«International 17 Workshop th Nitrogen The was jointly organised by Teagasc and AFBI Printed by Print Depot Suggested citation Authors, 2012. Title ...»
Vallejo, A., Skiba, U., Garcia-Torres, L., Arce, A., Lopez-Fernandez, S. and Sanchez-Martin, L. 2006. Nitrogen oxides emission from soils bearing a potato crop as inﬂuenced by fertilization with treated pig slurries and composts. Soil Biology and Biochemistry 38, 2782-2793.
Yeomans, J.C., Bremner, J.M. and McCarty, G.W. 1992. Denitrification capacity and denitrification potential of subsurface soils. Communications in Soil Science and Plant Analysis 23, 919-927.
Nitrogen Workshop 2012
Malting industry effluents as a source of nitrogen to soils Campaña H.a, Cordovil C.b, Benedetti Pa., Uribe Etchevarría Ma.,Airasca Aa., de Varennes A.b a GEIA – Grupo de Estudio de Ingeniería Ambiental – Facultad Regional Bahía Blanca- Universidad Tecnológica Nacional – 11 de Abril 461 – 8000 Bahía Blanca - Argentina b Biosystems Engineering Centre, Instituto Superior de Agronomia, TU Lisbon, Tapada da Ajuda, 1349-017, Lisbon, Portugal
1. Background & Objectives The amount of mineral nitrogen (N) applied to soil should be reduced whenever organic sources of the nutrient are available. A large number of studies have addressed the value of several sludges as sources of N, in particular sewage and pig sludges (Chantigny et al., 2004; Mora et al., 2005; Yague and Quilez, 2010; Antil et al., 2011). The malt industry generates effluents which could be applied to soil as organic amendment, but the amount of N that can be supplied from these sludges has not been investigated before. The objective of this paper is to provide preliminary information on the N fertiliser value of two types of sludges from a malt industry.
2. Materials & Methods In this experiment, two types of sludges were applied to a Mollisol from Cabildo, in the Province of Buenos Aires, Argentina. Both sludges came from the same barley malting plant, the first was an aerobic sludge from wastewater treatment that used an activated sludge process (A), and the second was the same sludge treated by a subsequent anaerobic digestion (AN). Soil without any amendment (C) and soil receiving the same amount of N as urea (U) were used as controls.
Nitrogen added was equivalent to 120 kg N ha-1 (0.32 g N for each pot amended or fertilized). The amount of soil used was approximately 2600 g per pot. The soils were incubated at room temperature and water added regularly to keep a constant moisture content. The effects on soil pH, electric conductivity (EC), and nitrate-N and ammonium-N were measured one week, and one and three months after amendment application.
3. Results & Discussion The application of urea led to the lowest pH both after one and three months of incubation, while the AN treatment had the greater initial pH (Figure 1). The decrease in pH derived from a rapid nitrification of N in urea, as discussed later. Three months after the beginning of the incubation no differences between unamended soil and that receiving both types of sludges were apparent.The EC increased due to the application of both organic amendments at the beginning of the experiment and after one month, but became similar in all treatments after three months of incubation, except for control unamended soil (Figure 1). Mineral N (both nitrate and ammonium) was greatest when urea was applied by comparison with the organic amendments. The amount of mineral N following urea application became the same as in all other three treatments after three months of incubation, suggesting that this was lost or converted into organic forms by soil microorganisms. The organic amendments did not lead to greater levels of mineral N suggesting that they act as slow release N fertilisers and may contribute to the pool of organic N in soils.
Figure 1.Values of pH, electric conductivity (EC), ammonium-N and nitrate-N during the incubation of a Mollisol with urea (U), aerobically digested sludge (A), aerobically digested sludge followed by an anaerobic digestion (AN) and control soil with any amendment (C).
4. Conclusion Both sludges from the malting industry can be used as slow release sources of N when applied to soils. Further studies are required to investigate their effects on plant growth.
References Antil, R.S., Bar-Tal, A., Fine, P. and Hadas, A. 2001 Predicting nitrogen and carbon mineralization of composted manure and sewage sludge in soil, Compost Science & Utilization 19, 33-43.
Chantigny, M.H., Angers, D.A., Morran, T. and Pomar, C. 2004 Dynamics of pig slurry nitrogen in soil and plants as determined with 15N, Soil Science Society of Amarica Journal 68, 637-643.
Mora, R., Paredes, C., Perez-Murcia, M.D., Perez-Espinosa, A. and Moreno-Caselles, J. 2005 Nitrogen dynamics in a calcic petrocalcic soil from the SE Spain treated with an anaerobic sewage sludge compost, Advances in Geoecology 36,589-594.
Yague, M.R. and Quilez, D. 2010 Response of maize yield, nitrate leaching, and soil nitrogen to pig slurry combined with mineral nitrogen, Journal of Environmental Quality 39, 686-696.
Nitrogen Workshop 2012
Managing nitrogen losses in shallow glacial aquifers: denitrifying bioreactors as a potential mitigation measure Ibrahim, T.G.a, Fenton O.a, Lanigan, G.J.a, Richards, K.G.a, Healy M.G.b a Teagasc Environment Research Centre, Johnstown Castle, Co. Wexford, Ireland b Civil Engineering, National University of Ireland, Galway, Co. Galway, Ireland
1. Background & Objectives Denitrifying bioreactors enhance the microbiologically-mediated reduction of nitrate (NO3-) in water using an organic carbon (orgC) rich media, to treat diffuse and point-sources of nitrogen (N).
They achieve high NO3- removal, have a long life-time, and are easier to manage and less-costly than larger bioremediation designs (Schipper at al., 2010). Healy et al. (2012) showed that such bioreactors also produce substantial amounts of greenhouse gases (GHG) and dissolved contaminants (“pollution swapping”, Figure 1c), with such losses mainly originating from the media in the initial operation period. The widespread installation of bioreactors at large scale in Irish farms will require the development of design criteria that allows for 1) high denitrification rates and 2) reduced ancillary pollution. The objectives of the study are to integrate gaseous and solute flux patterns in a field-scale bioreactor filled with woodchip and sand to reproduce transit times occurring in shallow drift aquifers. This paper focuses on the design of the experiment and describes the initial monitoring results.
Figure 1. a.
Map of the area. b. Top view schematic of the bioreactor. c. Pollution swapping components
2. Materials & Methods A reinforced plastic tank with water storage compartments and a base layer of gley soil was installed at the Teagasc Environment Research Centre, Co. Wexford, Ireland (Figure 1). The open section was divided in seven cells using plastic sheets pushed into the gley and leaving a 1 m width aperture on alternate sides of the tank. The woodchip was spread on a concrete surface and washed to reduce initial contaminant levels. Over two periods of nine days (Figure 2), it was regularly sprayed with pumped groundwater for circa one hour (“washing period”). Sprayed and leaching water were analysed for dissolved organic carbon (DOC), ammonium (NH4-N), dissolved reactive phosphorus (DRP) and chloride (Cl-). Next, the tank cells were alternatively filled with sand and washed woodchip (1 m thick). A set of injection/pumping wells and peristaltic pumps allowed for groundwater to circulate within the media (Figure 1). Within each cell, nests of wells (one well and one multi-level sampler with 3 depths of sampling) allowed for assessing changes in water table depth and groundwater hydrochemistry. Physiochemical parameters quantified included Cl-, NO3-, NH4-N, and Dinitrogen/Argon (N2/Ar) ratios. Gaseous emission fluxes to the atmosphere were monitored using static chambers installed on top of the media.
Figure 2. Changes in solute concentrations in leaching water out of the woodchip for the two washing periods
3. Results & Discussion Ammonium and DRP concentrations in leaching water strongly decreased during initial washes (7.19 to 0.06 mg L-1 and 6.77 to 0.84 mg L-1, respectively, Figure 2). Although DOC concentrations decreased during a washing event, they increased again between washes. After woodchip was installed in the bioreactor, high NO3- removal was achieved in the second cell of the tank (2.66 mg L-1 down to detection limits, Figure 3a). This removal was related to an increase in N2/Ar ratios at shallow and medium depth (10 and 40 cm, Figure 3b) indicating that complete denitrification occurred. Later variations in N2/Ar ratios could relate to degassing linked to the production of other gases in strongly reducing conditions (e.g. methane, data not shown). Ammonium concentrations strongly increased between the inlet and outlet of the tank (0.01 to 1.73 mg L-1, respectively, Figure 3c). Processes such as dissimilatory NO3- reduction to NH4+ (DNRA) may in part explain this pattern. Nevertheless, the strong increase in NH4-N in the deeper layers (70 cm in Figure 3c, up to
29.49 mg L-1 at nest 7) may indicate leaching from the gley soil or mineralisation of organic N.
Figure 3. Longitudinal and depth profiles (10, 40 and 70 cm below media top surface) of NO3-N, N2/Ar and NH4-N ratios in the bioreactor.
See Figure 1 for nest numbers
4. Conclusion Pre-washing of woodchip proves to be efficient to reduce initial contaminant losses, except for DOC. Assessing the coupling between gas and solute patterns at high spatial resolution within a bioreactor will allow for improved design criteria based on 1) identifying optimal transit times for high denitrification and low pollution swapping and 2) developing additional mitigation sequences to further limit losses of dissolved contaminants and GHGs from such bioreactors.
References Healy, M.G., Ibrahim, T.G., Lanigan, G., Serrenho, A. and Fenton, O. 2012. Effect of different carbon media on nitrate removal efficiency and pollution swapping in laboratory denitrifying bioreactors. Ecological Engineering 40, 198-209 Schipper, L.A., Robertson, W.D., Gold, A.J., Jaynes, D.B. and Cameron, S.C. 2010. Denitrifying bioreactors-An approach for reducing nitrate loads to receiving waters. Ecological Engineering 36, 11, 1532-1543
Nitrogen Workshop 2012
Methodology for the selection of the geographic location of new experimental sites and treatments to generate new N2O emission factors and data for model validation in the UK: the prioritisation phase of the InveN2Ory project.
Chadwick, D.a, Olave, R.b, Laughlin, R.b, Cardenas, L.a, Williams, J.c, Skiba, U.d, Rees, B.e, Buckingham, S.e, Topp, Ke and Anthony, S.c a North Wyke (Rothamsted Research), b AFBI Hillsborough, cADAS UK Ltd., dCEH Edinburgh and eSAC
1. Background & Objectives
The UK Government has challenging national commitments for the mitigation of greenhouse gas emissions. In order to improve the emissions estimates and increase the ability of the Agricultural GHG inventory to better reflect the country’s soils, climate, nitrogen (N) management of the range of farming systems, livestock breeds and diets, and take account of explicit mitigation strategies, the UK has funded a 5-year programme of research which in essence, will support the transition from a Tier 1 IPCC methodology for reporting, to a Tier 2 approach. The nitrous oxide (N2O) component of this programme is being co-ordinated via the InveN2Ory project, through a number of linked activities. The first of these being a prioritisation phase in which standard joint experimental protocols have been generated (to ensure new N2O fluxes are measured using the same approaches by the multiple research groups across the nine new experimental platforms), and the location of the new experimental sites has been confirmed. In this paper we describe the approach taken to determine where the geographical locations for these sites should be, and which experimental treatments should be included.
The project team made an initial ‘gap analysis’ prior to the proposal submission, of what additional N2O emission factors (EFs) from soils would be required to compliment the number of existing and already planned experiments under other government funded projects that will deliver IPCC compliant N2O EFs under UK conditions. In this paper we summarise the more complete ‘gap analysis’ that was carried out to confirm the selection of experimental platforms and treatments to compliment project modelling and the database of existing and planned EF data from current projects, in order to improve the N2O inventory from Tier 1 to Tier 2.
2. Materials & Methods A geographical assessment was made of the land area (ha) under the range of key soil texture-rainfall zone combinations for grassland and arable land in the UK. The sensitivity of the N2O EF to these combinations of soil texture and rainfall was assessed following typical N management on arable and grassland soils using the DNDC94 model (see Figure 1), and scaled indicative N2O EFs from soils were generated for these soil-rainfall-N management combinations. This generated information to establish the relative importance of the individual soil texture-rainfall zones to the total UK indicative N2O emission.
Additional information used in this assessment was provided by a collation of UK N2O EF from existing and planned experiments in current projects. Not all of these EF measurements could be used, as some were not IPCC compliant, i.e. were not of 12-month duration or did not include a non-amended control. These were our primary filters for removing experimental measurements and deriving a list of IPCC compliant EFs for the key N sources applied to agricultural soils (for grass and arable land). These current and planned N2O EFs were then ‘mapped’ onto the spatially explicit scaled indicative N2O emissions to generate an index of the number of EF measurements per unit of emission.
3. Results & Discussion The results of the sensitivity modelling (with DNDC) of N inputs on grassland to soil texture and rainfall are shown in figure 1.
Figure 1. Sensitivity of N2O emissions to soil texture (a), and rainfall (b), on grassland (modelled using DNDC94).