Molecular Insights into the Transformation Mechanisms of Dissolved Organic Matter Based on Ultrahigh Resolution Mass Spectrometry

doi:10.6023/A22010044

Abstract

In this study, the removal of dissolved organic matter (DOM) in pharmaceutical wastewater effluent by five treatment processes [including ultraviolet (UV), UV/H₂O₂, potassium persulfate (PS), carbon nano tubes (CNTs) and CNTs/PS] was investigated, which was characterized by excitation-emission matrix spectra spectroscopy (EEM), total dissolved carbon (TOC), zeta potential and dynamic light scattering analysis, while the transformation mechanism of DOM fractionations induced by PS, CNTs and CNTs/PS processes was further explored by ultra-high-resolution mass spectrometry (UPLC-Q-TOF-MS). The results suggested that the PS, CNTs and CNTs/PS processes proved to have the best treatment effect for the removal of DOM via EEM analysis, with TOC removal of 128, 204 and 243 mg/L, respectively. Zeta potential and dynamic light scattering analysis indicated that DOM molecules were removed by PS process through electrostatic polymerization and oxidation, and by CNTs process via adsorption, while CNTs/PS process degraded DOM by combining adsorption, electron transfer and the generation of strongly oxidizing singlet oxygen (¹O₂). Molecular characterization analysis demonstrated that the condensed aromatic compounds (76%) and proteins/lipids (65%) in DOM were the most vulnerable to PS attack, and the adsorption of CNTs was more effective for oxygenated compounds with lower levels of unsaturation (such as lignin, protein polypeptides and amino sugars (90%)), while the CNTs/PS process achieved indiscriminate degradation of various DOM molecules, which was a complement and enhancement to the separate CNT and PS treatment processes. In terms of different elemental compositions, the PS process had little effect on the elemental composition of the residual DOM molecules, while the CNTs and CNTs/PS processes showed a more obvious effect on the removal of CHON and CHONS molecules. Furthermore, by combining the quantitative distribution of chemical parameters of DOM molecules and linear fitting analysis, PS and CNTs/PS system had little effect on the distribution of chemical parameters of residual DOM molecules, while the adsorption of CNTs would lead to an increase in the average O/C, aromaticity index (AI_mod), double bond equivalence (DBE) and nominal oxidation state of carbon (NOSC) value of residual molecules, and the contribution of oxygen atoms to DBE. The results of this study provide important information for further understanding the behavior of DOM in the aquatic environment during various processes.

Key words: dissolved organic matter, potassium persulfate, carbon nanotubes, high resolution mass spectrum, molecular transformation

Cite this article

Shouming Cheng, Bo Zhou. Molecular Insights into the Transformation Mechanisms of Dissolved Organic Matter Based on Ultrahigh Resolution Mass Spectrometry[J]. Acta Chimica Sinica, 2022, 80(8): 1106-1114.

Export EndNote|Reference Manager|ProCite|BibTeX|RefWorks

share this article

Fig. & Tab. 10

Figure 1. EEM spectra of (a) pristine samples, and the samples reaction after (b) UV, (c) UV/H2O2, (d) PS, (e) CNTs and (f) CNTs/PS processes [H2O2]=100 mmol/L, [PS]=100 mmol/L, [CNTs]=1 g/L, pH 8.5, [DOC]0=1258 mg/L, processing time t=60 min

Region	Typical substance class	Excitation wavelength/nm	Emission wavelength/nm
I	Aromatic protein I	200~250	280~330
II	Aromatic protein II	200~250	330~380
III	Fulvic acid-like	200~250	380~550
IV	Soluble microbial byproduct-like	250~400	280~380
V	Humic acid-like	250~400	380~550

Table 1. Excitation and emission wavelength boundaries of the five regions of the EEM spectrum

Figure 2. (a) Zeta potential and average molecular size analysis of water samples before and after treatment; (b) molecular size distribution and cumulative distribution percentage of water samples before and after treatment [PS]=100 mmol/L, [CNTs]=1 g/L, pH 8.5, [DOC]0=1258 mg/L

Figure 3. Mass spectrum of pristine samples and after reaction in (a) PS process, (b) CNTs process and (c) CNTs/PS process; (d) distribution comparation of DOM molecules weight [PS]=100 mmol/L, [CNTs]=1 g/L, pH 8.5, [DOC]0=1258 mg/L, processing time t=60 min

Figure 4. Van Krevelen diagrams of DOM in pharmaceutical wastewater effluent after reaction in (a) PS process, (b) CNTs process and (c) CNTs/PS process; (d) statistics on the number of removed, residual and product molecules. Points in green represent peaks that disappeared after reaction (removed), points in pink represent peaks that were unchanged (resistant), and points in blue denote new peaks that appeared after reaction (produced)

Region	Compound class	H/C	O/C
I	Lipids	1.5~2.0	0~0.3
II	Proteins	1.5~2.2	0.3~0.52
III	Aminosugars	1.5~2.2	0.67~1.2
IV	Lignins	0.7~1.5	0.1~0.67
V	Carbohydrates	1.5~2.4	0.67~1.2
VI	Unsaturated hydrocarbons	0.7~1.5	0~0.1
VII	Condensed aromatic structures	0.2~0.7	0~0.67
VIII	Tannins	0.5~1.5	0.67~1.2

Table 2. Demarcation boundary of different biochemical components based on van Krevelen diagram

Figure 5. (a) Radar charts of different biochemical classifications recognized in the Van Krevelen diagrams; (b) Radar charts of different molecular formula classifications

Figure 6. (a) Changes of molecule number of the four major subcategories (CHO, CHON, CHOS, CHONS) before and after reaction; (b) changes of relative percentage contribution of the four major subcategories

Figure 7. Quantitative distributions of O/C (a), H/C (b), AImod (c), DBE (d) and NOSC (e) of molecules before and after reaction in PS, CNTs and CNTs/PS processes

Figure 8. DBEaverage as a function of the number of O atoms in molecular formulas before (a) and after reaction in (b) PS, (c) CNTs and (d) CNTs/PS processes DBEaverage as a function of the number of O atoms in molecular formulas before (a) and after reaction in (b) PS, (c) CNTs and (d) CNTs/PS processes

References 25

[1]	Kalinichev, A.-G.; Kirkpatrick, R.-J. Eur. J. Soil. Biol. 2007, 58, 909.
[2]	Adusei-Gyamfi, J.; Ouddane, B.; Rietveld, L.; Cornard, J.-P.; Criquet, J. Water Res. 2019, 160, 130. doi: S0043-1354(19)30452-X pmid: 31136847
[3]	Bravo, A.-G; Bouchet, S.; Tolu, J.; Bjorn, E.; Mateos-Rivera, A.; Bertilsson, S. Nat. Commun. 2017, 8, 14255. doi: 10.1038/ncomms14255
[4]	Knauer, K.; Homazava, N.; Junghans, M.; Werner, I. Integr. Environ. Assess. Manage. 2017, 13, 585. doi: 10.1002/ieam.1867
[5]	Chu, W.; Krasner, S.-W.; Gao, N.; Templeton, M.-R.; Yin, D. Environ. Sci. Technol. 2016, 50, 388. doi: 10.1021/acs.est.5b04856
[6]	Davis, C.-C.; Edwards, M. Environ. Sci. Technol. 2017, 51, 11652. doi: 10.1021/acs.est.7b02038
[7]	Metsämuuronen, S.; Sillanpää, M.; Bhatnagar, A.; Mänttäri, M. Sep. Purif. Rev. 2014, 43, 1. doi: 10.1080/15422119.2012.712080
[8]	Li, H.; Li, A.; Shuang, C.; Zhou, Q.; Li, W. Water. Res. 2014, 66, 233. doi: 10.1016/j.watres.2014.08.027
[9]	Von Gunten, U. Environ. Sci. Technol. 2018, 52, 5062. doi: 10.1021/acs.est.8b00586 pmid: 29672032
[10]	Liu, Y.-C.; Su, M.-M.; Zhang, Y.; Duan, J.-M.; Li, W. Acta Chim. Sinica 2019, 77, 72. (in Chinese) doi: 10.6023/A18090365
	(刘玉灿, 苏苗苗, 张岩, 段晋明, 李伟, 化学学报, 2019, 77, 72.) doi: 10.6023/A18090365
[11]	Fang, Z.; Huang, R.; How, Z.-T.; Jiang, B.; Chelme-Ayala, P.; Shi, Q.; Xu, C.; Gamal El-Din, M. Sci. Total. Environ. 2020, 730, 139072. doi: 10.1016/j.scitotenv.2020.139072
[12]	Yang, B.; Cheng, X.; Zhang, Y.-L.; Li, W.; Wang, J.-Q; Guo, H.-G. Environ. Sci. Ecotechnol. 2021, 8, 100127. doi: 10.1016/j.ese.2021.100127
[13]	Cheng, X.; Guo, H.; Zhang, Y.; Korshin, G. V.; Yang, B. Water. Res. 2019, 157, 406. doi: S0043-1354(19)30297-0 pmid: 30978663
[14]	Lv, J.; Zhang, S.; Wang, S.; Luo, L.; Cao, D.; Christie, P. Environ. Sci. Technol. 2016, 50, 2328. doi: 10.1021/acs.est.5b04996
[15]	Zhou, Y.; Gao, Y.; Jiang, J.; Shen, Y.-M.; Pang, S.-Y.; Wang, Z.; Duan, J.-B.; Guo, Q.; Guan, C.-T.; Ma, J. Chem. Eng. J. 2020, 379, 122378. doi: 10.1016/j.cej.2019.122378
[16]	Yang, F.; Zhang, Q.; Jian, H.; Wang, C.; Xing, B.; Sun, H.; Hao, Y. J. Hazard. Mater. 2020, 396, 122598. doi: 10.1016/j.jhazmat.2020.122598
[17]	Yang, B.; Wang, C.; Cheng, X.; Zhang, Y.; Li, W.; Wang, J.; Tian, Z.; Chu, W.; Korshin, G.-V.; Guo, H.-G. Water Res. 2021, 202, 117379. doi: 10.1016/j.watres.2021.117379
[18]	Yang, B.; Zhang, Y.-L. Acta Chim. Sinica 2019, 77, 1017. (in Chinese) doi: 10.6023/A19060203
	(杨波, 张永丽, 化学学报, 2019, 77, 1017.) doi: 10.6023/A19060203
[19]	Cheng, X.; Guo, H.; Zhang, Y.; Wu, X.; Liu, Y. Water. Res. 2017, 113, 80. doi: S0043-1354(17)30091-X pmid: 28199865
[20]	Yuan, Z.; He, C.; Shi, Q.; Xu, C.; Li, Z.; Wang, C.; Zhao, H.; Ni, J. Environ. Sci. Technol. 2017, 51, 8110. doi: 10.1021/acs.est.7b02194
[21]	Bae, E.; Yeo, I. J.; Jeong, B.; Shin, Y.; Shin, K. H.; Kim, S. Anal. Chem. 2011, 83, 4193. doi: 10.1021/ac200464q
[22]	Yang, B; Zhang, Y.-L.; Guo, H.-G. Acta Chim. Sinica 2021, 79, 1494. (in Chinese) doi: 10.6023/A21080408
	(杨波, 张永丽, 郭洪光, 化学学报, 2021, 79, 1494.) doi: 10.6023/A21080408
[23]	Riedel, T.; Biester, H.; Dittmar, T. Environ. Sci. Technol. 2012, 46, 4419. doi: 10.1021/es203901u
[24]	Ren, X.-D.; Xiong, Z.-H. Acta Chim. Sinica 2013, 71, 625. (in Chinese) doi: 10.6023/A12110910
	(任晓东, 熊振湖, 化学学报, 2013, 71, 625.) doi: 10.6023/A12110910
[25]	Schaumann, G. E.; Thiele-Bruhn, S. Geoderma 2011, 166, 1. doi: 10.1016/j.geoderma.2011.04.024

基于超高分辨质谱的溶解性有机质分子转化机理分析