Guidance on Measurement

Elaboration and Examples

Central principle of C and GHG accounting

Emissions rate = “Activity” ☓ “Emission factor”

Central principle of C and GHG accounting

Emissions rate = “Activity” ☓ “Emission factor”

What is being done

E.g. • Area being planted to trees• Amount of fertilizer applied• Number of dairy cattle

Central principle of C and GHG accounting

Emissions rate = “Activity” ☓ “Emission factor”

What is being done

E.g. • Area being planted to trees• Amount of fertilizer applied• Number of dairy cattle

Emission per unit of activity

E.g. • Growth rate for 5-20 yr poplar• N2O emission per unit N

applied• Enteric CH4 emission for

lactating females

Stratification• Activities are stratified (subdivided)

according to factors that most affect GHG emission rates/C sequestration rates

• Example for soil C stock changes– Cropland area is subdivided by:

• type of vegetation (grass vs crop), • relative productivity (fertilized vs non-fertilized), • plant residues (removed vs retained), • tillage type (intensity of soil disturbance)• etc.

Soil C stocks

C inputs

CO2

C losses

Example – factors determining soil C change

Variables in stock change factorsVegetation typeProductivityResidue managementManure additions

Soil type DrainageTillage

Stratification• Activities are stratified (subdivided)

according to factors that most effect GHG emission rates/C sequestration rates

• The factors used to stratify activities (e.g. subdivide land area) are reflected in the values of the emission factors

Simple example - Stock change factors for soil C

Δsoil C stocks = f (SOCref, Flu, Fi, Fm) for different climate and soil types

Climate/tillage type Conv.tillage

Reduced tillage

No-till

Temperate – dry 1 1.02 1.1

Temperate - moist 1 1.08 1.15

Tropical - dry 1 1.09 1.17

Tropical - moist 1 1.15 1.22

Values for Fm in Simple Assessment

Impact of Method used on stratification of activity data

Simple assessment• Emission & stock change factors are default values

supplied by the tool (cannot be changed)• Therefore, the stratification requirements for activity

data are already defined!

Thus the only data needed for GHG estimates are the stratified activity data (i.e., the area associated with each specified management system). But stratification needs to be consistent with the default factor definitions!

Collecting Activity Data• Participatory Rural Appraisal

– Most accurate and comprehensive– Requires good sampling design– Can be expensive

Collecting Activity Data• Participatory Rural Appraisal

– Most accurate and comprehensive– Requires good sampling design– Can be expensive

• Remote sensing– Appropriate for land cover changes (e.g. afforestation

area change)– Most management activities cannot be remotely-

sensed

Collecting Activity Data• Participatory Rural Appraisal

– Most accurate and comprehensive– Requires good sampling design– Can be expensive

• Remote sensing– Appropriate for land cover changes (e.g. afforestation area

change)– Most management activities cannot be remotely-sensed

• Aggregate provincial/district statistics, practice recommendations, expert knowledge– E.g. crop area statistics, yields, fertilizer sales, etc.– Information needs to be ‘disaggregated’ to apply to project area

(often needs ‘expert’ knowledge)

Impact of Method used on stratification of activity data

Simple assessment• Emission & stock change factors are default values

supplied by the tool• Therefore, the stratification requirements for activity

data are already set!

Detailed assessment

• Emission & stock change factors can be changed to project- or region-specific values.

• Project- or region-specific values need to be measured• Activity data may be stratified differently to coincide with

the project-specific emission (or stock change) factors!

For the Detailed Assessment, you can estimate your own emission or stock factors using measurements

Define project boundaries

Stratify project area

Determine which stock and/or emission factors to measure

Determine type, number and location of measurements

Estimate and apply new factors

Modified from Pearson et al. – Winrock Guide

General procedure for project-specific determination of stock and emission factors

Define project boundaries

Stratify project area

Determine which stock and/or emission factors to measure

Determine type, number and location of measurements

Estimate and apply new factors

Modified from Pearson et al. – Winrock Guide

Common strata• Land use (cropland, agroforestry,

etc).• Management system• Vegetation type (forest species, crop)• Soil type• Drainage• Terrain (e.g. steep, flat)

Define project boundaries

Stratify project area

Determine which stock and/or emission factors to measure

Determine type, number and location of measurements

Estimate and apply new factors

Modified from Pearson et al. – Winrock Guide

Selection criteria• What are the main C pools/fluxes ?• Capacity ?• Cost ?

Define project boundaries

Stratify project area

Determine which stock and/or emission factors to measure

Determine type, number and location of measurements

Estimate and apply new factors

Modified from Pearson et al. – Winrock Guide

Measurement design• Variability in the target attribute (e.g.,

tree biomass stocks, tree growth rates, soil C stocks)

• Desired precision in the measurement

Example: Biomass C Losses from Deforestation

Ldf = A * (Bwp – Bwr) * (1+R) * CF *CO2-C

1) Forest area was stratified into two species/age groupsPines – 2000 haHardwoods – 1000 ha

2) Determine your sample requirements a) Get preliminary estimate of mean biomass and variability for these types of forests

- from literature or forest statistics- from a few preliminary plot measurements

Pines: mean = 100 t C/ha, SD = 15 t C/haHardwoods: mean = 80 t C/ha, SD = 25t C/ha

Example: Biomass C Losses from Deforestation

2) Determine your sample requirements b) plot numbers needed for desired precision

n = [(t * SD)/(m * p)]2

n – number of plotst – ‘t statistic’ (use t=2 for 95% CI)m - meanSD – standard deviationp – desired precision (e.g. use 0.1)

Pines: mean = 100 t C/ha, SD = 15 t C/haHardwoods: mean = 80 t C/ha, SD = 25t C/ha

How many plots needed for each forest type?

9 plots for the pines, 39 for the hardwoods

Example: Biomass C Losses from Deforestation

3) Establish plotsrandom vs griddedpermanent (fixed location)plot size and shape

4) Make measurements• typical tree measurements – diameter, height, crown density, etc.• For C inventory, use allometric equations to convert to biomass e.g. biomass per tree = f (dbh, height, basal area)

5) Estimate per tree biomass for each plot and sum biomass total for each plot

6) Compute mean and SD and apply expansion factor to scale from plot size to per ha

e.g. plot size = 100 m2, expansion factor = 100

7) Convert biomass units to C (e.g. default factor=2)

8) You’ve now derived your site specific value for ‘Bwp’ !

Ldf = A * (Bwp – Bwr) * (1+R) * CF *CO2-C

Sources for Measurement

and Monitoring Methods

Example protocols and guidance provided in the Measurement component of the CBP system

General guidance

designed for GEF projects

General Sources for Measurement and Monitoring

Methods

More Questions?

Obrigado!