通过傅立叶变换红外光谱法评估聚氯乙烯和聚四氟乙烯过滤器直接过滤结晶二氧化硅的效果。

IF 1.5 4区 医学 Q4 ENVIRONMENTAL SCIENCES
Bankole Osho, Mohammadreza Elahifard, Xiaoliang Wang, Behrooz Abbasi, Judith C Chow, John G Watson, W Patrick Arnott, Wm Randolph Reed, David Parks
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引用次数: 0

摘要

利用傅立叶变换红外(FTIR)光谱对可吸入结晶二氧化硅(RCS)进行滤波直接分析(DoF)是评估暴露风险的有用工具。随着 RCS 暴露限值越来越低,描述和减少测量的不确定性非常重要。本研究系统地评估了两种类型的过滤器(即聚氯乙烯 [PVC] 和聚四氟乙烯 [PTFE])通过多频谱傅立叶变换红外光谱进行 RCS 测量的情况,包括过滤器与过滤器之间的差异以及空白过滤器傅立叶变换红外参考光谱的日间差异、颗粒沉积模式、过滤效率和压降。对于以 2.5 升/分钟的流速取样 8 小时的 PVC 过滤器,如果使用指定的实验室参考过滤器来校正过滤介质的吸收,则 RCS 检测限 (LOD) 为 7.4 μg/m3 。如果使用采样前过滤器(灰尘采样前的空白过滤器)的光谱进行校正,则检测限可高达 5.9 微克/立方米。聚氯乙烯的吸收率随参比过滤器质量的增加而线性增加,为校正预取样过滤器和参比过滤器之间的吸收率差异提供了一种方法。对于 PTFE,当使用指定的实验室空白或样品前过滤器光谱进行空白校正时,LOD 值分别为 12 和 1.2 μg/m3 ,这表明使用样品前空白光谱可以减少 RCS 定量的不确定性。在使用三片盒收集颗粒时,两种类型的过滤器都表现出一致的径向对称沉积模式,这表明 RCS 可以通过过滤器中心的单次测量进行量化。在 2.5 升/分钟的流速和低压降(0.2-0.3 千帕)条件下,在测量的颗粒尺寸范围内,穿透力最强的空气动力学直径约为 0.1 微米,过滤效率≥ 98.8%。本研究的结论是,PVC 或 PTFE 过滤器都适合通过多频傅立叶变换红外进行 RCS 分析,但需要适当的方法来解释不同过滤器之间空白吸收的变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of PVC and PTFE filters for direct-on-filter crystalline silica quantification by FTIR.

Direct-on-Filter (DoF) analysis of respirable crystalline silica (RCS) by Fourier Transform Infrared (FTIR) spectroscopy is a useful tool for assessing exposure risks. With the RCS exposure limits becoming lower, it is important to characterize and reduce measurement uncertainties. This study systematically evaluated two filter types (i.e., polyvinyl chloride [PVC] and polytetrafluoroethylene [PTFE]) for RCS measurements by DoF FTIR spectroscopy, including the filter-to-filter and day-to-day variability of blank filter FTIR reference spectra, particle deposition patterns, filtration efficiencies, and pressure drops. For PVC filters sampled at a flow rate of 2.5 L/min for 8 h, the RCS limit of detection (LOD) was 7.4 μg/m3 when a designated laboratory reference filter was used to correct the absorption by the filter media. When the spectrum of the pre-sample filter (blank filter before dust sampling) was used for correction, the LOD could be up to 5.9 μg/m3. The PVC absorption increased linearly with reference filter mass, providing a means to correct the absorption differences between the pre-sample and reference filters. For PTFE, the LODs were 12 and 1.2 μg/m3 when a designated laboratory blank or the pre-sample filter spectrum was used for blank correction, respectively, indicating that using the pre-sample blank spectrum will reduce RCS quantification uncertainty. Both filter types exhibited a consistent radially symmetric deposition pattern when particles were collected using 3-piece cassettes, indicating that RCS can be quantified from a single measurement at the filter center. The most penetrating aerodynamic diameters were around 0.1 µm with filtration efficiencies ≥ 98.8% across the measured particle size range with low-pressure drops (0.2-0.3 kPa) at a flow rate of 2.5 L/min. This study concludes that either the PVC or the PTFE filters are suitable for RCS analysis by DoF FTIR, but proper methods are needed to account for the variability of blank absorption among different filters.

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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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