Ammonia (NH3) emission from animal manure contributes to air pollution and ecosystem degradation, and the loss of reactive nitrogen (N) from agricultural systems. Estimates of NH3 emission are necessary for national inventories and nutrient management, and NH3 emission from field-applied manure has been measured in many studies over the past few decades. In this work, we facilitate the use of these data by collecting and organizing them in the ALFAM2 database. In this paper we describe the development of the database and summarise its contents, quantify effects of application methods and other variables on emission using a data subset, and discuss challenges for data analysis and model development. The database contains measurements of emission, manure and soil properties, weather, application technique, and other variables for 1899 plots from 22 research institutes in 12 countries. Data on five manure types (cattle, pig, mink, poultry, mixed, as well as sludge and "other") applied to three types of crops (grass, small grains, maize, as well as stubble and bare soil) are included. Application methods represented in the database include broadcast, trailing hose, trailing shoe (narrow band application), and open slot injection. Cattle manure application to grassland was the most common combination, and analysis of this subset (with dry matter (DM) limited to <15%) was carried out using mixed-and fixed-effects models in order to quantify effects of management and environment on ammonia emission, and to highlight challenges for use of the database. Measured emission from cattle slurry ranged from < 1% to 130% of applied ammonia after 48 hours. Results showed clear, albeit variable, reductions in NH3 emission due to trailing hose, trailing shoe, and open slot injection of slurry compared to broadcast application. There was evidence of positive effects of air temperature and wind speed on NH3 emission, and limited evidence of effects of slurry DM. However, random-effects coefficients for differences among research institutes were among the largest model coefficients, and 4 showed a deviation from the mean response by more than 100% in some cases. The source of these institute differences could not be determined with certainty, but there is some evidence that they are related to differences in soils, or differences in application or measurement methods. The ALFAM2 database should be useful for development and evaluation of both emission factors and emission models, but users need to recognize the limitations caused by confounding variables, imbalance in the dataset, and dependence among observations from the same institute. Variation among measurements and in reported variables highlights the importance of international agreement on how NH3 emission should be measured, along with necessary types of supporting data and standard protocols for their measurement. Both are needed in order to produce more accurate and useful ammonia emission measurements. Expansion of the ALFAM2 database will continue, and readers are invited...

Abstract. Tropospheric ammonia (NH 3 ) is a threat to the environment and human health and is mainly emitted by agriculture. Ammonia volatilisation following application of nitrogen in the field accounts for more than 40 % of the total NH 3 emissions in France. This represents a major loss of nitrogen use efficiency which needs to be reduced by appropriate agricultural practices. In this study we evaluate a novel method to infer NH 3 volatilisation from small agronomic plots consisting of multiple treatments with repetition. The method is based on the combination of a set of NH 3 diffusion sensors exposed for durations of 3 h to 1 week and a shortrange atmospheric dispersion model, used to retrieve the emissions from each plot. The method is evaluated by mimicking NH 3 emissions from an ensemble of nine plots with a resistance analogue-compensation point-surface exchange scheme over a yearly meteorological database separated into 28-day periods. A multifactorial simulation scheme is used to test the effects of sensor numbers and heights, plot dimensions, source strengths, and background concentrations on the quality of the inference method. We further demonstrate by theoretical considerations in the case of an isolated plot that inferring emissions with diffusion sensors integrating over daily periods will always lead to underestimations due to correlations between emissions and atmospheric transfer. We evaluated these underestimations as −8 % ± 6 % of the emissions for a typical western European climate. For multiple plots, we find that this method would lead to median underestimations of −16 % with an interquartile [−8-22 %] for two treatments differing by a factor of up to 20 and a control treatment with no emissions. We further evaluate the methodology for varying background concentrations and NH 3 emissions patterns and demonstrate the low sensitivity of the method to these factors. The method was also tested in a real case and proved to provide sound evaluations of NH 3 losses from surface applied and incorporated slurry. We hence showed that this novel method should be robust and suitable for estimating NH 3 emissions from agronomic plots. We believe that the method could be further improved by using Bayesian inference and inferring surface concentrations rather than surface fluxes. Validating against controlled source is also a remaining challenge.

Abstract. Three different nitrogen (N) fertiliser types, ammonium nitrate, urea and urea coated with a urease inhibitor (Agrotain®), were applied at standard rates (70 kg N ha−1) to experimental plots in a typical and intensively managed grassland area at the Easter Bush Farm Estate (Scotland). The nitrogen use efficiency of the fertilisers was investigated as well as nitrogen losses in the form of nitrous oxide fluxes (N2O) and ammonia (NH3) during fertilisation events in the 2016 and 2017 growing seasons. Nitrous oxide was measured by the standard static chamber technique and analysed using Bayesian statistics. Ammonia was measured using passive samplers combined with the Flux Interpretation by Dispersion and Exchange over Short Range (FIDES) inverse dispersion model. On average, fertilisation with ammonium nitrate supported the largest yields and had the highest nitrogen use efficiency, but as large spatial and seasonal variation persisted across the plots, yield differences between the three fertiliser types and zero N control were not consistent. Overall, ammonium nitrate treatment was found to increase yields significantly (p value < 0.05) when compared to the urea fertilisers used in this study. Ammonium nitrate was the largest emitter of N2O (0.76 % of applied N), and the urea was the largest emitter of NH3 (16.5 % of applied N). Urea coated with a urease inhibitor did not significantly increase yields when compared to uncoated urea; however, ammonia emissions were only 10 % of the magnitude measured for the uncoated urea, and N2O emissions were only 47 % of the magnitude of those measured for ammonium nitrate fertiliser. This study suggests that urea coated with a urease inhibitor is environmentally the best choice in regards to nitrogen pollution, but because of its larger cost and lack of agronomic benefits, it is not economically attractive when compared to ammonium nitrate.

Abstract. Tropospheric ammonia (NH 3 ) is a threat to the environment and human health and is mainly emitted 9 by agriculture. Ammonia volatilisation following application of nitrogen in the field accounts for more than 40% 10 of the total ammonia emissions in France. This hence represents a major loss of nitrogen use efficiency which 11 needs to be reduced by appropriate agricultural practices. In this study we evaluate a novel method to infer 12 ammonia volatilisation from small agronomic plots made of multiple treatments with repetition. The method is 13 based on the combination of a set of ammonia diffusion sensors exposed for durations of 3 hours to 1 week, and 14 a short-range atmospheric dispersion model, used to retrieve the emissions from each plot. The method is 15 evaluated by mimicking ammonia emissions from an ensemble of 9 plots with a resistance-analogue-16 compensation-point surface exchange scheme over a yearly meteorological database separated into 28-days 17 periods. A multi-factorial simulation scheme is used to test the effects of sensor number and heights, plot 18 dimensions, source strengths and background concentrations, on the quality of the inference method. We further 19 demonstrate by theoretical considerations in the case of an isolated plot that inferring emissions with diffusion 20 sensors integrating over daily periods will always lead to underestimations due to correlations between emissions 21 and atmospheric transfer. We evaluated these underestimations as -8% ± 6% of the emissions for a typical 22 western European climate. For multiple plots, we find that this method would lead to median underestimations of 23 -16% with an interquartile [-8% -22%] for two treatments differing by a factor of up to 20 and a control 24 treatment with no emissions. We further evaluate the methodology for varying background concentrations and 25ammonia emission patterns and demonstrate the low sensitivity of the method to these factors. The method was 26 also tested in a real case and proved to provide sound evaluations of ammonia losses from surface applied and 27 incorporated slurry. We hence showed that this novel method should be robust and suitable for estimating 28 ammonia emissions from agronomic plots. Further work should anyway be produced for validating this method 29 in real conditions. 30 31

&lt;p&gt;&lt;strong&gt;Abstract.&lt;/strong&gt; Three different nitrogen fertilizer types, ammonium nitrate, urea and urea coated with a urease inhibitor (Agrotain&lt;sup&gt;&amp;#174;&lt;/sup&gt;), were applied at standard rates (70&amp;#8201;kg&amp;#8201;N&amp;#8201;ha&lt;sup&gt;&amp;#8722;1&lt;/sup&gt;) to experimental plots in a typical and intensively managed grassland area at Easter Bush Farm Estate (Scotland). The nitrogen use efficiency of the fertilisers was investigated as well as nitrogen losses in the form of nitrous oxide fluxes (N&lt;sub&gt;2&lt;/sub&gt;O) and ammonia (NH&lt;sub&gt;3&lt;/sub&gt;) and during fertilisation events in the 2016 and 2017 growing seasons. Nitrous oxide was measured by the standard static chamber technique and analysed using Bayesian statistics. Ammonia was measured using passive samplers combined with the FIDES inverse dispersion model. On average, fertilisation with ammonium nitrate supported largest yields and had the highest nitrogen use efficiency, but as large spatial and seasonal variation persisted across the plots, yield differences between the three fertilizer types and zero N control were not consistent. Overall, ammonium nitrate treatment was found to increase yields significantly (p-value&amp;#8201;&lt;&amp;#8201;0.05) when compared to the urea fertilisers. Ammonium nitrate was the largest emitter of N&lt;sub&gt;2&lt;/sub&gt;O (0.76&amp;#8201;% of applied Nr) and the urea was the largest emitter of NH&lt;sub&gt;3&lt;/sub&gt; (16.5&amp;#8201;% of applied Nr). The urea coated with a urease inhibitor did not significantly increase yields; however, ammonia emissions were substantially smaller (90&amp;#8201;%) when compared to the uncoated urea and N&lt;sub&gt;2&lt;/sub&gt;O emissions were also smaller (47&amp;#8201;%) when compared with ammonium nitrate fertiliser. This study suggests that urea coated with a urease inhibitor is environmentally the best choice in regards to nitrogen pollution, but because of its larger cost and lack of agronomic benefits, it is not economically attractive when compared to ammonium nitrate.&lt;/p&gt;

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