Meryl RichardsCGIAR Research Program on Climate Change, Agriculture and Food Security
Improving data on greenhouse gas emissions—and mitigation potentials—from agriculture
With contributions from:Todd RosenstockLini WollenbergKlaus Butterbach-BahlMariana Rufinoand many others
• How can we tell when we’re reducing emissions? On the farm In the life cycle of a product At subnational and national scales
Many CSA practices and policies have potential to lower emissions from agriculture
Estimating emissions
IPCC 1996 and 2006 guidelines
Emissions = Activity x Emissions FactorNitrous oxide = Annual amount of synthetic fertilizer N applied to soils, kg N yr-1 x 1%
4
How accurate are these methods in tropical systems?
• Compared EX-ACT and Cool Farm Tool with field measurements of soil fluxes
• 9 studies, 8 countries, 51 data points• Maize, rice, vegetable crops, tea, coffee, fodder grass
1. GHG balance of systems (sites, practices)2. Changes in GHG balance with changes in practice
Comparison of GHG calculators with field measurements
= ?
5Richards et al. 2016
1. Greenhouse gas balance
2. Change in GHG balance between control and alternative management practices
Richards et al. 2016
Studies of N2O emissions from managed soils in SSA
Hickman et al. 2014
Very little data on GHG sources and sinks in tropical developing countries
What is needed for better estimates?
1. More data
What is needed for better estimates?
2. Use the data we already have Tier 2 emission factors where available Calibration of empirical models with data more
representative of tropical developing countries Coordinated data platforms
Resources to support better estimation
www.samples.ccafs.cgiar.org
• Reducing cost of measurement• Handling heterogeneous
landscapes• Livelihoods as a primary
concern
Data examples: Fallow and straw management in paddy rice
• Methane (CH4) emissions strongly influenced by fallow and straw management
• Soil drying between rice crops in the tropics can reduce CH4 emissions during the subsequent rice crop
Sander et al. 2014
Flooded Dry Dry + tillage Dry and wet0
500
1000
1500
2000
With residueWithout residue
g C
O2e
/m-2
a
c
y
c
b
y
x
y
Data examples: Excreta from African cattle
Source Kg C-CH4 / Head. Year
EF N-N2O %
IPCC, 2006 0.77 2
Yamluki, 1999 and Yamluki, 1998
0.26 0.53
This study 0.14 (Friesian)0.026 (Boran)
0.23 (Friesian)0.53 (Boran)
Pelster et al. 2016
• Emissions from manure and urine patches on pasture much lower than IPCC Tier 1
14:00 - 14:30 Climate-Smart Agriculture Compendium:
The scientific basis of CSA
Todd Rosenstock (World Agroforestry Centre)
Discussion
• How do you use information on GHG emissions and mitigation potentials?
• What are your biggest challenges in estimating emissions and emission reductions?
• What information do you or your organization need most in order to estimate the mitigation potential of your activities?
References• Arias-Navarro C, Díaz-Pinés E, Kieseb R, Rosenstock TS, Rufino MC, Stern D, Neufeldt H, Verchot
LV, Butterbach-Bahl K. (2013) Gas pooling: a sampling technique to overcome spatial heterogeneity of soil carbon dioxide and nitrous oxide fluxes. Soil Biology and Biochemistry 67: 20-23.
• Hickman JE, Scholes RJ, Rosenstock TS, et al (2014) Assessing non-CO2 climate-forcing emissions and mitigation in sub-Saharan Africa. Curr Opin Environ Sustain 9-10:65–72. doi: 10.1016/j.cosust.2014.07.010
• Kuyah S, Rosenstock TS (2015) Optimal measurement strategies for aboveground tree biomass in agricultural landscapes. Agrofor Syst 89:125–133. doi: 10.1007/s10457-014-9747-9
• Richards M, Metzel R, Chirinda N, Ly P, Nyamadzawo G, Duong Vu Q, de Neergaard A, Oelefse M, Wollenberg E, Keller E, Malin D, Olesen JE, Hillier J, Rosenstock TS (2015) Limits of greenhouse gas calculators to predict soil fluxes in tropical agriculture. Submitted to Sci. Rep.
• Sander BO, Samson M, Buresh RJ (2014) Methane and nitrous oxide emissions from flooded rice fields as affected by water and straw management between rice crops. Geoderma 235-236:355–362. doi: 10.1016/j.geoderma.2014.07.020
• Smith P, Bustamante M, Ahammad H, et al (2014) Agriculture, Forestry and Other Land Use (AFOLU). In: Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Edenhofer O, Pichs-Madruga R, Sokona Y, et al. (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
• Van Vuuren DP, Stehfest E, den Elzen MGJ, et al (2011) RCP2.6: Exploring the possibility to keep global mean temperature increase below 2°C. Clim Change 109:95–116. doi: 10.1007/s10584-011-0152-3
Innovations in methods: Targeting measurement within landscapes
Arias-Navarro et al. 2013 SBB
Innovations in methods: Gas pooling
Innovations in methods: Using diameter only for tree biomass measurements
To save resources on tree measurements:• Allometric equations for trees
on farms can be based solely on diameter at breast height
• Sampling strategy should capture the range of tree sizes found in the landscape
• Future indirect quantification should focus on diameter at breast height
Kuyah & Rosenstock 2015
Static chamber for soil flux measurements
Respiration chamber for enteric methane measurement
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Calculator estimates are within the range of error in the IPCC 2006 Guidelines
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Example: carbon accumulation in existing trees
• EX-ACT assumes no biomass C sequestration without land use change
• EX-ACT estimate could be improved by using Tier 2 factors (e.g. tree growth rates)
Full sun ShadeCoffee, Costa Rica (N2O, biomass C, soil C)
-16
-14
-12
-10
-8
-6
-4
-2
0
2
Measured
Cool Farm Tool
EX-ACT
GH
G e
mis
sion
s (tC
O2e
ha-
1 yr
-1 )
Data: Hergoualc'h et al. 2012
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Caveat: Measurements aren’t perfect either
• In low-emissions environments, standard errors associated with soil GHG flux measurements may be of nearly the same magnitude as the fluxes themselves.
Conve
ntion
al till
age
No-till,
legu
me inte
rcrop
No-till,
mine
ral fe
rtilize
r
No-till,
heav
y mulc
h
No-till,
legu
minous
trees
0.00
0.02
0.04
0.06
0.08
0.10
0.12
tCO
2e h
a-1
yr-1
Data: Kimaro, A. A. et al. (2015) Nutr. Cycl. Agroecosyst.