Ammonia emissions from a grazed field estimated by miniDOAS measurements and inverse dispersion modelling

Abstract

Abstract. Ammonia (NH 3 ) 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 while the cattle were present and for 6 subsequent days. The deposition of emitted NH 3 to "clean" patches on the field was also simulated, allowing both "net" and "gross" emission estimates, where the dry deposition velocity (v d ) was predicted by a canopy resistance (R c ) model developed from local NH 3 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 and 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 likely 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 NH 3 cow −1 day −1 , or 9 ± 3 % of excreted urine-N emitted as NH 3 , when deposition is not simulated and 7 ± 2 g NH 3 cow −1 day −1 , or 10 ± 3 % of excreted urine-N emitted as NH 3 , when deposition is included in the gross emission model. The results suggest that around 14 ± 4 % of emitted NH 3 was deposited to patches within the field that were not affected by urine or dung.

Process-based modelling of NH<sub>3</sub> exchange with grazed grasslands

“…One of the consequences is that the atmospheric concentration of NH 3 is not homogeneous over the field (see e.g. Bell et al, 2017). Both effects result in a horizontal advection of NH 3 , neglecting which leads to an error of the estimation of the total NH 3 flux.…”

“…This parameter ranges widely (2-20 g N dm −3 ; Whitehead, 1995), not just amongst different animals but also for different urination events by the same animal (Betteridge et al, 1986;Hoogendoorn et al, 2010). In the baseline simulation a constant average N content was applied.…”

“…For cows, the resulting grazing densities are above the 40 LSU ha −1 ; therefore, even in the worst case, the error will be under 5 %. For sheep, calculating with 44 LSU ha −1 , the highest grazing density in Bell et al (2017), the error will be 8 %, which can be still considered reasonable for the worst-case scenario. While patch overlap can therefore be generally neglected for continuous grazing and short periods of rotational grazing, we acknowledge that there may be some extreme cases of intense extended grazing where patch overlap could become relevant.…”

“…Bell et al, 2017), whilst the animals are typically on the field only for a few days. If it is assumed that an intensive grazing period typically lasts for a maximum of 3 days, using Eqs.…”

CH<sub>4</sub> emission estimates from an active landfill site inferred from a combined approach of CFD modelling and in situ FTIR measurements

“…The use of backward Lagrangian modelling for estimating gaseous emissions from a known area source in flat terrain with a single sensor has been described in detail by Flesch et al (1995Flesch et al ( , 2004. This technique was also applied by Bell et al (2017) for monitoring ammonia emissions from grazing cattle. Hrad et al (2014) used backward Lagrangian modelling to estimate emissions from an open windrow composting plant.…”