We have estimated the standing stocks in carbon units per m² in the Baltic Sea ecosystem for 18 living and non-living groups relevant to carbon cycle and management activities in the Baltic Sea. We included three non-living apartments: POC, DOC and sediment carbon. The living groups comprise: phytoplankton, protozooplankton, bacteria, zooplankton, macrophythes, benthos, plaice, flounder, herring, sprat, cod, ringed seals, seals, grey seals and harbour porpoises. The estimates are based on ICES raw data and literature data and represent spatial and temporal averages. Data, data sources, assumptions and calculations are described in detail to ensure reproducibility.
We have estimated the standing stock biomass in carbon units per m² in the Baltic Sea ecosystem for 18 living and non-living groups relevant to carbon cycle and management activities in the Baltic Sea. We included three non-living apartments: POC, DOC and sediment carbon. The living groups comprise: phytoplankton, protozooplankton, bacteria, zooplankton, benthos, plaice, flounder, herring, sprat, cod, ringed seals, seals, grey seals and harbour porpoises. The estimates are based on ICES raw data and literature data and represent spatial and temporal averages. Data, data sources, assumptions and calculations are described in detail to ensure reproducibility.
Real time control will get more important to reduce CSO emissions. Most of the already existing real time control strategies minimize spill flows from the viewpoint of volume minimization. For receiving water the reduction of emissions is much more important. Measured waste water data and probabilistic approach of these data are the focal points in this research. With an UV-VIS spectrometer installed in a swimming pontoon absorption is measured directly and constant. Based on absorption measurements waste water time series curves of COD, TSS and nitrate are shown. A forecast of CSO emissions and the adjustment of ANN for the control system will be the next step included for this project. By statistical evaluation of rain and measured waste water data as well as forecast of CSO emissions with ANN, spill loads can be reduced. The results of this research are basis for future real time control of CSOs in Graz (Austria).