• Energy Research
• 2025-2025close
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The severity of drought is predicted to increase across Europe due to climate change. Droughts can substantially impact terrestrial nitrogen (N) cycling and the corresponding microbial communities. Here, we investigated how ammonia-oxidizing bacteria (AOB), archaea (AOA), and complete ammonia oxidizers (comammox) as well as inorganic N pools and N2O fluxes respond to simulated drought under different cropping systems. A rain-out shelter experiment was conducted as part of a long-term field experiment comparing cropping systems that differed mainly in fertilization strategy (organic, mineral, or mixed mineral and organic) and plant protection management (biodynamic versus conventional pesticide use). We found that the effect of drought varied depending on the specific ammonia-oxidizing (AO) groups and the type of cropping system. Drought had the greatest impact on the structure of the AOA community compared to the other AO groups. The abundance of ammonia oxidizers was also affected by drought, with comammox clade B exhibiting the highest sensitivity. Additionally, drought had, overall, a stronger impact on the AO community structure in the biodynamic cropping system than in the mixed and mineral-fertilized conventional systems. The responses of ammonia-oxidizing communities to drought were comparable between bulk soil and rhizosphere. We observed a significant increase in NH4+ and NO3− pools during the drought period, which then decreased after rewetting, indicating a strong resilience. We further found that drought altered the complex relationships between AO communities and mineral N pools, as well as N2O fluxes. These results highlight the importance of agricultural management practices in influencing the response of nitrogen cycling guilds and their processes to drought. Soil Biology and Biochemistry, 201 ISSN:0038-0717 ISSN:1879-3428

The importance of climate change for driving adverse climate impacts has motivated substantial effort to understand the rate and magnitude of regional climate change in different parts of the world. However, despite decades of research, there is substantial uncertainty in the time remaining until specific regional temperature thresholds are reached, with climate models often disagreeing both on the warming that has occurred to-date, as well as the warming that might be experienced in the next few decades. Here, we adapt a recent machine learning approach to train a convolutional neural network to predict the time (and its uncertainty) until different regional warming thresholds are reached based on the current state of the climate system. In addition to predicting regional rather than global warming thresholds, we include a transfer learning step in which the climate-model-trained network is fine-tuned with limited observations, which further improves predictions of the real world. Using observed 2023 temperature anomalies to define the current climate state, our method yields a central estimate of 2040 or earlier for reaching the 1.5 degrees C threshold for all regions where transfer learning is possible, and a central estimate of 2040 or earlier for reaching the 2.0 degrees C threshold for 31 out of 34 regions. For 3.0 degrees C, 26 degrees C out of 34 regions are predicted to reach the threshold by 2060. Our results highlight the power of transfer learning as a tool to combine a suite of climate model projections with observations to produce constrained predictions of future temperatures based on the current climate. Environmental Research Letters, 20 (1) ISSN:1748-9326 ISSN:1748-9318

This paper investigates the use of deep multi-agent reinforcement learning (MARL) for the coordination of residential energy flexibility. Particularly, we focus on achieving cooperation between homes in a way that is fully privacy-preserving, scalable, and that allows for the management of distribution network voltage constraints. Previous work demonstrated that MARL-based distributed control can be achieved with no sharing of personal data required during execution. However, previous cooperative MARL-based approaches impose an ever greater training computational burden as the size of the system increases, limiting scalability. Moreover, they do not manage their impact on distribution network constraints. We therefore adopt a deep multi-agent actor-critic method that uses a centralised but factored critic to rehearse coordination ahead of execution, such that homes can successfully cooperate at scale, with only first-order growth in computational time as the system size increases. Training times are thus 34 times shorter than with a previous state-of-the-art reinforcement learning approach without the factored critic for 30 homes. Moreover, experiments show that the cooperation of agents allows for a decrease of 47.2% in the likelihood of under-voltages. The results indicate that there is significant potential value for management of energy user bills, battery depreciation, and distribution network voltage management, with minimal information and communication infrastructure requirements, no interference with daily activities, and no sharing of personal data. Applied Energy, 377, Part A ISSN:0306-2619 ISSN:1872-9118

Earth materials are subsoils used in construction due to their natural cementing properties. These properties originates from its clay fraction, which becomes cohesive during drying. Unlike common cement, earth materials are recyclable and have no CO2 emission apart from manufacturing. Unfortunately, earth materials containing the abundant clay mineral smectite exhibit large swelling and shrinkage strains. Such earth materials are considered unsuitable for construction unless a stabiliser is added, which is commonly Portland cement or quicklime. This study explored the use of MgO-based cementitious Binder (MB) as alternative with a focus on the mineralogical effect of MB on smectite during hydration. A series of MB/smectite blends and MB components/smectite was cured up to six months to investigate the mineralogical changes and the formation of magnesium (alumino) silicate hydrate. The results showed that MB transformed smectite into Mg-hydroxy-interlayered smectite (Mg-HIS) within hours. The reason is the dissolution of MgO, a main constituent of MB. The dissolved Mg precipitates as Mg-hydroxy in the interlayer and transforms the smectite to Mg-HIS in this process. This is causing a pH increase and may prevent a complete HIS formation as the MgO dissolution mechanism will change once the pH is above the point-of-zero charge of MgO. An advantage of the smectite to Mg-HIS transformation is the strongly reduced the swelling/shrinkage properties of the clay. This suggests that adding MB to smectite could be a superior binding approach compared to quicklime, which primarily causes clay particle flocculation. Applied Clay Science, 265 ISSN:0169-1317

Decentralized multi-energy systems (MESs) are a key element of a future low-carbon energy supply. Here, we address the crucial role of grid-connected and off-grid MESs in achieving a low-carbon future, particularly relevant for regions like the Mediterranean with high renewable energy potential and carbon-intensive grid networks, using a mixed integer linear program for optimal economic and environmental MES design considering location-specific regulations. The results reveal that substantial cost (up to 30%, potentially saving 1.6 million) and greenhouse gas (GHG) emission reductions can be reached in Mediterranean regions with sufficient solar and wind energy resources currently relying on fossil fuel-based generators. However, our case study shows that the actual cost and emission reductions are most likely limited due to location-specific regulations (limiting cost savings to 0.8 million), especially those that constrain solar photovoltaic and onshore wind. Off-grid energy systems might be suitable decarbonization options in Mediterranean regions, to avoid absorbing current GHG-intensive power from the local power grid, under marginal cost increase (15%) compared to grid-connected cost optimization. However, off-grid MESs require substantial upfront investments and exhibit some environmental trade-offs, especially on material utilization, which could be overcome by balanced autonomy. Overall, truly sustainable and secure decentralized energy systems can only be reached by considering life cycle environmental impacts, social acceptance, and regulations during the design phase. Applied Energy, 377 ISSN:0306-2619 ISSN:1872-9118