Boletín de la Sociedad Geológica Mexicana Volumen 67, núm. 3, 2015, p. 545-586 http://dx.doi.org/10.18268/BSGM2015v67n3a16

Control temporal y geología del magmatismo Permo-Triásico en Sierra Los Tanques, NW Sonora, México: Evidencia del inicio del arco magmático cordillerano en el SW de Laurencia

Harim E. Arvizu^1,*, Alexander Iriondo¹

¹ Centro de Geociencias, Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, Qro., 76230, México.

^* This email address is being protected from spambots. You need JavaScript enabled to view it.

Resumen

Sierra Los Tanques se localiza en el NW del Estado de Sonora, México y representa uno de los principales afloramientos de rocas graníticas permo-triásicas reportados en esa región. Geocronología U-Pb en zircón realizada en dos grupos de granitoides, los cuales afloran en el área de estudio y en diversas localidades del NW de Sonora, proporcionan un rango de edades entre 284 – 221 Ma. Las variedades litológicas predominantes son las granodioritas, seguido por las cuarzomonzodioritas y monzogranitos. Se pueden diferenciar dos suites principales: granitoides melanocráticos y leucocráticos. La relación de campo existente entre los dos tipos es que los melanocráticos son más antiguos ya que son intrusionados por los leucocráticos. Esta característica es corroborada, en la mayoría de los casos, por las edades U-Pb en zircón obtenidas de las muestras de ambas suites.

La mayoría de los zircones de los granitoides permo-triásicos indican altas concentraciones de U (~ 47 – 9508 ppm), pudiéndose así explicar las pérdidas de Pb apreciadas en muchos de los zircones analizados. Los zircones permo-triásicos muestran relaciones Th/U altamente variables (0.01 – 0.73). La morfología prismática típica, además de las zonaciones oscilatorias de crecimientos magmáticos observadas en las imágenes de catodoluminiscencia, sugieren un carácter ígneo para estos zircones. La presencia de edades proterozoicas, que corresponden a núcleos heredados como se muestra en las imágenes de catodoluminiscencia, se asocia al basamento meta-ígneo de ~ 1.7 – 1.6 Ga, ~ 1.4 Ga y ~ 1.1 Ga presente en la región, confirmado por las edades proterozoicas obtenidas de rocas de basamento para la zona de estudio.

Estos granitoides permo-triásicos asociados a subducción representan evidencia del inicio del magmatismo cordillerano en el SW de Laurencia instaurado a lo largo del borde oeste de Pangea, inmediatamente después de culminar la colisión entre Gondwana y Laurencia. Este magmatismo es importante para entender la evolución tectónica del NW de México, ya que regionalmente su ocurrencia se asocia tentativamente a una zona de debilidad cortical relacionada al basamento paleoproterozoico del Yavapai mexicano en el NW de Sonora. El entendimiento de este pulso magmático también es de particular importancia ya que representa una fuente regional de zircones detríticos permo-triásicos no reconocida anteriormente para cuencas sedimentarias mesozoicas y cenozoicas en Sonora y sur de Arizona.

Este pulso magmático, relacionado a los estadios iniciales de la subducción que propició el establecimiento de un arco magmático continental en el SW de Norteamérica, es parte de un gran evento a nivel cordillerano que se extiende desde el oeste-suroeste de Estados Unidos pasando por Sonora, Chihuahua y Coahuila a través del centro y sur de México y hasta el norte de Sudamérica.

Palabras clave: Sierra Los Tanques, permo-triásico, arco magmático continental, subducción, Laurencia.

Abstract

Sierra Los Tanques is located in NW Sonora, Mexico, and represents one of the main outcrops of Permo-Triassic granitic rocks reported in the region. U-Pb zircon geochronology conducted in two groups of granitoids from various locations in NW Sonora provide a range of ages between 284 – 221 Ma. Rock types are dominated by granodiorite, followed by quartzmonzodiorites, and monzogranites. There are two main granitic suites—leucocratic and melanocratic granitoids. Field relationships between the two types suggests that the melanocratic granitoids are older as they are clearly intruded by the leucocratic suite. This field evidence is supported, in most cases, by the U-Pb zircon ages obtained in samples of both granitic suites.

Most of the zircons from these Permo-Triassic granitoids have high U concentrations (~ 47 – 9508 ppm), suggesting significant Pb loss in their crystal structure. The Permo-Triassic zircons show highly variable Th/U ratios (0.01 – 0.73). These zircons have an igneous origin not only because of their prismatic morphologies, but also due to their oscillatory zoning characteristic of magmatic growth as observed in cathodoluminescence studies. The presence of inherited cores, as shown in cathodoluminescence images, can be associated with the ages of meta-igneous Proterozoic basement present in Sierra Los Tanques (~ 1.7 – 1.6 Ga, ~ 1.4 Ga and ~ 1.1 Ga) that could have been incorporated during magma-genesis in Permo-Triassic time.

These granitoids associated with subduction give evidence for the beginning of cordilleran arc magmatism in SW North America (Laurentia) established along the western margin of Pangea immediately following the latest stages of the collision between Laurentia and Gondwana. This Permo-Triassic magmatism is important for understanding the tectonic evolution of NW Mexico. Tentatively, the occurrence of this magmatism is associated with a zone of crustal weakness spatially associated with the Mexican Yavapai basement province in NW Sonora. Understanding this magmatic pulse is also of particular importance as it represents a regional source of detrital Permo-Triassic zircons previously unrecognized for Mesozoic and Cenozoic sedimentary basins in Sonora and southern Arizona.

Lastly, this Permo-Triassic subduction-related magmatic pulse present in NW Sonora is part of a larger magmatic arc event along the American Cordillera that extends from western–southwestern United States, passing through northern, central, and southern Mexico and reaching northern South America.

Keywords: Sierra Los Tanques, Permo-Triassic, continental magmatic arc, subduction, Laurentia.

1. Introducción

El arco magmático cordillerano del SW de Norteamérica es uno de los más conocidos e investigados, sin embargo, su inicio y evolución geodinámica regional son muy controvertidos. Hasta hace poco no se tenía conocimiento sobre el tiempo exacto del inicio de la subducción. Algunos estudios geológicos proponían que la convergencia a lo largo del margen continental pasivo del Paleozoico en el SW de los EUA se había originado durante el Permo-Triásico por la presencia de plutones graníticos con edades entre ~ 260 – 207 Ma (e.g., Burchfiel y Davis, 1972, 1975, 1981; Kistler y Peterman, 1973; Dickinson, 1981; Burchfiel et al., 1992), la mayoría de edad triásica intrusionando al Cratón Laurenciano (e.g., Barth y Wooden, 2006 y sus referencias). Sin embargo, algunos de estos plutones, en la parte norte y centro de California y en el oeste de Nevada, se piensa que están relacionados a un magmatismo de arco de islas formado paralelamente al margen continental, el cual a la postre se acreció contra el continente durante el Mesozoico (e.g., Snow et al., 1991; Bateman, 1992; Burchfiel et al., 1992; Miller et al., 1992, 1995; Dunne y Saleeby, 1993; Schweickert y Lahren, 1993; Barth et al., 1997). Por su parte, los plutones en la parte sur de California y en el oeste de Arizona se encuentran asociados a subducción y fueron emplazados dentro de basamento proterozoico e intrusionando su cubierta meta-sedimentaria paleozoica (Barth et al., 1997; Barth y Wooden, 2006).

La extensión de este cinturón plutónico hacia México dentro de Sonora había sido inferida pero no así localizada (e.g., Stewart et al., 1986; Riggs et al., 2003), sino hasta el descubrimiento de rocas graníticas de edad pérmica en la Sierra Pinta, en el NW de Sonora (Figura 1), en un rango de edad entre ~ 275 – 258 Ma (Arvizu et al., 2009a). De acuerdo a esto, Arvizu et al.(2009a) proponen que el inicio del margen continental activo del SW de Norteamérica está representado por la ocurrencia de este magmatismo pérmico en el NW de México.

Como resultado del trabajo exploratorio regional en el NW de Sonora se han localizado nuevos afloramientos de rocas plutónicas asociadas al pulso magmático pérmico (Figura 1). Estas ocurrencias de afloramientos de rocas graníticas de edad permo-triásica, que intruyen a rocas de basamento meta-ígneo paleoproterozoico (~ 1.7 – 1.6 Ga) de la provincia Yavapai mexicana (Iriondo y Premo, 2010) que forman parte del SW de Laurencia, han permitido contribuir y avanzar en el conocimiento geológico de este pulso magmático mediante su reciente estudio de caracterización geoquímica y temporal (e.g., Arvizu et al., 2009a; Arvizu-Gutiérrez, 2012; Velázquez-Santelíz, 2014).

En general, las características geoquímicas del magmatismo Permo-Triásico en el NW de Sonora, detalladas en algunos trabajos recientes (e.g., Arvizu et al., 2009a; Arvizu-Gutiérrez, 2012), indican una firma geoquímica de granitoides calco-alcalinos con alto potasio y de carácter peraluminoso a metaluminoso, típica de granitoides formados en un ambiente de arco magmático, aunque revelando la existencia de una contribución significativa de la corteza continental para su formación (Arvizu e Iriondo, 2011), específicamente del basamento meta-ígneo de edad paleoproterozoica presente en el NW de Sonora (e.g., Iriondo y Premo, 2010).

El área de estudio de la Sierra Los Tanques (Figura 1) representa geológicamente uno de los afloramientos de mayor extensión de rocas ígneas permo-triásicas encontradas hasta la fecha en el NW de México. En particular, representa una localidad interesante por la existencia de las rocas más jóvenes de este pulso magmático encontradas hasta el momento, comparadas con las localizadas en otros lugares del NW de Sonora donde únicamente se han reconocido rocas del Pérmico medio-tardío (e.g., Sierra Pinta, Sierra San Francisco, Sierra Blanca; Figura 1), permitiendo extender este pulso magmático en la región hasta el Triásico tardío (~ 221 Ma) de acuerdo a los resultados obtenidos en este estudio.

En este trabajo se presentan datos geocronológicos de U-Pb en zircón, además de cartografía geológica, de granitoides permo-triásicos de la Sierra Los Tanques. Estos nuevos datos, junto a los ya existentes en la región, permitirán documentar y constreñir, por ahora, el rango de edad de este importante pulso magmático de edad permo-triásica en el NW de Sonora asociado, tentativamente, al inicio de la subducción y formación del margen continental activo del SW de Norteamérica (e.g., Arvizu et al., 2009a).

Figura 1. Mapa geológico regional del NW de Sonora y SW de Arizona modificado de Iriondo et al. (2005).

2. Geología de la Sierra Los Tanques

2.1. Localización

La Sierra Los Tanques está localizada en la porción noroeste del estado de Sonora, a ~ 15 km al suroeste del poblado de Sonoyta y a ~ 100 km al noreste de la ciudad de Puerto Peñasco; específicamente se encuentra al este del campo volcánico El Pinacate de edad cuaternaria (Figura 1). Así mismo se encuentra ubicada dentro de la Reserva de la Biosfera El Pinacate, en la parte más oriental del Gran Desierto de Altar, justo al sur de la frontera con Arizona (Figura 2).

Figura 2. Mapa litológico sintetizado de Sierra Los Tanques (Sonora) a partir de la cartografía realizada en este estudio. La cartografía de Quitobaquito Hills (Arizona) y alrededores es a partir de mapas publicados por Campbell y Anderson (2003), Haxel et al. (1984) y SGM (2002).

2.2. Trabajos previos en el área de estudio

Los primeros estudios de cartografía geológica en Sierra Los Tanques fueron los realizados por el Servicio Geológico Mexicano (2002) y posteriormente los llevados a cabo por Campbell y Anderson (2003). Estos últimos estudios son los más detallados, los cuales demuestran la complejidad geológica de la zona de estudio que es avalada por las descripciones litológicas mostradas en las leyendas de los mapas geológicos presentados en su trabajo. El propósito de su estudio fue realizar una cartografía geológica-estructural que les permitiera describir las estructuras y cinemática presentes en las rocas mesozoicas y precámbricas milonitizadas que afloran en el área, sugiriendo que estas rocas se formaron a lo largo de una falla lateral izquierda, activa a finales del Jurásico (concepto de la hipotética Megacizalla Mojave-Sonora; Silver y Anderson, 1974; Anderson y Silver, 1979, 2005).

2.3. Descripción geológica y marco tectónico de las unidades litológicas

El área de estudio fue dividida en tres sectores principales: Sector NW, Central y SE (Figuras 2 – 5) con fines logísticos para llevar a cabo la cartografía geológica. A continuación se describen las unidades litológicas en orden cronológico.

Figura 3. Mapa geológico-litológico del Sector NW de Sierra Los Tanques a partir de la cartografía realizada en este estudio. La leyenda y explicación, además de la simbología, son las mismas que la Figura 2. En este mapa se observan, con estrellas de color verde, los puntos de muestreo para los análisis geocronológicos y geoquímicos, además el nombre de la muestra y su edad U-Pb en zircones.

Figura 4. Mapa geológico-litológico del Sector Central de Sierra Los Tanques a partir de la cartografía realizada en este estudio. La leyenda y explicación, además de la simbología, son las mismas que la Figura 2.

Figura 5. Mapa geológico-litológico del Sector Central y SE de Sierra Los Tanques a partir de la cartografía realizada en este estudio. La leyenda y explicación, además de la simbología, son las mismas que la Figura 2.

2.3.1. Proterozoico

2.3.1.1. Paleoproterozoico. Las rocas paleoproterozoicas presentes en la Sierra Los Tanques (Figuras 2 – 5) se encuentran como unidades litológicas de diversas composiciones constituidas principalmente por gneises bandeados cuarzo-feldespáticos de biotita, gneises de clorita-biotita y, en menor cantidad, paragneises de biotita y de dos micas incluyendo algunos esquistos y filitas de clorita-biotita-epidota. En algunas ocasiones, estas rocas se encuentran con intercalaciones de anfibolitas con espesor variable.

Los afloramientos principales de esta unidad litológica se encuentran en el sector sureste de la Sierra Los Tanques, en donde se ubican los afloramientos de mayor extensión y algunas exposiciones aisladas afloran en el sector central y noroeste (Figura 2). En varias localidades, principalmente en el sector sureste, esta unidad gnéisica paleoproterozoica aflora casi siempre como remanentes en o dentro de las rocas más jóvenes (granitoides permo-triásicos) a manera de techos colgantes (roof pendants) o como grandes bloques o xenolitos (Figuras 6 A y B).

La relación que tiene esta unidad con las rocas graníticas más jóvenes presentes en el área es de tipo intrusivo ya que la mayoría de los granitoides y pegmatitas-aplitas de edad permo-triásica se encuentran cortando perpendicular y/o sub-paralelamente a la foliación del basamento precámbrico (Figura 6C). En ocasiones también se observan bandas cuarzo-feldespáticas abudinadas (Figura 6D). Aunque en algunas zonas aún se preservan las texturas ígneas de los protolitos de estas rocas gnéisicas, en algunos otros lugares muestran una foliación milonítica (Figura 6E).

La foliación, localmente, está plegada a escala centimétrica y en algunas ocasiones a escalas mayores (Figura 6F). Las foliaciones del sector noroeste (Figura 3) muestran un patrón de rumbos entre 30° – 40° NW con echados entre 50° y 70° preferentemente hacia el NE. Por otro lado, el patrón que presentan las foliaciones en el sector sureste (Figura 5) es más homogéneo en rumbos y echados. Los rumbos predominantes de las foliaciones varían entre 10° y 30° NW, algunas veces N-S y echados entre 60° y 80° hacia el NE, y en ocasiones llegando a ser verticales. En el sector sureste, cerca del contacto con las rocas jurásicas por discordancia, las foliaciones no son tan homogéneas variando ligeramente sus rumbos y echados en diferentes direcciones, encontrándose algunos hacia el SW y otros hacia el NE, incluso algunos hacia el NW y SE (Figura 5). Estas diferentes orientaciones son interpretadas como plegamiento de estas unidades previamente foliadas.

Edades U-Pb en zircón determinadas en gneises bandeados de varios afloramientos ubicados en diferentes sectores del área de estudio (estrellas verdes en la Figura 2) oscilan entre 1763 y 1682 Ma (Arvizu-Gutiérrez, 2012). Este rango de edades es similar al resto de las rocas del basamento paleoproterozoico presente en Sierra Los Tanques (1747 – 1720 Ma; R. García, com. pers., 2015) y consistentes y correlacionables con rocas en otras regiones en el NW de Sonora (e.g., Iriondo et al., 2004; Nourse et al., 2005; Izaguirre et al., 2008; Arvizu et al., 2009b).

Figura 6. (A) Fotografías mostrando afloramientos representativos y relaciones de campo de la unidad gnéisica paleoproterozoica de Sierra Los Tanques. (A) y (B) Vistas panorámicas de dos afloramientos representativos ubicados en el sector central y sur, respectivamente, de Sierra Los Tanques, en donde se observa a la unidad gnéisica paleoproterozoica aflorando como remanentes sobre las rocas más jóvenes a manera de techos colgantes (roof pendants) o como grandes bloques o xenolitos dentro de las unidades graníticas permo-triásicas. (C) Segregaciones leucocráticas de diques pegmatíticos cortando a la foliación de la unidad gnéisica. También se observan bandas de la misma composición paralelas a la estratificación. (D) Bandas leucocráticas con textura pegmatítica abudinadas compuestas principalmente de cuarzo. (E) Afloramiento representativo de la unidad de gneises bandeados. Nótese que la foliación define una fábrica general gnéisica. (F) La deformación presente en esta unidad gnéisica es muy alta mostrándose en algunos sectores un fuerte plegamiento.

2.3.1.2. Mesoproterozoico. El magmatismo mesoproterozoico en la Sierra Los Tanques está representado por un pulso granítico de ~ 1.1 Ga (Iriondo et al., 2008); uno de los dos episodios de actividad magmática mesoproterozoica (~ 1.4 Ga y ~ 1.1 Ga) asociados posiblemente a rifting, que son conocidos regionalmente en el SW de Norteamérica (e.g., Anderson y Cullers, 1999; Goodge y Vervoort, 2006 y sus referencias).

El afloramiento principal de granitoides mesoproterozoicos se encuentra en Lomas El Berrendo ubicado en la porción oriental del área de estudio (Figura 2). Estos cuerpos intrusionan a rocas de basamento más antiguo de edad paleoproterozoica que tienen características y afinidad con corteza tipo Yavapai (e.g., Iriondo y Premo, 2010). Afloramientos aislados se encuentran en el sector sureste de la Sierra Los Tanques (Figura 5) en contacto discordante con las rocas metavolcánicas-metasedimentarias jurásicas (Figura 5). Un granito mesoproterozoico en la Sierra Los Tanques ha sido fechado en 1100 ± 8 Ma; edad ²⁰⁷Pb/²⁰⁶Pb en zircón determinada por Iriondo et al.(2008), y recientemente en otras localidades en un rango entre 1083 – 1064 Ma (estrellas amarillas en la Figura 2; R. García, com. pers., 2015).

2.3.2. Paleozoico-Mesozoico

2.3.2.1. Permo-Triásico. La unidad litológica predominante en la Sierra Los Tanques corresponde a un conjunto de granitoides permo-triásicos (Figuras 2 – 5). Las variedades litológicas presentes son las granodioritas y cuarzomonzodioritas, aunque también existen monzogranitos, monzodioritas, cuarzosienitas y cuarzomonzonitas (Tabla 1). Esta clasificación se detalla en el apartado de geoquímica en Arvizu-Gutiérrez (2012). Debido a la complejidad y a la gran diferenciación de los granitoides de esta unidad permo-triásica, estas rocas se pueden dividir en dos facies litológicas de acuerdo al índice de color (es decir, al contenido de minerales máficos y/o félsicos en la roca) en granitoides melanocráticos y leucocráticos. Petrográficamente también se pueden distinguir los dos grupos de granitoides, en general, ambos tipos de granitoides tienen texturas faneríticas a porfídicas con tamaños de grano medio a grueso, en algunas ocasiones con grandes fenocristales (Figuras 7 A y B). Algunos granitoides muestran texturas esquistosas-gnéisicas (Figuras 7 C y D) debido a la foliación incipiente producida por metamorfismo de bajo grado en facies de esquistos verdes asociado a un evento tectónico regional presente en el área de estudio de posible edad laramídica (R. García, com. pers., 2015). La plagioclasa, el cuarzo y el feldespato alcalino son las fases predominantes en la mayoría de los granitoides variando su contenido en mayor o menor proporción en cada una de las litologías presentes, aunque la plagioclasa tiende a ser la fase más dominante (Tabla 1). En menor cantidad se encuentran la hornblenda y la biotita (Figura 7E), las cuales son las fases máficas dominantes en los granitoides melanocráticos. Otro de los minerales comunes pero en los granitoides leucocráticos es la moscovita, típica de granitos peraluminosos. La moscovita es muy común en los granitoides leucocráticos y ocurre como mineral ígneo primario. Como mineral secundario reemplazando casi siempre al feldespato se observa mica blanca (Figuras 7 F y G). Algunos otros minerales secundarios, como la clorita y la epidota, también están presentes en algunas rocas, principalmente la clorita reemplazando a la biotita, y la epidota reemplazando a la plagioclasa y/o feldespato, igualmente en algunas ocasiones a la hornblenda (Figuras 7 H e I). Como minerales accesorios se encuentran principalmente el zircón, el apatito, la esfena o titanita y los minerales opacos como la magnetita-ilmenita, además del granate que es una fase mineral presente únicamente en los granitoides leucocráticos (Figuras 7 J, K y L).

Tabla 1. Localización de muestras, clasificación, arreglos minerales y edades U-Pb en zircones de granitoides permo-triásicos de Sierra Los Tanques, NW de Sonora, México.

Abreviaturas: Qtz = Cuarzo, Kfs = Feldespato potásico, Pl = Plagioclasa, Bt = Biotita, Ms = Moscovita, Ser = Sericita, Hbl = Hornblenda, Ep = Epidota, Chl = Chlorita, Ap = Apatito, Grt = Granate, Ttn = Titanita, Zrn = Zircón.
Min. Op. = Minerales opacos, F.A. = Feldespato Alcalino. N.D. = No Determinado.
^†Lat. = Latitud, Long. = Longitud. DATUM WGS84.
^*Edades ²⁰⁶Pb/²³⁸U de zircones determinadas en este estudio por técnica de ablación laser (LA-ICPMS) reportadas a precisión 2σ.

El conjunto de granitoides permo-triásicos intrusionan a la unidad metamórfica paleoproterozoica de gneises bandeados cuarzo-feldespáticos. Se observan cuerpos graníticos que intrusionan sub-paralelamente a la foliación de los gneises bandeados, y en algunas ocasiones se ve cortando perpendicularmente a ésta (Figura 8A). También se aprecian pequeños bloques, a manera de enclaves, de la unidad gnéisica paleoproterozoica dentro de las masas graníticas leucocráticas (Figura 8B).

En los afloramientos de esta unidad granítica en el sector noroeste (Figura 3), las foliaciones presentan un patrón de rumbos E-W (85° NW – 80° NE) con echados variables entre 30° – 60° con dirección preferentemente hacia el SW. En algunas zonas los granitoides muestran un diferente patrón de foliaciones con rumbos NW-SE, específicamente 20° – 45° NW con echados entre 30° – 70° hacia el NE (Figura 3). Esta orientación de foliaciones también está presente en las rocas gnéisicas paleoproterozoicas que se encuentran dentro de esta unidad a manera de bloques o xenolitos o simplemente como basamento. Por su parte, los granitoides en el sector central (Figura 4) tienen un patrón homogéneo de foliaciones con rumbos NW-SE y echados entre 30° – 60° hacia el SW, preferentemente. En el sector sureste de la Sierra Los Tanques (Figura 5) se encuentra la mayor extensión de afloramientos de granitoides permo-triásicos. En esta zona las foliaciones de las rocas tienen rumbos NW-SE con echados hacia el SW. También existe un patrón de foliación diferente con rumbos N-S, variando 5° – 10° NW con echados entre 45° – 65° hacia el E-NE, foliación similar a las de las rocas de basamento paleoproterozoico presentes en la zona. En la porción central del sector sureste las foliaciones en los granitoides siguen siendo N-S con echados hacia el E-NE, mientras que en la porción más oriental, el patrón principal de las foliaciones cambia a rumbos NW-SE con echados hacia el SW, aunque existen rumbos N-S y echados contrarios hacia el E-NE (Figura 5) debido a que la deformación presente en esa zona está representada por plegamientos de la foliación.

Los dos grupos de granitoides, melanocrático y leucocrático, no presentan ninguna distribución preferencial espacialmente aunque en un afloramiento en el sector sureste de la sierra (Figura 5), los granitoides melanocráticos son más abundantes y son claramente intrusionados por los leucocráticos, cortando subparalelamente y, en algunas ocasiones, perpendicularmente a su foliación. En esa zona en la parte más sureste de la Sierra Los Tanques justo al norte de la Sierra Cipriano (Figura 5), existe un afloramiento de gran importancia que se denominó como afloramiento Cerro Microondas, en donde se observan relaciones de campo interesantes entre las unidades permo-triásicas que ejemplifican la deformación pérmica-triásica presente en esa zona. En general, abundan los granitoides leucocráticos foliados de moscovita y granate, aunque existe una cantidad importante de granitoides melanocráticos (granodioritas y cuarzomonzodioritas de hornblenda y biotita), los cuales son cortados subparalelamente a su foliación por los leucocráticos (Figuras 8 C y D). Estas dos unidades, a su vez, son cortadas por diques pegmatíticos-aplíticos (Figuras 8 E y F) de edad permo-triásica (estrellas amarillas en las Figuras 2 y 5; R. García, com. pers., 2015), los cuales contienen abundante granate. En algunas zonas, se observan bloques y/o xenolitos de la unidad melanocrática dentro de la leucocrática. En ambas unidades graníticas permo-triásicas también existen bloques o xenolitos de la unidad gnéisica paleoproterozoica, la cual es cortada por los granitoides melanocráticos y leucocráticos, y por los diques leucocráticos aplíticos-pegmatíticos. De la unidad melanocrática se realizaron fechamientos U-Pb en zircón proporcionando edades entre 267 – 250 Ma (R. García, com. pers., 2015; Figuras 2 y 5).

El conjunto de diques de aplitas-pegmatitas, que cortan a los granitoides permo-triásicos y a los gneises bandeados paleoproterozoicos, generalmente se presentan a una escala menor de unos pocos centímetros de espesor hasta ~ 1 m, pero sin llegar a ser cartografiables. Las aplitas son de color blanco y de grano medio a fino (0.5 – 1.0 mm), compuestas principalmente por cuarzo y feldespato, con cantidades moderadas de moscovita y con menor abundancia de biotita; además muestran pequeñas cantidades de granate. Las pegmatitas presentan texturas porfídicas representadas por una matriz de grano fino a medio con grandes fenocristales de feldespato y plagioclasa y con moderada cantidad de granate. Ambos diques graníticos (aplíticos y pegmatíticos) comúnmente presentan forma tabular, a veces bifurcados. En algunas zonas muestran una foliación incipiente y, debido a la deformación presente en el área, a veces se muestran abudinados. Existen fechamientos U-Pb en zircón en tres muestras pegmatíticas-aplíticas, cuyas composiciones varían entre granodiorita, cuarzosienita y monzogranito, proporcionando edades permo-triásicas entre 261 – 251 Ma (R. García, com. pers., 2015; Figuras 2 y 5).

2.3.2.2. Jurásico Medio-Superior. En el área de estudio aflora una unidad metavolcánica-metasedimentaria del Jurásico Medio (R. García, com. pers., 2015), relacionado a la actividad de un arco magmático continental activo durante ese tiempo (Izaguirre-Pompa, 2009). Esta unidad está afectada por metamorfismo de bajo grado en facies de esquistos verdes y consiste principalmente en metariolitas y metandesitas. También están presentes rocas metavolcánicas esquistosas, filíticas y a veces gnéisicas con diferentes grados de deformación-milonitización. Los afloramientos de mayor extensión se localizan en la parte más oriental del área de estudio, en el sector sureste y en los alrededores del poblado de Sonoyta (Figuras 2 y 5). Por ejemplo, en la Sierra Los Tanques (Figura 5), esta unidad se encuentra en contacto discordante con las rocas más antiguas (unidad gnéisica paleoproterozoica) en la parte norte y más hacia el sur con la unidad granítica permo-triásica. Se han determinado edades U-Pb en zircón para los protolitos de estas rocas en un rango aproximado entre 176 – 164 Ma (R. García, com. pers., 2015; Figuras 2 y 5). Las foliaciones de esta unidad son variables predominando una familia con rumbos NW-SE y echados entre 40° – 80° hacia el NE. Algunas otras mediciones tienen buzamientos opuestos a esta familia debido a la deformación y plegamiento posteriores. Otro de los afloramientos de esta unidad jurásica se ubica en la parte noroeste de Lomas El Berrendo (Figura 2), en donde se expone una metariolita que está en contacto con la unidad de granito mesoproterozoico; en esa zona el contacto es de tipo intrusivo. Existe un fechamiento de U-Pb en zircones de ~ 180 Ma de una de estas rocas volcánicas (Campbell y Anderson, 2003) y otro más reciente, por el mismo método, de ~ 170 Ma (R. García, com. pers., 2015; Figuras 2 y 5).

2.3.2.3. Cretácico Superior. Extensos afloramientos de rocas graníticas de edad laramídica correspondientes al cinturón batolítico sonorense (e.g., Damon et al., 1983) afloran en los alrededores de la zona de estudio. Estas rocas varían entre granitos y monzogranitos de biotita o de dos micas, cuarzodioritas y cuarzomonzodioritas, predominando las granodioritas de biotita y/o hornblenda. Las expresiones más antiguas del magmatismo laramídico están representadas por pequeños cuerpos dioríticos ubicados en los sectores central y noroeste del área de estudio (Figuras 2, 3 y 4). El cuerpo más antiguo corresponde a una diorita de grano medio-grueso de ~ 78 Ma (R. García, com. pers., 2015) que corta a la unidad permo-triásica. Otros cuerpos corresponden a una cuarzomonzodiorita y una microdiorita con edades U-Pb en zircones determinadas por Arvizu-Gutiérrez (2012) de 75.4 ± 0.3 Ma y 72.7 ± 0.6 Ma, respectivamente, y que también intrusionan a rocas permo-triásicas. Existe también un fechamiento U-Pb en zircones de ~ 68 Ma (R. García, com. pers., 2015; ver estrellas de color amarillo en las Figuras 2 y 3) en una muestra de granito de biotita que corta localmente al basamento paleoproterozoico en el sector central (Figura 4). En la región también aflora un cuerpo granítico de edad laramídica de gran extensión llamado Cerro El Papalote (Figuras 2 y 3) en donde también existe un fechamiento U-Pb en zircones de ~ 73 Ma (R. García, com. pers., 2015; ver estrellas amarillas en las Figuras 2 y 3). Otras ocurrencias de este magmatismo del Cretácico Superior se localizan al sureste del área de estudio (Figura 2) en donde sobresalen dos grandes cuerpos graníticos que se identifican fácilmente por su elevada topografía; estos son la Sierra Cipriano y la Sierra Cubabi. En la Sierra Cipriano se han determinado edades U-Pb en zircones de ~ 68 Ma, mientras que para la Sierra Cubabi existen edades de cristalización de ~ 65 Ma (R. García, com. pers., 2015; ver estrellas amarillas para la ubicación en las Figuras 2 y 5). En la Sierra Cubabi, también se tiene el control temporal de aplitas y pegmatitas que cortan al plutón principal con edades de 62 y 59 Ma, respectivamente (R. García, com. pers., 2015). Estas edades más jóvenes, junto con la edad U-Pb en zircones determinada por Arvizu-Gutiérrez (2012) de 63.2 ± 0.6 Ma de una muestra de granito de dos micas, ubicada en el sector sureste de la Sierra Los Tanques (Figura 5), representan las expresiones del magmatismo laramídico más joven en la región.

Figura 7. Microfotografías mostrando el aspecto textural y la mineralogía general presentes en las muestras de granitoides permo-triásicos de Sierra Los Tanques. (A) y (B) Texturas representativas vistas en NX. La mayoría de las rocas muestran una textura fanerítica a porfídica con tamaño de grano de medio a grueso. Nótese en (A) la presencia de cristales equigranulares de plagioclasa, feldespato y cuarzo, y en (B) la presencia de un fenocristal de microclina. (C) y (D) Algunas rocas muestran texturas gnéisicas-esquistosas (en NX) producto del metamorfismo de bajo grado presente en esta unidad granítica. (E) Cristal de biotita visto en NX con colores de interferencia rosa, amarillo y verde de segundo orden. (F) y (G) Cristales de moscovita vistos en NX. Este mineral aparece comúnmente en los granitoides como mineral primario en (G), aunque en algunas ocasiones se encuentra alterada a clorita como en (F). (H) e (I) Algunos minerales secundarios, como la clorita y la epidota vistos en NX, también están presentes en los granitoides, frecuentemente la clorita reemplazando a la biotita como en (H), y la epidota a la plagioclasa y/o feldespato como en (I). (J) Cristales rómbicos de titanita o esfena con alto relieve vistos en NII. Mineral accesorio muy común en la mayoría de estas rocas graníticas. (K) Cristales de granate mostrando relieves altos vistos en NII y cuya presencia en los granitoides es variable. (L) Misma microfotografía pero tomada en NX en donde se observan totalmente en extinción los cristales de granate debido a su carácter isótropo.

Figura 8. (A) y (B) Fotografías mostrando afloramientos representativos y relaciones de campo entre la unidad gnéisica paleoproterozoica y la unidad granítica permo-triásica de Sierra Los Tanques. (A) Vista de un afloramiento representativo en donde se observa a la unidad granítica leucocrática intrusionando subparalelamente y, a veces, perpendicularmente a la foliación de las rocas del basamento paleproterozoico. (B) Cuerpos graníticos leucocráticos en forma de diques pegmatíticos-aplíticos cortando paralelamente a la foliación de la unidad gnéisica. También se observan bloques o enclaves de gneises bandeados dentro de las masas graníticas permo-triásicas. (C-F) Fotografías mostrando afloramientos representativos y las relaciones de campo existentes entre los granitoides melanocráticos y leucocráticos de Sierra Los Tanques. En todos los casos se evidencia y muestra que la unidad granítica melanocrática (rocas oscuras) es cortada por la leucocrática (rocas claras). Todos los afloramientos están ubicados en el sector sureste del área de estudio, en los alrededores del afloramiento denominada Cerro Microondas. (C) y (D) Afloramientos en donde se observa a la unidad granítica leucocrática intrusionando paralelamente a la foliación de la unidad melanocrática como en A, y en algunas ocasiones cortando perpendicularmente a ésta como en (D). (E) y (F) Cuerpos graníticos leucocráticos en forma de diques pegmatíticos-aplíticos cortando a la unidad granitoide melanocrática pérmica. En (F) se puede observar que un dique pegmatítico corta tanto a la unidad leucocrática como a la melanocrática. Estos cuerpos pegmatíticos-aplíticos también son de edad permo-triásica (R. García, com. pers.).

2.3.3. Cenozoico

2.3.3.1. Mioceno. La presencia de un pulso magmático miocénico en la Sierra Los Tanques está representado por rocas volcánicas de composición basáltico-andesítica y por lavas riolíticas (e.g., Cerro Los Vidrios; Figuras 2 y 3). Una muestra de riolita de Cerros Los Vidrios, ubicada en el sector noroeste de la Sierra Los Tanques (Figura 3), fue fechada por Arvizu-Gutiérrez (2012) por el método U-Pb en zircones proporcionando una edad de 14.17 ± 0.13 Ma. Otro fechamiento de esta misma unidad riolítica, realizado anteriormente por Vidal-Solano et al. (2008) por el método ⁴⁰Ar/³⁹Ar en roca total, arroja una edad similar de 14.23 ± 0.15 Ma. Más hacia el suroeste, aproximadamente a 5 km de Cerros Los Vidrios en la localidad de Los Vidrios Viejos (Figura 2) existe un fechamiento ⁴⁰Ar/³⁹Ar en obsidiana, también de esta unidad riolítica, de 14.27 ± 0.87 Ma (Vidal-Solano et al., 2008). Se ha determinado una edad de ⁴⁰Ar/³⁹Ar en matriz volcánica de un basalto en la parte norte del sector noroeste de la Sierra Los Tanques (Figura 3) de ~ 22 Ma (F. Paz, com. pers.). Una muestra de esta unidad basáltica fue fechada por Vidal-Solano et al.(2008) en 19.0 ± 0.9 Ma por el mismo método pero en plagioclasa. Estas unidades lávicas miocénicas presentan basculamientos variables como reacción al pulso extensional Basin and Range presente en la región, mostrando en general, rumbos NW-SE con echados variables (aprox. 30° – 40°) hacia el NE y SW.

2.3.3.2. Cuaternario. Las rocas basálticas de edad cuaternaria y de composición alcalina que constituyen el Evento Volcánico El Pinacate (e.g., Gutmann, 1976, 1977, 1979, 1986, 2002; Lynch, 1981; Lynch et al., 1993; Gutmann et al., 2000), son encontradas coronando la mayoría de los afloramientos de la región. Cubriendo discordantemente a las rocas más antiguas afloran depósitos no consolidados del Cuaternario, constituidos por coluvión, aluvión y eólicos compuestos principalmente de gravas, arenas, limos y arcillas distribuidos al pie de las montañas y algunos otros cubriendo los amplios valles y rellenando cuencas locales (Figuras 2 – 5). Los sedimentos arcillo-arenosos transportados por acción eólica forman y modelan grandes dunas de arena.

3. Geocronología U-Pb en zircón de granitoides permo-triásicos de la Sierra Los Tanques

3.1. Introducción

Un total de 12 muestras de granitoides permo-triásicos fueron fechadas por el método geocronológico U-Pb en zircón para determinar las edades de cristalización utilizando la técnica de Ablación Láser y Espectrometría de Masas con Plasma Acoplado Inductivamente (LA-ICPMS, Laser Ablation-Inductively Coupled Plasma Mass Spectrometry Ablación Láser y Espectrometría de Masas con Plasma Acoplado Inductivamente; ver técnica analítica en Suplemento Electrónico). Todas estas muestras representativas fueron seleccionadas de diversos afloramientos ubicados en diferentes sectores del área de estudio (Figuras 2 – 5) con el fin de obtener un mejor control temporal del evento permo-triásico. Un promedio de 35 zircones para cada muestra fueron seleccionados y utilizados para realizar los análisis in situU-Pb en zircón.

A continuación se describen de forma general, las características de los zircones analizados y los resultados geocronológicos U-Pb de las muestras. Los datos geocronológicos obtenidos (diagramas de concordia U-Pb), además de imágenes de catodoluminiscencia de algunos de los zircones fechados más representativos de cada muestra, donde se observa el punto de ablación y la edad obtenida en ese punto del zircón se muestran en las Figuras 9 – 12. Todos los datos se reportan en la Tabla SE1 en el Suplemento Electrónico. Por otro lado, en la Tabla 1 se enlista un resumen de las edades permo-triásicas obtenidas, además de la localización de muestras y mineralogía de las diferentes unidades graníticas fechadas.

3.2. Descripción de zircones

Alrededor de 100 granos de zircón de cada muestra fueron estudiados utilizando imágenes de luz reflejada y transmitida, además de imágenes de catodoluminiscencia. Algunas imágenes de zircones representativos de cada muestra son mostradas en las Figuras 9 – 12. Vistos en luz transmitida, los zircones de todas las muestras comparten características similares: tienen formas euhedrales a subhedrales, la mayoría son incoloros, algunos granos exhiben tonos amarillos, además, la mayoría de los cristales muestran inclusiones. Las morfologías de los zircones principalmente son prismas bipiramidales alargados con bordes y puntas bien definidas, algunas veces ligeramente redondeadas, con relaciones de aspecto entre 1:3 y 1:4. Algunos cristales exhiben morfologías prismáticas cortas y anchas (stubby prisms), aunque predominando las primeras. Los tamaños son variables entre 100 – 350 µm pero la mayoría rebasando los 200 µm y los más grandes con tamaños > 300 µm.

Por otro lado, las imágenes de catodoluminiscencia (Figuras 9 – 12 D, H y L) revelan la naturaleza ígnea de los zircones mostrando estructuras internas típicas de crecimiento magmático con una zonación oscilatoria bien definida para la mayoría de los zircones. La mayoría de estos muestra una buena luminiscencia, revelando zonaciones oscilatorias suavemente marcadas en algunos granos. Otros cristales no exhiben una clara zonación oscilatoria sino que muestran una zonación más homogénea. Se ablacionaron intencionalmente los dominios zonados para determinar la edad de cristalización de cada roca (Figuras 9 – 12 D, H y L; Tabla SE1). Otra característica muy común y distintiva de los zircones de estos granitoides permo-triásicos es la presencia significativa de semillas o núcleos heredados que se distinguen fácilmente por presentar una alta luminiscencia y por ser redondeados (Figuras 9 – 12 D, H y L). Más del 50 % de los zircones de cada muestra presentan esta característica. Cabe señalar, que algunas de estas herencias fueron confirmadas por las edades U-Pb individuales obtenidas de algunos zircones (> 1.0 Ga, predominando un rango aproximado entre 1.6 – 1.8 Ga) (Figuras 9 – 12 D, H y L; Tabla SE1). En la mayoría de los zircones se muestra alta luminiscencia y zonaciones magmáticas oscilatorias bien definidas, algunos otros granos solamente muestran un núcleo heredado bordeado por un dominio más oscuro rico en U como lo indican las altas concentraciones (ppm) de ese elemento (Figuras 9 – 12D, H y L; Tabla SE1). Algunos zircones muestran estructuras internas o texturas complejas no muy comunes en zircones magmáticos (Figuras 9 – 12 D, H y L), quizá producto de recristalización por metamorfismo o hidrotermalismo como lo revelan algunas de las relaciones muy bajas de Th/U (≤ 0.02, Tabla SE1).

3.3. Resultados

3.3.1. Granodiorita de biotita (TANW09-06)

El contenido de U es alto en un rango entre 277 – 2904 ppm y las concentraciones de Th varían de 56 – 419 ppm. Las relaciones Th/U varían de 0.06 – 0.27 (Tabla SE1). Se observan algunos zircones discordantes (2 – 14 %) que representan herencias con edades proterozoicas. Destaca la presencia de un zircón heredado con edad ²⁰⁷Pb/²⁰⁶Pb de 1700 ± 17 Ma (zircón/análisis 15, Figura 9A; Tabla SE1). Por otro lado, los análisis más jóvenes (Figura 9B) muestran una dispersión a lo largo de la línea de concordia con diferentes grados de discordancia, debido a que representan zircones que han sufrido pérdida de Pb, o en el caso de zircones más viejos, representan herencias. Se determinó una edad ²⁰⁶Pb /²³⁸U media ponderada de 257 ± 5 Ma (2s, MSWD = 2.4, n = 4; Figura 9C) para ésta granodiorita de biotita.

Figura 9. Datos analíticos de U-Pb obtenidos de zircones de granitoides pérmicos de Sierra Los Tanques utilizando la técnica de ablación láser (LA-ICP-MS). (A), (E) e (I) Gráficos de concordia tipo Tera-Wasserburg mostrando todos los datos de los zircones analizados de las muestras TANW09-06, GneisSur-1 y TANSE09-01. (B), (F) y (J) Acercamientos a los datos más jóvenes en donde se muestra la edad ²⁰⁶Pb/²³⁸U media ponderada calculada para cada muestra. Los análisis representados por las elipses y cuadrados de color negro fueron empleados para el cálculo de la edad media ponderada, mientras que los análisis en color gris (elipses y cuadrados) fueron descartados para este cálculo debido a que representan zircones con herencias y/o pérdida de Pb. (C), (G) y (K) Gráficos de media ponderada mostrando los análisis empleados para calcular la edad media ponderada. (D), (H) y (L) Imágenes de catodoluminiscencia de algunos zircones representativos de cada muestra, mostrando el lugar de ablación y debajo de cada zircón la edad determinada en ese punto del zircón.

3.3.2. Gneis de biotita (GneisSur-1)

Las concentraciones de U varían de 332 – 6125 ppm; las más altas pertenecen a los zircones más jóvenes a lo largo de la línea de concordia que han perdido Pb (Figura 9E), lo cual también es confirmado por los dominios más oscuros ricos en U (Figura 9H; Tabla SE1). El contenido de Th es bajo variando de 4 – 331 ppm, mientras que las relaciones Th/U tienen un rango entre 0.01 – 0.32. Se observa una población importante pero dispersa de zircones con edades permo-triásicas con diversos grados de discordancia (0 – 9 %) (Figura 9F). Algunos de estos análisis también representan la presencia de Pb común, efecto que puede deducirse cuando la edad ²⁰⁸Pb/²³²Th del zircón es más vieja que la edad ²⁰⁶Pb/²³⁸U (Tabla SE1). Los análisis relativamente concordantes (≤ 3 %), proporcionan una edad ²⁰⁶Pb/²³⁸U media ponderada de 255 ± 3 Ma (2s, MSWD = 2.3, n = 8; Figura 9G) que se interpreta como la edad de cristalización del protolito de esta roca gnéisica.

3.3.3. Granodiorita leucocrática de biotita y granate (aplita) (TANSE09-01)

Las concentraciones de U y Pb para los zircones son de 47 – 1479 ppm y 1 – 137 ppm, respectivamente, con relaciones Th/U entre 0.01 – 0.36 (Tabla SE1). Presencia de zircones heredados, identificados en las imágenes de catodoluminiscencia con edades proterozoicas entre 1.2 – 1.6 Ga (e.g., zircón/análisis 3, 6, 8, 19 y 25; Tabla SE1), ligeramente discordantes (1 – 5 %) (Figura 9I). Los datos más jóvenes de edad permo-triásica muestran una dispersión a lo largo de la concordia; algunos datos son relativamente concordantes (-2 a 2 %) y otros muestran pérdida de Pb (Figura 9J). Se determinó una edad ²⁰⁶Pb/²³⁸U media ponderada de 254 ± 2 Ma (2s, MSWD = 2.5, n = 5; Figura 9K), interpretada como la edad de cristalización de este leucogranito con granate.

3.3.4. Monzogranito de biotita (CG09-10)

Los contenidos de U son de 260 – 3584 ppm (Tabla SE1). Los valores más altos de 3584 ppm y 1908 ppm corresponden a los análisis más jóvenes (zircón/análisis 32 y 15; Tabla SE1) con pérdida de Pb, los cuales se muestran a lo largo de la concordia (Figura 10B). Las concentraciones de Th varían de 7 – 1505 ppm mientras que las relaciones Th/U se encuentran en un rango entre 0.01 – 0.73, predominando los valores > 0.1 (Tabla SE1), típicas de zircones magmáticos. Se observan zircones heredados de edad mesoproterozoica con diversos grados de discordancia (< 5 % y > 10 %, Tabla SE1). Cabe destacar la presencia de dos zircones concordantes (0 y 1%) con edades ²⁰⁷Pb/²⁰⁶Pb de 1090 ± 19 Ma y 1443 ± 18 Ma (Figura 10A). Los datos más jóvenes de edades permo-triásicas muestran una población de datos relativamente concordantes (Figura 10B) empleados para calcular una edad ²⁰⁶Pb/²³⁸U media ponderada de 254 ± 3 Ma (2s, MSWD = 1.9, n = 9; Figura 10C), la cual se interpreta como la edad de cristalización del monzogranito de biotita.

Figura 10. Datos analíticos de U-Pb obtenidos de zircones de granitoides pérmicos de Sierra Los Tanques utilizando la técnica de ablación láser (LA-ICP-MS). (A), (E) e (I) Gráficos de concordia tipo Tera-Wasserburg mostrando todos los datos de los zircones analizados de las muestras CG09-10, TANSE-09 y MICRO-3. (B), (F) y (J) Acercamientos a los datos más jóvenes en donde se muestra la edad ²⁰⁶Pb/²³⁸U media ponderada calculada para cada muestra. Los análisis representados por las elipses y cuadrados de color negro fueron empleados para el cálculo de la edad media ponderada, mientras que los análisis en color gris (elipses y cuadrados) fueron descartados para este cálculo debido a que representan zircones con herencias y/o pérdida de Pb. (C), (G) y (K) Gráficos de media ponderada mostrando los análisis empleados para calcular la edad media ponderada. (D), (H) y (L) Imágenes de catodoluminiscencia de algunos zircones representativos de cada muestra, mostrando el lugar de ablación y debajo de cada zircón la edad determinada en ese punto del zircón.

3.3.5. Granodiorita leucocrática de biotita (TANSE-09)

Las concentraciones de U oscilan de 207 – 4518 ppm (Tabla SE1). Los valores más altos de U (2165 – 4518 ppm) representan los análisis más jóvenes que han experimentado pérdida de Pb. El contenido de Th varía entre 28 – 551 ppm con relaciones Th/U en un rango entre 0.03 – 0.42, prevaleciendo los valores > 0.1 (Tabla SE1). Existe un número elevado de zircones heredados de edad proterozoica (1591 – 1758 Ma) con diferentes grados de discordancia (-2 % a 10 %) (Figura 10E). Se destaca la presencia de dos análisis concordantes con edades de 1351 ± 28 Ma y 1643 ± 20 Ma (Tabla SE1). Un acercamiento a los zircones más jóvenes de edad permo-triásica (Figura 10F) muestra una población de análisis relativamente concordantes (< 4 %), los cuales fueron empleados para calcular una edad ²⁰⁶Pb/²³⁸U media ponderada de 252 ± 3 Ma (2s, MSWD = 0.69, n = 7; Figura 10G) para este leucogranito de biotita. Los análisis más jóvenes no fueron utilizados para este cálculo debido a que representan zircones que han sufrido pérdida de Pb como lo indican las concentraciones altas de U (2165 – 4518 ppm; Tabla SE1).

3.3.6. Cuarzomonzodiorita de biotita (MICRO-3)

Las concentraciones de U y Th para los zircones analizados son de 394 – 4248 ppm y de 51 – 780 ppm, respectivamente, con relaciones Th/U que varían en un rango entre 0.08 – 0.25. Los valores más altos de U pertenecen a los análisis más jóvenes que pudieran representar zircones con pérdida de Pb. Se observa poca presencia de herencias, destacando un zircón heredado concordante con una edad ²⁰⁷Pb/²⁰⁶Pb de 1716 ± 18 Ma (Figura 10I). Un acercamiento a los análisis más jóvenes (Figura 10J) permite visualizar una gran dispersión de datos con diversos grados de discordancia, aunque existen algunos análisis relativamente más concordantes entre -1 % y 3 %. Se determinó una edad ²⁰⁶Pb^/238U media ponderada de 243 ± 2 Ma (2s, MSWD = 0.23, n = 5; Figura 10K) para la muestra de cuarzomonzodiorita de biotita. Los análisis más jóvenes claramente han sufrido pérdida de Pb como lo podrían indicar los elevados contenidos de U de esos zircones (Tabla SE1).

3.3.7. Granodiorita leucocrática de biotita (GranCen-5)

Los zircones tienen de moderadas a altas concentraciones de U y Th (395 – 2106 ppm y 26 – 827 ppm, respectivamente) con relaciones Th/U que varían entre 0.05 – 0.47, predominando los valores > 0.1 (Tabla SE1). Se observan algunos análisis altamente discordantes > 3 % (entre 3 – 22 %) que representan zircones heredados (e.g., zircón/análisis 18, 20, 21, 25 y 30) (Figura 11A). Un acercamiento a los análisis más jóvenes muestra una población de datos dispersos, relativamente concordantes (≤ 3 %) a lo largo de la línea de concordia (Figura 11B). Se determinó una edad ²⁰⁶Pb/²³⁸U media ponderada de 240 ± 3 Ma (2s, MSWD = 1.5, n = 5; Figura 11C) para la granodiorita leucocrática de biotita. El resto de los análisis, que se representan como elipses y cuadrados de color gris, no fueron usados para calcular la edad media ponderada debido a que representan zircones que han experimentado pérdida de Pb (análisis más jóvenes con altas concentraciones de U; Tabla SE1) y/o son zircones en donde simplemente se han muestreado dominios del zircón un poco más viejos.

Figura 11. Datos analíticos de U-Pb obtenidos de zircones de granitoides pérmicos de Sierra Los Tanques utilizando la técnica de ablación láser (LA-ICP-MS). (A), (E) e (I) Gráficos de concordia tipo Tera-Wasserburg mostrando todos los datos de los zircones analizados de las muestras GranCen-5, TANW09-01 y TANC09-04. (B), (F) y (J) Acercamientos a los datos más jóvenes en donde se muestra la edad ²⁰⁶Pb/²³⁸U media ponderada calculada para cada muestra. Los análisis representados por las elipses y cuadrados de color negro fueron empleados para el cálculo de la edad media ponderada, mientras que los análisis en color gris (elipses y cuadrados) fueron descartados para este cálculo debido a que representan zircones con herencias y/o pérdida de Pb. (C), (G) y (K) Gráficos de media ponderada mostrando los análisis empleados para calcular la edad media ponderada. (D), (H) y (L) Imágenes de catodoluminiscencia de algunos zircones representativos de cada muestra, mostrando el lugar de ablación y debajo de cada zircón la edad determinada en ese punto del zircón.

3.3.8. Granodiorita leucocrática de dos micas (TANW09- 01)

Los contenidos de U y Th para los zircones analizados son moderados variando de 18 – 1097 ppm y de 6 – 183 ppm, respectivamente, con relaciones Th/U 0.01 – 0.70 prevaleciendo valores > 0.1 (Tabla SE1). Existe la presencia de herencias, destacando la presencia de tres análisis concordantes (≤ 3 %) con edades ²⁰⁷Pb/²⁰⁶Pb de 1111 ± 52 Ma, 1476 ± 17 Ma y 1612 ± 17 Ma (Figura 11E). Otros tres análisis con discordancias altas, representan zircones con diferentes grados de herencia (e.g., zircón/análisis 3, 8 y 23 Figura 11E ; Tabla SE1). Un acercamiento a los análisis más jóvenes (Figura 11F) muestra una dispersión significativa a lo largo de la línea de concordia de los datos que son relativamente concordantes (- 1 % a 2 %). Una agrupación de análisis concordantes, representados por las elipses y cuadrados de color negro, fueron usados para el cálculo de una edad ²⁰⁶Pb/²³⁸U media ponderada de 238 ± 1 Ma (2s, MSWD = 1.8, n = 12; Figura 11G), interpretada como la edad de cristalización de esta granodiorita leucocrática de dos micas.

3.3.9. Granodiorita leucocrática de biotita (TANC09-04)

El contenido de U para los zircones analizados va de 66 – 2495 ppm y de Th va de 12 – 1302 ppm con relaciones Th/U que varían entre 0.07 – 0.59, predominando valores altos > 0.1 (Tabla SE1). Existe un gran número de zircones heredados de edades proterozoicas ²⁰⁷Pb/²⁰⁶Pb entre 1183 – 1934 Ma (Figura 11I), pero con diversos grados de discordancia (> 10 %, Tabla SE1). Los análisis más discordantes tienen valores entre 10 – 42 % de discordancia, mientras que los menos discordantes tienen valores < 5 % (Tabla SE1). Cabe destacar tres análisis concordantes (0 – 1 %) con edades ²⁰⁷Pb/²⁰⁶Pb de 1191 ± 20 Ma, 1598 ± 17 Ma y 1720 ± 17 Ma. En el acercamiento a los datos más jóvenes (Figura 11J) se observa una agrupación de análisis representados por elipses y cuadrados de color negro, que han sido empleados para calcular una edad ²⁰⁶Pb/²³⁸U media ponderada de 231 ± 1 Ma (2s, MSWD = 2.1, n = 6; Figura 11K), la cual es interpretada como la edad de cristalización de la granodiorita leucocrática de biotita.

3.3.10. Granodiorita leucocrática de biotita (LeucoCen-1)

Las concentraciones de U de los zircones van de 75 – 6455 ppm, algunas de las más altas corresponden a los análisis más jóvenes que se interpreta han sufrido pérdida de Pb. Por su parte, los contenidos de Th van de 3 – 1979 ppm con relaciones Th/U en un rango que varía de 0.01 – 0.60 (Tabla SE1). Se corrobora la existencia de varios zircones heredados que presentan diferentes grados de discordancia, destacando la presencia de tres análisis relativamente concordantes (< 2 %) con edades proterozoicas ²⁰⁷Pb/²⁰⁶Pb de 1058 ± 21 Ma, 1287 ± 29 Ma y 1688 ± 19 Ma (Figura 12A). Un acercamiento a los datos más jóvenes (Figura 12B) permite visualizar una dispersión de los análisis con diferentes grados de discordancia a lo largo de la línea de concordia. Una población de zircones concordantes (- 1 % a 1 %) permite calcular una edad ²⁰⁶Pb/²³⁸U media ponderada de 226 ± 5 Ma (2s, MSWD = 1.6, n = 5; Figura 12C) para este leucogranito de biotita. La agrupación de los análisis más jóvenes representa zircones que han experimentado una pérdida de Pb, como lo sugieren las concentraciones altas de U (1928 – 6455 ppm; Tabla SE1), comparadas con el resto de los análisis de esta muestra.

Figura 12. Datos analíticos de U-Pb obtenidos de zircones de granitoides pérmicos de Sierra Los Tanques utilizando la técnica de ablación láser (LA-ICP-MS). (A), (E) e (H) Gráficos de concordia tipo Tera-Wasserburg mostrando todos los datos de los zircones analizados de las muestras LeucoCen-1, GranCen-4 y GranCen-3. (B) y (E) Acercamientos a los datos más jóvenes en donde se muestra la edad ²⁰⁶Pb/²³⁸U media ponderada calculada para cada muestra. Los análisis representados por las elipses y cuadrados de color negro fueron empleados para el cálculo de la edad media ponderada, mientras que los análisis en color gris (elipses y cuadrados) fueron descartados para este cálculo debido a que representan zircones con herencias y/o pérdida de Pb. (C), (G) y (K) Gráficos de media ponderada mostrando los análisis empleados para calcular la edad media ponderada. (D), (H) y (L) Imágenes de catodoluminiscencia de algunos zircones representativos de cada muestra, mostrando el lugar de ablación y debajo de cada zircón la edad determinada en ese punto del zircón.

3.3.11. Granodiorita leucocrática de dos micas (GranCen-4)

Los zircones analizados tienen concentraciones altas de U entre 344 – 3118 ppm y contenidos de Th que varían de 36 – 549 ppm, con relaciones Th/U que van de 0.02 – 0.26 (Tabla SE1). Se observa una gran dispersión de los datos, los cuales poseen diferentes grados de discordancia (- 1 % a 19 %) (Figura 12E). Los análisis con edades más antiguas, altamente discordantes (> 10 %), representan zircones con algún grado de herencia. También existe una población de zircones más jóvenes, con mayor o menor grado de discordancia (aunque algunos muy concordantes), con edades entre 203 – 265 Ma que muestran gran dispersión a lo largo de la línea de concordia. Una agrupación de estos análisis, relativamente concordantes, permiten calcular una edad ²⁰⁶Pb/²³⁸U media ponderada de 224 ± 3Ma (2s, MSWD = 1.8, n = 5; Figura 12F) que se interpreta como la edad de cristalización de esta granodiorita leucocrática de dos micas.

3.3.12. Granodiorita leucocrática de dos micas (GranCen-3)

Las concentraciones de U y Th para los zircones analizados son las más altas, comparadas con el resto de las muestras, variando de 604 – 9508 ppm y 87 – 958 ppm, respectivamente, con relaciones Th/U entre 0.03 – 0.26 (Tabla SE1). Se observa una gran dispersión de los datos con diferentes grados de discordancia (- 1 % a 13 %), aunque algunos análisis son más concordantes que otros (entre - 1 % y 3 %) (Figura 12H). Una población de zircones representada por la agrupación de los análisis en color negro (elipses y cuadrados) fueron utilizados para el cálculo de una edad ²⁰⁶Pb/²³⁸U media ponderada de 221 ± 2 Ma (2s, MSWD = 2.0, n = 9; Figura 12I).

4. Discusión

4.1. Edad del magmatismo permo-triásico y geocronología U-Pb en zircón

El magmatismo permo-triásico del NW de Sonora se encuentra representado por un conjunto de granitoides con edades de cristalización U-Pb en zircón en un rango aproximado de 284 – 221 Ma (Figura 13). Este rango indica un intervalo de actividad magmática de aproximadamente 60 Ma, sugiriendo el inicio del arco continental en el Pérmico temprano hasta el Triásico tardío. Las rocas afloran en diversas localidades del NW de Sonora como en el área de estudio de la Sierra Los Tanques (este estudio; R. García-Flores, com. pers., 2015), Sierra Pinta (Arvizu et al., 2009a), Sierra San Francisco (Velázquez-Santelíz, 2014), Sierra Enterrada (Paz-Moreno, com. pers., 2011) y Sierra Blanca (Paz-Moreno, com. pers., 2011) (Figura 1). Cabe señalar que la mayoría de estas rocas permo-triásicas distribuidas en las zonas antes mencionadas estaban cartografiadas como de edad proterozoica o incluso como rocas del Cretácico tardío o del Paleógeno-Neógeno (e.g., SGM, 2002). En el histograma de la Figura 14 se muestra una distribución de los datos geocronológicos existentes del magmatismo presente en el NW de Sonora, además del tipo de tectonismo dominante desde el Proterozoico hasta el Cenozoico. A grandes rasgos, se observa que en el NW de Sonora existen diversos pulsos y gaps magmáticos representados por ausencia de magmatismo y por rocas ígneas con características calcialcalinas asociadas a subducción para formar el arco magmático continental cordillerano desde el Pérmico hasta básicamente el Mioceno (e.g., Izaguirre-Pompa, 2006, 2009; Vidal-Solano et al., 2008; Roldán-Quintana et al., 2009; Valencia-Moreno et al., 2011; Arvizu-Gutiérrez, 2012), estableciéndose éste, en un basamento de edad proterozoica y paleozoica y de naturaleza totalmente laurenciana (Figura 14) (e.g., Iriondo, 2001; Iriondo et al., 2004; Nourse et al., 2005).

Por otra parte, la mayoría de los análisis de zircón de los granitoides permo-triásicos muestran concentraciones altas de U, sugiriendo que han sufrido diferentes grados de pérdida de Pb. En el caso de los zircones más viejos, estos podrían representar zircones con diferentes grados de herencia en los cuales se muestreó parte de un núcleo o simplemente dominios más viejos del zircón como lo revelan las imágenes de catodoluminiscencia (Figuras 9 – 12 D, H y L).

La presencia de análisis concordantes con edades proterozoicas (Figura 15), que corresponden a núcleos heredados como se muestra en las imágenes de catodoluminiscencia (Figuras 9 – 12 D, H y L), puede ser fácilmente explicada ya que estas edades son comunes para el basamento granítico meta-ígneo existente en la región de ~ 1.7 – 1.6 Ga, ~ 1.4 y ~ 1.1 Ga (e.g., Iriondo et al., 2004, 2005; Nourse et al., 2005; Izaguirre et al., 2008; Arvizu et al., 2009b; Iriondo y Premo, 2010), incluso consistentes con las edades proterozoicas obtenidas de rocas de basamento para la zona de estudio de Sierra Los Tanques (Arvizu-Gutiérrez, 2012). En el histograma de la Figura 15A se observan las edades individuales U-Pb en zircón obtenidas de todas las muestras fechadas en este estudio, observándose picos significativos a ~ 238 Ma y ~ 258 Ma que coinciden con el rango de edades de cristalización (edades U-Pb medias ponderadas) determinadas para la mayoría de las rocas datadas en este trabajo. Una interpretación importante que se podría evaluar y que no se puede descartar, es que algunos de los zircones más antiguos de edad pérmica y que son relativamente concordantes, en un rango entre ~ 258 – 288 Ma, podrían representar las edades de cristalización originales de algunas rocas, pero que posteriormente sufrieron un grado significativo de pérdida de plomo. No obstante, los granitoides permo-triásicos contienen abundantes zircones heredados (algunos altamente concordantes; Figuras 9 – 12 D, H y L) con edades que varían en un rango entre ~ 1071 – 1924 Ma, con picos o abundancias principales a ~ 1.1 Ga, ~ 1.4 Ga y ~ 1.6 – 1.7 Ga (Figura 15B). Se interpreta que estos zircones heredados fueron derivados de la fusión parcial y/o asimilación de las rocas encajonantes de basamento paleoproterozoico presente localmente en Sierra Los Tanques (e.g., bloques, xenolitos, roof pendants).

En los gráficos de Edad ²⁰⁶Pb/²³⁸U (Ma) vs. Concentración de U (ppm) de la Figuras 16 A – B se observan en (a) todos los análisis de zircón más jóvenes con edades < 300 Ma y en (b) un acercamiento a los zircones de edad permo-triásica (200 – 300 Ma). En ambos gráficos se observa una tendencia al incremento en las concentraciones de U a medida que el zircón/análisis es más joven. Es importante resaltar que la mayoría de los zircones con edades más jóvenes son zircones con valores altos en U (1000 – 6000 ppm) (Figuras 16 A-B, Tabla SE1) que sufrieron pérdida de plomo. De acuerdo a esto, no se descarta que algunos análisis de edades triásicas pudieran haber sido zircones pérmicos con pérdida generalizada de Pb siguiendo una trayectoria a lo largo de la línea de concordia (Figuras 9 – 12 D, H y L).

Figura 13. Histograma y diagrama de probabilidad de edades de cristalización U-Pb de zircones de granitoides permo-triásicos del NW de Sonora (datos de este trabajo y referencias mencionadas en el texto).

Figura 14. Histograma mostrando los periodos, rangos y gaps de magmatismo en el NW de Sonora empleando principalmente las edades U-Pb de cristalización en zircones de rocas ígneas. También se observa el tipo de tectonismo dominante desde el Proterozoico al Cenozoico relacionado a cada pulso o periodo de magmatismo y ausencia del mismo durante la evolución geológica de la región. La mayor parte de la base de datos utilizada para el desarrollo del histograma se encuentra recopilada en Izaguirre-Pompa (2009) y sus referencias, mientras que el resto son datos generados en Arvizu-Gutiérrez, 2012 y en este estudio.

Figura 15. A) Histograma y diagrama de probabilidad de edades U-Pb de zircones individuales de todas las muestras de granitoides permo-triásicos fechadas en este trabajo. B) Histograma y diagrama de probabilidad de edades U-Pb de zircones heredados fechados en las muestras de granitoides permo-triásicos.

4.2. Relaciones Th/U como indicadores del origen de zircones ígneos y metamórficos

Las relaciones Th/U se han convertido en un criterio comúnmente empleado para distinguir entre ambientes magmáticos, metamórficos e hidrotermales de formación del zircón (Harley et al., 2007). Incluso, algunos geocronólogos han reconocido por algún tiempo que la relación Th/U podría ser usada como un discriminante de primer orden entre zircones magmáticos y metamórficos (e.g., Bibikova, 1984; Pidgeon et al., 2000). Empíricamente, las relaciones Th/U de zircones magmáticos tienden a ser > 0.1 (Vavra et al., 1999; Hoskin e Ireland, 2000; Pidgeon et al., 2000; Belousova et al., 2002; Hidaka et al., 2002), mientras que las relaciones Th/U de los zircones metamórficos suelen ser < 0.1 (Hoskin e Ireland, 2000; Hidaka et al., 2002; Rubatto, 2002). Sin embargo, existen muchas situaciones con relaciones > 0.1 para zircones metamórficos (Vavra et al., 1999; Kröner et al., 2000; Wilde et al., 2001) y < 0.1 para zircones magmáticos (Young et al., 1995; Compston, 1995; Elburg, 1996; Muir et al., 1996; Singh et al., 2002; Lund et al., 2002; Li et al., 2003; Zhai et al., 2005). Las causas de las variaciones de tales relaciones Th/U son altamente controversiales (Klötzli, 1999) y su uso ha sido re-evaluado en vista de observaciones texturales y otros criterios químicos (e.g., Möller et al., 2003).

Aunque algunas de las relaciones Th/U en los zircones permo-triásicos analizados en este estudio son muy bajas (< 0.1) (Figura 16C; Tabla SE1), valores que podrían interpretarse como relaciones típicas para zircones metamórficos, la morfología prismática típica, además de las texturas observadas en las imágenes de catodoluminiscencia indican que la mayoría de los zircones son fácilmente asignados a un origen ígneo, ya que se aprecian zonaciones oscilatorias típicas de crecimiento magmático (Figuras 9 – 12D, H y L). Sin embargo, algunos zircones exhiben texturas o estructuras internas no muy comunes en zircones magmáticos (Figuras 9 – 12D, H y L), quizá producto de recristalización por metamorfismo o disolución por actividad hidrotermal como lo revelan algunas de las relaciones muy bajas de Th/U (≤ 0.02, Figura 16C; Tabla SE1). Se han documentado que estas relaciones tan bajas de Th/U son típicas de zircones que se han formado durante metamorfismo de alto grado (e.g., Williams y Claesson, 1987; Maas et al., 1992; Rubatto, 2002; entre otros) o zircones asociados con interacciones fluido-mineral en estadios tardíos a temperaturas moderadas a altas, durante la cristalización de los zircones (e.g., Vavra et al., 1999; Harley et al., 2001; Carson et al., 2002). Algunos otros zircones no muestran una zonación clara, sino dominios más oscuros ricos en U (Figuras 9 – 12D, H y L) como lo indican las concentraciones altas de este elemento (Tabla SE1).

Las altas variaciones en los contenidos de Th (~ 1 – 1503) y U (~ 47 – 9508) (Figura 16D; Tabla SE1) en los zircones permo-triásicos analizados también podrían indicar que existe una zonación química dentro de los cristales de zircón como los demuestran las imágenes de catodoluminiscencia. Algunos reportes sobre relaciones bajas de Th/U en zircones magmáticos (e.g., Zheng et al., 1999) sugieren que los valores bajos en estas relaciones, determinados en los zircones magmáticos de los granitoides permotriásicos son razonables.

Por ejemplo, las concentraciones de U y Th promedio en zircones graníticos han sido propuestas en 1330 ppm y 630 ppm, respectivamente (Figura 16D; Ahrens et al., 1967). Un resultado similar fue obtenido por Lyakhovich (1973), mostrando promedios de U y Th para zircones graníticos de 1150 ppm y 886 ppm, respectivamente (Figura 16D). Sin embargo, análisis más recientes muestran que los valores de U y Th en zircones graníticos son mucho menores que los valores aceptados antes mencionados (Wilde y Youssef, 2000; Claesson et al., 2000; Da Silva et al., 2000; Eichhorn et al., 2000; Singh et al., 2002; Lund et al., 2002; Zhou et al., 2002; Li et al., 2002; Thrane, 2002; Li et al., 2003; Liu et al., 2004; Zhai et al., 2005). Inclusive, en un trabajo recientemente publicado por Wang et al.(2011), donde se hace una compilación de datos de literatura, muestra que los contenidos de U y Th en zircones de rocas graníticas están mejor representados por valores promedio de 350 ppm y 140 ppm, respectivamente (Figura 16D). Aunque, como se mencionó anteriormente, valores mucho más altos de U y Th (> 1000 ppm para ambos) en zircones magmáticos han sido reportados en la literatura.

El criterio propuesto para distinguir entre zircones magmáticos y metamórficos utilizando las relaciones Th/U (e.g., Rubatto, 2002; Hoskin y Schaltegger, 2003) no es infalible de acuerdo a las variaciones considerables de este parámetro marcadas en varios trabajos (e.g., Carson et al., 2002; Kelly y Harley, 2005). Los datos de este estudio apoyan esta conclusión, ya que los zircones permo-triásicos muestran relaciones Th/U altamente variables (0.01 – 0.73; Figura 16D), variaciones similares a los valores propuestos para zircones magmáticos y/o metamórficos reportados en literatura (e.g., Ahrens et al., 1967; Lyakhovich, 1973; Wang et al., 2011). Dado este hecho y la evidencia de relaciones variables de Th/U descritas anteriormente, los valores de Th/U pueden sólo ser usados con precaución y en colaboración con otros criterios químicos para valorar el origen del zircón dentro de su contexto textural como lo podría ser la geoquímica de REE en el zircón.

Figura 16. A) Gráfico de Edad ²⁰⁶Pb/²³⁸U (Ma) vs. Concentración de U (ppm) de todos los zircones analizados más jóvenes < 300 Ma utilizando 233 análisis individuales. Los círculos en negro representan los análisis de zircón utilizados para calcular las diferentes edades de las rocas reportadas en este trabajo (ver Tabla 1 y Figuras 9 – 12), mientras que los círculos grises son los análisis descartados para el cálculo de la edad por representar zircones con diferentes grados de pérdida de Pb y/o núcleos heredados. B) Acercamiento mostrando solamente los zircones de edad permo-triásica (222 análisis). C) Gráfico de Edad ²⁰⁶Pb/²³⁸U (Ma) vs. Relación ²³²Th/²³⁸U. La línea punteada a 0.1 en la relación Th/U muestra una tentativa división para el origen de los zircones apoyada de datos de literatura (e.g., Hoskin y Black, 2000; entre otros discutidos en el texto). Los valores > 0.1 indican un origen ígneo mientras que los valores < 0.1 indican posiblemente un origen metamórfico para los zircones. D) Gráfico de concentraciones de U (ppm) vs. Th (ppm) de todos los zircones permo-triásicos.

4.3. Implicaciones tectónicas del magmatismo permo-triásico en el NW de México

El estudio de las rocas paleoproterozoicas del SW de Norteamérica ha permitido caracterizar y proponer una división del basamento paleoproterozoico en el margen continental del SW de Laurencia en tres diferentes provincias: Mojave, Yavapai y Mazatzal (Figura 17A) (e.g., Karlstrom et al., 1987; Karlstrom y Bowring, 1988; Karlstrom y Bowring, 1993; Wooden y Miller, 1990; Iriondo et al., 2004; Iriondo y Premo, 2010 y sus referencias). La presencia de rocas paleoproterozoicas aflorantes en el NW de Sonora, como en las regiones de Quitovac, Cabeza Prieta-Pinacate, Cerros San Luisito, Cerro Prieto y Zona Canteras-Puerto Peñasco (Iriondo et al., 2004; Nourse et al., 2005; Gutiérrez-Coronado et al., 2008; Izaguirre et al., 2008; Arvizu et al., 2009b) sugiere mediante estudios geocronológicos, geoquímicos e isotópicos que el basamento cristalino en esta región presenta similitudes con rocas asociadas a la provincia Yavapai, por lo que se propone la extensión de estas provincias hacia México (Figuras 17 A y B).

Iriondo (2005, 2007) sugiere que la agrupación de rocas paleoproterozoicas con características Yavapai en Sonora, que mantienen una dirección estructural predominantemente NW-SE (Figura 17), han podido actuar como una zona de debilidad cortical (sutura) desde el Paleoproterozoico. Esta debilidad pudo haber condicionado notablemente algunos eventos geológicos subsecuentes presentes en Sonora como la orientación del rifting continental durante la ruptura del supercontinente Rodinia; la ubicación preferencial para el emplazamiento del magmatismo y la formación de cuencas sedimentarias mesozoicas; la canalización de fluidos metamórficos para la formación del cinturón de Au orogénico laramídico; la ubicación preferencial para el magmatismo terciario, principalmente volcanismo; la orientación de la apertura (rifting) del Golfo de California; y quizá, la presencia de magmatismo máfico cuaternario (e.g., Campos volcánicos del Pinacate y Moctezuma) a lo largo de la franja de corteza Yavapai.

Algunos autores (e.g., Arvizu et al., 2009a; 2009b; Iriondo y Premo, 2010) sugieren que esta zona representada por la franja de Yavapai mexicano (Figura 17) también sirvió para que los primeros magmas asociados a la subducción permo-triásica y al inicio del arco magmático continental cordillerano del SW de Norteamérica ascendieran hacia la superficie con mayor facilidad (Figura 17B). Esto a través de una corteza continental comparativamente fría después de cientos de millones de años como corteza de margen continental pasiva generada posteriormente al rifting o ruptura del supercontinente Rodinia en el Neoproterozoico y/o Paleozoico Inferior (Stewart, 1976, 1988; Li et al., 2008) (Figura 14).

Cabe aclarar que lo que se considera como zona de debilidad cortical Yavapai es sólo una hipótesis para explicar el conducto por el cual los magmas generados por subducción durante el permo-triásico ascendieron hacia la superficie. Sin embargo, aún no se puede demostrar pero estudios recientes antes mencionados indican que esta hipótesis podría ser factible para explicar la presencia de las rocas ígneas permo-triásicas en el NW de Sonora como en las localidades de Sierra Enterrada, Sierra Blanca, Sierra San Francisco, Sierra Los Tanques y Sierra Pinta (Figura 17B).

Figura 17. (A) Distribución tentativa de las provincias paleoproterozoicas Mojave, Yavapai y Mazatzal en el SW de Laurencia, incluyendo los afloramientos del NW de México (Iriondo y Premo, 2010). El rango de edades de cristalización (en rojo) para rocas ígneas de cada una de las provincias está basado en la recopilación de edades de Iriondo et al. (2004). También se presenta, de forma tentativa, la extensión de la traza de fronteras de Nd y de las series geoquímicas al internarse en México (Iriondo y Premo, 2010). Las abreviaciones son LA: Los Ángeles, SD: San Diego, LV: Las Vegas, PHX: Phoenix, TUC: Tucson, HER: Hermosillo. (B) Acercamiento al NW de Sonora mostrando los afloramientos de rocas graníticas permo-triásicas encontrados hasta la fecha en la región y que se encuentran espacialmente asociadas a la franja del Yavapai mexicano (este estudio y referencias mencionadas en el texto).

4.4. Relación entre el magmatismo permo-triásico en el NW de Sonora y el magmatismo cordillerano del SW de Norteamérica, noreste, centro y sur de México

El descubrimiento del pulso magmático permo-triásico en el NW de Sonora, con edades U-Pb en zircones entre ~ 284 – 221 Ma (Figura 13) se puede asociar a subducción y al inicio del arco magmático continental del SW de Norteamérica. Esto contrasta con la idea de que el comienzo de la subducción para formar el arco magmático continental cordillerano en el SW de Norteamérica inició con la intrusión de plutones graníticos de edad básicamente triásica (~ 250 – 207 Ma; Barth et al., 1997; Barth y Wooden, 2006) emplazados en el basamento paleoproterozoico, como resultado del inicio de la convergencia a lo largo del margen continental paleozoico pre-existente (e.g., Burchfiel y Davis, 1972, 1975, 1981; Kistler y Peterman, 1973; Dickinson, 1981; Burchfiel et al., 1992). De esta manera, esta ocurrencia de magmatismo pérmico en el NW de México permite recorrer varios millones de años hacia atrás (> 30 Ma) el inicio de la subducción y el establecimiento del margen continental activo en el SW de Norteamérica.

La ocurrencia de algunos plutones de edad permo-triásica (~ 260 – 207 Ma) en los estados de Nevada, California y Arizona (e.g., Snow et al., 1991; Bateman, 1992; Burchfield et al., 1992; Miller et al., 1992, 1995; Dunne y Saleeby, 1993; Schweickert y Lahren, 1993; Barth et al., 1997; Barth y Wooden, 2006) parece estar asociada a dos diferentes procesos de formación. Por un lado, los plutones permo-triásicos localizados en la parte norte y centro de California y los del oeste de Nevada, parecen estar asociados a un arco magmático de islas constituido por terrenos oceánicos acrecionados (Figura 18), creado a distancia del margen continental y que posteriormente colisionaron contra el continente en tiempos mesozoicos (Barth et al., 1990, 1997; Busby-Spera et al., 1990; Saleeby y Busby-Spera, 1992; Barth y Wooden, 2006). Asimismo, estos autores plantean que algunos de estos plutones permo-triásicos en la parte sur de California y oeste de Arizona se encuentran asociados a una zona de subducción paralela al margen continental paleozoico pre-existente, como lo sugiere el patrón de orientación NW del plutonismo y volcanismo permo-triásico que corta basamento proterozoico en esas regiones (Figura 18).

Figura 18. Reconstrucción geotectónica hipotética del Permo-triásico del oeste de Pangea. Se muestra la sutura orogénica Ouachita-Marathon-Sonora propuesta por Poole et al. (2005), la cual se infiere se extiende hacia Sonora. Las posiciones o paleogeografías de los diferentes bloques corticales que conforman México en la actualidad son inferidas (modificadas a partir de Dickinson y Lawton, 2001; Elías-Herrera y Ortega-Gutiérrez, 2002; entre otros). En este mapa también se muestra la posición inferida del arco cordillerano continental Pérmico-Jurásico? y la zona de subducción (según Dickinson y Lawton, 2001; Dickinson, 2006; Godínez-Urban et al., 2011). La localización de los segmentos de arco intraoceánicos acrecionados en EUA son según Dickinson (2006), en donde BM = Blue Mountains, KM = Klamath Mountains, SN = Sierra Nevada y PR = Peninsular Ranges. También se muestran las principales localidades de rocas volcánicas-plutónicas de edad permo-triásica que forman parte del inicio del arco magmático cordillerano instaurado en el borde oeste de Pangea (Torres et al., 1999). Los afloramientos permo-triásicos no están a escala. Los círculos negros, como se muestra en la leyenda, representan la ubicación de algunas localidades con los principales cuerpos ígneos de edad permo-triásica reportados hasta la fecha en publicaciones científicas. Las localidades de estas rocas ígneas permo-triásicas se encuentran discutidas en el texto. Las estrellas en color negro representan magmatismo de arco de edad carbonífera generado previo a la fase final de colisión entre Laurencia y Gondwana creando la sutura orogénica en el Pérmico temprano (ca. 281 Ma). En línea punteada delgada se presenta la configuración geográfica actual de Norteamérica. Abreviaturas = Ac: Complejo Acatlán, CA: Andes Colombianos, ChB: Bloque de Chortís, CB-D: Bloque Coahuila-Delicias, DSB: Bloque Del Sur (Ac+Oax), F: Florida, FB: Bloque El Fuerte, M: Terreno Mérida, MCh: Macizo de Chiapas, Oax: Complejo Oaxaca, Tam: Bloque Tampico, YB: Bloque Yucatán-Chiapas.

Por otro lado, en el noreste, centro y sur de México el arco continental permo-triásico nombrado arco del Este de México (Torres et al., 1999) está relacionado a una zona de subducción con vergencia hacia el este en el margen oeste de Pangea (Torres et al., 1999; Schaaf et al., 2002; Weber et al., 2005, 2007; Ratschbacher et al., 2009) pero es establecido en corteza gondwánica. Algunos trabajos proponen que pudiera extenderse probablemente hasta el noroeste de Sudamérica (e.g., Centeno-García y Keppie, 1999), específicamente en Colombia, ya que también han sido reportadas rocas de estas edades en esa parte de la Cordillera (e.g., Pindell y Dewey, 1982; Pindell, 1985; Case et al., 1990). Sin embargo, algunas rocas graníticas permo-triásicas estudiadas en la parte norte de la Cordillera Central de Colombia se cree que han registrado el evento colisional entre Laurencia y Gondwana, completando el ensamble final de Pangea durante el Pérmico temprano (e.g., Restrepo et al., 1978, 1991; González, 2001; Vinasco et al., 2006). Investigaciones más recientes han comprobado la continuación del arco magmático permo-triásico hacia Sudamérica (e.g., Cochrane et al., 2014; Spikings et al., 2015).

La reconstrucción geotectónica hipotética presentada en este estudio para el Permo-triásico en la parte oeste-centro de Pangea (Figura 18) está basada principalmente en los modelos de Dickinson y Lawton (2001), Elías-Herrera y Ortega-Gutiérrez (2002) y Godínez-Urban et al. (2011). Primeramente, el cierre del océano Rhéico durante el Paleozoico tardío, a lo largo de una zona de subducción con orientación aproximadamente ENE-WSW y con dirección hacia el sur, permitió la colisión final entre el sur de Laurencia y el noroeste de Gondwana creando el cinturón orogénico o sutura Ouachita-Marathon-Sonora para lograr el ensamble final de Pangea (e.g., Poole et al., 2005). Esta zona inicial de subducción con dirección hacia el sur puede incluir el arco volcánico Las Delicias del Misisípico tardío-Pérmico temprano que se extinguió justo antes de la colisión final continente-continente entre Laurencia y Gondwana en el Pérmico temprano (ca. 281 Ma). De este evento se tiene registro de algunas rocas ígneas de composición dacítica y granítica del arco Las Delicias que están expuestas localmente dentro del bloque Coahuila (López, 1997). Aunque la secuencia expuesta en Las Delicias es interpretada como de tras-arco, por la presencia de wild-flysch, tiene un alcance estratigráfico hasta el Pérmico tardío (McKee et al., 1988). También se han reconocido rocas meta-volcánicas de edad carbonífera en Yucatán cortadas por algunos pozos de exploración petrolera (Marton y Buffler, 1994). Estas rocas, evidentemente, representan la existencia de un arco magmático de edad carbonífera formado previo a la sutura Ouachita-Marathon-Sonora (e.g., Viele y Thomas, 1989; Marton y Buffler, 1994; López, 1997; Stewart et al., 1999).

Estudios más recientes documentan magmatismo del Pensilvánico temprano en los Altos Cuchumatanes en Guatemala (312 – 317 Ma, Solari et al., 2009) debido a la convergencia oblicua entre Laurencia y Gondwana causada por el desarrollo de una zona de subducción. En este sentido, en el Macizo de Chiapas se han interpretado protolitos de anatexitas del Pérmico temprano (~ 272 Ma, Weber et al., 2007).

En la reconstrucción geotectónica durante el Permo-triásico (Figura 18), las posiciones o paleogeografías de los diferentes bloques corticales que conforman México en la actualidad son inferidas, aunque la posición más probable para estos era que el Bloque Del Sur (DSB), conformado por los Complejos Acatlán (Ac) y Oaxaca (Oax), estaba junto a los Andes Colombianos (CA), mientras que el Bloque de Chortís (ChB) se encontraba localizado más hacia el sur. Por su parte, el sur del bloque Maya (MCh = Macizo de Chiapas) durante ese tiempo estaba localizado al noroeste del margen de Gondwana, encontrándose, hacia el este, junto al terreno Mérida (M) (Andes Paleozoicos), actualmente Venezuela (Alemán y Ramos, 2000 y sus referencias) mientras que al oeste colindaba con el Bloque Tampico. Los Bloques de Yucatán-Chiapas, Coahuila-Delicias y El Fuerte, de afinidad gondwánica, estaban localizados más hacia el norte cerca de la sutura Ouachita-Marathon-Sonora.

Durante la última etapa de la colisión, en el Pérmico temprano, la parte oeste de Pangea experimentó una convergencia con orientación aproximadamente este-oeste generando una nueva zona de subducción con orientación general NW-SE hacia el este consumiendo una placa oceánica (¿Mezcalera?) y permitiendo el establecimiento del arco magmático continental del Este de México (Figura 18). Todas las unidades de basamento precámbrico y paleozoico de México y Centroamérica antes mencionadas estuvieron involucradas dentro de este complejo de subducción (Elías-Herrera y Ortega-Gutiérrez, 2002). Se propone que el arco del Este de México se instauró inicialmente a lo largo del Bloque Tampico marcando un arreglo linear norte-sur (Torres et al., 1999), extendiéndose hacia el sur dentro del Bloque del Sur (Sedlock et al., 1993). Dickinson y Lawton (2001) especularon que el magmatismo pre-jurásico del Bloque de Chortís (Donnelly et al., 1990) podría incluir rocas plutónicas que representarían una extensión hacia el sur del arco permo-triásico del Este de México. Estudios recientes han corroborado esa hipótesis (e.g., Cochrane et al., 2014; Spikings et al., 2015). Posteriormente, el magmatismo cruzó el Macizo de Chiapas, parte del Bloque Yucatán-Chiapas, continuando hacia el norte como un cinturón arqueado de plutones aislados emplazados dentro del Bloque Coahuila-Delicias (Salvador, 1991; Sedlock et al., 1993; López, 1997) y en menor proporción, dentro de corteza Laurenciana, al norte de la sutura Ouachita-Marathon-Sonora, en el estado de Chihuahua (Torres et al., 1999) (Figura 18).

Por su parte, el complejo de subducción de la Mesa Central es un ensamble de depósitos volcanoclásticos, algunos metamorfoseados. Algunos autores le han asignado una edad del Pérmico Inferior (Gursky y Michalzik, 1989; Stewart et al., 1999), pero también se considera una edad triásica basada en zircones detríticos (Barboza-Gudiño et al., 2010). Rocas de este complejo están expuestas al oeste del cinturón plutónico (Figura 18), localizado en "Oaxaquia" (término utilizado para nombrar al ensamble cortical, de afinidad gondwánica, de los Bloques Tampico [Tam] y Bloque Del Sur; Keppie y Ortega-Gutiérrez, 1995; Ortega-Gutiérrez et al., 1995). Otras secuencias, como la Formación Guacamaya de la Sierra Madre Oriental, han sido interpretadas por Dickinson y Lawton (2001) como depósitos de una cuenca antearco asociada con el arco del Este de México. El esquisto Granjeno que incluye rocas serpentinizadas y localmente expuesto en el anticlinorio Huizachal, cerca del borde oeste del Bloque Tampico, podría representar una exposición local del complejo de subducción relacionado con el arco del este de México (Sedlock et al., 1993), ya que ha proporcionado edades del Pérmico tardío (Carrillo-Bravo, 1961).

En conclusión, la ocurrencia de rocas graníticas permo-triásicas en el NW de Sonora nos permite enlazar este evento magmático a nivel cordillerano desde el SW de los Estados Unidos (Nevada-California-Arizona), a través de Sonora, hasta Chihuahua, Coahuila, Puebla, Oaxaca y Chiapas en el norte, centro y sur de México (Torres et al., 1999; Centeno-García y Keppie, 1999; Dickinson y Lawton, 2001; Solari et al., 2001; Weber et al., 2007). Se propone una conexión entre el arco magmático permo-triásico del SW de EUA (e.g., Damon et al., 1981; Barth et al., 1997; Barth y Wooden, 2006) y NW de Sonora (Arvizu et al., 2009a) con el arco triásico del Este de México (Torres et al., 1999) y el arco permo-triásico del sur de México (Torres et al., 1999; Solari et al., 2001; Dickinson y Lawton 2001; Weber et al., 2005, 2007; Kirsch et al., 2012; Ortega-Obregón et al., 2013) enlazando este evento magmático a nivel cordillerano hasta el noroeste de Sudamérica (e.g., Vinasco et al., 2006; Cardona et al., 2010; Spikings et al., 2015). Al igual que otros autores, esto nos lleva a la conclusión de que este cinturón magmático es el resultado de la subducción permo-triásica a lo largo de un margen continental activo establecido después del ensamble final o sutura de Pangea durante la orogenia Ouachita-Marathon-Sonora en el Carbonífero tardío-Pérmico temprano (e.g., Ross, 1986; Torres et al., 1999; Dickinson y Lawton, 2001; Poole et al., 2005) formada por el cierre diacrónico de una cuenca oceánica (i.e., océano Rhéico) entre Laurencia y Gondwana, permitiendo su posterior colisión (Graham et al., 1975; Ross, 1979; Viele y Thomas, 1989; Hatcher, 2002).

Iriondo y Arvizu (2009) plantearon como hipótesis que el magmatismo pérmico comenzó inicialmente en la parte sur de México, donde existían las rocas ígneas más antiguas, y avanzó hacia el norte pasando a través del NW de Sonora y siguiendo el camino a California y Nevada en el SW de EUA, en donde el magmatismo, aparentemente, era más joven. Sin embargo, cabe señalar que nuevas ocurrencias de rocas graníticas en el NW de Sonora (Arvizu et al., 2009a; este estudio y sus referencias) han resultado ser tan antiguas como las del sur de México (~ 284 – 250 Ma) y tan jóvenes como las del arco del SW de EUA (~ 250 – 221 Ma) descartándose esa idea inicial de la migración del magmatismo. De cualquier manera, este arco magmático continental permo-triásico representa un gran evento a nivel cordillerano en el SW de Norteamérica que difiere en tiempo y que es básicamente oblicuo al arco Las Delicias más viejo encontrado en el NE de México (e.g., Iriondo y Arvizu, 2009).

La hipótesis de la migración del magmatismo permo-triásico del sur y centro de México (instaurado dentro de corteza gondwánica) hacia el norte de México y suroeste de Estados Unidos (establecido dentro de corteza laurenciana) claramente ha sido descartada por la existencia de actividad magmática relacionada a subducción, tanto de edad pérmica como de edad triásica en ambas regiones. Incluso a lo largo de todo el margen oeste de Gondwana desde Norteamérica hasta Perú (e.g., Ratschbacher et al., 2009; Cochrane et al., 2014; Spikings et al., 2015).

El modelo más factible para explicar tal coexistencia de edades, tanto en el noroeste de Sonora-suroeste de Estados Unidos (Laurencia) como en el centro-sur de México (Gondwana), lo explica claramente la existencia de un arco continental activo desde el Pérmico temprano al Triásico tardío. El cual podría haber experimentado variaciones periódicas, a lo largo de ca. 60 Ma (284 – 221 Ma), en el ángulo de subducción (e.g., tectonic switching: Collins, 2002), sugiriendo que la variación entre una subducción plana, superficial o poco profunda (flat- slab subduction) y una abrupta (steep-slab subduction) fue espacialmente diacrónica a lo largo del margen cordillerano de Norteamérica. Además, otro factor importante que pudo haber influido fue la geometría de la placa subducida (Mezcalera?), la cual también pudo haber variado espacialmente a lo largo del margen continental cordillerano. Todos estos factores han sido documentados en la mayoría de las tectónicas acrecionales y sistema de arcos magmáticos modernos tales como Los Andes (e.g., Gutscher et al., 2000; Ramos y Folguera, 2008).

5. Conclusiones

El descubrimiento del magmatismo permo-triásico en el NW de Sonora, no reconocido anteriormente en la región, se encuentra representado por la ocurrencia de un conjunto de granitoides con edades de cristalización U-Pb en zircón en un rango de 284 – 221 Ma. Este rango indica un intervalo de actividad magmática de aproximadamente 60 Ma, sugiriendo el inicio del arco continental cordillerano en el margen SW de Laurencia en el Pérmico temprano hasta el Triásico tardío.

La mayoría de los análisis de zircón de los granitoides permo-triásicos muestran concentraciones altas de U, sugiriendo que han experimentado pérdida de Pb asociada a los eventos magmáticos posteriores a su emplazamiento presentes en la región de estudio. En el caso de los zircones más viejos, estos representan zircones heredados con edades proterozoicas comunes para el basamento meta-ígneo existente en la región de ~ 1.7 – 1.6 Ga, ~ 1.4 y ~ 1.1 Ga. Claramente estas herencias fueron derivadas de la fusión parcial y/o asimilación de las rocas encajonantes de basamento paleoproterozoico presente localmente en Sierra Los Tanques, lo cual se confirma con las edades proterozoicas obtenidas en estudios recientes de rocas de basamento para la zona de estudio.

Las relaciones bajas de Th/U de los zircones podrían interpretarse como relaciones típicas para zircones metamórficos, pero la morfología prismática típica, además de las texturas internas observadas en las imágenes de catodoluminiscencia indican que la mayoría de los zircones son de origen ígneo con zonaciones oscilatorias típicas de crecimiento magmático.

La ocurrencia del pulso magmático permo-triásico se asocia regionalmente a una zona de debilidad cortical relacionada al basamento paleoproterozoico del Yavapai mexicano en el NW de Sonora. Por lo tanto, su entendimiento es importante para contribuir en el conocimiento de la evolución tectónica del SW de Norteamérica, ya que representa una fuente regional de zircones detríticos (207 – 292 Ma) no reconocida anteriormente para cuencas sedimentarias mesozoicas y cenozoicas en Sonora y sur de Arizona. Su existencia también permite enlazar este evento magmático a nivel cordillerano desde el SW de los Estados Unidos pasando por Sonora en el norte, a través del centro y sur de México, hasta el norte de Sudamérica.

Este cinturón magmático es el resultado de la subducción permo-triásica hacia el este y su existencia representa el inicio del magmatismo cordillerano en el SW de Laurencia establecido a lo largo del borde oeste de Pangea inmediatamente después de culminar su ensamble final. El modelo más factible para explicar la coexistencia de rocas con edades permo-triásicas, tanto en Laurencia como en Gondwana, lo explica claramente la existencia de un arco continental activo inicialmente en el Pérmico temprano hasta el Triásico tardío, experimentando variaciones periódicas en el ángulo de subducción, a lo largo de ca.60 Ma (284 – 221 Ma).

Agradecimientos

Harim Arvizu agradece a las instituciones que otorgaron los proyectos de investigación PAPIIT/UNAM (clave IN-116709) y CONACYT (claves CB-82518 y CB-129370), a Alexander Iriondo, por el financiamiento proporcionado para realizar trabajo de campo y estudios de laboratorio. Al CONACYT por la beca otorgada durante la maestría. Agradecimiento especial al compañero y colega Aldo Izaguirre Pompa por el apoyo brindado en las campañas geológicas realizadas en Sierra Los Tanques, NW de Sonora. Se agradece a Luis M. Martínez Torres (Koldo) por el valioso apoyo en campo y valiosa aportación en la cartografía geológica de Sierra Los Tanques. A Luigi Solari, profesor-investigador, y a Carlos Ortega Obregón, técnico del LEI (Laboratorio de Estudios Isotópicos), ambos del CGEO, por la valiosa ayuda y apoyo durante los fechamientos U-Pb en zircones, en lo que respecta a la adquisición de los datos y reducción de los mismos. Se agradece a Luigi Solari por el apoyo ofrecido para obtener imágenes de luz reflejada y transmitida de los zircones. Agradecimiento enorme a Dan Miggins y Heather Lowers del U.S. Geological Survey de Denver por la asistencia en la obtención de imágenes de SEM-Catodoluminiscencia para realizar los estudios de geocronología U-Pb en zircones. Finalmente, Arvizu agradece y aprecia los comentarios, sugerencias y críticas constructivas realizadas por los revisores Bodo Weber y Peter Schaaf, las cuales mejoraron el manuscrito y, de igual manera, a los editores del BSGM por el apoyo logístico brindado para publicar este artículo.

Referencias

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1. Muestreo y preparación para análisis geocronológicos

Con base en el estudio cartográfico realizado para reconocer las diferentes unidades geológicas, se realizó un extenso muestreo de las rocas representativas de la Sierra Los Tanques para llevar a cabo estudios geocronológicos. Las muestras se procesaron en los laboratorios del Centro de Geociencias (CGEO), UNAM, Campus Juriquilla, Querétaro (Taller de Molienda, Laboratorio de Separación de Minerales, etc.).

2. Preparación y caracterización de zircones para análisis geocronológicos U-Pb

Los zircones fueron obtenidos de muestra de roca pulverizada usando una combinación de técnicas convencionales de separación magnética y líquidos pesados empleadas en el Laboratorio de Separación Mineral del Centro de Geociencias, UNAM, Campus Juriquilla, Querétaro. Alrededor de cien granos de zircón de cada muestra fueron seleccionados cuidadosamente bajo un microscopio binocular con la finalidad de asegurarnos que los cristales fueran representativos de varias poblaciones de zircones (tamaño, forma y color) para después ser montados en una resina epóxica y, posteriormente, desbastados hasta exponer una superficie lo más cercana posible a la mitad ecuatorial de los zircones. Antes de los análisis in situ por ablación láser, las superficies pulidas de los granos de zircón fueron fotografiadas en el Denver Microbeam Laboratory del U.S. Geological Survey en Denver, Colorado, usando un microscopio electrónico de barrido (SEM; Scanning Electron Microscope) marca JEOL 5800LV con detector de cátodoluminiscencia (imágenes SEM-CL). También se obtuvieron imágenes de luz reflejada y transmitida utilizando un microscopio óptico convencional marca Olympus en el Centro de Geociencias, UNAM. Las imágenes de cátodoluminiscencia, luz reflejada y transmitida fueron obtenidas con el propósito de caracterizar la estructura interna de los zircones y elegir los sitios potenciales para los análisis de U-Pb, observando el zoneamiento relacionado a los cambios de composición química de los zircones para poder detectar posibles inclusiones, sobrecrecimientos metamórficos o herencias que cambiarían el sentido de la interpretación de los datos analíticos. Esta es una herramienta ventajosa para interpretar las edades obtenidas.

3. Geocronología U-Pb en zircones por LA-ICP-MS

Los análisis isotópicos de U-Pb en zircones fueron realizados en el Laboratorio de Estudios Isotópicos (LEI) en el Centro de Geociencias (CGEO), UNAM, Campus Juriquilla, Querétaro, utilizando la técnica de ablación láser (LA-ICP-MS). En la actualidad, está técnica de microanálisis y fechamiento es ventajosa ya que permite hacer mediciones isotópicas de alta precisión y rapidez para obtener edades y concentraciones geoquímicas en materiales geológicos.

El LEI cuenta con un sistema de ablación láser modelo Resolution M50 de la marca "Resonetics" compuesto por un láser LPX 220 tipo excímero de 193 nm de longitud de onda utilizando una mezcla de fluoruro de argón (ArF) para generar la pulsación. Este se encuentra acoplado a un espectrómetro de masas (ICP-MS) tipo quadrupolo marca "Thermo X-Series". El sistema fue recientemente descrito por Solari et al.(2010), quienes presentaron la metodología para los análisis isotópicos U(Th)-Pb en zircones. Sin embargo, a continuación presentamos de manera breve la metodología básica utilizada en el LEI.

Previo a la medición isotópica, las muestras (probeta con zircones) se limpiaron con HNO₃ 1M con la finalidad de eliminar o minimizar cualquier posible contaminación por la presencia de Pb común en la superficie de los granos. La ablación láser se realiza en una celda de nueva generación de doble volumen que puede alojar hasta 4 probetas con muestras. Los cristales de zircón fueron ablacionados dentro de esta celda en una atmósfera de He, la cual proporciona una condición óptima para este proceso (Horn y Günther, 2003). Primeramente, el haz del láser incide sobre la superficie del cristal con una energía de ~ 130 – 140 mJ y a una tasa de repetición de 5 Hz creando un hoyo provocado por la volatilización de un área del zircón (spot o punto de análisis) de ~ 33 µm de diámetro y de ~ 25 µm de profundidad para obtener un total de ~ 75 – 85 ng de masa ablacionada durante cada análisis. La ablación se lleva a cabo por alrededor de 30 segundos con el fin de minimizar la profundidad del hoyo de ablación y, de la misma manera, el fraccionamiento elemental. Posteriormente, el material ablacionado (vaporizado) es evacuado de la celda de ablación y transportado al espectrómetro de masas en un flujo de He y N₂mezclado con gas Ar (flujos de gas optimizados diariamente) para después ser analizado.

En el caso de los análisis en zircones, una secuencia típica de medición por ablación láser en el LEI inicia con el análisis de dos muestras de referencia certificada (vidrios estándar NIST SRM 610), seguido por cinco análisis de material de referencia natural cuya composición y/o edad han sido ya publicadas (zircón estándar Pleŝovice; Sláma et al., 2008) y finalmente cinco zircones de edad desconocida. Posteriormente, se hace una medición de esta muestra natural de zircón estándar Pleŝovice después de cada cinco mediciones en muestras desconocidas. El experimento finaliza con dos zircones estándar y un vidrio NIST. Esta secuencia es de gran importancia y conocida como un método estándar para poder realizar la corrección por fraccionamiento de masa y deriva instrumental (e.g., Jackson et al., 1992, 1996; Gehrels et al., 2008; Solari et al., 2010). Los análisis del vidrio NIST son utilizados para calcular las concentraciones correctas de U y Th, además de las otras concentraciones de elementos traza y tierras raras medidas durante cada análisis, mientras que los análisis del estándar de zircón Pleŝovice son usados para recalcular las relaciones isotópicas.

La calibración de los datos y correcciones por deriva instrumental (drift) fueron basadas en los estándares de zircón Pleŝovice obtenidos de una granulita potásica que tiene una edad ²⁰⁶Pb/²³⁸U concordante con una media ponderada de 337.13 ± 0.37 Ma obtenida utilizando la técnica de dilución isotópica y espectrometría de masas por ionización térmica (ID-TIMS) (Sláma et al., 2008).

Los datos isotópicos fueron adquiridos utilizando el software analítico Thermo PlasmaLab con resolución temporal, permitiendo que las relaciones isotópicas sean calculadas de los datos adquiridos en un intervalo de tiempo específico.

Durante el análisis de cada zircón los isótopos de interés principal para el fechamiento U-Pb como ²⁰⁶Pb, ²⁰⁷Pb, ²⁰⁸Pb, ²³²Th y ²³⁸U fueron determinados, además de otros isótopos importantes como ²⁹Si, ³¹P, ⁴⁹Ti, ⁸⁹Y, ⁹¹Zr, ¹³⁹La, ¹⁴⁰Ce, ¹⁴⁷Sm, ¹⁵³Eu, ¹⁶³Dy, ¹⁷⁵Lu y ¹⁷⁷Hf. Por ejemplo, el silicio y el zirconio son usados como elementos estándar internos para la cuantificación del contenido de elementos traza, considerando su concentración estequiométrica en el zircón, mientras que elementos como el P, Ti e Y, además de algunas tierras raras, son monitoreados como indicadores de la presencia de inclusiones dentro de los zircones (p.ej., monazita, apatito o titanita), las cuales podrían modificar las relaciones U(Th)-Pb del zircón y proporcionar edades equívocas y mediciones erróneas como en el caso de la presencia de Pb común.

Debido a que el trabajo analítico requiere de una precisa y sistemática reducción de los datos, cálculo de edades y concentraciones elementales de los zircones analizados, en el LEI (UNAM) se ha desarrollado el software "UPb.age" para facilitar a los usuarios una rápida y transparente reducción de datos para los fechamientos U(Th)-Pb por LA-ICPMS (Solari y Tanner, 2011). "UPb.age" fue escrito en R, un software libre de lenguaje y entorno de programación para análisis estadístico y gráfico. Un sencillo script llamado "file.trans" es distribuido junto con el "UPb.age", el cual convierte los datos producidos de los análisis por ablación láser grabados por el Thermo PlasmaLab (csv, comma- separated-value) a un formato de archivo uniforme que pude leer fácilmente el "UPb.age".

Con una serie de comandos introducidos por el usuario, el "UPb.age" aplica diferentes correcciones y, además, recalcula las relaciones U(Th)-Pb, errores y coeficientes de correlación. El "UPb.age" realiza automáticamente el proceso de integración de las señales del ICP-MS y su respectiva corrección por blancos. También identifica, mediante regresión matemática, posibles outlierse inclusiones y los presenta para que éstos sean evaluados por el usuario. El software también ofrece la capacidad de corrección por deriva instrumental usando un modelo linear.

Los resultados y datos generados de los análisis isotópicos después de los diferentes pasos realizados en el proceso de reducción utilizando el "UPb.age" son automáticamente guardados como archivos csv (data.csv y results.csv). Estos archivos contienen información importante como, por ejemplo, las relaciones corregidas de ²⁰⁷Pb/²³⁵U, ²⁰⁶Pb/²³⁸U, ²⁰⁸Pb/²³²Th y ²⁰⁷Pb/²⁰⁶Pb con sus respectivos errores estándar reportados a 1 sigma.

Los archivos csv fueron procesados en un programa macro (in house) de Excel desarrollado en el LEI, el cual permite al operador ordenar automáticamente los datos, hacer una corrección por Pb común y generar una tabla de datos lista para publicar con las relaciones isotópicas y edades; también como recalcular las concentraciones de elementos traza y mayores de los zircones analizados y producir un diagrama de REE normalizado a condrita con los datos obtenidos. Las relaciones isotópicas son corregidas por Pb común utilizando la metodología algebraica propuesta por Andersen (2002) para recalcular posteriormente las edades obtenidas. Las edades fueron calculadas y graficadas en diagramas de concordia usando el programa computacional Isoplot 3.0 (add inpara Excel) (Ludwig, 2003).

4. Imágenes de Cátodoluminiscencia de zircones

La caracterización de zircones por técnicas de microscopía de luz transmitida y reflejada, además de Cátodoluminiscencia (Cathodoluminescence; CL), es fundamental para poder diseñar los experimentos de geocronología de U-Pb en zircones utilizando la técnica LA-MC-ICPMS (Laser Ablation-Multi-collector-Inductively Coupled Plasma Mass Spectrometry) y/o SHRIMP-RG (Sensitive High Resolution Ion Micro Probe-Reverse Geometry; Micro Sonda Iónica de Alta Resolución Sensible de Geometría Inversa).

La CL a partir de zircones montados en probetas de resina epóxy doblemente pulidas nos permite obtener imágenes de zoneamientos minerales del zircón, que en ocasiones, por si solos, proporcionan información fundamental para entender los procesos de formación de los mismos. Por ejemplo, es posible identificar semillas dentro de los granos únicos de zircón, que de forma preliminar se pueden interpretar como herencia de zircones más antiguos en los que se han nucleado nuevas generaciones de zircón. En ocasiones, también se aprecian bandeados de crecimiento característicos de zircones generados a partir de magmas. Por último, también se pueden observar recrecimientos de zircón que pudieran indicar recrecimientos asociados a metamorfismo. En ocasiones, estas relaciones de crecimiento de zircones nos permiten establecer la edad relativa de estos; sin embargo, son necesarios los fechamientos de U-Pb para establecer la edad absoluta de los mismos.

La cátodoluminiscencia es una herramienta importante en la geocronología U-Pb en zircones ya que el estudio de estas imágenes ayudan a decidir el lugar en donde se muestreará el zircón (núcleo o periferia, etc.), ya sea por la técnica de ablación láser o por la técnica de microsonda iónica.

En el siguiente apartado de geocronología se muestran imágenes de cátodoluminiscencia de algunos zircones para cada muestra de roca fechada de la Sierra Los Tanques, NW de Sonora, donde se presenta el lugar de ablación y la edad para ese punto en el zircón.

Las imágenes fueron tomadas en el U.S. Geological Survey de Denver, Colorado, utilizando un microscopio electrónico de barrido (SEM) marca JEOL modelo 5600. Estos estudios fueron supervisados por la Dra. Heather Lowers con ayuda de Dr. Daniel Miggins, ambos empleados del U.S. Geological Survey.

Referencias

Andersen, T., 2002, Correction of common lead in U-Pb analyses that do not report 204Pb: Chemical Geology, 192, 59-79.

Gehrels, G.E., Valencia, V.A., Ruiz, J., 2008, Enhanced precision, accuracy, efficiency, and spatial resolution of U-Pb ages by laser ablation–multicollector–inductively coupled plasma–mass spectrometry: Geochemistry, Geophysics, Geosystems, 9(3), 1-13.

Horn, I., Günther, D., 2003, The influence of ablation carrier gasses Ar, He, and Ne on the particle size distribution and transport efficiencies of laser ablation-induced aerosols: Implications for LA-ICP-MS: Applied Surface Science, 207, 144-157.

Jackson, S.E., Longerich, H.P., Dunning, R., Fryer, B.J., 1992, The application of laser-ablation microprobe-inductively coupled plasma mass spectrometry LAM-ICP-MS to in situ trace element determinations in minerals: Canadian Mineralogist, 30,1049-1064.

Jackson, S.E., Longerich, H.P., Horn, I., Dunning, R., 1996, The application of laser ablation microprobe (LAM)-ICP-MS to in situ U-Pb zircon geochronology: Journal of Conference Abstracts, 1, 283.

Ludwig, K.R., 2003, ISOPLOT, A geochronological toolkit for Microsoft Excel, Version 3.00: Berkeley Geochronology Center Special Publication 4, 70 p.

Sláma, J., Koŝler, J., Condon, D.J., Crowley, J.L., Gerdes, A., Hanchar, J.M., Horstwood, M.S.A., Morris, G.A., Nasdala, L., Norberg, N., Schaltegger, U., Schoene, B., Tubrett, M.N., Whitehouse, M.J., 2008, Pleŝovice zircon — A new natural reference material for U-Pb and Hf isotopic microanalysis: Chemical Geology, 249, 1-35.

Solari, L.A., Tanner, M., 2011, UPb.age, a fast data reduction script for LA-ICP-MS U-Pb geochronology: Revista Mexicana de Ciencias Geológicas, 28(1), 83-91.

Solari, L.A., Gómez-Tuena, A., Bernal, J.P., Pérez-Arvizu, O., Tanner, M., 2010, U-Pb zircon geochronology by an integrated LA-ICPMS microanalytical workstation: achievements in precision and accuracy: Geostandards and Geoanalytical Research, 34(1), 5-18.

Anexo. Suplemento electrónico. Técnicas analíticas.

Tabla SE1. Datos analíticos de U-Th-Pb obtenidos por LA-ICP-MS en zircones de granitoides permo-triásicos de Sierra Los Tanques, NW Sonora, México.

Tabla SE1. (Continuación). Datos analíticos de U-Th-Pb obtenidos por LA-ICP-MS en zircones de granitoides permo-triásicos de Sierra Los Tanques, NW Sonora, México.

Tabla SE1. (Continuación). Datos analíticos de U-Th-Pb obtenidos por LA-ICP-MS en zircones de granitoides permo-triásicos de Sierra Los Tanques, NW Sonora, México.

Tabla SE1. (Continuación). Datos analíticos de U-Th-Pb obtenidos por LA-ICP-MS en zircones de granitoides permo-triásicos de Sierra Los Tanques, NW Sonora, México.

Tabla SE1. (Continuación). Datos analíticos de U-Th-Pb obtenidos por LA-ICP-MS en zircones de granitoides permo-triásicos de Sierra Los Tanques, NW Sonora, México.

Tabla SE1. (Continuación). Datos analíticos de U-Th-Pb obtenidos por LA-ICP-MS en zircones de granitoides permo-triásicos de Sierra Los Tanques, NW Sonora, México.

Tabla SE1. (Continuación). Datos analíticos de U-Th-Pb obtenidos por LA-ICP-MS en zircones de granitoides permo-triásicos de Sierra Los Tanques, NW Sonora, México.

^#Las concentraciones de U y Th (ppm) son calculadas con relación al análisis del vidrio estándar NIST 612.
^†Relaciones isotópicas corregidas con relación al análisis de un zircón estándar de edad conocida PLE, Plešovice = ~ 337 Ma; [Sláma et al., 2008; (anexo)] aplicando el método de Andersen (2002) para la corrección de Pb común.
^*Todos los errores en las relaciones isotópicas y edades están reportados a nivel 1 sigma con la excepción de la edad media ponderada reportada a 2σ. (abs) = valor absoluto
^**Porcentaje de discordancia obtenido con la ecuación ([(edad ²⁰⁷Pb/²³⁵U – edad ²⁰⁶Pb/²³⁸U)/(edad ²⁰⁷Pb/²³⁵U)]*100) propuesta en Ludwig (2003); anexo. Valores positivos indican discordancias normales y valores negativos discordancias inversas.
Las edades en negritas representan las edades utilizadas para calcular la edad media ponderada.

Manuscrito recibido: Febrero 7, 2015
Manuscrito corregido recibido: Julio 10, 2015
Manuscrito aceptado: Julio 15, 2015

Boletín de la Sociedad Geológica Mexicana Volumen 67, núm. 3, 2015, p. 509-516 http://dx.doi.org/10.18268/BSGM2015v67n3a13

pH dependence of Glyphosate adsorption on soil horizons

Hector R. Tévez¹, Maria dos Santos Afonso^2,*

¹ Facultad de Ciencias Forestales, Universidad Nacional de Santiago del Estero. Avenida Belgrano Sur 1912. 4200 Santiago del Estero, Argentina.
² INQUIMAE, Facultad de Ciencias Exactas y Naturales- Universidad de Buenos Aires. Ciudad Universitaria, Pabellón II, 3er Piso, Ciudad Autónoma de Buenos Aires, C1428EHA, Argentina.

^* This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract

Pesticides bring many problems to the environment and to human health. The first rationale for their use is increased food production. Glyphosate N-(phosphonomethyl)glycine (PMG) is a non-selective, post emergent, and broad spectrum herbicide, very well known for its extensive application in agriculture worldwide. PMG adsorption experiments were carried out in three horizons of a Typic Haplustoll soil from the Province of Santiago del Estero, Argentina.

Adsorption isotherms were fitted using Freundlich and Langmuir models. The affinity constants (K_F and K_L), the adsorption intensity (1/n) and the maximum surface coverage (Γ_max) were obtained. The results show the dependence of the parameters K_L and Γ_maxwith pH and also with the different horizons and particle size.

Keywords: Glyphosate, Adsorption isotherm, horizon, profile.

Resumen

Los pesticidas producen muchos problemas al ambiente y a la salud humana. La primera racionalización que considera el aumento en su aplicación es incrementar la producción de alimentos. El glifosato, N-fosfonometilglicina (PMG) es un herbicida no selectivo, post-emergente y de amplio espectro que es de uso extensivo en agricultura a nivel mundial. La adsorción de PMG fue llevada a cabo en tres horizontes de un suelo de la Provincia de Santiago del Estero, Argentina, clasificado como Haplustol Típico.

Las isotermas de adsorción fueron ajustadas utilizando los modelos de Freundlich y de Langmuir. Se determinaron las constantes de afinidad (K_F y K_L), la intensidad de adsorción (1/n) y el recubrimiento superficial máximo (Γ_max). Los resultados muestran la dependencia con el pH de los parámetros de K_L y Γ_max así como con la identidad de los horizontes y el tamaño de partícula.

Palabras clave: Glifosato, isoterma de adsorción, horizonte, perfil.

1. Introduction

In the last century the Province of Santiago del Estero, Argentina, lost more than 80 % their natural forest as a result of irrational logging. In the arid soil of the province, agriculture replaced forests. Soybean cultivation was developed at the expense of others crops, native forests and livestock (Pérez-Carrera et al., 2008).

Pesticides are chemicals widely used in agriculture and their use increase with the increasing of crop areas. In particular, glyphosate (N-phosphonomethylglycine, PMG) is used to remove annual grasses and perennial broadleaf weeds and woody species in agricultural, forestry and landscape. Thus, PMG is a non selective, post-emergent and broad-spectrum commercial herbicide used worldwide in soybean agriculture. In the soil, the main way of PMG degradation is microbial mediated, considering that abiotic mineralization of PMG for the horizon A exceeds 1 % reaching a maximum of 12 % degradation for 60 days exposure (Jacobsen et al., 2008).

PMG exhibits fast vertical mobility in soil, reaching high concentrations in deeper horizons where degradation is slower (Veiga et al., 2001).

PMG is a good chelating agent and can coordinate metal ion in aqueous solution, especially at near-neutral pH levels where carboxylate and phosphonate chemicals groups are deprotonated forming strong complexes (Barja et al., 2001). It can also be retained in the soil through adsorption onto aluminum and iron oxides (Nowack and Stone, 1999; Barja and dos-Santos-Afonso, 2005), clays (Damonte et al., 2007; Khoury et al., 2010 and references cited therein) and organic matter (Sposito, 1984; Piccolo et al., 1996).

The PMG adsorption on soils or clays was studied by several authors (Nomura and Hilton, 1977; McConnell and Hossner, 1985; Morillo et al., 2000; Sheals et al., 2002; Pessagno et al., 2008). In all the cases, adsorption decreased with a pH increase following an anionic adsorption behavior.

The study of competitive adsorption between PMG and phosphate on iron oxides had shown that PMG could be exchanged by phosphate (McBride and Kung, 1989; Gimsing and Borggaard, 2001), but the exchange on clays or soils is not so easy to characterize (Dion et al., 2001). When the initial phosphate level is high the glyphosate sorption decreases (Dion et al., 2001).

Thus, the surface coverage and the affinity constants for adsorption on iron oxides are higher than on clays minerals or soils, but the experimental results suggest that phosphonate is the liable chemical group for the surface coordination through inner-sphere surface complexes formation (dos-Santos-Afonso et al., 2004; Pessagno et al., 2005, 2008; Tévez et al., 2008). Previous studies on the surface coverage and the adsorption isotherms of this herbicide on soil fractions from different provinces of Argentina (Santa Cruz, Misiones, and Corrientes) followed similar patterns to those of the pure minerals that form these soils (Pessagno et al., 2005).

The aim of this work is to study the adsorption of PMG onto three different horizons of soils from Santiago del Estero Province, Argentina, with different mineral composition to understand how the mineral composition and pH are controlling the environmental fate of glyphosate.

2. Materials and methods

2.1. Chemicals

All chemicals utilized were of analytical reagent grade and were used without further purification. All solutions and soil dispersions were prepared using Milli-Q water.

PMG solutions were fresh and prepared daily by dissolving the herbicide in Milli-Q water. All PMG solution concentrations ranged from 0.05 to 10 mM.

2.2. Study area

The study area is located near Quimili in the center-east of Santiago del Estero Province between 62º 06´ W and 61º 52´ W and, 27º 24´ S and 28º 00´ S (Figure 1). Climate is semiarid mesothermal, with an average annual temperature of 19.6 °C and rainfall of between 600 and 750 mm per year concentrated in the spring-summer period (Torres-Bruchman, 1981).

The sampling area is a soil catena corresponding to that found in recent agriculture (9 years) and low for ancient agriculture (25 – 27 years).

The soil is derived from loessic sediments and it is located at a depression relief, and classified as Typic Pachic Haplustoll with grasslands, Elionurus muticus (Lorenz et al., 2000).

Samples were taken up to 130 cm of depth (Figure 2.A) from three very well differenced horizons classified as Ap (0 – 18 cm), AB (18 – 50 cm) and BC (105 – 130 cm). The Ap is the uppermost mineral horizon, disturbed by plowing or other agricultural practices. AB and BC are transitional horizons, wherein the horizon properties are dominated by horizon A properties but also have characteristics of B horizon (AB) or by horizon B properties but also have characteristics of C horizon (BC). The soil at depths between 50 and 105 cm has intermediate characteristics varying in a continuous from AB to BC and was not considered in this study. An schematic top view of pit trial is shown in Figure 2.B, each horizon was sampled at three different places indicated as 1, 2 and 3, and afterward they were mixed to get one sample per horizon.

Figure 1. Map of South America, Argentina and Santiago del Estero Province. The sampling area near Quimilí City is represented by .

Figure 2. A: Pit profile from where samples were taken and B: schematic top view of trial pits and sampling site.

2.3. Characterizations

The fresh soil samples were air-dried and ground to pass a sieve of 2 mm. pH was measured in 0.01 M CaCl₂ solution at 1:2.5 ratio of soil suspension (Hendershot et al., 1993; Schlichting et al., 1995) using a combined glass electrode. Organic matter (OM) content and soils chemical analysis were determined by the dichromate oxidation method (Schlichting et al., 1995). The available phosphorus (P) is the inorganic P, that is extractable at pH 8.5 and was determined following the experimental procedure described in Olsen et al., 1954 and Page et al., 1982. The total surface area (Sw) was measured by H₂O adsorption (Torres-Sánchez and Falasca, 1997). The total iron oxides (Fe_tot) and amorphous iron oxides (Fe_amorph) were established by dithionite (Holmgren, 1967) and oxalate method (McKeague, 1967), respectively.

Soils samples were mixed with Lithium Metaborate/Lithium Tetraborate (LiBO₂ /Li₂B₄O₇) and fused in a furnace. The molten melt was completely dissolved in acidic media of 5 % nitric acid. This solution was analyzed for major and selected trace elements by Inductively Coupled Plasma - Atomic Emission Spectroscopy (ICP-AES) The sample composition are reported as oxide percentage.

The mineralogical composition and quantitative analysis of the soils were determined by X-ray Diffraction (XRD) and using the Rietveld method (Rietveld, 1969).

Point of zero net proton charge (PZNPC) or point zero salt effect (PZSE) is the pH where the net adsorption of protons and hydroxyl ions on the surfaces is independent of electrolyte concentration. Titration curves, when surface charge is plotted against pH, frequently showed a common intersection point that match with PZNPC.

PZNPC was determined by potentiometric titration of soils dispersions starting from natural pH values near neutrality and by adding increasing amounts of standardized NaOH or HCl 0.1 M at different initial ionic strength (0.1, 0.01 and 0.0012 M KCl) under N₂ atmosphere. Soils dispersions were prepared using Milli-Q water free of CO₂, and treated by continuous bubbling of N₂, for at least one hour before starting the titrations. The extent of adsorbed H⁺ and OH⁻by soil material was determined by subtracting the quantity of HCl or NaOH required to bring the dispersion and the electrolyte solution without soil to the same pH. The surface charge was calculated as follows:

(1)

where Q, V_Tit, V_b, [tit] and m are the surface charge, the volume of titrant used for dispersion titration, the volume of titrant used for electrolyte titration, titrant concentration and the mass of the solid, respectively.

2.4. Adsorption experiment

The adsorption of herbicide by the soils was studied using batch experiments. Solutions of different concentration of glyphosate in a final volume of 11 mL were added to 0.100 g of soil samples dispersions. Dispersions were kept in constant agitation overnight at constant pH, ionic strength and room temperature to reach equilibrium. pH was adjusted during the experiment using small aliquots of HCl or NaOH solutions (0.10 M) and ionic strength was kept constant (0.1 M) using a KNO₃ solution. The sample was filtered through a 0.45 μm membrane and adsorbed glyphosate was calculated from the difference between the total added ligand and the supernatant concentration (Ce). PMG was evaluated by ion chromatography (Zhu et al., 1999) using a DIONEX DX-100 instrument with a conductivity detector, a sample injection valve, and a 25 μL sample loop. Two plastic anion columns were coupled in series to serve both as pre-column (DIONEX AG-4) and analytical chromatographic column (DIONEX AS-4). The suppressor was regenerated with 50 mM H₂SO₄ with a flow rate of 12.5 mL.min^-1. A mixture of NaOH/CO₃^-2 4 mM/9 mM was chosen as eluent with a flow rate of 1 mL.min^-1. The typical experimental error is lower than 5 % for all results.

2.5. pH effect

The pH dependence of the glyphosate uptake by soil horizons was investigated using batch isotherm experiments in a pH range from 2 to 8 with a soil concentration of 9.1 g.L^-1 and different initial concentrations of PMG at a constant ionic strength of 0.1 M of KNO₃. The pH was measured using a Metrohm 644 pH-meter with a combined glass microelectrode, and the pH was adjusted throughout the experiments using 0.1 M HCl or 0.1 M NaOH. Adsorption experiments were conducted in triplicate following the procedure described above. There were no significant differences within each replicate (p < 0.01). The expressed values represent the average of the obtained results.

2.6. Isotherms Modeling

The relationship between the ligand uptake and the sorbate equilibrium concentration at constant temperature is known as the adsorption isotherm. The adsorbent capacity of a certain material is related to the material balance adsorption: the sorbate that disappears from solution must be in the adsorbent. There are a considerable number of expressions that describe adsorption isotherms and between them, Freundlich and Langmuir models were chosen and applied for describing the equilibrium data.

2.6.1. Freundlich Model

The Freundlich isotherm fits many soil adsorption systems and is represented by equation (2):

where, Γ_e is adsorption per unit area of adsorbent; K_F is the Freundlich constant indicating the relative adsorption capacity while 1/n is the index of the heterogeneity of the surface or the adsorption intensity and C_eqis the equilibrium concentration of adsorbate in solution.

2.6.2. Langmuir Model

The Langmuir isotherm is a well known model that indicates a decrease of the available surface sites as the adsorbent concentration increases. The Langmuir isotherm assumes monolayer adsorption:

(3)

where Γ is the amount of glyphosate adsorbed (µmol.m^-2), Γ_max is the maximum amount of glyphosate adsorbed on the surface (µmol.m^-2) at a fixed pH and temperature, K_L is the Langmuir adsorption constant (mM^-1) which is related to the free energy of the reaction and C_e is the equilibrium concentration of herbicide in the solution (mM). In other words, Γ_maxis the concentration of PMG surface saturation.

3. Results and Discussion

Soil characteristics, chemical analysis, mineralogical composition and quantitative analysis are presented in Table 1, 2 and 3 respectively. XRD of the three soil horizons are shown in Figure 3.

Figure 3. XRD of the three soil horizons. Q: Quartz, Ar: Clay, F: Feldspar, Mt: Magnetite.

Table 1. Characteristics of agriculture soils profile from Santiago del Estero/Argentina.

Table 2. Chemical Analysis of agriculture soils profile from Santiago del Estero, Argentina.

Table 3. Mineralogical Composition of agriculture soils profile from Santiago del Estero, Argentina. Values in parenthesis represent estimated standard deviations.

The experimental curves of PZNPC recorded for the BC horizon are illustrated in Figure 4. Similar behavior was found for all the horizons that showed PZNPC values in the range of 7.1 – 8.1 (Table 1) following the sequence: Ap<AB<BC. PZNPC value can be explained by the absence of clay minerals with a negative permanent charge, while the presence of 2:1 clays shift the PZNPC to lower pH values (Table 3).

Figure 4. Potentiometric titration curves of the dispersions of the BC horizon at three ionic strengths (I = ½ Σ_i c_iz_i²).

The higher PZNPC value for the horizons corresponds to horizon BC that contains similar amount of quartz, lower amount of feldspars (andesine) and high amount of illite. PZNPC increase with andesine feldspar content and OM decrease. The determination coefficients of a linear fit were R²_andesine = 0.9971 and R²_OM = 0.9189. The analysis of the three parameters variations in a 3D plot presented a determination coefficient of R²= 1.0000 and a constant variance test of p < 0.0001.

To describe the adsorption behavior Freundlich and Langmuir models were applied to the equilibrium data.

The PMG adsorption isotherms of soils dispersions equilibrated at different pH values are shown in Figure 5. The Freundlich model parameters values (K_Fand 1/n ) were calculated using equation 2 and are given in Table 4. The 1/n values vary between 0.1 and 1, which indicates that this model could be used for interpreting the data. The correlation between experimental and calculated curves had a p-level between 0.137 and 0.0035; the determination coefficients were between 0.7578 and 0.9953 for different pHs and horizons.

Figure 5. Adsorption isotherm of PMG on horizon Ap, AB and BC. Solid lines are calculated using Langmuir model with constants and maximum surface coverage detailed in Table 5. ●: pH 2, ■:pH 3,♦: pH 4, ▲: pH 5, ▼: pH 6 and : pH 8.

Table 4. Freundlich parameters (In μmol^1-1/n.m^-2) for glyphosate adsorption on Santiago del Estero Province soils.

Table 5. Langmuir parameters for PMG adsorption on soils of Santiago del Estero Province, Argentina

The Langmuir model was also applied to make an interpretation of PMG adsorption isotherms on soils dispersions equilibrated at different pH values. This is shown in Figure 5, where solid lines are calculated using this model (equation 3) and Γ_max and K_L, are given. The isotherm model parameters were obtained by a non-linear optimization using the Solver-Excel tool. The parameters values were obtained from the plot of the inverse of the surface coverage as a function of the inverse of the equilibrium concentration. Results of the adsorption and surface coverage calculations were normalized with Sw data and the various horizons were contrasted. The correlation between experimental and calculated curves had a p-level between 0.050 and 0.001; the determination coefficients (R²) obtained were between 0.9300 and 0.9999; and were higher than those obtained using the Freundlich model. Thus, the Langmuir model would better represent the adsorption process of PMG on the Santiago del Estero Province soil.

The dependence of the surface coverage with PMG concentration in the various horizons at constant pH = 5 is shown in Figure 6. Horizon Γ_maxsequence is Ap<AB <BC. This behavior is similar to those found for PZNPC.

Figure 6. Adsorption isotherm of PMG on horizon Ap, AB and BC at pH 5.

The dependence of the surface coverage with pH in the various horizons is also shown in Figure 5. The adsorption capacity increases from pH 8 to 2. This pH effect was normally observed during the adsorption of anionic species. Consequently, PMG interaction with the surface occurs throughout the anionic chemical groups (carboxylate or phosphonate) and not through the amine group (pKa = 10.14) that is positively charged at the studied pH range (Figure 7).

Figure 7. PMG acid-base equilibrium.

The surface coverage decrease, ΔΓ_max, for horizon Ap is around 41 % for this pHs range (Table 5). This difference is lower for horizons BC, 27 %, and AB, 12 %.

The different composition and properties of the soils (Table 1), will affect sorption of the sorbate. This variability may also be linked to the organic matter content (Table 1) because of the chemical groups present on the OM (carboxyl, hydroxyl, amine, phenoxy, etc) that can coordinate the solid inorganic surface active sites or block the access of PMG to the inorganic surface. In consequence, OM presence can reduce PMG adsorbed on the solid surface. In fact, Γ_max varies linearly with OM content with determination coefficients among R²_{pH = 2} = 0.9548 and R²_pH = 8= 1.0000. The affinities of the substances involved in the adsorption process are dependent on the identity and number of chemical groups present on the OM.

The highest adsorption capacity is obtained by horizon BC followed by horizon AB, and the lowest for horizon Ap. A similar sequence was obtained for PZNPC (Table 1), indicating that the horizon with higher positive surface charge presents higher PMG surface coverage.

The ratio of the Γ_max of the horizons (R_H1/H2) was calculated as follow

(4)

where H1 and H2 denote two different horizons, Γ_maxH1 and Γ_maxH2 indicate the maximum coverage of H1 and H2 horizons, respectively. This ratio between the horizons BC and AB was R_BC/AB = 46 %, between horizons BC and Ap was R_BC/Ap = 72 % and between horizon AB and Ap was R_AB/Ap = 50 %. These percentages are opposed to the phosphate content that follows the order of Ap> AB> BC. The high adsorption on deep horizons with regard to horizon Ap could be due to the competition of herbicide with phosphate groups for surface sites (Dion et al., 2001; Gimsing et al., 2007). Adsorption of glyphosate and phosphate in soil is similar to that which occurs on clay minerals (Dion et al., 2001; Gimsing and dos-Santos-Afonso, 2005).

The highest adsorption constants correspond to horizon AB (Table 5). The changes in the adsorption affinity between horizon BC and AB reach ∆K_L= 46 % while horizon BC decreases 73 % in respect to horizon Ap.

The relatively high phosphate and low surface area (Table 1) of the Ap horizon, could be the cause for which it reaches its maximum at relatively low concentrations of PMG adsorption. The greater slope of the adsorption curves in the AB horizon indicate that PMG binds more strongly to the active sites of this horizon. Previous studies indicated that PMG bound iron oxides surfaces more strongly than clay minerals (dos-Santos-Afonso et al., 2004). Thus, the active site of PMG adsorption on the AB horizon could be the surface iron atoms and the higher adsorption in this horizon is directly related to higher iron content.

The adsorption on horizon BC does not reach maximum coverage in the experimental conditions. The adsorption isotherms with a low initial slope describe an adsorption process with characteristic adsorption constants of low energy interaction (Figure 5).

Note that in the working pH range an acid-base dissociation of the PMG molecule that contains amine, carboxylate, and phosphonate functional groups take place The constant and the equilibrium reactions of acid-base dissociation of glyphosate (Barja and dos-Santos-Afonso, 1998) are shown in Figure 7, where I, II and III are the main species presents in the studied pH range. Previous studies suggested that the adsorption process occurs by surface complex formation via phosphonate group coordination to the mineral surface (Barja and dos-Santos-Afonso, 2005; Khoury et al., 2010). Similar behavior should be expected for the adsorption of PMG on soils where coordination would occur on the surface of the minerals that compose them.

4. Conclusions

The major factor in PMG adsorption on soil samples is given by the pH, which could be due to the influence of this parameter on the PMG molecule and on the surface charge of the soil particles. PMG adsorption increase with acidity, and this increase correspond to the adsorption of a ligand with a negative net charge.

Sorption of glyphosate in soils is similar to the adsorption of the organic molecule on the soil components such as clay minerals, iron oxides and OM. For these soils with a low organic matter contents and/or similar amounts of clay in the various horizons, the adsorption would be determined by the content of phosphorus, iron oxide and the specific surface. Regarding the relative adsorption capacity of the soil, the adsorption process has a different behavior profile, where the deeper horizon (BC) has a higher capacity retention for this herbicide. The lower adsorption in the AB and Ap horizons could be influenced by the higher content of phosphorus. However, the strength of the interaction, as given by the Langmuir Model Constant K_Lis larger on horizon AB and would be linked to the illite and iron oxide content that have a better distribution in AB.

It should be noted that the Langmuir adsorption model is the best fit to the adsorption experimental results in these soils, although the Freundlich model has a good fit for some pHs.

Given the adsorption extent found in this study, it is expected that pesticides will be retained in these soils. This strong interaction could prevent the pesticides movement into the groundwater. On the other hand, this retention rate could result in the release of the herbicide on the environment due to displacement by runoff.

Acknowledgements

The authors acknowledge the Universidad de Buenos Aires, Secretaría de Ciencia y Técnica and MINCyT- ANPCyT- FONCyT for financial support. The authors are also grateful to Susana Conconi and Jorge Maggi from Centro de Tecnología de Recursos Minerales y Cerámica (CETMIC) for Rietveld analysis of soils.

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Manuscript received: October 27, 2014
Corrected manuscript received: February 7, 2015
Manuscript accepted: February 10, 2015

Boletín de la Sociedad Geológica Mexicana Volumen 67, núm. 3, 2015, p. 493-508 http://dx.doi.org/10.18268/BSGM2015v67n3a12

Surface Complexation Modelling of Arsenic and Copper Immobilization by Iron Oxide Precipitates Derived from Acid Mine Drainage

Alba Otero-Fariña¹, Raquel Gago², Juan Antelo^2,*, Sarah Fiol¹, Florencio Arce¹

¹ Department of Physical Chemistry, University of Santiago de Compostela, Avenida de las Ciencias s/n, 15782 Santiago de Compostela, Spain.
² Department of Soil Science and Agricultural Chemistry. University of Santiago de Compostela, Rúa Lope Gómez de Marzoa s/n, 15782 Santiago de Compostela, Spain.

^* This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract

Acid mine drainage (AMD) constitutes a serious environmental problem in mining areas due to the acidification of soils and aquatic systems, and the release of toxic metals. Many of the pollutants that occur in AMD display a high affinity for the surfaces of the aluminium and iron oxides that are typically present in systems affected by AMD. This binding affinity reduces the mobility of trace metals and metalloids, such as copper and arsenic, thus helping to mitigate contamination of aquatic systems. In the present study, water samples and iron-rich bed sediments were collected in areas affected by copper mining activities. A loose ochre-coloured precipitate occurring on the banks of a river close to an abandoned tungsten and tin mine was also sampled. The composition of the precipitate was established, and adsorption experiments were performed with copper and arsenate ions to determine the ability of natural iron precipitates to reduce the concentration of these ions in solution. Surface complexation models provided a good description of the behaviour of natural iron oxides in terms of copper and arsenate retention. Use of this type of model enables prediction of the distribution of pollutants between the solid and solution phases and analysis of their mobility in relation to environmental conditions (pH, ionic strength, presence of competing species, etc.).

Keywords: Acid mine drainage, iron oxides, adsorption, trace elements, arsenic, surface complexation model.

Resumen

El drenaje ácido de mina (AMD) constituye un importante problema ambiental debido a la acidificación y la liberación de metales tóxicos que produce en el suelo y en los sistemas acuáticos próximos a las zonas mineras. Existe una elevada afinidad de muchos de los contaminantes presentes en AMD por la superficie de los óxidos de aluminio y hierro que son constituyentes típicos presentes en los sistemas afectados por AMD. Esta afinidad puede contribuir a atenuar la contaminación por metales traza y metaloides, tales como el cobre o el arsénico, en los sistemas acuáticos mediante la reducción de su movilidad. En el presente estudio se han recogido muestras de agua y de sedimentos con alto contenido en hierro en un área afectada por minería de cobre. Además, se recogió un precipitado amarillo de las orillas de un río situado en las proximidades de una antigua mina de wolframio y estaño. Estos precipitados fueron caracterizados para establecer su composición y se realizaron experimentos de adsorción con los iones cobre y arseniato para determinar la capacidad de los precipitados naturales de hierro para reducir su concentración en disolución. Se comprobó que los modelos de complejación superficial son capaces de reproducir el comportamiento de estos precipitados naturales en términos de retención de cobre y arseniato. Estos resultados permitirán predecir la especiación de estos contaminantes en presencia de óxidos de hierro formados en ambientes afectados por AMD y analizar su movilidad en función de las condiciones (pH, fuerza iónica, presencia de especies que compitan, etc.).

Palabras clave: Drenaje ácido de mina, óxidos de hierro, adsorción, elementos traza, arsénico, modelo de complejación superficial.

1. Introduction

Mining and processing of mineral ores constitute major sources of contamination in soils, sediments and aquatic systems worldwide. Oxidation of sulphide minerals (mainly iron sulphides such as pyrite, arsenopyrite and chalcopyrite) leads to acid mine drainage (AMD), which causes acidification of surface waters and the release of trace elements into soils and water systems (Bigham and Nordstrom, 2000; Olías et al., 2006; Nordstrom, 2011). Weathering of iron sulphide minerals produces large amounts of secondary iron precipitates, which may contribute to the removal and immobilization of trace elements present in systems affected by AMD (Regenspurg and Peiffer, 2005; Schroth and Parnell, 2005; Acero et al., 2006; Burgos et al., 2012).

The nature and composition of the secondary iron precipitates present in AMD systems is mainly determined by the concentration of sulphate ions and the pH of the aqueous phase (Bigham and Nordstrom, 2000). Thus, schwertmannite, Fe₈O₈(OH)₆(SO₄)₂, is commonly formed at pH 3.0 – 4.0, while jarosite, KFe₃(OH)₆(SO₄)₂, is usually formed at lower pH values. At circumneutral pH values (6 – 8), ferrihydrite or hydrous ferric oxide, Fe(OH)₃, and goethite, α-FeOOH, are the predominant secondary minerals present in the system. The precipitates formed in AMD systems usually contain different secondary iron minerals; some of these mineral phases change within weeks or months as forms such as schwertmannite are metastable and can undergo phase transformation to more crystalline mineral phases (Bigham et al., 1996; Regenspurg et al., 2004).

Study of the surface reactivity of the secondary iron minerals occurring in AMD has been of great concern in the last decade. These minerals are naturally occurring attenuators for species such as arsenic and trace metals that may be present in these systems. Many authors have attempted to elucidate the mechanism of such attenuation in natural precipitates and synthetic analogues (Jönsson et al., 2006; Burton et al., 2009; Paikaray et al., 2011; Antelo et al., 2012; Paikaray et al., 2012; Maillot et al., 2013). Immobilization of trace metals and metalloids by these iron minerals is known to take place via surface adsorption and coprecipitation (Martínez and McBride, 2001; Lee et al., 2002; Antelo et al., 2013). Iron oxide minerals usually have a high specific surface area and variable surface charge, properties that may favour the efficient retention of both anions and cations in systems affected by AMD. Schwertmannite and jarosite may decrease the mobility of trace elements by coprecipitation during formation of the iron mineral oxide or by surface adsorption onto the pre-existing minerals. Moreover, if anionic species such as arsenate are present in the system, the immobilization mechanism may involve anion exchange with the sulphate groups present in the crystalline structure of these minerals (Carlson et al., 2002; Burton et al., 2009; Antelo et al., 2012).

Numerous adsorption studies on synthetic analogues have been reported in the literature; however, this does not guarantee that the analogues are relevant or behave identically in natural systems. The data obtained in such studies do not reflect the fact that natural oxides are formed in multicomponent systems (e.g. AMD usually contains Fe, S, As and multiple trace metals). Therefore, coprecipitation is likely to occur and may lead to the formation of different secondary minerals and to the presence of impurities in the minerals. In order to determine the efficiency of secondary iron minerals as natural contaminant scavengers, as well as the immobilization mechanism involved, it is important to identify the reactions that the mineral adsorbent undergoes following changes in the physico-chemical properties of the system, e.g.pH, ionic strength and temperature. Thermodynamic description of the surface reactivity of iron oxides is crucial for developing surface complexation models that predict the fate of environmentally relevant species. Therefore, detailed description and quantification of adsorption reactions are necessary to predict the mobility and bioavailability of trace elements in soils and aquatic systems. In the present paper, we investigate the adsorption of arsenate and copper on natural iron oxide precipitates collected from aquatic systems affected by AMD. The aim of the study was to improve our understanding of the processes controlling the adsorption of trace elements and to assess the capacity of surface complexation models developed for synthetic analogues to predict the behaviour of arsenate and copper in the presence of natural iron precipitates.

2. Materials and methods

2.1. Field sites and sample collection

Iron oxide precipitates were collected in areas close to the abandoned Touro copper mine (NW Spain, 42° 52′ 34′′ N 8° 20′ 40′′ W) and the abandoned Fontao tungsten and tin mine (NW Spain, 42º 45´ 16´´ N 8º 13´ 55´´ W) between September and October 2013. In the area encompassing the Touro mine, which was exploited between 1974 and 1988, the geological substrate predominantly consists of amphibolite, with large quantities of metal sulphides such as pyrite and chalcopyrite. Weathering and oxidative dissolution of these minerals has led to the release of AMD to the neighbouring streams, producing frequent episodes of extreme acidity and mobilization of toxic elements in the surface waters (Álvarez et al., 1993). During the last 15 years, remediation processes and environmental monitoring have been conducted at the most critical sites (Álvarez et al., 2011). The area encompassing the abandoned Fontao mine, which was exploited between 1934 and 1973, includes numerous Sn-W quartz veins, with cassiterite and wolframite as the main ore minerals and with a significant presence of sulphide minerals such as pyrite, chalcopyrite and arsenopyrite.

Two streams were selected as sampling sites for the present study: the Portapego stream (T-PO), which flows from the Touro mine to the river Lañas, and the Orza stream (F-OR), which is close to the Fontao mine. At sampling site T-PO (Figure 1a), iron-rich AMD bed sediments were collected from the upper 10 cm. At sampling site F-OR (Figure 1b), loose ochre-coloured precipitates were collected from the banks of the stream. Both samples were kept in polyethylene flasks and stored at 4 ºC in darkness until analysis, to prevent changes in the chemical and mineralogical composition. The T-PO sediment sample was air-dried, sieved (< 50 μm) and ground to a fine powder for the laboratory study. The F-OR precipitate was washed carefully with ultrapure water and centrifuged for 20 minutes at 12000 rpm to remove soluble ionic species and other impurities, and the solid was then re-suspended in ultrapure water. The conductivity of the supernatant was measured to ensure that no ionic species were present. A fraction of the final suspension was freeze-dried to obtain solid samples for characterization of the iron precipitates, while the remaining fraction was maintained as a suspension for the adsorption experiments.

Water samples were also collected at both sampling sites to assess the physico-chemical properties and the degree of metal contamination. In the field, these samples were immediately filtered through 0.45 μm Millipore filters and subsamples were acidified with 1 % HNO₃for metal analysis. The pH, temperature, electrical conductivity (EC) and dissolved oxygen were measured in situ. Water samples were transported to the laboratory and stored at 4 °C until analysis.

Figure 1. Photographs of the sampling sites. a) ochreous precipitates on the Portapego stream bed sediments, and b) loose precipitate in the Orza stream.

2.2. Characterization of iron oxide precipitates

Powder X-ray diffraction (XRD) patterns were obtained (in a Phillips PW1710 diffractometer) by measuring the scintillation response to CuKα radiation over the range 15º to 70º 2θ, with a step size of 0.02º and a counting time of 6 seconds per step. XRD patterns of synthetic analogues (goethite, schwertmannite and ferrihydrite), previously prepared in the laboratory by the methods recommended in the literature (Cornell and Schwertmann, 1996), were also obtained for comparative purposes. ATR-FTIR spectra of the precipitates, synthetic schwertmannite and K₂SO₄, were recorded in a JASCO FTIR-4200 spectrophotometer. The powdered samples were mixed homogeneously and placed on a ZnSe ATR crystal plate (Pike MIRacle Single Reflection ATR). The spectra obtained corresponded to at least 50 co-added scans with a resolution of 4 cm^-1. The IR spectra of the sulphate bands were measured in the range 1250 – 900 cm^-1. The chemical composition of the iron oxide precipitates was determined after digestion of 0.05 g of the precipitate in 50 mL of 6 M HCl. The concentrations of Fe, Al, Mn, As, Cu, Ni, Pb and Ni were measured in the digested samples by inductively coupled plasma optical emission spectroscopy (ICP-OES, PerkinElmer Optima 3300DV). The sulphate concentration was determined by a turbidimetric method (Clesceri et al., 1998), in a Jasco V-530 UV/VIS spectrophotometer. The poorly crystalline iron oxides were extracted by ammonium oxalate for quantification (McKeague and Day, 1966). Operationally, the difference between the total digestion and the oxalate extraction enables distinction between the poorly crystalline forms (schwertmannite or ferrihydrite) and the more crystalline forms (goethite). The iron precipitates were extracted with 0.2 M acid ammonium oxalate (pH 3.0) in the dark for 4 h at a solid/solution ratio of 10 g/l. Dissolved Fe and Al in the oxalate extracts were measured by ICP-OES. The BET specific surface area (SSA) was measured by N₂adsorption in a Micromeritics ASAP 2000 analyzer (V3.03).

Trace metal concentrations in the water samples were analysed by ICP-OES, while the concentrations of major cations (Fe, Al, Ca, Mg, Na, and K) were determined by atomic absorption spectroscopy (AAS, PerkinElmer 1100B). The concentrations of sulphate, nitrate and chloride were determined by standard methods (Clesceri et al., 1998).

2.3. Arsenate and copper adsorption on AMD precipitates

The effect of pH on the adsorption of both arsenate and copper was evaluated in batch experiments. Suspensions of the AMD precipitates (1 g/l for the arsenate experiments, and 0.5 g/l for the copper experiments) were prepared in 20 ml of KNO₃ as the inert electrolyte. All experiments were carried out with initial arsenate concentrations of 285 and 570 µM or with initial copper concentrations of 100 and 500 µM. Adequate volumes of stock solutions of arsenate (0.04 M KH₂AsO₄) and copper (0.1 M Cu(NO₃)₂) were added to produce the desired concentrations on the suspensions of AMD precipitate. The pH of the suspensions was adjusted to within pH 3 – 10 by addition of 0.1 M HNO₃ or 0.1 M KOH. This broad pH range was selected to yield measurable adsorption of both arsenate (relatively low pH values) and copper (relatively high pH values) and to enable comparison of ion adsorption on the precipitates with that reported for synthetic analogues. The samples were shaken for 24 hours in a reciprocal shaker (IKA Labortechnik H5501 Shaker), as preliminary experiments indicated that shorter contact times were sufficient to ensure that equilibrium was achieved. During the equilibration period, the pH was measured periodically and, when necessary, readjusted by adding small amounts of HNO₃ or KOH solutions. Special care was taken to prevent the presence of CO₂, by maintaining the suspensions in N₂atmosphere.

In order to analyse the effect of the ionic strength on the adsorption of arsenate to the AMD precipitates, additional experiments were carried out at ionic strength 0.01, 0.1, and 0.5 M in KNO₃. Batch experiments were carried out as described above, i.e. arsenate was added (initial concentration of 570 μM) to 20 ml of the AMD suspension (1 g/l), the pH was adjusted (to within pH 4 – 10) with 0.1 M HNO₃or KOH, and the samples were shaken for 24 hours until equilibrium was achieved.

Once equilibrium was reached, the samples were filtered through 0.45 µm Millipore membrane filters, and the concentration of arsenate or copper was measured in the filtrate. The concentration of arsenate was determined by the colorimetric method proposed by Lenoble et al.(2003), and the concentration of copper was determined by ICP-OES. The concentration of the adsorbed ion was then calculated as the difference between the initial amount added to the suspension and the final amount remaining in solution.

Each experiment was carried out in duplicate (at least) to confirm the reproducibility. All chemicals were of Merck pro analysis grade quality and the water used in the experiments was ultrapure and CO₂free. Polyethylene flasks were used to prevent contamination of the AMD precipitates with silicate, and the temperature was maintained at 25 ± 1 ºC in all adsorption experiments.

2.4. Surface complexation modelling

Various geochemical and surface complexation models (SCMs) have been developed in the last few decades to elucidate the processes that control the mobility and bioavailability of chemical species in soil and aquatic systems (Groenenberg and Lofts, 2014). Models of the solid/solution interface are powerful tools that can help unravel the mechanisms controlling ion adsorption and predict the reactivity of the charged mineral surfaces present in soils and sediments. These models are generally divided into two main parts: i) one part that describes the solid surface, including the type and reactivity of surface sites, the species adsorbed, the surface charge, etc.; and ii) another part describes the electrostatics, charge distribution and potential decay at the solid/solution interface. Among many SCMs that have been applied so far, the generalized two-layer (GTL) model, the triple layer (TLM) model and the charge distribution (CD) model have become the most popular for describing the surface reactivity of crystalline and amorphous iron oxides such as goethite and ferrihydrite (Davis et al., 1978; Dzombak and Morel, 1990; Hiemstra and van Riemsdijk, 1996). However, use of these models to describe the adsorption behaviour of iron precipitates present in AMD is rather complicated due to the difficulties that exist in characterizing these natural oxides. AMD precipitates may comprise different crystalline and amorphous iron oxides, depending on the physico-chemical conditions of the system, and may contain impurities not present in the synthetic analogues.

In the present study, arsenate and copper adsorption data for the AMD precipitates were initially modelled using the GTL model, which is less mechanistic and structurally-based than other SCMs. The solid/solution interface is simplified to a surface plane and a diffuse double layer that neutralizes the surface charge. This conceptual interface structure does not distinguish inner- and outer-sphere complexes. More realistic SCMs consider a diffuse double layer with at least one Stern plane, resulting in a basic or an extended Stern layer model to describe the solid/solution interface. The simplicity of the GTL model results in fewer adjustable parameters in the modelling calculations, but may enable accurate description and prediction of the adsorption behaviour of anions and cations over a wide range of conditions (Mathur and Dzombak, 2006; Karamalidis and Dzombak, 2010). A detailed description of the SCM, including its formulation for ion adsorption, has been reported by Dzombak and Morel (1990) for amorphous iron oxides. Briefly, the surface groups (≡FeOH) behave as a diprotic acid and the surface charge behaviour is described using a 2-pK approach (log K_H1, log K_H2). An electrostatic term that accounts for the coulombic interactions is included in the model in order to obtain intrinsic constants that do not change with surface charge.

As a modelling exercise, the adsorption data were also simulated using the CD model, which assumes a more realistic approach to describe the solid/solution interface and the surface reactions occurring. The contribution of anion exchange reactions with the sulphate ions present in the structure of the precipitates was considered. The CD model considers separate surface groups (≡FeOH and ≡Fe₃O) and specific surface complexation reactions. Protons were assumed to bind to ≡FeOH and ≡Fe₃O groups, while arsenate and copper ions were assumed to bind only to ≡FeOH groups. Protonation of the surface groups was described using a 1-pK approach, while Pauling’s valence bond concept was used to determine the charge distribution of ions over the coordinating ligands. The CD model also considers a spatial distribution of the charge at the solid/solution interface. Therefore, the charge is distributed in 3 electrostatic planes: i) the 0-plane, corresponding to the mineral surface and where the charged surface groups are located; ii) the 1-plane, which divides the Stern layer; and iii) the 2-plane, which separates the Stern layer from the diffuse layer. The charge of inner-sphere complexes is distributed between the 0-plane and 1-plane, while outer-sphere complexes are assumed to be single point charges and are usually situated in the 1-plane (separated from the surface by water molecules). The interfacial charge distribution of a surface complex between the electrostatic planes can be calculated using the Brown bond valence concept.

Modelling calculations for the Generalized Two-Layer model were carried out using Visual MINTEQ (Gustafsson, 2012). The parameters required for describing the adsorption of both arsenate and copper were optimized by a trial-and-error procedure. Constants were systematically varied in order to minimize the root-mean-square error in the adsorbed fraction. CD model simulations were conducted with the Equilibrium Calculation of Speciation and Transport (ECOSAT) program (Keizer and van Riemsdijk, 1998).

3. Results and Discussion

3.1. Water chemistry

Sampling site T-PO is severely affected by AMD as indicated by the chemical composition and physico-chemical properties of the water samples, i.e. low pH, high electrical conductivity and high concentrations of Fe and SO₄ (Table 1). Oxidation of sulphide minerals releases high concentrations of sulphate and Fe ions (Nordstrom, 2011). The concentrations of Fe were lower than expected, indicating that most of the dissolved Fe was precipitated, via hydrolysis reactions, to form iron oxide minerals (Burgos et al., 2012). The bed sediments were coated with reddish-yellowish iron precipitates (Figure 1a). Moreover, the concentrations of dissolved trace metals in samples from the Portapego watercourse were higher than the recommended limits for drinking water, established by the EU (European Commission, 1998). However, the newly formed iron oxides can easily remove trace metals from solution either by coprecipitation or by adsorption processes.

The results obtained for the Orza stream indicate that the AMD had only a slight effect on the water quality. The pH, EC and concentrations of major elements were within the usual ranges for uncontaminated surface waters. The concentrations of most of the trace elements analysed were below detection limits, and the concentrations of Cu and Zn were 2 – 3 orders of magnitude lower than those found in the Portapego stream. Unlike in T-PO, As was detected in F-OR, [As] = 17.2 µg/l, indicating potential enrichment of the stream sediments with arsenic-rich mineral forms.

Table 1. Chemical analysis of the water samples from the Portapego (T-PO) and Orza (F-OR) streams.

3.2. Characterization of iron oxide precipitates

The iron oxides present in sampling sites T-PO and F-OR were characterized by XRD and the diffractograms were compared with those obtained for the synthetic analogues. The X-ray diffractograms revealed significant differences in the mineralogy of the iron oxides collected at both sampling sites (Figure 2). The dominant mineral phase in sample F-OR is an amorphous iron oxide that resembles ferrihydrite. The diffractogram shows a broad band at ~ 35º and a low intensity band at higher 2θ, ~ 60 – 65º. No additional peaks indicating the presence of goethite or schwertmannite were found for this sampling site. The absence of schwertmannite phases confirms that sampling site F-OR was not greatly affected by AMD discharges from the nearby abandoned tungsten-tin mine. Sample T-PO presents several peaks that can be assigned to the presence of goethite. According to Asta et al. (2010), the weak XRD peaks of schwertmannite can be masked by the peaks of more crystalline phases, which are usually of higher intensity. The XRD data do not clarify whether goethite is the only iron oxide phase formed or schwertmannite is also present. The metastable character of schwertmannite particles favours phase transformation to goethite or other iron crystalline phase within weeks or months, depending on the physico-chemical conditions and water chemistry of the AMD system. Studies by Kumpulainen et al. (2007) and Peretyazko et al.(2009) on the mineralogy of AMD precipitates showed seasonal variations in the occurrence of both mineral phases. Schwertmannite was the dominant mineral present during spring, but it was then partially transformed to goethite during the warmer summer months because of changes in the water chemistry.

Figure 2. X-ray diffractograms of the iron oxide precipitates T-PO and F-OR and of goethite (GOET), ferrihydrite (FERR) and schwertmannite (SCHW).

As already pointed out, poorly crystalline oxides, such as schwertmannite, may be difficult to detect by XRD in mixtures containing more crystalline forms. Nevertheless, on the basis of the concentration of Fe (4.41 mmol/g) measured in the ammonium oxalate extract, the amount of poorly crystalline forms exceeded the amount of the more crystalline forms. Partition of Fe between the oxalate and total extractable phases showed that 77.9 % of the total Fe corresponded to poorly crystalline oxides (schwertmannite-like). According to the concentrations of sulphate measured in the digested samples (Table 2), sample T-PO contained a large amount of sulphate in its crystalline structure (or adsorbed to the mineral surface). The ideal chemical formula for schwertmannite is Fe₈O₈(OH)_8-2x(SO4)_x, where x ranges between 1 and 1.75. Although the sulphate content range proposed by Bigham et al. (1990) is widely accepted, a recent study by Caraballo et al. (2013) pointed out that the proposed range was obtained with the data available in the 1990s. However, when more recent information on the chemical composition of natural schwertmannite particles is taken into account, a wider range (0.52 – 1.84) is obtained. The concentration of SO₄ measured after complete dissolution of the T-PO precipitate (Table 2) is within the latter range. The Fe:SO₄ molar ratio, which is commonly used to characterize the composition of schwertmannite particles, is 6.14. This molar ratio falls within the range proposed for ideal schwertmannite (4 – 8) and also within the broader range proposed by Caraballo et al. (2013), for natural schwertmannite samples (3.77 – 15.53). These results suggest the presence of schwertmannite particles in the sample collected at the T-PO site. The concentration of trace elements in the AMD precipitate was low (Table 2) or negligible. Although a higher concentration of Cu may be expected, the measured value is comparable with the values obtained by Kumpulainen et al.(2007) for AMD precipitates collected from the surroundings of copper mines.

Table 2. Concentration of major and trace elements in the iron precipitates collected from the Portapego and Orza streams.

Abbreviations: tot = total digestion; oxa = ammonium oxalate extraction.

The concentrations of Fe and SO₄ in sample F-OR were higher than those in sample T-PO. The Fe:SO₄ molar ratio was 2.84, which is outside the range proposed by Caraballo et al. (2013), confirming the XRD results indicating the absence of schwertmannite particles in the F-OR precipitate. The high concentration of sulphate may be associated with surface adsorption to the newly formed precipitate resembling ferrihydrite. Iron oxides such as goethite and ferrihydrite are known to act as scavengers for dissolved species and may immobilize sulphate ions under suitable conditions, i.e. pH < 7.0 (Fukushi et al., 2013). The Fe extracted with ammonium oxalate accounts for almost 95 % of the total iron content, indicating that ferrihydrite (or hydrous iron oxide) is the main mineral phase present in the F-OR precipitate. The concentration of the trace elements analysed was rather low, which was expected because, as stated above, this sampling site was not greatly affected by AMD.

Figure 3 shows the ATR-FTIR spectra obtained for the iron precipitates and the synthetic analogues. Data analysis focuses on the 1200 – 900 cm^-1 region, in which bands associated with sulphate vibrations (S-O stretching bands) are usually found. Bands at a lower wavenumber (represented by the dotted lines shown in Figure 3) can be assigned to Fe-O stretching. The number of peaks observed between 1200 and 900 cm^-1, along with their relative intensity and position, are characteristic of the molecular symmetry and coordination of sulphate ions (Zhang and Peak, 2007). Clear differences between samples are observed. In the case of sample T-PO, three bands were detected in this region, which might be assigned to asymmetric stretching (ν₃) bands (~ 1096 and ~ 1032 cm^-1) and to a symmetric stretching (ν₁) band (~974 cm^-1). These bands, previously identified in different studies involving synthetic (Peak et al., 1999) and natural (Kumpulainen et al., 2007) iron oxides, are indicative of the presence of adsorbed or structural sulphate groups. Splitting into separate ν₃ bands is common for iron oxides formed at low pH (Fukushi et al., 2013; Tresintsi et al., 2014) and was also observed in the synthetic schwertmannite analysed (~ 1110 and ~ 1066 cm^-1). This suggests that sulphate groups are present as inner-sphere complexes on the mineral surface and on the crystalline structure. If outer-sphere complexes were dominant, a broader band (with no peak splitting) would be observed at 1100 cm^–1, resembling the FTIR spectra of free sulphate groups. In the case of the F-OR precipitate, these bands were not present, which suggests that sulphate groups were not adsorbed as inner- or outer-sphere complexes. Considering the results reported by Kumpulainen et al. (2007), iron oxides collected from mine soils of neutral pH (as in the present case) do not display S-O stretching bands. Therefore, the broad band at 945 cm^–1could be assigned to Fe-O-Si, indicating co-precipitation or adsorption of silicate groups. However, the nature of sulphate groups present in the F-OR precipitates and detected by analysis of the chemical composition remains unresolved. Further analysis using more advanced techniques, such as X-ray absorption spectroscopy or X-ray photoelectron spectroscopy, should be carried out to clarify the nature and the location of the sulphate groups present in the iron precipitates under study.

The SSA of the T-PO precipitate determined by the BET method was 127 m²/g, which falls within the range for schwertmannite particles (100 – 300 m²/g) reported by Bigham et al. (1990). Slow crystallization may favour higher surface area values for schwertmannite particles (Regenspurg et al., 2004). On the other hand, lower SSA (< 100 m²/g) would be expected if goethite were the dominant mineral phase of the T-PO precipitate. The SSA obtained for the F-OR precipitate was 216 m²/g, which is similar to the surface area determined for synthetic ferrihydrite by the same method (Antelo et al., 2010; Zhu et al., 2011).

Figure 3. ATR-FTIR spectra of the iron precipitates collected at sampling sites T-PO and F-OR. The spectra of synthetic schwertmannite and K₂SO₄ are also shown.

3.3. Arsenate removal by AMD precipitates

The adsorption of arsenate as a function of pH and ionic strength is shown in Figure 4, along with the GTL modelling predictions. Adsorption decreased gradually and continuously as pH increased in the range 3 – 10. This decrease can be explained by the fact that the surface of the iron oxide becomes negatively charged (or less positively charged) as the pH increases. Greater electrostatic repulsion will occur towards the less protonated arsenate species that predominate at the highest pH values, favouring the mobilization of arsenate. In addition to surface complexation with the iron hydroxyl groups present at the mineral surface, adsorption of arsenate on sample T-PO, which can be defined as a mixture of goethite and schwertmannite particles, involves anion exchange reactions with the sulphate ions present in the schwertmannite crystalline structure. Evidence for anion exchange reactions involving sulphate release from schwertmannite has been obtained in different studies (Burton et al., 2009; Antelo et al., 2012). The exchange coefficient (R_ex) values obtained in those studies were pH dependent and always lower than 0.5 mol SO₄/mol AsO₄. An exchange coefficient below 1 can be interpreted as being due to partial substitution of the structural sulphate by the arsenate ions and the co-existence of both adsorption mechanisms. However, as the pH increases, structural sulphate may be substituted by OH^–ions and surface complexation with the iron hydroxyl groups will become the main adsorption mechanism. Unfortunately, in the present study sulphate concentration was not measured after arsenate adsorption and therefore the exchange coefficients cannot be calculated.

Figure 4. Adsorption envelopes for arsenate in (a) T-PO and (b) F-OR precipitates obtained at different ionic strengths and with an initial arsenate concentration of 570 μM. Symbols represent the experimental data. Solid, dashed and dotted lines correspond to the simulations of the GTL model at ionic strength 0.01 M, 0.1 M, and 0.5 M, respectively.

For both precipitates, the effect of ionic strength on arsenate adsorption is rather low at pH < 5. A minimal effect of ionic strength at low pH was previously observed for synthetic goethite and ferrihydrite particles (Antelo et al., 2005, 2010). At pH > 5, an increase in ionic strength produces an increase in the adsorption of arsenate on the iron precipitates. Ions that form inner-sphere complexes bind directly to the hydroxyl surface groups via ligand exchange and might not be affected by electrolyte ions or by changes in ionic strength. However, several cases of inner-sphere complexation and increased adsorption with increasing ionic strength have been reported (Rahnemaie et al., 2007; Antelo et al., 2010) and have been attributed to changes in the electrostatic potential at the solid/solution interface. An increase in the ionic strength produces a decrease in the electrostatic repulsion between the charged mineral surface and the arsenate ions, favouring adsorption. The opposite effect may occur at low pH, as an increase in the ionic strength may lower the electrostatic attraction between the positively charged mineral surface and the arsenate ions, minimizing the differences in the adsorption levels at the different ionic strengths.

The adsorption of arsenate on T-PO and F-OR precipitates is compared in Figure 5 for two different arsenate loadings. At the lower pH, adsorption on both precipitates is similar, but at pH above 5 – 6, adsorption on T-PO is higher at both arsenate loadings. The specific surface area of sample F-OR (216 m²/g) is greater than that of sample T-PO (127 m²/g) and therefore the former is expected to be more reactive. Nevertheless, as stated above, the structure of sample T-PO partly resembles that of schwertmannite particles, while sample F-OR can be described as ferrihydrite-like. In addition to the surface complexation of arsenate on the surface hydroxyl groups, which is possibly the only adsorption mechanism in sample F-OR, anion exchange reactions may occur in sample T-PO. Another possible explanation for the observed differences in the reactivity of both samples is the presence of co-precipitated trace metals. The T-PO precipitate contains larger amounts of Cu, Zn and Ni. The presence of trace metals in the crystalline structure may increase the adsorption of arsenate by 20 – 30 %, as already observed for schwertmannite and goethite (Mohapatra et al., 2006; Antelo et al., 2013). The presence of co-precipitated ions and their incorporation in the crystalline structure may lead to changes in the surface properties of the oxides (specific surface area, surface charge and point of zero charge).

Figure 5. Comparison of arsenate adsorption on F-OR (circles) and T-PO (triangles) precipitates as a function of pH at ionic strength 0.1 M. Filled and empty symbols correspond to an initial arsenate concentration of 570 and 285 μM, respectively. Solid and dashed lines represent GTL model simulations for F-OR and T-PO precipitates, respectively.

3.4. Copper removal by AMD precipitates

Copper adsorption on the natural precipitates shows the typical trend observed for metal retention by iron oxides (Jönsson et al., 2006; Ponthieu et al., 2006; Moon and Peacock, 2013) (Figure 6). Thus, the level of adsorption varied from 0 to 100 % within approximately two pH units. Both iron precipitates exhibited very similar behaviour, with the curves for F-OR shifted slightly towards higher pH. A previous study by Swedlund and Webster (2001) showed that copper has a higher affinity for synthetic schwertmannite than for synthetic ferrihydrite. These authors reported that at pH 4, 10 % of the copper was adsorbed on ferrihydrite and 30 % on schwertmannite, and at pH 5 the levels of adsorption were 80 % and 90 %, respectively. In the present study, more copper was adsorbed onto the T-PO precipitate (schwertmannite-like) than onto the F-OR precipitate (ferrihydrite-like) at the same pH. This result is consistent with the previous finding for arsenate, which displays a higher affinity for the surface of the T-PO sample. The difference observed in the case of arsenate was explained by the anion exchange reactions between structural sulphate groups and arsenate ions; however, this adsorption mechanism should not contribute to cation binding. Nevertheless, the presence of sulphate in the crystalline structure, along with other co-precipitated ions (Table 2), may alter the surface properties of these iron oxides. Assuming the same site density for iron hydroxyl groups in both precipitates, the observed differences in copper adsorption may be attributed to differences in the protonation constants or the metal affinity constants.

The percentage of Cu adsorption increased with increasing pH, during which the surface of the precipitates becomes more negatively charged, and with increasing the initial amount of metal ion present. The processes involved in the adsorption of copper by iron oxides have previously been reported (Rodda et al., 1996) and are mainly described as adsorption reactions on the surface - with and without the release of protons and exchange reactions between Cu²⁺ and H⁺ions. The pH dependence is mainly caused by the decrease in competition from protons for the binding sites as the pH increases. Moreover, electrostatic attraction between the metal cation and the iron hydroxyl groups becomes stronger as the pH increases, because the surface of the iron oxide becomes more negatively (or less positively) charged.

Figure 6. Copper adsorption envelopes in (a) T-PO and (b) F-OR precipitates obtained at two different initial concentrations: 100 μM (circles) and 500 μM (diamonds), and ionic strength, 0.1 M. Solid and dashed lines represent GTL model simulations for the copper loading 100 μM and 500 μM, respectively.

3.5. Surface complexation modelling of arsenate and copper immobilization

3.5.1. Arsenate modelling

To describe the experimental results using the GTL model, we assumed that only ligand exchange reactions occurred between the arsenate and the hydroxyl surface groups. In order to minimize the fitting parameters, i.e. parameters that need to be adjusted, anion precipitation and anion exchange reactions were not considered in the modelling calculations. The default values proposed by Dzombak and Morel (1990) for the surface parameters (specific surface area, site density) of hydrous iron oxides were initially considered in the calculations, along with the protonation constants, log K_H1 and log K_H2. Finally, the values for the arsenate surface complexation constants were initially taken from the database available in Visual MINTEQ, and extra fitting, or adjustment, was conducted when necessary. The arsenate surface complexation constants are shown in Table 3, and the corresponding model predictions for adsorption on both iron precipitates are shown in Figures 4 and 5. Use of the default SSA value for hydrous iron oxide (600 m²/g) in the calculations led to overestimation of the adsorption of arsenate on the precipitates. Although the BET method may underestimate the real surface area of amorphous iron oxides due to the aggregation of particles, the experimental values obtained were considered in the modelling calculations.

Table 3. Surface complexes of arsenate considered in the GTL model and the corresponding log K values.

Note. Surface site density and protonation constants were set at the values proposed by Dzombak and Morel (1990). The SSA values used in the modelling calculations were 264 and 216 m²/g for sample T-PO and F-OR, respectively.
^aDefault constants obtained by Dzombak and Morel (1990).
^bFitted constants.

As shown in Figure 4b, arsenate adsorption on sample F-OR was reasonably well simulated using the experimental SSA and the default values for the different surface complexation reactions. At the highest ionic strength, I = 0.5 M, the complexation parameters slightly underestimated adsorption at lower pH. Although extra fitting of the surface complexation constants improved the model estimates at this ionic strength, arsenate adsorption was then overestimated for the other conditions. In the case of sample T-PO, modelling predictions using the experimental SSA (127 m²/g) underestimated the adsorption of arsenate by ~ 50 %. This is consistent with the existence of an additional adsorption mechanism due to the presence of structural sulphate groups, which are not taken into account in these calculations. As explained above, in order to simplify the calculations, anion exchange reactions were not considered in GTL modelling. Therefore, we assumed that the modelling underestimation is due to an incorrect value of SSA (or site density) and that extra fitting was needed. An SSA of 264 m²/g yielded reasonable levels of arsenate adsorption; however, arsenate adsorption was slightly overestimated at pH below 7 and the effect of ionic strength was minimized when the default complexation constants were used. Additional fitting was conducted to improve the simulations, but the model was only adjusted for the complexation constants of the arsenate surface complexes that contributed to the adsorption at acidic pH (≡FeOAsO(OH)₂ and ≡FeOAsO₂OH). The fitted constants (see Table 3) yielded optimal simulation of the arsenate adsorption on the T-PO precipitate (Figure 4a) throughout the whole pH range and adequately described the effect of ionic strength. Overall, the GTL model adequately reproduced the adsorption of arsenate on these natural iron precipitates with a minimum number of fitting parameters. However, anion exchange reactions were not taken into account.

In a more realistic approach, CD model calculations were also conducted by initially assuming that the iron precipitates behave like ferrihydrite particles. Hiemstra and Van Riemsdijk (2009) proposed a ferrihydrite surface model based on goethite, with equal proportions of the crystal faces (110), (001), and (021). Surface site densities of 6 nm^-2 and 1.2 nm^-2 were considered for the singly and triply coordinated groups respectively, while the SSA determined by BET were used in the calculations. The affinity constants for protons and electrolyte ions were taken from Antelo et al. (2010) and are shown in Table 4. Arsenate adsorption was modelled by assuming the presence of protonated and non-protonated bidentate complexes, because the available data on iron oxides indicates both complexes as predominant (Waychunas et al., 1993; Stachowicz et al., 2006); formation of a protonated monodentate complex was also considered. The surface reactions for the three surface complexes can be formulated as follows:

≡FeOH1/2- + 2H+ + AsO43- ≡FeOAsO2OH3/2- + H2O	(1)
≡2FeOH1/2- + 2H+ + AsO43- ≡Fe2O2AsO22- + 2H2O	(2)
≡2FeOH1/2- + 3H+ + AsO43- ≡Fe2O2AsOOH- + 2H2O	(3)

Arsenate complexation constants previously obtained for goethite (Stachowicz et al., 2006) were used as initial estimates. In the case of the T-PO precipitate, it was not possible to reproduce the arsenate adsorption correctly with the structural parameters of ferrihydrite (Antelo et al., 2010). Adsorption was greatly underestimated across the whole pH range, indicating both that a higher surface area or surface site density would be necessary, and also that ligand exchange with the surface hydroxyl groups is not the only mechanism controlling the adsorption of arsenate. As explained above, the T-PO precipitate mainly comprises (~ 80 %) schwertmannite particles, and therefore the immobilization of arsenate may also involve sulphate anion exchange. This additional adsorption mechanism is specific to schwertmannite, as some of the sulphate groups present in the crystalline structure are weakly bound. Exchange coefficients between SO₄ and AsO₄ (R_ex) were derived by Burton et al. (2009) and by Antelo et al. (2012) for synthetic schwertmannite particles. In both cases, the R_ex values were lower than 1 mol_SO4/mol_AsO4, which may indicate the existence of both adsorption mechanisms, and the values were pH-dependent. The differences between the R_ex values for the two synthetic analogues were attributed to differences in the concentrations of outer-sphere sulphate complexes (Antelo et al., 2012).

Table 4. Surface species and CD model parameters for proton and arsenate adsorption to the surface of the iron precipitates, estimated using the Extended Stern layer model and considering C1 = 0.74 F/m² and C₂ = 0.93 F/m². Δz0, Δz1, and Δz₂ represent the change of the charge (or charge distribution) in the 0-, 1-, and 2-planes, respectively.

^a From Antelo et al.(2010).
^b From Stachowicz et al.(2006).
^c From Weng et al. (2008).

Assuming that the natural precipitate behaves similarly to the synthetic analogues and that the R_ex values obtained in both studies are valid, it would be possible to calculate the amount of arsenate exchanged with the sulphate groups in sample T-PO. As R_ex value and pH were correlated [r² values of respectively 0.99 and 0.92 were obtained by Antelo et al. (2012) and Burton et al. (2009)], the R_ex values at the different pH values considered here can be calculated. Taking into account that the concentration of sulphate groups in sample T-PO (0.92 mmol/g) is similar to that of the synthetic analogue obtained by Antelo et al. (2012) (1.02 mmol/g), extrapolation of R_ex at the different pH values was initially conducted with the observed correlation for this synthetic analogue. At I = 0.1 M, the exchange coefficient ranges from 0.29 mmol_SO4/mmol_AsO4 at pH 3.94 to 0.10 mmol_SO4/mmol_AsO4 at pH 8.39. With these R_ex values, and with the concentration of adsorbed arsenate measured at the different pH values, it is possible to calculate the amount of arsenate that was exchanged with the sulphate groups present in the T-PO precipitate (Figure 7). As seen in Figure 7a, the sum of the amount of arsenate adsorbed to the hydroxyl groups (simulated with the CD model) and the amount of arsenate exchanged with the sulphate groups (calculated with these R_ex values) slightly underestimates the adsorption of arsenate. Extrapolation of R_ex at the different pH values by considering the correlation reported by Burton et al. (2009) yielded values ranging from 0.56 to 0.31 mmol_SO4/mmol_AsO4. Using these R_ex values to calculate the exchangeable arsenate yields a higher contribution of the anion exchange mechanism than in the previous case (Figure 7b) (up to 50 % of the total adsorbed arsenate). Overall, the sum of the contributions from surface adsorption and anion exchange provides an adequate prediction of the arsenate adsorption in the T-PO precipitates. The exchange coefficients used here were obtained from two schwertmannite analogues with opposite sulphate content. The schwertmannite prepared by Burton et al. (2009), Fe₈O₈(OH)_4.80(SO₄)_1.60, contained a large amount of outer-sphere complexes that may readily react with arsenate, while the schwertmannite synthesised by Antelo et al. (2012), Fe₈O₈(OH)_5.95(SO₄)_1.02, mainly comprised inner-sphere complexes, and anion exchange is therefore less likely to occur. This modelling strategy was chosen as initial calculations showed that surface complexation modelling alone could not account for the amount of arsenate adsorbed under the experimental conditions used. Future studies should use a thermodynamic approach to account for the anion exchange reactions. This possibility will be best explored when more spectroscopic and molecular data become available.

Arsenate adsorption onto the F-OR precipitate was reasonably well simulated using the CD model (Figure 8), indicating that surface complexation to the iron hydroxyl groups is the main adsorption mechanism and no additional reactions needed to be considered. Modelling simulations were conducted using the SSA obtained by the BET method, the surface site densities proposed for ferrihydrite particles and with the modelling parameters shown in Table 4. Optimization of the affinity constants may yield better prediction of the arsenate adsorption at the lower pH values, although for reasons of simplicity no extra fitting was conducted. Figure 8 also shows the abundance of arsenate surface species as a function of pH according to the CD model predictions. Under these conditions, the dominant surface species are the bidentate complexes, which are protonated at low pH and non-protonated at high pH. These calculations showed that the non-protonated bidentate complex is the major surface species at intermediate to high pH. The protonated monodentate complex, at the lower pH values, contributes to the arsenate adsorption to a lower extent than the protonated bidentate complex, although it makes a higher contribution at relatively high pH.

Figure 7. Arsenate adsorption envelope on T-PO precipitate at ionic strength 0.1 M, an initial arsenate concentration of 570 μM and with R_ex values taken from (a) Antelo et al. (2012) and (b) Burton et al. (2009). Triangles correspond to the experimental data, while solid, dotted and dashed lines represent the total adsorption of arsenate, the amount of arsenate exchanged with the structural sulphate groups, and the amount of arsenate adsorbed to the hydroxyl surface groups calculated with the CD model for ferrihydrite, respectively.

Figure 8. Adsorption envelope for arsenate in F-OR precipitate, at ionic strength 0.1 M and with an initial arsenate concentration of 570 μM. Triangles correspond to the experimental data, solid lines correspond to CD model predictions and dashed, dotted and dot-dashed lines correspond to the arsenate surface species ≡Fe₂O₂AsOOH, ≡Fe₂O₂AsO₂ and ≡FeOAsO₂OH, respectively.

Figure 9. Cu adsorption envelope and surface speciation on T-PO. Symbols represent experimental data at [Cu] = 100 µM, and lines represent the adsorption percentage of the four surface complexes according to the CD model.

3.5.2. Copper modelling

The adsorption was simulated with the GTL model and, as explained for arsenate modelling, we tried to minimize the number of fitting parameters. We chose this approach because, rather than obtaining a set of complexation constants for each natural sample, we aimed to obtain a general set of constants that could be successfully applied to natural iron precipitates in addition to synthetic iron oxides. In the present modelling approach, cation adsorption is assumed to occur at the two types of surface sites available: high affinity or strong sites (≡Fe^sOH) and low affinity or weak sites (≡Fe^wOH). The same surface complex stoichiometry is usually considered for both types of site (≡Fe^sOCu⁺ and ≡Fe^wOCu⁺, respectively). Copper adsorption on the T-PO precipitate was well predicted (Figure 6a, Table 5) using the intrinsic adsorption constants obtained by Dzombak and Morel (1990) for the two surface complexes defined by the GTL model (2.89 and 0.6, respectively). The model-derived SSA obtained in the arsenate modelling (264 m²/g) was used here. Use of the original SSA proposed by Dzombak and Morel (1990) for hydrous iron oxides (600 m²/g) overestimated the copper adsorption on both iron precipitates. For the F-OR precipitate, use of the experimental SSA value (216 m²/g) slightly underestimated the adsorption and additional fitting of the complexation constant was therefore needed. The modelling simulations shown in Figure 6b were obtained following optimization of the first adsorption constant (log K = 3.19), whereas the second constant remained unchanged (Table 5).

Table 5. Surface complexes of Cu considered in the GTL model and the corresponding log K values.

^aDefault constant obtained by Dzombak and Morel (1990).
^b Fitted constant.

The CD model was also used to simulate copper adsorption on T-PO and F-OR precipitates. The intrinsic proton affinities and structural parameters of the precipitates required for CD model calculations were the same as in the arsenate adsorption modelling. One bidentate surface complex, (FeOH)₂CuOH, was initially considered, as proposed by Tiberg et al. (2013), to model copper adsorption on synthetic ferrihydrite, with a charge distribution between the 0-plane and the 1-plane, Δz₀ = 0.5 and Δz₁ = 0.5, and a log K = 0.97. Adsorption of copper on T-PO and F-OR was greatly underestimated by the model. However, further optimization of the surface complex constant was not sufficient to improve the model prediction. This appears reasonable if we consider the difference between the SSA reported by Tiberg et al. (2013) for ferrihydrite (650 m²/g) and the experimental SSA measured for T-PO (127 m²/g) and F-OR (216 m²/g). Only a significant increase in the SSA of the precipitates, far from their BET values, would lead to a better description of the copper adsorption on the natural precipitates.

In the next step, the surface complexes postulated by Weng et al.(2008) for describing Cu adsorption on goethite were used (Figure 9). Four bidentate inner-sphere complexes were considered between copper and the singly coordinated surface sites of the goethite, allowing for hydrolysis and dimer formation in copper surface species. The stoichiometry of the surface species and the charge distribution between the planes that comprise the solid/solution interface are shown in Table 4 and the corresponding surface reactions are:

≡2FeOH1/2- + Cu2+ ≡(FeOH)2Cu+	(4)
≡2FeOH1/2- + Cu2+ + H2O ≡(FeOH)2Cu(OH)0 + H+	(5)
≡2FeOH1/2- + 2Cu2+ + 2H2O ≡(FeOH)2Cu2(OH)2+ + 2H+	(6)
≡2FeOH1/2- + 2Cu2+ + 3H2O ≡(FeOH)2Cu2 (OH)30 + 3H+	(7)

Combining these complexation constants and the specific parameters for the natural iron oxides yielded a good description of Cu adsorption on sample T-PO at pH > 5, whereas the adsorption was overestimated at lower pH. The modelling was finally improved by fitting one of the constants. The decision about which complexation constant should be fitted was based on the distribution of the four surface complexes, which indicated that ≡(FeOH)₂Cu(OH) was the predominant species at the pH range where the model overestimated the copper adsorption (pH < 5). The fitted value of log K for the ≡(FeOH)₂Cu(OH) complex was 2.55 instead of 3.60. Although adsorption on sample F-OR was slightly overestimated throughout the entire pH range, irrespectively of whether the complexation constants were those proposed by Weng et al. (2008) or the fitted constants that described the adsorption on T-PO, no further fitting was done. As stated above, the idea of this modelling exercise was to simulate the adsorption on the iron precipitates using model parameters derived for synthetic analogues. Ideally, no fitting would be necessary.

Analysis of the distribution of the total percentage of adsorption across the different surface complexes shows that ≡(FeOH)₂Cu species dominate at pH < 5.2. From this pH onwards ≡(FeOH)₂Cu(OH) is the dominant species, although the other two hydroxylated forms also become important (Figure 9). This distribution of surface species is in agreement with that found by Weng et al.(2008). Modelling simulations on goethite showed that the monomer bidentate inner-sphere species is important at low pH, whereas the hydrolysed monomer bidentate species dominates at higher pH.

4. Conclusions

The findings of the present study suggest that the natural iron precipitates behave similarly to synthetic analogues. The iron-rich precipitates collected at two sites affected by AMD occurred as mixtures of varying proportions of schwertmannite-, goethite-, and ferrihydrite-like particles. The dominant mineralogy of the precipitates changed in the two sampling sites due to the differences in the water chemistry and the overall impact by AMD. The iron-rich bed sediments collected at the copper mine site (T-PO), which is greatly affected by AMD, were mainly constituted by amorphous schwertmannite (~ 78 %) and goethite-like (~ 22 %) particles. The loose precipitate collected in the sampling site close to the tungsten and tin mine (F-OR) was slightly affected by AMD and the mineralogy was dominated by the presence of ferrihydrite or amorphous iron oxides.

The arsenate and copper adsorption experiments carried out showed that mobility of these two trace elements was mainly governed by the presence of the iron oxides. Adsorption trends for both elements are identical to those found for their synthetic analogues, but the adsorption levels were always greater in the precipitates collected in the sampling site that was more affected by AMD. The main difference between the two iron precipitates is the existence of structural sulphate groups in the sample resembling schwertmannite, for which the arsenate adsorption process is controlled by two mechanisms: surface complexation with the iron hydroxyl groups and anion exchange with the structural sulphate groups present in the mineral particles. For copper, adsorption mechanisms should be the same for both precipitates, and differences can be assigned to the differences in the proton or metal affinity caused by the presence of metal impurities and sulphate ions. These adsorption mechanisms may be confirmed in the future by conducting a detailed surface chemical analysis with spectroscopic techniques.

The experimental results obtained for arsenate and copper were satisfactorily simulated with the GTL and the CD models. Despite the fact that the nature of the iron precipitates has been demonstrated to be different, most of the surface parameters available in the literature for synthetic iron oxides could be used as initial estimates. The good modelling predictions obtained at the different experimental conditions for both arsenate and copper adsorption indicate that using these estimates, obtained either for ferrihydrite or goethite, is a suitable approach. In general, the model simulations could be improved if additional fitting of the SSA or surface complexation constants was conducted. Among the two SCM studied, the CD model represents a more realistic approach, allowing the determination of the arsenate and copper surface species formed. Finally, if the sulphate-arsenate exchange coefficients obtained for synthetic analogues are considered, it is possible to determine the contribution of both anion exchange and surface complexation in the adsorption process of arsenate on the iron precipitates resembling schwertmannite. Although this is a simple approach, and the obtained results are promising, future studies should focus on the formulation of a thermodynamic approach to describe the anion exchange reactions.

Acknowledgements

The present work was financially supported by the Ministerio de Ciencia e Innovación under research project CTM2011-24985 and by the Xunta de Galicia under the research project EM2013/040. The authors thank Pilar Bermejo of the Department of Analytical Chemistry, Nutrition, and Bromatology of the University of Santiago de Compostela for the ICP-OES measurements and Alvaro Gil from the Ceramic Institute of the USC for the BET measurements. We thank Darío de la Iglesia and Carla Otero for their experimental work. We also acknowledge the assistance of Felipe Macías-García, Cristina Pastoriza, and María Santiso during the collection and the characterization of the samples. We thank two anonymous reviewers for their comments and suggestions, and guest editor Mario Villalobos for his time and effort.

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Manuscript received: October 21, 2014
Corrected manuscript received: January 8, 2015
Manuscript accepted: January 16, 2015

Boletín de la Sociedad Geológica Mexicana Volumen 67, núm. 3, 2015, p. 479-491 http://dx.doi.org/10.18268/BSGM2015v67n3a11

Identification of diagenetic calcium arsenates using synchrotron-based micro X-ray diffraction

Francisco Castillo^1,2,3, Miguel Avalos-Borja^4,5, Heather Jamieson⁶, Gerardo Hernández-Bárcenas¹, Nadia Martínez-Villegas^1,*

¹ IPICyT, Instituto Potosino de Investigación Científica y Tecnológica, División de Geociencias Aplicadas, Camino a la Presa San José No. 2055, Col. Lomas 4a Sec. 78216, San Luis Potosí, SLP, México.
² IPICyT, Instituto Potosino de Investigación Científica y Tecnológica, División de Materiales Avanzados, San Luis Potosí, SLP, México.
³ CONACYT Research Fellow, Instituto de Geología, Universidad Autónoma de San Luis Potosí.
⁴ Centro de Nanociencias y Nanotecnología-UNAM, Ensenada, BC, México.
⁵ On leave at IPICyT, Instituto Potosino de Investigación Cientifica y Tecnológica, División de Materiales Avanzados, San Luis Potosí, SLP, México.
⁶ Department of Geological Engineering, Queen's University, Kingston, ON, Canada.

^* This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract

In this work, we identify the type of calcium arsenates found in sediment samples from an aquifer located in Matehuala, San Luis Potosí, México. Sediments in contact with levels up to 158 mg/L of arsenic in neutral pH water were studied by X-ray diffraction, scanning electron microscopy coupled to energy dispersive X-ray analyses (SEM-EDS), and synchrotron based X-ray diffraction. Identification of these calcium arsenates by X-ray analysis has proved to be very difficult to achieve because the precipitates of interest are on the microscale and immerse in a matrix of calcite, gypsum, and quartz comprising nearly 100 % of the samples. Needle-like specimens composed of calcium, arsenic, and oxygen were, however, commonly observed in sediment samples during SEM-EDS analyses in backscattered mode. Synchrotron based X-ray analyses revealed some peaks that were compared with published data for guerinite, haindingerite, and pharmacolite suggesting that these were the calcium arsenates present in sediments, the calcium arsenates that control the solubility of arsenic in the contaminated aquifer in Matehuala, and the calcium arsenates that prevail in the long-term in the environment after cycles of dissolution and precipitation. The identification of these calcium arsenates is consistent with the environmental conditions prevailing at the study area and the SEM-EDS observations. However, its identification is not unequivocal as the comparison of experimental data collected in single crystal specimens against X-ray diffraction references collected in powders prevents a strictly proper identification of the specimens analyzed. In this way, scorodite was also identified by synchrotron based X-ray analyses however its presence is inconsistent with the environmental conditions and the calcium arsenate associations found in this study. Scorodite identification was therefore considered tentative. A thorough examination, with additional and/or improved analytical techniques, should be undertaken to find an environmentally sound explanation for the diffraction peaks assigned to scorodite, which might be from a clay a mineral, probably with no arsenic.

Keywords: calcium arsenates, arsenic contamination, guerinite, haindingerite, pharmacolite, diagenetic calcium arsenates.

Resumen

En este trabajo identificamos el tipo de arseniatos de calcio que se encuentran en muestras de sedimento de un acuífero altamente contaminado con arsénico ubicado en Matehuala, San Luis Potosí, México. Los sedimentos en contacto con hasta 158 mg/L de arsénico en agua a pH neutro se estudiaron por difracción convencional de rayos X, microscopía electrónica de barrido acoplado a análisis de dispersión de energía de rayos X (SEM- EDS) y micro difracción de rayos X en sincrotrón. La identificación de arseniatos de calcio por análisis convencionales de difracción de rayos X no fue posible debido a que los especímenes de interés son de tamaño microscópico y se encuentran en una matriz de calcita, yeso y cuarzo que comprende casi el 100 % de las muestras, lo que imposibilita separar la señal de los arseniatos de la señal de la matriz y/o el ruido. No obstante, especímenes aciculares compuestos de calcio, arsénico y oxígeno se observaron comúnmente en las muestras de sedimento durante los analices SEM-EDS utilizando un detector de electrones retrodispersados. En contraste, los análisis de rayos X en sincrotrón permitieron revelar algunos picos característicos de guerinita, haidingerita y farmacolita, lo que sugiere que estos son los arseniatos de calcio presentes en los sedimentos, los arseniatos de calcio que controlan la solubilidad del arsénico en el acuífero contaminado en Matehuala y los arseniatos de calcio que prevalecen a largo plazo en el ambiente después de ciclos de disolución y precipitación. La identificación de estos arseniatos es consistente con las condiciones ambientales del sitio de estudio y las observaciones SEM-EDS, sin embargo, dicha identificación no es inequívoca debido a la comparación de patrones experimentales de difracción de rayos X tomados en monocristales contra tarjetas de difracción de polvos, lo que previene la identificación estrictamente apropiada de los especímenes analizados. En este sentido, también se identificó escorodita pero su presencia es cuestionable a pH 7 y en presencia de guerinita, haidingerita y farmacolita por lo que este último resultado debe tomarse con reserva y un estudio más profundo, con técnicas analíticas adicionales y/o mejoradas, debe llevarse a cabo para encontrarle una explicación ambientalmente consistente a los picos de difracción de rayos X asignados a la escorodita, mismos que podrían corresponder a algún mineral arcilloso que podría no contener arsénico.

Palabras clave: arseniatos de calcio, contaminación con arsénico, guerinita, haidingerita, arseniatos de calcio diagénicos.

1. Introduction

In the past, lime neutralization has been used to precipitate arsenic from process solutions as calcium arsenates (Bothe and Brown, 1999a; Robins, 1981; Swash and Monhemius, 1995). Typical precipitates derived from this stabilization technology comprise a range of compounds with variously described stoichiometries, degrees of hydration and solubilities (Bothe and Brown, 1999a, 1999b; Nishimura and Robins, 1998; Zhu et al., 2006) that are further disposed of in soils (Robins, 1981).

An examination of the information available in the literature resulted in 22 calcium arsenates, including several dimorphs and hydrates (Table 1). Although it is not clear whether all arsenates with such stoichiometry indeed do exist (Nordstrom et al., 2014), no calcium arsenate will be suitable for arsenic immobilization unless the pH remains high in soils and large amounts of calcium are present (Magalhaes and Williams, 2007; Swash and Monhemius, 1995).

In the presence of excess lime, calcium arsenates appear to have low solubility (Table 1) (Bothe and Brown, 1999b; Nordstrom et al., 2014; Swash and Monhemius, 1995; Zhu et al., 2006) but these are expected to dissolve after the pH buffering effect of the excess lime is reduced through lime solubility and carbonation (Swash and Monhemius, 1995). Arsenic mobilization from calcium arsenates has proved to lead to ultrahigh concentrations of arsenic in surface and groundwater (Martínez-Villegas et al., 2013). Literature indicates, however, a lack of knowledge as to the calcium arsenates that are actually present in the environment controlling arsenic mobilization after long-term disposal.

Calcium hydroxide arsenate hydrates, johnbaumite, and calcium arsenate hydrates (Table 1) are the major phases reported to precipitate during arsenic stabilization using lime followed by guerinite, ferrarisite, pharmacolite, and haindengerite as the calcium/arsenic ratio and pH decreased (Table 1) (Bothe and Brown, 1999a, 1999b; Nishimura and Robins, 1998; Zhu et al., 2006). Guerinite, ferrarisite, pharmacolite, and haindengerite are therefore the calcium arsenates more likely to prevail in the environment, where soil pH and aqueous calcium concentrations are usually controlled by equilibrium with less soluble calcium compounds (Magalhaes, 2002). To the best of our knowledge, no study has specifically identified calcium arsenates precipitates after their disposal in soils. Nevertheless, sainfeldite, guerinite, pharmacolite, haindingerite, and weillite have been reported to occur on primary ores containing arsenic or native arsenic in carbonate gangue (Ondrus et al., 1997), mines (Bowell and Parshley, 2005; Pierrot, 1964), industrial sites (Julliot et al., 1999), and laboratory experiments at circumneutral pHs and low calcium/arsenic ratios (Bothe and Brown, 2002, 1999b; Nishimura and Robins, 1998; Pierrot, 1964; Swash and Monhemius, 1995). Unequivocal calcium arsenate identification is challenging in natural (Onac et al., 2007; Ondrus et al., 1997) or impacted environments (Donahue and Hendry, 2003; Pantuzzo and Ciminelli, 2010) due to the presence of (many different) calcium arsenates in samples largely dominated by other major minerals and/or because the X-ray patterns do not compare closely to published data and, in laboratory experiments, due to lack of reproducible and ambiguous X-ray patterns that do not match any known phases (Bothe and Brown, 1999a, 1999b; Myneni et al., 1997).

The present investigation pertains to an environment contaminated with calcium arsenates collected in a demolished smelter located in Matehuala, San Luis Potosi, Mexico (Figure 1), which originated from the stabilization of arsenic in metallurgical effluents with lime. In this study, we determine the identity of diagenetic calcium arsenates collected in sediments of the contaminated aquifer. Given the difficulties encountered in the identification of these calcium arsenates immersed in a matrix largely comprised of other calcium rich phases, such as calcite and gypsum, we describe in detailed the different approaches used in this study.

Table 1. X-ray diffraction “cards” and solubility products available in the literature for calcium arsenates showing lower solubility products for the more alkaline calcium arsenates.

^*Natural calcium arsenates. (1) Ondrus et al. (1997), (2) Worzala (1993), (3) Chiari and Ferraris (1971), (4) Ferraris and Jones (1972), (5) Herpin (1963), (6) Ferraris and Chiari (1970), (7) Ferraris et al. (1972a), (8) Binas (1966), (9) Cassien and Herpin (1966), (10) Calleri and Ferraris (1967), (11) Pierrot (1964), (12) Ferraris (1969), (13) Ferraris et al. (1971), (14) Brasse (1970), (15) Catti and Ferraris (1973), (16) Ferraris et al. (1972b), (17) Ferraris and Abbona (1972), (18) Catti and Ivaldi (1981), (19) Bari (1980), (20) Catti and Ferraris (1974), (21) Bari (1982), (22) Catti and Ivaldi (1983), (23) Dunn et al. (1980), (24) Bothe and Brown (1999), (25) Zhu et al. (2006), (26) Rodríguez-Blanco et al. (2007), (27) Nishimura and Robins (1998), (28) Mahapatra et al. (1986).

Figure 1. Location and pictures of the demolished smelter (332383"W, 2618114"N) and the arsenic contaminated spring (332802"W, 2617518"N) located in Matehuala, San Luis Potosi, Mexico.

2. Materials and methods

2.1. Mineralogy and total arsenic, calcium and iron analyses in sediment samples

Sediment samples contaminated with calcium arsenates were collected in a spring grossly polluted with arsenic. The spring is located in the vicinity of an abandoned smelter where residues of calcium arsenates from a former process of arsenic stabilization using lime took place six decades ago (Martínez-Villegas et al., 2013). The abandoned smelter and the spring are located in Matehuala, an urban center in San Luis Potosi, Mexico (Figure 1) where the long-term disposal of calcium arsenates has led to cycles of dissolution and precipitation of soluble calcium arsenates that cause ultrahigh concentrations of arsenic in surface and groundwater (Martínez-Villegas et al., 2013). Ultrahigh concentrations of arsenic in the spring vary from 36 to 158 mg/L in the water overlying the sediments (Martínez-Villegas et al., 2013). The spring is found within a perched aquifer that runs in a W to E direction and is believed not to mix with a low-As shallow aquifer (< 21 µgAs/L) that runs NW to SE between 15 and 50 m in depth (Martínez-Villegas et al., 2013). Procedures used in the sampling and determination of arsenic in the overlying water are described in detail in Martínez-Villegas et al. (2013). Briefly, water samples were collected over a year on a monthly basis at the spring in 120 mL polypropylene bottles previously washed with 10 % HNO₃and rinsed with deionized water. Water samples were filtered through a 0.45 µm-pore membrane, acidified to pH < 2, and stored at 4 ºC until analysis. Total dissolved arsenic was determined by inductively coupled plasma mass spectroscopy (ICP-MS).

Sediment samples were collected using a shovel within the first 0 – 5 cm of depth. Sediments were stored in polyethylene bags and maintained at 4 ºC until air-dried, ground and homogenized. Bulk mineralogy was determined by X-ray diffraction (XRD) in sediment samples using a Bruker D8 ADVANCE X-ray diffractometer fitted with a Cu Kα source. Sediment samples for X-ray powder diffraction were compacted into a glass holder covering an area of 1.5 cm² and analyzed from 5º to 90º 2Ɵ with a step interval of 0.01 2Ɵ and a counting time of 4s per step. Phase identification was made by matching the experimental diffractogram with data from PDF4 of the ICDD (International Center of Diffraction Data). Total arsenic, calcium, and iron were determined by inductively coupled plasma optical emission spectroscopy (ICP-EOS) in digests of sediment samples. For the digestion of samples, a representative 0.1 g sample was digested with 10 mL of aqua regia (HNO₃/HCl 3:2 V/V) in an Ethos 1 advanced microwave digestion system for 10 min at 150 ºC using a 750 W lamp with a ramp heating of 10 min and a ramp cooling of 30 min. For ICP analyses, the resultant digests were filtered through a 0.45 µm membrane, and then diluted to a final volume of 25 mL.

2.2. Methods initially used to identify calcium arsenates

As mentioned previously, calcium arsenate identification is challenging. Attempts include conventional X-ray analyses, imaging and elemental analyses by SEM-EDS, and sample preparation in a Helios NanoLab for electron diffraction analyses in transmission electron microscopy (TEM). Small amounts of sediment samples were directly mounted on a carbon tape. Each carbon tape was fixed on an aluminum holder. Scanning electron microscope (SEM) analyses in sediment samples were done in a FEI Quanta 200 SEM coupled to an EDAX energy dispersive system. SEM analyses were performed using either a large field or a backscattered electron detector at low vacuum (10 – 130 kPa). Additionally, sample manipulations were performed in a Helios NanoLab Dual Beam 600 to try to extract calcium arsenates specimens from sediment samples for milling until producing suitable quality samples for TEM imaging and diffraction analyses.

2.3. Micro X-ray diffraction analyses

Liftable thin sections of calcium arsenate contaminated sediment samples were prepared to identify selected targets of calcium arsenates by synchrotron microanalysis using petrographic techniques (Walker et al., 2009). Sections were first prepared on pure silica glass slides and then explored by SEM-EDS to identify those regions with specimens of interest. Sections where calcium arsenates were found were removed from the glass slide by soaking the slide in acetone and lifting it on kapton tape to be then analyzed at Beamline X26A at the National Synchrotron Light Source at Brookhaven National Laboratory, New York. Beamline X26A has proved to be suitable for obtaining high-resolution microdiffraction data on very small (5 µm) crystals (Jamieson et al., 2011; Walker et al., 2009). Once mounted on the X26-A beamline, liftable thin sections were explored by optical microscopy to identify those regions of interest. A detailed elemental map was obtained to identify spots with high levels of arsenic, calcium, and iron. Micro X-ray diffraction was completed in transmission mode using a Rayonix SX-165 CCD Image Plate area detector. The incident X-ray beam was tuned to a wavelength of 0.7093 Å, and the distance from the sample detector was 247 mm. Calibration of the detector was done using the SRM674a diffraction standard α-Al₂O₃ and Ag-Behenate (AgC₂₂H₄₃O₂). 2-D X-ray patterns were recorded on selected spots. Calibrations and corrections for detector distortions (camera sample distance, the camera tilt and rotation, and the beam center on the camera plane) were done using Fit2D^TMsoftware (Hammersley, 1998). One dimensional X-ray patterns were obtained and matched with those compiled in the PDF4 database of the ICDD. Calcium arsenates in the database are shown in Table 1. A total of 15 target spots were analyzed within three different liftable thin sections (Table 2).

Table 2. Arsenic, calcium, and iron counts from X-ray fluorescence analyses at each target spot selected for X-ray diffraction analyses.

3. Results

3.1. Mineralogy and total arsenic, calcium, and iron concentrations in sediment samples

According to peak matching with simulated data from the PDF4 of the ICDD, conventional X-ray diffraction analyses consistently show sediments comprise gypsum, calcite, and quartz (Figure 2). Total arsenic concentrations in sediment samples varied from 261 mg/kg to 1753 mg/kg without a clear trend with the concentration of arsenic in the overlying water (Figure 3). Total arsenic concentrations in sediment samples are due to a process of diagenetic precipitation of calcium arsenates firstly dissolved upstream in the terrains of a currently demolished smelter (Martínez-Villegas et al., 2013). In the case of calcium, total calcium concentrations vary from 8.7 % to 10.2 % and might rather be controlled by calcite and gypsum. Due to the commanding role of iron in the regulation of arsenic mobility in the environment, we also measured total iron concentrations in sediment samples. Total iron concentrations vary from 1.1 % to 1.3 %, however no correlation has been observed between arsenic and iron in this study area (Martínez-Villegas et al., 2013).

Figure 2. X-ray diffractograms representative of sediments in the study area showing how experimental peaks match with simulated gypsum, calcite, and quartz; which is not the case for guerinite, haidinguerite, pharmacolite, and scorodite. According to PDF4 of the ICDD database.

Figure 3. Arsenic concentration in sediments and the overlying water. Arsenic data in the overlying water was taken from Martínez-Villegas, et al. (2013).

3.2. Failed methods used to attempt to identify calcium arsenates

Factors complicating calcium arsenate identification in calcareous sediments include the relatively low concentration of the minerals of interest as compared with bulk sample, sample heterogeneity, sample composition, and sample properties.

The relatively low concentration of calcium arsenates in bulk samples hinders calcium arsenate data in X-ray diffraction analyses and makes impossible its identification. In this study, no calcium arsenates were possible to identify by conventional X-ray analysis in sediment samples (Figure 2). These results were consistent with previous studies that had failed to identify calcium arsenates using conventional X-ray diffraction analysis even in highly contaminated soils containing up to 5 % of arsenic on a mass basis (Martínez-Villegas et al., 2013).

On the other hand, the heterogeneous nature of sediment samples greatly complicates their analyses by SEM-EDS. Despite clear evidences of the presence of calcium arsenates in contaminated sediment samples (Figures 4 and 5), we were unable to confirm their presence using chemical spot analyses. This could be due to the small particle size of the arsenates and the “pear” effect of the analytical technique, where both the particle and the matrix are sampled simultaneously. Composition analyses were besides highly deterred by the nonconducting nature of the samples. Image distortions or severe cases of charging during secondary electron SEM analyses, observed as bright regions surrounded by dark haloes (Figure 4a), made difficult to acquire good quality images and therefore good quality chemical information results. Calcium arsenates in Figure 4b were obtained using a backscattered electron detector, which is less affected by electric charge but with less image resolution, making significantly more difficult to analyze smaller specimens like the diagenetic calcium arsenates present in sediment samples (Figure 5). The disadvantages of sample heterogeneity could have been overcome, in part, and in theory, by preparing ultrathin samples for electron diffraction analyses after TEM, however calcium arsenate specimens were unstable under the Helios NanoLab and no specimens could have ever been extracted for milling and TEM analyses (Figure 4c and d).

Figure 4. Image distortion, specimen charging, and sample instability problems during SEM observations. (a) Image distortion and calcium arsenate charging occurring during SEM analyses using a large field detector (LFD) of secondary electrons in low vacuum (10 – 130 kPa) in a FEI Quanta 200 SEM. (b) Image distortion and charging were usually overcome using a backscattered electron detector (BSD) at expenses of resolution but producing atomic number contrast. The use of a BSD was key to help localize calcium arsenate specimens by contrast in gypsum rich samples. (c) Calcium arsenate specimen found in sediment samples using a Helios NanoLab. (d) Track of the calcium arsenate shown in (c) after sublimation during Helios NanoLab manipulations.

Figure 5. Backscattered SEM images of samples A (a and b) , B (c and d) and D (e and f) showing diagenetic needle-like minerals commonly found in sediments of the contaminated spring (brighter areas indicate zones of higher atomic number).

3.3. Micro X-ray diffraction results

Figure 5 shows SEM images of specimens of calcium arsenates found on silica glass slides and their corresponding EDS analyses. As can be observed, all specimens show a needle-like morphology where EDS analyses revealed the presence of arsenic, calcium, oxygen, carbon, aluminum, silica, sulfur, potassium and iron (Figures 5 a to f) likely due to the presence of calcium arsenates, calcite, gypsum, and quartz. Aluminum and potassium might derive from phyllosilicate clays. Element counts detected by X-ray fluorescence collected in areas where calcium arsenates were observed are shown in Table 2. 2D diffraction patterns collected at each specific target spot were transformed to 1D.

Figure 6 shows the micro-X-ray diffractogram for sample A as compared with data from the PDF4 of the ICDD for gypsum, calcite, quartz, guerinite, haindingerite, pharmacolite, and scorodite. As it can be observed, a large set of peaks showed at positions 2.9, 9.1, 10.6, 12.2, 12.7, 13.4, 14.4, 15.8, 16.3, 17.8, 19.5, 21.4, 21.8, 22.5, 25.5 and 27.2. Because of the acquisition of data at a micron scale of very specific specimens (Figure 5), it was completely unexpected to observe that calcite, gypsum, and quartz from the sediment matrix were still dominant in the diffraction patterns (Figures 6). Peak positions accounting for calcite, gypsum, and quartz were found at 12.2, 12.7, 13.4, 14.4, 15.8, 17.8, 19.5, 21.4, 21.8, 22.5, 25.5 and 27.2. Remaining peaks (at positions 2.9, 9.1, 10.6 and 16.3) were explained by the presence of guerinite, haindingerite, pharmacolite, and scorodite (Figure 6) that show peaks at these specific positions as well as some other peaks that overlap with the matrix and other calcium arsenates (Figure 6). For example, the peak found at position 2.9, was explained by guerinite, whose reference data show another peak at 13.4 that overlaps with calcite, gypsum, and pharmacolite (Figure 6). Peak overlap was a major limiting factor on the identification of calcium arsenates in this study. Another factor that greatly deterred the identification of calcium arsenates was the collection of single crystal diffraction data as determined by micro-X ray results. Different to X-ray powder measurements, where the random orientation of crystals allows for peak acquisition at every characteristic position with proportional intensities, in single crystal measurements peak acquisition and their relative intensities depend on the orientation of the crystal analyzed. That is, in a single crystal diffractogram, not all the characteristic peaks of the mineral may show up and the intensities might not correspond to those of powder references. In this study, only a few crystal orientations might have diffracted, obtaining therefore incomplete sets of peaks with non-proportional intensities. These complications were observed even for dominant matrix minerals such as gypsum, for which not a whole set of peaks of proportional intensities was obtained (Figure 6). Guerinite, haindingerite, pharmacolite, and scorodite were consistently identified in the rest of the targets analyzed using synchrotron based X ray analyses (Figures 7 and 8). The presence of guerinite, haindingerite, and pharmacolite as secondary calcium arsenates has been reported to occur at circumneutral, calcium rich environments (Julliot et al., 1999) and in near neutral pH laboratory experiments in the presence of calcium (Bothe and Brown, 1999a, 1999b). In this study, the identification of guerinite and pharmacolite is thermodynamically consistent with data from the water overlying the sediments (Figure 9). While this data does not overlap with the equilibrium of haindingerite, the presence of this phase can be explained by the close association of this mineral with the precipitation of guerinite (Bothe and Brown, 1999a, 1999b; Julliot et al., 1999). On the other hand, the identification of scorodite is inconsistent with the environmental conditions referred in this paper (circumneutral, calcium rich environments) and very unlikely to occur in association with guerinite, haindingerite, and pharmacolite (Figure 9). Furthermore, no additional microscopic, spectroscopy, and/or hydrogeochemical evidences have been observed for the presence of scorodite in the study area therefore a thorough examination, with additional and/or improved analytical techniques, should be undertaken to find an environmentally sound explanation to the diffraction peaks assigned to scorodite, which might be from a clay mineral, probably with no arsenic.

Figure 6. X-ray diffractograms of sample A revealing experimental peaks that match with simulated guerinite, haindingerite, pharmacolite, scorodite, gypsum, calcite, and quartz according to PDF4 of the ICDD database.





Figure 7. X-ray diffractograms of sample B revealing experimental peaks that match with simulated guerinite, haindingerite, pharmacolite, scorodite, gypsum, calcite, and quartz according to PDF4 of the ICDD database.



Figure 8. X-ray diffractograms of sample D revealing experimental peaks that match with simulated guerinite, haindingerite, pharmacolite, scorodite, gypsum, calcite, and quartz according to PDF4 of the ICDD database.

Figure 9. Activity ratio diagram illustrating the data of the water overlying the studied sediments (black dots) is reasonably consistent with the equilibriums of guerinite and pharmacolite but inconsistent with formation of scorodite. The range denoted by the hatched region is where arsenic would be controlled by scorodite dissolution at the spring conditions. Data for this figure was taken from Martínez-Villegas et al. (2013). Guerinite, pharmacolite, and haindingerite equilibriums correspond to the solubility products shown in Table 1.

4. Conclusions

In this study, guerinite, haindingerite, and pharmacolite were identified in contaminated sediment samples as determined by X-ray synchrotron diffraction that revealed some peak positions that compared with these minerals. Guerinite, haindingerite, and pharmacolite are diagenetic calcium arsenates present in the aquifer after long-term disposal on soils of (other) original calcium arsenates upstream. Guerinite, haindingerite, pharmacolite are calcium arsenates highly soluble (Table 1). Results from this paper are in agreement with those of our previous paper (Martínez-Villegas et al., 2013) in that calcium arsenates would explain the ultrahigh concentrations of arsenic found in the aquifer. Our current results, however, differ from our previous paper in that we first observed that none of these minerals explained arsenic contamination according to geochemical calculations using PHREEQC (Martínez-Villegas et al., 2013). In that case, arsenic contamination was explained by calcium arsenate that showed the same stoichiometry than guerinite but a different solubility product. The challenge today is to match solubility data in the aquifer with their corresponding precipitating phases. In order to do so, an evaluation of the internal consistency of thermodynamic data on calcium arsenates and improved approaches for calcium arsenate identification are needed.

Acknowledgements

This study was supported by grants CB-2012-183025 and IPICYT S-2694 funded by CONACyT and Curso-Taller de Calidad del Agua y Modelación Hidrogeoquímica, respectively. Synchrotron-based X-ray diffractions were collected at beamline X-26A, National Synchrotron Light Source (NSLS), Brookhaven National Laboratory. X26A is supported by the Department of Energy (DOE) - Geosciences (DE-FG02-92ER14244 to The University of Chicago - CARS). Use of the NSLS was supported by DOE under Contract No. DE-AC02-98CH10886. F. Castillo and G. Hernández-Barcenas thank CONACyT for postdoctoral and undergrad fellowships, respectively. Special thanks are due to Gladis Labrada, Beatriz Adriana Rivera Escoto and Ana Iris Peña Maldonado from LINAN-IPICyT, Tyler Nash from Queen´s University, and Sue Wirick from University of Chicago.

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Manuscript received: November 28, 2014
Corrected manuscript received: April 21, 2015
Manuscript accepted: May 5, 2015

Boletín de la Sociedad Geológica Mexicana Volumen 67, núm. 3, 2015, p. 467-478 http://dx.doi.org/10.18268/BSGM2015v67n3a10

A concise synchrotron X-ray microdiffraction field guide for the Earth scientists

Nobumichi Tamura^1,*, Martin Kunz¹

¹ Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley CA 94720, USA.

^* This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract

Most geological samples are intrinsically heterogeneous at the micron scale making their quantitative study with conventional laboratory techniques challenging. The use of synchrotron radiation, which provides high quality data with unprecedented spatial and angular resolution, has become quite ubiquitous in many branches of experimental sciences, and geology, geochemistry, Earth and environmental sciences are no exception. The present chapter offers an overview of what can be measured using synchrotron X-ray microdiffraction using an X-ray beam size in the range between 100 nm to a few microns. Experiments using geological samples are described. Two techniques, their strengths and limitations, are emphasized: powder microdiffraction and Laue microdiffraction.

Keywords: X-ray microdiffraction, synchrotron, Laue diffraction, powder diffraction, stress, microstructure.

Resumen

La mayoría de las muestras geológicas son intrínsecamente heterogéneas en la escala del micrón, lo que convierte a su estudio cuantitativo realizado con técnicas de laboratorio convencionales en algo desafiante. El uso de radiación sincrotrón, que proporciona datos de calidad con una resolución espacial y angular sin precedentes, se ha convertido en ubicua en varias de las ramas de las ciencias experimentales, y la geología, la geoquímica, las ciencias de la Tierra y las ciencias del medio ambiente no son una excepción. El presente capítulo ofrece una visión general de lo que puede ser medido utilizando microdifracción de rayos X en sincrotrón, con el tamaño de haz de rayos X en el intervalo entre 100 nm y unas pocas micras. En el presente trabajo se describen los experimentos utilizando muestras geológicas. Se enfatizan dos técnicas, sus fortalezas y limitaciones: microdifracción de polvo y microdifracción Laue.

Palabras clave: microdifracción de rayos X, sincrotrón, difracción Laue, difracción de polvo, estrés, microestructura.

1. Introduction

Natural samples often exhibit higher levels of heterogeneity than manufactured materials and therefore their microstructure, chemical and crystalline phase distribution and level of deformation are often more challenging to characterize in a quantitative way. A piece of rock, a piece of meteorite, a sample of soil, when looked under a microscope generally appear as agglomerates of multiple crystalline and non-crystalline phases with varying compositions, impurities and defect contents, structures and different grain sizes. Deciphering the particular history of a sample, such as how a particular meteorite has formed or how much stress a particular piece of rock near an earthquake fault has experienced over time, requires a thorough understanding of the microstructure. A probe is needed, capable of providing as much information as possible at the relevant length scale (typically from a few microns down to a few nanometers). Moreover, the interpretation of some measurements, such as the crystalline phase distribution resulting from a transition between two states, requires that the probe perform the measurement without destroying the sample.

Among the arsenal of characterization tools available today at synchrotron facilities, techniques such as absorption spectroscopy, including XANES (X-ray Absorption Near Edge Structure), EXAFS (Extended X-ray absorption fine structure), X-ray fluorescence, high resolution powder diffraction, SAXS (Small Angle X-ray scattering), X-ray imaging such as STXM (Scanning Transmission X-ray Microscopy) and X-ray Tomography, are increasingly used by the Earth Science community. In particular, synchrotron microfocus techniques such as X-ray microdiffraction, μSAXS, X-ray microfluorescence (μXRF), μXANES and μEXAFS, which add high spatial resolution, have become increasingly attractive as effective in situcharacterization tools. The intrinsic high brightness and collimation of X-ray beams produced at synchrotron facilities around the world make possible the routine generation of very small but intense micron to submicron size X-ray beams ideally suited to probe sample heterogeneity at this length scale. Synchrotron facilities such as the Advanced Light Source (ALS) in Berkeley, CA, the Advanced Photon Source (APS) at Argonne, IL, the European Synchrotron Research Facility (ESRF) in Grenoble, France or the 8 GeV Super Photon Ring (Spring-8) in Hyogo, Japan are very large machines financed, built and maintained to the greater part by government agencies for the benefit of academics and industries to perform experiments that generally cannot be conducted anywhere else. The electron storage rings at the core of synchrotron facilities deliver X-rays to some 20 to 40 “beamlines”, each specialized in a few specific techniques. Experiment time, also known as “beamtime”, is allocated to users based on scientific merit through a peer review system. Access to most synchrotron facilities is free and the cost of using such facilities generally amount only to travel cost. As demand is generally high and therefore the amount of allocated beamtime scarce, for maximum efficiency of beamtime it is imperative that each experiment be planned carefully in collaboration with the beamline personnel. Multiple techniques over several beamlines, sometimes across a few facilities, are generally applied in succession to answer a particular question about a sample. For instance, elemental distribution can be obtained by scanning X-ray microfluorescence, while X-ray microdiffraction would be used to identify the structure or determine the crystallinity of particular phases. μXANES is typically used for finding the degree of oxidation of particular elements while μEXAFS can help identify semi-amorphous materials. X-ray microtomography would be used as a 3D imaging tool based on absorption contrast. The present review will focus on synchrotron X-ray microdiffraction (also called micro X-ray diffraction or μXRD). Following a brief description of the instrumentation, the review will show how such a beamline can be used effectively to solve many problems that are relevant to geochemists, earth scientists and geologists.

2. The X-ray microdiffraction toolkit

X-ray microdiffraction is in essence the century old X-ray diffraction technique optimized to the best of today’s technology in terms of X-ray focus, with, however, a few caveats. Producing a very small X-ray beam comes at a cost, but starting with high photon counts and very small beam divergence is certainly helpful in achieving this goal. This is why X-ray microdiffraction with a beam size in the order of a micron or below only appeared feasible at 3^rd generation synchrotron sources. Progress in X-ray focusing technologies combined with efficient vibration damping systems allow today for an X-ray beam in the order of a few tens of nanometers in size, but more routinely in a micron size range. All X-ray focusing optics are based on one, sometimes two, of the three following physical phenomena arising when a wave of X-rays encounter solid material: diffraction, total external reflection and refraction. They are therefore often classified into diffractive, reflective and refractive optics. Fresnel zone plates (or simply zone plates, ZPs) are examples of diffractive optics, consisting of concentric rings of alternating X-ray transparent and opaque material with widths inversely proportional to the radius of the ring. Their intrinsic chromaticity (focal length depends on X-ray wavelength) restrict their use to monochromatic applications. A focus size in the range of 10 nm has been achieved (Chao et al., 2005) and zone plates are therefore highly popular with “soft” and “tender” (energy below 10 keV) X-ray microscopy (Kirz et al., 1995; Larabell and Le Gros, 2004). For hard X-rays, zone plates need to be thick enough for absorption in the opaque regions to be effective, but high aspect ratio rings are quite challenging to manufacture (Feng et al., 2007a; Chu et al., 2008) and therefore zone plates are often replaced by other optics for X-ray above 10 keV. X-ray mirrors, consisting of a metal coating on top of a rigid substrate, use total external reflection to deflect the X-ray beam path. Bent to an elliptical profile, an X-ray mirror can be used to focus the beam in one direction. Kirkpatrick-Baez (KB) mirrors consist of an orthogonal pair of elliptically shaped mirrors to focus a beam in two directions (Kirkpatrick and Baez, 1948). Spot sizes of a few tens of nanometers have been achieved in the last decade with ultrasmooth KB mirrors (Mimura et al., 2005). KB mirrors offer the advantages of high efficiency and relatively high acceptance, making them ideal for “hard” X-ray (energy above 10 keV) applications. Since they are achromatic, they are the tool of choice for polychromatic and spectroscopic applications. Compound refractive lenses (CRLs) consist of a series of concave lenses carved out of light elements that are an alternate low-cost hard X-ray focusing optics (Snigirev et al., 1998; Schroer et al., 2003). CRLs are, however, highly achromatic and work for monochromatic beams only. Currently, ZPs, KBs and CRLs are the three most widely used X-ray focusing optics at synchrotrons. However, there are many other concepts that have been developed such as X-ray waveguides (Jark et al., 2001), Bragg-Fresnel lenses (Aristov et al., 1989), kinoform lenses (Evans-Lutterodt et al., 2007), X-ray capillaries (Bilderback, 2003) and prism array lenses (Jark et al., 2004).

For medium angular resolution measurements, the X-ray diffraction detectors of choice today are two dimensional area detectors that output diffraction patterns in easy-to-handle digital format. Examples of 2D detectors include X-ray charge coupled devices (CCDs), pixel array detectors and image plates. They come in increasingly larger sizes, number of pixels and speed and can capture in a single shot a large angular portion of the reciprocal space, making experiments much faster as the detector remains stationary throughout the duration of the measurement (Tate et al., 1995; Broennimann et al., 2006).

Many beamlines around the world offer microdiffraction capabilities, but only a few are fully dedicated stations. One such example is given by BL12.3.2 at the Advanced Light Source (Kunz et al., 2009b; Tamura et al., 2009). The outline of this beamline is shown in Figure 1. The source is a superconducting bending magnet that provides X-rays with a critical energy around 12 keV, i.e., well into the hard X-ray regime. A toroidal mirror refocuses the beam onto the entrance of the experimental hutch where a pair of slits are used as a virtual secondary source that is size adjustable. Final focusing is provided by a pair of elliptically bent KB mirrors with tungsten coating working at a nominal incidence angle of 3.5 mrad (Yashchuk et al., 2013). Nominal X-ray beam size on the sample is about 1 μm by 1 μm. A four-bounce constant-exit monochromator consisting of two identical channel-cut Si(111) crystals can be inserted in the path of the beam for an easy and rapid switch between polychromatic (white) beam and monochromatic beam, while illuminating the same spot on the sample. This is one capability which is rather unique to BL12.3.2, the possibility to conduct both white and monochromatic X-ray experiments on the same micron area of the sample (Dejoie et al., 2015). The available photon energy range is between 5 and 24 keV. The sample sits on a flexible xyzχϕ stage. X-ray diffraction patterns are collected using a DECTRIS Pilatus 1M hybrid pixel array detector, while X-ray fluorescence spectra can be collected with a VORTEX EM silicon drift detector. More technical details about the beamline can be found in Kunz et al., 2009b.

Besides ALS BL12.3.2, we can cite the APS undulator beamline 34 ID-E (Ice et al., 2005) specialized into a depth resolved technique called Differential Aperture X-ray Microscopy (DAXM), which uses polychromatic or monochromatic beam and a scanning wire near the surface of the sample to ray trace the reflections along the penetration depth of the beam into the sample (Larson et al., 2002). DAXM is one of the so-called 3D X-ray microdiffraction techniques that can reconstruct the volumetric distribution of grains and strains with submicron resolution. The VESPERS beamline at the Canadian Light Source (Feng et al., 2007b) and BM32 at the ESRF (Ulrich et al., 2011) offer capabilities similar to the ALS beamline. Undulator beamlines such as the 2-ID-D at the APS (Cai et al., 2000) and the Microfocus beamline ID 13 at the ESRF (Engström et al., 1995) provide monochromatic X-ray diffraction with high spatial resolution on the order of a few tens of nanometers. The ESRF Materials Science beamline ID11 offers a wide range of monochromatic diffraction techniques including 3D X-ray Diffraction (3DXRD), which is capable of mapping grains in 3D in deformed materials (Poulsen et al., 2001). The ESRF Microdiffraction Imaging beamline ID01 provides a submicron monochromatic beam for the study of engineered materials (Diaz et al., 2009), and the High Energy Scattering beamline ID15 has a high energy microdiffraction (HEMD) setup. Microspectroscopy beamlines such as the ALS BL10.3.2 often offer powder microdiffraction capability as well. For historical reasons, we also want to mention the now decommissioned NSLS X26C beamline (Wang et al., 1998) where some of the very first synchrotron microdiffraction experiments were performed with a 10 μm size white beam, as well as X26A (Lanzirotti et al., 2010) and X27A (Ablett et al., 2006) environmental science beamlines at NSLS.

Note that the X-ray photon flux (number of photons per second) reaching the sample, even with today’s 3^rdgeneration synchrotron sources, is still often a limiting factor for micro- and nano-focus applications, especially when a monochromatic beam is used. This is particularly true for the often weakly scattering environmental and geological samples where better signal-to-noise ratio and better diffracted intensity are needed. To that effect, several synchrotron facilities such as the ESRF, Spring8, APS and ALS are undertaking upgrades for smaller electron beam emittance to provide more photon flux and beam coherence.

Targeting a small micron-sized X-ray beam onto a specific small micron-sized area on the sample is difficult, so an efficient navigation system towards the point of interest has to be devised. This is generally provided by combining a good optical viewing system aimed at the sample and carefully calibrated to the focal point of the X-ray beam, and markings on the sample that are visible to X-rays, such as platinum marks deposited by Focused Ion Beam (FIB) that can be easily found by monitoring X-ray fluorescence. One caveat of microdiffraction is that sample rotation is generally to be avoided when the feature of interest is in the same order of size as the beam. Even the best diffractometer comes with a “sphere of confusion” exceeding today’s small beam sizes, which therefore moves the sample out of the beam during rotation (Noyan et al., 1999). Moreover, X-ray penetration also makes the volume of diffraction change with each angle, resulting in systematic errors when comparing reflections taken at different angles (Ice et al., 2000). This is why some methods used in X-ray microdiffraction differ from conventional ones used for regular “macroscopic” X-ray diffraction. Avoiding rotation in microdiffraction has been the driving force to seek alternate solutions to standard single crystal diffraction techniques for structure solution, reciprocal space mapping and residual stress measurement. Although the results may not always be as satisfying as those obtained by the well-established macroscopic techniques, these alternate methods offer the advantage of speed, as rotation is time consuming and not well suited for time resolved experiments. Besides, some samples, such as a precious small mineral embedded in a heterogeneous matrix or a high pressure compound inside a diamond anvil cell (DAC), are not suited to be freely rotated under the beam and the use of one of these alternate methods could be the only way to get around the limitation. Two methods, namely polychromatic X-ray microdiffraction and powder X-ray microdiffraction, are discussed in details in the following sections.

Figure 1. Outline of the BL12.3.2 dedicated to X-ray microdiffraction at the Advanced Light Source.

3. Sample preparation

Hard X-rays are penetrating, providing an advantage over electron microscopy or soft X-rays when it comes to sample preparation and sample environment. Sample preparation can be kept to a minimum and measurements performed in air (unless oxidation becomes an issue). This is particularly attractive for cases where the sample is buried inside a matrix or confined in a pressure chamber such as a DAC. A reasonably flat surface obtained through regular polishing is often all that is required for an experiment in reflective geometry. It is important, however, to complement mechanical polishing with chemical or electrochemical polishing for samples that are subject to mechanical deformation, such as metals and alloys, to remove the damaged surface layers. A note of caution, however, shall be given as X-ray penetration can also work against you if one is not careful; make sure that the sample is not too thick or that there is nothing underneath the sample that can diffract equally well. The superimposition of multiple diffraction patterns coming from different layers beneath the surface may become very difficult to interpret. If using a thin section on a glass slide, note that the slide itself would produce a contribution in the shape of a broad diffraction ring in monochromatic mode (Gräfe et al., 2014) and a large scattering background signal in polychromatic mode. These parasitic contributions can generally be digitally subtracted from the diffraction patterns, but may, however, become overwhelmingly high for weakly scattering samples. For transmission experiments, the thickness of the sample to use is determined by the average atomic number of the compound to be measured, but 20 – 40 μm is a good number for most geological samples.

4. Powder microdiffraction

Powder microdiffraction is the technique of choice for polycrystalline samples when the average size of crystallites or coherently diffracting units in the sample is much smaller than the X-ray beam size illuminating them (for a micron size X-ray beam, this means crystallite size of less than 100 nm). This is almost always the case for soil samples, and the fine fraction of industrial residues. When a monochromatic beam with a selected wavelength hits the sample, cones of diffraction specific to particular hkl crystallographic planes are formed and intersect the plane of the 2D detector as a portion of conics. The shape of the conics in the resulting diffraction pattern depends on the position and angle of the detector relative to the incident beam. It can be circular (direct transmission geometry), elliptic, parabolic or hyperbolic (Figure 2). The resulting diffraction patterns are called 2D powder patterns or Debye-Scherrer ring patterns. The angular positions and relative intensities of the rings are characteristics of the crystal structure of the diffracting materials and can be used for identifying the phases present in the sample. The common analytical practice is to integrate the 2D pattern along the azimuthal (χ) direction to form a 1D diffractogram that can be easily plugged into a database to search for matching crystal structures. The advantage of using a small beam becomes evident when a heterogeneous sample is considered. With a larger beam and such a sample, it can indeed become very difficult to disentangle reflections from a dozen different phases when there are many peaks overlapping and when some of the intensities are modified by texture.

Since most of the rings that help to unambiguously identify a crystalline structure occur at low angle, powder microdiffraction is generally best performed with the detector placed at a low 2θ angle, preferentially in transmission geometry, if the sample is thin enough. Poorly crystallized phases, such as clays, exemplify this very well as rings are broadened by the very small size of the constitutive crystallites; high angle rings have not only weakened intensities due to the decreasing form factor, but being more numerous, are also subject to strong overlaps. Clays are often identified by their lowermost angle of reflection. For example, for that of kaolinite and nontronite, 2θ = 9.2 and 4.6°, respectively, at 10 keV. For thicker samples, the sample surface will need to be put at a very shallow angle with respect to the incoming beam, which results in loss of spatial resolution in one direction as the beam footprint on the sample increases.

Reducing 2D patterns into 1D diffractograms is not always helpful, as much information about texture, crystal size and strain may be lost this way and is then difficult to retrieve in the final spectrum. The uneven intensity distribution along the azimuthal directions of diffraction rings reflects preferential orientation or texture, for instance. Highly textured samples show incomplete rings in the form of arcs that can be interpreted into pole figures. The level of graininess of the rings along the azimuthal direction is also a good qualitative indication of grain size. For a micron-sized beam, spotted rings are characteristics of samples with an average grain size that are about an order of magnitude smaller than the beam, while continuous rings indicate grain sizes two or more orders of magnitude smaller. In the latter case, the width of the rings in the radial direction is inversely proportional to the grain size, according to the Scherrer equation (Patterson, 1939). Perhaps a little less relevant for geological or environmental samples, mechanically or chemically induced strain can, in principle, be measured by powder microdiffraction. The standard distinction between “microstrain” and “macrostrain” is somewhat arbitrary, but as a rule of thumb, microstrain refers to strain distributions that vary within the X-ray illuminated area, which would cause a spread of interatomic spacings of hkl planes, resulting in a broadening of the rings associated to those planes. Formula such as the one provided by the Stokes-Wilson equation (Stokes and Wilson, 1944) can then be used to assess microstrain. Macrostrain, on the other hand, refers to a deformation which is uniform within the X-ray illuminated area. Such strain does not affect the broadening of the rings but their ellipticity. By fitting the shapes of multiple rings to a generalized sin² ψ equation, it is possible to derive the entire strain tensor of the crystal (Noyan and Cohen, 1987; Tamura, 2014). Finally, Rietveld refinement (Rietveld, 1969; McCusker et al., 1999) is a technique developed to refine the crystal structure of unknown compounds through a high resolution powder X-ray diffractogram (although originally formulated for neutron diffractograms). Note that Rietveld refinement could become quite problematic if not all reflections of the material are visible because of angular constraints or preferred orientation (texture). This well-established technique can be used for a wide variety of refinement such as size and strain distribution (Lutterotti and Scardi, 1990; Balzar and Popa, 2005) and texture (Popa, 1992; von Dreele, 1997).

A large variety of software exists to handle powder X-ray diffraction data obtained with an area detector, and can readily be used to treat powder microdiffraction data. Fit2D has been a pioneer in that area and was for a while the most widely used code for transmission geometry (Hammersley, 1996). The package contains all the standard tools such as distance calibration, center determination, intensity integration and peak fitting that have been adopted in all subsequent software. The Windows-based application XRD2DScan provides hands-on routines for determining average crystal size and quantification of preferential orientation (Rodriguez-Navarro, 2006) and can batch-process file series. XRDUA (De Nolf et al., 2014) is relatively new software that can also process diffraction tomography data. MAUD (Lutterotti et al., 1999) specializes in texture analysis via Rietveld refinement. XMAS (X-ray Microdiffraction Analysis Software) developed at the ALS (Tamura, 2014) can process data taken in both transmission and reflection geometries and can process raster scans into maps. Let’s also mention XPLOT2D of the XOP package (Sanchez del Rio and Dejus, 2004) and PyFAI (Kieffer and Karkoulis, 2013), both designed for performing azimuthal integrations of 2D detector data. Companies selling 2D X-ray detectors sometimes provide their own suite of software such as GADDS developed by Bruker AXS Inc. (Rowe, 2009). This list is in no way complete.

Powder microdiffraction has been widely used to identify minority phases in a wide range of geological samples. Some examples include speciation studies in ferromanganese nodules (Manceau et al., 2002), identification of interplanetary particles from the STARDUST mission (Nakamura et al., 2008), the study of acid mine drainage (Soler et al., 2008; Courtin-Nomade et al., 2012) or establishing the phase distribution at a heterogeneous cement-clay interface (Dähn et al., 2014). With regard to powder diffraction in general, we would like to stress the importance of crystallographic databases for phase identification. The International Centre for Diffraction Data (ICDD) has the most comprehensive database of inorganic compounds, but it is quite expensive and not always available at the institution hosting the beamline. Free but less complete databases available online includes the Crystallography Open Database (COD) (http://www.crystallography.net), the RRUFF project (http://rruff.info) and MINCRYST (http://database.iem.ac.ru/mincryst/).

Used in scanning mode, powder microdiffraction becomes an effective way to map phase distribution in a heterogeneous rock. Typical examples for very fine-scaled heterogeneous rocks can be found in partially weathered mine tailings, whose composition and evolution is of considerable interest since they pose a significant hazard to the environment due to their potential for toxic element release. To understand the processes occurring in acid mine tailings during exposure to atmospheric conditions, a detailed description, not only of the chemical composition but also of their mineralogical phase distribution on multiple scales from μm to km is required. A particular concern is the mobilization and transport of arsenic, which is present at toxic concentrations in tailings, where metals were mined in sulfide ore bodies. In an example from two former mines (gold and tungsten) in France (Courtin-Nomade et al., 2012), micro-spectroscopy is combined with powder microdiffraction to unravel the pH dependent dissolution and precipitation behavior of As. Combining chemical maps with powder microdiffraction-derived phase maps allows researchers to follow the speciation of As in different pH environment (Figure 3).

The possibility to mount thin sections of samples in transmission geometry and probe them with a small monochromatic beam also allows researchers to test in situ the spatial variation of texture. This has been nicely shown for authigenically grown ettringite in microscopic veins (Figure 4a) within decaying concrete (Wenk et al., 2009). The diffraction pattern in Figure 4b shows strong preferred orientation as evidenced by the significant azimuthal intensity variations. These intensity variations can be converted into pole figures and inverse pole figures, revealing a strong fiber texture with the c-axis perpendicular to the crack surface. This is interesting since ettringite (trigonal structure, space group P31c, a = 11.23 Å, c = 21.44 Å) exhibits the strongest stiffness parallel to c as opposed to another frequent secondary crack filling mineral phase, portlandite, Ca(OH)₂, which grows with its softest direction perpendicular to the crack surfaces.

Figure 2. Example of powder diffraction data taken with an area detector in transmission mode (left) and reflection mode (right).

Figure 3. Combining chemical mapping as for example derived from X-ray fluorescence (left) with phase maps (right) as obtained from powder microdiffraction in mapping mode, allows to deduce not only the distribution of As in mine tailings on a micron-scale, but also the mineralogical speciation. The white rectangle in the XRF map corresponds to the powder microdiffraction map (right); Ps = Parasymplesite, S0 = Sulfur, G = Goethite (From Courtin-Nomade et al., 2012).

Figure 4. (a) Optical micrograph of ettringite (white arrow) coating a microcrack in a decaying concrete. (b) Powder microdiffraction pattern. The strong azimuthal intensity variation along the Debye-Scherrer rings is evidence for a strong fiber texture perpendicular to the crack surface. (c) Pole figure and inverse pole figure (perpendicular to crack surface) of diffraction pattern displayed in (b) (from Wenk et al., 2009).

5. Polychromatic (Laue) microdiffraction

When crystallite sizes are in the order of magnitude of the X-ray beam size, monochromatic beam diffraction becomes challenging because of the necessity to bring sets of hkl planes into Bragg conditions. To that effect, sample rotation is a possibility if using a medium-sized beam (a few microns) large enough to accommodate sample motions during rotation. Single crystal diffraction conditions may be achieved this way; however, as noted in the introduction, the crystallite of interest would first need to be extracted first from the matrix. Another possibility is to reproduce a powder pattern. This method is more generally applied to polycrystalline samples where sample displacements become an ally rather than a hindrance; as many different crystals come into diffraction while rotating the sample, a powder pattern is generated and analytical methods described in section 3 can be applied. Raster scanning the polycrystalline sample is another solution to produce powder diffraction conditions, but this comes at the expense of spatial resolution. A better and less time consuming way to circumvent sample rotation is to use a polychromatic instead of monochromatic X-ray beam, simultaneously satisfying the Bragg condition for a number of reflections. The resulting diffraction pattern is called a Laue pattern (Figure 5). Since a single shot is all that is needed to obtain a Laue pattern, polychromatic microdiffraction is very fast and is suitable not only for samples having crystallite size larger than the beam size but also for time resolved studies. The interpretation of such patterns is usually not as easy; indexing requires matching a number of angles between reflections within the Laue pattern with those theoretically calculated for a given structure (Wenk et al., 1997). As the wavelength of each reflection is not known a priorifrom the Laue pattern alone, interplanar spacing values cannot be associated to it simply from the position of the reflection on the detector as with monochromatic beams. Nevertheless, successful indexing of a Laue pattern not only identifies the crystalline phase (although isomorphous compounds cannot be distinguished this way) but provides the full crystallographic orientation of the crystallite with respect to an arbitrarily chosen coordinate system (usually the sample coordinate system).

Small shifts in reflection positions relative to their ideal ones, as calculated from a perfect unit cell, can also be measured and converted into the deviatoric strain tensor and therefore can be used to assess the crystallite’s elastic deformation (Chung and Ice, 1999). Moreover, local lattice bendings generated by geometrically necessary dislocations will result in asymmetric broadening of the reflections. These reflections can be directly compared to simulations in order to determine such information as dislocation densities and crystallographically active slip systems (Barabash et al., 2001). This can be used to assess the local level of plastic deformation in the sample.

For a beamline with a maximum energy around 20 keV, Laue microdiffraction works best in reflection geometry with the detector placed at a higher 2θ angle. This stems from the fact that a sufficient number of reflections have to be visible on a diffraction pattern in order to unambiguously index it, and the population of possible reflections is denser at high angles. Indeed, most minerals have small to medium size unit cells that create only a few reflections at low angles. High energy beamlines do not have this limitation and Laue microdiffraction in that case works perfectly well in transmission geometry, but the detector has to be translated further back from the sample to preserve angular resolution. Since data collection is rather fast (second to sub second exposure time for each frame), Laue microdiffraction is often used in scanning mode. Thus, a raster scan of the sample can be used to map crystalline phase distribution, crystal orientation, as well as elastic and plastic strains. Figure 6 shows an example of such maps.

Analytical software capable of rapidly analyzing in a fully automated way tens of thousands of Laue patterns is a necessity for such experiments. The XMAS software, already cited in section 3, was originally written for that purpose. Additionally, part of its core capabilities are Laue X-ray microdiffraction patterns, reflection search and fitting, indexing and strain refinement, as well as many add-on routines for simulations and data visualization, and monochromatic beam data analysis. The open source code LaueTools developed at the ESRF (Robach et al., 2011) reproduces many of the Laue analysis functionalities of XMAS in an open source environment, providing publication ready outputs, and has lately gained increasing popularity among Laue microdiffraction users in Europe.

Synchrotron Laue microdiffraction had its initial successes in the study of the mechanical properties of functional materials and microelectronic devices (Valek et al., 2003; Rogan et al., 2003; Mehta et al., 2007), but has now expanded its range of applicability to many other scientific areas. Probably because the data interpretation is less straightforward and the methodology is less widely distributed, Laue microdiffraction has scarcely been used for geochemical and geological studies. However, recent studies show that it can be effectively employed to assess the level of stress in shocked quartz from a meteor impact site (Chen et al., 2011a) and to derive the hierarchy and sequence of mechanical twins in geological calcite, opening the prospect of using Laue microdiffraction measurements as a palaeopiezometer (Chen et al., 2011b).

A series of initial studies applying Laue X-ray microdiffraction to geological samples explored the possibilities to measure residual stresses in quartz crystals from a variety of rocks (Kunz et al., 2009a; Chen et al., 2011a). Quartz is a quite obvious choice as paleo-piezometer, since it shows very little chemical substitution giving rise to chemically induced variations in cell parameters, occurs in a wide variety of rocks and exhibits relatively high trigonal symmetry thus facilitating accurate determination of the deviatoric strain tensor. Figure 6 shows an example of high-resolution maps showing the variation in lattice orientation as well as the dislocation density within a grain of quartz from the Bergell granite intrusion. The resolution in orientation lies around 0.01°, therefore enabling the measurement of subtle changes in lattice orientations leading to undulatory extinction in quartz. The dislocation density map displays the accumulation of dislocations in the vicinity of cracks.

Figure 7 compares histograms of equivalent strain as defined by Liu (2005) for three different quartz crystals with different deformation histories, ranging from synthetic fully unstrained quartz to 2 billion year old quartz subject to a meteor impact. While the synthetic quartz showed no strain signal above experimentally inherent noise, the shocked crystal shows a distribution of equivalent strain values centered around 1.5 microstrains. In between these values is the strain distribution measured on a quartz crystal extracted from granite, which underwent some moderate deformation.

Figure 5. Examples of X-ray microdiffraction Laue patterns. From left to right and top to bottom: textured gold film on silicon, garnet crystal, silicon blister, shocked quartz, aragonite from abalone shell. The treatment of Laue patterns is usually more complex than for monochromatic patterns.



Figure 6. Orientation (top) and peak broadening (bottom) maps of a piece of quartz obtained by scanning Laue X-ray microdiffraction. Orientation varies up to 4o in the entire crystal and dislocation pile-up at subgrain boundaries are indicated by reflection broadening.



Figure 7. Distribution of equivalent strain within 3 different quartz crystals with strongly different deformation histories. Synthetic quartz is a synthetic, strain free crystal. ‘Granite’ denotes a sample from moderately deformed granite from the Santa Rosa granite (California); ‘Vredefort’ refers to shocked quartz granite from the Vredefort impact site (South Africa). The grain showed planar deformation features attributed to a meteor impact 2 billion years ago (Chen et al., 2011).

6. Conclusions and future perspectives

Synchrotron X-ray microdiffraction is a powerful but underutilized tool to study the microstructure of geological and environmental samples. It can be used effectively for mapping phase distribution, determining crystal structure of minute elements and measuring strain and dislocation densities. Monochromatic (powder) and polychromatic (Laue) microdiffraction can be used together in heterogeneous samples to map both nanocrystallized, or poorly crystallized, and microcrystallized phases using powder and Laue microdiffraction, respectively. For example, this combination has been exploited to maximum effect in the study of ancient ceramics (Leon et al., 2010; Dejoie et al., 2014; Dejoie et al., 2015). Initially, in an effort to avoid the sphere of confusion problem, X-ray microdiffraction experiments were confined to techniques that avoided sample rotation. However, due to developments in data reduction software, the absence of sample rotation has become the principal strength of microdiffraction. Today, area detectors work at unprecedented speed and angular resolution that take full advantage of the high photon flux provided by synchrotron beamlines (Gruner et al., 2002; Broennimann et al., 2006; Henrich et al., 2011; Ponchut et al., 2011). A full diffraction pattern can be collected in subsecond to a few seconds time with negligible instrumental downtime. This, combined with the exponential increase in computing power that we are currently experiencing, is triggering the next evolution for the X-ray microdiffraction technique that has been developed in the last decade. We are in the process of transitioning from a microstructure mapping tool where a few hundreds of diffraction patterns are obtained from a raster scan and processed off-line at the home institution of the experimenter, to a real-time microstructure imaging tool where several tens of thousands of patterns are collected in a reasonable amount of time (no more than a few hours for a few days of beamtime) and processed transparently and directly during the beamline. Codes such as XMAS have already been exported onto supercomputers allowing extraction of information such as crystal orientation and strains from thousands of patterns within minutes instead of hours, rendering the study of dynamic processes such as crack propagation within reach. Structure solution by Laue microdiffraction is another area that is benefiting geology (Dejoie et al., 2013). This might indeed be the only possible way to solve the atomic structure of tiny unknown crystals embedded in a heterogeneous, rocky matrix, or new phases generated under high pressure and temperature inside a DAC. There are, therefore, strong indications that synchrotron microdiffraction could become one of the standard techniques for the geologist and geochemist among the arsenal of already available tools such as synchrotron X-ray and Raman microspectroscopies, soft and hard X-ray imaging, and electron microscopies.

Acknowledgements

The Advanced Light Source (ALS) is supported by the Director, Office of Science, Office of Basic Energy Sciences of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231 at the Lawrence Berkeley National Laboratory (LBNL). The authors would like to thank the reviewers for their useful comments on how to improve the manuscript.

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Manuscript received: October 30, 2014.
Corrected manuscript received: May 12, 2015.
Manuscript accepted: May 15, 2015.

Boletín de la Sociedad Geológica Mexicana Volumen 67, núm. 3, 2015, p. 457-465 http://dx.doi.org/10.18268/BSGM2015v67n3a9

Modeling the additive effects of Pb(II) and Cu(II) on the competitive attenuation of As(V) through solid precipitation versus adsorption to goethite

Katherine Vaca-Escobar¹, Mario Villalobos^2,*

¹ Posgrado en Ciencias de la Tierra, Instituto de Geología, UNAM, Ciudad Universitaria, Coyoacán, México DF 04510, México.
² Departamento de Geoquímica, Instituto de Geología, UNAM, Ciudad Universitaria, Coyoacán, México DF 04510, México.

^* This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract

Mine-related activities cause widespread contamination of aqueous environments with high concentrations of arsenic and accompanying heavy metals. The natural attenuation of As(V) in soils and groundwater under oxic conditions occurs mainly through sorption processes to iron and aluminum (hydr)oxides; as well as through the formation of highly insoluble heavy metal(II) arsenates.

In the present investigation we used thermodynamic modeling to predict the environmental geochemical behavior of As(V) in the presence of Pb(II), Cu(II) and goethite, in an effort to approach the complexity of multi-component real contaminated scenarios. The key to this modeling was the coupling of a highly robust Surface Complexation Model of As(V) adsorption to goethite, which uses combined tenets of the Triple-Layer and CD-MUSIC models, together with appropriate metal(II) arsenate solid formation constants as well as those of all chemical equilibria taking place in the aqueous phase. Mixed-metal arsenates were predicted to form and increase the predominance region of the precipitation reactions for a highly surface-reactive goethite, at the expense of the adsorption mechanism, but the model yielded no aqueous As(V) released at any condition investigated.

Keywords: Adsorption, precipitation, arsenate, goethite, lead, copper, Surface Complexation Model, Triple-Layer Model, CD-MUSIC Model.

Resumen

Las actividades relacionadas con la minería provocan contaminación extendida de ambientes acuosos conjuntamente de arsénico y metales pesados. La atenuación natural de As(V) en suelos y acuíferos en condiciones óxicas ocurre principalmente a través de procesos de adsorción a (hidr)óxidos de hierro y aluminio; así como a través de la formación de arseniatos de metales(II) pesados altamente insolubles.

En esta investigación utilizamos modelación termodinámica para predecir el comportamiento geoquímico ambiental del As(V) en presencia de Pb(II), Cu(II) y goetita, tratando de aproximarnos a la complejidad de escenarios multicomponentes de contaminación real. La clave de esta modelación fue el acoplamiento de un modelo de complejación superficial altamente robusto de adsorción de As(V) en goetita, el cual utiliza postulados combinados de los modelos de Triple Capa y CD-MUSIC, junto con constantes apropiadas de formación de arseniatos de metales divalentes sólidos y de todos los equilibrios químicos que ocurren en la fase acuosa. Se predice la formación de arseniatos metálicos mixtos que aumentan la región de predominio de las reacciones de precipitación, a expensas del mecanismo de adsorción en goetitas de alta reactividad superficial, pero el modelo predice que no se libera As(V) acuoso en ninguna de las condiciones investigadas.

Palabras clave: Adsorción, precipitación, arseniato, goetita, plomo, cobre, Modelo de Complejación Superficial, Modelo de Triple Capa, Modelo CD-MUSIC.

1. Introduction

Arsenic is a metalloid constituent of more than 245 minerals, and is associated most frequently with other metals such as copper, gold, lead, and zinc in sulfidic ores (Cullen and Reimer, 1989; Oremland and Stolz, 2003; Shen et al., 2013). Many sources of arsenic contamination result from human activities like the disposal of industrial chemical wastes, including mine wastes, the smelting of arsenic-bearing minerals, the burning of fossil fuels and the application of arsenic compounds in many products, especially in the past few hundred years (Garelick et al., 2008; Chang et al., 2009; Mirza et al., 2014). For example, arsenic concentrations measured in soils near a lead smelter were in average 2 g kg^-1, near a copper smelter 0.55 g kg^-1, and near a gold smelter from 0.5 to 9.3 g kg^-1(Bissen and Frimmel, 2003).

The reduction of arsenic levels in contaminated drinking water and soils is one of the priority environmental challenges worldwide (Thirunavkukkarasu et al., 2002). In Mexico, arsenic contamination problems in water and soils have been reported in the following regions: Villa La Paz, San Luis Potosí (Gamiño-Gutiérrez et al., 2013); Matehuala, San Luis Potosí (Martínez-Villegas et al., 2013); Comarca Lagunera in NW Mexico (Ordáz et al., 2013); Zimapán, Hidalgo (Romero et al., 2008); Guanajuato (Arroyo et al., 2013); and Zacatecas and Guadalupe, Zacatecas (Mireles et al., 2012). To reduce arsenic contamination, it is of utmost importance to understand all aspects of arsenic environmental geochemistry, which in turn will provide useful information to optimize treatment and remediation schemes for contaminated environments.

The reactivity of Arsenate [As(V)] with individual soil minerals determines the general mobility of arsenic in soils. As(V) is the predominant inorganic species of arsenic under oxidizing soil conditions (Goldberg, 2011; Camacho et al., 2011), and is retained in soils by adsorption processes (Goldberg and Glaubig, 1988; Smith and Naidu, 2009). Important minerals that control the As(V) adsorption capacity of soils include Fe and Al oxides, such as goethite, ferrihydrite, gibbsite, etc. (Violante et al., 2010; Smedley and Kinniburgh, 2013). However, there is evidence that in situations where the metal contents that accompany As(V) are high (as in smelting, mining and metallurgical wastes), formation of (highly insoluble) heavy metal arsenates occurs, such as duftite, mimetite, hydroxymimetite and bayldonite, making precipitation the predominant immobilization mechanism over the adsorption process (Gutierrez-Ruiz et al., 2005; Villalobos et al., 2010; Drahota and Filippi, 2009; Vaca-Escobar et al., 2012). For example, Villalobos et al. (2010) reported various As-contaminated soils with pH values between 4.5 and 10.2, As/Fe molar ratios of 0.03 – 2.5, As/Pb molar ratios of 0.53 – 300, and As/Cu molar ratios of 0.44 – 32, in which the presence of mixed heavy metal arsenates was identified.

In the present research, we use thermodynamic modeling to investigate the environmental geochemical conditions of arsenate mobility in aqueous environments, focusing on the competition between formation of Pb and Cu arsenates and adsorption mechanisms to an Fe oxide. We chose goethite because it is thermodynamically one of the most stable iron oxides in the environment (Schwertmann and Cornell, 2007), and therefore it is well characterized and the subject of many studies on surface complexation modeling (Hayes et al., 1991; Mathur and Dzombak, 2006). We build from our previous research with Pb(II)-only arsenate/goethite systems (Vaca-Escobar et al., 2012), in a “bottom-up” approach to progressively describe more complex systems in a quantitative manner, particularly those with various heavy metals present simultaneously. In this previous work we found that As(V) adsorption is favored at low As/Fe molar ratios (less than 0.021) or high As/Pb molar ratios (above 0.667), but also with highly reactive goethites of large particle sizes. In opposite conditions, Pb(II) precipitation becomes the more competitive immobilizing mechanism (Vaca-Escobar et al., 2012).

The main question asked here is whether the simultaneous presence of Cu(II) with Pb(II) promotes a higher predominance of precipitated metal arsenates versusAs(V) adsorption to goethite, and to what extent this occurs. Also, in conditions that favor precipitation, how prevalent are the mixed Pb(II)-Cu(II) arsenates in comparison with the single Pb(II) or Cu(II) arsenates.

2. Materials and methods

2.1. Thermodynamic modeling

The arsenic species distribution was calculated by thermodynamic modeling using the Visual Minteq geochemical equilibrium and speciation interface, version 3.0 (Gustafsson, 2010). This program was updated with surface complexation constants for goethite reported by Salazar-Camacho and Villalobos (2010). These authors used combined tenets of the Triple-Layer and CD-MUSIC surface complexation models (SCMs) to describe in a unified manner the adsorption behavior of goethite, irrespective of its specific surface area (SSA), by defining the adsorption reactions per type of reactive site on the goethite surface. The two goethites for which the unified model has been calibrated have SSAs of 50 m² g^-1 (GOE50) and a 94 m² g^-1(GOE94) (Salazar-Camacho and Villalobos, 2010). The latter corresponds to small ideal goethite crystals, and the former to larger particles that show higher reactivity per unit area.

Table 1 lists all surface complexation constants used, including their expressions and corresponding formation reactions. Binary adsorption data for the unified goethite model were available for As(V) and Pb(II) (Salazar-Camacho and Villalobos, 2010), but not for Cu(II). Pb(II) shows a higher binding affinity for goethite (and other minerals) than Cu(II) (Christophi and Axe, 2000). Therefore, we hypothesized that As(V) (Kingston et al., 1972) and Pb(II) (Kooner, 1993) adsorption are sufficiently stronger than Cu(II) adsorption to goethite, and that the exclusion of the latter would not affect the modeling results. To test this hypothesis, we modeled the Pb(II)/As(V)/goethite system in the presence and absence of the binary Pb(II) adsorption reactions. We found no difference in the As(V) speciation results, but only in the case of the more surface reactive GOE50. Therefore, we decided to perform the modeling for the complete system including Cu(II) only with this GOE50, and for the moment to exclude GOE94 since we could not ensure that the absence of Cu(II) surface binding constants would affect the results for the latter.

To complete the SCM, in addition to the surface complexation constants, other input parameters are required. They include: the specific surface area (50m² g^-1); the surface site density (see below); two electrical capacitances (C₁ = 1.17 F m^-2 and C₂ = 0.20 F m^-2); a fixed GOE50 solids concentration (0.2 g L^-1); ionic strength (I = 0.01 mol L^-1 NaNO₃); and LogPCO₂= -3.5. Computations were performed by varying the concentration of total As(V), essentially increasing the total As/Fe ratio.

The surface site density is dependent on the contribution of the specific exposed crystal faces of the goethite sample used. It is calculated from chromate adsorption maxima at pH 4. For the 50m² g^-1 goethite they are: 6.86 sites nm^-2 for ≡FeOH; 2.87 sites nm^-2 for ≡Fe₂OH; and 1.12 sites nm^-2 for ≡Fe₃OH groups; with a face distribution of 37 % for {101} and 63 % for {010} (Salazar-Camacho and Villalobos, 2010).

The SCM was coupled to an aqueous and solid thermodynamic speciation model, for which the corresponding available formation constants of all species are listed in Table 2. The complete thermodynamic model applied was validated previously by wet chemical experimental results, which matched closely the model results for the As(V)/Pb(II)/goethite system (Vaca-Escobar et al., 2012). Therefore, we are confident that the model employed represents well the behavior of the system when one additional component, i.e., Cu(II), is added, so no additional experimental verification of the model results was performed.

For the As(V)/Pb(II)/Cu(II) system, two different ratios of total concentrations added were chosen (1/1/1 and 2/1/3) to represent those of the two main mixed-metal arsenates that form: duftite [PbCu(AsO₄)(OH)] and bayldonite [PbCu₃(AsO₄)₂(OH)₂].

Table 1. Surface complexation reactions uploaded in Visual Minteq with formation constants described per type of surface site (Vaca-Escobar et al., 2012; Villalobos et al., 2009).

^a SOH can be FeOH, Fe₂OH or Fe₃OH groups. As(V) surface complexation constants were taken from (Salazar-Camacho and Villalobos, 2010), and those for Pb(II) from (Villalobos et al., 2009).
^bnr = non-reactive group.
^c The log of acidity constants used was established through a ΔpKa of 4 around each pH of PZNPC for each site type, which were 8.8 and 9.66, for FeOH and Fe₃OH groups, respectively.

Table 2. Solid and aqueous species formation constants from their components, used in the thermodynamic model (Taken from Visual Minteq Database).

^a Log Kf taken from Villalobos et al., 2010 and included in Visual Minteq Database.

3. Result

The first step was to determine the solid speciation expected as a function of pH in the absence of adsorption processes, in order to gain knowledge of the metal(II) solids expected to compete for As(V) binding with the goethite surface (Figure 1). Table 3 summarizes the results by reporting the expected solids and their stability pH range at the different As(V)-Cu(II)-Pb(II) molar ratios studied.

After this, the complete model that includes adsorption onto goethite (GOE50) was applied, and the sum of three main types of As(V) species predicted – adsorbed, precipitated and dissolved – were plotted as percentage of the total As(V) applied. This was done as a function of the molar As/Fe ratio, to determine the species contributions as As(V) increased relative to goethite (Figures 2 and 3).

Table 3. pH range in which there are solid formations with respect to composition.

^a The corresponding chemical formulas are listed in Table 2.
^b Molar ratios taken from Vaca-Escobar et al. (2012).

Figure 1. Saturation indices of As-Cu-Pb solids in the absence of goethite, for a system composed of a) [AsO₄^3-] = 1×10^-4 M, [Cu²⁺] = 1×10^-4 M (As/Cu = 1/1); b) [AsO₄^3-] = 2×10^-4 M, [Cu²⁺] = 3×10^-4 M (As/Cu = 2/3); c) [AsO₄^3-] = 1×10^-4 M, [Cu²⁺] = 1×10^-4 M, [Pb²⁺] =1×10^-4 M (As/Pb/Cu = 1/1/1); and d) [AsO₄^3-] = 2×10^-4 M, [Cu²⁺] = 3×10^-4 M, [Pb²⁺] = 1×10^-4 M (As/Pb/Cu = 2/1/3). All systems have I = 0.01 M NaNO₃. Chemical formulas of solid minerals shown are listed in Table 2.

3.1. Simple As(V)-Pb(II) systems

The As(V)/Pb(II) system was investigated previously and the mineral hydroxymimetite [Pb₅(AsO₄)₃OH] was identified as the main solid forming in a pH range of 5 to 9 (Vaca-Escobar et al., 2012).

When adsorption processes to GOE50 were included in the model, this retention mechanism controlled As(V) speciation, and precipitation of hydroxymimetite did not occur until all surface sites were saturated, as As/Fe was increased. This was in stark contrast to the behavior shown by GOE94, in which precipitation of hydroxymimetite occurred considerably before surface site saturation with As(V) was attained, and quickly became the predominant mechanism as As/Fe was further increased (Vaca-Escobar et al., 2012).

3.2. Simple As(V)-Cu(II) systems

A Cu(II) arsenate is predicted to precipitate in a very narrow pH range around 6, which is the pH of minimal As(V) solubility for As/Cu molar ratios of 1 (Figure 1a) and 2/3 (Figure 1b). Therefore, pH 6 was one of the values chosen for further investigations in the complete system.

In the presence of goethite, adsorption of As(V) was not disrupted by the presence of Cu(II) (Figure 2). Even after surface site saturation is reached as As/Fe is increased, before the onset of the Cu(II) arsenate precipitation, dissolved As(V) reached values above 40 % at the maxima for both As/Cu ratios investigated at pH 6. At an As(V)/Cu(II) molar ratio of 1 (Figure 2a) the dissolved species contribution stabilized at around 30 %. At the lower As(V)/Cu(II) molar ratio (2/3) the dissolved species decreased to less than 10 % at high As(V)/Fe(III) molar ratios (Figure 2b). Thus, precipitation of the arsenate became highly predominant in this latter system. Therefore, in comparison with the As(V)-Pb(II) systems, the As(V)-Cu(II) systems are predicted to be much less efficient in removing aqueous As(V).

Figure 2. As(V) species distribution in the presence of Cu(II) and goethite (GOE50) at pH 6 and I = 0.01M NaNO₃ a) As/Cu molar ratio = 1, and b) As/Cu molar ratio = 2/3.

3.3. As(V)-Pb(II)-Cu(II) systems

In the As(V) system where both metals are present a more complex precipitation behavior was observed (Figures 1c and d), in which several solids may coexist over wide pH intervals (Table 3). For both As(V)/Pb(II)/Cu(II) molar ratios used in this research (1/1/1 and 2/1/3), pH 7 was chosen for investigating the system in the presence of goethite because at this value they showed the lowest As(V) solubility. At a 1/1/1 ratio the only solid predicted to form at pH 7 was duftite [PbCu(AsO₄)(OH)] (Figure 1c), while at the 2/1/3 ratio three simultaneous solids were predicted, two of them being mixed-metal arsenates: duftite [PbCu(AsO₄)(OH)], and bayldonite [PbCu₃(AsO₄)₂(OH)₂]. However, a much lower As(V) solubility was predicted in the former case (10 – 7.6 M — not shown in the scale of Figure 1c), in comparison to the latter (10 – 6 M — Figure 1d); as well as a wider pH range of insolubility.

In the systems that include adsorption to GOE50, the first important difference observed from those in the absence of Cu(II) is that the As/Fe region of predominance of the adsorption mechanism was diminished, on account of an increase in the corresponding region of arsenate precipitation. The As(V) insolubility behavior described above is well reflected here by showing a larger decrease in the adsorbed species distribution for the system with an As/Pb/Cu molar ratio of 1/1/1 (Figure 3a), and the corresponding increase in the precipitation of duftite, as compared to the system with a 2/1/3 ratio (Figure 3b). It is interesting to note that the onset of precipitation occurred at a very similar As/Fe ratio for both systems, but the former showed a considerably steeper precipitation curve, such that the crossing point where adsorption and precipitated species were equal appeared at a considerably lower As/Fe value (Figure 3a) than for the 2/1/3 system (Figure 3b) (0.019 for the 1/1/1 ratio and 0.027 for the 2/1/3 ratio).

In the 1/1/1 system at the As/Fe ratio of 0.01, at which site saturation occurs in the absence of metals, adsorption decreased to approximately 70 %; whereas in the 2/1/3 system the adsorption decrease was small (ca. to 90 %) at this As/Fe ratio, and the adsorption curve in general was close to the one in the absence of metals. Dissolved species did not appear in this system, because As(V) species were distributed exclusively between adsorbed and precipitated.

Figure 3 As(V) species distribution in the presence of Pb(II), Cu(II), and goethite (GOE50) at pH 7 and I = 0.01M NaNO3 a) As/Pb/Cu molar ratio = 1/1/1, and b) As/Pb/Cu molar ratio = 2/1/3.

4. Discussion and conclusions

Thermodynamic modeling is a powerful tool for predicting the behavior of complex multi-component systems in which adsorption and solid mineral precipitation occur as potential attenuation processes. This is the case for As(V) in the presence of heavy metals (II) and goethite, for which accurate geochemical modeling is possible when a robust adsorption model is available. This research can be of great interest because we have not found other investigations that combine adsorption and precipitation processes in compounded thermodynamic modeling to predict As(V) behavior in soils, and to propose remediation methods.

Previously it was found that in the presence of Pb(II), As(V) may form very insoluble minerals before it saturates the goethite surface, but only for an ideal goethite of small particle sizes. For larger more surface-reactive goethites, the adsorption mechanism prevails, and precipitation does not occur until all surface sites are occupied, except in the presence of chloride because of mimetite formation, which is considerably more insoluble than other lead arsenates (Vaca-Escobar et al., 2015).

In the present work we investigated the behavior of As(V) when a second metal component [Cu(II)] was added to the system, in an effort to approach the complexity of mine waste-contaminated environments. A considerable decrease in the adsorption of As(V) to a large goethite was found when the three components were added at a ratio of 1/1/1, in a similar fashion to the decrease observed in the presence of Cl^- and in the absence of Cu(II), due to formation of the extremely insoluble mimetite mineral (Vaca-Escobar et al., 2015). The adsorption decrease in the presence of Cu(II) was caused by the precipitation of a mixed-metal arsenate called duftite: PbCu(AsO₄)(OH).

At an added ratio of 2/1/3 for As/Pb/Cu, corresponding to another mixed-metal arsenate, bayldonite [PbCu₃(AsO₄)₂(OH)₂], a much lower effect on the adsorption of As(V) to goethite was observed, despite the fact that both mixed Pb(II)-Cu(II) minerals are predicted to precipitate simultaneously.

In the mixed-metal systems none of the existing single-metal arsenates were predicted to form at the two ratios investigated, and no aqueous As(V) appeared under any of the conditions investigated. In this manner, the interplay between adsorption and precipitation, whether one mechanism or the other prevails, allows for an efficient attenuation of As(V) in aqueous systems contaminated with As(V) and heavy metals Pb(II) and Cu(II).

Conversely, in the As(V)/Cu(II) system [i.e., without Pb(II) added], the Cu(II) arsenate solubility was not low enough to affect the adsorption process, and in fact a considerable fraction of aqueous As(V) appeared beginning from an As/Fe ratio of ca. 0.02. Therefore, it seems advantageous from an environmental perspective that more than one metal(II) be present simultaneously with As(V) in a contamination scenario to ensure their immobilization, in which the formation of insoluble mixed-metal arsenates seems to be a predominant attenuation mechanism. Given that mixed metal arsenates have been detected in contaminated soils, and that in previous laboratory experiments less than 14 days were required to reach equilibrium for Pb(II) arsenate solid formation, we believe no major kinetic impediments exist for the formation of mixed metal arsenates in contaminated environments.

The results of this work are highly relevant for understanding the environmental geochemistry of As(V) in aqueous environments, such as soils, with high contents of heavy metals, and for the conceptual design of efficient remediation schemes of As-contaminated environments by controlled addition of other heavy metal wastes in systems with a high As/Fe molar ratio.

Acknowledgements

This research was funded by the CONACyT through Project # CB-2010-01-153723. K. V.-E. is grateful to CONACyT for the Ph.D. student fellowship received.

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Manuscript received: October 27, 2014.
Corrected manuscript received: March 24, 2015.
Manuscript accepted: April 6, 2015.