We quantified excess N2 accumulation below the halocline of the Baltic Proper using in situ N2/Ar measurements combined with N2/Ar estimates derived from the three-dimensional ERGOM–MOM biogeochemical model. The observed temporal increase in excess N2 was subsequently converted to nitrogen loss. The analysis focused on the post-2014 Major Baltic Inflow period, when deep-water ventilation effects had largely subsided and stratification with progressive oxygen depletion was re-established. Both observations and model simulations showed increasing excess N2 below the halocline, particularly in the Eastern Gotland Basin (EGB). Observation-based estimates of nitrogen loss amounted to approximately 80.8 ± 22.7 kt N yr−1 in the EGB, ∼15.6 ± 7.8 kt N yr−1 in the Bornholm Basin (BB), and ∼9.3 ± 4.1 kt N yr−1 in the Gdańsk Basin (GB). Model-derived estimates were consistently lower, but basin-specific comparisons revealed no significant differences between observational and temporally matched model-derived excess N2 accumulation trends. The obtained values of net fixed nitrogen loss fall within the lower range of published Baltic Sea estimates, likely because the N2/Ar approach reflects integrated net accumulation of dissolved N2 rather than gross instantaneous denitrification rates. These results demonstrate that deep-water excess N2 accumulation provides an integrative basis for estimating first-order net fixed nitrogen loss in stratified marine systems such as the Baltic Sea.
Excess dinitrogen (ΔN2) is the net accumulation of N2 produced by nitrate-reducing processes in the water column and sediments of oxygen-deficient marine systems. Therefore, biological production and physical processes shape its spatial distribution. This study investigates ΔN2 distribution below the halocline in the Baltic Sea using a coupled biogeochemical model evaluated against observations from the Bornholm, Gdańsk, and Gotland Deeps during 2020–2021. Vertical distributions of temperature, salinity, oxygen (O2), nutrients, N2/Ar ratios, and ΔN2 were compared to assess model performance and identify controls on N2 production. A persistent spatial gradient in ΔN2 was observed, with highest concentrations in the Gotland Basin, intermediate levels in the Gdańsk Basin, and lowest values in the Bornholm Basin. These differences correspond to variations in stratification, ventilation, and organic matter (OM) accumulation. Seasonal variability was strongest in the Gdańsk Basin, where elevated winter ΔN2 suggests enhanced nitrogen-loss processes supported by OM export and mixing-driven nutrient redistribution. In contrast, the Gotland Basin exhibited relatively stable, persistently reducing conditions, while the Bornholm Basin showed strong interannual variability related to episodic North Sea inflows. The weak relationship between ΔN2 and modeled denitrification rates (ranging from �0.0010 to 0.0200 𝜇mol kg−1 day−1) indicates that ΔN2 should not be interpreted as a direct proxy for pelagic denitrification. Rather, it reflects the cumulative effects of both pelagic and benthic denitrification, together with physical transport processes. By comparison, denitrification rates were more strongly associated with particulate organic carbon (POC) availability. The reported ΔN2 patterns are representative of the investigated post-inflow period rather than a long-term Baltic Sea baseline.
The relative contributions of tidal, wind, and density forcing to the general circulation of the Gulf of Oman are investigated using a high-resolution three-dimensional hydrodynamic model. Currents were simulated for the year 2012 under spatially and temporally varying boundary conditions, including tidal elevation, atmospheric forcing, and density stratification derived from TPXO8, ERA5, and HYCOM datasets, respectively. Results reveal a seasonally reversing circulation system characterized by subtropical gyres with positive vorticity during the cold season and negative vorticity during the warm season. Maximum current velocities reach approximately 0.5 m s−1 under tidal forcing and increase to about 0.6 m s−1 when wind effects are included. Analysis of depth-averaged kinetic energy indicates that tidal forcing establishes the dominant energetic framework of the basin. Wind forcing contributes approximately 2.50% to the basin-scale kinetic energy, primarily during the Southwest monsoon, while density-driven processes account for about 2.18%, with a more pronounced influence during winter conditions. Although density effects do not significantly improve statistical model performance metrics, they play an important role in shaping vertical stratification and subsurface circulation. Overall, the results highlight a tide-dominated system in which wind modulates seasonal variability and density forcing contributes to vertical structure and basin-scale energetics
The applicability of TEOS-10 to marginal and enclosed seas with chemically non-standard waters has not been extensively evaluated. In this study, available experimental density data for Caspian Sea water were used to develop a refined regional density–salinity–temperature formulation. Because direct density measurements were unavailable for the present samples, their densities were calculated using the refined formulation. These density estimates, together with new conductivity-based salinity observations from the southern Caspian Sea, were used to invert the TEOS-10 equation of state and estimate Absolute Salinity (SA), Reference Salinity (SR), and Salinity Anomaly (𝛿SA). The resulting SA values ranged from 14.70 to 15.24 g kg−1, whereas SR derived from Practical Salinity (SP) was lower, yielding positive 𝛿SA values of 2.35–2.93 g kg−1. The anomaly was effectively invariant over 5–20°C but varied among stations, indicating that conductivity-derived SP alone does not fully represent the density-equivalent salinity of southern Caspian Sea water. The positive anomalies are consistent with the non-oceanic ionic composition of the Caspian Sea, although their magnitude may partly reflect uncertainty in the regional density formulation, particularly its extrapolation beyond the salinity range of the historical density dataset. These results show that TEOS-10 can be used to identify composition-related differences between enclosed-basin waters and Reference Composition seawater.
Coastal zones face increasing pressure from climate change and socioeconomic development, requiring robust, spatially explicit vulnerability assessments. This study develops an integrated Fuzzy Composite Coastal Vulnerability Index (FCVI) to evaluate spatial patterns of vulnerability along the Makran coast (Chabahar–Konarak, Iran) under three climate scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5). The framework integrates physical exposure from the InVEST Coastal Vulnerability model (version 3.19.0) with socioeconomic sensitivity and adaptive capacity, standardized using fuzzy logic in a GIS environment. The results reveal pronounced scenario-dependent shifts in both the extent and spatial configuration of vulnerability classes. The area classified as low vulnerability decreases from 1,315,095 ha under SSP1-2.6 to 1,096,947 ha under SSP2-4.5, while high-vulnerability areas increase from 396,095 ha to 498,223 ha. Under the high-emission SSP5-8.5 scenario, high-vulnerability areas expand further to 521,574 ha, accompanied by a marked reduction in moderate-vulnerability areas, from 616,608 ha to 420,038 ha. Beyond these quantitative changes, the results indicate a clear spatial reorganization of vulnerability patterns. Under lower-emission scenarios, high-vulnerability areas remain relatively fragmented and localized, whereas under SSP5-8.5, they become more continuous and spatially connected. This transition suggests a nonlinear response, whereby increasing climatic pressure may induce structural changes in the spatial distribution of vulnerability rather than a simple linear increase. The proposed framework provides a consistent and transferable approach for identifying emerging vulnerability hotspots and supporting scenario-based coastal planning, particularly in data-scarce regions.
