对 CPDM 样品进行快速二氧化硅分析:沉积回收粉尘并利用傅立叶变换红外光谱进行分析。

IF 1.5 4区 医学 Q4 ENVIRONMENTAL SCIENCES
August Greth, Emily Sarver
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引用次数: 0

摘要

在美国,严重的煤炭工人尘肺病的不断复发与过度暴露于可吸入结晶二氧化硅(RCS,主要以石英形式存在,并因此受到监管)有关。因此,能够更频繁地监测 RCS 的能力备受青睐。最近的发展包括使用便携式傅立叶变换红外光谱仪(FTIR)对传统的聚氯乙烯(PVC)过滤器收集的过滤器样本进行现场石英分析。不过,美国煤矿的大部分可吸入粉尘样本都是通过个人粉尘连续监测仪(CPDM)收集的,该监测仪可实时跟踪可吸入粉尘的总质量浓度。由于采样基质的材料和结构原因,傅立叶变换红外光谱无法直接分析采集到的粉尘样本。为了解决这个问题,我们设想了一种简单的三步法,即先将粉尘回收成悬浮液,然后用注射器过滤装置将其重新沉积到 PVC 过滤器上,再用傅立叶变换红外光谱进行分析。目前的研究旨在开发重新沉积和分析步骤。它特别考虑了 PVC 过滤器的尺寸、典型过滤装置产生的沉积模式以及傅立叶变换红外扫描位置等问题,以建立一个可从光谱数据预测石英质量的模型。在这里测试的方案中,以下组合被认为是最佳方案:25 毫米 PVC 过滤器,使用在线注射器过滤器支架沉积灰尘(产生 "轮辐 "模式),在四个中心偏移位置(相距 90°,距中心 8 毫米)进行傅立叶变换红外分析,并对光谱数据进行平均。在这些条件下,对于预期石英质量小于 0.150 毫克(相当于样品总质量小于约 1.5 毫克)的样品,在含有两种地质源材料(即代表真实煤矿二氧化硅源)之一沉积的可吸入粉尘的过滤器上观察到的预测石英质量的标准误差为 0.011 毫克(11 微克)。对于预期石英质量较高的样品,标准误差会增加,这表明随着样品总质量的增加,灰尘沉积的均匀性会降低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Toward rapid silica analysis of CPDM samples: Deposition of recovered dust and analysis by FTIR.

The ongoing resurgence of severe Coal Workers' Pneumoconiosis in the US has been linked to overexposure to respirable crystalline silica (RCS, which is predominantly present as quartz and regulated as such). Capabilities that enable more frequent RCS monitoring are highly sought. Recent developments include field-based quartz analysis of traditional filter samples-collected on polyvinyl chloride (PVC) filters-using portable Fourier Transform Infrared spectroscopy (FTIR). However, most respirable dust samples in US coal mines are collected with a continuous personal dust monitor (CPDM) that enables real-time tracking of total respirable dust mass concentration. FTIR cannot directly analyze the collected dust sample due to the materials and construction of the sampling substrate. To address this issue, a simple three-step method was envisioned wherein the dust could be recovered into a suspension, redeposited onto a PVC filter using a syringe filter apparatus, and then analyzed by FTIR. The current study was conducted to develop the redeposition and analysis steps. It specifically considers the issues of the PVC filter size and deposition pattern yielded by typical filtration apparatuses and the FTIR scanning locations to establish a model that predicts quartz mass from the spectral data. Of the options tested here, the following combination was found to be optimal: 25-mm PVC filter with dust deposition using an inline syringe filter holder (which yields a "wheel and spoke" pattern), and FTIR analysis at four center-offset locations (90° apart, 8-mm from the center) from which the spectral data were averaged. Under these conditions, the predicted quartz mass on filters with respirable dust deposited from one of two geologic source materials (i.e., representing real coal mine silica sources) was observed to have a standard error of 0.011 mg (11 µg) for samples with an expected quartz mass of less than 0.150 mg (which equated to a total sample mass of less than about 1.5 mg). For samples with higher expected quartz masses, standard error increased, suggesting that dust deposition becomes less uniform with increasing total sample mass.

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来源期刊
Journal of Occupational and Environmental Hygiene
Journal of Occupational and Environmental Hygiene 环境科学-公共卫生、环境卫生与职业卫生
CiteScore
3.30
自引率
10.00%
发文量
81
审稿时长
12-24 weeks
期刊介绍: The Journal of Occupational and Environmental Hygiene ( JOEH ) is a joint publication of the American Industrial Hygiene Association (AIHA®) and ACGIH®. The JOEH is a peer-reviewed journal devoted to enhancing the knowledge and practice of occupational and environmental hygiene and safety by widely disseminating research articles and applied studies of the highest quality. The JOEH provides a written medium for the communication of ideas, methods, processes, and research in core and emerging areas of occupational and environmental hygiene. Core domains include, but are not limited to: exposure assessment, control strategies, ergonomics, and risk analysis. Emerging domains include, but are not limited to: sensor technology, emergency preparedness and response, changing workforce, and management and analysis of "big" data.
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