TY - JOUR
T1 - Application of Fourier transform ion cyclotron resonance mass spectrometry to characterize natural organic matter
AU - Zhang, Xiaoxiao
AU - Han, Jiarui
AU - Zhang, Xiangru
AU - Shen, Jimin
AU - Chen, Zhonglin
AU - Chu, Wei
AU - Kang, Jing
AU - Zhao, Shengxin
AU - Zhou, Yaoyu
N1 - Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2020/12
Y1 - 2020/12
N2 - Advances in the ultra-high-resolution mass spectroscopy lead to a deep insight into the molecular characterization of natural organic matter (NOM). Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) has been used as one of the most powerful tools to decipher NOM molecules. In FTICR-MS analysis, the matrix effects caused by the co-occurring inorganic substances in water samples greatly affect the ionization of NOM molecules. The inherent complexity of NOM may hinder its component classification and formula assignment. In this study, basic principles and recent advances for sample separation and purification approaches, ionization methods, and the evolutions in formula assignment and data exploitation of the FTICR-MS analysis were reviewed. The complementary characterization methods for FTICR-MS were also reviewed. By coupling with other developed/developing characterization methods, the statistical confidence for inferring the NOM compositions by FTICR-MS was greatly improved. Despite that the refined separation procedures and advanced data processing methods for NOM molecules have been exploited, the big challenge for interpreting NOM molecules is to give the basic structures of them. Online share of the FTICR-MS data, further optimizing the FTICR-MS technique, and coupling this technique with more characterization methods would be beneficial to improving the understanding of the composition and property of NOM.
AB - Advances in the ultra-high-resolution mass spectroscopy lead to a deep insight into the molecular characterization of natural organic matter (NOM). Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) has been used as one of the most powerful tools to decipher NOM molecules. In FTICR-MS analysis, the matrix effects caused by the co-occurring inorganic substances in water samples greatly affect the ionization of NOM molecules. The inherent complexity of NOM may hinder its component classification and formula assignment. In this study, basic principles and recent advances for sample separation and purification approaches, ionization methods, and the evolutions in formula assignment and data exploitation of the FTICR-MS analysis were reviewed. The complementary characterization methods for FTICR-MS were also reviewed. By coupling with other developed/developing characterization methods, the statistical confidence for inferring the NOM compositions by FTICR-MS was greatly improved. Despite that the refined separation procedures and advanced data processing methods for NOM molecules have been exploited, the big challenge for interpreting NOM molecules is to give the basic structures of them. Online share of the FTICR-MS data, further optimizing the FTICR-MS technique, and coupling this technique with more characterization methods would be beneficial to improving the understanding of the composition and property of NOM.
KW - Formula assignment
KW - Ionization
KW - Kendrick mass analysis
KW - Mass spectrometry
KW - Natural organic matter
UR - https://www.webofscience.com/wos/woscc/full-record/WOS:000575197000005
UR - https://openalex.org/W3037485837
UR - https://www.scopus.com/pages/publications/85088022049
U2 - 10.1016/j.chemosphere.2020.127458
DO - 10.1016/j.chemosphere.2020.127458
M3 - Review article
C2 - 32693253
SN - 0045-6535
VL - 260
JO - Chemosphere
JF - Chemosphere
M1 - 127458
ER -