Environmental impacts of eco-local food systems final report from BERAS Work Package 2 Draft version last updated 27 September 2005

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1 Environmental impacts of eco-local food systems final report from BERAS Work Package 2 Draft version last updated 27 September 25 Editors: Artur Granstedt, Olof Thomsson and Thomas Schneider Abstract Already established initiatives with Ecological Recycling Agriculture (ERA) and local food systems in the eight EU-countries in the Baltic Sea drainage area are evaluate during the project period. Surplus of nitrogen was 5 % lower per ha and year on Swedish and Finnish BERAS-farms compared to the average agriculture (36 kg compared with 79 for Swedish and 38 kg compared to 73 for Finnish agriculture with the same animal density of.6 au/ha) and it was no surplus of P. For all studied 36 farms in the eight countries, the average surplus of nitrogen was 36 kg compared to the average of 56 kg for the eight countries today, which include the low intensive agriculture in the Baltic countries and Poland. All BERAS-farms with an animal density below.75 AU per ha have a surplus below 5 kg N/ha and can be defined as ERA-farms with animal production based on minimum 85 % own fodder. An estimated average loss of 3-4 % NH4 of the nitrogen exudates from the animal production gives a calculated reduction of nitrogen leaching with 7-75 % on BERAS-farms compared to the average Swedish agriculture farms (an average N- leakage of 7-9 kg compared with 28-3 kg). The same calculation made for the all eight BERAS countries gave a reduction of nitrogen leaching with 45-5 % on BERAS-farms compared to the studied average Baltic Sea agriculture which include regions with until now very extensive agriculture. Two scenarios were calculated for the BERAS countries; 1) business as usual where the Baltic Countries and Poland convert to the same structure and use of resources as Sweden and Finland, and 2) the whole studied Baltic Sea agriculture convert to ERA similar to the BERAS-farms. The conventional scenario gave an increased pollution of Nitrogen and Phosphorus from agriculture. The Nitrogen leakage would increase with 5 %. The ERA scenario gave a reduction of nitrogen leakage from agriculture with 5 % and an elimination of the surplus of Phosphorus. Four Swedish food basket scenarios are presenting results for Nitrogen surplus, Global warming impact and Consumption of primary energy resources. Scenario 2, where all the food is produced on ERA-farms, would give a global warming impact of 8 kg CO 2 - equivalents per capita and year compared to 9 kg in Scenario 1 with conventional agriculture. Scenario 3 with food from only ERA-farms and local processing and distribution gave a global warming impact of 7 kg CO 2 -equivalents per capita and year. Scenario 4 with food from only ERA-farms, more vegetable and less meat consumption and local processing and distribution gave a global warming impact of 5 kg CO 2 -equivalents per capita and year, a reduction by about 45 % compared to Scenario 1.

2 Contents 1. Executive summary...3 BERAS the project and cases...3 BERAS Work Package 2 environmental assessment...4 Results and discussion...7 General conclusions Plant nutrient balance studies...12 Background and problems...12 Material and Methods...14 Results of plant nutrient balances in the BERAS countries...16 Discussion and conclusions...29 Evaluation of nitrogen utilization by means of the concept of primary production balance31 References Effects of 1 % organic production on Funen, Denmark...37 Introduction...37 Methods...37 Results...37 References Nitrogen and phosphorus leakage in ecological recycling agriculture...5 Introduction...5 Methods...5 Results and discussion...53 Conclusions...57 References Global warming and fossil energy use...59 Methodology...59 Ecological Recycling Agriculture...6 Transports of locally produced food in Järna...64 Small-scale food processing industries in Järna...72 Global warming impact and primary energy consumption in a local food chain in Järna...74 References Organic waste management studies...78 Inventory in Juva...78 Biogas plant in Järna...83 Possibilities for developed recycling and renewable energy production in Juva and Järna Consumer surveys in Juva and Järna for identification of eco-local food baskets...87 Introduction...87 Methodology...88 Results and discussion...89 Conclusions...99 References Food basket scenarios...11 Food basket scenario, Järna Sweden...11 Food basket scenario, Juva Finland...16 Appendix 1. Farm gate nutrient balances

3 1. Executive summary This chapter give a brief summary of the studies and the results presented in the report. Since the report only concern the environmental assessment part of the project, this summary first give a comprehensive presentation of the whole project. BERAS the project and cases The BERAS project is a research and developing project. The aim of the project is to develop a knowledge base regarding possible means of significantly decreasing consumption of nonrenewable energy and other limited resources and of reducing the negative environmental impacts on the environment based on practical examples of ecological, economical and sociological sustainability in the real life. The goal is to reduce nutrient leaching to the water systems and emissions of reactive nitrogen and greenhouse gases to the atmosphere and protect the biological diversity of agricultural production, distribution, processing and consumption of food. At the same time, the measures identified should enhance landscape diversity and promote local economies and employment in rural areas of the Baltic Sea countries. The work is based on practical case studies, primarily in selected rural areas, complemented by selected reference farms in each country, where practical initiatives have been taken to bring about lifestyle changes through the whole of the food chain from primary agricultural production, via processing, distribution and storage to final consumption based on ecological production (agriculture and processing), recycling and a minimisation of transport systems. The term ecological is here used as an synonym to organic, which describe a type of food production that use nor chemical pesticides nor chemical fertilisers. Methodological approach The BERAS project includes five Work Packages (WPs). The first WP (1) promote selected, already established local ecological food initiatives and recycling farms in each country and exchange of experience with other initiatives in and between the project countries. Obstacles are identified and learning how solving such problems and developing initiatives further are promoted through confrontation with other similar initiatives and with the experts participating. The second WP (2) study what environmental benefits can be achieved through local ecological consumption, processing and ecological integrated recycling farming, in comparison with conventional food systems. Energy use, greenhouse gas emissions, surplus and emissions of reactive nitrogen (air/water pollution) and surplus of phosphorus compounds is quantified for the agriculture society system and related to the food consumption. The main part of this work is done for Sweden and in more limited extent for Finland and in further lower degree for the other BERAS countries related to the amount of economical resources for the project, but the results can be utilised for all countries. The third WP (3) evaluates market economic aspects, economic consequences at the societal level and consequences from a natural resource economy and the fourth WP (4) the consequences at the societal level including rural development and job opportunities. The fifth and final WP (5) will present an Agenda with recommendation for implementations and dissemination. Locations and criteria of activities Studies of the whole food systems are located in all EU member states around the Baltic Sea: (1) Järna, Stockholm county in Sweden; (2) Vassmolösa, Kalmar county in Sweden; (3) Juva, Mikkeli county in Finland; (4) Funen county, Denmark; (5) Bioranch Zempow Brandenburg in Germany; (6) Kluczbork and (7) Brodniza in Poland; (8) Raseiniai in Lithuania; (9) Organic farmer organisataion in Aizkraukle district in Latvia; (1) Pahkla Camphill village, Prillimäe in Estonia. Initially 35 reference farms were selected. They were mainly chosen for 3

4 calculations of plant nutrient balances and selected to cover the main environmental and farming conditions and together also include a big part of the basic food production in the countries respectively. The criteria of the BERAS-farms was that they should fulfil a high degree of plant nutrient recycling based on a balance between animal and crop production and a low part of purchased fodder. Dissemination Farmers involved in the project were continuously informed of results achieved and receive support for their activities but also dissemination through publications and adviser service organisations. Dissemination of results and promotion of further similar initiatives will be aimed at regional and local policymakers (special working with spatial planning), the food industry and distribution, and, at the grassroots level, at consumers, farmers and small-scale actors along the food chain, to encourage a transition to a more sustainable lifestyle in the agro-food sector. BERAS Work Package 2 environmental assessment The objective of Work Package 2 in BERAS was to promote reduced consumption of limited resources, reduced emission of nitrogen and phosphorus compounds to the Baltic Sea and reduced emission of greenhouse gases, and to promote the biological diversity of life within the food chain. This was realised through evaluation and demonstration of the potential of ecological recycling-based agriculture, local and regional processing, distribution and consumption. Already established initiatives in the countries involved were utilised and promoted during the project period. The evaluation of the potential for reduced losses of nitrogen and phosphorus was in this project mainly based on plant nutrient balances on ecological recycling agriculture farms (ERA-farms) with different agricultural conditions and production specializations in the eight BERAS countries. The nutrient balances give information about the potential risk for leaching and the potential risk of nitrogen emissions to the atmosphere when assuming a steady state in soil over a longer period of time (Granstedt et al. 24). In the BERAS report 2 Effective recycling agriculture around the Baltic sea (Granstedt, et al 24), it was emphasised that the consequences of mistakes in terms of agricultural specialisation must be taken into consideration in the new EU countries that are about to introduce changes in their agricultural sectors. Otherwise, there may, according to the final conclusions of the INTERREG IIIB BERNET project Baltic Eutrophication Research Network (Fyn s Amt, 22), be a dramatic increase in loadings also from these countries like Poland and the Baltic states. If we instead want to reduce the leakage and also emissions of reactive nitrogen to the atmosphere by 5 %, a reduction of the surplus of nutrient with more than 5 % is in a longer perspective necessary. For calculation of the efficiency of recycling, Pentti Seuri developed a method for primary nutrient efficiency within the BERAS project. The results of plant nutrient balances on farm level (i.e. farm gate balances) thus were complemented by this measure for nitrogen, which gives information of how much more nitrogen is harvested in the yield than is imported in external resources. These calculated results were also supplemented with measurements of nutrient leaching. To give full results, a scenario study of a conversion to a purely organic and nutrient self-supporting system of the whole agricultural system on the Danish island of Fyn was performed. 4

5 The assessment of global warming impact and consumption of primary energy resources were performed for the Swedish BERAS-farms and average agriculture, and Swedish cases of local processing, distribution and consumption. In order to put the environmental studies in relation to the consumers consumption of food, two scenario studies were performed; one in Järna and one in Juva. The scenarios reflect the difference in the environmental impacts of conventional and alternative systems for agriculture, processing, distribution in combination with two different food baskets (food consumption profiles). The alternative food baskets (containing more vegetables and less and different kinds of meat compared to the conventional) were based on consumer surveys performed on environmental conscious households in Järna and Juva. Also the organic waste management was judged as an important part of the food system. A higher degree of recycling of nutrients could lead to reduced emission to water and to atmosphere. Therefore the possibility of recycling wastes from local food processing, distribution and big kitchens was inventoried in Juva and discussed both for Juva and Järna. Partners and researchers BERAS coordinator: Artur Granstedt, arturgranstedt@jdb.se WP2 coordinator: Olof Thomsson, oloft@gotland.com Researchers: Assoc. Prof. Artur Granstedt, PhD Thomas Schneider, PhD, thomas.schneider@natgeo.su.se Olof Thomsson, PhD Winfried Schäfer, PhD Christine Wallgren, MSc Pentti Seuri, MSc Hanna-Riikka Tuhkanen, MSc Miia Kuisma, MSc Annamari Hannula, MSc Tiina Lehto, MSc Jaroslaw Stalenga, PhD Assoc. Prof. Jozef Tyburski, PhD Holger Fischer, MSc Ib Sillebak Kristensen, PhD Ole Tyrsted Jørgensen, MSc Principles of ERA systems The concept of ecological recycling agriculture (ERA) was presented in the BERASbackground report (Granstedt et al. 24) as an alternative to conventional agriculture. ERA agriculture will produce food and other products on following basic ecological principles: 1. Diversity of life 2. Renewable energy. 3. Recycling of plant nutrients In conventional agriculture we have the problem of damaging of the biological diversity through use of pesticides, consumption of energy resources, emissions of greenhouse gases and other input resource as a consequence, using up limited plant nutrient resources and to high emissions of plant nutrients in the environment. 5

6 The reduced recycling and increased surplus of nutrients caused of this separation increased after 195 and culminated in Sweden, Finland and Denmark until 198 and are after that on same level. This is illustrated through examples of nutrient balances in the background report as a more and more linear flows of nutrients. During the same more special forms of agriculture based on non renewable energy and use of pesticides was introduced. An ideal frame for an ERA farm (or farms in close cooperation similar to one farm unit) is adapted to the human consumption. For our European food consumption it is about 85 % of farm land used for fodder production and animal production (animal density) limited to this own fodder production and about 15 % of farm land used for crop production for sale according to the example from Skilleby-Yttereneby farm in Järna presented in the background report (Granstedt et al 24). The lower demand of external input of nitrogen depending on higher degree of internal recycling within the system is covered through biological nitrogen fixation of mainly clover/grass leys. For phosphorus and potassium it is only a limited deficit in the balance between input and output. Most of the amount the minerals are recycled with manure within the farm. The limited net export of phosphorus and other nutrients seemed to be compensated by the withering processes in most soils but a recycling of food residues could decrease these losses from the system further (Granstedt, 2). During practical condition we have a variation between farms and it is difficult to find the ideal ERA-farm in reality. It is necessary to set up realistic limits for inputs of external resources which can be realised in practise but that also fulfil the need of high internal recycling with the potential of reduced losses as a consequence. Even if the ideal concept is total self sufficiency with fodder some smaller inputs of seeds and fodder stuffs must be accepted under real conditions. A limitation of purchased fodder was set to 15 % of total used fodder for selection of the BERAS-farms. In addition to that it is also necessary that a part of the agricultural land is used for bread-grain or other cash crops for direct human consumption. Not all the selected farms fulfilled this condition during the whole project time (22-24) and this will be further discussed together with the results. The principal difference between conventional agriculture and the ERA-farms on system level are that in conventional agriculture crop and animal productions are more or less separated between different groups of farms on ERA-farms animal and crop production are integrated within each farm. Comparison have be done between these two systems (the separated conventional and integrated ecological system) but based on the same average animal density for all the farms together in the compared systems respectively and related to the human consumption of both animal and vegetable agricultural products. For Sweden this comparison was done with the help of a conventional food basket and an alternative food basket based on a more locally produced and vegetarian diet. In these studies the potential of reduced nutrient surplus and losses of nitrogen based on ERAfarm criteria will be evaluated during the different conditions in the production areas in the eight BERAS countries. Depending on the closed relation between animal density and surplus of plant nutrient which result in losses, the comparing with the conventional agriculture system with separated crop and animal production will be based on the same average relation between animal and vegetable crop production. 6

7 Results and discussion Nutrient balances influence of production systems (Chapter 2, 3, 4) Potential of ERA (ecological recycling agriculture). Surplus of nitrogen was 5 % lower per ha and year on Swedish and Finnish B-ERAS-farms compared to the average agriculture (36 kg compared with 79 for Swedish and 38 kg compared to 73 for Finnish agriculture with the same animal density of.6 au/ha) and it was no surplus at al of P. For all studied 36 farms in the eight BERAS countries the average surplus of nitrogen was 36 kg compared to the average of 56 kg for the eight BERAS countries which include the low intensive agriculture in the Baltic countries and Poland. All BERAS-farms with an animal density below.75 AU per ha have a surplus below 5 kg N/ha and can be defined as ERA-farms with animal production based on minimum 85 % own fodder. An estimated average loss of 3-4 % NH4 of the nitrogen exudates from the animal production gives a calculated reduction of nitrogen leaching with 7-75 % on BERAS farms compared to the average Swedish agriculture farms ( an average N- leakage of 7-9 kg compared with 28 3 kg). The same calculation made for the all eight BERAS countries gave a reduction of nitrogen leaching with 45-5 % on BERAS farms compared to the studied average Baltic Sea agriculture which include regions with until now very extensive agriculture. Two scenarios were calculated for the BERAS countries, business as usual where Baltic Countries and Poland convert to the same structure and use of resources as Sweden and Finland and the other alternative where the whole studied Baltic Sea agriculture convert to ERA agriculture like the BERAS farms. The conventional scenario gave an increased pollution of Nitrogen and Phosphorus from agriculture. The Nitrogen leakage would increase with 5 percent. The ERA scenario gave a reduction of nitrogen leakage from agriculture with 5 % and an elimination of the surplus of Phosphorus. Phosphorus leakage is specially related to farms with high animal density. The conventional scenario would give an increased production of crops for direct human consumption of about 3 % and increased animal production of about 1 %. The alternative BERA Scenario with a reduced nutrient leakage should result in a decreased crop production of 2 % and decreased and more ruminant meat dominated animal production of 3 % in the BERAS-countries. The lower production in the BERAS scenario would reduce the overproduction in Europe. Using agriculture land in the Baltic countries that today is not used could compensate this production loss. One scenario special for Fyn county was developed based on an earlier bigger study about converting the whole agriculture in Denmark to organic farming according ERA principles with total self-sufficiency with fodder and production related to the national food consumption. This gave, like the scenario for the whole BERAS study region, a reduction of the nitrogen surplus with 5 % but here related to Danish conditions. The balance contributed to 35 kg N-leaching per ha, around a 5 % reduction compared to the present situation in year 22 in Denmark. In the scenario without external P-inputs the P-balance is about 6 kg P/ha. 7

8 Global warming and energy use (Chapter 5) The global warming impact, measured in Global Warming Potentials (GWP) as CO 2 equivalents, is reported per kg products exported from the farm and per hectare. In both cases the GWP were lower for the average BERAS-farm than for the average Swedish agriculture (8 and 82 % lower respectively). The difference was reduced by the larger emission of methane from animals. The larger share of ruminant animals explains the difference on the BERAS-farms, compared to average Swedish agriculture having a larger part of monogastric animals which emit very little methane. The consumption of primary energy counted per kg product and per ha is substantially lower on the BERAS-farms in average compared to average Swedish agriculture (53 and 57 % respectively). The most important reason is the lesser use of fire oil (for drying of grain), no use of imported fertilisers and lower use of electricity. One sub-study describes how locally produced and consumed food in the food system case Järna, Sweden is transported, and how much fossil energy this transportation has used. The study comprises vegetables, potatoes and root crops from four local growers; milk and dairy products from Järna Dairy; bread from Saltå Mill & Bakery; and meat from animal keepers in the vicinity of Järna. The products are collected at the different producers and delivered to stores, schools and other large kitchens in both the Järna area and in Stockholm (about 6 km away). Counted per kg bread both the GWP and use of primary energy were lower for the average local bread distribution from Saltå Mill and Bakery (3 and 38 % respectively). Counted per kg vegetables both the GWP and use of primary energy were lower for the average local distribution from the gardens and farms (96 and 92 % respectively). In contrast counted per kg meat from animal keepers in the vicinity of Järna, depending on longer distances to the regional slaughters, both the GWP and use of primary energy were higher. Counted per kg milk products both the GWP and use of primary energy were lower for the average local distribution from Nibble dairy in Järna (77 and 19 % respectively). Improving nutrient balances by waste management (Chapter 6) An inventory was conducted at Juva municipality in Finland to determine the possibilities for recycling biowaste (organic waste) produced by local food actors back into agriculture. The examined food actors belong to the food chain after primary production (agriculture): food processors, grocery stores, schools, municipal kitchens, and private consumers. The research methods used are waste flow and substance flow study. Alternative treatment processes to recycling of nutrients and humus of biowaste are composting and biogas treatment (centralized or small-scale treatment or co-digestion plant). The conventional treatment of biowaste and wastewater cause nutrient losses and the most nutrients in the treated biowaste do not become available to plants. The composting process mainly affects the amount of nitrogen. The loss of nitrogen in composting can be as much as 5%. From the environmental viewpoint, separate urine collection would be preferable to the conventional system. It would increase the recyclable nutrient amounts to fields and at the same time decrease the emissions into water systems. In addition, phosphorous would be in more usable form for plants and risk of heavy metal contamination would be less compared to sewage sludge. The small scale biogas plant on farm level established as a prototype in Järna seemed to be the best solution for recycling of the solid fractions of nutrients from the human food sector 8

9 (local processors, ecological public kitchen), to reduce emissions of greenhouse gases and also have a good control against contaminations of pathogens and harmful substances. Influence of consumption patterns (Chapter 7, 8) Results from food basket surveys in Sweden and Finland Our food habits are, unquestionably, important both for the health and for the environment. That is recognised as one of the starting points in BERAS. The main objective of the consumer surveys was to put together realistic food baskets (consumption profiles) for a Swedish and a Finnish case, containing mainly locally and ecologically produced foodstuffs. The case studies were performed in Juva, Finland and Järna, Sweden the same sites used for many other studies in the BERAS project. For a more extended presentation of the sites see Seppänen (ed. 24). Both the municipality of Juva and the community of Järna have around 75 inhabitants. We conclude that the consumption profile of the participating households in Sweden differs more from the average Swedish consumers than was the case in the Finish study. However, also the Finnish households participating in this study buy more organic products than ordinary Finnish households. The food consumption profile of the Järna households seems to follow the diets suggested in the Nordic Nutrition Recommendations (NNR, 24) and in the S.M.A.R.T. project (CTN, 24). These households buy a larger share of vegetables (less meat), less empty calories, more ecological food, right vegetables (e.g. more legumes and root crops, and less lettuce and cucumbers) and less transported food, compared to the national average food. Scenarios are presenting results for Nitrogen surplus, Global Warming Potentials and Consumption of primary nutrient resources. The scenarios are: 1. Average Swedish food consumption, Average Swedish agriculture 22-24, and Conventional food processing and transports 2. Average Swedish food consumption, ERA farms, and Conventional food processing and transports 3. Average Swedish food consumption, ERA farms, and Local (small-scale) food processing and transports 4. Eco-local food consumption (presented in Chapter 1), ERA farms, and Local (smallscale) food processing and transports One scenario based on BERAS farms and with the same total meat consumption (but with a higher share of ruminant meat) will have an unrealistic acreage of arable land in Sweden as a consequence of the lower gross productivity on the studied BERAS farms. The conventional system use imports from farms outside Sweden but this aspect is not included here. However, in a study based on Järna type alternative consumption pattern and BERAS farms the need of agricultural arable land would instead decrease with almost 4 % compared with the situation of to day (figure 8-1, 8-2 and 8-3). Nutrient balances in Scenario 2 and 3 with food from only ERA-farms gave a nitrogen surplus of 14 kg and year compared with 22 kg for average agriculture counted per capita or 26 kg compared with 8 kg counted per ha (a reduction with about 35 % and 65 % respectively). Scenario 4 with reduced agricultural arable land gave a surplus of 8 kg counted per capita and 42 kg counted per ha and year (a reduction with about 65 % and 45 % respectively). The losses of ammoniac from manure is about the same in the compared systems and results in 9

10 lower losses and leaching of nitrogen from fields from the ERA farms compared to the conventional system than the above figures. Global warming calculations in scenario 2 with food from only ERA-farms would give a global warming potential of 8 kg CO 2 equivalents per capita compared with 9 kg CO 2 equivalents per capita and year in scenario 1 with conventional consumption. Scenario 3 with food from only ERA-farms and local processing and distribution gave a global warming potential of 7 kg CO 2 equivalents per capita compared with 9 kg CO 2 equivalents per capita and year. Scenario 4 with food from only ERA-farms, more vegetable and less meat consumption and local processing and distribution gave a global warming potential of 5 kg CO 2 equivalents per capita compared with 9 kg CO 2 equivalents per capita and year (a reduction with about 45 %). Primary energy calculations in scenario 2 with food from only ERA-farms and 3 with also local distribution and processing gave a consumption of primary energy resources of 5 GJ per capita compared with 8 GJ in the average food system (a reduction with about 4 %. Scenario 4 with food from only ERA-farms and local processing and distribution and eco local (more vegetable and less meat consumption) consumption gave a consumption of primary energy resources of 3 GJ per capita and year (a reduction with about 6 %). General conclusions Already established initiatives with Ecological Recycling Agriculture (ERA) and local food systems in the eight EU-countries in the Baltic Sea drainage area are evaluate during the project period. Surplus of nitrogen was 5 % lower per ha and year on Swedish and Finnish BERAS-farms compared to the average agriculture (36 kg compared with 79 for Swedish and 38 kg compared to 73 for Finnish agriculture with the same animal density of.6 au/ha) and it was no surplus of P. For all studied 36 farms in the eight BERAS countries the average surplus of nitrogen was 36 kg compared to the average of 56 kg for the eight BERAS countries which include the low intensive agriculture in the Baltic countries and Poland. All BERAS-farms with an animal density below.75 AU per ha have a surplus below 5 kg N/ha and can be defined as ERA-farms with animal production based on minimum 85 % own fodder. An estimated average loss of 3-4 % NH4 of the nitrogen exudates from the animal production gives a calculated reduction of nitrogen leaching with 7-75 % on BERAS farms compared to the average Swedish agriculture farms (an average N- leakage of 7-9 kg compared with 28-3 kg). The same calculation made for the all eight BERAS countries gave a reduction of nitrogen leaching with 45-5 % on BERAS-farms compared to the studied average Baltic Sea agriculture which include regions with until now very extensive agriculture. Two scenarios were calculated for the BERAS countries, business as usual where Baltic Countries and Poland convert to the same structure and use of resources as Sweden and Finland and the other alternative where the whole studied Baltic Sea agriculture convert to ERA agriculture like the BERAS farms. The conventional scenario gave an increased pollution of Nitrogen and Phosphorus from agriculture. The Nitrogen leakage would increase with 5 percent. The ERA scenario gave a reduction of nitrogen leakage from agriculture with 5 % and an elimination of the surplus of Phosphorus. Phosphorus leakage is specially related to farms with high animal density. 1

11 Scenarios are presenting results for Nitrogen surplus, Global Warming Potentials and Consumption of primary nutrient resources. Global warming calculations in scenario 2 with food from only ERA-farms would give a global warming potential of 8 kg CO 2 equivalents per capita compared with 9 kg CO 2 equivalents per capita and year in scenario 1 with conventional consumption. Scenario 3 with food from only ERA-farms and local processing and distribution gave a global warming potential of 7 kg CO 2 equivalents per capita compared with 9 kg CO 2 equivalents per capita and year. Scenario 4 with food from only ERA-farms, more vegetable and less meat consumption and local processing and distribution gave a global warming potential of 5 kg CO 2 equivalents per capita compared with 9 kg CO 2 equivalents per capita and year (a reduction with about 45 %). 11

12 2. Plant nutrient balance studies Artur Granstedt (where nothing else is stated) Background and problems This project focuses on the potential of reducing nitrogen and phosphorus load to the Baltic Sea by increasing the efficiency of recycling within the agricultural system, according to the principles of organic farming with an integration of crop and animal production with selfsufficiency of fodder. The BERAS background report, Effective recycling agriculture around the Baltic Sea (Granstedt, et al 24) gives an overview of the main objectives of the current project and the problems to be solved. The Baltic Sea countries have undertaken internationally efforts, within HELCOM and OSPARCOM, to halve their discharges of nitrogen and to reduce their discharges of phosphorus from human activities. The countries have not achieved these goals during the target period and no improvement has been observed until the year 2 according to the Executive Summary of the Fourth Baltic Sea Pollution Load Compilation. Measurements in streams to the Baltic Sea show no significant decrease of the total load (HELCOM, 1998; 24). BERAS countries in this project include all countries within the Baltic Sea drainage area which are EU-member and exclude the regions belonged to Russia and Belarus. The focus is to reduce the loadings of nitrogen and phosphorus to surface waters and the Baltic Sea. Well established ecological recycling model farms focusing on different production areas has been used to document to what extent emissions can be reduced and to serve as possible examples in the eight BERAS countries. The measures were taken account present growing conditions, the risks of nutrient losses, and the proximity of watercourses, lakes and sea areas. The ultimate aims is also to finally analyse possible changes in agricultural structures which will maximize recycling and minimize losses of nitrogen and phosphorus compounds on regional and country level and for the whole Baltic Sea drainage area. This is the reason way we in this introduction analyse the present and very different situation in the countries included in this project Nitrogen and phosphorus load in the Baltic Sea drainage area Total nitrogen input to surface waters within the Baltic Sea catchment was 822 kt in the year 2 of which diffuse sources (mainly agriculture) contributed with 58% according to HELCOM (24). Highest inputs were in Poland, Sweden and Finland (Figure 2-1 A). However, nitrogen load per capita is highest in Denmark, Sweden and Finland (Granstedt et al, 24). Even nitrogen surplus in agriculture is higher in these countries due to higher fertilizer usage and livestock density compared to countries like Latvia, Lithuania or Estonia (Figure 2-1 B). 12

13 N surface water (kt/year) N surplus (kg/ha year) A B Poland Sweden Finland Denmark Latvia Lithuania Estonia Germany Figure 2-1. Total nitrogen input to surface water (A) and nitrogen surplus in agriculture (B) in countries participating in BERAS. Data in (A) from HELCOM (24) and data in (B) from Granstedt et al (24). The distribution of sources differs slightly in the different countries but the pattern is similar. In Sweden about 6% of total nitrogen load to the Baltic Sea is anthropogenic and about half of the anthropogenic load originates from agriculture (Figure 2-2) (Brand and Ejhed 22). N load (kt/year) Gross load Net load Total Anthropogenic Agriculture Figure 2-2. Mean annual nitrogen load in Sweden for the period (Data from Brand and Ejhed, 22). Total includes total load to surface water and directly to the Baltic Sea, Anthropogenic - includes all anthropogenic emissions (incl all diffuse and point sources). Gross load is total load to surface water and directly to the Baltic Sea and net load is nitrogen load to the Baltic Sea after retention. The figures of nitrogen leakage from agriculture can be compared with calculated surplus of nitrogen calculated according to the farm gate method. Swedish agriculture produces a nitrogen surplus of 78 kg/ha year which corresponds to 184 kt/year (Granstedt et al., 24). Notice that N-surplus from agriculture in Sweden (Figure 2-1B) is as large as gross load of nitrogen to surface water and directly to the Baltic Sea (Figure 2-2). Gross leakage from Swedish agriculture to surface water is 61 kt/year of N-surplus (33%). The remaining 123 kt/year consist of ammonia losses from manure and animals (56 kt/year, 31%) (Granstedt et al., 24), leakage to groundwater (12 kt/year according to Brink, 199). Gaseous losses due to ammonia evaporation at the soil surface and denitrification processes in the soil equal the remaining 55 kt/year (36%) assuming steady state of mineral and organically fixed nitrogen in the soil. 13

14 Although calculated in a slightly different way, these results agree well with the results of the Swedish Statistics Agency (SCB 2. 22). SCB calculated nitrogen surplus from farm gate and field balances (surface balances) to 186 kt/year and N-leakage to 63 kt/year. N-losses from animal and manure can be calculated from the SCB data to 56 kt/year, as the difference between fodder production on one side and the production of animal products and manure on the other side by taking into account fodder production losses of 5%. An overall reduction of the nutrient load to the Baltic Sea by 5% is one of the national and international agreed environmental goals for the Baltic Sea Region (HELCOM, 24). This implies different strategies for the different countries. In countries with nutrient intensive agriculture like Sweden, Finland or Denmark loads have to be decreased, whereas in countries with today nutrient extensive agriculture, like Estonia, Latvia and Lithuania the development of agriculture towards more nutrient intensive methods has to be prevented. The overall goal of the nutrient studies in the BERAS-project is to investigate the potential of ERA to reach the proposed reduction of nutrient leakage from agriculture. Material and Methods The study is based on plant nutrient balance calculations for agriculture in the whole countries respectively in total figures and per ha. These values are representative for the average in the countries respectively and were compared to the selected BERAS farms in the countries respectively. Selected BERAS-farms ERA farms were selected in all BERAS countries to evaluate the potential to reduce nutrient surplus and losses from agriculture in the Baltic Sea drainage area. The test-farms were selected so they cover the main agricultural conditions and drainage regions in the area (Figure 2-3). Characteristics of the farms are presented in Appendix 1. The initially 35 farms were complemented with farms in Finland (the region of Juva close to Mikkeli) and in Järna in Sweden for more detailed studies and to cover different type of agricultural production so it finally was 5 farms included. During the project time some of the farms did not fulfil the preconditions for ERA farms and the consequences of that is discussed together with the evaluation of results. 14

15 Figure 2-3. The Baltic Sea drainage basin with locations of farms included in BERAS. 15

16 Field and farm gate balances The methods for calculating nutrient balances follow the concept described in earlier publications (Granstedt, 2; Granstedt et al 24) and are summarized below. The difference between this input and output of plant nutrients is here defined as surplus of plant nutrients and is the same as potential losses. For estimation of potential nutrient losses, plant nutrient balances can be calculated at field level (field balances) or for whole farms (farm gate balances). Farm gate balances are based on the difference between the import (input) of fertilizers, imported fodder, precipitation of atmospheric nitrogen and the export (output) of agricultural products from the farm. This method can also be used to calculate balances for larger systems such as administrative regions or drainage areas, e.g. the Baltic Sea drainage area. Field balances are based on the difference between input and output of plant nutrients on field level with the use the amount of manure and fertilizers for input data and the amount of harvested crops for output data. SCB (2. 22) in Sweden has present regularly both type of balances, farm gate balances for the whole Sweden based on agricultural according similar methods used of Granstedt et al for the eight countries around the Baltic Sea and field balances (of SCB called surface balances) based on collected information direct from the Swedish farms. Nitrogen fixation and input trough atmosphere deposition En important part of the nutrient balances is the input through nitrogen fixation. The nitrogen fixation on the farm in Sweden, Finland (F-BERAS farms), Estonia, Latvia Lithuania and Poland was estimated with the used calculation programme for nutrient balances Stank 2:1 (Jordbruksverket, 2) and the collected data on yield level an clover percent in the clover grass fields. The clover percent was estimated in field combined with cutting of proofs for calibrating of this estimation and done of the same person in the above countries during the actual years in the countries respectively. In estimating the contribution of nitrogen fixation on country level it was assumed that 25 % of the ley area in the form of a first-year ley with legumes producing 1 kg fixed nitrogen per ha. Fodder peas and beans were assumed to fix 5 kg nitrogen/ha. The figures for nitrogen deposition are based on measurements of wet and dry deposition made by the Environmental Research Institute for the years respectively according to Granstedt (2). The estimation of nitrogen fixation in Denmark and Germany is done according the there used methods and the estimated surplus of nitrogen can deviate from the other countries of this reason. The given fixation in Denmark is calculated as in Nielsen & Kristensen (25): Results of plant nutrient balances in the BERAS countries Sweden The average results of nutrient balance calculations on farm level is presented in Figure 2-5. For nitrogen, the results are presented for all the three years separately in Figure 2-4. For more detailed results, also for separate years, see Appendix 1. The average nitrogen surplus on the BERAS farms was in the range kg N per ha and year during the study period (Figure 2-4). Calculated all the 12 farms together and divided with total area of the BERAS-farms, the average surplus of N was 39 kg per ha and year. This value can be 16

17 compared to the average for Swedish agriculture which was calculated to 79 kg per ha and year for 2-22 (Figure 2-6). N (kg/ ha year) Surplus Anim Veg 37 Input Prod Export Surplus N (kg/ ha year) Surplus Anim Veg Input Prod Export Surplus N (kg/ ha year) Surplus Anim Veg Input Prod Export Surplus Figure 2-4. Average input, plant production, export and surplus of nitrogen (N) on the BERAS-farms in Sweden for the years 22, 23 and 24. N (kg/ ha year) N Surplus Anim Veg Input Prod Export Surplus P (kg/ ha year) P Surplus Anim Veg -1 Input Prod Export Surplus K (kg/ ha year) K Input Prod Export Surplus 4 Surplus Anim Veg 2 Figure 2-5. Average input, plant production, export of farm products and surplus of nitrogen (N), phosphorus (P) and potassium (K) on the BERAS-farms in Sweden N (kg/ ha year) N Surplus Anim Veg 79 Input Prod Export Surplus P (kg/ ha year) P Input Prod. Export Surplus 4 3 Surplus An.prod. V.prod. 3 Figure 2-6. Average input, production, export and surplus of nitrogen (N) and phosphorus (P) for Swedish agriculture 2-2 (Granstedt et al 24).. The calculated crop production in terms of N is higher but food production is about 25 % lower. This can be explained by the higher part of ruminant clover grass based animal production compared to conventional agriculture with domination of more grain converted meat production. It is a smaller rate between input of fodder protein and output of animal protein in grain converted meat production compared with clover grass based ruminant meat production. This only partly compensates the high yield in producing clover grass compared with grain. The grain production is significant lower on BERAS-farms compared with conventional agriculture. Surplus of nitrogen is in this comparisons more than 5 % lower on 17

18 Swedish BERAS-farms, with the same animal density of.6 au/ha but a little lower share of animal products of the total production in terms of N. The variation between the farms was rather high with lower surplus on farms with low animal density and higher on farms with high animal density (Figure 2-7). All BERAS-farms with an animal density below.75 AU per ha have a surplus below 5 kg N/ha and can be defined as ERA-farms with animal production based on minimum 85 % own fodder. The lowest values is the calculated surplus on the more extensive producing meat and cereal farms Oxsätra and Håknäs and the highest values for the intensive dairy farm Skogsgård which not fulfilled the conditions for an ERA-farm. 7 6 Nsurplus (kg/ ha year) ,,5 1, Animal density (au/ha) Figure 2-7. Average animal density and N-surplus 22-4 for the Swedish BERAS-farms. The External Fodder Rate (EFR) and surplus of nitrogen per ha and year for the three years period for the BERAS-farms is presented in Figure 2-8. Two farms, one of the dairy farms (Skogsgård) and the pig farm (Davidsta), bought more than 15 % of the fodder (but less than 2 %) and have a surplus of 66 and 44 kg N respectively and diverge more or less from the average value 36 kg N/ha for all farms. 7 6 Nsurplus (kg/ ha year) ,5,1,15,2 External fodder rate 18

19 Figure 2-8. External fodder rate and N-surplus 22-4 for the Swedish BERAS farms. The surplus was highest for the dairy farm Skogsgård which already in the beginning of the study period had too high animal density in relation to the criteria for an ERA-farm. During the study, the farm increased the animal density and the part of purchased fodder further to an average animal density of.9 AU per ha and an average surplus of 7 kg N per ha (Figure 2-9). Thus, it does not fulfil the condition for an ERA-farm. The pig raising farm Davidsta developed in the opposite way and decreased the animal density and need of purchased fodder during the study period with a decreased surplus of nitrogen as a consequence (Figure 2-9). 1,2 9 Animal density (au/ ha) 1,8,6,4 Skogsgård Davidsta Nsurplus (kg/ ha year),2 Animal density N-surplus Figure 2-9. Surplus of nitrogen on two farms with different animal densities. Increased N-surplus on the dairy farm Skogsgård due to increased animal density and increased use of purchased fodder (EFR:.8;.2;.21) and decreased N-surplus on the pig raising farm Davidsta due to decreased animal density and decreased use of purchased fodder (EFR:.24;.16;.18). The relation between animal density and surplus of nitrogen is illustrated in Figure 2-1. On the BERAS dairy farms with low animal density (.65 AU/ha), the surplus was average 42 kg N per ha. On more specialised conventional dairy farms, illustrated by the average of 68 dairy farms (Myrbeck 1999), the average surplus was 131 kg N per ha. Not published data from the Swedish action program Greppa Näringen with about 6 nutrient balances give nearly the same information with a surplus of 5 kg N/ha on crop farms and 133 kg N/ha on dairy farms. 19

20 Nsurplus (kg/ ha year) CA ERA,,5 1, 1,5 2, Animal density (au/ha) Figure 2-1. The low animal density on the BERAS dairy farms (ERA) resulted in average 42 kg N surplus per ha from this study, compared to average 131 kg N surplus per ha on 68 conventional dairy farms (CA) published of Myrbeck (1999). The study of Myrbeck (1999), with an evaluation of more than 1 conventional farms (dairy and specialised crop farms), is until now the largest study performed and it is representative for the Swedish agriculture also for the three BERAS-study year since the total surplus of plant nutrients is on the same level. Figure 2-11 shows the lower surplus of nitrogen on four groups of BERAS-farms compared to the corresponding four groups in conventional agriculture. The lower surplus of nitrogen on BERAS-farms is associated with described lower animal density on the animal farms, i.e. lower degree of specialisation and higher degree of integration of crop and animal production Nsurplus (kg/ ha year) CA ERA Animal density (au/ ha) A B C D Farm type Figure Surplus of nitrogen in four groups of BERAS-farms (ERA) and corresponding conventional farms (CA) (Myrbeck 1999). Dots show animal density. A - Mixed production with vegetables (2 farms), B - Milk, meat and cereals (6 farms), C - Cereals and ruminant meat (2 farms), D - Pork, poultry, egg and cereals (2 farms). Based on the above presented results from the BERAS farms are field balances (Field balance = N-manure + N-fertilizers + N-fixation + N-deposition + N-fixation + N-deposition - N-crop production) and possible losses trough denitrification and leakage calculated with the assumption of a steady state of stored amount nitrogen in soil. The calculation is done with 2

21 two alternative levels of NH 4 emissions from the animal production and manure management. One calculation is based on an estimated amount of N in manure based on an assumed emission of 3 % and one calculation is based on an assumed emission of 4 % of the difference between fodder consumption and animal production (Figure 2-12). This calculations gave a surplus of nitrogen to the fields of 2 and 14 kg N per ha respectively which can be compared to the same assumptions made for calculation for the whole average Swedish agriculture which give 68 and 58 kg per ha in surplus respectively. An assumed drainage leakage of 48 % the field balance surplus give a theoretical nitrogen leakage from the fields of 9 and 7 kg N per ha respectively according the discussion on page 1. This can be compared to the same assumptions made for calculation for the whole average Swedish agriculture which give 3 and 28 kg per ha in leakage respectively. This will give a reduction of nitrogen leaching with 7 and 75 % respectively on BERAS farms compared to the average Swedish agriculture farms. 9 Nitrogen losses (kg/ ha year) NH4-loss Denitrif. Leakage CA 3 % CA 4 % BERAS 3 % BERAS 4 % Types of NH4-losses Figure The distribution of N losses of the calculated N surplus for Swedish average agriculture and the BERAS-farms with two different manure handling systems (resulting in 3 and 4 percent ammonia losses from the animal exudates respectively). Finland Artur Granstedt and Pentti Seuri The Finnish study was based on five BERAS-farms (called F-BERAS-farms); two in the cereal-dominated south part of Finland, one in central part of Finland (Tampere), one in the animal-dominated north-west part of Finland (Österbotten) and one farm in east part of Finland in Juva. This is extended with a deeper study of 8 organic farms located in the Juva region (called J-BERAS-farms). The average nitrogen surplus on the five F-BERAS-farms range between kg N per ha and year during the study period (Figure 2-13). For more detailed results, see Table A1- and Table A1- in Appendix 1. 21

22 N (kg/ ha year) N Surplus Anim Veg 38 Input Prod Export Surplus P (kg/ ha year) P Surplus Anim Veg Input Prod Export Surplus K (kg/ ha year) K 2 Surplus Anim Veg Input Prod Export Surplus Figure Input, plant production, output of farm products and surplus of nitrogen (N), phosphorus (P) and potassium (K) on the F-BERAS-farms in Finland N (kg/ ha year) N Surplus Anim Veg 73 Input Prod Export Surplus P (kg/ ha year) P 1 1 Input Prod Export Surplus 3 2 Surplus Anim Veg 8 Figure The input, production, export and surplus of nitrogen (N) and phosphorus (P) in Finnish agriculture, averages per ha and year 2-22 (Granstedt et al 24). Mean animal density was.6 au/ha. The average nitrogen surplus on the five Finnish F-BERAS-farms range between kg N per ha and year during the study period and a range between the farms The average surplus of 38 kg N per ha and year can be compared to the average for Finnish agriculture which was calculated to 73 kg per ha and year for 2-22 (Figure 2-14) showing the surplus of nitrogen is twice the surplus on Finnish F-BERAS-farms with the same animal density (.6 au/ha). The calculated nitrogen fixation with deposition included was average 3 kg N per ha and the. calculated fodder production is 49 kg N per ha. Surplus of P is 3 kg per compared with average 8 kg for the whole Finnish agriculture (Figure 12 c and 12 d. Most of the Finnish BERAS farms have like in Sweden a deficit for P in the balance and the potential for P is reduced compared to main stream agriculture. The crop production in terms of N is only some percent lower but food production (vegetable and animal products) is about 4 % lower. This can also for Finland be explained by the higher part of ruminant clover grass based animal production compared to conventional agriculture with domination of for effective grain converted meat production. The variation between the farms was rather high with lover surplus on farms with low animal density and higher on farms with high animal density (Figure 2-15). All BERAS-farms with an animal density under.7 AU per ha show a surplus lower than 52 kg N/ha. 22

23 6 5 Nsurplus (kg/ ha year) Animal density (au/ha) Figure Average animal density and surplus of Nitrogen per ha and year for the three years period for all the Finnish F-BERAS-farms. The Baltic countries The selected BERAS-farms in the Baltic countries were studied during three years in Estonia and two years in Latvia and Lithuania. Nitrogen and phosphorus balances on these are presented in Figure The surplus of nitrogen is here higher than average agriculture in Estonia (Figure 2-17). The common agriculture is in Estonia like also in Latvia and Lithuania very extensive and use of artificial fertilisers very low compared to Sweden and Finland. The statistic for nutrient balances in Latvia and Lithuania probably give very uncertain values with partly not used agricultural land and, therefore, not presented here. Also the organic agriculture are producing under extraordinary circumstances with areas of land, not optimal used and with a week relation between field production and harvested yield and finally production of sold animal and vegetable products from the farms. Several technical problems and also social problems can be the reason for that and need further developing work. Some farms just harvesting what land and soil can give. The relation between animal density and surplus on the eleven studied farms is presented in Figure 2-18 and show a tendency with a higher surplus on farms with higher animal density. The animal density is on the organic farms low like in the average of the countries respectively rather low. It was a dramatic decrease of the animal production after 199 in all this countries depending on extraordinary low prices of agricultural product after the collapse of the Soviet Union which earlier was the most important market. If we exclude three of the BERAS farms with the most extreme surplus of nitrogen depending on high calculated nitrogen fixation in relation to utilized yield, the relation between surplus and animal density is more representative for the countries (the lower regression line in Figure 2-18). The surplus is then 31 kg N per ha and the animal density.3 animal unit per ha. That surplus is also more like the surplus for the BERAS-farms in Sweden and Finland. 23

24 N (kg/ ha year) N Surplus Anim Veg 41 Input Prod Export Surplus P (kg/ ha year) P Surplus Anim Veg -.5 Input Prod Export Surplus K (kg/ ha year) K Surplus Anim Veg -.7 Input Prod Export Surplus Figure Input, plant production, output of farm products and surplus of nitrogen (N), phosphorus (P) and potassium (K) on the BERAS-farms in the Baltic countries N (kg/ ha year) N Input Prod Export Surplus 7 Surplus Anim Veg P (kg/ ha year) P Input Prod Export Surplus 1 1 Surplus Anim Veg 2 Figure The input, production, export and surplus of nitrogen (N) and phosphorus (P) in Estonian agriculture, average per ha and year Nsurplus (kg/ ha year) Animal density (au/ha) Figure Average animal density and surplus of nitrogen per ha and year for the three years period for the Baltic countries BERAS-farms. The red circles represent three farms which are excluded in the blue (lower) regression line. 24

25 Poland Artur Granstedt, Jozef Tyburskij and Jaroslaw Stalenga In Poland 7 farms were selected, covering the main different farming conditions in the country during two years, Only during the last year 25 it was possible to visit all the farms to collect data and make fixation estimations depending of the extra economical resources BERAS-Poland got this year. But the farms were very well-known and representative for the farming conditions respectively. A special study on 2 organic farms in the district of Brodowice was done during 22. The results were published in Polish. The average surplus of the Polish BERAS-farms is presented in Figure 2-19 which can be compared to the figures for the average Polish agriculture in Figure 2-2. The calculated nitrogen surplus of 32 kg N per ha was 45 % lower compared the Polish nitrogen surplus of 57 kg N per ha. The export of phosphorus in agricultural was two kg lower than the input compared to the average Polish agriculture with a surplus of 19 kg P per ha. Big areas of the Polish agriculture is very extensive and other parts special in the north west part of Poland more intensive and more like agriculture in Western Europe. The high use of P-fertilisers is remarkable. Such an over-optimal use of P-fertilizers was earlier used also in Sweden and Finland but has decreased the last 2 years. N (kg/ ha year) N Surplus Anim Veg Input Prod Export Surplus P (kg/ ha year) P Surplus Anim Veg -3 Input Prod Export Surplus K (kg/ ha year) K Surplus Anim Veg -5 Input Prod Export Surplus Figure The input, production, export and surplus of Nitrogen, Phosphorus and Potassium on the seven BERAS-farms in Poland Animal density,6 au/ha. N (kg/ ha year) N Surplus Anim Veg 57 Input Prod Export Surplus P (kg/ ha year) P Surplus Anim Veg -2 Input Prod Export Surplus Figure 2-2. The input, production, export and surplus of Nitrogen, Phosphorus and Potassium in conventional agriculture in Poland Animal density,6 au/ha. 25

26 Germany Artur Granstedt and Holger Fischer Plant nutrient balances of the two selected BERAS-farms in the Oder drainage area in Germany are presented in Figure These figures can be compared with the diagram for Märkisch Oderland in Figure The very low surplus on the two German BERAS farms of 16 kg N per ha can be evaluated in relation to the very low animal density representative for this regions. The surplus compared with conventional agriculture in the region is only 22 % of the conventional surplus of 74 kg N per ha in the region but also the agricultural production seem to be rather extensive compared with the conventional production with only15 kg N per ha in agricultural products compared with the conventional production of 67 kg N per ha. Like for the most other BERAS-farms is the P balance negative with higher export of P in agricultural products compared near zero input of P. N (kg/ ha year) N Surplus Anim Veg 16 Input Prod Export Surplus P (kg/ ha year) P Surplus Anim Veg -3 Input Prod Export Surplus K (kg/ ha year) K Surplus Anim Veg -5 Input Prod Export Surplus Figure The input, production, export and surplus of Nitrogen, Phosphorus and Potassium on the two BERAS-farms in Germany Animal density,35 au/ha N (kg/ ha year) N Surplus Anim Veg P (kg/ ha year) P Surplus Anim Veg Input Prod Export Surplus -4 Input Prod Export Surplus Figure The input, production, export and surplus of Nitrogen, Phosphorus and Potassium in the region of Märkisch-Oderland in Germany Animal density,4 au/ha Denmark Ib Sillebak Kristensen, Anders Højlund Nielsen, Ole Tyrsted Jørgensen and Artur Granstedt The Danish farms were registered according to the method described in Kristensen (22). The fixation is quantified from yield of pure legume crops with the coefficients from Høgh- Jensen et al (23) and Høgh-Jensen et al (24). In grass/clover and mixtures of grain/peas the fixation was estimated from soil cover of legumes, according to the method of Kristensen et al (1995) and Kristensen et al (25b). The field yield of the farms were measured from sold crops and herd uptake of home-grown feed-crops. Yield from grazed field were calculated from animal production. The net storage change (storage final minus storage begin) of feed and manure were included in the figures of purchased feed/manure if net storage change were negative or exported crops if storage changes were positive. 26

27 The BERAS-farms in Denmark is in this report is represented of one vegetable farm situated on Funen, and 4 dairy farms on Jutland. The dairy farms were selected amongs 13 pilot farms having the lowest External Fodder Rate-EFR (Nielsen and Kristensen, 25). Due to net import of animal manure and high feed import it was not possible to find farms fulfilling the minimum 85 % External Fodder Rate. The farms had % EFR, in average the BERAS pilot farms had 21 % External Fodder Rate, 16 % lower than Danish average organic pilot farms in the period of , see appendix 1. The farm gate N-surplus were 87 kg N per ha (Figure 2-23) is higher than on other Baltic BERAS-farms presented, but 32 percent lower than the average Danish agriculture with a average surplus of 129 kg N per ha (Figure 2-24). Compared to all Danish dairy pilot farms in the period of the Danish BERAS farms had 18 % lower N-surplus, see appendix 1. However if the farm gate N-balance were recalculated to year 22 with the average BERAS stocking rate of.99 AU/ha the difference was narrowed to only 6 % lower farm gate balance on the Danish BERAS farms compared to average organic dairy farms. The correction used was 64 kg N/AU and 6.5 kg N/year, see Nielsen and Kristensen (25). The vegetable farm Nørregaard had 48 % of the farm area unused or with low productive permanent grass (1-2 tons DM/ha/year). If the entire farm area was used for calculating the per ha nutrient surplus the N surplus was 15 % lower than if only the arable land were included in the balance, se appendix. In Denmark only 8% of the farm area is permanent grass, and for average the Nørregaard figure on arable land is used. In the period the average N-surplus was decreased by 14 % (Nielsen and Kristensen, 25), due to restrictions in import of conventional feed, which was prohibited from year 21. On representative organic arable farms with.3 AU/ha a field balance of 61 kg N/ha was calculated (Knudsen et al (25) and Berntsen et al (24), corresponding to a farm gate balance of about 64 kg N/ha, if 3 kg N/ha in ammonia losses in stable and storage was assumed, Kristensen (25). In Denmark -year 22- the organic area is used as 54 % organic dairy, 25 % arable and 17 % mixed full time farmers and 5 % part time farmers, Berntsen, Petersen et al (24). If the measured farm gate N-surplus of the dairy and arable farmers represents the entire Danish organic production the average organic N-surplus can be calculated to 85 kg N/ha (16-64)/2, which is 27 % lower than the entire Danish N-surplus, Kristensen et al (25a). The surplus of nitrogen in a scenario of ERA agriculture on the whole of Funen, presented in Chapter 3, shows a surplus of 59 kg N/ha and, like the most other Baltic BERAS-farms, 45 % lower than the present agriculture on Funen. The chapter 3 1 % organic scenario on Funen shows the potential of organic production if no import was allowed and if the plant yield was at the present level as the pilot farms. However this low surpluss can be difficult and expensive to achieve, Anon. (21) All the above calculated organic balances is influenced by the assumptions of fixation. If 25 % higher/lower fixation is assumed the dairy farm balance will change by 17 % (Knudsen et al. 25). The P balance is the same on the Danish BERAS-farms shows an average surplus of 4 kg P per ha, 2 kg P lower than as for the whole agriculture in Denmark. The BERAS farms were also 33% lower than average of Danish organic milk pilot farms in the period of Nielsen and Kristensen, 25), see appendix 1. 27

28 Total area: N (kg/ ha year) N Surplus Anim Veg 52 Input Prod Export Surplus P (kg/ ha year) P Surplus Anim Veg -2 Input Prod Export Surplus K (kg/ ha year) K 39 Surplus Anim Veg Input Prod Export Surplus Cultivated area N (kg/ ha year) N < Surplus Anim Veg 68 Input Prod Export Surplus P (kg/ ha year) P Surplus Anim Veg -2 Input Prod Export Surplus K (kg/ ha year) K Surplus Anim Veg Input Prod Export Surplus 2 Figure The input, production, export and surplus of Nitrogen, Phosphorus and Potassium on the two BERAS-farms in Denmark Total area: N (kg/ ha year) Cultivated area: N (kg/ ha year) 84 N Surplus Anim Veg 129 Input Prod Export Surplus N P (kg/ ha year) Surplus Anim Veg 129 Input Prod Export Surplus P Input Prod Export Surplus P (kg/ ha year) Surplus Anim Veg Surplus Input Prod Export Surplus Figure The input, production, export and surplus of Nitrogen and Phosphorus in Denmark 22. P Anim Veg 8 28

29 Discussion and conclusions Nitrogen and phosphorus surpluses, calculated ammonic losses and based on that calculated field losses and leakage for all BERAS-countries and the BERAS-farms are presented in Table 2-1 and Figure The average nitrogen and phosphorus surplus is 56 and 11 kg per ha respectively in the BERAS-countries. On the selected BERAS-farms, the average nitrogen surplus was 35 kg N per ha which is 35 % lower and the calculated field losses was 5 % lower. Table 2-1. Total Load (according to HELCOM) and in the project calculated total surplus, field losses and leakage of N and P in average agriculture and BERAS agriculture based on BERAS farms presented in total figures, calculated per ha for the countries respectively and the total agricultural land area. HELCOM Average agriculture BERAS agriculture Arable Loads land 1 N surplus P surplus NH4 loss N surplus P surplus NH4 loss year 2 Mha N t/a P t/a kg/ha t/a kg/ha t/a kg/ha t/a kg/ha t/a kg/ha t/a kg/ha t/a Sweden Finland Est/Lat/Lith Poland Germany Denmark Total Field losses Farm gate balance Nutrient balance (kg/ ha year) Field balance AA - N AA - P BERAS - N BERAS - P Figure The average nutrient farm-gate and field balance in the agriculture of the BERAS-countries (AA) and on the BERAS-farms (BERAS). N - nitrogen, P - phosphorus. Average nitrogen fixation per ha for all BERAS-farms is 4 kg N per ha and year. Should nitrogen fixation be underestimated and nitrogen fixation 2 % higher should the calculated field surplus be 3 % lower and if nitrogen fixation should be overestimated with 2 % should the field surplus be 7 % lower compared to the average agriculture. 1 land in the Baltic Sea drainage area only 29

30 Based on these results, we have calculated one fully realistic scenario where Poland and the Baltic countries introduce an agriculture like the one we have in Sweden today and one scenario working in the opposite way with converting the whole Baltic Sea drainage area to ERA-type agriculture (Figure 2-26), where also the Baltic countries ERA-farms produce similar to the Swedish ERA-farms. The first conventional scenario would give an 5 % increase of the field surplus of nitrogen and corresponding increase load to the Baltic Sea and probably also a similar increase of the phosphorus load. The consequences would be the opposite with a decrease of the nitrogen surplus with 5 % if the whole agriculture in the Baltic Sea area should convert to an ecological recycling agriculture (ERA scenario). This scenario would also result in a nullsurplus of phosphorus which would result in a significant decrease of the phosphorus load from the agriculture to the Baltic Sea Farm gate balance Nutrient balance (kg/ ha year) Field balance N P N P N P Todays situation Conventional scenario ERA scenario Figure Surplus of nitrogen an phosphorus in farm-gate and field balances calculated for three alternatives: The present agriculture (Today s situation), if also Poland and the Baltic countries introduce an agriculture like the Swedish (Conventional scenario) and with converting the whole Baltic Sea drainage area agriculture to Ecological Recycling Agriculture (ERA scenario). 3

31 6 55 Nitrogen production (kt/ year) Crop production Animal production Todays situation Conventional scenario ERA scenario Figure Vegetables and animal production in the conventional Scenario and ERA scenario should give an increased and reduced agricultural production in the BERAS-countries respectively. The output of vegetables and animal production in total kt nitrogen is calculated for the conventional Scenario and ERA scenario. The conventional scenario should give an increased vegetal production of about 3 % and increased animal production of abot 1 % (average + 15 %) and reduced. The alternative BERAS Scenario with a reduced nutrient leakage should result in a decreased vegetable production of about 2 % and an decreased animal production of about 3 % the BERAS-countries. In the second scenario is an higher part of the animal production based on grass fodder compared to the conventional production with a high part meat produced with grain and concentrate as fodder. The lower production in the BERAS scenario should reduce the overproduction in Europe to day but could also be compensated through using to day not utilized agriculture land in the Baltic countries. Evaluation of nitrogen utilization by means of the concept of primary production balance Pentti Seuri, Helena Kahiluoto MTT Agrifood Research Finland, Huttulantie 1, FI-519 Juva, Finland, Tel , pentti.seuri@mtt.fi, helena.kahiluoto@mtt.fi, Key Words: nitrogen utilization, nutrient balance, primary nutrient, secondary nutrient, nutrient loading Abstract Primary production balance (PPB) indicates the ratio (*) between harvested nutrients and nutrients put into crop production from outside the system (=primary nutrients). The PPB is independent of the final output (crop vs. animal products) and can be used to evaluate different systems (farms). The utilization of nitrogen was evaluated by means of the PPB on nine organic farms, stockless and mixed ones, in eastern Finland. The mixed farms were able to reach a remarkably higher primary production balance (1. 1.2) compared with the stockless ones (.5). Values higher than 1. indicate recirculation of nutrients. Other components of the high PPB were legumes as nitrogen source and optimum livestock density. 31

32 Introduction Nutrient balances (farm-gate balance, surface balance or cattle balance) only indicate an absolute load of nutrients as a difference between input nutrients and output nutrients (kg or kg/ha); basically they do not tell anything about the efficiency of nutrient utilization. It is also possible to count a ratio between output and input. Sometimes this type of ratio has been used as a measure of efficiency of nutrient utilization. As long as the system is simple enough, i.e. stockless farm without any recycling nutrients, the output/input ratio indicates the efficiency of nutrient utilization. However, as soon as a system involves recycled nutrients, the output/input ratios are difficult to interpret (Myrbeck 1999). From an ecological point of view there is only one production process in the agricultural system, i.e. crop production or primary production. Primary production can be used either directly as human food or fed to animals. Nutrient load and nutrient utilization, i.e. efficiency to utilize nutrients, are two separate dimensions. If only crop products are produced, the nutrient load is less than an equal amount (kg nitrogen) of animal products, even the efficiency to utilize nutrients is equal. This is because more crop products are needed to produce an equal amount of animal products. In order to reduce the nutrient load there are two choices: either to produce less or to improve the efficiency of nutrient utilization. Since the amount of primary production is highly dependent on the priorities in the human diet, it can be taken as a given constant. According to this assumption, the harvested yield (Y) to external nutrient input (=primary nutrients, P) ratio alone indicates the nutrient utilization in any system. The concept of primary production balance (PPB) is based on this fact (Seuri 22). The aims of this study were: To introduce a new method, primary production balance, for the evaluation of nutrient utilization To demonstrate and find the key factors to reach a high utilization rate of nutrients (*) Note: the term balance is used to indicate a difference (input output) or ratio (output/input); the unit of difference is kg or kg/ha, the unit of ratio is either per cent or no unit. Material and methods A more profound analysis was made on nitrogen utilization on nine organic farms in eastern Finland. Data was collected by personally interviewing farmers in 24. An overall picture was drawn on how the farms were functioning and, to ensure the validity of data, the results were discussed personally with the farmers. The estimations of harvested yield (dry matter & nitrogen) were adjusted with the number of animals and total animal production. The nitrogen contents of all organic materials within the system (crops, fodder, bedding materials, seeds, animal products, purchased manure) were estimated by means of standard figures, unless measured values were available. Atmospheric deposition, 5 kg nitrogen/ha, was included as input. 32

33 All the main nutrient flows were identified. However, because of the steady-state assumption (i.e. balanced systems, no change in reserve nutrients in soil) and estimation of biologically fixed nitrogen the results may include some error. Biological nitrogen fixation was estimated using harvested legume yield: the assumption was 5 kg nitrogen per 1 kg harvested dry matter of legume. That means that roughly 7 % of the total nitrogen content in the legume biomass originated from BNF. The assumption was derived from the Swedish STANK model (STANK 1998), the Danish model by Kristensen et al. (1995) and the Finnish model by Väisänen (2). On all farms the most important legume was red clover. However, some white clover and alsike clover were grown in perennial mixture lays, too. Besides pea, which was the most important annual legume crop, some annual vetch was grown. Farm-gate balance, surface balance and primary nutrient balance were calculated for each individual farm (Table 2-2). Primary nutrient balance can be calculated from the following two equations (Seuri 22): (I) PPB = Y/P where Y = total harvested yield P = primary nutrients (=external nutrients) (II) PPB = U x C where U = utilization rate (=surface balance) C = circulation factor = (P + S)/P S = secondary nutrients (=recirculated nutrients) Equation (I) follows the definition of PPB. Equation (II) illustrates two components of PPB: utilization rate, which is equal to surface balance, and circulation factor, which indicates the importance of recirculated nutrients in the system. There is a major difference between stockless farms and livestock farms. Since there are no recirculated nutrients (S) on stockless farms, the circulation factor is always 1.. On livestock farms the circulation factor is always higher than 1.. To illustrate the difference between primary and secondary nutrients and to point out the role of recirculation in order to improve the nutrient utilization, some simple simulation was made on two stockless farms. The farms produce some fodder and receive some farmyard manure (FYM) from the neighbouring farm. The initial balance (A) indicates utilization in case manure from the neighbouring farm is external nutrient input (primary nutrient). The simulated balance (B) indicates the utilization in case all the harvested fodder yield is used on the farm for dairy cattle. It is assumed that 25 % of the nitrogen in the fodder is sold out from the farm in the form of milk and beef and 25 % is lost in the gaseous form before the manure is spread on the field. The rest of the nitrogen (5%) remains in the manure. The average utilization rate of the primary nitrogen in the agriculture in Finland was calculated from statistics. Rough estimations and comparisons were made between the farms in this study and national average utilization rates. Results and discussion Table 2-2. Comparison between primary production balance (PPB), surface balance (SB) and farm-gate balance (FGB) of nitrogen on nine organic farms in eastern Finland. Farms 8B and 9B are simulated from 8A and 9A, respectively. 33

34 Farm Production Primary Total N Harvested PPB SB FGB Circulation N surplus type N input on field N yield factor (kg/ha) (kg/ha) (kg/ha) (kg/ha) 1 dairy dairy dairy beef beef beef(+crop) goat(+crop) A crop B dairy A crop B dairy (+crop) The PPB of nitrogen fell in the range on all mixed farms except for farm 7, i.e. the farms were able to harvest more nitrogen than they received as an input into the crop production from outside the farm. Both stockless farms reached a PPB as low as around.5; the dairy farm simulation increased the PPB up to.8. The SB of nitrogen fell in the range.6.75 on all mixed farms and by definition PPB and SB are identical in a stockless system (around.5), i.e. in any system without recirculated nutrients. The FGB of nitrogen correlated strongly with production type, being around.3 on dairy farms and around.2 on beef farms. Analogously to PPB and SB, also FGB was identical on stockless farms (around.5). The dairy farm simulation decreased the FGP down to.19 on farm 8 and down to.3 on farm 9. Simulation on farm 8 shows clearly the role of recirculation and the difference between PPB and SB. On farm 8, the only difference between the real farm and the simulated farm is the method of definition of the origin of input nitrogen, i.e. the initial yield harvested and the initial amount of nitrogen available in the field are exactly the same. On farm 8A, all the nitrogen in FYM from the neighbouring farm is considered as primary nitrogen analogous to the nitrogen in artificial fertilizers or the nitrogen from BNF. This is analogous to any nitrogen input which increases the total amount of nitrogen in the system. On farm 8B, the nitrogen in the FYM from the neighbouring farm is considered as secondary nitrogen analogous to the nitrogen in FYM originating from the farm. This is analogous to any recycled nitrogen which does not increase the total amount of nitrogen in the system. However, the SB method does not identify the origin of the nutrients in the field, i.e. unlike PPB, SB remains constant on farm 8. The higher PPB value on the simulated farm 8B indicates higher efficiency of primary nitrogen utilization, thereby a lower nitrogen load potential. On farm 9B there are some green manure fields, from where yield is harvested instead of ploughing directly. Therefore also the SB is influenced by simulation on farm 9, but otherwise it is analogous to farm 8. 34

35 In Finland ( ), calculation of nitrogen balance in agriculture shows that the annual total primary nitrogen input (artificial fertilizers, atmospheric deposition and symbiotically fixed nitrogen) is about 1 kg/ha. The total harvested nitrogen yield is about 74 kg/ha, respectively (Lemola & Esala 24). Thus, the PPB in agriculture averages 74 kg/ha / 1 kg/ha =.74, indicating serious lack of nutrient re-cycling. However, there is huge potential to recycle nutrients in agriculture, because 8 % of the total crop yield is used as animal fodder. In this study, all the livestock farms exceeded the value.74, range.8 1.2, average around 1.. The high PPB on nitrogen was not only due to recycling but also to biological nitrogen fixation. The main source of primary nitrogen input was symbiotic fixed nitrogen by legumes. The utilization rate of nitrogen by legumes is clearly higher than for any other source of nitrogen into a system. In most cases about the same amount of nitrogen was harvested than was symbiotically fixed, i.e. the utilization rate is approx. 1%. In addition, the balance between livestock and field area (fodder production) was of major importance in reaching a high PPB. Whenever the livestock density was increased by means of purchased fodder, the utilization of farmyard manure was poor and resulted in lower PPB (farms 3, 6 and 7). Self-sufficient fodder production was the optimum. The farms with high PPB had also a slightly higher yield level than farms with lower PPB. On the other hand, two stockless organic farms indicated that without recirculation an organic system cannot utilize nitrogen very efficiently. On these farms the primary source of nitrogen consisted of legumes, but because the legume crop was partly used as green manure, there were heavy losses of nitrogen with resultant lower total PPB. Conclusions It was fairly easy to calculate the primary production balance for each of the nine farms included in this study. The estimation of biological nitrogen fixation and harvested nitrogen yield are, however, obvious sources of error. The assumption of steady state is not necessarily valid in all cases. Even though crop production causes only minor nutrient load compared with animal production, it does not necessarily mean that crop farms utilize nutrients effectively. Using the PPB it is easy to compare different farms. The results of this study show clearly that livestock farms are able to reach a remarkably higher PPB compared with crop farms despite the very low farm-gate balance on livestock farms. References Brandt, M. & Ejhed, H. 22. TRK Transport Retention Källfördelning. Belastning på havet. Naturvårdsverket, SE Stockholm, Rapport 5247, 12 p. Brink, N Land Use Changes in Europe. Process of Change, Environmental Transformation and Future Patterns (F. M. Brower editor). Kluwer Academic Publishers; London. Granstedt et al. 24. Effective recycling agriculture around the Baltic Sea. Background report. BERAS 2. Ekologiskt lantbruk 41. Centre for Sustainable Agriculture. SLU. Uppsala HELCOM. 24. The Fourth Baltic Sea Pollution Load Compilation (PLC-4). Helsinki Commission, Baltic Marine Environment Protection Commission, Baltic Sea Environment Proceedings

36 Kristensen, ES., Högh-Jensen, H. & Halberg, N A simple model for estimation of atmospherically-derived nitrogen in grass/clover systems. Biol Agric Hortic 12: Lemola, R. & Esala, M. 24. Typen ja fosforin virrat kasvintuotannossa. AESOPUShankkeen loppuseminaari SYKE, Helsinki. (Nitrogen and phosphorus flows in agriculture. Seminar on the AESOPUS project Finnish Environment Institute, Helsinki.) Myrbeck, Å Nutrient flows and balances in different farming systems A study of 13 Swedish farms. Bulletins from the Division of Soil Management, Department of Soil Sciences, Swedish University of Agricultural Sciences. 3: 1-47, 11 app. Seuri, P. 22 Nutrient utilization with and without recycling within farming systems. In: eds. Jakob Magid et al. Urban Areas - Rural Areas and Recycling - the Organic Way Forward? DARCOF Report 3: p SCB. 22. Kväve och fosforbalanser för svensk åkermark och jordbrukssektor 2. (In Swedish with English summary: Nitrogen- and phosphorus balances in arable land and agricultural sector in Sweden 2). Statistics Sweden, 34 pp. STANK Statens Jordbruksverks dataprogram för växtnäringsbalansberäkning. Stallgödsel och växtnäring i kretslopp (STANK) Jordbruksverket, Jönköping. (Plant nutrient balance calculation program) Väisänen, J. 2. Biological nitrogen fixation in organic and conventional grass-clover swards and a model for its estimation. Licentiate s thesis. University of Helsinki Department of Plant Production Section of Crop Husbandry. 42 p. + 2 app. 36

37 3. Effects of 1 % organic production on Funen, Denmark Ib Sillebak Kristensen 1, Ole Tyrsted Jørgensen 2 and Inge T. Kristensen 1 1 Danish Institute of Agricultural Sciences, Department of Agroecological, Research Group of Farming Systems, Post-box 5. DK-883 Tjele, DENMARK. 2 Fyns Amt (the Funen County), Nature Management & Water Environment Division, Oerbaekvej 1, 522 Odense S.E, Denmark. Contact: Ib Sillebak Kristensen, Tel , IbS.Kristensen@agrsci.dk Introduction Organic production has been found to lower the environmental impact compared to present conventional production. The effect is partly because of lower stocking rate and partly because of higher utilization of N-input (Nielsen and Kristensen, 25). The present organic production in Denmark is mainly milk production on specialized organic dairy farms, with a high stocking rate of 1.4 Livestock Units (LSU 1 ) per ha cultivated land and only 5% N-export in crop production (Kristensen et al., 25b). The milk production both use external inputs in feed, straw and animal manure. The input is partly conventional straw and pig manure and partly organic feed from mainly organic arable farms, which also have considerable external inputs from manure (33% of total N-inputs, Kristensen, 25a, 5 kg N/ha Berntsen et al., 24). A closer integration between animal and arable production within the same farm area is supposed to contribute to a better resource utilization and a lower environmental impact. In order to quantify the consequences of changing the present Danish Agriculture to organic production, a modelling approach has been developed. The aim was to analyse possible impact of organic production on the nutrient loss in the Baltic Sea compared to the present conventional situation. The Funen county has been chosen because it represent average stocking rate of.8 LSU/ha for the Danish agricultural production influencing the Baltic Sea. Also considerable previous work has been done on the Funen county in order to quantify the present environmental impact on the Baltic Sea (Madsen et al., 23 and Terlikowska et al., 2). Methods In Denmark data from all farms inclusive Funen - are available in 3 government databases: The Fertilizer Accounts, with data of fertilizer use and standard animal manure production, spreading and import/export. The Land use (General Agricultural Register), with data of ha per croptype(winterwheat, spring barley, grass/clover etc.). The Animal numbers (Central Husbandry Register), with data of present animal number of animal type (dairy cows, heifers, steers, sows, piglets, slaughter pigs, hens, chicken etc.). For each year 2,3 Danish farms Representative Accounts is available from economical data in the Farm Accountance Data Network (FADN-data) (Anon., 25). From the FADNdata the animal production and cash crop yields of organic production is deducted. Conventional cash crop yields from Funen are extracted from Danish Statistics 2. Only average yield per crop from the whole Funen County is available, and no data is available for organic yields from Funen. Therefore the organic grain yield is calculated from the national Representative Accounts. From 4 years the relative yield is calculated from 286 organic 1 1 LSU =.85 Frisian dairy cow or.34 heifer or steer or 36 slaughter pigs = 1 kg N from manure storage 2 Statbank Denmark, see 37

38 farms per year in relation to conventional yield, and the organic cash crop yield is calculated from average conventional yield reduced with the average yield reduction factor. For calculation of average yields for whole farm it is assumed than average N-yield of small area crops (seed-crops, lucerne and vegetables) gives average same N-yield as grain crops. For calculating the farm gate N- and P-balance the use of feed and nitrogen for feeding and animal products are calculated from the Representative Accounts, see Kristensen and Kristensen (24) for brief description and Dalgaard et al., (25) for details. The calculations assume standard Danish feed and protein requirements, in principle described in Poulsen and Kristensen (1998) and yearly updated. For this calculations standard livestock products are calculated from the number of Livestock Units (from Fertilizer Accounts ) and the animal production per LSU from Representative Accounts. The total feed requirement are calculated from standard feed requirement and with the N-requirement found by Nielsen and Kristensen (25): 22.1 % N-efficiency Herd of conventional dairy herds, 2.5 % N- efficiency Herd of organic dairy herds, 35.4 % N-efficiency Herd of pig herds, 48 % N- efficiency Herd of hens and chicken and 3 % of other animals. The N-feed requirement is calculated as N-products Animal /N-efficiency Herd, for example a dairy cow producing 4 kg N/cow has a N-requirement of 4/.221=181 kg N/cow/year. The feed- and proteinrequirement not fulfilled from home-grown roughage and grain is imported as feed from external source. For presentation specialized main farm types are calculated for main groups of farmers. The definitions of farm types is given by Larsen (23), shortly the dairy and pig farms have 9 % gross margin from dairy. Gross margin is defined in the FADN-data (Anon., 25). Arable farms grow more than 1 % area with sucker beets, seed crops or potatoes or they have less than.5 LSU/ha. The organic farms are divided into two groups: Dairy and all other organic farms, inclusive many hobby and part times farmers. Total Funen include also hobby and part time farmers. Fixation is calculated directly from the area of grass/clover. The level is set to the estimated level of around 5 pilot farms/year, during the period of In average a fixation of 15 kg N/ha on organic grass/clover and 1 kg N/ha on conventional grass/clover was estimated, assumptions and level for all crops is given in Kristensen et al., (25b) (appendix) and Nielsen and Kristensen (25). With the above assumptions the farm gate balance is calculated. The farm gate surpluses express the overall environmental losses (Halberg et al. 1995). The surplus can be divided into aerial losses of ammonia and denitrification, soil-n changes and an estimate of N- leaching can be calculated by difference. Aerial losses of ammonia were calculated using the emission coefficients of stall and houses mainly after Poulsen & Kristensen (1998), and updated by Hutchings et al (21) and Illerup et al (22) and the denitrification losses after Vinther & Hansen (24) respectively. The average weighted emissions are shown in the appendix of Kristensen et al. (25b). The P-balance is assumed equal as the Danish Representative Accounts only corrected for the present agricultural structure at Funen, in principle as nitrogen (Kristensen and Kristensen, 24). 38

39 Results Present agricultural production of Funen in year 22 Table 3-1 shows the agricultural production on Funen in year 22 based on data from Danish central registers. At the first 5 columns data from main farm types and organic farms are shown, they cover 66 % of the Funen agricultural area. On dairy farms the average herd size on conventional was 61 cows and 82 cows on organic farms. The average stocking rate on conventional dairy farms was 1.43 LSU/ha and.78 on organic dairy farms. 86 % of the conventional dairy farm area is part of a crop rotation. On conventional farms only 12 % of crop rotation is grown with grass/clover. On organic dairy farms the area grown with grass/clover is 36 % of the area. The remaining of the rotating area is mainly grown with cereals, partly for grain and partly for whole crop silage harvested 2-3 weeks before full ripe. Maize for silage has become important, mainly on conventional farms. Cereal grain yield was Scandinavian Feed Unit (SFU 1 )/ha on conventional farms and 31% lower on organic farms. Roughage yields were assumed to be on the average level of pilot farms, and the average yield of rotating crops is 5,7 SFU/ha 6,3 kg DM/ha on conventional dairy farms and 21% lower on organic farms, see appendix Kristensen et al. (25b). The milk yield level in 22 was 7,984 kg Energy Corrected Milk (ECM) milk/cow/year (Table 3-2) on conventional farms (Lauridsen, 25). Of the total SFU-intake by cows, 58% was home grown roughage on conventional farms and 75% on organic farms. An average level of protein was 18.4% of SFU 2% of DM. Pig farms have same stocking rate as conventional dairy farms LSU/ha. The crop production is like the arable farms, with % area grown with grain crops. On arable farms 14 % of the area is used for seed, vegetable and other special plant products. On organic arable farms the grain yield is only 6 % of the total arable area. In the right column of Table 3-1, the entire Funen area is presented on sandy loam and sandy soils, 6% of the area is on sandy loam with more than 1% clay of texture. Table 3-1. Farm characteristics on Funen in 22. Main time farmers 6) Not Funen Dairy Dairy Pig Arable dairy Sandy Sandy 4 Total conv. org. conv. conv. org. loam 5) Number of farms ,335 1,388 6,328 Livestock units 1) Cattle LSU 47, , ,814 24,434 66,476 Pig LSU ,856 9, ,595 4, ,446 Other LSU ,17 1,213 7,758 Area, incl. set aside & perm. grass ha 33, ,844 79,331 3, ,98 74, ,99 Stocking rate LSU/ha Area, incl. set aside ha/farm & perm. grass Set aside ha/farm SFU is equal to the feeding value of 1 kg grain. 39

40 Permanent grass ha/farm Area use of ploughed Grass/clover % of ha Maize & whole-crops % of ha Winter cereals % of ha Spring cereals % of ha Beets % of ha Rape % of ha Other % of ha Net yield Grass/clover 2) SFU 2 /ha 6, 5,52 6, 6, 5,52 6, 6, 6, Permanent 2) SFU/ha 2,32 2,18 2,32 2,32 2,18 2,32 2,32 2,32 Maize&whole-crops 2) SFU/ha 8,565 5,95 8,264 8,85 4,512 8,521 8,649 8,557 Cereals 3) SFU/ha 6,167 4,235 7) 6,422 6,385 3,22 7) 6,329 6,166 6,238 Peas 3) kg/ha 3,94 3,94 3,94 3,94 3,94 3,94 Winter rape 3) kg/ha 2,82 2,82 2,82 2,82 2,82 2,82 Total SFU/ha 6,756 3,984 6,625 6,542 2,889 6,444 6,463 6,411 1) 1 LSU =.85 Frisian dairy cow or.34 heifer or steer or 36 slaughter pigs from "DK Fertilizer Accounts", see 2) Average of pilot farms, , see appendix in Kristensen et al. (25b) 3) Funen average from Danish Statistic, StatBank: 4) < 1 % clay. 5) > 1 % clay, normally 1-15 %. 6) Main time farmers use more than 832 standard hours/farm/year, see Larsen (23) and Anon. (25) 7) Organic grain yield is calculated from an average of 286 farms/year in the period , Anon. (25) In Table 3-2, the N-balance in year 22 is calculated assuming that the Funen farmers have the same feed and product N- and P-turnover as the Danish average farmers, see Kristensen and Kristensen (24) and methods for assumptions. Artificial fertilizer and exchange of animal manure are measured values from individual farms; these amounts are included directly from the central register of Fertilizer Account. The farm gate N-efficiency Cash products is calculated form outputs of cash products only, which mean that exported animal manure is deducted animal manure import (=net animal manure import) before calculating the efficiency. Organic dairy farms have higher efficiency than conventional At the bottom of Table 3-2 the average losses are calculated. For calculations the same percentage losses per farm-type is used, also the soil-n changes is transformed from by Kristensen et al. (25b). The N-leaching are calculated by difference (the rest), and is shown is shown in the bottom of the table. In total the leaching from Funen is 63 kg N/ha, which is only 1 kg N/ha lower than the independent calculation made by Schrøder (24). As previous found the N-leaching calculated by difference is in good agreement of direct modelling of N- leaching (Kristensen et al (25). The conventional dairy farms have the highest N-surplus, denitrification and leaching, The pig farms has the highest ammonia volatilisation. The farm gate N-efficiency Cash Products is calculated with only cash products as outputs (output animal manure sold), and input as net animal manure input (input animal manure sold). The efficiency shows highest efficiency at conventional arable farms, and lowest efficiency at conventional dairy farms. 4

41 Table 3-2. Farm-gate balances of N on Funen in 22. Main time farmers 6) Not dairy Funen Units Dairy Dairy Pig Arable org. Sandy Sandy 4 Total conv. org. conv. conv. loam 5) Farm characteristics LSU 47, ,841 14, ,426 66, ,68 ECM milk/cow 7,984 Piglets/sow 21.5 Farm gate balance Inputs Artificial fertiliser kg N/ha Animal manure kg N/ha Net feed import kg N/ha Fixation kg N/ha Deposition kg N/ha Total inputs kg N/ha Outputs Milk kg N/ha Meat, cattle kg N/ha Meat, pigs kg N/ha Animal manure kg N/ha Grain export kg N/ha Vegetative products kg N/ha Total outputs kg N/ha Balance kg N/ha ) N-efficiency Cash Products % Ammonia losses % of N-surpl Ammonia losses kg N/ha Denitrification % of N-surpl Denitrification kg N/ha Nitrate leaching & soil- kg N/ha N change Soil-N change 8 kg N/ha (- breakdown + built up) Nitrate leaching kg N/ha ) < 1 % clay. 5) > 1 % clay, normally 1-15 %. 6) Main time farmers use more than 832 standard hours/farm/year, see Larsen (23) and Anon. (25) 7) N-efficiency Cash Products = (total outputs-output of animal manure)/(total inputs-output of animal manure) Dairy conv.= 32% = (88-16)*1/(237-16). 8) Soil-N changes are calculated with C-tool, see only in Danish, See for the Soil-N model included in the farm budgeting tool Farm-N. One day login: gst/guest 41

42 In Table 3-3, the P-balance is calculated to be 12 kg P-surplus/ha, which is 4% higher than Schrøder (24) and Nielsen et al (24). Due to feed minerals pig farms has the highest P- turnover, and the efficiency was highest on arable and organic farms. Table 3-3. Farm-gate balances of P on Funen in 22. Units Dairy conv. Main time farmers 1) Dairy Pig org. conv. Arable conv. Not dairy org. Total Funen Inputs Soy feed kg P/ha Grain kg P/ha Feed minerals kg P/ha Artificial fertiliser kg P/ha Animal manure kg P/ha Total inputs kg P/ha Outputs Vegetative products kg P/ha Meat kg P/ha Milk kg P/ha Animal manure kg P/ha Total outputs kg P/ha Balance kg P/ha P-efficiency Cash products % Feed minerals kg P/LSU Balance kg P/LSU ) Main time farmers use more than 832 standard hours/farm/year, see Larsen (23) and Anon. (25) Modelled agricultural production and emissions with 1 % organic production The assumptions for making Funen 1% organic are presented in Table 3-4. The details for the assumptions can be seen in Hermansen (1998), Alrøe & Kristensen (21), Anon. (1999) and Anon. (21). In order to illustrate the maximum benefit of organic production the scenario of 1% organic production with no external import has been calculated. In short the main assumptions were: o The same area as present situation. o 4% of the area is used for production of grass/clover in order to keep up the soil fertility at the minimum level of actual organic dairy farms with low stocking rate. At lower soil fertility the grain yield becomes unstable and sometimes low due to low N-level and infestation with weeds, especially rood weeds. o The dairy production is produced from 84% of roughage feed from grass/clover and 16% of grain feed, see Table 3-4. o 12% of the area is used for grain and vegetables for human consumptions. o The rest of the area in crop rotation (23% = (=whole crops and maize) 12 (=grain for human)-13 (=grain for cattle)) is used for organic pig production, where 9% area is grown with rape and peas in order to make a balanced feed ration for pig production. o The organic yields are assumed to be average from organic pilot farms studies, mainly after Halberg and Kristensen (1997). 42

43 Table 3-4. Farm characteristics on Funen in 22 and in Scenario Funen 1% organic. unit Funen 22 (conv.) Scenario 1% org. % of conv. Number of farms Area, incl. set aside & perm. grass ha Area, incl. set aside & perm. grass ha/farm Set aside ha/farm 2.4 Permanent grass ha/farm Area use of ploughed ha Grass/clover % of ha 4 4 Conv. maize or Org. whole crop % of ha 5 12 Winter cereals % of ha 41 4 Spring cereals % of ha 31 Beets % of ha 6 Rape % of ha Other (peas in org. scen.) % of ha Net yields assumed Grass/clover SFU/ha 6, 5,52 92 Permanent SFU/ha 2,32 2,18 87 Conv. maize & org. whole crop SFU/ha 8,557 3, 35 Undersown grass/clover SFU/ha incl. G/C 4 Cereals SFU/ha 6,238 3,4 55 Peas kg/ha 3,94 3, Winter rape seed kg/ha 2,82 1,5 53 Total SFU/ha 6,311 3, In Table 3-5, the production consequences of the farm characteristics assumptions in Table 3-4 are shown. The main results found are: o With high roughage uptake the milk production per dairy cow is depressed 25% compared to present level. o In order to use the fodder from 4% area grown with grass/clover the cattle herd shall be increased by 4% extra cattle livestock units. o The entire area used for cattle production is 65% of the area, leaving 23% of the area for pig feed production (23 = (= crops for human consumption)). o The pig production is assumed to rely on 1% from roughage and 6% grain. With this feed use around 28% of the present pig production can be produced on Funen. o It is assumed that production of cattle, human and pig products are produced within the same crop rotation in order to keep up the grain production to the same level as measured on present private cattle farms. So it is assumed that all farms produce both cattle and pig products. 43

44 Table 3-5 Production characteristics for Scenario Funen 1 % organic with no import. unit assumed value % of conv. Feed and area use for cattle Grass/clover & whole crop silage SFU/MPU Cereals SFU/MPU 1 32 No of cattle in herds MPU 7 7 No of cattle in herds LSU Cereals for cattle SFU Grass/clover, whole crop & perm. ha of Funen area Area use for cattle production ha of Funen area Livestock density on cattle farms on Funen LSU/ha.75 Feed and area use for pigs Grass/clover & whole crop silage SFU/PU 2 6 Cereals SFU/PU Peas SFU/PU Rape-cake SFU/PU 382 Cereals for pigs etc. ha of Funen area Cereals for pigs etc. SFU No of pigs PU No of pigs LSU Grass/clover & whole crop silage ha of Funen area Peas ha of Funen area Rape seed cakes ha of Funen area Area use for pigs ha of Funen area Livestock density of pig area on cattle farms LSU/ha.61 Manure production N-efficiency, cattle herd % N-production, cattle kg N/ha 19 N-production, cattle on grass kg N/ha 38 N-production, cattle in stable kg N/ha 72 N-efficiency, pig herd % N-production, pigs kg N/ha 36% 1 In Table 3-6, the farm gate balances and emissions are calculated when same coefficients of emissions as present agriculture are assumed. The main findings are: o The milk production per cow is reduced by approximately 25% less milk/cow and around 15% less milk from Funen County. o All male cattle were raised for steers and the cattle meat production was doubled compared to present situation. o The fertilizer and feed import is zero o The fixation input is increased mainly from the 4% grass/clover area with a fixation of assumed 15 kg N/ha. o The total inputs (only from fixation and deposition) were reduced to 4% of present inputs. 5 % if sold animal manure is deducted animal manure import. o The pig production is reduced to 2%, mainly because of lower pig number and partly because of lower productivity of only 19 slaughter pigs per sow compared to present 22. o The farm gate balance is reduced by 42%, bringing the farm gate N-surplus down to 59 kg N/ha. o With same coefficient of emissions and soil-n changes the balance will contribute to only 37 kg N-leaching per ha, around a 41% reduction compared to the present situation in year 22. o Without any external P-inputs the P-balance is about minus 6 kg P/ha. 1 MPU (Milk Producing Unit) =1 frisian dairy cow frisian heifer + 1 steer 2 1 PU (Pig Unit) = 1 year sow + 18,7 fattening pigs 44

45 Table 3-6 Farm gate N-balances of Funen in 22 and in Scenario Funen 1% organic. unit Funen 22 Scenario % of (conventional) 1% organic conv. Farm characteristics LSU LSU/ha kg ECM/cow piglets/sow Farm gate balance Inputs Artificial fertilizer kg N/ha 82 Animal manure kg N/ha 18 Net feed import kg N/ha 85 Fixation kg N/ha 5 66 Deposition kg N/ha Total inputs kg N/ha Outputs Milk kg N/ha Meat, cattle kg N/ha Meat, pigs kg N/ha Animal manure kg N/ha -18 Grain kg N/ha -38 Vegetable products kg N/ha Total outputs kg N/ha Balance kg N/ha N-efficiency Cash Products % Ammonia losses % of N-surplus Ammonia losses kg N/ha Denitrification % of N-surplus Denitrification kg N/ha Nitrate leaching & soil-n changes kg N/ha Soil-N change 1 (- break down, + built up) kg N/ha 3 3 Nitrate leaching kg N/ha ) Soil-N changes are calculated with C-tool, see Up scaling from farm production to N- and P-loading of the Baltic Sea. The calculated loss of nitrogen by leaching of 63 kg N/ha for Funen County 22 is nitrogen leaching from the root zone (1 meter depth) assuming actual average Danish farming practice. In the organic scenario this potential leaching is reduced by about 41 % to 37 kg N/ha. To calculate the potential reduction in the land based nitrogen loading due to the organic scenario presented, the actual retention percentage from root zone to watershed must be estimated taking the actual percolation of water into consideration, as well as the leaching from unfarmed land must be assumed. The contribution of leached nitrogen from nature and/or non-arable land can be roughly estimated to about 1 kg N/ha per year (Grant et al., 24). At the hydrological pathway from root zone to the coastal waters a substantial part of the leached nitrogen will be retained (mainly chemical denitrification) and the retention percentage may be described as the percentage of nitrogen leaving the root zone but not entering the coastal waters. 45

46 In 22 about 67 percent of the total area of Funen County was arable land (Anon., 22) and the N leaching can be calculated as (,33*1 kg N/ha) + (,67* 63 kg N/ha) = 46 kg N/ha per. The estimated actual diffuse N loading to the See from Funen County territory can roughly be estimated to about 16 kg N/ha per year in the period (Fyns Amt, 25), giving a retention percentage of about 65 percent. This is somewhat higher than normally expected for Funen County which is normally estimated to about 5 percent (Windolf, 25) but also based on the assumption of a loss of nitrogen from the root zone of farmed land of about 5 kg N/ha per year (Børgensen, 24). Assuming that the long term retention percentage is independent of the level of nitrogen leaving the root zone, the nitrogen loading to the Sea from the organic scenario can be calculated to (,33*1 kg N/ha) + (,67*37 kg N/ha) = 28 kg N/ha per year and a resulting diffuse nitrogen loading to the sea of about (1-,65) * 28 = 1 kg N/ha which is a reduction of around 39% of the N loading from diffuse sources compared to the situation of Funen County 22. Calculating nitrogen loading to the Baltic Sea, also the nitrogen loading from point sources (wastewater facilities and industries) should be taken into consideration. The N loading from point sources, has been estimated to an average of about 37 tons N per year in the 21-4 period (Fyns Amt, 25), which is about 1 kg N/ha per year. Taking this into consideration the organic scenario might reduce the nitrogen loading to the Baltic See from about 17 kg N/ha to about 11 kg N/ha or a reduction of 35 percent. Phosphorus may be lost from arable land to the aquatic environment through different pathways: surface loss, brink erosion, drainpipes run off, groundwater run off, and by wind and precipitation. The phosphorus loss may also be divided in two fractions with different origin: water soluble phosphorus loss and particle bound phosphorus loss (e.g. soil erosion, brink loss, wind and precipitation loss). For the period the total phosphor loading to the Sea from Funen County has been estimated to,47 kg P/ha/year. Around 24 percent of this loading is due to outlets from point sources (,11 kg P/ha/year), 27 percent is background loss (,13 kg P/ha/year) and 49 percent is from agricultural land and scattered settlements (,23 kg P/ha/year) (Fyns Amt 25). Too roughly estimate possible changes in P loading to the See due to changes in the farm gate balance, phosphor loss might be divided into particle bound phosphor loss and water soluble phosphor loss. Due to the very large pool of particle bound phosphorus in the Danish agricultural soils the loss of particle bound phosphor may be assumed to stay at its present level for the next many years independently of the agricultural practices. Some long term benefits, however, may be expected but is due to the implementing of other actions than organic farming, e.g. use of narrow strips of fallow along streams in order to reduce brink erosion. It has been estimated that phosphorus loss by brink erosion (particle bound phosphor loss) may constitute as much as about 5% of the total phosphorus loss from diffuse sources (Nielsen et al. 24). In Funen County in 24 it has been estimated that about 5% of the total phosphorus loss (including point source loss) is particle bound phosphorus (Brendstrup 25). 46

47 Any reduction of phosphorus loading to the Sea therefore must be expected to be seen due to changes in the loss of water-soluble phosphor. As no clear links between water soluble phosphorus loss and agricultural practices (e.g. supply of animal manure) have been established on the catchments scale no exact prognosis for the environmental benefit of changes in the P balance from a surplus to a negative balance of phosphorus can be made. Therefore, assuming that brink erosion or particle bound phosphorus loss may be as much as 5 percent of the P loss from agriculture and scattered settlement the water soluble part of the total loss would be about,11-,12 kg P/ha/year. Depending of the relation between water soluble phosphorus measured in streams and phosphor surplus on agricultural lands (e.g. in related to animal density), the potential reduction of phosphorus loading to the Baltic Sea due to the negative P balance in the organic scenario would be between,,12 kg P/ha/year or - 25 percent of the present loading. Furthermore local effects on e.g. lakes and near costal waters to a higher extent will be a result. Discussion The conversion of mainly conventional Funen agriculture for 1 % organic production was calculated in accordance to the principles outlined in the Danish Bichel-work, Anon (21). The political initiated Bichel-work made consensus amongst different disciplines within agronomical, environmental and economical researchers in Denmark, and the technical assumptions were agreed, which to a high degree assured that all known aspects up till year 1996 were included in calculations. With great uncertainty was calculated that the nitrogen for soil (leaching and soil-n changes) could be reduced by up to 5 % with the scenario of 1% organic production with imports. This scenario has been recalculated for the Funen County in year 22; this time the leaching loss was calculated to a 41% reduction compared with the conventional situation in year 22. The level is expected to represent the Bichel -year 1996 also, because the N-surplus of the Funen agriculture was the same until 22 (Schrøder, 24). The results of balance is calculated with great uncertainty, especially the result depend on the plant yield level, the N-input of the N-fixation and deficits of nutrients with no external inputs. These uncertainties are discussed in Anon (21) and the consequence of six scenarios can be looked up. Also the distribution of N-surplus into pools of losses are simplified assuming that level of losses are at the same level as the present agriculture, and the calculated level of N-leaching from surplus minus aerial losses and soil-n changes include these uncertainties. It could be recommended to calculate the N-leaching with alternative methods as well, all though this method of difference calculated N-leaching has been able to achieve the same level as model calculated N-leaching (Børgesen et al. 24 and Kristensen et al., 25a). With better technique -when adjustment and innovation is going on within the organic restrictions- it could be expected that organic production could improve output, the aerial N-losses could be reduced, and the fixation increased. Also higher level of accumulated soil-n could be assumed in the organic scenario when the grass/clover area is increased from 4 to 4% of the crop rotation (Knudsen et al., 25). All the above expected changes would reduce N-leaching further than the calculated 5%, so the level of leaching reduction is not unrealistic. However the 1 % organic production makes dramatically changes in the agricultural production: 4 % area with grass/clover equal distributed between all fields, double of cattle meat production, 7% reduction of pig production. The structural change from mixed milk/pig-production to mainly cattle production made the farm gate N-efficiency (output/input) 1% lower with the organic scenario compared with the present situation (see Table 3-6). The Socioeconomic consequences are dramatically and can be seen in Anon. (21). 47

48 The effects on the N-loadings on the Baltic Sea is calculate to a bit less (39%) than the 41 % reduction in nitrate leaching in 1 m depth, because 33% not agricultural area with only low leaching level of 1 kg N/ha - is included in the total loadings. In the organic scenario no P is imported, which with the output gives a deficit of 6 kg P/ha. The P-loading for the Baltic Sea is mainly influenced by the particle bound P which may be assumed to stay constant at the present level. The P-loading is calculated to only -25% reduction even though the surplus can be reduced from a surplus of 13 kg P/ha to negative balance of 6 kg P/ha. References Alrøe, H. F. and Kristensen, E. S. Matthies, M., Malchow, H., and Kriz, J. 21: Researching alternative, sustainable agriculture systems. A modelling approach by examples from Denmark.Integrative Systems Approaches to Natural and Social Dynamics Anon. 1999: Organic Scenarios for Denmark. The Bichel Committee, MILJØstyrelsen. Sekretariat for pesticidudvalget. Anon. 21: The Bichel Committee Report from the Bichel Committee - Organic Scenarios for Denmark. Report from the Interdisciplinary Group of the Bichel Committee Anon. 25: The Farm Accountancy Data Network (FADN) is an instrument for evaluating the income of agricultural holdings and the impacts of the Common Agricultural Policy. Berntsen, J., Petersen, B. M., Kristensen, I. S., and Olesen J.E. 24: Nitratudvaskning fra økologiske og konventionelle planteavlsbedrifter. - simuleringer med FASSET bedriftsmodellen. DJF rapport.markbrug 17, Brendstrup. 25. Børgesen et al. 24. Fyns Amt. 25. Halberg, N., Kristensen, E. S., and Kristensen, I. S. 1995: Nitrogen turnover on organic and conventional mixed farms. Journal of Agricultural and Environmental Ethics 8, Hermansen, J. E. 1998: Samhørende værdier for foderforbrug og produktion i økologiske husdyrproduktionssystemer., 1-8. Hutchings, N., Sommer, S. G., Andersen, J. M., and Asman, W. A. H. 21: A detailed ammonia emmision inventory for Denmark. Atmospheric Environment 35, Illerup, J. B., Birr-Pedersen, K., Mikkelsen, M. H., Winther, M., Gyldenkærne, S., Bruun, H. G., and Fenhann, J. 22: Projektion Models 21. Danish emissions of SO 2, NOX, NMVOC and NH3. NERI Technical Report 414, Knudsen, M. T., Kristensen, I. S., Berntsen, J., Petersen, B. M., and Kristensen, E. S. 25: The effect of organic farming on N leaching. Submitted. Journal of Agricultural Science, Kristensen, E. S., Høgh-Jensen, H., and Kristensen, I. S. 1995: A simple model for estimation of atmospherically-derived nitrogen in grass-clover systems. Biological Agriculture and Horticulture 12[3], Kristensen, I. S. 22: Principles and methods for collecting and evaluation nutrient balances, Danish Institute of Agricultural Science. Lithuanian Dairy Farms Demonstration Project. 48

49 Kristensen, I. S. 25a: Nitrogen balance from cash crop farms (22). Kristensen, I. S. 25b: Nitrogen balance from dairy farms (22) Kristensen, I. S. 25c: Nitrogen balance from pig farms (22). Kristensen, I. S., Dalgaard, R., Halberg, N., and Petersen, B. M. 25a: Kvælstofbalance og - tab fra forskellige bedriftstyper. Plantekongres og Planteproduktion i landbruget, 1-2. Kristensen, I. S., Halberg, N., Nielsen, A. H., and Dalgaard, R. 25b: N-turnover on danish mixed dairy farms. Part II. In: Bos,J.; Pflimlin,A., Aarts,F. and Vertés,F.(Eds): "Nutrient management on farm scale. How to attain policy objectives in regions with intensive dairy farming. Report of the first workshop of the EGF Workshop. d255b11f22d.pdf. Plant Research International. 83, Kristensen, I. T. and Kristensen, I. S. 24: Farm types as an alternative to detailed models in evaluation of agricultural practise in a certain area. Oral precentation on MIS 24: "Fourth International Conference on Management Information Systems, incorporating GIS and Remote Sensing September 24. Malaga, Spain., 1-1. Larsen, I. 23: LCAproject.Method description. htp:/ww.lcafood.dk/processes/agriculture/methoddescription.pdf, Goto Processes; Agriculture; Farm types; Larsen et al., 23. Madsen Nielsen, K., Andersen, H. E., Larsen, S. E., Kronvang, B., Stjernholm, M., Styczen, M., Poulsen, R. N., Villholt, K., Krogsgaard, J., Dahl-Madsen, K. I., Friis-Christensen, A, Uhrenholdt, T., Hansen, I. S, Pedersen, S. E., Jørgensen, O., Windolf, J., Jensen, M. H., Refsgaard, J. C., Hansen, J. R., Ernstsen, V., Børgesen, C. D., and Wiggers, L. 24: Odense Fjord - Scenarier for reduktion af næringsstoffer485, København, Danmarks Miljøundersøgelser, Miljøministeriet. Poulsen, H. D. and Kristensen, V. F. 1998: Standard values for farm manure. A revaluation of the Danish standard values concerning the nitrogen, phosphorus and potassium content of manure. Danish Institute of Agricultural Science report Animal Husbandry. 7, Schrøder, H. 24: N- og P-regnskaber for landbruget i Fyns Amt og Danmark 1984/85-21/2., Danedi for Fyns Amt. Terlikowska, K., Muus, K., Antsmäe, H., Effenberg, G., Joelsson, A., Kolk, M., Koppe, A., Maximova, L., Nilsson, B., Pedersen, S. E., Pevnev, E. N., Steinmann, F., Westberg, V., and Smeds, L. Muus, K. and Pedersen, S. E. 2: BERNET Theme Report: Sustainable Agriculture and Forestry, BERNET. Vinther, F. P. and Hansen, S. Vinther, F. P. and Hansen, S. 24: SimDen - en simpel model til kvantificering af N2O-emission og denitrifikation. see DJF rapport Markbrug. 49

50 4. Nitrogen and phosphorus leakage in ecological recycling agriculture Thomas Schneider 1), Miia Kuisma 2) and Pentti Seuri 2) 1) Department of Physical Geography and Quaternary Geology, Stockholm University, SE Stockholm, 2) MTT Agrifood Research Finland, Ecological Production, FI-51 9 Juva, Finland Introduction Organic farming is often considered as one solution to reduce eutrophication of the Baltic Sea. However, the efficiency of organic agriculture in reducing nutrient leakage from primary food production to the aquatic environment is still questioned. The most crucial part of organic agriculture for reducing nutrient leakage is nutrient management in the crop rotation. Nutrient balance studies showed that ecological recycling agriculture (ERA) had lower nutrient surplus and thus, lower potential of leakage (this report and Granstedt and others, 24). However, direct measurements of nutrient leakage in ecological agriculture are scarce. Bergström and Kirchmann, 2 reviewed the available literature on nitrogen leakage in organic agriculture and concluded that organic agriculture seems to have lower nitrogen leaching per hectare than conventional systems but differences were small and they were sensitive for small changes in either production system. The nitrogen leakage per mass of produced crops was higher in organic agriculture. They summarized, that nitrogen leakage is more a question of nitrogen management, e.g. crops and crop rotation, than of production system. They believed that a decrease of nitrogen leakage can be achieved by optimizing the conventional system. However, Bergström and Kirchmann, 2 did not consider differences of different organic systems. ERA is a nutrient extensive system based on an animal density adjusted to the own fodder production on each farm unit, which has a potential of low N- leakage (Granstedt and others, 24). In this report we quantify nitrogen and phosphorus leakage on three ERA farms in the BERAS project. The study is based on direct measurements of nitrogen and phosphorus concentration in drainage water and water flow measurements. The results are compared with calculated standard leakage as reported to the HELCOM PLC-4 report (Brandt and Ejhed, 22, HELCOM, 24). Methods Physical settings of the test fields The test sites in Sweden are located at Skilleby farm in Järna, 5 km south of Stockholm, and on Solmarka farm, 2 km south of Kalmar (Fig. 4-1 and Figure 2-3). Both Skilleby and Solmarka farm are managed according to the biodynamic farming practice since the 196:s and 197:s, respectively. The five-year crop rotation consists of three years of ley followed by winter cereals and spring cereals with insown clover grass. Skilleby farm is managed by the nearby Yttereneby farm and the animal density corresponds to.6 au/ha. Solmarka has its own cows and cattle and an animal density of,7 au/ha. The Finnish test site is located in Juva 27 km north of Helsinki (Figure 4-1 and Figure 2-3). Organic farming practices have been applied since The six year mixed crop rotation consists of one year of spring cereal and grass seeds, two years of grassland followed by 5

51 winter cereal, green manure, and spring cereal. Approximately 3 t/ha cattle sludge is spread continuously on the 1 st year plot which equals about.3 au/ha for the whole crop rotation per year. Harvested grain yields as net yields amounted to about 2 t DM/ha and grass yields to about 6 t DM/ha. The physical characteristics of the test fields are summarized in (Table 4-1). For more background information on the three investigation farms see Seppanen, 24 and. Granstedt and others, 24 Figure 4-1 Map of investigation fields in Skilleby (6), Solmarka (1) and Partala (14) with sampling site, drainage area and drainage system. Number in brackets according to location map (Figure 2-3). Farm characteristics are shown in Table 4-1. Table 4-1. Characteristics of test fields at Skilleby, Solmarka and Partala farm. Skilleby farm Solmarka farm Partala farm Available data /25-4/25 Soil type Clay Sandy loam - Moraine silty loam Mean air temperature ( C) 6.6 7,3 4 1) Mean precipitation (mm/a) ) Total drainage area (ha) ) Juva ) Mikkeli Data sampling Skilleby farm. Water samples were sampled manually every second week at the outlet of a drainage pipe from the test field. The samples were analysed on N-and P-concentration in accredited laboratories. Nutrient concentration was interpolated linearly between two sampling events. Water stage was measured continuously at a V-notch thin plate weir (9 ) by a pressure transducer. Stage values were transformed into discharge data by applying standard hydraulic equations (e.g. Shaw, 1993). The product of daily mean values of water discharge and interpolated nutrient concentration data yielded nutrient load from the test site. Air temperature and precipitation were measured continuously by an automatic climate station located in the test field. Solmarka farm. Water samples were sampled manually every week at the outlet of a drainage pipe from the test field. The samples were analysed on N-and P-concentration 51

52 according to accredited methods. Nutrient concentration was interpolated linearly between two sampling events. Water discharge was measured directly during the sampling events by means of a calibrated bucket and was interpolated linearly between sampling events. Discharge data was multiplied with measured nutrient concentration to obtain nutrient load. Air temperature and precipitation were measured continuously by an automatic climate station located in the test field. Partala farm. The test field at Partala consists of five plots with five of six crops in an entire crop rotation cycle. The drainage water from the plots is directed to a V-notch weir where water stage is measured continuously with a pressure transducer. Water samples were taken manually in proportion to water flow (once a day to once a week). The water samples were analysed for both total and soluble nitrogen and phosphorus, total solids, ph and conductivity. Nutrient concentration will be interpolated linearly between two sampling events. An automatic climate station located nearby the test field measured air temperature continuously and precipitation is measured manually every day. However, measurements at Partala started in April 25, thus, no results on nutrient leakage are available yet. Comparison with TRK The obtained results at Skilleby and Solmarka on annual nutrient leakage were compared with official Swedish leakage data published as the TRK-report (Brandt and Ejhed, 22) and reported to the Helcom pollution load compilation (HELCOM, 24). The TRK data was based on modelling nitrogen leakage with the SOIL-N (Johnsson and others, 1987) and HBV-N model (Arheimer and Brandt, 1998). The models simulate nitrogen leakage depending on soil type and crops. The TRK-dataset was normalized for long-term climatic fluctuations. In order to obtain comparable values of nutrient leakage, the standard values for the test fields were calculated from the standard leakage data in the TRK area 22 (Solmarka) and 6 (Skilleby) as presented in Table 4 in the TRK-report (Brandt and Ejhed, 22). The standard nitrogen leakage was calculated for soil type and grown crops. Standard phosphorus leakage, P L, (kg km 2 /year) was calculated according to Brandt and Ejhed, 22 and Ulén and others, 21 by the following equation: P L = ( LD +.3 S +.25 P HCl ) Q, (1) where S = (8. x clay x silt +.3 x sand ) ρ.1 (2) LD Livestock density (livestock unit ha -1 ) S Soil specific area (m 2 m ) P HCl HCl extractable phosphorus (mg/1 g dry soil) ρ Bulk density of soil = 125 kg m -3 x clay Clay fraction in top soil (-3 cm), < 2 µm x silt Silt fraction in top soil (-3 cm), 2 µm 6 µm x sand Sand fraction in top soil (-3 cm), 6 µm 2 µm Q Runoff (mm) 52

53 Results and discussion Standard leakage - TRK Nitrogen leakage from the test fields calculated according to the method described in the TRK-report (Brandt and Ejhed, 22) was 5.3 kg/ha year in Skilleby and 9.2 kg/ha year in Solmarka (Table 4-2 and 4-3). Table 4-2. Nitrogen leakage at Skilleby calculated from standard leakage defined in TRK report (Brandt and Ejhed, 22). N TRK - standard leakage depending on soiltype, crops and climate zone according to TRK. N TRK-Skilleby is calculated as the product of N TRK and the share of the respective soiltype and crop Area ha Share Soiltype Crops N TRK kg/ha year N TRK-Skilleby kg/ha year 8,8 35% Clay Oats ,73 43% Clay Ley 2.9 5,7 22% Forest ,8 35% Clay Ley 2.7 9,73 43% Clay Winterwheat ,7 22% Forest Table 4-3. Nitrogen leakage at Solmarka calculated from standard leakage defined in TRK report (Brandt and Ejhed, 22). N TRK - standard leakage depending on soiltype, crops and climate zone according to TRK. N TRK-Solmarka is calculated as the product of N TRK and the share of the respective soiltype and crop. 24 Area ha Share Soiltype Crops N TRK kg/ha year N TRK-Solmarka kg/ha year,93 8% Sandy loam Ley 6,5 7,47 68% Silty loam Ley 3 2,,74 7% Silty loam Potatoes 31 2,1,74 7% Silty loam Winter wheat 24 1,6,37 3% Silty loam Broccoli 27,9,75 7% Silty loam Oats 3 2, Standard phosphorus leakage was calculated according to equation (1) to.13 kg/ha year in Skilleby and to.14 kg/ha year in Solmarka. Input data are summarized in Table 4-4 and 4-5. Table 4-4. Input data from Skilleby farm to calculate phosphorus leakage according to TRK (Brandt and Ejhed, 22). P forest is standard leakage for forest, other parameters are defined in the text. Parameter Units References Area 22.6 ha Forest 2% Arable land 8% LD.6 LU/ha Granstedt and others, 24 S m 2 /m 3 P HCL 55 mg/1 g dry soil SBFI, 22 ρ 125 kg/m 3 Ulén and others, 21 x clay.43 Granstedt, 199 x silt.57 Granstedt, 199 x sand.24 Granstedt, 199 Q 23/4 121 mm 53

54 Q 24/5 185 mm P forest.45 kg/ha a Ulén and others, 21 Table 4-5. Input data from Solmarka farm to calculate phosphorus leakage according to TRK (Brandt and Ejhed, 22). All parameters are defined in the text. Parameter Units References Area 11. ha LD.7 LU/ha Granstedt and others, 24 S m 2 /m 3 P HCL 5 mg/1 g dry soil Eriksson, 1997 ρ 125 kg/m 3 Ulén and others, 21 x clay.15 Bernhard, 25 x silt.55 Bernhard, 25 x sand.3 Bernhard, 25 Q 23/4 163 mm Climatic and hydrologic conditions Measured precipitation is often lower than real precipitation because of losses due to evaporation from the rain gauge and due to wind effects. Results from discharge and precipitation measurements were compared with official data from the Swedish Meteorological and Hydrological Institute (SMHI). Precipitation at Skilleby was ~2% lower and runoff was ~3% lower than at the surrounding SMHI stations (Table 4-6). The difference in precipitation fits into the general precipitation pattern. However, the difference in runoff might have been caused by measuring errors e.g. ice damming in winter and during the spring flood event or leakage of water besides the gauging station. Accordingly, measured runoff was assumed to underestimate real runoff by 1%. Differences were larger at Solmarka. Runoff at Ljungbyån was three times as large as at Solmarka whereas precipitation was similar to that at the SMHI station. The lower runoff at Solmarka is most probably an underestimation of real runoff due to the lack of continuous measurements and difficulties of measuring high discharges at the outlet of the drain pipe. Additionally, there is only one year of data available. More data is needed to draw reasonable conclusions. All results from Solmarka are based on corrected runoff, where measured runoff was multiplied by 3.3 according to the relationship between runoff at Solmarka and runoff at Ljungbyån (Table 4-6). Table 4-6. Runoff and precipitation for the period at Skilleby and Solmarka and at different gauging stations from the Swedish Meteorological and Hydrological Institute (SMHI). The SMHI stations are located ~16 km from the investigation sites. Coordinates are given in local Swedish Grid (RT9, 2.5g W) Location Runoff (mm) Location Precipitation (mm) Skilleby N 11 Skilleby N E E Trosaån N 165 Gnesta N E E Saxbroån N E 172 Södertälje N E 634 Solmarka Ljungbyån N E N E 5 Solmarka N E 163 Kalmar N E

55 The regions of Skilleby and Solmarka had similar climatic conditions during the normal period of the TRK project (Precipitation, P = 65 mm, Mean air temperature, T = 7 C) (Johnsson and Mårtensson, 22). Compared to the investigation period in the BERAS project, the Skilleby region had similar conditions (Södertälje: P = 634 mm, T = 6,8 C). The Solmarka region, however, was dryer (Solmarka: P = 566, T = 7,3 C). Thus, the climatic influence on nutrient leakage is similar at Skilleby during both the TRK period and the BERAS investigation period which implies that differences in nutrient leakage solely depend on crops and the production system. At Solmarka, however, lower precipitation might cause lower nutrient leakage than during the TRK period. Measured leakage from ERA Water discharge, nitrogen and phosphorus concentration are shown in Figure 4-2 and 4-3. Discharge follows the usual pattern with flood events in fall and during the snow melt in spring and low discharge during summer. This results in high variability of nutrient load where large amounts can be leached during some few flood events. The difference between nutrient concentration in summer 23 and 24 at Skilleby were due to dry conditions in 23, where no samples were taken. However, nutrient load is not affected significantly as discharge is low during summer. P conc (mg/l) P conc (mg/l) N conc (mg/l) 2 1 N conc (mg/l) Discharge (l/s).4.2 Discharge (l/s) Figure 4-2. Discharge, nitrogen and phosphorus concentration, Skilleby P conc (mg/l) N conc (mg/l) Discharge (l/s) Figure 4-3. Discharge, nitrogen and phosphorus concentration, Solmarka Annual nutrient load is summarized in Table 4-7. In Skilleby, nitrogen leakage in 23/4 was of the same magnitude as standard leakage for this area in the TRK project, but for 24/5 it was the double. Nitrogen load differs significantly between the two years, whereas differences in phosphorus leakage were smaller. The large N-leakage 24/5 most probably 55

56 can be explained by releasing fixed nitrogen due to ley ploughing of half of the drainage area and spreading of manure on the same area during fall 24. Further analyses and measurements are necessary to study whether mineralization of organically fixed nitrogen in the manure can produce enough movable nitrogen during such a short time. Even in Solmarka a large part of the field area was grassland which was ploughed in fall 24 causing large nitrogen pulses. However, results from Solmarka are uncertain due to difficulties in discharge measurements. Table 4-7. Nitrogen and phosphorus leakage at Skilleby and Solmarka in comparison with the standard leakage according to the TRK-project (Brandt and Ejhed, 22). N TRK was calculated according to data shown in Table 4-2 and Table 4-3. P TRK was calculated according to Equation 1. N kg/ha year N TRK kg/ha year P kg/ha year P TRK kg/ha year Skilleby 23/ Skilleby 24/ Solmarka 24/ ) 9.2 1).14 1).19 1) 1) Results are based on corrected runoff, see text for more details. It is always difficult to draw conclusions about general nutrient leakage from a two year data series in a five-year crop rotation system. Nevertheless, we can try to generalise our two-yearresults to a larger scale. The test fields at Skilleby farm consist of two lots, on which ley was ploughed in 24 on one lot and in 25 on the other one. In a five-year crop rotation on two fields there are two years of ley-ploughing and three years of non-ley-ploughing. Assuming, the 23/4 results being representative for a non-ley-ploughing season (N nlp ) and the 24/5 results for a ley-ploughing season (N lp ), mean nitrogen leakage (N mean ) can be estimated as: 2 N nlp + 3 Nlp N mean = (3) 5 By applying this relationship, mean nitrogen leakage from the test fields at Skilleby farm was calculated to 8.14 kg/ha N. The TRK results are calculated for respective area with its characteristic climate, soiltypes and livestock density. In the TRK area 6 (Skilleby) livestock density is.2.4 au/ha (Granstedt, 2) whereas Skilleby farm has a livestock density of.6 au/ha. Nutrient surplus is strongly depending on livestock density. As shown earlier in this report (see Chapter???) nitrogen surplus can be decreased by 4% by halving livestock density. The ERA farm produces ~4% more nitrogen leakage than farms with a 5% lower livestock density in the same area. Taking livestock density into account nitrogen leakage from ERA is of the same magnitude as the calculated standard leakage in the respective TRK area. In the TRK area 22 (Solmarka) mean livestock density is.8-1 au/ha. Solmarka farm has a livestock density of.7 au/ha and a nitrogen leakage twice the leakage calculated in the TRK project. This is similar to the results at Skilleby during the ley-ploughing season. However, the results are limited and crop rotation is more complicated at Solmarka with several fields and crops than at Skilleby. More data is needed to draw reliable conclusions. Phosphorus leakage from ERA is ~.2 kg/ha year which confirms the calculated P leakage in the TRK project. The calculation of phosphorus in the TRK project depends mainly on livestock density (see Equation 1). 56

57 Comparison with nutrient balances Mean nitrogen surplus of all 36 BERAS farms was 36 kg/ha year. With ammonium losses of 3% respective 4%, the theoretical nitrogen leakage from the ERA farms in the project were 1 respective 7 kg N/ha year, assuming that leakage and denitrification in the soil contribute with equal parts. In addition, Skilleby farm has a livestock density of.6 au/ha which is similar to the mean of all BERAS farms. Mean leakage at Skilleby was calculated above to 8.1 kg/ha year. These results are, thus, in good agreement with results from the nutrient balances. Phosphorus surplus for all BERAS farms was calculated in Chapter 2 to -1 kg/ha year. Together with a measured leakage of.2 kg/ha year this indicates a constant loss of phosphorus from the fields, which most probably is fed by weathering of bedrock material in the soil matrix. Conclusions Within the BERAS project direct measurements of nitrogen and phosphorus leakage from fields were carried out on two ERA farms in Sweden and one in Finland. The data series which is available contains two years of measurements on Skilleby farm (Stockholm County). The data series from Solmarka farm (Kalmar County) and from the Finnish test farm in Partala were too short and are not reported here. The results from the measurements from Skilleby farm lead to the following conclusions: Nitrogen and phosphorus leakage from the ERA farm in Stockholm County were 8 kg N/ha year and.2 kg P/ha year, respectively. These results are in good agreement with the official nutrient leakage calculated in the TRK project for the same area, when taking into account differences in livestock density. The measured nitrogen leakage supports the results from the nutrient balances in the previous chapter of this report, where nitrogen leakage is 7-1 kg/ha year depending on the magnitude of ammoniac loses. The measured phosphorus leakage together with the deficit in the nutrient balances indicate a constant loss of phosphorus from the soil which most probably is fed by weathering of bedrock material in the soil matrix. References Arheimer, B. and M. Brandt Modelling Nitrogen Transport and Retention in the Catchments of Southern Sweden. Ambio, 27(6), Bergström, L. and H. Kirchmann. 2. Är övergång till ekologisk odling ett sätt att minska utlakningen av kväve från åkermark? In: G. Torstensson, A. Gustafson, L. Bergström and B. Ulén (Editors), Utredning om effekterna på kväveutlakning vid övergång till ekologisk odling (Investigation of the effects of conversion to ecological (organic) agriculture on nitrogen leaching - English summary). Ekohydrologi 56. Swedish University of Agricultural Sciences, Division of Water Quality Management, Uppsala, Bernhard, B. 25. Personal communication, May 25. Brandt, M. and H. Ejhed. 22. TRK Transport Retention Källfördelning. Belastning på havet. Naturvårdsverket, SE Stockholm, Rapport 5247, 12 p. Granstedt Fallstudier av kväveförsörjning i alternativ odling. (Case studies on the flow and supply of nitrogen in alternative farming. In Swedish with English summary.). Swedish University of Agricultural Sciences, Uppsala, PhD Dissertation. Alternativ odling 4. Granstedt, A. 2. Increasing the efficiency of plant nutrient recycling within the agricultural system as a way of reducing the load to the environment - Experience from Sweden and Finland. Agriculture Ecosystems and Environment, 8(1-2), Granstedt, A., P. Seuri and O. Thomsson. 24. Effective recycling agriculture around the Baltic Sea - Background report. BERAS report 2. CUL - Sveriges Lantbruksuniversitet, Uppsala, Ekologiskt Lantbruk

58 HELCOM. 24. The Fourth Baltic Sea Pollution Load Compilation (PLC-4). Helsinki Commission, Baltic Marine Environment Protection Commission, Baltic Sea Environment Proceedings 93. Johnsson, H., L. Bergström, P.-E. Jansson and K. Paustian Simulated nitrogen dynamics and losses in a layered agricultural soil. Agric. Ecosystems Environ, 18, Johnsson, H. and K. Mårtensson. 22. Kväveläckage från svensk åkermark. Beräkningar av normalutlakning för 1995 och Underlagsrapport till TRK. Naturvårdsverket, SE Stockholm, Rapport 5248, 89 p. SBFI. 22. Measurements of phosphorus in soils on Skilleby research farm. Swedish Biodynamic Research Institute. Unpublished report. Seppanen, L. (Editor). 24. Local and organic food and farming around the Baltic Sea. Ekologiskt jordbruk, 4. Centre for Sustainable Agriculture (CUL), Swedish University of Agricultural Sciences, Uppsala, 98 p. Shaw, E.M Hydrology in practice. Chapman & Hall, London, 539 p. Ulén, B., G. Johansson and K. Kyllmar. 21. Model predictions and long-term trends in phosphorus transport from arable lands in Sweden. Agricultural Water Management, 49,

59 5. Global warming and fossil energy use Olof Thomsson, Swedish Biodynamic Research Institute, Järna Sweden Christine Wallgren, fms, Stockholm University, Sweden Global warming and energy use are two environmental impact categories that are closely connected to each other since much of the greenhouse gas emission is caused by burning of fossil fuels. However, also emission of methane and nitrous oxide in agriculture and in industry are contributing to global warming. The aim of this part of BERAS was to compare the environmental impacts of conventional and alternative system settings in the three most important parts of the food chain: the agriculture, the transports and the food industry. The agriculture and food industry were assessed by Olof Thomsson while the transportation energy use assessment was performed by Christine Wallgren, Center for Environmental Strategies Research (fms), Royal Institute of Technology, Stockholm. At the end of the chapter, a section written by Olof Thomsson presents the global warming impact and consumption of primary energy resources in the transportation and processing parts of the food chain. For the agriculture, the assessment concerns comparison of conventional and ecological recycling agriculture, the latter earlier in this report defined as ERA. In this section, both the inventory results and the environmental impact results are reported together. For the transportation and food processing assessments, the comparison concern conventional large-scale systems vs. local more small-scale systems. In the transports section, existing local distribution of locally produced food in Järna and the conventional long-distance transportation of the same product groups found in Järna stores were compared. For the food industry, the same small-scale food processors operating in Järna were assessed and compared to large-scale food processing industries. For both these system parts, the inventory results of direct and in-direct energy and resource use first are reported separately. Then, the environmental impact results are reported together for the two parts in a separate section at the end of the chapter. Methodology The methodological aspects common for the three sub-studies are presented here. Specific methodological issues are described for each sub-study. Data inventory and impact assessment The environmental impact assessment used in this study follows the principle of the life cycle assessment (LCA) methodology, although it is not complete LCAs. First data concerning direct and indirect energy use and resource consumption were inventoried, in LCA terminology this is called LCI (life cycle inventory). Then, these data were characterised into impact groups. One emission may contribute to several impact categories. There is a list of 15 impact categories given in the Nordic Guidelines for LCA (Lindfors et al. 1995). In this part of the study we have paid attention to two of them; Global warming impact and Use of resources, fossil energy. The global warming is measured in global warming potentials (GWP) where all emissions are transformed into CO 2 equivalents. There are three given timespans that could be taken into account; 2, 1 and 5 years. We have chosen the 1 year perspective. Direct impacting gases only, have been counted. They are carbon dioxide (CO 2 ), 59

60 methane (CH 4 ) and nitrous oxide (N 2 O). The GWP of CH 4 and N 2 O correspond to 23 and 296 CO 2 equivalents respectively (IPCC, 21). This means that every kg of methane gives as much global warming impact as 23 kg of carbon dioxide, and is thus multiplied by 23 in order to get the GWP. The use of the resource fossil energy inventory separated the energy use in two categories of energy carriers; electricity and fossil fuels. These were then re-calculated to primary energy, i.e. the use of energy carriers were traced back to the consumption of primary energy resources. By that, it is possible to make comparisons between scenarios and activities which use much electricity with those mainly using fuels. This measure considers the consumption of resources in the lifecycle of the energy carriers. The primary energy consumption in production of average Swedish electricity demand is shown in Table 5-1. Transmission losses in the distribution net (7 %), pre-combustion energy consumption for fuels and efficiency in e.g. hydropower and nuclear power are included, making 2.35 MJ primary energy per MJ electricity used. The equivalent value for electricity produced in oil-fired power plants is 2.69 (Habersatter et al., 1998). For fuels, an average for different fuels has been used: 1.25 MJ primary energy per MJ fuel (calc. from Tables 16.4 and 16.9 in Habersatter et al., 1998). Fuel oil, fossil gas, petrol, and biofuels all have values ranging between 1.9 and 1.35 MJ. Table 5-1. Energy resources used for average Swedish electricity use (Lundgren, 1992) Energy resource MJ energy resource per MJ electricity Fossil oil.64 Fossil gas.93 Coal.4 Peat.45 Biofuels.45 Uranium Hydropower Sum Calculated as MJ in uranium. 35 % efficiency is used in the conversion of MJ nuclear electricity to MJ in uranium, i.e. 35 % of the theoretical heat obtained in the fission process can be utilised as electricity. 2 Calculated as MJ potential energy. 8 % efficiency is used in the conversion of MJ electricity to MJ potential energy. Ecological Recycling Agriculture Olof Thomsson, Swedish Biodynamic Research Institute, Järna Sweden This sub-study has investigated consumption of energy and resources and emission of gases that contribute to global warming on the 12 Swedish BERAS-farms (Table A1-8-4) and in average Swedish agriculture. The results are presented as consumption of primary energy resources and global warming impact. Method Fossil energy use and global warming impact from both direct and in-direct sources were included in the study. The direct use of fossil vehicle fuels, heating oil, electricity, and lubricants were included. In-direct impacts from production of fertilisers, fodder imported to the farm, packaging materials (primarily plastics for silage wrapping), and machinery (only primary energy consumption) were also investigated. Data for energy use, amounts of imported necessities, and production exported from the BERAS-farms were obtained from the farm accountings and interviews. For the average 6

61 Swedish agriculture, these data were obtained from Swedish official statistical data. Following Dalgaard et al. (21), the energy use was completed with norm values for lubricants and machinery. Literature data were used to obtain data for energy use and emissions in the production of all the energy carriers and necessities. For the calculation of the global warming impact, literature data on direct methane emission from animals (Cederberg & Flysjö 24, Hille 22) and nitrous oxide emission from soil (IPCC, 21) were used. Methane emissions from manure storages were neglected. Energy use and greenhouse gas emissions for the production of the different inputs are shown in Table 5-2. Impacts from the production of pesticides were omitted since the contribution was assumed to be small for the environmental impacts considered. Table 5-2. Norms for the energy use in production of different agricultural inputs (with references) value unit reference vehicle fuels (diesel) MJ/l heating oil MJ/l electricity MJ/kWh lubricants 3.6 MJ/l diesel fertilisers MJ/kg N fodder MJ/kg plastics (LLDPE) MJ/kg machinery 12 MJ/l diesel The calculations were performed for each BERAS-farm (not shown here) and for four production type groups of the BERAS-farms. All farms have more or less diversified production but they were group according to their main production in: 1) Mixed production with vegetables (2 farms), 2) Milk, beef and cereals (6 farms) 3) Pork, poultry, egg and cereals (2 farms) 4) Cereals and beef (2 farms) When grouped, the data for the included farms were aggregated and the group treated as one farm unit. The results are reported for the production groups of the BERAS-farms, for an average of the BERAS-farms and for average Swedish agriculture. Table 5-3 shows the number of different animals per hectare for the different groups. Table 5-3. Number of animals of different kind per hectare for the different BERAS-farm groups and for Swedish average agriculture, number per hectare BERAS type-farms Cattle Sheep and goats Pigs Poultry BERAS farms - mixed prod. with vegetables BERAS farms - milk, beef and cereals BERAS farms - pork, poultry, egg and cereals BERAS farms - cereal and cattle prod BERAS farms average Swedish average agriculture Results and discussion The global warming impact, measured in Global Warming Potentials (GWP) as CO 2 equivalents, is reported per kg products exported from the farm (Figure 5-1) and per hectare (Figure 5-2). Please observe that the per-hectare figures are calculated per hectare on the actual farms and for Sweden respectively, i.e. the acreage used for imported fodder is not included. In both cases the GWP were lower for the average BERAS-farm than for the 61

62 average Swedish agriculture. The difference was reduced by the larger emission of methane from animals. That is explained by the larger share of ruminant animals on the BERAS-farms, compared to average Swedish agriculture having a larger part of monogastric animals which emit very little methane. Secondly, it is a result of lower production per animal and per hectare, making more methane emitted per kg product compared to conventional production. The very large GWP from animals in the Pork, poultry, egg -group originates mainly from cattle (beef production) that also is kept on these farms. The global warming impact from other factors investigated was substantially lower on the BERAS-farms compared to average Swedish agriculture. 1,6 kg CO 2 equiv. per kg products exported 1,4 1,2 1,,8,6,4,2, BERAS farms - mixed prod. with vegetables BERAS farms - milk, beef and cereals BERAS farms - pork, poultry, egg and cereals BERAS farms - cereal and cattle prod. BERAS farms - average Swedish average agriculture Soil,5,4,2,8,6,9 Animals,4,49,83,29,49,33 Plastics,,,1,1,, Imported fertiliser/manure,4,,,6,1,21 Imported fodder,1,1,4,,1,3 Fossil energy,14,8,34,16,11,19 Figure 5-1. Global warming potentials for different BERAS-farm groups and for Swedish average agriculture, kg CO 2 equivalents per kg products exported kg CO 2 equiv. per hectare BERAS farms - mixed prod. with vegetables BERAS farms - milk, beef and cereals BERAS farms - pork, poultry, egg and cereals BERAS farms - cereal and cattle prod. BERAS farms - average Swedish average agriculture Soil Animals Plastics Imported fertiliser/manure Imported fodder Fossil energy

63 Figure 5-2. Global warming potentials for different BERAS-farm groups and for Swedish average agriculture, kg CO 2 equivalents per hectare The consumption of primary energy resources is shown in Figure 5-3 and Figure 5-4. Counted both per kg products and per hectare, the consumption is substantially lower on the BERASfarms in average compared to average Swedish agriculture. The most important reason is the lesser use of fire oil (for drying of grain), fertilisers and electricity. Concerning the fire oil, this might be due to a lower rate of on-farm drying but this was not investigated. If that was the case, that oil would be used in the industry instead and therefore, in a systems perspective, that part should be neglected. The differences is, however, still obvious. The difference in electricity consumption was not possible to explain within the study. Notable is also the very large diesel consumption in the Pork, poultry, egg -group, making this production more energy resources demanding than other production. This contradicts the common opinion that meat production from monogastric animals like pigs and poultry is more energy efficient. Whether this is a result of chance, there are only two farms in the group, or some other factors have not been possible to sort out MJ per kg products exported BERAS farms - mixed prod. with vegetables BERAS farms - milk, beef and cereals BERAS farms - pork, poultry, egg and cereals BERAS farms - cereal and cattle prod. BERAS farms - average Swedish average agriculture machinery,9,58 2,46 1,3,79,77 plastics,4,8,55,3,13,24 fertilisers,27,,1,2,3 1,49 imported fodder,13,26,73,6,26,54 electricity 1,4 2,22 2,26 2,6 2,12 3,77 fireoil,,,12,24,2 1,25 vehicle fuel 2,26 1,37 5,7 2,39 1,88 1,75 Figure 5-3. Consumption of primary energy resources for different BERAS-farm groups and for Swedish average agriculture, MJ primary energy resources per kg products exported 63

64 MJ per ha BERAS farms - mixed prod. with vegetables BERAS farms - milk, beef and cereals BERAS farms - pork, poultry, egg and cereals BERAS farms - cereal and cattle prod. BERAS farms - average Swedish average agriculture machinery plastics fertilisers imported fodder electricity fireoil vehicle fuel Figure 5-4. Consumption of primary energy resources for different BERAS-farm groups and for Swedish average agriculture, MJ primary energy resources per hectare Discussion To use Swedish average agriculture as representative for the conventional food producer for Swedish consumption in the global warming and energy use impact assessment is a somewhat weak point in the comparison. The data available are not fully comparable to the data obtained at farm-level recording. However, I judge the comparison to be conservative since a system expansion by including imports and exports in the calculations probably would work in favour of the ecological agriculture. For example, Johansson (25) and Engström (24) show a large dependence of imported animal feed in the conventional agriculture which is not the case for the BERAS-farms. Transports of locally produced food in Järna Christine Wallgren, fms, Stockholm University, Sweden This sub-study describes how locally produced and consumed food in Järna Sweden, are transported, and how much fossil energy that transportation has used. The study comprises vegetables, potatoes and root crops from four local growers; milk and dairy products from Järna Dairy; bread from Saltå Mill & Bakery; and meat from animal keepers in the vicinity of Järna. The products are collected at the different producers and delivered to stores, schools and other large kitchens in both the Järna area and in Stockholm (about 6 km away). Method The transports are described in terms of which vehicles that have been used, which routes that have been driven, distances, amount of products transported, and energy use for the transports. The energy use has been calculated as MJ/kg product transported. Only direct use was counted and transports for necessities and other ingredients than the main raw products were usually omitted. If included that is commented in the text. The results have been 64

65 compared to the transportation of equivalent products in today s conventional (large-scale) food system. Data used for comparisons to the conventional system are in most cases earlier reported in Carlsson-Kanyama et al. (24). All calculations are based on data for year 24 and/or measurements performed during spring 25. For some not accessible basic data, estimations have been done based on assumptions presented in the report. Three case studies of small-scale, ecological and local production and distribution are included: 1. Saltå Kvarn (mill and bakery); buying grain from ecological farms in Järna and in the south-central part of Sweden. Producing cereal products and bread sold all over Sweden. Included here are the transports to Järna and Stockholm consumers. 2. Järna Odlarring (a local farmers cooperation); buying and selling both newly harvested vegetables and root crops from four farms in Järna (during season), and meat from ecological beef producers in Järna (all year around). 3. Järna Mejeri (a farm-size dairy); producing and selling milk, yoghurt and cheese from cow milk produced on two farms in Järna. Data collection Data for the transportation of vegetables have been collected from the bookkeeping for Järna Odlarring 24, which record sold amounts of vegetables per every single day. The amount delivered is equivalent to amount sold since there are no intermediate storage and no losses (since the products are harvested the same day). Possible losses on the farms are ploughed into the soil. Weekly averages of deliverances were calculated from the basic data. Transport data was calculated for two different deliverance routes during three average seasonal routes; early, mid and late seasons. When vegetables and meat were co-transported that was taken into consideration. Two different cars were used. The average fuel consumptions for the two cars were calculated separately per yearly basis. The route distances were measured by the trip-km-meter in the cars. For the meat transports, data were obtained both from the slaughterhouse company (that transported the animals from the farms to the slaughterhouse) and from Järna Odlarring (that performed the deliverances). Data for the animal transports were average data for distances and fuel consumption, and a combination of detailed and yearly average data concerning the number of animals. The volumes and distances for the deliverance routes were recorded during two weeks in April 25. The measured routes were two transports from the slaughterhouse combined with two routes customers in the vicinity of Järna, and two routes to Stockholm. Delivered amounts were recorded at the loading of the cars and the distances driven were recorded for each trip. The cars used for vegetable transports were used also for the meat transport and the fuel consumption and deliverance route distances were assumed equal in both cases. During the winter season, only meat is transported in the cars. During the early and late vegetable seasons, vegetables and meat are co-transported as often as possible. Strict rules for this, concerning packaging and temperatures, have to be followed. However, the energy use calculations were performed separately for vegetables and meat. Allocation per weight was used in order to separate the energy use proportionally to vegetables and meat respectively. 65

66 For the milk and dairy products, the data collection was performed during April 25. The routes are one collecting milk on two Järna farms (the dairy is situated at one of the farms), and three deliverance routes; two local routes to customers in Järna and one to Stockholm. The three deliverance routes are about the same every week all year around. The distances were recorded for each route. The fuel consumption was measured by filling up the car before and after each route. Two different cars were used. The amounts of products loaded were recorded at each measuring occasion. The bread transports calculations were based on average deliverances during one year. This was assumed appropriate since the bread deliverances to Järna, and thus the consumption, are relatively constant over the year. The transports included here are performed by the company s own car to grocery stores in Järna and Stockholm. Bread is also delivered to other distributing channels, primarily to COOP, but they are omitted in this study. The transports in these cases are performed by the distributors themselves. Energy use calculations For each transport, data for fuel use, distance and amount products were collected as described above. All transports were performed by diesel-fuelled vehicles. The energy use per kg product was calculated in MJ/kg product. First, the fuel use per km was multiplied by the number of km per route giving the fuel use per route in litre/route. This figure was then multiplied by 35.86, which is the energy content of 1 litre diesel giving energy use per route in MJ/route. Lastly, the energy use per route was divided by the number of kg products transported giving energy use per kg product transported. These calculations were performed for meat, vegetables, milk and dairy products, and bread separately. Comparing data for transports of similar conventional products are collected from several sources but all are referred to in Carlsson-Kanyama et al. (24). Results and discussion The results are presented in text here and included in diagram form together with the processing industry in the following sub-chapter. Saltå Kvarn Saltå Kvarn produced 11 loafs of bread per week (production on 5 days) during 24 out of flour produced in the own mill. The grain was bought from about 2 farms, some in Järna but also farms in the south and central part of Sweden. The largest farm is situated outside Lidköping in the west of Sweden, some 33 km away. Grain is also bought from a wholesaler. The farms around Järna delivers about 5 ton. In total, Saltå Kvarn buys about 4 ton per year. Everything is transported by truck or tractor and wagon. The weight of the bread produced in the bakery was 6 6 kg per week or 343 ton per year. To produce one kg bread, about.6 kg flour was used and to produce one kg of flour about 1.3 kg grain was used making.78 kg grain per kg bread. So, in order to produce the 343 ton bread per year 267 ton grain was used. That amount is well within what the Järna farms delivers, thus we have only accounted for the local grain in-transports. Transportation of ingredients The transport of grain produced locally is transported by the farmers with tractor and wagon. The fuel consumption is 1-12 litre diesel per hour. The grain is transported direct from the 66

67 field to a silo at Järna Kvarn. This transport is between 3 and 5 km and take scarcely an quarter of an hour one way. Assuming the average load was 13 ton and each trip took 26 minutes give 4.8 litre diesel per 13 ton. This makes.13 MJ per kg grain or about.1 MJ per kg bread. This grain was, after drying, transported by truck to storage in Tystberga 42 km away. This transport used.26 MJ/kg bread. Together the grain transports used.36 MJ per kg bread. Other ingredients as dried fruit and seeds stand for about 7 % of the bread weight, some of them imported from e.g. Turkey. A rough estimation, assuming that most of them originate in Europe and use 5 MJ/kg for transports, give.35 MJ per kg bread. Hypothetically, it could of course be argued that the ingredients could be exchanged for locally produced berries and seeds but we have chosen to include the energy use for the imported ingredients. The sum for transportation of ingredients in the actual case was about.4 MJ per kg bread. Deliverances of bread Of the bread produced, about 16 ton was delivered locally in Järna with vicinity. 187 ton was delivered with own cars to Stockholm and 14 ton was collected by distributors at the bakery. Saltå Kvarn also sell flour, groats, muesli and imported colonial products like seeds and dried fruit but these are also transported by distributors and not included in this study. The local deliverances were made with a small lorry consuming 15 litre diesel per 1 km, to two grocery stores in Järna (ICA and COOP). The distance is 8 km round trip. About 1 loafs (55 kg) were delivered each time. No other transports were done at this transport and the car went empty back to the bakery. The fuel consumption was thus 1.2 l/route, making the energy use 43 MJ/route or.78 MJ per kg bread delivered. Deliverances to Stockholm were made five days a week with the same car used for the local transports. About 12 loafs weighing 72 kg were delivered each time. The average fuel use was the same as for the local transports (15 l/1 km) and the route was 15 km. The fuel consumption was 22.5 litre diesel, making 87 MJ per route or 1.12 MJ per kg bread delivered. Also here, no other transports were done and the car went empty back to the bakery. The car was, however, full when starting from the bakery, meaning that no extra space was available. Energy use per kg bread The conclusion is that the total energy use for transports of bread was 1.2 MJ per kg bread delivered locally in Järna. Using 1 % locally produced ingredients and local storage would lower the energy use by about.3 M//kg bread (a part of.35 and.26), resulting in a hypothetical energy use of.9 M//kg bread. However, the most influencing factor was how much that was transported each time. If the volume would have been 3 loafs instead of 1, the energy use would be a third. The second most influencing factor is which car that is used. Using a smaller car with fuel consumption of 7 l/1 km would halve the energy use. Comparison to LCA-studies of conventional bread transports show 1. MJ/kg bread (Carlsson-Kanyama and Faist, 2) and 3.8 MJ/kg bread (Johannisson and Olsson, 1998). Järna Odlarring Järna Odlarring has fixed deliverance routes of meat and vegetables but delivers also at other times and places in order to be flexible and to fulfil wishes of their costumers. Not all routes 67

68 are, therefore, optimised from an energy efficiency point of view. Two vehicles are used; a Citroën Berlingo model 1999 with a fuel consumption of 7 litre diesel/1 km (cooling cabin) and a Fiat Ducato model 2 with a fuel consumption of 12 litre diesel/1 km. Both cars are run without trailer. Animal transports Animals were collected on six farms around Järna and transported to a small slaughterhouse in Stigtomta outside Nyköping some 6-7 km away. These transports were performed by the slaughterhouse company. Animals were collected once every other week, usually 2-4 cattle, and during October-November also ca 1 lambs, each time. Besides these, also 1 calves from these farms are killed each year. Per year it makes about 75 cattle, 4 lambs and 1 calves. The vehicle was a Scania animal transport lorry of the smallest size, consuming 3-5 litre diesel/1 km. Max load is 13 cattle or 5 lambs. It is not allowed to mix animals from ecological and conventional farms, so the car was not always full. The route distance varied depending on which farms that delivered animals. An average round trip was assumed to be 156 km. Meat transports All deliverances of meat from the slaughterhouse to the Järna consumers were done by Järna Odlarring. The meat was delivered in closed packages, with the same cars that transported vegetables. Beef was cut in ready-to-eat pieces and vacuum-sealed, which is allowed to be cotransported with vegetables. Lambs were cut with bones and therefore not vacuum-sealed but packed in plastic bags that were put in cardboard boxes, which are not allowed to be cotransported. A thorough washing has to be performed between the transports. When possible the small van is used. The larger lorry is used about half of the tours to Stockholm. On Wednesday, even weeks, meat was fetched at the slaughterhouse and delivered to the two grocery stores in Järna. Some, that was not possible to sell immediately, was put in cool and cold storages in Järna. On Wednesdays, odd weeks, meat from the own storages were delivered to the two stores in Järna and to stores in Stockholm. The routes are about the same all year around. Deliverances to large kitchens were performed on Tuesdays each week. The orders were more varied, thus no average routes are possible to set. About 23 routes from the slaughterhouse and to Stockholm are performed per year. Each cattle give about 14 kg bone-free beef. A calf gives about 6 kg. An average lamb gives 17.5 kg meat including bones. In one year that makes about 1.5 ton beef, 6 kg calf meat and 7 kg lambs meat. Per deliverance that makes about 48 kg beef and calf meat. Adding the 7 kg lambs meat produced during October-November, 51 kg meat is transported per deliverance in average. During autumn 24, a test was performed with slaughter and of deliverance pig meat. This was not included in the calculation. If there are enough sales it is assumed that 3 pigs every other week could be added to the deliverances. This would probably make the energy efficiency for the transports better. Calculations of energy use for animal and meat transportations are performed in three steps: 1. The energy use for transporting the animals to the slaughterhouse was 156 km per route *.4 l diesel per km * MJ per l diesel / 51 kg meat per route = 4.4 MJ per kg meat 2. The energy use for fetching the meat at the slaughterhouse was 156 km per route *.13 l diesel per km * MJ per l diesel / 51 kg meat per route = 1.1 MJ per kg meat 68

69 3. The energy use for deliverances to the Järna customers was. =.45 MJ per kg meat. The value is a weighted average of different routes and seasons where the energy use has been allocated between meat and vegetable transports. (The calculations can be obtained in an Excel-sheet from the author.) Energy use per kg meat Together this makes 6 MJ per kg meat delivered in Järna. For the meat delivered to Stockholm, the deliverance route used 5.6 MJ per kg meat, making the total energy use for transports around 11 MJ per kg meat. The addition of three pigs every other week would lower the energy use to X.Y MJ per kg meat. If the volumes increased to a level where the animal transport lorry was fully used, the energy use would be lowered from 3.9 MJ per kg meat to about 1 MJ per kg meat. The total energy use should then be around 4 MJ per kg meat. Energy use for conventional animal and meat transports, collected from different LCAstudies, are presented in Table 5-4. Table 5-4. Energy use for conventional meat transports, from other studies. Examples Reference MJ per kg meat Meat from Sweden Johannisson and Olsson (1998).45 Meat from Sweden Edsjö (1995).97 Meat from Linköping to Stockholm Sunnerstedt (1996).46 Meat in Europe Carlsson-Kanyama and Faist (21) 5.7 Meat from Ireland to Stockholm Sunnerstedt (1996) 1.2 Meat from Latin America Wallgren (25) 12 Vegetable transports Collection of the vegetables and root crops at the growers was made at the same route as the deliverance. No intermediate storage was used. The deliverances 24 started the last week in May. During the first period, here called early season, which lasted to 1 July, one deliverance route was made per week in Järna and its vicinity. This route was 48 km. The second period, here called main season, three deliverance routes per week were made. Two of these went to the Järna area, were performed on Tuesdays and Thursdays and were 33 km long. The third route, on Wednesdays, delivered vegetables to Stockholm. This route was 123 km long. Together this makes 189 km per week for the three routes. During the late season, 1 October to 3 November, one local route in Järna was carried out each week and one route to Stockholm every other week. Distances were as before. A few after-season deliverances were performed during November-December of root crops and vegetables stored at one of the producers, Skilleby farm. The harvest, and thereby the deliverances, varied much between the periods. The deliverances per week are shown in Figure 5-5. In total, 21 5 kg was delivered during 24. The average weekly deliverances for the three seasons are shown in Table

70 25 2 kg per week week Figure 5-5. Weekly deliverances of vegetables and root crops by Järna Odlarring from week 2 to week 44 during 24. Table 5-5. Average weekly deliverances for the three seasons. Period number of weeks weight per period weight per week Early season Main season Late season Energy use per kg vegetable The energy use was calculated as a weighted average of the deliverances at the three seasons given in Table 5-5 and the estimated fuel consumption for the different routes. Also the cotransportation of vegetables and meat was considered. The results are that the energy use for the local transportation of vegetables and root crops in the Järna area consumed.3 MJ per kg product. Equivalent value for the deliverances to Stockholm was 5.9 MJ per kg product. Comparisons to LCA-studies show some results in the same range but most of them show a larger energy use per kg product (Table 5-6). Table 5-6. Energy use for vegetable transportation, results presented in other studies. Carlsson-Kanyama et al. (24) Sunnerstedt (1996) Sweden/Denmark Potatoes.8.6 (locally.6-.15) Tomatoes Carrots (Gotland) Apples Europe Tomatoes Tomatoes, by air 5 Carrots Lettuce 1.5* Apples Other continents Apples *Average for conditions in Europe, not for Stockholm 7

71 Järna Mejeri Milk in-transports Transport of milk to the dairy is carried out every second day all year around. The vehicle used was a Peugeot 1999 with trailer. Fuel consumption was 8 litres per 1 km. The milk was fetched at two farms at.5 and 4 km distance respectively. The collection route was 9 km round trip. In average, 1 litres were collected at Nibble and 8 litres at Yttereneby each time. The milk was transported in a cooler tank. Each collection trip used.72 litre diesel, making the energy use 25.8 MJ per 18 litres. It is assumed that one litre milk is equivalent to one kg milk, resulting in.14 MJ per kg milk. Deliverances of dairy products Deliverances of milk and dairy products to costumers are done with two different cars; the above mentioned Peugeot and a diesel fuelled Daewoo 2 with a fuel consumption of 12 litre diesel per 1 km. Three different deliverance routes are used. Route 1 Järna with vicinity. The route was 39 km and the Peugeot (8 l/1 km) was used. It starts at the dairy and stops at Nibble garden Saltå mill Mossvägens Livs Konsum Järna ICA Järna Konsum Hölö and then back to the dairy. The tour went once a week and the deliverance at the measuring week (w. 11) was 35 kg drinking milk, 18 kg sour-milk, 78 kg yoghurt and 1 kg other products (but no cheese). In total 545 kg delivered products. The fuel consumption was 3.1 litre diesel. Thus, the energy use was.24 MJ per kg product. When adding the energy use for the in-transport to the dairy (.14 MJ/kg) the total energy use was.22 MJ/kg. Route 2 Järna with vicinity. This route goes from the dairy Nibble garden ICA Järna Konsum Järna Konsum Gnesta Konsum Hölö The Culturehouse in Ytterjärna the dairy. The route was 57 km and the Daewoo (12 l/1 km) was used. This route was driven twice a week and the fuel consumption was 6.8 litre diesel per route. At the measuring week 62 kg products were delivered, making the energy use.39 MJ per kg product. When adding the intransport (.14 MJ/kg) we get.4 MJ/kg. Route 3 to Stockholm delivered to about 2 costumers using the Daewoo. The route was 195 km 23.4 litre diesel was used. The deliverances were; 268 litre milk, 7 litre sour-milk, 136 litre yoghurt, 72 kg cheese and 29 kg other products, in total 585 kg. That makes the energy use 1.43 MJ per kg product delivered. When adding the energy use for in-transport (.14 MJ/kg) the total was 1.44 MJ/kg. Energy use per kg dairy product The weighted average of the energy use for the locally delivered dairy products (Route 1 and 2) was.32 MJ per kg. Results from LCA-studies of conventional production are shown in Table 5-7 Table 5-7. Energy use for transports, results from other studies. Carlsson-Kanyama et al. (24) Sunnerstedt (1996) Sweden/Denmark/Finland Drinking milk Yoghurt Cheese Europe Yoghurt 2.1 Cheese 9* 1.9 *Average for conditions in Europe, not for Stockholm 71

72 Small-scale food processing industries in Järna Olof Thomsson, Swedish Biodynamic Research Institute, Järna Sweden This sub-study investigated the use of energy and packages in small-scale food processing industries for bread, vegetables and root crops, dairy products, and meat. The industries studied are the same companies studied in the transports sub-study; a mill and bakery company (Saltå Kvarn), a farmer s cooperative meat and vegetables wholesaler (Järna Odlarring), a farm-size dairy (Järna Mejeri), all situated in the vicinity of Järna, and a small slaughterhouse (Stigtomta Slakteri) situated some 65 km away from Järna. These are compared to conventional large-scale food processors. Method Data for direct energy use, use of packaging materials (in-direct energy use), and production in the small-scale industries were collected through bookkeeping records and interviews with responsible persons on each company for the year 24. Direct energy use, electricity, heating oil and fossil gas were inventoried separately in order to be able to calculate the consumption of primary energy resources and global warming impact reported in the next section. For the indirect energy use, the production and inherent energy of packaging materials were included (Audsley et al. 1997; Habersatter et al. 1998), also here electricity and fossil fuels were recorded separately. Energy use and recovery from packaging waste management, from the import of other raw materials and from water production and wastewater treatment were not included. Data for similar products produced in large-scale industries were mainly obtained from LCA Livsmedel (22). That was a project within the Swedish cooperative food industry performing seven LCAs on food products. The complete studies are not published but the aggregated results were presented in Swedish in the popular publication referred to and on some of the companies websites. The products studied were: drinking milk (1.5 % fat), beef (from dairy production animals, which represent 7 % of the Swedish beef production), pork, chicken, hamburger bread, potatoes, and iceberg lettuce. Here the waste management of packaging material was included. Results and discussion The direct energy use and indirect energy in MJ per kg product for bread, vegetables and root crops, meat, and dairy products in the Järna food industries and in examples or averages of large-scale food industries are shown in Table 5-8. The results show no trend whether the small-scale or large-scale in general use the least energy. One could expect that the large-scale industries should use less energy per kg product due to the large-scale efficiency factor. For the meat and dairy products examples that is true but for the bread and vegetable examples the contrary is shown. One should, however, remember that there are large differences concerning energy use in the literature and probably also in practise. The energy use in the different productions is further discussed in separate sections below. Table 5-8. Energy use in processing of four different product groups for conventional food systems and small-scale local food systems, MJ per kg product direct use electricity direct use fossil fuel packages electricity packages fossil fuel Total 72

73 bread conventional Järna vegetables, root crops conventional and potatoes Järna..... meat conventional Järna dairy products conventional Järna Bread The bakery on Saltå Kvarn used less fossil energy per kg bread than the conventional example but that was production of hamburger bread. In Saltå many different kinds of bread are baked. Saltå also used some fire-wood (some 5 m 3 piled paper wood annually) but that was assumed to be CO 2 -neutral and thus not included in the assessment. In scenario simulations based on other sources, presented in Thomsson (1999), the direct energy use in bakeries ranged from 1.6 to 3.8 MJ per kg bread and indirect energy use in packaging from 1.2 to 6.3 MJ per kg bread ( when the packaging material was recycled and incinerated). Together the range in that study was 2.8 to 1.1 MJ per kg bread (or 2.1 to 6.3 when the recycling was included) indicating that this comparison might be a bit unfair. On the other hand, if recycling of the packaging material would have been included in the Järna study the total would be in the range of 4.5 MJ per kg bread. Vegetables and root crops The processing of vegetables and root crops were not using any large amounts of energy. In Järna, the most products were delivered the same day as it was harvested without much treatment, and the handling that was carried out during the growing season implying that no heated locals were needed. The office was not included, which also seem to be the case in the conventional study. Concerning packages, the major energy use was used for the lettuce in the conventional example. The lettuce was put into plastic bags (primary package) and then transported in single-use cardboard boxes (secondary package). In the Järna case, the most of the vegetables were transported without primary package in re-usable plastic boxes. Meat As expected the conventional meat processing use less energy in the plant (25 % less). Since Stigtomta is a small slaughterhouse, and since it is specialised on individual slaughter, i.e. farmers are guaranteed to get their own animals if they want, that difference is almost surprisingly small a difference that very well can be compensated in other parts of the food system. Concerning the packages, the difference is around 15 % and that probably is within the margins of error in the estimation. Dairy products The energy use in the small-scale Järna dairy was more than double than the conventional example. However, they also produced a lot of cheese which use about 1 kg milk per kg cheese, which probably has an effect of the energy use since it makes less kg products to divide the energy use with. 1 hamburger bread (LCA Livsmedel 22) 2 all kinds of bread 3 average of potatoes and lettuce (LCA Livsmedel 22) 4 average of beef and pork, since that is what is slaughtered in Stigtomta (LCA Livsmedel 22) 5 drinking milk (LCA Livsmedel 22) 73

74 Global warming impact and primary energy consumption in a local food chain in Järna Olof Thomsson, Swedish Biodynamic Research Institute, Järna Sweden This section describe emission of gases that contribute to global warming and consumption of primary energy resources in the transportation and processing parts of the food chain described in previous sections. Method The environmental impacts were assessed as described above in the beginning of this chapter. The energy and packaging use data collected in the inventories of the transportation and processing were the starting point for the calculations. It was assumed that the electricity used was produced like the Swedish average, which roughly is produced by half hydropower and half nuclear power, and minor parts of fossil fuels. Concerning the emission of global warming gases in the production of packaging material, data from Audsley et al. (1997) and Habersatter et al. (1998) were used. The results are presented as Global Warming Potentials (GWPs) with the unit kg CO 2 - equivalents per kg product and MJ primary energy resources per kg product. Please note that this MJ is not the same unit as the MJ presented in the previous sections. The unit used here represents the consumption of resources while the ordinary MJ-unit represents the use of an undefined energy quality in a process where the energy quality is degraded, e.g. chemical energy in wood degraded to diffuse heat. Results and discussion When looking at the GWPs for the processing and transports together, the difference between conventional and the Järna systems is substantial for bread, vegetables & potatoes and dairy products especially for the latter two (Figure 5-6). The very inefficient transports for the meat produced in Järna and slaughtered in Stigtomta makes the GWP equal to the conventional. Somewhat larger volumes, as discussed in the Transports section, would make the result for the Järna alternative better. It should, however, be remembered that the data for the conventional processing is not entirely comparable to the Järna cases, and the literature data for transports from different references vary a lot. In other words, this comparison has to be taken not as a truth but as an example on differences that may occur. Both the conventional and the local small-scale can be better or worse concerning global warming impact. For example is the choice of energy carrier very important for the result. Comparing the results for meat in Table 5-8 and Figure 5-6 may serve as a good example. The energy use in the conventional plant is 2.6 MJ electricity +1.4 MJ fossil fuels, equals 4. MJ per kg meat, while the Järna plant use 5.2 MJ electricity. Thus 3 percent more energy is used in the Järna plant but when it comes to GWPs the Järna plant show 9 percent less impact. Looking at the bread processing alternatives, the comparison between large-scale and small-scale is the opposite. If the electricity had been produced from fossil fuels, the proportional difference between the systems for global warming impact from direct energy use would have been equal to that in Table 5-8. In order to show a broader picture of the environmental impacts more impact categories should have been included but that was not possible within this project. 74

75 Concerning the GWPs from packages and transports, these represent a fair difference since both packaging materials and fuels in principle are of equal origin.,7,6 kg CO2 equiv. per kg product,5,4,3,2,1, conventional Järna conventional Järna conventional Järna conventional Järna transports,19,9,48,2,26,47,16,3 packages,15,3,9,,15,7,4,3 direct energy use,9,18,,,18,2,2, bread vegetables and potatoes meat dairy products Figure 5-6. Global warming potentials for conventional processors and Järna small-scale processors for different product groups, kg CO 2 equivalents per kg products exported The general results for consumption of primary energy resources show similar patterns as the GWP (Figure 5-7). The exception is for the meat processing, where the Järna case show a substantially larger consumption. This is partly due to the inefficient transports but also a result of that the slaughterhouse only uses electricity, which, as discussed above, in Sweden is global warming friendly, but that uses a lot of primary energy resources. Also here, the contrary phenomena can be observed for the bread processing cases. A sensitivity analysis, where the Järna cases use the same proportion of electricity and fossil fuels as the conventional, show 75

76 3 MJ primary energy resources per kg product conventional Järna conventional Järna conventional Järna conventional Järna transports 3, 1,5 7,6,4 4,2 7,5 2,6,4 packages 3,1 2,4 3,1, 3,9 4,8 1,8 1,7 direct energy use 9,5 5,7,4, 7,9 12,2,8 2,1 bread vegetables and potatoes meat dairy products Figure 5-7. Consumption of primary energy resources for conventional processors and Järna small-scale processors for different product groups, MJ primary energy resources per kg product Conclusions The studies presented in this chapter show the potential for diminished global warming impact and use of primary energy resources by a systems change to Ecological Recycling Agriculture and to a more localised food industry. It should, however, be remembered that the examples shown sometimes are not fully comparable and that both the conventional and the ecological/local could be worse or better in other cases. References Audsley, Eric. Alber, Sebastian. Clift, Roland. Cowell, Sarah. Crettaz, Pierre. Gaillard, Gérard. Hausheer, Judith. Jolliett, Olivier. Kleijn, Rene. Mortensen, Bente. Pearce, David. Roger, Ettiene. Teulon, Hélène. Weidema, Bo. van Zeijts, Henk Harmonisation of environmental life cycle assessment for agriculture. Final Report Concerted Action AIR3- CT European Commission DG VI Agriculture (Silsoe, UK) Berlin, Johanna. 21. LCI of Semi-Hard Cheese Mat21, SIK-rapport 692. Carlsson-Kanyama & Faist. 2. Energy Use in the Food Sector - a data survey. Carlsson-Kanyama A., Sundkvist Å & Wallgren C. 24. Lokala livsmedelsmarknader en fallstudie. Miljöaspekter på transporter och funktion för ökat medvetande om miljövänlig matproduktion. (In Swedish: Local food markets a case study.) Centrum för miljöstrategisk forskning fms (Center for Environmental Strategies Research). KTH. Stockholm Cederberg, Christel & Flysjö, Anna. 24. Life Cycle Inventory of 23 Dairy Farms in South- Western Sweden. SIK-report 728. Gothenburg Dalgaard et al. 21. A model for fossil energy use in Danish agriculture used to compare organic and conventional farming. Agriculture, Ecosystems and Environment 87 (21). pp

77 Edström, K Potatis och griskött två livsmedels väg till restaurang Lantis. (In Swedish: Potato and pork two foodstuffs path to the restaurant Lantis). IVL. Arkiv A Stockholm Engström, Rebecka. 24. Environmental Impacts from Swedish Food Production and Consumption. Licentiate Thesis, Chemical Engineering and Technology, KTH (Stockholm) Fernlund, T. m.fl. (1997) Baktankar En liten bok med brödrecept, Saltå kvarn, Balders förlag. Habersatter et al Life Cycle Inventories for Packagings. Volume 1 and 2. Environmental Series Waste (25). SAEFL. Berne Hille, John. 22. Får og svin hvem er mest ålreit? (In Norwegian: Sheep and pigs who are most alright?) Minirapport, Desember 22. Framtiden i våre hender (Oslo) Husus-rapport 25; Wallgren & Höjer (forthcoming). IPCC. 21. (Authors: Boucher, O. Haigh, J. Hauglustaine, D. Haywood, J. Myhre, G. Nakajima, T. Shi, G Y. Solomon, S.) Radiative Forcing of Climate Change. In: Climate Change 21 (6): The Scientific Basis. pp IPCC. Cambridge Johannisson och Olsson, (1998) Miljöanalys ur livscykelperspektiv av fläskkött och vitt bröd. Förstudie. SIK-rapport 64. Johansson, Susanne. 25. The Swedish Foodprint - An Agroecological Study of Food Consumption. Acta Universitatis Agriculturae Sueciae 56. Uppsala LCA Livsmedel. 22. Maten och miljön. Livscykelanalys av sju livsmedel. (In Swedish: The food and the environment. Life cycle assessment of seven foodstuffs). LRF. Stockholm. Lindfors et al Nordic Guidelines on Life-Cycle Assessment. NORD 2. Nordic Council of Ministers. Lundgren, Lars Hur mycket påverkas miljön av en kilowattimme el i Sverige? (In Swedish: How much is the environment affected by a kwh used in Sweden?). Vattenfall Research. Sunnerstedt 1996 Stockholms Miljöförvaltning. Thomsson, Olof Systems Analysis of Small-Scale Systems for Food Supply and Organic Waste Management. Acta Universitatis Agriculturae Sueciae, Agraria 185. Uppsala Personal communications Jan Gustafsson, Saltå kvarn, market director, Henrik Almhagen, Saltå Kvarn, Mats Arman, Saltå kvarn, mill director, Dagfinn Reeder, Yttereneby farm, Hans-Petter Sveen, Järna Odlarring, executive director, Simon Vidermark, Järna Odlarring, Kristina Åström, Stigtomta slakteri, Rainer Höglund, Järna Mejeri, executive director, Job Michielsen, Järna Mejeri,

78 6. Organic waste management studies Two different cases of organic waste management systems have been studied in the BERAS project. The most extensive study was performed in Juva, Finland. Following that, a description of a farm-size biogas plant in Järna and a discussion about the possibilities for combined recycling (re-use of nutrients) and energy production is presented. Inventory in Juva Tiina Lehto, South Savo Regional Environment Centre, Finland The objective in the inventory conducted at Juva is to determine the possibilities for recycling biowaste (organic waste) produced by local food actors back into agriculture. The examined food actors belong to the food chain after primary production (agriculture): food processors, grocery stores, schools, communal kitchens, and private consumers. The research methods used are waste flow and substance flow study. The study first looked into the current waste management system within the Juva community and among specified food actors. Special attention was focused on biowaste and nutrient flows. Because biowaste recycling into fields in Juva was scarce in 22, an assessment was made of the possibilities to recycle biowaste back into agriculture. Recycling of biowaste can recycle nutrients back into agriculture and thereby add humus to agricultural land. In organic agriculture, nitrogen is fixated by plants, but it is estimated that there will be lack of phosphorus in the future. Biowaste could compensate nitrogen fixation and it could be a good source of phosphorus. Legislation sets demands on biowaste recycling and sewage sludge, for example, is not permitted to be used in organic agriculture in Finland. Considering the recycling of food waste and animal-based by-products, it is necessary to take into account regulation (EC) No. 1774/22, which lays down health rules concerning animal by-products not intended for human consumption. This regulation was enacted mainly because of the BSC epidemic and foot and mouth disease, and it affects and limits the recycling of animal-based by-products, including food waste from kitchens and animal-based biowaste from grocery stores. Materials and methods The system under study is aimed at food actors in the Juva population centre; a few food processors are situated in urban area. Food actors are food processors processing meat, milk, vegetables and cereals, three communal kitchens including schools, three grocery stores, and private households. Also included is the wastewater led to the communal wastewater treatment plant and the sewage sludge thus formed. The research methods used were waste flow and substance flow study. The substance flow study considered especially N and P flows included in the biowaste. Data for the study was mainly obtained through interviews, enquiries and analyses results (Savolab Oy 23, Jyväskylän yliopisto, 25). Also included was an assessment of the amount of biowaste produced by households because is assumed that part of biowaste ends up as landfill waste. The calculated amounts of biowaste produced by households are based on the following assumptions: one person in the region of South Savo produced about 22 kg of waste in 2 (Angervuori, 22); about 33% of all household waste in population centres and about 4% of the household waste produced in rural areas is biowaste (Statistics Finland 78

79 1994); in the case of the Juva population centre, about 4% of the inhabitants are included in separate biowaste collection, and the rest compost their biowaste on their property (YTItutkimuskeskus, 24); the inhabitants of the rural area of Juva are obligated to compost their biowaste; the yield of biowaste via separate collection is 7% (Rejlers Oy 2); Juva had a population of 7449 in 22, and 3628 of them are estimated to live within the population centre (48.7%). The estimates of the nutrient flows resulting from the biowaste (Table 6-1) are based on the Fineli-Finnish Food consumption Database of the National Public Health Institute (National Public Health Institute, 25) and the estimates of the nutrients included in household wastewater are based on the estimates presented by Eilersen et al. (Magid et al., 22). The dry matter content of food products have been estimated based on the feed tables produced by Agronet (25). Separately collected biowaste is assumed to contain 2 g/kg N and 4 g/kg P in dry matter, which is assumed to correspond to 35 mass-% (Sokka et al., 24). Laboratory analyses were made by studying sewage sludge samples from Juva wastewater treatment plant and from compost samples taken from the Juva stack-composting area (Jyväskylän yliopisto, 25) (Table 6-2) to determine the nutrients that could be recycled at present and to determine whether the heavy metal concentrations are below the limits set by regulations. The analysis results for the incoming wastewater at the treatment plant were already available (Savolab Oy, 23) (Table 6-1). These data are based on the average daily nutrient concentration of five samples analysed in laboratory conditions. The conversion factor used for biowaste is.3 tonnes/m 3. Table 6-1. The nutrient values used for different kinds of foodstuffs and biowaste. Waste component N P Dry matter Lettuce (g/kg) 1,76,4 1,3 % 1 Oat husk (g/kg) , % Turkey offal (g/kg) 35,2 1,5 35 % Raw milk (g/kg) (Tuhkanen 25) 5, % Organic milk (g/kg) 4,8,9 12 % Pig carcass (g/kg) 27,5 1,8 35 % Separately collected biowaste (g/kg dry matter) % Household wastewater 14 2, faeces g/cap/day 1, urine g/cap /d 11 1,5 6 - kitchen liquid waste g/cap/d,5,1 2 - bathroom, grey water g/cap/d 1,3 2 Nutrients to treatment plant, kg/d (Savolab Oy 23) 6,4 12,8 Nutrients into water systems, kg/d (Savolab Oy 23) 49,2,46 1 Dry matter of cabbage 2 Nutrients in oat bran Waste system in Juva Figure 6-1 shows the biowaste flows produced by the various food actors in 22 and Figure 6-2 presents an assessment of the nutrient flows included in biowaste. The total solid biowaste amount produced by the various food actors was about 1 15 tonnes, containing 27.6 tonnes of N and 1.6 tonnes of P (excluding quill waste). About 214 tonnes were treated in the communal waste management system by stack-composting the waste. The biowaste in the stack-composting area contained about.71 tonnes of N and.15 tonnes of P. The stackcomposted biowaste originated mainly from households and from one vegetable processor; the remainder came from grocery stores in the population centre and from communal 79

80 kitchens. About 1% of the biowaste originating from grocery stores was estimated to be former animal-based foodstuffs. About 7% of the biowaste produced was transported outside Juva; a large amount went to animal fodder industry, containing as much as 89% N (24.6 tonnes of N) and 66% of P (1.5 tonnes of P) of the total nutrient amount of the biowaste produced by the food actors covered by this study. A smaller amount appears to have ended up in a landfill in Mikkeli (5 km away) along with mixed waste. At maximum 12% of the biowaste was treated at the food actors own systems in Juva, but the said proportion appears not to have been utilised on fields to benefit food production. Wastewater led to the Juva waste-water treatment plant is mainly from households. Most significant industrial plants in the area are a diary and a slaughterhouse, adding BOD and nutrient load to the incoming waste water. In addition waste waters of a vegetable processor, a printer house and a fur refinery are led to the waste water treatment plant. The wastewater treatment plant in Juva is a BIOLAK treatment plant built in 1982, which has later been provided with a facility for phosphorus precipitation by iron(ii)sulphate. The resultant sewage sludge is subjected to filter-pressing; with polymers being used as aiding agents. In 22, the incoming wastewater to the treatment plant amounted to 421 m 3 with a solid matter content of 134 tonnes and containing 22. tonnes of N and 4.7 tonnes of P. The amount of iron(ii)sulphate used was 8.7 tonnes (Savolab Oy 23) and the removal efficiency of phosphorous was 96% and that of nitrogen was 19%. The sewage sludge amount formed in 22 was 512 m 3 (about 364 tonnes 1 ) with a dry matter content of 18%. According to analyses results obtained in 25 (Table 6-2), the sewage sludge contained 4.4% of N and 2.9% of P (in terms of dry matter). According to the removal efficiency in 22, the sewage sludge contains at maximum 4.1 tonnes of N and 4.5 tonnes of P. Nitrogen can escape from the process through denitrification and evaporation, but phosphorus is believed to be slightly soluble because of phosphorus precipitation. The heavy metal concentrations of the sewage sludge are below the requirements of the relevant regulations imposed on sewage sludge for agricultural use; the exception is chromium. The chromium concentration was much higher than the permitted amount. 1 According to analysis made in 25 volume weight was 771 g/l (Table 6-2). 8

81 Figure 6-1. Biowaste flows involving Juva food actors in 22 (DM = dry matter). Figure 6-2. Nutrient flows of biowaste involving Juva food actors in

82 The sewage sludge formed was composted in the communal stack-composting area along with the separately collected biowaste. Tree bark and leaves and gravel were mixed in with the sludge and biowaste being composted to promote the composting process and to produce a final product of better the quality. The nutrient concentrations of the compost as analysed in 25 were low;.28% of N and.32% of P, but the heavy metal concentrations fulfilled the requirements of the regulations. The nutrient concentrations of the biowaste can be assumed to be the same as in 22, because no noteworthy changes in biowaste flows or treatment have occurred. The organic matter (33%) and dry matter content (74%) of the compost samples indicate that the mineral content is relatively high (Jyväskylän yliopisto, 25). According to a decision of the Ministry of Agriculture and Forestry (46/1994), the humus content has to be at least 2% of the dry matter content. The compost product has previously been used in green areas and in road construction, and now it is being stored for the purpose of landscaping an old landfill; local farmers have not accepted it. Table 6-2. Analyses results for the compost product from the stack-composting area and the sewage sludge from the wastewater treatment plant in Juva (Jyväskylän yliopisto, 25). Analysed property Unit Sewage sludge from Juva Vnp 1 282/1994 MMMp 2 46/1994 Compost from Juva Volume weight g/l Conductivity ms/m ph-value ph Ignition loss % DM Dry matter (DM) % Total nitrogen % DM Total phosphorus % DM Total potassium % DM.2.18 Total magnesium % DM Total calcium % DM Mercury mg/kg DM Cadmium mg/kg DM <.5 Total chromium mg/kg DM Copper mg/kg DM Lead mg/kg DM Molybdenum mg/kg DM < 1 Nickel mg/kg DM Sulphur mg/kg DM Zinc mg/kg DM DM = dry matter 1 Decision of the Council of State (Vnp) No 282/ Decision of Ministy of Agriculture and Forestry (MMMp) No 46/1994 Conclusions In 22, biowaste composted in stacks could not be recycled back into agriculture at Juva. The treatment process did not fulfil the requirements; especially the by-product directive 1774/22 as the compost included former animal-based by-products in the form of food waste and former animal-based foodstuffs from grocery stores. The final product could then only be used in landfills (as covering or filling material). If final product is used in agriculture or in greening areas in the future, then the composting treatment has to fulfil the requirements of the by-product directive. Otherwise, the product can be taken only to landfills. Alternatively, it is possible to compost only the biowaste of vegetables and other non-animalbased by-products and sewage sludge. Alternative treatment processes to recycling of nutrients and humus of biowaste are biogas treatment and composting (centralized or small-scale treatment or co-digestion plant). The 82

83 treatment of biowaste and wastewater cause nutrient losses and all nutrients in the treated biowaste do not become available to plants. Figure 6-3 shows summarized total nutrient and dry matter percentages of the biowaste produced by food actors, including wastewater to the treatment plant, in Juva in 22. Most of the nutrient-containing components originated from food producers and from urine. Slaughterhouse waste and food-processing waste contained 52% of N and 19% of P of the total nutrient amount (93% of N and 75% of P of the solid biowaste) and urine contained 29% of N and 32% of P of the total nutrient amount (66% of N and 43% of P of wastewater nutrients). Slaughterhouse waste could be a good nutrient source, but the current regulations pertaining to former animal-based by-products may prevent the recycling of these nutrients back to agricultural land. Figure 6-3. N, P and DM flows of biowaste and wastewater to the treatment plant in 22, Juva. (Dry matter of wastewater is assumed to be double that of solid matter content.) It should be noted that urine contains about 1/3 of the nutrients formed within the studied food system and even a greater share of the nutrients in incoming wastewater flow to wastewater treatment plant in Juva in 22. From the environmental viewpoint, separate urine collection would be preferable to the conventional system. It would increase the recyclable nutrient amounts to fields and at the same time decrease the emissions into water systems. In addition, phosphorous would be in more usable form for plants and risk of heavy metals would be minor compared to sewage sludge. Because of present technology urine separate collection is not respectable in urban area. Biogas plant in Järna Winfried Schäfer, Agricultural Engineering Research (VAKOLA) MTT Agrifood Research Finland Artur Granstedt and Lars Evers, Swedish Biodynamic Research Institute, Järna Sweden The Biodynamic Research Institute in Järna developed an on-farm biogas plant integrated within the self-contained farm organism, BERAS-farm Skilleby-Yttereneby. The plant digests manure of dairy cattle and organic residues originating from the farm and the surrounding food processing units containing % total solids. The developed and implemented technique is based on stable manure and food residues on a two-phase process and new 83