The assessment is based upon the design ore production of 95 million tonnes / annum.

9A Air Quality Assessment Supporting Information This annex sets out the detailed methodology, input data and criteria for the assessment. The overarching assessment approach is detailed in Chapter 9: Air Quality, which should be read in conjunction with this annex. 9A.1 Assessment approach Chapter 9: Air Quality sets out the overarching methodology used in the impact assessment. This section sets out more detail in terms of assessment of ore handling sources at the port and the port power station. Further to the methodology set out in Chapter 9: Air Quality, more information is set out here relating to the assessment of ore handling sources (car dumper, conveying, stockpiling and ship loading). Modelling: the impacts were identified using detailed dispersion modelling (AERMOD). The model utilises the source parameters, receptors and meteorology. The AERMOD model is a state of the art detailed dispersion model capable to representing complex multiple emission sources. The model is widely recognised for use in this type of application, including the IFC, USEPA, UK Environment Agency and Australian Environmental Protection Agency. The model has been designed to represent and capture the maximum likely level of activity and therefore emissions. The key assumptions in the model approach are as follows. The assessment is based upon the design ore production of 95 million tonnes / annum. The port design and assessment is based upon a previous design at Ile Kaback. Whilst the use of this previous design is a limitation, as the key source of emissions and impacts is the stockpile, the activities of which are closely similar, this is not a critical limitation. As discussed in Chapter 9: Air Quality, the overlap of emissions and therefore impacts associated with the various sources at the port is not considered critical as the stockpile emissions dominate. The Power plant is based upon a design specification of 65MW thermal equipped with 32m stacks. Fuel sulphur content is assumed to be 500ppm. Figure 9.1, sets out a summary of the key sources of emissions considered in the study. 9A.2 Modelling of ore handling sources 9A.2.1 Overview When assessing impacts associated with the operational port activities, detailed dispersion modelling was utilised to predict the dispersion of emissions from the handling and stockpiling of ore at the port to predict the subsequent impacts at nearby sensitive receptors. The modelling approach was based upon a consideration of where emissions arise: Car dumpers; Ore conveying; Ore stockpiling; and Ship loading. These emission sources were defined in terms of specific sources of emissions which have a fixed location (ie ship loading,, conveyors, rail unloading). of dust and PM 10 /PM 2.5 are mainly generated from mechanical sources, that is the action of ore handling, from open surfaces at or from vehicles moving over unpaved surfaces. These sources are characterised by occurring at ambient temperature, close to ground level, with very little upward 9A-1

momentum of the emissions. Therefore, these sources were treated in the model as volume sources, in which the emission concentration and height of emission are defined. 9A.2.2 Source and emissions definition The definition of the sources and the emissions arising from the activities during the lifetime of the port is required to undertake the impact assessment. This information has been collated on the basis of a detailed review of the proposed mine activities, review of the National Pollution Inventory (NPi) document produced by the Australian government (1) and other relevant documentation as referenced in this Annex. NPi (2011) is built upon a process of national consultation within the Australian mining industry, and makes extensive reference to the United States Protection Agency AP-42 emissions database (2). The NPi documentation and the techniques for the estimation of emissions are the most recently published consolidation of suitable emissions data, and although derived from Australia mining, are considered to be robust and suitable for purpose in this assessment. Of particular importance is the fact that NPi takes into consideration local meteorological effects and provides opportunity to take into consideration other site specific factors such as silt content and distances travelled on roads. Where it is possible to take into account local conditions in the estimation of emissions careful consideration has been made of the Guinean climate and geology. Reference is also made to research undertaken specifically for the Simandou ore in order to determine Dust Extinction Moisture (DEM), as described in more detail in this annex. The NPi and AP-42 guidance documents have been used as the basis for the following: scoping significant emission sources; and estimating emissions from the identified significant sources. 9A.2.3 Primary sources Table 9A.1 outlines the sources of emissions identified at the port. This table also identifies if the source has been screened out, or included. Table 9A.1 Summary of Sources ore handling Activity Pollutants Assessment Unloading train (car dumpers) Dust, PM 10, PM 2.5 Modelling Conveyor Belts Dust, PM 10, PM 2.5 Modelling Loading to Dust, PM 10, PM 2.5 Modelling Reclaiming from Dust, PM 10, PM 2.5 Modelling Wind erosion of Dust, PM 10, PM 2.5 Modelling 9A.2.4 of total suspended particulates (dust) and PM 10 On the basis of the identification of the sources set out in Table 9A.1, the approach set out in NPi was used to estimate the emissions of TSP and PM 10 arising from each source. For some sources these are default emission factors for a given activity, for others these are formulae used to calculate emissions based upon source characteristics and other considerations, such as local meteorological conditions. from car dumpers and erosion from have been estimated using the following equation: s 365 365 p f (%) EF TSP 1.9 kg/ha/yr 1.5 235 15 (1) Australian Government (2011). National Pollutant Inventory Emission Estimation Technique Manual for Mining v3.0 June 2011. (2) United States Environmental Protection Agency AP-42 emissions database. 9A-2

Where: EF TSP is the emission rate in kg/ha/yr; s = silt content % by weight, taken to be 10%; p = number of days when precipitation is greater than 0.25 mm: for the purposes of this assessment, so that short term impacts are not under estimated it has been assumed no natural rainfall occurs, and for the long term impacts this attenuation is then applied for all emissions of PM 10 and TSP; and f(%) = percentage of time wind speed is greater than 5.4 m/s at the mean height of the stockpile (or conveyor).analysis of the NWP meteorological data indicates that there are no hours with wind speed >5.4 m/s, but it has been assumed there is likely to be at least one event in a year above this value, so 0.01% has been used. from conveying, loading of and unloading of have been estimated using the following equation: 0.8 U 0.005kg t E TSP 2.2 / 2.2 Where: kg/tonne ore U = mean wind speed at 10 m above surface. This equation is based upon the USEPA batch drop equation. In addition U (wind speed) has been calculated on the basis of the height of release being 5 m, rather than 10 m. This used the USEPA 1/7 law: 5 510 10 (1/ 7) U U 5 m m/s Table 9A.2 Summary of Emission Factors for Dust and PM 10 Sources (unmitigated) Activity Dust emission PM 10 emission Unit Type of Factor Unloading train (car dumpers) 8.3 x10-7 4.2 x10-7 kg/ha/hour Conveyor Belts 0.0042 0.00168 kg/t Loading to Reclaiming from Wind erosion of 0.0042 0.00168 kg/t 0.0042 0.00168 kg/t 8.3 x10-7 4.2 x10-7 kg/ha/hour As discussed in Chapter 9: Air Quality, a commitment was made to use of watering to sufficient level to achieve Dust Extinction Moisture in order to reduce emissions of dust and PM 10 by 99% compared to unmitigated emissions. 9A.2.5 Dust Extinction Moisture Rio Tinto commissioned a study using an iron ore sample from the Ouéléba region of the Simandou hills. This was tested for a number of properties by Tunra Bulk Solids Handling Research Associates at the Bulk Solids Handling Laboratories at the University of Newcastle. As part of this study tests have been undertaken to identify the Dust Extinction Moisture (DEM), of the ore at Simandou. The moisture content at which the sample is considered to emit no more dust is determined using the Australian Standard AS- 4 156.6-2 000, and is referred to as the DEM. This study shows the DEM of the sample location as occurring 9A-3

at moisture contents of above 2.6%. The sample is considered to be emitting no more dust at approximately a 99% reduction compared to a dry sample. This site specific information has been incorporated into the assessment of air quality at the port on the understanding that this is a refined information source. It is recognised that in using just one sampling location and only 10 sub samples for this test, it may not be possible to achieve 99% reduction at all locations across the port by maintaining exactly 2.6% moisture. Therefore, on this understanding, this research is taken to imply that a dust suppression of 99% is achievable when ore moisture content is maintained at above 2.6%. It has also been assumed that the same suppression would occur for the PM 10 fraction of particulates. The activities this mitigation has been applied to for dust and PM 10 are as follows: unloading of trains; loading to ; reclaiming from ; conveying; and loading to ships. 9A.2.6 Inventory On the basis of the derivation of emissions described in Section 9A.2.4, an emissions inventory for dust and PM 10 has been developed for the port activities. The inputs for modelling the port are presented in Table 9A.3 along with information which has been assumed in order to calculate the emission rate used. Table 9A.3 for Ore Handling Sources Source Unloading train (car dumpers) Dust PM 10 Units Abatement Achievable (ie with DEM) Dust (g/s) PM 10 (g/s) 8.3 x10-7 4.2 x10-7 kg/ha/hour 99% 2.38x10-10 1.19x10-10 Conveyor Belts 0.0042 0.00168 kg/t 99% 1.27 0.507 Loading to Reclaiming from Wind erosion of 0.0042 0.00168 kg/t 99% 0.0633 0.0253 0.0042 0.00168 kg/t 99% 0.190 0.0760 8.3 x10-7 4.2 x10-7 kg/ha/hour 99% 3.50x10-8 1.75x10-8 9A.3 Modelling of power station The port power plant included in this assessment is of 65MW thermal capacity, operating on diesel fuel for the provision of electrical power. The operation of the power plant will result in emissions of, PM 10, PM 2.5, NO x /NO 2 and SO 2. Based upon published data for a similar power plant in Africa (1), a conceptual emissions inventory for the port power plant has been developed. The data pertaining to the power plant as modelled in this assessment are set out in Error! Reference source not found.3. (1) Reference: Contourglobal (2008). Etude d Impact Environnemental et Social du projet de Réhabilitation, Extension et Exploitation de la Centrale Thermique de Lomé Volet Extension. Available at http://www.ifc.org/ifcext/spiwebsite1.nsf/0/a370748c334a1f31852576ba000e2dde/$file/esia%20200811.pdf 9A-4

Table 9A.4 Summary of Emission Factors for Power Generation Emission and Stack Data Units Base plant design (100MWe) Mine (65MWe) Number of engines 11 Engine power (per engine) MWe 10.8 Number of stacks 1 1 Number of flues per stack 1 1 Stack height actual m 38 32 Flue diameter m 2.118 2.309 Emission velocity m/s 38.1 38.1 Volume flow rate (nominal) Nm3/s 146.70 174 Volume flow rate (nominal) Am3/s 421.5 501 Emission temperature Celsius 326.7 326.7 Oxygen (actual) % 12.7 Oxygen (normalised) % 11 Moisture (actual) % 7.3 Moisture (normalised) % 0 NO x g/s 237 282 SO 2 (based on fuel sulphur content of 500ppm) g/s 15.8 PM (dust) g/s 1.32 1.57 are expressed as NO x. To assess against standards for NO 2 a factor of 70% conversion for NO to NO 2 is applied for calculating the annual mean and 35% conversion for NO to NO 2 is applied for the 1 hour. In terms of the power plant no specific mitigation measures are proposed for the control of emissions. However, as discussed, a commitment is made to the use of fuel with sulphur content of no greater than 500ppm. This measure is proposed in order to achieve acceptable impacts due to emissions of SO 2. 9A.3.1 References for dust deposition criteria As described in Section 9.2.4.2, the point at which substantiated nuisance complaints due to dust deposition is likely to occur when deposition is >350mg/m 3 /day, based upon the TA-Luft criteria. In order to give greater resolution of impacts references have been gathered to identify the deposition rates at which different levels of nuisance are likely to occur. These are set out in Table 9A.5. Table 9A.5 Dust Deposition Nuisance Thresholds Potential for Complaint National Guidelines Measure of Soiling (mg/m 2 /day) Data Source Possible Nuisance 350 (monthly mean) TA-Luft Very Likely Nuisance 650 TA-Luft First Loss of Amenity 133 (monthly mean) West Australia Nuisance Standard Unacceptable reduction in air quality 333 West Australia Nuisance Standard Serious nuisance 200 UK recommended nuisance dust deposition rate Nuisance dust deposition 133 Malaysia air quality standard 9A-5

Potential for Complaint Evidence based guidelines Measure of Soiling (mg/m 2 /day) Data Source Noticeable (urban) 95 Source 1 Possible complaint (rural) 119 Source 1 Objectionable 167 Source 1 Probable complaint 476 Source 1 Serious complaint 1191 Source 1 Note: Source1 obtained from Good Quarry (1). The TA-Luft guideline was selected as the threshold of nuisance issues occurring, as it is the only limit enshrined in legislation. The following thresholds were set whereby nuisance is likely to occur: no significant impact: deposition <350 mg/m 3 /day; minor significant impact: deposition between 350 mg/m 3 /day and 650 mg/m 3 /day; moderate lower significant impact: deposition between 650 mg/m 3 /day and 950 mg/m 3 /day; major higher significant impact: deposition between 950 mg/m 3 /day and 1191 mg/m 3 /day; and critical significant impact: deposition >1 191 mg/m 3 /day. 9A.4 Fuel sulphur content The power plant utilises diesel engines, the diesel utilised in these processes will contain some sulphur, a naturally occurring by-product of fuel production. When the diesel is combusted there will be resulting emissions of sulphur dioxide. The relationship between the fuel sulphur content and emissions of sulphur dioxide is linear, with an increase in fuel sulphur directing proportional to SO 2 emissions. Fuel is available with defined maximum sulphur content: 50 ppm, 500 ppm or 5 000 ppm. However, availability of these fuels is not consistent, with the higher sulphur fuels being more readily available. There is therefore a practical driver to utilise higher sulphur content fuels. As part of the impact assessment, test models were undertaken with those sources emitting SO 2 in order to determine which fuel sulphur contents result in acceptable impacts to air quality, and would therefore be acceptable to be utilised in the proposed scheme. The test models were compared against the air quality standards for the annual mean for the protection of vegetation and the 24 hour mean and 10 minute mean for the protection of human health. The results show: the 50 ppm fuel does not result in significant impacts; the 500 ppm fuel results in a small area of minor significant impact immediately around the power plant and does not result in any air quality standard being exceeded; and the 5 000 ppm fuel results in critical and major significant impacts at receptors. On this basis of these results it has been concluded that using fuels of 5 000 ppm would results in exceedence of standards and therefore these fuels will be avoided. (1) Good Quarry (accessed November 2011) Dust Deposition available at http://www.goodquarry.com/article.aspx?id=58&navid=2: Citing: Hancock, R. P., Esmen, N. A., and Furber, C. P. (1976) "Visual Response to Dustiness", Journal of the Air Pollution Control Association, 26 (1), 1976, pp54-57; Beaman, A. L. and Kingsbury, R. W. S. M. (1981) "Assessment of Nuisance from Deposited Particles Using a Simple and Inexpensive Measuring System". Clean Air, 11, 1981; Bate, K. J. and Coppin, N. J. (1991) "Dust impacts from mineral workings", Mine and Quarry, 20 (3), 1991, pp31 35; Hofschreuder, P. and Vrins, E. L. M. (1992) "Nuisance from coarse dust", Journal of Aerosol Science, 23 (S1), 1992, pp691 - S694; Quality of Urban Air Research Group. (1996) "Airborne Particulate Matter in the United Kingdom: Third Report of the Quality of Urban Air Review Group", prepared at the request of the Department of the Environment. University of Birmingham, Birmingham 9A-6

9A.5 Evidence base for derivation of PM 2.5 emissions and impacts As previously discussed, NPi and AP-42 do not cite emissions factors for PM 2.5. Therefore, in order to provide a basis for estimating impacts of emissions of PM 2.5, factors have been developed for estimating PM 2.5 emissions on the basis of the predicted PM 10 emissions. The emissions of PM 10 arising from the proposed port arise from the handling of ore and as a result of power generation. Lighty, Veranth and Sarofim (2000) and DRI (2000) present data based upon several references setting out the particle size distribution for several sources of emissions. A summary of the findings are set out in Table 9A.6. Table 9A.6 Particle Size Distribution for Various Particle Emission Sources (by mass) Source >PM 10 PM 10 PM 2.5 PM 1 PM 10 as PM 2.5 Percentage of Road and soil dust emissions 52.3 47.7 10.7 4.5 22.4% Diesel truck emissions 3.8 96.2 92.3 91.8 95.4% Construction dust emissions 34.9 65.1 5.8 4.6 8.92% The data presented illustrate that for combustion sources, particles of size <2.5µm (ie PM 2.5 ) dominates PM 10 composition, whereas for mechanical sources particles of size 2.5 10µm dominates PM 10. Construction dust has also been included for comparison. The data set out in Table 9A.14 is considered to be a reasonable estimate of emissions likely to arise at the proposed project site, as the basis of particle generation is similar to those described in the study data. Therefore, on the basis of this evidence, estimated emissions of PM 2.5, as a fraction of PM 10 have been calculated. With regard to combustion sources, as 95.4% of PM 10 occurs as PM 2.5 it is reasonable to undertake the assessment on the basis that all PM 10 also occurs as PM 2.5. With regard to ore handling sources as 22.4% of PM 10 occurs as PM 2.5, it is unreasonable to undertake the assessment on the basis that PM 10 occurs as PM 2.5. Instead, for ore handling sources, the results of the modelling based upon the use of PM 10 emission factors are factored by 22% to calculate PM 2.5 emissions. This approach has been adopted in the assessment, as it is possible to consider emissions from ore handling sources and power generation sources separately. 9A-7