Bioenergy - International Energy Agency

Report
Future Land Cover Change and
Forests
- Global Challenges Bioenergy versus Deforestation
Florian Kraxner
E.-M. Nordström, P. Havlík, M. Obersteiner, et al.
+>30 collaborators
Ecosystems Services and Management Program (ESM) @
International Institute for Applied Systems Analysis (IIASA), Austria
The 3rd Global Forest Carbon Working Group Meeting
“Future of Global Forests”
27-29 May 2013
IIASA, Austria
Sustainable bioenergy feedstock
- global scenarios and outlook
Florian Kraxner, E.-M. Nordström, P. Havlík, M.
Obersteiner, et al.
Ecosystems Services and Management Program, IIASA
Bio-energy and CCS (BECCS): Options for Brazil,
13-14 June 2013, Sao Paulo, Brazil
ESM Lead / Management (MGT)
Environmental
Resources and
Development
(ERD)
(Havlik/ Mosnier/Valin)
Forest
Ecosystems
Management
(FEM)
AgroEnvironmental
Systems (AES)
(v.d.Velde/Balkovic)
(Forsell)
Earth Observation Systems (EOS)
(Fritz/See)
Policy and Science Interface (PSI)
(Khabarov/Fuss)
(Obersteiner/Kraxner)
(Kraxner/Boettcher)
Methods for Economic Decision–Making under
Uncertainty (MEDU)
ESM’s Organizational Structure
ESM’s Integrated Modeling Cluster
Modeling Biomass Supply at Global Scale – An Integrated Modeling Approach
3
1
2
Source: IIASA (2011)
G4M
Biophysical forest model G4M
• Forest parameters from G4M
0.8
0.6
0.4
0.2
– Harvesting costs
– Forest area change
– Spatially explicit
-0.1
-0.3
-0.5
-1
-3
-10
0.0
• Downscaling FAO
country level information on
above ground carbon in
forests (FRA 2005) to 30 min
grid (Kinderman et al., 2008)
Total Cabon Production / Maximum Carbon Production
1.0
– Provides annual harvestable wood (for sawn wood and
other wood)
– Afforestation/Deforestation (NPV)
– Forest management (rot/spec)
– Forest Carbon stock
0.0
0.2
0.4
0.6
Age / Max Age
7, date
0.8
1.0
Input Data Sets for the Global Forestry Model (G4M)
•
•
•
•
•
•
•
•
•
NPP
Population Density
Land cover
Agricultural suitability
Forest Biomass
Price level
Discount rate
Corruption
Product use
Source: Kindermann (2010)
Forest Area Development A2r (2000 – 2035)
Source: IIASA, G4M (2008)
Deforestation 2050 under BAU
Source: Kindermann et al. 2006
•
Losses under BAU by 2050 will be 300-500 mio ha
•
Tropical deforestation is considered the second
largest source of anthropogenic greenhouse gas
emissions (IPCC, 2007) and is expected to remain a
major emission source for the foreseeable future
(MEA, 2005)
•
the net effect of all deforestation is basically almost
an increase of 20 per cent additional emissions from
human activity going into the atmosphere and
feeding into climate change.
•
deforestation is to blame for about one and a half
billion tons of carbon dioxide being released into the
atmosphere every year for the past 15 years (GCP).
•
To the left we see the picture of tropical Africa now
and in 2100 under BAU (the more red the less
tropical forest, www.geo-bene.eu/?q=node/1653)
EPIC
The Biophysical Agriculture Model EPIC
Cropland - EPIC
Processes
•
•
•
•
•
•
•
•
•
•
•
•
•
Weather
Hydrology
Erosion
Carbon sequestration
Crop growth
Crop rotations
Fertilization
Tillage
Irrigation
Drainage
Pesticide
Grazing
Manure
E P IC
E va p o ra tio n
and
Tra n s p ira tio n
R a in , S n o w ,
C h e m ic a ls
S u rfa c e
F lo w
S u b s u rfa c e
F lo w
B e lo w R o o t
Zone
Major outputs:
Crop yields, Environmental effects (e.g. soil carbon, )
20 crops (>75% of harvested area)
4 management systems: High input, Low input, Irrigated, Subsistence
Source: Schmid (2008)
EPIC – Management Change (conventional  minimum tillage)
SOC
Crop Yield
increase SOC
0.18
t/ha/year
DM Crop Yield
-0.30 t/ha, or
-7.9%
Source: INSEA, Schmid (2006)
EPIC - Relative Difference in Means (2050/2100) in Wheat Yields
Source: Data: Tyndall, Afi Scenario, simulation model: EPIC (2011)
GLOBIOM
GLOBIOM
Model general structure
• Partial equilibrium model on land use at global scale
(endogenous prices balance supply and demand)
– Agriculture: major agricultural crops and livestock
products
– Forestry: managed forests for sawnwood, and pulp and
paper production
– Bioenergy: conventional crops and dedicated forest
plantations
• Optimization of the social welfare (producer + consumer
surplus)
• Base year 2000, recursively dynamic (10 year periods)
• Supply defined at the grid cell resolution
• Demand defined at the level of 52 world regions
• Main data source: FAOSTAT, complemented with bottom-up
sectoral models for production parameters
19
GLOBIOM - Supply chain
Wood products
Sawn wood
Pulp
Natural Forests
Wood
Processing
LAND USE CHANGE
Managed Forests
Short Rotation Tree
Plantations
BioenergyProcessing
Bioenergy
Bioethanol
Biodiesel
Methanol
Heat
Electricity
Biogas
Crops
Cropland
Grassland
Other natural land
Livestock
Feeding
Corn
Wheat
Cassava
Potatoes
Rapeseed
etc…
Livestock products
Beef
Lamb
Pork
Poultry
Eggs
Milk
21
World partitioned in 52 regions
28 regions represented on the map
+ Sub-saharan Africa split in Western Africa, Eastern Africa and Southern
Africa (Congo Basin and South Africa already separated)
GLOBIOM: Typical applications
•
Agricultural prospective
–
–
–
•
Deforestation
–
–
•
Valin et al. (2010) Climate change mitigation and food consumption patterns
Biofuels
–
–
–
•
•
Mosnier et al. (2010) Modeling impacts of development trajectories on forest cover
in the Congo Basin
Living Forest Report – WWF (2011)
Climate change mitigation
–
•
Schneider et al. (2011) Impacts of population growth, economic development, and technical
change on global food production and consumption. Agricultural Systems
Smith et al. (2010) Competition for land, Philosophical transactions
Applied scenarios such as Eastern Africa with CCAFS
Fuss et al. (2011) A stochastic analysis of biofuel policies
Havlik et al. (2010) Global land-use implications of first and second generation biofuel
targets. Energy Policy
Mosnier et al. (2010) Direct and indirect trade effects of EU biofuel targets on global GHG
emissions
Trade and trade-off assessments
Direct and indirect water demand of feedstock/livestock production
systems
Globally Consistent Assessment
of Forest Development
and Bioenergy…
Background
Global Future Energy Portfolios, 2000 – 2100
Source: modified after Azar et al., 2010
Cumulative biomass production (EJ/grid) for bioenergy between 2000
and 2100 at the energy price supplied by MESSAGE based on the
revised IPCC SRES A2r scenario (country investment risk excluded).
Source: Rokityanskiy et al. 2006
Source: IIASA, G4M (2008)
Forest Management Certification (Potentials)
Certified area relative to managed forest area by countries
Kraxner et al., 2008
Source: compiled from FAO 2005, 2001; CIESIN 2007, ATFS 2008; FSC 2008; PEFC 2008.
Global BE Feedstock Scenarios – Definitions & Objectives
Objectives:
a) to achieve a global perspective using an integrated
modeling approach;
b) to frame the boundaries for lower scale assessments;
and
c) to identify potential trade-offs to be considered in future
research.
Zero Net Deforestation and Degradation
(ZNDD) means no net forest loss
through deforestation and
no net decline in forest quality through
degradation.
Scenario name Description
BAU
”Business as usual”: Projection of future development
in line with historical trends
BE2010
As BAU but the production of bioenergy fixed at the
level in 2010
BEPlus
Projection of bioenergy demand by 2050 as in the
100 per cent renewable energy vision by the Ecofys
Energy Model
BEPlusRED
As BEPlus but with target ”no net deforestation”
(RED=Reducing Emissons from Deforestation)
BiodivRED
Stricter biodiversity protection combined with target
‘no net deforestation’
Global Deforestation Trends
Cumulative deforestation 2000-2050
caused by land-use change according to
the different scenarios.
•BEPlus similar to BAU
•BE2010 on same high level because of unrestricted deforestation
•RED keeps deforestation at present level
Regional Effects by Adding BE, Biodiv, RED - Unmanaged Forest rel to BAU
Loss of pristine (unmanaged) forest as a proxy for BE production on Biodiversity
Cumulative loss of area of
unmanaged forest 2000-2050 in
different regions under the BAU
scenario
•most of the loss of unmanaged forest
takes place in the tropical areas of South
America, Africa and Asia
Cumulative loss of area of
unmanaged forest 20002050 in different regions
under the BEPlus RED
scenario
•the loss of unmanaged forest is not
only considerably smaller but also
more evenly distributed from a global
perspective
GHG Emissions by Scenarios
GHG emissions from total land use 20002050 under the different scenarios
•Under the BE2010 scenario, the bioenergy use is small compared to the other
scenarios, and the GHG emissions are the highest, 8,091 Mt CO2/year. The GHG
emissions are lower under the BAU and BEPlus scenarios, where the bioenergy use is
more extensive.
•Lowest GHG emissions can be achieved under the RED scenarios
Agricultural Water Demand by Scenarios
Water consumption for agriculture 20002050 under the different scenarios
•All scenarios show increased demand
•Lowest restriction on forest and biodiversity conservation show less water need
•Higher restriction implies less land available for eg food production = intensification
Summary & Discussion & Conclusions
•
•
•
•
•
•
•
•
•
•
The demand for bioenergy will be high and will increase competition for land
Bioenergy production is a significant but not the major driver of forest loss
Avoiding large-scale deforestation is possible, even under expanded bioenergy
production.
Unmanaged forest will be lost under all scenarios but under the RED scenarios
the loss is only half of the loss under the BAU scenario
GHG emissions may be substantially reduced by minimizing deforestation
Minimization of deforestation may have negative impacts on other natural
ecosystems
The more forest and biodiversity one would like to be conserved, the less land
will be available for food production
The more conservation and protection, the higher the need for optimization and
intensification
Various policy areas must be coordinated to ensure sustainable use of
resources
Future studies need to go into the details identified here
High hopes…
Contact
Florian Kraxner
Ecosystem Services and Management Program
International Institute for Applied Systems Analysis, IIASA
Laxenburg, Austria
[email protected]
http://www.iiasa.ac.at
Paper contribuion:
Florian Kraxner; Eva-Maria Nordström; et al. (2013). Global Bioenergy Scenarios - Future Forest Development, Land-Use
Implications, and Trade-Offs. Biomass and Bioenergy (in press)

similar documents