Methodologies of Carbon Estimation

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Methodologies of Carbon Estimation
By Zahabu, E Malimbwi, R.E Department of
Forest Mensuration and Management (SUA)
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Introduction

• Carbon trade involves the sale of carbon credits.
  
• There are two main types of Carbon Trading
  Schemes that are operating globally to-date
• Voluntary Carbon Trading (VCT), and
• The official Kyoto Protocol Carbon Trading
  Mechanisms.
• Carbon benefit of any forest carbon project
  carbon changes to known levels of precision.
• Determination of carbon changes requires
  baselines

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Baselines

• Baseline historical trends against which
  additional carbon benefits as a result of carbon
  project can be determined.
• Baseline and monitoring schemes
• individual project,
• regional e.g Eastern Arc, and
• national levels
• Requires reliable data on forest extent and
  stocking.

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What Should be Measured?

• Forest Extent
• Forest Stocks in Five IPCC pools
• aboveground,
• belowground,
• litter,
• dead wood and
• soil organic carbon
• Widely accepted forest inventory procedures
  recommended by IPCC Good Practice Guide (IPCC,
  2003)
• CDM Approved LULUCF methodologies.

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Measurable Carbon changes

• Sequestration/Enhancement
• increases of forest biomass within areas of
  existing forest
• Conservation
• maintenance of a steady level of forest area and
  biomass density,
• relate to forests that are already properly
  managed, e.g
• protective forest reserves and
• national parks
• could be rewarded through a special
  conservation under REDD.
• Reduction in emissions from deforestation
• i.e. based on comparisons of rates of change of
  forest area over time,
• Reductions in emissions from degradation
• reductions in biomass/carbon stock in the forest
  without loss of forest area,

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Principles of Baseline Construction

• Net-net accounting
• compares emissions or removal in the commitment
  period to those of a reference scenario i.e
  historical base year (e.g. 1990) or base period
  (e.g. 1990-2000),
• Gross-net accounting
• Measurements of change of carbon stock are
  compared only over the commitment period itself.
• Measure stock at the beginning of the project and
  compares this to the future

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Baseline for Deforestation

• Principle
• a reference scenario from a historical period and
  net-net accounting.
• Based on remotely sensed data over a historical
  period which shows change in area covered by
  forest.
• Then data on carbon stock in different types of
  forest are used to calculate the change in terms
  of tons of carbon.
• May be projected into the future and used to
  credit the additional mitigation benefit of the
  project
• Challenges
• Setting reference base year
• Carbon stock data highly variable national
  forest inventory not undertaken
• Assumes carbon stock per unit area is constant

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FAO FRA 2005

• Tanzania used satellite imagery interpreted data
  of
• 1984 (Millington and Towsend, 1989) and compared
  these with
• 1995 Hunting Technical Services (1997) for the
  determination of land cover changes in the
  country.
• Annual deforestation 412,000 ha
• Average stocking 36 m3/ha from CEEST, (1999)
• Carbon data are reported with their statistical
  confidence intervals (expressed as ? values) at
  known precision level.
• Most previous studies had low precision levels
  due to low sampling intensity adopted.
• Moreover, they cover only a few forests.

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Baseline for Degradation

• Look at rates of biomass loss within the forest
• This is not visible in remote sensing
• Need ground measurements No previous quality
  data
• Possible to use one of the following techniques
• advanced remote sensing techniques (LiDAR),
• harvesting estimates from the local people,
• harvesting estimates from stumps counts,
• default values (rule of thumb)/modelling, or
• harvesting estimates from control sites.
• Will be captured together with enhancement under
  gross-net accounting

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Forest Degradation Enhancement Baselines

• No previous data on forest degradation
  enhancement
• Protective forest to determine the rate of
  recovery
• Productive forests to determine the rate of
  degradation

Recover toward the threshold
Baseline Degrd.
Start of mgt
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Establishment of Baseline at National Level

• Carryout national forest inventory to establish
  deforestation rates and stocking levels
• Determine land use cover changes for the period
  of 1975 to 1990 to 2000 to 2007 using Landsat TM
  (FAO, 2007)
• Conduct case studies to quantify emission factors
  for different forest types
• Identify drivers of deforestation
• Training on national forest inventories and
  remote sensing
• Development of tools for assessment and
  monitoring of deforestation
• Monitoring in PSP/LiDAR technology to capture
  forest enhancement and/or degradation levels.

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Establishment of Baselines at Projects Level

• Review and synthesize existing studies on
  degradation/ growth rates
• Development and testing of methodologies to
  measure and monitor enhancement and/or forest
  degradation
• Development of tools, guidelines and manual for
  degradation assessment and monitoring
• Carryout assessment and monitoring of forest
  degradation in demonstration projects for
  establishing historic degradation emission
  factors including cost implications, and accuracy
  level

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Carbon Assessment Monitoring by Local
Communities

• This is a strategy to involve local communities
  in order to reduce the transaction costs of
  measuring carbon
• Local communities were trained and tasked to
  conduct the measurements
• Techniques were developed to measure and monitor
  carbon stock.
• They are
• User friendly to the users - i.e.to the
  communities
• reliable and
• presented in a format acceptable to the
  scientific community

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The equipment

• Consists of
• A handheld computer with ArcPadTM 6.0 software
  and connected to GPS
• It is easy to use
• Is used to locate
• forestry boundaries
• sample plots and
• recording measurement data
• With a step-by-step guide to the procedures,
  local communities were trained in a short time
  and were able to use the system effectively

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Steps in Carbon Assessment

1. Forest mapping/stratification
2. Pilot survey to estimate variance and number of
   sample plots
3. Locate the sample plots on the ground
4. Measure the dbh of all trees
5. Set out the sub-plots for the grasses, herb and
   litter data
6. Take soil samples randomly within the plot

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Locating sample plots on ground
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Measurements taken from the plot
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Other forest types
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Data analysis

• The following trees stand parameters were
  computed
• Density i.e. the number of stems per ha (N)
• Basal area per hectare (Dominance)(G)
• Volume per ha (V) and
• Dry biomass / carbon (tones per ha)
• Trees volume and biomass were computed using
  tested local existing allometric functions for
  the areas.
• Computation were fitted on Ms Access database

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Results
With Project Case With Project Case With Project Case With Project Case With Project Case With Project Case With Project Case
Vegetation type Location Average annual increment (t/ha/yr)  CO2 sequestration (tCO2/ha/yr) Forest Area (ha) Total sequestration (tCO2/ha/yr)
Woodlands Kitulangalo 2.8 5.3 600 3,180
Ayasanda 1.7 3.2 550 1,760
Lowland Ludewa 4.4 8.3 28.5 237

Montane Mgambo 5.2 9.8 156 1,760
Without Project case Without Project case Without Project case Without Project case Without Project case Without Project case Without Project case
Vegetation type Location Average biomass loss (t/ha/yr)  Average CO2 Emissions (t/ha/yr)  Forest Area (ha) Total CO2 Emissions (tCO2/ha/yr)
Woodland Kitulangalo 1 1.8 600 1014
Montane Mgambo 3.5 6.5 156 1080

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Conclusions Recommendations

• Methods exists to assess and measure forest
  carbon, however these are complex to the users
• More studies are required for the Development of
  user friendly tools for the assessment and
  monitoring forest carbon

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The End!

• Thank You!!!
• Ahsanteni Sana!!!