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Butterbach Bahl Quantifiying ghg emissions soils chamber method Nov 11 2014

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Presentation at workshop: Reducing the costs of GHG estimates in agriculture to inform low emissions development
November 10-12, 2014
Sponsored by the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) and the Food and Agriculture Organization of the United Nations (FAO)

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Butterbach Bahl Quantifiying ghg emissions soils chamber method Nov 11 2014

  1. 1. 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
  2. 2. 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)
  3. 3. GHG emissions and underlying mechanisms Emission = produc@on (microbial/ chemical) – consump@on (microbial/ chemical) BuZerbach-­‐Bahl et al, 2013, Phil. Trans. R. Soc.
  4. 4. GHG emissions processes and measuring techniques BuZerbach-­‐Bahl et al, 2013, Phil. Trans. R. Soc.
  5. 5. Drivers of soil GHG emissions • 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 • …….. Turner et al. 2008, Plant & Soil Van Beek et al. 2010, Nutr. Cycl Agroecosys.
  6. 6. 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 • ….
  7. 7. Chamber techniques – general points
  8. 8. Chamber techniques – chamber placement
  9. 9. Chamber techniques – chamber placement
  10. 10. Chamber techniques – spa&al variability Arias-­‐Navarro et al., 2013, Soil Biol. Biochem.
  11. 11. 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 Measuring soil N2O emissions from a cropped land-uses soil using chambers. Photo: Graeme Schwenke, NSW, Australia
  12. 12. Chamber techniques – temporal variability APPROACH For each data set, we calculated: 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 Barton et al., 2014, in prep.
  13. 13. Chamber techniques – temporal variability 0 5 10 15 20 25 30 Measurement frequency SAMPLING FREQUENCY & ANNUAL FLUX: ‘Highly’ episodic Steppe grassland, semi-­‐arid climate, Inner Mongolia % Deviation of annual flux 350 300 250 200 150 100 50 0 -50 Barton et al., 2014, in prep.
  14. 14. Chamber techniques – temporal variability Barton et al., 2014, in prep. RECOMMENDED SAMPLING FREQUENCY Annual flux within 10%, 20% and 30% 0 7 14 21 28 Measurement frequency Number of data-sets 25 20 15 10 5 0 Within 10% Within 20% Within 30% 8%
  15. 15. Chamber techniques – data processing
  16. 16. Chamber techniques – auxiliary measurements and repor&ng
  17. 17. Summary • 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

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