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Drought is a significant challenge to semiarid Mediterranean grasslands, Increasing the accuracy of monitoring allows improving the conservation and management of these vital ecosystems. Meteorological drought is commonly monitored by the Standard Precipitation Index (SPI) or the Standard Precipitation Evapotranspiration Index (SPEI). On the other hand, agriculture drought is estimated by the Vegetation Health Index (VHI). This work aims to optimise the correlation between both drought types using the best transformation of VHI and the most appropriate time scale. Two drought-vulnerable Mediterranean grasslands were selected to evaluate the performance of the drought indexes. The SPI and the SPEI were calculated using data obtained from nearby weather stations. MODIS data were used to calculate the VHI. This index was standardised, naming it as SVHI. Our results revealed that SPEI was better correlated with VHI compared to SPI. In addition, SVHI obtained better results in the critical vegetation phases than VHI. Overall, SPEI and SVHI were the best correlated indexes. The quarterly scale showed stronger relationships than the monthly scale and the most correlated time frame were Mediterranean spring and autumn. This fact suggests that SPEI and SVHI could provide a plus point for increasing the precision of vegetation monitoring during these periods.

The structure and dynamics of the star-forming disk of the Small Magellanic Cloud (SMC) have long confounded us. The SMC is widely used as a prototype for galactic physics at low metallicity, and yet we fundamentally lack an understanding of the structure of its interstellar medium (ISM). In this work, we present a new model for the SMC by comparing the kinematics of young, massive stars with the structure of the ISM traced by high-resolution observations of neutral atomic hydrogen (H i) from the Galactic Australian Square Kilometre Array Pathfinder survey. Specifically, we identify thousands of young, massive stars with precise radial velocity constraints from the Gaia and APOGEE surveys and match these stars to the ISM structures in which they likely formed. By comparing the average dust extinction toward these stars, we find evidence that the SMC is composed of two structures with distinct stellar and gaseous chemical compositions. We construct a simple model that successfully reproduces the observations and shows that the ISM of the SMC is arranged into two superimposed, star-forming systems with similar gas mass separated by ∼5 kpc along the line of sight.

The Large Magellanic Cloud (LMC) and Small Magellanic Cloud (SMC) are the Milky Way’s nearest interacting galaxy pair, offering a unique laboratory for studying tidal effects on galactic disks. Despite extensive survey efforts, the 3D geometry of the Magellanic Clouds, particularly the putative warp of the LMC, remains poorly constrained due to incompleteness in their crowded centers and the low stellar density of their peripheries, which demand wide-field coverage. Using red clump (RC) stars as standard candles, corrected for age- and metallicity-dependent population effects with empirically calibrated color–magnitude relations and spatially resolved star formation histories, we construct the most detailed distance map of the Magellanic system to date. Based on ∼2.3 million RC stars from Gaia Data Release 3 combined with modern reddening maps, we measure median heliocentric distances of 50.62 ± 2.32 kpc for the LMC (to ∼23°) and 60.75 ± 2.85 kpc for the SMC (to ∼12°). The maps reveal substructures including the LMC Northern Arm, southern hooks, the Magellanic Bridge, and SMC peripheral overdensities, with refreshed distance estimates. Fitting the LMC disk within 7° yields a global inclination of i=25.°32±0.°10 and a line-of-nodes position angle of θ=142.°34±0.°21 . Most strikingly, we find the LMC periphery is warped azimuthally into a U-shaped structure reaching a vertical amplitude of ∼7 kpc at a radius of ∼15 kpc. In future work, we will perform detailed comparisons with live N-body simulations to assess possible formation scenarios for the LMC warp.

Elements with weak and blended spectral features in stellar spectra are challenging to measure and require specialized analysis methods to precisely measure their chemical abundances. In this work, we have created a catalog of approximately 120,000 giants with high signal-to-noise Apache Point Observatory Galactic Evolution Experiment (APOGEE) Data Release 17 (DR17) spectra, for which we explore weak and blended species to measure Na, P, S, V, Cu, Ce, and Nd abundances and 12C/13C isotopic ratios. We employ an updated version of the Brussels Automatic Code for Characterizing High-accuracy Spectra (BACCHUS) code to derive these abundances using the stellar parameters measured by APOGEE’s DR17 Stellar Parameters and Chemical Abundances Pipeline, quality flagging to identify suspect spectral lines, and a prescription for upper limits. Combined, these allow us to provide our BACCHUS Analysis of Weak Lines in APOGEE Spectra catalog of precise chemical abundances for these weak and blended species, which agrees well with the literature and improves upon APOGEE abundances for these elements, some of which are unable to be measured with APOGEE’s current, grid-based approach without computationally expensive expansions. This new catalog can be used alongside APOGEE and provides measurements for many scientific applications ranging from nuclear physics to Galactic chemical evolution and Milky Way population studies. To illustrate this we show some examples of uses for this catalog, such as showing that we observe stars with enhanced s-process abundances or that we can use the 12C/13C ratios to explore extra mixing along the red giant branch.

Heating and cooling (H&C) account for nearly half of the EU’s energy consumption, with significant potential for decarbonization through renewable energy sources (RES) integrated in district heating and cooling (DHC) systems. This study evaluates the environmental and social impacts of RES-powered DHC solutions implemented in three European small-scale demo sites (Bucharest, Luleå, Córdoba) under the Horizon 2020 WEDISTRICT project. Using the Life Cycle Assessment (LCA) and Social Life Cycle Assessment (S-LCA) methodologies, the research compares baseline fossil-based energy scenarios with post-implementation renewable scenarios. Results reveal substantial greenhouse gas emission reductions (up to 67%) and positive environmental trade-offs, though increased mineral and metal resource use and site-specific impacts on water and land use highlight important sustainability challenges. Social assessments demonstrate improvements in gender parity, local employment, and occupational safety, yet reveal persistent issues in wage equity, union representation, and inclusion of vulnerable populations. The findings emphasize that while renewable DHC systems offer significant climate benefits, social sustainability requires tailored local strategies and robust governance to avoid exacerbating inequalities. This integrated environmental-social perspective underscores the need for holistic policies that balance technical innovation with equitable social outcomes to ensure truly sustainable energy transitions.

This paper focuses on assessing the potential risks and strengths along the supply chain of a set of ten popular and precious metals associated with two solar energy technologies: concentrated solar power with thermal storage and photovoltaics with batteries. The Extended Multi-Regional Input–Output methodology is used to quantify the required extraction of the metals along the value chain. First, various metrics and indicators are explored to analyze the supply chain. Second, a framework of analysis is proposed to cover the main components of supply chain risks and strengths. Then, we compare the results from two perspectives: analysis of individual supply risk components and a combined index representing the strength of the value chain. The results show, in general, a better performance of the concentrated solar power supply chain in terms of resource availability and supplier diversity, but slightly worse scores in the resilience and governance components. The index reflects better overall performance for concentrated solar power. Among metals, platinum, silver, and tin play the leading role in the analyzed risks. The European deployment of renewables should be accompanied by measures to secure supply, such as cooperation agreements, and also foster the recovery of secondary materials, thereby maximizing intra-European resilience.

The dynamic of rangelands results from complex interactions between vegetation, soil, climate, and human activity. This scenario makes rangeland’s condition challenging to monitor, and degradation assessment should be carefully considered when studying grazing pressures. In the present work, we study the interaction of vegetation and soil moisture in semiarid rangelands using vegetation and soil moisture indices. We aim to study the feasibility of using soil moisture negative anomalies as a warning index for vegetation or agricultural drought. Two semiarid agricultural regions were selected in Spain for this study: Los Vélez (Almería) and Bajo Aragón (Teruel). MODIS images, with 250 m and 500 m spatial resolution, from 2002 to 2019, were acquired to calculate the Vegetation Condition Index (VCI) and the Water Condition Index (WCI) based on the Normalised Difference Vegetation Index (NDVI) and soil moisture component (W), respectively. The Optical Trapezoid Model (OPTRAM) estimated this latter W index. From them, the anomaly (Z-score) for each index was calculated, being ZVCI and ZWCI, respectively. The probability of coincidence of their negative anomalies was calculated every 10 days (10-day periods). The results show that for specific months, the ZWCI had a strong probability of informing in advance, where the negative ZVCI will decrease. Soil moisture content and vegetation indices show more similar dynamics in the months with lower temperatures (from autumn to spring). In these months, given the low temperatures, precipitation leads to vegetation growth. In the following months, water availability depends on evapotranspiration and vegetation type as the temperature rises and the precipitation falls. The stronger relationship between vegetation and precipitation from autumn to the beginning of spring is reflected in the feasibility of ZWCI to aid the prediction of ZVCI. During these months, using ZWCI as a warning index is possible for both areas studied. Notably, November to the beginning of February showed an average increase of 20–30% in the predictability of vegetation anomalies, knowing moisture soil anomalies four lags in advance. We found other periods of relevant increment in the predictability, such as March and April for Los Vélez, and from July to September for Bajo Aragón.

Sustainable Urban Drainage Systems (SUDS) represent a paradigm shift in stormwater management, offering holistic solutions to urban water challenges. This review examines SUDS principles, design strategies, effectiveness and barriers to implementation. SUDS prioritize infiltration and mimic natural hydrological processes to reduce flood risk, improve water quality and support ecosystems in urban environments. Effective SUDS design integrates different components such as permeable pavements, green roofs, and rain gardens, tailored to the local context. Evidence suggests that well-designed SUDS can mitigate peak flows, reduce runoff volumes, and purify water. However, barriers to widespread adoption include lack of awareness, upfront costs, and regulatory complexity. Overcoming these will require collaborative stakeholder action to prioritize education, policy support, and funding opportunities. Future research should focus on optimizing SUDS design, assessing long-term performance, and quantifying socio-economic benefits. By integrating SUDS into urban landscapes, cities can strengthen hydrological resilience, promote sustainability, and enrich urban life.

The energy sector is essential in the transition to a more sustainable future, and renewable energies will play a key role in achieving this. It is also a sector in which the circular economy presents an opportunity for the utilisation of other resources and residual energy flows. This study examines the environmental and social performance of innovative energy technologies (which contribute to the circularity of resources) implemented in a demonstrator site in Luleå (Sweden). The demo-site collected excess heat from a data centre to cogenerate energy, combining the waste heat with fuel cells that use biogas derived from waste, meeting part of its electrical demand and supplying thermal energy to an existing district heating network. Following a cradle-to-gate approach, an environmental and a social life cycle assessment were developed to compare two scenarios: a baseline scenario reflecting current energy supply methods and the WEDISTRICT scenario, which considers the application of different renewable and circular technologies. The findings indicate that transitioning to renewable energy sources significantly reduces environmental impacts in seven of the eight assessed impact categories. Specifically, the study showed a 48% reduction in climate change impact per kWh generated. Additionally, the WEDISTRICT scenario, accounting for avoided burdens, prevented 0.21 kg CO2 eq per kWh auto-consumed. From the social perspective, the WEDISTRICT scenario demonstrated improvement in employment conditions within the worker and local community categories, product satisfaction within the society category, and fair competition within the value chain category. Projects like WEDISTRICT demonstrate the circularity options of the energy sector, the utilisation of resources and residual energy flows, and that these lead to environmental and social improvements throughout the entire life cycle, not just during the operation phase.

Detailed modelling of water dynamics at the catchment is of paramount importance for the optimal management and allocation of water resources. The main objective of this work is to present a set of QGIS-based routines for processing easily available geographical information to deliver inputs for integration into hydrological models developed in the Python environment. We present QGIS processes that deliver open format exchangeable files with physical information required for hydrological modelling, allowing a better tailoring of hydrological modelling tasks compared to other blinded existing models. We present the general framework by processing spatial information and running a set of hydrological models in different cases studies in the Spanish Ebro River basin, proving the utility of the proposed method for applying complex and tailored hydrological simulations.