Scottish Natural Capital Accounts: 2021

This report estimates quantity and value of services supplied by Scottish natural capital for:

Agricultural biomass

Fish capture


Water abstraction


Fossil fuel

Renewable energy

Carbon sequestration

Air pollution removal

Noise mitigation

Urban cooling

Recreation and house price values

7. Methodology

This article was produced for the Scottish Government by the Office for National Statistics. The article is available from both the Office for National Statistics and the Scottish Government. Office for National Statistics natural capital accounts are produced in partnership with the Department for Environment, Food and Rural Affairs (Defra). Further details about the natural capital accounting project are also available.

The methodology used to develop these estimates remains under development; the estimates reported in this article are experimental and should be interpreted in this context. Experimental Statistics are those that are in the testing phase, are not yet fully developed and have not been submitted for assessment to the UK Statistics Authority. Experimental Statistics are published to involve customers and stakeholders in their development and as a means of building in quality at an early stage.

This methodology section provides a detailed summary of the methodology used to develop the natural capital accounts. This summarises the broad approach to valuation and the overarching assumptions made, as well as giving a more detailed description of the methods used to value the individual components of natural capital and physical and monetary data sources.

We have used a wide variety of sources for estimates of UK natural capital, which have been compiled in line with the guidelines recommended by the United Nations (UN) System of Environmental-Economic Accounting Central Framework and System of Environmental-Economic Accounting Experimental Ecosystem Accounting principles, which are in turn part of the wider framework of the system of national accounts.

As the UN guidance is currently still under development, the Office for National Statistics (ONS) and the Department for Environment, Food and Rural Affairs (Defra) published a summary of the principles underlying the accounts.

We welcome discussion regarding any of the approaches presented via email at

Overview of services

This section provides a high-level overview of the ecosystem services relative quality and future aims. For detailed information on the methods used please continue to the methodology by service section.

Table 9: Summary of service estimates quality
Service Suitability Coverage Source data Granularity Timeliness Timespan
Agricultural biomass 3 2 1 3 2 1
Fish capture 1 2 2 1 2 1
Timber 1 1 1 1 1 1
Water 3 2 1 3 2 1
Minerals 2 1 1 3 2 1
Fossil fuels 1 1 1 3 2 1
Renewable energy 3 3 2 2 2 1
Carbon sequestration 1 3 2 2 2 1
Air pollutant removal 1 1 2 1 3 2
Urban cooling 1 3 3 2 2 2
Noise mitigation 1 2 2 1 3 3
Recreation 1 3 2 1 2 1
Recreation (house prices) 1 2 1 1 3 2
Aesthetic (house prices) 1 2 1 1 3 2

Source: Office for National Statistics


1. 1/Green = relatively strong, 2/Amber = could be improved, 3/Red = needs improvement.

2. Suitability: Suitability of method in the valuation of natural capital asset, particularly considering the ability to integrate condition and sustainability measures. A suitable natural capital value has a clear logic chain where the impact of changes can be measured and sustainability influences asset valuation.

3. Coverage: The ability to provide a well-rounded and fair coverage of the full benefits the service provides.

4. Source data: The quality of the underlying data sources for estimating the ecosystem service.

5. Granularity: The ability to disaggregate the service, primarily by geography.

6. Timeliness: The ability to provide full up to date estimates.

7. Timespan: The ability to provide a consistent timeseries going back several years.

Service summary and future aims

Agricultural biomass

Estimates of the provisioning value of agricultural biomass based on a resource rent residual value of industry national accounts data does not offer a strong logic chain from extent through condition and flow to valuation. As a result, it is difficult observe how changes in agriculture impact its natural capital asset valuation. Further development and examination of alternative methods is required. The methodology for the valuation of agricultural biomass is likely to change substantially in the future.

Fish capture

Using net profit estimates of fish capture of individual species in different areas provides a clear logic chain from natural capital asset to valuation. As a result, we can now begin to integrate sustainability measures that directly influence the asset valuation, as seen in the annex and within the marine accounts. Although illustrated in the annex, to maintain consistency with the 2020 UK accounts, these methodological improvements are not included within this account.


Estimates of the provisioning value of timber provides a strong logic chain from flow to valuation, through stumpage prices, and integrate future projections of provisioning. We currently have no development plans for the near future.

Water abstraction

Estimates of the provisioning value of water abstraction based on a resource rent residual value of industry national accounts data does not offer a strong logic chain from flow to valuation. As a result, it is difficult observe how changes in the water industry affect its natural capital asset valuation. The methodology for the valuation of water abstraction is likely to change substantially in the future. Long term we hope to net off the costs of any water restrictions to society from overall industry income.


Estimates of the provisioning value of mineral extraction based on a resource rent residual value of industry national accounts data does not offer a strong logic chain from flow to valuation. As a result, it is difficult observe how changes in the mineral extraction industry affect its natural capital asset valuation. Data for the minerals industry is relatively sparse. We currently have no development plans for the near future.

Fossil fuels

Estimates of the provisioning value of fossil fuels based on a wholesale price integrated resource rent residual value adaptation represent the best available practical approach to the valuation of the fossil fuels asset. There are unlikely to be any significant changes to this methodology in upcoming accounts.


Estimates of the provisioning value of renewable energy based on a resource rent residual value of industry national accounts data does not offer a strong logic chain from flow to valuation. As a result, it is difficult observe how changes in the renewables industry affect its natural capital asset valuation. The methodology for the valuation of renewables is likely to change substantially in the future. We aim to use data on subsidies and levelized costs of operation to estimate the overall income for the renewable providers. The direction of the change is uncertain.

Carbon sequestration

Carbon sequestration largely suffers coverage issues as to the extent of land-based emissions (such as from degraded peatland) that are currently not fully covered within the greenhouse gas inventory. Potentially significant sequestration from marine habitats (covered in the annex) is also not included. There are also issues as the exclusion of 'natural' emissions, if sequestration moved from a gross to a net sequestration basis the value would fall. The valuation process for carbon sequestration is unlikely to change soon but the coverage of different habitats is likely to improve.

Air pollution removal

We hope to update the models and data to provide more accurate and timely values of air pollutant removal by vegetation. Direction of the change would be uncertain, but it is unlikely to be large.

Urban cooling

Longer term it is desirable to use remote sensing temperature data to ground truth our estimates of urban cooling. If we can move from a relatively simple model to a more precise site-specific prediction, we may also switch to a less conservative valuation price.

Noise mitigation

We hope to use other data to provide yearly estimates of noise production. This would allow us to see expected changes between years but should not impact on the scale of the service. There are also likely to be changes in the modelling for noise dispersion which may reduce benefits.


Recreation largely suffers coverage, lacking overnight tourism, and timeliness issues. Day visit surveys across the UK are not consistent and, increasingly, lack the essential questions on expenditure needed for estimations of the recreational cultural service. We have recently published the tourism accounts, providing a different and consistent approach to estimating recreation, inclusive of overnight tourism. This will significantly increase the value of recreation in future accounts. To maintain consistency with the 2020 UK accounts, these methodological improvements are not included within this account.

Recreation (house prices)

The original data source for advertised house prices is no longer readily available. We will therefore move to actual recorded sale prices. In addition, we need to make more direct estimates of urban and rural house numbers but also include the value of recreation outside of formal parks. The overall impacts of these changes are unknown but could be significant.

Aesthetic (house prices)

See Recreation (house prices). However, in addition we would need to change the basis on which a, "view" is identified which again will have an uncertain impact on value.

Annual ecosystem service flow valuation

Broadly, two approaches are used to value the annual service flows. For fish capture, timber, carbon sequestration, pollution removal, noise mitigation, urban cooling, and recreation, an estimate of physical quantity is multiplied by a price. This price is not a market price but satisfies two accounting conditions:

  • identifying a price that relates, as closely as possible, to contributions provided by the ecosystem to the economy
  • where no market exists, imputing a price that an ecosystem could charge for its services in a theoretical market

These conditions are necessary to integrate and align ecosystem services to services elsewhere in the national accounts, for example, in the accounts woodland timber is an input to the timber sector.

For agricultural biomass, water abstraction, minerals, fossil fuels, and renewable energy generation a “residual value” resource rent approach is used.

Resource rent definition and assumptions

The resource rent can be interpreted as the annual return stemming directly from the natural capital asset itself. This is the surplus value accruing to the extractor or user of a natural capital asset calculated after all costs and normal returns have been considered.

The steps involved in calculating the resource rent are given in Table 10. Variations of this approach are applied depending on the category of natural capital under assessment; the variations are explained in the individual ecosystem service methodology.

Table 10: Derivation of resource rent
Calculation Measure
Less Operating costs
Less Intermediate consumption
Less Compensation of employees
Less Other taxes on production PLUS other subsidies on production
Equals Gross operating surplus – SNA basis
Less Specific subsidies on extraction
Plus Specific taxes on extraction
Equals Gross operating surplus – resource rent derivation
Less User costs of produced assets (consumption of fixed capital and return to produced assets)
Equals Resource rent

Source: Office for National Statistics

Most of the data used in Scottish resource rent calculations are available from the Scottish Government input-output tables (1998 to 2017). Return to produced asset estimates are calculated using apportioned industry-based net capital stocks and the nominal 10-year government bond yield published by the Bank of England, then deflated using the gross domestic product (GDP) deflator to produce the real yield. This rate is relatively conservative compared with those expected in certain markets and could overstate the resulting resource rent estimates.

Technical guidance on SEEA Experimental Ecosystems Accounting (page 193) (PDF, 5.33 MB) acknowledges that the use of the method may result in small or even negative resource rents. Obst, Hein and Edens (2015) conclude that:

“resource rent type approaches are inappropriate in cases where market structures do not permit the observed market price to incorporate a reasonable exchange value for the relevant ecosystem service. Under these circumstances, alternative approaches, for example, replacement cost approaches, may need to be considered”.

If the residual value approach does not produce plausible estimates for subsoil assets and provisioning services, alternative methods should be explored (Principle 7.7). Finally, where unit resource rents can be satisfactorily derived, care still needs to be taken in applying these at a disaggregated level. Even for abiotic flows, the extraction or economic costs could vary spatially and hence national unit resource rents could be misleading for specific regions.

Asset valuation

The net present value (NPV) approach is recommended by the System of Environmental-Economic Accounts (SEEA) and is applied for all ecosystem services to estimate the asset value. The NPV approach estimates the stream of services that are expected to be generated over the life of the asset. These values are then discounted back to the present accounting period. This provides an estimate of the capital value of the asset relating to that service at a given point in time. There are three main aspects of the NPV method:

  • pattern of expected future flows of values
  • asset life – time period over which the flows of values are expected to be generated
  • choice of discount rate

Pattern of expected future flows of services

A principal factor in the valuation of natural capital is determining the expected pattern of future flows of services. These paths are not observed and hence assumptions concerning the flows must be made, generally as a projection of the latest trends.

A more basic way to estimate the expected flows is to assume that the current flow (averaged over recent years) is constant over the asset life, but this might not be the case. In some cases, more information is available on future expected levels of services in non-monetary terms or future unit prices. Where there are readily available official projections these have been considered but otherwise the default assumption in these estimates is that the value of the services is constant over time.

This article assumes constant service values throughout the asset life, except for the estimates for carbon sequestration and air pollutant removal by vegetation, where further projections are used.

Where the pattern of expected service values is assumed to be constant, it is based on averages over the latest five years of data, up to and including the reference year in question.

Asset life

The asset life is the expected time over which the services from a natural resource are expected to be provided. An estimate of the asset life is a key component in the NPV model because it determines the expected term over which the service flows from an asset should be discounted.

Following the ONS and Defra principles paper, this article takes one of three approaches when determining the life of a natural capital asset.

Non-renewable natural capital assets: where a sufficient level of information on the expected asset lives is available this asset life is applied in the calculations. Where a sufficient level of information on their respective asset lives is not available a 25-year asset life is assumed.

Renewable natural capital assets: a 100-year asset life is applied to all assets that fall within this category of natural capital.

Choice of discount rate

A discount rate is required to convert the expected stream of service flows into a current period estimate of the overall value. A discount rate expresses a time preference – the preference for the owner of an asset to receive income now rather than in the future. It also reflects the owner’s attitude to risk. The use of discount rates in NPV calculations can be interpreted as an expected rate of return on the environmental assets.

Based on an extensive review by external consultants, the ONS and Defra use the social discount rate set out in the HM Treasury Green Book (2003, page 100). In line with guidance set out in the document, estimates presented in this article assume a 3.5% discount rate for flows projected out to 30 years, declining to 3.0% thereafter and 2.5% after 75 years. The rationale for this approach is discussed further in the ONS and Defra principles paper.

Methodology by service

The following section provides an explanation of the data sources and methods used in each service.

As well as updated data and a newer price basis there have been some methodological improvements and underlying data source changes from the previous Scottish natural capital accounts: 2020. Results should not be compared across accounts. Please use the data available in this alongside this release for time series analysis. The scale of these changes varies across different ecosystem services. Table 11 provides a broad explanatory summary of these changes and the impact they have on service valuations.

Table 11: Percentage change in 2016 asset values by service because of methodological changes between 2020 and 2021 accounts
Service Percentage change Explanation
Fish capture 52% Improved net profit estimations from Seafish
Water abstraction 56% Updates to the Scottish input output tables for standard industry code 36/37
Minerals -75% Updates to the Scottish input output tables for standard industry code 08
Fossil fuels -12% Updates to the Office for National statistics capital stocks data for standard industry code 06
Other services 0% No change
Total -4%

Source: Office for National Statistics

These experimental accounts are being continually revised to produce the best statistics with the available data and methods.

Agricultural biomass

Agricultural biomass relates to the value of crops, fodder and grazed biomass provided to support agricultural production. Agricultural statistics are published by the Scottish Government. Grazed biomass calculations are based upon livestock numbers and livestock annual roughage requirements provided in the Eurostat Economy-wide Material Flow Accounts (PDF, 2.96MB) (EW-MFA) questionnaire. This approach is also used in the UK Material Flows Accounts.

Estimating the proportion of agricultural production, which can be attributed to nature rather than modern intensive farming practices, is challenging. Modern farmers heavily manage and interact with the natural services supplied on their land. For example, sowing, irrigation, fertiliser spreading, pesticide use, and livestock management are all industrial practices applied to the land. Very intensive farming may even take place entirely indoors without soil or natural light. At the other extreme, livestock may be allowed to roam freely over semi-natural grassland with limited human intervention.

As with the principles applied to the UK natural capital accounts, we draw the line between the farmland ecosystem and the economy at the point at which vegetable biomass is extracted (Principle 5.3). This means farmed animals are not included in these estimates as they are considered as produced rather than natural assets. Instead, the grass and feed that livestock eat are regarded as ecosystem services and so are included. This is also consistent with the boundary between the environment and the economy used in the material flows accounts.

For the primary valuation of agricultural biomass, a “residual value” resource rent approach is used. This is based upon data for the Standard Industrial Classification (SIC) subdivision class: crop and animal production, hunting and related service activities (SIC 01). The Input-output supply and use tables and capital stocks data do not provide further SIC breakdowns so the industry residual value includes animal production. The factor used for apportioning net capital stocks and consumption of fixed capital is the proportional relationship between Scotland and UK aggregate agriculture accounts consumption of fixed capital.

While residual value resource rent approaches should be used for valuing provisioning services in the first instance (Principle 7.5) top-down industry-level estimates present difficulties in establishing clear ecosystem service logic chains and disaggregation. Condition indicators, or even physical flows of agricultural biomass, cannot readily be related to the estimated valuation of the service.

Fish capture

We have been working to improve our fisheries statistics and more work is needed. We rely on a range of external sources that all involve known uncertainties. For instance, Norway and Faroese landings are excluded from this analysis. The economic data are based on UK fleet data, which we also apply to foreign vessels that may face different costs and prices.

Aquaculture or farmed fish, like farmed livestock, have been removed from estimates as farmed fish are viewed as a produced asset and not a natural asset.

Physical data on marine fish capture (live weight) is sourced from the rectangle-level landings data published annually by the EU Commission's Joint Research Centre (JRC) Scientific, Technical and Economic Committee for Fisheries (STECF) as part of the Fisheries Dependent Information (FDI) data call (deep sea).

To calculate marine fish capture in the Scottish exclusive economic zone (EEZ) Marine Management Organisation ICES statistical rectangle factors were used. The overall fish capture provisioning service physical flow presented in this article represents landings (tonnage) from UK waters. UK boundaries do not perfectly align with the geographical areas of fish capture statistics. For more detail on how fish capture in UK waters is estimated, see the Marine Management Organisation Exclusive Economic Zone Analysis and associated publications.

Valuations are calculated using net profit per tonne (landed) estimates, provided by Seafish, for different marine species by marine areas. Net profit per tonne is calculated using Seafish economic estimates for fleet segments and Marine Management Organisation data on landings by stocks (landed value and landed weight) and landings by stocks and species (in cases where species are not managed by total allowable catches). Annual net profit per tonne (landed weight) is multiplied by tonnes of fish captured (live weight) for a specific species. The data are aggregated for overall annual valuations of fish provisioning from the UK EEZ.

Landed weight is the weight a product at the time of landing, regardless of the state in which it has been landed. Landed fish may be whole, gutted and headed or filleted. Live weight is the weight of a product, when removed from the water.

A notable limitation of the fish capture provisioning valuation methodology is that landed weight net profits were multiplied by live weight fish capture. Based on Marine Management Organisation data on live and landed weights of UK vessel landings into the UK, aggregate landed weight is around 7% less than live weight.

Net profit per tonne was not available for all fish species so not all the physical flow is valued. Based on available net profit per tonne annual data, 93% of fish provisioning (live tonnes) from Scottish waters was valued in 2018.


The method used to value the provisioning services related to timber supply requires two inputs: the stumpage price and the physical amount of timber removed. Annual flow values are then generated by multiplying the two factors together.

Timber provisioning service asset valuations used Forestry Commission forecasts of timber availability to estimate the pattern of expected future flows of the service over the asset lifetime.

Removals estimates are taken from Forest Research Timber Statistics and converted from green tonnes to cubic metres (m3) overbark standing, using a conversion factor of 1.222 for softwood and 1.111 for hardwood.

The stumpage price is the price paid per standing tree, including the bark and before felling, from a given land area. Stumpage prices are sourced from the Forestry Commission Coniferous Standing Sales Price Index in the Timber Price Indices publication (2018). The Coniferous Standing Sales Price Index monitors changes in the average price received per cubic metre (overbark) for timber that the Forestry Commission or Natural Resources Wales sold standing, where the purchaser is responsible for harvesting.

Water abstraction

Physical data for water abstraction for public water supply are sourced from Scottish Water.

Monetary estimates are based on resource rents calculated for the Standard Industrial Classification (SIC) subdivision class: Water collection, treatment, and supply (SIC 36). The definition of this industry subdivision states: “the collection, treatment and distribution of water for domestic and industrial needs. Collection of water from various sources, as well as distribution by various means is included.” A limitation of this approach, therefore, is that the calculated resource rent is not purely related to water supply, but also includes the process of treating the water.

In estimating the resource rent for the Scottish water abstraction provisioning service Input-output supply and use tables and capital stocks data are used. The factor used for apportioning net capital stocks and consumption of fixed capital was the proportional annual relationship between Scotland and UK water collection, treatment, and supply (SIC 36) intermediate consumption at purchasers' prices.

Further work is required to value the services relating to other uses of the water provisioning services, and to explore the roles of different ecosystem types in providing clean water.


Physical estimates of mineral extraction are provided by the British Geological Survey (BGS) as a country-level breakdown of the United Kingdom Minerals Yearbook. Mineral extraction after 2014 are estimated.

Monetary estimates are based on the “residual value” resource rent approach calculated from the SIC subdivision class: Other mining and quarrying (SIC 08). This division includes extraction from a mine or quarry, but also dredging of alluvial deposits, rock crushing and the use of salt marshes. The products are used most notably in construction, such as stone and aggregates, and manufacture of materials, such as clay and gypsum, and manufacture of chemicals. This division does not include processing (except crushing, grinding, cutting, cleaning, drying, sorting, and mixing) of the minerals extracted.

Monetary estimates are based on the “residual value” resource rent approach calculated from the SIC subdivision class: other mining and quarrying (SIC 08). In estimating the resource rent for the Scottish minerals abiotic provisioning service Scottish input-output tables and source-level apportioning of ONS UK capital stocks is used. The factor used for apportioning net capital stocks and consumption of fixed capital was the proportional annual relationship between Scotland and UK other mining and quarrying (SIC 08) intermediate consumption at purchasers' prices.

Fossil fuels

Physical estimates of oil and gas production are available from the Scottish Government. Country-level coal production were requested from the Department for Business, Energy, and Industrial Strategy (BEIS) Digest of UK Energy Statistics (DUKES).

Monetary estimates of oil and gas are based on the methodology published by the ONS in June 2013, following a “residual value” resource rent approach calculated from the SIC subdivision class: Extraction of crude petroleum and natural gas (SIC 06). Production statistics are combined with oil and gas price data supplied by the Oil and Gas Authority (OGA) to calculate income. Deductions are then made for operating expenditure, from the Scottish Government, and user costs of produced assets, from ONS UK capital stocks data. The factor used for apportioning net capital stocks and consumption of fixed capital was the proportional annual relationship between Scotland and UK oil and gas capital expenditure.

For the valuation of coal, a “residual value” resource rent approach is used. This is based upon supply and use and capital stocks data for the Standard Industrial Classification (SIC) division: Mining of coal and lignite (SIC 05). The factor used for apportioning net capital stocks and consumption of fixed capital was the proportional annual relationship between Scotland and UK other mining and quarrying (SIC 05) intermediate consumption at purchasers' prices.

For the asset valuation of fossil fuels an asset life of 25 years has been assumed. Asset valuation utilises annual projected UK oil and gas production from the OGA until 2035. Then, following OGA methodology, assumes a further 5% production decline per year (for all years following 2035) to be able to project over the full 25-year asset lifetime. UK production projections are apportioned for Scotland based upon the last five years of Scottish contribution to UK production. To estimate valuations in future years annual five-year averages of “unit resource rent” (average resource rent divided by average production) are applied to production projections.

As with all services, the methods used will be reviewed for future updates.

Renewable generation

Energy generated by renewable sources is published in the Scottish Government Energy Statistics Database.

Monetary estimates are based on the “residual value” resource rent approach calculated from the SIC Group 35.1: Electric power generation, transmission, and distribution. UK capital stocks data are apportioned for Scotland based on relative installed capacity. These data are then apportioned using turnover from the ONS Annual Business Survey (ABS) to derive the resource rent of 35.11: Production of electricity. To estimate the renewable provisioning valuation, data were further apportioned using renewables proportion of total energy generation.

Carbon sequestration

Estimates relate to the removal of carbon dioxide equivalent (CO2e) from the atmosphere by habitats in Scotland. However, because of a lack of data we are unable to include the marine habitat, including those intertidal areas such as saltmarsh. Furthermore, peatlands are only partially covered. The UK Centre for Ecology and Hydrology estimates that damaged peatland in Scotland emitted 9.3 million tonnes of CO2 equivalent. This nearly completely negated the gross terrestrial sequestration of Scotland reported in the Greenhouse Gas Inventory (GGI).

The carbon sequestration data come from the UK National Atmospheric Emission Inventory (NAEI), which reports current and future projections of carbon removal for the land use, land use change and forestry (LULUCF) sector.

The LULUCF sector breakdown identifies net carbon sequestration activities in the following subcategories:

  • forest land remaining forest land
  • land converted to forest land
  • grassland remaining grassland
  • land converted to grassland
  • cropland remaining cropland
  • land converted to cropland
  • wetlands remaining wetlands
  • land converted to wetlands

For the years 1990 to 2017, estimates of Scottish carbon sequestration are sourced from the Greenhouse Gas Inventory. In the asset valuation, projections of carbon sequestration are provided for the years 2017 to 2050 using the central values. This is produced by the National Atmospheric Emission Inventory (NAEI) in the LULUCF emission projections. For years used in the projections beyond 2050, the carbon sequestration rate is assumed to be constant as at 2050 levels.

To work out the annual value, we multiply the physical flow by the carbon price. The carbon price used in calculations is based on the projected non-traded price of carbon schedule. This is contained within the Data table 3 of the Green Book supplementary guidance. Carbon prices are available from 2010 to 2100. Prices beyond 2100 are constant at 2100 levels.

The non-traded carbon prices are used in appraising policies influencing emissions in sectors not covered by the EU Emissions Trading System (ETS) (the non-traded sector). This is based on estimates of the marginal abatement cost (MAC) required to meet a specific emission reduction target. Beyond 2030, with the (expected) development of a more comprehensive global carbon market, the traded and non-traded prices of carbon are assumed to converge into a single traded price of carbon.

Air pollution removal by vegetation

Air quality regulation estimates have been supplied in consultation with the UK Centre for Ecology and Hydrology (UKCEH). A very brief overview of the methodology will be explained here. A more detailed explanation can be found in the full methodology report published in July 2017.

Calculation of the physical flow account uses the European Monitoring and Evaluation Program Unified Model for the UK (EMEP4UK) atmospheric chemistry and transport model, which generates pollutant concentrations directly from emissions and dynamically calculates pollutant transport and deposition, considering meteorology and pollutant interactions.

Air pollution data removal by Scottish vegetation has been modelled for the years 2007, 2011, 2015 and then scaled to create values in 2030. Between these years a linear interpolation has been used and adjusted for real pollution levels as an estimation of air pollution removal.

The health benefits were calculated from the change in pollutant exposure from the EMEP4UK scenario comparisons, that is, the change in pollutant concentration to which people are exposed. Damage costs per unit exposure were then applied to the benefiting population at the local authority level for a range of avoided health outcomes:

  • respiratory hospital admissions
  • cardiovascular hospital admissions
  • loss of life years (long-term exposure effects from PM2.5 and nitrogen dioxide (NO2))
  • deaths (short-term exposure effects from ozone (O3))

The damage costs were updated in February 2019. For a method of how the damage costs are calculated (PDF, 1.01MB) please see the report published by Defra.

Future flow projections used for asset valuation incorporate an average population growth rate and an assumed 2% increase in income per year (declining to 1.5% increase after 30 years and 1% after 75 years). Income elasticity is assumed to be one. Annual forecasts are discounted to 2018 present values using a 3.5% discount rate, reducing appropriately as per the Green Book methodology. More work is being conducted in this area.

Noise mitigation by vegetation

Please see the full methodology report published by Defra.

Urban cooling

A brief overview of the methodology of urban cooling will be provided here but for more detailed description please see Eftec and others (2018). To calculate the physical flow of local climate regulation services for the urban blue and green space assets, Eftec and others (2018) calculated the proportional impact on city-level temperatures caused by the urban cooling effect of blue and green space features and their buffers using the cooling values from various sources.

The monetary account measures the value of the cooling effect in pounds. The cooling effect is monetised through the estimated cost savings from air conditioning and the benefit from improved labour productivity. The benefit from improved labour productivity makes up most of the value, with avoided air conditioning energy costs only accounting for a small fraction.

This is assessed by non-financial business sectors, based on averaging temperature mitigation across urban areas, and applying temperature-output loss functions to estimate the gross value added (GVA) that would have been lost because of heat in the absence of the cooling effect, accounting for adaptation behaviours.

These adaptation behaviours consider the averted loss of labour productivity from air conditioning and behaviour change. A 40% reduction is applied to the estimated additional avoided productivity loss from urban cooling to more labour-intensive or non-office based sectors. For example, mining and utilities, and manufacturing are reduced at 40%. An 85% reduction is applied for less labour-intensive or office-based sectors for averted losses because of air conditioning (for example, information and communication; real estate activities).

These estimates represent exchange values as they are based on avoided losses in economic output and expenditure. Welfare values would be included if the valuation covered the non-market benefits to the public of urban cooling, for example, the value of tree shading. In principle, some of these non-market benefits may be captured within the recreational account, to the extent that the cooling and shading features of green and blue space generate more recreational visits to such sites on hot days.

Additionally, avoided air conditioning energy costs are based on estimates in London and extrapolated to other city regions. To extrapolate to other city regions, data on the relative air-conditioned office space and percentage green space in other regions are used. This figure is more tentative. The value of the service will fluctuate year to year reflecting the number of hot days (defined as over 28 degrees Celsius) experienced.

The monetary account of the future provision of the ecosystem service, or future benefit stream, accounts for the benefits received over a specified time period, in this case 100 years. The account incorporates a projection for an annual increase in working day productivity losses because of climate change, which increases the value of urban cooling over time. The assessment of future climate impact relies on broad estimation of the number and degree of hot days in future across Great Britain.

As well as including climate change impacts, an annual uplift is applied to the monetary values to account for year-on-year increases in gross value added (GVA) over the 100-year assessment period. For the first 30 years this uplift is 2% annually, decreasing to 1.5% for years 31 to 75, and 1% for years 76 to 100.

Further work is needed to measure this ecosystem more accurately, for example, adoption of a more granular, bottom-up approach to physical account modelling. For a full list of all the recommendations to update this service please see Eftec and others (2018).


The recreation estimates are adapted from the “simple travel cost” method developed by Ricardo-AEA in the methodological report Reviewing cultural services valuation methodology for inclusion in aggregate UK natural capital estimate. This method was originally created for use on the Monitor of Engagement with the Natural Environment (MENE) Survey, which covers recreational visits by respondents in England.

The method looks at the expenditure incurred to travel to the natural environment and some expenditure incurred during the visit. This expenditure method considers the market goods consumed as part of making the recreational visit (that is, fuel, public transport costs, admission charges and parking fees). This expenditure is currently assumed as a proxy for a marginal price for accessing the site.

Estimates for the cultural service of outdoor recreation in this publication use respondent data from two surveys in Scotland. The questions used from these surveys can be broadly summarised as:

  • How many visits to the outdoors for leisure and recreation have you made in the last four weeks?
  • On the last visit to the outdoors, what type of habitat did you go to?
  • What was the main means of transport used on this last visit?
  • How far did you travel to get to and from the main destination of this visit?
  • How long was the visit, in terms of time (including travel time)?
  • How much did you spend on [spending category]?

From 2003 to 2012, data from the Scottish Recreation Survey (ScRS) were used. The ScRS was undertaken through the inclusion of a series of questions in every monthly wave of the TNS Omnibus Survey, the Scottish Opinion Survey (SOS). In every month of the Scottish Opinion Survey around 1,000 face-to-face interviews are undertaken with adults in Scotland aged 16 years and over.

Replacing the ScRS, Scottish Natural Heritage commissioned the Scotland’s People and Nature Survey (SPANS) for the first time in 2013 to 2014, then again in 2017 to 2018. Unlike ScRS, SPANS excludes questions relating to respondent expenditure during their last outdoor recreation visit. To produce estimates of Scottish outdoor recreation expenditure beyond 2012 we created a statistical model. Using comparable Monitor of Engagement with the Natural Environment (MENE) from Natural England and ScRS data, this model examined the relationship between English and Scottish per visit expenditure on a habitat basis. Linear interpolation was used to produce estimates of Scottish recreation from 2014 to 2016.

Habitat disaggregated estimations of expenditure and time spent may not sum to overall time spent. This is because habitat estimates may be based upon a different sample – those answering a question on habitats visited.

Table 12: Scottish recreation broad habitat classifications
Broad habitat Scotland survey habitats
Built up areas and gardens Village
Built up areas and gardens Local Park or open space
Built up areas and gardens Towns
Built up areas and gardens Golf course/football stadium
Built up areas and gardens Local urban
Built up areas and gardens Local area
Built up areas and gardens City
Built up areas and gardens Country lanes
Built up areas and gardens Castle/historical building
Built up areas and gardens Garden/gardening
Built up areas and gardens Local show/festival
Built up areas and gardens Leisure/sports centre
Built up areas and gardens Streets/roads
Coastal margins Sea/Sea loch
Coastal margins Beach/Cliff
Coastal margins Beach
Coastal margins Cliff
Coastal margins Wildlife area
Woodland Woodland/forest - managed by Forestry Commission/Forest Enterprise
Woodland Woodland/forest - other type of owner
Woodland Woodland/forest - do not know owner
Woodland Wildlife area
Farmland Farmland - fields with crops
Farmland Farmland - fields with livestock
Farmland Farmland - mixed crops and livestock
Farmland Wildlife area
Farmland Farmland unspecified
Farmland Country/countryside
Mountain, moorland and hill Mountain/moorland
Mountain, moorland and hill Mountain/hill
Mountain, moorland and hill Moorland
Mountain, moorland and hill Wildlife area
Freshwater Loch
Freshwater River/Canal
Freshwater River
Freshwater Canal
Freshwater Wildlife area
Freshwater Reservoir
Other Others
Other None of these
Other Do not Know/Not Stated

Source: Office for National Statistics, Scottish Recreation Survey, Scottish People and Nature Survey

For the asset valuation of outdoor recreation, projected population growth calculated from ONS population statistics and an income uplift assumption, were implemented into the estimation. The income uplift assumptions are 1%, declining to 0.75% after 30 years and 0.5% after a further 45 years. These assumptions project the annual value to increase over the 100 years.

It is acknowledged that the expenditure-based method provides an underestimation of the value provided by visits to the natural environment. Primarily, this is because there are several benefits that are not accounted for including scientific and educational interactions, health benefits and aesthetic interactions. Currently, there is no method in use that incorporates these considerations. Additionally, the time spent by people in the natural environment is not itself directly valued because of the accounting and methodological challenges involved.

A considerable number of outdoor recreation visits have no expenditure as people take local visits, such as walking to a local park. The value of local recreation and the aesthetic benefit from living near green and blue spaces is estimated through house prices.

Recreation and aesthetic value in house prices

There is a detailed methodology note on how the recreation and aesthetic value in house prices was produced for the UK accounts, please see this 2019 House Pricing Methodology paper. There are two significant differences for consideration for Scotland.

First, we were unable to include data on Scottish schools as Education Scotland only inspect a sample of schools and educational establishments are not given an overall inspection outcome in the same way that Ofsted and Estyn provide. Since there is a strong correlation between house prices and proximity to school, this lack of data will reduce the precision of the Scottish model. Future work might hope to use alternative data sources on the quality of Scottish schools.

Second, it is possible that our sample of urban property prices are underestimates of actual urban property prices in Scotland. We source property price data from Zoopla, which uses advertised price rather than the selling price. However, Scottish properties are marketed with either a fixed price or “offers over” – the minimum offer accepted by the seller. As bidding for “offers over” houses can drive up the selling price of properties, our data on advertised prices could underestimate the selling price.



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