Quantitative Analysis of Industrial Solid Waste Based on Terahertz Spectroscopy

Qingfang Wang; Qichao Wang; Zhangfan Yang; Xu Wu; Yan Peng

doi:10.3390/photonics9030184

Photonics (Mar 2022)

Quantitative Analysis of Industrial Solid Waste Based on Terahertz Spectroscopy

Qingfang Wang,
Qichao Wang,
Zhangfan Yang,
Xu Wu,
Yan Peng

Affiliations

Qingfang Wang: School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
Qichao Wang: School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
Zhangfan Yang: School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
Xu Wu: School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
Yan Peng: School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China

DOI: https://doi.org/10.3390/photonics9030184
Journal volume & issue: Vol. 9, no. 3
p. 184

Abstract

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Industrial solid waste refers to the solid waste that is produced in industrial production activities. Without correct treatment and let-off, industrial solid waste may cause environmental pollution due to a variety of pollutants and toxic substances that are contained in it. Conventional detection methods for identifying harmful substances are high performance liquid chromatography (HPLC) and gas chromatography-mass spectrometry (GC-MS), which are complicated, time-consuming, and highly demanding for the testing environment. Here, we propose a method for the quantitative analysis of harmful components in industrial solid waste by using terahertz (THz) spectroscopy combined with chemometrics. Pyrazinamide, benazepril, cefprozil, and bisphenol A are four usual hazardous components in industrial solid waste. By comparing with the Raman method, the THz method shows a much higher accuracy for their concentration analysis (90.3–99.8% vs. 11.7–86.9%). In addition, the quantitative analysis of mixtures was conducted, and the resulting prediction accuracy rate was above 95%. This work has high application value for the rapid, accurate, and low-cost detection of industrial solid waste.

Published in Photonics

ISSN: 2304-6732 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Technology: Engineering (General). Civil engineering (General): Applied optics. Photonics
Website: http://www.mdpi.com/journal/photonics

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