In mitigating greenhouse gas (GHG) emissions and reducing the carbon footprint of dairy milk, the use of generic estimates in inventory and accounting methodology at farm level largely ignores variation of on-farm GHG emissions. The present study aimed to implement results of an extant dynamic, mechanistic Tier 3 model for enteric methane (CH4) (applied in Dutch national GHG inventory) in order to capture variation in enteric CH4 emission, and in faecal N and organic matter (OM) digestibility, ultimately required to predict manure CH4 and ammonia emission. Tier 3 model predictions were translated into calculation rules that could easily be implemented in an annual nutrient cycling assessment tool including GHG emissions, which is currently used by Dutch dairy farmers. Calculations focussed on (1) enteric CH4 emission, (2) apparent faecal OM digestibility and (3) apparent faecal N digestibility. Enteric CH4 was expressed in CH4 yield indicated with the term emission factor (EF; g CH4/kg DM) for individual dietary components and feedstuffs. Factors investigated to cover predicted variation in EF value included the level of feed intake, the type of roughage fed (proportions of grass silage and maize silage) and the quality of roughage fed. A minimum number of three classes of roughage type (i.e. 0. 40% and 80% maize silage in roughage DM) appeared necessary to obtain correspondence between interpolated EF values from EF lists and Tier 3 model predictions. A linear decline in EF value with 1% per kg increase in DM intake is adopted based on model simulations. The quality of roughage was represented by the effect of maturity of harvested grass or of the whole plant maize at cutting, based on a survey of modelling as well as experimental work. Also, predictions were assembled for apparent faecal OM digestibility which could be used in national inventory and in farm accounting. Apparent faecal N digestibility (as a major determinant of predicted urinary N excretion) was predicted, to support current Dutch national ammonia emission inventory and to correct the level of N digestibility in farm accounting. Compared to generic values or values retrieved from the Dutch feeding tables, predicted OM and N digestibility and enteric CH4 are better rooted in physiological principles and better reflect observed variation under experimental conditions. The present results apply for conditions with fairly intensive grassland management in temperate regions.

在减少温室气体（GHG）的排放和减少的牛奶的碳足迹，在库存和会计方法农场一级使用通用的估计很大程度上忽略农场温室气体排放量的变化。本研究旨在实施针对肠甲烷（CH 4）的现有动态力学Tier 3模型的结果（适用于荷兰国家温室气体清单），以便捕获肠CH 4排放以及粪便N和有机质的变化（OM）的消化率，最终可预测粪便CH 4和氨气排放。方法3的模型预测被转换为计算规则，可以很容易地在包括GHG排放在内的年度养分循环评估工具中实施，荷兰奶农目前正在使用该工具。计算集中在（1）肠CH 4排放，（2）表观粪便OM消化率和（3）表观粪便N消化率。肠内CH 4以CH 4产率表示，用术语排放因子（EF ; g CH 4/ kg DM），用于单独的饮食成分和饲料。为覆盖EF值的预计变化而进行调查的因素包括采食量，饲喂的粗饲料的类型（青贮饲料和玉米青贮饲料的比例）以及饲喂的粗饲料的质量。为了获得EF列表中插值的EF值与方法3的模型预测之间的对应关系，似乎需要最少三种类型的粗饲料类型（即粗饲料DM中0. 40％和80％的玉米青贮）。基于模型模拟，EF值线性下降，DM摄入量每千克增加1％。根据对模型和实验工作的调查，粗饲料的质量由收获的草或整株玉米在切割时的成熟度的影响表示。也，结合了对粪便表观消化率的预测，这些消化率可用于国家清单和农场会计。可以预测粪便的表观N消化率（作为预测尿N排泄的主要决定因素），以支持荷兰目前的国家氨气排放清单，并在农场核算中纠正N消化率的水平。与一般值或从荷兰喂养表中检索的值相比，预测的OM和N消化率以及肠溶性CH4更好地扎根于生理原理，并更好地反映了在实验条件下观察到的变化。目前的结果适用于温带地区草地管理相当集约的条件。