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Related Experiment Video

Updated: Jun 3, 2026

Production and Testing of Moisture Behavior and Thermal Properties of Rapeseed Straw and Ganoderma resinaceum Mycelium Bio-Composites

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Published on: September 5, 2025

Measuring mixed cellulose ester (MCE) filter mass under variable humidity conditions.

Kenneth T Bogen¹, Greg Brorby, D Wayne Berman

¹Exponent, Oakland, CA 94607, USA. kbogen@exponent.com

The Annals of Occupational Hygiene

|March 25, 2011

Summary

This summary is machine-generated.

Accurate dust mass measurements using mixed cellulose ester (MCE) filters are challenging due to humidity. This study developed a method to correct MCE filter mass for relative humidity and temperature variations, improving fiber analysis accuracy.

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Area of Science:

Environmental Science
Analytical Chemistry
Materials Science

Background:

Mixed cellulose ester (MCE) filters are standard for air dust and fiber analysis.
Humidity significantly affects MCE filter mass, complicating accurate dust mass determination.
Existing methods struggle with precise dust mass quantification under variable humidity.

Purpose of the Study:

To develop a method for accurate dust mass estimation on MCE filters.
To account for the influence of relative humidity and temperature on MCE filter mass.
To improve the reliability of fiber analysis by correcting for environmental factors.

Main Methods:

Collected baseline data on MCE filter mass changes across varying relative humidity (RH) and time.
Utilized linear regression to model the relationship between RH and MCE filter mass.
Extended the model to incorporate temperature variations based on theoretical principles.

Main Results:

Established reproducible relationships between RH and MCE filter mass for 37-mm and 25-mm filters.
Developed regression models to accurately estimate dust mass by correcting for RH.
Generalized the methodology to include temperature effects for broader applicability.

Conclusions:

The developed method enhances the accuracy of dust mass measurements on MCE filters.
This approach mitigates errors caused by humidity and temperature fluctuations.
Improved MCE filter mass estimation supports more reliable air quality and fiber analysis.