AS3.25

Sulfur dioxide (SO₂) is one of the most abundant gases released by volcanic eruptions. It is of concern due to its potential to influence climate on the global scale. Next to advection and diffusion, various chemical and geophysical processes need to be considered to properly represent volcanic SO₂ plumes in Lagrangian transport simulations. The chemical reaction of SO₂ with the hydroxyl radical (OH) and wet deposition are major processes depleting SO₂ from volcanic plumes. In this study, we implemented and revised new modules for OH chemistry and wet deposition in the Massive Parallel Trajectory Calculations (MPTRAC) Lagrangian transport model. In MPTRAC, the OH chemistry module adopts the newest JPL data evaluation to calculate the temperature- and pressure-dependent reaction coefficient of the termolecular reaction of SO₂ and OH. Similar to other Lagrangian chemistry transport models, monthly mean zonal mean OH fields are applied in the MPTRAC simulations. However, here we propose to introduce a correction factor depending on the solar zenith angle in order to represent the diurnal variations of the OH concentrations. The wet deposition module of MPTRAC mainly uses cloud ice and liquid water content retrieved from ECMWF’s meteorological data as well as an effective Henry constant, considering both, the dissociation and dissolution of SO₂ in cloud water. The revised and improved MPTRAC model is evaluated in the case study on the July 2018 eruption of Ambae, Vanuatu, the most voluminous volcano of the New Hebrides archipelago. It is reported that during the eruption, the island of Ambae suffered from acid rain, which means that the volcanic plume encountered clouds and significant wet deposition of SO₂ due to precipitation. A series of sensitivity tests was conducted to assess the two new chemistry modules of MPTRAC. An inspection of the time series of SO₂ total mass revealed that the diurnal variations due to the OH chemistry are now properly represented in the model. The trajectories of the SO₂ parcels have large influence on the wet deposition because they determine whether they pass through cloudy regions or not at a certain time and location. Therefore, it is important to use the most accurate meteorological data and source information. With the revised MPTRAC model, we found that a significant part of the loss of SO₂ total mass from the Ambae eruption is represented in the simulations. However, satellite observations reveal even shorter tropospheric lifetimes of the volcanic SO₂ plume from the Ambae eruption, which indicates that future work needs to focus on including additional chemical and geophysical processes in the simulations.

How to cite: Liu, M., Griessbach, S., and Hoffmann, L.: Modeling of hydroxyl oxidation and wet deposition in volcanic sulfur dioxide plumes: the July 2018 Ambae eruption, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2629, https://doi.org/10.5194/egusphere-egu22-2629, 2022.

Wind-blown dust, emitted from the surface of the earth to the atmosphere as a result of the disintegration of material due to wind drag, can have a significant impact on the atmospheric concentration of PM levels, not only over arid, deserted areas, where their emission occurs, but due to long-range transport over distant areas too. Considering the increasing potential of longer dry periods between days with precipitation in a warming climate, one can expect however, that such emissions could be occasionally considerable also over non-arid areas, like Europe.

Here we provide a model based estimate of the regional impact of PM emissions from wind erosion (wind-blown dust - WBD) on urban and rural PM levels for a central European domain using a well-established wind-blown dust module (called ‘‘WBDUST’’) for the 2007-2016 period. As driving meteorological data, we used WRF simulations. WBD emissions were implemented into the CAMx chemistry transport model and we performed simulations with and without these emissions. Our results showed that both urban and rural PM levels are significantly increased if wind-blown dust is considered. The effects of the mineral content of WBD on ion chemistry and consequent effects on aerosol components (secondary (in-)organic aerosol) are analyzed too.

How to cite: Liaskoni, M., Bartik, L., and Huszar, P.: The potential role of wind-blown dust emissions in PM pollution over non-arid areas: a modeling study over Central Europe, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1303, https://doi.org/10.5194/egusphere-egu22-1303, 2022.

During the SHIVA (Stratospheric Ozone: Halogen Impacts in a Varying Atmosphere) campaign in Nov. and Dec. 2011, polluted air masses were observed in the marine and terrestrial boundary layer (0 – ~2 km) and in the free troposphere (~2 – 12 km) over Borneo/Malaysia. The measurements include CO, CO₂, CH₄, N₂O, NO₂, and SO₂ as primary pollutants, O₃ and HCHO as secondary pollutants, and meteorological parameters. This set of trace gases combined with a Lagrangian particle dispersion model (e.g., FLEXPART) and emission inventories are used to fingerprint different sources (e.g., biomass burning) of local and regional air pollution.

The long-term trend and seasonal variation of biomass burning emissions in this region are first presented and discussed based on the FINN inventory the FLEXPART simulation. Results highlighted the recurrent influence of palm plantation fires near the Miri airport, allowing regular sampling of this fire at different age plumes. The study of the emission ratio compared to CO₂ or CO can be used as a measure of combustion efficiency to help define the type of biomass burning. Additionally, the age of plume sampled by the aircraft measurement is determined by FLEXPART and compared with the ΔO₃/ΔCO ratio measured in this study and bibliographic database in order to study the ozone production during the transport of biomass burning plumes and implement such database with palm fire data.

How to cite: Krysztofiak, G., Xue, C., Catoire, V., Schlager, H., Eckhardt, S., and Pfeilsticker, K.: Aircraft-Based Measurements of Biomass Burning Emissions of Malaysia Oil Palm Cultivation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4888, https://doi.org/10.5194/egusphere-egu22-4888, 2022.

Flux towers are essential tools for collecting measurements of trace gas concentrations/fluxes to investigate source regions of greenhouse gases (GHGs) and other pollutants. Most flux towers provide observations at heights of several meters to tens of meters and therefore only sample potential source regions in their immediate vicinity, i.e., these towers have small so-called footprints. Here we are interested in estimating the footprint of 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. Measurements are taken at an altitude of 212m above ground. This relatively high observation height results in a larger tower footprint and therefore the tower observations are predestined for a source analysis on a much larger scale than typical for flux towers.

We will present preliminary results of a sensitivity study performed with the Lagrangian atmospheric transport model FLEXPART using different meteorological input data of various spatial resolution, different model internal time step settings, as well as two
different convection schemes used in the convective atmospheric boundary layer — a Gaussian Hanna-type turbulence model and a more realistic skewed turbulence scheme in which a larger area is occupied by downdrafts than by updrafts.

The range of simulated footprints will be used in combination with emission inventories of CO₂ and CH₄ to simulate observations at the tower. By comparing the simulated with the actual observations at the tower we aim to evaluate the quality of the simulated footprints for the respective input data and model setting.

How to cite: Plach, A., Leuenberger, M., and Stohl, A.: FLEXPART model sensitivity study for the footprint of a Swiss tall tower site, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7206, https://doi.org/10.5194/egusphere-egu22-7206, 2022.

Atmospheric inverse modelling is a ’top-down’ emission estimation method, which utilises numerical models to estimate emissions from observed and simulated concentrations of atmospheric compounds. Inverse emission modelling can be applied for the support of emission inventories and emission reporting, which are usually based on ’bottom-up’ methods. The latter employ activity data and emission factors for the relevant processes. Depending on the emitting process, both may be afflicted by large uncertainties, especially when spatially-resolved emissions are considered on sub-national scales. Inverse modelling offers an alternative tool to emission estimation, validation and optimization of emission inventories. It is widely used by the scientific community for different atmospheric compounds and from global to the facility scale.

Atmospheric inversions can be carried out by combining source sensitivities simulated by atmospheric transport models, observations, and an inversion framework. Here, we focus on emissions of synthetic greenhouse gases (GHG) in the Swiss domain. 'Bottom-up' estimates of these emissions are connected to large uncertainties in the leakage rates of these compounds from various applications (e.g., refrigeration, foam blowing). Globally, synthetic GHGs account for a considerable fraction of the total anthropogenic radiative forcing (~10%), and their future environmental impact depends on the replacement of compounds with long lifetimes by compounds with short lifetimes and minimal global warming potential (GWP). In Switzerland, synthetic GHGs contribute about 3.5% to national total GHG emissions according to bottom-up reporting.

Newly available synthetic gases observations, collected as part of the Swiss project IHALOME (Innovation in Halocarbon Measurements and Emission Validation), from the Swiss Plateau at the Beromünster and Sottens tall towers, allow us to localise and quantify the emissions in Switzerland and in the neighboring countries. We apply the Lagrangian Particle Dispersion Model (LPDM) FLEXPART, driven by meteorological fields of the Numerical Weather Prediction (NWP) model COSMO, at two different spatial resolutions (7 km x 7 km and 1 km x 1 km). During the last decade, FLEXPART-COSMO was successfully operated at 7 km x 7 km spatial resolution to estimate Swiss emissions of methane and nitrous oxide. Reliable simulations at 1 km x 1 km resolution were recently established and required an update of FLEXPART-COSMO's turbulence scheme.

Inversion results for the most important (by emissions) synthetic GHGs (HFCs and SF₆) are presented. Special attention is given to comparisons between inversions for different transport model resolutions and the question if the high resolution simulations are able to enhance the capability of the inversion method to localise emissions. Additionally, the sensitivity of the inversions to different a priori emission fields is presented. Finally, the sensitivity of the inversion towards covariance parameters, either obtained from maximum likelihood optimisation or from expert judgment, is examined. Inversions with the high resolution model amplify the emission differences between the Swiss Plateau and the high altitude regions in the Alps by both increasing the emissions in the big cities and decreasing the emissions in the high altitude regions. At the same time, no significant difference in total national emissions is observed between high and low resolution model inversions.

How to cite: Katharopoulos, I., Rust, D., Vollmer, M., Brunner, D., Reimann, S., Emmenegger, L., and Henne, S.: Impact of transport model resolution on the estimate of Swiss synthetic greenhouse gases emissions by inverse modelling, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1453, https://doi.org/10.5194/egusphere-egu22-1453, 2022.

Inverse modeling provides a powerful statistical tool to verify national greenhouse gas (GHG) emission inventories by making use of in-situ atmospheric observations. Regional inversions are often based on atmospheric transport simulations with Lagrangian Particle Dispersion Models (LPDMs), where a large number of virtual particles are released from observation sites and traced backward for a limited amount of time to establish a relationship between atmospheric concentrations and emission sources within the simulated period. In order to account for all emissions prior to this simulation period, which also contribute to the corresponding observations, a baseline needs to be defined. This baseline definition is a crucial task, bearing a lot of uncertainties. Most studies investigating halocarbons use statistical methods to calculate the baseline by selecting low concentration observations at individual stations. In this study we show that statistical baseline methods have large systematic problems, that accumulate with increasing backward simulation periods and lead to a non-negligible underestimation of emissions that systematically increases with the length of the backward simulation time. As an alternative, we present a global distribution based (GDB) approach, where baseline concentrations are determined directly from global concentration fields at the termination points of the backward trajectories. These global fields are simulated with the FLEXible PARTicle dispersion chemical transport model (FLEXPART CTM) using a nudging routine to push modeled concentrations towards observed concentrations. We illustrate that this method is fully consistent with the length of the backward simulation, has the ability to account for meteorological variability, and leads to inversion results, that agree well with global emissions calculated with a simple box model.

How to cite: Vojta, M., Thompson, R., Plach, A., and Stohl, A.: The importance of baseline methods for the consistent estimation of regional and global emissions from inverse modeling, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2830, https://doi.org/10.5194/egusphere-egu22-2830, 2022.

Investigation of the transport and distribution of atmospheric concentrations of microplastic (MP) particles is an important challenge, since MP may have a negative impact on human health and ecosystems. When considering particle shape, most of the atmospheric transport models assume only spherical particles, whereas MP particles cover a wide range of observed shapes. Non-spherical particles experience a larger drag in the atmosphere, which leads to a reduction of their settling velocity, hence longer atmospheric residence times. Here we study gravitational settling of one of the dominant microplastic shapes – fibers. To reduce the difference between model output and ground-based measurements, we have implemented a parameterization of the shape correction in the gravitational settling scheme of the Lagrangian transport model FLEXPART.

We have determined model sensitivity to the shape correction to explore its impact on particles transport for a range of scenarios.  This was done with a statistical comparison of 3D fields of mass concentration and deposition patterns of shape-corrected and non-corrected parameterization schemes. Using the model output, we quantified average horizontal transport distances and atmospheric residence times for spheres and fibers of different sizes and aspect ratios in different climatic regions and for different release heights of the MP particles.

How to cite: Tatsii, D., Bucci, S., Bagheri, G., Stohl, A., and Bakels, L.: Atmospheric transport of microplastic particles as a function of their size and shape, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13404, https://doi.org/10.5194/egusphere-egu22-13404, 2022.

Airborne microplastic is a new area of research in the microplastic domain. Recently, microplastic presence was reported in areas remote from any urban, industrial, and agricultural sources. This reveals the role of the atmosphere in the transport and dispersion of microplastics. Dust storms can shift significant quantities of soil particles and associated microplastics, especially in arid and semi-arid regions. This study reports the presence, characteristics, and potential sources of microplastics in a severe dust storm in Shiraz, southern Iran, in May 2018. Using the method adopted by Bergmann et al. (2019), 22 dust samples were collected from parked cars directly after the event. Dust samples were analyzed for microplastic using the density extraction method and Raman Spectroscopy. The hybrid Lagrangian and Eulerian model of HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) was used for back trajectory analysis in order to determine the origin of air masses.

Results showed that MP concentrations ranged from 0.04 to 1.06 particles per g of dust. In total, 485 microplastics were detected in all dust samples. The main shape of microplastics was fibrous and polymer makeup was dominated by nylon, polypropylene, and polyethylene terephthalate. Scanning Electron Microscope (SEM) images revealed different degrees of weathering in microplastics. Results of modeling together with the geochemical evidence suggested that the Arabian Peninsula constitutes the principal distal and transboundary source. Results also estimated that about 2 * 10¹² microplastics could be transported by such a dust event. According to the literature on MP concentrations in urban dust and remote arid soils, it was estimated that between 0.1 and 5% of MPs in the dust samples were originated from local sources, and the remainder arose from more distant sources. The outcome of this study is proving the atmospheric transport of microplastic far beyond its sources and a potential pathway for microplastics to the oceans and land through dust storm events.

How to cite: Rezaei, M., Abbasi, S., Ahmadi, F., and Turner, A.: Dust storms as a means of transport for microplastics in the atmosphere, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5155, https://doi.org/10.5194/egusphere-egu22-5155, 2022.

Microplastic particles in the atmosphere, even in very remote locations (Allen 2021; Allen 2019, Materić 2020, 2021), have attracted considerable interest in recent years. The origin, chemical transformation, transport and abundance of airborne microplastics still remains largely unexplained. Detection techniques are scarce and often include visual classification with the naked eye or with an optical microscope (Lulu 2021).

In this study, fluorescence spectroscopy is used to characterize microplastic particles in the laboratory. Pure samples of polyethylene terephthalate (PET), polyethylene (PE) and polypropylene (PP), as well as everyday products (PET-drinking bottle, packaging) were shredded with a swing mill into particles < 100 μm. The samples were analyzed with a fluorescence spectrometer, revealing clear excitation-emission maxima, with slight differences among the samples. To test if fluorescence is a promising property for the online detection of airborne microplastics, we use a Bioaerosol Sensor, which enables single particle fluorescence measurements at two excitation wavelengths and in two emission windows. For this aim, the microplastic particles are dispersed in air and are characterized by the bioaerosol sensor.

Literature:

Allen, S., et al. "Evidence of free tropospheric and long-range transport of microplastic at Pic du Midi Observatory." Nature communications 12.1 (2021): 1-10.

Allen, Steve, et al. "Atmospheric transport and deposition of microplastics in a remote mountain catchment." Nature Geoscience 12.5 (2019): 339-344.

Materić, Dušan, et al. "Nanoplastics transport to the remote, high-altitude Alps." Environmental Pollution 288 (2021): 117697.

Materić, Dušan, et al. "Micro-and nanoplastics in Alpine Snow: a new method for chemical identification and (semi) quantification in the nanogram range." Environmental science & technology 54.4 (2020): 2353-2359.

Lv, Lulu, et al. "Challenge for the detection of microplastics in the environment." Water Environment Research 93.1 (2021): 5-15.

How to cite: Gratzl, J., Seifried, T. M., Koyun, A., and Grothe, H.: Characterization of microplastics using fluorescence spectroscopy and online single particle fluorescence measurements, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9512, https://doi.org/10.5194/egusphere-egu22-9512, 2022.