The Characterisation of Airborne Particulate Matter By

The Characterisation of Airborne Particulate Matter by Automated Mineralogy: The Potential of the Mineral Liberation Analyser for the Monitoring of Mine-Derived Emissions.

Michele Elmes BSc Honours

0000-0003-3194-3354

A thesis submitted for the degree of Doctor of Philosophy at the University of Queensland in 2020 School of Earth and Environmental Sciences Abstract With its links to adverse environmental and human health impacts, air pollution is an increasing and ubiquitous global concern. Air pollution, especially the particulate matter component, has been linked to cancer, pulmonary and cardiac disease, neurotoxicity and pernicious impacts on fertility and pregnancy. It has also been observed to affect climate by altering the radiation and chemical balance of the atmosphere. Unlike other pollution vectors, airborne particles are not constrained by topography, enabling them to be rapidly dispersed over vast distances. Although international air quality guidelines have been implemented, more than 90% of the global population are exposed to levels higher than those recommended by the World Health Organisation.

Airborne particulate matter (APM) is a physically and chemically complex mix of organic and inorganic substance and, to accurately assess the potential environmental and human health implications, a detailed physical and compositional characterisation at the single particle level is required. The ultimate goal of an analytical technique for APM is to quantitatively identify all the chemical species within each individual particle to predict potential impacts and develop successful mitigation strategies.

Micro-beam techniques, such as energy dispersive scanning electron microscopy (SEM-EDS) have been used extensively to generate information on the physical, morphological and chemical properties of single atmospheric particles down to a nominal diameter of 0.1µm. Traditional SEM-EDS methods, however, are prone to operator error and bias and the manual data processing is time consuming and costly and therefore impractical for regular monitoring purposes. As a result, computer-controlled SEM (CCSEM) is rapidly gaining predominance. Although the use of automated SEM-EDS analysis is well documented, few studies to date have used automated mineralogy systems, such as the Mineral Liberation Analyzer (MLA).

The MLA was designed to improve the efficiency of mineral processing plants and, although the technique has been extensively used in the mining industry since its inception, it is only recently that this technique has been applied to other environmental fields. To our knowledge this is the first time the MLA has been used in the application of ambient APM analysis and has the potential to be a powerful tool in the APM analytical arsenal.

Prior to APM analysis, a suitable sampling and sample preparation technique was determined, a spectral reference library constructed and the accuracy and precision of the instrument tested by repeat analysis and comparison to certified reference materials (CRM), with mineral abundances (modal mineralogy) and repeat analysis showing relative standard deviations typically below 10%.

Using the developed methodology, ambient APM was collected from four stations in the vicinity of a large iron-ore mining operation in Congonhas, Minas Gerais, Brazil, as well a control station lying outside the influence of the mine. To observe spatio-temporal variations, sampling was conducted over the dry, wet and transitional periods. The mineral phases observed strongly reflected the local geology, with clays and iron oxides contributing 70-80% of the particulates sampled. Particle size distributions reflected sources dominated by mechanical processes, with coarse particles (>2.5µm) accounting for 80-90%. A strong seasonality was observed with coarser particles more prevalent during the drier periods of May and August, with fine particles (<2.5µm) contributing to less than 10% of the total particulates sampled.

Although the transport and ultimate fate of APM is largely controlled by particle size and shape, chemical species is critical in assessing the potential toxicity, as different species of the same elements can have different toxicological properties, bulk elemental concentrations may not be a true representation of bioaccessibility. As a result the ability to accurately identify potentially toxic elements in the atmosphere is essential to formulate a realistic risk assessment. Manganese bearing particles, predominantly Mn oxides and jacobsite, were detected in appreciable numbers, although only contributing to less than 1% of the total particulates sampled. The particle size distribution, however, indicated a geogenic, rather than anthropogenic, source. As deposition within the human lung is largely determined by size and density, the predominantly coarse particles and relatively insoluble mineral phases, suggested that the risk of inhalation toxicity for the exposed population is potentially relatively small.

Declaration by Author

This thesis is composed of my original work, and contains no material previously published or written by another person except where due reference has been made in the text. I have clearly stated the contribution by others to jointly-authored works that I have included in my thesis.

I have clearly stated the contribution of others to my thesis as a whole, including statistical assistance, survey design, data analysis, significant technical procedures, professional editorial advice, financial support and any other original research work used or reported in my thesis. The content of my thesis is the result of work I have carried out since the commencement of my higher degree by research candidature and does not include a substantial part of work that has been submitted to qualify for the award of any other degree or diploma in any university or other tertiary institution. I have clearly stated which parts of my thesis, if any, have been submitted to qualify for another award.

I acknowledge that an electronic copy of my thesis must be lodged with the University Library and, subject to the policy and procedures of The University of Queensland, the thesis be made available for research and study in accordance with the Copyright Act 1968 unless a period of embargo has been approved by the Dean of the Graduate School.

I acknowledge that copyright of all material contained in my thesis resides with the copyright holder(s) of that material. Where appropriate I have obtained copyright permission from the copyright holder to reproduce material in this thesis and have sought permission from co-authors for any jointly authored works included in the thesis.

Publications included in this thesis

The following publication has been incorporated as Chapter 2.

ELMES, M. & GASPARON, M. 2017. Sampling and single particle analysis for the chemical characterisation of fine atmospheric particulates: A review. J Environ Manage, 202, 137-150.

Contributor Statement of contribution % Michele Elmes Drafting of Manuscript 100 Preparation of figures 100 Study Conception and Design 50 Massimo Gasparon Supervision, guidance 100 Study Conception and Design 50

The following publication has been incorporated as Chapter 4.

ELMES, M., DELBEM, I., GASPARON, M. & CIMINELLI, V. 2020. Single-particle analysis of atmospheric particulate matter using automated mineralogy: the potential for monitoring mine-derived emissions. International Journal of Environmental Science and Technology.

Contributor Statement of contribution % Michele Elmes Drafting of Manuscript 90 Acquisitio n of Data 10 Preparation of Figures 50 Interpretation of Data 60 Itamar Delbem Drafting of Manuscript 5 Acquisitio n of Data 90 Preparation of Figures 50 Massimo Gasparon Study conception and design 50 Supervision, guidance 50 Drafting of Manuscript 5 Interpretation of Data 20 Preparation of Figures 10 Critical Revisio n 50 Virginia Cimine lli Study conception and design 50 Supervision, guidance 50 Interpretation of Data 20 Critical Revisio n 50

Other publications during candidature

GASPARON, M., DELBEM, I., ELMES, M. & CIMINELLI, V. Detection and analysis of arsenic-bearing particles in atmospheric dust using Mineral Liberation Analysis. Arsenic Research and Global Sustainability: Proceedings of the Sixth International Congress on Arsenic in the Environment (As2016), June 19-23, 2016, Stockholm, Sweden, 2016. CRC Press, 217.

MOSTERT, M., GASPARON, M. & ELMES, M. 2017. Analysis of Iron Ores by Fusion and ICP-OES. AXT Application note, 1-9, http://www.axt.com.au/analysis-of-iron-ores-by-fusion-and-icp-oes/

Contributions by others to the thesis

No contributions by others

Statement of parts of the thesis submitted to qualify for the award of another degree

No works submitted towards another degree have been included in this thesis.

Research involving human or animal subjects

No animal or human subjects were involved in this research.

Acknowledgments

I would like to thank my supervisors Massimo Gasparon and Virginia Ciminelli, whose brainchild this project is, for their guidance, support and encouragement. I would like to thank my supervisor Carlos Spiers for helping me when everything seemed lost.

I am grateful to Itamar Delbem at the Federal University of Minas Gerais (UFMG) for his patience training me on the MLA, his tireless work analysing the samples and his continued support throughout the project. I am also grateful to all the people at the UFMG Centre of Microscopy for providing the equipment and support for all MLA analyses and INCT-Acqua for their help on this project.

I am indebted to Marietjie Mostert, chemist extraordinaire, for her patience during my training in the Geochemistry laboratory and her unstinting support throughout my candidature. She was the shining beacon when everything seemed darkest.

Lastly, I would like to thank my family with their endless patience during my candidature.

Financial Support

I would like to acknowledge the Brazilian agencies, Conselho Nacional de Desenvolvimento Científico e Tecnológico—CNPq—and Fundação do Amparo a Pesquisa do Estado de Minas Gerais-FAPEMIG, including a PVE Fellowship from the Science Without Borders program to M. Gasparon and the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil (CAPES) for financing this project.

Keywords

airborne particulate matter, automated mineralogy, Mineral Liberation Analyer, single particle analysis, geogenic emissions, potentially toxic elements

Australian and New Zealand Standard Research Classifications (ANZSRC)

ANZSRC code: 040101, Atmospheric aerosols, 50%

ANZSRC code: 039901, Environmental Chemistry, 50%

Fields of Research (FoR) Classification

FoR code: 0401, Atmospheric Sciences, 50%

FoR code: 0399, Other Chemical Sciences, 50%

Table of Contents Abstract...... 2 List of Figures ...... 14 List of Tables...... 16 List of Abbreviations ...... 18 Chapter 1 ...... 20 Introduction ...... 20 1.1 Mineral Dust in the Atmosphere ...... 24 1.2 The Mineral Liberation Analyzer (MLA) ...... 26 1.2 Thesis Aims and Research Outline ...... 28 References ...... 32 Chapter 2 ...... 36 Sampling and Single Particle Analysis for the Chemical Characterisation of Fine Atmospheric Particulates: A Review...... 36 2.1 Introduction ...... 36 2.2 Air sampling techniques...... 39 2.2.1 Active samplers...... 40 2.2.2 Passive Samplers ...... 45 2.2.3 Sampling substrates ...... 47 2.3 Off-line analytical techniques ...... 48 2.3.1 Electron Microscopy...... 49 2.3.2 Atomic Spectroscopy...... 51 2.4. On-line analytical techniques ...... 58 2.5. Conclusion ...... 61 References ...... 65 Chapter 3 ...... 74 Combining Gravimetric and Single Particle Analysis to Determine the Contribution of an Active Gold Mine to Arsenic in the Atmosphere ...... 74 3.1.INTRODUCTION...... 74 3.2 METHODS ...... 76 3.2.1 Sampling locations ...... 76 3.2.2 Local geology and mineralogy of the ore deposit...... 78 3.2.3 Sample collection and analysis ...... 78 3.3. RESULTS AND DISCUSSION ...... 80

3.3.1 APM Mass Concentrations ...... 80 3.3.2 Single-particle characterisation by SEM-EDS ...... 82 3.4CONCLUSION ...... 91 References ...... 93 Chapter 4 ...... 95 Single-Particle Analysis of Atmospheric Particulate Matter Using Automated Mineralogy: The Potential for Monitoring Mine-derived Emissions ...... 95 4.1. INTRODUCTION ...... 95 4.2. Materials and Methods...... 97 4.2.1 The Mineral Liberation Analyzer (MLA)...... 97 4.2.2. Sample collection and assessment of particle collection methods ...... 100 4.2.3. Sample Preparation...... 101 4.2.4. SEM/MLA operating conditions...... 101 4.2.5. Formulation of the mineral library...... 102 4.2.6. Limitations of the method ...... 103 4.3.0 Results and discussion ...... 104 4.3.1 Selection of a sampling substrate ...... 104 4.3.2 Accuracy and precision relative to certified reference materials (CRM) ...... 106 4.3 Spatial homogeneity of the sample and operator bias ...... 108 4.3.4 Pilot Study ...... 109 4.4. CONCLUSION ...... 114 Supplement 1. BSE contrast (a) of particles and after background elemination (b) for different sampling substrates ...... 116 Supplement 2. Particle size distribution tables and graphs for Site B. The electronic sieve size (in µm) represents the particle size based on the equivalent circle area diameter as determined by the BSE image analysis...... 118 Supplement 3. Particle-type size distribution in tabular and graphical form generated for Site A. The electronic sieve size (in µm) represents the particle size based on the equivalent circle area diameter as determined by the BSE image analysis...... 119 References ...... 120 Chapter 5 ...... 123 Characterisation of Airborne Particulate Matter Near a Large-Scale Iron-Ore Mine by Automated Mineralogy...... 123 5.1. Introduction ...... 123 5.2Materials and Methods ...... 125

5.2.1 Sampling Locations ...... 125 5.2.2 Sample Collection ...... 127 5.2.3 SEM/MLA Operating Conditions...... 128 5.2.4 Formulation of the Mineral Library...... 128 5.3. Results and Discussion ...... 128 5.3.1 Mineralogy and Particle Morphology...... 128 5.3.2ParticleSize Distributions ...... 132 5.3.3 Particle size and number distributions for individual mineral phases ...... 134 5.0 Conclusions...... 140 References ...... 142 Chapter 6 ...... 145 Characterisation of Manganese-Bearing Mineral Phases in Atmospheric Particulate Matter ...... 145 6.1.0 Introduction ...... 145 6.2.0 Materials and Methods ...... 148 6.2.1 Sampling Locations ...... 148 6.2.2 Sample Collection ...... 150 6.2.3 SEM/MLA Operating Conditions...... 150 6.2.4 Formulation of the mineral library ...... 150 6.3 Results and Discussion ...... 151 6.3.1 Mn-bearing phases in APM ...... 151 6.3.2 Assessment of the health risk related to exposure to atmospheric Mn-bearing particles 154 6.4 Conclusions...... 156 References ...... 157 Chapter 7 ...... 177 Thesis Summary...... 177 7.1 Thesis Summaryand Conclusions ...... 177 7.2 Suggestions for Future Work ...... 180 Appendix 1 ...... 182 Normalised EDS data, Paracatu ...... 182 Appendix 2 ...... 261 Particle Size Distribution, Congonhas...... 261 Appendix 3 ...... 267

TSP Modal Mineralogy, Congonhas ...... 267 Appendix 4 ...... 273 Particle Size Distribution for Selected Individual Mineral Phases ...... 273

List of Figures

Figure 1.1 Relative sizes of airborne particulate matter...... 21 Figure 1.2 Modelled distributions of particulates in the atmosphere...... 22 Figure 1.3 Percentage of the world's population exposed to PM2.5 pollution above WHO guidelines ...... 22 Figure 1.4 Depositional efficiency of APM in the human bronchopulmonary system...... 23 Figure 1.5 Saharan dust storm extending into the Atlantic Ocean and mine-derived geogenic emissions, Casa de Pedra Congonhas, Brazil...... 24 Figure 1.6 Particle classification process ...... 27 Figure 2.1Deposition of APM in the respiratory system...... 39 Figure 2.2Cascade impactor...... 42 Figure 2.3 a) Dichotomous impactor; b) Cyclone impactor...... 43 Figure 2.4Personal exposure samplers. a) Cyclone; b) IOM...... 46 Figure 3.1Location of Paracatu and the six monitoring stations...... 77 Figure 3.2Precipitation levels and wind speed for Paracatu during the sampling periods...... 78 Figure 3.3 Variations in TSP mass concentrations for the sampling periods...... 81 Figure 3.4Particle size distribution for A) 2-14 December 2011 and B) 13-20 September 2012...... 83 Figure 3.5Relative proportions of mineral phases for the periods A) 2-14 December 2011 and B) 13- 20 September2012...... 84

Figure 3.6BSE image and corresponding EDS spectrum of a sulphide mineral...... 84

Figure 3.7SEM images and corresponding EDS spectra for silicate mineral phases...... 85 Figure 3.8 Size distribution of individual mineral phases...... 86 Figure 3.9Super-coarse silicate aggregates sampled during December...... 87 Figure 3.10SEM image and corresponding EDS spectra of carbonaceous material...... 88 Figure 3.11SEM image and EDS spectrum of carbonate mineral phase...... 89 Figure 3.12SEM image and EDS spectra of Al-rich particle...... 90 Figure 4.1Example of the mineral classification process using MLA...... 100 Figure 4.2 SEM image and elemental analysis of S-bearing particulates from site A...... 110 Figure 4.3 Particle size distribution for sampling sites A and B...... 110 Figure 4.4 SEM images and elemental composition of Mn-bearing phases from Site B...... 111 Figure 4.5 Elemental differences between Fe-(hydr) oxide and Al-enriched Fe-(hydr) oxide...... 112 Figure S.1.1 Particulates on a cellulose filter: raw BSE image and b) BSE image after background elimination...... 116

Figure S.1.2 Particulates on a cellulose filter: raw BSE image and b) BSE image after background elimination ...... 116 Figure S.1.3 Particulates sampled on a polycarbonate filter: a) raw BSE image and b) BSE image after background elimination...... 117 Figure 5.1 Location of the five monitoring stations in the Congonhas region...... 126 Figure 5.2Average temperature, rainfall and prevailing wind direction (%) for Congonhas...127 Figure 5.3 Relative proportions (wt%) of mineral phases in sampled APM...... 129 Figure 5.4SEM images of (a) TSP sampled on a polycarbonate filter,(b)Fe-oxide, (c) clay agglomerate with Fe-oxides, (d)calcite with secondary crystal growths, (e)surface reactions on calcium phosphate particle, and carbonaceous particles exhibiting similar morphologies (f) biological material, g) carbon cenospheres and h) soot aggregate...... 132

Figure 5.5 Size distribution of TSP...... 133 Figure 5.6 Size distribution for common mineral phases in cumulative weight percent...... 135 Figure 5.7Particle number for individual mineral phases in the coarse (10-2.5 µm) and fine (1-2.5 µm) fractions...... 138 Figure 6.1 Location of Congonhas and the five monitoring stations...... 149 Figure 6.2 Particle numbers of manganese-bearing phases detected in sampled APM...... 151 Figure 6.3 Relative proportion of manganese particles in the sampled particulates (weight percentage) and particle number of collective manganese-bearing phases...... 153 Figure 6.4 Raw SEM images and classified particle images of a) jacobsite and b) Mn Oxide..153

Figure 6.5 Particle size distributions for Mn oxide and Jacobsite at selected sampling sites...... 155

List of Tables Table 2.1 International Air Quality Standards for total suspended particulates (TSP), PM10 and PM2.5...... 39

Table 2.2 Physical and chemical characteristics of common air filters and compatible single particle analytical techniques……………………………………………………………………………………………………...... ………...... 53

Table2. 3. Advantages and disadvantages of different single particle analytical techniques…....61

Table 3.1 Classification of mineral phases based on stoichiometric mineral formulae………….…..79

Table 4.1 Different MLA analysis modes……………………………………………………………………………..…...98

Table 4.2 Concentrations of selected elements in the different filter media. All values in mg kg-1 ……………………………………………………………………………………………………………………………………..…….....104

Table 4.3 Comparison between XRD and MLA data for USGS CRM BHVO-2 and GSP-2……….....106

Table 4.4 Data for spatial homogeneity and operator bias. Mean values in area %...... 107

Table 4.5 Modal mineralogy for particulates sampled from site A…………………………………...……110

Table 4.6 Modal mineralogy for particulates sampled from site B…………………………….………..…113

Table A1-1. Normalised EDS data, station 1, 12-14 December 2011...... 181

Table A1-2. Normalised EDS data, station 1, 13-20 September 2012...... 183

Table A1-3. Normalised EDS data, station 3, 2-14 December 2011...... 190

Table A1-4. Normalised EDS data, station 3, 13-20 September 2012...... 204

Table A1-5. Normalised EDS data, station 4, 2-14 December 2011...... 221

Table A1-6. Normalised EDS data, station 4, 13-20 September 2012...... 222

Table A1-7. Normalised EDS data, station 5, 2-14 December 2011...... 236

Table A1-8. Normalised EDS data, station 5, 13-20 September 2012...... 239

TableA1-9. Normalised EDS data, station 6, 2-14 December 2011...... 255

Table A1-10. Normalised EDS data, station 6. 13-20 September 2012...... 256

Table A2- 1. Particle Size Distribution for Basilica (BAS)...... 260

Table A2-2. Particle Size Distribution for Casa de Pedra (CDP)...... 261

Table A2-3. Particle Size Distribution for Pires (PIR)...... 262

Table A2-4. Particle Size Distribution for plataforma (PLA)...... 263

Table A2-5 .Particle Size Distribution for Retiro (RET)...... 264

Table A3-1. TSP Modal Mineralogy, Basilica (BAS)...... 266

Table A3-2. TSP Modal Mineralogy, Casa de Pedra (CDP)...... 267

Table A3-3. TSP Modal Mineralogy, Pires (PIR)...... 268

TableA3-4. TSP Modal Mineralogy, plataforma (PLA)...... 269

Table A3-5. TSP Modal Mineralogy, Retiro (RET)...... 270

Table A4-1. Particle Size Distribution Fe (hydr)oxides...... 272

Table A4-2. Particle Size Distribution Clay minerals...... 275

Table A4-3. Particle Size Distribution calcite...... 280

Table A4-4. Particle Size Distribution carbonaceous matter...... 285

List of Abbreviations

APM Airborne particulate matter

AFM Atomic force microscopy

AMS Aerosol mass spectrometer

AS Australian Standards

ATOFMS Aerosol time-of-flight mass spectrometer

BAS Basilica

BSE Backscattered electron

CDP Casa de Pedra

CRM Certified reference materials

dae Aerodynamic diameter

dp Physical (geometric) diameter

EELS Electron energy-loss spectrometry

ELPI Electric low pressure impactor

EPA Environmental Protection Agency

EPMA Electron probe X-ray microanalysis

FEG Field emission gun

FTIR Fourier transform infrared spectroscopy

GXMAP Grain-based X-ray mapping

HRTEM High-resolution transmission electron microscopy

ICDD International Centre for Diffraction Data

ICP-MS Inductively-coupled plasma mass spectrometer

IOM Institute of Occupational Medicine

kV Kilovolt

LAMPAS Laser mass analyzer for particles in the airborne state

LIBS Laser-induced breakdown spectroscopy

LMMS Laser microprobe mass spectrometry

LPI Low pressure impactor

mA Milliampere

MLA Mineral Liberation Analyzer

NIOSH National Institute for Occupational Safety and Health

NZS New Zealand Standards

PALMS Particle analysis by laser mass spectrometry

PIR Pires

PIXE Proton induced X-ray emission

PLA Plataforma

PM Particulate matter

QEMSCAN Quantitative evaluation of minerals by scanning electron microscopy

QF Quadrilátero Ferrífero

RET Retiro

RMS Raman microscopy

RSD Relative standard deviation

RSMS Rapid single-particle mass spectrometer

SEM-EDX/EDS Scanning electron microscopy with energy dispersive X-ray spectrometry

SIMS Secondary ion mass spectrometry

SP-ICPMS Single particle inductively coupled plasma mass spectrometry

SPMS Single particle mass spectrometry

TEM Transmission electron microscopy

TEOM Tapered element oscillating microbalance

TOF-SIMS Time-of-flight secondary ion mass spectrometry

TSP Total suspended particulates

USGS United States Geological Survey

Wt% Weight percent

XAFS X-ray absorption fine structure spectroscopy

XANES X-ray absorption near edge structure

XBSE Extended BSE

XRD X-ray diffraction

XRF X-ray fluorescence

XPS X-ray photoelectron spectroscopy

µm Micrometre

Chapter 1

Introduction

The adverse effects of airborne particulate matter (APM), or aerosols, on human health and the environment is an increasing and ever-present global concern. In 2013 the World Health Organisation’s International Agency for Research on Cancer (IARC) concluded that outdoor (ambient) air pollution is carcinogenic, with the particulate matter component affecting more people than any other pollutant and bearing a close association with increased cancer incidence(IARC, 2013). In 2017 air pollution was the fourth most common mortality risk factor, with approximately 4.2 million global deaths (GBD, 2018).

Epidemiological, clinical, and toxicological studies have identified a wide range of adverse health outcomes associated with APM including chronic obstructive pulmonary disease, lung cancer, cardiovascular disease and the onset of type-2 diabetes (Hong et al., 2002; Kim et al., 2015; Liu et al., 2013; Pope 3rd et al., 1995; Rajagopalan and Brook, 2012; Zanobetti et al., 2000) as well as deleterious effects on fertility and pregnancy (Bobak, 2000; DeFranco et al., 2015; Hackley et al., 2007; Radwan et al., 2016; Sapkota et al., 2012; Somers, 2011). There is also increasing evidence of the neurotoxicity of atmospheric particulates, especially in vulnerable groups such as children and the elderly (Brockmeyer and D’Angiulli, 2016; Cacciottolo et al., 2017; Elder et al., 2015; Wang et al., 2017b).

APM is a physically and chemically complex mixture of solid and liquid particles of organic and inorganic substances. Some particulates occur naturally but human activities, such as agriculture, industrial activities and mining, also generate significant amounts. The behaviour of atmospheric particulates and their effects on human health and the environment is strongly governed by particle properties, with size the most important parameter. As a result, an understanding of particle size distributions in the atmosphere is essential to the overall understanding of the origin and the potential effects of APM (Fig.1.1).

Figure 1.1 Relative sizes of airborne particulate matter. The PM nomenclature refers to particles with an aerodynamic diameter of less than 10 and 2.5 µm. Image courtesy of US EPA.

Coarse particles (>2.5µm) are generated primarily through mechanical processes, such as wind or abrasion, and are predominantly comprised of crustal elements such as silicon, aluminium, iron, calcium and sea-salt particles. Fine (<2.5 µm) and ultra-fine (<0.1 µm) particles are generated by nucleation and condensation, largely from high-temperature combustion sources, and are dominated by sulphates, nitrates, ammonia, elemental and organic carbon and metals (Brunekreef and Forsberg, 2005).Airborne particulates can also transport biological material such as pollen, spores, fungi, bacteria, viruses and endotoxins, some of which are pathogenic to plants, animals and humans, including meningitis, Valley Fever, foot and mouth disease and coral reef diseases (Degobbi et al., 2011; Garrison et al., 2006; Griffin, 2007; Hallegraeff et al., 2014; Morakinyo et al., 2016; Sprigg et al., 2014).

Unlike other pollution vectors, particulates in the atmosphere are not constrained by topographical boundaries and can be transported rapidly over vast distances (Fig. 1.2; Csavina et al., 2012). Research shows significant transport of natural and anthropogenic APM from Africa to Europe and the American continent (Kabatas et al., 2018; Prospero et al., 2014; Rizzolo et al., 2017), from Asia to North America (Ault et al., 2011; Tao et al., 2016), from North America to Europe (R. Pausata et al., 2013) and from Europe and Asia to the Arctic and Antarctic (Chin et al., 2007; Lee et al., 2015; Sand et al., 2017).

Figure 1.2 Modelled distributions of particulates in the atmosphere: mineral dust (red), sea spray (blue), combustion smoke and soot (green) and sulphate from fossil fuel combustion and volcanoes (white). Image from Knippertz and Stuut (2014).

Several guidelines and regulations have been adopted to define air quality levels and, though not legally binding in most countries, provide a basis for setting standards and limiting values for air pollution. Current air quality standards are expressed in terms of particle mass concentration of PM10 or PM2.5, which are mass concentrations of particles with aerodynamic diameters smaller than 10 and 2.5 µm, respectively. Despite these regulations more than 90% of the world's population are exposed to levels exceeding that of the World Health Organisation guidelines (Fig.1.3).

Figure 1.3 Percentage of the world's population exposed to PM2.5 pollution above World Health Organisation guidelines, 2016. Image courtesy of World Bank.

The health risks associated with APM arise from the inhalation and deposition of particles in the human respiratory system and depend on the physical properties of the particles such as size, shape and capacity to induce an inflammatory response. Coarse particles are deposited in the upper airways and are typically swallowed and eliminated through the digestive system (Fig.1.4). In contrast, particles <1µm are taken deep into the lungs where they may be transported directly to the blood stream (Darquenne, 2014). Particle size has also been shown to strongly influence solubility, with smaller particles more likely to be mobilized in body fluids due to their higher available surface area (Guney et al., 2016).

Figure 1.4 Depositional efficiency of APM in the human bronchopulmonary system. Image courtesy of the Encyclopaedia of the Environment.

The assessment of the potential environmental and human health risks associated with APM requires detailed physical and chemical characterisation. In the past, analysis has concentrated on determination of the size, mass concentration and bulk chemistry, however, the impact and toxicity of PM is related not only to total elemental composition and size distribution but also to mineral species present and the chemical heterogeneity of the particles. Information regarding chemical heterogeneity at the individual particle level is essential for understanding and predicting the reactivity, environmental and health impacts of particulates and to identify sources for mitigation techniques. While methods for

measuring particle concentrations and size distribution are well established, measuring particle composition at the single-particle level remains problematic.

Scanning electron microscopy with an energy dispersive X-ray spectrometer (SEM- EDS) has been widely used in atmospheric science, as it can generate information on size, morphology and elemental composition of individual particles. To obtain a statistically significant data set, however, a large number of particles need to be analysed which is time- consuming and costly using traditional manual methods. To overcome these drawbacks, computer-controlled SEM-EDS methods are gaining popularity.

1.1 Mineral Dust in the Atmosphere

Compared to trace gases and simple compounds such as sulphates, nitrates and sea- salt, geogenic APM, or mineral dust, has been relatively poorly investigated despite contributing more than half the total global aerosol burden, which has been estimated to be in the order of 1-3 billion tonnes per annum (Middleton, 2017). Natural sources of mineral dust are located in arid and semi-arid regions, however, over the past decades anthropogenic activities such as agriculture, mining and deforestation have significantly increased geogenic emissions (Fig. 1.5).

Figure 1.5 (left) Saharan dust storm extending into the Atlantic Ocean (image courtesy of NASA); (right) mine- derived geogenic emissions, Casa de Pedra Congonhas, Brazil.

Geogenic APM usually contains quartz, phyllosilicates such as clays and mica, carbonates, oxides and evaporites such as gypsum and potassium sulphate. It plays an important role in climate forcing by altering the radiation balance in the atmosphere through scattering and absorption of radiation (Schepanski, 2018). In addition to its direct radiative effect, mineral particles are recognised to affect climate indirectly by nucleating cloud droplets and ice (Engelbrecht and Derbyshire, 2010). During transport, mineral dust interacts with trace gases which alter the chemical balance in the atmosphere, particularly Ca-rich particles which can act as an acidity buffer and result in an increase in precipitation pH (Cao et al., 2005). Geogenic APM, particularly iron- and phosphorous-rich species, is also a vital source of nutrients in marine ecosystems and can increase primary productivity by stimulating nitrogen fixation by plankton (Griffin and Kellogg, 2004).

Amongst the anthropogenic sources of geogenic APM, mining operations potentially pose a significant risk to human health and the environment (Csavina et al., 2012b). They are especially notable due to the quantity of particulates produced, the extent of the affected area and the toxicity of contaminants associated with the emissions. Traditionally, research on environmental contamination from mining operations focused on the transport of contaminants via soil and water, with little attention paid to atmospheric dispersal, despite it being an important mechanism for exposure to potentially toxic metal(oids) (Csavina et al., 2011).

Although all stages of mining operations produce large quantities of APM, research has predominantly focused on the fine and ultrafine particulates generated by smelting processes with little attention paid to the impact of coarse (2.5-10 µm) particulates despite the majority of the particles generated occurring in this size fraction. Major sources of coarse geogenic APM from mining operations include fugitive dust from blasting and the removal of overburden (Bui et al., 2019; Silvester et al., 2009), loading and stockpiling(Cong et al., 2016; Lashgari and Kecojevic, 2016), transport (Kristensen et al., 2015; Singh and Perwez, 2018; Tian et al., 2019; Žibret et al., 2013) and tailings and waste piles (Castillo et al., 2013; de la Campa et al., 2011; Fernández-Caliani et al., 2013; Moreno et al., 2007). Furthermore, as larger particles remain suspended in the atmosphere for shorter periods of

time (minutes to hours) they can result in elevated surface concentrations of contaminants within a highly localised area.

1.2 The Mineral Liberation Analyzer (MLA)

The MLA is an automated digital image analyser coupled to a scanning electron microscope equipped with an energy dispersive X-ray spectrometer (SEM-EDS) that was developed to examine fine grained mineral mixtures, such as mill products and flotation concentrates, in order to improve the efficiency of mineral processing plants (Gu, 2003). The instrument is based on a Quanta SEM platform, fitted with dual, liquid nitrogen-free, SDD-type spectrometers, a BSE detector and a secondary electron detector. The SEM provides up to 30kV electron beam excitation energy, with typical operating conditions using an accelerating voltage of 25kV and beam currents of 10-15 nA. The smallest practical particle size that can be identified and mapped by the MLA software is 0.2µm. The SEM is available either as a conventional tungsten filament or Field Emission Gun (FEG) source system (Sylvester, 2012). The MLA software package controls the hardware settings of the SEM, including accelerating e-beam voltage, SEM magnification, BSE brightness and contrast, spot size and working distance. Backscatter data is acquired as a 256 level grey scale image and relates the backscattering coefficient (ƞ) value for each mineral to a range of greyscale values between 0 and 255.

MLA analysis relies on the segmentation of regions based on backscattered electron (BSE) brightness, with the average BSE greyscale value of each defined region corresponding with a phase of unique average atomic number. The first stage of the analysis identifies all distinct mineral phases and defines their boundaries. This process is called phase segmentation and is performed on each individual particle. After background elimination of the mounting material, phase segmentation outlines regions of homogenous BSE values and assigns a specific colour to each identified region (Fig.1.6). Following phase segmentation, the chemical composition for every homogeneous region is obtained by EDS. The system can be configured to collect only one X-ray spectrum per region or X-ray mapping across a grid. In a typical point measurement, the MLA performs one X-ray analysis (typically >2000 counts) for each grey level region identified within a segmented particle (Fandrich et al.,

2007). Using only single EDS measurement, the MLA is capable of analysing more than 10, 000 particles within an hour.

Figure 1.6 Particle classification process (a) Raw BSE image after background removal; (b) phase segmentation and EDS analysis; (c) classified particle.

Mineral classification compares the sample information with a pre-defined list of mineral spectra. This library is constructed before analysis and involves the collection of high quality X-ray spectra for each mineral in the sample with each mineral phase typically characterised by 2-5 spectra, depending on their complexity. Mineral phases are classified based on user-defined criteria and assigned a false colour to each mineral phase/composition to produce a mineral map of the particles which allows for the direct visual comparison of samples. X-rays that do not match any minerals are classified as “unknown” and can be relocated and classified with user input. The pixels representing each mineral phase in the classified particle is the basis for all subsequent quantitative analysis.

The use of BSE imaging for scanning of mineral grains has a number of advantages. Many more points can be analysed in a BSE image, with around 819, 200 bits of independent information obtained in 100 seconds, in contrast to the 40, 000-60, 000 X-ray points that can be obtained (Goodal et al., 2007). Spatial resolution is also higher for BSE imaging than X- ray analysis, with a resolution of between 0.1µm and 0.2µm compared to 2-5µm for X-ray

analysis (Gu, 2003). The use of BSE for particle segmentation also reduces the incidence of grey-scale overlap for minerals with the same or similar average atomic numbers (Burrows and Gu, 2006).

Although this technology has been used extensively in the mining industry for the past two decades, it is only recently that that this technique has been applied to other environmental fields, including predicting acid mine drainage (Parbhakar-Fox et al., 2017), identifying structural controls on hardpan formation in mine tailings (Redwan, 2012; Redwan et al., 2016), identifying the geochemical and mineralogical controls on metal mobility (Stavinga et al., 2017), soil contamination near a lead smelter (de Andrade Lima and Bernardez, 2017), identifying lead species in sintering dust (Tang et al., 2015), the source of aeolian dune sands (Li et al., 2019)and sediment provenancing (Øxnevad, 2017; Tsikouras et al., 2011). To our knowledge, the MLA has not previously been applied to the characterisation of ambient airborne particulates. An advantage of the MLA over other well developed techniques, such as the electron probe microanalyzer (EPMA), lies in their widespread use in the mining industry which precludes the need to invest in further instrumentation and user training.

1.2 Thesis Aims and Research Outline

The guiding question for this research is whether the Mineral Liberation Analyser (MLA) can be applied to characterisation of ambient airborne particulate matter.

The major objectives for this study are:

• Can particles be accurately classified by the reference spectral library? • Can the MLA produce statistically reliable data for sampled airborne particulates?

Flow-on objectives from this are:

• Can the MLA generate sufficient data to observe spatial and temporal variations in APM? • Can major source contributions of particulate emissions be distinguished

and

• Can potentially toxic elements and other target mineral phases be identified in ambient APM? To this end several areas need to be addressed:

1. the development of suitable sampling and sample preparation methods 2. the creation of a mineral database for the specific test site to enable the characterisation of the mineralogy in both the original material and in the ambient particulates 3. the identification of the spatial and temporal variations of the geogenic APM 4. the identification of the size distribution and chemical fractionation of transported mine-derived dust.

The aims and objectives of this research thesis will be addressed in five chapters.

A variety of methods and instruments are available for the physico-chemical characterisation of APM, ranging from filter-based sample collection for off-line laboratory analysis to on-line instruments that detect the airborne particles and generate size distribution and chemical data in real time. A single practical technique, however, does not exist for obtaining all the required information, specifically the size, morphology and composition. Chapter 2 “Sampling and Single Particle Analysis for the Chemical Characterisation of Fine Atmospheric Particulates: A Review” is a review of some of the techniques currently available for the sampling and subsequent analysis of individual inorganic particles.

Chapter 3 “Combining Gravimetric and Single Particle Analysis to Determine the Contribution of an Active Gold Mine to Arsenic in the Atmosphere” uses SEM-based single particle analysis in combination with traditional gravimetric measurements to ascertain the source(s) of APM and the contribution of an active gold mine to arsenic in the atmosphere. Although single-particle analysis revealed the absence of arsenic-rich phases, suggesting the mine is not a major contributor to the atmospheric arsenic load, the manual processing of the EDS data was time-consuming and prone to operator bias.

Chapter 4 “Single-Particle Analysis of Atmospheric Particulate Matter Using Automated Mineralogy: The Potential for Monitoring Mine-derived Emissions” details the development of the methodology for the analysis of APM using the Mineral Liberation Analyzer (MLA). This chapter outlines the considerations in determining the optimal sampling technique and filter substrate for subsequent MLA analysis. The accuracy and precision of the instrument were tested by repeat analyses and by comparing the modal mineralogy with two certified reference materials, achieving relative standard deviations of typically less than 10%. From the pilot study to test the newly developed methodology the technique was shown to have a significant potential for the rapid acquisition of reliable data for the characterization of airborne particulates, which is requisite for effective emissions management and for the monitoring of human and environmental health.

The remaining chapters focus on detailed characterisation of geogenic emissions by MLA. Chapter 5 “Characterisation of Airborne Particulate Matter Near a Large-Scale Iron- Ore Mine by Automated Mineralogy” outlines the findings from the detailed analysis of ambient APM samples collected from 5 locations over 3 sampling periods. The mineral phases observed strongly reflected the local geology, with clays and iron oxides contributing to approximately 70-80% of the particulates sampled. Particle size distributions indicate sources dominated by mechanical processes, with coarse particles (>2.5 µm) accounting for more than 80-90% of the samples. A strong seasonality was observed with greatest proportions of coarser particles during the dry seasons of May and August. Particle numbers for individual mineral phases also reflected this seasonality, although the similarity in numbers in the coarse and fine fraction during January and August indicates a relatively high proportion of agglomerated particles during these periods.

Chapter 6 "Characterisation of Manganese-Bearing Mineral Phases in Atmospheric Particulate Matter" highlights the potential of the MLA to target potentially toxic elements and other species of interest in ambient APM. As the toxicity of inhaled manganese depends not only on its physical parameters, such as size and shape, but also on its chemical species, the ability to identify and characterise different Mn-bearing phases is essential to accurately assess its potential environmental and human health impacts. The most common

Mn-bearing phases observed were Mn oxide and jacobsite, with minor amounts of spessartine, rhodonite, romanechite and Al-rich Mn oxide. Mn-bearing phases were predominantly in the coarse and super-coarse fractions, suggesting that the risk of inhalation toxicity is potentially relatively low.

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Chapter 2

Sampling and Single Particle Analysis for the Chemical Characterisation of Fine Atmospheric Particulates: A Review

This chapter has been re-produced from the Journal of Environmental Management.

Abstract To better understand the potential environmental and human health impacts of airborne particulate matter (APM), detailed physical and chemical characterisation is required. The only means to accurately distinguish between the multiple compositions in APM is by single particle analysis. A variety of methods and instruments are available, which range from filter-based sample collection for off-line laboratory analysis to on-line instruments that detect the airborne particles and generate size distribution and chemical data in real time. There are many reasons for sampling particulates in the ambient atmosphere and as a consequence, different measurement strategies and sampling devices are used depending on the scientific objectives and subsequent analytical techniques. This review is designed as a guide to some of the techniques available for the sampling and subsequent chemical analysis of individual inorganic particles.

2.1 Introduction

Compared to trace gases, airborne particulate matter (APM) is a complex mixture of solid and liquid particles of organic, inorganic and biological substances. Some particulates occur naturally but human activities, such as traffic and industrial emissions, also contribute significant amounts of particulates. The assessment of the potential environmental and human health risks associated with fine APM (>1µm) requires detailed physical and chemical characterisation. In the past, analysis has concentrated on determination of size, mass concentration and bulk chemistry. Individual particles however, vary in properties such as toxicity, light attenuation and hygroscopic behaviour which are functions of their three- dimensional chemical composition. The impact and toxicity of APM is related not only to

total elemental composition and size distribution but also to their chemical heterogeneity. Information regarding chemical heterogeneity at the individual particle level (the mixing state) is essential for understanding and predicting the reactivity and environmental and human health impacts of APM. The only means to accurately distinguish between the multiple compositions in APM is by single particle analysis.

Once in the atmosphere, and under favourable weather conditions, particulates can be transported over long distances by prevailing winds and can act as a vector for pollution. As pollutants are commonly taken up on the particle surface, they are typically present in loosely bound forms that are highly mobile and potentially bio-available. The health effects of exposure to APM are well documented (Møller, 2008; Pope et al., 2004; Zanobetti and Schwartz, 2009) and as a result several guidelines have been adopted (Table2.1). These guidelines, though not legally binding in most countries, provide a basis for setting standards and limiting airborne particulate pollution. The most frequently used reference guidelines for ambient particulate concentration are the World Health Organisation Air Quality Guidelines(WHO, 2000), the European Union Limit Values for Air Quality (European Union 2008) and the United States Environmental Protection Agency National Ambient Air Quality Standard (Environmental Protection Agency (EPA), 1997). Most guidelines are measured in µg/m3 and averaged over a 24 hour time period, however the United Kingdom and European Union standards are averaged over a year. These guidelines are based on clinical, toxicological, and epidemiological evidence and were established by determining the concentrations with the lowest observed adverse effect, however, to date there is no evidence to support a threshold level below which no adverse health effects occur (Kim et al., 2015).Standards have also been implemented for other air toxins such as lead, cadmium, arsenic and mercury, however, these lie outside the scope of this review.

Atmospheric residence time, deposition rates, and inhalation processes are predominantly influenced by the size of the particles. Even though many particles are not spherical, they are typically classified to size by their aerodynamic diameter which is defined as the diameter of a spherical particle of density 1g/cm3 having a settling velocity equal to that of the particle in question (John, 2011). The aerodynamic diameter is useful for particles larger than 0.5µm and is considered to be the most appropriate measure to describe particle motion in the atmosphere (Sullivan and Prather, 2005)and the ability of the particle to

penetrate and deposit at different sites within the respiratory tract (Pinkerton, 2000).The aerodynamic properties of particles also depends on density and shape. The health risks associated with APM arises from the deposition of particles in the human respiratory system (Fig. 2.1). After inhalation, particles in the 2.5-10 µm size fraction (thoracic particles) are primarily deposited in the tracheal and bronchial region, from where they are transported by mucociliary processes and typically swallowed, thus reaching the gastrointestinal tract. Finer particles can travel deeper into the alveolar region (respirable particles) where they interact with lung fluids (Asgharian et al., 2001). Ultrafine particles (<0.1µm) can not only deposit in the respiratory tract, they can also traverse the alveolar epithelium to be absorbed directly into the bloodstream. Their large specific surface area, with its increased surface reactivity, has the potential to result in greater toxicity (Oberdörster et al., 2005). These ultrafine particles not only have an enhanced inflammatory potential, they also have a higher deposition efficiency within the pulmonary system. There has been an increasing awareness of the impacts of these ultrafine particles, however methods for characterizing these particles is outside the scope of this review. The site of particle deposition within the respiratory system strongly influences the health effects of exposure to these particles and, as a result, regulation and monitoring of APM has evolved over time from total concentrations (total suspended particulates, TSP) to a focus on smaller inhalable particles that can be deposited into the respiratory system, namely fine (PM2.5) and coarse (PM10) particles, which are defined as particles with an aerodynamic diameter of less than 2.5µm and 10µm respectively.

While methods for measuring particle concentrations and size distribution are well established, the compositional analysis of single particles remains problematic. A variety of methods and instruments are available, which range from filter-based sample collection for off-line laboratory analysis to on-line instruments that detect the airborne particles and generate size distribution and chemical data in real time. Despite the array of instrumentation, a single practical technique does not exist for obtaining all the required information, specifically the size, morphology, composition and molecular structure of fine particulate matter(Pratt and Prather, 2012). The ultimate goal of analytical techniques developed for APM is to quantitatively identify all species within each individual particle but as single particles are complex mixtures containing in the order of ~10²-1015 molecules per

particle, which translates to masses in the order of ~10-20 to 10-6 g/particle, measurement can be challenging (Pratt and Prather, 2012).

Figure 2.1 Deposition of APM in the respiratory system (background image from msnucleus.org)

Off-line techniques generally allow for greater molecular and structural speciation than on-line techniques, however, on-line techniques are able to examine the chemical changes in APM on short time scales (Pratt and Prather, 2012). In most APM measurement applications, the challenges of selecting the instruments and the measurement strategy that will provide the desired information often dominate the measurement approach. This review is designed as a guide to some of the techniques available for the sampling and subsequent chemical analysis of individual inorganic particles.

2.2 Air sampling techniques

There are many reasons for sampling particles in the ambient atmosphere including compliance with air quality standards, data for epidemiological studies and assessment of pollution sources. As a consequence, different measurement strategies and sampling devices are used depending on the scientific objectives.

Table 2.1 International Air Quality Standards for total suspended particulates (TSP), PM10 and PM2.5 (µg/m³, 24 hour mean unless otherwise stated).(a)(Defra, 2012);(b)(National Environment Protection Council, 1998); (c)(National Environmental Standards for Air Quality, 2004); (d)(SANS 1929, 2011); (e)(Clean Air Initiative for Asian Cities, 2010); (f)(Clean Air Institute, 2012). WHO AQG - World Health Organisation Air Quality Guidelines; NAAQS – National Ambient Air Quality Standard; EU LVAQ – European Union Limit Values for Air Quality.

TSP PM10 PM2.5 WHO AQG - 50 25 NAAQS (United States) - 50 35 EU LVAQ (Europe) - 50 25 (annual mean) United Kingdom (a) - 50 25 (annual mean) Australia (b) - 50 25 New Zealand (c) - 50 - South Africa (d) - 120 65 China (e) 300 150 - Hong Kong (e) - 100 75 India (e) - 100 60 Japan (e) - 100 35 Bangladesh (e) - 150 65 Bhutan (e) 200 100 -

Indonesia (e) 230 150 - Malaysia (e) 260 150 - South Korea (e) - 100 50 Mongolia (e) 150 150 50 Nepal (e) 230 120 - Singapore (e) - 150 35 Pakistan (e) 500 150 35

Philippines (e) 230 150 - Sri Lanka (e) - 150 50 Thailand (e) 330 120 - Vietnam (e) 200 150 - Bolivia (f) - 150 - Brazil (f) - 150 - Colombia (f) - 100 50 Chile (f) - 150 50 Ecuador (f) - 150 65 Mexico(f) - 120 65 Peru (f) - 150 50 Puerto Rico(f) - 150 35

2.2.1 Active samplers

Traditionally, most atmospheric monitoring programs have relied on the use of active air samplers to assess the levels and spatial and temporal variability of atmospheric pollutants. The most common approach is by actively aspirating air through a filtering media using a pump. The rationale of the process is to accumulate a sufficient particle mass over the filtering media (the particle collector) for a statistically robust determination of

total particle mass, while at the same time being able to accurately measure the amount of air pumped through the filter so total particle concentrations can be measured and reported as particle mass per cubic meter of air.

Typically, active samplers are deployed for short time periods (< 24 hours) but in high frequency (Hayward et al., 2010). Active samplers provide reliable quantitative concentration data, and high temporal resolution, however, they are expensive to operate and require a stable power source and frequent maintenance which makes them inappropriate for unattended operation and/or in remote areas.

The original reference method for TSP involved a high-volume (hi-vol) active air sampler accompanied by gravimetric analysis to determine the bulk weight of particulate matter in the atmosphere (U.S EPA, 1982). The typical flow rate of hi-vol samplers ranges between 100-1000 L min-1 and as a result, these samplers require a relatively porous filter media withlow flow resistance. The most commonly used filters for hi-vol sampling are either glass fibre or cellulose however the inherent design of these filters, which generates their high-loading capacity, is typically unsuited for many single particle analytical techniques (see section on sampling substrates). Hi-vol sampling can also be unsuitable for individual particle analysis due to over-accumulation resulting in overlap of particles.

As the international guidelines have evolved from measuring TSP to PM10 and PM2.5 so has the range of instrumentation, although most involve either cyclones or impactors for particle-size separation. Conventional cascade impactors operate at atmospheric pressure and as the air passes through a sequence of stages, particles larger than the cut-off size are collected, with smaller particles following the gas flow to be collected in the next stages (Fig. 2.2). In conventional impactors, the substrates are placed with the collection surface parallel to the air flow at the exit of the particle acceleration nozzle. A constant flow rate results in an increase in velocity at each stage, resulting in deposition of size-fractionated particles.

This method of collecting size-fractionated samples can suffer from the effects of particle bounce and re-entrainment which frequently result in substantial errors in the measured mass concentrations (Markowski, 1984). Conventional samplers also require regular cleaning to prevent the build-up of particles which has the potential to affect the

cut-off characteristics. The cut-off point can also be affected by flow-rate, acceleration nozzle diameter and particle density, composition and shape. The most common cascade samplers are the Andersen cascade impactor and the low pressure impactor.

Figure 2.2 Cascade impactor (TISCH Environme ntal, 2015)

Another group of cascade impactors are based on the Micro-Orifice Uniform Deposit Impactor, which uses micro-orifice nozzles for jet acceleration. The MOUDI has features not normally found in other cascade impactors (Marple et al., 1991). The sampler covers a broad range of particle sizes and is equipped with various combinations of impacting stages, capable of collecting particles smaller than 0.056 µm. By rotating the impaction plate relative to the nozzles, particles are deposited uniformly over the entire plate (Maenhaut et al., 1993). The uniform deposit prevents heavy particle build-up under the nozzles thus reducing particle bounce. The type of collection substrate is determined by the type of particulates to be collected and the subsequent analytical method, with thin foils or membrane filters typically used.

The virtual impactor, or dichotomous sampler (Fig. 2.3a), achieves inertial size- segregation under laminar flow conditions as the airstream impacts against a mass of

relatively slow moving air rather than against a plate thus avoiding particle bounce and re- entrainment from the impaction surface(Solomon et al., 1983).Air is drawn through a size- selective inlet restricted to particles <10 µm. Particles are subsequently fractionated into a fine (<2.5µm) and coarse (2.5-10µm) fraction which are collected on separate Teflon filters. The inlets are designed so that 50% of particles of the critical size are rejected, however as the cut-off characteristics depend on the speed of the air passing through the inlet, flow control and calibration are essential for accurate size fractionation. Typically, the dichotomous sampler operates at a low sampling rate (<20L min-1), though medium-volume (50 L min-1) and high-volume (>50 L min-1) dichotomous samplers are also commercially available.

Figure 2.3 a) Dichotomous impactor (McFarland et al., 1978); b) Cyclone impactor (Bergmans, 2014).

A range of real-time instruments have been developed to provide the virtually continuous monitoring of TSP, PM10, PM2.5 and PM1.Several papers have provided comprehensive reviews of the capabilities and limitations of these instruments (Chung, 2001; Schwab, 2006). Although some of these instruments allow the collection of samples for further single particle analysis, the physical and chemical nature of the substrate used for

sample collection is typically not suitable for optical/SEM analysis and instrumental design makes it difficult to obtain undisturbed and reliable samples.

A commonly used real-time instrument is the tapered element oscillating microbalance analyser (TEOM). In this device APM is measured by passing air through a hollowed tapered element where the particles are collected on a filter. The tapered element oscillates at a frequency that is inversely proportional to the weight of particles collected on the filter (Chung, 2001). Typically the TEOM operates 3 L min-1 with a filter temperature of 50°C to avoid condensation and to maintain a constant temperature for the tapered element to minimize thermal expansion. This heating however results in losses of semi-volatiles which has been shown to potentially lead to lower estimations of APM concentrations (Allen et al., 1997). To overcome this limitation, a Filter Dynamics Measurement System (FDMS) was developed which operates at 30°C, enabling the measurement of volatile particles. Although TEOM filters are typically composed of glass fibre, several studies have used them with scanning electron microscope with energy dispersive X-ray (SEM-EDX) for elemental and morphological studies (Baquero et al., 2015; Chung et al., 2012; Srivastava and Jain, 2007; Williamson, 2013).

Another real-time sampler is the electric low pressure impactor (ELPI). The ELPI is comprised of three main components; a cascade impactor, a unipolar diode charger and a multichannel electrometer (Marjamäki et al., 2000). Particles are first charged to a well- defined charge level before the particles are introduced into the impactor. The electrometer is used to simultaneously measure the charges carried by the collected particles from each stage which is then converted to number concentration. Typically the ELPI operates at 10 l/minute and can collect particles down to 3nm in size (Marjamäki et al., 2000).

In contrast with the static instruments described above, which are typically bulky, require a dedicated installation site and are left at the same location for the duration of the monitoring program, personal exposure samplers and monitors have been developed to assess the level of exposure of particular individuals to APM as they perform their daily routine. These devices typically consist of a small battery-operated pump which is attached to the belt or carried in a backpack, tubing to connect the pump with the sampling device

and the sampling device itself, which is normally placed near the person’s face and consists of a protective casing and substrate for particle collection. The pump is usually configured to low flow-rates of approximately 2 L min-1 to simulate the typical air intake of an adult. The design of these devices are typically based on either cyclone or impactor samplers which allows for the collection of either respirable or inhalable size fraction.

Inertial separation in cyclone impactors is achieved by the creation of a vortex-like flow in which large particles that cannot follow the streamlines exit the flow and are deposited on the walls of the cyclone (Fig.2.3b). As this method of particle segregation mimics the removal of large particles in the upper respiratory tract, cyclones have been used to measure the respirable fraction of APM in occupational and personal air sampling since the early 1960’s (Fig. 2.4a).

With the increasing awareness of the health impacts of respirable particles, personal samplers designed to measure the total inhalable fraction have been developed. An example of a widely-used device is the Institute of Occupational Medicine (IOM) personal sampler (Fig. 2.4b) (Kenny et al., 2001; Mark and Vincent, 1986). This sampler is designed to sample particles with an aerodynamic diameter of up to 100µm however the sampling efficiency has been shown to deviate with low (< 0.5ms-1) and high wind (> 4 ms-1) (Kenny et al., 1997).

2.2.2 Passive Samplers

Passive sampling has been suggested as a low-tech and cost-effective monitoring tool which can avoid most of the disadvantages of active sampling techniques (Brown, 1996). It is especially useful for multipoint sampling over large and remote areas where a reliable power source cannot be guaranteed. Passive samplers, however, have a lower sampling efficiency compared to active samplers and as a result, a longer sampling time (>24 hours) is required to obtain sufficient particle mass.

Passive samplers are usually based on a combination of gravity, inertia, electrostatic attraction and convective diffusion. Capture by gravitational forces, however, is highly biased towards larger particles and on its own unsuitable for measuring the fine and ultrafine fractions of APM. Also, samplers do not collect all sizes with equal probability, depending significantly on the speed and direction of the wind. As a result, the accuracy and

precision of these devices may not meet sampler performance standards prescribed for regulatory measurements (Butler et al., 2013).

Figure 2.4 Personal exposuresamplers. a) Cyclone; b) IOM (Zefon, 2016)

A common passive sampler is the Sigma-2. With an almost wind-free interior, impaction of particles is achieved via sedimentation, with the virtual elimination of deposition by turbulent diffusion. Coarse particles (>2.5 µm) are sampled onto a transparent collection plate coated with a weather-resistant adhesive, with subsequent single-particle analysis by optical microscopy to obtain size distributions and particle type based on morphology and optical features in transmitted light (Guéguen et al., 2012). By assuming spherical shape and unit density for all particles, a size fractionated mass deposition rate can also be calculated (Norra et al., 2016). The instrument and analysis method have been calibrated to provide an output in size-fractionated bulk particle mass per cubic meter of air, however the results of Sigma-2 analyses cannot be directly compared with those of active samplers although a broad correlation exists between TSP data obtained using hi-vol samplers and Sigma-2 APM data (Anonymous, 2013). Since the 1980’s, the Sigma-2 sampler has been used for the assessment of air quality in German spas by the German Meteorological Service and in world-wide research projects.

In the passive sampler developed by Wagner and Leith (2001) APM concentrations are estimated from the surface loading of collected particles and a knowledge of the flux, or rate of transfer, of these particles to the sampler. Surface loading is determined by microscopy, by counting and sizing deposited particles while the flux is estimated from a semi-empirical model that is a function of the particle aerodynamic diameter. The sampler consists of a standard aluminium or carbon scanning electron microscope (SEM) stub, a collection substrate and protective mesh cap. During sampling particles are transported by gravity, diffusion and inertia through the holes in the mesh cap and deposited on the foil substrate mounted on the stub.

2.2.3 Sampling substrates

Selecting a substrate is a key issue which needs to take into consideration the proposed analytical technique(s) as there is no filter amenable to the full complement of analyses for individual particle characterisation. Filter selection therefore becomes a compromise between various factors, namely cost, collection efficiency, the requirements of the analytical procedures and the ability of the filter to retain its filtering properties and physical integrity under sampling conditions. The applicable method must also allow particles to be presented as a homogeneous uniform deposit without a significant effect on particle characteristics (Maynard, 2000). A desirable filter should have high collection efficiency and the capacity to retain large sample masses and as all filters contain various elements as major, minor and trace components, the optimum filter should have little or no background level for the elements being analysed. Commonly used filter substrates include glass fibre, quartz, Teflon and polycarbonate (Table 2.2).

Glass fibre filters are depth filters, consisting of compressed borosilicate glass fibres which form an irregular three-dimensional mesh with interspaces of variable sizes. As a result, particles are both retained on the surface and trapped within the filter structure. They have a high collection capacity and tolerate high flow rates, however the high and variable filter blanks can affect the analysis of metals in APM, particularly zinc and iron and to a lesser extent aluminium, calcium and barium(Schroeder et al., 1987). The thermal stability of these filters makes them useful for gravimetric analysis though due to the

complex structure they are unsuitable for direct analysis using electron microscopy. The chemistry of the fibres can also interfere with X-ray analysis due to the background signals contributed by the elements in the filter matrix.

Quartz fibre filters are also depth filters. Their low and relatively constant blank values allows for the analysis of metal components, however analysis of aluminium and silica can be problematic. Similar to the glass fibre filters, they are unsuitable for electron microscopic analysis. They are also relatively friable, with the potential for filters to flake off in the filter holder, making them unsuitable for gravimetric analyses.

Membrane and pore filters, such as Teflon and polycarbonate, are surface filters, with particulates collected solely on the top of the membrane. Although their loading capacity is lower than depth filters, their blank values are near zero which makes them ideal for the analysis of metallic components. Teflon filters are made from polytetrafluoroethylene (PTFE) and are hydrophobic, resistant to acids, alkalis and solvents, and have high thermal stability. A low tare rate makes these filters ideal for gravimetric analysis. Polycarbonate filters are pore filters with uniformly sized pores. They have a low, uniform weight, are non-hygroscopic, chemically inert and can be used for gravimetric analyses. They are mechanically strong and their smooth surface allows for good resolution making them ideal for electron microscopy, however analysis of micron and submicron size particles can be problematic, with the X-ray signals difficult to detect against the substrate spectra and the broad continuum background (Nelson et al., 2001). Other commonly used membrane filters are silver foil and carbon coated TEM grids. The TEM grid is a metal mesh screen, typically 2-3 mm in diameter and come in a variety of mesh shapes and sizes, ranging generally from 50 to 400 holes per inch. Grids are usually made of copper, though beryllium, gold, molybdenum, steel, titanium and nickel grids are also used.

2.3 Off-line analytical techniques

Off-line techniques are characterised by distinct collection and transportation procedures prior to analysis. These techniques are valuable, especially for detailed, specific investigations and for sampling in areas where on-line instruments cannot be used because

of size or operating conditions. These techniques, however, suffer from both positive and negative artefacts: evaporative losses can occur during sampling, storage and transport of samples which can cause significant errors; gases can be adsorbed onto filters and react with surfaces; particulate filter loading can result in some of the sample being bounced or blown off the filter and samples may also further react with other compounds within the sample or the collection substrate during storage (Sipin et al., 2003). For this review, off-line techniques have been divided in electron microscopy-based and atomic spectrometry- based.

2.3.1 Electron Microscopy

Over the years, micro-beam analytical techniques have been increasingly used to provide information on the physical, morphological and chemical properties of single atmospheric particles, including scanning electron microscope (SEM), computer controlled SEM (CCSEM) and transmission electron microscopy (TEM). Among them, Electron Probe X- ray Microanalysis (EPMA) based on SEM equipped with an Energy-Dispersive X-Ray (EDX) detector has shown itself to be an effective technique to investigate the size and elemental composition of single solid dry particles (Sobanska et al., 2003).

SEM-EDX has been extensively used to characterise the mineralogical phase of individual particles. It enables the morphological and elemental analysis of single particles down to a nominal diameter of 0.1µm with a detection limit of 1-10 %, depending on the element analysed, and can provide quantitative data on elemental composition (Laskin and Cowin, 2001). Deboudt et al. (2008)noted that the technique, which requires only small sample sizes (1000 particles) and with sampling times as short as a few minutes, was able to describe temporal variations in the chemical composition of the particles.

As the 2D geometrical information from the SEM images cannot reveal the full particle shape and volume, a coupling of this technique with atomic force microscopy (AFM) was suggested to determine both morphological and particle mass estimation as the 3D technique of AFM can provide a more accurate morphological measurement (Barkay et al., 2005). AFM, however, provides no elemental data and despite providing a good estimate on volume, it still requires knowledge of the composition to derive the particle density.

Automated systems for mineralogical characterisation using SEM-EDX are of increasing importance because of their ability to rapidly analyse individual particles (~10, 000 particles/hour) and provide mineral/phase identification alongside size and shape characterisation for different size categories. Originally designed to examine fine grained mineral mixtures in order to improve the efficiency of mineral processing plants, QEMSCAM (Quantitative Evaluation of Minerals by Scanning Electron Microscopy) has recently been applied to the characterisation of urban PM10 in London (Williamson et al., 2013) and to quantify respirable crystalline silica in ambient air around open-cut coal mines to determine the potential health-risks to the surrounding population (Morrison, 2011).

Although SEM-EDX measures the elemental composition, it is unable to provide information on volume and Williamson et al. (2013) noted that mass measurements were problematic due to mineral categories containing a number of different mineral and chemical species. Another limitation in EPMA analysis lies in the loss of semi-volatile components under the vacuum and the determination of low-Z elements such as carbon, nitrogen and oxygen is hindered by the absorption of characteristic X-rays by the beryllium windows of the EDX detectors (Stefaniak et al., 2006). To overcome this, a low-Z particle EPMA, using an EDX with an ultrathin polymer window, was developed by Ro et al. (2000), which allows for the quantitative determination of low-Z elements.

Current knowledge of the internal structure of atmospheric particles collected under ambient conditions presents a significant analytical challenge due to particle size as well as the physical and chemical complexity(Sobanska et al., 2014). Most molecular characterizations of size-segregated particles to date have used confocal Raman microscopy (RMS) (Batonneau et al., 2006; Iordanidis et al., 2014; Potgieter-Vermaak and Van Grieken, 2006) or Fourier transform infrared (FTIR) spectroscopy (Ryu and Ro, 2009; Song et al., 2010).

As each molecular species exhibits a characteristic “fingerprint” Raman spectrum, Raman mapping can be used to determine how different chemical components are distributed spatially within a single particle. The sensitivity of Raman spectrometry, which enables the analysis of composition, phase and crystal orientation, makes it an ideal tool for characterizing particles (Sobanska et al., 2014). The information obtained by this technique

includes molecular characteristics, identification of different mineral phases and the determination of different oxidation states. A limitation of this technique is that due to the refraction limit particles need to be greater than 1µm.

A method combining low-Z particle EPMA and RMS has also been used to characterise the internal structure and physiochemical properties, including speciation and mixing state of APM. This emerging technique, called the Raman SCA (structural and chemical analyser), has been used to speciate iron in underground subway particulates (Eom et al., 2013) and identify the internal structure and physiochemical properties of Asian dust (Sobanska et al., 2012).

Detailed knowledge about internal particle structure can also be obtained using a high-resolution transmission electron microscope (HRTEM). HRTEM has been demonstrated to be a powerful tool for the analysis and identification of individual submicron airborne particles by revealing details of the microstructure, composition, morphology, bonding structure and elemental oxidation states within particles (Pósfai, 2013; Semeniuk et al., 2014). Through the use of high-resolution imaging and selected-area electron diffraction, HRTEM has been used to identify the phase and crystalline structure of particles (Li et al., 2003). It has also been used in combination with electron-beam based spectroscopy to provide element-specific chemical imaging along with structural and elemental characterization (Pósfai and Buseck, 2010). While this technique provides sensitive chemical analysis, it is limited to the analysis of submicron size particles that are sufficiently transparent to the electron beam and to analyse larger, non-transparent particles using these techniques, the milling of particles down to a thickness accessible by the instrument is required.

2.3.2 Atomic Spectroscopy

As the chemical reactions that occur during atmospheric processing occur primarily on particle surfaces, the determination of the surface composition of APM is important to understand transformation and growth processes (Guascito et al., 2015). Particle surfaces can also adsorb potentially toxic contaminants, which come into direct contact with body fluids after inhalation (Klejnowski et al., 2012). X-ray photoelectron spectroscopy (XPS) is a surface sensitive technique with an analysis depth of less than 10nm. It has the ability to

determine and quantify the average metal speciation of particle surfaces. A number of studies have used this technique to obtain information about elemental composition, surface chemistry and chemical states of particulates collected on filters (Cheng et al., 2013; Vander Wal et al., 2011). Samples can be directly examined by XPS without any sample preparation and the concentration of elements can be determined with an accuracy of up to 0.1 % (Cheng et al., 2013). Although this technique offers a contribution in determining average metal speciation of the particle surface, the requirement of charge compensation, spectral decomposition and a complete database of reference spectra was considered by Batonneau et al. (2004) to be a limiting factor.

Secondary ion mass spectrometry (SIMS) is another well-established surface characterization technique that has been used for spatially resolved chemical imaging in inorganic particles. The inherent depth profiling capabilities, along with its high sensitivity and full elemental coverage, its capability of measuring isotope ratios and its ion imaging potential of specific constituents makes it a valuable technique (Berghmans et al., 1994). It has the ability to generate multiple mass spectra of both polarities from a single particle, allowing for the determination of heterogeneities associated with depth in a particle (Suess and Prather, 1999). A limiting factor with this technique, however, is due to the size range of atmospheric particulates. To characterise the broad range of particles requires a highly focused ion beam that is not standard in conventional SIMS instruments. Also, most SIMS applications are performed in the dynamic mode that uses high ion doses for elemental analysis as a function of depth. Under these conditions, most of the molecular information is lost (Sipin et al., 2003). The irregular topography of particles can also degrade the depth resolution to a considerable extent (Berghmans et al., 1994). The development of a nanoscale SIMS (NanoSIMS) has aided in overcoming some of these issues. The high resolution (<100 nm) and greater sensitivity (>10 times higher than conventional SIMS) can measure up to five different secondary ions simultaneously, enabling analysis of small particles with a high degree of precision (Harris et al., 2012).

Although most of the studies using this technique are related to biological materials and soil aggregates several studies have applied it to the chemical characterisation of APM (Ghosal et al., 2014; Winterholler et al., 2008)

With its high spatial resolution (~100 nm) and surface sensitivity, time-of-flight SIMS (TOF-SIMS) has also proven valuable in studying the surface composition of individual particles and a combination of static and dynamic operation of the TOF-SIMS allows the analysis of chemical speciation as a function of depth within an individual particle(Prather et al., 1994).The high detection sensitivity also enables the detection of trace elements, however as the quantification of TOF-SIMS data is done using standards with known chemical compositions and concentrations, quantifying the complex chemical composition of APM can be problematic (Zhu et al., 2001).

A technique with significant potential for elemental speciation of fine APM is the synchrotron-based technique of extended X-ray absorption fine structure spectroscopy (EXAFS). This technique is non-destructive, sensitive to ppm concentrations and can be used directly either with bulk or filter samples (Huggins et al., 2000). As each element has a characteristic and unique X-ray absorption edge, there is virtually no spectral interference from co-existing elements (Sakata et al., 2014). This method has been successfully used to identify the chemical species of Fe(Takahashi et al., 2011) and Pb (Sakata et al., 2014).

X-Ray absorption near edge structure (XANES), which can detect metal chemical forms on the basis of electron states around the target element, has been successfully used to measure the speciation of Pb (Barrett et al., 2010), S(IV) (Higashi and Takahashi, 2009), Cu and Zn (Osán et al., 2010)and As (Kim et al., 2013). This technique is capable of non- destructive speciation of metals in solid samples even when the element occurs in low concentrations. In this technique, the XANES spectra is used as a fingerprint and compared with the spectra of reference materials. Although it can determine elemental oxidation states and main chemical components, it is only a qualitative method and cannot measure elemental concentrations (Hiranuma et al., 2013).

Table 2.2. Physical and chemical characteristics of common air filters and compatible single particle analytical techniques. (a)(SKC, 2015) ; (b) (Sartorius, 2015); (c) (Millipore, 2015); (d)(Agar Scientific, 2015)

Filter Type Physical Characteristics Chemical Characteristics Compatible Single Particle Techniques

Glass Fiber (a) • Borosilicate glass • Inert XPS (Song and Peng, 2009) • High loading capacity • Res is ta nt to a ll but s trongly • Heat resistant (max ~600°C) alkaline bases or acids • Diffus es transmitted light • High blank levels of Zn and Fe • Low flow resistance • Low hygroscopicity

Quartz Fiber (a) • Quartz • Inert SP-ICP-MS (Lynam et al., 2013) • Humidity resistant • Large and variable quantities XANES (Higashi and Takahashi, 2009) • Heat resistant (max ~ 1000°C) of Al and Si • Diffus es transmitted light • Soft/friable edges can flake in filter holders • High particle collection efficiencies • Moderate flow resistance

Polycarbonate • Mechanically strong • Inert SEM/TEM(Saitoh et al., 2008) (a) • Microscopically smooth • Chemically resistant XPS(Klejnowski et al., 2012) • Precise pore sizes • Low blank levels RMS (Nelson et al., 2001) • Moderate flow resistance • Low hygroscopicity PIXE (Berghma ns et al., 1994) • Retains static charge

Filter Type Physical Characteristics Chemical Characteristics Compatible Single Particle Techniques

Teflon (PTFE) • Temperature resistant to 260°C • Inert XPS (Cheng et al., 2013) (a,b) • Hydrophobic • Low tare mass TOF-SIMS (Zhu et al., 2001) • Low blank levels PIXE (Lucarelli et al., 2011) • Resistant to acids, bases and XAFS (Furukawa, 2011) solvents XANES (Higashi and Takahashi, 2009) SEM-EDS (Saitoh et al., 2008) FTIR (Anıl et al., 2014)

Silver membrane • High flow resistance • Low background EPMA (Spolnik et al., 2004) (c) • Resistant to thermal stress (max • Resistant to chemicals Low-Z EPMA (Ro et al., 2000) 550°C) • Low hygroscopicity RMS (Worobiec et al., 2010) • Reusable • High blank weight SIMS (Rogowski and Bem, 2006)

Coated TEM Grid • Porous carbon membrane on • No background inteference RMS (Potgieter-Vermaak and Van Grieken, 2006) (d) Cu, Ni or Au grid LMMS (Dierck et al., 1992) • 15-20 nm thickness EPMA (Dierck et al., 1992) • Precise and well-defined hole EELS (Berghmans et al., 1994) s ha pe, s ize a nd arrangement TEM (Ogura et al., 2014)

Another analytical tool available is electron energy-loss spectrometry (EELS). This technique allows samples to be characterised from energy losses experienced by electrons as they interact with the sample. The primary importance of EELS to single particle analysis is its ability to detect and quantify most elements, including those with low atomic number. Maynard (1995) noted that this technique gave higher count rates than EDX and was able to detect elements not easily accessible by EDX. Chen et al. (2006) also observed that compared to the EDX spectra, which only gave information on chemical composition, EELS provided additional information about bonding and oxidation states. Transmission electron microscopy coupled with EELS (TEM-EELS) was used by Marris et al. (2013) to determine the oxidation states of metals emitted from an Fe-Mn alloy manufacturing plant in the north of France. Despite observing the difficulties that particle heterogeneity, shape-irregularity and sample dimensions introduced to this technique, combining TEM-EELS with SEM-EDX overcame some of these limitations. This combination has also been used to characterise the mixing state of African dust (Deboudt et al., 2010) and identify ultrafine titanium particles retained in the lung tissue of rats (Kapp et al., 2004).

Proton induced X-ray emission (PIXE) has been applied to the elemental analysis of APM for many years. It is a fast, non-destructive technique, requiring no sample preparation, with multi-elemental analysis capabilities and low minimum detection limits (Lucarelli et al., 2011). The use of an external beam reduces the risk of the loss of more volatile elements, such as chlorine and bromine, however due to X-ray attenuation inside the target particle PIXE cannot successfully quantify the low-Z elements (Calzolai et al., 2010). The analysis of the lightest measureable elements (Na, Mg, Al, Si and P) can also be difficult to accurately quantify due to difficulties in evaluating the absorption of their X-rays in the sample. Recently, a device for the simultaneous use of PIXE and XRF was built for the analysis of atmospheric particulates, allowing for the detection of heavier elements (Rb, Sr, Zr) which cannot be obtained through PIXE analysis alone (Reyes-Herrera et al., 2015).

To analyse individual particle size and composition, Denoyer et al. (1982) pioneered the off-line technique of laser microprobe mass spectrometry (LMMS). This technique involves placing the particles on a surface before selectively desorbing the particles and ionizing the molecules by a single laser pulse. The ions are separated and analysed using a time-of-flight mass spectrometer. LMMS has been used to detect trace levels of metals in

individual particles at the parts-per-million (Bruynseels et al., 1988) and distinguish surface species from those contained within the particle (Wouters et al., 1988). Carson et al. (1997) discovered that at high laser irradiance, the mass spectra reflected the bulk composition whereas at low irradiance the signal intensities of surface-enriched species were enhanced. This allowed qualitative differences between surface and core compositions to be inferred. A major limiting factor with this analysis technique, however, lies in its destructive nature. It also suffers from the same condensation, evaporation and chemical reaction problems as bulk methods since the sampling process is similar. Another limitation is that it is a relatively slow method (<1 particle per minute) (Noble and Prather, 1996).

Single particle ICPMS (SP-ICPMS) is an emerging analytical method with the potential to measure chemical composition, particle size, size distribution and number concentrations at environmentally relevant concentrations (Kawaguchi et al., 1986). Because its dynamic range can extend to the micrometre regions, poly-dispersed systems as well as aggregation/agglomeration processes may be studied. In traditional ICPMS, multiple intensity readings are integrated over long dwell times (0.3-1s) and averaged to produce an overall concentration for the sample. In contrast, SP-ICPMS intensity readings are integrated over a shorter dwell time (<10ms) and plotted individually as a function of time. This technique can be used to detect and characterise nanoparticles from low number concentrations (103 cm-3 to 105 cm-3)(Pace et al., 2011).

Single particle ICPMS measurements require a series of unique considerations. The number of particles entering the plasma must be limited to prevent the overlapping of signals from two particles (Laborda et al., 2011; Pace et al., 2012). The processes of particle vaporization, ion production and diffusion and the area of the sampling orifice within which ions can be detected can also affect the relationship between particle mass and the measured signal (Olesik and Gray, 2012). Another limitation is that sampled ambient particles are typically not compatible with the sample introduction system that is standard for these instruments and need to be modified prior to analysis (Bustos and Winchester, 2016).

2.4. On-line analytical techniques

Most analytical measurements of APM require collection times of at least 6-12 hours, with most more than 24 hours, to obtain sufficient material. Such long sampling times, however, do not capture variations in elemental composition and concentrations due to changes in meteorological conditions. To overcome some of these fluctuations, which include emission strength, temperature, relative humidity, wind direction and speed and mixing heights, methods capable of providing continuous or near-continuous measurements of 1 hour or less are desirable. Ideally, the technique should be fast enough to track changes in concentration and/or composition as they occur, sensitive enough to detect the species of interest and free of interference from other species present (Sipin et al., 2003). Other considerations may include weight and portability of the developed instrumentation.

The majority of the work developed for on-line particle analysis has relied on mass spectrometry or atomic emission spectrometry. On-line mass spectrometry provides the ability to determine chemical changes in APM over short timescales and can either measure the chemistry of particulate assemblages (bulk analysis) or individual particles. A number of single-particle mass spectrometers (SPMS) instruments have been developed over the years including the aerosol time-of-flight mass spectrometer (ATOFMS), laser-induced breakdown spectroscopy (LIBS), laser mass analyser for particles in the airborne state (LAMPAS), particle analysis by laser mass spectrometry (PALMS)and rapid single-particle mass spectrometer (RSMS). The major differences between these instruments include the laser wavelength used to perform the desorption and ionization and the method used to determine particle size(Sullivan and Prather, 2005). Most SPMS instruments transport particles from the air into the vacuum using specially designed inlets. Once inside the vacuum, the particles are detected by optical light scattering and sized either by measuring velocities or the intensity of scattered light. Since the intensity of light scattered by particles decreases considerably with decreasing particle size, the optical detection efficiencies for particles <~150nm are low (Zelenyuk and Imre, 2005).

Prather et al. (1994) developed an aerosol time-of-flight mass spectrometer (ATOFMS) which is capable of measuring the size and chemical composition of individual poly-disperse particles in real-time. Advantages of this technique include a fast analysis time (up to 19 particles per second) and the ability to collect the entire mass spectrum of a single particle over a theoretically unlimited mass range. ATOFMS has been shown to be useful for determining size and chemical correlation information of individual particles (Noble and Prather, 1996); for tracking particles with distinct chemical signatures (Liu et al., 1997) and for observing meteorological effects on particulate pollution (Noble and Prather, 1996). ATOFMS can also provide information on the distribution of chemical species within individual particles(Sullivan et al., 2007). Using a lower laser power Cahill et al. (2015) selectively segregated the surface molecules to create a depth-profile of the major chemical components. A limitation of this technique is that the chemical composition measurements are not quantitative. Ion signal intensities produced by laser ablation/ionization vary greatly from shot to shot for virtually identical particles, primarily because of inhomogeneities in the laser (Bhave et al., 2002). Instrument sensitivities can also be affected by the size and composition of the sampled particle. By comparing ion signals from ATOFMS with the signal intensities of particles collected with an impactor Bhave et al. (2002) noted that the instrument sensitivities to nitrate and ammonium decrease with increasing aerodynamic range of 0.32 - 1.8 µm. It also can’t distinguish the oxidation state and chemical species (Wang et al., 2016).

The laser mass analyser for particles in the airborne state (LAMPAS) was used by Hinz et al. (1994) for the on-line analysis of single atmospheric particles and was noted for its ability to detect single particles from ambient air with a high mass resolution constant over the entire mass range. This technique has since been used to perform size-resolved determination of the chemical composition of particle populations (Trimborn et al., 2000) and to investigate environmental exchange processes (Gelhausen et al., 2011).

Developed by Murphy and Thomson (1995) the particle analysis by laser mass spectrometry (PALMS) has been used for numerous atmospheric measurements. Murphy et al. (2006)used this technique to examine mercury-containing APM. It has also been used to determine the chemical composition of mineral dust (Gallavardin et al., 2008).

The rapid single-particle mass spectrometer (RSMS)was developed by McKeown et al. (1991) and has been used in several field campaigns. As it uses an aerodynamic lens to focus the particles, the divergence of the particle beam is reduced and it can efficiently detect particles <300nm (Sullivan and Prather, 2005).Murphy et al. (2007)used this technique to measure lead in single atmospheric particles. It has also been used to determine sources of particulate pollution (Bein et al., 2006; Reinard et al., 2007).

Laser- induced breakdown spectroscopy (LIBS) is another important laser technique in fine APM analysis. It is based on plasma formation on the surface of analysed samples by means of focused laser pulses. This plasma samples the substrate and excites its atoms. The light emitted from this plasma is then spectrally analysed and compared to well-known atomic emission lines. Quantification of the elemental species concentration is via quantification of the intensity of the emission lines. It can also generate quantitative mass measurements of constituent species, which enables a direct simultaneous measurement of particle mass and composition (Hahn and Lunden, 2000). The main advantages of this technique is the ability to provide direct chemical analysis without laborious preparation as only optical access to the sample is required (Evans et al., 2014). LIBS has been applied to the quantification of emissions from incinerators (Dutouquet et al., 2014; Hahn et al., 1997; Neuhauser et al., 1999) to measure hourly concentrations of metals in urban air (Kwak et al., 2012) and for ambient pollution monitoring (Gaudiuso et al., 2010).

A second class of on-line mass spectrometry instruments uses thermal vaporisation of particles followed by various ionization techniques, most commonly electron impact. The most widely used instrument is the aerosol mass spectrometer (AMS). Particles are transmitted into the AMS detection region using an aerodynamic focusing lens where they impact on a tungsten vaporiser typically at temperatures of 400-950⁰C, vaporising the volatile and semi-volatile components(Allan et al., 2003). The instrument alternates between two modes during operation, mass spectrum (20s) and time of flight (40s) with the data averaged over 5-30 minutes. Ambient mass concentrations (µg/m3) and information on the composition can be derived from the mass spectrum while the data obtained in the time of flight mode can be used to calculate mass distributions for a particular component as a function of aerodynamic diameter(Allan et al., 2003). A limitation of using thermal vaporising is that it can only detect non-refractive particles. It is also not designed to

refractory such as soot, fly ash, metal oxides and sea salt (Canagaratna et al., 2007). There are three versions of the AMS, however the only difference being the type of mass spectrometric detector; quadrupole (Q-AMS), time-of-flight (TOF-AMS) and high resolution TOF (HF-TOF-AMS). A limitation of this technique is that as only one type of ion can be studied at a time so complete mass spectra of individual particles cannot be obtained.

2.5. Conclusion

Recently, the negative effects of atmospheric particulate matter on the environment and human health, particularly fine particles, has gained increasing attention. To obtain a true assessment of the risks associated with airborne particles a detailed physical and chemical characterization is required. Traditionally, the chemical characterization of APM has been achieved by bulk composition. As the impact and toxicity of APM is related not only to total elemental composition but also to chemical heterogeneity at the individual particle level, single particle analysis has increasingly gained importance.

A variety of methods and instruments are available and continue to be developed for single particle analysis, however, a single practical technique does not currently exist for obtaining all the required information, specifically the size, morphology, composition, mixing state and molecular structure of APM. Existing sampling and analytical techniques are also time-intensive and expensive and frequently do not allow for the collection of the large number of particles required to generate a statistically valid data set.

As the choice of techniques used to characterise fine atmospheric particulates is strongly dependent on the scientific objectives, careful consideration is needed, even at the sampling stage. This review is designed as a guide to the array of sampling and single particle analysis techniques available for the chemical characterisation of fine airborne particulate matter.

Table2 . 3 Advantages and disadvantages of different single particle analytical techniques

Advantages Disadvantages Size Reference Range Technique

Off-line

Scanning electron microscopy • Morphological and elemental • Unable to generate information on mass >0.1 µm (Laskin and with energy dispersive X-ray analysis • Loss of volatiles under vacuum Cowin, 2001) (SEM-EDX) • Fast sampling times • Cannot determine low-Z elements

Raman Microscopy (RMS) • Enables analysis of composition, • Not suitable for ultrafine and >1 µm (Sobanska et phase and crystal orientation nanoparticle al., 2014) • Can determine different oxidation states High-resolution TEM (HRTEM) • Can generate information on • Particles need to be transparent to the >5 nm (Mäkelä et microstructure, composition, electron beams al., 2002) morphology and elemental • Loss of volatiles under vacuum oxidation states

X-ray photoelectron • Generates information on • Charging can be a problem >50 nm (Cheng et al., spectroscopy (XPS) elemental composition, surface • Need a complete database of reference 2013) chemistry and chemical states spectra • No sample preparation • Non-destructive Nano-scale secondary ion mass • Determination of • Destructive >50 nm (Li et al., spectrometry (NanoSIMS) heterogeneities associated with • Quantifying data can be difficult 2016b)

depth

• High detection sensitivity

Time-of-flight SIMS (TOF-SIMS)

>100 nm

X-ray absorption fine structure • Non destructive • Requires synchrotron X-ray source >20 nm (Davidson et spectroscopy (XAFS) • High detection sensitivity al., 2015) • No spectral interference from co-existing elements X-ray absorption near edge • Non destructive • Cannot measure elemental >15 nm (Fittschen, structure (XANES) • High detection sensitivity concentrations 2014) • Determine oxidation states • Requires synchrotron X-ray source

Technique Advantages Disadvantages Size range Reference

Electron energy loss spectrometry • Higher count rate than EDX • Difficult to interpret data >100 nm (Marris et (EELS) • Information on bonding and • Problems with shape irregularity oxidation states Proton induced X-ray emission (PIXE) • Fast • Cannot quantify low-Z elements >100 nm (Lu et al., 2014) • Non destructive • No sample preparation • Low minimum detection limits Single particle inductively coupled • Information about the elemental • Destructive >90 nm (Suzuki et al., mass spectrometry (SP-ICPMS) chemical composition, number • Sampled ambient particles not compatible 2010) concentration, size and size with the standard sample introduction

distribution system • Low detection limits

Laser microprobe mass • Can distinguish surface enriched • Slow (<1 particle/minute) unknown spectrometry (LMMS) species from bulk composition • Destructive

On-line

Aerosol time-of-flight mass • Measures size and chemical • Destructive >100 nm (Cahill et al., spectrometer (ATOFMS) composition in real time • Not quantitative 2012) • Fast (up to 19 particles/second) • Variation in ion signal intensities • Information on the distribution of • Instrument sensitivity affected by the size chemical species in an individual and composition of the particle particle Laser-induced breakdown • No sample preparation • Large interference effects >300 nm (Kwak et al., spectroscopy (LIBS) • simultaneous measurement of 2012) particle mass and composition Aerosol mass spectrometer (AMS) • Fast • Can only detect non-refractive particles >50 nm (Durant et al., • Measures mass concentrations • Difficulty detecting some refractory particles 2010) such as sea salt and mineral dust • Doesn’t generate complete mass spectra of particles

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Chapter 3

Combining Gravimetric and Single Particle Analysis to Determine the Contribution of an Active Gold Mine to Arsenic in the Atmosphere

Abstract

Gold mining operations have the potential to be a significant source of arsenic in the atmosphere, which can pose major health risks to the environment and nearby human populations. For this study a combination of high volume and passive sampling for gravimetric analysis and electron microscopy was used for the spatio-temporal and physico- chemical characterisation of ambient airborne particulates to determine the contribution of an open cast gold mine to arsenic in the atmosphere. Mass concentrations show a strong seasonality, with an almost three-fold increase during the dry season, although the prevailing wind regime suggests non-exhaust traffic emissions rather than the mine as a major source for most of the sampling locations. Coarser particles were found to be more prominent during the wet season whereas during the dry season half of the sampled particulates were observed in the fine fraction. The mineral phases observed strongly reflect the local geology and are dominated by silicates, carbonaceous material and carbonate. The absence of arsenic-rich phases and the presence of only a nominal amount of sulphur-rich particles (3 particles detected out of more than 20,000) suggests that the local mine, where gold mineralisation is associated with arsenopyrite, is not a major contributor to arsenic in the atmosphere.

3.1INTRODUCTION

As a source of heavy metals and other potentially toxic elements, such as arsenic, mining operations can pose a significant health threat to the environment and populations living nearby. Traditionally, research on mine-related contamination has concentrated on transport of pollutants via soil and water with little attention paid to atmospheric dispersal.

Unlike the other vectors, airborne particulate matter(APM) is not geographically constrained, allowing pollutants to be transported readily over relatively large distances(Csavina et al., 2012). Research has also focused predominantly on smelting and other combustion processes (Batonneau et al., 2004; Sanchez-Rodas et al., 2012; Williamson et al., 2004; Zhang et al., 2018) with little regard to particulates derived from a geogenic source.

The negative effects of airborne particulates on human health are well documented (Brunekreef and Forsberg, 2005; Davidson et al., 2005; Kim et al., 2015; Pope et al., 2004), although the exact mechanisms of APM-related health effects are still incompletely understood. The health risks associated with APM arise from the inhalation and deposition of particles within the broncho-pulmonary system, the efficiency of which relies on the physical properties of the particle, such as size and shape, and the capacity of the particle to induce an inflammatory response (Kim et al., 2015). As the impact and toxicity of APM is related not only to size but also to chemical heterogeneity, the determination of the chemical composition of APM is important for predicting potentially deleterious effects on human health and the environment, as well as source apportionment (Niu et al., 2010).

Traditional monitoring programs typically include the measurement of particle mass using a range of sampling devices and spatio-temporal sampling schedules. Less commonly, bulk elemental concentrations are measured using a range of methods that include X-ray fluorescence or inductively coupled plasma mass spectrometry (Perrino et al., 2008). Although these methods are effective in providing information on bulk particle size and composition, they do not readily identify different sources, nor provide quantitative information of the elemental concentration from individual sources. This is a serious limitation, because in any environment there are typically different sources that contribute to the total particle load (such as agriculture, transport, construction and industrial activities, erosion and forest fires). As a result, environmental regulators are often forced to establish stringent dust suppression procedures that fail to reduce the total particle load as the sources have not been correctly identified.

Electron beam techniques such as scanning electron microscopy with energy dispersive X-ray analysis (SEM-EDS) have been widely used in atmospheric science for the

physical and chemical characterisation of airborne particulates (Ault et al., 2012; Pachauri et al., 2013; Zeb et al., 2018). The ability to generate information on the elemental composition, size and morphology of individual particles is important to accurately ascertain thesource(s) and impact of potentially toxic elements in APM.

Using a combination of conventional gravimetric analysis and SEM characterisation of individual atmospheric particles, the aim of this study is toidentify which particle size fractions and mineral phases contribute to the total mass of APM and to determine the contribution of an active gold mine as a potential source of contaminants for the surrounding communities and environment.

3.2 METHODS

3.2.1 Sampling locations

Samples were collected from four monitoring stationsaround the mine property within the city of Paracatuin the state of Minas Gerais, Brazil (Figure 3.1, S1-S4) and at control sites upwind and downwind of the mining area (S5 and S6). In 2019, Paracatu had a population of 93,158 people and an economy largely based on agriculture and mining (IBGE, 2020). The region has been explored for gold since 1722 and theMorro do Ouro mine is operated by Rio Paracatu Mineração (RPM), a 100% owned subsidiary of the Canadian company Kinross Gold Corporation.It is the largest gold mine in Brazil and one of the largest in the world. Themine commenced production in 1987 and currently processes ore at a nominal plantthroughput rate of 61 Mt/a(Kinross, 2020). The Paracatu operations comprises an open pit mine, two processing plants and two tailings facilities. Major souces of APM arise from blasting and extraction processes, haulage on unsealed roads, tailings and waste rock piles.

The locations of the sampling points were already established prior to the beginning of this study (with the exception of Station 6) and are based on the results of extensive modelling undertaken by the mine operators to comply with the state Environmental Agency and regional council monitoring requirements (EcoSoft, 2010). Station 2 (S2) is located in a rural area along the main highway, immediately south (downwind) of the mine. Three stations in the city (S1,S3 and S4) are within a 3 km radius of the mine pit. Two stations were established as control sites: station 5(S5), approximately 6 km NE (upwind) of the mine, and station 6 (S6), at the southern edge of the city and around 5 km S (downwind) of the pit. The monitoring program was

established in August 2010 and is still ongoing, however only data for the periods December 2011 and September 2012 are considered here.

Figure 3.1 Location of Paracatu, the Kinross Paracatu mining operation and the six monitoring stations. Background maps from Google Earth™

The municipality of Paracatu is situated in a “cerrado” environment, or tropical savannah, and is influenced by a regional tropical system with a well-defined dry season (April to September) and wet season (October to March). Rainfall for the different sampling periods are illustrated in Figure 3.2, with monthly totals exceeding 200 mm in December compared to 26 mm during September. The average relative humidity for the sampling periods ranged from 43% in September to 88% in December (INMET, 2018).Winds are typically from the north to northeast quadrants and tend to be more frequent at the end of the dry season (Ecosoft, 2010). Average wind speeds tended to be higher during September

(~9 km/h) compared to December (~7 km/h). During December the prevailing winds are predominantly N-NE, changing to E-NE during September (ECOSOFT, 2012).

Figure 3.2 Precipitation levels and wind speed for Paracatu during the sampling periods. Dashed red lines represent the sampling periods.Data from World Weather Online (2019)

3.2.2 Local geology and mineralogy of the ore deposit

The Paracatu gold deposit, also known as Morro do Ouro, is a Neoproterozoic vein-type deposit hosted in deformed carbonaceous phyllites and argillaceous quartzites, characterized by low gold grades (~0.4 g/t Au) and low but appreciable amounts of As, Ag, Pb, Zn and Cu (Oliver et al., 2015). The gold is closely associated with arsenopyrite (FeAsS), pyrite (FeS2), pyrrhotite

(FeS), sphalerite ((Zn,Fe)S), galena (PbS) and chalcopyrite (CuFeS2), and occurs predominantly(>90%) as free gold or electrum along the grain boundaries or in fractures within individual grains (Kinross, 2020). The sulphides typically occur as individual crystals or aggregates and are predominantly within boudinaged quartz veins or on their edges. Some sulphides are also observed as veinlets and disseminations within the host rock (Oliver et al., 2015). Arsenopyrite is the only mineral present that contains significant amounts of As and typically occurs as relatively large crystals (1-3 mm) (Kinross, 2006).

The typical mineralogy of the phyllite includes quartz (~30-40 wt%), muscovite/sericite

(~40-50 wt%), kaolinite (~2-7 wt%), albite and siderite (7-16 wt%) and calcite and ankerite (2-3 wt%). Very fine-grained (µm to sub-µm size) graphite or carbonaceous material disseminated within the sericite accounts for up to 20 wt% of the rock mass (Kinross, 2020).

3.2.3 Sample collection and analysis

Conventional high-volume active samplers were deployed every six days to collect total suspended particulates (TSP) (model AGVPTS1; Energetica, Brazil). 24-h TSP samples were

collected on glass fiber filters (203 x 254 mm, GF18X10IN; Energetica, Brazil) at a flow rate of 1.0 m3 min-1, with the filters gravimetrically analysed on site before and after sampling.

As high-volume sampling is unsuitable for single particle analysis due to high particle loading and ensuing particle overlap, samples for SEM analysis were collected on Sigma-2 passive samplers deployed continuously over approximately a week (2-4 December 2011 and 13-20 September 2012) with airborne particulates collected on an adhesive sampling plate suitable for light microscopy and SEM(VDI, 2013).Samples were processed at the German Meteorological Service (DWD) in Freiburg, Germany, with SEM and microscopy analyses carried out in three randomly selected areas of the filters, each area measuring approximately 2 mm2, for all particles within the 1-80 µm size range.

Particle imaging was performed on an automatic scanning stage (Prior Scientific) coupled to a motorized microscope (ZEISS Axioplan 2) with an attached CCD-digital camera. Autofocus and measurement of particle size range was performed through an integrated Digitrace V.3.4 (IMATEC) image processing software. Images were acquired using an FEI XL 30 Sirion FEG scanning electron microscope (Schottky Field Emitter; 20 kV voltage and 24 nA beam current) at the University of Fribourg, Switzerland. The microscope was equipped with a secondary electron (SE) detector, a Centaurus scintillator type backscattered electron detector (BSD) and an EDAX energy dispersive X-ray spectrometer (EDS) system equipped with a lithium doped silicon detector. The images and data were processed using the AnalySiS Image acquisition program and the EDAX Genesis software version 5.2 which incorporates spectrum analysis, elemental mapping and automated particle analysis.

The SEM data and EDS spectra were further processed manually to eliminate analyses with statistically insignificant counts (<3,000 cps) and artifacts, such as air bubbles and scratches in the collector plates, which have the potential to be mistaken for particles by the SEM software. Mineral phase classification was manually calculated based on theoretical stoichiometric mineral formulae, using O, C, Si, Al, Fe, Mg, Mn, Ca, Na, K, S and As for percentage mass calculations (Table 3.1).

Table 3 .1Classification of mineral phases based on stoichiometric mineral formulae. Element(s) Wt% Classification C+O >80 Carbonaceous

Other phases <~1

Si >15 Silicate

Al+Si >20

Ca+Mg+Fe+Mg >20 Carbonate

S >10 Sulphide (other than arsenopyrite)

Al >30 Al-rich

As ~30-50 As-rich

Fe >30 Fe-rich

3.3. RESULTS AND DISCUSSION

3.3.1 APM Mass Concentrations

The strong seasonality of the region is reflected in the particle mass concentrations, with significantly higher concentrations during the dry season (40-160µg m-3 ) compared to the wet season(11-50 µg m-3) although for all the sampling periods concentrations were well below the Brazilian 24 hour guidelines of 240µg m-3(Fig.3.3) (CONAMA, 1990).This marked seasonality is consistent with the increased generation and dispersal of particles during dry conditions, and their longer residency time in the atmosphere and washout and suppressed re-suspension under rainfall conditions (Feng and Wang, 2012; Friese et al., 2016; Javed et al., 2015).

During December the stations located closest downwind to the mine site typically exhibited higher concentrations than the other city stations with the exception of station 6, ranging from 20-45µg m-3 at site 1 and 24-52 µg m-3 at site 2, with a gradual decrease observed with increasing distance from the mine. Although Station 2 recorded the highest

concentration for this period (50µg m-3) as this sampling location is in rural area and adjacent to the main highway, re-entrained road dust could be a significant contributor to the total particle load.

60 2/12/2011 180 9/09/2012 8/12/2011 14/12/2011 160 15/09/2012 ) 50

- 3 140 40 120 µg m 100 30 80 20 60 40 Particle mass ( mass Particle 10 20 0 0 S1 S2 S3 S4 S5 S6 S1 S2 S3 S4 S5 S6 sampling site sampling site

Figure 3.3 Variations in TSP mass concentrations for the sampling periods. Mass concentrations for S6 were not collected during the 15 September sampling. All results were well below the Brazilian 24 hour guidelines of 240µg m-3 (CONAMA, 1990)

For two of the deployments (2/12/11 and 8/12/12) Station 6 recorded higher or similar mass concentrations to those located more proximal to the mine, with concentrations ranging from 44-45µg m-3 , compared to 20-42µg m-3(S1) and 32-50 µg m-3 (S2) for the same sampling periods. Although it is the furthest sampling location from the mine, it is situated adjacent to a major ring road and as a result, the primary source for the particulates sampled here is most likely to be re-entrained road dust and other local surfacedisturbances, which are independent of seasonal variations, such as wind speed and direction.

As station 5 is located in a rural area outside the influence of the mine, variations in mass concentrations are inferred to represent contributions from local sources, such as surface disturbances from agricultural practices, wind-blown dispersal of soil and non- exhaust traffic emissions and as such are temporally highly variable, ranging from 20-35µg m-3 during December and 70-104µg m-3 during September.

During September, higher mass concentrations were typically observed at the city stations further from the mine, with the highest concentrations observed at station 6

(162µg m-3 ) and station 4(154µg m-3). Mass concentrations for S6 were not collected during the 15th September sampling. Compared to station 2, which is located approximately 1 km closer to the mine, station 4 has significantly higher concentrations for the same sampling periods (89-154µg m-3vs 79-93µg m-3). The other city station (S3) recorded similar or higher concentrations to those observed at station 1 (102-104µg m-3 and 89-110µg m-3 respectively). Due to the prevailing wind direction (ENE) and the location of these sites, the mining operations are not likely to be a significant contributor to the total particle load at these locations.

3.3.2 Single-particle characterisation by SEM-EDS

More than 20,000 particles were analysed and characterised based on the filters described in Section 2.3. All particles >1µm were analysed and the relative proportions (volume %) were calculated from SEM particle size data on an assumption of spherical shape. Sampling plates collected from S2 for both sampling periods were contaminated by insects, which prevented accurate analysis. As a result, only five sampling locations are reported here.

APM generated by mechanical processes typically associated with mining activities, such as drilling, blasting and traffic on unsealed roads, as well as other mechanical processes such as agriculture and the re-suspension of surface deposits by wind and traffic, are predominantly comprised of coarse particles (Liu &Harrison, 2011). This is reflected in particle morphology and the high proportions of coarse (2.5-10 µm) and super-coarse (>10 µm)particles for both sampling periods, particularly at Station 1and Station 6(Fig.3.4). The sizes reported in this study are the physical size calculated by the instrumentation using the equivalent circle diameter and do not represent the aerodynamic diameter.

During December, coarser particles are predominant, typically contributing to more than 60 % of the TSP, with super-coarse particles accounting for approximately 30-60% across most locations. This is consistent with the increased precipitation scavenging efficiency for fine particles and washout of larger particles (Friese et al., 2016). As super- coarse particles are likely to travel only a limited distance (<1 km) from the source (Petavratzi et al., 2005), the influence of mining operations on this size fraction is confined to the station closest to the mine (S1) and the high proportion of super-coarse particles at

locations more distal (S4 and S6) are inferred to have been derived from a more localized source.

Figure 3.4 Particle size distribution for A) 2-14 December 2011 and B) 13-20 September 2012. (Sizes in µm. All values are percentages of total measured particle number).

With the exception of station 3, fine particles for the December sampling period typically account for <25% of the TSP. As the prevailing winds for this period are primarily from the north, the high proportion of fine particles observed at S3 (44%), which is located approximately 2 km south of the mine, most like represent a mine-derived source.

Fine (1-2.5 µm) particulates are more prevalent during the September, consistent with the dryer conditions. With the exception of stations 1 and 6, fine particles contributed approximately 50% of the TSP, with coarse particles typically ~40% and the super-coarse fraction ~10%.The preponderance of fine particles during September, combined with prevailing winds predominantly E-NE, suggests the influence of the mine on APM at most sites during this period is minimal. With the location of station 5 upwind of the city and the mine, the observed particle size distribution is inferred to more strongly reflect the influence of local agricultural and rural activities, such as tilling, harvesting and transport on unsealed roads.

The metamorphosed phyllites that host the ore body are dominated by quartz, graphite, chlorite((Mg, Fe)3(Si, Al)4O10(OH)2(Mg,Fe)3(OH) 6), muscovite (KAl2(AlSi 3O10)(OH)2),

illite(K0.65Al2.0[Al0.65Si3.35O10](OH)2)and sericite (KAl2(AlSi 3O10)(OH)2), with minor amounts of

2+ apatite (Ca5(PO4)3(F,Cl,OH)), margarite (CaAl2(Al2Si2O10)(OH)2), ankerite (Ca(Fe ,Mg)(CO3)2),

dolomite (CaMg(CO3)2), albite (NaAl3O6) and anorthite (CaAl2Si2O8) (Oliver et al., 2015, Almeida, 2009).This is reflected in the mineral phase distributions, with samples predominantly composed of varying proportions of silicates and carbonaceous material, with minor amounts of carbonate (Fig.3.5).

A 100 B

60 40 Volume % 20

S1 S3 S4 S5 S6 S1 S3 S4 S5 S6 Sampling site carbonaceous silicate carbonate

Figure 3.5Relative proportions of mineral phas es for the periods of A) 2-14 December 2011 and B) 13-20 September 2012.

The most striking observation is the lack of As-bearing particles and the presence of sulphides only at the sampling location closest to the mine site (S1) although only in nominal amounts, with only 3 particles detected out of more than 20, 000 particles (Fig. 3.6).

Figure 3.6BSE image and corresponding EDS spectrum of a sulphide mineral.

For most of the sampling locations, silicates (Fig. 3.7) were the dominant mineral phase, with higher relative proportions typically observed during December across most stations (~80-90%) with the highest observed atS1 and S4, downwind of the mine (90% and

88% respectively) and at site 6 adjacent to the road(~80%). Although present in all size fractions, silicates dominate the coarse and super-coarse fractions across the stations for both sampling periods, with the exception of station 6 in September (Fig.3.8).

Figure 3.7SEM images and corresponding EDS spectra for different silicate mineral phases.

S1 S3 S4 S5 S6 100 Al-rich A 80 sulphide 60 carbonate silicate 40 carbonaceous 20

100 B 80 Al-rich sulphide 60 carbonate silicate 40 Volume % carbonaceous 20

0 1-2.5 2.5-10 >10 1-2.5 2.5-10 >10 1-2.5 2.5-10 >10 1-2.5 2.5-10 >10 1-2.5 2.5-10 >10 Particle size (µm)

Figure 3.8 Size distribution of individual mineral phases (relative proportions represented by volume % ) for the periods A) 2-14 December 2011 and B)13-20 September 2012. Station 2 sampling plates were contaminated with insects for both sampling periods which prevented accurate analysis and as a result, are not included.

The high proportion observed at station 1 during December, combined with the presence of sulphides, suggests that during this season the mine is a major contributor to the atmospheric particulate load. Although station 4 is also downwind of the mine during this season, the limited atmospheric residency time for coarse and super-coarse particles and the increased efficiency of washout under wet conditions suggests that the source of the coarser particles at this location probably includes a significant localised contribution. The prominence of silicate minerals could also attribute to the significantly higher proportion of super-coarse particles observed in December due to aggregation of hydrophilic minerals, such as clays and mica, under conditions of high humidity (Huertas et al., 2012; Jane A. Plant et al., 2012). During September, apart from station 1, all sampling locations typically lie outside the influence of the mine due to meteorological conditions.

Figure 3.9Super-coarse silicate aggregates sampled during December.

With the exception of station 3, carbonaceous material is typically present in

higher relative proportions during September (typically >~35%) than December (<~15%) and, while present in all size fractions, is typically more prevalent in the fine fraction, with super-coarse C-rich particles observed only at stations 5 and 6. Carbonaceous material in the coarse fraction for September ranged from 6% (S4) to ~ 30% (S5 and S6). Due to the seasonal wind regime during this sampling period, carbonaceous particles are

unlikely to be sourced from the mining operations for all stations, with the exception of station 1, and more likely originate from soil disturbances during agricultural activities and the resuspension of road dust and other surficial deposits due to wind and traffic. During December super-coarse carbonaceous material were unreported and coarse particles typically accounted for less than 20% of the carbonaceous particles analysed.

The high relative proportion of fine particles observed in the TSP at station 3 during December (45%), combined with the predominance of carbonaceous material within this fraction (>70%) and the prevailing wind direction, suggests the mine as a potential source for the carbonaceous material observed at this location during this sampling period.

As airborne carbonaceous material derived primarily from vehicle exhaust and other combustion sources occur as fine (<1 µm) particles with diameters approximately 300nm,coarser C-rich particles are typically attributed to a biological or soil derivation(Fig. 3.10; Herner et al., 2006; Kleeman et al., 2000; Wang et al., 2017).

Figure 3.10SEM image and corresponding EDS spectra of a) crystalline and b) biological carbonaceous material.

The prevalence in the coarser size range, combined with its abundance in the local ground rock and surficial deposits, suggests a primarily geogenic rather than anthropogenic source for the observed carbonaceous particles. This might also be a reflection of the sampling bias of the Sigma-2 sampler towards coarser particles and the inability of SEM to accurately analyse particles in the ultrafine fraction.

Carbonate particles (Fig. 3.11) are found at all sampling locations and exhibit minimal spatial or temporal variations in relative proportions (typically <10 %), with the highest amount recorded at station 6 during December (20%).They are found predominantly in the coarse and super-coarse particle fractions, with typically <5% occurring in the fine fraction.

Figure 3.11SEM image and EDS spectrum of carbonate mineral phase.

Whilst carbonate minerals such as siderite, calcite and ankerite can contribute up to 20% of the phyllite, they typically account for only 2-3%, therefore some of the carbonate particles analysed could be derived from anthropogenic sources, such as construction (cement)and agriculture (fertiliser).Although it was difficult to differentiate between geogenic and anthropogenic sources for carbonate particles, the similarity in relative proportions at all sites for both sampling periods, including the site upwind of the pit, and the high proportions at site 6 suggests that the mine is not a major source

and instead is more likely to originate from re-entrained soil and road dust and other anthropogenic sources.

During the September sampling, one of the city sites (S3) recorded an anomalous

amount of Al-rich particles (~4%), present as oxides (Fig. 3.12). The combination of particle morphology and the absence of aluminium oxide phases reported in the local geology suggests a localised anthropogenic source.

Figure 3.12SEM image and EDS spectra of Al-rich particle.

From the results, a seasonality can be inferred from both the particle mass concentrations and size distribution, with an almost three-fold increase in mass concentrations between the wet and dry season. Fine particles are also more prevalent during September, consistent with the enhanced generation and suspension of fine geogenic particles and their longer residency time in the atmosphere under dry conditions (Friese et al., 2016).

The contribution of the mine is most discernible during December due to the prevailing wind direction, with the closest stations, (S1 and S2, and to a lesser degree S3), showing the greatest impact in terms of particle mass and size distribution. Although there is no individual particle SEM data for station 2, due to contamination of the sampling plates, the high mass concentrations most probably reflect a mine-derived contribution to the APM, though a significant component could also arise from re- entrained road dust from the adjacent main road. The influence of the mine during this

period is also reflected in the single particle analysis, with high proportions of particles of coarse and super-coarse particles and the presence of sulphides, which are only associated with the gold mineralisation. To a lesser degree, the influence of the mine was also inferred for station 3during December, due to the significantly high relative proportion of fine particles, nearly 10 times that reported at any of the other downwind station for this deployment. During September due to the meteorological conditions, most sites lie outside the influence of the mine and the APM load is more likely to be sources by other mechanical sources, such as construction, agriculture, windblown resuspension of soil and non-exhaust traffic emissions.

Although the Sigma 2 collector plates are suitable for optical analysis, the deterioration of the adhesive surface under the electron beam created significant problems with the particle identification software used in this study and manual checking of each particle was required to eliminate potential artefacts such as scratches and air bubbles. The software also couldn't generate mineralogical characterisations, which had to be done manually based on the EDS spectra and backscattered SEM images. Although the data acquisition time for each sample was relatively short

(typically around 6 hours for ~3,000 particles), the manual processing was time consuming, taking several minutes per particle. Whilst able to provide detailed physico- chemical characteristics on individual particles, the manual data processing makes this method time consuming and expensive and therefore impractical for regular monitoring purposes. Another inherent limitation of the passive sampler is its reliance on gravity and inertia for particle capture, both of which processes are highly biased towards larger particles, with the contribution of fine particles to the total mass underrepresented.

3.4 CONCLUSION

A combination of gravimetric and single particle analysis of airborne particulates by SEM-EDS was undertaken to determine the contribution of an open pit gold mine to APM and the arsenic detected in the atmosphere of the city of Paracatu. Our study revealed that the concentration of TSP at all sample locations for both the wet and dry

periods were well below the Brazilian 24 hour guidelines of 240µg m-3(CONAMA, 1990)(CONAMA, 1990).

The influence of the mine was observed at locations closest to the mine site (S1, S2 and to a lesser extent S3), primarily during December when the meteorological conditions were favourable for the southwards dispersal of mine-derived emissions. These emissions comprised predominantly coarse and super-coarse particles of silicates and carbonaceous material, with minor amounts of carbonate. The absence of As-rich particles observed during this study implies that the mining operation is not a significant source of atmospheric As. The bias towards large size particles introduced by the passive sampler, however, prevents a definitive conclusion. Further studies are required, focusing on small size particles, and continued monitoring needs to be undertaken to ascertain other potential sources of atmospheric As. The minor amounts of sulphides, with only 3 particles detected out of more than 20, 000 analysed particles, also suggests that the exposure risk to heavy metals for populations living proximal to the mine is relatively low.

As reported in this study, the combination of gravimetric and single particle analysis has the potential for the identification of sources of atmospheric particulates in Paracatu. The problems created by the decomposition of the Sigma-2 sampling plate under the electron beam and the resulting interference with the particle identification software, combined with the manual data processing, however, made this technique time consuming and impractical for regular monitoring applications.

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LIU, Y. J., HARRISON, R.M. 2011. Properties of coarse particles in the atmosphere of the United Kingdom.Atmospheric Environment, 45, 3267-3276. Niu, J., Rasmussen, P. E., Hassan, N. M., and Vincent, R., 2010, Concentration distribution and bioaccessibility of trace elements in nano and fine urban airborne particulate matter: influence of particle size: Water, Air, & Soil Pollution, v. 213, no. 1-4, p. 211-225. Oliver, N. H. S., Thomson, B., Freitas-Silva, F. H., Holcombe, R. J., Rusk, B., Almeida, B. S., Faure, K., Davidson, G. R., Esper, E. L., Guimarães, P. J., and Dardenne, M. A., 2015, Local and regional mass transfer during thrusting, veining, and boudinage in the genesis of the giant shale-hosted paracatu gold deposit, minas gerais, Brazil: Economic Geology, v. 110, no. 7, p. 1803-1834. Pachauri, T., Singla, V., Satsangi, A., Lakhani, A., and Kumari, K. M., 2013, SEM-EDX characterization of individual coarse particles in Agra, India: Aerosol and Air Quality Research, v. 13, no. 2, p. 523-536. Perrino, C., Canepari, S., Cardarelli, E., Catrambone, M., and Sargolini, T., 2008, Inorganic constituents of urban air pollution in the Lazio region (Central Italy): Environmental monitoring and assessment, v. 136, no. 1-3, p. 69-86. Petavratzi, E., Kingman, S., and Lowndes, I., 2005, Particulates from mining operations: A review of sources, effects and regulations: Minerals Engineering, v. 18, no. 12, p. 1183-1199. Pope, C. A., Burnett, R. T., Thurston, G. D., Thun, M. J., Calle, E. E., Krewski, D., and Godleski, J. J., 2004, Cardiovascular Mortality and Long-Term Exposure to Particulate Air Pollution: Epidemiological Evidence of General Pathophysiological Pathways of Disease: Circulation, v. 109, no. 1, p. 71-77. Sanchez-Rodas, D., De La Campa, A. S., Oliveira, V., and De La Rosa, J., 2012, Health implications of the distribution of arsenic species in airborne particulate matter: Journal of inorganic biochemistry, v. 108, p. 112-114. Wang, H., An, J., Zhu, B., Shen, L., Duan, Q., and Shi, Y., 2017, Characteristics of Carbonaceous Aerosol in a Typical Industrial City—Nanjing in Yangtze River Delta, China: Size Distributions, Seasonal Variations, and Sources: Atmosphere, v. 8, no. 4, p. 73. Williamson, B., Udachin, V., Purvis, O., Spiro, B., Cressey, G., and Jones, G., 2004, Characterisation of airborne particulate pollution in the Cu smelter and former mining town of Karabash, South Ural Mountains of Russia: Environmental monitoring and assessment, v. 98, no. 1-3, p. 235-259. World Weather Online, 2019, Volume 2019. Zeb, B., Alam, K., Sorooshian, A., Blaschke, T., Ahmad, I., and Shahid, I., 2018, On the Morphology and Composition of Particulate Matter in an Urban Environment: Aerosol and air quality research, v. 18, no. 6, p. 1431-1447. Zhang, K., Chai, F., Zheng, Z., Yang, Q., Zhong, X., Fomba, K. W., and Zhou, G., 2018, Size distribution and source of heavy metals in particulate matter on the lead and zinc smelting affected area: Journal of Environmental Sciences, v. 71, p. 188-196.

Chapter 4

Single-Particle Analysis of Atmospheric Particulate Matter Using Automated Mineralogy: The Potential for Monitoring Mine-derived Emissions

This chapter has been re-produced from the Journal of Environmental Science and Technology.

Abstract

This article describes a new method for the analysis of fine (>1µm) atmospheric particulates using the Mineral Liberation Analyser. After determining the optimum sampling technique, the accuracy and precision of the instrument was tested by repeat analysis and by comparison to certified reference materials, with relative standard deviations of less than 10% achieved. A pilot study using this method was applied to identify arsenic-bearing phases near a gold mine and to identify particulates near a large iron-ore mining operation. The results revealed the presence of only negligible amounts of the arsenic-bearing phases and sulfides typically associated with the gold deposit, with only 159 particles detected in the 22511 particles analysed. The presence of aluminium-enriched iron oxides in the particulates sampled near the iron-ore operation suggest that re-entrained soil is a significant source of particulates in this region. From the results of this study, the technique has been shown to have a significant potential for the rapid acquisition of reliable data for the characterisation of airborne particulates, which is requisite for effective emissions management and for the monitoring of human and environmental health.

4.1. INTRODUCTION

A recent assessment by the World Health Organization International Agency for Research on Cancer recognized that ambient air pollution is carcinogenic to humans, with particulate matter component affecting more people than any other pollutant and bearing a close association with increased cancer incidence (International Agency for Research on Cancer, 2013). Airborne particulate matter (APM) can also have deleterious effects on local ecosystems, particularly when the particles comprise potentially toxic elements and compounds. APM is a complex mixture of solid and liquid particles of

heterogeneous compounds varying in size, chemical composition, surface area and concentration. Some particulates occur naturally but human activities, such as agriculture, industry and mining, also generate significant amounts.

In the past, analysis of atmospheric particulates has concentrated on the determination of size, mass concentration and bulk chemistry. The impact and toxicity of APM, however, is related not only to total elemental composition and size distribution but also to shape, surface properties and chemical heterogeneity (Fang et al., 2017; Schraufnagel et al., 2019). The only means to accurately distinguish between the multiple compositions that occur in APM is by single particle analysis.

As APM studies require the analysis of a large number of particles, automated systems using energy-dispersive scanning electron microscopy (SEM-EDS) are of increasing importance because of their ability to rapidly collect statistically valid quantitative data on mineral distributions, allowing for precise information on particulates. A significant advantage of automated analysis over traditional SEM studies lies in the elimination of operator bias and human error and the ability to obtain data for fine-grained or complexly inter-grown minerals.

Although the use of automated SEM-EDS in APM analysis is well documented, few studies to date have used automated mineralogy systems to characterise atmospheric particulates. QEMSCAN (Quantitative Evaluation of Minerals by Scanning Electron Microscopy) has been used for blast monitoring (Tonzetic et al., 2006), to characterise fine silicate particles in a volcanic plume (Martin et al., 2009), identify phase partitioning in volcanic ash (Hornby et al., 2019), demonstrate the spatiotemporal variations of flue dust particles (Balladares et al., 2014; Kelm et al., 2014), determine the influence of the physical attributes of aeolian sediments on grain transport and deposition(Speirs et al., 2008), in the forensic analysis of soil and dust (Pirrie et al., 2004), to quantify respirable crystalline silica in ambient air around open-cut coal mines

(Morrison, 2011) and in the analysis of urban PM10(Williamson et al., 2013).

Another automated mineral analysis device that has the ability to generate reliable single-particle information with a high degree of precision is the Mineral Liberation Analyzer (MLA). Although this technology has been used extensively in the

mining industry for the past two decades, it is only recently that that this technique has been applied to other environmental fields, including predicting acid mine drainage (Parbhakar-Fox et al., 2017), identifying structural controls on hardpan formation in mine tailings(Redwan, 2012; Redwan et al., 2016), identifying the geochemical and mineralogical controls on metal mobility (Stavinga et al., 2017), soil contamination near a lead smelter (de Andrade Lima and Bernardez, 2017), identifying lead species in sintering dust (Tang et al., 2015), the source of aeolian dune sands (Li et al., 2019)and sediment provenancing (Øxnevad, 2017; Tsikouras et al., 2011). To our knowledge, this is the first time the MLA has been used for the analysis of ambient airborne particulates. Research was undertaken on particulates sampled in 2015 in the Paracatu and Paraopeba regions in Minas Gerais, Brazil with the aim of demonstrating the potential of the MLA to be an important tool for the characterization of atmospheric particulates.

4.2. Materials and Methods

4.2.1 The Mineral Liberation Analyzer (MLA).

The Mineral Liberation Analyzer (MLA) is an automated digital image analyser coupled to an SEM-EDS that was developed to determine liberation potential and improve the efficiency of mineral processing plants. The system was first introduced in 1997 and relies on combining backscattered electron images (BSE) with X-ray analysis (Gu and Napier-Munn, 1997). In its standard configuration, the MLA consists of a Quanta SEM platform, fitted with dual, liquid nitrogen-free, silicon drift detector (SDD)-type spectrometers, a BSE detector and a secondary electron detector. The SEM can generate up to 30kV electron beam excitation energy, however typical operating conditions use an accelerating voltage of 25kV and beam current of 10-15 nA. The SEM is available either as a conventional tungsten filament or Field Emission Gun (FEG) source system (FEI, 2007). The MLA software package controls the hardware settings of the SEM, including accelerating e-beam voltage, SEM magnification, BSE brightness and contrast, spot size and working distance. Backscatter data is acquired as a 256 level greyscale image and relates the backscattering coefficient (ƞ) value for each mineral to a range of greyscale values between 0 and 255.

MLA analysis relies on the segmentation of regions based on BSE brightness, with the average BSE greyscale value of each defined region corresponding with a mineral of unique average atomic number(Gasparon et al., 2016). BSE imaging enables the analysis of a greater number of points able to be analysed, with over 800, 000 bits of independent information obtained in 100 seconds, in contrast to 40, 000-60, 000 for X- ray points (Goodall and Scales, 2007). BSE imaging also has higher spatial resolution than X-ray analysis, with a resolution of between 0.1µm and 0.2µm compared to 2-5µm for X-ray analysis (Gu, 2003a). The use of BSE for particle segmentation also reduces the incidence of greyscale overlap for minerals with the same or similar average atomic numbers (Burrows and Gu, 2006).

Samples submitted for analysis are similar to those used for conventional SEM and microprobe analysis and typically consist of mineral grains mounted in resin- impregnated blocks that are cut and polished to expose the mineral surfaces. This preparation technique, however, is impractical for atmospheric particulates due to the small sample mass and particle sizes and the high likelihood of particle loss, fractionation and deterioration during the polishing stage.

A de-agglomeration function in the MLA detects agglomerates and separates them into individual particles according to a set of predetermined parameters (Fandrich et al., 2007). Once the individual particles have been recognized, the first stage of the analysis identifies all distinct mineral phases and defines their boundaries in a process called phase segmentation, which is performed on each individual particle(Fandrich et al., 2007). After background elimination of the mounting material (or, in the case of APM, the substrate used for sample collection) and undersized particles(<1 µm), phase segmentation outlines regions of homogenous BSE values and assigns acolor to each identified region. This step also identifies and eliminates common artifacts such as fractures, voids and shadows.

Following this, the chemical composition of every phase is obtained by EDS. The MLA software has a number of measurement modes that combine BSE and X-ray analysis, ranging from a purely BSE-based technique to a predominantly X-ray based analysis (Gu, 2003). For the APM analyses performed in this study, the MLA was

configured to collect one X-ray spectrum (typically >2,000 counts) for each greyscale region identified within a segmented particle. Where overlapping grey-scale peaks occurred between adjacent phases, the grain boundaries could not be delineated and were resolved by X-ray mapping using a grid with a user-defined spacing (Table 4.1).

Table 4.1 Different MLA analysis modes

Analysis Mode Method

BSE segmentation Single point EDS analysis Extended BSE (XBSE)

Step size (defined by the Operator) X-ray collection at each step point Grain-Based X-ray Mapping Particles selected either through a BSE or a specific X-ray trigger (GXMAP)

Mineral classification compares the sample information with a pre-defined list of mineral spectra, using a pattern matching algorithm (Dobbe et al., 2009). Non-mineral phases, if present in the sample, can also be identified and treated in the same way, however the matching spectra are defined by the operator. This library is constructed before analysis and involves the collection of a high quality X-ray spectrum for each phase (mineral or non-mineral) in the sample(Gasparon et al., 2016). The building of a standards library directly from the sample ensures that the instrument parameters, such as beam energy, are consistent (Fandrich et al., 2007).

Based on user-defined criteria, phases are assigned a false color to produce a map of the classified particle, with the pixels representing each phase in the classified particle forming the basis for all subsequent quantitative analysis (Fig.4.1).

Figure 4.1 Example of the mineral classification process using MLA: (a) raw BSE image; (b) segmented image with EDS spectra; and (c) the classified image (figures represent the total area of pixels and the relative proportion (wt% ) of the identified minerals).

4.2.2. Sample collection and assessment of particle collection methods

In previous SEM studies, filters from aerosol sampling have been measured directly (Pirrie and Rollinson, 2011), and double-sided carbon tape has also been used in the analysis of dust samples (McVicar and Graves, 1997). For this study different sampling techniques and particle collection substrates were evaluated to determine their suitability for analysis by MLA. As high volume sampling is unsuited to single particle analysis due tohigh particle loading and resulting particle overlap (Elmes and Gasparon, 2017), low-volume and passive samplers were trialed to determine the optimum sampling regime; a)a Sigma-2 passive sampler equipped with a conventional adhesive collection plate (Tian et al., 2017; VDI, 2013) deployed for a week and b)a personal IOM (Institute of Occupational Medicine) sampler without size segregation (SKC item 225-70A) fitted with a portable, battery-operated SKC ‘AirChek 52’ low-volume pump (SKC item 224-52; flow rate of 2 L min-1). The IOM sampler was deployed for 6 hours and particulates were collected on three different types of SKC filters to assess their suitability for MLA analysis:

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polycarbonate (0.8 µm x 25mm, SKC item 225-1601), glass (0.5 µm x 25mm, SKC item 225-2708) and cellulose (0.8 µm x 25mm, SKC item 225.1930). Throughout this article, the term “filter” will be used to indicate the substrate used for particle collection with the IOM sampler. Blank filters were analysed for trace element concentrations on an Agilent 7900 Inductively- Coupled Plasma Mass-Spectrometer (ICP-MS) after multi-acid, open-beaker hotplate digestion. The procedure for hot plate digestion of the filter material was developed at the University of Queensland based on an optimization of the NIOSH 7303 (Anonymous, 2003), US EPA 200.2 (Martin, 1994) and AS/NZS 3580.9.15:2014 (Anonymous, 2014)methods. For the pilot study, particulates were sampled on polycarbonate filters using a personal IOM sampler without size segregation. Samplers were deployed for 6 hours at each location with a flow rate of 2 L min-1.

4.2.3. Sample Preparation

The success of a measurement system to obtain statistically reliable data depends not only on representative sampling being achieved but also on the use of valid sample preparation methods. An important requirement for MLA analysis is that there is sufficient contrast between the particles and the surrounding mounting medium (for resin-impregnated samples) or underlying substrate.

For MLA analysis, the filters were mounted directly onto an aluminium stub with double-sided carbon tape and coated with a conductive carbon film to prevent electrical charging. The Sigma-2 adhesive collection plates were mounted directly into the SEM, however, as they are poorly resistant to the incidence of the electron beam it was necessary to apply a thicker conductive coating to prevent electrical charging and deterioration during analysis.

4.2.4. SEM/MLA operating conditions

Analysis was done on an MLA 650 system coupled to a FEI Quanta 650 SEM-FEG, equipped with two Bruker Quantax silicon-drift EDS spectrometers. The SEM was set to

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operate in a high vacuum with an accelerating voltage of 25 kV, beam current of 18 nA, spot size 5.1 and a 10 mm working distance. The MLA was configured to collect 2,000 X- ray counts for each point of analysis and to process 20,000 particlesor a maximum run time of 2 hours per sample.

4.2.5. Formulation of the mineral library

The key to successful MLA analysis lies in the construction of the spectral reference library. Each mineral phase in the library is typically characterised by 2-5 spectra, depending on the complexity, and incorporates variable X-ray peak intensities. Each X-ray in the measurement is matched against known spectra from the reference list and is assigned a probability value based on a chi-squared difference test, referred to as full spectrum pattern matching. For this study, the X-ray matching tolerance was configured for 85%. Species that could not be matched to any spectra in the library were designated as ‘unknown’. After analysis, unknown particles were manually relocated for further X-ray collection to improve phase identification.

Over 500, 000 particles from 30 regional soil and rock samples and more than 300, 000 airborne particles were analysed by MLA during the compilation of the reference library. For an independent validation of the sample mineralogy, five oxisols and six tailings samples from the gold-mining region were analysed by X-ray diffraction (XRD) using a Shimadzu 7000 diffractor with Cu-Kα radiation, an energy resolution of 35 kV, tube current of 40 mA, a step time of 0.6 seconds and a 0.02° sampling step for a 2Ɵ range from 2 to 80°. Furthermore, fourteen samples from the iron-rich area were analysed on a Philips PANalyticalX'Pert-APD system with a PW 3710/31 controller, PW 1830/40 generator and PW 3020/00 goniometer, with Cu graphite monochromatised radiation, a 1 second step speed, 0.06° sampling step and 4-90° 2θ range. Peak recognition and mineral identification for all analyses were performed using the PDF-2 database (ICDD, 2003).The accuracy of the method was further assessed by the analysis of two certified reference materials, finely dispersed over the filter, and by comparing the MLA results with the known modal mineralogy.

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4.2.6. Limitations of the method

Sample heterogeneity, mineral grain size, electron beam-spot size and sample interaction volume are parameters that either individually or collectively can result in the simultaneous excitation of multiple phases, resulting in a combined X-ray signal(Johnson et al., 2015). Under a 25kV operating voltage, the X-ray interaction volume is approximately 1-2µm across and extending to a similar depth. For particles smaller than 2 µm, the electron beam passes through, creating interference from the underlying substrate. However, as the library is constructed from the sample, these interferences, such as the generation of excess carbon from polycarbonate filters, are incorporated into the representative spectra and identification can be achieved with a high degree of precision for most minerals.

Analysing agglomerates <2.5 µm can also be problematic as at the finest point measurement spacing there are insufficient points on a particle to ensure accurate analysis due to the potential for analytical overlap from adjacent minerals. When mixed X-ray signals cannot be accurately identified by the operator they are allocated a suggestive name.

Carbonaceous material could be identified by a combination of morphology coupled with high levels of carbon and minor contributions from other elements such as Si, Al and Mg. This method, however, has not yet been refined to distinguish between natural organic (e.g., pollen and spores) and anthropogenic (e.g., combustion residue) sources.

Potential difficulties in analysis also occur when phases of similar chemistry have similar average atomic numbers, which makes distinctions difficult. Mineral polymorphs, such as calcite and aragonite, and minerals with very similar chemistry such as the pyroxene group can be difficult to identify (Pirrie and Rollinson, 2011). In addition, trace or minor elements (or submicron minerals included within larger particles) may not be detected if the element accounts for less than about 1-3 wt% of the particle (depending on the element) due to the detection level capabilities of the EDS spectrometers. Lighter elements such as Be, B, C, N, O and F also generally need to be present at levels >1 wt%.

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4.3.0 Results and discussion

4.3.1 Selection of a sampling substrate

The glass fiber filter was not resistant to the impact of the SEM electron beam, even with a thicker conductive coating, and as a result there was significant surface deterioration which made analysis problematic. Glass fiber filters have also been shown to have high blank values of element concentrations, such as Si, K, Ca, Mn and Fe, which makes them unsuitable for trace element determination. Further complications arise due to the thickness (5µm) and the depth profile of deposition, with smaller particles trapped amongst the fibers limiting detection and X-ray signal generation.

The cellulose filter was relatively stable under the electron beam, however, particles of lower average atomic weight, such as silicates, showed limited BSE contrast and when the background was eliminated these particles were also artificially removed (Supplement 1). As a result, this type of filter is impractical for APM analysis. The other disadvantage of both glass fiber and cellulose filters is that their mass is very large compared with the mass of the particles. Although this is not a problem for MLA analysis, it is a significant issue for bulk elemental analysis after acid digestion (e.g., by ICP-MS) because the filter cannot be physically separated from the particles prior to analysis and must therefore be dissolved together with the particles. This may introduce a large error into the analysis because the mass of the filter cannot be measured accurately – it can only be estimated from the filter area by assuming constant density. Furthermore, the filters typically contain large amounts of some trace elements. This makes the blank subtraction problematic because of the large filter: sample mass ratio, or even impossible for elements whose concentrations in the filters exceed typical environmental values by orders of magnitude (e.g., Cr and Zn; see Table 4.2).

For these reasons, and as it is envisaged that most investigations would benefit from both MLA and bulk chemistry data, the use of glass fiber and cellulose filters is not recommended for MLA analysis of APM. This is in contrast with the requirements of conventional APM gravimetric analysis, because most types of high-volume samplers for

TSP, PM10 and PM2.5 use these types of filters.

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Table 4 .2 Concentrations of selected elements in the different filter media. All values in mg kg -1

V Cr Co Ni Cu Zn As Cd Tl Pb

Glass fibre #1 0.72 687 0.1 0.59 32.4 3.38

Glass fibre #2 0.18 540 0.17 0.50 42.1 18.23

Cellulose #1 0.05 854 0.06 1.40 21.5 3.89

Cellulose #2 0.13 529 0.07 0.19 19.6 0.93

Polycarbonate #1 0.13 365 0.05

Polycarbonate #2 0.14 364 0.13 0.33 21.9 7.11

Polycarbonate #3 0.09 483 0.06 0.99 24.8 4.07

Procedural blank 0.000 0.001 0.004 0.001 0.042 0.043

Although the Sigma-2 adhesive collection plate exhibited sufficient particle contrast after background elimination (Supplement 1), under the electron beam the adhesive would often deteriorate resulting in particle movement and the sinking of smaller particles. This issue appears to be particularly severe for particles with very low density (e.g., carbonaceous matter), and the surface destruction also prevented duplicate analysis. Another problem encountered with the Sigma-2 adhesive collection plates is that imperfections and scratches in the glue surface can be mistakenly detected as particles, and must be removed manually from the image prior to processing. Furthermore, the mass of the Sigma-2 adhesive collection plates is extremely high (orders of magnitude higher than the mass of the particles), and this makes them unsuitable for bulk chemical analysis following acid digestion.

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The polycarbonate filter was the most stable under the incidence of the electron beam and particles were well-preserved after background elimination (Supplement 1). Another advantage of the polycarbonate filters is their very low and consistent mass and negligible concentration of elements of environmental interest (with the exception of Cr, Cu and Zn; see Table 4.2). These features make them highly suitable, not only for MLA analysis, but also for acid digestion and bulk ICP-MS analysis.

Following these tests, it was concluded that the polycarbonate filters were the most suited for MLA analysis, and further method validation analyses were carried out using only these filters.

4.3.2 Accuracy and precision relative to certified reference materials (CRM)

The accuracy of the MLA analyses was evaluated by comparing the MLA- generated modal mineralogy with the reported mineral abundances (modal analyses) of USGS BHVO-2 (basalt) and GSP-2 (granite), two CRM commonly used in geochemical investigations(Pretorius et al., 2006; Wilson et al., 2012). The MLA data were obtained from the analysis of a thin layer of the CRM dispersed over the polycarbonate filter. This was produced by placing a small amount of the CRM over a clean sheet of paper and by aspirating this material on the polycarbonate filter using the same pump and IOM sampler utilized for APM sampling as described in Section 4.2.2. The modal analyses reported in the CRM description documentation were obtained by XRD followed by Rietveld refinement, and are provided for information only (i.e., they are not certified values).

Results of the MLA and modal analyses are reported in Table 4.3. MLA data for BHVO-2 are in excellent agreement with modal analysis (5% RSD accuracy or better), and the precision is also very high and well within the error of modal analysis. Data for GSP-2 are more variable, with RSD accuracy ranging from less than 20% for quartz, albite, microcline and muscovite, but as high as 183% for biotite. Similarly, precision RSD is 28% for biotite but better than 20% for the other mineral phases.

If all results were normalized biotite-free, both precision and accuracy would improve significantly and would be similar to those observed for BHVO-2. We postulate

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that the MLA sample preparation introduced a bias in GSP-2, with the preferential aspiration of the smaller and more easily airborne biotite particles relative to the other mineral phases. It is conceivable, however, that the MLA may be unsuitable for the correct quantification of minerals that have a strong cleavage, as the crystallographic orientation of a particular mineral grain relative to the incident electron beam may to some extent influence the spectral analysis and thus produce inaccurate results.

Table 4 .3Comparison between XRD and MLA data for USGS CRM BHVO-2 and GS P-2

USGS values MLA values (n=3 for each CRM)

Precision Accuracy

Weight Error % Weight σ* RSD σ RSD % %

BHVO-2 Augite 43 1 46 2 2 2 5

Andesine/Labradorite 53 1 50 2 4 2 5

Magnetite 4 0 4 0.5 11 0.2 4

Total 100 100

GSP-2 Quartz 34 0 27 3 11 5 14

Albite 33 0 25 2 9 6 18

Microcline 25 0 25 5 19 0.1 0.4

Biotite 5 0 18 5 28 9 183

Muscovite 4 0 5 0.5 11 1 14

Anatase 0.01 0.02 173

Total 101 100

* standard deviation

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This effect may be resolved by changing the instrument settings, however this will be considered in a future study and will not be further discussed here. The current data indicate that the MLA is suitable to (i) correctly identify the mineral phases present in APM derived from a rock sample, and (ii) correctly quantify their proportions, as long as only small amounts of micas are present.

4.3.3 Spatial homogeneity of the sample and operator bias

Different, randomly selected areas of one filter were analysed to assess spatial sample homogeneity. The same areas were also analysed by three different operators to evaluate the impact of operator-controlled parameters (mainly focus and greyscale calibration) on the analysis. Instrument conditions were kept constant during these tests.

Approximately 20,000 particles were analysed in each run. Analyses of different regions in the same filter led to statistically similar results (Table 4.4), indicating homogenous distribution of particles over the filter.

Table 4.4 Data for spatial homogeneity and operator bias. Mean values in area %

Three different areas, same sample Three different operators, same area

Phases* M ean σ RSD Mean σ RSD

Clay Minerals/Mica 51.12 2.83 5.54 53.18 0.24 0.45

Fe Oxides/Hydroxides 19.86 1.98 9.97 18.24 0.51 2.77

Calcite 7.40 0.67 9.00 7.13 0.23 3.16

Al Rich - Fe Oxides/Hydroxides ** 7.19 0.58 8.07 6.40 0.17 2.68

Carbonaceous Material *** 6.64 0.68 10.25 6.11 0.73 12.01

Quartz 1.74 0.15 8.82 2.18 0.20 9.06

Dolomite 1.21 0.07 6.08 1.16 0.10 8.38

* Only phases >1% are reported ** Al present in concentrations greater than detection limit (typically 1%) ***

Non-crystalline carbon-rich material

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When the same area was analysed by different operators the RSD are generally lower, with the exception of carbonaceous material (12.01%) and dolomite (8.38%), which is ascribed to decomposition under repeat exposure to the electron beam.

In summary, the results demonstrate that MLA system can be applied to analyse air particulates >1µm collected in a commercial filter apparatus. Special care, however, should be taken for repeat analyses of organic matter or other constituents that can be decomposed by the electron beam.

4.3.4 Pilot Study

For populations living in the vicinity of mining operations, exposure to airborne particulates is a significant vector for potentially toxic elements such as As and Mn. The ability to reliably identify these phases and their concentrations is important for emissions management and human and environmental health monitoring. To test the new methodology and determine the suitability of the MLA for generating reliable single particle data on particle size, morphology, elemental composition and mineralogy, two locations were selected for a pilot study; A) an area adjacent to an active gold mine and

B) a region near a large-scale Fe-ore operation. Particulates were sampled on polycarbonate filters using a personal IOM sampler without size segregation deployed for 6 hours at each location with a flow rate of 2 L min-1.

The BSE imaging allows for individual particle types to be clearly identified on the polycarbonate substrate, providing valuable morphological information, while the elemental data easily delineates the mineral type/phase present, for example arsenopyrite versus pyrite (Fig.4.2), which is advantageous when assessing potential sources of contamination.

The MLA software generates information on particle size distribution in both tabular form and graphically (Supplement 2 and 3) enabling the identification of the relative abundance of particles in different size fractions, reported in weight % (Fig.4.3). The size data reported in this study are the physical size based on the measured 2D surface and calculated by the MLA software using the equivalent circle diameter, and

does not represent the aerodynamic diameter.

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Figure 4.2 SEM image and elemental analysis of S-bearing particulates from site A

Particles collected from near the gold mine (site A) show a size distribution dominated by coarse (2.4-9.6 µm) and super-coarse particles (>9.6µm), which together contribute approximately 90% of the sample. In comparison, the proportion of fine particles (1-2.4µm) is significantly higher at site B than site A (16.36 and 4.13 % respectively).

100 80 60 40 20 Cumulatigve % 0 75 53 38 27 19 13.5 9.6 6.8 4.8 3.4 2.4 1.75 1.2 0.870.62 0

Particle Size (µm)

Site A Site B

Figure 4.3 Particle size distribution for sampling sites A and B

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The relative abundances of individual minerals, or modal mineralogy, for the analysed sample is formulated in weight%, and particle number (Table 4.5).

Samples from site A are dominated by clay and mica (81.82%), quartz (10.17 %) and carbonaceous material (3.34 %), Fe oxides (1.40%) and feldspar (1.39%), which is supported by the XRF data obtained during the validation of the spectral library.

Table 4.5 Modal mineralogy for particulates sampled from site A

TSP <10µm

Phase* Wt% Particle Wt% Particle number number

Clay Minerals/Mica 81.82 16910 76.02 13531

Quartz 10.17 2385 13.41 1818

Carbonaceous Material** 3.34 6461 3.91 5157

Fe Oxides 1.40 583 2.14 468

Feldspar 1.39 555 1.91 405

Py r ite 0.36 98 0.48 80

Fe Oxides w ith As*** 0.20 172 0.25 121

Arsenopyrite 0.03 5 0.05 4

Galena 0.02 30 0.03 20

Sphalerite 0.01 8 0.02 8

Chalcopyrite 0.01 6 0.01 6

Other 1.25 1220 1.76 893

Total 100 28433 100 22511

*Only As-bearing phases and phases > 1 % are reported ** Non-crystalline carbon-rich particles *** As present in

concentrations greater than the detection limit (typically 0.5%)

The concentrations of sulphides and arsenic-bearing phases, typical of the ore mineralogy, are negligible, with only 159 particles detected in the < 10µm fraction out of the 22,511 particles sampled.

The dominant particulate types from site B (Table 4.6) are clay minerals/mica (53.29%) and Fe (hydr) oxides (18.10%), with minor calcite (6.89%), carbonaceous

111 material (6.89%) and Al-rich Fe (hydr) oxides (6.24%). Manganese-bearing phases (such as romanechite, rhodochrosite, rhodonite and spessartite) are present in only minor amounts, with only 26 particles detectedin the < 10µm fraction out of the 5,603 particles sampled (Figure 4.4).

Figure 4.4. SEM images and elemental composition of Mn-bearing phases from Site B

In another investigation, Mössbauer spectroscopy of samples from the region of site B revealed a compositional variation between the ferruginous phases in the soil and the Fe-ore, with soil-derived Fe-(hydr)oxides samples enriched in aluminium(Tavares et al., 2017). Aluminium-rich Fe (hydr) oxides have been widely reported in lateritic soils from this and other regions (de Carvalho Filho et al., 2015; Diógenes Costa et al., 2014; Stucki et al., 2012). This compositional variation can be readily detected during MLA analysis (Fig.4.5) which is a potential aid to source apportionment.

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Figure 4.5 Elemental differences between Fe-(hydr) oxide and Al-enriched Fe-(hydr) oxide

From the modal analysis of samples from site B, the relative contribution of ore- derived Fe-(hydr) oxides (6.13%) and soil-derived Al-rich Fe-(hydr) oxides (5.10%) suggests that entrained soil is as significant a source of airborne particulates, possibly contributed by transport on unpaved roads and other mining operations that disturb the soil surface (Table 4.6).

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Table 4.6 Modal mineralogy for particulates sampled from site B

TSP <10µm Phase* % Particle Wt% Particle number number

Clay Minerals/Mica 53.29 2381 49.83 2194 Fe Oxides/Hydroxides 18.10 721 21.64 666 Calcite 6.89 469 7.72 409 Carbonaceous Material** 6.89 1851 7.07 1699 Al Rich - Fe Oxides/Hydroxides*** 6.24 328 6.37 268 Quartz 1.96 66 1.35 49 Dolomite 1.28 76 1.52 61 Vesuvianite 1.13 42 0.83 32 Rhodonite 0.15 5 0.03 3 Al rich Mn oxide*** 0.11 6 0.15 4 Romanechite 0.11 1 0.17 1 Apatite 0.08 10 0.09 7 Rhodochrosite 0.06 8 0.09 8 Spessartine 0.05 6 0.05 5 Jacobsite 0.05 4 0.08 4 Ankerite 0.02 2 0.01 1

Other 3.59 265 3.02 192 Total 100.00 6241 100.00 5603

*Only Fe- and Mn-bearing phases and phases > 1 % are reported. ** Non-crystalline carbon-rich material

***Al present in concentrations greater than the detection limit (typically 1%).

4.4. CONCLUSION

The identification of mineral, chemical and textural properties, such as size and shape, is fundamental in characterising the potential source and impact of atmospheric particulates. With its ability to rapidly analyse individual particles and provide mineral/phase identification and morphological information for different size categories, automated mineralogy has the potential to be a powerful tool in APM research.

After determining the optimum sampling technique and testing the accuracy and precision of the instrument by repeat analysis and comparison to CRMs, a pilot study was undertaken in two regions of diverse mineralogy. The MLA was able to identify potentially harmful mineral phases and phase variations demonstrating (i)the presence of negligible amounts of sulfides and arsenic-bearing phases typically associated with the gold deposit,with only 159 particles detected in the < 10µm fraction out of the

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22,511 particles sampled; (ii) Mn-bearing minerals in airborne particulates from near an Fe-ore operation are present in minor amounts (26 out of 5,603 sampled particles) and (iii) the contribution to the source of particulates near the Fe-ore operation is not only from ore extraction but also from the entrainment of soil by haulage on unpaved roads.

From the results of this study, the MLA has been shown to have a significant potential for the rapid acquisition of reliable, statistically valid data for the physical and chemical characterisation of airborne particulates, including the detection of potentially toxic phases. This information is requisite for effective emissions management and for the monitoring of human and environmental health.

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Supplement 1. BSE contrast (a) of particles and after background elemination (b) for different sampling substrates

Figure S1.1. Particulates on a cellulose filter: a) raw BSE image and b) BSE image after background elimination. Circled particles illustrate the poor BSE contrast after background elimination and the artificial removal of these particles.

Figure S.1.2. Particulates sampled on a Sigma-2 adhesive plate: a) raw BSE image and b) BSE image after background elimination.

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Figure S.1.3. Particulates sampled on a polycarbonate filter: a) raw BSE image and b) BSE image after background elimination.

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Supplement 2. Particle size distribution tables and graphs for Site B. The electronic sieve size (in µm) represents the particle size based on the equivalent circle area diameter as determined by the BSE image analysis.

Electronic Cum. Cum. Retained Sieve Size Retained Pas sing Wt% (µm) Wt% Wt% 75 0.00 0.00 100.00 63 2.50 2.50 97.50 53 1.58 4.08 95.92 45 1.36 5.45 94.55 38 0.79 6.24 93.76 32 1.25 7.49 92.51 27 2.11 9.60 90.40 22 2.07 11.67 88.33 19 2.43 14.10 85.90 16 2.56 16.66 83.34 13.5 2.34 19.00 81.00 11.4 3.44 22.44 77.56 9.6 4.84 27.28 72.72 8.1 5.37 32.66 67.34 6.8 6.17 38.83 61.17 5.7 7.04 45.87 54.13 4.8 7.97 53.84 46.16 4.1 7.73 61.57 38.43 3.4 8.79 70.37 29.63 2.9 6.86 77.22 22.78 2.4 6.42 83.64 16.36 2 4.89 88.53 11.47 1.75 3.00 91.53 8.47 1.45 3.13 94.66 5.34 1.2 2.13 96.79 3.21 1 1.53 98.32 1.68 0.87 0.70 99.02 0.98 0.73 0.73 99.75 0.25 0.62 0.24 99.99 0.01 0.52 0.00 99.99 0.01 0 0.01 100.00 0.00

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Supplement 3. Particle-type size distribution in tabular and graphical form generated for Site A. The electronic sieve size (in µm) represents the particle size based on the equivalent circle area diameter as determined by the BSE image analysis. Fe Oxides Cum. Electronic Passing Grain Size Distribution Sieve Size Wt% 100 0.52 0 95 0.62 0.01 90 0.73 0.01 85 0.87 0.05 80 75 1 0.16 70 1.2 0.46 65 1.45 1 60 1.75 1.87 55 Fe Oxides 2 2.62 50 Quartz 2.4 3.84 45 40 Clay Minerals/Mica 2.9 5.42 35 Feldspar 3.4 7.03 30 4.1 9.68 25 Carbon

4.8 12.58 (Wt%) Passing Cumulative 20 5.7 17.63 15 6.8 25.59 10 8.1 36.49 5 0 9.6 51.78 0 1 2 16 19 22 27 11.4 68.95 1.2 2.4 2.9 3.4 4.1 4.8 5.7 6.8 8.1 9.6 0.52 0.62 0.73 0.87 1.45 1.75 11.4 13.5 13.5 85.16 Sieve Size (µm) 16 94.96 19 98.75 22 99.73 27 100

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WILLIAMSON, B. J., ROLLINSON, G. & PIRRIE, D. 2013. Automated mineralogical analysis of PM10: New parameters for assessing PM toxicity. Environmental Science and Technology, 47, 5570- 5577.

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Chapter 5

Characterisation of Airborne Particulate Matter Near a Large Scale Iron-Ore Mine by Automated Mineralogy

Abstract

To determine the potential environmental and human health impacts of atmospheric emissions from open cast mining operations, an understanding of the physical and chemical characteristics of individual airborne particulates is essential. As a large number of particles need to be analysed to generate a statistically robust data set, techniques that require manual analysis and data processing can be time consuming and therefore impractical for regular monitoring purposes. With their ability to rapidly generate data on size, shape and mineral phases automated mineralogy systems have the potential to overcome this limitation.

This study analysed total suspended particulates collected near a large-scale iron ore mining operation in Minas Gerais, Brazil. Due to the marked seasonality of the region, three sets of samples were collected over 6 hour periods from five monitoring sites during summer, winter and the transitional period to determine seasonal variations. The mineral phases observed strongly reflected the local geology, with clays and iron oxides contributing to approximately 70-80% of the particulates sampled. Particle size distributions indicate sources dominated by mechanical processes, with coarse particles (>2.5 µm) accounting for more than 80-90% of the samples. A strong seasonality was observed with greatest proportions of coarser particles during the dry seasons of May and August, with fine particles (1-2.5 µm) contributing to less than approximately 10% of the particulates analysed.

5.1. Introduction

Mining operations are significant sources of airborne particulate matter (APM), and are especially notable due to the quantity produced, the extent of the area affected and the toxicity of associated contaminants (Csavina et al., 2012). Although atmospheric dispersion of particles is a potentially important route of human exposure to metal(loid)s in communities close to active and abandoned mining areas, most of the studies investigating the impacts of mine-derived contamination have concentrated on smelting and other

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combustion processes (Barcan, 2002; Batonneau et al., 2004; Bi et al., 2006; Chaoyang et al., 2009), with less attention paid to particulates derived primarily from a geological origin (Balabanova et al., 2011; Geranian et al., 2013; Meza-Figueroa et al., 2009; Noble et al., 2017).

Traditionally, most studies on APM have focused on particle size, mass concentrations and bulk chemistry, however other particle characteristics such as shape and the distribution of chemical species within individual particles are also of importance. A variety of methods and instruments are available for APM measurement, however, a single practical technique does not exist for obtaining all the information required for detailed characterisation (Elmes and Gasparon, 2017). Although scanning electron microscopy and energy dispersive X-ray spectrometry (SEM-EDS) has been used extensively in APM studies, manual analysis can be time consuming, expensive and subject to operator bias. SEM-based automated mineralogy systems, such as the Mineral Liberation Analyzer (MLA), are gaining popularity in aerosol research due to their ability to rapidly collect a statistically significant amount of data on size, shape and mineral phases, allowing for precise information on individual particles (Choël et al., 2005; Morrison et al., 2011; Wilkinson et al., 2013; Williamson et al., 2013).

The MLA is an automated digital image analyser coupled to an SEM-EDS that was developed to improve the efficiency of mineral processing plants (Gu, 2003). Although this technology has been used extensively in the mining industry for the past two decades, it is only recently that it has been used for other applications such as detailing micro-structural controls on hardpan formation in mine tailings (Redwan et al., 2012), determining the potential for acid mine drainage from waste rock (Buckwalter-Davis, 2013) and sediment provenancing(He et al., 2017; Rütters et al., 2018; Septama et al., 2011; Tsikouras et al., 2011). This widespread use in the mining industry, which precludes the need to invest in further instrumentation and user training, provides an advantage for the MLA over other well developed techniques, such as the electron probe microanalyzer (EPMA), for the monitoring of mine-derived APM.

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The aim of this study is to illustrate the potential of automated mineralogy for the monitoring of mine-derived geogenic particulates in the atmosphere and to determine whether the MLA can generate data suitable for the identification of seasonal variations in the dominant mineral phases and their relative contribution to the different size fractions in APM near a large scale iron ore operation.

5.2 Materials and Methods

5.2.1 Sampling Locations

The banded iron formation in the Quadrilátero Ferrífero (QF) in the state of Minas Gerais, Brazil, is one of the largest iron ore producing areas in the world (Klein and Ladeira, 2000). Congonhas lies in the far southwest corner of the QF, approximately 60km south of the state capital Belo Horizonte. The city is surrounded by five major open pit iron ore mines and as a result is exposed to high levels of geogenic APM emissions, with estimates of approximately 2.5 tonnes emitted hourly(Andrade et al., 2016).

Particulates were collected at five sampling stations within and around Congonhas city (Fig.5.1). Sampling locations were chosen either for their proximity to the mine sites (Casa de Pedra) or to the rail line servicing the mines (Plataforma and Pires). Basilica is located within the city, approximately 6km downwind of the mine site. A control site within the same geological setting but outside the influence of the Casa de Pedra mining operation was selected to the north at Retiro.

The high-grade iron deposits in the QF are hosted in a Proterozoic metamorphosed banded iron formation, locally called itabirite (Spier et al., 2003).Iron ore was formed throughout the QF by the iron enrichment of itabirite (protore). Two types of iron ore are

mined in the QF; high-grade ore (>62 wt. % Fe) and itabiritic ore (~30-62 wt. % Fe). High- grade ores are comprised of almost pure iron oxides (hematite/magnetite) whilst the itabiritic ores contain hematite (with subordinate magnetite) and goethite. Quartz is the main gangue mineral, with minor amount of apatite, carbonates (dolomite/calcite) and Mn- oxides (Rosière et al., 2008; Spier et al., 2008).

Chemical weathering of itabirite, iron ore and the country rocks in the QF has resulted in the formation of thick lateritic profiles (up to 400 m depth), capped by a

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Figure 5.1 Location of Congonhas and the five sampling locations: Plataforma (PLA), Casa de Pedra(CDP), Pires (PIR), Basilica (BAS) and Retiro (RET).Background maps from Google Earth™

ferruginous duricrust (Spier et al., 2018). At the Casa de Pedra deposit, high grade ore is the major ore type mined, with an average modal composition of hematite/magnetite (87%), goethite (11%) and quartz (2%). Itabiritic ores surround the high-grade ore body and are comprised of hematite/magnetite (52%), goethite (16%) and quartz (32%))(Trzaskos et al., 2011). The country rocks mined as waste material (phyllite and dolomite) are strongly

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weathered and incorporate clays, sericite, quartz, goethite and Mn-oxides (Rosière and Chemale Jr, 2017; Spier et al., 2006).

The climate of the region is temperate because of the altitude, which ranges from 600 to 2100 metres. The temperature varies little throughout the year and there is a distinct wet (November-February) and dry season (June-September), with short transition periods between (Fig.5.2).Prevailing regional winds are predominantly from the northeast, however the Sierra da Moeda mountain range to the north of Congonhas deflects it towards the city in the southeast.

Figure 5.2 Average temperature, rainfall and prevailing wind direction (% ) for Congonhas( EC OS O FT , 2012)

5.2.2 Sample Collection

To determine seasonal variations, particulates were sampled during the wet season. the dry season and the transitional period, based on the methodology developed by Elmes et al. (2020b). Total suspended particulates (TSP) were collected using a portable, battery- operated SKC ‘AirChek 52’ low-volume pump (SKC item 224-52; flow rate of 2 L min-1) fitted with a personal IOM (Institute of Occupational Medicine) sampler for respirable dust without size selection (SKC item 225-70A) and deployed for 6 hours. Particulates were collected on polycarbonate filters (0.8 µm x 25mm, SKC item 225-1601). For SEM/MLA analysis filters were mounted directly onto an aluminium stub with double-sided carbon tape and coated with a conductive carbon film. Although only TSP was collected for this

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study, this technique is suitable for any low or medium-volume sampler with size selective inlets for particles greater than 1µm. High-volume sampling is unsuited to this technique as the high particle loadings and ensuing particle overlap makes single particle analysis problematic.

5.2.3 SEM/MLA Operating Conditions

Analysis was done on an MLA 650 system coupled to a FEI Quanta 650 SEM-FEG, equipped with two Bruker Quantax silicon-drift EDS spectrometers. The SEM was set to operate in a high vacuum with an accelerating voltage of 25 kV, beam current of 18 nA, spot size 5.1 and a 10 mm working distance. The MLA was configured to collect 2,000 X-ray counts for each point of analysis and to process 20,000 particles, or a maximum run time of 2 hours, per sample.

5.2.4 Formulation of the Mineral Library

Mineral classification is based on matching the spectrum collected on an unknown mineral to a library of X-ray spectra for known reference minerals collected using the same instrument parameters. Each mineral phase in the library is typically characterised by 2-5 spectra, depending on the complexity, and incorporates variable X-ray peak intensities (Elmes et al., 2020). For this study, the X-ray matching tolerance was configured for 85%.

For validation of the mineral library, fourteen regional soil and rock samples were analysed by X-ray diffraction (XRD) on a Philips PANalyticalX'Pert-APD system with a PW 3710/31 controller, PW 1830/40 generator and PW 3020/00 goniometer, with Cu graphite monochromatised radiation, a 1 second step speed, 0.06° sampling step and 4-90° 2θ range. Peak recognition and mineral identification for all analyses were performed using the PDF-2 database (ICDD, 2003).

5.3. Results and Discussion

5.3.1 Mineralogy and Particle Morphology

The observed mineralogy of the sampled particulates strongly reflects the local geology with all sampling locations/periods dominated by Fe-(hydr) oxides, hereafter referred to as Fe-oxides, and clay/micaceous minerals, which collectively contributed to

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approximately 70-80% of the TSP (Fig.5.3). Only mineral phases present in relative proportions (expressed as weight percent) greater than 1%have been reported.

The weathered, near-surface exposures of the ore deposit are dominated by of iron oxides (hematite, goethite, magnetite), kaolinite and albite with minor mica, quartz, graphite, chlorite, talc and dolomite (Clout and Manuel, 2015; Ramanaidou, 2009; Spier et al., 2003; Spier et al., 2008).

Figure 5.3 Relative proportions (wt% ) of mineral phases in sampled APM. Only phases >1 wt% are reported."Other" includes mineral phases present in proportions <1 wt%.

For this study, phyllosilicate phases, such as clays and mica, were grouped together for ease of analysis due to the complex range of compositional end-members and the highly variable ionic substitution that occurs in this mineral group. With the exception of

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Plataforma (PLA) and Casa de Pedra (CDP) during January, clays and micaceous minerals were the dominant phase present, typically contributing approximately 35-55 wt% of the TSP.

Iron oxides typically contributed approximately20-30 wt% of the TSP, with the exception of Plataforma and Casa de Pedra during January, which recorded 49 wt% and 40 wt% respectively. Iron oxides containing approximately 8-10 wt% aluminium were observed at all stations, though typically present in relative proportions of less than 5 wt%. Substitution of Al for Fe has been postulated to occur during weathering and pedogenesis and Al-rich Fe-oxides, inferred to represent surficial ferruginous phases, have been widely reported in the area (Camêlo et al., 2017; Carvalho Filho et al., 2015; Fontes and Weed, 1991; Ramanaidou, 2009; Tavares et al., 2017).

Significant proportions of calcite were observed during January at Retiro (RET, 34 wt%), Basilica (BAS, 24 wt%) and Pires (PIR, 15 wt%) and at Casa de Pedra during August (27wt%). For the other sampling periods, calcite typically contributed to less than 7 wt%. Only minor variations were observed in the relative proportions of calcite at Plataforma during the three sampling periods. Although it was difficult to distinguish between geogenic and anthropogenic calcite, Plataforma, which despite being located adjacent to the loading facility, is situated in a rural village that has largely been de-populated due to the mining operations. With minimal agricultural and construction activities nearby, coupled with the virtual absence of road traffic, the proportions of calcite observed at this site are suggestive of a predominantly geogenic origin, reflecting the concentrations present in the local bedrock. Based on this assumption, and combined with the spatio-temporal variations observed at the other locations, the higher relative proportions of carbonates reported most likely include a significant contribution derived from anthropogenic sources, such as construction and agricultural activities and non-exhaust traffic emissions.

Quartz was present in only minor amounts (<~5 wt%), which is consistent with the depletion of silica during lateritic weathering (Hagemann, 2008; Lascelles, 2012). Other

minor phases include dolomite, gypsum and pyroxene, though typically these contribute <~2

wt% of the TSP. During August, Casa de Pedra recorded an anomalously high amount (~30

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wt%) of calcium phosphate particles, most likely derived from an anthropogenic source, such as fertilizer.

Carbonaceous material was observed at all sampling locations/periods, with proportions ranging from <~1 wt% to 12 wt % with higher values typically observed during May. Although the MLA was able to quantify carbon-rich particles, the method to date hasn’t been refined to readily distinguish between natural organic (e.g. pollen and spores) and anthropogenic (e.g. combustion) sources, particularly when they exhibit similar morphologies. As this precludes the accurate assessment of potential source contributions, a detailed characterisation of the carbonaceous material detected in the sampled APM lies outside the scope of this study.

Particle shape is generally a good, though not conclusive, indicator of particle source and transportation history. Particles were typically irregular, exhibiting relatively smooth, unweathered surfaces and distinct crystal structures (Fig. 5.4a-b), occurring as either individual large particles with smaller attached particles or agglomerates of similar-sized particles (Fig. 5.4c).

Geogenic APM, particularly Ca-containing species, provide reactive surfaces for

secondary reactions in the atmosphere with gases such as SO2, which can modify the original morphology and chemical composition(Li et al., 2016a). Atmospheric processing of particles, or particle aging, was observed either as individual growths, such as the fine, needle-like carbonate crystals in Figure 4d, or S-rich surface coatings and spherical growths on calcium phosphate particles (Fig. 5.4e).The transformation of carbonate particles into Ca- rich spheres under humid conditions has been attributed to surface reactions in the atmosphere with SO2(Okada et al., 2005).

Carbonaceous material was predominantly present asfine-grained graphitic particles derived from the local phyllite, however biological material (Fig. 5.4f), combustion-derived carbon cenospheres (Fig.5.4g) and soot aggregates (Fig. 5.4h) were also observed.

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Figure 5.4 S EM images of (a) TSP sampled on a polycarbonate filter,(b)Fe-oxi de , (c) clay agglomerate wi th Fe-oxides, (d)calcite with secondary crystal growths, (e)surface reactions on calcium phosphate particle, and carbonaceous particles exhibiting similar morphologies (f) biological material, g) carbon cenospheres and h) soot aggregate.

5.3.2 Particle Size Distributions

Mechanical processes associated with mining operations, such as blasting, extraction and transportation on unsealed roads, as well as agricultural and construction activities, non-exhaust traffic emissions and windblown re-suspension of soil, typically generate coarse

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particles (Patra et al., 2016). This is reflected in Figure 5.5, with the coarse (2.4-9.6 µm) and super-coarse(>9.6 µm) fractions contributing approximately 80-90% of the TSP.As size- selective inlets were not deployed in this study, particle sizes reported here are physical (geometric) size, calculated by the MLA software as an equivalent circle based on particle area, and do not represent the aerodynamic diameter.

Figure 5.5 Geometric size distribution of TSP. Shaded area represents the coarse particle fraction(9.6-2.4 µm). Dashed horizontal line represents the median.(BAS-Basilica, RET-Retiro, PLA- plataforma, CDP- Casa de Pedra, PIR- Pires)

For most sampling locations the highest proportion of super-coarse particles were observed during August, contributing approximately 30-40 wt% of the TSP, compared to less

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than 30 wt% during January. Coarse particles were more prevalent in May and August, typically comprising ~50-65 wt%, with median particle sizes of around 8.1 and 6.8µm respectively. All stations displayed higher relative proportions of fine (<2.4 µm) particles during January (10-20 wt%) compared to the other sampling periods, with the median particle size ranging from 5.7-4.1µm. For most locations, the distribution of fine particles was similar in May and August with relative proportions of less than 10 wt%.

5.3.3 Particle size and number distributions for individual mineral phases

As geogenic APM is frequently comprised of agglomerations of smaller particles, to accurately assess the potential impacts of APM exposure, as well as identify potential sources and develop successful mitigation strategies, an understanding of size distribution for individual mineral phases is important. To enable the characterization of individual grains within a particle, the MLA has a de-agglomeration function which can separate agglomerations based on boundary identification parameters. The size distributions for the most common mineral phases are shown in Figure 5.6.

At all locations Fe-oxides in the coarser fractions were more prevalent in May (>90

wt%) compared to January (~60-80 wt%) and August (~70-80 wt%). The highest proportions of fine Fe oxides were reported at Pires (40 wt%) and Basilica (38 wt%) during January and Casa de Pedra (45 wt%), Pires (31 wt%) and Basilica (30 wt%) during August. At Retiro, fine

Fe-oxides were observed in similar amounts (~27 wt%) for both the January and August sampling periods.

Clay minerals exhibited a similar distribution with coarse and super-coarse particles contributing to more than 90 wt% of the clay minerals analysed during May, with more than 25 wt% observed in the super-coarse fraction across most sampling locations. During

January and August fine clay particles typically contributed less than ~20 wt%, compared to less than 10 wt% during May.

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Fe Oxides 100 BAS PLA PIR RET CDP 80 60

Wt% 40 Ja nuary May 20 Augus t 0 0 1 0 1 0 27 38 22 27 6.8 3.4 8.1 4.8 2.9 38 22 6.8 3.4 27 8.1 4.8 2.9 6.8 3.4 13.5 1.75 0.87 13.5 1.75 0.62 13.5 1.75 0.87 13.5 1.75 0.62 13.5 1.75 0.87

Clays 100 BAS PLA PIR RET CDP 80 60

Wt% 40 Ja nuary May 20 Augus t 0 0 1 0 2 1 53 27 38 22 27 6.8 3.4 8.1 4.8 2.9 6.8 3.4 45 22 32 16 5.7 2.9 8.1 4.1 13.5 1.75 0.87 13.5 1.75 0.62 13.5 1.75 0.87 11.4 1.45 0.73 0.52

Calcite 100 PIR RET BAS PLA 80 CDP 60

Wt% 40 Ja nuary May 20 Augus t 0 2 0 27 16 1.2 9.6 5.7 3.4 45 22 32 19 27 5.7 2.9 6.8 4.1 2.4 6.8 4.1 2.4 6.8 3.4 0.73 11.4 1.45 0.73 11.4 1.45 0.87 0.52 1.45 0.87 11.4 13.5 1.75 0.87 19.00 Figure 5.6 Size distribution for common mineral phases in cumulative weight percent. Sizes in µm. Shaded area represents coarse (2.4-9.6 µm)fraction. Horizontal dashed line represent median particle size. (BAS-Basilica, RET-Retiro, PLA- plataforma, CDP- Casa de Pedra, PIR- Pires)

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The median particle size of calcite particles observed at Plataforma, which are

inferred to be primarily of geogenic derivation, ranged from ~4.8µm in January, to 11.4 and 6.8 µm during May and August, with 59 wt% and 33 wt% observed in the super-coarse fraction for these sampling periods respectively. Fine particles at this site contributed to

<~15 wt% of the calcite particles analysed, with the lowest reported during May (2.6 wt%). Apart from during May, the other sampling locations exhibited highly variable size distributions of calcite particles and a temporal trend was not obvious, with fine calcite particles ranging from 8-36 wt% during January and 14-31 wt% during August.

The size distribution of mineral phases is also reflected in the particle numbers for the individual phases in the coarse and fine size fractions (Fig.5.7). The particle numbers reported here represent different mineral phases identified in individual particles by the MLA software prior to EDS analysis. As the MLA is configured to analyse a maximum of 20,000 particles per sample, the results do not represent TSP particle number concentrations nor do they correlate with other techniques, such as condensation particle counters, that are regularly used for compliance monitoring. The sizes reported are also geometric sizes and do not represent the aerodynamic diameter. Despite this, the particle number data generated by the MLA provides a useful insight into the relative contribution to the different size fractions of individual mineral phases.

A strong seasonality is observed, with the maximum particle number for individual phases within the 10-2.5 and <2.5 µm size fractions across all stations during January below 4,000, compared to maximums of more than 40,000 during May and August. This is consistent with other studies that have reported lower particle numbers during wet conditions (Komppula et al., 2009; Wang et al., 2018).

During January, when the relative proportions of fine particles are highest, across most stations clays, carbonaceous material and Fe-oxides contribute strongly to this fraction in terms of particle numbers. Interestingly during January, "other" phases, which include siderite (FeCO3), jacobsite (FeMn2O4), ilmenite (FeTiO3) and gibbsite (AlOH3), although contributing individually to less than 1 wt% of TSP, are predominantly in the fine fraction, particularly at Casa de Pedra. During May, all mineral phases are predominantly in the coarse fraction, though again the major contributors to the fine fraction are clays,

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carbonaceous material and Fe oxides. During August, most mineral phases were present in similar amounts in both size fractions. The anomalous proportion of Ca phosphate particles observed at Casa de Pedra during this period also significantly contributed to the number of fine particles observed at this site.

From the results of this study, the observed mineralogy strongly reflects the local geology with all sampling locations dominated by Fe-oxides and clays, which contribute 70- 80 wt% of the TSP. Although the high-grade ore deposit at Congonhas is hosted in a dolomitic iron formation, locally called dolomitic itabirite, the deep lateritic weathering, reaching depths of 400-500 meters , has resulted in the leaching of quartz and dolomite from the parent rock (Amorim and Alkmim, 2011; Silveira et al., 2018; Spier et al., 2006b). This is consistent with the low levels of quartz and dolomite detected in the MLA analysis.

A strong seasonality is observed in particle size distributions with all stations recording their highest proportions of coarser particles (>2.4 µm) during the dry periods of May and August. This was also reflected in the size distribution for individual mineral phases, with all sites recording the highest proportion of coarse particles during May.

Particle numbers for individual mineral phases were also significantly higher during the dry periods. This is consistent with other studies that have demonstrated increased washout and shortened atmospheric residency times of coarser particles during rainfall conditions (Guo et al., 2016; Rathnayake et al., 2017; Zhang et al., 2018). Wet conditions also hinder the re-suspension of surface deposits, particularly for highly cohesive minerals such as clay. As Plataforma and Pires are located adjacent to the loading facility and rail line respectively, variations in size distribution and particle numbers at these sites are inferred to be independent of seasonal influences.

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PLA PIR BAS CDP RET 4000 January 10-2.5 µm 3000 <2.5 µm 2000 1000 0 C-rich Other C-rich Other Calcite Quartz C-rich Other C-rich Other C-rich Other Calcite Quartz Calcite Calcite Quartz Quartz Calcite Quartz Gypsum Dolomite Pyroxe ne Chlorite Fe Oxides Gypsum Clay/Mica Dolomite Pyroxe ne Pyroxe ne Fe Oxides Fe Oxides Fe Oxides Clay/Mica Pyroxe ne Clay/Mica Clay/Mica Fe Oxides Clay/Mica Al_Fe Oxides Al_Fe Oxides Ca-phospate Al_Fe Oxides Al_Fe Oxides Al_ Fe Oxides

12000 50000 10-2.5 µm 10000 May 40000 <2.5 µm 8000 30000 6000 20000 4000 10000 2000 Particle number Particle 0 0 C-rich Other C-rich Calcite Other Quartz C-rich Other Calcite Quartz Chlorite C-rich Other C-rich Calcite Other Gypsum Quartz Calcite Calcite Quartz Quartz Pyroxe ne Fe Oxides Clay/Mica Dolomite Pyroxe ne Gypsum Fe Oxides Clay/Mica Fe Oxides Clay/Mica Dolomite Pyroxe ne Pyroxe ne Fe Oxides Fe Oxides Clay/Mica Clay/Mica Al_Fe Oxides Al_Fe Oxides Al_Fe Oxides Ca phospha te Al_Fe Oxides Al_Fe Oxides

10-2.5 µm 15000 8000 50000 <2.5 µm August 40000 10000 6000 30000 4000 5000 20000 2000 10000 0 0 0 C-rich Other Calcite Quartz C-rich Other C-rich Other Calcite Quartz C-rich C-rich Other Other Calcite Quartz Calcite Calcite Quartz Quartz Gypsum Fe Oxides Clay/Mica Chlorite Gypsum Dolomite Pyroxe ne Dolomite Pyroxe ne Fe Oxides Fe Oxides Clay/Mica Clay/Mica Pyroxe ne Pyroxe ne Fe Oxides Fe Oxides Clay/Mica Clay/Mica Al_Fe Oxides Ca phospha te Al_Fe Oxides Al_Fe Oxides Al_Fe Oxides Al_Fe Oxides

Figure 5.7 Particle number for individual mineral phases in the coarse (10-2.5 µm) and fine (1-2.5 µm) fractions. BAS -Basilica, RET-Retiro, PLA- plataforma, CDP- Casa de Pedra, PIR- Pires.

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Although fine particles can be transported large distances, super-coarse particles usually have a shorter atmospheric residency time. Under the meteorological conditions observed during the May sampling (19oC and wind speed of 2.7m/s), a 10µm Fe-oxide particle will travel less than 1km due to its high density (5.25 g/cm3). The high relative proportions of super-coarse particles at Casa de Pedra and Basilica, which are located approximately 3 and 6 kilometres from the mine site respectively, and at Retiro, which lies outside the area of the Casa de Pedra mining operation, suggests that a significant proportion of the Fe oxides sampled at these locations are derived from a more localised source, most likely re-entrained soil. The presence of Al-rich Fe-oxides, which is inferred to represent surficial ferruginous phases, also supports this observation. The influence of the mine, however, is inferred from the higher relative proportions of fine Fe-oxide particles at Basilica and Casa de Pedra, which are located downwind from the mine site, however the only way to truly substantiate this is to combine the MLA analysis with gravimetric data. Other anthropogenic APM contributions are observable in anomalously high relative proportions of calcite particles, most likely derived from construction activities and non- exhaust traffic emissions.

A limitation of the current method is the inability to distinguish between biogenic and anthropogenic carbonaceous material and, as a result, the interpretation of the potential source(s) of carbonaceous material detected in the sampled particulates lies outside the scope of this study. To enable this distinction a detailed spectral library would need to be constructed, potentially using marker trace elements, as combustion-derived particles have been shown to contain metallic elements such as As, Ba, Sn, Mo, Cr, V, Fe, Ni, Cu, Zn, and Pb (Genga et al., 2017). Potassium associated with carbonaceous material has been observed as a marker for biomass burning (Kılavuz et al., 2019) whilst primary biogenic material, such as spores and pollen, has been shown to contain minor amounts of N, P, Cl and Si (Mico et al., 2015). Using trace element markers, however, could be potentially problematic, due to the small sample size and the potential for these elements to be present in concentrations lower than the detection limits of the instrument.

A further limitation of this study was the use of a TSP sampler rather than one fitted with a size selective inlet. Whilst the MLA has been shown in this study to be capable of generating physico-chemical information on sampled particulates, without the ability to

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measure the aerodynamic diameter a true understanding of the potential sources and impacts is unable to be accurately determined.

5.0 Conclusions

Atmospheric particulates derived from mining operations can pose significant risks to the environment and nearby populations. The successful mitigation of these risks requires a detailed physical and chemical characterisation at the individual particle level. For this to be achieved thousands of particles need to be analysed which using conventional SEM-based techniques can be time consuming and costly. Automated systems, such as the MLA, can overcome some of these drawbacks with their ability to rapidly collect statistically valid quantitative data on size, morphology and mineralogy.

Using the MLA to analyse ambient APM, a strong seasonality was observed near the Casa de Pedra iron ore mine in Congonhas, Brazil, with coarse and super-coarse particles more prevalent during May and August, with fine particles contributing to less than 10 wt% of the TSP. Size distributions and particle numbers for individual mineral phases during January and August, however, indicated a large proportion of agglomerated particles.

Iron oxides and clay minerals were the dominant phases sampled, contributing 70-80 wt% the TSP. The high proportion of clay minerals, which are representative of surficial deposits, combined with soil-derived Al-rich Fe-oxides and similar relative proportions of Fe- oxides at the control site to sampling locations proximal to the mine, indicate re-entrained soil, occurring either through natural or anthropogenic disturbances, is a significant source of Fe-oxides in the atmosphere. The influence of the mine, however, is inferred from the higher relative proportions of fine Fe-oxide particles at locations situated downwind from the mine-site.

To our knowledge, this is the first time the MLA has been used for a detailed characterisation of APM. This study shows that the MLA is capable of generating the physico-chemical information at the single particle level that is requisite for source apportionment and predicting the impact on human and environmental health. With its rapid data acquisition and software capabilities, the MLA has the potential to be an

140 invaluable tool for the monitoring of mine-derived geogenic particulates in the atmosphere.

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Chapter 6

Characterisation of Manganese-Bearing Mineral Phases in Atmospheric Particulate Matter

Abstract

Although an essential element, inhaled manganese has long been recognised as a potential neurotoxin. To date, the majority of research into atmospheric manganese has concentrated on occupational exposure with fewer studies focussing on ambient exposures, despite growing evidence of adverse health outcomes from long-term exposure to ambient concentrations. The toxicity of manganese depends not only on the route of exposure but also its chemical species. The ability to accurately identify the mineral phases of potentially toxic elements in the atmosphere is necessary for the implementation of successful mitigation techniques.

The present study is aimed at assessing the potential of the Mineral Liberation Analyzer (MLA) system to identify and characterise manganese-bearing mineral phases in airborne particulate matter, and tests its application to monitor potentially toxic elements in atmospheric emissions. The city of Congonhas in Minas Gerais, Brazil is surrounded by five major open pit mines and was selected for the study.

Our study indicates that the MLA is able to identify the Mn-bearing particles and rapidly generate statistically significant data sets, and can be an effective tool for the monitoring of geogenic emissions to safeguard environmental and human health. The most common Mn-bearing phases observed were Mn Oxide and jacobsite, with minor spessartine, rhodonite and romanechite. Particles exhibited irregular, crystalline morphologies, with physical diameters predominantly greater than 2.5 µm, indicative of a geogenic rather than anthropogenic source. As the aerodynamic diameter of the particles will be significantly higher than their physical diameter, the risk of inhalation and deposition within the alveoli and the potential bioaccessibility of the inhaled Mn- bearing particles is likely to be minimal.

6.1.0 Introduction

For populations living near large-scale mining operations airborne particulate matter (APM) is a potentially significant contaminant vector. Traditionally, research on the

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environmental impact from mining operations has focused on the transport of contaminants via soil and water, with little attention paid to atmospheric transport which, unlike the other vectors, has the potential to be transported rapidly over vast distances (Csavina et al., 2012a).Research on mine-related APM and its impact on human health has also tended to concentrate on smelting and metallurgical activities with less investigation into geogenic particulates (Chaoyang et al., 2009; de la Campa et al., 2015; Félix et al., 2015; Noble et al., 2017; Williamson et al., 2004). Mining processes generate diverse pathways for the emission of geogenic particles, such as the removal of overburden, blasting, crushing, haulage on unsealed roads and dispersal from waste piles.

Historically research on mine-derived metal(loid) contaminants has focused on mercury (Loredo et al., 2007; Moreno et al., 2005), arsenic (Corriveau et al., 2011; Hwang et al., 1997; Kim et al., 2013; Martin et al., 2014) and lead (Félix et al., 2015). Recent toxicological and epidemiological studies, however, have highlighted the hazards associated with the inhalation of transition metals such as manganese (Riojas-Rodríguez et al., 2010).

Manganese (Mn) is ubiquitous in the environment, occurring naturally in rocks, soils and water. In the environment, manganese occurs primarily in three valence states, Mn2+, Mn3+, and Mn4+, and is commonly associated with iron. It is an essential metal necessary for the normal functioning of a variety of physiological processes, including amino acid, lipid, protein and carbohydrate metabolism (Santamaria and Sulsky, 2010). It also plays an essential role in immune system functioning, bone and connective tissue growth and blood clotting(Williams et al., 2012). In the brain, it is an important co-factor for enzymes involved in neurotransmitter synthesis and metabolism (Aschner et al., 2007). Despite this essentiality, Mn has been known to be a neurotoxin for more than 100 years. Overexposure is associated with a variety of psychiatric and motor disturbances, including postural instability, hallucinations and parkinsonian-type symptoms (Guilarte, 2010). Cognitive deficits such as memory impairment and visuomotor and visuospatial difficulties have also been reported (Lucchini et al., 2017).

The toxicity of manganese varies according to the route of exposure, with inhalation recognised as the most hazardous (Andersen et al., 1999). When ingested, Mn is efficiently eliminated, however, inhaled Mn bypasses the normal excretionary mechanisms and may

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enter the central nervous system directly. Entry of Mn to the brain can occur via three known pathways: through the blood-brain barrier, by cerebrospinal fluid or via the olfactory nerve from the nasal cavity directly to the brain (Martinez-Finley et al., 2013). While the half-life of Mn in the blood ranges from 10-42 days (Kafritsa et al., 1998), once it has crossed the blood-brain barrier, its average half-life is 51-74 days (Takeda et al., 1995). Furthermore, animal studies reveal that the penetration of Mn into the central nervous system is three orders of magnitude greater than by ingestion (Andersen et al., 1997). Inhalation exposure to manganese has also been associated with toxicity to the pulmonary and reproductive systems(Williams et al., 2012).

Most of the studies on the neurotoxic effects of inhaled Mn, however, have been conducted on occupational groups exposed to high levels (Antonini et al., 2006; Bowler et al., 2006; Halatek et al., 2008). There is now, however, growing evidence that low-level, long-term (chronic)exposure to airborne Mn can also have lasting toxic effects on human health (O’Neal and Zheng, 2015; Santos-Burgoa et al., 2001), with ambient exposure also affecting sensitive groups such as children and the elderly (Menezes-Filho et al., 2011; Riojas-Rodríguez et al., 2010).

Although the transport and fate of APM is largely determined by particle size and shape, the knowledge of the species of a metal is critical in assessing its toxicity as the chemical aspects that determine the speciation of a metal controls its mobility and solubility and, as a result, different species of the same element will have different toxicological properties (Carmona et al., 2014; Reeder et al., 2006; Roels et al., 1997). Geochemistry has been shown to influence the mobility, and thus the potential bioaccessibility, of various hazardous metals, such as chromium (Moreira et al., 2018), zinc(Molina et al., 2013), lead (Denys et al., 2007; Hayes et al., 2012), mercury (Bernaus et al., 2006; Davis et al., 1997; Hojdová et al., 2009) and arsenic (Ehlert et al., 2018; Nejeschlebová et al., 2015). As a result, monitoring programs which traditionally rely on the bulk measurement of total metal concentrations without distinguishing the mineral phases present may not be a true indicator of the potential impact of metal(oid) contamination on human populations and the environment.

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The only way to accurately identify the diverse mineral phases present in APM is by single-particle analysis. Although scanning electron microscopy and energy dispersive X-ray spectrometry (SEM-EDS) has been widely used for the physico-chemical characterisation of APM, and can provide useful information on morphology and elemental composition, the traditional method of manual data analysis can be time consuming and subject to operator bias. Automated mineralogy systems, such as the Mineral Liberation Analyzer (MLA), are of increasing importance in particulate research due to their ability to rapidly collect quantitative data on size, chemical composition and mineral distributions, allowing for precise information on individual particles (Elmes et al., 2020). Particles with an average diameter as small as 1 µm can be detected and measured with an analytical throughput of over 10,000 particles per hour, generating data on particle size, morphology and mineralogy. As manganese is intimately associated with iron, there is the potential for chronic inhalation exposure to manganese for populations living near large scale iron ore mining operations. The aim of this study is to identify and characterise the manganese-bearing mineral phases in APM near a major iron-ore mining operation to illustrate the potential of the MLA to be a potent tool for the monitoring of potentially toxic elements in atmospheric emissions.

6.2.0 Materials and Methods

6.2.1 Sampling Locations

The Quadrilátero Ferrífero (QF) in the state of Minas Gerais, Brazil, is a mountainous region, 650-1500 metres above sea level and is one of the largest iron ore producing areas in the world (Klein and Ladeira, 2000). The city of Congonhas, which was selected for this study, lies in the far southwest corner of the QF, approximately 65km south of the regional capital Belo Horizonte, and is surrounded by five major open pit mines, with estimates of approximately 2.5 tonnes of geogenic particulates emitted hourly and 120 tonnes removed from the streets monthly (Carvalho, 2013).

Conghonas has a distinct wet (November-February) and dry season (June- September). Although the regional prevailing winds are predominantly from the east-

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northeast, the Sierra da Moeda mountain range deflects its direction towards the city in the southeast, with average monthly wind speeds ranging from 3 m/s during January to 3.5 m/s during August (Andrade et al., 2016).

Figure 6.1 Location of Congonhas and the five sampling locations: Plataforma (PLA), Casa de Pedra(CDP), Pires (PIR), Basilica (BAS) and Retiro (RET). Background maps from Google Earth™

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Particulates were collected during the wet season (January) and the dry season (August) from five sampling stations within and around Congonhas city (Fig. 6.1). Sampling locations were chosen either for their proximity to the mine site (Casa de Pedra (CDP)) and to the rail line servicing the mines (Plataforma (PLA) and Pires (PIR)). Basilica (BAS) is located within the city of Congonhas, approximately 6km downwind of the mine-site. A site to the north, within the same geological setting was selected at Retiro (RET). Although Retiro lies outside the influence of the Casa de Pedra iron ore operation, acitve and historic iron-ore and manganese oxide mines are situated in the vicinity, with the potential for fugitive emissions from waste piles and unreclaimed soils.

6.2.2 Sample Collection

Sample collection and preparation techniques were based on the methodology developed by Elmes et al. (2020). Although only total suspended particulates (TSP) were collected for this study, the technique is applicable to any low- or medium-volume sampler. TSP was collected using a portable, battery-operated SKC ‘AirChek 52’ low-volume pump (SKC item 224-52; flow rate of 2 L min-1) fitted with a personal IOM (Institute of Occupational Medicine) sampler for respirable dust (SKC item 225-70A) and deployed for 6 hours. Particulates were collected on polycarbonate filters (0.8 µm x 25mm, SKC item 225- 1601). For SEM/MLA analysis filters were mounted directly onto an aluminium stub with double-sided carbon tape and coated with a conductive carbon film.

6.2.3 SEM/MLA Operating Conditions

6.2.4 Formulation of the mineral library

MLA analysis relies on X-ray spectra matching to known spectra from a reference library. Each mineral phase is typically characterised by multiple spectra which incorporate

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variable X-ray peak intensities (Elmes et al., 2020). For this study, the X-ray matching tolerance was configured for 85%.

During the compilation of the mineral library, regional soil and rock samples and airborne particles were analysed by MLA and independently verified by XRD. Fourteen samples from the Congonhas area were analysed on a Philips PANalyticalX'Pert-APD system with a PW 3710/31 controller, PW 1830/40 generator and PW 3020/00 goniometer, with Cu graphite monochromatised radiation, a 1 second step speed, 0.06° sampling step and 4-90° 2θ range. Peak recognition and mineral identification for all analyses were performed using the PDF-2 database (ICDD, 2003).

6.3 Results and Discussion

6.3.1 Mn-bearing phases in APM

As manganese occurs naturally in a variety of oxidation states, multivalent compositions are common, even within a single mineral. This, combined with the similarity of crystal structures for many of the Mn oxide minerals, makes the identification of individual manganese oxide mineral phases by SEM-EDS difficult without supplementing it with techniques such as infrared spectroscopy and electron microprobe analysis. As a

4+ result, for this study the different oxide mineral phases, most likely pyrolusite (Mn O2),

2+ 3+ 2+ hausmannite (Mn Mn 2O4) and manganite (Mn O(OH)), are referred collectively to as Mn oxides.

January August 150 150

100 PIR 100 CDP 50 RET 50 BAS 0 PLA 0 Paritcle numbers

Figure 6.2 Particle numbers of manganese-bearing phases detected in sampled APM.RET-Retiro, PLA- plataforma, BAS- Basilica, PIR-Pires, CDP- Casa de Pedra.

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The most common Mn-bearing mineral phase observed, apart from Mn oxide, was

2+ jacobsite (Mn Fe2O4). Other Mn-bearing phases interpreted to be spessartine (Mn2+3Al 2(SiO4)3 ),

2+ 4+ 3+ rhodonite (Mn SiO3), romanechite ((Ba,H2O)2(Mn ,Mn )5O10) and Al-rich manganese oxide

(AlMn2+O) were also observed (Fig.6.2).

The high grade iron ore deposit at Congonhas is hosted in a deeply weathered dolomitic iron formation, with alteration reaching depths of 400-500 metres (Silveira et al., 2018). This lateritic weathering profile is characterised by the leaching of silica and carbonate minerals and the increased oxidation of manganese phases (Melfio et al., 1988). Supergene Fe- and Mn-bearing (hyd) oxides are the dominant mineral phases formed during weathering of the dolomitic protore (Carmo and Vasconcelos, 2004; Spier et al., 2018; Spier et al., 2006; Vasconcelos and Carmo, 2018), which explains the dominance of Mn-oxides and jacobsite in our analyses. Aluminium enrichment has been observed in minor amounts at the contact between Mn oxides and the hosting iron ore(Spier et al., 2006). Thus, it is likely that Al-rich Mn-oxide in our samples were formed together with the Fe and Mn-(hyd) oxides.

Although the protores are carbonatic, their main carbonate minerals are dolomite and ankerite (Nogueira et al., 2019; Spier et al., 2007). In addition, the rocks mined at Casa de Pedra are strongly weathered and as a result little of the primary Mn-bearing minerals, such as rhodonite and spessartite, were detected.

Although the relative proportions of Mn phases typically contributed less than 1 wt% of the TSP, this was not a true indication of the particle numbers present, which could be appreciable. For example, during January manganese phases collectively contributed approximately 0.9 wt% of the TSP at Retiro (RET), which was comprised of 43 individual particles, whereas during August 0.12 wt% of the TSP represented 230 individual particles (Fig. 6.3).

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January August Particle 300 1.5 300 number 0.8 Weight % 250 250 0.6 200 1.0 200 150 150 0.4 100 0.5 100 Weight % 0.2

Particle number 50 50 0 0.0 0 0 RET PLA BAS PIR CDP RET PLA BAS PIR CDP Sampling location Sampling location

Figure 6.3 Relative proportion of manganese particles in the sampled particulates (weight percentage) and particle number of collective manganese-bearing phases. RET-Retiro, PLA-platafor ma, BAS- Basilica, PIR-Pires, CDP- Casa de Pedra.

Individual manganese particles were crystalline, irregular and angular to sub-angular with smooth surfaces, suggesting a geological rather than anthropogenic source (Fig. 6.4).

a B

Figure 6.4 Raw S EM image and classified particle image of a) jacobsite and b) Mn oxide

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6.3.2 Assessment of the health risk related to exposure to atmospheric Mn-bearing particles

Whilst the physico-chemical characteristics responsible for the adverse health effects of particulate inhalation are incompletely understood, the behaviour of particles in the respiratory tract is largely determined by their aerodynamic diameter (dae), which is defined as the equivalent diameter of a sphere of unit density (1 g cm −3) that has the same settling velocity as the particle in question, regardless of its geometric size and shape (Hinds, 2012).

Coarse particles (dae2.5-10 µm) are primarily deposited in the tracheal and bronchial region, from where they are transported by mucociliary processes and typically swallowed, thus reaching the gastrointestinal tract whilst fine particles (dae<2.5 µm) can travel deeper into the alveolar region where they interact with lung fluids and have the potential to be transported directly into the blood stream (Hinds, 2012; Tsuda et al., 2013). In this study particle sizes represent the physical (or geometric) diameter (dp), calculated by the MLA software as an equivalent circle based on particle area, and do not equate to the aerodynamic diameter. As density is a key physical parameter in the determination of aerodynamic diameter, Mn-bearing phases will have a larger aerodynamic diameter than the reported physical diameter due to their high mineral densities (approximately 5 g cm−3)(Hinds, 2012).

jacobsite at selected sampling locations, with the coarse (dp2.5-10 µm) and super-coarse

(dp>10µm) particles typically contributing more than 70-80% and, as with the particle numbers, exhibiting little seasonal variation (Fig. 6.5).

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Mn Oxide 100 80 60 January August 40 20 0 Cumulative weight Cumulative weight % 2 1 2 1 16 8.1 5.7 4.1 2.9 8.1 5.7 4.1 2.9 11.4 1.45 0.73 0.52 1.45 0.73 0.52

Jacobsite 100 80 RET 60 PLA January BAS 40 August 20 0 Cumulative weight Cumulative weight % 2 1 2 1 8.1 5.7 4.1 2.9 8.1 5.7 4.1 2.9 11.4 1.45 0.73 0.52 11.4 1.45 0.73 0.52 Particle size (µm) Particle size (µm)

Figure 6.5 Geometric particle size distributions for Mn oxide and jacobsite at selected sampling sites. Shaded areas represent the coarse (dp2.5-10 µm)fraction.R ET -Retiro, PLA-platafor ma, BAS- Basilica.

From the predominance of particles in the coarse fraction, the risk of penetration of inhaled particles into the terminal alveoli is minimal, with most particles likely confined to the nasopharyngeal and upper tracheobronchial regions, thereafter ingested. Although research has highlighted the olfactory nerve in the nasal cavity as a significant route of exposure, these studies involved relatively soluble forms of manganese such as manganese

chloride (MnCl 2) (Lucchini et al., 2012), manganese phosphate (Mn3(PO4)2)(Dorman et al., 2002;

Normandin et al., 2002) and manganese sulphate (MnSO4)(Dorman et al., 2004).

Experiments using the more insoluble MnO2, however, suggest that coarser particles deposited in the nasal airways are not readily solubilised and transported via this route (Fechter et al., 2002).

As ingested Mn is regulated by a number of physiological systems such as the gastrointestinal tract, hepatobiliary system, transferrin and other blood transport proteins, only a small percentage is typically absorbed (Roth, 2006). The development of increased

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brain manganese concentrations from ingested Mn is therefore unusual unless exposure to extremely high levels or chronic ingestion overwhelms the regulatory systems.

From the results of this study, the Mn-bearing mineral phases observed in the atmosphere near the city of Congonhas are predominantly greater than 2.5 µm in diameter and show little seasonal variation in size distribution and particle numbers. As the aerodynamic diameter of the Mn-bearing phases will be greater than the physical diameter due to higher densities, the risk of penetration of inhaled particles deep into the lungs and subsequent solubilisation and bioaccessibility is suggested to be minimal.

6.4 Conclusions

Although adverse effects from exposure to different manganese species have been observed, most of the studies on toxicity differences arise from acute exposures to high doses. Most studies also incorporate highly soluble phases such as manganese chloride, manganese phosphate and manganese sulphate, and little is known about chronic exposure to ambient concentrations of insoluble phases, such as Mn Oxide and jacobsite. Mn-bearing mineral phases in APM nearby the city of Congonhas are predominantly greater than 2.5 µm in diameter and there is little seasonal variation in size distribution and particle numbers. The risk of penetration of inhaled Mn-bearing particles deep into the lungs and subsequent solubilisation and bioaccessibility, therefore, is suggested to be minimal.

This study successfully highlights the potential of the Mineral Liberation Analyser to identify and characterise potentially toxic elements in the atmosphere. With the ability to rapidly generate statistically significant data sets, the MLA could be an effective tool for the monitoring of geogenic emissions to safeguard environmental and human health.

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Chapter 7

Thesis Summary

7.1 Thesis Summary and Conclusions

The inimical effects of airborne particulates on the environment and human health are well documented. Although some particulates occur naturally, anthropogenic sources such as mining operations are substantial contributors to the atmospheric burden and for populations living near these operations exposure to airborne potentially toxic metalliferous dust is a serious concern.

Traditional monitoring programs typically measure particle size and mass concentrations. The toxicity of airborne particulate matter (APM), however, is related not only to particle size but also its shape and chemical composition and the only way to distinguish between the multiple phases present in APM is by single particle analysis. Although an array of instruments and techniques for single particle analysis are available and continue to be developed, as detailed in Chapter 2, to date few practical techniques exist that can rapidly and cost-effectively generate the physico-chemical data on atmospheric particulates that is required to enable realistic risk assessments and implement successful mitigation strategies. This thesis was designed with one overarching question in mind; could an automated mineralogy platform, such as the Mineral Liberation Analyzer (MLA), be one of these techniques?

Energy dispersive scanning electron microscopy (SEM-EDS) has been extensively used in APM research and can, in combination with gravimetric analysis, readily identify which size fractions and mineral compositions contribute to the total particulate mass. The traditionally manual data processing, however, is time-consuming and liable to operator bias, as discussed in Chapter 3, making standard SEM-EDS-based techniques impractical for regular monitoring purposes.

Automated mineralogy platforms such as the MLA have been used extensively within the mining industry to aid in the optimisation of ore beneficiation processes but could this

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instrumentation be applied to atmospheric particulates, with their small particle sizes and sample mass? Prior to testing this hypothesis, however, several considerations needed to be addressed. The first of these considerations was to determine the optimum sampling and sample preparation technique.

The high volume sampling typically used in monitoring programs is unsuited to single particle analysis due to the high particle loading and ensuing particle overlap. As a result, a low-volume sampler and a Sigma-2 passive sampler, along with different filter substrates, were investigated. The deterioration of the adhesive collection plate during analysis, coupled with the inherent sampling bias towards particles greater than 2.5µm and potential for measurement errors introduced into gravimetric calculations, made the Sigma-2 unsuited for MLA analysis and monitoring purposes. For a suitable sampling substrate, stability under the electron beam and sufficient BSE contrast between the particles and the substrate is necessary and out of the different filters examined, polycarbonate filters were deemed to be the most suited to MLA analysis.

The second major consideration lay with the EDS analysis and accuracy of mineral phase recognition. With an X-ray excitation volume that approximates the size of fine airborne particulates and the lack of a flat, polished surface, with the potential to create topographic effects influencing x-ray intensity, could the MLA generate reliable geochemical data?

As the success of MLA analysis is underpinned by the correct matching of acquired EDS spectra with those of known spectra in the reference library, especial care is required during its construction. For this study, 500, 000 particles from 30 regional soil and rock samples and more than 300, 000 airborne particles were analysed by MLA during the compilation of the spectral reference library. After construction, it was further validated with XRD analysis of regional soils and rocks, and the precision and accuracy of the MLA analysis evaluated by comparison with the reported mineral abundances (modal mineralogy) of two certified USGS reference materials, BHVO-2 (basalt) and GSP-2 (granite). The modal mineralogy data generated by the MLA indicated that the technique is able to identify and quantify mineral phases with a relatively high degree of precisions and accuracy, with relative standard deviations of less than 5% for BHVO-2 and less than 20% for most phases in GSP-2.

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Although the MLA can process 10, 000 particles within an hour and generate statistically relevant data, is it statistically reliable? Does the analysed section of filter accurately reflect the dispersal of particles across the entire filter surface and are the results reproducible? To investigate this, randomly selected areas of one filter were analysed separately to assess sampling homogeneity, along with a single area analysed by three different operators to evaluate the impact of operator-controlled parameters on repeat analyses. Both these experiments generated statistically similar results, with standard deviations typically below 10%, indicating that particulates are sampled homogenously across the filter and analysis of any location on the filter is representative of the sample as a whole. It also indicated that repeat analysis is largely free of operator bias.

After these main objectives were addressed, the follow on objectives of observing the seasonal variations of APM and the identification of major source contributions to the sampled particulates were investigated using the developed method.

Samples collected near the Casa de Pedra iron ore mine in Congonhas, Brazil, during the wet, dry and transitional periods exhibited a strong seasonality in particle size, with coarse and super-coarse particles more prevalent during the drier periods of May and August. The relative proportions of mineral phases, however, showed little seasonal variation, with iron oxides and clay minerals consistently the dominant phases observed. The high proportion of clay minerals, which are representative of surficial deposits, combined with soil-derived Al-rich Fe-oxides, indicate re-entrained soil, occurring either through natural or anthropogenic disturbances, is a significant source of Fe-oxides in the atmosphere. Anthropogenic sources of calcite, such as construction and non-exhaust traffic emissions, were inferred at most sampling locations due to relative proportions greater than those indicative of the local geology. A further anthropogenic contribution was observed at one location during one sampling period, with a large number of calcium phosphate particles detected, most likely derived from fertiliser.

The ability of the technique to identify potentially toxic elements and other target mineral phases in ambient air was also investigated. Mn-bearing mineral phases observed in the APM surrounding the Casa de Pedra mining operation were dominated by Mn-oxide

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phases and jacobsite. The particles were predominantly greater than 2.5 µm in physical diameter and show little seasonal variation in size distribution and particle numbers. As the aerodynamic diameter of Mn-bearing particles will be greater than the physical diameter due to their high mineral density, the risk of penetration of inhaled Mn-bearing particles deep into the lungs and subsequent solubilisation and bioaccessibility, therefore, is suggested to be minimal.

Although the results from this preliminary work have been positive the technique requires some refinements.

7.2 Suggestions for Future Work

As the low-volume sampler used in this study measured total suspended particulates

(TSP) only, the use of samplers fitted with size-selective inlets to generate PM2.5 and PM10 data, which is requisite for regulatory monitoring, needs to be explored. Also, although the polycarbonate filters are suitable for gravimetric analysis, the very low sample mass collected by low-volume sampling might create potential measurement errors during weighing. Future studies need to incorporate these in the sampling strategy to determine the potential of this technique for compliance monitoring, as well as single particle analysis. The suitability of medium volume samplers also needs to be ascertained as an alternative to low-volume samplers.

The technique as it stands is unable to distinguish between biogenic and anthropogenic carbonaceous material. To enable this distinction a detailed spectral library would need to be constructed, potentially using marker trace elements, such as As, Sn, Mo, Cr, V, Ni, Cu, and Pb (Genga et al., 2017). These, however, need to be present in amounts greater than the detection limit of the instrument (approximately 1 wt%). Repeat analysis is also problematic due to the destruction of particles under the electron beam. These limitations need to be explored to determine whether this technique is suited for the qualitative analysis of non-crystalline carbonaceous material.

The spectral library requires continued refinement, including the effect of different instrument parameters, such as accelerating voltage, beam current and spot size, on x-ray intensity particularly for phases with a strong cleavage, such as mica, to prevent

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misclassification and potential under-representation. A more detailed spectral library also needs to be constructed for phases with complex mineral chemistry, such as clays.

The results of this research have illustrated that the MLA has the ability to rapidly and cost-effectively generate statistically reliable data and has the potential to be an invaluable tool for the regular monitoring of mine-derived geogenic emissions and the detection of potentially toxic elements in the atmosphere.

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Appendix 1

Normalised EDS data, Paracatu

182

Table A1-1. Normalised EDS data, station 1, 12-14 December 2011

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

45.94 22.16 39.57 0.92 0.61 5.18 25.56 0.00 1.60 0.00 0.00 3.60 0.80 34.17 28.46 36.83 0.00 0.00 4.66 26.56 0.20 2.31 0.15 0.21 0.60 0.00 30.88 21.02 38.70 0.00 0.00 0.73 38.35 0.25 0.26 0.00 0.26 0.43 0.00 25.09 35.33 29.53 0.00 0.47 11.13 16.56 0.00 5.15 0.21 0.35 1.28 0.00 24.47 31.72 31.02 0.00 0.45 13.14 15.09 0.25 6.05 0.18 0.24 1.86 0.00 21.66 30.88 32.50 0.00 0.58 5.64 27.10 0.00 2.34 0.00 0.00 0.96 0.00 20.42 35.92 28.95 0.00 0.43 11.93 14.35 0.00 5.73 0.00 0.00 2.69 0.00 18.16 34.47 31.52 0.00 0.00 8.24 20.78 0.00 3.73 0.00 0.23 1.04 0.00 17.88 39.45 28.91 0.00 0.51 11.17 13.57 0.00 5.29 0.00 0.00 1.11 0.00 17.82 31.79 34.78 0.00 0.65 11.97 14.32 0.00 5.34 0.00 0.00 1.15 0.00 16.8 41.84 33.89 0.00 0.00 7.15 13.00 0.00 2.53 0.00 0.00 0.86 0.72 16.62 43.27 29.37 0.00 0.31 10.90 5.98 0.00 0.99 4.32 0.00 4.85 0.00 15.55 34.46 29.41 0.00 0.00 8.85 10.14 0.00 0.47 0.00 0.00 14.74 1.93 15.5 35.97 35.28 0.00 0.55 10.29 11.96 0.00 4.42 0.15 0.16 1.20 0.00 15 37.56 31.42 0.00 0.00 1.35 27.64 0.00 0.26 0.18 0.28 1.32 0.00 13.79 38.58 30.99 0.00 0.00 10.68 12.77 0.00 5.12 0.00 0.20 1.65 0.00 13.67 34.53 30.19 0.00 0.72 12.27 13.99 0.17 5.29 0.17 0.25 1.42 0.99 13.56 43.08 29.66 0.00 0.42 9.42 12.03 0.00 3.98 0.00 0.00 1.40 0.00 13.22 40.89 28.31 0.24 0.33 4.11 22.15 0.00 0.81 0.33 0.24 1.99 0.59 13.17 52.91 28.86 0.00 0.32 6.26 7.24 0.00 3.11 0.00 0.00 0.72 0.56 12.81 36.14 30.67 0.00 0.50 11.86 13.80 0.00 5.24 0.00 0.20 1.60 0.00 12.8 42.29 28.79 0.00 0.48 2.90 21.36 0.00 0.41 0.88 0.00 2.89 0.00 12.79 46.14 8.63 0.00 0.00 0.00 0.00 24.33 0.00 0.00 0.00 20.90 0.00 12.19 42.22 28.53 0.26 0.24 11.56 10.41 0.00 0.19 0.00 0.00 6.59 0.00 11.77 39.25 36.06 0.00 0.00 0.43 23.63 0.00 0.15 0.00 0.28 0.20 0.00 11.34 48.07 21.55 0.00 0.00 10.37 12.28 0.00 5.05 0.22 0.20 1.59 0.67 11.13 44.60 27.70 0.00 0.00 1.21 26.05 0.00 0.00 0.00 0.00 0.43 0.00 11.08 45.26 29.91 0.00 0.00 0.64 23.01 0.17 0.24 0.16 0.24 0.37 0.00 183

Table A1-1 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

10.82 41.08 32.89 0.00 0.29 14.55 8.06 0.00 0.19 0.00 0.00 2.94 0.00 10.51 45.08 29.76 0.23 0.19 0.80 22.94 0.00 0.16 0.19 0.18 0.46 0.00 10.36 46.71 25.48 0.00 0.00 1.72 24.84 0.00 0.63 0.00 0.00 0.63 0.00 10.29 46.57 27.06 0.00 0.00 12.17 11.78 0.00 0.51 0.26 0.00 1.65 0.00 9.85 46.30 30.63 0.00 0.23 1.92 19.26 0.17 0.56 0.00 0.19 0.73 0.00 9.56 46.05 26.52 0.00 0.00 0.99 23.65 0.00 0.27 0.40 0.00 2.13 0.00 9.49 43.85 29.85 0.00 0.19 0.49 24.90 0.00 0.00 0.00 0.16 0.56 0.00 8.94 59.75 23.99 0.00 0.00 5.81 6.46 0.00 2.70 0.12 0.27 0.90 0.00 8.35 34.10 30.68 0.27 0.40 2.99 29.19 0.20 1.33 0.00 0.00 0.83 0.00 8.3 52.52 23.74 0.00 0.00 2.36 19.38 0.00 1.14 0.17 0.30 0.38 0.00 8.09 48.66 25.01 0.00 0.52 9.51 10.33 0.00 3.56 0.00 0.00 2.40 0.00 7.43 55.81 23.54 0.00 0.00 2.49 16.04 0.00 1.07 0.00 0.00 0.48 0.58 7.27 51.15 24.96 0.00 0.35 8.16 9.93 0.00 3.90 0.22 0.23 1.09 0.00 6.93 50.04 20.39 0.00 1.02 8.21 12.86 0.00 4.89 0.00 0.00 2.59 0.00 5.83 61.51 20.19 0.00 0.00 1.07 0.76 0.00 0.00 15.35 0.00 1.11 0.00 4.73 66.69 25.03 0.00 0.00 5.99 1.31 0.00 0.00 0.00 0.00 0.98 0.00 2.91 54.43 24.14 0.00 0.00 0.84 19.55 0.00 0.21 0.00 0.21 0.61 0.00 2.52 62.80 14.82 0.00 0.16 0.42 21.13 0.00 0.00 0.00 0.12 0.55 0.00 1.94 68.67 10.60 0.00 0.00 0.28 20.44 0.00 0.00 0.00 0.00 0.00 0.00 1.5 83.86 16.14 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.14 66.61 14.96 0.00 0.00 6.66 8.09 0.00 3.11 0.00 0.00 0.56 0.00 1.09 64.46 20.26 0.00 0.00 4.02 8.75 0.00 0.60 0.00 0.00 1.91 0.00

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Table A1-2. Normalised EDS data, station 1, 13-20 September 2012

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

31.67 25.21 35.81 0.00 0.54 13.95 16.05 0.00 6.20 0.00 0.00 1.57 0.66 23.92 13.76 36.58 0.00 0.53 17.64 20.90 0.00 8.62 0.00 0.00 1.96 0.00 23.69 30.29 29.71 0.00 0.00 0.63 38.29 0.00 0.00 0.18 0.25 0.65 0.00 22.19 26.39 36.42 0.00 0.51 13.60 16.20 0.00 5.54 0.00 0.00 1.34 0.00 20.3 30.68 35.00 0.00 0.49 13.20 14.44 0.00 2.02 0.00 0.00 4.18 0.00 19.36 63.45 24.06 0.00 0.00 5.90 5.68 0.00 0.90 0.00 0.00 0.00 0.00 18.88 24.31 37.56 0.00 0.00 0.75 36.23 0.00 0.25 0.00 0.22 0.68 0.00 17.87 35.19 31.56 0.00 0.00 11.82 14.10 0.00 5.37 0.00 0.00 1.10 0.85 17.37 27.53 35.18 0.00 0.66 2.62 30.18 0.46 1.26 0.27 0.42 1.41 0.00 15.92 42.26 27.12 0.00 0.70 10.35 12.83 0.60 4.67 0.00 0.00 1.48 0.00 15.51 33.90 30.32 0.00 0.00 0.82 33.86 0.00 0.36 0.23 0.00 0.51 0.00 14.89 44.97 25.61 0.00 0.42 10.68 12.02 0.00 4.86 0.14 0.22 1.08 0.00 14.47 39.08 27.23 0.00 0.33 9.55 18.86 0.00 4.08 0.00 0.00 0.87 0.00 14.23 30.68 31.24 0.34 0.70 13.30 16.17 0.00 6.21 0.23 0.00 1.13 0.00 14.09 42.10 27.48 0.00 0.35 7.32 18.08 0.00 3.48 0.00 0.00 1.19 0.00 13.31 40.66 24.70 0.00 0.00 2.84 29.06 0.00 0.55 0.14 0.23 1.82 0.00 12.07 45.75 31.71 0.00 0.51 8.06 9.13 0.00 3.36 0.00 0.00 1.49 0.00 12.05 39.79 28.91 0.00 0.00 0.97 28.99 0.00 0.34 0.20 0.26 0.54 0.00 12.01 37.88 35.05 0.00 1.05 7.47 9.98 1.20 1.33 1.68 0.00 3.77 0.58 12.01 44.70 26.82 0.00 0.77 9.10 11.78 0.00 3.87 0.00 0.00 2.35 0.62 11.99 24.67 39.47 0.00 0.64 13.26 15.11 0.00 5.69 0.00 0.00 1.17 0.00 11.97 36.95 35.89 0.00 0.00 10.10 11.21 0.00 4.54 0.14 0.00 1.17 0.00 11.95 43.59 26.57 0.00 0.00 0.68 0.58 0.00 0.00 27.10 0.00 0.00 1.48 11.62 45.03 29.60 0.00 0.33 9.68 10.63 0.00 3.71 0.00 0.00 1.01 0.00 11.23 49.15 30.05 0.00 0.46 7.72 8.90 0.00 2.17 0.00 0.00 1.55 0.00 11.22 40.73 21.59 0.00 0.00 4.96 2.45 0.00 0.00 0.39 0.35 29.53 0.00 10.67 29.35 34.85 0.00 0.49 13.10 15.27 0.00 5.65 0.00 0.00 1.29 0.00

185

Table A1-2 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

10.55 39.29 28.71 0.00 0.50 11.66 13.31 0.00 4.78 0.19 0.24 1.32 0.00 10.44 41.14 25.18 0.00 0.45 5.62 5.26 0.00 0.84 0.00 0.00 21.52 0.00 10.09 45.09 24.73 0.00 0.78 9.47 13.60 0.34 2.26 0.00 0.00 3.74 0.00 9.97 48.49 22.94 0.00 0.34 9.92 11.60 0.00 4.78 0.00 0.00 1.93 0.00 9.58 45.78 27.87 0.00 0.00 0.92 24.70 0.00 0.00 0.00 0.24 0.49 0.00 9.4 48.59 27.14 0.00 0.00 8.54 9.80 0.00 4.06 0.00 0.00 1.88 0.00 9.23 45.16 28.84 0.00 0.42 7.94 8.63 0.00 3.51 0.00 0.00 4.31 1.18 9.2 80.98 17.96 0.00 0.00 0.00 1.06 0.00 0.00 0.00 0.00 0.00 0.00 9.11 45.63 27.32 0.00 0.00 0.60 25.05 0.00 0.28 0.00 0.27 0.85 0.00 9.08 44.44 25.52 0.00 0.44 10.72 12.22 0.16 4.94 0.00 0.24 1.31 0.00 8.62 41.73 25.39 2.25 0.00 8.60 16.55 0.00 0.92 2.69 0.19 0.97 0.70 8.61 54.58 19.27 0.00 0.39 8.82 10.66 0.00 4.15 0.00 0.00 2.13 0.00 8.61 41.29 31.57 5.45 1.27 0.00 17.32 0.00 0.00 3.11 0.00 0.00 0.00 8.49 61.04 22.37 0.00 0.00 7.45 7.80 0.00 0.00 0.32 0.13 0.89 0.00 8.33 48.84 25.96 0.00 0.56 9.35 10.22 0.21 3.87 0.00 0.00 1.01 0.00 8.24 52.99 19.65 0.00 0.34 9.38 10.59 0.00 2.00 0.00 0.00 4.13 0.92 7.9 49.46 23.93 0.00 0.37 12.75 6.68 0.00 1.19 0.00 0.00 5.63 0.00 7.81 52.37 21.34 0.00 0.00 7.73 6.90 0.00 0.37 0.18 0.36 10.74 0.00 7.73 45.76 26.11 0.00 0.65 11.15 7.09 0.00 0.63 0.00 0.00 8.59 0.00 7.61 48.01 24.89 0.00 0.96 6.97 8.91 0.57 1.24 4.59 0.00 3.84 0.00 7.51 41.31 32.87 0.00 1.02 7.25 6.08 0.00 0.78 1.66 0.19 8.83 0.00 7.45 44.59 26.63 0.00 0.45 0.36 0.56 0.00 0.00 27.40 0.00 0.00 0.00 7.43 53.31 28.37 0.00 0.00 6.35 7.17 0.00 2.68 0.14 0.22 1.76 0.00 7.17 50.06 22.16 0.00 0.00 1.79 25.01 0.00 0.58 0.00 0.00 0.40 0.00 7.06 56.97 23.57 0.00 0.00 0.41 18.71 0.00 0.00 0.00 0.00 0.34 0.00 7.03 50.29 16.44 0.00 0.44 12.19 13.07 0.00 5.10 0.30 0.25 1.25 0.67 7.01 35.98 37.91 0.00 0.00 0.94 23.73 0.00 0.00 0.00 0.20 0.43 0.81

186

Table A1-2 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

6.92 43.63 31.40 0.00 0.00 9.31 10.49 0.00 3.47 0.00 0.00 1.70 0.00 6.92 51.84 29.76 0.00 0.23 1.68 15.10 0.00 0.47 0.00 0.00 0.35 0.57 6.87 81.52 16.69 0.00 0.00 0.00 1.29 0.19 0.00 0.30 0.00 0.00 0.00 6.69 82.61 16.72 0.28 0.00 0.17 0.11 0.11 0.00 0.00 0.00 0.00 0.00 6.56 68.13 16.35 0.00 0.00 0.37 14.54 0.00 0.00 0.00 0.15 0.46 0.00 6.55 55.51 29.45 0.00 0.00 4.00 4.35 0.24 1.39 0.53 0.14 4.40 0.00 6.47 87.64 8.55 0.00 0.00 0.00 0.00 0.00 3.80 0.00 0.00 0.00 0.00 6.43 82.67 14.03 0.00 0.00 0.27 1.51 0.24 0.22 0.77 0.15 0.14 0.00 6.31 44.11 28.10 0.00 0.00 1.81 2.05 0.00 0.00 23.92 0.00 0.00 0.00 6.23 56.12 20.65 0.00 0.00 1.30 0.74 0.00 0.00 0.00 0.00 21.20 0.00 6.23 36.01 36.70 1.04 1.91 10.15 10.18 0.00 0.47 0.00 0.00 3.54 0.00 6.14 81.84 18.16 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.99 51.79 27.62 0.00 0.00 3.37 12.22 0.00 0.19 0.00 0.52 4.29 0.00 5.95 54.52 24.96 0.00 0.00 0.00 0.00 8.40 0.00 12.12 0.00 0.00 0.00 5.93 62.20 10.96 0.00 0.33 4.94 5.14 0.00 0.78 0.00 0.00 15.65 0.00 5.9 53.95 28.77 0.00 0.00 6.64 6.78 0.00 2.41 0.27 0.14 1.04 0.00 5.86 80.14 17.32 0.00 0.00 0.00 1.41 0.00 0.00 0.60 0.25 0.28 0.00 5.82 35.52 30.20 0.00 0.00 6.07 23.99 0.00 3.28 0.00 0.00 0.93 0.00 5.68 66.51 24.34 0.00 0.00 4.01 2.97 0.00 0.27 0.31 0.21 1.38 0.00 5.57 67.11 23.00 0.00 0.00 3.22 3.72 0.00 1.45 0.61 0.12 0.77 0.00 5.55 51.33 26.42 0.00 0.70 1.39 1.14 0.00 0.00 18.30 0.00 0.72 0.00 5.51 58.77 23.43 0.00 0.36 6.23 6.52 0.00 2.05 0.29 0.00 1.46 0.88 5.39 56.20 23.41 0.00 0.28 7.32 8.22 0.00 3.41 0.00 0.13 1.02 0.00 5.31 55.67 13.28 0.00 0.00 3.46 3.98 0.00 0.49 0.00 0.00 23.11 0.00 5.16 65.06 18.29 0.00 0.00 0.33 14.95 0.00 0.00 0.18 0.27 0.31 0.61 5.15 59.92 18.98 0.00 0.00 7.28 6.72 0.00 0.22 0.20 0.39 6.28 0.00 5.13 56.02 23.34 0.00 0.28 0.97 18.63 0.00 0.29 0.15 0.14 0.19 0.00

187

Table A1-2 cont. AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

5.08 63.90 23.19 0.00 0.23 6.50 3.27 0.00 0.00 0.00 0.00 2.91 0.00 5.03 50.86 21.06 0.00 0.00 8.65 9.05 0.00 1.08 0.00 0.00 8.71 0.58 4.98 40.14 26.55 0.95 1.23 3.45 4.77 0.37 0.59 20.45 0.00 1.49 0.00 4.97 43.58 32.19 0.58 0.96 9.26 9.44 0.00 1.52 0.00 0.00 2.47 0.00 4.93 59.32 21.93 0.00 0.00 1.80 15.94 0.00 0.48 0.00 0.00 0.52 0.00 4.68 76.79 18.58 0.00 0.00 1.70 1.93 0.00 0.62 0.00 0.00 0.36 0.00 4.68 54.28 17.53 0.00 0.00 3.44 2.23 0.00 0.25 0.00 0.00 22.27 0.00 4.62 63.63 19.83 0.00 0.00 5.54 5.62 0.00 0.35 0.00 0.00 5.03 0.00 4.62 42.10 25.81 0.00 0.94 10.08 13.92 0.00 4.61 0.00 0.00 2.53 0.00 4.61 60.27 23.67 0.00 0.00 7.15 5.76 0.00 0.58 0.00 0.00 2.57 0.00 4.59 55.54 17.34 0.00 0.28 8.58 8.70 0.00 3.25 0.15 0.31 5.84 0.00 4.55 51.92 27.22 0.00 0.00 11.73 3.87 0.00 0.00 0.53 0.00 4.73 0.00 4.54 67.81 22.84 0.00 0.00 3.34 3.58 0.00 1.53 0.27 0.11 0.50 0.00 4.53 61.28 23.55 0.00 0.35 5.63 5.66 0.00 2.03 0.00 0.00 0.99 0.50 4.52 42.10 29.05 0.44 0.59 1.03 2.51 0.00 0.00 23.65 0.00 0.64 0.00 4.52 53.10 22.45 0.00 0.00 1.62 21.51 0.00 0.52 0.00 0.00 0.80 0.00 4.48 81.07 17.80 0.00 0.00 0.00 1.13 0.00 0.00 0.00 0.00 0.00 0.00 4.48 59.19 18.32 0.00 0.00 8.97 9.55 0.00 3.29 0.00 0.00 0.69 0.00 4.42 65.83 8.39 0.00 0.00 0.38 0.43 12.76 0.00 0.00 0.00 12.23 0.00 4.39 62.15 14.27 0.00 0.38 8.51 9.55 0.00 4.16 0.00 0.00 0.98 0.00 4.36 80.67 16.70 0.00 0.00 0.25 0.24 0.79 0.00 1.11 0.00 0.23 0.00 4.34 63.40 15.59 0.00 0.23 8.13 7.37 0.00 1.60 0.00 0.00 2.75 0.92 4.3 52.33 22.18 0.00 0.00 0.00 0.39 0.00 0.00 24.79 0.00 0.30 0.00 4.27 60.19 21.52 0.00 6.31 0.40 0.69 0.00 0.00 10.22 0.23 0.43 0.00 4.25 73.18 19.10 0.00 0.35 0.59 1.56 0.14 0.18 4.28 0.16 0.46 0.00 4.25 56.64 20.05 0.00 0.00 0.68 21.61 0.15 0.29 0.00 0.24 0.33 0.00 4.21 59.85 18.74 0.00 0.00 3.23 16.39 0.00 0.22 0.28 0.18 1.11 0.00 4.2 40.65 39.49 0.00 4.17 0.95 1.17 3.45 0.00 9.75 0.00 0.37 0.00 188

Table A1-2 cont. AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

4.2 67.75 23.33 0.00 0.27 3.29 2.94 0.17 0.38 0.18 0.00 1.69 0.00 4.07 48.12 25.97 0.00 0.34 9.70 10.99 0.00 1.01 0.00 0.00 2.45 1.41 4.04 56.58 24.50 0.00 6.33 0.80 10.17 0.00 0.19 0.37 0.14 0.92 0.00 3.99 62.16 21.76 0.00 0.36 6.23 6.55 0.00 1.43 0.00 0.00 1.51 0.00 3.97 71.05 21.72 0.00 0.00 3.06 3.26 0.00 0.00 0.00 0.00 0.30 0.61 3.93 64.03 16.12 0.00 0.00 9.12 9.31 0.29 0.00 0.30 0.00 0.83 0.00 3.88 53.31 19.18 0.00 0.00 9.26 8.67 0.00 2.23 0.42 0.00 6.30 0.63 3.87 52.27 28.09 0.00 0.00 8.28 5.38 0.00 0.42 0.00 0.00 4.70 0.86 3.81 61.40 17.05 0.00 0.00 8.58 5.27 0.20 0.67 0.34 0.19 6.32 0.00 3.81 60.14 18.94 0.00 0.40 0.85 18.35 0.00 0.18 0.00 0.00 1.13 0.00 3.77 68.30 13.51 0.00 0.27 6.28 7.38 0.00 2.62 0.00 0.00 1.08 0.56 3.77 62.35 19.74 0.00 0.00 3.05 13.44 0.00 0.32 0.00 0.00 1.10 0.00 3.65 67.56 21.88 0.00 0.28 3.54 3.21 0.21 0.58 0.28 0.00 2.47 0.00 3.65 67.99 13.91 0.00 0.00 1.19 16.03 0.00 0.00 0.00 0.00 0.88 0.00 3.56 68.14 15.57 0.00 0.00 6.76 5.51 0.00 1.39 0.18 0.13 2.32 0.00 3.52 72.51 16.68 0.00 0.00 4.58 2.96 0.00 0.24 0.11 0.28 2.65 0.00 3.5 68.47 19.31 0.00 0.00 4.23 2.32 0.00 0.16 3.39 0.23 1.88 0.00 3.47 64.77 19.43 0.00 4.41 0.57 2.64 0.00 0.00 8.18 0.00 0.00 0.00 3.47 45.63 23.09 0.00 0.22 1.81 27.96 0.00 0.69 0.00 0.18 0.43 0.00 3.29 62.74 14.53 0.00 0.54 6.75 9.88 0.19 3.35 0.18 0.22 1.62 0.00 3.21 51.57 23.46 0.00 5.97 2.33 1.66 0.00 0.00 10.83 0.00 4.18 0.00 3.21 78.09 16.79 0.00 0.00 1.96 2.19 0.00 0.13 0.19 0.30 0.35 0.00 3.18 48.08 23.06 0.00 0.74 1.80 2.97 0.00 0.39 20.19 0.00 1.60 1.17 3.14 61.83 15.55 0.00 0.00 0.78 20.67 0.00 0.22 0.00 0.18 0.77 0.00 3.09 62.91 17.45 0.00 0.00 0.51 18.19 0.00 0.00 0.00 0.12 0.33 0.49 3 69.70 13.35 0.00 0.29 2.80 3.73 0.00 0.55 0.00 0.00 9.58 0.00 2.99 66.89 18.40 0.00 0.00 3.91 9.03 0.26 1.51 0.00 0.00 0.00 0.00 2.95 72.01 21.28 0.00 0.00 2.45 2.56 0.00 0.87 0.00 0.19 0.64 0.00 189

Table A1-2 cont. AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

2.91 63.37 19.45 0.00 0.40 3.05 3.17 0.00 0.42 7.80 0.16 2.17 0.00 2.9 75.60 17.35 0.00 0.00 3.97 2.41 0.00 0.00 0.00 0.00 0.68 0.00 2.84 84.98 14.70 0.00 0.00 0.18 0.14 0.00 0.00 0.00 0.00 0.00 0.00 2.84 75.98 12.47 0.00 0.00 0.43 10.24 0.00 0.16 0.13 0.25 0.33 0.00 2.8 81.96 16.09 0.00 0.00 0.00 1.01 0.00 0.00 0.24 0.00 0.00 0.69 2.78 81.76 17.68 0.00 0.00 0.26 0.29 0.00 0.00 0.00 0.00 0.00 0.00 2.76 50.58 18.12 0.00 0.46 6.88 5.66 0.00 0.00 2.40 0.00 14.38 1.52 2.68 61.68 15.50 0.00 0.39 8.07 9.51 0.00 2.19 0.00 0.00 2.66 0.00 2.64 63.74 18.46 0.00 0.89 2.01 11.80 0.00 0.32 1.44 0.16 1.18 0.00 2.62 56.05 16.64 0.00 0.52 9.02 12.15 0.00 4.36 0.00 0.17 1.09 0.00 2.6 61.06 14.30 0.00 0.52 6.58 6.38 0.00 1.19 1.03 0.31 8.62 0.00 2.58 75.51 22.22 0.00 0.00 0.72 0.57 0.00 0.00 0.32 0.00 0.00 0.64 2.56 67.88 18.35 0.00 0.00 2.04 10.23 0.00 0.40 0.19 0.00 0.91 0.00 2.27 76.42 18.60 0.00 0.89 0.00 0.00 1.00 0.00 3.08 0.00 0.00 0.00 2.27 84.26 12.23 0.00 0.00 0.00 1.82 0.80 0.00 0.89 0.00 0.00 0.00 2.17 82.29 15.55 0.00 0.00 0.00 1.51 0.23 0.00 0.42 0.00 0.00 0.00 2.15 81.91 18.09 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.05 79.69 18.60 0.00 0.00 0.60 0.51 0.00 0.00 0.00 0.00 0.59 0.00 2.02 79.94 17.76 0.40 0.00 0.00 1.27 0.00 0.00 0.00 0.00 0.00 0.63 1.97 76.75 19.38 0.00 0.00 1.57 1.46 0.00 0.42 0.00 0.00 0.42 0.00 1.94 78.08 16.34 0.00 0.00 0.27 4.84 0.00 0.00 0.00 0.21 0.26 0.00 1.88 82.95 16.65 0.00 0.00 0.21 0.19 0.00 0.00 0.00 0.00 0.00 0.00 1.88 79.57 18.13 0.00 0.00 0.60 0.62 0.00 0.27 0.18 0.27 0.35 0.00 1.85 77.41 18.65 0.29 0.00 0.00 0.00 1.17 0.00 1.69 0.00 0.15 0.63 1.85 79.87 19.24 0.00 0.00 0.41 0.48 0.00 0.00 0.00 0.00 0.00 0.00 1.85 78.45 20.10 0.00 0.00 0.00 1.20 0.00 0.00 0.24 0.00 0.00 0.00 1.7 81.75 17.20 0.00 0.00 0.00 1.04 0.00 0.00 0.00 0.00 0.00 0.00 1.7 82.26 15.55 0.00 0.00 0.00 1.72 0.00 0.00 0.47 0.00 0.00 0.00 190

Table A1-2 cont. AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.64 83.20 15.82 0.00 0.00 0.00 0.99 0.00 0.00 0.00 0.00 0.00 0.00 1.61 89.57 10.13 0.00 0.00 0.00 0.00 0.00 0.00 0.13 0.00 0.17 0.00 1.61 81.92 17.61 0.26 0.21 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.61 83.45 14.06 0.32 0.00 0.33 1.37 0.00 0.00 0.47 0.00 0.00 0.00 1.54 80.85 18.76 0.00 0.00 0.00 0.39 0.00 0.00 0.00 0.00 0.00 0.00 1.54 80.39 18.66 0.00 0.00 0.00 0.95 0.00 0.00 0.00 0.00 0.00 0.00 1.5 90.77 8.75 0.00 0.00 0.27 0.21 0.00 0.00 0.00 0.00 0.00 0.00 1.47 78.96 17.91 0.00 0.00 1.00 1.33 0.00 0.00 0.00 0.18 0.62 0.00 1.47 82.12 15.04 0.00 0.00 0.27 1.56 0.31 0.14 0.43 0.12 0.00 0.00 1.39 80.09 19.91 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.39 78.29 18.97 0.31 0.00 0.22 1.45 0.19 0.00 0.42 0.00 0.13 0.00 1.39 80.80 17.26 0.00 0.00 0.00 1.69 0.00 0.00 0.26 0.00 0.00 0.00 1.39 82.79 13.67 0.00 0.00 0.32 1.94 0.27 0.61 0.41 0.00 0.00 0.00 1.39 74.88 14.62 0.00 0.00 4.82 2.96 0.00 0.36 0.00 0.00 2.37 0.00 1.35 79.77 19.16 0.00 0.00 0.43 0.38 0.00 0.00 0.00 0.00 0.26 0.00 1.31 81.72 16.11 0.00 0.00 0.26 1.27 0.30 0.00 0.33 0.00 0.00 0.00 1.27 82.22 15.43 0.36 0.00 0.00 1.41 0.22 0.00 0.35 0.00 0.00 0.00 1.23 91.18 8.61 0.00 0.00 0.00 0.21 0.00 0.00 0.00 0.00 0.00 0.00 1.18 80.83 18.22 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.95 1.18 88.76 10.40 0.25 0.19 0.23 0.17 0.00 0.00 0.00 0.00 0.00 0.00 1.18 83.33 14.53 0.25 0.00 0.00 0.88 0.22 0.00 0.42 0.14 0.22 0.00 1.14 81.44 18.56 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.14 83.77 13.85 0.00 0.00 0.00 1.29 0.00 0.00 0.00 0.00 0.00 1.09 1.09 83.76 15.26 0.00 0.00 0.28 0.00 0.00 0.00 0.00 0.00 0.00 0.70 1.09 80.75 19.25 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.04 75.78 20.62 0.00 0.00 0.25 0.59 1.03 0.00 1.73 0.00 0.00 0.00 1.04 69.67 16.51 0.00 0.00 4.76 5.39 0.00 2.22 0.12 0.24 0.56 0.53 1.04 72.24 13.56 0.00 0.42 4.90 5.59 0.19 2.24 0.00 0.17 0.69 0.00 1.04 51.06 26.95 0.00 0.00 7.57 9.26 0.00 3.38 0.00 0.00 0.92 0.86 191

Table A1-3. Normalised EDS data, station 3, 2-14 December 2011.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

37.13 18.53 39.35 0.00 0.64 14.61 18.28 0.00 6.68 0.00 0.00 1.91 0.00 32.66 21.82 35.86 0.00 0.65 14.83 17.79 0.00 6.83 0.20 0.35 1.67 0.00 30.12 23.33 33.70 0.00 1.18 13.91 17.85 0.00 6.92 0.00 0.00 3.11 0.00 26.05 20.63 41.14 0.51 12.94 0.72 0.45 0.00 0.00 23.01 0.00 0.60 0.00 25.64 48.59 25.70 0.00 0.28 7.62 8.33 0.00 1.17 0.25 0.00 8.05 0.00 25.42 36.97 32.44 0.00 0.66 9.79 12.32 0.00 4.00 0.24 0.00 2.61 0.98 25.13 24.95 35.00 0.00 0.00 0.69 36.34 0.00 0.00 0.00 0.24 2.78 0.00 24.35 24.10 38.49 0.00 0.35 0.85 35.30 0.00 0.00 0.00 0.20 0.70 0.00 24.34 34.00 28.95 0.00 0.51 11.62 16.48 0.00 5.10 0.28 0.00 2.31 0.73 23.95 48.84 26.33 0.00 0.50 10.26 5.44 0.39 0.70 1.31 0.00 6.23 0.00 22.58 33.66 30.08 0.00 0.58 12.69 14.84 0.00 5.89 0.00 0.18 1.38 0.71 22.51 27.69 35.89 0.00 0.00 1.14 34.21 0.00 0.39 0.00 0.00 0.68 0.00 21.78 25.99 33.28 0.00 0.00 14.81 17.43 0.00 5.68 0.20 0.25 2.38 0.00 21.05 29.52 38.73 0.00 0.00 10.51 11.60 0.00 3.96 0.00 0.31 5.38 0.00 21.02 25.81 36.75 0.00 0.67 14.16 15.31 0.00 6.10 0.00 0.00 1.20 0.00 20.88 31.18 34.58 0.00 0.00 13.79 13.89 0.00 0.50 0.37 0.46 5.24 0.00 20.21 26.04 34.89 0.00 0.55 13.94 16.08 0.00 6.24 0.00 0.22 1.31 0.74 19.11 34.67 30.87 0.00 0.93 12.08 14.20 0.00 4.26 0.23 0.00 2.77 0.00 17.91 40.16 29.88 0.00 5.73 2.87 6.11 0.31 0.50 12.32 0.00 2.13 0.00 17.33 33.14 33.06 0.40 0.80 11.78 13.19 0.19 5.03 0.00 0.36 1.29 0.76 17.15 28.53 37.74 0.50 12.18 0.00 0.00 0.00 0.00 21.05 0.00 0.00 0.00 16.8 56.81 23.16 0.00 0.63 4.46 8.20 0.21 0.67 1.66 0.14 4.06 0.00 16.52 52.46 29.76 0.00 1.32 5.56 4.65 0.00 0.61 2.59 0.00 3.05 0.00 15.74 30.39 30.37 0.00 0.61 14.60 16.23 0.00 6.78 0.00 0.00 1.03 0.00 15.7 41.50 27.32 0.00 0.00 10.38 13.61 0.00 5.12 0.00 0.00 2.07 0.00 15.56 37.22 32.99 0.00 0.52 10.64 12.52 0.00 4.42 0.00 0.00 1.70 0.00 15.46 36.05 39.04 0.45 0.56 11.13 11.13 0.00 0.85 0.00 0.15 0.62 0.00 15.24 39.48 27.99 0.00 0.41 9.84 16.52 0.00 2.60 0.41 0.35 2.41 0.00 192

Table A1-3 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

15.24 42.11 28.81 0.00 0.00 1.52 26.38 0.00 0.00 0.00 0.19 0.99 0.00 15.2 39.87 31.46 0.51 9.50 0.57 0.45 0.23 0.00 15.62 0.00 0.33 1.45 15.14 30.35 33.08 0.85 0.98 1.99 1.45 0.60 0.51 28.12 0.52 1.54 0.00 14.87 43.27 28.43 0.00 0.00 0.87 25.68 0.20 0.27 0.27 0.31 0.71 0.00 13.98 47.12 24.40 0.23 0.24 1.29 25.43 0.00 0.24 0.00 0.25 0.82 0.00 13.77 49.25 24.48 0.00 0.32 10.01 9.19 0.46 3.18 0.44 0.00 2.69 0.00 13.39 44.75 25.36 0.31 0.39 2.67 23.82 0.00 0.83 0.00 0.00 1.87 0.00 13.36 45.73 27.64 0.00 0.77 8.49 7.20 0.71 0.90 1.71 0.00 6.86 0.00 13.15 40.27 31.41 0.00 0.54 10.33 11.77 0.00 4.29 0.00 0.20 1.20 0.00 12.93 49.71 24.31 0.00 0.00 11.08 7.76 0.00 1.12 0.00 0.00 5.33 0.70 12.88 51.14 18.58 0.00 0.00 2.32 6.85 0.00 0.46 0.34 0.36 19.96 0.00 12.47 50.37 24.97 0.00 0.00 1.02 22.50 0.00 0.00 0.27 0.00 0.88 0.00 12.31 47.91 23.24 0.00 0.26 0.46 27.16 0.00 0.28 0.12 0.24 0.33 0.00 12.09 51.71 22.45 0.00 0.63 1.86 20.05 0.00 0.33 1.07 0.31 1.59 0.00 12.08 42.70 28.79 0.00 0.00 5.88 6.54 0.00 0.36 0.28 0.39 15.04 0.00 11.76 36.21 35.27 0.42 9.79 0.73 0.42 0.00 0.00 16.22 0.00 0.95 0.00 11.48 44.40 27.21 0.00 0.47 10.47 11.54 0.00 4.39 0.33 0.00 1.19 0.00 11.29 62.94 18.48 0.00 0.00 2.51 11.24 0.91 0.31 0.66 0.00 2.95 0.00 11.08 48.65 22.91 0.00 0.00 2.14 24.11 0.00 0.31 0.00 0.18 1.70 0.00 10.94 37.41 29.85 0.77 1.21 2.14 1.48 0.32 0.23 23.98 0.25 1.37 0.99 10.92 46.14 29.19 0.28 0.56 8.76 9.92 0.00 3.50 0.00 0.00 1.63 0.00 10.81 62.79 21.51 0.00 0.00 6.46 7.01 0.00 0.27 0.16 0.00 1.80 0.00 10.56 42.80 40.79 0.26 0.32 15.56 0.28 0.00 0.00 0.00 0.00 0.00 0.00 10.28 47.94 24.50 0.00 9.24 0.38 0.37 0.00 0.00 16.64 0.00 0.00 0.93 10.1 52.46 31.84 0.30 0.46 5.57 6.36 0.00 2.32 0.00 0.14 0.54 0.00 9.85 50.06 27.03 0.00 0.53 7.24 9.51 0.30 2.88 0.40 0.18 1.87 0.00

193

Table A1-3 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

9.54 56.62 27.46 0.00 0.00 2.22 11.23 0.22 1.06 0.23 0.23 0.73 0.00 9.54 55.41 18.81 0.00 0.00 2.10 21.37 0.00 0.41 0.31 0.24 1.35 0.00 9.46 57.89 17.64 0.00 0.00 1.55 20.95 0.00 0.40 0.26 0.00 1.31 0.00 9.28 50.39 23.95 0.00 6.47 1.93 1.04 0.00 0.00 14.20 0.42 1.60 0.00 9.23 55.93 27.48 0.29 0.34 6.65 6.56 0.00 1.78 0.00 0.00 0.98 0.00 9.15 50.08 28.57 0.00 0.38 7.85 7.11 0.00 1.60 0.29 0.00 4.11 0.00 9.12 52.14 24.96 0.00 0.47 8.09 9.28 0.15 3.59 0.00 0.24 1.08 0.00 9.09 56.08 21.43 0.00 0.00 2.22 2.17 0.00 0.80 0.00 0.29 15.92 1.09 8.96 60.42 23.07 0.00 0.00 5.56 6.67 0.00 2.25 0.00 0.00 2.03 0.00 8.93 43.28 32.43 0.00 0.37 9.37 9.75 0.00 3.58 0.00 0.00 1.23 0.00 8.84 54.25 20.27 0.00 0.00 9.24 7.82 0.00 1.25 0.31 0.40 4.91 1.54 8.72 50.70 24.33 0.00 0.66 6.06 14.82 0.00 1.38 0.17 0.00 1.88 0.00 8.67 64.35 22.82 0.00 0.00 2.96 4.07 0.38 0.78 2.52 0.27 1.87 0.00 8.39 49.94 22.82 0.00 0.24 2.11 23.78 0.00 0.42 0.00 0.00 0.68 0.00 8.32 49.82 23.80 0.00 0.68 8.88 9.31 0.19 2.21 0.26 0.24 4.62 0.00 8.22 54.80 27.44 0.32 0.44 6.53 7.05 0.00 1.83 0.25 0.26 1.09 0.00 8.14 57.41 24.34 0.00 0.33 7.49 6.63 0.00 0.61 0.00 0.00 3.18 0.00 7.98 40.65 21.00 0.84 1.26 5.17 3.27 1.08 0.66 19.64 0.65 4.54 1.22 7.98 59.52 20.23 0.00 0.00 9.27 5.83 0.00 0.78 0.36 0.00 4.01 0.00 7.94 45.31 23.07 0.00 0.37 7.29 6.22 0.00 0.23 0.58 0.19 16.73 0.00 7.88 53.86 24.87 0.00 0.35 5.95 5.85 0.00 0.17 0.14 0.14 8.66 0.00 7.67 61.17 18.06 0.00 0.00 7.49 7.02 0.00 2.19 0.17 0.18 3.70 0.00 7.53 57.43 24.71 0.00 2.07 4.63 3.63 0.00 0.39 3.63 0.00 3.51 0.00 7.5 69.28 16.32 0.00 0.00 2.77 7.56 0.00 3.36 0.00 0.19 0.52 0.00 7.46 80.98 19.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 7.33 60.47 19.52 0.00 0.27 7.92 7.11 0.00 1.78 0.44 0.31 2.17 0.00 7.19 63.52 10.52 0.00 0.00 5.65 5.39 0.23 0.00 0.00 0.27 14.43 0.00

194

Table A1-3 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

7.1 68.54 21.45 0.48 0.74 0.83 1.72 0.88 0.00 5.37 0.00 0.00 0.00 6.97 65.38 19.53 0.00 3.77 1.56 1.24 0.00 0.31 6.66 0.24 1.32 0.00 6.93 61.52 21.95 0.00 0.50 2.17 1.96 0.23 0.46 8.95 0.41 1.85 0.00 6.85 66.69 18.00 0.00 0.36 2.27 10.44 0.21 0.00 1.58 0.17 0.26 0.00 6.76 61.00 21.58 0.00 0.66 2.65 4.02 0.35 0.33 6.92 0.00 2.48 0.00 6.73 67.59 21.20 0.00 0.87 3.14 3.04 0.00 0.93 1.74 0.25 1.24 0.00 6.6 54.58 28.70 0.00 4.41 0.99 0.61 0.00 0.00 7.73 0.41 1.80 0.77 6.55 59.97 17.06 0.00 0.28 3.32 2.26 0.00 0.19 0.16 0.28 16.48 0.00 6.52 66.92 23.17 0.00 1.43 0.91 1.48 0.82 0.00 4.98 0.00 0.30 0.00 6.49 59.64 20.87 0.00 1.00 4.67 3.97 0.25 0.55 1.91 0.00 7.15 0.00 6.48 58.00 19.65 0.00 0.00 5.34 2.34 0.00 0.23 0.00 0.20 13.47 0.77 6.45 48.13 27.02 0.31 6.78 2.09 1.52 0.00 0.32 11.18 0.29 0.99 1.38 6.39 68.19 16.25 0.00 0.20 0.66 13.75 0.00 0.15 0.12 0.23 0.44 0.00 6.32 70.36 16.58 0.00 0.00 4.57 4.59 0.00 1.03 0.13 0.20 2.53 0.00 6.25 78.66 15.76 0.00 0.24 1.72 1.84 0.00 0.65 0.00 0.20 0.93 0.00 6.25 54.58 22.92 0.00 0.00 5.08 2.62 0.00 0.54 0.29 0.26 13.69 0.00 6.24 71.11 17.82 0.00 0.00 5.39 4.41 0.00 0.18 0.13 0.19 0.78 0.00 6.2 50.23 26.81 0.32 7.73 0.00 0.00 0.19 0.00 14.44 0.00 0.27 0.00 5.98 59.71 23.34 0.00 0.00 0.32 16.00 0.00 0.15 0.00 0.00 0.48 0.00 5.96 57.98 20.74 0.00 0.24 3.15 16.37 0.00 0.00 0.46 0.18 0.86 0.00 5.93 80.41 19.13 0.21 0.00 0.25 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.92 61.12 19.97 0.00 0.52 5.96 8.18 0.00 2.73 0.19 0.28 1.05 0.00 5.92 55.29 21.22 0.00 0.00 1.08 20.87 0.00 0.18 0.27 0.21 0.88 0.00 5.84 57.17 21.41 0.00 0.29 8.87 6.84 0.00 1.00 0.00 0.00 4.41 0.00 5.83 68.17 16.37 0.00 0.39 0.00 0.42 0.43 0.28 0.24 0.37 13.34 0.00 5.82 44.12 30.96 0.00 0.00 0.51 23.43 0.00 0.00 0.20 0.20 0.57 0.00 5.8 65.23 21.54 0.00 0.00 5.37 2.87 0.18 0.34 0.54 0.20 2.99 0.74

195

Table A1-3 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

5.78 59.93 20.18 0.00 0.00 5.33 4.82 0.00 0.58 0.54 0.00 8.62 0.00 5.77 71.14 18.91 0.74 0.84 1.46 0.96 1.11 0.00 4.85 0.00 0.00 0.00 5.72 56.68 26.30 0.00 0.00 6.18 6.07 0.00 0.83 0.38 0.18 3.38 0.00 5.71 83.17 16.55 0.28 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.69 62.35 22.81 0.30 3.78 1.03 0.93 0.20 0.29 6.64 0.28 1.37 0.00 5.54 71.92 14.98 0.00 0.00 4.70 5.70 0.00 1.89 0.00 0.00 0.81 0.00 5.51 69.10 19.83 0.00 0.00 5.58 5.04 0.00 0.00 0.00 0.00 0.45 0.00 5.5 56.20 23.63 0.00 0.55 0.31 0.42 0.00 0.00 18.89 0.00 0.00 0.00 5.5 69.20 19.42 0.00 0.74 3.03 2.71 0.61 0.33 1.77 0.00 2.20 0.00 5.35 68.33 17.92 0.00 0.00 2.57 1.73 0.00 0.37 7.35 0.19 1.54 0.00 5.34 55.06 24.50 0.00 0.71 6.86 8.15 0.00 2.27 0.00 0.00 2.45 0.00 5.34 71.44 17.29 0.00 0.00 1.63 7.10 0.00 0.22 0.24 0.24 1.85 0.00 5.31 66.01 16.83 0.00 0.00 3.32 3.15 0.00 0.97 0.22 0.36 9.14 0.00 5.2 54.95 25.27 0.37 7.75 0.00 0.00 0.00 0.00 11.66 0.00 0.00 0.00 5.2 55.04 23.72 0.00 0.00 0.27 19.22 0.00 0.00 0.00 0.11 0.53 1.11 5.12 59.81 17.14 0.00 0.00 1.76 3.80 0.00 0.33 0.35 0.38 16.43 0.00 5.08 57.15 24.20 0.00 0.23 3.75 2.69 0.00 0.19 0.00 0.25 11.54 0.00 5.03 59.67 16.93 0.00 0.43 7.86 5.60 0.00 0.77 0.24 0.32 8.18 0.00 4.97 67.33 16.96 0.00 0.00 0.57 14.09 0.00 0.00 0.00 0.41 0.63 0.00 4.94 57.89 27.07 0.00 3.92 1.16 0.95 0.00 0.24 6.53 0.20 1.25 0.79 4.93 64.42 14.12 0.00 0.00 7.69 6.07 0.00 0.59 0.30 0.28 6.54 0.00 4.92 74.85 15.53 0.50 0.31 0.78 0.64 0.22 0.19 6.26 0.22 0.50 0.00 4.88 54.20 19.26 0.34 9.18 0.33 0.00 0.23 0.00 15.61 0.00 0.00 0.85 4.74 74.40 18.76 0.00 0.00 2.14 1.78 0.00 0.50 0.21 0.35 1.85 0.00 4.71 73.23 19.33 0.00 1.94 1.88 2.60 0.00 0.00 0.00 0.00 1.02 0.00 4.64 64.18 16.89 0.00 0.48 6.75 7.20 0.00 1.76 0.00 0.00 2.73 0.00 4.64 63.52 21.82 0.00 0.00 2.17 2.47 0.35 0.44 7.19 0.36 1.67 0.00

196

Table A1-3 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

4.62 70.67 18.04 0.00 0.52 2.45 1.93 0.00 0.43 1.46 0.35 3.20 0.96 4.62 78.89 21.11 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.57 66.67 25.11 0.52 0.86 0.33 0.20 2.26 0.19 3.57 0.00 0.27 0.00 4.55 67.79 20.46 0.00 0.00 6.75 1.66 0.32 0.18 0.44 0.13 2.28 0.00 4.54 77.25 18.81 0.00 0.35 1.39 1.36 0.00 0.00 0.00 0.00 0.83 0.00 4.47 68.17 16.11 0.00 0.00 7.60 6.10 0.00 0.31 0.27 0.00 1.44 0.00 4.46 64.67 22.01 0.00 0.00 1.04 0.99 0.00 0.00 10.49 0.00 0.80 0.00 4.39 68.53 17.89 0.33 0.22 5.98 5.25 0.00 0.44 0.00 0.19 1.16 0.00 4.37 62.55 18.99 0.00 0.87 3.84 6.81 0.28 0.32 1.82 0.00 4.54 0.00 4.32 66.67 19.00 0.00 0.00 1.85 10.26 0.00 0.00 0.26 0.00 1.97 0.00 4.27 70.42 17.14 0.00 0.00 3.04 2.30 0.00 0.19 4.98 0.24 1.70 0.00 4.16 71.79 21.40 0.00 0.00 3.08 2.50 0.00 0.00 0.00 0.12 1.11 0.00 4.15 90.73 8.45 0.00 0.00 0.00 0.00 0.27 0.00 0.00 0.30 0.24 0.00 4.09 75.98 15.37 0.00 0.00 3.41 2.26 0.00 0.32 0.00 0.00 2.65 0.00 4.04 60.38 18.77 0.00 0.00 8.78 8.77 0.00 1.19 0.00 0.20 1.91 0.00 4.03 70.24 21.42 0.00 0.00 2.46 2.90 0.00 1.04 0.20 0.18 0.79 0.75 3.96 74.66 18.48 0.00 0.38 2.56 2.24 0.00 0.00 0.35 0.00 1.33 0.00 3.96 70.19 16.79 0.00 0.00 0.95 10.06 0.00 0.28 0.20 0.20 0.63 0.69 3.95 77.15 18.73 0.24 0.25 1.18 1.03 0.00 0.00 0.80 0.00 0.62 0.00 3.89 65.83 24.83 0.00 3.11 0.40 0.32 0.14 0.00 4.79 0.14 0.43 0.00 3.88 76.99 19.22 0.61 0.00 0.00 0.00 1.54 0.00 1.64 0.00 0.00 0.00 3.81 62.23 20.60 0.00 0.00 2.28 2.94 0.63 0.33 10.07 0.17 0.75 0.00 3.75 77.39 17.35 0.00 0.00 0.99 0.85 0.00 0.39 1.87 0.25 0.93 0.00 3.75 77.26 18.92 0.00 0.46 0.30 0.44 0.95 0.17 1.23 0.00 0.27 0.00 3.64 84.76 14.46 0.00 0.00 0.23 0.20 0.00 0.16 0.00 0.00 0.19 0.00 3.62 69.20 17.44 0.42 0.47 2.64 6.09 0.13 1.04 0.25 0.17 1.33 0.82 3.61 80.82 17.64 0.00 0.00 0.74 0.34 0.00 0.00 0.00 0.00 0.46 0.00

197

Table A1-3 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

3.52 68.74 23.10 0.00 2.07 1.06 0.78 0.00 0.21 2.93 0.00 1.11 0.00 3.48 76.63 19.72 0.36 0.38 1.07 0.85 0.00 0.00 0.00 0.00 1.00 0.00 3.47 80.41 18.91 0.27 0.00 0.18 0.12 0.00 0.00 0.00 0.00 0.11 0.00 3.47 67.52 22.04 0.00 3.16 0.51 0.40 0.00 0.00 5.14 0.30 0.93 0.00 3.47 70.98 16.08 0.30 1.23 3.11 2.66 0.19 0.62 1.71 0.16 2.96 0.00 3.41 74.84 20.25 0.00 0.00 0.42 3.97 0.00 0.00 0.00 0.00 0.50 0.00 3.41 87.00 11.99 0.32 0.35 0.34 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.36 62.89 19.33 0.00 0.44 6.66 6.63 0.00 1.56 0.00 0.00 2.47 0.00 3.36 72.53 14.99 0.31 0.33 0.80 8.67 0.00 0.00 0.84 0.12 0.76 0.64 3.33 84.79 14.73 0.22 0.26 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.26 80.33 13.70 0.00 0.00 1.47 1.08 0.00 0.17 0.29 0.43 1.62 0.90 3.18 83.52 16.16 0.32 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.11 72.75 17.71 0.00 0.00 2.07 4.95 0.00 2.13 0.00 0.00 0.39 0.00 3.09 75.01 15.94 0.00 0.00 2.09 5.99 0.00 0.00 0.00 0.00 0.97 0.00 3.09 72.78 14.78 0.00 0.00 0.27 11.71 0.00 0.00 0.15 0.00 0.30 0.00 3.06 85.64 14.04 0.31 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.04 78.63 20.74 0.00 0.00 0.00 0.00 0.27 0.00 0.36 0.00 0.00 0.00 3.04 58.47 15.09 0.00 0.00 1.69 21.92 0.00 0.33 0.19 0.14 1.45 0.71 3 77.02 15.52 0.47 0.00 1.75 3.65 0.00 0.38 0.25 0.25 0.71 0.00 2.99 81.26 16.23 0.37 0.27 0.29 0.21 0.66 0.00 0.71 0.00 0.00 0.00 2.91 81.74 15.15 0.00 0.00 0.00 0.80 0.00 0.00 0.00 0.00 0.19 2.12 2.9 82.93 15.87 0.35 0.42 0.22 0.20 0.00 0.00 0.00 0.00 0.00 0.00 2.9 78.85 14.33 3.56 0.33 0.00 0.00 2.93 0.00 0.00 0.00 0.00 0.00 2.88 71.00 21.81 0.54 0.57 1.33 1.30 0.31 0.00 3.01 0.00 0.13 0.00 2.88 77.42 16.46 0.38 0.54 1.24 3.02 0.00 0.31 0.00 0.00 0.62 0.00 2.88 80.73 14.29 0.31 0.21 1.10 1.05 0.26 0.27 0.35 0.37 1.06 0.00 2.88 64.50 19.86 0.00 0.49 4.68 4.06 0.00 0.72 1.24 0.44 4.02 0.00 2.88 69.91 10.12 0.32 0.47 3.31 13.07 0.00 0.98 0.00 0.00 1.81 0.00

198

Table A1-3 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

2.88 69.91 10.12 0.32 0.47 3.31 13.07 0.00 0.98 0.00 0.00 1.81 0.00 2.82 81.54 17.15 0.29 0.00 0.00 0.27 0.00 0.00 0.00 0.00 0.74 0.00 2.8 79.11 18.73 0.00 0.00 0.79 0.84 0.00 0.00 0.00 0.00 0.52 0.00 2.76 81.19 16.08 0.00 0.28 0.75 0.47 0.00 0.00 0.00 0.00 1.23 0.00 2.74 77.83 18.89 0.34 0.23 0.23 0.00 0.00 0.00 2.27 0.00 0.19 0.00 2.7 82.48 17.52 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.68 67.60 12.53 0.00 0.37 6.11 8.09 0.18 3.32 0.19 0.29 1.31 0.00 2.66 79.06 16.93 0.36 0.24 0.00 0.27 0.00 0.00 0.00 0.00 3.14 0.00 2.62 67.70 12.85 0.39 0.68 4.15 6.47 1.27 2.25 0.94 0.00 3.29 0.00 2.58 80.66 16.87 0.00 0.00 0.34 0.52 0.22 0.00 0.77 0.25 0.36 0.00 2.56 79.37 17.40 0.00 0.21 0.89 0.65 0.00 0.22 0.14 0.26 0.85 0.00 2.56 81.86 15.96 0.34 0.19 0.20 0.26 0.25 0.27 0.24 0.17 0.27 0.00 2.56 72.94 10.07 0.00 0.00 0.83 14.82 0.00 0.00 0.00 0.00 0.60 0.73 2.54 78.79 17.33 0.00 0.00 1.27 0.90 0.00 0.20 0.37 0.30 0.83 0.00 2.54 78.29 17.46 0.00 0.00 0.76 1.28 0.00 0.19 0.00 0.00 0.46 1.55 2.54 85.37 14.63 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.54 69.21 18.32 0.40 1.08 2.13 1.69 0.73 0.00 5.69 0.00 0.00 0.76 2.5 86.29 13.71 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.5 35.95 30.03 0.00 0.00 0.87 31.97 0.00 0.00 0.00 0.00 0.43 0.74 2.45 86.94 12.67 0.00 0.00 0.20 0.19 0.00 0.00 0.00 0.00 0.00 0.00 2.43 80.72 19.28 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.39 81.66 15.95 0.34 0.00 0.54 0.96 0.00 0.36 0.00 0.00 0.18 0.00 2.39 81.71 17.52 0.30 0.27 0.20 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.36 80.45 18.53 0.22 0.25 0.25 0.14 0.00 0.00 0.16 0.00 0.00 0.00 2.32 78.24 17.53 0.00 0.34 1.03 0.86 0.38 0.00 0.82 0.00 0.79 0.00 2.32 74.32 18.94 0.00 0.00 0.94 0.74 0.00 0.00 3.76 0.00 1.31 0.00 2.27 73.94 14.04 0.39 4.69 1.15 3.71 0.26 0.00 1.02 0.26 0.54 0.00

199

Table A1-3 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

2.25 80.48 17.66 0.27 0.41 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.18 2.25 82.37 17.63 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.22 76.95 16.23 0.34 1.88 0.54 1.09 0.00 0.00 2.63 0.00 0.35 0.00 2.22 81.23 16.84 1.15 0.40 0.00 0.00 0.37 0.00 0.00 0.00 0.00 0.00 2.2 47.56 22.50 0.00 8.96 0.34 0.34 0.00 0.00 20.29 0.00 0.00 0.00 2.2 75.70 12.79 0.00 0.00 3.00 2.73 0.35 0.32 0.64 0.18 4.29 0.00 2.2 52.00 19.75 0.18 0.20 0.82 26.56 0.00 0.00 0.00 0.00 0.48 0.00 2.15 84.17 15.41 0.00 0.00 0.22 0.20 0.00 0.00 0.00 0.00 0.00 0.00 2.15 85.48 14.12 0.00 0.00 0.21 0.19 0.00 0.00 0.00 0.00 0.00 0.00 2.12 81.95 17.56 0.00 0.00 0.25 0.24 0.00 0.00 0.00 0.00 0.00 0.00 2.1 81.39 16.34 0.00 0.22 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.05 2.1 87.46 12.54 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.1 62.34 13.34 0.00 0.45 2.53 17.93 0.00 0.44 0.72 0.00 2.26 0.00 2.07 82.57 16.75 0.00 0.00 0.40 0.28 0.00 0.00 0.00 0.00 0.00 0.00 2.05 81.18 17.98 0.00 0.00 0.27 0.57 0.00 0.00 0.00 0.00 0.00 0.00 2.02 82.01 16.00 0.23 0.31 0.55 0.48 0.00 0.00 0.00 0.00 0.42 0.00 2.02 85.85 14.04 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.11 0.00 1.99 79.00 17.97 0.28 0.00 0.73 0.86 0.00 0.21 0.30 0.23 0.41 0.00 1.99 80.68 19.13 0.00 0.00 0.00 0.19 0.00 0.00 0.00 0.00 0.00 0.00 1.97 81.61 17.71 0.00 0.00 0.32 0.36 0.00 0.00 0.00 0.00 0.00 0.00 1.97 81.47 18.30 0.00 0.23 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.94 81.81 16.45 0.00 0.00 0.57 0.54 0.00 0.00 0.19 0.00 0.45 0.00 1.94 82.21 16.51 0.25 0.31 0.32 0.21 0.00 0.00 0.00 0.00 0.18 0.00 1.91 81.87 17.81 0.00 0.00 0.00 0.32 0.00 0.00 0.00 0.00 0.00 0.00 1.91 81.74 18.26 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.88 82.40 17.60 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.88 69.48 12.46 0.00 0.26 4.88 5.03 0.00 1.59 0.00 0.00 5.50 0.81 1.85 81.61 18.39 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

200

Table A1-3 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.83 82.32 16.24 0.00 0.27 0.50 0.00 0.00 0.00 0.00 0.00 0.67 0.00 1.83 78.67 20.25 0.00 0.43 0.00 0.00 0.00 0.00 0.65 0.00 0.00 0.00 1.83 82.67 17.33 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.83 81.43 18.57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.8 78.15 15.33 0.00 0.96 1.30 1.03 0.00 0.35 1.46 0.27 1.14 0.00 1.8 75.38 9.14 0.21 0.19 5.61 5.46 0.00 1.89 0.11 0.21 1.81 0.00 1.77 81.82 16.91 0.00 0.32 0.37 0.28 0.00 0.00 0.00 0.00 0.29 0.00 1.73 82.62 16.07 0.27 0.24 0.44 0.35 0.00 0.00 0.00 0.00 0.00 0.00 1.73 84.71 14.23 0.29 0.19 0.27 0.15 0.00 0.00 0.00 0.00 0.16 0.00 1.73 81.13 18.04 0.24 0.00 0.26 0.00 0.00 0.00 0.33 0.00 0.00 0.00 1.73 84.31 15.69 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.73 83.78 16.22 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.7 81.76 17.18 0.24 0.20 0.24 0.19 0.00 0.00 0.00 0.18 0.00 0.00 1.7 81.02 18.31 0.34 0.33 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.7 56.36 24.98 0.33 4.64 0.95 2.16 0.54 0.00 10.04 0.00 0.00 0.00 1.7 66.16 17.04 0.00 0.00 5.50 6.03 0.00 1.56 0.22 0.00 3.48 0.00 1.67 81.97 17.47 0.00 0.00 0.31 0.24 0.00 0.00 0.00 0.00 0.00 0.00 1.67 87.14 11.16 0.51 0.34 0.30 0.20 0.19 0.15 0.00 0.00 0.00 0.00 1.67 83.99 15.83 0.00 0.00 0.00 0.18 0.00 0.00 0.00 0.00 0.00 0.00 1.67 75.54 11.06 0.00 0.00 1.15 10.60 0.00 0.33 0.21 0.22 0.88 0.00 1.64 79.01 18.27 0.00 0.00 1.26 1.01 0.00 0.00 0.00 0.00 0.46 0.00 1.64 83.86 15.44 0.00 0.23 0.25 0.22 0.00 0.00 0.00 0.00 0.00 0.00 1.64 85.09 14.57 0.34 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.61 78.90 16.18 0.00 0.48 1.30 1.26 0.00 0.00 1.04 0.00 0.84 0.00 1.61 66.63 20.89 0.00 0.00 3.00 3.93 1.21 0.00 4.00 0.00 0.34 0.00 1.57 84.49 15.02 0.00 0.23 0.26 0.00 0.00 0.00 0.00 0.00 0.00 0.00

201

Table A1-3 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.57 80.99 16.24 0.00 0.24 0.00 0.57 0.00 0.00 0.00 0.00 0.00 1.95 1.57 87.32 11.68 0.00 0.00 0.00 0.00 0.18 0.19 0.18 0.31 0.13 0.00 1.57 86.44 13.37 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.19 0.00 0.00 1.57 82.57 17.43 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.57 87.02 12.98 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.57 87.62 12.38 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.54 86.48 12.77 0.25 0.00 0.31 0.19 0.00 0.00 0.00 0.00 0.00 0.00 1.54 86.67 12.09 0.30 0.23 0.20 0.00 0.16 0.13 0.00 0.00 0.20 0.00 1.54 84.19 15.63 0.00 0.00 0.18 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.54 80.98 18.24 0.00 0.22 0.00 0.00 0.00 0.00 0.00 0.00 0.56 0.00 1.5 75.16 20.01 0.00 0.00 2.00 1.83 0.00 0.39 0.00 0.00 0.60 0.00 1.5 82.99 16.29 0.00 0.00 0.00 0.18 0.15 0.14 0.00 0.10 0.14 0.00 1.5 56.54 16.74 0.00 0.56 8.60 10.73 0.17 4.16 0.19 0.00 1.43 0.88 1.47 78.83 19.05 0.21 0.21 0.44 0.32 0.00 0.21 0.21 0.29 0.20 0.00 1.47 82.17 17.39 0.00 0.00 0.00 0.23 0.20 0.00 0.00 0.00 0.00 0.00 1.47 85.96 14.04 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.47 85.78 14.22 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.47 79.91 20.09 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.47 32.82 31.31 0.67 1.30 4.19 3.69 0.38 0.97 22.19 0.34 2.13 0.00 1.47 62.60 14.20 0.00 0.31 7.32 9.51 0.00 3.95 0.00 0.00 0.74 1.38 1.43 82.92 16.71 0.00 0.00 0.00 0.18 0.00 0.00 0.00 0.00 0.19 0.00 1.43 84.68 14.79 0.33 0.20 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.43 86.23 13.77 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.39 73.31 16.80 0.00 0.00 3.60 2.82 0.00 0.00 0.00 0.00 3.47 0.00 1.39 82.75 15.57 0.00 0.00 0.77 0.63 0.00 0.00 0.00 0.00 0.28 0.00 1.39 85.39 13.95 0.43 0.00 0.23 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.39 80.75 18.52 0.29 0.22 0.22 0.00 0.00 0.00 0.00 0.00 0.00 0.00

202

Table A1-3 cont. AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.39 81.47 18.53 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.39 55.62 18.27 0.00 0.00 11.20 8.74 0.24 1.12 0.33 0.21 3.61 0.67 1.35 79.20 20.32 0.00 0.00 0.00 0.19 0.10 0.00 0.00 0.00 0.18 0.00 1.35 86.36 11.88 0.00 0.00 0.00 0.00 0.24 0.00 0.16 0.00 0.22 1.13 1.35 81.96 18.04 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.31 80.28 18.85 0.00 0.24 0.26 0.18 0.00 0.00 0.18 0.00 0.00 0.00 1.31 82.49 17.29 0.00 0.00 0.00 0.22 0.00 0.00 0.00 0.00 0.00 0.00 1.31 82.54 16.67 0.00 0.00 0.00 0.00 0.18 0.00 0.18 0.13 0.29 0.00 1.31 82.27 17.54 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.19 0.00 1.31 86.34 13.66 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.31 84.10 15.90 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.31 80.91 17.57 0.90 0.00 0.00 0.00 0.62 0.00 0.00 0.00 0.00 0.00 1.31 55.29 22.94 0.00 0.00 7.92 6.82 0.00 1.24 0.00 0.00 5.78 0.00 1.31 57.92 17.33 0.00 0.00 0.89 22.44 0.19 0.20 0.56 0.22 0.27 0.00 1.27 79.69 19.26 0.00 0.23 0.46 0.36 0.00 0.00 0.00 0.00 0.00 0.00 1.27 78.16 20.93 0.27 0.00 0.31 0.33 0.00 0.00 0.00 0.00 0.00 0.00 1.27 83.14 16.14 0.24 0.25 0.23 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.27 84.40 15.60 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.27 41.38 30.49 0.00 1.51 3.38 15.75 0.00 0.38 2.53 0.39 3.62 0.57 1.27 52.44 21.16 0.00 0.00 0.85 23.93 0.00 0.38 0.23 0.34 0.67 0.00 1.23 75.65 19.25 0.00 0.37 1.61 1.40 0.15 0.24 0.26 0.00 1.06 0.00 1.23 87.22 11.39 0.00 0.21 0.26 0.19 0.00 0.15 0.14 0.21 0.22 0.00 1.23 81.76 17.98 0.00 0.00 0.00 0.15 0.11 0.00 0.00 0.00 0.00 0.00 1.23 80.82 18.06 0.30 0.00 0.00 0.00 0.00 0.15 0.19 0.24 0.23 0.00 1.23 84.58 15.42 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.23 70.10 20.33 0.00 0.00 2.14 2.14 0.00 0.51 1.41 0.39 2.99 0.00 1.23 61.56 11.66 0.00 0.00 0.34 25.68 0.00 0.00 0.00 0.00 0.76 0.00 1.18 82.10 16.87 0.00 0.00 0.50 0.52 0.00 0.00 0.00 0.00 0.00 0.00 1.18 81.35 18.49 0.00 0.00 0.00 0.16 0.00 0.00 0.00 0.00 0.00 0.00

203

Table A1-3 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.18 82.85 17.15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.18 81.05 18.95 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.18 80.79 18.78 0.43 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.18 85.41 13.20 0.28 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.11 1.18 69.49 5.04 0.00 0.00 8.79 10.75 0.00 4.31 0.24 0.27 1.11 0.00 1.18 51.85 12.89 0.00 0.65 6.35 21.66 0.00 2.02 0.47 0.41 3.69 0.00 1.14 81.55 17.01 0.47 0.41 0.35 0.21 0.00 0.00 0.00 0.00 0.00 0.00 1.14 80.72 18.83 0.00 0.24 0.21 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.14 81.95 16.96 0.00 0.00 0.00 0.00 0.21 0.22 0.25 0.13 0.26 0.00 1.14 84.47 15.36 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.17 0.00 1.14 87.60 12.40 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.14 80.35 19.65 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.14 82.07 17.93 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.14 64.91 20.57 0.47 3.85 1.14 0.69 0.17 0.00 6.54 0.23 0.65 0.78 1.14 75.30 13.12 0.00 0.00 0.70 10.45 0.00 0.00 0.00 0.00 0.43 0.00 1.09 81.21 17.18 0.00 0.00 0.59 0.57 0.00 0.00 0.45 0.00 0.00 0.00 1.09 81.88 16.93 0.40 0.19 0.37 0.22 0.00 0.00 0.00 0.00 0.00 0.00 1.09 86.06 12.33 0.00 0.30 0.34 0.35 0.14 0.17 0.00 0.14 0.17 0.00 1.09 85.45 13.13 0.34 0.31 0.29 0.34 0.14 0.00 0.00 0.00 0.00 0.00 1.09 79.84 19.59 0.20 0.00 0.24 0.13 0.00 0.00 0.00 0.00 0.00 0.00 1.09 82.00 17.57 0.25 0.00 0.00 0.18 0.00 0.00 0.00 0.00 0.00 0.00 1.09 81.00 18.41 0.35 0.24 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.09 83.41 16.12 0.24 0.23 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.09 82.49 17.51 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.09 80.96 19.04 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.09 84.56 15.44 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.09 86.01 13.73 0.26 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.09 37.03 29.77 0.00 0.00 10.51 9.07 0.25 1.67 0.00 0.00 11.69 0.00

204

Table A1-3 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.04 72.74 20.07 0.00 0.38 1.14 1.69 0.28 0.34 1.21 0.26 1.89 0.00 1.04 87.15 11.18 0.00 0.00 0.32 0.26 0.00 0.00 0.00 0.00 0.00 1.08 1.04 82.31 17.43 0.00 0.00 0.26 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.04 82.52 16.50 0.29 0.29 0.25 0.14 0.00 0.00 0.00 0.00 0.00 0.00 1.04 87.33 11.29 0.00 0.19 0.21 0.00 0.00 0.00 0.00 0.00 0.00 0.98 1.04 84.55 14.95 0.32 0.00 0.18 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.04 85.58 13.65 0.21 0.30 0.00 0.25 0.00 0.00 0.00 0.00 0.00 0.00 1.04 81.47 18.32 0.00 0.00 0.00 0.21 0.00 0.00 0.00 0.00 0.00 0.00 1.04 84.28 15.72 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.04 87.65 12.35 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.04 80.95 19.05 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.04 81.42 18.33 0.25 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.04 65.96 21.33 0.00 1.19 0.96 1.12 0.38 0.00 9.06 0.00 0.00 0.00 1.04 60.61 19.79 0.00 0.00 4.70 8.68 0.00 0.60 0.00 0.00 5.62 0.00

205

Table A1-4. Normalised EDS data, station 3, 13-20 September 2012.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

25.28 24.76 37.98 0.00 0.00 1.34 35.04 0.00 0.00 0.00 0.00 0.88 0.00 22.88 28.33 35.01 0.00 0.00 5.93 27.17 0.00 0.29 0.16 0.23 2.88 0.00 21.4 22.82 39.27 0.00 13.60 0.00 0.00 0.00 0.00 22.99 0.00 1.31 0.00 20.52 29.13 33.77 0.00 0.00 2.79 32.72 0.00 0.00 0.00 0.00 1.59 0.00 18.33 43.89 28.10 0.00 0.00 0.50 26.93 0.00 0.00 0.00 0.23 0.35 0.00 18.16 25.55 28.43 0.00 0.00 10.88 10.80 0.00 3.90 0.00 0.30 20.14 0.00 18.08 33.14 28.54 0.00 0.00 7.08 5.05 0.00 0.00 0.34 0.00 25.84 0.00 17.77 27.07 33.49 0.00 0.57 13.72 16.01 0.00 6.51 0.17 0.00 1.83 0.63 15.83 26.76 36.07 0.49 0.55 13.11 15.28 0.20 5.89 0.17 0.00 1.49 0.00 15.35 19.90 42.31 0.00 0.00 1.13 36.24 0.00 0.00 0.00 0.00 0.42 0.00 14.63 24.16 37.34 0.41 13.57 0.47 0.47 0.00 0.00 23.25 0.00 0.33 0.00 13.9 22.33 41.63 0.00 0.00 0.49 35.55 0.00 0.00 0.00 0.00 0.00 0.00 13.86 48.20 27.59 0.00 0.52 7.66 11.00 0.18 3.21 0.20 0.00 1.43 0.00 13.78 28.77 32.32 0.00 0.91 12.00 15.96 0.37 5.23 0.48 0.00 3.10 0.86 13.14 44.50 26.49 0.00 0.31 7.65 12.19 0.00 0.75 0.00 0.00 8.11 0.00 13.1 44.52 27.23 0.00 0.00 0.93 25.87 0.00 0.00 0.00 0.00 0.65 0.81 13.09 33.42 34.75 0.00 0.64 11.48 13.62 0.00 3.10 0.00 0.21 2.78 0.00 12.81 50.27 29.73 0.00 0.48 7.03 8.33 0.00 2.42 0.00 0.00 1.75 0.00 12.59 29.03 35.76 0.00 0.00 1.65 33.13 0.00 0.00 0.00 0.00 0.42 0.00 12.34 25.88 36.92 0.00 0.48 13.43 15.92 0.00 5.82 0.00 0.00 1.54 0.00 12.29 23.62 42.64 0.33 12.63 0.00 0.00 0.00 0.00 20.78 0.00 0.00 0.00 12.19 46.05 31.30 0.00 0.00 11.48 4.06 0.00 0.55 0.24 0.22 5.53 0.56 11.96 38.67 27.85 0.53 0.00 12.83 12.75 0.00 3.71 0.20 0.00 3.47 0.00 11.96 45.41 29.91 0.00 0.37 4.74 12.95 0.00 0.50 2.31 0.00 3.81 0.00 11.38 32.29 32.52 0.23 0.00 0.72 33.49 0.00 0.00 0.21 0.00 0.55 0.00 11.24 33.46 38.85 0.00 0.00 14.45 5.74 0.00 0.46 0.00 0.00 7.03 0.00 11.16 36.78 25.80 0.00 0.00 1.15 33.76 0.00 0.28 0.25 0.00 0.66 1.32 11.03 55.56 23.84 0.00 0.72 5.78 5.64 0.83 1.92 1.42 0.00 3.43 0.86

206

Table A1-4 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

11 49.88 19.57 0.00 0.48 6.74 18.49 0.00 3.26 0.00 0.00 1.59 0.00 10.33 36.36 27.72 0.00 0.00 12.22 14.35 0.00 5.44 0.00 0.00 3.90 0.00 10.3 59.44 14.33 0.00 0.41 8.61 10.31 0.21 4.31 0.16 0.00 1.62 0.61 10.13 40.03 32.59 0.00 0.00 10.24 11.43 0.00 4.31 0.00 0.00 0.88 0.51 9.86 34.06 30.57 0.00 0.64 12.41 15.00 0.00 5.48 0.00 0.00 1.85 0.00 9.62 49.15 29.34 0.00 0.61 7.86 8.86 0.00 3.08 0.00 0.00 1.08 0.00 9.57 48.25 27.80 0.00 0.36 8.60 9.58 0.00 3.24 0.20 0.17 1.80 0.00 9.43 38.29 33.11 0.00 0.50 10.41 11.98 0.00 4.49 0.00 0.00 1.22 0.00 9.11 35.87 27.47 0.00 0.00 9.78 8.98 0.00 0.57 0.00 0.00 16.42 0.93 8.96 42.09 28.33 0.00 0.00 1.06 27.32 0.00 0.00 0.00 0.20 0.99 0.00 8.8 52.20 24.66 0.00 0.00 8.30 8.92 0.00 2.60 0.47 0.00 2.85 0.00 8.78 71.62 20.04 0.00 0.21 3.59 1.80 0.11 0.36 0.16 0.17 1.93 0.00 8.77 26.18 40.37 0.00 0.00 14.62 15.51 0.00 1.47 0.00 0.00 1.84 0.00 8.61 39.23 21.51 0.00 0.00 1.70 2.08 0.00 0.27 0.29 1.38 33.52 0.00 8.53 47.15 29.26 0.00 0.53 8.20 9.55 0.00 2.77 0.00 0.00 2.53 0.00 8.4 37.63 25.54 0.86 1.00 0.98 0.82 0.58 0.58 30.69 0.53 0.79 0.00 8.16 77.97 7.09 0.00 0.00 0.00 13.66 0.00 0.00 0.00 0.17 0.21 0.90 8.15 38.19 34.85 0.00 0.38 11.25 11.92 0.00 1.26 0.22 0.00 1.92 0.00 8.11 42.83 30.11 0.00 0.00 1.73 19.34 0.00 0.23 0.00 0.17 5.58 0.00 8.02 19.55 47.35 0.00 0.00 28.83 1.90 0.96 0.00 0.00 0.00 0.00 1.41 7.93 45.10 31.10 0.00 0.00 0.61 21.87 0.18 0.00 0.37 0.18 0.58 0.00 7.84 48.24 30.97 0.00 0.00 9.56 8.65 0.00 0.20 0.11 0.22 2.05 0.00 7.82 45.49 29.67 0.00 0.00 10.33 11.07 0.00 0.53 0.38 0.24 2.29 0.00 7.76 47.41 24.48 0.00 0.00 1.13 25.94 0.00 0.00 0.23 0.26 0.54 0.00 7.71 39.19 21.88 0.00 0.00 2.78 2.82 0.22 0.35 0.45 0.27 30.77 1.27 7.7 51.55 23.52 0.00 0.00 0.94 23.33 0.00 0.00 0.00 0.00 0.67 0.00 7.64 47.55 24.65 0.00 0.00 0.33 27.02 0.00 0.00 0.00 0.16 0.28 0.00 7.6 48.26 23.57 0.00 1.31 8.14 12.09 0.00 3.62 0.00 0.00 3.01 0.00

207

Table A1-4 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

7.37 40.05 27.76 0.00 0.00 1.78 28.79 0.00 0.21 0.00 0.23 1.18 0.00 7.32 46.68 25.49 0.00 0.00 0.78 25.66 0.00 0.00 0.00 0.20 0.71 0.48 7.27 46.64 24.50 0.00 0.00 0.80 0.70 0.00 0.00 26.72 0.00 0.64 0.00 7.22 44.24 30.13 0.00 0.00 0.54 24.42 0.00 0.00 0.33 0.00 0.35 0.00 7.2 37.21 30.53 0.00 8.06 2.79 2.49 0.00 0.40 15.17 0.00 2.38 0.97 7.18 47.03 24.39 0.00 0.40 11.08 10.55 0.00 1.07 0.27 0.00 5.22 0.00 7.09 46.43 26.82 0.00 0.00 8.60 8.92 0.00 0.91 0.00 0.36 6.84 1.11 7.08 52.18 22.54 0.00 0.00 0.97 23.21 0.00 0.00 0.00 0.00 0.65 0.45 6.89 35.10 36.02 0.00 0.00 0.67 27.19 0.00 0.00 0.00 0.00 0.48 0.55 6.87 41.30 34.36 0.68 1.65 9.67 8.71 0.00 0.15 0.15 0.00 3.34 0.00 6.76 55.00 19.18 0.66 1.83 9.14 9.40 0.00 0.00 0.40 0.27 4.12 0.00 6.73 39.00 34.30 0.41 10.35 0.41 0.00 0.00 0.00 15.52 0.00 0.00 0.00 6.7 47.11 24.01 0.00 0.00 2.40 24.86 0.00 0.00 0.21 0.00 1.42 0.00 6.67 56.22 14.60 0.00 0.51 5.08 3.69 0.00 1.25 0.40 0.00 17.28 0.96 6.64 51.11 25.90 0.00 0.19 0.37 22.07 0.16 0.00 0.00 0.00 0.20 0.00 6.63 41.25 30.26 0.00 0.00 13.45 7.25 0.00 0.00 0.00 0.22 7.58 0.00 6.61 79.37 19.30 0.00 0.00 0.73 0.31 0.00 0.00 0.00 0.00 0.28 0.00 6.56 55.53 22.89 0.19 0.00 0.76 19.50 0.00 0.31 0.17 0.19 0.46 0.00 6.36 52.13 19.92 0.00 0.47 7.53 9.04 0.00 1.60 0.00 0.00 8.80 0.52 6.32 45.54 29.58 0.00 0.00 13.10 6.21 0.00 0.25 0.00 0.28 5.03 0.00 6.3 38.65 32.50 0.00 5.55 5.38 4.82 0.47 1.45 8.73 0.00 2.44 0.00 6.19 54.93 17.22 0.00 0.37 4.72 4.26 0.34 0.19 0.34 0.26 17.38 0.00 6.13 52.44 26.32 0.00 0.00 1.41 18.62 0.00 0.00 0.14 0.25 0.81 0.00 6.08 48.44 21.74 0.00 0.00 5.90 2.94 0.00 0.00 0.00 0.26 20.72 0.00 6.06 46.93 23.83 0.00 0.00 0.75 27.29 0.00 0.24 0.23 0.27 0.46 0.00 6.05 31.62 31.67 0.00 0.00 14.10 15.68 0.00 3.34 0.00 0.00 1.82 1.77 5.87 46.26 30.17 0.00 1.02 1.80 3.61 0.00 0.00 16.66 0.00 0.48 0.00 5.83 42.14 24.60 0.00 0.30 7.12 9.74 0.00 0.70 1.75 0.32 13.34 0.00

208

Table A1-4 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

5.72 17.26 50.84 0.00 0.34 30.43 0.49 0.65 0.00 0.00 0.00 0.00 0.00 5.64 52.50 24.47 0.00 5.29 2.15 2.36 0.00 0.43 10.61 0.00 2.19 0.00 5.49 60.99 23.02 0.00 0.75 4.95 6.93 0.00 2.48 0.00 0.00 0.89 0.00 5.48 45.82 27.05 0.00 0.00 8.54 6.34 0.33 0.38 0.00 0.21 10.67 0.66 5.45 31.36 31.82 0.00 0.65 13.15 15.30 0.00 6.27 0.00 0.00 1.46 0.00 5.44 51.93 20.03 0.00 0.00 3.14 1.65 0.24 0.38 0.31 0.26 22.07 0.00 5.43 55.53 20.11 0.00 0.00 0.99 22.70 0.00 0.18 0.15 0.00 0.34 0.00 5.33 48.88 25.53 0.00 0.00 10.16 10.92 0.00 0.58 0.67 0.37 2.89 0.00 5.32 38.64 39.95 0.00 0.00 20.14 0.71 0.56 0.00 0.00 0.00 0.00 0.00 5.27 28.60 37.39 0.00 0.38 15.00 14.14 0.27 0.41 0.47 0.32 2.26 0.75 5.09 37.89 27.84 0.00 0.00 2.32 30.14 0.00 0.52 0.00 0.00 1.29 0.00 5.07 60.92 16.30 2.93 0.00 5.18 13.84 0.00 0.00 0.45 0.00 0.39 0.00 4.94 69.07 21.16 0.00 0.41 2.98 3.73 0.00 1.56 0.00 0.15 0.95 0.00 4.91 39.18 34.77 0.00 2.39 3.72 5.40 0.00 0.00 12.22 0.00 2.31 0.00 4.87 25.72 37.30 0.00 0.00 1.46 34.82 0.00 0.00 0.00 0.00 0.69 0.00 4.83 68.43 22.75 0.00 0.00 0.43 6.95 0.00 0.20 0.50 0.15 0.60 0.00 4.82 56.80 21.33 0.00 0.00 1.24 18.68 0.00 0.00 0.12 0.19 1.63 0.00 4.78 46.92 25.65 0.00 0.00 2.99 21.95 0.00 0.61 0.00 0.00 1.47 0.42 4.78 54.73 23.79 0.00 0.00 7.99 8.76 0.00 2.47 0.00 0.00 1.68 0.58 4.77 55.44 16.75 0.00 0.00 0.59 24.20 0.22 0.20 2.05 0.00 0.57 0.00 4.76 53.17 24.41 0.00 1.66 5.95 5.70 0.00 1.47 2.99 0.00 3.37 1.28 4.75 50.76 26.52 0.00 0.25 1.20 20.79 0.00 0.00 0.00 0.00 0.48 0.00 4.72 78.34 14.30 0.30 0.00 1.71 1.99 0.18 0.28 0.63 0.20 1.22 0.86 4.64 57.91 17.16 0.00 0.00 4.34 9.83 0.00 0.44 0.23 0.29 9.81 0.00 4.61 46.96 24.09 0.00 0.00 3.06 22.97 0.00 0.40 0.00 0.00 1.54 0.98 4.61 67.16 18.34 0.00 0.00 0.56 12.43 0.00 0.28 0.13 0.28 0.82 0.00 4.6 46.45 33.03 0.00 0.00 3.56 15.28 0.00 0.00 0.00 0.00 1.68 0.00 4.58 43.40 31.03 0.00 0.00 12.05 9.08 0.00 0.00 0.25 0.00 3.65 0.54

209

Table A1-4 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

4.53 50.52 20.73 0.00 0.35 0.81 0.91 0.00 0.00 25.94 0.00 0.74 0.00 4.52 61.80 17.09 0.00 0.00 5.19 4.58 0.19 0.00 0.68 0.00 10.48 0.00 4.48 44.26 27.17 0.00 0.94 9.22 12.06 0.00 4.13 0.00 0.00 2.23 0.00 4.46 46.12 22.66 0.00 0.00 1.50 28.04 0.00 0.00 0.00 0.32 0.66 0.69 4.43 59.28 19.14 0.00 0.27 8.01 5.10 0.00 0.50 0.00 0.19 6.85 0.66 4.39 44.74 22.93 0.00 1.16 6.72 6.39 0.00 0.00 13.12 0.00 4.95 0.00 4.35 51.01 28.72 0.00 0.39 8.16 7.03 0.00 0.00 0.46 0.00 4.24 0.00 4.34 56.40 19.45 0.00 0.50 7.94 9.67 0.00 3.17 0.00 0.00 2.35 0.52 4.32 44.43 30.40 0.00 0.38 9.12 10.61 0.00 3.74 0.00 0.00 0.72 0.61 4.32 65.14 16.94 0.00 0.63 1.87 1.71 0.00 0.31 1.44 0.27 11.68 0.00 4.3 74.69 20.63 0.00 0.00 0.60 3.20 0.00 0.16 0.20 0.19 0.33 0.00 4.3 50.95 22.19 0.00 7.82 0.73 0.39 0.23 0.00 14.41 0.33 1.86 1.09 4.3 31.13 35.33 0.00 0.00 2.91 28.78 0.00 0.97 0.00 0.00 0.88 0.00 4.29 44.82 30.32 0.00 0.46 5.26 15.26 0.00 2.14 0.00 0.00 0.88 0.87 4.22 53.24 23.30 0.00 0.00 8.89 9.72 0.00 0.74 0.17 0.00 3.93 0.00 4.19 42.18 21.33 0.78 0.85 0.98 0.87 0.62 0.46 30.90 0.47 0.55 0.00 4.16 61.17 20.98 0.00 0.87 5.52 6.94 0.00 2.25 0.00 0.00 2.27 0.00 4.15 45.93 23.04 0.00 0.00 0.55 29.62 0.00 0.00 0.19 0.21 0.48 0.00 4.13 75.61 15.09 0.00 0.22 2.77 2.95 0.00 0.92 0.00 0.00 2.44 0.00 4.13 49.64 21.49 0.00 0.00 0.44 27.36 0.00 0.00 0.00 0.19 0.34 0.54 4.12 57.66 21.17 0.00 1.03 5.68 7.54 0.23 2.30 1.33 0.00 3.06 0.00 4.09 57.79 24.97 0.00 0.00 5.92 5.72 0.00 0.32 0.11 0.31 4.86 0.00 4.09 68.00 19.05 0.00 0.37 4.52 4.83 0.00 1.25 0.00 0.00 1.98 0.00 4.07 68.94 17.88 5.35 2.61 0.21 0.00 3.17 0.65 1.19 0.00 0.00 0.00 4.03 84.09 15.91 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.02 49.85 20.59 0.00 0.32 8.49 7.32 0.00 0.43 0.00 0.00 13.01 0.00 4 79.89 17.95 0.21 0.22 0.39 0.55 0.00 0.21 0.00 0.26 0.31 0.00

210

Table A1-4 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

3.97 63.89 14.62 0.00 0.00 0.30 20.69 0.00 0.00 0.00 0.28 0.23 0.00 3.95 47.21 25.82 0.00 0.45 10.92 9.98 0.00 2.86 0.48 0.00 2.28 0.00 3.95 44.40 28.71 0.00 0.68 8.37 8.51 0.50 0.81 3.05 0.00 4.96 0.00 3.89 51.15 27.96 0.00 0.00 7.62 7.10 0.20 0.79 1.91 0.20 3.08 0.00 3.89 65.89 14.93 0.00 0.00 4.74 3.86 0.00 0.48 0.00 0.00 10.11 0.00 3.88 49.15 22.23 0.00 8.32 0.00 0.00 0.00 0.00 17.48 0.00 1.88 0.94 3.75 64.11 23.24 0.00 4.14 0.29 0.20 0.00 0.00 6.95 0.00 0.25 0.82 3.74 38.50 30.31 0.00 0.00 4.55 24.98 0.00 0.25 0.00 0.20 1.22 0.00 3.72 47.71 26.87 0.00 0.00 14.38 3.42 0.00 0.56 0.22 0.19 6.64 0.00 3.71 26.23 43.65 0.00 0.00 28.44 0.92 0.76 0.00 0.00 0.00 0.00 0.00 3.71 60.24 18.69 0.00 0.82 6.43 6.54 0.52 0.92 1.09 0.00 4.75 0.00 3.71 44.08 36.70 0.00 0.00 3.85 7.67 0.00 0.24 5.12 0.00 2.35 0.00 3.68 59.08 20.70 0.00 0.00 0.94 18.43 0.13 0.00 0.14 0.19 0.38 0.00 3.67 39.79 31.03 0.00 0.00 13.67 13.64 0.00 0.70 0.00 0.00 1.18 0.00 3.56 76.50 16.77 0.00 0.00 2.26 2.26 0.00 0.96 0.18 0.17 0.33 0.57 3.5 80.12 18.50 0.00 0.00 0.57 0.46 0.00 0.00 0.00 0.00 0.34 0.00 3.5 61.41 19.81 0.00 0.00 6.37 6.54 0.00 0.41 0.00 0.24 5.22 0.00 3.41 57.91 20.36 0.00 0.00 1.34 17.78 0.00 0.29 1.03 0.00 0.86 0.43 3.39 57.64 18.73 0.00 5.00 2.28 2.72 0.00 0.53 11.13 0.29 1.69 0.00 3.39 48.85 28.99 0.37 8.59 0.33 0.00 0.00 0.00 12.88 0.00 0.00 0.00 3.38 80.05 17.73 0.00 0.00 0.27 0.32 0.00 0.00 1.63 0.00 0.00 0.00 3.38 42.65 26.74 0.00 0.00 11.51 12.34 0.00 0.00 0.00 0.00 6.76 0.00 3.34 45.04 17.02 0.49 0.64 1.14 1.02 0.31 0.00 31.83 0.00 0.62 1.90 3.34 52.10 23.74 0.00 0.00 4.79 14.83 0.00 0.54 0.22 0.19 3.60 0.00 3.29 57.00 18.55 0.00 0.47 6.32 13.06 0.00 1.46 0.00 0.00 3.13 0.00 3.29 71.99 14.44 0.00 0.00 1.08 1.07 0.00 0.00 0.13 0.25 11.03 0.00 3.28 49.47 24.21 0.00 0.00 3.42 20.41 0.00 0.72 0.00 0.00 1.76 0.00 3.26 55.06 23.56 0.00 0.00 4.60 14.30 0.00 0.92 0.00 0.00 1.56 0.00

211

Table A1-4 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

3.26 59.62 18.23 0.00 0.00 3.04 15.55 0.00 0.00 1.27 0.00 2.29 0.00 3.26 56.05 18.73 0.00 0.38 5.36 10.53 0.00 0.72 2.09 0.00 6.14 0.00 3.23 22.92 43.36 0.00 0.00 31.07 1.90 0.75 0.00 0.00 0.00 0.00 0.00 3.23 52.12 17.35 0.00 7.74 0.59 1.21 0.00 0.30 20.24 0.00 0.44 0.00 3.21 43.52 27.22 0.00 0.39 9.79 12.13 0.00 1.63 0.30 0.00 4.00 1.03 3.21 74.51 12.09 0.00 0.00 1.73 7.74 0.00 0.26 0.15 0.13 2.87 0.52 3.16 75.81 15.37 0.00 2.22 1.07 0.37 0.28 0.30 3.69 0.00 0.89 0.00 3.08 63.69 21.17 0.00 1.81 3.92 4.12 0.00 0.78 3.54 0.00 0.97 0.00 3.06 71.55 10.83 0.20 0.00 0.35 16.23 0.00 0.18 0.00 0.28 0.39 0.00 3.04 74.46 11.39 0.00 0.00 3.21 2.51 0.00 0.54 0.29 0.19 7.41 0.00 3.02 29.79 35.66 0.47 11.63 0.53 0.38 0.27 0.00 18.76 0.00 0.59 1.91 3 54.39 16.90 0.00 0.48 6.43 6.86 0.00 2.56 0.00 0.23 11.20 0.96 3 69.40 18.59 0.00 0.00 0.35 10.94 0.00 0.00 0.10 0.22 0.40 0.00 2.99 83.29 16.71 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.99 60.01 18.28 0.00 0.57 7.44 8.98 0.00 3.12 0.38 0.15 1.07 0.00 2.97 57.43 21.72 0.00 0.36 3.86 14.13 0.00 0.81 0.24 0.00 1.44 0.00 2.97 61.50 18.81 0.00 0.00 1.11 16.36 0.00 0.49 0.16 0.21 0.88 0.50 2.95 53.21 19.68 0.00 0.00 0.83 25.61 0.00 0.33 0.00 0.00 0.35 0.00 2.95 46.55 21.94 0.59 0.51 9.30 9.50 0.84 1.31 0.28 0.00 8.59 0.59 2.95 54.12 24.60 0.00 0.32 8.95 9.30 0.00 0.27 0.19 0.21 2.05 0.00 2.93 61.02 21.21 0.00 0.00 6.89 6.99 0.00 0.26 0.00 0.00 3.64 0.00 2.91 42.16 20.34 0.74 1.00 2.21 2.00 0.35 0.00 29.87 0.00 1.32 0.00 2.91 51.04 21.95 0.00 0.25 4.25 18.64 0.21 0.38 0.32 0.18 2.24 0.54 2.91 31.36 39.24 0.00 0.00 14.96 7.39 0.00 0.99 0.00 0.00 6.06 0.00 2.9 51.57 16.12 0.00 0.00 3.78 24.32 0.00 0.56 0.25 0.27 3.13 0.00 2.9 63.58 18.93 0.00 0.32 7.19 5.96 0.00 1.39 0.35 0.00 2.29 0.00 2.88 66.76 21.33 0.00 0.00 6.64 3.02 0.00 0.00 0.00 0.00 2.24 0.00 2.86 31.26 37.32 0.00 12.38 0.44 0.00 0.00 0.00 18.61 0.00 0.00 0.00

212

Table A1-4 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

2.86 35.00 33.40 0.00 0.00 14.63 14.34 0.00 0.26 0.32 0.22 1.84 0.00 2.84 56.75 17.23 0.00 0.00 0.51 24.83 0.00 0.16 0.00 0.28 0.23 0.00 2.8 71.50 21.72 0.26 0.00 1.59 2.41 0.00 0.00 0.00 0.00 1.70 0.83 2.8 38.67 28.63 0.00 0.00 0.31 30.88 0.00 0.00 0.00 0.00 0.42 1.08 2.8 72.98 9.87 0.00 0.28 3.45 11.53 0.00 0.00 0.00 0.24 1.64 0.00 2.8 60.54 23.01 0.00 0.00 7.72 7.24 0.00 0.00 0.16 0.17 1.17 0.00 2.8 62.82 17.03 0.44 0.49 6.54 6.70 0.00 0.70 0.00 0.00 5.28 0.00 2.8 51.21 31.04 0.00 3.41 1.17 6.37 0.00 0.17 5.68 0.26 0.68 0.00 2.78 51.66 20.70 0.00 0.00 0.77 24.86 0.00 0.32 0.30 0.24 0.64 0.51 2.74 57.41 19.03 0.00 0.00 11.03 10.80 0.00 0.72 0.00 0.00 1.02 0.00 2.74 63.21 17.92 0.00 0.44 6.84 5.68 0.00 0.58 0.00 0.00 5.33 0.00 2.74 68.21 18.18 0.00 0.26 1.35 1.27 0.00 0.27 9.00 0.00 0.83 0.64 2.72 53.78 23.22 0.00 0.00 1.30 0.98 0.00 0.00 19.88 0.00 0.85 0.00 2.7 80.77 18.89 0.00 0.00 0.20 0.14 0.00 0.00 0.00 0.00 0.00 0.00 2.7 63.39 24.53 0.00 0.27 4.63 5.16 0.00 1.00 0.00 0.00 1.02 0.00 2.68 72.69 19.12 0.00 0.00 2.86 2.22 0.00 0.34 0.10 0.16 1.57 0.94 2.66 62.25 24.22 0.00 0.23 5.93 6.12 0.00 0.00 0.00 0.00 1.25 0.00 2.64 72.71 19.64 0.00 0.36 1.47 1.92 0.00 0.55 2.58 0.00 0.78 0.00 2.64 63.65 13.64 0.00 0.00 0.34 21.45 0.00 0.16 0.16 0.30 0.31 0.00 2.62 41.39 29.96 0.00 0.00 13.88 13.26 0.00 0.22 0.25 0.00 1.04 0.00 2.62 55.19 17.25 0.00 0.00 4.00 19.95 0.00 0.32 0.42 0.00 2.89 0.00 2.6 72.06 17.27 0.00 0.00 3.88 4.37 0.00 0.27 0.00 0.13 2.02 0.00 2.58 81.66 18.34 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.58 58.44 15.92 0.00 0.00 0.65 23.75 0.00 0.00 0.13 0.25 0.85 0.00 2.58 46.50 25.12 0.00 0.00 14.52 6.47 0.00 0.00 0.18 0.26 6.09 0.87 2.56 58.88 18.31 0.00 0.00 9.71 10.26 0.00 0.39 0.28 0.28 1.89 0.00 2.54 53.26 17.41 0.00 0.00 0.47 28.33 0.00 0.00 0.00 0.23 0.30 0.00 2.54 45.57 24.91 0.00 0.00 13.80 6.65 0.00 0.00 0.00 0.20 8.88 0.00

213

Table A1-4 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

2.54 67.73 16.11 0.00 0.00 6.55 5.72 0.18 0.17 0.20 0.00 2.49 0.84 2.54 74.79 13.81 0.00 0.00 1.67 1.38 0.00 0.28 0.00 0.23 7.20 0.64 2.52 36.15 31.49 0.00 0.00 15.41 8.38 0.00 0.26 0.19 0.27 7.85 0.00 2.48 62.38 18.63 0.00 0.00 1.16 16.52 0.00 0.00 0.29 0.00 1.02 0.00 2.45 68.33 14.77 0.39 0.98 5.60 5.49 0.00 0.35 1.03 0.31 2.76 0.00 2.43 75.39 19.02 0.00 0.28 1.79 1.53 0.13 0.20 0.14 0.00 1.51 0.00 2.41 72.10 18.48 0.00 0.00 5.02 2.26 0.13 0.13 0.10 0.19 1.58 0.00 2.41 80.70 19.09 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.20 0.00 2.41 52.56 26.77 0.00 0.90 6.73 6.88 0.00 1.28 1.38 0.00 3.49 0.00 2.36 49.41 24.13 0.00 0.00 5.08 4.03 0.30 0.00 13.43 0.00 3.09 0.53 2.36 56.77 19.60 0.00 0.00 3.65 17.07 0.00 0.50 0.22 0.16 2.03 0.00 2.36 50.78 27.44 0.00 0.00 12.57 4.76 0.00 0.18 0.00 0.00 4.28 0.00 2.36 62.30 19.36 0.00 0.78 5.15 5.64 0.35 0.52 1.76 0.00 4.13 0.00 2.32 62.97 22.06 0.00 0.00 0.00 0.00 0.00 0.00 14.97 0.00 0.00 0.00 2.32 61.94 23.79 0.00 1.25 7.19 3.14 0.00 0.00 0.00 0.00 2.70 0.00 2.29 62.47 22.56 0.00 0.00 7.02 5.22 0.00 0.00 0.12 0.23 2.38 0.00 2.29 69.12 17.30 0.00 2.42 1.94 1.97 0.22 0.65 5.56 0.00 0.84 0.00 2.27 69.87 24.60 0.00 0.00 3.20 0.71 0.00 0.00 0.00 0.19 0.90 0.52 2.27 78.56 18.68 0.00 0.00 1.16 0.45 0.17 0.00 0.00 0.00 0.98 0.00 2.27 79.59 17.29 0.00 0.00 0.42 0.37 0.17 0.00 0.00 0.00 2.16 0.00 2.25 49.76 20.71 0.00 0.40 10.29 10.31 0.00 1.94 0.00 0.00 5.18 1.41 2.22 46.23 27.70 0.00 0.00 13.19 8.32 0.00 0.76 0.00 0.00 3.81 0.00 2.22 66.51 13.14 0.00 0.00 0.60 19.34 0.00 0.00 0.00 0.00 0.41 0.00 2.2 59.07 19.27 0.00 4.46 0.67 3.91 0.00 0.00 11.64 0.35 0.63 0.00 2.2 55.24 24.48 0.00 0.00 11.03 5.50 0.00 0.00 0.16 0.28 3.31 0.00 2.2 70.46 18.97 0.00 0.00 4.67 3.03 0.00 0.48 0.00 0.00 1.91 0.49 2.17 79.38 11.91 0.00 0.00 0.49 0.51 0.00 0.00 0.00 0.00 7.71 0.00 2.17 49.60 27.21 0.00 8.56 0.37 0.00 0.00 0.00 14.27 0.00 0.00 0.00

214

Table A1-4 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

2.17 52.21 19.52 0.00 0.00 2.43 23.43 0.00 0.35 0.00 0.16 1.89 0.00 2.17 60.51 21.62 0.00 0.00 8.21 6.30 0.00 0.00 0.29 0.00 3.07 0.00 2.15 61.91 15.68 0.00 0.50 6.84 6.02 0.38 0.51 1.99 0.00 4.84 1.32 2.12 67.70 22.91 0.00 2.68 0.92 0.73 0.17 0.00 4.06 0.00 0.82 0.00 2.12 79.84 18.01 0.00 0.23 0.29 0.28 0.00 0.00 1.17 0.00 0.18 0.00 2.12 34.57 31.48 0.00 4.49 5.61 9.80 0.00 1.03 11.12 0.23 1.66 0.00 2.12 42.45 24.79 0.00 0.45 7.86 18.58 0.00 0.90 0.45 0.00 4.51 0.00 2.12 60.49 19.58 0.00 0.00 0.44 19.07 0.00 0.00 0.00 0.14 0.27 0.00 2.12 56.92 20.05 0.00 1.08 6.21 9.36 0.00 1.46 2.00 0.00 2.31 0.61 2.12 51.76 28.26 0.00 0.00 8.05 6.76 0.00 0.61 0.22 0.15 4.18 0.00 2.12 54.80 17.82 0.00 1.09 5.30 8.15 0.00 0.50 8.51 0.42 3.41 0.00 2.1 24.76 40.88 0.00 0.00 31.45 1.99 0.91 0.00 0.00 0.00 0.00 0.00 2.1 39.95 26.67 0.00 0.59 7.88 6.80 0.00 1.17 6.57 0.00 9.65 0.72 2.07 26.44 47.85 0.00 0.00 25.71 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.07 73.58 18.45 0.00 0.00 2.01 1.13 0.00 0.15 2.21 0.16 2.31 0.00 2.07 64.08 14.61 0.21 0.00 1.50 18.74 0.00 0.23 0.00 0.00 0.62 0.00 2.07 52.54 22.21 0.00 0.00 6.97 13.24 0.00 0.71 0.52 0.00 3.81 0.00 2.07 53.07 18.11 0.00 0.00 14.19 5.52 0.00 0.58 0.00 0.00 6.64 1.89 2.07 59.72 19.06 0.00 0.00 0.95 17.63 0.00 0.21 1.00 0.15 1.27 0.00 2.05 80.38 18.79 0.00 0.00 0.31 0.36 0.00 0.00 0.00 0.00 0.16 0.00 2.05 80.53 18.83 0.30 0.00 0.00 0.34 0.00 0.00 0.00 0.00 0.00 0.00 2.05 79.14 18.99 0.00 0.00 0.00 0.00 0.87 0.00 1.00 0.00 0.00 0.00 2.05 59.99 23.77 0.00 0.00 6.86 6.25 0.00 0.95 0.34 0.00 1.84 0.00 2.02 71.13 11.64 0.00 0.00 0.83 15.65 0.00 0.00 0.25 0.00 0.51 0.00 2.02 74.37 9.92 0.00 0.00 0.25 14.79 0.00 0.00 0.68 0.00 0.00 0.00 2.02 64.52 14.50 0.00 0.00 3.87 10.85 0.00 0.68 0.18 0.21 5.19 0.00 2.02 66.97 18.10 0.00 0.44 4.86 6.27 0.00 1.17 0.00 0.00 1.76 0.43 1.99 36.44 28.24 0.00 0.00 17.96 8.33 0.00 0.00 0.00 0.00 7.58 1.46

215

Table A1-4 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.99 56.59 23.02 0.00 0.43 7.63 6.87 0.00 1.10 0.00 0.00 3.50 0.86 1.97 80.52 18.31 0.00 0.00 0.38 0.36 0.20 0.00 0.00 0.00 0.22 0.00 1.97 68.22 15.03 0.00 0.00 5.75 5.07 0.00 1.14 0.00 0.00 4.79 0.00 1.94 73.16 18.02 0.00 0.17 0.75 6.92 0.00 0.00 0.39 0.19 0.39 0.00 1.94 75.39 16.65 0.00 0.00 0.21 7.04 0.16 0.18 0.20 0.16 0.00 0.00 1.94 58.58 22.41 0.00 0.26 7.76 6.91 0.00 0.71 0.40 0.00 2.97 0.00 1.94 49.81 22.79 0.00 0.00 6.57 7.01 0.00 0.00 0.20 0.46 13.17 0.00 1.94 67.50 15.23 0.38 0.34 5.23 5.24 0.44 1.00 0.36 0.23 4.05 0.00 1.91 69.45 12.93 0.00 0.00 5.28 3.80 0.00 0.23 0.21 0.26 7.85 0.00 1.88 76.03 16.86 0.00 0.00 3.17 2.57 0.00 0.00 0.15 0.14 1.07 0.00 1.88 79.15 17.94 0.00 0.35 0.85 1.23 0.00 0.00 0.00 0.00 0.47 0.00 1.88 79.57 18.88 0.00 0.00 0.27 0.00 0.00 0.00 0.00 0.00 1.28 0.00 1.88 46.64 21.57 0.00 0.00 9.93 8.56 0.00 0.43 0.00 0.00 12.86 0.00 1.85 43.46 26.58 0.00 0.00 1.75 26.45 0.00 0.26 0.00 0.20 1.31 0.00 1.85 52.27 22.24 0.00 0.46 9.37 11.06 0.00 2.26 0.00 0.00 2.33 0.00 1.85 63.01 13.72 0.00 0.00 8.42 9.65 0.00 3.99 0.00 0.22 0.99 0.00 1.85 72.76 16.46 0.00 0.00 0.28 8.88 0.00 0.17 0.98 0.21 0.26 0.00 1.85 67.42 21.78 0.00 0.00 4.51 1.08 0.00 0.00 0.00 0.19 5.02 0.00 1.83 51.24 22.63 0.00 0.00 2.05 22.74 0.00 0.00 0.31 0.00 1.02 0.00 1.8 80.15 19.85 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.8 35.24 31.71 0.42 12.27 0.45 0.00 0.00 0.00 19.91 0.00 0.00 0.00 1.8 57.42 15.51 0.00 0.00 1.21 24.11 0.00 0.00 0.20 0.00 0.80 0.74 1.8 61.44 17.38 0.00 0.00 4.74 14.36 0.00 0.24 0.00 0.15 1.69 0.00 1.77 80.52 15.33 0.00 0.00 0.28 3.45 0.00 0.00 0.00 0.00 0.43 0.00 1.77 80.96 18.49 0.00 0.29 0.26 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.77 73.34 10.56 0.00 0.29 2.71 9.67 0.00 1.88 0.40 0.00 1.15 0.00 1.73 38.46 32.95 0.00 0.00 25.93 0.87 0.85 0.30 0.21 0.00 0.43 0.00 1.73 26.07 36.76 0.00 0.00 1.50 34.93 0.00 0.00 0.18 0.00 0.56 0.00

216

Table A1-4 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.73 47.61 23.40 0.79 1.84 10.89 10.75 0.00 0.00 0.00 0.00 4.73 0.00 1.73 49.16 28.60 0.00 0.34 10.02 7.42 0.00 0.00 0.42 0.00 4.03 0.00 1.73 61.16 19.24 0.00 0.71 5.27 9.21 0.00 0.27 1.50 0.00 2.64 0.00 1.73 68.80 12.89 0.00 0.00 6.56 6.92 0.00 2.39 0.81 0.00 1.11 0.53 1.7 79.80 19.32 0.00 0.00 0.56 0.32 0.00 0.00 0.00 0.00 0.00 0.00 1.7 49.80 21.88 0.00 6.02 2.21 5.38 0.00 0.80 12.92 0.00 1.00 0.00 1.7 65.42 18.43 0.00 5.78 0.00 0.00 0.00 0.00 10.04 0.00 0.33 0.00 1.67 75.52 21.06 0.00 0.00 1.48 1.19 0.00 0.00 0.46 0.00 0.29 0.00 1.67 39.27 26.74 0.00 0.00 6.57 21.63 0.00 0.97 0.33 0.35 4.13 0.00 1.67 56.48 17.31 0.30 0.37 9.78 11.19 0.00 3.75 0.00 0.00 0.82 0.00 1.67 65.12 14.24 0.00 0.00 0.47 17.64 0.00 0.12 0.17 0.20 2.03 0.00 1.64 69.65 22.20 0.00 0.00 3.15 2.94 0.00 0.65 0.10 0.00 1.30 0.00 1.64 53.18 27.61 0.00 0.00 0.00 0.00 0.00 0.00 19.21 0.00 0.00 0.00 1.64 43.15 22.25 0.00 0.25 3.29 28.63 0.00 0.43 0.26 0.23 1.52 0.00 1.64 66.00 11.91 0.00 0.00 1.83 18.35 0.00 0.21 0.25 0.00 1.46 0.00 1.61 86.85 13.15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.61 48.75 28.51 0.00 0.00 0.53 8.82 0.00 0.00 12.60 0.25 0.56 0.00 1.61 35.09 33.41 0.00 0.00 2.79 26.96 0.00 0.19 0.00 0.24 1.33 0.00 1.61 64.89 8.17 0.00 0.00 1.09 24.64 0.00 0.21 0.00 0.27 0.73 0.00 1.61 51.77 19.78 0.00 0.00 3.31 21.25 0.00 0.74 0.30 0.00 2.30 0.53 1.61 65.16 12.86 0.00 0.00 1.27 19.61 0.00 0.00 0.00 0.00 0.65 0.46 1.57 45.80 25.57 0.00 0.00 0.73 27.02 0.00 0.00 0.00 0.22 0.66 0.00 1.57 57.57 14.42 0.00 0.00 1.66 23.61 0.00 0.56 0.21 0.00 1.98 0.00 1.57 61.20 18.27 0.00 0.00 4.65 13.54 0.00 0.21 0.00 0.00 2.14 0.00 1.57 53.31 26.29 0.00 0.00 8.42 8.90 0.00 0.40 0.00 0.00 2.68 0.00 1.57 58.64 23.46 0.00 0.00 5.45 9.18 0.00 0.00 0.00 0.00 3.27 0.00 1.57 68.10 17.96 0.00 0.00 2.05 10.75 0.00 0.00 0.23 0.00 0.91 0.00 1.57 75.00 14.91 0.00 1.56 1.60 2.62 0.00 0.62 2.67 0.34 0.68 0.00

217

Table A1-4 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.54 53.84 11.58 0.00 0.00 5.74 5.78 0.00 0.00 0.00 0.00 23.07 0.00 1.54 53.64 26.54 0.31 7.91 0.33 0.00 0.00 0.00 11.27 0.00 0.00 0.00 1.54 72.42 13.21 0.00 0.00 6.04 6.91 0.00 0.00 0.29 0.00 1.13 0.00 1.54 71.68 13.02 0.00 0.00 1.85 10.91 0.00 0.16 0.00 0.11 2.26 0.00 1.5 80.74 16.63 0.00 0.00 0.84 0.70 0.00 0.00 0.00 0.00 1.10 0.00 1.5 84.55 15.45 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.5 46.19 21.47 0.00 0.42 11.08 13.41 0.00 5.26 0.00 0.00 1.64 0.52 1.5 46.87 22.81 0.00 0.00 12.02 11.25 0.00 1.24 0.00 0.00 5.82 0.00 1.5 48.48 21.57 0.00 0.73 7.00 15.08 0.00 0.00 1.17 0.00 5.96 0.00 1.5 32.64 34.49 0.00 0.00 10.72 8.73 0.00 0.57 0.00 0.00 12.85 0.00 1.5 67.10 15.80 0.00 0.32 1.33 12.33 0.00 0.19 2.01 0.00 0.91 0.00 1.5 66.85 17.85 0.00 0.00 6.47 5.68 0.00 0.58 0.18 0.17 2.21 0.00 1.47 15.48 44.46 0.00 0.00 35.27 2.58 0.80 0.00 0.00 0.00 0.00 1.41 1.47 79.41 19.68 0.26 0.24 0.22 0.19 0.00 0.00 0.00 0.00 0.00 0.00 1.47 85.44 14.56 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.47 37.78 26.94 0.00 0.34 12.39 10.26 0.00 1.24 0.00 0.00 11.05 0.00 1.47 51.09 29.29 0.00 0.43 6.18 8.73 0.00 0.00 0.00 0.00 4.28 0.00 1.47 57.85 12.18 0.00 0.00 6.83 6.41 0.00 0.31 0.00 0.00 15.69 0.72 1.47 70.75 16.75 0.00 0.00 6.38 4.26 0.00 0.17 0.00 0.20 1.48 0.00 1.43 16.61 44.06 0.00 0.00 36.12 2.40 0.81 0.00 0.00 0.00 0.00 0.00 1.43 80.04 19.96 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.43 44.92 26.60 0.33 9.99 0.00 0.00 0.00 0.00 18.16 0.00 0.00 0.00 1.43 51.31 21.69 0.00 0.43 10.80 9.64 0.00 2.82 0.66 0.26 2.38 0.00 1.43 73.89 8.92 0.00 0.00 0.51 15.67 0.00 0.00 0.25 0.00 0.76 0.00 1.43 69.80 14.53 0.00 0.00 0.69 13.55 0.00 0.15 0.00 0.00 1.27 0.00 1.39 16.71 46.80 0.00 0.34 32.26 2.34 0.86 0.00 0.22 0.25 0.22 0.00 1.39 76.18 15.83 0.00 0.00 1.48 6.08 0.00 0.00 0.00 0.00 0.42 0.00 1.39 77.59 19.11 0.00 0.00 0.50 0.58 0.00 0.25 0.12 0.22 0.98 0.66

218

Table A1-4 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.39 42.57 25.64 0.00 0.29 10.86 9.78 0.00 0.51 0.34 0.31 9.69 0.00 1.39 63.76 12.69 0.00 0.00 2.15 18.02 0.00 0.37 0.00 0.00 1.68 1.33 1.39 60.94 16.20 0.00 1.00 7.19 8.82 0.00 3.03 0.14 0.18 2.51 0.00 1.39 57.26 14.27 0.00 0.00 7.00 6.45 0.00 0.34 0.00 0.00 14.67 0.00 1.39 67.04 19.50 0.00 0.00 4.84 4.76 0.00 0.31 0.15 0.22 3.17 0.00 1.35 79.07 18.42 0.00 0.00 0.00 2.04 0.00 0.00 0.00 0.21 0.25 0.00 1.35 35.89 28.91 0.00 0.00 2.29 29.70 0.00 0.23 0.00 0.27 2.13 0.59 1.35 36.12 30.95 0.00 0.00 16.23 11.15 0.00 0.93 0.00 0.00 4.63 0.00 1.35 48.74 23.35 0.00 0.00 0.36 26.88 0.00 0.00 0.12 0.29 0.26 0.00 1.35 55.77 20.92 0.00 0.00 10.06 8.70 0.00 0.19 0.35 0.17 3.85 0.00 1.35 67.64 18.00 0.00 0.21 7.31 3.53 0.00 0.00 0.00 0.00 3.30 0.00 1.35 71.46 16.48 0.00 0.00 0.85 9.37 0.00 0.21 0.11 0.20 0.76 0.55 1.31 43.19 30.60 0.00 0.00 24.99 0.67 0.55 0.00 0.00 0.00 0.00 0.00 1.31 80.20 19.80 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.31 80.19 19.25 0.26 0.30 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.31 36.87 30.03 0.00 0.00 0.67 30.60 0.00 0.00 0.14 0.00 1.69 0.00 1.31 63.01 15.14 0.00 0.00 2.39 16.31 0.00 0.41 0.71 0.16 1.86 0.00 1.31 55.26 18.97 0.00 0.00 8.95 6.17 0.00 0.29 0.00 0.00 9.90 0.45 1.31 62.85 21.54 0.00 3.92 1.49 1.28 0.00 0.00 7.38 0.00 1.53 0.00 1.27 17.67 42.44 0.00 0.00 35.27 2.44 0.97 0.26 0.20 0.33 0.41 0.00 1.27 68.12 25.52 0.00 0.19 4.10 1.36 0.00 0.00 0.00 0.00 0.71 0.00 1.27 25.55 36.49 0.00 0.35 1.24 34.40 0.00 0.24 0.40 0.21 1.12 0.00 1.27 30.12 35.21 0.00 0.00 0.40 33.89 0.00 0.00 0.00 0.00 0.38 0.00 1.27 47.72 19.11 0.00 0.19 0.71 30.68 0.00 0.34 0.23 0.40 0.61 0.00 1.27 54.25 16.52 0.00 0.00 3.23 23.19 0.00 0.28 0.20 0.23 1.48 0.62 1.27 48.34 24.61 0.00 0.00 3.59 20.93 0.00 0.29 0.14 0.23 1.87 0.00 1.27 57.68 23.98 0.00 0.00 8.67 8.37 0.00 0.00 0.00 0.00 1.30 0.00 1.27 70.85 16.97 0.00 0.00 0.33 11.85 0.00 0.00 0.00 0.00 0.00 0.00

219

Table A1-4 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.27 63.39 24.06 0.00 0.23 2.55 7.75 0.00 0.31 0.37 0.15 1.20 0.00 1.27 65.45 14.03 0.00 0.00 4.93 4.70 0.00 0.71 1.11 0.00 9.07 0.00 1.23 18.71 44.87 0.00 0.00 32.67 2.29 0.94 0.00 0.00 0.26 0.26 0.00 1.23 80.16 19.84 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.23 53.17 23.05 0.00 0.00 0.89 22.89 0.00 0.00 0.00 0.00 0.00 0.00 1.23 53.70 22.71 0.00 0.00 9.20 11.19 0.00 0.31 0.00 0.00 2.37 0.52 1.23 54.99 17.02 0.00 0.52 8.50 11.45 0.00 4.17 0.00 0.25 2.31 0.79 1.23 67.93 17.73 0.00 0.37 4.55 5.55 0.00 1.70 0.14 0.00 2.02 0.00 1.23 70.99 13.63 0.00 0.46 4.07 4.46 0.24 0.94 0.65 0.00 4.56 0.00 1.23 73.10 15.19 0.00 0.24 3.39 4.76 0.00 1.02 0.15 0.15 1.51 0.48 1.23 67.19 22.32 0.00 0.00 1.90 5.60 0.00 0.55 0.11 0.20 1.26 0.86 1.18 77.47 19.30 0.00 0.00 1.20 1.16 0.00 0.17 0.00 0.00 0.69 0.00 1.18 80.16 18.63 0.24 0.29 0.42 0.26 0.00 0.00 0.00 0.00 0.00 0.00 1.18 57.62 22.02 0.00 2.74 1.16 0.73 0.00 0.00 7.13 0.00 8.60 0.00 1.18 42.89 24.43 0.00 0.00 1.30 30.44 0.00 0.00 0.00 0.00 0.38 0.57 1.18 41.33 27.53 0.00 0.00 1.46 28.21 0.00 0.24 0.23 0.00 1.01 0.00 1.18 42.56 22.55 0.19 0.47 8.33 18.18 0.00 2.92 0.24 0.00 4.55 0.00 1.18 58.20 14.64 0.00 0.00 0.46 25.38 0.00 0.00 0.97 0.19 0.16 0.00 1.18 30.83 38.10 0.00 0.00 16.80 5.67 0.00 0.44 0.29 0.25 7.63 0.00 1.18 45.37 30.42 0.00 0.00 12.24 8.13 0.00 0.70 0.00 0.00 3.14 0.00 1.18 52.00 19.77 0.00 0.34 9.87 9.02 0.00 1.66 0.19 0.20 6.95 0.00 1.18 50.12 26.56 0.00 0.00 6.59 9.61 0.00 0.42 0.39 0.00 6.31 0.00 1.18 58.54 17.42 0.00 0.71 6.30 6.34 0.69 1.15 2.22 0.00 6.64 0.00 1.18 69.27 18.97 0.00 0.00 5.09 5.15 0.00 0.28 0.00 0.28 0.95 0.00 1.18 56.92 22.51 0.00 1.68 4.75 5.30 0.00 0.48 4.24 0.00 4.13 0.00 1.14 17.16 47.36 0.00 0.00 32.71 2.00 0.77 0.00 0.00 0.00 0.00 0.00 1.14 20.45 43.39 0.00 0.44 31.51 2.19 0.99 0.00 0.00 0.00 0.30 0.73 1.14 45.43 32.87 0.00 0.00 20.48 0.77 0.45 0.00 0.00 0.00 0.00 0.00

220

Table A1-4 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.14 79.36 20.43 0.00 0.21 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.14 40.71 20.55 0.48 11.50 0.39 0.00 0.00 0.00 25.52 0.00 0.00 0.85 1.14 61.31 14.73 0.00 0.00 0.61 23.08 0.00 0.00 0.00 0.00 0.27 0.00 1.14 61.44 14.80 0.00 0.23 1.31 20.16 0.00 0.65 0.00 0.17 0.52 0.71 1.14 75.85 13.55 0.00 0.00 0.38 9.74 0.00 0.00 0.00 0.14 0.34 0.00 1.14 61.39 18.76 0.00 0.74 2.21 6.62 0.42 0.00 6.89 0.00 2.98 0.00 1.14 64.13 16.77 0.00 0.00 3.33 4.80 0.00 1.15 7.74 0.32 0.85 0.91 1.14 59.86 15.03 0.00 0.00 4.77 2.93 0.20 0.40 0.58 0.00 15.37 0.85 1.09 77.32 14.65 0.00 0.00 0.36 5.68 0.00 0.00 1.99 0.00 0.00 0.00 1.09 78.90 19.86 0.26 0.00 0.22 0.00 0.13 0.00 0.00 0.00 0.00 0.63 1.09 82.11 17.11 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.78 1.09 70.66 15.72 0.00 2.40 0.32 0.25 0.00 0.00 9.75 0.25 0.66 0.00 1.09 29.73 34.67 0.00 0.00 3.38 30.69 0.00 0.21 0.20 0.00 1.13 0.00 1.09 36.82 32.55 0.00 0.00 15.06 9.55 0.00 0.88 0.00 0.00 4.20 0.93 1.09 49.22 27.33 0.28 0.00 2.39 18.93 0.00 0.75 0.00 0.00 1.10 0.00 1.09 44.79 25.23 0.00 0.00 13.46 7.47 0.00 0.00 0.00 0.00 9.05 0.00 1.09 33.90 36.82 0.00 0.70 7.99 11.76 0.00 0.93 2.80 0.00 5.10 0.00 1.09 46.58 30.60 0.00 0.25 11.58 7.46 0.00 0.36 0.00 0.00 3.18 0.00 1.09 51.88 25.79 0.00 0.00 11.10 4.26 0.00 0.30 0.13 0.18 5.88 0.48 1.09 69.69 16.38 0.00 0.00 7.15 3.95 0.00 0.27 0.00 0.00 2.56 0.00 1.09 63.57 21.27 0.00 0.00 6.78 3.99 0.00 0.55 0.33 0.00 3.50 0.00 1.09 60.18 16.80 0.00 1.29 3.36 3.75 0.67 0.66 4.58 0.00 8.72 0.00 1.09 66.82 20.83 0.00 0.37 3.26 2.73 0.28 0.00 0.79 0.00 3.97 0.95 1.09 70.86 18.06 0.00 0.00 3.39 2.41 0.00 0.00 0.17 0.15 4.95 0.00 1.04 78.77 17.05 0.00 0.00 1.17 1.67 0.16 0.24 0.20 0.00 0.74 0.00 1.04 81.49 17.75 0.00 0.00 0.21 0.00 0.00 0.00 0.00 0.00 0.00 0.55 1.04 82.28 17.72 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

221

Table A1-4 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.04 79.83 20.17 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.04 47.30 24.48 0.28 0.00 3.25 23.44 0.00 0.00 0.00 0.21 1.04 0.00 1.04 59.88 12.85 0.00 0.00 0.92 24.79 0.00 0.00 0.00 0.21 0.47 0.89 1.04 42.12 25.05 0.00 0.61 9.60 14.34 0.27 4.30 0.00 0.00 3.70 0.00 1.04 56.62 19.94 0.00 0.27 1.46 18.48 0.00 0.00 2.24 0.00 0.99 0.00 1.04 49.99 23.91 0.00 0.47 8.76 10.89 0.00 3.22 0.00 0.00 2.13 0.62 1.04 56.54 25.02 0.00 0.00 6.64 6.10 0.00 1.19 0.00 0.00 3.94 0.57 1.04 63.62 16.62 0.00 0.00 5.47 4.59 0.20 0.43 0.17 0.25 7.88 0.79 1.04 69.24 19.61 0.00 0.00 3.84 4.57 0.00 1.79 0.00 0.21 0.73 0.00 1.04 61.02 20.39 0.00 0.00 3.99 3.66 0.40 0.00 3.13 0.00 6.69 0.72 1.04 59.95 22.26 0.00 0.00 2.28 3.41 0.00 0.44 9.77 0.22 1.67 0.00

222

Table A1-5. Normalised EDS data, station 4, 2-14 December 2011.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

0.73 48.62 22.82 0.00 0.00 6.52 18.68 0.00 1.68 0.00 0.00 1.66 0.00 1.54 82.32 17.68 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.57 48.00 24.22 0.31 0.33 9.87 11.99 0.00 4.18 0.00 0.13 0.97 0.00 5.3 50.00 30.45 0.00 0.00 1.22 17.17 0.00 0.43 0.00 0.00 0.73 0.00 5.42 55.82 24.88 0.00 0.32 6.83 7.35 0.00 2.70 0.21 0.18 1.72 0.00 7.76 45.35 25.75 0.00 0.67 2.05 2.09 0.00 0.68 0.00 0.00 23.42 0.00 8.37 51.56 23.47 0.00 0.00 0.96 22.93 0.00 0.27 0.00 0.25 0.57 0.00 8.89 47.55 23.55 0.00 0.00 2.20 25.17 0.00 0.78 0.00 0.00 0.74 0.00 9.92 36.40 31.45 0.00 0.00 0.64 30.59 0.19 0.00 0.13 0.19 0.41 0.00 9.97 38.31 27.23 0.00 0.00 1.28 30.57 0.00 0.28 0.35 0.27 0.95 0.78 10.66 44.57 26.84 0.00 0.26 0.82 26.95 0.00 0.00 0.00 0.23 0.34 0.00 10.87 45.12 28.52 0.00 0.32 4.87 17.50 0.00 0.55 0.31 0.00 2.82 0.00 10.93 38.63 29.92 0.00 0.00 1.99 27.40 0.00 0.68 0.16 0.15 0.35 0.72 10.93 42.91 27.84 0.00 0.00 0.83 27.23 0.00 0.24 0.19 0.24 0.54 0.00 20.82 29.97 31.99 0.00 0.00 1.19 34.27 0.00 0.20 0.19 0.33 1.02 0.85 25.24 32.99 33.12 0.00 0.00 12.60 14.24 0.21 4.89 0.00 0.36 1.60 0.00 27.98 24.75 33.02 0.00 0.40 14.10 16.63 0.00 7.09 0.00 0.00 2.93 1.08

223

Table A1-6. Normalised EDS data, station 4, 13-20 September 2012.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

33.32 27.55 39.64 0.00 0.00 15.16 13.76 0.00 0.00 0.38 0.37 3.15 0.00 27.92 38.46 34.16 0.00 0.00 13.02 11.65 0.00 0.00 0.00 0.00 2.07 0.65 27.91 33.01 32.57 0.00 0.73 9.57 16.35 0.00 2.20 0.00 0.00 5.57 0.00 26.18 23.24 34.44 0.00 1.27 13.49 17.69 0.00 6.08 0.00 0.00 3.79 0.00 24.18 29.83 32.96 0.00 0.48 12.96 15.89 0.00 6.19 0.00 0.00 1.70 0.00 22.22 34.27 26.18 0.00 0.00 7.07 4.53 0.00 0.27 0.24 0.29 27.15 0.00 20.78 26.32 37.21 0.00 0.00 0.82 34.97 0.00 0.00 0.21 0.14 0.34 0.00 19.75 28.99 33.86 0.00 0.68 13.56 15.23 0.00 6.39 0.00 0.00 1.28 0.00 19.67 23.66 34.51 0.40 0.00 17.69 18.55 0.00 3.75 0.00 0.00 1.45 0.00 19.36 21.13 38.63 0.00 1.14 12.86 16.93 0.00 6.04 0.00 0.00 3.27 0.00 18.85 37.03 28.68 0.00 0.52 12.19 14.36 0.00 5.60 0.00 0.00 0.99 0.63 17.92 28.01 31.99 0.00 0.72 13.60 16.38 0.41 6.41 0.49 0.40 1.58 0.00 17.66 33.58 30.14 0.00 0.41 12.63 13.85 0.00 4.94 0.00 0.00 4.45 0.00 17.57 29.02 31.56 0.00 0.65 13.74 16.93 0.00 6.78 0.00 0.00 1.33 0.00 17.42 30.17 36.26 0.00 0.00 16.14 14.49 0.00 0.00 0.22 0.00 2.71 0.00 17.05 22.59 39.82 0.00 0.00 0.45 36.39 0.00 0.00 0.00 0.29 0.45 0.00 16.14 32.14 36.33 0.00 0.00 15.10 14.51 0.00 0.00 0.00 0.00 1.92 0.00 15.67 17.42 42.11 1.12 2.98 15.66 15.04 0.00 0.00 0.00 0.00 5.68 0.00 15.4 35.85 32.06 0.00 10.33 1.45 1.31 0.00 0.00 18.29 0.00 0.71 0.00 15.33 26.75 38.67 0.00 0.00 16.16 15.40 0.00 0.00 0.00 0.00 3.02 0.00 13.94 40.92 32.89 0.00 0.38 10.01 10.78 0.00 3.21 0.00 0.00 1.83 0.00 13.72 39.95 31.86 0.36 0.43 10.50 11.43 0.26 3.32 0.00 0.00 1.89 0.00 13.34 31.13 31.27 0.00 0.69 13.12 14.54 0.50 5.06 0.00 0.00 2.49 1.20 13 40.68 25.22 0.00 0.00 12.68 15.02 0.00 5.33 0.00 0.00 1.07 0.00 12.8 50.34 25.74 0.00 0.46 8.33 9.64 0.00 3.87 0.00 0.00 1.17 0.47 12.62 35.62 34.85 0.00 2.48 6.15 6.04 0.00 0.48 2.40 0.29 11.70 0.00 12.6 46.74 28.09 0.30 0.53 9.19 10.61 0.00 3.73 0.00 0.00 0.80 0.00

224

Table A1-6 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

12.58 58.87 23.14 0.00 0.31 6.46 7.49 0.00 3.00 0.00 0.00 0.73 0.00 12.54 37.26 28.46 0.00 0.43 12.65 14.39 0.00 5.47 0.00 0.00 1.35 0.00 12.33 33.26 33.06 0.00 0.00 1.19 31.10 0.00 0.27 0.19 0.17 0.76 0.00 12.32 35.77 30.31 0.00 0.69 12.02 14.22 0.24 5.05 0.00 0.00 1.21 0.49 11.73 43.99 33.26 0.00 0.38 8.26 8.89 0.00 3.47 0.14 0.17 1.44 0.00 11.22 45.07 29.43 0.00 0.41 6.03 15.25 0.00 2.39 0.21 0.00 1.22 0.00 11.22 42.52 27.28 0.00 0.42 4.10 19.81 0.39 1.72 0.39 0.22 1.97 1.18 10.37 30.12 33.58 0.00 0.00 0.54 35.30 0.00 0.00 0.00 0.00 0.45 0.00 10.3 32.70 32.69 0.00 0.57 11.39 15.51 0.00 5.02 0.00 0.00 1.26 0.86 10.16 43.48 26.14 0.00 0.32 12.66 12.80 0.00 2.90 0.00 0.00 1.71 0.00 9.95 39.11 29.19 0.00 0.00 13.36 10.82 0.00 1.48 0.00 0.00 6.04 0.00 9.83 48.76 30.52 0.00 7.45 0.40 0.26 0.00 0.00 12.32 0.00 0.30 0.00 9.57 56.54 22.17 0.00 0.26 8.10 8.42 0.00 2.59 0.18 0.14 1.05 0.56 9.5 42.77 31.35 0.00 0.00 9.76 11.11 0.00 3.65 0.00 0.00 1.37 0.00 9.24 43.05 34.20 0.00 0.00 11.59 8.18 0.00 0.28 0.15 0.00 2.55 0.00 9.2 45.25 26.09 0.00 0.53 7.99 12.51 0.23 3.78 0.00 0.00 2.94 0.69 9.2 52.12 24.91 0.00 0.43 7.62 9.93 0.00 3.38 0.00 0.00 1.11 0.51 9.06 57.69 24.82 0.00 0.00 6.98 7.14 0.00 2.43 0.00 0.00 0.94 0.00 9.01 43.44 34.93 0.00 0.27 9.18 9.16 0.00 1.20 0.00 0.00 0.95 0.88 8.91 48.99 25.70 0.00 0.00 0.98 23.76 0.00 0.00 0.00 0.00 0.57 0.00 8.86 44.22 28.50 0.00 0.00 11.42 9.49 0.00 1.72 0.00 0.00 4.65 0.00 8.85 44.97 26.30 0.00 0.33 10.53 12.08 0.00 3.85 0.00 0.00 1.94 0.00 8.68 51.70 27.70 0.70 1.43 8.06 7.28 0.00 0.00 0.00 0.00 3.13 0.00 8.67 49.43 24.23 0.00 0.00 10.52 9.23 0.20 0.89 0.00 0.00 5.50 0.00 8.65 52.33 25.21 0.00 0.37 7.79 8.63 0.00 2.92 0.00 0.00 2.74 0.00 8.55 52.73 22.84 0.00 0.00 1.99 21.43 0.00 0.42 0.00 0.00 0.59 0.00 8.54 33.32 32.54 0.00 0.00 13.01 14.22 0.00 4.32 0.00 0.00 2.10 0.49

225

Table A1-6 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

8.54 55.30 25.68 0.00 0.30 6.72 7.49 0.00 2.62 0.00 0.00 0.95 0.94 8.5 61.47 22.17 0.00 0.75 2.62 2.31 3.24 0.23 0.00 0.00 7.21 0.00 8.12 48.11 27.22 0.00 0.00 11.39 5.56 0.00 0.18 0.19 0.00 7.35 0.00 8.06 39.34 23.36 0.00 0.54 14.05 15.18 0.00 5.40 0.33 0.42 1.37 0.00 7.89 50.55 22.29 0.00 0.51 9.62 10.75 0.00 2.94 0.00 0.00 2.70 0.64 7.83 49.70 26.73 0.00 5.49 1.11 1.40 0.00 0.00 7.54 3.88 4.15 0.00 7.75 48.16 28.69 0.00 3.81 0.00 0.00 1.97 12.57 3.87 0.00 0.35 0.58 7.74 55.59 23.87 0.00 0.00 1.49 16.79 0.00 0.17 0.00 0.14 1.93 0.00 7.68 42.93 27.13 0.00 1.10 1.48 2.05 0.00 0.00 24.01 0.00 1.30 0.00 7.66 41.75 24.16 0.00 0.44 11.16 9.60 0.21 1.97 0.00 0.00 9.79 0.92 7.57 43.06 26.84 0.00 0.52 10.75 12.48 0.00 5.02 0.00 0.00 1.33 0.00 7.52 53.77 21.35 0.00 0.64 7.55 9.58 0.00 2.21 0.00 0.00 4.05 0.84 7.47 50.17 24.93 0.00 0.00 1.22 22.18 0.00 0.19 0.22 0.14 0.95 0.00 7.46 43.07 28.56 0.00 0.00 3.07 3.40 0.00 0.00 21.91 0.00 0.00 0.00 7.35 43.53 26.88 0.00 0.00 2.59 25.36 0.00 0.38 0.00 0.00 1.26 0.00 7.33 51.33 28.90 0.00 0.34 7.29 5.61 0.21 0.73 1.21 0.00 4.38 0.00 7.31 60.99 22.74 0.00 0.39 5.36 6.08 0.00 2.56 0.56 0.27 1.06 0.00 7.3 56.58 26.69 0.00 0.28 6.00 6.44 0.00 2.80 0.16 0.17 0.87 0.00 7.2 53.15 27.36 0.00 0.00 0.34 18.59 0.00 0.13 0.00 0.15 0.28 0.00 7.11 54.89 24.47 0.00 0.23 0.42 19.22 0.15 0.18 0.00 0.21 0.25 0.00 6.84 44.91 31.60 0.00 0.44 8.35 9.69 0.00 3.67 0.00 0.00 1.33 0.00 6.84 49.00 31.05 0.00 0.00 0.23 19.05 0.00 0.00 0.11 0.24 0.31 0.00 6.74 51.03 24.44 0.00 0.00 0.44 23.21 0.00 0.00 0.16 0.27 0.46 0.00 6.73 54.00 23.60 0.00 0.45 8.25 9.12 0.00 3.47 0.00 0.00 1.11 0.00 6.72 56.85 20.69 0.00 0.00 1.61 18.43 0.00 0.28 0.11 0.17 1.87 0.00 6.62 51.61 24.38 0.00 0.00 0.86 21.87 0.00 0.22 0.29 0.14 0.65 0.00 6.61 63.51 14.14 0.00 0.00 2.96 2.28 0.18 0.00 0.00 0.24 16.22 0.47 6.55 84.36 15.64 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

226

Table A1-6 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

6.37 40.29 31.53 0.29 0.67 10.13 11.69 0.00 4.15 0.00 0.13 1.11 0.00 6.35 45.38 16.97 0.00 0.00 5.37 4.12 0.00 0.25 0.37 0.27 27.26 0.00 6.22 44.19 28.54 0.00 0.00 1.12 25.18 0.15 0.28 0.00 0.00 0.53 0.00 6.1 48.87 34.22 1.01 1.13 6.14 4.97 0.36 0.58 0.00 0.00 2.72 0.00 6.04 46.73 25.48 0.00 0.00 2.16 22.60 0.00 0.25 0.24 0.21 2.34 0.00 5.82 47.52 21.97 0.00 0.81 8.94 10.37 0.00 4.02 0.00 0.26 6.10 0.00 5.78 45.85 29.87 0.00 8.73 0.00 0.00 0.00 0.00 14.00 0.00 0.59 0.96 5.78 65.19 21.46 0.00 0.00 5.37 4.82 0.00 1.29 0.00 0.00 1.88 0.00 5.77 57.13 10.81 0.00 0.00 0.47 0.32 0.00 0.00 0.00 0.30 30.96 0.00 5.65 52.50 25.03 0.00 0.39 5.57 11.79 0.00 1.14 0.72 0.00 2.86 0.00 5.51 59.69 18.25 0.00 0.31 7.71 9.70 0.19 2.41 0.00 0.00 1.22 0.52 5.49 45.07 24.47 0.00 10.60 0.00 0.00 0.00 0.00 18.85 0.00 0.00 1.00 5.49 58.77 24.80 0.00 0.00 6.73 6.09 0.00 1.11 0.19 0.13 2.18 0.00 5.47 66.01 19.47 0.00 0.26 5.39 5.84 0.00 2.03 0.15 0.00 0.84 0.00 5.44 44.74 26.00 0.00 0.23 1.25 25.61 0.00 0.40 0.16 0.28 0.71 0.62 5.4 48.23 24.55 0.00 0.00 1.25 24.71 0.00 0.25 0.00 0.21 0.80 0.00 5.34 54.33 28.87 0.00 0.00 0.00 16.50 0.00 0.00 0.00 0.10 0.19 0.00 5.28 48.96 23.67 0.00 0.00 0.51 26.23 0.00 0.00 0.30 0.00 0.33 0.00 5.2 50.55 22.53 4.43 0.00 5.86 16.63 0.00 0.00 0.00 0.00 0.00 0.00 5.13 60.15 23.22 0.00 6.05 0.56 0.42 0.00 0.00 8.95 0.17 0.48 0.00 5.04 64.59 12.78 0.00 0.31 3.32 3.07 0.00 0.73 0.00 0.00 14.58 0.62 5.01 49.90 24.51 0.00 0.00 0.46 0.72 0.68 0.00 23.03 0.00 0.00 0.70 4.94 68.86 19.50 0.17 0.16 0.31 10.27 0.00 0.00 0.00 0.12 0.60 0.00 4.77 45.80 27.56 0.00 0.00 0.00 0.42 11.32 0.00 14.10 0.00 0.00 0.80 4.67 70.08 15.14 0.00 0.00 0.90 12.79 0.00 0.00 0.00 0.31 0.77 0.00 4.65 46.57 19.16 0.00 0.42 12.60 14.26 0.00 4.99 0.00 0.00 1.22 0.77 4.62 56.19 21.89 0.00 0.00 8.07 9.14 0.00 3.51 0.00 0.17 1.03 0.00 4.59 64.51 22.02 0.00 0.00 7.90 1.35 0.00 0.15 0.00 0.19 3.87 0.00

227

Table A1-6 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

4.46 63.31 25.15 0.00 0.00 4.46 4.54 0.00 1.75 0.00 0.00 0.80 0.00 4.43 58.99 13.63 0.00 0.00 0.64 1.24 3.50 0.00 18.35 0.00 3.65 0.00 4.4 45.27 26.54 0.00 0.00 1.83 25.01 0.00 0.00 0.38 0.00 0.97 0.00 4.37 53.69 20.01 0.00 0.00 1.42 24.15 0.00 0.53 0.00 0.00 0.21 0.00 4.36 41.83 28.96 0.00 9.26 1.63 1.59 0.00 0.39 15.96 0.00 0.38 0.00 4.31 53.64 24.00 0.00 0.00 7.48 7.85 0.00 2.58 0.20 0.00 4.24 0.00 4.27 63.28 13.28 0.00 0.58 7.46 9.50 0.40 4.14 0.00 0.00 1.35 0.00 4.16 35.57 32.49 0.83 0.84 3.19 3.93 0.72 0.45 20.57 0.57 0.84 0.00 4.13 60.31 22.17 0.00 0.00 0.53 16.45 0.00 0.00 0.21 0.14 0.19 0.00 4.13 39.59 29.83 0.00 0.00 0.50 28.83 0.00 0.14 0.00 0.00 0.45 0.65 4.06 63.62 13.88 0.00 0.32 7.95 9.58 0.00 3.92 0.00 0.00 0.72 0.00 4.04 75.54 19.56 0.00 0.00 1.84 1.95 0.00 0.71 0.00 0.00 0.40 0.00 4.04 53.07 21.50 0.00 0.00 10.50 8.21 0.00 0.95 0.00 0.00 5.20 0.57 4.03 66.80 18.83 0.26 0.00 0.97 0.94 5.47 0.00 6.73 0.00 0.00 0.00 4 52.53 25.80 0.00 0.00 7.86 7.08 0.00 0.66 0.00 0.00 5.21 0.86 3.99 53.36 22.30 0.00 0.00 1.27 22.35 0.00 0.00 0.00 0.00 0.73 0.00 3.96 52.70 18.27 0.00 0.51 9.65 9.21 0.00 1.36 0.26 0.28 7.76 0.00 3.96 59.28 22.63 0.00 0.00 8.44 6.62 0.00 0.20 0.00 0.16 2.67 0.00 3.95 54.27 23.57 0.00 0.00 1.69 19.13 0.00 0.17 0.00 0.17 0.99 0.00 3.92 81.90 18.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.92 62.25 20.41 0.00 0.35 1.56 1.73 0.00 0.00 12.49 0.00 0.00 1.21 3.89 51.13 27.38 0.00 0.00 1.51 19.21 0.00 0.00 0.14 0.14 0.49 0.00 3.87 35.85 30.74 0.00 0.00 14.40 11.38 0.00 1.44 0.00 0.00 6.19 0.00 3.82 53.73 26.97 0.00 0.00 6.98 8.39 0.33 2.86 0.00 0.00 0.74 0.00 3.78 60.47 18.76 0.00 0.00 5.26 5.31 0.00 0.84 0.45 0.00 8.04 0.87 3.78 66.13 16.73 0.00 0.37 4.59 8.40 0.00 1.45 0.47 0.00 1.85 0.00 3.77 71.62 18.74 0.00 0.00 3.35 3.76 0.00 1.49 0.15 0.16 0.72 0.00 3.75 59.00 21.78 0.00 0.32 0.68 1.01 0.00 0.00 16.66 0.00 0.00 0.55

228

Table A1-6 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

3.72 56.38 19.05 0.00 0.56 8.14 9.77 0.00 1.83 0.00 0.00 3.29 0.98 3.71 58.28 17.18 0.00 0.27 8.79 10.74 0.00 3.52 0.00 0.00 1.22 0.00 3.64 56.76 24.71 0.00 0.00 8.31 4.98 0.00 0.40 0.00 0.00 4.84 0.00 3.59 65.46 19.76 0.00 2.69 2.30 2.04 0.00 0.27 5.63 0.17 1.67 0.00 3.59 39.52 27.32 0.00 0.00 13.62 10.43 0.00 1.36 0.00 0.00 7.10 0.65 3.47 82.52 17.48 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.47 44.62 23.54 0.00 0.56 11.28 13.24 0.27 5.11 0.00 0.00 1.38 0.00 3.45 60.98 25.95 0.00 0.26 5.41 5.30 0.00 1.42 0.00 0.00 0.68 0.00 3.39 48.47 21.89 0.00 0.00 1.39 27.26 0.00 0.00 0.00 0.00 0.98 0.00 3.38 59.69 18.23 0.00 0.47 7.95 8.45 0.00 2.16 0.24 0.00 2.81 0.00 3.33 72.18 17.44 0.00 0.00 0.00 9.71 0.00 0.00 0.00 0.23 0.43 0.00 3.31 52.36 23.56 0.00 0.40 8.59 9.77 0.00 3.32 0.00 0.00 2.00 0.00 3.31 51.50 24.21 0.00 0.00 8.26 11.79 0.00 0.89 0.00 0.00 3.34 0.00 3.31 67.16 16.50 0.00 0.23 5.04 5.04 0.00 1.14 0.00 0.00 4.89 0.00 3.25 70.40 18.52 0.24 0.00 3.53 4.91 0.00 1.44 0.00 0.00 0.96 0.00 3.23 72.35 19.79 0.00 0.00 1.43 1.27 0.00 0.42 0.15 0.22 4.38 0.00 3.2 61.58 20.30 0.00 0.00 3.01 2.12 0.00 0.25 0.44 0.00 12.30 0.00 3.13 56.72 20.15 0.00 0.41 8.83 9.57 0.00 3.33 0.00 0.16 0.83 0.00 3.11 53.84 19.28 0.00 0.00 2.79 20.81 0.00 0.46 0.14 0.00 2.67 0.00 3.08 57.25 19.26 0.00 0.00 8.90 9.10 0.00 2.06 0.00 0.00 3.44 0.00 3.08 65.68 17.35 0.00 0.00 6.12 7.79 0.00 2.34 0.00 0.00 0.72 0.00 3.08 69.22 10.22 0.00 0.00 0.35 19.31 0.41 0.00 0.50 0.00 0.00 0.00 3.04 80.05 19.76 0.00 0.00 0.00 0.19 0.00 0.00 0.00 0.00 0.00 0.00 3.04 55.12 18.92 0.00 0.37 9.90 10.67 0.00 3.11 0.00 0.00 1.92 0.00 3 55.54 27.93 0.00 6.05 0.73 0.46 0.00 0.00 8.88 0.00 0.41 0.00 2.99 58.81 18.05 0.00 0.43 8.06 9.66 0.00 3.99 0.00 0.00 1.01 0.00 2.97 56.68 15.25 0.00 0.00 0.70 26.67 0.00 0.00 0.00 0.20 0.49 0.00 2.95 78.58 15.49 0.00 0.22 0.23 0.28 2.51 0.00 2.68 0.00 0.00 0.00

229

Table A1-6 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

2.95 49.46 25.18 0.00 0.00 3.97 2.59 0.00 0.49 0.22 0.00 17.54 0.55 2.91 64.72 13.95 0.25 0.00 0.34 19.28 0.00 0.00 0.14 0.21 0.18 0.91 2.9 65.35 26.61 0.00 0.00 3.58 2.38 0.00 0.70 0.14 0.17 1.08 0.00 2.9 70.50 18.94 0.00 0.00 2.76 3.87 0.00 0.63 0.17 0.23 2.89 0.00 2.86 49.73 28.84 0.00 0.00 9.10 7.46 0.00 1.05 0.00 0.00 3.83 0.00 2.8 51.65 20.96 0.00 0.54 8.96 11.83 0.00 4.30 0.13 0.18 1.46 0.00 2.8 66.00 13.22 0.00 0.00 8.41 7.20 0.00 1.60 0.00 0.00 3.57 0.00 2.76 73.97 19.94 0.00 0.00 2.24 1.73 0.00 0.00 0.66 0.00 1.46 0.00 2.76 62.58 14.32 0.00 0.00 8.22 8.99 0.00 2.41 0.00 0.00 2.76 0.73 2.76 68.76 20.19 0.00 0.00 4.13 4.65 0.00 1.67 0.00 0.00 0.59 0.00 2.74 56.26 22.72 0.27 0.37 7.57 8.71 0.00 3.32 0.00 0.00 0.76 0.00 2.72 71.50 10.25 0.00 0.00 6.81 7.21 0.00 3.24 0.00 0.00 0.49 0.50 2.72 73.98 16.83 0.00 0.00 3.56 3.04 0.00 0.42 0.00 0.00 2.17 0.00 2.7 78.61 21.39 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.7 75.97 17.46 0.28 2.66 0.00 0.00 3.63 0.00 0.00 0.00 0.00 0.00 2.66 69.07 16.59 0.00 0.00 5.09 5.96 0.00 2.33 0.14 0.16 0.66 0.00 2.66 71.03 17.17 0.00 0.00 4.84 4.49 0.00 0.16 0.25 0.00 2.06 0.00 2.64 60.38 19.35 0.00 0.46 5.97 6.28 0.00 0.67 0.25 0.61 6.02 0.00 2.62 64.33 21.14 0.00 0.00 1.86 1.04 2.52 0.00 8.67 0.00 0.44 0.00 2.58 54.51 13.67 0.00 0.56 8.23 9.38 2.79 4.39 0.00 0.00 6.47 0.00 2.58 75.32 15.93 0.00 0.29 1.44 2.44 0.00 0.19 2.07 0.00 2.32 0.00 2.56 54.78 19.69 0.00 0.00 8.99 7.79 0.00 1.23 1.16 0.00 6.36 0.00 2.56 62.74 12.98 0.00 0.32 4.83 9.83 0.00 1.08 0.31 0.00 7.91 0.00 2.56 73.44 14.24 0.00 0.00 3.32 2.47 0.00 0.30 0.19 0.25 5.79 0.00 2.56 72.66 20.78 0.00 0.00 0.00 5.68 0.00 0.00 0.32 0.21 0.34 0.00 2.54 83.21 16.48 0.00 0.00 0.00 0.18 0.13 0.00 0.00 0.00 0.00 0.00 2.54 66.52 15.86 0.00 0.00 8.60 8.11 0.00 0.00 0.00 0.00 0.92 0.00

230

Table A1-6 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

2.54 69.34 9.93 0.00 0.00 6.57 7.57 0.00 3.14 0.26 0.39 2.79 0.00 2.54 67.28 19.13 0.28 0.00 5.30 3.60 0.00 0.76 0.20 0.19 2.72 0.53 2.54 56.24 26.43 0.00 0.00 1.72 14.34 0.00 0.79 0.00 0.00 0.47 0.00 2.52 51.55 19.68 0.00 0.00 4.02 4.33 1.25 0.51 17.25 0.00 1.41 0.00 2.5 81.57 18.10 0.33 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.48 58.82 16.51 0.30 0.00 8.35 8.56 0.00 2.24 0.00 0.00 4.37 0.84 2.43 73.73 15.10 0.00 0.00 3.83 4.28 0.00 1.48 0.13 0.20 1.25 0.00 2.41 57.79 19.40 0.00 6.59 1.79 0.00 0.00 0.00 13.75 0.00 0.68 0.00 2.41 63.73 18.88 0.00 0.00 0.74 15.58 0.00 0.00 0.32 0.24 0.51 0.00 2.41 74.05 12.74 0.00 0.00 0.31 12.61 0.29 0.00 0.00 0.00 0.00 0.00 2.39 65.53 16.19 1.87 0.00 4.47 11.00 0.00 0.53 0.00 0.21 0.20 0.00 2.39 65.35 26.53 0.00 0.48 2.21 2.49 0.00 0.25 1.27 0.00 1.41 0.00 2.36 53.32 23.28 0.00 0.00 9.57 10.00 0.00 2.34 0.00 0.00 1.49 0.00 2.36 56.53 19.71 0.00 0.00 8.66 6.89 0.00 1.12 0.21 0.19 6.69 0.00 2.36 57.52 21.61 0.00 0.00 7.55 6.48 0.17 1.24 0.32 0.00 5.11 0.00 2.36 69.10 10.65 0.00 0.30 5.51 9.93 0.00 2.55 0.00 0.00 1.96 0.00 2.34 53.65 23.85 0.00 0.00 10.14 9.13 0.00 0.17 0.22 0.24 1.47 1.15 2.32 69.80 15.41 0.00 0.44 5.09 5.51 0.00 1.50 0.17 0.00 2.08 0.00 2.29 86.17 13.54 0.29 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.29 74.28 17.86 0.00 0.00 3.99 2.48 0.00 0.25 0.00 0.00 1.14 0.00 2.29 76.02 18.15 0.00 0.00 2.10 2.23 0.00 0.82 0.12 0.17 0.39 0.00 2.27 79.43 15.58 0.31 0.00 0.60 0.83 1.09 0.83 0.72 0.18 0.43 0.00 2.25 67.98 19.16 0.00 0.00 0.89 1.13 0.00 0.00 10.85 0.00 0.00 0.00 2.22 40.31 25.70 0.00 0.38 12.64 14.48 0.00 5.04 0.00 0.00 1.45 0.00 2.22 57.97 15.16 0.00 0.00 2.27 20.91 0.00 0.25 0.00 0.27 2.40 0.77 2.2 44.05 28.62 0.00 0.00 11.05 11.56 0.00 0.61 0.00 0.00 3.56 0.56 2.2 43.80 23.17 0.00 0.51 11.02 13.68 0.32 5.84 0.00 0.00 1.65 0.00 2.2 53.25 21.43 0.00 0.00 10.34 7.85 0.00 0.80 0.00 0.00 5.74 0.60

231

Table A1-6 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

2.2 66.97 21.11 0.00 0.00 4.09 4.67 0.00 1.59 0.11 0.23 1.23 0.00 2.17 63.05 10.39 0.00 0.00 9.28 10.83 0.00 4.98 0.00 0.00 1.47 0.00 2.17 67.81 18.63 0.00 0.28 4.95 4.94 0.00 1.56 0.56 0.00 1.28 0.00 2.17 64.72 19.62 0.00 0.40 4.77 7.44 0.00 1.97 0.00 0.00 1.08 0.00 2.15 52.38 27.11 0.00 0.00 0.34 0.26 0.00 0.00 19.89 0.00 0.00 0.00 2.15 57.38 19.61 0.27 0.30 8.70 9.73 0.00 2.68 0.00 0.00 0.75 0.58 2.15 71.23 14.45 0.24 0.26 5.39 5.08 0.00 1.39 0.00 0.00 1.97 0.00 2.15 67.44 18.38 0.00 0.00 3.67 8.26 0.00 1.58 0.00 0.00 0.67 0.00 2.12 81.12 18.56 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.31 0.00 2.12 67.74 20.54 0.00 1.96 2.08 2.53 0.75 0.00 3.19 0.00 1.21 0.00 2.12 54.96 24.57 0.00 0.00 10.16 4.99 0.00 0.00 0.00 0.00 5.32 0.00 2.12 63.88 12.92 0.00 0.00 1.88 20.34 0.00 0.27 0.00 0.19 0.52 0.00 2.1 82.20 15.74 0.00 0.00 0.47 0.00 0.29 0.00 0.93 0.11 0.25 0.00 2.07 77.52 20.22 0.00 0.23 0.67 0.39 0.00 0.00 0.00 0.00 0.29 0.68 2.07 59.25 18.47 0.00 0.00 10.68 9.72 0.00 0.00 0.00 0.19 1.69 0.00 2.07 70.90 16.32 0.00 0.00 5.17 5.71 0.41 0.19 0.00 0.18 1.12 0.00 2.05 56.71 16.27 0.00 0.00 10.09 10.77 0.00 3.19 0.00 0.00 2.97 0.00 2.05 56.14 16.77 0.00 0.47 9.74 11.06 0.00 4.33 0.00 0.00 0.96 0.51 2.05 62.42 16.19 0.00 0.00 7.75 7.92 0.00 2.73 0.00 0.00 2.52 0.47 2.02 75.84 17.47 0.00 0.25 2.81 2.18 0.00 0.38 0.00 0.00 1.06 0.00 1.99 60.23 18.71 0.00 0.00 10.01 9.09 0.00 0.00 0.00 0.00 1.47 0.50 1.99 57.80 14.89 0.00 0.31 7.94 9.64 0.00 2.95 0.00 0.00 6.47 0.00 1.99 62.91 21.89 0.00 0.00 6.30 5.91 0.00 0.40 0.19 0.12 2.28 0.00 1.99 72.83 14.00 0.00 0.32 4.63 5.44 0.00 1.95 0.00 0.00 0.83 0.00 1.99 61.88 22.18 0.52 0.00 3.65 4.45 0.00 0.00 5.21 0.00 2.12 0.00 1.97 62.59 12.56 0.00 0.00 8.43 9.25 0.00 3.73 0.46 0.20 2.79 0.00 1.97 55.55 27.25 0.55 0.79 6.37 5.52 0.00 0.20 0.11 0.15 3.51 0.00 1.97 75.33 13.42 0.00 0.00 2.04 2.39 2.76 0.76 0.00 0.00 3.30 0.00

232

Table A1-6 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.94 86.28 13.47 0.00 0.00 0.25 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.94 52.89 19.90 0.21 0.20 0.60 25.55 0.00 0.17 0.00 0.16 0.31 0.00 1.88 87.16 11.98 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.86 1.88 58.01 25.72 0.00 0.00 0.00 0.00 0.00 0.00 16.27 0.00 0.00 0.00 1.88 56.40 16.43 0.00 0.48 9.65 10.93 0.00 4.64 0.15 0.21 1.11 0.00 1.85 20.40 39.47 0.00 0.00 18.45 17.37 0.00 0.31 0.42 0.27 2.67 0.64 1.85 52.91 24.02 0.00 0.00 9.78 7.43 0.00 0.48 0.00 0.00 5.37 0.00 1.85 62.08 22.97 0.00 0.00 6.69 3.76 0.00 0.31 0.12 0.00 4.05 0.00 1.83 45.95 22.56 0.00 0.00 3.03 4.25 0.00 0.00 23.45 0.00 0.75 0.00 1.83 77.91 12.76 0.00 0.26 2.54 3.56 0.00 0.64 0.21 0.00 2.11 0.00 1.8 80.49 18.42 0.00 0.00 0.72 0.37 0.00 0.00 0.00 0.00 0.00 0.00 1.8 54.97 18.29 0.00 0.00 2.13 21.93 0.00 0.94 0.35 0.18 1.22 0.00 1.8 65.98 12.08 0.00 0.40 1.88 17.05 0.30 0.79 0.00 0.00 1.52 0.00 1.77 65.48 12.66 0.00 0.29 5.14 12.16 0.00 2.57 0.00 0.00 1.10 0.59 1.77 70.30 11.25 0.00 0.47 3.58 11.10 0.00 1.69 0.30 0.00 1.31 0.00 1.77 62.30 24.02 0.00 0.00 0.26 1.12 5.39 0.16 6.52 0.00 0.22 0.00 1.73 78.77 15.82 0.00 0.00 2.03 1.26 0.00 0.29 0.20 0.27 1.35 0.00 1.73 86.02 13.51 0.00 0.00 0.00 0.00 0.20 0.15 0.11 0.00 0.00 0.00 1.73 74.19 20.36 0.00 0.00 2.56 2.09 0.00 0.00 0.00 0.00 0.80 0.00 1.7 84.93 14.24 0.27 0.19 0.19 0.18 0.00 0.00 0.00 0.00 0.00 0.00 1.7 37.26 14.88 0.42 0.72 5.84 8.38 0.69 0.00 29.94 0.00 0.95 0.92 1.7 24.80 39.85 0.00 0.00 16.73 15.63 0.00 0.32 0.31 0.00 2.34 0.00 1.7 50.35 19.29 0.00 0.31 10.73 11.78 0.00 3.17 0.22 0.00 3.58 0.55 1.67 59.50 20.44 0.00 0.00 10.17 4.02 0.00 0.26 0.25 0.28 5.08 0.00 1.67 55.03 18.93 0.00 0.49 9.13 10.90 0.00 4.18 0.00 0.00 1.33 0.00 1.64 82.34 17.66 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.64 57.22 19.53 0.00 0.00 2.60 3.82 0.00 0.00 16.83 0.00 0.00 0.00 1.64 59.61 15.61 0.00 0.48 8.43 9.08 0.00 2.21 0.00 0.00 4.58 0.00

233

Table A1-6 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.64 70.86 11.67 0.00 0.00 6.53 6.91 0.00 3.43 0.00 0.00 0.59 0.00 1.61 78.97 17.73 0.00 0.00 1.48 1.42 0.00 0.40 0.00 0.00 0.00 0.00 1.61 74.59 12.36 0.00 0.00 3.89 7.00 0.00 1.72 0.00 0.00 0.44 0.00 1.57 81.00 16.94 0.00 0.00 0.55 0.31 0.00 0.00 0.00 0.00 1.20 0.00 1.57 79.63 18.54 0.00 0.00 0.30 0.30 0.00 0.00 0.00 0.00 0.00 1.22 1.57 69.94 18.24 0.00 0.00 1.26 1.65 0.21 0.18 8.22 0.00 0.30 0.00 1.57 40.76 28.69 0.00 0.49 11.16 14.21 0.00 3.48 0.00 0.00 1.21 0.00 1.57 58.81 21.44 0.00 0.00 7.51 7.82 0.00 1.16 0.22 0.00 3.04 0.00 1.57 65.32 14.34 0.26 0.24 6.15 9.17 0.00 0.98 0.15 0.21 2.71 0.48 1.57 68.69 13.35 0.00 0.00 5.21 10.50 0.00 1.54 0.00 0.00 0.70 0.00 1.57 66.93 21.20 0.00 0.00 4.68 5.15 0.00 1.56 0.00 0.00 0.48 0.00 1.57 49.19 18.80 0.00 0.38 4.67 22.90 0.00 1.07 0.00 0.00 2.98 0.00 1.54 82.93 17.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.54 50.71 22.98 0.00 0.00 1.54 1.74 0.00 0.00 22.27 0.28 0.47 0.00 1.54 69.23 19.85 0.00 0.00 5.78 2.11 0.00 0.27 0.00 0.20 2.57 0.00 1.54 71.44 14.94 0.00 0.00 4.55 5.58 0.00 2.03 0.00 0.00 0.37 1.08 1.5 77.52 19.61 0.00 0.00 0.91 0.93 0.00 0.39 0.10 0.24 0.28 0.00 1.5 75.19 21.24 0.00 0.71 0.76 1.11 0.00 0.21 0.14 0.14 0.50 0.00 1.5 79.03 20.97 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.5 83.97 16.03 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.5 57.83 18.43 0.00 0.28 9.45 10.29 0.00 2.20 0.00 0.00 1.52 0.00 1.5 66.25 18.63 0.00 0.00 8.32 3.69 0.00 0.49 0.24 0.18 1.63 0.59 1.5 61.15 18.66 0.00 0.00 8.00 8.06 0.00 1.90 0.00 0.00 1.02 1.21 1.5 62.12 13.33 0.00 0.74 7.43 7.84 0.00 1.94 0.00 0.00 6.02 0.58 1.5 63.41 19.97 0.00 0.00 7.10 5.69 0.00 1.18 0.00 0.00 2.65 0.00 1.5 62.77 18.42 0.00 0.28 6.90 7.60 0.00 2.84 0.00 0.00 1.19 0.00 1.5 70.06 13.46 0.00 0.00 6.04 6.42 0.14 1.64 0.00 0.00 1.76 0.48 1.5 63.39 17.63 0.00 0.43 4.71 3.26 0.64 0.56 0.73 0.00 8.65 0.00

234

Table A1-6 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.5 75.38 17.94 0.00 0.34 2.28 2.01 0.00 0.00 0.26 0.00 1.79 0.00 1.47 79.03 17.33 0.00 0.00 1.31 1.33 0.00 0.00 0.00 0.00 0.00 1.01 1.47 43.42 27.27 0.00 0.41 10.50 11.06 0.00 3.40 0.23 0.22 3.51 0.00 1.47 65.40 13.29 0.00 0.00 7.84 9.16 0.00 3.54 0.00 0.00 0.78 0.00 1.47 60.90 16.95 0.22 0.00 0.20 18.78 1.31 0.00 1.62 0.00 0.00 0.00 1.43 81.00 17.15 0.00 0.00 0.71 0.47 0.00 0.00 0.14 0.17 0.35 0.00 1.43 82.11 17.89 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.43 83.58 16.42 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.43 79.91 19.32 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.77 1.43 68.12 17.88 0.00 3.23 1.83 1.48 0.00 0.39 5.33 0.21 1.53 0.00 1.43 35.15 33.60 0.00 0.29 14.26 13.54 0.00 0.21 0.31 0.00 2.64 0.00 1.43 70.13 18.65 0.00 0.00 4.60 4.37 0.00 1.13 0.00 0.00 1.12 0.00 1.39 78.74 19.29 0.00 0.00 0.65 0.49 0.00 0.00 0.00 0.00 0.82 0.00 1.39 74.79 17.01 0.00 0.00 0.00 0.38 0.72 0.00 0.25 0.40 6.45 0.00 1.39 51.04 22.03 0.00 0.00 0.53 0.68 0.00 0.00 25.28 0.00 0.43 0.00 1.39 20.03 39.54 0.00 0.43 18.71 18.06 0.00 0.28 0.35 0.00 2.61 0.00 1.39 23.91 36.59 0.00 0.46 17.93 16.96 0.00 0.35 0.50 0.44 2.86 0.00 1.39 63.18 22.72 0.00 0.00 8.55 3.37 0.00 0.13 0.16 0.00 1.89 0.00 1.35 79.94 19.57 0.00 0.00 0.22 0.27 0.00 0.00 0.00 0.00 0.00 0.00 1.35 81.48 18.52 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.35 63.76 11.68 0.00 0.00 1.94 19.60 0.00 0.52 0.00 0.27 1.71 0.53 1.31 77.20 19.23 0.00 0.00 0.80 1.09 0.00 0.29 0.00 0.00 1.39 0.00 1.31 81.42 18.58 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.31 84.21 15.79 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.31 45.67 23.30 0.00 0.38 12.65 9.71 0.00 1.79 0.00 0.23 6.28 0.00 1.31 45.81 26.98 0.00 0.60 9.24 11.29 0.00 4.06 0.00 0.00 2.02 0.00 1.31 64.19 17.96 0.00 0.00 6.25 6.69 0.00 2.09 0.31 0.17 1.83 0.52 1.31 59.29 13.84 0.00 0.00 5.92 4.70 0.00 0.00 0.21 0.00 15.39 0.65

235

Table A1-6 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.31 47.08 34.91 0.00 0.00 0.39 16.74 0.00 0.00 0.68 0.00 0.20 0.00 1.27 85.18 14.82 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.27 86.02 13.98 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.27 57.85 27.07 0.00 0.00 6.00 5.95 0.00 1.59 0.16 0.00 1.37 0.00 1.27 70.35 15.91 0.00 0.28 4.56 6.02 0.00 2.18 0.00 0.00 0.69 0.00 1.27 77.75 16.17 0.00 0.00 1.75 1.28 0.00 0.17 0.13 0.21 2.54 0.00 1.27 46.39 23.88 0.00 0.00 1.44 27.24 0.00 0.54 0.00 0.00 0.52 0.00 1.23 77.34 19.32 0.00 0.00 1.19 1.21 0.00 0.19 0.00 0.20 0.56 0.00 1.23 80.31 19.69 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.23 50.09 17.01 0.00 0.00 0.00 0.00 0.00 0.00 32.90 0.00 0.00 0.00 1.23 53.05 29.96 0.00 0.00 7.84 6.85 0.00 0.14 0.24 0.19 1.73 0.00 1.23 53.83 21.56 0.00 0.00 6.09 14.38 0.00 1.24 0.25 0.00 1.94 0.71 1.23 64.68 19.30 0.00 0.24 5.96 4.42 0.00 0.38 0.00 0.00 5.02 0.00 1.23 74.22 13.88 0.00 0.00 4.20 5.35 0.00 2.06 0.00 0.00 0.29 0.00 1.23 65.91 23.54 0.00 0.80 3.45 3.73 0.00 0.52 0.00 0.00 2.05 0.00 1.18 79.32 18.07 0.00 0.00 0.58 1.01 0.00 0.00 0.16 0.26 0.60 0.00 1.18 85.80 13.82 0.00 0.00 0.22 0.00 0.16 0.00 0.00 0.00 0.00 0.00 1.18 43.81 20.36 0.80 0.87 1.56 1.85 1.35 0.57 27.20 0.72 0.90 0.00 1.18 23.40 37.94 0.00 0.00 17.96 16.78 0.00 0.32 0.26 0.23 3.11 0.00 1.18 32.71 34.54 0.00 0.00 15.06 14.29 0.00 0.00 0.26 0.00 2.27 0.87 1.18 54.21 7.49 0.00 0.28 11.87 14.80 0.00 8.41 0.29 0.40 2.26 0.00 1.18 58.19 21.57 0.00 0.00 8.76 5.39 0.00 0.60 0.00 0.13 5.36 0.00 1.14 76.25 19.31 0.00 0.00 1.38 1.27 0.00 0.33 0.00 0.14 0.67 0.65 1.14 81.48 16.46 0.00 0.00 0.33 0.22 0.18 0.00 0.00 0.00 0.23 1.10 1.14 78.57 21.43 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.14 80.06 18.61 0.63 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.69 1.14 30.02 35.14 0.00 0.00 16.49 16.15 0.00 0.00 0.00 0.00 2.20 0.00 1.14 57.64 14.39 0.00 0.00 9.64 11.89 0.00 5.16 0.00 0.00 1.28 0.00

236

Table A1-6 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.14 59.83 18.85 0.00 0.00 8.70 3.83 0.00 0.00 0.00 0.00 8.79 0.00 1.14 44.74 24.13 0.00 0.00 6.41 5.29 0.00 0.00 0.00 0.00 18.63 0.80 1.14 54.39 23.91 0.00 0.49 5.53 8.83 0.25 0.48 1.60 0.00 4.52 0.00 1.09 80.68 19.32 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.09 54.74 18.63 0.00 0.30 9.80 7.45 0.00 1.71 0.00 0.32 7.07 0.00 1.09 49.72 22.23 0.00 0.80 9.47 11.51 0.00 4.23 0.00 0.00 2.05 0.00 1.09 56.84 18.83 0.00 0.34 8.51 10.27 0.00 4.14 0.00 0.00 1.06 0.00 1.09 57.22 24.11 0.00 0.00 7.70 6.54 0.00 0.38 0.00 0.00 4.06 0.00 1.09 70.08 11.76 0.00 0.00 3.40 11.32 0.15 0.45 0.19 0.00 1.20 1.43 1.09 42.60 26.47 0.00 0.00 0.64 29.20 0.00 0.00 0.00 0.00 0.00 1.10 1.04 79.31 18.83 0.00 0.00 0.83 0.81 0.00 0.00 0.00 0.00 0.21 0.00 1.04 84.27 14.72 0.33 0.20 0.30 0.18 0.00 0.00 0.00 0.00 0.00 0.00 1.04 83.19 15.04 0.00 0.00 0.22 0.15 0.12 0.00 0.00 0.00 0.00 1.28 1.04 79.90 20.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.04 83.00 17.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.04 84.77 14.94 0.29 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.04 21.69 39.14 0.00 0.00 18.23 17.21 0.00 0.28 0.36 0.00 3.09 0.00 1.04 45.49 18.74 0.00 0.95 11.16 13.70 0.88 5.89 0.21 0.22 2.09 0.66 1.04 53.37 22.18 0.00 0.32 10.36 7.59 0.00 0.55 0.00 0.00 4.98 0.66 1.04 68.82 12.39 0.00 0.00 6.45 7.77 0.00 3.45 0.14 0.00 0.98 0.00 1.04 33.28 27.23 0.00 0.32 4.48 29.69 0.00 0.21 0.30 0.34 3.50 0.64 1.04 70.06 24.10 0.00 0.00 2.79 2.50 0.00 0.27 0.00 0.00 0.29 0.00 1.04 41.73 28.40 0.00 0.00 2.10 25.93 0.00 0.36 0.00 0.18 0.81 0.49

237

Table A1-7. Normalised EDS data, station 5, 2-14 December 2011.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

44.7 22.34 35.85 0.00 1.08 14.38 17.71 0.25 5.34 0.00 0.00 3.04 0.00 32.59 30.01 33.52 0.00 0.84 12.77 15.80 0.00 4.20 0.00 0.00 2.86 0.00 28.27 21.12 35.25 0.00 1.37 14.01 17.71 0.00 5.60 0.23 0.48 4.24 0.00 19.85 44.25 26.53 0.00 0.00 3.92 18.86 0.00 1.47 0.25 0.20 4.52 0.00 19.37 29.93 31.12 0.00 0.43 29.87 29.87 0.29 1.86 0.00 0.00 1.33 0.63 16.43 43.05 27.87 0.00 0.47 10.54 11.18 0.00 1.44 0.00 0.25 5.20 0.00 16.26 55.57 25.40 0.00 2.88 5.71 6.26 0.00 0.43 0.00 0.00 3.74 0.00 14.83 42.29 27.26 0.00 0.00 0.97 28.66 0.00 0.15 0.00 0.20 0.47 0.00 14.8 48.10 29.68 0.00 0.40 8.72 7.60 0.00 1.37 0.00 0.00 4.13 0.00 13.05 47.49 23.64 0.21 0.00 1.51 24.19 0.00 0.20 0.16 0.26 1.47 0.87 12.19 45.00 26.67 0.00 0.00 0.58 0.41 0.00 0.00 27.35 0.00 0.00 0.00 11.99 41.19 26.67 0.88 3.16 11.73 12.07 0.00 0.50 0.25 0.00 3.57 0.00 11.98 48.91 28.47 0.00 0.00 7.11 10.87 0.00 0.95 0.00 0.00 3.69 0.00 11.95 47.81 25.90 0.00 0.79 9.92 9.15 0.00 1.57 0.00 0.00 4.85 0.00 11.75 45.09 29.49 0.00 0.00 3.65 19.43 0.00 0.47 0.00 0.00 1.88 0.00 11.75 46.88 20.92 0.00 0.00 1.23 29.95 0.00 0.21 0.00 0.23 0.58 0.00 11.26 49.13 21.58 0.00 0.00 3.76 21.72 0.00 0.37 0.00 0.16 2.65 0.63 11.06 42.22 29.53 0.00 0.63 10.92 8.83 0.00 1.25 0.00 0.00 6.62 0.00 10.97 40.26 27.99 0.24 0.00 0.87 29.46 0.00 0.34 0.00 0.26 0.56 0.00 10.46 44.83 25.14 0.00 0.00 1.92 26.76 0.00 0.21 0.00 0.21 0.92 0.00 9.31 41.40 28.56 0.00 0.50 11.18 10.37 0.00 1.61 0.00 0.00 6.38 0.00 9.29 53.58 25.88 0.00 0.69 6.21 7.81 0.00 3.27 0.11 0.20 2.25 0.00 9.26 66.12 16.29 0.00 0.00 2.76 12.06 0.00 0.42 0.00 0.24 2.13 0.00 9.26 53.65 22.10 0.00 0.00 9.02 8.40 0.00 2.16 0.31 0.00 4.36 0.00 8.93 44.57 24.74 0.00 0.00 10.87 10.42 0.00 2.53 0.25 0.00 5.64 0.99 8.35 47.37 24.35 0.00 0.00 1.03 25.96 0.00 0.20 0.15 0.35 0.60 0.00 7.8 60.12 20.62 0.00 0.26 1.05 16.59 0.00 0.00 0.27 0.00 1.09 0.00 7.76 43.07 26.07 0.00 0.00 3.96 24.42 0.00 0.24 0.17 0.16 1.27 0.64

238

Table A1-7 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

7.69 53.94 21.44 0.00 0.62 8.75 8.71 0.00 2.07 0.00 0.00 4.47 0.00 7.35 51.66 17.84 0.00 0.41 6.63 14.49 0.00 0.97 0.22 0.00 7.21 0.57 7.06 46.42 24.22 0.00 0.53 10.98 9.49 0.00 1.86 0.00 0.00 6.50 0.00 7.02 51.58 29.07 0.00 0.00 8.49 7.63 0.00 0.34 0.00 0.00 2.89 0.00 6.84 46.33 27.95 0.00 0.00 12.05 11.31 0.21 0.49 0.20 0.00 1.45 0.00 6.82 55.22 20.76 0.00 0.46 7.57 7.57 0.00 2.09 0.26 0.00 6.07 0.00 6.81 52.37 27.12 0.00 0.30 8.38 7.30 0.00 0.46 0.00 0.00 4.07 0.00 6.75 47.86 29.78 0.00 0.41 8.98 7.63 0.00 1.55 0.15 0.00 3.65 0.00 6.22 52.20 20.12 0.00 0.36 3.96 20.18 0.00 0.40 0.17 0.27 2.35 0.00 5.78 62.47 16.25 0.00 0.00 0.59 18.56 0.00 0.16 0.22 0.21 1.03 0.51 5.67 61.21 20.51 0.00 0.00 3.65 12.23 0.00 0.40 0.00 0.00 2.01 0.00 5.6 51.33 29.32 0.00 0.55 7.22 6.39 0.14 1.54 0.15 0.00 3.36 0.00 5.58 65.97 28.49 0.00 0.00 2.32 1.72 0.00 0.00 0.00 0.00 1.49 0.00 5.14 68.74 17.47 0.00 0.00 2.08 9.70 0.00 0.31 0.14 0.19 1.36 0.00 5.12 55.33 23.90 0.00 0.33 7.89 6.76 0.00 1.09 0.00 0.00 4.70 0.00 4.65 65.44 14.53 0.00 0.00 2.59 1.81 0.00 0.45 0.00 0.00 15.19 0.00 4.65 53.59 25.09 0.00 0.00 2.08 17.33 0.00 0.32 0.15 0.18 1.26 0.00 4.37 81.87 9.80 6.35 0.32 0.00 0.00 0.36 0.00 0.15 0.00 0.11 1.04 3.69 67.64 14.48 0.00 0.68 0.29 8.47 0.00 0.30 7.51 0.30 0.31 0.00 3.06 47.67 26.83 0.00 0.55 9.55 9.10 0.00 2.08 0.00 0.00 3.27 0.94 2.8 44.75 23.64 0.00 0.67 12.13 10.57 0.00 1.82 0.00 0.00 6.42 0.00 2.74 82.55 17.45 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.5 44.68 22.71 0.00 0.00 3.40 26.44 0.00 0.00 0.00 0.00 2.12 0.65 2.29 65.79 16.68 0.26 0.30 6.44 5.87 0.00 1.24 0.22 0.22 2.99 0.00 2.22 83.41 12.36 0.00 0.00 0.00 0.00 0.24 3.98 0.00 0.00 0.00 0.00 2.15 84.46 15.26 0.28 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

239

Table A1-7 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.83 72.38 10.31 0.00 0.21 1.84 13.76 0.00 0.30 0.00 0.00 1.20 0.00 1.77 66.22 16.56 0.00 0.38 6.20 5.80 0.00 1.58 0.00 0.14 3.11 0.00 1.7 60.00 17.81 0.00 0.40 2.67 17.24 0.00 0.26 0.00 0.00 1.62 0.00 1.67 80.16 19.19 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.65 1.61 34.98 32.81 0.00 0.31 2.84 26.06 0.00 0.71 0.00 0.19 1.40 0.70 1.57 57.19 17.26 0.00 0.46 9.35 7.66 0.00 1.38 0.19 0.22 6.30 0.00 1.27 53.95 21.99 0.00 0.00 8.96 8.92 0.00 2.67 0.35 0.21 2.97 0.00 1.18 73.17 21.17 0.00 0.00 1.34 1.18 0.19 0.29 0.30 0.16 1.63 0.56 1.09 80.26 19.74 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.09 85.04 14.96 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.09 44.69 21.20 0.00 0.30 3.56 27.15 0.00 0.56 0.16 0.38 2.00 0.00 1.04 84.23 15.77 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.04 82.39 17.61 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

240

Table A1-8. Normalised EDS data, station 5, 13-20 September 2012.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

27.98 35.18 32.91 0.00 3.36 5.85 11.22 0.00 1.00 5.67 0.31 4.49 0.00 21.74 30.16 34.72 0.00 1.20 10.46 14.46 0.00 5.23 0.00 0.00 2.63 1.13 17.35 31.23 33.86 0.00 0.67 13.04 14.42 0.00 4.09 0.00 0.00 1.76 0.92 16.36 41.09 28.88 0.00 0.00 8.95 16.71 0.00 2.59 0.00 0.00 1.78 0.00 15.98 42.80 25.55 0.00 0.35 0.77 0.55 0.00 0.00 29.98 0.00 0.00 0.00 15.2 40.94 31.44 0.49 0.45 10.19 9.69 0.19 2.61 0.42 0.00 3.59 0.00 14.36 41.75 20.72 0.00 0.00 3.68 3.26 0.00 0.91 0.00 0.35 29.34 0.00 13.53 80.77 19.23 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 13.41 79.58 20.42 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 13.38 48.50 27.17 0.00 0.00 9.80 9.40 0.00 0.52 0.00 0.00 4.62 0.00 13.05 58.40 23.43 0.00 0.56 6.37 7.59 0.00 2.53 0.00 0.00 1.12 0.00 12.59 82.30 17.70 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 12.37 46.84 28.14 0.00 8.49 0.00 0.00 0.00 0.00 14.58 0.00 0.00 1.94 11.91 63.53 27.20 0.00 0.43 1.31 2.21 0.00 0.26 4.28 0.00 0.79 0.00 11.58 82.14 17.86 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 11.36 43.33 26.63 0.00 0.29 13.00 6.65 0.00 0.36 0.00 0.00 9.74 0.00 11.24 30.67 38.11 0.39 11.83 0.00 0.00 0.00 0.00 19.00 0.00 0.00 0.00 10.96 35.65 33.38 0.38 11.02 0.48 0.30 0.25 0.16 17.38 0.35 0.64 0.00 10.26 48.25 26.65 0.00 0.45 6.00 12.31 0.00 2.21 1.22 0.30 2.61 0.00 10.23 49.50 27.74 0.00 0.33 3.31 3.40 0.00 1.15 12.82 0.23 0.65 0.87 10.13 80.86 19.14 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 10.12 52.68 23.23 0.00 0.00 5.18 15.75 0.00 0.63 0.00 0.00 2.54 0.00 9.74 40.80 29.10 0.00 0.27 1.63 27.46 0.00 0.00 0.00 0.00 0.74 0.00 9.54 80.79 19.21 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 9.47 34.73 30.99 0.43 12.62 0.37 0.00 0.29 0.20 19.73 0.31 0.33 0.00 9.42 54.00 21.13 0.00 0.00 0.86 23.21 0.00 0.00 0.14 0.24 0.42 0.00 9.04 68.83 22.02 0.00 3.39 0.00 0.00 0.00 0.00 5.76 0.00 0.00 0.00 9.03 81.11 18.51 0.00 0.21 0.00 0.00 0.00 0.00 0.00 0.00 0.17 0.00

241

Table A1-8 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

8.91 43.81 27.59 0.22 0.00 1.08 26.39 0.00 0.00 0.00 0.21 0.70 0.00 8.54 57.80 19.67 0.00 0.59 7.04 8.51 0.00 1.71 0.00 0.00 4.68 0.00 8.35 79.70 19.86 0.00 0.00 0.28 0.16 0.00 0.00 0.00 0.00 0.00 0.00 8.13 49.01 22.03 0.24 0.00 0.72 26.71 0.00 0.00 0.00 0.00 0.63 0.67 8.02 59.81 27.37 0.00 0.00 5.05 5.12 0.00 1.70 0.00 0.00 0.94 0.00 7.79 45.84 25.90 0.00 0.00 0.93 26.29 0.00 0.00 0.00 0.18 0.86 0.00 7.71 73.53 20.36 0.00 0.00 2.92 2.58 0.00 0.00 0.00 0.00 0.00 0.61 7.7 83.46 16.54 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 7.66 43.77 27.24 0.00 0.36 10.72 12.30 0.00 2.09 0.00 0.00 3.53 0.00 7.65 73.85 9.59 0.00 0.00 0.00 0.28 11.50 0.00 0.00 4.78 0.00 0.00 7.65 61.01 22.48 0.00 0.00 6.06 8.41 0.00 0.30 0.21 0.28 1.26 0.00 7.65 56.15 19.96 0.00 0.00 0.38 22.67 0.00 0.00 0.00 0.26 0.58 0.00 7.64 80.43 19.15 0.25 0.17 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 7.63 59.40 21.09 0.00 0.00 6.48 10.35 0.00 0.44 0.00 0.00 2.24 0.00 7.51 50.23 18.97 0.00 0.00 2.00 27.33 0.00 0.38 0.28 0.00 0.80 0.00 7.5 62.59 20.30 0.00 0.00 0.89 13.99 0.35 0.00 0.64 0.00 0.33 0.90 7.32 54.23 12.13 0.32 0.00 1.86 3.05 0.00 0.00 0.00 0.00 28.41 0.00 7.25 58.25 26.29 0.00 0.00 7.68 3.53 0.00 0.00 0.00 0.00 4.25 0.00 7.1 80.64 18.97 0.00 0.14 0.25 0.00 0.00 0.00 0.00 0.00 0.00 0.00 7.07 78.42 21.58 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.99 54.55 25.01 0.00 0.51 7.40 7.85 0.00 1.83 0.00 0.00 2.85 0.00 6.95 51.42 17.77 0.00 0.42 10.29 10.51 0.00 3.42 0.00 0.00 5.58 0.60 6.94 58.11 22.26 0.00 0.00 8.04 6.22 0.00 1.08 0.00 0.19 4.10 0.00 6.79 54.06 20.39 0.00 0.00 8.17 5.27 0.00 0.52 0.00 0.23 11.36 0.00 6.73 65.38 18.20 0.00 0.00 1.70 11.37 0.00 0.26 1.93 0.00 1.16 0.00 6.67 58.90 21.82 0.00 6.34 0.39 0.46 0.00 0.00 11.68 0.00 0.41 0.00 6.53 81.76 18.24 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 6.51 60.43 20.77 0.00 1.43 4.81 4.88 0.00 1.20 2.52 0.36 3.60 0.00

242

Table A1-8 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

6.42 59.22 32.74 0.00 0.00 0.00 0.28 0.00 0.29 6.33 0.20 0.29 0.65 6.29 52.43 20.90 0.00 0.58 8.34 10.29 0.00 3.05 0.00 0.00 3.86 0.55 6.17 52.92 21.33 0.00 0.51 8.29 9.52 0.00 1.30 0.00 0.00 5.33 0.80 6.14 57.06 24.11 0.00 0.00 8.17 7.21 0.00 0.33 0.26 0.00 2.87 0.00 5.94 57.78 13.74 0.00 0.00 8.53 6.22 0.00 0.82 0.00 0.00 12.91 0.00 5.94 64.68 14.84 0.00 0.00 4.41 4.28 0.00 0.32 0.19 0.19 10.22 0.87 5.83 79.27 20.54 0.00 0.00 0.19 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.83 53.70 18.86 0.00 0.94 8.19 8.19 0.00 1.83 1.70 0.49 5.52 0.58 5.74 67.81 21.54 0.00 0.00 4.45 3.84 0.00 0.15 0.13 0.18 1.05 0.84 5.73 52.14 27.60 0.00 0.36 5.94 11.16 0.00 0.58 0.31 0.00 1.90 0.00 5.68 56.27 25.24 0.00 0.00 0.65 16.85 0.00 0.20 0.13 0.24 0.43 0.00 5.58 68.15 19.78 0.00 0.35 0.91 1.32 0.00 0.16 7.93 0.30 1.11 0.00 5.57 58.40 18.78 0.00 0.00 1.42 20.35 0.00 0.30 0.00 0.00 0.75 0.00 5.56 76.28 18.68 0.00 0.21 1.92 1.96 0.00 0.73 0.00 0.00 0.21 0.00 5.51 53.95 23.97 0.00 0.60 7.87 8.39 0.00 1.58 0.20 0.00 3.44 0.00 5.5 50.07 23.60 0.00 0.36 10.95 9.79 0.00 0.78 0.00 0.00 4.45 0.00 5.49 77.96 22.04 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.47 81.11 18.89 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.46 56.38 21.76 0.00 0.25 9.65 7.92 0.00 0.53 0.00 0.00 3.52 0.00 5.45 58.90 20.45 0.00 0.00 8.57 7.37 0.00 0.00 0.15 0.00 4.56 0.00 5.32 83.59 16.22 0.00 0.19 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.3 68.70 18.80 0.00 0.27 3.95 5.56 0.00 0.57 0.36 0.00 1.81 0.00 5.3 68.61 12.60 0.00 0.00 1.73 0.45 0.00 0.21 0.19 0.26 15.94 0.00 5.28 66.04 22.56 0.00 0.36 4.11 4.51 0.00 1.86 0.00 0.00 0.56 0.00 5.27 41.57 24.43 0.00 1.60 6.16 6.38 0.35 0.86 2.71 0.00 15.94 0.00 5.27 42.82 32.64 0.00 9.17 0.00 0.00 0.00 0.00 14.94 0.00 0.43 0.00 5.26 56.87 22.50 0.00 0.00 10.69 5.61 0.00 0.19 0.17 0.19 3.09 0.69 5.19 84.54 15.46 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

243

Table A1-8 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

5.19 61.71 15.79 0.00 0.00 7.31 6.32 0.00 0.87 0.00 0.23 7.77 0.00 5.13 82.37 17.25 0.00 0.00 0.23 0.15 0.00 0.00 0.00 0.00 0.00 0.00 5.11 74.84 19.31 0.00 0.00 2.10 2.28 0.00 0.48 0.00 0.00 0.99 0.00 5.09 82.09 17.37 0.33 0.21 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.07 80.64 19.36 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 5.06 84.08 14.78 0.00 0.00 0.21 0.19 0.00 0.00 0.00 0.00 0.00 0.74 5.06 52.75 26.81 0.00 0.77 6.65 8.35 0.00 2.47 0.25 0.00 1.95 0.00 5.03 51.59 21.12 0.00 0.00 10.63 10.28 0.19 2.21 0.18 0.00 3.79 0.00 5 60.57 15.56 0.00 0.00 0.99 22.87 0.00 0.00 0.00 0.00 0.00 0.00 4.91 81.98 18.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.9 63.45 24.94 0.00 4.43 0.00 0.00 0.00 0.00 6.67 0.00 0.50 0.00 4.85 48.86 23.18 0.00 0.27 6.32 16.57 0.00 0.80 0.00 0.00 3.45 0.54 4.78 74.79 19.88 0.00 0.00 1.65 1.47 0.00 0.21 0.00 0.28 1.19 0.53 4.78 68.12 17.17 0.00 0.00 6.27 5.22 0.00 0.38 0.00 0.00 2.29 0.55 4.77 77.21 22.15 0.00 0.00 0.34 0.29 0.00 0.00 0.00 0.00 0.00 0.00 4.69 54.28 24.79 0.00 0.00 9.97 7.81 0.00 0.38 0.14 0.00 2.63 0.00 4.67 58.59 25.60 0.00 0.00 0.69 14.43 0.00 0.12 0.00 0.15 0.42 0.00 4.66 72.89 14.96 0.00 0.00 6.27 3.20 0.00 0.17 0.22 0.00 2.29 0.00 4.65 61.68 16.39 0.00 0.47 8.35 8.41 0.00 1.98 0.00 0.00 2.72 0.00 4.6 50.75 23.38 0.00 9.12 0.00 0.00 0.00 0.00 16.74 0.00 0.00 0.00 4.59 69.73 19.27 0.00 0.00 3.05 2.74 0.00 0.50 0.00 0.14 4.56 0.00 4.57 58.11 20.39 0.00 0.33 0.31 0.68 0.00 0.00 20.18 0.00 0.00 0.00 4.54 83.09 16.14 0.00 0.22 0.21 0.21 0.00 0.00 0.00 0.12 0.00 0.00 4.53 57.22 24.31 0.00 0.00 9.13 7.28 0.00 0.00 0.18 0.17 1.70 0.00 4.49 83.38 16.62 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.47 63.93 21.62 0.00 0.00 6.36 5.29 0.26 0.00 0.29 0.00 1.70 0.54 4.42 82.96 17.04 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.35 65.14 23.72 0.00 0.00 0.18 10.64 0.00 0.00 0.00 0.15 0.17 0.00

244

Table A1-8 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

4.31 81.34 18.10 0.00 0.15 0.26 0.15 0.00 0.00 0.00 0.00 0.00 0.00 4.31 57.58 19.95 0.00 0.00 1.62 20.20 0.00 0.16 0.00 0.00 0.49 0.00 4.22 62.14 20.24 0.00 0.00 8.61 4.49 0.00 0.79 0.00 0.00 3.72 0.00 4.17 76.42 17.33 0.00 0.22 2.95 0.61 0.00 0.00 0.00 0.00 1.87 0.60 4.17 65.60 19.34 0.00 0.34 5.57 5.48 0.00 0.67 0.00 0.00 3.00 0.00 4.16 53.05 23.43 0.00 0.00 11.66 9.80 0.00 0.00 0.00 0.00 2.07 0.00 4.13 66.86 19.72 0.00 0.00 6.67 3.58 0.00 0.18 0.00 0.00 3.00 0.00 4.13 66.09 15.18 0.00 0.00 3.05 2.38 0.00 0.29 0.00 0.21 12.80 0.00 4.09 76.85 17.02 0.00 0.00 2.33 2.23 0.00 0.27 0.00 0.00 1.31 0.00 4.07 54.09 25.50 0.00 0.00 4.41 11.08 0.00 1.84 0.85 0.25 1.98 0.00 4.04 61.72 20.66 0.00 0.00 6.69 7.34 0.00 0.95 0.14 0.28 2.22 0.00 4.02 78.07 21.93 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.99 50.93 17.90 0.00 0.47 11.86 10.31 0.00 2.68 0.00 0.00 5.84 0.00 3.96 63.98 14.67 0.00 0.00 3.29 2.29 0.00 0.70 0.41 0.34 14.32 0.00 3.96 58.78 22.28 0.00 0.00 7.58 9.20 0.00 0.19 0.00 0.00 1.97 0.00 3.93 82.54 16.97 0.30 0.19 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.89 77.11 21.06 0.00 0.00 0.00 0.00 0.00 1.83 0.00 0.00 0.00 0.00 3.88 58.49 21.39 0.00 0.00 9.70 5.00 0.00 0.75 0.00 0.00 4.66 0.00 3.87 56.22 19.32 0.00 0.25 10.29 9.44 0.00 1.13 0.00 0.00 3.35 0.00 3.87 71.79 15.31 0.00 0.00 1.96 8.85 0.00 0.23 0.00 0.00 1.85 0.00 3.81 72.33 18.86 0.00 0.00 3.42 3.52 0.00 0.41 0.00 0.00 1.45 0.00 3.78 72.78 18.70 0.00 0.26 3.03 3.01 0.00 0.32 0.00 0.26 1.66 0.00 3.75 80.19 19.81 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.74 56.67 17.28 0.00 0.00 2.08 21.52 0.00 0.19 0.18 0.15 1.25 0.68 3.72 85.26 14.74 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.69 65.23 21.30 0.00 0.63 1.41 9.48 0.26 0.20 0.92 0.00 0.58 0.00 3.68 56.11 18.81 0.00 0.32 2.84 18.02 0.00 0.27 1.75 0.00 1.88 0.00 3.67 75.99 20.17 0.00 0.00 0.90 1.62 0.00 0.24 0.24 0.25 0.57 0.00

245

Table A1-8 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

3.64 76.73 18.17 0.00 1.84 0.00 0.00 0.00 0.00 2.42 0.00 0.17 0.68 3.62 84.10 15.54 0.00 0.00 0.22 0.00 0.13 0.00 0.00 0.00 0.00 0.00 3.61 62.18 19.51 0.00 0.00 8.10 6.57 0.00 0.41 0.00 0.00 3.23 0.00 3.58 71.66 18.03 0.23 0.00 3.74 3.98 0.15 1.15 0.00 0.00 1.07 0.00 3.56 81.80 17.12 0.24 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.84 3.52 78.55 19.40 0.00 0.00 0.69 0.62 0.00 0.21 0.00 0.00 0.53 0.00 3.5 68.24 18.82 0.00 0.36 4.70 4.72 0.00 0.88 0.00 0.00 2.27 0.00 3.45 80.99 18.68 0.00 0.00 0.00 0.00 0.00 0.15 0.00 0.00 0.18 0.00 3.45 81.88 17.85 0.00 0.00 0.00 0.00 0.15 0.00 0.00 0.12 0.00 0.00 3.45 82.86 17.14 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 3.44 62.53 16.31 0.00 0.00 2.13 18.54 0.00 0.00 0.00 0.00 0.50 0.00 3.44 68.00 17.95 0.00 0.00 1.66 10.62 0.00 0.52 0.00 0.00 1.25 0.00 3.42 64.94 23.99 0.00 4.29 0.00 0.00 0.00 0.00 6.78 0.00 0.00 0.00 3.39 76.58 17.72 0.00 0.00 2.92 1.45 0.00 0.00 0.00 0.17 1.16 0.00 3.36 80.90 17.98 0.00 0.00 0.00 0.95 0.00 0.00 0.17 0.00 0.00 0.00 3.31 64.79 19.61 0.00 6.11 0.00 0.00 0.00 0.00 9.31 0.00 0.17 0.00 3.28 63.28 21.66 0.00 0.00 8.28 4.04 0.00 0.00 0.00 0.00 2.74 0.00 3.28 75.19 16.99 0.00 0.00 3.26 2.27 0.00 0.00 0.00 0.00 1.67 0.62 3.26 64.01 13.25 0.00 0.36 7.99 8.41 0.00 0.95 0.00 0.00 4.39 0.64 3.25 71.71 16.49 0.00 0.00 2.49 6.53 0.00 2.79 0.00 0.00 0.00 0.00 3.23 68.59 15.14 0.00 0.00 6.91 5.03 0.00 0.21 0.00 0.00 4.12 0.00 3.23 66.44 17.14 0.00 0.23 1.73 13.00 0.00 0.19 0.24 0.00 1.04 0.00 3.21 63.50 17.75 0.00 1.31 5.76 5.90 0.00 0.75 2.36 0.00 2.67 0.00 3.2 74.31 17.43 0.00 0.00 3.09 3.65 0.00 0.55 0.00 0.00 0.97 0.00 3.16 66.43 20.24 0.00 0.33 4.74 4.65 0.00 0.80 0.28 0.16 2.38 0.00 3.14 76.27 20.43 0.00 0.22 1.41 1.19 0.00 0.00 0.00 0.00 0.46 0.00 3.09 66.85 18.01 0.00 0.00 4.86 3.72 0.00 0.00 0.00 0.00 6.57 0.00 3.08 78.85 17.95 0.24 1.08 0.23 0.00 0.00 0.00 1.45 0.00 0.19 0.00

246

Table A1-8 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

3.06 76.31 17.97 0.00 2.28 0.00 0.00 0.00 0.00 3.45 0.00 0.00 0.00 3.06 70.99 20.52 0.00 0.00 4.10 3.07 0.00 0.20 0.00 0.00 1.11 0.00 3.02 55.45 20.59 0.00 0.61 8.11 9.92 0.00 2.99 0.00 0.00 1.63 0.70 3 70.79 11.57 0.00 0.32 5.64 7.37 0.00 1.43 0.00 0.00 1.80 1.08 3 60.80 21.55 0.00 0.27 1.67 13.22 0.00 0.34 0.15 0.24 0.95 0.80 2.97 74.66 18.27 0.00 0.00 1.74 1.80 0.00 0.41 0.12 0.16 2.30 0.55 2.97 83.36 16.64 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.97 42.20 27.65 0.00 0.57 11.07 9.99 0.00 2.14 0.24 0.22 5.93 0.00 2.95 60.22 18.17 0.00 0.00 9.03 6.06 0.00 0.63 0.00 0.00 5.90 0.00 2.93 74.96 18.03 0.00 0.00 2.10 1.95 0.19 0.39 0.49 0.14 1.76 0.00 2.93 83.87 16.13 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.93 64.27 17.65 0.00 0.30 4.69 10.73 0.00 0.55 0.00 0.00 1.81 0.00 2.91 77.49 18.80 0.00 0.00 1.34 1.35 0.00 0.44 0.00 0.14 0.43 0.00 2.9 53.45 18.88 0.00 0.67 8.07 10.20 0.00 1.87 0.00 0.00 6.01 0.86 2.88 77.03 15.84 0.00 0.00 0.52 6.43 0.00 0.00 0.00 0.00 0.18 0.00 2.88 81.65 18.35 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.88 67.87 13.83 0.00 0.00 5.36 3.66 0.00 0.53 0.19 0.33 8.24 0.00 2.88 56.48 24.88 0.00 0.89 2.57 2.50 0.00 0.25 9.07 0.34 3.01 0.00 2.86 81.85 17.46 0.00 0.22 0.30 0.17 0.00 0.00 0.00 0.00 0.00 0.00 2.86 60.50 19.99 0.00 0.00 9.88 7.81 0.00 0.00 0.22 0.00 1.59 0.00 2.86 59.95 18.08 0.00 0.48 7.71 8.02 0.00 2.11 0.24 0.00 3.41 0.00 2.86 58.64 22.71 0.00 0.39 5.99 6.96 0.00 1.34 0.00 0.00 3.97 0.00 2.84 76.18 18.85 0.00 1.94 0.00 0.00 0.00 0.00 3.02 0.00 0.00 0.00 2.84 85.59 14.41 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.84 84.07 15.93 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.82 70.38 15.09 0.00 0.00 0.33 14.09 0.00 0.00 0.00 0.12 0.00 0.00 2.8 85.09 14.91 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.78 80.28 18.88 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.84

247

Table A1-8 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

2.76 81.05 18.95 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.72 82.82 17.18 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.7 74.99 19.47 0.00 0.00 1.74 1.64 0.00 0.42 0.13 0.17 1.44 0.00 2.68 64.86 18.20 0.00 0.00 8.36 4.01 0.00 0.73 0.00 0.00 3.84 0.00 2.66 81.99 18.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.58 75.08 21.27 0.00 1.57 0.00 0.00 0.00 0.00 2.09 0.00 0.00 0.00 2.58 56.22 17.12 0.00 0.28 7.07 14.70 0.00 1.64 0.19 0.00 2.78 0.00 2.56 78.98 16.45 0.00 0.00 1.90 1.32 0.00 0.14 0.00 0.20 1.01 0.00 2.54 78.63 17.99 0.00 0.00 0.97 1.03 0.00 0.22 0.00 0.18 0.98 0.00 2.52 84.71 15.29 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.5 83.53 16.25 0.00 0.00 0.22 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.48 81.56 18.44 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.48 80.13 19.87 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.48 61.61 18.16 0.00 0.38 6.94 7.42 0.00 1.29 0.17 0.00 3.31 0.72 2.45 80.84 17.20 0.00 0.00 0.58 0.60 0.00 0.13 0.15 0.11 0.39 0.00 2.43 58.14 23.66 0.00 0.37 6.46 6.52 0.00 0.93 0.65 0.00 3.27 0.00 2.43 59.61 21.23 0.00 0.00 2.95 14.96 0.00 0.98 0.00 0.00 0.26 0.00 2.41 36.15 38.56 0.00 0.00 12.82 11.63 0.00 0.19 0.15 0.00 0.50 0.00 2.36 67.13 19.56 0.00 0.00 4.79 5.12 0.00 0.68 0.00 0.00 2.29 0.43 2.34 82.44 17.56 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.34 82.50 17.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.32 79.84 15.66 0.24 0.22 1.02 0.86 0.00 0.17 0.13 0.20 0.65 0.99 2.32 79.11 18.82 0.00 0.71 0.28 0.23 0.00 0.00 0.71 0.00 0.14 0.00 2.32 66.53 25.95 0.00 3.15 0.23 0.00 0.00 0.00 4.14 0.00 0.00 0.00 2.32 57.68 19.66 0.00 0.35 10.85 5.10 0.00 1.01 0.19 0.00 5.16 0.00 2.32 58.59 20.56 0.00 0.00 9.37 6.83 0.00 0.44 0.00 0.00 4.20 0.00 2.29 73.75 24.35 0.00 0.00 0.00 0.00 0.00 0.00 1.90 0.00 0.00 0.00

248

Table A1-8 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

2.29 82.85 16.36 0.00 0.00 0.00 0.00 0.16 0.15 0.00 0.17 0.29 0.00 2.27 79.73 19.06 0.00 0.00 0.00 0.35 0.00 0.00 0.00 0.00 0.86 0.00 2.25 84.25 15.44 0.00 0.00 0.00 0.15 0.00 0.00 0.00 0.00 0.15 0.00 2.22 82.06 17.94 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.22 53.79 31.90 0.00 0.32 4.89 5.26 0.00 1.34 0.00 0.00 1.94 0.56 2.22 70.30 19.10 0.00 0.39 1.65 1.63 0.00 0.37 3.98 0.14 2.43 0.00 2.2 71.29 20.53 0.00 0.70 1.63 2.33 0.00 0.34 0.15 0.18 2.84 0.00 2.2 82.13 17.33 0.00 0.31 0.00 0.00 0.00 0.00 0.23 0.00 0.00 0.00 2.17 80.30 18.79 0.00 0.00 0.29 0.00 0.00 0.00 0.00 0.00 0.62 0.00 2.17 62.63 21.66 0.00 0.27 6.83 5.56 0.00 0.59 0.00 0.00 2.45 0.00 2.17 65.54 18.89 0.00 0.28 6.22 5.94 0.00 1.15 0.00 0.00 1.98 0.00 2.17 73.55 15.41 0.00 0.00 4.76 3.27 0.00 0.56 0.28 0.15 2.02 0.00 2.15 79.95 19.46 0.00 0.00 0.27 0.32 0.00 0.00 0.00 0.00 0.00 0.00 2.15 83.65 15.91 0.00 0.00 0.24 0.20 0.00 0.00 0.00 0.00 0.00 0.00 2.15 80.82 19.18 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.15 80.94 18.65 0.00 0.00 0.00 0.41 0.00 0.00 0.00 0.00 0.00 0.00 2.12 79.80 18.70 0.00 0.00 0.38 0.44 0.00 0.00 0.14 0.21 0.33 0.00 2.12 84.61 14.34 0.27 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.78 2.12 58.92 14.66 0.00 0.00 9.48 10.71 0.00 4.16 0.17 0.00 1.90 0.00 2.12 68.39 14.65 0.00 0.25 7.03 6.63 0.00 0.76 0.00 0.00 2.28 0.00 2.1 83.16 16.84 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.1 52.80 20.19 0.00 0.00 13.19 10.35 0.00 0.21 0.29 0.24 2.73 0.00 2.1 42.06 30.15 0.00 0.00 5.56 18.02 0.00 0.51 0.55 0.00 3.14 0.00 2.07 80.20 19.80 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.05 79.68 18.60 0.00 0.00 1.07 0.65 0.00 0.00 0.00 0.00 0.00 0.00 2.05 83.03 16.97 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.02 61.39 20.74 0.00 0.00 0.47 2.12 0.56 0.00 14.72 0.00 0.00 0.00 2.02 70.51 15.74 0.00 0.00 5.41 5.67 0.00 1.68 0.00 0.13 0.85 0.00

249

Table A1-8 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.99 79.72 19.93 0.00 0.00 0.22 0.00 0.13 0.00 0.00 0.00 0.00 0.00 1.99 81.72 18.28 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.97 71.86 22.88 0.00 0.00 1.86 1.90 0.00 0.40 0.13 0.24 0.73 0.00 1.97 72.58 20.08 0.00 1.29 1.23 0.82 0.00 0.29 2.48 0.00 0.58 0.66 1.97 83.52 16.48 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.97 80.71 19.29 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.94 81.69 17.20 0.00 0.00 0.53 0.58 0.00 0.00 0.00 0.00 0.00 0.00 1.94 84.27 15.30 0.00 0.00 0.28 0.15 0.00 0.00 0.00 0.00 0.00 0.00 1.94 84.86 14.58 0.00 0.00 0.20 0.17 0.00 0.00 0.00 0.00 0.18 0.00 1.94 78.52 21.18 0.00 0.00 0.16 0.14 0.00 0.00 0.00 0.00 0.00 0.00 1.94 49.54 22.77 0.00 8.84 0.00 0.00 0.00 0.00 18.84 0.00 0.00 0.00 1.91 69.25 20.10 0.00 1.72 0.85 1.28 0.45 0.00 6.35 0.00 0.00 0.00 1.88 80.02 19.98 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.88 81.30 18.70 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.88 52.57 26.38 0.00 0.00 8.35 8.12 0.00 1.16 0.45 0.00 2.97 0.00 1.85 82.32 17.04 0.00 0.00 0.00 0.11 0.00 0.00 0.00 0.00 0.00 0.53 1.85 61.87 17.66 0.00 0.00 8.93 7.83 0.00 0.00 1.16 0.00 1.81 0.74 1.83 84.62 15.38 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.8 79.20 17.84 0.00 0.00 1.14 0.90 0.00 0.27 0.00 0.22 0.42 0.00 1.77 79.63 18.08 0.00 0.20 0.92 0.69 0.14 0.00 0.00 0.00 0.33 0.00 1.77 80.76 17.46 0.00 0.21 0.73 0.47 0.00 0.00 0.00 0.00 0.37 0.00 1.77 80.01 19.99 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.73 78.24 17.28 0.00 0.00 1.49 1.40 0.00 0.00 0.00 0.00 0.97 0.61 1.73 78.97 20.27 0.00 0.26 0.27 0.23 0.00 0.00 0.00 0.00 0.00 0.00 1.73 82.74 16.92 0.00 0.00 0.20 0.14 0.00 0.00 0.00 0.00 0.00 0.00 1.73 86.16 13.84 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.73 85.56 14.44 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.73 66.90 12.68 0.00 0.00 8.05 8.59 0.00 1.88 0.00 0.00 1.90 0.00

250

Table A1-8 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.73 63.19 11.18 0.00 0.45 7.42 8.27 0.00 2.26 0.00 0.00 7.23 0.00 1.73 69.60 19.05 0.00 0.30 4.01 3.97 0.00 0.71 0.00 0.00 2.36 0.00 1.73 71.46 23.90 0.00 0.00 2.17 1.94 0.00 0.00 0.00 0.00 0.53 0.00 1.7 80.20 19.80 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.7 83.06 16.79 0.00 0.00 0.00 0.15 0.00 0.00 0.00 0.00 0.00 0.00 1.67 76.89 20.71 0.00 1.17 0.00 0.00 0.00 0.00 1.23 0.00 0.00 0.00 1.67 80.93 18.71 0.00 0.00 0.00 0.00 0.00 0.00 0.11 0.10 0.14 0.00 1.67 32.82 34.25 0.32 11.87 0.00 0.00 0.00 0.00 20.74 0.00 0.00 0.00 1.67 67.88 18.41 0.00 0.00 0.72 11.58 0.00 0.20 0.22 0.18 0.26 0.56 1.64 78.92 18.86 0.00 0.00 0.32 0.30 0.58 0.00 1.01 0.00 0.00 0.00 1.64 78.63 20.88 0.00 0.26 0.00 0.23 0.00 0.00 0.00 0.00 0.00 0.00 1.64 79.98 20.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.64 82.15 17.08 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.77 1.61 81.27 17.52 0.00 0.22 0.25 0.00 0.00 0.00 0.00 0.00 0.00 0.73 1.61 64.81 19.50 0.00 0.35 5.99 5.68 0.00 0.80 0.50 0.16 2.21 0.00 1.61 73.11 9.98 0.00 0.00 5.81 7.09 0.00 1.27 0.18 0.00 2.57 0.00 1.61 64.60 20.73 0.00 0.30 5.58 6.52 0.00 0.56 0.00 0.00 1.70 0.00 1.57 82.49 16.95 0.00 0.00 0.15 0.13 0.10 0.00 0.00 0.18 0.00 0.00 1.57 58.32 14.58 0.00 0.73 9.67 10.38 0.00 3.24 0.81 0.00 2.27 0.00 1.57 68.65 12.11 0.00 0.00 5.92 6.50 0.00 1.65 0.00 0.00 5.16 0.00 1.54 80.40 16.57 0.00 0.00 0.51 0.51 0.14 0.14 0.10 0.25 0.39 0.98 1.54 79.84 20.16 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.54 81.01 18.99 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.54 81.72 18.28 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.54 65.11 16.11 0.00 0.00 8.48 6.78 0.31 0.29 0.61 0.31 2.01 0.00 1.5 80.01 15.18 0.00 0.25 1.71 1.72 0.00 0.34 0.00 0.00 0.80 0.00 1.5 78.90 19.93 0.00 0.22 0.33 0.23 0.00 0.00 0.39 0.00 0.00 0.00 1.5 84.62 14.86 0.30 0.22 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

251

Table A1-8 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.5 79.36 20.64 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.5 47.08 25.02 0.00 10.12 0.00 0.00 0.00 0.00 16.63 0.00 0.00 1.14 1.47 76.62 19.89 0.24 0.00 1.28 0.77 0.00 0.00 0.00 0.00 0.59 0.60 1.47 80.37 18.51 0.00 0.00 0.67 0.45 0.00 0.00 0.00 0.00 0.00 0.00 1.47 79.74 20.26 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.47 80.95 19.05 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.47 84.76 14.92 0.00 0.00 0.00 0.20 0.11 0.00 0.00 0.00 0.00 0.00 1.43 75.27 20.56 0.00 0.91 0.80 0.59 0.00 0.00 1.87 0.00 0.00 0.00 1.43 81.59 18.14 0.00 0.00 0.27 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.43 79.64 19.52 0.30 0.00 0.22 0.18 0.00 0.00 0.00 0.00 0.14 0.00 1.43 80.41 18.29 0.47 0.33 0.00 0.23 0.00 0.00 0.00 0.00 0.26 0.00 1.43 80.06 19.61 0.00 0.33 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.43 77.62 22.38 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.43 86.93 12.23 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.84 1.39 79.92 18.29 0.31 0.21 0.23 0.34 0.00 0.00 0.00 0.00 0.00 0.70 1.39 83.25 16.49 0.00 0.25 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.39 83.71 16.29 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.39 84.24 15.76 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.39 76.55 22.39 0.28 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.78 1.39 62.52 16.50 0.00 0.00 11.04 5.75 0.00 0.00 0.00 0.20 3.99 0.00 1.39 52.39 29.53 0.00 1.15 5.18 8.22 0.00 2.28 0.91 0.00 0.33 0.00 1.39 78.51 12.43 0.00 0.00 3.36 4.08 0.00 0.72 0.00 0.00 0.90 0.00 1.39 76.09 11.51 0.00 0.00 2.46 7.47 0.00 1.14 0.15 0.19 0.99 0.00 1.35 82.81 16.64 0.00 0.21 0.19 0.14 0.00 0.00 0.00 0.00 0.00 0.00 1.35 84.00 15.78 0.00 0.22 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.35 82.98 17.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.35 81.55 18.45 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.35 84.89 14.38 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.73

252

Table A1-8 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.35 47.52 22.14 0.46 10.47 0.43 0.24 0.00 0.00 18.75 0.00 0.00 0.00 1.35 60.41 17.37 0.00 0.00 7.78 8.70 0.00 1.60 0.00 0.00 4.14 0.00 1.31 80.48 19.09 0.00 0.00 0.00 0.21 0.00 0.00 0.22 0.00 0.00 0.00 1.31 81.51 18.49 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.31 82.88 17.12 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.31 84.03 15.97 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.27 77.96 21.33 0.00 0.33 0.20 0.17 0.00 0.00 0.00 0.00 0.00 0.00 1.27 81.24 18.65 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.11 0.00 0.00 1.27 79.53 20.47 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.27 83.32 16.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.68 1.27 44.19 24.15 0.00 10.06 0.00 0.00 0.00 0.00 21.61 0.00 0.00 0.00 1.27 76.18 11.07 0.00 0.23 4.42 3.35 0.00 0.30 0.00 0.00 4.44 0.00 1.23 83.17 16.25 0.00 0.00 0.30 0.16 0.00 0.12 0.00 0.00 0.00 0.00 1.23 82.88 17.12 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.23 78.20 21.80 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.23 83.86 16.14 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.23 83.40 16.60 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.23 82.98 16.87 0.00 0.00 0.00 0.15 0.00 0.00 0.00 0.00 0.00 0.00 1.23 79.66 20.02 0.00 0.00 0.00 0.31 0.00 0.00 0.00 0.00 0.00 0.00 1.23 66.03 17.43 0.00 2.83 1.84 1.94 0.00 0.00 7.72 0.00 2.21 0.00 1.23 54.69 32.52 0.00 0.00 1.77 1.98 1.13 0.39 5.56 0.00 1.11 0.86 1.18 82.32 17.15 0.00 0.00 0.30 0.23 0.00 0.00 0.00 0.00 0.00 0.00 1.18 82.33 17.13 0.00 0.28 0.26 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.18 80.96 18.79 0.00 0.00 0.00 0.00 0.12 0.00 0.13 0.00 0.00 0.00 1.18 79.21 20.79 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.18 80.91 19.09 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.18 78.94 21.06 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.18 80.18 19.82 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 253

Table A1-8 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.18 81.93 18.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.18 84.84 14.98 0.00 0.00 0.00 0.18 0.00 0.00 0.00 0.00 0.00 0.00 1.18 80.65 18.57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.78 1.18 48.44 27.02 0.00 0.00 12.64 7.06 0.00 0.00 0.25 0.19 3.67 0.73 1.18 47.54 29.57 0.00 0.00 10.43 7.16 0.00 0.74 0.00 0.00 3.56 0.99 1.18 62.67 14.21 0.00 0.00 8.75 8.12 0.00 2.02 0.00 0.00 4.23 0.00 1.18 45.16 23.41 0.00 0.66 8.17 10.53 0.00 2.70 0.00 0.00 9.36 0.00 1.14 78.67 19.27 0.00 0.00 0.52 0.40 0.00 0.00 0.00 0.00 0.17 0.97 1.14 86.24 12.51 0.00 0.24 0.24 0.15 0.00 0.15 0.14 0.12 0.20 0.00 1.14 86.15 12.92 0.00 0.18 0.21 0.00 0.15 0.14 0.00 0.11 0.12 0.00 1.14 83.05 16.77 0.00 0.00 0.18 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.14 79.92 19.81 0.00 0.27 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.14 85.47 14.53 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.14 79.05 20.95 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.14 82.55 17.45 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.14 81.43 18.57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.14 82.80 17.20 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.14 80.60 19.40 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.14 79.76 20.24 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.14 82.98 16.75 0.27 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.14 79.23 19.92 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.85 1.14 66.39 20.38 0.00 0.00 5.09 4.25 0.00 0.55 0.49 0.00 2.86 0.00 1.14 50.12 21.81 0.00 0.00 1.71 25.25 0.15 0.23 0.13 0.00 0.60 0.00 1.09 73.26 21.71 0.00 0.00 1.43 0.89 0.00 0.18 0.00 0.16 2.35 0.00 1.09 80.01 17.81 0.25 0.20 0.36 0.32 0.20 0.19 0.16 0.20 0.29 0.00 1.09 79.65 18.63 0.29 0.32 0.28 0.17 0.00 0.00 0.00 0.00 0.00 0.66 1.09 83.90 15.81 0.00 0.00 0.16 0.13 0.00 0.00 0.00 0.00 0.00 0.00

254

Table A1-8 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.09 79.57 20.43 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.09 81.44 18.56 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.09 79.35 20.65 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.09 81.73 18.27 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.09 84.64 14.69 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.67 1.09 82.55 16.54 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.91 1.09 49.02 21.85 0.00 0.34 13.55 6.62 0.22 0.66 0.18 0.20 7.36 0.00 1.09 46.81 19.70 0.00 0.00 12.63 12.71 0.00 5.53 0.28 0.00 2.33 0.00 1.09 49.69 17.22 0.00 0.62 11.98 11.70 0.00 3.56 0.23 0.00 5.01 0.00 1.09 56.91 18.68 0.00 0.00 11.73 9.69 0.00 0.21 0.24 0.17 2.37 0.00 1.09 58.19 17.68 0.00 0.43 9.05 9.53 0.00 2.21 0.00 0.00 2.91 0.00 1.09 45.49 25.13 0.00 0.00 6.21 19.89 0.00 0.72 0.00 0.00 2.56 0.00 1.04 80.45 18.54 0.00 0.23 0.13 0.21 0.12 0.00 0.00 0.18 0.13 0.00 1.04 84.70 14.62 0.41 0.27 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.04 84.46 14.65 0.00 0.26 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.63 1.04 81.67 17.93 0.00 0.00 0.00 0.17 0.00 0.00 0.00 0.00 0.23 0.00 1.04 81.27 18.73 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.04 77.42 22.58 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.04 83.80 16.20 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.04 80.16 19.84 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.04 77.93 22.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.04 83.68 16.32 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.04 86.11 13.89 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.04 84.03 15.97 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.04 78.41 21.48 0.00 0.00 0.00 0.00 0.11 0.00 0.00 0.00 0.00 0.00 1.04 84.08 15.78 0.00 0.00 0.00 0.00 0.13 0.00 0.00 0.00 0.00 0.00 1.04 78.02 21.84 0.00 0.00 0.00 0.14 0.00 0.00 0.00 0.00 0.00 0.00 1.04 84.61 15.25 0.00 0.00 0.00 0.00 0.14 0.00 0.00 0.00 0.00 0.00

255

Table A1-8 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.04 82.17 17.56 0.27 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.04 80.52 18.73 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.75 1.04 71.68 19.89 0.00 0.00 0.00 1.08 0.91 0.00 6.45 0.00 0.00 0.00 1.04 55.36 19.94 0.00 0.46 7.68 8.68 0.00 2.18 0.00 0.00 5.71 0.00 1.04 54.70 23.52 0.00 0.00 7.60 7.91 0.26 1.62 0.00 0.00 4.39 0.00 1.04 30.90 31.48 0.00 0.34 3.02 32.25 0.00 0.57 0.00 0.31 1.13 0.00 1.04 71.94 20.91 0.00 0.00 2.63 2.87 0.00 0.55 0.14 0.13 0.83 0.00 1.04 63.35 22.00 0.00 0.00 0.71 12.78 0.00 0.31 0.34 0.24 0.28 0.00 1.04 61.15 14.48 0.00 0.00 0.31 24.07 0.00 0.00 0.00 0.00 0.00 0.00

256

TableA1-9. Normalised EDS data, station 6, 2-14 December 2011.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

24.61 37.78 25.10 0.00 0.00 4.30 2.24 0.00 0.26 0.00 0.00 30.32 0.00 20.23 53.60 8.19 1.03 0.84 1.08 0.75 0.68 33.21 0.24 0.38 0.00 0.00 15.65 37.68 29.42 0.00 0.00 1.37 29.45 0.17 0.31 0.22 0.29 1.09 0.00 14.17 45.15 28.53 0.50 0.29 10.17 10.17 0.00 3.39 0.00 0.00 1.80 0.00 13.85 38.51 27.07 0.00 0.00 2.05 30.68 0.00 0.56 0.00 0.00 1.13 0.00 11.63 41.72 29.88 0.00 0.00 0.74 27.14 0.00 0.20 0.00 0.00 0.33 0.00 8.06 49.88 20.23 0.00 0.25 0.55 28.63 0.00 0.00 0.00 0.19 0.28 0.00 3.71 59.84 19.74 0.29 0.00 1.77 0.97 0.00 0.00 0.00 0.00 17.38 0.00 3.2 52.93 20.37 0.00 0.00 0.49 25.13 0.00 0.20 0.12 0.32 0.44 0.00 1.94 65.86 22.32 0.00 0.00 5.37 3.16 0.00 0.28 0.00 0.00 2.43 0.58

257

Table A1-10. Normalised EDS data, station 6. 13-20 September 2012.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

41.72 78.65 20.41 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.94 26.38 82.81 16.42 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.77 24.22 82.61 16.67 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.72 22.13 77.90 21.42 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.68 21.69 81.63 18.16 0.00 0.00 0.21 0.00 0.00 0.00 0.00 0.00 0.00 0.00 19.78 79.83 20.02 0.00 0.00 0.00 0.00 0.15 0.00 0.00 0.00 0.00 0.00 18.66 79.63 20.37 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 18.3 80.41 19.59 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 18.28 78.70 21.30 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 16.95 84.00 16.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 11.47 83.10 16.90 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 11.33 79.65 20.35 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 11.17 79.41 20.59 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 11.03 79.69 20.31 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 10.71 80.25 19.75 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 10.51 79.64 20.01 0.00 0.00 0.20 0.15 0.00 0.00 0.00 0.00 0.00 0.00 10.01 79.91 19.60 0.00 0.00 0.19 0.18 0.12 0.00 0.00 0.00 0.00 0.00 9.91 80.87 19.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.13 0.00 0.00 9.55 80.34 19.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.16 0.00 9.43 80.50 19.03 0.00 0.00 0.00 0.17 0.11 0.00 0.00 0.19 0.00 0.00 8.4 83.19 15.89 0.32 0.23 0.22 0.15 0.00 0.00 0.00 0.00 0.00 0.00 8.25 79.80 19.95 0.00 0.25 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 7.14 78.16 21.04 0.00 0.00 0.00 0.19 0.15 0.15 0.00 0.15 0.14 0.00 5.41 50.42 21.29 0.00 0.00 0.81 27.14 0.00 0.00 0.00 0.00 0.34 0.00 5.26 81.67 17.98 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.17 0.18 0.00 4.9 81.39 18.08 0.00 0.00 0.00 0.00 0.00 0.16 0.11 0.12 0.14 0.00 4.67 59.51 29.06 0.00 0.00 4.60 4.61 0.00 1.73 0.00 0.00 0.48 0.00 4.55 43.65 32.75 4.23 0.00 5.41 13.29 0.00 0.00 0.14 0.18 0.35 0.00

258

Table A1-10 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

4.22 62.96 21.83 0.00 0.00 1.17 13.18 0.00 0.17 0.00 0.00 0.68 0.00 4.09 45.09 19.17 0.00 0.00 1.20 33.07 0.19 0.38 0.00 0.28 0.64 0.00 4 22.73 36.44 0.00 0.00 0.83 38.75 0.00 0.25 0.22 0.29 0.49 0.00 3.92 76.94 15.00 0.00 0.00 3.33 3.10 0.00 0.57 0.00 0.00 1.06 0.00 3.87 41.55 26.27 0.00 0.23 2.19 28.19 0.00 0.63 0.19 0.00 0.75 0.00 3.26 69.57 23.86 0.00 0.00 0.77 4.61 0.00 0.00 0.00 0.25 0.94 0.00 3.09 48.91 27.19 0.00 0.00 1.06 21.44 0.00 0.21 0.22 0.28 0.70 0.00 3.06 63.44 26.56 0.00 0.00 3.75 3.52 0.00 1.05 0.11 0.00 1.10 0.48 3 69.00 22.51 0.00 0.00 2.91 3.44 0.00 0.74 0.00 0.00 1.41 0.00 2.97 58.15 10.50 0.00 0.00 11.73 13.61 0.00 4.23 0.26 0.00 1.52 0.00 2.97 42.54 35.63 0.00 0.43 8.62 9.11 0.00 2.61 0.00 0.00 1.06 0.00 2.93 68.17 23.94 0.00 0.00 2.87 2.76 0.00 0.45 0.00 0.00 1.81 0.00 2.7 61.17 15.27 0.00 0.28 8.87 10.14 0.00 2.68 0.00 0.00 1.58 0.00 2.66 50.61 26.85 0.29 0.31 9.53 9.47 0.00 1.36 0.16 0.00 1.41 0.00 2.48 58.90 16.81 0.00 0.00 8.07 13.02 0.00 0.92 0.22 0.00 2.08 0.00 2.32 46.57 25.79 0.00 0.68 2.53 22.07 0.00 0.70 0.23 0.18 1.24 0.00 2.29 16.53 46.64 0.00 0.58 13.56 15.86 0.00 5.02 0.22 0.23 1.36 0.00 2.25 62.24 24.83 0.00 0.00 5.58 4.54 0.00 0.39 0.56 0.00 1.85 0.00 2.05 62.04 24.20 1.37 0.36 3.14 5.86 0.00 0.11 1.47 0.00 0.79 0.66 1.91 70.45 24.19 0.00 0.46 1.27 1.08 0.15 0.21 1.05 0.18 0.96 0.00 1.88 45.98 27.79 0.00 0.82 8.95 10.69 0.00 3.59 0.18 0.25 1.76 0.00 1.88 72.05 14.40 0.00 0.00 5.91 3.91 0.00 0.84 0.22 0.00 2.66 0.00 1.83 65.28 24.33 0.43 0.34 3.08 3.30 0.00 0.26 1.13 0.11 1.75 0.00 1.7 65.92 17.97 0.00 0.00 8.18 3.72 0.00 0.57 0.19 0.00 3.45 0.00 1.67 56.39 25.60 0.41 2.09 6.54 5.76 0.12 0.30 0.39 0.00 1.60 0.79 1.61 53.51 23.41 0.00 0.26 10.48 7.51 0.00 0.64 0.19 0.00 4.00 0.00

259

Table A1-10 cont.

AvgDiam CK OK NaK MgK AlK SiK SK KK CaK MnK FeK AsK

1.54 72.47 22.19 0.00 0.00 0.00 0.40 0.00 0.00 4.94 0.00 0.00 0.00 1.5 67.24 10.13 0.00 0.54 8.34 6.45 0.00 2.81 1.16 0.00 3.32 0.00 1.5 59.19 25.05 0.00 0.00 5.61 4.12 0.00 0.32 0.81 0.12 4.78 0.00 1.47 62.01 19.69 0.00 0.00 4.73 5.67 0.00 0.61 0.16 0.16 6.98 0.00 1.47 64.79 22.73 0.00 0.00 2.41 2.24 0.00 0.33 0.00 0.00 6.79 0.71 1.47 71.84 20.97 0.00 0.00 0.00 0.72 0.33 0.00 5.77 0.12 0.24 0.00 1.27 37.33 26.44 0.00 0.00 11.85 12.24 0.22 3.31 0.37 0.00 7.56 0.66 1.27 61.03 24.21 0.00 0.00 3.00 2.42 0.00 0.62 0.15 0.16 8.42 0.00 1.18 61.79 23.68 0.00 0.00 2.65 2.21 0.00 0.45 0.00 0.00 8.81 0.41 1.14 31.18 34.42 0.00 0.52 13.42 10.26 0.00 1.34 0.42 0.00 8.44 0.00 1.14 54.29 15.03 0.00 1.02 8.26 8.94 0.00 3.24 1.58 0.00 6.39 1.26 1.14 48.07 24.54 0.00 0.00 8.96 6.75 0.00 0.62 0.28 0.23 10.54 0.00 1.14 42.30 35.83 0.00 0.82 5.68 5.04 0.00 0.37 2.33 0.00 7.11 0.51 1.09 26.38 31.05 0.00 0.00 13.13 10.24 0.00 0.53 0.28 0.29 17.35 0.75 1.09 39.35 23.36 0.00 0.33 6.98 5.40 0.00 0.37 0.24 0.00 23.97 0.00 1.09 41.40 31.49 0.00 0.34 4.32 2.88 0.00 0.57 0.27 0.32 18.42 0.00 1.09 51.07 27.76 0.37 5.81 2.50 2.12 0.00 0.34 8.33 0.00 1.69 0.00 1.04 43.40 22.28 0.77 0.72 1.07 0.79 0.39 0.00 30.01 0.00 0.57 0.00

260

Appendix 2

Particle Size Distribution, Congonhas

261

Table A2- 1.Particle Size Distribution for Basilica (BAS). CR wt%- cumulative retained weight percent, CP wt%- cumulative passing weight percent.

µm CR wt% CP wt% µm CR wt% CP wt% µm CR wt% CP wt% January 2015 May 2015 August 2015 75 0.00 100.00 75 0.00 100.00 75 0.00 100.00 63 2.55 97.45 63 0.00 100.00 63 0.00 100.00 53 4.18 95.82 53 0.48 99.52 53 0.00 100.00 45 5.57 94.43 45 1.39 98.61 45 2.66 97.34 38 6.38 93.62 38 1.77 98.23 38 2.66 97.34 32 7.67 92.33 32 2.89 97.11 32 2.66 97.34 27 9.84 90.16 27 4.89 95.11 27 5.52 94.48 22 11.92 88.08 22 8.98 91.02 22 7.91 92.09 19 14.37 85.63 19 12.35 87.65 19 10.19 89.81 16 16.92 83.08 16 17.50 82.50 16 12.25 87.75 13.5 19.09 80.91 13.5 23.71 76.29 13.5 16.42 83.58 11.4 22.60 77.40 11.4 30.91 69.09 11.4 23.49 76.51 9.6 27.39 72.61 9.6 38.82 61.18 9.6 32.98 67.02 8.1 32.81 67.19 8.1 46.80 53.20 8.1 41.90 58.10 6.8 39.05 60.95 6.8 55.95 44.05 6.8 51.50 48.50 5.7 46.21 53.79 5.7 65.04 34.96 5.7 61.48 38.52 4.8 54.16 45.84 4.8 72.88 27.12 4.8 68.73 31.27 4.1 61.91 38.09 4.1 79.48 20.52 4.1 74.90 25.10 3.4 70.61 29.39 3.4 86.52 13.48 3.4 81.21 18.79 2.9 77.35 22.65 2.9 90.97 9.03 2.9 86.03 13.97 2.4 83.69 16.31 2.4 95.13 4.87 2.4 90.73 9.27 2 88.55 11.45 2 98.29 1.71 2 94.15 5.85 1.75 91.53 8.47 1.75 99.42 0.58 1.75 95.88 4.12 1.45 94.64 5.36 1.45 99.99 0.01 1.45 97.68 2.32 1.2 96.77 3.23 1.2 99.99 0.01 1.2 98.82 1.18 1 98.30 1.70 1 100.00 0.00 1 99.61 0.39 0.87 99.01 0.99 0.87 100.00 0.00 0.87 99.91 0.09 0.73 99.74 0.26 0.73 100.00 0.00 0.73 100.00 0.00 0.62 99.99 0.01 0.62 100.00 0.00 0.62 100.00 0.00 0.52 99.99 0.01 0.52 100.00 0.00 0.52 100.00 0.00 0 100.00 0.00 0 100.00 0.00 0 100.00 0.00

262

Table A2-2. Particle Size Distribution for Casa de Pedra (CDP). CR wt%- cumulative retained weight percent, CP wt%- cumulative passing weight percent.

µm CR wt% CP wt% µm CR wt% CP wt% µm CR wt% CP wt% January 2015 May 2015 August 2015 53 0.00 100.00 75 0.00 100.00 27 0.00 100.00 45 2.98 97.02 63 2.37 97.63 22 0.00 100.00 38 2.98 97.02 53 2.37 97.63 19 2.60 97.40 32 10.39 89.61 45 2.37 97.63 16 8.08 91.92 27 11.44 88.56 38 2.98 97.02 13.5 12.38 87.62 22 12.12 87.88 32 3.41 96.59 11.4 16.76 83.24 19 12.74 87.26 27 3.99 96.01 9.6 23.14 76.86 16 14.82 85.18 22 4.78 95.22 8.1 32.72 67.28 13.5 16.62 83.38 19 5.44 94.56 6.8 40.94 59.06 11.4 20.31 79.69 16 6.58 93.42 5.7 48.52 51.48 9.6 25.62 74.38 13.5 8.79 91.21 4.8 54.79 45.21 8.1 32.60 67.40 11.4 12.58 87.42 4.1 62.07 37.93 6.8 40.77 59.23 9.6 17.92 82.08 3.4 69.39 30.61 5.7 49.95 50.05 8.1 25.21 74.79 2.9 75.50 24.50 4.8 60.11 39.89 6.8 35.08 64.92 2.4 81.71 18.29 4.1 68.02 31.98 5.7 46.43 53.57 2 87.08 12.92 3.4 77.54 22.46 4.8 58.28 41.72 1.75 90.71 9.29 2.9 83.46 16.54 4.1 67.94 32.06 1.45 94.40 5.60 2.4 89.74 10.26 3.4 78.58 21.42 1.2 97.04 2.96 2 94.18 5.82 2.9 85.65 14.35 1 99.08 0.92 1.75 96.29 3.71 2.4 92.03 7.97 0.87 99.70 0.30 1.45 98.21 1.79 2 97.18 2.82 0.73 99.99 0.01 1.2 99.12 0.88 1.75 99.27 0.73 0.62 100.00 0.00 1 99.62 0.38 1.45 99.96 0.04 0.52 100.00 0.00 0.87 99.80 0.20 1.2 99.97 0.03 0 100.00 0.00 0.73 99.95 0.05 1 100.00 0.00 0.62 100.00 0.00 0.87 100.00 0.00 0.52 100.00 0.00 0.73 100.00 0.00

263

Table A2-3.Particle Size Distribution for Pires (PIR). CR wt%- cumulative retained weight percent, CP wt%- cumulative passing weight percent.

µm CR wt% CP wt% µm CR wt% CP wt% µm CR wt% CP wt% January 2015 May 2015 August 2015 22 0.00 100.00 150 0.00 100.00 45 0.00 100.00 19 1.92 98.08 125 0.57 99.43 38 2.81 97.19 16 1.92 98.08 106 0.57 99.43 32 2.81 97.19 13.5 5.60 94.40 90 0.57 99.43 27 3.39 96.61 11.4 7.43 92.57 75 0.77 99.23 22 4.06 95.94 9.6 11.78 88.22 63 0.90 99.10 19 6.77 93.23 8.1 15.43 84.57 53 0.90 99.10 16 14.47 85.53 6.8 21.19 78.81 45 1.04 98.96 13.5 20.46 79.54 5.7 28.43 71.57 38 1.47 98.53 11.4 26.32 73.68 4.8 36.20 63.80 32 1.91 98.09 9.6 36.95 63.05 4.1 43.84 56.16 27 3.00 97.00 8.1 46.29 53.71 3.4 53.06 46.94 22 5.19 94.81 6.8 57.55 42.45 2.9 61.61 38.39 19 7.96 92.04 5.7 66.68 33.32 2.4 70.38 29.62 16 13.05 86.95 4.8 74.13 25.87 2 78.02 21.98 13.5 19.96 80.04 4.1 79.40 20.60 1.75 83.16 16.84 11.4 28.97 71.03 3.4 84.74 15.26 1.45 88.92 11.08 9.6 39.15 60.85 2.9 88.58 11.42 1.2 92.99 7.01 8.1 49.43 50.57 2.4 92.31 7.69 1 96.12 3.88 6.8 59.74 40.26 2 95.33 4.67 0.87 97.68 2.32 5.7 68.99 31.01 1.75 96.52 3.48 0.73 99.32 0.68 4.8 77.01 22.99 1.45 98.01 1.99 0.62 99.98 0.02 4.1 83.14 16.86 1.2 99.00 1.00 0.52 99.99 0.01 3.4 89.19 10.81 1 99.66 0.34 0 100.00 0.00 2.9 93.00 7.00 0.87 99.91 0.09 2.4 96.21 3.79 0.73 100.00 0.00 2 98.68 1.32 0.62 100.00 0.00 1.75 99.64 0.36 0.52 100.00 0.00 1.45 99.97 0.03 0 100.00 0.00 1.2 99.98 0.02 1 100.00 0.00

264

Table A2-4. Particle Size Distribution for plataforma (PLA). CR wt%- cumulative retained weight percent, CP wt%- cumulative passing weight percent.

µm CR wt% CP wt% µm CR wt% CP wt% µm CR wt% CP wt% January 2015 May 2015 August 2015 32 0.00 100.00 125 0.00 100.00 45 0.00 100.00 27 0.53 99.47 106 2.37 97.63 38 3.33 96.67 22 4.27 95.73 90 8.19 91.81 32 3.33 96.67 19 5.52 94.48 75 14.46 85.54 27 7.21 92.79 16 7.52 92.48 63 15.88 84.12 22 11.44 88.56 13.5 9.30 90.70 53 17.99 82.01 19 12.95 87.05 11.4 12.92 87.08 45 19.52 80.48 16 17.52 82.48 9.6 18.26 81.74 38 20.52 79.48 13.5 21.93 78.07 8.1 24.38 75.62 32 24.19 75.81 11.4 28.97 71.03 6.8 32.65 67.35 27 27.65 72.35 9.6 37.93 62.07 5.7 41.20 58.80 22 33.14 66.86 8.1 45.97 54.03 4.8 51.05 48.95 19 36.51 63.49 6.8 55.35 44.65 4.1 60.41 39.59 16 40.20 59.80 5.7 64.24 35.76 3.4 70.62 29.38 13.5 45.24 54.76 4.8 71.67 28.33 2.9 78.02 21.98 11.4 50.17 49.83 4.1 77.64 22.36 2.4 84.93 15.07 9.6 55.03 44.97 3.4 83.53 16.47 2 89.96 10.04 8.1 59.90 40.10 2.9 87.99 12.01 1.75 92.85 7.15 6.8 64.78 35.22 2.4 91.73 8.27 1.45 95.63 4.37 5.7 70.08 29.92 2 94.79 5.21 1.2 97.53 2.47 4.8 74.45 25.55 1.75 96.17 3.83 1 98.75 1.25 4.1 78.27 21.73 1.45 97.79 2.21 0.87 99.30 0.70 3.4 83.01 16.99 1.2 98.87 1.13 0.73 99.81 0.19 2.9 87.13 12.87 1 99.63 0.37 0.62 100.00 0.00 2.4 91.89 8.11 0.87 99.89 0.11 0.52 100.00 0.00 2 96.73 3.27 0.73 100.00 0.00 0 100.00 0.00 1.75 99.22 0.78 0.62 100.00 0.00 1.45 99.96 0.04 0.52 100.00 0.00 1.2 99.98 0.02 0 100.00 0.00 1 100.00 0.00

265

Table A2-5.Particle Size Distribution for Retiro (RET). CR wt%- cumulative retained weight percent, CP wt%- cumulative passing weight percent.

µm CR wt% CP wt% µm CR wt% CP wt% µm CR wt% CP wt% January 2015 May 2015 August 2015 75 0.00 100.00 75 0.00 100.00 53 0.00 100.00 63 2.86 97.14 63 0.67 99.33 45 3.10 96.90 53 2.86 97.14 53 0.67 99.33 38 3.10 96.90 45 4.23 95.77 45 0.67 99.33 32 3.10 96.90 38 5.21 94.79 38 0.86 99.14 27 5.12 94.88 32 7.43 92.57 32 1.57 98.43 22 8.81 91.19 27 8.43 91.57 27 2.36 97.64 19 10.65 89.35 22 11.00 89.00 22 4.95 95.05 16 13.14 86.86 19 14.08 85.92 19 6.62 93.38 13.5 18.74 81.26 16 17.70 82.30 16 9.81 90.19 11.4 27.50 72.50 13.5 21.41 78.59 13.5 15.33 84.67 9.6 36.75 63.25 11.4 25.10 74.90 11.4 21.25 78.75 8.1 45.60 54.40 9.6 29.20 70.80 9.6 28.89 71.11 6.8 53.68 46.32 8.1 33.77 66.23 8.1 37.54 62.46 5.7 61.01 38.99 6.8 39.11 60.89 6.8 46.86 53.14 4.8 69.16 30.84 5.7 45.74 54.26 5.7 56.99 43.01 4.1 75.59 24.41 4.8 53.01 46.99 4.8 66.17 33.83 3.4 81.99 18.01 4.1 60.64 39.36 4.1 74.48 25.52 2.9 86.27 13.73 3.4 68.79 31.21 3.4 82.80 17.20 2.4 90.76 9.24 2.9 75.70 24.30 2.9 88.63 11.37 2 93.83 6.17 2.4 82.32 17.68 2.4 93.68 6.32 1.75 95.60 4.40 2 87.83 12.17 2 97.81 2.19 1.45 97.38 2.62 1.75 91.07 8.93 1.75 99.36 0.64 1.2 98.61 1.39 1.45 94.53 5.47 1.45 99.98 0.02 1 99.50 0.50 1.2 96.88 3.12 1.2 99.99 0.01 0.87 99.83 0.17 1 98.42 1.58 1 100.00 0.00 0.73 99.99 0.01 0.87 99.07 0.93 0.87 100.00 0.00 0.62 100.00 0.00 0.73 99.75 0.25 0.73 100.00 0.00 0.52 100.00 0.00 0.62 99.99 0.01 0.62 100.00 0.00 0 100.00 0.00 0.52 100.00 0.00 0.52 100.00 0.00

266

Appendix 3

TSP Modal Mineralogy, Congonhas

267

Table A3-1 TSP Modal Mineralogy, Basilica (BAS). Wt% - weight percent, PC- particle count, GC-grain count

Basilica Jan May August Mineral Phase Wt% PC GC Wt% P C G C Wt% PC GC Fe (hydr)Oxides 17.89 2912 2961 27.21 5224 5293 22.18 8767 9377 Al Rich - Fe (hydr)oxides 2.94 535 543 4.24 1059 1086 0.74 390 504 Chromite 0.14 25 25 0.03 17 18 0.03 28 31 Siderite 1.15 83 83 0.08 18 19 0.23 80 105 Calcite 23.68 3410 3495 6.26 2011 2029 5.14 2298 2568 Dolomite 2.57 449 458 0.49 181 181 1.10 651 680 Ankerite 0.03 4 5 0.00 1 1 0.02 12 15 Rhodonite 0.01 10 10 0.01 5 5 0.04 32 32 Spessartite 0.11 21 22 0.05 21 21 0.04 26 28 Romanechite 0.00 0 0 0.00 0 0 0.00 0 0 Jacobsite 0.33 23 23 0.19 33 33 0.41 107 120 Mn Oxide 0.11 36 36 0.12 31 31 0.00 1 1 Al rich - Mn oxide 0.07 2 2 0.12 8 8 0.04 15 17 Clay Minerals/Mica 32.56 5718 5848 44.81 12502 12581 55.62 20981 22824 Gibbsite 0.61 150 152 0.77 293 296 0.47 320 347 Chlorite 0.73 91 94 1.14 247 254 0.88 169 227 Serpentine 0.10 2 3 0.23 13 13 0.16 8 9 Quartz 2.48 353 356 4.12 844 854 3.39 1285 1378 Wollastonite 0.18 10 17 0.12 10 13 0.09 16 26 Carbonaceous Matter 7.51 5235 5674 5.23 5087 6208 4.49 23631 30383 Gypsum 1.27 162 178 0.15 63 64 0.16 172 200 Apatite 0.24 22 22 0.13 43 43 0.17 104 110 Xenotime-(Y) 0.00 0 0 0.00 0 0 0.01 1 1 Monazite-(La) 0.00 0 0 0.00 0 0 0.03 1 1 (Ti, Al, Fe, Si, O) Comp 0.32 59 60 0.52 166 168 0.43 349 373 Ilmenite 0.16 20 20 0.21 59 59 0.21 61 65 Anatase 0.04 7 7 0.48 167 168 0.14 64 66 Titanite 0.01 6 6 0.01 3 3 0.01 4 4 Orthoclase 0.17 13 15 0.55 74 76 0.40 119 143 Albite 0.61 76 76 0.70 177 178 0.56 169 199 Zircon 0.00 0 0 0.01 3 3 0.03 3 3 Epidote 0.13 10 10 0.12 14 14 0.05 27 32 Pyroxene 3.74 688 704 1.88 820 823 1.88 1521 1914 (Ca, Na, P, S, O) Comp 0.10 35 35 0.01 9 9 0.67 615 661 (Ca, Si, P, Na, S, O) Comp 0.00 0 0 0.00 1 1 0.19 164 177 Total 100.00 19702 23395 100.00 27767 32510 100.00 46181 72950

268

Table A3-2 TSP Modal Mineralogy, Casa de Pedra (CDP). Wt% - weight percent, PC- particle count, GC-grain count

Casa de Pedra January May August Mineral Phase Wt% PC GC Wt% PC GC Wt% PC GC Fe (hydr)Oxides 40.41 1552 1609 33.76 7259 7311 14.10 1189 1197 Al Rich - Fe (hydr)oxides 5.45 261 273 4.41 1252 1261 0.08 8 8 Chromite 0.19 2 5 0.01 2 2 0.00 1 1 Siderite 0.34 9 9 0.16 26 26 0.03 3 4 Calcite 6.21 292 301 2.60 895 902 27.16 3256 3275 Dolomite 0.47 30 30 0.42 161 161 0.68 71 71 Ankerite 0.00 0 0 0.01 3 3 0.09 1 1 Rhodonite 0.04 4 5 0.05 18 18 0.00 0 0 Spessartite 0.06 6 6 0.14 34 34 0.00 0 0 Romanechite 0.00 0 0 0.00 2 2 0.00 0 0 Jacobsite 0.63 18 18 0.69 112 112 0.20 5 8 Mn Oxide 0.19 18 18 0.27 96 96 0.02 4 4 Al rich - Mn oxide 0.06 3 3 0.03 8 8 0.00 0 0 Clay Minerals/Mica 35.50 1889 1944 45.05 13375 13411 20.26 1584 1590 Gibbsite 0.78 40 41 0.59 228 229 0.21 22 22 Chlorite 0.12 2 2 0.76 116 117 0.85 18 20 Serpentine 0.02 1 1 0.02 4 4 0.00 0 0 Quartz 2.31 74 76 3.36 1028 1035 0.64 54 55 Wollastonite 0.00 0 0 0.00 0 0 0.00 0 0 Carbonaceous Matter 3.96 1167 1248 5.19 5469 5474 3.92 5576 5778 Gypsum 0.26 12 18 0.12 42 42 0.34 46 48 Apatite 0.02 5 5 0.06 24 24 0.04 4 4 Xenotime-(Y) 0.00 0 0 0.00 0 0 0.00 0 0 Monazite-(La) 0.00 0 0 0.00 1 1 0.00 0 0 (Ti, Al, Fe, Si, O) Comp 0.16 14 14 0.32 91 91 0.23 20 22 Ilmenite 0.44 13 13 0.19 56 56 0.01 2 2 Anatase 0.17 5 5 0.11 38 38 0.01 2 2 Titanite 0.03 4 4 0.02 3 3 0.00 0 0 Orthoclase 0.13 5 5 0.12 35 35 0.06 3 3 Albite 0.29 9 9 0.53 155 155 0.12 6 7 Zircon 0.02 1 1 0.01 4 4 0.00 0 0 Epidote 0.37 3 3 0.07 16 16 0.00 0 0 Pyroxene 1.31 61 63 0.89 235 238 0.44 41 43 (Ca, Na, P, S, O) Comp 0.07 3 3 0.02 12 12 30.43 6107 6125 (Ca, Si, P, Na, S, O) Comp 0.00 0 0 0.00 1 1 0.08 10 10 Total 100.00 8894 10346 100.00 29808 31142 100.00 17002 18350

269

Table A3-3 TSP Modal Mineralogy, Pires (PIR). Wt% - weight percent, PC- particle count, GC-grain count

Pires January May August Mineral Phase Wt% PC GC Wt% PC GC Wt% PC GC Fe(hydr)oxides 13.78 857 872 23.35 18541 18887 22.52 4049 4367 Al Rich - Fe (hydr)oxides 6.07 374 398 8.46 7321 7515 5.52 996 1136 Chromite 0.02 3 3 0.00 8 8 0.01 6 6 Siderite 0.00 1 1 0.14 114 116 0.23 82 92 Calcite 14.96 1418 1431 5.94 8951 9123 6.28 1861 1987 Dolomite 1.31 113 114 1.08 1360 1373 1.32 302 314 Ankerite 0.00 0 0 0.03 19 21 0.01 3 4 Rhodochrosite 0.17 14 14 0.04 19 19 Rhodonite 0.01 2 2 0.01 8 8 0.00 0 0 Spessartite 0.06 10 11 0.05 68 68 0.01 5 5 Jacobsite 0.20 7 7 0.29 288 291 0.34 70 71 Mn Oxide 0.17 14 14 0.06 122 125 0.01 1 1 Al rich - Mn oxide 0.04 1 1 0.03 36 36 0.02 3 3 Clay Minerals/Mica 54.81 4906 4962 46.13 55335 56212 50.59 10697 11417 Gibbsite 0.53 54 55 0.74 1249 1257 0.54 186 198 Chlorite 0.13 7 7 0.43 390 407 0.18 47 52 Serpentine 0.00 0 0 0.04 14 16 0.00 0 0 Quartz 2.85 113 113 2.35 2110 2147 2.10 295 320 Wollastonite 0.00 0 0 0.06 18 18 0.01 1 1 Carbonaceous Matter 0.89 498 502 6.71 26788 27171 5.95 45583 46300 Gypsum 0.00 2 2 0.37 418 424 0.31 143 173 Apatite 0.09 9 9 0.09 135 136 0.12 43 49 Xenotime-(Y) 0.00 0 0 0.00 0 0 0.00 0 0 Monazite-(La) 0.00 0 0 0.00 1 1 0.00 0 0 (Ti, Al, Fe, Si, O) Comp 0.70 77 78 0.32 428 436 0.63 193 217 Ilmenite 0.30 20 20 0.22 246 250 0.22 66 85 Anatase 0.23 10 10 0.18 201 201 0.20 57 60 Titanite 0.00 0 0 0.01 11 11 0.04 4 5 Orthoclase 0.10 3 3 0.25 175 179 0.31 35 50 Albite 0.61 21 23 0.51 491 496 0.34 46 59 Zircon 0.04 1 1 0.01 13 13 0.00 0 0 Epidote 0.06 3 3 0.07 52 55 0.07 12 18 Pyroxene 1.99 132 134 2.06 2176 2237 1.94 620 739 (Ca, Na, P, S, O) Comp 0.05 8 8 0.00 9 9 0.14 62 67 (Ca, Si, P, Na, S, O) Comp 0.00 1 1 0.00 1 1 0.02 6 7 Total 100.00 8650 9340 100.00 115938 130973 100.00 60035 68104

270

TableA3-4 TSP Modal Mineralogy, plataforma (PLA). Wt% - weight percent, PC- particle count, GC-grain count

Plataforma January May August Mineral Phase Wt% PC GC Wt% PC GC Wt% PC GC Fe(hydr)oxides 49.71 6219 6638 29.03 1895 1941 35.06 12295 13499 Al Rich - Fe (hydr)oxides 5.47 1151 1220 2.71 298 321 0.94 651 915 Chromite 0.01 6 6 0.03 4 5 0.01 16 16 Siderite 0.27 25 29 0.02 2 2 0.05 46 54 Calcite 4.94 846 866 7.36 543 597 1.89 776 903 Dolomite 0.47 100 104 1.74 97 123 0.50 245 261 Ankerite 0.01 1 1 0.00 0 0 0.01 6 10 Rhodonite 0.04 11 11 0.00 1 1 0.00 1 1 Spessartite 0.07 23 23 0.02 3 3 0.02 14 14 Romanechite 0.00 0 0 0.00 0 0 0.00 1 1 Jacobsite 0.80 126 129 0.30 14 14 0.50 160 186 Pyrolusite 0.28 83 83 0.10 16 16 0.08 44 46 Al rich - Mn oxide 0.06 8 8 0.06 3 3 0.02 10 11 Clay Minerals/Mica 29.73 5962 6310 38.55 3727 3774 48.65 18583 21071 Gibbsite 0.89 205 210 0.82 110 110 1.15 737 840 Chlorite 0.26 31 35 0.36 20 21 0.61 92 121 Serpentine 0.00 3 3 0.14 1 2 0.05 6 14 Quartz 1.38 231 236 3.21 218 220 2.69 936 1031 Wollastonite 0.01 1 1 0.00 0 0 0.01 2 4 Carbonaceous Matter 2.55 2162 2191 11.35 12646 12663 4.68 28300 38160 Gypsum 0.23 89 94 0.20 45 49 0.12 120 153 Apatite 0.06 18 18 0.03 8 8 0.13 115 124 Xenotime-(Y) 0.00 0 0 0.00 0 0 0.00 0 0 Monazite-(La) 0.00 0 0 0.00 0 0 0.00 0 0 (Ti, Al, Fe, Si, O) Comp 0.17 58 60 0.40 38 38 0.40 389 436 Ilmenite 0.09 27 27 0.08 10 10 0.11 95 118 Anatase 0.10 19 19 0.22 15 15 0.29 111 118 Titanite 0.03 6 6 0.03 1 1 0.01 5 5 Orthoclase 0.10 14 15 0.41 18 19 0.15 61 77 Albite 0.63 84 88 0.24 23 25 0.23 96 113 Zircon 0.00 0 0 0.01 1 1 0.01 1 2 Epidote 0.05 4 4 0.01 2 2 0.00 6 6 Pyroxene 1.50 293 310 2.54 153 170 0.97 678 909 (Ca, Na, P, S, O) Comp 0.08 28 31 0.02 11 11 0.59 1149 1212 (Ca, Si, P, Na, S, O) Comp 0.00 0 0 0.00 1 1 0.07 59 67 Total 100.00 16509 19627 100.00 19601 20500 100.00 48189 80949

271

Table A3-5 TSP Modal Mineralogy, Retiro (RET). Wt% - weight percent, PC- particle count, GC-grain count

Retiro January May August Mineral Phase Wt% PC GC Wt% PC GC Wt% PC GC Fe (hydr)Oxides 26.90 3011 3078 18.26 4233 4268 27.10 3501 3627 Al Rich - Fe (hydr)oxides 3.74 648 675 2.38 722 735 0.79 102 125 Chromite 0.46 43 43 0.02 8 8 0.04 19 19 Siderite 0.06 11 11 0.02 6 7 0.06 5 6 Calcite 33.92 6133 6213 3.60 1315 1333 6.18 816 856 Dolomite 0.53 90 90 0.51 201 203 0.13 33 37 Ankerite 0.00 0 0 0.01 1 1 0.00 0 0 Rhodonite 0.00 1 2 0.01 4 4 0.00 0 0 Spessartite 0.00 2 2 0.06 19 19 0.00 1 1 Romanechite 0.00 1 1 0.02 1 1 0.00 0 0 Jacobsite 0.01 3 3 0.15 39 39 0.11 14 15 Mn Oxide 0.88 36 40 0.00 0 0 0.00 0 0 Al rich - Mn oxide 0.00 0 0 0.00 1 1 0.00 0 0 Clay Minerals/Mica 21.16 3407 3452 56.08 18512 18604 48.11 7339 7602 Gibbsite 0.44 90 91 0.54 177 180 0.35 62 65 Chlorite 0.76 69 74 0.99 172 178 3.65 386 423 Serpentine 0.20 8 8 0.11 12 12 0.41 15 29 Quartz 1.68 227 233 4.90 1434 1441 3.61 374 387 Wollastonite 0.00 0 0 0.04 8 9 0.03 2 3 Carbonaceous Matter 5.01 3593 3623 5.80 6587 6603 5.31 10170 11400 Gypsum 1.88 785 835 0.12 59 62 0.15 46 51 Apatite 0.06 17 19 0.08 30 31 0.07 18 19 Xenotime-(Y) 0.02 1 1 0.00 0 0 0.00 0 0 Monazite-(La) 0.00 0 0 0.01 2 2 0.00 0 0 (Ti, Al, Fe, Si, O) Comp 0.11 28 29 0.46 166 167 0.32 107 111 Ilmenite 0.09 13 13 0.14 43 43 0.09 13 13 Anatase 0.07 11 11 0.14 55 56 0.17 21 22 Titanite 0.02 4 4 0.01 2 2 0.01 1 1 Orthoclase 0.20 11 11 0.70 141 141 0.37 44 50 Albite 0.21 31 31 1.29 379 381 0.57 56 62 Zircon 0.00 1 1 0.00 3 3 0.00 0 0 Epidote 0.13 3 5 0.22 23 23 0.11 5 14 Pyroxene 1.41 191 197 3.29 775 780 1.24 243 294 (Ca, Na, P, S, O) Comp 0.03 10 10 0.02 22 22 0.89 496 505 (Ca, Si, P, Na, S, O) Comp 0.00 2 2 0.00 3 3 0.13 31 35 Total 100.00 18267 19649 100.00 34012 35689 100.00 20583 26242

272

Appendix 4

Particle Size Distribution for Selected Individual Mineral Phases

273

Table A4-1 Particle Size Distribution Fe (hydr)oxides. CR Wt%- cumulative retained weight percent, CP Wt%- cumulative passing weight percent.

Basilica January May August µm CR Wt% CP Wt% µm CR Wt% CP Wt% µm CR Wt% CP Wt% 9.6 0.00 100.00 16 0.00 100.00 11.4 0.00 100.00 8.1 2.57 97.43 13.5 0.92 99.08 9.6 0.66 99.34 6.8 6.18 93.82 11.4 6.35 93.65 8.1 7.02 92.98 5.7 10.53 89.47 9.6 15.25 84.75 6.8 12.68 87.32 4.8 18.04 81.96 8.1 26.04 73.96 5.7 20.05 79.95 4.1 27.05 72.95 6.8 38.08 61.92 4.8 27.37 72.63 3.4 38.81 61.19 5.7 51.84 48.16 4.1 35.56 64.44 2.9 50.15 49.85 4.8 64.76 35.24 3.4 47.82 52.18 2.4 61.91 38.09 4.1 74.70 25.30 2.9 56.44 43.56 2 72.10 27.90 3.4 85.55 14.45 2.4 66.05 33.95 1.75 78.43 21.57 2.9 90.46 9.54 2 75.75 24.25 1.45 86.07 13.93 2.4 94.66 5.34 1.75 83.20 16.80 1.2 91.96 8.04 2 97.67 2.33 1.45 90.75 9.25 1 95.40 4.60 1.75 98.67 1.33 1.2 94.41 5.59 0.87 97.21 2.79 1.45 99.67 0.33 1 96.50 3.50 0.73 98.96 1.04 1.2 99.91 0.09 0.87 97.58 2.42 0.62 99.79 0.21 1 100.00 0.00 0.73 98.86 1.14 0.52 99.92 0.08 0.87 100.00 0.00 0.62 99.86 0.14 0 100.00 0.00 0.73 100.00 0.00 0.52 99.98 0.02 0 100.00 0.00

Casa de Pedra January May August µm CR Wt% CP Wt% µm CR Wt% CP Wt% µm CR Wt% CP Wt% 13.5 0.00 100.00 19 0.00 100.00 11.4 0.00 100.00 11.4 1.15 98.85 16 0.69 99.31 9.6 5.70 94.30 9.6 4.18 95.82 13.5 1.12 98.88 8.1 5.70 94.30 8.1 7.59 92.41 11.4 2.64 97.36 6.8 11.74 88.26 6.8 14.91 85.09 9.6 6.64 93.36 5.7 13.76 86.24 5.7 23.15 76.85 8.1 12.82 87.18 4.8 19.65 80.35 4.8 36.60 63.40 6.8 21.24 78.76 4.1 26.85 73.15 4.1 48.39 51.61 5.7 32.12 67.88 3.4 35.69 64.31 3.4 61.97 38.03 4.8 45.27 54.73 2.9 43.66 56.34 2.9 72.08 27.92 4.1 56.97 43.03 2.4 54.09 45.91 2.4 82.80 17.20 3.4 70.33 29.67 2 69.87 30.13 2 90.45 9.55 2.9 79.38 20.62 1.75 75.78 24.22 1.75 93.88 6.12 2.4 88.41 11.59 1.45 82.28 17.72 1.45 97.10 2.90 2 95.37 4.63 1.2 86.56 13.44 1.2 98.57 1.43 1.75 98.46 1.54 1 91.99 8.01 1 99.38 0.62 1.45 99.68 0.32 0.87 94.08 5.92 0.87 99.65 0.35 1.2 99.88 0.12 0.73 96.74 3.26 0.73 99.89 0.11 1 100.00 0.00 0.62 99.80 0.20 0.62 99.97 0.03 0.87 100.00 0.00 0.52 100.00 0.00 0.52 99.98 0.02 0.73 100.00 0.00 0 100.00 0.00 0.62 100.00 0.00

274

Table A4-1 cont.

Pires January May August µm CR Wt% CP Wt% µm CR Wt% CP Wt% µm CR Wt% CP Wt% 11.4 0.00 100.00 38 0.00 100.00 16 0.00 100.00 9.6 3.62 96.38 32 0.28 99.72 13.5 1.02 98.98 8.1 3.62 96.38 27 0.28 99.72 11.4 2.27 97.73 6.8 7.36 92.64 22 1.02 98.98 9.6 6.91 93.09 5.7 11.34 88.66 19 2.54 97.46 8.1 12.74 87.26 4.8 17.86 82.14 16 5.27 94.73 6.8 17.55 82.45 4.1 29.35 70.65 13.5 8.98 91.02 5.7 25.10 74.90 3.4 38.16 61.84 11.4 17.01 82.99 4.8 32.88 67.12 2.9 47.85 52.15 9.6 27.96 72.04 4.1 42.22 57.78 2.4 59.26 40.74 8.1 38.60 61.40 3.4 51.70 48.30 2 69.49 30.51 6.8 48.94 51.06 2.9 58.63 41.37 1.75 75.42 24.58 5.7 59.17 40.83 2.4 68.30 31.70 1.45 82.78 17.22 4.8 68.54 31.46 2 79.00 21.00 1.2 89.31 10.69 4.1 76.51 23.49 1.75 85.30 14.70 1 93.95 6.05 3.4 84.34 15.66 1.45 91.54 8.46 0.87 96.44 3.56 2.9 89.47 10.53 1.2 94.85 5.15 0.73 98.59 1.41 2.4 94.00 6.00 1 97.20 2.80 0.62 99.66 0.34 2 97.49 2.51 0.87 98.48 1.52 0.52 99.84 0.16 1.75 98.91 1.09 0.73 99.09 0.91 0 100.00 0.00 1.45 99.67 0.33 0.62 99.81 0.19 1.2 99.88 0.12 0.52 99.99 0.01 1 100.00 0.00 0 100.00 0.00 0.73 100.00 0.00

Plataforma January May August µm CR Wt% CP Wt% µm CR Wt% CP Wt% µm CR Wt% CP Wt% 27 0.00 100.00 38 0.00 100.00 27 0.00 100.00 22 2.47 97.53 32 2.23 97.77 22 0.56 99.44 19 4.37 95.63 27 4.05 95.95 19 0.56 99.44 16 5.15 94.85 22 11.02 88.98 16 3.36 96.64 13.5 6.15 93.85 19 18.03 81.97 13.5 6.43 93.57 11.4 7.79 92.21 16 26.00 74.00 11.4 11.96 88.04 9.6 9.40 90.60 13.5 31.64 68.36 9.6 18.07 81.93 8.1 11.94 88.06 11.4 37.28 62.72 8.1 25.05 74.95 6.8 17.14 82.86 9.6 44.74 55.26 6.8 32.74 67.26 5.7 24.06 75.94 8.1 51.23 48.77 5.7 41.27 58.73 4.8 33.80 66.20 6.8 59.15 40.85 4.8 50.12 49.88 4.1 46.12 53.88 5.7 66.27 33.73 4.1 56.43 43.57 3.4 58.32 41.68 4.8 72.95 27.05 3.4 65.07 34.93 2.9 68.44 31.56 4.1 79.07 20.93 2.9 71.41 28.59 2.4 78.52 21.48 3.4 85.65 14.35 2.4 78.36 21.64 2 85.98 14.02 2.9 90.26 9.74 2 85.04 14.96 1.75 90.05 9.95 2.4 94.10 5.90 1.75 89.64 10.36 1.45 93.96 6.04 2 97.62 2.38 1.45 94.46 5.54 1.2 96.47 3.53 1.75 98.98 1.02 1.2 96.74 3.26 1 98.04 1.96 1.45 99.87 0.13 1 98.02 1.98 0.87 98.86 1.14 1.2 99.96 0.04 0.87 98.66 1.34 0.73 99.54 0.46 1 100.00 0.00 0.73 99.37 0.63 0.62 99.86 0.14 0.87 100.00 0.00 0.62 99.90 0.10 0.52 99.93 0.07 0.73 100.00 0.00 0.52 99.99 0.01 0 100.00 0.00 0.62 100.00 0.00 0 100.00 0.00

275

Table A4-1 cont.

Retiro January May August µm CR Wt% CP Wt% µm CR Wt% CP Wt% µm CR Wt% CP Wt% 27 0.00 100.00 22 0.00 100.00 13.5 0.00 100.00 22 2.90 97.10 19 0.75 99.25 11.4 1.48 98.52 19 2.90 97.10 16 1.28 98.72 9.6 5.97 94.03 16 4.69 95.31 13.5 4.47 95.53 8.1 10.90 89.10 13.5 5.86 94.14 11.4 8.00 92.00 6.8 20.10 79.90 11.4 7.59 92.41 9.6 15.55 84.45 5.7 26.67 73.33 9.6 10.60 89.40 8.1 23.86 76.14 4.8 36.57 63.43 8.1 14.10 85.90 6.8 32.51 67.49 4.1 44.55 55.45 6.8 17.50 82.50 5.7 43.51 56.49 3.4 53.60 46.40 5.7 24.88 75.12 4.8 54.52 45.48 2.9 62.07 37.93 4.8 32.64 67.36 4.1 65.40 34.60 2.4 72.81 27.19 4.1 42.76 57.24 3.4 75.99 24.01 2 83.30 16.70 3.4 54.41 45.59 2.9 83.78 16.22 1.75 88.56 11.44 2.9 64.03 35.97 2.4 90.60 9.40 1.45 92.39 7.61 2.4 73.84 26.16 2 96.55 3.45 1.2 94.93 5.07 2 81.54 18.46 1.75 98.71 1.29 1 97.12 2.88 1.75 86.11 13.89 1.45 99.76 0.24 0.87 97.92 2.08 1.45 91.52 8.48 1.2 99.91 0.09 0.73 98.97 1.03 1.2 95.06 4.94 1 100.00 0.00 0.62 99.89 0.11 1 97.54 2.46 0.87 100.00 0.00 0.52 100.00 0.00 0.87 98.57 1.43 0.73 100.00 0.00 0 100.00 0.00 0.73 99.56 0.44 0.62 100.00 0.00 0.62 99.93 0.07 0.52 99.97 0.03 0 100.00 0.00

276

Table A4-2 Particle Size Distribution Clay minerals. CR Wt%- cumulative retained weight percent, CP Wt%- cumulative passing weight percent.

Basilica January May August µm CR Wt% CP Wt% µm CR Wt% CP Wt% µm CR Wt% CP Wt% 22 0.00 100.00 53 0.00 100.00 27 0.00 100.00 19 2.06 97.94 45 0.83 99.17 22 1.65 98.35 16 4.27 95.73 38 1.35 98.65 19 4.28 95.72 13.5 5.36 94.64 32 1.35 98.65 16 8.41 91.59 11.4 7.74 92.26 27 1.98 98.02 13.5 14.06 85.94 9.6 10.84 89.16 22 3.38 96.62 11.4 21.45 78.55 8.1 16.00 84.00 19 6.50 93.50 9.6 29.47 70.53 6.8 21.89 78.11 16 10.14 89.86 8.1 37.87 62.13 5.7 29.14 70.86 13.5 16.98 83.02 6.8 46.35 53.65 4.8 39.87 60.13 11.4 24.64 75.36 5.7 54.58 45.42 4.1 49.34 50.66 9.6 33.22 66.78 4.8 61.43 38.57 3.4 60.75 39.25 8.1 42.32 57.68 4.1 67.65 32.35 2.9 69.98 30.02 6.8 52.83 47.17 3.4 74.52 25.48 2.4 78.82 21.18 5.7 63.38 36.62 2.9 79.58 20.42 2 85.35 14.65 4.8 71.83 28.17 2.4 84.97 15.03 1.75 89.39 10.61 4.1 78.88 21.12 2 89.70 10.30 1.45 93.49 6.51 3.4 86.17 13.83 1.75 92.96 7.04 1.2 96.19 3.81 2.9 90.98 9.02 1.45 96.30 3.70 1 98.02 1.98 2.4 95.14 4.86 1.2 98.00 2.00 0.87 98.82 1.18 2 98.35 1.65 1 98.91 1.09 0.73 99.65 0.35 1.75 99.38 0.62 0.87 99.25 0.75 0.62 99.94 0.06 1.45 99.96 0.04 0.73 99.64 0.36 0.52 99.97 0.03 1.2 99.98 0.02 0.62 99.96 0.04 0 100.00 0.00 1 100.00 0.00 0.52 99.99 0.01 0.87 100.00 0.00 0 100.00 0.00

277

Table A4-2 cont.

Casa de Pedra January May August µm CR Wt% CP Wt% µm CR Wt% CP Wt% µm CR Wt% CP Wt% 27 0.00 100.00 27 0.00 100.00 45 0.00 100.00 22 2.23 97.77 22 0.67 99.33 38 15.35 84.65 19 2.23 97.77 19 1.41 98.59 32 15.35 84.65 16 3.51 96.49 16 2.58 97.42 27 15.35 84.65 13.5 5.23 94.77 13.5 5.23 94.77 22 15.35 84.65 11.4 7.27 92.73 11.4 10.22 89.78 19 15.35 84.65 9.6 12.74 87.26 9.6 16.40 83.60 16 15.35 84.65 8.1 20.91 79.09 8.1 24.93 75.07 13.5 17.78 82.22 6.8 28.24 71.76 6.8 35.15 64.85 11.4 19.44 80.56 5.7 40.69 59.31 5.7 47.49 52.51 9.6 24.04 75.96 4.8 51.95 48.05 4.8 59.85 40.15 8.1 28.74 71.26 4.1 61.76 38.24 4.1 69.50 30.50 6.8 37.03 62.97 3.4 73.38 26.62 3.4 80.09 19.91 5.7 42.90 57.10 2.9 81.32 18.68 2.9 87.03 12.97 4.8 49.28 50.72 2.4 88.90 11.10 2.4 92.75 7.25 4.1 54.83 45.17 2 94.10 5.90 2 97.47 2.53 3.4 62.72 37.28 1.75 96.07 3.93 1.75 99.31 0.69 2.9 69.76 30.24 1.45 98.19 1.81 1.45 99.93 0.07 2.4 77.29 22.71 1.2 99.03 0.97 1.2 99.96 0.04 2 84.49 15.51 1 99.58 0.42 1 100.00 0.00 1.75 88.51 11.49 0.87 99.76 0.24 0.87 100.00 0.00 1.45 91.98 8.02 0.73 99.92 0.08 0.73 100.00 0.00 1.2 94.76 5.24 0.62 99.98 0.02 0.62 100.00 0.00 1 96.97 3.03 0.52 99.99 0.01 0.52 100.00 0.00 0.87 97.76 2.24 0 100.00 0.00 0.73 98.88 1.12 0.62 99.92 0.08 0.52 100.00 0.00

278

Table A4-2 cont.

Pires January May August µm CR Wt% CP Wt% µm CR Wt% CP Wt% µm CR Wt% CP Wt% 22 0.00 100.00 38 0.00 100.00 32 0.00 100.00 19 1.64 98.36 32 0.42 99.58 27 0.89 99.11 16 1.64 98.36 27 1.04 98.96 22 2.08 97.92 13.5 2.50 97.50 22 2.64 97.36 19 2.85 97.15 11.4 3.14 96.86 19 5.01 94.99 16 5.63 94.37 9.6 6.50 93.50 16 9.26 90.74 13.5 8.35 91.65 8.1 10.98 89.02 13.5 15.12 84.88 11.4 12.09 87.91 6.8 14.99 85.01 11.4 23.58 76.42 9.6 16.25 83.75 5.7 22.36 77.64 9.6 34.01 65.99 8.1 22.46 77.54 4.8 29.66 70.34 8.1 44.47 55.53 6.8 30.50 69.50 4.1 38.15 61.85 6.8 55.46 44.54 5.7 38.25 61.75 3.4 48.46 51.54 5.7 65.59 34.41 4.8 46.87 53.13 2.9 57.98 42.02 4.8 74.51 25.49 4.1 55.15 44.85 2.4 67.71 32.29 4.1 81.33 18.67 3.4 65.58 34.42 2 76.29 23.71 3.4 88.09 11.91 2.9 74.83 25.17 1.75 81.89 18.11 2.9 92.34 7.66 2.4 83.18 16.82 1.45 88.10 11.90 2.4 95.84 4.16 2 89.30 10.70 1.2 92.52 7.48 2 98.55 1.45 1.75 92.48 7.52 1 95.71 4.29 1.75 99.55 0.45 1.45 95.67 4.33 0.87 97.36 2.64 1.45 99.91 0.09 1.2 97.54 2.46 0.73 99.21 0.79 1.2 99.96 0.04 1 98.69 1.31 0.62 99.94 0.06 1 100.00 0.00 0.87 99.18 0.82 0.52 99.97 0.03 0.87 100.00 0.00 0.73 99.64 0.36 0 100.00 0.00 0.73 100.00 0.00 0.62 99.95 0.05 0.62 100.00 0.00 0.52 99.99 0.01 0.52 100.00 0.00 0 100.00 0.00

279

Table A4-2 cont.

Plataforma January May August µm CR Wt% CP Wt% µm CR Wt% CP Wt% µm CR Wt% CP Wt% 32 0.00 100.00 63 0.00 100.00 45 0.00 100.00 27 1.62 98.38 53 3.17 96.83 38 1.38 98.62 22 2.66 97.34 45 5.35 94.65 32 1.85 98.15 19 3.47 96.53 38 5.35 94.65 27 5.46 94.54 16 5.77 94.23 32 8.57 91.43 22 10.86 89.14 13.5 7.15 92.85 27 9.95 90.05 19 13.85 86.15 11.4 9.66 90.34 22 15.24 84.76 16 18.42 81.58 9.6 14.83 85.17 19 18.15 81.85 13.5 24.48 75.52 8.1 19.37 80.63 16 23.20 76.80 11.4 31.14 68.86 6.8 25.75 74.25 13.5 30.73 69.27 9.6 38.23 61.77 5.7 34.00 66.00 11.4 38.54 61.46 8.1 45.66 54.34 4.8 44.05 55.95 9.6 45.50 54.50 6.8 52.64 47.36 4.1 53.85 46.15 8.1 55.00 45.00 5.7 60.03 39.97 3.4 65.72 34.28 6.8 63.36 36.64 4.8 66.03 33.97 2.9 74.52 25.48 5.7 72.18 27.82 4.1 71.55 28.45 2.4 82.20 17.80 4.8 78.78 21.22 3.4 77.46 22.54 2 87.97 12.03 4.1 84.38 15.62 2.9 82.13 17.87 1.75 91.56 8.44 3.4 89.88 10.12 2.4 86.96 13.04 1.45 94.80 5.20 2.9 93.52 6.48 2 91.08 8.92 1.2 97.07 2.93 2.4 96.62 3.38 1.75 94.10 5.90 1 98.46 1.54 2 98.81 1.19 1.45 97.12 2.88 0.87 99.06 0.94 1.75 99.55 0.45 1.2 98.49 1.51 0.73 99.68 0.32 1.45 99.96 0.04 1 99.22 0.78 0.62 99.93 0.07 1.2 99.98 0.02 0.87 99.46 0.54 0.52 99.96 0.04 1 100.00 0.00 0.73 99.76 0.24 0 100.00 0.00 0.87 100.00 0.00 0.62 99.96 0.04 0.73 100.00 0.00 0.52 99.99 0.01 0.62 100.00 0.00 0 100.00 0.00

280

Table A4-2 cont.

Retiro Janaury May August µm CR Wt% CP Wt% µm CR Wt% CP Wt% µm CR Wt% CP Wt% 27 0.00 100.00 32 0.00 100.00 32 0.00 100.00 22 2.07 97.93 27 0.23 99.77 27 1.10 98.90 19 3.81 96.19 22 1.56 98.44 22 1.82 98.18 16 5.84 94.16 19 2.21 97.79 19 3.05 96.95 13.5 8.15 91.85 16 5.30 94.70 16 6.17 93.83 11.4 11.40 88.60 13.5 10.12 89.88 13.5 10.20 89.80 9.6 16.37 83.63 11.4 15.62 84.38 11.4 17.15 82.85 8.1 21.96 78.04 9.6 24.54 75.46 9.6 20.65 79.35 6.8 29.22 70.78 8.1 34.05 65.95 8.1 27.71 72.29 5.7 37.92 62.08 6.8 44.75 55.25 6.8 37.66 62.34 4.8 46.59 53.41 5.7 55.86 44.14 5.7 45.41 54.59 4.1 56.36 43.64 4.8 66.03 33.97 4.8 53.21 46.79 3.4 65.48 34.52 4.1 74.71 25.29 4.1 60.15 39.85 2.9 73.22 26.78 3.4 83.24 16.76 3.4 67.56 32.44 2.4 80.63 19.37 2.9 89.08 10.92 2.9 75.14 24.86 2 86.75 13.25 2.4 94.00 6.00 2.4 82.96 17.04 1.75 90.33 9.67 2 97.91 2.09 2 90.20 9.80 1.45 93.93 6.07 1.75 99.37 0.63 1.75 93.53 6.47 1.2 96.55 3.45 1.45 99.96 0.04 1.45 96.04 3.96 1 98.15 1.85 1.2 99.98 0.02 1.2 97.42 2.58 0.87 98.93 1.07 1 100.00 0.00 1 98.63 1.37 0.73 99.71 0.29 0.87 100.00 0.00 0.87 99.05 0.95 0.62 99.98 0.02 0.73 100.00 0.00 0.73 99.57 0.43 0.52 99.99 0.01 0.62 100.00 0.00 0.62 99.97 0.03 0 100.00 0.00 0.52 100.00 0.00 0.52 100.00 0.00 0 100.00 0.00

281

Table A4-3 Particle Size Distribution calcite. CR Wt%- cumulative retained weight percent, CP Wt%- cumulative passing weight percent.

Basilica January May August µm CR Wt% CP Wt% µm CR Wt% CP Wt% µm CR Wt% CP Wt% 27 0.00 100.00 27 0.00 100.00 19 0.00 100.00 22 3.40 96.60 22 1.31 98.69 16 4.09 95.91 19 3.40 96.60 19 3.43 96.57 13.5 7.91 92.09 16 4.30 95.70 16 5.51 94.49 11.4 11.14 88.86 13.5 6.33 93.67 13.5 11.51 88.49 9.6 17.20 82.80 11.4 10.20 89.80 11.4 18.54 81.46 8.1 27.01 72.99 9.6 15.09 84.91 9.6 27.64 72.36 6.8 35.63 64.37 8.1 22.07 77.93 8.1 37.22 62.78 5.7 42.49 57.51 6.8 28.96 71.04 6.8 47.02 52.98 4.8 51.18 48.82 5.7 38.29 61.71 5.7 58.33 41.67 4.1 57.25 42.75 4.8 47.47 52.53 4.8 68.15 31.85 3.4 66.36 33.64 4.1 56.90 43.10 4.1 76.09 23.91 2.9 73.15 26.85 3.4 68.11 31.89 3.4 85.26 14.74 2.4 80.24 19.76 2.9 77.14 22.86 2.9 89.86 10.14 2 86.95 13.05 2.4 84.35 15.65 2.4 94.79 5.21 1.75 92.06 7.94 2 89.45 10.55 2 97.98 2.02 1.45 96.59 3.41 1.75 92.52 7.48 1.75 99.26 0.74 1.2 98.32 1.68 1.45 95.58 4.42 1.45 99.96 0.04 1 99.05 0.95 1.2 97.42 2.58 1.2 99.99 0.01 0.87 99.36 0.64 1 98.63 1.37 1 100.00 0.00 0.73 99.69 0.31 0.87 99.16 0.84 0.87 100.00 0.00 0.62 99.96 0.04 0.73 99.74 0.26 0.52 99.98 0.02 0.62 99.95 0.05 0 100.00 0.00 0.52 99.97 0.03 0 100.00 0.00

282

Table A4-3 cont.

Casa de Pedra January May August µm CR Wt% CP Wt% µm CR Wt% CP Wt% µm CR Wt% CP Wt% 19 0.00 100.00 19 0.00 100.00 13.5 0.00 100.00 16 6.53 93.47 16 1.96 98.04 11.4 2.00 98.00 13.5 12.14 87.86 13.5 4.76 95.24 9.6 2.74 97.26 11.4 12.14 87.86 11.4 10.17 89.83 8.1 6.10 93.90 9.6 17.15 82.85 9.6 13.18 86.82 6.8 9.42 90.58 8.1 27.31 72.69 8.1 20.07 79.93 5.7 16.51 83.49 6.8 34.80 65.20 6.8 29.31 70.69 4.8 26.34 73.66 5.7 45.73 54.27 5.7 41.73 58.27 4.1 37.65 62.35 4.8 57.71 42.29 4.8 53.76 46.24 3.4 50.05 49.95 4.1 65.66 34.34 4.1 65.70 34.30 2.9 58.90 41.10 3.4 78.64 21.36 3.4 76.73 23.27 2.4 68.03 31.97 2.9 84.97 15.03 2.9 84.66 15.34 2 78.25 21.75 2.4 91.53 8.47 2.4 91.27 8.73 1.75 82.93 17.07 2 94.56 5.44 2 97.02 2.98 1.45 88.11 11.89 1.75 97.61 2.39 1.75 99.24 0.76 1.2 91.40 8.60 1.45 98.68 1.32 1.45 99.86 0.14 1 94.63 5.37 1.2 99.34 0.66 1.2 99.95 0.05 0.87 96.10 3.90 1 99.76 0.24 1 100.00 0.00 0.73 98.08 1.92 0.87 99.82 0.18 0.87 100.00 0.00 0.62 99.88 0.12 0.73 99.91 0.09 0.73 100.00 0.00 0.52 100.00 0.00 0.62 99.96 0.04 0.62 100.00 0.00 0.52 99.98 0.02 0.52 100.00 0.00 0 100.00 0.00

283

Table A4-3 cont.

Pires January May August µm CR Wt% CP Wt% µm CR Wt% CP Wt% µm CR Wt% CP Wt% 16 0.00 100.00 27 0.00 100.00 19 0.00 100.00 13.5 3.12 96.88 22 0.30 99.70 16 2.10 97.90 11.4 10.16 89.84 19 1.62 98.38 13.5 7.39 92.61 9.6 10.16 89.84 16 3.90 96.10 11.4 9.51 90.49 8.1 11.19 88.81 13.5 7.35 92.65 9.6 13.04 86.96 6.8 16.90 83.10 11.4 16.20 83.80 8.1 17.83 82.17 5.7 20.05 79.95 9.6 27.24 72.76 6.8 22.02 77.98 4.8 29.04 70.96 8.1 38.04 61.96 5.7 34.24 65.76 4.1 35.61 64.39 6.8 49.06 50.94 4.8 41.35 58.65 3.4 45.26 54.74 5.7 59.30 40.70 4.1 48.38 51.62 2.9 52.75 47.25 4.8 68.75 31.25 3.4 56.46 43.54 2.4 63.54 36.46 4.1 76.55 23.45 2.9 64.47 35.53 2 73.40 26.60 3.4 84.49 15.51 2.4 72.97 27.03 1.75 81.00 19.00 2.9 89.92 10.08 2 80.91 19.09 1.45 88.48 11.52 2.4 94.58 5.42 1.75 87.33 12.67 1.2 93.10 6.90 2 97.92 2.08 1.45 93.83 6.17 1 96.32 3.68 1.75 99.24 0.76 1.2 96.54 3.46 0.87 97.98 2.02 1.45 99.82 0.18 1 98.12 1.88 0.73 99.35 0.65 1.2 99.92 0.08 0.87 98.84 1.16 0.62 99.94 0.06 1 99.99 0.01 0.73 99.46 0.54 0.52 99.97 0.03 0.87 100.00 0.00 0.62 99.91 0.09 0 100.00 0.00 0.73 100.00 0.00 0.52 100.00 0.00

284

Table A4-3 cont.

Plataforma January May August µm CR Wt% CP Wt% µm CR Wt% CP Wt% µm CR Wt% CP Wt% 13.5 0.00 100.00 45 0.00 100.00 32 0.00 100.00 11.4 1.90 98.10 38 8.25 91.75 27 8.06 91.94 9.6 6.12 93.88 32 12.87 87.13 22 8.06 91.94 8.1 16.76 83.24 27 24.67 75.33 19 11.81 88.19 6.8 27.90 72.10 22 36.05 63.95 16 14.92 85.08 5.7 36.40 63.60 19 36.05 63.95 13.5 18.95 81.05 4.8 47.50 52.50 16 38.70 61.30 11.4 26.41 73.59 4.1 57.57 42.43 13.5 43.55 56.45 9.6 32.84 67.16 3.4 71.61 28.39 11.4 50.32 49.68 8.1 40.83 59.17 2.9 78.50 21.50 9.6 58.75 41.25 6.8 47.81 52.19 2.4 86.31 13.69 8.1 63.92 36.08 5.7 54.73 45.27 2 92.15 7.85 6.8 71.33 28.67 4.8 62.21 37.79 1.75 94.11 5.89 5.7 77.17 22.83 4.1 67.84 32.16 1.45 96.78 3.22 4.8 82.71 17.29 3.4 74.84 25.16 1.2 98.18 1.82 4.1 88.55 11.45 2.9 79.81 20.19 1 99.29 0.71 3.4 92.52 7.48 2.4 85.35 14.65 0.87 99.56 0.44 2.9 95.30 4.70 2 90.08 9.92 0.73 99.85 0.15 2.4 97.39 2.61 1.75 94.00 6.00 0.62 99.97 0.03 2 99.10 0.90 1.45 97.65 2.35 0.52 99.99 0.01 1.75 99.54 0.46 1.2 98.82 1.18 0 100.00 0.00 1.45 99.83 0.17 1 99.27 0.73 1.2 99.94 0.06 0.87 99.47 0.53 1 100.00 0.00 0.73 99.77 0.23 0.87 100.00 0.00 0.62 99.96 0.04 0.73 100.00 0.00 0.52 99.99 0.01 0.62 100.00 0.00 0 100.00 0.00

285

Table A4-3 cont.

Retiro January May August µm CR Wt% CP Wt% µm CR Wt% CP Wt% µm CR Wt% CP Wt% 22 0.00 100.00 19 0.00 100.00 32 0.00 100.00 19 1.78 98.22 16 2.70 97.30 27 8.53 91.47 16 2.53 97.47 13.5 5.12 94.88 22 14.95 85.05 13.5 2.98 97.02 11.4 10.87 89.13 19 14.95 85.05 11.4 4.72 95.28 9.6 18.81 81.19 16 21.41 78.59 9.6 10.16 89.84 8.1 27.45 72.55 13.5 26.59 73.41 8.1 13.12 86.88 6.8 36.87 63.13 11.4 28.26 71.74 6.8 17.73 82.27 5.7 51.28 48.72 9.6 35.55 64.45 5.7 25.28 74.72 4.8 62.85 37.15 8.1 39.96 60.04 4.8 35.53 64.47 4.1 72.69 27.31 6.8 49.57 50.43 4.1 46.17 53.83 3.4 82.79 17.21 5.7 54.90 45.10 3.4 58.28 41.72 2.9 88.65 11.35 4.8 62.09 37.91 2.9 66.94 33.06 2.4 93.97 6.03 4.1 68.05 31.95 2.4 76.75 23.25 2 98.02 1.98 3.4 74.73 25.27 2 84.90 15.10 1.75 99.19 0.81 2.9 79.61 20.39 1.75 89.61 10.39 1.45 99.81 0.19 2.4 85.77 14.23 1.45 94.32 5.68 1.2 99.97 0.03 2 92.06 7.94 1.2 97.16 2.84 1 100.00 0.00 1.75 94.99 5.01 1 98.72 1.28 0.87 100.00 0.00 1.45 96.86 3.14 0.87 99.28 0.72 1.2 97.76 2.24 0.73 99.82 0.18 1 98.63 1.37 0.62 99.99 0.01 0.87 99.05 0.95 0.52 100.00 0.00 0.73 99.52 0.48 0 100.00 0.00 0.62 99.96 0.04 0.52 100.00 0.00

286

Table A4-4Particle Size Distribution carbonaceous matter. CR Wt%- cumulative retained weight percent, CP Wt%- cumulative passing weight percent.

Basilica January May August µm CR Wt% CP Wt% µm CR Wt% CP Wt% µm CR Wt% CP Wt% 19 0.00 100.00 32 0.00 100.00 19 0.00 100.00 16 3.49 96.51 27 2.46 97.54 16 0.51 99.49 13.5 5.22 94.78 22 9.83 90.17 13.5 0.51 99.49 11.4 7.04 92.96 19 14.88 85.12 11.4 1.32 98.68 9.6 10.74 89.26 16 19.13 80.87 9.6 2.94 97.06 8.1 14.83 85.17 13.5 23.54 76.46 8.1 3.93 96.07 6.8 20.19 79.81 11.4 28.13 71.87 6.8 7.57 92.43 5.7 25.76 74.24 9.6 33.70 66.30 5.7 11.44 88.56 4.8 34.94 65.06 8.1 39.96 60.04 4.8 17.10 82.90 4.1 42.94 57.06 6.8 48.18 51.82 4.1 22.82 77.18 3.4 54.46 45.54 5.7 56.75 43.25 3.4 30.32 69.68 2.9 63.10 36.90 4.8 64.97 35.03 2.9 37.46 62.54 2.4 72.22 27.78 4.1 72.83 27.17 2.4 45.96 54.04 2 79.07 20.93 3.4 80.38 19.62 2 55.06 44.94 1.75 83.55 16.45 2.9 86.31 13.69 1.75 61.69 38.31 1.45 88.67 11.33 2.4 91.88 8.12 1.45 71.11 28.89 1.2 92.56 7.44 2 96.20 3.80 1.2 80.04 19.96 1 95.73 4.27 1.75 98.33 1.67 1 89.29 10.71 0.87 97.42 2.58 1.45 99.19 0.81 0.87 92.95 7.05 0.73 99.17 0.83 1.2 99.37 0.63 0.73 95.52 4.48 0.62 99.78 0.22 1 99.50 0.50 0.62 96.99 3.01 0.52 99.82 0.18 0.87 99.61 0.39 0.52 97.67 2.33 0 100.00 0.00 0.73 99.79 0.21 0 100.00 0.00 0.62 99.79 0.21 0.52 100.00 0.00

287

Table A4-4 cont.

Casa de Pedra January May August µm CR Wt% CP Wt% µm CR Wt% CP Wt% µm CR Wt% CP Wt% 27 0.00 100.00 19 0.00 100.00 11.4 0.00 100.00 22 9.26 90.74 16 0.45 99.55 9.6 2.32 97.68 19 9.26 90.74 13.5 2.23 97.77 8.1 2.32 97.68 16 9.26 90.74 11.4 5.88 94.12 6.8 2.32 97.68 13.5 9.26 90.74 9.6 8.87 91.13 5.7 4.28 95.72 11.4 11.67 88.33 8.1 15.47 84.53 4.8 5.74 94.26 9.6 14.29 85.71 6.8 26.54 73.46 4.1 7.10 92.90 8.1 15.29 84.71 5.7 38.55 61.45 3.4 9.76 90.24 6.8 16.84 83.16 4.8 50.34 49.66 2.9 13.61 86.39 5.7 21.03 78.97 4.1 60.77 39.23 2.4 21.45 78.55 4.8 27.34 72.66 3.4 72.67 27.33 2 31.14 68.86 4.1 34.79 65.21 2.9 81.24 18.76 1.75 38.95 61.05 3.4 50.87 49.13 2.4 89.49 10.51 1.45 50.19 49.81 2.9 61.82 38.18 2 95.76 4.24 1.2 65.58 34.42 2.4 73.23 26.77 1.75 98.99 1.01 1 79.58 20.42 2 82.34 17.66 1.45 99.90 0.10 0.87 84.58 15.42 1.75 88.27 11.73 1.2 99.91 0.09 0.73 89.02 10.98 1.45 93.30 6.70 1 100.00 0.00 0.62 91.98 8.02 1.2 96.54 3.46 0.87 100.00 0.00 0.52 93.86 6.14 1 98.37 1.63 0.73 100.00 0.00 0 100.00 0.00 0.87 99.04 0.96 0.62 100.00 0.00 0.73 99.69 0.31 0.52 100.00 0.00 0.62 99.87 0.13 0.52 99.89 0.11 0 100.00 0.00

288

Table A4-4 cont.

Pires January May August µm CR Wt% CP Wt% µm CR Wt% CP Wt% µm CR Wt% CP Wt% 4.1 0.00 100.00 19 0.00 100.00 13.5 0.00 100.00 3.4 3.82 96.18 16 0.06 99.94 11.4 0.51 99.49 2.9 18.09 81.91 13.5 2.51 97.49 9.6 0.87 99.13 2.4 34.87 65.13 11.4 9.54 90.46 8.1 2.50 97.50 2 45.04 54.96 9.6 19.20 80.80 6.8 3.47 96.53 1.75 54.86 45.14 8.1 32.07 67.93 5.7 7.24 92.76 1.45 66.21 33.79 6.8 47.65 52.35 4.8 10.90 89.10 1.2 77.78 22.22 5.7 60.28 39.72 4.1 14.85 85.15 1 86.57 13.43 4.8 70.78 29.22 3.4 21.26 78.74 0.87 91.94 8.06 4.1 78.70 21.30 2.9 27.68 72.32 0.73 98.12 1.88 3.4 86.12 13.88 2.4 35.11 64.89 0.62 99.91 0.09 2.9 90.93 9.07 2 43.77 56.23 0.52 99.94 0.06 2.4 94.84 5.16 1.75 49.92 50.08 0 100.00 0.00 2 97.94 2.06 1.45 58.77 41.23 1.75 99.37 0.63 1.2 67.29 32.71 1.45 99.85 0.15 1 76.69 23.31 1.2 99.92 0.08 0.87 80.63 19.37 1 100.00 0.00 0.73 84.81 15.19 0.87 100.00 0.00 0.62 88.07 11.93 0.73 100.00 0.00 0.52 89.85 10.15 0.62 100.00 0.00 0 100.00 0.00 0.52 100.00 0.00

289

Table A4-4 cont.

Plataforma January May August µm CR Wt% CP Wt% µm CR Wt% CP Wt% µm CR Wt% CP Wt% 22 0.00 100.00 16 0.00 100.00 45 0.00 100.00 19 6.16 93.84 13.5 0.21 99.79 38 1.38 98.62 16 6.16 93.84 11.4 2.30 97.70 32 1.85 98.15 13.5 6.16 93.84 9.6 6.84 93.16 27 5.46 94.54 11.4 13.19 86.81 8.1 10.25 89.75 22 10.86 89.14 9.6 17.03 82.97 6.8 15.34 84.66 19 13.85 86.15 8.1 21.07 78.93 5.7 20.78 79.22 16 18.42 81.58 6.8 24.18 75.82 4.8 25.87 74.13 13.5 24.48 75.52 5.7 29.72 70.28 4.1 30.85 69.15 11.4 31.14 68.86 4.8 39.78 60.22 3.4 40.38 59.62 9.6 38.23 61.77 4.1 49.08 50.92 2.9 51.77 48.23 8.1 45.66 54.34 3.4 60.02 39.98 2.4 67.68 32.32 6.8 52.64 47.36 2.9 67.41 32.59 2 86.30 13.70 5.7 60.03 39.97 2.4 75.68 24.32 1.75 97.10 2.90 4.8 66.03 33.97 2 81.07 18.93 1.45 99.79 0.21 4.1 71.55 28.45 1.75 85.02 14.98 1.2 99.90 0.10 3.4 77.46 22.54 1.45 89.45 10.55 1 100.00 0.00 2.9 82.13 17.87 1.2 93.18 6.82 0.87 100.00 0.00 2.4 86.96 13.04 1 96.44 3.56 2 91.08 8.92 0.87 97.92 2.08 1.75 94.10 5.90 0.73 99.47 0.53 1.45 97.12 2.88 0.62 99.98 0.02 1.2 98.49 1.51 0.52 99.99 0.01 1 99.22 0.78 0 100.00 0.00 0.87 99.46 0.54 0.73 99.76 0.24 0.62 99.96 0.04 0.52 99.99 0.01 0 100.00 0.00

290

Table A4-4 cont.

Retiro January May August µm CR Wt% CP Wt% µm CR Wt% CP Wt% µm CR Wt% CP Wt% 22 0.00 100.00 38 0.00 100.00 19 0.00 100.00 19 2.61 97.39 32 0.95 99.05 16 1.23 98.77 16 8.37 91.63 27 0.95 99.05 13.5 5.56 94.44 13.5 9.77 90.23 22 2.53 97.47 11.4 7.49 92.51 11.4 12.33 87.67 19 3.73 96.27 9.6 8.51 91.49 9.6 16.18 83.82 16 7.56 92.44 8.1 10.61 89.39 8.1 22.36 77.64 13.5 12.83 87.17 6.8 14.17 85.83 6.8 27.79 72.21 11.4 17.86 82.14 5.7 18.44 81.56 5.7 35.17 64.83 9.6 24.08 75.92 4.8 22.28 77.72 4.8 41.17 58.83 8.1 31.29 68.71 4.1 26.90 73.10 4.1 47.52 52.48 6.8 40.26 59.74 3.4 32.40 67.60 3.4 55.63 44.37 5.7 50.64 49.36 2.9 39.14 60.86 2.9 64.22 35.78 4.8 59.80 40.20 2.4 48.40 51.60 2.4 71.99 28.01 4.1 67.93 32.07 2 59.64 40.36 2 78.38 21.62 3.4 77.23 22.77 1.75 67.09 32.91 1.75 82.37 17.63 2.9 84.29 15.71 1.45 78.39 21.61 1.45 87.43 12.57 2.4 90.92 9.08 1.2 87.13 12.87 1.2 91.84 8.16 2 96.50 3.50 1 91.54 8.46 1 95.49 4.51 1.75 98.99 1.01 0.87 93.30 6.70 0.87 97.08 2.92 1.45 99.92 0.08 0.73 95.16 4.84 0.73 99.18 0.82 1.2 99.96 0.04 0.62 96.62 3.38 0.62 99.92 0.08 1 100.00 0.00 0.52 97.38 2.62 0.52 99.96 0.04 0.87 100.00 0.00 0 100.00 0.00 0 100.00 0.00

291