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  • 1.
    Algotsson, Josefina
    et al.
    SMHI, Samhälle och säkerhet.
    Edman, Moa
    SMHI, Forskningsavdelningen, Oceanografi.
    Förslag till statusklassning av parameter 9.5 Sötvatteninflöde och vattenutbyte i kustvatten och vatten i övergångszon: En jämförelse mellan Kustzonsmodellens naturliga och normala uppsättning2019Rapport (Annet vitenskapelig)
    Abstract [sv]

    Omkring hälften av Sveriges elproduktion utgörs idag av vattenkraft vilken produceras i omkring 2000 kraftverk. Den största avrinningen av vatten från land sker under våren och vattnet lagras i magasin för elproduktion under vintern. Denna förändring av den naturliga avrinningen har stora effekter på de akvatiska ekosystemen och vara ett av de största miljöproblemen för svenska vattendrag och sjöar.Det saknas idag en vägledning för statusklassificering av hydromorfologiska parametrar i kustvatten enligt Vattendirektivet. SMHI fick i uppdrag av Vattenmyndigheterna att ta fram ett förslag till klassgränser och klassning för parameter 9.5 Sötvatteninflöde och vattenutbyte i kustvatten och vatten i övergångszon enligt Havs- och vattenmyndighetens föreskrifter HVMFS 2013:19. Den hydrologiska modellen S-HYPE och den oceanografiska Kustzonsmodellen användes för att studera de skillnader i färskvattentillförsel samt färskvatteninnehåll, salinitet och vattenålder i ytan som orsakas av reglering av vattenflödet på land.Baserat på resultaten har regleringen av vattenflödet på land överlag lett till en ökning av färskvatteninnehållet med 2 % längs Norrlandskusten och en motsvarande minskning av färskvatteninnehållet på västkusten. Typiskt leder regleringen av vatten på land till en lägre färskvattentillförsel till kusten under våren och sommaren och en högre färskvattentillförsel till kusten på hösten och vintern jämfört med ett scenario med en naturlig landavrinning.Den naturliga bakgrundsvariationen, enligt definitionen ± 2 MAD (Median Absolute Deviation), och den Maximala Absoluta Avvikelsen, MAA, användes för att konstruera 5 statusklasser. Denna metod gav upphov till att 98 % av kustvattenförekomsterna fick en Hög eller God status för parametrarna färskvattentillförsel och salinitet, 87 % av kustvattenförekomsterna fick en Hög eller God status för färskvatteninnehåll och 83 % av kustvattenförekomsterna fick en Hög eller God status för vattenålder.

  • 2.
    Almroth-Rosell, Elin
    et al.
    SMHI, Forskningsavdelningen, Oceanografi.
    Edman, Moa
    SMHI, Forskningsavdelningen, Oceanografi.
    Eilola, Kari
    SMHI, Forskningsavdelningen, Oceanografi.
    Meier, Markus
    SMHI, Forskningsavdelningen, Oceanografi.
    Sahlberg, Jörgen
    SMHI, Affärsverksamhet.
    Modelling nutrient retention in the coastal zone of an eutrophic sea2016Inngår i: Biogeosciences, ISSN 1726-4170, E-ISSN 1726-4189, Vol. 13, nr 20, s. 5753-5769Artikkel i tidsskrift (Fagfellevurdert)
  • 3.
    Edman, Moa
    et al.
    SMHI, Forskningsavdelningen, Oceanografi.
    Eilola, Kari
    SMHI, Forskningsavdelningen, Oceanografi.
    Almroth-Rosell, Elin
    SMHI, Forskningsavdelningen, Oceanografi.
    Meier, Markus
    SMHI, Forskningsavdelningen, Oceanografi.
    Wåhlstrom, Irene
    SMHI, Forskningsavdelningen, Oceanografi.
    Arneborg, Lars
    SMHI, Forskningsavdelningen, Oceanografi.
    Nutrient Retention in the Swedish Coastal Zone2018Inngår i: Frontiers in Marine Science, E-ISSN 2296-7745, Vol. 5, artikkel-id UNSP 415Artikkel i tidsskrift (Fagfellevurdert)
  • 4.
    Edman, Moa
    et al.
    SMHI, Forskningsavdelningen, Oceanografi.
    Sahlberg, Jörgen
    SMHI, Affärsverksamhet.
    The Swedish Coastal zone Model (SCM)2020Rapport (Annet vitenskapelig)
    Abstract [en]

    SMHI develops and maintains a model system for water quality calculations in coastal zone waters around Sweden. It is called the Swedish Coastal zone Model (SCM) and has previously been presented in Sahlberg (2009). Since that report was published the model has been further developed and it is now also used in scientific research. This now calls for an updated report.The SCM is a coupled 1-dimensional physical and biogeochemical model. The model calculates the vertical profiles of all its variables and assumes that they are horizontally homogeneous in the studied area. In order to resolve horizontal variations, a region is divided into several smaller sub-regions, called basins, connected by sounds. Through these sound connections both water and mass of different constituents are exchanged. The basins in SCM are identical to the national water bodies defined in accordance with the Water Framework Directive (WFD). The vertical resolution is half a metre in the uppermost layers, one metre in the 4-70 m interval, and two metres between 70-100 m. Below 100 m the layer thickness increases to 5 m and to 10 m below 250 m.The physical part of SCM consists of the equation solver Program for Boundary Layers in the Environment (PROBE, Svensson (1998)), but also several subroutines which calculates, e.g., insolation, ice-cover, and the exchanges between basins. The exchanges that connect the modelled basins are assumed to be governed by baroclinic and barotropic pressure gradient between the coupled basins.The biogeochemical model is the Swedish Coastal Ocean BIogeochemical model (SCOBI, Marmefelt et al. (2000)). SCOBI is a process-oriented model that includes marine nitrogen, phosphorous and oxygen dynamics, as well as a simple representation of plankton dynamics typical for the Baltic Sea. It calculates 11 variables: zooplankton, three functional phytoplankton groups, detritus, nitrate, ammonium, phosphate, oxygen, benthic nitrogen and benthic phosphorus. SCOBI uses the O2 variable to also, indirectly, model H2S. H2S is represented as a negative oxygen concentration, i.e. the oxygen needed to oxidize a certain accumulated H2S concentration, which can also be considered as an oxygen debt.The mixing and advection of the nine pelagic biogeochemical variables are calculated by PROBE, while SCOBI calculates the process rates which decide how matter is exchanged between the 11 biogeochemical variables, and also the vertical transfers between the SCM’s grid cells due to the sinking of phytoplankton and detritus, i.e. sedimentation.SCM needs input data from the atmosphere (weather variables and deposition on nitrogen and phosphorus), from land (land run-off and point sources, e.g. sewage treatment plant and industries) and also from the open ocean.The model is part of the Swedish water management, but it is also used within research project which results in peer reviewed scientific publications.

  • 5.
    Eilola, Kari
    et al.
    SMHI, Forskningsavdelningen, Oceanografi.
    Almroth-Rosell, Elin
    SMHI, Forskningsavdelningen, Oceanografi.
    Edman, Moa
    SMHI, Forskningsavdelningen, Oceanografi.
    Eremina, Tatjana 
    Russian State Hydrometeorological University, Sankt-Petersburg, Russia.
    Larsen, Janus
    Aarhus University, Roskilde, Denmark.
    Janas, Urszula 
    Institute of Oceanography, Gdansk University, Poland.
    Timmermann, Karen 
    Aarhus University, Roskilde, Denmark.
    Tedesco, Letizia 
    Finnish Environment Institute, Helsinki, Finland.
    Voloshchuk, Ekaterina 
    Russian State Hydrometeorological University, Sankt-Petersburg, Russia.
    Model set-up at COCOA study sites2015Rapport (Annet vitenskapelig)
    Abstract [en]

    COCOA will investigate physical, biogeochemical and biological processes in a combined and coordinated fashion to improve the understanding of the interaction of these processes on the removal of nutrients along the land-sea interface. The results from the project will be used to estimate nutrient retention capacity in the coastal zone of the entire Baltic Sea coast. An ensemble of biogeochemical models will be used in combination with field studies at seven different coastal study sites around the Baltic Sea. The present report is a deliverable of COCOA work package 5 (WP5). Within the objective of WP5 process understanding and process descriptions will be improved in state-of-the-art biogeochemical models of the Baltic Sea coastal zone. This report presents brief information about the models available for the COCOA project and defines the needed input to the models that will be set-up at several learning sites. The aim is to perform ensemble modelling at several sites, using at least two different models at each site. A pilot study to estimate nutrient retention capacity in the Stockholm Archipelago with the existing Swedish model system is ongoing and first results are presented and the concept of nutrient retention is briefly discussed. The existing models for different learning sites presented in the report are; 1) The Swedish model system SCM (Öre river estuary and the Stockholm archipelago) - A multi-box-model approach 2) The Danish model system FLEXSEM (Roskilde fjord) - A combined box-model and 3-D model approach 3) The Finnish model system ESIM-BFMSI (Tvärminne Archipelago) - A 1D box-model approach 4) The Polish model system M3D UG/ProDeMo (Puck Bay) - A 3-D model approach. Operational model. 5) The Lithuanian model system SYFEM/AQUABC (Curonian Lagoon) - A combined box-model and 3-D model approach 6) The Swedish open Baltic model system RCO-SCOBI (for the open Baltic Sea and the Gulf of Gdansk/Vistula). - A 3-D model approach In addition a biogeochemical model (Boudreau, 1996) for the Gulf of Finland (Russian State Hydrometeorological University model) is used to study the quantitative effect of Marenzelleria on the Gulf of Finland ecosystem. Process studies at selected sites will be performed with a reactive transport model developed at Utrecht University. Focus will be on the role of iron and phosphorus cycling. Process studies with the Danish model system will support the development of new parameterizations of nutrient fluxes taking benthic habitat into account. The new parameterizations of the nutrient fluxes will in addition also be implemented into SCM and the models will be used to estimate nutrient fluxes, retention times and the filter capacity of the coastal zones. The In Kind contributions from previously (in the literature) well described open Baltic Sea models RCO-SCOBI, BALTSEM, ERGOM and SPBEM that will be used for the description of open sea conditions are also briefly mentioned in the report with references to the relevant literature. 6) The Swedish open Baltic model system RCO-SCOBI (for the open Baltic Sea and the Gulf of Gdansk/Vistula). - A 3-D model approach In addition a biogeochemical model (Boudreau, 1996) for the Gulf of Finland (Russian State Hydrometeorological University model) is used to study the quantitative effect of Marenzelleria on the Gulf of Finland ecosystem. Process studies at selected sites will be performed with a reactive transport model developed at Utrecht University. Focus will be on the role of iron and phosphorus cycling. Process studies with the Danish model system will support the development of new parameterizations of nutrient fluxes taking benthic habitat into account. The new parameterizations of the nutrient fluxes will in addition also be implemented into SCM and the models will be used to estimate nutrient fluxes, retention times and the filter capacity of the coastal zones. The In Kind contributions from previously (in the literature) well described open Baltic Sea models RCO-SCOBI, BALTSEM, ERGOM and SPBEM that will be used for the description of open sea conditions are also briefly mentioned in the report with references to the relevant literature.

  • 6.
    Eilola, Kari
    et al.
    SMHI, Forskningsavdelningen, Oceanografi.
    Lindqvist, Stina
    Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden.
    Almroth-Rosell, Elin
    SMHI, Forskningsavdelningen, Oceanografi.
    Edman, Moa
    SMHI, Forskningsavdelningen, Oceanografi.
    Wåhlstrom, Irene
    SMHI, Forskningsavdelningen, Oceanografi.
    Bartoli, Marco
    Klaipeda University, Lithuania.
    Burska, Dorota
    Institute of Oceanography, University of Gdansk, Poland.
    Carstensen, Jacob
    Aarhus University, Denmark.
    Hellemann, Dana
    Department of Environmental Sciences, University of Helsinki, Helsinki, Finland.
    Hietanen, Susanna
    Department of Environmental Sciences, University of Helsinki, Helsinki, Finland.
    Hulth, Stefan
    Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden.
    Janas, Urszula
    Institute of Oceanography, University of Gdansk, Poland.
    Kendzierska, Halina
    Institute of Oceanography, University of Gdansk, Poland.
    Pryputniewicz-Flis, Dorota
    Institute of Oceanography, University of Gdansk, Poland.
    Voss, Maren
    Leibniz Institute for Baltic Sea Research Warnemünde, Germany.
    Zilius, Mindaugas
    Klaipeda University, Lithuania.
    Linking process rates with modellingdata and ecosystem characteristics2017Rapport (Fagfellevurdert)
    Abstract [en]

    This report is related to the BONUS project “Nutrient Cocktails in COAstal zones of the Baltic Sea” alias COCOA. The aim of BONUS COCOA is to investigate physical, biogeochemical and biological processes in a combined and coordinated fashion to improve the understanding of the interaction of these processes on the removal of nutrients along the land-sea interface. The report is especially related to BONUS COCOA WP 6 in which the main objective is extrapolation of results from the BONUS COCOA learning sites to coastal sites around the Baltic Sea in general. Specific objectives of this deliverable (D6.4) were to connect observed process rates with modelling data and ecosystem characteristics.

    In the report we made statistical analyses of observations from BONUS COCOA study sites together with results from the Swedish Coastal zone Model (SCM). Eight structural variables (water depth, temperature, salinity, bottom water concentrations of oxygen, ammonium, nitrate and phosphate, as well as nitrogen content in sediment) were found common to both the experimentally determined and the model data sets. The observed process rate evaluated in this report was denitrification. In addition regressions were tested between observed denitrification rates and several structural variables (latitude, longitude, depth, light, temperature, salinity, grain class, porosity, loss of ignition, sediment organic carbon, total nitrogen content in the sediment,  sediment carbon/nitrogen-ratio, sediment chlorphyll-a as well as bottom water concentrations of oxygen, ammonium, nitrate, and dissolved inorganic  phosphorus and silicate) for pooled data from all learning sites.

    The statistical results showed that experimentally determined multivariate data set from the shallow, illuminated stations was mainly found to be similar to the multivariate data set produced by the SCM model. Generally, no strong correlations of simple relations between observed denitrification and available structural variables were found for data collected from all the learning sites. We found some non-significant correlation between denitrification rates and bottom water dissolved inorganic phosphorous and dissolved silica but the reason behind the correlations is not clear.

    We also developed and evaluated a theory to relate process rates to monitoring data and nutrient retention. The theoretical analysis included nutrient retention due to denitrification as well as burial of phosphorus and nitrogen. The theory of nutrient retention showed good correlations with model results. It was found that area-specific nitrogen and phosphorus retention capacity in a sub-basin depend much on mean water depth, water residence time, basin area and the mean nutrient concentrations in the active sediment layer and in the water column.

  • 7. Kratzer, Susanne
    et al.
    Kyryliuk, Dmytro
    Edman, Moa
    SMHI, Forskningsavdelningen, Oceanografi.
    Philipson, Petra
    Lyon, Steve W.
    Synergy of Satellite, In Situ and Modelled Data for Addressing the Scarcity of Water Quality Information for Eutrophication Assessment and Monitoring of Swedish Coastal Waters2019Inngår i: Remote Sensing, ISSN 2072-4292, E-ISSN 2072-4292, Vol. 11, nr 17Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Monthly CHL-a and Secchi Depth (SD) data derived from the full mission data of the Medium Resolution Imaging Spectrometer (MERIS; 2002-2012) were analysed along a horizontal transect from the inner Braviken bay and out into the open sea. The CHL-a values were calibrated using an algorithm derived from Swedish lakes. Then, calibrated Chl-a and Secchi Depth (SD) estimates were extracted from MERIS data along the transect and compared to conventional monitoring data as well as to data from the Swedish Coastal zone Model (SCM), providing physico-biogeochemical parameters such as temperature, nutrients, Chlorophyll-a (CHL-a) and Secchi depth (SD). A high negative correlation was observed between satellite-derived CHL-a and SD (rho = -0.91), similar to the in situ relationship established for several coastal gradients in the Baltic proper. We also demonstrate that the validated MERIS-based estimates and data from the SCM showed strong correlations for the variables CHL-a, SD and total nitrogen (TOTN), which improved significantly when analysed on a monthly basis across basins. The relationship between satellite-derived CHL-a and modelled TOTN was also evaluated on a monthly basis using least-square linear regression models. The predictive power of the models was strong for the period May-November (R-2: 0.58-0.87), and the regression algorithm for summer was almost identical to the algorithm generated from in situ data in Himmerfjarden bay. The strong correlation between SD and modelled TOTN confirms that SD is a robust and reliable indicator to evaluate changes in eutrophication in the Baltic proper which can be assessed using remote sensing data. Amongst all three assessed methods, only MERIS CHL-a was able to correctly depict the pattern of phytoplankton phenology that is typical for the Baltic proper. The approach of combining satellite data and physio-biogeochemical models could serve as a powerful tool and value-adding complement to the scarcely available in situ data from national monitoring programs. In particular, satellite data will help to reduce uncertainties in long-term monitoring data due to its improved measurement frequency.

  • 8.
    Meier, Markus
    et al.
    SMHI, Forskningsavdelningen, Oceanografi.
    Edman, Moa
    SMHI, Forskningsavdelningen, Oceanografi.
    Eilola, Kari
    SMHI, Forskningsavdelningen, Oceanografi.
    Placke, Manja
    Neumann, Thomas
    Andersson, Helén
    SMHI, Forskningsavdelningen, Oceanografi.
    Brunnabend, Sandra-Esther
    Dieterich, Christian
    SMHI, Forskningsavdelningen, Oceanografi.
    Frauen, Claudia
    Friedland, Rene
    Groger, Matthias
    SMHI, Forskningsavdelningen, Oceanografi.
    Gustafsson, Bo G.
    Gustafsson, Erik
    Isaev, Alexey
    Kniebusch, Madline
    Kuznetsov, Ivan
    Mueller-Karulis, Baerbel
    Omstedt, Anders
    Ryabchenko, Vladimir
    Saraiva, Sofia
    Savchuk, Oleg P.
    Assessment of Eutrophication Abatement Scenarios for the Baltic Sea by Multi-Model Ensemble Simulations2018Inngår i: Frontiers in Marine Science, E-ISSN 2296-7745, Vol. 5, artikkel-id UNSP 440Artikkel i tidsskrift (Fagfellevurdert)
  • 9.
    Meier, Markus
    et al.
    SMHI, Forskningsavdelningen, Oceanografi.
    Edman, Moa
    SMHI, Forskningsavdelningen, Oceanografi.
    Eilola, Kari
    SMHI, Forskningsavdelningen, Oceanografi.
    Placke, Manja
    Neumann, Thomas
    Andersson, Helén
    SMHI, Forskningsavdelningen, Oceanografi.
    Brunnabend, Sandra-Esther
    Dieterich, Christian
    SMHI, Forskningsavdelningen, Oceanografi.
    Frauen, Claudia
    Friedland, Rene
    Groger, Matthias
    SMHI, Forskningsavdelningen, Oceanografi.
    Gustafsson, Bo G.
    Gustafsson, Erik
    Isaev, Alexey
    Kniebusch, Madline
    Kuznetsov, Ivan
    Muller-Karulis, Barbel
    Naumann, Michael
    Omstedt, Anders
    Ryabchenko, Vladimir
    Saraiva, Sofia
    Savchuk, Oleg P.
    Assessment of Uncertainties in Scenario Simulations of Biogeochemical Cycles in the Baltic Sea2019Inngår i: Frontiers in Marine Science, E-ISSN 2296-7745, Vol. 6, artikkel-id UNSP 46Artikkel i tidsskrift (Fagfellevurdert)
  • 10. Omstedt, Anders
    et al.
    Edman, Moa
    SMHI, Forskningsavdelningen, Oceanografi.
    Claremar, Bjorn
    Rutgersson, Anna
    SMHI, Forskningsavdelningen, Klimatforskning - Rossby Centre.
    Modelling the contributions to marine acidification from deposited SOx, NOx, and NHx in the Baltic Sea: Past and present situations2015Inngår i: Continental Shelf Research, ISSN 0278-4343, E-ISSN 1873-6955, Vol. 111, s. 234-249Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We have examined the effects of historical atmospheric depositions of sulphate, nitrate, and ammonium from land and shipping on the acid-base balance in the Baltic Sea. The modelling considers the 1750-2014 period, when land and ship emissions changed greatly, with increasing carbon dioxide concentrations, SOx, NOx, and NHx emissions, and nutrient loads. The present results indicate that Baltic Sea acidification due to the atmospheric deposition of acids peaked around 1980, with a pH cumulative decrease of approximately 10(-2) in surface waters. This is one order of magnitude less than the cumulative acidification due to increased atmospheric CO2. The acidification contribution of shipping is one order of magnitude less than that of land emissions. However, the pH trend due to atmospheric acids has started to reverse due to reduced land emissions, though the effect of shipping is ongoing. The effect of strong atmospheric acids on Baltic Sea water depends on the region and period studied. The largest total alkalinity sink per surface area is in the south-western Baltic Sea where shipping is intense. Considering the entire Baltic Sea over the 2001-2010 period, the pH changes are approximately -3 x 10(-3) to -11 x 10(-3) and -4 x 10(-4) to -16 x 10(-4) pH units attributable to all emissions and ship emissions only, respectively. The corresponding changes in total alkalinity are approximately -10 to -30 mu mol kg(-1) and -1 to -4 mu mol kg(-1) attributable to all emissions and ship emissions only, respectively. (C) 2015 Elsevier Ltd. All rights reserved.

  • 11. Turner, David R.
    et al.
    Edman, Moa
    SMHI, Forskningsavdelningen, Oceanografi.
    Gallego-Urrea, Julian Alberto
    Claremar, Bjorn
    Hassellov, Ida-Maja
    Omstedt, Anders
    Rutgersson, Anna
    The potential future contribution of shipping to acidification of the Baltic Sea2018Inngår i: Ambio, ISSN 0044-7447, E-ISSN 1654-7209, Vol. 47, nr 3, s. 368-378Artikkel i tidsskrift (Fagfellevurdert)
  • 12.
    Wåhlström, Irene
    et al.
    SMHI, Forskningsavdelningen, Oceanografi.
    Eilola, Kari
    SMHI, Forskningsavdelningen, Oceanografi.
    Edman, Moa
    SMHI, Forskningsavdelningen, Oceanografi.
    Almroth-Rosell, Elin
    SMHI, Forskningsavdelningen, Oceanografi.
    Evaluation of open sea boundary conditions for the coastal zone. A model study in the northern part of the Baltic Proper.2017Rapport (Annet vitenskapelig)
    Abstract [en]

    The environmental conditions in the coastal zone are strongly connected with the conditions in the open sea as the transports across the boundaries are extensive. Therefore, it is of critical importance that coastal zone models have lateral boundary forcing of high quality and required parameters with good coverage in space and time.

    The Swedish Coastal zone Model (SCM) is developed at SMHI to calculate water quality in the coastal zone. This model is currently forced by the outcome from a one-dimensional model, assimilated to observations along the coast. However, these observations are scarce both in space, time and do usually not include all required parameters. In addition, the variability closer to the coast may be underestimated by the open sea monitoring stations used for the data assimilation. These problems are partly overcome by utilize the one-dimensional model that resolves all the variables used in the SCM. However, the method is not applicable for examine either the past period or future scenario where the latter analyze how climate change might affect the coastal zone. In the present study, we therefore evaluate the possibility to use results from a three-dimensional coupled physical and biogeochemical model of the Baltic Sea as open sea boundary conditions for the coastal zone, primarily to investigate the two periods mentioned above.

    Seven sensitivity experiments have been carried out in a pilot area of the coastal zone, the northern part of the Baltic proper, including the Stockholm Archipelago. The sensitivity tests were performed in order to explore methods to extract the outcome from the three-dimensional model, RCO-SCOBI, and apply as lateral boundary forcing for the SCM. RCO-SCOBI is a model for the open Baltic Sea with high horizontal and vertical resolution of the required variables. The results from the different tests were examined and evaluated against observations in the coastal zone. This was executed for both the physical and the biogeochemical variables utilizing a statistical method.

    The results from this study concluded that the outcome from the RCO-SCOBI is applicable as forcing files for the SCM. The best results in the tests was obtained with a method extracting depth profiles for the required variables from the RCO-SCOBI at a position 10 nautical miles to the east and 10 nautical miles to the south in the Baltic proper or north in the Gulf of Bothnia outside each of the outer basins.

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