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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 Markku Kanninen, CIFOR
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 = [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)
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
Examples De Jong et al. (2007) using CO2FIX
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
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 • 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 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
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
Growth model: from yield tables to CO2FIX Yield tables
Growth data from yield tables:- literature - inventory- estimation Inventory/filed assessment Literature/laboratory Parameterization of tree growth in CO2FIX
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) Montero & Kanninen (2005)
Same as foliage Data from:- literature - inventory- estimation Field data Field data Field data Previous studies, literature Foliage, branches, roots
Tectonagrandis:Total above-ground biomass Perez & Kanninen (2003)
Pet.xls Meteorological data, e.g. from http://www.worldclimate.com Soils – general parameters
From field and laboratory data Soils – cohort parameters
If you don't have data – choose one of these Products – default parameter
Output example (1) Tectona grandis plantation
Output example (2) Multi-strata agroforestry system
Output example (3) Table of C stocks
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.
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.
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.