Data fusion strategy based on ultraviolet-visible spectra and near-infrared spectra for simultaneous and accurate determination of key parameters in surface water

Zhuopin Xu; Xiaohong Li; Weimin Cheng; Guangxia Zhao; Liwen Tang; Yang Yang; Yuejin Wu; Pengfei Zhang; Qi Wang

doi:10.1016/j.saa.2023.123007

Data fusion strategy based on ultraviolet-visible spectra and near-infrared spectra for simultaneous and accurate determination of key parameters in surface water

Spectrochim Acta A Mol Biomol Spectrosc. 2023 Dec 5:302:123007. doi: 10.1016/j.saa.2023.123007. Epub 2023 Jun 12.

Authors

Zhuopin Xu¹, Xiaohong Li², Weimin Cheng², Guangxia Zhao², Liwen Tang³, Yang Yang¹, Yuejin Wu¹, Pengfei Zhang⁴, Qi Wang⁵

Affiliations

¹ Anhui Key Laboratory of Environmental Toxicology and Pollution Control Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, People's Republic of China.
² Anhui Key Laboratory of Environmental Toxicology and Pollution Control Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, People's Republic of China; University of Science and Technology of China, No. 96 Jinzhai Road, Hefei 230026, People's Republic of China.
³ Anhui Key Laboratory of Environmental Toxicology and Pollution Control Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, People's Republic of China; Institutes of Physical Science and Information Technology, Anhui University, Hefei 230601, People's Republic of China.
⁴ Anhui Key Laboratory of Environmental Toxicology and Pollution Control Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, People's Republic of China. Electronic address: pfzhang@aiofm.ac.cn.
⁵ Anhui Key Laboratory of Environmental Toxicology and Pollution Control Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, People's Republic of China. Electronic address: wangqi@ipp.ac.cn.

PMID: 37393670
DOI: 10.1016/j.saa.2023.123007

Abstract

Chemical oxygen demand (COD), ammonia nitrogen (AN) and total nitrogen (TN) are the key parameters to reflect the degree of surface water pollution. Ultraviolet - visible (UV-Vis) spectroscopy and near - infrared (NIR) spectroscopy are ideal techniques for rapid monitoring of these indicators. In this study, a strategy based on the fusion of UV-Vis and NIR spectral data (UV-Vis-NIR) for water quality detection was proposed to further improve the quantitative analysis accuracy of spectroscopic methods. Seventy river samples with different levels of pollution were used for spectroscopic analysis. The UV-Vis-NIR fusion spectrum of each water sample was obtained by directly splicing sample's UV-Vis spectrum and NIR diffuse transmission spectrum. The UV-Vis-NIR fusion models were optimized through using different variable selection algorithms. The results show that the UV-Vis-NIR fusion models for surface water COD, AN and TN achieves better prediction results (the root mean square errors of prediction are 6.95, 0.195, and 0.466, respectively) than single-spectroscopic based models. Since better prediction performances were shown under different optimization conditions, the robustness of fusion models were also better than the single-spectroscopic based models. Therefore, the data fusion strategy proposed in this study has a promising application prospect for further accurate and rapid monitoring of surface water quality.

Keywords: Ammonia nitrogen; Chemical oxygen demand; Data fusion; Near-infrared spectroscopy; Surface water; Ultraviolet–visible spectroscopy.