Modeling of gaseous emission in pig production Jean-Yves Dourmad, Florence Garcia-Launay, Sandrine Espagnol INRA Agrocampus Ouest UMR Pegase France IFIP Institut du Porc le Rheu, France
Content Origin of gaseous emissions Animal metabolism Indigested nutrient Indirect emissions Modeling of animal excretion and gaseous emissions Excretion of nutrients Emission of CH 4 and CO 2 Modeling of emissions from manure Emission factors and empirical models Mechanistic models Modeling of emissions from the production chain Life Cycle Assessment
Origin of gaseous emissions Two main origins Digestion and metabolism of nutrients Respiration CO 2 and enteric CH 4 Biochemical transformation of excreta From urine From feces Collected as slurry or solid manure During storage and spreading During treatment
Origin of gaseous emissions CO 2 energy metabolism of nutrient (respiration) transformation of urea into ammonia aerobic and anaerobic microbial digestion of excreta and manure organic matter CH 4 enteric fermentation of digestible feed fiber anaerobic digestion in manure of undigested feed organic matter H 2 S anaerobic digestion of undigested feed organic matter in manure in presence of sulfur
Origin of gaseous emissions NH 3 Fecal excretion (microbial production in the hindgut) Emission from manure in anaerobic conditions (NH 4 + from urea and microbial digestion of undigested protein) N 2 O, NO x, N 2 Nitrification/denitrification of ammonia (aerobic conditions) Organic volatile compounds (odours) More than 300 compounds (identified or not)
Origin of gaseous emissions Implications for modeling Gaseous emissions are essentially issued from the non retained fraction of the feed => modeling of animal gaseous emissions (CH 4, CO 2, water) and nutrient (N and C compounds, minerals) and water excretion Different bio-chemical processes are involved in the emission of each gas => modeling of these bio-chemical processes The emissions occur at different location and time => modeling of the whole production and manure management chain (animal, housing, storage, spreading) => integrated/dynamic modeling
Content Origin of gaseous emissions Animal metabolism Indigested nutrient Indirect emissions Modeling of animal excretion and gaseous emissions Excretion of nutrients Emission of CH 4 and CO 2 Modeling of emissions from manure Emission factors and empirical models Mechanistic models Modeling of emissions from the production chain Life Cycle Assessment
Modeling of animal excretion and gaseous emissions heat CO 2 CH 4 water Water Body retention Feces Feed Urine CP, P, K, Cu, Zn, MM, DM, ME, NE, fiber N, P, K, Cu, Zn, MM DM, OM, minerals
Modeling of animal excretion and gaseous emissions Heat production HP = f(energy intake, body weight, ME/NE ratio) HP = energy for maintenance + heat increment (+ heat for thermoregulation below thermoneutratily) Noblet et al.(1990) Respiration CO 2 Resp_CO 2 = f(heat production) Water evaporated WE = f(latent heat production) CIGR Latent heat production = f(hp, ambient temperature) CIGR Rigolot et al., 2010
Modeling of animal excretion and gaseous emissions Water excretion/balance WE = f(dinking water, feed water, metabolic water, body water, evaporated water) Metabolic water = f(respiration CO 2 ) Body water = f(body protein) Dry matter excretion DM_F = f(feed intake, feed DM, DM digestibility) DM digestibility = f(digestible energy, NDF, mineral matter) Amount of slurry SL = Water excretion + DM excretion Le Goff et al.(2001) Rigolot et al., 2010
Prediction of enteric methane emission by the different categories of pig (g/d) 20 15 10 5 0 Rigolot et al., 2010
Effect diet composition on enteric methane emission by fattening pigs (g/d) 4 + 47% 3 2 1 0 Low fiber cereals, soybean meal High fiber cereals, rapeseed meal, DDGS Jarret et al., 2012
Comparison of amount of slurry predicted and collected (slated floor) 55 exp groups from 25 publications on fattening pigs, weaners and sows Rigolot et al., 2010
Comparison of amount of N excreted and collected in slurry (slated floor) 55 exp. groups from 25 publications on fattening pigs, weaners and sows N in slurry = 0.755 x N excreted (R 2 = 0.91) Gaseous losses of N compounds = 24.5% Rigolot et al., 2010
Comparison of amount of N excreted and collected (slated floor) after correction 55 exp. groups from 25 publications on fattening pigs, weaners and sows N in slurry = 0.755 x N excreted (R 2 = 0.91) Gaseous losses of N compounds = 24.5% Rigolot et al., 2010
Content Origin of gaseous emissions Animal metabolism Indigested nutrient Indirect emissions Modeling animal excretion and gaseous emissions Excretion of nutrients Emission of CH 4 and CO 2 Modeling of emissions from manure Emission factors and empirical models Mechanistic models Modeling of emissions from the production chain Life Cycle Assessment
A large diversity in chains of manure management in practice Rigolot et al., 2010b
Evaluation of gaseous N compounds during storage Choice of a rather empirical but generic approach Because of the large diversity of chains (solid, liquid) To be applied to storage inside and outside The emission factor expressed as a % of excretion (inside storage) of per m 2 (outside storage) The variation factors are specific to each manure chain Rigolot et al., 2010b
Evaluation of NH 3 emission from housing of pigs on slatted floor (slurry) N_NH 3 = N_Excreted x 0.24 x VF_Ndilution x VF_Temperature x VF_Air ventilation x VF_floor x VF_Frequency f(nurine, slurry volume) f(ambient temperature) f(ventilation rate/kg BW) f(type of floor) f(freq of slurry removal) Rigolot et al., 2010b
Evaluation of N-emissions from housing of pigs on litter bedding (expert knowledge) Rigolot et al., 2010b
Simulation of the effect of feed efficiency of growing pig on NH 3 emission NH3, ppm - Volat. N, % N Air, N slurry (kg/pig) 45 4.0 40 35 30 2.9 27% 2.7 2.4 3.5 3.0 2.5 25 20 15 10 21 1.06 27% 18 0.96 26% 16 0.84 2.0 1.5 1.0 0.5 5 low average high FCR 2.9 2.7 2.5 0.0 Dourmad et al., 2003
NH3, ppm - Volat. N, % N Air (kg/pig) N slurry Simulation of the effect of dietary protein content on NH 3 emission and N balance Water : -------- ad libitum restricted 45 40 35 30 25 20 15 10 5 13 15 17 19 21 Dietary protein content, % 4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 Dourmad et al., 2003
NH3, ppm - Volat. N, % N Air - N Slurry (kg/pig) Simulation of the effect of ambient temperature on NH 3 emission and N balance 50 Water : -------- ad libitum restricted 3.5 40 30 20 10 3.0 2.5 2.0 1.5 1.0 0.5 0 16 18 20 22 24 26 28 Temperature, C 0.0 Dourmad et al., 2003
Simulation of the effect of the manure management chain on NH 3 and N 2 O emissions of fattening pigs Slurry Slurry & anaerobic digestion Slurry & aerobic digestion Slurry composting on straw Straw litter N2O NH3 Composted straw litter 0,0 0,5 1,0 1,5 2,0 Gaseous emissions, kg N/pig (30-110 kg BW) Rigolot et al., 2010b
Simulation of the effect of the manure management chain on GHG emission from housing and storage Slurry Slurry & anaerobic digestion Slurry & aerobic digestion Slurry composting on straw Straw litter CH4 N2O Composted straw litter 0 50 100 150 200 GHG emission, g eq CO 2 /pig (30-110 kg BW) Rigolot et al., 2010b
Content Origin of gaseous emissions Animal metabolism Indigested nutrient Indirect emissions Modeling animal excretion and gaseous emissions Excretion of nutrients Emission of CH 4 and CO 2 Modeling of emissions from manure Emission factors and empirical models Mechanistic models Modeling of emissions from the production chain Life Cycle Assessment
Mechanistic modeling Characteristics of mechanistic models Representation of chemical, biological and physical processes Dynamic models (time step of 1 mn to 1 day) Variation factors Slurry production and composition Temperature, air renewal, emission area, floor cleanness Type of gas Mainly NH 3 emission, some models on H 2 S, CO 2 and CH 4 Scope of models Storage pit : Olesen and Sommer (1990); Olesen and Sommer (1993); Sommer et Husted (1995); Zhang et al., (1994); Arogo et al.,(1999); Aneja et al. (2001); De Visscher et al. (2002); Liang et al. (2003); Bajwa et al., (2006); Teye and Hautala (2008); Rumburg et al., (2008); Blanes-Vidal et al. (2009)... Housing : Aarnink et Elzing (1998), Ni et al. (1999, 2000); Dourmad et al. (2008, 2012) Anaerobic digestion
Factors affecting ammonia emission in pig buildings Floor T indoors T outdoors Insulation Nutrition Manure storage ventilation rate NH 3 production NH 3 extraction NH 3 concentration Volume Dourmad et al., 2007
The system to be considered Dourmad et al., 2007
The system to be considered Dourmad et al., 2007
The system to be considered Dourmad et al., 2007
The animal : produce heat and excreta Dourmad et al., 2007
Regulation of ventilation and temperature Dourmad et al., 2007
Evaluation of ammonia emission Air surface NH 3a air speed Urea N Org NH 4 + NH 3l NH 3g k mass transfer coefficient ph H Henry constant T ph = 7.91 + 1.86 x (log([nh 3 ]) - 0.446) 0.0046 x (NSP - 182) + 0.002388 x (EB - 178) Liquid Dourmad et al., 2007
Model description : ammonia Dourmad et al., 2007
Effect of season and type of air extraction on NH 3 concentration in the room
Predicted effects of season, types of floor and air extraction on cumulated N-NH 3 emission
Predicted effects of season, types of floor and air extraction on NH 3 concentration in the room
Content Origin of gaseous emissions Animal metabolism Indigested nutrient Indirect emissions Modeling animal excretion and gaseous emissions Excretion of nutrients Emission of CH 4 and CO 2 Modeling of emissions from manure Emission factors and empirical models Mechanistic models Modeling of emissions from the production chain Life Cycle Assessment
Modeling the emission of greenhouse gases in the pig production chain using LCA at farm gate
Modeling the emission of NH3 in the pig production chain using LCA at farm gate
A large diversity of modelling approaches Type of models : statistical, empirical, mechanistic Boundaries : animal, animal house, storage, treatment, spreading, animal farm, production chain, territory Scope : greenhouse gas, ammonia, odours, particles Objectives : scientific/applied, understand/aggregate mechanisms, predict/control emissions Time handling: dynamic/ static, time step (min, hour, year ) A diverse community of modellers disciplines Environment, biochemistry, bioclimatology, process control, engineer, Animal nutrition A scientific challenge : Conclusion A real opportunity to take benefit of existing knowledge, diversity and competences to integrate the different approaches and disciplines and build integrated scientific projects => A challenge addressed by Emili
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