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4.5. Carbon accounting: Modeling. Markku Kanninen, CIFOR. What kind of models we use and why?. Models for indirect estimation of carbon pools Use existing known relationships (statistical models) Avoid destructive measurements; lower the field costs

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4.5. Carbon accounting: Modeling

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4 5 carbon accounting modeling

4.5. Carbon accounting: Modeling

Markku Kanninen, CIFOR


What kind of models we use and why

What kind of models we useand why?

  • Models for indirect estimation of carbon pools

    • Use existing known relationships (statistical models)

    • Avoid destructive measurements; lower the field costs

  • Models to explore the potential of various options (ex-ante evaluation) of CDM and/or REDD schemes

    • Use simulation models with existing data for generating scenarios

  • Models for baselines & reference levels

    • Use simulation models to project future development of carbon pools in the absence of [project] [program] activity

      • CDM or REDD

    • Use historic , economic, demographic and other data


Models for indirect estimation of carbon pools

Models for indirect estimation of carbon pools

= [Allometric] models between easily measurable variables and tree biomass component and/or carbon pool

  • Examples:

    • Volume tables (section 4.2)

    • Crown diameter vs. tree biomass (section 4.2)

    • Biomass expansion factor (section 4.3)


Examples

Examples


Models to explore the potential of various options

Models to explore the potential of various options

  • Used for ex-ante evaluation of CDM and/or REDD schemes

  • Using simulation models with existing data for generating scenarios

  • Existing models:

    • CO2FIX - the oldest and most widely used simulation model

    • GORCAM - carbon accounting model, excel spreadsheet

    • CAMFor - developed for the Australian Greenhouse Office (AGO) for tracking the carbon associated with a stand of trees


Examples1

Examples

De Jong et al. (2007) using CO2FIX


Models for baselines reference levels

Models for baselines & reference levels

  • Use simulation models to project future development of carbon pools in the absence of [project] [program] activity either CDM or REDD

  • Use historic , economic, demographic and other data - e.g. known relationships between economic activity and land use change - to generate scenarios

  • Existing models:

    • CO2FIX (Masera et al. 2003) – An approved CDM methodology (AR-AM002) – used for CDM A/R projects

    • Brown et al. (2007) – review of proposed methods for REDD schemes


Examples2

Examples

De Jong et al. (2007) using CO2FIX

Brown et al. (2007) – same as illustrated in Section 4.1


Co2fix c sequestration at stand patch level

CO2FIX - C sequestration at stand (patch) level

  • Existing simulation models

    • CENTURY (Parton et al., 1987)

    • GORCAM (Marland & Schlamadinger, 1997)

    • Original CO2FIX V1 (Mohren et al., 1999)

  • Preference: a locally developed model

  • Models [should] project the changes in relevant carbon stocks in each land-use category over time

  • CO2FIX model V2 description with examples

    • Masera et al., 2003 – Ecological Modelling 164


Co2fix

CO2FIX


Co2fix model

CO2FIX model

  • Over 1000 users in more than 60 countries

  • An approved CDM methodology (AR-AM002) – used for CDM A/R projects

  • Available at http://www.efi.fi/projects/casfor/

  • Modular structure (biomass, soils, products, bioenergy)

  • Cohort model operating at patch scale:

    • Cohorts can be species, species-groups, etc.

    • Parameterization based on existing biomass growth data

  • Allows

    • Comparison between projections (baseline & project case)

    • Calculation of carbon credits


Co2fix model structure

Carbon in the atmosphere

Increment

(yield tables)

Competition

(between or within cohorts)

Biofuels for

energy

Fossil Fuels

for energy

  • Cohort 3

  • Tree biomass

  • stemwood

  • foliage

  • branches

  • roots

  • Cohort 2

  • Tree biomass

  • stemwood

  • foliage

  • branches

  • roots

Raw material

Timber harvesting

Cohort 1

Tree biomass

Burning of

by-products

Primary

Processing

Harvest residues

and mortality due

to management

Burning of

disposed-off

products to

generate energy.

Decomposition

Litter fall

Production line:

Recycling

Products in use

Litter

  • sawnwood

  • boards

  • paper

use

disposal

Humification

Intermediate humus

Decay

  • firewood

Products

in landfill

Humification

Stablehumus

CO2FIX: model structure


Yield tables

Growth model:

from yield tables to CO2FIX

Yield tables


Parameterization of tree growth in co2fix

Growth data from yield tables:- literature - inventory- estimation

Inventory/filed assessment

Literature/laboratory

Parameterization of tree growth in CO2FIX


Cai vol plot data vs co2fix model

CAIVol:Plot data vs. CO2FIX model

Calophyllumbrasilense

Virola

koschnyi

Vochysia

guatemalensis

CAIVol input for the CO2FIX model

Plot data


Terminalia amazonia ica and mai of c mg ha 1 year

Terminalia amazonia: ICA and MAI of C (mg ha-1 year)

Montero & Kanninen (2005)


Foliage branches roots

Same as foliage

Data from:- literature - inventory- estimation

Field data

Field data

Field data

Previous studies, literature

Foliage, branches, roots


Tectona grandis total above ground biomass

Tectonagrandis:Total above-ground biomass

Perez & Kanninen (2003)


Co2fix simulations vs plot data

CO2FIX simulations vs. plot data


Soils

Soils


Soils general parameters

Pet.xls

Meteorological data, e.g. from

http://www.worldclimate.com

Soils – general parameters


Soils cohort parameters

From field and

laboratory data

Soils – cohort parameters


Products types of products

Products – types of products


Products default parameter

If you don't have data – choose one of these

Products – default parameter


Carbon accounting

Carbon accounting


Output example 1

Output example (1)

Tectona grandis plantation


Output example 2

Output example (2)

Multi-strata agroforestry system


Output example 3

Output example (3)

Table of C stocks


Conclusions future needs

Conclusions/future needs

  • Carbon sequestration dynamics of the above-ground biomass rather well understood

  • Data and knowledge gaps in below-ground biomass and soil carbon

  • Different modeling approaches available (e.g. based on yield tables; eco-physiological models etc.)

  • Models and already used e.g. in baseline methods of A/R CDM projects

  • Challenges: REDD and large-scale avoided deforestation modeling – degradation etc.


4 5 carbon accounting modeling

Thank you for your attention


References

References

  • Brown, S., Hall, M., Andrasko, K., Ruiz, F., Marzoli, W., Guerrero, G., Masera, O., Dushku, A., de Jong, B. and Cornell, J. 2007 Baselines for land-use change in the tropics: application to avoided deforestation projects. Mitigation and Adaptation Strategies for Global Change, 12:1001-26.

  • de Jong, B. H., Masera, O. Olguın, M. and Martınez, R. 2007 Greenhouse gas mitigation potential of combining forest management and bioenergy substitution: A case study from Central Highlands of Michoacan, Mexico. Forest Ecology and Management 242:398–411.

  • Liski, J., Palosuo, T., Peltoniemi, M. and Sievanen, R. 2006 Carbon and decomposition model Yasso for forest soils. Ecological Modelling 189 (2005) 168–182.

  • Masera, O., Garza-Caligaris, J.F., Kanninen, M., Karjalainen, T., Nabuurs, G., Pussinen, A., de Jong, B.J. and Mohren, G.M.J. 2003 Modelling carbon sequestration in afforestation and forest management projects: the CO2FIX V 2.0 approach. Ecological Modelling 164: 177-199.

  • Mohren, G.M.J., Garza Caligaris, J.F., Masera, O., Kanninen, M., Karjalainen, T., Pussinen, A. and Nabuurs, G.J. 1999 CO2FIX for Windows: a dynamic model of the CO2-fixation in forests, Version 1.2. IBN Research Report 99/3, 33 pp.

  • Montero, M. and Kanninen, M. 2005 Terminalia amazonia; ecología y silvicultura. CATIE, SérieTécnica, Informe Técnico No. 339. 32 p.

  • Nabuurs, G. J., van Putten, B., Knippers, T.S. and Mohren, G.M.J. 2008 Comparison of uncertainties in carbon sequestration estimates for a tropical and a temperate forest. Forest Ecology and Management 256:237–245.


References1

References

  • Parton, W.J., Schimel, D.S., Cole, C.V. and Ojima, D.S. 1987 Analysis of factors controlling soil organic matter levels in Great Plains grasslands. Soil Science Society of America Journal 5:1137-1179.

  • Pérez Cordero, L.D. and Kanninen, M. 2003 Aboveground biomass of Tectona grandis plantations in Costa Rica. Journal of Tropical Forest Science 15(1): 199-213.

  • Schelhaas, M.J., van Esch, P.W., Groen, T.A., de Jong, B.H.J., Kanninen, M., Liski, J., Masera, O., Mohren, G.M.J., Nabuurs, G.J., Palosuo, T., Pedroni, L., Vallejo, A. and Vilén, T. 2004 CO2FIX V 3.1 - description of a model for quantifying carbon sequestration in forest ecosystems and wood products. ALTERRA Report 1068. Wageningen, the Netherlands. 122 p.

  • Schelhaas, M.J., van Esch, P.W., Groen, T.A., de Jong, B.H.J., Kanninen, M., Liski, J., Masera, O., Mohren, G.M.J., Nabuurs, G.J., Palosuo, T., Pedroni, L., Vallejo, A. and Vilén, T. 2004 CO2FIX V 3.1 - description of a model for quantifying carbon sequestration in forest ecosystems and wood products. ALTERRA Report 1068. Wageningen, the Netherlands. 122 p.

  • Schlamadinger, B. and Marland, G. 1996 The role of forest and bioenergy strategies in the global carbon cycle. Biomass and Bioenergy, 10:275-300.


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