air quality modelling

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Air Quality Modelling Mark Chapman, Air Quality and Odour Discipline Manager [email protected] 01483 731378 07976 344 311

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Page 1: Air Quality Modelling

Air Quality ModellingMark Chapman, Air Quality and Odour Discipline Manager

[email protected]

01483 731378

07976 344 311

Page 2: Air Quality Modelling

Air Quality ModellingMark Chapman, Air Quality and Odour Discipline Manager

[email protected]

01483 731378

07976 344 311

Page 3: Air Quality Modelling

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Air Quality Modelling Overview

• Key Guidance Documents

• Defining the AQ Modelling Domain

• Model Setup

– Input Parameters

– Road Traffic Emissions;

• Model Verification and Adjustment

Page 4: Air Quality Modelling

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Key Guidance Documents

Page 5: Air Quality Modelling

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Defining The AQ Modelling Domain

Brief Reminder: DMRB Screening Criteria (Guidance)

For Local Air Quality ‘Affected roads’ are those that meet any of the following criteria:

• road alignment will change by 5 m or more; or

• daily traffic flows will change by 1,000 AADT or more; or

• Heavy Duty Vehicle (HDV) flows will change by 200 AADT or more; or

• daily average speed will change by 10 km/hr or more; or

• peak hour speed will change by 20 km/hr or more.

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Defining The AQ Modelling Domain

For Regional Emissions ‘Affected roads’ are those that are expected to have :

• a change of more than 10% in AADT; or

• a change of more than 10% to the number of HDV; or

• a change in daily average speed of more than 20 km/hr.

However…

Air Quality Assessments are

Receptor Based not Source Based

Page 7: Air Quality Modelling

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Defining The AQ Modelling Domain

In addition to identifying ‘Affected roads’:

• Receptors within 200m of Affected roads;

– Including future receptors

• Roads (including non-affected) within 200m of these receptors;

• Locations where it is anticipated that EU Limit Values are likely to be exceeded in the Opening Year;

– Air Quality Management Areas (AQMA)

– Monitoring Locations

Page 8: Air Quality Modelling

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Air Quality Modelling – Affected Roads

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Air Quality Modelling - Final Study Area

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Model Setup

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Model Setup – The ‘basics’

Air Quality Concentration = …

Emission

• Factors derived from speeds, fleet composition (LDV/HDV), fleet age (EURO Standard)

X

Activity

• Magnitude of each factor for local network

X

Dispersion

• Chemistry - Oxidation reactions, etc.

• Physics – Turbulence, Meteorology, etc.

Better inputs = Better outputs

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Model Setup – Input Parameters

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Model Setup – Input Parameters

Internal to Model:

• Terrain Data

• Meteorological Data

• Surface Roughness (Horizontal Dispersion)

• Monin-Obukhov Length (Vertical Dispersion)

• Road Traffic Emissions Data

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Model Setup – Input Parameters

External Processing:

• Local Monitoring Data

– Model Verification and Adjustment

• Background Concentrations

– National Mapping

– Local Monitoring Data

• NOx to NO2 Empirical Formulae (Basic Chemistry)

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Model Setup – Road Traffic Emissions2010 LDV vs HDV Nox Emissions

0

2

4

6

8

10

12

14

16

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 105 110 115 120

Speed (kph)

Em

iss

ion

s

LDVs HDVs

Optimum speed for HDVs is 60-70 kph

Optimum speed for LDVs is 45-50 kph

x16

x20

x14

x10

Page 16: Air Quality Modelling

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Model Setup – Road Traffic Emissions2010 Motorway NOx Emissions

0

500

1000

1500

2000

2500

3000

5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 105 110 115 120

Speed (kph)

Em

iss

ion

Ra

te

LDVs HDVs Cumulative

Optimum speed for LDVs is 45-50 kph

Optimum speed for HDVs is 60-70 kph

Optimum speed for entire motorway fleet is 55-65

kph

Best Resolution Fleet Breakdown

Page 17: Air Quality Modelling

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Model Setup – Road Traffic EmissionsNOx Emissions 2010-2025

0

500

1000

1500

2000

2500

3000

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025

LDVs HDVs Cumulative

45% Reduction in Nox Emissions from 2011 to

2016

72% Reduction in Nox Emissions from 2011 to

2021

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Model Verification and Adjustment

The predicted results from a dispersion model may differ from measured concentrations for a large number of reasons:

• estimates of background concentrations;

• meteorological data uncertainties;

• uncertainties in source activity data such as traffic flows and emissions factors;

• model input parameters such as roughness length, minimum Monin-Obukhov; and

• overall model limitations; and

• uncertainties associated with monitoring data, including locations.

Page 20: Air Quality Modelling

20202020

Model Verification and Adjustment

• checks on:

– traffic data;

– road widths;

– distance between sources and monitoring;

– monitoring data;

– estimates of background concentrations;

• consideration of speed estimates on roads in particular at junctions where speed limits are unlikely to be appropriate;

• consideration of source type, such as roads and street canyons;

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Model Verification and Adjustment

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Model Verification and Adjustment

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Model Verification and Adjustment

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Model Verification and Adjustment

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Model Verification and Adjustment

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Model Verification and Adjustment

Page 27: Air Quality Modelling

Mark ChapmanAir Quality and Odour Discipline [email protected] 01483 731 37807976 344 311