Search Results (297)

This study examines how the newly established United States pursued economic development through diplomatic and commercial initiatives with the Ottoman Empire, navigating regional powers and the era’s political-economic conditions. It analyzes using American archival sources how America endeavored to establish commercial and diplomatic relations with the Ottoman Empire in the Mediterranean and Black Sea regions, which it viewed as critical markets in the late 18th and early 19th centuries, before signing any formal agreement. The research tracks how these early efforts laid foundations for what would become one of the world’s largest economies. The study analyzes America’s diplomatic efforts to secure an agreement with the Ottoman Empire prior to the 7 May 1830 trade agreement—which laid the foundation for bilateral relations—alongside the reactions of regional powers, the prevailing conditions of the period, and the Ottoman administration’s reluctance due to various factors, based on U.S. archival sources that, to the best of our knowledge, have not previously been utilized in existing studies. Full article

The polyvalent nature of water is one often explored in fiction by Caribbean writers, and this paper will consider the ways that the representations of mermaids act as an extension of this exploration. Mermaids are central to a number of folk traditions across the Caribbean region and its diaspora. On islands, including Trinidad, Martinique, Carriacou, and Haiti, with names such as Fairymaid, Mama Glo, and La Siren, mermaids are often regarded as mothers and protectresses of both the sea and the creatures within it. This paper will analyse the representation of the mermaid in Monique Roffey’s The Mermaid of Black Conch (2020) and consider how the novel utilises the mermaid and an aquatic poetics to explore Kamau Brathwaite’s conceptualisation of a submarine unity for the Caribbean. Full article

Increasing drought conditions at the global level have created concerns about the decrease in water resources. This situation has made the correct planning of irrigation applications the most important situation. Irrigation management in future periods is possible with the correct determination of the reference evapotranspiration (ET₀) trend. In the current situation, the trend is usually determined using one or two methods. Failure to conduct a detailed trend analysis results in incorrect irrigation management. With the new approach presented in the research, all of the Mann–Kendall (MK), innovative trend analysis (ITA), Sen’s slope (SS) and Spearman’s rho (SR) tests were used, and the common results of the four tests, namely increase, decrease, and no trend, were taken into account. The ET₀ values calculated in different approaches were focused on temporal and spatial analysis for the future irrigation management of Türkiye with the Blaney–Criddle (BC), Turc (TR), and Coutagne (CT) methods. The future period forecast was made using four different trend analyses with geographical information system (GIS) based spatial applications using 12-month ET₀ data calculated from 59 years of data between 1965 and 2023. Statistical analysis was performed to reveal the relationship between ET₀ calculation methods. The findings showed that although there is a general increasing trend in ET₀ values in the region, this situation is more pronounced, especially in the provinces in the western and central regions. The research results improve the determination of plant water needs for future periods in terms of irrigation management. This new approach, which determines ET₀ trend analysis in the Black Sea region, can be used in regional, national, and international studies by supporting different calculations to be made in order to plan future water management correctly, to reduce the concern of decreasing water resources in drought conditions, and to obtain comprehensive data in order to provide appropriate irrigation. Full article

Growing concern over anthropogenic underwater noise, highlighted by initiatives like the Marine Strategy Framework Directive (MSFD) and its Technical Group on Underwater Noise (TG Noise), emphasizes regions like the Western Black Sea, where increasing activities threaten marine habitats. This region is experiencing rapid growth in maritime traffic and resource exploitation, which is intensifying concerns over the noise impacts on its unique marine habitats. While machine learning offers promising solutions, a research gap persists in comprehensively evaluating diverse ML models within an integrated framework for complex underwater acoustic data, particularly concerning real-world data limitations like class imbalance. This paper addresses this by presenting a multi-faceted framework using passive acoustic monitoring (PAM) data from fixed locations (50–100 m depth). Acoustic data are processed using advanced signal processing (broadband Sound Pressure Level (SPL), Power Spectral Density (PSD)) for feature extraction (Mel-spectrograms for deep learning; PSD statistical moments for classical/unsupervised ML). The framework evaluates Convolutional Neural Networks (CNNs), Random Forest, and Support Vector Machines (SVMs) for noise event classification, alongside Gaussian Mixture Models (GMMs) for anomaly detection. Our results demonstrate that the CNN achieved the highest classification accuracy of 0.9359, significantly outperforming Random Forest (0.8494) and SVM (0.8397) on the test dataset. These findings emphasize the capability of deep learning in automatically extracting discriminative features, highlighting its potential for enhanced automated underwater acoustic monitoring. Full article

The purpose of this study was to evaluate the energy and environmental potential of waste biomass in the form of hazelnut shells from selected Turkish varieties of Corylus avellana L. Eight commercial varieties (Çakıldak, Foşa, İnce Kara, Kalın Kara, Palaz, Tombul, Yassı Badem and Yuvarlak Badem) grown in different regions of the Black Sea coast of Turkey were analyzed. The scope of this study included whole nut and shell weight determination, technical and elemental analysis, higher heating value (HHV) and lower net heating value (LHV), as well as emission factors (CO, CO₂, NO_x, SO₂, dust) and flue gas composition based on stoichiometric calculations. The results showed a significant effect of varietal characteristics on all analyzed parameters. The share of shell in the total weight of the nut ranged from 43.5% (Tombul) to 55.3% (İnce Kara). HHV values ranged from 18.37 to 19.20 MJ·kg⁻¹, and LHV from 17.05 to 17.90 MJ·kg⁻¹. The İnce Kara and Yassı Badem varieties showed the most favorable energy properties. Elemental analysis confirmed a low nitrogen and sulfur content, which translated into low NO_x and SO₂ emissions. NO_x emissions were lowest for the Tombul variety (1.43 kg·Mg⁻¹), and SO₂ emissions were close to zero in each variety. The results confirm that Turkish hazelnut shells are a valuable energy resource and can be used as solid fuel or supplementary biomass. In particular, the İnce Kara variety was identified as the most promising due to its high shell weight, very good fuel properties, and high yield potential. This study underscores the importance of selecting the right variety to optimize agricultural waste utilization strategies within a circular economy. Full article

Global mean sea level has been rising steadily since the early 1990s, yet regional sea level changes exhibit complex spatial variability that frequently contrasts with global trends. Investigating sea level variations in semi-enclosed basins such as the Black Sea is crucial for elucidating regional responses to climate change and characterizing its unique spatiotemporal evolution patterns. In this study, we employ satellite altimetry (SA) data to study sea level changes, spatial variability, and seasonal patterns in the Black Sea over eight distinct time periods with temporally correlated noise, and our results show good consistency with existing studies. The results show that sea level changes are non-linear over time and exhibit spatial variability in the Black Sea. The estimated sea level trend fluctuates over brief intervals, but extended time series provide reduced uncertainty in the trend and more precise estimation over a 28-year time series. The annual amplitude and phase derived from virtual altimetry data (1993–2020) exhibit a distinct seasonal pattern, with peak sea levels typically occurring between November and February. Furthermore, to reduce the uncertainty induced by noise in the sea surface height (SSH) time series, principal component analysis (PCA) was utilized to denoise the SSH data from 1993 to 2020, yielding a sea level trend of 1.76 ± 0.56 mm/yr. Denoising reduced the trend uncertainty by 57%, decreased the root mean square error of the SSH series by 5.06 mm, and decreased the annual amplitude by 23.35%. Full article

Microplastic pollution presents a significant and rising risk to both ecological integrity and the long-term viability of economic activities reliant on marine ecosystems. The Black Sea, a region sustaining economic sectors such as fisheries, tourism, and maritime transport, is increasingly vulnerable to this form of contamination. Mytilus galloprovincialis, a well-established bioindicator, accumulates microplastics, providing a direct measure of environmental pollution and indicating potential economic consequences deriving from degraded ecosystem services. While previous studies have documented microplastic pollution in the Black Sea, our paper specifically quantified microplastic contamination in M. galloprovincialis collected from four sites along the western Black Sea coast, each characterised by distinct levels of anthropogenic influence: Midia Port, Constanta Port, Mangalia Port, and 2 Mai. We used statistical analysis to quantify site-specific microplastic contamination in M. galloprovincialis and employed machine learning to develop models predicting accumulation patterns based on environmental variables. Our findings demonstrate the efficacy of mussels as bioindicators of marine plastic pollution and highlight the utility of machine learning in developing effective predictive tools for monitoring and managing marine litter contamination in marine environments, thereby contributing to sustainable economic practices. Full article

Open Responsible Research and Innovation (ORRI) promotes ethical, inclusive, and transparent research aligned with sustainability goals and societal values. This systematic review examines the implementation of ORRI principles in marine research across the Black Sea region—a geopolitically fragmented and under-resourced context—and explores their implications for the broader Responsible Research and Innovation (RRI) discourse. Using PRISMA methodology and bibliometric mapping, we analyzed the peer-reviewed literature and project deliverables from 2014 to 2024, focusing on six ORRI pillars: public engagement, science education, open access, gender equality, ethics, and governance. The findings indicate consistent progress in public engagement and science education, particularly through citizen science and stakeholder training. However, ethics, gender equity, and governance remain weakly institutionalized, with most ORRI practices driven by short-term, externally funded projects. To contextualize these results, we introduce a comparative framework contrasting the Black Sea’s scaffolded model of ORRI with structurally embedded models in Northern and Western Europe. This framework highlights disparities in capacity, funding, and institutional maturity that shape regional implementation. Conceptually, the study contributes to RRI theory by proposing a flexible, context-sensitive model for under-resourced regions. It supports SDGs 4, 5, 14, 16, and 17 and emphasizes the need for durable, inclusive approaches to responsible research and sustainability education. Full article

Current models of sedimentary environments and organic matter (OM) enrichment for the Lower Cambrian black shales in the Yangtze Platform have not yet incorporated its northern carbonate platform margin where the related research is lacked. This study focuses on the SNZ1 well in the northern carbonate platform margin, utilizing total organic carbon (TOC) content and major and trace element data to reveal the main controlling factors of OM enrichment during the Early Cambrian. The results show that the shale stratum is tentatively ascribed to the Lower Cambrian Stage 3 and that, during its deposition, the redox transitioned from anoxic to suboxic–oxic conditions, the hydrodynamic conditions weakened initially and then strengthened, the primary productivity first increased and then decreased, the paleoclimate shifted from arid–cold to warm–humid conditions, and the terrigenous clastic input gradually diminished. Overall, the OM enrichment is primarily controlled by preservation conditions. By systematically analyzing the data from the intraplatform basin to the deep-sea basin across the Yangtze Block, a model of the sedimentary environments and OM enrichment during the Early Cambrian was suggested. Additionally, this study highlights the intrinsic link between the expansion of oxygenated surface water and the Cambrian explosion. These results provide critical insights for shale gas exploration in this region. Full article

The aim of the present work is to assess the wind and hydrogen production capacity of the Black Sea basin from a spatial point of view, by using reanalysis data that covers a 10-year interval (2015–2024). Based on the ERA5 data it was possible to highlight the general distribution of the wind resources at 100 m height, with more consistent resources being noticed in the region of the Azov Sea or in the north-western sector of the Black Sea, where average values of 8.3 m/s are expected. Taking into account that at this moment in the Black Sea area there are no operational offshore wind farms, several generators ranging from 3 to 15 MW were considered for assessment. In this case, from a single turbine, we can expect values in the range of 11.04 GWh (3 MW system) and 89 GWh (15 MW system), respectively. As a next step, the electricity generated from each wind turbine was used to highlight the hydrogen production of several electrolysers systems (or PEMs). The equivalent number of PEMs was identified, and in some cases it was noticed that some devices will not reach their full capacity, while for smaller PEMs a single 10 MW wind turbine could support the operation of almost four modules. Regarding hydrogen output, a maximum of 1560 tons/year can be expected from the PEMs connected to a 15 MW wind turbine. Full article

In recent years, the utilization of renewable energy sources has significantly increased due to their environmentally friendly nature and sustainability. Among these sources, wind energy plays a critical role, and accurately forecasting wind power with minimal error is essential for optimizing the efficiency and profitability of wind power plants. This study analyzes hourly wind speed data from 23 meteorological stations located in Türkiye’s Western Black Sea Region for the years 2020–2024, using the Weibull distribution to estimate annual energy production. Additionally, the same data were forecasted using the Long Short-Term Memory (LSTM) model. The predicted data were also assessed through Weibull distribution analysis to evaluate the energy potential of each station. A comparative analysis was then conducted between the Weibull distribution results of the measured and forecast datasets. Based on the annual energy production estimates derived from both datasets, the revenues, costs, and profits of 10 MW wind farms at each location were examined. The findings indicate that the highest revenues and unit electricity profits were observed at the Zonguldak South, Sinop İnceburun, and Bartın South stations. According to the LSTM-based forecasts for 2025, investment in wind energy projects is considered feasible at the Sinop İnceburun, Bartın South, Zonguldak South, İnebolu, Cide North, Gebze Köşkburnu, and Amasra stations. Full article

In recent years, frequent open biomass burning (OBB) activities such as agricultural residue burning and forest fires have led to severe air pollution and carbon emissions across South and Southeast Asia (SSEA). We selected this area as our study area and divided it into two sub-regions based on climate characteristics and geographical location: the South Asian Subcontinent (SEAS), which includes India, Laos, Thailand, Cambodia, etc., and Equatorial Asia (EQAS), which includes Indonesia, Malaysia, etc. However, existing methods—primarily emission inventories relying on burned area, fuel load, and emission factors—often lack accuracy and temporal resolution for capturing fire dynamics. Therefore, in this study, we employed high-resolution fire point data from China’s Feng Yun-4A (FY-4A) geostationary satellite and the Fire Radiative Power (FRP) method to construct a daily OBB emission inventory at a 5 km resolution in this region for 2020–2022. The results show that the average annual emissions of carbon (C), carbon dioxide (CO₂), carbon monoxide (CO), methane (CH₄), non-methane organic gases (NMOGs), hydrogen (H₂), nitrogen oxide (NO_X), sulfur dioxide (SO₂), fine particulate matter (PM_2.5), total particulate matter (TPM), total particulate carbon (TPC), organic carbon (OC), black carbon (BC), ammonia (NH₃), nitric oxide (NO), nitrogen dioxide (NO₂), non-methane hydrocarbons (NMHCs), and particulate matter ≤ 10 μm (PM₁₀) are 178.39, 598.10, 33.11, 1.44, 4.77, 0.81, 1.02, 0.28, 3.47, 5.58, 2.29, 2.34, 0.24, 0.58, 0.43, 0.99, 1.87, and 3.84 Tg/a, respectively. Taking C emission as an example, 90% of SSEA’s emissions come from SEAS, especially concentrated in Laos and western Thailand. Due to the La Niña climate anomaly in 2021, emissions surged, while EQAS showed continuous annual growth at 16.7%. Forest and woodland fires were the dominant sources, accounting for over 85% of total emissions. Compared with datasets such as the Global Fire Emissions Database (GFED) and the Global Fire Assimilation System (GFAS), FY-4A showed stronger sensitivity and regional adaptability, especially in SEAS. This work provides a robust dataset for carbon source identification, air quality modeling, and regional pollution control strategies. Full article

Within a dam reservoir landscape in the Western Black Sea Region of Türkiye, a dense young-mature stand composed diversely of oriental beeches, European hornbeams, sessile oaks, and silver lindens was chosen as a study field to analyze canopy parameters and to determine phenological patterns along the altitudinal gradients. Referring to the air-soil temperature and precipitation data, intra-annual eco-physiological characteristics of that stand tree canopies, were aimed to be determined regarding those altitudinal gradients. For each of the 10 altitudinal gradients, the mixed deciduous stand canopy physiological characteristics were analyzed by hemispherical photographing. Canopy parameters were acquired from those digital hemispherical photographs, which were confirmed with secondary LAI data from the LAI-2200C. Leaf Area Index, Light Transmission, Canopy Openness, and Gap Fraction were obtained during a total of 21 study field visits throughout the monitoring year. Beginning from a theoretical leafless stage with 0.51 m² m⁻², average LAI increased to 0.89 m² m⁻² during budburst stage, and then gradually up to 3.60 m² m⁻² during climax leaf period, and then to 1.38 m² m⁻² during senescence period, and gradually down to 0.50 m² m⁻² during the next theoretical leafless stage. However, average LT (64%, 61%, 9%, 36%, 74%), CO (65%, 62%, 9%, 37%, 75%), and GF (18%, 14%, 1%, 8%, 14%) followed opposite patterns. Though no apparent trend was valid for those canopy parameters from the lowest to the highest altitudinal gradient, their obvious intra-annual patterns emerged as compatible with the annual air-soil temperature data course. Full article

In recent scholarship, the impact of palaeoclimate change is often understood as a main factor contributing to the fragmentation and “fall” of Rome’s empire. The various attempts at postulating disastrous effects of temperature shifts in the fifth to sixth centuries—cooling caused harvest failures, famine, political and social unrest, and disruptions in food supply—have been criticized for a good reason: compelling causal links between cooler weather conditions and decreasing agricultural productivity are missing. The socio-economic and political impact of a prolonged climate-related Late Roman drought (ca. 360–440 CE), however, has been widely overlooked. This paper aims to compare palaeoecological data from cave speleothems and lake sediments that indicate palaeoclimate and environmental change through precipitation shifts in the southern Black Sea region with the archaeological data of the urban granary in Pompeiopolis. Combining these data offers fresh insights into Roman environmental imperialism, command ecologies and economies, and the impact of climate change on Rome’s tax system that kept the network of redistributive food supply running. This archaeo-environmental approach sheds light on the ecological vulnerability of integrated economies, failures of the dysfunctional metabolic regimes of ›polis command economies‹, and the chain of cause-and-effect provoking the “fall” of Rome. Full article

The assessment of surface water quality of the Danube River and Black Sea was performed taking into account the amounts determined for heavy metals (As, Cd, Cr, Cu, Hg, Mn, Ni, Pb, Zn), nutrients (compounds of N and P, chlorophyll a), emerging contaminants (CECs) (pharmaceutics and endocrine disruptors—19 quantified compounds, out of 30 targeted chemicals), heterotrophic bacteria and total coliforms, in thirty-two locations from the lower Danube sector (starting with km 375 up to the river mouths), the Danube Delta Biosphere Reserve (three Danube branches—Chilia, Sulina, and Sf. Gheorghe) and the Romanian coastal area of the Black Sea. The heavy metals levels were found in the following ranges: 3.0–6.5 μg/L As; 0.51–1.32 μg/L Cd; 21.6–61.2 μg/L Cr; 10.2–28.6 μg/L Cu; 196–351 μg/L Mn; 12.3–47.67 μg/L Ni; 5.2–15.5 μg/L Pb; 44–74 μg/L Zn; 0.01–0.08 μg/L Hg. The nutrient concentrations vary in the intervals: 0.04–0.45 mg/L N-NH₄; 0.01–0.06 mg/L N-NO₂; 0.07–1.9 mg/L N-NO₃; 1.0–3.2 mg/L N total; 0.01–0.05 mg/L P-PO₄; 0.02–0.27 mg/L P total, and 0.8–17.3 μg/L chlorophyll a. The concentrations of CECs from various classes (sulfamethoxazole, trimethoprim, ciprofloxacin, flumequine, amoxicillin, cefuroxime, dicloxacillin, carbamazepine, pravastatin, erythromycin, piroxicam, ketoprofen, diclofenac, naproxen, enilconazole (imazalil), clotrimazole, drospirenone, 17α-ethinylestradiol, and bisphenol A) were compared with values reported for European rivers and the Danube River water in various river sectors. The highest detection frequencies were registered for bisphenol A (100%), sulfamethoxazole (96%), carbamazepine and diclofenac (87%), trimethoprim (78%), pravastatin (46%), and imazalil (34%). Bisphenol A exhibited the largest concentrations (342 ng/L), followed by diclofenac (132 ng/L), carbamazepine (38 ng/L), and sulfamethoxazole (36 ng/L). For most of the contaminants, Black Sea coastal water showed lower concentrations than the Danube water and good ecological status for surface water. Correlations between CECs and total coliforms suggest insufficient treated wastewater effluents as a common contamination source and possible use of CECs as indirect fecal pollution indicator in aquatic systems. This is the first study carried out in the connected system Danube River–Danube Delta–Black Sea for a large palette of toxicants classes and microbial pollutants, which will serve as a baseline for future monitoring of water quality in the region. Full article