air quality and greenhouse gas technical report
TRANSCRIPT
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Environmental Impact Statement - February 2018
Saint Elmo Vanadium Project
Volume 2 A14 - Air Quality and Greenhouse Gas Technical Report
Saint Elmo Vanadium Project
Air Quality and Greenhouse Gas Technical Report
Report: 197401.0129.R01V09.docx
Prepared for:
Multicom Resources Ltd
1 June, 2020
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Document Control Document Ref Date of Issue Status Author Reviewer
9461R01V01 7 February, 2019 Final Michelle Yu AM
9461R01V02 30 August, 2019 Revision to address DES comments and process changes
Michelle Yu AM
9461R01V03 3 September, 2019 Revision with minor clarifications Michelle Yu AM
197401.0129.R01V04 28 April, 2020 Revision to address public submission
Michelle Yu AM
197401.0129.R01V05 22 May, 2020 Revision to include the OWSF Michelle Yu AM
197401.0129.R01V06 25 May, 2020 Revision to address Epic’s comments Michelle Yu AM
197401.0129.R01V07 26 May, 2020 Revision to address Epic’s comments Michelle Yu AM
197401.0129.R01V08 28 May, 2020 Update to greenhouse emission reference and emissions
Michelle Yu AM
197401.0129.R01V09 1 June, 2020 Update to include additional table notes
Michelle Yu AM
Document Approval
Approver Signature
Name Andrew Martin
Title Air Quality Manager
Disclaimer: This document and associated tasks were undertaken in accordance with the ASK Consulting Engineers Quality Assurance System, which is based on Australian Standard / NZS ISO 9001:2008. This document is issued subject to review, and authorisation by a Senior Consultant noted in the above table. If the table is incomplete, this document shall be considered as preliminary or draft only and no reliance shall be placed upon it other than for information to be verified later.
This document is prepared for our Client's particular requirements which are based on a specific brief with limitations as agreed to with the Client. It is not intended for and should not be relied upon by a third party and no responsibility is undertaken to any third party without prior consent provided by ASK Consulting Engineers. The information herein should not be reproduced, presented or reviewed except in full. Prior to passing on to a third party, the Client is to fully inform the third party of the specific brief and limitations associated with the commission.
The information contained herein is for the identified purpose of air quality assessment only. No claims are made and no liability is accepted in respect of design and construction issues falling outside of the specialist field of air quality science including and not limited to structural integrity, fire rating, architectural buildability and fit-for-purpose, waterproofing, safety design and the like. Supplementary professional advice should be sought in respect of these issues.
Copyright: This report and the copyright thereof are the property of Trinity Consultants Australia Pty Ltd (ABN 62 630 202 201). It must not be copied in whole or in part without the written permission of Trinity Consultants Australia Pty Ltd. This report has been produced specifically for the Client and project nominated herein and must not be used or retained for any other purpose. www.askconsulting.com.au
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Contents
1. Introduction 7
1.1 Background 7
1.2 Terms of Reference 8
1.3 Public Submission 10
2. Study Area Description 19
2.1 Overview 19
2.2 Identification of Existing Sensitive Receptors 19
2.3 Description of the Existing Air Environment at the Proposed Project Site and the Surrounding Region 22
3. Proposed Development 23
3.1 Project Overview 23
3.2 Operations 23
3.2.1 Open-Cut Mine Methodology 23
3.2.2 Mine Sequencing 24
3.2.3 Choice of Modelling Scenarios 26
3.2.4 Mobile Plant and Production 28
3.2.5 Processing Plant 29
Beneficiation 29
Flotation 29
Roasting 30
Atmospheric Leaching 30
Filtration 30
Concentration 30
Desilication 30
AMV Precipitation 30
Deammoniation 30
Product Handling 30
3.3 Construction and Commissioning 31
3.4 Decommissioning and Closure 31
3.5 Off-site Water Storage Facility 31
3.5.1 Construction 31
3.5.2 Operation 32
3.5.3 Decommissioning 32
4. Air Quality Criteria 33
4.1 Relevant Pollutants 33
4.1.1 Particulates 33
4.1.2 Gaseous Emissions 33
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4.2 State Legislative Instruments 33
4.2.1 Queensland Environmental Protection Policy 33
4.2.2 National Environmental Protection (Ambient Air Quality) Measure 34
4.2.3 Department of Environment and Science (DES) Guideline 35
4.3 Other State Legislation 35
4.4 Dust Deposition 35
4.5 Summary of Relevant Pollutant Concentration Criteria 36
5. Greenhouse Gas Regulatory Requirements 37
5.1 National Greenhouse and Energy Reporting (NGER) 37
5.2 Reporting Thresholds 38
5.3 Greenhouse Gases 38
6. Greenhouse Gas Emissions 39
6.1 Methodology for Impact Assessment 39
6.2 Emissions from Vegetation Clearing 40
6.3 Process Gas Emissions 40
6.4 Liquid Fuel Combustion Emissions 40
6.5 Leakage Emissions from Storage and Transfer of LNG 41
6.6 Emissions from Exposure of Ore Body and Oil Shale 42
6.7 Summary of Greenhouse Gas Emissions 42
6.8 Recommendations for Mitigation Measures 43
6.8.1 Equipment and Energy Efficiency 44
6.8.2 Mine Planning 44
6.8.3 Mine Operations 44
6.8.4 New Technology 45
6.8.5 Management Systems 45
7. Regional Climate 46
7.1 Weather Stations 46
7.2 Existing Wind Records 46
7.3 Existing Temperature and Rain 48
7.4 Potential Future Changes to Climate 49
7.4.1 Wind 49
7.4.2 Rain & Humidity 49
7.4.3 Elevated Temperature Inversions 49
8. Meteorological Modelling 50
8.1 TAPM Meteorological Modelling 50
8.1.1 TAPM Fundamentals 50
8.1.2 TAPM Configuration 50
8.1.3 Observational Data Assimilation 50
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8.1.4 TAPM Validation 52
8.2 Topography and Land Use 53
8.3 Calmet Modelling Configuration. 55
8.4 Calmet Results 56
9. Monitoring Method 59
9.1 Overview 59
9.2 Pollutant Monitoring Methodology 61
9.3 Monitoring Results 62
9.4 Dust Deposition Monitoring 64
10. Existing Air Quality 65
10.1 Overview 65
10.2 DES The Gap (Mount Isa) 65
10.3 DES Memorial Park (Gladstone) 66
10.4 DES Boyne Island (Gladstone) 67
10.5 DERM Runcorn Monitoring 67
10.6 Polycyclic Aromatic Hydrocarbons 67
10.7 Ammonia Concentration 68
10.8 Dust Deposition 68
10.9 Other Pollutants 68
10.10 Summary of Estimated Background Levels 68
11. Pollution Modelling Methodology 70
11.1 Overview 70
11.2 Modelling Scenarios 71
11.3 Calpuff Configuration 71
11.4 Emission Inventory Calculations for Particulates 72
11.5 Dust Control Measures 72
11.6 Summary of Emission Inventories 72
11.7 Other Source Parameters 76
11.8 Emissions Inventory for the Processing Plant 79
11.8.1 Flotation 79
11.8.2 Roasting 79
11.8.3 Leaching 81
11.8.4 Solvent Extraction 82
11.8.5 NH3 Emissions from De-ammoniation Plant 82
11.8.6 Emissions from Power Generation 82
11.9 Nitrogen Dioxide Modelling 83
11.9.1 Overview 83
11.9.2 Janssen Method 84
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11.9.3 Conversion Relevant to this Study 84
11.10 Calpost Processing 84
12. Dispersion Modelling Results 85
12.1 Limitations 85
12.2 Suspended Particulate Results 85
12.2.1 Short-Term (24-Hour Average) TSP Impact 86
12.3 Dust Deposition Results 90
12.4 Combustion Pollutant Results 93
12.5 Roasting Emissions 94
13. Discussion 96
13.1 Summary of Results 96
13.2 Recommendations 97
13.2.1 Overview 97
13.2.2 Review of NSW Study 97
13.2.3 Management During Adverse Winds 98
13.2.4 Project-specific Recommendations 98
13.2.5 Monitoring 98
14. Risk Assessment of Impacts 100
14.1 Risk Assessment 100
15. Conclusion 103
References 104
Appendices
Appendix A Glossary 109
Appendix B Emission Inventory Equations for Particulates 111
Appendix C Air Quality Management Plan 115
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1. Introduction
1.1 Background
ASK Consulting Engineers Pty Ltd (ASK) has been commissioned by Multicom Resources Limited (Multicom) to provide air quality consultancy services for the Saint Elmo Vanadium Project, a proposed vanadium mine. The proposed location is approximately 14 km to the east of Julia Creek, immediately to the north of Flinders Highway in north-west Queensland (QLD) as shown in Figure 1.1.
Figure 1.1 Location of the Saint Elmo Project (Image from Google Earth Pro)
This report presents an assessment of the air quality impacts and greenhouse gas emissions generally associated with the proposed operations of the Saint Elmo Project. The construction, commissioning, decommissioning and closure phases of the project have been assessed qualitatively in Section 14. This report is based on the following tasks which are in accordance with the Department of Environment and Science (DES) EIS Information Guideline - Air:
• Review the project and the associated potential air emissions.
• Review existing air quality monitoring data applicable to the project site.
• Prepare a greenhouse gas inventory for combustion sources and processing emissions including based on current National Greenhouse Accounts Factors and NGER guidelines. Discuss the relative scale and implications of these emissions compared to state and national emissions.
• Develop an emission inventory based on National Pollutant Inventory (NPI) and United States Environmental Protection Agency (USEPA) AP-42 literature for particulates less than 2.5 µm (PM2.5),
150 km
Mount Isa Saint Elmo Project
Julia Creek
Townsville
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particulates less than 10 µm (PM10), total suspended particles (TSP), dust deposition and combustion gases from power generation.
• Model meteorological conditions using The Air Pollution Model (TAPM) and Calmet.
• Model the dispersion of expected air pollutants based on proposed activities using Calpuff to estimate levels of the emissions reaching sensitive receptors and develop contours over the modelling domain for the two likely most severe (worst case) scenarios.
• Analyse the results of meteorological and pollutant dispersion modelling and compare modelling results with the relevant air quality criteria.
• Provide recommendations on control measures.
To aid in the understanding of the terms in this report a glossary is included in Appendix A. This technical document forms an Appendix to the main Environmental Impact Statement (EIS) for the project.
1.2 Terms of Reference
This report addresses the Terms of Reference for the impact assessment issued by the Queensland Department of Environment and Science (DES) as summarised in Table 1.1.
Table 1.1 Requirements from the Terms of Reference
Requirements from the Terms of Reference Addressed in this Report
Describe the existing air environment at the proposed project site and the surrounding region.
Section 2.3
Provide an emissions inventory and description of the characteristics of contaminants or materials that would be released from point and diffuse sources and fugitive emissions when carrying out the activity (point source and fugitive emissions). The description should address the construction, commissioning, operation, upset conditions, and closure of the proposed project.
Section 3 – Description of the project.
Section 4.1 – Description of characteristics of pollutants
Sections 3.3, 3.4 and 11.1 – Briefly discusses why emission inventories and modelling for the construction, commissioning and closure of the proposed project are not necessary.
Sections 11.4, 11.5, 0 and 11.7 – Emissions inventory of the worst-case mining operation
Section 11.8 – Emissions inventory of the processing plant.
Predict the impacts of the releases from the activity on environmental values of the receiving environment using established and accepted methods and in accordance with the EP Regulation, Environmental Protection (Air) Policy 2008 (EPP (Air)), and the department’s EIS information guideline—Air. The description of impacts should take into consideration the sensitivity and assimilative capacity of the receiving environment and the practices and procedures that would be used to avoid or minimise impacts. The impact prediction must address the cumulative impact of any release with other known releases of contaminants, materials or wastes associated with existing development and possible future development (as described by approved plans and existing project approvals). It should also quantify the human health risk and amenity impacts associated with emissions from the proposed project for all contaminants whether or not they are covered by the National Environmental Protection (Ambient Air Quality) Measure or the EPP (Air) or not.
Section 2.2 - Describes the sensitive receptors in the receiving environment.
Section 4 - Describes the air quality criteria that are the values.
Sections 8 and 11 – The modelling methodology used in the prediction of impacts is described in these sections.
Section 12 – Predicted impacts at the sensitive receptors. Estimated background levels are also presented to account for cumulative impacts. The relevant criteria compared against the predicted impacts are for human health risk and amenity.
Section 14 – Risk assessment of impacts for the construction, commissioning, operating, decommissioning and closure phase of the mine. This assessment includes anticipated consequences for human health.
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Requirements from the Terms of Reference Addressed in this Report
Describe the proposed mitigation measures to limit impacts from air emissions and how the proposed activity will be consistent with best practice environmental management. The EIS must address the compatibility of the proposed project’s air emissions with existing or potential land uses in surrounding areas. Potential land uses might be gauged from the zonings of local planning schemes, or State Development Areas or other relevant planning frameworks.
Section 13.2 – Mitigation measures are recommended in this section.
Section 2.2 identifies sensitive land uses in surrounding areas.
Describe how the proposed project’s air emission objectives would be achieved, monitored, audited and reported, and how corrective actions would be managed for the life of the proposed project.
Section 13.2 – Mitigation measures are recommended to help achieve the project’s air emission objectives.
Proponents are responsible for determining if they have obligations under the Commonwealth National Greenhouse and Energy Reporting Act 2007 (NGER Act) and ensuring that information regarding greenhouse gas emissions and energy production and consumption provided in the EIS is consistent with requirements of the NGER Act and its subordinate legislation.
Sections 5 and 6
Provide an inventory of projected annual emissions for each relevant greenhouse gas, with total emissions expressed in ‘CO2 equivalent’ terms. Estimate emissions from upstream activities associated with the proposed project, including the fossil fuel based electricity to be used during construction, operation and decommissioning and briefly describe the methods used to make the estimates. Scope 3 emissions will not be assessed under this TOR. The National Greenhouse and Energy Reporting (Measurement) Determination 2008 provides methods and criteria for calculating greenhouse gas emissions and energy data under the NGER Act which can be used in combination with NGER technical guidelines30 as a reference source for emission estimate methods and supplemented with information from other sources where practicable and appropriate.
Section 6
Assess the potential impacts of operations within the proposed project area on the state and national greenhouse gas inventories and propose greenhouse gas abatement measures, including:
• a description of the proposed preferred and alternative measures to avoid and/or minimise greenhouse gas emissions directly resulting from activities of the proposed project, including such activities as transportation of products and consumables, and energy use by the proposed project
• an assessment of how the preferred measures minimise emissions and achieve energy efficiency
• a comparison of the preferred measures for emission controls and energy consumption with best practice environmental management in the relevant sector of industry
• a description of any opportunities for further offsetting of greenhouse gas emissions through indirect means.
Sections 6.7 and 6.8
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1.3 Public Submission
Submissions have been received from various State and Commonwealth government departments requesting further information relating to the project. The submissions relevant to air quality were all received from DES. This report addresses the relevant submissions as summarised in Table 1.2.
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Table 1.2 Public Submission
Item No.
Comment Recommendation ASK Response
177 Diesel generator air emissions
Specific information is required in relation to the diesel generator. Section 9.5.5.1 of Chapter 9 of the EIS provides estimated emission rates based on a typical worst-case scenario generator stack. In order to accurately condition an EA, particularly point source emission requirements, information about the specific generator, including the plant’s capacity and manufacturer specifications for emissions, is required. The department requires information about the location of any release points to air, the contaminants of concern, the minimum release height, the minimum exit gas temperature and the minimum efflux velocity.
Additional information is also required regarding how the power generation plant will be managed to ensure all environmental values are protected.
The EIS should provide specific information in relation to point source emissions, particularly as it relates to conditioning of any EA. Provide additional information in the EIS about the specific generator to be used to generate electricity for the site. Information is required on the location of any release points to air, the contaminants of concern, the minimum release height, the minimum exit gas temperature and the minimum efflux velocity.
Section 11.8.6 presents modelled emission rates and parameters. Table 11.11 presents the modelled point source parameters which can be used to condition emissions. The exhaust temperature and flowrate are based on the Cummins QSK78-G9 model. The rest of the parameters are conservative assumptions of typical generator emissions. The rain cap option was turned on in the model for conservatism, hence a low minimum efflux velocity should be sufficient.
Table 11.10 presents the modelled emission rates of contaminants of concern. As discussed in Section 12.4, NOx is the most critical pollutant emitted. It should be noted that despite the conservative assumptions, the most critical pollutant, NO2, is still predicted to comply with the relevant criteria.
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Item No.
Comment Recommendation ASK Response
178 Gas generators
Chapter 5, section 3.3.3 of the EIS states that gas generators will be used and operational gas demand will be supplied on-site. There was no assessment in the EIS of carbon dioxide released from gas generators or the potential leakage of methane. The EIS should discuss if this would result in the release of carbon dioxide and methane (such as leaks from gas storage and transfer).
Provide an assessment of the potential for gas generators to release carbon dioxide. Assess the impacts from the potential release of methane (such as leaks from gas storage and transfer).
Section 6.4 provides a greenhouse gas assessment of the combustion emissions from gas generators. Greenhouse gas (mainly carbon dioxide) emission from gas generators is calculated to be 127 kt CO2-e per annum.
Section 6.5 provides a greenhouse gas assessment of the leakage from storage and transfer of gas. Greenhouse gas leakage emission from storage and transfer of LNG is mainly composed of methane and is calculated to be 3 kt CO2-e per annum.
Greenhouse gas emissions from gas generators and leakage from storage and transfer of LNG have been included in calculation of the Project’s annual greenhouse gas emission in Section 6.7, which is 258 kt CO2-e per annum or 0.061% of Australian NGER emissions, and 0.16% of Queensland emissions, and 0.9% of Queensland mining emissions. Section 6.7 provides the range of recent changes to greenhouse gas emissions in Queensland and Australia.
179 Greenhouse gas emissions
There was no discussion in the EIS on the potential for release of methane or gas from the ore body or volatile emissions from exposure of the underlying oil shale unit. The EIS should discuss if the ore body has any trapped gas that would be released or any other sources of greenhouse gas emissions such as exposing the oil/shale to air.
The EIS should discuss all sources of greenhouse gas emissions from the proposed project, including the release of methane or gas from the ore body or volatile emissions of greenhouse gas from the oil shale unit.
Section 6.6 presents a discussion on potential release of greenhouse gas from the ore body and exposure of the underlying oil shale unit.
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Item No.
Comment Recommendation ASK Response
194 Given the enhanced risk of impacts from dust and particulates predicted to receptor A (Saint Elmo Homestead), monitoring for indicators of impacts is necessary to ensure ambient air quality is meeting the relevant ambient guideline criteria values for particulates. It is considered that monitoring of PM10 on a continuous basis at receptor A (Saint Elmo Homestead) is required. This continuous monitoring could take the form of either high or low volume sampling in accordance with the relevant Australian standard, and a one in six day running cycle, if that is referenced in the relevant Australian Standard, will comply with the requirement of continuous monitoring.
Include a proposed environmental authority condition requiring that continuous monitoring of ambient PM10 levels at Saint Elmo Homestead be conducted.
Refer to the proposed environmental conditions.
A proposed PM10 monitoring location at Saint Elmo homestead has been provided in Table 22.8, within Chapter 22 of the EIS. PM10 monitoring is to be undertaken for a minimum of 3 months during the first year of mining and reviewed to determine the extent of future monitoring. This will also be undertaken during years 22 and 23 when mining operations are closest to the homestead.
195 The general dust deposition monitoring proposed in the first row of Table 22.6 in section 22.1.2 is necessary and must be included as a monitoring requirement. Locations based on the general direction of sensitive receptors in the area (particularly Saint Elmo Homestead) should be finalised for inclusion as defined monitoring points. These monitoring points should be referenced in a monitoring location table and an associated condition enacting the monitoring requirement.
Proposed condition B2 will meet this requirement, but the table referenced must include monitoring at locations on the mining lease boundary based on the general direction of all sensitive receptors in the area and propose that dust deposition monitoring is conducted at each location on a 30-day cycle, in accordance with the relevant Australian Standard.
Limits within the monitoring table are not required, as the model mining condition for dust and particulates (as proposed as condition B5) covers the applicable limits and compliance requirements.
Refer to the proposed environmental conditions.
Proposed dust deposition monitoring locations on the mining lease boundary based on the general direction of sensitive receptors and at the Saint Elmo homestead has been provided in Table 22.7, within Chapter 22 of the EIS. Limits and frequency of monitoring are specified in Table 22.6. The relevant standard to be referred to is specified in condition B5 a).
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Item No.
Comment Recommendation ASK Response
196 Condition B5 is not the appropriate location for sub-condition points e) and f) as this condition B5 relates to particulates and dust. The monitoring should be referenced under condition B2.
It is assumed that the first line TBA reference in table 22.5 in section 22.1.2 should be to indicate sulfur dioxide and the second line TBA reference should be to indicate ammonia.
The department does not consider that the monitoring of these parameters is essential based on the assessed level of risk from the predicted level of emissions of sulphur dioxide and ammonia.
If this monitoring is still proposed to be undertaken, the “TBA” references should be corrected. Quarterly monitoring at this location, given prevailing wind predictions, is unlikely to yield meaningful result data sets as the wind direction may not frequently be coming from the direction of the source emissions on site.
Remove points e) and f) from proposed condition B5 in section 22.1.2.
Amend the EIS to include the following information:
• Correct TBA references in table 22.5 in section 22.1.2 of Chapter 22.
• Alternatively, remove these monitoring requirements outlined in table 22.5 5 in section 22.1.2, based on the low level of risk associated with these contaminants.
Refer to the proposed environmental conditions provided in Chapter 22 of the EIS.
Subconditions B5 e) and f) have been moved under condition B2.
The previous Table 22.5 has been deleted and replaced.
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Item No.
Comment Recommendation ASK Response
197 The table referred to in proposed condition B4 in section 22.1.2 is incorrectly referenced/missing. Table 22.5, section 22.1.2 (that it appears the above-mentioned condition should refer to is not populated with any proposed emission limits.
The emission limits for the stack should be proposed based on the calculated acceptable emission rates presented in Table 11.9 of Appendix 14. These should be calculated and presented in the appropriate concentration units (i.e. g/Nm3 as opposed to ppm).
Ammonia should be monitored in the discharge stack emissions from the de-ammoniation plant, to ensure the scrubber performance results in acceptable ammonia emission levels.
The Stack monitoring points in the proposed environmental authority conditions should be defined and include (but not necessarily be limited to) the following:
Table B1—Release points (air) *refer to original comments for table*
Table B2 - Contaminant limits (air) *refer to original comments for table*
Amend the EIS to include the following information:
• Correct the issue with stack emission limit table referred to under proposed EA condition B4 in section 22.1.2.
• Include a table for stack monitoring locations and an additional table for stack monitoring requirements and limits in section 22.1.2 that will be referred to in condition B4.
• Include minimum monitoring locations, parameters and limits as proposed by the department in the above-mentioned tables. Ensure that all stack discharges are converted from discharge rate to a concentration as per the recommended units shown in table B2 in the comments column.
Refer to the proposed environmental conditions provided in Chapter 22 of the EIS.
Condition B4 has been amended with references to Table 22.4 and Table 22.5. Table 22.4 specifies point sources with locations and minimum emission parameters (release height, exit temperature and velocity). Table 22.5 specifies air pollutant emission limits.
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Item No.
Comment Recommendation ASK Response
199 Tables 4.1 and 4.5 include a note that relates to the allowable number of PM10 exceedances per year. The recently remade EPP Air commenced on 1 September 2019. No exceedances are allowed for now, so the reference to allowing for exceedances of the criteria on five occasions for bushfires etc. should be removed. See:
https://www.legislation.qld.gov.au/view/whole/html/asmade/sl-2019-0153
Amend the EIS to include the following information:
• Remove “Note 1” from Table’s 4.1 and 4.5 in Appendix 14.
• Remove “Note” from Table 9.5 in Chapter 9.
• Section 9.2.1.1 of Chapter 9 and section 4.2.2 of Volume 2 Appendix 14 should also be updated to reflect the existence of the new PM10 1-year average criterion in the EPP Air, and an explanation included as to why it was not used as a project criterion. The reference to allowing for exceedances of the criteria on five occasions for bushfires etc. should also be removed.
Notes under Table 4.1 and Table 4.5 have been removed. The notes were relevant to the superseded EPP Air 2008, but not to the current EPP Air 2019.
The note under Table 9.5 in Chapter 9 of the EIS has been removed.
Section 9.2.1.1 of Chapter 9 of the EIS and Sections 4.2.1, 4.5, 10.2, 10.10, , 12, 13.1 of this report have been updated to include the annual average PM10 criterion, background and predicted concentrations. The annual average PM10 is a recent addition to the EPP Air. This project was initially assessed under EPP Air 2008, prior to the release of EPP Air 2019.
200 Previous feedback to the proponent related to the need to include an Air Quality Management Plan (AQMP). High-level statements referring to aspects of air quality management and monitoring are included in the “Environmental Management Plan Framework” – eg section 1.5.10 (page 8) and 1.5.12 (page 9). Section 13.2 – Recommendations of A14 also identifies actions that should be included in an AQMP. It is considered that further detail and information is required to fulfil the requirements of section 10 of the Terms of Reference for the EIS, and this should be provided in the form of a specific AQMP.
Include an Air Quality Management Plan for assessment in the amended EIS.
An AQMP has been provided in Appendix C of this report.
201 Table 3.2 listing the proposed production fleet does not indicate scrapers within the mobile plant listing. Table’s 11.3 and 11.4 list the use of scrapers for several emission source listings.
Update Table 3.2 to include all mobile plant proposed to be utilised for all mining activities.
Table 3.2 has been updated to include the potential scraper. Other mobile plant were already included.
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202 The maximum 24-hour averaged PM10 concentration was predicted to exceed the criterion at receptor A for scenario 2. The special control measures applied for scenario 2b resulted in the criterion only just being met. The potential for unacceptable environmental impacts at this location is greater than at any other sensitive receptor and this is stipulated as the highest risk from the proposed project in terms of air emissions.
Table 11.4 indicates that the operation of bulldozers is a major source contribution for particulate emissions for scenario 2 (and possibly 2b) at 12% of total PM10 emissions.
Table 11.2 indicates an emission reduction factor of 50% has been applied to bulldozer operations through the use of water sprays as a control measure.
The National Pollutant Inventory (NPI) Emission Estimation Technique Manual for Mining Version 3.1 January 2012, in Table 4, allows for a 50% emission reduction factor to be generically applied when water sprays are to keep ore wet at metalliferous mines.
Topsoil and overburden material that is being stripped would not meet the criteria to be classified as ore. It is noted that the coal mine section of Table 4 of the Emission Estimation Technique Manual for Mining states that for bulldozers working on coal or other material, no reduction factor can be applied. A 50% reduction factor for the use of scrapers is indicated if the soil is moist (either naturally or artificially).
Section 9.4 of the report titled NSW Coal Mining Benchmarking Study: International Best Practice Measures to Prevent and/or Minimise Emissions of Particulate Matter from Coal Mining, Katestone Environmental, 2001 states the following:
Include an emission estimation calculation for bulldozer clearing that is fully in accordance with the NPI Emission Estimation Technique Manual for Mining, or alternatively, present an alternative emission estimation methodology from another suitable reference document.
Provide further information which justifies the application of an emission reduction factor for the use of bulldozers for topsoil and overburden clearing that:
1) describes how water sprays from tankers will be implemented for broad scale clearing using bulldozers, including a calculation to predict the availability of enough water for this purpose, and;
2) demonstrates that water spraying for bulldozing has successfully been implemented by use of case studies or has covered other emission estimation technique references.
Emission estimation equations used to calculate particulate emissions from bulldozer activities are in accordance with the NPI Emission Estimation Manual for Mining and the USEPA AP-42 and are provided in Appendix B of this report.
Although "there is very little information in the literature on minimising emissions from bulldozers” and that “NPI states that there are no controls to reduce emissions from bulldozers working on coal or other materials” (Katestone Environmental, 2011), the emission estimation equation for bulldozing activities shows that moisture is a factor for the emission rate. As shown in Appendix B of this report, the PM10 emission for bulldozing overburden is inversely proportional to the moisture content raised to the power of 1.4. This means that to reduce the PM10 emissions from bulldozing of overburden by 50%, the moisture content of the material has to be increased by 64 percent. Figure 49 of Katestone Environmental (2011) provides the various PM10 emission factors corresponding to different silt and moisture contents based on the NPI and AP-42 emission estimation equations. It clearly shows reduction in emissions with higher moisture content for materials with the same silt content. In addition, West Wallsend Colliery (2012) observed no visible emissions from bulldozing on coal stockpile due to the product coal’s high moisture content (ranging from 7 to 10 percent) and water spraying, contradicting the NPI statement that no reduction factor can be applied to dozers working on coal or other materials. West Wallsend Colliery (2012) also noted that the AP-42 emission factors account for coal ripping and handling within open cut mines and therefore overestimates emissions for dozing that does not include coal ripping.
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Item No.
Comment Recommendation ASK Response
There is very little information in the literature on minimising emissions of particulate matter from bulldozers. The NPI states that there are no controls to reduce emissions from bulldozers working on coal or other materials. The NPI provides a 50% control factor for scrapers operating on topsoil when the soil is naturally or artificially moist and it is likely that a similar effect would be achieved for bulldozers if the working areas could be kept moist.
Further justification for taking a different approach to that recommended by the Emission Estimation Technique Manual for Mining should be provided. This may include conducting calculations in accordance with the relevant methodology outlined in the USEPA AP-42 Compilation of Air Emissions Factors.
Watering to sufficient moisture to a sufficient depth for dust emission reduction is impractical (Bengalla Mining Company, 2012) for most mines due to the amount of overburden they handle. Saint Elmo Mine has the advantage of the activities being shallow, and hence will require less water than a typical mine to reduce emissions from bulldozing; however, Saint Elmo Mine will still require a substantial amount of water to achieve sufficient moisture content for the overburden, especially in years with higher overburden moved, based on the emission factor equation.
The amount of overburden moved by dozers range from 5,229,574 to 167,555,815 bcm per year (based on 10,000 to 20,000 tonnes of product per year). Its moisture content is assumed to be 7.9%. Increasing the moisture content by 64%, the following equation was applied to calculate for the amount of water needed:
0.64 𝑥 0.079𝑡 𝑤𝑎𝑡𝑒𝑟
𝑡 𝑜𝑣𝑒𝑟𝑏𝑢𝑟𝑑𝑒𝑛𝑥[𝑎𝑚𝑜𝑢𝑛𝑡 𝑜𝑣𝑒𝑟𝑏𝑢𝑟𝑑𝑒𝑛]𝑏𝑐𝑚 𝑥 1.8
𝑡
𝑏𝑐𝑚
The amount of water calculated for overburden pushed by dozers range from 476 to 15,249 ML per year, assuming no rainfall. As this is a very large amount of water, it is recommended to keep water spraying to a practical level, and to monitor PM10 in real time at the Saint Elmo homestead so that dozing activities could be minimised or ceased when elevated PM10 levels are being recorded. It is considered that substantially less water will be required than the above calculation especially during the wet season and that the NPI and AP-42 emission factors are likely to be overestimating the emissions, as in the case in West Wallsend Colliery.
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2. Study Area Description
2.1 Overview
The site for the proposed vanadium mine is located on rural, agricultural land. Immediately to the south of the proposed mining boundary is the Flinders Highway.
2.2 Identification of Existing Sensitive Receptors
The definition of a sensitive place required to be considered by operators of environmentally relevant activities is provided by the Department of Environment and Science (DES 2019). This definition is a place that could include but is not limited to:
• a dwelling, residential allotment, mobile home or caravan park, residential marina or other residential premises
• a motel, hotel or hostel
• a kindergarten, school, university or other educational institution
• a medical centre or hospital
• a protected area under the Nature Conservation Act 1992, the Marine Parks Act 2004 or a World Heritage Area
• a public park or garden
• a place used as a workplace including an office for business or commercial purposes.
The predominant existing land use in the surrounding area is grazing with some homesteads interspersed on rural properties. The nearest existing sensitive receptors are summarised in Table 2.1 and are shown in Figure 2.1. The closest receiver is receptor A (Saint Elmo) and is approximately 270 m west of the mining lease boundary. All of the receptors listed in Table 2.1 are residences. The last receptor (E) has not been included in the model, because this is least likely to be impacted by mining operations due to its distance and predominant direction of the prevailing winds in the area. Furthermore, the pollution contours shown in Figure 12.1 to Figure 12.4 demonstrate that impacts do not reach that far south.
Table 2.1 List of Sensitive Receptors with UTM Coordinates (WGS84 Z54)
ID Name / Address
Real Property Description
Approximate Distance and Direction from Site Boundary
Easting
(m)
Northing
(m)
Latitude (°)
Longitude (°)
A Saint Elmo
Lot 13 EN89 270 m west 590175 7722971 -20.5901
141.8653
B Argyle Lot 4 EN30 4.2 km west 584451 7724151 -20.5798
141.8104
C Burwood Lot 4 MF16 6.8 km north 588714 7739955 -20.4369
141.8503
D Lindfield Lot 2 MF3 10 km north-east 598316 7739202 -20.4431
141.9424
E Garomna Lot 11 EN105 6.2 km south-west 591181 7709990 -20.7074
141.8756
Julia Creek township is approximately 13 km from the western boundary of the mining lease and therefore very unlikely to be impacted by emissions from the mine.
Drivers on the Flinders Highway may observe dust from mining operations but are not considered sensitive to health effects due to the very short duration of exposure. Nuisance due to dust reaching the highway
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should be prevented by mine dust mitigation measures, which will be designed to allow safe mining operations.
Based on the land uses, it is considered unlikely that additional residences would be constructed in the surrounding areas during the lifetime of the proposed mine.
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Figure 2.1 Location of Site and Sensitive Receptors (Image from Queensland Globe Overlay)
Argyle Saint Elmo
Saint Elmo Project
Lindfield
Burwood
5000 m
Garomna
OWSF
OWSF pipeline
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2.3 Description of the Existing Air Environment at the Proposed Project Site and the Surrounding Region
A survey of the surrounding area was conducted with no other existing air emission sources found, with the exception of grazing operations and their associated activities.
There are no other mining lease production permits in the area. There are several other exploration permits in the vicinity of the sensitive receptors (held by AXF Vanadium, Jorge Resources, MM Metals, and Interim Resources) however at the time of publication ASK and Epic Environmental (Epic) are not aware of any other operations proposed in the foreseeable future.
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3. Proposed Development
3.1 Project Overview
The information in this section has been provided to ASK.
Multicom is seeking to develop the Saint Elmo Vanadium Project (the Project) for the purposes of mining and processing vanadium pentoxide and alternative vanadium-based products. The Project proposes to take advantage of the increasing supply gap associated with high-strength steel production, the growth market of vanadium batteries and the emergence of vanadium based compounds as a revolutionary metal in new technologies. There is an increasing global demand for lighter weight and higher strength steels as well as an increasing global demand for renewable and reliable energy, making vanadium a valuable resource.
The Project will consist of a shallow open cut mine, ranging in depth from 20 to 40 metres (depending on depth of overburden), with associated dump and haul operations in order to obtain access to large known deposits of vanadium bearing sedimentary material. Strip mining is proposed to be carried out sequentially from mining panels along the north-south axis of Mining Lease Application (MLA) 100162, a greenfield site. Once the material is removed, the panel will be back filled with beneficiated gangue and overburden material, then contoured and sheeted with topsoil. Subsequently, revegetation with native species or as otherwise agreed with relevant stakeholders will take place.
Operational production is scalable and based on market demand, with an initial target of 5,000-10,000 tonnes per annum (tpa) and a maximum tonnage of 20,000 tpa V2O5 product over at least a 30 year mine life. Run of Mine (ROM) operations to produce the maximum 20,000 tpa will be up to 15 million tpa. Mine processing will occur onsite, with overburden and process tailings that are unsuitable to go directly into the mined pit, managed in a Tailings Storage Facility (TSF). The assessment of impacts within this Environmental Impact Statement (EIS) is based on the conservative maximum tonnage of 20,000 tpa.
MLA100162 is located approximately 25 kilometres east of Julia Creek in the priority North West Minerals Province of north western Queensland, within the McKinlay Local Government Area (LGA). The area of MLA100162 is approximately 8,882 hectares.
In order to support mining activities, an operating water supply will be stored in an Offsite Water Storage Facility (OWSF). The OWSF and associated infrastructure are located approximately 21 km to the east of MLA100162. A water entitlement to harvest from the Flinders River is through the Department of Natural Resources, Mines and Energy (DNRME). The OWSF and associated infrastructure comprise three separate mine (infrastructure) lease components: MLA100244 – OWSF infrastructure area, MLA100245 – pipeline from OWSF to Project site and MLA100246 – aqueduct from the OWSF to Flinders River. The assessment of impacts associated with the OWSF and infrastructure is through this EIS.
The following sections specify details of the project that are relevant to the air quality and greenhouse assessment.
3.2 Operations
3.2.1 Open-Cut Mine Methodology
The mine plan is based on typical truck and excavator operations. Mining will be carried out sequentially from mining panels. Once material is removed, the panel will be back-filled with reject materials including beneficiated gangue, and overburden materials. Overburden materials from other panels will be pushed with dozers to back-fill the mined panel, exposing ore from the other panels which will then be mined. The back-filled overburden and reject materials will then be sheeted with topsoil for revegetation. Progressive rehabilitation will then be undertaken.
The mining operations are summarised as follows:
197401.0129.R01V09.docx 24
• Vegetation will be cleared.
• Topsoil will be removed, temporarily stockpiled and used to progressively rehabilitate exposed areas.
• Shallow pits (on average 20 metres deep) will be excavated and the overburden stockpiled for use during in-pit covering of reject material to final landform level.
• Dozers will push reject material/overburden to back-fill the areas that have been previously mined. This will also expose the coquina ore materials underlying the pushed overburden. Other dozers will be used to rehabilitate the mine.
• Excavators will side cast the rehandle overburden wedge.
• Excavators will load the mined ore into haul trucks to be transported from the pits to the run-of-mine (ROM) pad.
• Haul trucks will unload ROM ore at the ROM pad. All the ore from the ROM stockpiles will be rehandled to feed the processor which will involve loading the ore from the ROM stockpiles to trucks and hauling to the processing area.
• Reject material that is discarded during the processing phase will be temporarily stockpiled, loaded and hauled back to the open pit where it will be used for backfilling and rehabilitated.
• Ore will be processed within the MIA until a high purity vanadium pentoxide flake is produced.
• Product will be transported to Townsville by rail.
• Maintenance and servicing of plant and equipment will be undertaken at the MIA.
3.2.2 Mine Sequencing
The mine sequencing plan is to target the lowest strip ratio areas first. Figure 3.1 presents a layout of the mining sequencing plan. Table 3.1 presents the proposed schedule of materials to be handled over the life of the mine. As shown, there is an increasing general trend of the overburden removed while the amount of ore and rejects remain generally consistent from year 3 onwards. This is due to the increasing depth of the ore and the consequent additional overburden to be removed.
It has been assumed that the processing and mining plant will operate 24 hours per day throughout the year.
The life of the open cut mine is estimated to be 30 years, with the first 25 years of sequencing established. This assessment has only considered the mining of coquina units with a cut-off grade of 0.29% V2O5.
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Figure 3.1 Mine Sequencing Plan (cropped from Epic Environmental, BE180134.01 Rev 3, May 2020)
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Table 3.1 Indicative material handling quantities over the first 25 years of mine life
Year Topsoil removal (bcm) Overburden (bcm) Ore – ROM (bcm) Rejects (m3)
1 496,648 7,155,489 2,961,480 3,252,378
2 251,779 7,761,105 3,059,775 3,360,503
3 378,158 16,857,121 5,795,972 6,365,569
4 404,728 20,343,126 5,920,462 6,502,508
5 406,159 21,178,711 6,042,184 6,636,402
6 1,588,023 22,068,775 5,434,523 5,967,975
7 875,396 25,183,164 5,522,766 6,065,043
8 783,759 24,099,228 5,810,170 6,381,187
9 791,357 30,675,721 5,713,489 6,274,838
10 1,148,144 35,741,735 5,956,368 6,542,005
11 687,870 38,511,487 6,057,097 6,652,807
12 539,250 39,062,320 6,046,755 6,641,431
13 471,000 39,213,148 6,070,120 6,667,132
14 429,000 41,860,066 6,016,608 6,608,269
15 421,500 43,951,317 5,943,139 6,527,453
16 302,250 47,770,066 5,940,764 6,524,840
17 635,700 51,058,098 6,215,699 6,827,269
18 827,752 57,695,418 6,228,665 6,841,532
19 1,085,915 54,074,005 5,965,326 6,551,859
20 1,342,165 50,900,780 6,121,906 6,724,097
21 1,335,206 75,319,621 6,170,907 6,777,998
22 1,545,885 75,412,636 6,268,125 6,884,938
23 1,053,292 87,892,323 6,571,431 7,218,574
24 1,351,181 124,610,693 6,457,989 7,093,788
25 1,350,804 170,893,787 6,502,340 7,142,574
Source: Downer Mining (2018)
3.2.3 Choice of Modelling Scenarios
The major determinant of air quality impacts over the lifetime of the mine is the quantity of materials handled and the location of emission sources relative to the receptors. Estimated material handling quantities over the life of the mine are provided in Table 3.1.
Two mine scenarios have been considered as follows:
• Scenario 1: Year 6 mine site layout as shown in Figure 3.1 with Year 11 production rate.
• Scenario 2: Year 23 mine site layout as shown in Figure 3.2.
○ Scenario 2b: Scenario 2 with additional controls.
The two scenarios were chosen to represent the likely worst-case impacts at the nearest sensitive receptors A and B for the early life of the mine up to 20 years, and the late life after 20 years. The emission sources are anticipated to be closest to the nearest sensitive receptors A and B during year 6 and year 23 of the mine. Hence, these mining scenarios are considered worst-case and have been used in this assessment. As the quantities of materials handled for year 6 are relatively low in comparison to other years within 20 years of the life of the mine, the quantities of materials handled for year 11, which are typical but erring on the higher side of the quantities of materials, were used for scenario 1. The combination of the year 6 source locations with year 11 materials handled provides a worst-case scenario with a good balance between the proximity of emission sources to the sensitive receptors and amount of materials handled.
197401.0129.R01V09.docx 27
Similarly, year 23 was chosen for scenario 2 due to the proximity of the emission sources to the sensitive receptors and the median quantities of materials handled.
Figure 3.2 Scenario 1 (Year 6) Mine Site Layout Plan
5000 m
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Figure 3.3 Scenario 2 (Year 23) Mine Site Layout Plan
3.2.4 Mobile Plant and Production
The ore will be processed to produce high grade vanadium pentoxide (V2O5).
The proposed fleet for the open cut mining operations is presented in Table 3.2.
5000 m 5000 m
197401.0129.R01V09.docx 29
Table 3.2 Proposed Production Fleet
Equipment Model Scenario 1 Quantity
Scenario 2 Quantity
Application Annual Target Work Hours
Hitachi EX2600 Excavator (Backhoe)
2 2 Bulk waste and ore removal
5650
Caterpillar 785 Dump Trucks
7 to 13 7 to 13 Primary production – ore and waste
5000
Caterpillar D11 Carry Dozer
12 32 Primary production - waste
6250
Caterpillar D10 Dozer 2 2 Ore on run-of-mine (ROM) pad
6250
Caterpillar D10 Dozer 1 1 Pit and haul road establishment and
maintenance
6520
Caterpillar 854 Wheel Dozer
1 1 Pit and haul road establishment and
maintenance
4500
Caterpillar 14 Motor Grader
2 2 Pit and haul road establishment and
maintenance
4500
Kenworth 17kl Water Truck
2 2 Dust control 4500
Caterpillar 992 Wheel Loader
2 to 3 2 to 3 Rejects loading and general use
4500
Caterpillar 30 tonne Excavator
1 1 Drainage, clean-up 4200
John Deere Scraper 9570R/9620R
1 1 Topsoil removal 4500
Source: Wave International (2018) and Downer Mining (2018) except for scraper information which was provided by email.
3.2.5 Processing Plant
The processes involved will comprise of scrubbing and screening, cyclone sizing, rejects dewatering, flotation, flash drying, roasting, atmospheric leaching, filtration, solvent extraction or ionic exchange, desilication, ammonium metavanadate (AMV) precipitation, deammoniation, and product and waste handling.
Beneficiation
The beneficiation process includes a ROM feeder, scrubber, screening, cyclone sizing centrifuge and float and tailings thickener. The scrubber will liberate more vanadium into fine fractions. It will then be followed by a standard vibrating screen to further screen material for cyclone feed. The coarse rejects will be dewatered for easier transport of materials back to the pit.
Flotation
Further beneficiation of the product will be undertaken by a reverse flotation process where the vanadium grade is increased. The reverse flotation process works using a specific combination of flotation reagents (including a tailings thickener) to achieve optimal processing outputs. The material is then filtered, with the vanadium concentrate continuing onto the next stage of processing, with any rejected material transferred to the TSF. The vanadium concentrate will go through a flash dryer to remove water prior to roasting.
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Roasting
The dried concentrate will be roasted in a directly heated gas fired rotating kiln. No reagents or chemicals are used in the roasting process. The kiln will operate at a temperature of approximately 800°C with any vapours released through appropriate pollution control equipment (as recommended in Section 13.2.4) and then through an approximately 35 metre high stack.
Atmospheric Leaching
The concentrate is dispersed within four 900 m3 open air agitation tanks containing sulphuric acid (H2SO4), that will be enclosed within a structure to protect them from the elements. The flow of material is in sequence and movement is by gravity between tanks as the ore is leached. The duration of leaching is governed by the residence time required to put vanadium into solution.
Filtration
The slurry from the atmospheric leaching stage will then be filtered and the filter cake will be washed with water, repulped with material from the flotation concentrate, and discarded to the TSF for general waste. The filtrate will contain the NaVO3.
Concentration
The filtrate from the atmospheric leaching will be cooled and subjected to solvent extraction or ion exchange.
In the ion exchange process, metavanadate in the leachate will be adsorbed on the resin replacing hydroxide ions. Ammonium chloride solution will be added to the system whereby the ammonium ions react to form AMV product and the chloride ions will be removed by the resin. Caustic soda solution is used to regenerate the ion exchange columns.
Desilication
The solution will then be heated and pumped into a series of agitated tanks where aluminium sulphate will be added and pH adjusted to facilitate the removal of silica (SiO2). The precipitated silica will be filtered and the filtrate will be fed into the AMV precipitation unit.
AMV Precipitation
The AMV will be precipitated by the addition of ammonium sulphate (NH4)2SO4. The AMV slurry will then be thickened and pumped to a continuous belt filter where it will be washed with water. The filter cake will be fed into a flash dryer and the dried product will be transported into a bin prior to the de-ammoniator. The filtrate will be returned to the AMV thickener and the overflow fed into a barren storage and then the evaporator. The ammonium sulphate solution becomes concentrated in the evaporator. The sodium sulphate (Na2SO4) in the solution will crystallise and the slurry will be centrifuged to remove the crystals which will be dumped on the hazardous waste dump. The concentrated (NH4)2SO4 solution will be cooled and returned to the AMV precipitation.
Deammoniation
The deammoniator will be externally heated where the AMV will be thermally decomposed to produce V2O5 powder. The off gas will go through a cyclone and then a bag filter. The particles removed from the cyclone and bag filter will be returned into the deammoniator via a feed screw. The V2O5 from the deammoniator is fed into a fusion furnace.
Product Handling
In the fusion furnace, the V2O5 powder will melt and tap out of the furnace onto a rotating cooling wheel resulting in V2O5 flake. Coming off the wheel, the flake produced will be transferred to the final product bin
197401.0129.R01V09.docx 31
via a metal cooling conveyor into a product bin which feeds an automatic bagging facility, before being palletised, and loaded into containers for shipment to customers.
3.3 Construction and Commissioning
Prior to the operation of the project, ancillary facilities will be constructed at the MIA which will include (but not be limited to) the processing plant, offices, solar farm and rail siding. The TSF and evaporation pond will be constructed to the north of the MIA and stock route. The emissions from the construction phase will include dust emissions from clearing of land and material handling, and minor gaseous combustion emissions from mobile equipment. The emissions due to the construction activities are expected to be of similar nature, albeit minor in comparison to the mining operations emissions. The activities will also be short-lived and located relatively far from the sensitive receptors. Hence, emissions from these sources were not modelled in this assessment; however, risk of impacts from these activities has been assessed in Section 14.
3.4 Decommissioning and Closure
Closure of the project will include decommissioning of the facilities onsite. As with the construction activities, emissions will be of similar nature to the construction activities and are likely minimal in comparison to mining operations, will be short-lived and located relatively far from the sensitive receptors. During this phase, the emissions from mining and processing will also cease and the closure of the project will also include rehabilitation of the site which will involve revegetation of exposed areas and so will substantially reduce emissions. Emissions from these sources were not modelled in this assessment; however, risk of impacts from these activities has been assessed in Section 14.
3.5 Off-site Water Storage Facility
An off-site water storage facility (OWSF) will be constructed approximately 13 kilometres to the east of receptor D (Lindfield homestead). Figure 3.4 shows the location and layout of the OWSF. The OWSF will have a diversion channel which will divert water from the Flinders River. A river diversion pump station will transfer the diverted water to Cell 1 at a rate of 1,400 ML per day. The pump station energy will be supplied by four 1 MW diesel generators.
There will be four 40 hectare cells with a total capacity of 11,300 ML. The water from Cell 1 will be distributed to the other cells by gravity via pipelines and control gates upstream. To minimise evaporation, water surface area will be reduced by consolidating water from the other cells back to Cell 1 by means of an amalgamation outlet and channels.
From Cell 1, water is pumped to the mine at a rate of 13 ML per day.
3.5.1 Construction
The construction of the OWSF is anticipated to use the following equipment: excavators, scrapers, front-end loaders/dozers, moxies/dump trucks, mobile crane and fork lift. The construction activities would generate dust; however, this or any emissions would be substantially smaller in scale in comparison to the mining dust emissions. The area of the cells will be 40 hectares compared to the area of the mining lease being 8,882 hectares. Dust generated from the construction activities of the OWSF is not likely to cause discernible impacts at the nearest sensitive receptor 13 kilometres away. The closest construction activity from receptor D would be the pipeline works which would be approximately 4.7 kilometres away to the south-east at the nearest point. Dust emissions from the pipeline works would be relatively minimal and would be indiscernible at 4.7 kilometres away. Hence, the impacts from the construction activities have not been considered further in this report.
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3.5.2 Operation
The main air emission sources of the OWSF operation would be combustion gases from the 4 x 1 MW pump generators. These are substantially less than the 12 x 2 MW generators planned for the mine infrastructure area. These emissions are not likely to cause discernible changes to the air quality at the nearest sensitive receptor 13 kilometres away. Hence, these emissions have not been considered further in this assessment.
Greenhouse gas emissions from the pump generators have been included in Section 6.4.
3.5.3 Decommissioning
The OWSF and associated infrastructure will be decommissioned after approximately 30 years, or when mining activities have been completed and plant and structures decommissioned. The OWSF will be returned to current landform, unless an agreement is reached with the landowner for it to remain. The decommissioning activities would generate dust. The dust generated from the decommissioning activities of the OWSF is anticipated to be similar to those for construction, and as such is not likely to cause discernible impacts at the nearest sensitive receptor 13 kilometres away.
Figure 3.4 OWSF Location and Layout
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4. Air Quality Criteria
4.1 Relevant Pollutants
This section identifies and assesses the contaminants anticipated to be released from point and diffuse sources and fugitive emissions anticipated as a result of the Project. Quantitative details of these emissions are provided in Sections 11.6 and 11.8.
4.1.1 Particulates
The proposed project’s operation would result in the emission of particulates characterised as:
• total suspended particulate matter (TSP)
• particulate matter with equivalent aerodynamic diameters of 10 µm or less (PM10)
• particulate matter with equivalent aerodynamic diameters of 2.5 µm and less (PM2.5).
4.1.2 Gaseous Emissions
Anticipated emissions also include exhaust emissions from mobile equipment and stationary sources including power generation. From mining operations that apply standard control measures, combustion gases normally have substantially less air quality impact than particulates. Therefore, compliance with particulate criteria generally indicates compliance with criteria for gaseous pollutants. The modelling of mining operations has therefore been undertaken for particulate emissions. Dispersion of particulate and gaseous emissions from power generation has been modelled separately and includes the following species: acetaldehyde, benzene, carbon monoxide (CO), formaldehyde, oxides of nitrogen (NOx), PM2.5, PM10, polycyclic aromatic hydrocarbons (PAHs), sulfur dioxide (SO2), toluene and xylene.
Gaseous pollutants will also be emitted from processing operations onsite. Gaseous pollutants from processing operations are included in the emission inventory for the purpose of assessing whether dispersion modelling is required. The gaseous emission sources included in the emission inventory are:
• vapour emission of flotation reagent
• SO2, particulate and metals emissions from roasting ore
• H2SO4 mist emissions from the leaching tanks
• volatile organic compounds (VOCs) from evaporation of solvent used in solvent extraction
• ammonia (NH3) emissions from the deammoniation plant.
4.2 State Legislative Instruments
4.2.1 Queensland Environmental Protection Policy
The Terms of Reference for the impact assessment issued by the Queensland Department of Environment and Science (DES), identifies the relevant assessment criteria as the environmental values defined in the Environmental Protection (Air) Policy (EPP Air) (2008), which is now superseded by EPP Air 2019, under the Environmental Protection Act (1994).
The EPP Air provides objectives for air quality indicators (pollutants) that address health, the aesthetic environment, ecosystems and agriculture. The objectives relevant to this project and human health and wellbeing and aesthetic environment have been summarised in Table 4.1.
197401.0129.R01V09.docx 34
Table 4.1 Air Quality Criteria (EPP Air) for Health and Wellbeing
Air Quality Indicator Period Criteria (µg/m3)
PM2.5 1 day 25
1 year 8
PM10 1 day 50
1 year 25
TSP 1 year 90
vanadium in PM10 1 day 1.1
SO2 1 hour 570
1 day 230
1 year 57
benzene 1 year 10
CO 8 hour 11,000
formaldehyde 1 day 54
30 minutes (aesthetic environment) 110
nitrogen dioxide (NO2) 1 year 62
1 hour 250
benzo(a)pyrene (as a marker for PAHs)
1 year 0.0003
toluene 1 year 410
1 day 4,100
30 minutes (aesthetic environment) 1,100
xylene (total of all isomers) 1 year 950
1 day 1,200
arsenic and compounds 1 year 6 ng/m3
lead and compounds 1 year 0.5
manganese and compounds 1 year 0.16
nickel and compounds 1 year 0.02
Note that the EPP Air also contains a criterion for visibility reducing particles, but this is a measure of regional air quality and is not relevant to point sources. The impact of visible particles from point sources is addressed by the PM2.5 criteria.
4.2.2 National Environmental Protection (Ambient Air Quality) Measure
The EPP(Air) incorporates the goals nominated within the previous 2003 version of the National Environmental Protection (Ambient Air Quality) Measure (NEPM). The current NEPM dated February 2016 has multiple changes including the new standard and goals listed in Table 4.2. Exceedances of the particulate standard are no longer allowed apart from the exceptional events defined below.
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Table 4.2 New Standard and Goals in 2016 NEPM (Ambient Air Quality)
Air Quality Indicator Period Criteria (µg/m3)
PM2.5 goals for 2025 1 day 20
1 year 7
PM10 1 year 25
Notes: For the purpose of reporting compliance against PM10 and PM2.5 1 day average standards, jurisdictions shall exclude monitoring data that has been determined as being directly associated with an exceptional event (bushfire, jurisdiction authorised hazard reduction burning or continental scale windblown dust that causes exceedance of 1 day average standards).
These goals have not yet been adopted into the EPP(Air) so it is thus not clear how much reduction of existing background concentrations is expected to assist with achievement of the 2025 goals, and how much is to be achieved by restrictions on development. Thus, these goals have not been adopted for this assessment.
4.2.3 Department of Environment and Science (DES) Guideline
The Department of Environment and Science (DES) Guideline, version 4.03, (DES, 2019) for the Application requirements for activities with impacts to air suggested that a short-term (24-hour average) TSP concentration at the sensitive receptor of greater than 90 µg/m3 may cause dust nuisance and so has advised the assessment of the short-term (24-hour average) maximum TSP impact to be undertaken and compared against the trigger levels provided in the Good practice guide for assessing and managing the environmental effects of dust emissions (NZ Ministry for the Environment, 2016) as shown in Table 4.3. The most recent 24-hour average trigger level for a residential area is 60 µg/m3 which is more stringent than the annual average TSP criterion of 90 µg/m3. The NZ Ministry for the Environment guide clearly states that these trigger levels are not meant for regulatory compliance purposes but are only applicable to monitoring data and for the purpose of alerting the operators into potentially taking additional dust control measures when triggered. Hence, the current trigger levels are well below those that may impact onto receptors.
Table 4.3 Suggested 24-Hour Trigger Levels for TSP (NZ Ministry for the Environment, 2016)
Sensitivity of Receiving Environment High Moderate Low
Trigger Level (µg/m3) 60 80 100
Notes: 1. In general, all residential areas will be high sensitivity 2. For managing chronic dust only
4.3 Other State Legislation
The EPP Air does not contain criteria for NH3. Thus in this assessment, the NH3 criterion from the State Environment Protection Policy (Air Quality Management) of the Environment Protection Authority Victoria (VIC EPA, 2001) as presented in Table 4.4 has been used in this assessment.
Table 4.4 Air Quality Criteria (VIC EPA, 2001)
Air Quality Indicator Period Criterion (µg/m3)
NH3 3 minutes 600
acetaldehyde 3 minutes 76 (odour)
590 (toxicity)
H2SO4 3 minutes 33
4.4 Dust Deposition
Whilst there are no quantitative limits specified in legislation, there are guidelines designed to avoid nuisance caused by dust deposition fallout onto near horizontal surfaces.
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The Department of Environment and Science (DES 2019) suggests the guideline that deposited matter averaged over one month should not exceed 120 mg/m2/day (3.6 g/m2/month). For extractive industries, it is the insoluble component of analysed dust that is used.
It should be noted that these values are a guideline for the level that may cause nuisance at a sensitive receptor such as a residence or sensitive commercial land use. It is not normally necessary to achieve this level at the boundary, but boundary measurement can assist in the assessment of whether there is risk of nuisance occurring or not.
4.5 Summary of Relevant Pollutant Concentration Criteria
Table 4.5 Summary of Relevant Air Quality Criteria
Air Quality Indicator Period Criteria (µg/m3)
PM2.5 1 day 25
1 year 8
PM10 1 day 50
1 year 25
TSP 1 year 90
vanadium in PM10 1 day 1.1
SO2 1 hour 570
1 day 230
1 year 57
benzene 1 year 10
CO 8 hour 11,000
formaldehyde 1 day 54
30 minutes 110
NO2 1 year 62
1 hour 250
benzo(a)pyrene (as a marker for PAHs) 1 year 0.0003
toluene 1 year 410
1 day 4,100
30 minutes 1,100
xylene (total of all isomers) 1 year 950
1 day 1,200
arsenic and compounds 1 year 6 ng/m3
lead and compounds 1 year 0.5
manganese and compounds 1 year 0.16
nickel and compounds 1 year 0.02
NH3 3 minutes 600
acetaldehyde 3 minutes 76 (odour)
590 (toxicity)
H2SO4 3 minutes 33
dust deposition 30 days 120 mg/m2/day
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5. Greenhouse Gas Regulatory Requirements
5.1 National Greenhouse and Energy Reporting (NGER)
The legislative framework for a national greenhouse and energy reporting system is established via:
• the National Greenhouse and Energy Reporting Act 2007 (NGER Act)
• the National Greenhouse and Energy Reporting Regulations 2008 (NGER Regulations) as amended 1 March 2017
• the National Greenhouse and Energy Reporting (Measurement) Determination 2013 (NGER Determination) as amended 1 July 2017.
The NGER Technical Guidelines (Department of the Environment and Energy, 2017) provide additional guidance and commentary to assist in estimating greenhouse gas emissions for reporting under the NGER system. The emission factors used in these guidelines are consistent with those specified in the National Greenhouse Accounts Factors (Department of the Environment and Energy, 2019). The National Greenhouse Account Factors have no standing in relation to reporting under the NGER legislation; however, they are generally referred to as the current values to use.
The NGER Act makes reporting mandatory for corporations whose energy production, energy use, or greenhouse gas emissions meet certain specified thresholds. These thresholds are detailed in the NGER Regulations. Section 5.2 summarises the reporting thresholds.
The NGER Determination provides methods for the estimation and measurement of:
(1) greenhouse gas emissions
(2) the production of energy
(3) the consumption of energy.
Greenhouse gas emissions are defined in Section 2.23 of the NGER Regulation as follows:
(2) Emissions of greenhouse gas, in relation to a facility, means the release of greenhouse gas into the atmosphere as a direct result of one of:
(a) an activity, or series of activities (including ancillary activities) that constitute the facility (scope 1 emissions)
(b) one or more activities that generate electricity, heating, cooling or steam that is consumed by the facility but that do not form part of the facility (scope 2 emissions).
Coverage of scope 1 emission sources is given in Section 1.3 (4) of the NGER Determination by:
(a) fuel combustion, which deals with emissions released from fuel combustion
(b) fugitive emissions from fuels, which deal with emissions mainly released from the extraction, production, processing and distribution of fossil fuels
(c) industrial processes emissions, which deal with emissions released from the consumption of carbonates and the use of fuels as feedstock or as carbon reductants, and the emission of synthetic gases in particular cases
(d) waste emissions, which deal with emissions mainly released from the decomposition of organic material in landfill or wastewater handling facilities.
Scope 2 emissions are generally emissions that result from activities that generate power offsite for consumption onsite. The largest contributor to scope 2 emissions is consumption of electricity or steam.
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5.2 Reporting Thresholds
Section 13 of the NGER Act sets reporting thresholds for the operation of a facility or corporations, as per the following excerpts:
(1) A controlling corporation’s group meets a threshold for a financial year if in that year:
(e) the total amount of greenhouse gases emitted from the operation of facilities under the operational control of entities that are members of the group has a carbon dioxide equivalence of: ....
(iii) 50 kilotonnes or more; or ....
(c) the total amount of energy consumed from the operation of facilities under the operational control of entities that are members of the group is:
.... (iii) 200 terajoules or more; or
(d) an entity that is a member of the group has operational control of a facility the operation of which during the year causes:
i) emission of greenhouse gases that have a carbon dioxide equivalence of 25 kilotonnes or more; or
ii) production of energy of 100 terajoules or more; or iii) consumption of energy of 100 terajoules or more
Note that within a corporation, incidental facilities may be reported as percentages of the total or otherwise estimated as per the NGER Regulations as updated by the National Greenhouse and Energy Reporting Amendment (Streamlining Reporting) Regulation 2013.
5.3 Greenhouse Gases
Gases addressed by the NGER Regulations (Department of Climate Change, 2008a), are the six key greenhouse gases consistent with the Kyoto Protocol. These gases differ in their capacity to trap heat and contribute to the greenhouse effect. The capacity of each gas to contribute to global warming is referred to as its Global Warming Potential (GWP) relative to that of carbon dioxide. The GWP’s of the six Kyoto greenhouse gases are provided in Table 5.1.
Table 5.1 Global Warming Potential of Greenhouse Gases
Greenhouse Gas GWP
Carbon dioxide (CO2) 1
Methane (CH4) 25
Nitrous oxide (N2O) 298
Hydrofluorocarbons (HFC’s) 92 – 14,800
Perfluorocarbons (PFC’s) 7,390 – 12,200
Sulphur hexafluoride (SF6) 22,800
Note: Source is Department of the Environment and Energy (2019).
Because of the variation in GWP between different gases, the emission factors used to calculate greenhouse gas emissions from the project are stated in terms of carbon dioxide equivalents (CO2-e) and consider the various GWP’s of the different greenhouse gases.
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6. Greenhouse Gas Emissions
6.1 Methodology for Impact Assessment
The following data and assumptions were used in emission calculations:
• Fugitive gas emissions from the use of liquid fuels for the production fleet have been determined using Method 1 from the NGER Technical Guidelines (Department of the Environment and Energy, 2017).
• It is understood that there are no areas of vegetation to be cleared that have crown cover greater than 20%.
• The diesel combusted onsite by mobile fixed mining equipment is calculated using diesel consumption per overburden removed of 19 kL/Mbcm based from another mine.
• Water for the process and for dust suppression will be provided by an offsite water storage facility.
• Emissions from the processes are assumed to be not significant for the purposes of this assessment.
• Emissions resulting from the combustion of petrol are assumed to be insignificant for the purposes of this assessment.
• The processing plant will require 24 MW of electricity. It is currently proposed to generate this onsite using gas generators, in which case there will be no scope 2 emissions from consumption of purchased electricity from a grid.
• The maximum greenhouse gas emission for the mine is anticipated to occur in Year 25 of the mine as this represents the maximum amount of overburden removal and number of equipment in operation. Hence, the greenhouse gas emission of the project has been assessed using the Year 25 production and equipment schedules.
The mobile equipment anticipated to utilise diesel fuel are summarised in Table 6.1.
Table 6.1 Mobile Plant for Year 25
Equipment Type Make Model Quantity
Scraper Caterpillar 627 1
Hydraulic Excavator Hitachi Ex2600 2
Hydraulic Excavator Caterpillar (30 tonne) 1
Rear Dump Truck Caterpillar 789D 13
Track Dozer Caterpillar D11 65
Track Dozer Caterpillar D10 3
Motor Grader Caterpillar 14 2
Water Truck Kenworth (17kL) 2
Wheel Loader Caterpillar 992 3
Wheel Dozer Caterpillar 854 1
Train deliveries of supplies to the site and product from the site will also utilise diesel fuel. Total tonnage of materials hauled by train eastbound is 22,240 tonnes per year and westbound is 615,170 tonnes. For this assessment, only the Scope 1 greenhouse gas emissions from train operations within the site are included. The length of the rail within the site is approximately 7.29 km.
Other fixed or minor equipment may include integrated tool handler, crane, lighting plants, tyre handler and forklift.
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6.2 Emissions from Vegetation Clearing
It is understood that there are no areas of vegetation to be cleared that have crown cover greater than 20%. Thus, vegetation removal is not included in the inventory.
6.3 Process Gas Emissions
Greenhouse gas emissions from chemicals used in processing are anticipated to be negligible.
6.4 Liquid Fuel Combustion Emissions
Diesel fuel will be used primarily by mining equipment, fixed plant such as lighting rigs and pumps, and light vehicles. Power will likely be supplied by twelve 2 MW gas generators, with possible contribution from an installed solar system/farm. The worst case for greenhouse gas emissions is likely to be created by the gas generators, which will be fuelled by liquefied natural gas (LNG). LNG will also be used for the gas burner for the roaster kiln. Approximately 2,500 TJ per annum (1,246 TJ per annum or 49,243 kL of LNG per annum for power generation and 1,226 TJ per annum or 48,468 kL of LNG per annum for the roaster kiln) will be consumed for a production rate of 20,000 tonnes per annum.
The OWSF river diversion pumps require 4 MW of energy from 4 x 1 MW diesel generators. It will pump water at a rate of 1,400 ML per day. The mine supply pumps will transport water at a rate of 13 ML per day. The total energy requirement of both the river diversion pumps and the mine supply pumps would be 4,037 kW. The diesel requirement for these pumps would be 7,780 kL per year, which has been calculated based on the 550 L/h diesel consumption of a 2,500 kW booster pump quoted in the Sunshine Coast Airport Expansion Project EIS Appendix A5 (2014).
The diesel consumption of trains was calculated using the anticipated material tonnages eastbound and westbound, and assuming the empty weight of a train is 1,140 tonnes. A total of 184 trips per annum for the delivery of supplies and 8 trips per annum for product delivery are anticipated (Multicom Resources 2018). A fuel consumption rate of 0.0026 L/km/tonne was assumed for diesel locomotives (Connell Hatch, 2009). A diesel consumption rate of 20 kL per year was calculated for on-site travel.
Greenhouse emission factors for liquid fuel consumption are shown in Table 6.2. Note that the emission factors are per kilolitre of fuel.
Table 6.2 Liquid Fuel Greenhouse Gas Emission Factors
Fuel Type Energy Content
(GJ/kL) 1
Scope 1 Emission Factor
(kg CO2-e/GJ) 1, 2
GHG Emission Factor (tonnes CO2-e/ kL) 3
Diesel oil (stationary engine)
38.6 70.2 2.71
Diesel oil (general transport)
38.6 70.5 2.72
Diesel oil (heavy vehicles – Euro IV or higher)
38.6 70.01 2.70
LNG 25.3 51.53 1.56
Notes: 1. Energy content of fuel is sourced from Table 2 to Table 4 of Department of the Environment and Energy (2019). 2. Emission factors include contributions from CO2, CH4 and N2O. 3. GHG Emission Factor is the Energy Content multiplied by Scope 1 Emission Factor.
The greenhouse gas emission from fuel usage is calculated by multiplying the fuel consumption by the emission factor from the last column in Table 6.2. Table 6.3 below present the total fuel consumption and the resultant emissions, with a total greenhouse gas emission of 255 kt CO2-e from fuel combustion.
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Table 6.3 Fuel Combustion Emission Summary
Activity Total Fuel Consumed (kL) Emission factor
(t CO2-e/kL) 1
Total Emissions
(kt CO2-e)
Mobile plant diesel combustion
36,148 2.70 98
Fixed mining plant diesel combustion
3,263 2.71 9
OWSF water pump generators diesel
combustion
7,780 2.71 21
Train diesel combustion 20 2.72 0.06
LNG combustion 97,710 1.56 127
Notes: 1. Emission factors from Table 6.2.
6.5 Leakage Emissions from Storage and Transfer of LNG
Fugitive emissions from the LNG storage tank have been calculated using a typical loss rate of 0.05% of the total tank volume per day due to Boil Off Gas (BOG) from storage tanks (The LEVON Group, 2015). Five days supply of gas (approximately 1,338 kL or 33,864 GJ, see calculations below) will be stored on-site. Assuming a tank volume capacity margin of 20%, the tank volume would be 1,606 kL, which is equivalent to 40,637 GJ of LNG. The loss due to storage and transfer would be equivalent to (40,637 GJ x 0.0005 x 365 days) 7,416 GJ per annum.
Amount of LNG stored on-site (5-days supply):
2,472,074 𝐺𝐽
𝑎𝑛𝑛𝑢𝑚𝑥
1 𝑦𝑒𝑎𝑟
365 𝑑𝑎𝑦𝑠𝑥 5 𝑑𝑎𝑦𝑠 = 33,864 𝐺𝐽
33,864 𝐺𝐽 𝑥 1
25.3 𝐺𝐽/𝑘𝐿= 1,338 𝑘𝐿
Tank volume (assuming 20% capacity margin):
1,338 𝑘𝐿 𝑥 1.2 = 1,606 𝑘𝐿
Tank volume equivalent in GJ:
33,864 𝐺𝐽 𝑥 1.2 = 40,637 𝐺𝐽
Amount of LNG emitted due to leakage:
1,606 𝑘𝐿 𝑥0.0005
𝑑𝑎𝑦𝑥
365 𝑑𝑎𝑦𝑠
1 𝑦𝑒𝑎𝑟= 293 𝑘𝐿 𝑝𝑒𝑟 𝑎𝑛𝑛𝑢𝑚
293 𝑘𝐿
𝑦𝑒𝑎𝑟𝑥
25.3 𝐺𝐽
𝑘𝐿= 7,416 𝐺𝐽 𝑝𝑒𝑟 𝑎𝑛𝑛𝑢𝑚
Table 6.4 Natural Gas Leakage Summary
Fuel Type Energy Content
(GJ)
Scope 1 Emission Factor
(kg CO2-e/GJ) 1
Total Emissions
(kt CO2-e)
LNG 7,416 377.8 3
Notes: 1. Emission factor from 3.81A of the Department of Climate Change (2017b). The emission factor is based on Queensland LNG composition of approximately 95% methane and 5% CO2, resulting in contributions of 377 and 0.8 kg CO2-e/GJ respectively.
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6.6 Emissions from Exposure of Ore Body and Oil Shale
The top layers of the mining area are completely oxidised and have been leached of oil (Coxhell & Fehlberg, 2000). In addition, the materials excavated are shallow and relatively close to the surface. Hence, the exposure of the vanadium ore body is anticipated to result in negligible greenhouse gas emissions.
The vanadium-rich layer is within the oxidised layers above the fresh oil shale layer. The top of the fresh oil shale units will be briefly exposed during mining although rejects and fresh overburden will be placed on top following mining of each section. The fresh oil shale at the site is below 15 metres in depth, and has an average grade of 65 to 75 litres of oil per tonne (Coxhell & Fehlberg, 2000). There has been no literature found regarding emissions of greenhouse gases from exposure of ore body or oil shale units from shallow open cut mining; however, the subsequent information regarding oil shale provides a basis for determining the likely greenhouse gas emissions from exposure of oil shale.
“The Julia Creek oil and vanadium rich shale is located within marine sediments of the Early Cretaceous Tollebuc Formation” (Coxhell & Fehlberg, 2000). Oil shale is a sedimentary rock which contains solid, combustible organic matter called kerogen in its mineral matrix (Siirde et al, 2013). Oil shale is a thermally immature source rock which has not generated and expelled hydrocarbons (Bradshaw et al, 2012). It is generally in the deeper, more mature sections where the conditions are suitable for oil generation, similar with shale gas. Hence, oil shale had to be mined, crushed and subjected to high temperature through pyrolysis to produce oil by chemical destruction of kerogen (Siirde et al, 2013).
Kerogen is capable of storing carbon dioxide and to a lesser degree methane, however this typically happens deep underground where there is higher pressure (Sherifa & Reza, 2018). Methane has been detected in mudlogs across most the Toolebuc Formation deeper than 300 metres below ground level (Troup et al, 2018). Butane and pentane have been detected at greater than 600 metres below ground level (Troup et al, 2018). Higher concentrations were generally detected at deeper sections of the formation where maturity is higher (Troup et al, 2018).
Based on the above information, it is likely that any greenhouse gas emissions from the exposure of oil shale units to 40 metres below ground level will be negligible. In addition, progressive backfill and rehabilitation will be undertaken, which will minimise exposure duration of the oil shale units.
6.7 Summary of Greenhouse Gas Emissions
Based on the emission calculations, the major source of greenhouse gas emissions is the LNG fuel combustion for onsite power generation and the roaster kiln gas burner. The annual scope 1 emissions from the Project are estimated to be 258 kilotonnes CO2-e. A summary of the emissions breakdown is presented in Table 6.5.
Table 6.5 Greenhouse Gas Emissions in Year 25
Activity Total Annual Emissions (kt CO2-e)
Scope 1 Processing gas emissions 0
Scope 1 Equipment and power generation fuel combustion 255
• Mobile plant diesel combustion • 98
• Fixed mining plant diesel combustion • 9
• OWSF water pump diesel combustion • 21
• Train diesel combustion • 0.06
• LNG combustion • 127
Scope 1 Fugitive emission from LNG storage and transfer 3
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Activity Total Annual Emissions (kt CO2-e)
Scope 1 Fugitive emission from ore body and oil shale 0
Scope 1 Vegetation cleared 0
Scope 2 Grid electricity consumption 0
Total 258
The total scope 1 and scope 2 greenhouse gas emissions in 2017 - 2018 from Australian corporations that had to report to NGER was 423 Mt CO2-e (Clean Energy Regulator 2020). The total emissions in 2017 from Queensland under the Kyoto Protocol Accounting Framework were 161 Mt CO2-e (Department of Industry, Science, Energy and Resources, 2020), of which 28 Mt CO2-e from Queensland mines. Based on the sum of the totals from each activity, emissions from the operation of the mine would be 258 kt CO2-e or 0.061% of Australian NGER emissions and 0.16% of Queensland emissions, and 0.9% of Queensland mining emissions.
The Queensland and Australia greenhouse gas emissions for the five most recent years with available data are presented in Table 6.6. The annual change in greenhouse gas emissions for Queensland ranges from - 4125 kt CO2-e to 3247 kt CO2-e from 2013 to 2017. For Australia, the annual increase ranges from 1134 kt CO2-e to 6894 kt CO2-e from 2014 to 2018. The project’s anticipated greenhouse gas emission is within the range of the annual change of the Queensland emissions from 2013 to 2017, and is a fraction (7% of the average) of the annual change of the Australia emissions from 2014 to 2018. The contribution of the project would not cause an atypical increase to the state and national greenhouse gas inventories.
Table 6.6 Queensland and Australia Greenhouse Gas Emissions
Year Queensland Emission
(kt CO2-e) 1
Queensland Emission Increase from Previous
Year (kt CO2-e)
Australia Emission (kt CO2-e) 2
Australia Emission Increase from Previous
Year (kt CO2-e)
2018 (unavailable at the time
of writing this report) - 423357 3537
2017 161201 3247 419820 1134
2016 157954 -151 418686 2988
2015 158104 3110 415698 6894
2014 154995 -4125 408803 -
2013 159120 - - -
Sources: 1. Department of Industry, Science, Energy and Resources (2020) 2. Clean Energy Regulator (2020)
6.8 Recommendations for Mitigation Measures
Best practice measures for reducing greenhouse gas emissions from mining have been published by Environment Australia (2002) and include the following:
• Energy audits are to provide a breakdown of energy use by activity, profiles of energy load across key plant items, analysis of energy efficiency initiatives, trending of energy usage over time and addressing energy usage in procedures.
• Training should be provided to all staff in energy management specific to their roles.
• Less greenhouse intensive fuels for vehicles should be considered.
• Reducing haulage emissions by using conveyors or in-pit crushing.
• Appropriate design of water management systems to minimise consumption and pumping can have substantial savings in energy consumption as can use of variable speed drives on large pumps.
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• Appropriate choice of crushing method is critical. It is recommended that optimising feed size into mills be a priority in the design and purchasing of the primary and secondary crushers.
• Air leaks account for most of the energy loss in compressed air systems.
Other measures considered are:
• Use large haul trucks where practical, provided they will be taking full loads. This has potential for substantial reductions in diesel consumption.
The recommended measures to minimise greenhouse gas emissions from the project are in the following subsections.
6.8.1 Equipment and Energy Efficiency
(1) Include energy efficiency as a criterion when selecting diesel and electric powered motors and other equipment for purchase, for example variable speed drive pumps for the OWSF and processing plant. This has potential for substantial reductions in electricity demand.
(2) Where practical use biodiesel for mobile plant. This has potential for substantial reductions in net greenhouse gas emissions.
(3) Install light sensitive switches and motion sensors to switch on lighting throughout the project site where practical and safe. This has potential for small reductions in electricity demand.
(4) Large haul trucks are to be used, as these decrease diesel consumption by reducing the number of trips.
6.8.2 Mine Planning
(5) Design pit and dump haul roads and ramps to limit the travel time and duty cycle for both waste and ore trucks especially when fully loaded.
(6) Minimise vegetation clearing. This has potential for small reductions in emissions due to decay of vegetation.
(7) Where practical reuse vegetation that has to be cleared as timber product or mulch for rehabilitation. This has potential for small reductions in emissions due to decay of vegetation.
(8) Vegetation buffers could be established in the direction of the nearest sensitive receptor and the highway, using mulch from cleared vegetation.
(9) Rehabilitate the land as soon as practical. The subsequent growth of vegetation would provide an offset sink for CO2.
6.8.3 Mine Operations
(10) Use production monitoring systems and payload management to maximise the loads of each bucket dug by excavators and each load carried by trucks. This will eliminate unnecessary bucket pass and truck hauls.
(11) Use production monitoring systems to minimise fuel burn rates and reduce the time when trucks are idling.
(12) Use remote or mobile crib huts and in-pit parking so trucks can be left at the work sites.
(13) Maintain equipment to retain energy efficiency. This has potential for reductions in electricity demand.
(14) Compact haul roads to minimise rolling resistance. This has potential for reductions in diesel consumption.
(15) Recycle water in the processing operations to reduce off site pumping requirements at the OWSF.
(16) Undertake regular checking of compressed air tubing to reduce leaks. This has potential for substantial reductions in electricity demand.
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(17) Provide training for operators of mobile plant in how to minimise fuel consumption, including no unnecessary idling.
(18) Where suitable, use local personnel to reduce transport emissions. This has potential for reductions in transport fuel consumption.
(19) As far as practical, obtain construction materials and ongoing consumables from local suppliers to reduce fuel consumption.
6.8.4 New Technology
(20) Investigate development of autonomous systems for hauling. This has the benefit of reducing truck weight by removing personnel support structures.
(21) Consider use of solar energy and other clean energy sources, including using solar panels to extend battery life at workshops, diesel lighting plant and at remote monitoring and control stations.
6.8.5 Management Systems
(22) Following completion of annual reporting, undertake an internal energy audit and energy mass balance to ensure that the activities are using best practice for minimisation of energy consumption.
(23) Complete a Mine Energy Management System for the mine.
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7. Regional Climate
The Saint Elmo mining lease is located in north Queensland approximately 535 kilometres inland west-southwest from Townsville. The climate class nominated by the Bureau of Meteorology (2018) for this area is grassland with a hot climate and winter drought.
7.1 Weather Stations
A search of the Bureau of Meteorology’s weather station directory has revealed that the nearest rain gauge and the nearest public weather station to the site was at Julia Creek Post Office approximately 14 kilometres to the southwest of the site. The rain data were collected from 1912 to 2011. Wind data were recorded from 1948 to 2002 and temperature and humidity data were collected from 1965 to 2002.
The nearest rain gauge and the nearest public weather station that is currently operating is at Julia Creek Airport approximately 17 kilometres to the southwest of the site. The rain gauge was installed in 2002. Wind, temperature and humidity data have been collected since 2001.
7.2 Existing Wind Records
Seasonal wind roses derived from Julia Creek Airport data from December 2011 until February 2018 are provided in Figure 7.1 to Figure 7.4.
Figure 7.1 Wind Rose for Summer
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Figure 7.2 Wind Rose for Autumn
Figure 7.3 Wind Rose for Winter
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Figure 7.4 Wind Rose for Spring
7.3 Existing Temperature and Rain
Long-term weather and climate data from the Julia Creek Airport weather station (site number: 029058) are summarised in Table 7.1.
Table 7.1 Climate Statistics for Julia Creek Airport for years 2001 to 2020
Month Mean Daily Maximum
Temperature (°C)
Mean Daily Minimum
Temperature (°C)
Mean Monthly Rainfall (mm)
Highest Monthly
Rainfall (mm)
Lowest Monthly
Rainfall (mm)
Jan 37.7 24.1 130.2 572.6 12.8
Feb 37.1 23 109.9 482 2.6
Mar 36.4 21.3 76.9 290.8 0
Apr 34.4 17.8 12.4 113.2 0
May 30.7 13.6 8 69.8 0
Jun 27.1 9.9 16.1 147.2 0
Jul 27.5 9.0 8.5 104.6 0
Aug 29.6 9.7 3.8 19.2 0
Sep 34 14.4 2.9 23 0
Oct 37.5 18.5 10.1 62.6 0
Nov 39.1 21.8 27.7 66 0.2
Dec 39.9 23.9 56.7 166.2 4
Annual 34.2 17.3 455.7 857.6 220.6
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7.4 Potential Future Changes to Climate
Future climate patterns may differ from the existing data due to global warming or other trends. The important parameters for dispersion are wind speed and direction, rain & humidity, and the frequency of elevated temperature inversions.
7.4.1 Wind
Prevailing wind patterns are determined by regional topography and land-sea interface, so it is unlikely that in the foreseeable future, these patterns will change even with global warming; however, to allow for minor fluctuations in wind patterns, contours can be smoothed to remove inward curves when recommending buffer zones.
Research into predicted changes in wind patterns due to climate change have been focussed on strong winds, with an increase in frequency of events. This could lead to increased wind-blown dust.
7.4.2 Rain & Humidity
Predicted changes in rainfall in North-West Queensland due to climate change are shown in Table 7.2. If rainfall reduced, more water would be required for dust suppression or dust emissions would increase. Reduced rain and humidity would also cause a minor reduction in wet deposition of particles.
Note that the Queensland government approach is to allow for a +25% increase in rainfall intensity when designing projects.
Table 7.2 Annual Rainfall Change Projections for North-West Queensland (Percentage Change)
Emissions Scenario
Projections for 2030 [Range – 5th to 95th percentile (median
change) %]
Projections for 2050 [Range – 5th to 95th percentile (median
change) %]
Projections for 2070 [Range – 5th to 95th percentile (median
change) %]
Low Emissions (RCP 4.5) -11 to +10
(-2)
-14 to +14
(-1)
-26 to +12
(-3)
High Emissions (RCP 8.5) -19 to +13
(-3)
-24 to +18
(-0)
-24 to +19
(+1)
Notes:
1. Source: Queensland Government (2019)
2. RCP is Representative Concentration Pathways. RCP 4.5 assumes reduction in greenhouse gas emissions. RCP 8.5 assumes business as usual or no curbing of greenhouse gas emissions
7.4.3 Elevated Temperature Inversions
When temperature inversions are elevated above the ground at heights of 100 or 200 metres, a mixing layer is formed underneath and trapping of emissions within this layer can occur. This occurs most commonly in the mornings.
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8. Meteorological Modelling
8.1 TAPM Meteorological Modelling
8.1.1 TAPM Fundamentals
The meteorological component of The Air Pollution Model (TAPM) was used to provide wind fields over the region. Wind speed and direction data from the nearest continuous monitoring station were assimilated into the model as described in Section 8.1.3.
The databases required to run TAPM are provided by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) and include global and Australian terrain height data, vegetation and soil type datasets, sea surface temperature datasets and synoptic scale meteorological datasets.
The Australian terrain data are in the form of 9-second grid spacing (approximately 0.3 kilometres) and is based on data available from Geosciences Australia. Australian vegetation and soil type data are on a longitude/latitude grid at 3-minute grid spacing (approximately 5 kilometres) and is public domain data provided by CSIRO Wildlife and Ecology.
The synoptic scale meteorology dataset used is a six-hourly synoptic scale analysis on a longitude/latitude grid at 0.75 or 1.0-degree grid spacing (approximately 75 kilometres or 100 kilometres). The database is derived from US NCEP reanalysis synoptic product.
TAPM dynamically fits the gridded data for the selected region to finer grids including the influences of terrain, surface type and surface moisture conditions. It produces detailed fields of hourly estimated temperature, winds, pressure, turbulence, cloud cover and humidity at various levels in the atmosphere as well as surface solar radiation and rainfall.
8.1.2 TAPM Configuration
The year 2017 has been used as discussed in Section 8.1.3.
TAPM was setup using four nested 30 x 30 grids centred on latitude 20°33’ south, longitude 141°51’ east, which are coordinates within one kilometre of the source. The four nested grids were as follows:
• 900 km x 900 km with 30 km resolution
• 300 km x 300 km with 10 km resolution
• 90 km x 90 km with 3 km resolution
• 30 km x 30 km with 1 km resolution
Thirty (30) vertical levels were used with lower level steps at 10, 25, 50, 75 and 100 metres up to 8 kilometres in altitude. This is greater than the normal number of vertical layers in order to provide better resolution of vertical layers. Boundary conditions on the outer grid were derived from the synoptic analysis. Non-hydrostatic pressures were ignored due to the gentle terrain and moderate resolution.
8.1.3 Observational Data Assimilation
Meteorological data from the BoM Julia Creek Airport station, located approximately 17 kilometres south-west from site, were available for assimilation into the model run. The percentage of wind conditions in each wind speed category of the five most recent years are presented in Table 8.1.
As shown in Table 8.1, the year 2017 at the Julia Creek Airport station experienced typical wind speed conditions, and more importantly near-calm and light-wind conditions. These conditions are critical for this assessment as the sources are at ground level and hence higher proportion of near-calms will lead to more conservative results. Hence, the year 2017 was used.
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Table 8.1 Percentage of Wind Conditions in Each Wind Speed Category
Year Calm (0-0.5 m/s) (%) 0.5 – 1.5 m/s (%) 1.5-3 m/s (%) 3-5 m/s (%) > 5 m/s (%)
2017 1.9 6.3 20.5 44.2 27.2
2016 3.1 8.1 26.4 38.9 23.1
2015 0.8 4.3 18.8 43.2 32.7
2014 1.0 4.9 21.3 43.1 29.0
2013 0.7 4.7 21.2 44.5 28.8
Average 1.5 5.7 21.6 42.8 28.2
Meteorological data from the BoM Julia Creek Airport station for the period from 1 January to 31 December 2017 was available for assimilation into the model run. ASK has analysed data from the BoM Julia Creek Airport station. A wind rose of this data is shown in Figure 8.1. TAPM was run without assimilation of this data and the wind rose for the same period is shown in Figure 8.2. The two wind roses show a very similar pattern except TAPM predicted a slightly lower proportion of calm conditions and higher proportion of light wind conditions and winds from the north-east quarter.
Figure 8.1 Wind Rose of BoM Julia Creek Airport Weather Station Data
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Figure 8.2 Wind Rose from TAPM for same Period as Julia Creek Airport Station Data
Statistical parameters were calculated to determine the relative agreements between data from the BoM Julia Creek Airport station and the TAPM prediction, and are presented in Table 8.2. As shown, the Index of Agreement values are > 0.6 meaning there is good agreement between the datasets. Therefore, the observational data from the Julia Creek Airport station were included into the TAPM model for generating data for the project. Assimilation of data from the BoM Julia Creek station was modelled with a radius of influence of 30,000 metres and a data quality of 0.31, which allows for a gradual blending of the two datasets near the limit of the radius of influence.
Table 8.2 Statistical Agreement Between the Data from the BoM Julia Creek Station and TAPM
Statistical Parameter Wind Speed u-Component of Wind Speed v-Component of Wind Speed
Root Mean Square Error (RMSE)
1.13 1.12 1.57
Index of Agreement 0.66 0.75 0.85
8.1.4 TAPM Validation
The TAPM GIS visualisation tool was used to examine the final windfields generated by the model. The last few hours of the year were reviewed to ensure the model completed the run correctly. The windfields in the inner grid throughout the month of June were examined in detail to understand the local wind patterns, influence of topography, and to ensure that the data assimilation had progressed smoothly. The following patterns were observed:
• Topography within the domain was not sufficiently complex to substantially influence wind conditions.
• Wind in the vicinity of the observational station was generally consistent with the remainder of the inner grid.
• Winds were generally strong south-easterlies although at times were moderate at night and in the early mornings.
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8.2 Topography and Land Use
For the purpose of providing topographic data for the detailed modelling, the coordinates of a rectangular grid representative of the area around the proposed site were derived using WGS84 coordinates from Google Earth Professional. The south-west corner coordinates were (574604, 7713423), north-east corner coordinates were (602604, 7741423) and the grid interval was 400 metres.
The WGS84 and GDA94 grids are identical to an accuracy of less than one metre. All coordinates in this report are rounded off to the nearest metre and are valid for both coordinate grids.
Gridded topographic data for Calmet was created using Global Mapper to process data from Geosciences Australia using the Kriging method. The terrain data used was Shuttle Radar Topography Mission (SRTM) elevations on a 1-second grid (approximately 30 metre spacing) using the Digital Elevation Model (DEM) 1.0 data which is the raw data.
The land use and topography in Calmet are shown in Figure 8.3 and Figure 8.4.
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Figure 8.3 Terrain in the Calmet Model
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Figure 8.4 Land Use in the Calmet Model
8.3 Calmet Modelling Configuration.
The Calmet configuration used is consistent with NSW OEH guidance (TRC 2011).
The model was run over the full year of 2017 based on a 3-dimensional grid produced using the Caltapm utility program to convert TAPM data to MM5 format suitable for Calmet to read. The Calmet grid was set to grid spacing of 400 metres and 70 by 70 grid points. Twelve vertical layers were modelled with cell face heights of 0, 20, 40, 80, 160, 300, 450, 650, 900, 1200, 1700, 2300, and 3200 metres above ground level. This is greater than the normal number of vertical layers in order to provide better resolution of vertical layers.
Mixing height calculation parameters were set to default values with the exception of the minimum overland mixing height, which was lowered to 25 metres to accommodate the influence of low mixing heights on ground level sources, considering that the surface roughness in this area is low. The maximum mixing height was set to 3000 metres. Temperature prediction parameters were set to default.
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Divergence minimisation was used. The critical Froude number was set to 1. Slope flow effects were included. The radius of influence of terrain features was set to 7 kilometres being approximately half the distance between ridges.
The output from Calmet was a three dimensional grid of wind-field data for incorporation into Calpuff.
8.4 Calmet Results
The frequency distributions of occurrences of winds for each direction sector and for each wind class (wind rose) as generated by Calmet are illustrated in Figure 8.5. This shows predominant winds from the south-east quarter.
Figure 8.5 Wind Rose for Saint Elmo Mining Lease
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Figure 8.6 and Figure 8.7 show, respectively, the frequency of stability classes throughout the day, and the variation of mixing height throughout the day.
Day time conditions are either neutral or unstable, whilst night time conditions are stable. Modelling of emissions will therefore consider this high proportion of stable conditions, which may lead to poor dispersion of ground level or downwashed emissions, whilst maintaining height on elevated emissions not subject to downwash. Structural downwash will therefore be important in the dispersion modelling.
At the project site, there is an unusually high frequency of E class stability. The frequency of F class stability is lower than typical. Overall there is a higher frequency of stable conditions than nearer the coastline.
Figure 8.6 Diurnal Frequency of Stability Classes
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In the morning, the mixing height rises gradually reaching an average of approximately 1.9 kilometre by the afternoon, then reforming at ground level again at nightfall.
The maximum has an unusual peak at 9am. The 99th percentile mixing height at 9am was 1442 metres, which is similar to the maxima at other times. The median at 9am follows the regular pattern. Hence this is unlikely to influence the modelling of anything other than tall stacks.
Figure 8.7 Prediction of Mixing Height from Calmet Model
It shows mixing layer heights are commonly 80 to 300 metres above ground during the hour ending 6am, and 90 to 330 metres above ground in the hour ending 7am.
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9. Monitoring Method
9.1 Overview
Monitoring of background air quality was undertaken at one location within the mining lease boundary as shown in Figure 9.1.
Figure 9.1 Air Quality Monitoring Location
Osiris Monitoring Location
5000 m
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Figure 9.2 Photo of Monitoring Set-up (Looking to the South)
The monitoring undertaken at the location included the following parameters:
○ TSP
○ PM10
○ PM2.5
○ particulate matter less than one micron in diameter (PM1)
○ wind speed
○ wind direction.
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9.2 Pollutant Monitoring Methodology
The purpose of this monitoring was to assist with derivation of appropriate values representing the background air quality at the site. Since 240 volt main power was not available, the choice of instruments was limited to those that can work from a solar panel.
Osiris Environmental Dust Monitors (serial numbers 2387 calibrated on 06 September 2017 and 20 May 2019, and 2118 calibrated on 29 June 2018) were used for particulate measurement within the mining lease boundary at the same location. The Osiris uses a light scattering technique to determine the concentration of airborne particles and dust in a size range. The air sample is continuously drawn into the instrument by a pump with a flow rate set by a micro processor. The incoming dusty air passes through a laser beam in a photometer and then through a filter to remove the particles before reaching the pump. The light is scattered by the individual particles of dust and is converted into an electrical pulse which is proportional to the size of the particle.
The Osiris analyses only the light scattered through 10 degrees or less, which is the diffracted component and depends only on the size of the particle irrespective of its material composition. Other light-scattering photometers detect light refracted or reflected through wider angles such as 90 degrees, which is also dependent on the type of particle, as a white particle will reflect more light than a black particle of the same size. In addition, the Osiris uses a scattering volume of less than 0.1 µL, allowing it to analyse the intensity of light scatter by each individual particle. Hence it counts and sizes individual particles.
It is important to note, that while light-scattering instruments such as the Osiris are not currently covered by Australian Standard methods and is not currently considered a compliance monitor, the instrument does provide a good indication of the ambient dust concentrations for a projects area and surrounds. Equivalence tests of Osiris instruments have previously been undertaken using high volume air samplers (HVAS) (Ecowise Environmental, 2007) and with a tapered element oscillating microbalance (TEOM) and a beta attenuation monitor (BAM) (Access Macquarie Ltd, 2011). In both studies, the measured levels from the various Osiris instruments used correlated well with each other with coefficient of correlation, r2, ranging from 0.98 to 1.00 and a linear slope between 0.91 and 1.1 (Ecowise Environmental, 2007 and Access Macquarie Ltd, 2011). The 24-hour average TSP and PM10 measurements between the Osiris and HVAS also returned a good correlation with an r2 of 0.97 (Ecowise Environmental, 2007). The 24-hour average PM10 measurements between the Osiris and TEOM produced relatively moderate correlation with an r2 of 0.67 (Access Macquarie Ltd, 2011). The linear correlation in that study being forced to zero (i.e. y-intercept=0) may have likely contributed to a poorer correlation. The correlations between the measurements from Osiris instruments and Australian Standard methods being relatively moderate to good show that the Osiris can provide a good indication of ambient dust concentrations.
The Osiris monitor was setup to log particulate concentrations with a 15 minute sampling interval. The monitoring included the following periods:
• Monitoring using the Osiris (serial number 2387) was undertaken onsite from 23 May 2018 to 13 June 2018. The monitoring setup onsite relied solely on solar power due to the absence of a mains power source. Due to faster battery drain than anticipated overnight, the monitor had not run 24 hours per day and was generally off during night time.
• For the same reason, the monitor had failed to automatically turn on from 13 June 2018 to 31 July 2018, and as a result there is a gap in the data until a larger new solar panel and battery system were installed along with a replacement Osiris (serial number 2118 calibrated on 29 June 2018). This continued monitoring until 25 June 2019; however, the Osiris did not record data from 6 February to 26 March 2019 as the solar panel had blown over and pulled the battery leads loose, resulting in loss of power to the Osiris due to a severe storm and major flooding event in the area. On 25 June 2019, the measured data had dropped to very low values continuing to record PM10 results mostly less than 1 µg/m3 until 4 July 2019. These values were removed from the data to be conservative. Post-monitoring calibration of this Osiris was within the acceptable range.
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• The recalibrated Osiris (serial number 2387) was returned to site for the final period of background monitoring from 4 July until 26 August 2019.
9.3 Monitoring Results
The wind rose for the monitoring period as measured by the wind cup and vane on the Osiris (2387) is shown in Figure 9.3. The winds during the monitoring period are predominantly from the south-southeast and south which are similar to the typical south-easterly winter winds at the Julia Creek Airport (shown in Figure 7.3). There was low frequency (3%) of calm conditions. It should be noted that the wind data generally do not include night time conditions.
Figure 9.3 Wind Rose from the Osiris Monitor (Serial Number 2387)
The wind rose for the monitoring period as measured by the wind cup and vane on the Osiris (2118 and 2387) is shown in Figure 9.4. The winds during the monitoring period are predominantly from the south. There was higher frequency (8%) of calm conditions.
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Figure 9.4 Wind Rose from the Osiris Monitor (Serial Number 2118 and 2387)
The 24-hour average concentrations for the measured particulates within the monitoring period are presented in Table 9.1. Based on the average and 70th percentile 24-hour average concentrations, the concentrations in the vicinity are generally low; however, the recorded maximum 24-hour average concentrations indicate that there are occasions when the concentrations reach very high levels. The three highest 24-hour averages corresponded to high peaks at the Mount Isa monitoring station indicating the cause was regional dust storms.
The monitoring data to date may not be representative of the whole year.
Table 9.1 Measured 24-Hour Average Particulate Concentrations
Rank TSP (µg/m3) PM10 (µg/m3) PM2.5 (µg/m3) PM1 (µg/m3)
Osiris 2387 (23/05/2018 – 12/06/2018) (not including night time)
Maximum 17.8 10.1 5.9 3.4
Average 9.9 6.0 2.8 1.3
70th Percentile 10.5 6.4 3.2 1.5
Osiris 2118 and 2387 (01/08/2018 – 26/08/2019)
Maximum 215.7 138.5 61.2 16.3
Average 11.2 7.1 3.4 1.5
70th Percentile 9.4 6.0 3.5 1.7
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9.4 Dust Deposition Monitoring
Dust deposition gauges were installed at the sensitive receptors identified in Section 2.2 from June 2018.
Table 9.2 Measured Deposited Dust Levels (mg/m2/day)
Date Saint Elmo (near the homestead)
Saint Elmo (near the front of the property)
Argyle Burwood
June 13 11 20 37
July 4 8 6 16
August 13 10 13 37
September 7 7 14 59
October 28 14 31 17
Maximum 28 14 31 59
Average 13 10 17 33
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10. Existing Air Quality
10.1 Overview
Based on the rural nature of the regional area, it is expected that the air quality for the study area would be acceptable for the foreseeable future with possible exceptions including dust and particulates. The existing air quality would be influenced by wind-blown dust, sporadic traffic on unsealed roads as well as bushfires and controlled burning activities in the region.
Monitoring data from similar locations have been used to represent the existing background. The estimated background concentrations have not been included in the modelling runs but are provided with the results so that the cumulative impact can be compared to criteria. In the absence of continuous monitoring data, it is recommended (Victoria 2001) to use the 70th percentile as a background concentration for dispersion modelling.
The nearest location to the site with publicly available data is The Gap (Mount Isa) monitoring station operated by Department of Environment and Science (DES).
Historical reports of the DES data do not provide the 70th percentile. Recently data from 2010 has become freely available on the Queensland Government data website (https://data.qld.gov.au).
As discussed in Section 2.3, no other substantial sources of pollutants are anticipated in the vicinity.
10.2 DES The Gap (Mount Isa)
The DES ‘The Gap’ monitoring station is the closest monitoring station located approximately 130 kilometres west of the project. The monitoring station was established in 2009 and is located close to an operating mine and a large metal smelter and so the pollutant concentrations at this station is considered conservatively high for this project. Table 10.1 shows the PM10 and SO2 concentrations over the available period from 2010.
Table 10.1 Concentrations Recorded by the DES The Gap Station
Year
70th percentile 24-hour average
PM10 concentration
(µg/m3)
Annual average PM10
concentration (µg/m3)
70th percentile 1-hour average SO2
concentration (µg/m3)
70th percentile 24-hour average
SO2 concentration
(µg/m3)
Annual average SO2
concentration (µg/m3)
2010 10 9 0 2 9
2011 19 18 3 4 13
2012 22 19 3 3 11
2013 25 23 0 5 13
2014 22 20 3 6 10
2015 21 19 3 5 11
2016 19 17 3 7 12
2017 20 18 0 6 12
2018 25 24 3 3 10
Average 1 22 20 2 4 11
Note: 1. The measured concentrations for 2009 were not included in the calculation of the average as the concentrations were substantially lower than all the other years and so were considered outliers.
Based on a typical ratio of PM10 to TSP around Australian mines being 0.39 (ACARP, 1999), the annual average TSP was estimated as 51 µg/m3. Based on an assumed PM2.5 to PM10 ratio of 0.25, the background 24-hour
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average PM2.5 concentration was estimated as 5.5 µg/m3 and the annual average PM2.5 concentration as 5 µg/m3.
In the two equivalence test studies of the Osiris instruments discussed in Section 9, the following 24-hour average PM10 correlations were determined as follows:
𝐻𝑉𝐴𝑆 24ℎ 𝑃𝑀10 = 0.7688 (𝑂𝑠𝑖𝑟𝑖𝑠 24ℎ 𝑃𝑀10) + 6.4340 µg/m3 (Ecowise Environmental, 2007)
𝑇𝐸𝑂𝑀 24ℎ 𝑃𝑀10 = 0.98 (𝑂𝑠𝑖𝑟𝑖𝑠 24ℎ 𝑃𝑀10) (Access Macquarie Ltd, 2011)
Using the 70th percentile 24-hour average PM10 of 6.0 µg/m3 measured by the Osiris as presented in Table 9.1, the HVAS and TEOM equivalent measurements would have been 11.0 and 5.9 µg/m3, respectively.
To provide a realistic but conservative background of the 24-hour average PM10, a background concentration of 17 µg/m3 has been adopted for this assessment. This is midway between the 22 µg/m3 (based on measured levels at the DES The Gap station) and the 11 µg/m3 (Osiris results standardised to the HVAS method).
The annual average PM10 of 7.1 µg/m3 as measured by the Osiris would have HVAS and TEOM equivalent measurements of 11.9 and 7.0 µ̲g/m3 if using the same correlations as the 24-hour average PM10 in the absence of correlations for annual average PM10. To provide a realistic but conservative background of the annual average PM10, a background concentration of 16 µg/m3 has been adopted for this assessment. This is midway between the 20 µg/m3 (based on measured levels at the DES The Gap station) and the 12 µg/m3 (Osiris results standardised to the HVAS method).
10.3 DES Memorial Park (Gladstone)
Established in 2009, the Memorial Park station uses differential optical absorption spectroscopy (DOAS) equipment to monitor pollutants over a light path from the Entertainment Centre to Memorial Park. It is classified as a neighbourhood station.
The measured ozone (O3), NO2 and air toxics (organic pollutants) concentrations are presented in Table 10.2.
Table 10.2 Concentrations Recorded by the DES Memorial Park Station
Ye
ar
70
th %
1h
O3
(pp
m)
70
th %
1h
NO
2 (
µg/
m3 )
An
nu
al a
vera
ge N
O2
(µg/
m3 )
An
nu
al a
vera
ge b
en
zen
e
(µg/
m3 )
70
th %
1h
to
lue
ne
(µg/
m3 )
70
th %
24
h t
olu
en
e
(µg/
m3 )
An
nu
al a
vera
ge t
olu
en
e
(µg/
m3 )
70
th %
24
h x
yle
ne
(µg/
m3 )
An
nu
al a
vera
ge x
yle
ne
(µg/
m3 )
70
th %
1h
fo
rmad
eh
yde
(µg/
m3 )
70
th %
24
h f
orm
ade
hyd
e
(µg/
m3 )
2010 i.d. 13 11 i.d. i.d. i.d. i.d. i.d. i.d. i.d. i.d.
2011 0.019 6 6 i.d. i.d. i.d. i.d. i.d. i.d. i.d. i.d.
2012 i.d. i.d. i.d. i.d. i.d. i.d. i.d. i.d. i.d. i.d. i.d.
2013 0.024 13 i.d. i.d. i.d. i.d. i.d. i.d. i.d. i.d. i.d.
2014 0.025 9 5 i.d. 7 6 6 45 41 3 2
2015 0.025 9 5 i.d. 9 8 7 47 44 3 3
2016 0.021 9 11 3 5 5 4 38 33 3 3
2017 0.024 9 4 4 9 9 7 25 22 4 4
2018 0.024 9 10 i.d. 10 9 8 22 20 4 4
Average 0.023 10 7 4 8 7 7 36 32 4 3
Note: i.d. = insufficient data
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10.4 DES Boyne Island (Gladstone)
This station is located in the residential area of Boyne Island likely to be worst-affected from industrial emissions according to modelling. CO data from this monitoring station is presented in Table 10.3.
Table 10.3 Concentrations Recorded by Queensland DES Boyne Island Monitoring Station
Year 70th % 8-hour CO (µg/m3)
2010 65
2011 115
2012 49
2013 72
2014 115
2015 115
2016 115
2017 115
2018 0
Average 84
10.5 DERM Runcorn Monitoring
Heavy metals, aldehydes and other pollutants were monitored from September 2009 to March 2010 near the Bradken Resources Foundry at Runcorn (Department of Environment and Resource Management (DERM) 2010). Arsenic and aldehyde levels were found to be consistent with background, whereas other heavy metals increased when the wind blew from the foundry.
Sampling was completed at three sites. The proportion of time wind was blowing from the foundry was less at Bonemill Road and Selsey Street during metals sampling and Bonemill Road during aldehyde sampling. The data summarised in Table 10.4 is the Bonemill Road formaldehyde concentration and, for metals, the y-intercept from plots of concentration against wind for these two sites. The VOC concentrations listed are the average across the three sites.
Table 10.4 Summary of DERM Runcorn Monitoring Results Most Relevant to Background
Pollutant Concentration (µg/m3) Maximum 7-day Average (µg/m3)
arsenic 0.001 -
chromium 0.001 -
cobalt 0.0001 -
copper 0.003 -
iron 0.1 -
lead 0.0005 -
manganese 0.01 -
nickel 0.002 -
vanadium 0 -
zinc 0.01 -
acetaldehyde - 2.5
10.6 Polycyclic Aromatic Hydrocarbons
Background concentrations of benzo(a)pyrene have been reported in five studies:
• Kumar (2008) found an average of 0.1 ng/m3 in 56 PM10 samples at Rocklea in 2003 and 2004.
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• Yang (1991) found an average of 0.89 ng/ m3 in TSP samples at a roadside location in Brisbane.
• Muller (1998) found an average of 0.32 ng/ m3 in TSP samples at a roadside location in Brisbane.
• Lim et al (2005) found that benzo(a)pyrene in TSP samples were below detection limits (0.001 ng/ m3) at ANZ stadium in Robertson in 2002. Lim et al (2005) also measured other PAHs.
• Martin & Mejia (2010) reported that in 10 samples analysed for PAHs at Willawong in 2010, all benzo(a)pyrene measurements were below the limit of reporting 0.4 ng/ m3.
The Kumar study appears to be a robust measure of background and was used in this assessment.
10.7 Ammonia Concentration
Ambient ammonia concentration on a four-hectare grazed pasture in Australia was found to be between 12 to 28 µg/m3 (Shah et al, 2006). Other grazed pastures and agricultural land fertilised with urea have been found to have higher ammonia concentrations, as expected (Shah et al, 2006). For this assessment, the background ammonia concentration for the site is assumed to be 28 µg/m3.
10.8 Dust Deposition
The criterion for dust deposition in Queensland is generally based on the EHP guideline that insoluble deposited matter should not exceed 120 mg/m2/day (3.6 g/m2/month). Background dust deposition levels vary according to local sources. In rural agricultural or industrial areas, these are typically 50 mg/m2/day and in urban areas these are typically 40 mg/m2/day. The DES Mount Isa data published does not include dust deposition. Based on the dust deposition monitoring undertaken onsite, the dust deposition levels at the nearest sensitive receptors ranged from 4 to 59 mg/m2/day. The maximum measured monthly dust deposition level of 59 mg/m2/day has been used in this assessment as the background level.
10.9 Other Pollutants
Background concentrations of H2SO4 are not routinely monitored and are expected to be negligible. Since there is no background data available for H2SO4 the maximum predicted concentration is compared to the criterion.
10.10 Summary of Estimated Background Levels
Based on the discussions in the preceding sections, the expected background air quality for key pollutants has been summarised with the estimated concentrations listed in Table 10.5. These are well within the criteria contained in Table 4.5. It is anticipated that the criteria would only be exceeded during regional events such as bushfires or dust storms.
Since the monitoring period onsite is currently insufficient to cover multiple seasons, it is more appropriate to use the long-term Mount Isa data. Further, the Osiris site data obtained to date suggests that the suspended particulate concentrations in Mount Isa are higher than those onsite. Thus, it is conservative to use the Mount Isa suspended particulate data.
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Table 10.5 Background Air Quality
Pollutant Averaging Period Concentration (µg/m3)
TSP 1 year 51
PM10 24 hours 17
1 year 16
PM2.5 24 hours 6
1 year 5.0
Dust deposition 30 days 59 mg/m2/day
vanadium in PM10 1 day 0
SO2 1 hour 2
24 hours 4
1 year 11
O3 1 hour 0.023 ppm
NO2 1 hour 10
1 year 7
benzene 1 year 4
toluene 30 minutes 8
24 hours 7
1 year 7
xylene 24 hours 36
1 year 32
formaldehyde 30 minutes 4
24 hours 3
CO 8 hours 84
arsenic (As) 1 year 0.001
lead (Pb) 1 year 0.0005
manganese (Mn) 1 year 0.01
nickel (Ni) 1 year 0.002
acetaldehyde 3 minutes 2.5
PAH as benzo(a)pyrene 1 year 0.1 ng/m3
NH3 3 minutes 28
H2SO4 3 minutes 0
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11. Pollution Modelling Methodology
11.1 Overview
As discussed in Sections 3.3 and 3.4, the emissions from the construction, commissioning, rehabilitation and closure of the project will likely be minimal in comparison to emissions from mining operations. In addition, the main sources are to be further from the sensitive receptors. Therefore, these scenarios were not modelled in this assessment. Worst case operating conditions however have been incorporated into the assessment by the use of a high production schedule throughout the modelled calendar year which includes periods of adverse weather conditions.
In order to predict what happens to the pollutants after they are emitted to air, a mathematical model is used to simulate their dispersion and deposition. It is accepted by regulatory agencies that this type of modelling has associated uncertainties. These are normally addressed by using statistics over long simulation times and deriving emission rates based on published emission factors or data representing high emission conditions.
With sources close to ground level, the critical wind conditions tend to be near-calm i.e. low wind speeds. Gaussian plume models such as Ausplume and Aermod cannot model near-calm conditions and have low accuracy in light winds, especially in valleys where katabatic flows are present and where drainage flows turn to follow the valley. Calpuff, being a non-steady-state Lagrangian puff model, is able to simulate stagnation over time, which is critical in near-calm conditions. Its meteorological pre-processor Calmet performs diagnostic simulation of terrain effects on the wind field. It has a specific slope flow algorithm that predicts katabatic flows (Scire, J.S. & Robe, F.R., 1997).
Due to the low source height for emissions sources associated with the Project, the worst conditions may be near-calm conditions. In near-calm conditions there is little turbulent mixing and less dilution by incoming wind. Large sources (such as mine dust) can travel long distances (slowly) with only slight reduction in concentration. Windy conditions cause more emission of dust from some sources, but much greater mixing and dispersion of the dust before its travels far.
Thus Calpuff (Version 7.2.1) was chosen as the most appropriate model. The predictions undertaken for this assessment are based on the following method:
• The activity scenarios selected for modelling were based on the highest potential to cause impact to nearby sensitive receivers.
• Emission estimates were based on accepted methods and data consolidated by the National Pollutant Inventory (NPI) and the United States Environmental Protection Agency (USEPA) and calculated theoretical concentrations using the mass-balance method. The main emission calculation methods utilised are included in Appendix B and Section 11.8.
• Prediction of input meteorology was completed using TAPM developed by the CSIRO Division of Atmospheric Research. TAPM has a prognostic 3 dimensional meteorological component which can be used to generate hourly meteorological data for input into dispersion models. TAPM was run over a full representative year (2017) to include all seasons. It uses gridded terrain data at approximately 300 metre grid spacing to shape the windfields.
• TAPM input meteorology was enhanced using Calmet, the meteorological pre-processor for Calpuff. This fits the windfields to the terrain based on gridded terrain data at approximately 30 metre grid spacing.
• Particulate and gaseous concentrations and dust deposition were predicted using Calpuff.
197401.0129.R01V09.docx 71
11.2 Modelling Scenarios
The modelling scenarios selected to predict emissions from the project are presented in Table 11.1. Scenario 1 is based on the year 11 production schedule as presented in Table 3.1 using the year 6 mine sequencing layout and Scenario 2 is based on the year 23 production schedule and site layout. The number of dozers used were estimated to be 12 in pit for Scenario 1 and 32 for Scenario 2, with 2 dozers at the ROM pad for both scenarios. The dozers in pit were split equally into the extraction area and the rehabilitation area. For scenario 2, the dozers in pit were also split equally between the two pits. The emissions of other mobile equipment listed in Table 3.2 such as excavators and dump trucks are based on amount of materials handled.
The emission rates determined for the modelled sources are presented in Section 11.6. Although it is planned that the product will be hauled from site via train, the modelling scenarios for dust emissions were based on the worst case hauling of all the products via the access road.
Table 11.1 Modelled Scenarios of Materials Handled
Material handled Scenario 1 Amount Scenario 2 Amount Density (tonne/bcm)
Load and haul bulk waste 3,254,376 bcm 2,807,666 bcm 1.8
Dozer push waste 35,083,612 bcm 84,940,531 bcm
Sidecast wedge 173,499 bcm 144,126 bcm
Total overburden extracted
38,511,487 bcm 87,892,323 bcm
Topsoil removed 687,870 bcm 1,053,292 bcm 1.8
Extracted ore 13,325,613 tonnes 14,457,148 tonnes 2.2
Product 20,000 tonnes 20,000 tonnes -
Rejects 13,305,613 tonnes 14,437,148 tonnes 2.0
11.3 Calpuff Configuration
The three dimensional wind fields from Calmet were entered into Calpuff for the full year 2017. Calpuff was run over a smaller computational grid (20.4 kilometres x 28 kilometres) with spacing of 400 metres, and with receptors gridded over the same domain with a resolution of 800 metres.
Dry deposition was modelled with vegetation state set to active and stressed. Gravitational settling was included due to the large particle size in the dust being modelled.
Wind speed profile was set to the Industrial Source Complex (ISC) Rural exponents. Transitional plume rise and partial penetration of boundary layers were included. Briggs rise algorithm was used since the sources are not very hot.
The emissions were modelled as puffs and puff-splitting was turned off.
Dispersion coefficients were derived by the model using turbulence generated by micrometeorology. The Heffter curve was used to compute time-dependent dispersion beyond 550 metres. The partial plume height adjustment method was used to allow winds to approach hills as terrain increases.
The minimum turbulence velocity, sigma v, was set to 0.2 m/s.
For the purpose of calculating the influence of deposition, Calpuff only allows each particulate species to be characterised by a single mean diameter and standard deviation. Therefore, suspended TSP concentrations were modelled as three separate components: PM2.5, coarse (between 2.5 and 10 microns) and “dust” (between 10 and 75 microns). Emission rates of the species “dust” were calculated as the difference between TSP and PM10 emissions from the inventory. Emission rates of the species “coarse” were calculated as the difference between PM10 and PM2.5 emissions from the inventory. The predicted TSP results were then
197401.0129.R01V09.docx 72
calculated as the sum of the model outputs for each of the three components. Similarly, dust deposition was predicted as the sum of the deposition of the deposition of each of the three components.
11.4 Emission Inventory Calculations for Particulates
The emission rates entered into the dispersion modelling are based on the activity and source information provided as listed in Section 3. For the purpose of dispersion modelling, it has been conservatively assumed that product will be transported via road instead of rail. Loading of product onto delivery trucks or trains was assumed to have insubstantial emissions as the product will be in bags. Appendix B provides the calculation methods, for significant particulate sources.
Note that the NPI manual is designed for estimating total annual emissions. Some of the equations are based on annual averages of wind speed and rainfall. Using annual averages is not appropriate for dispersion modelling where maximum 24 hour concentrations may occur during dry, windy conditions.
Therefore, in this project, rain has been removed from the emission calculations and, emission rates are variable dependent on wind speed category.
11.5 Dust Control Measures
Emission controls proposed to be used to reduce particulate emissions that have been included in the dispersion modelling are presented in Table 11.2. The control efficiencies of these technologies are derived from Environment Australia (2012), Katestone (2011) and Department of Environmental Quality (2015).
Table 11.2 Dust Emission Controls
Emission Source Control(s) Utilised Control Efficiency Applied
Vehicles on unpaved roads Chemical suppressants and watering 85%
Dozers, scrapers and graders Water sprays 50%
In addition to Table 11.2, pit retention factors of 50% for TSP and 5% for PM10 were utilised for activities located within the pit. These factors are specified by Environment Australia (2012).
Scenario 2b also had additional control measures implemented during the months of March to May with no dozer and scraper activities to occur between 6pm to 7am in the pit closest to the Saint Elmo homestead.
11.6 Summary of Emission Inventories
The total emission inventories for all sources are provided in Table 11.3 and Table 11.4. The modelled source locations are presented in Figure 11.1 and Figure 11.2. These locations are those anticipated by ASK, based on operating mine site experience, for mining years 6 and 23.
Table 11.3 Modelled Total Controlled Emission Rates for Scenario 1
Source TSP (kg/y) PM10 (kg/y) PM2.5 (kg/y)
Loading trucks with overburden 534 480 76
Loading trucks with ore (pit) 1,153 1,036 44
Loading trucks with ore (ROM pad) 2,306 1,091 44
Loading trucks with rejects 1,151 1,034 44
Excavator for drainage and cleanup 1,177 557 22
Bulldozing on overburden (pit) 93,453 42,637 19,625
Bulldozing in pit (pit and haul road establishment and maintenance)
7,788 3,553 1,635
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Source TSP (kg/y) PM10 (kg/y) PM2.5 (kg/y)
Bulldozing on overburden (ROM pad) 28,755 6,905 3,109
Bulldozing out-of-pit (pit and haul road establishment and maintenance)
10,352 2,486 1,087
Unloading overburden from trucks 1,014 479 73
Unloading ore from trucks (ROM pad) 2,306 1,091 44
Unloading ore from trucks (MIA) 2,306 1,091 44
Unloading rejects from trucks 2,302 1,089 44
Hauling of overburden and rejects (in pit) 115,497 55,928 5,887
Hauling of ore and rejects (in pit) 45,008 21,795 2,294
Hauling of ore and rejects (pit to MIA) 672,012 171,271 17,127
Hauling of ore and rejects (within MIA – ROM pad to processing area)
143,539 36,583 3,658
Product delivery trucks on access road 6,040 1,159 116
Scraper in travel mode 40,799 5,610 1,265
Topsoil Removal by Scraper 17,953 4,488 557
Grader in pit 535 454 33
Grader out-of-pit 1,069 478 33
Wind erosion 300,301 150,150 11,261
Scraper unloading 12,382 3,095 384
Total 1,509,730 514,540 68,416
Note: Slight discrepancy between the numbers and the total is due to rounding off.
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Figure 11.1 Modelled Source Locations (Scenario 1)
Table 11.4 Modelled Total Controlled Emission Rates for Scenario 2
Source TSP (kg/y) PM10 (kg/y) PM2.5 (kg/y)
Loading trucks with overburden
460 413 66
Loading trucks with ore (pit) 1,251 1,124 48
Loading trucks with ore (ROM pad)
2,501 1,183 48
Loading trucks with rejects 1,249 1,122 47
Excavator for drainage and cleanup
1,177 557 22
Bulldozing on overburden (pit) 221,033 100,843 46,417
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Source TSP (kg/y) PM10 (kg/y) PM2.5 (kg/y)
Bulldozing in pit (pit and haul road establishment and maintenance)
6,401 2,920 1,344
Bulldozing on overburden (ROM pad)
28,755 6,905 3,019
Bulldozing out-of-pit (pit and haul road establishment and maintenance)
10,352 2,486 1,087
Unloading overburden from trucks
874 414 63
Unloading ore from trucks (ROM pad)
2,501 1,183 48
Unloading ore from trucks (MIA)
2,501 1,183 48
Unloading rejects from trucks 2,498 1,181 47
Hauling of ore (north pit) 14,341 6,944 731
Hauling of ore and overburden (north pit)
53,789 26,047 2,605
Hauling of ore and rejects (north pit)
19,520 9,453 945
Hauling of overburden and rejects (south pit)
69,845 33,822 3,560
Hauling of overburden, ore and rejects (south pit)
34,103 16,514 1,738
Hauling of ore and rejects (out-of-pit from north pit to T-intersection)
119,296 30,404 3,040
Hauling of ore and rejects (out-of-pit from south pit to T-intersection)
133,499 34,024 3,402
Hauling of ore and rejects (from T-intersection to MIA)
634,232 161,642 16,164
Hauling of ore and rejects (within MIA – ROM pad to processing area)
155,737 39,692 3,969
Trucks on access road 6,040 1,159 116
Scraper in travel mode 38,014 5,227 1,178
Topsoil Removal by Scraper 25,614 6,404 794
Grader in pit 535 454 33
Grader out-of-pit 1,069 478 33
Wind erosion 250,508 125,254 9,394
Scraper unloading 17,665 4,416 548
Total 1,855,362 623,449 100,555
Note: Slight discrepancy between the numbers and the total is due to rounding off.
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Figure 11.2 Modelled Source Locations (Scenario 2)
11.7 Other Source Parameters
Other source parameters used in modelling are provided in Table 11.5 and Table 11.6.
Table 11.5 Other Source Parameters for Scenario 1
Source Easting (m)
WGS84 Northing
(m) WGS84
Effective height
(m)
Horizontal spread
(m)
Vertical spread
(m)
Loading trucks with overburden 592520 7723071 5.0 4.7 4.7
Loading trucks with ore (pit) 592414 7723112 5.0 4.7 4.7
Loading trucks with ore (ROM pad) 596509 7720748 5.0 4.7 4.7
Loading trucks with rejects 596445 7721289 5.0 4.7 4.7
Excavator for drainage and cleanup 596355 7721382 5.0 4.7 4.7
Bulldozing on overburden (pit) 592656 7723146 2.5 23.3 4.7
592720 7723041
592653 7722942
592700 7722839
592688 7722634
592481 7725365
592638 7722734
592519 7725166
592568 7725266
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Source Easting (m)
WGS84 Northing
(m) WGS84
Effective height
(m)
Horizontal spread
(m)
Vertical spread
(m)
592452 7725067
592515 7724961
592470 7724863
Bulldozing in pit (pit and haul road establishment and maintenance)
592827 7722682 2.5 23.3 4.7
Bulldozing on overburden (ROM pad) 596475 7720874 2.5 23.3 4.7
596419 7720666
Bulldozing out-of-pit (pit and haul road establishment and maintenance)
594955 7721066 2.5 23.3 4.7
Unloading overburden from trucks 592455 7724749 6 7 7
Unloading ore from trucks (ROM pad) 596291 7720860 6 4.7 7
Unloading ore from trucks (MIA) 596319 7721525 6 4.7 7
Unloading rejects from trucks 592662 7724733 6 7 7
Hauling of overburden and rejects (in pit) various various 4.4 27 4.1
Hauling of ore and rejects (in pit) various various 4.4 27 4.1
Hauling of ore and rejects (pit to MIA) various various 4.4 27 4.1
Hauling of ore and rejects (within MIA – ROM pad to processing area)
various various 4.4 27 4.1
Trucks on access road various various 3.7 14 3.4
Scraper in travel mode 592913 7722948 1.9 46.5 4.7
Topsoil Removal by Scraper 592913 7723194 2 23.3 4.7
Grader in pit 592550 7724008 2 23.3 4.7
Grader out-of-pit 594111 7721567 2 23.3 4.7
Wind erosion various various 0 (pit)
3 (ROM pad)
- 1.9
Scraper unloading 592943 7722756 2 11.6 4.7
Table 11.6 Other Source Parameters for Scenario 2
Source Easting (m)
WGS84 Northing
(m) WGS84 Effective
height (m)
Horizontal spread
(m)
Vertical spread
(m)
Loading trucks with overburden 590521 7722347 5.0 4.7 4.7
592321 7718336
Loading trucks with ore (pit) 590517 7722483 5.0 4.7 4.7
592323 7718471
Loading trucks with ore (ROM pad) 596509 7720748 5.0 4.7 4.7
Loading trucks with rejects 596445 7721289 5.0 4.7 4.7
Excavator for drainage and cleanup 596355 7721382 5.0 4.7 4.7
Bulldozing on overburden (pit) 590737 7722681 2.5 23.3 4.7
590687 7722580
590732 7722477
590697 7722377
590699 7722179
590723 7722078
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Source Easting (m)
WGS84 Northing
(m) WGS84 Effective
height (m)
Horizontal spread
(m)
Vertical spread
(m)
590728 7722278
590695 7721978
590719 7721167
590676 7721068
590724 7720970
590675 7720869
590721 7720768
590675 7720667
590714 7720567
590669 7720464
592570 7718609
592597 7718509
592569 7718408
592597 7718309
592569 7718210
592599 7718110
592570 7718011
592604 7717911
593029 7717029
593069 7716928
593042 7716828
593072 7716727
593031 7716628
593070 7716528
593038 7716428
593070 7716328
Bulldozing in pit (pit and haul road establishment and maintenance)
590875 7722872 2.5 23.3 4.7
Bulldozing on overburden (ROM pad) 596475 7720874 2.5 23.3 4.7
596419 7720666
Bulldozing out-of-pit (pit and haul road establishment and maintenance)
594616 7720388 2.5 23.3 4.7
Unloading overburden from trucks 590472 7720626 6 7 7
592787 7716538
Unloading ore from trucks (ROM pad) 596291 7720860 6 4.7 7
Unloading ore from trucks (MIA) 596319 7721525 6 4.7 7
Unloading rejects from trucks 590482 7720522 6 7 7
592781 7716402
Hauling of overburden (north pit) various various 4.4 27 4.1
Hauling of overburden and rejects (in pit) various various 4.4 27 4.1
Hauling of ore and rejects (in pit) various various 4.4 27 4.1
Hauling of ore and rejects (pit to MIA) various various 4.4 27 4.1
Hauling of ore and rejects (within MIA – ROM pad to processing area)
various various 4.4 27 4.1
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Source Easting (m)
WGS84 Northing
(m) WGS84 Effective
height (m)
Horizontal spread
(m)
Vertical spread
(m)
Trucks on access road various various 3.7 14 3.4
Scraper in travel mode 590873 7722232 1.9 46.5 4.7
592748 7718339
Topsoil Removal by Scraper 590879 7722469 2 23.3 4.7
592766 7718571
Grader in pit 590551 7721632 2 23.3 4.7
Grader out-of-pit 592995 7720375 2 23.3 4.7
Wind erosion various various 0 (pit)
3 (stockpiles
at ROM pad)
- 1.9
Scraper unloading 590880 7721982 2 11.6 4.7
592758 7718082
11.8 Emissions Inventory for the Processing Plant
11.8.1 Flotation
For confidentiality reasons, the name of the flotation agent to be used as part of the processing phase for the Project is not specified in this assessment; however, its potential impacts have been assessed in this section.
The vapour pressure of the flotation agent that will be used as part of the processing phase is 0.0±2.3 mmHg at 25°C (ChemSpider, 2019). This means that the flotation agent is not likely to emit vapour at ambient temperature. To be conservative, the emission of the flotation agent has been calculated based on a vapour pressure of 2.3 mmHg. At equilibrium, the vapour concentration of the flotation agent is calculated as 44 g/Nm3. It should be noted that this equilibrium concentration is likely only in the thin film immediately above the liquid surface. The concentration will be substantially diluted above this film.
A screening calculation was undertaken based on the equilibrium concentration and the dilution achieved by the dispersion modelling of the generator emissions adjusted to normal temperature and pressure. The maximum 1-hour concentration at the worst-affected sensitive receptor was calculated as 219 µg/m3 and the annual average concentration was 2.2 µg/m3. In the absence of air quality criteria for the flotation agent, the likely impacts are assessed against the effects screening levels (ESL). The short term ESL for the flotation agent is 1,000 µg/m3 and the long term ESL is 100 µg/m3 (TCEQ, 2016). Hence, emission from the flotation agent is not likely to cause unacceptable health impacts at the sensitive receptors.
11.8.2 Roasting
The average composition of ore is shown in Table 11.7.
Using the maximum amount of ore extracted in a year, 6,571,431 bcm or 14,457,148 tonnes, subtracted by the amount of rejects prior to roasting, 7,594,920 tonnes, the maximum amount of ore to be roasted in a year is calculated as 6,862,228 tonnes.
Table 11.7 Average ore composition
Species Concentration (% wt)
arsenic trioxide (As2O3) 0.012
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Species Concentration (% wt)
manganese (II) oxide (MnO) 0.069
nickel (II) oxide (NiO) 0.057
lead (II) oxide (PbO) 0.003
sulfur trioxide (SO3) 0.048
The source was modelled as a point source with parameters presented in Table 11.8. The assumed temperature and velocity are conservative estimates. Building wake effect was modelled using the BPIP processor and the Prime algorithm. A rectangular building with a height of 25 metres was modelled to represent the roasting plant.
Table 11.8 Modelled Source Parameters
Parameters Modelled
easting (m) WGS84 596594
northing (m) WGS84 7721476
height above ground (m) 35
exit temperature (ᵒC) 150
exit diameter (m) 0.6
velocity (m) 10
The source was modelled with an arbitrary emission rate (1 g/s). The predicted concentrations at the sensitive receptors were then used to back-calculate the maximum emission rates for PM10 and SO2, so that the impacts would comply with the relevant criteria at the sensitive receptors. The background concentrations and the cumulative impact from the mining and material handling operations and power generation, were subtracted from the criteria. The maximum allowable PM10 emission rate was calculated to be 10 g/s and the maximum SO2 emission rate is 91 g/s.
Table 11.9 presents the predicted maximum impacts at the sensitive receptor with the highest predictions using the calculated maximum allowable emission rates for PM10 and SO2. The emission rates for metal emissions were calculated assuming the PM10 emitted has the same metal composition as the ore (Table 11.7).
197401.0129.R01V09.docx 81
Table 11.9 Emission rates and predicted concentrations at receptor A [background] {criterion}
Species Emission rate
(g/s) Annual concentration
(µg/m3)
Maximum 24h average concentration
(µg/m3)
Maximum 1h average concentration (µg/m3)
SO2 91 5 (11) {57} 92 (4) {230} 568 (2) {570}
PM10 10 - 3 (47){50} 1
10 (26){50} 2 -
As2O3 0.0012 0.000070 (0.001)
{0.006} - -
MnO 0.0070 0.00040 (0.01) {0.16} - -
NiO 0.0058 0.00033 (0.002) {0.02} - -
PbO 0.00030 0.000017 (0.0005)
{0.5} - -
Notes: 1) The worst allowable cumulative impact for 24 hour PM10 is 50 µg/m3 occurring when the background including mining and
generator emissions at the worst-affected sensitive receptor is 47 µg/m3. This leaves a maximum allowable incremental impact of 3 µg/m3 from the roaster. The 10 g/s emission rate is based on this maximum.
2) The maximum incremental 24 hour PM10 impact due to the roasting emissions is 10 µg/m3 but this is not the worst cumulative impact since it occurs when the cumulative background including mining and generator emissions is 26 µg/m3.
Based on material balance, assuming all SO3 in the ore is converted to SO2, the SO2 emission rate was calculated as 84 g/s, lower than the calculated maximum allowable SO2 emission rate of 91 g/s.
As the ore is coquina, mainly composed of limestones, the most appropriate emission factor found is the particulate emission factor for gas-fired rotary kiln with electrostatic precipitator (ESP) for lime manufacturing (US EPA, 1998a). The particulate emission factor is 0.086 kg per tonne of lime produced and PM10 comprise of 50% of the mass of the particulate emission (US EPA, 1998a). The emission factor was multiplied with the amount of roasted materials instead and the PM10 emission rate was calculated to be 9 g/s, within the calculated maximum allowable PM10 emission rate. As this is based on a kiln with ESP, an ESP or a fabric filter (which is more efficient) is recommended for the kiln stack emissions.
As there are no readily available emission factors specific for the vanadium mine industry and the sulfur content of the ore may vary, it is recommended that monitoring of the stack emissions be undertaken to check that the amounts emitted remain below the calculated maximum emission rates.
11.8.3 Leaching
Leaching will be undertaken using 98% H2SO4 solution in agitated tanks. The amount of H2SO4 mist that will be emitted from the tanks is calculated in this section.
The more conservative of the two Henry’s law constants for H2SO4 presented by Sander (2015) is 2.9x107 mol/(m3 Pa). Using the concentration of the H2SO4 in solution of 98%, the molecular weight of 98 g/mol and density of the solution of 1.84 g/cm3, the partial pressure of H2SO4 was calculated as follows:
98 𝑔 𝐻2𝑆𝑂4
100 𝑔 𝑠𝑜𝑙𝑢𝑡𝑖𝑜𝑛𝑥
1.84 𝑔 𝑠𝑜𝑙𝑢𝑡𝑖𝑜𝑛
1 𝑐𝑚3𝑠𝑜𝑙𝑢𝑡𝑖𝑜𝑛𝑥 (
100 𝑐𝑚
1 𝑚)
3
2.9𝑥107𝑚𝑜𝑙/(𝑚3𝑃𝑎)𝑥98𝑔
𝑚𝑜𝑙
= 0.00063 𝑃𝑎
Assuming atmospheric pressure of 101,325 Pa, the equilibrium concentration in the gas phase is calculated as follows:
0.00063 𝑃𝑎
101,325 𝑃𝑎𝑥
98 𝑔/𝑚𝑜𝑙
0.022414 𝑚3/𝑚𝑜𝑙𝑥
106 µ𝑔
1 𝑔= 27 µ𝑔/𝑚3
197401.0129.R01V09.docx 82
With a background concentration of zero, the concentration of H2SO4 at the source complies with the 3 minute criterion of 33 µg/m3. Hence, it is very unlikely that the H2SO4 emissions from the leaching tanks would cause unacceptable impacts at the sensitive receptors at least 6,000 metres away from the source.
11.8.4 Solvent Extraction
The solvent to be used for solvent extraction is Alamine 336. Based on a vapour pressure of 0.007 Pa at 25°C (Friess, 2016) and a molecular weight of 354 g/mol, the equilibrium vapour concentration was calculated as 1.09 mg/Nm3. As with the flotation agent, the equilibrium vapour concentration is likely to only occur in the thin film immediately above the liquid surface. Conservatively using this equilibrium concentration and the modelling for the generator emissions adjusted to normal temperature and pressure, the maximum 1-hour concentration at the worst-affected sensitive receptor is calculated as 0.0054 µg/m3. In the absence of air quality criteria and ESLs for Alamine 336, a default short term ESL is 2 µg/m3 (TCEQ, 2019). The emission from the solvent used is very unlikely to result in adverse health impacts at the sensitive receptors.
11.8.5 NH3 Emissions from De-ammoniation Plant
The source of ammonia emissions will be the decomposition of NH4VO3. As advised by the client, 2.55 tonnes of (NH4)2SO4 will be consumed for every tonne of product. Based on the maximum potential production rate of 20,000 t/y of V2O5, the amount of (NH4)2SO4 consumed would be 51,000 t/y. The ammonia emitted has been calculated as shown below to be 13,146 t/y or 417 g/s.
51,000 𝑡 (𝑁𝐻4)2𝑆𝑂4
𝑦𝑒𝑎𝑟𝑥
17.031𝑔
𝑚𝑜𝑙𝑁𝐻3
132.14𝑔
𝑚𝑜𝑙(𝑁𝐻4)2𝑆𝑂4
𝑥2 𝑚𝑜𝑙 𝑁𝐻3
1 𝑚𝑜𝑙 (𝑁𝐻4)2𝑆𝑂4=
13,146 𝑡 𝑁𝐻3
𝑦𝑒𝑎𝑟
A scrubber will be used to minimise the ammonia emissions with a guaranteed ammonia exhaust concentration of <100 mg/Nm3. The emission will require at least 175 times dilution for the concentration to comply with the 3-minute average NH3 criterion of 600 µg/m3 with a background concentration of 28 µg/m3. Modelling of the emissions from power generation indicates that emissions from the MIA will be diluted at least 200,000 times prior to reaching the receptor with the highest predictions (receptor A). It is very unlikely that the ammonia emissions will impact the nearest sensitive receptors, approximately 6,000 metres away, and hence dispersion modelling is not necessary in this assessment.
11.8.6 Emissions from Power Generation
Power for the MIA is likely to be supplied by gas-fired generators onsite; however, this assessment has assumed a worst case emissions scenario being diesel power generation of 24 MW. This will likely consist of twelve 2 MW diesel or gas generators, with possible contribution of up to 40% from a solar system.
The emission rates were calculated based on the emission factors for stationary large (greater than 450 kW) diesel engines provided in Table 43 of DEWHA (2008) and presented in Table 11.10. The emission rates are based on a diesel consumption rate of 167,040 L/day for power generation.
Table 11.10 NPI Emission Factors and Calculated Emission Rates
Pollutant Emission factor (kg/m3) Emission rate (g/s)
acetaldehyde 4.14E-04 8.00E-04
benzene 1.28E-02 2.47E-02
CO 1.40E+01 2.71E+01
formaldehyde 1.30E-03 2.51E-03
Oxides of nitrogen (NOx) - uncontrolled 5.26E+01 1.02E+02
NOx - controlled 3.12E+01 6.03E+01
PM2.5 1.60E+00 3.09E+00
PM10 1.64E+00 3.17E+00
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Pollutant Emission factor (kg/m3) Emission rate (g/s)
PAH (kg TEQ/m3) 1.90E-07 3.67E-07
SO2 1 16.6 x S2 3.21E-05
toluene 4.62E-03 8.93E-03
xylenes (individual or mixed isomers) 3.22E-03 6.23E-03
Notes: 1. S in the emission factor signifies the fuel sulfur content (wt%) in the diesel. For this assessment, the sulfur content was assumed to be 0.001% based on the maximum sulfur content of diesel required by the Australian Government in the Fuel Standard (Automotive Diesel) Determination 2001.
The source was modelled as a point source with parameters as presented in Table 11.11. The assumed dimension and velocity are based on a typical worst-case generator stack. Specifications of a 2 MW diesel generator include an exit temperature of 410ᵒC and an exhaust gas wet volume flow rate of 326 m3/min. Using our assumed diameter, the calculated exit velocity is 28 m/s. An exit velocity of 10 m/s, with rain cap and building downwash were modelled using the BPIP processor and the Prime algorithm. A rectangular building with a height of 3 metres was modelled with the same centre as the generator stack.
Table 11.11 Modelled Source Parameters
Parameters Modelled
easting (m) WGS84 597117
northing (m) WGS84 7721453
height above ground (m) 6
exit temperature (ᵒC) 400
exit diameter (m) 0.5
velocity (m/s) 10
11.9 Nitrogen Dioxide Modelling
11.9.1 Overview
Most of the NOx emitted by combustion engines are in the form of nitric oxide (NO). This reacts with other gases in the atmosphere to form NO2.
A typical proportion of NO2 in urban airsheds during peak concentration events is 20%. This includes both regional sources and local sources. The contribution from regional sources would have built up over a longer time period i.e. NO emissions would have had substantial time to react to form NO2. In a rural environment, the proportion would be lower.
The rate of conversion from NO to NO2 is related to a large number of factors. The most critical are ozone concentration, hydrocarbon concentration and the amount of sunlight, which increases the rate of the reverse reaction. Both hydrocarbons and ozone can be responsible for oxidising NO to form NO2. Generally, the conditions that favour NO2 formation are when ozone concentrations are high and sunlight low. This scenario could occur in the late afternoons following a clear day. In rural areas, ozone concentrations are low, so NO2 formation is not favoured.
As a guide, under worst conditions, ozone can oxidise approximately 5% of NO in 10 minutes. Oxidation by hydrocarbons is more dependent on pre-existing quantities of different species. Over time periods longer than 10 minutes, polluted air will be substantially mixed with the regional background air.
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11.9.2 Janssen Method
The Janssen Method (Middleton et al 2007) is a popular technique for estimating conversion of nitrogen oxides to NO2 downwind of a source. It is based on aircraft-based measurements taken downwind of power stations. The Janssen equation is as follows:
𝑁𝑂2
𝑁𝑂𝑥= 𝐴(1 − 𝑒−𝛼𝑥)
Where the values of A and α are presented in Janssen et al (1988) and varies according to ozone concentration, wind speed and season of the year, and x is the distance travelled by the plume.
11.9.3 Conversion Relevant to this Study
The Janssen Method was used in this assessment as the sources are power stations which are applicable to this method.
The average 70th percentile 1-hour ozone concentrations in the DES Memorial Park station is 23 ppb as presented in Table 10.2. For ozone concentration between 20-30 ppb, the factors for spring/autumn (A=0.74 and α=0.10) gives the highest NO2 to NOX ratio at the receptor with the highest predictions (receptor A) which is 7.1 kilometres away from the source. These factors have been chosen to calculate the NO2 to NOx ratio in this assessment. The predicted 99.9th percentile 1-hour average NOx concentrations were multiplied to the calculated NO2 to NOx ratio. For the annual average NO2 concentrations, 100% conversion of NOx to NO2 was assumed.
11.10 Calpost Processing
To calculate 30 minute and three minute averages from one hour averages, the power law was used:
p
p
m
m
p
TT
AC
C
=
where Cp = peak concentration; Cm =mean hourly average concentration; Tm = mean time of 60 minutes; Tp = peak time of 30 or 3 minutes; A = constant close to unity; p = coefficient ranges from 0.15 for volume sources up to 0.4 for tall stacks.
For A=1 and p = 0.15, the ratio for converting 60 minutes to 30 minutes is 1.1.
For A=1 and p = 0.15, the ratio for converting 60 minutes to 3 minutes is 1.6.
Following dispersion modelling, contours of pollution concentrations were generated using the GIS software Surfer. Surfer was used to overlay the model outputs onto a scan of a rectified aerial photograph of the area. Contours shown in this report were generated using the Kriging method and contours were created with smoothing set to high.
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12. Dispersion Modelling Results
12.1 Limitations
The uncertainties associated with this type of assessment are normally only dealt with in a qualitative manner, but include:
• emission estimation techniques
• meteorological data variability
• inherent uncertainty in dispersion modelling.
This has been addressed by conservative assumptions that will over-predict the ambient concentrations including the following:
• Emission rates are based on the high of amount of materials to be handled.
• Activities are assumed to operate throughout the day and year.
• The mining years with the closest disturbance footprint to the nearest sensitive receptors were used in this assessment.
• Within the footprint for the modelled scenarios, the sources were modelled relatively close to receptor A and the locations were modelled as unchanging throughout the year.
• Due to the presence of clay and siltstone, the silt content of haul roads was assumed to be high.
• The adopted background deposition and suspended concentrations are conservatively high.
12.2 Suspended Particulate Results
The predicted concentrations at the sensitive receptors are shown in Table 12.1, Table 12.2 and Table 12.4 along with the criteria. The estimated background levels are listed separately and not included in the predicted concentrations.
The concentrations at all the receptors assessed are predicted to comply with all the relevant criteria for scenario 1. For scenario 2, the maximum 24-hour average PM10 concentration is predicted to exceed the criterion at receptor A, whilst compliance is predicted with the other criteria. Hence, the PM10 model results for scenario 2 at receptor A have been further investigated. Table 12.3 presents the top 5 maximum predicted 24-hour average PM10 concentrations at receptor A. As shown, there are two days of predicted exceedances. It was found that the major source contributors are dozers and scrapers and elevated PM10 concentrations at receptor A mainly occur from 6pm to 7am during the months of March to May.
Hence another modelling scenario (scenario 2b) has been assessed which is similar to scenario 2 except without dozer and scraper activities occurring between the hours of 6pm and 7am during the months of March to May at the pit closest to receptor A. The predicted concentrations at all the assessed receptors are predicted to comply with all the relevant criteria for scenario 2b.
The most critical pollutant is 24 hour average PM10, with the maximum predicted concentrations of 47 µg/m3 and 46 µg/m3 including background for scenarios 1 and 2b, respectively. These are 94% and 92%, respectively, of the relevant criterion of 50 µg/m3. The results of the PM10 modelling for scenarios 1 and 2b are illustrated in Figure 12.1 and Figure 12.2 by pollution contours overlayed onto an aerial photo.
The vanadium concentrations were calculated as a fraction of PM10 with the assumption that 0.29% of PM10 is V2O5 (based on the properties of the ore). The predicted vanadium concentrations at all sensitive receptors are well below the criterion.
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Table 12.1 Predicted Suspended Particulate Concentrations (Scenario 1)
Receptor ID
Annual Average TSP
(µg/m3)
Maximum 24h Average PM10 (µg/m3)
Annual Average PM10
(µg/m3)
Maximum 24h Average
PM2.5 (µg/m3)
Annual Average PM2.5
(µg/m3)
Maximum 24h Average V2O5 (µg/m3)
Criterion 90 50 25 25 8 1.1
Background 51 17 16 6 5.0 0
A 3 30 3 4 0.4 0.1
B 1 11 1 2 0.1 0.0
C 0 2 0 0 0.0 0.0
D 0 1 0 0 0.0 0.0
Table 12.2 Predicted Suspended Particulate Concentrations (Scenario 2)
Receptor ID
Annual Average TSP
(µg/m3)
Maximum 24h Average PM10 (µg/m3)
Annual Average PM10
(µg/m3)
Maximum 24h Average
PM2.5 (µg/m3)
Annual Average PM2.5
(µg/m3)
Maximum 24h Average V2O5 (µg/m3)
Criterion 90 50 25 25 8 1.1
Background 51 17 16 6 5.0 0
A 9 44 7 8 1.2 0.1
B 1 14 1 2 0.1 0.0
C 0 2 0 0 0.0 0.0
D 0 1 0 0 0.0 0.0
Table 12.3 Top Five Maximum 24-hour PM10 Concentration at Receptor A (Scenario 2)
Rank Maximum 24 h Average PM10 (µg/m3) Date of occurrence
Criterion 50 -
Background 17 -
1 44 9/03/2017
2 35 1/05/2017
3 32 23/03/2017
4 30 22/03/2017
5 30 29/04/2017
Table 12.4 Predicted Suspended Particulate Concentrations (Scenario 2b)
Receptor ID
Annual Average TSP
(µg/m3)
Maximum 24h Average PM10 (µg/m3)
Annual Average PM10
(µg/m3)
Maximum 24h Average
PM2.5 (µg/m3)
Annual Average PM2.5
(µg/m3)
Maximum 24h Average V2O5 (µg/m3)
Criterion 90 50 25 25 8 1.1
Background 51 17 16 6 5.0 0
A 8 29 6 5 1.0 0.1
B 1 11 1 2 0.1 0.0
C 0 2 0 0 0.0 0.0
D 0 1 0 0 0.0 0.0
12.2.1 Short-Term (24-Hour Average) TSP Impact
The maximum 24-hour average TSP concentrations at the receptor with the highest predictions (receptor A) is predicted to be 30 µg/m3 for both scenarios, not including background. The 24-hour average TSP concentrations including background are predicted to be higher than the NZ Ministry for the Environment
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trigger level of 60 µg/m3 at some of the modelled discrete receptors. As discussed in Section 4.2.3, the NZ Ministry for the Environment trigger levels are not for regulatory compliance purposes but are only for potentially taking additional dust control measures when the monitoring data reach trigger levels. Thus it is recommended that complaint-based monitoring be included in the facility’s environmental management plan as discussed in Section 13.2.4.
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Figure 12.1 Predicted Maximum 24h PM10 Concentrations (µg/m3) Including Background – Scenario 1
5000 m
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Figure 12.2 Predicted Maximum 24h PM10 Concentrations (µg/m3) Including Background – Scenario 2b
5000 m
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12.3 Dust Deposition Results
The predicted dust deposition levels at sensitive receptors are shown in Table 12.5 along with the criterion and estimated background level. The cumulative level including background at all the receptors are within the guideline limit. The results of the dust deposition modelling are illustrated in Figure 12.3.
Table 12.5 Predicted Maximum 30-Day Dust Deposition Levels (mg/m2/day)
Receptor ID Scenario 1 Scenario 2 Scenario 2b
Criterion 120
Background 59
A 10 51 50
B 1 1 1
C 0 0 0
D 0 0 0
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Figure 12.3 Predicted Maximum 30 Day Dust Deposition (mg/m2/day) Including Background – Scenario 1
5000 m
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Figure 12.4 Predicted Max 30 Day Dust Deposition (mg/m2/day) Including Background – Scenario 2b
5000 m
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12.4 Combustion Pollutant Results
The predicted combustion emission concentrations at the sensitive receptors are shown in Table 12.6 along with the criteria. The estimated background levels are listed separately and not included in the predicted concentrations.
The predicted 99.9th percentile 1 hour NO2 concentration at the receptor with the highest predictions is 175 µg/m3 including background, or 70% of the criterion of 250 µg/m3, however, it should be noted that this prediction is based on the uncontrolled NOx emission factor, and the Janssen parameters producing the highest NO2/NOx conversion ratio at the receptor with the highest predictions. Despite these conservatisms, the predicted NO2 concentrations still comply with the criteria at the sensitive receptors.
The predicted particulate concentrations at the sensitive receptors are within the relevant criteria, even when taking into account the predicted maximum particulate concentrations from the mining and material handling operations presented in Section 12.2. Adding the particulate predictions from Section 12.2, the maximum 24 hour PM10 concentration would be 49 µg/m3 including background. The maximum particulate concentrations from mining and material handling operations occur on different days to the maximum particulate concentrations from power generation. Hence, the maximum 24 hour PM10 concentration would be less than 49 µg/m3 from the cumulative sources including background.
The results of the NO2 modelling are illustrated in Figure 12.5 by pollution contours overlayed onto an aerial photo.
Apart from NO2 and particulate concentrations, all other predicted concentrations are well below their relevant criteria.
Table 12.6 Predicted Concentrations from Combustion Emission
Air Quality Indicator
Period Criteria (µg/m3)
Background (µg/m3)
Maximum Predicted Concentrations Not Including Background (µg/m3)
Receptor ID A B C D
PM2.5 1 day 25 6 2 1 1 1
1 year 8 5.0 0.2 0.1 0 0
PM10 1 day 50 17 2 1 1 1
1 year 25 16 0.2 0.1 0 0
SO2 1 hour 570 2 0 0 0 0
1 day 230 4 0 0 0 0
1 year 57 11 0 0 0 0
benzene 1 year 10 4 0 0 0 0
CO 8 hour 11,000 84 54 27 13 10
formaldehyde 1 day 54 3 0 0 0 0
30 minutes
110 4 0 0 0 0
NO2 1 year 62 7 6 3 2 1
1 hour 1 250 10 165 100 59 39
benzo(a)pyrene (as a marker
for PAHs)
1 year 0.0003 0.0001 0.0000 0.0000 0.0000 0.0000
toluene 1 year 410 7 0 0 0 0
1 day 4,100 7 0 0 0 0
30 minutes
1,100 8 0 0 0 0
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Air Quality Indicator
Period Criteria (µg/m3)
Background (µg/m3)
Maximum Predicted Concentrations Not Including Background (µg/m3)
xylene (total of all isomers)
1 year 950 32 0 0 0 0
1 day 1,200 36 0 0 0 0
acetaldehyde 3 minutes
76 (odour)
590 (toxicity)
2.5 0 0 0 0
Note:
1. 99.9th percentile
12.5 Roasting Emissions
The modelling results of the emissions from roasting are presented in Section 11.8.2. The PM10 emission rate has been back-calculated from the modelling results to determine the maximum PM10 emission rate from roasting that will result in compliance with the relevant criterion at the sensitive receptors. The assumed background concentration and the cumulative impacts from mining operations and generator emissions were subtracted from the criterion. The SO2 emissions are expected to result in compliance of the relevant criteria. The metals emissions are also predicted to result in compliance with the relevant criteria provided there is compliance of the PM10 criterion.
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Figure 12.5 Predicted 99.9th Percentile 1 Hour NO2 Concentrations (µg/m3) Including Background
5000 m
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13. Discussion
13.1 Summary of Results
The concentrations and levels at all the modelled receptors are predicted to be within the relevant criteria.
Table 13.1 Summary of Results for Scenario 1
Indicator Worst Affected
Receptor Prediction from Project (µg/m3)
Cumulative Prediction with Background
(µg/m3)
Criterion (µg/m3)
Annual average TSP A 3 1 52 1 90
Maximum 24 h average PM10 A
30 1
30 2
33 3
47 1
47 2
50 3
50
Annual average PM10 A
3 1
3 2
4 3
19 1
19 2
20 3
25
Maximum 24 h average PM2.5 A 4 9 25
Annual average PM2.5 A 0.4 5.2 8
Maximum 24 h average V2O5 A 0.1 0.1 1.1
Dust deposition A 10 mg/m2/day 69 mg/m2/day 120
mg/m2/day
Notes: 1. Mining and material handling. 2. Mining, material handling and power generation. 3. Mining, material handling, power generation and maximum allowable emission for roasting.
Table 13.2 Summary of Results for Scenario 2b
Indicator Worst Affected
Receptor Prediction from Project (µg/m3)
Cumulative Prediction with Background
(µg/m3)
Criterion (µg/m3)
Annual average TSP A 8 1 49 1 90
Maximum 24 h average PM10 A
29 1
30 2
32 3
46 1
47 2
49 3
50
Annual average PM10 A
6 1
6 2
7 3
22 1
22 2
23 3
25
Maximum 24 h average PM2.5 A 5 11 25
Annual average PM2.5 A 1.0 5.7 8
Maximum 24 h average V2O5 A 0.1 0.1 1.1
Dust deposition A 50 mg/m2/day 109 mg/m2/day 120
mg/m2/day
Notes: 1. Mining and material handling. 2. Mining, material handling and power generation. 3. Mining, material handling, power generation and maximum allowable emission for roasting.
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Table 13.3 Summary of Results for Other Assessed Pollutants
Air Quality Indicator
Period Worst Affected
Receptor
Maximum Predicted
Concentrations from Project
(µg/m3)
Cumulative Prediction with
Background (µg/m3)
Criteria (µg/m3)
SO2 1 hour A 0 2 570
1 day A 0 4 230
1 year A 0 11 57
benzene 1 year A 0 4 10
CO 8 hour A 54 138 11,000
formaldehyde 1 day A 0 3 54
30 minutes A 0 4 110
NO2 1 year A 6 13 62
1 hour 1 A 165 175 250
benzo(a)pyrene (as a marker for
PAHs) 1 year A 0.0000 0.0001 0.0003
toluene 1 year A 0 7 410
1 day A 0 7 4,100
30 minutes A 0 8 1,100
xylene (total of all isomers)
1 year A 0 32 950
1 day A 0 36 1,200
acetaldehyde 3 minutes A 0 2.5 76 (odour)
590 (toxicity)
Notes: 1. 99.9th percentile
13.2 Recommendations
13.2.1 Overview
The following section identifies actions that should be undertaken to achieve compliance. These actions form the basis of an air quality management plan provided in Appendix C.
13.2.2 Review of NSW Study
Methods to mitigate and manage dust emissions in the Hunter Valley have been described and benchmarked by Katestone (2011).
Measures that are relevant and recommended for the Saint Elmo Project are listed in Table 13.4.
Table 13.4 Key Management Options from Hunter Valley Study
Source Measure proposed for Hunter Valley
Haul roads Watering, chemical surface suppressant e.g. salt, lignosulphonate or polymer, larger haul trucks to reduce number of trips, and limiting vehicle speeds to 40 km/hr.
Wind erosion Windbreaks using shade cloth on fresh dumps, revegetating as soon as practical, hydraulic mulch seeding.
Dozers and scraper Watering by watering truck dedicated to this.
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Source Measure proposed for Hunter Valley
Trucks dumping overburden Minimise drop height.
13.2.3 Management During Adverse Winds
The USEPA AP-42 methods for estimating fugitive dust have up until 2006 generally assumed a threshold for dust generation on exposed surfaces as being 5.4 m/s, however, the accepted knowledge was updated by AP-42 13.2.5 Industrial Wind Erosion (2006b). Based on that publication ASK has calculated emission rates for the different Pasquill Wind Speed Classes. These classes are commonly used in air quality to characterize the effect of wind on emissions and dispersion. With units of m/s they are:
• 0 – 1.54
• 1.54 – 3.09
• 3.09 – 5.14
• 5.14 – 8.23
• 8.23 – 10.80
• > 10.80
For exposed earth (not including coal), ASK calculated low emissions in the range 5.14 – 8.23 and substantial emissions in the ranges above 8.23 m/s. Hence a suitable threshold for adverse wind conditions may be 8 m/s. Monitoring of wind data either onsite or from Julia Creek Airport should be undertaken so that appropriate management measures can be undertaken such as watering of exposed areas during adverse weather conditions.
13.2.4 Project-specific Recommendations
The following specific actions are recommended to be undertaken during operation and should form the basis of an air quality management plan:
(1) Haul roads are to be treated with a chemical surface binder such as salt, lignosulphonate or polymer and watered as required.
(2) Haul trucks to be speed limited to a maximum of 40 km/hr.
(3) Surfaces being worked by dozers and scrapers are to be sprayed with water prior to the activities.
(4) When wind speed exceeds 8 m/s, undertake spraying of water onto all exposed surfaces.
(5) If monitoring shows exceedance of the PM10 criterion, no dozer and scraper activities shall be undertaken between 6pm to 7am during the months of March to May in the pit closer to the Saint Elmo homestead.
(6) An ESP or a fabric filter shall be installed for the roasting emissions and monitoring of stack emissions is to be undertaken to check that the roasting emissions do not exceed 10 g/s for PM10 and 91 g/s for SO2.
13.2.5 Monitoring
Monitoring during operation provides a measure of actual impacts at the monitoring locations.
(7) Monitor wind speed and direction at a height of eight or ten metres on a site meeting the requirements of AS3580.14 Methods for sampling and analysis of ambient air – Meteorological monitoring for ambient air quality monitoring applications as far as practical, either using the existing Julia Creek airport weather station or onsite.
(8) Monitor PM10 concentrations at or close to receptor A using an Australian Standard method such as AS/NZS 3580.9.9 Determination of suspended particulate matter – PM10 low volume sampler –
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Gravimetric method, or AS/NZS 3580.9.11 Determination of suspended particulate matter – PM10 beta attenuation monitors. This monitoring should be undertaken at least every sixth day in August, September and October for the first year of operation, and reviewed to determine the extent of future monitoring. It should also be undertaken in years when mining operations are in the areas close to Saint Elmo homestead as indicated by years 22 and 23 shown in Figure 3.1.
(9) For the duration of mining activities while receptor A is used as a residence, monitor dust deposition at or near the residence and at an upwind background location at the south-east of the mining lease, according to AS/NZS 3580.10.1 Methods for sampling and analysis of ambient air – Determination of particulate matter – Deposited matter – Gravimetric method.
(10) Should a non-frivolous complaint regarding health concerns about dust be received, monitor PM10 concentrations at a site representative of the complainant’s residence using an Australian Standard method such as AS/NZS 3580.9.9 Determination of suspended particulate matter – PM10 low volume sampler – Gravimetric method, or AS/NZS 3580.9.11 Determination of suspended particulate matter – PM10 beta attenuation monitors. This monitoring would be undertaken at least every sixth day over at least the subsequent three months from July to December, and reviewed to determine the extent of future monitoring.
(11) Should a non-frivolous complaint regarding dust nuisance be received, undertake dust deposition monitoring at a site representative of the complainant’s residence according to AS/NZS 3580.10.1 Methods for sampling and analysis of ambient air – Determination of particulate matter – Deposited matter – Gravimetric method. This monitoring would be undertaken for 12 months and the results reviewed to determine the extent of future monitoring.
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14. Risk Assessment of Impacts
14.1 Risk Assessment
Based on the results of the air quality assessment and the identified mitigation measures, a risk assessment has been undertaken for impacts associated with the operation of the Saint Elmo Vanadium Project. This risk assessment is also undertaken to assess likely impacts for the construction, commissioning, and decommissioning and closure phases of the mine. The risk assessment has applied the consequence criteria outlined in Table 14.1, and the likelihood of impact criteria in Table 14.2 to determine the overall risk of impact for individual project activities based on Table 14.3. The derived risk rating for each of the project activities is then summarised in Table 14.4.
The consequence criteria are based on accepted quantitative air quality criteria that address both health risks and impacts on amenity.
Table 14.1 Consequence Criteria
Impact Consequence Description of Consequence
Catastrophic
A substantial exceedance of an air quality criterion occurs that may lead to death.
Major
An exceedance of an air quality criterion occurs that may lead to serious but non-fatal health effects.
Moderate
Predictions are that the cumulative impacts will exceed a health criterion by up to a factor of two, or exceed a nuisance criterion.
Minor
Predictions are that incremental impacts are below the criterion, but within an order of magnitude, and cumulative impacts are also below the criterion.
Insignificant
Predictions are that incremental impacts will be an order of magnitude below the criterion.
Beneficial Action results in an improvement to air quality.
Table 14.2 Likelihood of Impact
Likelihood of Impacts Risk Probability Categories
Highly Unlikely Highly unlikely to occur but theoretically possible
Unlikely May occur during construction of the project but probability well below 50%; unlikely, but not negligible
Medium Probability of approximately 50%
Likely Likely to occur during construction or during a 12 month timeframe; probability greater than 50%
Almost Certain Very likely to occur as a result of the proposed project construction and/or operations; could occur multiple times during relevant impacting period
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Table 14.3 Risk Matrix
Likelihood Consequence
Insignificant Minor Moderate Major Catastrophic
Highly Unlikely Negligible Negligible Low Medium High
Unlikely Negligible Low Low Medium High
Medium Negligible Low Medium Medium High
Likely Negligible Medium Medium High Extreme
Almost Certain Low Medium High Extreme Extreme
Table 14.4 Air Emission Impact Assessment Table
Sources and Location Impacts Consequence Likelihood Risk Rating
Construction and Commissioning
Clearing of vegetation Exceedance of 24h particulate criteria insignificant unlikely negligible
Exceedance of annual particulate criteria insignificant unlikely negligible
Exceedance of dust deposition criterion insignificant unlikely negligible
Exceedance of gas criteria insignificant unlikely negligible
Construction of processing facility at the MIA and OWSF and associated infrastructure
Exceedance of 24h particulate criteria insignificant highly unlikely negligible
Exceedance of annual particulate criteria insignificant unlikely negligible
Exceedance of dust deposition criterion insignificant unlikely negligible
Exceedance of gas criteria insignificant highly unlikely negligible
Construction of access road
Exceedance of 24h particulate criteria insignificant unlikely negligible
Exceedance of annual particulate criteria insignificant unlikely negligible
Exceedance of dust deposition criterion insignificant unlikely negligible
Exceedance of gas criteria insignificant highly unlikely negligible
Operation
Mining and processing Exceedance of 24h particulate criteria moderate medium medium
Exceedance of annual particulate criteria minor medium low
Exceedance of dust deposition criterion minor medium low
Exceedance of gas criteria negligible unlikely negligible
OWSF operation Exceedance of 24h particulate criteria insignificant highly unlikely negligible
Exceedance of annual particulate criteria insignificant highly unlikely negligible
Exceedance of dust deposition criterion insignificant highly unlikely negligible
Exceedance of gas criteria insignificant highly unlikely negligible
Decommissioning and Closure
Decommissioning of equipment
Exceedance of 24h particulate criteria insignificant highly unlikely negligible
Exceedance of annual particulate criteria insignificant highly unlikely negligible
Exceedance of dust deposition criterion insignificant highly unlikely negligible
Exceedance of gas criteria beneficial NA NA
Rehabilitation Exceedance of 24h particulate criteria beneficial NA NA
Exceedance of annual particulate criteria beneficial NA NA
Exceedance of dust deposition criterion beneficial NA NA
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Sources and Location Impacts Consequence Likelihood Risk Rating
Exceedance of gas criteria beneficial NA NA
Notes: 1. NA = Not applicable as no risks associated with a benefit.
The implications of the risk ratings are listed in Table 14.5.
Table 14.5 Risk Rating Legend
Risk Rating Risk Probability Categories
Extreme An issue requiring change in project scope to reduce risk.
High For air quality this rating requires gathering of detailed project-specific data to improve the accuracy of the assessment, and/or extensive monitoring to ensure control measures are effective.
Medium An issue requiring project scope specific controls and procedures to manage.
Low Manageable by standard mitigation and similar operating procedures.
Negligible No additional management required.
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15. Conclusion
An air quality and greenhouse gas assessment has been conducted for the proposed Saint Elmo Vanadium Project. A summary of the results of the greenhouse gas assessment is as follows:
• The total Scope 1 and Scope 2 greenhouse gas emissions from the project is calculated to be 258 kt CO2-e or 0.062% of Australian NGER emissions and 0.17% of Queensland emissions.
Based on the assumptions used in the modelling, the results of the assessment are summarised as follows:
• There is a likelihood for receptor A to be impacted by the project especially during years of relatively high production schedule when the sources are closest to it.
• Other receptors are unlikely to be impacted by the emissions from the mine if appropriate dust control measures are in place as recommended in Section 13.2.
• Control and management measures have been recommended to prevent impacts at all the receptors.
• The emissions from construction, commissioning, the processing facility, OWSF, decommissioning and rehabilitation are unlikely to cause unacceptable impacts at the nearest sensitive receptors.
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Appendix A Glossary
Parameter or Term Description
Al2(SO4)3 Aluminium sulphate
As Arsenic
As2O3 Arsenic trioxide
AMV Ammonium metavanadate
ASK ASK Consulting Engineers Pty Ltd
BAM Beta attenuation monitor
BCM Bank Cubic Metres (volume of material in the ground prior to mining)
BoM Bureau of Meteorology
CSIRO Commonwealth Scientific and Industrial Research Organisation
DEM Digital Elevation Model
DERM Department of Environment and Resource Management
DES Department of Environment and Science
EHP Queensland Department of Environment and Heritage Protection
Epic Epic Environmental Ltd
EPA Queensland Environmental Protection Act 1994
EPP (Air) Queensland Environmental Protection (Air) Policy 2008
ESL Effects screening level
ESP Electrostatic precipitator
g/m2/month Grams per square metre per month
H2SO4 Sulphuric acid
HVAS High volume air sampler
kt/y Kilotonnes per year
Multicom Multicom Resource Ltd
mg/m2/day Milligrams per square metre per day
Mn Manganese
MnO Manganese (II) oxide
Na2CO3 Sodium carbonate
NaOH Sodium hydroxide
NaVO3 Sodium metavanadate
NEPM National Environmental Protection (Ambient Air Quality) Measure
NGER National Greenhouse and Energy Reporting
NH3 Ammonia
(NH4)2SO4 Ammonium sulphate
Ni Nickel
197401.0129.R01V09.docx 110
Parameter or Term Description
NiO Nickel (II) oxide
NOX Oxides of nitrogen
NO2 Nitrogen dioxide
NPI National Pollutant Inventory
NSW OEH New South Wales Office of Environment and Heritage
PAH Polycyclic aromatic hydrocarbons
Pb Lead
PbO Lead (II) oxide
PM2.5 Particulates suspended in air with aerodynamic diameter less than 2.5 microns
PM10 Particulates suspended in air with aerodynamic diameter less than 10 microns
QLD Queensland
RCP Representative Concentration Pathways
ROM Run of mine
SO2 Sulphur dioxide
SO3 Sulphur trioxide
SRTM Shuttle Radar Topography Mission
TAPM The Air Pollution Model developed by CSIRO and used by ASK for meteorological modelling
TEOM Tapered element oscillating microbalance
TSP Total particulates suspended in air
µg/m3 Micrograms per cubic metre
USEPA United States Environmental Protection Agency
V2O5 Vanadium pentoxide
VIC EPA SEPP Victorian Environment Protection Agency State Environment Protection Policy
VOC Volatile organic compounds
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Appendix B Emission Inventory Equations for Particulates
Topsoil removal by scraper
From USEPA (1998b) and Section A1.1.3 of Environment Australia (2012)
ETSP = 0.029 kg/Mg
Scraper Unloading
From USEPA (1998b)
ETSP = 0.02 kg/Mg
Scraper Travelling
Section A1.1.12 of Environment Australia (2012)
𝐸 =𝑘 (𝑠)1.3(𝑊)2.4
1,000,000
where
E = Emission Factor with units kg/VKT
s = silt content of material (%)
W = vehicle mass (t)
k = 9.6 for TSP
k = 1.32 for PM10
Loading to Trucks by Excavator
Equation 10 of Environment Australia (2012) has been used because it provides a method of varying emission rates with wind speed.
𝐸 = 0.0016 𝑘 (
𝑈
2.2)
1.3
(𝑀
2)
1.4
where
E = Emission Factor with units kg/t of overburden
U = mean wind speed (m/s)
M = soil moisture content (%)
k = 0.74 for TSP
k = 0.35 for PM10
Bulldozing
Equations 16 and 17 of Environment Australia (2012) have been used.
𝐸𝑇𝑆𝑃 = 2.6 × (𝑠)1.2
(𝑀)1.3
197401.0129.R01V09.docx 112
𝐸𝑃𝑀10= 0.34 ×
(𝑠)1.5
(𝑀)1.4
where
E = Emission factor with units kg/h/vehicle
s = Material silt content (%)
M = Soil moisture content (%)
Trucks Dumping
From equation 1 of USEPA (2006b):
𝐸 = 0.0016 𝑘 (
𝑈
2.2)
1.3
(𝑀
2)
1.4
where
E = Emission Factor with units kg/t of overburden
U = mean wind speed (m/s)
M = soil moisture content (%)
k = 0.74 for TSP
k = 0.35 for PM10
Wheel Dust Generation from Mine Vehicles on Unpaved Roads
From equation 1a of USEPA (2006c)
TSP
𝐸 = 4.9 × (𝑠
12)
0.7
× (𝑊
3)
0.45
{𝑙𝑏/𝑉𝑀𝑇}
Where: E = Emission factor s = Material silt content (%) W = mean vehicle weight (tonnes) Note – lb/VMT was converted to kg/VKT by multiplying lb/VMT by 0.2819
– vkt = vehicle kilometres travelled
PM10
𝐸 = 1.5 × (𝑠
12)
0.9
× (𝑊
3)
0.45
{𝑙𝑏/𝑉𝑀𝑇}
Where: E = Emission factor s = Material silt content (%) W = mean vehicle weight (tonnes) Note – lb/VMT was converted to kg/VKT by multiplying lb/VMT by 0.2819
197401.0129.R01V09.docx 113
Wheel Dust Generation from Mine Vehicles on Paved Roads
Equation 1 of USEPA (2011) as shown below has been used to calculate emissions from truck movements on paved road.
𝐸 = 𝑘 (𝑠𝐿)0.91(𝑊)1.02
where
E = Emission Factor with units matching the units of k
sL = road surface silt loading (g/m2)
W = average weight (tons) of vehicles on the road
k = 3.23 for TSP (g/VKT)
k = 0.62 for PM10 (g/VKT)
k = 0.15 for PM2.5 (g/VKT)
Due to the absence of silt loading data, the average silt loading for paved roads in quarries of 8.2 g/m2 (USEPA, 2011) has been used.
Grader
From Section A1.1.14 of Environment Australia (2012):
𝐸 = 0.0034 × 𝑆𝑘 where
E = Emission factor with units kg/vkt (vkt = vehicle kilometre travelled)
k = 2.5 for TSP
k = 2.0 for PM10
S = Mean Vehicle Speed (km/h)
Wind Erosion from Un-vegetated and Unsealed Surfaces
Environment Australia (2012) provides an NPI method for estimating annual emissions of dust from wind erosion based on either a default value published in 1983 or an equation published in 1998, which has several variables including number of rain days and average wind speed; however dispersion modelling is normally based on hourly time-steps and using this equation, the model will predict a small quantity of wind-blown dust every hour of the year. In reality, peak emissions of wind-blown dust will occur only during high wind speeds conditions during dry periods. During low wind speed conditions when particulates from other sources can accumulate, wind-blown dust will be negligible. Thus using the NPI equations will lead to inaccurate and un-timely contribution of wind-blown dust to the peak 24 hour predictions.
ASK calculates variable wind-blown dust emissions from exposed surfaces based on equations 2 and 3 of USEPA (2006a), which combine to become:
𝐸 = 𝑘 × (58 × (𝑢∗ − 𝑢𝑡∗)2 + 25 (𝑢∗ − 𝑢𝑡
∗))
Where: E = Emission factor with units g/m2/disturbance hour k = Constant (1.0 for TSP, 0.5 for PM10 and 0.075 for PM2.5) u* = surface friction velocity (m/s) ut
* = threshold friction velocity (m/s)
The surface friction velocity can be calculated for different wind speed classes (at 10 metre anemometer height, based on Equations 13.2.5-6 and 13.2.5-7 of AP-42 (USEPA 2006a) using the following three factors:
197401.0129.R01V09.docx 114
(12) Based on Table 13.2.5-3 the ratio of surface wind to 10 metre approach wind over a steep stockpile area ranges from 0.2 to 1.1. Parts of the stockpile where the ratio is 0.2 will likely never be eroded by wind. Parts of the stockpile where the ratio is 0.6 will trigger rarely if ever for coal only. Overburden will only trigger when the ratio reaches 1.1, which is 4% of less of the stockpile. Coal will trigger when the ratio is 0.9 to 1.1, which occurs over 15% of the stockpile.
(13) Using equation 13.2.5-7, the surface friction velocity is one tenth of the surface wind.
(14) However these calculations are based on “fastest-mile” wind speeds, which approximate the fastest 1-minute mean wind speed (Graybeal 2006). The wind speeds used in modelling are one hour means. Ratios (“G60”) of 1 minute means to one hour means are estimated by Ashcroft (1984) for different terrain types. For mostly open, fairly level terrain with a few buildings, G60 = 1.26.
Therefore for overburden, the surface friction velocity is calculated as 1.1 x 0.1 x 1.26 times the 10 metre approach wind. For coal the ratio is assumed to be 0.6 x 0.1 x 1.26 x the 10 metre approach wind.
For each wind speed category, the geometric mean surface friction velocities are shown in Table 15.1.
Table 15.1 Wind Speeds and Corresponding Surface Friction Velocities (m/s) for 4% of Exposed Earth and Overburden
Pasquill Wind Speed Class Corresponding Surface Friction Velocities
Mean Surface Friction Velocity
0 – 1.54 0 – 0.21 0.11
1.54 – 3.09 0.21 – 0.43 0.30
3.09 – 5.14 0.43 – 0.71 0.55
5.14 – 8.23 0.71 – 1.14 0.90
8.23 – 10.80 1.14 – 1.50 1.31
> 10.80 > 1.50 1.52
The threshold friction velocity (Table 13.2.5-2, USEPA 2006a) for overburden is 1.02 m/s, and for fine coal dust on concrete stockpile pads is 0.54 m/s. The resultant emission rates for different Pasquill wind speed classes are given in Table 15.2.
Table 15.2 Wind Erosion Emission Rates for Exposed Surfaces
Source Pasquill Wind Speed Class (m/s)
TSP (kg/ha/hour)
PM10 (kg/ha/hour)
PM2.5 (kg/ha/hour)
Overburden dumps 5.15 – 8.23 0.7 0.3 0.03
Overburden dumps 8.24 – 10.80 5 2 0.2
Overburden dumps > 10.80 10 5 0.4
197401.0129.R01V09.docx 115
Appendix C Air Quality Management Plan
Trinity Consultants Australia Pty Ltd T/A ASK Consulting Engineers
ABN: 62 630 202 201 ACN: 630 202 201 PO Box 3901 South Brisbane QLD 4101
[email protected] www.askconsulting.com.au
P +61 7 3255 3355
Saint Elmo Vanadium Project
Air Quality Management Plan
Report: 197401.0129.R03V02.docx
Prepared for:
Multicom Resources Ltd
22 May, 2020
197401.0129.R03V02.docx 2
Document Control Document Ref Date of Issue Status Author Reviewer
197401.0129.R03V01 28 April, 2020 Final Michelle Yu AM
197401.0129.R03V02 22 May, 2020 Updated to address comments
Michelle Yu AM
Document Approval
Approver Signature
Name Andrew Martin
Title Air Quality Manger
Disclaimer: This document and associated tasks were undertaken in accordance with the ASK Consulting Engineers Quality Assurance System, which is based on Australian Standard / NZS ISO 9001:2008. This document is issued subject to review, and authorisation by a Senior Consultant noted in the above table. If the table is incomplete, this document shall be considered as preliminary or draft only and no reliance shall be placed upon it other than for information to be verified later.
This document is prepared for our Client's particular requirements which are based on a specific brief with limitations as agreed to with the Client. It is not intended for and should not be relied upon by a third party and no responsibility is undertaken to any third party without prior consent provided by ASK Consulting Engineers. The information herein should not be reproduced, presented or reviewed except in full. Prior to passing on to a third party, the Client is to fully inform the third party of the specific brief and limitations associated with the commission.
The information contained herein is for the identified purpose of air quality assessment only. No claims are made and no liability is accepted in respect of design and construction issues falling outside of the specialist field of air quality science including and not limited to structural integrity, fire rating, architectural buildability and fit-for-purpose, waterproofing, safety design and the like. Supplementary professional advice should be sought in respect of these issues.
Copyright: This report and the copyright thereof are the property of Trinity Consultants Australia Pty Ltd (ABN 62 630 202 201). It must not be copied in whole or in part without the written permission of Trinity Consultants Australia Pty Ltd. This report has been produced specifically for the Client and project nominated herein and must not be used or retained for any other purpose. www.askconsulting.com.au
197401.0129.R03V02.docx 3
Contents
1. Introduction 4
1.1 Background 4
1.2 Scope and Objectives 5
1.3 Relevant Legislative Instruments 5
1.4 Air Quality Criteria 5
1.5 Roles and Responsibilities 6
2. Background Information 8
2.1 Overview 8
2.2 Sensitive Receptors 8
2.3 Mining Operations 9
2.4 Processing Operations 10
3. Air Quality Management Strategy 11
3.1 Air Quality Control Measures 11
3.2 Monitoring 11
3.3 Adaptive Dust Management 13
3.4 Complaint Management 13
3.5 Reporting, Auditing and Corrective Measures 14
References 15
Appendices
Appendix A Glossary 16
Table of Figures Figure 1.1 Location of the Saint Elmo Project (Image from Google Earth Pro) 4
Figure 2.1 Location of Sensitive Receptors & Monitors (Image from Queensland Globe Overlay) 9
197401.0129.R03V02.docx 4
1. Introduction
1.1 Background
ASK Consulting Engineers Pty Ltd (ASK) has been commissioned by Multicom Resources Limited (Multicom) to develop an Air Quality Management Plan (AQMP) for the Saint Elmo Vanadium Project, a vanadium mine. The location is approximately 14 km to the east of Julia Creek, immediately to the north of Flinders Highway in north-west Queensland (QLD) as shown in Figure 1.1.
Figure 1.1 Location of the Saint Elmo Project (Image from Google Earth Pro)
Multicom is seeking to develop the Saint Elmo Vanadium Project (the Project) for the purposes of mining and processing vanadium pentoxide and alternative vanadium-based products. The Project will consist of a shallow open cut mine, ranging in depth from 20 to 40 metres (depending on depth of overburden), with associated dump and haul operations in order to obtain access to large known deposits of vanadium bearing sedimentary material. Strip mining is proposed to be carried out sequentially from mining panels along the north-south axis of Mining Lease Application (MLA) 100162, a greenfield site. Once the material is removed, the panel will be back filled with beneficiated gangue and overburden material, then contoured and sheeted with topsoil. Subsequently, revegetation with native species or as otherwise agreed with relevant stakeholders will take place.
MLA100162 is located approximately 25 kilometres east of Julia Creek in the priority North West Minerals Province of north western Queensland, within the McKinlay Local Government Area (LGA). The area of MLA100162 is approximately 8,882 hectares.
In order to support mining activities, an operating water supply will be stored in an Offsite Water Storage Facility (OWSF). The OWSF and associated infrastructure are located approximately 21 km to the east of
150 km
Mount Isa Saint Elmo Project
Julia Creek
Townsville
197401.0129.R03V02.docx 5
MLA100162. A water entitlement to harvest from the Flinders River is through the Department of Natural Resources, Mines and Energy (DNRME). The OWSF and associated infrastructure comprise three separate mine (infrastructure) lease components: MLA100244 – OWSF infrastructure area, MLA100245 – pipeline from OWSF to Project site and MLA100246 – aqueduct from the OWSF to Flinders River.
1.2 Scope and Objectives
The scope of this AQMP is as follows:
• Identify relevant legislative requirements and criteria.
• Outline the key roles and responsibilities for the implementation of this AQMP.
• Review the relevant information including identification of sensitive receptors and the Project’s air emission sources.
• Develop air quality management strategies including air quality control measures, monitoring, adaptive dust management, complaint management and reporting and auditing.
The objectives of this AQMP are as follows:
• to achieve compliance with regulatory requirements
• to mitigate risks and complaints from regulators, community and other stakeholders
• to document and continually improve the Project’s performance related to this AQMP.
1.3 Relevant Legislative Instruments
The following legislations and guidelines provide relevant air quality criteria for this Project:
• Queensland Environmental Protection (Air) Policy 2019 (EPP(Air))
• Queensland Department of Environment and Sciences (DES) Guideline, version 4.03 (DES, 2019)
The proposed EA conditions include additional criteria for stack emissions.
1.4 Air Quality Criteria
The relevant ambient air quality criteria for this Project based on state legislation are summarised in Table 1.1. As discussed in Section 2.3, PM10 is the critical size fraction based on the Environmental Impact Statement (EIS) report and would therefore determine compliance. Table 1.2 presents the objectives of the Project for its stationary source emissions as per the proposed EA conditions.
Table 1.1 Relevant Ambient Air Quality Criteria at the Sensitive Receptors
Air Quality Indicator Period Criteria (µg/m3)
PM10 1 day 50
1 year 25
dust deposition 30 days 120 mg/m2/day
Table 1.2 Relevant EA Criteria for Stationary Sources
Source Minimum Release
Height (m)
Minimum Exit Gas Temperature (°C)
Minimum Efflux Velocity (m/s)
Pollutant Release Limit
Minimum Monitoring Frequency
Roasting kiln 35 150 10 50 g/Nm3 SO2
5.5 g/Nm3 PM10 Annually
De-ammoniation plant
N/A N/A N/A 100 mg/Nm3 Annually
197401.0129.R03V02.docx 6
1.5 Roles and Responsibilities
The key roles and responsibilities for this AQMP are presented in Table 1.3.
Table 1.3 Key Responsible People of Saint Elmo Mine for this AQMP
Role Responsibilities
Mine Management • Ensure that the Mine is adequately resourced to implement the requirements of the AQMP.
Environmental Manager • Oversee the implementation of this AQMP.
• Coordinate the necessary resources to ensure the monitoring requirements of the EA are satisfied.
• Provide training to employees and contractors for the implementation of the air quality control and management measures outlined in this AQMP.
• Inform DES of all instances of non-compliance with the EA conditions as soon as practicable.
• Ensure that appropriate reporting is undertaken in a timely manner and ensure the quality of data and reports.
• Oversee the non-compliance and complaint investigation, and develop plan to avoid or mitigate potential similar future incidents.
• Liaise with DES and other relevant stakeholders with respect to all significant air quality matters.
• Monitor and review the performance of the Mine in relation to this AQMP.
• Identify improvement opportunities in this AQMP.
• Organise internal and external audit of this AQMP and prepare a revision if necessary.
Environmental Officers • Assist the Environmental Manager with regards to the implementation of this AQMP.
• Prepare air quality reports for DES and other stakeholders. Ensure reports are prepared in a timely manner.
• Liaise with complainant and record and investigate the complaint in a timely manner.
• Assist the Environmental Manager in providing training to employees and contractors for the implementation of the air quality control and management measures outlined in this AQMP.
• Undertake routine maintenance of air quality monitors and routine inspection or review of performance of air quality control equipment.
• Monitor and review the monitoring data, and inform the Environmental Manager of suspect data or non-compliance.
• Take appropriate immediate action during trigger events as discussed in Section 3.3 in consultation with the Environmental Manager and mine operators.
• Maintain proper documentation of monitoring data and complaints register.
Air Quality Monitoring Contractors
• Collect, analyse and report the data in accordance with legislative requirements, Australian Standards, US EPA Methods, or equivalent.
197401.0129.R03V02.docx 7
Role Responsibilities
Mine operators • Apply the control measures outlined in this AQMP.
• Assist the Environmental Team in applying adaptive dust management strategies.
• Report excessive dust emissions to their supervisor or the Environmental Team.
197401.0129.R03V02.docx 8
2. Background Information
2.1 Overview
The site for the proposed vanadium mine is located on rural, agricultural land. Immediately to the south of the proposed mining boundary is the Flinders Highway. The OWSF and the associated infrastructure are located near the Flinders River north-east of the mine, with the pipeline from OWSF to the mine following Punchbowl Road.
2.2 Sensitive Receptors
The predominant existing land use in the surrounding area is grazing with some homesteads interspersed on rural properties. The nearest existing sensitive receptors are summarised in Table 2.1 and are shown in Figure 2.1. The closest is receptor A (Saint Elmo) and is approximately 270 metres west of the mining lease boundary. All of the receptors listed in Table 2.1 are residences.
Table 2.1 List of Sensitive Receptors with UTM Coordinates (WGS84 Z54)
ID Name / Address
Real Property Description
Approximate Distance and Direction from Site Boundary
Easting
(m)
Northing
(m)
Latitude (°)
Longitude (°)
A Saint Elmo
Lot 13 EN89 270 m west 590175 7722971 -20.5901 141.8653
B Argyle Lot 4 EN30 4.2 km west 584451 7724151 -20.5798 141.8104
C Burwood Lot 4 MF16 6.8 km north 588714 7739955 -20.4369 141.8503
D Lindfield Lot 2 MF3 10 km north-east 598316 7739202 -20.4431 141.9424
E Garomna Lot 11 EN105 6.2 km south-west 591181 7709990 -20.7074 141.8756
Julia Creek township is approximately 13 kilometres from the western boundary of the mining lease and therefore very unlikely to be impacted by emissions from the mine.
Based on the land uses, it is considered unlikely that additional residences would be constructed in the surrounding areas during the lifetime of the proposed mine.
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Figure 2.1 Location of Sensitive Receptors & Monitors (Image from Queensland Globe Overlay)
2.3 Mining Operations
The mine plan is based on typical truck and excavator operations. Mining will be carried out sequentially from mining panels. Once material is removed, the panel will be back-filled with reject materials including beneficiated gangue, and overburden, subsoil and topsoil materials. Overburden materials from other panels will be pushed with dozers to back-fill the mined panel, exposing ore from the other panels which will then be mined. The back-filled overburden and reject materials will then be sheeted with topsoil for revegetation. Progressive rehabilitation will then be undertaken.
The mining operations are summarised as follows:
• Vegetation will be cleared.
Saint Elmo Project
5000 m
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• Topsoil will be removed, temporarily stockpiled and used to progressively rehabilitate exposed areas.
• Shallow pits (on average 20 metres deep) will be excavated and the overburden stockpiled for use during in-pit covering of reject material to final landform level.
• Dozers will push reject material/overburden to back-fill the areas that have been previously mined. This will also expose the coquina ore materials underlying the pushed overburden. Other dozers will be used to rehabilitate the mine.
• Excavators will side cast the rehandle overburden wedge.
• Excavators will load the mined ore into haul trucks to be transported from the pits to the run-of-mine (ROM) pad.
• Haul trucks will unload ROM ore at the ROM pad. All the ore from the ROM stockpiles will be rehandled to feed the processor which will involve loading the ore from the ROM stockpiles to trucks and hauling to the processing area.
• Reject material that is discarded during the processing phase will be temporarily stockpiled, loaded and hauled back to the open pit where it will be used for backfilling and rehabilitated.
• Ore will be processed within the MIA until a high purity vanadium pentoxide flake is produced.
• Product will be transported to Townsville by rail.
• Maintenance and servicing of plant and equipment will be undertaken at the MIA.
• Water will be supplied from the OWSF which will pump water to the mine via pipeline along Punchbowl Road.
Based on the air quality assessment undertaken for the Project (ASK, 2020), receptor A would be the most affected by air emissions from the mine, and receptor E the least affected. The 24-hour average PM10 criterion is the most likely to be exceeded especially from 6pm to 7am during the months of March to May. Dozers and scraper would be the major air emission contributors. The 24-hour average PM10 exceedance at receptor A is more likely during the years when mining activities are closer to the receptor.
The operation of the OWSF would emit combustion gases from diesel generators, but these are not likely to cause discernible impacts at the nearest sensitive receptor (receptor D). The nearest emission source relevant to the OWSF would be the dust emissions from the pipeline works, approximately 4.7 kilometres from receptor D at the nearest point. Although not likely to cause discernible impacts at the sensitive receptors, construction and decommissioning of the OWSF and pipelines would adapt the dust management measures in this AQMP.
2.4 Processing Operations
The processing operations at the mining infrastructure area (MIA) also have emissions that are predicted to be acceptable after dispersion to the sensitive receptors based on the air quality assessment (ASK, 2020), except that as there is no site-specific information for the roasting emissions, the maximum allowable roasting emissions were calculated to determine compliance at the sensitive receptors. The roasting emission limits of critical pollutants are included in the proposed EA conditions and summarised in Table 1.2.
The de-ammoniation plant will have a scrubber with a guaranteed ammonia exhaust of <100 mg/Nm3.
The roasting emissions and the de-ammoniation plant emissions are to be monitored at the source as per the proposed EA conditions.
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3. Air Quality Management Strategy
3.1 Air Quality Control Measures
The air quality control measures to be implemented as part of the Saint Elmo Mine Project are summarised in Table 3.1. These are consistent with best practice dust management measures as benchmarked by Katestone (2011), while some are project-specific based on the outcome of the air quality assessment (ASK, 2020).
Table 3.1 Air Quality Control Measures
Source Emission Control Measures
Haul roads • Water haul road surfaces.
• Apply chemical surface suppressant e.g. salt, lignosulphonate or polymer to major haul road surfaces.
• Use large haul trucks to reduce number of trips.
• Limit vehicle speeds to 40 km/hr.
Wind erosion • Install windbreaks using shade cloth on fresh dumps.
• Revegetate as soon as practical, hydraulic mulch seeding.
• Water exposed areas during adverse weather conditions. A suitable threshold for adverse wind conditions may be 8 m/s.
Dozers, scraper and graders • Water surfaces by watering truck prior to the activities.
• No dozer and scraper activities shall be undertaken between 6pm to 7am during the months of March to May in the pit closer to the Saint Elmo homestead if monitoring shows exceedance of the PM10 criterion.
Trucks dumping overburden • Minimise drop height.
Roasting • An electrostatic precipitator (ESP) or a fabric filter shall be installed for the
roasting emissions.
De-ammoniation plant • A scrubber shall be installed for the de-ammoniation plant.
3.2 Monitoring
Monitoring during operation provides a measure of actual impacts at the monitoring locations.
(1) Monitor wind speed and direction at a height of eight or ten metres on a site meeting the requirements of AS3580.14 Methods for sampling and analysis of ambient air – Meteorological monitoring for ambient air quality monitoring applications as far as practical, either using the existing Julia Creek airport weather station or onsite.
(2) Monitor PM10 concentrations at or close to receptor A using an Australian Standard method such as AS/NZS 3580.9.9 Determination of suspended particulate matter – PM10 low volume sampler – Gravimetric method, or AS/NZS 3580.9.11 Determination of suspended particulate matter – PM10 beta attenuation monitors. This monitoring should be undertaken at least every sixth day in August, September and October for the first year of operation, and reviewed to determine the extent of future monitoring. It should also be undertaken in real-time in years when mining operations are in the areas close to Saint Elmo homestead as indicated by years 22 and 23 in the EIS.
(3) For the duration of mining activities while receptor A is used as a residence, monitor dust deposition at or near the residence and at an upwind background location at the south-east of the mining lease, according to AS/NZS 3580.10.1 Methods for sampling and analysis of ambient air – Determination of particulate matter – Deposited matter – Gravimetric method. Dust deposition
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monitors shall also be installed within the mining boundary at the general upwind and downwind direction of the mine to the sensitive receptors
(4) Should a non-frivolous complaint regarding health concerns about dust be received, monitor PM10 concentrations at a site representative of the complainant’s residence using an Australian Standard method such as AS/NZS 3580.9.9 Determination of suspended particulate matter – PM10 low volume sampler – Gravimetric method, or AS/NZS 3580.9.11 Determination of suspended particulate matter – PM10 beta attenuation monitors. This monitoring would be undertaken at least every sixth day over at least the subsequent three months from July to December, and reviewed to determine the extent of future monitoring.
(5) Should a non-frivolous complaint regarding dust nuisance be received, undertake dust deposition monitoring at a site representative of the complainant’s residence according to AS/NZS 3580.10.1 Methods for sampling and analysis of ambient air – Determination of particulate matter – Deposited matter – Gravimetric method. This monitoring would be undertaken for 12 months and the results reviewed to determine the extent of future monitoring.
(6) Monitoring of roasting and de-ammoniation emissions shall be undertaken once per year according to the following methods:
(a) AS 4323.1-1995 or equivalent
(b) USEPA Methods 2 Determination of Stack Gas Velocity and Volumetric Flow Rate (Type S Pitot Tube), or equivalent
Roasting emissions shall also be undertaken according to the following additional methods:
(c) USEPA Method 6 Determination of Sulfur Dioxide Emissions from Stationary Sources, or equivalent
(d) USEPA Method 201A Determination of PM10 and PM2.5 Emissions from Stationary Sources, or equivalent
De-ammoniation emissions shall also be undertaken according to the following additional method:
(e) USEPA Conditional Test Method (CTM) 027 Determination of Ammonia Emissions in Stationary Sources, or equivalent
The proposed ambient monitoring locations are summarised in Table 3.2 and Table 3.3 and are shown in Figure 2.1.
Table 3.2 Dust Deposition Monitoring Location
Monitoring Location
Approximate Location (GDA 94 MGA Zone 54)
Location Description
DDG1 590440, 7722966 General downwind direction of Saint Elmo and Argyle homesteads
DDG2 589396, 7733165 General downwind direction of Burwood homestead
DDG3 592200, 7731258 General downwind direction of Linfield homestead1
DDG4 590203, 7722982 Saint Elmo homestead2
DDG5 597371, 7723069 Upwind when wind blowing toward Saint Elmo homestead
1 General direction of Linfield homestead when mining activities are closest to the homestead. 2 DDG4 also serves as upwind dust gauge of Burwood and Linfield homesteads when mining activities are closest these homesteads. DDG4 is the only location in this table that needs to comply with the relevant limit.
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Table 3.3 PM10 Monitoring Location
Monitoring Location
Approximate Location (GDA 94 MGA Zone 54)
Location Description
PM10-1 590203, 7722982 Saint Elmo homestead
1 Due to the anticipated higher risk impacts at Saint Elmo homestead, continuous monitoring will be undertaken at the Saint Elmo homestead in August to October for the first year of mining operation, and reviewed to determine the extent of future monitoring. PM10 monitoring at Saint Elmo homestead should also be undertaken in years when mining operations are in the areas close to the
homestead as indicated by years 22 and 23 in the EIS report.
3.3 Adaptive Dust Management
The adaptive dust management measures will include additional control measures based on the following triggers:
• Visual monitoring of dust generation
• Real time PM10 monitoring at Saint Elmo homestead or at a complainant’s residence
• Real time monitoring of wind conditions
• Complaint.
In the event dust emissions continue to cause adverse impacts on site or to surrounding sensitive receptors, additional dust control measures will be implemented in the following hierarchy:
(1) Increase watering application to haul roads, exposed surfaces and/or materials to be handled.
(2) Minimise dust-generating activities responsible for elevated dust levels such as the suspension of some or all of the dozer and scraper operations or suspension of excavation, loading and unloading during high wind speed conditions.
(3) Suspension of night-time dust-generating activities responsible for elevated dust levels such as dozer and scraper operations (6pm to 7am).
(4) Suspension or modification of other dust-generating activities such as excavation, loading and hauling.
3.4 Complaint Management
Saint Elmo Mine shall have a complaint hotline telephone number that is available at all times and email address for complaints. The complaints shall be recorded in a register and will include the following information:
(1) Date and time of complaint
(2) Nature of complaint
(3) Method by which the complaint was received (e.g. phone, email, etc)
(4) Name and title of the person who receives the complaint
(5) Address and contact details of the complainant, if made available
(6) Action taken in relation to the complaint, including any follow-up contact, the outcome of investigations and any required on-going actions.
(a) If no action was taken, then include the reason why no action was taken.
(7) The status of the concern (e.g. resolved, continuing or unresolved).
Complaints are to be investigated by the Environmental Team which will include an immediate review of the following at the time of complaint:
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(1) Meteorological data
(2) Air quality monitoring data
(3) Mine operations
If the current operation of the mine is likely causing valid air quality concerns based on the results of the complaint investigation, appropriate actions are to be taken as soon as practicable as discussed in Section 3.3.
If the immediate investigation is inconclusive, further investigation is to be undertaken which may include:
• a site inspection of the complainant’s residence
• monitoring of air quality at or near the complainant’s residence as per discussions in Section 3.2
• investigation of other potential air emission sources in the vicinity of the complainant’s residence
• review of regional air quality data.
3.5 Reporting, Auditing and Corrective Measures
The Environmental Team shall prepare an annual air quality report that provides results of the monitoring undertaken for the year and the report shall be made publicly available on the Saint Elmo Mine’s website and also submitted to the DES.
The Environmental Team shall notify the DES of non-compliance of air quality criteria as soon as practicable. Non-compliances shall be investigated and preventative and corrective actions shall be planned.
The performance of the AQMP shall be audited annually by internal parties and every three years by external third party auditors. The audit shall include the examination of the key components of the AQMP, review of complaints management and evaluation of the overall performance of the air quality management. The outcome of the audit will guide the revision of the AQMP, if needed, to ensure compliance of air quality criteria and continual improvement.
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References
AS/NZS 3580.9.9-2006 Determination of suspended particulate matter – PM10 low volume sampler –
Gravimetric method
AS/NZS 3580.10.1-2016: Methods for sampling and analysis of ambient air – Determination of particulate
matter – Deposited matter – Gravimetric method
AS3580.14-2014 Methods for sampling and analysis of ambient air – Meteorological monitoring for
ambient air quality monitoring applications
AS4323.1-1995: Stationary Source Emissions – Selection of Sampling Positions
ASK (2020), Saint Elmo Vanadium Project Air Quality and Greenhouse Gas Technical Report, Report
197401.0129.R01V04 for Multicom Resources Limited, 28 April, 2020.
DES (2019), Guideline: Application requirements for activities with impacts to air, version 4.03, Queensland
Department of Environment and Science.
Environmental Protection Agency (2019), Environmental Protection (Air) Policy, Queensland Government.
Katestone (2011), NSW Coal Mining Benchmarking Study: International Best Practice Measures to Prevent
and/or Minimise Emissions of Particulate Matter from Coal Mining, Katestone Environmental report
KE1006953 for NSW Office of Environment and Heritage.
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Appendix A Glossary
Parameter or Term Description
AQMP Air Quality Management Plan
ASK ASK Consulting Engineers
DES Queensland Department of Environment and Science
EIS Environmental Impact Statement
EPP(Air) Queensland Environmental Protection (Air) Policy 2019
g/Nm3 Grams per normal cubic metre
LGA Local Government Area
m/s Metres per second
mg/m2/day Milligrams per square metre per day
mg/Nm3 Milligrams per normal cubic metre
MLA Mining Lease Application
PM2.5 Particulates suspended in air with aerodynamic diameter less than 2.5 microns
PM10 Particulates suspended in air with aerodynamic diameter less than 10 microns
QLD Queensland
SO2 Sulphur dioxide
TSP Total particulates suspended in air
µg/m3 Micrograms per cubic metre