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Quantitative Analysis of Microplastics Based on Micro-Raman Spectroscopy |
ZHENG Li-na, FENG Zi-kang, HAN Zhen, LI Jia-lin, FENG Wen-ting |
School of Safety Engineering, China University of Mining and Technology, Xuzhou 221116, China
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Abstract The extensive existence of microplastics in the environment has potential exposure risks. So it is very necessary to develop a reliable and accurate monitoring method. This paper has studied two quantitative methods of microplastics based on Raman spectroscopy. The first is the quantitative analysis of the mass concentration of microplastics in suspension. Raman spectroscopy was used to measure the characteristic peak intensity of microplastic suspension calibrated by silica,and the relationship between the characteristic peak intensity, and the concentration of microplastics was studied. The results showed a good correlation between the concentration of microplastics and the characteristic peak intensity (R2=0.96), but this method needed stirring and ultrasonic oscillation to prepare the suspension in advance. Before the measurement, the characteristic peak intensity of microplastic suspension should be calibrated by silica. Moreover, the result was not good when the concentration was high. All these problems reduced the practicability of this method. The second is quantitative analysis of microplastics’ quality on the filter membrane’s surface. The aerosol generator generates microplastic aerosol samples, which were collected on the surface of the filter membrane. Raman mapping mode was used to measure the characteristic peaks of microplastic samples on the filter to determine the existence of microplastics to determine the correlation between peak recognition frequency and the mass of microplastic on filter. The results showed a good correlation between peak recognition frequency and the mass of microplastic measured by this method (R2=0.95). However, the traditional sampling method made microplastic samples unevenly distributed in a large area and made a small proportion of the measurement area. All these problems led to a large relative measurement error (2%~6%). In this study, aerosol micro-concentration technology was used to sample under the condition of keeping the surface deposition density of samples unchanged to reduce the deposition area of samples, reduce the collection amount of microplastic samples and increase the proportion of measurement area. The results showed that the correlation between peak recognition frequency and mass of microplastic could be effectively improved by aerosol micro-concentration technology (R2=0.97), and the relative measurement error could be reduced to 2%~4%. This method does not need complex operations such as preparation and calibration of the microplastic suspension, and it can directly collect microplastics in the air on the filter for quantitative analysis of microplastic quality, reducing the time required for measurement. This method is expected to be applied in the real-time measurement of microplastics in the environment.
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Received: 2022-02-24
Accepted: 2022-06-24
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[1] Geyer Roland, Jambeck Jenna R, Law Kara Lavender. Science Advances, 2017, 3(7): e1700782.
[2] Wang Jiajia, Zheng Lixia, Li Jinhui. Waste Management & Research, 2018, 36(10): 898.
[3] XU Pei, PENG Gu-yu, ZHU Li-xin, et al(徐 沛,彭谷雨,朱礼鑫,等). China Environmental Science(中国环境科学), 2019, 39(5): 2071.
[4] QU Sha-sha, ZHU Hui-juan, LIU Feng-ping, et al(屈沙沙, 朱会卷, 刘锋平,等). Journal of Hygiene Research(卫生研究), 2018, 46(6): 986.
[5] CAI Hui-wen, DU Fang-ni, ZHANG Wei-wei, et al(蔡慧文,杜方旎,张微微,等). Research of Environmental Sciences, 2021, 34(11): 2547.
[6] Kaeppler Andrea, Fischer Dieter, Oberbeckmann Sonja, et al. Analytical and Bioanalytical Chemistry, 2016, 408(29): 8377.
[7] YANG Si-jie, FENG Wei wei, CAI Zong-qi, et al(杨思节,冯巍巍,蔡宗岐,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2021, 41(8): 2469.
[8] Lynch John A, Birch Quinn T, Ridgway Thomas H,et al. Annals of Work Exposures and Health, 2018, 62(5): 604.
[9] LIU Dan-tong, SONG Yang, LI Fei-fei, et al(刘丹童,宋 洋,李菲菲,等). China Environmental Science(中国环境科学), 2020, 40(10): 4429.
[10] JIANG Cheng-zhi, SUN Qiang, LIU Ying, et al(姜承志,孙 强,刘 英,等). Acta Optica Sinica(光学学报), 2014, 34(6): 307.
[11] Zheng Lina, Kulkarni Pramod, Zavvos Konstantinos, et al. Journal of Aerosol Science, 2017, 104: 66.
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