Copernicus Institute Sustainable Development and Innovation Management
Biobased economy: outlook
on sustainable supplies and
future demand
UNECE/FAO workshop – Forest Products and Technologies for the
Future
22th May 2013, St Petersburg - Russia
André Faaij Scientific Director, Copernicus Institute – Utrecht University;
Head of Unit, Energy & Resources
Copernicus Institute Sustainable Development and Innovation Management
Why biobased economy?
Copernicus Institute Sustainable Development and Innovation Management
Biomass & bioenergy
flows according to IEA
+ other refs (2008)
[IPCC-
SRREN, 2011]
Copernicus Institute Sustainable Development and Innovation Management
Energy system transformation…
[GEA/van Vuuren et al CoSust, 2012]
Copernicus Institute Sustainable Development and Innovation Management
Advancing markets…pushed
by technological progress and
pulled by high oil prices • Advanced biofuels…(strong economic
perspective)
• Biorefining, biochemicals, biomaterials…
• Aviation and shipping…
• Likely to compete for the same resources…
• Should meet the same sustainability criteria…(but that is not the case today!)
• Competition or synergy?
Copernicus Institute Sustainable Development and Innovation Management
Breakdown of CO2 reduction
options for aviation till 2050
[IIATA, 2010]
Copernicus Institute Sustainable Development and Innovation Management
Biobased chemicals; not covered in
current global scenario’s (to date…)!
[Daioglou et al., 2013 (forthcoming)]
Energy demand
for major
Chemicals
towards
2100 with
and without
Biomass
deployment HVC’s,
including
recycling
Copernicus Institute Sustainable Development and Innovation Management
Biofuels; they are not
going away.
Large-scale deployment of advanced biofuels vital to meet the roadmap targets
Advanced biofuels reach cost parity around 2030 in an optimistic case
Fin
al e
ner
gy (
EJ)
[IEA Biofuels Roadmap]
Copernicus Institute Sustainable Development and Innovation Management
Current & future biomass
markets
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
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.
(Source: Lamers et al., in Faaij & Junginger (eds), forthcoming in 2013)
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)
Global biodiesel trade streams of minimum 1
PJ in 2011.
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
European pellet markets
2
1
4
Bulk large
scale power
Bulk medium
DH&CHP
Bulk pellets
households
Pellets in bags
households
Major
exporters
2
4
1
3 3
NE Europe (coasters)
Central Europe (trucks)
[Sikkema et al, BioFPR, 2011]
Copernicus Institute Sustainable Development and Innovation Management
Simulated Biomass trade flows 2020
RU
FI
SE
FR
UA
ES
NO
TR
PL
DE
IT
UKBY
RO
IE
LT
BG
AT
LV
HU
CZ
PT
RS
GR
EE
SK
BA
HR
NL
CH
DK
BE
MD
AL
SI
MK
ME KS
CY
LU
MT
MC
RU
FI
SE
FR
UA
ES
NO
TR
PL
DE
IT
UKBY
RO
IE
LT
BG
AT
LV
HU
CZ
PT
RS
GR
EE
SK
BA
HR
NL
CH
DK
BE
MD
AL
SI
MK
ME KS
CY
LU
MT
MC
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Import non-EU
Low Import scenario High Import scenario
Year: 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
2009 2015 2020
(pellets) Low Import High Import Low Import High Import
Total trade (Mtoe) 1.6 5.4 6.2 12.6 17.4
Total trade (Mt wood pellet
eq.)* 3.8 12 14 29 40
Of which Intra-EU 55% 38% 32% 52% 32%
Of which Inter-EU 45% 62% 68% 48% 68%
*) Mt eq. = million metric tonne pellet equivalent (18 MJ/kg)
[Hoefnagels et al, UU/Task 40, 2011]
Copernicus Institute Sustainable Development and Innovation Management
A future vision on global
bioenergy markets (2050…)
[GIRACT FFF Scenario project; Faaij, 2008]
250 Mha = 100 EJ
= 5% ag land + pasture
= 1/3 Brazilie
Copernicus Institute Sustainable Development and Innovation Management
Forestry biomass supply chain
Source:
Röser &
Sikanen
Copernicus Institute Sustainable Development and Innovation Management
Biomass densification options BALING
• pressing and mechanical dewatering
• mostly straw, but also forest residues
BRIQUETTING
• popular with straw
• easy moisture uptake
PELLETIZING
• mostly woody biomass e.g. saw dust
• straw difficult, but employed (DK,PL)
• mechanical damaging, moisture uptake
TORREFACTION
• thermochemical process (200ºC, 1h)
• anaerobic conditions,
• solid product (char)
• any type of biomass
• fibrous structure loose
• hydrophobic character
• low energy density – volume reduced
only slightly in the process
Copernicus Institute Sustainable Development and Innovation Management
+++
0** ++ ++* ++* ++ PELLETIZING
__ +++ +++ +++ PYROLYSIS
+ +++ +++ +++ TORREFACTION
+ PELLETIZING
+ +++ +++ +++ 0 TORREFACTION
0** + ++* ++* ++ BRIQUETTING
0 0
__
+ + BALING
0 0 __ __ + SIZING
CORROSION FEEDING STORAGE
HEALTH &
SAFETY
STORAGE
ENERGY
LOSSES
TRANSPORT
Comparison of densification options
+ Positive
- Negative
0 Neutral
*if proper storage conditions provided **unless pelletized with additives lowering the ash melting point (then +)
+
Copernicus Institute Sustainable Development and Innovation Management
Experience curve for primary forest fuels
in Sweden and Finland (1975 and 2003).
Sourc
e:
Jungin
ger
Faaij
et al., 2005
Copernicus Institute Sustainable Development and Innovation Management
Estimated future costs of
sugarcane and ethanol production
assuming 8% annual growth
Cumulative sugarcane production [106 TC]
1000 2000 4000 8000 16000 32000Pro
duction c
osts
sugarc
ane [U
S$/tonne] and e
thanol [U
S$/m
3]
10
20
40
200
400
800
10 20 40 80 160 320 640 1280
Sugarcane
Ethanol prod. cost (excl. feedstock)
Expected range of cane prod. costs in 2020
Expected range of ethanol prod. costs in 2020
PR = 0.68 + 0.03
PR = 0.81 + 0.02
2020
2020
Cumulative ethanol production [106 m
3]
Explaining the experience
curve:
Cost reductions of
Brazilian ethanol from
sugarcane
J.D. van den Wall Bake, M.
Junginger, A. Faaij, T.Poot,
A. da Silva Walter
Biomass & Bioenergy, 2008
Copernicus Institute Sustainable Development and Innovation Management
Biomass resources;
potentials <-> preconditions
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
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
[IPCC-SRREN, 2011]
Driving forces, dimensions, scales…
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
Contributors to land use
change…
Copernicus Institute Sustainable Development and Innovation Management
World
North America
75
168204
39
Oceania
America
5593
114
40
Japan
Ameri
2 2 2 2
19 25 30
W.Europe
13 E.Europe
13 24295
CIS &
Baltic States
111
223
269
83
Caribean &
Latin America
160
232
279
87
sub-Saharan
Africa
117
282
347
49
Middle East &
North Africa
2 31 39
2
South Asia
26 31 3723
East Asia
28
158194
22
1270
1545
607
364 forest growth
agricultural and forestry
wastes and residues
dedicated woody
bioenergy crops
surplus forest growth
agricultural and forestry
wastes and residues
dedicated woody bioenergy crops on surplus agricultural land
Total bioenergy production potential in 2050 based on system 1 to 4 (EJy-1; the left bar is system 1, the
right bar is system 4
Bioenergy production potential in
2050 for different levels of change in
agricultural management
Sourc
e:
Sm
eets
, F
aaij
2007
Pro
gre
ss in E
nerg
y &
Com
bustion S
cie
nce
Copernicus Institute Sustainable Development and Innovation Management
[See e.g: van Dam et al., RSER, 2010]
Copernicus Institute Sustainable Development and Innovation Management
Copernicus Institute Sustainable Development and Innovation
Operationalisation of sustainability criteria
costs
land
availability
Criteria
deforestation
competition with
food production
biodiversity
soil erosion
fresh water
nutrient leaching
pollution from
chemicals
employment
child labour
wages
Impact
crop
management
system
yield quantity
cost supply
curve
[Smeets et al., 2010]
Copernicus Institute Sustainable Development and Innovation Management
Cramer Cie.: minimum safeguard->
stabilisation-> improvement…
1. GHG balance -> Chain performance (30-80%+..)
2. Land-use/competition with food: reporting; to be developed.
3. Biodiversity -> reporting/FSC/RSPO; to be developed.
4. Wellfare -> Reporting EPI; to be developed further.
5. Well being -> ILO, Social accountability standards, etc.
6. Environment – Waste; law, GPG’s
– Agrochemicals; law, GPG’s (further development).
– Soil quality; reporting/monitoring (further development).
– Water quality & quantity; law, reporting/monitoring (further development).
Cramer et al., 2007
Copernicus Institute Sustainable Development and Innovation Management
Snapshot on certification
• RED crucial; proposal to CAP 1st gen biofuels. iLUC factors ‘put aside’. Evaluated in 2014 (likely to expand). Runs till 2020.
• ISCC gained ground. RSB lags behind. Variety of other systems RED approved.
• ISO process ongoing…
• Announcement that criteria for solid biomass will be introduced (meets resistance as well).
• Response from IWPB (large utilities).
• Attention for iLUC prevention and carbon payback (additional criteria?)
Copernicus Institute Sustainable Development and Innovation Management
GHG mitigation peformance
Copernicus Institute Sustainable Development and Innovation Management
GHG/MJ of major modern bioenergy chains vs.
conventional fossil fuel options
Excluding
(i)LUC
effects;
these can
have
strong
impacts
[IPCC-SRREN, 2011]
Copernicus Institute Sustainable Development and Innovation Management
Copernicus Institute Sustainable Development and Innovation Management
Uncertain!!!
‘depreciation
Carbon losses
over 20 years;
after that iLUC
= zero.
Carbon intensity
fossil ref
excludes upstream
Emissions.
These will increase
(>200 g/MJ
possible)
Copernicus Institute Sustainable Development and Innovation Management
GHG emissions per km driven
[Van Vliet et al., 2009]
No CCS CCS
Copernicus Institute Sustainable Development and Innovation Management
iLUC; scientific status, gaps
next steps…
Copernicus Institute Sustainable Development and Innovation Management
Confrontation
bottom-up vs. top down
iLUC modelling Key steps iLUC
modelling efforts:
• CGE; historic data basis
• Model shock, short term, BAU, current technology.
• Quantify LUC
• Quantify GHG implications (carbon stocks)
Bottom-up insights:
• Coverage of BBE options, advancements in agriculture, verification of changes (land, production)
• Gradual, sustainability driven, longer term, technological change (BBE, Agriculture
• LUC depends on zoning, productivity, socio-economic drivers
• Governing of forest, agriculture, identification of ‘’best’’ lands.
[IEA & other workshops, 2011-2013; pubs under preparation]
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
• Controlling (i)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
Contrast:
• Modeling for iLUC factors is only half the science we need; reactive instead of pro-active concept.
• Biofuel policies also half the policy we need; mandates without proper preconditions, resulting in CONFLICTS
Versus
• Interlinked agricultural& biobased economy
policies (agri, clima, energy…).
• Investigate (and implement) Integral land use strategies (agriculture, BBE, nature, rural development) to achieve SYNERGIES
Copernicus Institute Sustainable Development and Innovation Management
Ins and outs carbon debt debate
Copernicus Institute Sustainable Development and Innovation Management
Basic principle of GHG emission
reductions through bioenergy
Source: adapted from
IEA Bioenergy Task 38
The fact that bioenergy is ultimately renewable is
not debated, but the time until the repayment of
any potential carbon debt is repaid is under
debate
Rapid removal
Slow uptake
Copernicus Institute Sustainable Development and Innovation Management
Two very important
methodological choices:
1. Does the analysis consider the stand-level
and/or the landscape level
2. Does the study analyse the time until the
initial carbon-debt is repaid, or does it
compare the carbon flows of a bioenergy
scenario with a reference scenario (e.g. a
no-use scenario)
Copernicus Institute Sustainable Development and Innovation Management
Stand-level
Source: Eliasson et al. 2011
Copernicus Institute Sustainable Development and Innovation Management
Landscape-level
Source: Eliasson et al. 2011
Copernicus Institute Sustainable Development and Innovation Management
CT
“parity point”
“carbon debt
repayment”
t C0
Bioenergy scenario (landscape)
Bioenergy scenario (plot)
No harvest scenario (plot)
No harvest scenario (landscape)
Change in carbon stored in forest from t = 0
CT = -DCstorage + Cff saving
DCstorage
Cff saving Carbon saved from displacing fossil fuel
energy generation
Notes:
• Both bioenergy scenarios account for loss of carbon in one
plot
• Landscape scenario accounts for growth over all plots
therefore has faster growth
• No harvest landscape also, therefore, accounts for growth
that would have occurred had harvest not taken place
• Concept based on Mitchell (2012) with extension to
stand/landscape level by Robin Grenfell / MWH
51
Carbon debt & parity points –
stand & landscape level “Foregone
sequestration”
Copernicus Institute Sustainable Development and Innovation Management
Overview of parity times
per biome •
Source: Lamers and Junginger, 2013, BioFPR, in press
Copernicus Institute Sustainable Development and Innovation Management
C-debt mitigation options
1. New plantations on degraded/C-poor land -> imminent
carbon credit!
2. For managed/commercial forests: Use of fertilizer and
weed control (within SFM limits) – increases productivity
strongly
3. Increased early stand density & use of pre-commercial
thinnings
Options 2 & 3 cause no additional land use and reduce any
C-payback times strongly (+ additional output for pulp &
timber), but all need incentives
Copernicus Institute Sustainable Development and Innovation Management
No use of plantation for fossil fuel
substitution
-3000
-2000
-1000
0
1000
2000
3000
4000
5000
6000
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75
Sum
of c
arb
on
flo
ws
[Mg
Car
bo
n /
25
ha]
Tree carbon
Forest floor and litter
Balance no use of forest
Balance low productive
plantation
Balance medium productive plantation
Balance high productive plantation
[Jonker et al., GCB-Bioenergy, 2013]
Copernicus Institute Sustainable Development and Innovation Management
[Magnus Fridh,Swedish Forest Agency]
Copernicus Institute Sustainable Development and Innovation Management
Avoided emissions 1970-2010
Substitution with bioenergy cut emissions
of 550 Mton CO2 in 40 yrs
0
500
1000
1500
2000
2500
3000
3500
1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Döda trädDead orwindthrown trees
LövträdBroad-leaved
GranNorway spruce
TallScots pine
Carbon stock: 1970-2010 = + 840 Mton Million m3
[Magnus Fridh Swedish Forest Agency]
Copernicus Institute Sustainable Development and Innovation Management
General conclusions
Payback times reported in scientific literature vary
widely, but many of them are based on rather
hypothetical scenarios.
Vast majority of currently utilized solid biomass in the EU
is still residue based – but primary forest biomass share
will increase in the future.
Determining the most adequate method / reference
scenario etc. is strongly case–dependent – there is no
‘one-size fits all solution’
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
Thanks for your attention
For more information, see:
- Sciencedirect/Scopus (scientific)
- Google scholar citations (personal)
- http://srren.ipcc-wg3.de/report (IPCC)
- www.bioenergytrade.org (IEA)
Copernicus Institute Sustainable Development and Innovation Management
Perspective on Europe
Copernicus Institute Sustainable Development and Innovation Management
Factors complicating the debate
• Carbon debt vs. carbon parity
• Stand level vs. landscape level
• Large variety in different sourcing areas (EU, US SE, Ca BC, Russia
etc.) and different feedstocks , such as precommercial & commercial
thinnings, forest residues left after clear-cut for timber, insect-damaged
(e.g. MPB) wood
• Choice of fossil fuel reference system (coal, EU average, NG)
• Use (and substitution/displacement factors) of (by-) products
• What is the reference (aka counterfactual) scenario: protection, use for
timber or paper, or land use change (e.g. conversion to agricultural
crops, or urban development)?
• Carbon debt vs. carbon credit (in case of man-made plantations)
=> There is no single correct method. These choices depend on the
specific situation and political preference.
Copernicus Institute Sustainable Development and Innovation Management
0
1
2
3
4
5
6
7
8
9
10
1960 1970 1980 1990 2000 2010 2020 2030
Yie
ld [to
n/h
a]
Source FAOSTAT
Observed historic yields
Yield projections Europe
Observed yield CEEC and WEC
Linear
extrapolation of
historic trends Widening yield gap
Applied scenarios Low, baseline and high 0
1
2
3
4
5
6
7
8
9
10
1960 1970 1980 1990 2000 2010 2020 2030
Yie
ld [to
n/h
a]
Source FAOSTAT
Observed historic yields Projections
0
1
2
3
4
5
6
7
8
9
10
1960 1970 1980 1990 2000 2010 2020 2030
Yie
ld [to
n/h
a]
Source FAOSTAT
Observed historic yields Projections
[Wit & Faaij, Biomass & bioenergy, 2010]
Copernicus Institute Sustainable Development and Innovation Management
Average annual yield growth rate
projections for Europe for the
period 2000-30 for four studies
0.35%
2.3%
1.5%
0.82%
1.12%
0.62%
0.02%
0.31%
1.2%
0.4%
0.9%
0.6%
0.9%
1.1%
0% 1% 2% 3%
Sugar
Oils
Grains FAO
REFUEL
EEA
Ew ert et al.
5.2%
3.2%
Aggr. crops
Sugar
Oils
Grains
Cereals
Rapeseed
Wheat (durum)
(durum)Cereals
Rapeseed
Wheat (durum)
Aggr. crops
Aggr. crops
Aggr. crops
WEC CEEC Ukraine
De Wit, et al., RSER 2011
Copernicus Institute Sustainable Development and Innovation Management
Absolute productivity increases and
relative growth rates for the period
1961-2007 and per decade. Absolute Relative
1961-2007 1961-2007 ‘61-‘69 ‘70-‘79 ‘80-‘89 ‘90-‘99 ‘00-‘07 kg ha
-1 y
-2
kg animal-1 y
-1 % y
-1
France Wheat 104 3.6 5.2 2.5 2.5 1.6 -0.9 Rapeseed 40 2.5 1.4 0.3 -0.3 2.1 1.2 Sugarbeet 1024 3.1 3.6 0.2 2.4 1.0 2.8 Cattle 2.8 1.6 0.5 1.2 0.9 -0.1 0.9
Netherlands Wheat 110 2.7 0.7 3.8 1.4 0.5 -0.6 Rapeseed 25 1.0 -0.6 -1.8 -0.1 0.6 0.2 Sugarbeet 489 1.2 2.6 0.1 1.4 -1.9 2.5 Cattle 1.1 0.6 0.7 0.9 2.1 -0.9 -1.0
Poland Wheat 39 1.8 3.6 2.3 4.1 -0.6 1.6 Rapeseed 21 1.4 1.7 0.4 -0.4 -0.6 4.0 Sugarbeet 319 1.2 3.5 -0.5 2.6 1.0 3.7 Cattle 2.5 2.7 3.6 6.1 4.9 0.6 10.1
Ukraine (USSR) a Wheat n.a. n.a. 5.1 1.0 3.6 -4.5 -0.2
Rapeseed n.a. n.a. 3.5 -2.7 -0.4 -7.4 9.4 Sugarbeet n.a. n.a. 9.0 0.3 5.0 -3.2 11.3 Cattle n.a. n.a. 6.3 2.1 2.1 -4.9 1.2
De Wit, et al., RSER, 2012
Copernicus Institute Sustainable Development and Innovation Management
Developments in yields and
inputs
Source: FAOSTAT and own calculations
[De Wit et al, RSER 2011]
Copernicus Institute Sustainable Development and Innovation Management
Selected remarks on yields
• Yield growth projections in WEC at 0.5-1.5% y-1, are modest when compared to historic developments between 1961-2007, but seems high compared to developments in the last two decades. Declining growth rates in the latter period, explained by an expansion in organic farming, set-aside obligations and a decoupling of production support. REFUEL projections (0.4% y-1) for the WEC seem conservative in this respect.
• Projected growth rates for the CEEC around 1% y-1 – as projected by FAO (0.9% y-1) and EEA (1.2% y-1) – seem modest when compared to average growth figures between 1961 and 2007, even more so when compared to growth rates prior to 1990 and past 2000.
De Wit, et al., RSER 2012
Copernicus Institute Sustainable Development and Innovation Management
Results - spatial production
potential Arable land available for dedicated
bio-energy crops divided by the
total land
Countries
Low
potential
High
potential
Moderate
potential
< 6,5%
NL, BE, LU, AT, CH, NO, SE and FI
Potential
6,5% - 17%
FR, ES, PT, GE, UK, DK, IE, IT and GR
> 17% PL, LT, LV, HU, SL, SK, CZ, EST, RO, BU and UKR
[Wit & Faaij, Biomass & Bioenergy, 2010]
Copernicus Institute Sustainable Development and Innovation Management
Results - spatial cost
distribution Production cost (€ GJ-1) for
Grassy crops
PL, PT, CZ, LT, LV, UK, RO, BU, HU, SL, SK, EST, UKR
FR, ES, GE, IT, SE, FI, NO, IE
NL, BE, LU, UK, GR, DK, CH, AT
< 2,00 Low Cost
Moderate
Cost
2,00 – 3,20
> 3,20 High
Cost
Potential Countries
[Wit & Faaij, Biomass & Bioenergy, 2010]
Copernicus Institute Sustainable Development and Innovation Management
1 EJ (ExaJoule) = 24 Mtoe
Summary baseline 2030
0
3
6
9
12
15
18
21
24
0 6 12 18Supply (EJ/year)
Pro
duction C
osts
(€/G
J)
Oil
Summary baseline 2030
0
3
6
9
12
15
18
21
24
0 6 12 18Supply (EJ/year)
Pro
duction C
osts
(€/G
J) Starch
Oil
Summary baseline 2030
0
3
6
9
12
15
18
21
24
0 6 12 18Supply (EJ/year)
Pro
duction C
osts
(€/G
J) Starch
Oil
Sugar
Summary baseline 2030
0
3
6
9
12
15
18
21
24
0 6 12 18Supply (EJ/year)
Pro
duction C
osts
(€/G
J)
Wood
Starch
Oil
Sugar
Summary baseline 2030
0
3
6
9
12
15
18
21
24
0 6 12 18Supply (EJ/year)
Pro
duction C
osts
(€/G
J)
Grass
Wood
Starch
Oil
Sugar
Summary baseline 2030
0
3
6
9
12
15
18
21
24
0 6 12 18Supply (EJ/year)
Pro
duction C
osts
(€/G
J)
Grass
Wood
Starch
Oil
Sugar
Grass
Wood
1st
generation
2nd
generation
Crop specific supply curves • Feedstock potentials
Produced on 65 Mha arable and 24
Mha on pastures (grass and wood)
• Significant difference
between ‘1st and 2nd
generation crops’
• Supply potentials high
compared to demand 2010 (0,78 EJ/yr) and 2020 (1,48
EJ/yr)
[Wit & Faaij, Biomass & Bioenergy, 2010]
Copernicus Institute Sustainable Development and Innovation Management
Results – cost-supply curves
Production costs vs.
supply potential
for 2010, 2020 and 2030
Variation areas indicated
around the curves represent
uncertainties and scenario
variables.
Only CEEC cost level increases
[Wit & Faaij, Biomass & Bioenergy, 2010]
Copernicus Institute Sustainable Development and Innovation Management
Total annual biomass supply
potential, per European country.
[Wit & Faaij, Biomass & Bioenergy, 2010]
Copernicus Institute Sustainable Development and Innovation Management
Total energy potential under
three different crop schemes.
‘Low yielding crops’:
all arable land
available planted
with oil crops.
‘High yielding
crops’: all available
land planted with
grass crops.
[Wit & Faaij, Biomass & Bioenergy, 2010]
Copernicus Institute Sustainable Development and Innovation Management
Developments coupled to drivers
Example: the Netherlands
Inputs (fertilizer, machinery, labour and pesticides)
Outputs (wheat, sugarbeet, rapeseed and cattle)
90
120
150
180
210
1961 1966 1971 1976 1981 1986 1991 1996 2001 2006
Ind
ex
, 1961=100
Supply security and
price stability
Environment
Rural development
M anure application restrictions
intensification and up-scaling Quotation and fallow regulations
intervention prices Decoupling support
Holding up-scaling by re-allo tment of agr. land Diversification of (non-)farming act.
Environmental regulations
InputOutput
The Netherlands
[De Wit et al, RSER 2011]
Copernicus Institute Sustainable Development and Innovation Management
Example: GHG balance of combined agricultural intensification + bioenergy production in Europe + Ukraine
[Wit et al., GCB-B
Under review]
Copernicus Institute Sustainable Development and Innovation Management