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Appendix 5 - Air quality assessment report
Air Quality Assessment - Proposed Service Station, Noosaville Belo Developments Date of Issue: 18 July 2019 Prepared by: Air Noise Environment ABN: 13 081 834 513
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DOCUMENT CONTROL SHEET
Document Details
Project Reference: 4694.2-AirReport02.odt
Document Title: Air Quality Assessment - Proposed Service Station, Noosaville
Client: Belo Developments
Document Reference: /Network/Projects/4694.2/Reporting/4694.2-AirReport02.odt
Revision History
Version: Issue Date: Author: Description: Approved by:
00 10/6/19 Sally Fergus Internal Draft -
01 14/6/19 Sally Fergus Draft for Client Samuel Wong
02 18/7/19 Sally Fergus Final for Client Samuel Wong
Revision: Issue Date: Author: Details of Revision:
01.1
01.2
02.1
02.2
Copyright:
Air Noise Environment retains ownership of the copyright to all reports, drawings, designs, plans, figures and other work
produced by Air Noise Environment Pty Ltd during the course of fulfilling a commission. The client named on the cover of this
document shall have a licence to use such documents and materials for the purpose of the subject commission provided they
are reproduced in full or, alternatively, in part with due acknowledgement to Air Noise Environment. Third parties must not
reproduce this document, in part or in full, without obtaining the prior permission of Air Noise Environment Pty Ltd.
Disclaimer:
This document has been prepared with all due care and attention by professional environmental practitioners according to
accepted practices and techniques. This document is issued in confidence and is relevant only to the issues pertinent to the
subject matter contained herein. Air Noise Environment Pty Ltd holds no responsibility for misapplication or misinterpretation
by third parties of the contents of this document. If the revision history does not state that a Final version of the document
has been issued, then it remains a draft. Draft versions of this document should not be relied upon for any purpose by the
client, regulatory agencies or other interested parties.
Where site inspections, testing or fieldwork have taken place, the report is based on the information made available by the
client or their nominees during the visit, visual observations and any subsequent discussions with regulatory authorities. It is
further assumed that normal activities were being undertaken at the site on the day of the site visit(s).
The validity and comprehensiveness of supplied information has not been independently verified and, for the purposes of this
report, it is assumed that the information provided to Air Noise Environment Pty Ltd for the purposes of this project is both
complete and accurate.
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Table of Contents
1 Introduction 6
1.1 Scope of Study 6
1.2 Subject Site and Surrounding Land Uses 6
1.3 This Report 8
2 Assessment Criteria 9
3 Air Emission Data Data 10
3.1 Service Station Air Emission 10
3.1.1 Potential Air Emission Sources 10
3.1.2 Emission Factors 11
3.1.3 Odour Emission Factors 11
3.1.4 VOC Composition 12
3.1.5 Fuel Throughput 12
3.1.6 Bulk Tanker Deliveries 14
3.1.7 Derived Emission Rates 14
4 Air Dispersion Modelling 16
4.1 Overview 16
4.2 Modelling Methodology 16
4.2.1 Introduction 16
4.2.2 TAPM 16
4.2.3 CALMET 17
4.2.4 CALPUFF Dispersion Modelling 21
4.2.5 CALPOST 21
4.3 Meteorological Predictions 21
4.3.1 Wind Predictions 21
4.3.2 Predicted Atmospheric Stability 23
4.3.3 Predicted Mixing Heights 24
4.4 Source Locations 25
4.5 Downwash Structures 26
4.6 Discrete Receptors 27
4.7 Background Air Monitoring Data 28
4.8 Emission Parameters 29
5 Summary of Assumptions 29
5.1 Modelling Results 29
6 Conclusions 33
Appendix A - Air Quality Glossary 34
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Index of Tables
Table 2.1 - Air Quality Quality Criteria 9
Table 3.1 - Service Station Operating Data 10
Table 3.2 - Service Station Emission Factors 11
Table 3.3 - Composition of Unleaded Petrol 12
Table 3.4 - Representative Service station Fuel Throughput Profile for Brisbane Area 13
Table 3.5 - Estimated Fugitive Emission Rates 14
Table 3.6 - Estimated Vent Emissions 15
Table 4.1 - TAPM Settings 17
Table 4.2 - Summary of Predicted Stability Classes by Hour 23
Table 4.3 - Summary of Average Ambient Pollutant Concentrations for QLD (January 2015 to
December 2017) 28
Table 4.4 - Predicted Results – Residential Receptors 30
Index of Figures
Figure 1.1 - Subject Site Layout and Surrounding Land Uses 7
Figure 1.2 - Proposed Site Layout 8
Figure 4.1 - Modelled Terrain 18
Figure 4.2 - CALMET modelled BOM Station location 20
Figure 4.3 - Measured Wind Roses 2012-2016 vs 2016 CALMET Predicted Site Wind Roses 22
Figure 4.4 - Predicted Mixing Heights 24
Figure 4.5 - Modelled Source Locations 26
Figure 4.6 - Building Downwash Structures 27
Figure 4.7 - Discrete Air Modelling Receptor Locations 28
Figure 4.8 - Predicted Ground Level Odour Concentrations 31
Figure 4.9 - Predicted First Floor Odour Concentrations 32
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1 Introduction
1.1 Scope of Study
Belo Developments commissioned Air Noise Environment to undertake an air quality assessment for
a redevelopment of an existing service station at 52-54 Mary Street, Noosaville.
The assessment has been undertaken to determine potential odour and air quality impacts on
nearby sensitive receptors from the refurbished service Station. The results of the assessment have
been compared to the air quality goals specified in the Environmental Protection (Air) Policy 2008.
1.2 Subject Site and Surrounding Land Uses
The subject site is located at 52-54 Mary Street, Noosaville and is described as Lot 1 on RP72829 and
Lot 21 on RP131598. The site is currently occupied by an existing service station, with a proposal to
redevelop the service station. The redevelopment of the service station will involve the demolition of
the existing service station and the construction of a new service station (including new fuel system)
and retail store. Limited food cooking is proposed to occur inside the new service station retail store.
It is noted that there will be no external discharge from the limited cooking processes. As such, these
processes have not been considered as part of this assessment. The service station is proposed to
operate from 5 am to 10 pm.
Under The Noosa Plan (2018), the subject site and immediate surrounding area is zoned as Business
Centre. The surrounding land uses include a mix of residential and light commercial uses. Nearby
commercial uses include a veterinarian, dentist, physiotherapy, real estate and an insurance agent
located to the west and south.
The nearest sensitive receptors have been identified as two storey residential uses located in the
adjoining lots to the north. Other nearby sensitive uses include the the Noosa Gardens Riverside
Resort located approximately 20 m to the north and residential uses to the north west and south.
Figure 1.1 shows the subject site location and surrounding land uses. Figure 1.2 shows the proposed
site layout.
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Figure 1.1 - Subject Site Layout and Surrounding Land Uses
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Figure 1.2 - Proposed Site Layout
1.3 This Report
This report summarises the methodologies, results and conclusions of the air quality assessment.
Glossaries of terms are available in Appendix A to assist the reader.
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2 Assessment Criteria
The key air quality indicators for assessing impacts from service stations include volatile organic
compounds (VOCs) and odour.
The Noosa Plan (2018) does not specify criteria for air quality impact assessments. Therefore,
reference has been made to criteria for VOCs as presented in the Environmental Protection (Air)
Policy 2008 (EPP Air). Where relevant criteria is not provided in the EPP Air, reference has been made
to the Brisbane City Council (BCC) 2014 Service Station Code. For odour, reference has been made to
criteria presented in the Odour Impact Assessment for Developments Guideline (2013) published by
the Department of Environment and Heritage Protection (now Department of Environment and
Science, DES). Table 2.1 summarises the criteria adopted for the target compounds considered in the
air quality assessment.
Table 2.1 - Air Quality Quality Criteria
Air Quality Criteria
Compound Averaging Period Outcome
mg/m3
Protecting aesthetic
1100 30 Minutes
environment
Toluene1
4100 24 Hour Health and well being
410 Annual Health and well being
1200 24-hour Health and well being
Xylene1
950 Annual Health and well being
1
Benzene 10 Annual Health and well being
2
Cyclohexane 19,000 1 Hour Health and well being
2
n-Hexane 3,200 1 Hour Health and well being
2
Ethylbenzene 8,000 1 Hour Health and well being
Protecting aesthetic
75 30 Minutes
Styrene1 environment
280 7 days Health and well being
2
Cumene 21 1 hour Odour
0.5 OU for tall stacks
1 hour,
Odour3 2.5 OU for ground level Odour
99.5th percentile
and wake-affected plumes
1
Criteria based on Environmental Protection (Air) Policy 2008
2
Criteria based on Brisbane City Plan 2014 Industrial Amenity Overlay Code
3
Criteria based on the Department of Environment and Heritage Protection (EHP) Odour Impact Assessment from Developers
Guide (2013)
Air emissions from the underground tank vents are considered wake affected due to the presence of
nearby buildings. Therefore, the 2.5 OU criteria is applicable to the tank vents. All other air emission
sources (e.g. refuelling) are at ground level hence, the 2.5 OU criteria is applicable for these sources.
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3 Air Emission Data Data
3.1 Service Station Air Emission
3.1.1 Potential Air Emission Sources
Air emissions from the proposed service station are expected to occur from a number of different
sources and activities. These include:
⚫ refuelling areas (during filling of cars, and ‘whoosh’ emissions during removal of fuel cap on
vehicle);
⚫ tank breathing from underground tanks via the vent pipes;
⚫ bulk filling of underground tanks (emissions occur when vapour in the head space is displaced as
tank filling occurs); and
⚫ other fugitive emissions such as spillage.
The key air quality indicators associated with the above sources are general odour and Volatile
Organic Compounds (VOCs) which include compounds such as benzene, toluene, xylene, styrene,
cyclohexane, n-hexane and ethylbenzene. Exposure to elevated concentrations of VOCs are related
to health and nuisance odour impacts.
In relation to bulk filling, when a vapour return system is used on the road tanker to return vapours
to the tanker rather than allowing them to be emitted to the atmosphere, emissions can be reduced
substantially (in the order of 95%). This type of mitigation is called Phase 1 vapour recovery. Phase 1
vapour recovery is proposed to be installed at the site. Phase 2 vapour recovery, which reduces
emissions during vehicle refuelling, is also proposed to be installed at the site.
Table 3.1 presents a summary of the proposed service station operating data. Figure 4.5 in Section
4.4 presents the location of the air emission sources.
Table 3.1 - Service Station Operating Data
Parameter Details
Proposed Operating Hours 5 am to 10 pm
Fuel Sales 6.3 ML/year
Vent Stack 4m
Filling Stations/Petrol Bowsers 5 bowser ranks (2 filling points each side)
Storage Tanks ULP and diesel
Fuel Deliveries Maximum 40 kL per hour
Emission Controls Phase 1 and 2 Vapour Recovery
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3.1.2 Emission Factors
To derive air emission rates for the proposed service station, reference has been made to the
following documents:
⚫ Emissions Estimation Technique Manual for Aggregated Emissions from Service Stations
(November 1999, National Pollution Inventory); and
⚫ LORAX Report, Gasoline Service Stations Industry Wide Risk Assessment Guidelines (Toxics
Committee of the California Air Pollution Control Officers Association 1997).
Table 3.2 summarises the available literature estimates for VOC emissions from the various sources
at services stations.
Table 3.2 - Service Station Emission Factors
NPI 1999 LORAX
Emission Sources
mg / litre throughput Lbs / 1000 gallons throughput
Underground Tank Filling
Submerged Filling 880 8.4
Splash Filling 1380 -
Submerged Filling with vapour
40 0.42
balance
Underground tank breathing
120 0.84
losses
Vehicle Refuelling
Displacement Losses (uncontrolled) 1320 8.4
Displacement Losses (controlled) 132 0.74
Spillages
Uncontrolled 80 0.61
Controlled - 0.41
“Whoosh” Emissions - 0.26 – 0.66
All volume sources (refuelling, spillages and whoosh emissions) have been modelled based on the
emission factors presented in the LORAX report. Emissions from the underground tank vents have
been modelled using the NPI data.
3.1.3 Odour Emission Factors
In order to estimate odour emissions from various activities at the service station, data has been
obtained from odour and VOC sampling of unleaded petrol vapour. The study involved taking
simultaneous VOCs and odour samples from a fuel storage container containing unleaded petrol. The
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samples were then analysed for total VOCs and odour concentrations for use in determining a
correlation factor. This correlation factor has then been applied to VOC emission factors for various
activities to derive odour emission rates. Odour sampling was completed and analysed in accordance
with AS 4323.3:2001 Station source emissions – Determination of odour concentration by dynamic
olfactometry.
Based on the sampling, an odour-to-Total VOC ratio of 439 (OU:g/m3) was established. Total VOC
emission data was factored by 439 to establish odour emission data.
3.1.4 VOC Composition
The types of pollutants emitted from service stations include a range of VOCs. Air Noise Environment
has obtained VOC composition data from the analysis of head space vapour in a fuel storage
container containing unleaded petrol. Duplicate samples were collected on charcoal sorbent tubes
and analysed for total VOCs and speciated VOCs. The sampling identified benzene, toluene, xylene,
ethylbenzene and cumene as being above the detection limits.
Cyclohexane and n-hexane was not included in the speciated VOC analysis. For the purpose of the
assessment, reference has been made to Equation 2 of the NPI Emissions Estimation Technique
Manual for Aggregated Emissions from Service Stations (1999). The equation provides a means for
estimating vapour weight % of a compound based on the liquid weight % and associated boiling
point. Based on a review of various Australian Safety Data Sheets for petrol, n-hexane composition in
petrol is up to 5%. Information on cyclohexane was not provided in any Australian Safety Data
Sheets (possibly due to very low weight % values). Nevertheless, as a conservative approach, a
weight % value of 5 has been considered based on a review of international safety data sheets for
petrol.
Table 3.3 presents a summary of the VOC composition data considered in this assessment.
Table 3.3 - Composition of Unleaded Petrol
Species VOC Vapour Composition % Source
Benzene 0.838% ULP head space sample
Cyclohexane 1.58% Equation 2 of NPI Service Station Manual
Ethylbenzene 0.267% ULP head space sample
n-Hexane 2.47% Equation 2 of NPI Service Station Manual
a
Styrene < 0.00190% ULP head space sample
Toluene 3.24% ULP head space sample
Xylenes 1.45% ULP head space sample
Cumene 0.0134% ULP head space sample
a
Styrene was below the detection limit. Styrene has been considered in the assessment as this compound is specifically
referred to in the BCC Service Station Code.
3.1.5 Fuel Throughput
In order to convert mass per volume of fuel emission factors, it is necessary to determine the likely
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fuel throughput adopted at a service station. Reference has been made to a methodology developed
by Brisbane City Council (BCC) for the assessment of service stations to determine diurnal profiles for
the service station. BCC recommends two methods of calculating the fuel dispensing throughput for
a service station:
⚫ Method 1 – If site data is available for total daily or weekly fuel sales:
⚫ Estimate daily petrol dispensing rate (preferably the peak rate not average)
⚫ Use the daily profile presented in Table 3.4 to apportion the amount of fuel dispensed
per hour
⚫ For sites that operate less than 24 hours, recalculate the daily profile for the hours of
operation (e.g. for operation from 6am to 9pm (15 hours, representing 83.4% of sales),
the hourly profile of 6.0% at 11 am gets re-calculated as 6.0/0.834 = 7.2%)
Table 3.4 - Representative Service station Fuel Throughput Profile for Brisbane Area
Hourly Profile Adjusted to
Hour
24-hour Profile 4 am – midnight
1 1.20% 0.0%
2 0.80% 0.0%
3 0.60% 0.0%
4 0.80% 0.0%
5 1.90% 2.0%
6 4.60% 4.8%
7 5.50% 5.7%
8 5.70% 5.9%
9 5.50% 5.7%
10 5.70% 5.9%
11 6.00% 6.2%
12 6.00% 6.2%
13 5.70% 5.9%
14 5.60% 5.8%
15 5.90% 6.1%
16 6.10% 6.3%
17 6.00% 6.2%
18 5.80% 6.0%
19 5.10% 5.3%
20 4.00% 4.1%
21 3.50% 3.6%
22 3.40% 3.5%
23 2.60% 2.7%
24 1.80% 1.9%
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⚫ Method 2 – If no fuel sales data is available:
⚫ Count the number of bowsers and multi product pumps on site;
⚫ Estimate peak petrol dispensing rate by assuming 40 L/vehicle, and each vehicle takes
4 minutes at the pump;
⚫ Assume the estimated peak throughput is equivalent to the fuel dispensed for Hour 16
(the peak hour), and then extrapolated to other hours of the day using the proportions
show in Table 3.4.
As fuel sales data has been provided by the client, method 1 has been adopted for the purpose of
the assessment. As required by Method 1, this daily throughput has been factored according to the
hourly profile presented in Table 3.4.
3.1.6 Bulk Tanker Deliveries
A maximum 1-hour throughput emission rate has been assumed for a maximum tanker bulk delivery
of 40 KL in one hour. As a conservative approach, this considers 40 KL of ULP, which is associated
with higher volatility compared to diesel.
3.1.7 Derived Emission Rates
Tables 3.3 and 3.4 present the estimated total VOC emission rates for fugitive sources (refuelling,
spillages, whoosh emissions) and for vent emissions during breathing and fuel deliveries. Fuel
emissions from fugitive sources have been modelled from 4 am to midnight, presenting a more
conservative scenario than the proposed operating hours of 5 am to 10 pm.
Table 3.5 - Estimated Fugitive Emission Rates
Hourly profile Calculated Fugitive
Fuel Throughput Calculated Fugitive
Hour (% of Odour Emission Rates
(L/hour) VOC Emissions (g/s)
Throughput) (OU.m3/s)
1 0.0% 0 0.000 0
2 0.0% 0 0.000 0
3 0.0% 0 0.000 0
4 0.0% 0 0.000 0
5 2.0% 339 0.023 10
6 4.8% 821 0.055 24
7 5.7% 981 0.066 29
8 5.9% 1017 0.068 30
9 5.7% 981 0.066 29
10 5.9% 1017 0.068 30
11 6.2% 1070 0.072 31
12 6.2% 1070 0.072 31
13 5.9% 1017 0.068 30
14 5.8% 999 0.067 29
15 6.1% 1052 0.070 31
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Hourly profile Calculated Fugitive
Fuel Throughput Calculated Fugitive
Hour (% of Odour Emission Rates
(L/hour) VOC Emissions (g/s)
Throughput) (OU.m3/s)
16 6.3% 1088 0.073 32
17 6.2% 1070 0.072 31
18 6.0% 1035 0.069 30
19 5.3% 910 0.061 27
20 4.1% 713 0.048 21
21 3.6% 624 0.042 18
22 3.5% 606 0.041 18
23 2.7% 464 0.031 14
24 1.9% 321 0.021 9
Table 3.6 - Estimated Vent Emissions
Tank Filling
Source
VOC Emission Rate (g/s) Odour Emission Rate (OUV/s)
Vent stack 0.44 195
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4 Air Dispersion Modelling
4.1 Overview
Air dispersion modelling has been undertaken to assess the potential for air quality impacts on the
nearest receptors. The following sections present the modelling methodology, input data and
predicted results.
4.2 Modelling Methodology
4.2.1 Introduction
Atmospheric dispersion modelling involves the mathematical simulation of the dispersion of air
contaminants in the environment. The modelling utilises a range of information to estimate the
dispersion of pollutants released from a source including:
⚫ meteorological data for surface and upper air winds, temperature and pressure profiles, as well
as humidity, rainfall, cloud cover and ceiling height information;
⚫ emissions parameters including source location and height, source dimensions and physical
parameters (e.g. exit velocity and temperature) along with pollutant mass emission rates;
⚫ terrain elevations and land use both at the source and throughout the surrounding region;
⚫ the location, height and width of any obstructions (such as buildings or other structures) that
could significantly impact on the dispersion of the plume; and
⚫ sensitive receptor locations and heights.
For the purpose of the assessment, meteorological modelling has been undertaken using TAPM (The
Air Pollution Model) and CALMET to predict localised meteorological conditions. The meteorological
data derived from these models has been used as an input for the CALPUFF dispersion modelling.
4.2.2 TAPM
A site specific meteorological data set has been determined using the prognostic model TAPM (The
Air Pollution Model). Prognostic models, such as TAPM, permit the development of localised
meteorological data sets, based on synoptic weather conditions. The model predicts the regional
flows important to dispersion, such as sea breezes and terrain induced flows, against a background
of larger-scale meteorology provided by synoptic analyses. The output of this model provides a
meteorological data set suitable for introduction into a diagnostic meteorological model, such as
CALMET. Where good quality prognostic data is available for a site, this methodology is the
recommended approach for the modelling of contaminant concentrations using CALMET 1. It is noted
1 TRC Environmental Corporation (March 2011) 'Generic Guidance and Optimum Model Settings for the CALPUFF Modelling
System for Inclusion into the ‘Approved Methods for the Modelling and Assessments of Air Pollutants in NSW, Australia’
prepared on behalf of the NSW Office of Environment and Heritage.
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that a TAPM only run was considered initially however, calms were not accurately represented by the
model (under-predicted significantly). Therefore, observational data has also been considered in
conjunction with TAPM data as discussed in Section 4.2.3.4.
The 3D prognostic data was derived using TAPM (Version 4.05). The model was configured with a
series of nested grids chosen to provide an appropriate communication and transfer of information
from the broad synoptic to the local scale. The model was configured to use a domain consisting of
25 x 25 x 25 grid points with nesting spacings of 30 km, 10 km, 3 km and 1 km. Table 4.1 presents a
summary of the TAPM settings.
Table 4.1 - TAPM Settings
Setting/Input Value
Latitude, Longitude 26°24', 153°4'
Easting X, Northing Y (m) 506834, 7079975
Date 2014
Grid Points 25 x 25
Outer Grid Spacing 30 km x 30 km
Vertical Grid Levels 25 grid levels
10, 25, 50, 100, 150, 200, 250, 300, 400, 500, 600,
750, 1000, 1250, 1500, 1750, 2000, 2500, 3000, 3500,
4000, 5000, 6000, 7000, 8000
All levels stored in output
Number of Grid Domains 4 (30 km, 10 km, 3 km, 1 km)
4.2.3 CALMET
4.2.3.1 Overview
As discussed in the previous section, a three dimensional prognostic data set derived from the TAPM
model was input to CALMET to predict meteorological conditions at the development and
surrounding area. The following sections provide an overview of the data utilised in the CALMET
modelling, along with details of some of the key parameters selected to establish calculation limits
within CALMET.
4.2.3.2 Vertical Stations
For the purposes of the modelling, CALMET was initialised with a total of 10 vertical layers with layer
boundaries at 20 m, 40 m, 80 m, 160 m, 320 m, 640 m, 1,200 m, 2,000 m, 3,000 m and 4,000 m
respectively. The vertical levels used in the modelling were selected to provide the model with the
ability to predict atmospheric conditions at a range of heights. A greater resolution of vertical heights
has been adopted nearer to the ground, given the ground level sources considered in the
assessment.
4.2.3.3 Terrain And Land Use Data
Terrain data for the area surrounding the development was obtained from the Digital Elevation Model
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(DEM) 5 Metre Grid of Australia derived from LiDAR model, which represents a National 5 metre (bare
earth) DEM that has been derived from some 236 individual LiDAR surveys between 2001 and 2015.
Data for a 10 km x 10 km area (0.2 km spacing) has been extracted for use in the modelling.
Figures 4.1 and Error: Reference source not found presents the modelled terrain and land use in
CALMET. A TERRAD value of 6 km has been adopted based on the surrounding topography and ridges.
Figure 4.1 - Modelled Terrain
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4.2.3.4 Observation Data
Meteorological data from the nearest Bureau of Meteorology station at Tewantin RSL Park (3 km
north-west of the site) has been incorporated into the CALMET modelling. The Tewantin data set was
99.99% complete for the majority of surface parameters, including temperature, pressure, relative
humidity and wind speed/direction. Cloud cover and ceiling height were noted to be unavailable at
Tewantin RSL Park, as such prognostic cloud cover data from TAPM has been adopted. Figure 4.2
presents the location of the Tewantin RSL Park BOM station in relation to the site location.
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Legend
● Modelled BOM Stations
◆ Site Location
Figure 4.2 - CALMET modelled BOM Station location
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To incorporate both TAPM prognostic data and measured data, CALMET was run in a hybrid mode
(NOOBS=1) which combines both data sets to produce a site specific windfield. The NOOBS = 1
setting also utilises TAPM outputs for upper air data, this setting was adopted as the nearest station
to monitor upper air data is located in Brisbane (110 km south of the site) and is not considered
representative of the site conditions. An R1 and RMAX1 value of 8 km and 12 km have been adopted
for the Tewantin RSL Park BOM Station.
4.2.4 CALPUFF Dispersion Modelling
The CALPUFF modelling system treats emissions as a series of puffs. These puffs are then dispersed
throughout the modelling area and allowed to grow and bend with spatial variations in meteorology.
In doing so, the model is able to retain a memory of the plume's movement throughout a single hour
and from one hour to the next while continuing to better approximate the effects of complex air
flows.
CALPUFF utilises the meteorological processing and prediction model CALMET to provide three
dimensional wind field predictions for the area of interest. The final wind field developed by the
model (for consideration by CALPUFF) includes an approximation of the effects of local topography,
the effects of varying surface temperatures (as is observed in land and sea bodies) and surface
roughness (resulting from varied land uses and vegetation cover in an area). The CALPUFF model is
able to resolve complex terrain influences on local wind fields including consideration of katabatic
flows and terrain blocking.
4.2.5 CALPOST
Post processing of modelled emissions is undertaken using the CALPOST package. This allows the
rigorous analysis of pollutant predictions generated by the CALPUFF system. In particular CALPOST is
able to provide an analysis of predicted pollutant concentrations for a range of averaging periods
from 1 hour to 1 year.
4.3 Meteorological Predictions
4.3.1 Wind Predictions
Predicted 2014 wind conditions have been compared to measured wind data (2012-2016) at the
Tewantin RSL Park Bureau of Meteorology Station (3 km north-west of the development site).
Figure 4.3 presents shows wind roses for the measured and predicted data.
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2012-2016 Measured (Tewantin RSL Park Station) 2016 CALMET Prediction (Tewantin RSL Park Station)
2016 CALMET Prediction (Site)
Figure 4.3 - Measured Wind Roses 2012-2016 vs 2016 CALMET Predicted Site Wind Roses
Predicted and measured wind roses are noted to be comparable at the Tewantin RSL BOM station.
The wind roses show a dominant southerly and south-easterly component, and low proportion of
westerly winds. The southerly source-to-receiver component is under-predicted by the model (11.9%
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predicted vs 16.3% measured). However, overall source-to-receiver winds towards the northern two-
storey buildings are predicted to occur as a similar frequency to the measured data (i.e. predicted
southerly flows (SSW,S,SSE) are noted to be similar compared to the measured data (28.1%
measured and 25.1% predicted)).
Calm conditions are noted to be well represented by the model with calm conditions occurring at the
BOM station 13.7% of the time vs 13.6% predicted. CALM conditions are slightly lower at the subject
site which is likely due to the site’s close proximity to the coast line (10.7% predicted). Low wind
speeds are over-represented by the model with wind speeds less than 2 m/s (measured 17.5% and
predicted 22.6%).
Overall, based on the above comparison, the predicted wind conditions are considered suitable for
the assessment of potential air quality impacts.
4.3.2 Predicted Atmospheric Stability
The amount of turbulence in the ambient air has a major effect upon the rise and dispersion of
emissions. The amount of turbulence in the atmosphere is often described using series of six Pasquill
stability classes A, B, C, D, E and F. Of these, Class A denotes the most unstable or most turbulent
conditions and Class F denotes the most stable or least turbulent conditions. Table 4.2 provides a
summary of the predicted atmospheric stability conditions (derived by CALMET) for the area.
Table 4.2 - Summary of Predicted Stability Classes by Hour
Predicted Pasquill Stability Class
Hour
A B C D E F
0 0 0 0 139 28 196
1 0 0 0 150 23 190
2 0 0 0 164 17 182
3 0 0 0 177 16 170
4 0 0 0 181 19 163
5 0 0 38 207 8 110
6 0 11 96 212 2 42
7 0 29 105 229 0 0
8 1 59 69 234 0 0
9 2 69 63 229 0 0
10 14 82 60 207 0 0
11 6 90 60 207 0 0
12 2 88 83 190 0 0
13 0 66 94 203 0 0
14 0 26 97 240 0 0
15 0 12 104 247 0 0
16 0 1 72 290 0 0
17 0 0 8 259 21 75
18 0 0 2 150 74 137
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Predicted Pasquill Stability Class
Hour
A B C D E F
19 0 0 0 114 87 162
20 0 0 0 106 77 180
21 0 0 0 115 49 199
22 0 0 0 121 40 202
23 0 0 0 132 31 200
% 0.29% 6.12% 10.92% 51.69% 5.65% 25.34%
4.3.3 Predicted Mixing Heights
Figure 4.4 presents a plot showing predicted mixing heights for each hour of the day. As expected,
higher mixing heights occur during the day time, while lower mixing heights occur during the night
period when stable conditions are dominant and temperature inversions occur.
° Represents outliers to the data set. Outliers are defined as those values in the data set which are
greater than 1.5 x the Inter Quartile Range above the upper (Q3) or lower (Q1) quartiles.
Figure 4.4 - Predicted Mixing Heights
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4.4 Source Locations
Figure 4.5 in presents the location of the CALPUFF modelled air emission sources for the service
station.
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Figure 4.5 - Modelled Source Locations
4.5 Downwash Structures
Based on a review of the modelled stack heights and existing/proposed buildings, various downwash
structures have been included. Buildings which are greater than stack heights divided by a factor of
2.5, and within a radius of 5 times the lesser of the building height or projected building width have
been considered. Figure 4.8 presents the modelled buildings and relative heights.
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Note: Numerical values represent relative heights of buildings
Figure 4.6 - Building Downwash Structures
4.6 Discrete Receptors
Discrete receptors have been modelled at 1.5 m and 4.5 m above ground level to represent the
facades of the nearest residential houses. Additionally, a 92 m x 98 m grid with a spacing of 2 m has
been modelled to allow for the creation of plots at 1.5 m and 4.5 m above ground level. The location
of the facade receptors and gridded receptors is shown in Figure 4.7.
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Figure 4.7 - Discrete Air Modelling Receptor Locations
4.7 Background Air Monitoring Data
To allow assessment of cumulative pollutant concentrations, background concentrations have been
considered for the types of compounds emitted from service station. Air quality data from the
Queensland Government air quality monitoring network has been utilised in the air quality
assessment. Data utilised was from the Springwood air quality monitoring station for the years 2015,
2016 and 2017, which was accessed from the Queensland Government Data website 2,3,4. It is noted
that Springwood is the only station in South-East Queensland which monitors for VOCs. Table 4.3
presents the background air quality data used in the dispersion modelling.
Table 4.3 - Summary of Average Ambient Pollutant Concentrations for QLD (January 2015 to
December 2017)
Averaging Time, Ambient Pollutant
Pollutant Station
Statistic Concentration (µg/m3)
Benzene Maximum Annual Average 5.5 Springwood
th
Toluene 1 hour, 70 percentile 23.0 Springwood
2 https://data.qld.gov.au/dataset/air-quality-monitoring-2015
3 https://data.qld.gov.au/dataset/air-quality-monitoring-2016
4 https://data.qld.gov.au/dataset/air-quality-monitoring-2017
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Averaging Time, Ambient Pollutant
Pollutant Station
Statistic Concentration (µg/m3)
24 hours, 70th percentile 22.4
Maximum Annual Average 18.5
24-hr, 70th percentile 47.1
Total Xylenes Springwood
Maximum Annual Average 41.3
4.8 Emission Parameters
Fugitive emissions from refuelling areas have been modelled as volume sources (one per rank of
bowsers, total of 4) at a height of 1.0 m above ground with horizontal and vertical dispersion values
of 1.0 m. Vent stack emission parameters for the petrol vent have been modelled with the following
parameters:
⚫ Diameter (m) – 0.1;
⚫ Velocity (m/s) – 0.1;
⚫ Temperature – Ambient; and
⚫ Height (m) – 4.
5 Summary of Assumptions
Below is a list of key assumptions considered in the modelling:
⚫ It is assumed that 40 kL bulk tanker deliveries occur continuously throughout the day (24/7). In
reality, tanker deliveries would likely occur a few times a week only;
⚫ all fuel handling is considered to be petrol providing a conservative emissions generation
procedure (i.e., petrol has a higher volatility than diesel);
⚫ for tank filling, a maximum fuel delivery of 40 kL/hour has been considered;
⚫ worst case CAPCOA “whoosh” emissions adopted to represent slightly higher volatility of
Australian fuels;
5.1 Modelling Results
Table 4.4 presents the predicted maximum concentrations at the adjacent residential receptors. The
results of the modelling show compliance with the air quality goals at all discrete receptors. The
highest pollutant concentrations are predicted at 4.5m above ground (second storey of nearest
dwellings). Figures 4.8 and 4.9 presents the predicted ground level and first floor concentrations of
odour.
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Table 4.4 - Predicted Results – Residential Receptors
Maximum Predicted Concentrations at Modelled
Sensitive Receptors (mg/m3) Air Quality Averaging
Compound 3
Goal (mg/m ) Time
Source Only Background Cumulative
Benzene 1.7 5.5 7.2 10 Annual
102.2 23 125.2 1100 30 Minutes
Toluene 30.4 22.4 52.8 4100 24 Hours
6.7 18.5 25.2 410 Annual
13.6 47.1 60.7 1200 24 Hours
Xylenes
3.0 41.3 44.3 950 Annual
Cyclohexane 43.3 - - 19000 1 Hour
n-Hexane 68.0 - - 3200 1 Hour
Ethylbenzene 7.3 - - 8000 1 Hour
0.1 - - 75 30 Minutes
Styrene
0.009 - - 280 7 Days
Cumene 7.6 - - 21 1 Hour
1-hour, 99.5th
Odour 0.9 - - 2.5
Percentile
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Figure 4.8 - Predicted Ground Level Odour Concentrations
Height: 1.5 m above ground Averaging Time: 1-hour, 99.5th Percentile
Location: Noosaville Units: OU
Pollutant: Odour Criteria: 2.5
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Figure 4.9 - Predicted First Floor Odour Concentrations
Height: 4.5 m above ground Averaging Time: 1-hour, 99.5th Percentile
Location: Noosaville Units: OU
Pollutant: Odour Criteria: 2.5
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6 Conclusions
Air dispersion modelling of potential air emissions from a proposed service station redevelopment at
52-54 Mary Street, Noosaville. Predicted pollutant concentrations of VOCs and odour have been
compared to the criteria specified in the Environmental Protection (Air) Policy 2008 (EPP Air) and
other relevant air quality goal guidelines. The results of the dispersion modelling indicates
compliance with the relevant air quality and odour criteria at the nearest sensitive receptors,
provided the following measures in place:
⚫ Operating hours of 5 am to 10 pm;
⚫ Stage 1 and 2 vapour recovery;
⚫ 4 m high fuel tank vents at the location identified in Figure 4.5.
From an air quality perspective and provided the above measures in implemented, the site
represents a suitable location for the proposed service station.
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Appendix A - Air Quality Glossary
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APPENDIX A: GLOSSARY OF AIR QUALITY TERMINOLOGY
Conversion of ppm to Where R is the ideal gas constant; T, the temperature in Kelvin (273.16
mg/m3 + T°C); and P, the pressure in mm Hg, the conversion is as follows:
g m-3 = (P/RT) x Molecular weight x (concentration in ppm)
= P x Molecular weight x (concentration in ppm)
62.4 x (273.2 + T°C)
g/s Grams per second
mg/m3 Milligrams (10-3) per cubic metre.
μg/m3 Micrograms (10-6) per cubic metre.
ppb Parts per billion.
ppm Parts per million.
PM10, PM2.5, PM1 Fine particulate matter with an equivalent aerodynamic diameter of less
than 10, 2.5 or 1 micrometres respectively. Fine particulates are
predominantly sourced from combustion processes. Vehicle emissions
are a key source in urban environments.
50th percentile The value exceeded for 50 % of the time.
NOx Oxides of nitrogen – a suite of gaseous contaminants that are emitted
from road vehicles and other sources. Some of the compounds can react
in the atmosphere and, in the presence of other contaminants, convert
to different compounds (eg, NO to NO2).
VOC Volatile Organic Compounds. These compounds can be both toxic and
odorous.
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