DRAFT

i-Tree Eco Report

PREPARED FOR:
Kevin Frediani

PREPARED BY:
Kevin Frediani -National Trust for Scotland
Annabel Buckland -Treeconomics
Dave Hansford -Treeconomics

CHECKED BY:

Kenton Rogers -Treeconomics

November 2018

Executive Summary
In order to produce this report, the trees and landscape of Inverewe gardens have been assessed. The
immediate surroundings of the house, including car parks and gardens, has been assessed by a complete
inventory of trees. The shelterbelt and woodland on the estate has been assessed using an i-Tree Eco
sample survey, and the moorland included within the wider estate has been assessed using a value transfer
approach.

Trees such as those in Inverewe gardens are generally recognised and appreciated for their amenity, and in
the case of those in the garden, also on how unusual some of the species are. However, society is often
unaware, of the many other benefits (or ecosystem services) which trees provide to us.

The trees within Inverewe gardens improve our air, protect watercourses, save energy, and improve
economic sustainability1 . There are also many health and well-being benefits associated with being in close
proximity to trees and there is a growing research base to support this2 .

Economic valuation of the benefits provided by our natural capital3 can help to mitigate for development
impacts, inform land use changes and reduce any potential impact through planned intervention to avoid a
net loss of natural capital. Such information can be used to help make better management decisions. Yet,
as the benefits provided by such natural capital are often poorly understood, they are often undervalued in
the decision making process.

In order to produce values for some of the benefits provided by the trees of Inverewe, a state of the art,
peer reviewed software system called i-Tree Eco4 (referred to as ‘Eco’ throughout the report) was used.

Highlights Include:
The trees in the Inverewe estate remove over 7,020 kilograms of air-borne pollutants each year and store
over 12,231 tonnes of carbon.

These trees also divert an estimated 27,178 cubic meters of storm water runoff away from the local sewer
systems each year. This is worth £41,211 in avoided stormwater treatment costs.

The total replacement cost of the trees currently stands at £58.9 million.

Just in the gardens surrounding Inverewe house, the amenity value as assessed by the Capital Asset Value
for Amenity Trees (CAVAT) of the trees is calculated to be worth £2,119,280

Table 1 (below) contains the headline figures.

1 Doick et al (2016)

2 http://depts.washington.edu/hhwb/

3 Natural capital can be defined as the world’s stocks of natural assets which include geology, soil, air, water, trees and all living things

4 i-Tree Eco is i-Tree is a suite of open source, peer-reviewed and continuously improved software tools developed by the USDA Forest
Service and collaborators to help urban foresters and planners assess and manage urban tree populations and the benefits they can
provide. i-Tree Eco is one of the tools in the i-Tree suite. It is designed to use complete or sample plot inventories from a study area
along with other local environmental data to: Characterise the structure of the tree population, Quantify some of the environmental
functions it performs in relation to air quality improvement, carbon dioxide reduction, and stormwater control, Assess the value of the
annual benefits derived from these functions as well as the estimated worth of each tree as it exists in the landscape.

I-Tree Eco is adaptable to multiple scales from a single tree to area-wide assessments.
For more information see www.itreetools.org
1
 Complete Inventory Sample Survey
(House and (Shelterbelt and Total all areas
Carparks) Woodland)

Structural Information

Number of
226 110,647 110,873
Trees

Leaf Area 4 hectares 684 hectares 688 hectares

Most Pinus sylvestris,

Pinus contorta, Betula Pinus contorta, Betula
Common Sorbus aucuparia,
pendula, Pinus sylvestris pendula, Pinus sylvestris
Species Pinus muricata

Replacement
£349,458 £58,537,618 £58,887,076
Cost

Species
53 18 62
Recorded
Benefit Values

Carbon 77 metric 12,154 12,231

£18,593 £2,944,051 £2,962,644
Storage tons metric tons metric tons

Pollution 50 6,970 7,020

£79 £11,900 £11,979
Removal kilograms kilograms kilograms

Carbon 2.35 metric 512 metric 514 metric

£569 £123,944 £124,513
Sequestration tons tons tons

26,964 27,178
Avoided 214 cubic
£325 cubic £40,886 cubic £41,211
Runoff metres
metres metres

Total Annual
£973.00 £176,730.00 £177,703.00
Benefits

Table 1: Headline figures.

Total Number of Trees Measured: For further details see the methodology section below.
Leaf Area: The area of ground covered by leaves when viewed from above (not to be confused with Leaf Area Index (LAI) which is the
total surface area of leaves).
Replacement Cost: Value based on the physical resource itself (e.g., the cost of having to replace a tree with a similar tree) using the
Council of Tree and Landscape Appraisers (CTLA) Methodology guidance from the Royal Institute of Chartered Surveyors
Carbon storage: The amount of carbon bound up in the above-ground and below-ground parts of woody vegetation.
Carbon sequestration: The annual removal of carbon dioxide from the air by plants

Carbon storage and carbon sequestration values are calculated based on CO2e and the DECC figures of £66 per metric ton for 2019.
Pollution removal: This value is calculated based on the UK social damage costs for ‘Rural’ and the US externality prices where UK
figures are not available; £0.984 per Kg (carbon monoxide - USEC), £0.01 per kg (ozone - USEC), £7.8153 per Kg (nitrogen dioxide -
UKSDC), £1.953 per Kg (sulphur dioxide - UKSDC), £17.99 per Kg (particulate matter less than 2.5 microns - UKSDC).
Avoided Runoff: Based on the amount of water held in the tree canopy and re-evaporated after the rainfall event. The value is based
on an average volumetric charge of £1.516 per cubic metre and includes the cost of the avoided energy and associated greenhouse
gas emissions in treating the water.
Data processed using i-Tree Eco Version 6.0.13.

2
Methodology
The methodology of this project involves 3 distinct methods of measuring the ecosystem services provided.
In the gardens and car parks, a complete tree inventory has been undertaken, measuring 226 trees in a 5.4
hectare area. This survey collected the following data for each tree:

• Species
• DBH
• Crown Condition
• Total Height
• Crown: Top Height
• Crown: Base Height
• Crown Width (E/W and N/S)
• Crown: % missing
• Crown: Light Exposure
• Building distance and direction

Figure 1: Methodology of tree measurements taken for the i-Tree Eco Survey

In the shelterbelt and woodland, an i-Tree Eco sample survey was completed to estimate the trees and their
benefits in these areas. 8 plots were surveyed in the 10.3 hectares of shelterbelt, and 10 plots in the 91.4
hectares of forest. In this survey, land cover was also measured, including percentage impervious and
percentage shrub cover. Building Distance and direction were not measured in this survey, as there were no
buildings in the area.

The final methods used are value transfer, and recreational valuation of the remainder of the Inverewe
estate. Figure 2 (below) shows the land classifications used in this report for Inverewe.

The inventory data is processed within Eco using the in-built local pollution and climate data to provide the
following results (listed in Table 2 below). Please refer also to Appendix IV for further details on
methodology.

3
 Figure 2: The land cover on the Inverewe Estate. The Shelterbelt, Garden, Carpark and
Woodland are assessed using i-Tree Eco, and the moorland is assessed using value
transfer methodology.

Tree Structure and Composition Species diversity.

Dbh size classes.

Leaf area.

% leaf area by species.

Ecosystem Services Air pollution removal by urban trees for CO, NO₂, SO₂, O₃ and

PM2.5

% of total air pollution removed by trees.

Current carbon storage.

Carbon sequestered.

Stormwater attenuation (Avoided runoff).

i-Tree Eco also calculates oxygen production of trees, this service

is not valued or included in the report.

Structural and Functional values Replacement cost in £.

Amenity value (CAVAT) in £.

Carbon storage value in £.

Carbon sequestration value in £.

Pollution removal value in £.

Avoided runoff in £.

Table 2: Study Outputs

For each category the top ten performing species (based on trees performance rather than their quantity or
size) have been used for charts and tables within this report. However, all other figures for the remaining
species are available within the Eco program files for this project. For a more detailed description of the
model calculations, see Appendix IV. 


4
Results Section

Tree Population Characteristics

Tree Species
The complete survey including the gardens and carparks has expectedly high species diversity (53
species amongst only 226 individual trees), however there is clearly still a reliance on the most common
species, Pinus sylvestris accounting for more than a quarter of all trees (see Figure 3). In the shelterbelt and
woodland, there is much lower species diversity (with only 18 species recorded in over 100,000 individual
trees). There is a strong reliance on the three most common species, Pinus contorta representing one third
of the trees, and Betula pendula and Pinus Sylvestris both also represent large portions (19% and 15%
respectively) of the tree population. Appendix II contains a full list of species included in the inventory.

Scots Pine


26.1%
All Other Species
32.3%

Rowan
8.0%

Beech
2.7%
Cherry
3.1% Bishop Pine
7.5%
Apple
3.5%
Ash Silver Birch
4.0% Birch 4.4%
4.0%
Eucalyptus
4.4%

Figure 3: Percentage Composition of Tree Species (Complete Survey)

5


All Other Species
4.1%

Sessile Oak
1.6%
Pine
1.8% Alder
European Larch 1.1%
2.1%

Rowan
3.9%

Douglas Fir Lodgepole Pine

5.3% 33.7%

Sitka Spruce
12.1%

Scots Pine
15.0%
Silver Birch
19.3%

Figure 4: Percentage Composition of Tree Species (Sample Survey)

6
Tree Diversity
Tree diversity is an important aspect of the tree population to take into account. Tree diversity increases
overall resilience in the face of various environmental stress-inducing factors. Diversity includes both the
individual diversity within a tree species (i.e. genetic diversity) and between different tree species in terms
of different genera or families (e.g. Acer (maple family); Ligustrum (olive family)).

Tree species which originate from more distant regions to each other may be more genetically dissimilar,
their presence may therefore increase resilience to environmental perturbations. A more diverse tree-scape
is better able to deal with possible changes in climate or potential pest and disease impacts. This is
because with more diverse tree populations the likelihood that they all will be vulnerable to a particular
threat is lower and therefore a smaller proportion will be detrimentally affected. The tree population within
Inverewe represents a relatively rich community of trees given the area, with 62 species identified. However,
some of the inventory records provided are at the genus level only, indicating that species richness may
actually be greater than the 62 species provided.

Tree Species from 5 continents are represented in the Gardens (see figure 5 below), which have a much
higher diversity than in the shelterbelt and woodland, which shows only 3 continents (see figure 6 below).

50%

38%

25%

13%

0%
ia

ia

lia

pe

ia

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ic

ic

w
As

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ia

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&
th
or
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Figure 5: Origin of Tree Species (Complete Survey)

7
80%
Shelterbelt
Woodland
Garden and Car Park
60%

40%

20%

0%
pe

ia

+
ic
As

ia

a
ro

er

ic
As
Eu

er
&

Am
&

Am
pe

th
pe
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or

th
ro
Eu

or
N
Eu

N
Figure 6: Origin of Tree Species (Sample Survey)

Note: The + sign indicates that the species is native to more than one continent. For example, Europe & Asia + would
indicate that the species is native to Europe, Asia, and one other continent.


8
 Size Distribution
Size class distribution is also an important aspect to consider in managing a sustainable and diverse tree
population, as this will ensure that there are enough young trees to replace those older specimens that are
eventually lost through old age or disease. In a garden such as this, it is important to maintain younger trees
of established species, to ensure that rare or unusual species are not lost.

In this survey, trees were sized by their stem diameter at breast height (dbh) at 1.3m. Figure 7 and 8
(below) shows the percentage of tree population for the ten most common trees by dbh class for the
complete survey and sample survey.

The chart below represents a fairly typical size class contribution, displaying a negative correlation (with
percentage composition declining as size increases). There is, however, some variation between species. If
new plantings are made up of smaller stature species there will be a definite lack of larger trees in the
future. To maintain or increase canopy cover and tree benefits at or above current levels then more trees
capable of attaining a larger size will need to be planted and cared for in areas where their presence can
be guaranteed to ensure that there is no shortfall in the future.

90%

68%
Percentage of Trees

45%

23%

0%
2

+
5.

2.

0.

8.

5.

3.

1.

8.

6.

3.

1.

9.

.2
-1

-2

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-8

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-9

99
0

.3

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.6

.2

.8

.4

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.7

.3

.9

.5
7.

15

23

30

38

45

53

61

68

76

83

91

Diameter at Breast Height Classes (cm)

Scots Pine Rowan Bishop Pine Silver Birch Eucalyptus
Birch Ash Apple Cherry Beech

Figure 7: Composition (%) of tree population by DBH class (Complete Survey)

9
 100%

75%
Percentage of Trees

50%

25%

0%
2

+
5.

2.

0.

8.

5.

3.

1.

.1
-1

-2

-3

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61
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7.

15

23

30

38

45

53
Diameter at Breast Height Classes (cm)
Lodgepole Pine Silver Birch Scots Pine Sitka Spruce Douglas Fir
Rowan European Larch Pine Sessile Oak Alder

Figure 8: Composition (%) of tree population by DBH class (Sample Survey)

10
 Leaf Area and Population

Leaf area is an important metric because the total photosynthetic area of a trees canopy is directly related
to the amount of benefit provided. The larger the canopy and its surface area, the greater the amount of air
pollution or rainfall which can be held in the canopy of the tree.

Within Inverewe, total leaf area is estimated at 6,884,600m². If all the layers of leaves within the tree
canopies were spread out, they would cover an area over 600 times the size of a football pitch.

The three most dominant species in terms of leaf area are Scots Pine (which has 22.24% of the total leaf
area for all trees), Silver Birch (18.71%) and Lodgepole Pine (14.34%).

Figures 8 and 9 (below) show the top ten dominant trees’ contributions to total leaf area in the complete
survey and sample survey respectively. The top three species in the complete survey account for 38% of
the tree population, and contribute over 40% of the total leaf area. In total the top three species in the
sample survey, representing 68% of the tree population, contribute over 55% of the total leaf area. This is a
significant reliance on three species.

20% 19 30
% of leaf area
26
Leaf Area (as % of total

% of total tree population

Population for all trees

25
for the top 10 trees)

% of the Total Tree

16%
12 20
12%
10
15
8
8% 7
8 6 10
4
4% 4 4 4 3 3 3 4
3 5
2 1 2
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av
Sc

Eu

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C
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al
Sm

Figure 9: Percentage Leaf Area and Population of the Ten Most Dominant Trees (Complete
Survey)

30% 40
% of leaf area
34
Leaf Area (as % of total

Population for all trees

% of total tree population 33
for the top 10 trees)

% of the Total Tree

24% 22
19 27
18%
19 14 20
15 11 11
12% 10 12
13
6% 5 5 4 7
2 2 1 1
1 1 1
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Si
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Figure 10: Percentage Leaf Area and Population of the Ten Most Dominant Trees (Sample Survey)


11
Results - Ecosystem Services Resource
Air Pollution Removal

50kg £60
Pollution (kg) £48
38kg
Value (£)
£36
25kg
£24
13kg £12
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ne

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Figure 11: Value of the pollutants removed and quantity per-annum (Complete Survey)
6000kg £8,000
Pollution (kg) £6,400
4500kg Value (£)
£4,800
3000kg
£3,200
1500kg £1,600
e

ne

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Figure 12: Value of the pollutants removed and quantity per-annum (Sample Survey)

Note: Valuation methods used are UK social damage cost (UKSDC) where they are available - where there are no UK
figures, the US externality cost (USEC) is used as a substitution.

Greater tree cover, pollution concentrations and leaf area are the main factors influencing pollution filtration
and therefore increasing areas of tree planting have been shown to make further improvements to air
quality. Furthermore, because filtering capacity is closely linked to leaf area it is generally the trees with
larger canopy potential that provide the most benefits.

Figures 13 and 14 (below) show the breakdown for the top ten pollution removing tree species in the
Inverewe complete survey and sample survey respectively. As different species can capture different sizes
of particulate matter,5 it is recommended that a broad range of species should be considered for planting in
any air quality strategy.

It is interesting to note that despite being the 2nd most common species, Rowan is only the tenth most
important in air pollution removal. This is likely due to its generally smaller size and leaf area. This illustrates
how large trees provide more benefits than smaller specimens.

5 Freer-Smith et al. 2005

12
 Scots Pine
Bishop Pine
Eucalyptus
Silver Birch
Beech
Cypress
Birch
Common Ash
Ash
Rowan

0 2000 4000 6000 8000 10000

Pollutants Removed (g)
CO O3 NO2 SO2 PM2.5
Figure 13: Pollution removal by tree species (Complete Survey)

Scots Pine
Silver Birch
Lodgepole Pine
Beech
Pine
Sitka Spruce
Douglas Fir
Rowan
Bird Cherry
Sycamore

0 800 1600 2400 3200 4000

Pollutants Removed (g)
CO O3 NO2 SO2 PM2.5

Figure 14: Pollution removal by tree species (Sample Survey) 


13
Carbon Storage
The main driving force behind climate change is the concentration of carbon dioxide (CO2) in the
atmosphere. Trees can help mitigate climate change by storing and sequestering atmospheric carbon as
part of the carbon cycle. Since about 50% of wood by dry weight is comprised of carbon, tree stems and
roots can store up to several tonnes of carbon for decades or even centuries6.

Overall the trees on the Inverewe estate store an estimated 12,231 tonnes of carbon with a value of almost
£3 million.

Figure 15 and 16 (below) illustrate the carbon storage of the top ten tree species in the complete survey
and sample survey respectively.

30t
Tonnes of Carbon Stored

22.5t

15t

7.5t

0t
us

ss

um

h
ne

ss
n

ec

rc

rc

As
re
pt

Pi

re
Pi

Bi

Bi

G
Be
ly

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yp
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gi
er
ca

ot

C
rin
sh

lv
Eu

Sc

ey
Si

gi
Bi

r
te
Ti

on
M
Figure 15: Carbon Storage (tonnes) for top ten tree species (tonne = metric ton, 1000kg)
(Complete Survey)

3000t
Tonnes of Carbon Stored

2250t

1500t

750t

0t
ce

ne

ne

ne

rry
r

h
Fi
rc

ec

or

rc
ru

Pi

Pi

Pi

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La
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an
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dg
Si

ro
Lo

Eu

Figure 16: Carbon Storage (tonnes) for top ten tree species (tonne = metric ton, 1000kg)
(Sample Survey)

6 Kuhns 2008, Mcpherson 2007

14
As trees die and decompose they release this carbon back into the atmosphere. Therefore, the carbon
storage of trees and woodland is an indication of the amount of carbon that could be released if all the trees
died.

Maintaining a healthy tree population will ensure that more carbon is stored than released. Utilising the
timber in long term wood products or to help heat buildings or produce energy will also help to reduce
carbon emissions from other sources, such as power plants.

Species Carbon Storage CO₂ Equivalent Carbon Storage

(tonnes/yr) (tonnes/yr) (£/yr)
Sitka Spruce 2,788.40 10,233.43 £675,406
Scots Pine 2,214.20 8,126.11 £536,324
Lodgepole Pine 2,142.90 7,864.44 £519,053
Silver Birch 1,851.30 6,794.27 £448,422
Beech 1,758.20 6,452.59 £425,871
Pine 476.00 1,746.92 £115,297
Douglas Fir 320.30 1,175.50 £77,583
Sycamore 222.70 817.31 £53,942
Bird Cherry 120.10 440.77 £29,091
European Larch 99.00 363.33 £23,980
All other Species 237.9 873.09 £57,624

Total 12,231 44,887.77 £2,962,593

Table 3: Carbon Storage by Species across the study area (including Complete and
Sample Survey Areas) 


15
Carbon Sequestration
Carbon sequestration is calculated from the predicted growth of the trees based on field measurements of
the tree, climate data and genera specific growth rates within Eco. This provides a measure of tree growth
(converted volume). This volume is then converted into tonnes of carbon based on species specific
conversion factors, it is then converted to CO2 equivalent before then being multiplied by the unit cost for
carbon. The current (2019) UK social cost for carbon is £66 / tonne.

Inverewe’s trees sequester an estimated 514.05 tonnes of carbon per year, with a value of £124,513. Table
4 (below) shows the ten trees that sequester the most carbon per year and the value of the benefit derived
from the sequestration of this atmospheric carbon.

Species Carbon Sequestration CO₂ Equivalent Carbon Sequestration

(tonnes/yr) (tonnes/yr) (£/yr)
Lodgepole Pine 120.53 442.35 £29,195
Silver Birch 106.78 391.88 £25,864
Sitka Spruce 91.13 334.45 £22,074
Scots Pine 74.94 275.03 £18,152
Beech 44.95 164.97 £10,888
Pine 15.18 55.71 £3,677
Douglas Fir 14.19 52.08 £3,437
Bird Cherry 10.64 39.05 £2,577
Rowan 8.99 32.99 £2,178
Sycamore 7.08 25.98 £1,715
All other species 19.06 69.95 £4,617

Total 513.47 1,884.43 £124,373

Table 4: Carbon Sequestration by Species for the Whole Survey Area

Of the tree species inventoried, the Lodgepole Pine store and sequester the most carbon, adding
approximately 120 tonnes in the study year to the current Lodgepole Pine’s carbon storage of 2,143 tonnes.

For comparison, the average newly registered car in the UK produces 34.3g carbon per km7 . Carbon
sequestration in Inverewe’s trees therefore corresponds to nearly 15,000 ‘new’ vehicle km per year.

7 http://naei.beis.gov.uk/data/emission-factors
https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/454981/veh0150.csv/preview
16
 Avoided Runoff
Surface runoff can be a cause for concern in many areas as it can contribute to flooding and is a source of
pollution in streams, wetlands, waterways, lakes and oceans. During precipitation events, a portion of the
precipitation is intercepted by vegetation (trees and shrubs) while the remainder reaches the ground.
Precipitation that reaches the ground and does not infiltrate into the soil becomes surface runoff8.

Annual avoided surface runoff in Eco is calculated based on rainfall interception by vegetation, specifically
the difference between annual runoff with and without vegetation. The trees within Inverewe estate reduce
runoff by an estimated 27,178 m³ a year with an associated value of £41,211.

Figures 17 and 18 (below) shows the volumes and values for the ten most important species for reducing
runoff.

50 £70
Amount
Value
40
Avoided Runoff m³

£53
30
£35
20
£18
10

0 £0
ne

us

ss

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ne

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pt
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Pi

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ca
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ve
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Eu
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om
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ea
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C
lL
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Sm

Figure 17: Avoided runoff by top ten species (Complete Survey)

6000 £10,000
Amount
Value
Avoided Runoff m³

4800
£7,500
3600
£5,000
2400
£2,500
1200

0 £0
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ne

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Br
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Si
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Figure 18: Avoided runoff by top ten species (Sample Survey)

The trees in Inverewe play an important role in reducing runoff: The Scots Pine intercepts the largest
proportion of the precipitation for a species, and is, by a considerable margin, the most important species
in this category. This is due to the trees’ population, canopy size and leaf morphology


8 Hirabayashi 2012
17
 Replacement Cost
In addition to estimating the environmental benefits provided by trees Eco also provides a structural
valuation which in the UK is termed the ‘Replacement Cost’. It must be stressed that the way in which this
value is calculated means that it does not constitute a benefit provided by the trees. The valuation is a
depreciated replacement cost, based on the Council of Tree and Landscape Appraisers (CTLA) formulae9.

Replacement Cost is intended to provide a useful management tool, as it is able to value what it might cost
to replace any or all of the trees (taking account of species suitability, depreciation and other economic
considerations) should they become damaged or diseased for instance. The replacement costs for the ten
most valuable tree species are shown in Figure 19, below.

The total value of all trees in the study area as estimated by Eco currently stands at £59.2 million. Sitka
Spruce is the most valuable species of tree, on account of both its size and population, followed by Scots
Pine and Lodgepole Pine. These three species account for £39.6 million (67%) of the total replacement cost
of the trees in Bexley's tree inventory, with the sitka spruce alone accounting for 23% of the total structural
value.

A full list of trees with the associated replacement cost is given in Appendix III.

Sitka Spruce £13,750,801

Scots Pine £13,068,259

Lodgepole Pine £12,830,131

Beech £6,435,076

Silver Birch £5,729,854

Pine £3,070,464

Douglas Fir £1,506,108

Sycamore £798,789

Rowan £446,682

Bird Cherry £383,127

£0.00 £3,500,000.00 £7,000,000.00 £10,500,000.00 £14,000,000.00

Figure 19: Replacement Cost for top ten trees (Whole Study Area)

9 Hollis, 2007
18
CAVAT - The amenity value of trees
Capital Asset Valuation for Amenity Trees (CAVAT) is a method developed in the UK to provide a value for
the public amenity that trees provide. The CTLA valuation method does not take into account the health or
amenity value of trees, and is a management tool rather than a benefit valuation.

Particular differences to the CTLA valuation include the Community Tree Index (CTI) value, which adjusts
the CAVAT assessment to take account of the greater benefits of trees in areas of higher population density,
using official population figures. CAVAT allows the value of Inverewe’s trees to include a social dimension by
valuing the visual accessibility and prominence within the estate.

The Complete Inventory only included within this estimation of amenity value. The CTI value has been
assumed at 100%, Access at 100%, and SULE at 60%. Table 5 shows the all assumptions made in the
CAVAT valuation

Factor Assumption

CTI 1.00
Access 1.00
SULE 0.60
Excellent = 0%, Good = 20%, Fair = 40%,
Canopy Missing
Poor = 60% and Dying = 100%

Table 5: The assumptions made to calculate amenity value using CAVAT

The final CAVAT valuation of the complete survey (Gardens and Car Parks) of Inverewe, came to
£2,119,279.18 for the 226 trees included in the survey.

Table 6, below, shows the top ten highest CAVAT valued trees. It is possible to see here that the CAVAT
value is not directly related to the percent of total population or replacement cost.

Species CAVAT Value (£) Percent of Replacement Cost

Total (£)
Population
Pinus muricata £493,536 7.49 £94,922
Pinus sylvestris £480,194 25.99 £84,998
Eucalyptus £315,921 4.41 £43,958
Fagus sylvatica £116,243 2.64 £21,582
Cupressus £113,633 1.76 £18,212
Betula pendula £80,688 4.41 £12,392
Betula £71,218 3.96 £12,456
Fraxinus £37,061 3.96 £7,321
Tilia cordata £25,398 0.88 £4,115
Laburnum alpinum £21,956 2.64 £1,780

Table 6: The ten species with the highest CAVAT valuation 


19
Valuing Inverewe’s Moorland
Methodology:
Using a number of different sources, it is possible to place a value on the moorland of Inverewe estate.
There are a number of methods that can be employed for this, and in this case a value transfer method has
been used. There has not been a direct valuation of the moorland surrounding Inverewe, and so estimations
of the ecosystem services have been calculated based on measurements of the peatland that were
available.

In terms of ecosystem services, this report deals with the regulating services of peatland, and does not
specifically value the provisioning, supporting or cultural services the peatland provides.

Known Information:
Inverewe contains 378 hectares of peatland (Source: Survey of peat deposits on NTS properties, Lindsay
Buchanan, Jan 2014).

The peatland depth ranges between 0-200cm (Source: Inverewe Peatland Report), averaging across 5
locations to 81cm.

Table 1 shows the 5 areas surveyed in this report and the depth of peat measured with them. (Source:
‘Inverewe Peatland Report’).

Using this information the volume of peat across the landscape of inverewe can be estimated at 3,061,800
m3 (3,061,800,000,000 cm3).

Area Grid Reference Size of Area Depth of Peat Average Depth

(range) (cm)

Polygon 001 NG 867823 0.58 50 cm approx 50

Polygon 006 NG 869820 0.77 50cm 50

Polygon 013 NG 874824 3.60 50 to 90 cm 70

Individual Grips Various locations 0.74 0-170cm 85

Polygon 003 NG 852835 5.76 100-200 cm 150

AVERAGE 81

Table 7: Information from ‘Inverewe Peatland Report’ and the calculation of Average Peat
Depth across Inverewe.

20
Carbon Storage:
Therefore, this known information can be applied to measurement of soil carbon storage in peatland to
estimate the current carbon storage of Inverewe’s peatland.

Table 2 shows the results of this application using a number of different sources. For comparison, the per
hectare value of carbon storage for the woodland and shelterbelt of Inverewe has been measured in this
report at £28,863.

The values recommended to estimate the carbon storage value of Inverewe’s Peatland using the value of 47
kg/m3 (highlighted in Light Blue in Table 8).

Reference Title Carbon Carbon Carbon Carbon Value for the

Measure Storage Storage in Storage in Inverewe
Value per Inverewe Inverewe Estate (£)
Hectare (tC) (tCO2e)
(£)
37.5, 23.9, 35.5
Carbon
mg/cm3
Accumulation
(based on the
and C/N
Anderson depths provided
ratios of Peat £62,382 98896.14 362948.83 £23,954,623
(2002) in ‘Inverewe
Bogs in
Peatland
North-west
Report’) Average
Scotland
of 32.3 mg/cm3
Mapping soil
carbon
stocks across
Aitkenhead and Scotland
631200 kg/ha £150,500 238,593.60 875,638.51 £57,792,142
Coull (2015) using a
neutral
network
model
Carbon in the
Vegetation
Milne and
and Soils of 47 kg/m3 £90,772 143,904.60 528,129.88 £34,856,572
Brown (1995)
the Great
Britain
Lindsay (2010) Peatbogs
(referenced in and Carbon:
47 kg/m3 £90,772 143,904.60 528,129.88 £34,856,572
Nature.scot and A Critical
nts.org Synthesis
Average £98,607 156,324.74 573,711.78 £37,864,977

Table 8: Carbon Storage in the Peatland of Inverewe

21
Carbon Sequestration:
The calculations for carbon sequestration followed the same basic principles as those for carbon storage.

Table 3 shows the results for carbon sequestration in Inverewe’s peatland. For the sake of comparison, the
value of carbon sequestration by the woodland and shelterbelt is £1,215 per hectare.

Reference Title Carbon Seq. Carbon Carbon Carbon Annual Value

Measure Seq. Seq. for Seq. for (£)
Value per Inverewe Inverewe
hectare (tC) (tCO2e)
(£)
Management
of Carbon-
Scottish 250-300kg per
rich Soils -
Government hectare per year £67 103.95 381.50 £25,179
Overview and
(n.d.) (275kg)
Discussion
Paper
Carbon Min: 14g per m2
£34 52.92 194.22 £12,818
Sequestratio per year
n in Peatland:
Belyea and patterns and
Malmer (2004) mechanisms Max: 72 g per
in response £174 272.16 998.83 £65,923
m2 per year
to climate
change
Average £92 143.01 524.85 £34,640

Table 3: Carbon Sequestration by the Peatland of Inverewe

The values reported above for carbon sequestration are assuming that the peatland surrounding Inverewe
are pristine, however we know this is not the case. Degraded peatland is often reported as being a source
of carbon, rather than a sink. In the future, further work would be beneficial to explore the specific carbon
sequestration or emissions of Inverewe’s Peatland, and therefore put a more accurate value on the annual
benefits. In this case to mitigate for this potential overestimation of benefits, we have chosen the lowest
carbon sequestration value for carbon in peatland.

Peatlands additionally provide numerous other services, including flood risk mitigation, water quality
regulation, removal of air pollution, provision of recreational services, and biodiversity benefits. These are
not considered in here, and would be expected to add great value to the Inverewe’s Natural Capital
assessment. In future, by estimating these, a more complete picture of the value of Inverewe’s peatland
could be formed.

22
Discussion of Peatland Value
The comparison of the carbon storage and carbon sequestration of the 378 hectares of peat to the 102
hectares of woodland and shelterbelt two distinct differences should be noted.

The carbon storage of the peatland is significantly higher than that of the woodland. There are a number of
reasons for this, the most prominent being that the peatland has been forming over many thousands of
years, and the woodland is comparatively very new. This means that there has been a huge amount of time
for the carbon to be sequestered and stored in comparison to the woodland and shelterbelt.
Additionally, the measure of carbon storage for the woodland only includes the carbon stored in the trees,
and therefore does not include soil carbon which would add significantly to the carbon stocks of the
woodland and shelterbelt. The peatland measurements also do not include the carbon which is stored in
the vegetation. This is worth taking into account when comparing the two ecosystems in terms of the
carbon storage, that in this brief assessment not all faucets of the carbon storage of Inverewe estate have
been fully explored.

The other visible patterns is that the carbon sequestration of the peatland is much lower per hectare than
the woodland. Trees sequester carbon more quickly than the vegetation associated with peatland. an
interesting consideration to come out of this is that the combination of the carbon storage in peatland, and
the carbon sequestration of trees could be a very effective method of maintaining and enhancing the
carbon storage. This would be dependant on any planting on peatlands being done in a way that maintains
the carbon stocks in peat, and allowed sufficient growth by trees to sequester carbon at a reasonable rate.
Species selection would have to be done very carefully to ensure that this delicate balance could be
achieved.

23
Conclusions and Recommendations
To Discuss with Kevin

24
Appendix I. Relative Tree Effects
The trees in Inverewe provide benefits that include carbon storage and sequestration and air pollutant
removal. To estimate the relative value of these benefits, tree benefits were compared to estimates of
average carbon emissions and average family car emissions. These figures should be treated as a
guideline only as they are largely based on US values (see footnotes).

Carbon storage is equivalent to:

• Annual carbon emissions from 9,450 family cars

• Annual carbon emissions from 3905 homes

Nitrogen dioxide removal is equivalent to:

• Annual nitrogen dioxide emissions from 145 family cars

• Annual nitrogen dioxide emissions from 65 homes

Sulphur dioxide removal is equivalent to:

• Annual sulphur dioxide emissions from 6,208 family cars

• Annual sulphur dioxide emissions from 16 homes

Annual carbon sequestration is equivalent to: 


• Annual carbon emissions from 400 family cars

• Annual carbon emissions from 200 family cars

Average passenger automobile emissions per mile were based on dividing total 2002 pollutant emissions from light-duty
gas vehicles (National Emission Trends http://www.epa.gov/ttn/chief/trends/index.html) divided by total miles driven in
2002 by passenger cars (National Transportation Statistics http://www.bts.gov/publications/
national_transportation_statistics/2004/).

Average annual passenger automobile emissions per vehicle were based on dividing total 2002 pollutant emissions from
light-duty gas vehicles by total number of passenger cars in 2002 (National Transportation Statistics http://www.bts.gov/
publications/national_transportation_statistics/2004/).

Carbon dioxide emissions from automobile assumed six pounds of carbon per gallon of gasoline if energy costs of



refinement and transportation are included (Graham, R.L., Wright, L.L., and Turhollow, A.F. 1992. The potential for short-
rotation woody crops to reduce U.S. CO2 Emissions. Climatic Change 22:223-238).

25
Appendix II. Species Dominance Ranking List
Dominance value is based on the combination of leaf area and tree population and gives a much better
idea of the tree species dominance in the landscape than on tree numbers or leaf area alone. 

Complete Survey
Species Percent Population Percent Leaf Area Dominance Value

Pinus sylvestris 26.10 19.00 45.10

Pinus muricata 7.50 12.30 19.90

Eucalyptus 4.40 9.80 14.20

Betula pendula 4.40 7.60 12.00

Sorbus aucuparia 8.00 2.10 10.00

Fagus sylvatica 2.70 7.20 9.90

Betula 4.00 4.20 8.20

Cupressus 1.80 5.70 7.50

Fraxinus 4.00 2.80 6.70

Fraxinus excelsior 1.80 3.30 5.10

Prunus 3.10 1.60 4.70

Laburnum alpinum 2.70 1.70 4.40

Tilia cordata 0.90 3.40 4.30

Malus 3.50 0.60 4.10

Fagus 0.90 1.90 2.80

Cupressus macrocarpa aurea 0.40 1.80 2.20

Olea 1.30 0.80 2.10

Quercus 1.30 0.60 2.00

Eucalyptus macrocarpa 1.30 0.50 1.80

Ulmus minor 0.40 1.30 1.80

Nothofagus antarctica 0.90 0.90 1.80

Aesculus hippocastanum 0.90 0.90 1.80

Prunus vulgaris 1.30 0.30 1.70

Chamaerops 1.30 0.10 1.50

Eucalyptus delegatensis 0.40 1.00 1.40

Ulmus glabra 0.90 0.50 1.40

Acer pseudoplatanus 0.90 0.40 1.30

Eucalyptus glaucescens 0.40 0.80 1.30

Ilex aquifolium 0.90 0.40 1.20

26
Species Percent Population Percent Leaf Area Dominance Value

Pyrus 0.90 0.30 1.20

Ulmus procera 0.90 0.20 1.00

Ilex 0.40 0.50 1.00

Chamaecyparis lawsoniana 0.40 0.50 1.00

Prunus avium 0.40 0.50 0.90

Quercus robur 0.40 0.50 0.90

Acer pseudoplatanus 'Spaethii' 0.40 0.40 0.90

Prunus yedoensis 0.40 0.40 0.80

Leptospermum 0.40 0.40 0.80

Acer 0.40 0.40 0.80

Sorbus commixta 0.40 0.30 0.80

Pinus 0.40 0.30 0.80

Griselinia 0.40 0.30 0.70

Sorbus aria 0.40 0.20 0.70

Populus canescens 0.40 0.20 0.70

Crataegus crus-galli 0.40 0.20 0.70

Prunus padus 0.40 0.20 0.60

Betula costata 0.40 0.20 0.60

Crataegus 0.40 0.10 0.60

Quercus/live ilex 0.40 0.10 0.60

Acer palmatum 0.40 0.10 0.50

Thuja occidentalis 0.40 0.10 0.50

Elaeis 0.40 0.00 0.50

Tilia x europaea 0.40 0.00 0.50

27
Sample Survey
Species Percent Population Percent Leaf Area Dominance Value

Pinus contorta 33.70 14.30 48.10

Betula pendula 19.30 18.70 38.00

Pinus sylvestris 15.00 22.20 37.30

Picea sitchensis 12.10 9.80 22.00

Pinus 1.80 11.10 12.90

Fagus sylvatica 0.80 11.10 11.80

Pseudotsuga menziesii 5.30 5.10 10.40

Sorbus aucuparia 3.90 2.10 6.00

Larix decidua 2.10 1.10 3.20

Prunus padus 1.10 1.30 2.40

Quercus petraea 1.60 0.50 2.00

Acer pseudoplatanus 0.50 1.20 1.80

Picea 0.70 0.70 1.40

Alnus glutinosa 1.10 0.30 1.30

Corylus avellana 0.50 0.20 0.70

Ilex aquifolium 0.20 0.10 0.30

Pinus nigra ssp. salzmannii 0.10 0.10 0.20

Betula 0.10 0.00 0.20

28
Appendix III. Tree Values by Species
Species Trees Carbon Gross Avoided Pollution Replacement
Storage Carbon Runoff Removal Cost
(Tonnes) Seq (m3/Yr) (Tonne/Yr) (£)
(Tonnes/Yr)

Picea sitchensis 13407.00 2788.43 91.13 2653.60 0.69 13750801.27

Pinus sylvestris 16676.00 2214.25 74.94 6037.77 1.56 13068259.46

Pinus contorta 37306.00 2142.92 120.53 3866.52 1.00 12830131.11

Fagus sylvatica 852.00 1758.20 44.95 2999.88 0.77 6435075.51

Betula pendula 21405.00 1851.37 106.78 5060.64 1.30 5729854.03

Pinus 2012.00 476.01 15.18 2999.95 0.78 3070464.17

Pseudotsuga 5829.00 320.28 14.19 1378.91 0.36 1506108.34

menziesii

Acer 585.00 222.67 7.08 331.39 0.09 798788.83

pseudoplatanus

Sorbus 4361.00 78.57 8.99 572.89 0.15 446682.13

aucuparia

Larix decidua 2332.00 98.98 6.55 307.40 0.08 218874.78

Quercus petraea 1749.00 27.97 4.39 122.59 0.03 142630.34

Alnus glutinosa 1166.00 36.00 3.57 74.19 0.02 122333.15

Pinus muricata 17.00 11.87 0.25 26.47 0.01 94921.80

Picea 788.00 25.92 1.85 187.09 0.05 59803.06

Corylus avellana 583.00 4.11 0.78 46.02 0.01 53008.21

Eucalyptus 10.00 21.82 0.37 20.96 0.01 43958.06

Betula 140.00 7.42 0.47 18.09 >0.01 24403.24

Ilex aquifolium 265.00 2.94 0.38 14.56 >0.01 21897.61

Cupressus 4 3.76 0.07 12.20 >0.01 18212.33

Pinus nigra ssp. 131 2.92 0.18 17.51 >0.01 13208.47

salzmannii

Fraxinus 9 1.93 0.07 5.90 >0.01 7321.11

Cupressus 1 1.08 0.02 3.83 >0.01 5579.90
macrocarpa
aurea

Eucalyptus 1 2.19 0.05 1.81 >0.01 4521.01

glaucescens

Tilia cordata 2 0.52 0.03 7.28 >0.01 4114.98

Fraxinus 4 0.62 0.04 7.08 >0.01 3151.73

excelsior

Fagus 2 0.63 0.04 4.15 >0.01 2362.25

Malus 8 0.50 0.05 1.26 >0.01 2132.93

29
Species Trees Carbon Gross Avoided Pollution Replacement
Storage Carbon Runoff Removal Cost
(Tonnes) Seq (m3/Yr) (Tonne/Yr) (£)
(Tonnes/Yr)

Chamaerops 3 0.01 >0.01 0.29 >0.01 2075.20

Laburnum 6 0.58 0.05 3.74 >0.01 1780.04
alpinum

Olea 3 0.49 0.03 1.63 >0.01 1670.03

Leptospermum 1 0.51 0.01 0.81 >0.01 1530.52

Eucalyptus 1 0.43 0.02 2.07 >0.01 1418.13

delegatensis

Eucalyptus 3 0.52 0.03 1.04 >0.01 1407.56

macrocarpa

Nothofagus 2 0.39 0.02 1.91 >0.01 1364.67

antarctica

Prunus 7 0.52 0.05 3.49 >0.01 1345.04

Griselinia 1 0.46 0.01 0.59 >0.01 1235.64

Ilex 1 0.22 0.02 1.14 >0.01 1035.09

Ulmus procera 2 0.42 0.02 0.34 >0.01 1012.07

Prunus avium 1 0.27 0.01 0.98 >0.01 920.12

Aesculus 2 0.24 0.02 1.90 >0.01 889.09

hippocastanum

Chamaecyparis 1 0.13 0.01 1.13 >0.01 835.94

lawsoniana

Prunus vulgaris 3 0.23 0.03 0.72 >0.01 736.51

Quercus/live ilex 1 0.21 0.01 0.26 >0.01 691.59

Elaeis 1 >0.01 >0.01 0.06 >0.01 661.43

Prunus 1 0.25 0.01 0.86 >0.01 646.94
yedoensis

Ulmus minor 1 0.24 0.02 2.89 >0.01 621.65

Acer 1 0.17 0.01 0.76 >0.01 527.68

Acer 1 0.14 0.01 0.94 >0.01 390.68

pseudoplatanus
'Spaethii'

Tilia x europaea 1 0.08 >0.01 0.03 >0.01 359.42

Sorbus aria 1 0.11 0.01 0.50 >0.01 326.46

Quercus robur 1 0.12 0.01 0.97 >0.01 300.34

Quercus 3 0.10 0.01 1.38 >0.01 294.30

Prunus padus 1167 120.07 10.64 363.54 >0.01 265.10

Ulmus glabra 2 0.10 0.01 1.02 >0.01 239.49

30
Species Trees Carbon Gross Avoided Pollution Replacement
Storage Carbon Runoff Removal Cost
(Tonnes) Seq (m3/Yr) (Tonne/Yr) (£)
(Tonnes/Yr)

Pyrus 2 0.05 0.01 0.70 >0.01 198.11

Sorbus 1 0.07 0.01 0.74 >0.01 178.73
commixta

Populus 1 0.05 >0.01 0.46 >0.01 144.78

canescens

Crataegus 1 0.06 >0.01 0.28 >0.01 143.27

Betula costata 1 0.04 >0.01 0.36 >0.01 103.60

Acer palmatum 1 0.03 >0.01 0.14 >0.01 93.75

Thuja 1 0.02 >0.01 0.14 >0.01 88.34

occidentalis

Crataegus crus- 1 0.02 >0.01 0.45 >0.01 82.69

galli

Total 110872 12231.23 514.02 27178.20 6.91 58504213.81

31
i-Tree
i-Tree Eco is designed to use standardised field data and local hourly air pollution and meteorological data
to quantify forest structure and its numerous effects, including:

• Forest structure (e.g., species composition, tree health, leaf area, etc.). 


• Amount of pollution removed hourly by trees, and its associated percent air
quality improvement throughout a year. Pollution removal is calculated for
ozone, sulphur dioxide, nitrogen dioxide, carbon monoxide and particulate matter (<2.5
microns). 


• Total carbon stored and net carbon annually sequestered by trees. 


• Effects of trees on building energy use and consequent effects on carbon

dioxide emissions from power plants. 


• Structural value of the forest, as well as the value for air pollution removal
and carbon storage and sequestration. 


• Potential impact of infestations by pests, such as Asian Longhorned beetle,

emerald ash borer, gypsy moth, and Dutch elm disease.



To calculate current carbon storage, biomass for each tree was calculated using equations from the
literature and measured tree data. Open-grown, maintained trees tend to have less biomass than predicted
by forest-derived biomass equations10. To adjust for this difference, biomass results for open-grown urban
trees were multiplied by 0.8. No adjustment was made for trees found in natural stand conditions. Tree dry-
weight biomass was converted to stored carbon by multiplying by 0.5.

To estimate the gross amount of carbon sequestered annually, average diameter growth from the
appropriate genera and diameter class and tree condition was added to the existing tree diameter (year x)
to estimate tree diameter and carbon storage in year x+1.

The amount of oxygen produced is estimated from carbon sequestration based on atomic weights: net O2
release (kg/yr) = net C sequestration (kg/yr) × 32/12. To estimate the net carbon sequestration rate, the
amount of carbon sequestered as a result of tree growth is reduced by the amount lost resulting from tree
mortality. Thus, net carbon sequestration and net annual oxygen production of trees account for
decomposition11.

Recent updates (2011) to air quality modelling are based on improved leaf area index simulations, weather
and pollution processing and interpolation, and updated pollutant monetary values.

Air pollution removal estimates are derived from calculated hourly tree-canopy resistances for ozone, and
sulphur and nitrogen dioxides based on a hybrid of big-leaf and multi-layer canopy deposition models12 . As
the removal of carbon monoxide and particulate matter by vegetation is not directly related to transpiration,
removal rates (deposition velocities) for these pollutants were based on average measured values from the
literature13 14 that were adjusted depending on leaf phenology and leaf area. Particulate removal
incorporated a 50 percent resuspension rate of particles back to the atmosphere15 .Annual avoided surface

10 Nowak 1994

11 Nowak, David J., Hoehn, R., and Crane, D. 2007.

12 Baldocchi 1987, 1988

13 Bidwell and Fraser 1972

14 Lovett 1994

15 Zinke 1967
32
runoff is calculated based on rainfall interception by vegetation, specifically the difference between annual
runoff with and without vegetation. Although tree leaves, branches and bark may intercept precipitation and
thus mitigate surface runoff, only the precipitation intercepted by leaves is accounted for in this analysis.
The value of avoided runoff is based on estimated or user-defined local values. As the local values include
the cost of treating the water as part of a combined sewage system the lower, national average externality
value for the United States is utilised and converted to local currency with user-defined exchange rates.

Replacement Costs were based on valuation procedures of the Council of Tree and Landscape Appraisers,
which uses tree species, diameter, condition and location information16 17.

For a full review of the model see UFORE (2010) and Nowak and Crane (2000).
For UK implementation see Rogers et al (2014).
Full citation details are located in the bibliography section

16 Hollis, 2007

17 Rogers et al (2012)
33
CAVAT
An amended CAVAT method was chosen to assess the trees in this study, in conjunction with the CAVAT
steering group (as done with previous i-Tree Eco studies in the UK).
In calculating CAVAT the following data sets are required:

• The current Unit Value,

• Diameter at Breast Height (DBH),
• The CTI (Community Tree Index) rating, reflecting local population density
• An assessment of accessibility,
• An assessment of overall functionality, (that is the health and completeness of the crown of the tree);
• An assessment of Safe Life Expectancy.

The current Unit Value is determined by the CAVAT steering group and is currently set at £15.88 (LTOA
2012).

DBH is taken directly from the field measurements.

The CTI rating is determined from the approved list (LTOA, 2012) and is calculated on a borough by
borough basis. The CTI for Bexley is 1.25, thereby increasing the basic CAVAT value.

Accessibility, i.e. the ability of the public to benefit from the amenity value of trees, was generally judged to
be 100% for trees in Parks, street trees and other open areas, and was generally reduced for residential
areas and transportation networks to 60% (increased to 100% if the tree was on the street), to 80% on
institutional land uses and to 40% on Agricultural plots. For this study, park trees and street trees only were
included, with 100% accessibility therefore assumed.

As there was no condition assessment taken into account with this inventory, we assumed the overall
functionality of the trees at 80%. This therefore may not be fully accurate, especially for each individual tree.

Safe Life Expectancy assessment was intended to be as realistic as possible, but based on existing
circumstances. For the purposes of this study, SULE was applied at 80% of the optimal for all trees, as
public trees will have reduced life expectancy compared with the same tree in its natural setting. No SULE
data was supplied with the inventory. For full details of the method refer to LTOA (2010).

34
Bibliography

landscape%20trees%20and%20global%20warmi
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