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European Carbon Sinks Modeling Status, Data, Analytical Gaps, EUFASOM. Uwe A. Schneider Research Unit Sustainability and Global Change Hamburg University. Sink Modeling Status. EU Commission 2002: Potential of European sinks from both agriculture and forestry unclear

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European carbon sinks modeling status data analytical gaps eufasom

European Carbon SinksModeling Status, Data, Analytical Gaps, EUFASOM

Uwe A. Schneider

Research Unit Sustainability and Global Change

Hamburg University


Sink modeling status
Sink Modeling Status

  • EU Commission 2002: Potential of European sinks from both agriculture and forestry unclear

  • Fast analysis needed for

    • International negotiation of Kyoto Protocol (define own position and understand others)

    • EU emission trading system


Eu emission trading sinks
EU Emission Trading - Sinks

  • No initial allowance to use credits from carbon sinks projects such as forestry to meet emission targets

  • Review of the emissions trading directive in 2006: if reporting and accounting uncertainties surrounding sinks can be lifted, it leaves open the possibility of using the credits from 2008.


Integrated sink enhancement assessment insea project
Integrated Sink Enhancement Assessment (INSEA) Project

  • Funded by European Commission to address analytical gap of carbon sinks in European Agricultural and Forestry

  • January 2004 – July 2006


Insea model structure

  • Common Data

  • Soil

  • Forests

  • Climate

  • Technologies

  • Markets

  • Model Results

Geographical Analysis

  • Biophysical Models

  • EPIC

  • PICUS

  • Economic Models

  • Hohenheim

  • AROPAJ

  • EFI

  • EU-FASOM

  • AGRIPOL

INSEA Model Structure


Available data
Available Data

  • Soils (MOSES, JRC)

  • Climate (MARS)

  • Forest Inventories (EFI)

  • Conventional Management (FADN, EUROCARE, EUROSTAT, IIASA)

    Problems: Confidentiality restrictions, Data quality, Property rights


Soil data source luca montanarella joint research center ispra italy
Soil DataSource: Luca Montanarella, Joint Research Center, Ispra, Italy


Analytical and data gaps
Analytical and Data Gaps

  • Farm level impacts of alternative agricultural and forest management

    • Costs

    • Inputs

    • Outputs

    • Environmental Impacts


Addressing the gaps
Addressing the Gaps

  • Engineering Analysis

  • Link to other (European) projects

    • GREENGRASS - Sources and Sinks of Greenhouse Gases from managed European Grasslands and Mitigation Strategies

    • CARBOINVENT - Multi-Source Inventory Methods For Quantifying Carbon Stocks And Stock Changes In European Forests

    • MIDAIR - Greenhouse Gas Mitigation for Organic and Conventional Dairy Production

    • CARBO-AGE - Age-related dynamics of carbon exchange in European forests


European non food agriculture enfa project
European Non-Food Agriculture (ENFA) Project

  • Starting in 2005

  • Includes detailed biofuel analysis

  • Environmental impact analysis consistent with food options

  • Integration in EUFASOM

  • Analysis of fuel directives


Benefits for north american sink analysis
Benefits for North American Sink Analysis

  • Refinement of European Data in global models

  • Parallel links, i.e. USFASOM and EUFASOM

  • Extrapolation of European Strategies currently not modeled in US


European forest and agricultural sector model eu fasom
European Forest and Agricultural Sector Model (EU-FASOM)

  • Model built from scratch

  • Uses conceptual approach of (US)-FASOM

  • Mathematical programming based optimization model

  • Partial equilibrium


Eu fasom deviations from usfasom
EU-FASOM - Deviations from USFASOM

  • Texture based land quality classifications

  • Rotations vs. individual crops

  • Dynamic soil carbon rates

  • Validation


Dynamic soil carbon coefficients
Dynamic Soil Carbon Coefficients

  • Soil-climate-regime andsoilmanagement history determines soil carbon coefficients

  • Various strategies can be a source or sink depending on the carbon level of the associated land unit



Problem of dimensionality
Problem of Dimensionality

  • Consider a forward looking decision model with 20 alternative soil management practices and 30 time periods

  • The number of possible management sequences equals 2030 ~ 1E+39

  • Many models yield more combinations (regions, crops, …)


Technical implementation
Technical Implementation

  • Details available in paper available from author

  • X = land use variable

  • S = Soil carbon variable

  • t = time index

  • r = region index

  • i = soil type index

  • u = land use index

  • o = soil carbon class index

  • s = sequestration coefficient

  • c = carbon content coefficient

  • = soil carbon class transistion probability


Soil carbon class distribution
Soil Carbon Class Distribution

Calculation of probabilities is not shown but available in the paper

Soil Carbon Levels