the ranch poultry production complex...the ranch poultry production complex farm 3 - proposed...

Appendix D

Air Quality Impact Assessment (SLR 2017a)

The Ranch Poultry Production Complex

Farm 3 - Proposed Expansion

Air Quality Impact Assessment

Report Number 630.11566

31 July 2017

Scolexia Pty Ltd

16 Learmonth Street

MOONEE PONDS VIC 3039

Version: v1.0

Scolexia Pty Ltd The Ranch Poultry Production Complex Farm 3 - Proposed Expansion Air Quality Impact Assessment

Report Number 630.11566 31 July 2017

v1.0 Page 2

SLR Consulting Australia Pty Ltd

The Ranch Poultry Production Complex

Farm 3 - Proposed Expansion

Air Quality Impact Assessment

PREPARED BY:

SLR Consulting Australia Pty Ltd ABN 29 001 584 612

10 Kings Road

New Lambton NSW 2305 Australia

(PO Box 447 New Lambton NSW 2305 Australia)

+61 2 4037 3200 +61 2 4037 3201

[email protected] www.slrconsulting.com

This report has been prepared by SLR Consulting Australia Pty Ltd

with all reasonable skill, care and diligence, and taking account of the

timescale and resources allocated to it by agreement with the Client.

Information reported herein is based on the interpretation of data collected,

which has been accepted in good faith as being accurate and valid.

This report is for the exclusive use of Scolexia Pty Ltd.

No warranties or guarantees are expressed or should be inferred by any third parties.

This report may not be relied upon by other parties without written consent from SLR.

SLR disclaims any responsibility to the Client and others in respect of any matters outside the agreed scope of the work.

DOCUMENT CONTROL

Reference Status Date Prepared Checked Authorised

630.11566 V1.0 31 July 2017 F. Rahaman K. Lawrence/ A. Williams

K. Lawrence/ A. Williams



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Table of Contents


1 INTRODUCTION 6

2 DEVELOPMENT OVERVIEW 8

2.1 Regional Context 8

2.2 Local Context 10

2.3 Development Summary 11

2.4 Surrounding Land Use 11

2.5 Sensitive Receptors 13

2.6 Hours of Operation 16

2.7 Local Topography 16

3 IMPACT ASSESSMENT CRITERIA 17

3.1 Odour 17

3.2 Particulate Matter 18

3.2.1 Total Suspended Particulate 18

3.2.2 PM10 and PM2.5 19

3.2.3 Deposited Dust 19

3.3 Summary of Project Air Quality Goals 19

4 POLLUTANT EMISSION ESTIMATION 20

4.1 Odour 20

4.1.1 Methodology 20

4.1.2 Odour Emissions Estimation 20

4.1.3 Validation of Estimated Ventilation Rate 24

4.2 Particulates 25

5 DISPERSION MODELLING CONFIGURATION 26

5.1 Model Selection 26

5.2 Accuracy of Modelling 26

5.3 Meteorological Modelling 27

5.3.1 Selection of the Meteorological Year 27

5.3.2 TAPM 28

5.3.3 CALMET 28

5.3.4 Meteorological Data Used in Modelling 29

5.4 Odour Peak-to-Mean Ratios 35

5.5 Emission Sources 35

5.5.1 Odour 35

5.5.2 Particulates 36

5.6 Building Wake Effects 36

5.7 Regional Odour Sources 36



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Table of Contents


5.8 Scenarios Assessed 37

6 RESULTS AND DISCUSSSION 38

6.1 Odour Impact Assessment 38

6.1.1 Scenario 1 – Incremental Impact of Farm 3 38

6.1.2 Scenario 2 – Cumulative Impacts 40

6.2 Sensitivity Analysis – Bird Placement Date 42

6.3 Sensitivity Analysis – Other Operational Parameters 42

6.4 Dust Impact Assessment 43

7 MITIGATION AND MONITORING MEASURES 44

8 CONCLUSIONS 45

9 REFERENCES 46



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Table of Contents


TABLES

Table 1 Key Elements of The Ranch Farm 3 11 Table 2 Location of the Identified Sensitive Receptors 13 Table 3 Impact Assessment Criteria for Complex Mixtures of Odorous Air Pollutants 18 Table 4 EPA Goals for Allowable Dust Deposition 19 Table 5 Project Air Quality Goals 19 Table 6 Parameters used in the Odour Emissions Estimation for The Project Site 21 Table 7 Shed Ventilation as a Percentage of Maximum Ventilation 22 Table 8 A Summary of the Schedule for Bird Removal from Each Poultry Shed 22 Table 9 Meteorological Parameters used for the AQIA - TAPM 28 Table 10 Meteorological Parameters used for this Study – CALMET (v 6.42) 29 Table 11 Meteorological Conditions Defining Pasquill Stability Classes 32 Table 12 Parameters for each Vent type for each Poultry Shed 36 Table 13 Summary of the Parameters used in Modelling of Background Odour Sources 37 Table 14 Predicted 99

th Percentile Nose-Response Odour Concentrations (OU) – Scenario 1 38

Table 15 Predicted 99th Percentile Nose-Response Odour Concentrations (OU) – Scenario 2 40

Table 16 Sensitivity Analysis – Bird Placement Date 42 Table 17 Predicted PM10 Concentrations 43

FIGURES

Figure 1 Regional Location of the Development Site 9 Figure 2 Local Setting of the Development Site 10 Figure 3 Residential and Commercial Receptors Surrounding the Project Site (UTM Zone

55) 15 Figure 4 Local Topographical Features 16 Figure 5 Varying Bird Density and Ventilation Rate Profile for the Project Site 21 Figure 6 Modelled Shed Odour Emission Rates through a Representative Bird Cycle 23 Figure 7 Modelled Shed Odour Emission Rates throughout the Year – Sheds 1, 2 and 3 24 Figure 8 Comparison of Estimated and Measured Ventilation Rates (%) 25 Figure 9 Predicted Seasonal Wind Roses for the Development Site (CALMET predictions,

2012) 31 Figure 10 Predicted Stability Class Frequencies at the Development Site (CALMET

predictions, 2012) 33 Figure 11 Predicted Mixing Heights at the Development Site (CALMET predictions, 2012) 34 Figure 12 Predicted Temperatures at Development Site (CALMET predictions, 2012) 35 Figure 13 Predicted 99

th Percentile Nose-Response Odour Concentration (OU) –Scenario 1 39

Figure 14 Predicted 99th Percentile Nose-Response Odour Concentration (OU) – Scenario 2 41

APPENDICES

Appendix A Selection of Representative Meteorological Data


Report Number 630.11566 v1.0

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1 INTRODUCTION

SLR Consulting Australia Pty Ltd (SLR) has been commissioned by Scolexia Pty Ltd (Scolexia), on behalf of VOAG 3 Pty Ltd (VOAG 3), a subsidiary of VOAG Pty Ltd (VOAG), to undertake an air quality impact assessment (AQIA) for the proposed expansion of an approved poultry broiler production farm (“The Ranch Farm 3”) within a rural property in the area known as Tabbita, approximately 26 kilometres (km) northwest of Griffith in southwestern New South Wales (NSW).

On 15 December 2015, Carrathool Shire Council (Council) granted Development Consents DA

2016/017, DA 2016/022 and DA 2016/023 to develop The Ranch Farm 1, The Ranch Farm 2 and The

Ranch Farm 3 respectively. On 15 November 2016 Council granted Development Consents DA

2016/043 and DA 2016/044 to develop The Ranch Farm 4 and The Ranch Farm 5 respectively. The

Ranch Farm 1, The Ranch Farm 2 and The Ranch Farm 3 were approved to operate 8 sheds in each

farm with a bird capacity of 400,000 birds per farm. The Ranch Farm 4 and The Ranch Farm 5 were

approved to operate 16 sheds in each farm with a bird capacity of 800,000 birds per farm.

Given the environmental impact assessments for these developments did not predict any significant

adverse impacts on the local environmental or surrounding community, and responding to the

increasing demand for poultry meat in the Australian market, VOAG is now seeking a new

development consent. The new development consent will be to allow all currently approved

construction and operation of The Ranch Farm 3, along with the construction and operation of an

additional eight poultry sheds (the Development). The Development (i.e. the subject of this

document)will increase the bird capacity from 400,000 birds to 800,000 birds. Collectively, The Ranch

Farms 1 to 5 are being referred to as The Ranch Poultry Production Complex.

For the purposes of this AQIA, the overarching development site comprising the five farms is referred to as “The Ranch Development Site”, while the development site subject to this particular AQIA is referred to as “The Ranch Farm 3 Site” (the Development Site).

The aim of this AQIA is to quantify the change in potential dust and odour impacts in the region due to the operation of the Development in isolation, as well as the cumulative impacts of The Ranch Poultry Production Complex (i.e. the five farms) and other surrounding poultry developments. This AQIA forms a part of the overall EIS for the Development Site.

This report has been prepared with reference to the guideline document Approved Methods for the Modelling and Assessment of Air Pollutants in New South Wales (DEC 2005) (hereafter Approved Methods). For the assessment of potential odour emissions, this report also refers to the Technical Framework: Assessment and management of odour from stationary sources in NSW (DEC 2006a) (hereafter the Odour Framework) and the Technical Notes: Assessment and management of odour from stationary sources in NSW (DEC 2006b) (hereafter the Technical Notes).

The Approved Methods and the Odour Framework outline the parameters that need to be determined in any AQIA as follows:

All potential emission sources - materials, equipment or activities (including transport, waste management and maintenance) (Section 2.3).

All nearby receptors potentially affected by dust and odour emissions (both current and future); this is particularly important where there is a potential for rezoning or subdivision (Section 2.5).

Operating hours and times when intermittent emission generating activities are likely to occur (Section 2.6).

Site features that may affect pollutant propagation and dispersion, including topography, vegetation, buildings and surrounding land uses (Section 2.7).



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The pollutant assessment criteria that were used to assess the proposal under current and future circumstances (for example, where possibility of a change in land use exists) (Section 3).

Weather conditions particular to the site (including prevailing wind directions and the likelihood of inversions or katabatic drift) (Section 5.3).

Likely air quality impacts (including odour impacts predicted using level 2 assessment) (Section 6).



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2 DEVELOPMENT OVERVIEW

2.1 Regional Context

The Development Site is located to the west of Back Hillston Road, approximately 26 km northwest of Griffith and 19 km southeast of Goolgowi in the Riverina region of southwestern NSW (see Figure 1).



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Figure 1 Regional Location of the Development Site



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2.2 Local Context

The Development Site is positioned within Lot 3 in Deposited Plan (DP) 1220390 and comprises approximately 51 hectares (ha) of vacant rural land within the Parish of Denny, County of Sturt and in Carrathool Local Government Area (LGA) (see Figure 2).

Figure 2 Local Setting of the Development Site



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2.3 Development Summary

With the proposed expansion, The Ranch Farm 3 will comprise sixteen tunnel-ventilated, fully-enclosed, climate-controlled poultry sheds.

On each shed, air extraction fans mounted at one end will uniformly draw air into the shed through mini-vents along the sides of the shed, and later in the growing cycle, across cooling pads and through tunnel vents. The air will flow over the chickens and be exhausted through a series of ventilation fans that will be housed within a fan box designed to direct the exhaust vertically upwards. Temperature sensors within the sheds will allow the ventilation to be adjusted as required.

The release of odorous air in a horizontal direction tends to ‘pool’ the odorous air in the atmosphere, especially during calm wind conditions (early morning and late night), which results in higher odour concentrations in the vicinity of the discharge point. The release of odorous air from the sheds using a fan box is expected to improve the vertical dispersion of odorous air in the atmosphere, thereby decreasing odour concentrations in the vicinity of the source.

Tunnel ventilation is easier to manage than natural ventilation and enables the grower to provide close to optimum conditions for bird health, growth and performance throughout the year. Additional benefits include better control over shed moisture levels, which is directly related to odour production.

Each shed will have the capacity to house a maximum of 50,000 birds at any one time, equating to a farm population of up to 800,000 birds.

The disturbance footprint for The Ranch Farm 3 will be relatively small and the commercial activities associated with the poultry operation will be largely confined to this area. The key elements of the development are summarised in Table 1.

Table 1 Key Elements of The Ranch Farm 3

Development Characteristic Proposed Development

Purpose Birds grown for human consumption

Number of poultry sheds 16, each measuring 176 metres (m) long by 18 m wide

Type of poultry sheds Tunnel-ventilated, fully-enclosed, climate-controlled

Maximum shed population 50,000 birds

Maximum farm population 800,000 birds

Maximum bird density within sheds 18 birds per square metre (m

2)

(and will not exceed a density of 34 kg/m2)

Hours of operation 24 hours a day, 7 days a week

Production cycle length Approximately 9 weeks (63 days), comprising 7.5 weeks (53 days) of bird occupation and a 1.5 week (10 days) cleaning phase

Number of production cycles per year On average, approximately 5.7

2.4 Surrounding Land Use

The land surrounding the Development Site is characterised by traditional agricultural production. Additional land uses within the area include a privately-owned and operational silo on Tysons Road located approximately 4.6 km southwest of the Development Site, the GrainCorp Tabbita Silo, which is currently closed, approximately 4.3 km southwest, JBS Australia’s Tabbita Feedlot (cattle feedlot) approximately 12.5 kilometres to the west and a number of approved/operational poultry farms. There is also a low density of surrounding residential dwellings. Additional detail regarding sensitive receptors is provided in Section 2.5.



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As advised in Section 1, The Ranch Farm 3 expansion is part of a larger development known as The Ranch Poultry Production Complex. This Complex comprises five approved farms (The Ranch Farm 1, The Ranch Farm 2, The Ranch Farm 3, The Ranch Farm 4 and The Ranch Farm 5).

At the time of preparing this AQIA, the following additional poultry developments were approved/proposed (i.e. Briefing Paper/Development Application Lodged) within the vicinity of the

Development Site1:

Existing

The Ranch Farm 1 (VOAG 1) – approved by Council in December 2015 under Development Consent DA 2016/017 and currently under construction. This development will comprise eight poultry sheds to accommodate up to 400,000 birds and is located approximately 1.4 kilometres south of the Development Site;

Jeanella Poultry Production Complex (ProTen) - approved by Council in 2012 under Development Consent DA 2013/005 and constructed in 2013. It is located approximately 23 km to north-west of the Development Site on the northern side of the Mid Western Highway. The Jeanella Complex comprises two PPUs, each with 12 poultry sheds (i.e. 24 poultry sheds in total), and accommodates up to 1,284,000 birds;

Jeanella South Poultry Production Complex (ProTen) – approved by Council in 2015 under Development Consent DA 2016/009 and constructed in 2016. It is located approximately 23 kilometres north-west of Expansion. The Jeanella South Complex comprises one PPU, with 16 poultry sheds and accommodates up to 856,000 birds;

Tabbita Farm 1 (NMS Enterprises) – approved by Council in August 2015 under Development Consent DA 2015/040 and constructed. This development comprises 20 poultry sheds to accommodate up to 1,020,000 birds and is located approximately 8.7 km west of the Development Site;

Tabbita Farm 2 (NMS Enterprises) – approved by Council in September 2015 under Development Consent DA 2016/005 and constructed. This development comprises 20 poultry sheds to accommodate up to 1,020,000 birds and is located approximately 8.2 km west of the Development Site; and

Tabbita Farm 3 (NMS Enterprises) – approved by Council in December 2015 under Development Consent DA 2016/018 and under construction. The development will comprise 20 poultry sheds to accommodate up to 1,020,000 birds and will be located approximately 10 km west of the Development Site.

Privately owned silo on Tysons Road. It is noted that the odour from a silo is likely to be significantly different from the odour generated from a poultry farm,

GrainCorp’s Tabbita Silo, which is currently closed.

JBS Australia’s Tabbita Feedlot (cattle feedlot), located approximately 13 km west of the Project Site.

Approved (i.e. development consent issued but not yet constructed)

Maylands Farm A (Lemic Holdings) – approved by Council in August 2015 under Development Consent DA 2015/041. This development comprises 24 poultry sheds to accommodate up to 1,360,800 birds and will be located approximately 17 km north-west of the Development Site to the east of Goolgowi.

1 Source: Carrathool Shire Council available online at

http://www.carrathool.nsw.gov.au/planning/public-exhibition, on 18 August 2015.

http://www.carrathool.nsw.gov.au/planning/public-exhibition



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Maylands Farm B (Lemic Holdings) – approved by Council in December 2015 under Development Consent DA 2016/021. This development will comprise 24 poultry sheds to accommodate up to 1,360,800 birds and will be located approximately 14 km north-west of the Development Site to the east of Goolgowi;

The Ranch Farm 2 (VOAG 2) – approved by Council in December 2015 under Development Consent DA 2016/22. This development will comprise eight poultry sheds to accommodate up to 400,000 birds and is located approximately 600 metres south of the Development Site;

The Ranch Farm 3 (VOAG 3) – approved by Council in December 2015 under Development Consent DA 2016/23. This development will comprise eight poultry sheds to accommodate up to 400,000 birds;

The Ranch Farm 4 (VOAG 4) – approved by Council in November 2016 under Development Consent DA 2016/043. This development will comprise sixteen poultry sheds to accommodate up to 800,000 birds and is located approximately 800 metres north of the Development Site; and

The Ranch Farm 5 (VOAG 5) – approved by Council in November 2016 under Development Consent DA 2016/044. This development will comprise sixteen poultry sheds to accommodate up to 800,000 birds and is located approximately 1.4 kilometres north of the Development Site.

Proposed (i.e. Briefing Paper/Development Application Lodged)

Tabbita Farm 4 (Tabbita Poultry Pty Ltd) – poultry production complex proposed approximately 9.5 km west of the Development Site. The proposal comprises 18 poultry sheds to accommodate up to 918,000 birds;

The Ranch Farm 2 Expansion (VOAG 2) – continued construction and operation of approved The Ranch Farm 2 (see above) with the construction and operation of an additional eight poultry sheds. The expanded development will comprise 16 sheds to accommodate up to 800,000 birds;

The Ranch Farm 1 Expansion (VOAG 1) – continued construction and operation of approved The Ranch Farm 1 (see above) with the construction and operation of up to an additional eight poultry sheds. The expanded development will comprise up to 16 sheds to accommodate up to 800,000 birds; and

Goolgowi Poultry Farms (Muscat Developments) - poultry production complex comprising five farms, of 20 sheds each which will accommodate up to 1,200,000 birds. The development is located 47 kilometres south-west of the Expansion.

The background odour impacts from the above land uses are discussed in detail in Section 5.7.

2.5 Sensitive Receptors

The Development Site is removed from any urban areas. Council has advised that Tabbita, which is located approximately 3.9 km southwest of the Development Site, comprises five residences. The nearest sensitive receptor lies 3.9 km southwest of the Development Site. The receptor locations adopted within this assessment are listed in Table 2 and shown in Figure 3.

Table 2 Location of the Identified Sensitive Receptors

Receptor ID Location

X (km) UTM 56

Y (km) UTM 56

Elevation (m, AHD)

Approximate Distance from Development Site (km)

R1 Tysons Road, Tabbita 398.741 6,225.241 142.4 3.9

R2 Back Hillston Road, Tabbita 398.938 6,224.469 144.0 4.7

R3 Back Hillston Road, Tabbita 396.509 6,222.022 116.6 6.6

R4 Kidman Way, Tabbita 394.968 6,222.975 113.7 5.9

R5 Tabbita Lane, Tabbita 392.512 6,223.637 115.4 6.2



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Receptor ID Location

X (km) UTM 56

Y (km) UTM 56

Elevation (m, AHD)

Approximate Distance from Development Site (km)







R12 Youngs Lane, Tabbita 391.297 6,232.258 125.9 5.6

R13 Kidman Way, Tabbita (workshop/shed on Lot 40 DP756045)

392.469 6225.940 119.0 4.5

The dwelling identified on Figure 3 in Lot 6 in DP 1220390 is derelict and uninhabitable. A complying development certificate was issued by Council on 15 June 2015 for the demolition of this dwelling (CDC 2015_016).



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Figure 3 Residential and Commercial Receptors Surrounding the Project Site (UTM Zone 55)



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2.6 Hours of Operation

While the development will operate 24 hours a day, seven days a week, the majority of activity will be carried out between 7.00 am and 7.00 pm. As the birds reach their desired processing (slaughter) weight they will be removed from the sheds and transported from the site between 7.00 pm and 4.00 pm, although for reasons of livestock welfare they will generally be removed overnight and in the morning when it is cooler and the birds are more settled.

There will typically be one daily shift for farm workers commencing at 7.00 am and finishing at 4.00 pm.

2.7 Local Topography

The topographical data used in the modelling assessment was sourced from the United States Geological Service’s Shuttle Radar Topography Mission database that has recorded topography across Australia with a 3 arc second (approximately 90 m) spacing. The topography of the region surrounding the Development Site is shown in Figure 4.

Figure 4 Local Topographical Features



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3 IMPACT ASSESSMENT CRITERIA

The potential emissions to air associated with poultry farm operations are odour and particulate matter. The regulatory criteria used to assess the potential impacts on ambient air quality of these emissions are discussed below.

3.1 Odour

Impacts from odorous air contaminants are often nuisance-related rather than health-related. Odour performance goals guide decisions on odour management, but are generally not intended to achieve “no odour”.

The detectability of an odour is a sensory property that refers to the theoretical minimum concentration that produces an olfactory response or sensation. This point is called the odour threshold and defines one odour unit (OU). An odour goal of less than 1 OU would theoretically result in no odour impact being experienced.

In practice, the character of a particular odour can only be judged by the receiver’s reaction to it, and preferably only compared to another odour under similar social and regional conditions. Based on the literature available, the level at which an odour is perceived to be a nuisance can range from 2 OU to 10 OU depending on a combination of the following factors:

Odour Quality: whether an odour results from a pure compound or from a mixture of compounds. Pure compounds tend to have a higher threshold (lower offensiveness) than a mixture of compounds.

Population sensitivity: any given population contains individuals with a range of sensitivities to odour. The larger a population, the greater the number of sensitive individuals it may contain.

Background level: whether a given odour source, because of its location, is likely to contribute to a cumulative odour impact. In areas with more closely-located sources it may be necessary to apply a lower threshold to prevent offensive odour.

Public expectation: whether a given community is tolerant of a particular type of odour and does not find it offensive, even at relatively high concentrations. For example, background agricultural odours may not be considered offensive until a higher threshold is reached than for odours from a landfill facility.

Source characteristics: whether the odour is emitted from a fan box (point source) or from an area (diffuse source). Generally, the components of point source emissions can be identified and treated more easily than diffuse sources. Point sources tend to be located in urban areas, while diffuse sources are more often located in rural locations.

Health Effects: whether a particular odour is perceived to potentially be associated with adverse health effects. In general, odours from agricultural activities are less likely to present a health risk than emissions from industrial facilities.

Experience gained through odour assessments for proposed and existing facilities in NSW indicates that an odour performance goal of 7 OU is likely to represent the level below which “offensive” odours should not occur (for an individual with a ‘standard sensitivity’ to odours). The NSW Environment Protection Authority (EPA) recommends within the Odour Framework that, as a design goal, no individual be exposed to ambient odour levels of greater than 7 OU. This is expressed as the 99

th

percentile value, as a nose response time average (approximately one second).



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Odour performance goals need to be designed to take into account the range in sensitivities to odours within the community, and provide additional protection for individuals with a heightened response to odours. In NSW this is done using a statistical approach which depends on the size of the affected population. As the affected population size increases, the number of sensitive individuals is also likely to increase, which suggests that more stringent goals are necessary in these situations. In addition, the potential for cumulative odour impacts in relatively sparsely populated areas can be more easily defined and assessed than in highly populated urban areas. It is often not possible or practical to determine and assess the cumulative odour impacts of all odour sources that may impact on a receptor in an urban environment. Therefore, the proposed odour performance goals allow for population density, cumulative impacts, and anticipated odour levels during adverse meteorological conditions and community expectations of amenity.

A summary of odour performance goals for various population densities, as referenced in the Approved Methods is shown in Table 3.

Table 3 Impact Assessment Criteria for Complex Mixtures of Odorous Air Pollutants

Population of Affected Community Impact Assessment Criteria for Complex Mixtures of Odours (OU)

Urban area (> 2000) 2.0

~500 3.0

~125 4.0

~30 5.0

~10 6.0

Single residence (< 2) 7.0

Source: EPA 2017

The Approved Methods state that the impact assessment criteria for complex mixtures of odorous air pollutants must be:

Applied at the nearest existing or likely future off-site sensitive receptor(s); and

The incremental impact (predicted impact due to the pollutant source alone) must be reported in units consistent with the impact assessment criteria (OU), as peak concentrations (i.e. approximately 1 second average) and as the 99

th percentile of dispersion model predictions for

Level 2 impact assessments.

Based on the feedback provided by the NSW EPA on the odour impact assessment for The Ranch Farm 4 and The Ranch Farm 5, a conservative odour criterion of 5 OU was adopted in this assessment for the surrounding sensitive receptors.

3.2 Particulate Matter

3.2.1 Total Suspended Particulate

Airborne contaminants that can be inhaled directly into the lungs can be classified on the basis of their physical properties as gases, vapours or particulate matter. In common usage, the terms “dust” and “particulates” are often used interchangeably. The term “particulate matter” refers to a category of airborne particles, typically less than 30 microns (μm) in diameter and ranging down to 0.1 μm and is termed total suspended particulate (TSP). The annual average goal for TSP recommended by the EPA is 90 micrograms per cubic metre of air (μg/m

3).



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3.2.2 PM10 and PM2.5

Emissions of particulate matter less than 10 μm and 2.5 μm in diameter (referred to as PM10 and PM2.5 respectively) are considered important pollutants due to their potential health implications.

The EPA’s particulate assessment goals set out in the Approved Methods (2017) are as follows:

A maximum 24-hour average PM10 concentration of 50 µg/m3; and

An annual average PM10 concentration of 25 µg/m3.

A maximum 24-hour average PM2.5 concentration of 25 µg/m3; and

An annual average PM2.5 concentration of concentration of 8 µg/m3.

3.2.3 Deposited Dust

The preceding section is concerned in large part with the health impacts of airborne particulate matter. Nuisance impacts need also to be considered in relation to deposited dust. In NSW, accepted practice regarding the nuisance impact of dust is that dust-related nuisance can be expected to impact on residential areas when annual average dust deposition levels exceed 4 g/m

2/month.

Table 4 presents the impact assessment goals set out in the Approved Methods for dust deposition, showing the allowable increase in dust deposition level over the ambient (background) level to avoid dust nuisance.

Table 4 EPA Goals for Allowable Dust Deposition

Averaging Period Maximum Increase in Deposited Dust Level Maximum Total Deposited Dust Level

Annual 2 g/m2/month 4 g/m

2/month

Source: Approved Methods, EPA 2017.

3.3 Summary of Project Air Quality Goals

The air quality goals adopted for this assessment, which conform to current EPA and Federal air quality criteria, are summarised in Table 5.

Table 5 Project Air Quality Goals

Pollutant Averaging Time Goal

Odour 1-second nose response 99

th percentile

5 ou

TSP Annual average 90 µg/m3

PM10 Maximum 24 Hours Annual average

50 µg/m3

25 µg/m3

PM2.5 Maximum 24 Hours Annual average

25 µg/m3

8 µg/m3

Dust Deposition Annual Maximum incremental increase of 2 g/m

2/month

Maximum cumulative of 4 g/m2/month (Project and other sources)



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4 POLLUTANT EMISSION ESTIMATION

4.1 Odour

4.1.1 Methodology

The estimation of odour emissions from a poultry shed is a complex matter and depends on a number of inter-related parameters including, but not limited to, bird age/weight, ambient temperature, shed target temperature and ventilation rate. A literature review showed that a range of odour emission estimation methodologies are available to calculate the potential odour emission rate from a typical climate-controlled (tunnel ventilated) poultry shed in publicly available odour impact assessment reports for different farms. For this assessment, the widely accepted odour emissions model of Ormerod et al (2005) has been adopted.

The methodology presented by Ormerod et al (2005) takes into account a number of factors which have an impact on the odour generation within the chicken sheds, such as:

the number of birds, which varies later in the batch as harvesting takes place;

the stocking density of birds, which is a function of bird numbers, bird age and shed size;

ventilation rate, which depends on bird age and ambient temperature; and

design and management practices, particularly those aimed at controlling litter moisture.

The odour emissions model of Ormerod et al (2005) generates hourly varying emission rates from meat chicken farm sheds and is represented by the following equation:

𝑂𝐸𝑅 = 0.025 × 𝐾 × 𝐴 × 𝐷 × 𝑉0.5

where:

OER = hourly odour emission rate (OU.m³/s)

K = scaling factor between 1 and 5, where a value of 1 represents a very well designed and managed shed operating with minimal odour emissions, and a value of 4-5 would represent a shed with a serious odour management issues.

A = total shed floor area (m²)

D = average bird density (kg/m²)

V = ventilation rate (m³/s)

4.1.2 Odour Emissions Estimation

As discussed in Section 2.3, there will be a total of 16 sheds each capable of housing a total of 50,000 birds. The parameters used for the estimation of odour emissions from each shed are summarised in Table 6.



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Table 6 Parameters used in the Odour Emissions Estimation for The Project Site

Parameter Value Units Notes

K 2.0 - Confirmed with NSW EPA and used in The Ranch Farm 4 and The Ranch Farm 5 odour impact assessments

A 3,168 m2 Calculated based on the shed dimensions (see Table 1)

D hourly varying

kg/m2

Based on the number of birds and weight of each bird in the bird cycle (see Figure 5)

V hourly varying

m3/s

Based on bird age and target temperature inside the shed (see Figure 5)

The estimated varying bird density and the varying ventilation rate for a typical bird growth cycle during summer months are shown in Figure 5.

Figure 5 Varying Bird Density and Ventilation Rate Profile for the Project Site

Note: Ventilation rate representative of summer season.

It is noted that the bird density (D) is related to the age of the birds (and hence bird weight) and the stocking density (i.e. the number of birds placed per unit area).

The ventilation rate (V) at any given time is a function of the age of the birds and the ambient temperature. Table 7 provides an estimate of the ventilation required for a tunnel ventilated shed as a percentage of the maximum for summertime conditions.



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Table 7 Shed Ventilation as a Percentage of Maximum Ventilation

Bird Age (Weeks) 1 2 3 4 5 6 7 8

Temperature (°C) above Target

Ventilation Rate (as a percentage of the Maximum)

<1 1.7 2.6 5.1 7.7 9.8 11.5 17.0 17.0

1 1.7 12.5 12.5 25.0 25.0 25.0 25.0 25.0

2 1.7 25.0 25.0 37.5 37.5 37.5 37.5 37.5

3 1.7 37.5 37.5 50.0 50.0 50.0 50.0 50.0

4 1.7 37.5 37.5 50.0 50.0 50.0 50.0 50.0

6 1.7 37.5 37.5 62.5 75.0 75.0 75.0 75.0

7 1.7 37.5 37.5 62.5 75.0 75.0 87.5 100.0

8 1.7 62.5 62.5 62.5 75.0 75.0 100.0 100.0

9 1.7 62.5 62.5 87.5 100.0 100.0 100.0 100.0

Source: Ormerod et al 2005

It is noted that the ventilation rate may vary depending on the ambient temperature, for example during the winter months lower ventilation rates may be required to maintain the target temperature inside the shed. The varying ventilation rate profile shown in Figure 5 represents the bird cycle during the summer season.

As discussed in Section 2.3, the total bird cycle is assumed to be 63 days, including a 10 day cleanout period. Bird thinning will be carried out to maintain the stocking density below 34 kg/m² (RSPCA 2013). The Proponent anticipates that 25% of the total birds (i.e. 12,500 per shed) would be removed on day 32, day 38 and day 44, with the remaining birds removed around day 53. A summary of the periodic removal of birds from each of the sheds is shown in Table 8.

Table 8 A Summary of the Schedule for Bird Removal from Each Poultry Shed

Day of Cycle Variation in Number of Birds Number of Birds Remaining

1 +50,000 50,000

32 -12,500 37,500

38 -12,500 25,000

44 -12,500 12,500

53 -12,500 0

63 0 0

It is noted that bird mortality at day 32 is normally at least 2%. However, due to the uncertainty associated with estimating bird mortality, the data presented in Table 8 are based on a 0% mortality rate, which will result in a conservative assessment of potential odour impacts. It is expected that in reality, the number of birds in each shed will be slightly less than as presented in Table 8.

The variability of odour emissions for each shed during a full bird growth cycle is shown in Figure 6.



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Figure 6 Modelled Shed Odour Emission Rates through a Representative Bird Cycle

In Figure 6, the decline in emissions after day 53 represents the clean-out of the sheds. It is noted that the shed clean-out may result in elevated odour release associated with disturbance of the litter, but odour emissions from the sheds can be easily managed by minimising the amount of air exchange through the shed during clean-out and cleaning only during the daytime when atmospheric dispersion is most effective (Ormerod et al 2005).

The variability of estimated odour emissions for each shed for a year of operations is shown in Figure 7.

The drop in the overall emissions midway through the year corresponds to lower temperatures in the late autumn and winter months which result in lower ventilation rates and therefore less odour emissions from the sheds.



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Figure 7 Modelled Shed Odour Emission Rates throughout the Year – Sheds 1, 2 and 3

4.1.3 Validation of Estimated Ventilation Rate

As outlined in Section 4.1.2, shed ventilation rate was estimated based on the temperature difference (ambient and target shed temperature) and variation of percentage of maximum ventilation rate with temperature difference. Estimated required percentage of ventilation rates were compared with measured dataset from Australian Poultry CRC (APCRC 2011) for validation purpose and is presented in Figure 8. The measured dataset were collected at a number of tunnel ventilated poultry sheds located in Queensland (Gatton, Ipswich, Caboolture and Esk) and Victoria (Bendigo) with shed age ranging between 0 to 5 years. Farms were selected in Queensland and Victoria in an attempt to ensure that the measurements would be representative of poultry sheds in sub-tropical and temperature regions.

The comparison showed that the estimated ventilation rates are in reasonably good agreement with the measured dataset. The comparison also showed that the measured ventilation rate is generally within the range of the estimated ventilation rate. Based on this comparison, it can be concluded that the adopted ventilation rate estimation method is likely to be representative of the actual operation of the proposed farm.

It is noted that SLR has also investigated the option for validating the estimated ventilation rates with the empirical relations for five farms (two in Queensland, two in NSW and one in Victoria) published in RIRDC document “Monitoring Mechanical Ventilation Rates in Poultry Buildings” (RIRDC 2014). These empirical relationships are site specific and varied significantly between the five farms making the choice of which relationship is most appropriate to the farm being assessed difficult. Therefore, due to the differences in the meteorological (e.g. ambient temperature) and operating (e.g. target shed temperature, breed and growth rate) parameters between the proposed farm and the sampled farms, use of these relationships to estimate the ventilation rate for the proposed development would not be appropriate and therefore has not been considered further in this study.



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Figure 8 Comparison of Estimated and Measured Ventilation Rates (%)

4.2 Particulates

In addition to emissions of odour, intensive agricultural operations such as poultry farms have the potential to give rise to emissions of particulate matter (or ‘dust’). Dust from poultry farms can be generated from a range of sources including:

Earthworks and construction of the sheds during the construction phase;

Operational emission from the chicken sheds;

Vehicle movements on site;

Feed delivery; and

Shed cleaning.

Fugitive emissions of dust from construction activities, vehicle movements and shed cleaning operations are most appropriately managed by good site management and the implementation of dust suppression measures as outlined in Section 7. The significant separation distance between the farm and the nearest sensitive receptors would also reduce the risk of any off-site nuisance dust impacts.

Notwithstanding the above, to assess the potential off-site impacts of particulate emissions due to the operations of The Ranch Farm 3, reference is made to a study conducted by the Australian Poultry Cooperative Research Centre “Dust and Odour Emissions from Meat Chicken Sheds” (APCRC 2011). As part of this study, semi-continuous dust measurements were conducted on 50 separate days at three broiler farms using a DustTrak

TM and reported in terms of mass concentrations of PM10 and

PM2.5.

It was noted in the findings of this study that the concentration of particulate matter in the air exiting the sheds was highly variable and was influenced by ventilation rate, farm, bird age, season, microenvironment, litter management practices and other factors. The majority of the PM10 emission rates measured ranged from 5 mg/s to 50 mg/s per shed. For the purposes of this study, as a conservative approach, a PM10 emission rate of 50 mg/s per shed has been adopted for this study.



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5 DISPERSION MODELLING CONFIGURATION

5.1 Model Selection

Odour emissions from The Ranch Farm 3 have been modelled using the US EPA’s CALPUFF (Version 6) modelling system, as recommended by the EPA. CALPUFF is a transport and dispersion model that ejects “puffs” of material emitted from modelled sources, simulating dispersion and transformation processes along the way. In doing so it typically uses the fields generated by a meteorological pre-processor CALMET, discussed further below. Temporal and spatial variations in the meteorological fields selected are explicitly incorporated in the resulting distribution of puffs throughout a simulation period. The primary output files from CALPUFF contain either hourly concentration or hourly deposition fluxes evaluated at selected receptor locations. The CALPOST post-processor is then used to process these files, producing tabulations that summarise results of the simulation for user-selected averaging periods.

The advantages of using CALPUFF (rather than using a steady state Gaussian dispersion model such as Ausplume) is its ability to handle calm wind speeds (<0.5 m/s), complicated terrain and cumulative pollution impacts. Steady state models assume that meteorology is unchanged by topography over the modelling domain and may result in significant over or under estimation of air quality impacts.

More advanced dispersion models (such as CALPUFF) are approved for use by many regulatory authorities in situations where these models may be more appropriate than use of steady-state models and assumptions.

5.2 Accuracy of Modelling

All atmospheric dispersion models, such as CALPUFF, represent a simplification of the many complex processes involved in the dispersion of pollutants in the atmosphere. To obtain good quality results it is important that the most appropriate model is used and the quality of the input data (meteorological, terrain, source characteristics) is adequate.

The main sources of uncertainty in dispersion models, and their effects, are discussed below.

Oversimplification of physics: This can lead to both under-prediction and over-prediction of ground level pollutant concentrations. Errors are greater in Gaussian plume models as they do not include the effects of non-steady-state meteorology (i.e., spatially- and temporally-varying meteorology).

Errors in emission rates: Ground level concentrations are proportional to the pollutant emission rate. In addition, most modelling studies assume constant worst case emission levels or are based on the results of a small number of stack tests, however operations (and thus emissions) are often quite variable. Accurate measurement of emission rates and source parameters requires continuous monitoring.

Errors in source parameters: Plume rise is affected by source dimensions, temperature and exit velocity. Inaccuracies in these values will contribute to errors in the predicted height of the plume centreline and thus ground level pollutant concentrations.

Errors in wind direction and wind speed: Wind direction affects the direction of plume travel, while wind speed affects plume rise and dilution of plume. Errors in these parameters can result in errors in the predicted distance from the source of the plume impact, and magnitude of that impact. In addition, aloft wind directions commonly differ from surface wind directions. The preference to use rugged meteorological instruments to reduce maintenance requirements also means that light winds are often not well characterised.

Errors in mixing height: If the plume elevation reaches 80% or more of the mixing height, more interaction will occur, and it becomes increasingly important to properly characterise the depth of the mixed layer as well as the strength of the upper air inversion.



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Errors in temperature: Ambient temperature affects plume buoyancy, so inaccuracies in the temperature data can result in potential errors in the predicted distance from the source of the plume impact, and magnitude of that impact.

Errors in stability estimates: Gaussian plume models use estimates of stability class, and 3D models use explicit vertical profiles of temperature and wind (which are used directly or indirectly to estimate stability class for Gaussian models). In either case, errors in these parameters can cause either under-prediction or over-prediction of ground level concentrations. For example, if an error is made of one stability class, then the computed concentrations can be off by 50% or more.

The US EPA makes the following statement in its Modelling Guideline (US EPA, 2005) on the relative accuracy of models:

“Models are more reliable for estimating longer time-averaged concentrations than for estimating short-term concentrations at specific locations; and the models are reasonably reliable in estimating the magnitude of highest concentrations occurring sometime, somewhere within an area. For example, errors in highest estimated concentrations of

10 to 40% are found to be typical, i.e., certainly well within the often quoted factor-of-two accuracy that has long been recognised for these models. However estimates of concentrations that occur at a specific time and site, are poorly correlated with actually observed concentrations and are much less reliable.”

This AQIA utilises the CALPUFF dispersion model in full 3D mode, incorporating 3D meteorological output from TAPM and CALMET (refer Section 5.3). The meteorological dataset has been compiled using observations from nearby automatic weather stations and a five year period of meteorological data was reviewed to ensure that the year selected for use in the modelling is representative of long-term meteorological conditions. The use of the 99

th percentile (88

th highest) predictions given by the

model in assessing off-site impacts (in accordance with the relevant odour impact assessment guideline) also means that uncertainties associated with the peak model predictions for rare or unusual meteorological conditions are removed.

5.3 Meteorological Modelling

Meteorological mechanisms govern the dispersion, transformation and eventual removal of pollutants from the atmosphere. The extent to which pollution will accumulate or disperse in the atmosphere is dependent on the degree of thermal and mechanical turbulence within the earth’s boundary layer. Dispersion comprises vertical and horizontal components of motion. The stability of the atmosphere and the depth of the surface-mixing layer define the vertical component. The horizontal dispersion of pollution in the boundary layer is primarily a function of the wind field. The wind speed determines both the distance of downwind transport and the rate of dilution as a result of plume ‘stretching’. The generation of mechanical turbulence is similarly a function of the wind speed, in combination with the surface roughness. The wind direction, and the variability in wind direction, determines the general path pollutants will follow, and the extent of crosswind spreading.

Pollution concentration levels therefore fluctuate in response to changes in atmospheric stability, to concurrent variations in the mixing depth, and to shifts in the wind field (Oke 2004).

To adequately characterise the dispersion meteorology of the Development Site, information is needed on the prevailing wind regime, mixing depth and atmospheric stability and other parameters such as ambient temperature, rainfall and relative humidity.

5.3.1 Selection of the Meteorological Year

The Bureau of Meteorology (BoM) maintains automatic weather stations (AWS) throughout Australia. The closest such station was identified as Griffith Airport (Station # 75041).



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In order to determine a representative meteorological year for use in dispersion modelling, five years of meteorological data (2010-2014) from Griffith Airport were analysed against the long term meteorological conditions. Specifically, the following parameters were analysed:

Percentage of calm wind speed events (wind speed <0.5 m/s). Calm wind conditions are conducive to higher concentrations of odour due to poor dispersion of the odour plume.

Hourly wind speeds observed at 9:00 am and 3:00 pm.

Hourly temperature at 9:00 am and 3:00 pm.

Hourly relative humidity at 9:00 am and 3:00 pm.

Based on this analysis, it was concluded that the year 2012 was representative of the last five years of meteorological conditions experienced at the Development Site and hence the 2012 calendar year was adopted for use in this AQIA. A detailed analysis is shown in Appendix A.

5.3.2 TAPM

The TAPM prognostic model, developed by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) was used to generate the three dimensional upper air data required for CALMET modelling (Section 5.3.3).

TAPM predicts wind speed and direction, temperature, pressure, water vapour, cloud, rain water and turbulence. The program allows the user to generate synthetic observations by referencing databases (covering terrain, vegetation and soil type, sea surface temperature and synoptic scale meteorological analyses) which are subsequently used in the model input to generate one full year of hourly meteorological observations at user-defined levels within the atmosphere.

Additionally, TAPM may assimilate actual local wind observations so that they can optionally be included in a model solution. The wind speed and direction observations are used to realign the predicted solution towards the observation values. Available observed meteorological data from the nearby BoM station located at Griffith Airport were incorporated into the TAPM setup. Table 9 details the parameters used in the TAPM meteorological modelling for this assessment.

Table 9 Meteorological Parameters used for the AQIA - TAPM

TAPM (v 4.0.4)

Number of grids (spacing) 4 (30 km, 10 km, 3 km and 1 km)

Number of grid points 30 x 30 x 35

Year of analysis 1 January 2012 to 31 December 2012

Centre of analysis 380,690 m E 6,238,940 m S

Data assimilation Griffith Airport BOM Station (#75041)

5.3.3 CALMET

In the simplest terms, CALMET is a meteorological model that develops hourly wind and other meteorological fields on a three-dimensional gridded modelling domain that are required as inputs to the CALPUFF dispersion model. Associated two dimensional fields such as mixing height, surface characteristics and dispersion properties are also included in the file produced by CALMET. The interpolated wind field is then modified within the model to account for the influences of topography, sea breeze, as well as differential heating and surface roughness associated with different land uses across the modelling domain. These modifications are applied to the winds at each grid point to develop a final wind field. The final hourly varying wind field thus reflects the influences of local topography and land uses.



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CALMET modelling was conducted using the nested CALMET approach, where the final results from a coarse-grid run were used as the initial guess of a fine-grid run. This has the advantage that off-domain terrain features including slope flows, blocking effect can be allowed to take effect and the larger –scale wind flow provides a better start in the fine-grid run.

The outer domain (70 km × 70 km) was modelled with a resolution of 1.4 km. TAPM-generated three dimensional meteorological data was used as the initial guess wind field and the local topography and available surface weather observations in the area were used to refine the wind field predetermined by TAPM data. Hourly surface meteorological data from the BoM station located at Griffith Airport were incorporated in the outer domain modelling.

The output from the outer domain CALMET modelling was then used as the initial guess field for the mid domain CALMET modelling. The mid domain encompassed an area of 30 km × 24 km and a horizontal grid spacing of 0.6 km was used to adequately represent the important local terrain features and land use. The local topography and land use information was used in this run to refine the wind field parameters predetermined by the coarse CALMET run.

The output from the mid domain CALMET modelling was then used as the initial guess field for the inner domain CALMET modelling. The inner domain encompassed an area of 25 km × 20 km and used a horizontal grid spacing of 0.2 km.

As mentioned in Section 2.7, the topographical data was sourced from the United States Geological Service’s Shuttle Radar Topography Mission database that has recorded topography across Australia with a 3 arc second (approximately 90 m) spacing. The land use data file was created using the latest publically available aerial imagery.

Table 10 details the parameters used in the meteorological modelling.

Table 10 Meteorological Parameters used for this Study – CALMET (v 6.42)

Outer Domain

Meteorological grid 70 km × 70 km

Meteorological grid resolution 1.4 km

Surface station data Griffith Airport BoM Station

Initial guess filed 3D output from TAPM modelling

Mid Domain



Initial guess field 3D output from ‘Outer’ domain model run

Inner Domain



Initial guess field 3D output from ‘Mid’ domain model run

5.3.4 Meteorological Data Used in Modelling

Wind Speed and Direction

A summary of the annual wind behaviour predicted by CALMET at the Development Site is presented as wind roses in Figure 9.



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Figure 9 indicates that winds experienced at the Development Site are predominantly light to moderate (between 1.5 m/s and 8 m/s). Calm wind conditions (wind speed less than 0.5 m/s) were predicted to occur approximately 1.0% of the time throughout the modelling period.

The seasonal wind roses indicate that typically:

In summer, winds are moderate to high and are experienced almost evenly from all quadrants with the exception of the north-western quadrant from which a low percentage of winds are experienced. Calm winds were experienced approximately 0.4% of the time during summer.

In autumn, winds are moderate to high and are experienced almost evenly from all quadrants, with a slightly higher percentage of winds from the north-eastern and south-eastern quadrant and a lower percentage of winds from the north-western quadrant. Calm winds were experienced approximately 1.0% of the time during autumn.

In winter, winds are moderate to strong and are experienced predominantly from the north-western quadrant, with very few winds from the southeastern quadrants. Calm winds were experienced approximately 0.7% of the time during winter.

In spring, winds are moderate to strong predominantly from the north-eastern and south-western quadrants with very few winds from the east and west-northwest. Calm winds were experienced approximately 1.3% of the time during spring.



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Figure 9 Predicted Seasonal Wind Roses for the Development Site (CALMET predictions, 2012)



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Atmospheric Stability

Atmospheric stability refers to the tendency of the atmosphere to resist or enhance vertical motion. The Pasquill-Turner assignment scheme identifies six Stability Classes, A to F, to categorize the degree of atmospheric stability as follows:

A = Extremely unstable conditions

B = Moderately unstable conditions

C = Slightly unstable conditions

D = Neutral conditions

E = Slightly stable conditions

F = Moderately stable conditions

The meteorological conditions defining each Pasquill stability class are shown inTable 11.

Table 11 Meteorological Conditions Defining Pasquill Stability Classes

Surface wind speed (m/s)

Daytime insolation Night-time conditions

Strong Moderate Slight Thin overcast or > 4/8 low cloud

<= 4/8 cloudiness

< 2 A A - B B E F

2 - 3 A - B B C E F

3 - 5 B B - C C D E

5 - 6 C C - D D D D

> 6 C D D D D

Notes:

Strong insolation corresponds to sunny midday in midsummer in England; slight insolation to similar conditions in midwinter.

Night refers to the period from 1 hour before sunset to 1 hour after sunrise.

The neutral category D should also be used, regardless of wind speed, for overcast conditions during day or night and for any sky conditions during the hour preceding or following night as defined above.

Source: Pasquill, 1961

The frequency of each stability class predicted by CALMET, extracted at the Development Site during the modelling period is presented in Figure 10. The results indicate a high frequency of conditions typical to Stability Class F. Stability Class F is indicative of very stable conditions, conducive to a low level of pollutant dispersion due to mechanical mixing, resulting in higher predicted odour concentrations.



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Figure 10 Predicted Stability Class Frequencies at the Development Site (CALMET predictions, 2012)

Mixing Heights

Diurnal variations in maximum and average mixing depths predicted by CALMET at the Development Site during the 2012 modelling period are illustrated in Figure 11.

As would be expected, an increase in mixing depth during the morning is apparent, arising due to the onset of vertical mixing following sunrise. Maximum mixing heights occur in the mid to late afternoon, due to the dissipation of ground based temperature inversions and growth of the convective mixing layer.



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Figure 11 Predicted Mixing Heights at the Development Site (CALMET predictions, 2012)

Temperature

The modelled temperature variations as predicted at the Development Site during the year 2012 are illustrated in Figure 12. The maximum temperature (41.9°C) was predicted on 12 November 2012 and the minimum temperature (0.9°C) was predicted on 12 September 2012.



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Figure 12 Predicted Temperatures at Development Site (CALMET predictions, 2012)

5.4 Odour Peak-to-Mean Ratios

The Approved Methods (DEC 2005) states that peak-to-mean ratios should be incorporated when conducting atmospheric dispersion modelling of odour.

It is commonly recognised that dispersion models such as CALPUFF need to be supplemented to accurately simulate atmospheric dispersion of odours. This is because the instantaneous perception of odours by the human nose typically occurs over a time scale of approximately one second but dispersion model predictions are typically valid for time scales equivalent to ten minutes to one hour averaging periods. To estimate the effects of plume meandering and concentration fluctuations perceived by the human nose, it is possible to multiply dispersion model predictions by a correction factor called a “peak-to-mean ratio”. The peak-to-mean ratio (P/M60) is defined as the ratio of peak 1-second average concentrations to mean 1-hour average concentrations.

To estimate peak concentrations, this assessment has used data presented in Table 6.1 of the Odour Framework. Specifically, to establish a conservatively high estimate of peak odour concentrations, the following peak-to-mean ratio (P/M60) has been adopted, corresponding to near-field receptors:

A peak-to-mean ratio (P/M60) of 2.3 has been applied to the emission rate for all sources which is consistent with wake-affected point sources and volume sources for all stability classes.

5.5 Emission Sources

5.5.1 Odour

The estimated hourly-varying odour emission rates for each vent type on the sheds, calculated using the methodology presented in Section 4, were input into the CALPUFF dispersion model via hourly-varying emission files. The Plume Rise Model Enhancements (PRIME) building downwash algorithm was also used to incorporate building wake effects from proposed structures/sheds on the site in the dispersion model (see Section 5.6).



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The parameters for each vent type were provided by the Proponent based on engineering design data and are presented in Table 12.

Table 12 Parameters for each Vent type for each Poultry Shed

Parameter Height (m)

Diameter (m)

Vertical Exit Velocity (m/s)

Exit Temperature (°C)

Vertically emitting fan boxes 6.0 2.2 3.0 Daily varying1

Endwall fan 6.0 3.3 3.0 Daily varying1

Sidewall fan 6.0 3.7 0.12

Daily varying1

Tunnel fan 6.0 8.7 3.0 Daily varying1

Note: 1

Assumed to be equal to target shed temperature relevant to bird age (ranging from 21-32°C) as per Section 4.1.2.

Note: 2

Sidewall fans will ventilate in horizontal direction, therefore assumed a minimum vertical velocity of 0.1 m/s

5.5.2 Particulates

The majority of the PM10 emission rates measured from poultry sheds ranged from 5 mg/s to 50 mg/s per shed (APCRC 2011). In order to provide a conservative and worst case screening-level assessment of particulate emissions from the Development Site, the CALPUFF model was configured with a single stack source located at the centre of the farm, emitting at a height of 6 m above ground level (same as odour release) with an exit velocity of 3 m/s and an emission rate of 0.8 g/s (based on 16 sheds emitting 50 mg/s PM10 each).

5.6 Building Wake Effects

The BPIP (Building Profile Input Program) PRIME algorithm was used to compile building height and width data so that building wake effects could be accounted for in the dispersion model. Building wake effects were only included in the dispersion model for the vertical exhausts.

5.7 Regional Odour Sources

As noted in Section 2.4, the surrounding area is primarily characterised by traditional agricultural production. Other odour generating industries identified in the area are:

Privately owned silo on Tysons Road. It is noted that the odour from a silo is likely to be significantly different from the odour generated from a poultry farm, hence it is not considered any further in this assessment.

GrainCorp’s Tabbita Silo, which is currently closed, hence not considered any further in this assessment.

JBS Australia’s Tabbita Feedlot (cattle feedlot), located approximately 13 km west of the Project Site. Based on the large separation distance from the Development Site, it is not considered any further in this assessment.

Maylands Farm A and Farm B – approved poultry production complexes approximately 20 km to the northwest of the Development Site. Based on the large separation distance from the Development Site, these developments have not been considered any further in this assessment.

Tabbita Farm 1, Farm 2 and Farm 3 – poultry production complexes approximately 9 km to the west of the Development Site.

Tabbita Farm 4 – proposed poultry production complex approximately 9 km to the west of the Development Site.

The Ranch Poultry Production Complex comprising approved operation of The Ranch Farm 1 (8 sheds), The Ranch Farm 2 (8 sheds), The Ranch Farm 4 (16 sheds) and Farm 5 (16 sheds).



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Jeanella Poultry Production Complex (ProTen) - located approximately 23 km to north-west of the Development Site on the northern side of the Mid Western Highway. Based on the large separation distance from the Development Site, these developments have not been considered any further in this assessment;

Jeanella South Poultry Production Complex (ProTen) –located approximately 23 kilometres north-west of Expansion. Based on the large separation distance from the Development Site, these developments have not been considered any further in this assessment;

Goolgowi Poultry Farms (Muscat Developments) - located approximately 47 kilometres north-west of Expansion. Based on the large separation distance from the Development Site, these developments have not been considered any further in this assessment;

With regards to The Ranch Farm 1 and Farm 2 Proposed Expansions, VOAG is yet to finalise the proposed layout (including number of additional sheds) for these expanded developments. As a result, the cumulative odour modelling undertaken as part of this AQIA has not included these expansion proposals. Once the proposed layouts are finalised, the cumulative odour associated with the proposed expansion of The Ranch Farm 1, The Ranch Farm 2 and other surrounding poultry developments, will be assessed within the relevant EIS for The Ranch Farm 1 and The Ranch Farm 2 expansions.

The odour emissions from the three identified regional odour sources listed above were estimated using the same methodology as described in Section 4.1.1. A summary of the key parameters used in the emissions estimation is shown in Table 13.

Table 13 Summary of the Parameters used in Modelling of Background Odour Sources

Site Number of Farms

Number of Sheds

Number of Birds/shed

Shed Dimensions

Development Application

1

Tabbita Farm 1 1 20 51,000 161 m x 17.7 m DA 2015/040



Proposed Tabbita Farm 4 1 18 51,000 161 m x 17.7 m Not yet lodged

The Ranch Farm 1 1 8 50,000 176 m x 18 m DA 2016/017




Source: 1

http://www.carrathool.nsw.gov.au

The dispersion modelling performed to account for the cumulative impacts for these developments used the same meteorological set and methodology adopted for The Ranch Farm 3 as outlined in the previous sections.

5.8 Scenarios Assessed

To assess the impacts from the Development Site and the regional odour sources, two scenarios have been modelled:

Scenario 1 – The Ranch Farm 3 (approved + proposed expansion) only; and

Scenario 2 – The Ranch Farm 3 (approved + proposed expansion) plus other regional odour sources (see Table 13).



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6 RESULTS AND DISCUSSSION

6.1 Odour Impact Assessment

6.1.1 Scenario 1 – Incremental Impact of Farm 3

The 99th percentile nose-response odour concentrations predicted at the surrounding sensitive

receptors for Scenario 1 are presented in Table 14.

The dispersion modelling performed for this assessment was performed using the ‘standard’ hourly time step (assuming continuous emission release throughout the hour) and hourly average meteorological data. The predicted hourly odour concentrations were then converted to nose response level (approximately 1-second peak concentration) using the appropriate peak to mean ratio as outlined in Section 5.4.

Based on the above, the predicted nose response odour concentrations presented in this report are concluded to represent the conservative worst case impacts at surrounding sensitive receptors. Therefore, the actual odour concentrations at surrounding receptors due to operations at the Ranch Farm 3 are expected to be lower than the predicted odour concentrations presented in Table 14.

Table 14 Predicted 99th

Percentile Nose-Response Odour Concentrations (OU) – Scenario 1

Receptor ID

Incremental Odour Concentration (OU)

Approved Operation (8 sheds)

Proposed Operation (Approved + Expansion)

(16 sheds)

R1 0.3 0.5

R2 0.3 0.3

R3 0.1 0.1

R4 0.5 0.5

R5 0.5 0.6

R6 0.7 0.9

R7 0.7 1.0

R8 0.8 1.0

R9 0.9 1.0

R10 0.9 1.0

R11 0.5 1.1

R12 0.6 0.7

R13 0.7 1.1

Criterion 5

The results presented in Table 14 show that the incremental 99th percentile nose-response odour

concentrations predicted as a result of the expanded operations at The Ranch Farm 3 are well below the adopted criteria at all receptors assessed. It should be noted that the predicted results are based on a number of conservative assumptions, which include zero mortality rate within the sheds and continuous release of emissions throughout any hour of the year.



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The predicted 99th percentile odour concentrations (for nose-response time, 1-second average) are

presented as a contour plot in Figure 13. It is noted that the odour contour plot does not reflect odour concentrations occurring at any particular instant in time, but rather illustrates a compilation of the predicted 99

th percentile (88

th highest) odour concentration at all locations downwind, taking into

account all combinations of meteorological conditions modelled across the entire year.

Figure 13 Predicted 99th

Percentile Nose-Response Odour Concentration (OU) –Scenario 1



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6.1.2 Scenario 2 – Cumulative Impacts

The 99th percentile nose-response odour concentrations predicted at the surrounding sensitive

receptors for Scenario 2 are presented in Table 15. The predicted 99th percentile odour

concentrations (for nose-response time, 1-second average) are presented as a contour plot in Figure 14. The concentrations presented in Table 15 and Figure 14 represents the cumulative odour impacts from The Ranch Poultry Production Complex (all five farms) and four farms located at Tabbita Lane (Tabbita Lane Farms 1 to 4).

Table 15 Predicted 99th

Percentile Nose-Response Odour Concentrations (OU) – Scenario 2

Receptor ID

Cumulative Odour Concentration (OU)

R1 3.0

R2 2.6

R3 1.3

R4 2.4

R5 2.9

R6 3.7

R7 3.8

R8 3.8

R9 3.9

R10 3.7

R11 4.6

R12 4.0

R13 3.8

Criterion 5

The results presented in Table 15 show that the predicted cumulative 99th percentile nose-response

odour concentrations are below the adopted criteria at all receptors assessed. The highest impacts are predicted to occur at receptor R11 (located on Kidman Way, Tabbita) which is predicted to be exposed to a 99

th percentile concentration of 4.6 OU (nose-response time).

As noted above, the predicted results are based on a number of conservative assumptions, which include zero mortality rate within the sheds and continuous release of emissions throughout any hour of the year. Given this, the predicted nose response odour concentrations presented in this report are concluded to represent the conservative worst case impacts at surrounding sensitive receptors. Therefore, the actual 99

th percentile odour concentrations at surrounding receptors are expected to be

lower than the predicted odour concentrations presented in Table 15.



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Figure 14 Predicted 99th

Percentile Nose-Response Odour Concentration (OU) – Scenario 2



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6.2 Sensitivity Analysis – Bird Placement Date

Predicted odour modelling results presented in Section 6.1 are based on assuming the placement of birds will start on day 1 of the year. Changes in the bird placement date may result in increase/decrease of the predicted odour concentrations at surrounding sensitive receptors due to the occurrence of peak odour emissions from the poultry operation in different meteorological conditions. To address this and to predict the potential worst case impact, cumulative odour impacts at the surrounding sensitive receptors have also been assessed for the following two scenarios.

Scenario 2A – Bird placement starts on Day 14 of the year; and

Scenario 2B – Bird placement starts on Day 28 of the year

A comparison of the predicted odour concentrations at surrounding sensitive receptors for Scenario 2, Scenario 2A and Scenario 2B is presented in Table 16. The results presented in Table 16 show that the proposed expansion of The Ranch Farm 3 complies with the odour criterion of 5 OU at all surrounding sensitive receptors for each modelled scenario.

Table 16 Sensitivity Analysis – Bird Placement Date

Receptor ID

Cumulative Odour Concentration (OU)

Scenario 2 Scenario 2A Scenario 2B

R1 3.0 2.4 2.4

R2 2.6 2.3 2.2

R3 1.3 1.4 1.6

R4 2.4 2.5 2.6

R5 2.9 2.7 2.7

R6 3.7 3.3 3.3

R7 3.8 3.3 3.4

R8 3.8 3.5 3.4

R9 3.9 3.7 3.4

R10 3.7 4.0 3.4

R11 4.6 4.6 4.0

R12 4.0 4.5 3.3

R13 3.8 3.9 3.3

Criterion 5.0 5.0 5.0

6.3 Sensitivity Analysis – Other Operational Parameters

Other operational parameters that can influence the model predictions include the lengths of clean out and grown out periods and duration of bird placement (number of birds per day). Sensitivity of these operational parameters on the model predictions was investigated in The Ranch Farm 4 and The Ranch Farm 5 EIS, following the NSW EPA’s comments on the odour impact assessment reports of these developments (SLR 2016). The investigation found that the changes in predicted odour impacts associated with changes in these operational parameters are minimal and below the odour detection threshold. Following these results and in consultation with NSW EPA, sensitivity of these parameters on the predicted odour impacts outlined in Section 6.1 has not been investigated in this study.



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6.4 Dust Impact Assessment

Modelling of potential particulate emissions from The Ranch Poultry Production Complex (The Ranch Farms 1 to 5) was conducted using the same methodology used in The Ranch Farm 4 and The Ranch Farm 5 EISs (SLR 2016). This involved modelling an emission rate of 0.8 g/s for The Ranch Farm 3, The Ranch Farm 4 and The Ranch Farm 5, and 0.4 g/s for The Ranch Farm 1 and The Ranch Farm 2. The results of this modelling are presented in Table 17.

As shown in Table 17, the highest incremental 24-hour average PM10 concentration predicted at any of the sensitive receptor locations is 1.6 µg/m³. Given that the emission rate used in the modelling is highly conservative, these results indicate that any exceedances of the 24-hour average criterion of 50 µg/m³ are highly unlikely.

Table 17 Predicted PM10 Concentrations

Receptor ID Predicted Incremental PM10 Concentrations (µg/m3)

Annual Average Maximum 24-Hour Average

R1 0.08 1.6

R2 0.07 1.3

R3 0.04 0.8

R4 0.10 1.5

R5 0.11 1.1

R6 0.16 1.3

R7 0.17 1.4

R8 0.18 1.3

R9 0.18 1.2

R10 0.17 1.2

R11 0.11 1.1

R12 0.06 1.5

R13 0.14 1.1

Criterion 30 50



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7 MITIGATION AND MONITORING MEASURES

The following design features, best management practices and mitigation measures will be employed at The Ranch Farm 3 to minimise the potential for dust and odour emissions:

The poultry sheds will be fully enclosed, have adequate roof overhang (wide eaves) and be surrounded by concrete bund walls to prevent rainwater entering the sheds and to allow for the controlled discharge of wash down water from the sheds. These measures will assist in reducing the level of moisture within the poultry sheds.

The feed silos will be fully enclosed to both prevent the entry of rainwater and minimise emissions of dust/particulate matter when loading and unloading.

The poultry sheds will be tunnel-ventilated, which will allow control over the moisture levels and promote optimum growing conditions and bird health. The increased airflow and improved feed conversion in tunnel-vented sheds helps to maintain bedding material within the optimal moisture range.

All sheds will be fitted with nipple drinkers with drip cups, as opposed to traditional cup drinkers, to minimise water spillage and reduce the risk of increased shed moisture.

Regular monitoring and maintenance of the tunnel ventilation systems and bird drinkers will be undertaken to avoid spillage, leaks and uneven distribution.

Stocking densities and bird health within each of the poultry sheds will be regularly checked and, if necessary, appropriate corrective measures will be implemented.

Daily monitoring and maintenance of the bedding material will occur to identify, remove and replace any caked material beneath drinking lines and/or areas with excessive moisture content.

Poultry litter (spent bedding material) will be promptly removed from the sheds and generally transported off-site in covered trucks at the end of each production cycle during the clean-out phase. Wherever possible the handling of the material will be avoided during adverse climatic conditions, such as strong winds. The shed ventilation systems will not be used during the removal of bedding material.

Dead birds will be collected from the sheds on a daily basis and stored in on-site chillers prior to removal from site.

The insides of the poultry sheds and the surrounds will be maintained at all times to ensure a clean and sanitary environment.

During sanitisation, the amount of air released from the sheds while any sanitising scent is present will be minimised and, if possible, a low scent sanitiser will be utilised.

Internal access roads will be appropriately maintained to minimise dust emissions and speed restrictions (<40 km/h) will be implemented on any unsealed internal roads.



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8 CONCLUSIONS

SLR was commissioned by Scolexia on behalf of VOAG 3, to undertake an AQIA for the proposed expansion of The Ranch Farm 3.

The aim of this assessment was to quantify the change in potential dust and odour impacts in the region due to the operation of The Ranch Farm 3 in isolation and cumulatively with other surrounding developments, including approved farms of the Ranch Poultry Production Complex. Potential odour emissions from the proposed expansion were estimated based on site specific design parameters and publicly available research studies on the odour emissions generation from poultry farms. Potential hourly varying odour emission rates were estimated based on a number of factors in a bird growth cycle, such as:

the number of birds, which varies later in the batch as harvesting takes place;

the stocking density of birds, which is a function of bird numbers, bird age and shed size;

ventilation rate, which depends on bird age and ambient temperature; and

design and management practices, particularly those aimed at controlling litter moisture.

The CALPUFF dispersion model was used to predict the potential odour levels at surrounding sensitive receptors based on an hourly, 1-year site-representative meteorological file compiled using observational data from Griffith Airport BoM Station during 2012. A peak-to-mean ratio of 2.3 was used to convert the predicted hourly odour concentrations to nose-response (1-second average) odour levels.

The modelling results showed that emissions from The Ranch Farm 3 (increment from approved and proposed expansion) and combined (cumulative) with other approved/proposed poultry farms in the surrounding area are predicted to comply with the adopted odour criteria at all identified surrounding sensitive receptors. Based on the modelling results it has been concluded that the proposed expansion of the poultry farm operation is unlikely to cause any significant odour nuisance at the nearby surrounding sensitive receptor locations.

The particulate emissions modelling results showed that the highest incremental 24-hour average PM10 concentration predicted at any of the sensitive receptor locations is 1.6 µg/m³. Given that the emission rate used in the modelling is highly conservative, these results indicate that any exceedances of the 24-hour average criterion of 50 µg/m³ are highly unlikely.



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9 REFERENCES

APCRC 2011, Dust and Odour Emissions from Meat Chicken Sheds, Australian Poultry CRC, Project No – 04-45

DEC 2006a, Technical Framework - Assessment and Management of Odour from Stationary Sources in New South Wales, NSW Department of Environment and Conservation, November 2006.

DEC 2006b, Technical Notes - Assessment and Management of Odour from Stationary Sources in New South Wales, NSW Department of Environment and Conservation, November 2006.

EPA 2017, Approved Methods for the Modelling and Assessment of Air Pollutants in New South Wales, NSW Department of Environment and Conservation, 26 August 2005

Ormerod R and Holmes G 2005, Description of PAE Meat Chicken Farm Odour Emissions Model, Brisbane: Pacific Air and Environment.

Oke 2004, Boundary Layer Climates, Second Edition, Routledge, London and New York, 435 pp.

Pasquill, 1961 The estimation of the dispersion of windborne material, The Meteorological Magazine, Vol 90, No. 1063, pp 33-49.

PEL 2015, Air Quality Impact Assessment – Jeanella South Poultry Complex. 6 August 2015

RIRDC 2014, Monitoring Mechanical Ventilation Rates in Poultry Buildings. January 2014, RIRDC Publication No. 13/024

SLR 2016, Response to Submissions for The Ranch Farm 4 and 5, SLR Report Number 630.11662

Appendix A

Report Number 630.11566-R4

Page 1 of 4

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Selection of Representative Meteorological Data

In dispersion modelling, one of the key considerations is the representative nature of the meteorological data used. Once emitted to atmosphere, emissions will:

rise according to the momentum and buoyancy of the emission at the discharge point relative to the prevailing atmospheric conditions;

be advected from the source according to the strength and direction of the wind at the height which the plume has risen in the atmosphere;

be diluted due to mixing with the ambient air, according to the intensity of turbulence; and

possibly be chemically transformed and/or depleted by deposition processes.

Dispersion is the combined effect of these processes.

Dispersion modelling is used as a tool to simulate the air quality effects of specific emission sources, given the meteorology typical for a local area together with the expected emissions. Selection of a year when the meteorological data is atypical means that the resultant predictions may not appropriately represent the corresponding air quality impacts.

The year of meteorological data used for the dispersion modelling was selected by reviewing the most recent five years of historical surface observations at Griffith Airport AWS [station number 075041] (2010 to 2014 inclusive) to determine the most representative year of long-term conditions. Wind speed, ambient temperature and relative humidity were compared to long term averages for the region to determine the most representative year.

Data collected from 2010 to 2014 is summarised in Figure A1 to Figure A6. Examination of the data indicates the following:

Figure A1 and Figure A2 indicate that 2012 exhibit wind speeds that are closest to the long term average.

Figure A3 and Figure A4 show that temperatures in 2012 and 2013 more appropriately reflect the long term average. Temperatures in 2012 are slightly lower than the long term average at 9 am in autumn/winter however 2013 temperatures are slightly higher than the long term average at 3 pm in autumn/winter.

Figure A5 and Figure A6 indicate that relative humidity in 2012 appropriately reflect the long term average.

Years 2012 and 2013 indicate average wind speeds that are slightly lower than the long term average, especially at 3 pm. Using these years as the representative year would be a conservative approach because low wind speeds are associated with less effective plume dispersion. No other parameters significantly deter the use of any one of these years of data. Consequently, 2012 was selected as a representative year of meteorology.

Appendix A


Page 2 of 4

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Figure A1 Wind Speed at 9 am at Griffith Airport AWS for 2010 – 2014

Figure A2 Wind Speed at 3 pm at Griffith Airport AWS for 2010 – 2014

Appendix A


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Figure A3 Temperature at 9 am at Griffith Airport AWS for 2010 – 2014

Figure A4 Temperature at 3 pm at Griffith Airport AWS for 2010 – 2014

Appendix A


Page 4 of 4

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Figure A5 Relative Humidity at 9 am Griffith Airport AWS for 2010 – 2014

Figure A6 Relative Humidity at 3 pm Griffith Airport AWS for 2010 – 2014

the ranch poultry production complex...the ranch poultry production complex farm 3 - proposed...

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