Marine ecosystems are becoming increasingly vulnerable to cumulative anthropogenic effects and pressures. Therefore, various methodological approaches and tools have been designed to apply cumulative impact appraisal schemes and better assess the dynamics and interactions among pressures affecting marine ecosystems. This study aims to apply the Spatial Cumulative Assessment of Impact Risk for Management (SCAIRM) tool for the Black Sea coastal waters considering human activities, pressures, and effects on different ecosystem components coupled with one management scenario development for actual and new emerging sectors. According to the SCAIRM, the primary pressure on the marine ecosystem was identified as introducing or spreading non-indigenous species from shipping. Additionally, when considering cumulative impact, activities related to coastal defense and flood protection, particularly beach nourishment works, were found to have the highest impact. This is due to the cumulative scores associated with the physical loss from permanent alteration or removal of seabed substrates, and temporary or reversible physical disturbances to the seabed. The scenario development indicated that after shipping, oil and gas exploitation is anticipated to become the second-highest risk sector for additional impact in the Romanian Black Sea. Additionally, the increased military activities related to the war in Ukraine present escalating risks that must be considered in EBM strategies. The results assess the possible effects of human activities and the associated pressures to direct management toward achieving sustainability, biodiversity protection, and the marine ecosystem’s integrity.

This study aims to develop a methodology for identifying predominant pressures on the marine ecosystem, emphasizing the significance of examining these pressures and the necessity for management scenarios. The research focuses on how the Black Sea ecosystem responds to the combined effects of human pressures, climate change, and policies. An in-depth analysis was conducted on environmental pressures affecting the Romanian Black Sea, highlighting dominant pressures such as physical habitat loss, hydrocarbon introduction, and non-indigenous species invasion. The research employs a novel methodological approach to assess the implications of these pressures under different Shared Socioeconomic Pathways (SSPs): SSP1 “Taking the Green Road”, SSP2 “Middle of the Road”, and SSP5 “Taking the Highway”. The findings reveal a complex interplay between economic development and environmental conservation, with each pathway presenting distinct outcomes for marine ecosystems. Recent developments, including beach rehabilitation, maritime transport, and oil and gas exploitation, have overshadowed traditional pressures such as nutrient introduction and fishing. The study identifies the increasing vulnerability of critical habitats to anthropogenic pressures, with the rehabilitation of these ecosystems remaining challenging even under reduced pressures. The results underscore the need for adaptive management strategies to enhance the Black Sea ecosystem’s sustainability and resilience. The study’s insights are important for developing management strategies that address ongoing environmental challenges. This research provides knowledge for policymakers and stakeholders involved in marine management and conservation efforts in the Black Sea region, emphasizing the importance of adaptive strategies to mitigate the adverse effects of human activities and climate change on marine ecosystems.

Mariculture offers enormous potential for providing sustainable food, playing a key role in achieving nutrition security, employment, and Blue Growth. This is particularly true in geographical areas where the dependence of local economies on fishery products is high and yet access to sustainable landings is hindered by environmental drawbacks. One such area is represented by the Black Sea, which offers different degrees of suitability for aquaculture development. While the southern and eastern shores are sheltered enough to allow for the development of large aquaculture activities, the north-western shoreline is characterized by wide environmental fluctuations and the strong influence of the Danube. This study aimed at investigating the suitability of a selected area of the Romanian coast (Mangalia) for finfish cage farming by adapting an internationally endorsed methodology for determining its Degree of Compatibility (DC). The development and expansion of finfish aquaculture depends on the availability of space, so designating Allocated Zones for Aquaculture (AZAs) is essential. The result obtained (DC = 80) indicates that the Mangalia area is suitable for finfish aquaculture activities: there is no major interference with other uses of the maritime space, no conflicts with nature conservation, and the environmental conditions are appropriate for fish culture in floating cages. The novel information provided by this study can be the building block for authorities to settle the governance gap that has so far impeded the development of marine aquaculture in Romania. At a larger scale, this study can serve as a good practice example at the regional Black Sea level.

Coastal erosion poses a significant risk to the Romanian Black Sea coast, a region characterized by the interaction of natural geomorphological processes and anthropogenic pressures. The research focuses on developing a tool to quantify the cumulative impact of hydro-geo-morphological factors and to assess the vulnerability of the coastal zone to these influences. The approach involves adapting the Coastal Vulnerability Index (CVI)—previously applied in various methodologies—to the specific characteristics of this semi-enclosed basin, which included the exclusion of the tidal range variable due to the Black Sea’s negligible tidal amplitude. The selection of key variables, including coastal geology and geomorphology, shoreline change rates, coastal slope, sea level, and wave regime, was conducted with consideration for the specific characteristics of the Romanian coastal zone. By classifying these variables on a semi-quantitative scale and integrating them into a CVI, the study identifies and maps areas of high vulnerability. The analysis, based on a 1 × 1 km grid resolution, identified sectors of very high vulnerability in the northern Danube Delta unit, particularly along the coastlines of South Sulina–Câşla Vădanei, Sahalin, and Periboina-Edighiol-Vadu. These findings are validated through a comparison with long-term, multidecadal shoreline evolution data, confirming the model’s predictive accuracy. While the 1 × 1 km grid is effective for a macro-scale assessment, the study highlights the need for a finer resolution (e.g., 100 × 100 m) for detailed analysis in the southern region, due to localized geodynamic conditions and the significant influence of coastal infrastructure.

This study examines the hydro-sedimentological–radioecological controls governing the distribution of natural (K-40, Ra-226, Th-232) and anthropogenic (Cs-137) radionuclides in surface sediments of the western Black Sea shelf. Activity concentrations were determined by high-resolution gamma spectrometry, and radiological indices—including radium equivalent activity (Ra_eq), external hazard index (H_ex), and annual effective dose (AED)—were calculated to evaluate environmental safety. All indices remained well below internationally accepted thresholds, confirming the absence of radiological hazard in both coastal and offshore settings. Strong correlations between Ra-226 and Th-232 indicate dominant lithogenic control of natural radionuclides, whereas Cs-137 exhibits geochemical decoupling consistent with its behavior. A significant relationship between the fine-grained sediment fraction (<63 µm) and Cs-137 activity highlights the grain size effect, with offshore depositional zones acting as sediment-focusing areas where Cs-137 and excess Pb-210 co-accumulate under low-energy hydrodynamic conditions. Despite localized offshore enrichment, dose contribution analysis shows that natural radionuclides dominate the absorbed-dose budget, while Cs-137 contributes only marginally. Spatial predictive modeling using Artificial Neural Networks, validated under a Spatial Leave-One-Group-Out framework, yielded moderate generalization capacity (R² = 0.61 for Ra-226; R² = 0.41 for Cs-137), reflecting smoother spatial gradients of lithogenic radionuclides than heterogeneous radiocesium deposition. Furthermore, Machine Learning algorithms provided significant analytical value: a Random Forest (RF) model successfully classified environments (nearshore/shelf/depositional basin) based on distinct radionuclide signatures. At the same time, an optimized Artificial Neural Network (ANN-GA) enabled the nonlinear reconstruction of radiometric–granulometric patterns to identify local anomalies. The results show that radionuclide distributions are primarily structured by sediment provenance, grain size sorting, and hydrodynamic energy gradients rather than ongoing anthropogenic inputs.

Rapid assessment of coastal inundation along the Western Black Sea coast requires computationally efficient methods that can screen multiple compound storm scenarios while preserving a clear link to the controlling physical drivers. This study develops and evaluates an XBeach-informed machine-learning surrogate for coastal inundation and threshold-based flood-extent screening. The framework combines high-frequency sea-level observations from the Maritime Hydrographic Directorate monitoring network, Copernicus Marine wave and Black Sea physical products, ERA5 atmospheric forcing, Global Runoff Data Centre Danube discharge, bathymetric and coastal-elevation descriptors, and an intermediate cross-shore physical-response layer. The modelling dataset consists of 5,000 Monte Carlo forcing scenarios, 22 forcing and derived predictors, and a 10 × 10 spatial target grids, corresponding to 100 inundation-depth nodes per scenario. Four tree-based residual models, namely Random Forest, Gradient Boosting, Extra Trees, and Histogram Gradient Boosting, are combined using validation-derived weights. The conservative held-out node-level evaluation shows moderate quantitative skill for continuous inundation-depth prediction. The ensemble reaches R² = 0.409, RMSE = 1.181 m, MAE = 0.678 m, NSE = 0.409, KGE = 0.235, Pearson r = 0.914, and Spearman ρ = 0.923. In contrast, threshold-based flood-extent classification above the 0.30 m operational inundation threshold is substantially stronger, with F1 = 0.995, AUC-ROC = 0.9998, Matthews correlation coefficient = 0.989, and Cohen’s κ = 0.989. Split conformal prediction intervals provide near-nominal 90 % marginal coverage, with empirical coverage of 0.911, but the mean 90 % interval width is large, 3.25 m, indicating limited sharpness for local quantitative depth estimation. Extreme-event diagnostics show systematic underprediction of upper-tail inundation depths, with a mean bias of approximately −2.59 m for events above the 90th percentile. The present configuration is therefore most appropriate for rapid flood-extent screening, scenario ranking, and identification of cases where more detailed process-based simulations are required. It should not yet be interpreted as a stand-alone operational predictor of maximum inundation depth. The study demonstrates how in situ observations, Copernicus Marine products, physical-response modelling, machine-learning emulation, and uncertainty diagnostics can be combined into a transparent coastal-hazard screening workflow for the Western Black Sea coast.