Air Quality Assessment of the Birkenhead Cement Plant, Sep 2017

Air Quality Assessment of the Birkenhead Cement Plant

September 2017

FINAL

Prepared by:

Katestone Environmental Pty Ltd www.katestone.com.au ABN 92 097 270 276 [email protected] Ground Floor, 16 Marie Street | PO Box 2217 Ph +61 7 3369 3699 Milton, Brisbane, Queensland, 4064, Australia Fax +61 7 3369 1966 Document Control

Deliverable #: D16076-16

Title: Air Quality Assessment of the Birkenhead Cement Plant

Version: 1.6 (FINAL)

Client: Adelaide Brighton Cement

Document reference: D16076-16_Birkenhead_AirQuality_Modelling_v1.6.docx

Prepared by: Michael Burchill

Reviewed by: Simon Welchman

Approved by:

Simon Welchman

08/09/2017

PRIVATE & CONFIDENTIAL: This document records private and confidential information that has commercial value to Adelaide Brighton Cement Ltd and its competitors, and its disclosure could reasonably be expected to diminish that commercial value and have an adverse effect on the business and commercial affairs of Adelaide Brighton Cement. In addition, disclosure could reasonably be expected to prejudice the future supply of information to the EPA.

Disclaimer http://katestone.com.au/disclaimer/

This document, electronic files or software are the copyright property of Katestone Environmental Pty. Ltd. and the information contained therein is solely for the use of the authorised recipient and may not be used, copied or reproduced in whole or part for any purpose without the prior written authority of Katestone Environmental Pty. Ltd. Katestone Environmental Pty. Ltd. makes no representation, undertakes no duty and accepts no responsibility to any third party who may use or rely upon this document, electronic files or software or the information contained therein.

 Copyright Katestone Environmental Pty. Ltd.

Contents

Executive Summary ...... v 1. Introduction ...... 1 2. Legislative framework for air quality ...... 2 3. Existing environment ...... 5 3.1 Local terrain and land-use ...... 5 3.2 Existing air quality ...... 5 3.2.1 Existing sources of emissions ...... 5 3.2.2 Existing ambient air quality ...... 7 4. Air quality assessment methodology...... 9 4.1 Emission Rates ...... 9 4.2 Meteorology ...... 9 4.3 Dispersion Modelling ...... 9 4.4 Cumulative Impacts ...... 10

4.5 NOX to NO2 Conversion ...... 10 5. Emissions to the atmosphere ...... 11 5.1 Normal operations ...... 11 5.1.1 Stack sources ...... 11 5.1.2 Dust collectors ...... 12 5.1.3 Fugitive sources ...... 13 5.1.4 Varying emissions sources ...... 14 5.1.5 Controls...... 15 5.1.6 Summary...... 15 5.2 Particulate Emissions due to Process Variations ...... 16 6. Meteorology ...... 18 6.1 Wind speed and wind direction...... 18 6.2 Mixing height ...... 20 6.3 Stability Class ...... 20 7. Results ...... 22 7.1 Normal operations ...... 22 7.1.1 Isolation...... 22 7.1.2 Cumulative assessment ...... 22 7.1.3 Source contribution analysis ...... 22 7.1.4 Detailed stack emissions ...... 28 7.2 Particulate Emissions due to Process Variations ...... 29 8. Conclusions ...... 30 9. References ...... 31 Appendix A Ambient Monitoring ...... 42 A1 Introduction ...... 42 A2 EPA monitoring ...... 43

A2.1 Le Fevre 1 – PM10 and PM2.5 ...... 43

A2.2 Le Fevre 2 – NO2 and SO2 ...... 55 A2.3 CBD - CO ...... 56 A3 ABC Monitoring ...... 57 A3.1 Summary...... 57 A3.2 Analysis ...... 59 AppendIx B Meteorological and Dispersion Modelling Methodology ...... 62 B1 Meteorology ...... 62 B1.1 TAPM meteorology ...... 62 B1.2 CALMET meteorological modelling ...... 62 B1.3 Comparison of CALMET output with observational data ...... 63 B2 CALPUFF dispersion modelling ...... 65 B2.1 CALPUFF Setup ...... 65 B2.2 Building Inputs ...... 66 Appendix C Emissions Inventory ...... 67

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C1 Inventory and activity data ...... 67 C2 Vehicle movements ...... 72 C3 Dust collectors ...... 73 C4 Emission Factors for Dust ...... 75 C4.1 Material transfers ...... 75 C4.2 Wind erosion of stockpiles ...... 75 C4.3 Wind erosion of exposed areas ...... 75 C4.4 Haulage on unpaved roads ...... 75 C4.5 Haulage on paved roads ...... 76 C4.6 Vehicle combustion emissions ...... 76 C4.7 Dust collectors ...... 76 Appendix D Modelling and Monitoring Comparison ...... 77 D1 Model description ...... 77 D2 Analysis ...... 77 Tables

Table 1 Relevant criteria from the Air EPP Schedule 2 (unless noted otherwise) ...... 2 Table 2 Dust deposition objectives ...... 4 Table 3 Emissions reported to the NPI during the 2015/16 reporting period ...... 5 Table 4 Ambient concentrations at EPA monitoring sites ...... 8 Table 5 Ambient background levels used in the assessment (µg/m3) ...... 10 Table 6 Stack characteristics of the modelled stack sources ...... 11 Table 7 Emission rates of particulate matter from modelled stack sources (g/s)...... 11 Table 8 Emission rates from modelled stack sources (g/s) ...... 12 Table 9 Dust collector vertical release stack characteristics...... 13 Table 10 Measured concentrations (mg/Nm³) ...... 13 Table 11 Controls included in the assessment ...... 15 Table 12 Summary of normal operations emissions inventory ...... 16 Table 13 Stack characteristics and emission rates for process variation scenarios ...... 17

Table 14 Source contributions for the top 25 predicted 24-hour average concentrations of PM10 at the Community Park ...... 23

Table 15 Source contributions for the top 25 predicted 24-hour average concentrations of PM10 at the Le Fevre 1 monitoring site ...... 23

Table 16 Source contributions for the top 25 predicted 24-hour average concentrations of PM2.5 at the Community Park ...... 25

Table 17 Source contributions for the top 25 predicted 24-hour average concentrations of PM2.5 at the Le Fevre 1 monitoring site ...... 26 Table 18 Predicted maximum offsite ground-level concentrations of all pollutants from stacks in isolation 28 Table 19 Predicted maximum offsite ground-level concentrations of all pollutants from stacks including background...... 29 Figures

Figure 1 Facilities in the region that reported to the NPI in 2015/16 ...... 7 Figure 2 Schematic of Facility showing locations of stacks, dust collectors and fugitive dust sources ...... 14

Figure 3 Emissions of PM10 by source for normal operations ...... 16 Figure 4 Annual distribution of winds at the Facility (from CALMET) ...... 18 Figure 5 Seasonal distribution of winds at the Facility (from CALMET) ...... 19 Figure 6 Diurnal distribution of winds at the Facility (from CALMET) ...... 19 Figure 7 Box and whisker plot of mixing height at the Facility location (CALMET) ...... 20 Figure 8 Distribution of stability class by hour at the Facility location (CALMET) ...... 21

Figure 9 Source contributions for the top 25 predicted 24-hour average concentrations of PM10 at the Community Park ...... 24

Figure 10 Source contributions for the top 25 predicted 24-hour average concentrations of PM10 at the Le Fevre 1 monitoring site ...... 25

Figure 11 Source contributions for the top 25 predicted 24-hour average concentrations of PM2.5 at the Community Park ...... 27

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Figure 12 Source contributions for the top 25 predicted 24-hour average concentrations of PM2.5 at the Le Fevre 1 monitoring site ...... 27 Contour Plates

Plate 1 Predicted maximum 24-hour average ground-level concentrations of PM10 due to normal operations of the Facility in isolation ...... 32

Plate 2 Predicted maximum 24-hour average ground-level concentrations of PM2.5 due to normal operations of the Facility in isolation ...... 33

Plate 3 Predicted annual average ground-level concentrations of PM2.5 due to normal operations of the Facility in isolation ...... 34 Plate 4 Predicted annual average dust deposition rate due to normal operations of the Facility in isolation ...... 35

Plate 5 Predicted maximum 24-hour average ground-level concentrations of PM10 due to normal operations of the Facility including an ambient background of 18 µg/m³...... 36

Plate 6 Predicted maximum 24-hour average ground-level concentrations of PM2.5 due to normal operations of the Facility including an ambient background of 7.3 µg/m³ ...... 37

Plate 7 Predicted annual average ground-level concentrations of PM2.5 due to normal operations of the Facility including an ambient background of 7.3 µg/m³ ...... 38

Plate 8 Predicted maximum 24-hour average ground-level concentrations of PM10 due to normal operations of the Facility and under two process variation scenarios. All scenarios include an ambient background of 18 µg/m³...... 39

Plate 9 Predicted maximum 24-hour average ground-level concentrations of PM2.5 due to normal operations of the Facility and under two process variation scenarios. All scenarios include an ambient background of 7.3 µg/m³...... 40 Plate 10 Predicted maximum monthly average dust deposition rate due under two process variation scenarios in isolation ...... 41

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Glossary

Term Definition µg/m3 micrograms per cubic metre µm micrometre °C degrees Celsius m metre m/s metres per second m2 square metres m3 cubic metres m3/s cubic metres per second Nomenclature Definition CO carbon monoxide

NO2 nitrogen dioxide

NOx oxides of nitrogen

PM10 particulate matter with a diameter less than 10 micrometres

PM2.5 particulate matter with a diameter less than 2.5 micrometres

SO2 sulfur dioxide Abbreviations Definition Air EPP Environment Protection (Air Quality) Policy 2016 EF Emission factor EPA Environment Protection Authority EP Act Environment Protection Act 1993 NPI National Pollutant Inventory database

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EXECUTIVE SUMMARY

Katestone Environmental Pty Ltd (Katestone) was commissioned by Adelaide Brighton Cement (ABC) to complete an Air Quality Assessment of the Birkenhead Cement Plant (the Facility).

The Facility’s licence is due for renewal in October 2017. This report fulfils a requirement of the Environment Protection Authority (EPA) that ABC conducts an air quality assessment of the Facility as part of the licence renewal process. The air quality assessment has been conducted in accordance with the EPA’s guidance for air quality assessments.

Modelling of emissions of particulate matter from normal operations was conducted. The results show that:

• 24-hour average concentrations of PM10 are predicted to be more than 50 µg/m³ within a limited area beyond the site boundary.

• 24-hour average concentrations of PM2.5 are predicted to be less than 25 µg/m³ beyond the site boundary.

• Annual average concentrations of PM2.5 are predicted to be more than 8 µg/m³ within a limited area beyond the site boundary. The background concentration of 7.3 µg/m³ is the major contributor to

concentrations of PM2.5.

• Annual average dust deposition rates are predicted to be less than the NSW Approved Methods criterion of 66 mg/m²/day at all residential areas.

Modelling of emissions of other air pollutants from the stacks was conducted. The results show:

• All pollutants are less than their respective criteria.

• The maximum offsite 1-hour average concentration of nitrogen dioxide is predicted to be 168 µg/m³, which is 67% of the criterion of 250 µg/m³.

• All other pollutants are predicted to be less than 14% of their respective criteria.

• All pollutants are less than their respective criteria including background concentrations.

Higher stack particulate emissions were modelled that are representative of short-term process variations. The results show that these operating conditions do not change significantly the ground-level concentrations in the residential areas.

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1. INTRODUCTION

Katestone Environmental Pty Ltd (Katestone) was commissioned by Adelaide Brighton Cement (ABC) to complete an Air Quality Assessment of the Birkenhead Cement Plant (the Facility).

The Facility is located in the suburb of Birkenhead in South Australia and is around 13 kilometres from the Adelaide CBD. Birkenhead is a predominantly residential suburb situated between port facilities occupying the adjacent banks of the Port River to the east and the suburbs of Exeter and Peterhead to the west. The Facility has operated since 1913. The Facility manufactures cement that is used in the construction and mining industry.

This report addresses the following scope of work:

• Description of the regulatory framework for air quality in South Australia (Section 2)

• Description of the existing environment, including landuse and air quality (Section 3) and meteorology (Section 6)

• Configuration and description of a suitable dispersion model, CALPUFF, including meteorological modelling (TAPM/CALMET) (Section 4)

• Estimation of a comprehensive emissions inventory for the site, including emissions from cement kilns and fugitive dust sources (Section 5)

• Comparison of dispersion modelling results against relevant ambient air quality criteria (Section 7).

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2. LEGISLATIVE FRAMEWORK FOR AIR QUALITY

The Environment Protection Act 1993 (EP Act) provides for the management of the air environment in South Australia. The EP Act describes the general environmental duty of persons to take all reasonable and practicable measures to prevent or minimise environmental harm when operating an activity that pollutes, or might pollute, the environment. Part 6 of the EP Act deals with environmental authorisations and development authorisations including licences and renewals.

The EP Act enables development and implementation of legislative and non-legislative tools to address environmental issues. These tools include:

• Environment Protection Policies

• Regulations

• Codes of Practice

• National Environment Protection Measures

• Guidelines

• Position statements.

The Environment Protection (Air Quality) Policy 2016 (Air EPP) was developed under the EP Act and came into effect on 23 July 2016. The Air EPP provides a framework for the regulation of air pollution in South Australia and includes air quality criteria. Part 6, Section 47 of the EP Act specifies the criteria that must be considered by the EPA in granting an environmental authorisation. The criteria include any relevant environment protection policy. Predictions of ground-level concentrations of air pollutants have, therefore, been compared to the maximum ground level concentrations that are specified in the Air EPP.

The Air EPP does not specify a criterion for dust deposition. This is an important metric for the Facility, as it has been referred to in a number of complaints received by ABC, and therefore has been included in this assessment. Predictions of dust deposition rates have been compared to the impact assessment criteria in the NSW EPA publication: Approved Methods for the Modelling and Assessment of Air Pollutants in New South Wales (NSW EPA, 2017) (Approved Methods).

The Air EPP does not specify a criterion for dioxins and furans, therefore the impact assessment criterion from the Approved Methods has been adopted.

The criteria and averaging periods used to assess predictions of ground-level concentrations and dust deposition rates in this report are presented in Table 1 and Table 2, respectively.

Table 1 Relevant criteria from the Air EPP Schedule 2 (unless noted otherwise)

Maximum Pollutant Classification Averaging time concentration (µg/m³)

Particles as PM10 Toxicity 24 hours 50

24 hours 25 Particles as PM2.5 Toxicity 12 months 8

1 hour 250 Nitrogen dioxide Toxicity 12 months 60

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Maximum Pollutant Classification Averaging time concentration (µg/m³)

1 hour 31,240 Carbon monoxide Toxicity 8 hour 11,250

1 hour 570

Sulfur dioxide Toxicity 24 hours 230

12 months 60

Hydrogen chloride Toxicity 3 minutes 270

Chlorine Toxicity 3 minutes 110

24 hours 3

Fluoride Bioaccumulation 7 days 2

90 days 1

Benzene Group 1 carcinogen (IARC1) 3 minutes 58

Chromium (III) compounds Toxicity 3 minutes 19

Chromium VI compounds Group 1 carcinogen (IARC) 3 minutes 0.19

Benzo(a)pyrene as a marker for Group 1 carcinogen (IARC) 3 minutes 0.8 polycyclic aromatic hydrocarbons

Antimony and compounds Toxicity 3 minutes 19

Arsenic and compounds Group 1 carcinogen (IARC) 3 minutes 0.19

Barium Toxicity 3 minutes 19

Beryllium and beryllium Group 1 carcinogen (IARC) 3 minutes 0.008 compounds

Cadmium and cadmium Group 1 carcinogen (IARC) 3 minutes 0.036 compounds

Copper fume Toxicity 3 minutes 7.3

Iron oxide fume Toxicity 3 minutes 190

Lead Toxicity 12 months 0.5

Magnesium oxide fume Toxicity 3 minutes 360

Manganese and compounds Toxicity 3 minutes 36

Mercury - inorganic Bioaccumulation 3 minutes 4

Mercury - organic Bioaccumulation 3 minutes 0.36

Nickel and nickel compounds Group 1 carcinogen (IARC) 3 minutes 0.36

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Maximum Pollutant Classification Averaging time concentration (µg/m³)

Zinc oxide fume Toxicity 3 minutes 190

Dioxins and furans2 Group 1 carcinogen (IARC) 1-hour 0.0000037

Table notes: 1 International Agency for Research on Cancer 2 NSW Approved Methods

Table 2 Dust deposition objectives

Maximum deposition Pollutant Classification Averaging time rate (mg/m²/day) Deposited dust (incremental) Nuisance Annual 661 Note: 1 Converted from g/m2/month.

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3. EXISTING ENVIRONMENT

3.1 Local terrain and land-use

Land use surrounding the Facility is predominantly residential to the north, west and south. Existing industries are located within the port to the east and to the north of the Facility and include the Viva Energy Bitumen Plant, AGL Torrens Island Power Station, Osborne Cogeneration Plant and EDL Wingfield LFG plant.

The terrain at Birkenhead is relatively flat, with the site of the Facility at an elevation of approximately two metres above sea level.

3.2 Existing air quality

3.2.1 Existing sources of emissions

The Facility is located south of the Outer Harbour industrial area and west of Port Adelaide. A broad range of industrial activities is located in the surrounding area. The National Pollutant Inventory database for the 2015/16 reporting year identifies 67 other facilities within 10 km that reported emissions of air pollutants in common with the Facility (Table 3). These other facilities include electricity generation, metal fabrication, asphalt production, manufacturing of a broad range of products (including foods, beer and wine, paints, boxes, plastic and metal products), and storage and distribution of products.

The locations of the nearest facilities are shown in Figure 1.

Table 3 Emissions reported to the NPI during the 2015/16 reporting period

Emissions reported to the NPI (kg/year) Registered business Facility PM10 PM2.5 NOX SO2 CO ACI OPERATIONS PTY LTD ACI Glass Packaging 54,285 43,978 363,127 130,500 19,752 ADELAIDE BRIGHTON CEMENT Birkenhead Plant 121,734 19,999 2,966,640 22,187 611,083 LTD AGL SA GENERATION PTY AGL Torrens Island Power 107,941 103,318 3,115,936 297,970 323,921 LIMITED Station AGL SOUTH AUSTRALIA PTY AGL Coopers Cogeneration 1,026 989 51,297 92 12,824 LIMITED BORAL RESOURCES (SA) Gepps Cross Asphalt Plant 7,917 164 3,945 351 24,456 LIMITED BPL ADELAIDE PTY LIMITED BPL Adelaide Pty Limited 273 269 4,691 17 20,590 BRADKEN RESOURCES PTY Bradken Adelaide 26,190 331 8,155 91 10,805 LIMITED

CARGILL MALT ASIA PACIFIC Malt Cavan 1,313 180 2,390 26 2,039 PTY LTD Malt Port Adelaide 6,362 655 4,476 98 7,588 DOWNER EDI WORKS PTY LTD Wingfield 2,209 94 4,212 677 46,225 Wingfield 1 77 35 36,400 2,140 77,800 EDL LFG (SA) PTY LTD Wingfield 2 85 39 11,400 2,690 97,700 INTERCAST & FORGE PTY Intercast & Forge, Wingfield 26,399 123 2,396 505 1,156 LIMITED

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Emissions reported to the NPI (kg/year) Registered business Facility PM10 PM2.5 NOX SO2 CO KORVEST LTD Korvest Ltd 2,347 2,108 4,844 17 1,814 MCKECHNIE IRON FOUNDRY McKechnie Iron Foundry 2,674 1,367 - - - PROPRIETARY LIMITED Pty Ltd ORIGIN ENERGY POWER Quarantine Power Station 4,778 4,607 73,135 425 11,141 LIMITED ORORA LIMITED Orora Fibre Packaging 96 96 6,721 14 3,113 OSBORNE COGENERATION Osborne Cogeneration 412 412 326,473 22,339 13,701 PTY LTD Plant PELICAN POINT POWER Pelican Point Power Station 6,689 6,450 105,122 597 17,061 LIMITED SOUTH AUSTRALIAN WATER Bolivar Wastewater 1,674 1,674 38,501 366 5,440 CORPORATION Treatment Plant Cavan Meter Stations 97 97 1,315 15 1,108 Pelican Point Meter Station 100 100 1,345 15 1,134 SOUTH EAST AUSTRALIA GAS PTY LTD Quarantine Meter Station 17 17 232 3 195 Torrens Island Meter 2,118 2,118 28,588 316 24,088 Station THE SMITH'S SNACKFOOD Regency Park 8,757 703 4,946 104 8,440 COMPANY PTY LIMITED OTHER Other 6,711 5,024 91,489 1,061 73,360

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Figure 1 Facilities in the region that reported to the NPI in 2015/16

3.2.2 Existing ambient air quality

The EPA conducts ambient air quality monitoring at a number of locations around the state. There are three sites of relevance to the Facility. The EPA monitors concentrations of PM10 and PM2.5 at Le Fevre 1. Concentrations of

NO2 and SO2 are monitored by the EPA at Le Fevre 2 and CO is monitored at Adelaide CBD site. A detailed analysis of ambient monitoring data is presented in Appendix A.

Le Fevre 1 may potentially be influenced by the Facility when the wind direction is between 20° and 80°. To avoid double counting and as per Katestone’s discussion with the EPA on 8 March 2017, background concentrations of

PM10 and PM2.5 have been estimated based on the average concentration measured at Le Fevre 1 when winds are not from the direction of the Facility.

Due to the distance of Le Fevre 2 from the Facility, it is impractical to remove the potential influence of the Facility.

Consequently, the average concentrations of NO2 and SO2 measured at this site has been used as a background. Concentrations at Le Fevre 2 will potentially include a small contribution from the Facility and will therefore be conservative. The average concentration of CO from the Adelaide CBD site has been used as a conservative estimate of the background concentration in the vicinity of the Facility. In reality, levels of CO will be lower than measurements from the CBD.

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Average concentrations are based on all available data. Meteorological data is available for 2015 and 2016 only, therefore concentrations subset by wind direction are for this period only.

Table 4 Ambient concentrations at EPA monitoring sites

Average concentration (µg/m³) Monitor Pollutant from direction of not from direction of All directions Facility Facility

PM10 19.9 25.6 18.0 Le Fevre 1 PM2.5 7.5 8.8 7.3

NO2 10.8 NA NA Le Fevre 2 SO2 0.9 NA NA CBD CO 245 NA NA

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4. AIR QUALITY ASSESSMENT METHODOLOGY

This air quality assessment was conducted in accordance with recognised techniques for dispersion modelling and emission estimation. The assessment incorporates source characteristics, air pollution emission rates, local meteorology, terrain and land use.

4.1 Emission Rates

Emissions from the cement kilns, slag dryer and dust collectors have been based on stack tests. Where multiple samples were taken from the same source, the highest concentration has been used in the dispersion modelling.

Emissions from fugitive sources have been calculated primarily using the NPI Emissions Estimation Technique (EET) Manual for Cement Manufacturing v2.1. Emissions from vehicle movements have been calculated using NPI EET Manual for mining and the US EPA AP42 Paved Roads handbook.

4.2 Meteorology

The meteorological data for this study was generated by coupling TAPM (version 4.0.5), a prognostic mesoscale model, to CALMET (version 6.5.0), a diagnostic meteorological model. The coupled methodology for the TAPM/CALMET modelling system was developed by Katestone to enable high resolution modelling for regulatory and environmental assessments. The modelling system can incorporate synoptic, mesoscale and local atmospheric conditions, detailed topography and land use categorisation schemes to simulate synoptic and regional scale meteorology for input into pollutant dispersion models, such as CALPUFF.

Following discussions with the EPA, 2009 was selected for the meteorological model simulation as a representative year. Further details of the model configuration and output are supplied in Appendix B. Data from five monitoring stations operated by the Bureau of Meteorology was assimilated into the TAPM simulation to improve the representativeness of the generated dataset.

4.3 Dispersion Modelling

The dispersion modelling of emissions from the Facility has been conducted using the CALPUFF dispersion model. The CALPUFF model utilises the three-dimensional wind fields from CALMET to simulate the dispersion of air pollutants to predict ground-level concentrations across a gridded domain. CALPUFF is a non-steady-state Lagrangian Gaussian puff model containing parameterisations for complex terrain effects, overwater transport, coastal interaction effects, building downwash, wet and dry removal, and simple chemical transformation. CALPUFF employs the three dimensional meteorological fields generated from the CALMET model by simulating the effects of time and space varying meteorological conditions on pollutant transport, transformation and removal. CALPUFF contains algorithms that can resolve near-source effects such as building downwash, transitional plume rise, partial plume penetration, sub-grid scale terrain interactions, as well as the long-range effects of removal, transformation, vertical wind shear, overwater transport and coastal interactions. Emission sources can be characterised as arbitrarily-varying point, area, volume and lines or any combination of those sources within the modelling domain.

CALPUFF is a model recognised as suitable for air quality assessments by the EPA, particularly for facilities on complex terrain or in coastal locations.

Details of the CALPUFF model configuration are provided in Appendix B.

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4.4 Cumulative Impacts

Cumulative concentrations of particulates, NOx, SO2 and CO due to the Facility and ambient background levels have been calculated for comparison against the air quality criteria. Ambient background concentrations of these pollutants have been determined from monitoring data from the EPA monitoring network and are presented in Table 5. Predicted ground-level concentrations of all other air pollutants due to the Facility have been assessed without ambient background concentrations.

Table 5 Ambient background levels used in the assessment (µg/m3)

Ambient background Pollutant Averaging time Source concentration (µg/m³)

Average PM10 concentration at Le Fevre Particles as PM10 24 hours 18.0 1 when winds are not from the Facility 24 hours 7.3 Average PM2.5 concentration at Le Fevre Particles as PM2.5 Annual 7.3 1 when winds are not from the Facility 1 hour 10.8 Nitrogen dioxide Average NO2 concentration at Le Fevre 2 Annual 10.8 1 hour 245 Carbon monoxide Average CO concentration at CBD 8 hour 245 1 hour 0.9

Sulfur dioxide 24 hours 0.9 Average SO2 concentration at Le Fevre 2 Annual 0.9

4.5 NOX to NO2 Conversion

The prediction of ground-level concentrations of NO2 has been conducted by modelling the total emission rate in grams per second for NOX from each source, with the results scaled by an empirical nitric oxide/nitrogen dioxide conversion ratio. Measurements around power stations in Central Queensland show that under worst case conditions a conversion ratio of 25 - 40% of nitric oxide to nitrogen dioxide occurs within the first ten kilometres of plume travel. During days with elevated background levels of hydrocarbons (generally originating from bush-fires, hazard reduction burning or other similar activities), the resulting conversion is usually below 50% in the first thirty kilometres of plume travel (Bofinger et al., 1986).

For this assessment, conversion from NOX to NO2 has been conducted in the following way:

• 1 hour: A 10% in stack NO2:NOX ratio and a 30% ratio at 10 km downwind. At intervening distances, the ratio is linearly interpolated between these two points

• Annual: A conservative 30% NO2:NOX ratio has been applied at all distances.

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5. EMISSIONS TO THE ATMOSPHERE

5.1 Normal operations

5.1.1 Stack sources

The Facility’s licenced stack emission sources are as follows:

• Dry process kiln main stack (4A)

• Pre-calciner plant stack (4B)

• Slag processing plant (SPP)

The stack characteristics and emission rates for these three stacks were derived from emissions tests conducted by AirLabs.

Emissions for the stacks 4A and 4B are based on the worst-case emissions from tests conducted in October 2015 (AirLabs, 2016A) and June 2016 (AirLabs, 2016B). Data for the SPP stack is derived from tests conducted in July 2013 (AirLabs, 2013). Stack characteristics and emission rates that have been used in the dispersion modelling are presented in Table 6 and Table 7, respectively.

Table 6 Stack characteristics of the modelled stack sources

Dry process kiln Pre-calciner Slag processing Parameter Units stack (4A) stack (4B) plant Stack height m 75.5 96 12.3 Stack diameter m 3.23 3.0 1.25 Exhaust gas temperature °C 102 108 60 Exhaust gas velocity m/s 19.3 19.1 19.1 Moisture content % 8.9 23.8 0.8 Exhaust gas flow rate (actual) m³/s 158 135 24 Exhaust gas flow rate (0°C, 1 atm, dry) Nm³/s 107 74 19

Table 7 Emission rates of particulate matter from modelled stack sources (g/s)

Dry process kiln Pre-calciner stack Slag processing Pollutant stack (4A) (4B) plant TSP 2.50 2.23 0.02

a PM10 1.67 1.37 0.02

a PM2.5 0.52 0.67 0.02 Table note: a Particle size distribution not available for the slag processing plant. Emissions of PM10 and PM2.5 have been conservatively assumed to be equal to emissions of TSP

Emissions of other pollutants were based on the maximum of normal operations (AirLabs, 2016A and AirLabs, 2016B) and testing conducted during the increased plastics in wood trial, in October 2014 (AirLabs, 2015) to ensure that the potential worst-case emissions were considered.

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Stack characteristics are the same as presented in Table 6. Modelled emission rates are presented in Table 8.

Table 8 Emission rates from modelled stack sources (g/s)

Dry process kiln Pre-calciner stack Slag processing Pollutant stack (4A) (4B) plant

NOX as NO2 66.3 50.8 0.06 Carbon monoxide 17.0 26.5 0.83 Sulfur dioxide 5.33 0.23 0.02 Hydrogen chloride 0.45 0.33 0.004 Chlorine 0.27 0.17 0.005 Fluoride (as HF) 0.01 0.007 0.001 Total VOC 0.08 0.10 0.009 Benzene 0.009 0.02 0.001 Chromium VI 0.0001 1.8E-05 2.5E-06 PAHs 7.5E-07 5.8E-07 2.2E-07 Antimony and compounds 2.0E-05 1.4E-05 3.3E-06 Arsenic and compounds 2.0E-05 1.6E-05 3.3E-06 Barium 0.0004 0.0004 3.3E-05 Beryllium and compounds 1.1E-05 1.5E-05 3.3E-06 Cadmium and compounds 5.5E-05 5.7E-06 1.1E-06 Chromium III and compounds 0.0003 0.0002 5.0E-05 Copper oxide fume (as CuO) 0.004 0.0003 2.3E-05

Iron oxide fume (as Fe2O3) 0.05 0.03 0.002 Lead and compounds 0.0009 0.03 2.2E-05 Magnesium oxide fume (as MgO) 0.22 0.0001 0.002 Manganese and compounds 0.001 0.001 0.0001 Mercury (organic) 0.0002 0.0004 1.0E-06 Mercury (inorganic) 2.5E-05 3.5E-05 6.7E-07 Nickel and compounds 0.0002 0.0001 6.7E-05 Zinc oxide fume (as ZnO) 0.007 0.001 0.0007 Polychlorinated Dioxins and Furans 4.0E-09 2.5E-09 -

5.1.2 Dust collectors

More than 70 dust collectors are installed throughout the facility that remove particulate matter from air before it is vented to the environment or reintroduced into a building. Dust collectors that vent inside a building are not sources of emissions to the environment and therefore are not considered further. Of the remaining dust collectors, the three most important are attached to cement mill sheds. Emissions from these account for approximately half of all emissions from dust collectors.

The vents from the dust collectors attached to cement mills 6 and 7 are vertical release points and have been modelled as point sources. All other dust collectors have been modelled as volume sources. The associated emissions characteristics are presented in Table 9.

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Table 9 Dust collector vertical release stack characteristics

Parameter Units CM6 CM7 Stack height m 25.7 22 Stack diameter m 1.06 2.0 Exhaust gas temperature °C 25 25 Exhaust gas velocity m/s 21.6 11.1 Exhaust gas flow rate (actual) m³/s 18.9 34.9

In addition to dust collectors that vent inside a building, dust collectors that operate only periodically or that have very low flows, and therefore very low emissions, have not been considered as part of this assessment. Thirty- three dust collectors have been included in the inventory, representing over 95% of dust collector emissions.

Particulate matter concentrations from all modelled dust collectors are based on monitoring conducted in May and June 2017 (AirLabs, 2017). A summary of the monitoring data is presented in Table 10. A detailed description of all dust collectors is presented in Appendix C. Emission rates are based on the measured concentrations in Table 10, dust collector flow rates and estimated utilisation throughout the year.

Table 10 Measured concentrations (mg/Nm³)

a Dust collector TSP PM10 PM2.5 CM1 1.3 0.8 0.7 CM6 7.3 1.9 1.5 CM7 1.2 1.1 0.7 DC23 0.2 0.1 0.1 DC38 0.4 0.2 0.2 DC41 0.3 0.3 0.3 DC 2CR3/CS4 0.9 0.5 0.4 All other dust collectors 7.3 1.9 1.5 Table note: a PM2.5 concentrations are estimates based on microscopy analysis of TSP and PM10 filters (AirLabs, 2017)

5.1.3 Fugitive sources

The following sources of fugitive dust have been accounted for in the model:

• Unloading of limestone from ships

• Onsite transfers of limestone, gypsum, shale, black sand, mill scale, bauxite and slag

• Wind erosion of stockpiles

• Wind erosion of cleared areas

• Vehicle movements on paved and unpaved areas.

• Combustion emissions from vehicles onsite.

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A schematic showing the location of fugitive dust sources as well as the stacks and dust collectors is presented in Figure 2. Full details of the emissions estimation process for each source type is included in Appendix C as well as a detailed emissions inventory.

Figure 2 Schematic of Facility showing locations of stacks, dust collectors and fugitive dust sources

5.1.4 Varying emissions sources

The Facility operates 24-hours per day and most activities onsite may occur at any time of the day or night. However, a small number of activities occur at certain times, and some are more likely to occur during the day shift. This has been accounted for in this assessment.

Limestone is brought to the Facility by the ship Accolade, which arrives each evening. Therefore, all ship unloading and subsequent transfer of material to the Block 9 stockpile occurs at night. This has been incorporated into the modelling by ensuring that emissions from these sources only occur between 5pm and 5am.

Limestone is moved from Block 9 to the Shellblock stockpile by truck predominantly during the dayshift. Emissions have been apportioned in the model according to the assumption that 80% of truck movements and associated material handling occurs between 5am and 5pm.

Bulk cement is trucked offsite predominantly during the dayshift. Emissions have been apportioned in the model according to the assumption that 80% of truck movements and associated material handling occurs between 5am and 5pm.

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5.1.5 Controls

Controls that have been incorporated into the assessment are listed in Table 11. Control efficiencies have been taken from the NPI Emission Estimation Technique Manual for Cement v2.1 (NPI, 2008).

Table 11 Controls included in the assessment

Estimated control Control Activities efficiency 4-sided enclosure with water sprays Ship unloading 95% a 3-sided hopper Limestone hopper, Slag hopper 90% Enclosure with dust suppression Transfer of miscellaneous materials (MM) 98% b 3-sided bunkers with wind canopies MM Pit stockpiles 90% 3-sided bunkers with hard stand base Slag stockpile 90% Stockpiles (limestone, slag, bauxite, Chemical suppressant 80% gypsum), exposed areas Chemical suppressant Unpaved roads 80% Water cart Paved roads 75% Watering Limestone stockpile 50% Table notes: a 90% control for enclosure, 50% control for water sprays b 90% control for enclosure, 80% control for dust suppression

Not all control measures are able to be quantified. The following controls measures have been put in place by ABC but have not been accounted for in the model:

• Shade cloth – reduce wind speed and collect dust

• Truck wash

5.1.6 Summary

A summary of the emissions inventory for normal operations is presented in Table 12. Emissions have been calculated primarily using the NPI Emissions Estimation Technique (EET) Manual for Cement Manufacturing v2.1. Emissions from vehicle movements have been calculated using NPI EET Manual for mining and the US EPA AP42 Paved Roads handbook. A detailed emissions inventory is provided in Appendix C.

The inventory is dominated by emissions from the cement kiln stacks 4A and 4B, as shown graphically in Figure 3 for PM10.

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Table 12 Summary of normal operations emissions inventory

Emission rate (g/s) Emission rate (kg/year) Activity TSP PM10 PM2.5 TSP PM10 PM2.5 Handling - Transfer points 0.003 0.001 0.000 51 24 4 Handling - Stockpiles 0.012 0.006 0.001 272 128 19 Stockpile wind erosion 0.156 0.078 0.012 4,907 2,454 368 Exposed areas wind erosion 0.293 0.147 0.022 9,248 4,624 694 Dust collectors 0.508 0.170 0.132 16,011 5,363 4,164 Stacks 4.749 3.049 1.199 149,775 96,164 37,822 4A Stack 2.500 1.667 0.517 78,840 52,560 16,294 4B Stack 2.233 1.367 0.667 70,430 43,099 21,024 Slag Stack 0.016 0.016 0.016 505 505 505 Vehicle movements - unpaved 0.077 0.021 0.002 2,415 666 67 Vehicle movements - paved 0.398 0.076 0.018 12,554 2,410 583 Combustion emissions – 0.039 0.039 0.035 1,233 1,233 1,118 vehicles/stationary engines Total 6.2 3.6 1.4 196,466 113,066 44,839

Figure 3 Emissions of PM10 by source for normal operations

5.2 Particulate Emissions due to Process Variations

Two scenarios with higher particulate emission rates from the kiln (stack 4A) and calciner (stack 4B) have been modelled. These higher emission rates are representative of process variations including: calciner and kiln combustion trips; calciner and kiln light up and purge events; power failures; and shutdown and start-up of raw mills. These events are typically of short duration and an allowance is currently made in the licence for these events. The assessment has conservatively modelled emissions from both stacks at 250 mg/Nm³ and 100 mg/Nm³ continuously for the entire modelling period (1 year).

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The size distribution of the emitted particulate matter (PM10 and PM2.5 fractions) have been estimated based on typical distributions. Stack characteristics are based on typical parameters observed during these events. Emissions and stack characteristics are presented in Table 13.

Table 13 Stack characteristics and emission rates for process variation scenarios

4A 4B Parameter Units Scenario 1 Scenario 2 Scenario 1 Scenario 2 Stack height m 75.5 96.0 Stack diameter m 3.23 3.00 Exhaust gas temperature °C 105 120 Exhaust gas velocity m/s 15.4 4.5 Exhaust gas flow rate (actual) m³/s 126.2 33.9 TSP concentration mg/Nm³ 250 100 250 100 TSP emission rate g/s 20.8 8.3 4.9 1.9

PM10 concentration mg/Nm³ 170 68 155 62

PM10 emission rate g/s 14.2 5.7 3.0 1.2

PM2.5 concentration mg/Nm³ 75 30 50 20

PM2.5 emission rate g/s 6.3 2.5 1.0 0.4

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6. METEOROLOGY

The following sections describe the meteorology of the area around the Facility, focusing on parameters that are important for dispersion of air pollutants. The meteorological data that was generated by the coupled TAPM/CALMET approach is compared to observations in Appendix B.

6.1 Wind speed and wind direction

Wind speed and wind direction are important meteorological parameters that will influence the dispersion of air pollutants. Figure 4 illustrates the annual wind speed distribution during 2009 at the Facility, as predicted by CALMET. The predominant wind directions are northeast and southwest, with the strongest winds sea-breezes from the west.

The distribution of winds varies considerably throughout the year (Figure 5). During summer, winds are predominantly light and from the south-southeast to southwest. Through autumn and into winter winds are increasingly from the west and northeast, with a greater proportion of high wind speeds.

Figure 6 illustrates the diurnal distribution of winds. The most prominent feature is the south-westerly sea-breeze occurring in the afternoon (12 – 6pm). Winds are strongest during the day with the lightest winds occurring in the early morning (midnight – 6am).

Figure 4 Annual distribution of winds at the Facility (from CALMET)

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Figure 5 Seasonal distribution of winds at the Facility (from CALMET)

Figure 6 Diurnal distribution of winds at the Facility (from CALMET)

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6.2 Mixing height

The mixing height refers to the height above ground within which particulates or other pollutants released at or near ground can mix with ambient air. During stable atmospheric conditions, the mixing height is often quite low and particulate dispersion is limited to within this layer. During the day, solar radiation heats the air at the ground level and causes the mixing height to rise. The air above the mixing height during the day is generally cooler. The growth of the mixing height is dependent on how well the air can mix with the cooler upper level air and therefore depends on meteorological factors such as the intensity of solar radiation and wind speed. During strong wind speed conditions the air will be well mixed, resulting in a high mixing height.

Mixing height information extracted from CALMET at the Facility is presented in Figure 7. The data shows that mixing height is low overnight and begins to develop after 6am, as solar heating increases convection. The mixing height reaches a peak around 1 to 2 pm before dropping to an overnight minimum by approximately 8pm.

Figure 7 Box and whisker plot of mixing height at the Facility location (CALMET)

6.3 Stability Class

Atmospheric stability refers to the vertical movement of the atmosphere and is an important parameter in determining the dispersion and transport of air pollutants released within the boundary layer. Atmospheric stability is classified here under the Pasquill-Gifford scheme and ranges from Class A, which represents very unstable atmospheric conditions that typically occur on a sunny day, to Class F, which represents very stable atmospheric conditions that typically occur during light wind conditions at night.

Figure 8 presents the distribution of stability classes expected at the site, by hour of the day. Unstable conditions (Class A-C) are characterised by solar heating of the ground that induces turbulent mixing in the atmosphere close to the ground, which usually results in material from a plume reaching the ground closer to the source than it does

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for neutral conditions or stable conditions. This turbulent mixing is the main driver of dispersion during unstable conditions. Dispersion processes for neutral conditions (Class D), which are the most frequent at the site, are dominated by mechanical turbulence generated as the wind passes over irregularities in the local surface, such as terrain features and building structures. Overnight, the atmosphere is predicted to be characterised by D, E or F class stability classes, with cloud cover reducing solar heating and enhancing stability.

Figure 8 Distribution of stability class by hour at the Facility location (CALMET)

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7. RESULTS

This section presents the results of the dispersion modelling assessment of the Facility.

7.1 Normal operations

7.1.1 Isolation

Modelling was conducted of PM emissions from normal operations. Predicted ground-level concentrations of air

pollutants due to the Facility in isolation are presented the following contour plots: PM10 (Plate 1), PM2.5 (Plate 2 and Plate 3) and dust deposition rates (Plate 4).

The results show that:

• 24-hour average concentrations of PM10 due to the Facility in isolation are predicted to be less than the criterion of 50 µg/m³ at all residential areas.

• 24-hour average concentrations of PM2.5 due to the Facility in isolation are predicted to be less than the criterion of 25 µg/m³ across the modelling domain.

• Annual average concentrations of PM2.5 due to the Facility in isolation are predicted to be less than the criterion of 8 µg/m³ beyond the site boundary.

• Annual average dust deposition rates are predicted to be less than with the NSW Approved Methods criterion of 66 mg/m²/day at all residential areas.

7.1.2 Cumulative assessment

Predicted cumulative ground-level concentrations of air pollutants due to the Facility and background are presented

in the following contour plots: PM10 (Plate 5) and PM2.5 (Plate 6 and Plate 7).

The results show that:

• 24-hour average concentrations of PM10 are predicted to be more than the criterion of 50 µg/m³ within a limited area beyond the site boundary.

• 24-hour average concentrations of PM2.5 are predicted to be less than the criterion of 25 µg/m³ beyond the site boundary.

• Annual average concentrations of PM2.5 are predicted to be more than the criterion of 8 µg/m³ within a limited area beyond the site boundary. The background concentration of 7.3 µg/m³ is the major contributor

to concentrations of PM2.5.

7.1.3 Source contribution analysis

The 25 days with the highest predicted 24-hour average concentrations of PM10 at the Community Park and Le Fevre 1 monitoring station were analysed with respect to the relative contributions of all sources. The contributions are presented in Table 14 (Community Park) and Table 15 (Le Fevre 1). Contributions are presented in graphical form in Figure 9 and Figure 10, respectively. The results show:

• The major sources are wind erosion of stockpiles and exposed areas, vehicle movements and dust collectors.

• The cement kiln stacks do not make an important contribution to the highest concentrations

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• There is not a large variance in major contributing sources between the different days or across the two sites.

Table 14 Source contributions for the top 25 predicted 24-hour average concentrations of PM10 at the Community Park

Contribution 24-hr avg Exposed Stockpile Vehicles Rank conc. Handling - Handling - Areas - Dust Vehicles - Wind Stacks - Background (µg/m³) Transfers Stockpiles Wind Collectors - Paved Erosion Unpaved Erosion 1 43.8 0.2% 0.9% 14.3% 29.3% 1.6% 0.0% 11.0% 1.8% 41.0% 2 42.8 0.1% 0.5% 15.4% 28.4% 1.4% 0.1% 11.1% 1.0% 42.1% 3 39.5 0.1% 0.6% 13.6% 28.3% 1.2% 0.0% 9.4% 1.2% 45.6% 4 38.8 0.2% 1.0% 10.2% 25.6% 3.2% 0.6% 9.6% 3.2% 46.4% 5 38.3 0.1% 0.7% 11.0% 26.2% 2.5% 0.7% 9.9% 1.9% 47.0% 6 37.6 0.1% 0.7% 7.6% 20.2% 9.3% 0.0% 10.9% 3.2% 47.9% 7 37.4 0.2% 1.2% 10.3% 23.5% 3.4% 0.1% 11.2% 1.8% 48.2% 8 35.6 0.1% 0.5% 10.9% 23.2% 2.1% 2.4% 8.6% 1.7% 50.6% 9 35.6 0.1% 0.5% 10.4% 20.9% 4.0% 0.6% 9.9% 2.9% 50.6% 10 35.5 0.1% 0.5% 5.5% 19.0% 7.3% 0.0% 12.1% 4.8% 50.7% 11 35.2 0.1% 0.6% 10.1% 19.7% 5.8% 0.4% 10.6% 1.6% 51.2% 12 35.1 0.2% 0.8% 11.9% 23.0% 2.1% 0.0% 9.2% 1.4% 51.3% 13 34.8 0.2% 0.9% 12.1% 24.8% 1.3% 0.0% 7.9% 1.1% 51.8% 14 34.4 0.2% 1.0% 11.3% 24.4% 1.5% 0.0% 7.9% 1.4% 52.3% 15 34.4 0.1% 0.6% 10.6% 26.4% 2.8% 0.0% 6.0% 1.1% 52.4% 16 34.2 0.1% 0.7% 10.9% 23.9% 2.3% 0.0% 8.0% 1.6% 52.6% 17 34.0 0.1% 0.6% 12.2% 21.2% 1.5% 0.0% 10.5% 1.1% 52.9% 18 33.7 0.1% 0.6% 10.4% 21.3% 2.0% 1.1% 8.9% 2.3% 53.4% 19 33.6 0.1% 0.8% 8.4% 18.2% 5.7% 0.2% 10.7% 2.3% 53.5% 20 33.6 0.1% 0.5% 7.1% 18.0% 5.8% 0.1% 10.5% 4.4% 53.6% 21 33.5 0.1% 0.8% 8.7% 21.3% 5.1% 0.0% 8.2% 2.0% 53.7% 22 33.2 0.1% 0.8% 13.0% 19.0% 1.3% 0.0% 10.7% 0.9% 54.3% 23 33.1 0.2% 1.2% 10.6% 21.7% 1.0% 0.7% 8.1% 2.0% 54.3% 24 32.9 0.1% 0.6% 10.1% 19.0% 3.4% 0.2% 10.0% 1.9% 54.8% 25 32.7 0.1% 0.5% 6.8% 19.8% 4.7% 0.1% 9.3% 3.7% 55.0%

Table 15 Source contributions for the top 25 predicted 24-hour average concentrations of PM10 at the Le Fevre 1 monitoring site

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Figure 9 Source contributions for the top 25 predicted 24-hour average concentrations of PM10 at the Community Park

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Figure 10 Source contributions for the top 25 predicted 24-hour average concentrations of PM10 at the Le Fevre 1 monitoring site

The 25 days with the highest predicted 24-hour average concentrations of PM2.5 at the Community Park and Le Fevre 1 monitoring station were analysed with respect to the relative contributions of all sources. The contributions are presented in Table 16 (Community Park) and Table 17 (Le Fevre 1). Contributions are presented in graphical form in Figure 11 and Figure 12, respectively. The results show that for PM2.5 relative to PM10:

• Dust collectors are a more important source.

• The ambient background has a large contribution.

Table 16 Source contributions for the top 25 predicted 24-hour average concentrations of PM2.5 at the Community Park

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Table 17 Source contributions for the top 25 predicted 24-hour average concentrations of PM2.5 at the Le Fevre 1 monitoring site

Contribution 24-hr avg Exposed Stockpile Vehicles Rank conc. Handling - Handling - Areas - Dust Vehicles - Wind Stacks - Background (µg/m³) Transfers Stockpiles Wind Collectors - Paved Erosion Unpaved Erosion 1 11.4 0.1% 0.3% 3.6% 6.0% 19.3% 0.3% 5.9% 0.6% 63.9% 2 10.5 0.0% 0.2% 4.2% 7.2% 12.5% 0.1% 5.6% 0.5% 69.6% 3 10.4 0.0% 0.2% 2.5% 5.2% 15.8% 0.2% 5.0% 0.8% 70.3% 4 10.3 0.0% 0.2% 1.7% 3.0% 19.8% 0.3% 3.8% 0.4% 70.7% 5 9.8 0.0% 0.2% 3.2% 6.6% 10.4% 0.6% 3.9% 0.6% 74.3% 6 9.7 0.0% 0.2% 4.5% 9.0% 5.0% 0.7% 4.9% 0.5% 75.2% 7 9.6 0.0% 0.2% 2.4% 4.0% 13.4% 0.5% 3.4% 0.2% 75.8% 8 9.6 0.0% 0.1% 2.0% 5.2% 12.1% 1.4% 2.6% 0.7% 75.8% 9 9.6 0.1% 0.2% 2.1% 3.9% 13.5% 0.7% 3.1% 0.4% 76.0% 10 9.6 0.0% 0.3% 4.3% 8.0% 5.4% 0.3% 5.1% 0.5% 76.0% 11 9.5 0.0% 0.1% 2.0% 3.8% 9.4% 3.5% 3.4% 0.6% 77.1% 12 9.4 0.1% 0.3% 4.1% 7.2% 5.8% 0.0% 4.9% 0.3% 77.3% 13 9.4 0.0% 0.2% 4.2% 7.4% 6.0% 0.1% 4.2% 0.3% 77.6% 14 9.3 0.0% 0.2% 2.3% 4.2% 10.7% 0.7% 3.4% 0.3% 78.1% 15 9.3 0.0% 0.1% 1.2% 3.0% 12.6% 1.9% 2.4% 0.6% 78.2% 16 9.3 0.0% 0.2% 1.9% 4.0% 11.1% 1.1% 2.7% 0.4% 78.6% 17 9.3 0.0% 0.2% 2.4% 4.6% 7.8% 1.7% 4.1% 0.5% 78.8% 18 9.2 0.1% 0.2% 3.4% 5.9% 7.1% 0.0% 3.9% 0.3% 79.0% 19 9.2 0.0% 0.2% 2.4% 5.1% 8.1% 0.5% 3.9% 0.6% 79.2% 20 9.2 0.0% 0.2% 2.5% 5.1% 8.7% 0.2% 3.6% 0.6% 79.2% 21 9.1 0.0% 0.1% 1.7% 4.4% 9.5% 0.9% 2.6% 0.7% 80.0% 22 9.1 0.0% 0.0% 0.6% 1.7% 14.9% 0.4% 1.6% 0.4% 80.4% 23 9.0 0.0% 0.1% 1.0% 2.1% 13.3% 0.3% 2.0% 0.5% 80.7% 24 9.0 0.0% 0.2% 3.4% 6.3% 4.7% 0.6% 3.5% 0.2% 81.1% 25 9.0 0.0% 0.1% 2.7% 5.4% 5.4% 0.6% 3.8% 0.6% 81.3%

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Figure 11 Source contributions for the top 25 predicted 24-hour average concentrations of PM2.5 at the Community Park

Figure 12 Source contributions for the top 25 predicted 24-hour average concentrations of PM2.5 at the Le Fevre 1 monitoring site

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7.1.4 Detailed stack emissions

Ground-level concentrations of all pollutants emitted from the stacks were predicted at all points across the modelling domain lying outside of the Facility boundary (offsite). The maximum predicted offsite ground-level concentrations of all pollutants emitted from the stacks are presented in Table 18 for the Facility in isolation. The results show:

• All pollutants are less than their respective criteria.

• The maximum offsite 1-hour average concentration of nitrogen dioxide is predicted to be 168 µg/m³, which is 67% of the criterion of 250 µg/m³.

• All other pollutants are predicted to be less than 14% of their respective criteria.

The maximum predicted offsite ground-level concentrations of NO2, CO and SO2 emitted from the stacks are presented in Table 19 for the Facility including ambient background concentrations. The results show that all pollutants are less than their respective criteria including background concentrations.

Table 18 Predicted maximum offsite ground-level concentrations of all pollutants from stacks in isolation

Averaging Criteria Maximum offsite Proportion of Pollutant period (µg/m³) (µg/m³) criteria (%) 1 hour 250 168 67.3% Nitrogen dioxide 12 months 60 1.2 2.0% 1 hour 31,240 556 1.8% Carbon monoxide 8 hours 11,250 107 0.9% 1 hour 570 28.6 5.0% Sulfur dioxide 24 hours 230 2.5 1.1% 12 months 60 0.12 0.2% Hydrogen chloride 3 minutes 270 18 6.7% Chlorine 3 minutes 110 10 9.3% 24 hours 3 0.07 2.2% Fluoride 7 days 2 0.01 0.3% 90 days 1 0.003 0.3% Benzene 3 minutes 58 0.59 1.0% Chromium (III) compounds 3 minutes 19 0.02 0.1% Chromium VI compounds 3 minutes 0.19 0.003 1.6% Benzo(a)pyrene as a marker for 3 minutes 0.8 0.0001 0.0% polycyclic aromatic hydrocarbons Antimony and compounds 3 minutes 19 0.001 0.0% Arsenic and compounds 3 minutes 0.19 0.001 0.6% Barium 3 minutes 19 0.02 0.1% Beryllium and beryllium compounds 3 minutes 0.008 0.001 13.6% Cadmium and cadmium compounds 3 minutes 0.036 0.001 4.1% Copper fume 3 minutes 7.3 0.10 1.3% Iron oxide fume 3 minutes 190 1.9 1.0%

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Averaging Criteria Maximum offsite Proportion of Pollutant period (µg/m³) (µg/m³) criteria (%) Lead 12 months 0.5 0.0001 0.0% Magnesium oxide fume 3 minutes 360 9.7 2.7% Manganese and compounds 3 minutes 36 0.05 0.1% Mercury - inorganic 3 minutes 4 0.001 0.0% Mercury - organic 3 minutes 0.36 0.01 3.6% Nickel and nickel compounds 3 minutes 0.36 0.02 6.1% Zinc oxide fume 3 minutes 190 0.22 0.1% Dioxins and furans 1-hour 0.0000037 8.3E-08 2.2%

Table 19 Predicted maximum offsite ground-level concentrations of all pollutants from stacks including background

Averaging Criteria Maximum offsite Proportion of Pollutant period (µg/m³) (µg/m³) criteria (%) 1 hour 250 179 71.6% Nitrogen dioxide 12 months 60 12 20.0% 1 hour 31,240 801 2.6% Carbon monoxide 8 hours 11,250 352 3.1% 1 hour 570 29 5.2% Sulfur dioxide 24 hours 230 3.4 1.5% 12 months 60 1.0 1.7%

7.2 Particulate Emissions due to Process Variations

Two scenarios with higher particulate emissions from the kiln (stack 4A) and calciner (stack 4B) representative of process variations have been modelled, over an entire year at 250 mg/Nm³ and 100 mg/Nm³.

A comparison of the two scenarios to the normal operations is presented in Plate 8 and Plate 9, which shows the predicted ground-level concentrations of PM10 and PM2.5, respectively, due to the Facility including an ambient background. The results show that the potential emissions related to process variations do not have a significant impact on the ground-level concentrations in residential areas.

The maximum monthly average dust deposition rates due to the two scenarios are shown in Plate 10. The figure shows that under the conservative and unrealistic assumption of continuous elevated emissions, the dust deposition rate is likely to be very low. The highest dust deposition rates are predicted to occur to the north and east.

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8. CONCLUSIONS

Katestone was commissioned by ABC to complete an Air Quality Assessment of the Facility. The Facility’s licence is due for renewal in October 2017. This report fulfils a requirement of the EPA that ABC conducts an air quality assessment of the Facility as part of the licence renewal process. The air quality assessment has been conducted in accordance with the EPA’s guidance for air quality assessments.

Modelling of emissions of particulate matter from normal operations was conducted. The results show that:

• 24-hour average concentrations of PM10 are predicted to be more than 50 µg/m³ within a limited area beyond the site boundary.

• 24-hour average concentrations of PM2.5 are predicted to be less than 25 µg/m³ beyond the site boundary.

concentrations of PM2.5.

• Annual average dust deposition rates are predicted to be less than the NSW Approved Methods criterion of 66 mg/m²/day at all residential areas.

Modelling of emissions of other air pollutants from the stacks was conducted. The results show:

• All pollutants are less than with their respective criteria.

• The maximum offsite 1-hour average concentration of nitrogen dioxide is predicted to be 168 µg/m³, which is 67% of the criterion of 250 µg/m³.

• All other pollutants are predicted to be less than 14% of their respective criteria.

• All pollutants are less than their respective criteria including background concentrations.

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9. REFERENCES

Air EPP, 2016, Environment Protection (Air Quality) Policy, South Australia.

AirLabs, 2013. “Air Emissions Monitoring of the Slag Dryer Stack at Adelaide Brighton Cement Ltd in Birkenhead”. Test report no. JUN13103B.1. 18 October, 2013.

AirLabs, 2015. “Air Emissions Monitoring of Release Points 4A & 4B at Adelaide Brighton Cement Ltd in Birkenhead – Increase Plastics in Wood Trial”. Test report no. OCT14181.3. 30 January, 2015.

AirLabs, 2016A. “Air Emissions Monitoring of Release Points 4A & 4B at Adelaide Brighton Cement Ltd in Birkenhead”. Test report no. OCT15201.1. 12 January, 2016.

AirLabs, 2016B. “Air Emissions Monitoring of Release Points 4A & 4B at Adelaide Brighton Cement Ltd in Birkenhead”. Test report no. Jun16100.2. 7 November, 2016.

AirLabs, 2017. “Air Emissions Monitoring of Cement Mills 1, 6 & 7, and Dust Collectors 23, 38, 41 & 2CR3CS4 at Brighton Cement Ltd in Birkenhead”. Test Report no. MAY17107.3. 9 June, 2017.

Bofinger N.D, Best P.R, Cliff D.I, & Stumer L.J, 1986, The oxidation of nitric oxide to nitrogen dioxide in power station plumes, Proceedings of the Seventh World Clean Air Congress, Sydney, 384-392

Environ, 2001. “Enhanced Meteorological Modeling and Performance Evaluation for Two Texas Ozone Episodes”, prepared for the Texas Natural Resource Conservation Commission, prepared by ENVIRON International Corporation, Novato, CA.

National Pollutant Inventory, 2008. "Emission Estimation Technique Manual for Cement manufacturing v2.1". Department of Sustainability, Environment, Water, Population and Communities.

National Pollutant Inventory, 2008. "Emission Estimation Technique Manual for Combustion Engines v3.0". Department of Sustainability, Environment, Water, Population and Communities.

National Pollutant Inventory, 2012. "Emission Estimation Technique Manual for Mining v3.1". Department of Sustainability, Environment, Water, Population and Communities.

SEPP, 2001, State Environment Protection Policy (Air Quality Management) Environment Protection Act 1970. Victoria Government Gazette, Special No. S 240 Friday 21 December 2001. Victorian Government Printer.

United States Environmental Protection Agency, 2011. Paved roads, AP-42 Chapter 13.2.1, USEPA Office of Air Quality Planning and Standards.

United States Environmental Protection Agency, 2006a. Chapter 13.2.4 “Aggregate Handling and Storage Piles”, AP-42, USEPA Office of Air Quality Planning and Standards.

United States Environmental Protection Agency, 2006b. Chapter 13.2.5 “Industrial Wind Erosion”, AP-42, USEPA Office of Air Quality Planning and Standards.

United States Environmental Protection Agency, 2006c. Unpaved roads, AP-42 Chapter 13.2.2, USEPA Office of Air Quality Planning and Standards.

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Plate 1 Predicted maximum 24-hour average ground-level concentrations of PM10 due to normal operations of the Facility in isolation

Location: Averaging period: Data source: Units: Birkenhead, SA 24-hour CALPUFF µg/m³

Type: Criterion: Prepared by: Date: Maximum contours 50 µg/m³ M Burchill July 2017

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Plate 2 Predicted maximum 24-hour average ground-level concentrations of PM2.5 due to normal operations of the Facility in isolation

Location: Averaging period: Data source: Units: Birkenhead, SA 24-hour CALPUFF µg/m³

Type: Criterion: Prepared by: Date: Maximum contours 25 µg/m³ M Burchill July 2017

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Plate 3 Predicted annual average ground-level concentrations of PM2.5 due to normal operations of the Facility in isolation

Location: Averaging period: Data source: Units: Birkenhead, SA Annual CALPUFF µg/m³

Type: Criterion: Prepared by: Date: Average contours 8 µg/m³ M Burchill July 2017

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Plate 4 Predicted annual average dust deposition rate due to normal operations of the Facility in isolation

Location: Averaging period: Data source: Units: Birkenhead, SA Annual CALPUFF mg/m²/day

Type: Objective: Prepared by: Date: Average contours 66 µg/m³ M Burchill July 2017

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Plate 5 Predicted maximum 24-hour average ground-level concentrations of PM10 due to normal operations of the Facility including an ambient background of 18 µg/m³

Location: Averaging period: Data source: Units: Birkenhead, SA 24-hour CALPUFF µg/m³

Type: Criterion: Prepared by: Date: Maximum contours 50 µg/m³ M Burchill July 2017

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Plate 6 Predicted maximum 24-hour average ground-level concentrations of PM2.5 due to normal operations of the Facility including an ambient background of 7.3 µg/m³

Location: Averaging period: Data source: Units: Birkenhead, SA 24-hour CALPUFF µg/m³

Type: Criterion: Prepared by: Date: Maximum contours 25 µg/m³ M Burchill July 2017

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Plate 7 Predicted annual average ground-level concentrations of PM2.5 due to normal operations of the Facility including an ambient background of 7.3 µg/m³

Location: Averaging period: Data source: Units: Birkenhead, SA Annual CALPUFF µg/m³

Type: Criterion: Prepared by: Date: Average contours 8 µg/m³ M Burchill July 2017

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Location: Averaging period: Data source: Units: Birkenhead, SA 24-hours CALPUFF µg/m³

Type: Criterion: Prepared by: Date: Maximum contours 50 µg/m³ M Burchill July 2017

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Location: Averaging period: Data source: Units: Birkenhead, SA 24-hours CALPUFF µg/m³

Type: Criterion: Prepared by: Date: Maximum contours 25 µg/m³ M Burchill July 2017

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Plate 10 Predicted maximum monthly average dust deposition rate due under two process variation scenarios in isolation

Location: Averaging period: Data source: Units: Birkenhead, SA 720-hours CALPUFF mg/m²/day

Type: Objective: Prepared by: Date: Maximum contours NA M Burchill July 2017

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APPENDIX A AMBIENT MONITORING

A1 INTRODUCTION

Ambient air quality monitoring onsite and in the surrounding region is conducted by ABC and EPA. The location of monitors is shown in Figure A1. The purpose of the ABC monitoring network is to monitor air quality and identify sources of dust and opportunities for improvement. The EPA conducts monitoring to evaluate compliance with air quality standards. It therefore uses equipment that meets the rigorous requirements of the relevant Australian Standards. These monitors respond more slowly to short-term changes in dust levels, but provide a reliable determination of 24-hour and annual averages. The EPA monitoring equipment provides data that are more representative of typical levels experienced in the community away from the Facility and, therefore, are appropriate for use in determining a background.

The following sections describe the monitoring data collected within the region.

Figure A1 ABC and EPA monitoring sites

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A2 EPA MONITORING

A2.1 Le Fevre 1 – PM10 and PM2.5

A2.1.1 Summary

Le Fevre 1 is located in the grounds of the Lefevre Peninsula Primary School, 600 m from the southwest corner of the Facility. Le Fevre 1 is the closest compliance monitor to the Facility. The monitoring station measures the following:

• PM10 (TEOM until Dec 2015, BAM from Feb 2016)

• PM2.5 (BAM from Feb 2016)

• Meteorological parameters.

Timeseries of 24-hour average concentrations of PM10 and PM2.5 measured at Le Fevre 1 from January 2013 to January 2017 are presented in Figure A2 and Figure A3, respectively. A table of summary statistics of the data is presented in Table A1.

Table A1 Summary statistics of PM10 and PM2.5 concentrations – Le Fevre 1

PM10 PM2.5 Parameter 1-hour 24-hour 1-hour 24-hour Data capture 93.8% 94.0% 98.7% 98.8% Minimum -4.3 3.0 -4.0 0.3 10th %ile 7.6 10.4 3.0 4.9 Mean 19.9 19.9 7.5 7.5 Median 16.5 18.3 7.0 7.1 70th %ile 22.0 22.8 9.0 8.4 90th %ile 34.9 30.5 12.0 10.4 95th %ile 45.0 35.6 15.0 11.7 99th %ile 74.5 46.0 23.0 15.4 Maximum 366.7 85.4 167.0 19.4

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Figure A2 24-hour average concentrations of PM10 measured at Le Fevre 1. The 24-hour average criterion of 50 µg/m³ is shown as a dashed line.

Figure A3 24-hour average concentrations of PM2.5 measured at Le Fevre 1. The 24-hour average criterion of 25 µg/m³ is shown as a dashed line.

Le Fevre 1 may potentially be influenced by the Facility when the wind direction is between 20° and 80° (see Figure A4). To avoid double counting and as per Katestone’s discussion with the EPA on 8 March 2017, background concentrations of PM10 and PM2.5 have been estimated based on the average concentration measured at Le Fevre 1 when winds are not from the direction of the Facility.

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Figure A4 Map of ABC Facility showing Le Fevre 1 monitor and wind directions

Summary statistics showing the difference between concentrations when winds are from the Facility and other winds are shown in Table A2.

Table A2 Summary statistics of PM10 and PM2.5 concentrations – Le Fevre 1 – winds from ABC

PM10 – 1 hour PM2.5 – 1 hour Parameter From ABC Other Directions From ABC Other Directions Minimum -1.1 -3.6 -4.0 -4.0 10th %ile 10.5 7.2 4.0 3.0 Mean 25.6 18.0 8.8 7.3 Median 21.0 15.9 8.0 7.0 70th %ile 29.0 20.8 10.0 8.0 90th %ile 46.0 30.0 15.0 12.0 95th %ile 57.0 37.0 19.0 14.0 99th %ile 85.2 59.1 26.4 22.0 Maximum 176.0 300.0 40.0 45.0

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A2.1.2 Detailed Analysis

A more detailed analysis of concentrations of PM10 and PM2.5 measured at the Le Fevre 1 monitor is provided below.

The distribution of concentrations with wind speed and wind direction is presented in Figure A5, which indicates that:

• Elevated concentrations from the direction of the Facility occur at all wind speeds with the highest concentrations occurring with moderate to strong winds.

• Moderate to strong winds from the west to northwest also lead to elevated concentrations.

Figure A5 Pollution rose showing the average PM10 concentration as a function of wind speed (m/s) and wind direction (°)

An analysis of the monitoring data by time of day, day of week and month is shown in Figure A6. The analysis indicates that:

• There is a strong peak evident during weekdays between 7 am and 9 am that can be attributed to traffic.

• On average, summer months have higher concentrations while the winter months showed the lowest.

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Figure A6 Analysis of Le Fevre 1 monitoring data by time period

A2.1.3 Exceedance analysis

Le Fevre 1 monitoring station recorded seven exceedances of the 24-hour average criterion for PM10 of 50µg/m³ between January 2013 and January 2017. Each exceedance day is examined in detail in the following sections.

A2.1.3.1 26 March 2013

The 24-hour average concentrations of PM10 recorded at the EPA sites on 26 March 2013 are presented in Table

A3. A timeseries of 1-hour average concentrations of PM10 at each site for 26 March 2013 is presented in Figure A7. The data indicates that:

• Le Fevre 1 was the only site with data that recorded elevated levels.

• Monitoring shows peak concentration of PM10 in the morning, consistent with peak hour traffic, a second, more significant peak occurred in late evening (around 9pm).

Meteorological data from Le Fevre 1 was not available for this period.

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Table A3 24-hour average concentrations of PM10 recorded at EPA monitoring sites during 26 March 2013

Site 24-hour average PM10 (µg/m³) CBD No Data Elizabeth 23.8 Kensington Gardens 21.9 Le Fevre 1 62.6 Le Fevre 2 No Data Netley 26.9

Figure A7 1-hour average concentrations of PM10 at EPA monitoring data at Adelaide monitors during March 26 2013

A2.1.3.2 30 September 2013

The 24-hour average concentrations of PM10 recorded at the EPA sites on 30 September 2013 are presented in Table A4. A timeseries at each site for 30 September 2013 is presented in Figure A8. The data indicates that:

• All sites recorded elevated levels

• Timeseries show similar patterns of early morning high levels.

Meteorological data from Le Fevre 1 was not available for this period.

Table A4 24-hour average PM10 concentrations recorded at EPA monitoring sites during 30 September 2013

Site 24-hour average PM10 (µg/m³) CBD No Data Elizabeth 76.2 Kensington Gardens 66.5 Le Fevre 1 69.7 Le Fevre 2 82.3

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Netley 64.5

Figure A8 1-hour average PM10 concentrations at EPA monitoring data at Adelaide monitors during 30 September 2013

A2.1.3.3 30 January 2014

The 24-hour average concentrations of PM10 recorded at EPA sites on 30 January 2014 is presented in Table A5. A timeseries at each site for 30 January 2014 is presented in Figure A9. The data indicates that:

• Elevated levels were measured at both Le Fevre 1 and Le Fevre 2, although the criterion was exceeded at Le Fevre 1 only.

• The observed elevated levels at Le Fevre 1 were consistent with morning peak hour traffic.

Meteorological data from Le Fevre 1 was not available for this period.

Table A5 24-hour average PM10 concentrations recorded at EPA monitoring sites during 30 January 2014

Site 24-hour average PM10 (µg/m³) CBD No Data Elizabeth 33.0 Kensington Gardens 27.7 Le Fevre 1 69.1 Le Fevre 2 45.8 Netley 33.6

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Figure A9 1-hour average PM10 concentrations at EPA monitoring data at Adelaide monitors during 30 January 2014

A2.1.3.4 11 February 2014

The 24-hour average concentration of PM10 recorded at EPA sites on 11 February 2014 are presented in Table A6. A timeseries at each site for 11 February 2014 is presented in Figure A10. The data indicates that:

• Exceedances were observed at Le Fevre 1 and Netley.

• Elevated levels were also observed at Le Fevre 2, but did not exceed the criterion.

Meteorological data from Le Fevre 1 was not available for this period.

Table A6 24-hour average PM10 concentrations recorded at EPA monitoring sites during 11 February 2014

Site 24-hour average PM10 (µg/m³) CBD No Data Elizabeth 23.2 Kensington Gardens 25.7 Le Fevre 1 50.4 Le Fevre 2 46.4 Netley 56.9

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Figure A10 1-hour average PM10 concentrations at EPA monitoring data at Adelaide monitors during 11 February 2014

A2.1.3.5 12 February 2014

The 24-hour average concentrations of PM10 recorded at EPA sites on 12 February 2014 are presented in Table A7. A timeseries at each site for 12 February 2014 is presented in Figure A11. The data indicates that:

• Exceedances were recorded at Le Fevre 1 and Le Fevre 2, and concentrations at Kensington Gardens and Netley were 2% and 6% below the criterion.

• The diurnal profile of concentrations of PM10 are not consistent at the sites.

Meteorological data from Le Fevre 1 was not available for this period.

Table A7 24-hour average PM10 concentrations recorded at EPA monitoring sites during 12 February 2014

Site 24-hour average PM10 (µg/m³) CBD No Data Elizabeth 35.6 Kensington Gardens 49.2 Le Fevre 1 83.2 Le Fevre 2 61.4 Netley 47.1

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Figure A11 1-hour average PM10 concentrations at EPA monitoring data at Adelaide monitors during 12 February 2014

A2.1.3.6 4 May 2015

The 24-hour average concentration of PM10 recorded at EPA sites on 4 May 2015 are presented in Table A8. A timeseries at each site for 4 May 2015 is presented in Figure A12 and a pollution rose of concentrations at Le Fevre 1 is presented in Figure A13. The data indicates that:

• All sites recorded elevated concentrations, with 5 out of 6 sites recording an exceedance.

• The time series indicate that concentrations were elevated during the afternoon and into the evening at all sites, indicating a regional influence affecting all monitors.

• The pollution rose shows that winds from the north-northwest carried elevated concentrations to Le Fevre 1.

Table A8 24-hour average PM10 concentrations recorded at EPA monitoring sites during 4 May 2015

Site 24-hour average PM10 (µg/m³) CBD 68.2 Elizabeth 45.8 Kensington Gardens 61.2 Le Fevre 1 85.4 Le Fevre 2 114.2 Netley 95.7

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Figure A12 1-hour average PM10 concentrations at EPA monitoring data at Adelaide monitors during 4 May 2015

Figure A13 Pollution rose showing percentage contribution to 24-hour average PM10 concentration by wind speed and wind direction

A2.1.3.7 27 April 2016

The 24-hour average concentrations of PM10 recorded at EPA sites on 27 April 2016 are presented in Table A9. A timeseries at each site for 27 April 2016 is presented in Figure A14 and a pollution rose of concentrations at Le Fevre 1 is presented in Figure A15. The data indicates that:

• All sites recorded elevated concentrations, with all 5 sites with data recording an exceedance.

• The time series indicate that concentrations were elevated during the afternoon and into the evening at all sites, indicating a regional influence affecting all monitors.

• The pollution rose shows that winds from the north-northwest and northeast contributed the most to the 24-hour average at Le Fevre 1.

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Table A9 24-hour average PM10 concentrations recorded at EPA monitoring sites during 27 April 2016

Site 24-hour average PM10 (µg/m³) CBD 53.9 Elizabeth 138.3 Kensington Gardens 90.2 Le Fevre 1 58.6 Le Fevre 2 80.6 Netley No Data

Figure A14 1-hour average PM10 concentrations at EPA monitoring data at Adelaide monitors during 27 April 2016

Figure A15 Pollution rose showing percentage contribution to 24-hour average PM10 concentration by wind speed and wind direction

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A2.2 Le Fevre 2 – NO2 and SO2

Le Fevre 2 is located 4 km to the north of the Facility. The monitoring station measures NO2, SO2, PM10, PM2.5 and ozone. Timeseries of NO2 and SO2 measured at Le Fevre 2 from January 2013 to January 2017 are presented in Figure A16 and Figure A17, respectively. A table of summary statistics of the data collected is presented in Table A10. The data indicates that:

• Concentrations of NO2 and SO2 are well below the relevant criteria throughout the monitoring period.

• The average concentration of NO2 is 10.8 µg/m³, which has been adopted as background for the assessment.

• The average concentration of SO2 is 0.9 µg/m³, which has been adopted as background for the assessment.

Table A10 Summary statistics of concentrations of NO2 and SO2 – Le Fevre 2

Parameter NO2 SO2 Minimum 0.0 0.0 10th %ile 1.0 0.0 Mean 10.8 0.9 Median 6.2 0.0 70th %ile 12.7 0.0 90th %ile 26.7 2.9 95th %ile 34.9 4.8 99th %ile 49.2 12.9 Maximum 76.6 97.2

Figure A16 1-hour average concentrations of NO2 measured at Le Fevre 2. The 1-hour average criterion of 250 µg/m³ is shown as a dashed line.

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Figure A17 1-hour average concentrations of SO2 measured at Le Fevre 2. The 1-hour average criterion of 570 µg/m³ is shown as a dashed line.

A2.3 CBD - CO

CBD is located 13 km to the southeast of the Facility and is the closest monitor that measures CO. A timeseries of CO measured at CBD from January 2013 to January 2017 is presented in Figure A18. A table of summary statistics of the data collected is presented in Table A11. The data indicates that:

• Concentrations of CO are well below the relevant criteria throughout the monitoring period.

• The average concentration of CO is 244.9 µg/m³, which has been adopted as background for this assessment.

Table A11 Summary statistics of concentrations of CO – CBD

CO Parameter 1-hour Minimum 0.0 10th %ile 74.9 Mean 244.9 Median 199.8 70th %ile 283.1 90th %ile 472.5 95th %ile 599.5 99th %ile 932.6 Maximum 2,797.8

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Figure A18 1-hour average concentrations of CO measured at CBD. The 1-hour average criterion of 31,240 µg/m³ is shown as a dashed line.

A3 ABC MONITORING

A3.1 Summary

ABC monitors particulate matter at four locations within the grounds of the Facility (onsite monitors: Block 9, Northern grounds, Eastern grounds and southern grounds) and two locations within the community (offsite monitors: Community Park and Gunn St). The purpose of the monitoring network is to identify sources of dust and opportunities for improvement.

A timeseries of 24-hr average PM10 concentrations measured between January 2015 and January 2017 are presented in Figure A19. Summary statistics are shown in Table A12.

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Figure A19 Time series of 24-hour average PM10 concentrations measured by ABC monitoring stations

Table A12 Summary statistics of 24-hour average PM10 concentrations, onsite monitoring

Parameter Block 9 North Grounds East Grounds South Grounds Data capture 82.8% 83.9% 86.9% 84.5% Minimum 1.5 2.3 0.2 -1.1 10th %ile 9.6 4.9 4.4 1.7 Mean 21.6 9.8 10.8 8.3 Median 21.5 8.8 9.6 7.6 70th %ile 26.7 11.0 12.4 10.1 90th %ile 32.8 16.2 17.3 14.8 95th %ile 36.0 19.7 21.4 18.1 99th %ile 46.7 26.5 32.9 27.7 Maximum 110.0 45.9 93.0 38.2

Table A13 Summary statistics of 24-hour average PM10 concentrations, offsite monitoring

Parameter Community Park Gunn Street Data capture 791 791 Minimum 73.8% 66.1% 10th %ile -3.7 -0.5 Mean 3.7 3.5 Median 12.5 8.2 70th %ile 12.1 7.0

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Parameter Community Park Gunn Street 90th %ile 15.5 8.9 95th %ile 22.0 14.2 99th %ile 24.6 17.6 Maximum 30.8 25.9

A3.2 Analysis

Analysis by wind direction is presented in Figure A20. All pollution roses use 10-minute average wind speed and wind direction from Le Fevre 1. The data indicates:

• Higher concentrations from the direction of the Facility are generally observed.

• Sources in other directions are also evident, most notably to the northwest.

• The Block 9 monitor shows significantly higher concentrations consistent with its location close to stockpiles and exposed areas. The Block 9 data also indicates sources to the northwest and southeast where are not related to the Facility.

• Community Park indicates higher concentrations from sources to the east, which include the Facility and Victoria Road.

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Figure A20 Pollution roses showing the distribution of average PM10 concentration by wind speed and wind direction at each of the ABC monitoring sites

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Data analysed according to time of day, day of week and month are presented in Figure A21. The data indicates the following:

• The morning traffic peak is evident at all sites.

• Block 9 is significantly higher than other monitors, consistent with its location close to stockpiles and exposed areas.

• Most monitors (Community park, Gunn Street, Northern grounds and Southern grounds) show a minimum during the afternoon and elevated levels during the late evening.

Figure A21 Analysis of ABC monitoring data by time period

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APPENDIX B METEOROLOGICAL AND DISPERSION MODELLING METHODOLOGY

B1 METEOROLOGY

B1.1 TAPM meteorology

The prognostic model TAPM (The Air Pollution Model) v4.0.5, developed by CSIRO, was used to generate a three- dimensional wind field for input into CALMET. TAPM has been validated by CSIRO, Katestone and others for many locations in Australia, southeast Asia and North America. TAPM is a regulatory model recognised by EPA in its guidance document Ambient air quality assessment.

TAPM was configured as follows:

• 40 x 40 grid point domain with an outer grid of 30 km and nesting grids of 10 km, 3 km and 1 km

• 365 days modelled (1 January 2009 to 31 December 2009)

• Grid centred approximately 5 km east of the Facility at latitude 34°50’S, longitude 138°34’

• Geoscience Australia 9-second digital elevation model terrain data

• Observations from the following BoM AWS sites were assimilated into the model:

o Adelaide (Kent Town) 023090

o Adelaide Airport 023034

o Edinburgh RAAF 023083

o Mount Lofty 023842

o Parafield Airport 023013

• The landuse of the inner-most (1 km) grid was edited based on aerial imagery.

B1.2 CALMET meteorological modelling

CALMET is an advanced non-steady-state diagnostic 3D meteorological model with micro-meteorological modules for overwater and overland boundary layers. The model is the meteorological pre-processor for the CALPUFF modelling system. CALMET can read hourly meteorological data as data assimilation from multiple sites within the modelling domain; it can also be initialised with the gridded three-dimensional prognostic output from other meteorological models such as TAPM. This can improve dispersion model output, particularly over complex terrain as the near surface meteorological conditions are calculated for each grid point.

CALMET (version 6.5.0) was used to simulate meteorological conditions in the region. The CALMET simulation was initialised with the gridded TAPM 3D wind field data from the 1 km grid. CALMET treats the prognostic model output as the initial guess field for the CALMET diagnostic model wind fields. The initial guess field is then adjusted for the kinematic effects of terrain, slope flows, blocking effects and 3D divergence minimisation.

CALMET was set up with twelve vertical levels with cell boundaries at 0, 20, 60, 100, 150, 200, 250, 350, 500, 800, 1600, 2600, 4600 metres at each grid point.

All default options and factors were selected except where noted below.

Key features of CALMET used to generate the wind fields are as follows:

• 120 x 120 grid point domain with a 200 m spacing

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• Southwest coordinate of 264,000mE 6,127,600mS (WGS84 Zone 54)

• Terrain data from the Shuttle Radar Topography Mission (SRTM) 3-second dataset

• 365 days modelled (1 January 2009 to 31 December 2009)

• NOOBS = 2 (No surface, overwater, or upper air observations. Use MM4/MM5/3D for surface, overwater, and upper air data) - TAPM output used as 3D initial guess field

• Gridded cloud cover from prognostic humidity at all levels

• Step 1 wind field options include Froude number adjustment to critical Froude number of 1 and slope flows, divergence minimisation

• Terrain radius of influence (TERRAD) set as 4 km.

B1.3 Comparison of CALMET output with observational data

The meteorological data generated by CALMET was compared to data measured at EPA’s Le Fevre 1 site during 2009. Wind speed, wind direction and temperature were included in the analysis. Table B1 presents the key statistical comparisons of the modelled and observed data and compares to the benchmarks in Environ (2001). The statistics show that the model meets the targets and does an acceptable job overall.

Table B1 Statistical analysis of CALMET output at the LeFevre 1 EPA monitor

Parameter Statistic Value Target Root Mean Square Error 1.12 m/s <= 2 m/s Wind speed Bias -0.54 m/s <= ± 0.5 m/s Index of Agreement 0.70 >= 0.6 Gross Error 23.4° <= 30° Wind direction Bias -0.72° <=±10° Gross Error 1.62°K <=2°K Temperature Bias -0.76°K <=±0.5°K Index of Agreement 0.83 >=0.8

The modelled and observed distributions of wind speed and wind direction are examined in more detail in Figure B1 (annual wind roses), Figure B2 (seasonal wind roses) and Figure B3 (diurnal wind roses). The figures demonstrate that the CALMET model has performed very well and has captured the key features of the wind fields in the area such as:

• The predominant wind directions are southwest and northeast

• The strongest winds are from the west and southwest

• Winds from the south-southeast to southwest during summer

• Strong winds from the west and lighter north-easterlies during winter

• Strong sea-breezes in the afternoon and lightest winds during the early morning (midnight – 6am).

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Figure B1 Annual wind roses at the Le Fevre 1 monitor (observed and modelled by CALMET)

Figure B2 Seasonal wind roses at the Le Fevre 1 monitor (observed and modelled by CALMET)

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Figure B3 Diurnal wind roses at the Le Fevre 1 monitor (observed and modelled by CALMET)

B2 CALPUFF DISPERSION MODELLING

CALPUFF simulates the dispersion of air pollutants to predict ground-level concentration and deposition rates across a network of receptors spaced at regular intervals, and at identified discrete locations. CALPUFF is a non- steady-state Lagrangian Gaussian puff model containing parameterisations for complex terrain effects, overwater transport, coastal interaction effects, building downwash, wet and dry removal, and simple chemical transformation. CALPUFF employs the 3D meteorological fields generated from the CALMET model by simulating the effects of time and space varying meteorological conditions on pollutant transport, transformation and removal. CALPUFF considers the geophysical features of the study area that affects dispersion of pollutants and ground-level concentrations of those pollutants in identified regions of interest. CALPUFF contains algorithms that can resolve near-source effects such as building downwash, transitional plume rise, partial plume penetration, sub-grid scale terrain interactions, as well as the long-range effects of removal, transformation, vertical wind shear, overwater transport and coastal interactions. Emission sources can be characterised as arbitrarily-varying point, area, volume and lines or any combination of those sources within the modelling domain.

B2.1 CALPUFF Setup

Key features of CALPUFF used to simulate dispersion:

• Computational domain of 36 x 45 grid points at 200 m resolution, a subset of the CALMET domain

• Sampling grid of 64 x 82 grid points at 100 m resolution, a subset of the computational domain with a meshdown factor of 2

• 365 days modelled (1 January 2009 to 31 December 2009)

• Gridded 3D hourly-varying meteorological conditions generated by CALMET

• Partial plume path adjustment for terrain modelled

• Dispersion coefficients calculated internally from sigma v and sigma w using micrometeorological variables, with the minimum sigma v set to 0.2 over land and water

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• Minimum wind speed for calm conditions set to 0.2 m/s

• Dry depletion turned on for modelling of dust (normal operations) and process variation scenarios. No dry depletion was used for modelling the full suite of emissions from the stacks.

• Stack tip downwash, transitional plume rise and PDF used for dispersion under convective conditions

• Building wakes included using Prime methodology.

All other options set to default.

B2.2 Building Inputs

Figure B4 presents the locations of the buildings that were included in the dispersion modelling along with their heights.

Figure B4 Layout of the Facility with the buildings as included in the CALPUFF model

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APPENDIX C EMISSIONS INVENTORY

C1 INVENTORY AND ACTIVITY DATA

The annual emission rates of all sources included in the dispersion model of the Facility are presented in Table C1. The emission rates incorporate the controls also listed in the table.

Table C1 Annual particulate matter emission rates of modelled activities during normal operations

Activity rate Control a Emission rate (kg/year) Activity Parameter Units Value Description % TSP PM10 PM2.5

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Activity rate Control a Emission rate (kg/year) Activity Parameter Units Value Description % TSP PM10 PM2.5

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Activity rate Control a Emission rate (kg/year) Activity Parameter Units Value Description % TSP PM10 PM2.5

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Activity rate Control a Emission rate (kg/year) Activity Parameter Units Value Description % TSP PM10 PM2.5

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C2 VEHICLE MOVEMENTS

A summary of the vehicle movements modelled as part of the assessment of normal operating conditions is presented in Table C2.

Table C2 Vehicle movements

Single Empty Distance per round Total Distance Vehicle Destination / Total Description Material load size veh. Trips/yr trip (km) (VKT/yr) Type Location (t/yr) (t) mass (t) Paved Unpaved Paved Unpaved

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C3 DUST COLLECTORS

A summary of the vehicle movements modelled as part of the assessment of normal operating conditions is presented in Table C3.

Table C3 Dust collectors included in the air quality assessment

Volumetric Weeks Emissions kg/yr Area Dust Collector Hour /day Days /week Total h/y flowrate (m³/hr) /year TSP PM10 PM2.5

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Volumetric Weeks Emissions kg/yr Area Dust Collector Hour /day Days /week Total h/y flowrate (m³/hr) /year TSP PM10 PM2.5

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C4 EMISSION FACTORS FOR DUST

C4.1 Material transfers

Emissions for materials handling are dependent on the amount of materials being transferred. Materials handling and transfers includes the handling of incoming material, transfers during processing, and transfers to and from stockpiles. These were calculated using equation 6 from the Emission estimation technique manual for Cement manufacturing, Version 2.1 (NPI, 2008):

푈 1.3 ( ) 2.2 퐸퐹 = 0.75 × 0.001184 × × 퐸푅 푃푀10 푀 1.4 푃푀10 ( ) 2 where:

EFPM10 emission factor for PM10 (kg/Mg) k particle size multiplier (dimensionless) U mean wind speed (m/s) M material moisture content (%)

ERPM10 emission reduction factor for PM10

The emission factor for TSP was calculated by multiplying the emission factor for PM10 by 2.1, which is the ratio of the TSP and PM10 emission factors for material transfers presented in the AP42 documents, chapter 13.2.4

(USEPA, 2006a). The emission factor for PM2.5 was calculated in a similar fashion using a multiplier of 0.15.

C4.2 Wind erosion of stockpiles

Emissions of PM10 due to wind erosion from materials storage have been calculated using the default emission factor from the Emission estimation technique manual for Cement manufacturing, Version 2.1 (NPI, 2008), which is 0.3 kg/ha/hr.

The emission factor for TSP was calculated by multiplying the emission factor for PM10 by 2, which is the ratio of the TSP and PM10 emission factors for wind erosion presented in the AP42 documents, chapter 13.2.5 (USEPA,

2006b). The emission factor for PM2.5 was calculated in a similar fashion using a multiplier of 0.15.

C4.3 Wind erosion of exposed areas

Wind erosion from exposed areas has been calculated using the default emission factors from the National Pollutant Inventory Emission Estimation Technique Manual for Mining, Version 3.1 (NPI, 2012). These are 0.4 kg/ha/hr for TSP and 0.2 kg/ha/hr for PM10.

The emission factor for PM2.5 has been calculated from the emission factor for PM10, and the ratio of the PM2.5 and

PM10 emission factors for wind erosion in the presented in the AP42 documents, chapter 13.2.5 (USEPA, 2006b), which is 0.15.

C4.4 Haulage on unpaved roads

The emission factors for TSP, PM10 and PM2.5 emissions due to vehicle movements on unpaved roads were calculated from the AP42 documents in chapter 13.2.2 titled “unpaved roads” (US EPA, 2006c).

The equation included in the assessment is as follows:

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푠 푎 푊 푏 퐸 = 281.9 × 푘( ⁄12) ( ⁄3)

where E emission factor (g/VKT) s surface material silt content (%) W mean vehicle weight (tons).

The multiplier of 281.9 converts the units from lb/VMT to g/VKT.

C4.5 Haulage on paved roads

The emission factors for TSP, PM10 and PM2.5 emissions due to vehicle movements on paved roads were calculated from the AP42 documents in Chapter 13.2.1 titled “paved roads” dated December 2011.

The equation included in the assessment is as follows:

퐸 = 푘(푠퐿)0.91(푊)1.02

where

E emission factor (g/VKT)

k particle size multiplier for particle size range

sL road surface silt loading (g/m2)

W mean vehicle weight (tons).

C4.6 Vehicle combustion emissions

Emissions from combustion engines were calculated in accordance with the NPI EET Manual for Combustion Engines v3 (2008). Emissions are based on engine size and operating hours according to the following equation:

퐸 = 푃 × 푂푝퐻푟푠 × 퐿퐹 × 퐸퐹

Where:

E emissions of substance (kg/year)

P engine power (kW)

OpHrs operating hours per year (h)

LF load factor

EF Emission factor

C4.7 Dust collectors

Emissions from dust collectors are based on the flow rates presented in Table C3 and measured concentrations presented in Table 10. Emissions from dust collectors that were not measured were calculated using the maximum measured concentration.

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APPENDIX D MODELLING AND MONITORING COMPARISON

D1 MODEL DESCRIPTION

The emissions model was based on activities carried out during the 2015/16 NPI reporting period. The meteorological and dispersion models were rerun using 2015 and 2016 meteorology to provide a comparison to monitoring data collected during this period.

All model inputs were consistent with those described in Section 4 of the report and Appendix B, except for the modelling period and associated assimilated data. The meteorological model was compared to the monitoring data at Le Fevre 1 and the comparison statistics, presented inTable D1, indicate that it performed well for 2015 and 2016.

Table D1 Statistical analysis of CALMET output at the Le Fevre 1 EPA monitor

Parameter Statistic Units 2015 2016 Target Root Mean Square Error m/s 1.11 1.06 <= 2 Wind speed Bias m/s -0.46 -0.41 <= ± 0.5 Index of Agreement - 0.69 0.73 >= 0.6 Gross Error ° 26.25 24.3 <= 30 Wind direction Bias ° -0.01 -0.48 <=±10 Gross Error °K 1.5 1.4 <=2 Temperature Bias °K -0.23 0.04 <=±0.5 Index of Agreement - 0.84 0.83 >=0.8

D2 ANALYSIS

Analysis was performed on PM10, as more monitoring data was available. Predicted 1-hour and 24-hour concentrations were extracted at the location of Le Fevre 1. An ambient background of 18.0 µg/m³ has been added to each prediction and the results compared to the monitoring data over the 2015 – 2016 period. Table D2 presents summary statistics of the monitoring and modelling data. Timeseries of the two datasets are presented inFigure D1. The data indicates the following:

• The mean and median values of both datasets align.

• The model does not capture the level of variation in the monitoring dataset.

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Table D2 Monitoring and modelling data during 2015 and 2016

Modelling (Including Parameter Monitoring Modelling (Isolation) background) Minimum 4.2 0.0 18.0 10th %ile 10.3 0.0 18.0 Mean 19.5 1.5 19.5 Median 18.4 0.1 18.1 70th %ile 22.7 1.8 19.8 90th %ile 28.9 4.8 22.8 Maximum 85.4 10.9 28.9

Figure D1 Timeseries of 24-hour average PM10 measured at Le Fevre 1 (blue) and predicted at the same location (red)

The analysis in Appendix A indicates that morning traffic is a major source of PM10 at the Le Fevre 1 monitoring site. Traffic has not been explicitly included as a source in the model. The analysis also identified that the two exceedance days in the dataset (4 May 2015 and 27 April 2016) are due to regional influences.

A breakdown of observations and predictions by time of day, day of week and month is shown in Figure D2 (average concentrations) and Figure D3 (median and 30th to 70th percentile range). The data shows that:

• The model does not capture the morning traffic peak at Le Fevre 1, which is expected since roads have not been explicitly modelled.

• The model does a good job of capturing the nighttime peaks in concentration, which can be attributed to the Facility.

• The model does not capture the variation in daytime concentrations; on average, it overestimates these hours.

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Figure D2 Mean and 95% confidence interval of modelled and observed 1-hour average PM10 concentrations at Le Fevre 1

th th Figure D3 Median and 30 - 70 percentile range of modelled and observed 1-hour average PM10 concentrations at Le Fevre 1

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