Butterbach Bahl Quantifiying ghg emissions soils chamber method Nov 11 2014

Quan&fying greenhouse gas emissions from managed and natural soils

Klaus Bu(erbach-‐Bahl1,2, Bjoern Ole Sander3, David Pelster1, Eugenio Díaz-‐Pinés2

Rome, Reducing the costs of GHG es&mates in agriculture to inform low emissions

development, FAO-‐CCAFS Workshop, November 10-‐12, 2014

1Interna(onal Livestock Research Ins(tute, Kenya; 2Karlsruhe Ins(tute of Technology, Germany; 3Interna(onal Rice Research Ins(tute, Phillipines; 4The University of Western Australia, Australia

Agricultural GHG emissions and developing countries

•  Agriculture is responsible for 47 and 84% of anthropogenic CH4 and N2O emission, respec@vely (Smith et al. 2007) •  But these es@mates are based on studies in Europe / N America / Australia

•  Importance of smallholder farms (e.g. in SSA) •  75% of agricultural produc@on and 75% of job produc@on in SSA (Africa Development Bank, 2010)

•  80% of farms in SSA < 2 ha (FAO 2010) •  Yield are very low (~1 Mg ha-‐1)

GHG emissions and underlying mechanisms

Emission = produc@on (microbial/ chemical) – consump@on (microbial/ chemical) BuZ

erbach-‐Bahl et al, 2013, Phil. Trans. R. Soc.

GHG emissions processes and measuring techniques

BuZerbach-‐Bahl et al, 2013, Phil. Trans. R. Soc.

Drivers of soil GHG emissions

Turner et al. 2008, Plant & Soil Van Beek et al. 2010, Nutr. Cycl Agroecosys.

•  Soil proper@es and soil environmental condi@ons •  Agricultural management (e.g. fer@liza@on, irriga@on, residue management…)

•  Microbe-‐plant interac@ons and microbial diversity •  ……..

Advantages of chamber techniques

Plus •  Simple, low cost, „easy“ to apply •  Allows studying of management effects •  Can be established elsewhere •  Existence of protocolls (e.g. USDA, GRA)

Minus •  Change in soil environmental condi@ons •  Spa@al and temporal variability •  Accuracy of measurements •  ….

Chamber techniques – general points

Chamber techniques – chamber placement

Chamber techniques – spa&al variability

Arias-‐Navarro et al., 2013, Soil Biol. Biochem.

Chamber techniques – temporal variability Barton et al., 2014, in prep.

OVERALL OBJECTIVE

Investigate the effect of sample frequency on estimates of annual N2O fluxes, using published data collected:

•  On a sub-daily basis using automated chamber systems

•  From a variety of climates and land-uses Measuring soil N2O emissions from a cropped

soil using chambers. Photo: Graeme Schwenke, NSW, Australia

Chamber techniques – temporal variability APPROACH

Daily fluxes by averaging sub-‐daily fluxes (removed diurnal varia0on)

Annual fluxes at different sampling frequencies

Propor@on of ‘daily’ annual flux es@mated by each sample frequency = % devia0on of ‘daily’ annual flux

For each data set, we calculated:

Barton et al., 2014, in prep.

Chamber techniques – temporal variability

9%

Measurement frequency0 5 10 15 20 25 30

% D

evia

tion

of a

nnua

l flu

x

-50

0

50

100

150

200

250

300

350

SAMPLING FREQUENCY & ANNUAL FLUX: ‘Highly’ episodic

Steppe grassland, semi-‐arid climate, Inner Mongolia


Chamber techniques – temporal variability

9%


Measurement frequency0 7 14 21 28

Num

ber o

f dat

a-se

ts

0

5

10

15

20

25Within 10%Within 20% Within 30%

8%

RECOMMENDED SAMPLING FREQUENCY Annual flux within 10%, 20% and 30%

Chamber techniques – data processing

9%

Chamber techniques – auxiliary measurements and repor&ng

9%

Summary

9%

•  Measurements are needed, not only GHG fluxes, but also auxilliary data

•  Chamber techniques are best suited to address the diversity of systems in developing countries, but

•  hierachical approach should be considered (very detailed, detailed, basic)

•  Piralls at every step, QA/ QC is essen@al •  Targe@ng is needed, to close gaps in knowledge

Butterbach Bahl Quantifiying ghg emissions soils chamber method Nov 11 2014

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