Comparison of Methods for Pretreatment and Quantification of Bulk Asbestos Samples for Polarized Light Microscopy Analysis to Evaluate Asbestos-Containing Waste

• Main Authors: Seunghon Ham, Sungho Hwang, Chungsik Yoon
• Format: Article
• Language: English
• Published: MDPI AG 2019-11-01
• Series: Sustainability
• Subjects: asbestos; analysis; polarized light microscope; visual estimation; point counting; laboratory; asbestos-containing waste; pretreatment
• Online Access: https://www.mdpi.com/2071-1050/11/22/6440

This study aimed to compare sample pretreatment procedures for the identification and quantification of asbestos. The performance of visual estimation and point counting procedures for evaluating asbestos-containing waste was investigated, and the effect of analytical experience was studied. The efficacy of pretreatments for the identification and quantification of asbestos in various sample matrices was compared. To evaluate the effect of experience on analytical accuracy, three analysts with different analytical experiences were selected. There were significant differences in the quantitative analysis results obtained using different pretreatments. False negatives were reported when asbestos, especially amphiboles, were analyzed by a less-experienced analyst. Quantification via point counting and visual estimation resulted in differences in the asbestos content. The results of point counting were more accurate than those of visual estimation for all analysts, regardless of the asbestos type and concentration. Experience in asbestos analysis affected accuracy and precision. The findings show that pretreatment is an important factor in qualitative analysis. Appropriate pretreatments should be assigned based on the properties of the sample. For quantitative analysis, the accuracy of the results depends on the experience of the analyst. Until analysts are fully trained, all their analysis results should be checked by an experienced analyst. Point counting is an adequate quantitative method for analyzing samples with low concentrations.