greenhouse gas emissions and reduction potentials by

Greenhouse Gas Emissions and

Reduction Potentials

by Agriculture Activity

Tomoko HASEGAWA

Graduate school of Engineering, Kyoto University, Japan

Feb. 20 - 22, 2010, AIM WS10,Tsukuba, Japan

Outline

• Background• Objectives• Methodology

– Agricultural model– Data and assumptions

• Results– Future food production– Marginal abatement cost carve

F-gases1%N2O

8%CH4

14%

CO2(other)2.8%

CO2 fossilfuel use

57%

CO2

(deforestation, etc)17%

residential aland

commercial8%

transport13%

energysupply26% industry

19%

deforestation 17%

agriculture14%

waste andwastewater

3%

Contribution Ratio to Global Warming• Agriculture accounts for ...

– 14% of total GHG emission.– 50% of total CH4, and 60% of total N2O in 2005 (IPCC, 2007).

• GHG reduction measures in agriculture – Higher economic efficiency– Expected to play an important role

contribution ratio by gascontribution ratio by sector

Agriculture

GHG emission sources in agriculture

Livestock enteric

fermentationCH4

Cropland and Soils N2O

Livestock manure

managementCH4/N2O

Rice paddyCH4

economic development

population growth

changing food needs

increased production efficiency

GHG emission

food supply and

demand

reduction measures

Today’s topics(1) Estimation and evaluation of GHG emissions and

reduction potentials in agriculture in 2030(2) Specification of effective measures, countries/regions

and emission sources with high reduction potentials

To evaluate GHG emissions and reduction potentials, we need to integrate the related phenomenon such as…

Future populationscenario Exogenous

variables

Agriculture model

MethodologyWorld regions

Future economic scenario

Agricultural production

MitigationMeasure’sdatabase

-100

-50

0

50

100

150

200

. 200. 400. 600. 800.

Mar

gina

l aba

tem

ent

cost

(U

S$/t

CO2e

q)

Reduction quantity (MtCO2eq)

World

EmissionFactor’sdatabase

Marginal Abatement Cost carve

• Structure: partial equilibrium model

• Input: population and GDP

• Output: agricultural production

• Commodities: 34 commodities

• Region: 32 world regions

• Parameters: based on other literatures

• Estimation term: 2000 – 2030

• Data:– Population: UN (2006)

– GDP: Akashi (2009)

– Base year’s data: FAOSTAT (2007)

Agricultural model

World price

Shipping cost Tax and tariff

Producer subsidyConsumer subsidy Intermediate price

Producer pricePopulation Consumer priceGDP

Consumption

Stocks

32 world regions

Endogenousvariable

P

Q0

World Market

P

Q0

Domestic Market

Net trade

Production

Exogenousvariable

Agricultural model’s structure

World price




Consumption

Stocks

32 world regions

P

Q0

World Market

P

Q0

Domestic Market

Net trade

Production

Endogenousvariable

Exogenousvariable


World price




Consumption

Stocks

32 world regions

Endogenousvariable

P

Q0

World Market

P

Q0

Net trade

Production

Exogenousvariable

Production function

Consumption function


World price




Consumption

Stocks

32 world regions

P

Q0

World Market

P

Q0

Domestic Market

Net trade

Production

Endogenousvariable

Exogenousvariable


0

50

100

150

200

250

300

2000 2005 2010 2015 2020 2025 2030

Prod

ucti

on[m

il. to

nnes

] China

India

Other South-east Asia

Other South Asia

Indonesia

Thailand

USA

Korea

EU

Rest of world

World Cereal Production

• increase by 1.4 times from 2000 to 2030.• Wheat production will increase at high

growth rate• increases rapidly in Asia.

Rice

500

600

700

800

900

2000 2010 2020 2030Wor

ld p

rodu

ctio

n[m

il. t

on]

ricewheatmaize

1.4 times

0

50

100

150

200

2000 2005 2010 2015 2020 2025 2030

Prod

ucti

on[m

il. to

nnes

] EU

China

India

USA

Russia

Australia

Canada

Other Asia

Argentine

Rest of world

Wheat

50

100

150

200

2000 2010 2020 2030wor

ld p

rodu

ctio

n[m

il. to

n] . beef

porkpoultry

World Meat Production1.9 times

increases by 1.9 times throughout 2030.• 2.0 times in developing countries→ Main factors

• Population growth• Shift from cereals to meat

0

5

10

15

20

25

30

2000 2005 2010 2015 2020 2025 2030

Prod

ucti

on[m

il. to

n]

China

India

USA

Brazil

Argentine

Australia

Canada

EU

Other Asia

Rest of world 0102030405060708090

100

2000 2005 2010 2015 2020 2025 2030

Prod

ucti

on [m

il. to

n]

China

USA

Russia

Canada

Rest of world

Other Asia including IndiaEU

Brazil

Beef Pork

Mitigation measures

• Measure’s information collected from other literaturesBates(1998, 2001), DeAngelo et al. (2006), Graveland et al.(2002), Graus et al.(2004), IPCC(2007) and USEPA(2006)

Manure Management Enteric Fermentation

Anaerobic Digestion (12 types) Additives to feeds (11 types)Aerobic decomposition (2 types) Feed management (5 types)Covered lagoon (2 types) Productivity improvement (11 types)Applied manure as fertirilzer (1 type)Slowing down anaerbic decomposition (1 type)Cropland and Soils Rice PaddyOptimal fertil ization (4 types) Cultivate managements (8 types)Others (2 types) Fertilizer managements (2 types)

Marginal abatement cost carves (MAC)

Measure 1

RP1

Mar

gina

l aba

tem

ent c

ost

[US$

/tCO

2eq]

Reduction potential [MtCO2eq]

• Reduction potential (RPm ) = f0 (1-dm)・Xmm: type of measuresfo: emission factorsdm: reduction ratioXm: Activity

• Cost - initial cost, operating cost, subsidy and emission tax

Measure 2

RP2

Measure 3

RP3

•World

•All countries separately

•Large potential countries (4)

•East Asian countries (2)

•Southeast Asian countries (4)

Marginal abatement cost carves (MAC)

in 2030

-100

-50

0

50

100

150

200

. 200. 400. 600. 800.

Mar

gina

l aba

tem

ent

cost

(U

S$/t

CO2e

q)


World

CH4+N2OCH4N2O

Reduction potential under 200US$/tCO2eq[MtCO2eq]

CH4 330

N2O 265

CH4+N2O 596

World’s MAC

15% of emission in 2000

596

-100

-50

0

50

100

150

200

. 200. 400. 600. 800.

Mar

gina

l aba

tem

ent

cost

(U

S$/t

CO2e

q)


World

CH4+N2OCH4N2O

Reduction potential under 200US$/tCO2eq[MtCO2eq]

CH4 330

N2O 265

CH4+N2O 596

World’s MAC

15% of emission in 2000

596

541 596

-100

-50

0

50

100

150

200

. 20. 40. 60. 80. 100. 120. 140. 160.

Mar

gina

l aba

tem

ent

cost

(U

S$/t

CO2e

q)


World

JPN

KOR

CHN

IND

IDN

THA

MYS

VNM

USA

EU

RUS

AUS

BRA

USAIndia

China

EU

Indonesia

Thailand

Viet nam

Japan

Reduction potential under 200US$

[MtCO2eq]

MAC in Agricultural sector by country

CH4+N2O

USA 149

EU 68

India 67

Russia 63

China 50

Australia 23

Indonesia 13

Brazil 11

Thailand 9

Canada 9

Viet Nam 7

Japan 3

Korea 1

Malaysia 1

Russia

Australia

-100

-50

0

50

100

150

200

. 20. 40. 60. 80. 100.

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


USA

CH4

N2O

-100

-50

0

50

100

150

200

. 10. 20. 30. 40. 50.

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


EU

CH4

N2O

USA EUUSA EU

Cropland Large LargeRumen Very large LargeManure Large LargeRice Large Small

N2O > CH4

Livestock fertilizer

-100

-50

0

50

100

150

200

. 10. 20. 30. 40. 50.

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


EU

CH4

N2O

-100

-50

0

50

100

150

200

. 20. 40. 60. 80. 100.

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


USA

CH4

N2O

-100

-50

0

50

100

150

200

. 10. 20. 30. 40. 50.

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


EU

CH4

N2O

USA EU

Optimal fertilization etc.Optimal fertilization

USA EU


N2O > CH4


-100

-50

0

50

100

150

200

. 10. 20. 30. 40. 50.

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


EU

CH4

N2O

-100

-50

0

50

100

150

200

. 20. 40. 60. 80. 100.

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


USA

CH4

N2O

-100

-50

0

50

100

150

200

. 10. 20. 30. 40. 50.

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


EU

CH4

N2O

USA EU


N2O > CH4

USA EU



【Manure】 anaerobic digestion, covered lagoon, etc.

【Rumen】 improved productivity,feed management etc.

【Rice】

-100

-50

0

50

100

150

200

. 10. 20. 30. 40. 50.

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


EU

CH4

N2O

-100

-50

0

50

100

150

200

. 20. 40. 60. 80. 100.

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


USA

CH4

N2O

-100

-50

0

50

100

150

200

. 10. 20. 30. 40. 50.

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


EU

CH4

N2O

USA EU

N2O > CH4

USA EU



【Manure】 anaerobic digestion, covered lagoon, etc.

【Rumen】 improved productivity,feed management etc.

【Rice】

【Rumen】improved productivityfeed management etc.

【Manure】 anaerobic digestion(due to higher electricity price)【Rumen】

-100

-50

0

50

100

150

200

. 10. 20. 30. 40. 50.

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


EU

CH4

N2O

(20.0)

(10.0)

0.0

10.0

20.0

30.0

40.0

50.0

. 10. 20. 30. 40. 50.

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


CHN

CH4

N2O

China

(20.0)

(10.0)

0.0

10.0

20.0

30.0

40.0

50.0

. 10. 20. 30. 40. 50. 60.

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


IND

CH4N2O

India

CH4 > N2O

China India

Rice Large Large

(20.0)

(10.0)

0.0

10.0

20.0

30.0

40.0

50.0

. 10. 20. 30. 40. 50.

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


CHN

CH4

N2O

China

(20.0)

(10.0)

0.0

10.0

20.0

30.0

40.0

50.0

. 10. 20. 30. 40. 50. 60.

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


IND

CH4N2O

【Manure】Anaerobic digestion etc.(due to lower labor cost)【Rumen】

India100US$/tCO2eq~【Rumen】 improved productivity

additives to feed【Manure】CH4 > N2O

China India

Rice Large Large

【Rice】【Manure】anaerobic digestion

covered lagoon, etc.【Rumen】improved productivity

(20.0)

(10.0)

0.0

10.0

20.0

30.0

40.0

50.0

. 10. 20. 30. 40. 50.

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


CHN

CH4

N2O

(20.0)

(10.0)

0.0

10.0

20.0

30.0

40.0

50.0

. 10. 20. 30. 40. 50. 60.

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


IND

CH4N2O

CH4 > N2O

~0$/tCO2Optimal fertilization

Optimal fertilization, etc.

China IndiaChina India

Rice Large Large

-100

-50

0

50

100

150

200

0.0 0.5 1.0 1.5 2.0

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


JPN

CH4

-100

-50

0

50

100

150

200

0.0 0.2 0.4 0.6 0.8 1.0

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


KOR

CH4

N2O

Japan Korea

20US$/tCO2eq~【Rumen]】 additives to feed etc.

Japan Korea

Rice Very large LargeManure large Middle

【Rumen】improved productivityetc.

【Rice】【Manure】anaerobic digestion【Manure】applied manure as fertilizer【Rumen】improved productivity etc.

CH4 > N2O

-100

-50

0

50

100

150

200

. 10. 20. 30. 40. 50.

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


EU

CH4

N2O

-100

-50

0

50

100

150

200

0.0 0.5 1.0 1.5 2.0

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


JPN

CH4

-100

-50

0

50

100

150

200

0.0 0.2 0.4 0.6 0.8 1.0

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


KOR

CH4

N2O

Japan KoreaJapan Korea

Rice Very large LargeManure large Middle

CH4 > N2O


-100

-50

0

50

100

150

200

. 10. 20. 30. 40. 50.

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


EU

CH4

N2O

-20

-10

0

10

20

30

40

50

0 5 10 15

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


IDN

CH4

N2O

-20

-10

0

10

20

30

40

50

0 2 4 6 8 10

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


THA

CH4

N2O

-20

-10

0

10

20

30

40

50

0.0 2.0 4.0 6.0 8.0

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


VNM

CH4

N2O

-20

-10

0

10

20

30

40

50

0.0 0.2 0.4 0.6 0.8

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


MYS

CH4

N2O

Southeast Asian countriesReduction potentialRice：large ( the amount depending on rice paddy area)

MalaysiaViet nam

Indonesia Thailand

-100

-50

0

50

100

150

200

. 10. 20. 30. 40. 50.

Mar

gina

l aba

tem

ent c

ost

(US$

/tCO

2eq)


EU

CH4

N2O

ConclusionI introduced GHG emissions and reduction potentials in agriculture. I specified effective measures, countries and emission sources with higher reduction potentials.

• In 2030, the global reduction potential is expected to be 596 MtCO2eq (15% of emission in 2000).

• High reduction potentials: – Region: USA, India, China under 200US$/tCO2eq– USA, EU: Large RP in N2O from croplands– East and Southeast Asian countries: large RP in CH4 from rice

paddy.

Thank you for your attention !

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