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North East Link

AIR QUALITY IMPACT ASSESSMENT

Frank Fleer

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Presentation Overview

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Introduction

Existing environment

Construction

Models

Ventilation system modelling

Surface roads modelling

Combined impacts modelling

Ambient air quality monitoring

Filtration systems

Conclusions

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Introduction

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Data input Mathematical modellingPrediction of

concentrationsCompliance assessment

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Existing environment

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Existing environment

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Compared with international cities of similar size, Melbourne’s air quality is relatively good. There are periodic exceedances of air quality standards, principally PM10 and PM2.5, mainly due to the impact of wood heaters, dust storms, bushfires and fuel reduction burns.

Alphington AAQMS exceedances

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Alphington NO2 1 hour average

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0

20

40

60

80

100

120

140

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Concentr

ati

on (p

pb)

Year

AAQMS SEPP(AAQ) objective

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Alphington NO2 annual average

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0

5

10

15

20

25

30

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2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

Concentr

ation (p

pb)

Year

AAQMS SEPP(AAQ) objective

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Construction

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Selection of possible control measures

Filtration systems on temporary ventilation systems

Equipment maintenance, particulate filters/Euro V diesel fuelled equipment

Siting of temporary ventilation systems, stockpiles, parking areas

Location and design of site routes and exits

Installation of screens or wind breaks

Employee training

Cessation of work under adverse weather conditions

Minimise area cleared and revegetate as soon as possible

Vehicle speed limits and covering of loads

Use of road washers/street sweepers

Application of water to unsealed roads and stockpiles

Use of dust suppressants/tarpaulins/hydromulching

Ambient air quality monitoring and daily inspections

Reactive air quality management system and trigger response levels

Minimise engine idling and queuing

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Models

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Tunnel ventilation systems:

• AERMOD (Victorian & USEPA regulatory model)

• PM10, PM2.5, CO, NO2, BTEX, 1,3 butadiene, HCHO & PAH

Surface roads:

• AERMOD (USEPA regulatory model)

• PM10, PM2.5 & NO2

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Model scenarios

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2026 traffic volumes and fleet mix:

• A1 – COPERT Aust (V1.2) 2010 & PIARC 2020 future year factors

• A2 – COPERT Aust (V1.2) 2010 & Brisbane 2025 future year factors

2036 traffic volumes and fleet mix:

• B1 – COPERT Aust (V1.2) 2010 & PIARC 2020 future year factors

• B2 – COPERT Aust (V1.2) 2010 & Brisbane 2025 future year factors

Additional 2036 scenarios:

• C1 – COPERT Aust (V1.2) 2010 & Victorian (V1.3) 2025 future year factors

• C2 – COPERT Aust (V1.2) 2010 & Victorian (V1.3) 2025 including PEVs

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Model scenarios

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Ventilation system sensitivity analyses:

• NEL tunnels maximum capacity (6,000 vehicles/h, 24 h/d, 365 d/yr)

• Emissions at in-tunnel air quality limits (24 h/d, 365 d/yr)

• Increased diesel to petrol fuelled car ratios (30% v 15%)

• Alternative ventilation structure locations (potential footprints)

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Ventilation systems

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Input data:

• background pollutant concentrations:

o Alphington 2013 - 2017 (PM10, CO & NO2)

o Alphington 2014 – 2017 (PM2.5)

o EPA Victoria (PAH & VOCs)

• meteorology (Viewbank/Essendon Airport/Tullamarine Airport 2013 – 2017)

• topography (DELWP)

• traffic volumes and mix (Smedtech)

• vehicle emission factors

• receptors (gridded and discrete)

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Alphington PM10 1 h av background (2017)

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0

20

40

60

80

100

120

140

160

180

200

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

PM

10

concentr

ation (μg/m

3)

Month

Background SEPP(AQM) objective

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Alphington PM2.5 1 h av background (2017)

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0

10

20

30

40

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60

70

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Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

PM

2.5

concentr

atio

n (μg/m

3)

Month

Background SEPP(AQM) Objective

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Topography

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Australian emission standards

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Australian emission standards

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Receptors

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Grid (km)

Spacing (m)

10 x 16 100

2.5 x 2.5 25

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Vehicle emission factors

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Vehicle volume predictions

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NEL Strategic Transport Modelling Expert Conclave Statement

Modelled volumes tend to be higher than observed traffic counts for the peak periods by around 10% on average

Model appears to overestimate commercial vehicle traffic by around 15% on average

VicRoads Managed Motorway Design Guide - June 2019

Maximum sustainable flow 1,490 – 1,570 vehicles/h/lane cf. 2,000 vehicles/h/lane for maximum capacity modelling (22% to 25% overestimate)

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NO to NO2 conversion

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‘The following options should not be used without specific approval by EPA Victoria……OLM and PVMRM option for modelling conversion of NOx to NO2’. (EPA Victoria, October 2013)

‘Overall the PVMRM option appears to provide a more realistic treatment of the conversion of NOx to NO2 as a function of distance downwind from the source than OLM or the other NO2 screening options’. (MACTEC Federal Programs, 2004)

‘PVMRM is doing well at predicting the NO2/NOx ratio (minimal bias, with most ratiosfrom 0.2 to 0.4). OLM has a general 70% overprediction tendency for the NO2/NOx

ratio’. (Hanna, S., 10th USEPA Air Modelling Conference, 2012)

‘Work by Janssen et al. (1988) suggests that for large plumes there is a near-source region with a low conversion, but this is rapidly asymptotic to the photostationary state after a modest travel time (of perhaps 200 seconds according to our calculation using their method). As such it bears an unexpected but welcome similarity to our understanding of urban NO2 data’. (UK Environment Agency, 2007)

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NO to NO2 conversion

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Source: Trinity Consultants

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NO to NO2 conversion

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Ventilation systems

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Under normal operating conditions there is predicted to be a negligible impact on ambient air quality due to ventilation system emissions.

For scenarios A1, A2, B1 and B2, all pollutants complied

with SEPP(AQM) criteria, except for PM10 and PM2.5:

No additional PM10 exceedances (over the 8 due to background alone)

One additional PM2.5 exceedance (over the 20 due to background alone)

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Ventilation systems

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Sensitivity analyses:

Project contribution to maximum predicted GLCs could increase significantly (up to 100 per cent in the case of NO2

for doubling proportion of diesel cars). However, due to low project contribution, there was relatively little change in maximum predicted GLCs (project plus background).

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Surface roads

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Total vehicles in 2036 (with or without project) >30,000/d, with change (no project to project) >25%

or

HCVs in 2036 (with or without project) >1,000/d, with change (no project to project) >25%

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Surface roads

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Sensitive receptors

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Surface roads

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PM10 Scenarios C1 and C2

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PM2.5 Scenarios C1 and C2

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NO2 Scenarios C1 and C2

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NO to NO2 conversion

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‘Most of the NO2 assessment methods for on-road sources are either empirically-derived or have scientific basis with empirically-derived parameters. Each method needs to be evaluated for its performance in predicting NO2 impacts from NSW roads. The equations may also need to be modified to be suitable for NSW applications. Some of the methods would only allow assessment of NO2 at longer averaging periods (e.g. annual average)’. Todoroski, 2015

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NO to NO2 conversion (Kimbrough, S. et al, USEPA, 2017)

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‘the reaction rate can actually be on the order of tens of seconds to a few minutes, depending on the amount of available reactants such as O3 and volatile organic compounds (VOCs), solar energy, and ambient meteorological conditions’

‘while the chemical transition from NO to NO2 is occurring throughout the measurement locations, full conversion of all NO to NO2 is occurring throughout the measurement locations, full conversion of all NO to NO2 generally does not occur within 300 m of the roadway’

‘the ambient NO2/NOx ratio immediately downwind of roadway sources is not entirely a function of the roadway emissions. Instead, even at 20 m from the roadway edge, the ratio is a function of:1) the roadway emissions (i.e., the emitted NO2/NOx ratio)2) the in-situ and in-transport conversion of NO to NO2 and3) mixing of emissions with background air, with 2 and 3 being ongoing and competing processes that drive the NO2 concentrations in different directions. The conversion of NO to NO2 and mixing of emissions with background air can impact the changes in baseline NO2 and NOx and the resultant ratio. Thus, a single assumption about the NO2

chemistry cannot account for all of these processes. These results highlight the usefulness of long-duration gradient data in assessing the behaviour of NO2/NOx ratios to inform air quality modelling strategies in the near-road environment. These results also support the need for future enhancements to existing models to incorporate ambient background NO2/NOx ratio, emissions NO2/NOx ratio, and O3

concentration into a single NOx chemistry scheme within a dispersion model’.

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Roadside NO2 concentrations

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Source: Air Quality Consultants UK, 2008

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Roadside NO2 concentrations

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Golder monthly average NO2 roadside monitoring readily shows compliance with SEPP(AAQ) annual objective

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Roadside NO2 concentrations

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Golder annual average NO2 roadside monitoring shows compliance with proposed Air NEPM annual objective

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Combined impacts

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Combined impacts

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Combined impacts

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24 hour PM2.5 – Scenario B1 most impacted northern receptor (2036)

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Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Co

nce

ntr

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n (µ

g/m

3)

Month

Background Surface roads Tunnel ventilation structures SEPP(AAQ)

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Combined impacts

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24 hour PM2.5 – Scenario B2 most impacted northern receptor (2036)

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Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

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nce

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g/m

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Background Surface roads Tunnel ventilation structures SEPP(AAQ)

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Combined impacts

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NELP AAQMSs

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24 hour PM10 concentrations

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24 hour PM2.5 concentrations

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Daily max 1 hour NO2 concentrations

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AAQMS comparisons with Alphington

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Alphington PM10 and PM2.5

similar to Footscray, Belle Vue School, Middleborough Road, and Trinity College. Lower Plenty Road and Grimshaw Street have higher PM2.5 ratios, as expected due to proximity to Greensborough Road. Belle Vue School and Middleborough Road have higher NO2 ratios, due to proximity to Eastern Freeway.

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Filtration systems

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NHMRC 2008 - the most effective way to manage air quality both in and around tunnels is through vehicle fleet emission reductions.

M5 East tunnel trial 2012 – cost of PM10 reduction ($ per tonne) is substantially greater than the cost of implementing emission standards for wood heaters, replacing diesel locomotives and providing shore side power at Port Botany.

NZTA 2013 - the available evidence to date suggests that the effectiveness of pollution control technology for removing emissions from vehicles in tunnels is questionable.

EPA Victoria 2014 - previous tunnel ventilation system approvals did not require filters as emissions are diluted to a point where filters would not provide a significant benefit to the community.

NSW Advisory Committee on Tunnel Air Quality 2018 – ‘To date, there have been no upgrades of existing systems where the upgrading process has included the erection of stacks or the installation of filtration systems’.

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Conclusions Ventilation systems:

o No additional exceedances of SEPP(AQM) PM10 design criterion

o One additional exceedance of SEPP(AQM) PM2.5 design criterion

o CO, NO2, BTEX, 1,3-butadiene, formaldehyde and PAH comply

o PM10 and PM2.5 exceedances not considered to conflict with the intent of SEPP(AQM)

Surface roads:

o PM10, PM2.5 and NO2 incremental concentrations alongside 16 roads reduce due to NEL; eight roads increase with one mixed outcome

o Using more realistic 2025 emission factors for 2036 maximum predictions significantly reduced

Combined impacts:

o Surface roads typically contribute significantly more than ventilation systems at all receptors modelled

o PM10 and NO2 concentrations predicted to be less than SEPP(AAQ) EQOs

o PM2.5 predicted to be greater than SEPP(AAQ) EQOs due to high background

o Using more realistic 2025 emission factors predictions for 2036 significantly reduced