The former serpentinite quarry of Penas Albas (Moeche, Galicia, NW Spain)
left behind a large amount of waste material scattered over the surrounding
area, as well as tailing areas. In this area several soils were studied
together with the vegetation growing spontaneously over them with the aim of
identifying the bioavailability of heavy metals. The potential of spontaneous
vegetation for phytoremediation and/or phytostabilization was evaluated. The
pH of the soils ranges from neutral to basic, with very low organic matter
and nitrogen contents. There are imbalances between exchangeable cations like
potassium (K) and calcium (Ca), mainly due to high magnesium (Mg) content
that can strongly limit plant production. Moreover, in all of the studied
soils there are high levels of cobalt (Co), chromium (Cr) and nickel (Ni)
(
Environmental pollution is a global threat of increasing severity due to urban growth, industrialization and changing lifestyles (Liu et al., 2014). According to the “EC Guidance on Undertaking Non-Energy Extractive Activities in Accordance with Natura 2000 Requirements” and the COMG (Cámara Oficial Mineira de Galicia) it is possible to make extractive activities compatible with preservation of the natural environment (COMG, 2013). Land degradation is taking place in the world due to soil erosion, deforestation (Biro et al., 2013; de Souza et al., 2013; Mandal and Sharda, 2013; Milder et al., 2013; Zhao et al., 2013) and soil pollution (Fernández Calviño et al., 2013; Vacca et al., 2012; Yang et al, 2012). Serpentinite soils are stressful environment for plants and also for other living organisms, with low calcium to magnesium ratio, deficiencies of essential macronutrients, high concentrations of heavy metals and low water-holding capacity (Doubková et al., 2012).
Approximately 5 % of Galicia (Spain) is covered by serpentinitic areas; these sites were formerly quarries from which materials for roads, ballast for railway, and ornamental rock were extracted (Pereira et al., 2007). The tailings left behind are often a source of contamination. The soils formed on these tailings (Spolic Technosols; FAO, 2006) must be rehabilitated, as they provide an unsuitable environment for plant growth. They are susceptible to weathering and can cause environmental degradation mainly due to their high content of heavy metals and low organic matter and nutrient content (Asensio et al., 2013).
Spolic Technosols are very young soils that form over unstable materials with low cohesion and physical, chemical and biological deficiencies. These facts are due to their low nutrient and organic matter content, and a high content of heavy metals, which limits the development of bacteria, plants and animals (Deng et al., 2006; Ali et al., 2013).
The lack of nutrients and anomalous physicochemical properties means that the establishment of plant cover is strongly limited in these areas, favouring the accelerated weathering of the soil (Mendez and Maier, 2008). In addition, the limited plant cover contributes to the migration of heavy metals that contaminate surface and underground waters (Bidar et al., 2009).
In the soils from these types of tailings, the levels of copper (Cu), cobalt (Co), chromium (Cr) and nickel (Ni) are usually high (Brooks, 1987; Brooks et al., 1992; Gambi, 1992; Gough et al., 1989; Oze et al., 2004a, b; Rabenhorst et al., 1982; Schwertmann and Latham, 1986), and there is also a deficiency of essential nutrients for plants, such as nitrogen (N), phosphorus (P) and potassium (K) (Turitzin, 1991; Proctor and Woodell, 1975; Walker, 1954). Therefore, the recovery of serpentinite quarry soils must not only consist of eliminating or immobilizing the contaminants, but also of improving the quality and fertility of the soils.
The total heavy metal concentration of soils includes all of the chemical forms that are in there. Therefore this total content does not provide reliable information on the mobility, availability and toxicity of the metals (Adamo et al., 2002; Pueyo et al., 2004).
This means that it is essential to know the available content of heavy
metals in soils, the one that can interact with an organism and become
incorporated into its structure. This content depends on a large number of
factors, which include the properties of the contaminating element (ionic
radii, charge
Physicochemical and biological methods, such as precipitation–flocculation coupled with pre/post-oxidation, reduction and concentration, have all been studied (Agrawal et al., 2006) in order to decontaminate soils with a high content of heavy metals and to preserve the environment; they are also often employed to control environmental pollution. These techniques, known as “removal–disposal”, have numerous drawbacks, such as their high cost, low efficiency, lengthy and complex treatments for a wide variety of metals, and the formation of large amounts of toxic sub-products (Adki et al., 2013). Consequently, processes based on “recovery–reuse” are now being increasingly projected and used (Agrawal et al., 2006). Phytoremediation could avoid some of the problems of the aforementioned treatments, as it is a harmless procedure that respects the environment (Adki et al., 2013; Ali et al., 2013; Paz-Ferreiro et al., 2014).
Therefore, it is of great interest to study and analyse the plants that grow spontaneously in these zones. Their adaptation to the high concentrations of certain metals present in these soils, together with other limiting factors for plant growth, may provide an indication of the procedure to apply in the restoration process.
Hyperaccumulator plants are able to grow in these soils, as they have an extraordinary ability to absorb metals; but their efficiency may be limited due to the low bioavailability of the metals in the soils (Knight et al., 1997; Ali et al., 2013). These plants have unique characteristics, such as the ability to absorb and translocate metals from their roots to their shoot, and a high tolerance. Hyperaccumulators normally have little biomass, because they need a great deal of energy for the mechanisms required to adapt to the high concentrations of metals in their tissues (Garbisu and Alkorta, 2001).
The ideal plant for phytoextraction should be capable of growing in soils with large amounts of metals. It should also have a large radicular system and high levels of biomass production based on optimum growth and development, and be able to accumulate high concentrations of metals in its shoot, store several different metals at the same time and be resistant to pests and diseases (Garbisu and Alkorta, 2001).
Phytoextraction reduces the metal content of the bioavailable fraction of soils, and so this technique is used to reduce the damage caused to the environment (Martin and Ruby, 2004; Ali et al., 2013). When phytoextraction is not possible, phytostabilization should be carried out. This consists of fixing the metals in the soil, stabilizing contaminated soils and reducing the flow of contaminants into the environment. Plant cover also protects against weathering, thus reducing the risk of water infiltration and metals reaching aquifers. In the phytostabilization process, plants do not accumulate metals in their shoots, limiting the risk in terms of food safety (Garbisu and Alkorta, 2001; Ali et al., 2013).
In light of these issues, the aim of this study is: (a) to verify which is the ideal extractant to determine the phytoavailability of the heavy metals contained in soils from a former serpentine mine and (b) to evaluate the phytoremediation/phytostabilization capacity of the spontaneous vegetation growing in these soils.
The study area is located in the Penas Albas serpentinite quarry
(43
This serpentinite quarry (formed by the metamorphism of ultrabasic rocks) operated between the 1960s and mid-1990s. It left behind a large amount of waste material scattered over the surrounding area, as well as tailing areas.
Profile description.
The quarry produced around 50 000 Mg year
Four zones were selected (Fig. 1): three in different quarry spoils (S1, S2 and S3) and one (S4) in the cut zone (natural soils, whose parent material is the living rock: serpentinite). The control soil (CS) was sampled outside the quarry, in an area which has been reforested and treated with fertilizer and animal manure (Fig. 1, Table 1).
In each selected area, three sub-areas were selected with different degrees
of plant cover and diversity, as well as different degrees of slope
(Table 1).
In each of the sub-areas, three surface soil (20 cm, and less than 1 m distance among them) samples were collected using an Eijkelkamp sampler and then stored in polyethylene bags. The soil samples from each sub-area were pooled, air dried, sieved (2 mm), and homogenized in a Fritsch Laborette rotary sample divider, thus obtaining a composite sample of each sub-area. Each one of these composite samples was divided into three sub-samples to perform different analyses.
The soil profiles were described according to the FAO (2006) guidelines and the descriptions are shown in Table 1. The soil colours were determined using revised standard soil colour charts (Munsell Soil Color Charts, 2000).
In each zone, several specimens of
Three sub-samples per soil and plant were finally used for all of the analytical measurements, meaning that all of the analyses were performed in triplicate.
Soil pH, Kjeldahl-N, and organic C (OC) were determined, respectively, with a
pH electrode in 2 : 1 water / soil extracts, according to Bremner and
Mulvaney (1982) and following the Walkley and Black (1934) procedure. The
iron (Fe), manganese (Mn) and aluminium (Al) oxide contents were determined
using the dithionite–citrate method (Sherdrick and McKeague, 1975; Soil
Conservation Service US, 1972). The concentration in the extract was
determined by ICP-OES in a Perkin Elmer Optima 4300 DV apparatus. The
effective cation exchange capacity (ECEC) and exchangeable cation content
were determined according to Hendershot and Duquette (1986). Al, Ca, K, Mg
and Na were extracted with 0.1 M BaCl
Study area.
Particle size distribution was determined after oxidizing the organic matter
with H
The total metal content was analysed by the fusion method with
Li
In order to determine the bioavailable Co, Cr and Ni content in soils, five
extractants were selected – specifically, the most widely used by numerous
authors. In accordance with Houba et al. (2000), soil samples were extracted
with 0.01 M CaCl
The selected plants (shoot and root) were also analysed for total Co, Cr and
Ni contents after being extracted with H
Some physicochemical characteristics of the soils (mean values and standard deviation).
ul: undetectable level (detection limit
0.1
The extraction efficiency (EF) of each of the extractants accounts for the
amount of metal released from the soil with each extractant compared to the
total in the soil. It was estimated by the proportion of the total content
extracted by each one, as given by
It is a useful parameter to better understand the ability of the extractants used to release the metals studied. With EF data it is possible to compare the proportion of the metal released as it is related to the total content.
The translocation factor (TF) was estimated as the ratio between the trace
metal content (mg kg
The ratio of metal concentration in the plant to soil was used to determine
the bioconcentration factor (BF):
The data obtained in the analytical determinations were analysed with the
statistical program IBM-SPSS Statistics 19 (SPSS, Inc., Chicago, IL). The
results obtained in all the determinations were the average of the
standard deviation of three analyses and were expressed on a dry material
basis. One-factor ANOVA was carried out, together with homogeneity of
variance tests for the variables found. In the case of homogeneity of variance,
the minimum significant distance test among soil properties was carried out
as a post-hoc test (
The pH
The soil samples with the lowest OC contents
(S3
The oxide contents are low in all of the soils except for CS (Table 2). The
highest levels are of iron oxides. The lack of Mn and Al oxides, especially
in S3 and S4, is directly related to the parent material, where the mineral
chrysotile is in high proportion and lacks Fe, Mn and Al. In the rest of the
soils, serpentine
(Mg,Al,Fe,Mn,Ni,Zn)
Total content of metals (
For each element, values followed by different letters differ
significantly with
The effective cation exchange capacity is high in S2 and SC (Table 2) and
low in the rest of the soils. All of the soils are saturated in bases and
Ca
The levels of Co, Cr and Ni are high compared to the contents in soils developed over other materials in the region (Macías et al., 1993). Ni and Cr are potentially toxic elements and the content in the soils is very high (Table 3). The levels of Co are also high but in this case there are few toxicity data for higher plants (Li et al., 2009). Studies have been carried out into how Co toxicity affects soil microbes and invertebrates (Chatterjee and Chatterjee, 2000; Lock et al., 2006) and they have revealed that Co is relatively toxic to plants when given in high doses, but there is still little information regarding the toxicity of Co to higher plants.
Mean values and standard deviation of metal extracted from soils,
and content in plants (
In each row, for metal concentration in the extracts, values
followed by the different capital letter differ significantly (
Extraction efficiency. In each soil, bars with different letters
indicate significantly different EF values (
Chromium is the most abundant heavy metal in all the studied soils, followed by Ni and
Co, except in S1 where the most abundant is Ni. S2 has the highest amount of
all three metals. The total Co values are between 147 mg kg
The soil extractions were carried out using different reagents. The results (Table 4) show they pose different extraction capacities for each of the three metals studied.
In all cases the reagent that extracts the most Co, Ni and Cr is 0.01 M
CaCl
BDW is the reagent that extracts the least amount of Co, Cr and Ni in most of the cases – the extraction efficiency is always less than 0.07 % (Fig. 2).
Soil 1 (S1) has the highest amount of available Co when comparing the results obtained with all the reagents (except S2 when extracted with DTPA, Table 4). The control soil (CS) is the one with the least amount of available Co (Table 4).
The highest efficiency with CaCl
The amount of Cr extracted in all cases is low (Table 4) and always less than
1 % of the total content (Fig. 2), therefore there is no evidence of
available Cr and it is probably in strongly retained forms. In the case of
Cr, CaCl
According to CaCl
In general, the lowest extraction efficiency for all of the metals in the study was detected in the soils with the highest pH (S1, S3 and S4), and the more basic the soil, the stronger the retention of the metal cations.
In general, the sequences of greater to lesser extraction capacity differ
depending on the metal. In the case of Ni the sequence is different for different
soils and it can be related to the organic matter content of the soils:
Although a kind of trend was found in the CaCl
The content in both the shoot and roots of
Pearson's correlation between extracted Co, Cr and Ni and its content in plants.
Translocation and bioconcentration factors (mean values and standard deviation).
In each column (for TF) values followed by different letters
differ significantly (
Both species accumulate more Ni, Cr and Co in the roots than in the shoot,
except in S2, where
Li et al. (2009) indicated that plants can accumulate small amounts of Co,
and that their absorption and distribution depends on the species being
controlled by different mechanisms. The absorption of Co
In turn, soil properties also influence heavy metal availability for plants (Li et al., 2009). There is very little useful information available to quantify the effect of soil properties on the toxicity of Co in different plant species. On the whole, the baseline information is insufficient to evaluate the risks posed by Co in order to support the adoption of new guidelines in the European Union (European Commission, 2003). It has been suggested that threshold toxicity levels should be standardized using the exchangeable Ca content of the soil, as this content is correlated with the CECE; this means that it is indicative of the sorption capacity of the soil, which influences the solubility of Co.
Calcium can reduce the toxicity of Co for plants by competing for binding
sites in the root cells and Li et al. (2009) suggested that the Ca
Chromium is accumulated in higher amounts in the roots than in the shoot. These results agree with those of other authors (Adki et al., 2013; Rafati et al., 2011). They indicated that the lowest amounts are always in the vegetative and reproductive organs. They found that Cr distribution is crops is stable and does not depend on soil properties and concentration of the element.
As mentioned above, Ni was absorbed in greater amounts (except in plants from CS, Table 4) and this is probably because of the high pH of the soils from the quarry area. In general, the uptake of Ni usually declines at high soil solution pH values due to the formation of less soluble complexes (Yusuf et al., 2011). These complexes can remain on the soil surfaces in available forms. CS is the soil with the highest content of exchangeable Ca, which affects the decrease of Ni absorption, as demonstrated by Yusuf et al. (2011).
A plant growing in a soil containing heavy metals can be considered a
hyperaccumulator if it concentrates in its shoot without suffering from
toxicity problems, up to 1 % of Mn or Zn, 0.1 % of As, Co, Cr, Cu,
Ni, Pb, Sb, Se and Tl or 0.01 % of Cd (Verbruggen et al., 2009). Also,
according to Mongkhonsin et al. (2011), Reeves and Baker (2000) and Tappero
et al. (2007), considering a plant a hyperaccumulator of Cr is based on three
criteria: that the Cr concentration in the shoot
Thus, none of the plant species we evaluated behave like
hyperaccumulators, as the amounts of metals absorbed by the plants are less
than the criteria indicated. Only the
It is well known that the total content of heavy metals in soils is not suitable for establishing the mobility, availability and therefore the possible toxicity of trace elements (Pueyo et al., 2004).
Some authors, like Roy and McDonald (2013), have suggested that the combined soluble and exchangeable fractions from the Tessier (1979) method are correlated with Cd and Zn uptake in plants more so than the total soil concentration, but did not find any correlation for other elements, such as Pb and Cu. In this paper, in order to determine the extractant that best predicts bioavailability, a correlation analysis was carried out between the amount accumulated by the plant (root or shoot), and the amount extracted with the different reagents used (Table 5).
A positive and highly significant correlation was established (
A positive and highly significant correlation was also found between the
amount of Cr accumulated in both the shoot and roots of
In the case of Ni, the correlation is between the content in the shoot of
It can therefore be deduced from these results that above all, LMWOA is the extractant that best predicts the bioavailability of Cr, Ni and Co for these plants in the soils from the Moeche quarry. This is a rhizosphere-based extraction method that simulates the rhizosphere conditions and takes into account the effect of soil–root interactions as a whole, at least to some extent (Feng et al., 2005).
The highest TF values correspond to
The TF values in
The bioconcentration factor (Table 6) links the available content in the
soils with the amount absorbed by the plants. The bioconcentration factor
(BF) in the studied plants was determined by calculating the ratio of metal
concentration in the plant (
The BF (Table 6) in the shoot of
Moreover, these results indicate that
In addition, the BF for the shoot and root of
The levels of Co, Cr and Ni in the studied soils exceed the intervention
values indicated in different reference guides. Although CaCl
This research was supported by the Xunta de Galicia (project EM2013/018). F. A. Vega and D. Arenas-Lago would like to thank the Ministry of Science and Innovation and the University of Vigo for the Ramón y Cajal and FPI-MICINN grants, respectively. Edited by: A. Cerdà