HELSINKI COMMISSION HELCOM MONAS 8/2005 Monitoring and Assessment Group Eighth Meeting Riga, Latvia, November 2005

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1 HELSINKI COMMISSION HELCOM MONAS 8/2005 Monitoring and Assessment Group Eighth Meeting Riga, Latvia, November 2005 Agenda Item 7 HELCOM projects under HELCOM MONAS Document code: 7/6 Date: Submitted by: MARE PROGRESS REPORT BY MARE ON HELCOM PROJECT "ASSESSMENT OF IMPLICATION OF DIFFERENT POLICY SCENARIOS ON NUTRIENT INPUTS" HELCOM HOD established a joint HELCOM LAND/MONAS project in December 2004 on assessment of implication of different policy scenarios on nutrient inputs where the MARE model is used to simulate the impact of the implementation of the EU Common Agriculture Policy and other policies in the Baltic Sea area. Based on the existing regulations, and the extent to which they have been implemented, HELCOM may consider the need for additional measures, and examine where these measures could be implemented most cost-effectively. The project is carried out in steps. The first step was to further select most appropriate measures for the reduction of nutrient losses from agriculture based on the list of possible measures adopted by the HELCOM Ministerial Meeting in Bremen The following steps, carried out by MARE, were to include the above possible future measures into the MARE NEST model in order to assess the changes in nutrient inputs and the resulting effects on nutrient concentrations in the different parts of the Baltic Sea. The HELCOM-Baltic Sea Regional Project (BSRP) networking meeting in Tallinn in December 2004 considered the first steps in the project and how to better link the activities in the BSRP to this project in order to achieve synergies. The outcome of the meeting was that the existing measures in the countries should be included to the MARE NEST model (state of the art). This would provide the basis from which the changes in inputs of nutrients based on the different scenarios are modelled. In addition the meeting decided to task MARE in cooperation with the Contracting Parties to include the following scenarios for measures to the NEST model: a. Implementation of existing programmes and plans; b. Nitrates directive implementation in whole country/defined sensitive areas; c. EU CAP implementation (even if national programmes not finalized); d. Nitrogen surplus scenario; e. Manure handling scenarios. The task of MARE was to consequently evaluate the effectiveness of the implemented measures in cutting down inputs to the sea, the concentrations of nutrients and selected biological quality parameters reflecting the good ecological status. The scenarios were to be built on the best available data submitted by the Contracting Parties and a contact person from each Contracting Party has been assigned for more detailed discussions with the MARE scientists. Note by Secretariat: FOR REASONS OF ECONOMY, THE DELEGATES ARE KINDLY REQUESTED TO BRING THEIR OWN COPIES OF THE DOCUMENTS TO THE MEETING Page 1 of 13

2 In order to speed up the process all contact persons were invited to a seminar in Stockholm August 2005 with the aim to discuss the development of scenarios and the national data needed for this work. To provide the project with data, HELCOM asked all member states to fill in a questionnaire by the end of August. All Contracting Parties have not provided the necessary data on agricultural activities to develop the requested scenarios. As a consequence only one scenario has been developed showing the effects on nutrient loads if maximum possible reductions of nutrient effluent from point sources in urban areas were implemented everywhere. Thus, all people in urban areas were assumed to be connected to WWTP having tertiary cleaning (a cleaning with 75% N and 90% P) was tested. The NEST model includes the atmospheric nitrogen deposition scenario to six sub-basins and catchments of the Baltic Sea in the year 2010 provided by EMEP. The calculations have been made using emission projections according to agreed emission ceilings under the EU NEC Directive and the Gothenburg Protocol and ENTEC projections for shipping. The next step in the project is for HELCOM MONAS to assess the impact of the results from the input scenarios on the eutrophication status of the Baltic Sea. The final aim of the project is to enable the identification of cost-effective measures in the different parts of the Baltic Sea catchment area required to achieve good ecological status throughout the Baltic Sea area. The results of the project are to be used as input to the HELCOM thematic assessment on eutrophication which will be presented at HELCOM 27/2006. The Meeting is invited to: - discuss and consider the scenario provided by MARE, - assess the impact of the results from the input scenarios on the eutrophication status of the Baltic Sea, - consider further steps in the project in order to achieve the needed results for the preparation of the HELCOM thematic assessment on eutrophication which will be presented at HELCOM 27/2006. Page 2 of 13

3 NEST SCENARIOS Background Frequent discussions between MARE, HELCOM and the member states has taken place since 2004 in parallel to the scientific development of the decision support system, NEST. MARE has been presented and discussed in both The Monitoring and Assessment group (HELCOM MONAS) and in The Land-based Pollution group (HELCOM LAND). At the Heads of Delegation meeting in November 04 it was decided to take on board MARE as a HELCOM project. A number of scenarios of interest for future HELCOM work have been identified and suggested for NEST. The scenarios discussed were: 1. Implementation of existing programmes and plans PLC4-data is used for describing the baseline for the scenarios. The scenario will take into account changes in nutrient emission since year 2000, including improvement in agriculture and waste water treatment. The scenario will be based on national information provided to the MARE programme. 2. Nitrates directive implementation in the whole country/defined sensitive areas Scenarios on the land change from agriculture to forests/grassland and in fertilizer use will be made based on the national implantation plans. Further information on the national plans (considering transition time) to implement the Directive, including land use changes and manure handling, will be needed for the scenarios. 3. EU CAP implementation (even if national programmes are not finalized) CAP is under revision and it is difficult to foresee future consequences. If national plans for implementation exist, they can be used for a scenario. 4. Nitrogen surplus scenario A scenario will be developed if national data on nitrogen surplus is available in different regions. 5. Manure handling scenarios The scenarios will treat manure handling as an agriculture point source. Data on manure storage will be taken from the questionnaire. This scenario is related to the Nitrate Directive. The scenarios should be delivered in end of October 2005 in order for HELCOM MONAS 8/2005 to consider the estimated effects in the Baltic Sea at its meeting in Latvia on November The scenarios will be built on the best available data submitted by the Contracting Parties, and, therefore, the meeting emphasized the importance to receive the answers to the questionnaire and the abovementioned additional data as soon as possible. A contact person from each member state has been assigned for more detailed discussions with the MARE scientists. All contact persons were invited to a seminar in Stockholm August The aim of the meeting was to discuss the development of scenarios for the HELCOM project Assessment of Implication of Different Policy Scenarios on Nutrient Inputs and the national data needed for this work. To provide the project with data, HELCOM asked all member states to fill in a questionnaire by the end of August. Page 3 of 13

4 Conclusions We have done one scenario showing the effects on nutrient loads if maximum possible reductions of nutrient effluent from point sources in urban areas were implemented everywhere. Thus, all people in urban areas were assumed to be connected to WWTP having tertiary cleaning (a cleaning with 75% N and 90% P) was tested. For the other scenarios we did not receive the necessary information from the countries. The WWTP scenario resulted in a decrease in total N with 12% and total P with 50%. The effects on the marine ecosystems are considerable but vary greatly between basins and between ecological variables. Cyanobacterial blooms (nitrogen fixation) will decrease drastically and be eliminated in the basins adjacent to the Baltic proper. Overall primary productivity will decrease, particularly in the central basins but substantial hypoxia will still occur. The effects on the Danish straits and especially Kattegat are small, probably due to that the reduction scenario primarily affected P load and had very little effects on N loads Some of the variables calculated by the marine model using the contemporary nutrient load scenario. Nutrient concentrations are annual averages for the entire basins and Secchi depths are annually averaged offshore values. TotN TotP Secchi Prim N fix Basin depth prod µmol µmol meters g C m 2 yr -1 ton N yr -1 Bothnian Bay Bothnian Sea Baltic Proper: 0-60m Gulf of Finland Gulf of Riga Danish Straits Kattegat Baltic Proper: 60m - bottom Some of the variables calculated by the marine model using the nutrient future load reduction scenario TotN TotP Secchi Primary Nitrogen Basin depth production fixation µmol µmol meters g C m 2 yr -1 ton N yr -1 Bothnian Bay Bothnian Sea Baltic Proper: 0-60m Gulf of Finland Gulf of Riga Danish Straits Kattegat Baltic Proper: 60m - bottom Page 4 of 13

5 Modeling nutrient load scenarios In the present application the whole Baltic Sea drainage area is divided into 105 different drainage basins (Fig1). The division follows the EU JRC (Join Research Centre) data compilation for watersheds in Europe, which also is the base for the division of basins for the water framework directive (WFD). Each catchment must be supplied with data on land use, hydrology, soil type, erosion and sediment, nutrient concentrations in runoff, as well as daily temperature and precipitation data (see Fig. 2). Fig 1. A screen shot of the current drainage basin model as implemented in NEST (MCSIM v1). Shown here are the 105 sub drainage basins, summary information about drainage basin characteristic for the entire Baltic Sea drainage basin, and nutrient loads. Version 2 is not yet implemented in NEST. Fig. 2. Schematic block diagram of the model structure. Precipitation and evapotranspiration are applied to the various land covers. Water from each land cover type is routed both directly to stream flow and down to the soil water compartment. From the soil water compartment water is routed to stream flow and to the groundwater compartment, and from there on to the stream. New in version 2 is the handling of point sources. Four types of point Page 5 of 13

6 sources are handled. Sewage is calculated from the distribution of the population, urban or rural, and the degree of connection to WWTP and the effectiveness of the cleaning (primary, secondary and tertiary). The data required and used in the modeling of the Baltic Sea drainage basin in MCSIM can be divided into the following groups; General information of total catchment area (in ha) Precipitation and temperature, daily observations in order to drive the hydrology Land use data; now divided into the following land classes, Deciduous, Coniferous, Mixed forest, Herbaceous, Wetlands, Cultivated areas, Bare areas, Water, Snow and ice and Artificial areas. For each land use the following parameters are set; area (in ha), CN (Curve Number, see section about hydrology), KLSCP which is a combined value of land cover/soil type combination and type concentrations for N and P Groundwater; two boxes with storage volumes and parameters defining their tapping time as well as type concentrations for these boxes Point sources; Manure, urban and rural sewage. Validation and calibration data from the BED database. Data from the BED database was extracted and reorganized so that each drainage basin has its own database table with N and P fluxes as well as water discharge on a monthly basis in the period 1980 to Some aspects of the used data in the model must be discussed in more detail. In this supplementary documentation only the differences versus MCSIM v1 is discussed; Population and point sources The model requires input data in form of descriptive statistics for each sub area, i.e. population and point sources. In v2 the input data must also distribute the population between rural and urban. We divided the total population per watershed by means of GIS maps on light intensity by night (that is a measure for the spatial distribution of the population in a watershed) and artificial areas (cities) as well as non-artificial areas (rural). This complete new and detailed information on population distribution within 105 watersheds of the Baltic Sea catchment can be regarded as a more consistent approach to estimate point source emissions compared to the HELCOM PLC4 approach and is vital to estimate the effects of the EU sewage water directive. In v1 the official HELCOM data (PLC4) was used for the point source calculations within each drainage basin. In v2 this is changed to actively calculate the N,P load to the runoff by dividing the point sources into three different types; manure, rural sewage and urban sewage. Manure is calculated form the number of cattle (dairy cows and other cows) and pigs (slaughter pigs and sows) and the emission of N and P from each animal to stream water on a monthly basis (yearly emission/12). Data on the number of cows per country was taken from EUROSTAT; emission numbers for individual livestock are taken from FOASTAT and reports from the Swedish Agriculture University..( portal&_schema=portal). Emissions of N and P for these animals can be seen in Table 1. Page 6 of 13

7 Table 1; Emission of N and P to streams from cows and pigs in the investigated countries. Figures are in kg animal -1 year -1. Data was taken from EUROSTAT, FOASTAT and the Swedish Agricultural University Country Milk cows Other cattle Slaughter pigs Sows N P N P N P N P Bel Cze Den Est Fin Ger Lat Lit Nor Pol Rus Swe National livestock numbers were distributed in proportion to the cultivated areas per watershed. This is obviously an oversimplification since in many countries livestock is not at all uniformly distributed and, thus, more information on the spatial distribution of livestock per watershed is urgently needed to improve these first model runs. It should be emphasized here that although the retention of manure from cultivated areas is high, the primary emissions per head is some times higher for a livestock unit than for a human unit. In cases where the model underestimates the contribution from manure, the contribution of urban sewage will be automatically overestimated, since the model is calibrate vs. observed BED river nutrient data. The retention or the actual load of N and P entering the stream was assumed to be similar in all catchments, 83% retention for N and 97% for P (Johnes et al, 1996). Rural sewage was calculated from the population distribution and that each person emits 3.94 kg N and 1.16 kg P pear year (Johnes et al, 1996). The retention for these emissions was assumed to be same as for manure. Urban sewage was calculated from the population distribution and the number of people that is connected to a WWTP (Waste Water Treatment Plant). The country based connectivity to WWTP and degree of cleaning (primary, secondary, tertiary) was taken from EUROSTAT ( portal&_schema=portal) and distributed proportional to the population density in each watershed. Primary cleaning reduces N with 19%, P with 15%, secondary cleaning N, 37.5% and P, 35% and tertiary cleaning N, 75% and P 90%. Calculation of N and P loads In the marine (Baltic Sea) model organic and inorganic N and P are handled differently. The MCSIM model, on the other hand, does not calculate loads for these two forms directly but extracts information from the total and inorganic N and P loads. This is a problem since information is lacking on how inorganic and organic forms of N and P are distributed from point sources in the Baltic Sea drainage basins. The MCSIM model assumes that type concentrations are of the inorganic forms of N and P and that organic forms are added Page 7 of 13

8 through erosion and point sources. If the distribution between inorganic and organic forms is no correct as compared to observed data, point sources must be added to either the inorganic or the organic load of N and P. In the current version of the model, point sources are distributed between inorganic/organic N and P to fit the observed data. If the distribution between inorganic and organic is then not correct, erosion and sediment yield is adjusted to fit the observed data. If the load is too high or too low riverine retention is adjusted to finally fit the data. This is not an ideal approach; it would be much better to have precise knowledge on erosion, sediment yields and the riverine retention and to fit data only on the distribution of organic/inorganic form of N and P and the type concentrations. Scenario calculations The MCSIM model can be used to calculate several types of scenarios, in principal different types of scenarios can be tested with the new version 2; Changing land use from one class into another is possible if the change is not too large (10-20%). Otherwise, the groundwater N&P type concentrations have to be changed. The scenario itself can include the levels of nutrient reduction or increase. The simplest way to produce such a scenario is to test what happens if e.g. the nutrient losses from a certain land use are reduced with 5%, 10% etc. If the changes are assumed to be large, the groundwater N&P type concentrations have to be changed in this scenario as well. Thirdly reduction or increase in nutrient loads from point sources is another possible simulation change. Climate changes, like increased/decreased rainfall and/or temperature If there is a need of knowing detailed amendment strategies for achieving a certain nutrient reduction, the CSIM-model cannot tackle that since this large scale model is designed to address the relative role of point sources and diffusive sources in a Baltic Sea wide scale, i.e., an estimate to be done between 105 watersheds. Hence, process-based models should be used for creating such information. The complexity of large catchments makes it impossible to make expert judgments within these as well. Table 2A. Nutrient runoff (tons year -1 ) calculated the model with d data for the calibration period ( Country DIN Tot-N DIP Tot-P Bel 17,175 42, ,048 Cze 4,156 7, Den 57,520 76,266 1,311 2,512 Est 13,194 23, Fin 36,846 69,847 1,773 4,417 Ger 20,962 34,400 1,624 3,046 Lat 30,175 50, ,130 Lit 20,027 42, ,450 Nor 1,718 3, Pol 131, ,260 8,587 18,405 Rus 43,052 62,707 1,509 3,497 Swe 37,686 80, ,244 Sum 414, ,906 18,352 41,056 Page 8 of 13

9 Table 2B. Nutrient runoff (tons year -1 ) calculated by the model with maximum reductions from all point sources Country DIN Tot-N DIP Tot-P Bel 14,320 36, Cze 3,132 5, Den 56,397 74, ,810 Est 12,529 21, Fin 36,089 67,365 1,494 3,457 Ger 20,141 32,637 1,381 2,458 Lat 29,314 48, Lit 18,091 38, Nor 1,710 3, Pol 101, ,206 2,243 4,686 Rus 41,050 57, ,383 Swe 37,340 78, ,748 Sum 371, ,701 8,918 18,897 With the current version, the scenario where all people in urban areas were assumed to be connected to WWTP having tertiary cleaning was tested. This resulted in a decrease in total N with 12% and total P with 50% (Table 2B). It should be emphasized again that a cleaning with 75% N and 90% P for all human emissions from cities corresponds to a complete connectedness of all urban people to WWTP without losses on its way as well as most modern cleaning techniques available. This first runs of the MSCIM v2 has been compared to the MONERIS model runs for the Vistula watershed. The total emissions of P into the Vistula watershed has been estimated by MONERIS with tons P of which tons come from urban areas. MCSIM estimates the emissions with tons P and tons P from urban areas, i.e., there is good agreement between both models with respect to emissions. The MONERIS model estimate a P decrease with some 1600 tons in a green scenario whereas the MSCIM run estimate a reduction with almost 5000 tons P. This discrepancy can be explained by the unrealistic high P cleaning in the 90% reduction scenario for all urban people in the Vistula watershed and can be discussed accordingly. Atmospheric depositions Basin-wise contemporary (average ) estimates of inorganic nitrogen atmospheric deposition were obtained from EMEP ( thanks to assistance by Jerzy Bartnicki). Input of labile organic nitrogen from atmosphere is assumed 20% that of inorganic nitrogen, while for phosphorus the atmospheric deposition is assumed to deliver 15 kg P km -1 yr -1 evenly distributed over all basins as phosphate (Savchuk 2005). The nitrogen depositions for 2010 were calculated by Bartnicki & van Loon (2005). The same assumptions about organic N and P as for the contemporary situation were used Page 9 of 13

10 Table 3A. Contemporary atmospheric nutrient depositions to the sub-basins of the Baltic Sea Basin Lab Org N DIN TotN DIP TotP Bothnian 1,764 8,820 10, ,167 Bay Bothnian 5,439 27,197 32,636 1,178 65,272 Sea Baltic 25, , ,857 3, ,715 Proper Gulf of 2,566 12,828 15, ,788 Finland Gulf of 2,003 10,015 12, ,036 Riga Danish 4,742 23,711 28, ,906 Straits Kattegat 4,073 20,364 24, ,874 Table 3B. Future (2010) atmospheric nutrient depositions to the sub-basins of the Baltic Sea used in the marine model scenario. Basin Lab Org N DIN TotN DIP TotP Bothnian 1,580 7,900 9, ,960 Bay Bothnian 5,140 25,700 30,840 1,178 61,680 Sea Baltic 25, , ,400 3, ,800 Proper Gulf of 3,000 15,000 18, ,000 Finland Gulf of 2,200 11,000 13, ,400 Riga Danish 3,960 19,800 23, ,520 Straits Kattegat 3,320 16,600 19, ,840 Page 10 of 13

11 Effects on the marine ecosystems The nutrient load scenarios were used as inputs to the coupled physical-biogeochemical model BALTSEM, implemented in NEST (Fig3). Fig 3. A screen shot of the current marine model as implemented in NEST (BALTSEM). Results describing contemporary environmental conditions are shown in Table 4A while the effects of the nutrient load scenarios are shown in Table 4B. Page 11 of 13

12 Table 4A. Some of the variables calculated by the marine model using the contemporary nutrient load scenario. Nutrient concentrations are annual averages for the entire basins and Secchi depths are annually averaged offshore values. TotN TotP Secchi Prim N fix Basin depth prod µmol µmol meters g C m 2 yr -1 ton N yr -1 Bothnian Bay Bothnian Sea Baltic Proper: 0-60m Gulf of Finland Gulf of Riga Danish Straits Kattegat Baltic Proper: 60m - bottom Table 4B. Some of the variables calculated by the marine model using the nutrient future load reduction scenario TotN TotP Secchi Primary Nitrogen Basin depth production fixation µmol µmol meters g C m 2 yr -1 ton N yr -1 Bothnian Bay Bothnian Sea Baltic Proper: 0-60m Gulf of Finland Gulf of Riga Danish Straits Kattegat Baltic Proper: 60m - bottom These results show majors changes in most basins. Phosphorus (totp) concentrations will decrease everywhere, most pronounced in the Baltic proper and adjacent basins (Gulfs of Finland and Riga) between 40-50%. The effects on nitrogen (totn) are much smaller with even increasing concentrations in the Gulfs due to that here severe P limitation creates an excess of N (similar to the situation in the Bothnian Bay today) Primary production will decrease with about 20% in Bothnian Bay, with a third in the Baltic proper and more than 50% in the Gulfs. A 10% reduction in the still N limited Kattegat will occur, according to the model. Nitrogen fixation by cyanobacteria will decrease by 80% in the Baltic proper and be virtually eliminated in all other Basins. The hypoxic areas (O 2 < 2 ml/l) in the Baltic proper will decrease from 50,000 to 30,000 km2. Water transparencies (Secchi depths) show in these tables are not a model variable but calculated from empirical relations to N and P concentrations. Secchi depth increases in all basins, most pronounced in the Gulf of Riga. Page 12 of 13

13 References Bartnicki, J. and M. van Loon (2005) Estimation of atmospheric nitrogen deposition to the Baltic Sea in 2010 based on agreed emission ceilings under the EU NEC Directive and the Gothenburg Protocol. Met.no note No. 26 (ISSN ) Johnes, P., Moss, B., Phillips, G., 1996; The determination of total nitrogen and total phosphorus concentrations in freshwaters from land use, stock headage and population data: testing of a model for use in conservation and water quality management, Freshwater Biology, 36, MCSIM documentation v1; Lars Rahm, Christoph Humborg, Stefan Löfgren, Carl-Magnus Mörth and Erik Smedberg. MCSIM Documentation. Technical report, BALTSEM documentation: Oleg Savchuk. Simple As Necessary Long-Term large-scale simulation model of the nitrogen and phosphorus biogeochemical cycles in the Baltic Sea. Technical report, version 2, June Savchuk, O.P Resolving the Baltic Sea into 7 sub basins: N and P budgets for J. Mar. Syst., 56: Page 13 of 13