1.1.1 This TAG Unit provides guidance on assessing the impact of transport options on local air quality. Air quality became a prominent issue in the 1990s, primarily because of concerns relating to human health. In recent decades in the UK, transport atmospheric emissions, on a national basis, have grown to match or exceed other sources in respect of many pollutants, particularly in urban areas. Emissions from transportation sources result from various kinds of combustion processes and include:

oxides of nitrogen (NO_x);
fine particulate matter such as PM₁₀;
carbon monoxide (CO); and
volatile organic compounds (VOCs) such as benzene and 1,3-butadiene.

1.1.2 The Air Quality Strategy (AQS) for England, Scotland, Wales and Northern Ireland (DETR, 2000) set objectives for eight key air pollutants to protect health with achievement dates between 2003 and 2008. In 2000/01, the objectives for three of the pollutants were reviewed with more stringent targets being set and an objective for a ninth pollutant was introduced (Defra, 2003). It is expected that achieving objectives for ambient concentrations of NO₂ and PM₁₀ will be more challenging than for the other pollutants. The AQS objectives for PM₁₀ and NO₂ are shown below. The 2004 objectives for PM₁₀, the 2010 PM₁₀ objectives for Scotland and the NO₂ objectives have been incorporated into The Air Quality Regulations. The AQS objectives are equivalent to or more stringent than the mandatory EU limit values so achieving the objectives will ensure that the limit values are achieved.

Table 1: Air Quality Strategy Objectives for PM₁₀

Location	Concentration	Averaging period	Date to be achieved by
UK	50 µg/m³ not to be exceeded more than 35 times a year	24-hour mean	31 Dec 2004
UK	40 µg/m³	Annual mean	31 Dec 2004
England (excluding London), Wales and N. Ireland	50 µg/m³ not to be exceeded more than 7 times a year	24-hour mean	31 Dec 2010
England (excluding London), Wales and N. Ireland	20 µg/m³	Annual mean	31 Dec 2010
London	50 µg/m³ not to be exceeded more than 10 times a year	24-hour mean	31 Dec 2010
London	23 µg/m³	Annual mean	31 Dec 2010
Scotland	50 µg/m³ not to be exceeded more than 7 times a year	24-hour mean	31 Dec 2010
Scotland	18 µg/m³	Annual mean	31 Dec 2010

Table 2: Air Quality Strategy Objectives for NO₂

Concentration	Averaging period	Date to be achieved by
40 µg/m³	Annual mean	31 December 2005
200 µg/m³ not to be exceeded more than 18 times a year	1-hour mean	31 December 2005

The AQS will be the subject of regular reviews in the future and this may have a bearing on this appraisal guidance.

1.1.3 Road transport, which is a significant source of PM₁₀ and NO₂, is one of the major sources of local air pollution, especially in our towns and cities. In urban areas, emissions from road traffic (e.g. cars, buses, lorries etc.), combined with occasions of poor atmospheric dispersion, can make a significant contribution to pollutant concentrations. Concentrations of these two pollutants are at risk of exceeding the objectives near major roads so the Local Air Quality sub-objective focuses on these two pollutants.

1.1.4 The approach to assessing local air quality is based on:

at plan level, a quantification of the change in exposure at properties in the opening year (or 2005 if the option would be operational at this time); and
at a strategic level, identifying the change in total emissions from an option in the opening year (or 2005 if the option would be operational at this time) and relating it to the population within the area.

1.1.5 more widespread effects from transport emissions can occur, these are discussed in section 1.6 and should be assessed according to guidance in Regional Air Pollution (TAG Unit 3.3.4) if this is likely to be an issue. Carbon dioxide, which does not affect local or regional air quality, is discussed in the Greenhouse Gases Sub-Objective (TAG Unit 3.3.5).

1.1.6 The approach to assessing the Social and Distributional Impacts of changes in air quality resulting from transport interventions is described in Section 3 of this TAG Unit. The assessment should build upon the analyses of Nitrogen Dioxides (NO₂) and particulate matter (PM₁₀) that are described in detail in this section of this Unit.

1.2 Overall Approach

1.2.1 The principal effects of plans and strategies on air quality will arise from the extent to which they affect road traffic, the main source of transport-related local air quality pollutants. Consequently, the guidance on appraising local air quality impacts focuses on effects arising from changes in road traffic.

1.2.2 A high density of well-used road links within a relatively small area can lead to occasional episodes of high pollution. Impacts on this scale might be termed sub-regional or local. The UK Government introduced the system of local air quality management (LAQM) through the Environment Act 1995 in order to tackle air pollution 'hotspots'. Under this system, local authorities are required to undertake reviews and assessments of their local air quality and to designate Air Quality Management Areas, where the objectives that have been incorporated into Regulations, are unlikely to be achieved. The Government has issued LAQM guidance under section 88(1) of the 1995 Act to all authorities to assist with their statutory duties. The guidance (Defra, 2003) is amended and updated from time to time. The LAQM guidance is split into two parts to cover policy and technical issues.

Local Air Quality management: Policy Guidance LAQM.PG(09)
This sets out the statutory background and the legislative framework within which local authorities have to work, how local authorities should handle the designation of Air Quality Management Areas and the preparation of action plans, recommendations and suggestions on taking forward the development of local and regional air quality strategies, local transport measures that authorities might wish to consider and the general principles behind air quality and land-use planning.
Local Air Quality management: Technical Guidance LAQM.TG(09)
This sets out the general approach to be used for the assessment, together with detailed technical guidance, on a pollutant by pollutant basis. It includes guidance on monitoring, estimating emissions and the selection and use of dispersion models.

1.3 Approach to be Adopted for the Studies

1.3.1 There are a variety of accepted methods and models available for the assessment of air quality from transport that could be used. The approach set out below is based on the methods described in the Design manual for Roads and Bridges (DMRB) as this information is readily available. At the plan level, it is likely that there will be a spatially detailed transport model which will provide output to enable the appraisal of local air quality impacts to be undertaken. However, at the strategic level, options may be assessed using a spatially coarse transport model, the output of which will generally not enable local air quality impacts to be appraised as the precise location of each transport route will not be known, however, an assessment can still be made of the change in emissions and related to the population within the area.

1.3.2 Due to the uncertainty in traffic forecasting and the size of traffic flow change needed to affect air quality, options which change traffic flows by less than 10% can usually be scoped out, unless the road is a motorway (due to the high traffic flows) or there are particular sensitivities (e.g. traffic congestion, change to the speed limit or the presence of an Air Quality Management Area).

1.4 Methodology for Plans

1.4.1 At the plan level, individual link data is likely to be available. Therefore the aim at this level is to quantify the change in exposure at properties in the opening year (or 2005 if the option would be operational at this time) as a result of each option. The quantification needs to take account of all significant changes in exposure, whether on the existing or new routes, or elsewhere on the local network.

1.4.2 If the project is within one or more AQMA and Action Plans are proposed or exist, it is particularly important to understand the consequences of the option. Analysts are reminded of the need to consider not just changes in traffic flow but also changes in traffic composition and operating conditions (perhaps as a result of traffic management projects). Potential traffic management measures can be found at Annex 3 in "The Role of the HA in Local Air Quality management".

Step 1

1.4.3 In the first step, pollutant concentrations for the appropriate assessment years for the routes affected as discussed in 1.3.2, for both the do-minimum and do-something scenarios should be calculated. The calculation of pollutant concentrations is to be carried out using DMRB 11.3.1 air quality screening method.

Step 2

1.4.4 The second step is to quantify the exposure to this general change. The most readily available information, which will have already been used in the normal assessment approach, is the property count. However, properties should be banded to take account of the diminishing effects of pollution over distance. This assessment will produce a value that will define the magnitude of exposure due to the addition, or removal, of pollution from a specific number of properties. The method takes account of all significant changes in exposure, whether on existing or new routes, or elsewhere on the local network. A negative value will indicate that there is reduced exposure and therefore a general improvement in air quality, due to an option. A positive value will indicate an increase in exposure and therefore a general detrimental effect upon air quality due to an option. A qualitative comment will provide an indicator as to whether the option will cause an Air Quality Strategy objective to be exceeded or whether an exceedence has been removed.

The Calculations

1.4.5 The requirement to produce the quantified results for the worksheets below can be carried out in two ways. Either the TAG LAQ Excel spreadsheet can be completed, which is recommended as an easy to use approach, particularly as the summary tables in the spreadsheet collate the information for each route to produce the entries required for the Appraisal Summary Table. Alternatively, a separate spreadsheet/alternative means can be devised if preferred. The latter may be a preferred option for more complex assessments, but in this case, the ability to show the input data and results for individual routes will still be required (see the spreadsheet for an example of this).

1.4.6 The following steps can be taken to produce the quantified results, using the TAG LAQ Excel spreadsheet, facilitating the entry of all routes and the summary tables:

For each affected route, the properties should be "banded", and the number of properties within each band recorded for the scheme and do-minimum scenarios. The splits which the bands define closely relate to the diminishing contribution that vehicle emissions make to local air quality over distance. The bands are defined as:

Road centre to 50m from road centre
50m - 100m from road centre
100m - 150m from road centre
150m - 200m from road centre

Beyond 200 m, the contribution of vehicle emissions from the road centre to local pollution levels is not significant.
An assessment of annual mean concentrations of NO₂ and P₁₀ within each of these bands for all affected routes, is to be made using the method described in DMRB 11.3.1. Concentrations should be determined at 20 m, 70 m, 115 m and 175 m from the road centre to represent average concentrations within each band. If concentrations at 20 m are not representative of average concentrations encountered at properties within the first band due to the road occupying a large proportion of this band, then concentrations at a more representative distance should be used. If a new route is being assessed, the concentrations with the do-minimum should be taken to be the same as the background level. This assessment should be carried out for the opening year (or 2005 if the option would be operational at this time), for both the do-minimum and do-something scenarios. Affected routes are defined as the existing route, the new route (if the proposal provides one), and any other local routes on which traffic flow changes are considered to be significant.
In most cases, the same number of properties will be entered for the do-minimum and do-something scenarios. However, there may be a change where the area occupied by the carriageway changes, due to properties being demolished or the road centreline moving.
For each affected route for the do-minimum and do-something scenarios, the following values are to be calculated:

(pollutant concentration at fixed location within band) x (number of properties within that band)

This should be carried out for each of the four bands and the results added together to give a total for each scenario. The do-minimum value should be deducted from the do-something value for each affected route. A positive value should be assigned where an increase in concentration has been identified due to the proposal, and a negative value for a decrease in concentration.
The TAG LAQ Excel spreadsheet will carry out much of these calculations. Property counts and estimated concentrations should be entered into the pink cells in the spreadsheet. The spreadsheet will then calculate the change in concentrations for each route and will sum the changes for each of the routes to give the Overall Assessment Score which is described below. The spreadsheet is currently set up for five routes but any number of additional routes can be added by pressing the "add route" button. It is best to add any additional routes before any of the cells are filled in, otherwise the additional route cells will contain the entries for route 1, however, the entries in these new cells can be easily modified. Once a route has been added to the spreadsheet, it should not be deleted, as this would invalidate the summary table. If additional routes are added, the blue line below route five can then be dragged down below the final route. This will bring the colour back to all of the added route tables. After this procedure, if page dividing lines are lying over particular routes, they can simply be dragged between route tables, which will aid printing.

Quantitative Column

1.4.7 The entries in the quantitative column of the AST should show the numbers of properties where:

air quality would be improved (negative values); and
air quality would be made worse (positive values).

1.4.8 The number of properties affected in each group should be calculated by summing the number affected in the do-something scenario over all the affected routes in that group. The summary table at the top of the spreadsheet calculates these results by counting the number of properties with an improvement, deterioration or no change. If a property is demolished as part of the scheme, that property is counted as having an improvement whereas any property constructed as part of the scheme is counted as having a deterioration. If a property is within 200 m of two routes that are included in the assessment, then it would be counted twice in the number of properties affected in the spreadsheet. However, the number of affected properties should be adjusted manually for any multi-counted properties before entering into the AST.

Overall Assessment Score

1.4.9 The entries for the assessment column can be determined by aggregating the change in exposure score across all affected routes, separately for each pollutant. This can be taken directly from the summary table at the top of the spreadsheet.

Qualitative comment

1.4.10 A qualitative comment may be provided to support the above assessments. If any properties are demolished or constructed as part of the scheme, then this should be noted here. If the Air Quality Strategy objective is predicted to be exceeded or an exceedance is removed due to the option, then this should be noted here also. In particular, a qualitative comment must be provided if the proposals affect air quality within an Air Quality Management Area and state what the effect is, or if either of the following situations apply:

The proposal leads to an increase in annual mean PM₁₀ levels at 20 m from the road centre of at least 1 µg/m³;
The proposal leads to an increase in annual mean NO₂ levels at 20 m from the road centre of at least 2 µg/m³ and where concentrations are above the AQS NO₂ objective of 40 µg/m³.

1.5 Methodology for Strategies

1.5.1 At the strategic level, a study may initially involve output from a spatially coarse transport model. Output from this type of model, which can be used in the assessment of emissions, includes:

changes in speed by mode by model zone/study area (as defined in the transport model); and
changes in passenger car unit/vehicle kilometres travelled by mode by model zone/study area (as defined in the transport model).

1.5.2 This data, in conjunction with appropriate emission factors (see below), can be used to estimate the likely total emissions from a study area, or each model zone within it, resulting from a strategy option. This approach may lead to some anomalies in that the relationship between emissions and exposure to air pollution is not always direct and linear, but in most cases will allow a fair comparison between alternative modes or projects.

1.5.3 Changes in total emissions can be used as a surrogate or proxy for micro scale air quality impacts. Generally, reductions in total emissions in an area are likely to result in improved air quality, although to what extent will not be clear from an understanding of emissions alone. It is the change in personal exposure to air pollutants that is the key factor in understanding potential health effects. A reduction in total emissions may not in all cases lead to a reduction in the population's exposure to air pollution. For example, options which result in more people living and walking near busy road links may result in adverse effects due to greater exposure to air pollutants, even though emissions would reduce overall. These effects are on the micro-scale and, for those studies that are undertaken at a spatially coarse level of assessment, cannot be quantified reliably.

1.5.4 Ideally, in appraising options at the strategy level, one would want to include some consideration of the population exposed to changes in air pollution. While the use of population data works well for assessing noise, relating population densities to changes in emissions is not a valid approach for assessing local air quality impacts at the strategic level and, in fact, may be misleading. The population exposed to a level of emissions does not give an indication as to whether air quality standards are exceeded and therefore whether human health is affected to any significant degree. Emissions of air pollutants can undergo physical and chemical transformation in the atmosphere. Hence, emissions do not always equate directly with the resulting ambient concentrations affecting a population. An understanding of changes in ambient air quality in relation to air quality standards at specific receptor sites and effects on population can only be accurately determined where specific link traffic flows and speeds are available, as in the method for Plans. For this reason the swathe of exposure approach used in the noise methodology has not been translated into the assessment of local air quality impacts.

1.5.5 However, it is important that account is taken of both the magnitude of changes in emissions and where these emissions occur. For example, strategies that switch emissions from town centres to rural areas may result in less people being exposed to pollution. Zones within transport models will usually be of differing sizes. Study areas will also differ in size. Therefore, total emissions should be expressed in terms of emission per unit area (e.g. tonnes per km² per year). In view of this, the indicator selected for the appraisal of local air quality impacts is the total emission rate per unit area multiplied by a population density for the same unit area.

1.5.6 This approach allows two options that may yield the same benefits across the study area, in terms of the change in tonnes of emissions, to be differentiated if one tends to favour emissions savings in populated areas. Populations within these zones can be estimated from population databases (e.g. Ordnance Survey Codepoint or Addresspoint).

1.5.7 The concept of an "emissions exposure estimate" should be used. The steps to calculate this are outlined in the Calculation Sheets and Worksheet 2 provided at the end of this TAG Unit. In summary they involve the following steps:

i) calculate the total emissions (tonnes per year), for each zone, for NO_x and PM₁₀;

ii) estimate the total population per zone;

iii) for each zone, multiply i) by ii) and divide the result by the area of the zone, expressed in km²;

The three steps above should be carried out for the base year and opening year do-minimum scenario and for the opening year do-something scenario. If the option would be operational in 2005, then the calculations should be carried out for this year instead of the opening year.

iv) for each zone, subtract the value in iii) for the strategy from each of the do-minima (i.e. the strategy minus the base year do-minimum and the strategy minus the future do-minimum);

v) count the number of positive values in iv) - these are zones in which the strategy is unlikely to improve air quality over the do-minimum;

vi) count the number of negative values in iv) - these are zones in which the strategy is likely to improve air quality over the do-minimum;

vii) sum the values in iv) over all zones to create the emissions estimate (do this for NO_x and PM₁₀ separately and for the strategy compared to both the present and future do-minima).

1.5.8 The estimation of total emissions on the basis of vehicle kilometres, speed and emission factors can lead to inaccuracies of which the analyst should be aware. However, small differences in totals should not be given undue weight in the decision making process. Some of the reasons for potential errors are given below and the degree to which any particular study might be prone to them should be borne in mind when considering the outputs of any calculations.

The distribution of speeds about the mean is important in determining total emissions. The relationship of vehicle speed to emission rate per kilometre is not linear and varies with pollutant. A series of transport strategies may well change the distribution of speeds about an un-changing mean. These effects would not be evident if a single mean speed was used.
The distribution of traffic in relation to populations may be affected by a transport strategy. Without examining micro-scale effects this effect may not be picked up at the strategic level.
The mix of vehicle types is often crucial in determining the overall emissions of individual pollutants. The level of emission control in the vehicle fleet is important, as is the split in fuel between diesel and petrol.

1.5.9 DMRB 11.3 contains a simple method that allows total emissions to be estimated and this should be used for assessing strategic options. The calculation method is available as an Excel spreadsheet and can be downloaded from the Highways Agency website together with guidance on how to operate the spreadsheet contained that is contained in DMRB 11.3.1. Emissions can be calculated using the "regional" worksheets. The following input data is required to run the spreadsheet:

the number of vehicle kilometres travelled;
the year of assessment;
average vehicle speed;
the proportion of heavy duty vehicles; and
road type (used to define vehicle fleet composition)

1.5.10 The number of vehicle kilometres travelled should be entered by input to the traffic flow and link length cells to give the required distance travelled.

1.5.11 The predictions of emissions will be more accurate the more disaggregated the traffic flow data is in terms of modes (car, light duty vehicle, rigid HGV, articulated HGV and coaches/buses). If detailed information on the vehicle fleet composition across the study area or on distance travelled by road type is not available, the road type should be entered as A in the spreadsheet to represent motorways and A-roads, as these will carry the bulk of the traffic. Grossly aggregated data can lead to significant errors and expert opinion may be required in order to determine the validity of any conclusions drawn from numerical differences in calculated emissions.

Quantitative column

1.5.12 The entries in the quantitative column of the AST should show the numbers of zones considered winners and losers - each of these numbers should be provided for NO_x and PM₁₀. These numbers are calculated in steps v) and vi) in the procedure outlined above.

Overall Assessment score

1.5.13 The entry in the Overall Assessment column of the AST should be the emissions estimate for each strategy compared to the present and future do-minima. These are the results obtained at step vii) in the procedure outlined above.

Qualitative comment

1.5.14 Reductions in emissions (i.e. negative local air quality indices) arising from a strategy are then seen as 'beneficial' and the more negative the value the greater the relative benefit of the strategy. Conversely, increases in emissions (positive local air quality indices) should be taken as an 'adverse' effect and no change as neutral. This information should be recorded as a qualitative entry in the AST along with an indication of the key drivers which are responsible for any change in conditions. Any uncertainties involved in the calculation of emissions should also be identified in the qualitative column.

1.5.15 Calculation Sheets A and B and Worksheet 2 are provided to assist in developing the information to be input to the AST. Once the calculation sheets are completed, the data within them can also be presented graphically in the form of geographical-colour coded maps, a distribution graph (e.g. a bar chart) or other means, depending on the data and the number of zones.

1.6 Regional Air Pollution

1.6.1 Transport can also have air pollution impacts over larger areas than those which are described in this guidance as being local. most notably, these impacts are:

acidification;
excess nitrogen deposition; and
generation of tropospheric ozone.

1.6.2 In most areas of the country the potential for transport schemes to affect air quality on a regional basis will be limited and so regional air pollution will not normally be part of the decision making process. However, the validity of this statement should be reviewed for each transport scheme. If regional air pollution is likely to be an issue, the methodology presented in Regional Air Quality (TAG Unit 3.3.4) should be used to determine the change in emissions of oxides of nitrogen.

2. Application of TAG to Highway Schemes

This section provides advice on the links between TAG's treatment of the Local Air Quality sub-objective and the advice given in Volume 11 of the Design Manual for Roads and Bridges (DMRB), which deals with the environmental assessment of highway projects.

2.1 Methods and Worksheets

2.1.1 The current version of DMRB (February 2003, section 11.3.1) provides a 'generalised appraisal' method that is a supplement to the estimation of concentrations at specific properties. It focuses on two pollutants nitrogen dioxide (NO₂) and particulate matter (PM₁₀), which are identified as of particular concern with respect to compliance with the Air Quality Strategy objectives (DETR 2000, Defra 2003). The generalised appraisal method is based on GOmmmS local air quality plan level assessment i.e. the forerunner of TAG local air quality plan level assessment. This TAG method for local air quality supersedes the generalised appraisal or GOmmmS assessment in DMRB. The DMRB Excel air quality spreadsheet for the calculation of local and regional impacts should be used to provide data for the TAG assessment.

2.1.2 Worksheet 1a shows the information that should be reported for each route and Worksheet 1b shows the summary table for all routes for this sub-objective.

2.2 DMRB Stages and TAG

2.2.1 At Stage 1 the DMRB assessment will be limited to identifying the number of properties in distance bands within 200m of the existing and planned routes, and estimating locations where changes in flow, speed and congestion are expected. This gives a qualitative input to the TAG worksheet, but the remaining (quantitative) data for PM₁₀ and NO₂ would not be available at Stage 1. A localised air quality assessment will be carried out at DMRB Stage 2 where changes in air quality are expected together with the generalised appraisal method based on this TAG guidance. If the Stage 2 assessment indicates that the objectives are likely to be exceeded, a detailed modelling study would be carried out at Stage 3 in addition to the regional assessment required at Stage 3.

Worksheet 1a: Environment: Local Air Quality - Plan Level
Worksheet 1b: Environment: Local Air Quality - Plan Level Summary Table
Worksheet 1a: Environment: Local Air Quality - Plan Level
Calculation Sheet A for Worksheet 2: Local Air Quality - Strategy Level - NO₂
Calculation Sheet B for Worksheet 2: Local Air Quality - Strategy Level - PM₁₀
Worksheet 2: Environment: Local Air Quality - Strategy Level

Worksheets (as above) (Adobe Acrobat - 23KB)

3. Social and Distributional Impacts of Air Quality

3.1 Introduction

3.1.1 This section provides additional advice on the technical processes to be considered in the assessment of the potential social and distributional impacts of changes in air quality resulting from transport interventions. The analyst should, in addition, make reference to Detailed Guidance on Social and Distributional Impacts of Transport Interventions (TAG Unit 3.17) in undertaking this work.

3.2 Which groups of people are particularly vulnerable to the effects of air quality?

3.2.1 The impacts of air quality are primarily spatial. As poor air quality problems are often experienced in areas of deprivation, in which people already suffer relatively poor health, health problems can be exacerbated for deprived communities. Diabetes sufferers, in particular, have been identified as being at a higher risk of heart disease from increases in transport pollutants. There is evidence of higher rates of Diabetes in lower income groups and amongst certain ethnic groups. We consider, however, that there is not currently enough evidence to conclude that these groups are more prone to heart disease as a result of poor air quality. The evidence base is listed in Section 5 of this TAG Unit.

3.2.2 Evidence also suggests that children are at more risk from air pollution due to the fact that they generally spend more time outside and therefore experience more exposure to harmful pollutants that impact on lung development. Although there is not currently enough evidence to conclude that these groups are more at risk as a result of poor air quality, it is recommended that consideration is given to the changes in air quality that are experienced by children.

3.2.3 Air quality has strong distributional impacts. The poor air quality experienced in some areas of low car ownership is a clear issue of social justice as these people experience the impacts of car use, but do not themselves have access to a car. However it is prudent to concentrate the analysis of changes in air quality on the impacts on households in different income groups.

3.3 Process to be followed

3.3.1 The approach to the assessment of the social and distributional impacts should follow the process described in Detailed Guidance on Social and Distributional Impacts of Transport Interventions (TAG Unit 3.17). In terms of air quality, this follows the following steps:

Step 1: identification of the area impacted by changes in air quality;
Step 2: analysis of the demographic profile in the area impacted by changes in air quality;
Step 3: a screening process, to determine if it is appropriate to undertake further analysis of the changes in air quality and the approach to be taken;
Step 4: the analysis of air quality impacts; and
Step 5: the collation and presentation of the outputs from the air quality analysis.

3.3.2 The process to be followed for Steps 0-3 is described in TAG Unit 3.17.

3.3.3 In the event of air quality impacts being identified from the screening process (Step 3), the sections below should be used to guide the technical analyses required in Steps 4 and 5 of this process.

3.3.4 The following section refers to the full appraisal process. TAG Unit 3.17 also notes that alternative approaches can be taken when impacts are neither significant nor concentrated. These are intended to be more proportionate and are more qualitative than the full appraisal. TAG Unit 3.17 sets out the principles that can be applied.

3.3.5 For both the full appraisal and the more proportionate qualitative appraisal, the promoter should develop a specification for the appraisal and agree this with the Department (or equivalent) before proceeding with the appraisal.

3.3.6 In undertaking a 'Strategy' level appraisal, the limitations of the analytical methodology should be recognised, as noted in Section 1.5. In this case the analyst should develop a more qualitative approach to identifying the potential social and distributional impacts of air quality, and agree this with the Department (or equivalent). In the case of appraisal at the 'Plan' level, described in Section 1.4, it is likely that there will be more detailed data available that will facilitate a full appraisal, although the approach should again be agreed.

3.4 Analysis of Social and Distributional Impacts of Air Quality (Step 4)

3.4.1 The analyst should analyse the air quality impacts of the intervention, in accordance with the guidance described in Sections 1 and 2 of this TAG Unit.

3.4.2 The analyst should then map the outputs from the air quality analysis, ideally using GIS techniques. The approach taken should reflect the scale of the analysis. Where changes are localised to particular areas, it is sufficient to use simple tools, such as EXCEL, to attribute the impacts to specific areas. Where the impacts are widespread and complex, it is recommended that the air quality analysis is integrated into a GIS tool, to enable overlay of the demographic profile data, described below.

3.4.3 The Highways Agency is currently in the process of developing a GIS Tool that automates the calculations required in Volume 11 of the Design Manual for Roads and Bridges (DMRB). Whilst this tool is designed to be used for Highways Agency road schemes, it is not yet available at the time of writing and the analyst should contact the DfT's ITEA division to check its availability, contact details are available in Section 6 of this Unit. This tool could be expanded in future to include emission calculations from other modes, but it is not currently expected to include functionality to address social and distributional impacts. Whilst its outputs can be used in GIS format, further work is required to analyse the potential social and distributional impacts.

3.4.4 This air quality mapping should be overlain with income data to estimate the changes in air quality experienced, at a detailed level, by households in different income groups. TAG Unit 3.17 provides a discussion of the merits of different income datasets.

3.4.5 The review of available evidence has suggested that the key 'potential vulnerable group' in air quality terms are children. Children are not highlighted as a potential vulnerable group within Sections 1 and 2 of this Unit, and some additional analysis will therefore be required to assess changes in air quality in the vicinity of schools. In addition, it is recommended that assessment also takes place for hospitals and care homes for older people, reflecting the impacts of poor air quality on people with poor health.

3.4.6 The analysis of the potential impacts of air quality on children should focus on catchment areas for local schools and on areas in which there are high proportions of children within the general population. The analyst should examine (using GIS) the changes in air quality that are forecast in these areas, and assess the scale of the change in air quality in comparison with the change in air quality experienced by the population as a whole.

3.4.7 A similar approach should be used to assess the impacts of changes in air quality on older people resident in care homes and people in hospitals.

3.5 Outputs from Appraisal of Social and Distributional Impacts (Step 5)

3.5.1 The main outputs produced as a result of the local air quality appraisal process will be a series of analyses that describe the changes in air quality at a disaggregate scale, in most cases at Output Area level. This will then use the socio-demographic data to describe the numbers of people in different social groups experiencing improvements and deterioration in air quality as a result of the intervention.

3.5.2 The analysis of distributional impacts should provide, as an output, the relative numbers of people in different income groups experiencing improved or worse air quality. This will draw on the spatial analysis of socio-demographic data and changes in air quality in the affected area.

3.5.3 It is expected that analysis will be taken at Output Area level, which is described in detail in TAG Unit 3.17. In order to undertake the analysis the following assumptions will be required:

The population is evenly distributed across each Output Area;
The proportions of people in each income group are distributed evenly across each Output Area; and
The proportion of population affected in the Output Area is the same as the proportion of the Output Area covered by the transport corridor.

3.5.4 The table below sets out an example of the resulting analysis for the five quintiles in the income domain of Index of Multiple Deprivation (IMD).

Table 3: Example of Air Quality SDI Analysis

	IMD Income Domain					Total
	Most deprived areas			Least deprived areas
	0-20%	20-40%	40-60%	60-80%	80-100%
No of properties with improved air quality [A]	400	800	200	0	200	1,600
No of properties with no change in air quality [B]	300	400	100	200	200	1,200
No of properties with worse air quality [C]	100	150	150	50	150	600
No. of net winners / losers [D] = [A] - [C]	+300	+650	+50	-50	+50	-
Total number of Winners / Losers across all groups [E] = ∑[D]	-	-	-	-	-	1,000
Net winners/losers in each area as % of total [F] = [D] / [E]	30%	65%	5%	-5%	5%	100%
Share of Total Pop'n of Study Area	22%	25%	15%	28%	10%	100%
Assessment (see para 3.5.7 for details)	✓✓✓	✓✓✓	✓	XXX	✓	✓✓

(Note: identification of numbers of households with better or worse air quality should be based on the analytical approach described in Section 1 of this Unit).

3.5.5 In this illustrative case, there are forecast to be significant beneficial impacts that are experienced, in air quality terms, by the households in the second lowest quintile. The lowest income quintile (which comprises the areas suffering the highest income deprivation) also experiences relatively high benefits in relation to its total share of the population. In contrast, other areas experience only a small share of the benefits in comparison with their total share of the population. The second highest income quintile experiences a reduction in air quality, despite an overall improvement for the population as a whole. This group therefore experiences both absolute and relative disbenefits, and it is appropriate to give this group a score of 'large adverse'.

3.5.6 The table below presents the approach to the grading of Air Quality SDIs.

Table 4: System for Grading of Air Quality SDIs for each of the social groups

Consideration of each IMD group		Assessment
Overall air quality impact is beneficial, and the impact for the group as a proportion of the total is...	Beneficial (i.e. improved air quality) and significantly greater than the proportion of the group in the total population	Large Beneficial
	Beneficial (i.e. improved air quality) and in line with the proportion of the group in the total population	Moderate Beneficial
	Beneficial (i.e. improved air quality) and smaller than the proportion of the group in the population	Slight Beneficial
	A disbenefit (i.e. worse air quality)	Large Adverse
There are no Air Quality Benefits or Disbenefits experienced by the group		Neutral
Overall air quality impact is adverse, and the impact for the group as a proportion of the total is...	Adverse (i.e. worse air quality) and smaller than the proportion of the population of the group in the total population	Slight Adverse
	Adverse (i.e. worse air quality) and in line with the proportion of the population of the group in the total population	Moderate Adverse
	Adverse (i.e. worse air quality) and significantly greater than the proportion of the population of the group in the total population	Large Adverse
	A benefit (i.e. improved air quality)	Large Beneficial

3.5.7 This system should be applied for each of the five income groups. Using the example in Table 3 above would derive the following scores:

The least deprived quintile has a 10% share of the overall population, but only 5% of the 'net winners' in air quality terms. In this case the proportion of net winners is less than the proportion of the population as a whole, and it is therefore appropriate to give a score of slight beneficial.
The second least deprived quintile has 50 'net losers' in this group, despite an overall improvement in air quality for the population as a whole. This group therefore suffers in both absolute and relative terms, and it is appropriate to apply a score of large adverse.
The most deprived quintile has a 22% share of the population, and 30% of the 'net winners' are in this group. The proportion of net winners is higher than the proportion of the population as a whole, so it is appropriate to give a score of large beneficial.

3.5.8 The scores for each of the groups under consideration should then be reported in the matrix of social and distributional impacts, described in Step 5 of Detailed Guidance on Social and Distributional Impacts of Transport Interventions (TAG Unit 3.17).

3.5.9 A further qualitative statement should be provided if the transport intervention will result in social and distributional impacts on air quality in an Air Quality Management Area (AQMA).

4. Further Information

The following documents provide information that follows on directly from the key topics covered in this Unit.

For information on:	See:	TAG Unit number:
The background and overall approach to the Social and Distributional Impacts of transport interventions	Detailed Guidance on Social and Distributional Impacts of Transport Interventions	Unit 3.17

5. References

Atkins and MVA (forthcoming) Assessing Social and Distributional Impacts in Transport Scheme Appraisal.

DETR (2000). The Air Quality Strategy for England, Scotland, Wales and Northern Ireland. Working Together for Clean Air. TSO.

Defra (2003). The Air Quality Strategy for England, Scotland, Wales and Northern Ireland: Addendum. Defra.

Defra (2003). Part IV Environment Act 1995. Local Air Quality management. Policy Guidance . LAQM PG(03). Defra.

Defra (2003). Part IV Environment Act 1995. Local Air Quality management. Technical Guidance. LAQM TG (03). Defra.

Highways Agency, Scottish Executive Development Department, Welsh Assembly Government and The Department for Regional Development Northern Ireland. Design Manual for Roads and Bridges (DMRB), Volume 11, Section 3, Part 1 Air Quality (February 2003).
[www.standardsforhighways.co.uk/DMRB/vol11/index.htm]

National Atmospheric Emissions Inventory
[www.naei.org.uk/emissions/index.php]

6. Document Provenance

This Transport Analysis Guidance (TAG) Unit is based on Chapter 4, Section 4 of Guidance on the Methodology for Multi-Modal Studies Volume 2 (DETR, 2000) but has been updated.

Technical queries and comments on this TAG Unit should be referred to:

Integrated Transport Economics and Appraisal (ITEA) Division
Department for Transport
Zone 3/08 Great Minster House
33 Horseferry Road
London SW1P 4DR

Email: itea@dft.gsi.gov.uk
Tel: 020 7944 6176
Fax: 020 7944 2198

Updated: April 2011