Emission of Gas and Dust from Livestock
QUANTIFICATION OF SMALL SCALE NITROUS OXIDE EMISSIONS AND COMPARISON WITH FIELD-SCALE EMISSIONS OF A ROTATIONAL GRAZING SYSTEM
AMMANN, C.1, VOGLMEIER, K.1,2, JOCHER, K.1, MENZI, H.3
1 Agroscope Research Station, Climate and Air Pollution, Zürich, Switzerland
2 ETH Zürich, Institute of Agricultural Sciences, Zürich, Switzerland
3 Agroscope Research Station, Ruminant Nutrition, Posieux, Switzerland
ABSTRACT: The present study investigated the contribution of fresh dung and urine patches and other background areas to the total N2O emissions of a grazed pasture system in Switzerland. For this purpose small-scale chamber measurements were compared to field scale eddy covariance measurement of N2O fluxes. It was found that urine patches are strong hotspots of N2O emissions and contribute a dominant share (about 60%) to the overall pasture emission during grazing periods. A simple up-scaling showed a fair agreement of average emissions observed by the two methods. Short-term deviations between the methods indicate a strong effect of soil moisture conditions.
Keywords: N2O, grazing, chamber method, eddy covariance method, urine patches
INTRODUCTION: While grazed pastures are considered as advantageous for the animal welfare as well as for a minimised NH3 emission (Voglmeier et al., this issue), they are potentially strong sources of the greenhouse gas nitrous oxide (N2O), particularly for productive systems with additional fertilisation application (Flechard et al., 2007). The uneven spatial distribution of the excretion of the grazing animals can lead to local emission hot-spots. Especially urine patches can result in a high local nitrogen surplus, which can only partly be taken up by nearby plants (Moir et al., 2011). The strong spatial and temporal variability of the gaseous emissions represents an inherent problem for the quantification of gaseous emissions from pastures. For this reason, micrometeo-rological methods that integrate emissions over a larger domain like the eddy covariance (EC) method are well suited to quantify the total N2O emissions of grazed fields. In contrast, chamber methods are better suited to study the underlying processes and to measure the spatial and temporal variability of individual emission sources (urine and dung patches). We present first results of a pasture field experiment with grazing dairy cows in 2016 where N O fluxes were measured continuously with the EC method
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dyne Research Inc, Billerica, USA) for N2O quantification. Data from both instruments were recorded synchronously at 10 Hz. Small scale emissions of N2O from dung and urine patches as well as from 'background' surface areas were quantified on multiple days after grazing using an optimized chamber technique. These so called 'fast box' measurements (Hensen et al., 2006) also made use of the fast QCL instrument for N2O detection and allowed to measure a flux value within 60-120 s. The measurements were carried out on selected intensive observation areas within the pasture. The appropriate interpretation of the fast-box measurements required information about the location and distribution of the excreta patches of the grazing cows. While fresh dung pads could be identified visually, urine patches were detected using a soil dielectric conductivity sensor. It was manually operated with a spatial resolution of 0.25 m. Figure 1 shows an example of the obtained distribution of dung and urine patches shortly after a grazing phase. The dielectric conductivity turned out to be a very distinctive indicator for the presence of urine in the soil during more than 10 days after deposition.
Figure 1. Distribution of fresh dung pads (crosses) and urine patches represented by increased soil dielectric conductivity (gray scale with units of dS m-1) on a 15 x 15 m intensive observation sub-plot.
2. RESULTS AND DISCUSSION: More than 1000 individual flux measurements with the fast-box were performed on 46 days between July and October 2016. The resulting average small-scale N2O emission fluxes are plotted in Figure 2 as a function of time since last grazing (corresponding to the age of investigated urine and dung patches).
Directly after grazing, urine patches showed by far the highest emissions, more than an order of magnitude higher than dung patches and background pasture areas. However the urine patch emissions exhibited an approximately exponential decay with an e-folding time of 13 days, while there were only minor temporal changes for dung pads and background areas. It has to be taken into account that the displayed values are averages over space and time (different grazing rotations) with different weather and soil conditions. Therefore the scatter of individual values was high.
Measurement methods
Figure 2. Average N2O emissions for urine patches, dung pads and other areas (background) of the pasture observed by the fast-box measurements between July and October 2016 plotted as a function of time since the last grazing period (age of excreta). Vertical bars indicate the standard error for each time class.
In order to estimate the integral contribution of the three pasture surface sources (urine patches, dung pads, and background area) to the total N2O emission, a simple upscaling calculation was made. It is based on rough estimates of the number of urine and dung patches deposited per cow and grazing day. Using typical values for N excretion for the local cow type (see Felber et al., 2016) and a typical literature value of 20 g N for the content of a single urination event (Misselbrook et al., 2016) resulted in an average number density for urine patches of 500 ha-1 d-1. For dung pads a 25% higher number density was assumed. When integrated over a 30-day period, this resulted in average N2O emission contributions from the different sources of 78 g N2O-N ha-1 (urine), 18 g N2O-N ha-1 (dung), and 40 g N2O-N ha-1 (background). Thus for grazing periods (including the following regrowth) urine patches contribute more than half to the pasture emissions, but the other sources are not negligible.
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For comparison of the fast-box results with the field-scale EC emission measurements, the fast-box measurements were up-scaled to the EC footprint area (Häni, 2017) with the simple assumptions described above for each half hour. The results for two monthly periods are shown in Figure 3. The emissions derived by the two methods show a satisfying agreement concerning their average magnitude. However, the variability of the up-scaled fast-box fluxes is generally small, as it is mainly caused by the temporal decay of urine contributions (see Fig. 2). The EC fluxes, in contrast, exhibit a much larger variation that is related to changing soil water content. Fluxes are smallest for very low and very high soil water content and highest in between.
3. CONCLUSION: Manual fast-box and continuous EC flux measurements have been performed on a grazed pasture. It was found that urine patches are strong hotspots of N2O emissions and contribute a dominant share to the overall pasture flux during grazing periods. A simple up-scaling leads to fair agreement of average emissions observed by fast-box and EC. Deviations between the methods can be attributed mainly to the effect of soil moisture conditions, which was not considered in the fast-box up-scaling method applied here. This needs to be improved in a more detailed evaluation. For deriving excreta-specific N2O emission factors, a (conceptually) well defined approach to separate the longer term effects of excreta and other fertilisation activities will be necessary.
Acknowledgements. The financial support through project grants of the Swiss National Science Foundation (project NICEGRAS) is gratefully acknowledged. We also thank the many colleagues that supported the field measurements. nitrous oxide emissions in grassland systems across Europe. Agric. Ecosys. Environ., 121, 135-152.
Häni, C., 2017. bLSmodelR - An atmospheric dispersion model in R. R package version 2.4.1. URL: www.agrammon.ch/documents-to-download/blsmodelr/ (last access 21 April 2017).
Hensen A., Groot T.T., van der Bulk W.C.M., Vermeulen A.T., Olesen J., Schelde E.K., 2006.
Dairy farm CH4 and N2O emissions, from one square metre to the full farm scale.
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Misselbrook, T., Fleming, H., Camp, V., Umstatter, C., Duthie, C.-A., Nicoll, L., Waterhouse, T., 2016. Automated monitoring of urination events from grazing cattle, Agric. Ecosys. Environ., 230, 191–198.
Moir J.L., Cameron K.C., Di H.J., Fertsak U., 2011. The spatial coverage of dairy cattle urine patches in an intensively grazed pasture system. J. Agric. Sci., 149, 473-485.
Voglmeier K., Häni C., Jocher M., Ammann C., 2017. Ammonia emission measurements of an intensively grazed pasture (this issue).
Measurement methods
QUANTIFYING AMMONIA EMISSIONS FROM FARM-SCALE SOURCES USING AN