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@ARTICLE{Zherebker:180975,
      author       = {A. Zherebker and G. Rukhovich and A. Sarycheva and O. J.
                      Lechtenfeld and E. N. Nikolaev},
      title        = {{A}romaticity {I}ndex with {I}mproved {E}stimation of
                      {C}arboxyl {G}roup {C}ontribution for {B}iogeochemical
                      {S}tudies},
      journal      = {Environmental science $\&$ technology},
      volume       = {56},
      number       = {4},
      issn         = {0013-936X},
      address      = {Columbus, Ohio},
      publisher    = {American Chemical Society},
      reportid     = {DKFZ-2022-01700},
      pages        = {2729 - 2737},
      year         = {2022},
      abstract     = {Natural organic matter (NOM) components measured with
                      ultrahigh-resolution mass spectrometry (UHRMS) are often
                      assessed by molecular formula-based indices, particularly
                      related to their aromaticity, which are further used as
                      proxies to explain biogeochemical reactivity. An aromaticity
                      index (AI) is calculated mostly with respect to carboxylic
                      groups abundant in NOM. Here, we propose a new constrained
                      AIcon based on the measured distribution of carboxylic
                      groups among individual NOM components obtained by
                      deuteromethylation and UHRMS. Applied to samples from
                      diverse sources (coal, marine, peat, permafrost, blackwater
                      river, and soil), the method revealed that the most probable
                      number of carboxylic groups was two, which enabled to set a
                      reference point n = 2 for carboxyl-accounted AIcon
                      calculation. The examination of the proposed AIcon showed
                      the smallest deviation to the experimentally determined
                      index for all NOM samples under study as well as for
                      individual natural compounds obtained from the Coconut
                      database. In particular, AIcon performed better than AImod
                      for all compound classes in which aromatic moieties are
                      expected: aromatics, condensed aromatics, and unsaturated
                      compounds. Therefore, AIcon referenced with two carboxyl
                      groups is preferred over conventional AI and AImod for
                      biogeochemical studies where the aromaticity of compounds is
                      important to understand the transformations and fate of NOM
                      compounds.},
      ddc          = {333.7},
      typ          = {PUB:(DE-HGF)16},
      doi          = {10.1021/acs.est.1c04575},
      url          = {https://inrepo02.dkfz.de/record/180975},
}