QS_II Projects Overview

Towards operational uncertainty characterisation for high-resolution AI based biogenic CO₂ fluxes (TORCH)

Responsible partner:     Max-Planck-Institute for Biogeochemistry, Dr. Sophia Walther, Dr. Martin Jung, Dr. Gregory Duveiller, Zayd Hamdi

Project duration:           01.12.2023 – 30.11.2026

Funding reference:       01LK2304A

Our proposed project complements our tasks in WP-Q&S_I.3 ("Biogenic Fluxes") in the ITMS module Q&S regarding biogenic CO₂ fluxes based on machine learning with respect to a thorough assessment of the uncertainties of the generated products in order to realise an optimal integration with atmospheric inversions in the ITMS module M. The expected outcome is the introduction of automated tools that perform a series of complementary uncertainty assessments so that objective and quantitative information on error structures of the biogenic prior can become available in the future operational context of ITMS.

Our approach to assessing uncertainties and errors of biogenic CO₂ flux products for ITMS combines three complementary perspectives to address different aspects of uncertainty:

1. a consistent leave-station-out cross-validation, where the predictions are analysed for their errors when station data have been excluded from training;

2. the creation of an ensemble of products resulting from different methodological sources of uncertainty;

3. consistency checks with independently derived CO2 flux estimates, amongst others for specific sectors (agriculture and forestry) in Germany based on national inventories and specific process model simulations for Germany, which will become available in the Q&S module.

Improving the spatio-temporal variability of Analyzed and near Real-Time greenhouse gas EMISsions for North-Western Europe (ARTEMIS)

Responsible partner:     FUB, Dr. Sabine Banzhaf, Prof. Dr. Martijn Schaap

Project duration:           01.12.2023 – 30.11.2026

Funding reference:       01LK2307A

The ARTEMIS project aims to improve our understanding of the processes and mechanisms that induce the spatio-temporal variability in anthropogenic greenhouse gas emissions. An emission model is being developed for CO₂ and CH₄ and their isotope ratios to provide highly resolved (2 x 2 km²; hourly) emission fluxes for Europe consistent with national reporting as a-priori to the emission inversions for Germany with the ICON-ART model within the framework of the ITMS project. Specific attention is provided to include improved spatial gridding methodologies and to parameterize the impact of changing meteorological conditions on the emission variability for Germany for the sectors Energy and Industry, Road Traffic, Households, Waste management and Agriculture. To assure the efficient uptake into the ICON-ART model a dedicated emission interface to read and process the 4D emission data stream is being developed. The project is executed in close collaboration with UBA, DWD, KIT IMK-IFU and other ITMS partners.

At the end of ITMS Phase 1, the provision of the novel a-priori information from ARTEMIS will enable the ITMS to perform national scale emission verification simulations at unprecedented temporal and spatial resolution.

Modelling of Greenhouse Gas Emissions from Agricultural, Forest and Livestock systems of Germany (Agri-For-Live)

Responsible partner:     KIT IMK-IFU, PD Dr. Ralf Kiese

Participating partner:   TI, Dr. Roland Fuß, Dr. Sebastian Grayek, Dr. Wolfgang Stümer, Dr. Steffen Herrmann

                                   FZJ, Prof. Dr. Harrie-Jan Hendricks-Franssen, Dr. Michael Herbst,            
                                   Dr. Theresa Boas

Project duration:           01.02.2024 – 31.01.2027

Funding reference:       01LK2306A-C

Based on spatially and temporally improved activity, soil and vegetation data greenhouse gas (GHG: CO₂, N₂O, CH₄) emission inventories with unprecedented spatial and temporal resolution will be calculated using two different types of biogeochemical/ land surface models (KIT IMK-IFU: LandscapeDNDC and FZJ: eCLM) for agricultural and forest ecosystems in combination with the Gas-EM model (Thünen) for livestock. With this integrated proposal we jointly work on three out of the 10 topics of the ITMS Q&S_II call, i.e. b) Agriculture, forest and land use (AFOLU) activity data in high temporal and spatial resolution, c) GHG emission from livestock and e) Biogeochemical modeling of GHG exchange processes of agricultural and forest ecosystems, aiming to improve bottom up GHG emission inventories towards higher spatial and temporal resolution which is so far not available for Germany. To do so Thünen Institute will generate and compile improved new activity data for the states of Lower Saxony and Schleswig-Holstein, i.e. two states of Germany with high shares of agricultural land use and high data accessibility. For an efficient and transparent workflow, we will build up a data communication scheme consisting of databases, functions converting geospatial data into model input and model output in targeted inventory products. During initial geospatial data compilation, the LandscapeDNDC, eCLM and GasEM model will be tested and further developed for improved representation of temporal and spatial hotspots of GHG exchange with existing field data. As detailed information of animal numbers, housing and manure storage systems as well as agricultural land management are subject to data privacy laws, next to establishment of scientific data streams this project will also seek for necessary data regulation schemes with data owners as blueprint for further data provisioning at national scale. In this context models will be run with input data for agricultural and forest land use as well as livestock at different spatial scales (i.e. current county (“Kreis”) resolution, 7 x 7km, and 1 x 1 km and in increasing temporal resolution (up to sub-daily) to explore costs (data privacy) and benefits (spatially and temporally improvement) of different levels of data aggregation for the quality of bottom-up GHG inventories and the suitability of different spatial and temporal aggregation for inverse modeling approaches. This information is so far missing but essential for the development of ITMS since top-down and bottom-up estimates of GHG emissions are consistent at larger scales (continental to global), but uncertainty increases, and methods often diverge at smaller spatial scales and particularly when emissions are partitioned into different source categories. In this direction we seek close cooperation with the ITMS Modul M and also ITMS Modul B_II projects dealing with the topic d) Characterization of the spatial and temporal GHG concentration variability in a region in Northwest Germany.

Modeling of greenhouse gas emissions from peatlands in Germany: merging statistical and process based model approaches (MODELPEAT)

Responsible partner:     HSWT, Prof. Dr. Matthias Drößler, Dr. Janina Klatt, Florian Braumann,            
                                   Sebastian Friedrich

Participating partner:     KIT IMK-IFU, PD Dr. Ralf Kiese, Dr. Clemens Scheer,  
Dr. Sergey Blagodatsky

Project duration:           01.02.2024 - 31.01.2027

Funding reference:       01LK2305A/B

Due to their capability to preserve plant residues under anaerobic soil conditions caused by high standing water level, peatlands are among the world's most important carbon reservoirs. In Germany however, 95% of these ecosystems have been drained for agricultural and forestry use. Their storage capacity is therefore disrupted. As a result, they contributed around 6.6 % to national greenhouse gas emissions in 2014 (Tiemeyer et al. 2020) instead of being an ecosystem carbon stock. In recent years, the conservation and restoration of peatlands has increasingly become a political focus.

To date, the national German GHG inventory of agricultural land[IH1] s on peatlands has been based on a Tier 3 approach, combining country-specific emission factors with statistical modelling and spatial data on land use change, type of organic soil and mean annual water level. This approach has significantly improved German inventory reporting, but still only leads to an estimate of the average annual greenhouse gas emissions for a given land use system. Furthermore, this approach does not allow the characterization of detailed spatial and temporal patterns of GHG emissions, which are essential for the development and assessment of mitigation strategies. Process-based modeling approaches  can explicitly calculate GHG emissions in space and time and provide specific responses of GHG emissions to changing environmental conditions (e.g. climate or management changes). Process-based biogeochemical models such as LandscapeDNDC are validated and applicable for the calculation of GHG inventories for agricultural and forest ecosystems. However, the robustness of these models with respect to GHG emissions from peatlands[BS2] ,  is still very limited due to their particular hydrological characteristics that influence C and N dynamics. By combining current experimental data from national and Bavarian research projects (e.g. "Klimaschutz-Moornutzungsstrategien" (BMBF); MOORclimb (StMUV), KliMoBay (StMUV)) with spatially and temporally high-resolution activity[BS3]  and GHG exchange data, this project aims to synergistically develop empirical and process-based modeling approaches to provide the necessary tools for an improved spatio-temporal characterization of GHG emissions from peatlands.

The overall objective of this collaborative project is to develop new and refine existing methods to improve the quantification of GHG emissions from natural, drained and rewetted peatlands (note: the term "peatland" used in this proposal corresponds to the IPCC definition of organic soils) at unprecedented spatial and temporal resolution.

The specific objectives of the approach include:

• Comparing the performance of a statistical model with that of a process-based model and assessing uncertainties at different spatial scales.

• Refinement and optimization of both statistical and process-based modelling approaches.

• Development of a GIS-based modelling framework for the regionalization of GHG emissions from natural, drained and rewetted peatlands with high spatio-temporal resolution.

• Calculation of detailed emission inventories of peatland soils for the federal state of Bavaria.

• Identification of spatio-temporal patterns of GHG exchange of natural, drained and rewetted peatlands and assessment of their relevance for the development of GHG mitigation strategies.

Greenhouse gas emissions from German coastal waters (Coast-GEm)

Responsible partner:     AWI, Dr. Ingeborg Bussmann

Participating partner:     HEREON, Dr. Kirstin Dähnke, Dr. Tina Sanders, Dr. Yoana Voynova

Project duration:           01.05.2024 – 30.04.2027

Funding reference:       01LK2308A

Our project started in July / August 2024 by employing a senior scientist (25%, I. Bussmann) and a Post-doc (L. Rewrie, 100%).

The overarching ITMS project aims to enable Germany to operationally monitor the sources and sinks of the three most important long-lived greenhouse gases CO₂, CH₄, and N₂O with the help of independent measurements. In the proposed Q&S_II project, the focus lies on the quantification of greenhouse gas sources and sinks in the coastal area of the German North Sea. We will use existing monitoring infrastructures in a combination with cruises in the North Sea coastal zone to assess coastal emissions of greenhouse gasses. An important focus in the German North Sea coastal zone is the Elbe mouth, which is the largest source of nutrients to the German Bight and will likely exert major control on coastal greenhouse gas emissions. In addition, information from databases and own work on the distribution of greenhouse gasses in the German Bight and the Elbe estuary will be compiled. Whenever possible, data on greenhouse gas concentrations will be converted to emission data and finally made available to the ITMS-community. With our data on coastal greenhouse gas emission, we will contribute to the national data set of observation-based, spatially, temporally and sectorally resolved emission fields.

In the course of other projects (ElbeXtreme, Carmaflux) we have conducted three cruises in 2024. In August the tidal Elbe was investigated with continuous monitoring of all three GHGs. In September we performed a systematic zigzag course with continuous monitoring of CH4 in the Elbe Estuary and southern North Sea. For the first time we were able to assess the northern area of the German Economic zone and East Frisian Wadden sea with the RV Heincke. As we are using different instrumental set-ups, we plan to conduct an intercalibration of these set-ups.

The continuous monitoring in the River Elbe was started in spring 2024, however there are some technical issues to be solved. The established ICOS monitoring station at the estuary, is continuously monitoring dissolved CO2 and we plan to extend the measurements to CH4 in 2025. This site is the most challenging as strong currents, turbid water and biofouling require a lot of maintenance efforts. The marine station Helgoland is using established infrastructure. Our methane sensor is on site and colleagues are also measuring CO2 recently.

Our next steps are to apply a common estimation to convert concentrations of dissolved gases into fluxes, and subsequently how to best include these data into the ITMS community.

CoastGEm is accompanied by the AGRIO project (2025 - 2027) funded by the Helmholtz community establishing the first continuous coupled hydrodynamic and biogeochemical model system by laterally and procedurally connecting existing models for the Elbe river-sea continuum describing all three GHG pathways.

Atmospheric Boundary Layer Measurements of CO₂ and CH₄ from Ships (ATMO-SHIP)

Responsible partner: IOW, Dr. Gregor Rehder

Project duration: 01.07.2024 bis 30.06.2027

Funding reference:       01LK2401A

As a contribution to the Q&S II and B II modules of the ITMS, the ATMO-SHIP project aims to realise the measurement of atmospheric concentrations of the gases CO₂, CH₄ and CO with ICOS-ATC-compliant quality in the area of the German Baltic Sea coast. This will build on the results of the EU project RINGO, in which such a setup was realised on board the ICOS platform SOOP TAVASTLAND as a pilot project. The instrumentation is to be adapted and initially transferred to the research vessel ELISABETH MANN BORGESE, whereby the control and frequency of data transmission are to be significantly improved at the same time. The instrumentation will provide data for over a year and the transmission and data processing will be operationalised, probably directly via the ICOS-ATC. Routines and algorithms for filtering interference data are to be established and further developed. This year will also see the planning and preparation of the transfer of the instrumentation to the ICOS platform SOOP FINNMAID (Lübeck-Helsinki), on which the IOW will also carry out corresponding measurements of surface water as part of ICOS and where the system will then be operated for a further year. The data from atmospheric measurements and surface water measurements will be used to limit the uncertainty caused by the usual use of atmospheric mole fractions from fixed stations for oceanic flux calculations. Through analysis together with the ITMS, the added value of the atmospheric data for the tasks of the ITMS is to be analysed primarily, also in relation to the preferred platform (research vessel with partially recurring voyages compared to a continuously operating commercial ferry). A decision on continued operation (e.g. application for the establishment of an ICOS-ATC station) will be made on this basis. In addition to the expected added value for the tasks of the ITMS, the results are also of great importance in the context of strategy development for the WMO Global Greenhouse Gas Watch (G3W) initiative.

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