Experience using 2006 GL AFOLU methods
for estimating mitigation potential foragriculture and carbon footprint ofprimary agricultural products.
Brian McConkey1*, Steve Smith1, Xavier Vergé2, RayDesjardins1, Bob MacGregor3, Devon Worth1, Tingting Liu4,Darrel Cerkowniak1, Ted Huffman1
1Agriculture and Agri-Food Canada, 2 Consultant, 3AAFC

retired), 4Beijing University of Technology*brian.mcconkey@agr.gc.ca
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Outline• Background• Analysis of Mitigation Potential for Agriculture• C Footprinting for Primary AgriculturalCommodities

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Background• Emissions from agriculture aredominated by emissions of N2O for
N applied to soil and of CH4 fromenteric fermentation
 Key source categories so Canada has
predominantly Tier 2 methods
 Quantification is not simple sonational inventory methods provide ahighly acceptable source of methods• Soil C stock changes are important Quantification is not simple sonational inventory methods provide ahighly acceptable source of methods

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Emissions and removals from altering C and N cycles
Fertilizer
LegumesN2

CH4N2OCO2Soil organic matter
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4Mitigation Potential• Important that mitigation analysis are consistent with emissions and removals as
estimated in the National Inventory• Future “what if” scenarios of policy and prices• AFOLU not fully adequate for policy purposes Desire to capture all major emissions from agriculture
 So include the emissions from on-farm fossil fuel use and for transportation of agricultural
products from the farm to processor or export position- Reported within Transportation sector- Could be as high as 15% of total emissions depending on primary agricultural product So include emissions embodied in direct inputs to primary agriculture- Nitrogen fertilizer the most important and could be up to 20% of total emission depending on primary
agricultural product• Using the national inventory system directly was not viable option due to the detailof agricultural activity data required
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5May need to include potential future activities not yet ininventory• Existing 2006 GL-based inventory does not necessarily capture future mitigation
options
 For example, biogas production from manure not included in the inventory because not large
activity Not fault of 2006 GL, just lack of emission factors and accessible activity data in Canada

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6Metamodels Needed• Inventory has too much detail!
 Use existing economic input-output models for agriculture Activity data from future scenarios is less dense than actual
activity data

• Soil C has legacy effects
 Current or future C stock change affected by past changesof land use and/or land management
 Approach used was to use the inventory system to derive ametamodel of C change- expected average in year of future scenario for activities- marginal C stock changes due to change in activity in future These C change factors than used to estimate the effect on
C change of the future scenario

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Used an integrated modeling framework to estimate GHG
emissions from agriculture• The two components of the modeling framework are the Canadian Regional
Agricultural Model and the GHG Emissions Module The Canadian Regional Agricultural Model (CRAM) is an economic model that provides
information on how activity levels in the agricultural sector respond to a wide variety ofshocks
 The GHG Emissions Module (GHGEM) is a spreadsheet metamodel of the relevant portions ofthe national inventory which uses the activity levels that CRAM estimates and emissions
coefficients based on the national GHG inventory to calculate changes in GHG emissions fromthe agriculture- Emissions estimated by GHGEM in base year within 1% of those reported in national GHG inventory• When combining these two models, this provides a tool that allows us to estimatechanges in GHG emissions from agriculture in response to policy

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8Overview of the Canadian Regional Agricultural Model• CRAM is a static partial equilibrium model of
the Canadian Agriculture sector, covering allof primary production (crops and livestock)and some processing activities
 CRAM maximizes consumer and producer
surplus The only true constraint in CRAM is theavailability of land for agricultural
production• CRAM is divided into 55 regions and canprovide a very detailed regional breakdownof resource utilization in the agriculture
sector• CRAM does not provide a forecast but givesa before (baseline) and after (policyscenario) picture of the agriculture sector• Various values of 1 tonne CO2 eq mitigatedis input to derive mitigation cost curves

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9Structure of CEEMA
Physical Conditions
Technology
Management Practices

EconomicParameters
Crop andLivestock Production
Activities
Canadian Regional
Agriculture Model

Economic
Indicators
Greenhouse Gases
Emissions Module

Inventory
Tier 1&2
and potential
Tier 2 methods

Emissions ofGreenhouse Gases

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10The following diagram provides an overview of the method

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The economic potential for agriculture in Canada is limited
LegendCram_Region04_DD
Results

Revenue from the carbon credits (thousand $)with a $100 carbon price (CO2eq)

0.000000
0.000001 - 124.400000
124.400001 - 531.300000
531.300001 - 892.800000
892.800001 - 1734.200000
1734.200001 - 2749.300000

Emissions reduction in the primary agricultural
sectorCarbon price ($/CO2eq ton)

120
100
80
60
40
20
0
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40
60
80
100
120
140
160
GHG emissions reduction (thousand CO2eq tonne)

180
12AFOLU GHG situation for agriculture

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MITIGATION - Land Use Change modelingLand supply available
2500• In order to assess the potential for land usechange the supply of land suitable foragriculture that is not already in production
had to be estimated• Amount of new land brought into production
is relatively small compared with potential

1000's hectares• To achieve this, the land in with goodpotential for agriculture was identified

2000

1500

1000

500

0
BC

ALSA

MAON

QU

Forest

Shrub

NBPE

NS

NF

Source: Liu et al. 201408-058-dp

14Application of 2006 GL for
C Footprint Analysis

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15Use of Inventory for Footprinting• Use of 2006 GL well suited for commodity-level analyses
Grain, meat, milk, etc.
Supply is from many farms
Individual farms will not be competing based on C footprint- Most emissions in CO2eq will have to be estimated as measurements infeasible- Inventory methods are well accepted basis for estimates

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16Set boundaries, example beef cattle
The total GHG emissions associatedwith a product or service, considering
all relevant sources and sinks ofemissions

CO2For Cattle
production:

N2O

Field work
DieselEnteric Fermentation

CH4

CO2 N2O
Fertilizers
and agrochemicals

Productionof Fodderand grain

CO2
N2O
CH4CO2CO2Electricity
Buildings
Equipment

CO2

CO2 Heating fuelManure08-058-dp

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Select methods from 2006 GL-based inventory for different
relevant sources and gases
Fertilizer
Legumes

N2

CH4

N2O

CO2

Soil organic matter
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18But C stock changes are difficult
Fertilizer
Legumes

N2

CH4

N2O

CO2

Soil organic matter
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C stock changes• Legacy effects of past changes in land use and in management practices• Difficult to attribute C changes to individual product For example crops are grown in rotation so difficult to link C change to anindividual crop in the rotation
 Land-use change also difficult to relate to individual agricultural product• Approaches used
 Neglect some (e.g. LUC) or all or Include a regional area average C change directly from the national inventory as
the appropriate C change estimate for all agricultural land regardless of its history- C change due to “land occupation” by agriculture

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Grain Crops

1986

2006

GHG intensity of canola(rapeseed) decreased by
2/3 from 1986 to 2006
(about ½ of reduction dueto change of C stocks)
Source: Shrestha et al. 201408-058-dp

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Agricultural land

Livestock Crop Complex
Grain

Roughages- Animal Diet

- Statistics- Crop Yield- Land Allocation

AreaGrain

AreaRoughages

Notes:
1. Attributed areas do
not necessarily occur
where animals areraised due to off-farm
feed purchases.
2. Every type of
livestock in
subnational region has
same livestock cropcomplex

Source: Vergé et al. 2012a08-058-dp

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1.4
1.2
1
0.8
0.6

Since 1996, 0.08 kg CO2e reduction
or 8%

0.4
0.201981

1986

1991

1996

Source: Vergé et al. 2012b08-058-dp2001

2006

GHG emissions per kilogram of live weight
produced

GHG Emissions per kilogram of milk produced

Recently, significant gains in emissions per unit ofproduct have been made181981

1986

1991

1996

2001

2006

16Since 1996,
14
12108

0.7 kg CO2edecrease, 39%64

1.9 kg CO2edecrease, 18%

0.08 kg CO2edecrease, 8%2230Beef

Pork

Poultry23

Summary• Methods drawn from 2006 GL are useful for analysis of national and sub-national
mitigation options and commodity-level footprints
 Less useful for analysis for activities at finer resolution than the inventory, e.g. individualfarm AFOLU not fully adequate for either footprinting or policy purposes, need to capture fossil
fuel emissions• Methods are the best available for general use in the country so well accepted bypractitioners, reviewers, and users.
 Necessary for mitigation policy that is measured by changes in national inventory estimates Particularly important for agriculture where non-CO2 gases predominate• Including C stock changes are problematic because the current change is a legacy of
past changes to land use and land management.
 Easy to apply the inventory generated estimates but not common approach for footprint/LCA
analyses
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24Благодаря,Merci

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