Measurement of Crystalline Silica Aerosol Using Quantum Cascade Laser-Based Infrared Spectroscopy

被引:20
|
作者
Wei, Shijun [1 ,2 ]
Kulkarni, Pramod [1 ]
Ashley, Kevin [1 ]
Zheng, Lina [1 ]
机构
[1] NIOSH, Ctr Dis Control & Prevent, Cincinnati, OH 45226 USA
[2] Univ Cincinnati, Dept Mech & Mat Engn, Cincinnati, OH 45221 USA
来源
SCIENTIFIC REPORTS | 2017年 / 7卷
关键词
REGRESSION; FILTERS; MODEL; DUST; TOOL;
D O I
10.1038/s41598-017-14363-3
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Inhalation exposure to airborne respirable crystalline silica (RCS) poses major health risks in many industrial environments. There is a need for new sensitive instruments and methods for in-field or near real-time measurement of crystalline silica aerosol. The objective of this study was to develop an approach, using quantum cascade laser (QCL)-based infrared spectroscopy (IR), to quantify airborne concentrations of RCS. Three sampling methods were investigated for their potential for effective coupling with QCL-based transmittance measurements: (i) conventional aerosol filter collection, (ii) focused spot sample collection directly from the aerosol phase, and (iii) dried spot obtained from deposition of liquid suspensions. Spectral analysis methods were developed to obtain IR spectra from the collected particulate samples in the range 750-1030 cm(-1). The new instrument was calibrated and the results were compared with standardized methods based on Fourier transform infrared (FTIR) spectrometry. Results show that significantly lower detection limits for RCS (approximate to 330 ng), compared to conventional infrared methods, could be achieved with effective microconcentration and careful coupling of the particulate sample with the QCL beam. These results offer promise for further development of sensitive filter-based laboratory methods and portable sensors for near real-time measurement of crystalline silica aerosol.
引用
收藏
页数:8
相关论文
共 50 条
  • [41] Online measurement of bulk, tensile, brightness, and ovendry content of bleached chemithermomechanical pulp using visible and near infrared spectroscopy
    Tomkins, Matthew R.
    Gilbert, Wesley
    Thanh Trung
    TAPPI JOURNAL, 2018, 17 (04): : 207 - 216
  • [42] Rapid measurement of epimedin A, epimedin B, epimedin C, icariin, and moisture in Herba Epimedii using near infrared spectroscopy
    Yang, Yue
    Liu, Xuesong
    Li, Weili
    Jin, Ye
    Wu, Yongjiang
    Zheng, Jiyu
    Zhang, Wentao
    Chen, Yong
    SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY, 2017, 171 : 351 - 360
  • [43] Measurement of Fructose, Glucose, Maltose and Sucrose in Barley Malt Using Attenuated Total Reflectance Mid-infrared Spectroscopy
    Huang, Yichao
    Carragher, John
    Cozzolino, Daniel
    FOOD ANALYTICAL METHODS, 2016, 9 (04) : 1079 - 1085
  • [44] Determination of zinc oxide content of mineral medicine calamine using near-infrared spectroscopy based on MIV and BP-ANN algorithm
    Zhang, Xiaodong
    Chen, Long
    Sun, Yangbo
    Bai, Yu
    Huang, Bisheng
    Chen, Keli
    SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY, 2018, 193 : 133 - 140
  • [45] Estimation of soil salinity using three quantitative methods based on visible and near-infrared reflectance spectroscopy: a case study from Egypt
    Nawar, Said
    Buddenbaum, Henning
    Hill, Joachim
    ARABIAN JOURNAL OF GEOSCIENCES, 2015, 8 (07) : 5127 - 5140
  • [46] Surface roughness measurement of flat and curved machined metal parts using a near infrared super-continuum laser
    Alexander, Vinay V.
    Deng, Huaqiu
    Islam, Mohammed N.
    Terry, Fred L., Jr.
    Pittman, Raymond B.
    Valen, Thomas
    OPTICAL ENGINEERING, 2011, 50 (11)
  • [47] Non-destructive measurement of the dispersion of high-density polyethylene/Polystyrene blends using near-infrared diffuse reflectance spectroscopy based on deep learning
    Zhu, Shichao
    Wang, Mengmeng
    Li, Maoyuan
    Zhang, Mingjie
    Jin, Gang
    POLYMER, 2024, 315
  • [48] Near infrared spectroscopy quantitative analysis for Tricholoma matsutake based on information extraction by using the elastic net
    Li, Yuqiang
    Pan, Tianhong
    Li, Haoran
    Chen, Shan
    Li, Guoquan
    JOURNAL OF NEAR INFRARED SPECTROSCOPY, 2020, 28 (03) : 125 - 132
  • [49] Machine learning based technique to predict the water adulterant in milk using portable near infrared spectroscopy
    Lanjewar, Madhusudan G.
    Parab, Jivan S.
    Kamat, Rajanish K.
    JOURNAL OF FOOD COMPOSITION AND ANALYSIS, 2024, 131
  • [50] Ensemble Multivariate Calibration Based on Mutual Information for Food Analysis Using Near-Infrared Spectroscopy
    Tan, Chao
    Wang, Jinyue
    Qin, Xin
    Li, Menglong
    ANALYTICAL LETTERS, 2010, 43 (16) : 2640 - 2651