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Session 2
Peat Emission Factors:
Scientific Background
Erin Swails and Kristell Hergoualc’h
13 April 2020
Objectives
• Increase understanding of data requirements for
development of peat emission factors to estimate:
o Peat carbon dioxide (CO2) emissions/removals
§ Net peat decomposition loss
§ Dissolved organic carbon
§ Peat fire
o Methane (CH4) and nitrous oxide (N2O) emissions from peat
o Emissions from peat fire: CO2, CH4 and carbon monoxide (CO)
Tier 1 and Tier 2 emission factors (EFs)
• Wetlands Supplement Ch 2 and Ch 3 Annexes
provide methodological steps and data sources for
deriving Tier 1 EFs
• Tier 2 EFs may be refined with country or region-
specific data, or by peat nutrient status, climate, etc.
• Models can be used to derive relationships with
environmental parameters for development of Tier 2
EFs
Peat CO2 emissions and removals
Net peat decomposition loss determined by the
balance of inputs from litterfall and roots and outputs
from heterotrophic (microbial) soil respiration
(Drösler et al. 2013)
Calculating CO2 emissions from net peat
decomposition loss
1. Change over time in C stock
2. Balance of C fluxes
Peat C stocks: high spatial
variability, sampling to
mineral soil – Not
recommended by IPCC
C transfer into and out of peat
Time 1, Stock 1 Time 2, Stock 2
Peat Peat
CIn COut
Photo credit: K. Hergoualc’h
Non-CO2 GHG emissions from peat
• Methane (CH4)
o Produced and consumed by soil microorganisms
o Wetland vegetation (e.g. rice plants) can act as conduit from the
soil to the atmosphere
• Nitrous oxide (N2O)
o Produced and consumed by soil microorganisms
o High emissions can be expected as the result of N mineralization
and nitrogen fertilization in drained peatlands
• Global warming potential (GWP)
o Capacity of GHG to warm the
atmosphere
o 100 year time horizon (IPCC)
GHG CO2 CH4 N2O
GWP 20 years* 1 86 268
GWP 100 years* 1 34 298
*With climate carbon feedback (Myhre et al. 2013)
Soil GHG measurement using chambers
• High temporal variability of fluxes
o Minimum sampling intensity: every two
months over a year
o Evaluate diel variation in fluxes
o Intensive sampling required when high
emissions suspected – e.g. N fertilization
soilCH4flux
month
Photo credit: K. Hergoualc’h
Soil GHG measurement using chambers
• High spatial variability of fluxes
o Stratified sampling approach when
different spatial positions suspected to
consistently produce different emission
rates
§ Example 1. Peat swamp forest: hummock/hollow
§ Example 2. Oil palm on peat: close to/far from palm
o Minimum of three replicate chambers per
spatial position (Drösler et al. 2013)
Photo credit: K. Hergoualc’h
Upscaling soil GHG flux in time and space
• Temporal upscaling
o Annual budget calculated by integration
with linear interpolation between
measurement dates, especially if
intensive sampling is undertaken
• Spatial upscaling
o Example: Fertilized oil palm on peat
§ 2 spatial positions – Fertilized zone (FZ) and
Non-fertilized zone (NFZ)
§ Fluxes at the plot scale –
N2Oplot = 10%N2OFZ + 90%N2ONFZ
NFZ
1.5
m
FZ
soilCH4flux
month
Figure: K. Hergoualc’h
Gas sampling and GHG concentration analysis
• Chamber fanned manually previous to
each sampling
• Soil CO2 efflux: Portable infrared gas
analyzer (IRGA)
• Soil CH4, N2O
4 samples/chamber
(t0’, t10’, t20’, t30’)
Transportation to the laboratory
Analysis by gas chromatography
Photo credit: K. Hergoualc’h
Soil respiration partitioning
• Total soil respiration consists of root (autotrophic)
and microbial (heterotrophic) respiration
• Only heterotrophic respiration contributes to net
peat decomposition loss
• Partitioning methods: Incubation of root free soil
cores, respiration-root mass regression, root
trenching, isotopic discrimination
Other peat C fluxes
• Aboveground litter
o Litterfall collected in traps, ‘in situ’ litter
decomposition experiment
• Root dynamics
o Mini-rhizotrons, sequential coring,
ingrowth nets, ‘in situ’ root
decomposition experiment
• Dissolved organic carbon
o Total organic carbon analysis of water
samples
Photo credit: K. Hergoualc’h
Emissions from peat fire
• Which GHGs?
o CO2, CH4, CO
• Amount of each GHG emitted
determined by:
o Area burnt
o Mass of peat available for
combustion (Simpson et al. 2016)
o Peat combustion factor – mass peat
combusted per mass peat burnt
(Konecny et al. 2015)
o Emission factor for each gas – grams
gas produced per kg peat combusted
(Christian et al. 2003, Setyawati et al.
2017)
CO2 COCH4
Photo credit: CIFOR/Rini Sulaiman
Refinement of emission factors for peat fires
• Mass of peat available for
combustion influenced by burn
depth
o Direct measurement
o Remote sensing
• Peat combustion and emission
factors
o Laboratory chamber experiments
Photo credit: Simpson et al. 2016
(Setyawati et al. 2017)
References
Blaine, D, Murdiyarso, D, Couwenberg, J, et al. 2014. Chapter 3: Rewetted organic soils. In Hiraishi T, Krug T, Tanabe K, et al.
(eds) 2013 Supplement to the 2006 IPCC guidelines for national greenhouse gas inventories: Wetlands. Switzerland: IPCC
Comeau L-P, Hergoualc'h K, Smith J and Verchot LV. 2013. Conversion of intact peat swamp forest to oil palm plantation:
Effects on soil CO2 fluxes in Jambi, Sumatra. Working Paper 110. Bogor, Indonesia: CIFOR.
Drösler M, Verchot LV, Freibauer A, et al. 2014. Chapter 2: Drained inland organic soils. In Hiraishi T, Krug T, Tanabe K, et al.
(eds) 2013 Supplement to the 2006 IPCC guidelines for national greenhouse gas inventories: Wetlands. Switzerland: IPCC
Christian, T, Kleiss, B, Yokelson, R et al. 2003. Comprehensive laboratory measurements of biomass-burning emissions: 1.
Emissions from Indonesian, African, and other fuels. Journal of Geophysical Research 108: doi:10.1029/2003JD003704
Konecny, K, Ballhorn, U, Navratil, P et al. 2015. Variable carbon losses from recurrent fires in drained tropical peatland.
Global Change Biology 22: 1469 - 1480
Hergoualc’h K and Verchot LV. 2014. Greenhouse gas emission factors for land use and land-use change in Southeast Asian
peatlands. Mitig Adapt Strateg Glob Change 19:789–807.
Hergoualc’h K and Verchot LV. 2011. Stocks and fluxes of carbon associated with land-use change in Southeast Asian
tropical peatlands: A review. Global Biochemical Cycles 25. doi:10.1029/2009GB003718
Ryan MG and Law BE. 2005. Interpreting, measuring, and modeling soil respiration. Biogeochemistry 73:3–27.
Setyawati, W, Damanhuri, E, Lestari, P, Dewi, K. 2017. Emission factor from small scale tropical peat combustion. IOP
Conference Series: Materials Science and Engineering 180. doi:10.1088/1757-899X/180/1/012113
Simpson, J, Wooster, M, Smith, T, Trivedi, M, Vernimmen, R, Dedi, R, Shakti, M, Dinata, Y. 2016. Tropical peatland burn
depth and combustion heterogeneity assessed using UAV photogrammetry and airborne LiDAR. Remote Sensing 8.
doi:10.3390/rs8121000
Acknowledgements
The capacity building materials were made possible through a
grant given by the Norway’s International Climate and Forest
Initiative (NICFI) to the Center for International Forestry Research
(CIFOR) under the Agreement No. INS 2070-19/0010. While CIFOR
gratefully acknowledges the support, the information provided in
the materials do not represent the views or positions of the
Norwegian Government. CIFOR would like to recognize the support
by the United States Agency for International Development (USAID)
in generating some of information used in the materials.
Thank you

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Peat emission factors: Scientific background

  • 1.
  • 2. Session 2 Peat Emission Factors: Scientific Background Erin Swails and Kristell Hergoualc’h 13 April 2020
  • 3. Objectives • Increase understanding of data requirements for development of peat emission factors to estimate: o Peat carbon dioxide (CO2) emissions/removals § Net peat decomposition loss § Dissolved organic carbon § Peat fire o Methane (CH4) and nitrous oxide (N2O) emissions from peat o Emissions from peat fire: CO2, CH4 and carbon monoxide (CO)
  • 4. Tier 1 and Tier 2 emission factors (EFs) • Wetlands Supplement Ch 2 and Ch 3 Annexes provide methodological steps and data sources for deriving Tier 1 EFs • Tier 2 EFs may be refined with country or region- specific data, or by peat nutrient status, climate, etc. • Models can be used to derive relationships with environmental parameters for development of Tier 2 EFs
  • 5. Peat CO2 emissions and removals Net peat decomposition loss determined by the balance of inputs from litterfall and roots and outputs from heterotrophic (microbial) soil respiration (Drösler et al. 2013)
  • 6. Calculating CO2 emissions from net peat decomposition loss 1. Change over time in C stock 2. Balance of C fluxes Peat C stocks: high spatial variability, sampling to mineral soil – Not recommended by IPCC C transfer into and out of peat Time 1, Stock 1 Time 2, Stock 2 Peat Peat CIn COut Photo credit: K. Hergoualc’h
  • 7. Non-CO2 GHG emissions from peat • Methane (CH4) o Produced and consumed by soil microorganisms o Wetland vegetation (e.g. rice plants) can act as conduit from the soil to the atmosphere • Nitrous oxide (N2O) o Produced and consumed by soil microorganisms o High emissions can be expected as the result of N mineralization and nitrogen fertilization in drained peatlands • Global warming potential (GWP) o Capacity of GHG to warm the atmosphere o 100 year time horizon (IPCC) GHG CO2 CH4 N2O GWP 20 years* 1 86 268 GWP 100 years* 1 34 298 *With climate carbon feedback (Myhre et al. 2013)
  • 8. Soil GHG measurement using chambers • High temporal variability of fluxes o Minimum sampling intensity: every two months over a year o Evaluate diel variation in fluxes o Intensive sampling required when high emissions suspected – e.g. N fertilization soilCH4flux month Photo credit: K. Hergoualc’h
  • 9. Soil GHG measurement using chambers • High spatial variability of fluxes o Stratified sampling approach when different spatial positions suspected to consistently produce different emission rates § Example 1. Peat swamp forest: hummock/hollow § Example 2. Oil palm on peat: close to/far from palm o Minimum of three replicate chambers per spatial position (Drösler et al. 2013) Photo credit: K. Hergoualc’h
  • 10. Upscaling soil GHG flux in time and space • Temporal upscaling o Annual budget calculated by integration with linear interpolation between measurement dates, especially if intensive sampling is undertaken • Spatial upscaling o Example: Fertilized oil palm on peat § 2 spatial positions – Fertilized zone (FZ) and Non-fertilized zone (NFZ) § Fluxes at the plot scale – N2Oplot = 10%N2OFZ + 90%N2ONFZ NFZ 1.5 m FZ soilCH4flux month Figure: K. Hergoualc’h
  • 11. Gas sampling and GHG concentration analysis • Chamber fanned manually previous to each sampling • Soil CO2 efflux: Portable infrared gas analyzer (IRGA) • Soil CH4, N2O 4 samples/chamber (t0’, t10’, t20’, t30’) Transportation to the laboratory Analysis by gas chromatography Photo credit: K. Hergoualc’h
  • 12. Soil respiration partitioning • Total soil respiration consists of root (autotrophic) and microbial (heterotrophic) respiration • Only heterotrophic respiration contributes to net peat decomposition loss • Partitioning methods: Incubation of root free soil cores, respiration-root mass regression, root trenching, isotopic discrimination
  • 13. Other peat C fluxes • Aboveground litter o Litterfall collected in traps, ‘in situ’ litter decomposition experiment • Root dynamics o Mini-rhizotrons, sequential coring, ingrowth nets, ‘in situ’ root decomposition experiment • Dissolved organic carbon o Total organic carbon analysis of water samples Photo credit: K. Hergoualc’h
  • 14. Emissions from peat fire • Which GHGs? o CO2, CH4, CO • Amount of each GHG emitted determined by: o Area burnt o Mass of peat available for combustion (Simpson et al. 2016) o Peat combustion factor – mass peat combusted per mass peat burnt (Konecny et al. 2015) o Emission factor for each gas – grams gas produced per kg peat combusted (Christian et al. 2003, Setyawati et al. 2017) CO2 COCH4 Photo credit: CIFOR/Rini Sulaiman
  • 15. Refinement of emission factors for peat fires • Mass of peat available for combustion influenced by burn depth o Direct measurement o Remote sensing • Peat combustion and emission factors o Laboratory chamber experiments Photo credit: Simpson et al. 2016 (Setyawati et al. 2017)
  • 16. References Blaine, D, Murdiyarso, D, Couwenberg, J, et al. 2014. Chapter 3: Rewetted organic soils. In Hiraishi T, Krug T, Tanabe K, et al. (eds) 2013 Supplement to the 2006 IPCC guidelines for national greenhouse gas inventories: Wetlands. Switzerland: IPCC Comeau L-P, Hergoualc'h K, Smith J and Verchot LV. 2013. Conversion of intact peat swamp forest to oil palm plantation: Effects on soil CO2 fluxes in Jambi, Sumatra. Working Paper 110. Bogor, Indonesia: CIFOR. Drösler M, Verchot LV, Freibauer A, et al. 2014. Chapter 2: Drained inland organic soils. In Hiraishi T, Krug T, Tanabe K, et al. (eds) 2013 Supplement to the 2006 IPCC guidelines for national greenhouse gas inventories: Wetlands. Switzerland: IPCC Christian, T, Kleiss, B, Yokelson, R et al. 2003. Comprehensive laboratory measurements of biomass-burning emissions: 1. Emissions from Indonesian, African, and other fuels. Journal of Geophysical Research 108: doi:10.1029/2003JD003704 Konecny, K, Ballhorn, U, Navratil, P et al. 2015. Variable carbon losses from recurrent fires in drained tropical peatland. Global Change Biology 22: 1469 - 1480 Hergoualc’h K and Verchot LV. 2014. Greenhouse gas emission factors for land use and land-use change in Southeast Asian peatlands. Mitig Adapt Strateg Glob Change 19:789–807. Hergoualc’h K and Verchot LV. 2011. Stocks and fluxes of carbon associated with land-use change in Southeast Asian tropical peatlands: A review. Global Biochemical Cycles 25. doi:10.1029/2009GB003718 Ryan MG and Law BE. 2005. Interpreting, measuring, and modeling soil respiration. Biogeochemistry 73:3–27. Setyawati, W, Damanhuri, E, Lestari, P, Dewi, K. 2017. Emission factor from small scale tropical peat combustion. IOP Conference Series: Materials Science and Engineering 180. doi:10.1088/1757-899X/180/1/012113 Simpson, J, Wooster, M, Smith, T, Trivedi, M, Vernimmen, R, Dedi, R, Shakti, M, Dinata, Y. 2016. Tropical peatland burn depth and combustion heterogeneity assessed using UAV photogrammetry and airborne LiDAR. Remote Sensing 8. doi:10.3390/rs8121000
  • 17. Acknowledgements The capacity building materials were made possible through a grant given by the Norway’s International Climate and Forest Initiative (NICFI) to the Center for International Forestry Research (CIFOR) under the Agreement No. INS 2070-19/0010. While CIFOR gratefully acknowledges the support, the information provided in the materials do not represent the views or positions of the Norwegian Government. CIFOR would like to recognize the support by the United States Agency for International Development (USAID) in generating some of information used in the materials.