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Washington 11 June 2009 Analysis of Greenhouse Gas Emissions from Land User Change A Closer Look on Brazil Environmental Protection Agency Workshop on Lifecycle Greenhouse Gas Analysis for the Proposed Revisions to the National Renewable Fuels Standard Program Andre M. Nassar Director-General, ICONE

ICONE's Brazil Land Use Model

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Analysis of Greenhouse Gas Emissions from Land User Change: A Closer Look on BrazilEnvironmental Protection AgencyWorkshop on Lifecycle Greenhouse Gas Analysis for the Proposed Revisions to the National Renewable Fuels Standard ProgramOUTLINEProjections on land allocation (CARD/FAPRI) at a national level (out of US)Sugarcane: control case minus imports only casePer acre emission factors (Winrock International)Step one – step two approachOne shot emission in the year zeroCalculation of total emissionsNet expansion in total agricultural land times per acre emissions100 year period

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Page 1: ICONE's Brazil Land Use Model

Washington 11 June 2009

Analysis of Greenhouse Gas Emissions from Land User Change

A Closer Look on Brazil

Environmental Protection Agency Workshop on Lifecycle Greenhouse Gas Analysis for the Proposed Revisions to the National Renewable

Fuels Standard Program

Andre M. Nassar Director-General, ICONE

Page 2: ICONE's Brazil Land Use Model

ILUC Emissions: Three Topics

 Projections on land allocation (CARD/FAPRI) at a national level (out of US)   Sugarcane: control case minus imports only case

 Per acre emission factors (Winrock International)   Step one – step two approach

  One shot emission in the year zero

 Calculation of total emissions   Net expansion in total agricultural land times per acre emissions

  100 year period

Page 3: ICONE's Brazil Land Use Model

Projections on Land Allocation (Brazilian Land Use Model)

Outputs from CARD/FAPRI model:   National harvested area: wheat,

cotton, corn, barley, soybean, rice and sugarcane.

  Total agricultural land expansion is used for emissions calculations.

  Types of land displaced by the expansion of ag land are not identified.

Improvements to be made:   Regionalize the country:

  Emissions factors can be connected directly to the results.

  Project pasture land endogenously:   Capture pasture intensification due

to competition with crops.   Separate winter (wheat) and

second crops (corn) from the land use analysis.

  Include regional land availability taking into account:   Legal restrictions;   Suitability.

Page 4: ICONE's Brazil Land Use Model

Macro-Regions Used in the Brazilian Land Use Model

Source: ICONE.

North Amazonia

Center West Cerrado

MAPITO and Bahia

Northeast coast

Southeast

South

Tropical Forest

Savannas

Savannas

Savannas and Atlantic Forest

Atlantic Forest and Grasslands

Grasslands

Page 5: ICONE's Brazil Land Use Model

Brazil: Land Allocated to Agriculture According to the BLUM Regions

(million acres)

Source: IBGE/CONAB. Elaboration: ICONE.

44.7

104.8

131.9

118.0

27.1

79.2

34.7

22.1

24.9

9.4

10.2

12.3 0 20

40

60

80

100

120

140

160

180

South

Southeast

Center West Cerrado

North Amazonia

Northeast coast

MAPITO and Bahia

Pastures

Crops

Crops: Soybean, Corn (1st crop), rice, cotton, dry bean and sugarcane

Brazil, 1997 to 2008

0 100 200 300 400 500 600 700

1997

19

98

1999

20

00

2001

20

02

2003

20

04

2005

20

06

2007

20

08

Crops Pastures

Macro-regions, 2008

Page 6: ICONE's Brazil Land Use Model

Absolute Variation: Land Allocated to Agriculture (million acres, 1997 to current)

4.3

4.3

12.6

4.3

-0.6

4.2

-5.2

1.8

-3.0

29.4

3.0

-1.0

-6.0

-2

.0

2.0

6.0

10.0

14

.0

18.0

22

.0

26.0

30

.0

South

Southeast

Center West Cerrado

North Amazonia

Northeast coast

MAPITO and Bahia

Pastures

Crops

-0.9

6.2

9.6

34.9

2.4

3.2

-5.0

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

Soybean, Corn (1st crop), rice, cotton, dry bean, sugarcane and pastures

Total ag land

Source: IBGE/CONAB. Elaboration: ICONE.

Page 7: ICONE's Brazil Land Use Model

Example of Direct Substitution: Remote Sensing

Source: CANASAT/INPE, published in Nassar, A.M., Rudorff, B. F. T., Antoniazzi, L. B., Aguiar, D. A., Bacchi, M. R. P. and Adami, M, 2008. Prospects of the Sugarcane Expansion in Brazil: Impacts on Direct and Indirect Land Use Changes. In: Sugarcane Ethanol: Contributions to Climate Change Mitigation and the Environment. Zuurbier, P, Vooren, J (eds). Wageningen: Wageningen Academic Publishers.

572 580

1,152 434 557

991

0 250 500 750

1,000 1,250 1,500 1,750 2,000 2,250 2,500

2007 2008 2007-08

Crops Pastures Citrus Other

56% 50% 53%

42% 48% 45%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2007 2008 2007-08

South-Central Region: Classes of Land Use Converted to Sugarcane,, 2007 and 2008 (1,000 ha)

Page 8: ICONE's Brazil Land Use Model

Example of Expansion in the Amazon: Data from Soybean Moratorium Project

Source: Abiove e Globalsat (www.abiove.com.br).

50,240 32%

83,872 53%

6,328 4%

13,727 9%

3,730 2%

Pastures

Deforestation and burning Crops

Vegetation recover Other

Amazon Biome: Deforestated Area under Monitoring from 2006 to 2008 by Land Use Classes (hectares)

Total area cleared monitored by the

moratorium: 157,896 hectares

Page 9: ICONE's Brazil Land Use Model

100

120

140

160

180

200

220

0

10

20

30

40

50

60

97 98 99 00 01 02 03 04 05 06 07 08 Brazil South Southeast Center-west Cerrados North Amazon Northeast Costal MAPITO and Bahia

Total Herd (1,000 heads) and Stocking Rate (animals/ha)

Elaboração: ICONE.

0.0

0.2

0.4

0.6

0.8

1.0

1.2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

97 98 99 00 01 02 03 04 05 06 07 08 Brazil South Southeast Center-west Cerrados North Amazon Northeast Costal MAPITO and Bahia

region brazil region brazil

Page 10: ICONE's Brazil Land Use Model

Brazilian Land Use Model: Land Availability (1,000 acres)

Source: ICONE.

Region (A) Total Agricultural Land

(B) Pastures suitable for crops (C) Legally available (D) Total available

(E) Total available discounting legal

reserve deficit South 1 84,441 14,039 8,382 11,461 6,493 Southeast 2 133,791 74,959 16,691 32,644 26,299

Center-west Cerrados 3 158,570 105,149 31,161 65,555 56,703

North Amazon 4 124,129 96,563 45,293 318,883 261,867 Northeast Costal 5 35,995 0 481 481 -353 MAPITO and Bahia 6 92,157 20,670 61,907 98,872 84,420 Total 629,084 311,380 163,914 527,895 435,430 (A) Total land used for soybean, corn (1st crop), cotton, rice, drybeans, sugarcane, commercial forests and pastures. (B) Pastures that are under slopes below 12 percent and out of semi-arid climate. (C) Land under remaining vegetation in areas that can be used for crops (slopes below 12 percent). Legal reserve provision (amount of land with natural vegetation that must be preserved) is discounted. Soil suitability was not considered for the calculations. Soil suitability was not considered for the calculations. (D) Land uncer remaining vegetation in areas that can be used for crops (slope below 12 percent). Legal reserve provision (amount of land with natural vegetation that must be preserved) is not discounted. Soil suitability was not considered for the calculations. Soil suitability was not considered for the calculations. (E) Total land available if the deficits in legal reserve existing in cleared land is eliminated with forest recover or compensation. Soil suitability was not considered for the calculations.

Page 11: ICONE's Brazil Land Use Model

Recalculating Total Emissions Changing Per Acre Emissions Factors for Brazil

2,058 ths acres

1521 ths acres

86 ths acres

373 ths acres

77 ths acres

475 ths acres

499 ths acres

93 ths acres

145 ths acres

-44% 100 years -26% 30 years

Source: Figure extracted from EPA’s Draft Regulatory Impact Analysis: Changes to Renewable Fuel Standard Program

Additional land converted in Brazil when ethanol demand is

shocked (Control Case – Imports Only Case)

Page 12: ICONE's Brazil Land Use Model

Recalculating Total Emissions Changing Per Acre Emissions Factors for Brazil

55%

45% 0%

Sugarcane

Crops 100% Savanna

0% 2,058 ths acres

1,132 ths acres 1,132 ths acres

926 ths acres

-61% 100 years -49% 30 years

Source: Figure extracted from EPA’s Draft Regulatory Impact Analysis: Changes to Renewable Fuel Standard Program