Delivering information for national low-emission development strategies: acti...
T Tennigkeit soil carbon overview and issues july 2010
1. Soil carbon simulation models for carbon accounting: Overview and research issues
FAO, CCAFS and CGIAR joint workshop: Towards a Framework for Smallholder Agricultural Mitigation: Soil Carbon Measurements and Simulation Models, Rome July 13th2010, presented by Timm Tennigkeit; UNIQUE forestry consultants
2. Steady state of soil carbon accounting methodologies
Methodology
Status
Targeted standard/ applicationand key features
Sustainable AgriculturalLand Management (SALM)
Developer: World Bank BioCarbonFund
1stvalidationcompleted, except clarification from VSC requested related to the conditions to use of soil carbon models
VCS, broad applicabilitywith focus on smallholder agriculture.
Production/activity monitoring and model based default values.
Adoption of Sustainable Grassland Mgmt through Adjustment of Fire & Grazing
Developer:SyracuseUniversity, Soils for the Future LLC, JadoraInt. LLC
Public review process, 1stvalidation initiated
VCS, broad applicabilitywith focus on unfertilized grasslands, incooperatinglessons learned from SALM methodology.
Activity monitoring & model based AND ex-post rectification of ex-ante estimates based on soil C measurements.
Others
Still in the development/ review process or waiting until related business deals are signed before entering public review/domain
VCS, American CarbonRegistry, Panda Standard, Alberta Standard
3. Means to quantify carbon creditsSource: Coalition of Agricultural GHG (C-AGG)
Activity monitoring +
Remote sensing based, technology not ready to use
Direct emission measurements
Direct soil measurements
RothC, CENTURY, DNDC
4. Most widely used carbon simulation models
Simulation model
Application
Input data requirements
RothCfrom the RothamstedAgricultural Research Centre in the UK
Originallydeveloped for UK for agriculture
Mostflexible and less demanding compared with CENTURY or DNDC with regards to input data. In particular the version used in the Australian carbon accounting system is very user friendly.
CENTURYfrom Natural Resource Ecology LaboratoryColorado State University in the US
Originallydeveloped for grasslands in the US
Flexible and less demanding compared with DNDC with regards to input data
DNDC i.e. DeNitrification- DeComposition) is a computer simulation model of carbon and nitrogen biogeochemistry in agro-ecosystemsfrom the University of New Hampshire
Mainly for projects that aim to improve the use of fertilizer
Verydemanding with regards to input data and since the model is updated very frequently in-depth understanding of the model is required
5. Steps involved to develop a land based carbon accounting system for smallholder agriculture The Western Kenya Smallholder Agriculture carbon project
6. Flowchart of carbon stock change estimation
ΔC
Activity data(ha)
Emission factor (tCO2/ha/year)
=
XDefault value development
•Literature & expert knowledge
•C modeling
•Existing data
Project inventory & survey system-
Soil Organic Carbon
BiomassProject
BiomassBaseline
+
Project scenario
FactorMANAGEMENT
x
x
FactorLAND-USE
SOC ReferenceSOILTYPE
Baseline scenario*
FactorMANAGEMENT
x
x
FactorLAND-USE
SOC ReferenceSOILTYPE
-
7. RothCmodel calibration
•Stratification project region based on crop production and soil clay content
•Model inputs: Crop productivity Residue production, Clay content, climate parameters, additional residue inputs, additional manure inputs, soil cover in each month (bare or covered)
•Modelling equilibrium soil organic carbon stocks and with project stock changes
•Validation of model results with available research from similar agro- ecological zones using comparable management practices: “BatjesN.H., GicheruP. (2004). Soil data derived from SOTER for studies of carbon stocks and change in Kenya (ver. 1.0; GEFSOC Project). Report 2004/01, ISRIC -World Soil Information, Wageningen”
8. Key monitoring parameter of the SALM methodology
Crop production and activity monitoring:
•Production
•Area, crop, amount of production
•Residuals use
•Burning
•Number and type of livestock
•Manure use
•Cover crops use
•Nitrogen fixing species use
•Fertilizer use
•Estimate N2O emissions from N-fixing species and fertilizer use
•Measure woody perennial growth
•Trees and shrubs
9. Crop production and activity monitoring process
•Estimate number of farmers and the area where SALM activities will be adopted to generate carbon assets.
•Establish a transparent baseline and a monitoring system to reward farmer groups for generating carbon assets
•Receive a written commitment from farmers to adopt “climate smart“ land use practices
Design features:
•Pretesting survey design and sampling size
•Annual survey based on 200 farms (permanent samples), plus 20 temporary farm samples for annual retesting (to control biased treatment of permanent samples), plus 5 % additional plots (to consider late adopters)
•Structured interview + farm sketch map
10. RothC: Default value development
tC/ ha/ yr
for low/ high crop
production
Residues removed from
the field
Residues left in the field
Residues removed & 1 tC/
ha/ year of manure
distributed
Residues removed & 2 tC/
ha/ year of manure
distributed
Residues removed & 4tC/
ha/ year of manure
distributed
Residues left & 1 tC/ ha/
year of manure distributed
Residues left & 2 tC/ ha/
year of manure distributed
Residues left & 4 tC/ ha/
year of manure distributed
Residues removed from the field 0.28/1.34 0.08/ 0.08 0.33/ 0.33 0.65/ 0.65 0.36/ 1.43 0.61/ 1.67 0.94/ 2.00
Residues left in the field - 0.20/ -1.26 0.04/ -1.02 0.37/ -0.69 0.08/ 0.08 0.33/ 0.33 0.65/ 0.65
Residues removed & 1 tC/ ha/
year of manure distributed
0.57/ 0.57 0.28/ 1.34 0.86/ 1.92
Residues removed & 2 tC/ ha/
year of manure distributed
Residues removed & 4tC/ ha/ year
of manure distributed
-0.29/ 0.77 0.28/ 1.34
Residues left & 1 tC/ ha/ year of
manure distributed
0.57/ 0.57
Residues left & 2 tC/ ha/ year of
manure distributed
Residues left & 4 tC/ ha/ year of
manure distributed
Kitale (ViA) t/ ha of production
Low production 1st season 2nd season
Maize 1,01 2,73
Beans 0,39 0,62
Potatoes 2,58 2,16
High production 1st season 2nd season
Maize 7,1 11,4
Beans 2,0 2,2
Potatoes 4,9 6,7
C Model sensitiveness:
• climate data
• soil clay content
• crop production/ residues
• manure application
Example: Mixed cropping with maize, beans, potatoes
11. Project monitoring costs (US$)
Direct soil measurement
Activity
Cost estimate*
Total cost
% of carbon revenues
Project activity documentation
16 /day
80,000
3.2%
Sampling &reporting (incl. transport, contracted tonational research organization)
52/sample
452,400
18.3%
Soilsample analysis (laboratory)
18 /sample
156,600
6.3%
Sample archiving
0.1 /sample/month
104,400
4.2%
Management and administration
10%
79,340
3.2%
Activity & productivity monitoring survey (APMS)
Survey pretesting and training
16/day
138,048
5.6%
APMS survey & reporting
8/survey
24,488
1%
Surveyanalysis & database management
8/survey
24,488
1%
SOC modeling
50,000
2%
Management and administration
10%
23,702
1%
* Data sources: Canada’s Greenhouse Gas Offset System 2006: Guide to developing a quantification methodology and protocol; Winrock2004: Measurement and monitoring costs: influence of parcel contiguity, carbon variability, project size and timing of measurement events. Kenya project data.
12. Total cost comparison
Direct measurement
Crop production & activity monitoring
Project cost item
Total cost
% of carbonrevenues
Total cost
% of carbonrevenues
Carbon component
316,819
13%
316,819
13%
Carbon monitoring
872,740
35%
260,726
11%
Project implementation
1,293,600
52%
1,293,600
52%
Total costs
2,483,159
100%
1,871,145
76%
•Direct measurements would substantially increase carbon monitoring costs for the Kenya BioCarbonFund project without necessarily reducing uncertainty
•Major challenge in measuring SOC: measuring small changes against high background levels, sampling costs
•Crop production and activity monitoring: Quality assurance mechanisms are important
•Model: Application of models has to be standardized; i.e. model parameter should be constant in the baseline and the project scenario run
13. Related research issues
•Long-term controlled soil carbon monitoring plots for all farming systems and agro-ecology zones (or any other more appropriate stratification system)
•Critical assessment of agricultural mitigation and adaptation technologies from a agronomy, ecological and socio-economic perspective (considering scale issues from plot to landscape)
•Suitable inventory and statistical monitoring design (combining micro- plots, with remote sensing based technologies and direct emission measurements)
•Cost/benefit benchmarking for soil carbon models and soil carbon monitoring systems
•Implications from soil health research results for agricultural extension (demand specific aggregation & disaggregation of soil research results)
•Farmer aggregation mechanisms (cooperatives, farmer groups, farmer field schools, outgrowershemes) and performance based agricultural monitoring and extension