Research

FLEXPART trajectories of air parcels arriving at the research vessel Polarstern (indicated by the yellow circle) during the MOSAIC campaign in 2019. Colors show the height of the air parcels above the surface.

We study everything related to atmospheric transport:
Aaerosol transport, greenhouse gas transport, heat transport, microplastic transport, and moisture transport. Our main tool is the Lagrangian particle dispersion model FLEXPART, which is also actively developed in the group.

We aim to address the following research topics:

Aerosols

  • Interpretations of aerosol data from observational campaigns: which are the main sources and time of transport?
  • How does the shape of particles affect the gravitational settling and their lifetime in the atmosphere? How is the atmospheric transport of non-spherical particles (e.g. volcanic ashes, dust particles, microplastic)?
  • Which are the main sources of microplastic in the atmosphere, and which are their emission rates?

Greenhous Gases

  • What is the contribution of different countries to observed GHG concentrations?
  • What does the global and regional spatio-temporal emission distribution of certain GHG species look like?
  • How can we improve the method of atmospheric inverse modeling?

Energy and Moisture Transport in the Atmosphere

  • What is the impact of atmospheric transport on global and regional climate extreme events?
  • Can we make objective Lagrangian definitions of circulation patterns with the help of a Lagrangian reanalysis?
  • How long does moisture reside in the atmosphere?

Paleoclimate

  • Where are the source regions of moisture/dust archived in ice cores?
  • What influences the climate proxy signal in ice cores and other paleoarchives?

Lagrangian Modeling

  • How can we adapt FLEXPART to be able to run easily with input data from other models, e.g. CMIP6 models (CESM)?
  • How can we develop FLEXPARTiso?
  • Should we develop an online version of FLEXPART for a specific model, e.g. ICON / CESM?

Greenhouse Gases

Analysis of GHG concentration and flux measurements
We work on the analysis of Greenhouse Gas (GHG) concentration and (Eddy Covariance) flux measurements at a Swiss tall tower site. Most flux towers provide observations at heights of several meters to tens of meters and therefore provide information about possible flux sources on a local spatial scale. Here we focus on one of the few European tall towers located close to Beromünster, Switzerland. The tower was initially set up as a CarboCount CH site — a dense GHG observation network run for four years (2012 – 2015) — and is continued since by the University of Bern. The highest measurements are taken at an altitude of 212 m above ground. This relatively high observation height results in a a flux footprint (field of view) of the tower of many kilometers, making its observations predestined to a source analysis on a much larger spatial scale than typical for flux towers. On the one hand, we use a flux footprint parameterization to estimate where the measured fluxes originate. Additionally, we analyse GHG concentration measurements by season, time of day, wind direction, and other criteria and perform various correlation analyses. In future work, the FLEXPART model will be used to further investigate the origin of the measured pollutants. This work is done in a close collaboration with the University of Bern.

Scientists:
Andreas Plach, Andreas Stohl

Inverse Modeling
Inverse modeling provides a powerful tool to verify national greenhouse gas (GHG) emission inventories by using atmospheric observations. We use the Lagrangian particle dispersion model FLEXPART in the backward mode to obtain a relationship between changes in atmospheric mixing ratios and GHG emissions. We then use this relationship to perform Bayesian inversions with the framework FLEXINVERT+, where a priori estimates of the GHG emissions are optimized to better fit atmospheric observations.
On the one hand we use in-situ observations and satellite measurements to determine the emissions of different GHG species such as Sulfur Hexafluoride and Methane. On the other hand, we also investigate methodological aspects of inverse modeling to improve and further develop the method.

Scientists:
Martin Vojta, Rakesh Subramanian, Andreas Plach, Andreas Stohl


Energy and Moisture Transport in the Atmosphere

The FLEXPART model, based on ECMWF data, will be used to analyse total energy, heat and water transport in the atmosphere. By performing domain-filling transport model simulations with the Lagrangian particle dispersion model, as well as forward and backward simulations for particular sites, Lagrangian transport climatologies, as well as global statistics, can be established. Furthermore, case studies of particular extreme events shall be performed, for example heat waves and extreme precipitation events. The main goal is to gain a better understanding of the physical processes in the atmosphere. With this method the heat transport during heat waves, or the global moisture transport in the atmosphere (Stohl and James, 2004) can be analysed. 

Scientists:
Katharina Baier, Andreas Stohl, Lucie Bakels, Marina Duetsch


Paleoclimate

Interpretation of ice core data
Since a few years, the atmospheric transport model FLEXPART is also used to assist with the interpretation of ice core records (collected by our collaborators, e.g., in Greenland, Antarctica, the Alps, and the Andes). For this purpose, climatologies of so-called emission sensitivities are calculated with backward-in-time FLEXPART simulations, employing ECMWF re-analysis datasets as meteorological input (CERA-20C or more recently ERA5). These emission sensitivities result in spatial maps of areas which the individual ice core sites are sensitive to, meaning that if particles were released into the atmosphere within the highly emissions sensitive areas, deposition at the respective ice core site is likely to have occured. FLEXPART accounts for wet as well as dry deposition. In combination with estimates of past emission centers (e.g., due to high human activity), the emission sensitivities can be used to explain observations of particles found in ice cores (e.g., lead or black carbon). For this work we collaborate with ice core scientist all over the world.

Scientists:
Andreas Plach, Andreas Stohl


Aerosols

Microplastic atmospheric transport:

Atmospheric microplastic is a topic of raising concern, and particles of different sizes and shapes have been observed in precipitations and atmospheric samples all over the world, including in very remote regions such as the Arctic and high mountains glaciers. Exploiting the capability of FLEXPART, we try to reconstruct the pathways of transport of these particles and to understand their sources. For this purpose, we developed the model (Tatsii et al 2023) to take into account also the longer atmospheric lifetime of irregular and very elongated or very flat particles, as microplastic can be (e.g. fibers, films, fragments). We also seek to characterize the emissions of microplastic from the main sources and the consequent impact on the atmospheric concentration. We build the emissions starting from schemes as FLEXDUST (Zwaaftink et al., 2016, 2017) or the Grythe et al. 2014 sea spray function to estimate the fluxes of microplastic. With this approach, we estimated the microplastic emissions happening alongside the dust resuspension from arid regions for example, or the flux of microplastic escaping from the surface of the sea due to wave breaking and bubble bursting. The dispersion in the atmosphere is then evaluated using global 3-dimensional simulations of FLEXPART forward trajectories run on ECMWF reanalysis data (ERA5). In addition to the atmospheric concentration, the model allows also to evaluate the redistribution and the deposition fluxes (wet and dry) of the particles back to the surface, allowing for comparison with the current measurements of deposition rates. Overall, we aim to characterize the atmospheric sources and the pathways of transport of microplastic pollution, to better delineate their possible impacts and possible mitigation actions.

Scientists:
Silvia Bucci, Ioanna Evangelou, Daria Tatsii, Andreas Stohl