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.