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This study was conducted to explore the contribution of silicon dissolution from beach sediments to the dissolved silicon budget in the coastal waters. From March to September in 2017, six field surveying cruises were conducted in the Muping offshore area (Yantai, China), the southern North Yellow Sea. By investigating monthly distributions and the averaged values of dissolved inorganic nutrients, monthly accumulation of dissolved silicate anomaly (ΔSi, as defined with the difference between dissolved inorganic nitrogen and silicate concentrations)of 1.5 μmol·L^-1 was observed in this offshore area with weak circulation from May to August. Further combining laboratory incubation experiments, theoretical calculation and field data analyses, It was found that the permeable particles in beaches could be dissolved, leaching active silicate to seawater, and increasing the offshore silicate concentration by 0.7~2.0 μmol·L^-1 every month, roughly consistent with the monthly accumulation rate of field ΔSi. Extrapolating the beach silicate-leaching flux to the length of the coastline rounding the Yellow Sea, the previously reported imbalance in silicate budget in this coastal sea could roughly be bridged. This study indicated again that the dissolving of permeable particles might contribute significantly to coastal silicate budget.

The interaction between deep-ocean geostrophic current and seamounts can generate near-inertial internal waves (NIWs). While the intensity of these waves relates to the seamount height, its dependence on seamount width remains elusive. This study employs a two-dimensional, non-hydrostatic numerical model based on MITgcm to investigate the interaction of geostrophic current with deep-sea seamounts and examine how differing seamount widths influence the generation and dissipation of NIWs. Our results demonstrate that topographic forcing triggers robust nonlinear wave-wave interactions along the summit edges on the downstream flank of the seamount. This process generates energetic near-inertial internal waves that radiate away and develop, facilitating energy transfer from the geostrophic mean flow to the NIWs. For a fixed seamount height, narrower seamounts induce stronger near-inertial waves, characterized by more rapid wave development and decay. Moreover, the downstream flank exhibits significantly enhanced vertical shears within the near-inertial internal waves, driving greater turbulent dissipation compared to the upstream flank. Therefore, our findings highlight that, in addition to seamount height, seamount width is also a critical factor governing the generation and subsequent evolution of near-inertial internal waves.

Using the measured data of extreme waves causing by 6 typhoons and 2 cold waves (caused by typhoon is called typhoon wave, caused by cold wave is called cold wave)during a one-year wave observation process in the Cangnan sea area of Zhejiang Province, the distribution and variation characteristics of wave parameters for each extreme wave as well as the typical characteristics of typhoon waves during Typhoon “Lekima” and “Mitag” were analyzed. The results show that the typhoon waves in the study sea area were significantly affected by the typhoon track and intensity, the stronger the typhoon intensity and the closer its proximity to the study area, the more significant and intense the process of typhoon waves, the higher the wave height and spectral peak density of typhoon waves. Both summer and autumn could be affected by extreme typhoons and lead to extreme typhoon waves. Extreme waves caused by cold wave occured both in winter and spring, of which intensity were directly affected by the intensity of cold waves, overall, extreme waves caused by cold wave were not as severe as typhoon waves. The duration of the impact of typhoon waves was two to three days, and the duration of the impact of extreme waves caused by cold wave was about 1 day; the maximum wave height and spectral peak density during extreme waves exhibited a synchronous development process of initially increasing and then decreasing. During the impact of Typhoon “Lekima”, the maximum wave height in the studied sea area was 10.80 m, with a maximum spectral peak density of 55.10 m²/Hz, the development and change process of wave spectrum was bimodal spectrum-unimodal spectrum-bimodal spectrum, and the development and change process of wave types was mixed waves dominated by swell-wind wave-mixed waves dominated by wind wave. During the impact of Typhoon “Mitag”, the maximum wave height in the studied sea area was 8.89 m, with a maximum spectral peak density of 36.37 m²/Hz, the wave spectrum was mainly composed of unimodal spectrum, with occasional bimodal spectrum. The wave type was mainly swell, with occasional mixed waves dominated by swell.

Tidal flats are influenced by tides, experiencing periodic inundation and exposure, thus the inundation frequency reflects the elevation of tidal flats. This study utilizes time-series SAR satellite remote sensing data to conduct research on the remote sensing inversion method of tidal flat topography based on tidal level complementary cumulative distribution function. The key lies in proposing a new method for inundation frequency correction based on the weighting scale of remote sensing observation counts. And, based on the mathematical definition of inundation frequency, the functional relationship between inundation frequency and tidal flat elevation was explored, leading to the construction of a tidal flat topography inversion model based on the tidal level complementary cumulative distribution function. Then, the validation of the method was conducted in the Yueqing Bay. Based on the time-series Sentinel-1 satellite SAR remote sensing data, the tidal flat topographies for the periods 2019-2020 and 2021-2022 were successfully inverted. The accuracy assessment was conducted based on the corresponding period’s ICESat-2 satellite laser altimetry data. The root mean square errors (RMSE)of the tidal flat topographies for the periods 2019-2020 and 2021-2022 were 0.41 m and 0.51 m, respectively. Additionally, the RMSE of topography for the period of 2019-2020 using in-situ data was 0.48 m. The accuracy assessment suggest that the proposed method in this study can achieve high-precision tidal flat topography without field-measured topographic data. It is expected to be applicable to the monitoring of tidal flat topography in more regions.

During satellite operation, sensor malfunctions can lead to irregular strip-like missing areas in imagery, which compromises the integrity of observed information. To address this issue in geostationary satellite remote sensing imagery, a reconstruction model based on convolutional neural networks (CNN)is proposed. The model’s performance is evaluated under different combinations of temporal input data to identify the optimal configuration of consecutive temporal auxiliary data. In the auxiliary data combination, (taking the generation time of the image to be restored as the current time t), when the model takes the previous four phases (t-4, t-3, t-2, t-1)and the previous and subsequent three phases (t-3, t-2, t-1, t+1, t+2, t+3)as inputs respectively, the restoration effect is excellent and can be used for data restoration and reconstruction in real-time and delayed scenarios respectively. Compared with models that use only a single time point as auxiliary data, the proposed model utilizing multi-temporal inputs demonstrates better reconstruction results and higher accuracy. The model is also applicable to the restoration of missing information in other geostationary satellite images.

Island ecosystems are characterized by resource specificity and ecosystem vulnerability, thus, the scientific assessment of the impact of land use change on the carbon sequestration and other ecosystem service functions of island ecosystems is of great significance to the sustainability management of islands. The Dongtou Islands in Zhejiang Province represents a typical island ecosystem that has undergone developmental utilization such as land reclamation and conservation-restoration initiatives like the Blue Bay Project. It serves as an ideal case study for establishing assessment methods of how land use changes affecting the carbon sequestration service function of island coastal ecosystems and others, and for exploring the effectiveness of management measures. In this study, a land classification model based on XGBoost algorithm was used to obtain land use classification data of the Dongtou Islands in 12 phases (3 years as a phase)from 1988 to 2023 (with accuracy of 91.52%). On this basis, the changes in carbon sequestration amounts of major ecosystems, including woodland, salt marshes, and tidal flats, in the Dongtou Islands were calculated. A coupling coordination degree model of “economic development-land use-carbon sequestration function” was constructed by combining the socio-economic statistical data, and the degree of coupling coordination between the economy and ecosystem of the Dongtou Islands for more than 30 years was explored. The study found that from 1988 to 2023, the total land area of the Dongtou Islands increased by 34.97% due to natural silt deposition and sea reclamation efforts. The cumulative total of ecosystem carbon sequestration amount and net carbon sequestration amount for the main ecosystems amounted to 49.45×10⁴ t and 46.13×10⁴ t, respectively, basically showing an oscillating upward trend. Carbon sequestration mainly resulted from woodland and coastal wetlands (including tidal flats and salt marshes), with cumulative carbon sequestration amount of 25.44×10⁴ t and 24.01×10⁴ t, respectively. The “economic development-land use-carbon sequestration function” coupling coordination degrees of the Dongtou Islands were in a coordinated state from 2006 to 2023. Overall, the coupling coordination degree is greatly affected by the land use changes. Ecological restoration projects can enhance the comprehensive evaluation index of the land use and carbon sequestration function system, and then improve the coupling coordination degree. This study can provide a scientific theories and data foundation for the socio-economic development and ecological environmental protection planning of the Dongtou Islands.

The global ionospheric model based on the global navigation satellite systems (GNSS)reference stations is currently the most widely used global ionospheric product. The analysis and evaluation of the reliability and accuracy of the global ionospheric model during magnetic storms is a necessary prerequisite for the rational use of the model. In this study, the data of the reference stations near the South China Sea were used to verify the reliability of the ionospheric vertial total electron content (VTEC)calculated from shipboard GNSS data, and the accuracy of the global ionospheric model in the South China Sea during magnetic storms was preliminarily analyzed and evaluated using the shipboard GNSS observation data and reference stations data. The results show that the ionospheric VTEC calculated from the shipboard data and the reference stations data have the same trend of change. During the magnetic storm, the error between the global ionospheric model value in the South China Sea region of China and the shipboard observation data and the reference stations (HKSL, PIMO)data increases, and the daily average RMSE values are 41.21, 27.40 and 30.86 TECU, respectively, which indicates that the disturbance of the ionosphere by the magnetic storm activity has led to a significant decrease in the accuracy of the global ionospheric model.

The response coefficient method is one of the widely used methods for controlling the total amount of pollutants from land-based sources in harbors and gulfs. However, the current popular ocean models do not have a tracer module that simultaneously calculates the response coefficient field of multiple release points without interfering with each other. Aiming at the characteristics of the response coefficient method, this study improves the tracer module (DYE)of the three-dimensional hydrodynamic ocean numerical model FVCOM (Finite-Volume Community Ocean Model)by adding independent modules with the same functions as the original DYE module to DYE modules in parallel, so that FVCOM can simultaneously calculate the response coefficient fields of multiple release points without interfering with each other. The improved DYE algorithm was tested with one case of ideal rectangle grid and one case of ideal Xiangshan Bay grid. The results show that the advection-diffusion process of multiple point source tracers simulated by the improved algorithm does not interfere with each other, and the simulation results are the same as those of the traditional algorithm; at the same time, the computation process of the improved algorithm takes less time, and the computation efficiency of the ideal rectangle case is increased by up to 85% and that of the Xiangshan Bay case is increased by up to 78% compared to the traditional algorithm; and the improved algorithm has a higher utilization rate of the CPU process under the condition of parallel computation than those of the traditional algorithm. The use of the improved DYE to calculate the response coefficient field can shorten the total time for marine environmental capacity assessment.

Total nitrogen (TN)is an important indicator for measuring water eutrophication, and understanding its spatiotemporal variation is crucial for marine ecological protection. This study selected the Pearl River Estuary-Jiangmen sea area as the research area and utilized TN measurement data from 2021 to 2023, as well as the MODIS data from 2003 to 2023 and the Sentinel-3 remote sensing images from 2017 to 2023. By selecting high-correlation band combinations and constructing random forest regression models to invert TN mass concentration, the spatiotemporal variation characteristics of TN mass concentration in the region from 2003 to 2023 were analyzed. The results indicated that the inversion model achieved good fitting accuracy (R²=0.797-0.931). From 2003 to 2023, the TN mass concentration in the Pearl River Estuary-Jiangmen sea area showed an overall decreasing trend, with relatively high mass concentrations from 2003 to 2015, followed by a significant decline after 2016. TN showed obvious dry/wet seasonal variations, and the variations within the year in the estuary and shallow water areas were also significant. This study revealed the trend and distribution characteristics of TN in the study area through remote sensing inversion, which can provide a basis and reference for the formulation of pollution control measures in the coastal waters.

Mangroves are among the most effective carbon sequestration ecosystems on earth, which is crucial in addressing global climate change and achieving China’s “dual carbon” goals. This research focused on the Yanpu Bay mangroves in Zhejiang, where surface (0-25 cm)sediment samples were collected in the spring and autumn of 2018-2019 to analyze organic carbon, total nitrogen, total phosphorus, and sediment particle size. The findings revealed that the sediment organic carbon content ranged from 6.50 to 11.90 g/kg, the total nitrogen content ranged from 1.08 to 1.36 g/kg, and the total phosphorus content ranged from 0.57 to 0.74 g/kg. Correlation analysis revealed a significant positive correlation between sediment organic carbon and total nitrogen (p<0.05), indicating their potential sources shared similarities. The sediment organic carbon also showed a highly significant positive correlation with clay content (p<0.01), indicating that fine-grained sediments were more conducive to organic carbon sequestration. Conversely, it exhibited a highly significant negative correlation with total phosphorus, mean particle size, sand and silt content (p<0.01). Hierarchical segmentation analysis suggested that the sand and silt content in the sediment were key environmental factors affecting the distribution of organic carbon in the surface of mangroves. Additionally, mangrove species composition, stand age, surface runoff distribution, typhoon impacts, and pond dredging in aquaculture areas were also identified as driving factors influencing sediment organic carbon distribution.

The carbon sink capacity of muddy tidal flat plays a significant role in coastal blue carbon ecosystems. Microalgae, as the main primary producers in these habitats, are key contributors to carbon sequestration and storage. However, the community composition and carbon stock of microalgae in China’s muddy tidal flats remain poorly understanding. Here, microalgae samples were collected from muddy tidal flat of Aiwan Bay, Wenling, Zhejiang Province in August 2021. The microalgae were identified using an inverted microscope, and their carbon stock was estimated based on cellular biovolume measurements. A total of 59 species from 4 phyla were identified, with diatom being the overwhelmingly dominant group. The most abundant genera included Coscinodiscus, Nitzschia, Gyrosigma, and Synedra. The abundance and biomass of microalgae showed pronounced spatial heterogeneity across sampling sites, likely influenced by terrestrial inputs. In addition, tidal creeks caused by strong outflow from water gates might have affected the settlement and resuspension of microalgae. Based on biomass calculations, the regional microalgal carbon stock in muddy tidal flat of Aiwan Bay was estimated at approximately 2 134 t, with approximately 60% derived from settled planktonic microalgae. This study underscores the significant impact of phytoplankton on microalgal community composition and carbon storage. These findings provide valuable insights for assessing carbon sinks in muddy tidal flats and contribute to a better understanding of blue carbon dynamics in coastal ecosystems.