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Evaluating Domestic Carbon Markets With Forest Sector Models
Gregory Latta Oregon State University
Sara Ohrel US Environmental Protection Agency
Darius Adams Oregon State University
presented at:
A Community of Ecosystem Services
ACES Meeting 2012
December 13, 2012
Fort Lauderdale, Florida
Disclaimer
• Thoughts & concepts expressed today are those of the presenters only and do not reflect any position or sentiment of the U.S. Environmental Protection Agency.
1
Objectives
• Market models • EPA’s GHG mitigation models
• What is a forest sector model? • My view and overview
• Model solution techniques
• What forest sector models are out there?
• The FASOM-GHG model • What is Forest and Agricultural Optimization Model with Greenhouse Gases
(FASOM-GHG)
• Carbon market modeling example • Use FASOM-GHG
• A few quick results
2
3
What is a Market Model?
•Equilibrium model
•Price endogenous (one to many regions, one to
many industries or sectors, one to many products)
Quantity
Pri
ce
P*
Q*
Demand Curve
Supply Curve
Market Models
4
• Computable General Equilibrium Models • Broad all inclusive models including many industries (sectors)
• Partial Equilibrium Models • Detailed models focusing on specific sectors
Broad Narrow
Sim
ple
C
om
ple
x
Sectoral Scope (eg. Industries Included)
Secto
ral D
eta
il (e
g. Technolo
gie
s)
Partial
Equilibrium
Models
General
Equilibrium
Models
EPA Models and Corresponding GHG Mitigation
5
Domestic Forest and Agriculture Inputs to Larger EPA analysis
6
Figure 1: Total Domestic Forest and Agriculture Offset MACs for constant (a) and rising (b) prices
(avg MtCO2e yr-1
)
$-
$10
$20
$30
$40
$50
0 200 400 600 800 1000
MtCO2e/yr
$/t
CO
2e
2010
2020
2030
2040
2050
$-
$50
$100
$150
$200
$250
0 250 500 750 1000 1250 1500
MtCO2e/yr
$/t
CO
2e
2010
2020
2030
2040
2050
(a) (b)
U.S. EPA, 2009. Updated Forestry and Agriculture Marginal Abatement Cost Curves. Memorandum to John Conti, EIA, March 31, 2009.
Marginal Abatement Cost Curves (MACs) - mitigation supply curves
7
Forest Sector (partial equilibrium) Models by Solution Technique
•Dynamic Recursive
•Solves annual (typically) surplus, updates parameters, repeats
•Shorter-term
•Provides Most likely / Forecast type values
•Mill Manager Perspective
•Intertemporal Optimization
•Solves all time periods’ surplus simultaneously
•Longer-term
•Provides Potential / Possible values
•Forest Manager/Planner Perspective
8
Solution Technique
Quantity
Price
P*1
Q*1
Demand
Supply
Quantity
Price
P*2
Q*2
Demand
Supply
Quantity
Price
P*3
Q*3
Demand
Supply
P*1,2,3
Q*1,2,3 Quantity
Price
Demand1,2,3
Supply1,2,3
Recursive Dynamic
Intertemporal Optimization
Solve time period 1
Maximizing net surplus
Take harvest quantity
Associated with Q*1
Calculate
Inventory – Harvest + Growth
Shifts the supply curve
for the next period
Supply is the sum of
each possible
management in each
period. (steps of possible harvest values)
9
Forest Partial Equilibrium Models
Dyn
amic
Re
curs
ive
TAMM Timber Assessment
Market Model
CGTM CINTRAFOR Global Trade
Model
EFI-GTM European Forest Institute
Global Trade Model
PAPYRUS Model of the North American Pulp and
Paper Industry
IIASA GTM International Institute for Applied
Systems Analysis Global Trade Model
NAPAP North American Pulp
and Paper Model
FASOM Forest and Agriculture Sector
Optimization Model
NTM Norwegian
Trade Model
GFPM Global Forest
Products Model
TSM Timber Supply
Model
NorFor Norwegian Forest
Sector Model
PNW-RM Pacific Northwest Regional Models
SRTS Subregional Timber
Supply Model
EUFASOM European Forest Sector
Optimization Model
USFPM United States Forest
Products Module
SF-GTM Finnish Forest Sector Model
FFSM French Forest Sector Model
Inte
rte
mp
ora
l Op
tim
izat
ion
A little about FASOM-GHG • Linked model of U.S. agriculture and forest sectors
• Utilizes a intertemporal optimization approach to simulate markets for agriculture and forest products
• Tracks a variety of agriculture and forestry resource conditions and management actions
• Mitigation - four fundamental ways to mitigate emissions 1. Change land use
- Afforestation, grassland conversion… 2. Alter management practices
- Soil tillage practices, silviculture, extend timber rotations 3. Alter production levels and activity mix
- More/less animals or a different mix of grass fed / feedlot 4. Bioenergy
10
A little more about FASOM-GHG
11
FOREST SECTOR
MARKETS AND FOREST
LAND BASE: INVENTORY
SILVICULTURAL REGIME
ROTATION
FOREST TYPE
MANUFACTURING
AGRICULTURE
SECTOR MARKETS
AND AG LAND BASE: CROPPING
TILLAGE METHODS
LIVESTOCK
ENERGY SECTOR
FEEDSTOCK MARKETS
LAND USE
CHANGES
FLOWS OF
FEEDSTOCKS
FOR
BIOPOWER &
ETHANOL
Carbon Market Modeling Example
12
• Forest forest sector alone • Simplified – no land use change allowed
• Voluntary carbon market
• Based loosely on the Climate Action Reserves Improved Forest
Management Protocol • 100-year commitment to carbon project
• No land use change
• Payments for sequestration only when above average carbon stocking levels on current private forest
• Carbon stored in harvested wood products (HWP)evaluated at what remains after 50 years
• Caveats • Forest types (strata or stands) enrolled individually
• No baseline HWP values
• Land that does not participate has no control on emissions levels (no penalty)
Participation in Carbon Projects
Regional response differs
South not in at low C
prices
NE not much response
Quite a large enrollment
additionality?
Price CB LS NE PNWE PNWW PSW RM SC SE Total US
$/tonne CO2 ----------------------------------------------- percentage of private timberland base -----------------------------------------------
5 22 31 17 19 13 28 26 0 4 11
10 29 36 20 29 20 28 31 5 10 16
15 30 39 20 31 22 29 33 7 15 19
30 36 41 20 37 29 35 41 14 20 23
50 40 41 22 40 34 36 41 19 23 27
Potential Voluntary Market Participation on US Private Timberland
Forest Inventory Impacts
This was really the goal of the carbon project – you have to
increase the standing stock of trees
Forest Harvest Impacts
This is perhaps a side effect – when people are holding more
timber, harvests can fall
Forest Products Price Impacts
Yet another side effect – when harvests fall, forest products
production falls leading to higher prices
0
5
10
15
20
25
30
35
40
45
50
-60 -40 -20 0 20 40 60 80 100
C P
rice
($/
ton
ne
CO
2e)
Million tonnes CO2e per year
Forest Carbon MAC Scenario X
C_Total
Improved Forest Management Results
C_Total = All Carbon Pools ( both in and out of C market) = The net mitigation at a given price
C_In = All Carbon Pools (In C market)
C_Out = All Carbon Pools (Out of C market)
Tree and Product Carbon Only = The mitigation that the buyers paid for
0
5
10
15
20
25
30
35
40
45
50
-60 -40 -20 0 20 40 60 80 100
C P
rice
($/
ton
ne
CO
2e)
Million tonnes CO2e per year
Forest Carbon MAC Scenario X
C_In C_Total
0
5
10
15
20
25
30
35
40
45
50
-60 -40 -20 0 20 40 60 80 100
C P
rice
($/
ton
ne
CO
2e)
Million tonnes CO2e per year
Forest Carbon MAC Scenario X
C_In
C_Out
C_Total
0
5
10
15
20
25
30
35
40
45
50
-60 -40 -20 0 20 40 60 80 100
C P
rice
($/
ton
ne
CO
2e)
Million tonnes CO2e per year
Forest Carbon MAC Scenario X
C_In
C_Out
C_Total
Tree and Product Carbon Only
A
B C
Given that
•A is the quantity of
mitigation available
•Annual flux on
enrolled lands
And
•B is the net forest
sequestration
•Annual flux on all
lands
Therefore
•C is the quantity of
leakage
•Annual flux on
non-enrolled lands
Linking to the CGE’s
• How do we get these detailed results into an analysis of the economy at large?
• The MAC becomes the potential mitigation supply curve for the CGE
• How do we get the results from the economy at large into the detailed analysis • Linking models is a concept that deserves further exploration
18
Conclusions from our Example
• Policy (or Protocol) structure is important in mitigation effectiveness
• Leakage and Additionality will remain issues
• We most likely won’t get rid of them, so we should design protocols that minimize them
• The problem is worse at low prices
• It is also not constant across C price levels (fixed leakage adjustment factors may not be appropriate)
• Either way – Simple rules will have benefits over complex accounting frameworks
• And – partial equilibrium models are a great way to explore the impacts of such rules
19