GHG Emissions and Mitigation Potentials in Agriculture Tomoko - - PowerPoint PPT Presentation

GHG Emissions and Mitigation Potentials in Agriculture

Tomoko HASEGAWA

Graduate school of Engineering, Kyoto University 15,16 February,2009, 11th AIM International Workshop National Institute for Environmental Studies, Tsukuba, Japan

F-gases 1% N2O 8% CH4 14% CO2(other) 2.8% CO2 fossil fuel use 57% CO2 (deforestatio n, etc) 17%

residential al and commercial 8% transport 13% energy supply 26% industry 19% deforestatio n 17% agriculture 14% waste and wastewater 3%

Contribution Ratio to Global Warming

• Agriculture accounts for ...

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

contribution ratio by Gas contribution ratio by Sector

Agriculture

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Objectives

(1) To estimate and evaluate global GHG emissions and reduction potentials in Agriculture (2) To specify effective technologies, regions and emission sources with high reduction potentials To evaluate GHG emissions and reduction potentials, we need to integrate the relating events such as…

agricultural production economic development population growth changing food needs production efficiency technical innovation GHG emission climate change GHG reduction technology

Future population scenario

Exogenous variables

Agriculture Trade Model

Methodology

World regions determines combination and stocks of GHG reduction technologies

Enduse Model

• Model is used for estimation.

Future economic scenario GHG emissions Reduction Potentials Top-down Bottom-up

Production

• f agricultural commodities

Agricultural Trade Model (ATM)

• Structure: Partial equilibrium model

1200 functions and equations

• Input:

Population and GDP

• Output: Production of agricultural commodities
• Calibration term: 1971 - 2003
• Estimation term: 2004 - 2030
• Region: 23 world regions

World price Shipping cost Tax and tariff Producer subsidy Consumer subsidy Intermediate price Producer price Population Consumer price GDP Consumption Stocks 23 world regions Endogenous variable P Q World Market P Q Domestic Market Net trade Production

Structure

Exogenous variable

World price Shipping cost Tax and tariff Producer subsidy Consumer subsidy Intermediate price Producer price Population Consumer price GDP Consumption Stocks 23 world regions P Q World Market P Q Domestic Market Net trade Production

23 world regions are connected through world market.

Endogenous variable Exogenous variable

World price is decided in order to take balance in the world.

Structure

World price Shipping cost Tax and tariff Producer subsidy Consumer subsidy Intermediate price Producer price Population Consumer price GDP Consumption Stocks 23 world regions P Q World Market P Q Domestic Market Net trade Production

Structure

Endogenous variable Exogenous variable

Consumer price and producer price are related to world price. Policies, tax and tariff are given exogenously.

World price Shipping cost Tax and tariff Producer subsidy Consumer subsidy Intermediate price Producer price Population Consumer price GDP Consumption Stocks 23 world regions Endogenous variable P Q World Market P Q Net trade Production

Structure

Exogenous variable

Production function Consumption function

Functions: Production and Consumption

• Production function
• Consumption (Con.) function
• Import and export are also decided by prices.

, , , , 1 , ,

( , )

i r t i r t j r t

Production f Production Producer Price

• , ,

, , , , , , , , , ,

. ( , , ) . ( , )

i r t i r t r t r t i r t i r t i r t

Food Con f Consumer price GDPcap Population Feed Con f Consumer price Livestock production

World price Shipping cost Tax and tariff Producer subsidy Consumer subsidy Intermediate price Producer price Population Consumer price GDP Consumption Stocks 23 world regions P Q World Market P Q Domestic Market Net trade Production

Production, consumption and trade are calculated to take balance in one region.

Structure

Endogenous variable Exogenous variable

Balance Equations

• Domestic balance equation
• World balance equation

, , , , , , , , , , i r t i r t i r t i r t i r t

Production Import Consumption Export Stock

• ฀

, , , , i r t i r t r r

Export Import

Future population scenario

Exogenous variables

Agriculture Trade Model

Methodology

world regions decides combination and stocks of GHG reduction technologies

Enduse Model

• Model is used for estimation.

Future economic scenario GHG emissions Reduction Potentials Top-down Bottom-up

Production

• f agricultural commodities

23 world regions Technology 1 Technology 2 Technology 3 GHG emissions/ Reduction potentials

Enduse Model

Production Technology Database

• Structure: Dynamic model
• Input: Agricultural production
• Outputs: GHG emissions and Reduction potentials
• Calculates combination and stocks of GHG reduction technologies

in order to minimize total reduction cost.

Croplands Livestock animals Technology 4 Technology 5 Technology 6 Reduction Cost → Minimum

Technology Stock Change

A number of technology (tech. ) is changed by 1) exchange and 2) introduction.

② Introduced Technology ① Exchange

Tech2

Stock (T)= Stock(T-1) – ① exchanged tech.(T) + ② Introduced tech.(T) Technology change is calculated in order to minimize total reduction cost.

Technology stocks

Tech1

2000 ･ ･ ･ T-1 T ･ ･ ･ 2030 [year]

The number of livestock animal, or The area of croplands

･ ･ ･ ･

Tech1

Application

Objective

• 23 world regions
• 2000-2030
• Population: medium estimates of UN(2006)
• GDP: Akashi (2009)

Emission Sources Enteric fermentation Manure management Cropland and Soils Rice paddy Gases CH4 CH4, N2O N2O CH4, N2O

1000 2000 3000 4000 5000 6000 2000 2005 2010 2015 2020 2025 2030 CH4+N2O Emission [MtCO2eq] Cropland and Soils N2O Rice paddy CH4 Manure management N2O Manure management CH4 Enteric fermentation CH4

Baseline Emission in 2000-2030

• World GHG emission will increase by 1.4 times by 2030.
• In 2030,emissions from croplands and livestock enteric

fermentation account for 40% and 30% of it respectively.

• Emission from livestocks will increase at high growth rate.
• Emission from rice paddy will decrease.

40% 30% 1.4 times

3959MtCO2eq 5591MtCO2eq

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GHG Emission in 2000, 2030

2000 4000 6000 8000 This study USEPA A B C FAO This study USEPA A B C FAO GHG Emission[MtCO

2eq] .

Rice paddy CH4 Cropland and Soils N2O Manure management N2O Manure management CH4 Enteric fermentation CH4

in 2000 in 2030

• GHG Emission of this study is middle of other estimates.
• Cropland and Soils and Enteric Fermentations occupy

high contribution ratio.

IMAGE2.1 IMAGE2.1

Which is Effective Source?

In 2030 Reduction Potential by Source

• In 2030, total max. reduction potential is 1403 Mt CO2eq.
• Technologies for rice paddy is good.
• Technologies for enteric fermentation is not good.

Reduction Potentials [MtCO2eq] Marginal Abatement Cost [US$/tCO2eq] Emission sources <0 <20 <50 <100 >100 Enteric fermentation CH4 3 41 255 Manure management CH4 95 98 110 345 Manure management N2O 56 57 62 205 Rice paddy CH4 367 381 381 381 Cropland and Soils N2O 148 198 198 198 217 Total 148 716 737 793 1403

35% of total GHG emission from agriculture in 2000.

367 381 381 381 0 3 41 255

Where is Effective Region?

In 2030 Reduction Potential by region

• Reduction Potential in China, India and USA is large.
• Measurements in there regions take comparative low costs.

100 200 300 400 500 600 Japan EU15 USA

• ther developed

China India transition countries

• ther developing

GHG reduction potentials [MtCO2eq] <0 0-20 20-50 50-100 >100

Marginal reduction cost [US$/tCO2eq]

20 40 60 80 100 Anaerobic Digestion -Centralised plant Anaerobic Digestion -Farmscale plant Covered lagoon Daily spread of manure Slowing down anaerobic decomposition Pribiotics Propionate precursors Ammonium sulfate Midseason drainage Off-season straw Shallow flooding Upland rice Addition of Phosphogypsum Rice Straw Compost Direct Wet Seeding Alternative flooding/Drainage Spreader maintenance Fertilizer Free Zone Optimize distribution geometry Nitrogen inhibitor Convert fertilizational tillage to no-till Split fertilization Reduce fertilization to 70% Reduce fertilization to 80% Reduce fertilization to 90% Sub-optimal fertilizer application Average annual reduction potentials [MtCO2eq/yr] <0 <20 <50 <100 >100 Marginal Abatement Cost [US$/tCO2eq]

What is Effective Technology ?

Good but expensive Not good The highest economic efficiency

Conclusion

We introduced a model to estimate GHG emissions and reduction potentials in agriculture. We showed you an application to estimate and specify effective technologies, high reduction potential regions and emission sources.

• Total non-CO2 emission from agriculture is about 3959

MtCO2eq in 2000.

• Major emission source is Cropland and Soils．
• In 2030, the maximum global reduction potential is

expected to be 1403 MtCO2eq(35% of emission in 2000).

• China and India have major reduction potentials.
• The reduction technology with most economically

efficient is expected to be "daily spread of manure ".

Thank you for your attention