Particle size distribution: A key factor in estimating powder dustiness

Area of Science:

• Materials Science
• Industrial Hygiene
• Chemical Engineering

Background:

• Dust generation during bulk powder handling poses risks to industrial environments and worker health.
• Accurate prediction of material dustiness is crucial for implementing effective dust control measures.
• Existing methods for assessing dustiness can be time-consuming and resource-intensive.

Purpose of the Study:

• To develop a predictive model for material dustiness based on readily available material properties.
• To understand the influence of key material parameters on dust generation.
• To provide a practical tool for industrial applications to mitigate dust emissions.

Main Methods:

• Characterization of over 20 diverse raw materials, including quartzes, feldspars, and sands.
• Determination of dustiness using the continuous drop method.
• Analysis of material parameters such as particle size distribution, true density, flowability, and specific surface area.

Main Results:

• Material dustiness is significantly influenced by particle size distribution.
• A predictive model was developed, correlating dustiness with particle size distribution.
• Relative dust emission increased with mean particle size, but overall dustiness also depended on the fraction of erodible particles.

Conclusions:

• The developed model accurately estimates material dustiness using only particle size distribution data.
• This model facilitates industrial application by reducing the need for additional testing.
• The model serves as a valuable tool for developing preventive measures against dust emissions in bulk powder processing.