BIOMASS CARBON ACCOUNTS FOR EUROPE AND GLOBALLY IN GLOBIOMNicklas Forsell & Stefan Frank, Michael Obersteiner, Petr Havlík…..IIASA – International Institute for Applied Systems Analysis

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A global model with the possibility to zoom in one region

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30 Regions are interconnected

through international trade

Regional zooming allows detailed spatial representation of land (50x50km) and introduction of regional policies

306/03/2014

Simulation Units (SimU) – HRU – 50x50km grid – Country

boundaries

Source: Skalský et al. (2008)

GLOBIOM – Spatial resolution

PX5

Altitude class, Slope class, Soil Class

PX5

Altitude class (m): 0 – 300, 300 – 600, 600 – 1200, 1200 – 2500 and > 2500;

Slope class (deg): 0 – 3, 3 – 6, 6 – 10, 10 – 15, 15 – 30, 30 – 50 and > 50;

Soil texture class: coarse, medium, fine, stony and peat;

HRU = Altitude & Slope & Soil

Country HRU*PX30

PX5

SimU delineation relatedstatistics on LC classes and

Cropland management systems

reference for geo-coded data on crop management;

input statistical data for LC/LU economic optimization;

LC&LUstat

> 200.000 SimUs

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International trade

• Bi-lateral trade of agricultural, livestock and forestry products is considered between regions

• Trade is both taken into account in terms of biomass sources as well as semi-finished productsCornWheatSugarVegetable oilsetc.

TimberSawnwoodPlywoodWood pelletsetc.

BeefPorkEggsMilketc.

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GLOBIOM – EUHRU distribution

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SimU: Country NUTS2 Land cover HRU:

Elevation Slope Texture Depth to rock Stone content in subsoil River catchments

Irrigation

379.220 SimUs

Main differencesGLOBIOM GLOBIOM-EU

Land cover GLC 2000 Corine

Crop areas FAO EUROSTAT (CAPRI database)

Crop sector FAO EUROSTAT (CAPRI database)

Production quantities FAO EUROSTAT (CAPRI database)

Demand quantities FAO EUROSTAT (CAPRI database)

Prices FAO EUROSTAT (CAPRI database)

Mean annual increment G4M G4M/MS submissions

Soil organic carbon accounting

- JRC/EPIC

Crop rotations - EPIC

Tillage systems - EPIC

Spatial SimU grid Country + grid Country + NUTS2

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Economic modeling and dynamics

Main model outputs– Production Q – Consumption Q– Prices– Trade flows– Land use change– GHG emissions

Main input drivers– Population growth– GDP growth– Technological change– Bio-energy demand– Diet patterns

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Optimization problem: Maximize consumer and producer surplus Recursive dynamic: solution computed every 10-year period and

transmitted to the next period

2000 2010 2020 2030 2040 …

Production and consumption of food, feed, and fiber commodities

Bilateral trade Input requirements (fertilizer,

water…)

Calorie consumption

Land use and land use change

Conversion of highly biodiverse areas

….

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Carbon stock development (soil and biomass) Forests Cropland, grassland Lignocellulosic crops Other natural vegetation HWP stocks

Non-CO2 emissions Fertilizer Livestock (manure, enteric

fermentation) Rice

Commonly reported variables

G4M – Global Forest Model

• Estimates the impact of forestry activities on potential carbon stocks and increments of woody biomass

• Estimates forest area change, carbon sequestration and emissions in forests, impacts of carbon price and supply of biomass for bio-energy and timber

Input Output NPP – Yield description Temperature Precipitation Forest cover - Species

composition Stocking Biomass Age structure Slope Management target

Increment Biomass

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Stocking biomass Increments Harvests

Sawn wood Rest wood

Harvesting costs Species composition change

Global scale species distribution: Evergreen, Deciduous, Needle-

leaved, Broadleaved

Global scale species regions: Boreal, Temperate, Tropical,

Subtropical Forests

EU scale species distribution: Pine, Spruce, Beach, Pinus

Pinaster, Fir, Oak, Birch, and Larch

tC/h

a/ye

ar

MAI potential estimates

Forest area and carbon sequestration

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• Estimates the forest land use change (afforestation, deforestation) and impact of forest management

• Is calibrated to historic data (2000-2010) reported by Member States and FAO FRA

• Historical trends as well as driver developments (wood prices, crop price, carbon price, land use cost) can be used

• G4M estimates: Forest area change (afforestation/deforestation)Full Carbon Accounting Impacts of carbon incentives (e.g. avoided

deforestation)Mean annual incrementForest age structure developmentFinal harvesting and thinning intensities

Globally consistent carbon accounting

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Sector Source GHG Reference

Forest sector

Deforestation (biomass, soil)

CO2 Gallaun et al. 2010 scaled to total biomass using Kindermann et al. (2008)

Afforestation (biomass, soil)

CO2 Gallaun et al. 2010 scaled to total biomass using Kindermann et al. (2008)

Forest management(biomass)

CO2 G4M estimate of change in forest age structure, management intensity

Harvested wood products

CO2 IPCC Tier 2

Agri-cultural sector

Cropland management (soil, biomass)

CO2 EPIC model (Williams, 1995), Lugato/Jones map for carbon stocks

Grassland management (soil, biomass)

CO2 Ruesch and Gibbs (2008), UNFCCC

Short rotation plantations (biomass)

CO2 Havlik et al. (2011)

Land use change

Conversion of other vegetation types (biomass)

CO2 Ruesch and Gibbs (2008), Kindermann et al. (2008)

Biomass carbon

Soil carbon accounting cropland

• SOC dynamics captured explicitly in GLOBIOM

• ~300.000 carbon response functions estimated using EPIC

• Tillage systems, crop rotations, soil conditions etc.

Soil carbon stocks

Source: Lugato et al. (2013) Source: Jones et al. (2005)

Forest Management Reference Level

1990 1995 2000 2005 2010 2015 2020 2025 2030

-500000

-450000

-400000

-350000

-300000

-250000

-200000

-150000

-100000

-50000

0

Projection Baseline EFISCENProjection Baseline G4MCountry data submitted to UNFCCC 2011

FM e

mis

sion

s [G

g CO

2 pe

r yea

r]

• EU wide reporting together with EFI and JRC

• Used by 14 MS for UNFCCC reporting

EU Reference Scenario

EC: Reference scenario

• Harvest removals increase over time

• Increment of forests peak and decline due to aging

EC: Reference scenario

• Forest sector main driver of LULUCF sink

• Increasing demand for wood declining forestry sink

• Additional carbon sequestration due to perennial crops

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LULUCF sink is maintained until 2050 BUT declines steadily

LULUCF mitigation potential

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Preliminary results

Discussion & conclusions

• Globally consistent modelling & accounting approach across various sectors and scales

• Takes into account domestic and foreign impacts on biomass carbon stocks

• GLOBIOM is used by EC for various impact assessments and vetted by member states

• Flexible model structure allows for easy enhancement & reporting

• Extension feasible e.g. implementation of additional biodiversity map/indicators

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