Marginal Costs for Soil C: Scale Scenarios

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Sensitivity of Carbon Sequestration Costs to
Scale and to Economic and Biological Uncertainties
Susan M. Capalbo,Montana State University with
the collaboration of John M. Antle, Montana State
University,Siân Mooney, University of
Wyoming,Keith H. Paustian, Colorado State
University
Presented at the ASSA Annual MeetingsWashington,
DCJanuary 5, 2003
2
Acknowledgements
This research was funded by the USDA special
grants CASMGS, the USDA National Research
Initiative Competitive Grants Program, the NSF
Methods and Models for Integrated Assessment
Program, and the EPA STAR Program.
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Objectives
In this paper, we develop methods to investigate
the efficiency of alternative types of policies
or contracts for C sequestration in cropland
soils, taking into account

• 1. The spatial heterogeneity of agricultural
  production systems, and
• Sensitivity of the marginal cost of supplying
  carbon to
• a. carbon rates
• b. scale
• c. yield variations

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Objectives (2)
We describe per-hectare contracts for soil C and
use a model of farmers decisions to participate
in soil C contracts to derive the on-farm
opportunity costs.
We present an integrated assessment modeling
framework, based on coupled site-specific
biophysical simulation models and site-specific
economic data and models, that can be used to
simulate farmers decisions to participate in
both per-hectare contracts.
Using this coupled modeling framework in a case
study of the dryland grain production system of
the Northern Plains region of the United States,
we test the sensitivity of the model to show how
the costs vary depending upon scale of analysis
and uncertainty of input parameters.
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Related Papers Available at www.climate.montana.e
du
Antle, J.M., and S.M. Capalbo, Econometric-Proces
s Models for Integrated Assessment of
Agricultural Production Systems. American
Journal of Agricultural Economics 83 (May 2001)
389-401. Antle, J.M., S.M. Capalbo, S. Mooney, E.
Elliott and K.H. Paustian, Economics of
Agricultural Soil Carbon Sequestration An
Integrated Assessment Approach. Journal of
Agricultural and Resource Economics 26 (December
2001) 344-367. Mooney, S., J.M. Antle, S.M.
Capalbo, and K.H. Paustian, Contracting for
Carbon Credits Design and Costs of Measurement
and Monitoring. Staff Paper 2002-01, Dept. of
Ag. Econ. Econ., Montana State University.
(forthcoming JEEM) Antle, J.M., S.M. Capalbo, S.
Mooney, E.T. Elliott, and K.H. Paustian.
Sensitivity of Carbon Sequestration Costs to
Soil Carbon Rates. Environmental Pollution 116
(March 2002) 413422. Antle, J.M., S.M.
Capalbo, and S. Mooney. Optimal Spatial Scale
for Evaluating Economic and Environmental
Tradeoffs. Selected paper. AAEA Annual Meetings,
Nashville, TN, 1999.
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Designing Contracts for Soil C

• Per-tonne contract pays farmer P/tonne/yr for
  duration of contract
• Payment independent of practice
• Per-hectare contract payment for use of BMP
• Payment independent of quantity of C
• Must monitor practices for compliance with
  contract
• Farmers enter contract if g gt ?ji ?js
• Must quantify amount of C
• Establish baseline
• Measure accumulation of C
• Farmers enter contract ifP gt (?ji - ?js)/?cjis ,
  i.e., if price per tonne is greater than
  opportunitycost per tonne

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Result from Earlier Papers
For each quantity of C sequestered, the marginal
opportunity cost of the per-hectare payment
mechanism (MCH) is greater than or equal to the
marginal opportunity cost of the per-tonne
mechanism (MCT), i.e., MCH ? MCT, and MCT /MCH is
decreasing with spatial heterogeneity.
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Marginal Cost Functions for per-hectare and
per-tonne Payments
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Integrated Assessment Paradigm

• Economic data ? economic production
  models
• Soils climate data ?
• crop ecosystem models
• Output of crop ecosystem models ?
• economic models andenvironmental process models
• Output of economic models ?
  environmental process models

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Structure of an Econometric-Process Simulation
Model
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Design of EconometricProcess Simulation Model

• Estimate econometric production models (system of
  supply and input demand functions) for each
  activity.
• Simulate econometric models with site-specific
  data to obtain expected returns.
• Use structure of decision making process to make
  land use and management decisions.

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Linkage between Century Model and Economic
Production Model
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Simulation of Land Use Using Econometric-Process
Model of Montana Dryland Grain Production

• 1995 MT Cropping Practices Survey
• Statistically representative sample of
  Sub-MLRAs in grain producing regions of MT
• Useable data from 425 commercial grain farms

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Montana Dryland Grain Study Sub-MLRAs
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Soil C Simulations Performed with the Century
Model for Each Sub-MLRA

• Model parameterized for each sub-MLRA using
  various sources of data for soils, climate, and
  cropping practices
• Model executed over 50 years for each cropping
  system for each sub-MLRA to achieve new
  equilibrium soil C levels

• Link economic simulation model to Century
  ecosystem model
• Assess the costs of inducing changes in levels of
  soil C (opportunity costs)
• Alternative policies
• per hectare payments
• per tonne payments

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Land Allocation in Montana Dryland Grain
Production Systems
? Winter Wheat Recrop ? Barley Recrop ?
Spring Wheat Recrop ? Winter Wheat
Fallow ? Barley Fallow ? Spring Wheat
Fallow? Fallow
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Soil C Levels Predicted by Century Model for
Cropping Systems in Montana
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Additions to the Share of Cropland in Continuous
Cropping Base Scenario
Additional Share of CroplandIn Continuous
Cropping
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Changes in Soil C over a 20-Year Time Horizon
Base Scenario
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Marginal Cost of per-hectare andper-tonne
Payment Mechanisms
Sub-MLRA52-high
Sub-MLRA52-low
per-hectare payment per-tonne payment
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Marginal Cost of per-hectare and per-tonne
Payment Mechanisms
Sub-MLRA53a-high
Sub-MLRA53a-low
per-hectare payment per-tonne payment
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Marginal Cost of per-hectare and per-tonne
Payment Mechanisms
Sub-MLRA58a-high
Sub-MLRA58a-low
per-hectare payment per-tonne payment
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Sensitivity of Marginal Cost Results to

• Soil C rates
• Scale for measuring soil C rates
• Yield uncertainties
• Output price uncertainties

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Scenario Descriptions
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Changes in Soil C Rates

• Keep spatial heterogeneity
• Adjust by 50 increase in soil C rates
• Adjust by 50 decrease in soil C rates
• Show results for per hectare contracts

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Sensitivity of Marginal Costs to Carbon Rates,
Sub-MLRA 52-high
per-tonnecontract
per-hectarecontract

• Base Quantity ? 50 Increase in C ? 50
  Decrease in C

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Sensitivity of Marginal Costs to Carbon Rates,
Sub-MLRA 58a-low
per-tonnecontract
per-hectarecontract

• Base Quantity ? 50 Increase in C ? 50
  Decrease in C

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Results of Change in Soil C Rates

• Changes in soil C rates change the quantity of
  soil C sequestered at various prices (shifts the
  MC curve)
• Under per-hectare policy, as soil C rates
  increase, the impact on soil C sequestered
  increases in proportion to the square of the
  increase in soil C rates
• Under per-tonne policy, we have a linear mapping
  of changes in soil C rate and changes in MC curve

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Marginal Costs for Soil CSoil C Rate Scenarios
Sub-MLRA52-high
Sub-MLRA53a-high
Sub-MLRA58a-high

• Base Scenario ? Scenario 1 ?
  Scenario 2
  (150 of base) (50 of base)

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Sensitivity of Marginal Coststo Scale
Use average rates of soil C across all Sub-MLRAs

• Impacts are specific to Sub-MLRA
• Using mean rates of soil C overestimates the MC
  for Sub-MLRA 52-high and 58a-high
• Using mean rates of soil C underestimates the
  MC for Sub-MLRA 53a-high

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Marginal Costs for Soil CScale Scenario
Sub-MLRA52-high
Sub-MLRA53a-high
Sub-MLRA58a-high

• Base Scenario ? Scenario 3

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Sensitivity of Marginal Coststo Output Price
Changes

• Scenario 4 A 10 increase in the mean of the
  estimated sample distributions of output prices
  respectively.
• Scenario 5 A 10 decrease in the mean of the
  estimated sample distributions of output prices
  respectively.

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Marginal Costs for Soil COutput Price Scenarios
Sub-MLRA52-high
Sub-MLRA53a-high
Sub-MLRA58a-high

• Base Scenario ? Scenario 4 ?
  Scenario 5
  (10 Increase) (10 decrease)

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Sensitivity of Marginal Coststo Change in Yields
Scenario 6 A 10 increase in yields for fields
that are in the program.
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Marginal Costs for Soil CProductivity (Yield
Increase) Scenario
Sub-MLRA52-high
Sub-MLRA53a-high
Sub-MLRA58a-high
? Base Scenario ? Scenario 6 (10 yield change)
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Conclusions

• Contracts based on BMPs (per hectare contracts)
  are as much as 5 times more costly than efficient
  contracts that pay per tonne of C, a degree of
  inefficiency similar to that found in studies of
  industrial regulation.
• The case study confirms that the relative
  inefficiency of per-hectare contracts varies
  spatially and increases with spatial
  heterogeneity.
• The estimates of MC are sensitive to four key
  parameters (variable) in the model
• Soil C rates
• Scale of analysis (biophysical scale only)
• Yields
• Output prices

• Uncertainty in an integrated biophysical/economic
  model affects both biophysical and economic
  measures
• Not always a linear mapping
• Policy design plays a key role in assessing
  impacts of uncertainty and scale