Modelers aim to identify appropriate values of deposition velocity and/or emission factors for different chemical species, as well as to establish relationships to link these factors to surface characteristics and environmental parameters. Complex relationships can be envisaged when the exchanging surfaces are vegetated and when plant physiology and phenology should be considered.
Experimentalists are committed to characterize dry deposition and emissions from different land covers and environmental conditions, and to distinguish between stomatal and non-stomatal processes. Additionally, they need to assess the turbulent mixing between below and above canopy air masses in order to ensure that their measurements above canopy, commonly conducted via the eddy covariance method, are truly representative of the matter and energy actually exchanged by the ecosystems. Finally, they are trying to extend their measurements in time as long as possible in order to capture signals of responses to climate change. The current scarcity of datasets of direct measurements of atmospheric deposition is a major limitation on the development of deposition models, from local to regional and trans-boundary scales.
This session focusses on biosphere-atmosphere exchange dynamics of GHG, atmospheric pollutants (both gaseous and PM) and water, and welcomes contributions on dry and wet deposition; studies on emissions from different anthropogenic sources or landscapes; surface-atmosphere bi-directional exchange processes, including soil-vegetation-atmosphere transfer, from both an experimental and a modelling perspective.
We solicit contributions describing innovative studies, approaches, data processing techniques and modelling tools, to improve the understanding of land-atmosphere interaction with meteorology and climate and supporting operational applications.
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.
It is known that the ocean absorbs approximately on third of anthropogenic CO2 in the atmosphere through air-sea gas exchanges. The ocean’s uptake of anthropogenic CO2 plays a crucial role in mitigating the net source of CO2 in the atmosphere. The ocean biogeochemical processes are one of the most important fields for understanding Earth’s carbon cycle to understand the global climate system. The ocean’s capacity to absorb anthropogenic CO2 in the atmosphere is controlled by two processes: the biological carbon pump and solubility carbon pump. The biological carbon pump involves CO2 uptake through photosynthesis, and the solubility carbon pump is influenced by water temperature. Therefore, the spatial and temporal variability of carbon sink/source in the ocean is influenced significantly by the solubility and biological carbon pumps. Especially, phytoplankton growth can induce a strong biological pump, which can have a significant impact on regional carbon cycle. The North Pacific is known as a key region where the biological carbon pump occurs effectively. In this region, seasonal variability in chlorophyll concentration peaks occurs in spring and autumn. The peaks are influenced by factors such as water temperature, vertical mixing, and atmospheric deposition. Iron supply, among various factors, can lead to spatial and temporal variations in chlorophyll concentration, thereby potentially impacting the biological carbon pump. In this study, a coupled ocean physical-biogeochemistry model was employed to investigate the climatological variability in biogeochemical environment and CO2 flux (carbon cycle) resulting from atmospheric iron supply. The increase in chlorophyll concentration due to iron into the ocean can potentially trigger CO2 absorption through photosynthesis.
How to cite: Kim, D., Jung, H.-C., and Moon, J.-H.: Climatological variability of air-sea CO2 fluxes induced by iron flux in the North Pacific, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-703, https://doi.org/10.5194/ems2024-703, 2024.
Volatile organic compounds (VOCs) and nitrogen oxides are significant contributors to ground-level ozone and PM2.5 pollution via secondary organic aerosols (SOA), with detrimental effects on human health and the environment. While previous research has predominantly focused on quantifying VOC emissions from plant canopies and their drivers, less attention has been given to measuring the dry deposition of primary and secondary VOCs onto surfaces. As a result, dry deposition processes are associated with large uncertainties in atmospheric models. To address this gap, we conducted a measurement-based investigation into VOC dry deposition under the ‘Dry Deposition Processes of VOCs’ project funded by the Natural Environment Research Council. Our primary aim was to refine atmospheric chemistry models by improving parameterisations for the VOC dry deposition. Here, we present the findings of our laboratory study on plant exposure to methacrolein (MACR), among other selected VOCs.
An automated dynamic gas-exchange chamber system was developed to fumigate test plants with a range of VOCs concentrations. Five plant species were subjected to each experiment spanning four days: one day to observe background emissions and three days of VOC exposure at 20, 15 and 10 °C. Three levels of relative humidity (RH) were maintained over light and dark conditions, being fumigated with four concentrations of VOCs within each RH level. In total, eleven VOCs were chosen for exposure: water-insoluble (isoprene, benzene, toluene, xylene, a-pinene) and water-soluble (methanol, acetonitrile, acetaldehyde, acetone, acetic acid and MACR). VOCs were monitored using a proton transfer reaction instrument equipped with time-of-flight mass spectrometer (PTR-Qi-TOF). Fluxes were computed based on the concentration difference between reference and measurement chambers, subsequently normalized by the corresponding plant leaf area indices.
MACR, together with methyl-vinyl ketone, is the main product of isoprene oxidation (under NOx conditions) and ozonolysis, playing an important role in air pollution through SOA formation. The observed MACR deposition rate was larger at higher fumigating concentrations. We revealed that MACR deposition velocity (Vd) increased with increasing RH under light conditions; no similar pattern was observed for dark periods with much lower Vd magnitudes. This humidity-dependent Vd variation indicates a strong stomatal control (see Morumoto et al., 2015) and a possible contribution of on-leaf heterogenic chemistry under daylight conditions. At all times, MACR compensation points were found to be negligible, suggesting minor or no impact on deposition rates.
These findings will benefit atmospheric chemistry models, providing an improved parameterization for MACR dry deposition to typical coniferous, deciduous, and evergreen temperate climate plant species.
How to cite: Medinets, S., Langford, B., Di Marco, C., Vieno, M., and Nemitz, E.: Improved parameterization for dry deposition of methacrolein, an oxidation product of isoprene, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1077, https://doi.org/10.5194/ems2024-1077, 2024.
Methane (CH4) is the second most important greenhouse gas after carbon dioxide (CO2). It helps to increase the mixing ratio of these gases and accounts for 18% of the atmospheric greenhouse effect. Based on all measurements (both ground and satellite) the concentration of greenhouse gases such as CO2 and CH4 are increasing in the world. For an accurate evaluation of the significance of their dispersion, quantitative monitoring of greenhouse gas emissions in areas with urban and human sources is essential.
The WRF-GHG model is used in this work to better understand the contributions of different methane sources in Iran. In the simulation we have considered the Middle East as the first domain with a resolution of 30 km and Iran as the second domain with a resolution of 10 km.
The main sources of methane are taken into consideration: burning biomass, anthropogenic emissions, and emissions from wetlands. The warm (Aug) and cold (Feb) seasons in 2010 are contrasted in order to examine the impacts of the seasonal variations of natural sources and meteorological conditions.
Surface observations from synoptic stations are used to evaluate the simulated meteorological fields, showing that the model can accurately represent variations in wind, relative humidity, and surface temperature over time.
Compared to GOSAT data, the average bias error for methane concentration simulations in the warm and cold seasons, according to the results, is -24.99 and 7.50 ppb, respectively., the predicted methane concentration is often underestimated in August and overestimated in February. The WRF-GHG model performs statistically better in the cold season than in the summer season.
The monthly average of methane fluxes in Iran, shows the maximum methane occurs throughout the late night to early in the morning hours in February and August. Iran contributes significantly to the Middle East's methane emissions production. According to an analysis of the spatial distribution of emission sources for the months of February and August, the presence of oil refineries and rice-growing wetlands in the north and west of Iran contributes significantly to the concentration of gasses in the center of Iran.
How to cite: Karbasi, S., Abdi, A. H., and Malakooti, H.: Quantitative assessment of Methane concentration using WRF-GHG model over Middle East and Iran , EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-792, https://doi.org/10.5194/ems2024-792, 2024.
Tropospheric ozone (O3) is a secondary atmospheric pollutant that poses a significant threat to vegetation, leading to oxidative stress, growth reduction, and yield losses. Research activities have demonstrated that O3 damage is related more to the ozone flux absorbed by leaves, rather than simple O3 exposure, and dose-response relationships accounting for O3 stomatal flux effects on biomass growth have been defined for several crop species within the ICP-Vegetation program.
This study aimed at calculating and mapping the O3 deposition to winter wheat (Triticum aestivum L.) in the Lombardy region (Italy) by applying a dual-sink big-leaf model to estimate the stomatal uptake by crop, i.e. the POD6 which is the seasonal Phytotoxic Ozone Dose above a threshold of 6 nmol m-2 s-1.
The model run on spatialized measured data of air temperature, relative humidity, precipitation, wind speed, global radiation and O3 concentration provided by regional monitoring networks for year 2017, and included calculations of the evolution of crop’s geometry and phenology, light penetration within the canopy, stomatal conductance, atmospheric turbulence, and soil water availability to the plants.
This workflow was also used to assess the effect of different spatio-temporal resolutions on POD6 patterns, testing a wide array of configurations, from 1×1 km2 to 50×50 km2, and from 1h to 6h.
Results revealed that in 2017 POD6 was on average 2.03 ± 0.81 mmol m-2 PLA (Projected Leaf Area), leading to an estimation of 7.5 ± 3.1% relative grain loss. The analysis on the involved environmental factors identified air temperature as the most limiting factor to O3 stomatal conductance, while soil water emerged as the key factor influencing the POD6 spatial patterns.
Assessment of different spatio-temporal resolutions suggested that finer resolutions are the only ones being able to detect local features (thus being able to, e.g., guide spatially based mitigation measures), and that coarser resolutions might lead to lower POD6 values, even though they are much affordable from a computational point of view and represents a good compromise if only a general risk assessments is requested.
How to cite: Guaita, P. R., Marzuoli, R., and Gerosa, G. A.: Mapping ozone deposition to winter wheat in Northern Italy: integrated use of measured data to assess stomatal uptake at different spatio-temporal resolutions, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-1128, https://doi.org/10.5194/ems2024-1128, 2024.
