1. Soil Carbon Measurement Costs and Protocols Using a Linked Economic and Biophysical Model
Forestry and Agriculture GHG Modeling Forum
October 9th, 2002
Siân Mooney
Dept. Agricultural and Applied Economics
University of Wyoming

2. Other Collaborators John Antle and Susan Capalbo
Dept. Agricultural Economics and Economics
Montana State University
Keith Paustian
Natural Resource Ecology Laboratory
Colorado State University

3. Motivation C sequestration in agricultural soils C is “invisible”
Is it possible to sell?
Need monitoring/measurement
Possibly have large number of producers
How to design monitoring/measurement
Will it be too costly?

4. Study Objectives
Develop a measurement protocol for C credits sequestered in agricultural soils
Estimate its cost for a region of the US
Examine characteristics that influence measurement costs

5. Influence of Contract Design
Contract design will determine monitoring and measurement needs
Per-hectare contract
Per-credit contract
$MM=$monitoring practice+$measuring C

6. Measurement Issues Several producers – cover large area
Statistical sampling
$M=f(#samples,$/sample,frequency)
Combine field measurements and predictive models

7. Measurement - General Predictive biophysical models – estimate C
Measure baseline – statistical sampling/field samples/lab testing
Measure C periodically over duration of contract
Measure C at end of contract

8. Measurement - Specific
Stratified random sampling
Sample population – producers with contracts to supply C-credits
Strata based on crop system change
Cost/sample
$16.37
Frequency – 4 times
Years 1, 5, 10, 20.

9. Study Area Field level production data
Climate, soil and biophysical characteristics

10. Models parameter estimates carbon estimates
Econometric Models
(output supply, input demand)
Century Ecosystem Model
(NREL)
parameter estimates
carbon estimates
1. #producers participating
2. #producers in each strata
3. Opportunity cost of system changes
Land use simulation
-stochastic output and input prices
-policy designs and payment levels

11. Cost per credit (5% , 95% confid)
Price
/credit ($)
Sub-MLRA 52-high
Sub-MLRA 52-low
Sub-MLRA 53-high
MPC
($)
M Cost
(% of Price) 10
0.18
1.81
0.30
3.03
0.29
2.99 50
0.05
0.10
0.13
0.26
0.19
0.38
100
0.03
0.09
0.16
Price
/credit ($)
Sub-MLRA 53-low
Sub-MLRA 58-high
Sub-MLRA 58-low
MPC
($) M
Cost
(% of Price)
M Cost 10
1.05
10.57
0.14
1.39
0.29
2.92 50
0.51
1.03
0.07
0.18
0.37
100
0.39
0.05
0.13

12. C Change Variability and Cost per Credit
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.5 1
1.5 2
2.5 3
3.5
Cost/credit
Coefficient of Variation in C Changes
52H
52L
53H
53l
58H
58L
Variability Decreasing

13. Conclusions
Measurement costs not large enough to prevent producers from participating in C market
Efficiency of measurement protocol depends on the price of credits
Measurement costs largest in spatially heterogeneous areas

14. Other issues
Uncertainty associated with initial C change estimates (see other paper on web)
Baseline – will change costs per credit

15. Additional Information
Siân Mooney
Dept. Agricultural and Applied Economics
University of Wyoming
Phone: