In the absence of an internationally coordinated management strategy, continued exploitation of the North Sea is expected to exacerbate underwater radiated noise (URN), heightening risks of adverse impacts on marine life. Identifying indicator species and their habitats is a fundamental step in the EU framework for setting a scientifically grounded underwater noise limit value (UNLV). While past research has primarily emphasized marine mammals, there is an increasing effort to highlight that the impacts of URN extend to fishes and invertebrates. To support indicator species selection in the North Sea for URN risk assessment, a trait-based vulnerability scoring system for marine mammals, fishes and invertebrates was developed. Each scoring system evaluates multiple attributes related to a species' capacity to detect and produce sound, as well as the documented impacts from both impulsive and continuous anthropogenic noise, and highlights species of particular concern and socio-ecological significance. Five potential indicator species were identified from each of the three taxonomic groups (marine mammals, fishes and invertebrates) for URN risk assessment. The proposed vulnerability scoring system serves as an adaptive framework, open to iterative refinement as bioacoustics knowledge advances. Although data gaps persist, the establishment of regional UNLV to safeguard vulnerable species should not be delayed. By linking URN exposure with key habitats of identified indicator species, this approach facilitates an ecosystem-based management of URN in the North Sea and provides a transferable framework for other regions.
Legumes are among the most important plants capable of biological nitrogen fixation. However, there is a significant knowledge gap regarding the specifics of cultivating legumes in hydroponic systems under controlled environment conditions, particularly nitrogen metabolism at different growth stages, which this study addressed. Chickpeas, faba beans, lentils, soybeans, and sugar peas were cultivated in deep-water hydroponics without rhizobia, with a nutrient solution as the nitrogen source. The legumes displayed significant variations in growth patterns and nitrogen dynamics. Among them, soybeans had the longest growth cycle, characterised by extended vegetative and early reproductive phases, while sugar peas developed the fastest. In all species, nitrate was the dominant form of nitrogen found in the roots, stems, and leaves, followed by ammonium (NH3-N) and nitrite (NO2-). The levels of NH3-N varied among species, peaking early in faba beans and later in chickpeas. NO2- concentrations were low and decreased with development. The activities of nitrate reductase and nitrite reductase also varied across species, plant organs, and growth stages. The highest enzyme activity was consistently observed in the leaves. Notably, peas exhibited high enzyme activity across all organs, while the leaves of soybeans showed the highest activity in the studied legumes.
Safe-and-Sustainable-by-Design (SSbD) aims to integrate functionality with safety and sustainability in an iterative and lifecycle thinking approach, starting already at the design stage of the innovation process. This proactive approach ensures that chemicals, materials, and other products are produced and used without being a threat to human and planetary health. In the authors’ understanding, SSbD should ideally start with defining the function or service that is needed and how it can be delivered in the most sustainable way. This should include using the least amount of chemicals or even no chemicals when non-chemical or non-material alternatives are available (systems thinking). This perspective explores where SSbD fits into the bigger picture with respect to already existing chemistry frameworks such as Green Chemistry, Circular Chemistry, Chemistry within a Circular Economy, and Sustainable Chemistry. Analysing the design principles, assessment levels, and key aspects shows that SSbD is strongly interlinked with these chemistry concepts. Greener synthesis (Green Chemistry) and circular value chains (Circular Chemistry and Chemistry within a Circular Economy) are important aspects and objectives of SSbD, while the closed link and highest similarity is to Sustainable Chemistry as both operate on a system level and start with the function/service that needs to be provided. This in mind, the authors consider SSbD as an enabler of Sustainable Chemistry to accelerate the transition towards sustainability from the design stage, thereby moving the chemistry sector towards more sustainable practices, contributing to achieve the United Nations Sustainable Development Goals (SDGs), and ensuring humanity operates within the planetary boundaries.
Study region: Arabian Peninsula, Middle East. Study focus: The Arabian Peninsula (AP) faces increasing droughts due to a warming climate, threatening water security, ecosystems, socio-economic stability, and livelihoods. This study analyzes drought characteristics across four AP zones using a multi-index approach integrating the Standardized Precipitation Index (SPI), Standardized Precipitation-Evapotranspiration Index (SPEI), and Evaporative Demand Drought Index (EDDI). Drought frequency, duration, and severity were assessed at 3-, 6-, and 12-month timescales using ERA5 reanalysis data (1975-2024). Long-term trends were quantified with the Modified Mann-Kendall test and Sen's slope. The Innovative Trend Analysis (ITA) distinguished trends in extreme dry and wet periods. A SHAP-based XGBoost model identified dominant meteorological drivers of drought severity. New hydrological insights for the region: Major droughts occurred in 1983-1984, 1999-2002, 2007-2009, 2014-2015, and 2021-2023, with the Southeast and Southwest zones most droughtprone. Across all timescales, SPEI and EDDI indicated greater intensity, earlier onset, and persistence than SPI, underscoring the role of rising temperature and evaporative demand. SHAP analysis revealed dewpoint temperature, precipitation, and maximum temperature as key drivers, while wind speed had minor influence. ITA revealed asymmetric shifts in drought distributions, confirming intensification of dry extremes. These findings emphasize the need for multi-index drought monitoring and region-specific adaptation strategies to strengthen climate resilience in arid regions.
The hazard identification of chemicals is a key step of the 'Safe and Sustainable by Design' (SSbD) framework introduced by the European Commission, aiming to eliminate hazardous substances early in innovation. In this context, in silico methods such as (Quantitative) Structure-Activity Relationship ((Q)SAR) models offer rapid, cost-effective, and animal-free alternatives for early-stage hazard screening. The Partnership for the Assessment of Risks from Chemicals (PARC) is developing a toolbox to facilitate SSbD assessments containing numerous (Q)SAR models. Challenges, however, exist in using and combining multiple in silico tools. Here, we developed a workflow to assess chemical hazards using multiple in silico tools within the PARC toolbox. The workflow consists of three phases: 1) the preparation stage, 2) running the models, and 3) the evaluation stage. To demonstrate the approach, we applied it to a case study comparing Bisphenol A, Isosorbide, and Bisphenol AP. Tools from the PARC toolbox were screened for relevance, transparency, and open access availability. Only models aligned with SSbD required endpoints and adequately documented via (Q)SAR Model Reporting Formats were retained. The properties assessed in this study cover carcinogenicity, germ cell mutagenicity, reproductive toxicity, endocrine disruption, persistence, bioaccumulation, and aquatic toxicity. Predictions were filtered using applicability domain criteria and reliability scores. Next, three strategies were applied for integrating different model outputs. Model agreement varied across endpoints and integration methods. This emphasizes the possibility of different SSbD assessment outcomes and thus the need for transparent documentation of the chosen strategy and explicit handling of uncertainty. Our study demonstrates how multiple models can systematically and transparently be integrated via the developed workflow. Key areas for improvement are to refine integration strategies, harmonize the definition and communication of applicability domains across tools, expand in silico coverage for currently underrepresented endpoints, and to develop approaches to consider data gaps in SSbD assessments.
