Southwark Borough Council i-Tree Eco Stratified Inventory Report

Of Southwark’s Public Trees

December 2019

Forest Research The Authors

Danielle Hill - Treeconomics James Watson - Treeconomics

Reviewed By:

Kenton Rogers - Treeconomics Keith Sacre - Treeconomics Kieron Doick - Forest Research Annabel Buckland - Forest Research

Southwark Council

This assessment was carried out by Treeconomics

1 Executive Summary

In this report, the trees managed by Southwark Borough Council have been assessed based on a range of benefits that they provide to society. These trees, which form part of Southwark’s natural capital, are generally recognised and appreciated for their amenity, presence and stature in the cityscape. However, society is often unaware of the many other benefits, known as ecosystem services, that trees provide to those living in our towns and cities.

The trees in and around our urban areas (together with shrubs, hedges, open grass, green space and wetland) are collectively known as the ‘urban forest’. This urban forest improves our air through removing pollutants, protects watercourses, saves energy, and improves 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.

Southwark’s publicly managed trees are a crucial part of the city’s urban forest. Many of the benefits that Southwark’s urban forest provides are offered through its public trees.

Economic valuation of the benefits provided by our natural capital3 (including the urban forest) 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 Southwark’s publicly managed trees, a state of the art, peer reviewed software system called i-Tree Eco4 (referred to as ‘Eco’ throughout the report) was used. This is a partial analysis as not all trees or ecosystem services were quantified or valued. Therefore the figures presented in this report should be regarded as a conservative estimate.

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 2 Highlights:

• The trees managed by Southwark Borough Council remove over 21 tonnes of air-borne pollutants each year and store over 57,000 tonnes of carbon. • These trees divert over 35,000 cubic meters of storm water runoff away from the local sewer systems each year. This is worth an estimated £21,183 each year in avoided stormwater treatment costs. • The total replacement cost of all public trees in Southwark currently stands at £165,854,112.

Southwark Public Tree Inventory - Headline Figures

Number of Trees Measured 102,426

Most Common Tree Species Fraxinus excelsior, Acer pseudoplatanus, Platanus x acerifolia

Replacement Cost £165,854,112

CAVAT Valuation £2,629,973,096

Species Recorded 323

Amounts and Values - Trees

Pollution Removal 21 tonnes £135,395

Carbon Storage 57,269 tonnes £14,070,429

Carbon Sequestration 986 tonnes £242,334

Avoided Runoff 35,411 m³ £21,183

Total Annual Benefits £398,912

Table 1: Headline figures

Total Number of Trees Measured: Not all records supplied were used in the analysis. 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). This is not the total canopy cover for Southwark as only the inventoried trees are included in the analysis and some tree canopy dimensions were conservatively estimated. Capital Asset Value for Amenity Trees (CAVAT): A valuation method developed in the UK to express a tree’s relative contribution to public amenity and its prominence in the urban landscape. For this study, the ‘Quick Method’ has been applied. 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 £67 per metric ton for 2019. Pollution removal: This value is calculated based on the UK social damage costs for ‘Transport Inner London’ and the US externality prices where UK figures are not available; £0.98 per kg (carbon monoxide - USEC), £25.37 per kg (ozone - USEC), £58.97 per kg (nitrogen dioxide - UKSDC), £6.27 per kg (sulphur dioxide - UKSDC), £1,132.78 per kg (particulate matter less than 2.5 microns - UKSDC). Values calculated using an exchange rate of $0.75 = £1.00. Avoided Runoff: Based on the amount of water held in the tree canopy and re-evaporated after the rainfall event. The value is calculated using Thames Water 2019/2020 volumetric charge of £0.5982 per cubic metre. It includes the cost of the avoided energy and associated greenhouse gas emissions in treating the water.

Data processed using i-Tree Eco Version 6.0.16.

3 Methodology

Southwark’s tree inventory (which contained 55,076 records and included tree groups that were duplicated into individual records) was provided by Southwark Borough Council. Amongst the data collected were tree species, diameter at breast height (dbh), tree height, tree condition and tree location.

The minimum data required by Eco is tree species and dbh. However, the more data that is available for each tree, the more accurate the outputs will be. In this case, 23 records had to be removed due to insufficient data for processing. Reasons for removal included no dbh or no species. The Eco software requires data to be a value greater than 0 for all the structural data of each tree. Where required, estimates were made based on the information available. Of the original 55,076 records, 55,053 were suitable for import and processing. Woodland data were also added to the dataset for processing using the most common species and average tree measurements. In total, 102,426 records were processed.

The inventory data were processed within Eco using the in-built local pollution and climate data from 2013 and the Northolt weather station to provide the following results (listed in Table 2 below). Refer also to Appendix IV for further details on 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 but this service is not valued. Structural and Functional values Replacement Cost in £. Carbon storage value in £. Carbon sequestration value in £. Pollution removal value in £. Avoided runoff in £ Amenity value £

Table 2: Study Outputs.

For each category, the top ten species (based on tree performance rather than their quantity or size) were used for charts and tables within this report. However, all other figures for the remaining 313 4 species are available within the Eco files for this project. For a more detailed description of the model calculations see Appendix IV.

5 Tree Characteristics

Tree Species

Southwark's public tree inventory has a very high diversity of species (323). The most common tree species is ash (Fraxinus excelsior), which represents 8.5% of the 102,426 trees in the inventory. With all species individually representing less than 10% of the population, Southwark does not have an over reliance on one or two species.

Given that no single species represents 10% or more of the population, the (species benchmark -10%) 10-20-305 rule proposed by Santamour6 has already been exceeded. The 10-20-30 rule is applied by some urban foresters to guide maintaining a diverse population. This practice has been discussed by other authors such as Kendal7 and Sjöman8, who have further examined the evidence and practicality. Given that Southwark are already working beyond Santamour’s proposal, diversity could be further increased towards meeting Barker’s 1975 benchmark of 5%.

The second, third and fourth most common trees are respectively: sycamore (Acer pseudoplatanus - 7%), London plane (Platanus x acerifolia- 5.8%) and field maple (Acer campestre - 5.4%). Appendix II contains a full list of species included in the inventory.

5 Santamour, 1999

6 Forest Research, anon; Santamour, F.S, 1990 and Kendal, D, 2014

7 Kendal, 2014

8 Sjöman et al, 2012 6

Fraxinus excelsior 8.5%

Acer pseudoplatanus 7.0%

Platanus x acerifolia 5.8%

Acer campestre 5.4%

All Other Species 54.3% Quercus robur 3.9%

Crataegus monogyna 3.7%

Corylus avellana 3.2%

Ilex aquifolium 3.2%

Prunus avium 2.7%

Acer plananoides 2.4%

Figure 1: Percentage Population of Tree Species

7 Tree Diversity

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); Fraxinus (Ash family)).

Tree species which originate from more distant regions to each other may be more genetically dissimilar and 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 Southwark's public tree inventory represents a very rich community of trees given the area, with 323 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 323 species provided.

Tree species from 6 continents are represented in Southwark's public tree inventory. Most of the species are native to Europe and Asia (see Figure 2 below). However, further work would be required to assess the condition, size and populations of these trees and to provide recommendations on the best species to choose for any future plantings.

8 40.0%

30.0%

20.0% Percentage

10.0%

0.0%

Asia Africa Europe Unknown Australia

Europe & Asia North America Europe & Asia + North America +

North & South America + Continent Name

Figure 2: Origin of Tree Species

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

9 Size Distribution

Size class distribution is also an important aspect to consider in managing a sustainable and diverse tree population, as this helps ensure that there are enough young trees to replace those older specimens that are eventually lost through old age or disease.

In this inventory, trees were sized by diameter at breast height (dbh). Figure 3 (below) shows the percentage of the tree population for the ten most common trees by dbh class.

The chart below represents a fairly typical size class contribution for an urban area, 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 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 larger statures will need to be planted and maintained.

60%

45%

30% Percentage of Trees Percentage 15%

0%

0 - 7 7 - 15 120+ 15 - 30 30 - 45 45 - 60 60 - 90 90 - 120 Diameter at Breast Height Classes (cm)

Fraxinus excelsior Acer pseudoplatanus Platanus x acerifolia Acer campestre Quercus robur Crataegus monogyna Corylus avellana Ilex aquifolium Prunus avium Acer platanoides

Figure 3: Percentage of Tree Population by DBH Class

10 Leaf Area and Population

Leaf area is an important metric because the total photosynthetic area of a tree 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 Southwark's public tree inventory, total leaf area is estimated at 17,694,160m². If all the layers of leaves within the tree canopies were spread out, they would cover an area over 12 times the size of Hyde Park!

The three most dominant species in terms of leaf area are London plane (Platanus x acerifolia) (which has 23% of the total leaf area for all trees), sycamore (Acer pseudoplatanus - 11%) and ash (Fraxinus excelsior - 8%). Figure 4 (below) shows the top ten dominant trees’ contributions to total leaf area. In total, these ten species, representing 40% of the tree population, contribute almost 63% of the total leaf area.

25% 10%

% of leaf area % of total tree population

18.75%

6.667%

12.5% Percentage Percentage

3.333%

6.25%

0% 0%

Fraxinus

Quercus robur Prunus avium Acer platanoidesTilia x europaeaAcer campestre Fraxinus excelsior Platanus x hispanicaAcer pseudoplatanus Aesculus hippocastanum Tree Species

Figure 4: Percentage Leaf Area and Population of the Ten Most Dominant Trees

11 Leaf Area by Ward

Figure 5 (below) shows the leaf area in Southwark by ward. Peckham Rye has the largest leaf area (2,140,500m²) followed by Nunhead & Queen’s Road (1,965,400m²) and Dulwich Village (1,767,500m²).

2,200,000

1,760,000

1,320,000

880,000 Leaf Area (m ² ) Leaf Area

440,000

0 St Giles Faraday Chaucer Peckham Rye Lane Newington Rotherhithe Dulwich Hill St George's Surrey Docks Surrey Goose Green Peckham Rye Champion Hill Dulwich Wood Old Kent Road Dulwich Village North Walworth Camberwell Green North Bermondsey South Bermondsey Borough & Bankside Borough Nunhead & Queen's Road London Bridge & W Bermondsey

Ward Name

Figure 5: Leaf Area by Ward

12 Results - Ecosystem Services Resource

Air Pollution Removal

Poor air quality is a common problem in many urban areas, in particular along the road network. Air pollution caused by human activity has become a problem since the beginning of the industrial revolution. With the increase in population and industrialisation, large quantities of pollutants are produced and released into the urban environment. The problems caused by poor air quality are well documented, ranging from severe health problems in humans to damage to buildings.

Urban trees can help to improve air quality by reducing air temperature and directly removing pollutants9. Trees intercept and absorb airborne pollutants on to the leaf surface10. In addition, by removing pollution from the atmosphere, trees reduce the risks of respiratory disease and asthma, thereby contributing to reduced healthcare costs11.

Trees emit volatile organic compounds (VOCs) that can contribute to low-level ozone formation which is detrimental to human health. However, integrated studies have revealed that an increase in tree cover leads to a general reduction in ozone through a reduction in air temperature. Eco accounts for both reduction of ozone and production of VOCs within its algorithms and, as shown in Figure 6, Eco estimated that the inventoried trees in Southwark contribute to a net reduction in ozone concentrations.

9 Tiwary et al., 2009

10 Nowak et al., 2000

11 Peachey et al., 2009. Lovasi et al., 2008 13

10000 650,000 Pollution (kg) Value (£)

8000 520,000

6000 390,000

4000 260,000 Pollution Value (£) Pollution Value Amount of Pollution (kg)

2000 130,000

0 0 Ozone Sulphur Dioxide Nitrogen Dioxide Nitrogen Carbon Monoxide Particulate Matter 2.5 Pollutant

Figure 6: Value of the Pollutants Removed and Quantity Per-Annum within Southwark

The valuation method uses, where available, UK social damage costs (UKSDC). 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.

Figure 7 (below) shows the breakdown for the top ten pollution removing tree species in Southwark's public tree inventory. As different species can capture different sizes of particulate matter,12 it is recommended that a broad range of species should be considered for planting in any air quality strategy.

12 Freer-Smith et al. 2005 14 Platanus x acerifolia

Acer pseudoplatanus

Fraxinus excelsior

Acer platanoides

Acer campestre

Tilia x europaea

Tree Species Tree Quercus robur

Fraxinus

Aesculus hippocastanum

Prunus avium

All Other Species

0 1800 3600 5400 7200 9000 Pollutants Removed (kg)

COCO OO₃3 NO₂2 SOSO₂2 PM2.5

Figure 7: Pollution Removal by Tree Species

It is interesting to note that despite being the most common species, ‘Ash (Fraxinus excelsior)’ is the only the 3rd highest pollutant removing species. It is likely that this is due to the London plane’s generally larger size and leaf area. To further support this, Horse chestnut (Aesculus hippocastanum), a particularly large-leaved species, is not within the the top ten by percentage composition (it is 24th, with 0.9%) but it is 9th for pollution removal. Demonstrating that larger trees provide more benefits when compared with smaller specimens.

15 Pollution Removal by Ward

Table 3 (below) shows the amount of each pollutant removed by wards in Southwark. The Nunhead & Queen’s Road ward removes the highest concentration of pollutants, removing 2,398kg in total per annum.

Ward Name CO O3 NO2 SO2 PM2.5 Total Removed Removed Removed Removed Removed Pollutants (kg) (kg) (kg) (kg) (kg) (kg)

Peckham Rye 83.35 1170.69 1204.73 90.11 63.32 2612.2 Nunhead & Queen's 76.49 1074.96 1106.20 82.73 58.14 2398.52 Road Dulwich Village 68.82 966.69 994.83 74.44 52.28 2157.06 Rotherhithe 56.12 788.32 811.20 60.68 42.65 1758.97 Faraday 51.05 717.13 737.99 55.19 38.78 1600.14 Surrey Docks 49.84 700.46 720.79 53.90 37.87 1562.86

Champion Hill 48.25 678.25 697.99 52.21 36.68 1513.38 London Bridge & W 30.38 426.63 439.03 32.85 23.09 951.98 Bermondsey North Bermondsey 26.95 378.60 389.60 29.14 20.48 844.77 Chaucer 26.69 374.91 385.81 28.86 20.28 836.55

St Giles 19.25 270.63 278.50 20.84 14.64 603.86 Peckham 18.83 264.45 272.14 20.36 14.31 590.09 Newington 17.77 249.61 256.85 19.21 13.50 556.94 Dulwich Wood 16.00 224.69 231.23 17.29 12.15 501.36 Camberwell Green 15.40 216.30 222.59 16.65 11.70 482.64 South Bermondsey 13.89 195.10 200.76 15.02 10.55 435.32 North Walworth 13.03 182.99 188.31 14.09 9.90 408.32 Dulwich Hill 11.87 166.79 171.64 12.84 9.02 372.16 Borough & Bankside 11.47 161.17 165.86 12.41 8.72 359.63 Old Kent Road 11.09 155.75 160.28 11.99 8.43 347.54 St George's 8.50 119.47 122.95 9.20 6.47 266.59 Goose Green 7.60 106.85 109.96 8.23 5.78 238.42 Rye Lane 6.20 87.15 89.67 6.71 4.71 194.44

Study Area 688.84 9677.59 9958.91 744.95 523.45 21593.74

Table 3: Removal of Each Pollutant by Ward

16 Carbon Storage and Sequestration

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 centuries13.

Overall, the trees in the Southwark public tree inventory store an estimated 57,269 tonnes of carbon with a value of £14 million.

Figure 8 (below) illustrates the carbon storage of the top ten tree species.

11000 3,000,000 Carbon (t) Value (£) 2,571,429 9167

2,142,857 7333

1,714,286 5500 1,285,714

3667 857,143 Carbon Storage Value (£) Carbon Storage Value Amount of Carbon Storage (t) 1833 428,571

0 0 Prunus avium Quercus robur Quercus Betula Pendula Acer campestre Acer platanoides Fraxinus excelsior Platanus x acerifolia Acer pseudoplatanus Aesculus hippocastanum Pyrus calleryana 'Chanticleer' Tree Species

Figure 8: Carbon Storage (tonnes) for Top Ten Tree Species in Southwark

As trees die and decompose they release the stored 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.

13 Kuhns 2008, Mcpherson 2007 17 Maintaining a healthy tree population will ensure that more carbon is stored than released. Utilising the timber in long-term wood products, in energy production or to help heat buildings will also contribute to reducing carbon emissions from other sources, such as power plants.

Carbon Storage by Ward

The highest quantity of carbon is stored in Nunhead & Queens Road (6,401 tonnes) which is 11.2% of the total storage in Southwark (see figure 9 below). The second and third highest carbon storage wards, respectively, are Rotherhithe (5,085 tonnes) and Peckham Rye (5,072 tonnes).

7000 £1,600,000 Carbon (t) Value (£)

5600 £1,280,000

4200 £960,000

2800 £640,000 Carbon Storage Value (£) Carbon Storage Value

Amount of Carbon Storage (t) 1400 £320,000

0 £0 St Giles Faraday Chaucer Peckham Rye Lane Newington Rotherhithe Dulwich Hill St George's Surrey Docks Surrey Goose Green Peckham Rye Champion Hill Dulwich Wood Old Kent Road Dulwich Village North Walworth Camberwell Green North Bermondsey South Bermondsey Borough & Bankside Borough Nunhead & Queen's Road London Bridge & W Bermondsey

Ward Name

Figure 9: Carbon Stored by Ward

18 Carbon Sequestration

Carbon sequestration is calculated from the predicted growth of trees based on field measurements of individual trees, climate data and genera specific growth rates held within Eco. This provides a measure of tree growth (converted volume). The volume is converted into tonnes of carbon based on species specific conversion factors. Following this, the volume is converted to CO2 equivalent before being multiplied by the unit cost for carbon. The current UK social cost for carbon is £67/tonne14.

Southwark’s inventory trees sequester an estimated 986 tonnes of carbon per year, with a value of £242,340. Table 4 (below) shows Southwark's top ten trees in terms of carbon sequestration (annually), and the value of the benefit derived from the sequestration of this atmospheric carbon.

Carbon Sequestration CO2 Equivalent Carbon Sequestration Species (tonnes/yr) (tonnes/yr) (£/yr)

Platanus x acerifolia 157.48 577.49 £38,692 Acer pseudoplatanus 85.61 313.92 £21,033 Fraxinus excelsior 67.27 246.69 £16,528 Quercus robur 43.41 159.19 £10,666 Acer platanoides 31.21 114.44 £7,667 Prunus avium 29.64 108.69 £7,282 Acer campestre 29.07 106.61 £7,143 Aesculus hippocastanum 23.66 86.77 £5,814 Tilia x europaea 22.79 83.57 £5,599 Ilex aquifolium 20.38 74.73 £5,007

All Other Species 475.85 1,744.91 £116,909 Total 986.37 3,617.01 £242,339

Table 4: Top Ten Carbon Sequestration by Species

Of the tree species inventoried, London plane (Platanus x acerifolia) store and sequester the most carbon. They add approximately 157 tonnes in the study year to the current London plane (Platanus x acerifolia) carbon storage of 10,026 tonnes. For comparison, the average newly registered car in the UK produces 34.3g carbon per km15. Carbon sequestration in Southwark's public tree inventory therefore corresponds to around 2,875,714 ‘new’ vehicle km per year, equivalent to 549 people driving a car every year16.

14 gov.uk (2012)

15 http://naei.beis.gov.uk/data/emission-factors https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/454981/veh0150.csv/preview

16 https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/823068/national-travel- survey-2018.pdf (Page 15) 19 Carbon Sequestration by Ward

Trees remove four million tonnes of Carbon from the UK atmosphere each year17. Dulwich Wood has the largest carbon sequestration value at 105 tonnes/yr (table 5 below). The second and third highest, respectively, are Peckham Rye (97 tonnes) and Borough & Bankside (89 tonnes).

Ward Name Gross Carbon CO₂ Equivalent Sequestration Value (£) (metric ton/yr) (metric ton/yr)

Borough & Bankside 15.31 56.15 £3,762.05 Camberwell Green 21.34 78.24 £5,242.08 Champion Hill 75.76 277.82 £18,613.94 Chaucer 40.50 148.52 £9,950.84

Dulwich Hill 15.18 55.66 £3,729.22 Dulwich Village 105.75 387.80 £25,982.60 Dulwich Wood 28.46 104.37 £6,992.79 Faraday 68.69 251.88 £16,875.96 Goose Green 12.73 46.68 £3,127.56 London Bridge & W Bermondsey 45.48 166.78 £11,174.26 Newington 26.58 97.47 £6,530.49 North Bermondsey 35.93 131.76 £8,827.92 North Walworth 16.20 59.40 £3,979.80 Nunhead & Queen's Road 107.59 394.54 £26,434.18 Old Kent Road 15.03 55.12 £3,693.04 Peckham 25.91 95.01 £6,365.67 Peckham Rye 121.90 447.02 £29,950.34 Rotherhithe 73.20 268.42 £17,984.14 Rye Lane 9.20 33.72 £2,259.24 South Bermondsey 17.78 65.20 £4,368.40 St George's 10.34 37.92 £2,540.64 St Giles 28.96 106.19 £7,114.73 Surrey Docks 68.54 251.35 £16,840.45

Study Area 986.36 3,617.02 £242,340.34

Table 5: Carbon Sequestration in each ward

17 Forestry Commission England (2010) 20 Hydrology (Avoided Stormwater 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 proportion 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 runoff18.

In urban areas, the large extent of impervious surfaces increases the amount of runoff. However, trees are very effective at reducing surface runoff19. Tree canopies intercept precipitation, while root systems promote infiltration and storage of water in the soil.

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 Southwark's public tree inventory reduce runoff by an estimated 35,411m³ a year with an associated value of £21,18320. This volume is equivalent to over 14 Olympic swimming pools of stormwater being averted every single year. Figure 10 (below) shows the volumes and values for the ten most important species for reducing runoff.

9000 5,000 Avoided Runoff (m³) Value (£) 6750 3,750

4500 2,500

2250 1,250 Avoided Runoff Value (£) Value Runoff Avoided Amount of Avoided Runoff m ³ Runoff Amount of Avoided

0 0 Fraxinus Prunus avium Quercus robur Quercus Tilia x europaea Acer campestre Acer platanoides Fraxinus excelsior Platanus x acerifolia Acer pseudoplatanus Aesculus hippocastanum Tree Species

Figure 10: Avoided Runoff by Top Ten Species

18 Hirabayashi 2012

19 Trees in Hard Landscapes (TDAG) 2014

20 Thames Water Charges 2020/21 21 The trees in Southwark's public tree inventory play an important role in reducing runoff: London plane (Platanus x acerifolia) intercepts the largest proportion of precipitation for a species, and is the most important species in this category. This is due to the trees’ population, canopy size and leaf morphology.

Avoided Runoff by Ward

Figure 11 shows that Peckham Rye has the highest avoided runoff value, preventing 4,283m3 of stormwater each year from entering sewerage systems. This has an associated saving of £2,563; and represents 12% of the total runoff value for the Southwark Inventory. The second and third highest, respectively, are Nunhead & Queen’s Road with 11% (3,933m3) and Dulwich Village with 10% (3,537m3).

5000m³ £6,000 Avoided Runoff Value

3750m³ £4,500

2500m³ £3,000 Avoided Runoff Value (£) Value Runoff Avoided

Amount of Avoided Runoff m ³ Runoff Amount of Avoided 1250m³ £1,500

0m³ £0 St Giles Faraday Chaucer Peckham Rye Lane Newington Dulwich Hill Rotherhithe St George's Goose Green Surrey Docks Surrey Champion Hill Peckham Rye Dulwich Wood Old Kent Road Dulwich Village North Walworth Camberwell Green North Bermondsey South Bermondsey Borough & Bankside Borough Nunhead & Queen's Road London Bridge & W Bermondsey Ward Name

Figure 11: Avoided Runoff for each ward

22 Potential Pests and Diseases

Various pests and diseases can affect trees, reducing both their health and value, and therefore the sustainability of our urban forests. As most pests generally have a specific range of tree hosts, the potential damage that can be caused by each pest will differ.

In this instance Plane wilt (Canker stain disease) and Ash Dieback (Hymenoscyphus fraxineus) have been selected to illustrate how the results from this survey can be used to estimate the potential impacts on the trees in Southwark. These pathogens have the potential to reduce the performance of, or even kill, a number of trees that are present in Southwark. Figure 12 (below) illustrates the potential impact of these pathogens, the potential percentage of population that could become infected and those which are resistant.

9000 28,000,000

6750 21,000,000

4500 14,000,000 Replacement Cost (£)

Number of Susceptible Trees 2250 7,000,000

0 0 Plane Wilt Ash dieback Pathogen

Number of Susceptible Trees Replacement Cost (£)

Figure 12: Potential Pest Impacts on Species

Ash dieback (Hymenoscyphus fraxineus) is harmless in its native range in Asia, associating with native ash species including Fraxinus mandshurica. However, European ash (Fraxinus excelsior) has shown to be highly susceptible to the pathogenicity of H fraxineus. F excelsior is one of the most common species and alongside the other ash species, provide the high ecosystem benefits within the inventory to Southwark, such as pollution removal, avoided runoff, carbon storage and sequestration. They

23 currently account for 8.5% of the population (or 8751 trees). Ash trees can be large in stature and within Southwark, provide a significant amount of ecosystem service benefits. Therefore their replacement, should they perish, would be costly with regards to ecosystem services.

Plane wilt, also known as canker stain disease, is a serious disorder of plane trees, which are important amenity trees in the parks and avenues of many European cities. The disease is caused by the fungus Ceratocystis platani, which is present in the USA and Europe.21 The fungus causes the foliage to wilt and then dieback, causing limbs and stems to break. The disease is in most cases fatal, and will lead to the death of Plane trees within 2-5 years, according to the Woodland Trust22. This fungus could affect around 5.7% (or 5,906) of the public trees in Southwark.

For the purpose of this study all species of Ash including, Fraxinus, Fraxinus Excelsior, Fraxinus excelsior ‘Pendula', Fraxinus americana, Fraxinus Angustifolia, Fraxinus Ornus, Fraxinus oxycarpa and Fraxinus Pennsylvanica have been included. According to the Defra Management Plan for Ash Dieback, many species of Ash can be infected but the intensity and appearance of symptoms varies. Common Ash (Fraxinus Excelsior) is the most severely affected23. This information should be considered when reviewing the impacts of Ash Dieback on Southwark’s trees.

21 https://www.forestry.gov.uk/PDF/FCPH-PW.pdf/$FILE/FCPH-PW.pdf

22 Woodland Trust, anon

23 Defra, 2013 24 Replacement Cost

In addition to estimating the environmental benefits provided by trees, Eco also provides a structural valuation. In the UK this 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) formulae24.

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 13 (below).

The total value of all trees in the study area, as estimated by Eco, currently stands at over £165 million. London plane (Platanus x acerifolia) is the most valuable species of tree, on account of both its size and population, followed by Ash (Fraxinus excelsior) and Sycamore (Acer pseudoplatanus). These three species (or genera) account for £54 million (33%) of the total replacement cost of the trees in Southwark's public tree inventory, with the London plane alone accounting for 17% of the total replacement cost.

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

Platanus x acerifolia £27,763,394

Fraxinus excelsior £14,774,785

Acer pseudoplatanus £12,016,496

Quercus robur £5,291,023

Tilia x europaea £4,465,584

Acer platanoides £4,400,424 Tree Species Tree Prunus avium £4,192,727

Acer campestre £3,725,544

Pyrus calleryana 'Chanticleer' £3,646,046

Robinia pseudoacacia £3,338,988

0 7,500,000 15,000,000 22,500,000 30,000,000 Replacement Cost (£) Figure 13: Replacement Cost for Top Ten Trees in Southwark

24 Hollis, 2007 25 Replacement Cost by Ward

Nunhead & Queen’s Road has the highest Replacement Cost value at £19.8 million (Figure 14), which is 12% of the total replacement cost in Southwark (£165,854,112). The second and third highest, respectively, are Peckham Rye (£14.8 million) and Surrey Docks (£13.6 million).

Nunhead & Queen's Road £19,841,436 Peckham Rye £14,831,901 Surrey Docks £13,669,824 Rotherhithe £13,379,172 Champion Hill £12,832,745 Dulwich Village £11,985,122 London Bridge & W Bermondsey £9,774,084 Faraday £8,995,952 Chaucer £7,449,605 Peckham £6,512,432 North Bermondsey £6,083,721 Newington £5,189,370 Ward St Giles £5,079,698 Dulwich Wood £4,759,803 Camberwell Green £3,677,720 South Bermondsey £3,586,111 North Walworth £3,491,686 Old Kent Road £3,088,380 Goose Green £3,070,086 Borough & Bankside £2,616,599 Rye Lane £2,203,817 St George's £1,910,073 Dulwich Hill £1,824,775

0 3,333,333 6,666,667 10,000,000 13,333,333 16,666,667 20,000,000 Replacement Cost (£)

Figure 14: Replacement Cost in each Ward

26 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 Council of Tree and Landscape Appraisers (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 Southwark’s trees to include a social dimension by valuing the visual accessibility and prominence within the overall urban forest.

For the urban forest of Southwark, the estimated total public amenity asset value is over £2.6 billion.

Given the particular nature of local street trees, local factors and choices could not be taken into account as part of this study. The value should reflect the reality that street trees have to be managed for safety. They are frequently crown lifted and reduced (to a greater or lesser extent) and are generally growing in conditions of greater stress than their open grown counterparts. As a result, they may have a significantly reduced functionality under the CAVAT system.

This study also included some assumptions of Safe Useful Life Expectancy (SULE) based on condition, as this was not included in some of the Southwark public tree inventory information.

The London plane (Platanus x acerifolia) of Southwark holds the highest CAVAT value (Table 6, below), although the ash (Fraxinus excelsior) is the most numerous tree, representing 8.5% of the total tree population.

27 Percent of Total Species CAVAT Value Replacement Cost Population

Platanus x acerifolia 368,830,531 5.77% £27,763,394.13

Fraxinus excelsior 227,479,510 8.54% £14,774,785.22

Acer pseudoplatanus 173,872,506 6.95% £12,016,496.45

Quercus robur 81,300,967 3.93% £5,291,022.84

Tilia x europaea 56,797,393 2.16% £4,465,584.46

Acer platanoides 64,210,780 2.38% £4,400,424.23

Prunus avium 69,263,953 2.68% £4,192,727.15

Acer campestre 65,898,031 5.35% £3,725,543.76 Pyrus calleryana 'Chanticleer' 65,520,835 1.33% £3,646,046

Aesculus hippocastanum 54,322,138 0.99% £2,659,801

All Other Species £1,402,476,452 60.0% £82,918,287

Total £2,629,973,096 100% £165,854,112

Table 6: The Ten Species with the Highest CAVAT Valuation

28 Using this study

The results and data from previous i-Tree Eco studies have been used in a variety of ways to improve management of trees and inform decision making. With better information we can make better decisions about how trees are managed to provide long-term benefits to communities. This is one of the key outcomes of undertaking a project such as this.

For example:

• Data can be used to plan for increasing tree diversity through species selection. Thereby lessening the impacts from potential threats like Hymenoscyphus fraxineus (formerly Chalara fraxinea), more commonly known as Ash Dieback.

• Data can be used to produce educational information about Southwark’s trees (e.g. informational tree tags).

• Data can be used to analyse the variance between wards and enable Southwark to work towards a situation of greater environmental equity. It would be interesting to make comparisons with social indicators such as deprivation, education achievement, levels of crime and hospital admissions.

• Use the data for cost benefit analysis to inform decision making.

• Undertake a gap analysis to help inform where to plant trees to optimise ecosystem services and maximise the benefits, to align with the objectives and priorities of Southwark’s tree management plan.

• Inform species selection. Size does matter! Identify trees that can grow to full maturity and reach their optimal canopy size (given any site specific restrictions) and contribute the most benefits to the surrounding urban communities. Review together with an ancient tree management plan to include non-natives and heritage trees to broaden the potential for Southwark’s inventory trees to build resilience to future change.

29 Conclusions

The tree population within Southwark's public tree inventory has a very good species and age diversity. It is acknowledged that there are a number of constraints on urban planting that can hinder planting of larger-growing species. Additional larger-growing species would provide further resilience from possible future influences such as climate change and pest and disease outbreaks. The role of Southwark’s trees in complementing people's health is clear, through air pollution removal especially. Southwark’s trees provide a valuable benefit of over £431,000 in ecosystem services each year.

In terms of structural diversity, the London plane (Platanus x acerifolia) has the largest proportion of trees in the larger size classes within the top ten populated species. But, other tree species such as Ash (Fraxinus excelsior) and Sycamore (Acer pseudoplatanus) are also well represented. Larger- growing trees are important because they can provide greater canopy cover and therefore ecosystem service provision. They also tend to have higher amenity value than their smaller counterparts.

Southwark has a rich species diversity, with 323 species within the public tree inventory. However, there is a slight reliance on London plane (Platanus x acerifolia), Sycamore (Acer pseudoplatanus) and Ash (Fraxinus excelsior) to provide ecosystem services, including 31.5% of all carbon stored, 31.5% of annual carbon sequestration, and 41% of annual avoided runoff. Like many urban areas, Southwark would benefit from having a greater proportion of larger trees, with a continual diverse range of species, in order to continue building resilience into its tree population and reduce reliance on a small number of species.

The values presented in this study should be seen as conservative estimates, as only a proportion of the total benefits have been evaluated. Trees on privately owned land have not been included within this study and would greatly add to the value of Southwark’s tree stock. Trees confer many benefits which have not been valued as part of this report, such as contributions to our health and well-being, reducing urban temperatures, providing amenity value and habitats for wildlife25.

The extent of these benefits needs to be recognised. Strategies and policies that will conserve this important resource (through education for example) would be one way to address this. Targets to increase canopy cover including planting larger trees, protecting large and veteran trees and, where possible, diversify the urban forest through planting climate adaptable species should also be investigated through the production of an ‘Urban Forest Masterplan’.

25 Davies et al, 2017 30 As the amount of healthy leaf area equates directly to the provision of benefits, future management of the tree stock is important to ensure canopy cover levels continue to be maintained or increased. New tree planting can contribute to the growth of canopy cover. However, the most effective strategy for increasing average tree size and the extent of tree canopy can preserve and adopt a management approach that enables the existing trees to develop a stable, healthy, age and species diverse, multi- layered population.

Climate change could affect the tree stock in Southwark's public tree inventory in a variety of ways and there are great uncertainties about how this may manifest. Some species may be less able to survive under new climatic conditions. New conditions may also allow different pests and diseases to become prevalent. Further studies into this area would be useful in informing any long-term tree strategies or urban forest masterplans, such as species choice.

The challenge now is to ensure that policy makers and practitioners take full account of Southwark’s trees in decision making. Not only are trees a valuable functional component of our landscape, they also make a significant contribution to people’s quality of life.

31 Appendix I. Relative Tree Effects

The trees in the Southwark’s inventory 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: • Amount of carbon emitted in Southwark in 15 days

• Annual carbon (C) emissions from 44,700 automobiles

• Annual C emissions from 18,300 single-family houses

Carbon monoxide removal is equivalent to:

• Annual carbon monoxide emissions from 7 automobiles

• Annual carbon monoxide emissions from 19 single-family houses

Nitrogen dioxide removal is equivalent to:

• Annual nitrogen dioxide emissions from 1,570 automobiles

• Annual nitrogen dioxide emissions from 708 single-family houses

Sulfur dioxide removal is equivalent to:

• Annual sulfur dioxide emissions from 8,830 automobiles

• Annual sulfur dioxide emissions from 23 single-family houses

Annual carbon sequestration is equivalent to:

• Amount of carbon emitted in Southwark in 0.3 days

• Annual C emissions from 800 automobiles

• Annual C emissions from 300 single-family houses

Oxygen Production is equivalent to:

• Annual oxygen intake from 9,163 people

32 Municipal carbon emissions are based on 2010 U.S. per capita carbon emissions (Carbon Dioxide Information Analysis Center 2010). Per capita emissions were multiplied by city population to estimate total city carbon emissions.

Light duty vehicle emission rates (g/mi) for CO, NOx, VOCs, PM, SO2 for 2010 (Bureau of Transportation Statistics

2010; Heirigs et al 2004), PM2.5 for 2011-2015 (California Air Resources Board 2013), and CO2 for 2011 (U.S. Environmental Protection Agency 2010) were multiplied by average miles driven per vehicle in 2011 (Federal Highway Administration 2013) to determine average emissions per vehicle.

Household emissions are based on average electricity kWh usage, natural gas Btu usage, fuel oil Btu usage, kerosene Btu usage, LPG Btu usage, and wood Btu usage per household in 2009 (Energy Information Administration 2013; Energy Information Administration 2014)

•CO2, SO2, and NOx power plant emission per KWh are from Leonardo Academy 2011. CO emission per kWh assumes 1/3 of one percent of C emissions is CO based on Energy Information Administration 1994. PM emission per kWh from Layton 2004.

•CO2, NOx, SO2, and CO emission per Btu for natural gas, propane and butane (average used to represent LPG), Fuel #4 and #6 (average used to represent fuel oil and kerosene) from Leonardo Academy 2011.

•CO2 emissions per Btu of wood from Energy Information Administration 2014. • CO, NOx and SOx emission per Btu based on total emissions and wood burning (tons) from (British Columbia Ministry 2005; Georgia Forestry Commission 2009).

Oxygen production figures are based on the total oxygen produced by the trees within the inventory divided by the average intake of oxygen for each person per year - https://ntrs.nasa.gov/search.jsp?R=20060005209

33 Appendix II. Species Dominance Ranking List

Species Percent Population Percent Leaf Area Dominance Value

Platanus x acerifolia 5.8% 22.6% 28.40

Acer pseudoplatanus 6.9% 11.2% 18.10 Fraxinus excelsior 8.5% 7.6% 16.20

Acer campestre 5.3% 3.5% 8.80

Quercus robur 3.9% 3.2% 7.10

Acer platanoides 2.4% 4.3% 6.70

Tilia x europaea 2.2% 3.5% 5.70

Prunus avium 2.7% 2.1% 4.70

Crataegus monogyna 3.7% 0.8% 4.50

Ilex aquifolium 3.2% 1.0% 4.20

Corylus avellana 3.2% 0.9% 4.10

Fraxinus 1.7% 2.4% 4.10

Prunus laurocerasus 2.4% 0.9% 3.30

Aesculus hippocastanum 1.0% 2.1% 3.10

Taxus baccata 1.6% 1.3% 2.90

Betula pendula 1.8% 1.0% 2.70

Prunus cerasifera 1.7% 1.0% 2.70

Tilia cordata 1.2% 1.6% 2.70

Sambucus nigra 2.2% 0.4% 2.60

Robinia pseudoacacia 1.2% 1.4% 2.60

Laurus nobilis 1.8% 0.6% 2.50

Salix alba 1.0% 0.8% 1.90

Pyrus calleryana 'Chanticleer' 1.3% 0.5% 1.80

Ailanthus altissima 0.8% 1.0% 1.80

Acer saccharinum 0.6% 1.2% 1.80

Chamaecyparis lawsoniana 1.3% 0.5% 1.70

Carpinus betulus 1.0% 0.7% 1.70

Betula utilis ssp. jacquemontii 1.0% 0.5% 1.50

Prunus Kanzan 0.7% 0.6% 1.30

Quercus/live ilex 0.7% 0.6% 1.30

34 Species Percent Population Percent Leaf Area Dominance Value

Prunus 0.7% 0.4% 1.20

Populus alba 0.6% 0.6% 1.20

Cotoneaster 0.9% 0.2% 1.10

Sorbus aria 0.6% 0.6% 1.10

Populus nigra v. italica 0.5% 0.6% 1.10

Quercus 0.4% 0.6% 1.10

Tilia platyphyllos 0.4% 0.7% 1.10

Sorbus aucuparia 0.7% 0.4% 1.00

Salix caprea 0.6% 0.4% 1.00

Liquidambar styraciflua 0.6% 0.3% 0.90

Malus 0.5% 0.3% 0.90

Ulmus x hollandica 0.5% 0.4% 0.90

Fagus sylvatica 0.3% 0.5% 0.80

Alnus glutinosa 0.4% 0.2% 0.70

Alnus cordata 0.4% 0.3% 0.70

Alnus incana 0.3% 0.3% 0.70

Populus nigra 0.3% 0.4% 0.70

Syringa vulgaris 0.6% <0.1% 0.60

Amelanchier canadensis 0.6% 0.1% 0.60

Buxus sempervirens 0.5% 0.1% 0.60

Populus 0.3% 0.3% 0.60

Sorbus intermedia 0.3% 0.3% 0.60

Salix x chrysocoma 0.3% 0.3% 0.60

Fraxinus oxycarpa 0.3% 0.4% 0.60

Tilia 0.2% 0.4% 0.60

Malus domestica 0.4% 0.1% 0.50

Cupressocyparis leylandii 0.4% 0.1% 0.50

Malus tschonoskii 0.3% 0.2% 0.50

Ginkgo biloba 0.3% 0.2% 0.50

Prunus padus 0.3% 0.2% 0.50

Magnolia 0.3% 0.2% 0.50

Corylus colurna 0.3% 0.2% 0.50

Castanea sativa 0.2% 0.3% 0.50

Acer saccharum 0.2% 0.3% 0.50

35 Species Percent Population Percent Leaf Area Dominance Value

Ulmus procera 0.3% 0.1% 0.40

Prunus x yedoensis 0.3% 0.1% 0.40

Carpinus betulus 'Fastigiata' 0.2% 0.2% 0.40

Aesculus x carnea 0.1% 0.2% 0.40

Salix fragilis 0.2% 0.3% 0.40

Ficus carica 0.2% 0.1% 0.30

Salix 0.2% 0.1% 0.30

Pyrus communis 0.2% 0.1% 0.30

Prunus lusitanica 0.2% 0.1% 0.30

Prunus sargentii 0.2% 0.1% 0.30

Gleditsia triacanthos 0.2% 0.1% 0.30

Prunus serrulata 0.2% 0.1% 0.30

Chamaecyparis 0.2% 0.1% 0.30

Pinus sylvestris 0.2% 0.1% 0.30

Cordyline australis 0.2% 0.1% 0.30

Prunus serrulata 'Umineko' 0.2% 0.1% 0.30

Arbutus unedo 0.2% 0.1% 0.30

Malus sylvestris 0.2% 0.1% 0.30

Sorbus 0.2% 0.1% 0.30

Catalpa bignonioides 0.2% 0.1% 0.30

Prunus serrulata 'Amanogawa' 0.2% 0.1% 0.30

Ulmus glabra 0.2% 0.1% 0.30

Prunus spinosa 0.2% 0.1% 0.30

Betula papyrifera 0.1% 0.1% 0.30

Metasequoia glyptostroboides 0.1% 0.1% 0.30

Liriodendron tulipifera 0.1% 0.1% 0.30

Ulmus 0.2% 0.2% 0.30

Acer negundo 0.1% 0.2% 0.30

Quercus rubra 0.1% 0.2% 0.30

Acer platanoides 'Crimson King' 0.1% 0.2% 0.30

Populus balsamifera 0.2% 0.1% 0.20

Prunus cerasifera 'Nigra' 0.1% 0.1% 0.20

Celtis australis 0.1% 0.1% 0.20

Pinus nigra 0.1% 0.1% 0.20

36 Species Percent Population Percent Leaf Area Dominance Value

Fraxinus ornus 0.1% 0.1% 0.20

Juglans regia 0.1% 0.1% 0.20

Pterocarya fraxinifolia 0.1% 0.1% 0.20

Quercus cerris 0.1% 0.1% 0.20

Ligustrum 0.1% 0.1% 0.20

Crataegus x lavallei 0.1% 0.1% 0.20

Prunus domestica 0.1% 0.1% 0.20

Prunus x schmittii 0.1% 0.1% 0.20

Tilia cordata 'Greenspire' 0.1% 0.1% 0.20

Betula pubescens 0.1% 0.1% 0.20

Koelreuteria paniculata 0.1% 0.1% 0.20

Morus nigra 0.1% 0.1% 0.20

Sophora japonica 0.1% 0.1% 0.20

Platanus orientalis 0.0% 0.1% 0.20

Eucalyptus gunnii 0.0% 0.1% 0.20

Acer pseudoplatanus v. 0.1% 0.2% 0.20 purpureum

Crataegus 0.2% <0.1% 0.20

Crataegus prunifolia 0.2% <0.1% 0.20

Crataegus crus-galli 0.2% <0.1% 0.20

Cupressus 0.2% <0.1% 0.20

Cercis siliquastrum 0.1% <0.1% 0.20

Parrotia persica 0.1% <0.1% 0.20

Cercidiphyllum japonicum 0.1% <0.1% 0.10

Prunus serrula 0.1% 0.1% 0.10

Prunus virginiana 'Shubert' 0.1% 0.1% 0.10

Populus tremula 0.1% 0.1% 0.10

Prunus serrulata 'Accolade' 0.1% 0.1% 0.10

Prunus subhirtella 0.1% 0.1% 0.10

Acer platanoides 'Columnare' 0.1% 0.1% 0.10

Ulmus americana 0.1% 0.1% 0.10

Cedrus atlantica 0.1% 0.1% 0.10

Tilia euchlora 0.1% 0.1% 0.10

Robinia pseudoacacia 'Frisia' 0.1% 0.1% 0.10

Fraxinus americana 0.0% 0.1% 0.10

37 Species Percent Population Percent Leaf Area Dominance Value

Fagus sylvatica 'Purpurea' 0.0% 0.1% 0.10

Juglans nigra 0.0% 0.1% 0.10

Fraxinus excelsior 'Pendula' 0.0% 0.1% 0.10

Paulownia tomentosa 0.1% <0.1% 0.10

Ilex 0.1% <0.1% 0.10

Betula ermanii 0.1% <0.1% 0.10

Laburnum x watereri 0.1% <0.1% 0.10

Prunus domestica ssp. insititia 0.1% <0.1% 0.10

Acer 0.1% <0.1% 0.10

Salix matsudana 'Tortuosa' 0.1% <0.1% 0.10

Gleditsia triacanthos v. inermis 0.1% <0.1% 0.10 'Sunburst'

Tilia mongolica 0.1% <0.1% 0.10

Prunus maackii 0.1% <0.1% 0.10

Laburnum anagyroides 0.1% <0.1% 0.10

Tamarix 0.1% <0.1% 0.10

Olea europaea 0.1% <0.1% 0.10

Cornus sanguinea 0.1% <0.1% 0.10

Rhus 0.1% <0.1% 0.10

Magnolia grandiflora 0.1% <0.1% 0.10

Amelanchier lamarckii 0.1% <0.1% 0.10

Ulmus carpinifolia 'Hollandica' 0.0% <0.1% 0.10

Malus x purpurea 0.0% <0.1% 0.10

Ulmus 'Lobel' 0.0% <0.1% 0.10

Tilia tomentosa 0.0% <0.1% 0.10

Aesculus indica 0.0% <0.1% 0.10

Pinus 0.0% <0.1% 0.10

Populus canescens 0.0% <0.1% 0.10

Salix alba 'Tristis' 0.0% <0.1% 0.10

Mespilus germanica 0.0% <0.1% 0.10

Buddleja davidii 0.0% <0.1% 0.10

Pyrus 0.0% <0.1% 0.10

Sorbus x thuringiaca 0.0% <0.1% 0.10

Taxodium distichum 0.0% <0.1% 0.10

Acer griseum 0.0% <0.1% 0.10

38 Species Percent Population Percent Leaf Area Dominance Value

Acacia dealbata 0.0% <0.1% 0.10

Acer japonicum 0.0% <0.1% 0.10

Rhododendron 0.0% <0.1% 0.10

Prunus dulcis 0.0% <0.1% 0.10

Thuja plicata 0.0% <0.1% 0.10

Cedrus libani 0.0% <0.1% 0.10

Acer palmatum 0.0% <0.1% 0.10

Juniperus 0.0% <0.1% 0.10

Salix babylonica 0.0% <0.1% 0.10

Cupressus macrocarpa 0.0% <0.1% <0.10

Juniperus communis 0.0% <0.1% <0.10

Picea abies 0.0% <0.1% <0.10

Prunus subhirtella v. autumnalis 0.0% <0.1% <0.10

Magnolia x loebneri 0.0% <0.1% <0.10

Ligustrum vulgare 0.0% <0.1% <0.10

Taxus baccata 'Fastigiata' 0.0% <0.1% <0.10

Quercus castaneifolia 0.0% <0.1% <0.10

Cotoneaster salicifolius 0.0% <0.1% <0.10

Betula albosinensis 0.0% <0.1% <0.10

Quercus robur 'Fastigiata' 0.0% <0.1% <0.10

Abies alba 0.0% <0.1% <0.10

Hippophae rhamnoides 0.0% <0.1% <0.10

Eriobotrya japonica 0.0% <0.1% <0.10

Amelanchier laevis 0.0% <0.1% <0.10

Sequoia sempervirens 0.0% <0.1% <0.10

Morus alba 0.0% <0.1% <0.10

Pyrus salicifolia 0.0% <0.1% <0.10

Hamamelis 0.0% <0.1% <0.10

Wisteria sinensis 0.0% <0.1% <0.10

Ligustrum ovalifolium 0.0% <0.1% <0.10

Tilia petiolaris 0.0% <0.1% <0.10

Quercus frainetto 0.0% <0.1% <0.10

Cedrus deodara 0.0% <0.1% <0.10

Quercus palustris 0.0% <0.1% <0.10

39 Species Percent Population Percent Leaf Area Dominance Value

Amelanchier arborea 0.0% <0.1% <0.10

Quercus suber 0.0% <0.1% <0.10

Betula 0.0% <0.1% <0.10

Quercus petraea 0.0% <0.1% <0.10

Magnolia kobus 0.0% <0.1% <0.10

Aesculus 0.0% <0.1% <0.10

Zelkova carpinifolia 0.0% <0.1% <0.10

Acer davidii 0.0% <0.1% <0.10

Pinus pinea 0.0% <0.1% <0.10

Euonymus europaeus 0.0% <0.1% <0.10

Quercus coccinea 0.0% <0.1% <0.10

Fraxinus pennsylvanica 0.0% <0.1% <0.10

Cotoneaster frigidus 0.0% <0.1% <0.10

Cornus 0.0% <0.1% <0.10

Lagerstroemia indica 0.0% <0.1% <0.10

Chamaecyparis nootkatensis 0.0% <0.1% <0.10

Acer rubrum 0.0% <0.1% <0.10

Acer cappadocicum 0.0% <0.1% <0.10

Eucalyptus 0.0% <0.1% <0.10

Cornus kousa 0.0% <0.1% <0.10

Betula nigra 0.0% <0.1% <0.10

Sorbus torminalis 0.0% <0.1% <0.10

Pinus pinaster 0.0% <0.1% <0.10

Ligustrum japonicum 0.0% <0.1% <0.10

Cedrus atlantica v. glauca 0.0% <0.1% <0.10

Zelkova serrata 0.0% <0.1% <0.10

Acer ginnala 0.0% <0.1% <0.10

Sequoiadendron giganteum 0.0% <0.1% <0.10

Acer platanoides 'Schwedleri' 0.0% <0.1% <0.10

Aesculus flava 0.0% <0.1% <0.10

Chitalpa 0.0% <0.1% <0.10

Prunus x hillieri 0.0% <0.1% <0.10

Aesculus x carnea 'Briottii' 0.0% <0.1% <0.10

Philadelphus 0.0% <0.1% <0.10

40 Species Percent Population Percent Leaf Area Dominance Value

Liquidambar styraciflua 0.0% <0.1% <0.10 'Worplesdon'

Ulmus 'New Horizon' 0.0% <0.1% <0.10

Sorbus latifolia 0.0% <0.1% <0.10

Quercus acutissima 0.0% <0.1% <0.10

Malus prunifolia 0.0% <0.1% <0.10

Ceanothus 0.0% <0.1% <0.10

Chamaecyparis obtusa 0.0% <0.1% <0.10

Taxus 0.0% <0.1% <0.10

Albizia julibrissin 0.0% <0.1% <0.10

Alnus viridis 0.0% <0.1% <0.10

Viburnum rhytidophyllum 0.0% <0.1% <0.10

Acer monspessulanum 0.0% <0.1% <0.10

Trachycarpus fortunei 0.0% <0.1% <0.10

Larix decidua 0.0% <0.1% <0.10

Celtis occidentalis 0.0% <0.1% <0.10

Crataegus laevigata 0.0% <0.1% <0.10

Ligustrum lucidum 0.0% <0.1% <0.10

Pinus wallichiana 0.0% <0.1% <0.10

Photinia fraseri 0.0% <0.1% <0.10

Tilia americana 0.0% <0.1% <0.10

Cercis canadensis 0.0% <0.1% <0.10

Tilia henryana 0.0% <0.1% <0.10

Malus floribunda 0.0% <0.1% <0.10

Crataegus x grignonensis 0.0% <0.1% <0.10

Pyrus calleryana 'Red Spire' 0.0% <0.1% <0.10

Sorbus hupehensis 0.0% <0.1% <0.10

Fraxinus angustifolia 0.0% <0.1% <0.10

Lagerstroemia 0.0% <0.1% <0.10

Malus 'John Downie' 0.0% <0.1% <0.10

Cedrus 0.0% <0.1% <0.10

Salix cinerea 0.0% <0.1% <0.10

Ostrya carpinifolia 0.0% <0.1% <0.10

Cydonia oblonga 0.0% <0.1% <0.10

Cornus mas 0.0% <0.1% <0.10

41 Species Percent Population Percent Leaf Area Dominance Value

Euodia 0.0% <0.1% <0.10

Luma apiculata 0.0% <0.1% <0.10

Azara microphylla 0.0% <0.1% <0.10

Nothofagus antarctica 0.0% <0.1% <0.10

Prunus serotina 0.0% <0.1% <0.10

Aesculus pavia 0.0% <0.1% <0.10

Pseudopanax 0.0% <0.1% <0.10

Pinus mugo 0.0% <0.1% <0.10

Liriodendron tulipifera 0.0% <0.1% <0.10 'Fastigiatum'

Alnus rubra 0.0% <0.1% <0.10

Davidia involucrata 0.0% <0.1% <0.10

Quercus phellos 0.0% <0.1% <0.10

Picea 0.0% <0.1% <0.10

Betula lenta 0.0% <0.1% <0.10

Pinus strobus 0.0% <0.1% <0.10

Araucaria araucana 0.0% <0.1% <0.10

Clerodendrum trichotomum 0.0% <0.1% <0.10

Salix pentandra 0.0% <0.1% <0.10

Cornus controversa 0.0% <0.1% <0.10

Picea pungens 0.0% <0.1% <0.10

Picea sitchensis 0.0% <0.1% <0.10

Abies lasiocarpa 0.0% <0.1% <0.10

Ziziphus 0.0% <0.1% <0.10

Sorbus vilmorinii 0.0% <0.1% <0.10

Euonymus latifolius 0.0% <0.1% <0.10

Cupressus lusitanica 0.0% <0.1% <0.10

Acacia pravissima 0.0% <0.1% <0.10

Prunus incisa 0.0% <0.1% <0.10

Jubaea chilensis 0.0% <0.1% <0.10

Pinus radiata 0.0% <0.1% <0.10

Abies grandis 0.0% <0.1% <0.10

Quercus acerifolia 0.0% <0.1% <0.10

Carya cordiformis 0.0% <0.1% <0.10

Michelia doltsopa 0.0% <0.1% <0.10

42 Species Percent Population Percent Leaf Area Dominance Value

Sorbus domestica 0.0% <0.1% <0.10

Sorbus americana 0.0% <0.1% <0.10

Thuja orientalis 0.0% <0.1% <0.10

Catalpa speciosa 0.0% <0.1% <0.10

Magnolia x soulangeana 0.0% <0.1% <0.10

Picea orientalis 0.0% <0.1% <0.10

Acer capillipes 0.0% <0.1% <0.10

Styrax japonicus 0.0% <0.1% <0.10

Pinus x holfordiana 0.0% <0.1% <0.10

Quercus velutina 0.0% <0.1% <0.10

Quercus muehlenbergii 0.0% <0.1% <0.10

Cladrastis 0.0% <0.1% <0.10

Abies nordmanniana 0.0% <0.1% <0.10

Viburnum 0.0% <0.1% <0.10

Malus baccata 0.0% <0.1% <0.10

Thuja 0.0% <0.1% <0.10

Rhamnus cathartica 0.0% <0.1% <0.10

Hibiscus 0.0% <0.1% <0.10

Quercus x ludoviciana 0.0% <0.1% <0.10

Quercus imbricaria 0.0% <0.1% <0.10

Callistemon 0.0% <0.1% <0.10

43 Appendix III. Tree Values by Species

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

Fraxinus excelsior 8751 4126.30 67.27 2697.28 1.64 £14,774,785.22 Acer pseudoplatanus 7118 3882.29 85.61 3960.03 2.41 £12,016,496.45 Platanus x acerifolia 5906 10026.91 157.48 8014.21 4.89 £27,763,394.13 Acer campestre 5476 1251.52 29.07 1238.59 0.76 £3,725,543.76 Quercus robur 4025 2072.31 43.41 1137.71 0.69 £5,291,022.84 Crataegus monogyna 3796 686.78 16.45 275.10 0.17 £1,823,040.49 Corylus avellana 3304 439.90 10.21 324.23 0.20 £1,478,525.65 Ilex aquifolium 3284 832.26 20.38 337.45 0.21 £2,314,436.38 Prunus avium 2746 1568.92 29.64 729.98 0.45 £4,192,727.15 Acer platanoides 2433 1369.60 31.21 1523.55 0.93 £4,400,424.23 Prunus laurocerasus 2421 246.12 12.77 323.40 0.20 £639,172.80 Sambucus nigra 2278 422.10 10.05 142.27 0.09 £1,300,678.46 Tilia x europaea 2212 949.28 22.79 1249.71 0.76 £4,465,584.46 Laurus nobilis 1892 252.82 8.14 229.23 0.14 £737,695.37 Betula pendula 1795 1129.77 17.78 347.63 0.21 £2,953,479.08 Fraxinus 1749 696.62 20.36 861.14 0.53 £2,651,493.87 Prunus cerasifera 1712 1075.32 14.90 365.92 0.22 £1,814,993.48 Taxus baccata 1633 189.18 6.35 452.84 0.28 £1,145,787.84 Pyrus calleryana 'Chanticleer' 1361 1290.10 10.22 183.73 0.11 £3,646,046.16 Chamaecyparis lawsoniana 1284 174.04 4.75 160.78 0.10 £649,609.62 Robinia pseudoacacia 1223 1097.16 18.51 493.34 0.30 £3,338,987.62 Tilia cordata 1178 686.44 11.63 560.23 0.34 £2,728,628.68 Salix alba 1053 757.34 10.73 296.87 0.18 £2,184,912.82 Aesculus hippocastanum 1015 1393.84 23.66 757.24 0.46 £2,659,801.08 Betula utilis ssp. jacquemontii 1006 738.30 7.49 181.13 0.11 £1,786,130.90 Carpinus betulus 986 331.35 7.06 251.00 0.15 £995,427.22 Cotoneaster 895 143.04 3.09 87.29 0.05 £305,258.91 Ailanthus altissima 775 697.55 14.39 365.21 0.22 £1,861,364.39 Prunus 763 402.46 7.21 151.92 0.09 £860,146.43 Quercus/live ilex 714 352.08 8.15 202.96 0.12 £948,255.04

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

Prunus Kanzan 703 675.93 10.03 229.51 0.14 £1,497,117.99 Sorbus aucuparia 671 743.90 5.63 135.47 0.08 £2,117,713.23 Populus alba 636 484.36 7.22 196.64 0.12 £1,477,188.77 Salix caprea 629 343.11 4.56 128.79 0.08 £1,027,833.83 Syringa vulgaris 616 75.35 1.61 17.18 0.01 £250,724.87 Acer saccharinum 611 448.54 8.78 441.92 0.27 £1,784,078.76 Liquidambar styraciflua 610 94.47 2.36 113.39 0.07 £830,928.74 Sorbus aria 609 500.78 6.99 194.99 0.12 £1,549,626.07 Amelanchier canadensis 580 66.97 1.21 21.67 0.01 £228,501.80 Malus 547 634.80 6.21 118.29 0.07 £1,779,560.89 Populus nigra v. italica 535 430.41 8.32 200.99 0.12 £1,441,841.86 Ulmus x hollandica 526 645.01 2.59 137.02 0.08 £581,285.81 Buxus sempervirens 500 17.40 1.60 34.07 0.02 £48,933.39 Alnus glutinosa 443 114.52 2.63 84.98 0.05 £350,180.88 Quercus 437 402.13 9.19 222.92 0.14 £1,050,284.99 Cupressocyparis leylandii 429 32.75 1.26 40.85 0.02 £120,667.33 Alnus cordata 417 143.46 3.49 110.16 0.07 £440,764.58 Tilia platyphyllos 404 269.44 4.93 255.44 0.16 £1,150,743.84 Malus domestica 404 201.09 2.09 52.99 0.03 £558,927.79 Sorbus intermedia 350 172.77 3.83 104.35 0.06 £551,141.79 Alnus incana 350 165.77 3.78 117.93 0.07 £516,844.62 Malus tschonoskii 348 166.21 2.72 72.42 0.04 £506,085.31 Populus nigra 344 524.10 7.40 140.32 0.09 £1,573,890.89 Ginkgo biloba 334 214.54 3.03 69.15 0.04 £555,523.86 Ulmus procera 322 13.63 1.00 45.80 0.03 £22,172.95 Fagus sylvatica 313 167.59 4.00 177.77 0.11 £438,237.85 Populus 299 272.99 5.68 122.74 0.07 £826,707.65 Salix x chrysocoma 292 180.62 4.39 101.42 0.06 £557,080.66 Prunus x yedoensis 281 283.25 2.58 45.66 0.03 £553,985.18 Fraxinus oxycarpa 277 164.57 3.08 128.21 0.08 £612,614.08 Prunus padus 275 146.65 2.79 73.70 0.04 £396,326.65 Corylus colurna 273 104.21 2.15 72.73 0.04 £306,163.79

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

Magnolia 269 348.24 2.53 74.27 0.05 £961,071.18 Salix 251 44.96 1.42 36.39 0.02 £145,027.47 Tilia 233 133.30 2.52 132.42 0.08 £591,413.85 Prunus lusitanica 233 24.40 1.23 30.86 0.02 £54,004.22 Pyrus communis 230 258.20 2.23 42.84 0.03 £727,102.22 Gleditsia triacanthos 230 138.56 1.69 28.56 0.02 £345,770.25 Ficus carica 224 193.36 1.63 46.45 0.03 £445,528.92 Arbutus unedo 216 105.69 1.22 24.40 0.01 £299,373.62 Chamaecyparis 203 35.25 0.94 34.18 0.02 £155,266.60 Pinus sylvestris 201 42.40 0.76 33.71 0.02 £277,302.83 Salix fragilis 194 142.25 3.61 89.36 0.05 £442,924.93 Crataegus prunifolia 191 64.12 1.06 13.23 0.01 £152,673.71 Prunus serrulata 190 251.41 1.81 40.50 0.02 £515,807.36 Sorbus 190 67.96 1.08 30.50 0.02 £213,570.32 Prunus spinosa 187 23.85 1.09 24.82 0.02 £57,283.98 Crataegus 182 46.17 1.29 16.41 0.01 £120,394.04 Prunus sargentii 177 200.57 1.93 46.89 0.03 £423,915.54 Carpinus betulus 'Fastigiata' 173 121.19 2.13 68.30 0.04 £354,798.73 Cordyline australis 172 2.28 0.01 41.75 0.03 £51,838.55 Ulmus 171 25.03 1.05 53.79 0.03 £43,140.00 Ulmus glabra 171 30.62 0.71 31.05 0.02 £36,203.65 Castanea sativa 166 181.87 3.42 109.31 0.07 £534,409.86 Prunus serrulata 'Umineko' 165 178.39 1.95 42.67 0.03 £358,291.43 Populus balsamifera 164 44.30 1.44 31.06 0.02 £196,056.89 Malus sylvestris 163 215.77 1.64 41.63 0.03 £629,804.38 Crataegus crus-galli 163 157.58 1.36 15.54 0.01 £415,935.26 Catalpa bignonioides 162 92.78 1.94 38.88 0.02 £242,850.75 Acer saccharum 161 256.68 4.14 111.02 0.07 £672,246.11 Prunus serrulata 'Amanogawa' 161 209.45 1.73 36.37 0.02 £452,023.48 Cupressus 160 20.54 0.63 14.94 0.01 £95,529.15 Prunus cerasifera 'Nigra' 150 43.66 1.23 31.89 0.02 £103,576.77 Pinus nigra 135 55.66 0.96 32.26 0.02 £399,653.59

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

Betula papyrifera 134 322.81 1.66 49.44 0.03 £851,242.13 Cercis siliquastrum 133 20.81 0.53 15.36 0.01 £54,296.44 Acer negundo 132 85.48 1.71 57.60 0.04 £289,443.02 Crataegus x lavallei 131 194.56 1.26 18.80 0.01 £502,508.79 Aesculus x carnea 131 117.46 2.18 80.83 0.05 £351,284.79 Metasequoia glyptostroboides 124 30.14 0.73 48.61 0.03 £160,055.51 Prunus domestica 122 20.76 0.86 20.90 0.01 £39,767.98 Quercus rubra 117 106.58 1.91 53.12 0.03 £288,311.96 Parrotia persica 117 20.14 0.64 16.58 0.01 £51,435.95 Celtis australis 115 97.60 1.00 41.84 0.03 £243,978.25 Fraxinus ornus 114 91.78 1.02 36.41 0.02 £348,687.97 Cercidiphyllum japonicum 113 14.60 0.35 8.54 0.01 £39,550.29 Liriodendron tulipifera 110 45.75 0.90 50.85 0.03 £131,560.18 Ligustrum 102 176.82 0.98 29.30 0.02 £319,725.06 Ilex 101 6.14 0.46 9.47 0.01 £15,932.34 Tilia cordata 'Greenspire' 97 95.73 0.73 27.29 0.02 £281,228.50 Prunus x schmittii 96 58.29 1.03 28.17 0.02 £140,398.62 Acer platanoides 'Crimson King' 95 37.72 1.22 58.90 0.04 £122,312.07 Sophora japonica 90 97.42 1.10 22.84 0.01 £267,931.46 Prunus serrula 90 82.28 0.94 19.68 0.01 £172,253.05 Laburnum x watereri 90 16.68 0.35 11.25 0.01 £30,098.39 Koelreuteria paniculata 86 169.35 1.15 30.70 0.02 £410,781.01 Betula pubescens 86 63.06 1.05 31.02 0.02 £167,469.97 Prunus serrulata 'Accolade' 85 94.41 0.81 18.50 0.01 £217,680.00 Prunus domestica ssp. insititia 85 16.03 0.50 12.96 0.01 £36,790.35 Paulownia tomentosa 83 71.98 1.22 16.21 0.01 £178,753.40 Quercus cerris 81 143.81 1.73 38.10 0.02 £336,966.66 Gleditsia triacanthos v. inermis 81 87.29 0.81 13.60 0.01 £216,131.91 'Sunburst' Morus nigra 81 43.80 0.92 26.68 0.02 £120,240.90 Populus tremula 80 57.00 0.79 20.70 0.01 £175,836.23 Prunus virginiana 'Shubert' 79 123.36 0.74 21.85 0.01 £292,361.76 Prunus subhirtella 78 75.05 0.84 20.25 0.01 £165,538.18

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

Juglans regia 77 96.85 0.82 49.03 0.03 £269,588.21 Acer pseudoplatanus v. 77 49.60 1.20 53.50 0.03 £164,307.05 purpureum Rhus 77 65.92 0.57 2.38 0.00 £160,531.65 Acer 76 8.27 0.38 16.01 0.01 £24,533.84 Salix matsudana 'Tortuosa' 74 22.08 0.64 16.48 0.01 £63,106.74 Betula ermanii 73 44.52 0.55 17.28 0.01 £117,105.29 Cedrus atlantica 72 45.18 0.67 21.33 0.01 £260,387.75 Tamarix 72 9.55 0.25 6.54 0.00 £24,644.50 Pterocarya fraxinifolia 70 65.96 1.53 47.26 0.03 £181,913.47 Olea europaea 70 5.99 0.23 6.25 0.00 £18,193.84 Robinia pseudoacacia 'Frisia' 69 41.38 0.65 18.59 0.01 £115,305.29 Laburnum anagyroides 67 49.77 0.38 11.64 0.01 £83,955.40 Cornus sanguinea 64 10.13 0.21 7.31 0.00 £18,693.41 Tilia mongolica 63 31.42 0.42 15.70 0.01 £102,184.84 Tilia euchlora 59 77.20 0.81 24.98 0.02 £255,395.56 Prunus maackii 58 136.98 0.57 15.65 0.01 £285,742.98 Amelanchier lamarckii 57 17.15 0.36 4.19 0.00 £51,663.37 Ulmus americana 54 87.25 0.41 27.84 0.02 £83,325.20 Acer platanoides 'Columnare' 53 22.39 0.58 28.29 0.02 £71,548.93 Magnolia grandiflora 52 24.67 0.37 8.17 0.00 £70,810.05 Malus x purpurea 50 67.28 0.47 11.92 0.01 £191,519.19 Pinus 50 7.69 0.21 9.33 0.01 £65,849.74 Buddleja davidii 50 3.84 0.22 6.45 0.00 £12,026.57 Tilia tomentosa 49 13.36 0.27 10.82 0.01 £50,766.86 Fraxinus americana 48 33.19 0.77 23.00 0.01 £90,380.61 Pyrus 46 15.54 0.37 6.67 0.00 £49,683.75 Platanus orientalis 44 51.32 0.77 39.48 0.02 £140,451.47 Eucalyptus gunnii 44 48.66 0.82 38.52 0.02 £95,787.28 Thuja plicata 43 0.91 0.03 3.57 0.00 £14,371.02 Acer palmatum 43 0.98 0.11 3.19 0.00 £3,864.09 Rhododendron 43 1.30 0.13 4.06 0.00 £3,115.59 Mespilus germanica 40 121.59 0.43 11.93 0.01 £204,312.16

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

Fraxinus excelsior 'Pendula' 39 35.56 0.52 19.84 0.01 £137,034.46 Salix alba 'Tristis' 39 26.79 0.56 12.29 0.01 £77,046.63 Populus canescens 38 16.18 0.48 13.47 0.01 £63,362.38 Ulmus 'Lobel' 38 28.55 0.55 15.81 0.01 £34,305.49 Juniperus communis 38 6.45 0.11 4.14 0.00 £22,601.74 Betula albosinensis 38 0.83 0.09 2.54 0.00 £3,457.61 Juglans nigra 37 39.19 0.49 23.83 0.01 £112,380.12 Juniperus 37 4.36 0.11 5.02 0.00 £21,469.00 Taxus baccata 'Fastigiata' 37 1.03 0.07 3.77 0.00 £5,378.38 Abies alba 37 0.90 0.06 2.63 0.00 £3,592.87 Sorbus x thuringiaca 36 15.00 0.34 9.88 0.01 £48,280.31 Ulmus carpinifolia 'Hollandica' 35 14.78 0.39 17.32 0.01 £22,003.03 Ligustrum vulgare 35 3.92 0.16 4.78 0.00 £7,378.43 Acer japonicum 34 18.43 0.24 8.46 0.01 £55,277.14 Amelanchier laevis 33 7.87 0.11 2.45 0.00 £21,990.23 Prunus dulcis 32 66.10 0.40 7.61 0.00 £109,843.52 Acer griseum 32 12.37 0.23 10.20 0.01 £37,296.56 Aesculus indica 31 49.91 0.37 16.32 0.01 £124,860.20 Hippophae rhamnoides 31 46.89 0.39 4.26 0.00 £116,278.16 Prunus subhirtella v. autumnalis 31 37.29 0.47 6.32 0.00 £75,526.22 Salix babylonica 31 8.68 0.29 7.03 0.00 £24,680.65 Magnolia x loebneri 31 8.26 0.21 6.30 0.00 £21,056.68 Wisteria sinensis 31 0.20 0.04 1.57 0.00 £2,101.99 Acacia dealbata 30 46.57 0.32 10.47 0.01 £135,536.74 Cotoneaster salicifolius 30 4.17 0.20 5.80 0.00 £9,388.09 Hamamelis 30 0.98 0.10 2.60 0.00 £2,128.60 Cedrus libani 29 12.99 0.22 8.32 0.01 £75,873.23 Pyrus salicifolia 28 16.60 0.20 3.90 0.00 £50,812.54 Cupressus macrocarpa 27 21.19 0.27 8.33 0.01 £77,533.41 Taxodium distichum 27 13.00 0.24 12.48 0.01 £71,767.45 Picea abies 27 22.29 0.22 7.77 0.00 £44,078.28 Ligustrum ovalifolium 26 10.09 0.12 3.24 0.00 £20,790.89

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

Amelanchier arborea 26 5.37 0.15 1.87 0.00 £18,287.15 Fagus sylvatica 'Purpurea' 24 45.48 0.72 29.10 0.02 £114,519.54 Quercus robur 'Fastigiata' 23 29.60 0.33 7.56 0.00 £82,753.04 Morus alba 23 11.65 0.20 5.72 0.00 £34,514.19 Betula 22 6.27 0.16 3.00 0.00 £13,137.74 Quercus palustris 21 9.07 0.14 3.81 0.00 £26,296.82 Lagerstroemia indica 21 9.72 0.09 0.96 0.00 £25,265.65 Cotoneaster frigidus 21 0.43 0.04 1.36 0.00 £1,402.45 Eriobotrya japonica 20 74.65 0.28 7.05 0.00 £191,136.77 Cedrus deodara 20 25.08 0.21 5.06 0.00 £129,826.08 Quercus suber 20 8.99 0.15 3.82 0.00 £23,764.49 Pinus pinea 20 0.91 0.04 2.29 0.00 £6,850.49 Quercus frainetto 19 24.96 0.20 5.41 0.00 £66,076.94 Cornus 19 7.79 0.05 1.80 0.00 £14,111.72 Magnolia kobus 18 17.12 0.23 3.96 0.00 £44,480.41 Quercus petraea 18 14.85 0.19 4.37 0.00 £35,148.82 Chamaecyparis nootkatensis 18 2.07 0.05 1.80 0.00 £9,145.57 Cornus kousa 18 0.34 0.03 1.07 0.00 £1,520.79 Quercus castaneifolia 17 41.20 0.51 10.43 0.01 £111,787.44 Euonymus europaeus 17 14.05 0.27 2.98 0.00 £37,917.99 Sequoia sempervirens 17 3.18 0.10 7.84 0.00 £16,465.04 Acer davidii 16 11.47 0.12 3.88 0.00 £30,523.10 Tilia petiolaris 15 24.36 0.17 7.02 0.00 £75,856.80 Quercus coccinea 15 8.78 0.19 3.62 0.00 £22,499.84 Zelkova carpinifolia 14 27.52 0.21 4.60 0.00 £70,123.06 Acer rubrum 14 8.68 0.08 3.16 0.00 £23,115.22 Philadelphus 14 0.12 0.02 0.65 0.00 £949.28 Sorbus torminalis 13 8.72 0.10 2.72 0.00 £27,789.83 Fraxinus pennsylvanica 13 1.31 0.05 4.20 0.00 £8,840.67 Liquidambar styraciflua 13 0.19 0.02 0.79 0.00 £693.38 'Worplesdon' Cedrus atlantica v. glauca 12 3.58 0.07 2.29 0.00 £20,664.77 Ligustrum japonicum 12 1.14 0.07 2.39 0.00 £2,686.67

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

Chamaecyparis obtusa 12 0.48 0.02 0.79 0.00 £2,297.79 Viburnum rhytidophyllum 12 0.05 0.01 0.51 0.00 £922.50 Eucalyptus 11 5.58 0.12 3.90 0.00 £10,869.41 Ceanothus 10 33.93 0.13 1.51 0.00 £93,757.60 Zelkova serrata 10 10.99 0.14 2.94 0.00 £24,492.30 Acer ginnala 10 7.05 0.05 2.81 0.00 £23,034.89 Acer cappadocicum 10 6.99 0.13 4.35 0.00 £21,260.67 Prunus x hillieri 10 1.97 0.08 2.13 0.00 £4,336.43 Sorbus latifolia 10 1.13 0.06 1.66 0.00 £3,683.44 Trachycarpus fortunei 10 0.06 0.00 0.79 0.00 £2,796.28 Chitalpa 9 10.88 0.11 2.59 0.00 £27,861.40 Aesculus 9 5.76 0.16 6.54 0.00 £15,855.68 Crataegus laevigata 9 7.24 0.08 0.92 0.00 £15,602.41 Betula nigra 9 4.51 0.14 4.16 0.00 £12,905.76 Ligustrum lucidum 9 1.30 0.04 0.84 0.00 £3,058.95 Malus prunifolia 8 8.44 0.09 2.29 0.00 £25,774.15 Photinia fraseri 8 10.23 0.10 1.06 0.00 £22,297.94 Quercus acutissima 8 6.65 0.10 2.30 0.00 £14,278.50 Albizia julibrissin 8 3.25 0.08 2.11 0.00 £8,818.99 Ulmus 'New Horizon' 8 8.08 0.05 2.40 0.00 £6,630.75 Taxus 8 1.01 0.03 2.17 0.00 £6,458.55 Aesculus flava 8 1.53 0.07 3.13 0.00 £4,178.30 Larix decidua 8 0.44 0.02 1.39 0.00 £1,458.87 Pyrus calleryana 'Red Spire' 8 0.24 0.02 0.37 0.00 £755.50 Tilia americana 8 0.13 0.02 0.74 0.00 £706.34 Crataegus x grignonensis 8 0.19 0.02 0.41 0.00 £531.79 Sequoiadendron giganteum 7 5.89 0.08 3.75 0.00 £28,719.45 Pinus pinaster 7 3.81 0.08 4.12 0.00 £27,333.59 Lagerstroemia 7 7.63 0.10 0.60 0.00 £17,671.57 Sorbus hupehensis 7 0.27 0.02 0.65 0.00 £849.11 Luma apiculata 7 0.06 0.01 0.05 0.00 £474.64 Celtis occidentalis 6 18.30 0.17 2.05 0.00 £44,747.16

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

Cercis canadensis 6 7.60 0.04 1.34 0.00 £20,736.69 Pinus wallichiana 6 1.48 0.04 1.88 0.00 £11,276.98 Alnus viridis 6 2.66 0.09 2.67 0.00 £8,800.63 Aesculus x carnea 'Briottii' 6 2.87 0.08 3.50 0.00 £8,093.14 Malus 'John Downie' 6 2.18 0.05 0.80 0.00 £6,822.80 Cedrus 6 0.34 0.02 0.59 0.00 £1,927.79 Malus floribunda 5 6.78 0.10 1.53 0.00 £17,578.08 Cydonia oblonga 5 7.13 0.03 0.87 0.00 £15,738.61 Acer platanoides 'Schwedleri' 5 4.55 0.10 4.23 0.00 £15,366.68 Tilia henryana 5 2.49 0.05 1.65 0.00 £11,381.81 Cornus mas 5 3.62 0.06 0.78 0.00 £6,557.03 Azara microphylla 5 0.34 0.03 0.72 0.00 £709.91 Pseudopanax 5 0.15 0.02 0.41 0.00 £359.70 Euodia 4 20.44 0.06 1.12 0.00 £53,605.26 Ostrya carpinifolia 4 8.01 0.04 1.23 0.00 £21,609.81 Acer monspessulanum 4 2.89 0.07 3.15 0.00 £10,268.65 Nothofagus antarctica 4 4.06 0.06 1.00 0.00 £7,568.70 Fraxinus angustifolia 4 1.31 0.04 1.66 0.00 £5,318.52 Salix cinerea 4 1.16 0.05 1.23 0.00 £3,798.51 Pinus mugo 4 0.42 0.01 0.67 0.00 £3,669.42 Quercus phellos 4 0.11 0.01 0.36 0.00 £3,082.09 Prunus serotina 4 0.59 0.04 0.97 0.00 £1,199.31 Araucaria araucana 4 0.07 0.01 0.23 0.00 £359.76 Betula lenta 4 0.05 0.01 0.25 0.00 £307.50 Liriodendron tulipifera 4 0.09 0.01 0.60 0.00 £280.67 'Fastigiatum' Davidia involucrata 3 6.73 0.02 0.81 0.00 £14,863.40 Clerodendrum trichotomum 3 2.49 0.05 0.46 0.00 £6,672.57 Picea 3 0.32 0.02 0.70 0.00 £1,068.29 Picea sitchensis 3 0.07 0.01 0.19 0.00 £230.62 Ziziphus 3 0.05 0.01 0.10 0.00 £224.29 Alnus rubra 2 13.61 0.03 1.27 0.00 £37,578.66 Aesculus pavia 2 8.49 0.05 1.52 0.00 £22,403.45

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

Salix pentandra 2 6.99 0.02 0.81 0.00 £21,939.78 Cornus controversa 2 3.19 0.05 0.59 0.00 £5,930.14 Pinus strobus 2 0.86 0.02 0.93 0.00 £5,301.88 Cupressus lusitanica 2 0.84 0.02 0.35 0.00 £4,690.66 Picea pungens 2 0.29 0.01 0.55 0.00 £951.44 Sorbus vilmorinii 2 0.24 0.01 0.41 0.00 £732.97 Abies lasiocarpa 2 0.22 0.01 0.51 0.00 £659.50 Jubaea chilensis 2 0.02 0.00 0.24 0.00 £358.87 Acacia pravissima 2 0.15 0.01 0.34 0.00 £349.26 Prunus incisa 2 0.14 0.01 0.28 0.00 £216.98 Thuja orientalis 2 0.03 0.00 0.07 0.00 £166.79 Sorbus domestica 2 0.01 0.00 0.08 0.00 £158.44 Abies grandis 2 0.05 0.00 0.16 0.00 £135.97 Michelia doltsopa 2 0.01 0.00 0.10 0.00 £135.61 Sorbus americana 1 6.75 0.02 0.43 0.00 £21,135.77 Euonymus latifolius 1 6.78 0.02 0.70 0.00 £18,269.38 Carya cordiformis 1 5.35 0.07 0.46 0.00 £9,271.97 Pinus radiata 1 0.58 0.01 0.50 0.00 £4,055.61 Quercus acerifolia 1 0.52 0.02 0.47 0.00 £1,669.59 Catalpa speciosa 1 0.22 0.01 0.31 0.00 £729.16 Pinus x holfordiana 1 0.08 0.00 0.16 0.00 £375.36 Magnolia x soulangeana 1 0.12 0.01 0.27 0.00 £320.36 Picea orientalis 1 0.11 0.01 0.24 0.00 £289.56 Quercus velutina 1 0.07 0.01 0.13 0.00 £129.14 Acer capillipes 1 0.06 0.00 0.22 0.00 £121.37 Quercus muehlenbergii 1 0.05 0.00 0.12 0.00 £114.39 Styrax japonicus 1 0.06 0.00 0.16 0.00 £113.90 Viburnum 1 0.04 0.00 0.05 0.00 £87.58 Malus baccata 1 0.00 0.00 0.05 0.00 £76.88 Quercus imbricaria 1 0.00 0.00 0.01 0.00 £76.87 Quercus x ludoviciana 1 0.00 0.00 0.02 0.00 £76.87 Hibiscus 1 0.00 0.00 0.02 0.00 £71.94

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

Callistemon 1 0.01 0.00 0.01 0.00 £67.81 Cladrastis 1 0.01 0.00 0.06 0.00 £67.81 Rhamnus cathartica 1 0.01 0.00 0.03 0.00 £67.81 Thuja 1 0.01 0.00 0.04 0.00 £61.33 Abies nordmanniana 1 0.02 0.00 0.06 0.00 £50.74

Total 102426 57269 986 35411 21 £165,854,112.00

54 Appendix IV. Notes on Methodology Data Formatting

Tables 7 to 12 (below) show the list of edits which were made for this project in order to enable the street tree inventory to be processed.

In total, 55,076 records were provided.

Reason for Addition Details Number of records added

Count column lists duplicate These are trees which have 27459 trees duplicate details in each column.

NUMBER OF RECORDS 102,426 IMPORTED

Table 7: Inventory Records added for use in Eco

Reason for Removal Details Number of records removed

No Species There is no data in this field (a 23 minimum requirement for Eco)

NUMBER OF RECORDS 23 REMOVED

Table 8: Inventory Records removed for use in Eco

SULE Rating New Condition Rating i-Tree Equivalent

80 + Good Condition 87%

40 - 80 Good Condition 87%

10 - 20 Fair Condition 82%

20 - 40 Fair Condition 82%

< 5 Poor Condition 62%

05 - 10 Poor Condition 62%

None Fair 82%

Table 9: Condition Ratings for use in Eco

Height (Supplied) (m) DBH (Averaged) (cm)

0-3 7

55 Height (Supplied) (m) DBH (Averaged) (cm)

4-6 14

7-9 21

10-14 28

15-19 35

20-24 42

Table 10: Missing DBH Regression table for use in Eco

Crown Condtion SLE Value

Fair 10 - 20

Table 11: CAVAT Safe Life Expectancy Estimates

Incomplete data Assumption made

No SPECIES Supplied Miscellaneous Group/Mixed Species/Unknown Species - Oak, Ash, Field Maple - 1040 records

No DBH or HEIGHT Supplied 1600 records for DBH - 25cm average 2342 records for Height - 8m average

Woodlands: Species: Quercus robur DBH: 30cm Height: 15m Condition: Fair SULE: 40 - 80 years

Table 12: Assumptions made where dataset was incomplete

Woodland Name Area (ha) Density (trees Number of Trees per hectare)

Dulwich Upper Wood 2.4 500 1200

Syddenham Hill Wood 11 500 5500

Table 13: Woodland Tree Estimates

Species Name in Report Species Name in Dataset

Platanus x acerifolia Platanus x hispanica

Table 14: Species Name Changes

56 i-Tree Methodology 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 equations26. 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

26 Nowak 1994 57 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 decomposition27.

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 models28. 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 literature29 30 that were adjusted depending on leaf phenology and leaf area. Particulate removal incorporated a 50 percent resuspension rate of particles back to the atmosphere31. Annual avoided surface 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.

Replacement Costs were based on valuation procedures of the Council of Tree and Landscape Appraisers, which uses tree species, diameter, condition and location information32 33.

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

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

28 Baldocchi 1987, 1988

29 Bidwell and Fraser 1972

30 Lovett 1994

31 Zinke 1967

32 Hollis, 2007

33 Rogers et al (2012) 58 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 Community Tree Index (CTI) 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 Southwark is 2.00, 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.

The Safe Useful Life Expectancy (SULE) was partially provided and the remainder based upon the condition assessment. This therefore may not be fully accurate, especially for each individual tree.

For full details of the method refer to Doick, et al (2018)34

34 Doick, et al (2018) 59 Bibliography

Average CO2 emissions of newly registered Doick, K.J., Davies, H.J., Handley, P., Vaz cars, Great Britain (2015) Monteiro, M., O’Brien, L., Ashwood F. (2016) https://www.gov.uk/government/uploads/ Introducing England’s urban forests: Definition, system/uploads/attachment_data/file/454981/ distribution, composition and benefits. veh0150.csv/preview UFWACN (Urban Forestry and Woodlands Advisory Committees (FWAC) Network), 14 pp. Baldocchi, D (1988). A multi layer model for Doick, K.J., Neilan, C., Jones, G., Allison, A., estimating sulfur dioxide deposition to a McDermott, I., Tipping, A., Haw, R. (2018) deciduous oak forest canopy. Atmospheric CAVAT (Capital Asset Value for Amenity Trees): Environment 22, 869-884. valuing amenity trees as public assets. Arboricultural Journal, 2018, Vol. 40, No.2, Baldocchi, D., Hicks, B., Camara, P (1987). A 67-91. canopy stomatal resistance model for gaseous deposition to vegetated surfaces. Atmospheric Escobedo, F., Nowak, D (2009). Spatial Environment. 21, 91-100. heterogeneity and air pollution removal by an urban forest. Landscape and Urban Planning, Barker, P.A. (1975) Ordinance Control of Street 2009 Vol. 90 (3-4) pp. 102-110. Trees. Journal of Arboriculture. 1. pp. 121-215. Forest Research, anon; Santamour, F.S, 1990 Bidwell, R., Fraser, D (1972). Carbon monoxide and Kendal, D, 2014). uptake and metabolism by leaves. Canadian Journal of Botany 50, 1435-1439. Forest Research (anon) The Right Tree in the Right Place for a Resilient Future [online] Davies, H.J., Doick, K.J., Handley, P., O’Brien, Available at: https://www.forestresearch.gov.uk › L. (2017) Delivery of ecosystem services by 7111_FC_Urban_Tree_Manual_V15 urban forests. Forestry Commission Research Report. Forestry Commission Edinburgh. I-IV Freer-Smith PH, El-Khatib AA, Taylor pp.1-28. G. Capture of particulate pollution by trees: a comparison of species typical of semi-arid areas Defra (2013) Chalara Management Plan. [Online] (Ficus nitida and Eucalyptus globulus) within Available at: https:// European and North American species, Water assets.publishing.service.gov.uk/government/ Air Soil Pollut , 2004 uploads/system/uploads/attachment_data/file/ 221051/pb13936-chalara-management- plan-201303.pdf

60 Green Cities: Good Health. Kuhns, M (2008). Landscape trees and global http://depts.washington.edu/hhwb/ warming. [Online] Available at: http:// gov.uk (2012) Green Book supplementary www.doughnut/articles/ guidance: valuation of energy use and green landscape%20trees%20and%20global%20war gas emissions for appraisal. Supplementary ming%20-%2... 1/15/2008 [Accessed: Sep 2 guidance to Treasury’s Green Book providing 2011]. government analysts with rules for valuing energy usage and greenhouse gas emissions Lovasi, G., Quinn, J., Neckerman, K., [online] Available at: https://www.gov.uk/ Perzanowski, M. & Rundle, A. (2008) Children government/publications/valuation-of-energy- living in areas use-and-greenhouse-gas-emissions-for- with more street trees have lower prevalence of appraisal Last Updated: 11.04.2019 asthma. Journal of Epidemiology & Community Health, 62(7), pp. 647. Hirabayashi, S. 2012. i-Tree Eco Precipitation Interception Model Descriptions, http://www.i- Lovett, G (1994). Atmospheric deposition of Treetools.org/eco/resources/i- nutrients and pollutants in North America: an Tree_Eco_Precipitation_Interception_Model_Des ecological perspective. Ecological Applications cript ions_V1_2.pdf 4, 629-650.

Hollis, A. (2007) Depreciated replacement cost Mcpherson, G. (2007) Urban Tree Planting and in amenity tree valuation. UKI-RPAC guidance Greenhouse Gas Reductions. Available at: note 1. https://pdfs.semanticscholar.org/ 3c16/93b7f0945cf4900d41c5a9dd54d9409ae7 IGCB. Air quality damage costs per tonne, 2010 ad.pdf prices [Online]. Available at:http:// www.defra.gov.uk/environment/quality/air/air- Nowak, D. (1994) Atmospheric carbon dioxide quality/economic/damage/ [Accessed: May reduction by Chicago’s urban forest. In, 20th 2011]. McPherson, E., Nowak, D., Rowntree, R., (Eds). Chicago’s urban forest ecosystem: Results of i-Tree. (2013) ‘i-Tree software suite v5’ [Online] the Chicago Urban Forest Climate Project. Available at: http://www.i-Treetools.org/ USDA Forest Service, Radnor, PA. resources/manuals.php [Accessed: Dec 2016].

Nowak, D., Civerolo, K., Rao, S., Sistla, G,. Kendal, D., Dobbs, C., Lohr, V.I. (2014) “Global Luley, C., Crane, D. (2000). A modeling study of patterns of diversity in the urban forest: is there the impact of urban trees on ozone. evidence to support the 10/20/30 rule?” Urban Atmospheric Environment 34, 1601-1613. Forestry & Forest Greening, 13(3), pp. 411-417.

61 Nowak, D.J., D.E. Crane, and J.C. Stevens. Trees Design Action Group (2014). Trees in Hard 2006. Air pollution removal by urban trees and Landscapes - A guide for delivery. [Online] shrubs available at: www.tdag.org.uk/trees-in-hard- in the United States. Urban Forestry and Urban landscapes.html Greening. 4(2006):115-123. Woodland Trust (anon) Plane wilt (Ceratocystis Nowak, David J., Hoehn, R., and Crane, D. platani) [online] Available at: https:// 2007. Oxygen production by urban trees in the www.woodlandtrust.org.uk/trees-woods-and- United States. Arboriculture & Urban Forestry wildlife/tree-pests-and-diseases/key-tree-pests- 33(3):220-226. and-diseases/plane-wilt/

Rogers, K,. Hansford, D., Sunderland, T., Brunt, Yorkshire Water (2019/2020). https:// A., Coish, N., (2012) Measuring the ecosystem www.yorkshirewater.com/media/1466/ services of Torbayʼs trees: The Torbay i-Tree Eco charges-2019-20.pdf pilot project. Proceedings of the ICF - Urban Tree Research Conference. Birmingham, April Zinke, P (1967). Forest interception studies in 13-14. the United States. In Sopper, W., Lull, H., eds. Forest hydrology. Oxford, UK: Pergamon Press Santamour, F.S. (1990) Trees for urban planting: 137-161. Diversity, uniformity and common sense, in: Proceedings of the Conference Metropolitan Tree Improvement Alliance (METRIA). pp. 57–65.

Sjöman, H., Östberg, J., Bühler, O. (2012) Diversity and distribution of the urban tree pollution in ten major Nordic cities. Urban Forestry and Urban Greening. 11. pp. 31-39.

Tiwary, A., Sinnet, D., Peachey, C., Chalabi, Z,. Vardoulakis, S., Fletcher, T., Leonardi, G., Grundy, C., Azapagic, A., T, Hutchings. (2009). An integrated tool to assess the role of new planting in PM₁₀ capture and the human health benefits: A case study in London. Environmental Pollution 157, 2645-2653.

62