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Alternative Approaches to Quantifying and Reporting Carbon Sequestration Projects: The Case of Afforestation. Allan Sommer and Brian Murray (RTI) [email protected] Third USDA Symposium On Greenhouse Gases and Carbon Sequestration in Agriculture and Forestry, March 21-24, Baltimore MD. - PowerPoint PPT Presentation
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Alternative Approaches to Quantifying and Reporting Carbon Sequestration Projects: The Case of Afforestation.
Allan Sommer and Brian Murray (RTI)
Third USDA Symposium On Greenhouse Gases and Carbon Sequestration in Agriculture and Forestry, March 21-24, Baltimore MD
Outline of Presentation and Analysis
Overview of the role mitigation projects and quantification protocols play in GHG policy
Application of a generalized WRI/WBCSD GHG Protocol to a hypothetical mitigation project
Implications that variation in quantification procedures and protocols may have on quantified project benefits
Project Based Approaches to GHG Mitigation
Projects involve intentional activities or actions to reduce GHG’s
The product of these projects may (may not) be used to produce GHG emission offsets
Mitigation projects are voluntary, not required by law
Development of mitigation projects contain nuances that are location and sector specific
GHG Mitigation Project Programs/Registries
Domestic US Federal
Section 1605(b) of the Energy Policy Act of 1992: GHG Registry
State California Climate Action Registry Oregon Climate Trust Other emerging state programs
Private Chicago Climate Exchange
International Kyoto Mechanisms (JI and CDM)
The Role of “Protocols”
Emergence of different project-based GHG mitigation projects has created some confusion and demand for quantification/reporting standards
Protocol guidance on methods for quantifying and reporting GHG emission and sequestration effects at the project level
Current Efforts Program-specific: e.g., CA registry protocol,
1605(b), Kyoto Broad/harmonization: WRI/WBCSD
General Framework for Project Quantification
If No, Revise as needed Yes
Estimate Secondary Effects
Bottom-up (Project-specific) Approach
Top-down (Performance Standard) Approach
Set Project
Baseline
Calculate Net GHG Effects
Benefit-cost Screening
Define Project Dimensions
Initial AssessmentDefine primary and secondary effectsDetermine eligibilityPerform initial screening
oAdditionalityoLeakage
Assess Costs
Revise as needed
Report Estimates resulting from Baseline Approach
Estimate Project GHG Effects
Project Baselines and Additionality
General Definitions Baselines – activity and GHG effect that would
occur without the project Additionality – GHG mitigation relative to the
baseline
Two options/methods to setting baselines exist Project specific approach – bottom-up
approach, detailed evaluation of the circumstances pertaining to a specific project
Performance standard approach – top-down approach, based on the historical activities in a region and tracking the performance of a reference group over time
Case Study Application of Bottomland Hardwoods in the Lower Mississippi Valley
Project Description Afforestation of
marginal croplands in Miss. River Valley
Frequently flooded (2-year floodplain)
Issaquena County 13,784 acres in total;
2,000 met selection criteria
.Legend
LYRB
Mississippi
Data Sources
Biophysical Data Land Use Characterization (National Resource
Inventory) Geo-referenced Soil type, elevation etc Timber yields (Local Growth and Yield Functions) Carbon yields (FORCARB)
Economic Data Timber prices and costs Agriculture prices and costs
Preliminary Assessment
Generally involves a qualitative assessment of the following: Eligibility of project activities and GHG pools Initial screening for
Additionality Leakage
Assess Project Costs Assess Project Benefits
Project GHG Quantification
Recall basic steps from general quantification framework
Performance Standard Approach to setting baselines
1. Estimate the baseline afforestation rate NRI Data and logistic regressions to calculate annual
afforestation rates in MS counties
2. Estimate Baseline Carbon Accumulation Combine county specific afforestation rates with
carbon yield functions (time-dependent and dynamic), biophysical data, and forest carbon prediction model
Quantification: Estimate Baseline Afforestation Rate Using Logistic Regression Analysis
Lower and Upper Explanatory Variables Coef. P>| z| [95% Conf. Interval] Issaquena 0.38 0.69 -1.47 2.24
Sharkey -1.24 0.28 -3.50 1.02
Warren 1.13 0.23 -0.72 2.98
Yazoo -0.12 0.90 -1.96 1.72
Flooding_freq 0.75 0.00 0.26 1.25
Constant -3.07 0.00 -4.76 -1.38
• Full State Sample 82 Counties (4,299 observations)• County coefficients show effects relative to omitted county. • 81 of the 82 MS Counties were included in the regressions however only those in the LYRB used in the analysis are presented here.
Dependent Variable: Plot Conversion to Forest
Baseline Afforestation Rate Confidence Interval Upper Bounds Derived from Regression Analysis
Issaquena
Sharkey Warren Yazoo
Mean 0.80% 0.18% 1.41% 0.52%
Upper Bound of CI
1.58% 0.76% 2.38% 1.43%
Calculated from confidence intervals, upper bound most conservative
Baseline Quantification: Carbon Accumulation at Different Points in Time
Baseline carbon accumulation at year 10 and 60
1,509
62,723
2,634
69,624
-
20,000
40,000
60,000
80,000
10 years 60 years
Baseline Afforestation Rate (Mean) Baseline Afforestation Rate (Upper Bound)
Estimate Gross Project GHG: No Additionality or Leakage Adjustments
Estimated project carbon for year 10 and 60 Assume with project all trees planted in 1st year Quantities accumulated after 10 yrs, 60 yrs given
below
Soil Type Project Acres
C Accumulation Projection by Year 10 (tC)
C Accumulation Projection by Year 60 (tC)
1 1,506 30,554 170,751
2 149 3,254 18,232
3 345 8,130 45,664
Total 2,000 41,938 234,677
Estimate Secondary Effects – Leakage
Leakage: Shifting of GHG emissions to outside project boundaries (undermines project GHG benefits)
Estimates derived from study by Murray, McCarl and Lee (2004) Commercial forestry in South-Central USA is
estimated to be ~20% Adjust project GHG benefits downward by 20% See Murray presentation (this session) for more
details on leakage
Calculate Net Project Carbon Benefits (Gross – Baseline – Leakage)
-
50,000
100,000
150,000
200,000
250,000
Baseline Project Additional =Project -Baseline
Net =Additional -
Leakage
Acc
um
ula
ted
C i
n Y
ear
60
)
Performance Standard (Central Mean) Performance Standard (Upper Bound)
Sources of Variation in Results
Choosing the project-specific (“case study”) approach to establishing the baseline would result in all project carbon being deemed additional in our example
If timber harvesting is allowed, debits are imposed for carbon reversal
Natural disturbances also produce the potential for carbon reversal and debiting
These and other sources for variation in project results can affect project economic returns
Impacts on Economic Returns
Economic returns under different baseline stringency levels (Confidence intervals from regression results)
0
10
20
30
40
50
60
70
NP
V P
roje
ct
Re
turn
s $
/Ac
re
Performance Std. (Upper) Performance Std. (Mean)
Impacts on Economic Returns
Economic returns with and without baseline adjustments
0
20
40
60
80
100
120
NP
V P
roje
ct R
etu
rns
$/
Acr
e
Baseline Adj. No Baseline Adj.
Impacts on Economic Returns (cont.)
Commercial Forestry vs. Forest Preservation
51
54
57
60
NP
V P
roje
ct R
etur
ns $
/Acr
e
Preservation Forestry Commercial Forestry
Program-Specific Issues: CA Registry
Baseline guidance - additionality
Eligibility: Pools - above ground only
Secondary effects – leakage not required in CCAR
0
10
20
30
40
50
60
70
80
NP
V P
roje
ct R
etu
rns
$/A
cre
Baseline & Leakage (WRI)
Baseline, Above Grnd. Pools & Leakage Adj
Baseline & Above Grnd. Pools (No Leakage Adj)
Summary and Recap
Protocols are needed to ensure consistency of GHG project reporting
Program-specific and cross-program protocols are now being developed
Treatment of Baselines/Additionality and Leakage can substantially alter project benefits and economic returns
More work is needed to create project-based empirical estimates