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@PHDTHESIS{Liu:1034851,
      author       = {Liu, Mingzhao},
      title        = {{C}hemistry modeling and inverse reconstruction of
                      emissions with a {L}agrangian transport model},
      school       = {Bergische Universität Wuppertal},
      type         = {Dissertation},
      address      = {Wuppertal},
      publisher    = {Bergische Universität Wuppertal},
      reportid     = {FZJ-2024-07604},
      pages        = {1 Online-Ressource (113 Seiten)},
      year         = {2024},
      note         = {Dissertation, Bergische Universität Wuppertal, 2024},
      abstract     = {One of the major challenges in Lagrangian chemical
                      transport modeling is the accurate representation of the
                      pollutant sources and sinks. An important part of this work
                      involves the development of both explicit and implicit
                      chemistry schemes within the MPTRAC model. The explicit
                      chemistry scheme handles first-order reactions, making it
                      computationally efficient for large-scale, long-term
                      simulations, while the implicit chemistry scheme handles
                      complex non-linear chemical mechanisms with flexible user
                      definitions. This work includes case studies of two major
                      volcanic eruptions — the 2018 Ambae eruption and the 2019
                      Raikoke eruption to validate the developed models. By
                      analyzing the sensitivity of these processes to various
                      meteorological and chemical factors, the thesis provides
                      insights into the variability of the SO2 lifetime across
                      different altitudes and atmospheric conditions. Both
                      explicit and implicit chemistry schemes are tested and
                      evaluated through comparison with satellite retrievals. The
                      results also show that the volcanic SO2 decay has a strong
                      non-linear effect. To further improve the ability of the
                      model to estimate volcanic SO2 emissions, this thesis
                      develops an inverse modeling approach using a particle
                      filter algorithm, that accounts for the non-linear decay of
                      SO2 and provides a more accurate estimation of emission
                      sources compared to traditional backward trajectory methods.
                      By coupling the inverse modeling technique with the
                      developed chemistry schemes, the work enhances the ability
                      to estimate the time and altitude-resolved source parameters
                      of volcanic eruptions. This thesis also examines the
                      influence of the sink modeling on the reconstructed
                      emissions, demonstrating the importance of the accurate sink
                      modeling for source estimation.},
      cin          = {JSC},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
                      (SDLs) and Research Groups (POF4-511)},
      pid          = {G:(DE-HGF)POF4-5111},
      typ          = {PUB:(DE-HGF)11},
      urn          = {urn:nbn:de:hbz:468-2-5221},
      doi          = {10.25926/BUW/0-799},
      url          = {https://juser.fz-juelich.de/record/1034851},
}