alice gurung report jaqu air quality modelling report 2019

JAQU Air Quality Modelling Report

AQ3

December 2020


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Quality information

Prepared by Checked by Verified by Approved by

Alice Gurung

Graduate Air Quality Consultant

Helen Venfield

Principal Air Quality Consultant

Anna Savage

Associate Air Quality Director

Gareth Collins

Regional Director

Revision History

Revision Revision date Details Authorized Name Position

1 June 2019 Working Draft GC Gareth Collins Regional Director

2 September 2019 Updated Working Draft

GC Gareth Collins Regional Director

3 October 2019 Final GC Gareth Collins Regional Director

4 February 2020 Updated with T-IRP comments


5 November 2020 Updated draft for FBC


6 December 2020 Final version for FBC


Distribution List

# Hard Copies PDF Required Association / Company Name

Changes for FBC version highlighted in yellow.


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Prepared for:

Portsmouth City Council and Joint Air Quality Unit (JAQU)

Prepared by:

Alice Gurung

Graduate Air Quality Consultant

T: +44(0)020 043 9340

E: [email protected]

AECOM Infrastructure & Environment UK Limited

Sunley House

4 Bedford Park, Surrey

Croydon CRO 2AP

United Kingdom

T: +44 20 8639 3500

aecom.com

© 2019 AECOM Infrastructure & Environment UK Limited. All Rights Reserved.

This document has been prepared by AECOM Infrastructure & Environment UK Limited (“AECOM”)

for sole use of our client (the “Client”) in accordance with generally accepted consultancy principles,

the budget for fees and the terms of reference agreed between AECOM and the Client. Any

information provided by third parties and referred to herein has not been checked or verified by

AECOM, unless otherwise expressly stated in the document. No third party may rely upon this

document without the prior and express written agreement of AECOM.


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Table of Contents

1. Introduction ................................................................................................................................... 7

2. Atmospheric Dispersion Modelling Approach ............................................................................... 9

2.1 Dispersion Model Selection and Tools ................................................................................ 9

2.2 Assessment Scenarios ....................................................................................................... 9

2.3 Model Input Data ................................................................................................................ 9

2.3.1 Traffic Data ......................................................................................................................... 9

2.3.2 Baseline Emissions Inventory Development (NOx and f-NO2) ........................................... 9

2.3.3 Road Width Data .............................................................................................................. 12

2.3.4 Road Source Emission Rates (NOX and f-NO2) ............................................................... 12

2.4 Gradients, Tunnels, Flyovers and Street Canyon Effects................................................. 12

2.4.1 Road Gradient Effects ...................................................................................................... 12

2.4.2 Street Canyons ................................................................................................................. 13

2.4.3 Flyovers and Tunnels ....................................................................................................... 13

2.5 Surface Roughness and Minimum Monin-Obukhov Length ............................................. 13

2.6 Meteorological Data .......................................................................................................... 13

2.7 Modelled Receptor Selection ............................................................................................ 14

2.8 Model Output Data ........................................................................................................... 14

2.8.1 Base year 2018 and Projected Base Year 2022 ............................................................... 14

2.8.2 Interim and Future Base Year Interpolation ...................................................................... 14

3. Model Verification and Adjustment .............................................................................................. 15

3.1 Comparison of Modelled (Unadjusted) and Monitored Road NOx ................................... 15

3.2 Verification ........................................................................................................................ 15

3.3 Modelled Road NOx Adjustment ...................................................................................... 15

3.4 Model Adjustment Summary ............................................................................................. 17

4. Baseline Results ......................................................................................................................... 18

4.1 Vehicle Fleet ..................................................................................................................... 18

4.2 NO2 concentrations ........................................................................................................... 18

5. Source Apportionment ................................................................................................................ 24

5.1 Road Vs Non-Road Contribution ...................................................................................... 24

5.2 Road Contributions by Vehicle Type ................................................................................. 25

6. Options Modelling ....................................................................................................................... 26

6.1 Shortlisted Options ........................................................................................................... 26

6.2 Option Assumptions .......................................................................................................... 28

6.3 Options Model Results ..................................................................................................... 29

6.3.1 Identification of Benchmark .............................................................................................. 29

6.3.2 Identification of Alternative Package................................................................................. 32

6.3.3 Other options not taken forward ......................................... Error! Bookmark not defined.

7. Limitations and Assumptions ...................................................................................................... 49

7.1 Local Air Quality Model Limitations................................................................................... 49

7.2 Transport Model Limitations ............................................................................................. 50

7.3 Sensitivity tests ................................................................................................................. 50

7.3.1 Change in transport assumptions ..................................................................................... 52

7.3.2 Change in air quality assumptions.................................................................................... 53

Appendix A Model Verification ............................................................................................................... 57

Appendix B Supporting Information ...................................................................................................... 59

Appendix C Quality Assurance of Monitoring Data ............................................................................... 80

QA / QC of automatic monitoring ................................................................................................ 80

QA / QC of diffusion tube monitoring .......................................................................................... 82


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Figures

Figure 2-1 ANPR camera locations ....................................................................................................... 10 Figure 2-2 Comparison of Portsmouth Vehicle Fleet with National Fleet – Car Fuel Split ................... 11 Figure 2-3 Comparison of Portsmouth Vehicle Fleet with National Fleet – Euro Proportions .............. 11 Figure 3-1 - Modelled Road-NOx versus Monitored Road-NOx ........................................................... 16 Figure 3-2 - Adjusted NO2 versus Monitored NO2 Concentrations ....................................................... 16 Figure 4-1: Location of roadside receptor sites with modelled exceedances in 2022 baseline (EFT

v1.9b) .................................................................................................................................................... 20 Figure 6-1: Indicative boundary for Portsea Island CAZ ....................................................................... 27 Figure 6-2: Indicative boundary for Small Area CAZ ............................................................................ 28 Figure 7-1: Wind roses (wind speed/direction) at Thorney Island Met Office site ................................ 53

Tables

Table 2-1: Split of cars by compliant and non-compliant ...................................................................... 12 Table 4-1 Current and predicted vehicle fleet and non-compliance to CAZ emission standards, ........ 18 Table 4-2: Locations with modelled (or near) exceedances in 2022 Baseline ...................................... 21 Table 4-3: Comparison between modelled and observed traffic data, Church Street, 2019 ................ 23 Table 5-1 Percentage Contribution of Road and Non-Road Sources to background NOx in selected

areas of Portsmouth, 2018 .................................................................................................................... 24 Table 5-2: Percentage Contribution of Road and Non-Road Sources to NOx in selected areas of

Portsmouth, 2022 .................................................................................................................................. 25 Table 5-3 Contribution of vehicle type to road NOx emissions on exceedance road links, 2022 Future

Base ...................................................................................................................................................... 25 Table 6-1: Options modelled for 2022 ................................................................................................... 26 Table 6-2: Assumed responses of LGVs and HGVs to a CAZ (based on JAQU data) ......................... 29 Table 6-3: Modelled NO2 concentrations (µg/m3) in 2022 for different options (Based on Emissions

Factor Toolkit, v9.1b) ............................................................................................................................. 33 Table 6-4: Annual mean NO2 concentrations for individual non-charging measures, 2022.................. 35 Table 7-1 HGV response assumptions for the core scenario and sensitivity tests ............................... 52 Table 7-2 Impact of sensitivity tests on modelled NO2 (µg/m3) concentrations in 2022 of the

Alternative Package without Alfred Road signals – change in modelled NO2 (µg/m3) Error! Bookmark

not defined.

Appendix Figures

Figure B- 1 Study Area showing PCM Links and 50m Buffer ............................................................... 59 Figure B- 2 Location of Street Canyons ................................................................................................ 60 Figure B- 3 Location of Flyovers and Bridges ....................................................................................... 61 Figure B- 4 Exceedances of Annual Mean NO2 Limit Value, 2018 ....................................................... 62 Figure B- 5 Monitoring Locations .......................................................................................................... 62 Figure B- 6 Wind Rose, Thorney Island (2018 data) ............................................................................ 63 Figure B- 7 Receptor Locations ............................................................................................................ 64 Figure B- 8 Source Apportionment- Diesel Cars 2018 (L) and 2022 (R) .............................................. 65 Figure B- 9 Source Apportionment- Petrol Cars 2018 (L) and 2022 (R) ............................................... 66 Figure B- 10 Source Apportionment- Full Hybrid Diesel Cars 2018 (L) and 2022 (R) .......................... 67 Figure B- 11 Source Apportionment- Full Hybrid Petrol Cars 2018 (L) and 2022 (R) ........................... 68 Figure B- 12 Source Apportionment- Artic HGVs 2018 (L) and 2022 (R) ............................................. 69 Figure B- 13 Source Apportionment- Rigid HGVs 2018 (L) and 2022 (R) ............................................ 70 Figure B- 14 Source Apportionment- Diesel LGVs 2018 (L) and 2022 (R) ........................................... 71 Figure B- 15 Source Apportionment- Petrol LGVs 2018 (L) and 2022 (R) ........................................... 72 Figure B- 16 Source Apportionment- Buses and Coaches 2018 (L) and 2022 (R) .............................. 73 Figure B- 17 Source Apportionment- Taxis 2018 (L) and 2022 (R) ....................................................... 74 Figure B- 18 Source Apportionment- Motorcycles 2018 (L) and 2022 (R) ........................................... 75


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Appendix Tables

Table A- 1 Monitoring Sites Used in Verification ................................................................................... 57

Table B- 1 Details of automatic monitoring locations ............................................................................ 76 Table B- 2 Details of diffusion tube locations ........................................................................................ 77


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1. Introduction

This report constitutes the ‘Local Plan Air Quality Modelling Report (AQ3)’ and supplements the

information provided in the Local Plan Air Quality Modelling Tracking Table (AQ1) and Local Plan Air

Quality Modelling Methodology Report (AQ2). The documents remain ‘live’ documents and are

updated as required during the course of the various stages of the study.

On 26 July 2017, the government published the UK plan for tackling roadside nitrogen dioxide (NO2)

concentrations (‘the UK Plan’) to bring NO2 concentrations within the European Union (EU)’s statutory

annual limit value of 40 micrograms per cubic metre (µg/m3) in the shortest possible time, focussing

on five key urban areas. The Department for Environment, Food and Rural Affairs and the Department

for Transport’s Joint Air Quality Unit (JAQU) is responsible for overseeing the delivery of the UK Plan,

which includes supporting local authorities and other organisations on the delivery of local measures

in their area.

On 23 March 2018 the government directed 33 additional English local authorities with projected

annual mean NO2 exceedances in the short to medium term to undertake feasibility studies to

establish whether there are measures they can take to reduce NO2 air pollution in their areas in the

shortest possible time.

On 5 October 2018 the government published a supplement to the UK Plan which highlighted that

eight of the directed 33 local authorities had identified more persistent, longer term exceedances than

were initially forecast by the Pollution Climate Mapping (PCM) model. Under the terms of the

Environment Act 1995, the government has issued a Ministerial Direction to this group of local

authorities to develop a Local Plan to identify measures that could bring forward compliance dates

within the shortest possible time. Portsmouth City Council (PCC) is one of these local authorities.

PCC has previously worked with AECOM to undertake an initial targeted feasibility study, submitted to

JAQU in September 2018. This study included local modelling for the two non-compliant links and for

AQMA 6 to identify the main causes and extent of exceedances, as well as to determine the level of

emissions reductions required to achieve compliance, and potential measures that could bring this

forward.

Following this work, AECOM has provided further local air quality modelling support for the Local Plan

study. This work has inputted into target determination to understand the extent of exceedances

across the wider study area and further modelling of a range of measures against a Clean Air Zone

(CAZ) baseline intervention has been conducted. This has identified a preferred package of measures

that will bring forward compliance in the shortest time possible which feeds into the business case for

the Local Plan.

PCC submitted an Outline Business Case (OBC) to JAQU on 31 October 2019, and undertook public

consultation in Summer 2020. This version of the document is part of the Full Business Case (FBC),

submitted December 2020.


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Initial Evidence Submission


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2. Atmospheric Dispersion Modelling Approach

2.1 Dispersion Model Selection and Tools

The dispersion model selected for this study is CERC’s ADMS-Roads v4.1.1, which has been used to

simulate the dispersion of vehicle emissions of NOx from road links included in the model domain.

Annual mean NO2 concentrations were subsequently derived at identified receptor locations through

utilising the outputs of the model (road-NOx) in combination with the following tools published by

Defra1:

Emissions Factors Toolkit (EFT) v9.1.b;

2017 reference year Background Pollutant Maps (for NOx and NO2);

NO2 Adjustment for NOx Sector Removal Tool v7.0; and,

NOx to NO2 Calculator 2017 to 2030 v7.1.

Verification of the air quality model was completed with reference to Defra’s LAQM.TG16 document,

specifically:

Section 4: Dispersion Modelling of Emissions

─ Box 7.14: Initial Comparison of Modelled and Monitored Total NO2 Concentrations

─ Box 7.15: Comparison of Road-NOx Contributions Followed by Adjustment

─ Box 7.16: Importance of an Approach to Verifying Modelled NO2 Concentrations from Road

Traffic

─ Box 7.17: Methods and Formulae for Description of Model Uncertainty

2.2 Assessment Scenarios

The assessment scenarios focused on for the Target Determination submission were:

Base Year 2018 (scenario to be used for air quality model verification);

Projected Base Year 2022 (future baseline ‘without measures’); and,

Interim Base Years 2019, 2020 and 2021 (using interpolation methodology).

The air quality modelling process followed a number of sequential steps to convert the vehicle

emissions from traffic on the modelled road network into annual mean concentrations of NO2. An

overview of each step of the process is provided below.

2.3 Model Input Data

2.3.1 Traffic Data

Traffic data for the 2018 and 2022 baseline scenarios were obtained from the SATURN-based

Southern Regional Transport Model (SRTM) run by Systra. This provided period average flows along

with speeds for the AM peak, inter-peak, PM peak, and off-peak periods with associated link distances

for all PCM and non-PCM links included within the air quality model domain, as depicted in Figure B-1

in Appendix B. These were converted to 24 hourly data for the purpose of the air quality modelling.

The modelled road links were georeferenced prior to input to ADMS-Roads, with each road link

spatially matched to the Intelligent Transport Network (ITN) centre lines, thus ensuring a real-world

representation. Each road link was matched to the respective NOx link-specific emission rate derived

from the EFT using a common reference link.

2.3.2 Baseline Emissions Inventory Development (NOx and f-NO2)

An Automatic Number Plate Recognition (ANPR) camera survey was completed during a week’s

study in March 2019 at a large number of locations across the air quality model domain area (see

Figure 2-1).

1 LAQM tools published by Defra / JAQU specifically in relation to CAZ studies


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Figure 2-1 ANPR camera locations

The raw datasets were sent to the Department for Transport (DfT) via JAQU to match the number

plates against the DVLA database. The returned data of over 8 million vehicle captures were collated

and aggregated to generate a locally representative and domain-wide vehicle fleet composition. This

enabled total vehicle journeys on all modelled links to be proportioned according to characteristics

such as:

Vehicle size and class distributions;

Fuel splits (e.g. petrol, diesel, Liquid Petroleum Gas -LPG, hybrid, electric);

Estimated Euro emission standard based on year of manufacture;

Rigid and articulated Heavy Goods Vehicle (HGV) split; and,

Bus and coach split.

Given the availability of ANPR data, the detailed input option within the EFT was utilised (Alternative

Technology’) in combination with the use of a bespoke ‘simple User Euro’ work tab for the 2018

scenario. Therefore, the local fleet Euro composition relevant to the model domain was represented

within the emissions inventory calculations and outputs.

For the Projected Base Year (2022), Alternative Technology within the EFT was utilised along with the

‘Fleet Projection’ tool tab. ‘Option 1’ of the projection tool was utilised within EFT, which assumed the

future year 2022 Euro fleet composition has the same difference in Euro classes as observed

between the default base year profile and the ANPR data.

Version 9.1b of the EFT incorporates an updated Petrol/Diesel Projection Tool for forecasting the fuel

split of cars – as determined from the ANPR data – to future assessment years. The tool was used

predict the relative proportions of conventional petrol and diesel cars, hybrid cars and electric cars in

2022. Figure 2-2 shows the output of the Petrol/Diesel Projection Tool, comparing the default car fleet

fuel splits for 2019 and 2022 (from the EFT) with the ANPR observed fleet split for 2019 and projected

fleet split for 2022.


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Figure 2-2 Comparison of Portsmouth Vehicle Fleet with National Fleet – Car Fuel Split

A comparison of the Euro standards of main vehicle types identified in Portsmouth from the 2019

ANPR with the national fleet for the same year given in the EFT is shown in Figure 2-3.

Figure 2-3 Comparison of Portsmouth Vehicle Fleet with National Fleet – Euro Proportions

The traffic data provided numbers of cars, LGVs, HGVs and buses for each road link and were further

disaggregated into compliant and non-compliant vehicles. The modelled traffic data did not

distinguish taxis (including London-style black cabs and private hire vehicles) from cars. However,

CAZ B and CAZ C configurations both cover taxis whilst excluding cars. Consequently, the proportion

of taxis relative to cars was extracted from the ANPR survey data and used to calculate the numbers

of taxis in the modelled traffic datasets.

For each modelled scenario, emissions were therefore calculated for compliant and non-compliant

vehicles in separate EFT spreadsheets, as follows:

Compliant cars (excluding taxis), LGVs, HGVs and buses;

Non-compliant cars (excluding taxis), LGVs, HGVs and buses;

Compliant taxis; and

Non-compliant taxis.

Within the compliant EFT spreadsheets, the projected fleet composition as entered on the “Simple

User Euro” worksheet was renormalised based on fuel type into the compliant Euro standard fields

i.e. petrol-fuelled vehicles were renormalised across Euro 4/IV and newer, diesel vehicles of Euro 6/VI

and newer. For the non-compliant EFT spreadsheets, the renormalisation was done across the non-

compliant Euro standards (Euro 3/III and older for petrol; Euro 5/V and older for diesel). The vehicle

fleet assumed in the non-compliant and compliant vehicles was different. This is illustrated in Table

2-1 for the 2022 Projected Base Year for cars.


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Table 2-1: Split of cars by compliant and non-compliant

Category % split by car body and fuel type

Petrol car Diesel car Hackney carriage Alternative fuelled cars

Compliant cars (ex taxis) 74% 19% 0% 7%

Non-compliant cars (ex

taxis)

26% 71% 0% 3%

Compliant taxis 7% 82% 0% 11%

Non-compliant taxis 0% 96% 1% 3%

The outputs from the EFT for each assessment scenario included the following:

Link-specific NOx emissions rates for air quality model input (g/km/s);

Annual NOx emissions total for each link within the modelled road network (kg/annum);

Primary NO2 (f-NO2) emissions fraction for each link and, for the links included in the model, an

average-domain wide f- NO2 fraction; and,

Annual NOx emissions split by vehicle type for source apportionment.

The link-specific emission rates output from each of the four EFT spreadsheets were added together

to form the emissions dataset for input into ADMS-Roads. Annual total pollutant emissions for each

link were aggregated in the same way. For f-NO2, the EFT outputs were combined and emissions-

weighted average f-NO2 values were calculated.

2.3.3 Road Width Data

Road width data for each modelled link were derived based on an automated GIS approach, which

utilised the georeferenced road centreline to link the respective mapped road polygon that each

centreline was within. This identified the road boundaries. Subsequently, GIS was used to draw lines

to the centreline that extended to the road edge. For each link, an average width was calculated

based on lengths of each of these lines.

2.3.4 Road Source Emission Rates (NOX and f-NO2)

The geometry of each road link from the PCM network were entered into ADMS-Roads, including

road width. The link specific NOx emission rates were input into the ADMS-Roads model for all road

links included in the air quality domain.

The link specific f-NO2 outputs from the EFT were reviewed and used within air quality modelling. For

2018, these f-NO2 values ranged from 0.098 to 0.329. For 2022, the f- NO2 values ranged from 0.063

to 0.299.

2.4 Gradients, Tunnels, Flyovers and Street Canyon Effects

2.4.1 Road Gradient Effects

The effects of road gradients on vehicle emissions, particularly heavy duty vehicles (HDVs), should be

represented in the air quality modelling appropriately. OS DTM data was used to calculate road

gradients for all modelled road links within the study area. Gradient effects were calculated and

applied to all road links where the gradient exceeds 2.5%, in accordance with Defra’s LAQM.TG16

methodology and associated information provided by JAQU.

PCC were consulted on the locations of the identified gradients, and it was concluded that gradient

effects only needed to be considered for Portsdown Hill Road, north of the A27/M27. After further

analysis this road was considered to be outside of the study area.


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2.4.2 Street Canyons

With respect to street canyon effects, the road network and detailed OS mapping with address base

and building layer data were used to facilitate use of the ‘Advanced Street Canyon’ module within

ADMS-Roads. Figure B-2 in Appendix B shows an indication of those streets initially identified as

being street canyons, based on TG16 (paragraph 7.408), which states that:

“..Although street canyons can generally be defined as narrow streets where the height of buildings

on both sides of the road is greater than the road width, there are numerous example whereby

broader streets may also be considered as street canyons where buildings result in reduced

dispersion and elevated concentrations (which may be demonstrated by monitoring data).”

Street canyons were identified by measuring the road width (building façade to building façade) and

the heights of the building. Narrow streets where the height of buildings on both sides of the road was

greater than the road width were classed as a street canyon. Google Streetview and Google Earth

were used to measure the road widths and building heights.

A consideration of street canyons close to monitoring sites was made to determine whether it would

be appropriate to apply a separate verification factor to those roads with street canyons. However, as

the model verification factor is already low (1.61), and there are only a few street canyons in the

modelled road network, it was considered that the model was performing well so no further

consideration or modification to the verification was needed.

2.4.3 Flyovers and Tunnels

The locations of bridges and flyovers have been reviewed to identify the relevance of these with

respect to air quality modelling for the PCM links being investigated. Flyovers are represented within

ADMS-Roads by assigning road elevations to the respective links using elevations from OS digital

terrain model (DTM) data. The road elevations in metres are extracted using GIS and are cross-

checked against Google Earth elevation. The source (elevated road) height is determined in relation

to the receptor height. The elevation of source is calculated using the following formula:

Elevation of source= Measured source height - Measured receptor height

For the Portsmouth local model, the elevated sections of road were modelled at a height of 5 m

above the receptor at that road. The identified flyovers are presented in Figure B-3 in Appendix B.

No tunnels were identified within the modelled road domain.

2.5 Surface Roughness and Minimum Monin-Obukhov Length

Given that most of the study domain encompasses a suburban area, a single surface roughness

length of 0.5 m across the modelled area was assigned. Similarly, a minimum Monin-Obukhov length

of 30 m was assigned within ADMS-Roads to provide a measure of atmospheric stability, which is

considered representative of the landscape.

2.6 Meteorological Data

Hourly sequential meteorological data were obtained from Thorney Island meteorological station (Lat.

50.817; Lon. -0.917; elevation: 3m), which is approximately 15 km east of the study area. A wind rose

based on 2018 is shown in Figure B-6 in Appendix B. The dominant wind direction in this year was

from the southwest (270 degrees). The data were obtained for the same year as the Base Year model

scenario (2018) to maintain consistency. These data were used in all air quality modelling scenarios.

The following parameters were included in the meteorological data file:

Temperature;

Wind speed;

Wind direction;

Relative humidity;

Cloud cover extent; and


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Precipitation.

2.7 Modelled Receptor Selection

Each PCM link has a unique Census ID and a grid reference typically describing the DfT traffic count

points on each link. This location may not be where the highest roadside concentrations are occurring

along the entire link length when using a more detailed local modelling method, with more detailed

traffic data. For the purposes of Target Determination and with a focus on the primary objective, a

suite of discrete receptor points was identified adjacent to each PCM link and local road link from the

SRTM within the air quality model domain.

To comply with the PCM model and to facilitate direct comparison for Target Determination, each

receptor was modelled at 4 m from the kerb at a height of 2 m above ground level on either side of the

road link. The receptors adhered to the criteria referenced by Annex III of EU Directive 2008/50/EC,

which state that the receptor should be:

Representative of at least 100 m of road length;

At least 25 m from the edge of a major junction (one that interrupts flow of traffic); and,

Within 10 m of the kerbside.

The locations of the discrete receptors included in the air quality model are presented in Figure B-7 in

Appendix B.

2.8 Model Output Data

2.8.1 Base year 2018 and Projected Base Year 2022

The ADMS-Roads model provides annual mean NOx concentration values at each identified receptor

point. Defra’s NOx to NO2 calculator v7.1 was used to convert annual mean road-NOx to total annual

mean NO2 at each point.

This calculation required the background annual mean NOx and NO2 value to be known, which were

obtained from Defra’s national 1 km x 1 km grid pollutant maps for the respective years (2018 and

2022). These background values incorporated contributions from non-road sources of NOx and NO2.

Given the extent of the study area, the background pollutant values vary across the model domain

and thus were mapped using GIS and the relevant value assigned to the modelled receptors.

Background NOx and NO2 were adjusted to remove contributions from roads included in the ADMS-

Roads model (e.g. Trunk roads, A-roads), where applicable, thereby avoiding double-counting of

emissions.

The calculator also incorporates the domain-wide average f-NO2 fraction, which was derived from the

EFT outputs and applied to each receptor point to determine the proportion of the road-NOx

concentration as primary NO2.

2.8.2 Interim and Future Base Year Interpolation

The ADMS-Roads model was used to predict NO2 concentrations at sensitive receptor locations for

the Base Year (2018) and Projected Base Year (2022). The modelled road networks for the Base

Year and Projected Base Year were the same. To interpolate concentrations to interim years, the

approach for estimating roadside NO2 concentrations as described on the LAQM support website was

initially used. However, these yearly factors were found to result in a greater reduction in

concentrations as predicted by the local modelling. Therefore for this study, a set of yearly factors

specific to each road link was calculated based on a linear change in concentration from 2018 to

2022. These factors were extrapolated to beyond 2022 to identify the year of compliance without any

intervention up to 2030.


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3. Model Verification and Adjustment

This section provides an overview of the dispersion model verification process and outcomes for the

2018 baseline year. A fuller description of the process is given in Appendix A.

3.1 Comparison of Modelled (Unadjusted) and Monitored Road NOx

A comparison of the unadjusted modelled annual mean road NOx and total NO2 concentrations at all

of the Council’s monitoring locations was undertaken for 2018. These were reviewed and some

discounted due to low data capture and specific siting issues. A total of 34 monitoring sites from

across the air quality domain were included in the initial comparison, comprising of two real-time

continuous analysers and 32 passive diffusion tubes. Information on monitoring locations are given in

Appendix B

There was an overall tendency for the model to underestimate the monitored road-NOx and total NO2

equivalent. The model is shown to under predict at a large number of sites, with 26 out of the 34 sites

under predicting concentrations.

3.2 Verification

Following review of the model performance at monitoring sites and liaison with PCC’s monitoring

team and JAQU, the model was adjusted by a single verification across the study area.

The modelled road-NOx adjustment factor was applied to the modelled road-NOx values for the Base

Year 2018 and Projected Base Year 2022 as well as all modelled options at all receptors.

3.3 Modelled Road NOx Adjustment

The modelled road-NOx values were plotted graphically versus the monitored road-NOx equivalent

for each site within the respective zone. A road-NOx adjustment factor was derived for each zone

based on a ‘y=mx’ line of best fit, forced through a zero intercept. This graph is presented in Figure

3-1 which show the modelled road-NOx value versus the monitored road-NOx value before and after

the adjustment. The adjustment factor based on the line of best fit were derived to be 1.61. Once the

derived factor was applied to the modelled road-NOx value, the NOx to NO2 calculator was utilised to

calculate the total adjusted annual mean NO2 at each site. A secondary adjustment factor was not

applied. The monitored NO2 concentrations versus modelled total NO2 concentrations are presented

in Figure 3-2.


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Figure 3-1 - Modelled Road-NOx versus Monitored Road-NOx

Figure 3-2 - Adjusted NO2 versus Monitored NO2 Concentrations


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3.4 Model Adjustment Summary

Following model adjustment, there was no apparent tendency for the dispersion model to over or

under predict within each of the verification zones. Of the 34 monitoring sites considered, 32 were

shown to return adjusted modelled total NO2 concentrations within +/-25% of the monitored

equivalent, with 25 performing within +/-10%.

A statistical analysis was completed for the adjusted model road-NOx to facilitate comparison with the

unadjusted model road-NOx. The RMSE (average model uncertainty) value was within 10% of the air

quality limit value (3.4 µg/m3). The statistical analysis of the adjusted model performance and

uncertainty demonstrates that the atmospheric dispersion model is robust and representative for the

prediction of annual mean road-NOx concentrations at identified receptor locations throughout the

domain.

The use of a single verification factor across the large study area was requested by JAQU and PCC

as it was considered that there were not sufficient differences in the traffic network to warrant zoning

of the model and the use of multiple adjustment factors. Although the model performs well across the

study area, there are some monitoring locations where the outputs under or over-predict road NOx

concentrations to a greater extent than others. For example, the model over-predicts at Church Street

monitoring sites (DT32a, 32b and DT34) by 30-40%, but under-predicts on London Road (e.g. by

more than 40% at monitoring site DT26 and C2). It is important to be mindful of this when considering

the results.

A consideration of street canyons close to monitoring sites was also made to determine whether it

would be appropriate to apply a separate verification factor to those roads with street canyons.

However, as the model verification factor is already low (1.61), and there are only a few street

canyons in the modelled road network, it was considered that the model was performing well so no

further consideration or modification to the verification was needed.


18

4. Baseline Results

4.1 Vehicle Fleet

The data obtained from the ANPR camera survey was used to identify the Euro emission standard of

the current vehicle fleet captured in 2019. Table 4-1 provides a summary of the number of vehicles

captured in the week’s survey and the proportion that are currently non-compliant to a CAZ emission

standard (Euro 4 petrol or Euro 6/VI diesel).

Of the 8 million vehicle movements captured, some 45% relate to non-compliant vehicles and 42% of

fleet movements are undertaken by non-compliant diesel cars, 9% by non-compliant petrol cars, 9%

by non-compliant diesel LGVs, and 2% by non-compliant taxis.

Table 4-1 Current and predicted vehicle fleet and non-compliance to CAZ emission standards,

across all ANPR sites

Vehicle type Non-compliant

vehicle movements

(2019)

Compliant vehicle

movements (2019)

Total vehicle movements

(2019)

% non-compliant

vehicle movements

(2019)

What % of the total fleet do

non-compliant vehicles

account for (2019)?

Predicted % non-

compliant vehicle

movements (2022 future

base)

Diesel cars 1,896,439 816,376 2,712,815 70% 23.5% 47%

Petrol cars 715,954 2,838,207 3,554,161 20% 8.9% 6%

Diesel black cabs 1,337 28 1,365 98% 0.0% 51%

Diesel taxi cars 170,113 200,417 370,530 46% 2.1% 32%

Petrol taxi cars 0 19746 19,746 0% 0.0% 0%

Other taxi cars 174 16566 16,740 1% 0.0% 0%

Electric cars 0 10011 10,011 0% 0.0% 0%

Hybrid cars 1546 102172 103,718 1% 0.0% 0%

Gas cars 2,625 0 2,625 100% 0.0% 100%

Diesel LGVs 730,820 282,869 1,013,689 72% 9.0% 45%

Petrol LGVs 3,155 3,922 7,077 45% 0.0% 6%

Other LGVs 679 2241 2,920 23% 0.0% 0%

Rigid HGVs 40,218 52,313 92,531 43% 0.5% 21%

Artic HGVs 13,633 32,543 46,176 30% 0.2% 10%

Mini buses 15,822 11,317 27,139 58% 0.2% n/a*

Diesel buses/coaches

62,220 42,479 104,699 59% 0.8% 11%

Total 3,654,735 4,431,207 8,085,942 45% - -

A summary of the ANPR data for the camera sites closest to the two exceedance locations is provided

in Table 4-2.


19

Table 4-2 Current and predicted vehicle fleet and non-compliance to CAZ emission standards,

based on ANPR Camera 35 (Commercial Road) and ANPR Camera 32 (Marketway, close to

Alfred Road)

Camera 35 (Commercial Road) Camera 32a,b (Marketway)

Vehicle type Total vehicle movements

(2019)

% non-compliant

vehicle movements

(2019)

What % of the total fleet do

non-compliant vehicles

account for (2019)?

Total vehicle movements

(2019)

% non-compliant

vehicle movements

(2019)

What % of the total fleet

do non-compliant vehicles

account for (2019)?

Diesel cars 59,494 76% 28.3% 108,772 67% 23.9%

Petrol cars 73,950 20% 9.4% 131,953 17% 7.6%

Diesel black cabs 48 96% 0.0% 93 97% 0.0%

Diesel taxi cars 5,387 63% 2.1% 15,419 47% 2.4%

Petrol taxi cars 126 0% 0.0% 775 0% 0.0%

Other taxi cars 134 1% 0.0% 641 0% 0.0%

Electric cars 254 0% 0.0% 601 0% 0.0%

Hybrid cars 1,882 1% 0.0% 4,624 4% 0.1%

Gas cars 33 100% 0.0% 65 100% 0.0%

Diesel LGVs 14,113 80% 7.1% 27,836 70% 6.4%

Petrol LGVs 126 41% 0.0% 189 42% 0.0%

Other LGVs 63 14% 0.0% 95 25% 0.0%

Rigid HGVs 1,084 67% 0.5% 2,796 46% 0.4%

Artic HGVs 290 51% 0.1% 1,020 26% 0.1%

Mini buses 548 72% 0.2% 1,155 55% 0.2%

Diesel buses/coaches 2,053 84% 1.1% 7,840 56% 1.4%

Total 159,585 48% - 303,874 41% -

4.2 NO2 concentrations

Total annual mean NO2 concentrations were derived for all receptor locations identified in Figure B-7

in Appendix B for the 2018 Base Year and 2022 Projected Base Year. There are 41 Census IDs

present in the modelled road domain. Across the wider model domain, there were also a large number

of local roads without an associated Census ID.

Based on the local model results, there are predicted to be a total of 70 individual receptors

demonstrating exceedances of the annual mean EU limit value in the Base Year 2018, reducing to 11

receptors in the Projected Base Year 2022 scenario (see Figure 4-1 a).

The 2022 future baseline shows that there are three road links within the city centre where the NO2

EU Limit Value is predicted to be exceeded on Portsmouth controlled roads as shown in Figure 4-1 b.

This is indicated in Table 4-3 alongside other areas with concentrations close to the EU Limit Value.


20

Figure 4-1: Location of roadside receptor sites with modelled exceedances in 2022 baseline

(EFT v1.9b)

a) All receptors


21

b) City centre roads

Table 4-3: Locations with modelled (or near) exceedances in 2022 Baseline

Receptor ID Unique Link

ID (Census

ID if

applicable)

Road Name Modelled

NO2 (µg/m3)

–

2022

baseline

Modelled

Road-NOx

(µg/m3) –

2022

baseline

% Road NOx

reduction to

meet EU limit

Year

compliance

would be

achieved,

assuming no

intervention

Road sections on the local network modelled as exceeding the EU limit (40 µg/m3) in 2022

573 51842

(18114)

A3 Alfred Road (Unicorn Rd

to Queen St, s/b)

41.7 47.3 -6.7% 2023

546 51448

(80848)

A3 Commercial Road (south

of Church St Rbt, s/b)

41.1 39.6 -3.8% 2023

Road sections on the local network not exceeding the EU limit, but still above 37 µg/m3 in 2022

526 51411 Church Street (east of Church

St Rbt, n/b)

40.4 37.6 (+0.6%) -

526 51411 Church Street (sensitivity test)

– described below

38.7 33.4 (+1.0%) -

536 51546

(74735)

A3 Hope Street (south of

Church St R'bout, s/b)

38.9 34.9 (+11.0%) -

824 51828 (8250) A2030 Eastern Road Water

Bridge (s/b)

38.8 43.9 (+9.5%) -


22

Receptor ID Unique Link

ID (Census

ID if

applicable)

Road Name Modelled

NO2 (µg/m3)

–

2022

baseline

Modelled

Road-NOx

(µg/m3) –

2022

baseline

% Road NOx

reduction to

meet EU limit

Year

compliance

would be

achieved,

assuming no

intervention

648 51601

(38333)

A2047 London Road

(Stubbington Ave to Kingston

Crescent, s/b)

38.5 33.1 (+14.3%) -

520 51399

(48196)

Mile End Road (north of

Church St R'bout, s/b)

37.6 30.9 (+22.2%) -

557 51461

(18114)

A3 Marketway (Hope St Rbt to

Unicorn Rd)

37.4 38.5 (+19.8%)

Road sections on the Strategic Road Network exceeding the EU limit (40 µg/m3) in 2022

986 52157 A27 (north of Portsea Island,

w/b)

48.5 68.6 -29.5% 2026

1089 52408 A27 (east of Portsea Island,

w/b)

46.1 65.3 -21.3% 2025

11 51817 M27 (west of Portsea Island,

w/b)

45.3 68.0 -17.9% 2025

968 53122 A27 (north of Portsea Island,

e/b)

43.7 59.9 -14.7% 2024

834 51837 A27 (east of Portsea Island,

w/b)

41.1 49.0 -3.0% 2023

For target determination, a sub-set of receptors was chosen through a process of joining road links

and receptors in GIS to identify those with the maximum predicted annual mean NO2 concentrations

on each modelled road link.

Church Street sensitivity test

It was apparent from the model results, that NO2 concentrations on Church Street (receptor 526) were

higher than expected from the Council’s monitoring. Therefore, following a comparison between the

strategic transport model outputs and observed traffic counts in the city centre, it is apparent that the

SRTM2 traffic model substantially over-estimates flows on Church Street, primarily as a result of

the modelled link capturing movements on other local roads which are not represented in the strategic

model network. Table 4-4 summarises the comparison of modelled traffic against observed data. The

comparison draws on the two available sources of observed data:

the vehicles counted by the ANPR camera installed on the northern part of Church Street for the

week of 18/03/19 to 24/03/19 providing two-way all day coverage; and

a classified count on a single day (Thursday 04/04/19) for the AM and PM peak periods at the

junction between Church Street, Holbrook Road and Lake Road to the south of the link.

The Council undertook a more comprehensive two week traffic count in September 2019 which

provides additional supporting evidence.

2 Sub Regional Transport Model


23

Table 4-4: Comparison between modelled and observed traffic data, Church Street, 2019

Section -

Direction

Modelled Baseline 2019 (SRTM) ANPR 2019* One day Classified

Turning Count 2019 **

AM

peak

hour

IP

peak

hour

PM

peak

hour

24hr

AADT

AM

peak

hour

IP

peak

hour

PM

peak

hour

24hr

AADT

AM peak

hour

PM peak

hour

North – NB 1,044 764 787 10533 - - - - - -

North – SB 983 758 1,169 11,506 - - - - - -

North – 2way 2,028 1,523 1,957 22,037 1,057 880 768 14,225 - -

South – NB 1,303 768 1,260 12,735 - - - - 517 440

South – SB 765 650 756 8,884 - - - - 584 334

South – 2way 2,067 1,352 2,017 21,620 - - - - 1,101 774

North refers to the short section between Church Street Roundabout and Wingfield Street and most

closely represents the conditions at receptor ID526. South refers to the section between Wingfield

Street and Lake Road Roundabout, a 350 metre section south of ID526.

* ANPR data is a 7 day average, adjusted to account for average 93% capture rate over the week.

** Turning count undertaken on Thursday 04/04/19

The data shows that two-way modelled flows on the short section between Church Street Roundabout

and Wingfield Street, which most closely represents the conditions at receptor ID526, are 22,037

compared with an ANPR count of 14,225.

A comparison of modelled speeds against available data from Trafficmaster, TomTom and Google

mapping showed that modelled speeds appear to be close to observed speeds, despite the difference

in flow levels. For example, TomTom GPS journey speed data for 2018 (24hr flow weighted average)

provides the following comparison for the section between Church Street Roundabout and Wingfield

Street:

southbound: median speed = 29kph and mean speed = 29kph, compared to a modelled speed of

31kph;

northbound: median speed = 13kph and mean speed = 15kph, compared to a modelled speed of

9kph.

As a result of the overestimate of traffic flows, the air quality model over-estimates NO2

concentrations compared to the measured data on Church Street. A sensitivity modelling test was

conducted whereby the observed traffic flows were growthed to 2022 levels (using the forecast growth

from SRTM and a further 15% uplift to allow for uncertainty) to provide a more realistic, lower future

flow estimate for Church Street. Using these revised traffic flows, the predicted modelled NO2

concentration at receptor 526 is forecast to be lower in 2022 (38.7 µg/m3) compared to the predictions

from the SRTM baseline forecast traffic outputs (40.4 µg/m3) as presented in Table 4-4 above.

Based on the evidence from the traffic count data presented in Table 4-4, the sensitivity test is judged

to be a more accurate representation of concentrations on Church Street, and from this point on we

will assume the revised baseline figure of 38.7 µg/m3 for Church Street.


AECOM 24

5. Source Apportionment

NO2 concentrations are affected by NOx emissions from both non-road and road sources within and

outside Portsmouth. Further information on the relative contribution from these sources at selected

locations with the city is given in this section.

5.1 Road vs Non-Road Contribution

The contribution of all non-road sources, both those within and outside the city have been included

within the model as part of the background. This is represented by mapping data within 1km grid

squares (see Section 2.8.1). Between 2018 and 2022, there is a predicted reduction in background

NOx concentrations in the city, but the relative contribution of each source type is similar.

In some areas of the city, the contribution of road sources makes up 40% of total modelled NOx, with

non-road sources, such as combustion process, domestic and commercial heating, railway, off-road

vehicles and shipping from the port making up a similar amount. JAQU have provided further

disaggregation of the background mapping for 2018. This additional information shows that there are

areas of the city, such as close to the coast where the contribution from roads is lower and shipping

emissions at the port are much greater. For example, at Mile end Road/Church Street/Commercial

Road, shipping emissions make up more than 40% of background road NOx in 2018. Close to Alfred

Road, the combined contribution from shipping (34% and off-road industrial activities – i.e. portside

operation (11%) is of a similar magnitude (see Table 5-1). There is also around 20-25% of NOx from

rural sources from outside the city, which are outside of the control of the Council.

Table 5-1 and Table 5-2 provide selected examples of the range of contribution of different sources to

NOx within selected 1km grid squares for the Base Year of 2018 and Projected Base Year of 2022

respectively. The tables show that the background concentration declines from 2018 to 2022, but the

relative contribution by source is similar in both years.

Table 5-1 Percentage Contribution of Road and Non-Road Sources to background NOx in

selected areas of Portsmouth, 2018

Area (Background grid square and receptors)

Total bkd NOx

(µg/m3) Ind

us

try

Do

mesti

c h

eati

ng

Rail

way

Sh

ipp

ing

Off

-ro

ad

in

du

str

ial

Off

-ro

ad

oth

er

Po

int

so

urc

es

Ru

ral

(ou

tsid

e P

CC

)

To

tal N

on-R

oad

Sourc

es

To

tal

Road S

ourc

es

M275/A3 Mile End Rd/ Church St/Commercial Road (incl. Portsmouth Port)

Grid square: 464500, 101500 Receptors: 526, 546

Road link 18114

46.8 1.9% 6.3% 0.1% 43.8% 2.9% 0.1% 1.9% 18.4% 75.3% 24.7%

A3 Alfred Rd/Marketway (incl. the Naval Dockyard) Grid square: 463500. 100500 Receptor: 573

Road link 80848

38.3 1.9% 5.7% 0.1% 34.3% 10.9% 0.1% 5.7% 22.6% 81.4% 18.6%

Portsea Island (average of grid squares)

28.7 3.0% 7.1% 0.2% 21.7% 4.4% 0.2% 3.5% 30.1% 70.2 29.8


AECOM 25

Table 5-2: Percentage Contribution of Road and Non-Road Sources to NOx in selected areas of

Portsmouth, 2022

Area (Background grid square and receptors)

Total bkd NOx

(µg/m3) Ind

us

try

Do

mesti

c h

eati

ng

Rail

way

Sh

ipp

ing

Off

-ro

ad

in

du

str

ial

Off

-ro

ad

oth

er

Po

int

so

urc

es

Ru

ral

(ou

tsid

e P

CC

)

To

tal N

on-R

oad

Sourc

es

To

tal

Road S

ourc

es

M275/A3 Mile End Rd/ Church St/Commercial Road (incl. Portsmouth Port)

Grid square: 464500, 101500 Receptors: 526, 546

Road link 18114

40.4 1.9% 6.8% 0.0% 45.2% 3.1% 0.1% 2.2% 18.6% 77.9% 22.1%

A3 Alfred Rd/Marketway (incl. the Naval Dockyard) Grid square: 463500. 100500 Receptor: 573

Road link 80848

33.0 2.2% 6.2% 0.1% 34.0% 11.6% 0.1% 6.4% 22.7% 83.3% 16.7%

Portsea Island (average of grid squares)

24.8 3.4% 7.9% 0.1% 22.7% 4.7% 0.2% 4.1% 30.3% 73.4% 26.6%

Local estimate of port emissions

At the time of submission, reliable data on emissions associated with Portsmouth International Port

activity was not available. Prior to the pandemic, there were plans to expand shipping activity, but the

timescales and extent of any future growth plans are currently unconfirmed. The modelling presented

in this document is therefore based on the above JAQU estimates of background NOx concentrations.

5.2 Road Contributions by Vehicle Type

Road transport sources are the only source to be explicitly modelled in this study, as there is currently

not sufficient local data available to model the other non-road sources.

The contribution of road NOx emissions broken down by vehicle and fuel type is presented in Figures

B-8 to B-19 in Appendix B for each modelled road link in for Base 2018 situation and Future Base

2022. The figures show that it is the diesel cars that have the greatest contribution to road NOx, with

more than 50% on some roads, particularly routes down the western corridor into the city. In some

areas of the city, there is a much higher contribution from HGVs such as around Anchorage Park (at

least 50%) and from buses (which contribute to 18% on London Road).

The contribution by the main vehicle types to road NOx emissions at each of the receptors predicted

to exceed the EU Limit Value in 2022 is given Table 5-3.

Table 5-3 Contribution of vehicle type to road NOx emissions on exceedance road links, 2022

Future Base

PCM Road Link

Petrol Cars (%)

Diesel Cars (%)

Taxis (%)

Petrol LGVs (%)

Diesel LGVs (%)

Rigid HGVs (%)

Artic HGVs

(%)

Buses & Coaches (%)

M’cycles (%)

Hybrid (%)

18114 9.24 47.10 0.03 0.03 21.61 13.73 7.27 0.00 0.01 0.98

80848 10.64 49.80 0.03 0.03 22.63 7.24 3.64 4.91 0.02 1.07

PORTSMOUTH CITY COUNCIL

26

6. Options Modelling

6.1 Shortlisted Options at Strategic Outline Case (SOC) Stage

The study initially considered a Benchmark Charging Clean Air Zone (CAZ) option and three non-

charging air quality improvement package options as presented in the Strategic Outline Case (SOC)

submitted in January 2019.

6.2 Shortlisted Options at Outline Business Case (OBC) Stage

6.2.1 Options Shortlisted (at OBC stage)

Following further review of options and packages that took into account the more detailed evidence

and current understanding of exceedances across the city, these options were further refined as part

of the Outline Business Case (OBC) process. This process was based on the following activities:

A PCC workshop with officers to discuss further options

Input from the Air Quality Stakeholder Group and the Air Quality Project Board

Inputs from Members

Initial modelling of traffic and emissions impact, prior to detail transport and air quality modelling*

Further research and data collection relating to the baseline (including ANPR data) various

options.

This process has resulted in a shortlist of options for comparison (see Table 6-1).

Table 6-1: Options modelled for 2022 (at OBC stage)

Model Test Name Detail

0. 2022 Baseline 2022 Projected Base Year including committed developments.

1. Portsea Island CAZ B Targeting taxis and private hire vehicles (PHV), buses, coaches, HGVs across Portsea Island.

2. Portsea Island CAZ C Targeting taxis and Private Hire Vehicles (PHVs), buses and coaches, HGVs, LGVs on Portsea Island.

3. Small Area CAZ B Targeting taxis and private hire vehicles (PHV), buses, coaches, HGVs within a smaller area of the city.

4. Small Area CAZ B with non-charging measures As Test 3 + parking measures + strategic cycling routes + modification to the traffic signal timings at the Alfred Road / Queen Street junction.

5. Portsea Island CAZ B external trips only As Test 1 but charge only applied to trips into / out of Portsea Island (i.e. not including internal trips), as these trips make up the vast majority of movements on the two exceedance links.

6. City Centre Transport Link Modification to the road layout in the city centre to support wider ambitions for the City. No CAZ charges assumed.

The indicative boundary for the Portsea Island CAZ is shown in Figure 6-1. It is focused on the whole

of the Portsea Island area, excluding the M275 and the western arm of Rudmore Roundabout

(providing the option to exempt traffic to Portsmouth International Port).

The indicative boundary for the Small Area CAZ is shown in Figure 6-2. It includes key destinations

for targeted traffic on the two exceeding links including the City Centre, and Gunwharf Quay /

Wightlink Terminal, and is intended to minimise re-routing to avoid the CAZ. In particular, the

inclusion of Kingston Crescent and Fratton Road was intended to minimise re-routing along London

Road and Fratton Road which could result in new exceedances.


27

Figure 6-1: Indicative boundary for Portsea Island CAZ


28

Figure 6-2: Indicative boundary for Small Area CAZ (at OBC stage)

The modelled non-charging measures referred to in Test 4 comprise:

Changes to parking capacity and pricing south of the city centre including increased charges for Council and University staff, increased tariffs in short-stay car parks and seafront parking, reduced capacity in city centre car parks and a reduction in Park and Ride charging.

Strategic cycling routes proposed within the draft Local Cycling and Walking Investment Plan on two priority corridors (Eastern Road Water Bridge to City Centre and Southsea to City Centre to London Road and out of the city).

Alfred Road signal changes to allow for extra green time on south bound traffic on Alfred Road to increase the average speed on this road.

6.2.2 Option Assumptions (at OBC stage)

As for the Projected Base Year of 2022, ADMS-Roads modelling was conducted to determine how the

predicted forecast changes in road emissions for each of the options relate to changes in NO2

concentration at receptors in 2022. The modelling considered other factors such as weather

conditions and street geometry and combined with background concentrations as for the baseline.

The CAZ B and C options have been represented in the modelling using the following assumptions:

Fleet will continue to turnover, leading to some natural upgrade from non-compliant to compliant vehicles between the current year and 2022;

90% of buses and coaches and mini buses will be compliant after upgrades in response to the CAZ (as the majority will already be compliant due to the ongoing programme of retrofits);

90% of taxi trips in Portsmouth will all be undertaken by compliant Euro 6 vehicles (with the remaining 10% paying the charge). For Test 6, 100% taxis are assumed to be compliant;


29

LGV and HGV drivers respond to the CAZ in line with the JAQU national average response rates as set out in Table 6-2;

A charge of £50/day has been assumed for buses and HGVs, and £10/day for all other vehicles. The CAZ charge is applied to all trips undertaken by affected modes, and at this stage no account is taken of any potential exemptions;

Daily charges are converted into charges per trip on the basis of the estimated number of return trips made per vehicle within the day. However, as there is no scope for mode or destination shift within the model, this value only influences the routing for the small subset of trips that have a choice of passing through the CAZ zone or taking another route to their destination.

Table 6-2: Assumed responses of LGVs and HGVs to a CAZ (based on JAQU data)

Response LGV trips LGV vehicles HGV trips HGV vehicles

Replace/upgrade vehicle

64% 25% 83% 44%

Cancel trip 6% 12% 4% 13%

Change mode 2% 4% 0% 0%

Avoid zone 8% 17% 4% 13%

Pay charge 20% 42% 9% 29%

6.2.3 Model Results (for OBC options)

6.2.3.1 Identification of Benchmark (Portsea Island CAZ C)

Modelled reduction in road NOx – Figure 6-3 shows the forecast reduction in road NOx3 emissions

achieved by different levels of CAZ (implemented across the whole of Portsea Island) for the

exceedance locations (shown in red) and the near exceedance locations (shown in orange).

The results are based on outputs from the traffic model and estimated impact of the changes in traffic

flows and speed and vehicle fleet on traffic emissions (based on Emissions Factor Toolkit v1.9b).

The emissions spreadsheet provides an approximation of the impact on NO2 concentrations that the

air quality model will forecast at each receptor for each CAZ option. However, it is not a precise

indication as the relationship between NOx emissions and NO2 concentrations is not direct/linear and

the spreadsheet only accounts for emissions on the link the receptor is located on and not the

secondary effects of emissions from other nearby links (which are included in the air quality

model). The approach provides an understanding of the scale of the impact of the different CAZ

options and how they compare but may give slightly different results to the full air quality model.

The graphs show that a CAZ A (targeting taxis and private hire vehicles, buses and coaches)

achieves only a small reduction in road emissions (1% and 3% on Alfred Road and Commercial Road

respectively). A CAZ B (which also includes HGVs) would be substantially more effective in reducing

emissions on the two exceedance links (reducing road emissions by 11% and 14% on Alfred Road

and Commercial Road respectively), reflecting the relatively high proportion of non-compliant HGVs

on these links. A CAZ C (which also includes LGVs) would achieve a further reduction in emissions,

but the difference between a CAZ B and CAZ C is relatively small, reflecting the average age of LGVs

in Portsmouth (LGVs are typically newer than the national average). Finally, a CAZ D (covering all

vehicle types) would be most effective, achieving a much greater reduction in road emissions than a

CAZ C (29% and 34% on Alfred Road and Commercial Road respectively). This is not surprising as

cars (compliant and non-compliant) account for 52% of road emissions on Alfred Road and 55% on

Commercial Road.

3 Nitrogen oxides or NOx is the term that applies to a combination of nitric oxide (NO) and NO2. NOx gases are emitted from vehicles but as NO is considered to be harmless to health, the EU Limit Value is based on NO2 concentrations. Air quality modelling is conducted for NOx emissions from the road and then this is converted to NO2 taking into account the non-linear relationship between the two and the contribution from background concentrations.


30

Figure 6-3: Modelled reduction in road NOx in 2022 for different levels of CAZ (OBC analysis)

CAZ A (Indicative traffic model outputs and emissions spreadsheet)

P:\GBEMB\TP\HA\PROJECTS\5185637 - PCC AQ Plan - ROBI2323\40. Technical\08. Emissions Calculations\2.

CAZ\Emissions\Indicative\Indicative - High-level emissions analysis TD1 CAZC-D v5

CAZ B (based on CAZ B traffic model outputs and emissions spreadsheet)


CAZ\Emissions\ModelledSRTM\Modelled - High-level emissions analysis TD1 CAZB-D v8


31

CAZ C (based on CAZ C traffic model outputs and emissions spreadsheet)



CAZ D (based on CAZ D traffic model outputs and emissions spreadsheet)




32

Modelled reduction in NO2 (µg/m3) – Table 6-3 shows how the forecast changes in road emissions

for CAZ B and CAZ C relate to changes in NO2 concentration in 2022, taking account of other factors

such as weather conditions and street geometry and accounting for background concentrations

(including emissions from other roads.

A CAZ C is forecast to deliver compliance in NO2 concentrations at the Alfred Road and Commercial

Road exceedance locations in 2022, without worsening emissions elsewhere. A CAZ B is also

forecast to deliver compliance at both exceedance locations in 2022, but the concentrations of NO2 on

Alfred Road (40.4µg/m3) are very close to the statutory limit of 40.49µg/m3. Small changes in model

assumptions could result in the limit being exceeded.

There are no dis-benefits at any receptors in near exceedance areas. It is noted that under all

scenarios there are outstanding exceedances on the Strategic Road Network, but to a lesser extent

than in the baseline scenario.

Given the forecast proximity of the Alfred Road concentration to the statutory limit value in a

CAZ B scenario, a Level C CAZ applied at a cordon around Portsea Island, was taken forward

as the benchmark CAZ against which other options are compared.

6.2.3.2 Identification of Alternative Package (Small Area CAZ B + non-charging measures)

In recognition of the potential scale of impacts of a CAZ C on individuals and businesses, an

alternative package based on a CAZ B plus non-charging measures was also developed.

The following CAZ B options were considered as a basis for the alternative package:

CAZ B1 – Portsea Island CAZ B

CAZ B2 – Small Area CAZ B

CAZ B3 – Portsea Island CAZ B (ext/int trips only), i.e. excluding local movements within Portsea Island

Table 6-3 shows that the Small Area CAZ B performs as well as the Portsea Island CAZ B at

exceedance locations on the PCC network. As most significant destinations for taxis/private hire

vehicles and HGVs are inside the cordon, minimal re-routing occurs. The slight re-routing which does

occur results in a small shift from heavy to light vehicles relative to the Portsea Island CAZ and

actually improves performance slightly on the two exceedance links.

Eastern Road shows an increase relative to Portsea Island CAZ B due to fewer HGVs needing to

upgrade (e.g. vehicles to Anchorage Park no longer affected), however the NO2 concentration is still

lower than in the baseline and below the EU limit.

The Small Area CAZ performs slightly less well than the Portsea Island CAZ at SRN exceedance

locations, due to the lower overall upgrade of vehicles, but still performs better than the baseline.

The version of CAZ B based on ‘external trips only’ performs less well than the Portsea Island CAZ B

at each exceedance and near exceedance location. This primarily reflects the smaller scale reduction

in non-compliant HGVs. It results in a slight increase relative to the baseline at Church Street due to

small increase in HGVs using the route, although the concentrations are believed to remain below the

EU limit. However, overall as this option would not be as effective as the other CAZ B options and

would not provide any wider air quality benefits across the city.

On the basis of these results, the Small Area CAZ B is shown to deliver compliance in the

shortest possible time (matching the compliance year for the CAZ C), without significantly

worsening emissions elsewhere. It is also expected to have less of an adverse impact on

individuals and businesses than the other CAZ B options and was therefore identified as the

preferred CAZ format for the Alternative Package.

Results for the full Alternative Package (Small Area CAZ B with non-charging measures) show a

maximum concentration of 40.1µg/m3 on Alfred Road (PCM link 18114).


33

Table 6-3: Modelled NO2 concentrations (µg/m3) in 2022 for different options

(Based on Emissions Factor Toolkit, v9.1b) (at OBC stage)

Receptor

ID

(PCM Road

Link)

Road Name Annual mean NO2 concentration (µg/m3)

Future

baseline

Portsea

Island

CAZ C

Portsea

Island

CAZ B

Portsea Island

CAZ B

(Ext trips only)

Small Area

CAZ B

Small Area

CAZ B + Non-

charging

measures

Exceedances

573

(18114)

A3 Alfred Road

(Unicorn Rd to Queen St,

s/b)

41.7 39.7 40.4 41.1 40.3 40.1

546

(80848)

A3 Commercial Road

(south of Church St Rbt,

s/b)

41.1 39.2 40.0 40.6 39.9 39.5

Near Exceedances

526

(n/a)

Church Street (east of

Church St Rbt, n/b)

(revised assessment)

38.7 <38.7a <38.7a - <38.7a <38.7a

536

(74735)

A3 Hope Street

(s of Church St R'bout, s/b)

38.9 37.5 37.9 38.4 37.8 37.8

824

(8250)

A2030 Eastern Road Water

Bridge (s/b)

38.8 36.3 36.8 37.0 38.4 38.3

648

(38333)

A2047 London Road

(Stubbington Ave to

Kingston Cres, s/b)

38.5 37.3 38.1 38.5 37.7 37.6

520

(48196)

Mile End Road

(n of Church St R'bout, s/b)

37.6 36.3 37.0 37.5 36.9 36.9

557

(18114)

A3 Marketway

(Hope St Rbt to Unicorn Rd)

37.4 35.7 36.3 37.1 36.3 36.2

Strategic Road Network

986 A27 (north of Portsea

Island, w/b)

48.5 45.4 46.7 46.9 48.2 48.2

1089 A27 (east of Portsea Island,

w/b)

46.1 43.8 45.1 45.2 46.0 46.0

11 M27 (west of Portsea

Island, w/b)

45.3 42.6 44.0 44.0 45.3 45.3


Island, e/b)

43.7 40.7 41.7 42.0 43.1 43.1

834 A27 (east of Portsea Island,

w/b)

41.1 38.8 39.7 39.9 40.9 40.8

a. The concentration at Church Rd has not been modelled directly, but the above options reduce traffic levels and improve

average fleet emissions compared with the baseline. It therefore follows that the concentration will be lower than the baseline

concentration. Portsea Island CAZ (ext trips only) results in a slight increase in flows on Church Street, but concentrations are

believed to remain below the EU limit.

Note: Concentrations in bold are above the EU LV


34

Contribution of non-charging measures

A number of ADMS (air quality) model runs were conducted as a means to disaggregate the individual

impacts of the cycling, parking and signal changes within the non-charging elements of the Alternative

Package.

Modelling was conducted for (see Table 6-4):

Small Area CAZ B + Cycling measures; and

Small Area CAZ B + Cycling + Parking measures.

These model scenarios were then used to calculate crude (non-modelled) estimates for (see Table

6-4, columns highlighted in grey):

Small Area CAZ B + Parking

Small Area CAZ B + Signal changes

Small Area CAZ B + Parking + Signal changes

based on interpolation.

The results show that in combination, the non-charging measures reduce NO2 concentrations by

0.2µg/m3 on Alfred Road and 0.4µg/m3 on Commercial Road. The Alfred Road signal changes impact

on the Alfred Road concentration, and the parking measures reduce concentrations on Commercial

Road.

The impact of the individual non-charging measures is small but given the proximity of the

concentrations on Alfred Road and Commercial Road to the EU limit they provide greater confidence

that the Alternative Package will achieve compliance with the EU limit on both exceedance links, and

(in the case of the cycling measures particularly) provide additional transport user benefits.

6.2.3.3 Other options not taken forward

City Centre Transport Link - This test involved modification to the road layout in the city centre to

support wider ambitions for the City. No CAZ charge was assumed. Various layout scenarios were

considered, but the results showed no net benefits for air quality within the city.


35

Table 6-4: Annual mean NO2 concentrations for individual non-charging measures, 2022 (at

OBC stage)

ID Road Name Annual mean NO2 concentrations (µg/m3)

Small Area

CAZ B

(no non-

charging

measures)

(modelled)

Small Area

CAZ B +

Cycling

(modelled)

Small Area

CAZ B +

Cycling +

Parking

(modelled)

Small Area

CAZ B +

Cycling +

Parking +

Signals

(modelled)

Crude

estimate of

Small Area

CAZ B +

Parking

Crude

estimate of

Small Area

CAZ B +

Signals

Crude

estimate of

Small Area

CAZ B +

Parking +

Signals

573 A3 Alfred Road

(Unicorn Rd to

Queen St, s/b)

40.3 40.3 40.3 40.1 40.3 40.1 40.1

546 A3 Commercial

Road

(south of Church St

Rbt, s/b)

39.9 39.8 39.5 39.5 39.6 39.9 39.6

526 Church Street (east

of Church St Rbt,

n/b) (revised

assessment)

<38.7 <38.7 <38.7 <38.7 <38.7 <38.7 <38.7

536 A3 Hope Street

(south of Church St

R'bout, s/b)

37.8 37.8 37.8 37.8 37.8 37.8 37.8

824 A2030 Eastern Road

Water Bridge (s/b)

38.4 38.3 38.3 38.3 38.4 38.4 38.4

648 A2047 London Road

(Stubbington Ave to

Kingston Crescent,

s/b)

37.7 37.7 37.6 37.6 37.7 37.7 37.6

520 Mile End Road

(north of Church St

R'bout, s/b)

36.9 36.9 36.9 36.9 36.9 36.9 37.0

557 A3 Marketway

(Hope St Rbt to

Unicorn Rd)

36.3 36.3 36.2 36.2 36.2 36.3 36.2



Island, w/b)

48.2 48.2 48.2 48.2 48.2 48.2 48.2

1089 A27 (east of Portsea

Island, w/b)

46.0 46.0 46.0 46.0 46.0 46.0 46.0

11 M27 (west of Portsea

Island, w/b)

45.3 45.3 45.3 45.3 45.3 45.3 45.3


Island, e/b)

43.1 43.1 43.1 43.4 43.1 43.4 43.4

834 A27 (east of Portsea

Island, w/b)

40.9 40.8 40.8 40.8 40.9 40.9 40.9


36

6.3 Refined Options at Full Business Case (OBC) Stage

6.3.1 Measures receiving provisional funding from JAQU

Following submission of the OBC, JAQU approved provisional funding (subject to submission of this Full Business Case) for a Small Area CAZ + non-charging measures. However, funding was not received for the strategic cycle routes or travel planning for workplaces and schools.

Table 6-5: Summary of measures approved for provisional funding by JAQU

Measure Provisional funding

Small Area CAZ B

Parking measures N/A (no funding required)

Strategic cycling routes

Alfred Road signal changes

Taxi license requirements N/A (no funding required)

EV charging points () JAQU will only fund this measure if PCC amend the licensing policy to

require use of electric vehicles before FBC submission in November 2020.

Residents Parking Zone

permits

N/A (no funding required)

Travel planning for workplaces

and schools

Targeted communications and

marketing

As shown in Table 6-6, the JAQU-approved Alternative Package achieves the same concentrations on

Alfred Road and Commercial Road as the proposed OBC Alternative Package.

6.3.2 Proposed boundary modifications (FBC stage)

6.3.2.1 Approved boundary modifications

Following further analysis and feedback from businesses and the public (either directly to PCC or via the public consultation exercise), the following modifications have been made to the indicative boundary identified at OBC stage (see Figure 6-4). As shown in Table 6-6, none of these measures affect the NO2 concentrations on Alfred Road and Commercial Road forecast for 2022, or create new exceedance locations (see results for JAQU-approved Alt. Package A and B):

Removal of Kingston Crescent (‘A’ on map)

Will benefit taxis / PHVs and HGVs servicing premises in this area (offices, a supermarket, a hotel

and a restaurant).

Will allow affected vehicles to travel southbound along London Road, and then along Kingston

Crescent towards the M275 without entering the CAZ; discouraging rat running through the

residential roads north of Kingston Crescent.

Results in a small increase in NO2 (+0.3) on A2047 London Road (just north of Kingston

Crescent), but still well below the EU limit. Review of signal timings at Kingston Crescent and

Fratton Road junctions proposed to minimise impact.

Removal of Fratton Road (‘D’ on map)

Initially included to discourage re-routing around the CAZ; a potential problem associated with a

higher order CAZ, but not identified as an issue within the modelling undertaken for the proposed

CAZ B.

Will benefit taxis / PHV drivers serving residential areas in Fratton and the surrounding area.


37

Table 6-6: Modelled NO2 (µg/m3) for refined CAZ B scenarios in 2022 (at FBC stage)

ID Road Name Annual mean NO2 concentrations (µg/m3)

OBC Alternative

Package

Small Area CAZ

B + Parking +

Cycling +

Signals

JAQU-approved

Alternative

Package

Small Area CAZ

B + Parking +

Signals

JAQU-approved

Alt. Package A

(excl. Kingston

Cres and

Wightlink

Terminal)

JAQU-approved

Alt. Package B

(excl. Fratton Rd,

Fratton R’bout,

Holbrook Rd

R/bout)

FBC Alt. Package

Small Area CAZ

(with approved

boundary

changes*) +

Parking + Revised

Alfred Rd signals

scheme)

573 A3 Alfred Road

(Unicorn Rd to Queen

St, s/b)

40.1 40.1 40.1 40.1 40.2

546 A3 Commercial Road (s

of Church St Rbt, s/b)

39.5 39.5 39.5 39.5 39.5

526 Church Street (east of

Church St Rbt, n/b)


<38.7a <38.7a <38.7a <38.7a <38.7a

536 A3 Hope Street

(south of Church St

R'bout, s/b)

37.8 37.8 37.8 37.8 37.8

824 A2030 Eastern Road

Water Bridge (s/b)

38.3 38.4 38.4 38.3 38.5

648 A2047 London Road

(Stubbington Ave to

Kingston Cres, s/b)

37.6 37.7 38.0 37.8 37.9

520 Mile End Road

(north of Church St R'bout,

s/b)

(36.9) (36.9) (36.9) (36.9) (36.9)

557 A3 Marketway

(Hope St Rbt to Unicorn

Rd)

(36.2) (36.2) (36.3) (36.2) (36.2)


986 A27 48.2 48.2 48.2 48.2 48.2

1089 A27 46.0 46.0 46.0 46.0 46.0

11 M27 45.3 45.3 45.3 45.3 45.3

968 A27 43.1 43.1 43.1 43.1 43.1

834 A27 40.8 40.8 40.9 40.8 40.8

* Removal of Kingston Crescent, Fratton Rd, Fratton Roundabout and Holbrook Rd Roundabout, and Princess Royal Way (not

modelled directly).


38

Figure 6-4: Proposed and approved changes to CAZ boundary (at FBC stage)

Removal of Fratton Roundabout and Holbrook Road Roundabout (‘E’ on map)

Allows affected vehicles to drive around Fratton Roundabout (previously inside the CAZ) from

Goldsmith Avenue to Fawcett Road (both outside the CAZ) without being charged; and benefits

other similar movements associated with the use of Holbrook Road Roundabout.

Will benefit taxis / PHV drivers as these roundabouts connect large residential areas to key routes

in the city.

Consistent with the proposal to remove Fratton Road.

Removal of Princess Royal Way (‘B’ on map)

Allows affected vehicles to access the Naval Base, via Trafalgar Gate, without entering the CAZ.

The majority of traffic using Trafalgar Gate is travelling to / from the north, so does not contribute

to the high NO2 concentrations on Alfred Road and Commercial Road. Non-compliant HGVs and

coaches with origins / destinations to the south, which will generally be using Commercial Road

and Alfred Road, will still need to pay the CAZ charge.

Will discourage affected vehicles from entering the Naval Base via Unicorn Gate, and exiting via

Trafalgar Gate, this reducing use of Commercial Road by non-compliant vehicles.

Will also benefit HGVs accessing the businesses along Flathouse Road (including Morrison's and

Portico), whose non-compliant vehicles would otherwise be liable for the CAZ charge.

It should be noted that military vehicles are exempt from the CAZ charge (as detailed in the

relevant legislation), but any non-compliant third-party or military personnel vehicles travelling

through the CAZ would be liable for a charge.

6.3.2.2 Other boundary modifications considered but rejected

Exclusion of the Isle of Wight ferry terminal operated by Wightlink (‘C’ on map)

The proposed CAZ boundary means that non-compliant coaches and HGVs are required to pay the

CAZ charge of £50 per day. Of particular concern amongst individuals responding to the CAZ public

consultation survey in summer 2020 was the perceived negative impact of the CAZ proposal on the

Isle of Wight's economy, with a boundary change to allow access to the ferry terminal without


39

incurring a charge seen as one way to mitigate this. Wightlink has also repeatedly raised concerns

about the impact of the CAZ on its business, and the potential for non-compliant coaches and HGVs

to divert to the Red Funnel ferry from Southampton or cease travelling to the Isle of Wight (particularly

in the case of tourist or school coach trips).

The ferry terminal is located south of the two exceedance locations, and the majority of vehicles using

the ferry travel to / from the terminal via Commercial Road and Alfred Road. If the CAZ boundary were

to be bought north of St George's Road and Gunwharf Road, non-compliant vehicles would be able to

access the Isle of Wight ferry terminal via the A2030 Eastern Road route (rather than the A3) without

travelling through the CAZ. Modelling demonstrates a very minor re-routing effect from such a

boundary change (with most non-compliant vehicles choosing not to re-route), no change in NO2

concentration on Alfred Road and Commercial Road, and no change at Eastern Road Waterbridge

(identified as a near-exceedance location in the 2022 baseline) – see Table 6-6 (JAQU-approved Alt.

Package A (excl. Kingston Cres and Wightlink Terminal).

Impact of requiring Wightlink HGVs and coaches to use Eastern Road, rather than Alfred Road

Further scenarios were also considered involving diverting all Isle of Wight-bound HGVs and coaches

(i.e. not just non-compliant vehicles) along Eastern Road, either as part of a CAZ B package or as an

alternative to a CAZ. Indicative analysis, using estimated changes in traffic flows and the Emission

Factor Toolkit only (rather than the full AQ model) has been undertaken to consider the impact of

these different scenarios on emissions.

a) If the CAZ B+ remained in place, but excluded Wightlink terminal, the diversion would reduce

NOx by 2.2% on Alfred Road and by 1.3% on Commercial Road (see Figure 6-5a). This is relative

to a CAZ B+ which includes Wightlink (and therefore the majority of HGVs / Coaches on Alfred

Road and Commercial Road are assumed to have upgraded). The additional HGV / Coach traffic

on Eastern Road would not cause an exceedance at Eastern Road Water Bridge. However, there

are issues surrounding the wider suitability of the Eastern Road diversion for additional HGVs and

Coach traffic.

b) If there was no CAZ B in place, then the diversion would reduce NOx by 4.6% on Alfred Road,

and by 2.6% on Commercial Road, relative to the 2022 baseline (see Figure 6-5b). The %

reduction in NOx required to achieve compliance is 6.7% on Alfred Road, and 3.8% on

Commercial Road; implying that a CAZ would still be required. This scenario would increase NOx

emissions at Eastern Road Water Bridge, by 1.9%, or 2.1%; this would however not be a large

enough increase in emissions to result in a new exceedance.

Both scenarios involve removing the same number of HGVs from Alfred Road, but in the first scenario

the majority are compliant and in the second scenario more of the vehicles are non-compliant vehicles

producing more emissions.

However, the impact on NO2 concentrations associated with these scenarios needs to be considered

alongside the wider impact on the Council's strategic transport aims:

By routing non-compliant Isle of Wight-bound HGV and coach traffic along Eastern Road it is

likely that many vehicles would then continue along A2030 Goldsmith Avenue as part of their

route. This road forms part of the east-west strategic active travel corridor and therefore

encouraging more large vehicles along the road to avoid the CAZ poses a risk to road safety. It

would also be likely to reduce the attractiveness of the route for active travel, undermining the

Council’s work to promote active travel.

Another area of concern for this route is the Velder Avenue junction (at the bottom of Eastern

Road). This is already a heavily congested junction with ongoing high levels of NO2 (although not

projected to be a future exceedance location for the purpose of the Local Air Quality Plan) with

residential dwellings abutting the carriageway and nearby schools. Increasing volumes of large

vehicles at the junction as a result of the diversion would exacerbate the congestion and air

quality issues.

Councillors (Cabinet Meeting, 6th October) therefore recommended that the CAZ boundary is not

amended to enable charge-free access to the Isle of Wight ferry terminal, due to the potential

negative impact on residential amenity, road safety and public health related to traffic rerouting to use

Eastern Road to avoid passing through the CAZ to reach the terminal. Instead further work should be

carried out with businesses on the Isle of Wight to support them in preparing their fleets for the

introduction of the CAZ and accessing financial support to upgrade their vehicles to compliant types.


40

Figure 6-5: Impact of requiring Wightlink HGVs and coaches to use Eastern Road

a) With CAZ B+ in place

b) Assuming no CAZ B+ in place


41

6.3.3 Other amendments to Alternative Package (FBC stage)

Refinement of Alfred Road signal changes

There are 5 linked junctions operating in SCOOT Region W4, extending from Alfred Rd/Unicorn Rd to

Park Road / St Georges Road / Gunwharf Quays. The two traffic signalled locations at either end of

Alfred Road are most significant in terms of co-ordinating the phasing between the signals, and are

also most relevant in terms of the Alfred Road NO2 exceedance.

The Outline Business Case (OBC) proposed providing extra green time to southbound traffic on Alfred

Road, to increase average link speed and reduce emissions from queuing traffic. The modelling

undertaken at the time looked at the Alfred Road signals in isolation and did not take account of the

relationship with other upstream / downstream junctions.

Since then the proposal has been reviewed and concerns have been raised that the proposal would

not provide sufficient benefits to all road users. For example, the proposal did not consider the long

pedestrian wait times. This location is used by the large number of students walking between the

university and the town centre, and has a history of reported near misses where the long cycle time

results in unsafe behaviour (e.g. running across the road between gaps in the traffic).

Further consideration of the options available to improve traffic flow and meet the needs of

pedestrians has therefore been undertaken, this time taking account of the upstream / downstream

junctions. As a result of the detailed assessment undertaken the following intervention is now

proposed:

Alfred Road / Queen Street junction - Trial a reduced SCOOT Region cycle time of 104

seconds (rather than the current 120 seconds) during the AM and PM peak periods and inverse

stages 2 and 3 of the current signal phasing.

- A shorter cycle time will result in shorter wait times for vehicles, resulting in shorter queues

and lower at point emissions; and shorter wait times for pedestrians and students.

- Reversing the stages will improve progression in both directions, providing a ‘green wave’

effect and allowing s/b traffic on Alfred Road to flow straight through the junction (removing

the queue adjacent to the NO2 exceedance location). Good progression between junctions

offers a reduction in the number of stop-starts, and platooning of traffic between the two

junctions with fewer vehicles arriving on a red signal.

- This proposal greatly benefits the inbound (s/b) traffic and is expected to reduce emissions on

Alfred Road; but may create additional delay for outbound (n/b) traffic, e.g. from Gunwharf

Quay. The changes would therefore need to be implemented gradually and monitored and

refined over time. The NO2 benefits associated with the proposed approach are therefore

caveated accordingly.

Alfred Road / Unicorn Road junction – This is a large junction featuring toucan crossings with

pedestrian overhead detectors used to extend the red phase for traffic if pedestrians are detected

on the crossing. However, the equipment is old and unreliable, and subject to failure. When a fault

occurs the junction no longer operates efficiently, resulting in a longer red signal and additional

queuing time for vehicles (including n/b traffic on Alfred Road).

In the short-term, it is proposed that a new Detection Fault Monitoring group is created, dedicated

to on-crossing detection, and that the trigger values are reduced. This will result in detection

failures being reported sooner with reduced equipment downtime. This will minimise the duration

of the fault and therefore the duration of additional delay experienced at the junction (and the

duration of spikes in traffic emissions).

In the medium term, we are proposing to renew the signal equipment, as part of the wider

equipment modernisation programme, most likely coinciding with the changes to this junction

proposed as part of the South East Hampshire Rapid Transit Scheme (scheduled for 2022 /

2023). This will increase the options available to improve the efficiency of the junction.

4 SCOOT (Split Cycle Offset Optimisation Technique) is an adaptive traffic control system. It coordinates the operation of all the traffic signals in an area to give good progression to vehicles through the network. Whilst coordinating all the signals, it responds intelligently and continuously as traffic flow changes and fluctuates throughout the day.


42

These proposals have not been modelled but will add wider benefits by making the junction more

reliable for all road users; with the latest Extra Low Voltage controller hardware, new pedestrian

detection, upgraded SCOOT detection and operational techniques improving junction

performance.

The changes proposed at the Alfred Road / Queen Street junction have been represented in the AQ

model, as a change in average link speed, as shown in Table 6-7.

Table 6-7: Change in speed applied to Alfred Road junction to represent signal improvements

Measure Change in speed to apply to represent signals (kph)

Anglesea Road (Northbound) -2.17 kph

Alfred Road (Southbound) 0.71 kph

Queen Street 0.74 kph

Bishop Crispian Way 0.24 kph

As highlighted above, the changes would need to be implemented gradually and monitored and

refined over time. The NO2 benefits associated with the proposed approach are therefore indicative at

this stage. No modelling of the benefits associated with the improvements proposed at Alfred Road /

Unicorn Road junction has been undertaken.

The incremental impact of the revised proposals is to reduce the average annual NO2 concentration

by an additional 0.1 µg/m3 on Alfred Road, reducing the absolute concentration to 40.2 µg/m3.

6.3.4 Modelling results for the Refined Alternative Package (FBC stage)

As shown in Table 6-6, the FBC Alternative Package:

Small Area CAZ (with approved boundary changes5) + Parking + Revised Alfred Rd signals

scheme

results in a very similar estimate of NO2 concentrations in 2022 (40.2 µg/m3 on Alfred Road, 39.5 µg/m3 on Commercial Road), as the Alternative Package proposed in the Outline Business Case (40.1 µg/m3 on Alfred Road, 39.5 µg/m3 on Commercial Road).

6.3.5 Exemptions, sunset periods, and discounts

6.3.5.1 Proposed exemptions and sunset periods

The cost of replacing or upgrading vehicles to compliant types in time for the introduction of the CAZ

in autumn 2021 could be particularly difficult for some businesses and organisations. We are therefore

proposing to grant exemptions or 'sunset periods' for some types of vehicles where it can be shown

that this will not delay the year in which levels of NO2 are brought within the legal limit.

Exemptions

The national framework exempts the following categories of vehicle: Ultra Low Emissions Vehicles

(tax class 79), Disabled Passenger Vehicles (tax class 85), Military Vehicles, Retrofitted Vehicles,

Historic Vehicles (tax class 88). In addition, the following local exemptions are proposed for:

Emergency Service Vehicles, Specialist HGVs, and Vintage Buses. These exemptions are not

anticipated to have a noticeable impact on NO2 levels at the two exceedance locations, given the

random and / or infrequent nature of the movements. No modelling of impacts has been undertaken.

See Economic Case for further justification for this approach.

Sunset periods

We are also proposing to offer sunset periods for the following vehicle types:

Community and school transport coaches and mini-coaches (two year sunset period)

- This sunset period is not expected to have a noticeable impact on CAZ compliance, given the

limited number of vehicles and trips involved. Impact not modelled. See Economic Case for

further justification for this approach.

5 Removal of Kingston Crescent, Fratton Rd, Fratton Roundabout and Holbrook Rd Roundabout, and Princess Royal Way (not modelled directly).


43

Wheelchair accessible taxis (six month sunset period)

- Within the Portsmouth taxi fleet, there are 101 WAVs (as of Oct / Nov 2020) which make up

just under 10% of the total fleet size, of which 59 are non-compliant vehicles.

- It is expected that the total number of non-compliant taxis will reduce by 2022, due to natural

renewal of the fleet (rather than any CAZ-related upgrade); and similarly, the number of non-

compliant wheelchair accessible taxis would be expected to reduce. However, to take a

conservative approach it has been assumed that all 59 non-compliant WAVs (as per licence

application data from October 2020) remain non-compliant in 2022.

- These 59 vehicles represent 5.4% of the 1085 taxis assumed to be operating in 2022

(assuming the total size of the fleet remains the same as in Oct / Nov 2020).

- In order to calculate the emissions associated with these 59 wheelchair accessible vehicles,

5.4% of the taxi AADT (average annual daily traffic) has been re-allocated from the compliant

to non-compliant taxi category. This results in a 0.3% increase in road NOx emissions, which

translates into a 0.05 µg/m3 increase in the average annual NO2 concentration on Alfred

Road. If the sunset period lasted 6 months, and these vehicles all became compliant in the

second half of the year, the average annual NO2 concentration on Alfred Road would be

0.025 µg/m3.

6.3.5.2 Other exemptions, sunset periods and discounts considered but rejected

Potential exemption for Isle of Wight-bound HGVs and Coaches

Due to the potential negative impact of the CAZ proposal on the Isle of Wight's economy, the

possibility of providing exemptions for HGVs and Coaches travelling to the Isle of Wight via the

Wightlink ferry has been considered.

a) Potential HGV exemption - Table 6-8 shows that exempting non-compliant Wightlink HGVs from the

CAZ charge would result in an increase in the number of non-compliant rigid and artic HGVs on Alfred

Road, and would increase NOx emissions on the road by 2.9%. Assuming no other changes in

vehicle or background emissions, this results in an estimated increase in annual mean NO2

concentration of 0.5µg/m3 on Alfred Road compared to the CAZ B+ scenario.

Table 6-8: Impact of excluding non-compliant Wightlink HGVs from the CAZ charge

Scenario No. of

compliant

Rigid HGVs

No. of

compliant

Artic. HGVs

No. of non-

compliant

Rigid HGVs

No. of non-

compliant

Artic. HGVs

Total HGVs

on Alfred Rd

Total NOx

emissions on

Alfred Rd

(all vehicles)

Original HGV numbers

(CAZ B+ Test 10)

259 432 3 10 715 0.076076

Of which Wightlink account

for:

57 78 15 9 159 -

Adjusted HGV numbers

(Exemption test)

254 423 18 19 715 0.078248

(+2.9%)

The Exemption Test assumes that the compliance level amongst Wightlink HGVs reflects background compliance levels, as

there would no longer be any upgrade of vehicles in response to the CAZ charge. Note, Wightlink have estimated the expected

level of vehicle compliance in 2022, based on discussions with HGV operators. The estimated level of HGV compliance, based

on this feedback, is very similar to the background level assumed within the core model.

b) Potential Coach exemption - Exempting Wightlink coaches from the CAZ charge would result in an

increase in the number of non-compliant coaches on Alfred Road and consequently an increase in

road NOx emissions. Wightlink estimate that in 2022, the number of coach movements may have

dropped from the current 24 movements per day, to 12 movements per day, due to the long term

impact of the coronavirus pandemic (see Section 7-7, COVID-19 Sensitivity Tests).

To estimate the potential impact of additional non-compliant coach movements on Alfred Road, we

have calculated the emissions associated with 12 coach movements, based on:

(i) JAQU-derived compliance assumptions (42% non-compliant / 58% compliant coaches) in

2022;


44

(ii) Wightlink assumptions (50% non-compliant / 50% compliant coaches) in 2022.

The calculated changes in road NOx emissions and estimated changes in NO2 concentrations for

each of these scenarios is shown in Table 6-8. Assuming no other changes in vehicle or background

emissions and based on anticipated natural fleet turnover, an exemption for Wightlink coaches is

calculated to result in an increase in road NOx emissions on Alfred Road of:

(i) 0.86% and an increase in annual mean NO2 concentration of 0.1 µg/m3 compared to the CAZ

B+ scenario (based on JAQU derived compliance assumptions);

(ii) 1.01% and an increase in annual mean NO2 concentration of 0.2 µg/m3 compared to the CAZ

B+ scenario (based on Wightlink compliance assumptions).

Note – As coaches are not modelled explicitly, this sensitivity test assumes that the contribution of

coaches is accounted for in the overall model calibration / validation process.

Table 6-9: Impact of excluding non-compliant Wightlink HGVs from the CAZ charge

Scenario Total NOx emissions on Alfred Rd

(all vehicles; g/km/s))

Annual Mean NO2 Concentration on

Alfred Road

(Receptor 573; µg/m3)

CAZ B+ Test 10 0.076076 40.1

Wightlink Coaches Exemption test

(42% non-compliance)

0.076733 (+0.86%) 40.2

Wightlink Coaches Exemption test

(50% non-compliance)

0.076852 (+1.01%) 40.3

The Coach Exemption Tests assume lower compliance levels amongst Wightlink coaches as there would no longer be any

upgrade of vehicles in response to the CAZ charge. Based on natural fleet turnover it is expected that 42% of coaches would

be non-compliant. Wightlink have estimated the expected level of vehicle compliance in 2022 to be 50%, based on discussions

with coach operators.

These figures could be doubled if the number of coaches using the Wightlink ferry, and travelling via

Alfred Road, returns to current levels (i.e. 24 coach movements per day, on average).

It is noted that the SRTM model does not specifically include coaches as a separate category, so

adding on 12 coaches to the road for this test, may be double counting some of the emissions

calculated in the core scenario.

As expected, providing an exemption for HGVs and coaches travelling on Wightlink ferries results in

increases in road NOx emissions and consequently increases in annual mean NO2 concentrations on

the non-compliant road links: estimated as 0.5µg/m3 for HGVs and 0.1-0.3µg/m3 for coaches. These

increases would very likely result in concentrations on Alfred Road reaching or exceeding the

statutory limit value of 40.49µg/m3.

Potential reduction in CAZ charge for Isle of Wight-bound HGVs travelling at night

In addition, consideration was given to the possibility of reducing the CAZ charge for HGVs choosing

to travel at night, when there is less traffic and vehicles are less likely to be idling in queues. So, for

example, an HGV travelling through the CAZ between 7am and 7pm would be charged £50, but this

would be reduced to £25 if travelling through the CAZ between 7pm and 7am (i.e. overnight). This

would benefit HGV owners directly, and would also address concerns about the economic impact of

the CAZ on the island.

However, this arrangement would be very difficult to administer. In addition, JAQU raised concerns

that this may encourage a lower level of upgrade amongst HGVs, would result in mixed messaging,

and would not be consistent with the expectation that the CAZ should operate 24 hours a day.

Discount for taxi drivers

Feedback to the public consultation raised concerns that residents who use their vehicle for both

commercial use (as a taxi) and private use, would need to pay the CAZ charge regardless of the

purpose of their journey. This is because the ANPR cameras used to detect non-compliant vehicles


45

entering the CAZ will not be able to determine when the vehicle is being used for commercial

purposes and when it is being used for personal trips.

It is currently unknown to what extent taxis are also used as personal vehicles within Portsmouth, or

the ratio of personal against commercial use in cases where they are used for both.

Consideration has been given to charging these drivers for only 5 out of 7 days (equivalent to a

weekly charge of £50, rather than £70). For taxi drivers entering the CAZ on a daily basis, for

commercial or personal trips, this would reduce the daily charge to £7.14. The core model assumes

that the CAZ will result in 90.1% compliance amongst taxis in 2022, based on a £10 daily charge.

However, this percentage is likely to reduce if the daily charge reduces to £7.14.

In order to estimate the impact of the discounted charge on the compliance rate, the current rate of

90.1% has been factored based on the percentage change in compliance rates for different price

points identified in a stated preference survey undertaken for the Sheffield and Rotherham NO2 Local

Plan6.

Using a combination of the PHV and Black Cab behavioural responses for £5, £10 and £20 charge

points in the survey, the survey provided compliance rates of 79.0%, 89.5%, and 91.0% respectively.

Using a (non-linear) growth function to interpolation between £5 and £10 gives an estimated

compliance of 83.1%:

Price point % compliant taxis

Sheffield Survey, £5 CAZ charge 79.0%



Adjusted Sheffield Survey, £7.14 CAZ charge 83.1% (7% lower than the rate for £10)

The differences in compliance rate at each of the price points in the Sheffield survey were then used

to approximate what the compliance rate would be in Portsmouth at that new charge level, such that:

Portsmouth, £10 charge 90.1%

Portsmouth, £7.14 charge 83.7% (7% lower than the rate for £10)

The adjusted Portsmouth compliance rate was then normalised (to sum to 100%) in order to ensure

the appropriate level of AADT was modelled, to arrive at the final 84.7% compliance rate.

The above analysis was conducted using the ‘conservative’ approach outlined in the Sheffield survey,

whereby 'cancelled' trips (leaving industry or working in a different city) are reinstated as compliant

trips, since this was considered the most likely scenario and was what was applied to Sheffield’s

modelling.

Applying the new 84.7% taxi compliance rate to the Emissions Factor Toolkit spreadsheet, shows that

this discount makes very little difference to the emissions within the CAZ. On Alfred Road, the

discount is estimated to result in a 0.08% increase in NOx emissions and <0.01 ug/m3 increase to

modelled NO2, when compared with the ‘without discount’ scenario.

However, JAQU raised concerns regarding this proposal, and it was also rejected at a meeting of the

Executive Board on 30th November 2020.

6 Sheffield and Rotherham Clean Air Zone Feasibility Study, Behavioural Research – Additional Analysis (2018). https://www.sheffield.gov.uk/content/dam/sheffield/docs/pollution-and-nuisance/clean-air-zone/Sheffield%20and%20Rotherham%20CAZ%20-%20Behavioural%20Research%20Modelling%20Note.pdf


46

6.4 Performance of Preferred Package during and after implementation of the SE Hampshire Rapid Transit

Portsmouth City Region has been awarded £55.6 million from the DfT’s Transforming Cities Fund

(TCF) to deliver Tranche 2 of the South East Hampshire Rapid Transit (SEHRT) scheme. In addition,

a further £45 million public and private sector contributions have been secured.

The following infrastructure schemes (see Strategic Case for details) will have a significant impact on

traffic flow in the vicinity of the exceedance links:

PCC10: Lake Road (construction scheduled for Aug 2021 to Oct 2022)

PCC11: City Centre North Link (construction scheduled for Aug 2021 to Mar 2022)

PCC13: City Centre South Link (to be implemented by Mar 2023).

Model testing has therefore been undertaken to determine the impact of the SEHRT scheme on the

performance of the CAZ. Following discussion with JAQU (Oct 2020), it was agreed to model the full

SEHRT package + CAZ B for 2023. This was based on consideration of the following factors:

All traffic modelling for the TCF submission was based on the complete end-state scheme and

picking apart the TCF package to model just those elements in place in 2022 would be very time-

consuming, and not proportionate for a sensitivity test.

Similarly, modelling construction impacts will be very time-consuming as this was not undertaken

for the TCF submission, and final details are yet to be confirmed which would delay any modelling

for the AQ project.

The picture will be changing throughout 2022, so if only some scheme elements are included it

would only provide a snapshot of one point in time.

The only proportionate approach from a traffic modelling perspective is to model the full TCF

package, but modelling a fully operational SEHRT package in 2022 will over-estimate the

benefits.

Within the traffic model, the FBC CAZ+ scenario has been included on top of the end state SEHRT

package. The following additional adjustments have also been made within the Air Quality model:

Link speeds for the four arms of the Alfred Road / Queen Street junction have been increased to

represent the benefits of the signal enhancements, as per Table 6-7, including a 0.7 kph increase

for Alfred Road southbound traffic.

In addition, this test assumes that both hackney carriages and private hire vehicles are permitted

to use Isambard Brunel Road in preference to Alfred Road. In the CAZ B+ / SEHRT traffic model,

Isambard Brunel Road (past the station) is banned to all traffic except buses. It has always been

the intention that hackney carriages (HC) will be permitted to use this link, but as the traffic model

includes hackney carriages and PHVs within the car category, the outputs from the traffic model

assume that no taxis use this link. To model the benefits of allowing both HCs and PHVs to use

Isambard Brunel Road, the contribution that taxis make to NOx emissions on Alfred Road –

Anglesea Road – A2030 have been removed and added to the alternative Isambard Brunel Road

- Stanhope Road - Unicorn Road route. This adjustment involves the following steps:

- Calculate the change in HC and PHV emissions between the 2022 CAZB+ scenario and the

core 2023 CAZ B+ / SEHRT scenario on Alfred Road.

- Assume the difference in HC and PHV emissions is due to taxis being banned from Isambard

Brunel Road. Some of the change will be due to change in compliance between 2022 and

2023, but given that the majority of taxis will have upgraded in response to the CAZ, the

difference in compliance levels will be very small.

- Take the difference in HC and PHV emissions off Alfred Road - Anglesea Road - A2030 and

add to Isambard Brunel Road - Stanhope Road - Unicorn Road.

Table 6-10 shows the Refined Alternative Package CAZ B+ results for 2022 and the CAZ B+ / SEHRT

results for the 2023 opening year. In addition to the implementation of the SEHRT scheme, a key

difference between the two scenarios is in the background fleet, with the 2023 CAZ B+ / SEHRT

scenario benefiting from an additional year of fleet turnover and an increase in the proportion of newer

/ cleaner Euro 6 / VI vehicles in all vehicle categories.


47

Table 6-10: Modelled NO2 (µg/m3) for 2022 CAZ B+ and 2023 CAZ B+ / SEHRT scenarios (Based

on Emissions Factor Toolkit, V9.1b)

Receptor ID Road Name 2022 CAZ B+

Refined Alternative

Package

2023 CAZ B+ /

SEHRTa

Exceedance locations

573 A3 Alfred Road (Unicorn Rd to

Queen St, s/b)

40.2 40.5 (40.49)

546 A3 Commercial Road (south of

Church St Rbt, s/b)

39.5 38.2

Near exceedance locations

526 Church Street (east of Church St Rbt,

n/b) (revised assessment)

<38.7a <38.7a

536 A3 Hope Street (south of Church St

R'bout, s/b)

37.8 37.3

824 A2030 Eastern Road Water Bridge

(s/b)

38.5 36.1

648 A2047 London Road (Stubbington

Ave to Kingston Crescent, s/b)

37.9 36.2

520 Mile End Road (north of Church St

R'bout, s/b)

(36.9) 36.2

557 A3 Marketway (Hope St Rbt to

Unicorn Rd)

(36.2) 34.1

Road sections on the SRN exceeding the statutory limit (40.49 µg/m3)

986 A27 (north of Portsea Island, w/b) 48.2 46.0

1089 A27 (east of Portsea Island, w/b) 46.0 43.1

11 M27 (west of Portsea Island, w/b) 45.3 n/ab

968 A27 (north of Portsea Island, e/b) 43.1 41.7

834 A27 (east of Portsea Island, w/b) 40.8 39.4

Exceedances (>40.49µg/m3) shown in bold, near exceedances (>37µg/m3) shown in grey, lower concentrations

shown in brackets.

Note (a) – In addition to the measures outlined in the Strategic Case, this model run allows all taxis (hackney

carriages and private hire vehicles) to continue to use Isambard Brunel Road, avoiding the need for taxis to divert

via Alfred Road. The original proposal was to only allow hackney carriages to use this route.

Note (b) – the TCF network did not extend as far north to cover receptor 11.

The SEHRT scheme results in a reduction in two-way AADT7 flow on Commercial Road of

approximately 1200 vehicles, based on a comparison of the CAZ B+ only scenario in 2022 and the

CAZ B+ / SEHRT scenario in 2023. This is primarily a result of the improved public transport offer

and re-routing which occurs in response to the City Centre North scheme (including the replacement

of an existing general traffic lane on Commercial Road / Church Street roundabout (northbound) with

a bus priority lane). When combined with the additional year of fleet turnover, the result is a reduction

in emissions on Commercial Road, and a reduction in NO2 concentrations from 39.5 µg/m3 (2022 CAZ

B+ scenario) to 37.7 µg/m3 (2023 CAZ B+ / SEHRT scenario).

However, the SEHRT scheme also results in an increase in AADT flow of approximately 5800

vehicles on Alfred Road. This is primarily a result of the re-routing which occurs in response to the

City Centre South scheme. Specifically, the closure of Isambard Brunel Road (past the rail station) to

general traffic (cars, LGVs, HGVs), resulting in additional traffic using Alfred Road – A3 Anglesea

Road – A2030 Winston Churchill Avenue. This re-routing from Isambard Brunel Road to Alfred Road

7 Average annual daily traffic flow.


48

also applies to HGVs. Despite an additional year of fleet renewal, this results in an increase in

emissions on Alfred Road, and an increase in NO2 concentrations from 40.2 µg/m3 (2022 CAZ B+

scenario) to 40.5 (40.49) µg/m3 (2023 CAZ B+ / SEHRT scenario).

Based on the core assumptions, the above results estimate emissions on Alfred Road to be at the

statutory limit of 40.49 µg/m3 in 2023. No sensitivity tests have been undertaken for the 2023 CAZ B+

/ SEHRT scenario. However, the results presented in Section 7.3 show that changes in meteorological

and surface roughness assumptions would significantly reduce NO2 concentrations, and Section 7.4

highlights the uncertainty around the medium-term impact of COVID-19. Furthermore the analysis

does not take account of Portsmouth’s wider programme of measures to ensure sustainable travel

and improve air quality across the city (see Economic Case, Section 4.6.4); or the closure of Unicorn

Gate to general traffic, which is expected to further reduce NO2 levels on Alfred Road.

Comprehensive monitoring of NO2 and traffic levels will be undertaken following the implementation of

the CAZ, and modifications to the SEHRT scheme or other measures will be considered if necessary.

This could, for example, involve delaying the closure of Isambard Brunel Road to general traffic, to

avoid re-routing via Alfred Road. This would allow additional time for natural renewal of the vehicle

fleet, and to respond to the medium-term impacts of COVID-19 on travel behaviour.

In addition, it is proposed that all taxis (hackney carriages and private hire vehicles) will be permitted

to use Isambard Brunel Road (as per the option tested in Table 6-10), avoiding the need for taxis to

divert via Alfred Road. The original proposal was to only allow hackney carriages to use this route.

Impact during implementation (i.e. in 2022)

The potential impact of the SEHRT scheme during 2022 can be summarised as follows:

Infrastructure measures will be partly implemented in 2022, but the bus service improvements are

unlikely to be in place until 2023. This means that the adverse impacts of the infrastructure

measures in terms of reduced capacity for general traffic may be apparent, but without the mode

shift benefits that will occur in 2023 and without the benefit of an additional year of fleet renewal.

Construction works could result in additional delay to traffic.

Both factors could reduce the likelihood of achieving NO2 compliance in 2022. The most significant

risk relates to the City Centre South scheme and closure of Isambard Brunel Road (past the rail

station) to general traffic (cars, LGVs, HGVs), resulting in additional traffic using Alfred Road. It has

therefore been agreed that the construction works on this phase of the scheme will be postponed until

late 2022 / early 2023, as far as possible, so as not to impact Alfred Road NO2 concentrations in

2022. In addition, we will seek to mitigate the impact of construction works across all three SEHRT

schemes located within the CAZ. The impact of the SEHRT schemes on NO2 concentrations on

Commercial Road and Alfred Road in 2022 is expected to be small; especially when balanced against

the benefits of the scheme more widely across the city in delivering modal shift.


49

7. Limitations and Assumptions

The city-wide modelling of transport and air quality options is complex and time consuming, and the

project is working to a time and cost budget that has impacted on the number of scenario tests and

analysis that can be undertaken. The impact of time/ budget constraints has been minimised through:

a thorough review of modelling assumptions and outputs with key stakeholders;

a set of sensitivity tests to assess the robustness of the conclusions.

The limitations of the study are provided in greater detail in the Analytical Assurance Statement. A

summary of some of these key limitations or assumptions made are given below.

7.1 Local Air Quality Model Limitations

The air quality modelling relies on modelled traffic data from the Sub-Regional Transport Model

(SRTM). The model has been factored up from a 2015 baseline to the air quality model years of 2018

and 2022 based on a linear extrapolation, conducted by the Systra transport team.

The vehicle fleet in Portsmouth has been obtained from the ANPR survey, which registered more than

8 million vehicle movements. This was used to provide a breakdown of vehicle type and

disaggregation by Euro emission standard by matching to the DVLA database. Although this was only

conducted for one neutral week of the year, this data is considered to be more reliable than using

national fleet assumptions. Further analysis of the ANPR data has also been conducted to gain more

detailed information on specific vehicle types, for example:

Taxis with black cab body types (e.g. LTI TX4) have been matched based on their make and

model in the ANPR data;

Private hire and hackney carriages that have the same make and model types as private cars

were identified in the car fleet by matching the number plates of those taxis in Portsmouth

against the raw ANPR data. Taxis licensed outside of Portsmouth but travelling in were treated as

cars;

Public buses could be identified in the ANPR database based on their make and model as these

were provided by the two main bus operators in Portsmouth (Stagecoach and First). The Euro

emission standard of the bus fleet was further refined based on known information from the

operators;

Information on private coaches was provided and incorporated into the fleet assumptions where

possible. For example, National Express, who operate 117 Euro 6 coaches around Gunwharf

Quays/the Hard Interchange.

The baseline air quality modelling that has been completed has used the best and most up-to-date

available data and tools, including the latest emissions information from JAQU within EFT v.9.1b,

which contains information on current and projected vehicle fleets and emissions for different road

types in urban/rural areas. These updated tools were released midway through the modelling study,

so a significant amount of time and effort was required in order to incorporate these updates.

However, these sets of data represent the latest available information and evidence on future vehicle

fleets and background concentrations, so it was considered essential to utilise them. This also

ensures consistency with other 3rd wave JAQU studies.

EFT v9.1.b enables the user to define the proportion of each vehicle type that is registered as a

specific Euro emission standard within the fleet, which, whilst based on the ANPR data, is for the

purposes of the modelling regressed or progressed to be representative of the relevant year from the

2019-representative data that was captured within the ANPR. This tool has been provided at the

request of JAQU and is therefore considered a robust methodology. The guidance on the petrol/diesel

projection tool in the EFT wasn’t available at the time of modelling so this wasn’t included at target

determination stage. Further investigations in using this tool and impact on future car split for

compliant and non-compliant vehicles have been undertaken as part of the model refinements.

Interim years between the modelled base year and projected year of compliance have been

interpolated rather than explicitly modelled.


50

For the CAZ option models, national assumptions have been used on the response to the CAZ, in

terms of compliance rates and whether vehicles will replace or upgrade a vehicle, or avoid the charge

etc. A sensitivity test has been conducted to consider a more pessimistic compliance rate for HGVs as

outlined in Section 7.3

7.2 Transport Model Limitations

Traffic flows have been extracted from the existing SRTM (covering the areas of Southampton,

Portsmouth and South Hampshire), which has been validated to 2015.

The data used to build, calibrate and validate the SRTM includes roadside interview surveys (RSIs),

screenline, manual classified and automatic traffic counts, automatic number plate recognition

(ANPR) and TrafficMaster data for journey times. More detailed information is included in document

T2.

Local fleet composition data was derived from an analysis of a comprehensive automatic number

plate recognition (ANPR) camera survey covering 86 sites across the city over the period of 18th to

25th March 2019. This has been used to provide both compliant/non-compliant split in the traffic

model.

7.3 Core Sensitivity Tests

The following section sets out the results of various sensitivity tests undertaken to assess the

robustness of the Alternative Package, in terms of ensuring compliance is achieved in 2022. The

tests undertaken involve changes to both the transport and air quality assumptions which inform the

modelling process:

Category Description of sensitivity tests undertaken

Transport

assumptions

HGV pay charge response assumptions - Sensitivity test undertaken assuming a doubling / quadrupling of

the percentage choosing to pay the charge and continue with a non-compliant vehicle, reducing the

proportions of the other responses as in Table 7-2.

HGV trip rate assumption – Upper bound sensitivity test undertaken assuming each HGV makes only one

trip into the CAZ per day (resulting in a charge of £50 per day) rather than multiple trips.

Air quality

assumptions

Metrological assumptions - ADMS-Roads run with 2017 and 2016 meteorological year from Thorney Island

(to compare against 2018 data used from the same sites for core tests).

Surface roughness assumption - ADMS-Roads run with a modified surface roughness to represent the more

built up conditions in the city centre

The sensitivity tests were undertaken at OBC stage using earlier versions of the Alternative Package:

HGV daily trip rate assumption – Small Area CAZ B only;

HGV charge response, meteorology, and surface roughness assumptions – Small Area CAZ B +

parking measures + strategic cycling routes.

The results are therefore presented in Table 7-1 in terms of the scale of change associated with each

sensitivity scenario, i.e. change in modelled NO2 (µg/m3). In practice, there is very little difference in

the NO2 concentrations at Alfred Road and Commercial Road for the various versions of the

Alternative Packages used to undertake these sensitivity tests at OBC stage, and the Refined

Alternative Package presented in this FBC (see Table 6-6). The results for the FBC Refined

Alternative Package are therefore presented alongside the OBC sensitivity results, to demonstrate the

impact of the scenarios considered on the FBC Refined Alternative Package.

Table 7-1 shows that in all cases the absolute concentrations on the exceedance and near

exceedance links remain below the EU limit for NO2 concentrations of 40.49 µg/m3.


51

Table 7-1 Impact of sensitivity tests on modelled NO2 (µg/m3) concentrations in 2022 – change in modelled NO2 (µg/m3)

Receptor

ID Road Name Refined

Alternative

Package

HGV pay charge assumption Meteorological

test

(2017 met year)

Meteorological

test

(2016 met year)

Surface

roughness test

(high surface

roughness)

Double

national av.

Quadruple

national av.


573 A3 Alfred Road (Unicorn Rd to Queen St) 40.2 +0.1 +0.3 -0.6 -0.3 -0.7

546 A3 Commercial Road (south of Church

St Rbt)

39.5 0.0 +0.1 +0.4 0.0 -0.5

Near exceedances (37 µg/m3)

526 Church Street (east of Church St Rbt)


<38.7a 0.0 +0.1 -0.4 -0.5 -0.4

536 A3 Hope Street (south of Church St R'bout) 37.8 0.0 +0.1 -1.3 -0.5 -0.5

824 A2030 Eastern Road Water Bridge 38.5 0.0 +0.1 +1.5 +0.9 +0.4

648 A2047 London Road (Stubbington Ave to

Kingston Crescent)

37.9 +0.1 +0.1 +0.1 +0.1 -0.2

520 Mile End Road (north of Church St R'bout) (36.9) 0.0 +0.1 +0.7 +0.2 -0.2

557 A3 Marketway (Hope St Rbt to Unicorn Rd) (36.2) +0.1 +0.2 -0.9 -0.3 -0.6

Road sections on the Strategic Road Network exceeding the EU limit (40 µg/m3) in 2022

986 A27 (north of Portsea Island, w/b) 48.2 +0.1 +0.1 -1.8 -0.4 -0.4

1089 A27 (east of Portsea Island, w/b) 46.0 0.0 0.0 +1.6 +1.3 -0.4

11 M27 (west of Portsea Island, w/b) 45.3 0.0 0.0 -1.8 -0.5 -0.6

968 A27 (north of Portsea Island, e/b) 43.1 -0.3 -0.2 +2.0 -0.6 +0.1

834 A27 (east of Portsea Island, w/b) 40.8 0.0 +0.1 +0.1 +0.3 +0.8

Sensitivity test exceedances (>40.49µg/m3) highlighted in grey.

Note a: The concentration at Church Rd has not been modelled directly, but a CAZ reduces traffic levels compared with baseline, and improves average fleet emissions

compared with the baseline. It therefore follows that the concentration will follow the same trend as at all other sites and be lower than the baseline concentration.


52

7.3.1 Change in transport assumptions

HGV upgrade sensitivity test (response to HGV charge)

For the core / central scenario, assumptions regarding the responses of HGV drivers to a CAZ are

based on the national assumption provided by JAQU. This assumes that 9% of non-compliant trips

are made by HGV drivers who choose to pay the £50 indicative CAZ charge, with most (83%) made

in upgraded vehicles. It is likely that the proportion choosing to pay the charge will differ at a local

level. Two pessimistic sensitivity scenarios (Table 7-2) have therefore been modelled based on the

assumption that the number choosing to upgrade would be twice (18%) or four times (36%) the

national assumption (9%); resulting in a corresponding reduction in the proportion choosing to

upgrade, avoid the CAZ, or cancel their trip, and a lower impact in terms of reducing NO2

concentrations. No changes were made to other vehicle types in the fleet.

Table 7-2 HGV response assumptions for the core scenario and sensitivity tests

Central / Core Scenario Sensitivity Test 1 Sensitivity Test 2

Upgrade 83% 74.8% 58.4%

Avoid 4% 3.6% 2.8%

Cancel 4% 3.6% 2.8%

Pay charge 9% 18% 36%

Table 7-1 shows that the impact of increasing the percentage paying the charge to 18% is very small,

with increases of less than 0.1 µg/m3 predicted at receptors within the city centre compared to the

central / core test, and concentrations remaining below the statutory Limit Value at other locations

within the city. Increasing the percentage paying to 36% also results in relatively small increases in

concentrations within the city centre, with the maximum increase occurring at Alfred Road. This

estimated increase of 0.3 µg/m3 at Alfred Road would result in concentrations just reaching the limit

value. These tests therefore suggest that the CAZ would deliver compliance even with approximately

36% of non-compliant HGV trips paying the CAZ charge rather than using upgraded vehicles.

There are two reasons for the small response:

Firstly, although the percentage change in trips forecast to pay is large, the responses of upgrade,

avoid and cancellation still account for the majority of trips. By 2022, the natural compliance for

HGVs is forecast to be 82% meaning that, as a starting point, CAZ charges would only apply to

18% of the HGV fleet that interact with the CAZ area (i.e. in the Core scenario it is 9% of the non-

compliant 18% that pay the CAZ charge etc).

The second point is that the proposed CAZ area is relatively small so the number of HGVs that

interact with the charging area is therefore limited. In combination, these factors mean that the

actual number of HGVs where behavioural responses are relevant is modest.

HGV trip rate assumption

The daily trip rate and therefore average charge per trip for HGVs assumed in the traffic model only

influences routing choices. The upgrade and cancellation responses are exogenous inputs to the

model based on the JAQU national averages, with their own underlying assumptions on average daily

trip rates. Therefore, the key potential influence of a revised modelled daily trip rate is on the number

of HGVs choosing to re-route in order to avoid paying the charge.

However, the majority of HGVs paying the charge in the core test have either an origin or destination

in the CAZ area and therefore would not benefit from rerouting. The traffic flow plots for the core and

sensitivity scenarios confirm this, showing very little difference in flows, with any changes most likely

attributed to model noise. Sensitivity of the modelled result to the assumed daily trip rate is therefore

very low.


53

7.3.2 Change in air quality assumptions

Impact of changes to metrological assumptions.

For the core / central scenario, the ADMS-Roads model was run for the 2018 Base Year with 2018

meteorological data, with the same set of data used for the 2022 Future Year models. As pollutant

concentrations can vary significantly from year to year due to the influence of meteorological

conditions, sensitivity tests have been conducted using meteorological data from 2017 and 2016 from

the Thorney Island Meteorological Office site. The dominant wind direction in all years is from the

south-west, but there are variations seen from year to year as shown in Figure 7-1. For example, the

wind directions in 2016 and 2018 are similar with winds also coming from the north-east, whereas in

2017, the wind direction was predominantly distributed from south-west to west. Wind speeds were

highest in 2016, and lowest in 2017.

Figure 7-1: Wind roses (wind speed/direction) at Thorney Island Met Office site

The sensitivity results show that NO2 concentrations at the locations of concern are broadly similar for

each of the three years of meteorological data used, but there are variations in concentrations

between different receptor locations, as concentrations go down in some years, whilst others go up

(Table 7-1). These differences are due to changes in the wind direction/speed in each year in relation

to the orientation of the road and position of the receptor relative to this.

For example, receptor 546 (A3 Commercial Road) has the same NO2 concentration in 2016 and 2018

but levels are higher in 2017. This site is located to the east of a road going north-south. In 2017, as

the wind direction is predominately from south-west/west this will blow road traffic emissions across

the road towards the receptor more often than in other years, resulting in a higher annual mean

concentration.

Conversely, concentrations at receptor 573 (A3 Alfred Road) go down in 2016 and 2017. This receptor

is located south of a road that is orientated on a north-east to south-west axis, so the higher number

of days with wind direction coming from east in 2018 will result in the emissions from the road being

blown towards the receptor on more occasions compared to the other years when the wind direction

is more like the 2018 trend.

Concentrations of NO2 on the two exceedance links remain below the statutory limit of 40.49 µg/m3 in

all meteorological conditions, and below 38.7µg/m3 at all near exceedance locations within the City.

The biggest increase in NO2 concentration occurs on Eastern Road Water Bridge, where the

meteorological conditions in 2017 and 2016 result in an increase of 1.5 and 0.9 µg/m3 respectively,

relative to 2018 conditions. However, in all scenarios, the NO2 concentration at Eastern Road Water

Bridge remains below 40.0 µg/m3.

Impact of changes to surface roughness assumptions


54

The surface roughness (SR) parameter within ADMS-Roads model takes into account the texture of

the ground (i.e. what the surface topography is like and how built-up it is). This determines how air

flow interacts with the ground and affects the level of NO2 concentration.

For the core / central scenario, a surface roughness value of 0.5m was applied across the whole of

the Portsmouth study area, corresponding to “open suburbia” conditions in the model. This was

considered appropriate to reflect the average conditions across the large study area.

However, as the exceedance locations are situated within the city centre, a sensitivity test has been

conducted to examine the effects of applying a higher SR value (1.5m rather than 0.5m) within the

ADMS-Road model, to represent the more built up nature of the city centre.

The results of this test demonstrate that overall, the higher SR value results in lower modelled road

NOx at most locations. A higher surface roughness generally results in more turbulence and faster

dispersion of emissions. The majority of the receptor locations are therefore predicted to have lower

NO2 concentrations compared to the core scenario. Some receptors, however, are predicted to have

slightly higher NO2 concentrations (e.g. receptor 824 on Eastern Road Water Bridge) due to the

higher model verification factor compared to that applied in the core / central test.

Road NOx concentrations (and therefore NO2 concentrations) are higher at a small number of

receptors that are located on elevated sections of road (e.g. specific sites on the A27 and M27). This

is because due to emissions are not expected to disperse so rapidly away from the road above the

receptor.

The modelled NO2 concentrations on the exceedance links reduce by 0.7 and 0.5 µg/m3 on Alfred

Road and Commercial Road respectively (see Error! Reference source not found.); providing

confidence that the statutory limit will be achieved on both these links. The NO2 concentrations

on the near exceedance links reduce by up to 0.6 µg/m3 (with the exception of Eastern Road Water

Bridge), which provides certainty that the annual concentrations will also remain below the EU limit at

all these sites (including Eastern Road Water Bridge).

Summary

Overall, the air quality sensitivity tests, suggest that the core / central scenario represents a

pessimistic or worst-case picture in terms of the assumed meteorological conditions and surface

roughness (urban / built-up) conditions.

In terms of the transport assumptions, a doubling of the proportion of HGVs trips choosing to pay the

£50 indicative CAZ charge would result in only a very small increase in concentrations. It would take

the proportion of trips choosing to pay (and associated reduction in numbers using upgraded vehicles)

to increase to ~36% (quadrupling from the national average) to cause an increase in concentrations

that would cause concentrations at the Alfred Road receptor to reach the limit value. Changes in the

average number of HGV trips per vehicle per day assumed has very little impact on flows and

emissions.

Based on the findings of these sensitivity tests, the results presented in this study provide confidence

that the statutory limit will be achieved on both exceedance links, and that concentrations will

remain below the statutory limit at all ‘near exceedance’ sites.

7.4 COVID-19 Sensitivity Tests

The pandemic has the potential to influence future NO2 concentrations, by impacting future travel

behaviour, the economy (affecting both the volume of travel and the rate at which vehicles are

upgraded), and background NO2 levels.

The proposed Alternative Package (CAZ B+) is predicted to bring forward compliance from 2023 to

2022. Modelling shows (see Table 7-3) that the Alternative Package will not achieve compliance

with the statutory limit for NO2 in 2022 if there is a one year lag in the background vehicle

upgrade rate. This is because the core model assumes a substantial reduction in the proportion of

non-compliant petrol cars, taxis, LGVs and HGVs between 2021 and 2022, in line with JAQU’s

Emission Factor Toolkit v1.9b. However, if drivers choose to delay upgrading their vehicles for a year,

the proportion of older, more polluting vehicles on the road will remain at a higher level for longer,

resulting in a higher level of NOx emissions and higher NO2 concentrations.


55

Table 7-3 Impact of a one year lag in vehicle upgrade rate on modelled NO2 (µg/m3) concentrations in 2022

Receptor

ID Road Name Refined Alternative

Package

Paused natural fleet

turnover with core CAZ

upgrade assumptions


turnover with 0% CAZ

upgrade assumptions


turnover with core CAZ

upgrade assumptions

+ 7% reduction in AADT


573 A3 Alfred Road (Unicorn

Rd to Queen St)

40.2 +1.4

Above statutory limit

+2.4


+0.2

Below statutory limit

546 A3 Commercial Road

(south of Church St Rbt)

39.5 +1.4


+1.7


+0.3

Below statutory limit

Near exceedances Below statutory limit Below statutory limit Below statutory limit Below statutory limit

Assumptions

Vehicle fleet 2022

background levels

Paused at

2021 background levels

Paused at


Paused at


Traffic levels 2022 flows 2022 flows 2022 flows 93% of 2022 flows

Background NO2 2022 levels 2022 levels 2022 levels 2022 levels

% upgrading in response to CAZ

83% HGVs,

100% buses and

coaches, 90% taxis

83% HGVs,

100% buses and coaches,

90% taxis

0% HGVs,


0% taxis

83% HGVs,


90% taxis

Sensitivity test exceedances highlighted in grey.

For practical purposes, the above sensitivity tests were undertaken using an earlier version of the Alternative Package, which included cycling measures,

excluded the Alfred Road traffic signal improvements, and was based on the boundary proposed at OBC stage. The results are therefore presented above in

terms of the scale of change associated with each sensitivity scenario, i.e. change in modelled NO2 (µg/m3). In practice, there is very little difference in the

NO2 concentrations between the version of the Alternative Package used to undertake these tests and the Refined Alternative Package presented in this FBC

(40.3 v 40.2 µg/m3 at Alfred Road, and 39.5 v 39.5 µg/m3 at Commercial Road). The results for the FBC Refined Alternative Package are therefore presented

alongside the sensitivity results, to demonstrate the impact of the scenarios considered on the FBC Refined Alternative Package.

.


56

A 7% reduction in traffic on Alfred Road and a 2-3% reduction on Commercial Road would be

required in order to achieve compliance with the limit value, assuming a one year pause / lag

in natural fleet turnover. This would need to apply to all modes.

A 7% reduction in total traffic is unlikely as a result of a downturn in the economy only, but is feasible

in the context of a prolonged COVID-19 impact. In mid-Sep 2020 (when schools had re-opened and

restrictions were at their most relaxed) traffic in Portsmouth had recovered to 86% of equivalent 2019

levels. Given the uncertainty around the duration of COVID-19, it is possible that traffic levels will

remain below expected levels (i.e. under the pre-COVID-19 conditions assumed for the OBC) into

2022. If this is the case, a 7% reduction in total traffic in 2022 is a possibility.

Further analysis has also been undertaken to examine the impact of:

a long term reduction in HGV traffic, due to a downturn in the economy8; and

an increase in car traffic, due to a reluctance to return to public transport;

assuming a one year pause / lag in natural fleet turnover.

On the first point, a reduction in HGV traffic alone would not achieve compliance. Even if virtually all

HGVs (i.e. 95%) disappeared from the network, the vehicle emissions on Alfred Road would exceed

the levels for the Preferred Package (by ~11%), resulting in a likely exceedance of the statutory limit.

This is because the absolute number of non-compliant HGVs accounts for a low proportion of the

overall traffic. Total HGVs (compliant and non-compliant) account for just 3% of the flow on

Commercial Road and 4% on Alfred Road.

On the second point, any increase in car traffic will reduce the likelihood of achieving compliance in

2022.

Potential impact on coach traffic

Data provided by Wightlink (September 2020) shows that average daily coach crossings have

reduced significantly as a result of the coronavirus pandemic. Average daily coach crossings were 24

in 2019, but have dropped to just 6 per day in 2020 (based on actual figures to September 2020, and

live bookings for the remainder of the year). Live bookings for October, November and December

2020 are between 44% and 59% of the equivalent 2019 figures.

Bookings for 2021, to date, suggest that demand could be 35% lower than in 2019. Overnight coach

trips (e.g. for PGL holidays) are not expected to start until Spring 2021 at the earliest. Furthermore,

Wightlink estimate that there could be 50% fewer crossings in 2022 (i.e. 12 rather than 24 per day).

To estimate the potential impact of 12 fewer coach movements on Alfred Road, we have calculated

the emissions associated with 12 coach movements, based on:

(i) JAQU-derived compliance assumptions (42% non-compliant / 58% compliant coaches) in

2022;

(ii) Wightlink assumptions (50% non-compliant / 50% compliant coaches) in 2022.

This results in a (i) 1%, and (ii) 1.2% reduction in NOx emissions in 2022.

This would reduce baseline NO2 concentrations at Alfred Road from 41.7 µg/m3 to 41.5 ug/m3. A

similar order of impact (i.e. -0.2 µg/m3) could be expected if applied to the CAZ B+ Refined Alternative

Package.

Note – As coaches are not modelled explicitly, this sensitivity test assumes that the contribution of

coaches is accounted for in the overall model calibration / validation process.

8 Average daily traffic data for mid-September 2020 (when schools had re-opened and restrictions were at their most relaxed), shows that volumes of HGVS, LGVs, and buses had only returned to 78% of the equivalent figure for September 2019.


57

Appendix A Model Verification

Model verification is the comparison of modelled results versus monitoring results at relevant

locations. It is the process by which a factor is derived to adjust modelled concentrations so that the

final modelled concentrations are representative of monitoring information in the area.

Model verification was undertaken using monitoring sites close to the modelled road links. The

measurement sites used for the verification are set out in Table A.1.

Uncertainty in modelled estimates has been considered by calculating root mean square error

(RMSE) and fractional bias statistics. The fractional bias of the model may be used in order to identify

if the model shows a systematic tendency to over or under predict. An air quality model can be

considered to perform reasonably well where modelled concentrations are within 25% of monitored

concentrations in accordance with DEFRA’s Technical Guidance LAQM.TG(16). The RMSE should

ideally be within 10% of the relevant air quality criterion (4 µg/m3 for the NO2 annual mean limit value

of 40 µg/m3), but is acceptable where it is within 25% of the relevant air quality criterion (10 µg/m3).

The single verification factor derived for Portsmouth was 1.61. Note that the diffusion tubes on Church

Street (32A, 32B) were excluded from the model verification process following the Church Street

sensitivity study. The inclusion of these sites would result in a lower verification factor. As the traffic

data is considered to be overestimated on Church Street, the two diffusion tubes were excluded to

avoid falsely reducing the verification factor.

The RMSE was calculated to be 3.4 µg/m3 (less than 10% of the NO2 annual mean limit value). The

fractional bias was calculated to be 0.0. Therefore, the model is considered to perform well across the

entire study area.

Table A- 1 Monitoring Sites Used in Verification

Site ID X Y Total monitored

NO2 (µg/m3)

Total modelled NO2

(verification factor

of 1.61)

% difference

Modelled vs

Monitored NO2

DT1 463872 99874 42.9 44.5 3.7%

DT4 463190 100390 34.0 36.6 7.6%

DT5 464230 102194 28.1 29.4 4.6%

DT6 464331 102197 30.9 30.5 -1.1%

DT7 464291 102279 27.7 27.6 -0.5%

DT9 465621 105528 36.7 34.5 -6.0%

DT11 466883 103448 25.5 29.9 17.3%

DT15 466120 101324 27.6 30.5 10.4%

DT19 466392 100226 37.7 34.6 -8.2%

DT20 466712 99415 28.4 26.1 -8.0%

DT21 465209 98964 36.5 27.3 -25.2%

DT22 464778 99306 29.3 30.7 4.9%

DT23 464974 99766 37.6 35.8 -4.8%

DT24 465111 100737 36.8 31.6 -14.1%


58

Site ID X Y Total monitored

NO2 (µg/m3)

Total modelled NO2

(verification factor

of 1.61)

% difference

Modelled vs

Monitored NO2

DT25 465036 101547 38.2 33.9 -11.2%

DT30 464478 101457 39.2 36.3 -7.5%

DT34 464425 100893 33.3 42.8 28.5%

DT35 463837 99759 30.1 33.9 12.7%

DT36 464501 99329 30.6 27.2 -11.0%

DT55 463224 99590 25.4 23.2 -8.8%

DT58 463487 99659 29.3 30.9 5.5%

DT61 466136 100610 33.7 30.8 -8.5%

DT65 466681 100373 28.2 30.5 8.2%

DT70 466667 99546 25.1 25.2 0.3%

DT76 466002 102053 31.2 32.4 3.5%

DT78 466523 99599 25.0 23.6 -5.6%

DT86 465201 99734 28.9 26.3 -9.0%

DT87 465183 99904 27.3 27.9 2.1%

DT90 466095 100813 24.0 27.9 16.4%

DT91 466070 100819 26.7 28.0 4.8%

DT92 466525 99736 27.3 25.6 -6.1%

DT93 464826 99500 35.0 32.7 -6.5%

C2 464925 102129 40.6 37.0 -8.7%

C6 466004 102348 34.0 33.9 -0.3%


59

Appendix B Supporting Information

Figure B- 1 Study Area showing PCM Links and 50m Buffer


60

Figure B- 2 Location of Street Canyons


61

Figure B- 3 Location of Flyovers and Bridges


62

Figure B- 4 Exceedances of Annual Mean NO2 Limit Value, 2018

Figure B- 5 Monitoring Locations


63

Figure B- 6 Wind Rose, Thorney Island (2018 data)

\\Ukcrd1fp001\ukcrd1fp001-v1ie\projects\Environmental Services - Portsmouth ORTMCS AQ\03 EXECUTION\Modelling\Met data\Thorney_Island_18.met

0

0

3

1.5

6

3.1

10

5.1

16

8.2

(knots)

(m/s)

Wind speed

0°

30°

60°

90°

120°

150°

180°

210°

240°

270°

300°

330°

300

600

900

1200


64

Figure B- 7 Receptor Locations


65

Figure B- 8 Source Apportionment- Diesel Cars 2018 (L) and 2022 (R)


66

Figure B- 9 Source Apportionment- Petrol Cars 2018 (L) and 2022 (R)


67

Figure B- 10 Source Apportionment- Full Hybrid Diesel Cars 2018 (L) and 2022 (R)


68

Figure B- 11 Source Apportionment- Full Hybrid Petrol Cars 2018 (L) and 2022 (R)


69

Figure B- 12 Source Apportionment- Artic HGVs 2018 (L) and 2022 (R)


70

Figure B- 13 Source Apportionment- Rigid HGVs 2018 (L) and 2022 (R)


71

Figure B- 14 Source Apportionment- Diesel LGVs 2018 (L) and 2022 (R)


72

Figure B- 15 Source Apportionment- Petrol LGVs 2018 (L) and 2022 (R)


73

Figure B- 16 Source Apportionment- Buses and Coaches 2018 (L) and 2022 (R)


74

Figure B- 17 Source Apportionment- Taxis 2018 (L) and 2022 (R)


75

Figure B- 18 Source Apportionment- Motorcycles 2018 (L) and 2022 (R)


76

Table B- 1 Details of automatic monitoring locations

Site ID Site Name

Site Type X OS Grid Ref

Y OS Grid Ref

Pollutants Monitored

In AQMA?

Monitoring Technique

Distance to Relevant Exposure (m)

Distance to kerb of nearest major road (m)

Inlet Height (m)

C2 London Road

Kerbside 464925

102129

NO2 PM2.5 PM10

Y Chemiluminescent, HORIBA's APDA- 372

1.8m of the kerbside further to the south of the station

1m 1.8m

C4 Gatcombe Park Primary School

Urban Background

465403

103952

NO2 PM10 PM2.5 O3

N Chemiluminescent, FDMS

0m 119 m 2.5m

C6 Burrfields Road

Roadside 466004

102348

NO2 PM10

N Chemiluminescent, Eberline

0.5m 4.5m of Burrfields Road & 5.5m of Copnor Road

1.8m

C7 Mile End Road

Roadside 464397

101270

NO2 PM2.5 PM10

Y Chemiluminescent HORIBA's APDA- 372

2m 6.5m 1.8m

DEFRA

Anglesea Road

Roadside 463835

100259

NO2 PM10

Y Chemiluminescent; FDMS

2m 6.5m 1.8m


77

Table B- 2 Details of diffusion tube locations

Site ID

Site Name Site Type X OS Grid Ref

Y OS Grid Ref

Pollutants Monitored

In AQMA?

Distance to Relevant Exposure (m)

Distance to kerb of nearest road (m)

Tube collocated with a Continuous Analyser?

Height (m)

1 Lord Montgomery Way (FST) Roadside 463872 99874 NO2 Y 0 3.7m N 2m

2 12 Chadderton Gardens (CG-12) Urban background 463705 99371 NO2 N 0 N/A N 2m

3 High Street (HS-121A) Roadside 463408 99460 NO2 Y 0 3.1m N 2m

4 Queen Street (QS-Col 30) Roadside 463190 100390 NO2 Y N/A 3m N 2m

5 119 Whale Island Way (WIW-119) Roadside 464230 102194 NO2 N 0 16.23m N 2m

6 88 Stanley Road (SR-88) Roadside 464331 102197 NO2 N 0 9.88m N 2m

7 138 Lower Derby Road (LDR-138) Urban background 464291 102279 NO2 N 0 37.57m N 2m

8 492 Hawthorn Crescent (HC-492) Urban background 466690 104355 NO2 N 0 34m N 2m

9 6 Northern Road (NR-6) Roadside 465621 105528 NO2 N 0 5.43m N 2m

10 20 Stroudley Avenue (SA-20) Urban background 467107 104850 NO2 N 0 N/A N 2m

11 Anchorage Road (AR-Col6) Roadside 466869 103457 NO2 N 11.76M 6.56m N 2m

14 4 Merlyn Drive (MD-4) Roadside 466109 103736 NO2 N 0 11.26m N 2m

15 29 Milton Road (MR-29) Roadside 466120 101324 NO2 N 0 7.04m N 2m

16 Parade Court, London Road (LR-PC) Roadside 465474 104205 NO2 N 5.32m 5.15m N 2m

18 4 Milton Road (MR-4) Roadside 466097 101332 NO2 N 0 6.13m N 2m

19 7 Velder Avenue (VA-7) Roadside 466392 100226 NO2 Y 0 4.44m N 2m

20 136 Eastney Rd (ER-136) Roadside 466712 99415 NO2 N 0 6.23m N 2m

21 118 Albert Road (AR-116) Roadside 465209 98964 NO2 N 0 2.36m N 2m

22 2 Victoria Road North (VRN-2) Roadside 464778 99306 NO2 N 0 5.53m N 2m

23 106 Victoria Road North (VRN-106) Roadside 464974 99766 NO2 N 2.37m 2.42m N 2m

24 221 Fratton Road (FR-221) Roadside 465111 100737 NO2 Y 0 4.21m N 2m

25 117 Kingston Rd (KR-117) Roadside 465036 101547 NO2 Y 0 2.46m N 2m

26 The Tap London Road (Tap) Kerbside 464900 101976 NO2 Y 0 1.91m N 2m

30 Market Tavern (Mile End Rd) (MT) Roadside 464478 101457 NO2 Y 0 12.73m N 2m

32 Larch Court, Church Rd (CR-Corner) Roadside 464559 100980 NO2 N 0 5.84m N 2m

34 Sovereign Gate, Commercial Rd (UF) Roadside 464425 100893 NO2 Y 0 4.40m N 2m

35 Hampshire Terrace (AM) Roadside 463837 99759 NO2 N 0 4.9m to 10.74m

N 2m

36 Elm Grove (EG-103) Roadside 464501 99329 NO2 N 0 2.26m N 2m

54 Anglesea Road, Victoria Park, Column 234 (AR-VP-Col)

Roadside 463835 100257 NO2 N 0 1.5 N 2 m

55 Gunwharf Road, Column 12 (GWR-Col12) Roadside 463224 99590 NO2 n 0 1.5 m N 2m

56 Gunwharf Road, Column 4 (GWR-Col4) Roadside 463261 99782 NO2 N 0 1.5 m N 2m

58 St Georges Street-9 (St GS-9) Roadside 463487 99659 NO2 N N/A 6 N 2m

65 Mooring Way-12 (MW-12) Roadside 466681 100373 NO2 N 11.76M 1.5 m N 2m

70 Milton Primary School (ER-DS) Roadside 466667 99546 NO2 N 0 5 m N 2m

92 Locksway Road-13 (LR-13) Roadside 466525 99736 NO2 N 0 2.5 m, N 2m

104 219 Jervis Road Urban background 464120 102717 NO2 N 0 4 m N 2m


78

105 Column 8 Tipner Urban background 464097 102773 NO2 N N 2m

106 24 Tipner Urban background 464046 102932 NO2 N 0 N 2m

107 Column 3 Tipner Urban background 464058 103007 NO2 N 0 N 2m

112 Medina School Fratton Road (MS1) Urban background 465116 101029 NO2 N 0 30 m N 2m

113 Medina School Fratton Road (MS2) Roadside 465119 101015 NO2 N 5.32m 30 m N 2m

114 233 Southampton Road Roadside 462331 105651 NO2 N 0 6 m N 2m

115 Catholic Church St Agatha's Church Market Way

Roadside 464953 100705 NO2 Y 0 4 m N 2m

116 Catholic Cathedral Alfred Road Roadside 463891 100479 NO2 N 0 5m N 2m

42 Kingston Crescent-Admiral Drake PH- (KC-ADPH)

Roadside 464552 101940 NO2 Y 0 N 2m

43 Kingston Crescent-Vanguard House (KC-VH) Urban background 464774 101922 NO2 N 0 N 2m

44 Market Way-24 (MW-24) Roadside 464336 100833 NO2 Y 0 N 2m

45 Market Way-79 (MW-79) Roadside 464344 100808 NO2 Y N/A N 2m

46 Market Way-Column 5 (MW-Col5) Roadside 464339 101273 NO2 N 0 N 2m

47 Stamshaw Road West (1) Roadside 464586 102125 NO2 N 0 N 2m

48 Stamshaw Road East (28) Urban background 464597 102119 NO2 N 0 N 2m

49 Half Moon Street-The Ship and Castle(PH) (HMS-S&CPH)

Urban background 463042 100315 NO2 N 0 N 2m

50 Queen Street-47 (QS-47) Roadside 463388 100398 NO2 N 0 N 2m

51 Queen Street-57 (QS-57) Urban background 463333 100395 NO2 N 0 N 2m

52 Queen Street-Column 29 Roadside 463235 100412 NO2 N 11.76M N 2m

53 Anglesea Road Station-DEFRA (AR-Station) Roadside 463835 100258 NO2 N 0 Y 2m

57 Saint Jude School-Column 7 (StJSc-Col7) Urban background 463503 99362 NO2 N 5 0.5 m N 2m

59 Milton Road- Across the road from Column 42 on the fence (MR-Opposite Col42)

Roadside 466263 100334 NO2 N 1.5 m N 2m

60 Milton Road- Column 42 (MR-Col42) Roadside 466201 100478 NO2 N 5.32m N 2m

61 Milton Road-1 to 10 Southwick House (MR- SH(Fence))

Roadside 466136 100610 NO2 N 0 N 2m

62 Milton Road-12 Hambrook House (MR-HH) Roadside 466165 100573 NO2 Y 0 N 2m

63 Milton Road-209 (SR-209) Roadside 466354 100172 NO2 N 0 N 2m

64 Milton Road-Summerson Lodge (MR-SL) Roadside 466326 100165 NO2 N 0 N 2m

66 Velder Avenue-1 (VA-1) Roadside 466267 100216 NO2 N 0 N 2m

67 Velder Avenue-23 (VA-23) Roadside 466457 100253 NO2 N 2.37m N 2m

68 Velder Avenue-36 (VA-36) Roadside 466501 100277 NO2 Y 0 N 2m

69 Velder Avenue-Column 4 (VA-Col4) Roadside 466396 100248 NO2 Y 0 N 2m

71 Havant Road-19 (HR-19) Kerbside 465711 105624 NO2 Y 0 N 2m

72 Northern Road-60 (NR-60) Roadside 465657 105577 NO2 N 0 N 2m

73 Northern Road-52 Roadside 465653 105544 NO2 Y 0 N 2m

74 Northern Road-Column 38 (NR-Col38) Roadside 465610 105383 NO2 Y 0 N 2m

75 Southampton Road-1-6 Chipstead House (SR-CH)

Roadside 465618 105619 NO2 N 0 N 2m

76 Copnor Road-142 (CR-142) Roadside 466002 102053 NO2 Y 0 N 2m

77 Copnor Road-Copnor School Playground (CR-School)

Roadside 466008 102097 NO2 N 0 N 2m

78 Goldsmith Avenue-3 (GA-3) Roadside 466523 99599 NO2 N 0 N 2m

79 Goldsmith Avenue-Column 1 (GA-Col1) Kerbside 466555 99598 NO2 Y 1.8 m N 2m

80 Albert Road -147 (AR-147) Urban background 465204 98978 NO2 N 0 N 2m


79

81 Albert Road Column 22 (AR-Col22) Roadside 465278 98968 NO2 N 0.5 M N 2m

82 Albert Road-106 t0 108 On Waverley Road (AR-WR)

Roadside 465178 98945 NO2 Y 2m N 2m

83 Albert Road-141 (AR-141) Roadside 465166 98982 NO2 n N 2m

84 Albert Road-145 on Lawrence Road (AR-145) Roadside 465198 98996 NO2 N N 2m

85 Albert Road-96 (AR-96) Urban background 465150 98968 NO2 N 5 N 2m

86 Fawcett Road-91 (FR-91) Roadside 465201 99734 NO2 N N/A N 2m

87 Fawcett Road- Priory School (FR-PSc) Roadside 465183 99904 NO2 N N 2m

88 Lawrence Road -1 to 8 Brandon House (LR-BH)

Urban background 465186 98996 NO2 N 0 N 2m

89 Waverley Road-114 (WR-114) Urban background 465190 98946 NO2 N N 2m

90 Baffins Road-18 (BR-18) Urban background 466095 100813 NO2 N 0 N 2m

91 Baffins Road-3 (BR-3) Urban background 466070 100819 NO2 N 0 N 2m

93 Victoria Road North-40 (Nursery) (VRN-40 Nursery)

Roadside 464826 99500 NO2 N 0 N 2m

94 2&3 Selbourne Terrace Roadside 465162 100077 NO2 N 11.76M N 2m

95 189 Collins Place Fratton Roadside 465109 100005 NO2 N 0 N 2m

96 Mary Rose Centre, Albert Road Urban background 465465 98937 NO2 N 0 N 2m

97 29 Rowan Court, Goldsmith Avenue Roadside 465896 99852 NO2 N 5.32m N 2m

98 13-29 Eastern Road Roadside 466700 100591 NO2 N 0 N 2m

99 64-80 Eastern Road Roadside 466727 100572 NO2 Y 0 N 2m

100 340 Havant Road Roadside 467783 105677 NO2 N 0 N 2m

101 Havant Road Column 52 Roadside 467693 105687 NO2 N 0 N 2m

102 Hillside & Wymering Centre Roadside 464585 105714 NO2 N 0 N 2m

103 UTC Portsmouth Roadside 465556 103968 NO2 N 2.37m N 2m

108 137 London Road Roadside 464951 102418 NO2 Y 0 N 2m

109 122/124 London Road Roadside 464961 102383 NO2 Y 0 N 2m

110 2a/2b Gladys Avenue Roadside 464913 102419 NO2 Y N 2m

111 Column 3 Gladys Avenue Roadside 464898 102414 NO2 Y N 2m

117 Alfred Road Column 9 (AR-Col 9) Kerbside 463901 100508 NO2 N N 2.5m

118 Alfred Road Column 12 (AR-Col 12) Roadside 463951 100531 NO2 N N 2.5m

119 Alfred Road -left of St Agatha's bus shelter (MW-StABS)

Kerbside 464098 100748 NO2 N N 2.5m

120 Alfred Road Opposite MW-StABS (MW-OppStABS)

Kerbside 464086 100765 NO2 N N 2.5m

121 46 London Road (LR-46) Roadside 464930 102071 NO2 Y N 2.5m

122 47 London Road (LR-47) Roadside 464918 102090 NO2 Y N 2.5m

124 Hillsley Road Column 23 (HR-Col23) Urban Background 462491 106553 NO2 N N 2.5m

125 7 Tudor Crescent (TC-7) Urban Background 465624 104626 NO2 N N 2.5m

126 Column 32 Port Way (PW-Col32) Roadside 463756 105253 NO2 N N 2.5m

127 133 Southampton Road (SR-133) Roadside 463536 105652 NO2 N N 2.5m

131 16 London Road on Chichester Road (CR-PP) Roadside 464925 101969 NO2 Y N 2.5m

132 Column 50 Milton Road (MR-Col50) Roadside 466344 100139 NO2 Y N 2.5m

133 Labour Party Club Holbrook Road (HR-LPC) Roadside 464882 100475 NO2 N N 2.5m

134 Labour Party Club Coburg Street (CS-LPC) Roadside 464919 100464 NO2 N N 2.5m


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Appendix C Quality Assurance of Monitoring Data

QA / QC of automatic monitoring

Continuous Air Quality Monitoring, Quality Assurance and Quality Control PCC manages four air quality-monitoring stations. These are all fully equipped with PCC DEFRA / NETCEN approved real-time automatic continuous monitoring analysers. These are sophisticated automatic monitoring systems housed in purpose built air-conditioned enclosures. These analysers measure and record in real-time a combination of NO2, PM10 and PM2.5. PCC compiled continuous air quality monitoring data for the Further Assessment using Horiba’s APNA-370, NO2 based on the chemiluminescent analysis method. Routine site operations PCC employs a dedicated staff member to operate the network of continuous air quality monitoring stations. He is trained in all aspects of the monitoring processes including routine site operations, field calibrations and data ratification. He is also the NETCEN trained Local Site Operator (LSO) for the local affiliated AURN station. This is to ensure that both a high-level of accurate data and an acceptable percentage of data capture are obtained. All automatic monitoring equipment has both routine remote calibration check and routine (fortnightly) on-site checks. They also have maintenance visits, which follow documented procedures that stem from equipment manuals, manufacturer instructions and the UK Automatic Network Site Operators Manual. Routine visits include:

visual inspection of the station

regular inlet-filter changes

regular sampling head-cleaning and airflow

a two-point calibration of the NO2 analyser using a zero-air scrubber and a Nitric Oxide (NO) gas

on-site

AIR LIQUIDE supplies the NOx span gas with the concentration certificate. This gas is traceable

to national standards

All equipment fitted within each station’s enclosure (e.g. sample meteorological sensors, pumps, air conditioning units, modem etc.) is subject to independent routine maintenance and support via a service contract with Horiba. This includes:

six-monthly minor service and equipment check visits by the manufacturer for Horiba’s analysers

and approved engineers covering all non-Horiba equipment following national protocols and

traceable QA/QC procedures. Horiba is ISO 9001 accredited and carries out similar or identical

support work for a number of AURN network stations across the UK

six-monthly major service where a full multi-point calibration is carried out on the NO2 analyser,

using zero-air, NO and NO2 span gas (again traceable to national standards) meaning the

analyser data slope and offset factors are reset. In addition to multi-point calibration the following

checks are carried out:

linearity

noise

response time, leaks and flow

converter efficiency

stability of the on-site gas calibration cylinder.

The local AURN station is also subject to external audit. Site Inter-calibration checks carried out by

National Environmental Technology Centre Network engineers prior to each Horiba’s major service.


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Horiba also carries out non-routine site visits in response to equipment failure to the same standards.

Contract arrangements ensure that visits are carried out within two to three days of the notification of

call-out in order to minimise data loss.

All routine and non-routine site visits are fully documented and detail all works carried out, including

any adjustments, modifications and repairs completed.

Calibration check methods

The calibration procedure for NOx for sites C2, C4, C6 and C7 is based on a two point zero / span

calibration check being performed at intervals of two weeks. The calibration procedure for the NOx

analyser of the C4 AURN network was based on three points, the third being span NO2 to check the

NO2 Converter. However this was changed to two point calibration check. The methodology for the

calibration procedure is followed according to the manufacturers’ instruction handbooks:

pre-calibration check - the site condition and status of the analyser is recorded prior to the zero /

span check being conducted

zero check – the response of the analyser to the absence of the gas being monitored. The

stations were fitted with an integrated scrubber system incorporating a set of scrubbers,

Hopcalite, activated charcoal, Purafil and Drierite, to generate a dried gas with none of the

monitored pollutants. All were changed at least every six months but Hopcalite is changed more

frequently due to the high levels of humidity in Portsmouth. These were changed with to be fitted

with synthetic air cylinders supplied by Air Liquide UK Ltd

span check – the response of the analyser to the presence of the gas of a known concentration.

Traceable gases are used for calibration checks supplied as part of the maintenance contract

post calibration check - the site condition and status of the analyser upon completion of all

checks

all Horiba’s APNA-370 analysers have their own built in data storage facility. They are built in a

multi-drop set up. The calibration checks are done directly through the front panel. Each analyser

zero / span check is fully documented with records being kept centrally

Automatic data handling

All the stations are remotely accessible from a desktop computer at the civic offices via a telemetry

linkage by either landline or GSM system. The telemetry linkage software used is ‘Data

Communication Server’. It is set on a daily auto-dial collection mode for data retrieval. It is also set to

run calibration checks every three days.

Once the connection is established, the ‘Data Communication Server’ software retrieves the overnight

auto-calibration first and stores it in a temporary database and a calibration factor is generated

according to the following steps:

instrument span, F = C/(Vs-Vz) and

pollutant concentration (ppb) = Fx(Va-Vz) where:

C is the set gas value on the gas certificate

Vs span value

Vz zero span value

Va is the sample value as recorded by the analyser.

Raw measured data retrieved from the station data logger(s) is then subject to the calculated

correction factors and stored in the final database as corrected. The latter is then made readily

available to be queried via the ‘IDAZRW Central Station’, database access software.

Instrument status and internal auto-calibration data can be viewed in addition to the corrected

collected measured monitoring data.

The air quality data ratification is carried out manually from this station.


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Manual data handling

All collected data is screened or validated by visual examination to see if there are any unusual

measurements. The affected data is then flagged in the database. Any further remaining suspicious

data, such as large spikes, ‘flat-lines’ and excessive negative data is flagged for more detailed

investigation. ‘IDAZRW Central Station’ is capable to trace back any change made at all times with

the administrator’s name. An original raw dataset is always kept in the data processing software.

When data ratification has been completed the data is then made available for further statistical and

critical examination for reporting purposes.

Air quality monitoring data can be imported manually into a Microsoft Excel spreadsheet. This scaled

data (where values are above the lower detectable limit is considered to be valuable data) is then

further converted to generate data in the National Air Quality Objective format to enable direct

comparison to the standards. A file of raw data is always kept for reference in the database.

QA / QC of diffusion tube monitoring

Monitoring technique The continuous NO2 monitoring network is complemented by a secondary network of passive NO2 tubes that are located in suspected air quality hot spots. In addition, tubes are located at the relevant continuous monitoring sites to enable data adjustment. At a selection of sites three tubes are exposed simultaneously and the data compared. Where the data is consistent, the results are averaged. Where the tubes results show significant differences the data is discounted. This method provides a cost-effective means of monitoring a wide range of monitoring locations. The accuracy of tubes however is variable depending on the tube handling procedures, the specific tube preparation, adsorbent mixture and the analysing laboratory. These tubes are supplied and analysed by Gradko International Ltd.

PCC’s NO2 diffusion tubes are prepared by the supplier using 50% Triethanolamine (TEA) in acetone.

These tubes were exposed for one-month periods in accordance with LAQM.TG (16) guidance.

Tube Handling Procedures Once received by post, NO2 tubes are stored in cool location within the supplied packaging until use. The tube end caps are not removed until the tube has been placed at the monitoring location at the start of the monitoring period. The exposed tubes are recapped at the end of the monitoring period and returned as quickly as possible to a clean cool storage environment then sent to GIL for analysis. Laboratory QA / QC GIL is a UKAS accredited company for the analysis of NO2. GIL take part in the WASP scheme on a quarterly basis. An inter-comparison of results from other laboratories demonstrates that GIL’s performance is good in terms of accuracy and precision. Data Ratification Once analysed, the NO2 diffusion tubes results which, were significantly within the documented limit of detection, were laboratory blank corrected. The returned results are closely examined on a monthly basis to identify any spurious data (e.g. very high or very low data). The data is subjected to a further series of corrections for the monitored period under consideration:

Firstly, PCC use the data from the local collocation study of NO2 diffusion tubes to calculate the

bias following the approach prescribed in Box 6.4 of LAQM TG (16) using the appropriate

continuous monitoring data from the local air quality monitoring network for individual NO2

monitored site according to the site criteria


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Secondly, the estimation of the NO2 annual mean is deduced for individual NO2 diffusion tube

monitored locations following the approach prescribed in Box 6.5 of LAQM TG (16) using data

from both Portsmouth and Southampton AURN stations

The corrected results are then reported and used for comparison only, i.e. not for verification

processes in the Further Assessment (Review and Assessment process).


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