Chapter 8: Settlements

CHAPTER 8

SETTLEMENTS

2006 IPCC Guidelines for National Greenhouse Gas Inventories

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Volume 4: Agriculture, Forestry and Other Land Use

Authors
Jennifer C. Jenkins (USA), Hector Daniel Ginzo (Argentina), Stephen M. Ogle (USA), and Louis V. Verchot(ICRAF/USA)
Mariko Handa (Japan) and Atsushi Tsunekawa (Japan)

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Chapter 8: Settlements

Contents
8

Settlements
8.1

Introduction ...........................................................................................................................................8.5

8.2

Settlements Remaining Settlements ......................................................................................................8.6

8.2.1
8.2.1.1

Choice of method.....................................................................................................................8.6

8.2.1.2

Choice of emission/removal factors.........................................................................................8.8

8.2.1.3

Choice of activity data ...........................................................................................................8.10

8.2.1.4

Uncertainty assessment..........................................................................................................8.12

8.2.2

Choice of method...................................................................................................................8.12

8.2.2.2

Choice of emission/removal factors.......................................................................................8.13

8.2.2.3

Choice of activity data ...........................................................................................................8.13

8.2.2.4

Uncertainty assessment..........................................................................................................8.14
Soil carbon...................................................................................................................................8.14

8.2.3.1

Choice of method...................................................................................................................8.15

8.2.3.2

Choice of stock change and emission factors ........................................................................8.15

8.2.3.3

Choice of activity data ...........................................................................................................8.16

8.2.3.4

Uncertainty assessment..........................................................................................................8.17

Land Converted to Settlements ...........................................................................................................8.17

8.3.1

Biomass .......................................................................................................................................8.18

8.3.1.1

Choice of method...................................................................................................................8.18

8.3.1.2

Choice of emission/removal factors.......................................................................................8.18

8.3.1.3

Choice of activity data ...........................................................................................................8.19

8.3.1.4

Uncertainty assessment..........................................................................................................8.20

8.3.2

Dead organic matter ....................................................................................................................8.20

8.3.2.1

Choice of method...................................................................................................................8.20

8.3.2.2

Choice of emission/removal factors.......................................................................................8.21

8.3.2.3

Choice of activity data ...........................................................................................................8.21

8.3.2.4

Uncertainty assessment..........................................................................................................8.23

8.3.3

8.4

Dead organic matter ....................................................................................................................8.12

8.2.2.1

8.2.3

8.3

Biomass .........................................................................................................................................8.6

Soil carbon...................................................................................................................................8.23

8.3.3.1

Choice of method...................................................................................................................8.23

8.3.3.2

Choice of stock change and emission factor..........................................................................8.24

8.3.3.3

Choice of activity data ...........................................................................................................8.25

8.3.3.4

Uncertainty assessment..........................................................................................................8.25

Completeness, Time series, QA/QC, and Reporting ...........................................................................8.25

8.4.1

Completeness ..............................................................................................................................8.25

8.4.2

Developing a consistent time series.............................................................................................8.26

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8.4.3

Inventory Quality Assurance/Quality Control.............................................................................8.26

8.4.4

Reporting and Documentation.....................................................................................................8.26

8.5

Basis for future methodological development.....................................................................................8.27

References...............................................................................................................................................8.28

Equations
Equation 8.1

Annual carbon change in live biomass pools in Settlements Remaining Settlements ...........8.6

Equation 8.2

Annual biomass increment based on total crown cover area .................................................8.7

Equation 8.3

Annual biomass growth based on number of individual woody plants in broad classes .......8.7

Tables

8.4

Table 8.1

Tier 2a default crown cover area-based growth rates (CRW) for urban
tree crown cover by region ...................................................................................................8.9

Table 8.2

Tier 2b default average annual carbon accumulation per tree in urban
trees by species classes ........................................................................................................8.10

Table 8.3

Default activity data by potential natural vegetation (PNV) type for percent tree cover.....8.11

Table 8.4

Default biomass carbon stocks removed due to land conversion to settlements .................8.19

2006 IPCC Guidelines for National Greenhouse Gas Inventories

Chapter 8: Settlements

8 SETTLEMENTS
8.1

INTRODUCTION

This Chapter provides methods for estimating carbon stock changes and greenhouse gas emissions and removals
associated with changes in biomass, dead organic matter (DOM), and soil carbon on lands classified as
settlements. Settlements are defined in Chapter 3 as including all developed land -- i.e., residential,
transportation, commercial, and production (commercial, manufacturing) infrastructure of any size, unless it isalready included under other land-use categories. The land-use category Settlements includes soils, herbaceousperennial vegetation such as turf grass and garden plants, trees in rural settlements, homestead gardens and urban
areas. Examples of settlements include land along streets, in residential (rural and urban) and commercial lawns,
in public and private gardens, in golf courses and athletic fields, and in parks, provided such land is functionallyor administratively associated with particular cities, villages or other settlement types and is not accounted for inanother land-use category. See Chapter 3 for area reporting guidelines and for definitions of the six land-use
categories.
Roughly 2% of Earth’s terrestrial surface is covered by urban areas which are home to over 3 billion people.
Over half of the world population currently lives in cities; this number is projected to double within 50 years(Crane and Kinzig, 2005). In many regions, land classified as urban, based on population density or cityboundaries, is just a subset of land that can be classified as settlements using the criteria described above. These
areas of less-dense settlement may extend well beyond the officially-defined border of a city, and in many
regions their areas are expanding quickly (Elvidge et al., 2004; Gallo et al., 2004; Theobald, 2004). In areas thatare primarily rural, even if land uses are not changing quickly, land devoted to residential uses can occupy asignificant portion of the landscape. Transitions of Forest Land, Cropland, and Grassland to Settlements canhave important impacts on carbon stocks and fluxes (Imhoff et al., 2000; Milesi et al., 2003).
Vegetation management in settlements may result in gains, losses, or transfers of carbon amongst the relevant
pools. For example, branches removed during pruning or turfgrass clippings (biomass losses) may be left on site(transfer to litter), disposed of as solid waste (transfer to waste), or burned (emitted). Emissions of the relevant
greenhouse gases are accounted for in the appropriate sections of the present guidance. For example, Table 2.3 in
Chapter 2, Volume 5 (Waste), includes wood/ yard waste in national-scale statistics describing the fate ofmunicipal solid waste at the national scale. Biomass removed as fuelwood from trees in settlements and used asfuel is accounted for in the Energy Sector. The net effect of conversion or management leading to increment, on
the one hand, or to loss (such as from burning and decay), on the other, determines the overall C balance insettlements.
Soils and DOM in Settlements Remaining Settlements or in Land Converted to Settlements may be sources orsinks of CO2, depending on previous land use, topsoil burial or removal during development, current
management, particularly with respect to nutrient and water applications, and the type and amount of vegetation
cover interspersed among roads, buildings and associated infrastructure (Goldman et al., 1995; Jo, 2002; Pouyat
et al., 2002; Qian and Follett, 2002; Kaye et al., 2004; Kaye et al., 2005).
The 1996 IPCC Guidelines covered above-ground biomass in trees in rural settlements, but not other settlement
categories and pools.
The 2006 IPCC Guidelines differ from those in the GPG-LULUCF as follows:•

The discussion and detailed methodologies have been moved from the Appendix to the main text andconsidered as greenhouse gas emission source or removal sector;•

The discussion and methodologies have been expanded to include the five biomass pools described in
Chapter 1;•

Tier 1 default methodologies are presented;•

Additional data appropriate for Tiers 2 and 3 have been published since the GPG-LULUCF and are included
here; and•An expanded discussion on developing and applying country-specific Tier 2 and Tier 3 methodologies andvalues is included, including methods to work with more detailed activity data.

The carbon pools estimated for Settlements are above-ground and below-ground biomass, DOM, and soils.
Sections 8.2 and 8.3 respectively describe methodology to estimate changes in carbon stocks for Settlements
Remaining Settlements, and to estimate carbon stocks on Land Converted to Settlements. The methodology inthe second section is broadly applicable to Land Converted to Settlements from any other type of land.

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8.2

SETTLEMENTS REMAINING SETTLEMENTS

This category refers to all classes of urban formations that have been in use as settlements (e.g., areas that arefunctionally or administratively associated with public or private land in cities, villages, or other settlement
types), since the last time data were collected. Emissions and removals of CO2 in this category are estimated by
the subcategories of changes in carbon stocks in biomass (both woody and perennial non-woody components), in
DOM, and in soils, as summarized in Equation 2.3 in Chapter 2.
The biomass pool in settlements has woody and herbaceous components. For woody biomass, carbon stockchange is calculated as the difference between biomass increment and biomass loss due to management activities.
For herbaceous biomass (such as turfgrass or garden plants) in Settlements Remaining Settlements, the carbon
stock change in biomass can usually be assumed to be zero.
The DOM pool in settlements contains dead wood and litter from both woody and herbaceous components. For
the woody vegetation, changes in this pool can be quantified as production of coarse and fine litter from woody
plants. For herbaceous vegetation, annual production of DOM is estimated as the accumulation of thatch plus
production of herbaceous material such as garden waste and yard trimmings. Greenhouse gas emissions
associated with Waste Sector are estimated in Volume 5 (Waste) and therefore the methods in this Chapter
describe only those components of annual production that can reasonably be expected to stay on-site.
Soil C pools vary with time depending on the balance between C inputs from plant litter and other forms oforganic matter and C outputs resulting from decomposition, erosion and leaching. Estimating the impact ofsettlement management on soil C storage will be particularly important in countries with a large portion of landin cities and towns, or high rates of settlement expansion. For mineral soils, the impact of settlement land use
and management on soil C stocks can be estimated based on differences in storage among settlement coverclasses relative to a reference condition, such as native lands. Although organic soils are less commonly used forsettlements, C is emitted from these soils if they are drained for development due to enhanced decomposition,
similar to the effect of drainage for agricultural purposes (Armentano, 1986). In addition, peat may be harvested
from organic soils during settlement development, which will also generate emissions to the atmosphere.

8.2.1
8.2.1.1

BiomassC HOICE OF METHOD

The general method for biomass carbon stock change in Settlements Remaining Settlements follows the approachin Equation 2.7 in Chapter 2. This method estimates changes in biomass carbon stocks, accounting for gains incarbon stocks in biomass as a result of growth minus losses in carbon stocks as a result of pruning and mortality.
Depending on the relative magnitudes of the increment and loss terms, the average annual changes in biomass
carbon stocks in settlements may be positive or negative.
Biomass change in Settlements Remaining Settlements is the sum of biomass change in three components: trees,
shrubs, and herbaceous perennials (e.g., turfgrass and garden plants), as described in Equation 8.1.
EQUATION 8.1
ANNUAL CARBON CHANGE IN LIVE BIOMASS POOLS IN SETTLEMENTS REMAINING SETTLEMENTS
ΔC B = ΔCTrees + ΔC Shrubs + ΔC Herbs
Where:
ΔCB = annual carbon accumulation attributed to biomass increment in Settlements Remaining Settlements,
tonnes C yr-1
ΔCTrees = annual carbon accumulation attributed to biomass increment in trees in Settlements Remaining
Settlements, tonnes C yr-1
ΔCShrubs = annual carbon accumulation attributed to biomass increment in shrubs in Settlements
Remaining Settlements, tonnes C yr-1
ΔCHerbs = annual carbon accumulation attributed to biomass increment in herbaceous biomass inSettlements Remaining Settlements, tonnes C yr-1
Depending on the availability of relevant activity data and appropriate emission factors, any of themethodological tiers described below can be used. Figure 2.2 in Chapter 2 also provides guidance for theidentification of the appropriate tier to estimate changes in carbon in biomass.

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Chapter 8: Settlements

Tier 1
Tier 1 assumes no change in carbon stocks in live biomass in Settlements Remaining Settlements, in other words,
that the growth and loss terms balance. If the category Settlements Remaining Settlements is determined to be a
key category, then a country should collect appropriate activity data and/or develop emission factors appropriate
to the region and adopt Tier 2 or 3.
Tier 2
There are two options for Tier 2 estimation of changes in biomass in Settlements Remaining Settlements. Tier 2auses changes in carbon stocks per unit of plant crown cover area as a removal factor, and Tier 2b uses changes incarbon stocks per number of plants as a removal factor. The choice of method will depend on availability ofactivity data. Tier 2a and Tier 2b both provide methods for estimating ΔCG in Equation 2.7 (Gain-Loss Method).
This is appropriate for countries lacking a continuous inventory in Settlements Remaining Settlements.
The main perennial types are trees, shrubs, and herbaceous perennials (such as turfgrass and garden plants). The
methods as presented here set the change in biomass of herbaceous annuals to zero in Settlements Remaining
Settlements on the basis that growth of herbaceous biomass (whether perennial or annual herbaceous vegetation)is equal to loss from harvest or mortality. Countries may choose to define tree and woody perennial types asappropriate and each types may be further divided into classes defined according to species, climate zone,
seasonality, or other criteria as appropriate and if data are available.
Tie r 2a : C ro wn cov e r a rea m ethod
This method is represented by Equation 8.2 and should be used when data are available on total area of crowncover in perennial types (j) and their classes (i) in Settlements Remaining Settlements.
EQUATION 8.2
ANNUAL BIOMASS INCREMENT BASED ON TOTAL CROWN COVER AREA
ΔCG = ∑ ATi , j • CRWi , j
i, j

Where:ΔCG = annual carbon accumulation attributed to biomass increment in Settlements Remaining Settlements,
tonnes C yr-1
ATij = total crown cover area of class i in woody perennial1 type j, ha
CRWij = crown cover area-based growth rate of class i in woody perennial type j, tonnes C (ha crowncover)-1 yr-1
Tie r 2 b: Ind iv idua l p lan t 2 gro wth met hod
The method is represented by Equation 8.3 and should be used where data on the number of woody plants bybroad species class in Settlements Remaining Settlements are available. It is possible, when making estimates fortrees, to convert between the methods used in Tiers 2a and 2b by assuming that an individual tree in an urban
area covers approximately 50 m2 crown area when mature (cf. Akbari, 2002).
EQUATION 8.3
ANNUAL BIOMASS GROWTH BASED ON NUMBER OF INDIVIDUAL WOODY PLANTS IN BROAD
CLASSESΔCG = ∑ NTi , j • Ci , j
i, j

Where:ΔCG = annual carbon accumulation due to live biomass increment in Settlements Remaining Settlements,
tonnes C yr-1
NTij = number of individuals of class i in perennial type j
Cij = annual average carbon accumulation per class i of perennial type j, tonnes C yr-1 per individual

1

References to woody perennials include trees unless otherwise specified.

2

References to plants include trees unless otherwise specified.

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Tier 3Tier 3 approaches can be based either on Tier 2 methods above (Equations 8.2 and 8.3) with more detailed
measurements of parameters at disaggregated level for different settlement systems such as parks, rural or urban
residential areas, avenues, etc., or on a stock difference approach based on Equation 2.8. Changes in carbon
stocks are estimated at two points in time, where the changes account for biomass carbon gains and losses. The
generic approach for this method calls for forest-specific biomass expansion factors (BEFs) which do not apply
to settlements. Countries wishing to use the stock difference method to estimate biomass change in Settlements
Remaining Settlements should consider using allometric methods such as those based on individual tree diameterat breast height (dbh) (Jenkins et al., 2004), adjusted for open-grown trees as described above, rather than forest
specific BEFs for estimating tree biomass.

8.2.1.2

C HOICE OF EMISSION / REMOVAL FACTORS

Few allometric biomass equations exist specifically for trees or shrubs in urban settings (Nowak, 1996; Jo, 2002)
so investigators have tended to apply equations derived for forest trees, adjusting the resulting biomass with acoefficient (such as 0.80 [Nowak, 1994; Nowak and Crane, 2002]) intended to take account of the allometry of
open-grown trees in cities where above-ground biomass for a given diameter is typically lower than that offorest-grown trees (Nowak, 1996). Allometric equations for some shrub species exist, but have not routinely
been applied to urban settings (Smith and Brand, 1983; Nowak et al., 2002 for shrub leaf biomass estimates).
Below-ground tree biomass can be derived from above-ground biomass by multiplying the latter by an estimatedroot: shoot ratio, as described by Cairns et al. (1997) and applied for urban settings by Nowak et al. (2002). See
Chapter 4 (Forest Land) for examples of root: shoot ratios (R) (also called below-ground to above-groundbiomass ratio) often used in forest settings. Ratios appropriate to the region of interest can be assumed to apply
without modification to settlements.
Tree growth and mortality in settlements can be affected by urban conditions such as variations in local air
quality, atmospheric deposition, enhanced atmospheric CO2 concentrations, and reduced air exchange in the rootzone due to impermeable paving surfaces (e.g., Pouyat et al., 1995; Idso et al., 1998; Idso et al., 2001; Gregg etal., 2003; Pouyat and Carreiro, 2003). Therefore, the values and equations used to predict tree growth insettlements at higher tiers should, to the extent feasible, allow for the surrounding environment and the conditionof the trees.
Carbon stored in the woody components of trees makes up the largest compartment of standing biomass stocks
and annual biomass increment in settlements. Data are still sparse, though availability is increasing. For example,
Nowak and Crane (2002) estimated on a citywide basis that the net annual carbon storage by trees in cities in theconterminous USA ranged from 600 to 32,200 tonnes C yr-1. Jo (2002) found that the amount of C sequesteredannually in three Korean cities varied from 2,900 to 40,300 tonnes. In Australia, Brack (2002) estimated that theamount of C sequestered by trees in Canberra between 2008 and 2012 would be 6,000 tonnes C yr-1. Clearly, theestimates depend on the definition and hence extent of the settlement areas being considered.
The variation is less per unit land area; for ten cities in the United States, measurements of C stored in woody
biomass ranged from 150 to 940 kg C ha-1 yr-1 (Nowak and Crane, 2002) and for three Korean cities annual C
stored in woody biomass varied from 530 to 800 kg C ha-1 yr-1 (Jo, 2002). Trees in urban lawns in Colorado(USA) stored 1,590 kg C ha-1 yr-1 (Kaye et al., 2005). There is still less variation in estimates of annual C
storage per unit of tree crown cover. Nowak and Crane (2002) found that annual sequestration rates ranged from
0.12 to 0.26 kg C m-2 crown cover yr-1, while Brack (2002) used a model to estimate that annual sequestration in
Canberra between 2008 and 2012 would be 0.27 kg C m-2 yr-1.
Tier 1This method assumes, probably conservatively, that changes in biomass carbon stocks due to growth in biomass
are fully offset by decreases in carbon stocks due to removals (i.e., by harvest, pruning, clipping) from bothliving and from dead biomass (e.g., fuelwood, broken branches, etc.). Therefore, in a Tier 1 approach ΔCG = ΔCL
and for all plant components, and ΔCB = 0 in Equation 2.7.

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Chapter 8: Settlements

Tier 2Trees
Tier 2 calls for parameter values for CRWij (Equation 8.2) and Cij (Equation 8.3). A default removal factor fortree biomass (CRW) of 2.9 tonnes C (ha crown cover)-1 yr -1 is usually suitable for Tier 2a (see Table 8.1). Thisestimate is based on a sample of ten US cities, with values that ranged from 1.8 to 3.4 tonnes C (ha crown cover)1
yr-1 (Nowak and Crane, 2002). Values appropriate to national circumstances can also be developed. Using Tier
2b, the removal factor is Cij. Table 8.2 provides defaults carbon accumulation rates for tree species classes foruse at Tier 2b. These estimates are based on various allometric equations and limited field data from urban areasin the USA, and are averages for trees of all sizes (not just mature trees). Tiers 2a and 2b methods provide
biomass estimates for total combined above-ground and below-ground woody biomass. If required belowground biomass can be estimated separately using a root: shoot ratio of 0.26 (Nowak et al., 2002).
For Tiers 2a and 2b, the default assumption for ΔCL where the average age of the tree population is less than orequal to 20 years is zero. This is based on the assumption that urban trees are net sinks for carbon when they are
actively growing and that the active growing period (AGP) is roughly 20 years, depending on tree species,
planting density, and location. Thereafter, the method assumes that the accumulation of carbon in biomass slows
with age, and thus for trees older than the AGP, increases in biomass carbon are assumed to be offset by losses
from pruning and mortality. For trees older than the AGP this is conservatively accounted for by setting ΔCGwood= ΔCLwood. Countries can define AGP depending on their circumstances.

Other woody perennial types
Countries may, for any perennial type, develop their own values for CRWij (in Equation 8.2) and Cij (in Equation
8.3). A conservative assumption of no change in any of these components (i.e., CRWij = 0 and Cij = 0) can also
be applied.
Tiers 2a and 2b both assume no change in herbaceous biomass. Using this method, ΔCGHerbs = ΔCLHerbs and ΔCB isbased on the difference between increment and losses in woody biomass only.
Tier 3
For Tier 3, countries should develop plant type-specific biomass increment factors appropriate to national
circumstances. Country-specific parameters and growth equations should be based on the dominant climate
zones and particular species composition of the major settlements areas in a country, before making estimates forless extensive settlements. If country-specific biomass increment parameters are developed from estimates ofbiomass on a dry matter basis, they need conversion to units of carbon using either a default carbon fraction (CF)of 0.5 tonne C (tonne d.m.)-1, or a carbon fraction that is more appropriate to circumstances.
Under higher tiers, the assumptions for ΔCL should be evaluated and modified to address national circumstances
better. For instance, countries may have information on age-dependent and/ or species-specific carbon losses insettlement trees. In this case, countries should develop a loss term and document the resources and rationale
used in its development.
If a country adopts the stock-difference method (Equation 2.8), it should have representative sampling andperiodic measurement system to estimate the changes in biomass carbon stocks.

TABLE 8.1
TIER 2A DEFAULT CROWN COVER AREA-BASED GROWTH RATES (CRW) FOR URBAN TREE CROWN COVER BY REGION
RegionDefault annual carbon accumulation per ha tree crown cover[tonnes C (ha crown cover)-1 yr-1]

United States (global default)

2.9 a

Australia

3.6 b

a

Nowak and Crane 2002; average of 10 US cities.

b

Brack 2002; modelling analysis in Canberra.

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TABLE 8.2
TIER 2B DEFAULT AVERAGE ANNUAL CARBON ACCUMULATION PER TREE
IN URBAN TREES BY SPECIES CLASSES

Broad species classDefault annual carbon accumulation per tree
(tonnes C yr-1)

Aspen

0.0096

Soft maple

0.0118Mixed hardwood

0.0100Hardwood maple

0.0142Juniper

0.0033

Cedar/larch

0.0072

Douglas fir

0.0122

True fir/Hemlock

0.0104Pine

0.0087

Spruce0.0092

Source: D. Nowak (2002; personal communication)

8.2.1.3

C HOICE OF ACTIVITY DATA

Tier 1
No activity data are needed.
Tier 2
The activity data needed to implement a Tier 2 method are either ATij, area of crown cover for each class withina perennial type (Equation 8.2), or NTij, number of individual plants in each class within a perennial type
(Equation 8.3). Crown cover is defined as the percent of ground covered by a vertical projection of theoutermost perimeter of the natural spread of the foliage. For Tier 2a, crown cover area data (ATij) can beobtained from aerial photographs of urban areas, provided expertise in photo interpretation, image sampling andarea measurement (Nowak et al., 1996) are available. Values in percent crown cover should be converted to totalcrown cover area for use in Equation 8.2 by multiplying the percent crown cover by the total area of the plants(trees or shrubs) within the outermost perimeter.
If data are not available to determine percent crown cover, then default activity data can be used. This approachtakes advantage of the fact that settlements found in different biomes, as defined by different potential naturalvegetation or PNV (Kuchler, 1969), have been found to have similar values for percent tree cover, total
greenspace, and canopy greenspace (Nowak et al., 1996) (Table 8.3). Settlements found in regions where the
PNV is forest, for example, have substantially higher percent tree cover values than do settlements found inregions where the PNV is desert (Table 8.3). In Table 8.3, percent total greenspace is the proportion of land area
covered by vegetation or soil (i.e., not impervious surfaces or water), and canopy greenspace is the proportion ofthat greenspace filled with tree canopies (calculated as percent canopy cover/ percent total greenspace). The
default data on percent tree crown cover should be multiplied by the settlement area and used with the default
growth rates in Table 8.1, in a simplified version of Equation 8.2, to estimate the annual carbon accumulation in
the tree perennial type. Data on percent total greenspace and percent canopy greenspace in Table 8.3 are notneeded for a Tier 2 approach to estimate biomass carbon stocks, but may be useful for cross-checking.
For Tier 2b, records of plant populations, disaggregated into species or broad species classes, may be obtained
from municipal agencies caring for urban vegetation, or from sampling methods.
Tier 3
Under Tier 3, the type of activity data to be collected depends on the methodological approaches used. If thestock-difference method is used, then it is necessary to disaggregate and estimate area under different types ofvegetation types (parks, rural or urban settlements, avenues, playgrounds, etc) using remote sensing techniques
in different climate or economic development indicators. The higher the tier to be used, the more disaggregatedwill be the activity data, and the more precise the estimation methods. The area sampling methods described in
Chapter 3, Annex 3A.3 can be used for this.

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Chapter 8: Settlements

TABLE 8.3
DEFAULT ACTIVITY DATA BY POTENTIAL NATURAL VEGETATION (PNV) TYPE (KUCHLER, 1969) FOR PERCENT TREE
COVER

Percent tree cover(+ S.E.)

Percent total greenspace(+ S.E.)

Percent canopy
greenspace(+ S.E.)

Forest31.1 (+ 2.6)

58.4 (+ 2.9)

50.9 (+ 3.3)

Grassland

18.9 (+ 1.5)

54.8 (+ 2.1)

32.9 (+ 2.3)

Desert9.9 (+ 2.4)

64.8 (+ 4.2)

16.9 (+ 4.6)

Potential Natural
Vegetation (PNV)

Source: Nowak et al. (1996)

STEP-BY-STEP SUMMARY OF METHOD FOR ESTIMATING CHANGES IN
BIOMASS STOCKS
Tier 1The Tier 1 methodology assumes no change in biomass carbon stocks in Settlements Remaining Settlements.
Tier 2
Method A: Crown cover area method
Step 1: Define the total crown cover area in each of the woody perennial types in the settlement. If data are notavailable for all types, the method may be applied for trees only, setting the area in other perennial types to zero.
Default activity data for tree cover can be applied using Table 8.3. To estimate total tree crown cover for asettlement falling in a region where the PNV is grassland, for example, multiply the total land area in thesettlement by the 18.9%, which is the average percent tree cover for settlements found in areas where the PNV is
grassland, from Table 8.3. The total crown cover area of all vegetation (including trees) is calculated as (total
greenspace area = percent greenspace x settlement area) and the aggregated crown cover of the other perennial
vegetation types is the difference between the total greenspace area and the tree crown cover area.
Step 2: Calculate ΔCG for each of the perennial types, using Equation 8.2. The tree crown cover area value
obtained in Step 1 should be used for the tree perennial type. Countries may apply a default value of CRW fortrees from Table 8.1; should develop and apply their own values for CRWij. Default values are available only
for CRW for the tree component of vegetation. If CRW values for other perennial types do not exist and cannot
be developed, or if activity data for these types do not exist these parameters may be set to zero, and the treecomponent of biomass growth only be estimated.
Step 3: Calculate ΔCL for plant components, to be used in Equation 2.7 in Chapter 2. For the tree component ofvegetation, it is good practice to set this value equal to zero where the average age of the tree population is lessthan or equal to the active growing period (AGP; see Section 8.2.1.2). If the average age of trees is greater thanthe AGP, then either assume ΔCG = ΔCL or use situation-specific data. In the absence of data to the contrary,
assume that ΔCG = ΔCL for shrubs and herbaceous plants.
Step 4: Use the values obtained for ΔCG and ΔCL in Equation 2.7 in Chapter 2 to quantify the total change inbiomass carbon in Settlements Remaining Settlements.
Method B: Individual plant growth method
Step 1: Estimate the number of plants in Settlements Remaining Settlements for each perennial type (e.g., trees,
shrubs, and herbaceous plants). If data are not available for all of the perennial types, a minimum approach is touse data for trees only, setting the number of plants in other perennial types to zero. There are no default activity
data for this method.
Step 2: Using Equation 8.3, multiply each estimate by the appropriate rate of carbon increment per plant (Cij,)to obtain the amount of carbon sequestered annually. Default Cij values for trees can be found in Table 8.2; there
are no default values for shrubs or herbaceous species. Countries may choose to apply their own values if
appropriate, or set the missing values to zero and produce estimates for trees only.
Step 3: As in Equation 8.2, sum the amount of carbon sequestered, ΔCG, by each perennial type over all classes
present in Settlements Remaining Settlements.
Step 4: Use the estimate of ΔCG in Equation 2.7 in Chapter 2 to estimate the annual change in carbon stock inbiomass. For trees, set ΔCL = 0 if the average age of the tree population is less than or equal to the active
growing period (AGP); if average age of trees is greater than the AGP (Section 8.2.1.2), then either assume
ΔCG = ΔCL or use situation-specific data.

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Tier 3
A Tier 3 approach requires more detailed information than the Tier 2 approach, such as:•accounting for different land uses within settlements (residential, recreational, industrial, etc.);•

detailed estimates and models for growth and longevity of the most important plant species;•

fate of pruned and dead wood and other biomass transferred to the DOM pool; and•other items as appropriate for national circumstances.

8.2.1.4

U NCERTAINTY ASSESSMENT

Tier 1
Assessment of uncertainty is not required, because the change in living biomass is set to zero.
Tier 2 and Tier 3
The overall uncertainty of any estimate of the change in the carbon stock of living biomass will be a combinationof the individual uncertainties of its component terms. These will be influenced by the heterogeneity between
and within land-use urban types, and also by the intensity and frequency of the stewardship of plants in bothpublic and private spaces. The uncertainty is likely to be high since there is limited experience in measuring
carbon stock change in urban and rural settlements. The few studies done on the CO2 sink capacity of cities
differ in methodology and scope, but the overall relative uncertainty of the estimate of changes in carbon stocks
is unlikely to be less than 30-50% about the mean.

8.2.2

Dead organic matter

Most of the changes in carbon stocks associated with dead organic matter (DOM) will be associated withchanges in tree cover in settlements. Methods are provided for two types of DOM pools: 1) dead wood and 2)
litter. Chapter 1of this volume provides detailed definitions of these pools.
Dead wood is a diverse pool with many practical problems for measuring in the field and associated uncertainties
about rates of transfer to litter, soil, or emissions to the atmosphere. Amounts of dead wood depend on the timeof last disturbance, the amount of input (mortality) at the time of the disturbance, natural mortality rates, decay
rates, and management.
Litter accumulation is a function of the annual amount of litterfall, which includes all leaves, twigs and small
branches, fruits, flowers, and bark, minus the annual rate of decomposition. The litter mass is influenced by thetime since the last disturbance, and the type of disturbance. Management such as wood and grass collection,
burning, and grazing dramatically alter litter properties, but there are few studies clearly documenting the effects.
In herbaceous perennial turfgrass communities, thatch accumulates in a thin layer at the soil surface. The depthof this layer depends on the balance between accumulation (grass production) and decomposition, which varies
substantially with climate and management regime. While the function of this layer has been recognized (Raturi
et al., 2004), there are so far no published data on the overall impact of carbon accumulation in this DOM poolon landscape-level. As a result, these Guidelines acknowledge the potential importance of thatch in the DOM in
settlements but assume that inputs equal outputs so that the net change in carbon stock is zero.
No studies have yet been published on the accumulation rate of dead wood in settlements, though some studies
have described the production of leaf litter in settlements (cf. Jo and McPherson, 1995). In the only measured
data on this component of carbon flux, Kaye et al. (2005) found that leaf and shrub litter in residential lawns inColorado (USA) totalled 49 g C m-2 yr-1, or roughly 13% of total above-ground productivity (383 g C m-2 yr-1).
Since the rate of soil respiration in settlements is typically quite high compared to native landscapes (Koernerand Klopatek, 2002; Kaye et al., 2005), it is likely that fine litterfall decays quickly. The conservative approach,therefore, is to set the accumulation rate of the litter component of DOM to zero.

8.2.2.1

C HOICE OF METHOD

Estimation of changes in carbon stocks in DOM requires an estimate of changes in stocks of dead wood andchanges in litter stocks (refer to Equation 2.17 of Chapter 2). Each of the DOM pools is treated separately, but
the method for determining changes in each pool is the same. The decision tree in Chapter 2, Figure 2.3 helps
select the appropriate tier.

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Chapter 8: Settlements

Tier 1
Tier 1 assumes that the dead wood and litter stocks are at equilibrium, and so there is no need to estimate thecarbon stock changes for these pools. Countries experiencing significant changes in tree cover in settlements areencouraged to develop national data to quantify this change and report it under Tier 2 or 3 methodologies.
Tiers 2 and 3
Tiers 2 and 3 allow for calculation of changes in dead wood and litter carbon due to changes in tree cover. Two
methods are suggested for estimating associated carbon stock changes.
Method 1 (Also called the Gain-Loss Method, Equation 2.18 in Chapter 2): This involves estimating the area ofsettlement categories and the average annual transfer into and out of dead wood and litter stocks. It requires anestimate of area under Settlements Remaining Settlements according to different climate or ecological zones orsettlement types, disturbance regime, management regime, or other factors significantly affecting dead wood andlitter carbon pools. It also requires the quantity of biomass transferred into dead wood and litter stocks as well as
the quantity of biomass transferred out of the dead wood and litter stocks on per hectare basis according todifferent settlement types.
Method 2 (Also called the Stock-Difference Method, Equation 2.19 in Chapter 2): This method involves
estimating the area of settlements and the dead wood and litter stocks at two periods of time, t1 and t2. The deadwood and litter stock changes for the inventory year are obtained by dividing the stock changes by the period(years) between two measurements. The Stock-Difference Method is feasible for countries, which have periodic
inventories in settlements. This method is more suitable for countries adopting Tier 3 methods. Tier 3 methods
are used where countries have country-specific emission factors, and substantial national data. Country-defined
methodology may be based on detailed inventories of permanent sample plots for their settlements and/or models.

8.2.2.2

C HOICE OF EMISSION / REMOVAL FACTORS

Carbon fraction: The carbon fraction of dead wood and litter is variable, particularly for litter, and depends on
the stage of decomposition. A value of 0.50 tonne C (tonne d.m.)-1 can be used as a default in both cases.
Tier 1
Emission factors are unnecessary.
Tier 2
It is good practice to use country-level data on DOM for different settlement categories, in combination withdefault values, if country or regional values are not available for some settlement categories. Country-specificvalues for the transfer of carbon from live trees and grasses that are harvested to harvest residues anddecomposition (in the case of the Gain-Loss Method), or the net change in DOM pools (in the case of the StockDifference Method), can be derived taking into account domestic expansion factors, settlement types, the rate ofbiomass utilization, mortality, management and harvesting practices, and the amount of damaged vegetation
during management and harvesting operations.
Tier 3
Countries should develop their own methodologies and parameters for estimating changes in DOM. Thesemethodologies may be derived from Methods 1 or 2 specified above, or may be based on other modelling or
sampling approaches (see sampling methods set out in Chapter 3, Annex 3A.3).

8.2.2.3

C HOICE OF ACTIVITY DATA

Activity data consist of areas of Settlements Remaining Settlements summarised by major settlement types. Total
settlement areas should be consistent with those reported under other sections of this chapter, notably under thebiomass section of Settlements Remaining Settlements. The assessment of changes in DOM will be greatly
facilitated if this information can be used in conjunction with national soils and climate data, vegetation
inventories, and other geophysical data.

Step-by-step summary of method for estimating changes in DOM carbon stocks
Tier 1
Tier 1 assumes DOM inputs and outputs are equal so there are no net annual changes in dead wood or litter
carbon stocks and no further assessment is needed.
Tier 2 or Tier 3 (M ethod 1, Ga in-Loss M ethod)
Each of the DOM pools (dead wood and litter) is to be treated separately, but the method for each pool is thesame.

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Step 1: Determine the categories to be used in this assessment and the representative area. The category
consists of definitions of the type of settlements. Area data should be obtained using the methods described in
Chapter 3.
Step 2: Identify values from inventories or scientific studies for the average inputs and outputs of dead wood or
litter for each category. No default factors exist for inputs and outputs from these pools, so countries should use
locally available data. Calculate the net change in the DOM pools by subtracting the outputs from the inputs.
Negative values indicate a net decrease in the stock (Equation 2.18).
Step 3: Determine the net change in DOM carbon stocks for each category. Multiply the change in DOM
stocks by the carbon fraction of the dead wood or litter to determine the net change in dead wood and litter
carbon stocks.
Step 4: Determine the total change in the DOM carbon pools for each category by multiplying therepresentative area of each category by the net change in DOM carbon stocks for that category.
Step 5: Determine the total change in carbon stocks in DOM by taking the sum of the total changes in DOM
across all categories.
Tier 2 or Tier 3 (M ethod 2, S t o c k - D if f e re n c e M et h o d )Each of the DOM pools is to be treated separately, but the method for each pool is the same.
Step 1: Determine the settlement categories and area as described in Step 1 above.
Step 2: From the inventory data, identify the inventory time interval, the average stock of DOM at the initial
inventory (t1), and the average stock of DOM at the final inventory (t2). Use these figures to calculate the net
annual change in DOM stocks by subtracting the DOM stock at t1 from the DOM stock at t2 and dividing thisdifference by the time interval. A negative value indicates a decrease in the DOM stock (Equation 2.19).
Step 3: Determine the net change in DOM carbon stocks for each category. Determine the net change in DOM
carbon stocks by multiplying the net change in DOM stocks for each category by the carbon fraction of the
DOM.
Step 4: Determine the total change in the DOM carbon pool for each activity category by multiplying therepresentative area of each activity category by the net change in DOM carbon stocks for that category.
Step 5: Determine the total change in carbon stocks in DOM by taking the sum of the total changes in DOM
across all activity categories.

8.2.2.4

U NCERTAINTY ASSESSMENT

There is no need to estimate uncertainty under Tier 1, since DOM pools are assumed to be stable. For Tiers 2 and3 estimates, sources of uncertainty include the degree of accuracy in land area estimates, carbon increment andloss, carbon stocks, and expansion factor terms. Area data and estimates of uncertainty should be obtained using
the methods in Chapter 3 which provides default uncertainties associated with the different approaches.
Uncertainties associated with carbon stocks and other parameter values are likely to be at least a factor of threeunless country-specific data are available from well designed surveys.

8.2.3

Soil carbon

Soils in settlements may be sources or sinks of CO2 depending on previous land use, soil burial or collection
during development, and current management, particularly with respect to nutrient and water applications inaddition to the type and amount of vegetation cover interspersed among roads, buildings and associatedinfrastructure (Goldman et al., 1995; Pouyat et al., 2002; Jo, 2002; Qian and Follett, 2002; Kaye et al., 2004).
Only a few studies have been conducted at the time of writing that evaluate the effect of settlement management
on soil C, and most of the focus has been on North America (e.g., Pouyat et al., 2002), making it difficult togeneralize. For example, there are likely to be large differences that have not been well studied between
settlements in developed countries and developing countries.
Estimating the impact of settlement management on soil C storage will be particularly important in countries
with a large portion of land in cities and towns, or high rates of settlement expansion. For mineral soils, theimpact of settlement land use and management on soil C stocks can be estimated based on differences in storage
among settlement management classes relative to a reference condition, such as other managed land uses, or
native lands. Settlement management classes could include turf grass (e.g., lawns and golf courses), urban
woodlands, gardens, refuse areas (e.g., garbage dumps), barren areas (exposed soil), and infrastructure (e.g.,

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Chapter 8: Settlements

roadways, houses, and buildings). Although organic soils are less commonly used for settlement development, C
is emitted from these soils if they are drained due to enhanced decomposition, similar to the effect of drainage
for agricultural purposes (Armentano and Menges, 1986).
General information and guidelines for estimating changes in soil C stocks are found in Chapter 2, Section 2.3.3,
and should be reviewed before proceeding with specific guidelines dealing with settlements. The total change insoil C stocks for settlements is computed using Equation 2.24 in Chapter 2, which combines the change in soilorganic C stocks for mineral soils and organic soils; and stock changes for soil inorganic C pools (Tier 3 only).
The next section provides specific guidance on estimating the soil organic C stock change in settlements. For
general discussion on soil inorganic C, no additional information is provided in the settlements discussion below.
To account for changes in soil C stocks associated with Settlements Remaining Settlements, countries need tohave estimates of the relevant settlement area, stratified by climate region and soil type. More detailed inventory
estimations can be made through ground-based surveys and/or periodic analyses of remote sensing imagery to
determine settlement management classes (e.g., turf grass, urban woodlands, gardens, refuse areas, barren areasand infrastructure).
Inventories can be developed using Tier 1, 2 or 3 approaches, with Tier 3 requiring more detail and resources. It
is also possible that countries will use different tiers to prepare estimates for the separate components in thissource category, which includes mineral soils and organic soils in addition to soil inorganic C pools, if using a
Tier 3 approach. Figures 2.4 and 2.5 in Chapter 2 are decision trees that provide guidance for identification of
appropriate tier to estimate changes in carbon stocks in mineral soils and organic soils, respectively.

8.2.3.1

C HOICE OF METHOD

Mineral soils
Tier 1
It is assumed in the Tier 1 method that inputs equal outputs so that settlement soil C stocks do not change in
Settlements Remaining Settlements.
Tier 2The Tier 2 approach for mineral soils uses Equation 2.25 in Chapter 2; involves country- or region-specificreference C stocks and/or stock change factors and possibly suitably disaggregated land-use activity andenvironmental data.
Tier 3Tier 3 is an advanced method for estimating soil C stocks associated with settlement cover classes, such as adynamic model or measurement/monitoring network. Few if any models or measurement systems have beendeveloped for estimating soil C stocks in settlements that would be considered a Tier 3 method. This should beconsidered if settlement soil C is considered a key source category. Additional guidance on Tier 3 approaches isgiven in Chapter 2, Section 2.3.3

Organic soils
Tiers 1 and 2
Settlements are unlikely to be built on deep organic soils, but if needed, emissions can be computed using
Equation 2.26 in Chapter 2. A Tier 2 approach will incorporate country-specific information to estimate
emission factors, in addition to a settlement cover classification. However, it is also optional in the Tier 2
approach to use a more detailed classification of climate and soils than the default categories.
Tier 3Tier 3 approaches for organic soils will include more detailed management systems integrating dynamic models
and/or measurement networks. Additional guidance on Tier 3 approaches is given in Chapter 2, Section 2.3.3.

8.2.3.2

C HOICE OF STOCK CHANGE AND EMISSION FACTORS

Mineral soils
Tier 1
It is assumed in the Tier 1 method that inputs equal outputs so that settlement soil C stocks do not change in
Settlements Remaining Settlements.
Tier 2Since defaults are unavailable, Tier 2 requires estimation of country-specific stock change factors. Equation
2.25 in Chapter 2 uses three levels of stock change factor depending on the land use, the management within the2006 IPCC Guidelines for National Greenhouse Gas Inventories

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land use, and the level of inputs The inventory compiler should define management classes relevant tosettlements (such as turf grass); derive stock change factors for land use (FLU) based on the C storage for eachclass relative to the reference condition which is likely to be native lands. Management factors (FMG) give
flexibility to specify the way land use is managed (such as for sports fields or ornamental use) and input factors(FI) can be used to represent the influence of management on C of input such as watering or fertilization
practices.
Tier 3Tier 3 requires some combination of detailed process models and data gathering, with a sampling strategy andperiodic re-sampling, to capture land-use and management effects. See Chapter 2, Section 2.3.3.1 for further
discussion.

Organic soils
Tier 1
If soils are drained and the peat is not removed, the emissions can be computed using emission factors forcultivated organic soils, due to deep drainage in settlements similar to croplands. If the peat is removed thecarbon should be assumed to be released in the year of removal (see Chapter 5, Cropland).
Tier 2Emission factors are derived from country-specific experimental data in a Tier 2 approach. It is good practicefor emission factors to be derived for specific settlement management classes and/or a finer classification ofclimate regions, assuming the new categories capture significant differences in C loss rates. Additional
guidance is given in Chapter 2, Section 2.3.3.1.
Tier 3
The advice is the same as that given above for mineral soils.

8.2.3.3

C HOICE OF ACTIVITY DATA

Mineral soils
Tier 1
It is assumed in the Tier 1 method that inputs equal outputs so that settlement soil C stocks do not change in
Settlements Remaining Settlements.
Tier 2For the Tier 2 level, activity data consist of areas for settlements subdivided by climate, soil type, and /ormanagement classes, as needed, to correspond with the stock change factors described above. Municipality
records may be useful for determining the proportion of various management classes (e.g., shopping areas,
subdivisions, businesses, parks, schools, etc.), augmented with knowledge of country experts about theapproximate distribution of settlement classes (i.e., turf grass, urban woodlands, gardens, refuse areas, barren
areas and infrastructure). Tier 2 approaches may involve a finer stratification of environmental data, including
climate regions and soil types, provided the corresponding stock change factors have been developed.
Tier 3
The activity data for application of dynamic models and/or a direct measurement-based inventory will
characterise climate, soil, topographic and management regime, depending on the model or sampling design.

Organic soils
Tier 1
The total area of cultivated organic soils in settlements, stratified by climate region to correspond to Table 5.6 in
Chapter 5 or Table 6.3 in Chapter 6, is needed. A default can be obtained by multiplying total urban area, as afunction of climate region, by the area proportion of greenspace from Table 8.3 above.
Tier 2Tier 2 approaches for organic soils will involve more detailed specification of management classes, and possibly
finer division of those classes by drainage or climate regions. Stratification should be based on empirical data
demonstrating significant differences in C loss rates for the proposed classes.
Tier 3
The advice is the same as that given above for mineral soils.

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8.2.3.4

U NCERTAINTY ASSESSMENT

Uncertainties in soil C inventories are related at Tiers 1 and 2 to representation of 1) land-use and management
activities; 2) mineral soil reference C stocks; and 3) stock change and emission factors. Tier 3 uncertainties
depend on model structure and parameters, or measurement error/sampling strategy. Uncertainty is generally
reduced by more sampling and use of a higher Tier estimates incorporating country-specific information.
Uncertainties in reference C stocks and emission factors are indicated in Table 2.3 in Chapter 2; Tables 5.5 and
5.6 in Chapter 5; and Tables 6.2 and 6.3 in Chapter 6. Uncertainties in land-use and management data will need
to be assessed by the inventory compiler, and combined with uncertainties for the default factors and reference C
stocks using an appropriate method, such as simple error propagation equations. If using aggregate land-use area
statistics for activity data (e.g., FAO data), the inventory compiler may have to apply a default level of
uncertainty for the land area estimates (+50%). However, it is good practice for the inventory compiler to derive
uncertainties from country-specific activity data instead of using a default level.
Default reference C stocks for mineral soils and emission factors for organic soils can have high uncertainties,
when applied to specific countries. Defaults represent globally averaged values of land-use and management
impacts or reference C stocks that may vary from region-specific values (Powers et al., 2004; Ogle et al., 2006).
Bias can be reduced by deriving country-specific factors using Tier 2 method or by developing a Tier 3 countryspecific estimation system. The underlying basis for higher Tier approaches will be research in the country orneighbouring regions that address the effect of land use and management on soil C. It is good practice tominimize bias by accounting for significant within-country differences in land-use and management impacts,
such as variation among climate regions and/or soil types, even at the expense of reduced precision in the factor
estimates (Ogle et al., 2006). Bias is more problematic for reporting stock changes because it is not necessarily
captured in the uncertainty range (i.e., the true stock change may be outside of the reported uncertainty range if
there is significant bias in the factors).
Precision in land-use activity statistics may be improved through a better national system, such as developing or
extending a ground-based survey with additional sample locations and/or incorporating remote sensing toprovide additional coverage. It is good practice to design a classification that captures the majority of land-use
and management activity with a sufficient sample size to minimize uncertainty at the national scale.
For Tier 2 methods, country-specific information is incorporated into the inventory analysis for purposes of
reducing bias. For example, Ogle et al. (2003) utilized country-specific data to construct probability density
functions for US specific factors, activity data and reference C stocks for agricultural soils. It is good practice toevaluate dependencies among the factors, reference C stocks or land-use and management activity data. In
particular, strong dependencies are common in land-use and management activity data because management
practices tend to be correlated in time and space.
Tier 3 models are more complex and simple error propagation equations may not be effective at quantifying theassociated uncertainty in resulting estimates. Monte Carlo analyses are possible (Smith and Heath, 2001), but
can be difficult to implement if the model has many parameters (some models can have several hundredparameters) because joint probability density functions must be constructed quantifying the variance as well as
covariance among the parameters. Other methods are also available such as empirically-based approaches(Monte et al., 1996), which use measurements from a monitoring network to statistically evaluate therelationship between measured and modelled results (Falloon and Smith, 2003). In contrast to modelling,
uncertainties in measurement-based Tier 3 inventories can be determined directly from the sample variance,measurement error and other relevant sources of uncertainty.

8.3

LAND CONVERTED TO SETTLEMENTS

Conversion of Forest Land, Cropland, Grassland etc. to Settlements, leads to emissions and removals ofgreenhouse gases. Methods for estimating change in carbon stocks associated with land-use conversions are
explained in Chapters 2, 4, 5 and 6 of this volume. The decision tree (see Figure 1.3 in Chapter 1) and the same
basic methods can be applied to estimate change in carbon stocks in Forest Land, Cropland and Grassland
converted to Settlements.
Depending on the magnitude of carbon stocks in the previous land-use category, land converted to Settlements
may experience a relatively rapid loss of carbon in the first year, followed by a more gradual increase in carbon
pools subsequently. Forest Land converted to Settlements, for example, would normally be characterized by thisabrupt change followed by a gradual increase in carbon stocks. If carbon stocks in the previous land use werelower than in settlements, this abrupt transition would not take place in the first year. For example, abandoned
Cropland converted to Settlements would experience only the gradual carbon stock increase and not the initialabrupt transition.

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The methods described can have sometimes been simplified by estimating the effects of conversion in a single
year followed by application of the methods described above for Settlements Remaining Settlements. However,where this is done, the land area should be kept in the conversion state for the transition period adopted.
Otherwise, there are likely to be difficulties with maintaining the consistency of the land-use matrix.
Where Approach 1 is used in its simplest form for land area representation (see Chapter 3) and no supplementary
information is available that will allow the previous land uses to be inferred, only the total area of settlements
will be known as a function of time and the previous land uses will not be known. Under these circumstances,the biomass stocks before the conversion (Bbefore) cannot be estimated and Equation 2.16 cannot be applied. In
this case land converted to Settlements will have to be estimated with land remaining Settlements and theemissions or removals from conversion to Settlements as well as other land-use changes will be represented as
step changes in the remaining categories rather than properly allocated to the conversions consistent with theland-use change matrix. In effect transitions become step changes across the landscape. This makes it
particularly important to achieve coordination among each sector to ensure the total land base is remaining
constant over time, given that some land area will be lost and gained within individual sectors during each
inventory year due to land-use change.

8.3.1
8.3.1.1

BiomassC HOICE OF METHOD

The general approach for calculating the immediate change in live biomass accruing from the conversion to
Settlements is represented by Equations 2.15 and 2.16 in Chapter 2. The mean annual biomass increment
resulting from the transition is represented by the difference between the biomass in the settlement land-use
category immediately after the transition (BAfter) and the biomass in the previous category (BBefore).
This method follows the approach in the Guidelines for other land-use transitions: the annual change in carbon
stock in biomass due to land conversion is estimated (using Equation 2.16) by multiplying the area converted
annually to settlements by the difference in carbon stocks between biomass in the system prior to conversion(BBefore) and that in the settlements after conversion (BAfter).
Tier 1
For Tier 1, in the initial year following conversion to the settlement land use, the most conservative approach is
to set BAfter to zero, meaning that the process of development of settlements causes carbon stocks to be entirely
depleted. To do this it is necessary to add growth during the year of inventory (∆CG) and subtract loss (∆CL) to
obtain the net change in carbon stocks on land converted to Settlements (Equation 2.15).
Tier 2
At Tier 2, country-specific carbon stocks can be applied to activity data disaggregated to a level of detail adapted
to national circumstances. At the higher tiers, the area of each land-use or land cover type converted to anothertype in a settlement (examples of land use and land cover types are described in Section 8.2) should be recorded,
because that area is associated with the amount of carbon both before and after the conversion. Settlement landuse or land cover types are likely to differ in carbon density.
Tier 3
At Tier 3, countries can use the stock difference method (Equation 2.8) or other advanced estimation methods
that may involve complex models and highly disaggregated activity data including, if available, more detailed
information about BAfter on a country- or biome-specific basis.

8.3.1.2

C HOICE OF EMISSION / REMOVAL FACTORS

Tier 1
Tier 1 methods require estimates of the biomass of the land use before conversion and after conversion. It is
assumed that all biomass is cleared when preparing a site for settlements, thus, the default for biomass
immediately after conversion is 0 tonnes ha-1. Table 8.4 provides default values for biomass before conversion(BBefore).

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Chapter 8: Settlements

TABLE 8.4
DEFAULT BIOMASS CARBON STOCKS REMOVED DUE TO LAND CONVERSION TO SETTLEMENTS
Land-use category

Carbon stock in biomass before conversion (BBefore)(tonnes C ha-1)

Error range #Forest Land

See Chapter 4, Tables 4.7 to 4.12 for carbon stocks in a range of forest
types by climate regions. Stocks are in terms of dry matter. Multiply
values by a carbon fraction (CF) 0.5 to convert dry matter to carbon.

See Section 4.3(Land Converted
to Forest Land)

Grassland

See Table 6.4, Chapter 6 for carbon stocks in a range of grassland types
by climate regions.

+ 75%

CroplandFor cropland containing annual crops: Use default of 4.7 tonnes of carbon
ha-1 or 10 tonnes of dry matter ha-1 (see Chapter 6, Section 6.3.1.2)± 75%.

#

Represents a nominal estimate of error, equivalent to two times standard deviation, as a percentage of the mean.

Tiers 2 and 3
Tier 2 methods replace the default data by country-specific data and Tier 3 involves detailed modelling or
measurement data relevant to the conversion processes.

8.3.1.3

C HOICE OF ACTIVITY DATA

Activity data for estimating changes in biomass on land areas converted to Settlements can be obtained,
consistent with the general principles set out in Chapter 3, through national statistics, from forest services,
conservation agencies, municipalities, survey and mapping agencies. Cross-checks should be made to ensurecomplete and consistent representation of annually converted lands in order to avoid possible omissions or
double counting. Data should be disaggregated according to the general climatic categories and settlements types.
Tier 3 inventories will require more comprehensive information on the establishment of new settlements, withrefined soil classes, climates, and spatial and temporal resolution. All changes having occurred over the numberof years selected as the transition period should be included with transitions older than the transition period(default 20 years) reported as a subdivision of Settlements Remaining Settlements.
Higher tiers require greater detail but the minimum requirement for inventories to be consistent with the IPCC
Guidelines is that the areas of Forest Land conversion can be identified separately. This is because forest willusually have higher carbon density before conversion. This implies that at least partial knowledge of the land-use
change matrix, and therefore, where Approaches 1 and 2 from Chapter 3 are used to estimate land area,
supplementary surveys may be needed to identify the area of land being converted from Forest Land to
Settlements. As pointed out in Chapter 3, where surveys are being set up, it will often be more accurate to seek
to establish directly, areas undergoing conversion, than to estimate these from the differences in total land areas
under particular uses at different times.

Step by step method for implementation
Tier 1
Use default values for Bbefore from respective land-use category chapter (Forest Land, Grassland, etc) and assume
that BAfter equals zero in Equation 2.16.
Step 1: Apply Equation 2.16 to each land-use type converted to settlement lands;
Step 2: Add up the biomass changes over all the land-use types; andStep 3: Multiply the result by 44/12 to obtain the amount of CO2 equivalents emitted (the sum obtained in Step
2 will be a negative number) from the land conversion.
Tier 2The typical steps to implement a Tier 2 method are:
Step 1: Use the methods described in Chapter 3, including where relevant cadastral and planning records or the
analysis of remote sensing images (or both), to estimate the change in area between the present and the last area
survey.
Step 2: Define — as a first approximation — settlement land-use types on the basis of the proportion ofgreenspace. For instance, three tentative land-use classes could be: Low (less than 33% greenspace), Medium(from 33 to less than 66% greenspace), and High (more than 66% greenspace). Each one of those classes can be2006 IPCC Guidelines for National Greenhouse Gas Inventories

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assigned with an average carbon content, obtained from the species surveyed in similarly defined classes foraccounting biomass changes in Section 8.2.
Step 3: Draw a land-use conversion area matrix for the land-use transitions defined in Step 2.
Step 4: Estimate with equations the biomass stocks of the defined land-use types and the converted land-use
types (to obtain BBefore and BAfter), apply Equation 2.16 to each non-empty cell of the land-use change matrix, add
up the changes in carbon stocks, and multiply the sum by 44/12 to obtain the emission/removal of CO2
equivalents.
Step 5: Calculate ∆CG, using either Method A or Method B in Section 8.2.1, Settlements Remaining Settlements(the choice of method will depend on the applicability of the emission and removal factors, as well as theavailability of activity data). This will be used in Equation 2.15.
Step 6: Calculate ∆CL, using Methods as described in Section 8.2.1.3, Settlements Remaining Settlements.
Step 7: Calculate the change in carbon stocks in live biomass resulting from the land-use transition to
Settlements, accounting for the biomass increment, biomass losses, and biomass change due to land-use
conversion as given in Equation 2.15.

8.3.1.4

U NCERTAINTY ASSESSMENT

See guidance in Section 8.2.1.4.

8.3.2

Dead organic matter

Methods are provided for two types of DOM pools: 1) dead wood and 2) litter. Chapter 1of this report provides
definitions of these pools and Section 8.2.2 DOM in the context of settlements.
Some land converted to Settlements will not have an abrupt transition (e.g., Cropland that is abandoned andconverted to Settlements). In this case, Phase 1 methods will not be appropriate and there will be a gradualtransition in DOM pools to a new equilibrium. When this type of conversion occurs, the whole conversion
accounting can be treated with Phase 2 methods.

8.3.2.1

C HOICE OF METHOD

Estimation of changes in carbon stocks in DOM requires separate estimates of changes in stocks of dead woodand changes in litter stocks (refer to Equation 2. 17 of Chapter 2). The decision tree in Figure 2.3 in Chapter 2
helps select the appropriate tier to use.
Tier 1
Tier 1 default assumes all carbon contained in dead wood and litter is lost during conversion and does not takeaccount of any subsequent accumulation.
Tier 2Tier 2 approaches require greater disaggregation than that used in Tier 1. The immediate and abrupt carbon
stock change in dead wood due to conversion of other lands to Settlements under Tiers 2 and 3 will be estimatedusing Equation 2.23, where Co is set to zero and Ton is set at 1 year. Tier 2 assumes a linear change function,although during the transition period, pools that gain or lose C often have a non-linear loss or accumulation
curve that can be represented at Tier 3 through successive transition matrices.
For the calculation of changes in dead wood and litter carbon during the transition phase, two methods aresuggested:
Method 1 (Also called the Gain-Loss Method, Equation 2.18 in Chapter 2): This method involves estimating
the area of each type of land conversion and the average annual transfer into and out of dead wood and litter
stocks. This requires an estimate of area under land converted to Settlements according to different climate or
ecological zones or settlement types, disturbance regime, management regime, or other factors significantly
affecting dead wood and litter carbon pools and the quantity of biomass transferred into dead wood and litter
stocks as well as the quantity of biomass transferred out of the dead wood and litter stocks on per hectare basis
according to different settlement types.
Method 2 (Also called the Stock-Difference Method, Equation 2.19 in Chapter 2): This method involves
estimating the area of land converted to Settlements and the dead wood and litter stocks at two periods of time, t1
and t2. The dead wood and litter stock changes for the inventory year are obtained by dividing the stock changes

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Chapter 8: Settlements

by the period (years) between two measurements. The stock-difference method is feasible for countries, whichhave periodic inventories.
Tier 3
For Tier 3, countries should develop their own methodologies and parameters for estimating changes in DOM.
These methodologies may be derived from Methods 1 or 2 specified above, or may be based on other approaches.
The method used needs to be clearly documented. A Tier 3 approach should use or be consistent with the true
shapes of the loss or accumulation curves. These curves should be applied to each cohort that is under transition
during the reporting year to estimate the annual change in the dead wood and litter carbon pools.

8.3.2.2

C HOICE OF EMISSION / REMOVAL FACTORS

Carbon fraction: The carbon fraction of dead wood and litter is variable and depends on the stage ofdecomposition. Wood is much less variable than litter and a value of 0.50 tonne C (tonne d.m.)-1 can be used forthe carbon fraction. Litter values in settlements range from 0.30 to 0.50. When country- or ecosystem-specificdata are not available we suggest a carbon fraction value of 0.40 for litter.
Tier 1Dead wood and litter carbon stocks in lands converted to Settlements are assumed all lost during the conversion
and there is assumed to be no subsequent accumulation of new DOM in the settlements after conversion. Default
values for forest litter prior to conversion are provided in Table 2.2 in Chapter 2 but there are no default values
available for dead wood or litter in most systems. Countries should seek estimates and use local data fromforestry and agricultural research institutes to provide best estimates of the dead wood and litter in the initialsystem prior to conversion, or use the defaults in Table 2.2 in the absence of other information. Carbon stocks inlitter and dead wood pools in all non-forest land categories are assumed to be zero. Countries experiencing
significant conversions of other ecosystems to settlements are encouraged to develop domestic data to quantify
this impact and report it under Tier 2 or 3 methodologies.
Tier 2
It is good practice to use country-level data on dead wood and litter for different settlements categories, in
combination with default values if country or regional values are not available for some conversion categories.
Country-specific values for the transfer of carbon from live trees and grasses that are harvested to harvest
residues and decomposition rates, in the case of the Gain-Loss Method, or the net change in DOM pools in thecase of the Stock-Difference Method, can be derived from domestic expansion factors, taking into account thesettlements type, the rate of biomass utilization, harvesting practices and the amount of damaged vegetation
during harvesting operations. Country-specific values for disturbance regimes should be derived from scientificstudies.
Tier 3National level disaggregated DOM carbon estimates should be determined as part of a national inventory,
national level models, or from a dedicated greenhouse gas inventory programme, with periodic samplingaccording to the principles set out in Chapter 3, Annex 3A.3. Inventory data can be coupled with modellingstudies to capture the dynamics of all settlements carbon pools.
Tier 3 methods provide estimates of greater certainty than lower tiers and feature a greater link between
individual carbon pools. Some countries have developed disturbance matrices that provide a carbon reallocation
pattern among different pools for each type of disturbance. Other important parameters in a modelled DOM
carbon budget are decay rates, which may vary with the type of wood and microclimatic conditions, and site
preparation procedures (e.g., controlled broadcast burning, or burning of piles).

8.3.2.3

C HOICE OF ACTIVITY DATA

The activity data should be the same as that used for biomass and described in Section 8.3.1.3

Step-by-step summary of method for estimating changes in DOM stocks
Tier 1
Step 1: Determine the categories of land conversion to be used in this assessment and the representative area of
conversion by year. Area data should be obtained using the methods described in Chapter 3. Higher tiers require
greater detail but the minimum requirement for inventories to be consistent with the IPCC Guidelines, whenusing Tier 1, is that the areas of forest conversion are identified separately.
Step 2: For each activity category, determine the dead wood and litter stocks (separately) per hectare prior toconversion (see Table 2.2 in Chapter 2 for default values).

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Step 3: For each activity category, determine the stocks in the dead wood and litter (separately) per hectare forthe particular type of settlement. For Tier 1, dead wood and litter stocks following conversion are assumed to beequal to zero.
Step 4: Calculate the net change of dead wood and litter stocks per hectare for each type of conversion by
subtracting the initial stocks from the final stocks. A negative value indicates a loss in the stock (Equation 2.23).
Step 5: Convert the net change in the individual stock to units of tonnes C ha-1 by multiplying the net stockchange by the carbon fraction of that stock (0.40 tonne C (tonne d.m.)-1 for litter and 0.50 tonne C (tonne d.m.)-1
for dead wood).
Step 6: Multiply the net change in each C stock by the area converted during the reporting year.
Tiers 2 and 3
Step 1: Determine the categories of land conversion to be used in this assessment and the representative area of
conversion by year. When calculating for lands in the transition phase, representative areas for each category at
different stages of conversion are required. Higher tiers require greater detail but the minimum requirement for
inventories to be consistent with the IPCC Guidelines is that the areas of forest conversion are identified
separately.
Step 2: Abrupt changes•

Determine the activity categories to be used in this assessment and the representative areas. The activity
category consists of definitions of the type of conversion and, if applicable, the nature of management of theprevious land cover and settlements management, for example: ‘conversion of logged tropical seasonal
forest to cattle pasture using exotic grasses’. Area data should be obtained using the methods described in
Chapter 3.

•

For each activity category, determine the dead wood and litter stocks (separately) per hectare prior toconversion.

•

For each activity category, determine the stocks in the dead wood and litter (separately) per hectare
following one year of conversion to Settlements.

•

Calculate the net change of dead wood and litter stocks per hectare for each type of conversion by
subtracting the initial stocks from the final stocks. A negative value indicates a loss in the stock.

•

Convert the net change in the individual stock to units of tonnes C ha-1 by multiplying the net stock changeby the carbon fraction of that stock (0.40 tonne C (tonne d.m.)-1 for litter and 0.50 tonne C (tonne d.m.)-1 fordead wood).

•

Multiply the net change in each C stock by the area converted during the reporting year.

Step 3: Transitional changes•

Determine the categories and cohorts to be used in this assessment and the representative areas. The
category consists of definitions of the type of conversion and, if applicable, the nature of management of theprevious land cover and settlements type. Area data should be obtained using the methods described in
Chapter 3.

•

Determine the annual change rate for dead wood and litter stocks (separately) by activity type using either
the Gain-Loss Method or the Stock-Difference Method (see below) for each cohort of lands that are
currently in the transition phase between conversion and a new steady-state.

•

Determine the dead wood and litter stocks in the cohort during the previous year (usually taken from theprevious inventory).

•

Calculate the change in dead wood and litter stocks for each cohort by adding the net change rate to theprevious year’s stocks.

•

Convert the net change in the individual stock to units of tonnes C ha-1 by multiplying the net stock changeby the carbon fraction of that stock (0.40 tonne C (tonne d.m.)-1 for litter and 0.50 tonne C (tonne d.m.)-1 fordead wood).

•

Multiply the net change in each C stock by the area in each cohort for the reporting year.

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Chapter 8: Settlements

Ga i n- Los s M ethod• Determine the average annual inputs of dead wood and litter (separately).
•

Determine the average annual losses of dead wood and litter (separately).

•

Determine the net change rate in dead wood and litter by subtracting the outputs from the inputs.

S t o c k - D if f er e n c e M et h o d• Determine the inventory time interval, the average stocks of dead wood and litter at the initial inventory, andthe average stocks of dead wood and litter at the final inventory.
•

Use these figures to calculate the net change in dead wood and litter stocks by subtracting the initial stockfrom the final stock and dividing this difference by the number of years between inventories. A negativevalue indicates a loss in the stock.

•

A Tier 3 approach requires country- or region-specific expansion factors. There are no default expansion
factors for Tier 2, and the best available local data should be used (and documented).

8.3.2.4

U NCERTAINTY ASSESSMENT

Uncertainty at Tier 1 is the same as the uncertainty in the carbon stock on the area of land subject to annual
conversion. DOM changes are subsequently assumed to be zero, and no associated uncertainty is needed at Tier
1 after the initial transition. For Tiers 2 and 3 estimates, sources of uncertainty include the degree of accuracy inland area estimates, carbon increment and loss, carbon stocks, amount of carbon burned, and expansion factor
terms. Area data and estimates of uncertainty should be obtained using the methods in Chapter 3 which provide
default uncertainties associated with the different approaches. Uncertainties associated with carbon stocks andother parameter values are likely to be at least a factor of three unless country-specific data are available fromwell designed surveys.

8.3.3

Soil carbon

Land conversion to Settlements occurs with development and expansion of cities and towns on former Forest
Land, Cropland, Grassland, Wetlands, and Other Land. These conversions change soil C stocks due tomechanical disturbance of the soil; soil burial or collection during development; type and amount of vegetatedcover; in addition to the new management regime, particularly with respect to nutrient and water applications.
General information and guidelines for estimating changes in soil C stocks are found in Chapter 2, Section 2.3.3(including equations). The total change in soil C stocks for Land Converted to Settlements is computed using
Equation 2.24, which combines the change in soil organic C stocks for mineral soils and organic soils; and stockchanges associated with soil inorganic C pools (for Tier 3 only).
To account for changes in soil C stocks associated with land converted to Settlements, countries need to haveestimates of the areas of land converted to Settlements during the inventory time period, stratified by climate
region and soil type. If aggregate land-use data are used and specific conversions among uses are not known, soilorganic C (SOC) stock changes can still be computed using the methods provided in Settlements Remaining
Settlements, but the land-base area will then probably be different for settlements in the current year relative tothe initial year in the inventory, and the dynamics of the transition will be less well represented. Chapter 3(Consistent representation of lands) emphasises the importance of maintaining consistency in total land area.

8.3.3.1

C HOICE OF METHOD

Inventories can be developed using Tier 1, 2 or 3 approaches, with each successive Tier requiring more detailand resources than the previous one. It is also possible that countries may use different tiers to prepare estimates
for the separate sub-categories of soil C (i.e., soil organic C stocks changes in mineral soils and organic soils,
and stock changes associated with soil inorganic C pools, are estimated at Tier 3). Decision trees are provided
for mineral soils (Figure 2.4) and organic soils (Figure 2.5) in Section 2.3.3.1 (Chapter 2) to help selection of theappropriate tiers.

Mineral soils
Tier 1
Change in soil organic C stocks can be estimated for mineral soils with land-use conversion to Settlements using
Equation 2.25 in Chapter 2. For Tier 1, the initial (pre-conversion) soil organic C stock (SOC(0-T)) and C stock in
the last year of the inventory time period (SOC0) are determined from the common set of reference soil organic

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C stocks (SOCREF) and default stock change factors (FLU, FMG, FI). Areas of exposed bedrock in Forest Land or
the previous land use are not included in the soil C stock calculation (assume a stock of 0). Annual rates ofemissions (source) or removals (sink) are calculated as the difference in stocks (over time) divided by the timedependence (D) of the stock change factors (default is 20 years).
Tier 2The Tier 2 approach for mineral soils also uses Equation 2.25 in Chapter 2, but involves country- or regionspecific reference C stocks and/or stock change factors and possibly more disaggregated land-use activity andenvironmental data. Removal, translocation or burial of soil C during development is a particular issue forsettlements. To the extent that soil C is not decomposed during the development phase and resides deeper in the
profile, is translocated to another area, or possibly used as a commodity. It is good practice for Tier 2 stockchange factor to be adjusted to reflect the reduction in loss of C to the atmosphere as CO2.
Tier 3Tier 3 methods will involve more detailed and country-specific models and/or measurement-based approaches
along with highly disaggregated land-use and management data. It is good practice that Tier 3 approaches for
estimating soil C change from land-use conversions to Settlements, employ models, data sets and/or monitoring
networks that are capable of representing transitions over time from other land uses, including Forest Land,
Grassland, Cropland or other lands. Tier 3 methods need to be integrated with estimates of biomass removal andthe post-clearance treatment of plant residues (including woody debris and litter), as variation in the removal andtreatment of residues (e.g., burning, site preparation) will affect C inputs to soil organic matter formation and C
losses through decomposition and combustion. Models should be validated with independent observations fromcountry- or region-specific field locations that are representative of the interactions of climate, soil andmanagement on post-conversion change in soil C stocks.

Organic soils
Tiers 1 and 2
Land converted to Settlements on organic soils within the inventory time period is treated the same as
Settlements Remaining Settlements. Carbon losses are computed using Equation 2.26 in Chapter 2. Additional
guidance on Tiers 1 and 2 approaches are given in Section 8.2.3.1.
Tier 3
As with mineral soils, a Tier 3 approach will involve country-specific models and/or measurement-based
approaches along with highly disaggregated land-use and management data.

8.3.3.2

C HOICE OF STOCK CHANGE AND EMISSION FACTOR

Mineral soils
Tier 1
Default reference C stocks are found in Table 2.3 of Chapter 2, and stock change factors for previous land uses
can be found in the relevant Chapters (for Forest Land in Section 4.2.3.2, Cropland in 5.2.3.2, Grassland in
6.2.3.2, and Other Land in 9.3.3.2). Default stock change factors for land use after conversion (Settlements) are
not needed for the Tier 1 method for Settlements Remaining Settlements because the default assumption is that
inputs equal outputs and therefore no net change in soil carbon stocks occur once the settlement is established.
Conversions, however, may entail net changes and it is good practice to use the following assumptions:(i)for the proportion of the settlement area that is paved over, assume product of FLU, FMG and FI is
0.8 times the corresponding product for the previous land use (i.e., 20% of the soil carbon relative
to the previous land use will be lost as a result of disturbance, removal or relocation);(ii)

for the proportion of the settlement area that is turfgrass, use the appropriate values for improved
grassland from Table 6.2, Chapter 6;(iii)

for the proportion of the settlement area that is cultivated soil (e.g., used for horticulture) use theno-till FMG values from Table 5.5 (Chapter 5) with FI equal to 1; and(iv)

for the proportion of the settlement area that is wooded assume all stock change factors equal 1.

Tier 2Estimation of country-specific stock change factors is probably the most important development associated with
the Tier 2 approach. Differences in soil organic C stocks among land uses are computed relative to a reference
condition, using land-use factors (FLU). Input factor (FI) and management factor (FMG) are then used to further
refine the C stocks of the settlement management classes. Additional guidance on how to derive these stockchange factors is given in Settlements Remaining Settlements, Section 8.2.3.2. See the appropriate section for
specific information regarding the derivation of stock change factors for other land-use sectors (Forest Land in

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Chapter 8: Settlements

Chapter 4, Cropland in Chapter 5, Grassland in Chapter 6, and Other Land in Chapter 9). Reference C stocks canalso be derived from country-specific data in a Tier 2 approach and should of course be consistent across theland uses (i.e., Forest Land, Cropland, Grassland, Settlements, Other Land), and therefore coordinated among thevarious teams conducting soil C inventories for AFOLU.
Tier 3
Constant emission rate factors per se are less likely to be estimated in favor of variable rates that more accurately
capture land-use and management effects. See Chapter 2, Section 2.3.3.1 for further discussion.

Organic soils
Tiers 1 and 2
Land converted to Settlements on organic soils within the inventory period is treated the same as Settlements
Remaining Settlements. Tier 2 emission factors are derived from country- or region-specific data; additional
guidance is given in Section 8.2.3.2.
Tier 3
Constant emission rate factors per se are less likely to be estimated in favor of variable rates that more accurately
capture land-use and management effects. See Chapter 2, Section 2.3.3.1 for further discussion.

8.3.3.3

C HOICE OF ACTIVITY DATA

Mineral soils
Tiers 1 and 2
The amount of land converted to Settlements, stratified by climate region and soil type, is needed to estimate theappropriate stocks at the Tier 1 level. This can be based on overlays with suitable climate and soil maps andspatially-explicit data of the location of land conversions. Detailed descriptions of the default climate and soil
classification schemes are provided in Chapter 3. In the absence of specific information, default area within thesettlements that is paved over should be estimated as the non-greenspace proportion of the total area, using thedata in Table 8.3, and the same Table can be used to partition the greenspace area into wooded areas and nonwooded areas. The latter may be assumed all to be turfgrass unless data are available on the area otherwise
cultivated.
Tier 3For application of dynamic models and/or a direct measurement-based inventory in Tier 3, similar or moredetailed data on the combinations of climate, soil, topographic and management data are needed, but the exact
requirements will depend on the model or measurement design.

Organic soils
Tiers 1 and 2
Land converted to Settlements on organic soils within the inventory time period is treated the same as
Settlements Remaining Settlements, and guidance on activity data is discussed in Section 8.2.3.3.
Tier 3
As with mineral soils, Tier 3 approaches will likely require more detailed data on the combinations of climate,soil, topographic and management data, relative to Tier 1 or 2 methods, but the exact requirements will bedependent on the model or measurement design.

8.3.3.4

U NCERTAINTY ASSESSMENT

See guidance in Section 8.2.3.4.

8.4

COMPLETENESS, TIME SERIES, QA/QC, AND
REPORTING

8.4.1

Completeness

It is good practice for soil C inventories to track the changes in total area over time, and if using a Tier 2 or 3
approach, the inventory should track areas associated with the major management classes (e.g., turf grass, urban
woodlands, gardens, refuse areas, barren areas and infrastructure). The total area covered by the settlement
inventory methodology is the sum of land in Settlements Remaining in Settlements and Land Converted to2006 IPCC Guidelines for National Greenhouse Gas Inventories

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Settlements during the time period. This inventory methodology may not include some settlement areas where
greenhouse gas emissions and removals are believed to be insignificant or constant through time because of little
or no change in settlement management or no significant change in management inputs. However, countries areencouraged to track through time the total area of land in settlements within country boundaries, keeping
transparent records on which portions are used to estimate carbon dioxide emissions and removals. In this case, it
is good practice for countries to document and explain the difference in the area that is included in the inventorycomputations and the total settlement area in the land base.

8.4.2

Developing a consistent time series

To maintain a consistent time series, it is good practice for countries to apply the same inventory methods overthe entire reporting time period, including definitions for land-use and settlement systems, area included in a C
inventory, and calculation method. If changes are made, it is good practice to keep transparent records of thechanges, and then re-calculate the C stock changes over the entire inventory time period. Guidance on recalculation under these circumstances is given in Volume 1, Chapter 5. Consistent estimation and reporting also
requires common definitions of management activities, climate and soil types across the entire time series for theperiod of the inventory.

8.4.3

Inventory Quality Assurance/Quality Control

It is good practice to implement quality control checks and external expert review of inventory estimates anddata. Specific attention is expected to be paid to country-specific estimates of stock change and emission factors,
ensuring that they are based on high quality data and verifiable expert opinion.
Specific QA/QC checks across the settlements methodology include:
Settlements Remaining Settlements: It is good practice for settlement areas to be consistent for reporting of
biomass stock and soil stock changes. Settlements may include areas where soil stock changes are accounted forbut biomass changes are assumed to be zero (e.g., where non-woody biomass is largely absent), areas where bothbiomass and soil stocks are changing (e.g., development of a park), and areas where neither biomass nor soil
stocks are changing (e.g., infrastructure and barren areas). To increase transparency and eliminate errors, it isgood practice to report the total settlement area regardless of whether stocks are changing.
Land Converted to Settlements: Aggregate area totals for land converted to Settlements are expected to be thesame in the biomass and soils estimations. While biomass and soil pools may be disaggregated to different levelsof detail, it is good practice to use the same general categories for disaggregating the area data.
For all soil C stock change estimates, it is expected that the total areas will be the same for each climate-soil typecombination at the beginning (year(0-T)) and the last year (year(0)) of the inventory time period, unless it has been
demonstrated that some portion of the land base has been incorporated into another land-use sector or gained
from another sector. Ultimately, the sum of the entire land base for a country, which includes each sector, must
be equal across every year in the inventory time period.

8.4.4

Reporting and Documentation

It is good practice to maintain and archive all information used to produce national inventory estimates including:(i) data sources, databases, data sources for information used to estimate country-specific factors as well as theprocedures used to estimate factors; (ii) activity data and definitions used to categorize or aggregate the activity
data; and (iii) climate region classifications and soil types (for Tier 1 and Tier 2) must be clearly documented.
For Tier 3 approaches using modelling, it is good practice to document the model version and provide a model
description, in addition to permanently archiving copies of all model input files, source code and executable
programs.

Reporting tables and worksheets
The categories described in this Chapter can be reported using the reporting tables in Volume 1, Chapter 8. The
estimates under the Settlements category can be compared with the reporting categories in the IPCC Guidelines
as follows:•

8.26

Carbon dioxide emissions and removals in woody biomass in Settlements Remaining Settlements to IPCC
reporting category 5A and Land Converted to Settlements in IPCC reporting category 5B; and IPCC
reporting categories 4E and 4F for non-CO2 gases;

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Chapter 8: Settlements•

Carbon dioxide emissions and removals in soils in Settlements Remaining Settlements to IPCC reporting
categories 5D and 5E for CO2, and IPCC reporting category 4D for non-CO2 gases; and•Carbon dioxide emissions and removals resulting from land-use conversions to Settlements to IPCC
reporting category 5B for biomass, IPCC reporting categories 5D and 5E for soils; and IPCC reporting
categories 4D, 4E, and 4F for non-CO2 gases.

Worksheets are provided in Annex 1 for calculating greenhouse gases emissions and removals (Tier 1 methods)
for Settlements.

8.5

BASIS FOR FUTURE METHODOLOGICALDEVELOPMENT

Gaps in this methodology exist because sufficient data are not available to quantify all of the pools and fluxes ofgreenhouse gases in settlements. Obvious gaps include:•

Methodology for estimating emissions of non-CO2 greenhouse gases (N2O and CH4);•

Detailed methodology to account for carbon stocks other than live biomass and soils (specifically, deadwood and litter);•

Discussion of carbon stocks and fluxes from turfgrass and turf management;•

Discussion of carbon stocks and fluxes from gardens and other herbaceous plants; and•A generalized methodology to account for different classes of settled lands, with different amounts ofwoody and non-woody vegetation and different types of management.

Non-CO2 greenhouse gases. While some evidence exists to support the idea that nitrous oxide fluxes may beenhanced in urban areas relative to the native condition (Kaye et al., 2004), this result likely depends on thenative condition (i.e., the climate and region in which the settlement is located) and the management regime
typically applied in that settled area. Additional data are required before conclusions about the impact ofsettlement on non-CO2 greenhouse gas fluxes can be drawn.
Dead wood and litter. Dead wood is a class variously composed of fallen or pruned branches or trees, or deadstanding trees not yet replaced with live individuals. This dead wood may be burned or disposed of as solid
waste, used for composting, left to decay either in-site or off-site. This material is treated in this methodology asa loss from the live biomass term. Because dead wood is likely to be carried off-site in settlements (rather thanleft on-site to decay as in forests), a more detailed methodology developed in the future might account for the
proportion of dead wood taken to landfills, disposed of in compost piles, burned, or left on-site to decay. The
portion taken to landfills or composted might be treated as harvested wood products (HWP) or as waste, both ofwhich are treated in other sections of the Guidelines.
Turfgrass and turf management. Turfgrass biomass consists of roots, stubble, thatch, and above-groundcomponents. Though estimates of turfgrass productivity have been published (Falk, 1976; Falk, 1980; Qian etal., 2003), grass decomposes quickly and there is little information about the overall accumulation of biomass in
the longer-lived components of turf biomass. Turfgrass allocation to the above-ground and below-groundcomponents also depends on the management and mowing regime. Because of the lack of generalizable
information on this topic, as well as the lack of activity data quantifying the area covered by turfgrass insettlements, there is currently no detailed methodology describing carbon removed by turf systems. A moredetailed methodology would require additional information on turf productivity, turfgrass turnover, andallocation to different plant components as it varies with management regime. Of course, the activity datarequired to implement this methodology would include information on management regimes and the proportionof settlements covered by turfgrass.
Gardens and other herbaceous plants. Similar to the situation with turfgrass, information does not exist
describing the annual biomass accumulation and allocation of garden plants to different above-ground andbelow-ground parts. Similarly, information is not available describing the variation in plant productivity withmanagement regime. Activity data required to implement a more detailed methodology would include
information on management regimes and the proportion of settlement area covered by this type of vegetation.
These are mainly garden plants, so sampling them in private gardens presents the additional problem of theirlikely disturbance and consequent denial of access to them (cf. Jo and McPherson, 1995).
Land classes. A more detailed methodology would benefit from a consistent set of definitions of land classes
within settlements, that could be applied to any country regardless of its climate, native vegetation, or typicalsettlement regime. This would make settlements parallel to other land uses – Forest Land, Grassland, Cropland,

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Wetlands – which are easily defined based on a set of measurable and objective parameters. Some research has
been applied in this direction (Theobald, 2004), but current classifications are inconsistent. While the rate ofcarbon sequestration per unit of tree crown cover is fairly consistent, for example, the overall rate of carbon
storage per unit of settlement area depends entirely on the relative amounts of tree and turfgrass cover within that
settlement. This land classification would be part of the set of activity data collected by countries, and thedetailed methodology could be developed and applied consistently based on those land cover data. This type ofland-use classification would also enable countries to account for changes in carbon storage resulting frommanagement changes within areas broadly classified as settlements. For example, when vacant plots aredeveloped, the adventitious vegetation remaining in the non-built areas might be replaced with landscape species
differing in ability to store carbon.

References
Akbari, H. (2002). Shade trees reduce building energy use and CO2 emissions from power plants. Environmental
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