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 N 2 O emission per unit N applied Enteric CH 4 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 CO 2 C losses Example – factors determining soil C change Variables in stock change factors Vegetation type Productivity Residue management Manure additions Soil type Drainage Tillage

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 (SOC ref, F lu, F i, F m ) for different climate and soil types Climate/tillage type Conv. tillage Reduced tillage No-till Temperate – dry Temperate - moist Tropical - dry Tropical - moist Values for F m 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 *CO 2 -C 1) Forest area was stratified into two species/age groups Pines – 2000 ha Hardwoods – 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/ha Hardwoods: 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 plots t – ‘t statistic’ (use t=2 for 95% CI) m - mean SD – standard deviation p – desired precision (e.g. use 0.1) Pines: mean = 100 t C/ha, SD = 15 t C/ha Hardwoods: 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 plots random vs gridded permanent (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 m 2, 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

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