Current state of agriculture and mitigation: NAMAs, quantifying emissions and links to adaptation
A system for quantification ofsmallholder agriculture GHGsMarja-Liisa Tapio-BistromMitigation of climate change inAgriculture programme (MICCA)FAO
Elements and tools for mitigationplanning in agriculture• Data on emissions and projections for a baseline• Mitigation options – LCA as a tool• Knowledge on farming practices• Emission factors• A vision and means for landscape level optionsfor increasing the carbon content• Greetings from GHG quantification workshop• Food for thought
FAOSTAT Emissions from Agriculture andLand Use Database+IPCC Guidelines=& geo-referenced informationTier 1, all sources of emissions from agriculture and LU, timeseries from 1990, all countries, projections to 2030 and 2050
Life Cycle Analysis – identifyingmitigation options• LCA is an approach to emissions analysiswhich makes sense to policy makers, investorsfarmers since it describes the system• Global LCA on all livestock systems coming outsoon (different intensity levels, differentagroecological zones)
Emission intensity of milk in East AfricaFAO, 2013 Source: Global Environmental Assessment Model (GLEAM)0.02.04.06.08.010.012.014.016.018.0Kenya Uganda United Republicof TanzaniaKgCO2eq/kgFPCMCO2, Post-farmgateCO2, Direct andembedded energyFeed CO2Feed N20Manure N20Manure methaneEntericfermentation
0.001.002.003.004.005.006.007.00Temperate Arid HumidKgCO2e/kgFPCMKenya: Grazingsystems0.001.002.003.004.005.006.007.00Temperate Arid HumidKenya: Mixed systemsCO2, Direct andembedded energyFeed CO2Feed N20Manure N20Manure methaneEnteric fermentationSource: Global Environmental Assessment Model (GLEAM), FAO, 201360%2%6%28%2% 1% 1%Emission intensityof milk in Kenya
Enteric methane emissions at farm scale- Kaptumo, Kenya0.000.010.020.030.040.050.060.070.080.09500 1000 1500 2000 2500 3000 3500 4000KgEntericCH4perlitremilkLiter of milk per cow per lactationSource: Based on Global Environmental Assessment Model (GLEAM), farm scale LCA based onHousehold data, Opio et al., 2013
Enteric methane - improving feed useefficiency - Kaptumo, Kenya0.000.010.020.030.040.050.060.070.080.090.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 1.80KgentericCH4perlitremilkFeed efficiency (litre milk/kg DM intake)Source: Based on Global Environmental Assessment Model (GLEAM), farm scale LCAbased on Household data, Opio et al., 2013
More analysis of farming practices- We need rigorous analysis of farming practices combining thescience and farmers experiences to develop climate-smartpractices- What works , where or why not
Emission factors• Better emission factors for tropical and sub-tropical areas, major farming systems andfarming practices• A global plan, identifying priority systems andgaps• Longer term measurements – calibration ofmodels• Network of research partners – spearheaded byCCAFS?
Maximizing carbon content –landscape approach• Tap the mitigation potential at landscape leveltrough holistic participatory land use planning• CSA sourcebook gives ideas how• Aboveground biomass as a proxy? –stable orincreasing • Opportunities for remote sensing – landdegradation in grasslands
Greetings from GHG quantificationworkshopThe current systems are complex and expensive, notappropriate for most low-income countries. We must invest in creative, low-cost systems for datacollection and analysis, such as1. targeting global mitigation priorities and hotspots (or keycategories) in landscapes and farming systems2. combining modeling, remote sensing and fieldmeasurements (crowd-sourcing and mobile technology)3. building on existing activity data from other sources4. using consistent, comparable methods and data sharingnetworks that enable robust estimates for different systems
Food for thought• How exact do we need to know the netemission reductions?• Depends on the funding source – climatefunding vs. agricultural investments• We need to transform the way we producefood – more efficient, more resilient, withmitigation co-benefit.