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«International 17 Workshop th Nitrogen The was jointly organised by Teagasc and AFBI Printed by Print Depot Suggested citation Authors, 2012. Title ...»

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Zillmann, E., Graeff, S., Link, J., Batchelor, W.D. and Claupein W. 2006. Assesment of cereal nitrogen requirements derived by optical on-the-go sensors on heterogeneous soils. Agron. J. 98, 682-690.

Nitrogen Workshop 2012

Processes of nitrate-N loss to streamflow from intensive cereal crop catchments in Ireland Melland, A.R.a, Mellander, P-E.a Murphy, P.N.C.a, Wall, D.P.a, Mechan, S.a, Shine, O.a, Shortle, G.a, Jordan, P.b a Agricultural Catchments Programme, Teagasc, Johnstown Castle, Environmental Research Centre, Co Wexford, Rep.

of Ireland b School of Environmental Sciences, University of Ulster, Coleraine, N. Ireland

1. Background & Objectives Whilst cereal crops constitute only 7% of land use in Ireland, yields are amongst the highest in the world (Spink and Kennedy, 2012) and food production targets require yields to be sustained or increased into the future (Anon., 2010). At the same time, EU Water Framework Directive water quality targets must be met. Losses of total oxidised nitrogen (TON) to stream water in two intensive arable catchments with contrasting hydrological characteristics were monitored within an Agricultural Catchments Programme (Wall et al., 2011) to help identify opportunities for environmentally sustainable yield increases.

2. Materials & Methods Monitoring was conducted from October 2009 to September 2011 in a 9.5 km2 catchment with predominantly well-drained soils and 45% of land use under spring barley (Arable A), and in a 11.2 km2 catchment on moderate to poorly-drained soils (Arable B) farmed for winter wheat and barley (24%) and dairy and beef (47%). Monthly spatial surveys of stream and surface ditch nitrate-N concentrations were conducted. Groundwater was sampled monthly at multiple depths from 1 to 52 m below ground along two representative hillslope transects within each catchment. Stream discharge and TON concentrations were measured on a sub-hourly basis at the catchment outlet using a flow-rated water level recorder for discharge and an in situ calibrated UV sensor for TON.

3. Results & Discussion In Arable A, stream outlet TON concentrations were diluted in elevated flows and baseflow concentrations remained relatively stable and below drinking water standards (Figure1a). There was little spatial variation in stream water nitrate-N concentrations and the concentrations reflected those in connected near-stream and midslope groundwater (Figure 2a). In Arable B, TON concentrations were also diluted during elevated flow. Surprisingly, given the moderate-poorly drained nature of much of the catchment, and therefore a lower potential for N leaching, baseflow TON concentrations were similar to those in Arable A during winter (Figure 1b). During spring and summer, however, TON concentrations decreased markedly. There was a trend for decreasing stream nitrate-N concentrations towards the catchment outlet and neither groundwater nor tributary nitrate-N concentrations were reflected in the stream water concentrations (Figure 2b). Instead, it was hypothesised that a ‘critical source’ sub-catchment area, where springs and ephemeral surface ditches rich in nitrate-N emerged, contributed nitrate to the stream. It was hypothesized that nitratepoor groundwater from upper landscape areas emerged in low-lying areas over poorly-drained gley soils and interacted with rootzone N before discharging to ditches and the stream. The seasonally low concentrations in Arable B were attributed to seasonal disconnection of these localised N sources. It is less likely that lower stream TON concentrations were due to depleted rootzone N during the growth season because the ephemeral nature of the monitored ditch, and the low temporal variance in high concentrations from the perennial spring, would not support this hypothesis. Annual stream loads of TON varied from 15.5 to 34.7 kg ha-1 across the catchments.

The potential downstream ecological impact of the observed TON loads requires investigation.

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Figure 2. Monthly mean and standard error nitrate-N concentrations (mg L-1) of stream water in the main streams (main), tributaries (Trib), ephemeral ditches (Eph), lake outfalls (Lake) and near-stream and midslope groundwater (Gw), at representative sites upstream of the catchment outlets in a) Arable A and b) Arable B.

Drinking water (solid line) and groundwater (dashed line) maximum acceptable concentrations are shown

4. Conclusion Whilst the ecological impact of observed TON loads on downstream estuarine waters is not known, the processes of TON loss indicated that in both catchments further reductions in TON transfer to streams would require depletion of diffuse N stores that are connected to the stream. It was hypothesized that these N stores were localised in near-surface depths of a critical N source area in the mixed soil type catchment of Arable B, and that N stores were catchment-wide in the subsoil of Arable A.

Acknowledgement We acknowledge funding from the Irish Department of Agriculture Food and Marine.

References Anon. 2010. Food Harvest 2020. Department of Agriculture Fisheries and Food, Dublin, Ireland.

Spink, J. and Kennedy, S. 2012. Explaining cereal yields in 2011 In National Tillage Conference 2012, Teagasc, 25th January 2012. p 17-25, Carlow, Ireland.

Wall D, Jordan P, Melland AR, Mellander P-E, Reaney S. and Shortle G. 2011. Using the nutrient transfer continuum concept to evaluate the European Union Nitrates Directive National Action Programme. Environmental Science & Policy 14, 664-674.

Nitrogen Workshop 2012

GHG balance of bioenergy cropping systems under the environmental conditions of northern Germany Claus, S.a, Wienforth, B.b, Svoboda, N.c, Sieling, K.b, Kage, H.b, Senbayram, M.d, Dittert, K.e, Taube F.a, Herrmann A.a Christian-Albrechts-University of Kiel, Kiel, Germany a Institute of Crop Science & Plant Breeding, Grass and Forage Science/Organic Agriculture b Institute of Crop Science & Plant Breeding, Agronomy and Crop Science c Leibnitz Centre for Agricultural Landscape Research, Müncheberg, Germany d YARA GmbH & Co. KG, Dülmen, Germany e Georg-August-Ernst University of Göttingen, Institute of Applied Plant Nutrition, Göttingen, Germany

1. Background & Objectives Due to a considerable expansion of biogas plants (500 mid of 2011) and the resulting expansion of maize production, criticism on biogas production and its GHG mitigation potential has been voiced recently. Although various studies on Life Cycle Assessment (LCA) of biogas production are available, the majority are estimates only based on literature data, especially with regard to greenhouse gas (GHG) balance. Furthermore, data for northern Germany are generally limited. To overcome these limitations a 2-year field trial was conducted to evaluate the GHG mitigation potential and to generate a GHG balance for a LCA to come.

2. Materials & Methods

A 2-year field trial (2007-2009) was conducted at two experimental sites of Kiel University:

Hohenschulen (HS) and Karkendamm (KD). The annual precipitation at HS averages 750 mm with a daily temperature of about 8.3°C. The soil is classified as a pseudogleyic Luvisol of sandy loam structure. The annual precipitation at KD averages 844 mm with a daily temperature of about 8.3°C.

The soil is classified as a gleyic Podzol of sandy sand structure. Altogether three cropping systems have been investigated: maize monoculture and a maize–whole crop wheat–Ital. ryegrass rotation at HS, while maize monoculture and a four-cut permanent grassland were tested at KD. The plots were laid out in a randomised block design. N-fertiliser was applied at four levels (maize, wheat: 0, 120, 240, 360 kg N ha-1; grassland: 0, 160, 320, 480 kg N ha-1) and different N types: calcium ammonium nitrate (CAN) and biogas residue from co-fermentation. GHG balances were calculated according to the life cycle inventory analysis provided by the ISO guidelines 14044 (2006). The calculations are based on the energy balance by Claus et al. (2010), direct N2O emissions presented by Senbayram et al. (2009) and estimates of indirect N2O emissions based on measurements of NH3 emissions by Gericke (2009). All measurements were taken on the above named field sites.

Changes in soil carbon stocks have been considered according to German cross compliance commitments. For conversion a biogas plant (500 kW), with an electric efficiency of 40%, a thermal efficiency of 41.5% and a heat utilization of 45% was assumed. Energy demand for plant operation was assumed to be 20% of the generated electricity for heat and 7.5% for electricity. The relation of N input to total emission of CO2eq. from electricity and heat generation was quantified by an exponential function. The GHG emissions of energy production from biogas were compared to a reference system based on fossil sources (electricity: 0.72 kg CO2eq./kWh, heat: 0.31 kg CO2eq./kWh).

3. Results & Discussion The comparison of cropping systems at Hohenschulen revealed noticeably higher GHG

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emissions for the production of energy and heat from maize monoculture than from the maize– whole crop wheat–Ital. ryegrass rotation (Figure 1a). In agreement, higher total GHG emissions were found for maize monoculture than for permanent grassland at Karkendamm (Figure 1b). The higher emissions were caused by much higher N2O fluxes during maize cultivation (Senbayram et al., 2009). Due to higher dry matter yield, however, maize monoculture resulted in highest GHG saving potential at both experimental sites, as also reported by Gerin et al. (2008).

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The comparison of fertiliser types showed less pronounced differences for the emission of greenhouse gases (not shown). In contrast to N type, the experimental site had a considerable impact. GHG emissions of maize monoculture grown at HS exceeded those at KD by 2000 kg CO2 eq. ha-1. This could be traced back to a soil texture effect, where at the loamy soil site Hohenschulen N2O emissions were at least 3 times higher than at the sandy soil site Karkendamm (Senbayram et al., 2009).

4. Conclusion Considering the whole production chain, maize monoculture revealed a higher GHG mitigation potential than the other systems investigated. The type of N-fertilizer had no impact on the GHG emission and mitigation potential, whereas a pronounced influence of local soil conditions was observed.

References Claus, S., Wienforth, B., Sieling, K., Kage, H., Taube, F. and Herrmann, A. 2011. Energy balance of bioenergy cropping systems under the environmental conditions of Schleswig-Holstein. In: Grassland Farming and Land Management Systems in Mountainous Regions. Grassland Science in Europe 16, 365-367.

DIN NORM EN ISO 14044 2006: Umweltmanagement - Ökobilanz - Anforderungen und Anleitungen Gericke, D. 2009: Measurement and modelling of ammonia emissions after field application of biogas slurries. Doctoral thesis, Christian-Albrechts-Universität zu Kiel, Germany.

Gerin, P., Vliegen, F. and Jossart, J. 2008. Energy and CO2 balance of maize and grass as energy crops for anaerobic digestion. Bioresource Technology 99, 2620-2627.

Senbayram, M., Chen, R., Mühling, K.H. and Dittert, K. 2009. Contribution of nitrification and denitrification-derived nitrous oxide emissions from soil after application of biogas waste compared to other fertilizers. Rapid Communication in Mass Spectrometry 23, 2489-2498.

Nitrogen Workshop 2012 Animal delivery of the nitrification inhibitor DCD as a new effective method for reducing nitrogen losses from grazed pastures Ledgard, S.F., Welten, B.G., Luo, J.

AgResearch Ruakura Research Centre, Private Bag 3123, Hamilton 3240, New Zealand

1. Background & Objectives Nitrification inhibitors can be used to reduce the conversion of ammonium to nitrate in soil, thereby reducing the potential for nitrogen (N) losses by nitrate leaching and nitrous oxide (N2O) emissions (e.g. Amberger, 1989). In New Zealand the nitrification inhibitor DCD is now being used commercially on dairy farms by broadcasting it onto grazed pasture within about one week of grazing over the winter period when the risk of N losses is high. The aim of this is that it can act on urine-N excreted by animals, which is the major source of both nitrate leaching and N2O emissions. Ledgard et al. (2008) developed the concept of administering the DCD directly to animals so that it is excreted in the urine patches by animals and so can act directly on reducing losses from the urine-N. This makes it a more targeted method that requires less DCD in total and is potentially much more cost-effective. Previous research indicated that most of the DCD administered to sheep or cattle was excreted in urine in an unaltered form (Ledgard et al., 2008). The objective of this paper is to present research on evaluation of this approach by application of DCD in water troughs for consumption by dairy cows to reduce N losses from urine excreted on grazed pastures in autumn/winter.

2. Materials & Methods A grazing system trial on ryegrass/white clover pasture in the Waikato region of New Zealand was set up with two treatments. One was the standard practice on the dairy farm and the other was the same except that dairy cows were given access to a water trough in which DCD was added. The rate of DCD addition was based on a review of typical water intake and the rate of DCD required in relation to the typical urination volume, frequency and affected area. Two groups of dairy cows (20/treatment) separately grazed 12 pairs of randomly-allocated plots (c. 630 m2) corresponding to the two treatments as part of their standard rotation on the farm. The cows went

through two grazing rotations in late-autumn and late-winter. Measurements included:

i. assessment of the rate of DCD returned in urine patches. This was based on identification of urine patches after deposition and soil sampling to determine the rate of DCD returned in the urine patches. ii. nitrate leaching using ten ceramic cup samplers per plot (i.e. 120 per treatment) and collection of leachate at intervals corresponding with approximately 50 mm drainage for analysis of inorganic N.

Drainage volume was estimated using water budget modelling. iii. N2O emissions measured at regular intervals using randomly allocated cover plots within each treatment over time after grazing events.

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