The Role of Land Use in Determining Greenhouse Gases Mitigation - - PowerPoint PPT Presentation

▶
the role of land use in determining greenhouse gases
SMART_READER_LITE
LIVE PREVIEW

The Role of Land Use in Determining Greenhouse Gases Mitigation - - PowerPoint PPT Presentation

Sep 19, 2023 169 likes •452 views

The Role of Land Use in Determining Greenhouse Gases Mitigation Costs Thomas Hertel (Purdue Univ.), Huey-Lin Lee (NIES), Steven Rose (U.S. EPA), and Brent Sohngen (Ohio State Univ.) GTAP Working Paper No. 36 (Output from the research project

slide-1
SLIDE 1

The Role of Land Use in Determining Greenhouse Gases Mitigation Costs

Thomas Hertel (Purdue Univ.), Huey-Lin Lee (NIES), Steven Rose (U.S. EPA), and Brent Sohngen (Ohio State Univ.) GTAP Working Paper No. 36 (Output from the research project sponsored by the US-EPA)

slide-2
SLIDE 2

2

Motivation

  • Land is a significant source of GHG emissions

– Deforestation: 1/3 of total emissions since 1850 – Land management: 75% of N2O, 50% of CH4

  • Previous studies suggest land-based mitigation is cost-effective

– e.g., Sohngen and Mendelsohn (2003), Rao and Riahi (in press), van Vuuren et al. (in press)

  • Analytical challenges for land modeling

– Competition for land between land-based sectors – Land-based mitigation competition and net emissions effects – Land heterogeneity and dynamics – Lack of key consistent global data—land, emissions, mitigation costs

  • New global datasets—land, emissions, mitigation costs

Provide opportunities for improving our understanding of the role of land in determining GHG mitigation costs.

slide-3
SLIDE 3

3

Objective: To analyze the impact of GHG mitigation

  • n land use change in general equilibrium

framework Outline of this presentation:

  • Land, GHG emissions/sequestration data
  • Land supply and demand and land-based

emissions modeling in GTAP

  • Analysis set-up
  • Results
  • Conclusions
slide-4
SLIDE 4

4

GTAP AEZ Land Use Data

  • Our work builds on path-breaking work

by Darwin et al. at ERS/USDA, by adding:

– More refined definition of AEZs – Climate dimension—tropical, temperate, boreal – Implementation at the 226-country level – Documented in Lee et al. (2005) and available on the GTAP website

slide-5
SLIDE 5

5

Definition of AEZs in GTAP

  • 18 AEZs = 6 LGPs x 3 climatic zones

– 6 LGPs = 0–59, 60–119, 120–179,…., 300–365 days – 3 climatic zones = boreal, temperate, tropical

  • Follows pioneering work by FAO and IIASA in

definition of an AEZ as

– land with given “length of growing period” (LGP), as determined by: temperature, precipitation, soil condition and topography, combined with information from a water balance model and knowledge of physical requirements for growing certain crop.

  • Lands classified in same AEZ have homogeneous

units within the country—i.e., with similar climate and soil conditions for crop growing.

slide-6
SLIDE 6

6

Global Distribution of AEZs

slide-7
SLIDE 7

7

Global Land Cover: distribution

000000E+ 0 0200E+ 6 0400E+ 6 0600E+ 6 0800E+ 6 1000E+ 6 1200E+ 6 1400E+ 6 1600E+ 6 1800E+ 6 L G P1 L G P2 L G P3 L G P4 L G P5 L G P6 L G P1 L G P2 L G P3 L G P4 L G P5 L G P6 L G P1 L G P2 L G P3 L G P4 L G P5 L G P6 L G P1 L G P2 L G P3 L G P4 L G P5 L G P6 L G P1 L G P2 L G P3 L G P4 L G P5 L G P6 L G P1 L G P2 L G P3 L G P4 L G P5 L G P6 L G P1 L G P2 L G P3 L G P4 L G P5 L G P6 Forest Savan./ grassland Shrubland Cropland Pasture Built- up land Other land A rea (ha)

Boreal Temperate Tropical

slide-8
SLIDE 8

8

  • 20,000

40,000 60,000 80,000 100,000 120,000 140,000 160,000 180,000 AEZ1 AEZ2 AEZ3 AEZ4 AEZ5 AEZ6 AEZ7 AEZ8 AEZ9 AEZ10 AEZ11 AEZ12 AEZ13 AEZ14 AEZ15 AEZ16 AEZ17 AEZ18 1000 hectares Paddy rice Wheat Cereals grain nec Crops nec Vegetables, fruit, nuts Plant-based fibres Oil seeds Sugar cane, sugar beet

Tropical Temperate Boreal

Cropland Hectares by AEZ and crop

Paddy rice Wheat Cereal grain

slide-9
SLIDE 9

9

Distribution of Crop Land Rents, within AEZs

0% 20% 40% 60% 80% 100% 1 AEZ1 2 AEZ2 3 AEZ3 4 AEZ4 5 AEZ5 6 AEZ6 7 AEZ7 8 AEZ8 9 AEZ9 10 AEZ10 11 AEZ11 12 AEZ12 13 AEZ13 14 AEZ14 15 AEZ15 16 AEZ16 17 AEZ17 18 AEZ18 8 ocr 7 pfb 6 c_b 5 os d 4 v_f 3 gro 2 w ht 1 pdr

Vegies/fruits: quick growing, higher value.

slide-10
SLIDE 10

10

Non-CO2 emissions & forest sequest’n data

  • New 2001 non-CO2 emissions data

– Corresponds to GTAP v6 data 2001 base year and complements GTAP 2001 CO2 emissions data – Highly disaggregated – explicitly for more precise mapping to economic activity (output and input)

  • 226 countries
  • 21 non-CO2 GHG emissions categories (N2O,

CH4, F-gases) – ~145 types of emissions with subcategory disaggregation

  • Regional 2000 forest carbon stock data by AEZ,

management type, and tree age cohort

  • Soil carbon stock data and Other CO2 (non-fossil fuel

combustion) emissions data also available (but yet implemented in the model)

slide-11
SLIDE 11

11

GTAP-AEZ sectoral Non-CO2 emissions distribution by region

200 400 600 800 1000 1200 1400 1600 1800 2000 1 USA 2 CHN 3 ROW MtCeq 24 RWTrade 23 NTrdServices 22 OthManufact 21 OthExtractn 20 Transport 19 Services 18 EnrgIntnsMnf 17 WoodProcessn 16 OthFoodPrcsn 15 ProcessdRice 14 OtherMeatPrd 13 Rumint_Prods 12 GasDistribut 11 Electricity 10 RefinedFuels 9 Gas 8 Oil 7 Coal 6 Forest 5 NonRuminLivs 4 Ruminants 3 OtherCrops 2 OtherGrain 1 PaddyRice

Sectoral distribution of non-CO2 emissions, by region

China Paddy Rice 85% CH4 15% N2O

(in Ceq)

slide-12
SLIDE 12

12

The GTAP-AEZ model

  • Static global CGE
  • 3 Regions (for now): USA, China, ROW
  • 24 Sectors – 5 land-based sectors (3 crops, ruminant

livestock, forestry)

  • Key features:

– Land in 6 AEZs: aggregated from the 18 AEZs – 3-tier CET structure of AEZ-specific land supply

  • GHG emissions and sequestration modelling

– Incorporate new detailed non-CO2 GHG emissions data (N2O, CH4, F-gases) and forest carbon sequestration data – 3 classifications of emissions – output, intermediate inputs, primary factor related emissions – Introduce emissions pricing – Calibrate mitigation responses

slide-13
SLIDE 13

13

Land supply in GTAP

  • Standard, yet counterfactual

– 1 type of ag. land, imperfect mobility across uses

  • Now: Agro-ecologically zoned land

– Heterogeneous in terms of rainfall, temperature, topography, soil type and moisture, etc. – length of growing period (LGP) varies – Suitability for growing of certain crops – Restricting land mobility across uses

slide-14
SLIDE 14

14

3-tier CET structure for AEZ-specific land supply

Land of AEZ i Forestry Agriculture Grazing Crops Crop 1 Crop 2 ..... Crop N

ETREAL1 = -0.25yi ETRAEL3 = -yi ETRAEL2 = -0.5yi Index i allows for AEZ heterogeneity.

slide-15
SLIDE 15

15

Sector-specific CES structure for AEZ land demand

  • Big enough ESUBAEZ ensures returns to AEZ lands to move closely together
  • A good approximate of an alternative specification where:

– one prod. function for each AEZ in each activity – AEZ-specific comm. are perfect substitutes – Similar production function for AEZ-specific activity – Each AEZ-specific sector faces same input/factor prices.

Total land demanded by sector j AEZ N AEZ 2 ..... AEZ 1

ESUBAEZ = 20

slide-16
SLIDE 16

16

The GTAP-AEZ model

  • Static global CGE
  • 3 Regions (for now): USA, China, ROW
  • 24 Sectors – 5 land-based sectors (3 crops, ruminant

livestock, forestry)

  • Production with intra- and inter-regional land

heterogeneity – Land in 6 AEZs: aggregated from the 18 AEZs – CET – 6 different AEZ land endowments

  • GHG emissions and sequestration modelling

– Incorporate new detailed non-CO2 GHG emissions data (N2O, CH4, F-gases) and forest carbon sequestration data – 3 classifications of emissions – output, intermediate inputs, primary factor related emissions – Introduce emissions pricing – Calibrate mitigation responses

slide-17
SLIDE 17

17

Modeling emissions

  • 3 categories -
  • Output – emissions treated as an

input to production, represents alternative technologies, introduce new CES elasticity

– Follows Hyman et al. (2003) – e.g., coal, oil, energy intensive manufacturing

  • Input – emissions proportional

to input use

– Endowment – e.g, ruminant : capital stock (animal herd) – Intermediate input – e.g., grain crop : fertilizer use

USA China ROW 1 PaddyRice 2.971 70.160 137.364 Total non-CO2 GHG emissions (MtCeq)

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% USA China ROW Intermediate input Endowment Output

Paddy Rice

slide-18
SLIDE 18

18

  • Prod. structure: output related emissions incl.

Output Intermediate Inputs Value Added Land Skilled Labor Unskilled Labor Natural Resource Capital Output-Emissions composite Output-related emissions

slide-19
SLIDE 19

19

Emissions pricing

  • The economic impact of an emissions tax associated

with input usage depends on the size of the tax AND the emissions intensity (tC/$) of the input.

  • The larger the emissions intensity, the greater the

impact of a given carbon tax on the sector’s input use and production.

Emission intensities (tC/$ of input) Input USA China Fertilizer in crops production 0.0061 0.0043 Ruminant livestock capital 0.0099 0.9562 Land in paddy rice 0.0040 0.0125

slide-20
SLIDE 20

20

Calibrating mitigation responses

  • Non-CO2 mitigation

– Engineering mitigation cost estimates for detailed technologies (Delhotal and Kruger, in press; USEPA, 2006) – Calibrate substitution elasticities with partial equilibrium closure

  • Output emissions – ESUBMAC
  • Endowment emissions – ESUBT
  • Intermediate input emissions – ESUBVA
  • Forest sequestration supply

– Calibrated to regional forest carbon supply curves Sohngen (2005) – afforestation (extensification) and forest management (intensification) – Calibrated to forest carbon intensities due to presence

  • f unmanaged land in the base year data
slide-21
SLIDE 21

21

Calibrated ROW forest carbon sequestration curve via extensification (20-year annual equivalent abatement)

ROW forest sector sequestration MAC: extensification, 20-year annual equivalent abatement 25 50 75 100 125 150 175 200 100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 Abatement - MMTCE 2001 USD $ per tonne of C GTAP-AEZ_extensification DGTM_Land Storage

slide-22
SLIDE 22

22

Calibrated USA forest carbon sequestration curve via intensification (20-year annual equivalent abatement)

USA forest sector sequestration MAC: intensification, 20-year annual equivalent abatement 25 50 75 100 125 150 175 200

  • 5

5 15 25 35 45 55 65 75 85 95 105 115 125 135 145 155 Abatement - MMTCE 2001 USD $ per tonne of C GTAP-AEZ_intensification DGTM_age/management storage

slide-23
SLIDE 23

23

Analysis of mitigation responses

  • 1. GE global competition: USA-only vs.

global carbon tax

  • 2. GE inter-sector competition: USA-only

v.s. global carbon tax

slide-24
SLIDE 24

24

Mitigation affects regional land competition

GE % change in land rents and land use by sector due to a $50/tonne carbon tax: USA only 1. For a given use, similar land rent responses across AEZs 2. Changes in land rents reflect the net effect of mitigation costs and land competition (i.e., changes in land prices and changes in acreage) – mitigation cost/subsidy dominates in rice and forestry, land competition dominates in other ag sectors

Percentage change in land rents Forest PaddyRice OtherGrain Other Crops Ruminants AEZ1 253.5

  • 15.9

2 3.3 5.1 AEZ2 254.3

  • 15.3

1.9 3.2 5.1 AEZ3 236.9

  • 15.5

1.9 3.2 5.1 AEZ4 267.5

  • 15.5

2 3.2 5.1 AEZ5 295.2

  • 16.5

2 3.3 5.2 AEZ6 320.2

  • 20.2

2.3 3.6 5.4 Percentage change in land use, weighted by AEZ land rent share Forest PaddyRice OtherGrain Other Crops Ruminants AEZ1 0.286

  • 0.023
  • 0.211
  • 0.05

AEZ2 0.013

  • 0.017
  • 0.226

0.068 0.162 AEZ3 0.009

  • 0.029
  • 0.131

0.098 0.053 AEZ4 0.427

  • 0.026
  • 0.431
  • 0.003

0.034 AEZ5 2.134

  • 0.412
  • 1.215
  • 0.391
  • 0.084

AEZ6 5.604

  • 0.626
  • 1.366
  • 3.242
  • 0.153
slide-25
SLIDE 25

25

Mitigation affects global competition

  • Regional

GE MAC: 3 regions 10 20 30 40 50 60 70 80 90 100

  • 20

20 40 60 80 100 120 140 160 abatement - mmtce 2001US D per tonne of C. USA CHN ROW World GE MAC: 3 regions 10 20 30 40 50 60 70 80 90 100 200 400 600 800 1000 1200 1400 1600 1800 abatement - mmtce 2001US D per tonne of C. US A CHN ROW World

US only tax Global tax

World USA ROW China World USA ROW China

1. USA only carbon tax – USA less competitive, international emissions leakage (primarily deforestation) 2.

  • Vs. global carbon tax – all regions with net reductions, global emissions

reductions large, ROW mitigation least expensive (primarily forest carbon increases), USA mitigation most expensive.

slide-26
SLIDE 26

26

Mitigation affects global competition – sectors

GE MAC: U.S.A, sectoral, total 10 20 30 40 50 60 70 80 90 100 20 40 60 80 100 120 140 abatement - mmtce 2001US D per tonne of C. p_REGEMIT_AGR p_REGEMIT_FRS p_REGEMIT_IND p_REGEMIT_SVC p_REGEMIT GE MAC: U.S.A, sectoral, total 10 20 30 40 50 60 70 80 90 100 20 40 60 80 100 120 140 160 180 aba tement - mmtce 2001USD per tonne of C. p_REGEMIT_AGR p_REGEMIT_FRS p_REGEMIT_IND p_REGEMIT_S VC p_REGEMIT

US only tax

USA Ind Forest Svc Ag

Global vs. US tax – US mitigation responses diminished in all sectors.

Global tax

USA Ind Forest Svc Ag

slide-27
SLIDE 27

27

Conclusions

  • Biophysical and economic land

characteristics create comparative abatement advantages for land endowments intra- and inter-regional reallocation

  • f production, and thus land use change.
  • International market structure influences

regional mitigation responses

  • International leakage is an important

component of total GHG emissions

slide-28
SLIDE 28

28

Access to LU/GHG data and WP

  • Land use data:

– https://www.gtap.agecon.purdue.edu/resources/res_disp lay.asp?RecordID=1900

  • Greenhouse gas emissions data:

– CO2:

  • https://www.gtap.agecon.purdue.edu/resources/res_display.asp

?RecordID=1143

– CH4, N2O, F-gases:

  • https://www.gtap.agecon.purdue.edu/resources/res_display.asp

?RecordID=1186

  • GTAP Working Paper No. 36:

– https://www.gtap.agecon.purdue.edu/resources/res_disp lay.asp?RecordID=2230