Melynda Hassouna

Modelling of manure production by pigs and NH3, N2O and CH4 emissions. Part II: effect of animal housing, manure storage and treatment practices

A model has been developed to predict pig manure evolution (mass, dry and organic matter, N, P, K, Cu and Zn contents) and related gaseous emissions (methane (CH4), nitrous oxide (N2O) and ammonia (NH3)) from pig excreta up to manure stored before spreading. This model forms part of a more comprehensive model including the prediction of pig excretion. The model simulates contrasted management systems, including different options for housing (slatted floor or deep litter), outside storage of manure and treatment (anaerobic digestion, biological N removal processes, slurry composting (SC) with straw and solid manure composting). Farmer practices and climatic conditions, which have significant effects on gaseous emissions within each option, have also been identified. The quantification of their effects was based on expert judgement from literature and local experiments, relations from mechanistic models or simple emission factors, depending on existing knowledge. The model helps to identify relative advantages and weaknesses for each system. For example, deep-litter with standard management practices is associated with high-greenhouse gas (GHG) production (+125% compared to slatted floor) and SC on straw is associated with high NH3 emission (+15% compared to slatted floor). Another important result from model building and first simulations is that farmer practices and the climate induce an intra-system (for a given infrastructure) variability of NH3 and GHG emissions nearly as high as inter-system variability. For example, in deep-litter housing systems, NH3 and N2O emissions from animal housing may vary between 6% and 53%, and between 1% and 19% of total N excreted, respectively. Thus, the model could be useful to identify and quantify improvement margins on farms, more precisely or more easily than current methodologies.

Influence of rearing conditions and manure management practices on ammonia and greenhouse gas emissions from poultry houses

Poultry production has been identified as a major producer of NH3 and, to a lesser extent, of greenhouse gases (GHGs) mainly by national emissions inventories. However, since most national inventories are based on average emission factors for each type of animal (tier 1′ approach), the factors that influence these emissions (through breeding and manure-management practices) are not taken into account. The first step to improve inventories and propose mitigation options (e.g. best management practices, innovative systems) is a better understanding of the drivers of gaseous emissions and the identification of key factors for the mitigation of NH3 and GHG emissions. This paper presents a literature review of NH3 and GHG emissions from poultry housing, with a focus on the influence of practices and rearing conditions. It appears that flock-management practices (e.g. dietary practices, slaughtering age) and manure management (e.g. manure removal frequency, chemical treatment of litter) are presented as efficient ways to reduce emissions. Environmental conditions (e.g. ventilation rates, temperature) influence emissions; however, it was not possible to assess the effects of different combinations of these factors (compensatory or synergistic). Some factors, such as stocking density, which may play a significant role, were not studied. Modelling approaches that integrate these key factors with climate factors can be used to update emission factors in emissions inventories, consider national variability and uncertainties in mitigation scenarios, test synergistic and compensatory effects and avoid pollution swapping. Further research must be carried out to check the validity of emission factors and modelling parameters at a national scale.

Influence of pig rearing system on animal performance and manure composition

A total of 200 crossbred pigs (castrated males and females) were used in five replicates to evaluate the influence of rearing conditions for fattening pigs on growth performance, manure production and gaseous emissions. Approximately at 36 kg body weight (BW), littermates were allocated to either a conventional (fully slatted floor, 0.65 m2/pig, considered as control, CON) or an alternative (sawdust bedding, 1.3 m2/pig, with free access to an outdoor area 1.1 m2/pig, OUT) system, until slaughter at approximately 115 kg BW. Pigs had free access to standard growing and finishing diets. Manure was stored as slurry below the slatted floor in the CON system and as litter, for the inside area, or slurry and liquid, for the outside area, in the OUT system. The amount and composition of manure were determined at the end of each replicate. Ammonia emission from the rooms was measured continuously. Dust and odour concentrations were measured in replicates 1 and 2, and CH4, N2O and CO2 emissions were measured in replicate 3. Compared with the CON, the OUT pigs exhibited a faster growth rate (+8%, P < 0.001) due to their greater feed intake (+0.21 kg/day, P < 0.01), resulting in a heavier BW (+7.3 kg, P < 0.001) and a lower lean meat content (-1.6% points, P < 0.001) at slaughter. The total amount of manure produced per pig was similar in both systems (380 kg/pig), but because of the contribution of sawdust, dry matter (DM) content was higher (P < 0.001) and concentrations in N, P, K, Cu and Zn in DM were lower (P < 0.001) in manure from the OUT than from the CON system. In the OUT system, most of the manure DM (70%) was collected indoor, corresponding mostly to the contribution of the sawdust, and most of the manure water (70%) was collected outdoor. Pigs excreted indoor about 60% and 40% of urine and faeces, respectively. Ammonia emission from the room was lower for the OUT system, whereas total NH3 emissions, including the outdoor area, tended to be higher (12.0 and 14.1 g/day N-NH3 per pig for CON and OUT, respectively). Nitrous oxide emission was higher (1.6 and 4.6 g/day N-N2O per pig for CON and OUT, respectively) and methane emission was lower (12.1 and 5.9 g/day per pig for CON and OUT, respectively), for the OUT compared with the CON system.

Low degradable protein supply to increase nitrogen efficiency in lactating dairy cows and reduce environmental impacts at barn level

Generally, <30% of dairy cattles nitrogen intake is retained in milk. Large amounts of nitrogen are excreted in manure, especially in urine, with damaging impacts on the environment. This study explores the effect of lowering dietary degradable nitrogen supplies--while maintaining metabolisable protein--on dairy cows performance, nitrogen use efficiency and gas emissions (NH3, N2O, CH4) at barn level with tied animals. Two dietary N concentrations (CP: 12% DM for LowN; 18% DM for HighN) were offered to two groups of three lactating dairy cows in a split-plot design over four periods of 2 weeks. Diets were formulated to provide similar metabolisable protein supply, with degradable N either in deficit or in excess (PDIN of 84 and 114 g/kg DM for LowN and HighN, respectively). Cows ingested 0.8 kg DM/day less on the LowN diet, which was also 2.5% less digestible. Milk yield and composition were not significantly affected. N exported in milk was 5% lower (LowN: 129 g N/day; HighN: 136 g N/day; P<0.001) but milk protein yield was not significantly affected (LowN: 801 g/day; HighN: 823 g/day; P=0.10). Cows logically ingested less nitrogen on the LowN diet (LowN: 415 g N/day; HighN: 626 g N/day; P<0.001) resulting in a higher N use efficiency (N milk/N intake; LowN: 0.31; HighN: 0.22; P<0.001). N excreted in urine was almost four times lower on the LowN diet (LowN: 65 g N/day; HighN: 243 g N/day; P<0.001) while urinary urea N concentration was eightfold lower (LowN: 4.6 g/l; HighN: 22.9 g/l; P<0.001). Ammonia emission (expressed in g/h in order to remove periods of the day with potential interferences with volatile molecules from feed) was also lower on the LowN diet (LowN: 1.03 g/h per cow; HighN: 1.25 g/h per cow; P<0.05). Greenhouse gas emissions (N2O and CH4) at barn level were not significantly affected by the amount of dietary N. Offering low amounts of degradable protein with suitable metabolisable protein amounts to cattle improved nitrogen use efficiency and lowered ammonia emissions at barn level. This strategy would, however, need to be validated for longer periods, other housing systems (free stall barns) and at farm level including all stages of manure management.

Prediction of nutrient flows with potential impacts on the environment in a rabbit farm: a modelling approach

To face the increasing demand for animal products throughout the world, livestock-farming systems have been intensified. This intensification has proven to be economically effective but is noted for its negative impact on the environment through the production of ammonia (NH3) and the greenhouse gases nitrous oxide (N2O) and methane. In this context, dynamic models are useful tools to evaluate the effects of farming practice on nutrient flows and losses to the environment. This paper presents the development of a model simulating the flows of nitrogen (N) and phosphorus (P) in a rabbit production farm. The model is comprised of two submodels. The first submodel simulates the number of animals in the farm (births, deaths, culling of does/fatteners) and their respective performances (growth, feed intake, milk production). The second one simulates the excretion of N and P for each animal category using a mass-balance approach between intake (feed and/or milk intake) and exports (body deposition, milk production, gestation). Specific emission factors are then applied to the excreted N amounts to estimate total N, NH3 and N2O losses in the housing unit and during manure storage. Methane emissions from enteric fermentations and manure are also estimated. A simulation example based on French technico-economic data illustrates how the model could be used to study the dynamics of animal populations within the system and of nutrient flows. Finally, there is a need for new knowledge (experimental data) to improve the model and help design more sustainable rabbit production systems by identifying best practices that minimise environmental impacts.