Eddy covariance is the state-of-the-art technique for measuring fluxes of energy and gases between the land surface and the atmosphere. However, many processing steps sit between the data that are actually measured (typically a 10-Hz time series of wind speed components and gas mixing ratios) and the calculated flux. In practice, the data processing constitutes a modelling exercise, requiring a model of the measurement system and of the surface layer of the atmosphere. In conventional data processing, we treat the parameters of this model as known constants, and allow only for a random uncertainty term which diminishes as the duration of the observations increases.  This inevitably fails to comprehensively propagate the true uncertainties.

In a Bayesian approach, we treat the parameters of the model (of the measurement system and atmosphere) as uncertain parameters, which we characterise with probability distributions. We use our knowledge of the physics of the system and previous data to specify prior probability distributions for these parameters. We then update these with the data we actually observe (the high-frequency time series) to yield the posterior distributions for these parameters. By a simple extension, we can include a model of the biological processes governing uptake and emissions of gases (e.g. in the case of carbon dioxide, photosynthesis and respiration). In this way, we can produce estimates of the fluxes of interest, such as the long-term net carbon balance of an ecosystem, in the form of posterior probability distributions, in which the uncertainty is correctly represented following the axioms of conditional probability. We thereby correctly propagate all of the systematic uncertainties, giving a much more accurate representation of the true uncertainty.
  
For example, in most eddy covariance set-ups, the time lag between the sonic anemometer and the gas analyser is  estimated from the cross-covariance function, where it shows the maximum covariance. However, whenever there is noise in the data, this time lag can be misidentified, and results in systematic over-estimates in the calculated flux. The Bayesian approach represents this more correctly, as a system with two cross-correlated random variables where the time lag between them is itself a temporally-autocorrelated random variable with uncertainty. By estimating the distribution of plausible ("posterior") time lags to form a distribution of calculated fluxes, we incorporate this uncertainty in the results. We can apply similar principles to detrending the data, coordinate rotation, frequency-response corrections, and separating advection from the eddy flux.

How to cite: Levy, P. E.: A Bayesian approach to quantifying uncertainties in surface fluxes from the eddy covariance method, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-82, https://doi.org/10.5194/ems2024-82, 2024.

Methods to measure gaseous emissions from spatially confined sources (e.g. from plots with slurry application or grazing excreta) often rely on atmospheric dispersion models to relate downwind concentration or flux measurements to the respective emission rate. Since ammonia (NH₃) is very reactive and water soluble, it adsorbs readily to surfaces leading to a significant loss due to re-deposition, which affects concentration and surface-atmosphere exchange measurements even at short distances from the source.

In the present study, a backward Lagrangian stochastic (bLS) model was used, which has been enhanced to incorporate dry re-deposition. Controlled release experiments were carried out at a grassland site with a parallel release of ammonia (NH₃) and methane (CH₄) at a defined release rate through a source grid with 36 critical orifices at ground level. NH₃ and CH₄ concentrations and vertical fluxes (by eddy covariance) were measured downwind of the source and the bLS model was used to infer the emission fluxes from the measured quantities, with and without considering dry re-deposition. When disregarding deposition, the median recovery fractions (ratios between the observed emission and the known release rate) were close to 100% for CH₄ but considerably lower (between 32% and 72%) for NH₃. The difference in the recovered fraction of NH₃ compared to CH₄ could be attributed to dry deposition loss between the source and the concentration measurements. In a second step,  surface deposition velocities were derived to match recovered fractions of NH₃ and CH₄. This resulted in median NH₃ deposition velocities (related to 2 m height) between 0.6 and 1.7 cm s^-1. Compared to literature values this is in the expected range of deposition velocities for grassland sites.

How to cite: Ammann, C. and Häni, C.: Emission and short range re-deposition of ammonia on grassland determined by an inverse dispersion method, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-612, https://doi.org/10.5194/ems2024-612, 2024.

Measurements of gaseous SO₂, HNO₃ and NH₃ deposition fluxes at two remote wet fen field sites in the Alberta Oil Sand Region (Canada) have been performed by a COnditional Time Averaged Gradient system during the summer seasons over 2010-2012. The COTAG system works by measuring the concentration gradient only when the conditions for making flux measurements (sufficient fetch and turbulence) are suitable. In this way, average concentration gradients can be measured over periods of days to weeks. When combined with the average turbulence conditions during the sampling, such average gradients can be used to measure the average gas fluxes. With 6 replicate samplers set at two heights, the gradient system provided significant differences in gas concentrations at the two heights for at least half of the summer season, and showed that for periods where fluxes were measurable, the surface resistance to gas transfer was not significantly different from zero. However, during periods where there was no significant difference in gas concentrations at the two heights, the lack of a significant concentration gradient could result from a significant surface resistance, or could simply be the result of large uncertainties in the measurements at concentrations close to the limit of detection of the method. The COTAG measurements do, however, provide an indication of the range of dry deposition rates for these gases at wet fen sites, for which no other experimental data exist for use in inferential modelling of dry deposition across the region. The data here refer only to the summer season, so the dry deposition rates are only representative of surfaces clear of snow, as at low temperatures during winter, the snow pack coverage will cause deposition rates to be different.

How to cite: Famulari, D., Fowler, D., Tang, S. Y., and Cape, J. N.: Application of the Conditional Time-Averaged Gradient method to evaluate dry deposition in the Oil Sands region of Alberta, Canada, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1073, https://doi.org/10.5194/ems2024-1073, 2024.

Studies have shown that gas-phase nitrous acid (HONO) is a major precursor of hydroxyl (OH) radicals in the boundary layer, which plays an important role in the formation of pollutants such as ozone and secondary aerosol. Despite the many studies undertaken and the development of new techniques to measure HONO, the processes governing formation are not completely understood. As such, current atmospheric models are unable to reproduce daytime HONO concentrations observed by in-situ measurements, suggesting the existence of unknown sources of HONO. Soil has been suggested as a major source of atmospheric HONO under specific conditions. In this study, HONO flux measurements were made on a Scottish grassland using the aerodynamic gradient technique and two Long Path Absorption Spectrometers (LOPAPs) to determine the processes governing the surface-atmosphere exchange of HONO. Fluxes showed a bi-directional behaviour with values between -1.4 ± 0.2 ng N m^-2 s^-1 and 3.2 ± 0.4 ng N m^-2 s^-1. Deposition of HONO were observed at night while HONO emissions were observed during the day. In particular, the average flux diurnal pattern showed a distinctive peak around 9 am, suggesting a recurrent release or formation process in the morning.

Three potential processes were investigated to explain the observed emissions i) soil microbial activity, ii) photolysis of NO₃^- and HNO₃, iii) absorption/desorption of HONO from water films on vegetation. A simple model was developed to replicate the photolysis of NO₃^- and HNO₃, alongside the absorption/desorption of HONO from water films on vegetation. Whereas lab experiments were undertaken to determine whether microbial activity in soil was a possible source. It was discovered that it was unlikely that microbial activity played a major role in the observed emissions. Instead, a combination of photolysis of HNO₃/NO­₃^- and absorption/desorption of water films at the surface were more likely the processes contributing to the observed emissions. The inclusion of both processes into atmospheric chemistry models may help to improve the agreement between measurements and models in the future.

How to cite: Di Marco, C. F., Twigg, M. M., Kramer, L. J., Crilley, L. R., Drewer, J., Ramsay, R., Cowan, N. J., Jones, M. R., Leeson, S. R., Bloss, W. J., and Nemitz, E.: Processes governing emissions of HONO at a grassland site, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1075, https://doi.org/10.5194/ems2024-1075, 2024.

The global budget of aerosols in the atmosphere depends heavily on their deposition. For global scale transport models this presents great challenges, as especially the wet deposition of aerosols is a nonlinear sub-gridcell process. With a uniform precipitation rate in space and time, the aerosol concentration decreases exponentially. However, the precipitation is generally not spread evenly across a model gridcell, and in case the model relies on offline meteorological data, it is not spread evenly over the time step either. These inhomogeneities will easily lead to overscavenging, and effective parametrized methods are thus required to reduce it. We have developed simple limits for the scavenging rate based on the convective available potential energy and on the horizontal wind speed, assuming that these quantities limit the mixing rate of aerosols between the precipitating and non-precipitating parts of the gridcell. We have implemented the method within the global transport and chemistry model SILAM (silam.fmi.fi), and present an evaluation of the method against measurements of aerosol optical depth (AOD), surface particulate matter concentrations and depositions of various aerosol species. Specifically, we focus on the long-range transport of Saharan dust. AOD measurements over Sahara are overwhelmingly sensitive to dust emission, largely independent of scavenging or other aerosol species, which means that the modeled emission may be adjusted independently of the modeled deposition. On the other hand, the long-range transport of dust plumes across the Atlantic and the Mediterranean depends heavily on the scavenging model, with incorrect scavenging leading to greatly reduced skill scores against AOD and in situ measurements. Application of the method has led to model skill scores that are competitive with online models that assimilate satellite-retrieved AOD. However, finding out how the effective scavenging rate scales properly with the grid cell dimensions and the length of the model time step remains a challenge.

How to cite: Uppstu, A., Kouznetsov, R., and Sofiev, M.: Effective aerosol scavenging scheme for dispersion modelling, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1140, https://doi.org/10.5194/ems2024-1140, 2024.

Atmospheric aerosol is a global concern for its detrimental effects on human health and climate. Vegetation has been identified as a possible sink for atmospheric particles. However, the interactions between vegetation and aerosols are not completely understood, and they are not limited to deposition only since also bidirectional aerosol exchanges can appear. Moreover, the knowledge of aerosol-vegetation interactions is quite limited for deciduous forests, as well as its seasonality which follows the appearance and disappearance of leaves on the crowns. Much of research, in fact, has been focused on conifers which have almost constant leaf area during the year.

For this sake, eddy covariance measurements of size-resolved aerosol fluxes were conducted in a broadleaf deciduous forest in the Po Valley, by means of a fast electric low-pressure impactor able to resolve 14 dimensional classes with cut-off diameters ranging from 6 nm to 10 µm. The measurements spanned approximately eight months and covered both a leaf-off period and a leaf on period, from leaf sprout to leaf senescence.

Overall, aerosol fluxes exhibited a distinct seasonality and variations in exchange direction depending on particle diameter. During the winter, when leaves were absent, most aerosol classes exhibited positive upward fluxes. In contrast, during the leaf-on season, ultrafine (dp<100 nm) and fine aerosols (100 nm<dp<1 µm) displayed contrasting exchange patterns, with fine aerosol being predominantly deposited and ultrafine aerosol primarily emitted.

The vertical exchange of aerosols was found to be dependent on leaf area index, friction velocity and surface wetness. Vertical fluxes increased as LAI increased, both for fine aerosols -which were deposited- and for the ultrafine ones, which were emitted.

In dry conditions and in presence of leaves, at moderate friction velocities (u*<0.75 m/s) aerosol deposition increased as u* increased. However, above a u* value of 0.75 m/s upward fluxes appeared, and they increased as friction velocity increased becoming rapidly dominant. In wet conditions, leaf wetness did not enhance aerosol deposition and the latter started only when friction velocity increased above a certain threshold (0.4 m/s). No upward aerosol fluxes were observed in wet conditions.

An attempt to explain the observed deposition and resuspension processes will be provided.

How to cite: Bignotti, L., Gerosa, G. A., Finco, A., and Marzuoli, R.: Size resolved aerosol fluxes above a deciduous forest: seasonal variability and underlying processes, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-974, https://doi.org/10.5194/ems2024-974, 2024.