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Final stakeholder workshopScience-based Targetsfor agriculture and forestry commodities
08/09/2016
Giel Linthorst (Ecofys)
Detlef van Vuuren (PBL)
Pete Smith (University of Aberdeen)
© ECOFYS | |
Agenda for stakeholder workshop
PART 1 (50 minutes)
1. Introduction
2. Project structure and outline
3. Scope of project, selection of commodities
4. Method to calculate emission factors and targets
a) Decarbonisation pathways for selected commodities
b) Land-Use Change (LUC) pathways for selected commodities
5. SDA-methodology and Tool to set science-based targets
6. Q&A
PART 2 (40 minutes)
1. Interactive discussion based on methodology and results
2. Polling
CLOSURE
08/09/2016 Science-based Targets for agriculture and forestry commodities
© ECOFYS | | 08/09/2016 Science-based Targets for agriculture and forestry commodities
INTRODUCTION
© ECOFYS | |
Introduction to this project
> Agricultural and forestry commodities (ranging from meat, diary to rice, wheat
and to wood) have a large impact on the environment and on the other hand
suffer from climate change in many regions
> Growth of global population and welfare will lead to almost doubling of demand
for agriculture and forestry commodities in 2050
> Increase of productivity combined with mitigating of GHG emissions are
required to meet global development and climate goals
> Companies play an important role in increasing productivity while mitigating
GHG emissions
> However, there is no transparent methodology that guides companies to
improve efficiency and to reduce GHG emissions per unit of agricultural and
forestry commodity in line with keeping global warming well below 2 oC
t GHG/unit food productt GHG/ha/yr
e.g. Smith et al. (2008); IPCC
e.g. Macdiarmid et al.(2013)
t GHG/t commodity
08/09/2016 Science-based Targets for agriculture and forestry commodities
© freeimages.com/Andreas Krappweis © freeimages.com/Simon Stratford
© ECOFYS | |
Science-based Targets setting for companies
Inspire and enable companies to set GHG emission reduction
targets in line with the level of decarbonization required to
keep global warming 2°C
a) By the end of 2015 over 100 leading multinational
companies will have commited to adopt science-based
emission reduction targets
b) By the end of 2018 this will be more than 250 companies
c) This initiative will also demonstrate to policy-makers the
scale of ambition among leading companies to reduce their
emissions and act as a positive influence on international
climate negotiations
Goal
Expected outcomes
Science-based Targets08/09/2016 Science-based Targets for agriculture and forestry commodities
Science Based Targets initiative
Launched by CDP, UN Global Compact, WRI and WWF
© ECOFYS | |
New methodology to set Science-based Targets
08/09/2016 Science-based Targets for agriculture and forestry commodities
• For the Science Based Targets initiative, Ecofys
developed with CDP, WRI and WWF a new methodology,
called the Sectoral Decarbonization Approach (SDA)
• The SDA methodology is based on the least-cost
modelled 2oC scenario (2DS) developed by the
International Energy Agency (IEA) as part of its
publication, Energy Technology Perspectives 2014
• Development of the SDA methodology involved
intensive stakeholder consultation
• The SDA methodology is freely available and was
published in Nature Climate Change
• However, agriculture, forestry and land use (AFOLU)
was not covered in SDA methodology yet. In this
project we developed a methodology to extend the SDA
for this sectors.
© ECOFYS | | 08/09/2016 Science-based Targets for agriculture and forestry commodities
PROJECT STRUCTURE AND OUTLINE
© ECOFYS | |
Project structure and outline
08/09/2016 Science-based Targets for agriculture and forestry commodities
KR Foundation
University of Aberdeen ECOFYSPBL
FU
ND
ER
PR
OJE
CT
PA
RTN
ER
S
PR
OJE
CT
PH
AS
ES
CO
NS
ULT
AT
IO
N
Selection of
commodities
Tool &
Report
1 3
Literature review and MACC
One consistent framework PBL IMAGE model
Stakeholder
workshop
TAG meeting TAG meeting TAG meeting
Stakeholder
workshop
TAG meeting
2. Emission factors and targets
Agriculture LUC
2a 2b
© ECOFYS | |
Members of the Technical Advisory Group (TAG)
Members of Technical Advisory Group:
– Ms Tiffanie Stephani Fertilizer Europe
– Mr Jan Peter Lesschen Wageningen University & Research (WUR)
– Ms Mark Henson Monsato
– Mr Kevin Rabinovitch Mars
– Ms Lini Wollenberg University of Vermont/CCAFS
– Mr Pedro Faria CDP
– Mr Henry King Unilever
– Mr Petr Havlik IIASA
– Mr Shaun Ragnauth US EPA
– Mr Stephen Russell World Resources Institute (WRI)
08/09/2016 Science-based Targets for agriculture and forestry commodities
© ECOFYS | | 08/09/2016 Science-based Targets for agriculture and forestry commodities
SCOPE OF PROJECT, SELECTION OF COMMODITIES
© ECOFYS | |
Breakdown of global GHG emissions
08/09/2016 Science-based Targets for agriculture and forestry commodities
0
1
2
3
4
5
6
Direct agriculture GHG emissions
Rest
Palm oil
Soy
Chicken
Maize
Wheat
Pigs
Dairy
Rice
Beef
0
1
2
3
4
5
6
FOLU (LULUCF) GHG emissions
(GtCO2eq)
Rest
Palm oil
Beef
Soy
0
5
10
15
20
25
30
35
40
45
50
Total GHG emissions (GtCO2eq)
Electricity and Heat Other Energy
Industry Transport
Buildings AFOLU
24%
6%
14%
21%
10%
25%
59%
41%
24%
76%
Sources: IPCC, 2014 & CEA, 2014
0
2
4
6
8
10
12
AFOLU GHG emissions (GtCO2eq)
Agriculture FOLU (LULUCF)
51%
49%
Land use
CO2
(LUC)
Agriculture
emissions
Electricity
and heat
Other
energy
Industry
Transport
Buildings
Agriculture,
Forestry, LU
© ECOFYS | |
Selection of agriculture and forestry commodities
08/09/2016 Science-based Targets for agriculture and forestry commodities
The following commodities are selected:
1. Meat – Beef
2. Dairy
3. Poultry - Chicken
4. Meat – Pig
5. Rice
6. Maize
7. Wheat
8. Palm Oil
9. Soybeans
10.Round wood *)
The choice for these commodities was based on:
> Their large role in AFOLU emissions
> Their large volumes traded
Source: CEA 2014
*) Round wood will be treated on a more qualitative way in our final report
© ECOFYS | |
GHG emissions included
08/09/2016 Science-based Targets for agriculture and forestry commodities
Meat - Beef and Dairy, Poultry - Chicken, Meat - Pig:
1. CO2 emissions from land use change associated with livestock and feed for livestock
2. Emissions from feed production i.e. direct and indirect N2O emission from application of
fertilizer, crop residues and deposition of manure on pastures; CH4 emission from
manure and flooded rice.
3. CO2 emission from machinery used on farm and for feed production.
4. CO2 and N2O emissions from fertilizer production needed for feed production
5. Enteric CH4 emission (Meat - Beef , Dairy and Meat - Pig)
6. CH4 emission from manure management
7. Direct and indirect N2O emission from manure management
Rice, Wheat, Maize, Palm oil, Soybean
1. CO2 emissions from land use change
2. CH4 emission from flooded soil (for Lowland rice only)
3. CO2 and N2O emission due to fertilizer production
4. Fertilizer-direct N2O emission from soil due to fertilizer application
5. Fertilizer-indirect N2O emission from leaching, runoff and volatilization
6. N2O emission from crop residue
7. CH4 and N2O emission from agricultural waste burning
8. CO2 emission from machinery on farmlemissions arising from land use change
© ECOFYS | | 08/09/2016 Science-based Targets for agriculture and forestry commodities
Method for calculating emission factors and targets
© ECOFYS | | 08/09/2016 Science-based Targets for agriculture and forestry commodities
Emissions
(2010-2050)
Activity
change
EF per
commodity
Marginal
Abatement
curves
Method for calculating emission factors of commodities
IMAGE 3.0 model
Con
sis
ten
t descrip
tion
of a
gric
ultu
re
Develo
pm
en
t with
/w
ithou
t clim
ate
po
licy
© ECOFYS | | 08/09/2016 Science-based Targets for agriculture and forestry commodities
Emissions
(2010-2050)
Activity
change
EF per
commodity
Marginal
Abatement
curves
Method for calculating emission factors of commodities
SSP2: Medium scenario (following medium
population, income, agriculture scenario –
similar to FAO baseline)
Crop production Lifestock production
© ECOFYS | | 08/09/2016 Science-based Targets for agriculture and forestry commodities
Emissions
(2010-2050)
Activity
change
EF per
commodity
Marginal
Abatement
curves
Method for calculating emission factors of commodities
Energy
Land-use
• Crop residues,
• agricultural waste
burning
• wetland rice,
• enteric fermentation
• animal waste,
• Fertilizer use,
• fertilizer production,
• Biological N-Fixation
• Deforestation ,
• CO2 from energy,
© ECOFYS | | 08/09/2016 Science-based Targets for agriculture and forestry commodities
Emissions
(2010-2050)
Activity
change
EF per
commodity
Marginal
Abatement
curves
Method for calculating emission factors of commodities
Energy
Land-use
2-degree decarbonisation pathway
Climate policy implemented by cost-
optimisation for all sectors, globally
Energy : energy efficiency, renewables,
CCS, nuclear
Deforestation: REDD, ARD
Non-CO2: Emission reduction via MACCs
2 deg C
© ECOFYS | | 08/09/2016 Science-based Targets for agriculture and forestry commodities
Emissions
(2010-2050)
Activity
change
EF per
commodity
Marginal
Abatement
curves
Method for calculating emission factors of commodities
Showing emissions per commodity
Calculate all emissions for each commodity
- Include inputs (e.g. feed)
- Following production chain for trade
Divide total emissions associated with
commodity by production level (cereal
emissions by cereal production)
A. Agriculture emissions (connectedto activity)
B. Land use change emissions (connected to activity change)
© ECOFYS | |
IMAGE model distinguishes between 26 regions
08/09/2016 Science-based Targets for agriculture and forestry commodities
© ECOFYS | | 08/09/2016 Science-based Targets for agriculture and forestry commodities
a. Agriculture emissions(non-CO2, CO2 for energy)
© ECOFYS | | 08/09/2016 Science-based Targets for agriculture and forestry commodities
Update Marginal Abatement Cost Curves
> New MAC curves for agricultural CH4 and N2O emissions
> Built up out of sets of mitigation measures found in literature (non-mutually
exclusive)
> Estimated reduction for a specific measure: average of all the RE values for this
measure found in literature
-60
-50
-40
-30
-20
-10
0
10
Nitrificationinhibitors
Controlledrelease
fertilisers Reduced NImproved
placement of N
Improved landmanure
application
Improvedagronomypractices
Fertilizer freezone
Spreadermaintenance
Sub-optimalfertilizer
applications
Ch
an
ge i
n N
2O
em
issi
on
(%
)
Average
Example: Fertilizer N2O measures
© ECOFYS | | 08/09/2016 Science-based Targets for agriculture and forestry commodities
Update Marginal Abatement Cost Curves
> Included in analysis:
– Regional differences
– Increased implementation potential in time:
● Due to technology diffusion, applicability of measures, removal of
barriers, technology improvement
– Interaction between multiple measures
● Resulting in: marginal costs ꜛ, reduction potential per measure ꜜ
Example MAC: CH4 from rice - Asia
© ECOFYS | | 08/09/2016 Science-based Targets for agriculture and forestry commodities
Global decarbonization pathways for selected commodities
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
beef beef dairy dairy pork pork poultrymeat &
eggs
poultrymeat &
eggs
rice rice soy, palmoil
soy, palmoil
maize maize wheat wheat
2015 2050 2015 2050 2015 2050 2015 2050 2015 2050 2015 2050 2015 2050 2015 2050
Mt
CO
2 e
qu
ival
en
ts /
Mt
DM
co
mm
od
ity
Global commodity emission factors (total except LUC CO2)
CO2
N2O
CH4
© ECOFYS | | 08/09/2016 Science-based Targets for agriculture and forestry commodities
Global decarbonization pathways for selected commodities
0.0
2.0
4.0
6.0
8.0
10.0
12.0
dairy dairy pork pork poultrymeat &
eggs
poultrymeat &
eggs
rice rice soy, palmoil
soy, palmoil
maize maize wheat wheat
2015 2050 2015 2050 2015 2050 2015 2050 2015 2050 2015 2050 2015 2050
Mt
CO
2 e
qu
ival
en
ts /
Mt
DM
co
mm
od
ity
Global commodity emission factors (beef not shown)
CO2
N2O
CH4
© ECOFYS | | 08/09/2016 Science-based Targets for agriculture and forestry commodities
Regional decarbonization pathway for Soy in Brazil
Totals excluding LUC CO2
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
2015 2030 2050
t C
O2
eq
/ t
so
y
EF Soy - Brazil
biomass burning fertilizer production machinery
biological N-fixation irrigation agricultural waste burning
indirect fertilizer crop residues fertilizer use
© ECOFYS | | 08/09/2016 Science-based Targets for agriculture and forestry commodities
Regional decarbonization pathway for Beef in Brazil
Totals excluding LUC CO2
0
10
20
30
40
50
60
70
80
2015 2030 2050
t C
O2
eq/t
bee
f
EF Beef - Brazil
enteric fermentation animal waste FEED: fertilizer production
FEED: biomass burning FEED: machinery FEED: irrigation
FEED: crop residues FEED: indirect fertilizer machinery
FEED: fertilizer FEED: agricultural waste burning FEED: biological N-fixation
FEED: wetland rice
© ECOFYS | | 08/09/2016 Science-based Targets for agriculture and forestry commodities
b. LAND-USE CHANGE (LUC) PATHWAYS
© ECOFYS | |
CO2-emissions from land-use change (“LUC-CO2”)
08/09/2016 Science-based Targets for agriculture and forestry commodities
> Other than CH4 and N2O from agriculture, the level of these emissions is not related to the size of production, but to a change in production / change in agricultural area.
> LUC-CO2 emissions cannot easily be attributed to certain land uses of commodities (e.g. due to indirect land-use change)
> There is no consensus methodology on how to account for LUC-CO2
in Life Cycle Assessments.
> We have explored 4 different methods for accounting for LUC-CO2.
> Advantages and disadvantages of the methods will be discussed in detail on the website of the tool and in the report. Choice of methodalso depends on available information about region of origin, andreported recent direct land-use changes.
© ECOFYS | |
LUC-CO2: methods
08/09/2016 Science-based Targets for agriculture and forestry commodities
A. LUC marginal (“LUC marginal”): The emissions related to the additional production of
one unit of product, calculated by comparing this scenario to A counterfactual world where
this additional production would not have occurred.
B. Historic, weighted for area (“Hist, area”): Allocating LUC-CO2 which occurred over a
certain period (historic period, or future period) to all commodities (crops and grass) on a
per ha basis, i.e. constant average LUC-CO2 per ha agricultural area in one specific region/
country.
C. Historic, weighted for area expansion (“Hist, expansion”): Allocating LUC-CO2
which occurred over a certain period (historic period, or future period) to the commodities
which have increased in area, on a per ha basis (e.g. attributing the LUC-CO2 emissions to
palm-oil only if only palm oil has expanded). This method has been applied by FAO in
allocating LUC-CO2 to livestock, and is similar to the “direct LUC-CO2 emission factor
applied in the LCA methods by Blonk Consultants.
D. Foregone sequestration (“Foregone Sequ.”) : The sequestration that would have been
achieved, or the avoided emissions by no longer producing one unit of product, calculated
by comparing a baseline with a scenario where a certain amount of production would not
have occurred. This method has been applied implicitly by Nguyen et al. 2010, and a
slightly modified variant has been proposed by Müller-Wenk and Brandão 2010.
© ECOFYS | |
Comparison of 4 methods to calculate LUC-CO2 , for soy
08/09/2016 Science-based Targets for agriculture and forestry commodities
© ECOFYS | |
Emission factors across commodities & comparison to literature
Crop commodities, method D
08/09/201608/09/2016 Science-based Targets for agriculture and forestry commodities
© ECOFYS | |
Emission factors across commodities & comparison to literature
Livestock commodities, method D
08/09/201608/09/2016 Science-based Targets for agriculture and forestry commodities
beef WRI =440
© ECOFYS | |
LUC-CO2 in Science-based target setting
08/09/2016 Science-based Targets for agriculture and forestry commodities
> LUC-CO2 emissions under a 2 degree scenario are zero or negative on the
long term
> This would result in negative emission factors per commodity
> Difference in emission factors across regions are very scenario-dependent
> Therefore: impementation of a zero-deforestation target (in 2030), i.e.
zero LUC-CO2 emission intensity.
© ECOFYS | | 08/09/2016 Science-based Targets for agriculture and forestry commodities
Final emission factors (non-CO2 + CO2)
© ECOFYS | |
Comparison with literature
Emission factor including all sources
08/09/2016 Science-based Targets for agriculture and forestry commodities08/09/2016 Science-based Targets for agriculture and forestry commodities
0
10
20
30
40
50
60
70
80
IMAGE (2015) FAO (2013)
t C
O2
eq
/ t
be
ef
(CW
)
EF - beef Brazil (base year)
Energy
Feed - Fertilizer + residues
Feed - energy
Animal waste
LUC CO2(Method C - Hist, expansion)
Enteric fermentation
© ECOFYS | |
Comparison with literature
Emission factor including all sources
08/09/2016 Science-based Targets for agriculture and forestry commodities08/09/2016 Science-based Targets for agriculture and forestry commodities
© ECOFYS | | 08/09/2016 Science-based Targets for agriculture and forestry commodities
SDA METHODOLOGY & TOOL
© ECOFYS | |
Company-specific targets on agricultural commodities are
based on convergence towards regional intensity level in 2050
Homogeneous sectors Physical allocation
The SDA methodology assumes that the carbon intensity for the commodity tend to converge in 2050. The rate of convergence depends on the differential between the carbon intensity of the company’s production and the 2ºC carbon intensity of the average regional production in 2050 and the predicted regional growth of sourcing of the company.
Data levels
Climate targets for production/sourcing of agricultural commodities can be defined based on three levels of data
- Tonne of products purchased in regions1
2- GHG emissions
based on secondary data- Tonne of products purchased in regions
3- GHG emissions
based on primary data- Tonne of products purchased in regions
- Targets will be defined based on average decarbonization pathway in specific regions- Performance of company can not be compared to average
Pros and cons
- Targets will be defined based on convergence of GHG intensity of company towards regional intensity level in 2050- Performance of company can be compared to average, but effects of actions are not measurable
- Targets will be defined based on convergence of GHG intensity of company towards regional intensity level in 2050- Performance of company can be compared to average and effects of actions are measurable
Company data
08/09/2016 Science-based Targets for agriculture and forestry commodities
© ECOFYS | | 08/09/2016 Science-based Targets for agriculture and forestry commodities
Tool to set science-based targets per commodity and region
© ECOFYS | |
Key characteristics of new methodology for agriculture and
forestry commodities
08/09/2016 Science-based Targets for agriculture and forestry commodities
1. The methodology is based on a new least-cost modelled 2oC scenario
taking into account latest insights in mitigation potential and costs of
climate-smart solutions.
2. The methodology is based on intensity pathways per commodity, using
physical indicators (tonne of product) for the 10 major agriculture and
forestry commodities
3. Both carbon intensity and absolute targets can be set by the methodology
4. The methodology can be applied by farmers up to retailers to reduce GHG
emissions during production and to green the supply chain
5. The methodology is flexible to set targets for each year until 2050
6. The methodology will be improved continuously based on new insights
© ECOFYS | |
Questions on Part 1
08/09/2016 Science-based Targets for agriculture and forestry commodities
Please feel free to ask your questions:
- by raising your hand in the WebEx or
- by typing your question in the Chat box
After raising your hand, we will unmute you to hear your questions and we will
monitor the Chat box to answer the main questions.
After this short Q&A we will
address more specific points for
debate in part 2 of this workshop
© ECOFYS | |
CLOSURE AND NEXT STEPS
08/09/2016 Science-based Targets for agriculture and forestry commodities
Please contact Giel Linthorst of Ecofys if;
• You have any questions
• You have valuable feedback on the project results
• You want to pilot the methodology for your company.
© ECOFYS | |
Giel Linthorst
Programme leader Science-based Targets
T: +31 (0)30 662 3322
M: +31 (0)6 11 366 935
08/09/2016 Science-based Targets for agriculture and forestry commodities