Odour Impact Assessment (Level 3) · 05/09/2018 · inversions or katabatic drift) (Section 4.3)....

Odour Impact Assessment (Level 3)

Lowes Creek Maryland Precinct

Report Number 610.16684-R03

5 September 2018

NSW Department of Planning and Environment

GPO Box 39

Sydney NSW 2001

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NSW Department of Planning and Environment Odour Impact Assessment (Level 3) Lowes Creek Maryland Precinct

Report Number 610.16684-R03 5 September 2018

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SLR Consulting Australia Pty Ltd

Odour Impact Assessment (Level 3)

Lowes Creek Maryland Precinct

PREPARED BY:

SLR Consulting Australia Pty Ltd ABN 29 001 584 612

2 Lincoln Street

Lane Cove NSW 2066 Australia

(PO Box 176 Lane Cove NSW 1595 Australia)

+61 2 9427 8100 +61 2 9427 8200

[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 NSW Department of Planning and Environment.

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 Date Prepared Checked Authorised

610.16684-R03--v1.2 5 September 2018 Varun Marwaha Kirsten Lawrence Kirsten Lawrence

610.16684-R03-v1.1 30 November 2017 Varun Marwaha Kirsten Lawrence Kirsten Lawrence

610.16684-R03-v1.0 21 March 2017 Varun Marwaha Kirsten Lawrence FINAL



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Table of Contents


1 INTRODUCTION 5

2 PROJECT OVERVIEW 6

2.1 Study Area 6

2.2 Surrounding Topography 7

2.3 Potential Odour Sources 8

2.3.1 Broiler Farm - 18 Coates Park Road, Cobbitty 9

2.3.2 W2R Compost Farm 9

2.4 Hours of Operation 10

3 ODOUR ASSESSMENT CRITERIA 11

4 AIR DISPERSION MODELLING METHODOLOGY 13

4.1 Model Selection 13

4.2 Accuracy of Modelling 13

4.3 Meteorological Modelling 14

4.3.1 TAPM 15

4.3.2 CALMET 15

4.3.3 Meteorological Data Used in Modelling 16

4.3.4 Odour Peak-to-Mean Ratios 20

5 EMISSION ESTIMATION 21

5.1 Definitions 21

5.2 Emission Estimation Methodology 21

5.2.1 Broiler Farm - 18 Coates Park Road, Cobbitty 21

5.2.2 W2R Compost Farm 25

6 RESULTS AND DISCUSSION 27

7 CONCLUSIONS 32

8 REFERENCES 33



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Table of Contents


TABLES

Table 1 NSW EPA Impact Assessment Criteria for Complex Mixtures of Odorous Air Pollutants (nose-response-time average, 99

th percentile) 12

Table 2 Meteorological Parameters used for this Study (TAPM v 4.0.4) 15 Table 3 Meteorological Parameters used in this Assessment (CALMET v 6.42) 16 Table 4 Meteorological Conditions Defining Pasquill Stability Classes 19 Table 5 Parameters used in Estimating Odour Emissions from the Broiler Farm 22 Table 6 Shed Ventilation as a Percentage of Maximum Ventilation 23 Table 7 Source Parameters Used for the Broiler Farm 24 Table 8 Odour Emission Rates Identified from the Literature Review 26 Table 9 Odour Emission Rates Adopted for W2R Compost Farm 26

FIGURES

Figure 1 Locality of the Precinct 6 Figure 2 Local Topography 7 Figure 3 Location of the Broiler Farm and W2R Compost Farm 8 Figure 4 W2R Composting Farm located towards the Southwest Precinct Boundary 10 Figure 5 Annual and Seasonal Wind Roses for the Precinct (CALMET predictions, 2014) 17 Figure 6 Annual Wind Speed Frequencies at the Precinct (CALMET predictions, 2014) 18 Figure 7 Predicted Stability Class Frequencies at the Precinct (CALMET predictions, 2014) 19 Figure 8 Predicted Mixing Heights at the Precinct (CALMET predictions, 2014) 20 Figure 9 Bird Density and Varying Ventilation Rate Profile for the Precinct (example shed) 22 Figure 10 Modelled Shed Odour Emission Rates for the Broiler Farm (example shed) 24 Figure 11 Modelled Shed Odour Emission Rates throughout the Year (example shed) 25 Figure 12 Predicted Cumulative Ground Level 99

th Percentile Odour Concentrations 27

Figure 13 Predicted Incremental Ground Level 99th Percentile Odour Concentrations – Broiler

Farm 28 Figure 14 Predicted Incremental Ground Level 99

th Percentile Odour Concentrations – W2R

Compost Farm 29 Figure 15 Predicted Incremental Ground Level 99

th Percentile Odour Concentrations – W2R

Compost Farm 31

PHOTOS

Photo 1 Broiler Farm Sheds located at 18 Coates Park Road, Cobbitty 9



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1 INTRODUCTION

SLR Consulting Australia Pty Ltd (SLR) has been commissioned by the NSW Department of Planning and Environment (DPE) to conduct a Level 3 Odour Impact Assessment (OIA) for the Lowes Creek Maryland Precinct (the Precinct) located in the South West Growth Area.

The Precinct is located in the Camden Local Government Area, in the South West Growth Area. The precinct is approximately 517 hectares in size and currently consists of rural areas and the historic Maryland homestead.

In October 2016, a Level 1 OIA was completed by SLR (SLR 2016) and submitted to the Camden Council (the Council) as part of the Land Capability Assessment of the site to inform the Draft Indicative Layout Plan (ILP) for the Precinct. After review of the assessment, the Council requested that a Level 3 OIA be completed to further inform whether odour emissions from poultry sheds located at 18 Cobbitty Road and a Waste-to-Resource (W2R) composting farm located to the southwest of the Precinct have potential to affect amenity levels at the Precinct.

This study has been carried out in accordance with New South Wales (NSW) Office of Environment and Heritage (OEH) odour policy: Technical Framework: Assessment and Management of Odour from Stationary Sources in NSW (the Odour Framework) (DEC 2006a) and supporting documentation: Technical Notes: “Assessment and Management of Odour from Stationary Sources in NSW (the Technical Notes) (DEC 2006b).

The Odour Framework outlines the parameters that need to be determined in an odour impact assessment as follows:

All nearby receptors potentially affected by the odour emissions (both current and future); this isparticularly important where there is a potential for rezoning or subdivision (Section 2.1).

Site features that may affect odour propagation and dispersion, including topography, vegetation,buildings and surrounding land uses (Section 2.2).

All potential odour sources - materials, equipment or activities (including transport, wastemanagement and maintenance) (Section 2.3).

Operating hours and times when intermittent odour-generating activities are likely to occur(Section 2.4).

The odour assessment criteria that were used to assess the proposal under current and futurecircumstances (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 ofinversions or katabatic drift) (Section 4.3).

The location of the emission of each odour source as well as its characteristics and likelyemission frequency, timing, duration, intensity, characteristics and chemical composition(Section 5.2).

Likely odour impacts (predicted using the level 3 assessment approach) (Section 6).



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2 PROJECT OVERVIEW

2.1 Study Area

The Precinct is located on the Northern Road, approximately 9 kilometres (km) northwest of the Narellan Town Centre and approximately 60 km southwest of Sydney Central Business District (CBD). The surrounding land use is primarily rural and comprises rural residential holdings and agricultural activities.

As part of NSW Government’s strategy for the South West Growth Area, the Precinct site is to be rezoned for urban purposes, as has the neighbouring Oran Park, Turner Road, East Leppington, Austral, Leppington North, Edmondson Park and Catherine Fields precincts. The development will be staged over approximately 15 - 20 years commencing at the eastern boundary by Northern Road and extending westerly during that period.

The Precinct is anticipated to deliver approximately 7,000 dwellings. Figure 1 illustrates the local setting of the site.

Figure 1 Locality of the Precinct



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2.2 Surrounding Topography

The Precinct is located in relatively flat plains in the southwest region of the Sydney Metropolitan area. The Blue Mountains National Park (South) is located towards the west and Royal National Park is located to the southeast of the Precinct boundary. The regional topography is shown in Figure 2.

The topography of the area within the Precinct boundary is characterised by gently undulating terrain, with an approximate range of 70 to 130 AHD (Australian Height Datum).

Figure 2 Local Topography



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2.3 Potential Odour Sources

As mentioned in Section 1, the Council has requested that the Level 3 odour impact assessment assesses the following two odour sources in the region:

Broiler farm located at 18 Coates Park Road, Cobbitty (hereafter ‘the broiler farm’); and

W2R composting farm located towards the southwest boundary of the Precinct (hereafter ‘the W2R compost farm’).

The locations of both these odour sources with respect to the Precinct boundary are shown in Figure 3.

Figure 3 Location of the Broiler Farm and W2R Compost Farm



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2.3.1 Broiler Farm - 18 Coates Park Road, Cobbitty

This broiler farm is located at 18 Coates Park Road, Cobbitty on lot 5 of DP 1012683.

As shown in Photo 1, four sheds are located at the western end of the property, and four sheds are located towards the eastern end, with an access road joining the eight sheds.

Photo 1 Broiler Farm Sheds located at 18 Coates Park Road, Cobbitty

No operational information has been able to be sourced from the operator or Council for these sheds. For the purpose of this assessment, it has been assumed that all eight sheds are operational at all times and that the sheds are being used as broiler farms.

2.3.2 W2R Compost Farm

The W2R compost farm is located approximately 650 m west of the Precinct boundary. A teleconference was held between SLR and a W2R representative (Mike Ritchie, MRA Consultant) on 13 February 2017. MRA Consultant provided some key information regarding the W2R compost farm operations, as outlined below:

The site receives only Category 2 green waste, as defined under the ‘Environmental Guidelines - Composting and related organics processing facilities’ (DEC 2003).

The site is licensed to receive up to 50,000 tonnes per annum (tpa) of green waste, however currently only receives up to 26,000 tpa.

No leachate is stored on site and proactive leachate management practices are in place.

For future operations, a state of the art technology is proposed to be incorporated within the composting operations to further reduce the odour impacts. At this stage, no further information is available to SLR on the technology proposed.

A site layout of W2R compost farm is shown in Figure 4.



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Figure 4 W2R Composting Farm located towards the Southwest Precinct Boundary

The following activities and areas are identified as likely to generate odour due to green waste composting:

Fresh green waste stockpiles (including mulch and undisturbed);

Maturation of green waste (windrows); and

Storage of final compost product.

It is understood that the adjoining landowner between the W2R compost farm and the Precinct boundary has approached the NSW Department of Planning seeking consideration to the rezoning of its land for urban purposes.

2.4 Hours of Operation

No information is available for the operational hours of the broiler farm or the W2R compost farm. To be conservative, the hours of operation for both sources have been assumed to be 24 hours a day, 7 days a week.

Maturation Windrows

Fresh Green Waste (mulch)

Final Product

Fresh Green Waste

(sorted, undisturbed)



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3 ODOUR ASSESSMENT CRITERIA

Impacts from odorous air contaminants are often nuisance-related rather than health-related. Odour performance goals guide decisions on odour management, but are generally intended to achieve “no offensive odour” rather than “no odour”.

Under the odour measurement methods used in Australia (AS/NZS 4323.3), 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 how many times the original odour must be diluted with odour free air to reach the point of detectability. At the level of detectability, the person experiencing the odour would be able to say that the diluted odour was present without being able to ascribe an odour character to it. This is called the Detection threshold.

For example, if one volume of an odour sample required to be diluted with 499 volumes of odour free air to reach the Detection threshold, the original odour sample would be reported as 500 odour units (ou). At this level of dilution, no character can be ascribed to the diluted odour. In order for the diluted odour to be strong enough to have an odour character, less dilution would be required, and this level of dilution would be called the Recognition threshold. Again for example, a particular odour may have a Detection threshold of 500 ou and have a Recognition threshold of 250 ou (the stronger odour has the lower ou value).

It should be realised that these ou values are measured by trained odour assessors in an odour sterile laboratory. In “real life” conditions, due to the presence of ambient odours and other factors, the Detection threshold of an odour cannot be determined over the ambient background odour level. Only odours at or above the Recognition threshold normally illicit a response by the general population, and their potential reaction to the presence of this odour is assessed in the following terms:

Frequency: how often the odour occurs

Intensity: how strong the odour is perceived to be

Duration: how long the odour is present for

Offensiveness: how offensive the odour is perceived to be

Location or Context: where the person is experiencing the odour

An example for this can be shown in a theoretical case of a bakery. A person walking past the bakery may smell the bakery odours and like these baking odours (it can be shown that people generally react positively to baking odours). However, a person living next to the bakery and who experiences the baking odours throughout their house and garden on a continuous basis may find the baking odours offensive to the point where they complain to local authorities.

Other factors may also come into play when assessing odour impacts, such as:

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.



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Experience gained through odour assessments from proposed and existing facilities in NSW indicates that an odour performance goal of 7 ou detection 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 detection. This is expressed as the 99

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

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, 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 odour performance goals allow for population density, cumulative impacts, and anticipated odour levels during adverse meteorological conditions and community expectations of amenity.

Where a number of the factors above simultaneously contribute to making an odour “offensive”, an odour goal of 2 ou detection at the nearest residence (existing or any likely future residences) is appropriate, which generally occurs for affected populations equal or above 2000 people.

The equation used by the NSW EPA to determine the appropriate impact assessment criteria for complex mixtures of odorous air pollutants, as specified in the Odour Framework, is expressed as follows:

Impact assessment criterion (ou) = (log10(population)-4.5)/-0.6

A summary of the impact assessment criteria given for various population densities, as drawn from the Odour Framework, is given in Table 1.

Table 1 NSW EPA Impact Assessment Criteria for Complex Mixtures of Odorous Air Pollutants (nose-response-time average, 99

th percentile)

Population of Affected Community Impact Assessment Criteria for Complex Mixtures of

Odours (ou)

Urban area (> 2000) 2.0

~300 3.0

~125 4.0

~30 5.0

~10 6.0

Single residence (< 2) 7.0

Source: DEC, 2006

The Odour Framework states 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).

As mentioned in Section 2.1, approximately 7,000 dwellings are likely to be built within the Precinct. A ‘Demographic and Social Infrastructure Assessment’ was completed by Elton Consulting in September 2016 (Elton 2016), in which it was estimated that the average occupancy of the Precinct will be approximately 1.8-3.2 people per household. Based on this, an odour impact assessment criterion of 2 ou (expressed as the 99

th percentile for a nose response average, i.e. 1-second average)

is considered appropriate and has been adopted for this assessment.



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4 AIR DISPERSION MODELLING METHODOLOGY

4.1 Model Selection

Emissions from the identified odour sources have been modelled using the CALPUFF (Version 6) modelling system. CALPUFF is one of the modelling tools accepted by the NSW EPA. CALPUFF is a transport and dispersion model that breaks emission plumes into “puffs” of material emitted from modelled sources. The model predicts the trajectory of these puffs, simulating dispersion and transformation processes along the way.

In order to model the trajectory and dispersion / transformation of these puffs, the model requires input data on the emissions themselves (location, release times / frequencies, type and strength of the releases), the terrain over which the puffs travel and the meteorological conditions that occur at the location and in the time period under consideration. Both the terrain and meteorological data are in incorporated in three dimensions.

For the meteorological data, CALPUFF typically uses the wind field data generated by the 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 AERMOD) 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.

4.2 Accuracy of Modelling

Atmospheric dispersion models 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.



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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.

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 (USEPA 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 study utilises the CALPUFF dispersion model in full 3D mode, incorporating the 3D meteorological output from CALMET and TAPM (refer Section 4.3). The meteorological dataset has been compiled using observations from nearby automatic weather stations and a 5-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.

4.3 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 (that layer of the atmosphere closest to the surface of the Earth. 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 study 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.

Meteorological data collected over the period 2011-2015 at the nearest BOM station (Badgerys Creek AWS) were analysed to select a representative year for dispersion modelling. The analysis showed that data collected during the 2014 calendar year are in reasonably good agreement with long term averages compared to other years and was therefore selected for use in this assessment.



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4.3.1 TAPM

In order to calculate all meteorological parameters required by the dispersion modelling process, meteorological modelling using The Air Pollution Model (TAPM, v 4.0.4) has been performed. TAPM, developed by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) is a prognostic model which may be used to predict three-dimensional meteorological data and air pollution concentrations.

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 site-specific hourly meteorological observations at user-defined levels within the atmosphere.

TAPM may assimilate actual local wind observations so that they can optionally be included in a model solution. In this assessment, TAPM predictions have been nudged with the locally monitored observational data, as shown in Table 2.

Table 2 Meteorological Parameters used for this Study (TAPM v 4.0.4)

Modelling Period 1 January 2014 to 31 December 2014

Centre of analysis 295,310 E 6,239,686 N (UTM Coordinates)

Number of grid points 25 × 25 × 25

Number of grids (spacing) 5 (30 km, 10 km, 3 km, 1 km, 0.3 km)

Data assimilation Badgerys Creek AWS (Station # 67108)

Terrain AUSLIG 9 second DEM

4.3.2 CALMET

In the simplest terms, CALMET is a meteorological model that develops wind and temperature fields on a three-dimensional gridded modelling domain. 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, 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 wind field thus reflects the influences of local topography and land uses.

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 and blocking effects can be allowed to take effect and the larger scale wind flow provides a better start in the fine-grid run.

The outer domain (20 km × 20 km) was modelled with a resolution of 400 m. TAPM-generated 3-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 BoM stations 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 inner domain CALMET modelling. The inner domain encompasses an area of 10 km × 10 km. A horizontal grid spacing of 100 m was used to adequately represent the important local terrain features and land use. The fine scale local topography and land use information were used in this run to refine the wind field parameters predetermined by the coarse CALMET run (outer domain). Table 3 details the parameters used in the CALMET modelling.



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The approach to CALMET modelling taken within this assessment is guided by the NSW OEH document ‘Generic Guidance and Optimum Model Settings for the CALPUFF Modelling System for Inclusion into the Approved Methods for the Modelling and Assessment of Air Pollutants in NSW, Australia’ (TRC 2011). The approach taken in this assessment has been identified in TRC 2011 as the CALMET Hybrid Mode and is considered to be an ‘advanced model simulation’.

Table 3 Meteorological Parameters used in this Assessment (CALMET v 6.42)

Outer Domain

Meteorological grid 20 km × 20 km

Meteorological grid resolution 400 m

Surface station data Badgerys Creek Airport AWS (Station # 67108)

Camden Airport AWS (Station # 68192)

Initial guess filed 3D output from TAPM modelling

Inner Domain

Meteorological grid 6 km × 6 km

Meteorological grid resolution 100 m

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

4.3.3 Meteorological Data Used in Modelling

To provide information on the meteorological conditions predicted at the Precinct, the modelled meteorological data was ‘extracted’ at a location near the centre of the Precinct and is presented in this section.

The meteorological dataset developed for use in this assessment has been compiled to provide a robust and conservative assessment of potential downwind impacts due to odour emissions from activities occurring at the broiler farm and the W2R compost farm.

Wind Speed and Direction

A summary of the annual wind behaviour predicted at the Precinct for the 2014 calendar year is presented as wind roses in Figure 5 and an annual wind speed frequency chart is shown in Figure 6.

The wind roses show the frequency of occurrence of winds by direction and strength. The bars correspond to the 16 compass points (degrees from North). The direction of the bar shows the direction from which the wind is blowing. The length of the bar represents the frequency of occurrence of winds from that direction, and the widths of the bar sections correspond to wind speed categories, the narrowest representing the lightest winds. Thus it is possible to visualise how often winds of a certain direction and strength occur over a long period, either for all hours of the day, or for particular periods during the day. There are times when the wind is calm (defined as being from zero to 0.5 metres/second), and the percentage of the time that winds are calm are shown as a note on the wind rose.

Figure 5 shows wind roses for the full year and for each season, and indicates that wind direction is seasonally dependent. The seasonal wind roses indicate that typically:

In summer, wind speeds are low to moderate and occur predominantly from between the north-northeast and southwest directions, with very few winds from the northwest quadrant. Calm wind conditions are predicted to occur for approximately 8% of the time during summer.

In autumn, wind speeds are low to moderate and occur predominantly from the southwest direction. The calm wind conditions are predicted to occur for approximately 13% of the time during autumn.



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In winter, wind speeds are low to moderate and occur predominantly from the southwest direction, with very few winds from the northeast or southeast quadrants. Calm wind conditions are predicted to occur for approximately 8% of the time during winter.

In spring, wind speeds are low to strong and occur predominantly from the southwest direction. The calm wind conditions are predicted to occur for approximately 9% of the time during spring.

Figure 5 Annual and Seasonal Wind Roses for the Precinct (CALMET predictions, 2014)



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Figure 6 Annual Wind Speed Frequencies at the Precinct (CALMET predictions, 2014)

Atmospheric Stability

Atmospheric stability refers to the tendency of the atmosphere to resist or enhance vertical motion and therefore vertical mixing. 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 in Table 4. The frequency of each stability class predicted by CALMET for 2014, extracted at the Precinct, is presented in Figure 7.

The results indicate a high frequency of conditions typical to Stability Class F. Stability Class F is indicative of stable night time conditions, which will inhibit pollutant dispersion resulting in higher pollutant concentrations at ground level at surrounding areas.



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Table 4 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

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

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

3 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.

4 Source: (Pasquill 1961)

Figure 7 Predicted Stability Class Frequencies at the Precinct (CALMET predictions, 2014)

Mixing Heights

Diurnal variations in maximum and average mixing heights predicted by CALMET at the Precinct during the 2014 modelling period are illustrated in Figure 8. As would be expected, an increase in mixing height 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 8 Predicted Mixing Heights at the Precinct (CALMET predictions, 2014)

4.3.4 Odour Peak-to-Mean Ratios

The Approved Methods 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 (DEC 2006a). 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:

For the broiler farm, a Peak-to-Mean Ratio (P/M60) of 2.3 has been applied to odour emissions from each shed.

For the W2R compost operation, a Peak-to-Mean Ratio (P/M60) of 2.5 for stability class A-D and 2.3 for stability class E and F have been applied.



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5 EMISSION ESTIMATION

5.1 Definitions

As discussed in Section 3, odour concentration is measured in terms of odour units (ou), where 1 ou is the concentration of odour-containing air that can just be detected by 50% of members of an odour panel (persons chosen as representative of the average population sensitivity to odour). This process is defined within Australian Standard AS4323.3 (2001) Stationary Source Emissions – Part 3: Determination of Odour Concentration by Dynamic Olfactometry.

An Odour Emission Rate (OER) is the product of the odour concentration and the volumetric flow rate, and is often annotated as ou.m

3/s, or ou.m

3/min. The Specific Odour Emission Rate (SOER) may be

defined as the quantity of odour emitted per unit time from a unit surface area. The quantity of odour emitted is not determined directly by olfactometry, but is calculated from the concentration of odour (as measured by olfactometry) which is then multiplied by the volume of air passing through the measurement system per unit time. SOERs are often annotated as ou.m

3/m

2/s, or ou.m

3/m

2/min.

5.2 Emission Estimation Methodology

5.2.1 Broiler Farm - 18 Coates Park Road, Cobbitty

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. 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) was developed for chicken meat sheds. It is widely acknowledged that broiler farms are more odorous than egg layer farms due to a multitude of factors. A Jiang and Sands study (Jiang and Sands 1998) estimated that, on a per bird basis, odour emissions from chicken egg-layer farms may be approximately 0.4 times that from broiler farms. However, in order to provide a conservative assessment, the emissions estimation and modelling approach in this study has followed the broiler farm methodology with some factors altered (ie bird density, bird age and bird weight). The Ormerod method 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, 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 rate estimates 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)



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The parameters used for the estimation of odour emissions from each shed within the broiler farm are summarised in Table 5.

Table 5 Parameters used in Estimating Odour Emissions from the Broiler Farm

Parameter Value Units Notes

K 2.2 - Factor nominated in 2005 for new farms conforming to best practice. (Ormerod et al 2005). Expected to be appropriate for an existing operation, however new farms can now achieve a K factor of 2.

A Calculated m2 Calculated based on the shed dimensions

D hourly varying kg/m2

Based on the number of birds and weight of each bird in the bird cycle

V hourly varying m3/s

Based on bird age and target temperature inside the shed (varying with ambient temperature)

The estimated varying bird density and the varying ventilation rate for a typical bird growth cycle during summer months are shown in Figure 9. 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).

Figure 9 Bird Density and Varying Ventilation Rate Profile for the Precinct (example shed)

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 9 represents the bird cycle during the summer season.



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The ventilation rate (V) at any given time is a function of the age of the birds and the ambient temperature. Table 6 provides an estimate of the ventilation required for a tunnel ventilated shed as a percentage of the maximum for summertime conditions.

Table 6 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 17

1 1.7 12.5 12.5 25 25 25 25 25

2 1.7 25 25 37.5 37.5 37.5 37.5 37.5

3 1.7 37.5 37.5 50 50 50 50 50

4 1.7 37.5 37.5 50 50 50 50 50

6 1.7 37.5 37.5 62.5 75 75 75 75

7 1.7 37.5 37.5 62.5 75 75 87.5 100

8 1.7 62.5 62.5 62.5 75 75 100 100

9 1.7 62.5 62.5 87.5 100 100 100 100

Source: Ormerod et al 2005

The total bird cycle is assumed to be 50 days, including a 10 day cleanout period. It has been assumed that 25% of the total birds would be removed on day 32, day 38 and day 44, with the remaining birds removed on day 50. It is recognised that there may be a degree of variation in bird cycle lengths however; a 50 day cycle is a conservative assumption.

Bird mortality at day 32 is normally at least 2%. However, due to the uncertainty associated with estimating bird mortality, the estimated bird numbers used in this study are based on a 0% mortality rate which will result in a conservative assessment of potential odour impacts.

All sheds have been modelled using emission rates for mechanically ventilated sheds. When sheds are assumed to be mechanically ventilated, odour emissions are more consistently emitted during all meteorological conditions. Whilst this approach may therefore not reflect the potential build-up of odours within a naturally ventilated shed that would be emitted during wind gusts or when wind speeds increase, odour emissions are modelled under a wider range of meteorological conditions, including worst case poorly dispersive conditions.

In addition, the higher frequency of emissions would result in odours being predicted off-site more frequently. The approach used is therefore expected to provide a conservative assessment of potential odour impacts.

The sheds have been modelled as pseudo-point sources. The air flow has been calculated to provide 0.1 cubic feet of air flow per minute per pound of body weight of the chickens in each shed for each 10°F of temperature of outside air

1. The source parameters for the farms are presented in Table 7.

The estimated hourly-varying odour emission rates, calculated using the methodology presented above, were input into the CALPUFF dispersion model via hourly-varying emission files.

1 http://www.thepoultrysite.com/articles/2321/key-factors-for-poultry-house-ventilation/



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Table 7 Source Parameters Used for the Broiler Farm

Source ID

Easting (m)

Northing (m)

Ground Elevation (m)

Total Site Shed Width (m)

Sigma Y1 Sigma Z Max

Ventilation Rate (m

3/min)

1 285,385 6,237,618 82 14 3.25

0.1

6,489

2 285,385 6,237,574 84 12 2.80 5,562

3 285,376 6,237,548 86 14 3.25 7,787

4 286,173 6,237,765 113 14 3.25 7,787

5 286,148 6,237,752 111 13 3.02 5,543

6 286,014 6,237,744 97 13 3.02 5,543

7 286,014 6,237,709 96 18 4.20 7,675

8 285,409 6,237,662 81 18 4.20 7,675

Notes:

1. The total shed width from the entire farm has been used to base the calculation of sigma y. This generates a conservative estimate of the initial horizontal spreading of the plume as the shed width is shorter than the shed length (ie the initial plume will be more concentrated).

Estimated Emissions

The approximate variability of odour emissions is shown in Figure 10. The decline in emissions after day 50 represents the clean-out of the sheds. It is noted that the shed clean-out may result in elevated odour release during 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).

Figure 10 Modelled Shed Odour Emission Rates for the Broiler Farm (example shed)



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The variability of estimated odour emissions for each shed for a year of operations is shown in Figure 11. Lower temperatures in the late autumn and winter months lead to a drop in the overall emissions midway through the year, which result in lower ventilation rates and therefore less odour emissions from the sheds.

Figure 11 Modelled Shed Odour Emission Rates throughout the Year (example shed)

5.2.2 W2R Compost Farm

As discussed in Section 2.3.2, odours from the composting operation can be generated from the following onsite activities:

Fresh green waste stockpiles (including mulch and undisturbed);

Maturation of green waste (windrows); and

Storage of final compost product.

A review of publically available literature has been performed to identify the potential odour emission rates for green waste composting. Four relevant EIS were available and reviewed which included:

Woy Woy AWT and Composting Facilities – Air Quality Impact Assessment – URS 2007.

Proposed Ophir Road Resource Recovery Centre - Air Quality Assessment – Heggies 2009.

Myocum Landfill – Odour Emission Assessment Report – KMH 2011.

Proposed Modification to the Northern Extension Landfill at Eastern Creek – Air Quality Assessment – PAEHolmes 2010.

From each assessment, the odour emission rates used for fresh green waste and matured green waste areas were identified and are presented in Table 8. The odour emission rate for green waste maturation areas was shown to be the highest of all those referenced.



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Table 8 Odour Emission Rates Identified from the Literature Review

Material Type OER (ou.m

3/s)

Reference

Green waste maturation area 0.46 Woy Woy AWT and Composting Facilities (URS 2007)

Green waste stockpiles 0.055 Ophir Road RRC (Heggies 2009)

Green waste stockpile (quiescent) 0.25 Myocum Landfill (KMH 2011)

Green waste operations (ANL) 0.03 Eastern Creek Landfill (PAEHolmes 2010)

It was noted that the Ophir Road RRC AQIA (Heggies 2009) used a very low odour emission rate for green waste stockpiles and there was no information available regarding the status of the green waste (i.e. mature, fresh, disturbed etc). Therefore, it has not been used in this assessment.

Also, no odour emission rates were publicly available for final product. In the absence of such specific data, the ‘maturation windrows’ odour emission rate was adopted for the final product. This is considered to be conservative, as in reality the final compost product has negligible odour because of minimal microbial activity.

The adopted odour emission rates for this assessment were as shown in Table 9.

Table 9 Odour Emission Rates Adopted for W2R Compost Farm

Activity OER (ou.m

3/s)

Reference

Fresh green waste (mulch) 0.03 Eastern Creek Landfill (PAEHolmes 2010)

Fresh green waste (sorted, undisturbed)

0.25 Myocum Landfill (KMH 2011)

Maturation windrows 0.46 Woy Woy AWT and Composting Facilities (URS 2007)

Final product 0.46 Woy Woy AWT and Composting Facilities (URS 2007)



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6 RESULTS AND DISCUSSION

The predicted cumulative 99th percentile odour concentrations (nose-response time, 1-second

average) due to the operations of the broiler farm and the W2R compost farm are presented as a contour plot in Figure 12.

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 12 Predicted Cumulative Ground Level 99th

Percentile Odour Concentrations

Note: Project odour criterion of 2 OU (and greater) is shown in red.



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As shown in Figure 12, the cumulative 99th percentile 1-hour average odour concentrations are

predicted to exceed the odour criterion of 2 ou in a localised area at the western boundary of the Precinct.

Figure 13 and Figure 14 show the incremental odour impacts predicted as a result of the estimated odour emissions from the broiler farm only and the W2R compost farm only respectively. It can be seen from Figure 13 that odour emissions from the broiler farm are predicted to comply with the criterion at the Precinct, hence they would not be expected to have any significant odour impact on the Precinct. The exceedances of the criterion on the western boundary of the Precinct relate to emissions from the composting operation only.

Figure 13 Predicted Incremental Ground Level 99th

Percentile Odour Concentrations – Broiler Farm



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Percentile Odour Concentrations – W2R Compost Farm

It can be seen from Figure 14 that the 7 ou contour line is not predicted to encroach upon the Precinct boundary. As mentioned in Section 3, an odour performance goal of 7 ou detection is likely to represent the level below which ‘offensive’ odours should not occur (for an individual with a ‘standard sensitivity’ to odours). The NSW EPA recommends within the Odour Framework that, as a design goal, no individual be exposed to ambient odour levels of greater than 7 ou detection (99

th percentile,

nose response time).



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In August 2018, DPE finalised the draft ILP for the Lowes Creek Maryland Precinct for public exhibition. The predicted odour impacts from the W2R compost farm overlayed on the draft ILP is shown in Figure 15. It can be seen from Figure 15 that the 2 ou and 3 ou contour lines are predicted to encroach upon the northwestern Precinct boundary. The areas where the odour criterion of 2 ou is predicted to exceed are proposed in the draft ILP to be zoned as low density (15 to 25 dwellings per hectare), environmental living (maximum 10 dwellings per hectare), riparian corridor and environmental conservation. A park is also proposed to be located within this area.

The predicted dispersion modelling results should be viewed as conservative representation of the odour impacts due to the following reasons:

The odour from broiler farm and compost operation are likely to be distinctly different from each other due to the difference characteristics, hence cumulative impacts will be minimised;

The odour emission methodology for chicken meat farms has been adopted which have been shown to be more than twice as odorous as emissions from a layer farm;

Odour emission data for maturation windrows were used to estimate odour emission rates from the final product stockpiles at which is likely to overestimate the impacts; and

The screening and filtering effects of the vegetative buffer around the compost farm have not been included in the emission estimation or dispersion modelling due to the inability of the models to accommodate such features; and

Near-field peak to mean ratios have been used for area sources within the W2R compost farm, which is likely to overestimate the impacts.

In addition, as noted in Section 2.3.2, SLR understands that new technology is proposed to be incorporated within the composting operations, which is anticipated to reduce odour impacts.

The conservative assumptions listed above have been made due to the uncertainty associated with the relatively limited amount of operational data for the broiler farm and the absence of any site-specific monitoring data for the W2R compost farm. This means that the odour concentrations predicted within the Precinct as shown in Figure 15 are expected to overestimate actual odour levels.

However, as the modelling results indicate that there is potential for odours from compost farm to have an impact on amenity levels at the northwestern corner of the Precinct, the following mitigation measures have been identified to mitigate the odour nuisance impacts:

Construction of the Precinct will be staged over 15-20 years, commencing at the eastern boundary by Northern Road and extending westerly during that period. There is therefore a significant period of time before any construction would occur within the potentially affected areas of the Precinct and modifications to the Master Plan can be made to accommodate for these impacts.

As the construction of the Precinct will be staged over 15-20 years, before the development is undertaken in the potentially-affected area and if the operations at the compost farm are still ongoing, it is proposed that a series of odour intensity surveys (ground truthing) be conducted to confirm the results of the modelling study.

If the odour surveys do indicate odours from the compost farm are detectable within the Precinct Site boundary, the playing fields or parks areas within the Precinct Site may be relocated (see Figure 15) to this area to minimise population density in these areas and to be more reflective of the rural and working land surroundings.

Alternatively, a clause may be added to the titles of the affected properties such as ‘This property is potentially odour-affected by compost farm operations’.



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Percentile Odour Concentrations – W2R Compost Farm



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7 CONCLUSIONS

SLR Consulting Australia Pty Ltd (SLR) was commissioned by DPE to conduct a Level 3 Odour Impact Assessment (OIA) for the Lowes Creek Maryland Precinct (the Precinct) located in the South West Growth Area.

The Precinct is located in the Camden Local Government Area, in the South West Growth Area. The precinct is approximately 517 hectares in size and currently consists of rural areas and the historic Maryland homestead.

The aim of this Level 3 OIA was to quantify the odour impacts from poultry sheds located at 18 Cobbitty Road (the broiler farm) and Waste-to-Resource (W2R) compost farm (W2R compost farm) located at the southwest corner of Precinct.

This study has been carried out in accordance with New South Wales (NSW) Office of Environment and Heritage (OEH) odour policy: Technical Framework: Assessment and Management of Odour from Stationary Sources in NSW (the Odour Framework) (DEC 2006a) and supporting documentation: Technical Notes: “Assessment and Management of Odour from Stationary Sources in NSW (the Technical Notes) (DEC 2006b).

A number of conservative assumptions have been made in estimating the odour emission rates for

both the broiler farm and W2R compost farm. The cumulative 99th percentile 1-hour average odour

concentrations are predicted to exceed the odour criterion towards the western boundary of the Precinct.

Further analysis showed that the individual contributions from the broiler farm are unlikely to have any impact on the Precinct boundary. However, the predicted odour impacts from the compost farm are predicted to exceed the Project criterion in a localised area on the western boundary of the Precinct.

Given the long time frame of the staged development (15-20 years), the anticipated improvements in technology proposed for the W2R compost farm and the potential application for a change in use of the land between the W2R compost farm and the Precinct (which may expedite the adoption of improved technology or encourage the relocation of the use to another site), it is recommended that the development of the western part of the Precinct be subject to an updated assessment of potential odour impacts at the time that development within the potentially affected area identified in Figure 15 is proposed.

It is concluded that the operations of the broiler farm should not be seen as a deterrent to the rezoning application of the Precinct. Given the conservative assumptions used in the modelling and the limited nature of the exceedances predicted within the Precinct Site boundary due to the current W2R composting operations, it is also concluded that the predicted odour impacts from W2R should be able to be addressed through the development and implementation of an odour mitigation strategy.




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8 REFERENCES

Camden Council 2011, Land Zoning Map - Sheet LZN_007, Camden Local Environmental Plan2010,

DEC 2003, Environmental Guidelines - Composting and related organics processing facilities,Department of Environment and Conservation NSW, 24 September 2003.

DEC 2006a, Technical framework: assessment and management of odour from stationarysources in NSW, Department of Environment and Conservation NSW, November 2006.

DEC 2006b, Technical Notes: Assessment and management of odour from stationary sources inNSW, Department of Environment and Conservation NSW, November 2006.

Elton 2016, Demographic and Social Infrastructure Assessment, Lowes Creek Marylands (parts)Precinct, prepared for Macarthur Developments, September 2016.

Heggies 2009, Air quality impact assessment – Proposed Ophir road resource recovery centre,Prepared for: Orange City Council.

Jiang, & Sands 1998, Report on Odour Emissions from Poultry Farms in Western Australia -Principal Technical Report. Sydney: Centre for Water and Waste Technology, University of NSW.

KMH 2011, Odour Emission Assessment Report - Myocum Landfill, prepared fro Byron ShireCouncil, Project number 4011-099, 6 October 2011.

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

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

PAEHolmes 2010, Technical Report No.7, Air Quality Assessment – Odour and Dust: ProposedModification to the Northern Extension Landfill at Eastern Creek, prepared for NationalEnvironmental Consulting Services, Job no. 2965, 30 March 2010.

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

The Odour Unit 2008, Odour impact assessment study, Tharbogang Landfill, Tharbong NSW.

TRC 2011, Generic Guidance and Optimum Model Settings for the CALPUFF Modelling Systemfor Inclusion into the ‘Approved Methods for the Modelling and Assessment of Air Pollutants inNSW, Australia’, prepared for Ofice of Environment and Heritage, Sydney Australia, prepared by:Jennifer Barclay and Joe Scire, Atmopheric Studies Group, TRC Environmental Corporation,March 2011.

URS 2007, Appendix D - Air Quality Impact Assessment Report - Woy Woy AWT andComposting Facilities, prepared for Gosford City Council, August 2007.

USEPA 2005, Federal Register, Part III – Environmental Protection Agency 40CFR Part 51,November 9 2005.

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