Exploring the Effect of Particle Loading Density on Respirable Dust Classification by SEM-EDX

Author:

Sweeney Daniel1,Keles Cigdem1ORCID,Sarver Emily1ORCID

Affiliation:

1. Department of Mining and Minerals Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA

Abstract

Exposure to respirable coal mine dust (RCMD) still poses health risks to miners. Scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX) is a powerful tool for RCMD characterization because it provides particle-level data, including elemental ratios (via the EDX signals) that can enable classification by inferred mineralogy. However, if the particle loading density (PLD) is high on the analyzed substrate (filter sample), interference between neighboring particles could cause misclassification. To investigate this possibility, a two-part study was conducted. First, the effect of PLD on RCMD classification was isolated by comparing dust particles recovered from the same parent filters under both low- and high-PLD conditions, and a set of modified classification criteria were established to correct for high PLD. Second, the modified criteria were applied to RCMD particles on pairs of filters, with each pair having one filter that was analyzed directly (frequently high PLD) and another filter from which particles were recovered and redeposited prior to analysis (frequently lower PLD). It was expected that application of the modified criteria would improve the agreement between mineralogy distributions for paired filters; however, relatively little change was observed for most pairs. These results suggest that factors other than PLD, including particle agglomeration, can have a substantial effect on the particle EDX data collected during direct-on-filter analysis.

Funder

US Centers for Disease Control/National Institute Occupational Safety and health

Publisher

MDPI AG

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3