Further evidence for magnetic susceptibility as a proxy for the

Transcription

Further evidence for magnetic susceptibility as a proxy for the
Environ Earth Sci (2016)75:309
DOI 10.1007/s12665-015-5187-8
ORIGINAL ARTICLE
Further evidence for magnetic susceptibility as a proxy
for the evaluation of heavy metals in mining wastes: case study
of Tlalpujahua and El Oro Mining Districts
Juan Morales1 • Marı́a del Sol Hernández-Bernal2 • Pedro Corona-Chávez3
Avto Gogichaishvili1 • Francisco Bautista4
•
Received: 18 May 2015 / Accepted: 22 October 2015
Ó Springer-Verlag Berlin Heidelberg 2016
Abstract Magnetic susceptibility is nowadays used in
most areas of environmental research as a proxy for heavy
metal pollution in industrial and urban areas. Although the
relationship between magnetic susceptibility and concentration of toxic elements in different environments has been
pointed out in several studies, mining wastes (tailings) have
hardly been investigated by magnetic methods. We report
the relationships between magnetic susceptibility and
potentially toxic elements monitored at 12 vertical ground
profiles of the Tlalpujahua and El Oro mining districts,
western Mexico. Specific bulk magnetic susceptibility
(k) measurements, percentage frequency-dependent susceptibility (%XFD) determinations as well as the identification of the magnetic carriers within the samples were
accomplished using standard rock-magnetic techniques on
geochemically well characterized sister samples. Magnetite
and/or Ti-poor titanomagnetite seem to be the main magnetic carriers in the samples. Tight correspondence
between k and Fe concentrations, as well as Pb and As with
the iron content were found. This association seems to hold
also for pH variations.
& Juan Morales
[email protected]; [email protected]
1
Laboratorio Universitario de Geofı́sica Ambiental (LUGA),
Unidad Michoacán del Instituto de Geofı́sica, UNAM
Campus Morelia, Mich, Mexico
2
Escuela Nacional de Estudios Superiores (ENES), Unidad
Morelia, UNAM Campus Morelia, Mich, Mexico
3
Instituto de Investigaciones en Ciencias de la Tierra,
UMSNH, Morelia, Mich, Mexico
4
Laboratorio Universitario de Geofı́sica Ambiental (LUGA),
Centro de Investigaciones en Geografı́a Ambiental, UNAM
Campus Morelia, Mich, Mexico
Keywords Mining tailings Magnetic susceptibility Potentially toxic elements Proxy
Introduction
Industrial mining in Mexico has been developed since 1550
and consequently there are abundant mining districts
associated with several billion tons of waste mining (tailings) scattered around the country (Corona et al. 2010).
Nowadays, the study of the distribution and concentration of potentially toxic elements (PTE) contained in the
mining tailings acquires great relevance since it has been
recognized that such elements may cause serious environmental and health problems to populations established in
their vicinity (Monroy et al. 2002; Armienta et al. 2003;
Talavera et al. 2005; Ramos-Arroyo et al. 2004; Canet
et al. 2008 and references therein). Moreover, due to social
and demographic aspects, among other reasons, tailings of
abandoned mining districts in Mexico are now occupied
and serve as settlements for various inhabitant groups.
These studies are carried out traditionally by means of
geochemical analysis, which are expensive, laborious and
time-consuming. The need for fast and inexpensive monitoring tools of heavy metal pollution has led to the search
of other methods of determination (Morton-Bermea et al.
2009). The correlation between magnetic susceptibility and
heavy metal content has been reported in numerous works
(Petrovsky et al. 1998, 2001; Durza 1999; Shu et al. 2001).
This correlation could be due to the fact that heavy metal
elements are incorporated into the lattice structure of the
ferrimagnetics during combustion process or are adsorbed
onto the surface of ferrimagnetics already present in the
environments (Petrovsky et al. 1998; El Baghdadi et al.
2012).
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However, except by the study by Matasova et al. (2005)
carried out in wastes of the mining industry in Western
Siberia, Russia and very recently that of Pérez et al. (2014)
accomplished in a metallurgical area in the San Luis Potosi
State, Mexico; magnetic methods have not been applied
systematically to the study of tailings in spite of the fact
that magnetic measurements are sufficiently sensible to
detect the magnetic signal of the minor fraction of ferromagnetic materials, in most of the cases with concentrations less than 1 % (Chaparro 2006). Their results remain
scarce.
Because of the more than 60 years of abandon, the
Tlalpuhajua and El Oro mining districts, western Mexico
(see below for details), represent a potentially pollution
problem due to the more than 60 tons of wastes dispersed
on the area estimated by Uribe Salas (2008).
Aimed to overcome this situation, we focused on evaluating the potentiality of magnetic methods to reliably
determine PTE concentrations in tailings in a faster and an
economical way; magnetic susceptibility determinations
(the key magnetic parameter used in this study) are lowcost, easy and fast to obtain.
We report the relationships between magnetic susceptibility and pH with PTEs, monitored at 12 different vertical ground profiles in tailings of the Tlalpujahua and El
Oro mining districts, western Mexico.
Environ Earth Sci (2016)75:309
Fig. 1 Location map of the Tlapujahua-El Oro Mining District
(TOMD)
Corona-Chávez 2006 and references therein) and is
emplaced over a Jurassic-Early Cretaceous rock basement
(Centeno-Garcı́a et al. 2003), Fig. 2. The surface covered
by the tailings dams was estimated by Martı́nez-Medina
(2009) in approximately 62 ha.
Samples
Study area
Historical background
It is widely recognized that the extraction of metals in
Mexico began since pre-Hispanic times (e.g. Horcasitas de
Barros 1981; Maldonado 2005; Martı́nez-Medina 2009),
while the formal mining activity until the XVI century,
during the colonial era. In this time, a series of exposed
silver and gold veins were located and exploited for more
than five centuries in the heart of the modern cities of
Tlalpujahua and El Oro (hereafter referred to as TOMD);
which was known as the ‘‘Real de Minas of Tlalpujahua’’
(Corona et al. 2010) and where more than 60 tons of wastes
were generated and disposed of, as estimated by Uribe
Salas (2008).
The TOMD is located at the boundaries of the
Michoacán and Estado de Mexico states (Fig. 1) and is part
of the hydrological basin ‘‘Lerma Santiago River’’ (Corona
et al. 2010). Although the TOMD is recognized essentially
as a gold-deposit, the mineralization in this district is
considered as a part of the big-silver metallogenic province
(Ostrooumov and Corona Chávez 1999; Albinson et al.
2001). The TOMD is located within the Miocene-Pliocene
Trans-Mexican Volcanic Belt (Morales-Gámez and
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Samples were taken from tailings belonging to two mining
localities: Tlalpuhajua and El Oro, Michoacán and Estado
de Mexico states, respectively.
Tlalpujahua
At the Tlalpujahua District thickness of tailings varies from
2 up to 48 m (Fig. 3a). According to Martı́nez-Medina
(2009) textures are diverse, but using soil texture triangle
recognizable horizons are classified as silty loam, sandy
loam, loam sand, silty clay loam, silt, silty clay, medium
loam and sand.
El Oro
Thickness of tailings at El Oro District varies from 1 up to
20 m (Fig. 3b). Textures of the tails correspond to loamy
sand, silt, silty loam, clay loam and silty clay loam. In both
cases, the textures are different and there is no predominance of any, except in the profile of El Carmen (Tlalpujahua), where certain homogeneity is observed,
predominantly silty loam, because the deposit is the result
of the overflow of the dam tailings Los Cedros in 1937.
At both mining localities, samples of 1.5–2 kg in
weight were taken within each profile every 20 cm,
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Fig. 2 Simplified geological
map of TOMD. Modified from
‘El Oro de Hidalgo E14-A16’
chart of ‘Servicio Geológico
Mexicano 2000’
Fig. 3 Current view of Cedros tailings dam at Tlalpujahua (a) and Tiro México at El Oro (b)
packed into plastic bags and identified sequentially
accordingly to the corresponding profile (S) and horizon
(H). Particular attention of sampling was taken when
clear evidence of different horizons was evident. Some
isolated samples, when profile excavation was not
possible, were also taken. In total, 12 profiles were
sampled (Fig. 4); eight from Tlalpujahua and four from
El Oro, yielding 57 samples. Samples were dried by
placing them in an oven at a temperature \40 °C for a
period of 12 h, and were then homogenized by
quartering. Finally, they were stored in hermetic
cylindrical PVC containers.
Methodology
Background
Based on the results of a geochemical and mineralogical
study on the variations within Au-tailings from
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Fig. 4 Location of sampled
sites
XRF methodology
The procedure for pressed-pellet sample-preparation and
XRF analysis are widely described elsewhere (e.g. Lozano
and Bernal 2005). Chemical composition of samples was
determined by X-ray fluorescence using a Xenemetrix
energy dispersion spectrometer (EDXRF X-Calibur, with
Rh tube and a Beryllium detector) at Laboratorio Universitario de Geofı́sica Ambiental (LUGA) facilities.
Fig. 5 SiO2 vs Fe2O3tot plot from the mining district Tlalpujahua-El
Oro
Tlalpujahua-El Oro mining district, Corona et al. (in
preparation) noted certain linear variation between some
mayor element (ME) oxides (CaO, MgO, Al2O3, Fetot)
when plotted against the corresponding SiO2 and pH values. Worth of noting for the aim of the present study is the
inverse linear relationship between SiO2 (the oxide normally used in geochemical studies as an evolution parameter, depending on the mineral phases that crystallize) and
Fetot (Fig. 5). Based on this observation, it seems natural to
follow a symmetrical approach to that employed in geochemical analysis but using the Fe concentration (or
alternatively magnetic susceptibility, which is the key
parameter used as a proxy in magnetic studies) as the basis
for an alternatively magnetic methodology for the study of
PTEs, see below.
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Magnetic methodology
Magnetic susceptibility is directly proportional to the
quantity and grain size of the ferromagnetic or ferrimagnetic materials in a sample (Verosub and Roberts 1995).
Therefore, among other information, magnetic susceptibility measurements provide a straightforward and rapid
estimation of the iron content (Fe concentration) in a
sample. Powdered samples were packed into standard
10 cc cubic plastic containers for the magnetic analysis.
These specific bulk magnetic susceptibility (k) and percentage frequency-dependent susceptibility (%XFD) measurements were carried out using a Bartington MS2
susceptibility meter at LUGA facilities. Alternatively, the
identification of the magnetic carriers within the samples
was accomplished by means of continuous low-field hightemperature susceptibility (k–T) curves or saturation-magnetization curves (thermomagnetic curves) using standard
techniques at LUGA.
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Physical–chemical analysis
Electric conductivity and pH measurements were done at
the chemistry lab of the ENES facilities using a multiparametric kit HI 2020.
Results
Most samples present null and/or very low frequency
dependence of k (%XFD % 0), except those situated at the
very upper part of the profiles (10 % B %XFD B 15 %).
This fact reflects a considerable amount of superparamagnetic particles (SP) within the particulate matter (PM)
\0.03 lm. In most of the cases, magnetite or Ti-poor
titanomagnetite seem to be the main magnetic minerals
within the samples, with variable proportions of other
weaker phases (Fig. 6).
Magnetic susceptibility values of tailing samples were
plotted against their corresponding XRF-determined Fe
concentrations (FeXRF) values. The results of such correlation are presented in Fig. 7. Note the tight correspondence between k and Fe concentrations variations. This
correspondence seems to hold also for pH variations
(Fig. 8). It is also worth noting the predominantly alkaline
character of most of the tailings (7.5 \ pH \ 8.5), associated to very low conductivity values (EC \80 lS/cm),
which suggests an active leaching processes within the
tailings.
Following this approach, the plots of different trace
elements (TE) present in the tailing samples make evident
the correlation between these elements and the iron content
(Fe concentration) (Fig. 9). Figure 10 shows the individual
regression that best represents the correlation between
some TE concentrations with the corresponding FeXRF
within the samples.
In order to verify the above presented correlations, TE
concentrations of tailing samples were plotted against
Fig. 7 k values of tailing samples vs their corresponding XRFdetermined Fe concentrations (FeXRF). Tight correspondence between
k and Fe concentrations variations is observed
corresponding volume susceptibility j. Figure 11 shows
the obtained correlations.
Discussion and concluding remarks
In a study carried out in lake sediments of lake Nechranice,
the captive area being typical for intensive industrial and
mining activity from Northern Bohemia, Petrovsky et al.
(1998) found no positive correlation with magnetic susceptibility of toxic elements present in the samples, except
for Mn; arguing that the practically random observation of
magnetic susceptibility data could be caused by complex
effects of various pollution sources.
On the contrary, Matasova et al. (2005) found an inverse
correlation between Pb and Zn content in the upper ground
layer and magnetic susceptibility in an environmental study
of areas polluted with wastes of the mining industry in
Western Siberia. The authors concluded that the mechanisms responsible for the relationships between magnetic
characteristics of the deposit and the degree and characteristic of its pollution should be quite different from those
in industrial and urban areas.
Fig. 6 Representative
thermomagnetic curves. Both
curves show similar single
ferrimagnetic phases (Ti-poor
titanomagnetite). Curie
temperatures (Tc) of the
ferrimagnetic phases are quite
similar
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Fig. 8 pH vs k within the
tailing samples. A close
correspondence variation is also
observed. Abbreviations on the
horizontal axis are as follows:
S stands for profile while H for
horizon, so that S5H1
corresponds to sample taken
from horizon 1 at profile 5
Fig. 9 Overview of trends followed by different trace elements (TE)
with the iron content (Fe concentration)
Sarris et al. (2009) also confirm that magnetic susceptibility measurements provide the basis for an environmental study in polluted areas with the results they
obtained in an environmental study for pollution in the area
of Megalopolis power plant (Peloponnesos, Greece) where
a very high correlation among magnetic properties; specially between v and Fe was observed.
Likewise the former study, some other recent investigation (e.g. Zhang et al. 2012; Pérez et al. 2014) relates the
enhancement of magnetic susceptibility values with
increased concentration of PTEs based on the high positive
correlation coefficients between these elements and magnetic susceptibility. It is worth noting, however, that the
outcomes and conclusions of these studies are the result of
investigations carried out mainly on surface soils collected
in the vicinity of the tailings and on farmland soil irrigated
with polluted river water in the vicinity of a steel plant,
respectively.
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As properly pointed out by Matasova et al. (2005),
mining wastes seems to belong to a special class of objects
that has not been sufficiently investigated by magnetic
methods, in which an inverse correlation between PTE and
magnetic susceptibility exists.
Such an inverse correlation could be explained in terms
of the combined results of the active leaching processes
and significant differences in atomic weight between Fe
(*55.8) and some PTEs (e.g. As: *74.9; Pb: *207.2).
Samples at the bottom show low (high) Fe(Pb) concentrations. This relationship varies inversely through the
profile so that at the upper part of the tailings higher Fe
concentrations and lower Pb concentrations are observed
(Fig. 12). In the case of elements with similar atomic
weights to that of Fe (Cr: *52.0; V *51.0), direct linear
correlations between them are observed (Fig. 13).
On the other hand, recent environmental investigations
include a series of rock-magnetic measurements (e.g.
NRM, IRM, SIRM ARM, etc.), and the calculation of
different ratios (e.g. S, XLF/SIRM, FD/ARM, etc.) as
indicators of pollution in addition to magnetic susceptibility determinations. Their use is widely employed and
represents a comprehensive way to fully characterize the
magnetic mineralogy. However, their inclusion in any
environmental study protocol would make magnetic
investigations lose some of their distinctive characteristics
which make them nowadays an alternative to traditional
techniques as a proxy for heavy metal pollution investigations; namely, speediness, easiness and economy.
Furthermore, pH measurements seem to be also an
indirect and complementary sign of variation in Fe concentration and, consequently, of potentially polluted areas.
Among the analyzed elements, Pb and As versus j plots
show the highest correlation coefficients. Magnetic susceptibility, along with k–T curves, can be used as a preliminary fast and inexpensive method in the evaluation of
PTE content in mining wastes.
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Fig. 10 Trends followed by different trace elements (TE) plotted against SiO2 content (left part) and against the iron content (Fe concentration,
right part). Note the higher R2 value for plots on the right side, compared to the corresponding value for plots on the left part
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Fig. 11 a, b Trends followed by different trace elements (TE) with magnetic susceptibility (k)
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Fig. 12 Pb vs v plots along a single profile. Samples at the bottom of the profile show low v values that gradually increase, up to higher values at
the top of the profile. The situation for Pb is the opposite; gradually decreasing values from bottom to top of the profile
Fig. 13 Cr and V (atomic weights close to that of Fe) vs Fe concentration plots. Note the direct linear correlations with Fe followed by these
elements
A detailed and quantitative identification of polluted
areas should be based on a comprehensive study, focused
on those areas highlighted by the magnetic results as the
most probable contaminated areas.
Acknowledgments The authors are grateful to Doris A. Dı́az and
Julio C. Gómez, undergraduate students who actively participated in
this project. Neftali Razo is acknowledged for the supervision of
physical–chemical analysis. Gabriela Solis-Pichardo is greatly
acknowledged for her careful review of the manuscript for an
appropriate grammatical style. This study was supported by UNAMPAPIIT project IA102413.
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