Abstract Suspended particulate matter (SPM) consists both of an organic (OSPM) and an inorganic fraction (ISPM) and the latter can be used as an indicator for coastal influence in the Baltic Sea. The concentration of SPM can be derived from particle scatter if the specific scattering properties of the respective water body are known. In this paper we show that likewise, ISPM can be derived reliably from remotely sensed particle scatter. An empirical algorithm between particle scatter (AC9 data) and ISPM concentration (measured gravimetrically) was derived from in-water measurements. This regional algorithm was then applied to the iop_bpart level 2 product (i.e. the particle scatter measured at 443 nm) derived from OLCI data on Sentinel-A (S3A) using the C2RCC neural network and validated against an independent data set. The standard error of the derived OLCI match-up data was 10%, and was thus within the goal of the mission requirements of Sentinel-3. The generated S3 composite images from spring and autumn 2018 show that in the Baltic Sea most of the ISPM falls out rather close to the shore, whereas only a very small proportion of ISPM is carried further off-shore. This is also supported by in situ ISPM transects measured in the coastal zone. The ISPM images clearly highlight the areas that are most strongly influenced by terrestrial matter. Differences between the NE Baltic and the SE Baltic proper can be explained by the difference in hydrology and coastal influence as well as bathymetry and wind-wave stirring. The method is of interest for coastal zone management and for assessing the effect of seasonal changes in terrestrial run-off and wind-driven resuspension of sediments. It can also be used to evaluate the effect of climate change which has led to an increase of extreme storm and flooding events that are usually accompanied by increased erosion and run-off from land. Last but not least, turbidity caused by particles influences the light conditions in inner coastal areas and bays, which has a profound effect on pelagic productivity, the maximum growth of macroalgae as well as fish behaviour.

中文翻译：

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无机悬浮物作为波罗的海沿岸地区陆地影响的指标——算法开发和验证以及生态相关性

摘要 悬浮颗粒物 (SPM) 由有机部分 (OSPM) 和无机部分 (ISPM) 组成，后者可用作波罗的海沿海影响的指标。如果已知各个水体的特定散射特性，则可以从粒子散射中推导出 SPM 的浓度。在本文中，我们表明同样可以从遥感粒子散射中可靠地推导出 ISPM。粒子散射（AC9 数据）和 ISPM 浓度（按重量测量）之间的经验算法是从水中测量得出的。然后将该区域算法应用于 iop_bpart 2 级产品（即在 443 nm 处测量的粒子散射），该产品使用 C2RCC 神经网络从 Sentinel-A (S3A) 上的 OLCI 数据得出，并针对独立数据集进行验证。导出的 OLCI 匹配数据的标准误差为 10%，因此在 Sentinel-3 任务要求的目标范围内。2018 年春季和秋季生成的 S3 合成图像显示，在波罗的海，大部分 ISPM 落在离海岸较近的地方，而只有很小一部分 ISPM 被带到离岸更远的地方。这也得到了在沿海地区测量的原位 ISPM 横断面的支持。ISPM 图像清楚地突出了受陆地物质影响最强烈的区域。NE波罗的海和SE波罗的海之间的差异可以通过水文和沿海影响以及测深和风浪搅拌的差异来解释。该方法对沿海地区管理和评估陆地径流和风驱动沉积物再悬浮的季节性变化的影响很有意义。它还可用于评估气候变化的影响，气候变化导致极端风暴和洪水事件增加，这些事件通常伴随着土地侵蚀和径流增加。最后但并非最不重要的是，颗粒引起的浑浊会影响内陆地区和海湾的光照条件，这对远洋生产力、大型藻类的最大生长以及鱼类行为具有深远的影响。