GHG EMISSIONS FROM AGRICULTURE

Climate Change WorkshopDecember 12, 2000

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Background

Kyoto Protocol - created need to estimate GHG emissions National GHG inventory

Annual account of GHG emissions by sector

Canadian Economic and Emissions Model for Agriculture (CEEMA) Emissions projections to the first commitment

period (2008 - 2012) and beyond

Related systems - different function

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Modelling Framework

Canadian Regional Agricultural Model - CRAMexisting policy analysis model predicts level of agricultural activities

Greenhouse Gas Emissions module links agricultural activities to emission coefficients

Canadian Economic Emissions Model for Agriculture (CEEMA) integrated model incorporates science with policy analysis

Primary agriculture based on IPCC accounting and forward and backward linkages

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Greenhouse Gas Emissions Module

Estimates emissions of CO2, CH4 and N2O on a 100 year Global Warming Equivalent basis

Emission coefficients based on: IPCC coefficients empirical information biophysical models (i.e., Century)

Disaggregate approach by region, crop and livestock production activities source of GHG emissions CO2, CH4 and N2O GHG

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Greenhouse Gas Emissions Module

Estimated emissions = emission coefficient * production activity level

Flexibility in method of summation:IPCC agricultureIPCC agriculture minus sinkstotal agriculture and agri-food sector

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Activity IPCC Agr. IPCC — EnergyIPCC

Land UseChanges

Energy UseTrans-

portationManu-

facturingSinks

Farm — Direct Production Emissions — Crops

Crop Residues N2O

Fertilizer Use N2O

Fuel Use CO2 CH4 N2O

Manure Application N2O CH4

Nitrogen Fixing Crops N2O

Soil Organic Matter CO2 CO2

Farm — Direct Production Emissions — Livestock

Animals CH4

Stationary Combustion CO2 CH4 N2O

Manure Handling N2O CH4

IPCC Accounting of the Agricultureand Agri-Food Sector

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Activity IPCC Agr. IPCC — EnergyIPCC

Land UseChanges

EnergyUse

Trans-portation

Manu-facturing Sinks

Other Sub-Sectors

Indirect Emissions N2O

Transportation/Storage CO2 CH4 N2O

Food Processing CO2 CH4 N2O

Prod. Related Services CO2 CH4 N2O

Farm Inputs CO2 CH4 N2O

Other AgroecosystemComponents

N2O CO2 CH4 CO2

IPCC Accounting of the Agricultureand Agri-Food Sector (cont’d)

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Canadian Submission to the UNFCCCProposals related to Kyoto Protocol Articles 3.3 & 3.4

Estimate scale of sink potential 1990 - assigned amount (94%) 1996 1999 2008 to 2012 (1st commitment period)

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Canadian Submission to the UNFCCC(continued)

Land based accounting cropland management

frequency of zero tillage frequency of summerfallow

grazing land managementconversion of cropland to permanent cover intensity of pasture and grazing land management

shelterbelts

Low, medium, and high adoption rates

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2008 - 2012 Key AssumptionsLow adoption rate

General - relative to 1996 Land Base constant Increase crop and hay yields on trend Costs increase based on FIPI

Cropland management Zero tillage: held constant (17% of cropland) Prairie N Fertilizer use: increase 25% Summerfallow: 5 million ha

Grazing land management Beef cows increase: west - 10%; east - 2% Hogs increase: west - 31%; east - 8% Reduced stocking rates and complimentary grazing on 25% of grazing

land

Shelterbelts - 2,880 ha/yr from 2000 to 2012

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2008 - 2012 Key AssumptionsMedium adoption rate

Relative to low adoption scenario Cropland management

Summerfallow: 3 million ha Zero tillage: increased on trend (30% of cropland) Prairie N Fertilizer use: increase of 10% on new ZT land

Grazing land management Permanent cover increased by 1 million ha - Prairies Beef cows increase: west - 4.2%; east - 2% Reduced stocking rates on 35% of native land in west Complimentary grazing on 35% of grazing land in west Rotational grazing ranged from 10% in west to 5% in east

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2008 - 2012 Key AssumptionsHigh adoption rate

Relative to low adoption scenario Cropland management

Zero tillage: increased to 50% of cropland on Prairies Prairie N Fertilizer use: increase of 10% on new ZT land Summerfallow: 3 million ha

Shelterbelts 7,000 ha per year from 2000 to 2012

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Change in Activity Levels

1996 2010 2010 2010L M H

Cropland (m ha) 34.7 34.2 33.4 33.3Summerfallow (m ha) 6.2 5 5 3Zero tillage (m ha) 5 5 8.9 15Hayland (m ha) 6.2 6.4 6.8 6.8Pasture (m ha) 4.3 4.7 5.1 5.1Rangeland (m ha) 15.6 15.6 15.1 15.1Beef cows (m head) 4.7 5.1 5.3 5.3

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GHG Emissions- Cropland

-25

-20

-15

-10

-5

0

5

10

15T

g C

O2e

/yea

r

1996 2010L 2010M 2010H

CO2

Non-CO2

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GHG Emissions- Grazing land

-50

-40

-30

-20

-10

0

10T

g C

O2e

/yea

r

1996 2010L 2010M

CO2

non-CO2

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CO2e Emissions Relative to 2010 BAU - Mitigation Scenarios

-20

-15

-10

-5

0

5

10

15

20

% c

hang

e

IPCCIPCC + sinks

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Key Messages

Importance of soil sinks GHG reduction targets may be achievable

through a series of actions based on existing technology

Trade-off between GHG reduction scenarios Measures to promote adoption of mitigation

practices Uncertainty of GHG coefficients

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Acknowledgements

Suren Kulshreshtha, Department of Agricultural Economics, U. of S.

Bruce Junkins, Policy Branch, AAFC Ray Desjardins, Brian McConkey, Research

Branch, AAFC

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GHG Modeling Workshop

December 9-10, 2000 Hosted by Centre for Studies in Agriculture, Law

and the Environment, U. of S Sponsored by Prairie Adaptation Cooperative ~90 participants

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GHG Modeling Workshop

GHG/climate change modeling in agriculturegreat deal of activity important because agriculture is biologically

based - does not fit general energy-based models of most other sectors (Hanly - AMG work)

inventory work (Desjardins)Policy Branch - recognized early the need for

predictive capability, mitigation studies

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GHG Modeling Workshop

Take-home messages Current focus - need to continue work on

emission measurement reduce uncertainty better coefficients

scaling-up from point/site measures to landscape and region

refinement of process models

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GHG Modeling Workshop

Road ahead

Link mitigation and adaptation scenarios to emission research Link climate change scenarios to mitigation research

Develop measurement, verification and monitoring protocols for regional and national assessments Quantify uncertainty