Chapter 8: Settlements

CHAPTER 8

SETTLEMENTS

2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories

8.1

Volume 4: Agriculture, Forestry and Other Land Use

Authors
Atsushi Sato (Japan), Marina Vitullo (Italy), Thomas Gschwantner (Austria).

Contributing Authors
Yowhan Son (Korea, Republic of).

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Chapter 8: Settlements

Contents
8

Settlements

8.4

8.1

Introduction ......................................................................................................................................... 8.4

8.2

Settlements Remaining Settlements .................................................................................................... 8.4
8.2.1

8.3

Biomass.................................................................................................................................... 8.4

8.2.1.1

Choice of method ............................................................................................................... 8.4

8.2.1.2

Choice of emission/removal factors ................................................................................... 8.4

8.2.1.3

Choice of activity data ........................................................................................................ 8.6

8.2.1.4

Uncertainty assessment ...................................................................................................... 8.7

8.2.2

Dead organic matter ................................................................................................................. 8.7

8.2.3

Soil carbon ............................................................................................................................... 8.7

Land Converted to Settlements ........................................................................................................... 8.7
8.3.1

Biomass.................................................................................................................................... 8.7

8.3.1.1

Choice of method ............................................................................................................... 8.7

8.3.1.2

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

8.3.1.3

Choice of activity data ........................................................................................................ 8.9

8.3.1.4

Uncertainty assessment .................................................................................................... 8.10

8.3.2

Dead organic matter ............................................................................................................... 8.10

8.3.3

Soil carbon ............................................................................................................................. 8.10

8.4

Completeness, time series consistency, QA/QC and reporting ......................................................... 8.11

8.5

Basis for future methodological development ................................................................................... 8.11

References

8.12

TablesTable 8.1 (Updated)

Tier 2A default crown cover area-based growth rates (CRW) for urban tree crowncover by region ....................................................................................................... 8.6

Table 8.2 (Updated)

Tier 2B Default average annual carbon accumulation per tree in urban trees byspecies classes ......................................................................................................... 8.6

Table 8.4 (Updated)

Default biomass carbon stocks removed due to land conversion to settlements ..... 8.9

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Volume 4: Agriculture, Forestry and Other Land Use

8

SETTLEMENTS

8.1

INTRODUCTION

No refinement.

8.2

SETTLEMENTS REMAINING SETTLEMENTS

No refinement.

8.2.1

Biomass

No refinement.

8.2.1.1 C HOICE OF METH OD
No refinement.

8.2.1.2 C HOICE OF EMISSION / REMOVAL FACTORSThis section provides updates on methods.
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; Nowak et al., 2013]) intended to take accountof the allometry of open-grown trees in cities where above-ground biomass for a given diameter is typically lower
than that of forest-grown trees (Nowak, 1996). Allometric equations for some shrub species exist, but have notroutinely 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
estimated root: 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 aboveground biomass ratio) often used in forest settings. Ratios appropriate to the region of interest can be assumed toapply 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 root zone due
to impermeable paving surfaces (e.g., Pouyat et al., 1995; Idso et al., 1998; Idso et al., 2001; Gregg et al., 2003;
Pouyat and Carreiro, 2003; Nowak et al., 2013). In addition, management practices for urban trees also affect its
growth and mortality. Therefore, the values and equations used to predict tree growth in settlements at higher tiersshould, to the extent feasible, allow for the surrounding environment and the condition of the trees, and take into
account the urban environment, then conditions and management practices of urban trees.
Carbon stored in the woody components of trees makes up the largest compartment of standing biomass stocks
and annual biomass increment in settlements. For example, Nowak and Crane (2002) estimated on a citywide basisthat the net annual carbon storage by trees in cities in the conterminous USA ranged from 600 to 32,200 tonnes C
yr-1. Jo (2002) found that the amount of C sequestered annually in three Korean cities varied from 2,900 to 40,300
tonnes. Clearly, the estimates depend on the land use definition of Settlements in each country as well as kind oftree covered area considered 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). City level studies show that annual sequestration rates ranged fromless than 1.5 to more than 5.0 t C (ha crown cover) -1 yr-1but most of the rates are in the range from 2.0 to 4.0 t C(ha crown cover) -1 yr-1(Nowak et al., 2013, Escobedo et al., 2010, McPherson et al., 2013, Chaparro and Terradas,
2009, Mills et. al., 2015, Yang et al., 2005, Liu and Li, 2012 and Vaccari et al., 2013). The studies indicate thatthe annual sequestration per unit of urban area or even per unit of crown cover in settlements depends on thespecific situation on urban land such as type of vegetation, species composition, density of planted tree and shrub,
management type of urban area, shade of buildings etc. In the case of parks and urban trees, estimation methods
are provided below. For Settlements areas stocked by trees with forest-like conditions, refer to the estimation
methods in Chapter 4, Volume 4 (Forest Land).

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Chapter 8: Settlements

At a national level, data are still sparse, though availability is increasing. For example, Nowak et al., 2013
estimated the average removal factor of tree biomass (CRW) for US urban forest as 2.77 t C (ha crown cover)-1 yr-1
based on studies in 28 US cities and 6 US states, Pasher et al., 2014 provided the Canadian removal factor of
urban forest in settlement as 2.12 t C (ha crown cover)-1 yr -1 which adjusted the US removal factor to the Canadianclimate condition. McPherson et al., 2013 reviewed carbon sequestration rate per urban tree cover area in 32 cities
to encompass a range of sizes, climates and cultures (US, Canada, Spain, Germany, Korea and China) and derived
a mean value as 2.79 t C (ha crown cover)-1 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 both living
and from dead biomass (e.g., fuelwood, broken branches, etc.). Therefore, in a Tier 1 approach CG = CL and forall plant components, and CB = 0 in Equation 2.7 in Chapter 2, Volume 4 (Generic Methodologies Applicable toMultiple Land-Use Categories).

Tier 2Trees
Tier 2 calls for parameter values for CRWij (Equation 8.2) and Cij (Equation 8.3). In the 2006 IPCC guidelines, it
was explained that the default removal factors for tree biomass (CRW), i.e. 2.9 tonnes C (ha crown cover)-1 yr -1
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). An updated study based on 28 US cities and six US states provides an average removal
factor for tree biomass (CRW) of 2.8 tonnes C (ha crown cover)-1 yr -1 (Nowak et al., 2013), the value is used as
an updated of the global default. Additional removal factors for tree biomass (CRW) of 2.1 t C (ha crown cover) 1
yr-1is based on Canadian study which is adjusted the result of US study mentioned above to their climaticcondition. Countries located in cold temperate and boreal region as well as dry regions may use this lower default
parameter. These removal factors are usually suitable for Tier 2a. The updated Table 8.1 shows updated data andthe range of default CRWij. Values appropriate to national circumstances can also be developed.
Using Tier 2b, the removal factor is Cij. Updated Table 8.2 provides defaults carbon accumulation rates for tree
species classes for use at Tier 2b. These estimates of broad species classes are based on various allometricequations and limited field data from urban areas in the USA and are averages for trees of all sizes (not just mature
trees). Additional default carbon accumulation rates for common tree species in East Asia are based on a Japanesestudy for planted trees in urban parks. Averaged Cij for all trees in city area are almost within the range from 0.005
to 0.01 tonnes C (tree)-1 yr-1. Where large trees are dominant in the city area the upper range value may be used
for Cij, otherwise, the lower range value is used for Cij. Tiers 2a and 2b methods provide biomass estimates for
total combined above-ground and below-ground woody biomass. Additional explanation may be needed aroundhere about new default parameters for Tier 2b. If required below-ground biomass can be estimated separately using
a root: shoot ratio of 0.26 (Cairns et al., 1997). If trees in Settlements are subject to similar or same management
implemented in Forest Land, the updated root: shoot ratio of relevant category in Table 4.4 in Chapter 4, Volume
4 (Forest Land) may also be applied.
For Tiers 2a and 2b, the default assumption for CL 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 CGwood = CLwood.
Countries can define AGP depending on their circumstances.
When kind of perennial crop (e.g. home garden, hedgerows) are allocated in Settlements, countries may estimate
C stock changes based on the estimation method of perennial wood provided in Chapter 5, Volume 4 (Cropland)
by applying the default carbon accumulation ratio provided in Tables 5.1 to 5.4 in Chapter 5, Volume 4 (Cropland).

Other woody perennial types
Countries may, for any perennial type, develop their own values for CRW ij (in Equation 8.2) and Cij (in Equation
8.3). A conservative assumption of no change in any of these components (i.e., CRW ij = 0 and Cij = 0) can also be
applied.

Herbaceous biom ass
Tiers 2a and 2b both assume no change in herbaceous biomass in Settlements Remaining Settlements. Using thismethod, an equation of CGHerbs = CLHerbs is applied. CB is estimated based on the difference between increment
and losses in woody biomass only.

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

SD

SourceGlobal default

2.8

0.45

[1]

Cold temperate and Boreal

2.1

0.34

[2]

RegionReferences[1] Nowak et al., 2013: average of 28 US cities and 6 US states; [2] Pasher J. et al., 2014: study on Canada.

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

Ecological zone

Temperate(native species
in east Asia)

All

Default annual
carbon accumulation
per tree (tonnes C yr1)

SD

SourcesZelkova

0.02040.008[1]Ginkgo0.01030.008[1]

Oak (Quercus myrsinaefolia BLUME)

0.00950.002[1]Camphor tree (Cinnamonum camphora
PRESL)

0.01220.004[1]0.005 – 0.01

0.005[1],[2],[3],[4],[5],[6],[7],[8]Broad species class

Mixed trees at city level

References[1] Tonosaki, 2018; [2] Chaparro and Terradas, 2009; [3] Liu and Li, 2012; [4] Yang et al., 2005; [5] Nowak and Crane, 2002; [6]McPerson, 1998; [7] Vaccari et al. 2013; [8] Paoletti et al., 2011.

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 for lessextensive settlements. If country-specific biomass increment parameters are developed from estimates of biomass
on a dry matter basis, they need conversion to units of carbon using either the default carbon fraction (CF) values
in Table 4.3 in Chapter 4, Volume 4 (Forest land) or a carbon fraction that is more appropriate to the circumstances.
Under higher tiers, the assumptions for CL should be evaluated and modified to better address national
circumstances. For instance, based on national availability of country-specific information, i.e. age-dependent
and/or species-specific carbon losses in settlement trees, countries may estimate a loss factor, documenting theresources and rationale used in its estimation process, or may use country-specific active growing period (AGP).
In this case, it is good practice to use urban vegetation type specific AGP based on detailed categorisation of urban
area with vegetation. This is because management of urban trees are not implemented in an uniformed way, andcarbon accumulation ratio and growing years depend on management type of urban trees/urban area withvegetation, such as street trees, trees in urban park without frequent pruning and/or urban green area treated as
more natural state (Nowak et al., 2013; Chaparro and Terradas, 2009; Jo, 2002).
When countries consider applying data collected in other countries, it is good practice to assess how similar theconditions (climate, urban structure, tree types) are compared to the country from which data originate; where
needed, adjustment may be also applied to resolve dissimilarities. If a country adopts the stock-difference method(Equation 2.8), Chapter 2, Volume 4 and/or applying National Forest Inventory for urban trees, it should haverepresentative sampling and periodic measurement system to estimate the changes in biomass carbon stocks.

8.2.1.3 C HOICE OF ACTIVITY DATA
No refinement.

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Chapter 8: Settlements

8.2.1.4 U NCERTAINTY ASSESSMEN T
No refinement.

8.2.2

Dead organic matterNo refinement.

8.2.3

Soil carbon

No refinement.

8.3

LAND CONVERTED TO SETTLEMENTS

This section provides elaboration on methods.
Land Conversion to Settlements occurs due to expansion of urban area, construction of transportation
infrastructure and other reasons/purposes. Urban extent has been increasing globally over the last three decades(Seto et al. 2011). In areas that are primarily rural, even if land uses are not changing quickly, land devoted toresidential uses can occupy a significant portion of the landscape. Transitions of Forest Land, Cropland, Grassland,
and Wetlands to Settlements can have important impacts on carbon stocks and fluxes (Imhoff et al., 2000; Milesi
et al., 2003).
Estimation of annual greenhouse gas emissions and removals from Land Converted to Settlements includes thefollowing: Estimates of annual change in C stocks from all C pools and sources: Biomass (above-ground and below-ground biomass);
 Dead organic matter (dead wood and litter); Soils (soil organic matter).
 Estimates of non-CO2 gases (CH4, CO, N2O, NOx) from burning of above-ground biomass and dead organic
matter.

8.3.1

Biomass

8.3.1.1 C HOICE OF METH OD
This section provides elaboration on methods.
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 (B_After) and the biomass in the previous category (B_Before).
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(B_Before) and that in the Settlements after conversion (B_After).
In the higher tiers, it is necessary to add growth during the year of inventory (∆C G) and subtract loss (∆CL) to
obtain the net change in carbon stocks on Land Converted to Settlements (Equation 2.15). It should be noted thatgrowing periods of trees, other perennial woody biomass and herbaceous biomass are different. For example, ofthe default assumption in other chapter and sectors, the growing periods is 20 years for tree biomass in Settlements
Remaining Settlements (Tier 2, see section 8.2.1) and land converted to grassland achieve their steady-state ofbiomass during the first year following the conversion (Tier 1 see Section 6.3.1.1, Chapter 6, Volume 4). There isno default for shrubs. When estimate ∆CG, it is good practice to reflect differences on the growing period and/or
carbon density under steady-state for each tree species or vegetation type.

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Tier 1
For Tier 1, in the initial year following conversion to the settlement land use, the most conservative approach is toset B_After to zero, meaning that the process of development of settlements causes carbon stocks to be entirely
depleted. Under Tier 1, estimation of growth during the year of inventory (∆CG) and subtract loss (∆CL) are notnecessary since these estimations are only covered in Equation 2.16, Chapter 2, Volume 4 (for Tier 2) and also
this carbon stock change is not estimated under Tier 1 in Settlements Remaining Settlements. This is a consistent
approach explained in “Step by step method for implementation”.
When potential gains of carbon are expected in Land Converted to Settlements and information on crown coverarea or number of trees in Land Converted to Settlements is available, country can apply the default method ofTier 2 in Settlements Remaining Settlements for estimating ∆CG and ∆CL also for Tier 1.

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 for the estimation of B_Before. At the higher tiers, the area of each land-use or land covertype converted to another type 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 theconversion. Settlement land-use or land cover types are likely to differ in carbon density. For estimations of ∆CGand ∆CL, country can be use country-specific factors. Alternatively, default estimation consistent with Tier 2 inSettlements Remaining Settlements are also possible to be applied. For both cases, the information on crown coverarea or number of trees in Land Converted to Settlements is necessary for estimation.

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 B_After on a country- or biome-specific basis. The method using National Forest Inventory is
also covered by Tier 3. In this case, country should also take into account the guidance of Chapter 4, Volume 4(Forest Land) as appropriate.

8.3.1.2 C HOICE OF EMISSI ON / REMOVAL FACTORSThis section provides elaboration on methods.
This section refines guidance by updating Table 8.4 and provides further explanation for the Tier 2 and Tier 3
guidance. The updated Table 8.4 provides more complete information on how to use B_Before and suggests the useof consistent factors with other chapters’ default factors. The guidance on Tier 2 and Tier 3 are enhanced to clarify
how to choose and use emission/removal factors under higher tiers.
Ti er 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 C ha-1. Updated Table 8.4 provides default values for biomass before conversion(B_Before).

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Chapter 8: Settlements

TABLE 8.4 (UPDATED)DEFAULT BIOMASS CARBON STOCKS REMOVED DUE TO LAND CONVERSION TO SETTLEMENTS
Land-use category1

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

Error range %Forest Land

See Chapter 4, Volume 4, Tables 4.7 to 4.12 for carbon stocks in a rangeof forest types by climate regions. Stocks are in terms of dry matter.
Multiply values by a carbon fraction (CF) in Table 4.3, Chapter 4, Volume
4 consistent with what used in Forest Land estimation to convert dry
matter to carbon.

See Section 4.3,
Chapter 4,
Volume 4 (Land
Converted toForest Land)

Grassland

See Table 6.4, Chapter 6 for carbon stocks in a range of grassland types
by climate regions. Multiply default carbon fraction (CF) 0.47 (forherbaceous biomass for Grassland, see page 6.29, Chapter 6) to convert
dry matter to carbon.

+ 75%

CroplandFor Cropland containing annual crops: Use default of 4.7 tonnes ofcarbon ha-1 or 10 tonnes of dry matter ha-1 (see Updated Table 5-11,
Chapter 5, Volume 4).
For Cropland containing perennial crop: Use carbon stocks in Updated
Table 5.4, Chapter 5, Volume 4, as appropriate.

± 75%

1

The table includes the land-use categories most commonly converted to Settlements. For the remaining land-use categories refer torelevant chapters in Volume 4.

* Note that the condition of forests that are converted to Grassland or Cropland is not likely to be typical of the forest type in general, i.e.
the carbon stocks are probably lower than average (Carter et al., 2017; Puhlick et al., 2017). Specific values for disturbed forest may beappropriate.
#

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

Tiers 2Tier 2 methods replace the default data by country-specific data for B_Before. For calculation of ∆CG and ∆CL,
country country-specific data can be used. The default factors of Tier 2 in Settlement Remaining Settlements may
also be used when country-specific data is not available. In this case, countries should follow the guidance oneither Tier 2A or Tier 2B in Section 8.2.1, Settlements Remaining Settlements, i.e. using the default annual carbon
accumulation ratio provided in Table 8.1 or Table 8.2 for ∆CG and ∆CL considered to be zero noting that all lands
contained in Land Converted to Settlements are within the duration of the default AGP (=20 years).

Tiers 3Tier 3 involves detailed modelling or measurement data relevant to the conversion processes. Countries may use
average biomass stocks data for their estimations in Settlements instead of using carbon accumulation ratio. In thiscase, it may take more than one year to reach the average biomass stocks following land conversion. Countries
should consider the appropriate activity data to reflect the years to reach the average biomass stocks in its
estimation. When countries estimate annual carbon accumulation resulted from the establishment of trees, shrubs
or herbaceous biomass differently, they also need to consider the growing years in each tree or vegetation type.
Each removal factor should be multiplied by the appropriate activity data, i.e. areas under growing years in eachtree or vegetation type.

8.3.1.3

C HOICE OF ACTIVITY DA TAThis section provides an elaboration on methods.
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 ensure complete andconsistent representation of annually converted lands in order to avoid possible omissions or double counting. Datashould be disaggregated according to the general climatic categories and settlements types. For Tier.2 and Tier 3,
data related to green covered area, in land areas converted to Settlements is necessary. Tier 3 inventories will
require more comprehensive information on the establishment of new settlements, with refined soil classes,
climates, and spatial and temporal resolution. All changes having occurred over the number of 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.

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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, Volume 4, are used to estimate land area
will be needed, supplementary surveys may be needed to identify the area of land being converted from Forest
Land to Settlements. As pointed out in Chapter 3, Volume 4, where surveys are being set up, it will often be moreaccurate to seek to establish directly, areas undergoing conversion, than to estimate these from the differences intotal land areas under particular uses at different times.

Step by step method for implementation
Tier 1
Use default values for B_before from respective land-use category chapters (Forest Land, Grassland, etc) and assume
that B_After equals zero in Equation 2.16, Chapter 2, Volume 4.
Step 1: Apply Equation 2.16 , Chapter 2, Volume 4. 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 (the case of using the default assumption for ∆CG and ∆CL) are:
Step 1: Use the methods described in Chapter 3, Volume 4, 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 andthe last area survey.
Step 2: Define — as a first approximation — settlement land-use types on the basis of the proportion of green
area. For instance, three tentative land use classes could be: Low (less than 33percent green space), Medium(from 33 to less than 66percent green space), and High (more than 66percent green space). Each one of thoseclasses can be assigned with an average carbon content, obtained from the species surveyed in similarly definedclasses for accounting 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 B_Before and B_After), apply Equation 2.16, Chapter 2, Volume 4. 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/removalof 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, Chapter 2, Volume 4.
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, Chapter 2, Volume 4.

8.3.1.4 U NCERTAINTY ASSESSMEN T
No refinement.

8.3.2

Dead organic matterNo refinement.

8.3.3

Soil carbon

No refinement.

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Chapter 8: Settlements

8.4

COMPLETENESS, TIME SERIESCONSISTENCY, QA/QC AND REPORTING

No refinement.

8.5

BASIS FOR FUTURE METHODOLOGICALDEVELOPMENT

The section is updated by deletion of the sentences no more relevant.
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, dead wood andlitter);
Discussion of carbon stocks and fluxes from turfgrass and turf 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 the native
condition (i.e., the climate and region in which the settlement is located) and the management regime typicallyapplied in that settled area. Additional data are required before conclusions about the impact of settlement on nonCO2 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 as a loss
from the live biomass term. Because dead wood is likely to be carried off-site in settlements (rather than left onsite to decay as in forests), a more detailed methodology developed in the future might account for the proportionof 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 of which are treatedin 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 et al.,2003), grass decomposes quickly and there is little information about the overall accumulation of biomass in thelonger-lived components of turf biomass. Turfgrass allocation to the above-ground and below-ground components
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 in Settlements, there is currently
no detailed methodology describing carbon removed by turf systems. A more detailed methodology would require
additional information on turf productivity, turfgrass turnover, and allocation to different plant components as it
varies with management regime. Of course, the activity data required to implement this methodology would
include information on management regimes and the proportion of Settlements covered by turfgrass.
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,
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 of carbon
sequestration per unit of tree crown cover is fairly consistent, for example, the overall rate of carbon storage perunit 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 the detailed
methodology could be developed and applied consistently based on those land cover data. This type of land-use
classification would also enable countries to account for changes in carbon storage resulting from managementchanges within areas broadly classified as Settlements. For example, when vacant plots are developed, theadventitious vegetation remaining in the non-built areas might be replaced with landscape species differing inability to store carbon.

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Pouyat, R.V., McDonnell, M.J. and Pickett, S.T.A. (1995). Soil characteristics of oak stands along an urban-ruralland-use gradient. Journal of Environmental Quality 24:516-526.
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