溶解有机氮光铵化影响因子及在南海北部空间分布格局

光化学过程对海洋生物地球化学循环具有重要影响。溶解有机氮（DON）光铵化是有机氮向无机氮转变的重要途径之一，对海洋氮循环和初级生产具有重要贡献，但是对DON光铵化影响因素的认识还远远不足，亟需研究解决。本项目拟在南海北部海区开展如下研究：（1）探讨内因（溶解有机物来源、元素组成与光学性质）与DON光铵化表观量子产率（AQY）的定量关系；（2）综合研究环境因子（温度、盐度、pH和溶解氧浓度）与光铵化AQY的定量关系；（3）结合上述定量关系以及太阳辐射和温盐等大面观测数据资料，构建南海北部真光层内DON光铵化从河口到海盆的空间分布格局。对内、外因如何影响DON光铵化的系统研究是本项目的主要创新点，其特色是以室内光照实验与现场大面观测相结合，构建南海北部光铵化跨河口、陆架、陆坡和海盆的空间分布规律，并厘清其主要调控因子。该研究将有助于深入认识海洋氮循环，为海洋生态模型提供基础数据。

Photochemical processes significantly impact major biogeochemical cycles in marine ecosystems. Photoammonification is an important pathway of transforming dissolved organic nitrogen (DON) into dissolved inorganic nitrogen, thereby affecting the marine nitrogen cycle and primary production. However, our knowledge remains limited about the factors controlling photoammonification and about its quantitative contribution to the nitrogen cycle on regional and global scales. Using natural water samples collected in the northern South China Sea, this study aims (1) to quantify the relationships between the apparent quantum yield (AQY) of DON photoammonification and the properties of dissolved organic matter (DOM), such as its sources, elemental compositions and optical properties; (2) to establish quantitative relationships between the AQY of photoammonification and the temperature, salinity, pH and dissolved oxygen concentration (DO) of seawater; (3) to map the spatial distributions of the rate of photoammonification in the euphotic zone across the land-ocean continuum in the northern South China Sea area, using coupled optical-photochemical modeling that incorporates the relationships obtained from objectives (1) and (2). This research is novel in that it is the first of its kind (1) to systematically evaluate the impacts of the intrinsic properties of DOM and environmental factors on the rate of photoammonification, and (2) to elucidate the spatial variability of the rate of photoammonification on a large regional scale based on the quantitative relationships between photoammonification and its controlling factors. This research will help better understand the marine nitrogen cycle and provide fundamental data for improving ecosystem modeling.