Spectral Classification of Large-Scale Blended (Micro)Plastics Using FT-IR Raw Spectra and Image-Based Machine Learning-Reference-Cited by-同舟云学术

Spectral Classification of Large-Scale Blended (Micro)Plastics Using FT-IR Raw Spectra and Image-Based Machine Learning

Published:2023-04-13 Issue:16 Volume:57 Page:6656-6663
ISSN:0013-936X
Container-title:Environmental Science & Technology
language:en
Short-container-title:Environ. Sci. Technol.

Author:

Liu Yanlong¹,Yao Wenli¹,Qin Fenghui¹,Zhou Lei²^ORCID,Zheng Yian¹^ORCID

Affiliation:

1. Gansu Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, Gansu 730000, China

2. College of Chemistry and Chemical Engineering, Lanzhou University, Lanzhou, Gansu 730000, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Gansu Province

Publisher

American Chemical Society (ACS)

Subject

Environmental Chemistry,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.est.2c08952

Reference47 articles.

1. Predicted growth in plastic waste exceeds efforts to mitigate plastic pollution

2. A methodology for the fast identification and monitoring of microplastics in environmental samples using random decision forest classifiers

3. (Micro)plastics and the UN Sustainable Development Goals

4. Validated spreadsheet for the identification of PE, PET, PP and PS microplastics by micro-ATR-FTIR spectra with known uncertainty

5. What is known and unknown about the effects of plastic pollution: A meta‐analysis and systematic review

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