Classification of suspended particles characterizes the composition of seawater, which helps the interpretation of remote sensing data and promotes the researches of the matter exchanges in ocean processes. In this article, an in situ prototype based on polarized light scattering is introduced, and its ability to classify the suspended particles is demonstrated. The experimental results show that the prototype can classify the sediments, microplastics, and phytoplankton in seawater with an accuracy larger than 85%, and further calculate their relative proportion in water. In the summer and winter of 2020, the prototype was deployed three times in Daya Bay and lasted for dozens of hours each time, along with the additional commercial sensors, that is, Environment X Observation (EXO) and Acoustic Doppler Current Profiler (ADCP). The chlorophyll content measured by EXO and the acoustic backscatter intensity measured by ADCP are respectively related to the number of algal cells and sediments in the water, which helps to interpret the data of the prototype. The results of field data show that the prototype can effectively classify phytoplankton and sediment particles in seawater and monitor their temporal variations. Besides, the retrieved information of the suspended particles is consistent with the analysis from the flow dynamics and season variations in Daya Bay. These results indicate the ability of this prototype to classify the suspended particles in seawater, which promises its potential contribution to particulate oceanography in the future.

中文翻译：

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使用原位偏振光散射原型对海水中的悬浮颗粒进行分类

悬浮颗粒的分类表征了海水的组成，有助于遥感数据的解释，促进海洋过程中物质交换的研究。在本文中，介绍了一种基于偏振光散射的原位原型，并证明了其对悬浮颗粒进行分类的能力。实验结果表明，该原型机能够对海水中的沉积物、微塑料和浮游植物进行分类，准确率大于85%，并进一步计算出它们在水中的相对比例。2020年夏冬两季，原型机在大亚湾部署了3次，每次持续数十小时，同时还附加了环境X观测（EXO）和声学多普勒电流剖面仪（ADCP）商用传感器。EXO测量的叶绿素含量和ADCP测量的声学反向散射强度分别与水中藻类细胞和沉积物的数量相关，这有助于解释原型的数据。现场数据结果表明，该原型机能够有效地对海水中的浮游植物和沉积物颗粒进行分类并监测其时间变化。此外，反演的悬浮颗粒物信息与大亚湾水流动力学和季节变化分析一致。这些结果表明该原型能够对海水中的悬浮颗粒进行分类，这有望为未来颗粒海洋学做出潜在贡献。