Copernicus Institute Sustainable Development and Innovation Management ‘Birdsview of state-of-the-art scientific understanding on sustainable biomass sourcing.” BIO-BIOTA_PFPMCG-SCOPE Joint Workshop on Biofuels & Sustainability, 26 th February 2013, Sao Paulo – Brazil André Faaij Scientific Director, Copernicus Institute – Utrecht University; Head of Unit, Energy & Resources
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Copernicus Institute Sustainable Development and Innovation Management
‘Birdsview of state-of-the-art
scientific understanding on
sustainable biomass
sourcing.”
BIO-BIOTA_PFPMCG-SCOPE
Joint Workshop on Biofuels & Sustainability,
26th February 2013, Sao Paulo – Brazil
André Faaij Scientific Director, Copernicus Institute – Utrecht University;
Head of Unit, Energy & Resources
Copernicus Institute Sustainable Development and Innovation Management
Copernicus Institute Sustainable Development and Innovation Management
Energy demand, GHG emissions
and climate change…
Copernicus Institute Sustainable Development and Innovation Management
Potential emissions from remaining
fossil resources could
result in GHG concentration levels far
above 600ppm.
Copernicus Institute Sustainable Development and Innovation Management
Energy system transformation…
[GEA/van Vuuren et al CoSust, 2012]
Copernicus Institute Sustainable Development and Innovation Management
Biobased economy;
friend or foe?
• Food vs. Fuel
• Biofuels a crime against humanity
• Threats for biodiversity, water,
farmers…
• LUC & iLUC, Carbon Payback…
result in poor GHG balances
• Large number of external damages.
Copernicus Institute Sustainable Development and Innovation Management
[IPCC-SRREN, 2011]
Driving forces, dimensions, scales…
Copernicus Institute Sustainable Development and Innovation Management
2050 Bioenergy Potentials &
Deployment Levels
2008 Global
Energy Total
Chapter 2
Possible
Deployment
Levels
2011 IPCC Review*
Land Use
3 and 5
million km 2
Chapter 10 Modelled
Deployment Levels for CO2 Concentration
Targets
Past Literature
Range of
Technical
Potentials
0-1500 EJ
Glo
bal
Pri
mar
y En
erg
y Su
pp
ly, E
J/y
2008 Global
Biomass Energy
2050
Global
Energy
AR4,
2007
2050 Global
Biomass
AR4,
2007
<440 ppm
440-600 ppm
Technical Potential
2050 Projections
Minimum
median 75th
Maximum
100
300
150 190
80
265 300
Technical Potential Based on 2008
Model and Literature Assessment
118
20 25
25th
Percentile
2000 Total Biomass Harvest for Food/Fodder/Fiber as Energy Content
[IPCC-SRREN, 2011]
Copernicus Institute Sustainable Development and Innovation Management
Key factors
biomass potentials Issue/effect Importance Impact on biomass
potentials
Supply potential of biomass
supply as estimated in recent studies
Improvement agricultural management *** Choice of crops
***
Food demands and human diet
*** Use of degraded land
***
Competition for water
*** Use of agricultural/forestry by-products ** Protected area expansion
**
Water use efficiency
** Climate change ** Alternative protein chains
**
Demand for biomaterials
*
Demand potential of biomass
demand as estimated in recent studies
Bio-energy demand versus supply
** Cost of biomass supply **
Learning in energy conversion ** Market mechanism food-feed-fuel **
Dornburg et al., Energy &
Environmental Science 2010
Copernicus Institute Sustainable Development and Innovation Management
[Dornburg et al., 2010
in: IPCC-SRREN, 2011]
Copernicus Institute Sustainable Development and Innovation Management
Global biodiesel & fuel ethanol production
2000-2009
Biodiesel
EU
Ethanol
USA Brazil Argentina Others
(Source: Lamers et al., RSER, 15 (2011) 2655– 2676)
Copernicus Institute Sustainable Development and Innovation Management
(Source: Lamers et al. RSER, 16(2012) 3176-3199
Global wood pellet production 2000 - 2010
Copernicus Institute Sustainable Development and Innovation Management
(Source: Lamers et al. 2012)
Global wood pellet trade 2010
Source: Lamers et al., RSER, 16(2012) 3176-3199
Copernicus Institute Sustainable Development and Innovation Management
Policy context Europe:
• Renewable Energy Directive (RED):
– 20% Renewable Energy in the EU in 2020 (+ specific for member states; e.g. 14% for the Netherlands).
– Subtarget of at least 10% renewable energy transport (every member state).
• European Fuel Quality Directive: Fuel suppliers at least 6% less GHG in 2020 via: biofuels, efficiency refineries, or other energy carriers (gas, electricity, hydrogen, etc.).
• 20% less GHG in 2020 (possibly 30%) -> national targets + Emission Trading. Biomass in e.g. Refining, steel, etc. can contribute.
• June 2010 National Action Plans for implementation RED.
• Intervention in RED (…): CAP on 1st generation biofuels; iLUC discussion ‘’frozen’’.
• Evaluation in 2014.
• Now: Horizon 2020 activities (JTI’s/PPP’s, outlook to 2030; heavy emphasis on biobased economy
Copernicus Institute Sustainable Development and Innovation Management
• LUC depends on zoning, productivity, socio-economic drivers
• Governing of forest, agriculture, identification of ‘’best’’ lands.
[IEA Bioenergy 38/40/43, 2011]
Copernicus Institute Sustainable Development and Innovation Management
Example: Corn ethanol
Results from PE & CGE models
[Wicke et al., Biofuels, 2012]
-100 -50 0 50 100
Searchinger et al. [3]
CARB [13]
EPA [18]
Hertel et al. [14]
Tyner et al. [15] – Group 1
Tyner et al. [15] – Group 2
Tyner et al. [15] – Group 3
Al-Riffai et al. [16]
Laborde [17]
Lywood et al. [25]
Tipper et al. [2] – marginal
Tipper et al. [2] – average
LUC-related GHG emissions (g CO2e/MJ)
Corn
B: Ethanol
Copernicus Institute Sustainable Development and Innovation Management
But we need the aggregated
modeling frameworks…
• World is far too complex…
• E.g. consequential LCA becomes unmanageable.
• Many interactions come from global level: trade determining factor, food & energy prices, competing (energy & mitigation) technologies, etc.
• Showing BAU IS important: markets and governments are imperfect
Copernicus Institute Sustainable Development and Innovation Management
• Controlling extent of LUC
– Increasing efficiency in agriculture, livestock and
bioenergy production
– Integrating food, feed and fuel production
– Increasing chain efficiencies
– Minimizing degradation and abandonment of
agricultural land
• Controlling type of LUC
– Sustainable land use planning (incl. monitoring)
– Excluding high carbon stock and biodiversity areas
– Using set-aside, idle or abandoned agricultural land
– Using degraded and marginal land
ilUC mitigation options…
Copernicus Institute Sustainable Development and Innovation Management
IMAGE /
IMAGE –TIMER
PBL
MAGNET
LEI
Bottom-up analysis of
technological learning in
bioenergy & agriculture
UU
1. Improve existing
models, knowledge
and data
2. Better integrate
existing models
Redesigning modelling frameworks & scenario’s
Copernicus Institute Sustainable Development and Innovation Management
Bottom up IMAGE MAGNET
Bio
en
erg
y
- Current status
and future
prospects of
technologies;
- Sustainable
residue removal
(student project,
superv. by
Vassilis)
- Learning in
bioenergy chains
- Updating input data
TIMER based on
bottom-up
- Dynamic modeling
of residues –
sustainable residue
potential
- Updating crop
yields & learning
rates;
- Introduction of 2nd
generation fuels;
- Inclusion residues
as feedstock for bio-
based value chains
- Endogenize tech
learning for bioenergy
chains, shifts to new
technologies
Tech change & learning / integration
Copernicus Institute Sustainable Development and Innovation Management
Bottom up IMAGE MAGNET
Ag
ricu
ltu
re
Agriculture &
livestock (yields,
inputs for
different mgmt
systems &
regions – effects
of shifting
systems)
Updating &
reinforcing
scenarios for
agricultural crop
yields - link to
mgmt system
Endogenize tech
change, efficiency
improvements, shift
to new mgmt
systems /
technologies;
Price effect of tech
change
Tech change & learning / integration
Copernicus Institute Sustainable Development and Innovation Management
Challenges for science,
business and policy • Land & natural resources (local – global)
– Integral land use strategies (agriculture, BBE, nature, rural development)
– Full impact analyses and optimization;
– Include ‘macro’’-themes; iLUC, food security, rural development, water/biodiversity.
– Governance…
• Drive down the learning curves – Technologies (fuels, biomaterials, power, carbon
management (CCS)
– Cropping systems
– Logistics, markets, CoC
– Business models & investment.
Copernicus Institute Sustainable Development and Innovation Management
Work in Brazil BION/BE-BASIC
• Detailed regional analysis on land-use (potentials, dynamics).
• LCA/EIA/economics/optimisation over time of advanced biobased supply chains.
• Methodology development & demonstration regional impacts water & biodiversity.
• Socio-economic impacts on regional level.
Combined with (senior researcher capacity):
• Macro-economic analysis methods (LEI)
• Remote sensing (TUD)
• Stakeholder perspectives (TUD, univ A’dam)
In Brazil with CTBE and partners (ICONE, Embrapa, ESALQ, etc.); joint BIOEN project for 2013-2014.
Copernicus-UU is developing related efforts in: Southern Africa, Indonesia, Eastern Europe, Colombia, Argentina, SE-US and on sustainable forest management strategies.
Copernicus Institute Sustainable Development and Innovation Management
Thanks for your attention
For more information, see:
- Sciencedirect/Scopus
- http://srren.ipcc-wg3.de/report
- www.bioenergytrade.org
Copernicus Institute Sustainable Development and Innovation Management
Copernicus Institute Sustainable Development and Innovation Management
Land availability for biomass production under different scenario’s in Mozambique
F. van der Hilst, J.A. Verstegen, D. Karssenberg, A.P.C. Faaij,
Spatio-temporal land use modelling for the assessment of land
availability for energy crops – illustrated for Mozambique, Global
Change Biology – Bioenergy, Volume 4, Issue 6, November 2012,
Pages 859-874
Floor van der Hilst, André Faaij, Spatio-temporal cost supply
curves for bioenergy production in Mozambique. Biofuels,
Bioproducts and Biorefining (BioFPR), Volume 6, Issue 4, July
2012, Pages 405-430.
Copernicus Institute Sustainable Development and Innovation Management
Land use developments
Land Use
Mozambiqu
e
Economic
Environmental
Regional
‘Business as
usual’
Global
‘Progressive
and
sustainable’
Land use developments can not be predicted…
But future land use developments can be explored by means of a scenario approach.
High technological change High environmental concern High agricultural productivity
Copernicus Institute Sustainable Development and Innovation Management
Yield increase
Weighted average yield 2000 = 100% weighted average based on share % in total production in hectares
100
150
200
250
300
350
2000 2005 2010 2015 2020 2025 2030
% o
f yie
ld l
eve
l 2
00
0
BAU
Prograssive
Copernicus Institute Sustainable Development and Innovation Management
Land requirements for crop production
Business as usual scenario Progressive scenario
The area required for food production increases due to higher intake per
capita and population growth. The land requirements are smaller in the
progressive scenario, due to higher yields and higher cropping intensity.
0
2000
4000
6000
8000
10000
12000
14000
BAU 2000 BAU 2006 BAU 2015 BAU 2030 P 2000 P 2006 P 2015 P 2030
x1000 h
a
other
industrial
fruit&veg
roots&tubers
cereals
total
Additional land required due to low
Cropping Intensity
(Area harvested/Area cropland)
Copernicus Institute Sustainable Development and Innovation Management
Nr of neighboring cells
Distance to roads
Distance to water
Distance to cities
Population density
Soil suitability
Current land use
Priority grid
Land use allocation Land is allocated to a land use function when it is most suitable for that specific faction based on several land use change determinants
Copernicus Institute Sustainable Development and Innovation Management
Excluded areas
• For energy crops – All of the excluded land areas
• Previous slide
– Land required for crops
– Land required for pasture
– Deforested areas
– Farm areas
– DUAT
– Community areas
Excluded areas general
cropland
grazing
Deforested area
Farm areas
Community areas and DUAT
Excluded areas
Copernicus Institute Sustainable Development and Innovation Management
2009
BAU Progressive BAU Progressive
Copernicus Institute Sustainable Development and Innovation Management
2015
BAU Progressive BAU Progressive
Copernicus Institute Sustainable Development and Innovation Management
2020
BAU Progressive BAU Progressive
Copernicus Institute Sustainable Development and Innovation Management
2025
BAU Progressive BAU Progressive
Copernicus Institute Sustainable Development and Innovation Management
2030
BAU Progressive BAU Progressive
Copernicus Institute Sustainable Development and Innovation Management
Land availability
0
2
4
6
8
10
12
14
16
18
2005 2010 2030 2005 2010 2030
Mh
a
very suitable
suitable
moderatly suitabble
marginally suitable
not suitable
Development of land availability over time differentiated for suitability classes for the BAU scenario (left) and the Progressive scenario (right).
BAU scenario Progressive scenario
Copernicus Institute Sustainable Development and Innovation Management
Cost breakdown of eucalyptus
related to soil suitability.
Copernicus Institute Sustainable Development and Innovation Management
Spatial distribution of feedstock
potentials and costs (2015)
Progressive BAU
Copernicus Institute Sustainable Development and Innovation Management
Cost Supply curves for
eucalyptus €/GJ 2005-2030.
Copernicus Institute Sustainable Development and Innovation Management
Global (fuel) ethanol trade streams of
minimum 1 PJ in 2009.
(Source: Lamers et al., RSER, 15 (2011) 2655– 2676)
Copernicus Institute Sustainable Development and Innovation Management
Global (fuel) ethanol trade streams of
minimum 1 PJ in 2011.
[Lamers et al., RSER, 2012]
Copernicus Institute Sustainable Development and Innovation Management
(Source: Lamers et al., RSER, 15 (2011) 2655– 2676)
Global biodiesel trade streams of minimum 1
PJ in 2009.
Copernicus Institute Sustainable Development and Innovation Management
(Source: Lamers et al., in Faaij & Junginger (eds), forthcoming in 2013)