UNIVERSIDAD DE CHILE FACULTAD DE CIENCIAS FÍSICAS Y MATEMÁTICAS DEPARTAMENTO DE GEOLOGÍA

GEOQUÍMICA DE SULFUROS EN EL SISTEMA GEOTERMAL CERRO PABELLÓN

TESIS PARA OPTAR AL GRADO DE MAGÍSTER EN CIENCIAS, MENCIÓN GEOLOGÍA

NELSON JOSÉ ROMÁN MORAGA

PROFESOR GUÍA: MARTIN REICH MORALES

MIEMBROS DE LA COMISIÓN: FERNANDO BARRA PANTOJA DIEGO MORATA CÉSPEDES

Este trabajo ha sido financiado por el Centro de Excelencia en Geotermia de los Andes (CEGA), proyecto FONDAP-CONICYT 15090013, y por el Núcleo Milenio Trazadores de Metales NC130065

SANTIAGO DE CHILE 2018

RESUMEN DE LA TESIS PARA OPTAR AL GRADO DE: Magíster en Ciencias, mención Geología. POR: Nelson Román Moraga FECHA: Agosto 2018 PROFESOR GUÍA: Martin Reich Morales

GEOQUÍMICA DE SULFUROS EN EL SISTEMA GEOTERMAL CERRO PABELLÓN

Los sulfuros son minerales comunes en sistemas geotermales activos y fósiles. Estudios recientes han mostrado que la composición y texturas de la pirita, el sulfuro más común en estos sistemas, puede entregar información clave para dilucidar la evolución de sistemas hidrotermales. A pesar de estos avances, las concentraciones y límites de incorporación de metales y metaloides en pirita de sistemas geotermales andinos no han sido acotados de manera adecuada, y la relación entre las características composicionales y micro-texturales de la pirita con procesos físicoquímicos específicos, como puede ser la ebullición, aún es un aspecto poco estudiado.

En función de lo anterior, en este estudio se examinan las características composicionales y micro-texturales de la pirita del Sistema Geotermal Cerro Pabellón (SGCP), campo geotermal activo ubicado en el Altiplano del norte de Chile. Se integran datos de análisis por microsonda electrónica (EMPA) y por espectrometría de masas por plasma inductivamente acoplado utilizando ablación láser (LA-ICP-MS) con observaciones texturales de pirita y minerales de ganga asociados, en muestras obtenidas de un testigo de sondaje (~500 m) que atraviesa las zonas de alteración argílica, sub-propilítica y propilítica del SGCP. Además, se realizó análisis de componentes principales para inspeccionar la base de datos composicional de pirita.

Las concentraciones de metales preciosos (Au y Ag), metales base (Cu, Co, Ni y Pb) y metaloides (As, Sb, Se, Bi y Tl) en la pirita del SGCP son significativas. Entre éstos, As, Cu y Pb son los más abundantes, con concentraciones que varían entre algunas ppm hasta niveles de wt% (hasta 4,4 wt% de As, 0,5 wt% de Cu y 0,2 wt% de Pb). La pirita formada durante ebullición vigorosa se caracteriza por tener concentraciones mayores de As, Cu, Pb, Ag y Au, y menores de Co y Ni en comparación con pirita formada en condiciones diferentes. Estos granos de pirita son anhedrales a euhedrales, localmente con textura porosa con abundantes inclusiones minerales, sugiriendo una formación por cristalización rápida. Por otro lado, la pirita formada en condiciones de ebullición suave, o de no-ebullición, se caracteriza por tener concentraciones relativamente mayores de Co y Ni, y menores de As, Cu, Pb, Ag y Au. Texturalmente, estas piritas forman agregados de cristales euhedrales y prístinos, con escasos poros e inclusiones minerales, sugiriendo una formación bajo condiciones fisicoquímicas más estables.

Estos resultados sugieren que la geoquímica de la pirita de sistemas geotermales posiblemente es controlada por la incorporación de elementos a partir de los fluidos hidrotermales una vez que se alcanzan condiciones de saturación. Finalmente, se muestra que la pirita, además de poder registrar la evolución composicional de los fluidos hidrotermales, también puede proveer información crítica sobre procesos fisicoquímicos como ebullición y separación de fases. Dado que la ebullición de fluidos acuosos es un fenómeno común en sistemas geotermales activos y fósiles (depósitos epitermales de Au-Ag), estos resultados resaltan el potencial uso de la pirita como una herramienta complementaria para explorar la evolución geológica de sistemas geotermales activos, y también para vectorizar hacia mineralización de Au- Ag relacionada a ebullición en depósitos epitermales de baja a intermedia sulfuración. i

A mis padres

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AGRADECIMIENTOS

El presente trabajo es el resultado de todo el apoyo que recibí de diversas personas e instituciones durante mi estadía en el programa de Magíster. En primer lugar, quisiera agradecer a mi Profesor Guía, Martin Reich, por encaminar la tesis, por todas sus enseñanzas sobre geología y, sobre todo, por darme la libertad, motivación y soporte necesario para poder ser creativo en mi investigación. Del mismo modo, agradezco a los profesores Fernando Barra y Diego Morata por mejorar este trabajo con sus contribuciones e ideas, y a Artur Deditius por sus clarificantes observaciones al manuscrito asociado a esta tesis.

En los aspectos más técnicos, quiero reconocer a Bernardita Alvear por realizar el muestreo inicial del sondaje PEXAP-1 que sirvió para el presente estudio, y por su ayuda con las texturas de los minerales de sílice; a Eduardo Morgado, por enseñarme su planificación de trabajo para la microsonda; a Víctor Valencia, Jorge Gómez, Kenneth Domanik y Jorge Crespo por su apoyo para los análisis de sulfuros mediante microsonda electrónica; y a Mathieu Leisen y Rurik Romero por poner todo de sí para sacar adelante los análisis de sulfuros mediante LA-ICP-MS. Asimismo, agradezco a ENEL Green Power, especialmente a Germain Rivera, por permitirme acceder a la zona de Cerro Pabellón, y por darme acceso a los testigos de sondaje del proyecto y a la información asociada.

Reconozco también en estas líneas el soporte inconmensurable recibido por parte de Karin Rojas, Bernardette Vasquez, Blanca Baccola y Maritza Acuña, quienes me apoyaron y guiaron a través del complicado mundo de los clásicos trámites administrativos.

Parte relevante de las ideas que están reflejadas en esta tesis nacieron en el marco de las reuniones del grupo de alumnos de Martin, en las presentaciones del Núcleo, en las reuniones del Grupo de Alteraciones del CEGA, o en la conversa “científica” de la Sala Milenio. A todos los integrantes de estos grupos, les doy mis más sinceros agradecimientos. Gracias por compartir conmigo lo que saben de geología.

Finalmente, agradezco el apoyo financiero del Centro de Excelencia en Geotermia de los Andes, CEGA, proyecto FONDAP-CONICYT #15090013; del Núcleo Milenio Trazadores de Metales NC130065; y de CONICYT por financiar mis estudios mediante una beca de Magíster Nacional (CONICYT-PFCHA/MagísterNacional/2017 – 22170335).

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TABLA DE CONTENIDO

CAPÍTULO 1: Introducción ...... 1 1.1. Estructura de la Tesis ...... 1 1.2. Motivación ...... 1 1.2.1. Sulfuros en sistemas geotermales ...... 1 1.2.2. Importancia del estudio de la pirita en sistemas geotermales ...... 5 1.2.3. Sistema Geotermal Cerro Pabellón ...... 6 1.3. Objetivos ...... 6 1.3.1. Objetivo general ...... 6 1.3.2. Objetivos específicos ...... 6 1.4. Hipótesis de trabajo...... 7 1.5. Publicaciones y resúmenes resultantes de este trabajo ...... 7 1.5.1. Publicaciones ...... 7 1.5.2. Resúmenes en congresos ...... 7 1.5.3. Resúmenes de proyectos paralelos en congresos ...... 7 CAPÍTULO 2: Geochemical and micro-textural fingerprints of boiling in pyrite ...... 8 2.1. ABSTRACT ...... 8 2.2. INTRODUCTION ...... 9 2.3. GEOLOGICAL BACKGROUND ...... 11 2.4. SAMPLES AND METHODS ...... 12 2.4.1. SEM, EMPA and LA-ICP-MS methods ...... 12 2.4.2. Statistical analysis ...... 13 2.5. RESULTS ...... 14 2.5.1. Sulfide mineral phases ...... 14 2.5.2. Pyrite groups ...... 15 2.5.3. Textural features of pyrite groups ...... 15 2.5.4. Chemical composition of pyrite ...... 16 2.6. DISCUSSION ...... 18 2.6.1. Incorporation of metals and metalloids in pyrite ...... 18 2.6.2. Interpretation of pyrite and gangue minerals textures ...... 20 2.6.3. Processes controlling pyrite geochemistry ...... 22 2.6.4. Pyrite as a vector to mineralization in low- to intermediate-sulfidation epithermal systems ...... 25 2.7. CONCLUDING REMARKS ...... 26

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2.8. ACKNOWLEDGEMENTS ...... 27 2.9. REFERENCES ...... 28 2.10. FIGURES ...... 37 CAPÍTULO 3: Discusión sobre implicancias para la geotermia ...... 51 3.1. Pirita como complemento para el estudio de la arquitectura actual y pasada de sistemas geotermales ...... 51 3.1.1. Características de la pirita y la evolución del SGCP ...... 53 CAPÍTULO 4: Conclusiones ...... 55 BIBLIOGRAFÍA ...... 56 ANEXOS ...... 60 ANEXO A: Anexo Metodológico ...... 60 A.1. Análisis LA-ICP-MS ...... 60 A.1.1. Condiciones de análisis LA-ICP-MS ...... 60 A.1.2. Calibración de análisis LA-ICP-MS ...... 60 A.2. Análisis estadístico de datos composicionales ...... 62 A.2.1. Estadística descriptiva ...... 62 A.2.2. Análisis exploratorio de datos ...... 62 A.3. Referencias Anexo Metodológico ...... 66 ANEXO B: Gráficos resumen de análisis composicionales de otros sulfuros del Sistema Geotermal Cerro Pabellón ...... 69 B.1. Calcopirita ...... 69 B.2. Galena ...... 71 ANEXO C: Resultados de análisis EMPA en pirita del SGCP ...... 72 ANEXO D: Resultados de análisis EMPA en calcopirita del SGCP ...... 76 ANEXO E: Resultados de análisis EMPA en galena del SGCP ...... 78 ANEXO F: Resultados de análisis EMPA en acantita del SGCP ...... 79 ANEXO G: Resultados de análisis LA-ICP-MS en pirita del SGCP ...... 80 ANEXO H: Resultados de análisis LA-ICP-MS en calcopirita del SGCP ...... 85

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ÍNDICE DE FIGURAS

Figura 1: Distribución en profundidad de la alteración hidrotermal y asociaciones de sulfuros en el Sistema Geotermal Reykjanes, Islandia, y su relación con la temperatura actual del sistema (tomado de Libbey y Williams-Jones, 2016) ...... 2 Figura 2: Variación de concentraciones (máximas) de elementos traza en pirita del Sistema Geotermal Reykjanes en función de la profundidad (tomado de Libbey y Williams-Jones, 2016) 3 Figura 3: Zonación composicional en granos de pirita del Sistema Geotermal Tolhuaca, Chile (Tardani et al., 2017) ...... 4 Figura 4: Vínculo entre la composición de la pirita y la composición de los fluidos hidrotermales formadores de pirita (tomado de Tardani et al., 2017) ...... 5 Figure 5: Location and geological characteristics of the Cerro Pabellón Geothermal System (CPGS) ...... 37 Figure 6: Polarized reflected light and backscattered electron (BSE) images showing representative textural features of pyrite from the CPGS (Group I) ...... 38 Figure 7: Backscattered electron (BSE) and polarized reflected light images showing representative textural features of pyrite from the CPGS (Groups II and III) and late-stage base and precious metal sulfides ...... 39 Figure 8: Backscattered electron (BSE) and cathodoluminiscence (SEM-CL) images showing pyrite from CPGS in association with different veinlets ...... 40 Figure 9: Simplified paragenetic sequence of the CPGS for samples used in this study ...... 41 Figure 10: Concentration plot for minor and trace elements in pyrite from the CPGS ...... 41 Figure 11: Concentration boxplot for selected minor and trace elements in pyrite from Groups I, II and III. Only inclusion-free LA-ICP-MS spot analysis data were considered (n = 118) ...... 42 Figure 12: Representative micro-textures and chemical zonations of pyrite-I (Group I) from the propylitic alteration of the CPGS ...... 43 Figure 13: Representative microtextures and chemical zonations of pyrite-II (Group II) from the propylitic alteration of the CPGS ...... 44 Figure 14: Representative micro-textures and chemical zonations of pyrite-III (Group III) from the propylitic alteration of the CPGS ...... 45 Figure 15: Elemental concentration scatterplots in pyrite from the CPGS ...... 46 Figure 16: As-Fe-S composition of pyrite from the CPGS. Only EMPA data were considered. n = 264 ...... 47 Figure 17: LA-ICP-MS depth-concentration profile (time vs. intensity) of selected isotopes in pyrite from the CPGS ...... 47 Figure 18: Representative LA-ICP-MS depth-concentration profiles (time vs. intensity) of selected isotopes in pyrite from the CPGS ...... 48 Figure 19: Plot of Co and Ni concentrations in pyrite from the CPGS and other active geothermal systems ...... 49 Figure 20: Biplots for Varimax-rotated Principal Component Analysis (PCA) of CLR- transformed pyrite concentrations ...... 50 Figura 21: Modelo conceptual de un sistema geotermal volcánico asociado a magmatismo de arco. Tomado de Moeck (2014) y Henley y Ellis (1983) ...... 51 Figura 22: Modelo conceptual simplificado del SGCP (tomado de Urzúa et al., 2002, y Maza et al., 2018), donde se indica la ubicación del sondaje PEXAP-1 y su relación con la capa sello del sistema ...... 53

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Figura 23: Materiales de Referencia para calibración de análisis de sulfuros por LA-ICP-MS. A: PS-1 (MASS-1); B: STDGL2b2. Tomado de Danyushevsky et al. (2011)...... 61 Figura 24: Diagramas de dispersión Na vs. Mg, donde se indican las direcciones de los componentes principales (a través de las direcciones de máxima varianza) y las proyecciones de los puntos originales sobre las nuevas variables. Ejemplo tomado de Reimann et al. (2008)...... 64 Figura 25: Concentraciones de elementos menores y traza en calcopirita del SGCP, incluyendo datos composicionales de EMPA y LA-ICP-MS ...... 69 Figura 26: Gráficos de dispersión de concentraciones químicas en calcopirita del SGCP, considerando solo datos obtenidos por LA-ICP-MS ...... 70 Figura 27: Gráfico de dispersión Cu-Ag en calcopirita del SGCP, considerando solo datos de EMPA (n=91)...... 70 Figura 28: Concentraciones de elementos menores en galena del SGCP, medidas por EMPA (n = 26) ...... 71 Figura 29: Gráficos de dispersión de concentraciones químicas en galena del SGCP (datos obtenidos por EMPA) ...... 71

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CAPÍTULO 1: INTRODUCCIÓN 1.1. Estructura de la Tesis

El presente trabajo se centró en el estudio de las características composicionales y texturales de los sulfuros del Sistema Geotermal Cerro Pabellón, ubicado en el Altiplano del norte de Chile. Para lo anterior, se hizo especial énfasis en las características y asociaciones minerales de la pirita de este sistema.

En el Capítulo 2 se presenta el marco geológico, las metodologías, los resultados y las principales discusiones del estudio. Dicho capítulo, en inglés, consiste en el manuscrito “Geochemical and micro-textural fingerprints of boiling in pyrite”, enviado para revisión por pares a una revista indexada. En el Capítulo 3 se discuten, de forma más específica, las implicancias para la geotermia que tienen los resultados presentados en el Capítulo 2. Finalmente, las principales conclusiones del trabajo son presentadas en el Capítulo 4.

De forma adicional, se han incluido anexos que pueden ser consultados en caso de requerir conocer en mayor detalle alguno de los tópicos tratados en este estudio. El Anexo A consiste en un anexo metodológico que ahonda en detalles sobre la calibración de análisis composicionales y tratamiento estadístico de datos composicionales, en el Anexo B se incluyen gráficos composicionales de otros sulfuros del sistema, y en los Anexos C al H se incluyen todos los análisis composicionales realizados, incluyendo los de pirita y otros sulfuros.

1.2. Motivación

1.2.1. Sulfuros en sistemas geotermales

Los sulfuros son minerales comunes en sistemas geotermales activos y fósiles, como en Salton Sea en California (Skinner et al., 1967; McKibben y Elders, 1985; McKibben et al., 1988a,b; Hulen et al., 2004), Rotokawa, Ngawa y Broadlands-Ohaaki en Nueva Zelanda (Krupp y Seward, 1987; Cox y Browne, 1995; Simmons y Browne, 2000), Kirishima y Yanaizu- Nishiyama en Japón (Shoji et al., 1989, 1999), Baranskiy y Pauzhetka en Rusia (Rychagov et al., 2000, 2009), Los Azufres en México (González-Partida, 2001), Mataloko en Indonesia (Koseki y Nakashima, 2006a, b); Joaquina en Guatemala (Libbey et al., 2015), Reykjanes en Islandia (Libbey y Williams-Jones, 2016) y Tolhuaca en Chile (Tardani et al., 2017).

En estos sistemas, los sulfuros más abundantes son la pirita, calcopirita, pirrotina, galena y esfalerita. Adicionalmente, otros sulfuros ocurren en menor abundancia o acotados a ciertas zonas dentro de los sistemas, como marcasita, arsenopirita, bornita, isocubanita, digenita y covelina (ej.: Cox y Browne, 1995; González-Partida, 2001; Libbey y Williams-Jones, 2016; Tardani et al., 2017). La pirita es, por lejos, el sulfuro más común en los sistemas geotermales. En general, la presencia de pirita es de amplia distribución, pudiendo estar asociada con diversos tipos de alteración hidrotermal, formadas a su vez en un amplio rango de temperaturas, o con zonas dominadas por diferentes tipos de fluido como, por ejemplo, vapor, fluidos de zonas de upflow o aguas de zonas de recarga. La pirita puede incluso ocurrir cerca de la superficie en sistemas activos, donde puede ser abundante y estar asociada a alteración argílica (ej.: Rychagov et al., 2009). 1

La descripción de la ocurrencia y de las asociaciones de sulfuros dentro de sistemas geotermales ha sido, por si misma, una herramienta útil para inferir de forma directa propiedades fisicoquímicas de estos sistemas. Por ejemplo, en Reykjanes, la distribución de las asociaciones de sulfuros coincide, a modo general, con la geometría de las isotermas actuales y con las zonas de alteración hidrotermal definidas para el sistema (Fig. 1; Libbey y Williams-Jones, 2016). Del mismo modo, tanto en Reykjanes como en Los Azufres (González-Partida, 2001) se ha sugerido que la ocurrencia de marcasita está acotada a los niveles más someros, de menor pH (<5) y temperatura (<~250°C). Así, el estudio de las asociaciones de sulfuros tiene el potencial para delimitar zonas de interés en los sistemas geotermales.

Figura 1: Distribución en profundidad de la alteración hidrotermal y asociaciones de sulfuros en el Sistema Geotermal Reykjanes, Islandia, y su relación con la temperatura actual del sistema (tomado de Libbey y Williams- Jones, 2016). Ambas imágenes corresponden a un perfil oeste-este. a: alteración hidrotermal, donde act: actinolita, chl: clorita, ep: epidota, MLC: arcillas interestratificadas, smec: esmectita, zeo: ceolitas. b: asociaciones de sulfuros definidas para el sistema, donde ccp: calcopirita, icb: isocubanita, mrc: marcasita, po: pirrotina, py: pirita, sph: esfalerita.

1.2.1.1. Geoquímica en sulfuros de sistemas geotermales

Si bien la pirita es de ocurrencia generalizada en sistemas geotermales, solo unos pocos trabajos han reportado sus características composicionales (Shoji et al., 1989, 1999; Koseki y Nakashima, 2006a, b: Rychagov et al., 2009; Libbey y Williams-Jones, 2016; Tardani et al., 2017). En base a estos estudios se ha propuesto que la geoquímica de la pirita en sistemas geotermales (1) sería útil para explorar la estructura geológica e hidrogeológica de dichos sistemas (ej.: Rychagov et al., 2000; Koseki y Nakashima, 2006a,b; Libbey y Williams-Jones, 2016); (2) estaría controlada por la naturaleza y propiedades fisicoquímicas de los fluidos

2 mineralizadores (ej.: Tardani et al., 2017), o (3) incluso pudiera estar controlada por la composición química de la roca hospedante (Shoji et al., 1989).

Los trabajos más recientes sobre la geoquímica de sulfuros en sistemas geotermales son los de Libbey y Williams-Jones (2016), en el sistema geotermal Reykjanes; y de Tardani et al. (2017), en el sistema geotermal Tolhuaca. Ambas investigaciones abordan la temática en mayor detalle que trabajos precedentes, empleando métodos analíticos como LA-ICP-MS o SIMS. A continuación, se destacan algunos de los aportes más relevantes de estas dos investigaciones.

Geoquímica de sulfuros en el sistema geotermal Reykjanes (Libbey y Williams-Jones ,2016)

En la investigación sobre la geoquímica de sulfuros en Reykjanes, se muestra que la pirita de los sistemas geotermales puede incorporar una amplia gama de elementos menores y traza, con un gran rango de concentraciones (Fig. 2).

Figura 2: Variación de concentraciones (máximas) de elementos traza en pirita del Sistema Geotermal Reykjanes en función de la profundidad (tomado de Libbey y Williams-Jones, 2016). En los perfiles se indica aproximadamente el nivel de ebullición actual en el sistema. Además, se sugiere que la geoquímica de la pirita estaría controlada, al menos en parte, por el nivel de ebullición actual en el sistema (Fig. 2). Esto es inferido al notar que las mayores concentraciones de ciertos elementos (como Ag, As, Au y Pb, entre otros) ocurren en y sobre el nivel de ebullición aproximado del sistema. Este control estaría dado por la pérdida de solubilidad de metales y metaloides asociada al proceso de ebullición. También se sugiere que las concentraciones de elementos menores y traza en pirita de zonas de recarga, distales a la zona de upflow, son en general menores a las de la pirita de otros sectores del sistema.

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Cabe notar que las concentraciones mostradas en la Figura 2 corresponden a las concentraciones máximas de cada elemento por grano analizado, por lo que en estos datos se omite la variabilidad composicional intragrano de la pirita analizada.

Geoquímica de la pirita en el sistema geotermal Tolhuaca (Tardani et al., 2017)

Tardani et al. (2017) demostraron que la pirita del sistema geotermal Tolhuaca es rica en metales y metaloides, de modo similar que en Reykjanes. Los elementos que están en mayor concentración en la pirita de Tolhuaca son As y Cu, con concentraciones que abarcan desde niveles de sub-ppm hasta algunos wt.%. Sin embargo, y a diferencia de Reykjanes, en esta investigación se demostró que la pirita de Tolhuaca presenta zonaciones composicionales en As, Cu y Co, y que el estilo de las zonaciones es variable entre diferentes zonas del sistema (Fig. 3). Lo anterior, sumado a las zonaciones de pirita descritas por Koseki y Nakashima (2006a, b) para el sistema geotermal Mataloko, prueba que la pirita puede tener variaciones composicionales intragrano importantes, complejizando el análisis y aplicación directa de la geoquímica de los sulfuros en sistemas geotermales.

Figura 3: Zonación composicional en granos de pirita del Sistema Geotermal Tolhuaca, Chile (Tardani et al., 2017) Adicionalmente, en este trabajo se demostró el vínculo entre la composición de la pirita y la composición de los fluidos hidrotermales parentales (i.e., formadores de pirita), al notar que los centros de grano de la pirita de este sistema se caracterizan por altas razones Cu/As, las cuales se correlacionan bien con las razones Cu/As medidas en inclusiones fluidas de vetillas de calcita/cuarzo (Fig. 4). Las inclusiones fluidas se han interpretado, en este caso, como el paleofluido formador de los centros de granos de pirita. De manera similar, se observó que los bordes de grano de pirita, representativos del sistema actual, y de relativamente menor Cu/As, guardan estrecha relación con los fluidos actuales del sistema en términos composicionales. 4

Figura 4: Vínculo entre la composición de la pirita y la composición de los fluidos hidrotermales formadores de pirita (tomado de Tardani et al., 2017). a y b: mapas composicionales WDS de Cu y As, respectivamente, donde se denota una zona central (P1), y una zona de borde (P2). c: relación entre la razón Cu/As de la pirita y el fluido hidrotermal parental.

1.2.2. Importancia del estudio de la pirita en sistemas geotermales

A pesar de los avances recientes en el estudio de los sulfuros en sistemas geotermales y sus características composicionales, aún quedan aspectos poco conocidos o por investigar. Esto es de especial relevancia para la pirita, como es fundamentado a continuación.

En las últimas décadas, varios estudios han demostrado que la composición y las texturas de la pirita pueden entregar información valiosa para dilucidar la evolución de los sistemas hidrotermales (Wells y Mullens, 1973; Fleet et al., 1989; Cook y Chryssoulis, 1990; Reich et al., 2005; Large et al., 2009; Muntean et al., 2011; Deditius et al., 2014). Lo anterior tiene relación con que la pirita puede alojar concentraciones significativas de una gran cantidad de elementos químicos, entre los que están Au, Ag, Cu, Pb, Zn, Cd, Mn, Co, Ni, As, Sb, Se, Te, Hg y Bi (ej.: Reich et al., 2005, 2013, 2016; Deditius et al., 2009, 2011, 2014; Franchini et al., 2015; Libbey y Williams-Jones, 2016; Tardani et al., 2017). Dado que la composición de la pirita es fuertemente influenciada por las condiciones ambientales, la signatura geoquímica de la pirita podría reflejar la partición selectiva de elementos durante el crecimiento mineral, y en última instancia, la composición y naturaleza fisicoquímica de los fluidos parentales (ej.: Deditius et al., 2009, 2014, Reich et al., 2013; Gregory et al., 2014, 2015a; Large et al., 2014, 2015; Tardani et al., 2017).

Recientemente, y como fue comentado antes en relación a la pirita de Tolhuaca, las bien documentadas variaciones composicionales y texturales de la pirita han sido relacionadas a cambios en la composición de los fluidos, asociadas a su vez con cambios abruptos en las condiciones P-T-X (ej.: Peterson y Mavrogenes, 2014; Tanner et al., 2016; Sánchez-Alfaro et al., 2016b; Tardani et al., 2017). Sin embargo, los controles sobre la composición y las texturas de la pirita aún no son bien entendidos. Considerando, además, que la información sobre características texturales de la pirita en sistemas geotermales es limitada, y que estudios recientes han demostrado que los fluidos asociados a diversos sistemas geotermales en los Andes están

5 enriquecidos en metales y metaloides (ej.: Sánchez-Alfaro et al., 2016a), el estudio de la pirita en sistemas geotermales activos ofrece la oportunidad única de investigar la relación entre las características composicionales y texturales de la pirita con las de los fluidos hidrotermales actuales del sistema, y en última instancia, con los procesos fisicoquímicos que están detrás de las variaciones en esta composición. Por tanto, la pirita podría tener el potencial para registrar información sobre los procesos físicoquímicos más relevantes en los sistemas geotermales, como podrían ser la ebullición, la mezcla de fluidos o el enfriamiento de fluidos hidrotermales.

Finalmente, cabe notar que los datos composicionales en pirita de Tolhuaca son los únicos datos composicionales de pirita de sistemas geotermales andinos. Por lo anterior, los rangos de concentración y límites de incorporación de metales y metaloides en pirita de sistemas geotermales andinos no han sido constreñidos de manera adecuada, lo que es parte de la motivación del presente estudio.

1.2.3. Sistema Geotermal Cerro Pabellón

Para indagar en los aspectos antes mencionados, se estudiaron muestras provenientes del Sistema Geotermal Cerro Pabellón (SGCP), sistema geotermal activo ubicado 105 km al noreste de la ciudad de Calama, en el Altiplano del norte de Chile. Este sistema, de alta entalpía y de escasas manifestaciones termales en superficie (Urzúa et al., 2002; Maza et al., 2018) es de especial relevancia para el país, puesto que actualmente aloja a la Central Geotérmica Cerro Pabellón (ENEL Green Power-ENAP joint venture), con una capacidad instalada de 48 MW, que es la primera de su tipo en Chile. El detalle de las características del SGCP se puede encontrar en el Capítulo 2.

1.3. Objetivos

1.3.1. Objetivo general

El objetivo principal del presente trabajo es determinar las características y los posibles controles sobre la geoquímica de sulfuros en el SGCP.

1.3.2. Objetivos específicos

• Determinar la ocurrencia de sulfuros en el SGCP. • Caracterizar las microtexturas de estos sulfuros. • Caracterizar las concentraciones de elementos menores y traza en los sulfuros del sistema, incluyendo la detección de posibles zonaciones composicionales a escala de grano en estos minerales. • Examinar el posible vínculo entre características composicionales y texturales de los sulfuros • Evaluar el potencial de la geoquímica de sulfuros para monitorear procesos fisicoquímicos en sistemas geotermales activos y fósiles, incluyendo la posible vectorización hacia zonas o sectores de interés en sistemas hidrotermales.

6

1.4. Hipótesis de trabajo

En los sistemas geotermales, la geoquímica de los sulfuros, y en particular de la pirita, es reflejo de la composición de los fluidos hidrotermales parentales, y es dependiente de los procesos físicoquímicos más relevantes en estos sistemas, como puede ser la ebullición, la mezcla de fluidos y enfriamiento. Este tipo de control también está reflejado en las texturas de los sulfuros.

1.5. Publicaciones y resúmenes resultantes de este trabajo

1.5.1. Publicaciones

Román N., Reich M., Leisen M., Morata D., Barra F., Deditius A.P. Geochemical and micro- textural fingerprints of boiling in pyrite (under review). (Capítulo 2)

1.5.2. Resúmenes en congresos

Román N., Reich M., Leisen M., Morata D., Barra F., Deditius A.P. Geochemical and textural features of pyrite in the Cerro Pabellón Geothermal System as a tracer of boiling in epithermal Au-Ag deposits. SEG 2018, Keystone, Colorado, 22-25 septiembre, 2018

Román N., Reich M., Leisen M., Morata D., Barra F., Deditius A.P. Características composicionales y micro-texturales de la pirita como trazadores de ebullición en sistemas geotermales activos y fósiles. XV Congreso Geológico Chileno, Concepción, Chile, 18–23 noviembre, 2018

1.5.3. Resúmenes de proyectos paralelos en congresos

Romero R., Leisen M., Barra F., Palma G., Román N., Morata D., Reich M. Parámetros de operación para obtención de elementos traza con ablación láser: Aplicaciones y metodologías. XV Congreso Geológico Chileno, Concepción, Chile, 18–23 noviembre, 2018.

7

CAPÍTULO 2: GEOCHEMICAL AND MICRO-TEXTURAL FINGERPRINTS OF BOILING IN PYRITE

Nelson ROMÁN1*, Martin REICH1, Mathieu LEISEN1, Diego MORATA1, Fernando BARRA1 and Artur P. DEDITIUS2

1Department of Geology and Andean Geothermal Center of Excellence (CEGA), Facultad de Ciencias Físicas y Matemáticas, Universidad de Chile, Santiago, Plaza Ercilla 803, Chile

2School of Engineering and Information Technology, Murdoch University, Western Australia 6150, Australia

*E-mail: [email protected]

Keywords: pyrite, trace elements, boiling, Cerro Pabellón, geothermal system, epithermal deposit

2.1. ABSTRACT

The chemical composition, textures and mineral associations of pyrite provide key information that help elucidate the evolution of hydrothermal systems. However, linking the compositional and micro-textural features of pyrite with a specific physico-chemical process, e.g., boiling versus non-boiling, remains elusive and challenging.

In this study we examine pyrite geochemical and micro-textural features and relate these results to pyrite-forming processes at the active Cerro Pabellón Geothermal System (CPGS) in the Altiplano of the northern Chile. We integrate electron microprobe analysis (EMPA) and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) data with micro-textural observations of pyrite and associated gangue minerals recovered from a ~500 m long drill core that crosscuts the argillic, sub-propylitic and propylitic alteration zones of the CPGS. Additionally, we carried out a Principal Component Analysis (PCA) in order to inspect and understand the main data structure of the pyrite geochemical dataset.

The concentrations of precious metals (Au and Ag), metalloids (As, Sb, Se, Bi and Tl), and base and heavy metals (Cu, Co, Ni and Pb) in pyrite from the CPGS are significant. Among the elements analyzed, As, Cu and Pb are the most abundant with concentrations that vary from a few parts per million (ppm) to wt% levels (up to 4.4 wt% of As, 0.5 wt% of Cu and 0.2 wt% of Pb).

Based on contemporaneous gangue mineral associations and textures, the mechanisms of pyrite precipitation in the CPGS were inferred. Pyrite formed during vigorous boiling is characterized by relatively higher concentrations of As, Cu, Pb, Ag and Au and lower concentrations of Co and Ni compared to pyrite formed under different conditions. These anhedral to euhedral pyrite grains display zones with a porous texture and abundant mineral micro- to nano-inclusions (mainly galena and chalcopyrite) indicating a formation by rapid crystallization. In contrast, pyrite formed under gentle boiling (more gradual cooling and less abrupt physico-chemical variations than in vigorous boiling) to non-boiling conditions is characterized by a higher concentration of Co and Ni, and relatively lower concentrations of As, 8

Cu, Pb, Ag and Au. Texturally, these pyrites form aggregates of euhedral and pristine pyrite crystals with scarce pores and mineral inclusions suggesting formation under steadier physico- chemical conditions.

Our results show that pyrite can not only record the chemical evolution of hydrothermal fluids, but can also provide critical information related to physico-chemical process such as boiling and phase separation. Since boiling of aqueous fluids is a common phenomenon occurring in a variety of pyrite-forming environments, e.g., active continental and seafloor hydrothermal systems, and porphyry Cu-epithermal Au-Ag deposits, pyrite compositional and textural features are a valuable complement for discriminating and tracking boiling events in modern and fossil hydrothermal systems.

2.2. INTRODUCTION

In the last decades, several studies have shown that the composition and micro-textures of pyrite are valuable complements to other geochemical information used to elucidate the evolution of hydrothermal systems (Wells and Mullen, 1973; Fleet et al., 1989; Cook and Chryssoulis, 1990; Reich et al., 2005; Large et al., 2009; Muntean et al., 2011; Deditius et al., 2014). Pyrite is a ubiquitous and abundant sulfide in ore deposits, and several geochemical studies have highlighted its role as a major Au-bearing phase and scavenger of metals and metalloids. Most notably, pyrite has been used as a geochemical tracer in a wide variety of hydrothermal ore deposits including orogenic, sediment-hosted Carlin-type, epithermal Au deposits, volcanic- massive sulfide (VMS), porphyry Cu and iron-oxide apatite (IOA) deposits (Cook and Chryssoulis, 1990; Fleet et al., 1993; Huston et al., 1995; Simon et al., 1999; Vaughan and Kyin, 2004; Reich et al., 2005, 2006, 2013, 2016; Large et al., 2009, 2014; Cook et al., 2009a; Deditius et al., 2009a,b, 2011, 2014; Koglin et al., 2010; Franchini et al., 2015; Gregory et al., 2015a; Deditius and Reich, 2016; Tanner et al., 2016; Keith et al., 2018). These studies have provided not only a better understanding of metal speciation and partitioning during mineral precipitation, but also have illustrated how physico-chemical processes drive changes in trace element distributions during superimposed events, including hydrothermal alteration, metamorphism and/or associated deformation (Large et al., 2007; Cook et al., 2009a; Thomas et al., 2011; Reich et al., 2013; Deditius et al., 2014; Steadman et al., 2015; Meffre et al., 2016).

A plethora of studies have shown that pyrite can host appreciable concentrations of Au, Ag, Cu, Pb, Zn, Cd, Mn, Co, Ni, As, Sb, Se, Te, Hg, Tl and Bi. Additionally, it has been noted that metal and metalloids can occur as structurally-bounded elements or forming micro- to nano- scale mineral inclusions within pyrite (Reich et al., 2005; Deditius et al., 2011). Since pyrite composition is strongly influenced by environmental conditions, its geochemical signature reflects the selective partitioning of elements during pyrite growth and ultimately, the composition and physico-chemical nature of the ore-forming fluids and/or marine pore waters (e.g., Deditius et al., 2009a, 2014, Reich et al., 2013; Gregory et al., 2014, 2015a; Large et al., 2014, 2015; Tardani et al., 2017). Furthermore, the significant diversity of textural features in pyrite has been investigated in detail. A large amount of our current knowledge derives predominantly from textural interpretations in orogenic Au systems (Large et al., 2007, 2009; Cook et al., 2013), sediment-hosted Au deposits (Large et al., 2014, 2015), VMS (e.g., Wohlgemuth-Ueberwasser et al., 2015; Soltani Dehnavi et al., 2018), porphyry-Cu (e.g., Reich et al., 2013; Franchini et al., 2015) and epithermal Au-Ag deposits (e.g., Franchini et al., 2015; 9

Tanner et al., 2016; Kouhestani et al., 2017; Sykora et al., 2018). These studies have shown that pyrite textures can record physico-chemical conditions during precipitation, such as supersaturation or near-equilibrium crystallization, as well as post-formational events, i.e., deformation, dissolution-reprecipitation and recrystallization processes (Cook et al., 2009a).

Recently, the well documented variations in chemistry and texture of pyrite have been linked to changes in fluid composition related to abrupt changes in P-T-X conditions (e.g., Peterson and Mavrogenes, 2014; Tanner et al., 2016; Sánchez-Alfaro et al., 2016; Tardani et al., 2017). However, the controls over the pyrite composition and distribution of trace elements are not well understood. For example, the presence of finely spaced multiple growth zones in pyrite has been interpreted as the result of intermittent excursions of magmatic vapor, changes in internal overpressure and/or externally-forced disturbances such as earthquakes, which can dramatically affect the composition of hydrothermal fluids. Also, processes such as cooling, fluid mixing and boiling have been invoked to explain the compositional variability of pyrite. However, linking the chemical and textural features of pyrite with a single physico-chemical process remains unconstrained and challenging, in part, due the scarcity of pyrite data in shallow crustal circulation systems such as geothermal systems and epithermal Au-Ag deposits, where boiling is a common mechanism of sulfide and gold precipitation. In these systems, pyrite is widely distributed and can be associated with different types of hydrothermal alteration assemblages formed at various temperatures, under boiling and non-boiling conditions (Simmons et al., 2005; Libbey and Williams-Jones, 2016; Tardani et al., 2017).

Pyrite is by far the most common sulfide in active geothermal systems including Salton Sea in California (Skinner et al., 1967; McKibben and Elders, 1985; McKibben et al., 1988a,b; Hulen et al., 2004), Rotokawa, Ngawa and Broadlands-Ohaaki in New Zealand (Krupp and Seward, 1987, Cox and Browne, 1995, Simmons and Browne, 2000), Kirishima and Yanaizu- Nishiyama in Japan (Shoji et al., 1989, 1999), Baranskiy and Pauzhetka in Russia (Rychagov et al., 2000, 2009), Los Azufres in Mexico (González-Partida, 2001), Mataloko in Indonesia (Koseki and Nakashima, 2006a,b); Joaquina in Guatemala (Libbey et al., 2015), Reykjanes in Iceland (Libbey and Williams-Jones, 2016) and Tolhuaca in Chile (Tardani et al., 2017). Despite its ubiquitous occurrence, geochemical data of pyrite have been reported only for a few geothermal systems (Shoji et al., 1989, 1999; Koseki and Nakashima, 2006a,b: Rychagov et al., 2009; Libbey and Williams-Jones, 2016; Tardani et al., 2017). These studies have mostly focused on the use of pyrite geochemistry to explore the geological and hydrogeochemical evolution of each particular system, which are mediated to a large extent by the nature and physico-chemical properties of the mineralizing fluids (e.g., temperature, pH, physical state and chemical composition) and host rocks (e.g., permeability and whole-rock chemical composition). Hence, detailed information about textural features of pyrite from active continental geothermal systems is limited, and links to its geochemical signature have not been explored. This is of utmost importance because pyrite from young and active geothermal systems shows fewer growth zones and/or chemical oscillations associated with discrete boiling and fluid mixing events (Tardani et al., 2017), which provide crucial information to interpret the reported complex zoning of pyrite in ore deposits (e.g., Reich et al., 2013; Tanner et al., 2016). This is mostly due to the fact that pyrite in ore deposits records a time-integrated sequence of fluid flow episodes, hindering the accurate identification of major precipitation events.

Here we examine the relation between pyrite geochemistry and micro-textures in order to constrain the pyrite-forming processes at the active Cerro Pabellón Geothermal System (CPGS) in the Altiplano of the northern Chile. The CPGS hosts a high-enthalpy metal-rich geothermal 10 system that has been drilled to ~2 km depth, offering a unique opportunity to evaluate the impact of physico-chemical conditions on pyrite compositional and textural features, principally the impact of phase-change processes, e.g., boiling, and associated variations in parameters such as temperature, pH and fluid composition. We integrate micro-analytical data with micro-textural observations of pyrite and associated gangue minerals recovered from a ~500 m long drill core that crosscut the argillic, sub-propylitic and propylitic alteration zones of the CPGS. The major, minor and trace element contents of pyrite were determined using a combination of electron microprobe analysis (EMPA) and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). Additionally, we performed a Principal Component Analysis (PCA) to inspect and understand the main data structure of the pyrite geochemical dataset. This statistical analysis confirms that the geochemical features of pyrite are strongly dependent on the depositional conditions at the CPGS. Our data provide an explanation for the observed compositional differences between different pyrite types, and relate specific pyrite-bearing assemblages to vigorous boiling and gentle- to non-boiling mineralization events.

2.3. GEOLOGICAL BACKGROUND

The Cerro Pabellón Geothermal System (CPGS), formerly known as the Apacheta Geothermal System (Urzúa et al., 2002), is an active geothermal system located 105 km from the city of Calama and 55 km from the El Tatio Geothermal Field, in northern Chile (Fig. 5A). The high-enthalpy CPGS was discovered by Codelco in 1998 during drilling of a shallow water exploration well (PAE-1; Urzúa et al., 2002). Currently, the CPGS geothermal resource is being harnessed by the 48 MW Cerro Pabellón Geothermal Power Plant (ENEL Green Power-ENAP joint venture), the first geothermal power plant in Chile, which began operation in 2017.

The CPGS is located within the Central Volcanic Zone (CVZ) of Chile, and is associated with the Altiplano-Puna Volcanic Complex (APVC; de Silva, 1989). A magmatic, high- temperature heat source has been proposed for the CPGS, based on petrological, geophysical and fluid geochemistry evidence (Urzúa et al., 2002; Aguilera et al., 2006, 2008; Tassi et al., 2009, 2010; Piscaglia, 2012). The geology of the area is dominated by the Apacheta-Aguilucho Volcanic Complex (AAVC, Mercado et al., 2009; Piscaglia, 2012), dacitic domes (Chac Inca and Pabellón) and rhyolitic, dacitic and andesitic lava flows (Fig. 5B). The AAVC is located west of Pampa Apacheta, a flat-floored valley where the Cerro Pabellón Power Plant is located. The Pabellón Dome was emplaced over the trace of the northern fault of the NW-SE-trending Pabelloncito Graben, which also hosts the main zone of the geothermal system. The only visible geothermal surface manifestations are two high-temperature fumaroles and bubbling pools, which occur near the summit of the Apacheta volcano (Fig. 5C).

The geology of the area was first described by Ramírez and Huete (1981), and the evolution of the Apacheta-Aguilucho Volcanic Complex was studied by Mercado et al. (2009) and Piscaglia (2012). The Plio-Pleistocene Apacheta volcano is characterized by andesitic to rhyolitic lava flows and pyroclastic deposits, whereas the Pleistocene Aguilucho volcano is mainly represented by dacitic lava flows. The last manifestation of volcanism in the area corresponds to the Chac-Inca and Pabellón dacitic domes (80-130 ka based on 40Ar/39Ar dating; Renzulli et al., 2006). The CPGS is hosted in an andesitic to dacitic volcanic sequence, which comprises hydrothermally altered lava flows, volcanic breccias and tuffs (GDN, 2011). Hydrothermal alteration in the system is profuse. Urzúa et al. (2002) reported that argillic 11 alteration associated with the Apacheta fumaroles is the only superficial alteration associated with the active geothermal system at depth. Based on XRD mineralogy, petrographic observations and SEM-EDX analyses of samples from two boreholes (PEXAP-1 and CP-1, Fig. 5B, C and D), Maza et al. (2017) recognized three main hydrothermal alteration assemblages in the system, from top to bottom: argillic, sub-propylitic and propylitic alterations (Fig. 5D). The argillic zone is characterized by a pervasive alteration represented by smectite, zeolites, hematite, calcite and silica. The sub-propylitic alteration zone is dominated by the corrensite + chlorite association, with albite, quartz, calcite, hematite, stilbite and laumontite. Finally, the propylitic alteration zone is characterized by illite + chlorite, with epidote, titanite, albite, adularia, quartz, calcite, pyrite and chalcopyrite.

A 400-m thick low-resistivity layer, detected by a magnetotelluric (MT) geophysical survey, has been interpreted as the cap-rock of the geothermal system (Fig 5C; Urzúa et al., 2002). Maza et al. (2017) proposed that this impermeable seal layer comprises argillic- and subpropylitic-altered rocks, and which could explain the absence of well-developed hydrothermal alteration in rocks above this clay-cap, and the scarcity of geothermal surface expressions, allowing to define the CPGS as a blind geothermal field.

2.4. SAMPLES AND METHODS

Twenty representative samples from the argillic, sub-propylitic and propylitic alteration zones of the CPGS were selected at different depths from the PEXAP-1 drill core (561.4 m; Fig. 5D). Each sample was inspected and characterized using polarized light and scanning electron microscopy techniques. A subset of eight representative pyrite-bearing samples was selected for subsequent sulfide compositional analysis (samples BA20, BA21, BA27, BA30, BA31, BA33, BA34 and BA48, Fig. 5D).

2.4.1. SEM, EMPA and LA-ICP-MS methods

Scanning electron microscopy (SEM) observations were carried out at the Andean Geothermal Centre of Excellence (CEGA), Universidad de Chile, using a FEI Quanta 250 SEM equipped with secondary electron (SE), energy-dispersive X-ray spectrometry (EDS), backscattered electron (BSE) and cathodoluminescence (CL) detectors. The analytical parameters were: spot-size set to 1 - 3 μm, accelerating voltage of 15 keV, beam intensity of 80 µA, and a working distance of ~10 mm. For SEM-CL observations, the methodology proposed by Frelinger et al. (2015) was followed.

Electron microprobe analysis (EMPA) of pyrite grains was performed using a CAMECA SX100 microprobe equipped with five wavelength-dispersive spectrometers at the Lunar and Planetary Laboratory, University of Arizona. Operation conditions were: fully focused beam, 40 degrees take-off angle and beam energy of 15 keV. The beam current was 40 nA for spot analyses and 80 nA for WDS X-ray maps. No evidence of beam damage of pyrite grains was detected during analysis. Elements were acquired using the following analyzing crystals: LLIF for Fe Kα, Co Kα, Ni Kα, Cu Kα and Zn Kα; TAP for As Lα and Se Lα; PET for S Kα, Te Lα and Pb Mα; and LPET for Ag Lα, Sb Lα, Au Mα and Bi Mβ. The standards used included natural and synthetic metals, sulfides, arsenides, tellurides and selenides. Counting time (peak) was 20 s for Fe Kα, Co Kα, Ni Kα, Cu Kα, Zn Kα, Au Mα and Bi Mβ; 30 s for S Kα, Ag Lα, Sb Lα and 12

Te Lα; 40 s for Pb Mα; and 50 s for As Lα and Se Lα. The same (peak) counting time was used for total background reading. Mean detection limits ranged from 0.02 to 0.05 wt% for most analyzed elements. Matrix corrections were performed using the PAP method (Pouchou and Pichoir, 1991).

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) spot analyses were acquired on selected pyrite grains. LA-ICP-MS analyses were undertaken using a 193 nm ArF excimer laser (Photon Machines Analyte 193) coupled to a quadrupole ICP-MS (Thermo Fisher Scientific iCAP Q) at the Mass Spectrometry Laboratory of the Andean Geothermal Center of Excellence (CEGA), Universidad de Chile. Prior to each analysis session, the ICP-MS was tuned by ablating a NIST SRM 610 glass reference material, to ensure acceptable levels of plasma robustness (i.e., 238U+/232Th+ between 0.95 – 1.05), oxide production (ThO+/Th+ <0.5%) and double-charged production (22M+/44Ca++ <0.01%). Ablation was carried out using a laser pulse frequency of 4 Hz, an energy density of ~1.5 J/cm2, and a spot size of 30 µm in most cases. The laser spot size was reduced to 20 µm when analyzing small grains, or to avoid ablating visible mineral inclusions. Helium was used as carrier gas. Each spot was ablated for 30 s following 30 s of gas background collection. The following isotopes were monitored: 34S, 51V, 52Cr, 53Cr, 55Mn, 57Fe, 59Co, 60Ni, 63Cu, 65Cu, 66Zn, 69Ga, 72Ge, 73Ge, 75As, 77Se, 82Se, 95Mo, 97Mo, 107Ag, 109Ag, 111Cd, 115In, 118Sn, 120Sn, 121Sb, 123Sb, 125Te, 182W, 197Au, 202Hg, 205Tl, 206Pb, 207Pb, 208Pb and 209Bi, considering a total quadrupole sweep time of 0.55 s. The calibration procedure considered both external and internal standard calibration (Longerich et al., 1996). The MASS-1 pressed synthetic sulfide reference material (Wilson et al., 2002) was used as the primary standard, and total Fe concentrations obtained previously by EMPA were used as the internal standard. Additionally, the GSE-1G glass reference material (Jochum et al., 2005) was employed as secondary standard for quality control. External standard measurements were performed at the beginning and at the end of each analysis round of 20 spot analyses. Data integration and reduction was carried out using the IoliteTM (v. 2.5) data reduction software (Paton et al., 2011). Caution was taken in the interpretation of irregular signal profiles attributed to mineral or fluid inclusions, or unstable signals produced when ablating thin mineral grains or grain rims. However, and considering that the minimum particle size detectable during LA-ICP-MS profiling was ~500 nm, it is possible that in some cases nanometer-sized mineral inclusions affected the overall signal. Additionally, it is important to note that the MASS-1 reference material may contain some heterogeneities, most notably for Au (Wilson et al., 2002). Therefore, LA-ICP-MS depth profiles of the MASS-1 reference material were thoroughly inspected before calibration to avoid introducing Au heterogeneities, and MASS-1 readings were made in duplicates, each time. Therefore, it is expected that the impact of these Au heterogeneities in our data is negligible.

2.4.2. Statistical analysis

Principal Component Analysis (PCA) was used for a better understanding and interpretation of the pyrite compositional data, including the statistical relationships between the analyzed elements and their variance. Prior to PCA, a centered log-ratio (CLR) transformation was applied to the data (Aitchison, 1986). This procedure overcomes the effects of inherent “closure” of compositional data, i.e., fixed totals of 100 wt% or 106 ppm, and approximates the dataset to a normal distribution, which is required for PCA (see Reimann et al., 2008). After CLR transformation, data was standardized via calculation of Z-values. A Varimax rotation procedure (Kaiser, 1958) of the principal components was used to improve interpretability of the results.

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Rotated PCA solutions are shown via biplots (Gabriel, 1971) where the loadings of each principal component (PC), i.e., the relation between the PCs and the original variables (element concentrations) are represented by arrows. The scores of each PC, i.e., the relation between the PCs and each original data point (individual analysis), are represented by points. The loading of each PC is related to how much a PC explains a variable. High loadings (closer to 1 or -1) indicate that the PC is highly related to the variable. Arrows in biplots indicate, simultaneously, the loadings related to a certain variable on both of axis or PCs. On the other hand, scores result from the orthogonal projection of each data point onto the extracted PCs. Points in biplots show the scores related to a certain individual analysis on both PCs.

The number of principal components extracted for each PCA was determined as the minimum number of components that explains at least 80% of the total variance of the dataset. Whenever censored data was incorporated into a PCA procedure (i.e., compositional data below detection limit), it was explicitly indicated. In these cases, such data was replaced by half of the detection limit for that element. Nevertheless, only parameters with less than 10% of censored data were considered for PCA. Additionally, scatterplots of raw compositions are used to visualize some of the results. Scatterplots are intended to show unusual structure patterns and how ratios between variables behave in the dataset, and are not used here for assessing correlation between raw composition data. Therefore, when correlation coefficients are shown within scatterplots, they are presented as referential values only.

2.5. RESULTS

2.5.1. Sulfide mineral phases

The main sulfide minerals in the analyzed samples are pyrite, chalcopyrite, galena and acanthite (Figs. 6 and 7). Locally, minor chalcocite, covellite, bornite and Cu-bearing sulfosalts were identified. Sulfides are scarce in the upper section of the drill core, which corresponds to the clay-cap zone of the system (Fig. 5D). In this zone, only minor chalcocite and covellite were observed, exclusively within amygdales of the volcanic host rock. No pyrite or chalcopyrite were detected in samples from this zone. A sharp increase in the sulfide abundance was noticed at ~490 m depth, associated with a change in the hydrothermal alteration mineral assemblage from sub-propylitic to propylitic. Pyrite and chalcopyrite are abundant in this portion of the drill core, with galena and acanthite identified in some samples (Figs. 7C and D). Bornite and Cu-bearing sulfosalts occur only as minor phases associated with chalcopyrite, especially in the deepest portion of the drill core (>548 m depth), where pyrite is absent.

Pyrite, the dominant sulfide in the CPGS, is present as euhedral to anhedral disseminated grains, occurring within or adjacent to veinlets, and to a lesser extent in amygdales and vugs, and as a replacement mineral of primary magnetite (Fig. 7B). Chalcopyrite also occurs in veinlets and in amygdales, as well as disseminated in the host rock. Chalcopyrite is mainly associated with late (pyrite-free) calcite veinlets, and to a lesser extent, with late quartz + adularia + (pyrite) veinlets, where it precipitated within open spaces after pyrite formation.

A distinct feature of pyrite and chalcopyrite grains from the CPGS is the ubiquitous presence of micrometer-sized mineral inclusions. These inclusions are observable under polarized reflected light and SEM and consist mainly of galena (Fig. 6A, C, D, and Fig. 7A, B), chalcopyrite (Fig. 6C), and acanthite (Fig. 7A). Additionally, a few Cu-Sb-As-bearing inclusions were detected in some chalcopyrite grains. The presence and nature of inclusions was also 14 inferred by inspection and analysis of the time vs. intensity LA-ICP-MS depth profiles (see Discussion section).

2.5.2. Pyrite groups

Pyrite from the CPGS can be classified based on its association with different veinlet generations and gangue minerals (Figs. 8 and 9). Three main groups are recognized: Group I is characterized by pyrite that is mainly associated with colloform silica + Fe-oxide crustiform bands (Fig. 8A). The silica has Fe impurities detected by SEM-EDS analyses, and a red jasper- like appearance in hand sample. Group II is characterized by pyrite associated with crustiform bands of colloform silica + mosaic (jigsaw) quartz and zoned quartz + sub-rhombic adularia veinlets (Fig. 8B, C and D). In Group III, pyrite is exclusively associated with zoned quartz + sub-rhombic adularia veinlets (Fig. 8E and F). In some cases, quartz developed comb-like textures when crystallized in open spaces. There is no apparent change in veinlet abundance with depth in the analyzed core. These three pyrite groups occur simultaneously within the same section of the analyzed drill core.

Based on veinlet cross-cutting criteria, a relative sequence can be established for these pyrite groups (Fig. 9). The colloform silica + Fe-oxide banding that characterizes Group I predates Groups II and III, whereas the zoned quartz + adularia veinlets of Group II postdate the colloform silica + mosaic quartz events of the same group. The zoned quartz + sub-rhombic adularia veinlets of Group III are similar to the latest veinlet event of Group II. Thus, Group III and the late event of Group II appear to be synchronous. Therefore, from the earliest to the latest event, pyrite groups are paragenetically arranged as I, II and III, with a partial temporal overlap between Groups II and III. Despite of two different events can be distinguished in Group II, it is difficult to accurately associate the pyrite mineralization with exclusively one of these.

A late, post-Group III event of base- and precious metal sulfide mineralization was observed in the studied samples (Fig. 7C, D and Fig. 8E). This event, characterized by chalcopyrite, galena and acanthite, is closely associated with rhombic calcite precipitation in open spaces, and it is considered the latest mineralization event recognized in the propylitic alteration zone (Fig. 9). This event is best represented in sample BA-20, which marks the transition between the sub-propylitic and propylitic alteration zones (~490 m depth).

2.5.3. Textural features of pyrite groups

Pyrite from Groups I, II and III, i.e., pyrite-I,-II and -III, respectively, display the following distinct textural characteristics:

Pyrite-I occurs as elongated and relatively large (500 µm - 1 mm) anhedral to euhedral grains and aggregates, usually in close relation with adjacent colloform silica and Fe-oxide bands (Fig. 6 and Fig. 8A). The main feature of pyrite-I is its porous texture, represented by areas with clustered pores and abundant mineral inclusions, and areas of pristine pyrite, without visible inclusions or pores (Fig. 6A and C). Pores are commonly filled with Si-bearing phases. The porous textures of some pyrite grains from this group resemble sieve or corrosion-like textures. Irregular fractures are observed in some grains, and in some fractured areas, chalcopyrite and clustering of galena inclusions are noticed (Fig. 6D). It is common to observe pyrite aggregates with irregular rims at the contact with Fe-oxides or silica-rich colloform bands, and sharp,

15 straight pyrite rims on the opposite side (Fig. 6B and 8A), suggesting that pyrite growth started from the irregular edge and developed perpendicular to banding.

Pyrite-II grains are subhedral to euhedral (10 – 200 µm; Fig. 7A and B) with some showing zones with abundant pores and mineral inclusions, similar to those described in pyrite-I. These areas are located preferentially in the cores of pyrite grains, whereas the external zones of the same grains are generally pristine, with scarce pores and inclusions (Fig. 7A and B). Some pyrite grains from this group have irregular fractures, but not to the same degree as in pyrite-I.

Pyrite-III displays isolated to clusters of subhedral to euhedral crystals, characterized by morphologies dominated by cubic and pyritohedral shapes, with sizes between 20 and 500 µm (Fig. 7C, D and Fig. 8E, F). Pyrite grains from this group have scarce pores or no porosity at all, are less fractured that pyrite-I and II, and are usually surrounded by late chalcopyrite, galena and/or acanthite.

2.5.4. Chemical composition of pyrite

All EMPA and LA-ICP-MS analyses are reported in Appendices A and B, respectively, whereas statistical parameters for the dataset are shown in Figure 10. It is important to note that analyses were performed on clean pyrite areas with no visible mineral inclusions. However, and considering that discrete nano-inclusions and/or clusters of mineral nanoparticles are not fully resolvable by LA-ICP-MS during depth profiling, it is likely that some analyses may have been affected by the ablation of mineral inclusions within pyrite (i.e., irregular, “spiky” profiles). Therefore, and in order to evaluate this effect, the entire dataset is displayed in Figure 10 as white boxes, whereas inclusion-free LA-ICP-MS analyses are shown in grey, i.e., those analyses that did not show any visible evidence of mineral inclusions (e.g., flat profiles). Additionally, concentrations determined by EMPA are higher than those determined by LA-ICP-MS due to the higher detection limit of the EMP analyses. Moreover, EMPA data for Zn, Te and Au are possibly affected by mineral nano- to micro-inclusions, explaining the discrepancy between EMPA and LA-ICP-MS data for these elements.

Inspection of the entire LA-ICP-MS database reveals that pyrite from the CPGS is enriched in minor and trace elements, where Cu, Pb, As and Ag reach maximum concentrations of >1 wt%. However, concentrations of the aforementioned elements are highly variable, in particular for Pb and Ag, spanning five orders of magnitude from sub- ppm values to >1 wt%. Gold concentrations are also high, reaching up to 179 ppm with a median concentration of 1.7 ppm. It is likely that some minor and trace element concentrations measured in pyrite are influenced by the presence of mineral sub-micron inclusions. This seems to be more evident for Pb, Au and Ag, where maximum concentrations can be up to two orders of magnitude higher than in the inclusion-free data (Fig. 10).

Overall, the inclusion-free data are consistent with the total database (Fig. 10, gray boxes). Pyrite from the CPGS is characterized by high concentrations of As, Cu and Pb, with up to ~4.4, ~0.5 and ~0.2 wt%, respectively. These elements were detected in almost all analyzes. Arsenic shows the highest median concentration of all the analyzed elements, 0.10 wt%. Cobalt, Ni, Sb, Se and Ag were also detected in most analyses, showing concentrations spanning three to four orders of magnitude, and maximum values of 0.05, 0.12, 0.09, 0.11 and 0.10 wt%, respectively. Among the elements showing the lowest concentrations, Bi, Au and Tl were detected in more than a half of the analyzes, reaching maximum concentrations of 39, 14 and 62 16 ppm, respectively. Zinc, Hg and Te were detected in a few grains, with concentrations <1000 ppm for Zn, <100 ppm for Hg and <10 ppm for Te. Vanadium, Cr, Mn, Ge and W were detected in less than half of the analyzes. Among these elements, manganese shows the highest concentration, reaching a maximum of 242 ppm, whereas the remaining elements show concentrations of less than 30 ppm. Gallium, Sn, Mo, Cd and In have concentrations below 10 ppm, with the exception of Cd that displays a maximum of 36 ppm.

2.5.4.1. Minor and trace element concentrations in pyrite groups

In order to avoid the potential chemical bias introduced by mineral inclusions, only the inclusion-free data were used to differentiate pyrite Groups I, II and III (Fig. 11). In all groups, As is present in the highest concentration, however, major compositional differences arise between these groups, especially between pyrite-I and -III.

Pyrite-I displays the highest median concentrations of Cu, Pb, As, Au and Ag, and the lowest median for Ni and Co contents (yellow boxes in Fig. 11). In contrast, pyrite-III shows the highest median Ni concentration, a Co median concentration higher than in pyrite-I, and the lowest median of Cu, Pb, As, Sb, Bi, Au, Ag and Tl concentrations (white boxes in Fig. 11). Pyrite-II has the highest median for Sb, Bi and Tl, high Co concentrations similar to pyrite-III and intermediate median concentrations for the other analyzed elements (blue boxes in Fig. 11). Selenium concentrations are similar in all groups. It is important to note that the concentration range of the analyzed elements, i.e., maximum and minimum values, can be similar between pyrite groups. However, the concentration distribution can significantly vary, as evidenced by, e.g., Cu (median concentration of Cu is higher in pyrite-I than in pyrite-II and III, but the concentration range is similar in all three, Fig. 11).

2.5.4.2. Pyrite WDS X-ray maps

The WDS X-ray maps for selected elements in pyrite grains are shown in Figures 12, 13 and 14.

Pyrite-I grains show a distinct compositional zoning, where As-Cu-rich growth bands alternate with As-Cu-poor zones (Figs. 12B and C). The most external growth zone of these pyrite grains is depleted in these elements. The As-Cu rich zones are well-defined in pristine pyrite areas and are more diffuse in porous and inclusion-rich areas (e.g., Fig 12D and E). Additionally, As-poor zones with abundant chalcopyrite inclusions are observed (Fig. 12A, B and C), and in a single grain from this pyrite group, a thin Co-rich band was detected between an As- rich zone and the As-depleted outermost rim.

Pyrite-II grains have a different zoning pattern, consisting of well-defined As, Cu and Co zones (Fig. 13). All analyzed pyrite grains from this group are characterized by two or three compositional zones. From core to rim, these are: (a) Cu-(Co)-rich zones with relatively moderate contents of As; (b) As-rich, Co-poor zones, with relatively moderate contents of Cu; and (c) rims depleted in both As and Cu, similar to the outermost rims in pyrite-I grains (Fig. 12). Zone (a) may be absent (Fig. 13E), while zone (b) and depleted rims (c) are common in all mapped grains from this group. Zone (a) may show, in turn, zoning where As and Cu are geochemically decoupled (Fig. 13J and K). The grain shown in Figure 13E-H corresponds to a particular case where Cu zoning is not detected and As is enriched in the core. This grain corresponds to a pyrite-II subgroup which is associated with the highest concentrations of As, Sb and Hg in the 17 pyrite-II dataset, coupled with the highest Sb/Pb ratios as shown in the elemental scatter plots (Fig. 15F). Furthermore, a thin Co-enriched band between zones (b) and (c) was identified in some grains (e.g., Fig. 13H). The galena inclusions shown in Figure 13I are almost completely contained in compositional zone (a). Zones (b) and (c) are also characterized by sharp outlines.

In contrast, the WDS X-ray maps of pyrite-III grains (Fig. 14) do not display well-defined compositional zoning patterns such as the observed for As in pyrite-I and II grains. Arsenic is homogeneously low in pyrite-III, whereas the high Cu and Co zones are mainly related to later interstitial galena and acanthite, minerals which are relatively enriched in both metals (Fig. 14).

2.5.4.3. Elemental scatterplots

Elemental concentration scatterplots for Co-Ni, Co-Cu, Co-As, Au-As, Cu-As, Sb-Pb, Ag-Pb, Bi-Sb and Tl-Sb are shown in Figure 15, considering only inclusion-free data. Cobalt displays a positive correspondence with Ni (Fig. 15A), with almost all Co/Ni ratios between 0.1 and 10, and most commonly between 1 and 10. Co/Ni ratios for pyrite-III display a more scattered pattern than the other two groups, and correspond to the lowest Co/Ni ratios of the dataset. The Co/Ni ratios of pyrite-I are slightly higher than in the other groups. Cobalt shows a scattered pattern when plotted against Cu and As (Figs. 15B and C, respectively). Arsenic, on the other hand, shows a weakly positive and scattered trend with Au and Cu (Figs. 15D and E, respectively).

Positive trends were found for Sb-Pb (Fig. 15F), Ag-Pb (Fig. 15G), Bi-Sb (Fig. 15H) and Tl-Sb (Fig. 15I), with all of these elements showing similar behavior. The Sb vs. Pb scatter plot displays, for almost all samples, a very consistent Sb/Pb ratio that spans the entire concentration range of both elements, close to Sb/Pb = 0.1. However, a pyrite-II subgroup deviates and show a Sb/Pb >0.5. Pyrites from this subgroup are also relatively enriched in As, Tl and Hg. The higher Ag/Pb ratios, on the other hand, correspond, to a great extent, to pyrite-I. Pyrite Bi/Sb ratios are mainly between 1 and 0.01, and Tl/Sb ratios are mostly between 0.1 and 0.01, with no visible differences between veinlet associations.

2.6. DISCUSSION

2.6.1. Incorporation of metals and metalloids in pyrite

Analyzed pyrite grains from the CPGS can be classified as “arsenian” in terms of their arsenic content reaching up to ~4 wt% (Figs. 10 and 11). WDS compositional maps (Fig. 12B and E, Fig. 13B, F and J, and Fig. 14B and F) show that the distribution of As is relatively homogeneous in each pyrite zone, suggesting that As is structurally bound within pyrite. The As- Fe-S ternary diagram (Fig. 16A) and the As vs. S scatterplot (Fig. 16B) suggest that As-1 dominantly substitutes for S in pyrite. This is confirmed by the flat 75As spectrum in depth- profiles shown in Figures 17 and 18, which are in agreement with a solid solution mode of As incorporation. However, the As-Fe-S ternary diagram (Fig. 16A) suggests the (minor) occurrence of As0 nano-inclusions (Deditius et al., 2009a) in pyrite-I and II, a feature previously reported for pyrites from the Tolhuaca Geothermal System, Chile (Tardani et al., 2017). There is no clear evidence of the occurrence of As2+-pyrite or As3+-pyrite in the CPGS, nonetheless this cannot be ruled out as data clustering close to stoichiometric pyrite composition may hide these substitutional trends (Fig. 16A). In addition, the As-Fe-S ternary diagram also indicates that substitution of Fe2+ by Me2+, where Me represents metallic or similar elements, is a major 18 mechanism for incorporation of trace elements (i.e., Cu, Co, Ni, Pb and Ag) in pyrite from the CPGS (Figs. 10 and 11).

The copper content in pyrite from the CPGS (up to ~1 wt%) is related to two different mineralogical forms, which are observable in the WDS X-ray maps (Figs. 12, 13 and 14): (i) structurally bound Cu, and (ii) micrometer-sized Cu-bearing inclusions, mainly chalcopyrite. Structurally bound Cu is represented in WDS maps by the relatively uniform dark-blue color of pyrite grains, and by homogeneously-distributed, higher intensity Cu-bearing zones. The negative trend between Cu and Fe (EMPA data, Appendix A) indicates that substitution between Fe2+ and Cu2+ is the most likely mechanism for Cu incorporation into pyrite structure. Copper-bearing inclusions, on the other hand, are shown as discrete high-intensity zones in WDS maps (e.g., Fig. 12C and F, and Fig. 13K). The Cu-bearing inclusions shown in Figure 12A and C are chalcopyrite, which is the most common Cu-sulfide inclusion in pyrite (Reich et al., 2013). Late chalcopyrite precipitated into pyrite fractured areas (e.g., lower-right zone, Fig. 12C) can be differentiated from inclusions that are visible in the center-left zone of the same map. In addition, galena inclusions also bear appreciable Cu (and Co) contents, as suggested by WDS maps (Fig. 12D and F, Fig. 13I and K, and Fig. 14). Furthermore, the two mineralogical forms of Cu in pyrite can be inferred from LA-ICP-MS depth profiles, where structurally bound Cu is inferred from a flat profile (Fig. 18A), and Cu-bearing inclusions from spikes in the 63Cu signal (Fig. 18B). Copper-bearing inclusions are more common in pyrite-I in comparison with the other two groups of pyrite.

The WDS X-ray maps (Fig. 13D, H and L, and Fig. 14D and H) and the representative 59Co intensity vs. depth LA-ICP-MS profile (Fig. 18A) show that cobalt occurs as a structurally bound element within pyrite. The strong positive correspondence between Co and Ni suggests that this is also the case for Ni (Fig. 15A). Most of the EMPA data for Co and Ni are below detection limits and Fe was used as an internal standard for laser ablation measurements, hence a proper evaluation of the substitution mechanism of these two elements in the pyrite structure was unfeasible. Regardless, it is likely that Co substitutes extensively for Fe in pyrite because both have similar ionic radii and a structural affinity exists between pyrite and the CoS2 end-member (Vaughan and Craig, 1978; Tossell et al., 1981; Abraitis et al., 2004; Gregory et al., 2015a, b). As pointed out above, galena bears appreciable contents of Co (Fig. 14D and H), indicating that Co may also occur incorporated in discrete galena inclusions in pyrite, particularly in pyrite-I and II.

Cobalt/nickel ratios in pyrite from CPGS are between 0.1 and 10 for most analyzed spots, with the majority of the data showing Co/Ni between 1 and 10, which is characteristic of pyrite of hydrothermal origin (Bajwah et al., 1987; Reich et al., 2016, and references therein). Overall, there is a systematic decrease in Co/Ni ratios from pyrite-I to III, with pyrite-II displaying intermediate ratios. Compositional data of pyrite groups (Fig. 11) show that this difference may be due to an enrichment of Ni with respect to Co from pyrite-I to III. Cobalt and Ni concentrations in the CPGS are relatively lower than in other geothermal systems, such as Tolhuaca (Tardani et al., 2017), and Mataloko (Koseki and Nakashima, 2006a, b), but similar to Kirishima (Shoji et al., 1989) and Pauzhetka (Rychagov et al., 2009) (Fig. 19). The first two systems have been linked to mafic magmatic sources, whereas the volcanic host rocks of Kirishima and Pauzhetka have a relatively more felsic composition, being dominantly andesitic in Kirishima, and andesitic to dacitic in Pauzhetka. This suggests that the hydrothermal system associated with the CPGS is possibly linked to a relatively more felsic source, which is in agreement with the dominant andesitic to dacitic compositions of the volcanic products that characterize the host rock of the CPGS. 19

Lead is an abundant trace element in pyrite from the CPGS, i.e., up to ~0.2 wt% and ~9 wt% considering inclusion-free data vs. the entire dataset, respectively. Lead occurs dominantly as micrometer-sized galena inclusions in all three pyrite groups, as evidenced in BSE images (e.g., Figs. 6C and D, 7A and B, 13I and 17A) and in some LA-ICP-MS depth-profiles (Figs. 17B and 18C). In depth-profiles, galena inclusions feature coupled peaks of 208Pb and 209Bi, commonly associated with 107Ag. This observation is consistent with positive correspondences between Pb, Ag, Bi and Sb (Fig. 15F, G and H). However, lead can also occur as a structurally bound element or incorporated as nanometer-sized inclusions that are not resolved by LA-ICP- MS, as evidenced by a flat 208Pb profile (Fig. 18D). A high concentration of structurally bound Pb is associated with high concentrations of As, Sb, Tl and Hg in solid solution (Fig. 18D). The incorporation of Sb and other large anions might promote the incorporation of Pb into the pyrite structure in a similar way as As promotes the incorporation of Au (Reich et al., 2005) in pyrite, or the incorporation of Cu and Ag into sphalerite via coupled substitution associated with In3+ or Sb3+ (Cook et al., 2009b).

The median concentration of gold and silver in pyrite from the CPGS (1.7 ppm for Au and 86 ppm for Ag) is notoriously higher (up to one order of magnitude) than in pyrite from other geothermal systems, such as Tolhuaca (Tardani et al., 2017) and Reykjanes (Libbey and Williams-Jones, 2016). The incorporation of Au into pyrite is favored by the structural distortion or by superficial effects caused by the incorporation of cationic or anionic arsenic in pyrite (Simon et al., 1999; Palenik et al., 2004; Deditius et al., 2008, 2014). The solubility curve defined by Reich et al. (2005) for Au in arsenian pyrite illustrates the strong control of As on this element, and show that Au can occur as either a structurally bound element (Au+1) or forming Au0 nanoparticles. Furthermore, it has been shown that the higher concentrations of Au in pyrite are commonly related to the presence of Au-bearing inclusions (Reich et al., 2005; Deditius et al., 2014; Gregory et al., 2015a). On the other hand, silver can be incorporated into pyrite as solid solution via substitution of Ag+ for Fe2+ or constituting nano-inclusions of native silver, electrum, sulfides and sulfosalts within pyrite grains (Huston et al., 1995; Abraitis et al., 2004; Deditius et al., 2011).

At the CPGS, Au and Ag are incorporated into pyrite as both solid solution and mineral inclusions. Silver is associated with different types of inclusions, observable using BSE imaging and by the inspection of the 107Ag and 197Au signal intensities in LA-ICP-MS depth-profiles (Figs. 17 and 18). Among these are inclusions with Ag-S (Fig. 17A), Ag-Cu (Fig. 17A), Au-Ag- (Cu-Se) (Fig. 17B and 18C) and Ag-bearing galena (Fig. 17B). Ag-Au-(Cu-Se)-bearing inclusions probably correspond to acanthite, as supported by the WDS compositional maps of Figure 14, which show relatively higher concentrations of Cu in acanthite in relation to the adjacent pyrite. The incorporation of Ag as solid solution is suggested by the flat 107Ag intensity response shown in the LA-ICP-MS depth-profiles (Fig. 18A and D). Gold, as noted above, occurs as solid solution and also as Au-Ag-bearing inclusions in pyrite. Au-As analyses (inclusion-free LA-ICP-MS data only) plot under the Au solubility curve defined by Reich et al. (2005) (Fig. 15D), suggesting that Au in the analyzed spots occurs dominantly as a structurally bound element. This is also supported by the relatively flat 197Au spectrum in the depth-profile (Fig. 18A).

2.6.2. Interpretation of pyrite and gangue minerals textures

Studies in geothermal systems and epithermal Au-Ag deposits have shown that pyrite can display a large variety of textures, including brecciated, colloform, porous, fibrous and inclusion- 20 rich textures (e.g., Deditius et al., 2009a, b; Franchini et al., 2015; Tanner et al., 2016; Kouhestani et al., 2017). In the CPGS, pyrite grains show several of these textures and morphologies, including porous and inclusion-rich zones, and brecciated subhedral to euhedral pyrite grains (Figs. 6 and 7). Additionally, gangue minerals associated with pyrite, i.e., silica phases, adularia and calcite, can provide key information for the interpretation of the sulfide- forming conditions. In this section, the textural features are interpreted and physico-chemical conditions, including fluid boiling, cooling and/or mixing, are inferred for each pyrite group.

Pyrite I (vigorous boiling): These pyrites have the highest concentrations of As, Au, Ag, Cu and Pb of all analyzed pyrites at the CPGS, and are relatively depleted in Co and Ni (Fig. 11). The close association of elongated pyrite aggregates with adjacent colloform silica bands suggests that pyrite-I formation was synchronous with the development of silica and Fe-oxide banding. The presence of colloform silica, the dominant silica texture in this group, suggests rapid supersaturation of the hydrothermal fluid with respect to amorphous silica, compatible with multiple and vigorous boiling events (cf. Fournier, 1985; Dong et al., 1995; Moncada et al., 2012; Rusk, 2012). This is further supported by early, broken and small rhombic adularia crystals incorporated into late calcite veinlets in sample BA-33 (Pyrite-I), indicating that previous to carbonate precipitation, protracted boiling conditions were dominant during the formation of pyrite-I (cf. Reed and Spycher, 1985; Dong and Morrison, 1995). The clustered mineral inclusions and pores described in pyrite-I grains also point to boiling processes. These textural features are similar to those described at the Dongping Au deposit, China and the Chah Zard epithermal Au-Ag deposit, Iran (Cook et al., 2009a; Kouhestani et al., 2017). Cook et al. (2009a) suggested that areas of clustered pores and telluride inclusions in pyrite from Dongping were formed by a coupled dissolution-reprecipitation process triggered by a percolating fluid under fluctuating fO2 and fS2 conditions. A similar mechanism may be responsible for the porous, inclusion-rich zones in pyrite-I from the CPGS, since considerable variations in physico-chemical parameters (e.g., in fO2 and fS2, Williams-Jones et al., 2009) are expected during multiple vigorous-boiling events.

Pyrite-II (vigorous boiling to gentle/non-boiling): These pyrites have intermediate concentrations of As, Au, Ag, Cu and Pb in comparison with the other two groups of pyrite from the CPGS, and higher concentrations of Co and Ni compared with pyrite-I (Fig. 11). Pyrite-II textures shares some similarities with pyrite-I. The areas of clustered inclusions and pores found in the cores of some pyrite-II grains suggest that, as for pyrite-I, physico-chemical conditions during pyrite core formation were highly fluctuating. In contrast, the inclusion-free, clean pyrite rims are consistent with steadier physico-chemical conditions. Pyrite-II is associated with colloform and mosaic quartz veinlets, and late zonal quartz + sub-rhombic adularia. The colloform and mosaic (jigsaw) textures of quartz in this pyrite group are also linked to supersaturation with respect to amorphous silica, compatible with vigorous boiling of the parental hydrothermal fluid. In contrast, the presence of zonal quartz and sub-rhombic adularia is related to slower crystallization kinetics and slight supersaturation with respect to quartz and adularia. Considering that adularia is strongly associated with boiling (Browne, 1978; Dong and Morrison, 1995), it is likely that this late event of zonal quartz + sub-rhombic adularia was formed as a result of non-vigorous, gentle boiling conditions transitioning to non-boiling conditions. In summary, the formation of pyrite-II is compatible with a shift from vigorous boiling to gentle- and non-boiling conditions.

Pyrite-III (gentle boiling/non-boiling): These pyrites have the lowest concentrations of As, Au, Ag, Cu and Pb of all analyzed pyrites at the CPGS, and are relatively enriched in Co and 21

Ni, with cobalt concentrations similar to pyrite-II (Fig. 11). The formation of pyrite-III was related to gentle boiling transitioning to non-boiling conditions, as evidenced by the presence of zonal quartz + sub-rhombic adularia veinlets. Pyrite-III is characterized by euhedral to subhedral cubic and pyritohedron morphologies, which are consistent with direct precipitation from a hydrothermal fluid in open spaces under relatively steady physico-chemical conditions. This interpretation is also supported by the scarcity of areas with clustered pores and inclusions, and by the homogeneous size of pyrite aggregates, suggesting a slower growth. The scarcity of visible mineral inclusions may be related to precipitation of pyrite from a fluid undersaturated with respect to inclusion-forming metals, such as Pb, Ag and Au. This is consistent with the lower concentrations of Pb, Ag, Au and As in pyrite-III (Fig. 11). Pyrite-III was followed by a late event of chalcopyrite, galena, acanthite and rhombic calcite precipitation in open spaces and fractures. The formation of rhombic calcite is compatible with slow kinetics of crystallization and linked to non-boiling conditions (Simmons and Christenson, 1994; Moncada et al., 2012). This late stage mineralization might have been related to mixing of cold, descending CO2-rich waters with hotter, rising hydrothermal fluids, leading to subsequent base and precious metals precipitation. This is the proposed mechanism responsible for the formation of bonanza ores in carbonate-base metal-gold systems (e.g., Corbett and Leach, 1998), which shares several similarities with the late chalcopyrite-galena-acanthite-calcite mineralization in the CPGS. In summary, the close association of pyrite-III with the late base- and precious-metal sulfide precipitation stage suggests that these events represent the waning stages of boiling in the studied zone, before its complete cessation.

2.6.3. Processes controlling pyrite geochemistry

Several studies have shown that a wide variety of elements can be incorporated into pyrite from hydrothermal fluids. Structurally-bound incorporation of metals and metalloids can be enhanced by the presence of As in the growing pyrite surface, leading to efficient chemisorption and destabilization of metal complexes (Maddox et al., 1998; Rickard and Luther, 2007; Deditius et al., 2014; Reich et al., 2005, 2013, 2016). Furthermore, addition of metals by local supersaturation of metals, triggered by redox effects on pyrite surfaces (Mikhlin et al., 2011), is linked to the formation of nano- to micro-inclusions of sulfides and native metals (Reich et al., 2006, 2011; Deditius et al., 2011; Hough et al., 2011). This has led to several studies that show how the chemical composition of pyrite can be used to track changes in the evolving hydrothermal fluid (Deditius et al., 2009b, 2014; Reich et al., 2005, 2013, 2016; Tardani et al., 2017).

Different processes have been invoked to explain the variability or changes in the composition of pyrite-forming fluids. In the high-temperature porphyry environment, major compositional changes can be achieved during phase separation of a magmatic-hydrothermal supercritical fluid, owing to selective metal and metalloid partitioning between a low density, vapor-rich fluid and a high density hypersaline liquid (Kouzmanov and Pokrovski, 2012; Reich et al., 2013). In the shallow geothermal and epithermal environments (<1.5 km depth), the mixed influence of pyrite-forming fluids and magmatically-derived As-rich vapors have been proposed to explain the As-Cu decoupling detected in pyrite grains from certain systems such as in the Pueblo Viejo, República Dominicana and Yanacocha, Perú high-sulfidation Au-Ag epithermal systems (Deditius et al., 2009b) and in the Tolhuaca active geothermal system (Tardani et al., 2017). In the geothermal environment, processes such as cooling, fluid mixing and boiling have a strong impact on fluid chemistry. The influence of boiling on metal solubility has been investigated by several researchers (e.g., Spycher and Reed, 1989; Simmons and Browne, 2000; 22

Simmons et al., 2016), which have noted a major impact on the depletion of Au, Ag, Pb and Cu in the ascending geothermal fluids. Simmons et al. (2016) noted that not every element is affected in the same manner by boiling, reporting high concentrations of As, Sb and Tl (among others) in fluids that underwent boiling at depth (“boiled waters”). Furthermore, Libbey and Williams-Jones (2016) suggested that pyrite composition from the Reykjanes geothermal system is controlled, at least in part, by boiling processes, based in the observation that the maximum concentrations of pyrite had a clear relation with depth in the system, finding sharp increases in Au, Ag and Pb at depth of the current boiling level in the system.

During boiling in the geothermal and epithermal environment, bubbles of a low-density vapor are released from the aqueous fluids at depth. In contrast to other higher-temperature environments, the metal transport capacity of the vapor is hindered by its low hydration capacity and low density (Pokrovski et al., 2005, 2013; Heinrich, 2007). Because of this, the compositional differences between the different pyrite groups at the CPGS cannot be explained by selective vapor-phase fractionation. Nevertheless, there are elements such as Hg (and As in some cases), that could be easily volatilized and concentrated in the vapor phase (Spycher and Reed, 1989; Pokrovski et al., 2013). Furthermore, the influence of deep and high-temperature As- rich, Cu-poor vapors invading the geothermal reservoir cannot be discarded (Migdisov et al., 2014). However, this process does not seem likely to explain the chemical features of pyrite at CPGS, mainly because pyrite-I grains do not show evidence of As-Cu decoupling (Fig. 12B and C). Besides, compositional zoning of pyrite (Fig. 12 and Fig. 13) does not resemble the thin, oscillatory zoning found in pyrite from Pueblo Viejo and Yanacocha (Deditius et al., 2009b). Therefore, and considering the geochemical and textural data presented here, we argue that boiling and cooling processes can be invoked to explain the observed geochemical differences between the pyrite groups from the CPGS.

Both boiling and cooling processes may have a profound effect on metal and metalloid solubility in pyrite-forming fluids. In particular, sharp physico-chemical changes are triggered by boiling processes, including loss of H2S, H2, CO2 and other volatiles to the vapor phase, coupled with cooling and pH and fO2 increase (Simmons and Christenson, 1994; Dong and Morrison, 1995; Simmons and Browne, 2000; Williams-Jones et al., 2009). Such abrupt changes can lead to extensive saturation, thus, the high concentrations of As, Cu, Pb, Ag and Au in pyrite formed under boiling may be the result of the preferential incorporation of metals and metalloids from the pyrite-forming fluids once saturation conditions are met. On the other hand, the relative Co enrichment in pyrite formed under gentle boiling and non-boiling conditions could be related to a greater sensitivity of Co complexes to physico-chemical changes that are not necessarily associated with boiling. It has been shown that cooling may have a dramatic effect on destabilization of Co-chloride complexes in hydrothermal fluids. Specifically, a reduction of temperature from 300 to 200°C can lead to a decrease in Co solubility by up to two orders of magnitude (Migdisov et al., 2011). Finally, differences in the degree of destabilization of metal and metalloid complexes during boiling events could produce elemental fractionation and precipitation in different boiling horizons, depending on the nature of each complex. In particular, arsenic and other metalloids forming hydroxide complexes in solution (e.g., Pokrovski et al., 2013) may be transported further after boiling and destabilized later at shallow or distal levels of the system (e.g., Simmons et al., 2016). This could allow the formation of the As-Sb-Bi- Tl-rich, Cu-depleted pyrite-II subgroup.

We further explore the impact of boiling vs. non-boiling processes on pyrite composition by performing a principal component analysis (PCA) that provides a general overview of the 23 compositional variability in pyrite from the CPGS. This statistical approach has been used successfully to understand trace element concentrations in pyrite from sedimentary environments (e.g., Gregory et al., 2015a). In our analysis, six elements were considered: Co, Ni, As, Cu, Pb and Ag, as these elements have the highest variance and were detected in most spot analyses (Figs. 10 and 11).

We took advantage of the synthesis capability of biplots to show our PCA results (Fig. 20). Biplots can simultaneously display two selected Principal Components (PC, x and y axes of the plots), the analyzed elements (shown as arrows), the individual spot analyses (shown as points), and the relationship between these. This allows visualizing which elements are associated with the largest variance, the degree of correlation between the analyzed elements, and how the original individual analyses relate to analyzed elements in this multivariate space. The interpretation of biplots requires the use of arrow lengths and direction as well as the angles between them. Arrow length is related to how much of the total variance of the element is represented by the displayed PC. A long arrow (high loadings) indicates that a majority of the variance associated with the represented element is displayed in the biplot, whereas short arrows (low loadings) indicate that the shown PC contains almost no information about the corresponding element. Long arrows aligned with a single PC indicate that the variance of the represented element is almost entirely contained in that PC. The direction of each arrow is related to the direction in which the concentrations of the corresponding element increase, a feature that needs to be coupled with arrow length considerations, as explained above, and that is useful to be evaluated together with data points (scores). Finally, the angle between arrows is associated with the correlation between the analyzed elements. Small angles between arrows (as in near overlapping arrows) indicate a high positive correlation and well constrained ratios between elements. Two orthogonal long arrows suggest that the represented elements are not correlated, and two opposed long arrows represent a high negative correlation and highly variable ratios between these elements.

Two PCA procedures were carried out (Fig. 20). The first PCA was performed omitting below detection limit (BDL) data (Figs. 20A and B), whereas the second considered the BDL data by assigning half of the corresponding detection limit (Figs. 20C and D). In both cases, more than 80% of the variance can be explained with the extraction of three PC. The two PCAs yielded similar results, and the main difference is how Pb is related to other variables. Biplots show an evident clustering of data by pyrite groups, demonstrating their systematic compositional differences, as mentioned above. Pyrite-I data, linked to vigorous boiling, are clustered and associated with the Cu, Pb, Ag and As arrows. Pyrite-III data, on the other hand, are linked to gentle boiling or non-boiling conditions and cluster on the opposite side of the biplots, associated with Co-Ni maxima. Pyrite-II is transitional between pyrite-I and pyrite-III, supporting the idea that, compositionally, this group has intermediate characteristics.

Principal Component 1 (PC1), which corresponds to the horizontal axes in biplots (Fig. 20) and explains ~45% of the total variance of the six elements considered, is closely related to Co, Ni, Ag and Pb in both PCAs. Specifically, PC1 represents the variation from high Co-Ni, low Ag-(Pb) values to high Ag-(Pb), low Co-Ni values. The near overlap of the Co and Ni arrows (Fig. 20) indicate that Co and Ni are proportional in the entire dataset, a feature observed in the scatterplot shown in Figure 15A. The same is true for Ag and Pb when considering BDL data (Fig. 20D). Noting that, in general, pyrite-I data are clustered to the right in the biplots and pyrite- III data are concentrated to the left, we infer that the variation represented by PC1 is directly related to a change in pyrite depositional conditions, from vigorous boiling to gentle boiling or 24 non-boiling conditions. Considering this, and since PC1 is associated with the maximum variance of the dataset, these results indicate that high Ag values, in relation to Co and Ni, are key geochemical fingerprints of pyrite precipitated under vigorous boiling conditions. In contrast, high Co and Ni contents with respect to Ag correspond to pyrite formed under gentle boiling or non-boiling conditions.

PC2, which represents ~22% of total variance, and corresponds to the vertical axes in Figure 20A and C, is closely related to Cu in both PCA, and also to Pb when excluding BDL data. The Cu arrow is predominantly oriented towards the pyrite-I group, in agreement with the fact that higher Cu values are related to vigorous boiling associations. Considering the PCA that includes BDL data, the near orthogonality between the Cu arrow and the Ag and Pb arrows suggest that copper variance is almost uncorrelated to Ag and Pb variance. However, this is not the case for the PCA that excludes BDL data, where PC2 represents the variation from high Cu, low Pb values to high Pb, low Cu values, both end-members linked to vigorous boiling. We suggest then that Cu and Ag-(Pb) enrichment in pyrite are two compositional end-members, formed by similar processes, i.e., vigorous boiling. The processes leading to the development of these end-members are unclear, but differences in original fluid composition, as well as differences in how Cu-complexes and Ag-complexes are destabilized in a vigorous boiling scenario, might account for this observation.

Arsenic, on the other hand, varies almost independently of the main Co vs. Ag boiling trend (PC1), and it is closely related to PC3 (~20% of total variance), which corresponds to the vertical axes in Figure 20B and D. This metalloid, as shown previously, seems to be relatively enriched in pyrite formed under both boiling and non-boiling conditions.

2.6.4. Pyrite as a vector to mineralization in low- to intermediate-sulfidation epithermal systems

The precipitation of Au and Ag in low- to intermediate-sulfidation epithermal systems has long been attributed to boiling of metal-rich hydrothermal fluids (Seward, 1989; Spycher and Reed, 1989; Simmons et al., 2005; Williams-Jones et al., 2009; Pokrovski et al., 2013; Seward et al., 2014; Moncada et al., 2017). In these systems, Au-Ag mineralization concentrates preferentially in veins together with pyrite, adularia and quartz, associated with boiling levels. In this study, we have demonstrated that the systematic correlation between trace element chemistry and micro-texture in pyrite provides key information related to the physico-chemical evolution of the hydrothermal fluids. Since the CPGS can be considered as an active analogue to fossil epithermal Au-Ag deposits (Hedenquist and Lowenstern, 1994; Simmons et al., 2005), we explore the potential of using pyrite geochemistry as a tracer of boiling, and a complementary tool to other established methods, i.e., fluid inclusions studies and bulk rock geochemistry, to vector towards Au-Ag mineralization.

First, the Ag/Co ratio of pyrite is proposed here as a discrimination tool between boiling and non-boiling zones, as shown by PCA analyses (Fig. 20). Lower Ag/Co ratios characterize pyrite from gentle boiling to non-boiling zones, whereas higher Ag/Co ratios are expected in pyrite from vigorous boiling zones. It is important to note that, since Ag precipitation is dramatically triggered by boiling, probably there is no smooth transition in Ag/Co ratios in pyrite between boiling and non-boiling horizons. Hence, Ag/Co ratios in pyrite should be used with caution, and for vectoring purposes we suggest that Ag/Co ratios may be employed to delimit the lower zone of boiling horizons. The use of Ag/Co ratios in pyrite should be complemented with a 25 comprehensive characterization of pyrite micro-textures. For example, high Ag/Co ratios that are associated with pyrite textures indicating rapid precipitation, i.e., areas of clustered mineral inclusions, high porosity, and colloform overgrowths, are suggestive of boiling-dominated conditions during pyrite formation. In contrast, low Ag/Co ratios associated with more euhedral morphologies and a scarcity of inclusions and pores may reflect slower crystal growth under gentle-boiling to non-boiling conditions.

Secondly, the pyrite Sb/Pb (Fig. 15F), Bi/Pb or Tl/Pb ratios may be used to differentiate between boiling horizons and their marginal or shallower areas. Lead is not preferentially transported by uprising hydrothermal fluids after boiling in comparison to Sb, Bi and Tl, which can remain in solution (Simmons et al., 2016). High Sb/Pb (e.g., ≥0.5 in pyrite from the CPGS, Fig. 15F), Bi/Pb and Tl/Pb ratios are expected in pyrite formed from fluids that underwent boiling at deeper levels (i.e, “boiled waters”), while low to moderate ratios will mark vigorous boiling horizons. This discrimination could be useful for vectoring towards ore zones laterally and vertically, and for inferring the presence of deeper mineralized veins. Given the fact that not all boiling horizons are equally mineralized, ratios between Cu, Ag and Pb could be used for discrimination. These results are in agreement with Kouhestani et al. (2017), who showed the usefulness of Cu/Pb and Pb/Ag ratios in pyrite for vectoring to high-grade Au ore zones in low- to intermediate-sulfidation epithermal Au–Ag deposits.

It is important to note that the same horizon or level within the geothermal system or epithermal deposit can contain pyrite formed under both boiling and non-boiling conditions due to overlapping of different pyrite mineralization events. For example, pyrite formation environments may have undergone telescoping due to caldera collapse or uplift (Sillitoe, 1994). Therefore, vectoring tools as proposed above should be used with caution and detailed paragenetic and geochronological studies need to be performed to address temporality of the different pyrite-bearing assemblages. In addition, multiple mineralization events within a single system can form bonanza zones of different grades, depending on the initial concentration of metals in the mineralizing hydrothermal fluids, the duration of the event, the focalization of fluids during mineralization and the efficiency of boiling processes. Therefore, it is fundamental that pyrite geochemical vectoring aims also at discriminating between different mineralization events. Lastly, and considering that boiling is not the only process capable of leading to economic-grade mineralization in low- to intermediate epithermal systems (e.g., cooling and fluid mixing are also relevant processes), the use of pyrite as a geochemical vector should categorize which process is more prevalent in the studied system, and adapt the interpretation of the proposed elemental ratios.

2.7. CONCLUDING REMARKS

Pyrite from the Cerro Pabellón Geothermal System (CPGS) is characterized by significant concentrations of base metals (Co, Ni, Cu and Pb), precious metals (Au and Ag) and metalloids (As, Sb, Se, Bi, Tl), similar to pyrite from other active geothermal systems. These elements occur in both solid solution and as mineral inclusions within pyrite, with galena, chalcopyrite and acanthite being the most common mineral inclusions. Arsenic, Cu and Co commonly display compositional zoning in pyrite, but not detectable in every grain.

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The relative temporality of pyrite-bearing assemblages and inferred mechanisms of pyrite precipitation in the CPGS were determined based on contemporaneous gangue mineral associations and textures. Results indicate that physico-chemical conditions transitioned from an initial phase of vigorous boiling to a late event of gentle boiling and non-boiling. Pyrite formed during vigorous boiling is characterized by relatively higher concentrations of As, Cu, Pb, Ag and Au, coupled with lower concentrations of Co and Ni, and by textures resulting from rapid crystallization, such as irregular grain edges and areas of clustered pores and abundant mineral inclusions. Supersaturation conditions dominated during crystallization of these pyrites, given the abundance of galena, chalcopyrite, and other micro- to nano-sized mineral inclusions. In contrast, pyrite formed under gentle boiling to non-boiling conditions is characterized by higher concentrations of Co and Ni, and lower concentrations of As, Cu, Pb, Ag and Au. Textures associated with these pyrites, formed under slower crystallization kinetics and steady physico- chemical conditions during precipitation, include aggregates of euhedral and pristine homogeneously-sized crystals with scarce mineral inclusions.

The geochemistry of pyrite from the CPGS seems to be largely controlled by the incorporation of metals and metalloids from the pyrite-forming fluids once saturation conditions are met. Therefore, the high concentrations of As, Cu, Pb, Ag and Au in pyrite formed during boiling may be the result of the abrupt destabilization of metal and metalloid complexes due to abrupt physico-chemical changes during boiling.

Our study shows that pyrite can not only record the chemical evolution of hydrothermal fluids, as previously demonstrated by Reich et al. (2013) and Tardani et al. (2017), but also can provide critical data related to physico-chemical processes such as boiling and phase separation. Since boiling of aqueous fluids is a common phenomenon occurring in a variety of pyrite-bearing hydrothermal systems (active continental and seafloor hydrothermal systems, and porphyry Cu- Mo-(Au) and epithermal Au-Ag deposits, among others), pyrite compositional and textural features are a valuable complement for discriminating and tracking boiling events in these systems and elsewhere. Particularly, the notable relation between the chemical and micro-textural features of pyrite with its formation conditions highlights the potential of using this mineral as a vector to Au-Ag mineralization in low- to intermediate-sulfidation epithermal systems.

2.8. ACKNOWLEDGEMENTS

This study was funded by FONDAP project 15090013 “Centro de Excelencia en Geotermia de los Andes, CEGA”. Additional funding was provided through the MSI “Millennium Nucleus for Metal Tracing Along Subduction” (NC130065). We acknowledge Dr. Kenneth Domanik, from the Lunar and Planetary Laboratory at the University of Arizona in Tucson, and Dr. Victor Valencia for their help with EMP analyses. The LA-ICP-MS analytical work was supported by CONICYT-FONDEQUIP instrumentation grant EQM120098. N. Román thanks financial support provided by CONICYT-PFCHA/MagísterNacional/2017 – 22170335 through a M.Sc. scholarship. We thank ENEL Green Power for allowing access to sample Cerro Pabellón drill cores.

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2.10. FIGURES

Figure 5: Location and geological characteristics of the Cerro Pabellón Geothermal System (CPGS). (A) Location of the CPGS in relation to other geothermal areas of interest (as indicated by Aravena et al., 2016) and relevant ore deposits; (B) Simplified geological map of the Cerro Pabellón geothermal field, taken from Maza et al. (2017), showing the location of the PEXAP-1 drillhole collar (red circle) and the orientation of the cross section shown in C (red dashed line). (C) Simplified conceptual model for the CPGS, showing isotherms and magnetotelluric (MT) resistivity data, taken from Urzúa et al. (2002). (D) Simplified geological profile of the PEXAP-1 well, indicating hydrothermal alteration and zones of the geothermal system as interpreted by Maza et al. (2017). The location of the pyrite-bearing samples studied in the present work is also shown.

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Figure 6: Polarized reflected light (A) and backscattered electron (BSE) images (B-D) showing representative textural features of pyrite from the CPGS (Group I). Pyrite-I occurs as elongated grains associated with colloform silica and Fe-oxide bands (A, B). Porous and inclusion (galena and chalcopyrite)-rich zones are key textural features of pyrite-I (A-D). These porous zones can be elongated, following the facets of the host pyrite grains (A, B); can constitute the core of pyrite grains (C); or can be associated with fractured zones in some pyrite grains (D). Pristine pyrite areas occur in all of the grains. Late chalcopyrite can be seen in the rims of some pyrite grains (A, C, D) and also in the interstitial space between pyrite crystals (D). Cal: calcite; Ccp: chalcopyrite; Py: pyrite; Qz: quartz.

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Figure 7: Backscattered electron (BSE) (A, B, D) and polarized reflected light (C) images showing representative textural features of pyrite from the CPGS (Groups II and III) and late-stage base and precious metal sulfides. Pyrite- II grains are euhedral to subhedral and have porous, inclusion-rich cores and pristine rims (A, B; inclusions: galena and acanthite). Pyrite-III, in contrast, occurs as aggregates of euhedral to subhedral grains with relatively homogeneous sizes and it shows scarce porosity and mineral inclusions than pyrite-I and II (C, D). The mineral inclusions shown in (D) precipitated after pyrite deposition, in the interstities between pyrite grains. The late base and precious metal sulfide mineralization event consists of chalcopyrite followed by galena + acanthite. Usually, this assemblage is adjacent to previous pyrite grains (C, D). A minor mode of occurrence of pyrite from the CPGS is shown in (B), where it is found replacing ilmenite lamellae in Ti-magnetite. Ac: acanthite; Adl: adularia; Cal: calcite; Ccp: chalcopyrite; Gn: galena; Ilm: ilmenite; Mag: magnetite; Py: pyrite; Qz: quartz.

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Figure 8: Backscattered electron (BSE) and cathodoluminiscence (SEM-CL) images showing pyrite from CPGS in association with different veinlets; veintlet generations are arranged from the earliest (A) to the latest (E-F). (A) Pyrite from Group I (pyrite-I), associated with colloform silica + Fe-oxide crustiform bands; (B) Gangue minerals association for pyrite from Group II (pyrite-II), showing crustiform bands of colloform silica, mosaic quartz and later zoned quartz+sub-rhombic adularia; (D-E) (depicting the same area) Pyrite-II, associated with colloform silica and later zoned quartz; (E-F) (depicting the same area) Pyrite from Group III (pyrite-III), associated with sub- to euhedral, zoned quartz + sub-rhombic adularia. The brighter spots within colloform silica in (A) are due to the presence of Fe-oxides. Adl: adularia; Cal: calcite; Ccp: chalcopyrite; Chl: chlorite; Mag: magnetite; Py: pyrite; Qz: quartz. 40

Figure 9: Simplified paragenetic sequence of the CPGS for samples used in this study, highlighting the relative temporality of the groups of pyrite and their association with gangue minerals, and the late base- and precious metal sulfide mineralization event recorded in the samples.

Figure 10: Concentration plot for minor and trace elements in pyrite from the CPGS (samples BA20, BA21, BA27, BA30, BA31, BA33 and BA34). EMPA and LA-ICP-MS spot analysis data are included and shown as yellow- segmented lines and boxplots, respectively. Data are plotted in parts per million (ppm) on a vertical logarithmic scale. For boxplots, white color represents all available LA-ICP-MS data (n=264), while gray boxes represent inclusion-free data only (n=118). In each boxplot, minimum, median and maximum concentrations are marked, and the number of analyses above detection limit for each element is displayed inside of each box. The horizontal segmented line marks the mean detection limit (mdl) of EMP analyses for all elements.

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Figure 11: Concentration boxplot for selected minor and trace elements in pyrite from Groups I, II and III. Only inclusion-free LA-ICP-MS spot analysis data were considered (n = 118). Yellow boxes represent pyrite-I, which corresponds to pyrite associated with bands of colloform silica and Fe-oxides (n = 35); blue boxes represent pyrite-II, associated with crust-like bands of colloform silica, mosaic quartz and late zoned quartz + sub-rhombic adularia (n = 56); and white boxes represent pyrite-III, associated with zoned quartz + sub-rhombic adularia veinlets (n = 27). Data are plotted in parts per million (ppm) on a vertical logarithmic scale. In each boxplot, minimum, median and maximum concentrations are marked, and the number of analyses above detection limit for each element is shown as a number inside each box.

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Figure 12: Representative micro-textures and chemical zonations of pyrite-I (Group I) from the propylitic alteration of the CPGS. Sample: BA33. (A and D): backscattered electron (BSE) images. (B, C, E and F) Qualitative, wavelength dispersive spectrometry (WDS) X-ray maps of the same grains shown in the BSE images. (B and E) As (Lα) maps; (C and F) Cu (Kα) maps. The WDS maps show zonations of As (Lα) and Cu (Kα); white arrows in (B) and (C) highlight zones where As and Cu concentrations are coupled. Cu (Kα) distributions in (C) and (F) show discrete chalcopyrite inclusions, and additionally in (C), late chalcopyrite in fractures of pyrite grains. A color scale bar is shown for each WDS map. Ccp: chalcopyrite; Gn: galena; Py: pyrite.

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Figure 13: Representative microtextures and chemical zonations of pyrite-II (Group II) from the propylitic alteration of the CPGS. Samples: BA21 (first and second row) and BA31 (third row). (A, E, and I) backscattered electron (BSE) images showing pyrite grains. All other images are qualitative wavelength dispersive spectrometry (WDS) X- ray maps of areas shown in the BSE images. (B, F, and J) As (Lα) maps; (C, G, and K) Cu (Kα) maps; (D, H, and L) Co (Kα) maps. The WDS maps show zonation of As (Lα), Cu (Kα) and Co (Kα). Cu (Kα) distributions in (C) and (K) show discrete inclusions of chalcopyrite. Discrete galena and chalcopyrite inclusions are visible in the BSE images. A color scale bar for intensity is shown in each WDS map, and selected EMP analyses for As and Cu are included as reference (red crosses). Ccp: chalcopyrite; Gn: galena; Py: pyrite.

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Figure 14: Representative micro-textures and chemical zonations of pyrite-III (Group III) from the propylitic alteration of the CPGS. Sample: BA20. (A and E) backscattered electron (BSE) images showing pyrite grains. All other images are qualitative wavelength dispersive spectrometry (WDS) X-ray maps of areas shown in the BSE images. (B and F) As (Lα) maps; (C and G) Cu (Kα) maps; (D and H) Co (Kα) maps. The WDS maps show relatively homogeneous concentrations of As (Lα), Cu (Kα) and Co (Kα) in pyrite, and highlight the relatively higher concentration of Cu and Co in galena and achantite in relation to pyrite. Ac: acanthite; Ccp: chalcopyrite; Gn: galena; Py: pyrite.

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Figure 15: Elemental concentration scatterplots in pyrite from the CPGS (inclusion-free LA-ICP-MS data only, n = 118): (A) Co vs. Ni; (B) Co vs. Cu; (C) Co vs. As; (D) Au vs. As; (E) Cu vs. As; (F) Sb vs. Pb; (G) Ag vs. Pb; (H) Bi vs. Sb; (I) Tl vs. Sb. In (A), (F), (G), (H) and (I), the dashed lines represent different elements ratios for reference. The dashed curve in (D) represents solubility limit of Au as a function of As concentrations, as determined by Reich et al. (2005). All concentrations are in parts per million (ppm).

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Figure 16: As-Fe-S composition of pyrite from the CPGS. Only EMPA data were considered. n = 264. (A) Ternary diagram showing the As-Fe-S composition of pyrite. Five different trends show substitution of (i) As for S (As1-- pyrite); (ii) As0 nanoinclusions (Deditius et al., 2009a); (iii) As2+ for Fe (As2+-pyrite, Qian et al., 2013); (iv) As3+ for Fe (As3+-pyrite, Deditius et al., 2008); and divalent metals (Me2+) substituting isovalently for Fe. The composition for As2+-pyrite (after Qian et al., 2013; Deditius et al., 2014) was calculated based on the assumption of ideal occupancy of S (66.66 mol %). The dashed gray arrow marks a trend, parallel to the As0 nano-inclusions trend, displayed by a subgroup of the dataset. This deficiency in S and Fe concentration is interpreted as the presence of As0 nano-inclusions. (B) As vs. S scatterplot, showing the inverse correspondence between these elements in pyrite from the CPGS. Yellow circles: pyrite-I, blue symbols: pyrite-II, and white circles, pyrite-III. Correlation coefficients are also shown (rP = Pearson, rS = Spearman).

Figure 17: LA-ICP-MS depth-concentration profile (time vs. intensity) of selected isotopes in pyrite from the CPGS. (A) Backscattered electron (BSE) image of a pyrite grain in sample BA20, showing the location of spot analysis BA20-6-6 (30 µm). (B) LA-ICP-MS depth-concentration profile of spot analysis BA20-6-6, considering total beam, 63Cu, 75As, 107Ag, 123Sb, 197Au, 208Pb and 209Bi intensities. Coupled 208Pb and 209Bi, and 107Ag and 197Au peaks are detected (gray areas in B), reflecting the presence of individual galena and Au + Ag mineral particles (or a cluster). Isotopes 75As and 123Sb show a more homogeneous (solid solution) distribution, and without abrupt changes with depth. 47

Figure 18: Representative LA-ICP-MS depth-concentration profiles (time vs. intensity) of selected isotopes in pyrite from the CPGS. (A) (Pyrite-II) Flat signal for the investigated isotopes suggests incorporation as solid solution into pyrite or nanoparticles not resolved in the LA-ICP-MS depth-concentration profiles. (B) (Pyrite-I) Cu-bearing inclusions as seen in depth profiles, together with an Au-Ag-bearing inclusion. (C) (Pyrite-III) Ag-Se-bearing inclusions as seen in depth profiles. In this case, it occurs together with Ag and galena inclusions. (D) (Pyrite-II) flat signals for the isotopes represented, including Tl and Hg signals. In (A), the slight increase in 107Ag and 197Au intensities with time may be related to a higher concentration of Ag and Au in depth.

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Figure 19: Plot of Co and Ni concentrations in pyrite from the CPGS and other active geothermal systems. Data symbols for CPGS samples are the same as used in Figure 11.

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Figure 20: Biplots for Varimax-rotated Principal Component Analysis (PCA) of CLR-transformed pyrite concentrations. Only inclusion-free LA-ICP-MS data on Co, Ni, As, Cu, Ag and Pb were used. Bottom and left axes in every plot display the loadings of the Principal Components (PC), which are to be read considering the arrows (analyzed elements). The percentage shown on the axes represents the total variance explained by that component. Top and right axes show the scores of the PCs, which are associated to the points (individual analyses). (A) and (B) shows PCA performed without data below detection limit, and (C) and (D) shows a PCA where data below detection were replaced for a concentration equal to half of the detection limit. In both PCA, more than 80% of the total variance can be represented with the extraction of three PCs. (A and C) PC1 vs. PC2; (B and D) PC1 vs. PC3. In each biplot, the pyrite genetic interpretation is given (vigorous boiling vs. gentle boiling to non-boiling conditions).

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CAPÍTULO 3: DISCUSIÓN SOBRE IMPLICANCIAS PARA LA GEOTERMIA

3.1. Pirita como complemento para el estudio de la arquitectura actual y pasada de sistemas geotermales

La ebullición de fluidos hidrotermales es un fenómeno bien documentado en sistemas geotermales activos y fósiles (ej.: White et al., 1971; Arnórsson et al., 2007; Moncada et al., 2012, 2017). En estos sistemas pueden existir zonas bifásicas líquido-vapor, en donde la ebullición es un proceso dominante. La extensión de estas zonas es dependiente, entre otros, del tipo de sistema geotermal: en sistemas geotermales dominados por vapor (White et al., 1971) las zonas bifásicas líquido-vapor pueden ser de gran extensión, en las cuales los fluidos están habitualmente bajo una presión menor a la hidrostática (Browne, 1978); mientras que, en los sistemas geotermales dominados por líquido, las zonas de ebullición son más restringidas espacialmente. En otras zonas de los sistemas geotermales, la ebullición puede ser un proceso subordinado, como por ejemplo en sectores profundos (sujetas a mayor presión), en áreas de recarga de aguas meteóricas más frías (o agua marina) o en las zonas de outflow más distales a la zona de fluidos ascendentes. A modo de ejemplo, en la Figura 21 se incluye un modelo conceptual general para sistemas geotermales volcánicos, basado en el modelo de Henley y Ellis (1983), en donde es posible notar que la zona bifásica líquido-vapor se encuentra centrada principalmente en la zona de upflow del sistema, relativamente cercana a la fuente de calor magmática, mientras que las zonas de recarga y outflow, marginales a los sectores de fluidos ascendentes, son dominadas por líquido.

Figura 21: Modelo conceptual de un sistema geotermal volcánico asociado a magmatismo de arco. Tomado de Moeck (2014) y Henley y Ellis (1983). La zona bifásica de líquido-vapor se denota con círculos (“two-phase region”), en la parte más somera de la zona de upflow central. En otras zonas, como en las de recarga (“recharge”) o en las de outflow más distales a la fuente de calor, la ebullición puede ser un proceso subordinado.

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En base a lo mencionado antes, y debido a que las características composicionales y micro-texturales de la pirita pueden registrar procesos de ebullición en sistemas geotermales (Capítulo 2), es posible proponer el uso de la pirita como complemento directo para discriminar entre zonas dominadas por ebullición y no-ebullición en sistemas geotermales activos, en conjunto a otro tipo de estudios, como por ejemplo estudios geofísicos, de minerales de alteración, de inclusiones fluidas y de los fluidos actuales de cada sistema. De esta forma, la pirita puede tener una aplicación directa para inferir características importantes de la arquitectura de estos sistemas, y de este modo asistir a la generación de modelos más representativos de los sistemas geotermales activos.

Las zonas antes nombradas pudieran están caracterizadas, a su vez, por diferentes tipos de fluidos geotermales. Considerando el modelo de la Figura 21, los sectores más someros del upflow central, asociados a la zona bifásica líquido-vapor, pudieran estar relacionada a aguas con mayor componente sulfurada que aguas de otros sectores (cf. Giggenbach, 1988). Por otro lado, las zonas marginales a la zona de ascenso de fluidos pudieran ser caracterizadas por fluidos clorurados maduros, y localmente por aguas bicarbonatadas o aguas de recarga. Cabe notar los controles sobre la composición y tipo de los fluidos geotermales en general son complejos, donde sus características pueden cambiar por una diversidad de factores, entre los que están la precipitación de minerales a partir de ellos, interacción con la roca, con otros tipos de aguas y/o procesos de enfriamiento. En este sentido, la pirita podría ser empleada como complemento para indagar en la “madurez” o tipo de los fluidos del sistema, acoplándola a otros tipos de estudio, y teniendo en cuenta que las zonas caracterizadas por ebullición o no-ebullición no necesariamente estarán vinculadas a solo un tipo de fluido.

Todo lo antes mencionado es especialmente relevante considerando que la pirita es un mineral relativamente “refractario”, es decir, que es un mineral que se reequilibra relativamente lento frente a cambios fisicoquímicos que afecten al sistema (Vaughan y Craig, 1997; Libbey y Williams-Jones, 2016). Esta propiedad posibilita que la pirita no solo tenga el potencial para registrar procesos fisicoquímicos que ocurren en sistemas geotermales actualmente, sino que también puede registrar procesos que han caracterizado etapas anteriores en la evolución geológica de estos sistemas, como ha sido mostrado en el Capítulo 2 para el SGCP. Esto, sumado a que la pirita es de amplia distribución espacial en los sistemas geotermales, sugiere que las características texturales y composicionales de la pirita pudieran ser un valioso complemento para estudiar la evolución de la arquitectura de estos sistemas.

Una aplicación particular de lo nombrado antes es la posibilidad de considerar las características composicionales y texturales de la pirita como un complemento para detectar e identificar eventos de fracturamiento de roca que hayan ocurrido en sistemas geotermales activos y fósiles. Esto es debido a que eventos de fracturamiento de roca, desencadenados por sismos (ej.: Sánchez-Alfaro et al., 2016b) u otros, pueden causar la despresurización abrupta del sistema, local o generalizadamente, causando la ebullición abrupta (flashing) de fluidos hidrotermales en profundidad. Desde el punto de vista de los sistemas geotermales activos productivos, este tipo de eventos es relevante porque tiene grandes implicancias en la permeabilidad (secundaria) de los fluidos geotermales; y desde el punto de vista de los depósitos epitermales Au-Ag, análogos fósiles de los sistemas geotermales activos (Hedenquist y Lowenstern, 1994), los eventos de fracturamiento y ebullición abrupta tienen un rol directo en la precipitación de Au, Ag y otros metales de interés económico (ej.: Moncada et al., 2012, 2017, Sánchez-Alfaro et al., 2016b).

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3.1.1. Características de la pirita y la evolución del SGCP

Como es indicado en el Capítulo 2, la secuencia paragenética propuesta para el SGCP, en conjunto con la interpretación de las condiciones de precipitación de cada grupo de pirita, sugieren que la zona estudiada probablemente evolucionó desde condiciones de ebullición vigorosa o violenta a condiciones de no-ebullición. En particular, las características composicionales y texturales de la pirita registran especialmente bien esta transición. Este cambio mayor en las condiciones fisicoquímicas del sistema pudiera haber sido causado, entre otros, por la presurización del reservorio, por la infiltración de aguas someras más frías (de recarga o aguas ricas en CO2) y/o por un debilitamiento en el sistema convectivo del sistema geotermal relacionado a un enfriamiento local o generalizado.

Una primera posibilidad es que este cambio esté relacionado con la posible presurización del reservorio producto del desarrollo de la capa sello que caracteriza al SGCP (Fig. 22, Urzúa et al., 2002; Maza et al., 2018). En el trabajo de Maza et al. (2018) se describen las características mineralógicas de la capa sello del SGCP, sugiriendo que esta capa es especialmente impermeable, basándose en que la transición de esmectita a illita-esmectita R1, registrada en la capa sello del SGCP, ocurre abruptamente en función de la temperatura (aunque gradualmente en función de la profundidad, Fig. 22), y que la temperatura a la que ocurre dicha transición es mayor a la temperatura de esta transición en otros sistemas geotermales similares. Esto, sumado a la escasez de manifestaciones termales en superficie, confirman la eficiencia de la capa sello del SGCP para limitar el flujo de fluidos geotermales desde la zona de reservorio hasta superficie. Debido a esta característica de la capa sello, es plausible que su generación haya favorecido la posible presurización del sistema, con la consecuente detención de los procesos de ebullición en el nivel estudiado.

Figura 22: Modelo conceptual simplificado del SGCP (tomado de Urzúa et al., 2002, y Maza et al., 2018), donde se indica la ubicación del sondaje PEXAP-1 y su relación con la capa sello del sistema, que corresponde a la zona de menor resistividad eléctrica (aprox. <2 Ωm). También se muestra en detalle la variación de la temperatura a lo largo del sondaje PEXAP-1, así como la variación con la profundidad de la proporción de illita en illita-esmectita (Maza et al., 2018). 53

La infiltración de aguas someras más frías a la zona propilítica también pudiera haber tenido un rol en la detención de la ebullición, y pudiera ser un fenómeno complementario a la formación de la capa sello. De hecho, en las muestras estudiadas, el último evento de mineralización registrado (calcita rómbica-calcopirita-galena-acantita) podría sugerir que, en esta etapa registrada en el SGCP, aguas relativamente frías, ricas en CO2, pudieron haber interactuado con fluidos geotermales más calientes, ricos en metales, desencadenando la precipitación de calcita producto de su solubilidad retrógrada (Ellis, 1959). Cabe notar que las aguas calentadas por vapor ricas en CO2 son comunes en sistemas geotermales, donde se ha propuesto que son formadas cuando el CO2 derivado de la ebullición de fluidos geotermales más profundos es disuelto en aguas meteóricas más someras (ej.: Simmons and Browne, 2000). Además, los niveles caracterizados por este tipo de aguas (inicialmente levemente ácidas) usualmente presentan alteración argílica pervasiva, debido a reacciones de neutralización que alteran feldespatos a arcillas (ej.: Marini, 2000). Por todo lo anterior, la presencia e influencia de este tipo de aguas someras más frías, ricas en CO2, es compatible con la formación de la capa sello.

De este modo, el estudio de la composición y micro-texturas de la pirita es útil para sugerir la ocurrencia de otros procesos importantes en sistemas geotermales activos y fósiles, al combinarla con otro tipo de evidencias geológicas. En este caso, la evolución en las características composicionales y texturales de la pirita podría ser relacionada con procesos complejos como la formación de una capa sello, y la infiltración de otros tipos de fluidos.

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CAPÍTULO 4: CONCLUSIONES

La pirita es el sulfuro más común en el Sistema Geotermal Cerro Pabellón (SGCP). Su abundancia en el sistema es mayor en la zona de alteración propilítica (>490 m del sondaje PEXAP-1), donde ocurre junto a calcopirita, galena y acantita.

La pirita del SGCP se caracteriza por tener concentraciones significativas de metales base (Co, Ni, Cu y Pb), metales preciosos (Au y Ag) y metaloides (As, Sb, Se, Bi y Tl), de forma similar a otros sistemas geotermales, como el Sistema Geotermal Tolhuaca, en Chile (Tardani et al., 2017). Estos elementos ocurren tanto en solución sólida como formando inclusiones minerales de galena, calcopirita y acantita en granos de pirita. Adicionalmente, se pudo constatar que la pirita del sistema muestra zonaciones composicionales de As, Cu y Co, comunes, aunque no detectables en la totalidad de los granos.

En base a las texturas y asociaciones de minerales de ganga asociados a la pirita, y a la temporalidad relativa entre los eventos relacionados a estos minerales, se pudo inferir las condiciones fisicoquímicas dominantes durante la precipitación de la pirita, y cómo éstas evolucionaron en el sistema. Se infiere que las condiciones de precipitación cambiaron desde una fase inicial de ebullición vigorosa a una etapa tardía de ebullición suave (i.e., cambios fisicoquímicos menos abruptos que durante ebullición vigorosa) o de no-ebullición. La pirita formada durante ebullición vigorosa se caracteriza por tener concentraciones mayores de As, Cu, Pb, Ag y Au, y menores de Co y Ni en comparación con pirita formada en condiciones diferentes. Estos granos de pirita son anhedrales a euhedrales, localmente con textura porosa con abundantes inclusiones minerales, sugiriendo una formación por cristalización rápida. Por otro lado, la pirita formada en condiciones de ebullición suave, o de no-ebullición, se caracteriza por tener concentraciones relativamente mayores de Co y Ni, y menores de As, Cu, Pb, Ag y Au. Texturalmente, estas piritas forman agregados de cristales euhedrales y prístinos, con escasos poros e inclusiones minerales, sugiriendo una formación bajo condiciones fisicoquímicas más estables.

De los resultados antes mencionados, se sugiere que la geoquímica de la pirita de sistemas geotermales posiblemente es controlada por la incorporación de metales y metaloides a partir de los fluidos formadores de pirita, una vez que se alcanzan condiciones de saturación. Por lo tanto, las mayores concentraciones de As, Cu, Pb, Ag y Au en la pirita formada durante ebullición podría ser el resultado de la desestabilización abrupta de los complejos de metales y metaloides, debido a cambios fisicoquímicos abruptos durante la ebullición; mientras que las mayores concentraciones de Co y Ni en la pirita de no-ebullición pudieran ser reflejo de una mayor sensibilidad de los complejos de estos metales a ser desestabilizados por cambios fisicoquímicos no necesariamente ligados a ebullición, como puede ser el enfriamiento del fluido parental.

Estos resultados muestran que la pirita, además de poder registrar la evolución composicional de los fluidos hidrotermales, como fue demostrado por Reich et al. (2013) y Tardani et al. (2017), también puede proveer información crítica sobre procesos fisicoquímicos como ebullición y separación de fases. Dado que la ebullición de fluidos acuosos es un fenómeno común en sistemas geotermales activos y fósiles (depósitos epitermales de Au-Ag), estos resultados resaltan el potencial uso de la pirita como una herramienta complementaria para explorar la evolución geológica de sistemas geotermales activos, y también para vectorizar hacia mineralización de Au-Ag relacionada a ebullición en depósitos epitermales de baja a intermedia sulfuración. 55

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ANEXOS

ANEXO A: Anexo Metodológico

A.1. Análisis LA-ICP-MS

A.1.1. Condiciones de análisis LA-ICP-MS

Cada análisis puntual consistió en 30 s de lectura de fondo (background) y 30 s de lectura durante la ablación de la muestra. Durante estas mediciones, se consideró un tiempo de barrido de cuadrupolo (sweep time) de 0,55 s. En general se usó un diámetro de haz de 30 µm, reduciendo a 20 µm en casos específicos, para evitar incorporar inclusiones minerales. La metodología usada fue similar a la de Franchini et al. (2015), que considera tasa de repetición de pulsos de 4 Hz y energía del haz de 1,5 J/cm2.

Los análisis puntuales fueron realizados en tandas de 20 puntos, y al inicio y final de cada tanda fueron analizados, en duplicado, los materiales de referencia MASS-1 (Wilson et al., 2002) y GSE-1G (Jochum et al., 2005). El material MASS-1 fue usado para la cuantificación de las concentraciones (i.e., como estándar primario), mientras que GSE-1G fue usado como estándar secundario, para validación de la calibración. La reducción de datos fue realizada en el software IoliteTM v. 2.5 (Paton et al., 2011).

A.1.2. Calibración de análisis LA-ICP-MS

El método de calibración considerado fue el de Longerich et al. (1996), que es uno de los más utilizados para este fin. La expresión de este método de calibración es la siguiente:

= 𝑖𝑖 𝐸𝐸𝐸𝐸 𝐸𝐸𝐸𝐸 𝑖𝑖 𝑖𝑖 𝑪𝑪𝑀𝑀𝑀𝑀 𝑐𝑐𝑐𝑐𝑐𝑐𝑀𝑀𝑀𝑀 𝑐𝑐𝑐𝑐𝑐𝑐𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑪𝑪𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 𝑐𝑐𝑐𝑐𝑐𝑐𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 ∙ � 𝑖𝑖 � ∙ � 𝐸𝐸𝐸𝐸 � 𝐸𝐸𝐸𝐸 � Para cada elemento i, el método convierte𝑐𝑐𝑐𝑐𝑐𝑐 𝑀𝑀𝑀𝑀la medición𝑪𝑪𝑀𝑀𝑀𝑀 “en bruto”𝑪𝑪𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚 del elemento (intensidad de la señal, expresada en cuentas por segundo, cps), a una concentración “C”, expresada en µg/g o en partes por millón (ppm). Cabe notar que los términos cps a utilizar en la fórmula están corregidos, a su vez, por la intensidad del background.

Este método de calibración considera la aplicación de correcciones por estándar interno (EI) y material de referencia (MR).

Estándar Interno

El estándar interno consiste en un elemento químico del que se conoce previamente su concentración en los granos minerales a analizar. Comúnmente, para la obtención de un estándar interno válido se analizan los granos de forma previa por EMPA u otro método apropiado, aunque algunos investigadores optan por usar las concentraciones teóricas (estequiométricas) por simplicidad (ej.: Large et al., 2009, 2014). Cabe mencionar que las concentraciones reales de los elementos mayores pueden desviarse notoriamente de las teóricas en minerales, por lo que es recomendado analizar el estándar interno en vez de asumirlo.

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En el caso de los sulfuros analizados en el presente trabajo, se midió la concentración de Fe total en piritas y calcopiritas mediante EMPA, previo al análisis mediante LA-ICP-MS. Este valor, medido por cada grano analizado, fue usado como estándar interno para la calibración.

Material de Referencia

El material de referencia (MR) es un material químicamente homogéneo del que se conoce su composición con suficiente grado de certeza. Cada elemento a cuantificar en la muestra (incógnita) debe estar cuantificado en el MR, de modo contrario no es posible la calibración mediante el método antes expuesto.

Uno de los objetivos del uso de un MR es considerar y replicar los posibles efectos de fraccionamiento elemental o interferencias que son inherentes al material que está siendo analizado (ej.: Gilbert et al., 2014, para el caso de los sulfuros). Por esto, es fundamental que el MR tenga la misma naturaleza, o la misma “matriz” que la incógnita. Particularmente, al analizar sulfuros por LA-ICP-MS, el MR debe corresponder a un sulfuro o similar.

Uno de los desafíos más relevantes para el análisis de sulfuros por LA-ICP-MS ha sido la falta de MR comerciales de tipo sulfuro, debido, entre otras razones, a que lograr la homogeneidad de ciertos elementos en este tipo de material es difícil, si se consideran sulfuros sintéticos, y a que los sulfuros naturales son composicionalmente heterogéneos en general.

El único MR comercial con matriz sulfurada disponible actualmente es el MASS-1 del USGS (Wilson et al., 2002; Fig. 23A), que es usado ampliamente para el análisis de elementos traza en diversos sulfuros, y que fue utilizado para la calibración de los análisis del presente trabajo. Sin embargo, la necesidad de cuantificar elementos que no están certificados en este material, y las heterogeneidades reportadas para algunos elementos en este MR (ej.: Au), han limitado su aplicabilidad. La escasez de MR comerciales de este tipo ha promovido la fabricación propia de estándares por parte de los laboratorios (materiales de referencia in-house).

Figura 23: Materiales de Referencia para calibración de análisis de sulfuros por LA-ICP-MS. A: PS-1 (MASS-1); B: STDGL2b2. Tomado de Danyushevsky et al. (2011).

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La fabricación de MR sulfurados in-house ha sido realizada para la cuantificación de diferentes grupos de elementos y mediante diversos procedimientos. Una parte considerable de estos materiales ha sido preparada para cuantificar metales nobles en sulfuros (principalmente PGE y Au), mientras que solo una parte reducida ha sido fabricada para cuantificar un conjunto más grande de elementos en varios sulfuros. Dentro de este último grupo se encuentran los materiales MASS-1 (Wilson et al., 2002), STDGL-1 (Norman et al., 2003) y STDGL2b2 (Danyushevsky et al., 2011; Fig. 23B), concebidos para convertirse en estándares universales para el análisis de sulfuros. Del mismo modo, el estándar MUL-ZnS-1 (Onuk et al., 2017) está diseñado para la cuantificación de diversos elementos de interés en esfalerita. Recientemente, algunos materiales de referencia han sido preparados para la calibración de razones isotópicas en sulfuros, como YN411-m de Chen et al. (2017) o PSPT-x de Bao et al., (2017).

Los métodos que han sido utilizados para la preparación de estos materiales son diversos, y se pueden agrupar en: (I) segregación de sulfuro inmiscible por ensayo al fuego (Shibuya et al., 1998; Alard et al., 2000; Lorand y Alard, 2001; McDonald, 2005; Gilbert et al., 2013), (II) sulfuros sinterizados (Ballhaus y Sylvester, 2000; Wohlgemuth-Ueberwasser et al., 2007; Onuk et al., 2017), (III) nanopartículas de sulfuro prensadas en frio (Wilson et al., 2002; Bao et al., 2017), (IV) vidrios sulfurados (Norman et al., 2003; Danyushevsky et al., 2011; Chen et al., 2017) y (V) síntesis por fusión y templado (Cabri et al., 2003; Sylvester et al., 2005; Mungall et al., 2005).

A.2. Análisis estadístico de datos composicionales

A.2.1. Estadística descriptiva

Para la descripción general de los resultados de los análisis composicionales de sulfuros (EMPA + LA-ICP-MS) se consideraron los siguientes parámetros por cada elemento químico analizado: número de análisis sobre el límite de detección, media, mediana, mínimo y máximo. Todos estos parámetros fueron presentados en formato de diagramas de caja-bigote (boxplots). Los gráficos fueron preparados para el total de los análisis realizados, y también para subconjuntos de datos, propuestos a su vez según criterios geológicos (ej.: asociación de vetillas) o criterios metodológicos (ej.: grupo de análisis influenciados por inclusiones minerales).

A.2.2. Análisis exploratorio de datos

En una primera instancia, los datos composicionales de la pirita fueron examinados mediante el cálculo de la matriz de correlaciones acompañado de gráficos de dispersión (scatterplots). Posteriormente, y con la finalidad de inspeccionar e interpretar la base de datos geoquímica de pirita (LA-ICP-MS), se usaron dos siguientes técnicas estadísticas exploratorias para bases de datos multivariable: Análisis de Clusters y Análisis de Componentes Principales (ACP).

Matriz de correlaciones y scatterplots

La matriz de correlaciones para todos los elementos analizados fue calculada mediante el software ioGAS, a partir de las concentraciones en bruto (en ppm), y también aplicando una transformación logarítmica a las concentraciones. Del mismo modo, se examinó la matriz considerando coeficientes de correlación de Pearson (rP), así como también coeficientes de correlación de Spearman (rS), que es una versión más robusta del coeficiente de correlación. Las 62 correlaciones más altas (rP o rS cercano a -1 o 1) fueron verificadas gráficamente mediante scatterplots.

Análisis de Clusters

El análisis de clusters es una técnica estadística que permite evaluar la similitud entre cada muestra analizada, en términos de su composición química. La similitud entre las concentraciones químicas es evaluada a partir de la distancia entre muestras en el espacio multivariable definido por los elementos químicos analizados: a menor distancia en este espacio, mayor similitud entre muestras.

En el caso del presente trabajo, se aplicó análisis de clusters solo para verificar la similitud entre los grupos propuestos por el algoritmo empleado y las agrupaciones realizadas mediante la observación geológica. En primera instancia, a modo exploratorio, se realizó un análisis de clusters jerárquico en el software SPSS. Posteriormente, se usó un algoritmo de k- means (MacQueen, 1967) usando ioGAS.

Cabe notar que en este trabajo solo se muestra la agrupación realizada por criterio geológico, pero ésta fue validada por análisis de clusters.

Análisis de Componentes Principales

El Análisis de Componentes Principales (ACP) es una herramienta estadística cuya función principal es la de reducción de dimensiones de un conjunto de datos, manteniendo a la vez la mayor parte de la varianza del conjunto (ver Reimann et al., 2008). El ACP logra lo anterior al identificar las direcciones por las cuales la varianza del conjunto es máxima. A través de estas direcciones se calculan nuevas variables, denominadas “Componentes Principales”, que sintetizan en una nueva variable la información contenida en varias de las variables originales. De este modo, es posible representar la información de una muestra de manera más simple.

En el caso de una base de datos geoquímica, su dimensionalidad está dada por la cantidad de variables que ésta tenga, es decir, por los elementos químicos que fueron analizados. Mediante ACP es posible simplificar la base de datos geoquímica, al detectar cuáles elementos químicos están correlacionados entre sí, y que pudieran ser redundantes desde un punto de vista estadístico.

Por ejemplo, en la Figura 24 se muestra un diagrama de dispersión de Mg vs. Na (tomado de la base de datos geoquímica “moss” de Reimann et al., 2008), en donde se puede notar que el Componente Principal 1 (PC1) se calcula en la dirección de mayor varianza del conjunto de datos, mientras que el Componente Principal 2 (PC2) es calculado de manera ortogonal a PC1, y por la segunda dirección de mayor varianza.

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Figura 24: Diagramas de dispersión Na vs. Mg, donde se indican las direcciones de los componentes principales (a través de las direcciones de máxima varianza) y las proyecciones de los puntos originales sobre las nuevas variables. Ejemplo tomado de Reimann et al. (2008).

El ACP, además de servir para la simplificación de la base de datos geoquímica, es una herramienta útil para interpretar la estructura de la base de datos y apoyar interpretaciones sobre la misma. En este sentido, es especialmente útil combinar gráficamente los resultados de un ACP con los resultados de una agrupación mediante Análisis de clusters u otro criterio de subdivisión de los datos.

En este trabajo, se realizaron ACP mediante SPSS, y se muestran sus resultados gráficamente mediante biplots (Gabriel, 1958).

Tratamiento de datos para ACP

El tratamiento de datos para ACP fue realizado siguiendo los lineamientos propuestos por Reimann et al. (2008) y Cloutier et al. (2008). A continuación, se explicitan los criterios considerados.

Dimensionalidad

Para la aplicación de ACP se consideraron solo los elementos detectados en mayor proporción en pirita, para: (1) evitar sesgar los resultados e interpretación por valores bajo el límite de detección; y (2), lograr que el ACP fuera significativo, considerando una proporción suficiente de puntos analizados en relación a variables consideradas. En relación al punto (2), se consideró una regla general de n > 9p, donde n es el número de puntos analizados, y p, el número de variables (o parámetros) a considerar para ACP. En total se consideraron 6 elementos químicos para el análisis (Co, Ni, Cu, Pb, As y Ag).

Datos censurados (bajo el límite de detección)

Para evaluar el impacto de descartar valores bajo el límite de detección (bld), se realizaron ACP tanto descartando valores bld como considerándolos, al reemplazarlos por la mitad del límite de detección del análisis. 64

Tratamiento de outliers

Para los ACP solo se consideraron datos no influidos por inclusiones minerales, los que están asociados, a su vez, a los outliers del conjunto de datos. Con esto se descartaron todos los datos “anómalos” del conjunto de datos, no siendo necesaria otra técnica para identificar outliers.

Normalización de los datos

Se consideró como condición para el ACP que las variables sigan una distribución normal. Para asegurar esta condición, se inspeccionaron las distribuciones de los 6 elementos antes nombrados, y se aplicó una transformación logarítmica centrada para cumplir la condición.

En particular, la transformación aplicada fue la razón logarítmica centrada (centered log- ratio, CLR; Aitchison, 1986). Para un análisis puntual donde se consideran j elementos químicos, la transformación se expresa para la concentración del elemento i (Ci) en el análisis puntual considerado, de la siguiente forma:

( ) = 𝐶𝐶𝑖𝑖 𝑖𝑖 ⎛𝑗𝑗 ⎞ 𝐶𝐶𝐶𝐶𝐶𝐶 𝐶𝐶 𝑙𝑙𝑙𝑙 𝑗𝑗 �∏𝑘𝑘=1 𝐶𝐶𝑘𝑘 Una transformación logarítmica simple⎝ también pudo⎠ ser ocupada para lograr la normalidad de las variables, pero se optó por la CLR debido a que tendría el potencial para evitar el efecto de la “clausura” de los datos composicionales, es decir, el efecto que puede tener sobre los análisis estadísticos el hecho que la suma de las composiciones de la muestra analizada sea igual a 100 wt% o 106 ppm (ver Reimann et al., 2008).

Estandarización de los datos

Posteriormente, se estandarizaron los datos transformados mediante la aplicación del valor Z, con la finalidad de hacer comparables las variables consideradas (en cuanto a promedio y rango de valores).

( ) = 𝑥𝑥𝑖𝑖 − 𝑥𝑥̅𝑖𝑖 𝑍𝑍 𝑥𝑥𝑖𝑖 Donde = ( ), es el promedio de𝜎𝜎 𝑖𝑖 en todos los puntos medidos, y es la desviación estándar del mismo conjunto. 𝑥𝑥𝑖𝑖 𝐶𝐶𝐶𝐶𝐶𝐶 𝐶𝐶𝑖𝑖 𝑥𝑥̅𝑖𝑖 𝑥𝑥𝑖𝑖 𝜎𝜎𝑖𝑖

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A.3. Referencias Anexo Metodológico

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Alard O., Griffin W. L., Lorand J. P., Jackson S. E. y O’Reilly S. Y. (2000) Non-chondritic distribution of the highly siderophile elements in mantle sulphides. Nature 407, 891–894.

Ballhaus C. y Sylvester P. (2000) Noble Metal Enrichment Processes in the Merensky Reef, Bushveld Complex. Journal of Petrology 41, 545–561.

Bao Z., Chen L., Zong C., Yuan H., Chen K. y Dai M. (2017) Development of pressed sulfide powder tablets for in situ sulfur and lead isotope measurement using LA-MC-ICP-MS. International Journal of Mass Spectrometry (in press).

Cabri L., Sylvester P., Tubrett M., Peregoedova A. y Laflamme J. (2003) Comparison of LAM- ICP-MS and micro-PIXE results for palladium and rhodium in selected samples of Noril’sk and Talnakh sulfides. The Canadian Mineralogist 41, 321–329.

Chen L., Chen K., Bao Z., Liang P., Sun T. y Yuan H. (2017) Preparation of standards for in situ sulfur isotope measurement in sulfides using femtosecond laser ablation MC-ICP-MS. Journal of Analytical Atomic Spectrometry 32, 107–116.

Cloutier V., Lefebvre R., Therrien R. y Savard M. M. (2008) Multivariate statistical analysis of geochemical data as indicative of the hydrogeochemical evolution of groundwater in a sedimentary rock aquifer system. Journal of Hydrology 353, 294–313.

Danyushevsky L., Robinson P., Gilbert S., Norman M., Large R., McGoldrick P. y Shelley M. (2011) Routine quantitative multi-element analysis of sulphide minerals by laser ablation ICP- MS: Standard development and consideration of matrix effects. Geochemistry: Exploration, Environment, Analysis 11, 51–60.

Franchini M., McFarlane C., Maydagán L., Reich M., Lentz D. R., Meinert L. y Bouhier V. (2015) Trace metals in pyrite and marcasite from the Agua Rica porphyry-high sulfidation epithermal deposit, Catamarca, Argentina: Textural features and metal zoning at the porphyry to epithermal transition. Ore Geology Reviews 66, 366–387.

Gabriel K. R. (1971) The Biplot Graphic Display of Matrices with Application to Principal Component Analysis. Biometrika 58, 453–467.

Gilbert S., Danyushevsky L., Robinson P., Wohlgemuth-Ueberwasser C., Pearson N., Savard D., Norman M. y Hanley J. (2013) A Comparative Study of Five Reference Materials and the Lombard Meteorite for the Determination of the Platinum-Group Elements and Gold by LA-ICP- MS. Geostandards and Geoanalytical Research 37, 51–64.

Gilbert S. E., Danyushevsky L. V., Goemann K. y Death D. (2014) Fractionation of sulphur relative to iron during laser ablation-ICP-MS analyses of sulphide minerals: implications for quantification. Journal of Analytical Atomic Spectrometry 29, 1024–1033.

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Jochum K. P., Willbold M., Raczek I., Stoll B. y Herwig K. (2005) Chemical Characterisation of the USGS Reference Glasses GSA-1G, GSC-1G, GSD-1G, GSE-1G, BCR-2G, BHVO-2G and BIR-1G Using EPMA, ID-TIMS, ID-ICP-MS and LA-ICP-MS. Geostandards and Geoanalytical Research 29, 285–302.

Large R. R., Danyushevsky L., Hollit C., Maslennikov V., Meffre S., Gilbert S., Bull S., Scott R., Emsbo P., Thomas H., Singh B. y Foster J. (2009) Gold and Trace Element Zonation in Pyrite Using a Laser Imaging Technique: Implications for the Timing of Gold in Orogenic and Carlin- Style Sediment-Hosted Deposits. Economic Geology 104, 635–668.

Large R. R., Halpin J. A., Danyushevsky L. V., Maslennikov V. V., Bull S. W., Long J. A., Gregory D. D., Lounejeva E., Lyons T. W., Sack P. J., McGoldrick P. J. y Calver C. R. (2014) Trace element content of sedimentary pyrite as a new proxy for deep-time ocean–atmosphere evolution. Earth and Planetary Science Letters 389, 209–220.

Longerich H. P., Jackson S. E. y Gunther D. (1996) Laser ablation inductively coupled plasma mass spectrometric transient signal data acquisition and analyte concentration calculation. Journal of Analytical Atomic Spectrometry 11, 899–904.

Lorand J.-P. y Alard O. (2001) Platinum-group element abundances in the upper mantle: new constraints from in situ and whole-rock analyses of Massif Central xenoliths (France). Geochimica et Cosmochimica Acta 65, 2789–2806.

MacQueen J. (1967) Some methods for classification and analysis of multivariate observations. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, Volume 1: Statistics. University of California Press. pp. 281–297.

McDonald I. (2005) Development of a sulphide standard for the in situ analysis of platinum- group elements by laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS). 10th International Platinum Symposium: Oulu, Geological Survey of Finland, Extendend Abstracts. pp. 468–471.

Mungall J. E., Andrews D. R. A., Cabri L. J., Sylvester P. J. y Tubrett M. (2005) Partitioning of Cu, Ni, Au, and platinum-group elements between monosulfide solid solution and sulfide melt under controlled oxygen and sulfur fugacities. Geochimica et Cosmochimica Acta 69, 4349– 4360.

Norman M., Robinson P. y Clark D. (2003) Major- and trace-element analysis of sulfide ores by laser-ablation ICP-MS, solution ICP–MS, and XRF: new data on international reference materials. The Canadian Mineralogist 41, 293–305.

Onuk P., Melcher F., Mertz-Kraus R., Gäbler H.-E. y Goldmann S. (2017) Development of a Matrix-Matched Sphalerite Reference Material (MUL-ZnS-1) for Calibration of In Situ Trace Element Measurements by Laser Ablation-Inductively Coupled Plasma-Mass Spectrometry. Geostandards and Geoanalytical Research 41, 263–272.

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Reimann C., Filzmoser P., Garrett R. G. y Dutter R. (2008) Statistical Data Analysis Explained: Applied Environmental Statistics with R. John Wiley & Sons Ltd., Chichester, England (362pp)

Shibuya E., Sarkis J., Enzweiler J., Jorge A. y Figueiredo A. (1998) Determination of platinum group elements and gold in geological materials using an ultraviolet laser ablation high-resolution inductively coupled plasma mass spectrometric technique. Journal of Analytical Atomic Spectrometry 13, 941–944.

Wilson S. A., Ridley W. I. y Koenig A. E. (2002) Development of sulfide calibration standards for the laser ablation inductively-coupled plasma mass spectrometry technique. Journal of Analytical Atomic Spectrometry 17, 406–409.

Wohlgemuth-Ueberwasser C. C., Ballhaus C., Berndt J., Stotter née Paliulionyte V. y Meisel T. (2007) Synthesis of PGE sulfide standards for laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). Contributions to Mineralogy and Petrology 154, 607–617.

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ANEXO B: Gráficos resumen de análisis composicionales de otros sulfuros del Sistema Geotermal Cerro Pabellón

B.1. Calcopirita

La composición química de la calcopirita del SGCP se resume en la Figura 25, en donde se muestran los datos composicionales representativos obtenidos por EMPA (n=91) y LA-ICP- MS (n=41). En el caso de los datos de LA-ICP-MS, solo se consideraron aquellos análisis sin la influencia obvia de la ablación de inclusiones minerales, según lo observado en perfiles de profundidad de LA-ICP-MS.

Figura 25: Concentraciones de elementos menores y traza en calcopirita del SGCP (muestras BA20, BA30, BA34 y BA48), incluyendo datos composicionales de EMPA (cajas grises, n=91) y LA-ICP-MS (cajas blancas, n=41). Los elementos marcados en negrita fueron los detectados en mayor proporción por LA-ICP-MS.

Las relaciones entre los elementos cuantificados más relevantes en la calcopirita del SGCP se muestran mediante gráficos de dispersión en la Figura 26 y Figura 27, diferenciando por muestra, y considerando a Ag como la variable para comparar, por su ubiquidad en los granos analizados.

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Figura 26: Gráficos de dispersión de concentraciones químicas en calcopirita del SGCP, considerando solo datos obtenidos por LA-ICP-MS

Figura 27: Gráfico de dispersión Cu-Ag en calcopirita del SGCP, considerando solo datos de EMPA (n=91).

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B.2. Galena

La composición química de la galena del SGCP se resume en la Figura 28, donde se muestran los datos composicionales representativos obtenidos por EMPA (n=26) en dos muestras del SGCP. No se realizaron análisis LA-ICP-MS en granos de galena.

Figura 28: Concentraciones de elementos menores en galena del SGCP (muestras BA20 y BA33), medidas por EMPA (n = 26). Los elementos marcados en negrita fueron los detectados en mayor proporción.

En la Figura 29 se muestran gráficos de dispersión para Fe, Pb, Ag y Se en galena del SGCP, diferenciados por muestra.

Figura 29: Gráficos de dispersión de concentraciones químicas en galena del SGCP (datos obtenidos por EMPA)

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ANEXO C: Resultados de análisis EMPA en pirita del Sistema Geotermal Cerro Pabellón.

Este anexo es equivalente a “Supplementary material A” indicado en el manuscrito.

(b.d.: bajo el límite de detección)

Fe Cu Zn Ni Co As Sb Ag Au Se Bi S Pb Te TOTAL ID análisis Grupo [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] BA20_EMP_PY_1a_3 III 46,77 b.d. b.d. 0,09 0,06 0,03 b.d. b.d. b.d. 0,03 b.d. 53,59 b.d. b.d. 100,57 BA20_EMP_PY_1a_4 III 46,69 b.d. b.d. 0,03 b.d. b.d. b.d. b.d. b.d. 0,03 b.d. 53,49 b.d. 0,03 100,27 BA20_EMP_PY_1a_5 III 47,05 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,74 b.d. b.d. 100,79 BA20_EMP_PY_1b_1 III 46,88 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,79 b.d. b.d. 100,67 BA20_EMP_PY_1b_2 III 46,69 b.d. b.d. b.d. b.d. 0,03 b.d. b.d. b.d. b.d. b.d. 53,86 b.d. b.d. 100,58 BA20_EMP_PY_1b_3 III 46,83 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,93 b.d. b.d. 100,76 BA20_EMP_PY_1b_4 III 46,91 b.d. b.d. b.d. b.d. 0,04 b.d. b.d. b.d. b.d. b.d. 53,90 b.d. b.d. 100,85 BA20_EMP_PY_1b_5 III 46,78 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,68 b.d. b.d. 100,46 BA20_EMP_PY_1b_6 III 46,68 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,73 b.d. b.d. 100,41 BA20_EMP_PY_05_1 III 47,06 0,05 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,72 b.d. b.d. 100,83 BA20_EMP_PY_05_3 III 46,67 b.d. b.d. 0,09 0,26 0,05 b.d. b.d. b.d. b.d. b.d. 53,51 b.d. b.d. 100,58 BA20_EMP_PY_05_4 III 46,77 0,33 b.d. b.d. b.d. 0,28 b.d. b.d. b.d. 0,03 b.d. 53,49 b.d. b.d. 100,90 BA20_EMP_PY_05_2 III 46,88 b.d. b.d. 0,36 b.d. 0,06 b.d. b.d. b.d. b.d. b.d. 53,54 b.d. b.d. 100,84 BA20_EMP_PY_04_1 III 46,94 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,53 b.d. b.d. 100,47 BA20_EMP_PY_04_2 III 45,94 0,82 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,50 b.d. b.d. 100,26 BA20_EMP_PY_04_3 III 46,32 0,43 b.d. b.d. b.d. 0,03 b.d. b.d. b.d. b.d. b.d. 53,55 b.d. b.d. 100,33 BA20_EMP_PY_04_4 III 46,67 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,05 b.d. b.d. 53,49 b.d. b.d. 100,21 BA20_EMP_PY_04_5 III 46,91 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,46 b.d. b.d. 100,37 BA20_EMP_PY_04_6 III 46,80 0,05 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,45 b.d. b.d. 100,30 BA20_EMP_PY_06_1 III 46,71 0,22 b.d. b.d. b.d. 0,19 b.d. b.d. b.d. b.d. b.d. 53,46 b.d. b.d. 100,58 BA20_EMP_PY_06_2 III 46,38 0,13 b.d. b.d. b.d. 0,03 b.d. b.d. b.d. b.d. b.d. 53,80 b.d. b.d. 100,34 BA20_EMP_PY_06_3 III 46,71 b.d. b.d. 0,07 b.d. 0,02 b.d. b.d. b.d. b.d. b.d. 53,81 b.d. b.d. 100,61 BA20_EMP_PY_06_4 III 45,78 0,81 b.d. 0,10 b.d. 0,08 0,03 0,03 b.d. 0,04 b.d. 53,81 b.d. b.d. 100,68 BA20_EMP_PY_06_5 III 46,78 0,09 b.d. b.d. b.d. 0,03 b.d. 0,02 b.d. b.d. b.d. 53,84 b.d. b.d. 100,76 BA20_EMP_PY_06_6 III 46,35 0,33 b.d. b.d. b.d. 0,04 b.d. b.d. b.d. b.d. b.d. 53,63 b.d. b.d. 100,35 BA20_EMP_PY_06_7 III 46,00 0,67 b.d. b.d. b.d. 0,38 b.d. b.d. b.d. 0,02 b.d. 53,57 b.d. b.d. 100,64 BA20_EMP_PY_06_8 III 46,70 0,05 b.d. b.d. b.d. 0,09 b.d. b.d. b.d. b.d. b.d. 53,71 b.d. b.d. 100,55 BA20_EMP_PY_06_9 III 45,75 0,14 b.d. 0,07 0,16 0,03 b.d. 2,40 b.d. 0,04 b.d. 52,34 b.d. b.d. 100,93 BA20_EMP_PY_09_1 III 46,80 0,17 b.d. 0,05 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,66 b.d. b.d. 100,68 BA20_EMP_PY_09_2 III 46,77 b.d. b.d. 0,11 b.d. 0,05 b.d. b.d. b.d. b.d. b.d. 53,79 b.d. b.d. 100,72 BA20_EMP_PY_09_3 III 46,58 b.d. b.d. b.d. b.d. 0,03 0,03 b.d. b.d. b.d. b.d. 53,76 b.d. b.d. 100,40 BA20_EMP_PY_09_4 III 46,68 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,80 b.d. b.d. 100,48 BA20_EMP_PY_09_5 III 46,79 b.d. b.d. b.d. b.d. 0,02 b.d. b.d. b.d. b.d. b.d. 53,36 b.d. b.d. 100,17 BA20_EMP_PY_10_4 III 46,70 0,05 b.d. 0,04 b.d. 0,02 b.d. b.d. b.d. b.d. b.d. 54,04 b.d. b.d. 100,85 BA20_EMP_PY_10_5 III 46,81 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,60 b.d. b.d. 100,41 BA20_EMP_PY_11_1 III 46,74 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,90 b.d. b.d. 100,64 BA20_EMP_PY_11_2 III 46,82 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,91 b.d. b.d. 100,73 BA20_EMP_PY_11_3 III 46,70 b.d. b.d. b.d. 0,04 0,03 0,03 b.d. b.d. b.d. b.d. 53,86 b.d. b.d. 100,66 BA20_EMP_PY_11_4 III 46,68 0,06 b.d. b.d. b.d. 0,03 b.d. b.d. b.d. b.d. b.d. 53,94 b.d. b.d. 100,71 BA20_EMP_PY_11_5 III 46,43 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,68 b.d. b.d. 100,11 BA20_EMP_PY_11_6 III 46,76 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,82 b.d. b.d. 100,58 BA20_EMP_PY_12_1 III 46,69 b.d. b.d. b.d. 0,05 0,02 b.d. b.d. b.d. b.d. b.d. 53,64 b.d. b.d. 100,40 BA20_EMP_PY_12_2 III 46,48 0,10 b.d. b.d. b.d. 0,05 b.d. b.d. b.d. 0,02 b.d. 53,67 b.d. b.d. 100,32 BA20_EMP_PY_12_3 III 46,78 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,72 b.d. b.d. 100,50 BA20_EMP_PY_12_4 III 46,73 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,66 b.d. b.d. 100,39 BA20_EMP_PY_12_5 III 46,44 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,66 b.d. b.d. 100,10 BA20_EMP_PY_18_1 III 46,95 0,06 b.d. b.d. b.d. 0,12 b.d. b.d. b.d. b.d. b.d. 53,76 b.d. b.d. 100,89 BA20_EMP_PY_18_2 III 46,74 0,08 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,76 b.d. b.d. 100,58 BA20_EMP_PY_18_3 III 46,75 0,19 b.d. b.d. b.d. 0,18 b.d. b.d. b.d. b.d. b.d. 53,70 b.d. b.d. 100,82 BA20_EMP_PY_18_4 III 46,73 0,13 b.d. b.d. 0,04 0,41 b.d. b.d. b.d. b.d. b.d. 53,50 b.d. b.d. 100,81 BA20_EMP_PY_18_5 III 46,69 0,27 b.d. b.d. b.d. 0,47 b.d. b.d. b.d. b.d. b.d. 53,15 b.d. b.d. 100,58 BA20_EMP_PY_18_6 III 46,37 0,29 b.d. b.d. b.d. 0,38 b.d. b.d. b.d. b.d. b.d. 53,51 b.d. b.d. 100,55 BA20_EMP_PY_18_7 III 46,34 0,33 b.d. 0,04 0,25 0,36 b.d. b.d. b.d. 0,01 b.d. 53,22 b.d. b.d. 100,55 BA27_EMP_PY_01_1 II 46,14 0,06 b.d. 0,04 0,07 0,08 b.d. b.d. b.d. b.d. b.d. 54,04 b.d. b.d. 100,43 BA27_EMP_PY_01_2 II 46,38 0,06 b.d. b.d. 0,04 0,02 b.d. 0,16 b.d. 0,02 b.d. 53,64 b.d. b.d. 100,32 BA27_EMP_PY_01_3 II 46,27 0,13 b.d. 0,05 0,19 0,11 b.d. 0,04 b.d. 0,02 b.d. 53,50 b.d. b.d. 100,31 BA27_EMP_PY_01_4 II 45,85 0,22 b.d. b.d. 0,04 0,98 0,27 b.d. b.d. b.d. b.d. 52,80 b.d. b.d. 100,16 BA27_EMP_PY_01_5 II 46,17 0,18 b.d. b.d. b.d. 0,59 0,16 b.d. b.d. b.d. b.d. 53,28 b.d. b.d. 100,38 BA27_EMP_PY_01_6 II 46,23 0,09 b.d. b.d. 0,07 0,09 b.d. 0,04 b.d. b.d. b.d. 53,13 b.d. b.d. 99,65 BA27_EMP_PY_02_1 II 46,54 0,09 b.d. b.d. 0,04 0,03 b.d. b.d. b.d. b.d. b.d. 53,30 b.d. b.d. 100,00 BA27_EMP_PY_02_2 II 46,28 0,09 b.d. b.d. b.d. 1,13 b.d. b.d. b.d. b.d. b.d. 52,88 b.d. b.d. 100,38 BA27_EMP_PY_02_3 II 45,90 0,11 b.d. b.d. b.d. 2,29 0,03 b.d. b.d. b.d. b.d. 51,92 b.d. b.d. 100,25 BA27_EMP_PY_02_4 II 46,38 0,09 b.d. b.d. b.d. 0,45 0,10 0,02 b.d. b.d. b.d. 52,87 b.d. b.d. 99,91 BA27_EMP_PY_02_5 II 45,96 0,10 b.d. b.d. b.d. 0,27 b.d. b.d. b.d. b.d. b.d. 52,87 b.d. b.d. 99,20 BA27_EMP_PY_06_1 II 46,45 0,21 b.d. b.d. b.d. 0,17 b.d. b.d. b.d. b.d. b.d. 53,48 b.d. b.d. 100,31 BA27_EMP_PY_06_2 II 46,84 0,12 b.d. b.d. b.d. 0,02 b.d. b.d. b.d. b.d. b.d. 53,50 b.d. b.d. 100,48 BA27_EMP_PY_06_3 II 46,62 0,08 b.d. b.d. b.d. 0,54 b.d. b.d. b.d. b.d. b.d. 53,22 b.d. b.d. 100,46 BA27_EMP_PY_06_4 II 46,27 0,08 0,09 b.d. b.d. 1,99 b.d. b.d. 0,05 b.d. b.d. 52,10 b.d. b.d. 100,58 BA27_EMP_PY_06_5 II 46,47 0,06 b.d. b.d. b.d. 0,64 b.d. b.d. b.d. b.d. b.d. 53,57 b.d. b.d. 100,74 BA27_EMP_PY_06_6 II 46,37 0,09 b.d. 0,04 b.d. 0,57 0,02 b.d. b.d. b.d. b.d. 53,22 b.d. b.d. 100,31 BA27_EMP_PY_07_2 II 46,57 0,08 b.d. b.d. b.d. 0,21 b.d. b.d. b.d. b.d. b.d. 53,12 b.d. b.d. 99,98 BA27_EMP_PY_07_3 II 46,65 0,06 b.d. b.d. b.d. 0,21 b.d. b.d. b.d. b.d. b.d. 52,97 b.d. b.d. 99,89 BA27_EMP_PY_07_4 II 46,54 0,08 b.d. b.d. b.d. 0,38 b.d. b.d. b.d. b.d. b.d. 52,72 b.d. b.d. 99,72 BA27_EMP_PY_07_5 II 46,74 0,10 b.d. b.d. b.d. 0,08 b.d. b.d. b.d. b.d. b.d. 53,18 b.d. b.d. 100,10 BA27_EMP_PY_11_2 II 46,16 0,32 b.d. 0,04 b.d. 0,11 0,10 0,04 b.d. b.d. b.d. 53,22 0,28 b.d. 100,27 72

Fe Cu Zn Ni Co As Sb Ag Au Se Bi S Pb Te TOTAL ID análisis Grupo [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] BA27_EMP_PY_11_3 II 46,64 0,13 b.d. b.d. b.d. 0,04 b.d. b.d. b.d. b.d. b.d. 53,75 b.d. b.d. 100,56 BA27_EMP_PY_11_4 II 45,82 0,15 b.d. 0,04 b.d. 0,22 0,11 0,05 b.d. b.d. b.d. 53,10 0,16 b.d. 99,65 BA27_EMP_PY_11_5 II 46,05 0,10 b.d. b.d. b.d. 0,55 b.d. b.d. b.d. b.d. b.d. 53,18 b.d. b.d. 99,88 BA27_EMP_PY_12_1 II 45,91 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,92 b.d. b.d. 99,83 BA27_EMP_PY_12_2 II 45,86 0,07 b.d. b.d. b.d. 2,33 b.d. b.d. b.d. b.d. b.d. 52,44 b.d. b.d. 100,70 BA27_EMP_PY_12_3 II 46,43 b.d. 0,07 b.d. b.d. 0,75 b.d. b.d. b.d. 0,02 b.d. 53,55 b.d. b.d. 100,82 BA27_EMP_PY_12_4 II 45,91 0,07 b.d. b.d. b.d. 1,80 b.d. b.d. b.d. b.d. b.d. 52,68 b.d. b.d. 100,46 BA27_EMP_PY_12_5 II 46,42 b.d. b.d. b.d. b.d. 0,11 b.d. b.d. b.d. b.d. b.d. 53,44 b.d. b.d. 99,97 BA27_EMP_PY_07_1 II 46,50 0,13 b.d. b.d. b.d. 0,36 b.d. b.d. b.d. b.d. b.d. 53,16 b.d. b.d. 100,15 BA27_EMP_PY_11_1 II 45,85 0,83 b.d. b.d. b.d. 0,63 b.d. b.d. b.d. 0,02 b.d. 52,50 b.d. b.d. 99,83 BA30_EMP_PY_01_1 II 46,42 0,08 b.d. b.d. b.d. 0,40 b.d. b.d. b.d. b.d. b.d. 53,01 b.d. b.d. 99,91 BA30_EMP_PY_01_2 II 46,57 0,08 b.d. b.d. b.d. 0,29 b.d. b.d. b.d. b.d. b.d. 53,13 b.d. b.d. 100,07 BA30_EMP_PY_01_3 II 46,14 0,09 b.d. b.d. b.d. 0,03 b.d. b.d. b.d. b.d. b.d. 52,86 b.d. b.d. 99,12 BA30_EMP_PY_01_4 II 46,55 0,07 b.d. b.d. b.d. 0,15 b.d. 0,03 b.d. b.d. b.d. 53,12 b.d. b.d. 99,92 BA30_EMP_PY_01_5 II 46,57 0,09 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,45 b.d. b.d. 100,11 BA30_EMP_PY_02_1 II 46,47 0,10 b.d. b.d. b.d. 0,16 b.d. b.d. b.d. b.d. b.d. 52,74 b.d. b.d. 99,47 BA30_EMP_PY_02_2 II 46,51 0,10 b.d. b.d. b.d. 0,02 b.d. b.d. b.d. b.d. b.d. 53,35 b.d. b.d. 99,98 BA30_EMP_PY_02_3 II 46,54 b.d. b.d. b.d. b.d. 0,07 b.d. b.d. b.d. b.d. b.d. 53,10 b.d. b.d. 99,71 BA30_EMP_PY_02_4 II 46,54 0,06 b.d. b.d. b.d. 0,22 b.d. b.d. b.d. 0,02 b.d. 53,17 b.d. b.d. 100,01 BA30_EMP_PY_02_5 II 46,55 0,11 b.d. b.d. b.d. 0,02 b.d. b.d. b.d. b.d. b.d. 52,67 b.d. b.d. 99,35 BA30_EMP_PY_03_1 II 46,88 0,06 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,11 b.d. b.d. 100,05 BA30_EMP_PY_03_2 II 46,56 0,06 b.d. b.d. b.d. 0,11 0,02 b.d. b.d. b.d. b.d. 53,20 b.d. b.d. 99,95 BA30_EMP_PY_03_3 II 46,78 0,09 b.d. b.d. b.d. 0,08 b.d. b.d. b.d. b.d. b.d. 53,34 b.d. b.d. 100,29 BA30_EMP_PY_03_4 II 46,52 0,07 b.d. b.d. b.d. 0,07 b.d. b.d. b.d. b.d. b.d. 53,08 b.d. b.d. 99,74 BA30_EMP_PY_03_5 II 46,54 0,08 b.d. b.d. b.d. 0,07 b.d. b.d. b.d. b.d. b.d. 53,15 b.d. b.d. 99,84 BA21_EMP_PY_01A_1 II 46,53 0,57 b.d. 0,06 b.d. 0,49 b.d. b.d. b.d. b.d. b.d. 52,92 b.d. b.d. 100,57 BA21_EMP_PY_01A_2 II 46,92 b.d. b.d. b.d. b.d. 0,20 b.d. b.d. b.d. b.d. b.d. 53,36 b.d. b.d. 100,48 BA21_EMP_PY_01A_3 II 45,25 0,19 b.d. 0,07 0,28 2,61 0,08 0,80 b.d. 0,02 b.d. 50,79 0,32 b.d. 100,41 BA21_EMP_PY_01A_4 II 45,96 0,80 b.d. 0,05 0,05 0,32 b.d. b.d. b.d. b.d. b.d. 53,29 b.d. b.d. 100,47 BA21_EMP_PY_01A_5 II 46,79 0,06 b.d. b.d. b.d. 0,89 b.d. b.d. b.d. b.d. b.d. 52,67 b.d. b.d. 100,41 BA21_EMP_PY_01A_6 II 46,93 0,06 b.d. b.d. b.d. 0,06 b.d. b.d. b.d. b.d. b.d. 53,66 b.d. b.d. 100,71 BA21_EMP_PY_01A_7 II 46,51 0,26 b.d. b.d. b.d. 0,78 b.d. b.d. b.d. b.d. b.d. 52,67 b.d. b.d. 100,22 BA21_EMP_PY_01B_1 II 46,73 b.d. 0,06 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,25 b.d. b.d. 100,04 BA21_EMP_PY_01B_2 II 46,68 0,08 b.d. 0,04 0,04 0,51 b.d. b.d. b.d. b.d. b.d. 53,34 b.d. b.d. 100,69 BA21_EMP_PY_01B_3 II 46,47 0,26 0,07 b.d. b.d. 0,12 b.d. b.d. b.d. b.d. b.d. 53,27 b.d. b.d. 100,19 BA21_EMP_PY_01B_4 II 46,54 0,30 b.d. b.d. 0,04 0,30 0,02 b.d. b.d. b.d. b.d. 53,21 b.d. b.d. 100,41 BA21_EMP_PY_01B_5 II 46,77 0,13 b.d. b.d. 0,06 0,05 b.d. b.d. b.d. b.d. b.d. 53,32 b.d. b.d. 100,33 BA21_EMP_PY_03_1 II 46,46 0,31 b.d. b.d. b.d. 0,50 b.d. b.d. b.d. b.d. b.d. 53,18 b.d. b.d. 100,45 BA21_EMP_PY_03_2 II 45,92 0,45 b.d. b.d. b.d. 1,80 b.d. 0,03 b.d. b.d. b.d. 52,28 b.d. b.d. 100,48 BA21_EMP_PY_03_3 II 46,50 0,13 b.d. b.d. b.d. 0,66 b.d. b.d. b.d. 0,01 b.d. 52,95 b.d. b.d. 100,25 BA21_EMP_PY_03_4 II 46,48 0,12 b.d. b.d. b.d. 0,16 b.d. b.d. b.d. 0,02 b.d. 53,26 b.d. b.d. 100,04 BA21_EMP_PY_03_5 II 46,70 0,09 b.d. b.d. b.d. 0,36 b.d. b.d. b.d. b.d. b.d. 53,19 b.d. b.d. 100,34 BA21_EMP_PY_03_6 II 46,75 b.d. b.d. b.d. b.d. 0,02 b.d. b.d. b.d. b.d. b.d. 53,65 b.d. b.d. 100,42 BA21_EMP_PY_04_1 II 46,89 b.d. b.d. b.d. b.d. 0,14 b.d. b.d. b.d. b.d. b.d. 53,27 b.d. b.d. 100,30 BA21_EMP_PY_04_2 II 46,97 b.d. b.d. b.d. b.d. 0,10 b.d. b.d. b.d. b.d. b.d. 53,37 b.d. b.d. 100,44 BA21_EMP_PY_04_3 II 46,76 b.d. b.d. b.d. b.d. 0,02 b.d. b.d. b.d. b.d. b.d. 53,31 b.d. b.d. 100,09 BA21_EMP_PY_04_4 II 46,94 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,26 b.d. b.d. 100,20 BA21_EMP_PY_04_5 II 46,76 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,46 b.d. b.d. 100,22 BA21_EMP_PY_05_1 II 46,95 b.d. b.d. b.d. b.d. 0,03 b.d. b.d. b.d. b.d. b.d. 53,74 b.d. b.d. 100,72 BA21_EMP_PY_05_2 II 46,35 0,41 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,57 b.d. b.d. 100,33 BA21_EMP_PY_05_3 II 46,43 0,55 b.d. b.d. b.d. 0,02 b.d. b.d. b.d. b.d. b.d. 53,47 b.d. b.d. 100,47 BA21_EMP_PY_05_4 II 46,74 0,14 b.d. b.d. b.d. 0,13 b.d. b.d. b.d. b.d. b.d. 53,71 b.d. b.d. 100,72 BA21_EMP_PY_05_5 II 46,56 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,70 b.d. b.d. 100,26 BA21_EMP_PY_05_6 II 46,21 0,15 0,06 b.d. b.d. 0,17 b.d. b.d. 0,07 b.d. b.d. 53,66 b.d. b.d. 100,32 BA21_EMP_PY_06_1 II 46,66 0,07 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,56 b.d. b.d. 100,29 BA21_EMP_PY_06_2 II 46,40 0,28 b.d. b.d. b.d. 0,70 b.d. b.d. b.d. b.d. b.d. 52,99 b.d. b.d. 100,37 BA21_EMP_PY_06_3 II 46,79 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,43 b.d. b.d. 100,22 BA21_EMP_PY_06_4 II 46,76 b.d. b.d. b.d. b.d. 0,07 b.d. b.d. b.d. b.d. b.d. 53,41 b.d. b.d. 100,24 BA21_EMP_PY_06_5 II 46,79 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,03 b.d. b.d. 99,82 BA21_EMP_PY_06_6 II 46,84 0,05 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,53 b.d. b.d. 100,42 BA21_EMP_PY_06_7 II 46,91 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,46 b.d. b.d. 100,37 BA21_EMP_PY_07_1 II 46,32 0,47 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,83 b.d. b.d. 100,62 BA21_EMP_PY_07_2 II 46,96 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,46 b.d. b.d. 100,42 BA21_EMP_PY_07_3 II 46,80 b.d. b.d. b.d. b.d. 0,04 b.d. b.d. b.d. b.d. b.d. 53,48 b.d. b.d. 100,32 BA21_EMP_PY_07_4 II 46,90 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,51 b.d. b.d. 100,41 BA21_EMP_PY_07_5 II 46,50 0,11 b.d. b.d. b.d. 0,19 b.d. b.d. b.d. b.d. b.d. 53,42 b.d. b.d. 100,22 BA21_EMP_PY_07_6 II 46,62 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,47 b.d. b.d. 100,09 BA21_EMP_PY_21_1 II 46,62 0,06 b.d. b.d. b.d. 0,20 b.d. b.d. b.d. b.d. b.d. 53,27 b.d. b.d. 100,15 BA21_EMP_PY_21_2 II 46,59 0,29 b.d. b.d. b.d. 0,32 b.d. b.d. b.d. b.d. b.d. 53,21 b.d. b.d. 100,41 BA21_EMP_PY_21_3 II 46,89 b.d. b.d. b.d. b.d. 0,03 b.d. b.d. b.d. b.d. b.d. 53,20 b.d. b.d. 100,12 BA21_EMP_PY_21_4 II 46,88 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,17 b.d. b.d. 100,05 BA21_EMP_PY_21_5 II 46,76 b.d. b.d. b.d. b.d. 0,09 b.d. b.d. b.d. b.d. b.d. 53,44 b.d. b.d. 100,29 BA21_EMP_PY_21_6 II 46,71 0,09 b.d. b.d. b.d. 0,25 b.d. b.d. b.d. b.d. b.d. 53,14 b.d. b.d. 100,19 BA21_EMP_PY_08_1 II 46,86 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,60 b.d. b.d. 100,46 BA21_EMP_PY_08_2 II 46,87 0,05 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,52 b.d. b.d. 100,44 BA21_EMP_PY_08_3 II 46,50 0,10 b.d. 0,11 b.d. 0,14 b.d. b.d. b.d. b.d. b.d. 52,95 b.d. b.d. 99,80 BA21_EMP_PY_08_4 II 46,56 0,22 b.d. b.d. b.d. 0,85 b.d. b.d. b.d. b.d. b.d. 52,81 b.d. 0,04 100,48 BA21_EMP_PY_08_5 II 45,89 0,22 b.d. b.d. b.d. 0,52 b.d. 0,19 b.d. b.d. b.d. 52,29 b.d. b.d. 99,11 BA21_EMP_PY_08_6 II 46,41 b.d. b.d. 0,05 0,07 0,07 b.d. b.d. b.d. b.d. b.d. 53,66 b.d. b.d. 100,26 BA21_EMP_PY_09_1 II 46,75 b.d. b.d. 0,07 b.d. 0,07 b.d. b.d. b.d. b.d. b.d. 53,38 b.d. b.d. 100,27 BA21_EMP_PY_09_2 II 46,25 0,11 b.d. b.d. b.d. 1,73 b.d. b.d. b.d. b.d. b.d. 52,09 b.d. b.d. 100,18 BA21_EMP_PY_09_3 II 45,89 0,55 b.d. b.d. b.d. 0,71 b.d. b.d. b.d. b.d. b.d. 52,83 b.d. b.d. 99,98 BA21_EMP_PY_09_4 II 46,01 0,56 b.d. b.d. b.d. 0,80 b.d. b.d. b.d. b.d. b.d. 52,66 b.d. b.d. 100,03 BA21_EMP_PY_09_5 II 46,55 0,14 b.d. 0,16 0,03 0,10 b.d. b.d. b.d. b.d. b.d. 53,19 b.d. b.d. 100,17 BA21_EMP_PY_09_6 II 45,75 0,73 b.d. 0,05 b.d. 1,13 0,08 0,04 b.d. b.d. b.d. 52,66 b.d. b.d. 100,44 BA21_EMP_PY_09_7 II 46,70 0,11 b.d. b.d. b.d. 0,28 b.d. b.d. b.d. b.d. b.d. 53,07 b.d. b.d. 100,16 BA21_EMP_PY_10A_1 II 46,80 b.d. b.d. b.d. b.d. 0,03 b.d. b.d. b.d. b.d. b.d. 53,44 b.d. b.d. 100,27 BA21_EMP_PY_10A_2 II 46,20 0,30 b.d. b.d. b.d. 0,97 b.d. b.d. b.d. 0,02 b.d. 52,72 b.d. b.d. 100,21 73

Fe Cu Zn Ni Co As Sb Ag Au Se Bi S Pb Te TOTAL ID análisis Grupo [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] BA21_EMP_PY_10A_3 II 46,02 0,08 b.d. 0,05 b.d. 1,38 b.d. b.d. b.d. b.d. b.d. 52,07 b.d. b.d. 99,60 BA21_EMP_PY_10A_4 II 46,78 0,08 b.d. b.d. b.d. 0,10 b.d. b.d. b.d. b.d. b.d. 53,27 b.d. b.d. 100,23 BA21_EMP_PY_10A_6 II 45,13 0,06 b.d. b.d. b.d. 4,50 0,18 0,03 b.d. 0,05 b.d. 50,35 b.d. b.d. 100,30 BA21_EMP_PY_10B_1 II 46,79 b.d. b.d. 0,05 b.d. 0,06 b.d. b.d. b.d. b.d. b.d. 53,69 b.d. b.d. 100,59 BA21_EMP_PY_10B_2 II 46,72 b.d. b.d. b.d. b.d. 0,08 b.d. b.d. b.d. b.d. b.d. 53,43 b.d. b.d. 100,23 BA21_EMP_PY_10B_3 II 46,88 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,18 b.d. b.d. 100,06 BA21_EMP_PY_10B_4 II 46,90 b.d. b.d. b.d. b.d. 0,08 b.d. b.d. b.d. b.d. b.d. 53,52 b.d. b.d. 100,50 BA21_EMP_PY_10B_5 II 46,34 0,51 b.d. b.d. b.d. 0,06 b.d. b.d. b.d. b.d. b.d. 53,29 b.d. b.d. 100,20 BA21_EMP_PY_10B_6 II 46,86 0,08 b.d. b.d. b.d. 0,31 b.d. b.d. b.d. b.d. b.d. 53,32 b.d. b.d. 100,57 BA21_EMP_PY_11_1 II 46,67 0,07 b.d. b.d. b.d. 0,06 b.d. b.d. b.d. b.d. b.d. 53,64 b.d. b.d. 100,44 BA21_EMP_PY_11_2 II 46,69 0,05 b.d. b.d. b.d. 0,02 b.d. b.d. b.d. b.d. b.d. 53,39 b.d. b.d. 100,15 BA21_EMP_PY_11_3 II 46,73 b.d. b.d. b.d. b.d. 0,07 b.d. b.d. b.d. b.d. b.d. 53,52 b.d. b.d. 100,32 BA21_EMP_PY_11_4 II 46,17 0,47 b.d. b.d. b.d. 0,09 b.d. b.d. b.d. b.d. b.d. 53,24 b.d. b.d. 99,97 BA21_EMP_PY_11_5 II 44,15 1,08 b.d. b.d. 0,05 3,26 0,21 0,17 b.d. 0,08 b.d. 50,67 0,43 b.d. 100,10 BA21_EMP_PY_11_6 II 46,66 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,27 b.d. b.d. 99,93 BA21_EMP_PY_12_2 II 46,63 0,08 b.d. b.d. b.d. 0,39 b.d. b.d. b.d. b.d. b.d. 53,23 b.d. b.d. 100,33 BA21_EMP_PY_12_3 II 46,80 b.d. b.d. b.d. b.d. 0,05 b.d. b.d. b.d. b.d. b.d. 53,93 b.d. b.d. 100,78 BA21_EMP_PY_12_4 II 46,73 b.d. b.d. b.d. b.d. 0,22 b.d. b.d. b.d. b.d. b.d. 53,92 b.d. b.d. 100,87 BA21_EMP_PY_12_5 II 46,78 b.d. b.d. b.d. b.d. 0,16 b.d. b.d. b.d. 0,02 b.d. 53,80 b.d. b.d. 100,76 BA21_EMP_PY_14_1 II 47,07 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,41 b.d. b.d. 100,48 BA21_EMP_PY_14_2 II 45,65 b.d. b.d. b.d. b.d. 3,51 0,04 0,04 b.d. b.d. b.d. 50,99 b.d. b.d. 100,23 BA21_EMP_PY_14_3 II 45,02 b.d. b.d. b.d. b.d. 4,59 0,11 b.d. b.d. b.d. b.d. 50,13 b.d. b.d. 99,85 BA21_EMP_PY_14_4 II 46,80 0,11 b.d. b.d. b.d. 0,26 b.d. b.d. b.d. b.d. b.d. 53,06 b.d. b.d. 100,23 BA21_EMP_PY_14_5 II 45,90 b.d. b.d. b.d. b.d. 2,45 b.d. b.d. b.d. 0,02 b.d. 51,74 b.d. b.d. 100,11 BA21_EMP_PY_15_1 II 46,72 b.d. b.d. b.d. b.d. 0,25 b.d. 0,05 b.d. b.d. b.d. 53,20 b.d. b.d. 100,22 BA21_EMP_PY_15_2 II 46,60 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,29 b.d. b.d. 99,89 BA21_EMP_PY_15_3 II 45,89 0,06 b.d. b.d. b.d. 1,53 0,09 0,04 b.d. b.d. b.d. 52,26 b.d. b.d. 99,87 BA21_EMP_PY_15_4 II 46,54 b.d. b.d. b.d. b.d. 0,16 b.d. b.d. b.d. b.d. b.d. 53,45 b.d. b.d. 100,15 BA21_EMP_PY_15_5 II 46,44 0,08 b.d. b.d. b.d. 0,12 b.d. b.d. b.d. b.d. b.d. 53,34 b.d. b.d. 99,98 BA21_EMP_PY_15_6 II 46,72 b.d. b.d. b.d. b.d. 0,16 b.d. b.d. b.d. b.d. b.d. 53,38 b.d. b.d. 100,26 BA33_EMP_PY_04_1 I 46,39 b.d. b.d. b.d. b.d. 0,09 b.d. b.d. b.d. b.d. b.d. 53,41 b.d. b.d. 99,89 BA33_EMP_PY_04_2 I 46,61 b.d. b.d. b.d. b.d. 0,05 b.d. b.d. b.d. b.d. b.d. 53,54 b.d. b.d. 100,20 BA33_EMP_PY_04_3 I 46,54 0,19 b.d. b.d. b.d. 0,64 b.d. 0,02 b.d. b.d. b.d. 53,02 b.d. b.d. 100,41 BA33_EMP_PY_04_4 I 46,26 0,12 b.d. b.d. b.d. 1,19 b.d. b.d. b.d. b.d. b.d. 52,83 b.d. b.d. 100,40 BA33_EMP_PY_04_5 I 46,46 0,09 b.d. b.d. b.d. 0,20 b.d. 0,03 b.d. b.d. b.d. 53,37 b.d. b.d. 100,15 BA33_EMP_PY_04_6 I 46,70 b.d. 0,08 b.d. b.d. 0,17 b.d. b.d. b.d. b.d. b.d. 53,24 b.d. b.d. 100,19 BA33_EMP_PY_06_1 I 46,78 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,51 b.d. b.d. 100,29 BA33_EMP_PY_06_2 I 46,81 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,68 b.d. b.d. 100,49 BA33_EMP_PY_06_3 I 46,69 0,07 b.d. b.d. b.d. 0,77 b.d. b.d. b.d. b.d. b.d. 52,97 b.d. b.d. 100,50 BA33_EMP_PY_06_4 I 46,67 0,11 b.d. b.d. b.d. 0,32 b.d. b.d. b.d. b.d. b.d. 53,10 b.d. 0,05 100,25 BA33_EMP_PY_06_5 I 46,32 0,16 b.d. b.d. b.d. 0,76 b.d. b.d. b.d. b.d. b.d. 52,84 b.d. b.d. 100,08 BA33_EMP_PY_06_6 I 46,46 0,20 b.d. b.d. b.d. 0,08 b.d. 0,42 b.d. 0,02 b.d. 53,17 b.d. b.d. 100,35 BA33_EMP_PY_07_1 I 46,75 b.d. b.d. b.d. b.d. 0,03 b.d. b.d. b.d. b.d. b.d. 53,22 b.d. b.d. 100,00 BA33_EMP_PY_07_2 I 46,33 b.d. b.d. b.d. b.d. 0,93 b.d. b.d. b.d. b.d. b.d. 52,70 b.d. b.d. 99,96 BA33_EMP_PY_07_3 I 46,24 b.d. b.d. b.d. b.d. 1,67 b.d. b.d. b.d. b.d. b.d. 52,02 b.d. 0,04 99,97 BA33_EMP_PY_07_4 I 46,61 b.d. b.d. b.d. b.d. 0,30 b.d. b.d. b.d. b.d. b.d. 53,01 b.d. b.d. 99,92 BA33_EMP_PY_07_5 I 46,47 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 52,98 b.d. b.d. 99,45 BA33_EMP_PY_07_6 I 46,62 b.d. b.d. b.d. b.d. 0,04 b.d. b.d. b.d. b.d. b.d. 53,17 b.d. b.d. 99,83 BA33_EMP_PY_08_1 I 46,57 0,05 0,07 b.d. b.d. 0,05 b.d. b.d. b.d. b.d. b.d. 53,19 b.d. b.d. 99,93 BA33_EMP_PY_08_2 I 46,52 b.d. b.d. b.d. b.d. 0,04 b.d. b.d. b.d. b.d. b.d. 53,40 b.d. b.d. 99,96 BA33_EMP_PY_08_3 I 46,52 b.d. b.d. b.d. b.d. 0,03 b.d. b.d. b.d. b.d. b.d. 53,20 b.d. b.d. 99,75 BA33_EMP_PY_08_4 I 46,66 b.d. b.d. b.d. b.d. 0,02 b.d. b.d. b.d. b.d. b.d. 53,52 b.d. b.d. 100,20 BA33_EMP_PY_08_5 I 46,55 0,11 b.d. b.d. b.d. 0,10 b.d. b.d. b.d. b.d. b.d. 53,37 b.d. b.d. 100,13 BA33_EMP_PY_08_6 I 46,15 0,19 b.d. b.d. b.d. 1,23 b.d. b.d. b.d. b.d. b.d. 52,54 b.d. b.d. 100,11 BA33_EMP_PY_08_7 I 46,42 b.d. b.d. b.d. b.d. 0,02 b.d. b.d. b.d. b.d. b.d. 53,32 b.d. b.d. 99,76 BA33_EMP_PY_10_1 I 46,70 0,05 b.d. b.d. b.d. 0,23 b.d. b.d. b.d. b.d. b.d. 53,10 b.d. b.d. 100,08 BA33_EMP_PY_10_2 I 46,49 b.d. b.d. b.d. b.d. 0,02 b.d. 0,03 b.d. b.d. b.d. 53,22 b.d. b.d. 99,76 BA33_EMP_PY_10_3 I 46,61 b.d. b.d. b.d. b.d. 0,06 b.d. 0,34 b.d. b.d. b.d. 53,19 b.d. b.d. 100,20 BA33_EMP_PY_10_4 I 46,90 0,05 b.d. b.d. b.d. 0,15 b.d. b.d. b.d. b.d. b.d. 53,22 b.d. b.d. 100,32 BA33_EMP_PY_10_5 I 46,75 b.d. b.d. b.d. b.d. 0,04 b.d. 0,02 0,06 b.d. b.d. 53,20 b.d. b.d. 100,07 BA33_EMP_PY_12_1 I 46,77 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,49 b.d. b.d. 100,26 BA33_EMP_PY_12_2 I 46,91 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,44 b.d. b.d. 100,35 BA33_EMP_PY_12_3 I 46,63 0,05 b.d. b.d. b.d. 0,13 b.d. b.d. b.d. b.d. b.d. 53,37 b.d. b.d. 100,18 BA33_EMP_PY_12_4 I 46,38 b.d. b.d. b.d. b.d. 1,14 b.d. b.d. b.d. b.d. b.d. 52,48 b.d. b.d. 100,00 BA33_EMP_PY_12_5 I 46,71 b.d. b.d. b.d. b.d. 0,08 b.d. b.d. b.d. b.d. b.d. 53,42 b.d. b.d. 100,21 BA33_EMP_PY_18_1 I 46,31 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,16 b.d. b.d. 99,47 BA33_EMP_PY_18_2 I 46,31 b.d. b.d. b.d. b.d. 0,34 b.d. b.d. b.d. b.d. b.d. 52,90 b.d. b.d. 99,55 BA33_EMP_PY_18_3 I 46,44 b.d. b.d. b.d. b.d. 0,47 b.d. b.d. b.d. 0,02 b.d. 52,84 b.d. b.d. 99,77 BA33_EMP_PY_18_4 I 46,52 b.d. b.d. b.d. b.d. 0,06 b.d. b.d. b.d. b.d. b.d. 53,24 b.d. b.d. 99,82 BA33_EMP_PY_18_5 I 46,26 0,07 b.d. b.d. b.d. 0,31 b.d. b.d. b.d. b.d. b.d. 52,76 b.d. b.d. 99,40 BA34_EMP_PY_01_1 II 46,62 0,26 b.d. b.d. b.d. 0,32 b.d. b.d. b.d. b.d. b.d. 53,17 b.d. b.d. 100,37 BA34_EMP_PY_01_2 II 46,51 0,11 b.d. b.d. b.d. 0,02 b.d. b.d. b.d. b.d. b.d. 53,22 b.d. b.d. 99,86 BA34_EMP_PY_01_3 II 46,38 0,10 b.d. b.d. 0,16 b.d. b.d. b.d. b.d. b.d. b.d. 53,17 b.d. b.d. 99,81 BA34_EMP_PY_01_4 II 45,75 1,62 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 52,90 b.d. b.d. 100,27 BA34_EMP_PY_01_5 II 46,43 0,08 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,02 b.d. 53,17 b.d. b.d. 99,70 BA34_EMP_PY_02_1 II 46,55 0,05 b.d. b.d. b.d. 0,06 b.d. b.d. b.d. b.d. b.d. 53,05 b.d. b.d. 99,71 BA34_EMP_PY_02_2 II 46,63 b.d. b.d. b.d. b.d. 0,04 b.d. b.d. b.d. b.d. b.d. 52,99 b.d. b.d. 99,66 BA34_EMP_PY_02_3 II 46,71 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 53,11 b.d. b.d. 99,82 BA34_EMP_PY_02_4 II 46,44 0,12 b.d. b.d. b.d. 0,17 b.d. b.d. b.d. b.d. b.d. 52,86 b.d. b.d. 99,59 BA34_EMP_PY_02_5 II 46,03 1,10 b.d. b.d. b.d. 0,03 b.d. b.d. b.d. b.d. b.d. 52,32 b.d. b.d. 99,48 BA31_03_EMP_PY_01 II 46,74 0,05 b.d. b.d. b.d. 0,53 b.d. b.d. b.d. b.d. b.d. 52,80 b.d. b.d. 100,12 BA31_03_EMP_PY_02 II 46,60 0,07 b.d. b.d. b.d. 0,29 b.d. b.d. b.d. b.d. b.d. 53,26 b.d. b.d. 100,22 BA31_03_EMP_PY_03 II 46,70 0,05 b.d. b.d. b.d. 0,61 b.d. b.d. b.d. b.d. b.d. 52,68 b.d. b.d. 100,04 BA31_03_EMP_PY_04 II 46,55 0,05 b.d. b.d. b.d. 0,55 b.d. b.d. b.d. b.d. b.d. 53,07 b.d. b.d. 100,22 BA31_03_EMP_PY_05 II 46,20 0,10 b.d. b.d. b.d. 1,07 0,02 b.d. b.d. 0,02 b.d. 52,56 b.d. b.d. 99,97 BA31_03_EMP_PY_06 II 46,48 b.d. b.d. b.d. 0,05 0,51 b.d. b.d. b.d. b.d. b.d. 52,95 b.d. b.d. 99,99 BA31_03_EMP_PY_07 II 46,57 b.d. b.d. b.d. 0,04 0,67 b.d. b.d. b.d. b.d. b.d. 52,80 b.d. b.d. 100,08 BA31_03_EMP_PY_08 II 46,62 b.d. b.d. b.d. b.d. 0,09 b.d. b.d. b.d. b.d. b.d. 53,21 b.d. b.d. 99,92 74

Fe Cu Zn Ni Co As Sb Ag Au Se Bi S Pb Te TOTAL ID análisis Grupo [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] BA31_05_EMP_PY_01 II 46,69 b.d. b.d. b.d. b.d. 0,66 b.d. b.d. b.d. 0,02 b.d. 53,25 b.d. b.d. 100,62 BA31_05_EMP_PY_02 II 46,72 0,10 b.d. b.d. b.d. 0,50 b.d. b.d. 0,05 b.d. b.d. 52,99 b.d. b.d. 100,36 BA31_05_EMP_PY_03 II 46,17 0,19 b.d. b.d. b.d. 0,74 b.d. b.d. b.d. b.d. b.d. 52,70 b.d. b.d. 99,80 BA31_05_EMP_PY_04 II 46,48 0,05 b.d. b.d. 0,04 0,39 b.d. b.d. b.d. b.d. b.d. 52,95 b.d. b.d. 99,91 BA31_05_EMP_PY_05 II 46,19 0,10 b.d. b.d. b.d. 0,79 b.d. b.d. b.d. b.d. b.d. 52,97 b.d. b.d. 100,05 BA31_05_EMP_PY_06 II 46,66 b.d. b.d. b.d. b.d. 0,05 b.d. b.d. b.d. b.d. b.d. 53,32 b.d. b.d. 100,03 BA31_05_EMP_PY_07 II 46,63 b.d. b.d. b.d. b.d. 0,03 b.d. b.d. 0,05 b.d. b.d. 53,52 b.d. b.d. 100,23

Fe Cu Zn Ni Co As Sb Ag Au Se Bi S Pb Te Detection Limit [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] Minimum Detection Limit 0,042 0,045 0,059 0,031 0,031 0,008 0,018 0,016 0,042 0,013 - 0,033 0,100 0,023 Maximum Detection Limit 0,044 0,049 0,065 0,037 0,041 0,025 0,027 0,030 0,051 0,023 - 0,050 0,103 0,045 Mean Detection Limit 0,043 0,046 0,061 0,035 0,034 0,016 0,019 0,022 0,047 0,015 - 0,048 0,101 0,041 Median Detection Limit 0,043 0,046 0,061 0,035 0,034 0,015 0,019 0,021 0,047 0,014 - 0,049 0,102 0,043

Fe Cu Zn Ni Co As Sb Ag Au Se Bi S Pb Te Standard Deviation [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] Minimum Standard Deviation 0,406 0,065 0,086 0,050 0,046 0,022 0,026 0,030 0,067 0,020 - 0,425 0,151 0,033 Maximum Standard Deviation 0,625 0,106 0,087 0,059 0,055 0,127 0,032 0,080 0,070 0,034 - 0,909 0,158 0,062 Mean Standard Deviation 0,605 0,071 0,086 0,052 0,050 0,033 0,028 0,035 0,068 0,022 - 0,857 0,154 0,055 Median Standard Deviation 0,619 0,069 0,087 0,051 0,049 0,027 0,028 0,031 0,068 0,020 - 0,896 0,155 0,062

75

ANEXO D: Resultados de análisis EMPA en calcopirita del Sistema Geotermal Cerro Pabellón

(b.d.: bajo el límite de detección)

Fe Cu Zn Ni Co As Sb Ag Au Se Bi S Pb Te TOTAL ID análisis [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] BA20_CP_07_1 30,48 33,80 b.d. b.d. b.d. b.d. b.d. 0,20 b.d. b.d. b.d. 34,46 b.d. b.d. 98,94 BA20_CP_07_2 30,77 33,88 b.d. b.d. b.d. b.d. b.d. 0,21 b.d. b.d. b.d. 34,87 b.d. b.d. 99,73 BA20_CP_07_3 30,74 33,92 b.d. b.d. b.d. b.d. b.d. 0,24 b.d. b.d. b.d. 34,80 b.d. b.d. 99,70 BA20_CP_07_4 30,85 34,05 b.d. 0,04 b.d. b.d. b.d. 0,24 b.d. b.d. b.d. 34,55 b.d. b.d. 99,73 BA20_CP_07_5 30,30 33,55 b.d. b.d. b.d. b.d. b.d. 0,24 b.d. b.d. b.d. 35,14 b.d. b.d. 99,23 BA20_CP_08_1 30,96 33,94 b.d. b.d. b.d. b.d. b.d. 0,28 b.d. b.d. b.d. 34,92 b.d. b.d. 100,10 BA20_CP_08_2 30,72 34,07 b.d. b.d. b.d. b.d. b.d. 0,27 b.d. b.d. b.d. 35,00 b.d. b.d. 100,06 BA20_CP_08_3 30,82 33,96 b.d. b.d. b.d. b.d. b.d. 0,27 b.d. b.d. b.d. 34,77 b.d. b.d. 99,82 BA20_CP_08_4 30,83 34,05 b.d. b.d. b.d. b.d. b.d. 0,28 b.d. b.d. b.d. 35,04 b.d. b.d. 100,20 BA20_CP_08_5 30,71 33,87 b.d. b.d. b.d. b.d. b.d. 0,28 b.d. b.d. b.d. 34,60 b.d. b.d. 99,46 BA20_CP_09_1 30,72 33,94 b.d. b.d. b.d. b.d. b.d. 0,20 b.d. b.d. b.d. 34,73 b.d. b.d. 99,59 BA20_CP_09_2 30,79 33,87 b.d. b.d. b.d. b.d. b.d. 0,21 b.d. b.d. b.d. 34,55 b.d. b.d. 99,42 BA20_CP_09_3 30,81 33,92 b.d. b.d. b.d. b.d. b.d. 0,22 b.d. b.d. b.d. 34,83 b.d. b.d. 99,78 BA20_CP_09_4 30,69 33,91 b.d. b.d. b.d. b.d. b.d. 0,23 b.d. b.d. b.d. 34,75 b.d. b.d. 99,58 BA20_CP_09_5 30,90 33,87 b.d. b.d. b.d. b.d. b.d. 0,21 b.d. b.d. b.d. 34,43 b.d. b.d. 99,41 BA20_CP_13_1 30,76 34,04 b.d. b.d. b.d. b.d. b.d. 0,29 b.d. b.d. b.d. 34,50 b.d. b.d. 99,59 BA20_CP_13_2 30,78 34,21 b.d. b.d. b.d. b.d. 0,02 0,25 b.d. b.d. b.d. 34,42 b.d. b.d. 99,68 BA20_CP_13_3 30,68 33,94 b.d. b.d. b.d. b.d. b.d. 0,25 b.d. b.d. b.d. 34,74 b.d. b.d. 99,61 BA20_CP_13_4 30,58 33,98 b.d. b.d. b.d. b.d. b.d. 0,27 b.d. b.d. b.d. 34,81 b.d. b.d. 99,64 BA20_CP_13_5 30,64 33,84 b.d. b.d. b.d. b.d. b.d. 0,25 b.d. b.d. b.d. 34,81 b.d. b.d. 99,54 BA20_CP_15_1 30,89 34,11 b.d. b.d. b.d. b.d. b.d. 0,29 b.d. b.d. b.d. 34,51 b.d. 0,04 99,84 BA20_CP_15_2 30,76 33,92 b.d. b.d. b.d. b.d. b.d. 0,28 b.d. b.d. b.d. 34,85 b.d. b.d. 99,81 BA20_CP_15_3 30,41 33,71 b.d. b.d. b.d. b.d. b.d. 0,29 b.d. b.d. b.d. 34,16 b.d. b.d. 98,57 BA20_CP_15_4 30,88 33,89 b.d. b.d. b.d. b.d. b.d. 0,31 b.d. b.d. b.d. 34,81 b.d. b.d. 99,89 BA20_CP_15_5 30,75 33,66 b.d. b.d. b.d. b.d. b.d. 0,26 b.d. b.d. b.d. 34,86 b.d. b.d. 99,53 BA20_CP_15_6 30,82 33,89 b.d. b.d. b.d. b.d. b.d. 0,23 b.d. b.d. b.d. 34,82 b.d. 0,06 99,82 BA20_CP_16_1 30,76 33,90 b.d. b.d. b.d. b.d. b.d. 0,26 b.d. b.d. b.d. 34,40 b.d. b.d. 99,32 BA20_CP_16_2 30,77 33,81 b.d. b.d. b.d. b.d. b.d. 0,26 b.d. b.d. b.d. 34,92 b.d. b.d. 99,76 BA20_CP_16_3 30,85 33,97 b.d. b.d. b.d. b.d. b.d. 0,29 b.d. b.d. b.d. 34,62 b.d. b.d. 99,73 BA20_CP_16_4 30,87 34,10 b.d. b.d. b.d. b.d. b.d. 0,29 b.d. b.d. b.d. 34,60 b.d. b.d. 99,86 BA20_CP_16_5 30,77 33,97 b.d. b.d. b.d. b.d. b.d. 0,30 b.d. b.d. b.d. 34,69 b.d. b.d. 99,73 BA30_CP_04_1 30,84 33,85 b.d. b.d. b.d. b.d. b.d. 0,07 b.d. b.d. b.d. 34,61 b.d. b.d. 99,37 BA30_CP_04_2 30,78 33,71 b.d. b.d. b.d. b.d. b.d. 0,08 b.d. b.d. b.d. 34,44 b.d. b.d. 99,01 BA30_CP_04_3 30,88 34,02 b.d. b.d. b.d. b.d. b.d. 0,07 b.d. b.d. b.d. 34,72 b.d. b.d. 99,69 BA30_CP_04_4 30,72 33,55 b.d. b.d. b.d. b.d. b.d. 0,07 b.d. b.d. b.d. 34,85 b.d. b.d. 99,19 BA30_CP_04_5 30,73 33,63 b.d. b.d. b.d. b.d. b.d. 0,06 b.d. b.d. b.d. 34,53 b.d. b.d. 98,95 BA30_CP_08_1 30,26 34,15 b.d. b.d. b.d. 0,06 0,23 0,07 b.d. 0,08 b.d. 34,75 b.d. b.d. 99,60 BA30_CP_08_2 30,13 34,00 b.d. b.d. b.d. b.d. 0,02 b.d. b.d. 0,07 b.d. 34,59 b.d. b.d. 98,81 BA30_CP_08_3 30,38 33,76 b.d. b.d. b.d. b.d. b.d. 0,03 b.d. 0,09 b.d. 34,63 b.d. b.d. 98,89 BA30_CP_08_4 30,66 34,22 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,06 b.d. 34,87 b.d. b.d. 99,81 BA30_CP_08_5 30,45 34,13 b.d. b.d. b.d. b.d. b.d. 0,03 b.d. 0,05 b.d. 34,91 b.d. b.d. 99,57 BA30_CP_09_1 30,64 33,74 b.d. b.d. b.d. b.d. b.d. 0,07 b.d. b.d. b.d. 34,76 b.d. b.d. 99,21 BA30_CP_09_2 30,89 33,50 b.d. b.d. b.d. b.d. b.d. 0,07 b.d. 0,02 b.d. 34,96 b.d. b.d. 99,44 BA30_CP_09_3 30,79 33,87 b.d. b.d. b.d. b.d. b.d. 0,08 b.d. 0,02 b.d. 34,91 b.d. b.d. 99,67 BA30_CP_09_4 30,65 33,86 b.d. b.d. b.d. b.d. b.d. 0,08 b.d. 0,03 b.d. 34,80 b.d. b.d. 99,42 BA30_CP_09_5 30,80 34,12 b.d. b.d. b.d. b.d. b.d. 0,10 b.d. 0,04 b.d. 34,82 b.d. b.d. 99,88 BA30_CP_10_1 31,11 34,02 b.d. b.d. b.d. b.d. b.d. 0,08 b.d. 0,02 b.d. 34,79 b.d. b.d. 100,02 BA30_CP_10_2 30,93 33,94 b.d. b.d. b.d. b.d. b.d. 0,07 b.d. b.d. b.d. 35,16 b.d. b.d. 100,10 BA30_CP_10_3 30,88 33,75 b.d. 0,04 b.d. 0,02 0,03 0,06 b.d. b.d. b.d. 34,68 b.d. b.d. 99,46 BA30_CP_10_4 31,02 33,86 b.d. b.d. b.d. b.d. b.d. 0,08 b.d. b.d. b.d. 34,90 b.d. b.d. 99,86 BA30_CP_10_5 31,06 33,79 b.d. b.d. b.d. b.d. b.d. 0,06 b.d. b.d. b.d. 34,75 b.d. b.d. 99,66 BA33_CP_02_1 31,03 33,95 b.d. b.d. b.d. b.d. b.d. 0,14 b.d. b.d. b.d. 34,83 b.d. b.d. 99,95 BA33_CP_02_2 30,38 33,64 b.d. b.d. b.d. b.d. b.d. 0,13 b.d. b.d. b.d. 34,55 b.d. b.d. 98,70 BA33_CP_02_3 30,9 34,36 b.d. b.d. b.d. b.d. b.d. 0,13 b.d. b.d. b.d. 34,92 b.d. b.d. 100,31 BA33_CP_02_4 31,11 34,33 b.d. b.d. b.d. b.d. b.d. 0,14 b.d. b.d. b.d. 34,94 b.d. b.d. 100,52 BA33_CP_02_5 30,95 34,26 b.d. b.d. b.d. b.d. 0,02 0,15 b.d. b.d. b.d. 34,82 b.d. b.d. 100,20 BA33_CP_03_1 30,85 34,10 b.d. b.d. b.d. b.d. b.d. 0,14 b.d. b.d. b.d. 34,86 b.d. b.d. 99,95 BA33_CP_03_2 30,87 34,22 b.d. b.d. b.d. b.d. b.d. 0,14 b.d. b.d. b.d. 34,68 b.d. b.d. 99,91 BA33_CP_03_3 30,91 34,42 b.d. b.d. b.d. b.d. b.d. 0,16 b.d. b.d. b.d. 34,70 b.d. b.d. 100,19 BA33_CP_03_4 31,04 34,38 b.d. b.d. b.d. b.d. b.d. 0,14 b.d. b.d. b.d. 34,80 b.d. b.d. 100,36 BA33_CP_03_5 31,22 34,29 b.d. b.d. b.d. b.d. b.d. 0,14 b.d. b.d. b.d. 34,93 b.d. b.d. 100,58 BA34_CP_01_1 30,50 33,64 b.d. b.d. b.d. b.d. b.d. 0,09 b.d. b.d. b.d. 35,33 b.d. b.d. 99,56 BA34_CP_01_2 29,85 34,21 b.d. b.d. b.d. b.d. b.d. 0,12 b.d. b.d. b.d. 34,91 b.d. b.d. 99,09 BA34_CP_01_3 30,41 34,28 b.d. b.d. b.d. b.d. b.d. 0,12 b.d. b.d. b.d. 34,88 b.d. b.d. 99,69 BA34_CP_01_4 30,38 34,23 0,07 b.d. b.d. b.d. b.d. 0,11 b.d. b.d. b.d. 34,94 b.d. b.d. 99,73 76

Fe Cu Zn Ni Co As Sb Ag Au Se Bi S Pb Te TOTAL ID análisis [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] BA34_CP_01_5 30,62 34,25 b.d. b.d. b.d. b.d. b.d. 0,10 b.d. b.d. b.d. 34,90 b.d. b.d. 99,87 BA34_CP_20_1 30,28 34,19 b.d. b.d. b.d. b.d. b.d. 0,10 b.d. b.d. b.d. 34,97 b.d. b.d. 99,54 BA34_CP_20_2 30,25 34,21 b.d. b.d. b.d. b.d. b.d. 0,11 b.d. 0,03 b.d. 35,00 b.d. b.d. 99,60 BA34_CP_20_3 30,19 34,04 b.d. b.d. b.d. b.d. b.d. 0,11 b.d. b.d. b.d. 35,04 b.d. b.d. 99,38 BA34_CP_20_4 30,01 34,26 b.d. b.d. b.d. b.d. b.d. 0,08 b.d. b.d. b.d. 34,73 b.d. b.d. 99,08 BA34_CP_20_5 29,80 33,85 b.d. b.d. b.d. b.d. b.d. 0,12 b.d. b.d. b.d. 34,60 b.d. b.d. 98,37 BA34_CP_14_1 30,61 34,63 b.d. b.d. b.d. b.d. b.d. 0,16 b.d. b.d. b.d. 35,17 b.d. b.d. 100,57 BA34_CP_14_2 30,50 34,53 b.d. b.d. b.d. b.d. b.d. 0,16 b.d. b.d. b.d. 35,22 b.d. b.d. 100,41 BA34_CP_14_3 30,49 34,43 b.d. b.d. b.d. b.d. b.d. 0,12 b.d. b.d. b.d. 34,90 b.d. b.d. 99,94 BA34_CP_14_4 30,53 34,24 b.d. b.d. b.d. b.d. b.d. 0,17 b.d. b.d. b.d. 35,02 b.d. b.d. 99,96 BA34_CP_14_5 30,59 34,38 b.d. b.d. b.d. b.d. b.d. 0,15 b.d. b.d. b.d. 34,95 b.d. b.d. 100,07 BA48_CP_04_1 30,43 34,34 b.d. b.d. b.d. b.d. 0,02 0,11 b.d. b.d. b.d. 34,83 b.d. b.d. 99,73 BA48_CP_04_2 30,53 34,15 b.d. b.d. b.d. b.d. b.d. 0,08 b.d. b.d. b.d. 34,95 b.d. b.d. 99,71 BA48_CP_04_3 30,81 33,91 b.d. b.d. b.d. b.d. b.d. 0,10 b.d. b.d. b.d. 34,12 b.d. b.d. 98,94 BA48_CP_04_4 30,51 34,41 b.d. b.d. b.d. b.d. b.d. 0,09 b.d. b.d. b.d. 34,91 b.d. 0,05 99,97 BA48_CP_04_5 30,60 34,40 b.d. b.d. b.d. b.d. b.d. 0,09 b.d. b.d. b.d. 34,92 b.d. b.d. 100,01 BA48_CP_05_1 30,08 34,10 b.d. b.d. b.d. b.d. b.d. 0,11 b.d. b.d. b.d. 34,89 b.d. b.d. 99,18 BA48_CP_05_2 30,28 34,37 b.d. b.d. b.d. b.d. b.d. 0,12 b.d. b.d. b.d. 34,75 b.d. b.d. 99,52 BA48_CP_05_3 30,32 34,81 b.d. 0,05 b.d. b.d. b.d. 0,11 b.d. b.d. b.d. 34,69 b.d. b.d. 99,98 BA48_CP_05_4 30,55 34,72 b.d. b.d. b.d. b.d. b.d. 0,09 b.d. b.d. b.d. 34,99 b.d. b.d. 100,35 BA48_CP_05_5 30,48 34,67 b.d. b.d. b.d. b.d. b.d. 0,09 b.d. b.d. b.d. 34,71 b.d. b.d. 99,95 BA48_CP_06_1 29,71 34,21 b.d. b.d. b.d. b.d. b.d. 0,17 b.d. b.d. b.d. 35,02 b.d. b.d. 99,11 BA48_CP_06_2 30,11 34,35 b.d. b.d. b.d. b.d. b.d. 0,10 b.d. b.d. b.d. 34,76 b.d. b.d. 99,32 BA48_CP_06_3 30,14 34,43 b.d. b.d. b.d. b.d. b.d. 0,08 b.d. b.d. b.d. 34,79 b.d. b.d. 99,44 BA48_CP_06_4 30,03 34,56 b.d. b.d. b.d. b.d. b.d. 0,11 b.d. b.d. b.d. 34,91 b.d. b.d. 99,61 BA48_CP_06_5 30,39 34,41 b.d. b.d. b.d. b.d. b.d. 0,11 b.d. b.d. b.d. 34,70 b.d. b.d. 99,61 BA48_CP_08_1 29,67 34,21 b.d. b.d. b.d. b.d. b.d. 0,07 b.d. 0,02 b.d. 35,08 b.d. b.d. 99,05 BA48_CP_08_2 29,38 33,76 b.d. b.d. b.d. b.d. b.d. 0,07 b.d. b.d. b.d. 35,25 b.d. b.d. 98,46 BA48_CP_08_3 29,96 34,42 b.d. b.d. b.d. b.d. b.d. 0,06 b.d. 0,02 b.d. 35,16 b.d. b.d. 99,62 BA48_CP_08_4 29,94 34,32 b.d. b.d. b.d. b.d. b.d. 0,09 b.d. 0,02 b.d. 35,00 b.d. b.d. 99,37 BA48_CP_08_5 29,63 33,76 b.d. b.d. b.d. b.d. b.d. 0,06 b.d. b.d. b.d. 35,12 b.d. b.d. 98,57 BA48_CP_15_1 30,34 34,11 b.d. b.d. b.d. b.d. b.d. 0,11 b.d. 0,03 b.d. 35,17 b.d. b.d. 99,76 BA48_CP_15_2 30,50 34,29 b.d. b.d. b.d. b.d. b.d. 0,11 b.d. 0,05 b.d. 34,92 b.d. b.d. 99,87 BA48_CP_15_3 30,52 35,00 b.d. b.d. b.d. b.d. b.d. 0,08 b.d. 0,04 b.d. 35,09 b.d. b.d. 100,73 BA48_CP_15_4 30,58 34,60 b.d. b.d. b.d. b.d. b.d. 0,06 b.d. 0,03 b.d. 35,06 b.d. b.d. 100,33 BA48_CP_15_5 30,48 34,44 b.d. b.d. b.d. b.d. b.d. 0,13 b.d. 0,06 b.d. 34,99 b.d. b.d. 100,10

Fe Cu Zn Ni Co As Sb Ag Au Se Bi S Pb Te Detection Limit [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] Minimum 0,04 0,06 0,06 0,03 0,03 0,02 0,02 0,02 0,05 0,02 - 0,04 0,12 0,04 Maximum 0,04 0,09 0,06 0,04 0,03 0,02 0,02 0,02 0,05 0,02 - 0,04 0,12 0,05 Mean 0,04 0,07 0,06 0,04 0,03 0,02 0,02 0,02 0,05 0,02 - 0,04 0,12 0,04 Median 0,04 0,06 0,06 0,04 0,03 0,02 0,02 0,02 0,05 0,02 - 0,04 0,12 0,04

Fe Cu Zn Ni Co As Sb Ag Au Se Bi S Pb Te Std Deviation [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] Minimum 0,28 0,62 0,09 0,05 - 0,03 0,03 0,03 - 0,02 - 0,36 - 0,06 Maximum 0,49 0,91 0,09 0,05 - 0,03 0,03 0,04 - 0,02 - 0,56 - 0,06 Mean 0,42 0,82 0,09 0,05 - 0,03 0,03 0,03 - 0,02 - 0,48 - 0,06 Median 0,47 0,90 0,09 0,05 - 0,03 0,03 0,03 - 0,02 - 0,55 - 0,06

77

ANEXO E: Resultados de análisis EMPA en galena del Sistema Geotermal Cerro Pabellón

(b.d.: bajo el límite de detección)

Fe Cu Zn Ni Co As Sb Ag Au Se Bi S Pb Te TOTAL ID análisis [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] BA20_GN_1b_1 0,65 b.d. b.d. b.d. b.d. b.d. b.d. 0,15 b.d. 0,09 b.d. 12,96 85,20 b.d. 99,05 BA20_GN_1b_2 0,22 b.d. b.d. b.d. b.d. b.d. b.d. 0,18 b.d. 0,06 b.d. 13,25 87,54 b.d. 101,25 BA20_GN_1b_3 0,12 b.d. b.d. b.d. b.d. b.d. b.d. 0,14 b.d. 0,07 b.d. 13,08 86,67 b.d. 100,08 BA20_GN_1b_4 0,09 0,10 b.d. b.d. b.d. b.d. b.d. 0,10 b.d. 0,07 b.d. 13,13 86,75 b.d. 100,24 BA20_GN_1b_5 0,25 0,33 b.d. b.d. b.d. b.d. b.d. 0,11 b.d. 0,09 b.d. 13,32 87,54 b.d. 101,64 BA20_GN_10_1 0,48 b.d. b.d. b.d. b.d. b.d. 0,05 0,07 b.d. 0,11 b.d. 13,31 85,68 b.d. 99,70 BA20_GN_10_2 0,21 b.d. b.d. b.d. b.d. b.d. 0,04 0,08 b.d. 0,13 b.d. 13,06 85,18 b.d. 98,70 BA20_GN_10_3 0,50 b.d. b.d. b.d. b.d. b.d. b.d. 0,11 b.d. 0,12 b.d. 13,35 86,45 b.d. 100,53 BA20_GN_10_4 0,34 b.d. 0,09 b.d. b.d. b.d. b.d. 0,10 b.d. 0,13 b.d. 13,13 85,42 b.d. 99,21 BA20_GN_10_5 0,45 b.d. b.d. b.d. 0,04 b.d. 0,04 0,10 b.d. 0,10 b.d. 13,24 86,18 b.d. 100,15 BA20_GN_11_1 0,72 0,06 b.d. b.d. b.d. b.d. 0,03 0,12 b.d. 0,07 b.d. 13,25 85,63 b.d. 99,88 BA20_GN_11_2 1,06 b.d. b.d. b.d. b.d. 0,02 b.d. 0,12 b.d. 0,04 b.d. 13,29 84,82 b.d. 99,35 BA20_GN_11_3 0,20 b.d. b.d. b.d. b.d. b.d. b.d. 0,14 b.d. 0,06 b.d. 13,23 85,32 b.d. 98,95 BA20_GN_11_4 0,38 b.d. b.d. b.d. b.d. b.d. 0,05 0,14 b.d. 0,02 b.d. 13,26 85,99 b.d. 99,84 BA20_GN_11_5 1,18 b.d. b.d. b.d. b.d. b.d. b.d. 0,15 b.d. 0,09 b.d. 13,37 84,77 b.d. 99,56 BA20_GN_12_1 0,04 b.d. b.d. b.d. b.d. b.d. b.d. 0,09 b.d. 0,10 b.d. 13,21 85,81 b.d. 99,25 BA20_GN_12_2 0,04 b.d. b.d. b.d. b.d. b.d. b.d. 0,10 b.d. 0,08 b.d. 13,21 85,96 b.d. 99,39 BA20_GN_12_3 b.d. b.d. b.d. b.d. b.d. b.d. 0,03 0,11 b.d. 0,10 b.d. 13,11 85,33 b.d. 98,68 BA20_GN_12_4 b.d. b.d. b.d. b.d. b.d. b.d. 0,04 0,07 b.d. 0,13 b.d. 13,15 85,51 0,06 98,96 BA20_GN_12_5 0,05 b.d. b.d. b.d. b.d. b.d. b.d. 0,10 b.d. 0,16 b.d. 13,23 85,55 b.d. 99,09 BA20_GN_17_1 b.d. 0,07 b.d. b.d. b.d. b.d. 0,05 0,08 b.d. 0,02 b.d. 12,69 82,91 b.d. 95,82 BA20_GN_17_2 0,03 0,08 b.d. b.d. b.d. b.d. 0,05 0,11 b.d. 0,05 b.d. 12,72 83,85 0,08 96,97 BA20_GN_17_3 b.d. 0,07 b.d. b.d. b.d. b.d. 0,04 0,06 b.d. 0,04 b.d. 12,83 83,59 b.d. 96,63 BA20_GN_17_4 b.d. b.d. b.d. b.d. b.d. b.d. 0,07 0,07 b.d. 0,06 b.d. 12,67 82,74 b.d. 95,61 BA20_GN_17_5 b.d. 0,09 b.d. b.d. b.d. b.d. 0,06 0,18 b.d. 0,04 b.d. 12,63 82,41 b.d. 95,41 BA20_GN_19_1 0,23 b.d. b.d. b.d. 0,06 b.d. 0,04 0,10 b.d. 0,17 b.d. 13,16 85,91 b.d. 99,67 BA20_GN_19_2 0,04 b.d. b.d. b.d. b.d. b.d. 0,05 0,07 b.d. 0,12 b.d. 13,22 86,05 b.d. 99,55 BA20_GN_19_3 0,04 b.d. b.d. b.d. b.d. b.d. 0,04 1,02 b.d. 0,14 b.d. 13,09 83,17 b.d. 97,50 BA20_GN_19_4 b.d. 0,07 b.d. b.d. b.d. b.d. 0,04 0,07 b.d. 0,15 b.d. 13,22 85,75 b.d. 99,30 BA20_GN_19_5 0,06 b.d. b.d. b.d. b.d. b.d. 0,04 0,07 b.d. 0,11 b.d. 13,29 85,92 b.d. 99,49 BA33_GN_01_1 2,05 0,47 b.d. b.d. b.d. b.d. b.d. 0,10 b.d. 0,34 b.d. 13,35 84,63 b.d. 100,94 BA33_GN_01_2 1,81 0,57 b.d. b.d. b.d. b.d. 0,03 0,09 b.d. 0,36 b.d. 13,31 84,69 b.d. 100,86

Fe Cu Zn Ni Co As Sb Ag Au Se Bi S Pb Te Detection Limit [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] Minimum 0,03 0,06 0,07 0,04 0,04 0,02 0,02 0,03 0,05 0,02 0,09 0,02 0,17 0,03 Maximum 0,03 0,06 0,07 0,04 0,04 0,02 0,03 0,04 0,05 0,03 0,10 0,03 0,31 0,06 Mean 0,03 0,06 0,07 0,04 0,04 0,02 0,03 0,03 0,05 0,02 0,10 0,03 0,22 0,06 Median 0,03 0,06 0,07 0,04 0,04 0,02 0,02 0,03 0,05 0,02 0,10 0,03 0,22 0,06

Fe Cu Zn Ni Co As Sb Ag Au Se Bi S Pb Te Std Deviation [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] Minimum 0,05 0,08 0,10 - 0,05 0,02 0,03 0,04 - 0,02 - 0,19 0,93 0,08 Maximum 0,08 0,09 0,10 - 0,05 0,02 0,04 0,06 - 0,04 - 0,25 1,88 0,08 Mean 0,05 0,08 0,10 - 0,05 0,02 0,04 0,04 - 0,03 - 0,23 1,70 0,08 Median 0,05 0,08 0,10 - 0,05 0,02 0,04 0,04 - 0,02 - 0,24 1,86 0,08

78

ANEXO F: Resultados de análisis EMPA en acantita del Sistema Geotermal Cerro Pabellón

(b.d.: bajo el límite de detección)

Fe Cu Zn Ni Co As Sb Ag Au Se Bi S Pb Te TOTAL Analysis ID [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] BA20_AC_09_1 0,28 1,69 b.d. b.d. b.d. b.d. b.d. 84,41 0,09 0,32 b.d. 11,4 b.d. b.d. 98,19 BA20_AC_10_1 0,19 0,77 b.d. b.d. b.d. b.d. b.d. 76,44 0,07 0,21 b.d. 16,59 b.d. b.d. 94,27

Fe Cu Zn Ni Co As Sb Ag Au Se Bi S Pb Te Detection Limit [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] Minimum 0,03 0,05 - 0,04 0,04 0,02 0,02 0,07 0,05 0,02 - 0,02 0,07 - Maximum 0,03 0,06 - 0,04 0,04 0,02 0,02 0,08 0,05 0,02 - 0,03 0,07 - Mean 0,03 0,05 - 0,04 0,04 0,02 0,02 0,08 0,05 0,02 - 0,03 0,07 - Median 0,03 0,06 - 0,04 0,04 0,02 0,02 0,08 0,05 0,02 - 0,03 0,07 -

Fe Cu Zn Ni Co As Sb Ag Au Se Bi S Pb Te Std Deviation [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] [wt%] Minimum 0,05 0,09 - 0,06 0,05 0,02 0,03 0,79 0,07 0,03 - 0,22 0,10 - Maximum 0,05 0,11 - 0,06 0,05 0,02 0,03 0,86 0,08 0,03 - 0,30 0,10 - Mean 0,05 0,10 - 0,06 0,05 0,02 0,03 0,83 0,08 0,03 - 0,26 0,10 - Median 0,05 0,10 - 0,06 0,05 0,02 0,03 0,83 0,08 0,03 - 0,26 0,10 -

79

ANEXO G: Resultados de análisis LA-ICP-MS en pirita del Sistema Geotermal Cerro Pabellón

Este anexo es equivalente a “Supplementary material B” indicado en el manuscrito.

(b.d.: bajo el límite de detección)

Co Ni Cu Zn Pb As Sb Se Te Bi Au Ag V Cr Mn Ga Ge Sn Mo W Cd Hg In Tl Analysis ID Profile Group [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] BA20_6_1 Inclusion III 41 207 19,4 b.d. 23,2 85 1,38 b.d. b.d. b.d. 0,33 15,3 1,6 b.d. b.d. 1,7 3,6 b.d. 1,11 b.d. b.d. b.d. b.d. 0,14 BA20_6_2 Inclusion III 123 188 980 b.d. 77 480 18,6 30 b.d. 0,12 0,26 680 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_6_3 Inclusion III 61 35 173 b.d. 340 180 0,72 106 b.d. 0,64 2 720 b.d. b.d. b.d. b.d. 2,9 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_6_4 Inclusion-free III 410 1230 4970 b.d. 480 2290 65 109 b.d. 2,86 2,59 161 b.d. b.d. b.d. b.d. 4,2 b.d. b.d. b.d. b.d. 0,94 b.d. b.d. BA20_6_5 Inclusion III 223 362 2700 b.d. 260 506 83 68 b.d. 1,14 2,14 870 b.d. 2,8 b.d. b.d. 4,3 b.d. b.d. b.d. 2,3 b.d. b.d. 0,09 BA20_6_6 Inclusion-free III 340 400 3640 b.d. 451 1960 75 64 b.d. 3,17 3,6 339 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 11,5 b.d. 1,36 BA20_6_7 Inclusion III 351 870 3940 b.d. 171 920 26,1 97 b.d. 0,81 47 3800 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1,9 b.d. b.d. 0,18 BA20_6_8 Inclusion III 70 194 157 b.d. 8200 337 4,1 89 b.d. 11,6 5 1430 b.d. b.d. b.d. b.d. b.d. b.d. 1,8 b.d. 6 b.d. b.d. b.d. BA20_9_2 Inclusion III 122 328 25,8 b.d. 9,3 496 1,55 b.d. b.d. b.d. 0,08 13,4 b.d. b.d. b.d. b.d. 2,8 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_9_3 Inclusion III 154 29,7 22,8 b.d. 1,94 279 0,76 b.d. b.d. b.d. 0,06 9 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_9_4 Inclusion III 167 19,8 48 b.d. 6,8 387 1,26 56 b.d. b.d. 4,6 1080 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,93 b.d. b.d. b.d. BA20_9_5 Inclusion-free III 109 28,9 1,5 b.d. b.d. 167 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_9_6 Inclusion-free III 64 48 15,1 b.d. b.d. 202 b.d. b.d. b.d. b.d. b.d. 0,93 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_9_7 Inclusion-free III 32,4 87 23,7 b.d. 22,3 241 1,92 b.d. b.d. 0,07 0,1 14,4 b.d. 3,3 b.d. b.d. b.d. 0,43 b.d. b.d. b.d. b.d. b.d. b.d. BA20_9_8 Inclusion-free III 337 70 6,3 b.d. b.d. 470 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1,03 b.d. b.d. b.d. BA20_9_9 Inclusion-free III 29 570 7,3 b.d. b.d. 101 b.d. 23 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 2,9 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_9_10 Inclusion-free III 94 156 4,7 b.d. b.d. 158 b.d. b.d. b.d. 0,13 b.d. b.d. b.d. b.d. b.d. b.d. 8,7 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_10_1 Inclusion-free III 32,5 33 35,9 b.d. 7,9 630 b.d. 22 b.d. b.d. b.d. b.d. b.d. 3 19,6 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_10_2 Inclusion III 28,6 13,2 1550 b.d. 16,2 91 0,83 296 b.d. b.d. 47 18000 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 4,9 b.d. 0,13 b.d. BA20_10_3 Inclusion-free III 15,4 13 8,1 b.d. b.d. 57 b.d. 19 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,78 b.d. b.d. BA20_10_4 Inclusion III 144 20 251 b.d. 12700 670 5,6 98 b.d. 16 18,5 2000 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 2,3 b.d. 0,13 b.d. BA20_10_5 Inclusion-free III 162 19 142 b.d. 25,2 443 0,74 b.d. b.d. b.d. 0,09 4,2 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_11_1 Inclusion-free III 21,3 5,9 19,7 b.d. 1,05 96 b.d. b.d. b.d. b.d. b.d. 0,5 b.d. 4,9 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_11_2 Inclusion-free III 19,1 9 7,6 b.d. 64,9 88 0,95 51 b.d. b.d. b.d. 4,09 b.d. b.d. 37,1 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_11_3 Inclusion III 25 10,4 38,7 6 58 91 1,11 29 b.d. 0,2 0,1 46 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1,02 b.d. b.d. b.d. BA20_11_4 Inclusion-free III 9,6 2,4 8,2 b.d. b.d. 119 b.d. 24 b.d. b.d. b.d. b.d. b.d. 5,8 b.d. b.d. 4 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_11_5 Inclusion III 12,4 3,1 37 b.d. 2,7 56,3 0,82 18 b.d. b.d. 0,72 220 b.d. b.d. b.d. b.d. 2,5 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_11_6 Inclusion-free III 63 33 75 b.d. 22,7 283 3,3 b.d. b.d. 0,39 0,32 17,2 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_11_7 Inclusion-free III 7,7 4,2 b.d. b.d. b.d. 123 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_11_8 Inclusion III 168 291 1200 b.d. 112 570 23,7 37 b.d. 0,33 3,2 1170 b.d. b.d. b.d. b.d. 2,1 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_11_9 Inclusion-free III 8,8 2,1 7 b.d. b.d. 103 b.d. b.d. b.d. b.d. b.d. 0,52 b.d. 2,6 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_11_10 Inclusion III 0,97 1,03 28,4 b.d. b.d. 65 b.d. b.d. b.d. b.d. 0,2 9,1 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_12_1 Inclusion III 70 20,9 700 b.d. 29300 172 17,3 144 b.d. 35 37 5600 b.d. 6,4 b.d. 4 b.d. b.d. b.d. b.d. 8,9 b.d. b.d. 0,38 BA20_12_2 Inclusion III 63,7 21,8 310 6,2 19,5 125 1,75 123 b.d. b.d. 40 4600 b.d. 4 b.d. b.d. b.d. b.d. b.d. b.d. 1,75 b.d. b.d. b.d. BA20_12_3 Inclusion III 68 8,8 1350 b.d. 85 205 1,69 125 b.d. b.d. 167 15000 b.d. b.d. b.d. b.d. b.d. b.d. 1,39 b.d. 7,1 b.d. b.d. b.d. BA20_12_4 Inclusion III 234 99 920 b.d. 670 155 6,8 255 b.d. 0,91 144 14800 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 2 b.d. b.d. b.d. BA20_12_5 Inclusion III 108 33 1620 b.d. 32000 58 8,3 77 b.d. 36 27 2400 1,5 b.d. 2,4 b.d. b.d. b.d. b.d. b.d. 4,6 b.d. b.d. b.d. BA20_12_6 Inclusion III 192 80 139 b.d. 25100 113 12,1 55 b.d. 25,1 16,9 1950 3,9 b.d. b.d. b.d. b.d. b.d. 1,48 b.d. 10 b.d. b.d. b.d. BA20_18_1 Inclusion III 54,7 393 1240 b.d. 121 330 10,2 63 b.d. 0,61 0,32 29,8 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,07 b.d. BA20_18_2 Inclusion-free III 51 173 390 b.d. 3 173 1,1 b.d. b.d. 0,14 b.d. 3,2 b.d. b.d. b.d. b.d. b.d. b.d. 1,4 b.d. b.d. b.d. b.d. b.d. BA20_18_3 Inclusion III 48 243 890 b.d. 11,8 195 2,4 40 b.d. b.d. 0,23 20 b.d. b.d. b.d. b.d. b.d. b.d. 0,92 b.d. b.d. b.d. b.d. b.d. BA20_18_4 Inclusion-free III 1,7 15,7 61 b.d. b.d. 683 b.d. 38 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 8,2 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_18_5 Inclusion III 221 610 2590 b.d. 54 1590 26,9 52 b.d. 0,73 1,41 164 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,15 b.d. BA20_18_6 Inclusion III 518 560 1320 b.d. 133 1900 54 b.d. b.d. 1,96 11,5 2340 b.d. b.d. b.d. b.d. b.d. b.d. 1,5 b.d. b.d. b.d. b.d. b.d. BA20_18_7 Inclusion III 389 560 2370 b.d. 990 2440 96 25 b.d. 12,1 15,2 2540 b.d. b.d. b.d. b.d. b.d. b.d. 1,38 b.d. 1,8 b.d. 0,15 b.d. BA20_18_8 Inclusion III 225 197 920 b.d. 13800 1250 11,7 43 b.d. 33,8 5,1 1070 b.d. b.d. b.d. b.d. b.d. b.d. 0,98 b.d. 3,9 b.d. b.d. b.d. BA20_18_9 Inclusion III 150 233 2140 b.d. 193 1740 31,6 39 b.d. 1,93 2,44 134 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,12 BA20_16_1 Inclusion-free III 19,2 690 18,2 b.d. b.d. 261 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_16_2 Inclusion III 25,2 157 80 b.d. 102 207 1,13 18 b.d. 0,17 0,47 124 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_16_3 Inclusion-free III 13 100 82 b.d. 0,78 267 b.d. 16 b.d. b.d. b.d. 0,82 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 80

Co Ni Cu Zn Pb As Sb Se Te Bi Au Ag V Cr Mn Ga Ge Sn Mo W Cd Hg In Tl Analysis ID Profile Group [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] BA20_15_1 Inclusion-free III b.d. 97 4,5 b.d. b.d. 141 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 2,7 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_15_2 Inclusion-free III 72 340 10,3 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA21_1a_1 Inclusion II 218 42 680 b.d. 331 4400 7,9 b.d. b.d. 1,5 9,7 124 b.d. b.d. 51 b.d. b.d. 0,72 b.d. b.d. b.d. b.d. b.d. 0,12 BA21_1a_2 Inclusion II 248 102 630 6,7 970 3600 10,6 8,6 b.d. 2,75 9,7 156 1,21 2,8 47,3 0,59 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,26 BA21_1a_3 Inclusion II 46,3 18 1080 b.d. 84 5200 2,8 10,9 b.d. 0,38 19,1 28,8 b.d. 1,6 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA21_1a_4 Inclusion II 227 64 1160 b.d. 138 2890 7 17 b.d. 1,27 3,7 132 b.d. 2,5 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA21_1b_1 Inclusion-free II 106 72 750 10 174 5810 8,7 23 b.d. 1 13,7 17,3 3,2 5,7 45,3 0,96 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,18 BA21_1b_2 Inclusion II 264 149 750 b.d. 1280 2770 14,1 9,8 b.d. 3,31 5,4 78 1,12 b.d. 21 b.d. b.d. b.d. b.d. 0,15 b.d. b.d. b.d. 0,28 BA21_1b_3 Inclusion II 297 155 753 b.d. 690 2710 11,7 b.d. b.d. 1,92 2,92 121 1,7 3,1 30,2 b.d. b.d. b.d. b.d. 0,25 b.d. b.d. b.d. 0,32 BA21_1b_4 Inclusion-free II 500 153 1440 b.d. 670 1890 9,5 18 b.d. 3,16 3,24 376 b.d. b.d. 28,4 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,25 BA21_3_1 Inclusion-free II 38,4 8,7 317 b.d. 115 1790 4,94 9 b.d. 0,44 b.d. 7,6 9,7 b.d. 9,5 b.d. b.d. b.d. b.d. 0,25 b.d. b.d. b.d. 0,28 BA21_3_2 Inclusion-free II 187 108 212 19,9 53,5 1550 4,5 18 b.d. b.d. 0,23 4,8 3 6,3 75,7 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA21_3_3 Inclusion-free II 97 49 338 b.d. 65 1390 2,53 16 b.d. 0,18 1,39 2,99 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,18 BA21_3_4 Inclusion-free II 101 82 217 b.d. 65,6 1070 3,19 b.d. b.d. 0,19 2,19 4,58 b.d. 3,3 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,13 BA21_3_5 Inclusion II 102 40,5 416 b.d. 212 1690 5,7 37 b.d. 0,36 0,74 96 b.d. b.d. 1,81 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,16 BA21_4_1 Inclusion II 97 76 230 b.d. 19300 310 1,21 145 b.d. 23,9 15,4 3600 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 12,2 b.d. b.d. b.d. BA21_4_2 Inclusion II 49 36,2 34,5 b.d. 82 650 b.d. 10 b.d. 0,16 0,05 5,1 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,08 BA21_4_3 Inclusion-free II 39,9 26,4 18,7 b.d. 45 544 3,53 11 b.d. 0,24 0,04 4,98 b.d. b.d. 3,6 b.d. b.d. b.d. b.d. 0,31 b.d. b.d. b.d. 0,13 BA21_5_1 Inclusion II 43 8,1 290 b.d. 24,7 638 1,61 b.d. b.d. 0,12 0,95 0,71 b.d. b.d. b.d. b.d. b.d. b.d. 0,69 b.d. b.d. b.d. b.d. b.d. BA21_5_2 Inclusion-free II 59 19 820 b.d. 284 630 14,5 b.d. b.d. 0,71 b.d. 9,4 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,16 BA21_5_3 Inclusion-free II 45,6 16,6 234 b.d. 25,7 359 2,33 14 b.d. 0,2 b.d. 3,07 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA21_5_4 Inclusion-free II 8,3 6,9 8,7 b.d. 5,8 47,4 0,62 15,8 b.d. 0,08 b.d. 1,93 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA21_5_5 Inclusion II 179 96 1740 b.d. 5900 284 9,8 164 b.d. 4,97 6,1 2590 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 4,5 b.d. b.d. b.d. BA21_5_6 Inclusion II 149 45,1 1740 63 1890 608 77 165 b.d. 2,39 2,24 1960 b.d. 1,8 b.d. b.d. 1,6 b.d. b.d. b.d. 320 0,49 b.d. 0,06 BA21_6_1 Inclusion-free II 14,7 12,9 700 b.d. 33,2 147 2,61 16 b.d. 0,12 0,24 14,2 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,2 BA21_6_2 Inclusion-free II 36,1 11,4 54,6 b.d. 23,5 505 2,59 b.d. b.d. 0,12 0,24 46 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA21_6_3 Inclusion II 24,6 6,4 375 b.d. 7,1 830 b.d. b.d. b.d. b.d. b.d. 9,9 b.d. 8,1 b.d. b.d. 3,6 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA21_6_4 Inclusion-free II 11,6 2,9 640 b.d. 15,8 1820 1,2 30 b.d. b.d. b.d. 2,53 b.d. 3,2 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA21_6_5 Inclusion-free II 12,4 11,2 4440 b.d. 34,1 1640 2,3 10 b.d. 0,14 0,81 141 b.d. b.d. b.d. b.d. b.d. b.d. 0,47 b.d. b.d. b.d. b.d. 0,19 BA21_7_1 Inclusion II 522 200 4040 41,4 1600 1510 331 50 0,35 3,76 10,6 1820 1,2 b.d. b.d. b.d. 1,5 b.d. b.d. b.d. 40 1,47 b.d. 0,46 BA21_7_2 Inclusion II 202 192 5730 b.d. 3890 2160 76 125 0,33 4,15 3,59 1710 b.d. b.d. b.d. b.d. b.d. b.d. 0,6 b.d. 19 b.d. b.d. 0,37 BA21_7_3 Inclusion II 130 81 3170 b.d. 99 740 7,9 18 b.d. 0,36 0,81 146 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,18 BA21_7_4 Inclusion-free II 32,7 10,8 43,4 b.d. 11,5 491 1,13 b.d. b.d. b.d. 0,18 21,7 b.d. b.d. b.d. b.d. 2,2 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA21_7_5 Inclusion-free II 39 16,7 329 b.d. 36 337 3,1 10 b.d. 0,11 b.d. 16,3 b.d. 1,6 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,18 BA21_7_6 Inclusion II 75 18,4 1080 17 163 1110 390 74 b.d. 0,35 1,65 1920 b.d. b.d. b.d. b.d. b.d. b.d. 0,49 b.d. 53 2,3 b.d. b.d. BA21_7_7 Inclusion-free II 8,6 1,36 79 b.d. 0,82 715 b.d. 35 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1,6 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA21_21_1 Inclusion-free II 99 48 36 b.d. 35,7 371 12,4 b.d. b.d. 0,22 0,11 4,9 26 b.d. 14,3 2,6 4,8 b.d. b.d. 3,2 b.d. b.d. b.d. b.d. BA21_21_2 Inclusion II 69 32 890 b.d. 230 1650 11,4 34 b.d. 0,35 2,98 241 b.d. b.d. 1,58 b.d. b.d. b.d. b.d. 0,3 b.d. b.d. b.d. 0,19 BA21_21_3 Inclusion-free II 209 80 344 b.d. 127 920 16 19 b.d. 0,41 0,16 24,9 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,16 BA21_21_4 Inclusion-free II 37,8 24,6 24,4 b.d. 23,2 483 5 b.d. b.d. b.d. b.d. 3,1 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,31 BA21_21_5 Inclusion-free II 51,7 24 95 b.d. 47,2 781 5,6 15 b.d. 0,23 0,11 7,4 1,89 b.d. 8,9 b.d. b.d. b.d. b.d. 0,78 b.d. b.d. b.d. 0,21 BA21_21_6 Inclusion II 81 23,8 730 b.d. 70 2130 4,4 53 b.d. b.d. 2,1 410 b.d. b.d. b.d. b.d. b.d. b.d. 0,53 b.d. b.d. b.d. b.d. b.d. BA21_8_1 Inclusion-free II 500 179 2180 b.d. 1560 2340 40 49 b.d. 2,19 3,38 560 21,1 b.d. 12,8 b.d. b.d. b.d. b.d. 1,52 b.d. b.d. b.d. 0,51 BA21_8_2 Inclusion-free II 397 227 2130 b.d. 1440 1960 15,4 23 b.d. 2,4 3,86 670 9,6 4,2 37,4 b.d. b.d. b.d. 0,46 0,53 b.d. b.d. b.d. 0,11 BA21_8_3 Inclusion-free II 51 22,7 49,7 b.d. 62 531 3,4 b.d. b.d. 0,27 0,04 9,2 b.d. 3,2 9,9 b.d. b.d. b.d. b.d. 0,48 b.d. b.d. b.d. 0,19 BA21_8_4 Inclusion-free II b.d. b.d. 24,3 b.d. 29 426 b.d. 20 b.d. b.d. b.d. 1,32 b.d. b.d. b.d. b.d. 3,4 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA21_8_5 Inclusion II 137 40,6 362 b.d. 2940 1870 3,8 30 b.d. 3,06 0,72 155 b.d. b.d. 3,2 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA21_8_6 Inclusion II 83,3 77 150 b.d. 1060 793 2,64 12 b.d. 1,32 0,06 11,6 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA21_9_1 Inclusion-free II 285 88 720 b.d. 288 3610 20,3 b.d. b.d. 0,31 1,17 41,9 b.d. 4 5,6 b.d. b.d. b.d. b.d. 2,4 b.d. b.d. b.d. 0,26 BA21_9_2 Inclusion-free II 48,1 26,6 296 b.d. 292 1070 14,7 7,5 b.d. 0,59 1,2 10,1 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA21_9_3 Inclusion-free II 186 91 1010 7,8 432 5780 55,5 9,9 b.d. 0,52 3,86 42,2 b.d. b.d. 3,7 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,46 BA21_9_4 Inclusion II 216 880 4000 7,3 6100 3560 103 12,1 b.d. 18,2 6,3 1010 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 4,9 0,68 b.d. 0,56 BA21_9_5 Inclusion II 537 228 2290 b.d. 1210 2620 21,9 20 b.d. 1,57 2,55 305 b.d. 1,9 25,9 b.d. 1,3 b.d. b.d. 0,28 b.d. b.d. b.d. 0,19 BA21_9_6 Inclusion II 356 156 1710 8,9 2000 2300 19,2 25 b.d. 1,24 1,31 400 b.d. b.d. 15,7 b.d. b.d. b.d. b.d. 0,23 b.d. 0,83 b.d. 0,18 BA21_10a_1 Inclusion II 70,4 68 39,5 b.d. 186 483 3,7 13,6 b.d. 0,51 0,09 19,9 b.d. 1,9 10,8 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,11 BA21_10a_2 Inclusion II 19,8 24,8 34 b.d. 30,6 460 1,2 11,8 b.d. 0,15 b.d. 0,51 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA21_10a_3 Inclusion II 47,6 41,2 23,9 b.d. 44 518 0,78 7,4 b.d. 0,13 0,61 52 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA21_10a_4 Inclusion II 528 138 1790 9,8 2870 8000 128 31 b.d. 3,73 14,5 970 2,1 b.d. 87 b.d. b.d. b.d. b.d. b.d. 5,3 b.d. b.d. 2,11 BA21_10a_5 Inclusion II 167 245 550 b.d. 540 2700 17,1 9,4 b.d. 0,84 9,8 106 b.d. b.d. 14,9 b.d. 1,5 b.d. b.d. b.d. b.d. 0,86 b.d. 0,87 BA21_10b_1 Inclusion-free II 41,9 21,9 670 b.d. 134 1790 14,6 11,3 0,51 b.d. 3,86 44,4 b.d. b.d. b.d. b.d. 2,6 b.d. b.d. b.d. b.d. 1,34 b.d. 0,3 BA21_10b_2 Inclusion II 36 15,1 403 b.d. 114 1580 8 10,7 b.d. 0,07 b.d. 1,33 b.d. b.d. b.d. b.d. 1,52 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 81

Co Ni Cu Zn Pb As Sb Se Te Bi Au Ag V Cr Mn Ga Ge Sn Mo W Cd Hg In Tl Analysis ID Profile Group [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] BA21_10b_3 Inclusion II 117 77 2100 b.d. 1280 1880 5,1 40 b.d. 0,39 1,35 430 b.d. b.d. b.d. b.d. 1,72 b.d. b.d. b.d. b.d. b.d. b.d. 0,06 BA21_10b_4 Inclusion II 30,5 9,5 638 b.d. 73 1570 2,39 18 b.d. 0,16 0,5 96 b.d. b.d. b.d. b.d. 1,8 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA21_10b_5 Inclusion II 168 49 650 b.d. 206 720 9,6 13 b.d. 0,31 0,1 30 b.d. 3 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA21_10b_6 Inclusion II 23,4 22,3 890 b.d. 280 1310 12 32 b.d. 0,1 3,35 62 b.d. b.d. 1,55 b.d. 2,32 b.d. b.d. b.d. b.d. 0,88 b.d. 0,19 BA21_11_1 Inclusion-free II 20,9 16,6 8,3 b.d. 17,8 1590 b.d. 100 b.d. b.d. b.d. 2,52 b.d. b.d. 6,3 7,6 b.d. b.d. 3,5 b.d. b.d. b.d. b.d. 1,13 BA21_11_2 Inclusion-free II 16,5 10 21,2 b.d. 8,3 350 0,5 59 b.d. 0,08 b.d. 5,1 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,07 BA21_11_3 Inclusion II 94 32,3 1500 b.d. 1970 850 11,9 340 b.d. 1,77 4,18 300 1,37 b.d. 3,6 b.d. 2,6 b.d. 0,82 b.d. 1,03 1,18 b.d. 0,22 BA21_11_4 Inclusion II 46,1 24,9 314 b.d. 57 743 2,31 360 b.d. 0,11 0,64 6,6 2 3,5 8,4 b.d. b.d. b.d. b.d. b.d. b.d. 1,7 b.d. 0,36 BA21_11_5 Inclusion II 57 23,3 93 17,6 88 1080 8,7 b.d. b.d. 0,28 0,48 42 4 b.d. 121 b.d. 4,8 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA21_11_6 Inclusion II 70 29 14,6 b.d. 6,4 1240 b.d. b.d. b.d. b.d. b.d. 0,57 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 2,3 b.d. b.d. BA21_12_2 Inclusion II 26,2 13,6 66 8,5 47 1450 1,7 b.d. b.d. b.d. 0,25 19,1 b.d. b.d. 2,9 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA21_12_3 Inclusion II 145 80 640 21,3 12700 2840 3,4 b.d. b.d. 10 0,34 72 b.d. b.d. 6,7 b.d. 3,1 0,61 b.d. b.d. 6,5 b.d. 0,12 b.d. BA21_15_1 Inclusion II 228 70 990 b.d. 2200 3370 134 b.d. b.d. 3,89 1,97 354 b.d. b.d. b.d. b.d. 2,3 b.d. b.d. b.d. 9,4 b.d. b.d. 1,61 BA21_15_2 Inclusion-free II 495 126 623 7,9 2210 5440 328 1050 b.d. 3,79 6,9 960 b.d. b.d. 3 b.d. 2,8 b.d. b.d. b.d. 36,2 1,51 b.d. 4,15 BA21_15_3 Inclusion II 405 102 790 b.d. 1170 3960 143 140 b.d. 3,83 5,5 770 b.d. b.d. 3,3 b.d. b.d. b.d. b.d. b.d. 8,4 b.d. b.d. 1,46 BA21_14_1 Inclusion-free II 102 80 89 b.d. 173 990 23,9 80 b.d. 0,69 0,6 57 12,6 b.d. 25,1 b.d. b.d. b.d. b.d. 0,47 b.d. b.d. b.d. 0,16 BA21_14_2 Inclusion-free II 25,4 11,6 46,5 b.d. 71,1 148 6,4 b.d. b.d. 0,12 0,31 38,3 6,7 b.d. 12,8 b.d. b.d. b.d. b.d. 0,45 b.d. b.d. b.d. 0,12 BA21_14_3 Inclusion-free II 9,8 8,7 102 6,4 664 44000 868 b.d. b.d. 0,22 0,8 171 b.d. 3,1 9,8 b.d. b.d. b.d. 1,69 b.d. 4,2 41,8 b.d. 61,9 BA21_14_4 Inclusion-free II 66 17,3 130 4 632 31600 461 13 b.d. 0,78 0,67 137 b.d. 1,3 13,5 b.d. b.d. b.d. 0,78 0,24 1,91 11,1 b.d. 20,6 BA27_6_1 Inclusion II 43 14,6 670 b.d. 141 455 8,6 b.d. b.d. 14,5 0,72 78 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,19 BA27_6_2 Inclusion II 68 6,8 130 b.d. 396 9200 89 b.d. b.d. 78 1,42 169 b.d. b.d. 13,4 b.d. 3,4 b.d. b.d. b.d. 2,1 20,3 b.d. 4,9 BA27_6_3 Inclusion II 158 30,1 292 b.d. 930 7870 29,7 14 0,81 136 1,36 149 3 b.d. 4,6 b.d. 2,7 b.d. b.d. 0,37 b.d. b.d. b.d. 1,92 BA27_6_4 Inclusion-free II 12,5 12,4 710 b.d. 118 910 32,1 23 b.d. 13,1 0,16 17,3 2,9 b.d. b.d. b.d. 6,2 b.d. b.d. b.d. b.d. b.d. b.d. 0,83 BA27_6_5 Inclusion II 321 53,4 1490 17,2 970 3690 50,4 59 2,5 203 4,42 238 2,5 b.d. 18,7 b.d. 2,9 b.d. b.d. 0,36 b.d. 11,3 b.d. 4,93 BA27_6_6 Inclusion-free II 55 15,4 500 14,7 27 26900 151 b.d. 2,2 8,2 0,64 30,9 b.d. b.d. 31,8 b.d. b.d. b.d. b.d. b.d. b.d. 23,8 b.d. 2,41 BA27_6_7 Inclusion II 173 28,7 1250 b.d. 466 5780 34,7 50 b.d. 98 2,7 143 7,4 b.d. 72 b.d. b.d. b.d. 2,9 b.d. 1,6 4,9 b.d. 0,67 BA30_1_1 Inclusion II 65 19,5 2660 b.d. 30,3 1860 66,8 b.d. b.d. 14,68 1,33 75,1 24,6 b.d. 15,4 1,2 b.d. b.d. b.d. 0,86 b.d. 1,91 b.d. 4,2 BA30_1_2 Inclusion-free II 7 6,1 484 b.d. 13 1840 31,1 b.d. b.d. 2,93 0,89 27,7 4,9 b.d. 2,9 b.d. b.d. b.d. b.d. b.d. b.d. 2,6 b.d. 1,61 BA30_1_3 Inclusion-free II 10,2 2,1 480 b.d. 10 1560 22,2 b.d. b.d. 2,48 0,63 90 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1,32 BA30_2_1 Inclusion-free II 2,78 4,3 19,6 b.d. 9,4 846 14,6 b.d. b.d. 0,3 0,4 12,4 1,7 b.d. b.d. b.d. 2,9 b.d. b.d. b.d. b.d. b.d. b.d. 0,55 BA30_2_2 Inclusion-free II 72 23,1 3920 b.d. 38 427 44,3 b.d. b.d. 10,9 0,6 81,5 25 6,3 12,1 b.d. b.d. b.d. b.d. 0,95 b.d. b.d. b.d. 2,44 BA30_2_3 Inclusion-free II 21,7 13,6 1570 10,7 58,1 252 35,3 b.d. b.d. 5,99 0,3 40,2 13,6 4,2 10,2 b.d. b.d. b.d. b.d. 0,41 b.d. 2,2 b.d. 2,07 BA30_2_4 Inclusion-free II 10,8 17,9 880 b.d. 17,3 388 27,8 20 b.d. 2,73 0,31 27 6,5 3,7 6,6 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1,93 BA30_3_1 Inclusion-free II 20,9 22 1110 b.d. 22,4 90 31,5 b.d. b.d. 3,37 0,36 26,1 18 b.d. 8,6 b.d. b.d. b.d. b.d. 0,19 b.d. 1,72 b.d. 3,04 BA30_3_2 Inclusion-free II 64 40 4560 b.d. 74 392 34,6 79 b.d. 10,9 0,48 75 15,5 b.d. 13,3 2,2 b.d. b.d. b.d. 0,52 b.d. b.d. b.d. 1,26 BA30_3_3 Inclusion-free II 1,17 2,6 7,6 b.d. 0,85 543 b.d. 25 b.d. b.d. 0,26 0,37 b.d. b.d. b.d. 1,02 3 b.d. b.d. b.d. b.d. b.d. 0,12 b.d. BA34_1_1 Inclusion II 54 4,1 800 14,2 2900 123 4,8 30 1,38 10,6 0,71 29,7 b.d. 1,5 b.d. b.d. b.d. b.d. b.d. b.d. 0,66 b.d. 0,19 b.d. BA34_1_2 Inclusion II 84 6,2 1500 10,1 1760 259 3,49 46 0,95 8,3 0,81 38,4 b.d. b.d. 58,9 b.d. b.d. b.d. b.d. b.d. 2,4 b.d. 0,06 b.d. BA34_1_3 Inclusion II 81 10,2 5200 b.d. 13100 570 14,4 109 6,1 82 1,36 116 b.d. 2,9 b.d. b.d. 5,9 b.d. b.d. 0,19 2,1 b.d. 0,14 b.d. BA34_1_4 Inclusion II 95 7,6 600 b.d. 3550 396 3,2 71 2,6 13,5 0,79 43 b.d. b.d. b.d. b.d. b.d. b.d. 1,7 b.d. 1,9 b.d. 0,15 b.d. BA34_2_1 Inclusion II 216 9,6 1340 b.d. 243 1220 14,6 41 b.d. 6,9 4,3 111 5,8 b.d. 12,1 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,73 BA34_2_2 Inclusion II 286 7,1 5300 b.d. 294 860 22,4 65 0,95 9,5 2,39 174 3,3 b.d. 8 b.d. b.d. b.d. b.d. 0,32 b.d. 2,9 b.d. 0,96 BA34_2_3 Inclusion II 133 20,6 3300 b.d. 250 357 15,2 30 b.d. 12,3 3,11 103 8,2 2,5 9,5 b.d. 4,5 b.d. b.d. b.d. b.d. b.d. b.d. 0,29 BA34_2_4 Inclusion-free II 198 8,8 2130 b.d. 249 1290 23,4 59 b.d. 10,6 2,51 212 13,8 5,4 17,8 b.d. 3,2 b.d. b.d. 0,25 b.d. b.d. b.d. 0,66 BA34_2_5 Inclusion-free II 25,8 2,5 99 b.d. 120 322 16,5 62 b.d. 9,1 0,19 15,1 14,8 b.d. 13,4 b.d. b.d. b.d. 1,04 0,43 b.d. b.d. b.d. 0,25 BA34_2_6 Inclusion II 54,2 3,1 260 b.d. 81 274 4,3 29 b.d. 5,35 1,21 76 1,8 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA31_5_1 Inclusion II 229 11,5 1070 5,7 580 2930 10,5 b.d. b.d. 3,74 0,54 75 b.d. 3 5 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,28 BA31_5_2 Inclusion II 167 12,5 1250 b.d. 3400 1630 11,3 30 b.d. 11,7 7,9 367 b.d. b.d. 9 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,12 BA31_5_3 Inclusion II 310 35 480 b.d. 440 4160 6 b.d. b.d. 2,68 1,26 88 b.d. b.d. 20,9 b.d. 3,6 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA31_5_4 Inclusion II 72 5,1 800 b.d. 94 3590 3,16 39 b.d. 0,56 0,73 62 b.d. b.d. 4,5 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA31_3_1 Inclusion II 41,2 7,2 730 b.d. 395 3760 1,47 b.d. b.d. 2,21 3 116 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA31_3_2 Inclusion-free II 236 9 600 b.d. 273 6200 15,8 b.d. b.d. 3,3 0,2 18 1,5 4,5 5,3 b.d. 3,2 b.d. b.d. b.d. b.d. b.d. b.d. 0,33 BA31_9_1 Inclusion-free II 191 44 242 24,4 84 2900 9,8 b.d. b.d. 0,66 1,81 10 2,8 3,5 57 2 5,6 1,35 b.d. b.d. b.d. b.d. b.d. 0,36 BA31_9_2 Inclusion-free II 318 44,8 51 402 110 2010 13,3 b.d. b.d. 1,17 0,41 14 21,9 6,5 242 3,5 b.d. b.d. b.d. 0,56 b.d. b.d. b.d. 0,54 BA31_9_3 Inclusion II 155 219 446 b.d. 2740 2290 5,08 11 b.d. 6,6 4,1 40 2,38 b.d. 5,6 b.d. 2,7 b.d. b.d. 0,22 1,14 b.d. 0,08 0,14 BA31_9_4 Inclusion-free II 139 31,5 111 52 219 3200 25,4 31 b.d. 1,53 1,62 21,4 20,3 2,1 123 0,79 2,8 0,48 b.d. 2,2 0,79 b.d. b.d. 0,69 BA31_9_5 Inclusion II 530 290 540 10,4 282 1460 3,5 50 b.d. 1,42 6,2 28 b.d. 4,5 92 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA31_9_6 Inclusion II 80 171 660 b.d. 25,6 1500 1,91 b.d. b.d. 0,24 1,81 2,61 b.d. b.d. 10,2 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA33_4_1 Inclusion-free I 35 b.d. 460 b.d. 17,3 1430 1,9 216 b.d. 0,25 b.d. 2,86 b.d. b.d. b.d. b.d. 3,6 b.d. 0,6 b.d. b.d. b.d. b.d. b.d. BA33_4_2 Inclusion-free I 6,5 b.d. 264 b.d. 27,9 930 1,45 130 b.d. 0,36 b.d. 0,93 b.d. b.d. 2,29 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA33_4_3 Inclusion-free I 1,68 b.d. 730 b.d. 51 3130 2,9 260 b.d. 0,12 b.d. 1,47 b.d. b.d. 5 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,19 82

Co Ni Cu Zn Pb As Sb Se Te Bi Au Ag V Cr Mn Ga Ge Sn Mo W Cd Hg In Tl Analysis ID Profile Group [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] BA33_4_4 Inclusion I 80 5,8 295 b.d. 143 595 18,9 720 b.d. 0,76 0,13 27,5 13 4,1 26,3 b.d. b.d. b.d. b.d. 1,45 b.d. b.d. b.d. 0,19 BA33_4_5 Inclusion-free I 3,8 b.d. 1860 b.d. 80,6 8110 11,6 470 b.d. 0,16 0,74 52,1 b.d. b.d. b.d. b.d. 1,16 b.d. b.d. b.d. b.d. b.d. b.d. 0,12 BA33_4_6 Inclusion-free I 19,4 1,4 1360 b.d. 48 5680 0,96 40 b.d. 0,27 0,59 21,5 b.d. b.d. 33,8 b.d. 3,4 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA33_4_7 Inclusion-free I 8,4 1,5 1090 b.d. 18,4 2350 1,9 b.d. b.d. 0,23 0,26 28 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,13 BA33_4_8 Inclusion I 50 5,9 840 b.d. 242 3010 6,1 280 b.d. 0,95 3,1 137 b.d. b.d. 27 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA33_18_1 Inclusion-free I 19,3 2 2,32 b.d. 3,01 216 0,75 96 b.d. b.d. b.d. 0,71 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA33_18_2 Inclusion-free I 25,7 4,3 248 b.d. 337 2160 28,3 49 b.d. 0,53 2,06 105 3,8 b.d. 7,2 b.d. 2,8 b.d. b.d. b.d. b.d. b.d. b.d. 1,44 BA33_18_3 Inclusion-free I 1,3 b.d. 75 b.d. 73 3940 12,2 b.d. b.d. b.d. 0,48 67 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,18 BA33_18_4 Inclusion-free I 14,5 2,6 205 b.d. 253 3280 10,7 25 b.d. 0,36 0,99 62,1 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,53 BA33_18_5 Inclusion I 25,6 6,5 1480 b.d. 6500 1440 14,7 39 b.d. 14,8 1,12 80 3,1 b.d. 4,4 b.d. b.d. b.d. b.d. 0,18 b.d. b.d. b.d. 0,26 BA33_18_6 Inclusion I 13,2 5,9 2700 b.d. 137 3390 5,4 15 b.d. 0,43 0,26 28,9 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA33_18_7 Inclusion I 126 8,5 446 b.d. 910 1450 59,3 54 b.d. 3,04 3,6 177 24,2 b.d. 14 b.d. b.d. 0,93 b.d. 1,7 b.d. b.d. b.d. 2,4 BA33_18_8 Inclusion I 62 4,4 202 b.d. 250 663 7,6 58 b.d. 0,61 7,3 330 b.d. b.d. b.d. b.d. 3,1 b.d. b.d. b.d. b.d. b.d. b.d. 0,19 BA20_1a_1 Inclusion III 48,1 41,4 253 b.d. 4500 534 3 b.d. b.d. 7 2,21 640 2 4,2 b.d. b.d. 3,6 b.d. b.d. b.d. 1,11 b.d. b.d. b.d. BA20_1a_2 Inclusion III 178 308 1350 b.d. 11600 256 61 75 1,6 20,7 15,7 2540 b.d. 2,7 b.d. b.d. b.d. b.d. b.d. b.d. 3,5 b.d. b.d. b.d. BA20_1a_3 Inclusion III 121 179 35 b.d. 14,7 309 b.d. b.d. b.d. b.d. 0,55 45 b.d. b.d. 23 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_1a_4 Inclusion III 186 188 4420 b.d. 740 702 98 23 b.d. 1,25 2,3 940 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1,96 b.d. b.d. 0,1 BA20_1a_5 Inclusion III 296 480 3740 b.d. 413 1520 15,1 54 2,7 0,67 9,1 1570 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_1b_1 Inclusion III 174 110 34 b.d. 85 47,4 2,47 14 1,01 0,38 4,4 530 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1,47 0,66 b.d. b.d. BA20_1b_2 Inclusion III 600 348 4370 b.d. 3700 386 17,7 203 7,6 7 179 23100 b.d. b.d. 3,5 b.d. b.d. 0,78 b.d. b.d. 6,4 b.d. b.d. b.d. BA20_1b_3 Inclusion III 189 28 880 b.d. 85 114 3,7 52 1,01 0,46 15 1420 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1,7 b.d. b.d. b.d. BA20_4_1 Inclusion-free III 9,1 7,7 169 b.d. 2,3 48 b.d. 42 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_4_2 Inclusion-free III 1,16 b.d. 19,3 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_4_3 Inclusion III 27 49,6 46 b.d. b.d. 259 b.d. b.d. b.d. b.d. b.d. 5,1 b.d. b.d. b.d. b.d. 4,9 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_4_4 Inclusion-free III 30,8 41 322 b.d. 1,3 461 b.d. 36 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_4_5 Inclusion III 15,7 40,1 267 b.d. 72000 39 8,8 55 b.d. 110 0,17 91 b.d. b.d. b.d. b.d. 4,9 b.d. b.d. b.d. 33,6 b.d. b.d. b.d. BA20_4_6 Inclusion III 219 181 10500 410 84000 2560 4600 790 2,9 135 126 52000 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 40,1 b.d. b.d. 0,2 BA20_4_7 Inclusion III 50 127 1500 b.d. 3,3 500 19 39 b.d. b.d. 0,23 320 b.d. b.d. b.d. b.d. 3,1 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_4_8 Inclusion-free III 11,9 10,7 145 b.d. 1,03 135 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_4_9 Inclusion III 74 37 191 b.d. b.d. 93 b.d. 32 b.d. b.d. b.d. 2,1 b.d. b.d. b.d. b.d. 4,8 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA20_4_10 Inclusion III 55 8,7 151 b.d. 7,9 41,2 1,11 27 b.d. b.d. 5,7 430 b.d. b.d. b.d. b.d. 4,4 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA33_6_1 Inclusion-free I 60,5 32,9 2030 b.d. 79,1 4150 6,7 16,1 b.d. 1,17 1,68 176 b.d. b.d. b.d. b.d. 2,6 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA33_6_2 Inclusion-free I 2,8 b.d. 1340 5,5 19,3 5180 3,8 b.d. b.d. 0,19 0,13 14,2 b.d. b.d. b.d. b.d. b.d. 0,86 b.d. b.d. b.d. 0,51 b.d. 0,13 BA33_6_3 Inclusion I 21 7,5 1170 b.d. 60 4110 4,6 b.d. b.d. 0,39 0,18 23,8 1,05 2,9 2,7 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,12 BA33_6_4 Inclusion I 33,5 4,1 103 b.d. 9,5 670 b.d. 21 b.d. 0,08 0,06 12,5 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA33_6_5 Inclusion-free I 26,3 3,8 1530 b.d. 229 3210 10,1 b.d. b.d. 0,67 1,65 133 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,26 BA33_6_6 Inclusion I b.d. b.d. 430 b.d. 3,1 2340 b.d. b.d. b.d. 0,11 0,3 12,8 b.d. b.d. b.d. b.d. 2,3 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA33_6_7 Inclusion I 6,7 b.d. 42 b.d. 5,1 410 1,19 b.d. b.d. b.d. 0,25 36 b.d. 4,1 b.d. b.d. 3,1 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA33_6_8 Inclusion I 47 b.d. 420 b.d. 290 114 1,9 b.d. b.d. 1,36 5,4 253 b.d. b.d. b.d. b.d. 6,7 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA33_6_9 Inclusion-free I 50,3 26,6 1760 b.d. 73 2640 5,6 24 b.d. 1 1,7 137 b.d. 5,2 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,13 0,12 BA33_6_10 Inclusion I 29,7 12 420 b.d. 2370 217 3,3 22 b.d. 7,8 19,8 1000 b.d. 5,5 b.d. b.d. b.d. b.d. b.d. b.d. 0,86 b.d. b.d. b.d. BA33_6_11 Inclusion I 104 61 134 b.d. 16,5 243 2,6 31 b.d. 0,22 5 191 b.d. 4,6 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,13 BA33_7_1 Inclusion-free I 10,6 1,56 273 b.d. 24,8 5900 2,06 14 b.d. b.d. 4,48 11,2 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,14 BA33_7_2 Inclusion-free I 7,2 b.d. 630 b.d. 119 11700 12,5 b.d. b.d. 0,19 7,94 46 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA33_7_3 Inclusion-free I 46,2 4,7 2050 5,2 298 7550 26,5 19 b.d. 1,09 2,35 125 4,2 b.d. 3,3 b.d. b.d. b.d. b.d. 0,3 b.d. b.d. b.d. 0,31 BA33_7_4 Inclusion-free I 1,97 b.d. 1170 b.d. 136 1570 15 b.d. b.d. 0,21 0,23 53,7 b.d. b.d. b.d. b.d. b.d. 0,63 b.d. b.d. b.d. b.d. b.d. 0,29 BA33_7_5 Inclusion I 255 32,7 1170 b.d. 19800 890 38,1 77 b.d. 35,2 9,6 723 10,5 b.d. 11,6 b.d. b.d. b.d. b.d. b.d. 2,6 b.d. b.d. 0,57 BA33_7_6 Inclusion I 130 14,9 1160 b.d. 1680 1440 24,4 20 b.d. 6,82 4 169 6,5 b.d. 7,9 b.d. b.d. b.d. b.d. 0,32 3 b.d. b.d. 1,04 BA33_7_7 Inclusion I 24,8 10,3 580 b.d. 1150 530 56,7 23 b.d. 1,27 2,12 178 4,2 b.d. 3,5 b.d. 3,9 b.d. b.d. b.d. 2,4 1,41 b.d. 4,13 BA33_7_8 Inclusion-free I 7,5 1,6 245 b.d. 139 626 21,9 b.d. b.d. 0,16 0,26 58 b.d. 2,2 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1,36 BA33_7_9 Inclusion-free I 62,5 20,2 780 b.d. 752 1010 49,7 b.d. b.d. 0,92 2 194 3,9 3,2 7 b.d. 2,2 b.d. b.d. b.d. b.d. 0,74 b.d. 3,49 BA33_7_10 Inclusion I 76 22,8 1750 b.d. 920 508 27,2 b.d. b.d. 1,92 2,57 239 b.d. b.d. 4,22 b.d. 2 b.d. b.d. b.d. b.d. b.d. b.d. 1,19 BA33_7_11 Inclusion-free I 18,6 1,82 2240 b.d. 136 6880 8,3 b.d. b.d. 0,57 4,69 117 b.d. 1,5 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,16 BA33_7_12 Inclusion-free I 34,8 6,8 2600 b.d. 58 7300 3,5 22 b.d. 0,38 7 430 b.d. b.d. b.d. b.d. 3,6 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA33_7_13 Inclusion I 24,4 15,5 219 b.d. 8,4 560 1,26 32 b.d. b.d. 0,76 25 b.d. b.d. 24 b.d. 3 b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA33_8_1 Inclusion I 10,2 6,1 1000 b.d. 342 2190 22,5 b.d. b.d. 1,65 0,61 65 b.d. 8,6 b.d. b.d. b.d. 1,52 b.d. b.d. 2,1 b.d. b.d. 1,63 BA33_8_2 Inclusion I 76 7 430 b.d. 6560 889 26,1 18 b.d. 26,2 9,7 770 1,72 2,4 3,8 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1,17 BA33_8_4 Inclusion-free I 4,3 2,3 195 b.d. 297 372 29,7 b.d. b.d. 0,26 0,12 44,6 1,63 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 2,13 BA33_8_5 Inclusion-free I 4,3 2 307 b.d. 366 556 44,5 b.d. b.d. 0,49 0,7 100 2,71 b.d. 6,5 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 3,1 BA33_8_6 Inclusion-free I 4,1 7,1 159 b.d. 185 523 30,2 b.d. b.d. 0,56 0,16 44 b.d. b.d. 2,8 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 2,92 BA33_8_7 Inclusion-free I 22,7 4,3 880 b.d. 435 5560 17,4 b.d. b.d. 1,48 3,37 93 b.d. 2,7 11,4 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,58 83

Co Ni Cu Zn Pb As Sb Se Te Bi Au Ag V Cr Mn Ga Ge Sn Mo W Cd Hg In Tl Analysis ID Profile Group [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] BA33_8_8 Inclusion-free I 50 16 670 11,5 1500 1280 33,9 b.d. b.d. 5,4 7,1 519 4,7 8,9 132 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1,71 BA33_8_9 Inclusion-free I 38 2,5 1410 b.d. 393 4900 13,8 b.d. b.d. 3,08 8,5 286 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,11 0,22 BA33_10_1 Inclusion I 62 3,9 900 5 420 3660 11,2 29 b.d. 2,59 6,5 356 b.d. b.d. 4,6 0,76 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,17 BA33_10_2 Inclusion I 50,1 3 660 5,3 2750 860 24 19 b.d. 8 2,97 209 b.d. 2,2 3,7 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,18 BA33_10_3 Inclusion-free I 15 b.d. 132 b.d. 260 2200 8,4 b.d. b.d. 0,46 2,82 140 b.d. b.d. 6,5 b.d. 3,1 0,83 b.d. b.d. b.d. b.d. b.d. 0,2 BA33_10_4 Inclusion-free I 26 b.d. 197 b.d. 403 4170 5,4 28 b.d. 0,61 2,58 127 b.d. b.d. 5,9 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA33_10_5 Inclusion-free I b.d. b.d. 23,5 b.d. 126 3490 11,4 b.d. b.d. b.d. 0,34 60,8 b.d. b.d. 1,46 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,2 BA33_10_6 Inclusion-free I 8,1 1,05 488 b.d. 180 3320 8,8 22 b.d. 0,68 0,26 27,8 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,41 BA33_10_7 Inclusion I 26,2 2,8 890 b.d. 372 1960 14,1 b.d. b.d. 1,08 2,56 134 b.d. b.d. 1,68 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,24 BA33_12_1 Inclusion-free I 4,6 2,1 305 b.d. 55,7 634 7,3 12 b.d. b.d. 0,69 16,7 2,6 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,08 BA33_12_2 Inclusion I 9,4 2,28 1800 b.d. 88 1290 3,14 b.d. b.d. 0,49 1,81 86 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,06 BA33_12_3 Inclusion-free I 2,99 2,4 210 b.d. 12,1 8400 1,74 b.d. b.d. b.d. 2,92 16,2 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,13 BA33_12_4 Inclusion I 0,69 0,56 33,4 b.d. 6,17 4430 1,03 b.d. b.d. b.d. 2,2 21,2 b.d. 3,4 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,09 BA33_12_5 Inclusion I 72 20 770 b.d. 2340 771 30,2 21 b.d. 8,8 6 560 8,9 3,1 6,9 b.d. b.d. b.d. b.d. 0,36 b.d. b.d. b.d. 1,22 BA33_12_7 Inclusion-free I 9,8 b.d. 810 b.d. 111 6040 16 b.d. b.d. b.d. 2,69 122 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA33_12_8 Inclusion I 25 3,9 145 b.d. 790 1120 17,2 15 b.d. 1,89 3,2 161 2,4 b.d. 1,9 b.d. b.d. b.d. 0,68 0,26 b.d. b.d. b.d. 0,55 BA27_1_1 Inclusion II 130 57 240 b.d. 338 1590 33,2 240 b.d. 27,5 1,43 91 6 6 11,3 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,63 3,9 BA27_1_2 Inclusion II 493 330 4600 b.d. 3150 2860 393 46 b.d. 226 9,8 587 18,4 5,6 20,8 b.d. b.d. b.d. b.d. 3,1 b.d. 37,9 b.d. 18,2 BA27_1_3 Inclusion II 162 100 1990 b.d. 920 5260 278 16 b.d. 77 8,9 373 3 b.d. 9,9 b.d. b.d. b.d. b.d. b.d. b.d. 20,8 b.d. 12,5 BA27_1_4 Inclusion II 143 49 8800 25 1370 10700 52 180 b.d. 134 4,7 386 b.d. b.d. 11,7 b.d. b.d. b.d. b.d. 1,2 b.d. 11,2 b.d. 1,38 BA27_1_5 Inclusion II 120 95 490 b.d. 1370 6600 1820 70 b.d. 87 2,9 128 b.d. b.d. 20 b.d. b.d. b.d. b.d. b.d. b.d. 6 b.d. 41 BA27_1_6 Inclusion II 650 349 11200 24 2540 3970 174 46 b.d. 188 7,4 466 3 b.d. 16 b.d. 7,9 b.d. b.d. b.d. b.d. 16,8 0,29 17,1 BA27_2_1 Inclusion II 485 31 2350 b.d. 1730 4360 158 13 b.d. 60 1,22 87 b.d. 5,2 9,2 b.d. b.d. b.d. b.d. b.d. b.d. 18,5 b.d. 15,6 BA27_2_2 Inclusion II 321 66 1010 b.d. 2010 1070 26,7 137 b.d. 66 1,47 135 8,8 b.d. 7,8 b.d. b.d. 1,2 b.d. b.d. b.d. b.d. b.d. 0,72 BA27_4_1 Inclusion-free II 5,7 40 1220 b.d. 115 1650 b.d. 370 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. BA27_7_1 Inclusion-free II 100 61 311 16,3 980 1050 57 94 b.d. 11,4 1,09 85 b.d. b.d. 51 2,1 b.d. b.d. b.d. b.d. 7 52,6 b.d. 9,5 BA27_7_2 Inclusion-free II 124 116 192 14 1400 780 40,3 140 b.d. 38,6 2,65 178 b.d. b.d. 50 b.d. 5,2 b.d. b.d. b.d. 10,8 47 b.d. 7,5 BA27_11_1 Inclusion II 188 80 780 b.d. 1680 2540 24,4 b.d. b.d. 90 1,07 107 10,1 b.d. 1810 b.d. b.d. b.d. b.d. b.d. b.d. 10,8 0,41 5 BA27_12_1 Inclusion II 89 b.d. 300 b.d. 607 11000 36,6 41 3,6 34 0,83 86 3,4 b.d. 14,2 b.d. b.d. b.d. b.d. b.d. b.d. 3,4 b.d. 0,68 BA27_12_2 Inclusion II 7,6 b.d. 22 b.d. 60 13500 90 50 b.d. 3,2 b.d. 2 b.d. b.d. 16,9 b.d. b.d. 2,6 b.d. b.d. b.d. 9,5 b.d. 1,21 BA27_12_3 Inclusion II 100 40 800 13 1750 6700 1170 44 b.d. 80 3,23 135 b.d. b.d. 30,8 b.d. b.d. b.d. b.d. b.d. b.d. 214 b.d. 42,4

Co Ni Cu Zn Pb As Sb Se Te Bi Au Ag V Cr Mn Ga Ge Sn Mo W Cd Hg In Tl Detection Limit [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] Minimum 0,30 0,43 0,93 2,84 0,11 2,16 0,21 4,27 0,23 0,04 0,01 0,17 0,76 1,03 1,08 0,48 0,65 0,32 0,24 0,06 0,40 0,33 0,04 0,04 Maximum 7,93 13,99 21,58 87,52 15,41 40,38 7,24 155,92 12,40 1,13 0,65 4,32 19,09 23,85 27,92 8,52 24,41 8,57 9,32 2,14 19,53 11,06 2,19 1,24 Mean 0,82 1,43 2,31 7,45 1,00 4,61 0,82 13,71 1,08 0,11 0,06 0,44 1,71 2,22 2,38 1,15 3,00 0,74 1,36 0,29 1,74 1,15 0,14 0,11 Median 0,68 1,19 1,79 6,21 0,67 4,09 0,67 12,11 0,83 0,09 0,04 0,35 1,46 1,97 1,98 0,96 2,50 0,63 0,98 0,23 1,26 0,92 0,11 0,09

Co Ni Cu Zn Pb As Sb Se Te Bi Au Ag V Cr Mn Ga Ge Sn Mo W Cd Hg In Tl Absolute Error (±2σ) [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] Minimum 0,32 <0,01 0,92 1,30 0,16 4,10 0,16 4,50 <0,01 0,02 <0,01 0,14 0,42 1,50 0,52 0,27 <0,01 0,16 <0,01 <0,01 0,07 0,14 <0,01 <0,01 Maximum 160 250 3200 130 17000 3800 1400 4700 3 35 57 14000 8 13 280 3,6 8,2 5,4 4,2 1,6 120 30 0,48 10 Mean 23,01 19,31 225,84 5,44 462,81 302,59 13,14 68,28 0,45 1,92 1,81 227,26 1,35 3,76 4,07 0,71 1,61 0,49 0,48 0,55 1,88 1,03 0,06 0,29 Median 12,00 6,05 100,00 3,80 30,00 145,00 1,90 23,50 0,24 0,15 0,51 16,50 1,00 3,40 1,50 0,58 1,40 0,41 0,37 0,43 0,74 0,53 0,06 0,08

84

ANEXO H: Resultados de análisis LA-ICP-MS en calcopirita del Sistema Geotermal Cerro Pabellón

(b.d.: bajo el límite de detección)

Co Ni Zn Pb As Sb Se Te Bi Au Ag V Cr Mn Ga Ge Sn Mo W Cd Hg In Tl Analysis ID Profile [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] BA20_7_1 inclusion-free b.d. b.d. 261 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1620 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 12,7 6,8 0,76 b.d. BA20_7_2 inclusion-free b.d. b.d. 274 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1740 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 17,4 b.d. 0,71 b.d. BA20_7_3 inclusion-free b.d. b.d. 236 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1840 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 16,8 b.d. 0,93 b.d. BA20_7_4 inclusion-free b.d. b.d. 253 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1890 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 18,5 b.d. 0,91 b.d. BA20_7_5 inclusion-free b.d. b.d. 249 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1670 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 15,1 3,8 0,94 b.d. BA20_9_1 inclusion-free b.d. b.d. 194 5,4 b.d. b.d. b.d. b.d. b.d. b.d. 1327 b.d. 3,1 b.d. b.d. b.d. b.d. b.d. b.d. 12,8 b.d. 0,61 b.d. BA20_9_2 inclusion-free b.d. b.d. 216 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1440 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 12,8 b.d. 0,54 b.d. BA20_9_3 inclusion-free b.d. b.d. 222 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1350 b.d. 8,7 b.d. b.d. b.d. b.d. b.d. b.d. 14,5 b.d. 0,59 b.d. BA20_9_4 inclusion-free b.d. b.d. 188 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1312 b.d. b.d. b.d. b.d. 4,2 b.d. b.d. b.d. 14,6 b.d. 0,62 b.d. BA20_9_5 inclusion-free b.d. b.d. 211 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1570 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 12 b.d. 0,63 b.d. BA20_9_6 inclusion-free b.d. b.d. 266 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1800 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 13 b.d. b.d. b.d. BA20_13_1 inclusion-free b.d. b.d. 204 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1642 b.d. b.d. b.d. b.d. 4,6 b.d. b.d. b.d. 11 b.d. 0,72 b.d. BA20_13_2 inclusion-free b.d. b.d. 215 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1600 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 14,9 b.d. 0,58 b.d. BA20_13_3 inclusion-free b.d. b.d. 201 8,1 b.d. b.d. b.d. b.d. b.d. b.d. 1506 b.d. 11,6 b.d. b.d. b.d. b.d. b.d. b.d. 12,4 b.d. 0,65 b.d. BA20_13_4 inclusion-free b.d. b.d. 166 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1672 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 16,9 b.d. 0,64 b.d. BA20_13_5 inclusion-free b.d. b.d. 218 11,8 b.d. b.d. b.d. b.d. b.d. b.d. 1506 b.d. 7,8 b.d. b.d. b.d. b.d. b.d. b.d. 13,9 b.d. 0,44 b.d. BA20_15_1 inclusion b.d. b.d. 254 17,7 b.d. 4,4 b.d. b.d. b.d. b.d. 2040 b.d. b.d. b.d. b.d. 6,4 b.d. b.d. b.d. 17,6 b.d. 0,56 b.d. BA20_15_2 inclusion-free b.d. b.d. 250 b.d. b.d. 4,9 b.d. b.d. b.d. b.d. 2340 b.d. b.d. b.d. b.d. 8,3 b.d. b.d. b.d. 8,4 b.d. b.d. b.d. BA20_15_3 inclusion-free b.d. b.d. 190 3 b.d. b.d. b.d. b.d. b.d. b.d. 1720 b.d. 11,8 b.d. b.d. b.d. 1,47 b.d. b.d. 15,5 b.d. b.d. 0,22 BA20_15_4 inclusion-free b.d. b.d. 209 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1930 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 11,9 b.d. b.d. b.d. BA20_15_5 inclusion-free b.d. b.d. 216 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 2050 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 11 b.d. b.d. b.d. BA20_16_1 inclusion-free b.d. b.d. 210 1,45 b.d. b.d. b.d. b.d. b.d. b.d. 2051 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 12,1 b.d. 0,33 b.d. BA20_16_2 inclusion-free b.d. b.d. 243 0,84 b.d. b.d. 16 b.d. b.d. b.d. 2038 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 18,2 b.d. 0,16 b.d. BA20_16_3 inclusion-free b.d. b.d. 226 1,45 b.d. 1,08 b.d. b.d. b.d. b.d. 1970 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 16,5 b.d. 0,24 b.d. BA20_16_4 inclusion b.d. b.d. 239 19,7 b.d. 1,02 b.d. b.d. b.d. b.d. 1937 b.d. b.d. b.d. b.d. b.d. 1,27 b.d. b.d. 16,8 b.d. 0,72 b.d. BA20_16_5 inclusion-free b.d. b.d. 216 0,95 b.d. b.d. b.d. b.d. b.d. b.d. 2057 b.d. b.d. b.d. b.d. b.d. 1,43 b.d. b.d. 13,3 b.d. 0,54 b.d. BA20_17_1 inclusion-free b.d. b.d. 252 1,4 b.d. b.d. b.d. b.d. b.d. b.d. 1760 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 16,7 b.d. 0,67 b.d. BA20_17_2 inclusion-free b.d. b.d. 254 1 b.d. b.d. b.d. b.d. b.d. b.d. 1800 b.d. b.d. b.d. 2,3 b.d. b.d. b.d. b.d. 19,5 b.d. 0,93 b.d. BA30_8_1 inclusion-free 29,1 10,9 98 2,6 b.d. b.d. 740 b.d. b.d. b.d. 153 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 5,4 1,49 b.d. BA30_8_2 inclusion 51,5 b.d. 620 56,7 360 1480 590 b.d. 46 0,39 366 b.d. 9 21 b.d. b.d. b.d. b.d. b.d. 40 b.d. 1,69 1,9 BA30_9_1 inclusion-free b.d. b.d. b.d. 9,1 85 15 190 b.d. 1,61 1,23 820 b.d. 15 b.d. b.d. b.d. b.d. b.d. b.d. 9,7 b.d. 1,51 1,34 BA30_9_2 inclusion b.d. b.d. 101 64 53 39,3 20 b.d. 6,9 1,53 489 104 15 86 13,4 b.d. 5 b.d. 5 11,3 b.d. 1,86 2,4 BA34_1_5 inclusion-free 2,7 b.d. 169 25,2 15,1 b.d. b.d. b.d. b.d. b.d. 904 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 35 b.d. 0,64 b.d. BA34_14_1 inclusion b.d. b.d. 120 80,2 53,6 2 b.d. b.d. 0,72 b.d. 1270 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 15,6 b.d. 2,7 b.d. BA34_14_2 inclusion-free 2,3 b.d. 128 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1256 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 14,8 b.d. 2,4 b.d. BA34_14_3 inclusion-free 2,4 b.d. 136 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1208 b.d. 4 b.d. b.d. b.d. 1,35 b.d. b.d. 14,8 b.d. 2,11 0,23 BA34_14_4 inclusion 2,72 b.d. 116 6,9 b.d. 1,54 15 b.d. 0,244 b.d. 1180 b.d. 5,1 b.d. b.d. b.d. 1,71 b.d. b.d. 16,1 b.d. 2,39 b.d. BA34_14_5 inclusion-free b.d. b.d. 117 b.d. b.d. b.d. b.d. b.d. b.d. b.d. 1160 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 12,3 b.d. 2,3 b.d. BA34_20_1 inclusion-free 2,7 b.d. 129 5,1 65 5,8 69 b.d. 1,63 0,36 755 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 50 b.d. b.d. 0,28 BA48_5_1 inclusion-free b.d. b.d. b.d. b.d. b.d. b.d. 640 b.d. b.d. b.d. 830 b.d. 47 b.d. b.d. b.d. b.d. b.d. b.d. 29,5 b.d. b.d. b.d. BA48_5_2 inclusion-free b.d. b.d. 150 b.d. b.d. b.d. b.d. b.d. 1,6 b.d. 764 b.d. 152 b.d. b.d. b.d. b.d. b.d. b.d. 29 b.d. b.d. b.d. BA48_6_1 inclusion-free b.d. b.d. b.d. b.d. 32 b.d. b.d. b.d. 0,61 b.d. 698 b.d. b.d. b.d. b.d. 28 5 b.d. b.d. 26,7 b.d. b.d. b.d. BA48_6_2 inclusion-free b.d. b.d. b.d. 5,7 b.d. b.d. b.d. b.d. 0,46 b.d. 769 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 24,2 b.d. b.d. b.d. BA48_10_1 inclusion b.d. b.d. b.d. 18 b.d. b.d. b.d. b.d. 3 b.d. 650 b.d. b.d. b.d. b.d. b.d. b.d. 10,7 b.d. 17 10,3 3,9 b.d. BA48_10_2 inclusion 11,5 b.d. b.d. 31 b.d. b.d. 190 b.d. 4,2 44 9600 19 b.d. 37 b.d. b.d. b.d. 17,2 b.d. 24,5 b.d. 5,2 b.d. BA48_14_1 inclusion-free b.d. b.d. b.d. 4,6 16 b.d. 320 b.d. 1,77 b.d. 830 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 28,1 6,1 1,21 b.d. BA48_14_2 inclusion-free b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 0,62 b.d. 640 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 13,3 b.d. 2,6 b.d. BA48_15_1 inclusion b.d. b.d. 64 73 b.d. 8,1 680 8,3 8,9 10,1 4300 b.d. b.d. 20 b.d. b.d. b.d. b.d. b.d. 28,4 b.d. 3,6 b.d. BA48_15_2 inclusion b.d. b.d. b.d. 4,8 b.d. b.d. 70 b.d. 1,77 b.d. 830 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 30 b.d. 5,7 b.d. BA48_15_3 inclusion-free b.d. b.d. b.d. b.d. b.d. b.d. 500 b.d. b.d. b.d. 779 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 33 b.d. 3,7 b.d. BA48_17_1 inclusion 5,5 b.d. 58 34 b.d. b.d. 490 b.d. 15 5,3 2560 b.d. 19 b.d. b.d. b.d. b.d. b.d. b.d. 29,1 b.d. 1,94 b.d. BA48_17_2 inclusion b.d. b.d. 59 570 b.d. b.d. 390 b.d. 72 12,7 4200 b.d. b.d. b.d. b.d. b.d. b.d. 4,3 b.d. 29,1 b.d. 1,68 b.d. BA48_17_3 inclusion-free b.d. 23 b.d. b.d. b.d. b.d. 280 b.d. b.d. b.d. 1050 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 19 b.d. 3,6 b.d. BA48_17_4 inclusion b.d. b.d. 73 314 b.d. b.d. 820 b.d. 34 26 8100 b.d. b.d. b.d. b.d. b.d. b.d. b.d. b.d. 27 b.d. 3,8 b.d. 85

Co Ni Zn Pb As Sb Se Te Bi Au Ag V Cr Mn Ga Ge Sn Mo W Cd Hg In Tl Detection Limit [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] Minimum 1,00 1,21 7,89 0,54 6,63 0,72 8,89 0,89 0,11 0,04 0,51 2,14 2,76 2,41 1,48 2,76 1,05 0,89 0,24 1,64 2,27 0,15 0,08 Maximum 22,27 36,20 139,23 180,88 97,16 28,15 78,55 19,04 1,32 1,45 8,74 43,88 28,16 51,15 26,79 71,17 15,18 18,55 6,09 21,50 22,49 3,58 1,55 Mean 3,76 7,24 29,99 6,78 17,65 5,03 18,50 4,58 0,31 0,38 1,78 7,01 6,61 10,29 5,11 14,56 3,08 5,48 1,38 4,00 5,12 0,64 0,34 Median 1,85 3,80 15,22 2,81 11,62 4,32 14,12 2,36 0,19 0,29 1,37 3,54 4,99 6,81 2,59 6,40 1,90 4,78 0,58 2,99 4,27 0,41 0,23

Co Ni Zn Pb As Sb Se Te Bi Au Ag V Cr Mn Ga Ge Sn Mo W Cd Hg In Tl Associated Error [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] Minimum 0,47 <0,01 15,00 <0,01 2,80 0,33 2,70 <0,01 0,02 <0,01 23,00 0,95 4,50 1,50 0,66 0,01 0,49 <0,01 <0,01 2,10 0,95 0,14 <0,01 Maximum 12,00 21,00 230,00 320,00 100,00 500,00 1100,00 15,00 31,00 12,00 3000,00 39,00 84,00 32,00 17,00 28,00 11,00 9,40 3,50 14,00 12,00 2,30 1,10 Mean (±2σ) 2,21 1,99 35,94 10,29 16,09 11,46 145,43 1,57 1,57 1,34 286,35 5,19 12,88 6,41 3,18 5,29 1,96 1,84 0,70 5,36 3,15 0,53 0,13 Median (±2σ) 1,05 0,55 27,00 1,70 6,10 1,10 27,50 1,00 0,09 1,00 99,00 1,80 6,95 2,95 1,30 2,40 0,92 1,00 1,00 4,00 2,50 0,33 0,04

86