Four-metal-element quantitative analysis and pollution source discrimination in atmospheric sedimentation by laser-induced breakdown spectroscopy (LIBS) coupled with machine learning-Reference-Cited by-同舟云学术

Four-metal-element quantitative analysis and pollution source discrimination in atmospheric sedimentation by laser-induced breakdown spectroscopy (LIBS) coupled with machine learning

Published:2020 Issue:2 Volume:35 Page:403-413
ISSN:0267-9477
Container-title:Journal of Analytical Atomic Spectrometry
language:en
Short-container-title:J. Anal. At. Spectrom.

Author:

Zhang Xin¹²³⁴⁵,Li Nan¹²³⁴⁵,Yan Chunhua¹²³⁴⁵,Zeng Jiahui¹²³⁴⁵,Zhang Tianlong¹²³⁴⁵^ORCID,Li Hua¹²³⁴⁵^ORCID

Affiliation:

1. Key Laboratory of Synthetic and Natural Functional Molecular Chemistry of Ministry of Education

2. College of Chemistry & Materials Science

3. Northwest University

4. Xi'an

5. China

Abstract

The laser-induced breakdown spectroscopy (LIBS) technique coupled with machine learning was proposed to perform four metal elements quantitative analysis and pollution source discrimination in atmospheric sedimentation.

Funder

National Natural Science Foundation of China

Publisher

Royal Society of Chemistry (RSC)

Subject

Spectroscopy,Analytical Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2020/JA/C9JA00360F

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1. Transboundary health impacts of transported global air pollution and international trade

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4. Biomonitoring trace element contamination impacted by atmospheric deposition in China's remote mountains

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