Nitrogen transfer processes and NO3− sources in the East China Sea (ECS) were analyzed using dual isotopes of NO3− and NO2−, the concentration and isotopes of dissolved O2 and N2 gases, nutrient concentrations, and the hydrological conditions. It was clear that the δ15N and δ18O values of NO3− in the Changjiang freshwater were 5.6–6.6‰ and 0.6–1.0‰, respectively, affected by human activities (fertilizer, sewage, and manure) and nitrification. Off the Changjiang Estuary to the ECS continental slope, the NO3− concentration was lower or exhausted in the upper water layers, where both available δ15N and δ18O values for NO3− were high related to phytoplankton assimilation. In the lower water layers, organic matter remineralization, nitrification, and coupled sedimentary nitrification and denitrification resulted in low NO3− isotope values. Moreover, in the upper water layers of the ECS continental slope, NO3− showed high δ15N and δ18O values and low Δ(15, 18) values affected by assimilation, nitrification, and N2 fixation. NO2− in the ECS was dominated by NH4+ oxidation, and NO2− oxidation plays an important role in depleting NO2− in δ15N values. An overall NO3− budget is built for the ECS shelf, indicating that open boundary exchanges of NO3− flux and isotopes through Kuroshio invasion and Taiwan Warm Current Water are comparable to outflow off the ECS shelf, and nitrogen transformation processes (such as NO3− assimilation and nitrification) play an important role in nitrogen cycle, and NO3− is modified on the ECS shelf.

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Dissolved organic nitrogen (DON) is an important component of the marine nitrogen (N) inventory and plays an essential role in N cycling in global estuaries and marginal seas. Understanding DON cycling is important but challenging. Global estuaries and marginal seas are experiencing significant anthropogenic impacts and have intensive physical/biochemical gradients. Therefore, high-quality DON concentration and N-isotope (δ15N–DON) data are very difficult to obtain. To enrich this knowledge, we take the Changjiang Estuary and the adjacent East China Sea shelf seas as a representative example and analyzed multiple isotopes and the concentrations of nitrate (NO3−), particulate nitrogen (PN), and DON. N isotopes combined with optimum multiparameter analysis proved to be very informative. This integrated analysis discriminates active DON production and consumption from a seemingly conservative distribution pattern of DON. The study area was divided into DON production zones 1 and 2 (P-zone 1 and 2) and DON consumption zones 1 and 2 (C-zone 1 and 2). For P-zone 1, the PN-originated DON elevated the δ15N–DON, while in P-zone 2, the DON excreted by phytoplankton was characterized by low δ15N and lowered δ15N–DON. DON consumption occurred in the NO3− depleted surface waters (C-zone 1) as well as the shelf middle and bottom waters (C-zone 2). This study discovers and consolidates the active and dynamical zoning of DON cycling from the estuary to the offshore marginal sea and establishes a useful means that is of valuable reference to DON cycling studies in global estuaries and marginal seas.

With the development of airborne synthetic aperture radar (SAR) technology, the 3D SAR point cloud reconstruction has emerged as a crucial development trend in the current SAR community. However, due to measurement errors, environmental interference, radar decoherence, and other noises associated with the SAR system, the reconstructed tomogram is often deteriorated by numerous noisy scatterers. As a result, it becomes challenging to obtain high-quality 3D point clouds of the observed object, making it difficult to further process the point cloud and realize target identification. To address these issues, we propose a K nearest neighbor comprehensive weighted filtering algorithm. The filtered point cloud is evaluated quantitatively using three-dimensional entropy. In this study, we adopted various filtering methods for simulated data, P-band data of Genhe, and Ku-band data of Yuncheng to refine the tomogram and compare their performances. Both qualitative and quantitative analyses demonstrate the superiority of the filtering algorithm proposed in this paper.