CURRENT KNOWLEDGE FOR ESTIMATION OF EMISSIONS AND PRIORITIES FOR MITIGATION AND ADAPTATION: SOUTH AFRICA S PERSPECTIVE Luanne Stevens 1, L. Du Toit 2 and M. Scholtz 3 1 North-West 2 Tshwane 3 ARC-Animal University, Potchefstroom, SA University of Technology, Pretoria, SA Production Unit, University of the Free State, SA
South Africa s GHG Inventory History Base year 1990 Followed the IPCC 1996 Guidelines Agriculture included: Enteric fermentation; Manure management; Biomass burning of savannas; Burning of agricultural residues; Agricultural soils No communal livestock Updated for 1994 Same components as above Inventory for 2000 Transitioning to IPCC 2006 Guidelines, but agriculture section followed 1996 Guidelines Agriculture included: Enteric fermentation; Manure management; Indirect N2O emissions No communal livestock
South Africa s GHG Inventory History cont.. Agriculture inventory was updated for year 2004 IPCC 2006 Guidelines Included more country specific data Moving towards a Tier 2 approach Agriculture included: Livestock (including communal livestock): Enteric fermentation; Manure management; Aggregated sources and non-co2 emission sources on land: Biomass burning; Lime and urea application; N2O (direct and indirect) from managed soils; Indirect N2O from manure management
Current inventory SA has recently completed its 2010 GHG inventory Follow the IPCC 2006 guidelines More country specific data; Includes trends between 2000 to 2010 First attempt at including the Forestry and Other Land Use sector AFOLU sector contributes between 5 7% of the total
Livestock contribution to AFOLU 80% ANCO2 60% Livestock 40% 20% 2000-20% -40% 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Other Land 0%
Key livestock sources of GHG emissions Enteric fermentation Beef cattle and sheep are the largest contributors due to population numbers Manure management Much lower than enteric fermentation emissions Pigs and dairy cattle are the largest contributors to manure CH4 Poultry is the largest contributor to manure N2O
Key livestock GHG emission sources cont N2O from urine and dung deposited on PRP
Key areas for current research and technology transfer Measurement of emission factors: Livestock emissions Country specific emission factors Emissions from manure (particularly N2O) Emissions from dung/urine on PRP Determination of agricultural emission intensities Farm level carbon accounting models: Assist farmers to understand the impacts of their management Assist farmers to be more efficient Pasture management and quality: Impacts on carbon budget Effects of pasture quality of EF s
Existing research infrastructure and capacity Key institutes conducting research around GHG emissions from livestock Tshwane University of Technology University of Pretoria Livestock and manure emissions Respiration chambers for sheep Static chambers for manure and PRP emissions Pasture management and carbon sequestration ARC-Animal production unit Genetics breeding and fertility Livestock productivity Livestock diet research Laser methane detector North-West University Has experience and equipment for measuring GHG emissions in general Continuous GHG analysers Several other agricultural universities which conduct general livestock research
Current methods for estimating livestock GHG emissions Population data: Disaggregated data for all livestock; Commercial and communal numbers for all livestock Enteric fermentation emission factors: Calculated Tier 2 EF for all livestock except horses and donkeys; IPCC methodology combined with methodology used by Australia; Requires feed intake or gross energy intake information: Cattle - live weights, weight gain, metabolic rate, milk production, DMD (varied over the 4 seasons); Sheep/goats/pigs - body size, proportion of diet metabolised, relative intake, DMD, intake for milk/wool production, feed adjustment Feedlot intake of specific feed components, and DMI
Enteric fermentation emission factors: Livestock 1990 EF (kg/head/yr) 2004 Dairy TMR 70 44 107 21 132 40 81 Dairy pasture 70 44 107 20 127 40 81 Other cattle (commercial) 50 70 28 125 51 112 31 60 Other cattle (communal) 50 28 125 40 83 31 60 Sheep 5 5 3-14 5 8 Goats 5 5 3-16 5 5 Pigs 1 1 0.4 2.5 1 1.5 Current IPCC default EF Africa Oceania
Current methods for estimating livestock GHG emissions cont Manure CH4 emissions Calculated using Tier 2 methods for all livestock; Manure characteristics: Volatile solids (Gross energy intake; Feed digestibility (varied over 4 seasons); DMI; Urinary energy); Max methane producing capacity for manure; Methane conversion factor; Manure management characteristics Manure N2O emissions Followed methods used by Australia; Updated method for calculating N excretion per head for dairy and feedlot cattle: Based on determination of faecal and urinary N excreted: Crude protein inputs (dry matter intake; nitrogen storage); Nitrogen excreted in faeces (DMD; crude protein intake; metabolizer energy; DMI); Nitrogen retention (milk production; relative intake; relative weight)
Manure CH4 emission factors: Livestock EF (kg/head/yr) 1990 2004 Current Australian EF IPCC default EF Africa Oceania Dairy TMR 5.13 24 83 0.2 14.8 8.8 1 29 Dairy pasture 5.13 24 83 0.3-5 8.8 1 29 Other cattle (commercial) 3.62 0.5 3.5 0.01 0.8 0.04 2.91 1 2 Other cattle (communal) 3.62 1 2.7 0.01 0.02 0.04 1 2 Sheep 0.23 0.1 0.3 0.001 0.04 0.002 0.15 0.28 Goats 0.23 0.1 0.2 0.004 0.02 0.002 0.17 0.2 Pigs 11.2 9.3-25 0.08-24 23 1 13-24
Current methods for estimating livestock GHG emissions cont N2O emission from urine and dung in PRP Calculated using following IPCC equation: N2O-NPRP = [(FPRP,CPP * EF3PRP,CPP) + (FPRP,SO * EF3PRP,SO)] Where: FPRP = annual amount of urine and dung N deposited on PRP (kg N yr-1); EF3PRP = EF for N2O emissions from urine and dung N deposited on PRP by grazing animals (kg N2O-N (kg N input)-1); CPP = Cattle, Poultry and Pigs; SO = Sheep and Other. Emissions may be overestimated as IPCC default factors are being used: IPCC default EF Australia NZ Germany/ GBR 0.01-0.02 0.004 0.007 0.02
Key barriers to improved estimates of livestock GHG emissions Data. Country specific emissions factors Impact of livestock breed, age/sex class and diet on EF Need annual measurements to determine annual variation Livestock population data Highly variable depending on source Communal livestock numbers are not well known Manure management data Very little data on the manure management systems being used in the various livestock industries Reasons for lack of data: Financial Lack of understanding of what data is required for estimates No central point for data collection
Country priorities for mitigation and adaptation strategies/policies Reduce GHG emissions from livestock (particularly beef cattle) by: Improving production efficiency Improve fertility (calving percentages) Improve cow efficiency (kg calf weaned/lsu) Improve post weaning efficiency Select for residual traits low RFI animals produce up to 28% less methane Effective crossbreeding Breeding to reduce the carbon footprint of livestock products Implementing new or adapted climate smart production systems Use of appropriate/adapted genotypes Herd structure management
Country priorities for mitigation and adaptation strategies/policies cont Reduce GHG emissions from manure by: Improving manure management Making use of biodigesters In the future: Should investigate demand-side management (food wastage, dietary change) Carbon labelling of products
Main gaps to implement adaptation and mitigation strategies/policies Information dissemination: Need to improve agricultural extension network Finance Buy-in: Farmers and agricultural associations Incentives Research: Need to understand mitigation potential Need assessment of socio-economic and environmental impacts (feasibility studies)
THANKS