Dissertation / PhD Thesis FZJ-2024-07604

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Chemistry modeling and inverse reconstruction of emissions with a Lagrangian transport model



2024
Bergische Universität Wuppertal Wuppertal

Wuppertal : Bergische Universität Wuppertal 1 Online-Ressource (113 Seiten) () [10.25926/BUW/0-799] = Dissertation, Bergische Universität Wuppertal, 2024

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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.


Note: Dissertation, Bergische Universität Wuppertal, 2024

Contributing Institute(s):
  1. Jülich Supercomputing Center (JSC)
Research Program(s):
  1. 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511) (POF4-511)

Appears in the scientific report 2024
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 Record created 2024-12-20, last modified 2025-02-03


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