal, and gamma distributions for PSD fitting.
• Derivation and validation of PSD model parameters for different waste types.
• Development of a mixed waste PSD model based on component summation and bimodal distribution.

Main Results:

• The Rosin-Rammler distribution was identified as the best-fitting PSD model for both raw and processed MSW samples.
• Validated parameters for the Rosin-Rammler model were derived for various MSW material categories.
• A novel model for mixed household waste PSD was developed, considering waste composition.
• A simplified bimodal distribution model was derived for mixed waste, reflecting organic and inorganic fractions.

Conclusions:

• The Rosin-Rammler distribution provides a superior fit for MSW particle size characterization compared to other common distributions.
• Waste composition is a key factor influencing mixed waste PSD, enabling the development of predictive models.
• The developed PSD models offer improved tools for the design and optimization of MSW processing facilities.