The inclusion of grass-clover (GC) leys in crop rotations on dairy farms may contribute to climate change mitigation by facilitating carbon sequestration in soils. A long-term experiment in Denmark found that soil organic carbon (SOC) and soil total nitrogen (STN) increased with the proportion of GC (i.e., 2 and 4 years of GC in a six-year rotation) from 2006 to 2020. However, the incorporation of GC residues may potentially increase nitrous oxide (N₂O) emissions due to the increased SOC and STN stocks. Yet, limited information exists regarding N₂O emissions with different proportions of GC. We hypothesized that N₂O emission will increase with more GC years in the rotation. This study aimed to quantify the emissions of N₂O in two long-term crop rotations with different proportions of GC years (1/3 or 2/3), and all crops present each year. A one-year experiment is currently conducted including the rotation year preceding, and the year following GC cultivation where spring barley is cultivated, in both crop rotations (n=2, total: 8 plots). Emissions of N₂O were quantified starting from April 2023 (day of year, DOY 111). Surface N₂O fluxes were measured with the LI-7820 N₂O/H₂O trace gas analyzer connected to the 8200-01S Smart Chamber (LI-COR Biosciences, Lincoln, NE, USA). Linear mixed models were used to analyze N₂O with crop rotation (1/3 or 2/3 GC) and rotation year (pre- or post-GC) as fixed effects and sampling date and block as random effects. Preliminary results showed elevated N₂O fluxes (up to 443 ug N₂O-N m^-2 h^-1) with a longer high-flux period in post-GC rotation years (DOY 111-151), than pre-GC years (DOY 111-139). The highest cumulative emission was 420 mg N₂O-N m^-2 in the post-GC year of DOY 320 in 1/3 GC. For pre-GC in 1/3 GC, pre-GC and post-GC in 2/3 GC, emissions were 249, 341 and 252 mg N₂O-N m^-2, respectively. For both N₂O fluxes and cumulative emissions, the 1/3 GC rotation was significantly higher (p<0.01) than the 2/3 rotation. In addition, the N₂O fluxes and cumulative emissions in the post-GC year were significantly (p<0.01) higher than the pre-GC year in the 1/3 GC crop rotation, while the years pre- and post-GC showed no difference in rotation with 2/3 GC. In contrast to our initial hypothesis, the preliminary results did not show higher N₂O emissions with increased GC years. This currently suggests that the 2/3 GC inclusion in crop rotations has a greater potential for climate mitigation as compared to 1/3 GC. Further investigations will focus on the drivers of N₂O emissions and the climate mitigation potential, considering both C sequestration in soil and N₂O emissions in the long term.

How to cite: Kong, M., Petersen, S. O., Eriksen, J., and Dold, C.: Assessing Nitrous Oxide Emissions from Agricultural Soil: A Comparison of Two Grass-clover Proportions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1586, https://doi.org/10.5194/egusphere-egu24-1586, 2024.

Agriculture contributes to climate changes through land use changes and greenhouse gas emissions. Models can provide crucial insights into the extent of this contribution; however, their effectiveness relies on proper evaluation within the application context. Moreover, crop models that can simulate greenhouse gas emissions have not been extensively tested for the semi-arid tropics. We calibrated and used the STICS soil-crop model to explore the skills of the model to reproduce observed variations in greenhouse gas emissions for a millet-groundnut rotation in an agro-silvo-pastoral parkland dominated by Faidherbia albida trees located in central Senegal. Model simulations were compared with observations of soil temperature, soil water content, N₂O and CO₂ emissions, aboveground and belowground biomass of millet and groundnut, collected between 2018 and 2022. CO₂ emissions were simulated with a two-step approach. Initially, STICS simulated crop leaf area index and biomass (aboveground and belowground), and soil heterotrophic respiration. These variables were then integrated into an independent autotrophic respiration module, and summed with STICS simulated' heterotrophic respiration. In general, the STICS model tends to underestimate the observed minimum soil water content (wilting point) during the dry season and overestimate the observed soil water content after the wet season. However, the temporal dynamics of the soil temperature in the upper layer (0-30 cm) are generally well-represented by the model throughout the simulation period. Simulated N₂O emissions were generally consistent in terms of magnitude compared to on-site measurements, although the model currently does not account for N₂O absorption by the soil (i.e. negative fluxes). For instance, the simulated peak reached 0.041 kg N ha^-1 d^-1, while the observed peak was 0.048 kg N ha^-1 d^-1. The simulated average annual N₂O emissions for the period 2018 to 2022 amounted to 0.368 kg N ha^-1 yr^-1. Simulated CO₂ emissions were also comparable to on-site measurements (2021: EF = 0.63, BIAS = -0.75 kg C ha^-1 d^-1, and RMSE = 15.01 kg C ha^-1 d^-1; 2022: EF = 0.56, BIAS = -3.25 kg C ha^-1 d^-1, and RMSE = 5.01 kg C ha^-1 d^-1). These results indicate that the STICS model can be used to explore the impact of land use and crop management changes on greenhouse gas emissions in a tropical semi-arid context.

How to cite: Agbohessou, Y., Ba, S., Ferchaud, F., Léonard, J., Sow, S., Bouvery, F., Duthoit, M., Delon, C., Vezy, R., Falconnier, G. N., Mougin, E., Ngom, D., Taugourdeau, S., and Roupsard, O.: Modelling CO2 and N2O emissions from a tropical semi-arid parkland cultivated with groundnut and millet, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7588, https://doi.org/10.5194/egusphere-egu24-7588, 2024.

With the advent of synthetic nitrogen fertiliser, the proportion of reactive nitrogen (Nr) in terrestrial ecosystems has doubled. While this has enabled high crop productivity, it has also triggered mass environmental effects, with almost half of the applied fertiliser lost into air (in the form of N₂O or NH₃) as well as nutrient runoff and leaching of nitrates into water bodies. Nanomaterials present an opportunity to improve nutrient use efficiency of crops and minimise agricultural pollution via reducing losses. This study screened engineered nanomaterials, including zeolites and metal oxides, to assess their impact on greenhouse gas (CH₄, N₂O and CO₂) emissions when co-applied with NPK (nitrogen, phosphorus and potassium) fertiliser to grow lettuce (Lactuca sativa). The findings show that there are highly differential emissions from soils with nanomaterial co-application with reduced fertiliser application rates. One of the zeolites used, ZSM-5-15, when co-applied with a reduced dose (50% of RB209 nutrient management guide recommendation) of NPK fertiliser, increased N₂O emissions relative to reduced NPK fertiliser alone and negative controls. Another zeolite, BEA-19, had limited effect on either NH₃ or N₂O volatilization, but did reduce the concentration of ammonium in the leachate. Nitrate leaching gradually rose over the course of the 8-week experiment for full NPK fertiliser dose application, reduced NPK dose and negative control. This pattern was altered by BEA-19, triggering elevated nitrate leaching earlier in the experiment, peaking in week 1 compared to week 4 for other treatments. While nanomaterial treatment was able to increase lettuce biomass accumulation compared to full NPK and negative fertiliser treatments, understanding the impact of nanomaterials on N cycling has proven more complex. The mechanism for N loss from soils triggered by ZSM-5-15 application is unknown, potentially through impact on denitrifying enzymes. My work posits that the earlier release of nitrate from BEA-19 application is due to selective binding of the NPK to the nanomaterial surface. More data on nanomaterial endpoints is pending and may help elucidate the nature of this binding and nutrient release mechanisms.

How to cite: Chadwick, J., Lynch, I., and Ullah, S.: Greenhouse gas emissions under nanomaterial co-application with reduced fertiliser input, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8547, https://doi.org/10.5194/egusphere-egu24-8547, 2024.

Rice is a crucial crop for food security, but it is also a significant source of anthropogenic greenhouse gas emissions, particularly methane (CH₄). Projected sea level rise caused by climate change will impact on rice yield through increased salinity. On the other hand, increased salinity potentially mitigates CH₄ emissions by inhibiting methanogenesis mediated by the dominance of sulphate-reducing bacteria. To investigate this dual effect, we conducted a mesocosm experiment creating a water salinity gradient with four levels: 2 ppm (control), 4 ppm, 6 ppm and 35 ppm (seawater). CH₄ emissions, abundance and gene expression of microbial populations and grain yield were assessed.

The experiment took place in year 2022 at IRTA facilities (Spain) using a variety of japonica rice (Oryza sativa L.). Rice was grown following the standard practices, notably permanent flooding, and crop residue incorporation into the soil after the harvest. CH₄ emissions were weekly assessed throughout the rice growing season (May to September) and the post-harvest (October to December). Gas samples were collected using gas chambers and analysed through gas chromatography. Yield and aboveground biomass were measured at harvest. Thereafter, crop residues in each mesocosm, where present, were incorporated into the soil. Soil samples for microbial analyses were taken twice during post-harvest:  6 days before the harvest and 28 days after straw incorporation.  The microbial community diversity was assessed based on 16S/ITS-metataxonomy of total (DNA) and metabolically active (cDNA) bacteria, archaea, and fungi, as well as the quantification of total bacteria (16S rRNA gene), methanogenic archaea (mcrA gene ), and sulphate-reducing bacteria (aprA gene) by qPCR.  The activity of methanogenic archaea and sulphate reducing populations were assessed by quantifying gene transcripts of mcrA and aprA by RT-qPCR.

Rice grain yield decreased by 30% with increasing salinity from 2 ppm to 4 ppm, while there was no yield above 6 ppm. The biomass of straw produced and then added into the soil declined along the salinity gradient: 72.9 ± 12.4 g and 49.8 ± 6.1 g at 2 ppm and 4 ppm treatments, respectively, and zero in the remainder. The results confirmed that salinity significantly reduces CH₄ emissions, but the sensitivity of this response differed between the growing and post-harvest seasons. During the growing season, CH₄ declined with increasing salinity, ranging from 8.0 ± 1.7 to 0.05 ± 0.02 mg CH4 m^-2 h^-1. However, in the post-harvest, no CH₄ emissions were detected at water salinities above 4 ppm, in contrast to 14.8 ± 0.75 mg CH4 m^-2 h^-1 found at 2 ppm. In regard to the microbial processes, the abundance of methanogenic archaea declined with increased salinity and the gene expression was highly inhibited at salinities larger than 6 ppm. By contrast, the abundance of sulphate-reducing bacteria was preserved over the salinity gradient while gene expression remained active, though slightly reduced from 6 ppm, probably due to the lower availability of organic carbon at the highest salinities.

Acknowledgments: The study has been carried out within the framework of the MIC-RICE project PID2019-111572RB-I00 funded by AEI/10.13039/501100011033

How to cite: Martínez-Eixarch, M., Padinhariyil, S., Lucas, Y., Guivernau, M., Alcaraz, C., Jornet, L., Garnier, J., Fernández, A., Noguerol, J., and Viñas, M.: Effect of a salinity gradient on methane emissions in paddy rice: a mesocosm experiment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9530, https://doi.org/10.5194/egusphere-egu24-9530, 2024.

The IPCC provides three distinct protocols (Tier 1-3) that can be used for reporting on greenhouse gas (GHG) emissions under the UNFCCC. While Tier 1 and 2 use relatively straightforward methods based on global and region-specific emission factors, Tier 3 is more complex and uses process models for emission estimation. Although Tier 3 is considered to have higher accuracy potential, its complexity requires expert knowledge and extensive input data, which is often not available, hindering widespread adoption.

This study critically evaluates all three Tier approaches for CH₄ emissions from rice production in Vietnam, using the ecosystem process model LandscapeDNDC for the Tier 3 approach. As a first step, we evaluate all three approaches based on a comprehensive dataset covering 73 cropping seasons from 36 sites across Vietnam. On this basis, we show the extent to which Tier 3 performs better when considering commonly available information, and which information is most important to outperform simpler methods. As a second step, we present national CH₄ emission inventories for each approach and show under which circumstances the approaches differ the most. We also present a web-based tool that improves the accessibility of Tier 3 applications for users who are not familiar with the application of a particular complex process model.

Our findings aim to provide valuable insights into the effectiveness of UNFCCC reporting approaches, particularly the under-researched Tier 3.

How to cite: Nguyen, C., Vo, T. B. T., Bui, P. L., Mai, V. T., Nguyen, T., Butterbach-Bahl, K., Sander, B. O., Wassmann, R., Kiese, R., and Kraus, D.: Assessing different IPCC Tier Approaches for estimating Methane Emissions in Vietnamese Rice Agriculture, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15750, https://doi.org/10.5194/egusphere-egu24-15750, 2024.

In Denmark, the agricultural sector contributes almost 1/3 of total GHG emissions, second only to the energy sector. As significant GHG emission reductions have been achieved for the energy sector, there is increasing pressure on the agricultural sector to achieve GHG reductions of about 55-65% in the coming years.

While the current GHG emission inventory for the agricultural sector at national level in Denmark is based on a combination of Tier 1 and Tier 2 methodology following the standard IPCC methodology, the vision is to report national soil N₂O emissions to the UNFCCC at either Tier 2 or Tier 3 level, the latter being the preferred level for the authorities as they plan to incentivize farmers to reduce emissions based on predictive yield and N₂O emission models.

Against this background, the Danish SmartField initiative aims to establish an innovative field-scale platform for testing and validating solutions to reduce N₂O emissions from agricultural fields. The data obtained will be used to further develop modeling tools for scaling, design and targeting of incentives to be included in regulatory frameworks to encourage adoption of knowledge and solutions by farmers and to ensure that these measures are accurately reflected in national inventories.

The core activities of SmartField are to establish: 1) a field measurement infrastructure to provide state-of-the-art benchmark datasets of N₂O fluxes and other N loss and turnover pathways (NH₃ volatilization and deposition, NOx fluxes, NO₃ leaching, harvest N, soil N stock changes) for the most prominent field management practices in Denmark, including testing of classical and novel mitigation measures, 2) a data assimilation and modeling hub with a consolidated framework to provide evidence-based models for N₂O emission quantification and to test N₂O mitigation measures at large scale in scenario studies, and 3) a science-policy-practice interface (SPPI) to exchange knowledge and information and to build a smooth interaction with agricultural decision and policy models.

This will ensure that SmartField develops and delivers an improved methodology for accounting N₂O emissions at field and farm scale, upon which policy incentives can be developed for farmers to adopt technologies and management measures with verified emission reductions.

SmartField is led by the Danish Technological Institute (DTI) in collaboration with Aarhus University (AU), the University of Copenhagen (UCPH), Colorado State University (CSU), SEGES Innovation (SEGES) and the Danish Ministry of Food, Agriculture and Fisheries (MFAF).

Note, that final funding decision for SmartField is pending approval

How to cite: Butterbach-Bahl, K. and Ann Britt Værge, A.-B.: SmartField – Accounting and mitigation of N2O emissions and N budgets of agricultural soils in Denmark, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17763, https://doi.org/10.5194/egusphere-egu24-17763, 2024.

Globally, agriculture is one of the main drivers of wetland loss, leading to reduced soil carbon (C) and changes in greenhouse gas (GHG) emissions. In recent decades, wetland loss in Africa appears to be faster than the global losses, at about 43% compared to 35% globally. Valley-bottom wetlands in African highland regions support the livelihoods of >65% of the people who live there, but the effect of agricultural conversion on soil C and GHG emissions is understudied. This study compares GHG emissions between 1 intact, 12 agricultural (converted), and 10 recovered valley-bottom wetlands in Taita Hills, Kenya. Using the static gas chamber method, CO₂, CH₄, and N₂O emissions were measured monthly from April 2023 to date along with soil NO₃-N, NH₄-N, soil C, and soil moisture. The results indicate that CO₂ emissions from the converted wetlands is similar to recovered wetlands (mean = 183 ± 11 SE mg CO₂-C m^-2 h^-1 and mean = 174 ± 13 SE mg CO₂-C m^-2 h^-1 respectively; p > 0.05). This is in contrast with both CH₄ and N₂O emissions, which showed strong differences (p<0.005). The average CH₄ emission in agricultural versus intact wetlands was mean = 0.31 ± 9 SE mg CO₂-C m^-2 h^-1 and mean = 10 ± 1 SE mg CO₂-C m^-2 h^-1, respectively, and the N₂O mean emission was mean = 41 ± 0.2 µg N m^-2 h^-1 vs. 9 ± 3 µg N m^-2 h^-1, respectively. Addition of organic and inorganic fertilizer to the agricultural wetlands showed an increase in NO₃-N in the soil and a high correlation with N₂O.  High soil moisture levels and organic matter in the intact wetlands was a major contributing factor for the high CH₄ emissions while low soil moisture in the converted wetlands led to low CH₄ emissions. The soil organic carbon in the recovered wetlands was higher (Mean = 11 ± 0.1 SE Kg C m^-2) compared to the converted wetlands (Mean= 8 ± 0.2 SE Kg C m^-2) indicating higher carbon storage in the recovered wetlands. Overall, recovered wetlands contribute more to Global Warming Potential GWP (0.84 CO₂-equivalents), but these estimates do not take into account losses in soil C storage, which amount to 1043 Kg C m^-2 year^-1. On-going data analysis and field work will use seasonal variation and take into account historical losses in C storage to refine annual emission estimates.

Presentation preference: Oral, On-site
Billing address: Sharon Gubamwoyo
Gregor-Mendel-Straße 33/ DG34 
Institute of Hydrobiology
1180 Vienna, Austria

How to cite: Gubamwoyo, S., Gettel, G. M., Kisha, D. G., Leitner, S., Weigelhofer, G., and Hein, T.: Greenhouse gas emissions from valley-bottom wetlands in an agricultural tropical highland system, Taita Hills, East Africa, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18445, https://doi.org/10.5194/egusphere-egu24-18445, 2024.

Managed grasslands influence global warming by the exchange of the greenhouse gases (GHG) like carbon dioxide (CO₂), nitrous oxide (N₂O) and methane (CH₄). Application of animal waste, such as slurry, rich in inorganic nitrogen (N), may escalate soil processes and thus soil GHG emissions, particularly in organic systems that rely on input of animal manures without chemical inputs.

The objective of this study was to evaluate GHG mitigation potential of biological amendments that might be relevant to organic systems and their effects on soil N and N leaching over a 2-month period. To achieve this a plot-scale field experiment on a grassland site in Rosemount (Dublin, Ireland) was conducted over a period from May to July 2023. Closed static chamber technique was used to measure soil emissions of N₂O, CH₄ and CO₂ with an increased sampling frequency after the slurry application. The dynamics of soil ammonium, nitrate and dissolved organic N were evaluated weekly in soil surface samples from 0-15 cm and in a 10-day interval in the leachate collected at a 50 cm depth. The grass yield was assessed twice during the course of the experiment. The plots were equally irrigated to stimulate soil processes during the dry periods. The treatments assigned to the plots in a randomised complete block design with 5 replicates included control (CON), cattle slurry (SLU) and slurry mixed with biochar (BIO; added at 2 kg/m²), neem oil high with slurry (NEEM H; added at 100% of N applied) and neem oil low with slurry (NEEM L; added at 20% of N applied). The slurry was applied at 50 kg N ha^-1 to all plots apart from CON.

The application of neem oil at both levels of input consistently reduced soil N₂O and CH₄ daily emissions (p<0.001), while NEEM H at the same time increased soil CO₂ daily emissions (p<0.001), compared to the SLU treatment. Biochar reduced soil CH₄ daily emissions (p<0.001), but did not influence soil N₂O and CO₂ daily emissions relative to the SLU treatment.  

These results might be highly relevant for the climate-change policies relevant to organic farming systems and achievements of the national and international climate goals.

How to cite: Pariyar, P., Harty, M., and Necpalova, M.: Biological amendments reduce soil N2O and CH4 emissions from slurry application under field conditions., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20143, https://doi.org/10.5194/egusphere-egu24-20143, 2024.

Agriculture is responsible for about 94% of UE ammonia (NH₃) emissions, notably from livestock, manure management and soil fertilization. NH₃ volatilization is a significant cause of reactive nitrogen (N) loss, leading to lower fertilizer efficiency as well as environmental and health concerns. Loss predictions can be estimated using process-based biogeochemical models, but many of them lack precise estimations of NH₃ volatilization. In this work, we modified the Environmental Policy Integrated Climate (EPIC) model incorporating a mechanistic sub-model to simulate NH₃ volatilization following the application of N fertilizers in agricultural fields. The newly added algorithm in EPIC functions on an hourly time step and describes the ammonium (NH₄⁺) adsorption by clay and organic matter and estimates the partitioning of total ammoniacal N into NH₃ and NH₄⁺ based on the pH of the soil solution. The sub-model then determines the NH₃ concentration in the gas phase using Henry’s law and estimates NH₃ emission using a mass transfer coefficient that considers the resistance in the turbulent and laminar layers. Additionally, the sub-model uses the soil’s pH buffering capacity to recalculate pH following hydrogen ion consumption by urea hydrolysis and hydrogen ion release by NH₃ volatilization. The sub-model further integrates a reduction factor for volatilization to account for the effects of soil layer depth and the depth of fertilizer application. The new EPIC sub-model was validated using datasets from Veneto, NE Italy, and Georgia, USA. In Italy, NH₃ volatilization was measured in four experiments, testing cattle slurry, farmyard manure, and mixed silage maize and animal slurry digestate. Whereas in Georgia, NH₃ volatilization was examined following surface application of urea and poultry manure to grasslands. The new sub-model improved NH₃ loss prediction, yielding reasonable hourly NH₃ fluxes and cumulative volatilization estimates. As a result, the EPIC model exhibited lower prediction errors for soil mineral N (e.g. NH₄⁺and NO₃^-) dynamics. While the new sub-model marks a notable advancement in accurately modeling N cycling, additional enhancements should prioritize certain modeling aspects, including slurry infiltration rates, NH₃ fluxes within the soil profile, and the mitigation effects resulting from urease inhibitor application.

How to cite: Gozio, A., Longo, M., Cabrera, M. L., Izaurralde, R. C., Kissel, D. E., Lazzaro, B., Dal Ferro, N., and Morari, F.: Optimizing Ammonia Volatilization Simulation in Agricultural Soils: Advancements of the EPIC Model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10933, https://doi.org/10.5194/egusphere-egu24-10933, 2024.

Pesticide usage has been expanding since the 1950s. Their use has been known to harm human and environmental health for decades. Pesticide volatilisation to the atmosphere is a known process which is however not well documented, especially for periods beyond a few days after pesticide application. This is partly due to the difficulty to measure gaseous pesticides concentration in the atmosphere continuously for long time periods. Indeed, current state-of-the-art measurements is made by thermo-desorption gaseous chromatography involving semi-manual sampling with cartridges.

In this study, we report first monthly outdoor online measurement of concentrations and volatilisation of one fungicide and two herbicides by proton transfer reaction, quadrupole injection, time of flight, mass spectrometry (PTR-QI-TOF-MS). The fungicide Chlorothalonil was measured over a wheat field in spring, while the herbicides Prosulfocarb and Pendimethalin were measured over a bare soil in autumn. Comparison with state-of-the-art TD-GC-MS and calibration by a home-made permeation system proved the PTRMS to be adapted for pesticides measurements.

Maximum measured concentrations ranged from 12 ppt for Chlorothalonil to 600 ppt Prosulfocarfb. Maximum daily volatilisation fluxes ranged from 35 ng m-2 s-1 for Chlorothalonil to 350 ng m^-2 s^-1 for Prosulfocarb. We found that volatilisation of Chlorothalonil lasted more than three weeks, leading to up to 50% of the applied quantity volatilised, a duration and an amount much larger that what has been reported before.

Volatilisation of pesticides may contribute much more significantly than expected to atmospheric burden, and be wet and dry deposited over larger areas. Further PTRMS pesticides measurements should be done to gain insight into pesticide transfer to the environment, and better characterize human exposure to these harmful compounds.

How to cite: Loubet, B., Lafouge, F., Bsaibes, S., Bedos, C., Decuq, C., Esnault, B., Ciuraru, R., Kammer, J., Vuolo, R., and Gros, V.: Online pesticide concentration and fluxes measurements over crops with a PTRMS shows unexpected volatilisation rates, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10183, https://doi.org/10.5194/egusphere-egu24-10183, 2024.