aa-ex961_518.htm

EX-96.1 15 aa-ex961_518.htm EX-96.1 aa-ex961_518.htm

EXHIBIT 96.1

Technical Report Summary on the Darling Range, Western Australia S-K 1300 Report Alcoa Corporation SLR Project No: 425.01184.00071 February 24, 2022

Technical Report Summary on the Darling Range, Western Australia

SLR Project No: 425.01184.00071

Prepared by

SLR International Corporation

22118 20th Ave SE, Suite G202

Bothell, WA 98021 USA

for

Alcoa Corporation

201 Isabella Street, Suite 500

Pittsburgh, Pennsylvania

15212-5858

Effective Date – December 31, 2021

Signature Date - February 24, 2022

Distribution:1 copy – Alcoa Corporation

1 copy – SLR International Corporation

1 copy – SLR Consulting Ltd

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Technical Report Summary - February 24, 2022

Contents

1.0	EXECUTIVE SUMMARY	1-1
1.1	Summary	1-1
1.2	Economic Analysis	1-7
1.3	Technical Summary	1-9
2.0	INTRODUCTION	2-1
2.1	Site Visits	2-1
2.2	Sources of Information	2-2
2.3	List of Abbreviations	2-3
3.0	PROPERTY DESCRIPTION	3-1
3.1	Location	3-1
3.2	Land Tenure	3-1
3.3	Naming Conventions	3-6
3.4	Encumbrances	3-7
3.5	Royalties	3-8
3.6	Required Permits and Status	3-8
3.7	Other Significant Factors and Risks	3-9
4.0	ACCESSIBILITY, CLIMATE, LOCAL RESOURCES, INFRASTRUCTURE AND PHYSIOGRAPHY	4-1
4.1	Accessibility	4-1
4.2	Climate	4-1
4.3	Local Resources	4-2
4.4	Infrastructure	4-2
4.5	Physiography	4-3
5.0	HISTORY	5-1
5.1	Prior Ownership	5-1
5.2	Exploration and Development History	5-1
6.0	GEOLOGICAL SETTING, MINERALIZATION, AND DEPOSIT	6-1
6.1	Bauxite deposits	6-1
6.2	Regional Geology	6-1
6.3	Local Geology	6-4
6.4	Mineralization	6-4
6.5	Property Geology	6-5
7.0	EXPLORATION	7-1
7.1	Exploration	7-1
7.2	Resource Definition Drilling	7-1
7.3	Drilling methods	7-5
7.4	Drill sampling	7-7
7.5	Topography	7-11
7.6	Surveying	7-13
7.7	Sampling conclusions	7-15
7.8	Hydrogeology Data	7-15
7.9	Geotechnical Data	7-15
8.0	SAMPLE PREPARATION, ANALYSES, AND SECURITY	8-1
8.1	Sample security	8-1

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8.2	Sample preparation	8-1
8.3	Assaying	8-3
8.4	Quality Assurance (QA)	8-8
8.5	Quality Control (QC)	8-9
9.0	DATA VERIFICATION	9-1
9.1	Data structures	9-1
9.2	Data verification measures	9-2
9.3	QP Opinion	9-3
10.0	MINERAL PROCESSING AND METALLURGICAL TESTING	10-1
10.1	QP opinion	10-3
11.0	MINERAL RESOURCE ESTIMATES	11-1
11.1	Summary	11-1
11.2	Resource Database	11-3
11.3	Geological Interpretation	11-3
11.4	Statistical Checks	11-8
11.5	Treatment of High-Grade Assays	11-12
11.6	Compositing	11-14
11.7	Trend Analysis - Variography	11-14
11.8	Bulk Density	11-15
11.9	Resource Models	11-18
11.10	Block Model Validation	11-20
11.11	Cut-off Grade and Mining Constraints	11-26
11.12	Reconciliation	11-27
11.13	Mineral Resource estimation risk	11-29
11.14	Classification	11-31
11.15	Mineral Resource Reporting	11-35
11.16	QP Opinion	11-36
12.0	MINERAL RESERVE ESTIMATES	12-1
12.1	Summary	12-1
12.2	Modifying Factors	12-2
12.3	Basis of Estimate	12-4
12.4	Dilution and Ore Loss	12-4
12.5	Extraction and Mine Planning	12-5
12.6	Cut-off Grade	12-10
12.7	Metallurgical Factors	12-11
12.8	QP Opinion	12-11
13.0	MINING METHODS	13-1
13.1	General Description of Operations	13-1
13.2	Haul Roads and Infrastructure	13-4
13.3	Geotechnical and Hydrogeology Considerations	13-7
13.4	Mine Equipment	13-11
13.5	Personnel	13-14
14.0	PROCESSING AND RECOVERY METHODS	14-1
14.1	Process Description	14-1
14.2	Primary Equipment List	14-4
14.3	Consumables and Power	14-5
14.4	QP Opinion	14-5

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15.0	INFRASTRUCTURE	15-1
15.1	Access Roads	15-3
15.2	Power	15-3
15.3	Water	15-3
15.4	Accommodation Camp	15-4
15.5	Mine Waste Management	15-4
16.0	MARKET STUDIES	16-1
16.1	Overview	16-1
16.2	Market: Darling Range	16-2
16.3	Contracts	16-3
17.0	ENVIRONMENTAL STUDIES, PERMITTING, AND PLANS, NEGOTIATIONS, OR AGREEMENTS WITH LOCAL INDIVIDUALS OR GROUPS	17-1
17.1	Environmental Studies	17-1
17.2	Waste and Tailings Disposal, Site Monitoring, and Water Management	17-1
17.3	Project Permitting	17-4
17.4	Social or Community Requirements	17-4
17.5	Mine Closure Requirements	17-5
17.6	Local Procurement and Hiring	17-6
18.0	CAPITAL AND OPERATING COSTS	18-1
18.1	Capital Costs	18-1
18.2	Operating Costs	18-1
19.0	ECONOMIC ANALYSIS	19-1
19.1	Economic Criteria	19-1
19.2	Cash Flow Analysis	19-2
19.3	Sensitivity Analysis	19-3
20.0	ADJACENT PROPERTIES	20-1
21.0	OTHER RELEVANT DATA AND INFORMATION	21-1
22.0	INTERPRETATION AND CONCLUSIONS	22-1
22.1	Geology and Mineral Resources	22-1
22.2	Mining and Mineral Reserves	22-2
22.3	Mineral Processing	22-3
22.4	Infrastructure	22-3
22.5	Environment	22-4
23.0	RECOMMENDATIONS	23-1
23.1	Geology and Mineral Resources	23-1
23.2	Mining and Mineral Reserves	23-2
23.3	Mineral Processing	23-2
23.4	Infrastructure	23-2
23.5	Environment	23-2
24.0	REFERENCES	24-1
25.0	RELIANCE ON INFORMATION PROVIDED BY THE REGISTRANT	25-1
26.0	DATE AND SIGNATURE PAGE	26-1

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iii

TABLES


Table 1 1: LOM Technical-Economic Assumptions	1-7
Table 1‑2: LOM Indicative Economic Results	1-8
Table 1-3: 10 Year LOM Sustaining Capital Costs by Area	1-18
Table 1-4: LOM On-site Mine Operating Costs by Category	1-18
Table 3-1: ML1SA license details	3-2
Table 4-1: Historical Climate Data	4-1
Table 6-1: Alcoa’s Darling Range deposit typical stratigraphic column	6-5
Table 6-2: Summary of typical (modal) stratigraphic horizons within each area	6-6
Table 7-1: Drill quantities by year and location	7-2
Table 7-2: Logging codes for Material Type	7-10
Table 8-1: Assaying methodologies for resource estimation samples	8-5
Table 8-2: Standards used for drilling and REF monitoring (IRMs)	8-10
Table 8-3: Summary of performance of IRMs KH10 and KH14 for the full analytical suite	8-11
Table 8-4: Summary of precisions for umpire check results on assay dataset P175	8-16
AL, SI, FE and OX at SGS and BV compared to KWI	8-16
Table 8-5: Summary of precisions and means for 678 STE tests (November 2020)	8-22
Table 8-6: Summary of precisions and means for REF vs FTIR (final corrected result)	8-26
Table 8-7: Summary of pulp repeats for Myara North (P159): MD-ICP (Original) vs New FTIR	8-27
Table 8-8: Summary of pulp repeats for Larego (P163): MD-ICP (Original) vs New FTIR	8-28
Table 8-9: Summary of pulp repeats for Larego (P163) – trimmed: MD-ICP (Original) vs New FTIR	8-28
Table 8-10: Summary of Stockpile Belt paired samples for Myara North in 2018: 292 pairs for SP-271 vs SP-171	8-33
Table 9-1: Count of records by database Table for two database extracts	9-2
Table 10-1: Product grades of Darling Range Operation (Willowdale – Wagerup refinery feed)	10-1
Table 10-2: Product grades of Darling Range operations (Huntly–Pinjarra refinery feed)	10-2
Table 10-3: Product grades of Darling Range operations (Huntly– Kwinana refinery feed)	10-2
Table 11-1: Summary of Mineral Resources exclusive of Mineral Reserves – 31st December 2021	11-2
Table 11-2: Summary of density test data (t/m3) from 1980 to 1992 (Senini, 1993)	11-16
Table 11-3: Ordinary Kriging search parameters	11-20
Table 11-4: Summary of Mineral Resources exclusive of Mineral Reserves by Mining Region – 31st December 2021	11-35

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Table 12-1: Summary of Mineral Reserves – Effective 31st December 2021	12-1
Table 13-1: Darling Range operations equipment list	13-11
Table 13-2: Darling Range personnel	13-14
Table 14-1: Primary equipment list (Willowdale)	14-4
Table 14-2: Primary equipment list (Huntly)	14-4
Table 15-1: Water Abstraction License Volumes	15-4
Table 18-1: LOM Sustaining Capital Costs by Area	18-1
Table 18-2: LOM Mine Operating Costs by Category	18-2
Table 18-3: Workforce Summary	18-2
Table 19-1: Technical-Economic Assumptions	19-1
Table 19-2: LOM Production Summary	19-2
Table 19-3: LOM Indicative Economic Results	19-3

FIGURES


Figure 3-1: ML1SA lease extents (Alcoa, 2022)	3-3
Figure 3-2: Map of Mining Reporting Centers, Mining Regions, and Production Sheets (Alcoa, 2022)	3-4
Figure 3-3: Map of current Mineral Resource and Mineral Reserve extents (Alcoa, 2022)	3-5
Figure 3-4: Exploration Sheet, Production Sheet, and Map Sheet conventions (SRK, 2021)	3-7
Figure 5-1: Bauxite exploration in the southwest of Western Australia 1961 (adapted from Hickman, 1992)	5-2
Figure 6-1: Regional Geology (adapted from SRK, 2021)	6-2
Figure 6-2: Surface geology showing laterite over granite (Alcoa, 2015)	6-3
Figure 6-3: Bauxite deposit formation schematic – relief exaggerated (Alcoa, 2021)	6-4
Figure 6-4: Typical Alcoa Darling Range mineralogy profile (Hickman et al, 1992)	6-6
Figure 6-5: Typical Alcoa Darling Range grade profile (Alcoa, 2015)	6-6
Figure 6-6: Typical Alcoa Darling Range mining sequence and vertical profile (SLR, 2021)	6-7
Figure 7-1: Chart of resource drill holes by year (Alcoa, 2021)	7-4
Figure 7-2: Example geological section – F55 N 6,325,500 (SRK, 2021)	7-5
Figure 7-3: Resource drilling tractor accessing the forest (SLR, 2021)	7-5
Figure 7-4: Drill bits, reverse circulation drill string and particle size of the sample residue (SLR, 2021)	7-7
Figure 7-5: Sample catching and riffle splitting practices (SLR, 2021)	7-9

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Figure 7-6: Barcode reader and digital recorder mounted on the drill rig (SLR, 2021)	7-10
Figure 7-7: Topographic data coverage of the 2015, 2016 and 2018 LiDAR surveys (Alcoa, 2022)	7-12
Figure 7-8: Error in actual collar location from the nominal (planned) position is monitored for the three drill rig types (Alcoa, 2021)	7-14
Figure 7-9: Possible lateral and vertical sample location error on 15o sloping ground (SLR, 2021)	7-15
Figure 8-1: The Bella robotic sample preparation using Rocklabs ring mills (SLR, 2021)	8-2
Figure 8-2: The pulverized sample is stored in a barcoded dedicated receptacle for assay (SLR, 2021)	8-3
Figure 8-3: The pulverized sample is tracked digitally through the Bella preparation and assaying (SLR, 2021)	8-3
Figure 8-4: The robotic FTIR assaying equipment (RHS shows the sampling scoop arm and pulp dish with the lid elevated) (SLR, 2021)	8-4
Figure 8-5: Digestion and assay equipment used for REF samples at the KWI Clockwise from top left: BD, MD, TICTOC, ICP, XRF, GC (SLR, 2021)	8-7
Figure 8-6: Sample preparation monitoring (Alcoa, 2021)	8-9
Figure 8-7: Assaying Standards (left IRMs KH09 and KH10, right CRM for MALSI) (SLR, 2021)	8-12
Figure 8-8: Umpire checks of REF A.Al2O3 at SGS and BV (SLR, 2021)	8-14
Figure 8-9: Umpire checks of REF R.SiO2 at SGS and BV (SLR, 2021)	8-15
Figure 8-10: Twinned hole comparison for 238 data points from 2018 (after SRK 2021a)	8-17
Figure 8-11: Precision of STE Parent AL to Average of Daughters (top) and to Daughter 1 (bottom) (SLR, 2021)	8-20
Figure 8-12: Precision of STE Parent SI to Average of Daughters (top) and to Daughter 1 (bottom) (SLR, 2021)	8-21
Figure 8-13: Example of the methodology used for broken stick correction of the FTIR results (from Franklin, 2019)	8-24
Figure 8-14: Precision of REF vs Corrected FTIR for AL and SI (SLR, 2021)	8-25
Figure 8-15: Poor precision of REF vs RAW FTIR for BO (SLR, 2021)	8-27
Figure 8-16: P159 Myara North pulp re-assaying of old MD vs new FTIR for AL and SI. Note artefacts in SI plots, which can be removed by trimming (SLR, 2021)	8-29
Figure 8-17: P163 Larego pulp re-assaying of old MD vs new FTIR for AL and SI (trimmed) (SLR, 2021)	8-30
Figure 8-18: Precision of paired Stockpile Belt samples for AL and SI (SLR, 2021)	8-32
Figure 9-1: Visual display of hole status (logged and assayed) for hole G39150224 in Serpentine (Alcoa, 2021)	9-1
Figure 11-1: Plan View of Polygonal Approach (Pass = red, pass open = green, marginal = yellow, fail = blue) (Alcoa, 2022)	11-5

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Figure 11-2: Example Section showing Domain (DOMAF) and Wireframed Surfaces (SLR, 2022)	11-7
Figure 11-3: Plan View of Bauxite Zone and Interpreted Dykes at Serpentine (SLR, 2022)	11-8
Figure 11-4: Histograms of AL by DOMAF at Serpentine (SRK, 2021)	11-9
Figure 11-5: Histograms of SI by DOMAF at Serpentine (SRK, 2021)	11-10
Figure 11-6: Scatterplots of SI versus ST for DOMAF 50 at Serpentine (SRK, 2021)	11-11
Figure 11-7: Scatterplots of AL versus SI by Domain at Serpentine (SRK, 2021)	11-11
Figure 11-8: Cumulative Log Probability Plots for Serpentine Composites	11-13
Figure 11-9: AL, SI, FE, and ST Directional Variogram Models at Serpentine	11-15
Figure 11-10: Example section showing Bauxite Zone and mining solid (SLR, 2021)	11-20
Figure 11-11: Resource comparison scatterplots for Huntly (Tonnage, AL, SI, OX) (SLR, 2021)	11-22
Figure 11-12: Example sections showing DOMAF, AL, and SI block estimates (SLR, 2021)	11-23
Figure 11-13: AL swath plots by DOMAF at Serpentine (SLR, 2021)	11-24
Figure 11-14: Scatterplots of AL versus SI by DOMAF at Serpentine (SLR, 2021)	11-25
Figure 11-15: AL grade-tonnage DG curves versus Serpentine block model	11-26
Figure 11-16: Resource versus Sample Plant Reconciliation – Huntly (Alcoa, 2021)	11-28
Figure 11-17: Resource versus Sample Plant Reconciliation – Willowdale (Alcoa, 2021)	11-29
Figure 11-18: Plan view of Resource Classification (SLR, 2021)	11-34
Figure 12-1: Undulating Hanging wall hardcap surface; and footwall (white clay, lower right in the floor) (Left: Pearman, 2015 & Right: SLR, 2021)	12-5
Figure 12-2: Willowdale Ten-Year Mine Plan Resource confidence (drill hole spacing in meters shown in brackets) (SRK, 2021)	12-6
Figure 12-3: Huntly Ten-Year Mine Plan Resource confidence (drill hole spacing in meters shown in brackets) (Alcoa, 2022)	12-7
Figure 12-4: Example of reconciliation between Mineral Resource and Grade Control models for tonnage, Al, Si, and OX (Alcoa, 2022)	12-10
Figure 13-1: SOBR (SLR, 2021)	13-2
Figure 13-2: Topsoil removal (background), blasting of hardcap and marking of ore (foreground) (SLR, 2021)	13-3
Figure 13-3: Contour mining (SLR, 2021)	13-4
Figure 13-4: Truck on haul road (SLR, 2021)	13-5
Figure 13-5: Haul roads with berms (SLR, 2021)	13-6
Figure 13-6: Covered conveyor (SLR, 2021)	13-7
Figure 13-7: Contour Mining (SLR, 2021)	13-8
Figure 13-8: Soil being returned for backfilling and landscaping the pit (Alcoa, 2018)	13-9

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vii


Figure 13-9: Landscaped mining area, prior to replanting of forest (SLR, 2021)	13-10
Figure 13-10: Rehabilitated pit through re-plantation of native vegetation (SLR, 2021)	13-10
Figure 13-11: Ore mining at Darling Range (SLR, 2021)	13-11
Figure 13-12: Blasthole drill working on hardcap (SLR, 2021)	13-13
Figure 14-1: Simplified block flow diagram of the Willowdale operation	14-2
Figure 14-2: Simplified block flow diagram of the Huntly operation	14-3
Figure 15-1: Infrastructure Layout (Alcoa, 2022)	15-2

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viii

2.0	Executive Summary

2.1

Summary

SLR International Corporation (SLR) was appointed by Alcoa Corporation (Alcoa) to prepare an independent Technical Report Summary on the Darling Range bauxite mines, located in Western Australia. The purpose of this report is to support the Mineral Resource and Mineral Reserve estimates for the mines as of December 31, 2021. This Technical Report Summary (TRS) conforms to the United States Securities and Exchange Commission’s (SEC) Modernized Property Disclosure Requirements for Mining Registrants as described in Subpart 1300 of Regulation S-K, Disclosure by Registrants Engaged in Mining Operations (S-K 1300), and Item 601(b)(96) of Regulation S-K, Technical Report Summary.

2.1.1

Conclusions

2.1.1.1

Geology and Mineral Resources

•

SLR is independently declaring the 31 December 2021 Mineral Resources for the defined bauxites located within Alcoa’s Darling Range deposits. The Mineral Resource models were prepared by Alcoa using their in-house estimation procedures and reviewed extensively by SLR.

•

As of December 31, 2021, exclusive of Mineral Reserves, as summarized in Table 11‑4 at an appropriate level of precision reflecting confidence, the Measured Mineral Resources are estimated to be 48.0 Mt at a grade of 32.9% available alumina (A.Al₂O₃) and 1.11% reactive silica (R.SiO₂). Similarly the Indicated Mineral Resources are estimated to be 34.8 Mt at 31.9% A.Al₂O₃ and 1.12% R.SiO₂, and the Inferred Mineral Resources are estimated to be 320 Mt at 33.0% A.Al₂O₃ and 1.2% R.SiO₂.

•

SLR considers that, because of the integrated process by which Measured and Indicated Mineral Resources translate to Mineral Reserves for Alcoa’s Darling Range operation, there are no foreseeable risks associated with Modifying Factors (mining, processing, metallurgical, infrastructure, economic, marketing, legal, environment, social, or government) that materially affect the Mineral Reserve estimate at 31 December 2021.

Specific conclusions reached by the SLR QP and provided in the body of this report in Sections 6, 7, 8. 9, and 11 are aggregated here as follows:

•

In the SLR QP’s opinion, the drill sampling and sample control procedures at Alcoa’s Darling Range Bauxite Operations are adequate and appropriate for use in the estimation of Mineral Resources. The defined volumes and grades of mineralization are not expected to be systematically impacted (biased) by errors in either the collar location or the 3D sample location.

•

In the opinion of the SLR QP, the QA/QC of sample preparation and assaying is adequate and the assay results are suitable for use in Mineral Resource estimation.

•

It is the opinion of the SLR QP that the analytical procedures used for the Alcoa Mineral Resource comprises part of conventional industry practice. FTIR is not widely used yet in the bauxite industry but is becoming more widely accepted and applied to more operations. At Alcoa the method has been consistently applied successfully for a decade and is routinely validated by industry standard XRF and wet chemical procedures as discussed in Section 8.3 and 8.4.

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•

It is the opinion of the SLR QP from the studies on FTIR repeatability discussed above that the overall precision and accuracy of the FTIR assaying is acceptable..

•

The SLR QP is of the opinion that the database is adequate and the data is appropriate for the purpose of Mineral Resource estimation.

•

In SLR’s opinion the dry bulk density data is less well controlled than other analytes, but the long history of mining production and stockpile reconciliation means that the assumed values are adequate for resource estimation.

•

In the SLR QP’s opinion, the condition of Reasonable Prospects For Economic Extraction is met by constraining the Mineral Resource model using the ArcGIS system, by ensuring that the model defines key parameters for the refinery, and by sound reconciliation practices providing feedback at the modelling is appropriate for the purpose.

2.1.1.2

Mining and Mineral Reserves

•

As of December 31, 2021, Proven Mineral Reserves are estimated to total 108.6 Mt at 32.4% A.Al₂O₃ and 1.01% R.SiO₂ and Probable Mineral Reserves are estimated to total 132.7 Mt at 32.2% A.Al₂O₃ and 1.38% R.SiO₂.

•

SLR has used the December 31, 2021 Mineral Resource estimate as the basis for its Mineral Reserve estimate. The bauxite operations are operating mining projects with a long history of production for which establishment capital has been repaid and for which sustaining capital and supported operating costs have been observed to be applied in economic analysis. Consequently, the QP considers that support by a Feasibility Study is demonstrated by the demonstrable history of profitable operation and the level of technical support for the Modifying Factors. The QP has reviewed the operating and planning procedures and parameters for the operations.

•

The QP considers that the accuracy and confidence in the Mineral Reserve estimate to be appropriate for the classification applied, which is supported by both the conservative operational processes and the long operational history.

•

The QP is not aware of any risk factors associated with, or changes to, any aspects of the Modifying Factors such as mining, metallurgical, infrastructure, permitting, or other relevant factors that could materially affect the Mineral Reserve estimate.

2.1.1.3

Mineral Processing

•

The operating data between 2010 to 2020 indicates that the product from the Darling Range operations consisted of an average A.Al₂O₃ grade of 33%, with R.SiO₂ below the target for refinery feed.

•

SLR is of the opinion that the Darling range operation demonstrated that ore can be effectively crushed and supplied to a refinery for further upgrading to produce Alumina. The historical operational data confirmed that the ore consistently met refinery specifications without any deleterious elements.

Based on this, and additional information provided by Alcoa regarding the mine plan, it is reasonable to assume that the ore from Darling range can be economically processed for the next 10 years.

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Technical Report Summary - February 24, 2022

2.1.1.4

Infrastructure

•

The Darling Range mining operations have established and operational infrastructure, with mining hubs that host administrative offices, as well as crushing facilities and maintenance facilities.

Hubs are relocated periodically as production moves away from the hub and transportation costs increase. These relocations are well-understood with planning and associated budgeting occurring well in advance of relocations; production restarted seven days after the shutdown.

•

An extensive haul road network, rail, and overland conveyors transport crushed bauxite from the Hub to the refineries.

Bauxite is transferred from each mine to the refineries primarily via long distance conveyor belt, apart from the Kwinana refinery which receives bauxite via railway. The

Alumina produced by the three refineries is then shipped to external and internal smelter customers through the Kwinana and Bunbury ports.

•

The Huntly and Willowdale mines are located near the towns of Pinjarra and Waroona respectively. These are easily accessible via the national South Western Highway, a sealed single carriageway road, spanning almost 400 km from the southern side of Perth to the southwest corner of Western Australia.

•

Major haul roads have been established to each mining area, while secondary haul roads, cross-cut each individual mining plateau. Roads are unsealed and require continuous maintenance.

•

The Darling Range’s Pinjarra refinery receives power from the South West Interconnected System (SWIS), but also has internal generation capacity of 100 MW from four steam driven turbine alternators, with steam produced by gas fired boilers and a gas turbine Heat Recovery Steam Generator (HRSG).

The refinery supplies power to the Huntly Mine by a 33,000 volt power supply line and two 13,800 volt lines.

•

The Wagerup refinery is a net exporter of power to the SWIS, with internal generation capacity of 108 MW from three steam driven turbine alternators and one gas turbine; steam being generated by gas fired boilers.

The refinery supplies power to the Willowdale Mine by a single 22,000 volt power supply.

•

Water is used on the mines for dust suppression, dieback washdown, vehicle washdown, workshops, conveyor belt wash, construction, and domestic purposes.

The water supplies for mining consist of licensed surface water sources supplemented with treated wastewater from vehicle washdowns, stormwater runoff and maintenance workshops.

In 2020, water abstraction comprised approximately 15% of the total Department of Water and Environmental Regulation license allocation (for those sites where abstraction occurred). An additional 534,975 kL was also abstracted from South Dandalup Dam under the agreement with Water Corporation.

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•

On site facilities include offices, ablutions, crib-rooms, and workshops, however there are no Alcoa accommodation facilities, as the Huntly and Willowdale mining areas are close to established population centers.

•

No tailings are generated within the boundaries of the mining operations. The management of tailings generated downstream at the refineries is beyond the boundaries of the Darling Range mining operations and are therefore not considered in this TRS. Waste rock is used to backfill shallow completed before covering with topsoil and reforesting.

2.1.1.5

Environment

•

Alcoa has established processes to facilitate conformance with environmental requirements, while identifying sensitive areas ahead of time enables them to be managed ahead of disturbance.

•

Overburden is carefully segregated for later contouring and rehabilitation of adjacent, completed mining operations. Caprock and other non-viable rock is used to backfill these shallow, completed pits and the viable topsoil spread on top, contoured, and revegetated.

•

Bauxite processing residue is only generated at the Refineries, with no tailings generated within the boundaries of the mining operations. Absence of mine waste prevents the need for waste dump construction and monitoring.

•

Site monitoring is completed in accordance with conditions of government authorizations and operational licenses at Huntly and Willowdale.

•

Alcoa implements a comprehensive water management and monitoring program in accordance with the requirements of its abstraction and operational licenses.

•

The Darling Range operations have no groundwater monitoring programs associated with legislation, licenses or approvals.

Additional groundwater monitoring may be required if groundwater quality or quantity has been identified as potentially at risk due to mining activities, or potential exists for mining to impact offsite/private groundwater supply quantity or quality.

Alcoa has a long-term groundwater research project within the Intermediate Rainfall Zone to evaluate potential impacts of clearing on groundwater salinization.

•

Outcomes of and compliance with the management and monitoring programs are tracked and reported within a Triennial Environmental Review report.

Review of the most recent report, published for the period from 2018 to 2020 largely reported compliance with environmental commitments and success of operational controls to managed environmental objectives.

•

Only a small number of non-compliances were noted; none of which represent a risk that could adversely affect its license to operate.

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Technical Report Summary - February 24, 2022

2.1.2

Recommendations

2.1.2.1

Geology and Mineral Resources

It is apparent to the SLR QP that the long history of exploration, development and mining of Alcoa’s Darling Range bauxite tenements have established sound knowledge and understanding of the geology and mineral endowment. The QP has not identified any fatal flaws in the current practices of mapping (based on the ArcGIS system), drill sampling (based on progressive continuous improvement), assaying (based on calibrated and validated FTIR, with reasonable Quality Control), estimation (3DBM), database management (using acQuire), the application of mining criteria that assure Reasonable Prospects for Economic Extraction (RPEE), and the application of Modifying Factors (again using the ArcGIS system to establish forestry, heritage and noise constraints). The following recommendations are offered as suggestions for further improvement, aligned with Alcoa’s comprehensive approach to research and development (seen for example in the evolution of their drilling, sampling and assaying technologies). These recommendations are prioritized in terms of their perceived value to the overall operation:

•

More effort on the 3D block modelling methodology, leading to a script-based semi-automated approach will enable more robust rapid model building over the Indicated and Inferred Resources. The validation of interpolation parameters using risk-based (conditional simulation) techniques to quantify confidence should be considered.

•

More rapid infill drilling of the 60 by 60 m and 30 by 30 m drill grids.

•

Further redrilling or where viable re-assaying of pulps

•

Moving away from the having drill holes notionally at the centroids of the 15 by 15 m grid map sheet system would mean that the use of offset grids and more flexible grid spacings would be viable.

•

Implementation of a mine wide reconciliation system should be considered as a way to overcome the issue of density estimation. This could be integrated with the extensive production tracking data already available from the current fleet management system and operational control system (covering the mining equipment, crushers, conveyors, sampling towers, stockpile stackers and reclaimers).

•

Technology now becoming available, including volume surveys using drones and truck gantry scanning, wet mass measurement using weightometers on conveyors and LoadRite sensors on mining equipment, and infra-red moisture determination, mean that better in situ dry density estimation may become possible if the operation requires it for better refinery feedstock control.

Specific recommendations noted in previous Sections are reiterated here:

•

The SLR QP considers that twinned hole studies are of limited value and should only be implemented once the sample splitting and preparation demonstrates good repeatability, using Field Duplicates (or the equivalent STE samples). They may be of value to investigate specific issues under closely supervised conditions.

•

While the STE procedure could be retained for specific studies, in the SLR QP’s opinion, the reintroduction of Field Duplicates using appropriate riffle splitters under supervision should be considered.

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Technical Report Summary - February 24, 2022

•

The grade characteristics of the bauxite profile could be reproduced in the model, enabling optimization techniques to be used for the definition of mining floors and boundaries, better support for ore loss and dilution studies, and more accurate reconciliation studies.

2.1.2.2

Mining and Mineral Reserves

•

Currently a dilution and mining recovery factor is applied to the final Reserves to reconcile the tonnes and grade. The SLR QP recommends applying dilution and ore loss at the re-blocked model level before performing the optimization and reporting these values independently.

•

The life-of-mine scheduling requires further refinement with regards to sequencing of the different mining areas and assigning the scheduled years back to the orebest model.

•

The SLR QP recommends detailed haulage analysis focusing on haulage profiles and cycle times to provide more accurate operating costs.

•

The SLR QP noted the mining models were in both a 2D grid and 3D model system. Aligning all the mining models within the same 3D mining model system will provide clarity and consistency across Darling Range project with regards to evaluation and reporting processes.

2.1.2.3

Mineral Processing

As mentioned in Section 22.3, the historical operational data for the Darling Range demonstrate that ore consistently met refinery specifications. SLR make the following recommendations regarding processing:

•

SLR recommends independent verification of the sample analysis by a certified laboratory, on a structured program to ensure the QA/QC aspects of the internal analysis.

•

It is recommended that a proportion of samples from each batch could be sent to the independent laboratory for analysis and the results can be compared with the internal analysis.

2.1.2.4

Infrastructure

As mentioned in Section 22.4, the Darling Range mining operations have well established infrastructure, with mining hubs that are periodically moved to reduce transportation distances between mining operations and the hubs. SLR make no recommendations regarding infrastructure.

2.1.2.5

Environment

•

As mentioned in Section 22.5, Alcoa has established systems to facilitate adherence to environmental commitments. SLR recommend that the following actions are taken to monitor previously enacted corrective actions, made in response to minor environmental incidents:

•

Monitor efficacy of corrective actions made following drainage failures related to significant rainfall events, which resulted in surface water flow from dieback areas into dieback free areas.

•

Monitor efficacy of corrective actions made following recordings of elevated turbidity for a period exceeding the compliance criteria (25 NTU).

•

Monitor efficacy of Interim PFAS Water Management Strategy implemented in response to incidents involving PFAS and AFFF contamination.

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Technical Report Summary - February 24, 2022

2.2	Economic Analysis

2.2.1

Economic Criteria

An un-escalated technical-economic model was prepared on an after-tax discounted cash flow (DCF) basis, the results of which are presented in this subsection.

Annual estimates of mine production with associated cash flows are provided for years 2022 to 2028, based on Proven and Probable Reserves only.

Key criteria used in the analysis are discussed elsewhere throughout this TRS. General assumptions used are summarized in Table 1‑1. All values are presented in United States Dollars ($) unless otherwise stated.

Table 1‑1: LOM Technical-Economic Assumptions

Description	Value
Start Date	January 1, 2022
Mine Life based on Mineral Reserves	7 years
Price Assumption	$25.49
Total Operating Costs	$3,259.8 million
Sustaining Capital over next seven years	$349.3 million
Discount Rate	$867.4 million
Discounting Basis	9%
Inflation	End of Period
Corporate Income Tax Rate	0%

2.2.2

Cash Flow Analysis

The indicative economic analysis results, presented in Table 1‑2, indicate an after-tax Net Present Value (NPV) of $1,315.2 million, using a 9% discount rate and an average bauxite price of $25.49/tonne.

Capital identified in the economics is for sustaining operations, haul roads, conveyor replacements and major mine moves.

The cashflow is presented on a 100% attributable basis.

The economic analysis was performed using the estimates presented in this TRS and confirms that the operations have a positive cash flow that supports the statement of Mineral Reserves.

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Technical Report Summary - February 24, 2022

Table 1‑2: LOM Indicative Economic Results


Description	Units	Total LOM
LOM	Years	7
LOM Bauxite Production	Mt	241.3
Average LOM Price	$/t	25.49
Gross Revenue	$ million	6,151.0
Labor	$ million	969.9
Service	$ million	858.2
Other	$ million	536.0
PAE – Corporate Chargebacks	$ million	139.4
Energy	$ million	81.0
Fuel	$ million	118.8
Supplies	$ million	164.9
Maintenance	$ million	288.2
On-site Mine Operating Costs	$ million	3,156.3
Off-site Mine Operating Costs	$ million	103.5

Corporate Income Tax	$ million	867.4
Net Income after Taxes	$ million	1,332.4
Depreciation Tax Savings	$ million	691.5
Sustaining Capital (2021 to 2028 inclusive)	$ million	$349.3
Closure Costs	$ million	Included in ARO under operating costs
Free Cash Flow	$ million	1,754.0
NPV @ 9%	$ million	1,315.2

2.2.3

Sensitivity Analysis

Project risks can be identified in both economic and non-economic terms. Key economic risks were examined by running cash flow sensitivities. The operation is nominally most sensitive to operating costs followed by market prices (revenues).

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Technical Report Summary - February 24, 2022

2.3	Technical Summary

2.3.1

Property Description

The Mineral Resource estimates declared in this Report were derived for bauxite deposits located within the Darling Range in the southwest of Western Australia. The mining center of Huntly is located approximately 80 km to the southeast of Perth, and approximately 30 km east of the township of Pinjarra. Willowdale is located 100 km south-southeast of Perth, and approximately 15 km east of the township of Waroona.

The Pinjarra refinery is located adjacent to the east of the town of Pinjarra and is approximately 25 km southwest of the Huntly mining areas. The Kwinana refinery, also supplied by Huntly, is approximately 50 km northwest of Huntly in the city of Kwinana, a suburb approximately 40 km south of Perth. The Wagerup refinery, supplied by Willowdale, is located immediately adjacent to the east of the South Western Highway, approximately 8 km south of Waroona and 20 km west of the Willowdale mining area.

2.3.2

Land Tenure

The bauxite deposits are all located within ML1SA. The Agreement permits the exploration and mining of bauxite within the tenement boundaries. ML1SA was granted on 24 September 1961, for four 21-year periods, and the current lease expires on 24 September 2024, with provision for renewal extending beyond 2045. The current lease covers an area of 7,022.61 km², and extends from just north of Perth, to Collie in the south. The legislation under which Alcoa operates is overseen by the Mining and Management Program Liaison Group, which comprises representatives from several State Government departments.

A number of environmental and statutory constraints exist within ML1SA, and Alcoa is not permitted to access bauxite from the areas covered under these constraints. Mineral Resources have not been defined in the constrained areas. In August 2001, Alcoa entered a sub-lease arrangement with a consortium referred to as the Worsley Participants. This arrangement permits the Worsley Participants to mine and process bauxites within the sub-lease area. Alcoa has not declared Mineral Resources within the sub-lease area.

2.3.3

Ownership

The mining rights and assets involved with bauxite mining and alumina refining in Australia are 100% owned by Alcoa of Australia Limited (AofA), an affiliate of Alcoa owned by Alcoa World Alumina and Chemicals (AWAC). AWAC is an unincorporated global joint venture between Alcoa and Alumina Limited, a company incorporated under the laws of the Commonwealth of Australia and listed on the Australian Securities Exchange. AWAC consists of a number of affiliated entities that own, operate or have an interest in bauxite mines and alumina refineries, as well as an aluminum smelter, in seven countries. Alcoa Corporation owns 60% and Alumina Limited owns 40% of these entities, directly or indirectly, with such entities being consolidated by Alcoa Corporation for financial reporting purposes.

2.3.4

History

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Technical Report Summary - February 24, 2022

on localities in the Darling Range close either to Perth or to railway lines servicing towns such as Toodyay and York. By 1938 bauxite deposits were known to be common throughout the Darling Range over an area of 560 km long by 40 km to 80 km) wide. The Geological Survey maintained interest in Darling Range laterite as an economic source of aluminum until the 1950s. However, by the late 1950s exploration had been taken over by mining companies. The earliest non-government exploration for bauxite was carried out in 1918 by the Electrolytic Zinc Co. of Australia Pty Ltd, deeming the deposits to be generally low grade and not of commercial value, though like earlier explorers, did not focus upon the underlying friable units.

No further private exploration took place until 1957 when Western Mining Corporation Ltd (WMC) began to explore for bauxite in the Darling Range. Following a regional reconnaissance, a joint venture company, Western Aluminium NL (WANL), formed by WMC with North Broken Hill Ltd and Broken Hill South Ltd, explored temporary reserves over a large portion of the southwest. These areas were part of a Special Mineral Lease (ML1SA) granted to WANL in 1961.

By 1961, WANL had delineated 37 Mt of bauxite at an average grade of 33% A.Al₂O₃. Also in 1961, WANL joined with the Aluminum Company of America Ltd (Alcoa US), allowing additional systematic exploration of lease ML1SA. Commercial mining was finally started in 1963 at Jarrahdale and continued until 1998, supplying bauxite to the Kwinana refinery.

The Huntly and Willowdale mines commenced commercial production in 1972 and 1984 respectively. In 1977 WANL became Alcoa. As of 2021, the Huntly and Willowdale mining operations remain active. Huntly supplies bauxite to the Kwinana and Pinjarra refineries (approximately 27 Million tonnes per annum) while Willowdale supplies the Wagerup refinery (approximately 10 Mtpa).

2.3.5

Geological Setting, Mineralization, and Deposit

The Mineral Resource estimates declared in this Report were derived for bauxite deposits located within the Darling Range in the southwest of Western Australia. The Darling Range comprises a low incised plateau formed by uplift along the north-south trending Darling Fault, which is a major structural lineament that separates the Pinjarra Orogen to the west, from the Yilgarn Craton to the east. The range extends for over 250 km, from Bindoon in the north to Collie in the south.

Bauxite deposits have been identified throughout the Darling Range and generally occur as erratically distributed alumina-rich lenses within the eroded laterites that mantle the granites to the east of the scarp line. The bauxites are thought to have formed from the lateritization of the peneplained surface of the Western Gneiss Terrane rocks. Lateritization is thought to have commenced during the Cretaceous and continued through to the Eocene, with the subsequent periodic activity of the Darling Fault resulting in the current landform of scarps and deeply incised valleys on the western edge of the Darling Range.

Most of the bauxites display a typical profile comprising the following sequence, from the top down:

•

Overburden: A mix of soils, clays, rock fragments and humus that is typically 0.5 m deep, but deeper pockets are common.

•

Hardcap: An indurated iron-rich layer that is usually 1 m to 2 m thick. It is generally high in available alumina (A.Al₂O₃) and low in reactive silica (R.SiO₂).

•

Friable Zone: A partially leached horizon that usually contains a mix of caprock fragments, clasts, nodules, pisolites, and clays. It is usually a few meters thick but can exceed several meters in places. It is generally high in A.Al₂O₃ and low in R.SiO₂.

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•

Basal Clay: A kaolinitic clay horizon that represents the transition zone between the Friable Zone and the underlying saprolitic material. It is generally high in R.SiO₂ and low in A.Al₂O₃.

The Hardcap and Friable Zone are targeted as the ore horizon. Selective mining practices are applied to minimise the inclusion of Overburden, because of its elevated organic carbon levels, and Basal Clay because of its elevated R.SiO₂ concentrations. Within the Hardcap and Friable Zone, the dominant minerals, in order of abundance, are gibbsite, quartz, goethite, kaolinite, and haematite, with lesser amounts of anatase and muscovite.

2.3.6

Exploration

Systematic exploration for bauxite within the region commenced in the 1960s and is conducted on a continuous basis to maintain sufficient Resources and Reserves to meet refinery supply. Alcoa systematically drills the laterite areas on a regular grid spacing of 60 × 60 m, followed by successive infill programs in selected areas that reduce the spacing to 30 × 30 m, and finally to 15 × 15 m. The 2021 Mineral Resource estimates were derived from data acquired from a total of 310,906 holes, drilled between 1981 and 2020, with almost 80% of the holes drilled after 2009.

The planned drill hole collar locations are pegged by Alcoa surveying staff using real time kinematic differential global positioning system (RTK DGPS). Prior to mid-2015, theodolite/ total stations and DGPS were used to position the 60 m spaced holes, and the 30 m and 15 m grids were positioned by taping and optical square sighting between the 60 m pegs. If the drill rig cannot be setup within 2 m of the peg, the offset distance is measured and marked on the driller’s log. Alcoa has recently introduced the practice of resurveying all drill hole locations after drilling. However, the planned coordinates are used for subsequent modelling activities.

All holes are assumed to be vertical. However, the drill rigs have limited levelling capability, and most holes are orthogonal to the local surface gradient, resulting in deviations of several degrees from vertical.

A digital elevation model representing the natural surface was prepared from a combination of collar survey data, LiDAR data, and satellite imagery.

The drilling is conducted using a fleet of tractor-mounted vacuum rigs, which have been modified to operate in forested areas with minimal clearing or ground preparation. In 2015, Alcoa added aircore drilling rigs to the fleet. These rigs are also tractor-mounted and are fitted with a similar sample collection system to that used on the vacuum rigs. The rigs are fitted with hollow-bladed bits that have a nominal cutting diameter of 45 mm and an internal retrieval tube diameter of 22–25 mm.

All samples are collected on 0.5 m intervals, with the material extracted via the hollow drill stem into a collector flask attached to the cyclone underflow. Each sample, which weighs approximately 1.5 kg, is repeatedly passed through a riffle splitter to yield a retained split weighing approximately 200 g. This material is placed into barcode-labelled sample packets for despatch to the test laboratory. The remaining material is discarded.

For each hole, the drillers prepare a log sheet that contains survey, drilling, geological logging, and sample submission information.

2.3.7

Mineral Resource Estimates

The long production history of Alcoa’s ML1SA operations has resulted in the development of an integrated approach for data collection, bauxite delineation, and production planning, aimed at providing feedstock that meets the technical specification requirements of the local refineries. In the past few years, Alcoa

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Technical Report Summary - February 24, 2022

recognized that some of its procedures required optimization and updating to be more consistent with best practice approaches within the industry. They commenced a process of investigation and revision of many of these procedures but recognized that this must be implemented in a staged manner to ensure that the Mineral Resources and Mineral Reserves delineation procedures remain consistent with, and do not result in significant disruption to, current mining practices. In 2019, they began introduction 3D block modelling techniques to replace the polygon and gridded seam modelling resource estimation procedures. Approximately 30% of the tonnages that contribute to the current Mineral Resource inventory have been prepared using the new 3D block modelling procedures.

The majority of the estimates that make up the current Mineral Resource inventory were prepared using techniques that Alcoa has developed since the commencement of mining in 1963. Over the period, Alcoa developed an integrated approach to data collection, resource definition, and mining that has proven effective in meeting the refineries’ feedstock requirements.

The development of the resource estimation procedures largely predates the wider industry move to block modelling and geostatistical estimation techniques that occurred in the 1990s. Although there have been numerous changes and refinements to Alcoa’s procedures, these systems are essentially a semi-automated implementation of the traditional 2D polygonal estimation techniques.

A legacy of the development history of the resource estimation system is that different procedures were used to delineate Mineral Resources using the 30 m and 60 m spaced data, termed the ResTag procedures, compared to those defined using the 15 m spaced data, termed the Gridded Seam Model (GSM) procedures.

The estimates defined using the 15 m spaced data are limited to the material that is planned to be mined. The parameters used by Alcoa meant that the resultant estimates were essentially nearest neighbor polygonal estimates.

In 2019, Alcoa introduced 3D block modelling and geostatistical estimation techniques, which they term the 3D Block Model (3DBM) procedures, to replace the polygonal and gridded seam modelling techniques.

In essence, all techniques largely rely upon the definition of a resource floor based on A.Al₂O₃ and R.SiO₂ cut-off grade criteria applied to both individual and accumulated sample grades (for the traditional approaches) or individual and accumulated model grades (for the 3DBM approach). Minimum thickness criteria are also considered. For the models defined using the 15 m spaced data, practical mining constraints are also included in floor definition, including stripping ratios, and the floor heights in surrounding holes. The sample grades in each drill hole or column of model cells are composited over the interval between the base of overburden and the resource floor.

The lateral constraints are initially defined using A.Al₂O₃ and R.SiO₂ grade thresholds, and then modified to include minimum area, minimum composite numbers, and maximum internal waste criteria. Additional constraints are applied for the resources defined using 15 m spaced data. These include maintaining equipment transit corridors and including minimum buffer distances around environmental exclusion zones and bedrock outcrop.

The resource outlines are divided into resource blocks that delineate sub-regions containing material with similar grade characteristics, and contain tonnages that can be used for long-term, medium-term, and short-term scheduling activities (80 kt to 100 kt for 60 m spacing, down to 20 kt to 40 kt for 15 m spacing). For the 30 m and 60 m areas, the resource blocks are assigned the length-weighted average grades of the enclosed composites.

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Technical Report Summary - February 24, 2022

The model contains estimates for a range of constituents that are of prime importance for Bayer processing including A.Al₂O₃, R.SiO₂, oxalate, sulphate, boehmite, and iron. Validation included visual and statistical checks between the input data and resource block estimates, comparisons of the estimates derived from different data spacings, and comparisons of the estimates with production data.

The annual reconciliation data for the past 19 years indicate the presence of grade and tonnage biases which, although some show long-term trends, appear to be relatively consistent and predictable on a year-to-year basis. The As Mined tonnage estimates are consistently biased high by approximately 5%. The As Mined A.Al₂O₃ is biased low but has shown a gradual improvement from 5% to 1%, relative over the past decade. The As Mined R.SiO₂ is biased low but has shown a gradual improvement from around 30% to 10% relative over the past decade. Most other constituents exhibit similar bias reductions over the past decade.

The Mineral Resource classifications have been applied to the resource estimates based on consideration of the confidence in the geological interpretation, the quality and quantity of the input data, the confidence in the estimation technique, and the likely economic viability of the material.

There are limited quality assurance data to enable a thorough assessment of the reliability of the estimation datasets, and the majority of the Mineral Resource estimates have been prepared using traditional 2D estimation techniques which have known limitations when used to prepare local estimates. However, the long production history and significant amount of reconciliation data indicate that past estimates prepared using these techniques have been relatively reliable and predictable.

Based on the above considerations, the main controlling factors for Mineral Resource classification are deemed to be sample spacing and data quality.

2.3.8

Mineral Reserve Estimates

A Mineral Reserve has been estimated for Alcoa’s Darling Range bauxite mining operations in accordance SEC S–K 1300 which are consistent with the guidelines of the Australasian Code for Reporting of Exploration Results, Mineral Resources and Mineral Reserves (The JORC 2012 Code).

The SLR QP inspected the Alcoa Huntly and Willowdale operations on October 14, 2021, and Alcoa’s Mine Planning department on October 27, 2021, interviewing relevant personnel on these dates and on other occasions. The QP has had prior exposure to Alcoa’s Darling Range operations earlier in his career.

The Mineral Reserve is classified with reference to the classification of the underlying Mineral Resource and with reference to confidence in the informing Modifying Factors. The QP considers the Proven and Probable classification to be appropriate to the deposit and associated mining operations.

The reference point for the Mineral Reserve is prior to the processing plant at the refinery.

The Proven Mineral Reserve is a subset of Measured Resources only. The Proven Mineral Reserve is legally permitted for mining and is included in the Ten-Year Mine Plan.

The Probable Mineral Reserve is estimated from that part of the Mineral Resource that has been classified as Indicated.

Variable cut-off grades are applied in estimation of the Mineral Reserve and these are related to operating cost and the nature of the Mineral Resource in relation to blending requirements. The Mineral Reserve estimate is expressed in relation to available aluminum oxide (A.Al₂O₃) and reactive silica (R.SiO₂), this being the critical contaminant in relation to the Refinery.

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Technical Report Summary - February 24, 2022

2.3.9

Mining Methods

The Huntly and Willowdale mines employ conventional open pit mining practices and equipment. The fleet is mixed between contract and owner-operator, depending on the nature of the task at hand. Owner operator equipment is used for mining the bulk of the Mineral Reserve, operating in areas away from those subject to environmental restrictions. Contract mining operates smaller equipment, day shift only, in environmentally (noise) sensitive areas and at the perimeter of the mining area.

Following definition of Mineral Reserve blocks, vegetation is cleared ahead of mining by the Western Australian State Forest Products Commission (FPC), saleable timber being harvested for use. On receipt of clearance to proceed from the FPC, Alcoa operations commence stripping topsoil and secondary overburden removal (SOBR) using small excavators, scrapers, and trucks. Soil is stockpiled at the site, away from the proposed pit, for rehabilitation purposes.

Mining progresses on 4 m benches, utilizing a contour-mining sequence, cutting benches across the topography, working from top to bottom, maintaining the flattest floor obtainable to a maximum gradient of 1:10. This is most pronounced in steep areas. Most of the mineralization lies beneath a gently undulating topography and contour mining is minimal.

After completion of mining, overburden is progressively backfilled into adjacent exhausted pits, topsoiled and rehabilitated by re-establishment of native vegetation, creating a stable post-mining landform that replicates the pre-existing environment.

2.3.10

Processing and Recovery Methods

SLR understands that, according to the mine plan, total (T.SiO₂) and R.SiO₂ contents, on an annual average basis, remaining below the target for refineries for the next 10 years. This means, there are no evidence of any deleterious element’s presence in the Darling Range ore within the next 10 years of production.

The process plant for the Darling Range operations consists of two separate crushing facilities at the Huntly and Willowdale mines. Both facilities crush the Run-of-Mine (ROM) and convey the crushed ore to three separate refineries located at Pinjarra, Kwinana and Wagerup.

The power consumption of the Huntly operation is approximately 8,000 Megawatt-hour (MWh) to 9,000 MWh per month. The Willowdale power consumption is approximately 2,000 MWh per month.

The process plant is a dry crushing operation and therefore water is only required for dust suppression and is included as part of mine water consumption. Water is not required as a consumable for the plant.

2.3.11

Infrastructure

The infrastructure for the mining operations is established and operational. In 2021, the infrastructure hub for Willowdale was relocated 16 km southwards from Orion (after having been based there for 21 years) to the Larego Hub which is located about 20 km north-east of the town of Harvey. The hub hosts administrative offices, as well as crushing facilities and maintenance facilities. The Orion Hub site is currently being decommissioned.

An extensive haul road network, rail, and overland conveyors transport crushed bauxite from the Hub to the refineries (namely Kwinana, Wagerup and Pinjarra). Bauxite is transferred from each mine to the refineries primarily via long distance conveyor belt, apart from the Kwinana refinery which receives bauxite via railway. The Alumina produced by the three refineries is then shipped to external and internal smelter customers through the Kwinana and Bunbury ports.

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Technical Report Summary - February 24, 2022

The Darling Range’s Pinjarra refinery receives power from the South West Interconnected System (SWIS). The refinery also has internal generation capacity of 100 MW from 4 steam driven turbine alternators, with steam produced by gas fired boilers and a gas turbine Heat Recovery Steam Generator (HRSG). The refinery supplies power to the Huntly Mine by three different power supply lines (a single 33 kV and two 13.8 kV). Willowdale Mine has a single 22 kV power supply fed from the Wagerup refinery. The Wagerup refinery is a net exporter of power to the SWIS, with internal generation capacity of 108 MW from three steam driven turbine alternators and one gas turbine. The steam is produced by gas fired boilers.

The WA mines are licensed by the Department of Water and Environmental Regulation (DWER) to draw surface water from five locations to meet their water supply requirements. The Huntly mine draws water from Banksiadale Dam and Boronia Waterhole. Huntly mine also holds a license to draw water from Pig Swamp and Marrinup, however these resources are retained as a backup water supply and have not been utilized in recent years. Huntly mine is also permitted to draw water from South Dandalup Dam under an agreement with the Water Corporation. A pumpback facility from South Dandalup Dam to Banksiadale Dam is used to raise levels in Banksiadale Dam during periods of low rainfall runoff. Willowdale Mine draws water from Samson Dam.

There are no Alcoa accommodation facilities within the Darling Range. As described above, the Huntly and Willowdale mining areas are within proximity to established population centers including Pinjarra approximately 25 km to the West of Huntly and Waroona approximately 20 km West of Willowdale. On site facilities includes offices, ablutions, crib-rooms and workshops, all of which were observed to be in excellent condition.

No tailings are generated within the boundaries of the mining operations. The management of tailings generated downstream at the refineries is beyond the boundaries of the Darling Range mining operations and are therefore not considered in this TRS. Alcoa’s Darling Range mining operations do not produce mine waste or “mullock” in the same manner as conventional mining operations and waste dumps are not constructed.

2.3.12

Market Studies

Alcoa Corporation is a vertically integrated aluminum company comprising bauxite mining, alumina refining, aluminum production (smelting and casting), and energy generation.

Through direct and indirect ownership, Alcoa Corporation has 28 operating locations in nine countries around the world, situated primarily in Australia, Brazil, Canada, Iceland, Norway, Spain, and the United States. Governmental policies, laws and regulations, and other economic factors, including inflation and fluctuations in foreign currency exchange rates and interest rates, affect the results of operations in these countries.

There are three commodities in the vertically integrated system: bauxite, alumina, and aluminum, with each having their own market and related price and impacted by their own market fundamentals. Bauxite, which contains various aluminum hydroxide minerals, is the principal raw material used to produce alumina. Bauxite is refined using the Bayer process to produce alumina, a compound of aluminum and oxygen, which in turn is the raw material used by smelters to produce aluminum metal.

Alcoa obtains bauxite from its own resources and processes over 85% of its combined bauxite production into alumina. The remainder is sold to the third-party market. In 2021, total Alcoa production was 47.6 million dmt (dry metric tonne) of bauxite.

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China is the largest third-party seaborne bauxite market and accounts for more than 90% of all bauxite traded. Bauxite is sourced primarily from Australia, Guinea, and Indonesia on the third-party market. In the long run, China is expected to continue to be the largest consumer of third-party bauxite with Guinea expected to be the majority supplier. Further, third-party traded bauxite is expected to be in surplus over the next decade, with most new mining projects announced recently being located in Guinea.

Bauxite characteristics and variations in quality heavily impact the selection of refining technology and refinery operating cost. A market bauxite with high impurities could limit the customer volume an existing refinery could use, resulting in a discount applied to the value-in-use price basis.

Besides quality and geography, market fundamentals, including macroeconomic trends – the prices of raw materials, like caustic soda and energy, the prices of Alumina and Aluminum, and the cost of freight – will also play a role in bauxite prices.

In 2016, Darling Range entered into a 5-year third-party sales contract with a major alumina producer in China. The volume exported was immaterial compared to the total production of the two mines and was immaterial to the overall operation. In 2021, less than 4% of the Darling Range bauxite was sold externally. Following the expiration of the third-party sales contract at the end of 2021, all bauxite production from Huntly and Willowdale will be consumed internally by the Darling Range refineries and there are no current plans for further bauxite export.

The pricing mechanism of the third-party sales contract was based on a value-in-use methodology (as described in Section 16-1) that was anchored to the customer’s other bauxite sources at the time of execution, with a market adjustment factor linked to the Alumina price.

As discussed in Section 16.2.1, all Western Australia bauxite production will be sold internally to Western Australia refineries following the expiration of the third-party sales contract in 2021. In 2021, the Western Australia internal bauxite transfer price referenced this third-party sales contract as a three-year trailing average.

2.3.13

Environmental Studies, Permitting and Plans, Negotiations, or Agreements with Local Individuals or Groups

Alcoa has established practices and processes for ensuring conformance to environmental requirements. Sensitive areas are identified and managed ahead of disturbance. Environmental factors are taken into account prior to infill drilling; hence, mining blocks carrying environmental risks do not feature in the Mineral Reserves (for example, areas around granite outcrops and water courses have a buffer applied and are essentially no-go areas from a mining perspective).

Additional baseline studies are understood to be in progress to support the Environmental Protection Act 1986 (WA) and the Environment Protection and Biodiversity Conservation Act 1999 (Commonwealth) approvals for future extensions to the mining footprint. Baseline studies are guided by the requirements of the Environmental Protection Authority (WA) and are well understood.

No tailings are generated within the boundaries of the mining operations as bauxite processing residue is only generated at the Refineries. Similarly, Alcoa’s Darling Range mining operations do not produce mine waste or “mullock” in the same manner as conventional mining operations and as such waste dumps are not constructed. Overburden from Darling Range ore blocks is carefully segregated for later contouring and rehabilitation of adjacent, completed mining operations. Caprock and other non-viable rock is used to backfill these shallow, completed pits and the viable topsoil spread on top, contoured, and revegetated.

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As such, there is no requirement for the monitoring of any tailings or mine waste dumps associated within the mining operations as all tailings are processed outside the mine lease boundary.

Alcoa’s mine sites are monitored in accordance with the conditions of Government authorizations and its operational licenses at Huntly (L6210/1991/10) and Willowdale (L6465/1989/10). Outcomes of and compliance with the management and monitoring programs are tracked within Alcoa’s Environmental Management System and reported within the Annual Environmental Review report.

The environmental reviews and approvals form part of the Mining and Management Program Liaison Group (MMPLG) approvals process. Compliance with the MMPLG is demonstrated through an annual report submitted to the Department of Jobs, Tourism, Science and Innovation (DJTSI). Operational matters at the Willowdale and Huntly mines are licensed by the Department of Water and Environmental Regulation via instruments L6465/1989/10 and L6210/1991/10, respectively. These licenses condition the processing of ore and reporting is required annually to DWER describing the total volume of bauxite crushed and any non-compliance. The latest available reporting at the time of writing is for calendar year 2020. Compliance with the Alcoa ISO14001 accredited Environmental Management System (EMS) was audited in December 2021, with results expected in April 2022.

Alcoa has established systems and processes for maintaining its social license to operate and was admitted to ICMM in 2019, aligning to its social performance requirements. Related to the requirements of the MMPLG, Alcoa’s actions in relation to social performance include an annual consultation process aligned with the 5 Year Mine Plan. The consultation process involves engaging with affected landowners. Alcoa’s consultation extends to shires, as well as state and local government members. Where appropriate, the mine plan accommodates community requirements, in particular, concerns related to noise, dust, etc., and allows for buffer zones and modified working hours.

Alcoa’s Closure Planning group for Darling Range (located within the Global Planning Team) is responsible for developing the closure planning process as well as the subsequent Long-Term Mine Closure Plans (LTMCPs) of Alcoa’s WA Mining Operations (Huntly and Willowdale). Closure Strategies, Schedules and Cost Estimates are being developed across organizational divisions and includes multidisciplinary inputs from Operations, Mid- and Short-term Planning, Finance, Centre for Excellence, Environment and Asset Management (both Fixed and Mobile Plant). The agreed closure requirements for Darling Range centres around the return of Jarrah Forest across the site. End land uses are required to comply with the State’s Forest Management Plan and include water catchment protection, timber production and biodiversity conservation.

The Alcoa procurement system defines “local” as the localities of Dwellingup, Harvey, Pinjarra, Waroona, Coolup, North Dandalup and Yarloop. Within Alcoa’s guidelines of safe, ethical and competitive business practices, they state they will:

•

Invite capable local business to bid on locally supplied or manufactured goods or services.

•

Give preference to local business in a competitive situation.

•

Work with local business interest groups to identify and utilize local suppliers.

•

Where possible, structure bids to enable local supplier participation.

2.3.14

Capital and Operating Cost Estimates

Alcoa forecasts its capital and operating costs estimates based on annual budgets and historical actuals over the long life of the current operation.

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2.3.14.1

Capital Costs

The operation is well-established and since the LOM plan does not envisage any significant change of the production rate. Anticipated future major capital expenditure is related to major mine moves and sustaining the on-going operations.

Projected capital expenditure over the next seven years of mine life is estimated to total $349.3 million. Of this total, $160 million is associated with the completion of the mine move to the Myara North site . Capital for the Holyoake move will be incurred from 2027 to 2030 and is not include in this TRS cashflow.

A breakdown of the major expenditure areas and total expenditure over the full Ten-Year Mine Plan is shown in Table 1‑3

Table 1‑3: 10 Year LOM Sustaining Capital Costs by Area

Project	Cost $ Million	Percentage of Total
Myara North Mine Moves	160	62%
Conveyor Belt Replacements	25	7%
Haul Road Improvements	51	15%
Other Sustaining Capital	113	32%
Total	349	100%

Other capital costs are for replacement of conveyors, haul road improvements and other sustaining capital needed to continue the operations.

Alcoa’s sustaining capital estimates for Darling Range are derived from annual budgets and historical actuals over the long life of the current operation. According to the American Association of Cost Engineers (AACE) International, these estimates would be classified as Class 1 with an accuracy range of ‑3% to -10% to +3% to +15%.

2.3.14.2

Operating Costs

The main production mining operations are primarily Owner-operated using Alcoa equipment and employees. Contractors are also used for certain activities on site.

Operating costs for the current LOM of seven years are based on the 2022 budget.

No items have been identified that would significantly impact operating costs either positively or negatively over the life of mine. Minor year-to-year variations should be expected based upon maintenance outages and production schedules. Forecast costs for 2022 and average mine operating costs the seven-year LOM are shown below in Table 1‑4.

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Table 1‑4: LOM On-site Mine Operating Costs by Category

Cost Centre	2022 ($/wmt)	Average LOM ($/wmt)	%age of Operating Cost
Direct Labour	$3.44	$4.50	30%
Services	$1.56	$4.26	31%
Other	$1.73	$3.80	27%
Corporate Chargebacks for support services	$0.53	$2.37	17%
Energy	$0.30	$0.61	4%
Fuel	$0.35	$0.36	3%
Operating Supplies and Spare Parts	$0.61	$0.53	4%
Maintenance (fixed plant and mobile fleet	$1.08	$0.72	5%
On-site Mine Operating Cash Cost ($/wmt)	$9.63	$1.26	9%

Off-site Costs
G & A, selling and other expenses	$0.20	0.18
R & D Corporate Chargebacks	$0.22	0.22
Other Costs of Goods Sold	0.03	0.03
Total Cash Operating Costs	$0.20	0.18

Services costs includes contractor costs for certain mining activities such as in noise sensitive areas and for haul road construction services, in select areas of pit development, and during landscaping activities for rehabilitation after mining.

As of Q4 2021, the Huntly and Willowdale operations together employ a total of 890 employees consisting of 92 Technical, 132 Management and 634 operations employees. Additionally, 32 employees are centrally employed on the combined operations.

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3.0	Introduction

SLR International Corporation (SLR) was appointed by Alcoa Corporation (Alcoa) to prepare an independent Technical Report Summary (TRS) on the Darling Range bauxite mines, located in Western Australia. The purpose of this report is to support the Mineral Resource and Mineral Reserve estimates for the mines as of December 31, 2021. This Technical Report Summary conforms to the United States Securities and Exchange Commission’s (SEC) Modernized Property Disclosure Requirements for Mining Registrants as described in Subpart 1300 of Regulation S-K, Disclosure by Registrants Engaged in Mining Operations (S-K 1300), and Item 601(b)(96) of Regulation S-K.

Alcoa is one of the world’s largest aluminum producers and is a publicly traded company on the New York Stock Exchange (NYSE). The company owns and operates integrated bauxite mining, alumina refining and aluminum smelting operations at numerous assets globally including in Australia, Brazil, Canada, and the United States. Alcoa is also a Joint Venture partner for several other integrated operations in Brazil, Canada, Guinea, and Saudi Arabia.

The Darling Range, located south of Perth in Western Australia, comprises two active bauxite mining areas – the Huntly and Willowdale mines – owned and operated by Alcoa of Australia Limited, which is 60% owned by Alcoa Corporation and 40% owned by Alumina Limited. The Huntly and Willowdale operations collectively represent one of the world’s largest bauxite mines which supplies Alcoa’s three aluminum refineries in the region: Kwinana, Pinjarra, and Wagerup. On the basis that both mining areas supply ore to the same local refineries which are also operated by Alcoa, and that both mining areas are located within the same mining lease boundary, SLR considers the mines a single property for the purposes of this report.

Alcoa has a long history of mining in the Darling Range with Huntly and Willowdale commencing commercial production in 1972 and 1984 respectively. These mining areas were preceded by the Jarrahdale bauxite mine which was operational between 1963 and 1998. The Huntly mine currently supplies bauxite to the Pinjarra and Kwinana refineries, while the Willowdale mine supplies the Wagerup refinery. The mines collectively produce approximately 37 Mtpa of bauxite, with approximately 27 Mtpa from Huntly and 10 Mtpa from Willowdale.

3.1	Site Visits

SLR Qualified Persons (QPs) visited the site on October 14, 2021. The SLR Mining Geologist QP and SLR Mining Engineer were accompanied by Alcoa’s Principal Geologist Global Planning to undertake site visits and inspections of various aspects of the Huntly and Willowdale mining areas.

The site visit commenced with a general induction overview at Alcoa’s Pinjarra office (Bindjareb). The group then visited the Willowdale mine site (specifically, the new mine office near the Larego crusher) as well as various locations on Larego accompanied by Alcoa’s Short Term Planning Superintendent.

The QPs then inspected the Darling Scarp including the covered downhill conveyor, sampling station, ore stockpile stacker/reclaimer, and Wagerup refinery.

The mine office at Huntly situated near the Myara crusher was visited with Alcoa’s Short-Term Planner, then the QP group proceeded to various mining locations around that operation. As it was a maintenance day, the crusher and conveyor were not operating.

The Digital fleet management system (FMS) was reviewed at the Myara site.

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The SLR QPs interviewed several senior Alcoa staff at the operation sites.

Alcoa provided permission to document the site visit with video, photos and audio which were shared with the other SLR team members. Some interviews were also carried out using remote video access.

SLR QPs visited the Alcoa’s Mine Planning department at Booragoon on October 27, 2021, for discussions about Alcoa’s planning systems. One of SLR’s QPs carried out inspections of the Kwinana laboratory facilities, in particular the FTIR assaying procedures on November 01, 2021. Drilling methods were inspected on site on November 8, 2021, along with an examination of the database management procedures. The stockpile sampling, stacking, and reclaiming at Pinjarra refinery was inspected on November 12, 2021.

The SLR Metallurgist QP did not visit the site, since travel restriction related to the COVID-19 pandemic made this impractical, however the site was visited by others who reviewed all Modifying Factors.

3.2	Sources of Information

During the preparation of this Technical Report Summary, discussions were held with personnel from Alcoa Corporation and the Huntly and Willowdale Mines, including:

•

Mr Alex Hatch, Principal Geologist, Alcoa

•

Mr Gary Johnson, Short Term Planning Superintendent Willowdale Mine, Alcoa

•

Mr Damien Brown, Short Term Planner, Huntly mine, Alcoa

•

Mr John Greenwood, Director of Bella Analytical Services

•

Mr Neylor Aguiar, Principal Mining Engineer - Global Planning

•

Ms Beth Butler, Community Relations Advisor – WA Mining, Alcoa

•

Ms Suellen Jerrad, Corporate Affairs Manager, Alcoa

•

Mr Andrew Richardson, Senior Environmental Scientist – Approvals and Compliance – WA Mining, Alcoa

This Technical Report summary was prepared by SLR QPs. The documentation reviewed, and other sources of information, are listed at the end of this report in Section 24.0 References.

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3.3	List of Abbreviations

Units of measurement used in this report conform to the metric system. All currency in this report is United States dollars (US$), unless otherwise noted.


Abbreviation	Description
°C	degree Celsius
°F	degree Fahrenheit
2D	2-dimensional
3D	3-dimensional
3DBM	3D Block Model
a	annum
A	ampere
A.Al₂O₃	available alumina
AACE	American Association of Cost Engineers
AFFF	Aqueous Film Forming Foams
AGD	Australian Geodetic Datum
Alcoa	Alcoa Corporation
Alcoa US	Aluminum Company of America Ltd
AMG	Australian Map Grid
AMPD	Absolute Mean Percentage Difference
AMSL	above mean sea level
AMWU	Australian Metal Workers Union
AofA	Alcoa of Australia Ltd
API	Alumina Price Index
ARO	Asset Retirement Obligations
AWAC	Alcoa World Alumina and Chemicals
AWU	Australian Workers Union
B&P	Bias and Precision
bbl	barrels
BD	Bomb digest
BD-GC	bomb digest gas chromatography
BD-ICP	bomb digest inductively coupled plasma
BD-NDIR	bomb digest non-dispersive infrared
Bella	Bella Analytical Systems
Btu	British thermal units
BV	Bureau Veritas
C$	Canadian dollars
cal	calorie
CalVal	calibration and validation for FTIR
cfm	cubic feet per minute
CIM	CIM (2014)
cm	centimeter
cm²	square centimeter

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CRM	certified reference material
CV	Coefficient of Variation
d	Day
DBCA	Water Corporation, Department of Biodiversity, Conservation and Attractions
DCF	Discounted Cash Flow
DEM	Digital Terrain Model
DG	Discrete Gaussian
DGPS	(Differential) Global Positioning System
dia	Diameter
DIBD	dry in situ bulk density (t/m3)
DJTSI	Department of Jobs, Tourism, Science and Innovation
DMIRS	Department of Mines Industry Regulation and Safety
dmt	dry metric tonne
DWER	Department of Water and Environment Regulation
dwt	dead-weight ton
EMS	Environmental Management System
ETU	Electrical Trades Union
EWR	Ecological water requirements
FMS	Fleet Management System
FPC	Forest Products Commission
ft	foot
ft/s	foot per second
ft²	square foot
ft³	cubic foot
FTIR	fourier transform infrared spectrometry
g	gram
G	giga (billion)
g/L	gram per liter
g/t	gram per tonne
Gal	Imperial gallon
GC	gas chromatography
Geological Survey	Geological Survey of Western Australia
GIS	Geographical Information System
Gpm	Imperial gallons per minute
gr/ft³	grain per cubic foot
gr/m³	grain per cubic meter
GSM	gridded seam model
ha	hectare
HARD	Half Absolute Relative Difference
hp	horsepower
hr	hour
HRSG	Heat Recovery Steam Generator
Hz	Hertz

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ICP-OES	inductively coupled plasma optical emission spectrometry
IDW	inverse distance weighting
in.	inch
in²	square inch
IRM	internal reference material
IRR	Internal Rate of Return
ISO	International Standardization Organization
J	Joule
JORC	JORC Code (2012)
k	kilo (thousand)
kcal	kilocalorie
kg	kilogram
km	kilometer
km/h	kilometer per hour
km²	square kilometer
kPa	kilopascal
kV	kilovolt
kVA	kilovolt-amperes
kW	kilowatt
kWh	kilowatt-hour
KWI	Kwinana Mining Laboratory
L	liter
L/s	liters per second
lb	pound
LiDAR	Light Detecting and Ranging
LIMS	laboratory information management system
LME	London Metal Exchange
LOM	Life of Mine
LTMCPs	Long-Term Mine Closure Plans
m	micron
m	meter
M	mega (million); molar
m²	square meter
m³	cubic meter
m³/h	cubic meters per hour
Ma	Million years ago
MALSI	microwave available alumina (AL) and reactive silica (SI)
MASL	meters above sea level
MD	microwave digest
MD-ICP	microwave digest inductively coupled plasma optical emission spectrometry
mg	microgram
mi	mile
min	minute

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mL	milliliters
ML	Mineral Lease
mm	millimeter
MMPLG	Mining and Management Program Liaison Group
MMPs	Mining and Management Programs
mph	miles per hour
MS	Ministerial Statement or Magnetic Susceptibility
Mtpa	Million tonnes per annum
MVA	megavolt-amperes
MW	megawatt
MWh	megawatt-hour
NATA	Australian National Association of Testing Authorities
NI 43-101	National Instrument 43-101 (2014)
NPC	Net Present Cost
NPV	Net Present Value
NTU	Nephelometric Turbidity Units
NYSE	New York Stock Exchange
OK	ordinary kriging
oz	Troy ounce (31.1035g)
oz/st, opt	ounce per short ton
PFAS	per- and polyfluoroalkyl substances
ppb	part per billion
ppm	part per million
psia	pound per square inch absolute
psig	pound per square inch gauge
QA	Quality Assurance
QA/QC	Quality Assurance / Quality Control
QC	Quality Control
QP(s)	Qualified Person(s)
R.SiO₂	reactive silica
RC	Reverse Circulation
REF	reference method
ResTag	mineral resource estimation system
RL	relative elevation
ROM	Run of Mine
RTK	real time kinematic
s	second
SEC	Securities and Exchange Commission
S-K 1300	Subpart 1300 of Regulation S-K
SLR	SLR International Corproation
Snowden	Snowden Mining Consultants
SOBR	stripping topsoil and secondary overburden removal
SPU	sample presentation unit

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SRK	SRK Consulting (Australasia) Pty Ltd
st	short ton
STE	sample to extinction
stpa	short ton per year
stpd	short ton per day
SWIS	South West Interconnected System
t	metric tonne
T.Al2O3	Total Alumina
T.SiO2	Total silica
TICTOC	Total Inorganic Carbon and Extractable Organic Carbon
tpa	metric tonne per year
tpd	metric tonne per day
TRS	Technical Report Summary
US$	United States dollar
USg	United States gallon
USgpm	United States gallon per minute
V	volt
W	watt
WA	Western Australia
WANL	Western Aluminium NL
WMC	Western Mining Corporation Ltd
wmt	wet metric tonne
wt%	weight percent
XRD	x-ray diffraction
XRF	x-ray fluorescence
Xstract	Xstract Resources
yd³	cubic yard
yr	Year

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4.0	Property Description

4.1

Location

The Darling Range is located in the southwest of Western Australia and comprises an extensive uplifted plateau of bauxite deposits which is host to several mining operations including the Huntly and Willowdale mining areas, approximately 80 km and 100 km southeast of Perth, respectively. The nearest towns to the mining centers are North Dandalup (approximately 15 km west of Huntly) and Waroona (approximately 15 km west of Willowdale). Both towns are within the Peel Region of southwest Western Australia and are on the route of the South Western Highway, a major national road connecting Perth with the south coast.

All spatial data used for Mineral Resource estimation are reported using a local grid based on Australian Map Grid 1984 (AMG84) system (Zone 50) and using Australian Geodetic Datum 1984 (AGD84) coordinate set. The approximate coordinates of the mining areas are 410000 m East and 6390000 m North (Huntly) and 410000 m East and 6365000 m North (Willowdale). The Huntly and Willowdale mining areas are separated by approximately 35 km (Figure 3‑1).

4.2	Land Tenure

The Huntly and Willowdale bauxite mines are covered by a single mineral concession referred to as Mineral Lease (ML) 1SA. The concession was originally granted on September 25, 1961, by the State Government of Western Australia under the Alumina Refinery Agreement Act, 1961, permitting the exploration and extraction of bauxite. ML1SA was granted for a period of four, 21-year periods the third period of which is due to expire on September 24, 2024. Prior to September 24, 2024, Alcoa will notify the State Government of Western Australia of its intention to exercise its right to renew for a further 21-year period to extend the concession to 2045. Subject to Alcoa having complied with the Alumina Refinery Agreement Act, 1961, the State Government will grant Alcoa the renewal. The State Government concession agreement includes the potential for conditional renewal beyond 2045. This will require negotiation between Alcoa and the State Government prior to this date to agree on an extension of the agreement, and is therefore not guaranteed.

Conditions which must be fulfilled by Alcoa to retain ML1SA include annual reporting requirements under several State Agreement Acts, Ministerial Statements, and Environmental Protection Acts. These are described in Section 3.6 below.

The current concession of ML1SA covers an area of 7,022.61 km², extending from the north of Perth on the eastern side to the town of Collie in the south (Table 3‑1). Alcoa has the exclusive right to explore for and mine bauxite on all Crown Land within the ML1SA. This area includes sub-lease arrangements made between Alcoa and the Worsley Alumina joint venture participants which include South32, Japan Alumina Associates (Australia) Pty Ltd and Sojitz Alumina Pty Ltd (Worsley Participants). The agreements, made in August 2001 and September 2016, provide bauxite mining concessions to the Worsley Participants. No

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Mineral Resources or Mineral Reserves attributable to the Darling Range mining areas have been declared within these sub-lease areas.

Table 3‑1: ML1SA license details


Concession Name	Title Holder	Expiry Date	Area (km²)
ML1SA	Alcoa of Australia	24/09/2024	7,022.61

Alcoa pays rental for each square mile of ML1SA in accordance with the Alumina Refinery Agreement Act 1961 (WA). In 2021 this amounted to A$13,560.

The boundary of the ML1SA concession area, including the limit of the Worsley Participants’ area, is illustrated in Figure 3‑1. The contained Mining Regions are shown in Figure 3‑4, while the extents of the mined areas and Mineral Resources and Mineral Reserves are shown in Figure 3‑3:

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Figure 3‑1:ML1SA lease extents (Alcoa, 2022)

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Figure 3‑2:Map of Mining Reporting Centers, Mining Regions, and Production Sheets (Alcoa, 2022)

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Figure 3‑3:Map of current Mineral Resource and Mineral Reserve extents (Alcoa, 2022)

4.3	Naming Conventions

Alcoa has developed a terminology to refer to various parts of the Mineral Lease. There are three major Mining Reporting Centers exist in ML1SA: North (previously Jarrahdale), Huntly in the central area, and Willowdale in the south. The boundaries are nominal and may change to match the planned ore destination. The southernmost region of the North mining center was reallocated to Huntly in 2017 and named Myara North.

Mining Regions subdivisions of the Reporting Centers that cover several years of mining activities, focused on a specific crusher location. The boundaries are named after forestry blocks. A total of 12 Mining Regions are represented in the current resource estimate: 1 in North, 7 in Huntly, and 4 in Willowdale.

Mining Pits are named based on their sequence along haul roads. These names are used by the mining fleet when referring to local short-term production. The map reference system outlined below is used for drilling, estimation, and long-term planning.

The Mineral Lease is divided into a grid of Exploration Sheets being rectangles 4.2 km (north) by 3.6 km (east). Each 15.12 km² Exploration Sheet is assigned a name and coded using letters A to V (west to east), and numbers 10 to 80 (north to south), e.g. G45.

Each Exploration Sheet is divided into 28 Production Sheets 900 m (east) by 600 m (north), an area of 0.54 km². The Production Sheets are assigned a number (1 to 28), sequentially 4 across (towards the east) and 7 down (towards the south), e.g. G4520.

Each Production Sheet is divided using a 15 m by 15 m grid resulting in 2,400 grid cells (40 north by 60 east). Each of these is regarded as a point, and assigned a numeric code 1 to 40 towards the south and 1 to 60 towards the east. These are appended to the Production Sheet name to provide a grid point label, e.g. G4520 1430 and used on 1:1000 Map Sheets to define drill hole locations.

The Exploration Sheet, Production Sheet, and Map Sheet conventions are shown in Figure 3‑4:

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Figure 3‑4:Exploration Sheet, Production Sheet, and Map Sheet conventions (SRK, 2021)

4.4	Encumbrances

Constraints on mining activities within the ML1SA concession are in place which prevent bauxite mining in these areas including:

•

Within 200 m from the Top Water Level of Drinking Water Reservoirs

•

National Parks

•

Aboriginal Heritage Sites

•

Old Growth Forest

•

Formal Conservation Areas

•

Within a 50 m buffer of Granite Outcrop (greater than 1 ha).

Mineral Resources and Mineral Reserves have not been defined in these restricted areas. Operating rights are obtained by Alcoa through annual submission and approval of the Mining and Management Programs (MMPs) which include mining schedules and the authorizations provided by the Mining and Management Program Liaison Group (MMPLG).

Mining on a day-only basis is conducted in “noise zones” where noise from the mining operations will potentially exceed allowable levels. The operation actively seeks to maintain lower noise levels than those

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mandated, thus mining in these areas is undertaken by contract miners using smaller equipment on day shifts only.

4.5

Royalties

Alcoa is the holder of ML1SA. For bauxite that is mined and processed in Alcoa’s Western Australian alumina refineries, Alcoa pays royalties on the alumina produced in accordance with the Alumina Refinery Agreement Act 1961 (WA). For bauxite that is mined and exported, Alcoa pays royalties in accordance with the Mining Act 1978 (WA).

4.6	Required Permits and Status

Alcoa operates under several State Agreement Acts as well as Ministerial Statements and environmental operating licenses issued under the Environmental Protection Act 1986 (WA) including:

•

Alumina Refinery Agreement Act 1961 (WA)

•

Alumina Refinery (Pinjarra) Agreement Act 1969 (WA)

•

Alumina Refinery (Wagerup) Agreement Act 1978 and Acts Amendment Act 1978 (WA), which provided for the creation of the MMPLG

•

Alumina Refinery Agreements (Alcoa) Amendment Act 1987 (WA)

•

Ministerial Statement 728 (as amended by Ministerial Statements 897, 1069 and 1157) (MS728)

•

Ministerial Statement 646

•

Environmental Protection (Alcoa – Huntly and Willowdale Mine Sites) Exemption Order 2004 (Exemption Order)

•

Environmental licenses L6210/1991/10 and L6465/1989/10 granted under Part V of the Environmental Protection Act 1986 (WA)

The MMPLG is chaired by the Department of Jobs, Tourism, Science and Innovation. The MMPLG was first established in 1978 and consists of representatives of the Department of Jobs, Tourism, Science and Innovation (DJTSI), Department of Water and Environment Regulation (DWER), Water Corporation, Department of Biodiversity, Conservation and Attractions (DBCA), and the Department of Mines Industry Regulation and Safety (DMIRS). The MMPLG is recognized by the Minster for Environment in Ministerial Statements (95, 390, 564, 728, 897 and 1069) regarding expansion of Alcoa operations. The management and oversight of all Darling Range operations by the MMPLG involves:

•

Provide oversight to mining, infrastructure, processing and related operations within ML1SA

•

Advise on the environmental and social adherence of the 5-year MMPs developed by Alcoa on a recurring annual basis.

•

Provide six-monthly authorizations for ground clearance for mining in accordance with the submitted and approved MMPs.

•

Provide oversight to ongoing rehabilitation of mined areas

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The permitting and approval processes, as provided by Alcoa, are summarized below:

•

Clause 9 (1) of the 1961 State Agreement provides Alcoa the sole rights to explore and mine the bauxite deposits within ML1SA.

•

Clause 5 of the Wagerup State Agreement specifies that Alcoa must consult with the DBCA in relation to the requirement to submit annual mine plans for mining associated with the Wagerup refinery.

•

Under Clause 6 (1) of the Wagerup State Agreement, Alcoa has submitted several environmental review documents to the State Government for subsequent approvals of the Wagerup refinery construction and expansions. Within these environmental assessment documents, significant information on Alcoa’s bauxite mining operations associated with the Wagerup refinery was included, resulting in several conditions in relation to Alcoa’s bauxite mining operations associated with the Wagerup refinery being incorporated in the Ministerial Statements of which the current one is Ministerial Statement 728 (as amended). Procedure 3 of MS728 outlines Alcoa’s requirements to have a publicly available Completion Criteria document for its bauxite mining operations, developed in consultation with the MMPLG. Procedure 4 of MS728 outlines the MMPLG’s authority to review and approve Alcoa’s mining operations through the five-year Mine Plan process. To the extent the conditions on bauxite mining operations in Ministerial Statement 728 and the predecessor Ministerial Statements did not cover bauxite mining unrelated to the Wagerup refinery, Alcoa agreed to extend the conditions to the rest of its bauxite mining.

•

Through the Wagerup State Agreement, MS728, and agreement between the State Government and Alcoa, the MMPLG is responsible for reviewing and providing a recommendation to the Minister for Environment and the Minister for State Development to approve Alcoa’s five-year Mine Plans.

•

Alcoa’s mining operations within ML1SA are also conducted in accordance with the Environmental Protection (Alcoa – Huntly and Willowdale Mine Sites) Exemption Order 2004 (Exemption Order) made by the Minister for the Environment. The Exemption Order is consistent with the Wagerup State Agreement that established the MMPLG and MMP processes and it also reflects the procedures of MS728 that sets out the MMPLG’s responsibility to review annual rolling 5-year mine plans for Alcoa’s operations.

Alcoa reports that all licenses and permissions for the mining operations are currently valid. However, Alcoa is seeking formal environmental impact assessment and approval from the State and Federal Government, which is required prior to mining within the Myara North region of the Huntly mine. These approvals will be through the current process under the Environmental Protection Act 1986 (WA) and the Environment Protection and Biodiversity Conservation Act 1999 (Commonwealth). Alcoa is seeking these approvals to facilitate an increase in production at the Pinjarra refinery and additional bauxite mining for export as well as to modernize aspects of the regulatory framework for the Huntly mine.

4.7	Other Significant Factors and Risks

SLR is not aware of any environmental liabilities on the property. Alcoa has all required permits to conduct the proposed work on the property. SLR is not aware of any other significant factors and risks that may affect access, title, or the right or ability to perform the proposed work program on the property.

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5.0	Accessibility, Climate, Local Resources, Infrastructure and Physiography

5.1	Accessibility

As described in previous sections, the Darling Range Huntly and Willowdale operations are located approximately 150 km south of Perth. The Darling Range is readily accessible via road from Perth and surrounding areas. The mines are near the towns of Pinjarra and Waroona. Both towns are easily accessible via the national South Western Highway, a sealed single carriageway road, which starts on the southern side of Perth and continues for almost 400 km to the southwest corner of Western Australia.

Huntly is accessible from the South Western Highway via Del Park Road, a sealed single carriageway road which connects the town of North Dandalup in the north with Dwellingup in the south. From Del Park Road, a 3km sealed road following the route of the bauxite conveyor to the Pinjarra refinery provides access to the Huntly site administration offices.

Willowdale is similarly accessible 19 km from the South Western Highway via Nanga Brook Road, a sealed single carriageway road to the east of Waroona.

There are several airstrips in the region, although the closest major airport is in Perth, approximately 70 km north of North Dandalup. The nearest commercial port is at the Kwinana refinery, approximately 40 km south of Perth (as illustrated on Figure 15‑1).

While an extensive haul road network and overland conveyors transport crushed bauxite from the main mining hub to the Wagerup and Pinjarra refineries, bauxite is also transferred to the Kwinana refinery via the Kwinana freight railway system, using the Kwinana–Mundijong line.

5.2

Climate

The southwest region of Western Australia exhibits a temperate climate, with very hot and dry summers (December to February) and mild winters (June to August). Rainfall is generally low and variable, ranging from an average rainfall of 25 mm during the three summer months and exceeding 200 mm during the three winter months (Australian Government, Bureau of Meteorology). Local climate conditions generally do not interrupt the mining schedule, which continues throughout the year. Occasionally however, significant rainfall inhibits access and can impact mining activities.

Table 4‑1: Historical Climate Data


	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec
°C Mean Max	29.7	29.7	27.1	22.6	18.6	16.1	15.1	15.8	17.4	20.1	23.8	27.4
°C Mean Min	14.3	14.6	13.0	10.4	7.7	6.5	5.5	5.5	6.5	8.1	10.5	12.6
mm Mean Rainfall	16.5	22.0	26.8	65.1	156.4	233.7	234.9	193.4	130.1	79.2	46.2	20.6

Notes:

Temperature and rainfall data sourced from the Australian Government Bureau of Meteorology, collected from the weather station at Dwellingup http://www.bom.gov.au/climate/averages/tables/cw_009538.shtml

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Data includes that collected from 1935 to 2021.

5.3	Local Resources

The Darling Range is located in an easily accessible region of southwest Western Australia with the Huntly and Willowdale mining areas both within 15 km of well-established towns which act as residential and commercial centers. Several other towns and smaller settlements are positioned along the South Western Highway which acts as a major connection for the Darling Range to the city of Perth where a far greater range of general services is available.

5.4	Infrastructure

The following section refers to several named mining areas within the Huntly and Willowdale mining centers, including Myara, Larego, Orion, and Arundel, each of which is illustrated in Figure 3‑2 above.

Mining infrastructure in the Darling Range is generally concentrated in the Myara site in the northwest of the Huntly mining center, and at the Larego area in the center of the Willowdale mining area (20 km southeast of Wagerup) having been relocated 16 km southwards from the Orion Hub during 2021). Both operations include various ancillary facilities that are not listed exhaustively here, however both infrastructure areas include:

•

Ore crushing and handling facilities

•

Ore stockpile stacker/reclaimer

•

Maintenance facilities

•

Sampling stations

•

Site offices including a production tracking room

•

Haul road networks

•

Overland conveyors, as illustrated on Figure 15‑1.

•

Water supplies consisting of abstraction from licensed surface water sources supplemented with treated wastewater from vehicle washdowns, stormwater runoff, and maintenance workshops. Water sources are illustrated on Figure 15‑1.

The Huntly mine draws water from Banksiadale Dam and Boronia Waterhole. The mine also holds a license to draw water from Pig Swamp and Marrinup, although these are reported as being rarely utilized, and it is permitted to draw water from South Dandalup Dam under an agreement with the Water Corporation.

Willowdale Mine draws water from Samson Dam, approximately 10 km southeast of Waroona.

The Willowdale five-year mining plan recently included the relocation of the crusher from the former Orion infrastructure area in the north to Larego in the south. This included supporting infrastructure construction activities including:

•

Overland conveyor construction from Arundel to Larego, as illustrated in Figure 15‑1.

•

Haul road development into new mining areas

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Establishment of production office facilities

•

Access routes between gated mining areas and fire-fighting tracks

•

Water offtake points for Larego (along the Samson Dam)

Personnel are sourced from the area around Perth, Western Australia, which benefits from a skilled workforce due to the relatively large number of operating mines in the region. Personnel typically have private accommodation in the nearby city of Mandurah (60 km from the mine) and towns (Waroona, Hamel, Yarloop, Harvey and Wagerup).

Huntly Mine has three power supplies fed from the Pinjarra refinery. A single 33 kilovolt (KV) supply and two 13.8 kV supplies. The Pinjarra refinery is a net importer of power from the South West Interconnected System (SWIS), with internal generation capacity of 100 Megawatt (MW) from 4 steam driven turbine alternators. The steam is produced by gas fired boilers and a non-Alcoa gas turbine Heat Recovery Steam Generator (HRSG).

Willowdale Mine has a single power supply fed from the Wagerup refinery. A single 22 kV supply. The Wagerup refinery is a net exporter of power to the SWIS, with internal generation capacity of 108 MW from three steam driven turbine alternators and one gas turbine. The steam is produced by gas fired boilers.

5.5	Physiography

The western edge of the Darling Range is characterized by scarps and incised valleys, landforms which are attributed to tectonic activity along the Darling Fault, the dominant structural feature in the region which acts as the western boundary of the deposits. This feature is observable in regional topographical survey information and satellite imagery to roughly follow the coastline of southwest Western Australia and is approximately demarcated by the extent of Jarrah Forest, a recognized bioregion.

The topography of the ML1SA concession generally comprises wide valleys and undulating hills separated by minor surface water drainage channels and streams. Vegetation across the ML1SA is dominated by several areas of State Forest including Dwellingup, Lane Poole, and Youraling. These include distinct areas of old growth forest within which mining is prohibited.

The typical elevation ranges from 300 m to 400 m in the mining areas, however the highest points of the region (outside of the mining areas) are approximately 550 m.

Topography data was acquired from:

•

Drill hole collar survey data

•

Light Detecting and Ranging (LiDAR) surveys

•

Landgate satellite data.

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6.0

History

6.1	Prior Ownership

Prior to 1961, there were no records of ownership of the Darling Range mines. A Special Mineral Lease (ML ISA) was granted to Western Aluminium NL (WANL) in 1961. In the same year WANL joined Aluminum Company of America Ltd (Alcoa US). In 1977 WANL became Alcoa.

6.2	Exploration and Development History

The following text is sourced and modified from Hickman, et al, 1992.

Bauxite occurrences were first recorded in the Darling Range in 1902. Bauxite was detected as a result of analysing laterite from Wongan Hills, and subsequently through examination of lateritic road gravels from several localities in the Darling Range. The Geological Survey of Western Australia (Geological Survey) produced studies and publications, driving the bauxite exploration, though most attention was focused on localities in the Darling Range close either to Perth or to railway lines servicing towns such as Toodyay and York. The Geological Survey mapped the extent of laterite in the Darling Range (close to Perth) to determine whether it contained commercial deposits of iron or aluminum ore.

The earliest non-government exploration for bauxite was carried out in 1918 by the Electrolytic Zinc Co. of Australia Pty Ltd, deeming the deposits to be generally low grade and not of commercial value, though like earlier explorers, did not focus upon the underlying friable units.

Of 46 early samples of laterite analyzed in 1919, 26 contained 35% or more available alumina. It was then assumed that bauxite in the Darling Range was confined to the duricrust part of the profile, and not considered in the underlying friable units. By 1938 bauxite deposits were known to be common throughout the Darling Range over an area of 560 km long by 40 km to 80 km) wide.

The Geological Survey maintained an interest in Darling Range laterite as an economic source of aluminum until the 1950s. However, by the late 1950s exploration had been taken over by mining companies.

No further private exploration took place until 1957 when Western Mining Corporation Ltd (WMC) began to explore for bauxite in the Darling Range. Following a regional reconnaissance, a joint venture company, WANL, formed by WMC with North Broken Hill Ltd and Broken Hill South Ltd, explored temporary reserves over a large portion of the southwest. Profiles were sampled from road cuttings, with samples collected at 400 m intervals along main roads. Selected lateritic ridges and plateaus were sampled at 90 m intervals. These areas were part of a Special Mineral Lease (ML1SA) granted to WANL in 1961.

By 1961, WANL had delineated 37 Mt of bauxite at an average grade of 33% A.Al₂O₃. Also in 1961, WANL joined with the Alcoa US, allowing additional systematic exploration of lease ML1SA (Figure 5‑1). Holes were drilled initially on 370 m by 185 m centers. Progressive in-fill drilling down to a spacing of 45 m by 45 m blocked out the ore at Jarrahdale and was followed by grade-control drilling. Commercial mining was finally started in 1963 at the former Jarrahdale mining center and continued until 1998, supplying bauxite to the Kwinana refinery.

The Huntly and Willowdale mines commenced commercial production in 1972 and 1984, respectively. In 1977 WANL became Alcoa. As of 2022, the Huntly and Willowdale mining operations remain active. Huntly supplies bauxite to the Kwinana and Pinjarra refineries (approximately 27 Mtpa) while Willowdale supplies the Wagerup refinery (approximately 10 Mtpa).

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Figure 5‑1:Bauxite exploration in the southwest of Western Australia 1961 (adapted from Hickman, 1992)

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7.0	Geological Setting, Mineralization, and Deposit

7.1	Bauxite deposits

Bauxite deposits, economic concentrations of aluminum oxide, represent the world’s major source of aluminum and consist primarily of the minerals gibbsite, boehmite, and diaspore. These are commonly found alongside iron oxide minerals including goethite and hematite, kaolinite clay minerals, and minor accessory minerals.

Lateritic bauxite deposits such as those in the Darling Range of WA generally formed in tropical (hot and humid) environments through chemical weathering. As a result, lateritic bauxite deposits are known to exist across Central and South America, West Africa, Central Asia, and Australia.

With its large available resources, access to a stable workforce, infrastructure (comprising conveyors, rail, road and port access), and three captive (mine-to-mill) dedicated alumina refineries, Alcoa’s Darling Range Bauxite operations near Perth WA, has been one of the world’s leading alumina producing regions for at least 30 years (Hickman et al, 1992), or almost 60 years as of 2021.

7.2	Regional Geology

The bauxite deposits of the Huntly and Willowdale operations are located in the Darling Range region of southwest Western Australia. The predominant topographic feature of the region is the Darling Range Fault, a north-south trending scarp which extends approximately 220 km from Bindoon (70 km north-northeast of Perth) to Collie (160 km south-southeast of Perth).

The Darling Range Fault is the structural boundary between two geological terranes: the Pinjarra Orogen to the west, now the sedimentary Swan Coastal Plain, and the Yilgarn Craton to the east, a gneissic granite complex with greenstones. To the east of the Darling Range Fault intense weathering and erosion of exposed Archean basement rocks of the Western Gneiss Terrane, the western portion of the Yilgarn Craton, formed widespread lateritic bauxite deposits by the intense weathering, accumulation and leaching of the aluminosilicate rich material of the bedrock granites (Hickman et al, 1992).

Alcoa’s current bauxite mining areas of Huntly and Willowdale are on the eastern side of the Darling Range Fault, as low-lying plateaus separated by valleys in which alluvial deposits have accumulated. Figure 6‑1 shows the regional geology of the southwest region of Western Australia and Alcoa’s ML1SA lease boundary in relation to Perth, while Figure 6‑2 shows the distribution of surficial deposits across the region.

The Jarrahdale, Del Park, Huntly and Willowdale areas that have been mined by Alcoa are on laterite within the Western Gneiss Terrane (Figure 6‑2), formed over granites that have been intruded by numerous north trending tholeiitic, quartz dolerite dykes, of early to late Proterozoic age, with thicknesses ranging from 1 m to 200 m.

Lateritic bauxite developed from the Late Cretaceous (65 Million years ago, Ma) to the Eocene (40 Ma), with several periods of erosion and intense weathering of the basement granites and dolerites. Subsequent reactivation of the Darling Fault combined with periods of erosion led to the establishment of plateaus and incised valleys, trending to wider valleys and low hills to the east which now characterize the physiography of the region.

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Figure 6‑1:Regional Geology (adapted from SRK, 2021)

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Figure 6‑2:Surface geology showing laterite over granite (Alcoa, 2015)

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7.3	Local Geology

Laterite remnants are thickest and most extensive over a 150 km long region between the Avon and Harris Rivers, and within about 50 km of the Darling Scarp. The laterite occupies gently sloping (3^o to horizontal) upland areas with an average elevation of 280 to 300 meters above sea level (MASL), and high annual rainfall. Steeper slopes may have a thin cover of partly transported laterite with bedrock near the surface. Above 340 m the laterite is penetrated by bedrock which rises above the general topographic level. Below 200 m drainage has removed pre-existing laterite. Blocks of laterite, released by headward erosion of streams, decay to lateritic gravels on the lower slopes of valleys, which pass laterally into alluvial sands and silt in the valley floors (Hickman et al, 1992).

Bauxite deposits typically occur as irregularly shaped lenses on the flanks of plateaus. Critical to this is the laterite position on the slopes (Figure 6‑3): erosion generally dominates on steeper slopes which prevent accumulation and effective bauxite formation, whereas flat areas lack the necessary sub-surface water flows which drive the removal of clays and the enrichment of soluble silicate minerals.

Figure 6‑3:Bauxite deposit formation schematic – relief exaggerated (Alcoa, 2021)

7.4	Mineralization

Weathering, alteration and leaching of the granite bedrock has developed the bauxite mineralization which principally occurs as 65% microcrystalline gibbsite Al(OH)₃ with minor to rare boehmite AlO(OH), and accessory minerals of 18% goethite FeO(OH), 7% hematite Fe₂O₃, 9% quartz SiO₂, 1% kaolinite/halloysite Al₂Si₂O₅(OH)₄, and 0.5% anatase/rutile TiO₂.

Other minerals within the bauxite that may influence the alumina refinery performance include:

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•

Boehmite: generally occurring below 1%, this can cause premature precipitation of dissolved gibbsite resulting in alumina being lost to the red mud residues.

•

Organic Carbon: as oxalate, typically less than 0.2%, (2.0 kg/t, measured as Na₂C₂O₄) this can result in reduced digestion efficiencies and cause crystal growth issues during precipitation.

•

Sulphate: generally occurring at 0.25%, this can consume caustic soda during digestion resulting in lower yields.

7.5	Property Geology

Table 6‑1 provides a summary of the typical stratigraphy defined by Alcoa across their Darling Range deposits. The Hardcap and Friable Zones represent the primary horizons of economic interest due to their concentrations of alumina. A generalized mineralogical profile through these horizons is provided in Figure 6‑4 and a typical grade profile in Figure 6‑5 showing the alumina and iron-rich Hardcap, with increasing silica and decreasing alumina through the Friable Zone.

Table 6‑1: Alcoa’s Darling Range deposit typical stratigraphic column

Stratigraphic horizon	Typical thickness range (m)	Description
Overburden	0 to 0.5	Mixed soils and clays, high in organic matter, generally forming a thin layer which can penetrate deeper if the underlying Hardcap surface is variable.
Hardcap (Caprock)	1 to 3	Ferricrete formed by the remobilization of iron into a layer comprising iron and alumina-rich nodules which can exhibit the highest alumina concentrations across the deposit. Highly variable in thickness but generally 1 m to 3 m with a sharp contact against the underlying Friable Zone.
Friable Zone	3 to 5	Leached horizon resulting in the accumulation and enrichment of bauxite minerals. The Friable Zone comprises a mixture of the overlying Hardcap, clasts, Al and Fe rich nodules, and clays. Upper contact with the Hardcap is variable, found as a sharp or transitional boundary in places. Available Alumina (A.Al₂O₃) typically reduces with depth as Reactive Silica (R.SiO₂) increases, defining the lower boundary with the Basal Clay.
Basal Clay	-	Kaolinitic clay horizon which, transitions into a saprolitic zone above unweathered basement. This horizon is typically used as a marker indicating the full bauxite zone has been intersected and where drilling is often stopped.

Alcoa’s bauxite deposits across the Darling Range show high variability in both the thickness and relative proportion of each horizon. Table 6‑2 provides an extract from the acQuire database for the Mining Centres of Huntly (in the north) and Willowdale (more southerly) showing the most common (modal) Depth To Top and Thickness of the four stratigraphic horizons, based on logged drill holes from 2016 to 2020.

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Table 6‑2: Summary of typical (modal) stratigraphic horizons within each area

Area	Description (m)	Overburden	Hardcap	Friable Zone	Basal Clay
Huntly	Depth to top	-	0.64	1.51	4.54
Huntly	Thickness	0.64	0.87	3.04	-
Willowdale	Depth to top	-	0.58	1.51	4.91
Willowdale	Thickness	0.58	0.93	3.40	-
North	Depth to top	-	0.64	1.78	4.45
North	Thickness	0.64	1.14	2.67	-

Figure 6‑4:Typical Alcoa Darling Range mineralogy profile (Hickman et al, 1992)

Figure 6‑5: Typical Alcoa Darling Range grade profile (Alcoa, 2015)

Typical photos of the bauxite profile in current mining areas observed on 14 October 2021 are provided in Figure 6‑6.

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Figure 6‑6: Typical Alcoa Darling Range mining sequence and vertical profile (SLR, 2021)

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8.0	Exploration

8.1	Exploration

WANL, which became Alcoa (in 1977), carried out exploration over much of the ML1SA lease area in the 1960s as mentioned in Section 5.2. Samples were assayed for Total Al₂O₃ only and the data, referred to as the Imperial Drilling, is still retained comprising approximately 104,400 holes and approximately 670,000 samples.

The Imperial Drilling has not been used to prepare the current Mineral Resource estimate because the sample collection, preparation, and assaying techniques were not consistent with current practices and can no longer be validated.

8.2	Resource Definition Drilling

Resource definition drilling is initially done on a nominal regular grid spacing of 60 by 60 m. Infill drilling programs are then scheduled as required to reduce the drill spacing to 30 by 30 m, and then 15 by 15 m.

The planned drill hole collars are assigned a hole identifier (Hole ID) using the code of the 15 by 15 m grid point on the 1:1,000 Map Sheets (Section 3.3).

The drilling and sampling database used for resource estimates contains data acquired from over 1.8 million holes drilled between the early 1970s and 2021. A total of 310,906 holes are located within approximately 30 m of the 2021 resource blocks and theses holes were drilled between 1981 to 2021, with approximately 80% drilled after 2009.

A tabulation of the drill quantities by year and location is presented in Table 7‑1, and a graphical summary is shown in Figure 7‑1.

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Table 7‑1: Drill quantities by year and location

Year	Holes				Meters				Assay
Year	Huntly	North	Willowdale	Total	Huntly	North	Willowdale	Total	Huntly	North	Willowdale	Total
1981	613			613	5,216			5,216	9,748			9,748
1983	189			189	1,036			1,036	1,804			1,804
1984	941			941	6,711			6,711	11,456			11,456
1985	367			367	2,614			2,614	4,608			4,608
1990	251			251	1,620			1,620	2,955			2,955
1991	1,544		1,179	2,723	8,528		9,090	17,618	15,023		16,428	31,451
1992	5,269		1,760	7,029	29,335		12,706	42,041	51,432		22,986	74,418
1993	1,808		490	2,298	10,230		3,173	13,403	17,973		5,839	23,812
1994	5,838	632	1,145	7,615	32,694	4,019	6,348	43,061	56,873	7,103	11,010	74,986
1995	3,605	79	2,086	5,770	21,800	477	11,911	34,188	38,505	871	21,509	60,885
1996	5,036	336	836	6,208	28,387	1,522	5,125	35,034	49,934	2,667	9,274	61,875
1997	666		3,672	4,338	4,077		22,923	27,000	7,359		41,282	48,641
1998	372		912	1,284	2,495		5,411	7,906	4,603		9,784	14,387
1999	323		721	1,044	2,091		3,448	5,538	3,851		6,062	9,913
2000	232		213	445	1,530		1,266	2,796	2,773		2,287	5,060
2001	670		583	1,253	5,915		3,753	9,668	10,878		6,815	17,693
2002	1,087		214	1,301	9,886		1,190	11,076	18,293		2,110	20,403
2003	253		1,282	1,535	1,745		8,185	9,929	3,142		14,908	18,050
2004			264	264			1,354	1,354			2,459	2,459
2005	558		1,604	2,162	4,086		9,010	13,096	7,420		16,360	23,780
2006	1,090		794	1,884	8,113		4,736	12,849	14,973		8,680	23,653
2007	3,668		3,594	7,262	25,693		22,947	48,640	47,450		41,689	89,139
2008	2,036		556	2,592	12,723		3,248	15,970	23,072		5,865	28,937
2009	3,046		255	3,301	18,219		1,381	19,600	32,613		2,481	35,094

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Year	Holes				Meters				Assay
Year	Huntly	North	Willowdale	Total	Huntly	North	Willowdale	Total	Huntly	North	Willowdale	Total
2010	6,825		1,114	7,939	40,575		7,669	48,243	71,959		14,160	86,119
2011	10,600		880	11,480	60,565		6,172	66,737	106,091		11,236	117,327
2012	10,755		1,170	11,925	64,041		9,192	73,234	113,088		16,916	130,004
2013	14,006		2,600	16,606	88,290		21,940	110,230	155,854		40,472	196,326
2014	13,283		10,616	23,899	76,166		72,592	148,757	135,466		132,814	268,280
2015	21,215		10,752	31,967	121,628		65,444	187,072	215,338		118,527	333,865
2016	18,597		856	19,453	110,030		4,997	115,026	194,987		8,957	203,944
2017	9,464		9,110	18,574	51,789		55,021	106,809	90,914		97,972	188,886
2018	12,597		9,485	22,082	68,224		51,037	119,261	120,355		90,291	210,646
2019	16,144		13,287	29,431	95,715		90,153	185,868	170,082		163,143	333,225
2020	17,408		16,041	33,449	90,666		102,122	192,788	159,400		184,176	343,576
2021	11,021		10,411	21,432	69,545		79,810	149,355	123,076		146,100	269,176
Total	201,377	1,047	108,482	310,906	1,181,977	6,018	703,351	1,891,346	2,093,349	10,641	1,272,592	3,376,582

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Figure 7‑1:Chart of resource drill holes by year (Alcoa, 2021)

The Darling Range deposits contain more than 3 million drillholes distributed across a lease of over 7,000 km², making it unfeasible to show a plan view of the property with the locations of all drill holes and other samples. Figure 3‑3, however, shows the lateral extent of Alcoa’s mined areas and Mineral Resources and Mineral Reserves within the ML1SA lease. The Darling Range bauxite project is considered to be in the process of sustaining Mineral Reserve from already defined mineralisation, rather than in Exploration mode. Resource Definition drilling is planned to continue throughout all areas where Alcoa has mining permits as described, to sustain the Mineral Reserves and future production. Figure 7‑2 shows a typical section through 30 m spaced Resource definition drillholes:

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Figure 7‑2:Example geological section – F55 N 6,325,500 (SRK, 2021)

8.3	Drilling methods

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Description automatically generated The methods currently used for drill sampling in the Darling Range by Alcoa have been consistently used since the 1980s. Drilling is done using dedicated drills mounted on a fleet of tractors which can be driven off tracks into the forest, causing minimal damage or disturbance and obviating the need to clear drilling pads. Planned hole positions are located by the driller using Global Positioning System (GPS). The articulated tractors are highly maneuverable and there is only minor disruption to groundcover vegetation and saplings which may be eased out of the way (Figure 7‑3).

Figure 7‑3:Resource drilling tractor accessing the forest (SLR, 2021)

Drilling is completed by; Alcoa using vacuum drill rigs, by contractor Wallis Drilling using their patented reverse circulation (RC) aircore rigs, and by contractor JSW using a similar RC method. Wallis and JSW holes are both referred to as aircore drilling. In 2021 there were 5 Alcoa rigs, 3 Wallis rigs, and 4 JSW rigs.

In recent years the drilling period has been extended from 9 to 10 months. More wet ground is now encountered and, where required, vacuum drilling is either deferred until the ground conditions improve, or is re-assigned for aircore drilling.

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Drilling is rapid with holes typically completed every 15 minutes from locating the collar position to completing the drilling, cleaning the sampling equipment and readying the samples for despatch. While 12 rigs are currently used, the procedure is consistent across all rigs and virtually unchanged since the early 1990s at Jarrahdale. Minor modifications to the drilling procedures that have occurred include (in order of importance for their impact on the resource database):

•

Drilling initially was done by vacuum rigs but this has been supplemented by the aircore rigs.

•

GPS methods have been introduced to locate the drill hole collar positions in 3D space, providing more precision on the hole and sample locations (noting that hole positions are assigned to the planned position, see Section 7.6.

•

The sample catching, splitting and logging procedures have been progressively upgraded, following review by various independent consultants (Holmes, 2018; Snowden, 2015; SRK, 2017, 2018, 2019b, 2021a; Xstract, 2016). The riffle splitting system has been enhanced through simple changes to provide a better, more robust method.

•

The logging system has changed from manual paper plods to a completely digital recording system, albeit with paper backup where needed. Barcodes are now used on samples and matching these to the logs is now semi-automatic.

•

The splitting and logging equipment on the drill rig has been progressively improved to make setup and pack-down more efficient and to protect the logging equipment during site moves.

•

Rollover bars, guards, shields, lockouts and other safety protections have been added and safety procedures enhanced with industry norms.

•

Environmental protections and reporting have been enhanced to best practice in SLR’s opinion.

Samples used for Mineral Resource estimation are only acquired using vacuum drilling or aircore reverse circulation. Both methods generally drill dry holes in that water is not added. Water ingress into vacuum holes destroys the sample circulation and wet holes are abandoned. Alcoa commenced aircore drilling in 2015, with the initial plan being to phase out vacuum drilling. The prime advantage of aircore over vacuum is sample recovery when holes do encounter groundwater.

For the 2021 Mineral Resource inventory, 12% of the estimation dataset is derived from aircore holes. In the 2019-2021 drilling for which assay data is available, 79% was performed using aircore (71% for Huntly and 89% for Willowdale).

In vacuum drilling the sample is finely ground and sucked up from the bottom of the hole by a top-mounted vacuum pump. In aircore drilling, compressed air is blown down the annulus between the inner and outer drill string tubes, pushed out through ports on the face of the bit and then blows the sample through the centre of the bit and up the drill string.

In both methods, the sample material is extracted from inside the bit, avoiding sample delineation error (contamination), and carried up the centre of the drill string into the sampling container, avoiding sample extraction error (sample material left down the hole or lost as dust).

The aircore drilling uses a blade bit with a nominal cutting diameter of 45 mm and an internal retrieval tube diameter of 22 mm (Figure 7‑4). Alcoa increased the internal diameter to 25 mm in 2018 to reduce blockages. The particle size of drilled material is sufficiently small (less than 10 mm) to promote good sample splitting in dry conditions.

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Figure 7‑4: Drill bits, reverse circulation drill string and particle size of the sample residue (SLR, 2021)

Scale pen diameter 13 mm

8.4	Drill sampling

8.4.1

Procedure

The sample catching, splitting and logging procedures are the same for both vacuum and aircore drilling (Figure 7‑5).

The drilling and logging are controlled by the driller with minimal supervision by geologists. This has been observed and is deemed reasonable by the SLR QP due to the combination of very simple logging, experienced personnel, employment continuity and continual review by geologists.

Sampling commences at the base of the overburden and continues until the driller considers that the basal clays have been penetrated for at least 1 m or for infill holes at a 15 m spacing to the depth defined on the drill hole plan from surrounding data. Alcoa estimates that between 10% and 15% of the limited depth holes terminate in bauxite.

Samples are collected at 0.5 m intervals, measured using a laser gauge mounted on the rig. At the end of each 0.5 m interval, the drilling is paused and the sample passes from the cyclone (for aircore) into the collection flask. For vacuum drilling the collection flask is at the end of the vacuum system.

The sample, nominally 1.5 kg, is poured from the flask into a feed tray, distributed evenly, then on the vacuum rigs the tray is pivoted to feed a small 12-vane riffle splitter (the rotating tray is excellent but not

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yet fitted to the aircore rigs). Where (usually) required, the splitting is repeated to give a retained split of 150 to 200 g, small enough to be collected into a 120 mL measuring cup with minimal spillage. The riffle split subsample is poured into a barcoded Kraft packet and boxed for despatch to the assay laboratory. The sample retrieval and splitting systems are cleaned with compressed air after each hole.

During the site inspection, the JSW RC sampling procedures were observed closely. It was found that the principles of correct sampling were understood by all personnel at the rig and the equipment and practices were observed to be satisfactory.

Over the period 2015 to 2021 the drill sampling procedures have been externally reviewed (Snowden, 2015; Holmes, 2018; and others) and various improvements have been made such as using riffle splitters with more vanes, using a pivoting tray to consistently feed the splitter, training in the correct splitting and retention of all the subsample, digital recording of logging, monitoring of accuracy with Standards, and monitoring of precision with duplicates.

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Figure 7‑5:Sample catching and riffle splitting practices (SLR, 2021)

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8.4.2

Recording sampling data

The drill hole and sample information is recorded digitally onto a tablet at the rig during drilling (Figure 7‑6). The data is automatically loaded into an acQuire database. In previous years the same information was all recorded in a ticket book and manually transferred to the database. This approach remains as a backup method when needed. Data recorded includes hole number, drill rig number, driller name, offsider name, depth of overburden, depth of Caprock, map reference, material type code, and comments on the reason for ending the hole, e.g. if bedrock or water was encountered.

Figure 7‑6:Barcode reader and digital recorder mounted on the drill rig (SLR, 2021)

8.4.3

Sample logging

The geology of the Darling Range bauxite is well understood. The Material Type codes have been simplified to meet the production needs of the operation and the drill crew has been trained in their identification, which is primarily based on color and hardness.

This results in logging of a reasonably consistent regolith profile formed by surface weathering of the few bedrock types (granite or dolerite). A comprehensive geological log is not produced but the Material Type codes can be ratified by the assay results. The Material Type codes are provided in Table 7‑2.

Table 7‑2: Logging codes for Material Type

Material Type	Description	Comment
HB	Hard brown	Hardcap and Friable Zone
HSB	Hard / soft brown
SB	Soft brown
SY	Soft yellow
CLB	Clayish brown
CLY	Clayish yellow	Basal Clay Zone
BC	Brown clay
YC	Yellow clay
WC	White clay
DOL	Dolerite	Intrusion

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Material Type	Description	Comment
GR	Granite
WET	Wet	Other
ROD	Broken rod	Other

8.5	Topography

Topography data was acquired from:

•

Drill hole collar survey data and check surveys performed using Trimble R10 real time kinematic differential global positioning system (RTK DGPS) equipment

•

LiDAR surveys conducted in April 2015, November 2016, and June 2018 (no further surveys have been required). A plan showing the LiDAR coverage for each survey is provided in Figure 7‑7.

•

Landgate satellite data collected in the late 1990s.

A digital elevation model representing the natural surface was prepared by combining (in order of priority) the collar survey data, the LiDAR data and the satellite data.

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Figure 7‑7:Topographic data coverage of the 2015, 2016 and 2018 LiDAR surveys (Alcoa, 2022)

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8.6

Surveying

Alcoa has consistently drilled the Darling Range bauxite deposit on a 60 by 60 m grid (with infills to 30 by 30 m and 15 by 15 m) since the 1970s. Initially collar peg positions were surveyed using either a theodolite or Total Station. The 30 m and 15 m pegs were positioned between the 60 m pegs using tape and an optical square. Alcoa commenced using GPS survey control (RTK DGPS) in mid-2015.

Drilling is conducted before any forest clearing activities, which are only carried out for mine development. Positioning the drill rigs is thus imperfect. If the actual coordinates are within 2 m of the planned coordinates, the hole is considered to be correctly located, and the planned coordinates are used in in all subsequent processing. Holes that are collared more than 2 m away from the planned location are flagged accordingly in the database, but the planned coordinates are still used in preference to the actual locations. In 2015, Alcoa commenced check surveying of collar positions after drilling. Most of the holes drilled in 2016 and 2017 were check surveyed. Major discrepancies, such as large differences between the actual coordinates and the coordinates defined by the hole identifier, are investigated and corrected in the database.

The planned coordinates at the 15 by 15 m grid points on Map Sheets (see Section 3.3) are used in preference to the actual coordinates because the original resource delineation systems (Polygonal and GSM, see Section 11.3) were based on the use of regularly gridded data. The use of planned instead of actual coordinates does introduce some uncertainty in the local sample position and consequently the local estimates. However, it is noted that:

•

The lateral error is random, small in magnitude compared to the smallest drill grid spacing (15 m), and monitored (Figure 7‑8) with deviations from plan greater than 7 m redrilled.

•

The error affects few holes (for 2020 of the 52,546 holes drilled, 65.0% were within 2 m, and 99.7% within 5 m).

•

The long range of the grade continuity of mineralization as shown by the variograms is several hundred meters.

•

The local small-scale variations on the grade of mineralization due to variations in the amount of lateralization are uncontrolled and unpredictable (see discussions of drill hole twinning in Section 8.5.3.3).

•

The effect is a controlled ‘random stratified grid’, given that the nominal collar position is always used for estimation and there is no evident bias.

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Figure 7‑8:Error in actual collar location from the nominal (planned) position is monitored for the three drill rig types (Alcoa, 2021)

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Downhole surveys are not performed in drill holes because of their generally shallow depth and narrow diameter, so all holes are assumed to be vertical.

The drill rigs have limited capacity to be levelled and cannot drill angled holes, so in some circumstances the holes may be drilled perpendicular to the natural surface. The rigs are designed to safely operate on gradients of up to 15°, so holes could be drilled up to 15° off the vertical. For a 6 m hole drilled at the planned collar position, the offset may be up to 1.55 m horizontally and 0.2 m vertically (Figure 7‑8).

Figure 7‑9:Possible lateral and vertical sample location error on 15^o sloping ground (SLR, 2021)

The impact of differences between the actual locations of samples in 3D space compared to their nominal location on the mine plan is considered to not materially impact on the Mineral Resource because the errors in the spatial controls on mining are likely to be of the same magnitude as the spatial errors in mining (±2 m laterally and ±0.3 m vertically). Mining is locally controlled by DGPS on mining equipment to meet short-term plans and visually for indications of the base of ore (e.g., WC white clay).

8.7	Sampling conclusions

8.8	Hydrogeology Data

No site-specific hydrogeological data is available; however, no hydrogeological considerations are required for the definition of mining plans in Alcoa’s Darling Range operations.

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8.9	Geotechnical Data

No site-specific geotechnical data is available; however, as the slopes are so shallow, no geotechnical considerations are required for the definition of mining plans in Alcoa’s Darling Range operations.

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9.0	Sample Preparation, Analyses, and Security

Sample preparation is performed by Bella Analytical Systems (Bella). Although the laboratory is located within Alcoa’s Kwinana Refinery complex and only processes Alcoa material, it is independently owned and operated by Bella. A link exists between the Bella and Alcoa Laboratory Information Management System (LIMS) for the two-way exchange of data. The laboratory does not have Australian National Association of Testing Authorities (NATA) accreditation.

All assays produced by Bella are monitored and controlled by Alcoa at the Kwinana Mining Laboratory (KWI), which, although it has a QA/QC system based on ISO 9001 protocols, only has one section of the laboratory certified to ISO 9001 for the purpose of certification of shipment assays of alumina.

A robotic processing system is used to prepare each sample for Fourier Transform Infrared Spectrometry (FTIR) and Reference Method (REF) testing. This entails pulverizing each sample in a flow-through ring mill to a nominal grind size of 85% passing 180 µm, and then splitting off sufficient material to fill a barcoded scanning flask (20 mm high with an 80 mm diameter). The material from the ring mill is discharged through a rotary splitter, with approximately 80–100 g of material retained for geochemical testing, and the remainder discarded. A duplicate sample is collected from 1% of the samples via a rotary splitter fitted with twin select chutes. These samples are used for Reference Methods testing.

9.1	Sample security

Subsamples are collected by the drillers, sealed into Kraft packets with barcodes and submitted for assay. Cardboard boxes holding 50 packets are delivered at the end of each shift, by the drilling crew, to secure sample storage facilities. Unfilled boxes are stored in the drill support vehicle and completed in the next shift.

The filled sample boxes are stacked onto pallets in batches of 40 (i.e., 2,000 samples), wrapped with plastic and despatched by courier to the Bella assay facility at the Kwinana Refinery.

9.2	Sample preparation

Upon receipt by Bella, the sample barcodes are scanned and checked against the submission data in the Bella LIMS. Each sample packet is then split open at the top, placed in a cardboard drying tray and oven-dried at 100°C for 10 hours. The packets are transferred to a customized holder in batches of about 60, with a control between each batch, and automatically fed to a bank of 10 Rocklabs flow-through ring mills, (Figure 8‑1), each of which have three concentric milling rings. The barcode is read, the sample is pulverized, a subsample is rotary split, captured in a single-use plastic Petri dish with the barcode printed on the lid, then sent to the spectral analyzer for assay. The ring mills are air flushed and vacuumed between samples.

Each sample is pulverized to a nominal grind size of 85% passing 180 µm. The ring mill discharges through a chute and rotary splitter, retaining 80 to 100 g and discarding the rest. One of the ring mills is set up to take two splits and these are used for pulp duplicate assays and to generate the Reference (REF) samples. These are sent to the KWI for wet chemical assay checking of the spectral assay.

The robotic system can run 24 hours a day handling approximately 3,000 samples per day. Only the Mineral Resource estimation samples are processed at Bella with all other stockpile and processing control samples processed using the same methods as the REF samples.

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Figure 8‑1:The Bella robotic sample preparation using Rocklabs ring mills (SLR, 2021)

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Figure 8‑2:The pulverized sample is stored in a barcoded dedicated receptacle for assay (SLR, 2021)

A LIMS system controls the progress of the sample packet through the whole of the sample preparation and assay procedure enabling digital tracking of all stages (Figure 8‑3). This ensures inter alia that the sample is valid, not previously assayed, and the assay looks like one for a bauxite sample. It also generates pulp duplicates at a frequency of 1 in 100 which are also the REF samples.

Figure 8‑3:The pulverized sample is tracked digitally through the Bella preparation and assaying (SLR, 2021)

Grind size monitoring is carried out with the advantage of the robotic sample preparation being consistent grind size (see Section 8.5.1). A risk with all such systems is the possibility of contamination between samples. This is usually avoided by inserting blank samples of zero grade into the sample processing stream. The difficulty is that the blank samples may themselves contaminate the next sample being assayed. Blank sample submission is discussed in Section 8.5.2.1.

9.3

Assaying

Assaying of the drill samples is based on a spectral method, using a Nicolet 6700 FTIR Spectrometer with a robotic feeder (Figure 8‑4). FTIR obtains an infrared absorption spectrum from the sample. The FTIR spectrometer simultaneously collects high-resolution spectral data over a wide spectral range. A

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mathematical process (Fourier transformation) converts the raw data into the actual spectrum for subsequent determination of the component analytes.

All drill samples are currently assayed using a customized, bespoke FTIR method, with the final corrected results used for Mineral Resource estimation. Calibration and monitoring of the FTIR results are done using the Reference Method assay results.

Bella generates the raw FTIR spectral dataset for each sample, which is transferred to the Alcoa LIMS system for post-processing. Alcoa performs all the Reference Method analyses at KWI.

The FTIR spectra are determined using a robotic scoop arm that collects an approximately 5 g aliquot of the pulp from the Petri dish and presents it to a platinum crucible. The material in the crucible is pressed flat to ensure an even surface for scanning. The crucible is then rotated several times through the spectrometer and 20 scans are conducted on the aliquot. The scans are processed and validated by the Bella system and when accepted, they are then transferred to the Alcoa LIMS system for post-processing and further validation.

Figure 8‑4:The robotic FTIR assaying equipment
(RHS shows the sampling scoop arm and pulp dish with the lid elevated) (SLR, 2021)

9.3.1

FTIR Method assays and the CalVal dataset

The FTIR Method for bauxite assay uses infrared absorption spectra to characterize the presented sample for multiple analytes as element, compound, or mineral percentages. The approach has been developed using an extensive calibration and validation (CalVal) dataset, constant monitoring of Reference samples and Standards, and periodic revision of the prediction algorithms.

In 1990, an initial set of approximately 2,300 CalVal samples was collected covering the Darling Range tenement. A subset of approximately 700 samples was used to develop the initial FTIR prediction model. Extra CalVal samples have been added to help predictions in areas of low Reactive Silica (less than 0.5% R.SiO₂) and high Total Iron (greater than 50% Fe). The CalVal samples are run randomly through the FTIR equipment in triplicate, under differing conditions (time of day, season, operator, order, etc.) to test for external factors. The FTIR results based on the prediction model algorithm are monitored using the REF assays (Franklin, 2019).

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Initially some FTIR analytes (Available Alumina, Total Iron, Carbonate, Sulphate, Total Silica, Total Phosphorus and Magnetic Susceptibility) were all determined using a ‘common’ algorithm, whereas Reactive Silica, Oxalate, Extractable Organic Carbon, Total Alumina and Boehmite each used a specific algorithm. Since 2017 specific algorithms have been used for all analytes. The algorithms are periodically updated, typically if there has been a change in equipment or Reference Method. Retaining all FTIR spectra now means additional analytes can be determined using specific algorithms, with three new analytes being added to Method Set MIC#00005 in 2021 (Potassium, Titanium and Gallium).

9.3.2

Reference Method (REF) assays

The REF assaying is done by Alcoa in the KWI to validate and calibrate the FTIR assays. This is a suite of assays and tests that are carried out by wet chemical and other means and has included:

•

XRFx-ray fluorescence spectroscopy

•

ICP-OESinductively coupled plasma optical emission spectrometry

•

XRDx-ray diffraction

•

MSmagnetic susceptibility, a proxy for grindability

•

BD-ICPbomb digest in a caustic solution, with an ICP-OES finish

•

BD-GCbomb digest in a caustic solution, with a gas chromatography finish

•

BD-NDIRbomb digest in a caustic solution, with a non-dispersive infrared finish

•

MD-ICPmicrowave digest in a caustic solution, with ICP-OES finish

There are differences in the nature of these tests. Both XRF and ICP methods are instrument-based methods designed to replicate wet chemical analysis results, either total or partial assays depending on the digestion. Both XRD and MS methods are used to investigate mineralogy contents so are regarded as proxies for assays. Bomb digest (BD) methods have been developed by the alumina refining industry to determine the expected yield of bauxite ore during processing. They are the basis for ‘metallurgical assays’ that are designed to replicate the physicochemical reactions in the refinery and accordingly may be customized for a particular ore type or process plant. At Alcoa some BD assaying has been replaced with a microwave digest (MD) method.

9.3.2.1

REF assaying methods

A summary of the assaying used for the REF samples, which are used to calibrate and validate the FTIR Method, is provided in Table 8‑1.

Table 8‑1: Assaying methodologies for resource estimation samples

Name	Analyte	Code	Units	Reference Method
Available Alumina	A.Al₂O₃	AL	%	MD – ICP (MALSI)
Reactive Silica	R.SiO₂	SI	%	MD – ICP (MALSI)
Total Iron	Fe₂O₃	FE	%	XRF
Oxalate	NaC₂O₄	OX	kg/t	BD – GC

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Name	Analyte	Code	Units	Reference Method
Carbonate	Na₂CO₃	CO	kg/t	BD – NDIR (TICTOC)
Extractable Organic Carbon	C	EO	kg/t	BD – NDIR (TICTOC)
Total Phosphorous	P₂O₅	PT	%	XRF
Sulphate	Na₂SO₄	SU	kg/t	XRF
Total Silica	SiO₂	ST	%	XRF
Magnetic Susceptibility	MagSus	MS	None	MS (CGS system)
Total Alumina	Al₂O₃	AT	%	XRF
Boehmite	AlO(OH)	BO	%	XRD

The bomb digest (BD) method involves adding a measured amount of carbonate free 52% caustic soda to the sample aliquot (1 g), sealing it in a small 10 mL pressure vessel and then cooking it at 145°C. After cooling, the solution is assayed by titration or other methods to determine the alumina and silica contents. As the digestion of these elements by the hot caustic solution is determined by the physical conditions during digestion (mainly temperature and pressure) the results provide a proxy for the expected performance of ore of that nature in the alumina refinery plant. The resulting assays are termed available alumina (A.Al₂O₃) and reactive silica (R.SiO₂), measured as percentages.

The MD method was introduced in 1996 to supplant the BD methods for assaying of the Mineral Resource drill samples. Atmospheric digestion is done in a microwave oven using a 13% caustic solution. The advantage of this is that it is faster, more repeatable and uses a bigger aliquot (0.5 g). The MD assays are collectively named ‘microwave available alumina and reactive silica’ (MALSI). The BD methods are still used for the refinery monitoring samples including those taken from the sampling towers prior to the feed stockpiles of crushed ore.

Following digestion using either MD, BD, or wet chemical methods, the analytes are assayed (Table 8‑1) using the following methods (Figure 8‑5):

•

For ICP the digestion liquor is read using a PerkinElmer Optima 8300 machine.

•

For XRF an aliquot of 0.7 g is combined with a lithium borate flux, fused in platinum crucibles on a dedicated Phoenix 8-bank burner, and batches are assayed on an Axios Max PW4400 machine.

•

For gas chromatography (GC) a 1.00 g aliquot is used and assayed on an Agilent 7890B machine.

•

For Total Inorganic Carbon and Extractable Organic Carbon (TICTOC) a 1.00 g aliquot is digested and assayed using an Analytical Aurora 1030 Total Organic Carbon Analyzer with carousel.

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Figure 8‑5:Digestion and assay equipment used for REF samples at the KWI
Clockwise from top left: BD, MD, TICTOC, ICP, XRF, GC (SLR, 2021)

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Details on the assaying method used for the final (Best) assay value for every sample interval are carried in the acQuire database.

For resource estimation, the Reference Method results are used to monitor the performance of the FTIR assaying, and to calibrate (adjust) the FTIR results on a batch-by-batch basis. The Reference Method is also used for all monitoring of the refinery performance including the grades of ore presented to the sampling towers at Pinjarra and Wagerup prior to stockpiling and reclaiming of the ore feed.

A consistent approach to sample collection, preparation and assaying for Mineral Resource estimation has been used since 1980. Refinements to the assaying methods have comprised:

•

1996 Microwave digestion was introduced instead of bomb digestion for the REF samples

•

1999 The collection of the FTIR spectral data was outsourced to Bella, with direct control of processing and prediction still done by Alcoa

•

2006 Robotic sample preparation was introduced at Bella

•

2006 Digital retention of all FTIR spectral data was introduced, enabling additional post-processing of assayed samples for new analytes

•

2017 The calibration sets were rescanned with FTIR and an updated Method Set (MIC#00005), was developed

•

2018 Original wet chemical assays were replaced by FTIR for approximately 73,000 samples (drilled in Myara North from 1992 to 2002)

•

2019 Original wet chemical or FTIR assays were replaced by FTIR for approximately 251,000 samples (drilled in Myara North from 1991 to 1997).

The impact of these changes and validation of the results were investigated by Alcoa personnel and independently by SRK (2021a). It was concluded that the assaying precision (i.e. repeatability) and accuracy (lack of bias, as demonstrated by quantile-quantile plots) did not show significant differences between the pre-2018 and post-2018 data sets. Accuracy and repeatability are further discussed in Sections 8.5.2 and 8.5.2.2.

Since completion of the previous 2020 Mineral Resource inventory, an additional 61,906 vacuum and aircore holes have been drilled and approximately 644,000 routine FTIR analyses performed. These represent holes drilled between September 2020 and June 2021.

9.4	Quality Assurance (QA)

The Quality Assurance (QA) component of a sampling and assaying program is defined by the presence of written procedures which are used to guide current practice, and by which changes to practices over time may be monitored. These procedures also specify the Quality Control (QC) data that should be collected to monitor the performance of the sampling, sample preparation and assaying.

The existing written procedures include:

•

Franklin (2019) describing the FTIR process.

•

Use of the customized in-house Exploration PowerApps digital module to record and document field inspections by the geologist at the drill rigs (documenting visible contamination, Sample ID, Hole ID, splitting, chip size of sample, split volume, depth measurement, collection of Sample To

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Extinction (STE) samples discussed in Section 8.5.3.4, collection of further FTIR calibration and validation (CalVal) samples (discussed in Section 8.3.1), as well as other prestart, safety, risk and EHS inspections.

•

Procedures for generating STE samples.

•

Various PowerPoint presentations providing an overview of the laboratory procedures.

9.5	Quality Control (QC)

9.5.1

Sample preparation

QC procedures implemented to monitor the Bella robotic sample preparation system (Franklin, 2019) include:

•

Temperature testing on the ovens. These are recorded between 2 and 5 times a year since 2017 at 8 positions for each of 4 ovens and demonstrate consistent safe drying temperatures below 100^oC (average 97.9^oC for 352 readings).

•

Daily grind size checks. The percentage passing 180 microns and percentage exceeding 300 microns is recorded at Bella on all 10 ring mills at a rate of 1:200 for the resource drill samples, with independent checks by the KWI on a random selection of all samples milled for the week. These demonstrate satisfactory sample preparation, and the consistency of the Bella robotic system, which is critical for effective FTIR assaying (Figure 8‑6).

Figure 8‑6:Sample preparation monitoring (Alcoa, 2021)

Grind sizes for the robotic sample preparation unit tested by Bella and by KWI.

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9.5.2

Accuracy

Accuracy is determined by the difference (bias) between a result and the expected value. It is usually determined by assaying Standards (reference materials), blanks, and by comparing the means of datasets.

9.5.2.1

Blanks

Blank samples are routinely included in the FTIR submission batches after sample preparation, to prevent contamination of the mills by very low grade samples. Blanks are submitted with a frequency of 1 to 19 in the REF samples sets compiled by Bella and regularly despatched to KWI for Reference Method digestion and assay.

Blanks are not introduced into the robotic mills at Bella and there is no check on cross-contamination during sample preparation. Given the style of mineralization, the ore grades being assayed and the volume of material milled compared to the final aliquot assayed, the absence of sample preparation blanks is not considered material.

9.5.2.2

Standards

After the boxes of drill samples are received at Bella, packets of Reference Method samples (REF) are split out by the robotic sample preparation, based on a random selection by Alcoa LIMS, at a frequency of 1 in 100. These are submitted to the KWI in batches of 19 for REF assaying to calibrate and validate the Bella assays. Each batch of REF samples includes 1 Blank and 1 Standard.

Alcoa has used a series of specially prepared Internal Reference Material (IRM) samples derived from Darling Range bauxite, pulverized and homogenized by Gannet Holdings, labelled KH09 to KH18. Monitoring using these IRM samples provides arguably better assurance of assaying accuracy than commercial Certified Reference Material (CRM) samples. The IRMs have generally been sourced from stockpile material and used in both coarse-crushed and pulp form. IRMs are color coded as follows: pink for FTIR assay control, yellow for grain size, khaki for drill sampling. The IRMs have not been externally certified. A summary of the IRMs is provided in Table 8‑2.

Table 8‑2: Standards used for drilling and REF monitoring (IRMs)

Standard	Date	Comment
KH09	May 1999 to present	Boehmite analysis, FTIR, MD-ICP, and XRF analysis Mining reference analysis (IRM)
KH10	May 2012 to present	Mining reference analysis (IRM)
KH11	July 2008 to March 2015	FTIR analysis (IRM)
KH12	July 2008 to April 2014	Grind size control (IRM)
KH13	April 2014 to present	Grind size control (IRM)
KH14	March 2015 to present	FTIR analysis (IRM)
KH15	October 2015 to September 2017	Preparation and analytical control – introduced at the drill rig (IRM)

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Standard	Date	Comment
KH16	September 2017 to December 2018	Preparation and analytical control – introduced at the drill rig (IRM)
KH17	September 2017 to December 2018	Preparation and analytical control – introduced at the drill rig (IRM)
KH18	September 2017 to December 2018	Preparation and analytical control – introduced at the drill rig (IRM)

From October 2015 to December 2018 the IRMs KH15 to KH18 were introduced by the driller at the drill rig to monitor sample preparation (grinding and cross-contamination) and assaying. This material was sourced from the Kwinana Refinery stockpile crushed to nominal 3 mm, homogenized, and split into 200 g lots by Gannet Holdings, a commercial preparer of Standards.

Control of the accuracy of batches of FTIR samples is monitored using IRMs KH10 and KH14. FTIR batches of approximately 60,000 samples are controlled using Priority Codes (e.g. P157 to P175 covered the period September 2018 to October 2020). Priority Codes represent batches assayed by the FTIR Method using the same batch correction factors.

The frequency of insertion of IRMs such as KH10 is 1 in every REF batch (19 samples, 1 KH10 and 1 blank). The frequency of re-assaying the FTIR results (if rejected by a REF assay) has an expected rate of less than 1.5%. Actual performance depends on the total number of FTIR assayed samples, the area where they were drilled and whether there were issues with the Sample Presentation Unit (SPU) in the FTIR process.

A summary of the performance of IRMs KH10 and KH14 for batches tested between September 2018 and October 2020 is provided in Table 8‑3. The failure rates, using a criterion of Mean +35 Standard Deviations, are generally low with failure rates above 0.1% highlighted. Performance overall is excellent for AL, good for SI and generally reasonable for all analytes. This Table indicates that KH10 demonstrates better homogenization than KH14 (which admittedly has many more assay results) and repeatability of CO (carbonate), EO (extractable carbon) and BO (boehmite) are more challenging than the other analytes.

Table 8‑3: Summary of performance of IRMs KH10 and KH14 for the full analytical suite

Priority batches P157 to P175 for September 2018 to October 2020

Highlighted cells indicate %Fail rate exceeded 0.1%


IRM	Analyte	AL	SI	FE	OX	CO	EO	PT	SU	ST	MS	AT	BO
KH10	Count	934	934	849	810	811	824	841	841	841	820	841	811
	Fail	0	0	0	1	6	22	0	1	0	0	0	7
	% Fail	0.0%	0.0%	0.0%	0.1%	0.7%	2.7%	0.0%	0.1%	0.0%	0.0%	0.0%	0.9%
KH14	Count	30,828	30,828	30,828	30,828	30,828	30,828	24,641	30,828	30,828	30,828	30,828	30,828
	Fail	19	117	208	137	225	117	269	105	75	565	56	586
	% Fail	0.1%	0.4%	0.7%	0.4%	0.7%	0.4%	1.1%	0.3%	0.2%	1.8%	0.2%	1.9%

Alcoa uses CRMs for laboratory analytical control including NIST600 (used since June 1996), BXPA01 (used since December 2011) and SG11 (used February 1996 to May 1999) for XRF calibration. A commercial liquid CRM is used for monitoring the MD method for AL and SI referred to as MALSI (Figure 8‑7).

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Figure 8‑7:Assaying Standards (left IRMs KH09 and KH10, right CRM for MALSI) (SLR, 2021)

9.5.3

Repeatability

9.5.3.1

Measures Of Precision

There are a number of approaches to defining the repeatability of an assay result, and they are generally controlled by a framework first developed by Pierre Gy, now referred to as the Theory Of Sampling. Accepted approaches used here for determining the repeatability of sampling and assay results are:

•

Scatter plots with the same X and Y axes, showing the overall distribution of the paired samples, and obvious outliers, with perfect repeatability shown by the 45^o line of equality.

•

Measures based on the robust Half Absolute Relative Difference (HARD) bivariate statistic (Shaw, 1997; Abzalov, 2016). These include the precision (as Coefficient of Variation (CV) with a confidence interval of 68%) and the 90^th percentile HARD limit.

•

Other bivariate measures, that may be influenced by outliers, such as the slope of regression, variance and CV.

With all measures, trimming the data (excluding outliers, obvious errors, incorrect values, out of range values, and those near the Limit of Detection) can impact on statistical measures of precision, which is why scatter plots are helpful in interpreting results.

9.5.3.2

Umpire laboratory checks

Alcoa sends checks of REF samples assayed at the KWI to two independent laboratories, SGS and Bureau Veritas (BV). The Priority dataset P175 Bias and Precision (B&P) was examined by SLR. Results are provided in Figure 8‑8 and Figure 8‑9 for AL and SI results, and precisions for AL, SI, FE and OX are summarized in Table 8‑4.

It is apparent that there is a consistent bias with the Alcoa KWI reporting higher (by 3 to 4%) for AL and by 0.4 to 0.6% for SI. Precision measures indicate KWI shows better repeatability with BV than with SGS. Results for FE and OX are similar. Note that the precisions in the figures and Table 8‑4 are for untrimmed data, but the number of pairs vary due to some missing or zero values. The precisions are higher than expected, given the good repeatability of the REF assays at KWI (Section 8.5.3.6) and suggest that the KWI REF assays are better customized to the Alcoa bauxite than the umpire laboratories. Trimming the data

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to ranges appropriate to expected ore grades in some cases improves the precision (e.g. for AL but not for SI).

These results indicate that the repeatability of the MALSI assays in particular, and suggestions of possible bias, are because these are proxy metallurgical tests, and may be subject to slight variations in the microwave digestion procedures prior to XRF, between and within all three laboratories. While the precision results themselves are moderate, the lack of outliers and overall scatter indicates that the REF assays are reasonable as the basis for calibrating and validating the FTIR Method.

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Figure 8‑8:Umpire checks of REF A.Al₂O₃ at SGS and BV (SLR, 2021)

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Figure 8‑9:Umpire checks of REF R.SiO₂ at SGS and BV (SLR, 2021)

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Table 8‑4: Summary of precisions for umpire check results on assay dataset P175

AL, SI, FE and OX at SGS and BV compared to KWI

REF analyte	Check lab and analyte	Pairs	Precision	90th Percentile	Bias	Note
REF_AL	SGS_AL	890	18.0	21.5	3.86
	BV_AL	911	14.0	16.99	3.50
	BV_AL	713	6.3	12.61	3.71	Trimmed to AL > 15%
REF_SI	SGS_SI	958	24.0	26	0.58
	BV_SI	972	11.9	14.4	0.44
	BV_SI	824	12.2	14.7	0.16	Trimmed to SI > 0.05 and < 10%
REF_FE	SGS_FE	937	21.9	24.3	1.05
REF_FE	BV_FE	972	13.3	11.8	0.32
REF_OX	SGS_OX	934	32.6	38.65	0.04
REF_OX	BV_OX	972	18.7	17.6	0.04

Notes:

Precision is based on the CV of the HARD statistic at a confidence interval of 68%

90^th percentile is based on the ranked HARD statistic

Bias is the difference in the Means of Original and Duplicate sets, negative if REF is lower.

9.5.3.3

Twinned hole studies

Considering the long period of resource drilling since the 1970s, Alcoa has only relatively recently started the routine collection of QC data for drilling, sampling, and assaying.

The drillers carry out the logging and sampling of the resource estimation drill holes. In the past they have produced Field Duplicate samples, but these have now been replaced by STE samples (Section 8.5.3.4).

Various studies (Barnes, 2015, 2016, 2018a, 2018b; Crockford, 2011, 2012; Grigg, 2016; Hodgson, 2015) have been carried out and reported to determine the repeatability of the drill sampling and to compare the Alcoa vacuum drilling to the Wallis aircore and JSW reverse circulation drilling. These studies are of limited use in interpreting the quality of the different drilling methods and in comparing them. In these studies, the original vacuum hole (the parent) is twinned by a second hole (the twin) collared within approximately 30 cm. They may be summarized as follows:

•

Barnes (2015) produced 841 pairs of samples, with the parent sampled at 0.5 m and the twin at 1 m.

•

Grigg (2016) twinned 127 aircore holes (Huntly region, 862 paired samples), 34 vacuum holes (Huntly region, 185 paired samples), and 693 vacuum holes twinned with aircore holes (Huntly and Willowdale regions, 5,947 paired samples). As re-assessed by SLR, poor repeatability was demonstrated for all datasets, with 90% of the samples having a HARD measure of less than approximately 30% (good repeatability would have 90% less than 15%). Given the poor

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repeatability, it is not possible to determine any bias between the methods, or whether the sampling is better for any analyte.

•

SRK (2021a) presented results from 2018 for 21 pairs of vacuum holes and 6 pairs of aircore (Huntly region, 238 paired samples). The results show similar levels of poor precision for AL, SI, FE and TS (the ranked Absolute Mean Percentage Difference (AMPD) plots provide values twice those used in this report).

Figure 8‑10: Twinned hole comparison for 238 data points from 2018 (after SRK 2021a)

Scatter plots with overlayed Q-Q plot (in red), and ranked AMPD (HARD*2) plots

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The poor repeatability of the twinned hole programs, shown by the scatter plots and precision results, is not surprising and may be ascribed to:

•

Short-range geological variability in the laterite profile

•

Sample quality and recovery affected by splitting, moisture, seasonal effects, vertical control, and operator error at that time.

9.5.3.4

Field Duplicates

It is generally considered best practice to collect Field Duplicates in resource drill sampling programs. They should be a second split collected with the first split in exactly the same way (i.e. from the same drilled interval, using the same splitter, generally from the reject side of the splitter, sometimes by resplitting all of the reject a second time).

The routine collection of Field Duplicates by Alcoa has been intermittent and last commenced in February 2015, with duplicates collected at a nominal frequency of 1 in 200, with no more than one duplicate per hole. SRK (2021a) examined 5,885 sample pairs, from a mix of material types, locations and drilling types. They concluded that the Field Duplicates showed no evidence of significant grade bias but that the precision was lower than expected for this style of mineralization. From graphs they presented, the 90% threshold for the HARD statistic as a measure of precision (defined in Section 8.5.3.1) was between 12 and 20%. Precision was poorer for boehmite and oxalate. No significant precision differences were evident between the vacuum and aircore Field Duplicates, nor by year, nor between the Huntly and Willowdale Field Duplicates.

Alcoa and various independent reviewers (Holmes, 2018; SRK2021a) considered that there were some limitations to the benefit of collecting Field Duplicates because the sample splitting procedure was problematic (the small sample volume of 150 mL, and some poor splitting equipment and procedures). Work on implementing recommendations has resulted in procedures which were adequate during the site inspection by SLR (Figure 7‑5). There are still some limitations:

•

Field Duplicates are not routinely taken and have been replaced by a single Sample To Extinction sample per rig per shift (see Section 8.5.3.5).

•

The resulting sampling frequency may be lower than the usual industry practice of between 1 in 20 (5%) and 1 in 50 (2%).

•

The data is not regularly reviewed, documented, or systematically reported as a KPI.

•

The data does not cover the full resource estimation dataset.

•

Reverse circulation sampling of bauxite remains a significant risk in wet conditions (whether due to groundwater, or rain).

Alcoa discontinued the routine collection of Field Duplicates in January 2018.

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9.5.3.5

Sample To Extinction (STE) samples

In September 2018 an alternative procedure, termed Sample To Extinction (STE), was introduced. This involves taking the normal 0.5 m drill sample (referred to as the Parent) and collecting all the residue from that drilled interval (i. e. the riffle split reject, and previously any material left in the sampling cup). This residue is collected once per shift from each rig under supervision by the geologist. The residue is pulverized and homogenized, then two equal splits (referred to as the Daughters) are assayed.

Studies in 2016 (112 Parent-Daughter sets, reported by SRK 2021a) and 2018 (63 Parent-Daughters, reported by Barnes 2018b) showed good repeatability for the residue pulp repeats (i.e. between the Daughters) indicating acceptable pulverizing and correct splitting of the residue offsite. However generally poor repeatability was reported between the residue results (the average of the Daughters) and the normal drill sample (the Parent), with a suggestion of bias for some analytes.

This demonstrated that perhaps the splitting at the drill rig was incorrect, and also illustrated the sampling principle that pulverizing (reducing the particle size) before splitting will always reduce the error. On the basis of these studies and external review, modifications to the splitting procedure at the rig were carried out.

In 2020, Alcoa refined the STE sampling procedure to now collect one sample per shift from each drill rig and assay three Daughters after pulverizing and splitting. The 2020 STE dataset examined by SLR contained results for 745 intervals tested between February 2019 and June 2020. After eliminating some blank values for some analytes, a total of 678 intervals remained which all had valid values for the Parent and three Daughters. SLR has used this data set to prepare bivariate statistics, scatter plots and precision plots.

Comparisons were carried out for the analytes AL, SI, FE and ST between:

•

The average of the Daughters vs the Parent

•

Daughter 1 vs the Parent

•

Daughter 2 vs Daughter 1

Examples are provided in Figure 8‑11 for AL and Figure 8‑12 for SI. Precisions and means are summarized in Table 8‑5 for all analytes.

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Figure 8‑11: Precision of STE Parent AL to Average of Daughters (top) and to Daughter 1 (bottom) (SLR, 2021)

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Figure 8‑12: Precision of STE Parent SI to Average of Daughters (top) and to Daughter 1 (bottom) (SLR, 2021)

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Table 8‑5: Summary of precisions and means for 678 STE tests (November 2020)


Analyte	Original	Duplicate	Precision (± %)	90th Percentile (HARD %)	Mean (% grade)	Bias (% grade)
AL	Parent	Daughter Ave	14.6	7.2	26.9	-0.31
	Parent	Daughter 1	17.2	7.9	26.9	-0.35
	Daughter 1	Daughter 2	16.8	7.2	27.0	0.14
SI	Parent	Daughter Average	13.7	14.7	3.0	0.04
	Parent	Daughter 1	15.1	16.0	3.0	0.05
	Daughter 1	Daughter 2	14.6	13.5	3.0	-0.02
FE	Parent	Daughter Average	17.6	13.2	20.7	0.06
	Parent	Daughter 1	20.1	15.8	20.7	0.06
	Daughter 1	Daughter 2	19.1	16.5	20.7	-0.03
ST	Parent	Daughter Average	14.4	12.6	23.7	0.23
	Parent	Daughter 1	17.5	15.9	23.6	0.33
	Daughter 2	Daughter 1	18.3	16.9	23.6	-0.22

Notes:

Precision is based on the CV of the HARD statistic at a confidence interval of 68%

90^th percentile is based on the ranked HARD statistic

Mean is the mean of all pairs

Bias is difference in the Means of Original and Duplicate sets, negative if Original is lower.

There is a lot of information that can be drawn from the analysis presented in Table 8‑5:

•

The Precision between Daughter 1 and Daughter 2 defines the repeatability that can be expected after pulverizing the whole of the retained residue from the drill rig and splitting it under controlled laboratory conditions. For all 4 analytes the results are consistent, and the repeatability is only moderate (Precisions between 15 and 25%). This indicates that the particle size generated during drill sampling (refer to Figure 7‑4), and the mass of sample collected, are not limiting factors on the sampling quality.

•

The Precision between the Average Of Daughters and the Parent is only marginally better in all cases than that between the Parent and Daughter 1.

•

The split taken at the drill rig (Parent, taken by splitting down to 150 g) is as good a representation of the drill interval grade as collecting the whole of the residue and carrying out pulverizing, homogenization and splitting.

•

Improvement on the Field Duplicate practice has resulted from improved splitting at the drill rig and collection of the Duplicate (in this case the STE residue) under observed conditions by the geologist.

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9.5.3.6

Pulp Repeats

The frequency of Pulp Repeats generated by the Bella LIMS system for FTIR is 1%. These pulp repeats are actually the REF samples used for monitoring the quality of the FTIR assays. As the FTIR assays are adjusted to match the REF assays (using a ‘broken stick’ curve adjustment to remove bias and maintain precision, see Figure 8‑13) it is expected that there should be minimal bias between REF and FTIR corrected results (FTIR_corr). However, the repeatability between the two methods is an important attribute of the quality of the assay results used for Mineral Resource estimation, Mineral Reserves for mine planning, and mining grade control.

The REF samples are considered to serve the same purpose as pulp repeats in defining the repeatability of the assays.

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Figure 8‑13: Example of the methodology used for broken stick correction of the FTIR results (from Franklin, 2019)

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Figure 8‑14: Precision of REF vs Corrected FTIR for AL and SI (SLR, 2021)

Table 8‑6: Summary of precisions and means for REF vs FTIR (final corrected result)


Analyte	Pairs	Precision (± %)	90th Percentile (HARD %)	Mean	Bias	Min	Max
AL (REF vs FTIR corr.)	4376	12.5	7.8	25.2	0.06	0.0	61.2
AL (REF vs FTIR corr.)	3473	4.0	4.8	29.4	0.04	15.0	61.2
SI (REF vs FTIR corr.)	4616	10.2	10.7	4.7	-0.08	0.0	41.0
SI (REF vs FTIR corr.)	2520	7.8	9.0	1.8	0.05	0.1	5.0
FE (REF vs FTIR corr.)	4574	15.8	16.2	17.9	0.03	0.0	67.0
FE (REF vs FTIR corr.)	2555	8.7	10.2	14.5	-0.03	5.0	30.0
ST (REF vs FTIR corr.)	4453	12.6	11.0	30.0	-0.12	0.0	92.4
ST (REF vs FTIR corr.)	2865	13.4	13.5	17.2	0.00	0.5	40.0
AT (REF vs FTIR corr.)	4755	4.9	5.0	32.3	0.01	0.0	62.5
AT (REF vs FTIR corr.)	2675	2.8	3.2	37.7	0.13	30.0	50.0
OX (REF vs FTIR corr.)	4441	21.9	22.1	1.1	0.00	0.0	9.0
OX (REF vs FTIR corr.)	2324	10.5	12.5	1.5	0.00	0.5	5.0
BO (REF vs FTIR corr.)	411	50.3	86.4	0.6	0.20	0.01	6.0
BO (REF vs FTIR corr.)	344	45.0	78.9	0.39	0.23	0.02	2.0

Notes:

Datasets trimmed to within Min and Max values are in blue font

Precision is based on the CV of the HARD statistic at a confidence interval of 68%

90^th percentile is based on the ranked HARD statistic

Mean is the mean of all pairs (as % grade)

Bias is difference in the Means of Original and Duplicate sets, negative if Original is lower (as % grade)

Min and Max (as % grade) indicate the range of the data used and is relevant to the trimmed statistics in blue font.

The repeatability (precision) and accuracy (bias) bivariate statistics summarized in Table 8‑6 for this data set show:

•

There is no evidence of bias, except possibly for BO (boehmite) which is masked by very poor repeatability (see scatter plot) in Figure 8‑15. Note that the BO FTIR assays are Raw rather than corrected by the Method Set algorithm, evidently because the FTIR data provides only an indication of the boehmite mineralogy when calibrated to the XRD results. This is expected.

•

Precision is excellent (less than 5%) for AT (Total Al₂O₃)

•

Precision is good (between 5 and 15%) for AL, SI and moderate (15 to 25%) for FE and OX

•

Precision improves significantly in the range of grades around the bauxite ore grade (bounded by the trimming limits in blue font in Table 8‑6) except for SI.

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Based on the datasets selected for examination randomly (i.e. without prior knowledge of the sampled areas, Method Sets, Priority Codes, or other differences), it is apparent that correcting the FTIR results using the REF assays obtained by microwave digestion (with XRF or ICP finish) produces results that are sufficiently unbiased and repeatable for the purpose of Mineral Resource estimation, except for BO (which is not reported in the Mineral Resource).

Figure 8‑15: Poor precision of REF vs RAW FTIR for BO (SLR, 2021)

9.5.3.7

Pulp Re-Assay Programs

In 2018, Alcoa commenced using FTIR to re-assay batches of approximately 70,000 results that had been previously assayed using the MD – ICP REF method for AL, SI and FE. A number of packages and their interpretations were provided and SLR evaluated the data for P159 (Myara North, March 2019) as shown in Table 8‑7 and Figure 8‑16, and for P163 (Larego, June 2019) as shown in Table 8‑8, with results for trimmed data in Table 8‑9 and Figure 8‑17.

Table 8‑7: Summary of pulp repeats for Myara North (P159): MD-ICP (Original) vs New FTIR


Analyte	Pairs	Precision (± %)	90th Percentile (HARD %)	Mean	Bias	Min	Max
AL	68,295	19.0	13.66	26.7	1.02	0.10	65.0
SI	68,295	24.0	29.3	2.6	-0.04	0.10	35.5

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FE	68,295	37.3	44.7	15.3	0.33	0.25	67.5

Table 8‑8: Summary of pulp repeats for Larego (P163): MD-ICP (Original) vs New FTIR


Analyte	Pairs	Precision (± %)	90th Percentile (HARD %)	Mean	Bias	Min	Max
AL	40,238	26.9	23.2	26.7	-0.75	0.10	65.8
SI	26,493	21.7	23.6	3.3	-0.36	0.3	33.2
FE	40,233	30.1	32.38	17.2	1.32	0.25	98.1

Table 8‑9: Summary of pulp repeats for Larego (P163) – trimmed: MD-ICP (Original) vs New FTIR


Analyte	Pairs	Precision (± %)	90th Percentile (HARD %)	Mean	Bias	Min	Max
AL	13,071	7.1	8.2	32.4	-0.12	26.0	39.0
SI	20,783	20.9	24.2	1.35	-0.04	0.3	5.0
FE	29,309	18.3	20.0	19.6	1.10	5.0	50.0

Notes for Table 8‑7, Table 8‑8 and Table 8‑9:

Precision is based on the CV of the HARD statistic at a confidence interval of 68%

90^th percentile is based on the ranked HARD statistic

Mean is the mean of all pairs (as % grade)

Bias is difference in the Means of the paired data, negative if the FTIR assay is lower (as % grade)

Min and Max (as % grade) indicate the range of the data used, with trimmed limits in blue font.

Results are consistent with previous evaluations by SRK (2021a) and indicate that overall repeatability of the re-assaying is only moderate for AL and SI and poor for FE, for both very large data sets. However, it is apparent that there are artefacts and errors in the original MD-ICP data.

The large data sets obscure the scatter and outliers. Some systematic errors are also apparent on the plots. For SI assays, at the limit of detection of 0.1 for FTIR and 0.2 for MD this results in many pairs with a HARD statistic of 33.33% (see SI percentile graph for P159 Myara North, Figure 8‑16). Similarly, for SI the MD data has an upper limit of 22% and the FE data has an upper limit of 95% whereas the FTIR assays can be much higher. Such data errors seem to have slipped through Alcoa’s data cleansing procedures for these repeat batches and can impact on the mean and bias estimates.

Trimming the P163 data set to limits approximating ore feed grades (with the trimmed limits shown in blue font in Table 8‑9) significantly improves the precision and reduces the bias for AL. There is less improvement for SI and FE.

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Figure 8‑16: P159 Myara North pulp re-assaying of old MD vs new FTIR for AL and SI. Note artefacts in SI plots, which can be removed by trimming (SLR, 2021)

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Figure 8‑17: P163 Larego pulp re-assaying of old MD vs new FTIR for AL and SI (trimmed) (SLR, 2021)

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9.5.3.8

Stockpile Feed and Sampling

Refinery feed grade is monitored at Huntly and Willowdale using material collected at the Pinjarra and Wagerup sample plants. At each operation, the sample plants are located at the refinery end of the overland conveyors, just prior to the stockpile stackers.

The stockpile area at the Pinjarra refinery is fed by two conveyor belts (SP-171 and SP-271) that derive their ore from the same crusher (currently at Myara). Prior to the ore being combined from the belts and fed to the stockpile area, it passes through a sampling tower that alternatively takes a primary cut from each belt, dries, crushes, subsamples and combines them into two parallel samples for 12 hour shifts.

The repeatability of the ore grades can be determined by comparing these paired samples (Figure 8‑18 for AL and SI, Table 8‑10 summarising results for all analytes).

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Figure 8‑18: Precision of paired Stockpile Belt samples for AL and SI (SLR, 2021)

Table 8‑10: Summary of Stockpile Belt paired samples for Myara North in 2018: 292 pairs for SP-271 vs SP-171


Analyte	Precision	90th Percentile	Mean	Bias	Min	Max
AL	2.0	2.3	32.95	-0.13	28.16	37.42
SI	9.3	10.2	1.19	0.03	0.54	4.09
FE	6.3	7.0	17.15	-0.06	9.90	27.69
AT	1.6	1.8	38.72	-0.08	34.28	43.48
ST	5.6	6.5	21.10	0.24	13.25	34.60
SO	4.3	4.9	2.88	-0.03	1.83	4.14
OX	7.2	7.9	1.96	0.00	1.09	3.37
BO	37.2	43.5	0.22	0.00	0.01	1.47

Notes:

Precision is based on the CV of the HARD statistic at a confidence interval of 68%

90^th percentile is based on the ranked HARD statistic

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Mean is the mean of all pairs (as % grade)

Bias is difference in the Means of Original and Duplicate sets, negative if Original (SP-171) is lower (as % grade)

Min and Max (as % grade) indicate the range of the data, in this case the range of ore grades going to the stockpiles.

Precision demonstrated in Table 8‑10 is excellent for AL, AT, ST and SO. Precision is good for SI, FE and OX but poor for BO. The high quality of the repeatability results is surprising and attests to:

•

The quality of the REF assays performed

•

The sample preparation in the Pinjarra Laboratory of the 12 hourly shift samples

•

The homogenization and blending performance of the mining operation, despite the large particle size of material on the twin belts.

The lack of any significant bias attests to the performance and reliability of the sampling tower in taking a primary cut and reducing it correctly, despite various design flaws noted for some of the sampling towers during independent reviews since the late 1980s (Gy, 1984; Rennick et al, 1992; Knight, 2016; Lyman, 2017; Holmes, 2018).

The good performance for all analytes except BO indicates that the low grades of BO may be near detection limits (defined as where the precision approaches 100%).

Table 8‑10 also provides a good indication of the average grades of ore and the expected range (minimum to maximum) for the ore fed during the period covered by the data set. Arguably, all precision data previously presented could be trimmed to such ranges and would demonstrate improved precision (e.g. as shown by the results in blue font in Table 8‑6).

9.5.4

QP Opinion

It is the SLR QPs opinion that the large data sets collected over a long timeframe, the satisfactory mine production shown by reconciliation results (see 11.12), and the QC data sets examined, all provide sufficient confidence in the available data for resource estimation.

Specifically:

•

Appropriate internal reference material (standards), wet chemical certified reference materials, and blanks are monitored.

•

The paired data from stockpile belts SP-171 and SP-271 indicates that the REF assaying method, and the sampling tower, have excellent repeatability and the ore grades delivered to the Pinjarra stockpiles from Myara North show good homogeneity after crushing and prior to stockpile blending.

•

The programs of extensive re-assaying of pulps provide evidence that the procedures have been maintained and are sound over a long period.

•

The REF- FTIR data provides confidence that the FTIR assaying technique, a rapid spectral method, is sound when calibrated and validated with the REF data.

•

The comprehensive monitoring of REF data both internally and through umpire assays is appropriate and results are reasonable.

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•

The STE method is a reasonable alternative to Field Duplicates and indicates to SLR that the drill rig splitting is appropriate (unbiased, and producing moderate precisions of less than 20%).

•

The available twinned hole data indicated poor repeatability (as expected, due to geological variability and perhaps sample splitting) which obscures any analysis of possible bias.

In the opinion of the SLR QP, the QA/QC of sample preparation and assaying is adequate and the assay results are suitable for use in Mineral Resource estimation.

It is the opinion of the SLR QP from the studies on FTIR repeatability discussed above that the overall precision and accuracy of the FTIR assaying is acceptable.

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10.0	Data Verification

10.1	Data structures

Wherever possible the transfer of geological, sampling and assaying data is now carried out digitally.

The use of rugged field tablets was introduced after an external review (Snowden, 2015). The data recorded at the drill rig is uploaded daily via WiFi for validation prior to importing into the acQuire database. This allows the data to be captured, checked, approved, and then loaded without any further manual keystroke entry.

The sample preparation and assaying data are all recorded at the Bella facility (see Figure 8‑3) allowing all aspects of the sample preparation to be tracked and transferred to KWI through direct connection to their Laboratory Information Management System (LIMS). After calibration, validation and checking of the FTIR and REF assays they are transferred digitally to the acQuire database.

Within the database, scripts are run to prioritise the results and to define the BEST value for each analyte (e.g. AL_BEST, SI_BEST, etc). The downhole accumulations of all grades are calculated, and the base of mineralization is determined. Other values are also calculated such as the Density using a regression equation (see Section 11.8.5).

An events table is used to change the status of each hole at all stages as it progresses through the validation process from designed, to drilled, to despatched, to lab pending, to validated.

The various downhole geological features (LithCode, Seam, Geol Floor, etc) are all verified spatially, validated by geologists using the vertical position and assays (e.g. Figure 7‑7), and where appropriate metadata (e.g. Status Flag) is added to record the basis of the interpretation.

The required modelling files are exported from the acQuire database by the geostatisticians using queries. The final Mineral Resource models are then imported into the over-arching ArcMap environment for mine planning, and integration with the environmental and other planning protocols.

Figure 9‑1: Visual display of hole status (logged and assayed) for hole G39150224 in Serpentine (Alcoa, 2021)

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10.2	Data verification measures

The SLR QP interrogated the data extracted from the acQuire database for two areas (Serpentine and Millars). For these two areas the count of records in each Table is summarized in Table 11‑2.

Table 9‑1: Count of records by database Table for two database extracts


Data type	Table	Serpentine	Millars
Collars	tblass	6,362	8,298
Surveys	tblsur	6,362	8,298
Assays	tblass	59,622	70,905
REF Assays	tblassrefs	611	711
Lithology	tblgeoLithology	69,564	82,762
Geology Floor	tblgeoGeolFloor	69,561	82,761
Seam	tblgeoSeam	69,564	82,762

Extensive checks were run to validate the integrity. These included searching for duplicate records, downhole gaps¸ interval overlaps, missing collar or survey records, etc.

The following observations were made:

•

As expected the Validation Tables ensure that there are no anomalous codes.

•

Checks for assay closure (adding all assays to 100%) are done by Alcoa when the assay data is prepared for resource estimation. The availability of total oxide assays (e.g. AT and ST) has progressively increased over time.

•

In a few cases (156 for Serpentine, drilled from October 2019 to December 2019, and 114 for Millars) there were blank values for LithCode in the table geoLithology at the top of the hole, followed by a zero-length interval (e.g. From 1.2 m and To 1.2 m) with a valid LithCode. This is due to the practice of not sampling the overburden but instead discarding it, creating in some cases a short interval with no assay or LithCode. This type of database error is usually picked up by a validation check looking for zero length drill segments. In this deposit, because the geological logging is expected to follow a vertical sequence (which is used for some of the interpretation scripts), such zero length intervals are not uncommon to allow for pinching and swelling of some horizons.

Some calculation and range checks were run that highlighted gaps or anomalies in the scripts used to validate that data before resource estimation:

•

There are 19 records with ST_BEST values greater than 100% in Serpentine and 2 in Millars. Such values should be investigated, trimmed and flagged.

•

There are a number of records (107 for Serpentine and 165 for Millars) where AL (available alumina) is greater than AT (total alumina). There are also records (1,273 for Serpentine and 2,029 for Millars) where SI (reactive silica) is greater than ST (total silica). These should be further investigated, flagged in the database, and future instances flagged during data loading so that

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when such results (infrequently) occur there is recognition during the data loading that this is due to FTIR assays outside the normal calibration range, rather than due to sample mix-up or contamination.

•

Checks on the regression calculation for density were run on the Serpentine database. There were 1,187 records not flagged as Seam=CAP, that had density values ranging from 2.04 to 2.28. These were either 20% or 40% CAP and had a density value reflecting the length weighted average of the two domains assigned. Of the total 6,399 records with valid seam and iron data, SLR found that 5,566 (87%) were within ±0.1 of the database density value. The remaining 833 records with Seam=CAP and an FE_BEST assay, were either 60% or 80% CAP and had a density value reflecting the length weighted average of the two domains assigned.

10.3	QP Opinion

The database extracts that were provided proved very robust to scrutiny, save for a small number of anomalies noted, none of which are considered material in view of the vast number of drill holes, assays and other records.

The SLR QP is of the opinion that the database is adequate and the data is appropriate for the purpose of Mineral Resource estimation.

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11.0	Mineral Processing and Metallurgical Testing

Mineral processing and metallurgical test work samples representing the Darling Range operations are not available; however, this is an operating mine and consistent operating data demonstrates that the ore is directly transported to the refineries following size reduction. SLR understands that these operating data represent all material mined for ten years and sourced from four mining regions and as such represent the various types and styles of mineralization within the Darling Range operations.

It is important to note that there is no upgrading involved in the processing and therefore the processing recovery can be considered above 99% allowing for any losses in production.

The operating data between 2010 to 2020 indicates that the product from the Darling Range operations consisted of an average Al₂O₃ grade of 33% and average SiO₂ grade of 20%. It is important to note that higher grades of reactive SiO₂ is potentially deleterious but that remained below 1.2% throughout the 10 years of operation. SLR understands that according to the mine plan the Total SiO₂ content on an annual average basis remains below 20%, and that reactive SiO₂, on the same basis, remains at or below 1.25% for the next 10 years. This means there is no evidence of any deleterious elements present in the Darling Range ore within the next 10 years of production.

A summary of the product grades from the Darling Range operations are shown in Table 10‑1, Table 10‑2 and Table 10‑3.

Table 10‑1: Product grades of Darling Range Operation (Willowdale – Wagerup refinery feed)

Year	Moisture (%)	LOI (%)	Total Al₂O₃ (%)	Total SiO₂ (%)	Fe₂O₃ (%)	TiO₂ (%)	A.Al₂O₃ (%)	R.SiO₂ (%)
2010	7.959	22.34	38.10	21.76	17.49	1.431	32.81	1.134
2011	7.930	20.89	40.57	22.28	17.64	1.466	32.75	1.141
2012	7.990	21.02	38.13	21.12	18.06	1.577	32.96	1.164
2013	7.745	21.15	36.80	18.57	19.48	1.607	32.72	1.209
2014	7.853	21.24	37.21	18.09	19.34	1.624	33.10	1.170
2015	7.484	21.48	37.01	18.01	19.03	1.719	33.16	1.112
2016	7.816	21.63	37.56	16.73	20.63	1.746	33.06	1.139
2017	7.817	21.75	37.93	16.01	21.37	1.825	33.03	1.103
2018	7.952	21.64	38.29	15.89	21.34	1.880	33.02	1.131
2019	7.611	21.28	37.33	16.76	21.34	1.851	32.29	1.153
2020	7.835	21.50	37.40	14.12	23.25	2.098	32.45	1.074

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Table 10‑2: Product grades of Darling Range operations (Huntly–Pinjarra refinery feed)

Year	Moisture (%)	LOI (%)	Total Al₂O₃ (%)	Total SiO₂ (%)	Fe₂O₃ (%)	TiO₂ (%)	A.Al₂O₃ (%)	R.SiO₂ (%)
Year	Moisture (%)	LOI (%)	Total Al₂O₃ (%)	Total SiO₂ (%)	Fe₂O₃ (%)	TiO₂ (%)	A.Al₂O₃ (%)	R.SiO₂ (%)
2010	7.4	20.8	38.6	20.8	17.4	1.34	33.1	1.05
2011	7.8	21.0	38.8	20.0	18.0	1.41	33.0	1.04
2012	8.2	21.4	39.4	20.2	17.1	1.37	33.6	1.13
2013	8.1	21.5	39.8	19.5	17.1	1.35	33.9	1.12
2014	8.2	21.5	39.6	18.6	17.7	1.45	33.8	1.16
2015	8.0	21.6	39.3	19.5	17.3	1.41	33.8	1.08
2016	8.2	21.4	39.2	20.3	17.0	1.38	33.8	1.13
2017	8.3	21.3	39.3	19.6	17.5	1.42	33.9	1.11
2018	8.3	21.4	39.1	19.5	17.6	1.42	33.7	1.07
2019	8.1	21.3	38.9	20.1	17.2	1.38	33.5	1.12
2020	8.4	21.4	39.1	18.4	18.6	1.52	33.5	1.20

Table 10‑3: Product grades of Darling Range operations (Huntly– Kwinana refinery feed)

Year	Moisture (%)	LOI (%)	Total Al₂O_{3 (%)}	Total SiO_{2 (%)}	Fe₂O₃ (%)	TiO₂ (%)	A.Al₂O₃ (%)	R.SiO₂ (%)
Year	Moisture (%)	LOI (%)	Total Al₂O_{3 (%)}	Total SiO_{2 (%)}	Fe₂O₃ (%)	TiO₂ (%)	A.Al₂O₃ (%)	R.SiO₂ (%)
2006	7.8	21.7	39.3	18.7	18.0	1.37	33.9	1.10
2007	8.0	21.6	39.2	19.5	17.6	1.33	33.7	1.11
2008	7.9	21.3	39.1	20.1	17.3	1.34	33.8	1.09
2009	7.8	21.3	39.0	20.7	17.3	1.29	33.5	1.02
2010	7.5	21.4	38.6	20.8	17.4	1.26	33.1	1.04
2011	7.6	21.3	38.7	20.1	18.2	1.30	32.8	1.03
2012	8.2	21.5	39.4	20.3	17.0	1.25	33.5	1.13
2013	8.1	21.8	39.8	19.5	17.1	1.26	33.9	1.11
2014	8.2	22.0	39.6	18.8	17.7	1.37	33.7	1.17
2015	8.0	22.0	39.4	19.7	17.2	1.31	33.8	1.08
2016	8.2	21.7	39.1	21.3	16.1	1.32	33.8	1.03
2017	8.3	22.2	38.9	20.6	16.5	1.34	33.8	1.03
2018	8.3	22.1	38.6	20.8	16.7	1.33	33.9	1.05

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Year	Moisture (%)	LOI (%)	Total Al₂O_{3 (%)}	Total SiO_{2 (%)}	Fe₂O₃ (%)	TiO₂ (%)	A.Al₂O₃ (%)	R.SiO₂ (%)

2019	8.0	21.8	38.9	21.2	16.4	1.32	33.5	1.12
2020	8.4	21.7	39.1	19.8	17.6	1.44	33.5	1.16

11.1	QP opinion

SLR is of the opinion that the Darling Range operation demonstrated that ore can be effectively crushed and supplied to a refinery for further upgrading to produce Alumina. The historical operational data confirmed that the ore consistently met refinery specifications without any deleterious elements. Based on this, and the additional information about the mine plan provided by Alcoa, it is reasonable to assume that the ore from Darling Range can be economically processed for the next 10 years.

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12.0	Mineral Resource Estimates

12.1

Summary

The Darling Range resource inventory comprises over 13,000 resource blocks with a combined area of approximately 10,870 ha averaging 50 kt. The lateritic bauxites occur as surficial coverings of limited thickness, typically between 4 m to 8 m, but with significant lateral extent. Historically, resource estimation was by 2D plan-polygonal methods (Polygonal) referred to by Alcoa informally as the ResTag procedure. More recently, resource estimation by Alcoa has evolved to include gridded seam (GSM) and 3D block (3DBM) models using geostatistical techniques. Mineral Resource estimates based on GSM and 3DBM models (and some Polygonal models) consider practical mining constraints.

The delineation of Mineral Resources using 3D methods has focused on well drilled areas that fall within the 10-year mine plan and comprise approximately 30% of the Mineral Resources in 37 3DBM models. GSM models were typically constructed in areas with 15 m spaced drilling. Approximately half of the Mineral Resources are based on Polygonal (ResTag) estimates which are mostly located in areas of wider-spaced (30 m and 60 m) drilling and are of lower confidence. All new resource updates employ the 3DBM methods irrespective of drill hole spacing.

Mineral Resource estimation was carried out by Alcoa and resources are defined for 92 sheets in 70 mining regions. There are 13,467 discrete zones of mineralization that comprise the resource, each split vertically into 4 domains for which 11 elements were estimated. SLR carried out audits on representative models selected in conjunction with Alcoa and comprising:

•

Models to be mined in the short to medium term (less than 5 years)

•

Models with significant amounts of resource material

•

Models representing the three estimation methods used by Alcoa.

The models audited were:

•

ResTag estimation method: Teesdale

•

GSM estimation method: Larego (F54 and F55)

•

3DBM estimation method: Serpentine (R25) and Millars (R22).

The audit process by SLR comprised examination of the procedures used by Alcoa, independent review and discussion with staff, normal validation checks (e.g. statistics, swath plots, visual examination, change of support analysis and generation of grade-tonnage curves). The two 3DBM models were examined in detail. The other models were examined and interrogated to ensure that the documented procedures were followed and that results were consistent with SLR expectations based on the data inputs.

The process used by Alcoa involves an integrated approach to data collection, bauxite delineation, and production planning aimed at the provision of feedstock that meets the requirements of the local alumina refineries.

For all 3 estimation methods drill holes were flagged with geological units using multi-pass geochemical scripts that included thickness constraints. The GSM flagging process incorporated some additional mining constraints. Geological interpretations in both 2D and 3D were constructed with the flagged drill hole composite data, which constrain the spatial estimation of bauxite mineralization. Subsequent to block

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grade estimation, mining constraints are applied to the 3DBM models to restrict Mineral Resources to areas of potentially economic bauxite mineralization.

AL, SI, FE, ST, PT, OX, EO, CO, and SU are estimated for all models, but only AL and SI are reported for the Mineral Resource. GSM uses inverse distance weighting methods to assign grades to the bauxite profile, and 3DBMs rely on ordinary kriging block grade estimates. Validation methods differ slightly for the different model types, but all models are reported by Alcoa to validate well against the input drill hole data.

Mineral Resources have been classified in accordance with the definitions for Mineral Resources in S-K 1300, which are consistent with Australasian JORC Code (2012) and Canadian NI 43-101 (2014) definitions, and are determined primarily on drill hole spacing. Models constructed primarily with pre-2010 drill holes are downgraded as this information is considered to be of lower confidence.

Mineral Resource estimates exclusive of Mineral Reserves are shown in Table 11‑1, and include a 5% reduction factor in tonnage, based on the results of annual reconciliations (see discussion on density in Section 11.13).

Table 11‑1: Summary of Mineral Resources exclusive of Mineral Reserves – 31^st December 2021


Category	Tonnage (M dmt)	A.Al₂O₃ (%)	R.SiO₂ (%)
Measured	48.0	32.9	1.11
Indicated	34.8	31.9	1.12
Total Measured + Indicated	82.8	32.5	1.11
Inferred	320	33	1.2

Notes:

The definitions for Mineral Resources in S-K 1300 were followed, which are consistent with JORC (2012) definitions

Mineral Resources are 100% attributable to AWAC

Mineral Resources are estimated at a geological cut-off grade, which generally approximates to nominal cut-off grades of 27.5% A.Al₂O₃ with less than 3.5% R.SiO₂. Locally the cut-off grade may vary, dependent on operating costs and ore quality for blending. The target grade for mine planning is 32.7% available aluminum oxide (A.Al₂O₃) and 1.0% reactive silica (R.SiO₂)

Mineral Resources have been estimated using a three-year trailing average of arms-length sales of bauxite from Darling Range. The price that constrains the estimate for optimisation was discounted to exclude export logistics costs, i.e. the base price was USD24/t, and the discounted price was USD16/t.

A minimum total mining thickness of 1.5 m was used

In situ dry bulk density is variable and is defined for each block in the Mineral Resource model

A global downwards adjustment of tonnes by 5% is made to account for density differences based on historic mining performance

Mineral Resources are reported exclusive of Mineral Reserves

The reference point for the Mineral Resource is the in situ predicted dry tonnage and grade of material to be delivered to the refinery stockpile following the application of mining design parameters

10.

Metallurgical recovery has not been directly considered in the estimation of Mineral Resources as the Darling Range operations do not include a conventional processing plant, only crushing as described in Section 14.0. The metallurgical recovery of the three refineries (Kwinana, Pinjarra and Wagerup) are beyond the boundaries of the mining operations being the subject of the TRS.

11.

Numbers may not add due to rounding.

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12.2	Resource Database

12.2.1

Drill Hole Data

Drill hole collar, survey, and assay data are exported from the acQuire database for resource estimation.

Data exports from acQuire currently utilize Python scripts and the Spyder open-source plugin for validation and initial processing, including:

•

Assigning 999 as the Domain code where drill hole intervals lack AL, SI and Fe assays

•

Removing holes from the database if located greater than 7 m horizontally from the planned location

•

Identifying and removing duplicate or repeat holes based on a set of criteria

•

Resetting AL to AT where AL exceeds AT

•

Resetting SI to ST where SI exceeds ST

•

Calculating Assay Total = AT (AL if AT absent) + ST + BO + FE + SU + CO

•

Deleting assays for samples where the Assay Total is below 70% or greater than 100%.

The output is a set of CSV files for collar, survey, assay, and geology.

The validation checks have been implemented progressively over time as drill hole data for some project areas includes some samples where AL exceeds AT and SI exceeds ST.

Other than collar elevation adjustments, no further data transformations are applied prior to resource estimation.

12.2.2

Topographic data

Digital elevations models (DEMs) were generated from (in order of priority) drill collar survey data, LiDAR survey data, and Landgate satellite data. A 7.5 m by 7.5 m mesh is used for the DEMs. Drill hole collar elevations were registered to the DEM for resource estimation.

12.3	Geological Interpretation

12.3.1

Polygonal Models

For Polygonal resource estimates, grade-based ‘geological’ codes are assigned to drill hole intervals. These codes are used to define the top and bottom of the ‘bauxite’ horizon in each hole, which is then used to estimate the bauxite volumes and average grades within polygons.

The top of the bauxite usually coincides with the base of the overburden, as defined in the drillers’ logs. The base of the Bauxite Zone (termed the geological floor) is defined within the acQuire database using a multi-pass script that applies the following hierarchical set of rules to the sample grades:

Pass 1

•

Uphole search for two consecutive samples with individual AL values ≥27.0%

•

Record depth of the lower of the two samples

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•

Check that the cumulative AL at that depth is ≥27.5%

•

Check that the individual SI at that depth is ≤3.5%

•

Check that the cumulative SI at that depth is ≤3.0%

•

Check that the cumulative OX at that depth is ≤4 kg/t

•

Check that the sampled depth is ≥2.0 m, but less than hole depth (if equal, see pass 3)

•

If all criteria are met, set flag to “pass”, set geological floor depth to lower sample depth

•

Proceed to pass 2.

Pass 2

•

Uphole search for two consecutive samples with individual AL values ≥25.5%

•

Record depth of the lower of the two samples

•

Check that the cumulative AL at that depth is ≥27.5%

•

Check that the individual SI at that depth is ≤3.5%

•

Check that the cumulative SI at that depth is ≤3.0%

•

Check that the cumulative OX at that depth is ≤4 kg/t

•

Check that the sampled depth is ≥2.0 m, but less than hole depth (if equal, see Pass 3)

•

If all criteria are met, set flag to “pass”, set geological floor depth to lower sample depth

•

If any criteria fail, geological floor defined in Pass 1 is retained.

Pass 3

•

Uphole search for two consecutive samples with individual AL values ≥27.0%

•

Record depth of the lower of the two samples

•

Check that the cumulative AL at that depth is ≥27.5%

•

Check that the individual SI at that depth is ≤3.5%

•

Check that the cumulative SI at that depth is ≤3.0%

•

Check that the cumulative OX at that depth is ≤4 kg/t

•

Check that sampled depth = hole depth

•

If all criteria are met, set flag to “pass – open”, set geological floor depth to lower sample depth.

Pass 4

•

Uphole search for two consecutive samples with individual AL values ≥24.5%

•

Record depth of the lower of the two samples

•

Check that the cumulative AL at that depth is ≥25.0%

•

Check that the individual SI at that depth is ≤3.5%

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•

Check that the cumulative SI at that depth is ≤3.0%

•

Check that the cumulative OX at that depth is ≤4 kg/t

•

Check that the sampled depth is ≥2.0 m, but less than hole depth (if equal, see pass 3)

•

If all criteria are met, set flag to “marginal”, set geological floor depth to lower sample depth.

The application of these rules assigns a geological floor depth to each hole, along with a Pass, Pass-Open, Marginal, or Fail flag. Holes flagged as Marginal or Fail are inspected by Alcoa staff members, with manual adjustments applied if warranted. For areas infilled to 15 m spaced holes, the geological floor model is replaced by a mining floor model, which is discussed in the following section.

Results of geological floor flagging are used to subjectively define the lateral extents of the Mineral Resource. Outlines are manually interpreted by Alcoa geologists in ArcGIS or MineSight, and are guided by consistency in thickness, depth, and grade, minimum limits on the number of enclosed samples and the enclosed area, and local geomorphology. The polygons delineate separate areas that typically range in size from 10 ha to 100 ha, with most being around 30 ha. An example plan view is shown in Figure 11‑1.

Figure 11‑1: Plan View of Polygonal Approach (Pass = red, pass open = green, marginal = yellow, fail = blue) (Alcoa, 2022)

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12.3.2

Gridded Seam Models

GSM models are located in areas of 15 m spaced infill drilling and include practical mining constraints as part of the ‘geological’ interpretation used for resource models.

The base of overburden and the base of caprock is identified in each drill hole as 3D points and wireframed as surfaces. The geological bauxite zone floor, which is defined for the wider drill spacings used for Polygonal estimates, is replaced by a mining floor for GSMs. The mining floor is interpreted directly from the drill hole data presented on the 15 m spaced east-west cross sections, digitized in MineSight as strings, then linked to form wireframe surfaces.

The interpretation of the mining floor is a manual process performed by the site geologist, with the objective of achieving acceptable grades and practical mining outlines. The mining floors are defined using a set of guidelines instead of prescribed rules, including:

•

Nominal cut-off grades of ≥27.5% AL and ≤3.5% SI are used for mining floor definition;

•

If the SI grade in the sample immediately below the floor exceeds 5.0%, the floor is raized 0.5 m;

•

A minimum face height (distance from mining floor to the base of overburden) is targeted;

•

Face heights exceeding 4 m will require multiple cuts or bench mining;

•

The overburden to face height ratio should not exceed 1;

•

A maximum floor gradient of 1 in 7 is required between 15 m spaced holes (the gradient can be increased to 1 in 5 for second and third cuts);

•

Benching should be invoked where the gradient constraints cannot be maintained; and

•

The floor interpretations should be extended laterally into at least one of the surrounding waste holes.

The base of overburden and mining floor surfaces are used to flag the drill hole samples. For each drill hole, the samples located below the base of the overburden and above the mining floor are composited into a single interval, with composite grades length- and density-weighted. Additional drill hole composites are generated for second and third pass mining floors.

The composite data are examined in plan view, and polygons are digitized around the interpreted lateral extents of the mining zones using the following guidelines:

•

Nominal cut-off grades of ≥27.5% AL and ≤3.5% SI for lateral boundary definition

•

The boundary is positioned at least 15 m away from holes with SI grades exceeding 5%

•

Buffer zones are placed around environmental constraints, and around bedrock outcrop

•

Internal waste zones should contain at least three drill holes

•

Individual polygons should have an area of at least 1 ha

•

A width of at least 45 m should be retained for mining equipment movement.

The resulting polygons are divided into ‘mining’ blocks that each contain approximately 20 kt to 40 kt.

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12.3.3

3D Block Models

Similar to the Polygon and GSM interpretation approaches, a set of rules are used to assign initial domain codes to individual samples. These Domain codes are then modified in several subsequent passes that take into account the grades and coding of other intervals in the hole.

The initial script is used to assign a Domain code to each interval based on various combinations of major analyte threshold grades. A total of 6 main material type Domains (DOMAF) are defined, namely overburden (DOMAF=99), caprock waste (10), caprock bauxite (20), bauxite (30), low-grade bauxite (40), and clay (50). Each of these material types (apart from overburden) is divided into up to five grade-based sub-domains. Three subsequent coding passes are conducted that iteratively adjust the codes to combine the sub-domain into the 6 main Domains whilst ensuring that strict stratigraphic ordering is maintained. A further two passes are coded to assign Domain codes that denote whether the material is derived from granite or dolerite.

The base of each Domain is generated on a 7.5 m by 7.5 m grid using an automated modelling process. Where drill holes do not penetrate the full bauxite profile or where the Domain contact is not defined exactly due to missing assays a conditional simulation algorithm is used to estimate the Domain thickness from adjacent drill holes. The simulation algorithm employs a Matern variogram and selects the average of 10 simulations for the missing data point. The grid mesh is then wireframed in MineSight to provide 3D surfaces. The base of Domain 50 (Clay) is set at 10 m below the top of that Domain.

Figure 11‑2: Example Section showing Domain (DOMAF) and Wireframed Surfaces (SLR, 2022)

3:1 vertical to horizontal exaggeration

Potential dolerite dyke intervals are flagged for samples where FE exceeds 25% and ST is below 10%, and the entire hole is flagged as potential dolerite dyke if 3 or more samples are flagged in this manner. The interpretation of dolerite dykes is carried out manually using local orientation trends and may be based on one or more holes (see Figure 11‑3). Dolerite dykes are assumed to be vertical and are extended laterally half-way between drill holes. Dolerite dykes can represent up to 15% of material in some areas but unweathered material can generally be screened out in the pit or prior to crushing as oversize boulders. Dolerite dykes tend to be well defined only when drill hole spacings are reduced to 15 m by 15 m.

A lateral boundary is interpreted to constrain the resource model (see Figure 11‑3) and the 3D surfaces are extended where required. The lateral boundary, domain surfaces, and dolerite dyke interpretations are converted to wireframe solids.

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Figure 11‑3: Plan View of Bauxite Zone and Interpreted Dykes at Serpentine (SLR, 2022)

12.4	Statistical Checks

Statistical checks by Alcoa and independent reviewers are typically carried out by univariate statistical comparisons and histogram, grade trend, scatter, and cumulative log probability plots.

Univariate statistics by Domain are calculated pre- and post-compositing for validation, and for checks against the resulting resource models. For areas with multiple drilling campaigns carried out at significant time lags, SRK (2021a) previously noted that there were no material or unexpected differences between subsets of the dataset grouped by drilling period or drilling grid.

Histograms show that most analytes have distributions that are close to normal, as shown in Figure 11‑4 for AL. The exception being SI, which is moderately to strongly positively skewed, as shown in Figure 11‑5.

Marked grade trends with depth exist for most analytes but are consistent with the mineralization style and have been adequately accounted for by the geological interpretation and the use of unfolding methods during block grade estimation.

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Figure 11‑4: Histograms of AL by DOMAF at Serpentine (SRK, 2021)

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Figure 11‑5: Histograms of SI by DOMAF at Serpentine (SRK, 2021)

Figure 11‑6 plots SI versus ST for the clay zone at Serpentine. Note that reactive silica (SI) was greater than total silica (ST) for some composites (left-hand plot), and these relationships were carried through to the block model (right-hand plot). In the datasets reviewed, this issue was most common for SI in the clay zone, but there were also small numbers of bauxite zone samples with available alumina (AL) greater than total alumina (AT). This issue is not considered to be material for the Mineral Resource estimate, and adequate checks are now in place for future resource models.

Figure 11‑7 shows the relationship between AL and SI for the bauxite and clay zones at Serpentine. Note the progressive increase in SI as the bauxite profile changes with depth from Hardcap (20), through friable bauxite, and to Clay (50), which was supported by grade trend plots.

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Figure 11‑6: Scatterplots of SI versus ST for DOMAF 50 at Serpentine (SRK, 2021)

Figure 11‑7: Scatterplots of AL versus SI by Domain at Serpentine (SRK, 2021)

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12.5	Treatment of High-Grade Assays

High-grade caps for all analytes were applied to individual composites by Alcoa on a domain-by-domain basis following inspection of the data distribution. The SLR QP confirmed that high-grade caps were typically greater than the 99^th cumulative sample percentile, as shown by horizontal lines in the plots in Figure 11‑8.

No high-grade spatial restrictions were used by Alcoa in the resource estimation process.

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Figure 11‑8: Cumulative Log Probability Plots for Serpentine Composites

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12.6	Compositing

Drill holes were sampled at 0.5 m intervals in the bauxite zone below the base of the overburden, with a residual sometimes present at Domain contacts. The Polygon and GSM estimation approaches used the original drill hole data intervals. Prior to the interpretation of geological surfaces, holes used in the 3DBM resource estimates were composted to 0.5 m with residuals calculated to ensure their length was 0.25 m to 0.75 m.

Following the interpretation of geological surfaces, drill holes used for Polygonal and GSM resource models were composited to:

•

Polygonal – a single interval for samples located below the base of the overburden and above the geological floor.

•

GSM - a single interval for samples located below the base of the overburden and above the mining floor. Additional composites were generated in areas where second and third pass mining floors were identified.

All grade compositing for drill holes employs length-weighted linear averages.

12.7	Trend Analysis - Variography

Only some variogram analysis was carried out for Polygonal and GSM models as variogram parameters were not required to generate the resource models. Variogram analysis is routine for 3DBMs. Experimental variograms are calculated in unfolded space, with bauxite Domains 20, 30 and 40 unfolded to the 10/20 Domain contact and the clay Domain (50) unfolded to the 40/50 Domain contact.

Experimental variograms are calculated for AL, SI, ST, and FE for the bauxite zone, standardized to a sill of one, and modelled with 3-structure spherical models, as shown in Figure 11‑9. A single variogram model is selected that provides a best fit to these four variables. Variogram models tend to display nugget values of less than 20% and total ranges of several hundred meters, but 80% of the sill is generally reached within 100 m laterally. As expected, horizontal to vertical anisotropy ratios are high (typically exceeding 50:1), but there is little lateral anisotropy. Only minor differences in Huntly and Willowdale variogram models were noted by SRK (2021a). This good definition of continuity compared to the 15 m drill spacing is considered by SLR to be a benefit of the unfolding approach.

Independent variogram models for each bauxite domain and analyte are not used for grade estimation to enable correlations between analytes to be maintained during the change in support from drill hole samples to blocks, which is important for mine planning considerations.

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Figure 11‑9: AL, SI, FE, and ST Directional Variogram Models at Serpentine

12.8	Bulk Density

For Mineral Resource estimation purposes, density can be regarded as another analyte, and tests can be evaluated for repeatability (precision) and accuracy (bias). The determination of the metal content of a specified volume of ore is as sensitive to density as it is to grade, and this is certainly the case for gold mining with high value, low concentration assays. For bulk commodities there is usually much more emphasis on grade since product tonnages are measured by weightometer.

Alcoa does not routinely collect density data but relies on production records to define averages. This is due to the broad geological consistency of the ore zones and the local chemical and physical nature of the lateritized ore. Porosity and permeability in particular show high lateral and vertical variability, rendering repeatability of density test work meaningless. Even were large numbers of data points available (for example by developing a density algorithm from the FTIR assaying of every drill sample, and then modelling it) the resulting model would still need to be factored by the actual mining results for local porosity.

For 3DBM resource estimation, each drill hole bauxite composite is assigned a dry in situ bulk density (DIBD) value based on the logged material type and the FTIR iron grade using the regression equation defined below in Section 11.8.5.

The available density test work data is summarized as follows.

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12.8.1

1980 to 1992

Senini (1993) collated and reviewed all previous bauxite density data, including that by Sadleir done in 1986, and modified Sadleir’s algorithm used for computation of density from individual 0.5 m sample assays of Fe₂O₃. Results are summarized in Table 11‑2.

Table 11‑2: Summary of density test data (t/m³) from 1980 to 1992 (Senini, 1993)


Year	Source	Material	Count	Mean	Min	Max	Fe Mean	Regression On Fe₂O₃
Year	Source	Material	Count	Mean	Min	Max	Fe Mean	Slope	Intercept
1980	DOSCO	Hardcap	18	2.200	1.98	2.52	19.35	0.0089	2.032
1986	Sadleir (in Senini)	Hardcap	14	2.364	2.08	2.75	20.88	0.0092	2.172
1992	Senini	Hardcap	67	2.409	1.81	3.10	21.00	0.0103	2.192
1986	Sadleir (in Senini)	Friable	11	1.846	1.64	2.12	8.80	0.0015	1.830
1992	Senini	Friable	27	2.225	1.88	2.79	14.30	0.0045	2.289
1980 - 1992	reported above	Granitic	67	2.327	1.81	3.10	16.71
1980 - 1992	reported above	Doleritic	32	2.444	2.07	2.96	28.96

While the approach used has merit, there are some obvious challenges:

•

There are very few data points, unevenly distributed by material type and mining area

•

Methodologies for collecting and testing the samples varied (sand replacement method for Hardcap, driven cylinder for Friable, water displacement are all noted)

•

There is some lack of clarity on moisture, but it is assumed that the values are all in situ dry bulk density reported as t/m³.

The differences between Hardcap (caprock) and Friable (other material) and between granitic or doleritic derivation are however clear.

Senini (1993) concluded that the dry in situ bulk density (DIBD) should be estimated using a regression equation which is still used.

12.8.2

2013 to 2018 drill samples

Various further test programs have been attempted including collection of all material from drill samples (assuming the drill hole volume is constant) and then taking wet and dry weights and assaying for iron. There were 51 samples from 8 holes at Huntly and 93 samples from 24 holes at Willowdale. Scatter plots produced by SRK 2021a showed significant scatter of all available data for both Hardcap and Friable (other) material.

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12.8.3

2016 to 2017 pit samples

Alcoa collected 2 kg to 5 kg grab samples from 16 Huntly pits (76 samples) and 10 Willowdale pits (41 samples). Water immersion density testing was done by Bureau Veritas. The average of 2.01 t/m³ is significantly lower than that from the 2015 study of 2.23 t/m³. The drill samples did not account for porosity and voids, and were not adequately sealed.

FTIR assays for Fe2O3 were compared to sealed and unsealed density estimates and it was found that Senini’s regression equation better predicted the unsealed densities. Thus it appears that the current regression equation based on Fe₂O₃ assays overestimates the in situ dry tonnage.

12.8.4

2018 downhole density estimates

In December 2018 Alcoa contracted downhole geophysical measurements in 54 aircore holes drilled in the Larego area. The data from this study is still being evaluated and is not used for Mineral Resource estimation.

12.8.5

Density estimation

Ore grades range from 28 to 38% A.Al₂O₃ for paired belt sample data (see Section 8.5.3.8) whereas test work densities range from 1.5 t/m³ to 3.2 t/m³ but the data is sparse and unreliable.

For resource estimation, each 0.5 m drill hole sample is assigned a dry in situ bulk density (DIBD) value based on the logged material type and the FTIR iron grade, using Senini’s 1993 regression equation:

Hardcap (caprock)= 2.19 + 0.0103*Fe

Friable (other)= 2.00 (used for all non-Hardcap material)

If the sample is logged as comprising a mix of Hardcap and Friable, the assigned value for that 0.5 m interval represents a volume-weighted average. There is no differentiation between granitic and dolerite derived bauxite, due to the relatively small proportion of the latter (less than 15%).

In resource estimates prior to 2017 a moisture content of 9% was assumed and used to estimate wet tonnes. Since the implementation of 3D block modelling in 2018, densities are assigned after grade estimation, based on the regression equation and Fe grade of Hardcap, and using 2.0 t/m³ for all other material, weighted by the proportion of Hardcap or other material.

12.8.6

Reconciliation of density

Alcoa uses comparisons between the As Mined tonnages and the sampling tower weightometers to apply adjustment factors to mine design estimates, scheduling and stockpile planning. Such adjustments are not applied directly to the Mineral Resource estimate as they vary locally.

Reconciliation of Huntly and Willowdale mined production (see discussion on density in Section 11.13) indicates that the density estimates are biased, with the long-term average As Mined tonnages being approximately 5% higher than the actual production measured on calibrated weightometers.

12.8.7

Density conclusions

The density data is limited in coverage and there is significant uncertainty regarding the methodology used for some sampling programs. A simple regression algorithm is used to estimate the DIBD for Hardcap

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from the FTIR assays of Fe₂O₃. This does not account for voids or porosity, nor does it differentiate between Hardcap derived from granitic or doleritic material. All other material is assigned a density of 2.0. A constant moisture content of 9% is assumed for wet tonnages.

12.8.8

QP Opinion

12.9	Resource Models

12.9.1

Polygonal

For each drill hole contained within a polygon, the samples located below the base of the overburden and above the geological floor are composited into a single interval. The following quantities are assigned to each polygon:

•

Thickness = average length of contained composites

•

Grade = length-weighted average grade of contained composites (density weighting is not applied)

•

Density = average density of contained composites

•

Volume = Polygon area by Thickness

•

Tonnage = Volume by Density.

12.9.2

Gridded Seam Modelling

GSM employs 15 m by 15 m cells centered on the nominal drill hole locations. Separate seams are created for overburden, and for the interpreted Bauxite Zone (BXZ) between the overburden and the mining floor. BXZ is subdivided into separate seams where second and third mining cuts have been interpreted. Interpreted wireframe surfaces are used to assign a seam thickness to each cell (effectively the seam thickness of drill hole at the cell centroid).

Cell grade estimation used inverse distance weighting (IDW) techniques as follows:

•

Hard boundaries, with each seam cell only estimated using nearby composite drill hole data within the corresponding seam

•

IDW weighting factor of 1.2 for SI and 2 for all other variables

•

1 by 1 by 1 cell discretization

•

Isotropic search distance of 180 m

•

Minimum of 2 and maximum of 8 composites with a maximum of 2 per quadrant

Where drill holes are located at the centroid of cells the resulting cell grade estimates are essentially nearest neighbor estimates. In other words, the GSM outcomes are equivalent to 2D polygon estimates, with the usual constraint of that method, i.e. that the block variances are not smaller than the composite variances.

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The GSM is constrained to the interpreted lateral extents of the mining zones. For each mining zone the following attributes are determined:

•

Seam Thickness = average seam thickness of the contained GSM cells

•

Grade – weighted average grade of contained cells (density weighting is not applied)

•

Density = average density of contained cells

•

Volume = mining zone area by Seam Thickness

•

Tonnage = Volume by Density

12.9.3

3D Block Modelling

In 2019, Alcoa commenced preparing Mineral Resource estimates using 3DBM techniques, with the aim to progressively replace all Polygonal and GSM models. To date, Alcoa has prepared a total of thirty-seven 3DBM representing around 30% of the Mineral Resource.

This section describes the current 3DBM procedures, which have evolved over time, with some parts now automated or semi-automated. Changes in the 3DBM procedures have generally been minor and are not considered material to the resulting resource models.

Block models are initially generated:

•

using the ML1SA lease area grid

•

with an origin that ensures that the majority of the drill holes are located nearer to the block corners rather than the centroids

•

with a parent block size of 15 m by 15 m by 0.5 m and a sub-block size of 3 m by 3 m by 0.25 m (XYZ)

•

flagged with a Domain (DOMAF) code based on the domain surface interpretations.

Block grade estimation:

•

includes estimation of AL, SI, ST, FE, EO, PT, CO, SU, OX, BO, and AT

•

is done by ordinary kriging (OK) for parent blocks, with parent grade estimates assigned to all sub-blocks within the parent block

•

uses the same unfolding surfaces as used for variogram analysis

•

sets soft boundaries for bauxite Domains (DOMAF 20, 30, 40)

•

uses a 3-pass search strategy for bauxite Domains and only one pass for the clay zone (parameters listed in Table 11‑3), with:

the major and semi-major orientations in the unfolded horizontal plane

a minimum of 4 or 12 samples and a maximum of 27, with a maximum of 3 from any one drill hole. Thus, a minimum of 4 holes is required for Pass 3 and 2 holes for Passes 2 and 1

•

uses the same variogram for all analytes

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•

DIBD (density) is not estimated into individual parent and sub blocks, but is a post-estimation calculation based on the block domain compositions (see 11.8.5).

The OK estimation approach is designed to maintain correlations between analytes and assist in ensuring that estimation totals are consistent with the input drill hole data.

Table 11‑3: Ordinary Kriging search parameters

Domain	Pass	Search Distance (m)			Number of Samples
Domain	Pass	Major	Semi-major	Minor	Min	Max	Max Per Hole
20, 30, 40	3	300	300	50	4	27	3
	2	100	100	20	4	27	3
	1	55	55	20	12	27	3
50	1	300	300	50	4	27	3

A set of wireframe solids representing the mining outlines are generated using a similar grade accumulation and threshold approach to those used for the GSM model, as shown in Figure 11‑10. The sub-block model is then regularized to 15 m by 15 m by 0.5 m (XYZ), with blocks located within the mining solids flagged for reporting Mineral Resources. Block tonnages are factored to reflect the proportion of the block contained below the topographic surface and within the mining solid.

Figure 11‑10: Example section showing Bauxite Zone and mining solid (SLR, 2021)

Notes:

Vertical to horizontal exaggeration is 3:1

Drill holes colored by DOMAF variable

12.10

Block Model Validation

12.10.1

Polygonal and Gridded Seam Modelling

Alcoa uses a similar general approach to validate both the Polygonal and GSM resource models which includes:

Visual validation of cell estimated grades versus seam composited data

Comparison between composite and block model global statistics

Swath plots comparing cell grades against seam composite grades

Comparison between models when upgraded with new information.

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Estimated cell grades were compared visually to the drill hole composite grades to ensure that the cell grade estimates appeared consistent with the drill hole seam composite data.

As GSMs were effectively nearest neighbor estimates, checks by SRK (2021a) on several GSM models indicated excellent global and local correlation between the estimated cell grades and the input seam composite grades.

SLR undertook some independent checks on datasets and GSMs for the F54 and F55 blocks to confirm that the modelling procedures had performed as intended. Results were consistent with those observed by SRK (2021a) and no material issues were noted.

Polygonal resource models were updated by Alcoa when drill hole data is infilled from 60 m and 30 m spacings, and then GSM models were previously produced by Alcoa after 15 m infill drilling (3DBM models are now produced routinely at this stage). Changes in tonnages and average grades (AL, SI, OX) are presented as scatterplots in Figure 11‑11 for map sheets at Huntly where such infill drilling has occurred. It is noted that:

•

material differences in tonnages are evident for individual map sheets, represented by the scatter around the 45^o line in the top left-hand plot in Figure 11‑11

•

globally, there is only a 3% change in resource tonnage when infilling from 60 m to 30 m, but a 22% drop in tonnage when the deposit is further infilled to 15 m drill centers. The latter is mainly due to a change in the geological interpretation from a geological to a mining floor

•

decreasing the drill spacings from 60 m to 15m results in an average reduction in SI of 10%, an increase in OX of 5%, but little change to AL. These grade changes are likely due to the preferential loss of deeper DOMAF 40 material that is high-in SI and low in OX when mining constraints are considered (see Figure 11‑10)

•

similar grade-tonnage relationships related to infill drilling were noted at Willowdale by SLR.

Applying a global correction factor to Polygonal resource model tonnages generated from 30 m and 60 m spaced drill hole datasets is not considered appropriate as local differences are highly variable and not considered to be predictable, as shown by the red dots in the top left-hand plot in Figure 11‑11.

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Figure 11‑11: Resource comparison scatterplots for Huntly (Tonnage, AL, SI, OX) (SLR, 2021)

12.10.2

3D block modelling

Model validation checks by Alcoa include:

Volume checks between the geological interpretation solids and sub-block model

Visual validation of block model coding and estimated grades versus composite data

Comparison between composite and block model global statistics

Swath plots comparing block grades against composite grades.

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SLR undertook some independent checks on datasets and block models for Serpentine and Millars and obtained results that were consistent with those provided by Alcoa. Example screen captures of coded block models and AL and SI block estimates are shown in Figure 11‑12.

Figure 11‑12: Example sections showing DOMAF, AL, and SI block estimates (SLR, 2021)

3:1 vertical to horizontal exaggeration

Most global checks indicate generally good correlation between the estimated model grades and the input composite grades. However, Domain swath plots suggest that the use of a single unfolding surface and soft boundaries for the Bauxite Zone (DOMAF 20, 30, and 40) has led to grade smoothing. For example, Figure 11‑13 indicates overestimation of DOMAF 20 and 40 for AL, and underestimation for DOMAF 30. As Alcoa generally mines the majority of the bauxite profile this issue is not considered material and any estimated bauxite that is left behind would likely be DOMAF 40 (low-grade bauxite). Consequently, the impact of grade smoothing for AL would introduce some conservatism into the model. Bauxite Zone block estimates could be improved by unfolding each Domain independently and using semi-soft boundaries.

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Figure 11‑13: AL swath plots by DOMAF at Serpentine (SLR, 2021)

As discussed previously, the inequality constraint AL ≤ AT and SI ≤ ST was not met for all blocks due to:

•

the inequality constraints not being honored in the input data

•

incomplete assaying of AT and ST.

Scatterplots for some key analytes were spot checked by SLR to ensure that correlations identified for composite data were maintained during block grade estimation. In most instances there was good reproduction of the correlations during the change in support from 0.5 m composites to 15 m by 15 m by 0.5 m blocks (compare Figure 11‑7 and Figure 11‑14). However, there were commonly artefacts related to a small number of blocks that were generally located in the periphery of the deposit. These are shown as vertical lines in Figure 11‑14.

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Figure 11‑14: Scatterplots of AL versus SI by DOMAF at Serpentine (SLR, 2021)

A discrete Gaussian (DG) change-of-support check is appropriate to assess smoothing in resource estimation models. A range of variance reduction F factors from 0.20 through to 0.7 in 0.1 increments were also chosen to represent the results that may be achieved through various mining selectivities. Higher F values result in grade-tonnage distributions that could be achieved through more selective mining and high-quality grade control practices. Conversely, lower F values result in grade-tonnage distributions that would result from less selective mining and/or poorer-quality grade control practices.

The DG approach was used by SLR to determine the theoretical AL grade-tonnage curves for the Bauxite Zone at Serpentine by considering various F factors for the 0.5 m composite data (Figure 11‑15). This Figure also shows the actual grade-tonnage curve for the Serpentine 3DBM resource model. The resource model tonnage curves are consistent with the F=0.4 DG curves for all cut-offs likely to be considered at Serpentine for open pit mining. This provides further support that any grade smoothing present in the Serpentine model is unlikely to be material to the Mineral Resource estimate.

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Figure 11‑15: AL grade-tonnage DG curves versus Serpentine block model

12.11

Cut-off Grade and Mining Constraints

The generally accepted historical economic mining cut-off grade (Hickman et al, 1992) has not appreciably changed and is 27.5% A.Al₂O₃. Lowering this results in increases in R.SiO₂, offsetting gains made by increased alumina tonnages. The typical average mined grade of 30-35% A.Al₂O₃ is low by world standards. For Alcoa’s three captive alumina refineries the R.SiO₂ grade must be less than 5%, and preferably less than 2%. The minimum size for an orebody to be effectively mined is 70,000 t, and most orebodies are approximately 300,000 t.

The cut-off grade used for Mineral Resources is implicit in the delineation of the Bauxite Zone for the various resource model methods (see Section 11.9). In general, the cut-offs are AL ≥27.5%, SI ≤3.5%, with OX ≤4 kg/t, and a minimum 2 m thickness. However, bauxite resources can include material outside these specifications that may also be considered as mineable material, equivalent to dilution. The AL, SI, and OX grade constraints applied in the definition of the Bauxite Zone have demonstrated over many years to provide economic material to Alcoa’s alumina refineries.

Mining constraints applied to the GSM and 3DBM Mineral Resource include:

•

a minimum area of 1 ha

•

a minimum face height of 1.5 m (distance from mining floor to the base of overburden)

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•

face heights exceeding 4 m are treated as multiple benches

•

an overburden to face height ratio ≤1

•

a maximum floor gradient of 1 in 7 over a minimum of 15 m for the first cut, and 1 in 5 for second and third cuts

•

a minimum access corridor of 45 m for mining equipment.

Profitable mining since the 1960s has been based on the resource modelling outcomes described in this report, which demonstrates reasonable prospects of economic extraction for the Alcoa Mineral Resource.

Mineral Resources are estimated using a long-term metal price of A$25 /t alumina, this being an Alcoa internal transfer price related to the export price received for alumina

12.12

Reconciliation

12.12.1

Sampling tower data

Refinery feed grade is monitored for the Huntly and Willowdale mining regions using material collected just prior to the stockpile stackers at the Pinjarra and Wagerup sampling towers respectively.

Alcoa mine planning personnel rely upon historical comparisons between the As Mined estimates and the sampling tower data to apply adjustment factors to mine design estimates, to assist with scheduling and stockpile planning activities. The adjustments are not applied to the reported global Mineral Resource estimates as they are considered to be local factors.

Sampling tower performance was discussed in Section 8.5.3.8.

12.12.2

Resource to sampling tower comparison

Alcoa reconciles the resource (mine design) estimates with the sampling tower estimates once mining is completed for each mining zone. It is important to note that the majority of the Mineral Resources are prepared using 30 m or 60 m spaced data, whereas As Mined to sampling tower reconciliation is based on mine planning models constructed from 15 m spaced data that include additional mining constraints.

Figure 11‑16 and Figure 11‑17 show the annual relative tonnage and grade differences for both Huntly and Willowdale respectively. These plots indicate:

•

the presence of grade and tonnage biases, which for some grades show long-term trends. For example, both SI and ST display differences of up to 30% in the mid-2000s, followed by gradual reductions to approximately 5–10% in the last few years

•

that As Mined tonnage estimates are, on average, biased high by approximately 5%

•

that most As Mined grades are currently within 10% of the sample plant grades.

The sources of the reconciliation differences shown in Figure 11‑16 and Figure 11‑17 are not known, but the following factors could contribute:

•

Resource models were prepared using FTIR assay data, whereas the sampling tower samples are assayed using the same techniques as the REF Method (see Table 8‑1 in 8.3.2.1) but with BD rather than MD. Alcoa assumes that this is more accurate, but that is difficult to confirm for partial digestion methods such as AL, SI, and OX.

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•

Changes in the resource modelling procedures from Polygonal, to GSM, to 3DBM. The latter method has only recently been introduced and represents limited material processed in recent years.

•

The As Mined grades and tonnages could include some additional dilution and ore loss relative to the planned mine design.

•

Differences between the Pinjarra (inspected and validated by SLR, see Section 8.5.3.8) and Wagerup sampling towers.

Incremental reconciliation improvements appear to have commenced around 2010, which may reflect an improvement in data quality (drilling and assaying procedures) around this time. Consequently, Mineral Resources using data collected prior to approximately 2010 are considered to be of lower confidence and the classification of resource models constructed from this data has been downgraded accordingly.

Reconciliation data in recent years falls within acceptable limits on an annual basis to support the classifications used for reporting of Alcoa’s Darling Range Mineral Resource.

Figure 11‑16: Resource versus Sample Plant Reconciliation – Huntly (Alcoa, 2021)

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Figure 11‑17: Resource versus Sample Plant Reconciliation – Willowdale (Alcoa, 2021)

12.13

Mineral Resource estimation risk

The estimation of Mineral Resources for any commodity, including bauxite, is subject to significant risks, including those described below and elsewhere in the discussion of risks associated with mining and processing of bauxite to produce alumina (see Section 12.8). An investor should carefully consider these risks. If any of the described risks occur, the Darling Range bauxite mining and processing business, financial position and operational results could be materially affected adversely.

The purpose of Public Reports issued under S-K 1300 and other similarly purposed International Codes (JORC, 2012; NI 43-101, 2014) is to ensure that known risks are disclosed by the QP subject to expectations of Transparency, Materiality and Competency. This report addresses the technical risks associated with the Geology, Sampling, Assaying, Data Management in Sections 6.0 to 9.0 and Mineral Resource Estimation in Section 11.0. The Qualified Person considers that no material technical risks are identified in those Sections.

The risks described below are not comprehensive and there may be additional risks and uncertainties not presently known, for example due to market or technology changes, that are currently deemed immaterial but may also affect the business. SLR considers that the following risks specifically pertain to the Mineral Resources declared for Alcoa’s Darling Rang operations.

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12.13.1.1

Specific identified risks

•

Continuous improvement of all aspects of Alcoa’s resource delineation programs means that, changes have been incremental as refinement to previous procedures. Thus estimates for the majority of the Mineral Resource inventory are essentially variants of those devised in the late 1980s and early 1990s and are not consistent with current conventional practices. This is reflected in the large tonnage of Inferred Resources declared. The demonstrated successful operation of the Alcoa operations over an extended period indicates that it is unlikely that any aspects of the data collection and resource delineation process are significantly flawed, although there are recognized shortcomings.

•

Drill sampling is essentially the extraction of small volumes of material taken to be representative of the large tonnages being estimated. There are always local errors of precision and may be bias that is not recognized. Robust sample preparation and geostatistical estimation are used to identify and overcome these errors, backed up by closed-loop reconciliation with the stockpile tower samplers. These systems may not identify changes in the underlying geology or other data as the area to be delineated expands over time.

•

The Mineral Resource estimates may not contain adequate or relevant data if the bauxite is supplied to other refineries, or if processing methods change, or some new analyte is required.

•

The older ResTag and GSM estimation procedures, which represent the bulk of the Inferred Mineral Resource inventory, are relatively inflexible, and may not contain the level of detail necessary to adequately support mining optimization studies. This has been largely addressed by the recent move to 3DBM resource estimation techniques, which more easily enable the preparation of models that contain sufficient resolution and detail to support conventional mining optimization studies. These models will allow incremental improvements to address any challenges in meeting target grade specification, resolving reconciliation issues, or tailoring the estimation parameters and procedures to prepare models that better reflect local changes in mineralization characteristics. The 3DBM modelling procedures offer more flexibility in moderating any adverse effects of sampling imprecision compared to the older procedures and in producing grade tonnage curves to meet various impurity constraints (when modelled).

•

Further advances in geostatistical estimation may be expected including more use of directional anisotropy (through variograms), and conditional simulation to quantify estimation risk and optimize drill sampling grids.

•

A comprehensive program is required to resolve the issue of density estimation. Estimates in the resource models use a simplistic linear regression algorithm for iron rich material based on very few data, and otherwise assumed values. This deficiency is overcome by reconciliation of tonnages of material fed to stockpiles and the subsequent adoption of a downgrading factor (currently 5%) to account for differences to the model estimated density. Technology now becoming available, including volume surveys using drones and truck gantry scanning, wet mass measurement using weightometers on conveyors and LoadRite sensors on mining equipment, and infra-red moisture determination, mean that better in situ dry density estimation may become possible if the operation requires it for better refinery feedstock control.

•

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•

There is currently significant reliance upon the sample plant results for production scheduling and blending, as well as for assessing the reliability of the Mineral Resource estimates.

The current drill sampling methods have been improved over time, based on independent review, and the requirements for minimum impact on the Darling Range. The assaying methods, including the use of FTIR, have been comprehensively reviewed and validated. The geostatistical estimates of in situ dry tonnages and grades are reasonable and validated by comprehensive reconciliation. The SLR Qualified Person considers that these methods are appropriate to produce the declared Mineral Resources and Mineral Reserves.

12.13.1.2

Generic Mineral Resource uncertainty

•

Estimates of Measured and Indicated Mineral Resources are uncertain. The volume and grade of ore actually defined from these as Mineral Reserves is not predictable until mine planning is done to account for all the identified Modifying Factors. Forecasts based on the current transfer price of bauxite, current interpretations of geological data obtained from drill holes, and other information regarding the Modifying Factors, may not necessarily be indicative of future results. A significantly lower bauxite transfer price as a result of a decrease in aluminum prices, increases in operating costs, reductions in metallurgical recovery, or other changes to the Modifying Factors, could result in material write-downs of the value of the Darling Range mines.

•

Should changes be required due to exigent circumstances, it may take some years from exploration until commencement of production, during which time the economic feasibility of production may change.

•

Alcoa cannot be certain that any part or parts of a deposit or Mineral Resource estimate will ever be confirmed or converted into Regulation S-K Subpart 1300 compliant Mineral Reserves or that mineralization can in the future be economically or legally extracted.

To ameliorate such risks the Mineral Reserves declaration is limited to material for which extraction is currently planned within the next ten-year planning cycle. The Mineral Resources excluding Mineral Reserves indicate the likely potential beyond that time frame, given all the limitations on future knowledge outlined above.

12.14

Classification

12.14.1

Consideration of classification by the QP

Definitions for resource categories used in this report are those defined by the SEC in S-K 1300. Mineral Resources are classified into Measured, Indicated, and Inferred categories.

Mineral Resource classifications have been applied to the various resource models based on consideration of the quality and quantity of the input data, confidence in the geological interpretation, and confidence in the outcomes from the various estimation methods. Factors that impact the Mineral Resource classifications are summarized below.

•

Sampling: Alcoa has introduced incremental improvements to their drilling, sampling, sample preparation and assaying procedures since 2015. The sample collection procedures are efficient and optimized to routinely produce large numbers of drill samples and assays consistently that are considered to be fit for purpose.

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•

Sample preparation: routine sample preparation using a robotic facility which routinely provides an appropriate grind size for samples.

•

Assays: the FTIR spectral method is routinely used for all analytes, calibrated and validated with wet chemical Reference Method samples at a frequency of 1:100. The SLR QP has investigated this procedure and considers that appropriate assays and controls are used for the purpose of Public Reporting of a Mineral Resource estimate.

•

QA/QC: Quality assurance and quality control procedures have been incrementally improved since 2015. Further systematic refinements of these are expected to enable more data to be routinely collected, but the accuracy and precision demonstrated in Sections 8.5.2 and 8.5.3 respectively are not expected to change.

•

Density data: The dry in situ bulk density test work data is sparse and not appropriate for the reliable estimation of tonnages. Based on test work from 1992 a simple algorithm using the Fe₂O₃ grade for Caprock and an assumed value of 2.0 t/m³ for all other ore fed to the refineries has been used. Reconciliations have determined a consistent overestimation of 5%, and a moisture content of 9% provide reliable predicted tonnage estimates over an extended period of operation. In the opinion of the SLR QP the variable nature of the bauxite, especially the porosity, means that any alternative sampling method is unlikely to produce better estimates. Accordingly, the density values applied are not considered a limiting factor for resource classification.

•

Drill spacing: Drill hole spacings in the Darling Range vary from 15 m by 15 m up to 120 m by 120 m, with Mineral Resources only declared where drill hole spacings are ≤60 m by 60 m.

•

Geological interpretation: The regional geology of the Darling Range project is well understood with bauxite mineralization supporting mining and processing operations since the 1960s. Controls on the mineralization and the mineralogical and physical properties of the Bauxite Zone are well understood and have been adequately incorporated into the Mineral Resource modelling procedures.

•

Grade continuity: Grade and lithological continuity studies are routinely conducted by Alcoa for the 3D block models. Variography studies conducted by Alcoa were supported by independent review (Xstract, 2016; SRK 2021a) and indicate that grade and lithological continuity can be demonstrated at the drill spacings supporting the Mineral Resource classification.

•

Grade estimation: The majority (80% exclusive of Resources) of the current Mineral Resource inventory has been defined using polygonal techniques that are not industry best practice and can be prone to estimation bias. Consequently, irrespective of the drill hole spacing all estimates based on the Polygonal Method are considered to be of low confidence for local estimates and have been downgraded relative to 3DBM estimates. GSMs are only constructed using 15 m by 15 m spaced drill hole data, and although previously used to support Measured Mineral Resources, has been replaced by the 3DBM method, which as implemented by Alcoa aligns with industry best practice.

•

Reconciliation data: Annual reconciliation between mined ore based on the Mineral Resource estimates and received material on the refinery stockpiles (sampled by the sampling towers) show relative differences for both Huntly and Willowdale of within ± 15% for tonnes and all analytes (except SI) since 2010. Reconciliation performance prior to 2010 for some analytes exceeded ±

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Technical Report Summary - February 24, 2022

15%, casting doubt on the reliability of some data and models prior to that date. It is not possible to reconcile blended production data to individual resource models.

•

Production history: The integrated bauxite mining and alumina refining is based on appropriate data to ensure long-term supply and short-term management of the ore feed to the mine mouth refineries. The long production history demonstrates effective prediction and control of refinery performance.

SLR considers the primary controlling factors for the classification of the Mineral Resource estimates for the Darling Range Bauxite to be drill hole sample spacing, the quality of data collected, and the resource modelling technique. A 5% tonnage reduction factor is used in the reporting of Mineral Resource tonnages to account for the consistent annual reconciliation outcomes.

12.14.2

Methodology

The primary consideration for classification is confidence in the resource estimate. The Mineral Resource estimate for Darling Range is produced by aggregating many different models, produced using data of different qualities at different drilling densities, modelled using different estimation procedures.

A drill hole spacing study aimed at quantifying the differences in the reliability of local estimates with different drill spacings was undertaken by SRK (2019a) using a similar approach to Alcoa’s 3DBM procedures. The SRK study concluded that drill spacings of 30 m by 30 m and 60 m by 60 m were adequate to support the delineation of Measured and Indicated Resources respectively, provided that none of the other limiting factors discussed above were applicable.

The SLR QP considers, on the basis of the previously discussed acceptable sampling and assaying quality, that this drill hole spacing study and other knowledge justifies:

•

The classification of Measured where such data is on a 30 by 30 m grid. However where the estimation method is gridded seam modelling (GSM) rather than current industry standard 3D block modelling (3DBM) the Measured material is downgraded to Indicated, unless it is on a tighter drilling grid of 15 by 15 m. The additional data density overcomes any deficiency of the GSM method. Some of the defined Measured material estimated using a significant amount of older (pre-2010) drill sampling was also down-graded to Inferred, reflecting the lower confidence in that older drilling data, since data quality (due to drilling, sampling and assaying procedures) has been upgraded since then.

•

Furthermore, based on the same principles (data quality, drilling study, estimation procedures), 60 by 60 m drilling and 3DBM estimation is the basis for classification as Indicated. Estimation using the GSM or Polygonal method was allowed as Indicated where the drill spacing was on a tighter grid of at most 30 by 30 m. The additional data density is considered to overcome the similar deficiency of both these estimation methods, which because of the data configuration are similar to a nearest neighbor estimate.

•

All Measured and Indicated material already has mining constraints applied, effectively ensuring that reasonable prospects for economic extraction are assure should other required economic viability constraints obtain.

•

Where the data spacing is 60 by 60 m and the estimation method is Polygonal the resource estimate is classed as Inferred.

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There is a large tonnage estimated of Inferred Resources, partly due to the sufficiency of the current Proven and Probable Mineral Reserves for the ten year mine planning horizon and the immediate availability of additional Measured and Indicated Mineral Resources (reported exclusive of Reserves) to replace them. Further Measured and Indicated Resources may be defined when required from the established Inferred Resource in time, given more closely spaced drilling, estimation using 3DBM techniques, and the further application of cut-off grade and mining criteria.

Resource classification criteria are applied in the horizontal plane and so are consistent for the entire Bauxite Zone vertical profile. Thus, interpretation of the roof and floor of the Bauxite Zone are implicitly assumed to be of similar confidence. In some areas the geological floor may be erratic for Polygonal models and of lower confidence than the roof, but these areas are typically excluded when mining constraints are applied to the GSM and 3DBM resource models.

An example of the resource classification approach is shown in Figure 11‑18. Resource classification polygons are created for areas of 15 m, 30 m, 60 m and >60 m parts of the deposit. Note that these polygons can include small areas where the gaps between drill holes are at the next spacing increment. These polygons are then used to assign resource classifications for the full vertical profile of the Bauxite Zone.

Classification Polygons

block classifications

Figure 11‑18: Plan view of Resource Classification (SLR, 2021)

12.14.3

Application of classification criteria by the QP

The following classification criteria have been applied to the Mineral Resource estimates:

•

Measured Resources - areas estimated using:

15 m by 15 m drill data and GSM or 3DBM estimation procedures; and

30 m by 30 m drill data and 3DBM estimation procedures.

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•

Indicated Resources - areas estimated using

30 m by 30 m drill data and estimated using GSM, or Polygonal procedures;

60 m by 60 m drill data and estimated using 3DBM procedures; or

meeting the Measured criteria but estimated using a significant amount of pre-2010 drilling data.

•

Inferred Resources - areas estimated using:

60 m by 60 m drill data and estimated using Polygonal procedures.

12.15

Mineral Resource Reporting

Key refinery target grade requirements for AL, SI, and OX along with practical mining considerations have been taken into account when defining resource blocks using GSM and 3DBM modelling methods. Polygonal resource models do not account for mining constraints other than a 1.5 m minimum thickness.

ML1SA contains some sub-regions for which mining permission has not been granted, due to forestry, environmental, social or other constraints, and Mineral Resources have not been defined in these areas by constraining the Mineral Resource model using the ArcGIS system.

For Mineral Resource reporting, the block tonnage estimates have all been reduced by 5% on the basis that:

•

the reconciliation data at both Huntly and Willowdale indicate that the As Mined tonnage estimates over the past 20 years have been consistently higher than the stockpile received tonnages after the sampling tower by approximately 5%; and

•

the stockpile estimates are derived from weightometer readings, and the weightometers are regularly checked and calibrated.

12.15.1

Mineral Resource Estimation

A summary of the Mineral Resource estimates (exclusive of Mineral Reserves) for the three ML1SA mining regions is shown in Table 11‑4.

Table 11‑4: Summary of Mineral Resources exclusive of Mineral Reserves by Mining Region – 31^st December 2021


Category	Tonnage (Mt)	A.Al₂O₃ (%)	R.SiO₂ (%)
HUNTLY
Measured	20.9	32.7	1.20
Indicated	10.2	32.6	1.25
Inferred	126	34	1.3
NORTH
Measured	-	-	-
Indicated	0.8	32.3	1.38

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Inferred	15	32	1.0
WILLOWDALE
Measured	27.1	33.0	1.05
Indicated	23.8	31.6	1.05
Inferred	179	32	1.2

Notes:

The definitions for Mineral Resources in S-K 1300 were followed, which are consistent with JORC (2012) definitions

Mineral Resources are 100% attributable to AWAC

A minimum total mining thickness of 1.5 m was used

In situ dry bulk density is variable and is defined for each block in the Mineral Resource model

A global downwards adjustment of tonnes by 5% is made to account for density differences based on historic mining performance

Mineral Resources are reported exclusive of Mineral Reserves

The reference point for the Mineral Resource is the in situ predicted dry tonnage and grade of material to be delivered to the refinery stockpile following the application of mining design parameters

10.

11.

Numbers may not add due to rounding.

12.16

QP Opinion

In the opinion of the SLR QP the Mineral Resource classification scheme adopted by Alcoa and accepted by SLR is appropriate in defining expected relative confidence of the Mineral Resource in compliance with the S-K 1300 definitions as follows:

•

All sampling, sampling preparation, assaying and database management practices are compliant with current industry good practice and no fatal flaws were identified for all material classed as Mineral Resource

•

Appropriate industry good practice geological modelling techniques and variography are used to establish geological and grade continuity from appropriately spaced drill holes

•

Industry standard estimation techniques (3D block modelling or seam block modelling) are used for all Measured and Indicated Mineral Resources using appropriate drill spacings

•

Appropriate drill spacings, grade continuity and geological continuity are used to define higher confidence material as Measured Mineral Resource.

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13.0	Mineral Reserve Estimates

13.1

Summary

The reference point for the Mineral Reserve is prior to the processing plant at the refinery.

The Proven Mineral Reserve is a subset of Measured Resources only. The Proven Mineral Reserve is legally permitted for mining and is included in the Ten-Year Mine Plan.

The Probable Mineral Reserve is estimated from that part of the Mineral Resource that has been classified as Indicated.

Variable cut-off grades are applied in estimation of the Mineral Reserves and these are related to operating cost and the nature of the Mineral Resource in relation to blending requirements. The Mineral Reserve estimate is expressed in relation to available aluminum oxide (A.Al₂O₃) and reactive silica (R.SiO₂), this being the critical contaminant in relation to the Refinery.

Table 12‑1: Summary of Mineral Reserves – Effective 31^st December 2021


Region	Class	Tonnage (Mt)	A.Al2O3 (%)	R.SiO2 (%)
Huntly	Proven	45.8	32.5	1.05
	Probable	121.1	32.2	1.41
	Total	166.9	32.3	1.31
Willowdale	Proven	62.8	32.4	0.99
	Probable	11.5	31.8	1.09
	Total	74.3	32.3	1.01
Total	Proven	108.6	32.4	1.01
	Probable	132.7	32.2	1.38
	Total	241.3	32.3	1.22

Notes:

The definitions for Mineral Reserves in S-K 1300 were followed, which are consistent with JORC definitions.

Mineral Reserves are stated on a 100% ownership basis for AWAC although Alcoa’s share is 60%.

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Mineral Reserves are estimated at variable cut-off grades, dependent on operating costs and ore quality for blending. The target grade for mine planning is 32.7% available aluminum oxide (A.Al₂O₃) and around 1.0% reactive silica (R.SiO₂)

Mineral Reserves have been estimated using a three-year trailing average of arms-length sales of bauxite from Darling Range. The price that constrains the estimate for optimisation was discounted to exclude export logistics costs, i.e. the base price was USD24/t, and the discounted price was USD16/t.

Minimum mining widths are not used due to the surficial nature of the Mineral Resource, rather a minimum mining block size of 15m by 15m by 1m deep is applied.

The reference point for the Mineral Reserve is the refinery processing plant gate, with crushing, washing (as applicable), and transportation being the only process employed. As much metallurgical recovery factors are not applicable to the Mineral Reserve estimate.

Bulk density is variable, dependent on the nature of the Mineral Resource and is separately estimated in the Mineral Resource model.

Numbers may not add due to rounding.

The Modifying Factors are summarized as follows:

•

Only Measured and Indicated Mineral Resources are considered.

•

Only mineralization defined in mine planning work has been considered. This includes Measured and Indicated material, subject to the application of mining Modifying Factors.

•

Mineral Resources not scheduled for mining in the current Ten-Year Mine Plan are not considered.

•

Indicated Mineral Resources are classified as Probable Mineral Reserves, subject to the Modifying Factors and mine scheduling constraints.

•

Measured Mineral Resources are classified as Proven Mineral Reserves, subject to the Modifying Factors and mine scheduling constraints.

13.2	Modifying Factors

A Mineral Reserve is the economically mineable part of a Measured and/or Indicated Mineral Resource. It includes diluting materials and allowances for losses, which may occur when the material is mined or extracted and is defined by application of Modifying Factors that demonstrate that, at the time of reporting, extraction could reasonably be justified.

•

Mining – Alcoa’s Darling Range mining operations are conventional open pit mines and have been operating for a long time. The practicalities of mining and associated sustaining capital and operating costs are well understood and have been incorporated in Alcoa’s technical assessments to the satisfaction of the QP. For a more substantive description of Alcoa’s Darling Range mining operations, refer to Section 13.0. The mining schedule is discussed further in Section 12.5.

•

Processing – This Mineral Reserve is stated with reference to the refinery processing plant gate, with crushing and conveying being the sole processes employed. Bauxite is refined to alumina in the refinery using the Bayer process, which has been employed at the Darling Range operations for many years and a transfer price is used by Alcoa in its assessment of its mining operations. The

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QP is satisfied that the transfer price reasonably incorporates the costs associated with processing of the bauxite ore. For a more substantive description of Alcoa’s Darling Range processing operations, refer to Section 14.0.

•

Metallurgy – The mining operations are given an ore specification by the sole customers, the refineries. Blending is undertaken at the pit, before the crusher, to ensure that these specifications are met. The QP is satisfied that the procedures employed by mining technical staff have been developed over a lengthy period and are appropriate for the suppression of metallurgically deleterious material in ore sent to the refineries. For a more substantive description of Alcoa’s Darling Range metallurgy, refer to Section 10.0.

•

Infrastructure – The QP has observed the Darling Range infrastructure to be well established, maintained and complete. The operations are located near a major city, with excellent transportation, facilities, and workforce. Provision is made in Alcoa’s Life of Mine (LOM) plans for sustaining capital for infrastructure replacement. For a more substantive description of Alcoa’s Darling Range infrastructure, refer to Section 15.0.

•

Economic – Revenue for the mines is premised on a transfer price for bauxite ore at the refinery gate. Mining costs are well understood, as the mines have been operated for a long time. The QP is satisfied that the pit optimization, scheduling, and analysis undertaken by mine technical staff is appropriate to the operation and that the costs are well understood. For a more substantive description of Alcoa’s Darling Range economics, refer to Section 19.0.

•

Marketing – All bauxite is sold to Alcoa’s Darling Range refineries, the sole customer for the mines. The refineries produce alumina, which is variously further refined into aluminum metal at Alcoa’s aluminum plants or exported. Alumina and aluminum are internationally traded commodities and subject to normal market forces and cycles. For a more substantive description of Darling Range’s market aspects, refer to Section 16.0.

•

Legal – The QP observes that the Darling Range operations have been in operation for a long time and are licensed in relation to obligations under Western Australian legislation. Mining approval for the Darling Range operations is given by the statutory Mining and Management Program Liaison Group (MMPLG). The MMPLG consists of representatives from across government and is responsible for reviewing mine plans and associated activities and making recommendations to the Western Australian Minister for State Development.

•

Environmental - The QP observes that the Darling Range operations have a long history of progressive rehabilitation of mined-out areas. There are restrictions placed on some mining areas that are related to proximity to water catchments, places of social importance and fauna habitat. Operation under these conditions is by approval of the MMPLG. For a more substantive description of Alcoa’s Darling Range environmental obligations, refer to Section 17.0.

•

Social – The QP observes that the Darling Range operations have long been a major employer and economic contributor to the region and that the operations have numerous well-established community and social initiatives. A skilled workforce resides in the area, as do many service industries. The QP does not consider social risk to be material to the Darling Range operations.

•

Governmental – Western Australia and Australia in general are stable, developed democracies with an advanced economy. Governmental relations with the Darling Range operations are

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managed by the MMPLG, which has representation from the relevant government departments. The QP does not consider governmental risk to be material to the Darling Range operations.

13.3	Basis of Estimate

Historically, Alcoa did not report material in the Measured Mineral Resource category, reporting mineralization in areas of 15 m by 15 m spaced drilling as Mineral Reserves reported to the prior SEC standard. Alcoa has subsequently incorporated S-K 1300 and JORC Modifying Factor considerations into its mine planning processes and this was observed and confirmed on site.

Proven Mineral Reserves are derived from scheduled Measured Mineral Resources which are not located within Myara North. Probable Mineral Reserves are derived from scheduled Measured Mineral Resources which are located in Myara North, or from scheduled Indicated Mineral Resources. The Mineral Resource estimate reported in this document (Section 11.0) is exclusive of the Mineral Reserve.

Consequently, Modifying Factors that relate to community and environmental considerations are formally assessed. The QP considers that there is low risk to derive Proven Reserves relating to the project. Alcoa has stated to SLR during the site visit that in recent years there has been no instance of a requirement for Proven mining blocks to be downgraded or abandoned.

The Probable Mineral Reserve has also been defined by 15 m by 15 m drilling but has not yet been presented to the MMPLG for approval. Application of the Modifying Factors is otherwise identical.

The QP has formed an independent view of the Modifying Factors applied in the estimation of the Mineral Reserve. This view is supported by examination and verification of mine planning data and procedures and historic reconciliation information. The QP has interviewed technical staff responsible for Alcoa’s operations and reviewed the operating, planning and forecast reports for the operations supplied by Alcoa.

The mine planning process excludes mineralization that is not considered recoverable due to various constraints, defining no Mineral Resource or Mineral Reserve within these zones. Such constrained zones include Aboriginal heritage sites and old-growth forest, however are proactively and dynamically updated by Alcoa through engagement with stakeholders, such as the community, and in response to government requests.

13.4	Dilution and Ore Loss

Dilution and ore loss are not reported separately to the Mineral Reserve. Internal and edge dilution is modelled at the mine planning stage through the application of 15 m by 15 m mining blocks to the Mineral Resource model. These regularized blocks contain proportional estimates of ore and contaminants and are optimized through the application of a Lerchs-Grossman algorithm developed specifically for the operation. This variation of the conventional Lerchs-Grossman algorithm is applied vertically, given that

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the shallow nature of the mineralization precludes geotechnical considerations. Blocks that do not satisfy grade and contaminant parameters against revenue are thus excluded from the mine plan.

Mining dilution is controlled by excavation of dilution at the top of the mineralization (a source of oxalate or organic contamination) and the pit floor (R.SiO₂ contamination). The upper contact is a sharp geological contact on an undulating surface. GPS-controlled machinery is used to locate these intersections.

Figure 12‑1: Undulating Hanging wall hardcap surface; and footwall (white clay, lower right in the floor) (Left: Pearman, 2015 & Right: SLR, 2021)

Organic material reacts with sodium hydroxide in the refinery to form oxalate, which is considered to be a contaminant. Alcoa has developed a process known as Secondary Overburden Removal (SOBR) whereby the soil and clay on top of the hardcap that covers the mineralization and contains this organic material is removed by either scraper, surface miner or small excavator. This removes as much carbonaceous material overlying the undulating hardcap layer as possible. Further description of SOBR is given in Section 13.1.

A surface miner is employed as required at the Huntly mine to cut highly contaminated overburden to the hardcap contact, which results in a 2.9% ore loss, which is considered in the Mineral Reserve estimation.

The lower mineralization contact is gradational and dilution is minimal on contaminants other than R.SiO₂. This contact is defined through drilling and chemical analysis and excavation is controlled by GPS to modelled surfaces.

The Grade Control process checks the accuracy of excavation and assesses adherence to excavation of the target floor.

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13.5	Extraction and Mine Planning

13.5.1

Ten-Year Mine Plan

Alcoa prepares a Ten-Year Mine plan annually. The first five years of this plan is submitted to the statutory MMPLG for approval of mining areas. The Ten-Year Mine Plan includes a mine production schedule that demonstrates scheduling of mineralization classified as Mineral Resources for estimation as Mineral Reserves. This schedule contemplates higher confidence Mineral Resources during the early production periods, with lower confidence mineralization planned in subsequent periods (Figure 12‑2 and Figure 12‑3). Note that the Willowdale unclassified material in 2030 and 2031 includes resTAG Inferred material drilled at 60 m spacing.

The schedule has several operational parameters in addition to statutory limitations (refer Section 12.2 above):

•

The mineralization lies under haul roads and extraction is delayed until the road is no longer required.

•

Mineralization is near a planned crusher location and mining has been delayed until the crusher is installed.

•

Contaminants exclude a parcel from blending in the schedule.

•

The mining areas are small and demonstrate low mining efficiency and mining has been delayed.

Confidence in the Mineral Reserves is predicated on confidence in the underlying Mineral Resources in the mining schedule. Continuous Mineral Resource definition drilling maintains an inventory of sufficient confidence to maintain Mineral Reserves.

Figure 12‑2: Willowdale Ten-Year Mine Plan Resource confidence (drill hole spacing in meters shown in brackets) (SRK, 2021)

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Figure 12‑3: Huntly Ten-Year Mine Plan Resource confidence (drill hole spacing in meters shown in brackets) (Alcoa, 2022)

13.5.2

Mine Planning

Alcoa is actively refining the mine planning process in such a way that the Mineral Resource and Mineral Reserve Models are updated continuously using various scripts and a rationalizing of computer software. This process is currently incomplete, but the QP observed its progress both on the mine sites and at the Booragoon mine planning office.

The mine planning process commences with receipt by the mine planning department of the regularized and classified electronic Mineral Resource model from the geologists. The regularization process sees the Mineral Resource blocks agglomerated into blocks of 15 m by 15 m by 0.5 m vertically. Grade, bulk density and contaminant parameters are estimated into the model, which is expressed as a percentage model. This model is then manually checked and validated.

Electronic files are centrally stored, and the master versions are copied by relevant personnel for manipulation.

Optimization of the pits is undertaken using a bespoke variant of the Lerchs-Grossman algorithm designed to operate vertically. The algorithm accumulates blocks vertically on 0.5 m increments to find the pit floor.

The optimization is driven by Net Present Cost (NPC), rather than the conventional Net Present Value (NPV) due to the presence of a flat transfer price for product at the refinery gate.

Geotechnical constraints are not relevant, given that the pits are generally around 4 m in depth and placed on gently undulating country (Section 7.9). Contour mining is applied in areas of topographic relief, whereby mining progresses across the contour, maintaining a level pit floor as much as possible.

Optimization parameters are calculated for each block, including costs associated with drilling, blasting and ripping and haulage cost, which is estimated from major haulage roads and minor pit access roads against gradient. Electronic surface models are prepared to constrain the optimization; these are informed by LiDAR radar surveys and model the topography, the base of overburden and the base of

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mineralization, derived from chemical analysis of resource definition drilling samples. Caprock requires drilling and blasting, and modelled surfaces are contoured for thickness, which is derived from examination of drill logs and high-Fe assays.

Pit shells are visually assessed for practicality and minimum mining widths and any impractical pit shells removed. Minimum mining widths vary according to topography and material type.

Individual areas are optimized separately, and the resultant pit shells are combined to provide grade and contaminant specifications for Life of Mine (LOM) scheduling. Haul roads are divided into 50 m segments with appropriate cost increments applied to each segment using commercial haul road optimization software. This process electronically tags each block with haulage cost information as a function of distance of the relevant node (haul road) from the nearest crusher. The software then normalizes the data by calculating the equivalent flat haul distance, maintaining a gradient of less than 8% for all nodes.

The model is then depleted for mined material and blocks that have been otherwise committed for development or have been mined out and also for environmental constraints.

Environmental constraints include proximity to streams, designated heritage areas (both Aboriginal and European) and the water catchment offset. GIS software is used to continuously generate electronic shape files that are converted daily to string files for import into the mine design software. These are then used to deplete the model in relation to environmental constraints.

Mineralization that has been identified as being under infrastructure is scheduled for mining only after that infrastructure has been removed in the LOM plan.

Noise zones are those where noise from the mining operations will potentially exceed allowable levels and the operation actively seeks to maintain lower noise levels than those mandated. Mining in these areas is undertaken by contract miners using smaller equipment on day shift only and attracts higher costs than conventional owner-operator mining, which is applied to most of the operation.

The regularized model is then coded for the above parameters and checked. All the above processes are logged, checked and validated both electronically and visually. Electronic scripts are then run in the mine planning software, resulting in the reporting of Mineral Reserves.

Revenue for the Lerchs-Grossman optimization is applied as a transfer price obtained from Alcoa’s Financial Department. This revenue is related to the export price gained for refined alumina and is related to penalties for reactive silica content. Current revenue is around US$24/t. The optimization uses US$0.48 per unit alumina based on the average grades that are agreed with the refineries. A discount rate of 12.4% is mandated by the Finance Department and applied to the NPV scheduler during the mine planning process.Alcoa uses a three-year trailing average of arms-length sales of bauxite from Darling Range. The price that constrains the estimate for optimisation was discounted to exclude export logistics costs, i.e. the base price was USD24/t, and the discounted price was USD16/t.

The QP notes that costs and revenues used in this process demonstrate a slow movement over time and that revenue has remained constant over the past year.

In practice, the Grade Control Model is used to direct mining at the bench scale, because it has more up-to-date drilling data than the Mineral Resource Model. Reconciliation is undertaken between the Mineral Resource, Mineral Reserve and Grade Control Models, with the QP observing the reconciliations between Mineral Resource and Grade Control Models to be within acceptable parameters. Reconciliation of the Mineral Reserve model has not been regularly undertaken in the past and this process was observed to be in development.

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Figure 12‑4 shows an example of the reconciliation between Resource and Grade Control models undertaken regularly by Alcoa.

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Figure 12‑4: Example of reconciliation between Mineral Resource and Grade Control models for tonnage, Al, Si, and OX (Alcoa, 2022)

The resultant pit shells are scheduled using specialist automated mine scheduling software. A text file containing the model and its parameters is exported to the scheduling software, which is programmed with current wait times and the current mining capacity of 26.5 Mtpa. The software calculates and defers, as much as possible, capital haul road development costs for each block and identifies an optimal schedule.

Sustaining capital is calculated and added for haul road maintenance and equipment replacement. Not all machinery is capitalized, some being leased, and this is included the operating cost. Review of ownership costs against leasing is constant and appropriate factors applied to the model.

The resultant model is coded for grade and contaminants and blocks are flagged with the appropriate mining sequence. Mineral Reserve blocks are contained within the ten-year schedule. The model is then re-exported as a text file to the mine planning software and distributed to the relevant mine planning departments and mine closure engineers for detailed planning.

13.5.3

Abandoned Resources

Some planned mining areas that are included in the schedule are unable to be totally mined for a variety of operational reasons. These reasons usually relate to issues with rock outcrops, hard ground, contamination and access difficulties that are encountered when developing a new mining area. This process drives the continuous development of new mining areas to maintain production capacity.

Alcoa’s recorded average abandoned mineralization between 2016 to 2019 (inclusive) is estimated at an average of 1.5% of Huntly and 2.0% of Willowdale planned production but can vary materially. These factors are applied to forecast production in the Mineral Reserve estimation process.

13.6	Cut-off Grade

The cut-off grade used for mine production planning is a floating cut-off grade, dependent on capital and operating costs against a fixed product revenue at the refinery gate. These revenues are updated at least

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annually by Alcoa’s Finance Department and are observed by the QP to remain relatively constant, which is a three-year trailing average of the contractually received export product price.

The cut-off grade is thus cost-driven rather than revenue driven. Operating costs are observed to be driven by haulage distance and the use of contract mining in areas where mining is undertaken on day shift only due to environmental restrictions. Haulage distance is related to the presence or absence of capital haul roads and their maintenance costs.

The current nominal cut-off grades for Alcoa’s Darling Range operations are 27.5% for A.Al₂O₃ and 3.5% for R.SiO₂.

13.7	Metallurgical Factors

The Huntly and Willowdale Darling Range mining operations feed three refineries: Kwinana, Wagerup and Pinjarra. The Huntly mine provides feed for the Kwinana and Pinjarra refineries and the Willowdale mine provides feed for the Wagerup refinery. Ore is transported via conveyor belt from the relevant crushers, and mine the battery limit for the mining process is the refinery gate. All three refineries are established, mature and use the conventional low-temperature Bayer refining processes.

The refineries are designed to accommodate long-term average bauxite and impurity grades from the mines. Internal Alcoa specification contracts are established between the refineries and each of the mining operations and these contracts are updated annually and contemplate a five-year mine plan. These contracts set impurity targets, the key impurities being R.SiO₂, oxalate and iron. Mineral processing testing is discussed in Section 10.0, and processing and recovery in Section 14.0.

The internal LOM (nominally 2045) specification for bauxite is based on a 27.5% A.Al₂O₃ cut-off grade, which has not been optimized but is supported by the extensive operating history at the three refineries.

Deleterious elements are managed within contracted limits by blending at each mine, with the aim of minimizing variation. The refineries conduct metallurgical test work to ensure that any potential effects of variance caused by new mining areas are understood.

Geometallurgical analysis is conducted on drill hole samples using FTIR analysis as a primary method. A subset of the samples is assayed using conventional analytical procedures, with the results used for FTIR batch calibration and quality assurance purposes. The Mineral Resource model is coded for geometallurgical grades for available alumina and reactive silica. This information is reported in the Mineral Resource estimate as well as the Mineral Reserve estimate.

The Mineral Reserve is based on geometallurgical criteria that have been set by the refineries as suitable for producing alumina to agreed product marketing specifications.

13.8	QP Opinion

The SLR QP considers that, because of the integrated process by which Measured and Indicated Mineral Resources translate to Mineral Reserves for Alcoa’s Darling Range operation, there are no foreseeable risks associated with Modifying Factors (mining, processing, metallurgical, infrastructure, economic, marketing, legal, environment, social, or government) that materially affect the Mineral Reserve estimate at 31 December 2021.

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Operational risk associated with the COVID-19 pandemic, this may include labour shortages, disrupted supply chains affecting equipment and parts ordering. This could significantly disrupt operations and may materially and adversely affect Alcoa’s business and financial conditions.

Changes in the actual mined grade, lower alumina or higher reactive silica grades are a risk to the overall economics. Grade control is an important process for this type of deposit and effective control on minimising the dilution particularly along ore-waste boundaries is crucial to maintaining expected mined grades.

Haul distance is considered a risk factor due to the hauling cost making up a significant portion of the mining cost. Hauling is also directly linked to fuel cost and maintenance, the combination of an increased hauling distance as well as an increase in fuel cost and maintenance would result in a significant impact on the operational costs. Haul distances to Reserve blocks typical increase over time until such time there is a plant relocation and so there is an expected increase in hauling distance in the medium term.

Alcoa may be unable to obtain or retain necessary permits, which could adversely affect its operations. The Darling Range operation is subject to extensive permitting requirements. The requirements to obtain and/or achieve or maintain full compliance with such permits can be costly and involve extended timelines and possible delays. Alcoa strives to obtain and comply with all required permits but there can be no assurance that all such permits can be obtained and/or always achieve or maintain full compliance with such permits.

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14.0	Mining Methods

14.1	General Description of Operations

The Huntly mine currently operates at a nominal mining capacity up to 27 Mtpa. In recent years, licenses were gained for the export of a proportion of the bauxite produced. The Willowdale mine operates at a nominal production rate of 10 Mtpa.

The Darling Range operations currently have a nominal expected mine life until 2045 (when ML1SA expires), although provision exists for Alcoa to apply for a further mineral lease (Section 3.2). Mine Plans for 10 years of scheduling of mineralization classified as Mineral Resources for estimation as Mineral Reserves (Section 12.5.1). Mining units of 15 m by 15 m by 0.5 m vertically are in use at the operations (Section 12.5.2).

Dilution and ore loss are not reported separately to the Mineral Reserve (Section 12.4). Internal and edge dilution is modelled at the mine planning stage through the application of 15 m by 15 m mining blocks to the Mineral Resource model. These regularized blocks contain proportional estimates of ore and contaminants and are optimized through the application of a Lerchs-Grossman algorithm developed specifically for the operation. This variation of the conventional Lerchs-Grossman algorithm is applied vertically, given that the shallow nature of the mineralization precludes geotechnical considerations. Blocks that do not satisfy grade and contaminant parameters against revenue are thus excluded from the mine plan.

Mining recovery from Huntly and Willowdale are estimated to be 96% and 98%, respectively.

Figure 3‑3 shows the outlines of mined areas, Mineral Resources, and Mineral Reserves, which are collectively taken as representing the final pit outline, as currently understood. This does not account for any required extensions or additional licenses and assumes that all Mineral Resources and Mineral Reserves are ultimately mined.

14.1.1

Clearing

Following definition of Mineral Reserve blocks, vegetation is cleared ahead of mining by the Western Australian State Forest Products Commission (FPC), saleable timber being harvested for use. Clearing approval is sought a minimum of three years ahead of mining allowing time for harvesting of saleable timber before vegetation clearing.

14.1.2

Stripping

On receipt of clearance to proceed from the FPC, Alcoa operations commence stripping topsoil and Secondary Overburden Removal (SOBR) using small excavators, scrapers, and trucks. Soil is stockpiled at the site, away from the proposed pit, for rehabilitation purposes. Soil is stockpiled in windrows in such a manner that it maintains its organic viability.

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The dieback fungus (Phytopthora spp.) is endemic in parts of the mining areas, which are flagged by Alcoa and precautions are taken to contain the fungus, which is lethal to the eucalyptus forest. The QP observed these precautions, which include separation of machinery fleets in areas where dieback is present and washing of machinery before entry into different areas. This represents a minor short-term scheduling challenge, though it is well managed.

14.1.3

SOBR

The SOBR process is specialized and aims to remove as much overburden and organic material from the top of the mineralization as possible. This organic material reacts with NaOH in the refinery to produce oxalates, which are deleterious to the process. After scrapers have removed the topsoil and overburden, two small (60t class) excavators equipped with swivel buckets are used to scrape clay containing organic material from the undulating surface of the hardcap that sits on top of the mineralization. This is later used to backfill mined out areas.

Figure 13‑1: SOBR (SLR, 2021)

The SOBR process is applied to those areas where hardcap has been identified by Resource definition drilling, using the drillers’ logs. The hardcap is drilled and blasted before mining with the rest of the bauxite sequence.

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In areas without hardcap, wheel tractor-scrapers of 24 m³ capacity remove soil overburden, scraping directly to the top of the mineralization model surface, being controlled by GPS. This material is similarly stockpiled for rehabilitation or used as backfill in exhausted mining areas.

Figure 13‑2: Topsoil removal (background), blasting of hardcap and marking of ore (foreground) (SLR, 2021)

A surface miner is employed in limited areas of hardcap in the vicinity of blasting-sensitive infrastructure such as power lines. The surface mining is also employed in lieu of SOBR where appropriate, for example, where there are high levels of contaminants in the hardcap.

14.1.4

Mining

Mining progresses on 4 m benches, utilizing a contour-mining sequence, cutting benches across the topography, working from top to bottom, maintaining the flattest floor obtainable to a maximum gradient of 1:7. Most of the mineralization lies beneath a gently undulating topography and contour mining is minimal.

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Figure 13‑3: Contour mining (SLR, 2021)

On completion of overburden removal, the exposed surfaces are sheeted with 0.25 m of suitable mineralized material taken from the dozed second cut in adjacent pits. Where hardcap is present, a drill rig is mobilized, and the hardcap drilled and blasted on an appropriate pattern to fragment the hardcap.

Trucks haul the mined ore to fixed crushers, which crush the material to varying sizes (refer to Section 14.0) before conveying down the escarpment to the refinery where it is stockpiled to give surge capacity.

No visual grade control is applied, the ore contacts being gradational. Grade control is achieved by mining to electronic ore surfaces derived from drill assays, control being achieved using GPS equipped equipment, the GPS being regularly calibrated.

Blending takes place at the pit face, before which the crushed ore from different pits is assessed using specialist short-term mine planning software and pit production is scheduled to achieve the desired blend.

The SLR QP is of the opinion that considering the style of mineralization, the average depth of the deposit, and the material characteristics of the overburden material whereby it is amenable to ripping / excavation using conventional earth-moving equipment, the open pit mining method adopted at Darling Range is the most appropriate method for the Mineral Reserves.

14.2	Haul Roads and Infrastructure

14.2.1

Haul Roads

Haul roads are the limiting factor to the mining operations. Major haul roads are established to each mining area, honoring the topography at the least possible gradient. Roads are unsealed and formed by conventional bulldozer and grader and sheeted with appropriate material. Once established, haul road

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maintenance was observed to be continuous and forms part of the operating cost for each mining area. Haul roads are observed by the QP to be treated as sustaining capital in an appropriate manner.

Figure 13‑4: Truck on haul road (SLR, 2021)

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Figure 13‑5: Haul roads with berms (SLR, 2021)

Secondary haul roads to individual mining areas are formed in the same manner, with provision for rehabilitation once mining is complete.

The Darling Range climate is subject to wet winter months and trafficability of haul roads during these months is included in mine planning. Redundancy during wet months is planned for, allowing well drained areas to be mined in the wet.

There are some restrictions to the establishment and operation of haul roads, and these are incorporated into the road design and operation:

•

Water runoff from the roads is impounded in sumps and these were observed to be well formed and appropriate, being regularly dewatered, emptied of sediment and cleaned. This water is either re-used for dust suppression or road-forming purposes or is decanted for release in an approved manner.

•

Dieback control necessitates separation of machinery between that which operates in dieback-prone and dieback-free areas. This presents short-term scheduling challenges that were observed to be well controlled.

•

Proximity to a major water catchment restricts the volume of hydrocarbons that may be taken into particular areas around the catchment. This was observed to be adhered to, with particular road rules and scheduled delivery of approved volumes of hydrocarbons along haul roads that are specially formed with impoundments in the event of spillage.

The Qualified Person has observed that Alcoa’s Darling Range operations have a well-established system for haul road design, construction, maintenance and regulation and that this does not present a major impediment to mining efficiency.

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14.2.2

Infrastructure

The main elements of infrastructure at Alcoa’s Darling Range mining operations are the location of crushers and conveyors to the refineries. These crushers form hubs for the mining operations, connected by the primary haul roads and are scheduled to be moved every ten years or so, in accordance with the requirements of the mining schedule and the location of ore as the mines progress. This crusher movement is planned well in advance and is treated as sustaining capital expenditure.

The crushers see relatively light duty for a mining operation and are well maintained. Similarly, the conveyors, which operate all year round and are covered, negating any potential effect of weather.

Figure 13‑6: Covered conveyor (SLR, 2021)

Both the crushers and conveyors were observed to be in excellent condition and subject to scheduled maintenance, including replacement of conveyor belts.

Other ancillary equipment includes offices, ablutions, crib-rooms, and workshops, all of which were observed to be in excellent condition.

14.3	Geotechnical and Hydrogeology Considerations

Mining at Alcoa’s Darling Range operations is very shallow, pits being an average of 4 m deep. Consequently, geotechnical considerations are negligible other than immaterial localized batter failures. Similarly, the mining areas are elevated and well drained and groundwater and surface water hydrology is not material in these areas other than the catchment, impoundment, and decantation of runoff during the wet winter months. No drainage diversion occurs or is necessary because the mineralization sits between the stream beds and the bauxite occurs above the groundwater table. Deeper bauxite may be

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seasonally affected by the water table and is scheduled to be mined in summer. Backfilling of these places occurs before the rain raises the water table.

Contour mining (Figure 13‑7) is practiced in areas of relatively steep topography, maintaining access ramps at less than 1:8 gradient and mining across the contour and downwards, creating a flat working floor. Hydrological considerations in these areas include management of runoff during the wet winter months and trafficability.

Figure 13‑7: Contour Mining (SLR, 2021)

Mine overburden is progressively backfilled into adjacent exhausted pits (Figure 13‑8), topsoiled, landscaped (Figure 13‑9), and rehabilitated by re-establishment of native vegetation (Figure 13‑10), creating a stable post-mining landform that replicates the pre-existing environment.

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Figure 13‑8: Soil being returned for backfilling and landscaping the pit (Alcoa, 2018)

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Figure 13‑9: Landscaped mining area, prior to replanting of forest (SLR, 2021)

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Figure 13‑10: Rehabilitated pit through re-plantation of native vegetation (SLR, 2021)

14.4	Mine Equipment

Mining is undertaken by 300 t and 200 t-class excavators top-loading 190 t capacity rigid-bodied mining trucks (Figure 13‑11). This fleet was observed by the QP at Huntly to be aged. The equipment has undergone relatively light duties for a mining fleet, which prolongs its life. Sustaining capital is being invested in equipment replacement and modernization at Willowdale, progressively working toward Huntly. New equipment includes 250 t-class excavators and 190 t-class trucks.

A full list of equipment at Darling Range is provided in Table 13‑1.

Figure 13‑11: Ore mining at Darling Range (SLR, 2021)

Table 13‑1: Darling Range operations equipment list


Location	Classification	Type	No. Units
Huntly	Primary	Excavator	4x CAT 336D 3x Komatsu PC3000 1x Hitachi 2600-7
		Haul truck 1	8x CAT 789C (190T) 9x CAT 789D (190T) 1x Komatsu 730E (190T)
		Haul truck 2	1x HD1500 (150T)
	Ancillary	Bulldozer / Loader	3x CAT D11R 1x D575 1x CAT 992K 2x CAT 993K 2x WD600 2x WA600
		Grader	2x CAT 16M 1x CAT 24M
		Scrapers	5x CAT 637G
		Low Loaders	1x CAT 785C (250T) 1x CAT 777G (150T)
		Water truck	3x CAT 785C
		Drills	3x Atlas Copco L6 (Blast) 5x WB93 (Exploration)
Willowdale	Primary	Excavator	2x CAT 336D 2x Komatsu PC2000
		Haul truck 1	14x Komatsu 730E (190T)
		Haul truck 2	1x HD1500 (150T)
	Ancillary	Bulldozer / Loader	2x CAT D11T 1x CAT 993K 1x CAT 992G 1x Volvo L90
		Grader	1x CAT 16H 1x CAT 18M
		Scrapers	3x CAT 637G 1x CAT 637E
		Low Loaders	1x CAT 785D (220T)
		Water truck	2x CAT 777F 1x Komatsu 730E
		Drills	2x Epiroc D50 (Blast)

14.4.1

Contractors

Alcoa’s practice in noise sensitive areas such as the perimeter of the operation near residents is to engage contractors. These areas operate on day shift only and attract higher operating costs than the main production areas. The flexibility required in these areas precludes the use of the primary owner-operator

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fleet and equipment is dry or wet hired or mining takes place under conventional schedule of rates contracts.

Alcoa also engages contractors for aspects of haul road construction services, in select areas of pit development, and during landscaping activities for rehabilitation after mining.

This practice has led to the establishment of a secondary contracting industry around the Darling Range operations. Contractors are overseen by Alcoa personnel.

14.4.2

Ancillary Equipment

Ancillary equipment at Alcoa’s Darling Range operations includes a fleet of bulldozers, graders and loaders that are primarily used for haul road formation, pit development (for the removal of overburden and blasted caprock) and ground preparation for digging, landscaping, clean-up, and road maintenance.

The SOBR process requires small excavators, articulated trucks, scrapers, and specialist skills to grub organic-containing clay from the top of the mineralization.

Figure 13‑12: Blasthole drill working on hardcap (SLR, 2021)

All ancillary equipment was observed to be in good and well-maintained conditions, the conditions being relatively light duty in comparison to other Western Australian mining operations.

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14.5

Personnel

The main production mining operations are primarily Owner-operated using Alcoa equipment and employees. Contractors are also used for certain activities on site.

Three unions are recognized at the operations:

•

The Australian Workers Union (AWU), which covers most of the operations workers

•

Australian Metal Workers Union (AMWU), which covers the metal trades, being fitters, boilermakers and mechanics

•

Electrical Trades Union (ETU), which covers the electricians

Lost time during strikes is generally uncommon. An agreement with AWU that was made in late 2018 and ratified by Fair Work Australia in early 2019 is in place for a four-year period.

Alcoa’s Darling Range operations were observed to have a stable workforce, drawn from the surrounding areas. The location is highly desirable in the Western Australian mining context and skilled personnel are readily attracted to the operations. Primary haul roads are named after personnel with greater than forty years’ service and there are many of these.

A breakdown is shown in Table 13‑2 (current vacancies not accounted for).

Table 13‑2: Darling Range personnel


Location	Classification	No Personnel
Huntly 557	Technical	50
	Management	66
	Operations	441
Willowdale 301	Technical	42
	Management	66
	Operations	193
Central 32	Technical	21
	Management	7
	Operations	4
Total		890

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15.0	Processing and Recovery Methods

15.1	Process Description

The process plant for the Darling Range operations consists of two separate crushing facilities at the Huntly and Willowdale mines. Both facilities crush the ROM and convey the crushed ore to three separate refineries.

The Willowdale operation consists of a single stage crushing flowsheet and includes a series of conveyors to transport the crushed ore at an annual throughput of 10 Mtpa. The ROM is discharged from trucks on a dump hopper. An apron feeder transfers the ore from the dump hopper to a vibrating grizzly with an aperture of 180 mm. The grizzly oversize is discharged into a single toggle jaw crusher which crushes the ore to a top size of 180 mm. A hydraulic rock breaker is installed at the crusher to break the larger rocks that do not pass through the crusher opening. The crushed product and the grizzly undersize are discharged on to a discharge conveyor and subsequently discharged on to an overland conveyor. The discharge conveyor is fitted with a tramp magnet to remove any metal that is present along with the crushed ore product. The overland conveyor, which is 9.4 km long, transports the crushed ore to an intermediate transfer station. The ore is then transported by a second overland conveyor, 8.8 km long, to the transfer station located at Wagerup. An apron feeder is used to transfer the crushed ore from the Wagerup transfer station on to a stockpile conveyor and subsequently discharge on a stacker conveyor. The stacker conveyor discharges the ore into two separate stockpiles. The crushed ore is then reclaimed from there for processing in the Wagerup refinery. The total capacity of the stockpiles is approximately 0.7 Mt and sufficient for three weeks of feed to the refineries.

A simplified block flow diagram of the Willowdale operation is shown in Figure 14‑1.

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Figure 14‑1: Simplified block flow diagram of the Willowdale operation

The Huntly operation consists of multiple stages of crushing and includes a series of conveyors to transport the crushed ore to the refineries at an annual throughput of 25 Mtpa. The primary crushing is achieved by two similar crushing circuits operating in a parallel configuration. The ROM is discharged from trucks on dump hoppers. Apron feeders transfer the ore from the dump hopper to vibrating grizzlies with an aperture of 180 mm. The grizzly oversize fractions are fed to jaw crushers which crush the ore to a top size of 200 mm. The crushed product and the grizzly undersize are discharged on to discharge conveyors and transferred to the secondary crushers (sizers). The discharge conveyors are each fitted with a tramp magnet to remove any metal that is present in the crushed ore. Secondary crushing is achieved in sizers with the objective of reducing the ore particle size to a top size of 100 mm. The secondary crusher product is transported by three overland conveyors (operating in series with two intermediate transfer stations in between) to a transfer station and randomly split into two by a splitter bin.

One fraction from the splitter bin is transferred by another overland conveyor and discharged into a stockpile conveyor via an apron feeder. The stockpile conveyor transfers the ore and subsequently discharges onto a stacker conveyor. The stacker conveyor discharges the ore into two separate stockpiles identified as Stockpile 1 and Stockpile 2. The crushed ore is then reclaimed from there for processing in the Pinjarra refinery. The second fraction of the ore is transported by an overland conveyor to an apron feeder, to a transfer conveyor and then split again to two fractions by a splitter chute located at a separate transfer station. One of the splits from the splitter chute is destined for Kwinana refinery and the other split is destined for Pinjarry refinery.

The fraction for the Pinjarra refinery is transported by stockpile conveyor and subsequently discharged on to two sperate stockpiles (identified as Stockpile 3 and Stockpile 4) via a stacker conveyor. The ore is then

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reclaimed from the stockpiles for processing in Pinjarra refinery along with the ore from Stockpile 1 and Stockpile 2.

The split for Kwinana refinery is transported by a conveyor and processed by a tertiary crushing circuit consisting of two roller crushers operating in parallel configuration. The tertiary crusher product with a top size of 25 mm is transferred by a stockpile conveyor and discharged into two separate stockpiles identified as Stockpile 5 and Stockpile 6 via a stacker conveyor. The crushed ore from Stockpiles 5 and Stockpile 6 is reclaimed and transferred by a reclaim conveyor to a surge bin for subsequent loading and transport to the refinery by train. A simplified block flow diagram of the Huntly operation is shown in Figure 14‑2.

Figure 14‑2: Simplified block flow diagram of the Huntly operation

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15.2	Primary Equipment List

The primary equipment lists of the Willowdale, and Huntly operations are shown in Table 14‑1 and Table 14‑2.

OhTable 14‑1: Primary equipment list (Willowdale)


Equipment	Quantity	Installed Power (kW)
Apron feeder	1	264
Vibrating grizzly	1	75
Primary Crusher	1	355
Discharge conveyor	1	132
Overland conveyor	1	2500
Overland conveyor	1	1800
Apron feeder	1	75
Stockpile conveyor	1	300
Stacker boom conveyor	1	110

Table 14‑2: Primary equipment list (Huntly)


Equipment	Quantity	Installed Power (kW)
Apron feeder	1	260
Vibrating grizzly	1	55
Primary Crusher	1	250
Discharge conveyor	1	140
Secondary crusher	1	1000
Apron feeder	1	260
Vibrating grizzly	1	75
Primary Crusher	1	250
Discharge conveyor	1	140
Secondary crusher	1	1000
Overland conveyor	1	7500
Overland conveyor	1	5000
Overland conveyor	1	6100
Apron feeder	1	75
Overland conveyor	1	1500
Apron feeder	1	55

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Equipment	Quantity	Installed Power (kW)
Apron feeder	1	75
Overland conveyor	1	1350
Apron feeder	1	110
Stockpile conveyor	1	225
Stacker boom conveyor	1	110
Yard conveyor	1	250
Stockpile conveyor	1	150
Stacker boom conveyor	1	110
Conveyor	1	250
Apron feeder	1	75
Tertiary crusher	1	370
Apron feeder	1	75
Tertiary crusher	1	370
Stockpile conveyor	1	300
Stockpile boom conveyor	1	110
Bucket wheel reclaimer	1	264
Reclaim bridge conveyor	1	110
Transfer conveyor	1	280
Reclaim conveyor	1	280
Reclaim conveyor	1	900

15.3	Consumables and Power

The power consumption of the Huntly operation is approximately 8,000 MWh to 9,000 MWh per month. The Willowdale power consumption is approximately 2,000 MWh per month.

Other consumables of the process plant include crusher liners, screen panels and spares for feeders and conveyors. These are kept on site and replaced as part of the routine maintenance schedule according to manufacturer’s guidelines.

Personnel requirements for the operation and maintenance of the plant as described are included in Table 13‑2.

15.4	QP Opinion

SLR has the opinion that selected processing method and the flowsheet is suitable for Darling Range operations. It is important to note that the ore head grades meet the refinery specifications for processing

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in terms of Al₂O₃ grades and SiO₂ grades, this means the ore can be directly shipped to the refinery for further processing without any upgrading in the mineral processing plant. The crushing circuit reduces the particle size suitable for conveying as well as to meet particle size specified by the refinery.

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16.0	Infrastructure

The mining hubs are relocated periodically as production moves away from the hub and thus transportation costs increase. Alcoa plans for the Larego Hub to be in place for approximately 20 years, though this is the 4^th relocation since the mines opened in the 1970s/80s (approximately 13 years on average). The mining hub relocations are well-understood with planning and associated budgeting occurring well in advance of relocations; production restarted seven days after the shutdown.

An extensive haul road network, rail, and overland conveyors transport crushed bauxite from the Hub to the refineries on the coast (namely Kwinana, Wagerup and Pinjarra). Bauxite is transferred from each mine to the refineries primarily via long distance conveyor belt, apart from the Kwinana refinery which receives bauxite via railway. The Alumina produced by the three refineries is then shipped to external and internal smelter customers through the Kwinana and Bunbury ports.

The infrastructure layout for the Darling Range operations is shown below (Figure 15‑1).

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Figure 15‑1: Infrastructure Layout (Alcoa, 2022)

16.1	Access Roads

The Darling Range is readily accessible via road from Perth and surrounding areas. The mines are near the towns of Pinjarra and Waroona. Both towns are easily accessible via the national South Western Highway, a sealed single carriageway road, which starts on the southern side of Perth and continues for almost 400 km to the southwest corner of Western Australia.

The Huntly mining area is accessible from the South Western Highway via Del Park Road, a sealed single carriageway road which connects the town of North Dandalup in the north with Dwellingup in the south. From Del Park Road, a further sealed road which follows the route of the bauxite conveyor to the Pinjarra refinery provides access to the Huntly site.

The Willowdale mining area is similarly accessible from the South Western Highway via Nanga Brook Road, a sealed single carriageway road to the east of Waroona.

Major haul roads have been established to each mining area. Roads are unsealed and require continuous ongoing maintenance which was observed during the site visit. Secondary haul roads, also unsealed, cross-cut each individual mining plateau.

16.2

Power

Willowdale Mine has a single 22 kV power supply fed from the Wagerup refinery. The Wagerup refinery is a net exporter of power to the SWIS, with internal generation capacity of 108 MW from three steam driven turbine alternators and one gas turbine. The steam is produced by gas fired boilers.

The power consumption of the Huntly operation is approximately 8,000 MWh to 9,000 MWh per month. The Willowdale power consumption is approximately 2,000 MWh per month.

16.3

Water

Water is used on the mines for dust suppression, dieback washdown, vehicle washdown, workshops, conveyor belt wash, construction, and domestic purposes. The water supplies for mining consist of licensed surface water sources supplemented with treated wastewater from vehicle washdowns, stormwater runoff and maintenance workshops.

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Table 14‑2 summarizes the license allocation for water usage. In 2020, water abstraction comprised approximately 15% of the total DWER license allocation (for those sites where abstraction occurred). An additional 534,975 kL was also abstracted from South Dandalup Dam under the agreement with Water Corporation.

Table 15‑1: Water Abstraction License Volumes

Site	Water source	Surface Water license	Annual Water Entitlement
Huntly	South Dandalup Dam	N/A	N/A
Huntly	Banksiadale Dam	SWL63409	500,000
Huntly	Pig Swamp Waterhole	SWL153635	30,000
Huntly	Boronia Waterholeon Marrinup Brook	SWL83356	70,000
Marrinup Nursery	Lot 908 on Marrinup Brook	SWL68893	45,000
Willowdale	Samson Dam	SWL61024	450,000

16.4	Accommodation Camp

On site facilities includes offices, ablutions, crib-rooms, and workshops, all of which were observed to be in excellent condition.

16.5	Mine Waste Management

16.5.1

Tailings disposal

16.5.2

Waste rock disposal

Alcoa’s Darling Range mining operations do not produce mine waste or “mullock” in the same manner as conventional mining operations and waste dumps are not constructed.

Overburden from Darling Range ore blocks is carefully segregated for later rehabilitation of adjacent, completed mining operations. Non-viable rock is used to backfill these shallow, completed pits and the viable topsoil spread on top and contoured. Jarrah forest is then re-established through seeding and the planting of nursery-raised seedlings. Water runoff from active and backfilled mining areas is contained and directed toward settlement ponds, which are later rehabilitated and seeded.

To date, some 20,000 ha of mined areas have been backfilled and reforested, which represents 77% of the area mined since 1966, including areas reserved for long-term infrastructure. Rehabilitation standards

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are described in Alcoa’s 2016 statutory Bauxite Mine Rehabilitation Completion Criteria. These completion criteria have been progressively revised since inception in the 1990s.

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17.0	Market Studies

17.1

Overview

Alcoa Corporation is a vertically integrated aluminum company comprising bauxite mining, alumina refining, aluminum production (smelting and casting), and energy generation.

Aluminum is a commodity that is traded freely on the London Metal Exchange (LME) and priced daily. Pricing for primary aluminum products is typically composed of three components:

(i)

The published LME aluminum price for commodity grade P1020 aluminum;

(ii)

The published regional premium applicable to the delivery locale; and

(iii)

A negotiated product premium that accounts for factors such as shape and alloy.

Further, alumina is subject to market pricing through the Alumina Price Index (API), which is calculated by the Company based on the weighted average of a prior month’s daily spot prices published by the following three indices: CRU Metallurgical Grade Alumina Price; Platts Metals Daily Alumina PAX Price; and Metal Bulletin Non-Ferrous Metals Alumina Index. As a result, the price of both aluminum and alumina is subject to significant volatility and, therefore, influences the operating results of Alcoa Corporation.

Unlike alumina and aluminum, bauxite is not a standard commodity traded on an index. Bauxite’s grades and characteristics vary significantly by deposit location and the value of bauxite deposits for each downstream refinery could be different, based upon:

•

refinery technology;

•

the location of each refinery in relation to the ore deposit; and

•

the cost of related raw materials to each refinery.

As such, there is no widely accepted index for bauxite. Most bauxite traded on the third-party market is priced using a value-in-use methodology. The key assumption for the value-in-use methodology is that both the (1) offered bauxite and the (2) comparative bauxite being used in the target refinery will generate the same refining cost. As such, using the known price for the comparative bauxite used in the target

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refinery, the offered bauxite price will then be derived by considering the bauxite characteristics and quality differences between the offered and comparative bauxite.

17.1.1

Market Fundamentals

Bauxite is the principal ore of alumina (Al₂O₃), which is used to produce aluminum. Bauxite mining and alumina refining are the upstream operations of primary aluminum production. China is the largest third-party seaborne bauxite market and accounts for more than 90% of all bauxite traded. Bauxite is sourced primarily from Australia, Guinea, and Indonesia on the third-party market. In the long run, China is expected to continue to be the largest consumer of third-party bauxite with Guinea expected to be the majority supplier. Further, third-party traded bauxite is expected to be in surplus over the next decade, with most new mining projects announced recently being located in Guinea.

17.2	Market: Darling Range

17.2.1

Operation

The Darling Range mines are part of an integrated operation of two mines, three refineries and two ports. Prior to 2016, production from the Darling Range mines (Huntly and Willowdale) was used exclusively for consumption by the integrated refineries.

Bauxite is transferred from each mine to the refineries primarily via long distance conveyor belt, apart from the Kwinana refinery, which receives bauxite via railway. The Alumina produced by the three refineries is then shipped to external and internal smelter customers through two ports, based in Kwinana and Bunbury.

17.2.2

Pricing

As discussed in Section 16.2.1 above, all Western Australia bauxite production will be sold internally to Western Australia refineries following the expiration of the third-party sales contract in 2021. In 2021, the Western Australia internal bauxite transfer price referenced this third-party sales contract as a three-year trailing average.

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17.3

Contracts

All Darling Range production is shipped via conveyor or train to one of the Alcoa’s three Western Australia refineries.

Major operational contracts that are in place include, but are not limited to the following:

•

Railway contract: Alcoa has a long-term contractual agreement with a third-party to deliver bauxite to one of its refineries. Pricing is based on a fixed rate schedule, payable on volume of bauxite delivered.

•

Mining contractor contract: Alcoa has a long-term contractual agreement with a third-party to operate a designated mine region. The contractor is responsible for development, mining, hauling and rehabilitation of the designated mine pits; the contract runs a day-only operation. Pricing is based on a fixed rate schedule, payable on production tonnes.

•

Rehabilitation contract: Alcoa has a long-term contractual agreement with a third-party to rehabilitate certain mined areas, ready for closure. Pricing is based on a fixed rate schedule, payable on equipment and labor hire rates.

•

Fuel contract: Alcoa has a mid-term contractual agreement with a third-party to supply diesel fuel for mining operations. Pricing is based on market pricing for diesel, payable on volume consumed.

These types of contracts are typical of other similar mining operations.

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18.0	Environmental Studies, Permitting, and Plans, Negotiations, or Agreements with Local Individuals or Groups

18.1	Environmental Studies

Alcoa has established practices and processes for ensuring conformance to environmental requirements. Sensitive areas are identified and managed ahead of disturbance. Environmental factors are taken into account prior to infill drilling; hence, mining blocks carrying environmental risks do not feature in the Mineral Reserves (for example, areas around granite outcrops and water courses have a buffer applied and essentially no-go areas from a mining perspective).

The environmental reviews and approvals form part of the MMPLG approvals process outlined in Section 3.6.

Additional baseline studies are understood to be in progress to support the Environmental Protection Act 1986 (WA) and the Environment Protection and Biodiversity Conservation Act 1999 (Cth) approvals for future extensions to the mining footprint. Baseline studies are guided by the requirements of the Environmental Protection Authority (WA) and are well understood.

The threat of bushfires is the only significant naturally occurring risk identified. Bushfires have occurred in the past, but to date have not had a material impact on production.

The current plans are considered adequate and there are no other environmental, social, or permitting risks that affect mine operability or Reserve estimation. Risk of environmental approvals not being received are very low due to the nature of the state agreement and the environmental constraints on the resource itself being applied before deposit definition drilling (i.e. only includes material above the water table, that does not require redirection of surface water courses, impact heritage listed sites, etc).

18.2	Waste and Tailings Disposal, Site Monitoring, and Water Management

18.2.1

Waste and Tailings Disposal

No tailings are generated within the boundaries of the mining operations as bauxite processing residue is only generated at the refineries. Similarly, Alcoa’s Darling Range mining operations do not produce mine waste or “mullock” in the same manner as conventional mining operations and as such waste dumps are not constructed.

Overburden from Darling Range ore blocks is carefully segregated for later contouring and rehabilitation of adjacent, completed mining operations. Caprock and other non-viable rock is used to backfill these shallow, completed pits and the viable topsoil spread on top, contoured, and revegetated.

As such, there is no requirement for the monitoring of any tailings or mine waste dumps associated within the mining operations as all tailings are processed outside the mine lease boundary.

18.2.2

Site Monitoring

Alcoa’s mine sites are monitored in accordance with conditions of Government authorizations and its operational licenses at Huntly (L6210/1991/10) and Willowdale (L6465/1989/10). Environmental

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management and monitoring commitments exist for the following environmental aspects which have been assessed as being significant and therefore require operational controls as a minimum. The significant environmental aspects for which monitoring and/or management undertaken are:

•

Chemical releases including loss of containment prevention and response and dangerous goods storage. All underground storage tanks have been removed from Alcoa’s operations and are prohibited.

•

Waste management and minimization.

•

Catchment protection through the management of mining within the lower rainfall zone to minimize risks of salinization of land and water resources.

•

Water as detailed in Section 17.2.3

•

Air emissions including:

Smoke pollution associated with wood waste

An ambient dust monitoring program to identify and quantify fugitive dust emissions from operating areas

Ozone depleting substances

•

Hazardous materials management including asbestos, synthetic mineral fiber, polychlorinated biphenyls

•

Land including:

Recordkeeping and Geographical Information System (GIS) mapping of the location and timing of all soil removal, landscaping, soil return, ripping and seeding

Rehabilitation area monitoring to ensure the number of established plants meet the completion criteria targets associated with species enrichment, weed outbreaks and erosion

Dieback management, mapping and field identification

Forest and land clearing

•

Flora and fauna.

•

Aboriginal and European heritage.

•

Environmental value of national parks, nature reserves and native forests.

•

Visual amenity.

•

Noise.

Outcomes of and compliance with the management and monitoring programs are tracked within Alcoa’s Environmental Management System and reported within the Annual Environmental Review report. Review of the most recent report, published as a triennial report for the period from 2018 to 2020 largely reported compliance with environmental commitments and success of operational controls to managed environmental objectives with only the following non-compliances noted:

•

Several dieback breaches were reported resulting in a downgrade to dieback status of vegetation, the majority of which were associated with drainage failures following significant rainfall events

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resulting in surface water flow from dieback areas into dieback free areas. All incidences were investigated with corrective actions addressing the root causes actioned.

•

Several recordings of elevated turbidity were recorded for a period exceeding 1 hour above the reporting criteria (25 NTU), however only a small fraction of these events was confirmed to have a contribution from mining activities. All incidences were investigated with corrective actions addressing the root causes actioned where mining contributions were identified.

•

Alcoa reported one incident under Section 72 (s.72) of the Environmental Protection Act 1986 in 2019, and ten incidents in 2020. During the reporting period, Alcoa commenced voluntary reporting of the releases of C6 Aqueous Film Forming Foams (AFFF) to unsealed operational areas, due to low-level presence of per- and polyfluoroalkyl substances (PFAS). The Huntly mine reported two AFFF releases, one turbidity event and one release of hydrocarbon contaminated stormwater. Willowdale mine reported three releases of wastewater containing low concentrations of PFAS and four AFFF releases. Alcoa has since developed and implemented an Interim PFAS Water Management Strategy across its WA mining operations with the key commitment to manage PFAS affected water to minimise impact to the drinking water catchment and the environment.

Alcoa is proactively working with key regulatory agencies to address operational non-compliances and implement operational improvements to reduce releases to the environment. None of the reportable non-compliances represent a risk that could adversely affect its license to operate.

18.2.3

Water Management

Alcoa implements a comprehensive water management and monitoring program in accordance with the requirements of its abstraction and operational licenses. Key components of Alcoa’s water management and monitoring program include:

•

Treatment of stormwater that may contain traces of hydrocarbons via a wastewater treatment system to concentrations that meet DWER license requirements prior to release

•

Turbidity monitoring along tributaries to key catchments to prevent contaminated or turbid runoff into the drinking water supply

•

Wastewater treatment and monitoring to meet DWER license requirements prior to release including treated water quality monitoring prior to release and continuous discharge volumes

•

Surface water drainage management to prevent uncontrolled surface water runoff from operations to the surrounding forest and/or surface water bodies

•

Implementation of the Interim PFAS Water Management Strategy

•

Drainage protection management through the implementation of a Water Resource Sensitive Zone Management Plan

•

Sewage management though a biological aeration treatment unit (BioMAX)

•

Monitoring of cumulative water abstraction volumes at licensed and unlicensed surface water abstraction points in accordance with the Surface Water License Operating Strategies for Huntly and Samson Dam

•

Potable water monitoring for identification of possible biological or chemical contamination

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•

Ecological water requirements (EWRs) have not been defined for the site however, Alcoa undertakes monitoring of the downstream environments to ensure no unacceptable impact. This is completed via photographic monitoring for Banksiadale Dam, Pig Swamp Waterhole, Boronia Dam and Marrinup Nursery

•

Water use efficiency programs are implemented pertaining to wastewater recycling, efficient watering of haul roads, pumping and reusing water from roadside sumps, and effective mining planning to reduce dust suppression requirements

Alcoa’s WA Mining operations have no groundwater monitoring programs associated with legislation, licenses, or approvals. Additional groundwater monitoring may be required if:

•

Groundwater quality or quantity has been identified as potentially at risk due to mining activities, or

•

Potential exists for mining to impact offsite/private groundwater supply quantity or quality.

Alcoa has a long-term groundwater research project within the Intermediate Rainfall Zone to evaluate potential impacts of clearing on groundwater salinization.

18.3	Project Permitting

The environmental reviews and approvals form part of the MMPLG approvals process outlined in Section 3.6. Compliance with the MMPLG is demonstrated through an annual report submitted to the Department of Jobs, Tourism, Science and Innovation.

Operational matters at the Willowdale and Huntly mines are licensed by the Department of Water and Environmental Regulation via instruments L6465/1989/10 and L6210/1991/10, respectively. These licenses condition the processing of ore and reporting is required annually to DWER describing the total volume of bauxite crushed and any non-compliance. The latest available reporting at the time of writing is for calendar year 2020.

Compliance with the Alcoa ISO14001 accredited EMS was audited in December 2021, with recertification expected in April 2022.

There are no known requirements to post performance or reclamation bonds.

18.4	Social or Community Requirements

Alcoa has established systems and processes for maintaining its social license to operate and was admitted to ICMM in 2019, aligning to its social performance requirements. Related to the requirements of the MMPLG, Alcoa’s actions in relation to social performance include an annual 5-year consultation process aligned with the 5 Year Mine Plan. The consultation process involves engaging with affected landowners. Alcoa’s consultation extends to shires, as well as state and local government members.

Where appropriate, the mine plan accommodates community requirements, in particular, concerns related to noise, dust, etc., and allows for buffer zones and modified working hours.

Community consultation results (both in-bound [e.g. noise complaints] and out-bound [e.g. Alcoa-initiated engagement with stakeholder groups]) are recorded in the Community Consultation System (CCS). Annual targets for consultation are set based on current and proposed mine plans. CCS allocates and tracks follow-up actions.

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A stakeholder perception survey was undertaken in 2021; results were not available for consideration at the time of writing. The move towards formal, publicly scrutinized environmental impact assessment and approval under the State and Federal acts (section 3.6) is considered likely to expand the focus of consultation beyond the previous “neighbor” approach to a broader approach, more consistent with that expected from other major mining operators in the State of WA.

As described in 17.1, the threat of bushfires is a risk to operation and the local communities. Bushfire mitigation and firefighting activities within state forest are managed by the Department of Biodiversity Conservation and Attractions (DBCA). Alcoa maintains fire access tracks as required by the working arrangement with DBCA and complies with requirements of the Bushfires Act including seeking exemptions for certain activities during Total Fire Bans. Asset protection zones are not mandated although Alcoa do maintain them around infrastructure as per internal standards to mitigate risk.

Alcoa owned private property is maintained to local government requirements as per the requirements of the Bushfire Act.

Alcoa operations look to add value to the communities where it operates and beyond. Through a drive for sustainable development and desire to support reputable non-profit and community based organizations, community investment supports partnerships and initiatives that look to long-term community benefits.

Each year the community partnership program invests in a wide variety of community programs at the local, state and national level. Some of these partnerships, including the acclaimed Three Rivers, One Estuary initiative are supported by Alcoa’s global Alcoa Foundation.

The strategic focus is on partnerships targeting one or more of the following categories:

•

Sustainable environment

•

Community health and safety

•

Community capacity and resilience

•

Tomorrow’s workforce and leaders

In addition to community partnerships, employees are encouraged to participate each year in Alcoa Volunteers (volunteering as teams during work time) and employee giving programs.

18.5	Mine Closure Requirements

The agreed closure requirements for Darling Range centres around the return of Jarrah Forest across the site. End land uses are required to comply with the State’s Forest Management Plan and include water catchment protection, timber production and biodiversity conservation. Closure criteria were revised in 2015 by the MMPLG for rehabilitation works commencing in and after 2016. These criteria do not apply to areas which commenced rehabilitation prior to 2015, and represent a ‘step forward’ in rehabilitation practices at Darling Rage. The criteria are structured into the following broad steps, with documented guidelines for acceptance, standards and corrective active actions:

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•

Planning

•

Rehabilitation Earth Works

•

Early Establishment – first 5 years

•

Vegetation 12 years and Over.

As described in Section 15.5.2, overburden is used to backfill adjacent, completed mining operations and the topsoil spread on top and contoured. Maximum slopes (angle and length) are defined in the 2015 Criteria. If topsoil has been harvested and stored for up to three months prior to use as a rehabilitation input is it considered ‘direct-return’ and seeding may not be undertaken. If it is older than 3 months it is considered ‘fallow’ and requires seeding. Nursery-raised seedlings are also used in rehabilitated areas.

Current rehabilitation practices and closure planning have evolved positively since the 1990s.

Mine closure costs are described in Section 18.0.

18.6	Local Procurement and Hiring

The Alcoa procurement system defines “local” as the localities of Dwellingup, Harvey, Pinjarra, Waroona, Coolup, North Dandalup, and Yarloop. Within Alcoa’s guidelines of safe, ethical, and competitive business practices, they state they will:

•

Invite capable local business to bid on locally supplied or manufactured goods or services.

•

Give preference to local business in a competitive situation.

•

Work with local business interest groups to identify and utilize local suppliers.

•

Where possible, structure bids to enable local supplier participation.

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19.0	Capital and Operating Costs

Alcoa forecasts its capital and operating costs estimates based on annual budgets and historical actuals over the long life of the current operation. All values are presented in United States Dollars ($) unless otherwise stated.

19.1	Capital Costs

The operation is well-established, and the LOM plan does not envisage any significant change of the production rate. Anticipated future major capital expenditure is related to major mine moves and sustaining the on-going operations.

Projected capital expenditure over the next seven years of mine life is estimated to total $349.3 million. Of this total, $160 million is associated with the completion of the mine move to the Myara North site. Capital for the Holyoake move will be incurred from 2027 to 2030 and is not include in this TRS cashflow.

A breakdown of the major expenditure areas and other sustaining capital expenditure over the next seven years of mine life is shown in Table 18‑1.

Table 18‑1: LOM Sustaining Capital Costs by Area

Project	Cost $ Million	Percentage of Total
Myara North Mine Moves	160	62%
Conveyor Belt Replacements	25	7%
Haul Road Improvements	51	15%
Other Sustaining capital	113	32%
Total	349	100%

Other capital costs are for replacement of conveyors, haul road improvements and other sustaining capital needed to continue the operations.

19.2	Operating Costs

The main production mining operations are primarily Owner-operated using Alcoa equipment and employees. Contractors are also used for certain activities on site.

Operating costs for the current LOM of seven years are based on the 2022 budget.

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Table 18‑2: LOM Mine Operating Costs by Category

Cost Centre	2022 ($/wmt)	Average LOM ($/wmt)	Percentage of Operating Cost
Direct Labor	$3.44	$4.26	31%
Services	$1.56	$3.80	27%
Other	$1.73	$2.37	17%
Corporate Chargebacks for support services	$0.53	$0.61	4%
Energy	$0.30	$0.36	3%
Fuel	$0.35	$0.53	4%
Operating Supplies and Spare Parts	$0.61	$0.72	5%
Maintenance (fixed plant and mobile fleet	$1.08	$1.26	9%
Mine Operating Cash Cost ($/wmt)	$9.63	$13.90	100%

Off-site Costs
G & A, selling and other expenses	$0.20	0.18
R & D Corporate Chargebacks	$0.22	0.22
Other Costs of Goods Sold	0.03	0.03
Total Cash Operating Costs	$10.07	$14.33

Table 18‑3 summarizes the current workforce for the operations.

Table 18‑3: Workforce Summary


Category	Technical	Management	Operations	Total
Huntly	50	66	441	557
Willowdale	42	66	193	301
Central	21	7	4	32
Total	113	139	634	890

As regards mine closure, compensation for vegetation clearing is paid in advance and rehabilitation is an ongoing process that is incorporated into the mining cost (as part of Asset Retirement Obligations (ARO)).

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20.0	Economic Analysis

20.1	Economic Criteria

Alcoa prepares a rolling operational Ten-Year Mine plan for the purposes of long-term mine and business planning. The LOM plan is based on mining first the estimated Proven and Probable Mineral Reserves followed by lower confidence Mineral Resources that are expected to be annually converted to Mineral Reserves following further definition drilling, and before the current Mineral Reserves are fully depleted.

In accordance with the requirements of SK-1300, the economic analysis presented in this section of the TRS is based solely on mining the estimated Proven and Probable Mineral Reserves, which generate a current mine life of seven years (2022 to 2028 inclusive) at an average production rate of 34.5 Mtpa.

SLR recognizes that Alcoa undertakes on-going infill drilling to annually convert Mineral Resources to Reserves and based on Alcoa’s long operating history at the mine, the scale of the deposits available and the historic success of resource to reserve conversion, SLR sees no reason why the life of the operation will not be extended well beyond 2027.

The assumptions used in the analysis are current at the end of December 2021.

An un-escalated technical-economic model was prepared on an after-tax DCF basis, the results of which are presented in this section.

The cashflow is presented on a 100% attributable basis. Alcoa uses a 9% discount rate for DCF analysis. SLR is of the opinion that a 9% discount/hurdle rate for after-tax cash flow discounting of such large-scale bauxite operations in Western Australia is reasonable and appropriate.

Key criteria used in the analysis are discussed elsewhere throughout this TRS. General assumptions used are summarized in Table 19‑1.

Table 19‑1: Technical-Economic Assumptions

Description	Value
Start Date	January 1, 2022
Mine Life based on Mineral Reserves	7 years
Average LOM Price Assumption	$25.49
Total Operating Costs	$3,259.8 million
Sustaining Capital over seven years	$349.3 million
Income tax	$867.4 million
Discount Rate	9%
Discounting Basis	End of Period
Inflation	0%
Corporate Income Tax Rate	30%

Table 19‑2 provides a summary of the estimated mine production over the seven-year mine life.

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Table 19‑2: LOM Production Summary

Description	Units	Value
Total ROM Ore	Mt	241.3
Waste Mined	Mt	6.8
Total Material Moved	Mt	248.1
Annual Average Ore Mining Rate	Mtpa	34.5

20.2	Cash Flow Analysis

The indicative economic analysis results, presented in Table 19‑3, indicate an after-tax NPV of $1,315.2 million at a 9% discount rate and an average bauxite price of $25.49/t.

The cashflow is presented on a 100% attributable basis.

Capital identified in the economics is for sustaining operations and plant rebuilds as necessary.

Project economic results and estimated cash costs are summarized in Table 19‑3. Annual estimates of mine production with associated cash flows are provided for years 2022 to 2028, based on Proven and Probable Reserves only.

The economic analysis was performed using the estimates presented in this TRS and confirms that the outcome is a positive cash flow that supports the statement of Mineral Reserves.

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Table 19‑3: LOM Indicative Economic Results

20.3	Sensitivity Analysis

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21.0	Adjacent Properties

The Darling Range has no material adjacent properties.

22.0	Other Relevant Data and Information

No additional information or explanation is necessary to make this Technical Report Summary understandable and not misleading.

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23.0	Interpretation and Conclusions

23.1	Geology and Mineral Resources

•

The large Inferred Resource is sampled at a broad drill spacing. The lower confidence in the estimation of this material means that it is not used in any mine planning or reflected in the Mineral Reserves declared by SLR. However, all this material is considered to be defined by appropriate sampling and constrained so that the QP considers it meets the criteria of having reasonable prospects for economic exploitation. Alcoa has a well-established record of transforming Inferred to Indicated and Indicated to Measured Resources, where appropriate, in a timely manner through further drill sampling. Due to the inherent risks in resource estimation discussed subsequently (see Section 11.13), there can be no expectation that Inferred Resources will ultimately become Measured Resources (or Proven Reserves).

•

Compared to conventional Mineral Resource delineation and reporting practices, the Mineral Resource estimates prepared using the 3DBM and GSM procedures are constrained to material within a notional mine design, using mining criteria (minimum mining height, maximum slope, as discussed in Section 13.0). This may impose a degree of conservatism on the estimates, but this is appropriate because all mine production is tied to local Alcoa alumina refineries. The cut-off grades used to define in situ dry tonnages and report average grades of alumina and silica use procedures designed to reflect the performance of the Kwinana, Pinjarra, and Wagerup refineries. Alcoa has conducted bauxite mining in the region since the mid-1960s and has developed an integrated approach to data acquisition, ore delineation, and mining procedures, which is appropriate for the mineralization characteristics of the ore and the requirements of the local refineries.

•

Alcoa has consistently used drilling, sampling and estimation procedures that are appropriate to the requirement of identifying, delineating, and producing Darling Range ore for their adjacent refineries. The procedures have been progressively improved and modernized over time as industry practices have evolved. While not all data and estimates are at the same standard, the resource classification system indicate the level of confidence of the estimates. All material declared as Mineral Reserves meets the requirements for mine planning to define consistent, appropriate refinery feedstock within the next ten-year planning cycle. All material declared as Measured or Indicated Mineral Reserves is additional material for which there is a reasonable expectation that Mineral Reserves can be defined, contingent on meeting all required Modifying Factors (in short, that it will be economically viable and socially acceptable to mine them at that time).

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•

Specific conclusions reached by the SLR QP and provided in the body of this report in Sections 6, 7, 8. 9, and 11 are aggregated here as follows:

•

In the opinion of the SLR QP, the QA/QC of sample preparation and assaying is adequate and the assay results are suitable for use in Mineral Resource estimation.

•

It is the opinion of the SLR QP from the studies on FTIR repeatability discussed above that the overall precision and accuracy of the FTIR assaying is acceptable.

•

The SLR QP is of the opinion that the database is adequate and the data is appropriate for the purpose of Mineral Resource estimation.

•

23.2	Mining and Mineral Reserves

•

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•

23.3	Mineral Processing

•

Based on this, and additional information provided by Alcoa regarding the mine plan, it is reasonable to assume that the ore from Darling range can be economically processed for the next 10 years.

23.4	Infrastructure

•

The Darling Range mining operations have established and operational infrastructure, with mining hubs that host administrative offices, as well as crushing facilities and maintenance facilities.

•

An extensive haul road network, rail, and overland conveyors transport crushed bauxite from the Hub to the refineries.

Bauxite is transferred from each mine to the refineries primarily via long distance conveyor belt, apart from the Kwinana refinery which receives bauxite via railway. The

Alumina produced by the three refineries is then shipped to external and internal smelter customers through the Kwinana and Bunbury ports.

•

Major haul roads have been established to each mining area, while secondary haul roads, cross-cut each individual mining plateau. Roads are unsealed and require continuous maintenance.

•

The Darling Range’s Pinjarra refinery receives power from the South West Interconnected System (SWIS), but also has internal generation capacity of 100 MW from four steam driven turbine

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alternators, with steam produced by gas fired boilers and a gas turbine Heat Recovery Steam Generator (HRSG).

The refinery supplies power to the Huntly Mine by a 33,000 volt power supply line and two 13,800 volt lines.

•

The refinery supplies power to the Willowdale Mine by a single 22,000 volt power supply.

•

Water is used on the mines for dust suppression, dieback washdown, vehicle washdown, workshops, conveyor belt wash, construction, and domestic purposes.

The water supplies for mining consist of licensed surface water sources supplemented with treated wastewater from vehicle washdowns, stormwater runoff and maintenance workshops.

•

23.5	Environment

•

Alcoa has established processes to facilitate conformance with environmental requirements, while identifying sensitive areas ahead of time enables them to be managed ahead of disturbance.

•

Site monitoring is completed in accordance with conditions of government authorizations and operational licenses at Huntly and Willowdale.

•

Alcoa implements a comprehensive water management and monitoring program in accordance with the requirements of its abstraction and operational licenses.

•

The Darling Range operations have no groundwater monitoring programs associated with legislation, licenses or approvals.

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Alcoa has a long-term groundwater research project within the Intermediate Rainfall Zone to evaluate potential impacts of clearing on groundwater salinization.

•

Outcomes of and compliance with the management and monitoring programs are tracked and reported within a Triennial Environmental Review report.

•

Only a small number of non-compliances were noted; none of which represent a risk that could adversely affect its license to operate.

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24.0	Recommendations

24.1	Geology and Mineral Resources

•

More rapid infill drilling of the 60 by 60 m and 30 by 30 m drill grids.

•

Further redrilling or where viable re-assaying of pulps

•

Moving away from the having drill holes notionally at the centroids of the 15 by 15 m grid map sheet system would mean that the use of offset grids and more flexible grid spacings would be viable.

•

Specific recommendations noted in previous Sections are reiterated here:

•

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•

24.2	Mining and Mineral Reserves

•

The life-of-mine scheduling requires further refinement with regards to sequencing of the different mining areas and assigning the scheduled years back to the orebest model.

•

The SLR QP recommends detailed haulage analysis focusing on haulage profiles and cycle times to provide more accurate operating costs.

•

24.3	Mineral Processing

•

SLR recommends independent verification of the sample analysis by a certified laboratory, on a structured program to ensure the QA/QC aspects of the internal analysis.

•

It is recommended that a proportion of samples from each batch could be sent to the independent laboratory for analysis and the results can be compared with the internal analysis.

24.4	Infrastructure

24.5	Environment

•

Monitor efficacy of corrective actions made following drainage failures related to significant rainfall events, which resulted in surface water flow from dieback areas into dieback free areas.

•

Monitor efficacy of corrective actions made following recordings of elevated turbidity for a period exceeding the compliance criteria (25 NTU).

•

Monitor efficacy of Interim PFAS Water Management Strategy implemented in response to incidents involving PFAS and AFFF contamination.

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25.0	References

Abzalov, 2016. Applied Mining Geology. Springer International, 448 pp.

Alcoa of Australia Limited, 1993. Bauxite Density. Internal memorandum prepared by Alcoa, dated 10 August 1993.

Barnes, L., 2015. 1m composite twin hole report. 1m sample intervals at the primary exploration stage (60x60m). Internal report by Alcoa Australia Limited, March.

Barnes, L., 2016. Procedure for sampling till extinction. Trial for 0.5m sample homogeneity, testing the representation of a ½ cup measure of 0.5m sample intervals. Internal draft report by Alcoa Australia Limited, March.

Barnes, L., 2018a. Segregation study. Internal draft report by Alcoa Australia Limited, February.

Barnes, L., 2018b. Sample To Extinction (STE) programme report 2017-2018. Internal draft report by Alcoa Australia Limited, July.

Canadian Institute of Mining, Metallurgy and Petroleum (CIM), 2014, CIM Definition Standards for Mineral Resources and Mineral Reserves, adopted by the CIM Council on May 10, 2014.

CIM, 2014. Canadian Institute of Mining, Metallurgy and Petroleum (CIM) Definition Standards for Mineral Resources and Mineral Reserves. Prepared by the CIM Standing Committee on Reserve Definitions. Adopted by CIM Council on May 10, 2014

Crockford, L., 2011. 2nd split drill sample testwork in the Larego area. Internal memorandum by Alcoa Australia Limited, 26 October.

Crockford, L., 2012. 1st and 2nd split drill sample testwork in the Myara area. Internal memorandum by Alcoa Australia Limited, 10 April.

Firman, J. B., 2006, Ancient weathering zones, pedocretes and palaeosols on the Australian Precambian shield and in adjoining sedimentary basins: a review, Journal of the Royal Society of Western Australia, 89 (2), 57 – 82, 2006

Franklin, S., 2019. Mining Laboratory FTIR Process Description (KWI). Internal Alcoa of Australia Limited document AUACDS-2047-781, reviewed 15 February.

Grigg, C., 2016. Summer vacation programme report 2015/2016. Internal report by Alcoa Australia Limited, February

Gy, P. M., 1984. Comments on bauxite sampling, Report to Alcoa No PG/3276, 27 July.

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Hickman, A. H., Smurthwaite, A. J., Brown, I. M., and Davy, R., 1992, Bauxite Mineralization in the Darling Range, Western Australia, Geological Survey of Western Australia, Report 33

Hodgson, S., 2015. Ore development QAQC Processes. Vacation student – summer work program 2014/15. Internal report by Alcoa Australia Limited, February.

Holmes, R. J., 2018. Assessment of Alcoa’s sampling and sample preparation equipment and procedures. Report EP182329 prepared for Alcoa of Australia Limited by CSIRO Mineral Resources, March.

JORC Code, 2012. Australasian Code for Reporting of Exploration Results, Mineral Resources and Ore Reserves (The JORC Code 2012 Edition). Prepared by the Joint Ore Reserves Committee of the Australasian Institute of Mining and Metallurgy, Australian Institute of Geoscientists and Minerals Council of Australia (JORC), effective 20 December 2012.

Knight., S., Tuckwell, L. and O’Brien, S., 2016. Huntly 2016 sample plant monitoring. Report by Alcoa Australia Limited (Powerpoint file).

Lyman, G. J., 2017. Investigation into Pinjarra and Wagerup sample plants. Report by Downer no 15382‐19‐02‐04‐001, 18 May.

NI 43-101, 2014. Canadian National Instrument 43-101, ‘Standards of Disclosure for Mineral Projects’, Form 43-101F1 and Companion Policy 43-101CP, May.

Rennick, W., Riley, G. and Baker, G., 1992. The constitution heterogeneity of Huntly ore and the resulting fundamental sampling errors using the Pinjarra sample station. Internal Alcoa Report, July.

Senini, P., 1993. Bauxite density. Internal report and memorandum by Alcoa Australia Limited, August 10.

Shaw, W. 1997. Validation of Sampling and Assaying Quality for Bankable Feasibility Studies. The Resource Database Towards 2000. Wollongong, New South Wales, Australia. 16 May. AusIMM, Melbourne. 41-49.

S-K 1300, 2018. US Securities and Exchange Commission Regulation S-K, Subpart 229.1300, Item 1300 Disclosure by Registrants Engaged in Mining Operations and Item 601 (b)(96) Technical Report Summary.

Snowden, 2015. Willowdale and Huntly Bauxite Operations Resource Estimation. Report prepared for Alcoa of Australia Limited by Snowden Mining Industry Consultants Pty Ltd, project number AAU5035 Resource Estimation Review, August.

SRK, 2017. Mineral Resource Estimates for the Alcoa Darling Range Bauxite Operations – December 2016. Report prepared for Alcoa of Australia Limited by SRK Consulting (Australasia) Pty Ltd, project number AOA002, May.

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SRK, 2018. Mineral Resource Estimates for the Alcoa Darling Range Bauxite Operations – December 2017. Report prepared for Alcoa of Australia Limited by SRK Consulting (Australasia) Pty Ltd, project number AOA004, March.

SRK, 2019a. Drillhole spacing study for the Alcoa Darling Range Bauxite Operations. Report prepared for Alcoa of Australia Limited by SRK Consulting (Australasia) Pty Ltd, project number AOA005, April.

SRK, 2019b. Mineral Resource Estimates for the Alcoa Darling Range Bauxite Operations – December 2018. Report prepared for Alcoa of Australia Limited by SRK Consulting (Australasia) Pty Ltd, project number AOA006, October.

SRK, 2021a. Mineral Resource Estimates for the Alcoa Darling Range Bauxite Operations – December 2020. Report prepared for Alcoa of Australia Limited by SRK Consulting (Australasia) Pty Ltd, project number AOA007, April.

SRK, 2021b. Ore Reserve estimates for the Alcoa Darling Range bauxite operations – December 2020. Report prepared for Alcoa of Australia Limited by SRK Consulting (Australasia) Pty Ltd, project number AOA007, April.

US Securities and Exchange Commission, 2018: Regulation S-K, Subpart 229.1300, Item 1300 Disclosure by Registrants Engaged in Mining Operations and Item 601 (b)(96) Technical Report Summary.

Xstract, 2016. Mineral Resource and Ore Reserve audit, Huntly and Willowdale Operations. Report prepared for Alcoa of Australia Limited by Xstract Mining Consultants Pty Ltd, project number P2173, May.

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26.0	Reliance on Information Provided by the Registrant

This report has been prepared by SLR for Alcoa. The information, conclusions, opinions, and estimates contained herein are based on:

•

Information available to SLR at the time of preparation of this report,

•

Assumptions, conditions, and qualifications as set forth in this report, and

•

Data, reports, and other information supplied by Alcoa and other third party sources.

For the purpose of this report, SLR has relied on ownership information provided by Alcoa in a legal opinion by Paul Volich, Managing Counsel – Australia, dated February 10, 2022, entitled Alcoa of Australia to SLR Corporation - ML1SA in good standing. SLR has not researched property title or mineral rights for the Darling Range as we consider it reasonable to rely on Alcoa’s legal counsel who is responsible for maintaining this information.

SLR has relied on Alcoa for guidance on applicable taxes, royalties, and other government levies or interests, applicable to revenue or income from Darling Range in the Executive Summary and Section 19. As Darling Range has been in operation for over ten years, Alcoa has considerable experience in this area.

The Qualified Persons have taken all appropriate steps, in their professional opinion, to ensure that the above information from Alcoa is sound.

Except for the purposes legislated under provincial securities laws, any use of this report by any third party is at that party’s sole risk.

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27.0	Date and Signature Page

This report titled “Technical Report Summary on the Darling Range, Western Australia, S-K 1300 Report” with an effective date of December 31, 2021 was prepared and signed by:

SLR International Corporation		(Signed) SLR International Corporation.


Dated in WA, USA
February 24, 2022

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