Ammonia (NH) fluxes were estimated from a field beinggrazed by dairy cattle during spring by applying a backward Lagrangianstochastic model (bLS) model combined with horizontal concentration gradientsmeasured across the field. Continuous concentration measurements at fieldboundaries were made by open-path miniDOAS (differential optical absorptionspectroscopy) instruments while the cattle werepresent and for 6 subsequentdays. The deposition of emitted NH to patches on the fieldwas also simulated, allowing both and emission estimates,where the dry deposition velocity () was predicted by a canopyresistance () model developed from local NH flux andmeteorological measurements. Estimated emissions peaked during grazing anddecreased after the cattle had left the field, while control on emissions wasobserved from covariance with temperature, wind speed and humidity and wetnessmeasurements made on the field, revealing a diurnal emission profile. Largeconcentration differences were observed between downwind receptors, due tospatially heterogeneous emission patterns. This was likely caused by unevencattle distribution and a low grazing density, where ofemissions would arise as the cattle grouped in certain areas, such as aroundthe water trough. The spatial complexity was accounted for by separating themodel source area into sub-sections and optimising individual source areacoefficients to measured concentrations. The background concentration was thegreatest source of uncertainty, and based on a sensitivity/uncertaintyanalysis the overall uncertainty associated with derived emission factorsfrom this study is at least 30–40 %.Emission factors can be expressed as 6 ± 2 g NH cow day, or 9 ± 3 %of excreted urine-N emitted as NH, when deposition is not simulated and 7 ± 2 g NH cow day, or 10 ± 3 % of excreted urine-N emitted asNH,when deposition is included in the gross emission model. The results suggestthat around 14 ± 4 % of emitted NH was deposited to patcheswithin the field that were not affected by urine or dung.
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机译：通过应用反向Lagrangians随机模型（bLS）模型和在整个田间测量的水平浓度梯度，从春季被奶牛吃草的田地估算氨气（NH）通量。在有牛的情况下以及随后的6天中，使用开路miniDOAS（差分光学吸收光谱法）仪器对田间边界进行连续浓度测量。还模拟了排放的NH到田间斑块的沉积，可以同时进行排放估算，其中，干沉降速度（）是通过根据局部NH通量和气象测量结果开发的冠层阻力（）模型预测的。估计的排放量在放牧期间达到峰值，而在牛离开田地后减少，而排放量的控制是通过与田间温度，风速，湿度和湿度测量值的协方差来观察的，从而揭示了日排放量。由于空间上的异质排放模式，在顺风受体之间观察到了较大的浓度差异。这很可能是由于牛群分布不均和放牧密度低而导致的，这是由于牛群聚集在某些区域（例如水槽周围）而引起的排放。通过将模型源区域划分为多个子部分，并根据测量的浓度优化各个源区域的系数来解决空间复杂性问题。背景浓度是最大的不确定性来源，根据敏感性/不确定性分析，本研究得出的与排放因子相关的总体不确定性至少为30–40％。排放因子可以表示为6±±2 g NH牛天，或9如果不模拟沉积，则在总排放模型中包括沉积物时，±7％的排泄尿液中的N以NH的形式排放，而当模拟为7±±2％g NH牛日时，或10％±3％的排放的尿液中N以NH的形式排放。结果表明，在田间未受尿液或粪便影响的斑块中约有14±4 %%的NH沉积在斑块上。
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