The Internet of the Environment (IoE) represents a subset of the Internet of Things (IoT) where connected environmental monitoring sensors, that utilize edge computing and embedded power and communications, report on the state of the environment to improve scientific understanding via large-scale monitoring. 

The IoE approach offers several notable advantages compared to traditional methods:

• It facilitates measurements in almost any location, including large-scale deployments and remote, hard-to-reach areas.
• It supports consistent measurement techniques that are scalable from field to landscape to continental levels, all while reducing operational costs.
• It leads to cost savings and minimizes data loss through enhanced operations, utilizing predictive maintenance powered by machine learning.
• It integrates various external datasets into a unified cloud platform, enabling automated post-processing and advanced data analytics.

This presentation covers the integration of an eddy covariance (EC) sensor with an IoE Module, transforming it into a node within the IoE system. Other sensors, measuring different environmental parameters, can serve as additional nodes.

Once the data from these nodes is transmitted to the cloud, it can be utilized for automated quality assurance/quality control, gap filling, forecasting, accumulation, and spatial extrapolation, leveraging external datasets and statistical/machine learning tools.

This integration enables users to construct dynamic virtual networks of real measurements from various research sites and nodes, facilitating scientific research and fostering collaboration between institutions and groups.

An illustrative example of this approach is presented through a network of actual evapotranspiration EC sensors, which collect flux data across diverse irrigated and rain-fed agricultural landscapes for immediate societal applications.

How to cite: Griessbaum, F., Fratini, G., Ivans, S., Thomas, T., Singer, D., Parr, A., and Hupp, J.: Internet of the Environment (IoE) and Eddy Covariance-based Ecosystem Fluxes, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6426, https://doi.org/10.5194/egusphere-egu25-6426, 2025.

Regional flux networks, including AmeriFlux, ICOS, NEON, and OzFlux, are now regularly generating and updating FLUXNET data products for their sites. With that, flux data availability is considerably expanded, with an increased number of sites with data and addition of recent site-years. Other improvements include continued extension of variables and metadata supported and collected, deployment and operationalization of the jointly maintained ONEFlux pipeline, better integration of network-level data quality control processes, and expansion of adoption of open data policies, mainly based on the CC-BY data license. To facilitate access to these newer data, we are making available the FLUXNET Shuttle, a tool supporting the automated compilation of FLUXNET data products published by the regional networks. The tool supports creating the equivalent of global FLUXNET datasets on-demand, allowing more timely access to new data, while still offering replicability functionality through the use of versions. In this presentation, we show a demonstration version of this new tool, showcasing its mode of operation and the products made available through it. A production version of the tool is slated for release by the end of 2025. Based on the data access made possible by the FLUXNET Shuttle, we will show a short summary of the current FLUXNET data availability compiled from the regional network data published products. We also discuss approaches to continue properly assigning credit to site teams, fully following regional network data policies.

How to cite: Pastorello, G., Isaac, P., Sturtevant, C., Trotta, C., Cheah, Y.-W., Arndt, S., Durden, D., and Papale, D.: The FLUXNET Shuttle: accessing current global flux data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14073, https://doi.org/10.5194/egusphere-egu25-14073, 2025.

Eddy covariance stations collect in situ high frequency (10 Hz) measurements of wind speed and direction in three dimensions alongside high frequency (10 Hz) measurements of water vapor concentration. Raw high frequency data undergo processing onboard field-deployed sensor systems to provide flux measurements at 30-minute averaging intervals. The processed flux data are then transmitted via message queue telemetry transport (MQTT) to a cloud-based platform where post-processing can occur. This presentation provides an overview of a post-processing pipeline built on 30-minute fluxes and ancillary meteorological data inputs to arrive at cleaned and gap-filled evapotranspiration fluxes over multiple timeframes. The steps to arrive at these intermediate data products include physically plausible threshold detection, quality-control based on error condition for the flux averaging interval, statistical outlier detection, and gap filling using the marginal distribution sampling (MDS) method. Drivers for MDS gap filling shown include vapor pressure deficit (VPD), incoming shortwave radiation (SWin), and air temperature (Tair). Accumulated fluxes are then spatialized based on the flux footprint associated with the accumulation period, using inputs from flux sensors and global weather models as well as ancillary remote sensing multispectral imagery from the European Space Agency (ESA) Sentinel2 constellation. The provenance associated with this pipeline is available to promote scientific reproducibility.

How to cite: Thomas, T., Barker, T., Fratini, G., Hupp, J., Burba, G., Griessbaum, F., Kshatriya, K., and Roth, E.: A Cloud-Based Post-Processing Pipeline for Eddy Covariance Flux Datasets: From Actual Evapotranspiration Measurements to Spatial Water Balance, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7305, https://doi.org/10.5194/egusphere-egu25-7305, 2025.

Continuous accurate monitoring of greenhouse gas concentrations on a large number of tall towers (TT, approximately 100 m above ground level and higher) is increasingly becoming a tool to independently quantify regional emissions (top-down approach). However, installing or finding and equipping tall towers is costly. To densify the existing monitoring network as efficiently as possible, a secondary use of existing eddy-covariance flux stations (EC, typically 2 to 50 m above ground level depending on plant canopy height) as “virtual tall towers” (VTT) has been suggested. The basic idea is that the additional flux and turbulence information available at an EC station can be utilised to correct the near-surface concentration measurement, which is heavily influenced by local sinks and sources, towards an estimate that is more representative of the well-mixed part of the atmospheric boundary layer, and thus more indicative of regional emission sources. In the framework of the ITMS (https://www.itms-germany.de/) project, we aim to evaluate the feasibility of such methods on selected pairs of existing EC and TT stations in the ICOS (https://www.icos-cp.eu/) network. For this the EC gas analyzer needs to be calibrated directly or indirectly to the same reference as the TT gas analyzer, which is not commonly the case. Our first tests comprise one pair of an EC (DE-RuS, 2.5 m measurement height) and TT (AS-Jue, 120 m) stations approximately 5.6 km apart in Germany, as well a second pair on a single, tall tower in Sweden (SE-Svb) where EC measurements and shallow TT measurements are available on the same level (35 m). This latter unique situation allows us to estimate the higher TT measurement on the same tower (150 m) without requiring an additional calibration of the EC sensor. Together, the two test cases allow to separate calibration and spatial representativity issues on the one hand, from the actual VTT performance on the other hand. Our first results indicate that accurate, stable calibration at EC sites is crucial but difficult to achieve. In addition to an existing VTT technique (Haszpra et al. 2015), we also test a novel approach based on conditional sampling of eddies carrying air characteristic of the atmospheric boundary layer, building up on earlier work with temperature measurements (Graf et al. 2010).

Haszpra, L., Barcza, Z., Haszpra, T., Patkai, Z. and Davis, K.J., 2015. How well do tall-tower measurements characterize the CO2 mole fraction distribution in the planetary boundary layer? Atmospheric Measurement Techniques, 8(4): 1657-1671. https://doi.org/10.5194/amt-8-1657-2015

Graf, A. et al., 2010. Boundedness of Turbulent Temperature Probability Distributions, and their Relation to the Vertical Profile in the Convective Boundary Layer. Bound.-Layer Meteor., 134(3): 459-486. https://doi.org/10.1007/s10546-009-9444-9

How to cite: Marcon-Henge, L., Graf, A., Schmidt, M., Kubistin, D., Lindauer, M., Müller-Williams, J., Ney, P., Klosterhalfen, A., Peichl, M., and Vereecken, H.: Virtual Tall Towers: First test results for the German Integrated Greenhouse Gas Monitoring System, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6552, https://doi.org/10.5194/egusphere-egu25-6552, 2025.

Continental-scale research infrastructures and flux networks (e.g., AmeriFlux, AsiaFlux, ChinaFlux, ICOS, NEON, OzFlux), alongside smaller GHG flux networks and individual sites, assess CO2, CH4, and other GHG exchange, as well as evapotranspiration (ET), between ecosystems and the atmosphere. Over four decades, these flux stations have expanded to 2100+ stationary measurement points and various campaign sites, informing long-term climate modeling.

Despite the potential of these high-resolution measurements for measuring GHG emissions and ET, their applications still rarely extend beyond academia due to the perceived complexity of the method, actual complexity and cost of current instrumentation and site operation, lack of broad geographic data coverage, and absence of a comprehensive approach focused on using direct flux measurements for immediate societal benefits.

This presentation continues to address these challenges by simplifying explanations, offering detailed guides for method understanding, developing lower-cost simpler-to-use automated flux instrumentation and networks, facilitating peer-to-peer cross-sharing to reduce data gaps and station setup costs, and providing professional services for experiment design and executions. All of these allow adopting an overall approach inspired by current automated weather stations (AWS) feeding and tuning remote sensing products and resulting in weather modeling and forecasting.

In the most recent developments, in early 2025, three new guides on direct real-time dMRV/aMRV/MMRV of all carbon pools will be published. These guides aim to optimize costs, de-risk dMRV systems, create premium carbon products, develop standardized frameworks, and assist in writing protocols for carbon sequestration and credit verification. The books include:

• Harvesting Carbon: Fields & Grasslands
• Harvesting Carbon: Forests, Orchards, and Wooded Wetlands
• Harvesting Carbon: Lakes, Ponds, and Wetlands

These latest publications aim to fundamentally change carbon markets by providing a direct, defensible, traceable, repeatable, real-time, evidence-based approach to quantify sequestration and emission.

The ultimate goal of this presentation is to ignite discussions on utilizing these guides and direct flux measurements at large to help practical decision-making applications to benefit society, and identify current needs, ideas, and examples for leveraging flux data in everyday decision contexts.

How to cite: Burba, G.: Direct Flux Measurements for Immediate Societal Benefits: Clear Guidance, Modern Automation, Resource Sharing, Professional Services, and Weather Station-Inspired Approach, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3303, https://doi.org/10.5194/egusphere-egu25-3303, 2025.

The constant growth of population living in urban areas creates new opportunities for urban forest to provides ecosystem services for human wellbeing such as, cooling effect, and carbon neutrality of cities. Studies related to urban forest involve transdisciplinary fields that include environmental, social, and economic aspects, at a range of different spatial and temporal scales. Nevertheless, experimental observation of carbon and energy exchange in urban forest have been so far fragmented, limited to short period of time, and never spatially distributed. While a considering amount of remote sensing and modelling studies indicates the potential cooling capacity and carbon uptake of urban forest, the impact of climatic extreme events on it is still unclear. Through multiple years of unique Eddy Covariance (EC) observations of a mature urban forest located in southern Europe we highlighted how carbon and water fluxes respond differently, almost as if uncoupled, with evaporative cooling maintained during the climatic drought and net carbon sequestration reversed. A long term EC observation, coupled with  modeling simulations, highlight   the role of urban forest as potential tool for climate and microclimate mitigation with and without drought limitations. Our results have important policy implications for urban forest management and planning and more generally for strategies, on urban forest, in relation to carbon neutrality and thermal comfort. While the urban forest had an annual net loss of CO₂ to the atmosphere, its above- and below- ground biomass and the soil represent a relevant carbon reservoir, and its summer uptake of atmospheric CO₂ enabled evaporative cooling of the microclimate. However, the impact of summer drought reduced the levels of cooling benefits compared to non-drought summers. We identified a need for drought tolerant species selection to ensure their ability to tolerate future climate and provide needed ecosystem services such as maintained assimilation rates or survival during drought. Our results represents the first long term, and continuous experimental observation to demonstrate that the urban forest cooling capacity in warm seasons can decouple from net CO₂ uptake and will be limited by the amount of water available, either from precipitation or irrigation sources.

How to cite: Zenone, T., Calfapietra, C., Guidolotti, G., Bertolini, T., Ciolfi, M., Mattioni, M., Rezaei, N., and Pallozzi, E.: Carbon and water fluxes in urban forest: improving human well - being for a more sustainable society, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9741, https://doi.org/10.5194/egusphere-egu25-9741, 2025.

Direct CO₂ and H₂O flux measurements provide valuable insights into ecosystem processes and their societal benefits, such as greenhouse gas budget assessments and optimizing agricultural water management. This study presents a year-long dataset of eddy covariance flux measurements to examine the carbon and water dynamics of a vineyard ecosystem located in the Adige Valley of the Italian Alps. The vineyard trained as a pergola, with spontaneous herbaceous vegetation on the floor, employs a drip irrigation system during hot and/or dry periods. The eddy covariance station, operational since August 2023, was deployed as part of the Euregio project INTERFACE. High-frequency data were processed applying standard corrections using EddyPro® software and gap filling of 30-min fluxes was performed, enabling an investigation into the vineyard's carbon uptake and water dynamics. 

By examining these fluxes, we investigated the vineyard's capacity for carbon uptake and quantified its water use, gaining insights into its role in ecosystem dynamics. The results highlight how flux measurements can guide practical applications, such as optimizing irrigation scheduling, improving carbon budgeting, and supporting adaptive management practices to enhance agricultural sustainability. Notably, the findings suggest that the vineyard ecosystem in the Adige Valley can act as a carbon sink on an annual basis. By providing precise measurements of carbon uptake and water consumption, this research contributes to the development of equitable and science-driven solutions for reducing greenhouse gas emissions and conserving water resources in agricultural landscapes.

How to cite: Sankar, M. S., Carpentari, S., Giovannini, L., Zardi, D., and Vendrame, N.: Year-long measurements of CO2 and H2O fluxes above a vineyard in an Alpine valley, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6254, https://doi.org/10.5194/egusphere-egu25-6254, 2025.

Land cover change is a major driver of anthropogenic climate change, contributing to increasing CO₂ emissions and altering the exchanges of water, energy, and gases between the land surface and the atmosphere. As these changes can subsequently affect both regional and global climate feedback mechanisms, much attention has been invested into their quantification. While global observation networks of biosphere-atmosphere interactions have provided valuable data in this context, their spatial coverage is uneven, with substantial data gaps in critical regions. Africa, despite its ecological and climatic importance, remains one of the least represented regions in these networks. Furthermore, the continent hosts diverse ecosystems—from arid deserts to wetlands—that deliver essential environmental services and undergo rapid land use changes due to both natural and anthropogenic factors. The scarcity of field measurements in Africa has resulted in a heavy reliance on satellite remote sensing, which often lacks high-resolution ground validation. For example, remote sensing analysis in South and East Africa reveals that the net difference between carbon sequestration and increasing shortwave radiation forcing in drylands undergoing afforestation is not spatially uniform. While some African drylands are expected to show a net cooling effect over an 80-year forest lifetime, others are expected to exhibit a net warming effect. We will deploy a mobile biosphere-atmosphere laboratory to gather direct ground-based measurements to validate such remote sensing estimates, in currently underrepresented areas. The mobile lab integrates advanced methodologies, including eddy covariance flux measurements, multispectral radiation sensors, soil and leaf gas analyzers, and sun-induced fluorescence. Our preliminary studies demonstrated that short-term campaign data combined with local, continuous meteorological data can produce seasonal and annual-scale assessments of water, carbon, and energy budgets. The combination of advanced field measurements with remote sensing validation will fill critical observational gaps in Africa and enhance predictions of ecosystem resilience under future climate scenarios.

How to cite: Elhanati, D., Bohak, Y., Nemera, D.-B., Tatarinov, F., Lee, S.-C., Rotenberg, E., and Yakir, D.: Land Cover Change and Its Impacts on Land-Atmosphere Interactions in Africa: Bridging Critical Gaps Using a Mobile Field Lab, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12406, https://doi.org/10.5194/egusphere-egu25-12406, 2025.

Forests provide various ecosystem services (ES), including the delivery of natural resources, the regulation of atmosphere-land surface interactions, and the facilitation of social and cultural activities. However, the acceleration of climate change is increasingly threatening the sustainability of these ES by modifying essential ecological processes via biogeophysical-chemical determinants of critical processes such as fluxes of gases, water, energy, and nutrients. Atmospheric nitrogen deposition is a major air pollutant that affects forest ecosystems through nitrogen cycles. Across the European Alps, though the total nitrogen deposition has steadily decreased since the late 1980s, the present annual deposition remains at medium to high levels (on average 15 kg N/ha), while temperate forests are generally nitrogen-limited. How nitrogen deposition affects forests in the Alps, particularly in the context of reduced nitrogen deposition, is critical for anticipating future forest functions and ES. In addition, the promotion of some essential forest ES is inherently contradicting. For instance, timber production requires massive logs of standing trees, whereas mitigating abiotic disturbances and hazards generally necessitates retaining high biomass and biological diversity. Balancing forest multi-functions is, therefore, integral to ensuring better, more sustainable use of natural resources benefiting our societies in the context of rapid global change. Here, we focus on (i) building a framework to identify and integratively quantify various ES across 6000 Swiss National Forest Inventory plots; (ii) quantifying and comparing the impact of nitrogen deposition on various ES at the stand level since 1990 in a multivariate inference framework while explicitly taking into account potential spatial dependence and confounding factors using [YV1] a stochastics process embedded in the multivariate framework; (iii) quantifying the overall impact of two-decadal nitrogen deposition rates on forest multi-functionalities accounting for the synergies between each ES. Finally, we discuss the potential and conditions for transposing these impacts to other forest ecosystems.

How to cite: Chen, L., Vitasse, Y., Bose, A., Krumm, F., Lever, J., Wilhelm, M., and Gessler, A.: Decadal nitrogen deposition impacts on forest functions and ecosystem services across the Europeanof Alps, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6116, https://doi.org/10.5194/egusphere-egu25-6116, 2025.

Measuring evapotranspiration (ET) is crucial for understanding the complex interactions among the atmosphere, vegetation, and land. In the context of global climate change, distributed quantification of actual ET has become even more important, as alterations in the hydrological cycle affect water availability, ecosystem dynamics, and thus agriculture.

In this study we present a network to directly measure ET across different land uses in the Aosta Valley (Western Italian Alps) in the context of the Agile Arvier project. Supported by funding from the European Union’s economic recovery plan, the Agile Arvier project aims to transform the small village of Arvier into a hub for climate change research in the Alps. This activity is part of one of the five work packages (or “Laboratories”), the Green Lab, which includes studies on water use and smart agriculture, among other activities.

Typically, ET is a modelled component in irrigation water requirement (IWR) models, with estimates derived from meteorological data or crop coefficients. While these models provide valuable insights, they often lack the accuracy provided by direct measurements. Measuring actual ET, e.g., by means of the eddy covariance technique, is crucial for improving water management strategies, especially in regions characterized by diverse landscapes and land uses.

To this end, in 2025, seven LI-710 Evapotranspiration sensors (from LI-COR) will be installed to directly measure ET across different agricultural lands in the Aosta Valley region. We selected seven monitoring sites representative of the typical crop types in the region, including a vineyard, an apple orchard, and five meadows and pastures ranging from 500 to 1950 meters above sea level (m a.s.l.). To enhance the value of the data collected by the LI-710 sensors, we will integrate into the network decadal ET measurements already available from two ICOS (Integrated Carbon Observation System) associated sites located in the same region: an abandoned pasture and a larch forest at 2150 m a.s.l. (IT-Tor, IT-TrF).

Data from the ET network will be compared with IWR data available for the entire region to validate and refine the accuracy of IWR estimates using direct ET measurements. The results of this comparison will be used to inform policymakers and provide the Regional Agricultural Department with an enhanced tool for irrigation management.

Finally, by the end of the year, we aim to create an online open-access dataset for ET data consultation and download, available for scientists and policymakers.

How to cite: Koliopoulos, S., Guarnieri, C., Ferraris, D., Pogliotti, P., Avanzi, F., Chabloz, D., Filippa, G., Lodigiani, M., Nicora, M., Tagliaferro, F., and Galvagno, M.: Supporting Next-Generation Agriculture in the Alps: Direct Evapotranspiration Measurements for Smarter Water Management, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10592, https://doi.org/10.5194/egusphere-egu25-10592, 2025.

Integrated crop-livestock systems (ICL) hold significant potential as greenhouse gas sinks in Brazil, offering a promising avenue for mitigating climate change impacts. The DNDC (DeNitrification-DeComposition) model, a robust tool for simulating biogeochemical processes, provides an advanced framework for modelling nitrous oxide (N₂O) emissions. This capability is crucial for assessing the effects of nitrogen (N) management within ICL systems, enabling the optimization of agricultural sustainability by balancing productivity with environmental stewardship.

Field data were obtained from an ICL experiment conducted at the ‘Capivara Experimental Farm’ by Embrapa Rice and Beans, located in Santo Antônio de Goiás, GO, Brazil (16°28´S; 49°17´W; 823 a.s.l.). The ICL experiment was evaluated over four years (2019–2022) using the following crop rotation sequence: common beans (Phaseolus vulgaris) - aerobic rice (Oryza sativa) - forage grass (Urochloa spp). The soil was classified as clayey Ferralsol with 2% organic matter content. All crop phases were conducted under zero tillage.

N₂O emissions were measured using manual static chambers during the bean phase. The experiment included four treatments: Control (No N), Inoculated (No N + Ino), Urea (UR), and Inoculated + Urea (Ino + UR), with four replicates each. N₂O emissions were recorded during 30 sampling events over nearly 70 days throughout the bean cycle. Nitrogen was applied at a rate of 119 kg/ha.

The above treatments were used to parameterize the DNDCv.CAN model, which demonstrated satisfactory performance in predicting N₂O emissions in the ICL system, showing a significant correlation with observed data (r = 0.57, p < 0.001), a MAE of 0.011, and a RMSE of 0.016. The average daily observed N-N₂O fluxes were 0.017 kg ha⁻¹ day⁻¹, compared to 0.012 kg ha⁻¹ day⁻¹ simulated by the DNDC model.

Accumulated N₂O emissions were 0.770, 0.399, 0.808, and 0.991 kg ha⁻¹ for Control, No N+Ino, UR, and Ino+UR, respectively. Simulations by DNDC for these treatments were 0.636 (UR and Ino+UR) and 0.237 kg ha⁻¹ (No N+Ino). In general, the model showed a good fit with daily N₂O fluxes but tended to underestimate accumulated emissions. Moreover, the model requires improvements to more accurately capture the influence of using inoculants. Further model parameterization and calibration is currently in progress to improve predictions. Using inoculants to substitute N significantly reduces N₂O emissions in bean production, enhances soil health, and lowers costs for farmers, contributing to food security. This practice aligns with Brazil’s environmental policy and strengthens its leadership in sustainable agriculture.

How to cite: Matos, P. S., Soares, J. R., Carvalho, M. T. M., Mitra, B., Jones, E., Madari, B. E., Freitas, A. C. R., Alves, B. J. R., Silva, R. R., Araujo, W. A., Siqueira, M. M. B., Machado, P. L. O. A., and Yelupirati, J.: Evaluating the DNDC Model for Predicting N₂O Emissions in Integrated Crop-Livestock Systems: Insights from Inoculant and Nitrogen Fertilizer Management in Brazil, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18712, https://doi.org/10.5194/egusphere-egu25-18712, 2025.

FloraFlux is a collaborative initiative to collect plant species occurrence data from flux tower sites worldwide. The project is open and inclusive, requiring no botanical expertise and minimal time and costs for participants. Only a smartphone is needed, leveraging automated plant identification via the Flora Incognita app (Mäder et al., 2021). Participants are encouraged to "take pictures of as many species in the footprint as you like, the more the better", while we also facilitate optional additional information. FloraFlux complements and extends traditional, resource-intensive vegetation surveys, enabling widespread data collection across a global network of sites. The data collected by FloraFlux will be shared with participants and ultimately the scientific community by a joint publication in an open access format, enhancing the collective knowledge of plant diversity and ecosystem functions. More information on FloraFlux can be found on the FloraFlux website (https://floraincognita.com/floraflux/).

How to cite: Tautenhahn, S. and the FloraFlux team and participants: FloraFlux - Collaborative AI-Based Plant Data Collection at Flux Tower Sites, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18134, https://doi.org/10.5194/egusphere-egu25-18134, 2025.

Accurate and continuous monitoring of soil water content (SWC) and plant development provides significant benefits in various contexts, including long-term environmental observatories, the development and validation of environmental models and remote sensing products, as well as practical applications like digital and sustainable agriculture. Cosmic-Ray Neutron Sensors (CRNS) are becoming increasingly popular for continuous and non-invasive monitoring of SWC, and recent advancements have demonstrated their potential for vegetation monitoring. CRNS use a moderated detector to measure epithermal neutron intensity (E_n) and estimate SWC over a radius of approximately 200 m. An additional bare detector measures lower-energy thermal neutron intensity (T_n), which is more sensitive to vegetation biomass than to SWC. However, the benefits of simultaneous monitoring of SWC and vegetation properties with CNRS for monitoring networks such as ICOS and ILTER have not been investigated yet.

In this study, a CRNS that is part of the COSMOS-Europe network measured E_n and T_n over a 10-year period at the ICOS Class 1 ecosystem station in Selhausen, Germany (integrated into the already-present TERENO station in 2019). E_n and T_n were compared to a large dataset of a) SWC obtained from multiple point-scale sensors within 30 m of the CRNS, b) gross primary productivity (GPP) obtained with the eddy covariance (EC) method, and c) manual and drone-based measurements of plant height (PH), leaf area index (LAI), and dry aboveground biomass (AGB).

Discrepancies between the CRNS and the point-scale SWC measurements were observed (RMSE of 0.063 cm³/cm³). These were attributed to the periodic reinstallation of the point-scale sensors that sometimes led to abrupt changes in measured SWC, and to the fact that the CRNS, like the EC station, measures over a much larger area. Thanks to the co-location of the CRNS and EC station, a comparison of T_n and GPP showed a clear co-development during cropping periods and the lower responsiveness of T_n during senescence and desiccation indicated that factors such as plant structure and other hydrogen pools (e.g., below-ground biomass) may affect T_n. Crop-specific or annual models were used to estimate plant traits from T_n. The accuracy of plant traits predicted by the CRNS was relatively lower compared to manual and destructive methods (RMSE of 0.13 m for PH, 1.01 m for LAI, and 0.27 kg/m² for dry AGB). However, the effortless nature of the CRNS outweighs this reduction in accuracy, opening the possibility of generating continuous time series of plant traits with only a few manual measurements.

This study showcases the potential of CRNS for simultaneous field-scale monitoring of SWC and vegetation, which is of great interest for monitoring platforms and environmental modelling. Moreover, the novel findings obtained by comparing T_n and GPP showed that strengthened collaboration between observatories and networks such as COSMOS, TERENO, and ICOS, can provide information that is not only useful for researchers but also for instruments manufacturers. In fact, the possibility to extend the usage of CRNS beyond SWC and toward monitoring of plant traits could increase the interest towards thermal neutron detection and vegetation monitoring.

How to cite: Brogi, C., Bogena, H. R., Huisman, J. A., Jakobi, J., Schmidt, M., Montzka, C., Bates, J., and Akter, S.: Simultaneous monitoring of soil water content and vegetation with cosmic-ray neutron sensors: novel findings and future opportunities, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12743, https://doi.org/10.5194/egusphere-egu25-12743, 2025.

From academic research to carbon MMRV/MRV/dMRV/aMRV frameworks and across many industrial sectors, high-quality direct measurements of CO₂ fluxes between the earth surface and the atmosphere are emerging as strategic assets of unique usefulness. Correspondingly, demand for simple-to-use automated instrumentation to perform such measurements is growing fast.

The LI-720 is a new CO₂/H₂O “flux sensor”, designed to achieve performances comparable to traditional high-end EC systems but at significantly reduced costs, maintenance needs, and power consumption. Recently, LI-COR Environmental released the Carbon Node, which combines the LI-720 with a power/IoT communication box. The result is a wireless, lightweight instrument more akin to a meteorological sensor than to a traditional EC system, which delivers flux data directly to a cloud-based data management system where flux time series are further consolidated with automatic quality control and gap-filling procedures. The Carbon Node represents the most streamlined CO₂/H₂O flux system available to date.

Here we present the technical features of this new system and showcase its field performance against high-end EC systems across a variety of ecosystems and climates, discussing benefits, trade-offs and limitations. We find that, when unit-to-unit variability and other uncertainties are taken into account, the LI-720 performance is comparable to traditional open-path (LI-7500-based) and enclosed-path (LI-7200-based) EC systems, most notably when fluxes are aggregated over daily, weekly or monthly cumulates.

We also discuss the use of the new sensor in both traditional academic applications focused on process-level studies, and new commercial applications focused on decision-making for immediate societal benefits.

How to cite: Fratini, G., Kathilankal, J. C., Burba, G. G., Lynch, D., Welles, J., Osborn, S., Eckles, B., Fuhrman, I., Franzen, D., Griessbaum, F., Ivans, S., Tuccio, R., Roth, A., Barth, T., and McCoy, J.: New streamlined, reduced-cost CO2/H2O Flux Sensor & Node open a new era for eddy covariance measurements and applications, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10298, https://doi.org/10.5194/egusphere-egu25-10298, 2025.

The carbon and water balances of high-elevation (>2500 m) Alpine grasslands still offer important open questions. Understanding whether those grasslands act as a net carbon either source or sink, and quantifying the evapotranspiration – also depending on the meteorological and soil conditions - is still a challenge. In this analysis, a focus on two years of measurements (dry year 2022 and closer to normal conditions 2023) collected at a high elevation grassland site (2600 m a.s.l.) is presented. The interannual variations of ecosystem respiration, gross primary production (GPP), net ecosystem exchange (NEE) and actual evapotranspiration (ET_a) give insights on how the ecosystem reacts to different atmospheric and soil conditions, including the Winter snowpack coverage extent, depth and duration. First results show that the greater duration and depth of 2023 Winter snowpack may influence the grassland behaviour, being characterised by a higher emission in early growing season just after the snowmelt. Hence, the grassland sink ability in 2023 (-1.5  gC m^-2 ) is strongly reduced, if compared to the 2022 one (-73.4  gC m^-2) even if the 2023 year was more wet if compared to very dry 2022. Limiting the analysis to the period January-October (end of the very late growing season), results indicate that the cumulative ecosystem respiration reaches 420.0 gC m^-2 in 2023 whereas in 2022, the cumulative value is 345 gC m^-2. GPP cumulative values are instead -454 gC m^-2 and -469.1 gC m^-2 in 2022 and 2023, respectively.

Considering the most important part of the growing season (June-September), the cumulative ET_a does not show particular differences among the two years. In addition, the ET_a and NEE drivers can be analysed. Results indicate that the most significant drivers are net radiation, air temperature, wind speed, matric potential and ground heat flux for ET_a. Photosynthetic photon flux density, vapour pressure deficit, soil temperature and soil water content are the most important drivers for NEE.

This work was supported by the NODES project, funded under MUR - M4C2 1.5 of the PNRR with resources from the European Union - NextGenerationEU (Grant Agreement no. ECS00000036) as well as the MUR PRIN Project SUNSET (202295PFKP_003).

How to cite: Gisolo, D., Gentile, A., Hamza, T., Bechis, S., Canone, D., and Ferraris, S.: Year-round eco-hydrological monitoring of a high-elevation Alpine grassland, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17896, https://doi.org/10.5194/egusphere-egu25-17896, 2025.

The production of vegetable oils takes up a considerable portion of global arable land and has steadily increased during the 21st century. In the European Union, the growing of oil crops covers approximately 17% of arable land but the region also relies heavily on imports, particularly of palm oil and sunflower seed oil. So far, there are only few measurement-based estimates of the greenhouse gas budgets of agricultural systems, including the growing of vegetable oil crops. In this study, we evaluate and compare the global warming potential of cultivating four commonly used vegetable oils. Two of the oils, palm oil and soybean oil, are largely imported to the EU while the other two, olive oil and rapeseed oil are largely produced within the region. We use a comprehensive measurement-based Life Cycle Analysis (LCA) framework, combining the traditional LCA (using OpenLCA software and data from Ecoinvent database) with detailed greenhouse gas flux measurements of carbon dioxide (CO₂), methane (CH₄) and nitrous oxide (N₂O) from existing agricultural fields. We selected existing measurement sites in Indonesia for palm oil, Spain for olive oil, Argentina for soybean oil and Germany for rapeseed oil. Measurements of ecosystem CO₂ fluxes were done using eddy covariance while chamber methods were used for N₂O and CH₄ fluxes. This approach allows us to provide a detailed assessment of the emissions from the cultivation, including all the inputs and field emissions, to the production of these oils. These results contribute to understanding the climatic impacts of vegetable oil production, providing valuable insights for policy-making, agricultural management, and consumer choices aiming at mitigating the environmental footprint of agriculture, both from the production and consumer’s point of view.

How to cite: Tyystjärvi, V., Meijide, A., de la Rua, C., Aranda-Barranco, S., and Sánchez-Cañete, E. P.: Climatic impacts of different vegetable oils: A measurement-based life cycle analysis, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11875, https://doi.org/10.5194/egusphere-egu25-11875, 2025.