J Soils Sediments (2014) 14:810–818 DOI 10.1007/s11368-013-0784-1
POTENTIALLY HARMFUL ELEMENTS IN SOIL-PLANT INTERACTIONS
A methodological approach to estimate the geogenic contribution in soils potentially polluted by trace elements. Application to a case study Emilio Galán & Isabel González & Antonio Romero & Patricia Aparicio
Received: 30 May 2013 / Accepted: 20 September 2013 / Published online: 9 October 2013 # Springer-Verlag Berlin Heidelberg 2013
Abstract Purpose The determination of the contribution of background values in a potentially polluted soil is very important in defining the contamination extension, in particular in areas of geological complexity and long-term economic development, where mining and industry have been traditional activities and soils are showing both geogenic and anthropogenic contributions. Some approaches have been proposed for the estimation of the anthropogenic input vs. the background; in this paper we present a more robust approach. Materials and methods The proposed methodological approach includes the following steps. The first step consists of the comparison among the trace element contents in potentially polluted soils (PPS) and the reference and threshold values calculated both for the same geotectonic unit. A second stage is the calculation of the reference and threshold values for the surrounding area (LTV), natural setting, of the PPS with similar lithological characteristics. The final step is based on the analysis of the results by comparison of the PPS with LTV. On the other hand, the definition of a new pollution factor allows to grade the pollution and to classify the pollution importance. Results and discussion The protocol proposed was applied to PPS from a potentially polluted area of SW Spain. The anthropogenic vs. geogenic anomalies and the pollution grade of the three PPS were assessed, which is important to establish the priority to further actions. In addition, this study makes clear that the use of the enrichment factors to estimate the
Responsible editor: Claudio Bini E. Galán (*) : I. González : A. Romero : P. Aparicio Departamento de Cristalografía, Mineralogía y Química Agrícola, Facultad de Química, Universidad de Sevilla, 41012 Sevilla, Spain e-mail:
[email protected]
pollution of soils is not advisable. On the other hand, in this study, new areas close to the PPS were defined as potentially polluted because of the high trace element concentration. Conclusions The methodological approach proposed can be considered as a good indicator for evaluating the geogenic vs. anthropogenic contribution in polluted soils and for classifying the pollution importance in a more robust way than the use of other previous indexes. The proposal methodology could be used also by the administration to detect other PPS in a study area, which a priori were not considered as contaminated. Keywords Evaluation geogenic contribution . Geochemical background . Methodological approach . Soil pollution
1 Introduction The origin of contaminants in a soil is either geogenic if they come from soil parent rocks, volcanic activity, or mineral leaching, or anthropogenic if they come from hazardous industrial waste, agricultural or mining activities, or urban solid waste from households. However, anthropogenic contaminants are the only ones legally considered as true contaminants. Geogenic trace elements depend to a large extent on “geoavailability” which is that portion of the total content of a chemical element or a compound in an earth material that can be liberated to the surficial or near-surface environment (or biosphere) through mechanical, chemical, or biological processes (Plumlee 1994). Geoavailable heavy metals are those released by weathering from the bedrock to the soil, and they constitute, together with others coming from volcanic emissions and mineralization leachates, the geogenic elements. The geogenic heavy metals can accumulate in soils by edaphic processes (edaphogenic background), but in general, they present a low mobility and do not surpass the toxicity thresholds.
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The higher contents of trace metals in soils inherited from the bedrock correspond to Cr, Mn, and Ni, while Co, Cu, Zn, and Pb are present in lower concentration and As, Cd, and Hg display the lowest contents. The task to prove that trace element anomalies in a soil must be considered as a contamination is not easy. Firstly, it is necessary to distinguish between the background of the site for the trace elements under consideration and the anthropogenic contribution to the anomaly, which is the only one considered as pollution from the administrative point of view. But, this contamination can be acceptable up to a level, critical charge, from which an investigation is needed to deduce if pollution exists. The geochemical background of a chemical element represents its concentration in uncontaminated soil. Because it is virtually impossible to determine, it is usually replaced by the geochemical baseline, which is the average of superficial geochemical variations at the time of sampling. Geochemical baseline is obviously influenced by subsoil lithology and the presence of diffuse anthropic contamination (Salminen and Tarvainen 1997; Baize and Sterckeman 2001; Tarvainen and Kallio 2002). It includes the natural content (background) and the diffuse anthropogenic impact. Therefore, the measurements taken exclude areas directly exposed to contamination sources. A more accurate baseline would be the regional geochemical baseline, which is the geochemical background level for each region and element as determined with provision for the specific geological context of the region. Values are usually calculated for the same geotectonic unit, as the mean or median of uncontaminated soils, or by other more robust statistical methods. In a preliminary approach, these values allow the discrimination between natural and anthropogenic contaminants and also the provision of the competent authorities with reference values for possible polluted soils. In a potentially polluted site (PPS), the content of one or some trace elements (toxic elements) must be higher than the regional geochemical baseline (reference value, RV) for the corresponding geotectonic domain in which the site is located, and moreover, at least one should exceed the threshold value of that element in the corresponding geotectonic unit (threshold value, TV). This level can be calculated as the 90th or 95th percentile (p90, p95) of uncontaminated soils, but it can also be determined by the formula: TV ¼ RV þ 2SD where RV is the baseline calculated as the mean of the values of the regional population, and SD is the standard deviation. In Andalusia (Spain), a site is considered as potentially polluted when the concentration of one or several elements surpasses the p90 of the corresponding geologic domain (Galán et al. 2008). The determination of the geogenic contribution in potentially polluted soils (PPS) is very important to define the
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contamination extension. This is of particular importance in areas of geological complexity and long-term economic development, where mining and industry have been traditional activities, and soils show both geogenic and anthropogenic contributions. Some approaches have been proposed for the estimation of the anthropogenic input vs. the background, namely the contamination factor (CF), the enrichment factor (EF), or the geoaccumulation index (Igeo). CF was defined by Hakanson (1980) as the relation between the concentration of an element in the surface layer of a sediment (Xi) and its preindustrial concentration (Bni): CF ¼ Xi=Bni The sum of contamination factors for all elements examined represents the contamination degree of the sediment or soil. EFs were introduced to discriminate between oceanic, terrestrial, and other potential elemental sources in the atmosphere of remote regions (e.g., the offshore, Artic, Antarctic). The application has been extended to many terrestrial media and used to distinguish between natural and anthropogenic sources for elements. They are based on the normalization of a tested element against a reference or conservative one and can be calculated according to the following equation (BuatMenard and Chesselet 1979; Loska et al. 2004; Sutherland 2000): EF ¼ ðC x =C ref ÞS =ðC x =C ref ÞC; where C x is the concentration of element x, and C ref is the concentration of the reference element in soil or sediment (S) and Earth’s crust (C), respectively. Reference or conservative elements are those for which the concentration in the sample medium will exclusively be influenced by crustal sources, i.e., it is not anthropogenically affected, and it is characterized by low occurrence variability. Several elements have been used for this purpose (Al, Zr, Ti, Fe), but the most common reference elements used are Al and Fe (Buat-Menard and Chesselet 1979) in spite of their being more labile than Ti or Zr, for example. Owing to the fact that the average composition of the Earth’s crust is not representative for any given point, in many cases, crustal values have been substituted by the background (Bhuiyan et al. 2010; Loska et al. 1997, 2004; Sterckeman et al. 2006). Values of EF around 1 are indicative of a natural source for a given element, while higher values of EF have been attributed to anthropogenic contamination. Recently, Reimann and de Caritat (2005) have demonstrated that this index cannot be used as rigorous, objective, or sensitive tools to detect or prove anthropogenic impact on the environment. Real-world examples of regional geochemical surveys demonstrate that EFs can be high or low due to a multitude of reasons, of which contamination is but one.
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The geoaccumulation index (Igeo) was originally used for bottom sediments, and it is obtained from the following formula (Müller 1969): Igeo ¼ log2 ðCn=1:5BnÞ where Cn is the measured concentration of the element n in the pelitic sediment fraction ( p90)
Previous reports, historic data, pollution activities, etc.
PHASE 1 Searching information
Field data: checking the occurrence of residues, geology, lithology, etc. Chemical analyses previous data.
Data assessment
and
PHASE 2 Sampling PPS
Natural setting
PHASE 3 Determination of Local Baseline (LRV) and Threshold Level (LTV)
PHASE 4: Analysis of results
PPS
LTV
PPS
LTV
PPS >> LTV
Geogenic anomaly? Geogenic anomaly
Rule out anthropogenic proofs
Anthropogenic anomaly Delimitation of the contamination Assessment of the hazard
Fig. 1 Flow-sheet diagram to distinguish the geogenic vs. anthropogenic contribution of trace elements in potentially polluted soils (PPS)
Phase 2 Sampling the site and the surrounding area (natural setting) Because the anthropogenic contribution of trace elements will be estimated by comparing the concentration in the site with the local baseline, a detailed sampling of both the site and the surrounding soils is necessary. For the sampling of the local setting, potentially contaminated soils should be avoided, and samples must be collected on soils with the same lithological parent rocks represented in the PPS. The number of samples for the local area depends on the PPS extension and on the possibilities to find non-contaminated soil near the PPS formed on the same lithology. One sample in a 100×100-m grid is usually appropriate. This sample can be a compound sample of those collected from each 25×25-m grid for the same area. The data of the surrounding area of the PPS represent the geochemical anomalies of the natural setting where the PPS is located, and they are interesting not only because the local baseline is more representative than the geochemical regional baseline, but also because the whole area including the site could be a geogenic anomaly.
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Phase 3 Determination of the local baseline or reference level (LRV) and threshold level (LTV) for the surrounding area (natural setting) The determination of the local baseline (LRV) can be calculated as the mean or median of the available data. If there are different lithologies, it is possible to calculate a local baseline for all of them in order to increase the knowledge about the origin of the anomalies. But, in general, it is recommended to use a single baseline value to compare with the site. The threshold level (LTV) represents the value over which an anthropogenic input exists. When there are a lot of samples collected, the LTV can be calculated as the percentile 90th (p90) of the data. On the contrary, for a few samples, the LTV can be determined by the following formula: LTV ¼ LRV þ 2SD where LRV is the baseline calculated as the mean and SD is the standard deviation. Phase 4 Analysis of the results The results will be analyzed by comparing the values of the PPS with LTV (see Fig. 1). Case A PPS ≤ LTV When the concentrations in the site are lower than the threshold level established for the natural setting, trace elements of the PPS are geogenic (or the anthropogenic contribution is low) (see Fig. 1). Case B PPS > > LTV When one or several samples collected in the PPS widely surpass the established threshold level for the natural setting, an anthropogenic input occurred, and therefore, the soil is contaminated. In this case, a detailed study of the site must be carried out to delimit the contamination and to assess the hazard according to the metal availability and soil parameters (pH, texture, organic matter, carbonates, Fe oxides, mineralogy). Case C PPS ≈ LTV When the values of the site are similar to the established threshold level for the local area (natural setting), then it is recommended to review the results and study the number of samples surpassing the LTV, the correlation between the highest values and the presence of possible contaminant wastes, industrial activities, etc. In any case, a “confidence level” can be established (e.g., LTV+10% LTV) as the limit to consider that an anthropogenic input occurred.
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In order to assess quantitatively the anthropogenic contribution to the PPS, a pollution factor (PF) can be calculated, adapting the CF of Hakanson (1980). In this PF, Xi is the content of an element in a sample, and Bni is now the local baseline for the element i (i.e., LRVi), resulting in the formula PF ¼ Xi=LRVi Values less than 2 correspond to nonpolluted soils, PF=2–3 corresponds to slightly polluted soil, PF=3–5 indicates soils moderately polluted, and PF >5 corresponds to strongly polluted soils (intervals modified based on Hakanson 1980).
3 A case study The study case is located in the Iberian Pyrite Belt (SW Spain and Portugal), where mining activities developed during the nineteenth and twentieth centuries producing huge quantities of residues and waste rocks which covered surrounding soils. The abandonment of mines during the second half of the twentieth century has additionally had an adverse socioeconomic impact (e.g., a considerable loss of employment) which has been alleviated shifting agriculture as the new ground for social development. Poorly developed soils, where a diffuse contamination can exist, are now intensively cropped with citrus and other fruits. At no time, however, have the contamination of those soils and its potential impact on the quality of the products and population health been considered. Therefore, the competent administration for controlling soil quality selected three PPS to research, and according to the results, to declare them as polluted or not, because previous analytical results showed that trace element contents exceeded the p90 of the South Portuguese Zone, the geotectonic unit where the Iberian Pyritic Belt (IPB) occurs. But, as the sites are located in a region containing high anomalies of heavy metals, and probably a diffuse contamination exists, it is convenient to assess what is the influence of the background (baseline) on the total trace element content in the PPS. 3.1 Potentially polluted sites—previous data The sites studied are located near the village of Nerva (PPS 1), Campillo (PPS 2), and Las Delgadas (PPS 3), close to Riotinto mines (Fig. 2, Tables 1 and 2), in the IPB, South Portuguese Zone (Iberian Massif, Spain) (see López et al. 2008, for a more detailed description) According to the geological framework, the stratigraphic sequence of the IPB consists, from bottom to top, of the following formations (Schermerhörn 1971): (a) Phyllite– Quartzite (PQ) Group, a monotonous detrital sequence with lenses of limestone of Upper Devonian age; (b) Volcanic–
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Fig. 2 Geological setting, PPSs, and sampling
Sedimentary Complex (VSC), a heterogeneous lithological unit comprising mafic, intermediate, and felsic volcanic rocks within a sedimentary framework; and (c) Culm Group, an Upper Carboniferous turbiditic succession of slates and greywackes (see Fig. 2). The VSC is the only host for all the mineralizations. The three PPSs are located on slate. The soils were historically affected by the mine activities, particularly from the mine wastes (acid mine drainage, atmospheric particulate matter, Cu-extractive metallurgy, etc.) (Chopin and Alloway 2007; González et al. 2008; López et al. 2008; FernándezCaliani et al. 2009; González et al 2011; Sánchez de la Campa et al. 2011; Castillo et al. 2013), concentrating very high levels of many toxic elements, namely As, Cd, Cu, Pb, and Zn, in the topsoil (0–20 cm depth) (see Table 2).
Anomalies for Cd, Cu, Pb, and Zn found in soils exceed the p90 calculated for those elements in the South Portuguese Zone (Galán et al. 2008), and consequently, the Environmental Administration considered the sites as potentially polluted and decided to carry out an investigation to test the contamination and the risk assessment. But, in order to evaluate the geogenic contribution to the anomalies, which should be subtracted from the total toxic element contents found in the soils, a research was outlined following the working plan above described, starting from phase 2 (see Fig. 1). 3.2 The study It was not necessary to sample the PPSs again, because values supplied correspond to the average of a reasonable sampling.
J Soils Sediments (2014) 14:810–818 Table 1 Chemical analysis of major elements (in weight percent)
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Fe2O3
MnO
MgO
CaO
Na2O
K2O
TiO2
P2O5
LOI
Potentially polluted soils (PPS) PPS 1 51.59 15.85 7.23 PPS 2 56.24 11.42 5.97 PPS 3 54.4 13.8 6.75 Soils from local area (LAS)
0.085 0.096 0.17
0.96 0.81 2.38
1.98 2.5 4.22
0.43 0.68 2.06
3.12 1.67 1.44
0.896 0.804 1.45
0.86 0.74 0.51
17.38 19.52 11.89
0.043 0.081 0.016 0.05 0.158 0.193 0.103 0.012 0.035 0.059 0.02 0.02 0.1 0.2
0.75 0.74 0.81 0.5 3.38 1.84 0.57 0.48 0.96 1.04 0.92 0.83 1.87 1.78
0.13 0.39 0.14 0.81 1.58 1.87 1 0.22 0.09 0.52 0.07 0.03 1.78 4.43
0.72 0.48 0.39 0.68 0.89 2.47 0.8 0.41 0.41 0.45 0.39 0.39 0.84 2.41
3.09 2.94 3.68 2.44 1.78 1.09 1.34 3.6 3.05 3.41 3.07 2.71 1.91 0.21
1.039 0.89 1.155 0.699 0.797 1.131 0.789 0.939 0.947 1.002 0.87 0.81 0.57 1.63
0.14 0.23 0.18 0.3 0.18 0.27 0.12 0.24 0.12 0.24 0.15 0.11 0.07 0.14
7.895 10.53 11.07 20.52 10.45 10.43 6.397 9.18 9.238 9.966 7.59 7.34 6.76 9.23
Sample
RT 1 RT 2 RT 3 RT 4 RT 5 RT 6 RT 7 RT 8 RT 9 RT 10 RT 11 RT 12 RT 13 RT 14
Table 2 Chemical analysis of trace elements (in milligrams per kilogram) and S (in percent) and comparison to p90 of geotectonic domain and local background
In bold, >p90 SPZ; in italics, >LTV RV SPZ reference value (baseline) of the South Portuguese Zone, p90 SPZ 90th percentile of the South Portuguese Zone, LRV local reference value, LTV local threshold value
Sample
Al2O3
SiO2
59.89 61.14 54.27 51.79 61 58.95 71.61 61.04 58.82 56.74 62.13 63.83 66.4 51.1
19.37 17.47 21.76 13.71 12.23 14.05 11.49 18.85 18.16 19.62 18.15 17 13.8 18.4
As
7 5.26 6.73 7.14 7.31 7.47 5.41 4.86 7.08 7.5 6.49 6.5 5.27 10.12
Cd
Co
Cr
Cu
15 24 28
124 128 173
495 197 153
16 24 11 12 30 26 22 5 14 19 18 17 16 34
126 95 115 78 214 206 125 100 97 89 118 108 93 190
16 34 18 33
85 209 112 201
Ni
Pb
Zn
S
47 35 43
598 168 268
795 349 302
0.1 0.12 0.06
80 212 97 586 78 121 101 170 317 250 100 111 57 27
54 38 39 40 130 52 38 18 44 46 53 55 28 14
67 145 66 108 102 265 89 108 174 116 50 66 197 41
113 186 91 215 106 188 226 79 89 108 119 106 201 95
0.02 0.03 0.07 0.03 0.02 0.03 0.02 0.03 0.03 0.04 0.03 0.02 < 0.01 0.02
31 108 106 396
27 62 42 96
31 117 105 231
72 134 111 216
PPS PPS 1 77 3.2 PPS 2 52 0.5 PPS 3 50 0.5 LAS RT 1 46 0.3 RT 2 77 0.6 RT 3 54 0.3 RT 4 103 0.7 RT 5 32 0.4 RT 6 60 0.3 RT 7 35 1.4 RT 8 88 0.8 RT 9 142 0.3 RT 10 81 0.5 RT 11 39 0.5 RT 12 60 0.4 RT 13 22 0.7 RT 14 19
