Sea-surface wind fields are critical parameters in marine environments, influencing ocean circulation, meteorology, and climate dynamics. To assess the accuracy of satellite-derived ocean wind products and characterize their error distribution, this study validates sea-surface wind field retrievals using a combination of satellite remote sensing and ocean buoy measurements. Wind field estimates from the Advanced Scatterometer (ASCAT) aboard the European Organisation for the Exploitation of Meteorological Satellites’ MetOp series were compared against buoy observations from four buoy database including the U.S. National Data Buoy Center, et al. over the 2013—2022 period. Following data preprocessing and spatiotemporal collocation, statistical metrics—including mean bias, root-mean-square error, and correlation coefficients—were employed to evaluate ASCAT wind field accuracy. Results indicate strong agreement between ASCAT-derived and buoy-measured wind fields, with correlation coefficients of 0.928 for wind speed and 0.867 for wind direction. The standard deviation of wind speed is 0.889 m/s, while that of wind direction is 22.168°. Among buoy networks, NDBC sites exhibited the most stable wind speed and direction deviations. This validation study enhances the reliability of satellite-derived wind fields, contributing to improved weather forecasting, climate research, ocean engineering, and disaster warning systems. Additionally, the findings support the continuous refinement of satellite payloads and retrieval algorithms.

Oceanic carbon flux constitutes a critical component of the global carbon cycle and fundamentally informs climate change modeling and prediction. The advent of light detection and ranging(LiDAR) remote sensing has gradually revolutionized oceanic carbon flux measurements by providing high spatiotemporal resolutions, precision, and real-time monitoring capabilities. This review evaluates recent advances in LiDAR-based monitoring of diurnal-nocturnal oceanic carbon flux dynamics. We examine the fundamental principles, methodological approaches, and technical challenges associated with LiDAR applications in carbon flux quantification across the air-sea interface. Additionally, we identify knowledge gaps and propose future research directions to enhance the efficacy of LiDAR technology in characterizing temporal variability in oceanic carbon sequestration.

Accurate assessment of the scale and distribution of offshore marine aquaculture is critical for effective management, spatial planning, and ecological protection. This study employed high-resolution Sentinel-2A/2B satellite imagery, a U-Net deep learning model for automatic feature extraction, and human-computer interactive correction to map the spatial extent of raft-based kelp farming in Heiniwan Bay from 2016 to 2024. The analysis revealed a three-phase development trajectory in the aquaculture area over the nine-year period. Spatial distribution exhibited a stable “north-south agglomeration with central sparsity” pattern. The observed spatiotemporal dynamics reflect the combined influence of technological advancements, policy interventions, and natural environmental conditions. These findings offer a robust scientific basis for optimizing aquaculture zoning, adaptive management strategies, and ecological governance in coastal regions with comparable aquaculture practices and environmental settings.

Using Level-2 low-rate expert-level data obtained from the Surface Water and Ocean Topography (SWOT) satellites, this study calculates the positions of crossover points using a gridding method, quantitatively analyzes self-crossover discrepancies, and investigates the impacts of various factors—the time difference between the crossover points, crossover distance, distance from the coast, and latitude—on these discrepancies.Results show that in most regions, discrepancies fall within the range of -0.2 m to 0.2 m, indicating good data consistency, although notable discrepancies are observed in specific regions. Further analysis reveals that the distance between the crossover points has a minimal impact on discrepancies; discrepancies near the coastline are relatively dispersed, while those observed in regions farther from the coastline tend to decrease and stabilize. In high-latitude regions, discrepancies decrease. The time difference shows a certain degree of dispersion in its influence on discrepancies. In a certain range (within 2 km), the distance between the crossover points has a minimal impact on discrepancies. The findings of this study provide a scientific basis for improving the accuracy and reliability of altimetry data obtained from SWOT satellites.

Water quality monitoring and assessment are crucial for sustainable use of water resources and the preservation of aquatic ecosystems. Remote sensing technology, with its unique capability for long-distance detection, offers rapid, efficient, wide-coverage, and high-precision monitoring, and it is particularly suitable for large-scale, dynamic water environment surveillance. In recent years, China has made remarkable progress in the field of remote sensing satellite technology. The successful deployment and continuous high-quality data output of the domestic high-resolution satellite series have brought new opportunities for realizing advanced water quality monitoring. This paper systematically reviews and summarizes the current applications of data obtained from the Gaofen satellite series for water quality monitoring, focusing on the remote-sensing inversion of key water-quality parameters. Furthermore, it outlines future research directions, including the integration of multi-source data, optimization of algorithms and models, and the development of theoretical models. This study provides detailed references for the future development and research on water quality monitoring using domestic satellites.

Suspended sediment mass concentration (ρ_SSC) is a key indicator of estuarine water quality, influencing water transparency, turbidity, nearshore ecosystems, and shoreline stability. In this study, ρ_SSC dynamics in the Yellow River Estuary and adjacent sea areas were analyzed from 1984 to 2024 using satellite remote sensing data processed on the Google Earth Engine platform. We examined the spatiotemporal distribution patterns, long-term trends, and primary drivers of ρ_SSC changes. Over the 41-year period, ρ_SSC exhibited a general declining trend, with low-ρ_SSC waters increasingly dominant. High Suspended sediment mass concentration regions became more localized near the coast, primarily in southern Bohai Bay and the southwestern coast of Laizhou Bay, forming a banded distribution. Theil-Sen Median slope estimation and Mann-Kendall trend analysis revealed significant ρ_SSC increases in the Qingba waterway and artificial distributary channels, whereas significant decreases were observed in the Qingshui Ditch area. Bohai Bay and Laizhou Bay showed a slight upward trend overall. Human interventions, particularly river course diversions, significantly influenced ρ_SSC patterns: historical high Suspended sediment mass concentration estuarine zones contracted, whereas new high Suspended sediment mass concentration zones expanded seaward following each diversion.

Underwater three-dimensional (3D) imaging light detection and ranging (LiDAR) systems have the potential for accurately detecting underwater targets and mapping the seabed terrain, thus facilitating the development and utilization of marine resources. However, most existing underwater 3D imaging LiDAR systems suffer from large size and high power consumption, making them unsuitable for the operational requirements of underwater tasks. To overcome these issues, this study proposes a compact solution based on photon-counting technology that integrates single-point ranging with two-dimensional scanning to achieve 3D imaging. A compact underwater photon-counting 3D imaging LiDAR system was developed by optimizing optical and mechanical design, resulting in a device with a diameter of 165 mm and a length of 340 mm, considerably improving portability and underwater adaptability. A dual-axis synchronous scanning control method was implemented based on FPGA to achieve a scanning accuracy at the nanosecond level, ensuring precise alignment between the emitted pulse and measured target point. Laboratory water tank experiments revealed that the system has a detection capability exceeding 3.1 attenuation lengths. Furthermore, this system was used for underwater 3D imaging of a thruster model that validates its centimeter-level ranging accuracy. Owing to its strong compatibility, this system can be integrated into various underwater mobile platforms and holds strong potential for applications such as seabed topographic mapping, underwater cultural heritage detection, and underwater target identification.

Microbial fuel cells (MFCs) hold considerable potential in bioelectricity generation and bioremediation, and their operational processes are highly sensitive to pH fluctuations. Therefore, online pH monitoring is crucial for optimizing the performance of MFCs. Existing pH meters often fall short in meeting the specific demands associated with online pH monitoring. In this study, we designed a novel voltammetric pH sensor based on electrochemically in situ-synthesized graphene-modified screen-printed electrodes. By surface coupling with the hydrogen-bond carrier alizarin safirol SE, the sensor achieves excellent linearity in pH detection within the range of 4.0 to 9.0, with a sensitivity of 70.7 mV per pH unit. The measurement cycle could be controlled within 15 s. This study successfully demonstrated in situ long-term pH dynamic monitoring in a seawater-based MFC constructed using coastal activated sludge, yielding ideal results. Notably, the incorporation of the aforementioned hydrogen-bond carrier enhanced the proton diffusion rate at the graphene interface, thereby improving the performance of the voltammetric pH sensor. Furthermore, this study revealed the considerable potential of this strategy for improving the reference system, which is expected to further substantially enhance the long-term sensing performance of this strategy. In addition, this strategy provides a new approach for long-term in situ online pH monitoring and thereby contribues to the future development of MFCs.

Seawater chlorophyll-a sensors are essential tools for marine ecological monitoring, enabling the detection of spatial and temporal variations in chlorophyll-a concentration. However, these sensors are susceptible to measurement drift, which can compromise data reliability. This study proposes a metrological approach for evaluating sensor performance using fluorescein sodium as a reference standard. Sensor performance was assessed in terms of linear response range, accuracy, precision, and stability. Results indicated a strong positive correlation between fluorescence intensity and fluorescein concentration. Based on the fitted calibration curve, indication error and standard deviation were calculated. The linear response range was determined by controlling the correlation coefficient, whereas stability was assessed through repeated measurements over different time periods. Within the linear range of 0 to 200 μg/L, the maximum measurement error was ≤2.00 μg/L, and the relative standard deviation was <0.20%. The sensor exhibited consistent performance from 2021 to 2022. Maintaining consistent pipetting accuracy was identified as a critical factor for ensuring measurement reliability.

To meet the rapid response requirements of distributed energy supply systems for dynamic hydrogen production rates, a Ru/Ce-Al catalyst was prepared using a precipitation-hydrothermal method. This method addresses the challenge of maintaining dynamic stability in ammonia-decomposition-induced hydrogen production units under variable load conditions. Characterization techniques, such as XRD, NH₃-TPD, and H₂-TPR, were used to reveal the systematic regulation mechanism by which Al³⁺ doping in CeO₂ and the Ce/Al stoichiometric ratio influence the evolution of oxygen vacancies in the support; in addition, their ammonia-decomposition-induced hydrogen production performance were investigated. The results show that Al³⁺ doping induces the formation of a Ce-Al-O solid solution, which optimizes the distribution of oxygen vacancies on the support surface through strong metal-support interactions (SMSIs), thereby enhancing the dispersion of active metal Ru. At a space velocity of 15 000 h^-1 and reaction temperature of 525 ℃, the Ru/3Ce-Al catalyst achieved an ammonia-conversion efficiency of 93%. Its balanced performance over a wide temperature range (500 ℃ -550 ℃) effectively excessive minimized reaction rates at high temperatures that could lead to catalyst sintering. After 100 h of operation, the catalyst maintained an ammonia-conversion efficiency of 91.8%. An ammonia-hydrogen fuel-cell-based energy supply system, constructed using this catalyst, exhibited power, voltage, and current fluctuations of only 2.3%, 1.1%, and 0.6%, respectively, under a 2 kW load. Furthermore, in step-load tests (0.22 kW→0.45 kW→0.22 kW), the system demonstrated rapid power and current responses with pressure fluctuations below 5‰. This result verified its dynamic response capability and operational stability in complex environments.

Mesoscale eddies are ubiquitous in the ocean and play a key role in the transport of oceanic energy and matter. Current observation methods for mesoscale eddies includesatellite remote sensing, buoy tracking, and research vessel surveys. Each of these methods offer sdistinct scales and perspectives, resulting in varying mesoscale information standards and characteristics.Based on three mesoscale eddy datasets obtained using different methods, this study proposes a two-stage fusion strategy to generatea fused mesoscale eddy dataset for the South China Sea. Moreover,it analyzes the spatial distribution of mesoscale eddy centers in the South China Sea from 2014 to 2018.Results reveal that the fused dataset effectively mitigates issues such as over identification, omission, and misidentification found in single-source observations. Additionally, the fused dataset accurately reflects the wide spread spatial distribution of mesoscale eddies in the South China Sea, the substantial local aggregation of cyclonic and anticyclonic eddies, and clear partitioning between cyclonic and anticyclonic eddies. Furthermore, the fused dataset for the South can offerreliable data support for studies related totrajectory tracking of mesoscale eddies, inferring their three-dimensional structures, and understanding mesoscale oceanic phenomena and circulation.

Understanding nutrient flux in aquaculture systems is critical for sustainable coastal environmental management. This study comprehensively investigated nitrogen and phosphorus dynamics in land-based mariculture across four coastal cities of Zhejiang province: Ningbo, Taizhou, Wenzhou, and Zhoushan, utilizing data from 1 018 sampling points at marine outfalls. Elemental concentration analyses revealed total nitrogen levels ranging from 0.015 to 36.000 mg/L, with total phosphorus concentrations between 0.005 and 2.860 mg/L. Notably, over 90% of the samples remained within Category II of the Zhejiang Province Mariculture Tailwater Discharge Standards, indicating relatively controlled nutrient emissions. Employing both chemical analysis and pollution discharge coefficient methodologies, we estimated the annual nutrient flux from land-based mariculture tailwaters. Chemical analysis methods indicated annual total nitrogen and phosphorus fluxes of 2 969.2 t and 83.6 t, respectively. Significantly, the third and fourth quarters contributed 84.4% of the annual nutrient flux, coinciding with peak harvesting periods and influenced by complex hydrodynamic factors including oceanic currents and Yangtze River dilution waters. Comparative analysis between methodological approaches revealed substantial discrepancies, with pollution discharge coefficient methods estimating higher annual fluxes(4 634.3 t nitrogen and 801.4 t phosphorus). These variations suggest considerable nutrient sequestration within bottom sediments, presenting potential long-term environmental implications. The continuous accumulation of nitrogen and phosphorus in sedimentary environments raises critical concerns about secondary nutrient release mechanisms and escalating eutrophication risks in adjacent marine ecosystems. These findings underscore the necessity for sophisticated nutrient management strategies in coastal mariculture systems.

The assessment of PPP-B2b kinematic positioning performance under different scenarios will be an important reference for users and contribute to the expansion of the application scope and promotion of BDS-3. In this study, the kinematic positioning performance of the PPP-B2b service of BDS-3 under different scenarios was comprehensively analyzed by performing one vehicle experiment and one vessel experiment. Experimental results indicate that using the post-processing product released by the Helmholtz Centre Potsdam-German Research Centre for Geosciences (GFZ) as a reference, the PPP-B2b product had orbit correction accuracy up to the decimeter level and clock correction accuracy up to the sub-meter level. In the vehicle experiment of PPP-B2b, multipath-root mean square (MP-RMS) for BDS-3 B1/B2 frequencies was 41.3 cm, while that for GPS L1/L2 frequencies was 52.2 cm. The positioning accuracies of BDS-3 in the horizontal and vertical directions were 10.3 and 10.5 cm and those of the BDS-3+GPS combination were 5.6 and 4.9 cm, respectively. In the vessel experiment of PPP-B2b, the MP-RMS for BDS-3 B1/B2 frequencies was 52.5 cm, while that for GPS L1/L2 frequencies was 70.4 cm. The accuracy values of BDS-3 in the horizontal and vertical directions were 22.5 and 12.0 cm and those of the BDS-3+GPS combination were 9.7 and 5.1 cm, respectively. The overall impact of multipath effects on the kinematic positioning performance of PPP-B2b in the vessel environment was slightly greater than that in the vehicle environment.

Oceans are not only super-ecosystems but also strategic resource reservoirs, and thus, ocean monitoring is crucial. Unmanned surface vehicles (USVs) are new types of multifunctional unmanned platforms for ocean monitoring, and path planning plays a crucial role as a core technology in their operation. With the continuous increase in maritime traffic density and upgrading of navigation safety standards, traditional path planning methods are facing growing challenges in adapting to complex environments. In this study, a multidimensional improvement strategy is proposed to address the limitations of the bidirectional rapidly-exploring random tree star(Bi-RRT^*) algorithm in USV path planning. First, an adaptive step-size adjustment mechanism, based on environmental feature perception, is established; second, a key node selection strategy is designed; and finally, Bezier curves are used to smooth the generated path, producing a smoother trajectory that better meets the kinematic requirements of USVs. Simulation results show that the improved bidirectional RRT^* algorithm outperforms its traditional counterpart in terms of node-generation efficiency, overall performance, and path smoothness.