Global Forestry and Agricultural Model Initial Results EMF-22 - - PowerPoint PPT Presentation

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Global Forestry and Agricultural Model Initial Results EMF-22 - - PowerPoint PPT Presentation

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Global Forestry and Agricultural Model Initial Results EMF-22 Meeting, Tsukuba, Japan December, 2006 Brent Sohngen, Suk-won Choi, Bin Sun Ohio State University Tom Hertel, Alla Golub, Huey-Lin Lee(Purdue), Roger Sedjo (RFF), Robert

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SLIDE 1

Global Forestry and Agricultural Model Initial Results

EMF-22 Meeting, Tsukuba, Japan December, 2006

Brent Sohngen, Suk-won Choi, Bin Sun Ohio State University Tom Hertel, Alla Golub, Huey-Lin Lee(Purdue), Roger Sedjo (RFF), Robert Mendelsohn (Yale) Massimo Tavoni (FEEM) Funding: U.S. Department of Energy, Office of Biological and Environmental Research U.S. Environmental Protection Agency, Climate Analysis Branch;

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SLIDE 2

Two Issues:

  • Are Forests a Transition Tool?

– Results from Link with Integrated Assessment Model assessing a 500 ppm constraint. – WITCH Model (FEEM) linked to Global Timber Model, with Massimo Tavoni (FEEM)

  • Toward Development of PE Forest and Agr. LU Model

– PE Forest and Agricultural LU model – Structure of global forestry and agriculture model – Data – Analysis so far – Next Steps

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SLIDE 3

Are Forests a Transition Tool?

  • Link an IAM with Forestry/LU Model.
  • WITCH

– A dynamic model to study the economics of climate change – TOP DOWN optimization framework, with a energy sector description and a game theory set up.

  • World, 12 regions
  • Economy: optimal growth
  • Energy: Energy sector specification
  • Climate: damage feedback
  • The 12 regions interact strategically
  • Analysis: What Impact does forestry have
  • n “optimal” carbon prices under a

stabilization scenario?

– 550 ppm

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SLIDE 4

Emission Profile

Policy: 550 ppm constraint. Without Forestry

World Industrial Carbon Emissions (GtC)

5 10 15 20 25 2 2 2 1 2 2 2 2 2 3 2 2 4 2 2 5 2 2 6 2 2 7 2 2 8 2 2 9 2 2 1 2 BAU 550

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SLIDE 5

Trajectories in the energy intensity/carbon intensity wrt first period

  • 5%

0% 5% 10% 15% 20% 25% 0% 10% 20% 30% 40% 50% 60% Reduction in Energy Intensity wrt first period Reduction in Carbon Intensity wrt first period 550 w/out forest BAU

Energy Abatement Options

550 PPM; Without Forestry

Policy induces significant reduction in carbon and energy intensities

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SLIDE 6

Energy Abatement Options

550 PPM; Without Forestry

W orld Electric ity Generation TWh 2000 2020 2040 2060 2080 2100 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 x 10

4

Bac k Nuc lear Hydroelectric Oil Gas Adv Coal+CCS Coal deSOX deNOX Old Coal W ind&S olar

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SLIDE 7

Adding Forestry Reduces Carbon Prices by ~ 56%

  • ver Century & Reduces average rate of price

growth from >7% to 3.8% per year.

Price of Carbon iter 1 iter11 100 200 300 400 500 600 700 800 900 2 2 2 7 2 1 2 2 1 7 2 2 2 2 2 7 2 3 2 2 3 7 2 4 2 2 4 7 2 5 2 2 5 7 2 6 2 2 6 7 2 7 2 2 7 7 2 8 2 2 8 7 2 9 2 2 9 7 2 1 2 1995USD/tC

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SLIDE 8

Reduces Near-Term Income Losses

2000 2020 2040 2060 2080 2100

  • 0.5
  • 0.4
  • 0.3
  • 0.2
  • 0.1

0.1 0.2 0.3 0.4 0.5 W orld Percentage GW P loss

%

550 with Forestry 550 w/out Forestry

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SLIDE 9

Where Does the Sequest. Occur?

2025 2055 2095 Million TCE/year (TgC) USA 42 144 193 OLDEURO 37 82 132 NEWEURO 8 18 29 KOSAU 25 27 36 CAJAZ 31 115 125

  • Trans. Ec.

179 117 134 ME/NA 73 49 31 SubSahA 270 175 106

  • S. ASIA

34 57 32 CHINA 109 155 431

  • E. ASIA

451 481 371 LACA 391 326 330 Total 1649 1746 1950 C Price $57 $113 $271

Red Areas are Largely due to Reducing Defor.

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SLIDE 10

Increases the Trade of Permits

Net Import of Permits (cumulative to 2050)

  • 20
  • 15
  • 10
  • 5

5 10 15 20 USA OLDEURO NEWEURO KOSAU CAJAZ TE MENA SSA SASIA CHINA EASIA LACA GtC 550 w/out forest 550 with forest

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SLIDE 11

Delays Abatement in Energy

World Energy Intensity

50 100 150 200 250 300 2 2 2 1 2 2 2 2 2 3 2 2 4 2 2 5 2 2 6 2 2 7 2 2 8 2 2 9 2 Mtoe/US$ Trillions 550 w/out forest 550 with forest BAU

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SLIDE 12

Forest In “Transition”

  • Forests delay energy abatement. Are forests a transition

tool?

– Forest Carbon worth $1.1 trillion ($55 billion/yr AEA) – Total Economic cost: $2.5 – 12 Trillion (Richels et al.)

  • Transition tools:

– Allow forest projects to enter CDM?

  • Continue efforts to build projects, even though project based

approach suboptimal…

– Develop rules for reducing deforestation

  • Project based?
  • National targets?
  • Indirect programs?

– Use under national caps in developed countries

  • Current approach – but rules for forestry slow to evolve.
  • Competition with Biomass will be a key feature of future.
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SLIDE 13

Global Forest & Ag Model - Model Structure

Dynamic Optimization- Three Sectors

Subject to:

∑ ∑ ∑ ∑ ∑ ∑ ∫ ∑ ∑ ∫ ∑ ∑ ∫ ∑ ∑ ∑

⎪ ⎭ ⎪ ⎪ ⎬ ⎫ ⎪ ⎩ ⎪ ⎪ ⎨ ⎧ − − − + +

T region AEZ regiion Lv region Ag timber F QLv region Lv AEZ Lv Lv Lv QAg region Ag AEZ Ag Ag Ag QF region AEZ timber F F

C C C dQ L K X Y D dQ L K X Y D dQF m H a Y D Max

16 18 16 18 16 18 6

) ) , , ( ( ) , , ( ( ) ) , , ( ( ρ ⎪ ⎪

  • Forestry Production (Dynamic)
  • Crop Production
  • Livestock Production
  • Land Supply
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SLIDE 14

Structure of Production

Crops output Intermediate inputs Value added nest Capital Land Labor

∑∑

i a i t a t a i Y

H

, ,

QF(·) = Forestry Crops Livestock

AEZs

Livestock output Intermediate inputs Value added nest Capital Land&Feed Labor AEZs Land Feed Livestock output Intermediate inputs Value added nest Capital Land&Feed Labor AEZs Land Feed

σ = 20 σ = 0.5 σ = 0.24 σ = 20 σ = 0.24

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SLIDE 15

Production units are denominated by AEZ’s and 16 regions

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SLIDE 16

Regions

AEZs

  • F. Types

US 10 6 CHINA 12 6 BRAZIL 6 5 CANADA 8 4 RUSSIA 7 5 EU ANNEX I 9 5 EU NON-ANNEX 7 4 SOUTH ASIA 9 5 CENT AMERICA 12 5 REST SOUTH AM 18 5 SUB SAHARAN AF 9 4 SOUTHEAST ASIA 5 3 OCEANIA 9 5 JAPAN 5 2 AF MIDDLE E 3 2 EAST ASIA 4 3

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SLIDE 17

Land Supply

  • Land imperfectly

mobile across crops, livestock and forests.

  • Use CET function
  • Calibrated on initial

areas & rents

  • t = 0.9

Total Land in AEZ

LC LL LF1 LF2 LF3

[ ]

⎟ ⎠ ⎞ ⎜ ⎝ ⎛ − − − −

+ + ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛ =

1 1 , , 1 , , 1 , , , , τ τ τ τ τ τ τ τ τ τ

α α α α

j F j F j L j L j c j c j C j C j Ag L

R R R R XE XL

t = - 0.9

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SLIDE 18

Land Supply Calibration

  • Land Supply calibration based on current

area of accessible land

  • Can purchase new units of endowment in

regions with substantial inaccessible land

– Brazil, RSAM, Central Amer., S. Asia, SE Asia, Sub Saharan Africa

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SLIDE 19

Baseline Information

  • Demand Functions

i t i

n t i e t t i t i

P I A Q

−

= ) ( ) )( (

, , ,

,

  • Demand Functions

eCrops = 0.17 ↓ 0.06 nCrops = 0.25 eLivestock = 0.62 ↑ 0.76 nLivestock = 0.71 eForest = 0.88 ↑ 0.93 nForest = 1.10

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SLIDE 20

GDP/Capita Projections

5,000 10,000 15,000 20,000 25,000 30,000 35,000 40,000 2005 2015 2025 2035 2045 2055 2065 2075 2085 2095 2105 Year GDP/Capita

GTAP Projection Adapting Mosaics

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SLIDE 21

Technical Change % Ann.

  • Chg. TFP

Nin et al. (2003)

Crops Livestock US 2.50 1.20 CHINA 0.70 1.80 BRAZIL

  • 0.45
  • 0.95

CANADA 2.50 1.20 RUSSIA 0.55

  • 0.20

EU ANNEX I 2.50 1.20 EU NON-ANNEX 1.55 0.63 SOUTH ASIA

  • 1.70

0.83 CENT AMERICA 0.03 0.83 REST SOUTH AM 0.98 0.52 SUB SAHARAN AF

  • 0.32
  • 0.01

SOUTHEAST ASIA

  • 0.53

1.32 OCEANIA 2.50 1.20 JAPAN 1.00 1.00 AF MIDDLE E 0.20 0.01 EAST ASIA

  • 0.53

1.30

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SLIDE 22

Caution: ALL RESULTS ARE PRELIMINARY Comments Welcome….

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SLIDE 23

Results: Prices

50 100 150 200 250 2005 2015 2025 2035 2045 2055 2065 2075

Year Price Index (2005 = 100) CropsGT LiveGT ForGT CropsAM LiveAM ForAM

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SLIDE 24

Results: Outputs

Crop Output Index (2005 = 100)

50 100 150 200 250 300 350 400 450 2005 2015 2025 2035 2045 2055 2065 2075 Year Index US CHINA BRAZIL OECDO ROW TOTAL

Livestock Output Index (2005 = 100)

200 400 600 800 1000 1200 1400 1600 1800 2000 2005 2015 2025 2035 2045 2055 2065 2075 Year Index US CHINA BRAZIL OECDO ROW TOTAL

Feed Proportion of Total Crop Output

0.00 0.20 0.40 0.60 0.80 1.00 1.20 2005 2015 2025 2035 2045 2055 2065 2075 Year Proportion US CHINA BRAZIL OECDO ROW TOTAL

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SLIDE 25

Results: Global Land Area

500 1,000 1,500 2,000 2,500 3,000 3,500 2005 2015 2025 2035 2045 2055 2065 2075

Year Million Hectares

CrGT LvGT ForGT CrAm LvAm ForAm

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SLIDE 26

Results: Regional Land Areas

GTAP GDP & Population

Crop Area

200 400 600 800 1000 1200 1400 1600 1800 2005 2015 2025 2035 2045 2055 2065 2075 Year Million hectares US CHINA BRAZIL OECDO ROW TOTAL

Forest Area

500 1000 1500 2000 2500 3000 3500 2005 2015 2025 2035 2045 2055 2065 2075 Year Million hectares US CHINA BRAZIL OECDO ROW TOTAL

Livestock Area

500 1000 1500 2000 2500 3000 3500 2005 2015 2025 2035 2045 2055 2065 2075 Year Million hectares US CHINA BRAZIL OECDO ROW TOTAL

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SLIDE 27

Results: US Crops & Grazing

GTAP GDP & Population

US Crop Areas (GT)

10 20 30 40 50 60 70 80 2005 2015 2025 2035 2045 2055 2065 2075

Year Million Hectares

AEZ1 AEZ2 AEZ3 AEZ4 AEZ5 AEZ6 AEZ7 AEZ8 AEZ9 AEZ10 US Crop Rents (GT) 20 40 60 80 100 120 140 160 1 2 3 4 5 6 7 8

Year 2005 $/hectare

AEZ1 AEZ2 AEZ3 AEZ4 AEZ5 AEZ6 AEZ7 AEZ8 AEZ9 AEZ10

US Livestock Areas (GT)

20 40 60 80 100 120 140 160 180 200 1 2 3 4 5 6 7 8

Year Million Hectares

AEZ1 AEZ2 AEZ3 AEZ4 AEZ5 AEZ6 AEZ7 AEZ8 AEZ9 AEZ10 US Livestock Rents (GT) 50 100 150 200 250 1 2 3 4 5 6 7 8

Year Million Hectares

AEZ1 AEZ2 AEZ3 AEZ4 AEZ5 AEZ6 AEZ7 AEZ8 AEZ9 AEZ10

Tech change is positive in both crops and livestock

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SLIDE 28

Results: Brazil Crops & Grazing

GTAP GDP & Population

Brazil Crop Areas (GT)

10 20 30 40 50 60 2005 2015 2025 2035 2045 2055 2065 2075

Year Million Hectares

AEZ1 AEZ2 AEZ3 AEZ4 AEZ5 AEZ6 Brazil Crop Rents (GT) 20 40 60 80 100 120 140 2005 2015 2025 2035 2045 2055 2065 2075

Year 2005 $/hectare

AEZ1 AEZ2 AEZ3 AEZ4 AEZ5 AEZ6

Brazil Livestock Rents (GT)

1 2 3 4 5 6 7 2005 2015 2025 2035 2045 2055 2065 2075

Year $/Hectare (2005 USD)

AEZ1 AEZ2 AEZ3 AEZ4 AEZ5 AEZ6

Brazil Livestock Areas (GT)

20 40 60 80 100 120 140 160 2005 2015 2025 2035 2045 2055 2065 2075

Year Million Hectares

AEZ1 AEZ2 AEZ3 AEZ4 AEZ5 AEZ6

Tech change is negative in both crops and livestock

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SLIDE 29

Results: US & Brazil Forests

GTAP GDP & Population

U.S. Productive Forest Area 10 20 30 40 50 60 70 2005 2015 2025 2035 2045 2055 2065 2075 Year Million Hectares AEZ1 AEZ2 AEZ3 AEZ4 AEZ5 AEZ6 AEZ7 AEZ8 AEZ9 AEZ10

US Forest Rents (Average for AEZ) $0 $20 $40 $60 $80 $100 $120 $140 2005 2015 2025 2035 2045 2055 2065 Year $/hectare (2005) AEZ1 AEZ2 AEZ3 AEZ4 AEZ5 AEZ6 AEZ7 AEZ8 AEZ9 AEZ10

Brazil Productive Forest Area 10 20 30 40 50 60 70 80 2005 2015 2025 2035 2045 2055 2065 2075 Year Million Hectares AEZ1 AEZ2 AEZ3 AEZ4 AEZ5 AEZ6 Brazil Productive Forest Rents $0 $20 $40 $60 $80 $100 $120 $140 $160 $180 2005 2015 2025 2035 2045 2055 2065 2075 Year $/Hectare (2005 USD) AEZ1 AEZ2 AEZ3 AEZ4 AEZ5 AEZ6

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SLIDE 30

Carbon Emissions

Sensitivity to Demand & Technology

1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 10,000 2005 2015 2025 2035 2045 2055 2065 2075 Year Carbon Emission (MMTCE) ForestGT CropGT LiveGT Forest AM CropAM LiveAM 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 2005 2015 2025 2035 2045 2055 2065 2075 Year Carbon Emission (MMTCE) ForestGT CropGT LiveGT Forest GTHT Crop GTHT Live GTHT

Alternative Demand Alternative Tech. Chg.

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SLIDE 31

Forestry Carbon Emissions

Sensitivity to Tech. Chg.

200 400 600 800 1,000 1,200 1,400 2005 2015 2025 2035 2045 2055 2065 2075 Year Carbon Emission (MMTCE) ForestGT Forest GTHT TSM Baseline

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SLIDE 32

Next Steps

  • Refine Baseline
  • Develop carbon sequestration scenarios –

forest only

  • Introduce new sectors

– Ruminant/non-ruminant – Different crops (e.g., rice paddies)

  • Introduce abatement in agriculture