Probing nitro(so) and chloro byproducts and their precursors in natural organic matter during UV/NHCl treatment by FT-ICR MS with machine learning insights.

Journal: Water research
PMID: 39018583

Abstract

The UV/monochloramine (UV/NHCl) process, while efficiently eliminating micropollutants, produces toxic byproducts. This study utilized Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) to investigate molecular-level changes in natural organic matter (NOM) and to disclose formation pathways of nitro(so) and chloro byproducts in the UV/NHCl process. The UV/NHCl process significantly increased the saturation and oxidation levels and altered the elemental composition of NOM. Using N labeling and a screening workflow, nitro(so) byproducts with nitrogen originating from inorganic sources (i.e., reactive nitrogen species (RNS) and/or NHCl) were found to exhibit total intensities comparable to those from NOM. RNS, rather than NHCl, played a significant role in incorporating nitrogen into NOM. Through linkage analysis, nitro(so) addition emerged as an important reaction type among the 25 reaction types applied. By using phenol as a representative model compound, the nitro byproducts were confirmed to be mainly generated through the oxidation of nitroso byproducts instead of nitration. Machine learning and SHAP analysis further identified the major molecular indices distinguishing nitro(so) and chloro precursors from non-precursors. This study enhances our fundamental understanding of the mechanisms driving the generation of nitro(so) and chloro byproducts from their precursors in complex NOM during the UV/NHCl process.

Authors

  • Junfang Li
    Guangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation Technology, School of Environmental Science and Engineering, Sun Yat-Sen University, Guangzhou 510275, China; College of Chemistry and Chemical Engineering, Xinjiang Agricultural University, Urumqi 830052, China.
  • Zhechao Hua
    Guangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation Technology, School of Environmental Science and Engineering, Sun Yat-Sen University, Guangzhou 510275, China.
  • Wenlei Qin
    Guangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation Technology, School of Environmental Science and Engineering, Sun Yat-Sen University, Guangzhou 510275, China.
  • Chunyan Chen
    Guangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation Technology, School of Environmental Science and Engineering, Sun Yat-Sen University, Guangzhou, 510275, PR China.
  • Bao Zhu
    State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
  • Ting Ruan
    Key Laboratory of Food Quality and Safety of Guangdong Province, College of Food Science, South China Agricultural University, Guangzhou, 510642, China.
  • Yingying Xiang
    Nanyang Environment & Water Research Institute, Nanyang Technological University, 637141, Singapore; Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon 000, Hong Kong SAR, PR China. Electronic address: yxiangab@connect.ust.hk.
  • Jingyun Fang
    State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China; University of Chinese Academy of Sciences, Beijing 100049, China; Department of Ecology, Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, Beijing 100871, China. Electronic address: jyfang@urban.pku.edu.cn.

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