Assessment of the biochemical methane potential of in-house and outdoor stored pig and dairy cow manure by evaluating chemical composition and storage conditions

An integral assessment of the impact of diet and manure management on whole-farm greenhouse gas and nitrogen emissions in dairy cattle production systems using process-based models

Feed management decisions are crucial in mitigating greenhouse gas (GHG) and nitrogen (N) emissions from ruminant farming systems. However, assessing the downstream impact of diet on emissions in dairy production systems is complex, due to the multifunctional relationships between a variety of distinct but interconnected sources such as animals, housing, manure storage, and soil. Therefore, there is a need for an integral assessment of the direct and indirect GHG and N emissions that considers the underlying processes of carbon (C), N and their drivers within the system. Here we show the relevance of using a cascade of process-based (PB) models, such as Dutch Tier 3 and (Manure)-DNDC (Denitrification-Decomposition) models, for capturing the downstream influence of diet on whole-farm emissions in two contrasting case study dairy farms: a confinement system in Germany and a pasture-based system in New Zealand. Considerable variation was found in emissions on a per hectare and per head basis, and across different farm components and categories of animals. Moreover, the confinement system had a farm C emission of 1.01 kg CO2-eq kg-1 fat and protein corrected milk (FPCM), and a farm N emission of 0.0300 kg N kg-1 FPCM. In contrast, the pasture-based system had a lower farm C and N emission averaging 0.82 kg CO2-eq kg-1 FPCM and 0.006 kg N kg-1 FPCM, respectively over the 4-year period. The results demonstrate how inputs and outputs could be made compatible and exchangeable across the PB models for quantifying dietary effects on whole-farm GHG and N emissions.

In-vitro method and model to estimate methane emissions from liquid manure management on pig and dairy farms in four countries

Methane (CH4) emissions from manure management on livestock farms are a key source of greenhouse gas emissions in some regions and for some production systems, and the opportunities for mitigation may be significant if emissions can be adequately documented. We investigated a method for estimating CH4 emissions from liquid manure (slurry) that is based on anaerobic incubation of slurry collected from commercial farms. Methane production rates were used to derive a parameter of the Arrhenius temperature response function, lnA', representing the CH4 production potential of the slurry at the time of sampling. Results were used for parameterization of an empirical model to estimate annual emissions with daily time steps, where CH4 emissions from individual sources (barns, outside storage tanks) can be calculated separately. A monitoring program was conducted in four countries, i.e., Denmark, Sweden, Germany and the Netherlands, during a 12-month period where slurry was sampled to represent barn and outside storage on finishing pig and dairy farms. Across the four countries, lnA' was higher in pig slurry compared to cattle slurry (p < 0.01), and higher in slurry from barns compared to outside storage (p < 0.01). In a separate evaluation of the incubation method, in-vitro CH4 production rates were comparable with in-situ emissions. The results indicate that lnA' in barns increases with slurry age, probably due to growth or adaptation of the methanogenic microbial community. Using lnA' values determined experimentally, empirical models with daily time steps were constructed for finishing pig and dairy farms and used for scenario analyses. Annual emissions from pig slurry were predicted to be 2.5 times higher than those from cattle slurry. Changing the frequency of slurry export from the barn on the model pig farm from 40 to 7 d intervals reduced total annual CH4 emissions by 46 %; this effect would be much less on cattle farms with natural ventilation. In a scenario with cattle slurry, the empirical model was compared with the current IPCC methodology. The seasonal dynamics were less pronounced, and annual CH4 emissions were lower than with the current methodology, which calls for further investigations. Country-specific models for individual animal categories and point sources could be a tool for assessing CH4 emissions and mitigation potentials at farm level.