2. Emission Factors

Overview

This chapter is a technical reference for selecting and applying Tier 1 emission factors under the ART-TREES 2.0 standard. Chapter 1 on allometric uncertainty was a practicum, whereas this chapter is a catalogue of the emission factors, stock change parameters and calculation methods that jurisdictional REDD+ accounting requires, and it shows how the IPCC 2019 Refinement data can be used to find land management activities whose carbon gains are large and defensible under audit.

The 2019 Refinement matters for uncertainty because it lets a program replace assumptions with wide uncertainty by parameters with an empirical basis. Under the 2006 Guidelines, many land use transitions, in particular those involving soil carbon, required either very conservative default values or costly Tier 3 field measurement. The 2019 Refinement offers a middle path in Tier 1 defaults stratified by climate, soil type and management intensity, which lowers the coefficient of variation, the standard deviation as a share of the mean, of the key emission factors while keeping the estimate defensible under audit. The expanded grassland management factors (F_MG), for example, let a program separate improved from degraded pasture on observable management criteria rather than relying on a generic grassland value with an uncertainty range wider than plus or minus 50 per cent. The 20-year soil organic carbon (SOC) transition period likewise matches the accounting timeline to the rate at which soil carbon actually changes, and so removes the spike in uncertainty that arose when programs modelled an instantaneous soil carbon loss across varied landscapes.

Ranking the emission factors by their share of the total uncertainty, and choosing land use activities whose defaults are well parameterized, serves two aims at once. The overall uncertainty propagated through the Monte Carlo simulation falls, which lowers the confidence deduction applied at credit issuance, and effort goes to the activities whose carbon gains are both large and defensible under audit.

The chapter shows project developers how to calculate emissions correctly and how to choose the management scenarios that give the largest carbon benefit within political and landscape constraints. On completing it, trainees will be able to

distinguish mineral soil stock-difference accounting from organic soil flux-based accounting
select emission factors by land use transition, climate zone and management practice
apply IPCC Tier 1 default values with correct stratification by soil type, agroecological zone, climate and seasonality
identify carbon crediting opportunities from improved land management
calculate soil organic carbon (SOC) and above-ground biomass (AGB) changes with the standard equations
apply safeguards against double counting across time and space.

2.1 IPCC 2019 Refinement

The 2019 IPCC Refinement introduced four technical changes that widen the choices open to program developers. A 20-year SOC transition period replaces the assumption of instantaneous oxidation with a gradual stock change, so that credits are spread over the project duration rather than concentrated in the year of conversion. Grassland management factors now separate improved tropical grassland (F_MG = 1.17) from degraded grassland (F_MG = 0.70), a gap of about 67 per cent in SOC when management moves from degraded to improved. Agroforestry has system-specific growth rates (G = 2.37-6.24 tC/ha/yr) that separate silvopasture, silvoarable and multistrata systems on empirical data. Forest regrowth is stratified by age, and young secondary forests (≤20 years) accumulate biomass two to three times faster each year than mature stands, which lets a program time restoration to the fastest phase.

In practice, projects in landscape restoration, improved pasture management and agroforestry can now use higher default values with stronger technical justification and attractive annual carbon gains. The chapter treats these emission factors as the building blocks of carbon accounting, examines how their uncertainty propagates through the estimate, and sets out a procedure for finding the activities where uncertainty can be reduced most in line with program objectives.

Soil Accounting Methods

ART-TREES jurisdictional reporting requires a program to separate two accounting approaches by soil type, the stock-difference method for mineral soils and the flux-based method for organic soils, and Table 2.A compares them.

Table 2.A. Mineral Versus Organic Soil Carbon Stock Reporting

Criteria	Mineral Soils	Organic Soils
Soil Types	Cropland, Grassland, Forest on mineral substrates	Peatlands, Wetlands, Histosols (>12-20% OC)
Primary Driver	Land use change (discrete conversion event)	Drainage status (continuous hydrological process)
Carbon Dynamics	Assumed moving to steady-state over period	Oxidizes continually if drained unless re-wetted
Accounting Method	Stock-Difference: ΔC = (SOC₀ − SOC₀₋ₜ) / D	Flux-Based: Annual = EF × Area
Time Horizon	20-year transition period (IPCC default)	Perpetual emissions until water table restored
Credit Mechanism	Sequestration through enhanced inputs	Avoidance through drainage cessation
Key Parameters	Stock change factors (F_LU, F_MG, F_I)	Direct emission factors (tCO₂/ha/yr)
IPCC Source	2019 Vol. 4, Ch. 2, 5, 6	2013 Wetlands Supplement, Ch. 2

Crediting Opportunities

The 2019 Refinement improves the quantification of several land management transitions with substantial credit potential, listed in Table 2.B.

Table 2.B. Opportunities for Carbon Credit Generation

Activity Type	IPCC 2019 Advantage	Key Factor	Material Potential
Grassland Restoration	New management factors reward sustainable grazing + improvements	F_MG = 1.17 (improved) vs. 0.70 (degraded)	~67% SOC recovery over 20 years
Silvoarable Agroforestry	Highest documented biomass accumulation rate	G = 6.24 tC/ha/yr	28.8 tCO₂e/ha/yr (AGB+BGB)
Young Secondary Forest Protection	Age-stratified growth rates emphasize rapid early accumulation	G = 5.9 t DM/ha/yr (Americas, ≤20 yr)	10.8 tCO₂e/ha/yr
Conservation Agriculture	Multiplicative effect of no-till + high inputs	F_MG × F_I = 1.10 × 1.11	22% SOC retention vs. conventional
Multistrata Coffee and Cacao	Dual revenue from carbon credits + commodity production	G = 3.25 tC/ha/yr + SOC gains	Combined above and belowground benefits

2.2 Belowground Stock Change

Stock-Difference Method

The current IPCC Tier 1 method calculates the annual loss of SOC from mineral soils with a linear decay spread over a default transition period of 20 years, which replaces the 2006 assumption that 100 per cent of the SOC oxidizes at once. Mineral soil carbon stock change is therefore calculated by the stock-difference method, which rests on Equation 2.25 (IPCC, 2019, p. 33).

$\Delta C_{Mineral} = \frac{(SOC_0 - SOC_{(0-T)})}{D} \times Area$

where

ΔC_Mineral = annual change in organic carbon stocks (tonnes C/yr)
SOC₀ = soil organic carbon stock in the final year of the transition period (tonnes C/ha)
SOC_(0-T) = soil organic carbon stock at the start of the inventory period (tonnes C/ha)
D = time dependence of the stock change factors (default 20 years)
Area = land area of the stratum (hectares)

Stock Difference Computation

For each SOC inventory period, an initial and a final carbon value are computed from stock change factors estimated for the region and its general growing conditions, as Equation 2.25b defines.

\[SOC = SOC_{REF} \times F_{LU} \times F_{MG} \times F_I\]

where

SOC_REF = reference carbon stock under native vegetation (tC/ha), from Table 2.3
F_LU = land use stock change factor (dimensionless), specific to climate and land use
F_MG = management stock change factor (dimensionless), specific to the practice
F_I = input stock change factor (dimensionless), set by the level of organic amendment

Grassland Management Factors

Grassland is stratified by management intensity and input level, with separate factors for tropical zones and for temperate and boreal zones.

Management Factor (F_MG)

Table 2.C. Grassland Management Stock Change Factors (IPCC 2019, Vol. 4, Ch. 6, Table 6.4)

Management Status	Description	F_MG	Uncertainty	Climate
Nominal or Native	Low to medium intensity grazing; periodic cutting; no significant management improvements	1.00	NA (ref)	All climates
High Intensity Grazing	Shifts in vegetation composition and structure; NOT severely degraded; sustainable stocking rates maintained	0.90	±8%	All climates
Severely Degraded	Major long-term productivity loss; severe soil erosion; extensive bare soil patches; structural damage	0.70	±40%	All climates
Improved Grassland	Sustainable management (light or moderate grazing) PLUS ≥1 improvement: fertilization, species improvement, OR irrigation	1.14	±11%	Temperate and Boreal
Improved Grassland	Sustainable management (light or moderate grazing) PLUS ≥1 improvement: fertilization, species improvement, OR irrigation	1.17	±9%	Tropical (All moisture classes)
Improved Grassland	Sustainable management (light or moderate grazing) PLUS ≥1 improvement: fertilization, species improvement, OR irrigation	1.16	±40%	Tropical Montane

Improved Land Definitions

Improved land requires both a sustainable grazing intensity and at least one documented improvement practice (cite). High intensity grazing (F_MG = 0.90) is moderate degradation, with a change in vegetation but without severe overgrazing or downstream erosion. Severely degraded (F_MG = 0.70) is reserved for land with major structural damage, active erosion and a large loss of productivity, and this class carries the largest restoration credit potential.

Input Factor (F_I)

Table 2.D. Input Stock Change Factors for Improved Grasslands (IPCC 2019, Ch. 6, Table 6.2)

Input Level	Description	F_I	Uncertainty	Application
Medium	Baseline improved grassland; no additional inputs beyond the single improvement that qualifies the system as “improved”	1.00	NA (ref)	Default for F_MG = 1.14-1.17
High	Improved grassland receiving one or more additional management inputs or improvements beyond baseline	1.11	±7%	Multiple concurrent improvements

Critical Distinction

The F_I = 1.11 factor applies only to improvements added beyond the one that qualified the grassland as improved. Light grazing with fertilization gives F_MG = 1.17 and F_I = 1.00, whereas light grazing with fertilization and irrigation gives F_MG = 1.17 and F_I = 1.11. F_I = 1.11 is never applied to the single improvement that justified F_MG = 1.17.

Cropland Management Factors

Cropland accounting stratifies by tillage system (F_LU), tillage intensity (F_MG) and organic input level (F_I).

Land Use Factor

Table 2.E. Cropland Land Use Stock Change Factors (IPCC 2019, Vol. 4, Ch. 5, Table 5.5)

Tillage System	Description	F_LU	Climate Zone	Application
Long-term Cultivated	Continuous annual crops >20 years	0.69	Tropical Moist	Baseline degraded state
Long-term Cultivated	Continuous annual crops >20 years	0.80	Tropical Montane	Baseline degraded state
Long-term Cultivated	Continuous annual crops >20 years	0.92	Tropical Dry	Baseline degraded state
Set Aside	Temporary idle cropland or conservation reserve (<20 years)	0.93	Tropical Moist	Recovering or fallow lands
Paddy Rice	Long-term annual wetland cropping	1.35	All Tropical	Anaerobic SOC preservation

SOC Baseline Strategies

The F_LU = 0.69 factor for long-term cultivated tropical moist cropland means heavy SOC depletion, which gives conservation agriculture a favorable baseline.

Table 2.F. Cropland Tillage Intensity Stock Change Factors (IPCC 2019, Vol. 4, Ch. 5, Table 5.5)

Tillage Practice	Description	F_MG	Climate Zone	Materiality (Ref Value)
Full Tillage	Substantial soil disturbance; >30% surface bare after planting; moldboard or disc plowing	1.00	All climates	no benefit
Reduced Tillage	Primary or secondary tillage, or both, before planting; <30% residue remaining on surface	0.99	Tropical Dry	Minimal benefit
Reduced Tillage	Primary or secondary tillage, or both, before planting; <30% residue remaining on surface	1.02	Tropical Montane	Slight SOC gain
Reduced Tillage	Primary or secondary tillage, or both, before planting; <30% residue remaining on surface	1.04	Tropical Moist and Wet	Moderate SOC gain
No-Till	Direct seeding; minimal disturbance; >30% residue cover maintained	1.04	Tropical Dry	Moderate benefit
No-Till	Direct seeding; minimal disturbance; >30% residue cover maintained	1.07	Tropical Montane	Strong benefit
No-Till	Direct seeding; minimal disturbance; >30% residue cover maintained	1.10	Tropical Moist and Wet	Maximum benefit

Management Strategies (F_MG)

No-till in tropical moist climates gives a 10 per cent SOC increase (F_MG = 1.10) over full tillage. The factor multiplies with the input factor, and combined with high organic inputs (1.10 × 1.11 = 1.22) it can offset the SOC loss from forest conversion.

Input Factors

Input factors apply to cropland and to improved grassland, stratified by the level of organic matter added.

Table 2.F. Organic Input Stock Change Factors (IPCC 2019, Vol. 4, Ch. 5, Table 5.5)

Input Level	Description	F_I	Uncertainty	Examples
Low	Residue removal OR bare fallowing OR no N-fixing crops	0.92	±30%	Export all straw and stover; burn residues
Medium	All residues returned to field OR supplemental organic matter added	1.00	NA (reference)	Standard practice; residue retention
High (without manure)	High residue crops + green manures + cover crops	1.04	±30%	Intensive cover cropping; legume rotations
High (with manure)	High inputs PLUS regular animal manure application	1.11	±30%	Maximum SOC gain

Multiplicative Effect

Consider forest converted to conservation agriculture in a tropical moist climate.

Scenario: Forest → No-till cropland + high inputs + manure

Initial SOC: 38 tC/ha (LAC soil, native forest)
  F_LU = 1.0, F_MG = 1.0, F_I = 1.0
  SOC_initial = 38 × 1.0 × 1.0 × 1.0 = 38.0 tC/ha

Final SOC: 
  F_LU = 0.83 (long-term cultivated), F_MG = 1.10 (no-till), F_I = 1.11 (high+manure)
  SOC_final = 38 × 0.83 × 1.10 × 1.11 = 38.4 tC/ha

Result: SLIGHT NET GAIN despite forest conversion
Annual change: (38.4 - 38.0) / 20 = +0.02 tC/ha/yr (negligible)

The example shows how management can bring necessary agricultural expansion close to carbon neutrality.

Reference Stock Values

Reference stocks (SOC_REF) are the soil organic carbon content under native vegetation, stratified by climate zone and soil type. Tables 2.G to 2.J give the default pre-conversion stocks by soil type for the tropical montane, moist, wet and dry zones, each with its mean stock and its uncertainty.

Table 2.G. Reference SOC Stocks, Tropical Montane (IPCC 2019, Vol. 4, Ch. 2, Table 2.3)

Soil Type	SOC_REF (tC/ha)	Uncertainty	Typical Locations
High Activity Clay (HAC)	51	±10%	Montane valleys; moderate weathering; base-rich parent material
Low Activity Clay (LAC)	44	±11%	Older highly weathered montane soils; kaolinitic clays
Sandy (SAN)	52	±34%	Alluvial terraces (uncommon in mountains)
Volcanic (VOL)	96	±31%	Andean volcanic zones; highest SOC potential
Wetland Organic (WET)	82	±50%	High-altitude peatlands; páramo wetlands

Volcanic Soils

Volcanic soils (VOL) in the Andes hold nearly double the carbon of the other mineral soil types, so protection of volcanic soil landscapes gives the largest carbon benefit.

Table 2.H. Reference SOC Stocks, Tropical Moist (IPCC 2019, Vol. 4, Ch. 2, Table 2.3)

Soil Type	SOC_REF (tC/ha)	Uncertainty	Application
High Activity Clay (HAC)	40	±7%	Nutrient-rich floodplains; recent alluvial deposits
Low Activity Clay (LAC)	38	±5%	Most widespread tropical upland soils; use as default
Sandy (SAN)	27	±12%	Degraded leached soils; low fertility
Volcanic (VOL)	70	±90%	Volcanic regions; high uncertainty, use with caution
Wetland Organic (WET)	68	±17%	Swamp forests; seasonally flooded forests

Table 2.I. Reference SOC Stocks, Tropical Wet (IPCC 2019, Vol. 4, Ch. 2, Table 2.3)

Table 2.J. Reference SOC Stocks, Tropical Dry *(IPCC 2019, Vol. 4, Ch. 2, Table 2.3)*
Soil Type	SOC_REF (tC/ha)	Uncertainty	Context
HAC	60	±8%	Rich alluvial floodplains
LAC	52	±6%	Standard humid rainforest soils
SAN	46	±20%	Poor drainage; seasonally saturated
VOL	77	±27%	Volcanic rainforest zones
WET	49	±19%	Coastal mangroves; tidal zones

Soil Type	SOC_REF (tC/ha)	Uncertainty	Context (<1000mm Rainfall)
HAC	21	±5%	Vertisols in semi-arid zones
LAC	19	±10%	Lowest SOC; limited below-ground credit potential
SAN	9	±9%	Desert margins; very low productivity
VOL	50	±90%	Dry volcanic zones (rare)
WET	22	±17%	Seasonal wetlands; temporary flooding

Dry Tropics Strategies

Tropical dry zones have low SOC baselines (19-21 tC/ha for mineral soils), so carbon crediting there should favor above-ground biomass through agroforestry and forest protection over soil carbon sequestration.

2.3 Aboveground Stock Change

Agroforestry Systems

Agroforestry combines productive land use with substantial biomass accumulation and is a high-value crediting opportunity. The IPCC 2019 Refinement gives system-specific growth rates for the seven agroforestry types defined in Table 2.K.

Table 2.K. Agroforestry System Typology (IPCC 2019, Vol. 4, Ch. 5, Table 5.4)

System	Definition	Tree Component	Crop or Livestock Component
Silvoarable	Trees integrated with annual crop production in spatial mixture	Regularly spaced rows or scattered; 20-1,000 stems/ha; managed for timber or fruit	Cereals, legumes, vegetables in rotation
Silvopasture	Trees integrated with livestock grazing	Scattered individuals or clusters; 150-2,000 stems/ha; shade and fodder provision	Grasses, improved pasture species
Alley Cropping	Dense tree rows with annual crops planted in alleys between hedgerows	Dense hedgerows; ~8,500 stems/ha; regular pruning for biomass or mulch	Annual crops in rotation between tree rows
Multistrata	Vertical stratification of tree species (≥2 canopy layers)	Mixed species at different canopy heights; ~900 stems/ha	Shade-tolerant perennials (coffee, cacao, spices)
Shaded Perennial	Single-story tree canopy over perennial crop	Uniform overstory; ~4,200 stems/ha; managed for consistent shade	Coffee, tea, cacao as understory
Fallow (Rotational)	Woody vegetation regrowth phase in shifting cultivation systems	Dense natural regeneration; ~6,000 stems/ha during fallow	Crops planted after clearing fallow vegetation
Parkland	Scattered mature trees retained in extensive cropland	Very sparse; ~150 stems/ha; remnant trees from forest conversion	Extensive annual crop systems

Stock Accumulation Rates

Table 2.L. Tropical Agroforestry Aboveground Biomass Accumulation Rates (IPCC 2019, Vol. 4, Ch. 5, Tables 5.1 & 5.2; Cardinael et al. 2018)

System	AGB Growth (G)	BGB Growth	Total C Gain	Period	Max Stock (L_max)	Stem Density
Silvoarable	6.24 tC/ha/yr	1.62 tC/ha/yr	7.86 tC/ha/yr	20 years	72.2 tC/ha	880 stems/ha
Silvopasture	3.07 tC/ha/yr	0.84 tC/ha/yr	3.91 tC/ha/yr	20 years	58.2 tC/ha	1,609 stems/ha
Multistrata	3.25 tC/ha/yr	0.80 tC/ha/yr	4.05 tC/ha/yr	20 years	65.0 tC/ha	929 stems/ha
Shaded Perennial	2.40 tC/ha/yr	0.55 tC/ha/yr	2.95 tC/ha/yr	20 years	48.0 tC/ha	4,236 stems/ha
Alley Cropping	2.37 tC/ha/yr	0.79 tC/ha/yr	3.16 tC/ha/yr	20 years	47.4 tC/ha	8,568 stems/ha
Fallow	4.42 tC/ha/yr	1.21 tC/ha/yr	5.63 tC/ha/yr	5 years	22.1 tC/ha	6,074 stems/ha
Parkland	0.59 tC/ha/yr	0.16 tC/ha/yr	0.75 tC/ha/yr	20 years	11.8 tC/ha	152 stems/ha

Cost-Benefit Metrics

Accumulation rates carry an uncertainty of plus or minus 15 to 63 per cent, and that range is a useful benchmark for return on investment decisions and for managing crediting.

Comparing Systems

Silvoarable systems give the highest long-term accumulation, 7.86 tC/ha/yr or 28.8 tCO₂e/ha/yr, and suit jurisdictions with strong silvicultural capacity. Fallow systems accumulate quickly (4.42 tC/ha/yr) but on a short harvest cycle of 5 years, so they bridge short-term credit gaps at the cost of frequent re-establishment. Multistrata coffee and cacao (3.25 tC/ha/yr) balance commodity production with carbon credits and are attractive where markets exist. Below-ground accumulation adds 21 to 27 per cent to the total gain, so root biomass is always included in the credit calculation.

CO₂e Conversion


Total C Gain (tC/ha/yr) × 3.67 = tCO₂e/ha/yr

Example: Silvoarable 
7.86 tC/ha/yr × 3.67 = 28.8 tCO₂e/ha/yr

Temperate Agroforestry

Table 2.M. Cool Temperate Agroforestry Systems

System	Climate	AGB Growth (G)	Harvest Cycle	Max Stock	Application
Silvoarable	Cool Temperate	0.91 tC/ha/yr	30 years	27.3 tC/ha	Northern hemisphere programs
Silvopasture	Cool Temperate	2.33 tC/ha/yr	30 years	69.9 tC/ha	Temperate pasture regions
Hedgerow	Cool Temperate	0.87 tC/ha/km	30 years	26.1 tC/km	Per km, not per ha

Perennial Cropping System

Table 2.N. Perennial Monoculture Biomass Accumulation (IPCC 2019, Vol. 4, Ch. 4, Tables 4.8 & 4.10)

Crop	AGB Growth (G)	BGB Growth	Total Gain	Max Stock	Period	References
Oil Palm	2.40 tC/ha/yr	0.66 tC/ha/yr	3.06 tC/ha/yr	60 tC/ha	25 years	Ch. 4, Table 4.8
Rubber	3.00 tC/ha/yr	0.82 tC/ha/yr	3.82 tC/ha/yr	80.2 tC/ha	27 years	Ch. 4, Table 4.8
Coconut	0.70 tC/ha/yr	0.19 tC/ha/yr	0.89 tC/ha/yr	18 tC/ha	25 years	Default generic
Coffee (unshaded)	0.85 tC/ha/yr	0.23 tC/ha/yr	1.08 tC/ha/yr	17 tC/ha	20 years	Field data synthesis
Cacao (unshaded)	0.90 tC/ha/yr	0.25 tC/ha/yr	1.15 tC/ha/yr	18 tC/ha	20 years	Field data synthesis
Tea	0.70 tC/ha/yr	0.19 tC/ha/yr	0.89 tC/ha/yr	14 tC/ha	20 years	Ch. 4, Table 4.8

Mixed Versus Monoculture

Shaded coffee and cacao in a multistrata system (3.25 tC/ha/yr) accumulate 3.6 times the carbon of unshaded monocultures (~0.9 tC/ha/yr), which is a strong economic case for agroforestry in suitable climates.

Post-Clearance Stock Retention

When forest is converted to perennial cropland, the IPCC gives Year 1 biomass retention values, the carbon left after clearing and before the crop reaches maturity, listed in Table 2.O.

Table 2.O. First-Year Biomass Stock After Forest Conversion (IPCC 2019, Vol. 4, Ch. 5, Table 5.9)

Crop Type	Climate	Year-1 AGB (C_G)	Source
Perennial (generic)	Tropical Moist	4.7 tC/ha	Default
Perennial (generic)	Tropical Montane	4.7 tC/ha	Default
Oil Palm	Tropical	2.4 tC/ha	Specific factor
Rubber	Tropical	3.0 tC/ha	Specific factor
Coffee or Cacao (shaded)	Tropical	3.25 tC/ha	Multistrata proxy

One-Year Retention Limit

The C_G value is the biomass present in Year 1 only. Later years accumulate at the growth rate G in Table 3.4 until the stock reaches its maximum at the end of the harvest cycle.

Forest Stock Regrowth

Secondary forest regrowth depends on stand age, and young stands (≤20 years) accumulate biomass much faster than mature forest (cite). This matters to the aim of the chapter, which is to support project prioritization through the choice of emission factors.

Americas Rainforest

Table 2.P. Secondary Rainforest Growth Rates (Americas) (IPCC 2019, Vol. 4, Ch. 4, Table 4.9)

Age Class	Growth Rate (G)	Carbon Gain	Max Biomass	Strategic Application
≤ 20 years	5.9 t DM/ha/yr	2.77 tC/ha/yr	75.7 t DM/ha	Rapid regrowth phase; prioritize protection
> 20 years	2.3 t DM/ha/yr	1.08 tC/ha/yr	206.4 t DM/ha	Mature phase; lower annual credits

Carbon (tC) is dry matter (t DM) × 0.47, and CO₂ equivalent is carbon × 3.67. The conversion for a young secondary forest in the Americas (≤20 yr) is

2.77 tC/ha/yr × 3.67 = 10.2 tCO₂e/ha/yr

Asia Rainforest

Table 2.Q. Secondary Rainforest Growth Rates (Asia)

Age Class	Growth Rate (G)	Carbon Gain	Max Biomass
≤ 20 years	3.4 t DM/ha/yr	1.60 tC/ha/yr	45.6 t DM/ha
> 20 years	2.0 t DM/ha/yr	0.94 tC/ha/yr	151.2 t DM/ha

Africa Rainforest

Table 2.R. Secondary Rainforest Growth Rates (Africa)

Age Class	Growth Rate (G)	Carbon Gain	Max Biomass
≤ 20 years	3.6 t DM/ha/yr	1.69 tC/ha/yr	56.8 t DM/ha
> 20 years	2.4 t DM/ha/yr	1.13 tC/ha/yr	198.4 t DM/ha

Africa Moist Deciduous

Table 2.S. Secondary Moist Deciduous Forest Growth (Africa)

Age Class	Growth Rate (G)	Carbon Gain	Max Biomass
≤ 20 years	5.2 t DM/ha/yr	2.44 tC/ha/yr	55.7 t DM/ha
> 20 years	2.1 t DM/ha/yr	0.99 tC/ha/yr	179.0 t DM/ha

Americas Dry Forest

Table 2.T. Secondary Dry Forest Growth (Americas)

Age Class	Growth Rate (G)	Carbon Gain	Max Biomass
≤ 20 years	3.9 t DM/ha/yr	1.83 tC/ha/yr	32.2 t DM/ha
> 20 years	1.5 t DM/ha/yr	0.70 tC/ha/yr	72.8 t DM/ha

Age Classes

Young secondary forests (≤20 years) grow two to three times faster than mature stands in every forest type, so protection or restoration projects aimed at 0-20 year regeneration generate the most credits per year (annual tonnes CO₂e/ha). Mature forests (>20 years) hold larger carbon stocks and offer greater permanence. A portfolio that combines young regeneration, for high annual credits, with mature forest, for high stock and low leakage risk, is recommended.

Example A

Example A restores 1,000 ha of severely degraded tropical moist pasture to improved silvopasture with manure inputs.

Step 1 defines the baseline. The soil is a low activity clay (LAC) in a tropical moist climate with SOC_REF of 38 tC/ha (Table 2.7), severely degraded management (F_MG = 0.70), nominal inputs (F_I = 1.0) and biomass of 7.6 t DM/ha, the IPCC 2006 grassland default. The SOC at t=1 is

SOC_initial = SOC_REF × F_LU × F_MG × F_I
SOC_initial = 38 × 1.0 × 0.70 × 1.0
SOC_initial = 26.6 tC/ha

Step 2 defines the project state, with improved tropical grassland management (F_MG = 1.17), high inputs with manure (F_I = 1.11) and silvopasture biomass accumulation (G = 3.07 tC/ha/yr AGB plus 0.84 tC/ha/yr BGB). The SOC at t=20 is

SOC_final = SOC_REF × F_LU × F_MG × F_I
SOC_final = 38 × 1.0 × 1.17 × 1.11
SOC_final = 49.3 tC/ha

Step 3 calculates the annual SOC change.

ΔSOC = (SOC_final - SOC_initial) / 20 years
ΔSOC = (49.3 - 26.6) / 20
ΔSOC = 1.14 tC/ha/yr

Step 4 calculates the biomass accumulation.

ΔBiomass (total) = G_AGB + G_BGB
ΔBiomass = 3.07 + 0.84
ΔBiomass = 3.91 tC/ha/yr

Step 5 sums the total annual carbon benefit.

Total Gain = ΔSOC + ΔBiomass
Total Gain = 1.14 + 3.91
Total Gain = 5.05 tC/ha/yr

Convert to CO₂e:
Total Gain = 5.05 × 3.67 = 18.5 tCO₂e/ha/yr

Step 6 scales the credits to the project over 20 years.

Total Credits (1,000 ha):
Per hectare: 5.05 tC/ha/yr × 20 yr = 101 tC/ha
Project total: 101 tC/ha × 1,000 ha = 101,000 tC
In CO₂e: 101,000 × 3.67 = 370,670 tCO₂e

Annual credits: 18,500 tCO₂e/yr

At $15 per tCO₂e the revenue potential is $277,500 per year for 20 years.

Example B

Example B converts 500 ha of tropical moist forest to no-till annual cropland with high organic inputs, an unavoidable conversion for food security.

Step 1 sets the initial forest biomass and SOC. The soil is LAC (SOC_REF = 38 tC/ha), the biomass is 88 t DM/ha, the IPCC default for tropical moist secondary forest, and the root to shoot ratio is 0.207 (Table 4.4). The initial carbon stocks are

AGB: 88 × 0.47 = 41.4 tC/ha
BGB: 41.4 × 0.207 = 8.6 tC/ha
SOC: 38 × 1.0 × 1.0 × 1.0 = 38.0 tC/ha
Total: 41.4 + 8.6 + 38.0 = 88.0 tC/ha

Step 2 sets the final cropland stocks, with F_LU = 0.83 (long-term cultivated), F_MG = 1.10 (no-till), F_I = 1.04 (high inputs, no manure) and Year 1 biomass C_G = 4.7 tC/ha (Table 3.5). The SOC after 20 years is

SOC_final = 38 × 0.83 × 1.10 × 1.04
SOC_final = 37.1 tC/ha

Annual SOC change:
ΔSOC = (37.1 - 38.0) / 20 = -0.05 tC/ha/yr

Step 3 accounts for the biomass loss.

Biomass lost in Year 1:
  AGB + BGB - C_G retained = (41.4 + 8.6) - 4.7 = 45.3 tC/ha

Convert to CO₂e:
  45.3 × 3.67 = 166 tCO₂e/ha (one-time loss)

Step 4 gives the total carbon impact.

Over 20 years:
  Biomass loss: -166 tCO₂e/ha (Year 1)
  SOC loss: -0.05 tC/ha/yr × 20 yr × 3.67 = -3.7 tCO₂e/ha
  
Total loss: 166 + 3.7 = 169.7 tCO₂e/ha

For 500 ha: 84,850 tCO₂e total
Annual average: 4,243 tCO₂e/yr

Important

With full uncertainty reporting, conservation agriculture with no-till and high manure inputs very nearly cancels the SOC loss from forest conversion, leaving a decline of only about 0.18 tCO₂e/ha/yr across the inventory period. The biomass loss cannot be avoided, which shows the value of applying and documenting the fullest conservation practices where conversion is necessary, and of converting land that is already degraded rather than forest.

Example C

Example C prevents the clearing of 2,000 ha of 10-year-old secondary rainforest in the Americas.

Step 1 sets the baseline, what would happen without the project, and assumes conversion to severely degraded pasture.

Biomass loss:
  Accumulated after 10 yr: 5.9 t DM/ha/yr × 10 yr = 59 t DM/ha
  Carbon: 59 × 0.47 = 27.7 tC/ha (AGB)
  Roots: 27.7 × 0.221 = 6.1 tC/ha (BGB)
  Total biomass: 33.8 tC/ha

SOC degradation (over 20 years):
  Initial: 38 × 1.0 × 1.0 × 1.0 = 38.0 tC/ha
  Final: 38 × 1.0 × 0.70 × 1.0 = 26.6 tC/ha
  Loss: (26.6 - 38.0) / 20 × 20 = 11.4 tC/ha

Total baseline loss: 33.8 + 11.4 = 45.2 tC/ha
In CO₂e: 45.2 × 3.67 = 166 tCO₂e/ha

Step 2 is the project case, in which the protected forest keeps growing for the next 10 years (years 11-20).

Additional biomass accumulation:
  AGB: 5.9 t DM/ha/yr × 10 yr × 0.47 = 27.7 tC/ha
  BGB: 27.7 × 0.221 = 6.1 tC/ha
  Total: 33.8 tC/ha

SOC maintained (no change): 0 tC/ha

Total project gain: 33.8 tC/ha
In CO₂e: 33.8 × 3.67 = 124 tCO₂e/ha

Step 3 gives the net project benefit.

Avoided emissions: 166 tCO₂e/ha
Additional sequestration: 124 tCO₂e/ha
Total credits: 290 tCO₂e/ha over 10-year crediting period

Annual average: 29 tCO₂e/ha/yr

For 2,000 ha:
  Total credits: 580,000 tCO₂e over 10 years
  Annual: 58,000 tCO₂e/yr

At $12 per tCO₂e the revenue potential is $696,000 per year. Young secondary forests (≤20 years) can generate credits at an exceptional rate because the baseline threat of deforestation is high, the protected forest keeps growing at 5.9 t DM/ha/yr, and additionality is easy to demonstrate on marginal land that would otherwise be cleared. Areas regenerating over 20 years are therefore prime candidates for Tier 1 reporting.

2.4 Double-Counting Risks

Double-Counting SOC Timelines

The problem is that legacy emissions from historical land conversion overlap with credits for new management on the same land, and the rule is that each hectare reports in only one land category per reporting year. Three safeguards follow.

During the 20-year SOC transition period, all stock changes are attributed to the end-use land category, not the category of origin, so that each hectare sits in one category per year.
The conversion year of each hectare is recorded so that the remaining transition period can be calculated.
When a new management change occurs before the transition completes, the new factors apply only to the remaining years, as in the following example.

2015: Forest → Cropland (begins 20-year SOC transition)
2020: Apply improved management to same cropland

CORRECT approach:
  - Apply new factors only to remaining 15 years (2020-2035)
  - Calculate: (SOC_new_2035 - SOC_current_2020) / 15 years

INCORRECT approach:
  - Claim new full 20-year transition from 2020
  - This double-counts years 2020-2035 from original conversion

Critical Rule

Only the non-CO₂ gases from biomass burning should be reported separately, because the CO₂ is already counted in the biomass stock change through the Tier 1 assumption of immediate oxidation for that transition type.

Tracking Site-Specific Timelines

The problem is a claim of unlimited biomass accumulation in a system that is harvested periodically, and the rule is that agroforestry credits must account for the harvest cycle and the removal at harvest. The default harvest cycles (Table 3.2) are 20 years for tropical agroforestry, except fallow at 5 years, and 30 years for temperate agroforestry, and the biomass removed at harvest is accounted for as in the following example of a coffee multistrata system on a 20-year cycle.

Accumulation Phase (Years 1-20):
  Annual gain: 3.25 tC/ha/yr × 20 yr = 65 tC/ha accumulated

Harvest (Year 20):
  Biomass removal: L_mean = L_max / 2 = 65 / 2 = 32.5 tC/ha

Re-accumulation Phase (Years 21-40):
  Repeat accumulation: 3.25 tC/ha/yr × 20 yr = 65 tC/ha

Net Over 40 Years:
  Total gain: 3.25 × 40 = 130 tC/ha
  Total removed: 32.5 × 2 = 65 tC/ha
  Net accumulation: 65 tC/ha
  Average annual: 1.63 tC/ha/yr

Tier 2 data may report longer rotations, for example from the farm records of 20-year coffee systems.

Overlapping Activities

The problem is several improvements on the same land, for example a tillage change with lime and manure. Two cases decide how the SOC change is reported. In Case A the impacts are separable because they affect different pools.

Activity 1: No-till (affects 0-30cm mineral SOC) → F_MG = 1.10
Activity 2: Liming (affects inorganic C pool) → Report under Tier 3 inorganic C

Result: No double-counting; different carbon pools

In Case B the impacts overlap because they affect the same pool.

Activity 1: Switch to no-till → F_MG = 1.10
Activity 2: Add cover crops → F_I = 1.04
Activity 3: Add manure → F_I = 1.11 (instead of 1.04)

Decision Options:
  Option 1 (if cumulative effect proven): F_MG × F_I = 1.10 × 1.11 = 1.22
  Option 2 (conservative): Use only F_I = 1.11 (most dominant factor)

Required: Document choice and scientific justification for VVB audit

General Principle

Where it is uncertain whether effects are cumulative or saturating, the most conservative interpretation is applied and the reasoning is documented.

2.5 Uncertainty Quantification

Error Propagation

For independent variables, the total uncertainty is the square root of the sum of the squared component uncertainties.

$U_{\text{total}} = \sqrt{(U_1)^2 + (U_2)^2 + \dots + (U_n)^2}$

where U is the proportional uncertainty, so that plus or minus 11 per cent becomes 0.11. Table 2.U gives the typical range for each Tier 1 emission factor.

Table 2.U. Typical Range in Uncertainty from Tier 1 Emission Factors

Parameter	Source of Uncertainty	Typical Range	Impact on Credits
SOC_REF	Climate and soil classification ambiguity; spatial heterogeneity	±5-90%	High; drives the baseline calculation
F_MG (Improved Grassland)	Management definition; intensity measurement	±9-11%	Moderate; multiplicative factor
F_I (High Input)	Quantification of organic matter additions	±30%	Moderate; multiplicative factor
G (Agroforestry)	System definition; site variability; climate	±13-63%	High; direct rate parameter
Biomass Stock	Remote sensing error; allometric equation selection	±20-40%	High; one-time loss calculation
Activity Data (Area)	Land use classification; GPS accuracy	±5-15%	Scales all estimates

Worked Examples

The project is 1,000 ha of improved silvopasture (F_MG = 1.17, F_I = 1.11, G = 3.07 tC/ha/yr), and its uncertainty components combine as follows.

SOC_REF (LAC, Tropical Moist): ±5% → 0.05
F_MG (Improved Tropical): ±9% → 0.09
F_I (High Input): ±30% → 0.30
G (Silvopasture AGB): ±63% → 0.63
Area measurement: ±10% → 0.10

U_total = √[(0.05)² + (0.09)² + (0.30)² + (0.63)² + (0.10)²]
U_total = √[0.0025 + 0.0081 + 0.09 + 0.3969 + 0.01]
U_total = √0.5075 = 0.712 → ±71%

The credit calculation with that uncertainty is

Point Estimate: 18.5 tCO₂e/ha/yr × 1,000 ha = 18,500 tCO₂e/yr

Conservative Estimate (Lower Bound):
  18,500 × (1 - 0.712) = 5,328 tCO₂e/yr

Upper Bound:
  18,500 × (1 + 0.712) = 31,672 tCO₂e/yr

95% Confidence Interval: 5,328 - 31,672 tCO₂e/yr

2.6 Chapter Summary

Six decision points were compiled for program proponents.

Verify the soil type first, and separate mineral from organic soils before selecting the accounting method, because this is the most basic decision.
Stratify correctly, matching climate zone, soil type and management class to the IPCC lookup tables, because wrong stratification invalidates the result.
Document the baseline thoroughly, because large SOC or biomass changes need strong evidence of a degraded initial condition to justify additionality.
Apply harvest cycles, because agroforestry credits must account for periodic biomass removal and indefinite accumulation is never claimed.
Apply safeguards against double counting through tracking over time, separation of pools and conservative treatment of overlapping activities.
Quantify uncertainty by calculating and reporting the propagated total, and consider a Tier 2 upgrade where Tier 1 uncertainty exceeds plus or minus 50 per cent.

ART-TREES requires three items of uncertainty documentation.

The quantified uncertainty of each major parameter
The propagated total uncertainty of the final emission and removal estimates
Documented justification for a Tier 2 or Tier 3 upgrade in support of variance requests

Table 2.V ranks the conversion activities by carbon benefit.

Table 2.V. Emissions Factor Uncertainty Enhancements

Rank	Conversion Activity	Carbon Benefit	Key Considerations
1	Grassland Restoration (degraded to improved)	67% SOC increase	Requires documented degradation baseline
2	Silvoarable agroforestry establishment	7.86 tC/ha/yr total gain	Needs strong silvicultural capacity
3	Young secondary forest conservation	2.77-5.9 tC/ha/yr + avoided loss	High additionality, rapid credits
4	Multistrata coffee and cacao conversion	4.05 tC/ha/yr + commodity income	Market-dependent feasibility
5	Conservation agriculture adoption	22% SOC retention vs. tillage	Cumulative with other practices

--- title: "2. Emission Factors" format: docx: reference-doc: ../references/style.docx highlight-style: github execute: echo: true warning: false message: false knitr: opts_chunk: prefer-html: true dev: "png" dpi: 300 bibliography: ../references/references.bib csl: ../references/apa.csl --- ## Overview {.unnumbered} This chapter is a technical reference for selecting and applying Tier 1 emission factors under the ART-TREES 2.0 standard. Chapter 1 on allometric uncertainty was a practicum, whereas this chapter is a catalogue of the emission factors, stock change parameters and calculation methods that jurisdictional REDD+ accounting requires, and it shows how the IPCC 2019 Refinement data can be used to find land management activities whose carbon gains are large and defensible under audit. The 2019 Refinement matters for uncertainty because it lets a program replace assumptions with wide uncertainty by parameters with an empirical basis. Under the 2006 Guidelines, many land use transitions, in particular those involving soil carbon, required either very conservative default values or costly Tier 3 field measurement. The 2019 Refinement offers a middle path in Tier 1 defaults stratified by climate, soil type and management intensity, which lowers the coefficient of variation, the standard deviation as a share of the mean, of the key emission factors while keeping the estimate defensible under audit. The expanded grassland management factors (F_MG), for example, let a program separate improved from degraded pasture on observable management criteria rather than relying on a generic grassland value with an uncertainty range wider than plus or minus 50 per cent. The 20-year soil organic carbon (SOC) transition period likewise matches the accounting timeline to the rate at which soil carbon actually changes, and so removes the spike in uncertainty that arose when programs modelled an instantaneous soil carbon loss across varied landscapes. Ranking the emission factors by their share of the total uncertainty, and choosing land use activities whose defaults are well parameterized, serves two aims at once. The overall uncertainty propagated through the Monte Carlo simulation falls, which lowers the confidence deduction applied at credit issuance, and effort goes to the activities whose carbon gains are both large and defensible under audit. The chapter shows project developers how to calculate emissions correctly and how to choose the management scenarios that give the largest carbon benefit within political and landscape constraints. On completing it, trainees will be able to - distinguish mineral soil stock-difference accounting from organic soil flux-based accounting - select emission factors by land use transition, climate zone and management practice - apply IPCC Tier 1 default values with correct stratification by soil type, agroecological zone, climate and seasonality - identify carbon crediting opportunities from improved land management - calculate soil organic carbon (SOC) and above-ground biomass (AGB) changes with the standard equations - apply safeguards against double counting across time and space. ## 2.1 IPCC 2019 Refinement The 2019 IPCC Refinement introduced four technical changes that widen the choices open to program developers. A 20-year SOC transition period replaces the assumption of instantaneous oxidation with a gradual stock change, so that credits are spread over the project duration rather than concentrated in the year of conversion. Grassland management factors now separate improved tropical grassland (F_MG = 1.17) from degraded grassland (F_MG = 0.70), a gap of about 67 per cent in SOC when management moves from degraded to improved. Agroforestry has system-specific growth rates (G = 2.37-6.24 tC/ha/yr) that separate silvopasture, silvoarable and multistrata systems on empirical data. Forest regrowth is stratified by age, and young secondary forests (≤20 years) accumulate biomass two to three times faster each year than mature stands, which lets a program time restoration to the fastest phase. In practice, projects in landscape restoration, improved pasture management and agroforestry can now use higher default values with stronger technical justification and attractive annual carbon gains. The chapter treats these emission factors as the building blocks of carbon accounting, examines how their uncertainty propagates through the estimate, and sets out a procedure for finding the activities where uncertainty can be reduced most in line with program objectives. ### Soil Accounting Methods {.unnumbered} ART-TREES jurisdictional reporting requires a program to separate two accounting approaches by soil type, the stock-difference method for mineral soils and the flux-based method for organic soils, and Table 2.A compares them. Table 2.A. Mineral Versus Organic Soil Carbon Stock Reporting | Criteria | Mineral Soils | Organic Soils | |:-----------------------|:-----------------------|:-----------------------| | Soil Types | Cropland, Grassland, Forest on mineral substrates | Peatlands, Wetlands, Histosols (\>12-20% OC) | | Primary Driver | Land use change (discrete conversion event) | Drainage status (continuous hydrological process) | | Carbon Dynamics | Assumed moving to steady-state over period | Oxidizes continually if drained unless re-wetted | | Accounting Method | Stock-Difference: ΔC = (SOC₀ − SOC₀₋ₜ) / D | Flux-Based: Annual = EF × Area | | Time Horizon | 20-year transition period (IPCC default) | Perpetual emissions until water table restored | | Credit Mechanism | Sequestration through enhanced inputs | Avoidance through drainage cessation | | Key Parameters | Stock change factors (F~LU~, F~MG~, F~I~) | Direct emission factors (tCO₂/ha/yr) | | IPCC Source | 2019 Vol. 4, Ch. 2, 5, 6 | 2013 Wetlands Supplement, Ch. 2 | ### Crediting Opportunities {.unnumbered} The 2019 Refinement improves the quantification of several land management transitions with substantial credit potential, listed in Table 2.B. Table 2.B. Opportunities for Carbon Credit Generation | Activity Type | IPCC 2019 Advantage | Key Factor | Material Potential | |------------------|------------------|------------------|------------------| | Grassland Restoration | New management factors reward sustainable grazing + improvements | F~MG~ = 1.17 (improved) vs. 0.70 (degraded) | \~67% SOC recovery over 20 years | | Silvoarable Agroforestry | Highest documented biomass accumulation rate | G = 6.24 tC/ha/yr | 28.8 tCO₂e/ha/yr (AGB+BGB) | | Young Secondary Forest Protection | Age-stratified growth rates emphasize rapid early accumulation | G = 5.9 t DM/ha/yr (Americas, ≤20 yr) | 10.8 tCO₂e/ha/yr | | Conservation Agriculture | Multiplicative effect of no-till + high inputs | F~MG~ × F~I~ = 1.10 × 1.11 | 22% SOC retention vs. conventional | | Multistrata Coffee and Cacao | Dual revenue from carbon credits + commodity production | G = 3.25 tC/ha/yr + SOC gains | Combined above and belowground benefits | ------------------------------------------------------------------------ ## 2.2 Belowground Stock Change #### Stock-Difference Method {.unnumbered} The current IPCC Tier 1 method calculates the annual loss of SOC from mineral soils with a linear decay spread over a default transition period of 20 years, which replaces the 2006 assumption that 100 per cent of the SOC oxidizes at once. Mineral soil carbon stock change is therefore calculated by the stock-difference method, which rests on Equation 2.25 [@ipccChapter2Generic2019, p.33]. $\Delta C_{Mineral} = \frac{(SOC_0 - SOC_{(0-T)})}{D} \times Area$ where - ΔC~Mineral~ = annual change in organic carbon stocks (tonnes C/yr) - SOC₀ = soil organic carbon stock in the final year of the transition period (tonnes C/ha) - SOC~(0-T)~ = soil organic carbon stock at the start of the inventory period (tonnes C/ha) - D = time dependence of the stock change factors (default 20 years) - Area = land area of the stratum (hectares) #### Stock Difference Computation For each SOC inventory period, an initial and a final carbon value are computed from stock change factors estimated for the region and its general growing conditions, as Equation 2.25b defines. $$SOC = SOC_{REF} \times F_{LU} \times F_{MG} \times F_I$$ where - SOC~REF~ = reference carbon stock under native vegetation (tC/ha), from Table 2.3 - F~LU~ = land use stock change factor (dimensionless), specific to climate and land use - F~MG~ = management stock change factor (dimensionless), specific to the practice - F~I~ = input stock change factor (dimensionless), set by the level of organic amendment ### Grassland Management Factors Grassland is stratified by management intensity and input level, with separate factors for tropical zones and for temperate and boreal zones. #### Management Factor (F~MG~) {.unnumbered} Table 2.C. Grassland Management Stock Change Factors (IPCC 2019, Vol. 4, Ch. 6, [Table 6.4](https://www.ipcc-nggip.iges.or.jp/public/2006gl/pdf/4_Volume4/V4_06_Ch6_Grassland.pdf#page=27)) | Management Status | Description | F~MG~ | Uncertainty | Climate | |---------------|---------------|---------------|---------------|---------------| | Nominal or Native | Low to medium intensity grazing; periodic cutting; no significant management improvements | 1.00 | NA (ref) | All climates | | High Intensity Grazing | Shifts in vegetation composition and structure; NOT severely degraded; sustainable stocking rates maintained | 0.90 | ±8% | All climates | | Severely Degraded | Major long-term productivity loss; severe soil erosion; extensive bare soil patches; structural damage | 0.70 | ±40% | All climates | | Improved Grassland | Sustainable management (light or moderate grazing) PLUS ≥1 improvement: fertilization, species improvement, OR irrigation | 1.14 | ±11% | Temperate and Boreal | | Improved Grassland | Sustainable management (light or moderate grazing) PLUS ≥1 improvement: fertilization, species improvement, OR irrigation | 1.17 | ±9% | Tropical (All moisture classes) | | Improved Grassland | Sustainable management (light or moderate grazing) PLUS ≥1 improvement: fertilization, species improvement, OR irrigation | 1.16 | ±40% | Tropical Montane | ::: callout-important ## Improved Land Definitions Improved land requires both a sustainable grazing intensity and at least one documented improvement practice (*`cite`*). High intensity grazing (F~MG~ = 0.90) is moderate degradation, with a change in vegetation but without severe overgrazing or downstream erosion. Severely degraded (F~MG~ = 0.70) is reserved for land with major structural damage, active erosion and a large loss of productivity, and this class carries the largest restoration credit potential. ::: #### Input Factor (F~I~) {.unnumbered} Table 2.D. Input Stock Change Factors for Improved Grasslands (*IPCC 2019, Ch. 6, [Table 6.2](https://www.ipcc-nggip.iges.or.jp/public/2006gl/pdf/4_Volume4/V4_06_Ch6_Grassland.pdf#page=27))* | Input Level | Description | F~I~ | Uncertainty | Application | |---------------|---------------|---------------|---------------|---------------| | Medium | Baseline improved grassland; no *additional* inputs beyond the single improvement that qualifies the system as "improved" | 1.00 | NA (ref) | Default for F~MG~ = 1.14-1.17 | | High | Improved grassland receiving one or more additional management inputs or improvements beyond baseline | 1.11 | ±7% | Multiple concurrent improvements | ::: callout-warning ## Critical Distinction The F~I~ = 1.11 factor applies only to improvements added beyond the one that qualified the grassland as improved. Light grazing with fertilization gives F~MG~ = 1.17 and F~I~ = 1.00, whereas light grazing with fertilization and irrigation gives F~MG~ = 1.17 and F~I~ = 1.11. F~I~ = 1.11 is never applied to the single improvement that justified F~MG~ = 1.17. ::: ------------------------------------------------------------------------ ### Cropland Management Factors Cropland accounting stratifies by tillage system (F~LU~), tillage intensity (F~MG~) and organic input level (F~I~). #### Land Use Factor Table 2.E. Cropland Land Use Stock Change Factors (*IPCC 2019, Vol. 4, Ch. 5, [Table 5.5](https://www.ipcc-nggip.iges.or.jp/public/2019rf/pdf/4_Volume4/19R_V4_Ch05_Cropland.pdf#page=27))* | Tillage System | Description | F~LU~ | Climate Zone | Application | |---------------|---------------|---------------|---------------|---------------| | Long-term Cultivated | Continuous annual crops \>20 years | 0.69 | Tropical Moist | Baseline degraded state | | Long-term Cultivated | Continuous annual crops \>20 years | 0.80 | Tropical Montane | Baseline degraded state | | Long-term Cultivated | Continuous annual crops \>20 years | 0.92 | Tropical Dry | Baseline degraded state | | Set Aside | Temporary idle cropland or conservation reserve (\<20 years) | 0.93 | Tropical Moist | Recovering or fallow lands | | Paddy Rice | Long-term annual wetland cropping | 1.35 | All Tropical | Anaerobic SOC preservation | ::: callout-tip ## SOC Baseline Strategies The F~LU~ = 0.69 factor for long-term cultivated tropical moist cropland means heavy SOC depletion, which gives conservation agriculture a favorable baseline. ::: ------------------------------------------------------------------------ Table 2.F. Cropland Tillage Intensity Stock Change Factors (*IPCC 2019, Vol. 4, Ch. 5, [Table 5.5](https://www.ipcc-nggip.iges.or.jp/public/2019rf/pdf/4_Volume4/19R_V4_Ch05_Cropland.pdf#page=27))* | Tillage Practice | Description | F~MG~ | Climate Zone | Materiality (Ref Value) | |---------------|---------------|---------------|---------------|---------------| | Full Tillage | Substantial soil disturbance; \>30% surface bare after planting; moldboard or disc plowing | 1.00 | All climates | no benefit | | Reduced Tillage | Primary or secondary tillage, or both, before planting; \<30% residue remaining on surface | 0.99 | Tropical Dry | Minimal benefit | | Reduced Tillage | Primary or secondary tillage, or both, before planting; \<30% residue remaining on surface | 1.02 | Tropical Montane | Slight SOC gain | | Reduced Tillage | Primary or secondary tillage, or both, before planting; \<30% residue remaining on surface | 1.04 | Tropical Moist and Wet | Moderate SOC gain | | No-Till | Direct seeding; minimal disturbance; \>30% residue cover maintained | 1.04 | Tropical Dry | Moderate benefit | | No-Till | Direct seeding; minimal disturbance; \>30% residue cover maintained | 1.07 | Tropical Montane | Strong benefit | | No-Till | Direct seeding; minimal disturbance; \>30% residue cover maintained | 1.10 | Tropical Moist and Wet | Maximum benefit | ::: callout-tip ## Management Strategies (F~MG~) No-till in tropical moist climates gives a 10 per cent SOC increase (F~MG~ = 1.10) over full tillage. The factor multiplies with the input factor, and combined with high organic inputs (1.10 × 1.11 = 1.22) it can offset the SOC loss from forest conversion. ::: ------------------------------------------------------------------------ ### Input Factors Input factors apply to cropland and to improved grassland, stratified by the level of organic matter added. Table 2.F. Organic Input Stock Change Factors (*IPCC 2019, Vol. 4, Ch. 5, [Table 5.5](https://www.ipcc-nggip.iges.or.jp/public/2019rf/pdf/4_Volume4/19R_V4_Ch05_Cropland.pdf#page=27))* | Input Level | Description | F~I~ | Uncertainty | Examples | |---------------|---------------|---------------|---------------|---------------| | Low | Residue removal OR bare fallowing OR no N-fixing crops | 0.92 | ±30% | Export all straw and stover; burn residues | | Medium | All residues returned to field OR supplemental organic matter added | 1.00 | NA (reference) | Standard practice; residue retention | | High (without manure) | High residue crops + green manures + cover crops | 1.04 | ±30% | Intensive cover cropping; legume rotations | | High (with manure) | High inputs PLUS regular animal manure application | 1.11 | ±30% | Maximum SOC gain | #### Multiplicative Effect Consider forest converted to conservation agriculture in a tropical moist climate. ``` Scenario: Forest → No-till cropland + high inputs + manure Initial SOC: 38 tC/ha (LAC soil, native forest) F_LU = 1.0, F_MG = 1.0, F_I = 1.0 SOC_initial = 38 × 1.0 × 1.0 × 1.0 = 38.0 tC/ha Final SOC: F_LU = 0.83 (long-term cultivated), F_MG = 1.10 (no-till), F_I = 1.11 (high+manure) SOC_final = 38 × 0.83 × 1.10 × 1.11 = 38.4 tC/ha Result: SLIGHT NET GAIN despite forest conversion Annual change: (38.4 - 38.0) / 20 = +0.02 tC/ha/yr (negligible) ``` The example shows how management can bring necessary agricultural expansion close to carbon neutrality. ------------------------------------------------------------------------ ### Reference Stock Values Reference stocks (SOC~REF~) are the soil organic carbon content under native vegetation, stratified by climate zone and soil type. Tables 2.G to 2.J give the default pre-conversion stocks by soil type for the tropical montane, moist, wet and dry zones, each with its mean stock and its uncertainty. Table 2.G. Reference SOC Stocks, Tropical Montane (*IPCC 2019, Vol. 4, Ch. 2, [Table 2.3](https://www.ipcc-nggip.iges.or.jp/public/2019rf/pdf/4_Volume4/19R_V4_Ch02_Generic%20Methods.pdf#page=35)*) | Soil Type | SOC~REF~ (tC/ha) | Uncertainty | Typical Locations | |------------------|------------------|------------------|------------------| | High Activity Clay (HAC) | 51 | ±10% | Montane valleys; moderate weathering; base-rich parent material | | Low Activity Clay (LAC) | 44 | ±11% | Older highly weathered montane soils; kaolinitic clays | | Sandy (SAN) | 52 | ±34% | Alluvial terraces (uncommon in mountains) | | Volcanic (VOL) | 96 | ±31% | Andean volcanic zones; highest SOC potential | | Wetland Organic (WET) | 82 | ±50% | High-altitude peatlands; páramo wetlands | ------------------------------------------------------------------------ ::: callout-tip ## Volcanic Soils Volcanic soils (VOL) in the Andes hold nearly double the carbon of the other mineral soil types, so protection of volcanic soil landscapes gives the largest carbon benefit. ::: ------------------------------------------------------------------------ Table 2.H. Reference SOC Stocks, Tropical Moist *(IPCC 2019, Vol. 4, Ch. 2, Table 2.3)* | Soil Type | SOC~REF~ (tC/ha) | Uncertainty | Application | |------------------|------------------|------------------|------------------| | High Activity Clay (HAC) | 40 | ±7% | Nutrient-rich floodplains; recent alluvial deposits | | Low Activity Clay (LAC) | 38 | ±5% | Most widespread tropical upland soils; use as default | | Sandy (SAN) | 27 | ±12% | Degraded leached soils; low fertility | | Volcanic (VOL) | 70 | ±90% | Volcanic regions; high uncertainty, use with caution | | Wetland Organic (WET) | 68 | ±17% | Swamp forests; seasonally flooded forests | Table 2.I. Reference SOC Stocks, Tropical Wet *(IPCC 2019, Vol. 4, Ch. 2, Table 2.3)* | Soil Type | SOC~REF~ (tC/ha) | Uncertainty | Context | |---------------|---------------|---------------|-----------------------------| | HAC | 60 | ±8% | Rich alluvial floodplains | | LAC | 52 | ±6% | Standard humid rainforest soils | | SAN | 46 | ±20% | Poor drainage; seasonally saturated | | VOL | 77 | ±27% | Volcanic rainforest zones | | WET | 49 | ±19% | Coastal mangroves; tidal zones | : Table 2.J. Reference SOC Stocks, Tropical Dry *(IPCC 2019, Vol. 4, Ch. 2, Table 2.3)* | Soil Type | SOC~REF~ (tC/ha) | Uncertainty | Context (\<1000mm Rainfall) | |------------------|------------------|------------------|------------------| | HAC | 21 | ±5% | Vertisols in semi-arid zones | | LAC | 19 | ±10% | Lowest SOC; limited below-ground credit potential | | SAN | 9 | ±9% | Desert margins; very low productivity | | VOL | 50 | ±90% | Dry volcanic zones (rare) | | WET | 22 | ±17% | Seasonal wetlands; temporary flooding | ::: callout-important ## Dry Tropics Strategies Tropical dry zones have low SOC baselines (19-21 tC/ha for mineral soils), so carbon crediting there should favor above-ground biomass through agroforestry and forest protection over soil carbon sequestration. ::: ------------------------------------------------------------------------ ## 2.3 Aboveground Stock Change ### Agroforestry Systems {.unnumbered} Agroforestry combines productive land use with substantial biomass accumulation and is a high-value crediting opportunity. The IPCC 2019 Refinement gives system-specific growth rates for the seven agroforestry types defined in Table 2.K. Table 2.K. Agroforestry System Typology *(IPCC 2019, Vol. 4, Ch. 5, Table 5.4)* | System | Definition | Tree Component | Crop or Livestock Component | |------------------|------------------|------------------|------------------| | Silvoarable | Trees integrated with annual crop production in spatial mixture | Regularly spaced rows or scattered; 20-1,000 stems/ha; managed for timber or fruit | Cereals, legumes, vegetables in rotation | | Silvopasture | Trees integrated with livestock grazing | Scattered individuals or clusters; 150-2,000 stems/ha; shade and fodder provision | Grasses, improved pasture species | | Alley Cropping | Dense tree rows with annual crops planted in alleys between hedgerows | Dense hedgerows; \~8,500 stems/ha; regular pruning for biomass or mulch | Annual crops in rotation between tree rows | | Multistrata | Vertical stratification of tree species (≥2 canopy layers) | Mixed species at different canopy heights; \~900 stems/ha | Shade-tolerant perennials (coffee, cacao, spices) | | Shaded Perennial | Single-story tree canopy over perennial crop | Uniform overstory; \~4,200 stems/ha; managed for consistent shade | Coffee, tea, cacao as understory | | Fallow (Rotational) | Woody vegetation regrowth phase in shifting cultivation systems | Dense natural regeneration; \~6,000 stems/ha during fallow | Crops planted after clearing fallow vegetation | | Parkland | Scattered mature trees retained in extensive cropland | Very sparse; \~150 stems/ha; remnant trees from forest conversion | Extensive annual crop systems | #### Stock Accumulation Rates {.unnumbered} Table 2.L. Tropical Agroforestry Aboveground Biomass Accumulation Rates *(IPCC 2019, Vol. 4, Ch. 5, Tables 5.1 & 5.2; Cardinael et al. 2018)* | System | AGB Growth (G) | BGB Growth | Total C Gain | Period | Max Stock (L~max~) | Stem Density | |-----------|-----------|-----------|-----------|-----------|-----------|-----------| | Silvoarable | 6.24 tC/ha/yr | 1.62 tC/ha/yr | 7.86 tC/ha/yr | 20 years | 72.2 tC/ha | 880 stems/ha | | Silvopasture | 3.07 tC/ha/yr | 0.84 tC/ha/yr | 3.91 tC/ha/yr | 20 years | 58.2 tC/ha | 1,609 stems/ha | | Multistrata | 3.25 tC/ha/yr | 0.80 tC/ha/yr | 4.05 tC/ha/yr | 20 years | 65.0 tC/ha | 929 stems/ha | | Shaded Perennial | 2.40 tC/ha/yr | 0.55 tC/ha/yr | 2.95 tC/ha/yr | 20 years | 48.0 tC/ha | 4,236 stems/ha | | Alley Cropping | 2.37 tC/ha/yr | 0.79 tC/ha/yr | 3.16 tC/ha/yr | 20 years | 47.4 tC/ha | 8,568 stems/ha | | Fallow | 4.42 tC/ha/yr | 1.21 tC/ha/yr | 5.63 tC/ha/yr | 5 years | 22.1 tC/ha | 6,074 stems/ha | | Parkland | 0.59 tC/ha/yr | 0.16 tC/ha/yr | 0.75 tC/ha/yr | 20 years | 11.8 tC/ha | 152 stems/ha | ::: callout-tip ## Cost-Benefit Metrics Accumulation rates carry an uncertainty of plus or minus 15 to 63 per cent, and that range is a useful benchmark for return on investment decisions and for managing crediting. ::: ### Comparing Systems {.unnumbered} Silvoarable systems give the highest long-term accumulation, 7.86 tC/ha/yr or 28.8 tCO₂e/ha/yr, and suit jurisdictions with strong silvicultural capacity. Fallow systems accumulate quickly (4.42 tC/ha/yr) but on a short harvest cycle of 5 years, so they bridge short-term credit gaps at the cost of frequent re-establishment. Multistrata coffee and cacao (3.25 tC/ha/yr) balance commodity production with carbon credits and are attractive where markets exist. Below-ground accumulation adds 21 to 27 per cent to the total gain, so root biomass is always included in the credit calculation. #### CO₂e Conversion {.unnumbered} ``` bash Total C Gain (tC/ha/yr) × 3.67 = tCO₂e/ha/yr Example: Silvoarable 7.86 tC/ha/yr × 3.67 = 28.8 tCO₂e/ha/yr ``` ------------------------------------------------------------------------ #### Temperate Agroforestry Table 2.M. Cool Temperate Agroforestry Systems | System | Climate | AGB Growth (G) | Harvest Cycle | Max Stock | Application | |------------|------------|------------|------------|------------|------------| | Silvoarable | Cool Temperate | 0.91 tC/ha/yr | 30 years | 27.3 tC/ha | Northern hemisphere programs | | Silvopasture | Cool Temperate | 2.33 tC/ha/yr | 30 years | 69.9 tC/ha | Temperate pasture regions | | Hedgerow | Cool Temperate | 0.87 tC/ha/km | 30 years | 26.1 tC/km | Per km, not per ha | ------------------------------------------------------------------------ ### Perennial Cropping System {.unnumbered} ~~Table 2.N. Perennial Monoculture Biomass Accumulation (*IPCC 2019, Vol. 4, Ch. 4, Tables 4.8 & 4.10)*~~ | Crop | AGB Growth (G) | BGB Growth | Total Gain | Max Stock | Period | References | |-----------|-----------|-----------|-----------|-----------|-----------|-----------| | Oil Palm | 2.40 tC/ha/yr | 0.66 tC/ha/yr | 3.06 tC/ha/yr | 60 tC/ha | 25 years | Ch. 4, Table 4.8 | | Rubber | 3.00 tC/ha/yr | 0.82 tC/ha/yr | 3.82 tC/ha/yr | 80.2 tC/ha | 27 years | Ch. 4, Table 4.8 | | Coconut | 0.70 tC/ha/yr | 0.19 tC/ha/yr | 0.89 tC/ha/yr | 18 tC/ha | 25 years | Default generic | | Coffee (unshaded) | 0.85 tC/ha/yr | 0.23 tC/ha/yr | 1.08 tC/ha/yr | 17 tC/ha | 20 years | Field data synthesis | | Cacao (unshaded) | 0.90 tC/ha/yr | 0.25 tC/ha/yr | 1.15 tC/ha/yr | 18 tC/ha | 20 years | Field data synthesis | | Tea | 0.70 tC/ha/yr | 0.19 tC/ha/yr | 0.89 tC/ha/yr | 14 tC/ha | 20 years | Ch. 4, Table 4.8 | ------------------------------------------------------------------------ ::: callout-important ## Mixed Versus Monoculture Shaded coffee and cacao in a multistrata system (3.25 tC/ha/yr) accumulate 3.6 times the carbon of unshaded monocultures (\~0.9 tC/ha/yr), which is a strong economic case for agroforestry in suitable climates. ::: ------------------------------------------------------------------------ ### Post-Clearance Stock Retention When forest is converted to perennial cropland, the IPCC gives Year 1 biomass retention values, the carbon left after clearing and before the crop reaches maturity, listed in Table 2.O. Table 2.O. First-Year Biomass Stock After Forest Conversion (*IPCC 2019, Vol. 4, Ch. 5, Table 5.9)* | Crop Type | Climate | Year-1 AGB (C~G~) | Source | |--------------------|------------------|------------------|------------------| | Perennial (generic) | Tropical Moist | 4.7 tC/ha | Default | | Perennial (generic) | Tropical Montane | 4.7 tC/ha | Default | | Oil Palm | Tropical | 2.4 tC/ha | Specific factor | | Rubber | Tropical | 3.0 tC/ha | Specific factor | | Coffee or Cacao (shaded) | Tropical | 3.25 tC/ha | Multistrata proxy | ------------------------------------------------------------------------ ::: callout-important ## One-Year Retention Limit The C~G~ value is the biomass present in Year 1 only. Later years accumulate at the growth rate G in Table 3.4 until the stock reaches its maximum at the end of the harvest cycle. ::: ------------------------------------------------------------------------ ### Forest Stock Regrowth Secondary forest regrowth depends on stand age, and young stands (≤20 years) accumulate biomass much faster than mature forest (*`cite`*). This matters to the aim of the chapter, which is to support project prioritization through the choice of emission factors. #### Americas Rainforest Table 2.P. Secondary Rainforest Growth Rates (Americas) (*IPCC 2019, Vol. 4, Ch. 4, Table 4.9*) | Age Class | Growth Rate (G) | Carbon Gain | Max Biomass | Strategic Application | |---------------|---------------|---------------|---------------|---------------| | ≤ 20 years | 5.9 t DM/ha/yr | 2.77 tC/ha/yr | 75.7 t DM/ha | Rapid regrowth phase; prioritize protection | | \> 20 years | 2.3 t DM/ha/yr | 1.08 tC/ha/yr | 206.4 t DM/ha | Mature phase; lower annual credits | Carbon (tC) is dry matter (t DM) × 0.47, and CO₂ equivalent is carbon × 3.67. The conversion for a young secondary forest in the Americas (≤20 yr) is ``` 2.77 tC/ha/yr × 3.67 = 10.2 tCO₂e/ha/yr ``` #### Asia Rainforest Table 2.Q. Secondary Rainforest Growth Rates (Asia) | Age Class | Growth Rate (G) | Carbon Gain | Max Biomass | |-------------|-----------------|---------------|---------------| | ≤ 20 years | 3.4 t DM/ha/yr | 1.60 tC/ha/yr | 45.6 t DM/ha | | \> 20 years | 2.0 t DM/ha/yr | 0.94 tC/ha/yr | 151.2 t DM/ha | #### Africa Rainforest Table 2.R. Secondary Rainforest Growth Rates (Africa) | Age Class | Growth Rate (G) | Carbon Gain | Max Biomass | |-------------|-----------------|---------------|---------------| | ≤ 20 years | 3.6 t DM/ha/yr | 1.69 tC/ha/yr | 56.8 t DM/ha | | \> 20 years | 2.4 t DM/ha/yr | 1.13 tC/ha/yr | 198.4 t DM/ha | #### Africa Moist Deciduous Table 2.S. Secondary Moist Deciduous Forest Growth (Africa) | Age Class | Growth Rate (G) | Carbon Gain | Max Biomass | |-------------|-----------------|---------------|---------------| | ≤ 20 years | 5.2 t DM/ha/yr | 2.44 tC/ha/yr | 55.7 t DM/ha | | \> 20 years | 2.1 t DM/ha/yr | 0.99 tC/ha/yr | 179.0 t DM/ha | #### Americas Dry Forest Table 2.T. Secondary Dry Forest Growth (Americas) | Age Class | Growth Rate (G) | Carbon Gain | Max Biomass | |-------------|-----------------|---------------|--------------| | ≤ 20 years | 3.9 t DM/ha/yr | 1.83 tC/ha/yr | 32.2 t DM/ha | | \> 20 years | 1.5 t DM/ha/yr | 0.70 tC/ha/yr | 72.8 t DM/ha | ------------------------------------------------------------------------ ::: callout-tip ## Age Classes Young secondary forests (≤20 years) grow two to three times faster than mature stands in every forest type, so protection or restoration projects aimed at 0-20 year regeneration generate the most credits per year (annual tonnes CO₂e/ha). Mature forests (\>20 years) hold larger carbon stocks and offer greater permanence. A portfolio that combines young regeneration, for high annual credits, with mature forest, for high stock and low leakage risk, is recommended. ::: ------------------------------------------------------------------------ ### Example A {.unnumbered} Example A restores 1,000 ha of severely degraded tropical moist pasture to improved silvopasture with manure inputs. Step 1 defines the baseline. The soil is a low activity clay (LAC) in a tropical moist climate with SOC~REF~ of 38 tC/ha (Table 2.7), severely degraded management (F~MG~ = 0.70), nominal inputs (F~I~ = 1.0) and biomass of 7.6 t DM/ha, the IPCC 2006 grassland default. The SOC at t=1 is ``` SOC_initial = SOC_REF × F_LU × F_MG × F_I SOC_initial = 38 × 1.0 × 0.70 × 1.0 SOC_initial = 26.6 tC/ha ``` Step 2 defines the project state, with improved tropical grassland management (F~MG~ = 1.17), high inputs with manure (F~I~ = 1.11) and silvopasture biomass accumulation (G = 3.07 tC/ha/yr AGB plus 0.84 tC/ha/yr BGB). The SOC at t=20 is ``` SOC_final = SOC_REF × F_LU × F_MG × F_I SOC_final = 38 × 1.0 × 1.17 × 1.11 SOC_final = 49.3 tC/ha ``` Step 3 calculates the annual SOC change. ``` ΔSOC = (SOC_final - SOC_initial) / 20 years ΔSOC = (49.3 - 26.6) / 20 ΔSOC = 1.14 tC/ha/yr ``` Step 4 calculates the biomass accumulation. ``` ΔBiomass (total) = G_AGB + G_BGB ΔBiomass = 3.07 + 0.84 ΔBiomass = 3.91 tC/ha/yr ``` Step 5 sums the total annual carbon benefit. ``` Total Gain = ΔSOC + ΔBiomass Total Gain = 1.14 + 3.91 Total Gain = 5.05 tC/ha/yr Convert to CO₂e: Total Gain = 5.05 × 3.67 = 18.5 tCO₂e/ha/yr ``` Step 6 scales the credits to the project over 20 years. ``` Total Credits (1,000 ha): Per hectare: 5.05 tC/ha/yr × 20 yr = 101 tC/ha Project total: 101 tC/ha × 1,000 ha = 101,000 tC In CO₂e: 101,000 × 3.67 = 370,670 tCO₂e Annual credits: 18,500 tCO₂e/yr ``` At \$15 per tCO₂e the revenue potential is \$277,500 per year for 20 years. ### Example B Example B converts 500 ha of tropical moist forest to no-till annual cropland with high organic inputs, an unavoidable conversion for food security. Step 1 sets the initial forest biomass and SOC. The soil is LAC (SOC~REF~ = 38 tC/ha), the biomass is 88 t DM/ha, the IPCC default for tropical moist secondary forest, and the root to shoot ratio is 0.207 (Table 4.4). The initial carbon stocks are ``` AGB: 88 × 0.47 = 41.4 tC/ha BGB: 41.4 × 0.207 = 8.6 tC/ha SOC: 38 × 1.0 × 1.0 × 1.0 = 38.0 tC/ha Total: 41.4 + 8.6 + 38.0 = 88.0 tC/ha ``` Step 2 sets the final cropland stocks, with F~LU~ = 0.83 (long-term cultivated), F~MG~ = 1.10 (no-till), F~I~ = 1.04 (high inputs, no manure) and Year 1 biomass C~G~ = 4.7 tC/ha (Table 3.5). The SOC after 20 years is ``` SOC_final = 38 × 0.83 × 1.10 × 1.04 SOC_final = 37.1 tC/ha Annual SOC change: ΔSOC = (37.1 - 38.0) / 20 = -0.05 tC/ha/yr ``` Step 3 accounts for the biomass loss. ``` Biomass lost in Year 1: AGB + BGB - C_G retained = (41.4 + 8.6) - 4.7 = 45.3 tC/ha Convert to CO₂e: 45.3 × 3.67 = 166 tCO₂e/ha (one-time loss) ``` Step 4 gives the total carbon impact. ``` Over 20 years: Biomass loss: -166 tCO₂e/ha (Year 1) SOC loss: -0.05 tC/ha/yr × 20 yr × 3.67 = -3.7 tCO₂e/ha Total loss: 166 + 3.7 = 169.7 tCO₂e/ha For 500 ha: 84,850 tCO₂e total Annual average: 4,243 tCO₂e/yr ``` ::: callout-important With full uncertainty reporting, conservation agriculture with no-till and high manure inputs very nearly cancels the SOC loss from forest conversion, leaving a decline of only about 0.18 tCO₂e/ha/yr across the inventory period. The biomass loss cannot be avoided, which shows the value of applying and documenting the fullest conservation practices where conversion is necessary, and of converting land that is already degraded rather than forest. ::: ### Example C {.unnumbered} Example C prevents the clearing of 2,000 ha of 10-year-old secondary rainforest in the Americas. Step 1 sets the baseline, what would happen without the project, and assumes conversion to severely degraded pasture. ``` Biomass loss: Accumulated after 10 yr: 5.9 t DM/ha/yr × 10 yr = 59 t DM/ha Carbon: 59 × 0.47 = 27.7 tC/ha (AGB) Roots: 27.7 × 0.221 = 6.1 tC/ha (BGB) Total biomass: 33.8 tC/ha SOC degradation (over 20 years): Initial: 38 × 1.0 × 1.0 × 1.0 = 38.0 tC/ha Final: 38 × 1.0 × 0.70 × 1.0 = 26.6 tC/ha Loss: (26.6 - 38.0) / 20 × 20 = 11.4 tC/ha Total baseline loss: 33.8 + 11.4 = 45.2 tC/ha In CO₂e: 45.2 × 3.67 = 166 tCO₂e/ha ``` Step 2 is the project case, in which the protected forest keeps growing for the next 10 years (years 11-20). ``` Additional biomass accumulation: AGB: 5.9 t DM/ha/yr × 10 yr × 0.47 = 27.7 tC/ha BGB: 27.7 × 0.221 = 6.1 tC/ha Total: 33.8 tC/ha SOC maintained (no change): 0 tC/ha Total project gain: 33.8 tC/ha In CO₂e: 33.8 × 3.67 = 124 tCO₂e/ha ``` Step 3 gives the net project benefit. ``` Avoided emissions: 166 tCO₂e/ha Additional sequestration: 124 tCO₂e/ha Total credits: 290 tCO₂e/ha over 10-year crediting period Annual average: 29 tCO₂e/ha/yr For 2,000 ha: Total credits: 580,000 tCO₂e over 10 years Annual: 58,000 tCO₂e/yr ``` At \$12 per tCO₂e the revenue potential is \$696,000 per year. Young secondary forests (≤20 years) can generate credits at an exceptional rate because the baseline threat of deforestation is high, the protected forest keeps growing at 5.9 t DM/ha/yr, and additionality is easy to demonstrate on marginal land that would otherwise be cleared. Areas regenerating over 20 years are therefore prime candidates for Tier 1 reporting. ------------------------------------------------------------------------ ## 2.4 Double-Counting Risks ### Double-Counting SOC Timelines {.unnumbered} The problem is that legacy emissions from historical land conversion overlap with credits for new management on the same land, and the rule is that each hectare reports in only one land category per reporting year. Three safeguards follow. 1. During the 20-year SOC transition period, all stock changes are attributed to the end-use land category, not the category of origin, so that each hectare sits in one category per year. 2. The conversion year of each hectare is recorded so that the remaining transition period can be calculated. 3. When a new management change occurs before the transition completes, the new factors apply only to the remaining years, as in the following example. ``` 2015: Forest → Cropland (begins 20-year SOC transition) 2020: Apply improved management to same cropland CORRECT approach: - Apply new factors only to remaining 15 years (2020-2035) - Calculate: (SOC_new_2035 - SOC_current_2020) / 15 years INCORRECT approach: - Claim new full 20-year transition from 2020 - This double-counts years 2020-2035 from original conversion ``` ::: callout-warning ## Critical Rule Only the non-CO₂ gases from biomass burning should be reported separately, because the CO₂ is already counted in the biomass stock change through the Tier 1 assumption of immediate oxidation for that transition type. ::: ### Tracking Site-Specific Timelines The problem is a claim of unlimited biomass accumulation in a system that is harvested periodically, and the rule is that agroforestry credits must account for the harvest cycle and the removal at harvest. The default harvest cycles (Table 3.2) are 20 years for tropical agroforestry, except fallow at 5 years, and 30 years for temperate agroforestry, and the biomass removed at harvest is accounted for as in the following example of a coffee multistrata system on a 20-year cycle. ``` Accumulation Phase (Years 1-20): Annual gain: 3.25 tC/ha/yr × 20 yr = 65 tC/ha accumulated Harvest (Year 20): Biomass removal: L_mean = L_max / 2 = 65 / 2 = 32.5 tC/ha Re-accumulation Phase (Years 21-40): Repeat accumulation: 3.25 tC/ha/yr × 20 yr = 65 tC/ha Net Over 40 Years: Total gain: 3.25 × 40 = 130 tC/ha Total removed: 32.5 × 2 = 65 tC/ha Net accumulation: 65 tC/ha Average annual: 1.63 tC/ha/yr ``` Tier 2 data may report longer rotations, for example from the farm records of 20-year coffee systems. ### Overlapping Activities The problem is several improvements on the same land, for example a tillage change with lime and manure. Two cases decide how the SOC change is reported. In Case A the impacts are separable because they affect different pools. ``` Activity 1: No-till (affects 0-30cm mineral SOC) → F_MG = 1.10 Activity 2: Liming (affects inorganic C pool) → Report under Tier 3 inorganic C Result: No double-counting; different carbon pools ``` In Case B the impacts overlap because they affect the same pool. ``` Activity 1: Switch to no-till → F_MG = 1.10 Activity 2: Add cover crops → F_I = 1.04 Activity 3: Add manure → F_I = 1.11 (instead of 1.04) Decision Options: Option 1 (if cumulative effect proven): F_MG × F_I = 1.10 × 1.11 = 1.22 Option 2 (conservative): Use only F_I = 1.11 (most dominant factor) Required: Document choice and scientific justification for VVB audit ``` ::: callout-tip ## General Principle Where it is uncertain whether effects are cumulative or saturating, the most conservative interpretation is applied and the reasoning is documented. ::: ## 2.5 Uncertainty Quantification ### Error Propagation {.unnumbered} For independent variables, the total uncertainty is the square root of the sum of the squared component uncertainties. $U_{\text{total}} = \sqrt{(U_1)^2 + (U_2)^2 + \dots + (U_n)^2}$ where U is the proportional uncertainty, so that plus or minus 11 per cent becomes 0.11. Table 2.U gives the typical range for each Tier 1 emission factor. Table 2.U. Typical Range in Uncertainty from Tier 1 Emission Factors | Parameter | Source of Uncertainty | Typical Range | Impact on Credits | |------------------|------------------|------------------|------------------| | SOC~REF~ | Climate and soil classification ambiguity; spatial heterogeneity | ±5-90% | High; drives the baseline calculation | | F~MG~ (Improved Grassland) | Management definition; intensity measurement | ±9-11% | Moderate; multiplicative factor | | F~I~ (High Input) | Quantification of organic matter additions | ±30% | Moderate; multiplicative factor | | G (Agroforestry) | System definition; site variability; climate | ±13-63% | High; direct rate parameter | | Biomass Stock | Remote sensing error; allometric equation selection | ±20-40% | High; one-time loss calculation | | Activity Data (Area) | Land use classification; GPS accuracy | ±5-15% | Scales all estimates | ### Worked Examples The project is 1,000 ha of improved silvopasture (F~MG~ = 1.17, F~I~ = 1.11, G = 3.07 tC/ha/yr), and its uncertainty components combine as follows. ``` SOC_REF (LAC, Tropical Moist): ±5% → 0.05 F_MG (Improved Tropical): ±9% → 0.09 F_I (High Input): ±30% → 0.30 G (Silvopasture AGB): ±63% → 0.63 Area measurement: ±10% → 0.10 U_total = √[(0.05)² + (0.09)² + (0.30)² + (0.63)² + (0.10)²] U_total = √[0.0025 + 0.0081 + 0.09 + 0.3969 + 0.01] U_total = √0.5075 = 0.712 → ±71% ``` The credit calculation with that uncertainty is ``` Point Estimate: 18.5 tCO₂e/ha/yr × 1,000 ha = 18,500 tCO₂e/yr Conservative Estimate (Lower Bound): 18,500 × (1 - 0.712) = 5,328 tCO₂e/yr Upper Bound: 18,500 × (1 + 0.712) = 31,672 tCO₂e/yr 95% Confidence Interval: 5,328 - 31,672 tCO₂e/yr ``` ## 2.6 Chapter Summary Six decision points were compiled for program proponents. 1. Verify the soil type first, and separate mineral from organic soils before selecting the accounting method, because this is the most basic decision. 2. Stratify correctly, matching climate zone, soil type and management class to the IPCC lookup tables, because wrong stratification invalidates the result. 3. Document the baseline thoroughly, because large SOC or biomass changes need strong evidence of a degraded initial condition to justify additionality. 4. Apply harvest cycles, because agroforestry credits must account for periodic biomass removal and indefinite accumulation is never claimed. 5. Apply safeguards against double counting through tracking over time, separation of pools and conservative treatment of overlapping activities. 6. Quantify uncertainty by calculating and reporting the propagated total, and consider a Tier 2 upgrade where Tier 1 uncertainty exceeds plus or minus 50 per cent. ART-TREES requires three items of uncertainty documentation. 1. The quantified uncertainty of each major parameter 2. The propagated total uncertainty of the final emission and removal estimates 3. Documented justification for a Tier 2 or Tier 3 upgrade in support of variance requests Table 2.V ranks the conversion activities by carbon benefit. Table 2.V. Emissions Factor Uncertainty Enhancements | Rank | Conversion Activity | Carbon Benefit | Key Considerations | |------------------|------------------|------------------|------------------| | 1 | Grassland Restoration (degraded to improved) | 67% SOC increase | Requires documented degradation baseline | | 2 | Silvoarable agroforestry establishment | 7.86 tC/ha/yr total gain | Needs strong silvicultural capacity | | 3 | Young secondary forest conservation | 2.77-5.9 tC/ha/yr + avoided loss | High additionality, rapid credits | | 4 | Multistrata coffee and cacao conversion | 4.05 tC/ha/yr + commodity income | Market-dependent feasibility | | 5 | Conservation agriculture adoption | 22% SOC retention vs. tillage | Cumulative with other practices |