\documentclass[10pt]{article}

\usepackage{fullpage}
\usepackage{setspace}
\usepackage{parskip}
\usepackage{titlesec}
\usepackage[section]{placeins}
\usepackage{xcolor}
\usepackage{breakcites}
\usepackage{lineno}
\usepackage{hyphenat}





\PassOptionsToPackage{hyphens}{url}
\usepackage[colorlinks = true,
            linkcolor = blue,
            urlcolor  = blue,
            citecolor = blue,
            anchorcolor = blue]{hyperref}
\usepackage{etoolbox}
\makeatletter
\patchcmd\@combinedblfloats{\box\@outputbox}{\unvbox\@outputbox}{}{%
  \errmessage{\noexpand\@combinedblfloats could not be patched}%
}%
\makeatother


\usepackage{natbib}




\renewenvironment{abstract}
  {{\bfseries\noindent{\abstractname}\par\nobreak}\footnotesize}
  {\bigskip}

\titlespacing{\section}{0pt}{*3}{*1}
\titlespacing{\subsection}{0pt}{*2}{*0.5}
\titlespacing{\subsubsection}{0pt}{*1.5}{0pt}


\usepackage{authblk}


\usepackage{graphicx}
\usepackage[space]{grffile}
\usepackage{latexsym}
\usepackage{textcomp}
\usepackage{longtable}
\usepackage{tabulary}
\usepackage{booktabs,array,multirow}
\usepackage{amsfonts,amsmath,amssymb}
\providecommand\citet{\cite}
\providecommand\citep{\cite}
\providecommand\citealt{\cite}
% You can conditionalize code for latexml or normal latex using this.
\newif\iflatexml\latexmlfalse
\providecommand{\tightlist}{\setlength{\itemsep}{0pt}\setlength{\parskip}{0pt}}%

\AtBeginDocument{\DeclareGraphicsExtensions{.pdf,.PDF,.eps,.EPS,.png,.PNG,.tif,.TIF,.jpg,.JPG,.jpeg,.JPEG}}

\usepackage[utf8]{inputenc}
\usepackage[greek,english]{babel}



\usepackage{float}








\begin{document}

\title{From mass to structure: modified van Krevelen diagram and adjusted
indexes for high-resolution mass data of organic matter}



\author[1]{Yang Xiaoqiu}%
\author[1]{Hechao Chen}%
\author[1]{Jing Wu}%
\author[1]{Yaofei Li}%
\author[1]{Yulin Zhang}%
\author[1]{Qiwei Zhang}%
\affil[1]{Jianghan University Key Laboratory of Optoelectronic Chemical Materials and Devices}%


\vspace{-1em}



  
  \date{June 07, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
The traditional van Krevelen diagram, the nominal oxidation of organic
carbon, and several aromaticity indexes generally considered C, H, O, N,
P, and S factors, or just C, H, and O. However, these evaluated methods
may provide incorrect interpretation for high-resolution mass data of
organics containing halogen elements. Therefore, we adapted the van
Krevelen diagram and the other indexes with halogen elements and
verified with 2235 model organics. The results demonstrated that the
modified van Krevelen diagram and the adjusted indexes were more
accurate for the analysis of mass data, either in the compound
classification or in the evaluation of oxidation state of organic
matter.%
\end{abstract}%



\sloppy


\textbf{From mass to structure: modifiedvan Krevelen diagram and
adjusted indexes for high-resolution mass data of organic matter}

Dear Editor:

The development of high-resolution mass spectrometry (HRMS) has led to
deeper insight into the molecular characterization of organic matter.
However, a large amount of data obtained by HRMS cannot be immediately
converted into specific substances, especially for Fourier transform ion
cyclotron resonance mass spectrometry. Some methods have been developed
to further explore the information obtained by HRMS by interpreting the
data and predicting structures based on exact molecular weight and
element constituent patterns.\textsuperscript{1} Of these methods, the
van Krevelen diagram is widely used to classify of organic matter by
plotting atomic ratios of H/C and O/C in two-dimensional
ordinations.\textsuperscript{2} In addition, some index are employed to
evaluate molecular characterizations, such as the nominal oxidation
state of carbon (NOSC)\textsuperscript{3} and the aromaticity index (AI,
AImod and Xc),\textsuperscript{4,5}. While the traditional van Krevelen
diagram and the indexes were mainly targeted at natural organic matter
(NOM), the calculation equations normally considered C, H, O, N, P, and
S factors, or just C, H, and O. However, for organic matter,
particularly environmental contaminants and artificial chemicals,
halogen elements are important elements and their chemical and
toxicological properties cannot be overlooked. \textsuperscript{6-8}
Moreover, the application of HRMS in environmental pollutants and
anthropogenic organics is increasing, \textsuperscript{8,9} and the
ability to more accurately interpret large amounts of data is essential.
Therefore, we adapted the van Krevelen diagram and the other indexes
with halogen elements for the analysis of organic matter with complex
constituents.

To verify the modified van Krevelen diagram and the adjusted indexes,
chemical formulas of 2235 organics were evaluated, which originated from
a web database of disinfection byproducts
(\emph{http://dbps.com.cn/\#/main)} . The results were compared and
depicted as follows:

\textbf{The van Krevelen diagram}

The van Krevelen diagram is normally depicted as a two-dimensional plot
using the molar ratio of hydrogen to carbon (H/C) as the ordinate and
the molar oxygen-to-carbon ratio (O/C) as the
abscissa.\textsuperscript{2} The H/C ratio separates compounds according
to the degree of saturation, whereas O/C ratios separate compounds
according to O classes.\textsuperscript{10} Halogens are generally
bonded to organic matter by replacing hydrogen, so their contribution to
valence bond saturation should be equivalent to that of hydrogen. For
halogen-containing organics, if only the H/C ratio is considered, the
material structure will be misjudged. For example, the H/C ratio of
trichloromethane is 1, and it is classified as an unsaturated compound
by the traditional van Krevelen diagram; however, trichloromethane is a
typical saturated organic matter. When halogen is introduced to the
calculation of the H/C ratio, H(X)/C (H(X) is the sum of H and halogen
elements) of trichloromethane is 4, which is an apparent characteristic
of saturated compounds. Fig. 1(a) and (b) show the traditional van
Krevelen diagram with H/C versus O/C and the modified van Krevelen
diagram with H(X)/C versus O/C, respectively. The distribution of
organics clearly shifts upward in the diagram. In particular, compounds
with H/C ratios lower than 0.5 are classified as condensed aromatic
hydrocarbons,\textsuperscript{11,12}while almost no condensed aromatic
compounds are found in the 141 compounds with H/C ratios lower than 0.5
in the database. These compounds are mostly multihalogen substituted
organics with H(X)/C ranging from 0.67 to 4. The above results indicate
that using the modified van Krevelen diagram plotted with H(X)/C versus
O/C could provide a more accurate classification for the organic matter
detected by HRMS.

\textbf{The oxidation of organic carbon}

Three indexes are used to evaluate the oxidation state of organic
carbon, including Cox,\textsuperscript{3} NOSC,\textsuperscript{13} and
CHO.\textsuperscript{11} The equations of these three indexes are
calculated as follows:

Cox = (2O+2S-H+3N-5P)/C (1) NOSC = -((-Z+4C+H-3N-2O+5P-2S)/C)+4 (2) CHO
= (2O-H)/C (3)

In these three equations, C, O, H, N, P, and S represent the
stoichiometric numbers of the elements C, O, H, N, P and S,
respectively. Z in Eqn. (2) is the net charge of organic matter. Cox and
CHO are special cases of NOSC. When Z=0, Cox = NOSC, and when the
stoichiometric numbers of the heteroatoms are zero, CHO = NOSC. However,
even NOSC ignores the contribution of halogen to the oxidation state of
organic carbon. According to the definition of NOSC and
Cox,\textsuperscript{3,13} we recommend the equation used to adjust
NOSC, which is depicted as NOSC': NOSC' =
-((-Z+4C+H-3N-2O+5P-2S-X)/C)+4. In the equation of NOSC', X is the sum
of stoichiometric numbers of halogen elements (F, Cl, Br, I).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

Fig. 1 (a) The traditional van Krevelen diagram; (b) The modified van
Krevelen diagram; (c) The modified van Krevelen diagram associated with
NOSC; (d) The modified van Krevelen diagram associated with NOSC'. (In
(a) and (b), the red dots symbol the compounds with H/C\textless{}1.5,
the green dots are the compounds with 1.5[?]H/C\textless{}2.0, and the
blue dots are the compounds with H/C[?]2.0; NOSC: the nominal oxidation
state of carbon; NOSC': the adjusted nominal oxidation state of carbon)

Fig. 1(c) and (d) demonstrate the modified van Krevelen diagrams
associated with NOSC and NOSC', respectively. It can be seen that the
compounds with NOSC'\textgreater{}0 are slightly higher than those with
NOSC\textgreater{}0. Among the 2235 organics in the database,
approximately 21.3\% with NOSC\textless{}0 in Fig. 1(c) change into that
with NOSC'[?]0 in Fig. 1(d). Generally, compounds with NOSC\textgreater{}0
are more oxidized and less degradable, while those with NOSC\textless{}0
are more likely degraded. When the impact of halogen is not considered,
the oxidation state of organic carbon is underestimated, and the
degradation potential of organic matter is overestimated.

\textbf{Aromatic indexes}

Three methods were used for calculating the aromaticity index, including
AI, AImod \textsuperscript{4} and Xc.\textsuperscript{5} Of them, AI was
suggested for compounds in which oxygen was mainly present as carbonyl
functional groups; AImod was adjusted on the basis of AI when oxygen
could also be bound with \selectlanguage{greek}π-\selectlanguage{english}bonds in carboxyl
groups;\textsuperscript{12}and Xc was aimed at aromatic compounds with
long alkylation.\textsuperscript{5} Considering the contribution of
halogen elements to the saturation of organic matter, we adjusted these
three indexes based on the original equations and put forward them as
AI', AImod' and Xc', respectively. The equations used to calculate the
tree adjusted indexes are as follows:

AI' = (1+C-O-S-0.5(N+P+H+X))/(C-O-N-S-P) AImod' =
(1+C-0.5O-S-0.5(N+P+H+X)/(C-0.5O-N-S-P) Xc' =
{[}3((1+C-0.5(H+X)+0.5(N+P)-(O+S))-2{]}/(1+C-0.5(H+X)+0.5(N+P)-(O+S))\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

Fig. 2 Comparison of AImod and AImod' with actual data (organics with
AImod or AImod'[?]0.67 are classified as condensed aromatics, and those
with 0.5[?]AImod or AImod' \textless{}0.67 are categorized as aromatics)

According to the structures of the 2235 organics, a comparison between
AImod and AImod' was chosen to determine the validity of the adjusted
aromatic indexes (as shown in Fig. 2). The proportions of condensed
aromatics and aromatics predicted by AImod' are closer to the actual
data than those predicted by AImod.

In summary, introducing halogen to the interpretation models of HRMS
data for organic matter improves the accuracy. The modified van Krevelen
diagram, NOSC and aromatic indexes are equivalent for multiple organic
matter, including NOM, emerging environmental pollutants, and artificial
products.

\textbf{Acknowledgments}

The authors gratefully acknowledge the advice of Pro. Chenggang Zhou
from China University of Geosciences. This work was supported by the
Hubei Provincial Department of Education (General Guiding Project,
B2022279).

\emph{Hechao Chen\textsuperscript{1}, Jing Wu\textsuperscript{1}, Yaofei
Li\textsuperscript{1}, Yulin Zhang\textsuperscript{1}, Qiwei
Zhang\textsuperscript{1}, Xiaoqiu Yang\textsuperscript{1}*}

1. Key Laboratory of Optoelectronic Chemical Materials and Devices of
Ministry of Education, School of Optoelectronic Materials \& Technology,
Jianghan University, Wuhan 430056, China

*Corresponding to X.Q. Yang, School of Optoelectronic Materials \&
Technology, Jianghan University, Wuhan 430056, China.
Email:\emph{xiaoqiuyang@jhun.edu.cn}

\textbf{References}

1. Zhang XX, Han JR, Zhang XR, et al. Application of Fourier transform
ion cyclotron resonance mass spectrometry to characterize natural
organic matter. \emph{Chemosphere.} 2020;260.

2. Kim S, Kramer RW, Hatcher PG. Graphical method for analysis of
ultrahigh-resolution broadband mass spectra of natural organic matter,
the van Krevelen diagram. \emph{Anal Chem.} 2003;75(20):5336-5344.

3. Masiello CA, Gallagher ME, Randerson JT, Deco RM, Chadwick OA.
Evaluating two experimental approaches for measuring ecosystem carbon
oxidation state and oxidative ratio. \emph{Journal of Geophysical
Research: Biogeosciences.} 2008;113(G3).

4. Koch BP, Dittmar T. From mass to structure: an aromaticity index for
high-resolution mass data of natural organic matter (vol 20, pg 926,
2006). \emph{Rapid Commun Mass Spectrom.} 2016;30(1):250-250.

5. Yassine MM, Harir M, Dabek-Zlotorzynska E, Schmitt-Kopplin P.
Structural characterization of organic aerosol using Fourier transform
ion cyclotron resonance mass spectrometry: Aromaticity equivalent
approach. \emph{Rapid Commun Mass Spectrom.} 2014;28(22):2445-2454.

6. Richardson SD, Ternes TA. Water Analysis: Emerging Contaminants and
Current Issues. \emph{Anal Chem.} 2022;94(1):382-416.

7. Richardson SD, Plewa MJ, Wagner ED, Schoeny R, Demarini DM.
Occurrence, genotoxicity, and carcinogenicity of regulated and emerging
disinfection by-products in drinking water: a review and roadmap for
research. \emph{Mutat Res.} 2007;636(1-3):178-242.

8. Peng H, Chen CL, Cantin J, et al. Untargeted Screening and
Distribution of Organo-Iodine Compounds in Sediments from Lake Michigan
and the Arctic Ocean. \emph{Environmental Science \&
Technology.}2016;50(18):10097-10105.

9. Zhang HF, Yang M. Characterization of brominated disinfection
byproducts formed during chloramination of fulvic acid in the presence
of bromide. \emph{Sci Total Environ.} 2018;627:118-124.

10. Wu ZG, Rodgers RP, Marshall AG. Two- and three-dimensional van
Krevelen diagrams: A graphical analysis complementary to the Kendrick
mass plot for sorting elemental compositions of complex organic mixtures
based on ultrahigh-resolution broadband Fourier transform ion cyclotron
resonance mass measurements. \emph{Anal Chem.} 2004;76(9):2511-2516.

11. Mann BF, Chen HM, Herndon EM, et al. Indexing Permafrost Soil
Organic Matter Degradation Using High-Resolution Mass
Spectrometry.\emph{Plos One.} 2015;10(6).

12. Koch BP, Dittmar T. From mass to structure: an aromaticity index for
high-resolution mass data of natural organic matter. \emph{Rapid Commun
Mass Spectrom.} 2006;20(5):926-932.

13. LaRowe DE, Van Cappellen P. Degradation of natural organic matter: A
thermodynamic analysis. \emph{Geochim Cosmochim
Acta.}2011;75(8):2030-2042.

\par\null\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Fig/Fig}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Fih/Fih}

\end{center}
\end{figure}

\selectlanguage{english}
\FloatBarrier
\end{document}

