## 4 Discussion
In the case of Parnu Bay, for example, the 2022 in situ samples did not show significant cyanobacteria biomass in the area, whereas the turbidity was high. This would indicate an erroneous ES assessment as the turbidity is not a result of dead cyanobacteria cells but rather inorganic matter being picked up by the satellite. Upwelling is a possible cause for the seasonal dynamics in the Gulf of Finland (Hara-Kolga, Eru-Kasmu, Muuga-Tallinna-Kakumae, and Pakri bays) and in the NE Gulf of Riga. Upwelling in the Gulf of Finland (northern coast of Estonia) is a regular occurrence that displaces the warm surface water with cold water from the bottom layer of the sea while increasing nutrients in the upper layers. Because cyanobacteria generally prefer warmer temperatures and are normally phosphorous-limited [15; 79], upwelling has an effect in areas where it occurs. Due to the variability in upwelling events, which might be seasonal or one-off events, it is difficult to measure its effect on the annual ES of a coastal area. Upwelling can have a promoting effect on the formation of cyanobacteria blooms as it enriches the higher water levels with phosphorous [80; 81]. Other evidence has shown that the upwelling process can temporarily displace cyanobacteria species and disrupt the structure of community composition [82], but the effect is only temporary as communities tend to return to compositions similar to those before an upwelling event shortly after [82]. Water temperature which can be measured via satellites can be used as an additional parameter for future ES assessments which would link the impacts of upwelling to the environmental status assessment. An important aspect to note is the large year-to-year variation in the index results which shows high natural variability in the bloom parameters. Due to the limitations of using S3/OLCI data, our dataset extends only as far back as 2016. Because of this, the period from which a threshold ES value is calculated is rather small and might skew the result if an area has had a particularly turbid or chl-a-dominated year. The reliability of determining the \"good-bad\" threshold value and environmental status depends mainly on the representativeness of the data. Because the variability between years can be quite impressive, it would be beneficial to assess the environmental status of an area over a largertime frame. On the other hand, the data series analyzed here cannot be extended into the very distant past due to differences in EO instruments. In general, however, the results indicating the poor environmental status of the coastal areas are consistent with other methodologies. Previous assessments by HELCOM [37] indicated a poor environmental status based on the CyaBI in the Gulf of Finland, Gulf of Riga, Eastern Gotland Basin, and Northern Baltic Proper (areas that include Estonian coastal areas). However, under HELCOM's methodology, no sampling took place in the NW part of the Gulf of Riga, which, according to our analysis, achieved GES. This highlights the usefulness as well as the necessity of using satellites for more accurate monitoring. Similar to HELCOM, a national monitoring report by the Estonian Environment Agency indicated a poor environmental status for some Estonian coastal areas (Gulf of Riga (NW), Gulf of Riga (center), Parnu Bay, Muuga-Tallinna-Kakumae Bay, and Narva-Kunda Bay). Their assessment methodology is based on other factors instead of cyanobacteria blooms, such as plankton, bottom vegetation, and bottom fauna [83]. As the Sentinel-3 mission is going to continue [49], a longer time period for threshold detection would be beneficial. Future work should also focus on connecting the ES results as well as the chl-a given here to other environmental variables to explain the possible causes of the conditions of coastal areas. Causes will most likely differ between coastal areas.