Methods of assessment of direct field emissions for LCIs of agricultural production systems

Methods of assessment of direct field emissions for LCIs of agricultural production systems Data v3.0 (2012) Thomas Nemecek and Julian Schnetzer Agroscope Reckenholz-Tänikon Research Station ART Zurich, August 2011 This documentation file is mainly based on chapter 4 of ecoinvent report No. 15a (Nemecek et al. 2007) where the methods of assessment of direct field emissions for life cycle inventories (LCI) of agricultural crop production (ecoinvent data version 2) are described. Further elementary flows related to natural resources are described here, as well. This text represents an updated documentation of the methods and data sources used within the frame of updating agricultural LCIs for ecoinvent data version 3.

Life cycle inventories of Swiss and European agricultural production systems - Table of Contents Table of Contents TABLE OF CONTENTS... 2 ABBREVIATIONS... 3 1 BASIC ASSUMPTIONS... 4 2 DIRECT FIELD EMISSIONS... 5 2.1 EMISSIONS OF AMMONIA TO THE AIR... 5 2.1.1 The AGRAMMON model... 5 2.2 NITRATE LEACHING TO GROUND WATER... 8 2.2.1 The SALCA-NO3 model... 9 2.2.2 The SQCB-NO3 model... 12 2.3 EMISSIONS OF PHOSPHORUS TO THE WATER... 15 2.3.1 Phosphate Leaching to Ground Water... 16 2.3.2 Phosphate Run-Off to Surface Water... 17 2.3.3 Phorsphorous Emissions Through Water Erosion to Surface Water... 17 2.4 EMISSIONS OF N 2 O TO THE AIR... 17 2.5 EMISSIONS OF NO X TO THE AIR... 18 2.6 NUTRIENT INPUTS IN AGRICULTURAL SOILS... 19 2.7 RELEASE OF FOSSIL CO 2 AFTER UREA APPLICATIONS... 19 2.8 EMISSIONS OF HEAVY METALS TO AGRICULTURAL SOIL, SURFACE WATER AND GROUND WATER... 19 2.9 EMISSIONS OF PESTICIDES TO AGRICULTURAL SOIL... 21 3 NATURAL RESSOURCES... 22 3.1 CO 2 FROM THE ATMOSPHERE... 22 3.2 LAND USE... 22 APPENDIX A... 26 LITERATURE... 29

Direct field emissions and elementary flows in LCIs of agricultural production systems - Abbreviations Abbreviations CH CH 4 DM FAL FAT FiBL FU IPCC kg LCI LCIA LU m 2 m 3 N 2 O n.a. NH 3 NO x SALCA SIP Switzerland methane dry matter Swiss Federal Research Station for Agroecology and Agriculture, Zurich-Reckenholz (today part of ART) Swiss Federal Research Station for Agricultural Economics and Engineering, Tänikon (today part of ART) Research Institute of Organic Agriculture, Frick, Switzerland functional unit Intergovernmental Panel on Climate Change kilogram (measurement of weight) life cycle inventory life cycle impact assessment livestock unit square metre (measurement of area) cubic metre (measurement of volume) dinitrogen monoxide not available ammonia nitrous oxide Swiss Agricultural Life Cycle Assessment Swiss Integrated Production 3

Direct field emissions and elementary flows in LCIs of agricultural production systems - Basic Assumptions 1 Basic Assumptions The following general assumptions are valid for the Swiss plant production system datasets covered by this documentation file: The field was assumed to have a slight slope of 5% (Nemecek et al. 2005, Appendix 3.1.3; value valid for the lowlands). The field slope mainly affects soil erosion and P-emissions to the water. For the European datasets the values given by local experts were used. Humus content was assumed to be 2%, clay content 20% and potential rooting depth 80 cm (Nemecek et al. 2005, Appendix 3.1.3). These factors affect the quantity of nitrate leached. The field is situated in the lowlands. The majority of arable crops are cultivated in the lowlands, and most seed production takes place there as well. Nevertheless, a large proportion of grassland is located in the hills and mountains, and although studies (Nemecek & Huguenin 2002, Nemecek et al. 2005) have shown that the differences between the lowlands and mountainous regions in terms of environmental impacts were found to be relatively small, this fact must be borne in mind. The soil was assumed to be of average erodibility. The field plot was assumed to have no artificial drainage. The majority of the fields and meadows in Switzerland are not drained 1. For the canton of Zurich, for instance, the percentage of drained agricultural area lies between 7 and 38%, depending on the region (Schmid & Prasuhn 2000). For the other regions in Europe the same assumption was made. Fertilisation follows current recommendations (Walther et al. 2001). In order to obtain direct payments 2, the farmer must have a balanced nutrient balance. The fertilising recommendations (Walther et al. 2001) form the basis for calculating the nutrient balance. Consequently, it is likely that farmers generally follow these recommendations. Nevertheless, it is possible to deviate from these recommendations to a certain extent: there is a tolerance of up to 10% for a positive nutrient balance. Furthermore, a farmer may apply more fertilisers than recommended to one crop, and less to another. No special measures are taken to prevent soil erosion, except the application of green manure for spring-sown crops. This is in accordance with the data source chosen for the use of machinery (LBL et al. 2000). The average density of livestock units (LU) per hectare was set at 1.3 LU/ha (BLW 2003). This value was used to calculate the potential N-mineralisation of the soil, except for the extensive meadow, where no fertiliser is applied at all. No distinction has been made between integrated and organic farming, even if fertilising practise is different. Organic farms apply more manure to arable crops than do integrated farms. If the entire crop rotation is considered, however, this difference almost disappears (FAT 2000a), since the farmyard manure is applied to a larger extent to the meadows in the integrated farm. The Swiss plant production inventories in ecoinvent refer to this standard situation. In conditions differing from this situation, the emissions may differ substantially from the values in ecoinvent data. 1 Personal communication from V. Prasuhn, ART, September 2002. 2 Verordnung über die Direktzahlungen in der Landwirtschaft (Direktzahlungsverordnung, DZV), 7.12.1998. 4

Direct field emissions and elementary flows in LCIs of agricultural production systems - Direct Field Emissions 2 Direct Field Emissions 2.1 Emissions of Ammonia to the Air Ammonium (NH 4 + ) contained in fertilisers can easily be converted into ammonia (NH 3 ) and released to the air. Agriculture is the biggest source of ammonia emissions in Switzerland. For 2000, Thöni et al. (2007) estimated the total emissions of NH 3 to be 53,000 tonnes, thereof 93% from agriculture. Animal husbandry (emissions in the stable, during manure storage and spreading) is the largest source. About 30% of the excretions of N are lost in the form of ammonia. By taking appropriate measures, these emissions could be reduced by about 20-40% (Menzi et al. 1997). Ammonia contributes to acidification and the eutrophication of sensitive ecosystems. Its impact is mainly local and regional. A comparison of different emission factors for ammonia can be found in Menzi et al. (1997). 2.1.1 The AGRAMMON model Geographic scope of application: global The losses of NH 3 emissions were calculated based on the model Agrammon (www.agrammon.ch), a model especially designed for the assessment of NH 3 emissions from agriculture on either farm scale or on a regional scale. The relevant modules of the model applied here are, on the farm scale, application, referring to emissions from the application of farm manure, and plant production, referring to emissions from the application of mineral and recycling fertilisers. The model structure and technical parameters can be found in Agrammon Group (2009a, b). Parameters required by the model that were not available from the production inventories were complemented with standard values proposed in the user interface implemented online, e.g. the fractions of slurry application techniques in practice (cf. Tab. 2.1 & Tab. 2.2). These standard values shall reflect a representative distribution of alternatives in agricultural practices and do not necessarily correspond to the basic system in Agrammon and, thus, the resulting correction factors deviate from 1 (cf. following paragraph). The standard values are based on a survey described in Kupper et al. (2010) and a corresponding summary of the model parameters deducted from this survey (SHL 2010). Application of farmyard manure The module application is subdivided into three categories which are application of liquid manure, of solid manure and of poultry manure. The formulae for all sub-modules follow the same principle: NH 3 N = TAN * (er + c_app) * c x NH 3 N = nitrogen emissions in form of NH 3 (kg N/ha) TAN = Total ammonium nitrogen; this is considered equal to the soluble nitrogen content (Agrammon Group 2009b) and is calculated as the product of amount of farmyard manure (kg/ha) and the corresponding soluble nitrogen content (kg N/kg manure) according to Flisch et al. (2009) (kg N/ha) (Tab. 2.3) er = emission rate; this is a constant emission rate for each type of farm manure (%/100 of TAN) (Tab. 2.4) c_app = correction factor that influences the emission rate; it refers to the amount of manure per application and its degree of dilution; applies only for liquid manure (dimensionless). c x = correction factor x; this refers to various parameters of the crop production system; for the basic system assumed in Agrammon c x = 1; c x < 1 has a reducing effect on NH 3 emissions, c x > 1 an increasing effect (dimensionsless, see Tab. 2.1 for the explanation of the variables). 5

Direct field emissions and elementary flows in LCIs of agricultural production systems - Direct Field Emissions c x = c_tech * c_soft * c_season for liquid manure c x = c_incorp_time * c_season for solid and poultry manure The calculation of correction factors is described in Agrammon Group (2009a). The correction factors of liquid manure are characterised in Tab. 2.1; for solid and poultry manure the same correction factors apply (Tab. 2.2). In the case of solid and poultry manure, the date of base dressing was used to determine c_season. Tab. 2.1 Correction factors (c x) for application of liquid manure c x Description Calculation Applied c_app c_tech c_soft c_season represents the amount of manure per application (applied standard value: 30 m 3 /ha) and its degree of dilution (40% liquid manure : 60% water) represents the technical equipment applied for slurry spreading equipment: splash plate 90 trailing hose 10 % of application: represents the proportions of manure applied on hot days and in evening hours application in evening hours 20% application on hot days sometimes represents the proportions of manure applied in summer (June-August) and the rest of the year based on crop data based on standard values based on standard values based on crop data value -0.029 0.97 0.96 variable Tab. 2.2 Correction factors (c x) for the application of solid and poultry manure c x Description Calculation Applied value c_incorp_time c_season represents the time span between manure application and incorporation incorporation of manure: within 1 day 20 within 3 days 20 after more than 3 days 10 no incorporation 50 % of application: represents the proportions of manure applied in summer (June-August) and the rest of the year based on standard values based on crop data cattle/pig: 0.88; poultry: 0.82 variable Tab. 2.3 Nitrogen contents of different types of manure. N total = total nitrogen content; N soluble = soluble nitrogen content (Flisch et al. 2009), this is considered to be equal to TAN. The values for liquid manure apply to liquid manure without addition of water. Animal category Manure type Unit kg N soluble/unit Cattle liquid manure kg/m 3 2.3 low-excrement liquid manure kg/m 3 3.2 staple manure kg/t 0.8 solid manure from loose housing kg/t 1.3 6

Direct field emissions and elementary flows in LCIs of agricultural production systems - Direct Field Emissions Pigs liquid manure kg/m 3 4.2 solid manure kg/t 2.3 Poultry broiler manure kg/t 10.0 laying hen manure kg/t 6.3 laying hen litter kg/t 7.0 dried poultry litter kg/t 9.0 Tab. 2.4 Nitrogen emission rates (er) of different animal categories and manure types Animal category manure type er (% TAN) Cattle Liquid 50 Solid 80 Pigs Liquid 35 Solid 80 Poultry Solid, from growers, layers and other poultry 30 Solid, from broilers and turkeys 65 Plant production The module plant production is subdivided into the sub-modules agricultural area, mineral fertiliser and recycling fertiliser. The sub-module agricultural area defines a standard emission of 2 kg NH 3 -N/ha from the leaf surface of plants. As a similar level of emission could be expected from any other vegetated area and is not due to agricultural practice, this sub-module was left out of consideration. The sub-module for recycling fertilisers like compost and liquid or solid digestate is, so far, only applied to sugarcane production in Brazil, where vinasse, a by-product of sugar production and considered a liquid digestate, is applied to fields for nitrogen fertilisation (Tab. 2.5). The NH 3 emissions from applied mineral fertilisers are calculated by constant emission factors for each group of fertiliser. Instead of the emission factors suggested in Agrammon group (2009a) (15% for urea and 2% for all other mineral fertiliser) a set of emission factors was applied that distinguishes a greater number of different fertiliser groups (Asman 1992; Tab. 2.6). Tab. 2.5 Parameters used in calculation of NH3-N emissions due to vinasse application on sugarcane fields in Brazil. Parameter Value Source Total N content of vinasse [g/l] 0.27 Jungbluth et al. 2007 Fraction of TAN of total N in vinasse [%/100] 0.5 Flisch et al. 2009 Emission factor of TAN from liquid digestate [%/100] 0.6 Agrammon Gruop 2009b 7

Direct field emissions and elementary flows in LCIs of agricultural production systems - Direct Field Emissions Tab. 2.6 NH 3-emissions from mineral fertilisers (% N emitted in form of NH 3). Type of fertiliser Emission factor for NH 3-N ammonium nitrate, calcium ammonium nitrate 2 % ammonium sulphate 8 % urea 15 % multinutrient fertilisers (NPK-, NP-, NK-fertilisers) 4 % urea ammonium nitrate 5.7 % *) ammonia, liquid 3 % *) The weighted average of ammonium nitrate (2/3 of N) and urea (1/3 of N) was taken, since no emission factor is given by Asman (1992). 2.2 Nitrate Leaching to Ground Water Nitrate (NO 3 - ) is either supplied to the soil by fertilisers or produced by micro-organisms in the soil via the mineralisation of organic matter. Nitrate in the soil can be absorbed as a nutrient by the plants. In periods of heavy rainfall, however, precipitation exceeds soil evaporation and transpiration of the plants, which leads initially to saturation of the soil with water, and afterwards to percolation to the ground water. As nitrate is easily dissolved in water, the risk of leaching is high. This situation is quite frequent in Switzerland. The risk of nitrate leaching is highest in autumn and winter, when precipitation often or always exceeds uptake by the plants. Moreover, nitrogen mineralisation is generally highest in late summer, when the nitrogen often cannot be taken up by the plants (Stauffer et al. 2001). Experiments have shown that it is not the choice of crops but rather the succession of crops in a crop rotation that is determining the amount of nitrate leached (Stauffer et al. 2001). Since the modules in the ecoinvent database are life cycle inventories of products taking into account one single crop only, the succession of crops can only partly be taken into account. This fact should be borne in mind when interpreting the nitrate leaching values. Nitrate losses are undesirable for several reasons: From the agricultural point of view, valuable nutrients are lost from the soil, increasing the need for fertilisers. Nitrate in ground water used as drinking water may have a toxic impact to humans. Although the acute toxicity of nitrate is low, nitrate is easily converted into nitrite, which has a higher acute toxicity and is supposed to be indirectly carcinogenic (Surbeck & Leu 1998). Once ground water becomes surface water, nitrate contributes to eutrophication and also induces emissions of nitrous oxide, a major greenhouse gas (Schmid et al. 2000). The tolerance level for nitrate in drinking water is 40 mg/l in Switzerland and 50 mg/l in the EU, while the Swiss quality goal is 25 mg/l maximum. Results from the Swiss monitoring network NAQUA (Greber et al. 2002) show that these levels are exceeded only in areas with arable crops, or in fruitand wine-growing areas. In areas with forests or permanent grassland, these levels have never been exceeded. This shows the importance of arable crops and soil cultivation in nitrate leaching. Nitrate emissions to ground water can be estimated by simulation models, although this method is very complex and time-consuming and does not always lead to very satisfactory results (Oberholzer et al. 2001). A comparison of different methods for estimating nitrate leaching is given in Audsley et al. (1997). Depending on the country of crop production different models were used to calculate nitrate leaching. A model by Richner et al. (in prep.) specifically for the application to conditions in Switzerland (SALCA-NO3) was applied to Switzerland and other European countries, where similar conditions are found. For non-european countries the SQCB-NO3 model was used, a geographically unspecific and 8

Direct field emissions and elementary flows in LCIs of agricultural production systems - Direct Field Emissions simpler model (de Willigen 2000, in: Faist Emmenegger et al. 2009). Both models are described below. 2.2.1 The SALCA-NO3 model Geographic scope of application: Europe The model SALCA-NO3 calculates the expected nitrate leaching and comprises the following elements (Richner et al. in prep.): Nitrogen mineralisation from the soil organic matter per month Nitrogen uptake by vegetation (if any) per month Nitrogen input from the spreading of fertiliser Soil depth Factors not considered: o o Amount of seepage Denitrification The following description is an extract of the full description of the model SALCA-nitrate by Richner et al. (in prep.). The reader is referred to this report for further information. The model of Richner et al. (in prep.) calculates the expected nitrate leaching of arable crops, meadows and pasture land considering not only crop rotation, soil cultivation, nitrate fertilising but also nitrate mineralisation from the soil organic matter, nitrate uptake by the plants and various soil conditions. The model is valid for the Swiss lowland and adjoining regions. The calculation bases on the monthly difference between the amount of mineralized nitrate in the soil and the nitrate uptake of the plants. Furthermore, the nitrate leaching risk from fertiliser application during inappropriate time periods is taken into account. The expected nitrate leaching of pastures rises because of locally high nitrate concentrations. Therefore the total amount of nitrate on pastures is calculated from the number of animals, the grazing duration and the grazing period. The total expected nitrate leaching of an arable crop is assessed by the sum of the monthly values within the assessment period starting one month after the harvest of the former crop and ending in the month of harvesting of the given crop. The model distinguishes three different regions valley, hill and mountain each of which defines a specific climate regime. Virtually all Swiss plant production inventories in ecoinvent refer to production in the valley region, hence the model parameters shown below refer to that selfsame region. Tab. 2.7 shows the expected nitrogen mineralisation for default settings of clay and humus content in the valley region. The monthly mineralisation may be increased by certain intensive soil cultivation operations aerating the soil and thereby promoting microbial activity. Tab. 2.7 Expected nitrogen mineralisation (N min m, kg N per ha and month, from Richer et al. in prep.) in soils with 15% clay, 2% humus and N input from farm manure of 1 LU/ha in the valley region. Intensive soil cultivation means treatment by a rotary cultivator or a rotary harrow in the respective month. In months where there is no intensive soil cultivation, the values Without intensive soil cultivation are used. Jan. Feb. March Apr. May June July Aug. Sept. Oct. Nov. Dec. Without intensive soil cultivation 0 0 6 9 12 15 17 21 23 12 6 0 With intensive soil cultivation 0 0 10 15 20 25 29 38 38 20 10 0 9

Clay content(%) Direct field emissions and elementary flows in LCIs of agricultural production systems - Direct Field Emissions Nitrogen mineralisation was further corrected for clay and humus content of the soil (Tab. 2.8) as well as for green manuring and tillage of pastures (see Richner et al. in prep.). Tab. 2.8 Correction factors of nitrate mineralization (%) against the clay and humus content of the soil. Humus content (%) <3 3-5 5-8 8-15 0-20 0 + 10 % + 20 % + 40 % 20-30 - 10 % - 5 % + 5 % + 25 % 30-40 - 20 % - 20 % - 10 % + 5 % >40-30 % - 30 % - 25% - 15 % Nitrogen uptake by vegetation was estimated based on the model STICS (Brisson et al. 2003) with a high temporal resolution (100 time steps from sowing to physiological maturity of the crop in question). These nitrogen uptake functions were determined for the crops grass, protein peas, barley, potatoes, maize, rapeseed, soy beans, sunflower, wheat and sugar beets assuming for each crop a standard yield and a corresponding standard nitrogen uptake as given in Flisch et al. (2009). Nitrogen uptake of other crops was approximated by these functions or by combinations of them (for details refer to the appendix of Richner et al. in prep.). Variations in nitrogen uptake due to yields deviating from the standard yield were accounted for by scaling the nitrogen uptake relative to the difference between standard and real yields. Nitrogen input from farm manure is considered in terms of livestock units per hectare (LU/ha). Based on the average number of livestock units of farms in the Swiss lowlands (BLW 2003), this parameter (St) was set to 1.3 LU/ha for all calculations (average of the years 2000 to 2002), except for the extensive meadow, where St=0, since no fertiliser is applied (see chapter 1), and for other meadow types, where St varies in the range of 1.3-1.5. The basic values of nitrogen mineralisation which refer to 1 LU/ha linearly decrease or increase with St by 10% per 1 LU/ha. For the European datasets, a farm without livestock was assumed (St=0). The risk of nitrogen leaching due to fertiliser application is dependent on the crop and the month in which fertiliser was applied (Tab. 2.9.; Richner et al. in prep.). Tab. 2.9 Risk of nitrogen leaching (fraction of potentially leachable nitrogen of the N applied through fertilisers in %, from Richner et al. in prep.). Months Winter cereals Maize, soya beans sowing year harvestyear harvestyear Winter rape seed and green manure sowing year harvestyear Potato, sugar and fodder beets harvestyear Faba beans, protein peas (spring sown) harvestyear harvestyear Sunflowers Permanent meadow Int Permanent meadow Ext January 100 50 100 100 20 100 100 100 20 20 February 100 30 100 100 10 100 100 100 10 20 March 100 10 100 100 0 50 50 50 0 0 April 100 0 80 100 0 30 30 30 0 0 May 100 0 70 100 0 10 0 0 0 0 June 100 0 0 100 0 0 0 0 0 0 July 100-0 100-0 0 0 0 0 August 100-0 80-0 - 0 0 0 10

Direct field emissions and elementary flows in LCIs of agricultural production systems - Direct Field Emissions Months Winter cereals Maize, soya beans Winter rape seed and green manure Potato, sugar and fodder beets Faba beans, protein peas (spring sown) Sunflowers Permanent meadow Int September 90-0 0-0 - - 0 0 October 90 - - 0 - - - - 0 0 Permanent meadow Ext November 90 - - 20 - - - - 10 20 December 90 - - 20 - - - - 20 20 The correction of the expected nitrate leaching due to fertiliser application against the depth of the soil is listed in Tab. 2.10. Tab. 2.10 The correction of the expected nitrate leaching due to fertiliser application against the depth of the soil (Richner et al. in prep.) Soil depth (cm) Correction (%) > 100 0 91-100 +5 81-90 +10 71-80 +15 61-70 +20 51-60 +25 41-50 +30 40 +35 There is no leaching water during the intensive vegetation period because the evapotranspiration is similar or higher than the precipitation. Therefore usually no nitrate leaching occurs during this period. For various crops fertilising is only possible shortly before the growing period due to agronomic or technical reasons. The model accumulates the monthly values of nitrate mineralisation, nitrate uptake by the plants and the nitrate from fertilising during this period (Tab. 2.11). Tab. 2.11 Accumulation of the monthly values of nitrate mineralisation, nitrate uptake by the plants and the nitrate from fertilising for various crops (Richner et al. in prep.). Month Crop J F M A M J J A S O N D winter cereal spring cereal maize, soybean potato sugar beet, fodder beet sunflower fava bean, protein pea (spring sown) fava bean, protein pea (autumn sown) permanent meadow As nitrate leaching is strongly dependent on the availability of water percolating the top soil which, in turn, is dependent on precipitation, a correction factor is introduced, in addition to the model SALCA- NO3, for regions other than the Swiss lowlands to which the model is adapted. This nitrate leaching 11

Direct field emissions and elementary flows in LCIs of agricultural production systems - Direct Field Emissions transformation factor represents the ratio of winter precipitations (Octobre to March) of the region in question and of Reckenholz (Switzerland, site of model calibration) as most leaching occurs in this period. The results of SALCA-NO3 are multiplied by the respective transformation factor. For Swiss production systems this factor is constantly set to 1. For all other regions, the considered winter precipitations and transformation factors are presented in Tab. 2.12. Tab. 2.12 Winter precipitations and nitrate leaching transformation factors for the different regions Winter precipitations (October-March) in mm Nitrate leaching transformation factor Swiss lowlands (site Reckenholz) 433 1 Barrois 381 0.88 Castilla-y-Leon 266 0.61 Saxony-Anhalt 183 0.42 Europe *) 219 0.51 *) In this case, rye is the only affected crop which is mainly produced in Eastern Europe. Winter precipitation was calculated as the average of all available weather stations in the Polish middle and low lands (www.klimadiagramme.de). 2.2.2 The SQCB-NO3 model The SQCB-NO3 model is reported in Faist Emmenegger et al. (2009) and is an adaption of a formula developed by de Willigen (2000). The formula calculates the leaching of NO3-N and is a simple regression model of the form: P N 21.37 0.0037* S 0.0000601* Norg 0.00362* U c* L where: N = leached NO3-N [kg N/(ha*year)] P = precipitation + irrigation [mm/year] c = clay content [%] L = rooting depth [m] S = nitrogen supply through fertilisers [kg N/ha] N org = nitrogen in organic matter [kg N/ha] U = nitrogen uptake by crop [kg N/ha] It must be mentioned that in Faist Emmenegger et al. (2009) the formula has been taken from Roy et al. (2003), where it is not reported correctly (p. 51, formula OUT3 ), stating C org instead of N org (details for calculation of N org from C org see below). The SQCB model provides relatively simple approaches to assess most of the required input parameters. P and C org are determined through the ecozone in which the crop is produced. The ecozones for the whole globe are defined and presented as maps in FAO (2001). Fix values for carbon content in the upper 30 cm of soil and for annual precipitation are assigned to each ecozone (see Tab. 2.13). The carbon content in tonnes per 3000 m 3 (1 ha [area] * 30 cm [depth]) is converted into mass fraction by the formula: C org [%] = C org [t/3000 m 3 ] * (1 / 1.3 t m -3 ) * 100. In case of irrigation, the amount of irrigation water [mm] is added to the precipitation in order to obtain the parameter P. Precipitation values for montane ecozones were calculated as an average 12

Direct field emissions and elementary flows in LCIs of agricultural production systems - Direct Field Emissions weighted if sufficiently detailed data were available of the annual precipitations of all representative weather stations available at www.klimadiagramme.de. Where several ecozones were covered by the crop producing region of the respective transforming activity, the model was applied to each ecozone and an average nitrate leaching rate for the whole producing region was calculated from the ecozone-wide results, weighted by the contribution of each ecozone to crop production in terms of harvested acreage or production volume according to data availability. The same applied for several USDA soil orders within one producing region or ecozone (see below). The information for weighting the contribution of sub-units (by ecozone or USDA soil order) were gained from comparisons of the ecozone or soil map, respectively, with a map of the spatial distribution of crop production in the respective country or with equivalent spatial information. This information was taken from USDA (2009) for maize, wheat, potatoes, soybeans, rice, rape seed and cotton in the USA, from USDA (2004a) for soybeans and Goldemberg (2008) for sugarcane in Brazil, and from Hsu & Gale (2001) for cotton and Zhao (2008) for sweet sorghum in China. Tab. 2.13 FAO ecozones and their assigned carbon content and annual precipitation. Due to high variability in precipitation, no values are given for montane ecozones. For these ecozones precepetation values have to be researched in each individual case. (From Faist Emmenegger et al. 2009) FAO ecozones Carbon content [t/ha in upper 30cm = t/3000 m 3 ] Annual precipitation [mm] Tropical wet 59 2500 Tropical moist 48 1500 Tropical dry 34 1000 Tropical dry 34 500 Tropical dry 34 50 Tropical montane 55 - Warm temperate moist 55 1200 Warm temperate dry 25 700 Warm temperate dry 25 400 Warm pemperate dry 25 200 Warm temperate moist or dry 40 - Cool temperate moist 81 1500 Cool temperate moist 81 600 Cool temperate dry 38 300 Cool temperate dry 38 150 Cool temperate moist or dry 59 - Boreal moist 22 500 Boreal dry 22 400 Boreal moist and dry 22 - They clay content c is defined by the USDA soil order of a producing region or its sub-unit, respectively. A constant value for clay content is assigned to each USDA soil order based on USDA (1999) (see Tab. 2.14). The maps for defining sub-units of production regions or ecozones by soil orders were taken from USDA (1999), as well, and more detailed maps especially for the USA from the USDA website (http://soils.usda.gov/technical/classification/orders/). Tab. 2.14 USDA soil orders and their assigned clay contents. (From Faist Emmenegger et al. 2009) USDA soil order clay content [%] Alfisol 28.0 Andisol 10.4 13

Direct field emissions and elementary flows in LCIs of agricultural production systems - Direct Field Emissions USDA soil order clay content [%] Aridisol 17.2 Entisol 3.5 Gelisol 23.7 Histosol 2.0 Inceptisol 4.9 Mollisol 21.1 Oxisol 53.9 Spodosol 1.8 Ultisol 12.3 Vertisol 49.0 The rooting depth for several crops is given in the SQCB report by Faist Emmenegger (2009). The missing values were taken from other literature. Values and sources are presented in Tab. 2.15. Where information was available, values from the SQCB report were replaced by values from FAO (2011). Tab. 2.15 Crops and their rooting depth as assumed for calculations. Crop Rooting depth [m] Source Potatoes 0.5 FAO 2011 Sugar cane 1.6 FAO 2011 Sweet sorghum 1.5 FAO 2011 Rape seed 0.9 SQCB report Soybeans 0.95 FAO 2011 Oil palm 1.0 SQCB report Wheat 1.2 FAO 2011 Maize 1.35 FAO 2011 Rice 0.6 Mishra et al. 1997 Cotton 1.35 FAO 2011 The nitrogen supply S was taken from the unit process itself and, if necessary, converted to nitrogen supply per hectare by multiplication with the the yield given in the respective unit process general comment field. The nitrogen uptake U is given for several crops in Faist Emmenegger et al. (2009). For the remaining crops nitrogen uptake was taken from literature. Tab. 2.16 presents the nitrogen uptake per hectare; original values are given in kilogrammes per tonne of product in the SQCB report and are converted to tonnes per hectare here. For the other crops literature values were treated in the same way and values were adjusted by the ratio of yields in literature and in the unit process of the transforming activity, if necessary. In the case of soybeans, only 40% of the values given in the SQCB report are considered as nitrogen uptake in order to reflect the fact, that the remaining 60% are fixed from the air and are not directly relevant to the balance of nitrogen supplied through fertilisers and mineralised from the soil organic matter (Schmid et al. 2000). Tab. 2.16 Crops and their nitrogen uptake as assumed for calculations. Note that one crop can have several different values according to different yields and/or different literature sources for the respective countries. Crop Producing country Nitrogen uptake [kg N/ha] Source Potatoes USA 154 SQCB report Sugar cane Brazil 152 SQCB report Sweet sorghum China 193 SQCB report Rape seed USA 53 SQCB report 14

Direct field emissions and elementary flows in LCIs of agricultural production systems - Direct Field Emissions Crop Producing country Nitrogen uptake [kg N/ha] Source Soybeans USA 81 SQCB report Soybeans Brazil 78 SQCB report Oil palm Malaysia 150 SQCB report Wheat USA 51 Flisch et al. 2009 Maize USA 196 Flisch et al. 2009 Rice USA 119 Swain et al. 2006 Cotton USA 89 Boquet & Breitenbeck 2000 Cotton China 135 Dong et al. 2010 To calculate the organic nitrogen N org in soil [kg N/ha] from the soil organic carbon content C org [%] the following quantities are needed: soil volume V [m 3 /ha] V is taken to be 5000 m 3, which means that the upper 50 cm of soil are considered (according to pers. comm. J. Leifeld, ART, 2011), assuming the same carbon content for 30-50 cm depth as calculated above for 0-30 cm depth. bulk density D b [kg/m 3 ] Bulk density is taken to be 1300 kg/m 3, which is the standard value from the SQCB report. C/N ratio r C/N [dimensionless] The C/N ratio is taken to be 11. This is the mean value of the range (10-12) determined through literature research (Batjes 2008; Scheffer 2002; Eggleston et al. 2006) and consultation of experts (pers. comm. J. Leifedl, ART). ratio of N org to N tot (total soil nitrogen) r Norg [dimensionless] The C/N ratio expresses the ratio of C org and N tot. The ratio r Norg is needed calculate N org from N tot, which is calculated in a first step applying the C/N ratio. r Norg is assumed to be 0.85 (Scheffer 2002). N org is calculated by the formula: N org is the mass of organic nitrogen contained in the upper 50 cm of soil. Naturally only a fraction of this mass is mineralised and, hence, available for uptake by plants and leaching to the ground water. This fraction is determined by the mineralisation rate, which is 1.6% here and implicitly included in the regression coefficient of the term N org. 2.3 Emissions of Phosphorus to the Water Phosphorus (P) is an important plant nutrient and must be supplied to the plants in sufficient quantities. A part of the phosphorus is lost to water due to leaching, run-off and soil erosion through water. As phosphorus is a limiting nutritional element in natural water bodies, P emissions can cause eutrophication (Prasuhn & Grünig 2001). Soil erosion by wind is not considered here. We distinguish between three different kinds of phosphorus emissions to water: leaching of soluble phosphate (PO 4 ) to ground water (inventoried as phosphate, to ground water ), 15

Direct field emissions and elementary flows in LCIs of agricultural production systems - Direct Field Emissions run-off of soluble phosphate to surface water (inventoried as phosphate, to surface water ), erosion of soil particles containing phosphorus (inventoried as phosphorus, to surface water ). The emission models SALCA-P (Prasuhn 2006) developed by ART are applied in ecoinvent data. A comparison of different emission coefficients is given by Audsley et al. (1997), Schmid & Prasuhn (2000) and Prasuhn & Grünig (2001). The following factors are considered for the calculation of P emissions in ecoinvent data inventories: type of land use type of fertiliser quantity of P in fertilisers type and duration of soil cover for the calculation of the soil erosion (C-factor). For other factors, considered in the model SALCA-P, default values are used: distance to next river or lake topography chemical and physical soil properties drainage. As the field was assumed to have no drainage (see chapter 1), the emissions to surface water through drainage were not taken into account. The model takes soil erosion, surface run off and drainage losses to surface water and leaching to ground water into account. It should be borne in mind that the values are valid for the soil and site parameters chosen. Changes in soil conditions or in cropping practice could lead to emissions substantially different from the ones calculated in ecoinvent data. The key factors of the model are listed below. Please see Prasuhn (2006) for detailed calculations. 2.3.1 Phosphate Leaching to Ground Water P leaching to the ground water was estimated as an average leaching, corrected by P-fertilisation: P gw = P gwl * F gw P gw = quantity of P leached to ground water (kg/(ha*a)) P gwl = average quantity of P leached to ground water for a land use category (kg/(ha*a)), which is 0.07 kg P/(ha*a) for arable land and 0.06 kg P/(ha*a) for permanent pastures and meadows. F gw = correction factor for fertilisation by slurry (-) F gw = 1 + 0.2/80*P 2 O 5sl P 2 O 5sl = quantity of P 2 O 5 contained in the slurry or liquid sewage sludge (kg/ha). The values of P 2 O 5 -content were taken from Walther et al. (2001). 16

Direct field emissions and elementary flows in LCIs of agricultural production systems - Direct Field Emissions 2.3.2 Phosphate Run-Off to Surface Water Run-off to surface water was calculated in a similar way to leaching to ground water: P ro = P rol * F ro P ro = quantity of P lost through run-off to rivers (kg/(ha*a)) P rol = average quantity of P lost through run-off for a land use category (kg/(ha*a)), which is 0.175 kg P/(ha*a) for open arable land, 0.25 kg P/(ha*a) for intensive permanent pastures and meadows and 0.15 kg P/(ha*a) for extensive permanent pastures and meadows F ro = correction factor for fertilisation with P (-), calculated as: F ro = 1 + 0.2/80 * P 2 O 5min + 0.7/80 * P 2 O 5sl + 0.4/80 * P 2 O 5man P 2 O 5min = quantity of P 2 O 5 contained in mineral fertilisers (kg/ha) P 2 O 5sl = quantity of P 2 O 5 contained in slurry or liquid sewage sludge (kg/ha) P 2 O 5man = quantity of P 2 O 5 contained in solid manure (kg/ha) The values of P 2 O 5 -content for slurry and manure were taken from Walther et al. (2001). 2.3.3 Phorsphorous Emissions Through Water Erosion to Surface Water P emissions through erosion of particulate phosphorous to surface water were calculated as follows: P er = S er * P cs * F r * F erw P er = quantity of P emitted through erosion to rivers (kg P/(ha*a)) S er = quantity of soil eroded (kg/(ha*a)) P cs = P content in the top soil (kg P/kg soil). The average value of 0.00095 kg/kg was used. F r = enrichment factor for P (-). The average value of 1.86 was used (Wilke & Schaub 1996). This factor takes account of the fact that the eroded soil particles contain more P than the average soil. F erw = fraction of the eroded soil that reaches the river (-). The average value of 0.2 was used. The amount of eroded soil S er is calculated according to Oberholzer et al. (2006, Appendix A4.1). 2.4 Emissions of N 2 O to the Air Nitrous oxide or dinitrogen monoxide (N 2 O) is produced as an intermediate product in the denitrification process (conversion of NO 3 - into N 2 ) by soil micro-organisms. It can also be produced as a by-product in the nitrification process (conversion of NH 4 + into NO 3 -, Schmid et al. 2000). The total emissions of N 2 O caused by the Swiss agricultural sector in 1996 were estimated at 8,600 tonnes. N losses in the form of N 2 O are closely linked to the nitrogen cycle in agriculture; intensive agriculture with a high input of nitrogen fertiliser contributes to the increase in N 2 O-emissions. N 2 O is a greenhouse gas with a high impact. Calculations of N 2 O emissions are based on the IPCC method for calculating N 2 O emissions (Eggleston et al. 2006). Direct emissions of N 2 O and indirect or induced emissions are included. In the case of indirect N 2 O emission, nitrogen is first emitted as NH 3 or NO 3 - and subsequently converted to N 2 O. Direct N 2 O emissions [kg N 2 O] from mineral and organic fertilisers and from crop residues were calculated on the basis of the total nitrogen content (N tot [kg N]). The factor of 1.0% N lost as N 2 O was used. Induced N 2 O emissions [kg N 2 O] from ammonia (NH 3 ) were considered using a factor of 1.0% 17

Direct field emissions and elementary flows in LCIs of agricultural production systems - Direct Field Emissions of N in emitted NH 3, induced emissions from nitrate (NO 3 - ) with a factor of 0.75% of N in leached NO 3 -. According to the new IPCC-guidelines, no emissions are calculated from biological nitrogen fixation. The content of total nitrogen in farmyard manure was taken from Walther et al. (2001). The contents of total nitrogen in crop residues are taken from Walther et al. (2001) and the amounts of crop residues from Nemecek et al. (2007) as such, or scaled by the yields of the reference products (and by-products) based on the latter. For exceptions see Tab. 2.17. N 2 O = 44/28 * (0.01 (N tot + N cr ) + 0.01 * 14/17 * NH 3 + 0.0075 * 14/62 * NO 3 - ) N 2 O = emission of N 2 O (kg N 2 O/ha) N tot N cr NH 3 NO 3 - = total nitrogen in mineral and organic fertilisers (kg N/ha) = nitrogen contained in the crop residues (kg N/ha) = losses of nitrogen in the form of ammonia (kg NH 3 /ha) = losses of nitrogen in the form of nitrate (kg NO 3 - /ha). Tab. 2.17 Literature sources of amounts and nitrogen contents of crop residues (other than Walther et al. 2001) Crop Amount of crop residue Nitrogen content of crop residue Rice Nemecek et al. (2007) Swain et al. (2006) Cotton Boquet & Breitenbeck (2000) Boquet & Breitenbeck (2000) Sweet sorghum Khaledian et al. (2010) Keskin et al. (2009) Oil palm Khalid et al. (1999) (577 kg N/ha in standing biomass considered as N in crop residues, allocated over 25 years of plantation lifetime) Sugar cane No crop residues due to burning of fields before harvest. 2.5 Emissions of NO x to the Air During denitrification processes in soils, nitrous oxide (NO x ) may also be produced. These emissions were estimated from the emissions of N 2 O 3 : NO x = 0.21 * N 2 O Since this process is not one of conversion from N 2 O to NO x, but a parallel process, no correction of the N 2 O emissions is required. This equation includes the direct NO x emissions from fertilisers and the soil only. Other sources such as tractor exhaust gases are included in the respective inventories. 3 personal communication from Grub, 1996 18

Direct field emissions and elementary flows in LCIs of agricultural production systems - Direct Field Emissions 2.6 Nutrient Inputs in Agricultural Soils The input of nutrients (N, P, K, Ca, etc.) into the agricultural soil was not inventoried as emissions to the soil for the following reason: The inventories of agricultural products in ecoinvent data are based on the fertilising recommendations (Walther et al. 2001). These recommendations in turn are based on the assumption that the fertiliser should cover the needs of the plants. In a first step, the export of nutrients through the products (main- and co-products) was calculated. In a second step, the recommended fertiliser dose was calculated by accounting for various other aspects. The nutrients supplied to the soil will therefore either be exported in the products or lost to the air or water. The quantity of nutrients in the soil should not be changed on average in the long term. 2.7 Release of Fossil CO 2 after Urea Applications During the urea production process, CO 2 is used, which is chemically bound in the urea molecule. After application and transformation processes in the soil, this CO 2 is released to the atmosphere. Per kg of applied urea-n, 1570 g of fossil CO 2 are released that are inventoried as Carbon dioxide, fossil to air, low population density in ecoinvent data. 2.8 Emissions of Heavy Metals to Agricultural Soil, Surface Water and Ground Water According to an analysis of the heavy metals that are causing problems in Swiss agriculture (Kühnholz 2001), the following seven were selected for the inventories in ecoinvent data: Cadmium (Cd), Chromium (Cr), Copper (Cu), Lead (Pb), Mercury (Hg), Nickel (Ni) and Zinc (Zn). Typical heavy-metal content of agricultural and non-agricultural soils is given by Desaules & Dahinden (2000). Kühnholz (2001) gives a comparison of different emission factors and methods for calculating heavy metal balances. The heavy metal emissions were calculated by SALCA-heavy metal (Freiermuth 2006). Inputs into farm land and outputs to surface water and groundwater are calculated on the basis of heavy metal input from seed, fertilisers, plant protection products and deposition. Residues left on the field are not considered, because they do not leave the system. For erosion of soil average heavy metal contents for arable land, pastures, meadows and intensive crops are used. The amount of eroded soil is calculated as for P-emissions with the method described in Oberholzer et al. (2006). An allocation factor is used to distinguish between diffuse and agriculture-related introduction (Freiermuth 2006). We give only a summary description of the method here. For a full description, the reader is referred to Freiermuth (2006). Three types of emissions are considered in ecoinvent data: Leaching of heavy metals to the ground water (always positive values) Emissions of heavy metals into surface waters through erosion of soil particles (always positive values) Emissions of heavy metals to agricultural soil (positive or negative values according to the results of the balance). The following sources were used to calculate heavy-metal contents: Mineral fertilisers: Desaules & Studer (1993, p. 153), see Tab. A. 2 in the Appendix, Farmyard manure: Menzi & Kessler (1998) and Desaules & Studer (1993, p. 152), see Tab. A. 3 in the Appendix, 19

Direct field emissions and elementary flows in LCIs of agricultural production systems - Direct Field Emissions pesticides: FAW & BLW (2000), biomass (seed and products from plant production): Houba & Uittenbogaard (1994, 1995, 1996 & 1997), von Steiger & Baccini (1990) and Wolfensberger & Dinkel (1997); Bennett et al. (2000) & for Nickel Teherani (1987) for rice; generic mean of biomass for cotton due to lack of data with mass allocation to fibre and seed (Freiermuth 2006); see Tab. A. 1 in the Appendix. For grass seed, the values of wheat grains were used; for clover seed, the values of protein peas. Heavy metal emissions into ground and surface water (in case of drainage) are calculated with constant leaching rates as: M leach i = m leach i * A i M leach i agricultural related heavy metal i emission m leach i average amount of heavy metal emission (Tab. 2.18) A i allocation factor for the share of agricultural inputs in the total inputs for heavy metal i Tab. 2.18 Heavy metal leaching to groundwater according to Wolfensberger & Dinkel (1997). Cd Cu Zn Pb Ni Cr Hg mg/ha/year 50 3600 33000 600 n.a. 21200 1.3 Heavy metal emissions through erosion are calculated as follows: M erosion i = c tot i * B * a *f erosion * A i M erosion agricultural related heavy metal emissions through erosion [kg ha -1 a -1 ] c tot i total heavy metal content in the soil (Keller & Desaules 2001, see Tab. 2.19 [kg/kg]) B amount of soil erosion according to Oberholzer et al. (2006) [kg ha -1 a -1 ] a accumulation factor 1.86 (according to Prasuhn 2006 for P) [-] f erosion erosion factor considering the distance to river or lakes with an average value of 0.2 (considers only the fraction of the soil that reaches the water body, the rest is deposited in the field) [-] A i allocation factor for the share of agricultural inputs in the total inputs for heavy metal i [-] Tab. 2.19 Heavy metal contents in mg per kg soil (from Keller & Desaules 2001). Land use Cd [mg/kg] Cu [mg/kg] Zn [mg/kg] Pb [mg/kg] Ni [mg/kg] Cr [mg/kg] Hg [mg/kg] Permanent grassland 0.309 18.3 64.6 24.6 22.3 24.0 0.088 Arable land 0.24 20.1 49.6 19.5 23.0 24.1 0.073 Intensive crops 0.307 39.2 70.1 24.9 24.8 27.0 0.077 The balance of all inputs into the soil (fertilisers, pesticides, seed and deposition) and outputs from the soil (exported biomass, leaching and erosion), multiplied by the allocation factor is calculated as an emission to agricultural soil. M soil i = (Σ inputs i - Σ outputs i ) * A i Some of the values for emissions of heavy metals to the soil are negative. This means that more heavy metals are exported than imported. It must, however, be borne in mind that these heavy metals are transferred either to the water bodies or to the products harvested from the field (food, feed and straw). 20

Direct field emissions and elementary flows in LCIs of agricultural production systems - Direct Field Emissions A certain fraction of the heavy metal input into the soil stems from atmospheric deposition. The deposition would occur even without any agricultural production and is therefore not charged to the latter. An allocation factor accounts for this. The farmer is therefore responsible for a part of the inputs only (the rest stems mainly from other economic sectors), therefore only a part of the emissions is calculated in the inventory. A i = M agro i / (M agro i + M deposition i ) A i allocation factor for the share of agricultural inputs in the total inputs for heavy metal i M agro i total input of heavy metal from agricultural production in mg/(ha*year) (fertilisers + seeds + pesticides) M deposition i total input of heavy metal from atmospheric deposition in mg/(ha*year) (Tab. 2.20) In cases, where M agro i = 0, i.e. no agricultural inputs to the soil occur, A i also becomes 0. Tab. 2.20 Heavy metal deposition (see Freiermuth 2006). Cd Cu Zn Pb Ni Cr Hg Deposition [mg/ha/year] 700 2400 90400 18700 5475 3650 50 2.9 Emissions of Pesticides to Agricultural Soil All pesticides applied for crop production were assumed to end up as emissions to the soil. The amounts of pesticides used as inputs were thus simultaneously calculated as outputs (emissions to agricultural soil). For many active ingredients there are no own LCIs; in these cases, the amounts of active ingredients are aggregated and inventoried by their chemical class, for which an LCI exists, as assigned in Sutter (2010, Tab. 2.25). As emissions, though, the active ingredients appear under their specific name. Only for the inputs pesticides, unspecified, fungicides, unspecified and insecticides, unspecified, no corresponding emission flow could be assigned. Field emissions resulting from these admittedly small quantities of substances were thus not considered. 21