scoping uk urban natural capital account noise...

SCOPING UK URBAN NATURAL CAPITAL ACCOUNT – NOISE EXTENSION

Final Report For Defra

July 2018

Scoping UK Urban Natural Capital Accounts – Noise Extension Final Report

eftec & CEH i July 2018

This document has been prepared for the Department for Environment, Food and Rural Affairs (Defra)

by:

Economics for the Environment Consultancy Ltd (eftec)

4 City Road

London

EC1Y 2AA

www.eftec.co.uk

in association with the Centre for Ecology and Hydrology (CEH).

Study team

Jake Kuyer (eftec)

Phil Cryle (eftec)

Ian Dickie (eftec)

Laurence Jones (CEH)

Dan Morton (CEH)

Amy Thomas (CEH)

Alice Fitch (CEH)

Peer reviewer / Reviewer

Ece Ozdemiroglu (eftec)

Acknowledgements:

The study team would like to thank would like to thank members of the steering group and others

for the time and effort they have contributed to developing this report: Colin Smith (Defra), Hilary

Notley (Defra), Rocky Harris (Defra), Victoria Burch (Defra).

Disclaimer This publication has been prepared for general guidance on matters of interest only, and does not constitute professional advice. You

should not act upon the information contained in this publication without obtaining specific professional advice. No representation or

warranty (express or implied) is given as to the accuracy or completeness of the information contained in this publication, and, to the

extent permitted by law Economics for the Environment Consultancy Ltd, their members, employees and agents do not accept or

assume any liability, responsibility or duty of care for any consequences of you or anyone else acting, or refraining to act, in reliance

on the information contained in this publication or for any decision based on it.

eftec offsets its carbon emissions through a biodiversity-friendly voluntary offset purchased from

the World Land Trust (http://www.carbonbalanced.org) and only prints on 100% recycled paper.

http://www.eftec.co.uk/

http://www.carbonbalanced.org/


eftec & CEH ii July 2018

CONTENTS

KEY MESSAGES ................................................................................. 3

Key recommendations for future work ........................................................................ 5

1. INTRODUCTION ........................................................................... 6

1.1. Background ................................................................................................ 6

1.2. Study objectives .......................................................................................... 7

1.3. Report structure .......................................................................................... 7

2. SCOPE ...................................................................................... 9

2.1. Natural capital accounting framework ............................................................... 9

2.2. Natural capital assets .................................................................................. 10

2.3. Noise sources............................................................................................. 10

2.4. Urban boundary.......................................................................................... 10

3. METHODOLOGY ......................................................................... 12

3.1. Physical account of natural capital extent (Step 1) .............................................. 12

3.2. Physical account of natural capital condition (Step 2) ........................................... 13

3.3. Physical account of ecosystem service provision and use (Step 3) ............................. 13

3.4. Accounting for the supply and use of ecosystem services (Step 4)............................. 17

3.5. Upscaling of flow of physical account, supply and use (Relevant to steps 1-4) .............. 17

3.6. Monetary account of annual provision of ecosystem services (Step 5) ........................ 19

3.7. Monetary account of future provision of ecosystem services (Step 6) ......................... 21

4. RESULTS ................................................................................. 23

4.1. Physical account of natural capital extent ......................................................... 23

4.2. Physical account of natural capital condition ...................................................... 24

4.3. Physical account of ecosystem service provision .................................................. 25

4.4. Monetary account of annual provision of ecosystem service .................................... 26

4.5. Monetary account of future provision of ecosystem service .................................... 27

5. CONCLUSIONS AND RECOMMENDATIONS ........................................... 29

5.1. Summary .................................................................................................. 29

5.2. Recommendations ....................................................................................... 32

Addendum .................................................................................... 34

Glossary ....................................................................................... 40

Appendix 1 – ELECTRIC VEHICLES ........................................................ 41

REFERENCES ................................................................................. 43

Separate Documents:

ANNEX 1: Excel Workbooks


eftec & CEH 3 July 2018

KEY MESSAGES

This scoping study has tested how a natural capital account for noise mitigation in urban areas can

be developed in the UK. It builds on the methods for estimating noise regulation developed in the

precursor UK urban natural capital accounting scoping study (eftec et al, 2017). The underlying

structure follows that set out by SEEA (UN, 2013) and the Defra/ONS principles paper (Defra/ONS,

2017) as used in existing UK natural capital accounts. It features five accounts: extent, condition,

physical flow, annual monetary flow and monetary flow over time. A set of recommendations for

refining the coverage of noise mitigation in the initial UK urban natural capital account are also

provided.

The account shows the significant value provided by the UK’s urban woodland1 in terms of improved

amenity and health outcomes due to noise mitigation2. The urban initial scoping account (eftec et

al, 2017) produced estimates for noise mitigation by urban woodland in Greater Manchester only.

These calculations have been expanded to a national scale, showing how methods can be applied

across both national and local scales. The estimates in this report exclude impact outside of the

urban context and small scale green assets (e.g. shrubs and bushes). Therefore, while they are likely

an underestimate of overall value, they do give an indication of the scale of impact3.

Two approaches were adopted based on different data sources, National Tree Map (NTM) and

Ordnance Survey Master Map (OSMM). Results are presented for both. NTM provides a more robust

data source at finer resolution, but was only available for Manchester. So when extrapolating up to

UK level, that carries a larger uncertainty than just using the OSMM, which was available for all of

GB. Therefore, in general, the OSMM based approach is recommended as the preferred of the two.

Accompanying Excel documents4 provide detail on the data sources, assumptions, method steps and

calculations that underpin this analysis. As an element of uncertainty remains in the assumptions

adopted, conservative values were applied where appropriate. Table S.1 shows the physical and

monetary value estimated for both approaches included in this extension to the scoping account5.

Table S.1. Total UK Physical, Annual and Asset value of road noise regulating benefits from urban

natural capital using NTM and OSMM data

1 The coverage of natural capital assets is limited to woodland within the UK urban boundary. 2 This account focusses on the benefits of vegetation in reducing urban noise exposure for major roads only.

Aircraft noise is scoped out because natural capital has limited capacity to reduce this. 3 There is inherent uncertainty in the absolute values generated; however, these accounts are most useful when

repeated over time so that they can inform what the changes are and why they come about, aiding in the design

of policy and private sector intervention. 4 UK Urban Natural Capital Account Noise Extension_OSMM.xlsx

UK Urban Natural Capital Account Noise Extension_NTM.xlsx 5 The results are subject to a number of assumptions and caveats discussed throughout the report and

summarised in section 5.1, including: estimations of the noise reduction potential of vegetation, the choice of

approach in quantifying tree cover, the spatial location of residential buildings and the number of inhabitants

subject to noise impacts.

NTM approach OSMM approach

Number of

buildings 8,228,000 2,099,000

Annual

Value £245 million £66 million

Asset Value

(100 NPV) £13,310 million £3,577 million



The method applied for modelling the effect of urban vegetation on noise in the study Scoping UK

Urban Natural Capital Account – Noise Extension is an innovative and experimental method of

modelling noise mitigation for valuing urban natural capital. It represents a considerable

improvement on ecosystem service assessment approaches to this which have been conducted

previously. However, by necessity it differs from conventional noise modelling approaches which use

much more sophisticated models, with an associated time and computational cost. Conventional

noise modelling has not previously considered vegetation effects explicitly, but does modify

absorbance values under different types of landcover, often based on Corine data. Therefore, a trial

was undertaken by Acustica using commercial noise modelling software to compare the two

approaches, and improve the interpretation of the impact of urban woodland on noise reduction.

The output of the Acustica NTM_1.25 model should also be viewed critically, as the approach used is

not without caveats. An attempt has been made to simulate the effect of urban woodland on noise

reduction through increasing the ground absorbance value below the woodland and representing the

woodland as a 1.25m high barrier. Acustica results suggest that the mitigation effect of thick

woodland may be underestimated while the benefit from thinner tree bands may be overestimated.

Having assessed the impact of these differences in a small (3 x 3 km2) test area of North West

Manchester, some amendments are suggested to constrain the eftec-CEH UK results:

It is recommended that only mitigated area in noise bands above 60dBA is considered, this

would reduce the overestimation of the benefits provided by urban woodland and account

somewhat for flanking effects.

It is proposed that all 2dBA mitigated areas should be assigned to 1dBA. This would counter

the overestimation of 2dBA areas and provide an estimate of the impact of urban woodland

on noise reduction that is closer to the conventional noise modelling approach.

The accounts were amended with these constraints to bring the physicals accounts more in line

with what would be expected if extrapolating from the small test site used in the Acustica

NTM_1.25 trial to the whole of the UK. Subsequently the overall values from both the physical and

monetary accounts were significantly reduced. Table S.2. presents the results from the amended

accounts for both the NTM and OSMM approaches.

Table S.2. Total UK Physical, Annual and Asset value of road noise regulating benefits from urban

natural capital using NTM and OSMM data, amended approach

While we have confidence in the overall approach, there is clearly an implication from the data

sources and extrapolation methods applied in the physical accounts. Until such time as the approach

can be refined, or higher resolution data sets become available, we recommend conservatively using

the OSMM approach values, and accounting for dwellings lying within noise bands of 60dBA and above

and applying only a 1dB impact6.

6 Choice of the OSMM method is preferred, even though it omits the finer resolution data available in NTM

because of how noise propagates around barriers. The coarser resolution OSMM data makes this less important

because in general the woodland patches are larger, meaning that edge effects are smaller. Incorporation of

smaller patches in the NTM method exacerbates the influence of edge effects, and contributes to an over-

estimate using the current noise mitigation calculations in the approach taken in this study.

NTM approach OSMM approach

Number of

buildings 467,000 167,000

Annual

Value £41 million £14 million

Asset Value

(100 NPV) £2,168 million £786 million



Key recommendations for future work

The datasets used for this national level estimate of noise mitigation have been selected on the basis

of being readily available, of sufficient quality and in appropriate format to allow a reasonable order-

of-magnitude estimate for the physical and monetary value of this ecosystem service. There are

additional datasets and methods that can be explored to refine and/or validate the values produced

in this account. This includes, but is not limited to, the following sources and methods:

i. The noise mapping commissioned by central and devolved governments could be adapted to

include vegetation effects. This would entail two separate modelling exercises, i.e. one

which incorporates vegetation, as a barrier and with improved ground absorbance values,

and one which does not, to calculate the effect of vegetation by difference between the two

scenarios (similar to the approach taken by CEH for air quality modelling (Jones et al. (2017));

ii. Further refinement of the noise levels by using different metrics as appropriate (Lden, Lnight,

Lday) may help achieve improved monetisation of the health impacts;

iii. Use of a UK dataset for tree-cover that is of sufficiently high resolution, such as the Bluesky

National Tree Map7 (potential restrictions on using this, and the degree to which it provides

national coverage, will need to be understood) or similar products being designed by other

organisations. This would underpin an improved estimate of the noise mitigation service,

replacing the current extrapolated calculation;

iv. The current approach could be adapted to include seasonality aspects to account for

differential noise mitigation in summer compared with winter when deciduous trees have lost

their foliage. The trunks and branches of trees without foliage still provide a degree of noise

mitigation (Van Renterghem, 2014) so this service is also provided in autumn/winter, albeit

less so than in spring/summer. The current approach assumes an equal level of noise levels

and equal levels of mitigation throughout the year, and might over-estimate the service

provided in winter; and

v. There remains a lack of consensus on the magnitude of decibel reduction provided by

vegetation (Van Renterghem et al. 2012). This would require new data collection and

experiments under field conditions, to inform what magnitude of service that vegetation of

different structures and composition provides.

Alternative methods of valuing the benefits provided by vegetation could also be explored, including:

i. The use of hedonic pricing to ascertain if the value of noise dissipation by vegetation can be

captured in house price premiums. This could link the mapping in this study with the hedonic

pricing work ongoing in ONS;

ii. Revealed preference methods – focusing on estimating the extent to which technology/built

capital is used to replace the noise dissipating impacts of vegetation such as through

double/triple glazing or fencing of dual carriageways and other road side noise barriers, and

the associated costs of such technology. This would align more closely with an exchange

value; and

iii. Finally, the natural capital condition account could be developed. For this scoping study,

indicators of natural capital condition have been proposed for the future quantification based

on evidence of their importance to ecosystem service provision.

7 Information available from website accessed here: https://www.bluesky-world.com/ntm

https://www.bluesky-world.com/ntm



1. INTRODUCTION

1.1. Background

This report presents a natural capital account for the potential noise reducing benefit provided by

vegetation in urban areas in the UK. Natural capital accounts show the value of the stock of natural

capital on the basis of the quantity and economic value of the flows of ecosystem services they

provide. This extension to the urban account will form part of the suite of interconnected accounts

that are being developed for the Office for National Statistics and Defra for incorporation to UK

Environmental Accounts by 2020. They are two kinds of account: (i) physical accounts compile

information on the extent, condition and annual service flow from assets, and (ii) monetary accounts

show the economic value of quantified services on an annual basis, and in total based on the asset’s

ability to generate future flows of services.

This study follows work done to estimate the potential noise reducing benefit of vegetation for the

City of Manchester under the UK urban natural capital account scoping study (led by eftec, with the

Centre for Ecology and Hydrology, Collingwood Environmental Planning, Peter Neal Associates and

the University of Exeter). The headline results from that analysis are outlined in Table 1.1.

Table 1.1. Summary physical and monetary flow account of noise urban natural capital and

certainty assessment from scoping study (eftec et al, 2017).

Ecosystem service Physical flow account Monetary flow account (£/year)

Noise regulation – Manchester only 429,000 buildings with dBA mitigation

£59m

The estimated value of the service for Manchester is £59m/year based on 429,000 buildings having a

decibel reduction due to the existence of vegetation. This city scale was appropriate because:

i) Noise regulation is highly spatially specific - estimating the benefit with an acceptable level

of certainty requires highly resolute (detailed) data. The Woodland Trust helpfully provided

an excerpt of the National Tree Map (which identifies individual trees) for Manchester to

enable the analysis, otherwise obtaining such data would have been prohibitively costly for

the study;

ii) The method was innovative and experimental - no existing analysis has been done to

estimate the noise mitigating benefit provided by urban vegetation. There have been few

attempts to upscale noise reduction by vegetation in the UK. A study by Bateman et al. (2004)

created a method to value changes in noise levels, based on hedonic pricing. This was

reviewed by Nellthorp et al. (2007) and found to be comparable to other valuation studies in

Europe. Noise reduction is included in the EcoServ-GIS toolkit (Durham Wildlife Trust, 2012),

where the service from the natural environment is mapped by assigning a noise regulation

score to vegetation types, based on height, density, permeability and year round cover. It

has been applied in a few case studies (e.g. Sussex Wildlife Trust, Horsham case study, Sussex

Wildlife Trust, 2016). Some recognition of noise reduction as a service is also applied in the

South West Peak landscape opportunity mapping case study (Rouquette and Holt, 2016),

which utilised the CPRE National Tranquillity Data set 2007 (CPRE, 2007). The CPRE national

tranquillity map is based on 40 positive and negative indicators. The latter includes noise

levels from road and rail and visual blight from transport networks.

Possible reasons why such analysis has not been conducted previously may be that: noise

consultants have worked to a brief that has not included the role of vegetation in large scale



modelling (e.g. national noise mapping), since vegetation has previously been considered as

providing little additional benefit to that of sound absorption by soft ground. However, this

view is changing (e.g. van Renterghem et al. 2012; van Renterghem 2014; HOSANNA report

2013). It is also likely that the ecosystem services research community is largely unaware of

the existence of the national noise mapping data and because simpler assessments have

focused to a great extent on land cover rather than spatial context, they are only recently

becoming aware of the spatial tools to conduct such analyses.

The indicative value for Manchester in the urban account scoping study suggested that the UK scale

value across all urban areas could be significant within the context of the values in Table 1.1 (i.e.

billions of pounds a year). This potential value is driven by the amenity (sleep disturbance and

annoyance) and health implications (strokes, dementia, and heart attacks) of environmental noise,

which according to the World Health Organisation (WHO) is the second largest environmental health

risk in Western Europe (WHO, 2011).

1.2. Study objectives

The aim of this study is to extend the existing physical and monetary analysis of noise regulating

benefits of natural capital in urban areas to cover (if possible) the entire UK. This work will enable

Defra and ONS to make further progress in developing a full set of natural capital accounts for the

UK in line with the 2020 Natural Capital Accounting Roadmap.

Achieving this ambitious objective requires addressing both conceptual and practical challenges in

the process of estimating and reporting the ecosystem service flows associated with UK urban natural

capital. Inevitably the present work is subject to gaps in both scientific understanding of urban

ecosystems and the availability of data and methods. Overall the key contribution of the study is to

demonstrate and test the feasibility of developing estimates of noise regulating benefits of urban

natural capital at the UK scale, and assess how this could be refined in the future. Because this is a

scoping study, the account presented measures the current value of the urban stock and a discounted

value stream over the assessment period but does not measure changes over time.

1.3. Report structure

The remainder of this report is structured as follows:

Section 2

Scope: the natural capital accounting framework, the boundary of the urban area and

the natural capital assets included within the account.

Section 3

Method: the steps undertaken to develop the initial UK urban natural capital account

for noise, including the approach to quantifying and valuing natural capital stocks

and flows.

Section 4

Results and discussion: proof-of-concept physical and the monetary accounts for UK

urban areas for noise.

Section 5 Conclusions and recommendations: the application (purpose) of the urban natural

capital account for noise, along with the current limitations of data and potential

future refinement of the accounts.

The report is accompanied by an Annex supporting the decision that the impact from the

electrification of the vehicle fleet is not a material consideration for this assessment. In addition to



this document, an accompanying Excel file provides detail on the data sources, assumptions, method

steps and calculations that underpin this urban natural capital account for noise.



2. SCOPE

2.1. Natural capital accounting framework

Defra and ONS (2017) outline the key principles and framework structure to be followed when

developing natural capital accounts in the UK as part of the ONS Environmental Accounts. The

framework features two main types of account: (i) stock (assets) accounts which capture information

on the natural capital assets (e.g. freshwaters, grasslands) and (ii) flow (ecosystem services) accounts

which report information on the annual benefits produced by the natural capital assets (e.g.

recreation, climate regulation). Both stock and flow accounts are made up of several accounting

schedules that record monetary or physical (non-monetary) benefits, as shown in Figure 2.1. An

account is developed by collating and analysing financial, economic, social and environmental data

on natural capital across the UK, including via the use of Geographical Information Systems (GIS).

Figure 2.1 The general framework of national natural capital accounting schedules (Defra/ONS,

2017)

For the purposes of developing this account of the noise regulating effects of urban vegetation, the

scope of each account is defined as follows:

1. Physical account of natural capital extent (stock account): this account reports data on the

extent (size) of natural capital assets (see Section 2.2) relevant for this analysis of noise

mitigation, within the defined urban boundary (see section 2.4) for England, Scotland and Wales;

and uses simple extrapolation techniques to extend the estimates to include Northern Ireland.

2. Physical account of natural capital condition (stock account): for the purposes of this account,

bio-physical data on the key characteristics of the condition of natural capital assets has not been

collated but relevant metrics are noted.

3. Physical account of ecosystem service provision and use (flow account): reporting the physical

flow of ecosystem service which in this case is measured by the number of buildings for which

noise is mitigated by vegetation. Mapping the spatial area from which the ecosystem services are

generated (i.e. where vegetation is located) and the areas in which ecosystem services benefits

are delivered (i.e. where beneficiaries are located) are also set out.

4. Monetary account of annual provision of ecosystem service (flow account): reporting the

annual economic value of ecosystem service produced. This is the value of avoided disamenity



(sleep disturbance and annoyance) and avoided costs of health implications (strokes, dementia,

and heart attacks) associated with reductions in people’s exposure to environmental noise as per

UK government economic valuation guidance (Defra, 2014a). This requires identifying the

affected population, which is estimated based on the number of households affected as estimated

in the physical account.

5. Monetary account of future provision of ecosystem service (stock account): deriving economic

values for the assets by aggregating forecasted future flows (in this case 100 years) of ecosystem

service. In the case of noise mitigation, relevant variables to account for are: (i) car data – with

the possibility of quieter electric vehicles replacing those with combustion engines; (ii) number

of households affected; (iii) population demographics; and (iv) economic growth (income

growth).

2.2. Natural capital assets

The coverage of urban natural capital assets is limited to woodland within the UK urban boundary

(see section 2.4). This is because the noise modelling done by Defra specifies receptors at 4 metre

elevation on the basis that most of the health implications of noise are experienced during the night

when people sleep upstairs. While noise mitigation by other natural capital assets such as shrubs and

hedges is increasingly considered to occur, for this study we deemed them out of scope.

2.3. Noise sources

Noise dissipation depends in part on the presence and height of vegetation in relation to the height

of the noise source8. For this reason, aircraft noise is scoped out because natural capital has limited

capacity to reduce this. Construction noise is not (usually) consistently located in the same place

over time and therefore there is limited scope to manage vegetation to provide a service to reduce

it. Therefore, this account focusses on the benefits of vegetation reducing urban noise exposure for

major roads only. However, the method developed is applicable to both road and rail. In terms of

road traffic, the impact of the electrification of the road fleet has been considered and a decision

reached that it is not likely to be material to this assessment. Further details can be found in Annex

1.

2.4. Urban boundary

The urban boundary used for this analysis was developed by the project team under the UK Urban

account scoping project, which is based on the ONS (2011) Built-Up-Area dataset. The noise modelling

data used to calculate the account covers urban agglomerations with more than 100,000 people, and

major roads, and comes from the Round 2 mapping in England, Wales, Scotland, and Northern Ireland

(see Table 3.2 for sources of this data).

The Defra/ONS (2017) principles paper states that the starting point for any classification of

ecosystem types is the Land Cover Map (LCM). However, because this is based on land cover, the

definition of ‘urban’ includes gardens, roads and buildings, but excludes most green and blue spaces

which are captured under other categorisations (i.e. grassland, freshwaters). Therefore, defining the

urban area for the purposes of an urban natural capital account requires a departure from the use of

the LCM, with subsequent reconciliation to avoid double counting across UK natural capital accounts

by identifying the extent of overlaps with other broad habitat accounts that have been developed

using the LCM.

8 For example, while some studies suggest that hedges have little effect, hedges higher than 1.5 meters can act as a noise

barrier if they come between the noise and the receiving human population (Fang & Ling 2003).



The ONS (2011) Built-Up-Areas dataset was selected for the urban account on the basis that:

(i) It captures all built-up-areas and therefore all areas that will not be included in other

broad habitat accounts (this is not the case for Rural Urban Classification 2011 (RUC2011),

Major Towns and Cities);

(ii) Other urban classifications (e.g. major towns and cities) can be looked at within this

dataset, and

(iii) It is based on physical settlement morphology and not statistical units (i.e. Output Areas

that RUC2011 uses) which will extend into rural areas. The basic methodology to

‘enhance’ the urban boundary involved temporarily applying a variable sized buffer to

the existing ONS2011 built up area (BUA) layer. The buffer is scaled in proportion to the

area of the polygon (using the equation Buffer width = 0.012 * √Polygon area) 9. This

effectively ‘captures’ the majority of urban green and blue space within each urban area.

The buffer is then collapsed back to the original extent but including any new ‘captured’

green and blue infrastructure. For further information on how this boundary was

estimated, see the UK urban natural capital account scoping study report (eftec et al,

2017).

9 We apply a buffer scaled relative to an absolute size rather than relative to the largest polygon (i.e. London)

because if the largest polygon expanded and the buffer was expressed relative to this polygon, the size of the

buffer applied to other areas would change, even for polygons experiencing no change in size. This could

potentially lead to inconsistencies in what is included compared with previous accounts. The scaling results in a

buffer of approximately 500m for a polygon the size of Greater London.



3. METHODOLOGY

The urban natural capital account for noise is scoped following a six-step methodology:

Step 1: Physical account of natural capital extent

Step 2: Physical account of natural capital condition

Step 3: Physical account of ecosystem service provision and use

Step 4: Accounting for the supply and use of ecosystem services

Step 5: Monetary account of annual provision of ecosystem services

Step 6: Monetary account of future provision of ecosystem services

This chapter describes this method used to quantify and value the noise regulating ecosystem service

from urban environments in the UK. An accompanying Excel document outlines the data sources,

assumptions, method steps and calculations that underpin this analysis.

3.1. Physical account of natural capital extent (Step 1)

For this study, the ‘extent’ account refers to the urban area as defined under this project and the

area of natural capital assets within this area that are assumed to provide a noise mitigation service.

This focuses on trees/woodland areas which are mapped using the Ordnance Survey Master Map

(OSMM) which is the best available dataset to identify urban greenspace at a national scale. This

differs from the approach taken in the Urban natural capital accounting scoping study (eftec et al,

2017) which used the Bluesky’s National Tree Map (NTM) (Bluesky, 2017) which maps individual trees.

An excerpt of the NTM for Manchester was kindly provided by the Woodland Trust. However, the NTM

would have been prohibitively costly for this study to obtain, and therefore it could not be used.

OSMM was not available for Northern Ireland, for which CEH Landcover Map 2007 (LCM2007) was used

as a proxy for estimating the noise mitigation service there.

A comparison of the NTM, OSMM and LCM07 for Greater Manchester shows that:

The area of land that is classified as woodland greater than 200 m2 providing a service in

Manchester is largest in the OSMM: a total of 188 km2 for OSMM vs 112 km2 for NTM and 36 km2

for LCM2007 for this asset class. The OSMM area is bigger because OSMM defines polygons that

include trees as recorded by the surveyors in the description of each mapping unit, but are not

necessarily purely woodland.

Although the area is larger in OSMM, the area where noise is mitigated is smaller. This is because

the shape of the OSMM polygons fail to capture many of the linear features of continuous tree

canopy along roads which is captured by NTM. Thus, the mitigated area is 26 km2 for OSMM vs

412 km2 for NTM and 89 km2 for LCM2007.

Given the size and likely representativeness of large and small urban areas within Greater Manchester

compared with the UK, these observed differences in the shape and resolution of the different

tree/woodland layers, and consequent impacts on the size of the mitigated area, are likely to be

broadly similar for other UK urban areas. Therefore, the OSMM-based approach conducted at a

national scale is also likely to substantially under-estimate the mitigated area compared to the finer

resolution NTM data. Therefore, in this report, we present two estimates: an approach based on the

OSMM data, scaled to the UK, which represents a lower estimate, and an approach based on NTM

data for Manchester, upscaled with a number of assumptions detailed in Section 3.5 which represents

an upper estimate.

However, uncertainties in the spatial modelling approach and the lack of benchmarked data against

which to compare results mean that it is not currently possible to say to what extent these are over-



or under-estimates of the likely service provided. The most definitive answer would be provided by

bespoke noise modelling which incorporates the potential influence of woodland in addition to

buildings, topography and ground cover in noise mitigation. Ideally it would calculate the building

façade noise levels, and could use a method which is not the UK CRTN, but possibly Harmonoise,

Nord2000 or CNOSSOS-EU calculating in octave bands.

3.2. Physical account of natural capital condition (Step 2)

The condition account plays a critical role in estimating the benefits provided by natural capital, not

all of which could be included in the physical or monetary account. The broad dimensions of natural

capital condition from the Defra/ONS (2017) principles paper align to the following split:

The state of the natural capital asset: as measured through relevant volume estimates (e.g.

timber biomass), biodiversity indicators (e.g. abundance), soil indicators (e.g. carbon content),

ecological condition indicators (e.g. water quality) and spatial configuration (e.g. connectivity);

Other forms of capital: as measured through access (e.g. proximity of open access areas to

population) and management practices (e.g. agri-environment schemes).

The recording of such information in an account is both data dependent and subject to scientific

understanding of the links between condition (of natural and other capital) and service provision. For

this proof-of-concept study, we have focused on identifying indicators in the condition account that

are relevant to the provision of noise regulation but has not populated this account. The findings

from the scoping of an urban condition account for noise regulation are reported in Section 4 and

should form the basis for a future development of this account.

3.3. Physical account of ecosystem service provision and use (Step 3)

The physical flow account captures the physical quantity of noise regulation produced by natural

capital within the defined UK urban boundary. The relevant physical indicator to quantify noise is

the additional attenuation of noise by vegetation (i.e. the attenuation provided by vegetation which

is additional to natural noise attenuation over open ground due to friction in air and spherical

divergence (Gomez-Baggathun et al. 2013)) across the frequency range of human hearing (ca 0.02 -

20 kHz). The unit is A-weighted decibels (dBA), which adjusts decibels for human perceptions of

different frequencies. For the purposes of this study we develop a three-tier approach where:

i) Larger patches (>3,000m2) of woodland are associated with a 2dB reduction in noise. We take

this approach to account for uncertainty in the tree/woodland data as to the exact spatial

extent and vertical structure of the vegetation mapped as woodland or containing trees in

the OSMM data. For comparison, the maximum likely insertion loss (i.e. reduction due to

trees) is 7dBA for a single receiver behind a modelled strip of woodland of 25 m thickness

(i.e. perpendicular to the noise source) (HOSANNA report, 2013).

ii) Smaller patches of woodland (<3,000m2) provide a lower service: 1dB reduction. This takes

account of edge effects operating around the edges of smaller woodland patches. This

threshold was determined by a theoretical consideration of edge effects around patches of

woodland of varying length. We assumed a hypothetical strip of woodland of fixed width lying

parallel to a noise source and varied the length of woodland to determine when edge effects

reduced the mitigation to a single receiving point below 2 dB. For comparison, the maximum

likely reduction in noise levels due to trees in street canyons is expected to be no more than

2 dBA (HOSANNA report, 2013).



iii) Very small patches of woodland (<200m2) are excluded from the analysis. This excludes all

individual street trees, and small patches of woodland less than approximately 10 x 20 m.

However, strips of continuous canopy woodland alongside roads >200 m2 are included.

Table 3.1 shows the data sources that have been used in quantifying the noise regulating service of

vegetation within the UK urban environment. This includes noise data, at 10m x 10m resolution,

which has been produced by all countries as part of the Environmental Noise Directive (Defra 2014).

For tree cover in this study we primarily used Ordnance Survey Mastermap (OSMM), with reference

to National Tree Map (NTM) and CEH Landcover Map 2007. In OSMM, we defined mapped polygons as

woodland when the descriptor field of the ‘natural’ category contained the words ‘wood’, ‘trees’ or

‘woodland’. However, LCM2007 was used in the extrapolated calculations for Northern Ireland, where

OSMM was not available. The NTM was not used due to the prohibitive cost of purchasing it at national

scale, but upscaled projected estimates were made for the UK, using conversion factors described in

Section 3.5. Results from both the NTM and OSMM approaches are presented in section 4.

Table 3.1: UK urban noise regulation data sources

Indicator Unit Sources Year Coverage Use?

Vegetation location

- OS Mastermap; CEH Landcover 2007; Bluesky tree canopy (NTM)

- GB (OSMM)/ UK (LCM2007)

OSMM was used for most calculations within Great Britain, but NTM data for Manchester was used to provide an upper estimate of the amount of service, and LCM2007 was used to apply the approach in Northern Ireland.

(Spatial) population data

Buildings OS MasterMap (OSMM); Residential population (obtained from Defra)

- UK/

England

Required to identify the location and density of the beneficiary population. OS Mastermap was used to identify buildings as a proxy for spatial location of population at finer resolution. In England, the residential population (identified to building level) was used, and conversion factors based on this data allowed upscaling to UK level.

Spatial noise data

dB(A) Obtained from Noise mapping by Defra for major roads and urban agglomerations (England), the Welsh Government’s Lle Geo-portal10 (Wales), the ‘Scotland’s Environment’ data portal11 (Scotland) and Open Data NI (Northern Ireland)12

2011 England, Wales, Scotland, Northern Ireland

Defra (2014) Noise exposure data (Roads and major agglomerations), >100,000 population from Round 2 modelling: metric LA1018 (10m resolution, England, Wales, Northern Ireland), metric Lden (10m resolution, Scotland)

The following steps were taken to estimate the noise regulating benefit of vegetation in England,

Scotland and Wales using the data from Table 3.1:

Noise data for Roads were collated for the metrics LA1018 (England, Wales, Northern Ireland)

and Lnight (Scotland). Noise data for each of the UK devolved administrations used different

ranges (see Table 4.3) and were analysed separately.

The method identifies patches of tree cover greater than a threshold area of 200 m2, taken to be

the size above which noise mitigation happens. Two classes of mitigation were used: small

10 http://lle.gov.wales/catalogue/item/EnvironmentalNoiseMapping/?lang=en 11 https://noise.environment.gov.scot/ 12 https://www.opendatani.gov.uk/dataset/environmental-noise-directive-noise-mapping

http://lle.gov.wales/catalogue/item/EnvironmentalNoiseMapping/?lang=en

https://noise.environment.gov.scot/

https://www.opendatani.gov.uk/dataset/environmental-noise-directive-noise-mapping



patches of woodland <3,000 ha providing 1dBA mitigation and larger patches >3,000 ha providing

2 dBA mitigation and a spatial layer calculated with zones receiving 1 or 2 dBA mitigation.

Figure 3.1 below is a map showing the noise levels from roads (blue (low) through to red (high)),

patches of tree canopy greater than 200m2 providing a service, areas where noise levels are

calculated to be partially mitigated by those trees (purple shading mitigated by 1 dBA, green shading

mitigated by 2 dBA).



a) b)

c) d)

Figure 3.1. Noise mitigation West Manchester. a) satellite image, b) noise levels + legend (dBA, metric LA1018) c) Urban woodland providing mitigation,

d) areas receiving mitigation from woodland, purple – mitigated by 1dBA (small woodland patch), green – mitigated by 2dBA (large woodland patch).



3.4. Accounting for the supply and use of ecosystem services (Step 4)

Accounting for ownership and management of the ecosystems which supply the services (defined in

the Defra/ONS (2017) principles paper as enterprises, households, governments, rest of the world)

would require mapping ownership of the trees that are providing the service which is outside the

scope of this study.

However, the users (beneficiaries) of noise mitigation service provided by vegetation are the urban

residential population (households) and these are identified within the GIS mapping undertaken as

part of this study. The affected population in each of the 1dBA and 2dBA mitigation zones and each

noise band was obtained by counting the number of buildings using OSMM data. For England it was

possible to further differentiate the location of residential dwellings using a layer of residential

population recently available from Defra for updated noise mapping currently being completed. The

data to do this in other countries was not available. Therefore, we used conversion factors described

in Section 3.5 to estimate the number of dwellings benefitting from noise mitigation in Scotland,

Wales and Northern Ireland.

The impacts on these households in terms of improved amenity value and avoided health costs are

likely to have subsequent impacts on businesses (through improved worker productivity) and the

public sector (through reduced healthcare costs), but these indirect benefits are not captured within

this study.

3.5. Upscaling of flow of physical account, supply and use (Relevant to steps 1-4)

Three adjustment steps were used to calculate the OSMM equivalent mitigated dwellings for all four

countries:

A) Buildings to Dwellings, using national data for England

Detailed data on dwellings was only available for England (a spatially attributed dataset which

distinguishes residential buildings from commercial, and then attributes population and dwellings

(equivalent to households) to those residential buildings. From this data we calculated a conversion

based on the ratio of buildings/dwellings, by noise band from the entire England dataset to estimate

dwellings in the other countries (Table 3.2). The conversion uses the number of dwellings in combined

1dB and 2dB mitigated areas, with a separate conversion factor for each noise band. This was done

because the ratio changes by noise band, presumably because residential buildings are usually located

further away from main roads than commercial buildings. When evaluating the ratios, there was no

difference attributable to the size of the mitigated area, which is a function of the dimensions or

orientation of the woodland in relation to the noise levels. Therefore, the assumption was made that

this does not influence this relationship.

Table 3.2. Ratio of dwellings/buildings, by noise band, combined 1 and 2 dB mitigation areas

dB Ratio

dwellings/buildings

45-49.9 0.706

50-54.9 0.687

55.0-59.9 0.650

60.0-64.9 0.677

65.0-69.9 0.628

70.0-74.9 0.494

Combined >75 0.341



B) Adding missing noise bands for bands down to 45 dB

Lower noise bands were not modelled in some countries (discrete noise bands <55 dB not modelled

in Wales or Scotland, and <50 dB not modelled in Northern Ireland). Therefore, we applied a

conversion to estimate those based on the England data, as a ratio of the proportion of dwellings in

lower noise bands as a function of the combined number of dwellings in bands from 55 to >=75 dB.

When tested for the 50-55 dB range using Lnight data in Scotland, the estimate was within 2% of the

calculated value. This step was performed separately for the 1dB and 2 dB mitigated dwellings.

C) The number of mitigated dwellings in Northern Ireland

Estimates for Northern Ireland were based on the ratio of mitigated area from all LCM2007 woodland

within the urban mask to the mitigated area from OSMM woodland, taken from the Greater

Manchester comparison. This was applied to an estimate of LCM2007 woodland in NI. This was then

multiplied by the number of dwellings per unit of mitigated area using the OSMM method to estimate

an OSMM equivalent number of dwellings from the LCM2007 mitigated area in Northern Ireland (Table

3.3). The size of the areas for 1dB mitigated area is very small using this method as the threshold of

3000 m2 (0.3ha) is very close to the minimum mappable unit used in LCM2007. The number of

mitigated dwellings for lower noise bands (<50 dB) were estimated as for Scotland and Wales,

described in step B) above.

Table 3.3 shows the ratios applied to estimate mitigated dwellings in Northern Ireland from LCM2007

data, showing: OSMM/LCM2007 mitigated land area, OSMM buildings per mitigated ha, and the

combined ratio, by 1dB/2dB area and by noise band.

Table 3.3: Ratio mitigated area and buildings per ha (OSMM)

Ratio mitigated area

(OSMM/LCM2007) No. OSMM buildings per

mitigated ha Combined ratio

dB range 1db 2db Total 1db 2db Total 1db 2db Total

45-49.9 16.93 0.11 0.26 83.6 44.0 66.8 1415.5 4.8 17.1

50-54.9 18.10 0.11 0.27 63.0 33.3 50.8 1141.2 3.7 13.7

55.0-59.9 27.91 0.13 0.31 54.4 28.4 43.3 1517.5 3.8 13.6

60.0-64.9 55.98 0.15 0.36 38.4 19.5 30.4 2151.7 2.9 10.9

65.0-69.9 48.77 0.19 0.42 31.6 13.1 23.4 1543.1 2.4 9.7

70.0-74.9 34.30 0.21 0.48 13.3 6.5 10.4 457.7 1.3 5.0

Combined >75 21.76 0.18 0.42 1.4 0.7 1.1 30.9 0.1 0.5

D) Calculating a higher resolution estimate based on the NTM methodology for Manchester

This was done for all four countries and used a 2-stage conversion. The first stage estimates the

mitigated area as a ratio of the NTM method:OSMM method. The second adjusts this estimate based

on the mitigated dwelling density, which differs under the three methods, taking the ratio of the

NTM method and OSMM method. Both the mitigated area and the dwelling density differ by 1 dB/2

dB mitigated area, and by noise band. The two conversion factors were combined into a single scaling

factor for each band & dB combination (Table 3.4).

Table 3.4 shows the ratios applied to upscale estimates for number of mitigated dwellings based on

NTM data from Manchester, showing: NTM/OSMM mitigated land area, ratio of buildings per mitigated

ha NTM/OSMM, and the combined ratio, by 1dB/2dB area and by noise band.

Table 3.4: Ratio mitigated area and dwellings per ha (NTM)



Ratio mitigated area

(NTM/OSMM)

Ratio of dwellings per mitigated ha (NTM/OSMM) Combined ratio

dB range 1db 2db Total 1db 2db Total 1db 2db Total

45-49.9 10.57 27.15 17.61 0.41 0.15 0.24 4.35 4.02 4.26

50-54.9 11.09 25.30 16.95 0.34 0.17 0.23 3.78 4.41 3.95

55.0-59.9 11.69 19.05 14.83 0.24 0.23 0.22 2.79 4.32 3.22

60.0-64.9 12.28 13.88 12.95 0.17 0.39 0.23 2.12 5.39 3.01

65.0-69.9 13.58 11.19 12.52 0.13 0.55 0.23 1.82 6.18 2.90

70.0-74.9 14.15 11.33 12.95 0.11 0.47 0.19 1.51 5.30 2.51

Combined >75 10.12 5.91 8.32 0.07 1.07 0.28 0.75 6.32 2.31

3.6. Monetary account of annual provision of ecosystem services (Step 5)

The monetary account captures the economic value (£) of the ecosystem services that have been

quantified in the physical flow account. For commensurability with other national accounting data,

this should be the ‘exchange value’ observed in markets or ‘imputed exchange value’ (i.e. indirectly

measured or estimated) where markets do not exist. In practice, alternative welfare-based measures

including consumer surplus can be provisionally included as if they were proxy exchange values (Day,

2013; Defra/ONS, 2017) with an indication given of the likely overestimation of value.

The UK government (Defra, 2014b) economic valuation guidance and transport noise modelling tool

(Defra, 2014c) provide marginal values for changes in noise (decibels) associated with road (and rail

and aviation, but these are not relevant for this study). The monetary values are given as £ per

household for changes in decibel levels from the baseline in relation to the following impacts:

a) Amenity values: There are two parts to the amenity values from noise, sleep disturbance and

annoyance.

i) Sleep disturbance: The recommended approach for valuing sleep disturbance is (Defra, 2014a):

population

exposed

x proportion sleep

disturbed

x disability weight x health value

(1) (2) (3) (4)

The population exposed is a site-specific value (e.g. the population of a community); the disability

weight recommended by the WHO Night Noise Guidance for Europe is approximately 0.07 (WHO,

2009); and the proportion that are sleep disturbed can be estimated using a dose response function

which is based on the noise levels at night, following IGCB(N) (2007). These components are

multiplied by the associated QALY (Defra, 2014). The economic value of a QALY is estimated using a

willingness to pay estimate and is therefore a welfare-based measure13.

ii) Annoyance: The recommended approach for valuing annoyance is (Defra, 2014):

population

exposed

x proportion

highly annoyed

x disability weight x health value

(1) (2) (3) (4)

13 This is closely related to the estimation of the value of a life year (VOLY). A QALY is a VOLY weighted by their

quality of life and stands for ‘Quality Adjusted Life Year’.



(1), (2) and (3) are estimated through methods that are very similar to those for sleep disturbance

and the estimated health value (4) is identical i.e. welfare based. The ‘proportion highly annoyed’ is

estimated using dose response functions from Interdepartmental Group on Costs and Benefits Noise

Subject Group (Defra, 2014). One key difference between the values from sleep disturbance and

annoyance is that there are benefits from changes in noise levels at lower levels for annoyance than

for sleep disturbance.

b) Health values: There are three parts to the health costs associated with exposure to noise:

strokes, dementia and heart attacks (although in practice, the estimated values of strokes and

dementia are combined to estimate the impact on hypertension from noise). They all use

exposure and dose-response measures to calculate a QALY impact. This is given a monetary value

using a willingness to pay estimate and is therefore a welfare-based measure. The recommended

approach for valuing strokes and dementia follow the same approach:

Change in risk x health impact specific QALYS x value of QALY

(1) (2) (3)

The guidance for estimating the impacts on heart attacks (AMI) is based on the IGCB(N) report

(2010). This is dependent on the additional risk of AMI, based on a dose response function outlined

in Babisch (2006). This is combined with the probabiliy of AMI occuring within a population at a

specific location, the population in that location and the health value (i.e. the value of the QALY).

Therefore, as with the other estimates, this value is also welfare based.

c) Productivity values: The productivity costs are not a part of the formal recommendations of

Defra (2014a) and are not included in this study. However, the report presents a prospective

method to estimate productivity loss (e.g. from lack of sleep/disturbed sleep) based on the

financial cost of labour. As with other wage-based estimates, these are closer to an exchange

value. However, the estimates in Defra (2014a) were only considered partial, based on a mix of

national-level estimates from around the world, and does not take into account workers who are

ill but still active in the workplace, and the scale of loss of productivity (e.g. accounting for the

type of work) (Morgan et al., 2011).

We apply the “central scenario” estimate of marginal values which combine these impacts for each

unit decibel change (Defra, 2014b; 2014c). This assumes a QALY value of £60,00014, with a disability

weight for sleep disturbance of 0.07, a Highly Sleep Disturbed (HSD) sleep disturbance response

function, a disability weight for annoyance of 0.02, and a Highly Annoyed (HA) annoyance response

function for transport noise modelling.

We make the assumption that the mitigated buildings lying within each 5dBA noise band will

experience a 2dBA reduction in noise levels due to the presence of trees that cover an area >3,000m2

and a 1dBA reduction in noise levels due to the presence of trees that cover an area <3,000m2 as

explained in Section 3.3. As Table 3.4 shows, our application of these values takes a conservative

approach that the lowest 1dBA/2dbA reduction will be experienced for each banding: i.e. for the

banding 65dBA to 69.9dBA we assume a reduction in noise of 66dBA to 65dBA (for a small patch of

woodland providing a 1dBA reduction), whereas actually the reduction will be experienced by

individuals exposed to noise levels over the entire band range.

The “central scenario” value per change in decibel, by noise band is shown in Table 3.5. This is

considered to give a reasonably robust order-of-magnitude estimate of the value of the service, but

further work could refine the methodology, and reduce uncertainty.

14 As per HM Treasury guidance.



Table 3.5 “Central scenario” marginal values for road noise reduction from Defra guidance

(2014a)

Noise

banda

Smaller woodland (<3,100m2) Larger woodland (>3,100m2)

1dB reduction

applied

Marginal value £ per

household

2dB reduction

applied

Marginal value £ per

household

>=80 81 to 80 195 82 to 80 390

75.0-79.9 76 to 75 175 77 to 75 358

70.0-74.9 71 to 70 137 72 to 70 282

65.0-69.9 66 to 65 104 67 to 65 214

60.0-64.9 61 to 60 75 62 to 60 155

55.0-59.9 56 to 55 51 57 to 55 106

50.0-54.9 51 to 50 19 52 to 50 38

45.0-49.9 46 to 45 11 47 to 45 23

a The noise bands are showing the current range of decibels that are experienced

The transport noise modelling tool allows sensitivity to be applied to the “central scenario”. As

explained in the “model guide” tab (Defra, 2014b), the sensitivity tab allows the user to test the

range of uncertainty for the inputs for which we have a quantifiable range. In particular:

Value of a quality adjusted life year (QALY) using the Interdepartmental Group on the Value of

Life and Health (IGVLH) of between £30,000 and £80,000 (with £60,000 as the central scenario);

Quantifying the effects of sleep disturbance and annoyance using high, central and low disability

weights (disability adjusted life years, or DALYs); and

Applying low, moderate and high sleep disturbance, and moderate and low annoyance response

functions.

The calculation sheets in Annex 1 have been set to compute the outputs using the general inputs (i.e.

dose-response functions, population demographics etc.) as well as to take into account the user-

selected sensitivities. All the output sheets in the excel workbook (Annex 1) display which

combination of scenarios the results are for.

3.7. Monetary account of future provision of ecosystem services (Step 6)

The monetary asset value account captures the economic value for the assets by aggregating the

present value of forecast future flows (in this case over 100 years in line with Defra/ONS principles

paper, 2017) of ecosystem service. The following assumptions have been taken into account in

estimating the future flow of value from noise mitigation by urban vegetation:

Electric Cars in the vehicle stock – Due to a high degree of uncertainty of the impact of the

electrification of the car fleet, with the most likely impact assumed to be minimal, the impact

of electric vehicles is considered not material to this assessment. Greater detail can be found in

Annex 1.

Population – The impacted population will change over time; however due to a number of

influencing factors, the overall change in the affected population is highly uncertain, and so

future trends have not been modelled. Contributing factors include:

Overall population – birth rates and migration trends will impact the population;



Number of households affected by noise mitigation services - will change as the housing

stock changes, becoming more or less dense in residential areas due to varying rates of

urbanisation and urban spatial planning;

The average size of household – may change over time due to changes in family size and

cohabitation patterns; and

Population demographics – the age and gender distribution of the population will change

the overall effect of mitigation as different people have different propensities for

adverse health outcomes by noise and so the marginal value per household of noise

mitigation varies according to the demographics of the population.

Present values are calculated as the discounted flow of future value over 100 years, using a

variable discount rate as suggested by HM Treasury’s Green Book Guidance (2018) for health

impacts15: 1.5% for 0 - 30 years, 1.29% for 31-75, and 1.07% for 76 - 100 years.

15 Note that in the most recently published guidance, it is recommended that a different discount rate be used

for health impacts which are lower values than those used for general discounting.



4. RESULTS

This section describes the outputs from this study including the physical account of natural capital

extent, condition and ecosystem service provision, and the monetary accounts estimating annual

values and asset values. An accompanying Excel document (Annex 1) provides details on the data

sources, assumptions, method steps and calculations that underpin this analysis.

Note that throughout results are presented using both NTM and OSMM data. This shows that using

fine-grained data on individual tree canopies from NTM estimates the number of buildings receiving

mitigation to be 2-5 times greater than if the coarser resolution data on woodland cover available

from OSMM is used. This difference is greater for areas receiving the higher level of mitigation by 2

dBA, which may be due to more complete capture of linear woodland alongside roads, which in turn

provide a greater level of service due to their location within higher noise bands. NTM provides a

more robust data source at finer resolution, but was only available for Manchester. So when

extrapolating up to UK level, that carries a larger uncertainty than just using the OSMM, which was

available for all of GB.

4.1. Physical account of natural capital extent

Table 4.1 reports the total ‘urban area’ as defined within this study for England, Scotland and Wales.

It also shows the area of small woodland (<3,000m2) which is assumed to provide a 1dBA reduction in

noise and the area of large woodland (>3,000m2) which is assumed to provide a 2dBA reduction in

noise. The total urban woodland area of sufficient size to provide some form of noise mitigation is

75,180 ha in England, 12,746 ha in Scotland, 5,196 ha in Wales, and 6,019 ha in Northern Ireland

(Table 4.1). Note the data from Northern Ireland use LCM2007 rather than OSMM so are not directly

comparable.

Table 4.1. Extent of UK urban natural capital within enhanced ONS BUA (2011) urban extent

Indicator Scale Amount Unit Source

Total urban area16 England 1,500,884 Ha Enhanced ONS BUA (2011)

Small woodland (<3,000m2) England 40,326 Ha OS Mastermap within enhanced ONS BUA (2011)

Large woodland (>3,000m2) England 34,854 Ha OS Mastermap within enhanced ONS BUA (2011)

Total urban area Scotland 174,828 Ha Enhanced ONS BUA (2011)

Small woodland (<3,000m2) Scotland 5,669 Ha OS Mastermap within enhanced ONS BUA (2011)

Large woodland (>3,000m2) Scotland 7,077 Ha OS Mastermap within enhanced ONS BUA (2011)

Total urban area Wales 90,188 Ha Enhanced ONS BUA (2011)

Small woodland (<3,000m2) Wales 3,551 Ha OS Mastermap within enhanced ONS BUA (2011)

Large woodland (>3,000m2) Wales 1,646 Ha OS Mastermap within enhanced ONS BUA (2011)

16 Values for total urban area in each country calculated directly from the polygon layer are re-scaled here to

match those in the eftec et al. (2017) scoping study (calculated from a raster layer). The difference is less than

0.5%.



Total urban area N.I. 63,393 Ha Enhanced ONS BUA (2011)

Small woodland (<3,000m2) N.I. 0.3 Ha CEH LCM2007

Large woodland (>3,000m2) N.I. 6,019 Ha CEH LCM2007

4.2. Physical account of natural capital condition

The impact of UK urban vegetation on attenuating noise occurs primarily by scattering sound and

different components of the environment have different capacities to reduce noise. The benefit

provided by vegetation depends upon its location relative to the noise source and population.

Table 4.2 outlines the proposed indicators and units to include in the UK urban natural capital account

of noise mitigation. Indicators have been selected based on our understanding and review of evidence

and data for this ecosystem service. Table 4.2 includes factors not quantified in this study, but could

be incorporated in future (e.g. vegetation height):

Surface permeability: soft or permeable soils/lawns dissipate more noise than concrete (Bolund

and Hunhammar, 1999). Therefore, reporting the changing extent of permeable and impermeable

surfaces will indicate change in ecosystem service provision but also potentially improvements in

urban uses of vegetation technology (i.e. sustainable urban drainage systems (SuDS)). This factor

is already incorporated in the national noise modelling for Defra and other devolved

administrations but is not currently reported.

Vegetation width, height and structure: the greatest benefit is delivered by vegetation greater

than (15-) 25 m wide1 (HOSANNA report, 201317). Wide and dense belts of trees can reduce noise

levels by up to 7 dB(A). Greater tree trunk density and width/height/length of vegetation strips

generally provide increasing noise attenuation (Fang and Ling, 2003; Peng et al. 2014).

Extent of private gardens/hedges: These assets are important because they are located close

to population (by definition) and so have the potential to dissipate noise. Hedges (and street

trees) can deliver a relatively small noise reduction of 1-2 dB(A) (HOSANNA report, 2013). Hedges

have the capacity to mitigate noise, but since the majority of the UK population do not sleep on

the ground floor of buildings, it has a more limited impact on reducing people’s exposure to

night-time noise which has the greatest health impacts.

Vegetation near road/rail: This indicates the capacity of vegetation to reduce noise by virtue of

its location (near road/rail). This can potentially be produced as an output from modelling of

noise regulating service provided by urban vegetation.

Table 4.2. Linking natural capital extent and condition to noise regulation

Broad dimension Indicator Unit Source Noise Regulation

Extent See Table 4.1 Ha See Table 4.1

Soil Surface permeability Permeable Ha BGS, LCM

Impermeable Ha

Ecological condition

Vegetation height Ha by m LIDAR

Vegetation width Ha by m OSMM with processing

Vegetation size DBH LIDAR; NTM

Extent of private gardens/hedges Ha OSMM; LCM

17 HOSANNA: Holistic and Sustainable Abatement of Noise by optimized combinations of Natural and Artificial

means.



Spatial configuration

Vegetation near road/rail Ha by dBA OSMM; LCM; NTM

4.3. Physical account of ecosystem service provision

Tables 4.3a and Table 4.3b show the number of buildings experiencing a decibel reduction due to the

presence of natural capital (trees or woodland) within the defined urban boundary – broken down by

noise band and for England, Scotland, Wales and Northern Ireland, using NTM and OSMM data. The

total number of buildings mitigated is estimated at 8,228,000 using NTM data, and 2,099,000 using

OSMM data.

Note that the number of dwellings receiving mitigation in Scotland is likely to be lower than the

estimates for the other countries because we used the Lden noise metric rather than the LA1018

metric which was not available for Scotland. The mapped Lden noise bands physically covered a

smaller area than LA1018 where these were compared for Greater Manchester. Woodland as a

proportion of urban area varies from 5 – 10%. Note this will differ from other published statistics

because we are using a new definition of urban extent rather than one based on urban administrative

boundaries. These figures are based on the interpretation of NTM and OSMM, and will also differ if

other data sources are used.

Table 4.3a. Number of buildings where road noise levels are mitigated by natural capital in

England, Scotland, Wales and Northern Ireland (‘000s) with NTM data

Table 4.3b. Number of buildings where road noise levels are mitigated by natural capital in

England, Scotland, Wales and Northern Ireland (‘000s) with OSMM data

Noise band

Buildings mitigated by 1 dB (Number) Buildings mitigated by 2 dB (Number)

England Scotland Wales Northern

Ireland England Scotland Wales

Northern

Ireland

>=80

< 1

-

-

-

< 1

-

-

-

75.0-79.9

< 1

-

< 1

-

< 1

-

< 1

< 1

70.0-74.9

9

< 1

< 1

-

7

< 1

< 1

2

65.0-69.9

54

1

4

-

40

2

2

8

60.0-64.9

166

8

15

< 1

105

9

7

22

55.0-59.9

474

26

39

2

219

18

14

61

50.0-54.9

1,521

75

129

3

548

42

35

101

45.0-49.9

2,896

144

246

7

835

64

53

212

Total 5,121 255 435 11 1,754 135 111 406

Noise

band

Buildings mitigated by 1 dB (Number) Buildings mitigated by 2 dB (Number)



Northern

Ireland



4.4. Monetary account of annual provision of ecosystem service

Tables 4.4a and 4.4b show the annual monetary benefits of noise regulation based on the avoided

loss of QALYs associated with a loss of amenity (sleep and annoyance) and adverse health outcomes

due to noise as explained in Section 2, using NTM and OSMM data. The total annual value from noise

mitigation is estimated at £245 million with NTM data, and at £66 million with OSMM data.

Table 4.4a. Annual value of road noise regulating benefits from urban natural capital in England,

Scotland, Wales and Northern Ireland (£’000/yr) with NTM data

Table 4.4b. Annual value of road noise regulating benefits from urban natural capital in England,

Scotland, Wales and Northern Ireland (£’000/yr) with OSMM data

>=80 < 1 - - - < 1 - - -

75.0-79.9 < 1 - < 1 - < 1 - < 1 < 1

70.0-74.9 6 < 1 < 1 - 1 < 1 < 1 < 1

65.0-69.9 30 < 1 2 - 6 < 1 < 1 1

60.0-64.9 78 4 7 < 1 20 2 1 4

55.0-59.9 170 9 14 < 1 51 4 3 14

50.0-54.9 402 20 34 < 1 124 10 8 23

45.0-49.9 665 33 57 2 207 16 13 53

Total 1,352 67 115 4 409 32 25 95

Noise band

Annual value of small woodland (£’000/yr) Annual value of large woodland (£’000/yr)



Northern

Ireland

>=80

<1

-

-

-

2

-

-

-

75.0-79.9

92

-

8

-

226

-

7

29

70.0-74.9

1,301

8

128

-

1,969

19

163

574

65.0-69.9

5,687

154

461

-

8,577

408

530

1,691

60.0-64.9

12,463

683

1,142

7

16,453

1,482

1,083

3,378

55.0-59.9

24,474

1,346

2,015

87

23,338

1,881

1,443

6,519

50.0-54.9

28,927

1,435

2,462

59

21,187

1,635

1,338

3,920

45.0-49.9

32,900

1,632

2,800

75

18,925

1,461

1,195

4,807

Total

105,844

5,258

9,015

228

90,677

6,886

5,759

20,918



4.5. Monetary account of future provision of ecosystem service

Tables 4.5a and 4.5b show the asset value for noise regulation based on the estimated flow of future

benefits over 100 years, with NTM and OSMM data. The total asset value for noise mitigation is

estimated at £13,310 million with NTM data, and at £3,577 million with OSMM data.

Table 4.5a. Asset value of ecosystem service flows from UK urban natural capital18 (PV, 100 years)

with NTM data

18 The assessment of the future provision of the service relies on the trend assumptions discussed in section 3.7,

namely that: (i) the uptake of electric vehicles do not materially impact service provision; (ii) the impacted

population is stable over time (this may not be realistic, however as discussed there are several factors to

consider and even the direction of movement cannot be estimated with confidence, therefor there is currently

significant uncertainty in the overall effect of this trend and it has not been modelled); and, (iii) the published

HM Treasury Green Book Guidance for Health discount factors are applied for years 0 to 100.

Noise

band

Annual value of small woodland (£’000/yr) Annual value of large woodland (£’000/yr)



Northern

Ireland

>=80 1 - - - < 1 - - -

75.0-79.9 122 - 10 - 36 - 1 5

70.0-74.9 860 6 85 - 372 4 31 108

65.0-69.9 3,126 85 254 - 1,387 66 86 274

60.0-64.9 5,868 322 537 3 3,051 275 201 627

55.0-59.9 8,782 483 723 31 5,397 435 334 1,508

50.0-54.9 7,645 379 651 16 4,803 371 303 889

45.0-49.9 7,558 375 643 17 4,703 363 297 1,195

Total 33,962 1,650 2,903 67 19,749 1,514 1,253 4,606

Noise band

Value of small woodland for noise reduction

(£m)

Value of larger woodland for noise

reduction (£m)



Northern

Ireland

>=80

< 1

-

-

- < 1

-

-

-

75.0-79.9 5

-

< 1

- 12

-

< 1 2

70.0-74.9 71

< 1 7

- 107 1

9 31

65.0-69.9 309

8 25

- 467 22

29 92

60.0-64.9 678

37 62

< 1 895 81

59

184

55.0-59.9 1,332

73

110

5 1,270

102

79

355



Table 4.5b. Asset value of ecosystem service flows from UK urban natural capital19 (PV, 100

years) with OSMM data







50.0-54.9 1,574

78

134 3

1,153

89

73

213

45.0-49.9 1,790

89

152

4

1,030

80

65

262

Total 5,760 286 491 12 4,935 375 313 1,138

Noise

band

Value of small woodland for noise reduction

(£m)

Value of larger woodland for noise reduction

(£m)



Northern

Ireland

>=80 < 1 - - - < 1 - - -

75.0-79.9 7 - < 1 - 2 - < 1 < 1

70.0-74.9 47 < 1 5 - 20 < 1 2 6

65.0-69.9 170 5 14 - 76 4 5 15

60.0-64.9 319 17 29 < 1 166 15 11 34

55.0-59.9 478 26 39 2 294 24 18 82

50.0-54.9 416 21 35 1 261 20 17 48

45.0-49.9 411 20 35 1 256 20 16 65

Total 1,848 90 158 4 1,075 83 69 250



5. CONCLUSIONS AND RECOMMENDATIONS

This section provides a summary of the uncertainty associated with the accounting work and

recommendations for maintaining and refining it.

5.1. Summary

This study has demonstrated how an urban natural capital account for noise can be developed in the

UK, building on the principles of natural capital accounting outlined by Defra/ONS (2017) and the

data and methods for estimating noise regulation developed under the UK urban natural capital

accounting scoping study (eftec et. al, 2017), a precursor to this study. The structure of the account

follows that set out by SEEA (UN, 2013) and the Defra/ONS principles paper (Defra/ONS, 2017) as

used in existing UK natural capital accounts. It features five accounts: extent, condition, physical

flow, annual monetary flow and monetary flow over time. A set of recommendations for refining and

further developing the initial UK urban natural capital account are also provided.

The account shows the significant value provided by the UK’s urban vegetation in terms of improved

amenity and health outcomes due to noise mitigation. It also shows how methods can be applied

across both national and local scales, because the initial scoping account (eftec et. al, 2017)

produced estimates for noise mitigation by vegetation in Manchester. Two approaches were applied

with their respective results presented; in general, the OSMM based approach is recommended as the

preferred of the two. NTM provides a more robust data source at a finer resolution, but was only

available for Manchester. So when extrapolating up to UK level, that carries a larger uncertainty than

just using the OSMM, which was available for all GB. Accompanying Excel documents provide detail

on the data sources, assumptions, method steps and calculations that underpin this analysis for both

approaches.

Overall, we expect the range of estimates we have produced to be reasonably robust, given that this

is a new approach being developed for ecosystem service assessment of noise mitigation. The

requirements for a more accurate assessment of the role of vegetation in mitigating noise levels are

discussed in the following section. There are a number of assumptions to be borne in mind when

interpreting the estimates from this study:

The noise levels are at fine resolution, generated by noise consultants for Defra and other

devolved administrations. Their calculations take into account location of buildings, topography

and ground surface, but not vegetation. The account calculations work out the potential

additional effect of vegetation in further mitigating noise levels;

The science underpinning noise reduction is summarised in the final report of the HOSANNA

project (EC, 2013). The account makes a cautious estimate of the amount of noise reduction by

patches of vegetation. It has taken the simplest approach using data that is readily available, by

screening out vegetation that provides little or no noise mitigation service (canopy area <200m2),

and applying a two-tier estimate of noise reduction to the remaining vegetation depending on

patch size and the likelihood of edge effects (area <3,000m2 providing 1dBA mitigation, area

>3,000m2 providing 2dBA mitigation).

We note that the choice of data to quantify tree cover may result in quite widely varying

estimates of the magnitude of the service provided. This is exemplified in a sensitivity analysis

conducted for Manchester, comparing the current approach with three different datasets on tree-

cover (Table 5.2). This shows that using fine-grained data on individual tree canopies from

National Tree Map estimates the number of buildings receiving mitigation to be 2-5 times greater

than if the coarser resolution data on woodland cover available from OS MasterMap is used. This



difference is greater for areas receiving the higher level of mitigation by 2 dBA, which may be

due to more complete capture of linear woodland alongside roads, which in turn provide a greater

level of service due to their location within higher noise bands. When CEH Land Cover Map is used

(necessary for upscaling to N.I.), there are large differences in the smaller patches of woodland,

because the 3000m2 is close to the minimum mappable unit for CEH Land Cover Map, while the

larger patches show a cover broadly equivalent to OS Master Map. The resulting difference in

economic value is almost a factor of 10 higher with the fine resolution data from NTM compared

with OSMM (Table 5.3).

Table 5.2. Comparing number of dwellings mitigated for Manchester using different natural

capital datasets on tree cover (OS Mastermap, National Tree Map and CEH Landcover Map 2007)

Noise

band

Mitigated 1 dBA Mitigated 2 dBA

OS

Mastermap

National

Tree Map

CEH

Landcover

Map 2007

OS

Mastermap

National

Tree Map

CEH

Landcover

Map 2007

>=80 0 0 0 0 1 0

75.0-79.9 34 29 0 12 97 0

70.0-74.9 595 900 0 213 1,128 0

65.0-69.9 2,577 4,688 9 850 5,255 634

60.0-64.9 5,745 12,203 14 2,124 11,453 1,894

55.0-59.9 14,158 39,454 57 5,497 23,769 6,741

50.0-54.9 28,507 107,866 190 10,580 46,674 17,543

45.0-49.9 40,327 175,552 409 15,649 62,970 27,607

Total

91,943

340,692 679

34,925

151,347

54,419

Table 5.3. Comparing economic value for Manchester using different natural capital datasets on

tree cover (OS Mastermap, National Tree Map and CEH Landcover Map 2007), (£’000s)

Noise band


OS Mastermap

National Tree Map

CEH Landcover Map 2007

OS Mastermap

National Tree Map

CEH Landcover Map 2007

>=80 - - - - - -

75.0-79.9

6 5 - 4 35 -

70.0-74.9

82 125 - 61 320 -

65.0-69.9

270 491 1 183 1,134 137

60.0-64.9

432 918 1 331 1,787 295

55.0-59.9

730 2,036 3 587 2,538 720

50.0-54.9

542 2,052 4 409 1,804 678

45.0-49.9

458 1,994 5 355 1,428 626

Total 2,520 7,621 14 1,930 9,046 2,456



Calculating the number of buildings where noise is mitigated by vegetation is dependent on their

spatial locations. In order to identify the locations of beneficiaries at the fine spatial scale of the

noise data, we used three approaches. For England, we were able to identify residential

buildings. For Wales and Scotland, we could only identify all buildings. For Northern Ireland, we

extrapolated from the results for Great Britain based on population. Since the value estimates

are at the level of household, we made the assumption that people are uniformly distributed

among buildings, whereas in reality, some buildings are multi-occupancy. The lack of distinction

between residential and work buildings in Wales and Scotland also adds uncertainty to the

estimates.

Further comparison of the approach using residential buildings versus all mitigated buildings for

England suggests a scaling of results is needed where the detail on residential buildings is not

available. The number of residential buildings which receive mitigation is roughly a factor of 2

lower than the total number of buildings receiving mitigation (see Table 5.4). However, this ratio

differs by noise band, particularly for the higher noise bands which tend to be in more commercial

orientated areas. We propose that data for Scotland, Wales & Northern Ireland are scaled

according to noise band. Further minor adjustment for the number of mitigated dwellings

(equivalent to households, based on postcode units and census data) accounts for buildings of

multiple occupancy such as blocks of flats (Table 5.4). Figure 5.1 illustrates spatial patterns in

residential versus all buildings. The disparity appears to arise since the category ‘all buildings’

includes separate garages and outbuildings of residential properties and farms, as well as

commercial and industrial premises are included in the ‘all buildings’ total.

Table 5.4. Comparing number of buildings/dwellings mitigated for Manchester, by noise band

Noise band


All buildings

Residential buildings

Dwellings (House-holds)

Ratio All: Dwellings

All buildings

Residential buildings

Dwellings (House-holds)

Ratio All: Dwellings

>=80 119 4 4 29.8 19 3 3 6.3

75.0-79.9

2,411 436 858 2.8 415 70 109 3.8

70.0-74.9

176,545 5,176 7,590 23.3 40,617 962 1,423 28.5

65.0-69.9

48,437 23,046 31,801 1.5 10,173 4,605 6,033 1.7

60.0-64.9

112,887 57,508 77,647 1.5 27,737 13,816 17,529 1.6

55.0-59.9

268,212 136,491 173,575 1.5 68,938 36,298 45,586 1.5

50.0-54.9

615,064 333,361 418,827 1.5 163,407 88,597 109,006 1.5

45.0-49.9

985,317 561,502 701,109 1.4 263,295 148,569 180,398 1.5

Total 2,208,992 1,117,524 1,411,411 1.6 574,601 292,920 360,087 1.6

Figure 5.1. Two examples from West Midlands area showing all buildings (red) and residential

only (blue), for a) predominantly urban area and b) urban-rural fringe

a) b)



5.2. Recommendations

The datasets used for this national level estimate of noise mitigation have been selected on the basis

of being readily available, of sufficient quality and in appropriate format to allow a reasonable order-

of-magnitude estimate for the physical and monetary value of this ecosystem service. There are

additional datasets and methods that can be explored to refine and/or validate the values produced

in this account. This includes, but is not limited to, the following sources and methods:

The noise mapping commissioned by central and devolved governments could be adapted to

include vegetation effects. This would entail two separate modelling exercises, i.e. one

which incorporates vegetation, both as a barrier and with improved ground absorbance

values, and one which does not, to calculate the effect of vegetation by difference between

the two scenarios (similar to the approach taken by CEH for air quality modelling (Jones et

al. (2017));

Further refinement of the noise levels by using different metrics as appropriate (Lden, Lnight,

Lday) may help achieve improved monetisation of the health impacts;

Use of a UK dataset for tree-cover that is of sufficiently high resolution, such as the Bluesky

National Tree Map20 (potential restrictions on using this, and the degree to which it provides

national coverage, will need to be understood) or similar products being designed by other

organisations. This would underpin an improved estimate of the noise mitigation service,

replacing the current extrapolated calculation;

The current approach could be adapted to include seasonality aspects to account for

differential noise mitigation in summer compared with winter when deciduous trees have lost

their foliage. The trunks and branches of trees without foliage still provide a degree of noise

mitigation (Van Renterghem, 2014) so this service is also provided in autumn/winter, albeit

less so than in spring/summer. The current approach assumes an equal level of noise levels

20 Information available from website accessed here: https://www.bluesky-world.com/ntm

https://www.bluesky-world.com/ntm



and equal levels of mitigation throughout the year, and might over-estimate the service

provided in winter; and

There remains a lack of consensus on the magnitude of decibel reduction provided by

vegetation (Van Renterghem et al. 2012). This would require new data collection and

experiments under field conditions, to inform what magnitude of service that vegetation of

different structures and composition provides.

Alternative methods of valuing the benefits provided by vegetation could also be explored, including:

1. The use of hedonic pricing to ascertain if the value of noise dissipation by vegetation can be

captured in house price premiums. This could link the mapping in this study with the hedonic

pricing work ongoing in ONS;

2. Revealed preference methods – focusing on estimating the extent to which technology/built

capital is used to replace the noise dissipating impacts of vegetation such as through

double/triple glazing or fencing of dual carriageways and other road side noise barriers, and

the associated costs of such technology. This would align more closely with an exchange

value; and

3. Finally, the natural capital condition account could be developed. For this scoping study,

indicators of natural capital condition have been proposed for the future quantification based

on evidence of their importance to ecosystem service provision.



Addendum

Note on the comparison between a commercial noise modelling approach and the applied CEH

urban ecosystems services approach for investigating the impact of urban woodland on noise

reduction.

The method applied for modelling the effect of urban vegetation on noise in the study Scoping UK

Urban Natural Capital Account – Noise Extension is an innovative and experimental method of

modelling noise mitigation for valuing urban natural capital. It represents a considerable

improvement on ecosystem service assessment approaches to this which have been conducted

previously. However, by necessity it differs from conventional noise modelling approaches which use

much more sophisticated models, with an associated time and computational cost. Conventional

noise modelling has not previously considered vegetation effects explicitly, but does modify

absorbance values under different types of landcover, often based on Corine data. Therefore, a trial

was undertaken by Acustica using commercial noise modelling software to compare the two

approaches, and improve the interpretation of the impact of urban woodland on noise reduction.

For the comparison, a 3 x 3 km2 area in North West Manchester was selected. The Acustica noise trial

involved four scenarios, a baseline model and three different modifications using more refined tree

cover estimates for urban woodland:

The baseline model where CORINE ground cover was used for absorbance values, as per

Round 2 strategic noise mapping conducted for England (shown in

Figure A1)

Baseline with the ground cover altered to include a hybrid layer of Corine overlaid with OS

MasterMap woodland identified by CEH, and ground absorbance values modified accordingly

Baseline with the ground cover altered to include a hybrid layer of Corine overlaid with

National Tree Map woodland (merged polygons > 200 m2 in size) provided by CEH, and

ground absorbance values modified accordingly (

Figure A1)

Baseline with the ground cover altered to include a hybrid layer of Corine overlaid with

National Tree Map woodland (merged polygons > 200 m2 in size) provided by CEH, and

ground absorbance values modified accordingly (

Figure A1), PLUS all woodland modelled as a 1.25m high barrier. This is similar in concept

to the CEH model and is based on the attenuation effect of vegetation described in the

HOSANNA report, 2013. This model is subsequently referred to in the text as the Acustica

NTM_1.25 model.

a) b)



Figure A1. Area used in Acustica NTM_1.25 model, the 3 x 3 km2 test area is defined by the

purple box. a) CORINE ground cover with absorbance values + legend (0 = hard ground, 1= soft

ground), b) CORINE ground cover combined with National Tree Map woodland (merged polygons

> 200m2 in size) + legend (0 = hard ground, 1= soft ground).

Figure A1 illustrates the differences in mitigated area between the two approaches. It is apparent

that the CEH model is overestimating the area mitigated by urban woodland, but in particular

overestimating the area which receives a 2dBA or greater reduction in noise level. Conversely, for a

1dBA reduction in noise the CEH model is possibly underestimating the area mitigated in particular

noise bands. The primary reasons behind these differences are detailed below:

The CEH model is a proxy method for modelling noise, consequently mitigated areas behind

woodland have propagated further than would be observed in reality where road noise

would travel around woodland patches (a flanking effect) reducing the area mitigated.

Cell size may have exacerbated the size of the mitigated area. The resolution of the

mitigated area produced from the CEH model output is 25m x 25m, larger than the 10m x

10m underlying noise data and Acustica NTM_1.25 model. This was a necessity due to the

constraints associated with modelling the whole U.K. This larger resolution may have

resulted in a greater area being incorporated into the mitigated area than otherwise would

have been observed with a 10m x 10m analysis.

The Acustica NTM_1.25 model produced a greater 1dBA mitigated area for noise levels

between 55 and 80dBA compared to the CEH model. This under-representation of 1dBA area

may have resulted from where a 1dBA and 2dBA patch coincide, the 2dBA patch overrides

the 1dBA patch.

Buildings are not explicitly accounted for within the CEH modelling method as a noise

barrier, although they are included indirectly since the CEH method uses the underlying

noise outputs which do include this factor. Therefore, although the mitigated area appears

larger in the CEH method, the number of buildings affected is not proportional to the area

predicted as mitigated, since the underlying noise bands already reflect the barrier effects

of buildings.

The number of dwellings benefiting from the noise mitigation effects of woodland are potentially

overestimated in the tested CEH model by a factor of 14 compared to the Acustica NTM_1.25 model

(

Table A1). This stems from the larger mitigated area produced by this modelling method but also

where the mitigation occurs; the Acustica NTM_1.25 model predicts a higher 1dBA reduction between

55 and 80dBA, however, a greater number of dwellings are caught within the CEH model 1dBA

mitigated patches for these levels (

Figure A2).



a) b) c)

d)

Figure A2. Noise mitigation in North West Manchester. a) areas receiving mitigation from

woodland in the Acustica NTM_1.25 model; purple – mitigated by 1dBA, black – mitigated by

2dBA, b) areas receiving mitigation from woodland in the CEH model; purple – mitigated by 1dBA,

black – mitigated by 2dBA+ legend (dBA, metric LA1018) c) residential buildings benefitting from

noise mitigation in the Acustica NTM_1.25 model highlighted in green d) residential buildings

benefitting from noise mitigation in the CEH model highlighted in green.

The Acustica model can also provide specific results for noise levels to individual building facades at

a specified elevation, in this case at 4m above ground. The façade results from the Acustica baseline

and NTM_1.25 model show variable noise mitigation around buildings. As demonstrated in Figure 3

some buildings assigned as benefiting from a 1dBA reduction show that, based on the façade results,

some parts of the building may be benefiting from a 2dBA reduction.



Figure 3. Noise

levels (dBA, metric LA1018)

modelled at building façade

points. Baseline Acustica model,

blue text; Acustica NTM_1.25

model, red text. Legend colour

codes denote calculated

mitigated area with Acustica

NTM_1.25 model.

The output of the Acustica NTM_1.25 model should also be viewed critically, as the approach used is

not without caveats. An attempt has been made to simulate the effect of urban woodland on noise

reduction through increasing the ground absorbance value below the woodland and representing the

woodland as a 1.25m high barrier. The HOSANNA report (2013) suggests that vegetation can be

modelled as a barrier from 1.0 – 1.5m, and for the Acustica NTM_1.25 model all woodland was

modelled as a 1.25m high barrier. Potentially there exist patches of woodland that may qualify to be

modelled as a 1.5m high barrier, and equally as a 1.0m high barrier, which may impact the results.

Acustica results suggest that the mitigation effect of thick woodland may be underestimated while

the benefit from thinner tree bands may be overestimated. Urban woodland is difficult to model due

to the thinner nature that this type of vegetation can have; how to model the noise attenuation

impact of thin woodland bands is a challenge still being investigated by complex non-commercial and

commercial noise models.

Having assessed the impact of these differences in the test area of North West Manchester, some

amendments are suggested to constrain the eftec-CEH results:

It is recommended that only mitigated area in noise bands above 60dBA is considered, this

would reduce the overestimation of the benefits provided by urban woodland and account

somewhat for flanking effects. When only mitigated area above this level is considered for

both models, compared to the Acustica NTM_1.25 model the CEH model predicts a larger

mitigated area by a factor of 3, and the number of dwellings benefiting from mitigation is

reduced from the initial factor of 14 also to a factor of around 3.

It is proposed that all 2dBA mitigated areas should be assigned to 1dBA. This would counter

the overestimation of 2dBA areas and provide an estimate of the impact of urban woodland

on noise reduction that is closer to the conventional noise modelling approach.

The outcome of these adjustments in comparison to the initial CEH model and Acustica NTM_1.25

model is provided in

Table A1.

1 dBA

2 dBA



Table A1. Physical and monetary flow accounts for the noise mitigation benefits of urban natural

capital for the CEH model, Acustica NTM_1.25 model, and adjusted CEH model output for a test

area in North West Manchester, where all mitigated areas are assumed to be only 1dBA, and only

dwellings within noise bands 60 dBA and above are considered.

Noise

band21

Number of dwellings benefiting from noise

mitigation by urban woodland22 Annual value of noise mitigation (£/yr)

CEH Acustica

NTM_1.25 Adjusted CEH CEH

Acustica

NTM_1.25 Adjusted CEH

>=80 - - - - - -

75.0-79.9 - - - - - -

70.0-74.9 - 1 - - 138 -

65.0-69.9 24 18 24 4,513 1,885 2,513

60.0-64.9 216 29 216 26,671 2,182 16,249

55.0-59.9 490 23 - 44,817 1,297 -

50.0-54.9 293 5 - 8,480 95 -

45.0-49.9 40 - - 828 - -

Total 1,063 76 240 85,309 5,597 18,762

Results with amended approach

This section presents the results of the accounts adopting the amended approach suggested above.

Table A2 shows the total number of buildings where noise levels are mitigated with NTM and OSMM

data using the amended approach. The total number of buildings mitigated is estimated at 467,000

with NTM data and 167,000 with OSMM data. Note that while NTM provides a more robust data source

at finer resolution, it was only available for Manchester. So when extrapolating up to UK level, that

carries a larger uncertainty than just using the OSMM, which was available for all GB. Therefore, in

general, the OSMM based approach is recommended as the preferred of the two.

Table A2 Number of buildings where road noise levels are mitigated by natural capital in England,

Scotland, Wales and Northern Ireland with NTM and OSMM data, amended approach

21 5 dB bands applied along with guidance in Defra (2014a). 22 Urban vegetation includes large woodlands (>3,000m2) and smaller woodlands (<3,000m2), but not very small

woodlands (<200m2). Values for large and small woodland are combined in these tables.

Noise

band

Buildings mitigated (‘000) – NTM data Buildings mitigated (‘000) – OSMM data



Northern

Ireland

>=80

< 1

-

-

-

< 1

-

-

-

75.0-79.9

1

-

< 1

< 1

< 1

-

< 1

< 1

70.0-74.9

16

< 1

2

2

8

< 1

< 1

< 1

65.0-69.9

94

3

7

8

36

1

3

1

60.0-64.9

271

17

22

22

98

6

8

4



Table A3 shows the annual monetary benefits of noise regulation based on the avoided loss of QALYs

associated with a loss of amenity (sleep and annoyance) and adverse health outcomes due to noise

for NTM and OSMM data using the amended approach. The total annual value from noise mitigation

is estimated at £41 million with NTM data, and at £14 million with OSMM data.

Table A3. Annual value of road noise regulating benefits from urban natural capital in England,

Scotland, Wales and Northern Ireland with NTM and OSMM data, amended approach

Table 4 shows the asset value for noise regulation based on the estimated flow of future benefits

over 100 years, with NTM and OSMM data, using the amended approach. The total asset value for

noise mitigation is estimated at £2,168 million with NTM data, and at £786 million with OSMM data.

Total

383

21

31

32

142

7

12

6

Noise band

Annual value of benefit (£’000/yr) – NTM

data

Annual value of benefit (£’000/yr) – OSMM

data

England Scotland Wales Norther

n Ireland England Scotland Wales

Norther

n Ireland

>=80

2

-

-

-

1

-

-

-

75.0-79.9

202

-

11

14

139

-

11

2

70.0-74.9

2,261

18

208

280

1,041

7

100

53

65.0-69.9

9,848

352

719

820

3,799

117

295

133

60.0-64.9

20,396

1,398

1,664

1,636

7,339

454

634

305

Total 32,709 1,768 2,601 2,750 12,320 578 1,040 493

Noise

band

Value of noise reduction (£m) – NTM data Value of noise reduction (£m) – OSMM data

England Scotland Wales Norther

n Ireland England Scotland Wales

Norther

n Ireland

>=80 < 1

-

-

-

< 1

-

-

-

75.0-79.9 11

-

< 1

< 1 8

-

< 1

< 1

70.0-74.9 123 < 1

11

15 57

< 1

5

3

65.0-69.9 536 19

39

45

207

6

16

7

60.0-64.9

1,110 76

91

89

399

25

35

17

Total 1,780 96 142 150 670 31 57 27



Table A4. Asset value of ecosystem service flows from UK urban natural capital23 (PV, 100 years)

with NTM and OSMM data, amended approach

Glossary

LA10 The noise level just exceeded for 10% of the measurement period, A-weighted and

calculated by Statistical Analysis.

LA10(18) LA10 measured over an 18 hour period, from 6.00 am to midnight. LA10 (18-hour) is

considered good practice when reporting Road Traffic Noise measurements.

Lden Day-evening-night equivalent level A-weighted equivalent sound level, measured

over the 24 hour period, with a 10 dB penalty added to the levels between 23.00 and

07.00 hours and a 5 dB penalty added to the levels between 19.00 and 23.00 hours

to reflect people's extra sensitivity to noise during the night and the evening.

Lnight The A-weighted average sound level over the 8 hour night period of 23.00 – 07.00

hours.









Appendix 1 – ELECTRIC VEHICLES

Electric Vehicles (EVs) use electric motors to produce propulsion rather the combustion of fuel which

powers Internal Combustion Engine vehicles (ICE). EV motors produce less noise, measured in decibels

(dB), than ICE motors due to their reliance on electrical power sources (i.e. batteries), rather than

combustion which produces noise. EVs also contain fewer moving parts due to the simpler mechanical

nature of their engines and drive trains, which also mitigates the overall noise they produce.

Although the technology for electric propulsion has been available since the 19th century (and in fact

is predominantly used in many other modes of transport aside from passenger and transport road

vehicles), its adoption has not been widespread in passenger vehicles and their overall presence in

the vehicle stock is small (estimated at 2.5% of the UK car stock for 2018). However, more recent

technological advances along with a desire to move away from fossil fuel use, has seen increasing

uptake of EVs. While the rate of technological advance and consumer uptake are very difficult to

predict, a general consensus is that the proportion of the vehicle stock that is EV will increase over

the coming years and decades.

When assessing the impact that natural capital has on noise reduction within the urban context over

time, we must consider the future noise baseline which natural capital assets mitigate. Future noise

levels cannot be assumed to be a static extension of current levels, but will be subject to many trends

and unforeseen step changes. One of the trends that must be considered is the impact to future noise

levels that the uptake of EVs will have. There are many factors to consider, and in the absence of

empirical evidence, assumptions must be made as to their scale and direction. The key factors

thought to influence the impact that EVs will have on overall future noise levels are:

Uptake rate of EVs - EV uptake up to 2050 is very uncertain. The most recent baseline

projections from 2018-2050 considered for the purpose of this report, provided by the

Department for Transport, suggest a limited impact on noise reduction.

Difference in noise between EVs and ICEs - Although it is commonly accepted that EVs are

quieter than ICEs, limited research has been found to provide empirical evidence to quantify

this difference. The Danish Road Directorate24 compared similar EV and ICE vehicles under

urban conditions and suggest that, at speeds below 30km/h, EVs are 5 dBs quieter.

Speed of travel - As impact is measured as the health effects from disturbed sleep, it is the

speed of travel at night that is in question. Traffic congestion is minimal at night when most

people are at home, and so traffic should generally be expected to flow at around the speed

limit. In most cases, this will be above the 30km/h threshold beyond which the noise

differential between EVs and ICEs was found to converge.

Acceleration and deceleration versus steady movement – Engine noise measured at steady

speeds does not factor in the noise from acceleration and deceleration, which may play more

of a role in sleep disturbance than steady background noise levels.

Other traffic noise – It is likely that other traffic noise, such as honking, breaking, emergency

vehicles and motorcycles play a disproportional role in sleep disturbance than the steady

noise emitted by EV or ICE engines.

24 http://www.conforg.fr/euronoise2015/proceedings/data/articles/000541.pdf

http://www.conforg.fr/euronoise2015/proceedings/data/articles/000541.pdf



Pitch level – The impacts of the pitch of engine noise are not well understood. Higher or

lower pitched noises may play a greater impact on sleep disturbance than relative dBs, and

the ways that different pitches of sound travel through different barrier materials in the

urban context is not currently captured.

Noise dynamics of mixed vehicle traffic – The degree to which a reduction in the engine noise

of a part of the vehicle mix would translate to a reduction in overall noise in a real-world

context is uncertain. It is likely that the impact is not directly proportional to the aggregate

difference in engine noise, as various other dynamics would come in to play.

More research into each of these factors would help develop a better understanding on which to base

projections for the impact of EVs on future street traffic noise impacts. Making use of the available

evidence, we apply the average annual discounted proportion of EVs in the car stock of 16.84% to the

5dB difference in engine noise, to estimate the discounted average annual aggregate impact of

0.842dBs of noise reduction due to EVs. This is below the 1dB threshold at which noise impacts are

modelled, and would likely be an overestimate of impact given that it would only apply to vehicles

travelling below 30km/h.

When the additional factors as discussed above are considered, including the impact of acceleration

and deceleration, other traffic noise and pitch effects, and the potential non-linear relationship

between proportional reduction in engine noise and aggregate noise impact, the actual noise

reduction from the uptake of EVs is currently thought likely to be lower than 0.842dBs. As such, based

on the current understanding and available evidence, the impact of EVs has not been considered

material to this assessment.



REFERENCES

Coensel, B.D., Vanwetswinkel, S. and Botteldooren, D. (2011) Effects of natural sounds on the

perception of road traffic noise. The Journal of the Acoustical Society of America, 129, EL148‐EL153.

Defra (2014a) Noise pollution: economic analysis. Available online:

https://www.gov.uk/guidance/noise-pollution-economic-analysis

Defra (2014b) Environmental Noise: Valuing impacts on: sleep disturbance, annoyance, hypertension,

productivity and quiet.

https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/380852/environ

mental-noise-valuing-imapcts-PB14227.pdf

Defra (2014c) Transport noise modelling tool

https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/380849/transpor

t-noise-modelling-tool.xls

Defra/ONS (2017) Principles of Natural Capital Accounting

https://www.ons.gov.uk/economy/environmentalaccounts/methodologies/principlesofnaturalcapit

alaccounting

eftec, CEH, CEP, Peter Neal Consulting, University of Exeter, Countryscape and Woodland Trust

(2017) A study to scope and develop urban natural capital accounts for the UK.

http://randd.defra.gov.uk/Default.aspx?Menu=Menu&Module=More&Location=None&Completed=0&

ProjectID=19843

Doick, K.J., and Hutchings, T.R. (2013) Air temperature regulation by trees and wider green

infrastructure in urban areas: the current state of knowledge. Research note 12 (FCRN012). Forestry

Commission, Edinburgh.

European Commission (EC) (2013) HOSANNA (Holistic and sustainable abatement of noise by optimized

combinations of natural and artificial means). Available online:

http://cordis.europa.eu/result/rcn/144672_en.html

Evans, G.W., Hygge, S. and Bullinger, M. (1995) Chronic noise and psychological stress. Psychological

Science, 6, 333–338.

Evans, G.W., Lercher, P., Meis, M., Ising, H. and Kofler, W.W. (2001) Community noise exposure and

stress in children. The Journal of the Acoustical Society of America, 109, 1023.

Fang C, Ling D. (2003) Investigation of the noise reduction provided by tree belts. Landscape and

Urban Planning; Vol. 63; 2003. p. 187-195.

Galbrun, L. and Ali, T.T. (2013) Acoustical and perceptual assessment of water sounds and their use

over road traffic noise). The Journal of the Acoustical Society of America, 133, 227‐237.

Gómez-Baggethun, E., Gren, Å., Barton, D.N., Langemeyer, J., McPhearson, T., O’Farrell, P.,

Andersson, E., Hamstead, Z. and Kremer, P. (2013) Urban ecosystem services. In Urbanization,

biodiversity and ecosystem services: Challenges and opportunities (pp. 175-251). Springer

Netherlands.

https://www.gov.uk/guidance/noise-pollution-economic-analysis

https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/380852/environmental-noise-valuing-imapcts-PB14227.pdf

https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/380852/environmental-noise-valuing-imapcts-PB14227.pdf

https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/380849/transport-noise-modelling-tool.xls

https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/380849/transport-noise-modelling-tool.xls

https://www.ons.gov.uk/economy/environmentalaccounts/methodologies/principlesofnaturalcapitalaccounting

https://www.ons.gov.uk/economy/environmentalaccounts/methodologies/principlesofnaturalcapitalaccounting

http://randd.defra.gov.uk/Default.aspx?Menu=Menu&Module=More&Location=None&Completed=0&ProjectID=19843

http://randd.defra.gov.uk/Default.aspx?Menu=Menu&Module=More&Location=None&Completed=0&ProjectID=19843

http://cordis.europa.eu/result/rcn/144672_en.html



HOSANNA report (2013). Novel solutions for quieter and greener cities. Summary project brochure of

HOSANNA FP7 project.

http://www.hosanna.bartvanderaa.com/includes/upload/DELIVERABLES/HSNNA_SUMMARY_BROCH

URE_JANUARY_2013.pdf [Accessed 1 May 2018]

Jarup, L., Babisch, W., Houthuijs, D., Pershagen, G., Katsouyanni, K., Cadum, E., Dudley. M.,

Savigny, P., Seiffert, I., Swart, W., Breugelmans, O., Bluhm, G., Selander, J., Charalampidis, A.S.,

Dimakopoulou, K., Sourtzi, P., Velonakis, M., Vigna-Taglianti, F. (2008) Hypertension and exposure

to noise near airports - the HYENA study. Environ Health Perspect, 116, 329-333.

Jones, L., Vieno, M., Morton, D., Cryle, P., Holland, M., Carnell, E., Nemitz, E., Hall, J., Beck, R.,

Reis, S., Pritchard, N., Hayes, F., Mills, G., Koshy, A., Dickie, I. (2017). Developing Estimates for the

Valuation of Air Pollution Removal in Ecosystem Accounts. Final report for Office of National

Statistics, July 2017.

Nellthorp, J., Bristow, A., Mackie, P. (2005) Developing guidance on the valuation of transport-

related noise for inclusion in WebTAG. ITS/TSG Seminar Paper. 17th May 2005.

Nellthorp, J., Bristow, A., Day, B. (2007) Introducing Willingness-to-pay for Noise Changes into

Transport Appraisal: An Application of Benefit Transfer. Transport Reviews, 27(3), 327-353.

Office for National Statistics (ONS) (2011) Built-up Areas. Available online:

https://data.gov.uk/dataset/built-up-areas-december-2011-boundaries3

Peng, J., Bullen, R. and Kean, S., (2014) The effects of vegetation on road traffic noise. In INTERNOISE

and NOISE-CON Congress and Conference Proceedings. Institute of Noise Control Engineering (pp.

600-609), October.

Stansfield, S. and Matheson, P. (2003) Noise Pollution: Non-Auditory Effects on Health. British

Medical Bulletin, 68: 243–257.

Van Renterghem, T., 2014. Guidelines for optimizing road traffic noise shielding by non-deep tree

belts. Ecological Engineering, 69, pp.276-286.

Van Renterghem, T., Botteldooren, D. and Verheyen, K., 2012. Road traffic noise shielding by

vegetation belts of limited depth. Journal of Sound and Vibration, 331(10), pp.2404-2425.

Van Renterghem, T., Hornikx, M., Smyrnova, Y., Jean, P., Kang, J., Botteldooren, D. and Defrance,

J., (2012) Road traffic noise reduction by vegetated low noise barriers in urban streets. In Proceedings

of the 9th European conference on noise control (Euronoise 2012), Prague, June.

Van Renterghem, T., Hornikx, M., Forssen, J. and Botteldooren, D., (2013) The potential of building

envelope greening to achieve quietness. Building and Environment, 61, 34-44.

World Health Organisation (WHO) (2011) Burden of disease from environmental noise Quantification

of healthy life years lost in Europe. WHO European Centre for Environment and Health, Bonn Office,

WHO Regional Office for Europe.

https://data.gov.uk/dataset/built-up-areas-december-2011-boundaries3