Determining the environmental burdens and resource use in the production of agricultural and horticultural commodities: Defra project report IS0205

Tags: Environmental burdens, Defra, animal production, GWP, agriculture, Store lambs, production systems, organic production, horticultural commodities, primary energy consumption, UK, establishment, Organic production systems, energy consumption, Crop production, supplementary data, primary resources, nitrogen cycle, Silsoe Research Institute, Cranfield University, consumption systems, Defra Research Project, arable land, Raymond Jones, Primary Energy
Content: Determining the environmental burdens and resource use in the production of agricultural and horticultural commodities. Defra project report IS0205 natural resource management Institute, Cranfield University. Silsoe Research Institute. August 2006 www.cranfield.ac.uk Referencing and Acknowledgements For referencing this document should be referred to as: Williams, A.G., Audsley, E. and Sandars, D.L. (2006) Determining the environmental burdens and resource use in the production of agricultural and horticultural commodities. Main Report. Defra Research Project IS0205. Bedford: Cranfield University and Defra. Available on www.silsoe.cranfield.ac.uk, and www.defra.gov.uk The authors are grateful to Defra for funding this work, especially the guidance and support of Dr Donal Murphy-Bokern. The work was mainly carried out and the report was written by staff from SRI (who have since moved to Cranfield University: http://www.silsoe.cranfield.ac.uk), but the project team included the following, whose considerable inputs made the project possible: Raymond Jones & Richard Weller (IGER ), Rosie Bryson (Velcourt Ltd), Lois Philipps (Elm Farm Research Centre), Andy Whitmore, Margaret Glendining and Gordon Dailey (Rothamsted Research), Paul Cook (Rlconsulting), Nigel Penlington (MLC) and Gerry Hayman (Hayman Horticultural Consultancy). We also note the sudden and unexpected death earlier this year of Raymond Jones, whose contribution to the project and the research community was considerable. The editorial input of Dr David Parsons is also gratefully acknowledged. This report describes the current state of the LCI analysis which is now being distributed to independent experts for review and assessment.
Final report to Defra on project IS0205: Determining the environmental burdens and resource use in the production of agricultural and horticultural commodities. Executive Summary The research addresses key questions underpinning the development of sustainable production and consumption systems that are based on domestically produced agricultural and horticultural commodities. It quantifies the resource use and environmental burdens arising from the production of ten key commodities and delivers accessible models that enable resource use and emissions arising from various production options in England and Wales to be examined in detail. The commodities examined are: bread wheat, potatoes, oilseed rape, tomatoes, beef, pig meat, sheep meat, poultry meat, milk and eggs. The overall research aim agreed with Defra was to model the environmental burdens and resource use involved in producing ten agricultural and horticultural commodities using the principles of Life Cycle Assessment (LCA), and to deliver these models in a user-accessible form such as Microsoft Excel. The specific project objectives were to identify and define the major productions systems in England and Wales and the related process flow charts, to establish the relevant mass and energy flows and other necessary data and their uncertainties, to code the LCA models in a package, such as Microsoft Excel, with all the main data readily accessible and published, to use the LCA model to analyse these production systems and demonstrate that the model can compare production systems and can identify high risk parts the systems, and to publish and publicise the research outputs. All inputs into on-farm production for each commodity were traced back to primary resources such as coal, crude oil and mined ore. All activities supporting farm production, such as feed production and processing, machinery and fertiliser manufacture, fertility building and cover crops, were included. The system included soil to a nominal depth of 0.3 m. Where appropriate (tomatoes, potatoes), commodities were defined as national baskets of products, for example tomato types such as loose and on-the-vine tomatoes, each included as their proportion of national production. Abiotic resources used (ARU) were consolidated onto one scale based on relative scarcity. Individual emissions, such as Carbon Dioxide (CO2) and nitrous oxide (N2O), were quantified and aggregated into impacts for global warming (GWP), eutrophication (EP) and acidification (AP). Organic production systems were analysed for each commodity, as well as variations on non-organic (or contemporary conventional) production. Interactions between inputs, outputs and emissions were represented by functional relationships derived from process models wherever possible, so that as systems are modified they respond holistically to specific changes. For example, crop yields and nitrogen supply, dairy cow diet formulation and milk yield, and grass productivity, emissions, animal grazing and fertiliser applications are functionally related. Process simulation models were also used to derive the long term outcomes of nitrate leaching, soil, crop type and nitrogen supply. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 2 of 97
Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 3 of 97
Results Care is needed in comparing commodities as they have different nutritional properties and fill different roles for consumers. The results for plant commodities are shown in Table I, and those for animal commodities in Table II.
Table I The main burdens and resources used arising from the production of
field and protected crops in the current national proportions of production
systems (with the current organic share shown in parenthesis.
Impacts & resources used per t
Bread wheat (0.7%)
Oilseed rape (0%)
Potatoes (1%)
Tomatoes (3.6%)
Primary energy used, GJ GWP100, t CO2 (1) Eutrophication potential, kg PO43- Acidification potential , kg SO2 Pesticides used, dose-ha Abiotic resource used, kg antimony (2) Land use (Grade 3a), ha Irrigation water, m3
2.5
5.4
1.4
130
0.80
1.7
0.24
9.4
3.1
8.4
1.3
1.5
3.2
9.2
2.2
12
2.0
4.5
0.6
0.5
1.5
2.9
0.9
100
0.15
0.33
0.030
0.0030
21
39
(1) GWP100 uses factors to project global warming potential over 100 years. (2) ARU antimony is the element used to scale disparate entities.
The relationship between energy use and global warming gas emissions in agriculture contrasts with most other industries. N2O from the nitrogen cycle dominates GWP from field crops, contributing about 80% in wheat production (both organic and non-organic). In addition, methane from livestock production, particularly from beef, sheep meat and milk, is a global warming gas emission not related to energy use.
About 97% of the energy used in tomato production is for heating and lighting to extend the growing season Because energy use is almost identical for all tomato production systems per unit area, the highest yielding tomatoes (non-organic, loose, classic or beefsteak) incur lower burdens than all other types of tomato.
Table II The main burdens and resources used in animal production in the
current national proportions of production systems (with the current organic
share shown in parenthesis).
Impacts & resources used per t of carcass, per 20,000 eggs (about 1 t) or per 10m3 milk (about 1 t dm)
Beef (0.8%)
Pig meat (0.6%)
Poultry meat (0.5%)
Sheep meat (1%)
Eggs, (1%)
Milk, (1%)
Primary energy used, GJ GWP100, t CO2 Eutrophication potential, kg PO43Acidification potential, kg SO2 Pesticides used, dose ha Abiotic resource use, kg antimony Land use (1) Grade 2, ha Grade 3a, ha Grade 3b, ha Grade 4, ha
28
17
12
23
14
25
16
6.4
4.6
17
5.5
10.6
158
100
49
200
77
64
471
394
173
380
306
163
7.1
8.8
7.7
3.0
7.7
3.5
36
35
30
27
38
28
0.04
0.05
0.22
0.79
0.74
0.64
0.49
0.67
0.98
0.83
0.48
0.67
0.38
(1): Grazing animals use a combination of land types from hill to lowland. Land use for arable feed crops was normalised at grade 3a.
On the livestock side, poultry meat production appears, however, the most environmentally efficient, followed by pig meat and sheep meat (primarily lamb) with beef the least efficient. This results from several factors, including: the very low overheads of poultry breeding stock (c. 250 progeny per hen each year vs one calf Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 4 of 97
per cow); very efficient feed conversion; high daily weight gain of poultry (made possible by genetic selection and improved dietary understanding). Poultry and pigs consume high value feeds and effectively live on arable land, as their nutritional needs are overwhelmingly met by arable crops (produced both here and overseas). Ruminants can digest cellulose and so make good use of grass, both upland and lowland. Much of the land in the UK is not suitable for arable crops, but is highly suited to grass. One environmental disadvantage, however, is that ruminants emit more enteric methane. This contributes to the ratios of GWP produced to primary energy consumed, being about 50% higher for ruminant than pig or poultry meats. Unlike most of industry and domestic activity, the GWP from agriculture (excluding protected cropping) is dominated by N2O, not by CO2 from fuel use. N2O contributes about 80% to GWP in wheat production (both organic and non-organic). The N2O contribution falls to about 50% for potatoes as much fossil energy goes into cold storage. Because the underlying driver is the nitrogen cycle, the GWP of crop production is relatively similar across contrasting productions systems, including organic. In contrast, CO2 from the use of Natural Gas and electricity in tomato production is the dominant contribution to GWP. The balance of global warming gas emissions and fossil fuel consumption is thus quite different from most industries. In agriculture, N2O dominates, with substantial contributions too from methane. Consequently, a carbon footprint inadequately describes agriculture; it has a carbon-nitrogen footprint. Indeed, the nitrogen fluxes in agriculture (and other types of land) also contribute to eutrophication and acidification. The majority of environmental burdens arising from the production of agricultural food commodities arise either directly or indirectly from the nitrogen cycle and its modification, in organic and non-organic systems. Analyses of organic and non-organic production About 27% less energy was used for organic wheat production compared with nonorganic, but there was little difference in the case of potatoes. The large reduction in energy used by avoiding synthetic N production is offset by lower organic yields and higher inputs into field work. GWP is only 2-7% less for organic than non-organic field crops, reflecting the need for N supply to equal N take-off and the consequent emissions to the environment as nitrous oxide to air and nitrate to water. Most organic animal production reduces primary energy use by 15% to 40%, but organic poultry meat and egg production increase energy use by 30% and 15% respectively. The benefits of the lower energy needs of organic feeds is over-ridden by lower bird performance. More of the other environmental burdens were larger from organic production, but abiotic resource use was mostly lower (except for poultry meat and eggs) and most pig meat burdens were lower. GWP from organic production ranged from 42% less for sheep meat to 45% more for poultry meat. Land use was always higher in organic systems (with lower yields and overheads for fertility building and cover crops), ranging from 65% more for milk and meat to 160% Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 5 of 97
for potatoes and 200% more for bread wheat, but the latter is a special case as only part of a crop meets the specified bread-making protein concentration. Organic tomato yields are 75% of non-organic. Thus, the lowest yielding organic, onthe-vine, specialist tomatoes incur about six times the burden of non-organic, loose classic. Other analyses showed that: 1. Breeding a new variety of wheat that increases yield by 20% could reduce energy use by 9%. 2. The choice of indoor or outdoor sow housing has a negligible effect on pig meat burdens. 3. Free range (non-organic) poultry increases energy use for meat by 20% and for eggs by 15%, compared with all housed production. 4. If beef production were to based 100% on beef cows (i.e. no calves from the dairy herd), energy use would increase by 50%. 5. Tomato burdens can be reduced by 70% if the proportion of CHP used is increased nationally to 100% from the current 25%. The analyses were assembled in Microsoft Excel spreadsheets. These allow users to change key variables such as: the balance of organic and non-organic production at a national scale; N supply to crops; balance of housing types in animal production; use of Combined Heat and Power systems (CHP) in greenhouses. Alternative systems can thus be examined in detail. Default values representing the current balance of production methods in England and Wales for all commodities are included, e.g. national proportions of main production systems and sub-systems; fertiliser application rates. Model access and future developments The LCA model will be made available on the Cranfield University website at: http://www.silsoe.cranfield.ac.uk (then search for IS0205 and LCA). Users will be supplied with updates and invited to participate in a workshop. Development of the modelling continues under project IS0222. The main activities include: development of versions suitable for analysis at both farm and regional levels; inclusion of new commodities, such as sugar beet; and analysing the national basket of food commodities. The latter implies accounting for interactions between commodity production systems (for example, crop rotations) and considering land availability. The current model is a life cycle inventory of commodity production and this will be progressed to produce a life cycle assessment, for example viewing the relative importance of the burdens of producing commodities. Conclusions 1. Nitrous oxide (N2O) is the single largest contributor to global warming potential (GWP) for all commodities except tomatoes, exceeding 80% in some cases. 2. Organic field crops and animal products generally consume less primary energy than non-organic counterparts owing to the use of legumes to fix N rather than fuel to make synthetic fertilisers. Poultry meat and eggs are exceptions, resulting from the very high efficiency of feed conversion in the non-organic sector. 3. The relative burdens of GWP, acidification potential (AP) and eutrophication potential (EP) between organic and non-organic field-based commodities are more complex than energy and organic production often incurs greater burdens. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 6 of 97
4. More land is always required for organic production (65% to 200% extra). 5. All arable crops incur smaller burdens per t than meats, but all commodities have different nutritional properties and energy requirements beyond the farm, so care must be taken in comparisons. 6. Ruminant meats incur more burdens than pig or poultry meats, but ruminants can derive nutrition from land that is unsuitable for the arable crops that pigs and poultry must eat. 7. Heating and lighting dominate the burdens of tomato production; but maximising the national use of CHP could reduce the primary energy consumption by about 70%. 8. Non-organic, loose classic tomatoes incur the least burdens and they increase progressively and definably towards organic, on-the-vine specialist types. 9. The model has been used to inform other research projects and is well placed to analyse variations in existing production systems as well as being readily developed for new systems or commodities. 10. The model can be accessed via the Cranfield University web site at www.cranfield.ac.uk (then search for IS0205 and LCA). Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 7 of 97
TABLE OF CONTENTS EXECUTIVE SUMMARY................................................................................. 2 1 INTRODUCTION ...................................................................................... 10 2 METHODS.................................................................................................. 12 2.1 OUTLINE OF LCA PRINCIPLES ............................................................................................................ 12 2.1.1 Agriculturally specific aspects of LCA .......................................................................................... 12 2.1.2 Allocation of burdens to co-products ............................................................................................ 14 2.1.3 Separation of crops and animals................................................................................................... 14 2.1.4 Organic production systems .......................................................................................................... 14 2.1.5 Aggregation of burdens ................................................................................................................. 15 2.1.6 Data sources.................................................................................................................................. 16 2.2 BREAD WHEAT PRODUCTION............................................................................................................... 17 2.2.1 Summary of activities causing agricultural burdens ..................................................................... 17 2.2.2 Field operations ............................................................................................................................ 17 2.2.3 Fuel use for farm operations and machinery burdens .................................................................. 18 2.2.4 Crop yield and response to nitrogen ............................................................................................. 21 2.2.5 Nutrient inputs and crop protection .............................................................................................. 23 2.2.6 Grain storage ................................................................................................................................ 27 2.2.7 Direct soil-crop emissions to air and water .................................................................................. 28 2.3 OILSEED RAPE PRODUCTION ............................................................................................................... 32 2.4 POTATO PRODUCTION ......................................................................................................................... 33 2.5 ANIMAL FEED CROP PRODUCTION ....................................................................................................... 35 2.5.1 Feed wheat production.................................................................................................................. 35 2.5.2 Barley production.......................................................................................................................... 35 2.5.3 Field bean production ................................................................................................................... 35 2.5.4 Soya bean production.................................................................................................................... 36 2.5.5 Maize grain production ................................................................................................................. 36 2.5.6 Maize silage production ................................................................................................................ 37 2.6 GRASSLAND PRODUCTION .................................................................................................................. 37 2.6.1 Grass yield and nitrogen model .................................................................................................... 37 2.7 CROP BY-PRODUCTS AND FEED PROCESSING....................................................................................... 39 2.7.1 Wheatfeed ...................................................................................................................................... 40 2.7.2 Maize partitioning ......................................................................................................................... 40 2.7.3 Rape meal...................................................................................................................................... 40 2.7.4 Soya meal ...................................................................................................................................... 41 2.8 TOMATO PRODUCTION ........................................................................................................................ 42 2.8.1 Features of protected cropping ..................................................................................................... 42 2.8.2 Physical structure.......................................................................................................................... 42 2.8.3 Tomato production systems and products ..................................................................................... 42 2.8.4 Physical, chemical an biological inputs ........................................................................................ 43 2.8.5 Productivity of tomato types.......................................................................................................... 43 2.9 BUILDINGS AND MACHINERY .............................................................................................................. 44 2.9.1 Machinery ..................................................................................................................................... 44 2.9.2 Buildings ....................................................................................................................................... 45 2.10 ANIMAL PRODUCTION ......................................................................................................................... 46 2.10.1 Modelling the structure of the animal production industries ................................................... 46 2.10.2 Animal production network structure ....................................................................................... 47 2.10.3 Animal production models........................................................................................................ 49 2.10.4 Inputs to animal production ..................................................................................................... 50 2.10.5 Emissions and manures from animal production ..................................................................... 51 2.10.6 Allocation of burdens in animal production ............................................................................. 52 2.10.7 Organic livestock production ................................................................................................... 53 2.10.8 Summary of animal production data ........................................................................................ 53 2.11 IMPLEMENTATION OF THE LCA MODEL .............................................................................................. 61 3 RESULTS .................................................................................................... 65 Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 8 of 97
3.1 ARABLE .............................................................................................................................................. 65 3.1.1 Bread wheat .................................................................................................................................. 65 3.1.2 Oilseed rape .................................................................................................................................. 68 3.1.3 Potatoes......................................................................................................................................... 68 3.1.4 Feed crops, including imported crops........................................................................................... 70 3.2 ANIMAL PRODUCTS............................................................................................................................. 72 3.2.1 Beef................................................................................................................................................ 72 3.2.2 Pig meat ........................................................................................................................................ 73 3.2.3 Poultry meat .................................................................................................................................. 74 3.2.4 Sheep meat .................................................................................................................................... 74 3.2.5 Eggs............................................................................................................................................... 75 3.2.6 Milk ............................................................................................................................................... 75 3.3 TOMATOES.......................................................................................................................................... 76 3.3.1 Main burdens ................................................................................................................................ 76 3.3.2 Benefits of CHP ............................................................................................................................. 76 3.3.3 Effects of growing different tomato types ...................................................................................... 78 4 DISCUSSION.............................................................................................. 80 4.1 ARABLE .............................................................................................................................................. 80 4.2 ANIMAL PRODUCTS............................................................................................................................. 81 4.3 TOMATOES.......................................................................................................................................... 82 4.4 A CARBON-NITROGEN FOOTPRINT FOR AGRICULTURE. ....................................................................... 83 4.5 UNCERTAINTIES.................................................................................................................................. 84 5 PUBLICISING AND USING THE MODEL .......................................... 86 5.1 PUBLICISING THE MODEL .................................................................................................................... 86 6 FURTHER WORK .................................................................................... 87 7 CONCLUSIONS......................................................................................... 88 7.1 THE MODELS....................................................................................................................................... 88 7.2 THE RESULTS ...................................................................................................................................... 88 8 ACKNOWLEDGEMENTS ....................................................................... 90 9 REFERENCES ........................................................................................... 91 Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 9 of 97
1 Introduction This is the report of a project to develop a tool to analyse and compare the environmental impacts of alternative methods of production of major agricultural commodities. A comparison of production methods requires a procedure that provides an objective and systematic calculation of the primary energy, material consumption and environmental burdens associated with the production of each commodity. Life Cycle Assessment (LCA) provides such a method and was used. The objectives of the project were: 1. To develop, and later realise, a conceptual model to quantify the environmental burdens and resource use associated with the production of agricultural and horticultural commodities using the principles of Life Cycle Assessment (LCA). 2. To identify and classify the major typical production systems in England and Wales for the commodities specified and define a production process flow chart for each system. 3. To establish the mass and energy flows for each commodity and other necessary input data for the working LCA model, ensure that the sources and derivation are clearly identified and the uncertainties quantified. 4. To code the LCA model in a package, such as Microsoft Excel, with all the main data readily accessible. 5. To use the LCA model to analyse these production systems and demonstrate that the model can compare production systems and can identify high risk parts the systems (so called hot spots). 6. To publish and publicise the working LCA model.
The analysis determines the environmental burdens per unit of ten commodities at the national level (England & Wales, Table 1). The analysis ends at the farm gate.
Table 1 The commodities and standard quantities analysed in this project
Field crops
Quantity
Animal products
Quantity
Bread wheat
1t
Milk
10,000 l *
Potatoes
1t
Eggs
20,000 *
Oilseed (rape)
1t
Meat
Beef
1 t carcaseweight
Protected crop
Pigmeat
1 t carcaseweight
Tomatoes
1t
Sheep meat Poultry meat
1 t carcaseweight 1 t carcaseweight
* 20,000 eggs weigh approximately 1 t. 10,000 litres milk contains approximately 1 t dry matter.
Agricultural commodities are produced using a range of production systems and in various forms in order to satisfy consumer demand. Geographical location, land use, soil type, specialised markets and support mechanisms all influence individual production systems. Depending on the production system, the burdens will be influenced by factors such as type of fertiliser and pesticide used, frequency and nature of cultivations, type of crop rotation, stocking density and yield. Future changes, from whatever cause, will alter the production systems in use. The approach that was taken endeavours to account for all these factors.
Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 10 of 97
While it is possible to construct an LCA model using simply average values, it does not allow exploration of alternative production systems. Many terms are highly interactive and are much better described with functional relationships. As an example, the yield of wheat and its protein concentration respond to nitrogen supply. Increasing nitrogen fertiliser (an increased input burden) generally increases yield and protein concentration (useful outputs). Thus there is a trade-off between increasing burdens and outputs. For arable systems, important aspects that users may wish to consider include: The proportion of organic versus non-organic crop husbandry The use of reduced cultivation methods (to save energy use) The reduction in N application rate (potentially to reduce N emissions) The use of urea rather than ammonium nitrate fertiliser (effect on N emissions) The increases in crop yields due to technology (increased environmental efficiency) Improved varieties (reduced surplus N use, reduced pesticide use) The incorporation of straw (or use as animal bedding or fuel) The type of soil on which the crop is grown (to optimise yields and emissions) Use of irrigation for potatoes (to reduce water use) Main crop versus early potatoes For tomato production: The proportion of organic versus non-organic crop husbandry Types of tomato grown (e.g. classic, loose, on the vine, cherry) The proportion of nutrient film production (vs rockwool) The use of combined heat and power systems (CHP) For livestock systems: The proportion of organic versus conventional animal husbandry Fecundity of dams Longevity of dams Feed conversion ratios Liveweight gain, milk yield or egg production Forage requirements (grazing and conserved) Feed sources Housing systems Location (upland, lowland etc) for sheep These defined the variables of major importance in producing the LCA model, to ensure appropriate responses. The report is divided into a description of the methods used followed by results and discussion. The first section of the methods describes the details of life cycle assessment as applied to agriculture and is followed by a description of the analysis of wheat as the major field crop and the modifications necessary to model other field crops. The next sections describe the methods used for analysing livestock systems, tomato systems and finally the capital items (buildings and machinery) used by all the systems. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 11 of 97
2 Methods 2.1 Outline of LCA Principles Error! Objects cannot be created from editing field codes. Figure 1 Example of the LCA approach showing the system boundary LCA analyses production systems systematically to account for all inputs and outputs that cross a specified system boundary (Figure 1). The useful output is termed the functional unit, which must be of a defined quantity and quality, for example 1t breadmaking wheat. There may be co-products or waste products like straw, together with emissions to the environment, for example nitrate (NO3-) to water and nitrous oxide (N2O) to the air. All inputs are traced back to primary resources, for example electricity is generated from primary fuels like coal, oil and uranium. Ammonium based fertilisers use methane as a feedstock and source of energy. Phosphate (P) and potassium (K) fertilisers require energy for extraction from the ground, processing, packing and delivery. Tractors and other machinery require steel, plastic, and other materials for their manufacture, all of which incur energy costs, in addition to their direct use of diesel. The minerals, energy and other natural resources so used are all included in an LCA. Allowances should also be made for making the plant used in Industrial processes (factory or power station) as well as the energy used directly. 2.1.1 Agriculturally specific aspects of LCA Agriculture has particular features that are not relevant to the LCA of industrial processes. The main one is land itself and the soil. Farming systems must be considered in the long term to avoid illusory benefits. LCA requires the soil nutritional status to remain the same (over the course of a crop rotation). So, nitrogen (N), P and K inputs and outputs must balance. Omitting nitrogen fertiliser for one year may have a small effect on a conventional crop, but would have a much larger effect over many years as soil reserves are depleted. After one year, yields will only be slightly reduced owing to the soil fertility from previous seasons ­ the old system. The crop will, however, remove more nitrogen from the soil than enters the system as applied nitrogen. Over several years, the soil will reach a new steady state where the input and output of nitrogen become equal ­ and the yield stabilises at a new lower level. This is the true yield of the new system, which must be used in the LCA. Estimating long term nitrogen balances requires simulation models to project how practices would cause leaching and denitrification without soil nitrogen accumulating or being depleted. One consequence of this is that the estimates of leaching are often higher than the current actual ones, as current practices often appear to cause increases in soil organic nitrogen, which may not get microbially degraded and hence reach the environment for many years. A similar process applies to straw incorporation and soil carbon. Also weed accumulation over a rotation must be prevented by sufficient herbicide or cultivation. agricultural land is of varying quality, for example soil texture, rainfall potential and altitude. Models are thus needed to adjust yields according to land type for both arable and grassland. These must also reflect emissions such as leaching and denitrification. Long term data are needed for major inputs, such as fertiliser and lime use, pesticide use and grain drying energy requirement to avoid the normal variability of weather from year to year on activities. While it is possible to consider arable crops in relative isolation, this is not true for animal production. In the simplest cases of eggs, pig and poultry meat production, there are typically breeding nuclei, from which secondary herds or flocks are derived, and these feed replacement genetic material into the commercial sector. Within the commercial sectors, Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 12 of 97
several housing and rearing systems co-exist, each with its own characteristics. Changing the proportions of one part can have several interacting effects on other production areas. The situation with ruminant production (sheep meat and beef) is yet more complex. These may be reared in geographically diverse areas (such as hill, uplands and lowlands) and with a complex network of genetic flow. Beef animals are also partly derived from the dairy sector. Apart from these features, ruminants interact with the grassland that supports them. In addition, all livestock consume concentrates (e.g. wheat, soya, barley, maize, oil seed cake). These are grown on arable land and contribute to the total land requirements for livestock. Some are imported from overseas and their production and transport burdens must be estimated in addition to domestically produced feeds. Forages are also conserved as winter feed for ruminants (mainly grass and maize silage). Livestock produce manure, which when it is applied to agricultural land promotes crop or grass growth. It contains plant nutrients and thus displace the burdens of manufacturing these nutrients which is a benefit to animal production systems, making due allowances for the likely effectiveness of use. Manure storage and spreading, on the other hand, is a burden incurred by the animal production system. Livestock, like crops, respond to different levels of nutrition. For many meat and egg production systems, a single level can be assumed, but for example in dairying, the diet (and associated management intensity) influences not only milk production but also longevity, fecundity and methane emissions. A model combining these factors allows exploration of production systems. product quality is an important consideration, especially when dealing with biological materials. At the simplest end, meat is quantified as the edible carcass weight, as used in statistics produced by the Meat and Livestock Commission (MLC). This includes bones, fat, lean and skin in some cases. Milk is defined as the quantity of the fat-corrected product. Oilseed is simply that harvested, but wheat must reach a technical specification of breadmaking quality: 13.5% crude protein for conventional production. What does not reach this will end up as non-bread milling wheat or feed wheat. Tomatoes and potatoes cannot be specified as a single product as they are produced as diverse products to satisfy consumer demand, e.g. classic and cherry tomatoes, first early and maincrop potatoes. Each product has its own burdens and the functional unit of the commodity is instead defined as a 1 tonne basket consisting of a proportion of each product according to current national consumption. The system boundary of this study was specified as the farm gate. Some assumptions were needed to handle this equitably. It was assumed that the burdens of grain drying occurred inside the farm as did potato cooling and storage. These are required to keep the products stable. Tomato and egg packaging was assumed to be outside the gate, even though it may be economically linked to production, but it was considered to be part of distribution. The killing out percentage of carcasses is used to obtain the edible carcass weights of animals, but slaughtering and transport to slaughterhouses is not included. Milk cooling on the farm is also included, but not pasteurisation. A potential credit to the burdens arises from the consumption of considerable quantities of carbon dioxide by crops (and emission of oxygen). However, when the crops are consumed the same quantity is released to the atmosphere and conventionally it is ignored. However, if one was to consider the nations net imports and exports of carbon dioxide due to the consumption of food by the population, then this becomes an important benefit to agriculture compared with importing the same amount of food. Similarly the collection of energy from the sun is ignored, although it varies with crop type and yield and the zero option of no agriculture collects no energy from the sun. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 13 of 97
2.1.2 Allocation of burdens to co-products Some crops and animals produce more than one useful output, for example grain and straw from cereals or oil and meal from rape. Although the latter is produced beyond the farm gate, we need to analyse it because rapeseed meal is used as an animal feed. Growing the crop incurs a set of burdens and these must be allocated equitably to the co-products. In some cases, a functional approach could be used, for example based on nitrogen or energy distribution between products, but the main approach we used was by economic value. 2.1.3 Separation of crops and animals Although there are substantial interactions between animal and crop production, there is a need to separate them to determine the burdens of production of each commodity. Animals consume arable crops (and forages) and produce manure, which can fertilise grassland or arable land. Crops were analysed without manure. The benefits of the manure are credited to the animals in terms of displaced production and application of fertilisers. Summing a representative set of commodities will result in the same burdens as if the production systems were analysed as one integrated entity. 2.1.4 Organic production systems The terms "conventional" and "non-organic" tend to be used synonymously. Non-organic is probably more descriptive, but "conventional" when used in this report, implies the aggregation of contemporary non-organic practices. The organic sector is currently relatively small (although parts are growing rapidly). Table 2 shows the current proportion of organic production of the major commodities, and shows that the non-organic sector clearly dominates throughout. There may be many philosophical differences in outlook between organic and non-organic farmers, but there are only a few major differences that characterise the systems differently in LCA terms. The main one is fertilisation, in that organic farming does not use synthetically produced ammonium nitrate or urea (very energy intensive) or chemically processed P and K. Organic farming uses P and most K as directly extracted minerals, whereas P is commonly used as triple or single super-phosphate in the non-organic sector, because of the better availability of the nutrients in these forms. N is by far the biggest difference, however, with organic N being derived by N fixation through clover-grass leys. Cover crops are used much more in the organic sector between cash crops with a major aim of reducing N losses.
Table 2 Current proportions of organic commodity production
Commodity Bread wheat Potatoes Oilseed rape Tomatoes Milk Eggs Beef Pigmeat Sheep meat Poultry meat
Proportion, % 0.7 1 0 4 1 1 0.8 0.6 1 0.5
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Pesticide use in the organic sector is minimal, with no herbicides used and fungicides effectively limited to a derogation to spray for potato blight using copper based products. Potato tops are removed by mowing or flaming rather than spraying with desiccants. Organic farming places much more reliance on rotations and mechanical methods to control weeds. Ploughing is the dominant form of primary cultivation, although undersowing is often practised to provide control of weeds and other pests. There are some systematic overheads associated with organic crop production in fertility building and cover crops. A clover-grass ley is energy-free in terms of nitrogen application because of fixing nitrogen itself, but it requires some maintenance (typically chain harrowing and /or cutting) and stops the land itself being used for growing cash crops, so inflating the land requirement for organic cash crops. Cover crops are normally ploughed in, and so cannot be harvested. The seeds must be grown elsewhere on land dedicated to the purpose and then supplied to the farm. In total, three crops are sown, but not harvested: the ley, and two years of rye. We estimate how much extra land is used to produce these seeds. Livestock and manure are frequently an integral part of an organic cropping system. However the approach taken in the analysis was that the basic comparison between crops should be in stockless rotations because this determines the requirements for the crops and assesses their burdens more exactly and comparably. The fertiliser value of manure then becomes a reduction in fertility-building cropping required and hence land use of an organic arable crop, which is an environmental credit to the organic livestock. Note that the burdens of a whole farm, which are the sum of the burdens of the individual enterprises according to their proportions on the farm, are not affected by the choice of separation. Organic soils used for crop production are likely to contain systematically more organic matter (and hence C) than comparable soils used as non-organic arable land without leys. Some benefits of soils with higher organic matter content will appear in terms of actual yields recorded, so are implied as given by this study. Other potential benefits are not included. We have not found adequate data on cultivation energy to allow for this. There may be some effect on rain-driven soil erosion, but, this is likely to apply to light, steep fields and we propose that this should be considered at more local level. Soil C sequestration is enhanced through the use of leys, which is normal practice in the organic sector. There is no reason to expect this to differ significantly in non-organic farming using leys, but it is likely to be systematically higher than in soils using cropping without leys.
2.1.5 Aggregation of burdens The use of resources and emissions to the environment are collectively termed environmental burdens. Environmental impacts are a consequence of particular burdens. For example nitrate leaching is a burden, while the consequent eutrophication is an impact. Emissions to the environment, whether from farms, industrial processes or transport, are initially quantified by individual chemical species. Several of these are aggregated into environmentally functional groups of which the major ones that we use are: Global warming potential (GWP100): GWP is calculated using timescales of 20, 100 and 500 years, but we report the 100 year one in the "headline values". The main agricultural sources are nitrous oxide (N2O) and methane (CH4) together with carbon dioxide (CO2) from fossil fuel. It is quantified in terms of CO2 equivalents (Table 3). Table 3 Global Warming Potential (GWP) factors for major gases using the IPCC (2001) climate change values.
Substance
GWP 20 years, [kg
GWP 100 years, [kg
GWP 500 years, [kg
Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 15 of 97
CO2 CH4 N2O N2O-N
CO2-equiv] 1 62 275 432
CO2-equiv] 1 23 296 465
CO2-equiv] 1 7 156 245
Eutrophication potential (EP): The main agricultural sources are nitrate (NO3) and phosphate (PO4) leaching to water and ammonia (NH3) emissions to air. It is quantified in terms of phosphate equivalents: 1kg NO3-N and NH3-N are equivalent to 0.44 and 0.43kg PO4 respectively.
Acidification potential (AP): The main agricultural source is ammonia emissions, together with sulphur dioxide (SO2) from fossil fuel combustion. Ammonia contributes despite being alkaline. When deposited or in the atmosphere, it is oxidised to nitric acid. It is quantified in terms of SO2 equivalents: 1kg NH3-N is equivalent to 2.3kg SO2. Abiotic resource use (ARU): The use of natural resources was aggregated using the method of the Institute of Environmental Sciences (CML) at Leiden University (http://www.leidenuniv.nl/interfac/cml/ssp/index.html). Their data put many elements and natural resources onto a common scale that is related to the scarcity of the resources. It is quantified in terms of the mass of the element antimony (Sb), which was an arbitrary choice. Their data includes most metals, many minerals, fossil fuels and uranium for nuclear power.
Primary energy use: The major agricultural fuels include diesel, electricity and gas. These are all quantified in terms of the primary energy needed for extraction and supply of fuels (otherwise known as energy carriers). The primary fuels are coal, natural gas, oil and uranium (nuclear electricity). They are quantified as MJ primary energy which varies from about 1.1 MJ natural gas per MJ available process energy to 3.6 MJ primary energy per MJ of electricity. A proportion of electricity is produced by renewable sources such as wind and hydro-power, which account for 3.6% and 8% for UK and European electricity respectively.
Land use for crop production is reported assuming average yields for Grade 3a land (Bibby et al., 1969). Yields for were scaled up or down using linear coefficients derived from Moxey et al., (1995) for other land grades (Table 4) and required land use per one tonne of crop is one of these grades. However for animal grazing systems, owing to the network of rearing systems, land use is calculated as a proportion of each grade of land.
Table 4 Factors used to scale yields on different grades of agricultural land
Grade 2 3a 3b 4
Scaling Factor 0.88 1.00 1.08 1.12
2.1.6 Data sources There are established inventories and factors for many industrial processes and impacts. These were used in the present study, together with some established agricultural ones and new ones that we developed. While some values can be satisfactorily described by constants, many cannot and must be described by functional relationships. Typical examples are: yields in response to N in synthetic fertiliser or manure; leaching from soil in response to N application rate, crop yield, soil type and rainfall; milk yield and nutrients in diet. Specific examples are included as needed.
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Data were obtained from disparate sources. Much data on farm management, productivity and typical inputs were required, for example average N application rates, fecundity of sows, average potato yields. These were taken from standard texts, such as: Nix (2002-2005), Agro Business Consultants (2002-2005), Lampkin et al. (2002-2005), MLC yearbooks for pigs, sheep and beef, websites of organisations such as the MDC, Defra statistics from the June census, the Soil Associations ANNUAL REPORTS, HGCA and the Potato Marketing Council reports. Values for fertiliser use and manure compositions also came from Defras RB209 (MAFF, 2000) and the Surveys of British Fertiliser Practice (Defra, 2001-2005), pesticide use came from the annual pesticide surveys. Gaseous emissions of ammonia, nitrous oxide and methane came mainly from the UK national inventories, which also supplied some activity data (e.g. proportion of manures spread on arable and grassland). Chemical composition of crops came mainly from the UK tables of feed composition (MAFF, 1992), Ewing (1998) and McCance (2002). Apart from these standard sources, production data came from within the expertise of the project team. Commercial confidentiality precludes defining all such sources. Data also came from the scientific and popular literature as well as websites, such as those of the Feed Manufactures Association, Soil Management Initiative, Defra, and the United States Department of Agriculture. We developed our own inventory of materials and processes for the project. This was based on some of the data sources above, together with inputs from an EU harmonisation study (Audsley et al., 1997) and the Ecoinvent LCA data source (provided under the SimaPro platform). Ecoinvent is commercially sensitive so specific data have been masked in the working model. 2.2 Bread wheat production 2.2.1 Summary of activities causing agricultural burdens The main sources of agricultural burdens for field crop production are: Field diesel for cultivation, chemical and manure applications, irrigation and harvesting Machinery manufacture Producing fertiliser and pesticides Drying and cooling direct energy Direct soil-crop emissions to air and water (nitrate, nitrous oxide and ammonia) Construction of buildings Land use per t production All except the last involve energy and abiotic resource use and involve some gaseous and aquatic emissions. These apply in general to all crops, whether produced non-organically or organically, but with clear differences between crops and systems, for example potatoes are deep ploughed (never direct drilled), while conventional N comes from synthetic fertiliser and organic N from grass-clover leys and legumes. The same set of activities applies to grassland, whether grazed or used for forage conservation. So, the same list applies to feed production for livestock 2.2.2 Field operations All arable crops are grown in a similar way, with attendant burdens resulting from: 1. Seed bed establishment Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 17 of 97
2. Crop protection (weeds and diseases) 3. Fertilisation 4. Harvesting 5. Crop storage (including drying or cooling) Three alternative methods for planting crops were considered, namely plough-based, reduced cultivation and direct drill. Following the example of Chamen & Audsley (1993), the operations required to produce each crop were divided into: Pre-plough, such as subsoil which is carried out some years only Primary cultivation a. Plough followed by a rolling operation for winter crops. It is possible to use a combined operation of plough and press wheel, but with similar total power demand. b. Reduced cultivation such as discing or power harrowing, again followed by rolling c. None Secondary cultivation or seedbed preparation a. Power harrow operation, particularly on heavy land b. Discing or tining, particularly on light land Following Chamen & Audsley (1993), it is assumed that heavy land requires both a and b, medium land required two passes of b and light land required one pass of b. Combining this operation with the drilling operation in order to save labour, does not change the energy required for the operation. Planting ­ either a conventional or direct drill Crop protection ­ the number of passes depends on the system, with more weed control being required with less cultivation. Fertilising ­ the level of fertiliser depends on the yield expected, the desire to promote nitrogen content for bread quality, and the nitrogen carry-over from previous crops. Urea is less efficient due to greater ammonia losses and thus a higher application rate is required than with ammonium nitrate fertiliser. Harvest ­ if the straw is not being baled, then the combine harvester will also chop the straw (using more energy for this). Post harvest ­ baling and carting the straw 2.2.3 Fuel use for farm operations and machinery burdens All farm operations require a certain amount of energy. Thus, for example, ploughing (turning over one hectare of soil to a depth of 0.2 m) requires a certain energy input, MJ/ha. This energy is independent of the tractor power. In general, a tractor that is twice the power will be approximately twice the weight, have twice the width of implement, etc so that rolling resistance, traction, etc will be the same. Energy is represented by fuel use by a tractor. Table 5 shows data obtained from commercial farms on fuel use for operations, representing typical modern work rates and equipment. The Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 18 of 97
data on ploughing illustrate the point that the fuel use is not a function of the size of tractor or implement.
Table 5 Work rates and fuel use for field operations obtained from commercial farms
Tractor power, kW 336 194 130 243 114
Implement 12 furrow plough 7 legged sub-soiling Disc & pack ( 5.5 m) Disc (5.5m ) Drill ( 6 m) 5 furrow plough 12 t trailer 6.6 m rolls Sub-soiling tramlines 4 m Power harrow Harvest: OSR, peas, beans Harvest: barley/wheat Spraying
ha/h 2.5 3 4.5 5 4.2 0.84 5 5 1.16 2.54 2.27 10
Litres per 12h day 850 840 540 420 420 250 110 130 200 250 500 500 220
Litres/ha 28.3 23.3 10.0 7.0 8.3 24.8 2.2 3.3 17.9 17.9 20.0 1.8
Table 6 collates data from a number of sources on energy use for farm operations. There are wide differences, giving a coefficient of variation of about 40% in most cases. Energy use is a function of the soil type and Chamen & Audsley (1993) derived methods to calculate the work rate of operations as a function of the tractor power and soil type. The effect is biggest for cultivation activities, since more work is done to the soil, while surface activities like combining are unaffected. Average specific energy values (Table 7) (assumed to represent a loam soil) were thus adjusted by coefficients to compensate (Table 8).
Table 6 Direct energy use as diesel in field operations, MJ/ha as primary energy.
Activity
Sources Mean CoV, %
Ploughing
9
942
32
Sub-soiling - All field
3
752
29
Rotary cultivations
5
603
24
Heavy discs
7
506
53
Power harrow
6
641
23
Rolling
3
139
43
Grain drilling standalone 8
206
30
Potato planting
4
796
85
Ridging potatoes
2
634
96
Spraying
5
56
26
Potato harvesting
3
2112
66
Mowing
5
163
54
Forage harvesting
2
344
77
Transport as MJ/t
1
15
15
(Data sources included Witney (1988), Audsley (2002), Cope (1997, SRI pers. comm.. ), Koga et al. (2003),
Smith (1993), Chamen et al. (1996), Bridges & Smith (1979), Bailey et al. (2003), Anon (via Audsley pers.
comm.), Sijtsma et al. (1998), SRI farm data and commercial farms (this study).)
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Table 7 Energy used in field operations, expressed as MJ/ha of primary energy. All tillage is for working loam soils.
General Cultivations Spraying and fertilising Grain Harvesting Potato cultivation Forage conservation
Activity Sub-soiling Sub-soiling tramlines Plough (200 mm) Power harrow Rotary cultivator (4 m) Disc & pack Discing Spring tine harrows / weeding Conventional Drill Combined harrow & drill Direct drill Rolling (Cambridge rolls) Spraying, (self propelled) Disk fertiliser broadcasting Lime spreading Muck spreader Combine harvester with straw chopping Combine harvester without straw chopping Grain carting (yield dependent, 8 t/ha) Plough (250 mm) Potato destoner Potato ridger Potato planter Potato harvester Mower Mower-conditioner Tedder / Rake Forage harvester Baling
Total energy, MJ/ha 1,061 176 1,350 913 914 586 784 300 280 1,218 372 248 114 105 336 1259 1,134 1,096 399 1,688 3,082 860 1,116 3,142 198 299 183 1,392 298
Proportion as Field Diesel, % 78 74 76 77 72 66 71 75 74 75 73 61 54 78 70 37 69 68 29 76 81 81 78 74 90 90 97 88 77
Table 8 Factors to adjust cultivation energies from average values for loam soils
Activity
Clay factor
Sand factor
Ploughing
1.7
0.6
Disc & pack
2.0
1.0
Cambridge Rolls
1.0
1.0
Power harrow *
1.7
Conventional Drill
1.0
1.0
* In the context of plough based cultivation, power harrowing was only used with clay soils.
In organic cultivations, seedbed establishment uses ploughing as the norm. Reduced tillage
and direct drilling are much less applicable than in the non-organic sector because pesticides
are not normally used. Some crops in rotations are, however, undersown. In defining the
tillage requirements, additional light cultivations for weed control are used in organic for
weed and disease control. Typical pesticide applications were assumed in the non-organic
sector to achieve the same ends together with rotational control.
In both organic and non-organic crop production, rotations, tillage and spray use were defined that would achieve technically sustainable yields. The arbitrary removal of, for example, a spray application or weed control cultivation step might incur no yield loss in one year, but would progressively lead to long-term yield loss.
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2.2.4 Crop yield and response to nitrogen The effects of fertiliser nitrogen on crop yield and protein content were examined using data from Rothamsteds Broadbalk plots from 1991-2000, which used N application rates ranging from 0 to 288 kg N/hGar.ainTyhieilsd,dNactaosnectenitsravtioernyinugsreafinulanadsNthoefftafkeertfirloismer treatments have been applied for manycyoenatirnsu,osuostwhianttetrruwehleoant ggrotewrnmoenfBferocatsdbcaalnk pbleotsseaetnR(oFthigamursete2d). 1991-2000
8
160
Yield, t/ha or N conc. In grain, % N Offtake in Grain, kg/ha
7
140
6
Yield
120
N Offtake
5
100
4
80
3
60
2
N Conc.
40
1
20
0
0
0
50
100
150
200
250
300
N applied, kg/ha
Figure 2 Grain yield, N concentration in grain and N offtake from continuous winter wheat grown on Broadbalk plots at Rothamsted 1991-2000
The data clearly show that applied N increases the grain N (and hence protein) concentration, the grain yield and grain N offtake. Yield (Y) is well characterised by a standard form of linear-exponential curve: Y a bexp(cN) dN . The nitrogen offtake in grain is characterised by a logistic growth curve: Y a b /(1 exp(c(N d))) . The same forms of equation applied to straw, although the change in N concentration was less pronounced. The fitted values are shown in Table 9. The grain N concentration was calculated indirectly from the nitrogen offtake and yield.
Table 9 Fitted parameters for relating bread wheat crop yield to nitrogen fertiliser application (in kg/ha)
Parameter a b c d
Grain yield, t/ha 453.7 452.6 0.000626 0.237
Straw yield, t/ha 461.6 460.8 0.000333 0.135
Grain N offtake, kg/ha -37.35 204.9 0.0131 83.64
The Broadbalk data were for one type of wheat on one specific soil and are assumed to be for an average variety of wheat. Further adjustments were needed to allow for differences between bread and feed wheat protein concentrations and the effect of soil type on yield. The varieties chosen by farmers when growing for breadmaking are NABIM class 1 or 2. For feed they are likely to be class 3 or 4 which have higher yields (104% versus 99% of the control). Organic farmers (with lower soil nitrogen supply) need to choose the highest protein varieties to be able to achieve over 12% crude protein with any reliability and often grow spring wheat, which has a higher protein concentration, but is lower yielding. Using data from the NIAB Recommended List, the values of the yield and protein concentration were
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adjusted by the difference from the average of non-organic breadmaking, organic breadmaking and feed wheat varieties. Yields were adjusted according to soil texture, using coefficients derived in the Silsoe Farm Model (Audsley 1981). These vary between crops, but average wheat yields on clay soils are 104% of those from loams and those from sandy soils are 76% of those from loams. Only these three main soil textures were used and the national distributions (along with rainfall) were those established in the study Environmental Benchmarks of Arable Farming. (Defra project ES0112, Williams et al., 2004a). Another soil interaction is between sub-soiling and yield. We assumed that if sub-soiling is too infrequent on some soils (one third of all), there is a yield loss. This happens when the interval (i) exceeds i0 years. Below this interval, there is no yield loss or gain. The yield loss (l) is assumed to reach a maximum of lmax after a great time. The formula used for intervals above i0 years is thus: l lmax s / i , where s is a parameter. When the yield loss is zero, i = i0 and so lmax s / i0 and hence s i0lmax When i i0 , l 0 . We assumed a maximum yield loss of lmax =10%, with i0 =3 years. For non-organic wheat, the yield responses were further adjusted so that the national average yield (on the national distribution of soils) was obtained by using the national average N fertiliser rate. For organic wheat, the average organic yield was used to determine the nitrogen supply that would give that yield. This was then used to determine the protein content adjusted for high protein varieties. A similar response curve for applied N from organic materials such as compost was also derived. These relationships provide a model that can calculate national wheat yields in response to changes in major factors like soil type, wheat type and N application rate. 2.2.4.1 Determination of breadmaking quality Not all wheat intended for breadmaking achieves the quality required. HGCA (2003) reported a survey of samples of grain after harvest. For Hereward, the protein concentrations was typically 1%<11.3%, 21%<13.5%, 71%<15.5% and 6%>15.5%, suggesting a normal distribution of protein concentrations. Both the Hereward data above and Broadbalk data suggested a standard deviation of about 1% in protein concentration. Data on organic breadmaking wheat varieties shows a standard deviation of 0.66% protein, with a mean of 12.5%. It was decided to use a standard deviation of 0.6% to calculate the proportion of crop that met the breadmaking protein criteria of 13.5% for non-organic and 12.5% for organic from the mean protein concentration achieved by different systems. Furthermore, 5% of the NABIM 1 and 2 variety samples in the UK failed to meet the breadmaking quality criteria of Hagberg Index and specific weight, although 98% met the protein requirement. Typical reasons can be a laid crop or poor weather at harvest time. So, a further quality factor was needed to represent this, which was a constant of 4.4%, which resulted in 95% of the non-organically grown bread wheat being suitable for breadmaking. Wheat that is grown for breadmaking, but fails the grade becomes feed (or non-bread milling) wheat. The burdens were allocated between the bread and feed fractions according to their economic value. Let VF be the relative value of the feed grain and WB and WF be the t/ha respectively of bread and feed wheat portions, then the burden allocated to bread wheat is G*WB /(WB vFWF ) . An alternative would be to use the avoided burdens approach and deduct the burdens from producing that quantity of feed wheat from the total burdens for bread wheat. However, the difference is small. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 22 of 97
2.2.4.2 Allocation of burdens between grain and to straw Grain is harvesting by a combine harvester, but straw may be harvested or incorporated. If harvested, additional burdens are incurred by the straw baler, but the actual combine energy is reduced slightly as a straw chopper is not required. Thus one can calculate the burden attributable to the grain. The total burdens of producing grain and straw are: T H (1 ps )I ps B D
Then the burden allocated to grain is: G* (H I ) (Yg /(Yg vs psYs )) D ,
and the burden allocated to straw is: S * (H I ) (vs psYs ) (Yg vs psYs )
ps (B I) ,
where H is the vector of burdens of producing grain up to the end of combine harvesting per ha, I is the vector of burdens of chopping for incorporation for all straw produced, D is the vector of burdens of drying and storage of grain, B is the vector of straw baling burdens for all straw produced, ps is the proportion of straw baled and harvested, Yg is the net yield of grain per ha at standard DM content, Ys is the yield of straw per ha (whether harvested or not) at standard DM content, and vs is the relative value of the straw prior to baling versus the grain, typically 0.05.
2.2.5 Nutrient inputs and crop protection Nutrient inputs to a crop can be divided into readily mobile (nitrogen) and non-mobile (all others). Non-mobile nutrients do not need to be applied annually. Mobile nutrients are applied annually to ensure that as far as possible they are used by the crop and not lost. In a non-organic system, the level of nitrogen input to a crop is typically adjusted to be greater than the expected offtake by the crop, based largely on economic considerations. Data on the actual level of nitrogen input to crops were taken largely from the Survey of British Fertiliser Practice (Anon, 2000-2005). For scenarios where the N offtake of the crop is increased (eg increased yield or protein content), it is assumed that the N fertiliser input will be increased by the same amount.
For all other nutrients, farmers normally aim to apply quantities to maintain soil fertility levels which are checked and corrected over several years in response to soil tests. The input required to maintain a constant level of the main nutrients is therefore calculated by mass balance and it is assumed that this amount and its associated burdens are applied to the crop. One exception is potatoes when P is applied in excess of crop demand owing to the economic response. The surplus P thus displaced the P fertiliser requirement of other crops in proportion to the areas grown.
Table 10 Main burdens for producing, packing and delivering fertilisers.
Item Ammonium nitrate (AN) as N Urea (UN) as N Calcium ammonium nitrate (CAN) as N Ammonium sulphate (AN) as N Mean N fertiliser for grassland as N Triple super phosphate as P Single super phosphate as P Rock P from 25% P2O5 Tunisian Mean P fertiliser for grassland as P
Unit kg N as N kg N as N kg N as N kg N as N kg N as N kg P as P kg P as P kg P as P kg P as P
Primary GWP100, EP,
AP,
Energy, [kg CO2 [g PO43- [g SO2
MJ equiv.] equiv.] equiv.]
ARU, [g Sb equiv.]
N2O-N, to air, g
41
7.2 0.50
4.7
23
9.4
49
3.5 0.54
5.3
23 0.025
43
7.4 0.55
5.3
42
3.0 0.52
5.3
42
6.8 0.50
4.8
19
1.2 0.74
8.1
13 0.60 0.57
6.6
15
1.1 0.97
13
18
1.2 0.74
8.0
21
9.4
20 0.022
23
8.3
15 0.012
16 0.0094
17 0.012
15 0.012
Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 23 of 97
K fertiliser as K
kg K as K
5.7 0.53 0.30
7.2
3.9 0.0056
Rock K as K
kg K as K
15 0.86 1.40
8.8
17 0.0094
Gypsum as S (quarried)
kg S as S
5.50 0.35 0.58
3.7
5.9 0.0031
Gypsum as S from FDG
kg S as S
1.90 0.11 0.14
0.9
4.2 0.0020
Gypsum as S (Mixed)
kg S as S
3.70 0.23 0.36
2.3
5.0 0.0025
Limestone as rock
kg product
0.90 0.06 0.10
0.6
0.9 0.0005
Limestone as CaO
kg CaO
1.6 0.11 0.18
1.2
1.7 0.0010
Limestone as Ca
kg Ca
2.3 0.15 0.26
1.6
2.4 0.0014
Total for burnt lime (or chalk) as 90% CaO product
kg product
6.0 0.16 0.14
1.7
3.6 0.0014
Burnt lime (or chalk) as CaO
kg CaO
6.1 0.16 0.14
1.7
3.7 0.0014
Burnt lime (or chalk) as Ca
kg Ca
8.5 0.23 0.20
2.4
5.1 0.0020
Weighted lime usage as product kg product
3.4 0.19 0.31
2.1
3.2 0.0017
Weighted lime usage as CaO
kg CaO
2.3 0.12 0.18
1.2
2.0 0.0010
Weighted lime usage as Ca
kg Ca
3.2 0.16 0.25
1.7
2.8 0.0015
Sulphuric acid as a desiccant
kg
0.40 -0.13 0.06
0.6
1.0 -0.0008
Pesticide ­ dose ha
Dose ha
100
8.0
15
96
47 0.011
The burdens for producing, packing and delivering fertilisers (Table 10) were derived from several sources including: Audsley et al. (1997), Jenssen and Kongshaug (2003), Stout (1990), Shreve (1967), Sheldrick and Steier (1979), Reinhardt et al. (1991), Patyk and Reinhardt (1997), Patyk (1996), Mudahar and Hignett (1982, 1987a, 1987b), Mortimer et al. (2003), Martin and Shock (1989), Leach (1976), Helsel (1992), Goulding and Annis (1998), Elsayed et al. (2003), Elsayed and Mortimer (2001), Weidema et al. (1995), http://www.pda.org.uk/leaflets/23/no23-page3.htm, http://www.gct.com.tn/english/wcpg.htm and http://www.mining-technology.com/project_printable.asp?ProjectID=1198. The main burdens related to energy use (e.g. energy in the Haber process for converting N2 to NH3 or quarrying and transporting minerals), but one specific extra term is needed: N2O from nitric acid production. This is used for ammonium nitrate (AN) and calcium ammonium nitrate (CAN). Fertilisers are sold in a considerable variety of formulations, but we divided them into the principal component parts. Three minerals for use in organic systems are included: rock P, rock K and lime. These are extracted with minimal processing (quarrying and grinding being essential). We assumed that no burnt lime was used in the organic sector, and the lime used in the non-organic sector includes the small proportion recorded in the Fertiliser Survey. Chalmers (2001) reported the proportion of each major crop receiving manure (Table 11). The organic matter gradually becomes available to future crops at a rate of 10% per year and displaces the need for some of the artificial fertiliser. If we assume that the target crop occurs every 4 years and that otherwise the crop is a winter cereal, then we can estimate the proportion of the manure nitrogen becoming available to the different crops as fertiliser: Nc (rcU 0.1rcG /(1 0.94)) / Hc Nw (rwU 0.1rwG rcG(1 0.1/(1 0.94))) / Hw where N is the total nitrogen available as fertiliser to the crop (kg/ha) subscript c is the crop other than winter cereals and w is winter cereals U and G are the masses of manure nitrogen available nationally as UAN(1) (kg) and organic N (kg) respectively, (UAN(1) is the total of uric acid-N (from poultry manure) and total ammoniacal N (TAN) after storage and spreading losses have been accounted for.) U and G have values of 21128 t and 101981 t respectively. r is the proportion of manure received, Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 24 of 97
H is the cropped area (ha),
Table 11 Proportions of cropped non-organic arable land receiving manure applications
Areas
Cropped areas in England, kha
Potatoes Winter cereals & OSR Spring barley Sugar beet Forage maize All other crops Total arable area
112 2,596 291 154 107 673 3,932
Proportion Proportion of Plant available
receiving
manure
N, kg/ha
manure, % received, %
36
4.8
22
12
37.0
16
23
8.0
14
31
5.7
19
100
24.1
114
26
20.4
15
These values are reflected in the Fertiliser Survey by reductions in the amount of fertiliser applied. Chalmers showed that arable crop reductions are typically about 20 kg, which agrees with the above plant available N calculations. In terms of the LCA analysis this means that the ,,normal fertiliser level is the sum of the average from the survey and the value in the table. Forage maize values in the Fertiliser Survey show a very wide variation in rates from very low to 180 kg N/ha with a mean of 70. Thus the above result is not out of keeping with the values reported. The manure and hence animals are allocated the corresponding benefit. The level of crop protection applied is taken from Pesticide Survey data (Garthwaite et al., 2000-2004), cross referenced with data from commercial farms. The number of applications is taken as the number of doses applied to each crop and an average energy (and hence burden) was derived from Audsley et al. (1997).
2.2.5.1 Nutrient inputs in organic systems The additional burdens of fertility building and cover cropping are summarised as a typical organic rotation in Table 12. Leys and cover crops increase land requirements, but provide the necessary plant nutrients. The data shows that the additional ploughing required for fertility building per cash crop is a factor of 1.25 times the non-organic crop and the additional land required is a factor of 1.525. Note that if the second clover crop was wholly or partly grazed or cut for silage, the land requirement would be lower but there would be fertility implications for the later crops in the rotation.
Table 12 Overheads of cultivation and land needs in organic crop production
Eight year stockless organic crop rotation on 1 ha Clover 1 Clover 2 Spring wheat/ potatoes Forage rye Spring barley Winter beans Forage rye Spring oats No of ploughings
Establishment Undersown None Plough based Plough based Plough based Plough based Undersown Plough based TOTALS 5
Maintenance 1 x Chain harrowing 1 x mowing 1 x Chain harrowing 1 x mowing
Land for imported seeds, ha 0.033 0.033 0.033
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Eight year stockless organic crop rotation on 1 ha No of cash crops Total land use, ha
Establishment 4 6.099
Maintenance
Land for imported seeds, ha
Additional land is needed to grow seed for these crops. Rye has a typical gross yield (g) of 3.8 t/ha and the seeding rate (r) is 0.185 t/ha. So, the net land requirement for 1 t rye seed (s) is: s 1/(g r) ha/t, or 0.277 ha/t. The seed used for forage rye is 0.16 t/ha and three crops are required (assuming the same yield for grass and clover). This is spread over four cash crops, so the seed area per ha of cash crop (a) is: a 0.277 * 0.16*3/ 4 = 0.033 ha / ha and cash crop land requirements must be increased by 3.3% in addition to the ley land requirements (1 ha can supply 30 ha with seed). The establishment of grass leys in the non-organic sector was assumed to require the same land for seed production. With other seeds (e.g. mustard), the land requirement would still be similarly increased (and possibly with different burdens of producing the seeds).
For organic soya and maize production, the ratios are a little different, assuming the studies at Michigan State University are representative (Robertson et al., 2000). In their case, no extra land was used for leys, but two winter legumes were planted for three cash crops, hence:
a 0.277 * 0.185* 2 / 3 = 0.034 ha / ha, or a total land inflation factor of 3.4%.
Composts are used extensively in the organic sector. The burdens of composting have two main sources: energy for collection and turning, and gases emitted during composting. A simplifying assumption was that no leaching takes place from manure heaps, but all N losses are gaseous. Energy and emissions were estimated (Table 13) using data from several sources including: UK inventories of ammonia, nitrous oxide and ammonia, the MANNER manure N support system, RB209 (MAFF, 2000) as well as Amon et al. (2001), Chambers (2004), Hellebrand and Kalk (2001), Hьther et al. (1997), Kьlling et al. (2001), Morand et al. (2005), Osada et al. (1997), Petersen et al. (1998), Pratt et al. (2002), Sneath et al. (2006), Sommer (2001) and Williams (1998).
Table 13 Burdens of composting residues
Item Imported compost (total FW basis & energy based only) Compost-N (imported energy based only) Compost-P (imported energy based only) Compost-K (imported energy based only) Compost-S (imported energy based only) Cattle FYM composted - gases Pig FYM composted - gases Poultry No litter FYM composted ­ gases Poultry With litter FYM composted ­ gases
Primary GWP100, EP, AP, [g Unit Energy, [kg CO2 [g PO43- SO2 MJ equiv.] equiv.] equiv.]
t
80 5.10
7.1
43
kg
8.6 0.55 0.76
4.6
kg
8.6 0.55 0.76
4.6
kg
8.6 0.55 0.76
4.6
kg
8.6 0.55 0.76
4.6
kg N
4.40
68 300
kg N
1.30
570 2500
kg N
6.10
780 3400
kg N
4.40
620 2800
ARU, [g Sb equiv]
N2O-N, to air, g
170 0.094 18 0.010 18 0.010 18 0.010 18 0.010 3.6 2.0 11 9.2
It is assumed that organic farms import compost annually into arable soils at a rate of 1.4 t/ha (Soil Association, 2003). In reality it will vary between farms, depending on the local availability, but we use the national average. The burdens of making and carrying compost (turning and transport) are debited against crops, while the fertiliser value is credited to the crop. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 26 of 97
The N, P and K in ley and cover crops seeds must also be credited to the crop (Table 14). With other seeds (e.g. mustard), there are generally lower credits for N, P and K in the seeds owing to lower mass seeding rates. For the domestic rotations, rye seeds are applied twice at 0.16 t/ha and grass-clover seeds once at 0.025 t/ha for the benefit of four cash crops, thus averaging 0.086 t/ha per crop. The actual nutrient rates come from the composition with 86% DM, P and K at 0.5% of DM.
Table 14 Plant nutrient inputs from seeds of cover crops in organic rotations
Cover crop
Rye Clover or Grass 2 Grass- Grass- Grass-
legume
clover clover clover
for US
ley
ley
ley
soya and maize1
(75% (50% (25% grass) grass) grass)
Composition
75% 50% 25%
Dry matter, %
87
86
86
86
86
86
Crude Protein, %
11.6
26
12
16
19
23
N, %
1.9
4.2 1.93
2.5
3.0
3.6
P, %
0.5
0.6 0.49 0.52 0.55 0.57
K, %
0.5
1.1 0.28 0.49 0.69 0.90
Seed application rate, kg/ha
160
200
25
25
25
25
No of seedings per rotation
2
2
1
1
1
1
No of cash crops per rotation
4
3
4
4
4
4
Application rate of nutrients, kg/ha cash crop
N
1.29
4.77 0.10 0.13 0.16 0.19
P
0.35
0.69 0.026 0.028 0.029 0.031
K
0.35
1.26 0.015 0.026 0.037 0.048
1. Assumed same as peas
2. Assumed mean of rye, oats, barley and wheat (as in UK Tables on Feedingstuffs)
For the US soya and maize rotation, we assume that the seeds have the composition of peas
and are sown twice at 0.2 t/ha for 3 cash crops. The same composition was assumed for
clover seeds, and grass was assumed to have the same composition as the mean of major
domestic cereals: wheat, barley, oats and rye. The calculations show that seeds for cover
crops and the legume, used in the US are small relative to offtake, but should clearly be
included. Those for grass-clover leys (and other cover crops with similar seeding rates) could
be ignored without incurring great errors.
2.2.6 Grain storage After harvest, most grain is cooled, dried and stored. Depending on the moisture content, the crop may need drying and will require input to cool the crop for storage. Grain from one month (harvest time) was assumed to be shipped from the farm and used directly, thus incurring no farm storage requirement. This it was assumed that 11/12ths of the grain was stored and, although some grain can be stored in large central facilities, this was considered to be inside the farm boundary. The building requirement was derived from the floor area needed m2/t, A h / where h is the height of a stack of grain (m) and is the bulk density (t/m3). The mean value of A is 0.41 m2/t.
2.2.6.1 Grain drying Grain crops are subject to moulding in storage if the grains are too moist, and so often need drying after harvest before they can be put in a store. Over the course of the harvest period the harvested moisture content will vary due to weather conditions. In a very good year, no grain will require drying. A safe moisture content is related to the equilibrium moisture
Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 27 of 97
content and, for cereals, a minimum of 86% dry matter (DM) content is typically required. Data on long term harvested grain DM came from the Broadbalk dataset (Figure 3). These were used to calculate the energy needed for grain drying. The drying requirements for other crops were calculated by relating their equilibrium moisture curves (Nellist, 1998) to that of wheat so that the same distribution data from Broadbalk could be used as a proxy for DM at harvesting. The results (Table 15), show that the energy needed for drying barley is similar to wheat, but considerably more is needed for rapeseed, beans and maize. Furthermore, weather clearly influences the drying requirement, with less being needed in the last 10 years. Given the changes in climate, DwMecdoencteindteodf wtoheuastehatrhvees1te0dyfreoamr Bdraotaadsbeatl.k, 1991-2000 1.0 Average drying energy 0.8 needs calculated from fraction below 86% DM 0.6
Cum prob
0.4
0.2
0.0
70
75
80
85
90
95
DM, %
Figure 3 Cumulative probability of dry matter (DM) content of wheat harvested from Broadbalk plots at Rothamsted, 1991-2000 Table 15 Energy requirements for drying crops to achieve stable storage using three sets of data, MJ/t. Specific energy requirement for evaporating water was estimated to be 4.7 MJ/kg (McLean, 1989, Brooker et al., 1993)
Years to 2001 10 20 30
Wheat 68 153 152
Barley 83 169 170
Rape 101 280 257
Beans 88 245 230
Maize 238 732 649
2.2.6.2 Grain cooling In addition to drying and storage, some crops are cooled. Grains are cooled by ventilating with ambient air and an average value of 0.3 MJ/t was derived from data in McLean (1989) and Scotford et al. (1996).
2.2.7 Direct soil-crop emissions to air and water
2.2.7.1 Nitrate emissions to water The effects of soil and rainfall on leaching (emission of nitrate to water) and denitrification (emissions of nitrogen to air) were established using the SUNDIAL simulation program from Rothamsted Research (Smith et al., 1996). A range of non-organic and organic rotations were defined that contained representative crops. Simulations were run for long enough to ensure that the simulated rotations were in steady state, as indicated by the soil organic N (SON) fraction being the same at the start and end of a rotation. N inputs come from atmospheric deposition, fertiliser, fixing, seeds, returned roots, straw and haulm. N outputs come from primary crop offtake (grain, tubers), secondary crop offtake (straw), returned offtake (roots, straw and haulm), leached nitrate-N, denitrified-N and nitrogen from senescing leaves.
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The rotations were simulated for nine combinations of soil type and rainfall (clay, loam and sandy soil with low, medium and high rainfall, in the context of arable crops). Crops were also grown with and without straw incorporation. Yields, which are an input to SUNDIAL, were taken from national averages or standard texts, scaled according soil type using relationships previously developed by Audsley (1981). The N fertiliser inputs for nonorganic production were established from RB209 (MAFF, 2000) and use of the SUNDIAL (in the Fertiliser Recommendation System version). Individual crops were also simulated with N inputs increased or decreased by 20% from these standard values. Rotations present interesting challenges in allocating the amount of N leached or denitrified to specific crops. The N leached is generally related to the N surplus left after a harvest, but the contributions to that surplus may have arisen from the immediate inputs of fertiliser to the crop or from mineralisation or fixation from several preceding crops. The leaching may also occur from a crop over several years in the future, albeit in diminishing amounts. The hypothesis that leaching is related to N surplus was tested at a rotational level by linearly relating the whole-rotation N-leaching to the whole-rotation N-surplus. This produced highly significant linear relationships, but these were often specific to soil or rainfall combinations and differed between rotations. Allocations were then derived for the individual crops within each rotation on the basis that the allocations should be in proportion to the surplus for each crop. The results of this analysis were combined to generate linear relationships for each crop from which denitrification or leaching could be reliably calculated for each soil-rain combination from the N surplus for that crop. These coefficients were used in conjunction with crop husbandry data to predict denitrification, leaching and senescence for any given input of N. For beans, it was concluded that denitrification and leaching losses were a constant for each combination of soil and rainfall. For organically grown crops, an eight crop, six year stockless arable rotation was simulated with SUNDIAL, based on published data. This started with defining the crops and their typical current yields (Table 16). The crop yields (cereals, potatoes and winter beans) for these simulations were taken from Lampkin et al. (2002) and varied according to soil type. The initial assumption was made that these yields should be sustainable, using fixed N from a clover ley with beans in the 7th year, if it could provide sufficient N and not deplete soil reserves. Two variations of the rotations were examined in which wheat or potatoes were the principal cash crops, that is those grown after the clover ley. Preliminary runs were conducted to assess how well the rotation performed, which found that most crops could achieve their target yields, except for spring oats, which only yielded 3.0 t/ha, rather than the 3.8 t/ha that was forecast. Forage rye was used as a representative cover crop. The N fixed was calculated by SUNDIAL as nominally 300 kg/ha over the 2 years of clover, with more fixed in the second year than first year. This was based on standard values from the literature, and agreed as a possible value with the Elm Farm Research Centre. Nitrogen fixation varies with total soil organic N: the higher this is, the less N is fixed, because more inorganic N will be available from mineralization. Total N fixed also varies with soil type. The actual values calculated by SUNDIAL for each combination of soil and rainfall type and rotation accounted for these factors. The analysis of the outputs could not use exactly the same methods as with the non-organic rotations, because there was not a simple surplus that could be calculated for each crop (most N being fixed at the start by clover). There was also the question of how to allocate the N losses from the clover itself to a cash crop. Values for beans from non-organic rotations were used as that crops offtake and N losses. The sum of all other losses from a rotation was then allocated to the remaining cash crops in proportion to the useful N offtake of each crop. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 29 of 97
Table 16 Crops grown in stockless organic arable rotations that were analysed with the SUNDIAL simulation model
Crop
Yield t/ha
Sow date Harvest date
Sand Loam
Clover 1
2.1 2.5
Clover 2
2.6 3.0
Spring wheat or Potatoes 4.3/ 26.6 4.5/ 28
Forage rye
4.5 -6.7 4.5 -7.0
Spring barley
3.3 3.5
Winter beans
3
3.5
Forage rye
4.8 5.0
Spring oats
2.9 3.0
Clay 2.9 3.5 4.7/ 29.4 4.0-7.4 3.7 4.0 5.3 3.2
Oct Year 1 Mar Year 2 Mar Year 3 Sept Year 3 Mar Year 4 Oct Year 4 Sept Year 5 Mar Year 6
Feb Year 2 Feb Year 3 Sept Year 3 Feb Year 4 Sept Year 4 Sept Year 5 Feb Year 5 Sept Year 6
Crop period, months 17 12 7 5 7 12 5 7
The results of these analyses with SUNDIAL (Table 17) provided coefficients for linear equations in non-organic systems that predicted leaching and denitrification from crop type, N application rate, soil texture and rainfall. With organic systems, constants were estimated for each crop type, soil texture and rainfall combination.
Table 17 Summary of annual leaching and total denitrification for main crops as simulated with SUNDIAL under the standard (default) conditions of fertiliser application and cultivation methods for non-organic (N-org) and organic (Org.) crop husbandry.
Soil Clay Clay Clay Loam Loam Loam Sand Sand Sand Clay Clay Clay Loam Loam Loam Sand Sand Sand
Rain Dry Mid Wet Dry Mid Wet Dry Mid Wet Dry Mid Wet Dry Mid Wet Dry Mid Wet
Bread wheat N-org Org 37 59 41 78 46 91 39 47 43 63 46 74 60 69 60 79 62 88 78 56 75 51 71 52 77 49 74 44 70 44 56 32 57 34 55 37
Leaching, kg NO3-N/ha Main potatoes Spring barley Field beans
N-org Org N-org Org Org N-org
25 43
17 43 18 18
29 60
22 54 30 30
30 80
14 58 40 40
31 33
15 36 14 14
32 46
14 45 25 25
32 61
13 50 34 34
42 58
21 47 38 38
41 62
19 49 42 42
35 69
16 53 47 47
Total Denitrification, kg N/ha
38 37
19 40 38 38
36 35
14 35 47 47
36 43
22 33 52 52
32 31
22 36 30 30
33 29
22 31 39 39
36 32
23 29 45 45
21 23
15 21 30 30
22 23
17 21 33 33
26 25
20 22 34 34
WOSR Org N-org 32 47 36 59 42 63 40 39 39 50 43 55 54 53 52 55 64 58 94 44 93 38 88 36 89 40 92 34 89 32 78 24 80 23 68 24
2.2.7.2 Denitrification to nitrous oxide (N2O) using the IPCC methodology. SUNDIAL calculates total denitrification, but the major species of concern is N2O, given its great power in global warming. The IPCC method (IPCC, 1997), as reported in the UK GHG
Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 30 of 97
emission inventory (Baggott et al., 2004) was largely adopted for land based emissions. It was assumed that all direct inputs of N into soil are associated with an emission of N2O and each is associated with an emission factor. The following direct inputs are included:
1. Synthetic fertiliser
2. Biologically fixed nitrogen by legumes
3. Ploughed-in crop residues
4. Land spreading of organic fertilisers (animal manures, compost or sewage sludge)
5. Direct deposition of manures by grazing animals
In addition, two indirect emission sources are estimated:
1. Emission of N2O from atmospheric deposition of N 2. Emission of N2O from leaching of agricultural nitrate Emissions of N2O-N (kg/yr) from the application of synthetic fertiliser (O SN) are given by: OSN NF (1 e )1
where NF = total use of synthetic fertiliser (kg N/yr) e = fraction of synthetic fertiliser emitted as NOx + NH3 1 = emission factor for direct soil emissions (0.0125 kg N2O-N/kg N input) Emissions of N2O-N (kg/yr) from the biological fixation of nitrogen by crops (OBF) are given by:
OBF 2YFF1 where YF = production of legumes (kg dry mass/yr) F = fraction of nitrogen in N fixing crop (0.03 kg N/ kg dry mass by default or actual value if known explicitly) The factor of 2 converts the edible portion of the crop to the total biomass. The dry matter content for the crops considered is given in Table 18.
Table 18 Dry matter content and residue fraction of UK crops used for calculating N2O emissions under IPCC
Crop Type Broad beans, green peas Field bean, Peas(harvest dry) Rye, mixed corn, triticale Wheat, oats Barley Oilseed rape, linseed Maize Hops Potatoes Roots, onions Brassicas Sugar beet Other Phaseolus beans
Dry matter content 0.08 0.86 0.855a 0.855a 0.855a 0.91a 0.50 0.20 0.20 0.07 0.06 0.1 0.05 0.08 a Defra (2002)
Residue/Crop 1.1 1.1 1.6 1.3 1.2 1.2 1.0 1.2 0.4 1.2 1.2 0.2 1.2 1.2
Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 31 of 97
Emissions of N2O-N (kg/yr) from ploughing in crop residues (OCR) are given by:
OCR 2(YNN YFF )(1 R )1 where YN = production of non-N fixing crops (kg dry mass/yr) N = fraction of nitrogen in non-N fixing crops (0.015 kg N/ kg dry mass) R = fraction of crop that is removed from field as crop Emissions of N2O-N (kg/yr) from organic fertilisers (OOF) are given by: OOF 1 (Nm Nv ) where Nm = total N in each type of organic fertiliser Nv = N volatilised during storage and land spreading as N2O-N or NH3-N Indirect emissions of N2O-N (kg/yr) from the atmospheric deposition of ammonia and NOx (OAD) are estimated as:
OAD Na 4 where Na = total mass of nitrogen deposited annually (kg N/yr) 4 = N deposition emission factor (0.01 kg N2O-N/kg Na) Unlike IPCC, this includes all N deposited on agricultural land irrespective of its source. The estimate includes a correction to avoid double counting N2O emitted from synthetic fertiliser use.
Indirect emissions of N2O-N (kg/yr) from leaching (OLN) are estimated as:
where
OLN N L 5 NL = leached N (kg NO3/yr), calculated explicitly. 5 = N leaching/runoff factor (0.025 kg N2O-N /kg N(L)
2.2.7.3 Methane oxidation by soil A credit arises from agricultural land due to methane oxidation by methanotrophic soil bacteria. A value of 0.65 kg CH4 ha-1 year-1 for all non-organic land was established after an extensive examination of the literature (Ball et al. (1999), Ball et al. (2002), Boeckx and Van Cleemput (2001), Bronson and Mosier (1994), Dobbie et al. (1996), Dobbie and Smith (1996), Flessa et al. (1998), Freney (1997), Freibauer (2003), Goulding et al. (1995), Goulding et al. (1996), Goulding et al. (1998), Hutsch et al. (1993), Hutsch (1996), Jarvis et al. (1994), Mosier et al. (1991), Powlson et al. (1997), Prieme et al. (1997), Smith et al. (2000), Smith et al. (2003), Willison (1995), Willison (1995) and Willison et al. (1996)). This was arbitrarily increased by 25% for organic land on the basis that N fertiliser is not used and some work has shown inhibition of methane oxidation from this. The field evidence for more methane oxidation in organic soil was not, however, found in the literature. The extra land used for grass-clover leys in organic arable crop production is also credited with methane oxidation capacity.
2.3 Oilseed rape production Oilseed rape is grown in a generally similar way to bread wheat. The main differences between the systems are listed in Table 19.
Table 19 The main features of the crop cultivation methods of principal crops studied for nonorganic (N-org) and organic (Org.) systems
Gross yield, t/ha
Bread wheat Oilseed rape
Potatoes maincrop
Potatoes
Potatoes
first earlies second earlies
N-org Org N-org Org N-org Org N-org Org N-org Org
7.1 4.1 3.3 1.9 49.4 32.3 26.3 19.4 43.1 30.2
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N fertiliser (synthetic),
kg/ha
208
0 195
0 170
0 170
0 150
0
P fertiliser, kg/ha
18 10 18
8 110
9 10
4 17
9
K fertiliser, kg/ha
36 41 26 10 225 140 114 75 195 129
Straw/haulm
incorporation, %
75
5 100 100 100 100 100 100 100 100
Seed bed preparation:
Plough based, %
57 100 50 90 100 100 100 100 100 100
Reduced tillage, %
41
0 45
0
0
0
0
0
0
0
Direct drilling, %
2
0
5 10
0
0
0
0
0
0
Spraying:
Active ingredients per ha 14.7
0 14.4
0 21.2 2.0 14.8 2.0 21.2 2.0
Passes per ha
5.6
0 10.6
0 12.0 2.0 8.4 2.0 12.0 2.0
The yield­nitrogen curve of each crop was modified so that the optimum fertiliser rate was equal to the fertiliser rate from the Fertiliser Survey and gave the national average yield. The resulting parameters are given in Table 20. The main differences in husbandry are that seed is more often sown by broadcasting, rather than drilling and that very little straw is harvested. An organic crop was modelled, although almost none is grown. It must be acknowledged that the comparison is thus highly speculative as there are very few data relating to organic oilseed rape. The crop parameters used were essentially scaled by the ratios of organic to nonorganic wheat.
Table 20 Parameters for yield of crops versus nitrogen application
Crop Oilseed rape Winter barley Spring barley Potatoes-main Potatoes-1st Potatoes-2nd
a 203.55 412.35 360.07 3061.4 1628.3 2735.9
b -203.03 -411.29 -359.14 -3053.5 -1624.1 2728.9
c 0.000614 0.000784 0.00103 0.000670 0.000832 0.000725
D -0.104 -0.270 -0.311 -1.713 -1.131 -1.656
Nitrogen 200 154 110 220 170 200
2.4 Potato production There are three main types of potato grown: maincrop, first earlies and second earlies. The main differences between the potato systems and bread wheat are listed in Table 19. The yield-nitrogen curve of each crop was modified so that the optimum fertiliser rate was equal to the fertiliser rate from the Fertiliser Survey and gave the national average yield. The resulting parameters are given in Table 20. Earlies differ systematically from maincrop in that the crop is not stored. Yields of first earlies are about half of maincrop, while those of second earlies are about 90% of maincrop. Organic production is similar to non-organic and this is the only field crop upon which pesticides are sprayed, that is copper based products for blight control. Potatoes tend to be grown on lighter land than cereals. Crop establishment requires deep ploughing and additional operations to destone and or ridge the crop. Harvesting inevitably requires much work to be done on soil, so it is energy intensive. Potatoes are often irrigated, with the amount depending on the weather and soil type. Maincrop potatoes tend to need more irrigation than first earlies, which may be harvested before the summer soil water deficit sets in. A relationship for yield in terms of proportion of the area irrigated was developed. Weatherhead (1997) studied yield and water use on medium available water content (AWC) soil in the fens and showed a 25% increase where irrigation Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 33 of 97
was used. Assume yield, Y increases linearly with the proportion of crops using irrigation, then
Y () ((100 1) 1)Y (0) where 100 is the yield increase at 100% irrigation, for example 1.25 is the proportion of potatoes irrigated. The current yield, Ym and current level of irrigation m is known, thus Ym ((100 1)m 1)Y (0) Substituting for Y(0), the yield at any level of irrigation, , is: Y () (( 100 1) 1)Ym (( 100 1)m 1) A summary of irrigation activity (Table 21) was derived from commercial farm practice and survey data Weatherhead et al. (1997, 2002). The increase in yield by irrigation was derived from Weatherhead (1997) using 20 year data of yield and water use on medium AWC soil in the fens. This showed that irrigation increased yield by 25% for maincrop potatoes. In the absence of other data, this value was also used for earlies. Long term yield data were obtained from Defra, being 19.1 t/ha for earlies and 43.5 t/ha for maincrop. Care is needed in dealing with the early potato yields as the Defra statistics do not discriminate between 1st and 2nd earlies. Nix (2004, 2005) suggests yields of 44, 20 and 42 t/ha for main, 1st and 2nd earlies respectively, which are used.
Table 21 Mean irrigation rates, the proportions irrigated, the response to the proportion irrigated and the average yield of potato growing areas in England. (Numbers in brackets are % Coefficient of Variation)
Type of potato First earlies Second earlies Maincrop
Application rate, mm/year 90 (18) 105 (xx) 120 (23)
Proportion irrigated, % 40 (11) 48 (xx) 56 (24)
100 1.25 1.25 1.25
Ym 19 (21) 42 (xx) 44 (4)x
Maincrop potatoes may be stored for over a year (e.g. Defra Statistics: http://statistics.defra.gov.uk/esg/publications/auk/2004/6-11.xls). While the domestic market for maincrop potatoes falls in the spring, some are stored for processing (chips, crisps etc). Most potatoes are stored in temperature controlled environments, some using just ambient ventilation, while others use refrigeration. A small proportion is stored in clamps. The distribution of store types was found from the Pesticide Usage Survey (Anderson et al., 2002). Reported values for the specific energy needs for cooling potatoes range from 63 MJ/t as electricity for ambient cooling (Anon, 1999) to refrigerated stores at 700 MJ/t (Beukema and van der Zaag, 1990). Two crucial parts of the overall estimate are how long the storage phase lasts and how full a store is. If all stores are emptied gradually, the efficiency of cooling will fall with time. An ideal approach is to empty stores in sequence so that whole stores can be switched off in turn. The actuality must lie between these extremes, and this was modelled, together with data on the distribution of store types. Using the data sources above plus commercial practice (from this project), Bishop and Maunder (1980) and British Potato Council Monthly Data, a set of values was estimated (Table 22). This included an assumption that 10% of organic maincrop is sold directly (e.g. vegetable boxes and farm shops). This would probably not remain valid if the organic method became the main production system rather than the niche it currently occupies, so the cooling energy was scaled in proportion to
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the level of organic production so that the energy demand became the same for 100% organic and non-organic.
Table 22 Energy consumption during potato storage
Item
National Total - for nonorganic, %
Organic (estimated), %
Building, MJ (as primary energy)
Electricity (as primary energy), MJ
Weighted primary use, nonorganic, MJ
Weighted primary use, organic, MJ
Outdoor clamps
0.2
0.7
0.0
0.0
Unventilated
building
2.7
9.3
11
0.3
1.0
Ventilated building
35.8
33.2
11
224
84
78
Refrigerated building
61.3
56.8
11
929
576
534
Total
100.0
100.0
661
613
2.5 Animal feed crop production
Six feed crops are modelled as they are major components of animal feeds. In two cases (maize grain and soya), production is overseas. In these cases, production was modelled as closely as possible using local techniques, but transport burdens for importing were also included. Table 23 The main features of crop cultivation methods for the feed crops studied
Winter
Spring
Feed Wheat Barley
Barley Field Beans Soya Beans Maize Grain Maize Silage
N-org Org N-org Org N-org Org N-org Org N-org Org N-org Org N-org Org
Gross Yield, t/ha
8.0 4.6 6.5 3.8 5.7 3.1 3.5 3.3 2.6 2.6 7.2 4.0 11.2 7.5
N fertiliser (synthetic), kg/ha 192 0 150 0 110 0 0 0 0 0 120 0 100 0
P fertiliser, kg/ha
20 11 21 11 19 9 12 13 10 11 19 7 30 19
K fertiliser, kg/ha
41 43 56 46 60 44 32 28 40 38 54 6 138 92
Straw/haulm incorporation, % 75 5 15 0 0 0 100 100 100 100 100 100 0 0
Seed bed preparation
Sub-soiling
0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.20 .20 0.20 0.20 0.20
Plough based, %
57 100 57 100 57 100 57 100 27 100 30 100 57 100
Reduced tillage, %
41 0 41 0 41 0 43 0 53 0 58 0 41 0
Direct drilling, % Spraying
2 0 2 0 2 0 0 0 20 0 12 0 2 0
Active ingredients per ha
14.7 0 14.2 0 8.1 0 10.0 0 10.6 0 2.8 0 2.5 0
Passes per ha
5.6 0 4.9 0 4.9 0 6.1 0 6.5 0 7.8 0 7.5 0
2.5.1 Feed wheat production Feed wheat was modelled as bread wheat, except that higher yielding lower protein varieties were used. The details are shown in Table 23. 2.5.2 Barley production Barley was modelled as bread wheat, but using appropriate parameter values for both WINTER AND SPRING varieties of barley. About 70% winter barley is used for feeds and 30% of spring (the remainder being used for malting). 2.5.3 Field bean production Field beans were modelled on wheat, but with notable differences. Crop establishment does not include direct drilling, but broadcasting followed by ploughing is the norm (to set seeds deeper than is necessary for cereals). No N fertiliser is used, beans being leguminous. The
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only real difference between organic and non-organic is that pesticides are not used in organic production. The yields of organic beans are normally similar to non-organic ones, but the decision was taken to increase land requirements in the same way as wheat or potatoes for the grass-clover ley. While beans do not need the ley, they are grown with it as part of a whole system. Land requirements of the other arable crops would have had to have been increased yet more.
2.5.4 Soya bean production Soya beans were modelled in a similar way to field beans, except that direct drilling and reduced cultivation is practiced extensively on this crop. The main imports are from the USA, Brazil and Argentina. The proportions of crop establishment methods were estimated using data from the National Agriculture Statistics Service of the US Department of Agriculture (http://usda.mannlib.cornell.edu/reports/nassr/other/pcu-bb/#field), the European Conservation Agriculture Federation (ECAF), (http://www.ecaf.org/). Reduced tillage and direct drilling are used much more widely in the Americas than here, although much of the motivation is for water retention rather than energy saving. The summary is shown in Table 24.
Table 24 Distribution of cultivation methods used for soya and maize grown overseas
Soya USA Brazil Argentina Weighted tillage types for soya Maize for grain (all from USA)
Source of imports, % 70 20 10
Plough, % 30 23 16 27 30
Reduced Direct
tillage, Drilling,
%
%
58
12
45
32
33
51
53
20
58
12
Yields and fertiliser requirements were obtained from USDA, Benton Jones (2003) and Michigan State University (Robertson et al. 2000, plus supplementary data from the university web site). Transport burdens were based on the ocean travel distances, together with assumptions about a split of internal transport in the producing countries and in Britain (Table 25).
Table 25 Distances transported (km) and methods of calculating burdens for imported feeds.
Feed
Country
Soya, Maize Soya (Organic from here only) Soya
USA Brazil Argentina Weighted mean
Road 300 300 300 300
Rail 1,000 1,000 500 1,080
Ship 5,120 8,320 10,080 7,478
Proportion of soya imports 70% 20% 10%
2.5.5 Maize grain production Almost all maize grain used in the UK comes from the USA. Crop production and yield data were obtained from the same sources as for soya.
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2.5.6 Maize silage production Forage maize is grown to ensile and use as cattle feed. It is grown like other arable crops, although a forage harvester is used and manure applications are normally included in the fertilisation regime. Data on crop composition and fertilisation needs were taken from Wilkinson et al. (1999), with the crop nutritional needs being based on manure-free soil. 2.6 Grassland production Table 26 shows how various operations were combined into systems of work for grassland management. The extra field operations of rolling and forage harvesting or rolling, cutting, swathing and baling were added to calculate the burdens. Table 26 Field operations used in grassland production systems
Organic grassland establishment O(sarngadn) ic grassland establishment O(loragman)ic grassland establishment G(clraays)sland establishment G(sarnasds)land establishment G(loraamss)land establishment G(clraays)sland harvesting Grass Land agronomy GOragsasnliacnldowland agronomy -Upland Grassland agronomy Lowland
Seedbed cultivation Plough based - Clay
0.5
0.5
Seedbed cultivation Plough based - Loam
0.5
0.5 0.5
Seedbed cultivation Plough based - Sand
0.5
Seedbed cultivation Reduced tillage - Clay
0.4
0.4
Seedbed cultivation Reduced tillage - Loam
0.4
0.4 0.4
Seedbed cultivation Reduced tillage - Sand
0.4
Seedbed cultivation Direct drilling - Clay
0.1
0.1
Seedbed cultivation Direct drilling - Loam
0.1
0.1 0.1
Seedbed cultivation Direct drilling - Sand
0.1
Grass seeds (at 25 kg/ha seeding rate)
111111
Spraying for herbicide
111
Fertilisation
42
111
Liming (once) default rate is 1/7 years
111111
Chain harrowing
1
1
Grass roller
1
1
111111
Mower ­ conditioner
1
Rake
1
Forage harvesting
1
2.6.1 Grass yield and nitrogen model Grass yield was modelled using the grass site class system (Brockman and Gwynn, 1988). The dry matter (DM) yield (t/ha) of grass (YGDM) was related to site class (S) and N fertiliser applied (NF, kg/ha) by regression to obtain the following expression for grazed pastures:
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YGDM
cS a ln(1 b ek(N Nm ) ) k
where
cS is a fitted parameter for each site class
a 0.01485 0.00112cS k e(5.3020.594S ) b=1.5 Nm 296 /(1 e0.836(cS 5.15) ) The optimum nitrogen application (Nopt) for a ratio (r) of (price of grass):(cost of nitrogen) is given by:
Nopt

Nm

ln
b((a
1 r)

1)

/
k
where typically r=100. The values for Nopt in each site class are shown in Table 27, together with the fitted parameter cs..
Table 27 Parameter values for cs and calculated values of Nopt
Site class, S 7 (rough grazing) 6 5 4 3 2 1
cS 2.00 7.55 8.40 9.52 10.55 11.81 13.51
Nopt 12 263 285 304 324 356 417
In a grazing system, in addition to applied fertiliser, nitrogen is applied to the crop by the animals excreta. This causes the organic matter to build up and cycle round the system to become available to both the crop and loss processes to air and water. In addition the sward may include clover which fixes nitrogen. The resulting system can be described by a system of equations which can be solved for a steady state. The total nitrogen available annually to the grass crop is: Na Natm Nc N f Ns Ne , where Natm is the atmospheric nitrogen, which typically ranges from 15-35 kgN/ha, Nc is the nitrogen fixed by the clover percentage C, which was derived from NCYCLE (Scholefield et al, 1991) where Nc 8.6 CcS / c1 C 41.36 0.0128N f 0.0482Na if grazed C 28.2 0.1072N f if cut for silage Nf is the fertiliser nitrogen applied, which in a non-organic system is defined as the amount that makes the nitrogen available without atmospheric nitrogen, equal to the economic optimum. In the organic system it is zero. Ns is the nitrogen surplus not leached or denitrified over the winter. Ne is the nitrogen in grazed animal excrement which is not lost. The nitrogen content of the grass is a function of the nitrogen available
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gN =20.14+0.0136(Na-Natm) thus, the total nitrogen taken up by the crop is gNYGDM. The balance is thus at risk of loss to air and water. The proportion emitted to air and water is given (Sandars, 2003) by 0.45+0.08 I, where I is the soil index and the balance is Ns remains available to the crop. The proportion of this leached is 0.965-0.13 I and the balance is denitrified. This was partitioned into N2O-N and N2-N using the Bouwman equation for N2O (Bouwman, 1996). When grazing, 20% of the dry matter yield is assumed to be spoilt by trampling and defoliation and thus unavailable for consumption by the animal and returned as organic matter to the soil. When grazing, an animal utilises on average u% of the nitrogen content and the balance is excreted. (u=5.9% for sheep, 9.6% for beef and 24% for cows). Of the excreted proportion, 70% is urine and 10% of the dung is soluble. Of this soluble N, 15% is volatised as ammonia and the balance of the N excreted becomes available over time as part of the total N available to the crop, Ne. This system of equations is solved (iteratively) for Na and the resulting Nf were found to be comparable with typical values of fertiliser application. The default sources of fertility for grassland are, in the non-organic case ammonium nitrate (AN) as N, triple super phosphate as P, K fertiliser as K. In the organic case we assume that the equivalents are Clover N, Tunisian Rock P containing 25% phosphate, Rock K as K. The corresponding utilisation factors for phosphate and potash, for all classes of stock, are 0.33 and 0.1, respectively. 2.6.1.1 Calculation of sward types A sward type, such as lowland dairy grazing, is a composite of different grass growth site classes. For each 5 km grid square in England and Wales, the percentage of each soil type is known (NSRI database) and the percentage of the land of each land use types is known (MAGIC database). Soils are classified as potentially arable, potentially grassland or unsuitable. Uses are allocated to known soil types as far as possible, with sandy soils given priority for arable, then the unsatisfied uses are allocated pro-rata to the remaining soil. Thus the area of grassland in each grid is associated with a number of soils. Using the table of site classes (Brockman, 1995), each soil is defined as a site class based on the soil type, rainfall and altitude. Allowance is also made for northerly soils such that at the Scottish border 1 is added to the site class. The soil is also classified as lowland or upland. The final report on Defra project IS0209 (Morris et al., 2005) identified the area of land used by dairy, beef and sheep in the lowlands and uplands. Using these data, dairy land was identified as the ,,grass not heath of site classes 1 to 3. Beef was then allocated to all remaining land in site classes 1-5, in the lowland and upland proportions identified by the report. Sheep was allocated similarly, but also included site class 6. The resulting total areas of land closely matched the total areas from the June census (Defra, 2004) and the reports land allocations. Regionally, the method seemed to predict too good a site class in the East and particularly South-East, for the number of animals in the census, so an additional rainfall requirement was imposed on land in the east of the country. 2.7 Crop by-products and feed processing The main domestic by-product is straw for bedding (mainly wheat) and feed (mainly barley). Burdens for these were derived by economic allocation from the grain production burdens. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 39 of 97
Major feeds are also produced from oil-bearing crops (e.g. rape, soya and maize) and cereals (e.g. fractions of milled wheat). Much animal feed is processed in mills, with the rest being home fed, with little processing, except for crushing. Values for general feed processing on farms and in mills (rolling, flaking, pelleting etc) were derived from UKASTA data and the Ecoinvent database (Table 28).
Table 28 Energy consumption in general feed processing (not including oil extraction)
Type of feed All feeds at mills Domestic cereals ground on farms Peas and beans ground on farms
Primary energy, GJ/t 0.70 0.30 0.45
Milled feeds are also transported from the point of production to the mill and out to the receiving farms. For pigs and poultry, an eastern dominance was assumed with a mean 150 km back to farms, while for cattle and sheep, a western dominance was assumed with a mean of 250 km to farms (by large lorries). Delivery to the mills was assumed to be a mean of 100 km for wheat and barley and 260 km for rape (Elsayed et al., 2003). Imports of soya and maize come from several sources, with a mixture of methods (Table 25). These were weighted by the distribution of country of origin.
2.7.1 Wheatfeed Milling wheat produces the desired main product of flour and a variety of products that can be used for animal feed: collectively wheat offals or wheatings or wheatfeed or varieties thereof. We use the term wheatfeed as it is used in the Defra feed statistics. The allocation used was by economic value. Data on the composition of milled fractions came from INABIM (1979) and Pomeranz (1988).
2.7.2 Maize partitioning Maize grain can be split into starch, oil, gluten and minor components. Maize gluten is a major feed for cattle and is used for some other stock and is what we import. Other products from maize processing are used for feeds in the US, but these are often wet and are not suitable for export. The processing is much more intense than mere milling and involves screening, milling, steeping, centrifugation and drying stages. The main alternative products are maize starch and oil. Cederberg (1998) provided two sets of values for the partitioning of maize and the energy used (Table 29). It seems reasonable to set the gluten feed fraction as 22% of maize grain. Economic value is used in allocating the burdens.
Table 29 Mass fractions of maize during fractionation to produce maize gluten feed
Item Starch Maize gluten feed (22% CP) Maize gluten meal (60% CP) Germ meal Total accounted for
Source 1 63% 20% 5% 7% 95%
Source 2 61% 24% 9% 7% 100%
2.7.3 Rape meal Rapeseeds are converted into oil and meal residue, using crushing and solvent extraction. There is also a little wastage. Data on mass partitions, process energy and solvent requirements came from Elsayed et al. (2003). As far as we know, rape meal is not used as an organic feed.
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2.7.4 Soya meal As with rape seeds, soya beans are also split into oil, meal and a little wastage, but the hulls can also be extracted separately. Crushing and solvent extraction are also used. Allocation was also economic, using values for partitioning and prices from Cederberg (1998), Wolf and Cowan (1979) [cited by Cederberg (1998)] and some extrapolation of the extraction methodology from Elsayed et al. (2003). A major difference between soya and rape fractionation is that the soya meal is much more valuable that rape mean, given its very good amino acid profile and high protein concentration. Only whole soya beans are used in organic feed. It was also assumed that meal with hulls was fed to ruminants while pigs and poultry received meal without hulls. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 41 of 97
2.8 Tomato production Tomatoes require a similar set of activities to field crops, but also require heating to extend the growing season. They also need the greenhouse itself, support materials (twine and hooks) and a growing medium, e.g. rockwool, nutrient film or soil. Another major difference is that much more human labour is used in crop establishment, pesticide application and harvesting, so diesel use is much lower. Some of the principles described for field crops apply to organic tomatoes, for example synthetic fertilisers and pesticides are not used for organic tomato production and soil is used. Biological pest control is used in both sectors. Nitrogen fertility is supplied from manure based products. Some materials are not used in organic production, for example twine is made from jute rather than the fossil-fuel derived polypropylene. 2.8.1 Features of protected cropping Tomato production differs from arable cropping in that it takes place in the protected environment of glasshouses. This extends the cropping season from an unprotected one of July to October up to March to October-November. This provides a fresh salad crop for much more of the year than was previously possible and so enhances the national diet and reduces our dependency on importing alternatives. Protected cropping allows biological control of pests to be reliably deployed, so reducing the use of synthetic pesticides. Glasshouses for long-season tomato production are heated and ventilated with the aim of providing an optimum microclimate for fruits to develop. Heating is most commonly by gasfired boilers. The heat raises the temperature so that photosynthesis and hence fruit production is accelerated. Furthermore, the exhaust gas is chemically clean, containing mainly N2, O2, CO2 and H2O. The CO2 in exhaust gas can also be fed into glasshouses to enhance photosynthesis. Modern glasshouses use a variety of control systems to optimise heat and CO2 from boilers. Much CO2 is thus fixed as biomass during the growing season, but this is relatively temporary and is emitted to the atmosphere following digestion by humans and disposal of residues by composting etc. There is also an increasing trend to replace heating from gas-fired boilers by combined heat and power generation from gas, so that electricity is produced as well as heat and CO2. This applies to all production systems. Glasshouse production is a high input-high output system, with much higher yields per ha than from field crops, so having considerably lower land requirements. 2.8.2 Physical structure The burdens of producing the structures of the glasshouse must be included in the analysis. The main parts are the house itself, including glass, metal frames (typically aluminium), steel boiler, possibly a generator and heating pipes; concrete for foundation, passageways etc., plastic pipes and pumps for irrigation; metal motors and links for ventilation control. These have a relatively long life span and are written off over 10 to 30 years. Other components are brought in every 1-2 years, including steel supporting hooks, supporting twine plastic sheeting, rockwool, synthetic fertilisers, pesticides and composts. 2.8.3 Tomato production systems and products There are three main tomato production systems, two non-organic and organic, and several marketed products, which contribute to the national basket of tomatoes. The main nonorganic system uses rockwool as the growing medium (94.4%) and the rest use the nutrient film technique (NFT). Both non-organic systems supply nutrients and water in a closely Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 42 of 97
controlled way so that supply matches demand as exactly as possible. This eliminates leaching losses and, as long as nutrient solutions are aerobic, denitrification to N2O should be minimised. The third system is organic, which uses soil-based production with nutrients from composted manure and other residues. The soil water relationships can be closely controlled (unlike with field crops) so that leaching and denitrification losses should be lower than from field crops.
2.8.4 Physical, chemical an biological inputs The main glasshouse structure is the same for all production systems, but organic ones have soil, which must be cultivated and is periodically disinfected with steam to prevent disease build up. Rockwool is usually disposed of annually. Organic producers use less disposable plastic than non-organic producers do, for example twine is from imported jute rather than polypropylene. All systems use biological control, but synthetic pesticides are used in the non-organic sector and surfactants that act physically are also used in the organic sector. There is great commercial secrecy about the production of biological control agents, so that the burdens of their production are somewhat speculative. Tomatoes are required for their production, so we inflated tomato production burdens by 0.5% and included transport requirements. All systems use bees for pollination. Tomato products can be divided in several ways, which we have simplified a little. The main type is the classic tomato, with the rest being collectively "specialist". The specialist types include: cocktail, cherry, plum (mini, midi and maxi) and beef. Any tomato may be loose or on the vine, although beef seem to be only produced loose. Beef tomatoes have similar yields to classic so that they are subsequently grouped with classic rather than the other specialist varieties. Similarly, any tomato type could be produced organically, although the current market composition is biased more towards specialist and vine types.
2.8.5 Productivity of tomato types A critical feature of the LCA analysis is that the inputs of heat, electricity and fertilisation for each system are about the same per ha irrespective of the product grown. The yields of the tomato types differ substantially. Organic production yields about 75% of non-organic, but there is negligible difference in productivity between NFT and rockwool. The current weighted mean of specialist tomatoes yield about 50% of classic tomatoes while vine tomatoes yield about 42% of their loose equivalents. The land area required per t of the main tomato types consequently varies considerably (Table 30). Given that the main burdens for each type are related to the area-based inputs, this has a strong influence on the burdens of production. Table 30 Land needed to grow tomato of different types of tomato, m2/t
Product Classic loose Specialist loose Classic vine Specialist vine
Non-organic 19 38 45 92
Organic 25 51 61 122
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2.9 Buildings and machinery
2.9.1 Machinery Tractors, implements and other machinery are manufactured (mainly from steel and plastic), maintained and housed. The burdens of these were calculated over the typical life time of implement and tractor combinations. These depend on work rates and machinery longevity. The analysis used the method of Audsley et al. (1997), with data from that study, supplemented by data gathered in the present study. As with the energy input to operations, in terms of the burdens of making and maintaining machinery, operations are independent of tractor power.
Weights of tractors, ploughs and sub-soilers were found from manufacturers data and were fitted to linear equations as:
W2 15.2 P 2540 W4 71.5P 1420 where W2 and W4 are the weights of two and four wheeled tractors (kg) and P is the engine power in kW and:
Wp 401 629 Ws 281 24.9
where Wp and Ws and the weights of ploughs and sub soilers (kg) and is the number of furrows or legs. Maximum power available from a PTO shaft (Pmax) was related to engine power (Pe) by: Pmax Pe (0.000421 Pe 0.735) The main characteristics derived from Audsley et al. (1997) and using the above relationships were evaluated to give the lifespan of machinery as well as the energy needed for manufacturing, maintenance and housing (Table 31 and Table 32).
Table 31 Main characteristics of typical tractors and self-propelled machinery
Total primary
Machine
Engine power, kW
Machine mass, kg
Service life, years
Rate of Units utilisation unit/yr
Proportion of life per unit of use, %
energy for manufacturing and housing per unit of life of
item, MJ
75 kW Tractor (2 WD)
75 3,680
10 h
1,000 0.010%
59
75 kW Tractor (4 WD)
75 3,940
10 h
900 0.011%
60
150 kW Tractor (4 WD)
150 9,300
10 h
700 0.014%
182
300 kW Tractor (4 WD)
300 20,000
10 h
700 0.014%
392
Combine harvester with
straw chopping
150 11,500
7 ha
600 0.024%
350
Combine harvester without
straw chopping
150 11,500
7 ha
600 0.024%
346
Forage harvester per ha
370 11,900
5 ha
1,818 0.011%
165
Sprayer, self propelled
114 10,300
7 ha
3,500 0.004%
53
Fore end loader, self
propelled
75 4,440
7h
1,825 0.008%
44
Potato harvester
200 4000
5 ha
500 0.007%
33
Front loader (potato harvest
loading)
100 6229
5h
1,830 0.022%
172
Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 44 of 97
Table 32 Main characteristics of typical trailed and powered machinery
Machine
Machine mass, kg
Service life, years
Units
Rate of utilisation, unit/yr
Proportion of life per unit of use, %
Total primary energy for manufacturing and housing per unit of life of item, MJ
5 furrow plough
1,380
10 ha
83
0.120%
96
7 furrow plough
2,180
10 ha
167
0.060%
109
Subsoiler, 3 legs for tramlines
818
10 ha
500
0.020%
19
Subsoiler, 7 legs for normal
cultivation
1,940
10 ha
500
0.020%
45
Heavy discs 5.5 m width
4,580
10 ha
500
0.020%
107
Light discs 5.5 m width
4,500
10 ha
500
0.020%
105
Disc & pack 5.5 m width
4,750
10 ha
500
0.020%
111
Power harrow, 4 m
2,250
4 ha
431
0.020%
52
Power harrow & packer, 4 m
2,500
4 ha
431
0.020%
58
Seedbed conditioner 6 m
1,130
10 ha
500
0.020%
26
Inter-row cultivator 6 m
1,130
10 ha
500
0.020%
26
Spring tine harrows 6 m
1,130
10 ha
500
0.020%
26
Other light cultivations 6 m
1,130
10 ha
500
0.020%
26
Cambridge rolls, 6 m
3,180
15 ha
500
0.020%
75
Rotary cultivator 4 m
1,300
7 ha
200
0.071%
108
Conventional drill 6 m
1,200
5 ha
1,000
0.020%
28
Direct drill 6 m
1,800
5 ha
1,000
0.020%
42
Combined harrow/drill 6 m
4,580
5 ha
1,000
0.020%
106
Mounted crop sprayer 24 m
1,000
7 ha
2,000
0.007%
7.6
Disk fertiliser broadcaster 12 m 200
7 ha
1,000
0.014%
3.1
Lime spreader
1,300
5 ha
1,000
0.020%
30
Baler
1,800
7 bales
1,500
0.010%
20
Potato planter
2,250
7 ha
500
0.020%
52
Potato ridger
1,130
7 ha
500
0.010%
13
Potato destoner
1,300
7 ha
500
0.029%
43
Straw chopper on combine
150
7 ha
600
0.024%
3.9
Mower, 6 m
1,290
7 ha
1,000
0.014%
20
Mower - conditioner, 6 m
1,970
7 ha
1,000
0.014%
30
Tedder 6 m
700
7 ha
2,000
0.007%
5.8
Rake 12 m
700
7 ha
1,000
0.014%
12
Transport as MJ t-1 ha-1
30
7 ha
500
0.029%
1.0
Irrigator (fuel per mm applied) 1,000
7 m3
22,900
0.046%
58
2.9.2 Buildings The burdens of a representative set of farm buildings were derived from the typical material composition of building components, including steel, glass, concrete, insulation, wood plus energy for construction, demolition and maintenance. Values for these came from measurements made by the project team, Audsley et al. (1997), technical specifications of agricultural structures and interpretation of such data by a structural engineer from Silsoe Research Institute. Burdens of components came from proprietary software (SimaPro), data sheets from the Building Research Establishment (www.bre.co.uk/envprofiles/) and Audsley et al. (1997). The main building burdens are shown in Table 33.
Table 33 Summary of total resources used in agricultural buildings (per year per m2)
Building
Primary GWP 100, Energy [kg CO2
EP, [kg PO43-
AP, [kg SO2
ARU, [kg Sb
Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 45 of 97
Steel clad, concrete floor, e.g. grain, potato store Steel framed, fibre cement clad, concrete floor, e.g. grain, potato store Steel roof, earth floor, e.g. machinery store Broiler house, steel framed, wooden, earth floor, insulated Steel framed, Timber sided building, concrete floor, e.g. dairy cattle Pole barn, wood clad & steel roof Pig house, slatted floor Battery house Perchery / stilt Free range birds Outdoor pigs Low cost beef / sheep Greenhouse
use, MJ 26 39 17 34 62 8.7 87 87 28 24 1 10 16
equiv.] 2.7 3.9 1.4 3.9 7.9 6.0 11 11 3.3 2.8 0.1 6.1 1.3
equiv.] 0.0024 0.0030 0.0015 0.0051 0.0078 0.0027 0.0095 0.0095 0.0042 0.0035 0.0001 0.0028 0.0009
equiv.] 0.014 0.019 0.007 0.030 0.038 0.021 0.062 0.062 0.025 0.021 0.001 0.022 0.007
equiv.] 0.65 0.62 0.81 1.15 1.02 0.14 1.30 1.30 0.96 0.80 0.04 0.22 0.38
2.10 Animal production Six animal commodities were studied: poultry meat, pig meat, sheep meat, beef, milk and eggs. Poultry meat was assumed to be a composite of chicken and turkey meat. The other commodities were all produced by one class or species of stock. Milk comes from dairy cattle breeds and the contribution from other species, such as goats, is assumed negligible at the national level. Similarly, all eggs are assumed to be produced by chickens. The functional units are taken as 1 t of carcass dead weight, 10 m3 milk, or 20,000 eggs. The functional units were chosen to reflect the way that each commodity is traded, but the system boundary is the farm gate. The "Killing out Percentage" (KoP) is a factor for the conversion from liveweight to deadweight and is estimated as 47%, 55%, 70% for lamb, beef and poultry respectively; and as 72%, 75% and 77% for pigs of liveweights 76, 87 and 109 kg respectively (MLC data and http://statistics.defra.gov.uk/esg/evaluation/ofs/annexf.pdf). In addition to field emissions there are direct and indirect emissions from the animals (indirect ones coming from manure). These are: methane (enteric and manure), nitrous oxide (manure in housing, storage and land application) and ammonia (same sources as nitrous oxide). Nitrate can also be leached from land-applied manure. Animal production also requires feed processing (on or off the farm) and some overseas imports e.g. whole soya beans (organic) and soya meal after oil extraction (in Britain) for non-organic. Bedding is also used, mainly straw ­ a co-product of cereal production. 2.10.1 Modelling the structure of the animal production industries To model the production of livestock commodities in England and Wales, account has to be taken of the structure and diversity of the national industry. The meat-producing animal is produced by mothers who themselves have to be produced. The components of the sheep industry are spread amongst different farm types. From a farm management perspective, the industry is thus studied and reported as a set of different enterprises. These enterprise descriptions provide the essential building blocks from which we have modelled the industry. Transport steps connect some of them. Enterprise descriptions also define different ways of doing the same job. For example, piglets for finishing can be produced from indoor or outdoor breeding units. The non-organic sheep industry has a structure that maximises hybrid vigour in the terminal Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 46 of 97
generation. Pure bred hill flocks produce draft ewes that are used in the kinder uplands to produce cross breeds, which in turn supply the female breeding stock to the lowland fat lamb producers. These different ways co-exist but the model can be used to examine the implications for the environment of changes in their proportions. 2.10.2 Animal production network structure Changes in the proportion of any enterprise component must result in changes to the proportions of others in order to keep producing the desired amount of commodity. Establishing how much of each enterprise is required is found by solving simultaneous linear equations that describe the relationships that link the enterprises together. The equations have the following structure. The solution is the amount, X, of each activity, i, that produces the desired mass of output Z, n Z zi Xi i1 where zi is the output (meat, milk or eggs) of activity i, and also satisfies the set of flows between activities: n cij X i 0, j 1...p i1 where cij is the supply or demand of j by activity i, which describes the relationship between enterprises. Demands are negative and supplies are positive and total supply must equal total demand. For example, purebred lowland flocks produce rams, which are, in turn, demanded as terminal sires by lowland finishing flocks. The total amount of material k flowing into the system is: n M k mik X i , k 1...q i1 where mik is the flow of material k into activity i. The LCI for the system is the total of each burden l p Bl M kbk l , l 1...r k 1 where bkl is the amount of burden l produced by the use or disposal of material k and Mk is the total amount of material. The LCI identifies the contribution of each material Bkl M kbkl or activity q Bil X i mikbkl k 1 which provides the data to enable particular "hotspots" to be identified. Note that one of the burdens from ruminant systems is the land use is a combination of different land classes, indicating the proportion of the production which is on hills, upland or lowland. This contrasts with the field crops where land use can be any one of the land classes, the amount required being dependent on the quality of the land. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 47 of 97
2.10.2.1 Pig meat structural model Non-organic breeding and weaning units are modelled with indoor and outdoor options (Table 36). Finishing units are modelled as entirely housed, but three different finishing weights are modelled, 76, 87 and 109 kg liveweight. Replacements are modelled as retained females with inputs analogous to finishing. In the organic case the whole system is modelled as an outdoor combined breeding, weaning and finishing system. The model assumes that 80% and 25% of non-organic breeding and weaning units are outdoors, respectively. The non-organic finishing units produce 75% light and 20% medium and the balance as heavy. The model assumes that 0.6% of the market is organic. 2.10.2.2 Poultry meat structural model Three generations of breeders are required to produce the final generation; the breeding process is similar for organic and non-organic production. The final generation of nonorganic chickens can be finished in housed or free range condition. For non-organic turkeys the choice is between housed, pole barns or free range. The only finishing system for organic poultry is free range. The model (Table 38) assumes that 80% of the poultry market is derived from chickens and approximately 1% of the chicken and turkey market is organic. Free range accounts for 0.54% of non-organic production and barn production accounts for a further 15% of finished turkey production. 2.10.2.3 Eggs structural model Like poultry production there are three generations of breeding stock, which are similar for non-organic and organic production systems. Non-organic egg layers can be housed in cages or in barns (percheries) or free range; organic can only be housed free range. The model (Table 37) assumes that 66% of non-organic production is in caged housing and 27% is barn produced with the balance as free range production. 1% of the market is assumed to be currently organically produced. 2.10.2.4 Beef structural model The beef industry is characterised by numerous finishing systems of various intensities, taking advantage of the different finishing characteristics of purebred dairy, crossbred dairy and suckler beef bred calves (Table 41 and Table 42). A number of intermediate grass and indoor growing stages are modelled because beef take more than one season to finish. Under lowland conditions suckler herds can be spring or autumn calving. Intensive cereal beef finishing is modelled for non-organic production. The model assumes that 35% of beef calves originate from beef suckler herds. Of these suckler herds 33% and 33% are located in the hills and uplands respectively with 40% of the remaining lowland herds calving in the spring. Of the spring born non-organic lowland suckler calves 20% and 20% are assumed to be finished intensively as cereal beef and silage beef, respectively. Of the dairy bred calves 45% are finished in 18-20 months, 25% in 22-24 months and 15% are winter finished. 0.76% of the market is assumed to be currently organic. 2.10.2.5 Milk structural model Milk is modelled as self-contained herds at a series of yield levels (Table 35). In the nonorganic case, three yield levels are modelled for autumn and for spring calving herds. In the organic herds, we model three yield levels and an all year round calving pattern. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 48 of 97
The model assumes that 1% of the market is currently organic. For each of the series of yield levels 25% are low, 55% are medium yielding and the balance are the highest yielding. Of the non-organic herds 80% are autumn calving and 20% of the herds have access to maize silage in their diets. 2.10.2.6 Sheep meat structural model The non-organic sheep industry is a network of pure and cross bred flocks that come down from the hills to produce the terminal generation of fat lambs in the lowlands (Table 39 and Table 40). The organic industry is self contained. The model assumes that 1.17% of the market is currently organic. The organic industry assumes a 50:50 split between ewes in the lowland and upland. Of the non-organic industry the model assumes that there are three upland ewes to every hill ewe and that of the surplus hill lambs 10% can be sold as finished to continental markets with the remainder being finished as stores at home. In addition 10% of all non-organic lambs can be produced intensively as early lowland lambs. 2.10.3 Animal production models The technical performance of the livestock enterprises required data, such as values for daily liveweight gain, feed conversion ratio offspring per dam, longevity of dams, concentrate and forage requirements etc. The data came from the standard sources (for example Nix, ABC, MLC yearbooks). These provided constants, which are adequate for describing most current livestock production, but functional relationships (models) were also needed, for example relating energy and protein supply to milk yield and manure outputs in dairy cows, in order to allow changes within a system to be made and for all the effects to be properly quantified. This section details the models that were used 2.10.3.1 Milk production The following expressions were developed to give a system that is more responsive to change than one based solely on static coefficients derived from the standard sources. Cow productive life, L is a linear function of milk yield, Y: L L0Y / Y0 where L0 and Y0 are the average life and milk yield. Increased milk yield can be attributed to a number of factors, namely the size of cow, the feeding level and the milk productivity bred into the cow. Mature cow liveweight, W kg is defined as a function of milk yield, W W0 Y / Y0 The model produces the required number of purebred replacement female calves with a number of male calves produced. Surplus matings are crossbred to beef type bulls. The model assumes a 0.51 chance of a male calf. Given that the total dry matter intake from forage, maize and concentrates must equal the feed intake limit and that the energy intake must equal the energy required, these two equations can be solved for the amount of forage and concentrates required in the diet of any yield of cow. The feed model is derived from the Agricultural Research Council. (1980). Voluntary feed intake, V kg [dry matter] per year: V 9.125W 0.1Y Metabolisable energy (ME) needs, E MJ/year: E (3029.5 eWW ) eP eYY / 0.84 where eW is the ME requirement of live weight = 33.215 MJ/ kg eP is the ME requirement of a pregnancy = 2013.5 MJ/ year eY is the ME requirement of milk = 5.16 MJ/ litre Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 49 of 97
In England the proportion of the diet which is maize is largely correlated with the yield potential of the herd. The maize in the diet is estimated as z 0.001Y 5.5 kg DM Solving the two equations for dry matter intake and energy, the requirement for concentrates, xc kg DM: xc (E V ) /(mc ) where mc is the ME of concentrates = 12.5 MJ /kg DM z (1 g) / g s(1 g)(1 z ) / g 1 g is the proportion of the forage diet that is grazed = 0.6 and 0.4 for spring and autumn calving herds, respectively s is the factor by which silage suppresses appetite = 1.2 mzz (1 g) / g ms (1 g)(1 z ) / g mg mz is the ME content of maize silage = 11 MJ/t mg is the ME content of grazed grass = 10 MJ/t ms is the ME content of grass silage = 9 MJ/t is the substitution rate of concentrates for forage = 0.6 The diet responds to production requirements, which means that the properties of excreta, especially the nitrogen need to respond as well. The dietary Crude Protein nitrogen requirement P, g/year P 31025 146W ) (11000 50Y) where = Kjeldahl N content of protein = 0.16 kg [N]/ kg [Protein] The excreted nitrogen is XN, g[N] / year: X N P / d p YY where dP is the digestibility of dietary protein = 0.6 Y is the nitrogen content of milk, 5.44, g [N]/ litre As the fate of nitrogen in manure is linear with content, the correct environmental burdens can be calculated by the addition of appropriate proportions of slurry or farmyard manure using only two standard nitrogen contents of 4 and 5 kg [N]/t [fresh weight]. Thus 10t of 4kg/t plus 10 t of 5 kg/t is the same as 20t of 4.5kg/t. The enteric methane emission factor was scaled in proportion to the forage dry matter intake. 2.10.4 Inputs to animal production 2.10.4.1 Concentrate feedstuffs The precise mixture of ingredients varies for each concentrate fed to different classes of stock (Orr, 1995). Defra statistics (http://statistics.defra.gov.uk/esg/datasets/hstcomps.xls) show that wheat and derivatives dominate feeds blended by manufacturers (Table 34). The inclusion of six other main crops (and minerals) accounts for 84% of feed production. Diets were formulated using these feeds, assuming that the minor feeds provided similar nutritional properties for similar burdens. Further analysis of feed by IGER which included home mixing, suggested that concentrates consisted overall of: 50-60% wheat, 20-30% barley and about 20% of a protein source (e.g. rape meal, legumes, soya or fishmeal). There are only limited data on the breakdown between animal types as much feed is mixed on farms. Furthermore, commercial feed producers maintain a high degree of confidentiality over actual ingredient mixes. We believe that the major ingredients in Table 34 cover most of the industry. Proportions between classes clearly vary, for example the IGER analysis suggested that field beans and peas were included at 8-10% in ruminant feed and barley reached 38% in beef and sheep feeds. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 50 of 97
We aimed to include most livestock concentrates, but originally set an arbitrary threshold for inclusion of 5%. We lowered this to enable inclusion of feeds that we already modelled, e.g. field beans and minerals, but minor feeds like oats and some by-products were omitted. The formulation of rations was thus based on the feeds in Table 34, but the quantities were increased to cover the 16% of minor feeds not specifically modelled.
Table 34 Mean distribution of main raw feeds used by feed blenders in 2000-2004
Feed Wheat Cereals by-products, wheat feed and other cereals by-products
Proportion of total, % 25 21
Soya cake and meal
9
Barley
6
Oilseed rape cake and meal
5
Other oilseed cake and meal
8
Whole and flaked maize, and maize gluten feed
5
Minerals
4
Field beans and peas
1
Total accounted for
84
Source: http://statistics.defra.gov.uk/esg/datasets/hstcomps.xls
Burden calculation method Direct Economic allocation from wheat and barley Direct for bean production and import plus economic allocation for oil extraction Direct Direct for grain production plus economic allocation for oil extraction Analogous to imported soya and rape Maize grain direct and derivatives by economic allocation from maize grains Direct Direct (as beans)
2.10.4.2 Energy inputs Specific data were obtained by the project team that quantified the direct energy use in intensive pig and poultry housing systems. For other cases, the whole farm energy costs (Nix, 2004) were analysed. After allowing for the energy inputs into fieldwork, which are already integral in the feed burdens, we partitioned the remainder into diesel for stock management and related activities and electricity for activities such as milking and milk refrigeration. 2.10.4.3 Animal transport Simple assumptions were made to allow for the movement of animals between farms. Nonorganic systems are widespread, and an allowance of 100 km by medium sized lorry was assumed. Organic farming systems are more widely dispersed, but more self contained, so an allowance of 200 km was assumed. 2.10.5 Emissions and manures from animal production 2.10.5.1 Direct emissions from livestock Animals and their manures are the source of three important direct gaseous emissions: methane (CH4), nitrous oxide (N2O) and ammonia (NH3). Methane is a consequence of fibre digestion in the rumen (and lower gut to a lesser extent). Emissions from the animal and from its excreta within housing systems are calculated following the methods of the national inventories for methane, ammonia and nitrous oxide. 2.10.5.2 Credit for displaced fertiliser and crops Emissions from manure storage and land-spreading were quantified using and extension to the national inventory methods and data. The emission factors due to storage were re-estimated Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 51 of 97
using new evidence from research (Williams et al., 2002, Williams et al., 2004a, Williams et al., 2004b). The interactions between manures, soils and crops are complex. However, in the long term all of the nutrients that are applied to the soil as manure will be accounted for as either crop products or as losses to the environment. A series of projects at SRI has studied, and developed a method of tackling this problem (Sandars et al., 2003, Williams et al., 2002, Williams et al., 2004a, Williams et al., 2004b). After allowing for the effect of season, the proportion of the theoretically available nitrogen used to make fertiliser savings is variable. The combination of lack of knowledge of manurial nutrients, lack of respect for manure as a source of fertiliser, and a tendency to over application, lead to relatively low fertiliser saving (Scott et al., 2002). In the model, we assume that 50% of the available nitrogen in pig and dairy slurries is used to save fertiliser, but for broiler litter the figure is 40% because there is more evidence of over application. The remaining nitrogen is accounted for by several fates, which are calculated using the models. Typically, nitrous oxide losses account for 2.5% (OECD, 1991) of the nitrogen, the crops removes around 16%, and the rest is either lost as nitrate leaching (49%) or is denitrified (32.5%). In the extreme case of non-organic outdoor pig, poultry and broiler production the same land is used for more than one season and the animals will leave the ground devoid of vegetation. We assume that none of the nitrogen in half of the excreta is available as a fertiliser saving, there being no following crop. The nitrogen cycle in these cases is complex and warrants further investigation. With the routine use of soil testing it is safe to assume that all of the manurial potash and phosphate will, in time, be used as a source of fertility. Ruminant manures are modelled as applied to grassland, whereas pig and poultry manure are modelled as applied to winter wheat. The model assumes that non-organically derived manures are applied to non-organic crop land. In the non-organic case the fertility in manure displaces the need for Ammonium Nitrate (AN) as N, Triple Super Phosphate as P, K fertiliser as K. In the organic case we assume that the equivalents are sacrificial legume N, Rock P from 25% Tunisian phosphate, Rock K as K. Sacrificial legume N was modelled as a sacrificial winter bean crop, expressed per kg of nitrogen fixed, which is assumed to be 40 kg N/ t. 2.10.6 Allocation of burdens in animal production The focus of the meat production enterprises is prime meat, but meat also arises from culling breeding stock (ewes for mutton, sows, boars, dairy and beef cows, retired laying hens and broiler breeders). The quality of these meats is generally considered lower, but it is used in some catering and processed foods, which is reflected in lower prices, typically less than 25% of the value of prime meat. The basis of allocation is weight adjusted for the lower economic value. If the total meat production from a system consists of p kg prime meat with value Ј/kg and c kg culled meat with value Ј/kg, then the weight adjusted meat output (w) is: w p c This reduces the potential production of the prime meat by less than 5% in most cases. The interaction between milk and beef is a complex one. The primary purpose of pregnancy in dairying is to initiate lactation and the secondary one is to provide female herd replacements. A consequence is the production of surplus calves that are often, but not Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 52 of 97
always, taken into the beef industry. The bull used will be either a dairy or a beef bull and modern selection methods can increase the probability of a male or female calf. Purebred male dairy x dairy calves (e.g. Friesian-Holsteins) are often killed just after birth, but the majority of crossbred (beef x dairy) male (and some female) calves enter the beef sector. The maintenance costs and burdens of lowland suckler cows are avoided when dairy bred calves enter the beef sector. 2.10.7 Organic livestock production Differences between organic and non-organic animal production are much more apparent between dairying systems and poultry meat production, than production systems that are more extensive such as upland sheep and beef. All monogastric organic production is free range, and with greater land requirements per head than non-organic free range, while non-organic includes free range and fully housed systems. The non-organic sector uses slurry systems and bedded housing, while bedded is the norm in organic. Until September 2005, up to 20% of feed and bedding to organic could be sourced from the non-organic sector, if organic supplies were too limited, with the bulk being organic. Now, feed and bedding should be all organic, with minor exceptions. These differences are accounted for in our analysis. Soya is used in both organic and non-organic sectors, but is used as whole beans in organic and mainly as meal, after oil extraction, in the non-organic sector. In terms of dietary composition, however, the concentrations of energy and protein are generally similar between the sectors in compounded feeds. Outdoor organic stock are often associated with arable production. They tend to be rotated more frequently in the organic sector than non-organic, with the aim of minimising nitrogen N losses and maximising nitrogen use. This applies notably for pig and poultry production. 2.10.8 Summary of animal production data This section summarises the data used in the animal production models. Milk productions is shown in Table 35, pig meat in Table 36, eggs in Table 37, poultry in Table 38, organic sheep in Table 39, non-organic sheep in Table 40, and beef in Table 41 and Table 42. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 53 of 97
Table 35 Dairy production input data values used in the LCA model
Yield Level Cow places Time Calving index, day Productive life, lactations Replacement heifers, head Cow weight, kg Mortalities, % Milk Calf mortality, % Calf weight, kg Female dairy calves Male dairy calves Female dairy X calves Male dairy X calves Maize prop Dairy concentrates, kg DM Grazing, kg DM Grass silage, kg DM Maize silage, kg DM Excreted nitrogen, kg N Energy diesel, MJ Energy electricity, MJ Housing period Grazing period Straw bedding, kg Slurry, kg Slurry N, kg FYM, kg FYM N, kg Ammonia, kg [NH3-N] Methane, kg [CH4] Nitrous oxide, g [N2O-N]
Low Average High Low Average High Low Average High
Milk herd (Organic)
Non-organic autumn Non-organic spring calving
calving
1
1
1
1
1
1
1
1
1
52
52
52
52
52
52
52
52
52
weeks weeks weeks weeks weeks weeks weeks weeks weeks
400 400 400 385 385 385 385 385 385
5.63 4.50 3.75 4.49 3.80 3.09 4.49 3.80 3.09
0.162 0.203 0.243 0.211 0.249 0.307 0.211 0.249 0.307
537 600 657 552 600 666 552 600 666
1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
4000 5000 6000 5500 6500 8000 5500 6500 8000
10
10
10
10
10
10
10
10
10
65.0 65.0 65.0 65.0 65.0 65.0 65.0 65.0 65.0
0.162 0.203 0.243 0.211 0.249 0.307 0.211 0.249 0.307
0.169 0.211 0.253 0.220 0.260 0.320 0.220 0.260 0.320
0.240 0.200 0.159 0.207 0.169 0.111 0.207 0.169 0.111
0.250 0.208 0.166 0.215 0.175 0.116 0.215 0.175 0.116
0
0
0
0 0.200 0.500
0 0.200 0.500
544 911 1312 1377 1527 1673 850 1024 1253
2516 2383 2478 1684 1839 2080 2842 3061 3373
2516 2383 2478 2526 2207 1560 1894 1632 1124
0 552 1560
0 408 1124
63.7 74.0 84.2 76.1 85.9 100 76.1 85.9 100
475 475 475 475 475 475 475 475 475
671 839 1007 923 1091 1343 923 1091 1343
190 190 190 190 190 190 190 190 190
175 175 175 175 175 175 175 175 175
1020 1140 1249 357 388 430 357 388 430
4079 4560 4995 6963 7570 8398 6963 7570 8398
16.6 19.3 21.9 28.7 32.5 38.3 28.7 32.5 38.3
5098 5700 6244 1783 1938 2150 1783 1938 2150
13.8 16.1 18.5 6.4 7.2 8.5 6.4 7.2 8.5
5.63 6.29 6.89 7.03 7.65 8.48 7.03 7.65 8.48
119 126 143 101 119 150 113 132 162
163 182 200 168 182 202 168 182 202
Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 54 of 97
Table 36 Pig production input data values used in the LCA model
Indoor Outdoor weaners weaners
Indoor, Indoor, light medium (pork) (cutter)
Weaners, no Time, week Start liveweight, kg Daily gain, kg Exit liveweight, kg Killing out, % Transport, km Transport, % Mortality, % Feed conversion ratio Concentrates, kg proportion housed -fully slatted proportion housed -part slatted proportion housed -loose housing Built-up area, m2 Land area, m2 Excreta, l/day Pig excreta, t Pig slurry, t Bedding straw, t Pig FYM,t Outdoor pig manure before first winter, t Outdoor pig manure after first winter, t Energy (diesel), kg Energy (electricity), MJ Casualty stock Weaner exiting Finished pigs, kg dwt Ammonia, kg [NH3-N] Methane, kg [CH4] Nitrous oxide g [N2O-N] Productive life, yrs Sow weight Culls - inedible, % Org lactating sow concentrates, kg Org dry sow concentrates, kg Org weaner concentrates, kg Org finisher concentrates, kg Cutters produced Cutter weight, kg Baconers produced Baconer weight, kg Baconer killing out, %
1 7.1 7.2 0.462 30 80 0.2 0.07 1.77 40.4 0.27 0.23 0.5 0.03 0.04 1.5 0.07 0.04 0.05 0.09 8.61 3.85 0.93 0.09 0.17 0.5
1 7.2 7.2 0.455 30 80 0.8 0.03 1.65 37.6 0 0 1 0.04 0.65 0.05 0.06 0.06 0.00 1.71 0.97 0.13 0.02 0.5
1 10.5 30 0.627 76 0.72 0.07 2.74 126.0 0.25 0.25 0.5 0.18 0.24 5 0.37 0.18 0.05 0.23 4.86 3.45 51.16 0.57 0.81 2.0
1 13.0 30 0.627 87 0.75 0.07 2.74 156.2 0.25 0.25 0.5 0.25 0.32 5 0.45 0.23 0.06 0.28 5.14 3.95 60.85 0.78 1.11 2.7
Indoor heavy bacon 1 18.0 30 0.627 109 0.77
Rearing Organic
sow combined
replace-
unit
ments
1 1 sow
18.0
52.0
30
109 0.72
0.07 2.74 216.5 0.25 0.25 0.5 0.38 0.49 5 0.63 0.31 0.08 0.39
0.07 2.74 216.5 0.31 0.40 0.627 0.63 0.19 0.82
5.42
4.86
4.87
0.98
78.05
0.94
1.28
1.24
1.83
2.91
4.5
4.5
0.03 33.3 200 1.25 7.50 6.00 0.00 23.5 7.45 97.3 2.5 150 0.34 700 750 880 2500 12 83 4 94 0.75
Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 55 of 97
Table 37 Egg production input data values used in the LCA model
Eggs, no/layer Life, week Layer feed, kg Mortality Amount of manure deposited indoors, kg head-1year-1 Proportion of manure dropped outdoors Amount of manure deposited outdoors, kg head-1year-1 Proportion in non-mobile housing Proportion of housed layers with deep cages Proportion of housed layers with belt cleaned cages Proportion of pullets on manure based systems Proportion of pullets on litter based systems Housed area, m2 Range area in rotation, m2 Total range area, m2 Methane kg/head Ammonia, kg/head Nitrous oxide, g/head
Free Range Layers 289 55 49.3 0.08 44.4
Organic Free Range Layers 262 55 49.3 0.08 44.4
0.12
0.12
6.1
6.1
0.8
0
0.12
0.12
0.85
4.23
4.23
4.23
0.03
0.03
0.22
0.22
15.1
15.1
Barn Housed Eggs Layers
288
295
55
55
47.8
44.9
0.07
0.05
50.5
50.5
0.753 0.247
0.12
0.18
0.03
0.03
0.25
0.20
15.1
10.8
Pullets Layer Breeders
295
18
52
6.6
44.9
0.03
0.05
16.5
47.8
0.753
0.247
0.5
0.5
0.03
0.18
0.00
0.03
0.04
0.20
2.3
10.2
Table 38 Poultry production input data values used in the LCA model
Breeder
Systems
Time to laying, week
18
Finishing, day
Female finishing age, week
Female finishing weight, kg
Male finishing age, week
Male finishing weight, kg
Rejects, %
Laying, time, week
54
Eggs laid
170
Eggs rejected
20
Hatching rate, %
0.85
Chicks hatched
115
Feed, t/1000 birds
45
Poult feed, t/1000 birds
6.6
Spent broiler breeder, kg
5
Manure, t/1000 birds
42.0
Straw, t/1000 birds
Finished weight, kg
Mortality, %
Methane, g/head
31.6
Ammonia, g/head
203.7
Nitrous oxide, g/head
10.2
Broiler systems Free- Free- range range Organic
Housed
56
82
42
1.5
5.5
8
4.6
3.1
4.5
2.3
1
2
1
2.35
3
2.54
0.05
0.05
0.04
0.7
1.4
0.6
7.1
13.3
5.9
2.2
4.1
1.8
Free range
Turkey systems Free range - Pole-barn Organic housed
Fully housed
20
20
20
8
7.5
7.5
7.5
5
20
20
20
8
13.5
13.5
13.5
5
29
29
29
14
16.1
16.1
16.1
6.8
4
4
4
2
0.05
0.05
0.04
0.04
1.2
1.2
1.2
0.2
11.4
11.4
11.6
2.2
5.5
5.5
5.5
1.0
Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 56 of 97
Table 39 Organic sheep production input data values used in the LCA model
Flock life, year Store lambs, head[30-36kg lwt] Store lambs, head[26-30kg lwt] Sheep concentrates, kg Lamb concentrates, kg Minerals, kg Barley mix, kg Lowland grazing, kg DM/yr Upland grazing, kg DM/yr Hill stocking rate, ha/year Hay, kg DM Energy, diesel, MJ Energy, electricity, MJ Mean weight, kg Transport t.km Implied fecundity Dead ewes Culled ewes, head Culled rams, head Dead stores, head Store lambs, 26-30 kg lwt - in situ Store lambs, 30-36 kg lwt - in situ Store lambs, 26-30 kg lwt Store lambs, 30-36 kg lwt Finished standard lambs (32.1-39 kg) Wool, kg Nitrous oxide, g[N2O-N] Ammonia, kg[NH3-N] Methane, kg[CH4] FYM, kg
Organic production systems
Store
Organic
Organic
Upland
Lamb
Breeding
Organic Finishing
Stock &
Lowland
Short
Lamb
Lamb Keep -in
Production Production
situ
4.5
6
1.03
30
15
10
1.8
1.6
18
18
504
16
522
190
47
175
142
19.5
33
1.13 0.04 0.232 0.008 0.01 0.18 0 0.11 0.55 2.91 12.9 1.33 9.9 150
1.45 0.03 0.172 0.008 0.16 0.09 0.99 3.12 1.3 1.39 10.4 150
0 0.03 1 0.00494 0.0913 0.94
Store Organic Lamb Finishing Long Keep in situ 1.03 24.4 39 59 28 0 0.03 1 0.0124 0.228 2.34
Store Organic Lamb Finishing Short Keep 1.03 10 16 19.5 33 6.8 0 0.03 1 0.00494 0.0913 0.94
Store Organic Lamb Finishing Long Keep 1.03 24.4 39 59 28 5.8 0 0.03 1 0.0124 0.228 2.34
Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 57 of 97
Table 40 Non-organic sheep production input data values used in the LCA model
Hill pure bred flocks, option 1
Non-organic production systems
Lowland
Lowland Lowland broken
Hill pure Upland Upland
spring
early mouthed
bred pure bred pure bred Upland Lowland
lamb
lamb
ewes
flocks, flocks, flocks, halfbred pure bred Gimmer- productio productio productio
option 2 option 1 option 2 flocks flocks
ing
n
n
n
Store
lamb Store
finishing
lamb
short finishing
keep -in long keep
situ -in situ
Store
lamb Store
finishing
lamb
short finishing
keep long keep
Flock life, years
4
4
4.2
4.2
4.2
4.5
1
4.5
4.5
1
1
1
1
1
Rams
0.0083
0.0083 0.0083
Draft hill ewes
0.26
Cross breed ewe lambs
1.03
Broken mouthed ewes with lambs
1
Store lambs, head[30-36 kg lwt]
1.03
1.03
Store lambs, head[26-30 kg lwt]
1.03
1.03
Gimmers
0.28
0.28
Sheep concentrates, kg
30
30
50
50
50
53
53
53
53
Lamb concentrates, kg
12
12
97
12
12
18
12
18
Minerals, kg
Barley mix, kg
14
Lowland grazing, kg DM/yr
504
457
504
502
282
16
39
16
39
Upland grazing, kg DM/yr
541
541
541
Hill grazing, kg DM/yr
457
457
Hay/ big bale silage, kg DM
48
48
48
190
190
190
Energy, diesel, MJ
113
113
73
73
73
59
59
59
59
30
20
59
120
59
Energy, electricity, MJ
Mean weight
80
40
80
80
90
33
28
33
28
Transport t.km
2.1
4.1
2.3
2.3
9.0
3.4
2.9
Outputs
Implied fecundity Draft hill ewes 3-5 years old, head
0.998 0.998 1.383 1.373 1.375
1.49
0.2
0.2
1.51
1.46
1.45
0
0
0
0
Upland ram lambs, head
0.34
0
Crossed ewe lambs, head
0.69
Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture
Page 58 of 97
Terminal sires, head Gimmers, head Broken mouthed ewes Barren ewes Dead ewes Culled ewes, head Culled rams, head Dead stores, head Store lambs, 26-30 kg lwt -in situ Store lambs, 30-36 kg lwt -in situ Store lambs, 26-30 kg lwt Store lambs, 30-36 kg lwt Finished light lambs (25.5-32 kg lwt) Finished standard lambs (32.1-39 kg) Finished medium lambs (39.145.5 kg) Upland ewe lambs Wool, kg N2O, g[N] NH3, kg[N] CH4, kg FYM, kg
Hill pure bred flocks, option 1
Non-organic production systems
Lowland
Lowland Lowland broken
Hill pure Upland Upland
spring
early mouthed
bred pure bred pure bred Upland Lowland
lamb
lamb
ewes
flocks, flocks, flocks, halfbred pure bred Gimmer- productio productio productio
option 2 option 1 option 2 flocks flocks
ing
n
n
n
0.371
1 0.200 0.200 0.200
0.05
0.05
0.04
0.04
0.04
0.05
0.05
0.05
0.05
0.05
0.02
0.02
0.02
0.02
0.03
0.02
0.02
0.02
0.152
0.210 0.210
0.98
0.008 0.008 0.008 0.008 0.0083 0.008
0.0083 0.0083
0.06 0.260 0.05 0.21 0.11
0.0100 0.240 0.01 0.13 0.58 0.11 0.385
0.010 0.340 0.01 0.19 0.555
0.010 0.210 0 0.12 0.345
0.010 0.190 0 0.11 0.58
0.010
0
0
0.320 0.150
0.18
0.01
0
0
0.19
0.05
0.11
0.98
1.26
1.16
2.08 17.1 0.274 9.63
2.08 17.1 0.274 9.63
0.5 2.91 15.8 0.43 10.24 150
0.5 2.91 15.8 0.43 10.24 150
2.91 15.8 0.43 10.24 150
3.12 13.0 1.39 10.43 150
0.03 0.548 5.61
3.12 13.0 1.39 10.43 150
3.12 13.0 1.39 10.43 500
3.12 13.0 1.39 10.43
Store
lamb Store
finishing
lamb
short finishing
keep -in long keep
situ -in situ
Store
lamb Store
finishing
lamb
short finishing
keep long keep
0.03
0.03
0.03
0.03
1
1
1
1
0.0049 0.0913 0.94
0.0124 0.228 2.34
0.00494 0.0913 0.94
0.0124 0.228 2.34
Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture
Page 59 of 97
Table 41 Beef production input data values used in the LCA model (Part I)
Mortality, % Calf mortality, % Killing out, % Calves born/head/yr Productive life, year Weeks Mean transport distance, km Lowland grazing kg DM Upland grazing, kg DM Hill grazing, kg DM Calf liveweight Entrance liveweight, kg/ head Exit liveweight, kg /head Slaughter liveweight, kg/head Milk replacer, kg Whole milk, l Calf concentrates, kg Finishing concentrates, kg Cow concentrates, kg Rearing concentrates, kg Barley ration, kg Hay, kg Silage, kg DM Proportion cubicle housed Proportion loose housed Days housed FYM, kg Straw, kg Livestock units, LU Diesel, MJ Ammonia, kg N Nitrous oxide, kg N Methane, kg
18-20 Month beef 0.03 0.551 82.8 100 1680
22-24 Cereal
Month
Beef
Silage beef
beef (continent (dairy &
al X dairy continent
bulls), 12-
al X
13 months bulls), 16-
17 months
0.03
0.026
0.026
Lowland suckler herds autumn calving 0.02
Lowland suckler herds spring calving 0.02
Upland suckler herds autumn calving 0.03
0.551
0.543
0.543
100.2
54.5
71.9
100
100
100
3500
0.92 7.5 52.0 100 3920
0.91 8 52.0 100 3710
0.93 7 52.0 3234
45 515 15 160 800 30 1600 0.18 0.82 182 3200 640 0.585 377 3.83 0.19 56.96
45 565 15 160 950 30 0 0.18 0.82 365 3600 720 0.585 457 7.67 0.23 68.93
45 540 15 160 2100 90 0 0.18 0.82 382 2800 560 0.585 248 8.02 0.13 37.49
45 535 15 160 1050 30 1600 0.18 0.82 503 3200 640 0.585 328 10.58 0.17 49.46
365 155 200 690 884 0.18 0.82 182 3000 600 1.5 237 9.81 0.31 91.73
278 85 150 690 884 0.18 0.82 182 2200 440 1.33 237 8.70 0.28 81.33
335 200 200 80 1500 0.18 0.82 182 2800 560 1.5 237 9.81 0.31 91.73
Upland suckler herdsspring calving 0.03 0.93 6.5 52.0 2982 278 100 140 80 1500 0.18 0.82 182 2400 480 1.33 237 8.70 0.28 81.33
Hill suckler herds 0.02 0.91 5.6 52.0 3234 264 77 212 90 1257.5 0.18 0.82 0 1.33 237 0.00 0.28 81.33
Winter feeding spring- born suckled calves 0.015
Grass finishing springborn suckler stores 0.007
Winter Finished Suckled Calves 0.003
Cereal Beef spring born calves (Suckler bulls) 0.026
Silage Beef (suckler bulls and steers) 0.026
0.551
0.55
0.543
0.543
25.7
47.3
26.4
52.0
61.6
100
100
100
100
100
1610
275
380
365
280
280
385
530
560
530
520
295 875 0.18 0.82 182 2800 560 0.6 117 3.92 0.06 18.14
47 0 0.83 216 0.00 0.16 46.15
495 850 0.18 0.82 185 2400 480 0.86 120 5.72 0.09 26.73
1300 90 0 0.18 0.82 364 2800 560 0.74 237 9.68 0.15 45.25
800 1050 0.18 0.82 431 3200 640 0.74 281 11.46 0.18 53.58
Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture
Page 60 of 97
Table 42 Beef production input data values used in the LCA model (Part II)
Mortality, % Calf mortality, % Killing out, % Calves born, head/yr Productive life, year Duration, week Mean transport distance, km Lowland grazing kg DM Upland grazing, kg DM Hill grazing, kg DM Calf liveweight Entrance liveweight, kg/head Exit liveweight, kg/head Slaughter liveweight, kg/head Whole milk, l Calf concentrates, kg Concentrates, kg Cow concentrates, kg Rearing concentrates, kg Hay, kg Silage, kg DM Proportion cubicle housed Proportion loose housed Days housed FYM, kg Straw, kg LU (Cow and Calf) Diesel, MJ Ammonia, kg N Nitrous oxide, kg Methane, kg
Dairyherd bred calves 18-20 month grass finishing 0.03 0.55 83 200 3168
Organic lowland sucklerfinishing herds - spring calving 0.02 0.07 0.54 0.91 7.0 52 4312
45 515 320 130 700 30 0 1 182 3400 680 0.585 375 4.07 0.19 56.96
490 90 150 350 150 220 0 1 182 4400 880 1.25 474 8.69 0.26 76.44
Organic upland suckler herdsspring calving 0.03 0.07 0.93 6.5 52 3360 280 200 150 220 0 1 182 2400 480 1.33 474 9.25 0.28 81.33
Organic hill suckler herdsspring calving 0.02 0.91 5.6 52 3360 264 77 1258 212 90 0 1 0 1.33 237 0.00 0.28 81.33
Grass finished spring- born suckler stores 0.03
Silage beef spring born calves (suckler bulls and steers 0.03
0.54
0.54
47 2310
62 4620
280
280
530
520
250
350
50 600 0 1 182 0 0.75 216 5.21 0.14 41.71
100 950 0 1 431 0 0.74 281 12.18 0.18 53.58
2.11 Implementation of the LCA model The relationships and data were put into Excel workbooks of three generic types. Arable crops were put into standard templates for non-organic and organic systems, with values set to zero where not required, and a home page for each crop. Common data worksheets were used wherever possible. The tomato worksheet stands alone, except for accessing common data worksheets. The commodity sheets can be interrogated using the normal Excel interface as well as through macros that allow some scenarios to be investigated. The animal worksheets each have the same philosophy, but are tailored to the specifics of the sector. A common worksheet allows for quick selection of commodities and initiates the tool that solves the simultaneous equations that define the animal production systems. These underlying sheets allow detailed examinations to be made. In addition, a graphical interface was written in Visual Basic (VB) to allow rapid and easy interrogation of the model. Interfacing VB and Excel has presented many technical challenges and final development was postponed in favour of enhancing the underlying spreadsheets. The graphical interface (Figure 4) allows users to select values that define different production systems using a set of sliders. The default set of values are the ones that Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 61 of 97
we believe best represent current practices and proportions of production systems and methods. Users can thus quickly compare current and notional future practices. The model is interactive, so that changes to livestock systems, such as reducing the proportion of sheep on the hills, cause the structure of the production network to be automatically recalculated. In addition, crops can be influenced from the animal screens, for example changing the nitrogen application rate for wheat. All the commodities include the proportion of organic production. Typical options for field crops also include the proportions of tillage types (plough, reduced, direct drilling), N fertiliser application rate and soil texture distribution. For tomatoes, choices include the mixture of products (classic, specialist, loose, vine), production system and the amount of CHP used. For animal production, options include housing types, intensity of nutrition (for dairying), generic location for sheep production. Figure 4 Example of screen for users to change components of production systems Figure 5 shows an example of the input/output section of the bread wheat spreadsheet. Cells with blue text and a yellow background are for inputting values, green text is descriptive and black text shows calculated results, with the main LCI values at the bottom. Apart from those shown on this screenshot, the LCI dataset includes about 50 values (e.g. water use, N2O, GWP over 20 and 500 years) allowing for more detailed scrutiny. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 62 of 97
Main annual cultivation methods for Bread WPlhoeuagth based Reduced tillage Direct drilling Fertilisation and yield potential Mineral fertilisation assumed at std av. rate oPfroportion of N applied as urea Increase in yield of varieties Increase in protein content of varieties
Proportions u60se%d 35% 5% 208 11% 0.0% 0.0%
Harvested Outputs and properties Gross Grain yield (86% dry matter), t/ha Protein content of grain (Dry Basis), % Yield of bread wheat allowing for grain of uSntsruaiwtaybileeldq,uta/hliaty, t/ha Proportion incorporated (rest is baled)
7.72 13.6% 7.1 4.0 50%
Environmental burdens from the production oCf onventional system Summarised values per t Energy used, MJ Global Warming Pot'l, kg 100 year CO2 Equutriovp. hication Pot'l, kg PO43- Equiv. Acidification Pot'l, kg SO2 Equiv. Pesticides used, dose ha Abiotic depletion, kg Antimony Equiv. Land used Grade 2 Grade 3a Grade 3b Grade 4 N losses in detail NO3--N N2O-N NH3-N N2-N
Bread Wheat 2,646 420 3.0 2.8 1.4 15.8 0.12 0.14 0.15 0.16 kg t-1 4.4 0.7 0.7 4.8
Figure 5 Example of screen showing main input and output cells of the spreadsheet
Figure 6 to Figure 8 to are examples from the animal spreadsheet, showing the table allowing scenarios of pig production to be directly changed (all the others are similar), the table for changing the scenarios for the feed crops and the table of results. Note that this latter table actually has a large number of columns listing all the major environmental emissions.
Livestock Commodities
Default Altenative
Description
Minimum Maximum Value Value
Pig meat Breeding herd outdoors, %
1%
100%
80%
80%
Weaner herd outdoors, %
1%
100%
25%
25%
Pigmeat market as light, %
1%
100%
75%
75%
Pigmeat market as medium, %
1%
100%
20%
20%
Pigmeat market as organic, %
1%
100%
1%
1%
Figure 6 Screeenshot showing the input cells for changing scenarios to analyse pig systems
Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 63 of 97
Feed Crops
All
Description
Proportion of national area producing conventionally
Proportion of conventional using plough based tillage
Proportion of conventional using ploughless tillage (but not direct drilling)
Variation from average mineral N application rate
% N as Urea N
% Urea as liquid
Yield increase by technology (conv), %
Yield increase by technology (org), %
Protein conc increase of grain (conv), %
Protein conc increase of grain (org), %
Straw incorporated for conventional (rest baled)
Straw incorporated for organic (rest baled)
Affects energy of grain drying
Clay soil affects yields
Compost use (Organic), t/ha
Value Value
99%
99%
49%
49%
45%
45%
134.4 13% 0% 0% 0% 0% 0%
134.4 13% 0% 0% 0% 0% 0%
70% 58% 86% 31% 1.00
70% 58% 86% 31% 1.00
Figure 7 Screenshot showing the input cells for changing scenarios to analyse feed crops
Commodity Reference Unit
Primary energy used, MJ
Greenhouse gases, kg CO2 eqv. GWP (500 year)
Eutrophication potential, kg PO43- eqv.
Acidification potential, kg SO2 eqv.
Pesticides used, Dose ha
Abiotic resource use, kg Sb eqv.
Pig meat
1000 kg dwt 16,680
4,133
100
394
8.8
34.5
Poultry meat
1000 kg dwt 11,998
3,144
49
173.4
7.7
29.7
Beef
1000 kg dwt 27,681
8,145
158
471
7.1
36.2
Sheep meat
1000 kg dwt 23,083
8,003
200
382
3.0
27.2
Milk
10000 l 25,104
5,645
64
163.0
3.5
27.6
Eggs
20000 no 14,110
3,871
77
306.0
7.7
38.2
Figure 8 Screenshot showing the first six columns of burdens from the results table for all animal commodities
Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 64 of 97
3 Results
3.1 Arable Table 43 lists the basic burdens for each crop commodity as produced by present production systems. Note that each commodity stands alone. Caution is needed in comparing commodities as their nutritional, cultural and commercial properties differ. Rape incurs more burdens that wheat, but contains more protein and much more energy. Potatoes contain about 80% water (compared with wheat at 14%) and their storage is much more demanding. The main purpose of the analysis is to provide a mechanism by which the different methods of producing any one of the commodities might be compared.
The results combine the appropriate proportions of current non-organic and organic farming and different current cultivation systems. Note that the functional unit is tonnes of production, rather than tonnes of dry matter or MJ of energy produced.
Table 43 Main burdens of production of each crop commodity (per t)
Impacts & resources used Primary energy used, MJ GWP100, kg 100 year CO2 equiv. Eutrophication Potential (EP), kg PO43- equiv. Acidification Potential (AP), kg SO2 equiv. Pesticides used, dose ha ARU, kg antimony equiv. Land use, ha (One of the following) Grade 2, ha Grade 3a, ha Grade 3b, ha Grade 4, ha N losses NO3-N, kg NH3-N, kg N2O-N, kg N2-N, kg Irrigation water, m3
Bread wheat 2,460 804 3.1 3.2 2.0 1.5
Oilseed Rape
Potatoes
5,390
1,390
1,710
235
8.4
1.3
9.2
2.2
4.5
0.6
2.9
0.9
0.13
0.27
0.024
0.14
0.31
0.028
0.15
0.33
0.030
0.16
0.35
0.031
4.4
12.2
1.6
1.4
3.0
0.3
1.0
3.2
0.9
7.0
27.2
1.2
21
3.1.1 Bread wheat The contrast between non-organic and organic arable crop production is well illustrated by bread wheat in Table 44. The main differences are that non-organic production uses about 50% more energy than organic, while using only a third of the land area. Although emissions per ha are sometimes lower from organic than non-organic, because yields are about halved and nitrogen building crops are needed prior to the organic wheat crop, burdens are in many cases little changed and in the case of nitrate leaching and eutrophication actually increased. A breakdown of the use of primary energy shows that, after fertiliser production, cultivations and harvesting are the main energy consumers. Fertiliser manufacture dominates in nonorganic production. In organic production, field work dominates. Operations represents about a quarter of the total energy input to non-organic wheat, with the energy use for manufacturing the equipment making up about one third of that energy input. Cultivations represent about half of the fuel use. A typical breakdown of the energy used in operations (Figure 9) shows how crop establishment dominates when using plough-based or reduced tillage. The current mean of cultivations methods for non-organic bread wheat is also shown, together with associated spraying activity (not the spray manufacturing itself). More spraying Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 65 of 97
is used with reduced tillage and with direct drilling than with plough based tillage, although fertilisation remains the same. The energy used for manufacturing the equipment ranges from 26% for reduced tillage to 42% for harvesting.
Table 44 Burdens of producing bread wheat non- organically and organically (per t produced)
Impacts & resources used
Non-organic
Primary Energy used, MJ
2,460
GWP100, kg 100 year CO2 equiv.
804
Eutrophication Potential (EP), kg PO43- equiv.
3.1
Acidification Potential (AP), kg SO2 equiv.
3.2
Pesticides used, dose
2.0
ARU, kg antimony equiv.
1.5
Land use grade 3a ha
0.14
N losses
NO3--N kg
4.3
NH3-N kg
1.4
N2O-N kg
1.0
N2-N kg
7.0
Primary Energy Usage Proportions
Field work: Cultivation
19%
Field work: Spraying
3%
Field work: Fertiliser Application
3%
Field work: Harvesting
8%
Crop storage & drying or cooling
5%
Pesticide manufacture
8%
Fertiliser manufacture
53%
Contributors to GWP100
CO2
18%
CH4
1%
N2O (direct)
75%
N2O (via nitrate)Figure . Field energy for growing bread wheat conventionally 6%
Organic 1,740 786 9.3 3.4 0.0 1.3 0.44 18.3 1.5 0.9 12.4 60% 0% 3% 21% 8% 0% 9% 14% -1% 60% 27%
Plough Red. Till Direct D Mean cults Spraying (plough) Spray (Red. Till) Spray (Dir D) Fert. Apps. Mean chem. apps Harvesting 0
Field Diesel Manu'g
1000
2000
3000
Primary Energy, MJ/ha
4000
Figure 9 Typical breakdown of energy use in arable field operations In this example, field work at 6,100 MJ/ha represents 35% of total energy used (17,700 MJ/ha). The remainder comprises crop cooling, storage and drying (5%), pesticide manufacture (8%) and the dominating term of fertiliser manufacture at 52%. The field energy expended in all combinable crops is generally similar, although energy for fertiliser manufacture clearly changes between crops, with beans having the lowest requirement as no Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 66 of 97
N is applied. Buildings contribute little to the overall production burdens. In animal production, the energy flow that is embedded in the feed greatly outweighs that of the building itself. In contrast, grain storage occupies a relatively large area and once filled, the store cannot be readily used for another purpose, so these burdens are relatively higher, but are still small compared with production itself.
However primary energy is only a minor contributor to global warming as in arable agriculture the main contributor is the N2O-N emissions which are 80% of the cause because they are 400 times more potent than CO2. Nitrous oxide is emitted as a by-product of the nitrogen cycle in the soil as nitrogen is transformed between organic matter, ammonia and nitrate. The standard IPCC estimate is 1.25% of the N fertility and thus as much is generated per tonne by organic as non-organic.
Scenarios Table 45 shows the use of the model to investigate the impact of some scenarios of bread wheat production. Since non-organic represents 99% of the production, any effects on organic production are masked.
Currently 20% of the fertiliser applied to bread wheat is urea. If this is increased to 100%, the primary energy use is increased due to losses of ammonia which also increase acidification potential.
If energy input to cultivations is reduced by changing from about 50% ploughing and reduced cultivations to 50% reduced cultivation and 50% direct drilling, there is only a small reduction in primary energy use.
If the fertiliser input is reduced to 75% of its current level, this has the effect of reducing both yield and protein content so that more land is required to produce the bread wheat and all burdens are increased.
If the crop is grown on mainly the heaviest soils, this has the effect of reducing all burdens, which is largely a reflection of the increased yields.
If plant breeding provided varieties with 1% higher protein, there is no direct environmental benefit since a corresponding additional N input is required per tonne. However a greater proportion of the UK wheat could then be used, replacing the need for imports.
If breeding provides varieties with 20% higher yield and the same protein content, there is a significant reduction in all burdens, even though there is a 20% increase in nitrogen fertiliser used. Note that in breeding terms, there is a negative correlation between increased yield and increased protein.
Table 45 Effects of some scenarios on the burdens of bread wheat production (per t)
Impacts & resources used
Original All urea Reduced 75% 90% +1% +20%
cults Nfert clay protein yield
Primary Energy used, MJ
2,460 2,570 2,330 2,670 2,350 2,550 2,230
GWP100, kg 100 year CO2 equiv. EP, kg PO43- equiv. AP, kg SO2 equiv. Pesticides used, dose ha
804 711 808 872 743 843 735
3.1
4.0
3.2
4.0
2.7
3.2
2.6
3.2
9.2
3.1
3.5
3.0
3.4
2.9
2.0
2.0
2.3
2.1
1.8
2.0
1.6
ARU, kg antimony equiv.
1.5
1.4
1.4
1.6
1.4
1.5
1.4
Land use grade 3a ha
0.143 0.146 0.146 0.159 0.147 0.142 0.119
N losses NO3--N kg N2O-N kg NH3-N kg
4.4
3.9
4.5
6.1
3.7
4.6
3.5
1.4
1.2
1.4
1.5
1.3
1.5
1.3
1.0
3.6
1.0
1.1
0.9
1.1
0.9
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Page 67 of 97
N2-N kg
7.0
6.1
7.2
9.6
6.6
7.3
5.6
3.1.2 Oilseed rape Table 46 shows a breakdown of the comparison between organic and non-organic production systems. The results show the same effects as wheat. In absolute terms the values are higher than wheat due to the lower yield in tonnes of a higher energy crop.
Table 46 Burdens of producing oilseed rape non- organically and organically (per t)
Impacts & resources used Primary Energy used, MJ GWP100, kg 100 year CO2 equiv. EP, kg PO43- equiv. AP, kg SO2 equiv. Pesticides used, dose ha ARU, kg antimony equiv. Land use grade 3a ha N losses NO3--N kg NH3-N kg N2O-N kg N2-N kg Primary Energy usage proportions Field work: Cultivation Field work: Spraying Field work: Fertiliser application Field work: Harvesting Crop storage & drying or cooling Pesticide manufacture Fertiliser manufacture Contributors to GWP100 CO2 CH4 N2O (direct) N2O (via nitrate)
Non-organic 5,390 1,710 8.4 9.2 4.5 3.3 0.309
Organic 4,020 1,620 14.8 5.7 0.0 2.9 0.845
12.2
28.5
3.0
3.0
3.2
1.2
27.2
18.6
20%
53%
7%
0%
3%
2%
7%
17%
3%
4%
8%
0%
52%
23%
16%
19%
-1%
1%
64%
72%
21%
8%
3.1.3 Potatoes Table 47 shows a breakdown of the comparison between organic and non-organic potato production systems. In contrast to oilseed rape, potato yields are very high, being 80% water, and thus burdens per tonne are much lower. One might expect burdens to be a factor of about 10 less than those of oilseed rape therefore those that are, are do not require further explanation. The main difference is seen in crop storage. A large component is for cooling the potatoes through to May (a typical storage period). As it is a fresh crop rather than a dry crop, storage requires cooling and refrigeration and this is a considerable energy burden amounting to 50% of the total primary energy input. This is illustrated in Table 48 as the difference between second early and maincrop potatoes, which have a similar yield but second earlies are not stored. This has to be compared with the early crop which is of course also not stored and has burdens about twice that of the later crop. Although irrigation is lower per hectare, per tonne it is a similar level. Early potatoes have particularly high on nitrate leaching because they are fertilised at a similar level, with reduced yield, therefore leaving a greater residue of nitrogen in the soil. As the crop is harvested in June/July, there is the opportunity to make use of this fertiliser with a following crop, but we have not included this.
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Table 47 Burdens of producing potatoes produced non-organically and organically (per t)
Impacts & resources used Primary Energy used, MJ GWP100, kg 100 year CO2 equiv. EP, kg PO43- equiv. AP, kg SO2 equiv. Pesticides used, dose ha ARU, kg antimony equiv. Land use grade 3a ha N losses NO3--N kg NH3-N kg N2O-N kg N2-N kg Irrigation water, m3 Primary Energy Usage Proportions Field diesel Machinery manufacture Crop storage & drying or cooling Pesticide manufacture Fertiliser manufacture Contributors to GWP100 CO2 CH4 N2O (direct) N2O (via nitrate)
Non-organic 1,260 215 1.1 1.9 0.5 0.9 0.022
Organic 1,280 199 1.2 0.8 0.1 1.1 0.058
1.39
2.04
0.30
0.27
0.70
0.06
0.98
0.88
17.4
3.9
28% 8% 36% 3.9% 24%
35% 13% 40% 0.8% 11%
45%
49%
2%
1%
48%
42%
4%
7%
Table 48 Comparison of the burdens of producing early, second early and maincrop potatoes (per t)
Impacts & resources used Primary Energy used, MJ GWP100, kg 100 year CO2 equiv. EP, kg PO43- equiv. AP, kg SO2 equiv. Pesticides used, dose ha ARU, kg antimony equiv. Land use grade 3a ha N losses NO3--N kg NH3-N kg N2O-N kg N2-N kg Irrigation water, m3 Primary Energy Usage Proportions Field work Crop storage & drying or cooling Pesticide manufacture Fertiliser manufacture
Maincrop 1,510 208 0.8 2.0 0.5 1.1 0.022 0.7 0.3 0.8 0.7 16.6 28% 49% 4% 19%
Second earlies 775 178 1.0 2.1 0.6 0.4 0.025 0.9 0.3 0.9 0.8 14.4 61% 0% 8% 31%
Earlies 1,220 318 2.6 2.8 0.7 0.6 0.043 3.9 0.5 1.1 2.5 17.7 61% 0% 6% 33%
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Table 49 shows the effects of the use of irrigation on maincrop potato production. The main burden of energy use is barely affected, while land use and other burdens fall as yields increase. Note that the model takes into account the fact that the fertiliser requirement changes due to the changed yield with irrigation, so per tonne of production there is little change in fertiliser use.
Table 49 Effects of irrigation on potato production (per t). The current value for non-organic production is 50%
Impacts & resources used Primary energy used, MJ GWP100, kg 100 year CO2 equiv. EP, kg PO43- equiv. AP, kg SO2 equiv. Pesticides used, dose ha ARU, kg antimony equiv. Land use grade 3a ha N losses NO3-N, kg NH3-N, kg N2O-N, kg N2-N, kg Irrigation water, m3
Irrigation at 0% of total area 1,480 211 0.9 2.2 0.6 1.1 0.025
Irrigation at 100% of total area 1,540 206 0.8 2.0 0.5 1.1 0.020
0.8
0.7
0.3
0.3
0.9
0.7
0.7
0.6
0
27.0
3.1.4 Feed crops, including imported crops Table 50 lists the same burdens for the feed crops that are used by the livestock models in calculating the burdens of meat production. It is notable that the two highest users of primary energy are the protein crops which fix their own nitrogen. Because they have a high protein content, they also have low yields and therefore the field work energy becomes more important per tonne. Some major feeds are produced by extensive processing after the actual crop production. Five were modelled, of which only wheatfeed was grown organically (Table 51) There is a notable contrast between soya, which has its protein content increased by a relatively intensive process that also produces a high value product (oil), and wheatfeed where the feed is a cheap by-product of a relative low input process. Transport and processing burdens for soya are about the same, while wheatfeed milling incurs about 9 times the burdens of transport.
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Table 50 Main environmental burdens of production of each feed crop (per t)
Impacts & resources used Primary Energy used, MJ GWP100, kg 100 year CO2 equiv. EP, kg PO43- equiv. AP, kg SO2 equiv. Pesticides used, dose ha ARU, kg antimony equiv. Land use grade 3a ha N losses NO3-N, kg NH3-N, kg N2O-N, kg N2-N, kg Primary Energy Usage Proportions Field work: Cultivation Field work: Spraying Field work: Fertiliser application Field work: Harvesting Crop storage & drying or cooling Pesticide manufacture Fertiliser manufacture Contributors to GWP100 CO2 CH4 N2O (direct) N2O (via nitrate)
Feed Winter Spring Field Soya Grain Forage wheat barley barley beans beans maize maize 2,260 2,410 2,380 2,470 3,010 1,970 1,880 731 726 710 1,010 1,300 650 577 3.0 2.5 2.3 5.9 7.3 2.8 1.6 2.8 2.9 2.3 4.8 6.4 1.6 1.8 1.9 2.2 1.4 2.9 4.4 0.4 0.2 1.4 1.4 1.5 1.4 1.7 1.3 1.5 0.130 0.160 0.182 0.303 0.422 0.141 0.090 4.4 2.9 2.5 8.4 9.8 4.3 1.9 1.3 1.2 1.2 1.9 2.4 1.1 1.0 0.9 0.8 0.5 1.4 1.9 0.4 0.4 6.9 5.6 2.9 11.5 14.0 4.3 1.9 20% 21% 22% 45% 39% 22% 18% 4% 4% 4% 8% 10% 6% 4% 3% 3% 3% 6% 7% 3% 2% 9% 10% 11% 17% 17% 11% 9% 6% 6% 12% 6% 5% 1% 2% 8% 9% 6% 12% 15% 8% 4% 51% 47% 41% 6% 6% 49% 61% 19% 20% 20% 14% 13% 18% 20% 1% 1% 1% 0% 0% 0% 1% 74% 75% 75% 77% 79% 74% 76% 7% 5% 4% 10% 9% 8% 4%
Table 51 Total burdens of processed animal feeds, including field production, processing, import and delivery transport (per t)
Impacts & resources used Primary Energy used, MJ GWP100, kg 100 year CO2 equiv. EP, kg PO43- equiv. AP, kg SO2 equiv. Pesticides used, dose ha ARU, kg antimony equiv. Land use grade 3a ha N losses NO3-N, kg NH3-N, kg N2O-N, kg N2-N, kg
Wheat- Wheat- Maize Soya Soya Rape feed feed gluten meal meal meal (N-org) (Org) feed (no (with hulls) hulls) 795 576 3790 6630 5990 3450 128 108 338 944 853 550 0.9 1.9 1.1 7.5 6.8 3.9 0.82 0.73 1.2 8.5 7.7 4.6 0.45 0.00 0.15 4.5 4.1 2.1 0.51 0.43 2.3 6.7 6.1 2.1 0.032 0.083 0.055 0.424 0.384 0.144
1.3 3.6 1.7 9.8 8.9 5.7
0.2 0.2 0.1 2.0 1.8 1.5
0.3 0.3 0.4 2.5 2.2 1.4
2
2
2 14 13 13
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3.2 Animal products The animal products (Table 52) tend to show an effect of the different genetic capacities for meat production, with highly selected broilers having a very high feed conversion ratio and daily liveweight gain, together with low breeding overheads. These are in contrast to beef, where a calf also requires a cow to be fed. It should be remembered that the nutritional values of the meats will differ, so that a simple comparison of meat types may be misleading. Cattle and sheep are, of course, produced on land that is unsuitable for producing poultry feed.
Table 52 Main burdens of animal products (from current national balance of systems) per functional unit produced (1 t dead weight, 20,000 eggs, and 10,000 l milk)
Impacts & resources used
Beef
Pig Poultry Sheep Meat Meat Meat
Eggs
Milk
Primary energy used, MJ
27,700 16,700 12,000 23,100 14,100 25,100
GWP100, kg 100 year CO2 equiv. EP, kg PO43- equiv. AP, kg SO2 equiv. Pesticides used, dose ha
15,800 158 471 7.1
6,350 100 394 8.8
4,580 17,400 49 200 173 380 7.7 3.0
5,540 10,600 77 64 306 163 7.7 3.5
ARU, kg antimony equiv.
36 35 30 27 38 28
Land use (Note 1)
Grade 2, ha
0.04 0.00 0.00 0.05 0.00 0.22
Grade 3a, ha
0.79 0.74 0.64 0.49 0.67 0.98
Grade 3b, ha
0.83 0.00 0.00 0.48 0.00 0.00
Grade 4, ha
0.67 0.00 0.00 0.38 0.00 0.00
N losses
NO3-N, kg
149 48 30 287 36 72
NH3-N, kg
119 97 40 106 79 40
N2O-N, kg
11 6.4 6.3 9.0 7.0 7.1
Note 1: Land use for grazing animals comprises a combination of land types from hill to lowland. Land use for
arable feed crops consists of land of one of the types. In the above table, arable land use is taken as all grade 3a.
3.2.1 Beef Table 53 shows that 41% of the energy burden comes from the production of grass and a similar amount comes from the production of various concentrate feeds for beef. Manure represents a negative energy burden as it replaces fertiliser, but the emissions from manure and slurry mean that other burdens are positive.
Table 53: Distribution of burdens of beef production (per t)
Impacts & resources used Primary energy used, MJ GWP100, kg 100 year CO2 equiv. EP, kg PO43- equiv. AP, kg SO2 equiv. Pesticides used, dose ha ARU, kg antimony equiv.
Grass
Concentrates
Manure
41%
50%
-1%
21%
27%
6%
48%
7%
36%
26%
4%
57%
0%
97%
0%
25%
72%
-1%
Other 10% 46% 9% 13% 3% 4%
The scenarios examined in Table 54 show that with beef there is a substantial difference between non-organic and organic production in the energy use, reflecting the difference between organic and non-organic grass. The former is assumed to include substantial amounts of clover, whereas non-organic grassland is assumed to have none due to the use of fertiliser discouraging the growth of clover. This is very much a worst case assumption and it is likely that up to 10% clover is possible versus up to 40% in the organic case. Note however
Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 72 of 97
that all other burdens from organic production increase including land use by 80% and a trebling of nitrate leaching.
Three alternative scenarios are shown. The first considers producing all the calves by suckler cows rather than a proportion being by-products of the dairy industry. This is increasingly likely with developments such as sexed semen. The maintenance costs of lowland suckler cows are saved when dairy bred calves enter the beef sector. This change increases all burdens by 40% to 60%.
The last two scenarios consider the alternatives of beef produced either on the lowlands or not on the lowlands. The results are similar which is a reflection of the poor land classes used in the lowlands for beef production. The model might need to be revised to consider the impacts if better lowland were used.
Table 54 Comparison burdens of production of some alternative beef systems (per t)
Impacts & resources used Primary energy used, MJ GWP100, kg 100 year CO2 equiv. EP, kg PO43- equiv. AP, kg SO2 equiv. Pesticides used, dose ha ARU, kg antimony equiv. Land use, ha N losses NO3--N, kg NH3-N, kg N2O-N, kg
Nonorganic
Organic
27,800 18,100
15,800 18,200
157
326
469
711
7.2
0.0
36
31
2.3
4.21
100% suckler
Lowland
40,700 26,800
25,300 15,600
257
153
708
452
7.3
6.7
51
34
3.85
2.28
Hill & upland 29,700 16,400 169 510 8.0 41 2.41
147
427
269
146
156
119
180
178
114
130
10.9
11.8
15.9
10.7
11.3
3.2.2 Pig meat Table 55 shows the differences between non-organic and organic pig systems. Unlike other commodities, pig meat shows reductions of all burdens from organic production, but uses considerably more land for the production of feed. Three alternative systems are compared. Finishing pigs at a heavier weight shows a slight reduction in burdens, mainly as a result of reducing the overheads of breeding piglets. The breeding herd being indoors or outdoors makes only a small difference to the burdens.
Table 55 Comparison burdens of production of some alternative pig meat systems (per t)
Impacts & resources used Primary energy used, MJ GWP100, kg 100 year CO2 equiv. EP, kg PO43- equiv. AP, kg SO2 equiv.
Nonorganic
Organic
Heavier finishing
Indoor breeding
Outdoor breeding
16,700 14,500 15,500 16,700 16,700
6,360 5,640 6,080 6,420 6,330
100
57
97
119
95
395
129
391
507
362
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Pesticides used, dose ha ARU, kg antimony equiv. Land use, ha N losses NO3--N, kg NH3-N, kg N2O-N, kg
8.8
0.0
8.2
8.6
8.8
35
33
33
40
33
0.74
1.28
0.69
0.73
0.75
48
71
43
40
51
98
40
98
119
91
6.4
6.8
5.9
6.1
6.5
3.2.3 Poultry meat Table 56 shows the difference between organic and non-organic poultry meat production. Unlike pig meat, organic poultry has a higher food conversion ratio and a longer growing period for the heavier chickens that are produced, resulting in a net increase in energy requirement for organic poultry meat production. The scenario of increasing the proportion of free-range chickens (in the non-organic sector) to 100% increases energy use and most burdens by about 20%, but still less than organic.
Table 56 Comparison burdens of production of some alternative poultry meat systems (per t)
Impacts & resources used Primary energy used, MJ GWP100, kg 100 year CO2 equiv. EP, kg PO43- equiv. AP, kg SO2 equiv. Pesticides used, dose ha ARU, kg antimony equiv. Land use, ha N losses NO3--N, kg NH3-N, kg N2O-N, kg
Nonorganic
Free-range Organic (non- organic)
12,000 15,800
14,500
4,570 6,680
5,480
49
86
63
173
264
230
7.7
0.6
8.8
29
99
75
0.64
1.40
0.73
30
75
37
40
60
53
6.3
9.3
7.6
3.2.4 Sheep meat Table 57 shows the reduction in energy use with organic sheep meat production. As with beef, a considerable proportion of this reduction is due to the assumption of a large clover proportion in the grass, whereas, with non-organic production, the worst case assumption is made of no clover. Some of the other burdens, however, do not show a reduction.
One alternative scenario considered is to increase the value of mutton. At present, a ewe is valued at Ј35 and this is used to allocate the burdens between prime lamb meat and mutton. If the value of mutton is increased to Ј100 (the relative value that consumers ascribe to lamb meat and mutton), there is a reduction in burdens of about 15%.
Table 57 Comparison burdens of production of some alternative sheep meat systems (per t)
Impacts & resources used Primary energy used, MJ GWP100, kg 100 year CO2 equiv. EP, kg PO43- equiv. AP, kg SO2 equiv.
Nonorganic
Higher Organic valuation of mutton
23,100 18,400 19,400
17,500 10,100 14,600
195
594
168
368 1,511
321
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Pesticides used, dose ha ARU, kg antimony equiv. Land use, ha N losses NO3--N, kg NH3-N, kg N2O-N, kg
3.0
0.0
2.5
27
19
23
1.38
3.12
1.18
282
700
242
100
618
89
8.9
13.4
7.6
3.2.5 Eggs Table 58 shows that organic egg production needs 14% more energy than non-organic and increases most environmental burdens by 10% to 33% (except pesticides), but the land area needed more than doubles. Comparing non-organic systems, keeping 100% hens caged incurs 15% less energy than 100% free range, with similar differences for most other burdens, although abiotic resource is 10% higher for Caged Birds and land use 25% less.
Table 58 Comparison burdens of production of some alternative egg production systems (per 20,000 eggs)
Impacts & resources used Primary energy used, MJ GWP100, kg 100 year CO2 equiv. EP, kg PO43- equiv. AP, kg SO2 equiv. Pesticides used, dose ha ARU, kg antimony equiv. Land use, ha N losses NO3--N, kg NH3-N, kg N2O-N, kg
Nonorganic 14,100 5,530 77 306 7.8 38 0.66
Organic
100% cage, non- organic
100% free-range, nonorganic
16,100 13,600 15,400
7,000
5,250
6,180
102
75
80
344
300
312
0.1
7.2
8.7
43
39
35
1.48
0.63
0.78
36
78
35
39
79
88
77
81
7.0
9.0
6.6
7.9
3.2.6 Milk Table 59 shows the reduction in energy burdens from organic farming, but all other burdens increase, particularly the doubling of land use with the consequent effect on nitrate leaching. Three alternative scenarios are also shown. In the first scenario, maize silage is increased to represent 50% of the bulk fodder, replacing grass and grass silage. There is a generally small change in burdens. The second scenario considers increasing the milk yield profile of low, medium and high yielders in the national herd from 25:55:20 to 0:40:60. This results in small decreases in most burdens of 2% to 5%, with greater milk producing efficiency being partly offset by less longevity in higher producing cows. Changing from 80% to 20% autumn calving herds (i.e. more summer milk) reduces energy needs and GWP by about 5%, but nitrate leaching and hence eutrophication potential increased by 8% and 3% respectively.
Table 59 Comparison burdens of production of some alternative milk production systems (per 10,000 l milk)
Impacts & resources used Primary energy used, MJ GWP100, kg 100 year CO2 equiv. EP, kg PO43- equiv.
Nonorganic
More 60% Organic fodder as High maize yielders
20% autumn calving
25,200 15,600 23,600 24,200 23,400
10,600 12,300 9,800 10,200 10,300
63
103
61
60
65
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AP, kg SO2 equiv. Pesticides used, dose ha ARU, kg antimony equiv. Land use, ha N losses NO3--N, kg NH3-N, kg N2O-N, kg
162
264
164
159
159
3.5
0.0
2.8
3.4
2.9
28
14
24
27
25
1.19
1.98
1.18
1.14
1.21
71
117
65
65
77
40
63
41
39
39
7.1
7.6
6.3
6.6
6.6
3.3 Tomatoes
3.3.1 Main burdens The main burdens were calculated from producing the current national basket of tomatoes, the conditions of which are summarised in Table 60. An important systematic difference between the organic and non-organic sectors is that the organic sector favours both more specialist varieties and more on-the-vine (across the types). Combined heat and power (CHP) can theoretically be used in any production system and we have assumed an equal distribution of its use throughout.
Tomato production is a high input and high output system, with much higher yields per has than normal arable crops. Overall, however, the use of fuel for extending the season does result in substantially higher burdens per t than for arable crops.
Table 60 Summary of conditions used for producing the current national basket of tomatoes
Item CHP (same for all systems) Organic by mass (v. non-organic) Non-organic as NFT by mass (v. rockwool) Non-organic crop as classic (v. specialist) Non-organic crop as loose(v. on the vine) Organic crop as classic (v. specialist) Organic crop as loose(v. on the vine)
Proportion, % 25 3.6 100 80 80 43 57
Table 61 Burdens of producing 1 t of the current national basket of tomatoes
Impacts & resources used
Primary Energy used, GJ
125
GWP100, kg 100 year CO2 equiv.
9.4
EP, kg PO43- equiv.
1.5
AP, kg SO2 equiv.
12
Pesticides used, dose ha
0.5
ARU, kg antimony equiv.
100
Land used, m2
30
Water, m3
39
3.3.2 Benefits of CHP Unlike field crops, the distribution of energy and GWP burdens are clearly dominated by the main heating and lighting inputs from natural gas and electricity (Table 62). Some values for heating and electricity are greater than 100% as the credits from CHP offset these as negative values. The same general trends apply to most burdens, although fertilisation and direct crop emissions contribute disproportionately highly to eutrophication potential and the greenhouse structure itself to abiotic resource use.
Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 76 of 97
Table 62 Proportions of the main burdens attributable to each aspect of production with CHP, per t weighted production
Item
Primary Energy
GWP100
EP
AP
Abiotic resource use
Heating & electricity
105%
102%
86%
101%
77%
Fertilisation
0.55%
0.85%
9%
6%
0.4%
Chemical crop protection
0.02%
0.02%
0.2%
0.2%
0.1%
Biological crop protection
0.21%
0.20%
0.2%
0.2%
0.2%
Annual materials
1.03%
0.60%
2.0%
2.9%
1.9%
Construction of greenhouse
0.87%
1.03%
4.0%
4.2%
26%
Seedling production
0.3%
0.3%
0.3%
0.3%
0.2%
Waste disposal and compost credits
0.01%
0.01%
0.05%
0.05%
0.02%
Direct crop emissions of N and P
0.00%
0.36%
7.6%
0.1%
0.0%
CHP credit
-7.9%
-5.3%
-9.3%
-15%
-5.7%
Total
100%
100%
100%
100%
100%
With the main burden being from heating and lighting, the potential benefits of CHP were
explored by setting the national proportions to 0 and 100%. The results (Table 63) show that
70% of primary energy consumption could be saved with complete national implementation
of CHP. The effects on other burdens are even more dramatic, with both eutrophication and
acidification potentials becoming negative.
Table 63 Effects of changing the national proportions of CHP on main burdens, with current production systems
Burden
25% (current CHP) 0% CHP
Primary Energy used, GJ
125
111
GWP100, kg 100 year CO2 equiv. EP, kg PO43- equiv. AP, kg SO2 equiv. Pesticides used, dose ha
9.4
8.1
1.5
1.4
12.3
11.8
0.5
0.5
ARU, kg antimony equiv.
99
91
Land used, m2
30
30
Water, m3
39
39
Effect of increasing CHP use in an individual greenhouse for tomato production on
primary energy use and global warming emissions
150,000
15,000
100% CHP 37 6.7 -0.06 -10.4 0.5 48 30 39
Primary energy, MJ GWP, 100 year, kg CO2 Equi
120,000
12,000
90,000
9,000
60,000 30,000
PE GWP
6,000 3,000
0
0
0%
20%
40%
60%
80%
100%
Proportion of CHP
Figure 10 Effect of increasing CHP use in tomato production on primary energy use and global warming emissions, per t tomato production Implementation within a greenhouse presents an interesting picture. The effects are curvilinear with the peak burdens occurring between 20% and 45% CHP (Figure 10 and Figure 11). Burdens increase as more gas is needed for CHP and the benefits of exporting electricity are not reached until a suitable threshold is reached. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 77 of 97
Eutrophication Potential, kg PO4 Equiv Acidif'n Pot. kg SO2 Equiv
Effect of increasing CHP use in an individual tomato production on Eutrophication and Acidification potentials (per t tomatoes produced)
1.4
28
1.2
24
1.0
20
0.8
16
0.6
12
0.4
8
0.2
4
0.0
0
-0.2
Eut Pot, kg PO43- equiv
-4
Acid Pot, kg SO2 Equiv
-0.4
-8
-0.6
-12
0%
20%
40%
60%
80%
100%
Proportion of CHP
Figure 11 Effect of increasing CHP use in tomato production on eutrophication and acidification potentials, per t tomatoes produced
3.3.3 Effects of growing different tomato types Because the inputs to the greenhouse remain very similar, irrespective of the type of tomato grown, the burdens per type of tomato grown depend very much on their yield. This was explored in various scenarios (Table 64). These show that organic production with the current organic mixture of tomato types has nearly twice as high burdens as non-organic production with the current conventional mixture of tomato types. This results from both the lower yields of organic tomatoes (75% of equivalent non-organic types) and the higher proportion of specialist and on-the-vine that are produced organically, which are also intrinsically lower yielding. The relative differences between the two non-organic systems of rockwool and NFT are trivial in comparison. Changing the proportions of tomatoes grown organically to be that of the current non-organic mix, reduces the organic burdens to being about 30% more than non-organic. This is further highlighted by comparing the burdens of producing individual tomato types (Table 64). This shows the burdens increase nearly fivefold (in any production system) moving from loose classic to specialist on-the-vine. These are further increased by going over to organic from non-organic.
Table 64 Burdens of producing different types of tomatoes by different methods
Burden
All organic (current mix)
Primary Energy used, GJ
229
GWP100, kg 100 year CO2 equiv.
17.5
EP, kg PO43- equiv.
5.5
AP, kg SO2 equiv.
34.6
Pesticides used, dose ha
0.3
ARU, kg antimony equiv.
181
Land used, m2
55
Water, m3
49
All nonorganic (current mix) 122 9.14 1.3 11.5 0.5 96 29 38
All NFT (current mix)
All rockwool (current mix)
All organic (current conventional mix)
121
122
159
9.09
9.15
12.2
1.2
1.3
3.8
11.3
11.5
24.1
0.5
0.5
0.2
96
97
126
29
29
39
22
39
34
Table 65 Burdens of producing different types of tomatoes
Classic Classic Specialist Specialist Specialist
loose
on-vine
loose
on-vine on-vine
Non-organic
organic
Primary Energy used, MJ
79
188
159
380
505
GWP100, kg 100 year CO2 equiv.
5.9
14.1
11.9
28.5
38.6
Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture
Page 78 of 97
EP, kg PO43- equiv. AP, kg SO2 equiv. Pesticides used, dose ha ARU, kg antimony equiv. Land used, m2 Water, m3
0.8
1.8
1.6
3.7
12.1
7.3
17.5
14.8
35.4
76.3
0.3
0.7
0.6
1.5
0.6
62
148
125
299
398
19
45
38
92
122
14
34
29
69
107
Of course, organic production does not incur as much pesticide use as non-organic production. The small amount recorded has a physical rather than physiological effect.
Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 79 of 97
4 Discussion
4.1 Arable The results from arable crop production show a general trend for organic production to be less energy demanding per functional unit produced than non-organic. This is mainly due to not using synthetic nitrogen fertiliser, which has a high energy requirement, although this has reduced over the years. The reliance of nitrogen fixing by legumes in organic systems clearly reduces energy demand, but the throughput of nitrogen is limited, so restricting yields and / or protein concentration in crops like wheat. The organic system also has high losses of nitrogen leached as NO3- and volatilised as N2 and N2O. This is partly because the soil has to contain high levels of nitrogen and more than one years leaching occurs per cash crop.
Organic cropping uses the plough as the principal primary cultivation tool for the crops studied. Undersowing is also practiced, but the overall effect of using cover crops and the plough is for the direct energy consumption per ha to be generally higher in organic than nonorganic cropping. With the lower yields of organic production, this field consumption of fuel largely offsets the saving from not using fuel for fertiliser manufacture.
The land use for organic cropping is based on stockless rotations so that all the land used for N fixing was included in the lands requirements for the cash and feed crops. There is some dual use of such land in practice, although if there is too much offtake (for example by grazing animals or conserved forage), then the nutrients available for subsequent arable crops will be reduced. The arable (and animal) systems were analysed using a steady state analysis in which no long term accumulation or depletion of plant nutrients was allowed to occur. Thus all offtake had to be replaced by imports (for P & K) or fixing and import of N. It is quite plausible that many farmers are actually over-or under-supplying nutrients, so that, for example, organic farmers (especially early in conversion) may be depleting soil P and K until new equilibria are established. If our estimates of P & K imports seem high, this may be the reason. The long term steady state analysis does imply that some practices are technically unsustainable.
Wheat was analysed by Audsley et al. (1997) in a pan-European project. They calculated energy consumption for wheat with 12% CP to be 3.3 GJ/t for 8 t/ha non-organic production and 2.8 GJ/t for 4 t/ha organic wheat. We found rather lower values for bread wheat at 2.5 and 1.7 GJ/t, but of a similar magnitude. The Danish food LCA database (http://www.lcafood.dk/) has similar values for some aspects of wheat production, although the main contrast is that they have a much lower GWP and land use from organic wheat production. Our study calculates the burdens per tonne of wheat that reaches the bread quality threshold, which, especially for organic production, gives higher values than burdens per tonne of crop yield (Table 66).
Table 66 Comparison of wheat production burdens between this study and in Denmark
Impact category GWP Acidification Land use, ha
Non-organic
DK This study
710
804
5.3
3.2
0.15
0.14
Organic
DK This study
280
786
4.5
3.4
0.22
0.44
Generally good agreement was also found between potato and rape production in the Danish LCA work and ours (Table 67). The comparison shows second early potatoes because the Danish inventory did not include storage. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 80 of 97
A large amount of energy is used for storing maincrop potatoes, which comes from mainly electricity consumption. While we have endeavoured to represent the industry practice fairly, there is a need for more activity data on contemporary practice.
Table 67 Comparison of potato and rape production burdens between our study and in Denmark
Impact category GWP Acidification Land use, ha
Non-organic potatoes
DK
This study
160
178
1.16
1
0.031
0.025
Non-organic rape
DK This study
1,510
1,710
11.8
9.2
0.35
0.31
Rцver et al. (2000) compared primary energy consumption from non-organic and organic production in Germany (Table 68). Values from this study presented are bread wheat and second early potatoes (no storage required). Agreement between the two studies is good overall. The main difference is that our value for organic rape is substantially higher than theirs, but we acknowledge that our estimates for organic rape yields are based on the relative yields of organic and non-organic wheat. Very little organic rape is, however, grown in Britain.
Table 68 Comparison of primary energy consumption (GJ/t) between arable production in Germany and this study.
Crop Wheat Rape Potatoes
Non-organic
Germany This study
2.4
2.5
6.0
5.4
0.63
0.65
Organic
Germany
This study
1.5
1.7
2.5
4.0
0.58
0.65
There is thus reasonably close agreement between the values from the present study and those conducted elsewhere. It supports confidence in our results, but also has highlighted some differences. Whether these are because of geography and farming methods or simply the assumptions made requires more detailed investigation.
Pig feed production in Brittany (by non-organic methods) was examined in an LCA study by van der Werf et al. (2005). The mean of piglet, sow and finishing feeds were compared (Table 69). All results were generally similar, except GWP, which was almost twice as high in this study than in the Brittany one. Land use was identical.
Table 69 Comparison of pig feed (1 t) production between this study and in Brittany
Primary energy used, GJ GWP100, kg 100 year CO2 equiv. EP, kg PO43- equiv. AP, kg SO2 equiv. Land use (grade 3a in this study), ha
Brittany mean 3.7 0.53 4.4 4.6 0.17
This study mean 3.4 1.1 3.4 4.8 0.17
4.2 Animal products Cederberg (1998) compared organic and non-organic milk production in Sweden on 2 individual farms. Compared with ours (Table 70), Swedish production consumes more energy but creates similar GWP. Other values are all in the same order of magnitude. The lower energy land use in Britain suggests greater efficiency than in Sweden, probably enabled by geographic differences. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 81 of 97
Table 70 Comparison of milk production systems in this study and Sweden (per 1,000 l milk)
Impacts & resources used Primary Energy used, GJ GWP100, t 100 year CO2 equiv. AP, kg SO2 equiv. Land use, ha N losses NO3--N, kg NH3-N, kg N2O-N, kg
Non-organic
Sweden This study
3.6
2.5
1.1
1.1
18
16
0.19
0.12
Organic
Sweden This study
2.5
1.6
0.95
1.2
16
26
0.35
0.20
3.6
7.1
4.9
12
7.0
4.0
6.1
6.3
0.36
0.71
0.30
0.76
Subak (1999) calculated GWP from beef cattle in US feedlots and assuming 55% recovery of liveweight as edible carcass, this equated to 14.5 t CO2 equivalent per t beef. Cederberg (2002) calculated a value of 17 t CO2 equivalent per t beef for animals produced by home feed growing and mixing. Both are similar to our values. It is apparent that the ruminant products produce larger burdens than pig and poultry meat. This partly results from the much higher daily gains and better feed conversion ratios found in the mono-gastrics. It also stems from much greater fecundity of sows and hens, so that breeding overheads are lower. Non-ruminant pigs and poultry effectively live on arable land. Ruminants, however, permit animal production on land that is unsuitable for arable crop production, since they can digest cellulose, albeit with enteric emissions of methane which increase the ratio of GWP / Energy to about 0.3 versus 0.2 for mono-gastrics. Ruminants can also make good use of some arable by-products, such as barley straw as feed and straw as bedding (later returned as manure). This clearly imposes limits on the potential substitution of any animal commodity for another. Also, one should remember the close association of beef to milk production. 4.3 Tomatoes Tomato production is clearly much more energy demanding than other crops. That is the price for obtaining a greatly extended supply of fresh salad food. It is also the exception in this study in that organic production is more energy consuming per tonne owing to the lower yields from similar energy consumption. Although outside the system boundary, there may be significant differences in the fate of tomatoes post-production. The more specialist (and organic) are increasingly expensive in cash terms and there are probably also greater expectations about taste. Consumers are likely to be less wasteful of more expensive varieties, so that the relative burdens of the consumed fruits should be closer than that based on just production alone. There may also be systematic differences in the quantities of fruit types bought directly by end-consumers and the catering industry that could also affect the final burdens of productions and consumption. It would be very interesting to have these effects quantified. Increasing the use of CHP could reduce the burdens. Other possibilities are: Decoupling heat and CO2 supply: Heat and CO2 are currently normally supplied from one source, so that the supply rate tends to be a compromise. If an alternative source of CO2 were available, de-coupling, with more targeted supply rates could be achieved. The best source of CO2 is biogenic, e.g. from the fermentation industries. Using only waste heat without CO2 enrichment: This would provide one method of enhancing growth, with a low environmental (and presumably economic) cost, but would reduce productivity per unit area. Relocation is also implied. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 82 of 97
Reduced heat input: One option is to use heat only in the winter months. It would reduce the heat requirement and productivity and possibly hasten the end of the season. The exact balance could be environmentally favourable or not. It requires careful analysis. Short season cropping: Greatly limiting heat input would return the growing season to the summer months and so make the UK produced tomato supply much more seasonal, but less reliant on fossil fuel. It would be much less productive and increase the seasonality of labour requirement, with generally negative effects on employment and cost. The ultimate environmental effects would depend on the balance of imported alternatives (from where and how produced) as well as any change in consumer preferences. We do not yet have sufficiently detailed data on all aspects of production to be able to analyse all the possible options in great detail. This results from the main sources being commercial data in which some items, like green waste, would not be measured with scientific accuracy and others could be restricted for commercial reasons. Average data on items like fertiliser use and green waste tend to mask actual differences between specific production methods and varieties. For example, a house may contain several types of tomato, each with different nutritional needs. There are other possible outcomes from the use of CHP in that the balance of available heat and CO2 differ from boiler heating. There may be effects on productivity that have not been adequately described. Without sufficiently detailed data, we cannot model all options as closely as could be wished. 4.4 A carbon-nitrogen footprint for agriculture. Unlike most of industry and domestic activity, the GWP from arable cropping is dominated by N2O, not by CO2 from fuel use. N2O contributes about 80% to GWP in wheat production (both organic and non-organic). The N2O contribution falls to about 50% for potatoes as much fossil energy goes into cold storage. A similar pattern occurs with animal production as they live on crops. Another consequence is that the GWP of organic crop production is little lower than from non-organic cropping. In contrast, CO2 from the use of natural gas and electricity in tomato production is the dominant contribution to GWP. The balance of global warming gas emissions and fossil fuel consumption is thus quite different from most industries. Most industries consume energy (most from fossil C-based fuel) and thus emit CO2 as the main gas contributing to global warming. The carbon footprint is thus a reasonable shorthand for both the consumption of C-based resources and the emission of CO2. In agriculture, N2O dominates, with substantial contributions too from methane. Consequently, a carbon footprint inadequately describes agriculture; it has a carbon-nitrogen footprint. Indeed, the nitrogen fluxes in agriculture (and other types of land) also contribute to eutrophication and acidification. Others have noted the dominance of N2O in GWP. Robertson et al. (2000) compared arable cropping systems of wheat, maize and soya in a rotation (and other land management options). They found that the contribution of N2O (by field measurement) to GWP was 45% for plough-based conventional tillage, 46% for direct drilling and 80% for organic. These do not include soil carbon, which was not included in our study. In the present study, N2O contributed to between 75% and 84% of GWP for these crops grown non-organically and 60% to 88% organically. Robertson et al. (2000) did not, however conduct a full LCA, so sources like secondary N2O from leaching were not included and it is unclear if direct N2O emissions from fertiliser manufacturing were included or not, but both studies show the prominence of N2O. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 83 of 97
N2O emissions from land are the probably least well understood agricultural emission and thus the prominence of N2O makes calculation of the GWP more uncertain than from other industries (especially those with easy to measure emission outlets), They are also more uncertain than the other environmental emissions from agriculture. This reinforces the need to improve the understanding of N2O emissions. We used the IPCC methodology and there are other methods that could be justly used, for example the DNDC simulation model (Li et al., 1992). Broad agreement would be anticipated, but there could be substantial differences between particular features. Agriculture contributes 7% of aggregated greenhouse gases in the national inventory (Baggott et al., 2004). Agriculture, however, dominates ammonia emissions and nitrate leaching and these both contribute to eutrophication and ammonia to acidification. The agricultural carbon-nitrogen footprint thus affects three major areas of environmental pollution. 4.5 Uncertainties Measurements of major terms used in this study (e.g. pollutants and energy use on farms or in manufacturing) are all associated with errors. This can be very small in well-defined situations, but those to do with agriculture are inherently more variable. Measurements of individual emissions may have coefficients of variation, CV, (standard deviation divided by the mean) of as much as 70% (e.g. for N2O). The errors in national inventories of gaseous emissions from agriculture are typically about 30%. The errors in a whole farm model (which included field operations; profitability; emissions of ammonia, methane, nitrous oxide and nitrate; and soil P balance) were in the range of 10% to 34% (Williams et al., 2004b), with most the emissions at about 32%. Aggregating components reduces uncertainty. For example, summing three uncorrelated components of equal magnitude, each with a CV of 35%, results in an overall uncertainty of 20%. Multiplying increases uncertainty and multiplying the same three terms results in an overall uncertainty of 61%. The LCA model includes both additive and multiplicative terms. A reasonable estimate of the uncertainty associated with any calculated burden is 30%. Major factors (in addition to N2O) are N fertilisers, fuel and yield. Energies for ammonium nitrate production in the literature range from 38 to 51 MJ/[kg N], with values generally decreasing with time. We have used 41 MJ/[kg N]. Changing the estimate by 3 MJ/[kg N] corresponds to energy use changing by 67 MJ / [t bread wheat] or 3%. Fuel use estimates have been shown to have a typical coefficient of variation of 40%. This corresponds to 220 MJ / [t bread wheat] or 9%. An error of 0.5 t/ha in yield corresponds to 161 MJ / [t bread wheat] or 6%. Nitrate leaching was estimated using models which demand that all the nitrogen be accounted for. While this ensures that the surplus of intake over offtake is correct, the balance of emissions could be incorrect. The component ruminant rearing systems are taken from a number of sources to represent the major structure of the industries. It is acknowledged however that there are a very large number of ways used to rear beef and sheep, often making use of otherwise waste products. There is therefore still a need to examine further their uses of feed sources and their consequent use of energy. Data on national fertiliser use on grassland is aggregated and a model was created to estimate the use on different land types by different animal systems. Further work is needed to ensure this model accurately represents the different systems and correctly predicts N emissions. Despite the effects of uncertainty on the absolute accuracy of the LCA model, it is relatively accurate at performing comparative analyses. Uncertainty is highly correlated between Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 84 of 97
scenarios, thus comparative differences are largely a consequence of differences between systems. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 85 of 97
5 Publicising and using the model 5.1 Publicising the model A user workshop was held at which the interface and models were presented. It generated considerable interest from a number of parties and allowed the proposed approach of the interface to be tested. It generated incisive questions for the team as well as guidance on the type of studies that user might wish to undertake with the model. Several requests for working copies of the model followed. Descriptions of the model and preliminary outputs were put on the SRI website. This provided us with more feedback, thus indicating that it had been accessed. It was later mounted on the Cranfield University website at: http://www.silsoe.cranfield.ac.uk/ (then search for IS0205 and LCA). Presentations about the work were also given at conferences including: the Soil Association Annual Conference, the Agricultural Research Modellers Group and the European Society for Operational Research, as well as at university seminars and to visitors. The model has been used to inform other Defra-funded research projects and is well placed to analyse variations in existing production systems. It can also be readily developed to analyse new production systems or commodities. For example, sugar beet would be based on potatoes or farmed deer on sheep or beef. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 86 of 97
6 Further Work Further work is required and much should be achievable in the Defra-funded project IS0222 (Underpinning the delivery of computer based environmental Life Cycle Assessment (LCA) of agriculture), which is already underway. The objectives relating to model development are shown below, with limited descriptions. 1. Further development and delivery of the Defra life-cycle inventory of the production of agricultural commodities 1.1. User testing 1.2. Overcoming problems found in the tool 1.3. Development of the tool to meet users desired enhancements 1.4. Addition of other commodities 2. Development of a UK food basket version of the LCI tool This objective will seek to integrate the individual commodity analyses to a single UK food analysis which will explicitly consider the interactions between them. 3. Development of a farm-level version of the LCI tool 4. Disaggregation of the LCI tool to analyse production on a regional basis 5. Development of a life cycle assessment to follow from the inventory This objective will add an Impact Assessment section to the LCI tool to enable users to study the comparative importance of the identified burdens. Particular areas that have come to light since the writing of the project objectives for the Defra-funded project IS0222 include soil carbon loss from imported feeds, like Brazilian soya or palm oil residues, and overall soil carbon balances in domestic agriculture; use of , byproducts or waste products from the food industry. Also, given the great importance of nitrous oxide on GWP, consideration should be given to alternative calculation methods for emissions from soils. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 87 of 97
7 Conclusions 7.1 The models A procedure to calculate the burdens of production for current and future combinations of production systems, using the principles of life cycle assessment (LCA) was constructed for ten agricultural and horticultural commodities in England and Wales The modelling system allows users to compare different production systems by varying the proportions of the components within them, for example to study an increased proportion of higher yielding dairy cows. The models calculate all resource burdens back to primary units (e.g. energy as crude oil in the ground) and include all significant inputs and processes from phosphate rock quarrying to animal feed production, imports, processing and delivery. Emissions to the environment are aggregated as functional burdens, e.g. global warning potential (GWP) over a 100 year time frame, acidification (equated to sulphur dioxide), eutrophication (equated to phosphate) and abiotic resource used scaled in relation to the element antimony . Individual emissions are also accessible to allow more detailed analysis. Detailed breakdowns of components such as the energy of different arable operations or the components of animal production are available. Alternative grades of land use for arable crops are modelled, based on linear scaling of the grade 3a land class. In contrast, geographical data was used to estimate the entire range of land grades that are currently used for different grassland systems, such as upland sheep grazing. Animal production is modelled as a network so that changes to one part, e.g. upland sheep, are systematically reflected in another, e.g. lowland sheep. All analyses include organic and non-organic (or contemporary conventional) production systems, which may each have several sub-systems. All production was analysed using a long-term, steady-state approach to ensure that no depletion or accumulation of plant nutrients occurred. 7.2 The results Organic field crops and animal products mostly consume less primary energy than non-organic counterparts owing to the use of legumes to fix N rather than fuel to make synthetic fertilisers. Poultry meat and eggs are exceptions, resulting from the high overall efficiency of feed conversion in the non-organic sector. The relative burdens of GWP, acidification and eutrophication between organic and non-organic field-based commodities are more complex than energy. Organic production often results in increased burdens, from factors such as N leaching and N2O emissions from clover leys and lower yields. N2O is the single largest contributor to GWP for all commodities except tomatoes, exceeding 80% in several cases. It is also the emission about which there is the least understanding about its reliable quantification. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 88 of 97
The lower yields and fertility building requirement of organic production mean that more land is always required for organic production, ranging between 65% and 200% extra. Ruminant meats produce more burdens than pig or poultry meats, but ruminants can derive nutrition from land that is unsuitable for the arable crops that pigs and poultry must eat. Heating and lighting dominate the burdens of tomato production, but increasing the national use of combined heat and power (CHP) could reduce the primary energy consumption by about 70%. Unlike field crops, organic tomatoes always incur more burdens (except pesticide use) than non-organic counterparts because yields are lower, but the inputs are almost the same per unit area. Smaller and on-the-vine tomato types also incur definably more burdens of production than loose and larger ones (classic and beefsteak). The LCA model generally agrees with reported studies. Where substantial differences exist, it is not clear whether these stem from different assumptions in methods or the actuality of production in different geographic areas. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 89 of 97
8 Acknowledgements The authors are grateful to Defra for funding this work, especially the guidance and support of the Defra project officer, Dr Donal Murphy-Bokern. The work was mainly carried out and the report was written by staff from SRI (who have since moved to Cranfield University: http://www.silsoe.cranfield.ac.uk), but the project team included the following, whose considerable inputs made the project possible: Raymond Jones & Richard Weller (IGER ), Rosie Bryson (Velcourt Ltd), Lois Philipps (Elm Farm Research Centre), Andy Whitmore, Margaret Glendining and Gordon Dailey (Rothamsted Research), Paul Cook (Rlconsulting), Nigel Penlington (MLC) and Gerry Hayman (Hayman Horticultural Consultancy). We also note the sudden and unexpected death earlier this year of Raymond Jones, whose contribution to the project and the research community was considerable. This final report on IS0205 updates and extends the draft report submitted to Defra on 7th December 2005 on the closure of Silsoe Research Institute. It includes additional sub-models developed as part of the on-going project IS0222. The editorial input of Dr David Parsons is also gratefully acknowledged. Final report to Defra for project IS0205: Environmental burdens and resource use in agriculture Page 90 of 97
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