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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

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doi:10.5194/amt-2016-350
© Author(s) 2016. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
09 Dec 2016
Review status
This discussion paper is under review for the journal Atmospheric Measurement Techniques (AMT).
Ammonia emissions from a grazed field estimated by miniDOAS measurements and inverse dispersion modelling
Michael Bell1, Christophe Flechard1, Yannick Fauvel1, Christoph Häni2, Jörg Sintermann3,a, Markus Jocher3, Harald Menzi4, Arjan Hensen5, and Albrecht Neftel3,b 1INRA, Agrocampus Ouest, UMR 1069 SAS, Rennes, France
2Bern University of Applied Sciences, School of Agricultural, Forest and Food Sciences, CH-3052 Zollikofen, Switzerland
3Agroscope - Institute for Sustainability Science, Zürich, Switzerland
4Federal Research Station Agroscope, Inst. For Livestock Sciences, 1725 Posieux, Switzerland
5Energy research Centre of the Netherlands (ECN), Petten, The Netherlands
anow at AWEL, Zürich, Switzerland
bnow at Neftel research Expertise, C-3033 Wohlen b. Bern, Switzerland
Abstract. Ammonia (NH3) fluxes were estimated from a field being grazed by dairy cattle during spring, by applying a backward-Lagrangian Stochastic model (bLS) model combined with horizontal concentration gradients measured across the field. Continuous concentration measurements at field boundaries were made by open-path miniDOAS (differential optical absorption spectroscopy) instruments, during the cattle’s presence and for 6 subsequent days. The deposition of emitted NH3 to ‘clean’ patches on the field was also simulated, allowing both ‘net’ and ‘gross’ emission estimates, where the dry deposition velocity (vd) was predicted by a canopy resistance (Rc) model developed from local NH3 flux and meteorological measurements. Estimated emissions peaked during grazing and decreased after the cattle had left the field, while control on emissions was observed from covariance with temperature, wind speed and humidity/wetness measurements made on the field, revealing a diurnal emission profile. Large concentration differences were observed between downwind receptors, due to spatially heterogeneous emission patterns. This was caused by uneven cattle distribution and a low grazing density, where ‘hotspots’ of emissions would arise as the cattle grouped in certain areas, such as around the water trough. The spatial complexity was accounted for by separating the model source area into sub-sections, and optimising individual source area coefficients to measured concentrations. The background concentration was the greatest source of uncertainty, and based on a sensitivity/uncertainty analysis the overall uncertainty associated with derived emission factors from this study is at least 30–40 %. Emission factors can be expressed as 6 ± 2 g NH3 cow−1 day−1, or 9 ± 3 % of excreted urine-N emitted as NH3, when deposition is not simulated, and 7 ± 2 g NH3 cow−1 day−1, or 10 ± 3 % excreted urine-N emitted as NH3 when deposition is included in the gross emission model. The results suggest that around 14 ± 4 % of emitted NH3 was deposited to patches within the field that were not affected by urine or dung.

Citation: Bell, M., Flechard, C., Fauvel, Y., Häni, C., Sintermann, J., Jocher, M., Menzi, H., Hensen, A., and Neftel, A.: Ammonia emissions from a grazed field estimated by miniDOAS measurements and inverse dispersion modelling, Atmos. Meas. Tech. Discuss., doi:10.5194/amt-2016-350, in review, 2016.
Michael Bell et al.
Michael Bell et al.
Michael Bell et al.

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Short summary
This study applies horizontal concentration gradient measurements and inverse dispersion modelling to evaluate ammonia emissions from cattle grazing. The results can contribute to an emission factor for cattle grazing, where emissions where found to be towards the lower end of the range found in the limited number of existing studies. The influences of ammonia deposition, uneven urine patch distribution and climate conditions are discussed.
This study applies horizontal concentration gradient measurements and inverse dispersion...
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