Metal(loid)s Transport in Hydrographic Networks of Mining Basins: The Case of the La Carolina Mining District (Southeast Spain)

Abstract

This study analyses the distribution of the total metal(loid)s content accumulated in the sediments of the Grande River, the most important river course that runs through the old mining district of La Carolina (Jaén, Spain), whose waters are collected in an urban supply reservoir. In total, 102 sediments samples were taken along the river, 51 in the live-bed channel and another 51 in the floodplain. The samples analysed have high metal(loid)s content, sometimes much higher than the reference levels established by European and regional legislation for soils, especially Pb, As and Ba, with average values of 5452 mg/kg, 116 mg/kg and 2622 mg/kg, respectively. The statistical analysis of the values obtained allows the distribution of the contents of the different elements along the river to be characterized and the associations and dispersion patterns in the sediments of the metal(loid)s coming from the environmental liabilities of the numerous dumpsites and tailings dams generated by mining activity to be defined. In both cases, the high metal(loid)s content identified as well as the resulting values of various environmental indices (the enrichment factor, contamination factor, geoaccumulation index, potential ecological risk index and pollution load index), confirmed that the sediment samples were moderately to highly contaminated over extensive areas of the basin studied, with the greatest intensity and extent in the floodplain sediments.

1. Introduction

At the end of the last century, the mineral reserves of many deposits were depleted, causing a metal price crisis that led to the closure of many mining operations worldwide. These circumstances occurred in a context where the environmental protection laws of many countries were poorly developed or non-existent, so the necessary remediation measures were not adopted to mitigate environmental damage after abandonment.

Metallic mineral mining and its associated pyrometallurgical practices are one of the main causes of heavy metal contamination of soil and water resources worldwide [1,2], affecting up to several kilometres from the pollution source [3]. The main transport agent is water, both by infiltration and erosion in tailings deposits and by drainage of mining holes [4]. This has been demonstrated by the Environment Agency of England and Wales in the rivers that flow through old mining districts in the United Kingdom, where after more than 4000 years, the rivers have been contaminated by lead, zinc and copper and many other metals and metalloids, including iron, tin, arsenic and silver, from dumpsites and tailings dams that have contributed solid contaminants to live-bed channels and floodplains of the rivers for decades after their closure [2,4,5,6]. This has been equally evident in other mining districts of the world [7,8,9,10,11,12].

The effect is manifested with greater intensity in the fine fraction of the sediment, composed of clay and silt with particle sizes below 63 µm [13], generally by the metalloids associated with the minerals that had been mined. To determine this impact, the measured contents are compared with the geochemical background values and with the maximum allowable levels established for the regulations of the region and/or country using statistical methods and contamination indices [8,9,10,11].

In recent decades, scientists, ecologists, politicians and society in general have demonstrated greater awareness regarding the existing problems related to the extensive contamination of soils and the corresponding environmental consequences [14]. Therefore, the different environmental agencies have taken an interest in evaluating, informing and acting on these affected areas through the development of laws and projects with the aim of protecting both the environment and the health of living beings [4,5,15]. The concern is greater when the land is used for agriculture because of the risk of the transfer of metal contamination to humans through food consumption, affecting their health, especially that of the young [7,16,17].

The study area is located in the old metallogenic district of Linares-La Carolina (Southern Spain), which is characterized by the presence of vein deposits of lead and copper sulphides. This district, abandoned today, was the object of intense exploitation through underground mining from pre-Roman times, and was one of the most important lead producers the world in for a long time [18,19]. As a result of this intense activity, very large volumes of waste were generated from the extraction, concentration and smelting activities, sometimes with high ore grades due to the technical limitations of these processes [20]. Given the orography of the region, these wastes accumulate on the margins of the river channels that run through the sector, whose waters flow into the Rumblar reservoir, destined for human consumption (Figure 1).

This study is based on sampling performed in the sediments of the main river of the fluvial network of the mining district of La Carolina, specifically in the Grande River (Figure 1a,b). For this, a geochemical study was conducted in two sedimentary environments, a live-bed channel and a floodplain [21,22]. Through statistical techniques and environmental factors the distribution of the metal(loid)s contents was qualitatively and quantitatively evaluated from the different pollution sources derived from the mining activities. In addition, the distribution of Pb, As and pollution load index (PLI) has been modeled along the course of the affected rivers in this mining basin using the geostatistical kriging tool, giving information on the areas of greatest impact on their sediments. To determine the degree of contamination of this mining district, the generic reference levels established by the regional and Dutch regulations for each trace element according to soil use were compared. Finally, groups and associations of elements were defined according to their natural or anthropogenic origin, estimating the extent of the condition [15,23,24,25].

2. Materials and Methods

2.1. Study Area

The study area is located on the southeast slope of Sierra Morena within the Hesperic massif (southeastern Spain) in the old mining district of La Carolina. The area corresponds to the hydrographic basin of the Grande River and its two main tributaries, Campana and Renegadero (Figure 1a,b), which, with an approximate area of 100 km², collect the waters of the mining district until discharging them to the Rumblar supply and irrigation reservoir.

The climate of the region is continental Mediterranean, with cold winters and warm summers, so the flows that run throughout the year are very reduced and even disappear during the summer. The average annual precipitation is 613 mm, and the average annual temperature is 15.8 °C [26].

The water in the Grande River carries high concentrations of metal(loid)s, especially in low water periods and during the first autumn rainfall, so that it exceeds the maximum concentration limits for Cd, Pb and Zn established by environmental quality regulations for surface waters. When considering La Campana River, As is also added to these three elements. On average, discharges from mine adits located in the headwater catchment area account for the entry into surface waters of more than 20 tons of Fe, several tons of Mn, and hundreds of kilograms of As per year, which are transported downstream to the Rumblar reservoir [27]. During the wet season, especially during periods of flooding, there is a dilution of mining spills, so the stream water entering the reservoir presents good chemical quality and low mineralization. Despite this seasonal dilution effect, contents in As, Cu and Pb have been detected in the waters at the tail-end of the reservoir that exceed the maximum admissible limits for human consumption.

Geologically, two large groups stand out at the regional level: a Paleozoic basement and a posthercynian sedimentary cover (Figure 1b). The Paleozoic basement is made up of metamorphic rocks, basically phyllites with quartzite intercalations, that were intensely folded during the Hercynian orogeny and subsequently affected by a granitic intrusion. The intense folding and fracturing tectonics that affected the Paleozoic set resulted in a wide network of fractures, many of which were later mineralized by a hydrothermal fluid enriched in metallic sulphides, consisting mainly of galena, sphalerite, chalcopyrite and pyrite, with quartz, ankerite and calcite as accompanying minerals. The orientation of these veins, which have a subvertical disposition, is N 70°–110° E y N 30° E, highlighting those of “Los Guindos”, “Ojo Vecino” and “El Sinapismo”, among others [28]. Discordantly on the Palaeozoic basement and fossilizing these mineralizations, the posthercynian cover appears, which is subhorizontally arranged. The cover is made up of Triassic materials (red shales and conglomerates), Miocene (marls with levels of sandstones, silts and/or breccia at the base) and quaternaries (silts, sands and gravels associated with the filling of the channels) [18,19,29].

In this mining district, extraction was achieved by underground mining using the method of shrinkage stoping, for which it was necessary to excavate wells and galleries that generated a large amount of waste that accumulated in the vicinity. Everything obtained was treated through numerous concentration operations with the aim of obtaining a high-grade ore. The concentration processes were carried out by gravimetric techniques and by flotation, wet processing in both cases, generating a brine of treatment water that was poured directly into the channels and solid waste that was accumulated in dumps and in fine tailings ponds (Figure 1b), where the waters separated after the decantation of the solids were also drained into the nearby channels. Finally, the sulphide concentrates obtained were smelted in the metallurgical plants that were installed in the region to obtain metals of industrial interest, generating gaseous, liquid and slag waste [18,20,28].

In this district, up to 32 tailings ponds and dams have been counted (Figure 1b and Figure 2c) with significantly high total metal(loid)s content, especially, Pb, Zn and As [30], with the common assumption that all these wastes were deposited without any prior adaptation of the site for environmental mitigation [10,31]. In addition, the orography of this district, of valleys and hills sometimes with steep slopes and a well-developed hydrographic network, facilitates the mobilization of mining waste with high contents of metals and metalloids towards the drainage network [32].

2.2. Sampling and Analysis

For the study, 51 sampling points were selected along the river (Figure 1a,b) as follows: in the main channel of the Grande River (samples G1 to G25), in its tributary the Renegadero River (samples R1 to R17) and in the Campana River, a tributary of the Renegadero River (samples C1 to C9). The sampling was designed after the geological and mining cartographies of the area and previous field work were reviewed. The selection of the sampling sites ensured they were consistently spaced along the channel and that they sampled sedimentation zones, natural traps, meanders, bars, etc., downstream of the old mining operations, dumpsites and tailings ponds.

At all the selected points, two samples were taken, one in the channel bed and the other in the floodplain, to compare the distributions of the contents in both sedimentary environments [10,33].

Each sample consisted of four subsamples collected in the shape of a Greek cross with a spacing of 1 m (Figure 2a,b), taking the first 20 cm of the soil with an open-face “Edelman” auger (Figure 2a), which was subsequently placed in plastic bags in which they were mixed and stored, with an average weight of 1.5–2 kg.

Once in the laboratory, the samples were physically prepared for analysis, which consisted of drying and homogenization, quartering, sieving and grinding. The samples were sieved (PVC sieve and bottom) to separate the <2 mm fraction, classifying the fine fractions by sedimentation according to the UNE 103101:1995 standard.

For the determination of the total metal(loid)s content, the <2 mm fraction was ground in an agate ball mill until a size of less than 50 microns was obtained (Retsch PM 100). Chemical attack was performed on 1 g of the milled sample by total microwave digestion [34], using HNO₃ as reactants with the addition of H₂O₂, which facilitates the complete oxidation of organic matter [35]. The analysis of the solutions obtained was performed by ICP-MS (inductively coupled plasma mass spectrometry) in the laboratories of the Center for Scientific and Technical Instrumentation of the University of Jaén in a mass spectrometer with a plasma torch ionization source and an AGILENT model 7900 quadrupole ion filter. The samples with a Pb concentration exceeding the limit allowed by the analytical method (10,000 mg/kg) were analysed with portable X-ray fluorescence equipment (Niton XLT 792) according method 6200 (US EPA 1998). Three measurements were performed on the sample for 60 s, and the mean value was calculated [36,37].

2.3. Evaluation of the Heavy Metal Content in Sediments

To identify metalloid enrichment in the analysed sediments, values of the naturally occurring geochemical background are required to serve as a reference level. In this study, Clarke values and acid igneous rocks were used [38,39,40] for the calculation of different environmental factors and indices.

The enrichment factor (EF) assesses the impact of anthropogenic sources of heavy metals in the sediment using the following equation [41]:

$$\mathrm{EF}=\frac{{\left({\mathrm{C}}_{\mathrm{M}}/{\mathrm{C}}_{\mathrm{P}}\right)}_{\mathrm{sample}}}{{\left({\mathrm{C}}_{\mathrm{M}}/{\mathrm{C}}_{\mathrm{P}}\right)}_{\mathrm{background}}}$$

(1)

where (C_M/C_P)_sample is the ratio of the heavy metal concentration (C_M) to the phosphorus concentration (C_P) in the sediment sample and (C_M/C_P)_background refers to the background values for each metal in Clarke values and acid igneous rocks. A value of EF close to 1 suggests natural weathering processes, EF > 1.5 indicates human influence and EFs of 1.5–3, 3–5, 5–10 and >10 are considered evidence of minor, moderate, moderately severe, and severe enrichment, respectively [42,43,44].

The geoaccumulation index (I_geo) defines the level of contamination in the sediment by the following relationship [45]:

$${\mathrm{I}}_{\mathrm{geo}}={\mathrm{Log}}_2\left[\frac{{\mathrm{C}}_{\mathrm{n}}}{1.5{\mathrm{B}}_{\mathrm{n}}}\right]$$

(2)

where C_n is the average concentration of the metal in the sediment and B_n represents the average values for trace elements of acid igneous rocks [40]. A factor of 1.5 is introduced to minimize the possible variations in the background data that may be due to lithological variations. Seven levels of I_geo are established: uncontaminated (<0), uncontaminated to moderately contaminated (0–1), moderately contaminated (1–2), moderately to strongly contaminated (2–3), strongly contaminated (>3), strongly to extremely strongly contaminated (3–4) and extremely contaminated (>4) [46].

Another index analysed in this work is the ecological risk potential (E_rⁱ and RI), which estimates the potential ecological risk of each metal (E_rⁱ) and potential ecological risk index (RI) for the set of metals/metalloids in the sediment [47]:

$${\mathrm{E}}_{{\mathrm{r}}^{\mathrm{i}}}={\mathrm{T}}_{{\mathrm{r}}^{\mathrm{i}}}\times \frac{{\mathrm{C}}^{\mathrm{i}}}{{\mathrm{C}}_{{\mathrm{n}}^{\mathrm{i}}}}$$

(3)

$$\mathrm{RI}={\displaystyle \sum }_{\mathrm{i}=1}^{\mathrm{n}}{\mathrm{E}}_{{\mathrm{r}}^{\mathrm{i}}}$$

(4)

where T_rⁱ is the toxic factor of a metal/metalloid for As, Cd, Co, Cr, Cu, Mn, Ni, Pb, V and Zn with a value of 10, 30, 5, 2, 5, 1, 5, 5, 2 and 1, respectively [11,47]. Cⁱ is the average concentration of metal i in the sediment samples, and C_nⁱ is the background value of heavy metal i in acid igneous rocks [40].

The values of E_rⁱ are grouped into the following classes: very high risk (E_rⁱ > 320), high risk (160 ≤ E_rⁱ ≤ 320), considerable risk (80 ≤ E_rⁱ < 160), moderate risk (40 ≤ E_rⁱ < 80), and low risk (E_rⁱ < 40).

RI is defined as the sum of E_rⁱ and is classified as very high ecological risk (RI > 600), considerable ecological risk (300 ≤ RI ≤ 600), moderate ecological risk (150 ≤ RI < 300) and low ecological risk (RI < 150) [11].

Finally, the pollution load index (PLI) and contamination factor (CF) were considered, where the PLI is defined as the root of the multiplication of the metalloid CF [48]:

$${\mathrm{CF}}_{\mathrm{metals}}=\frac{{\mathrm{C}}_{\mathrm{metal}}}{{\mathrm{C}}_{\mathrm{background}}}$$

(5)

$$\mathrm{PLI}={({\mathrm{CF}}_1\times {\mathrm{CF}}_2\times {\mathrm{CF}}_3\times \dots \times {\mathrm{CF}}_{\mathrm{n}})}^{1/\mathrm{n}}$$

(6)

where CF is the relationship between the average concentration (C_metal) and the background values ford each metal (C_background). Four classes define the contamination of a metal: low (CF < 1), moderate (1 ≤ CF < 3), considerable grade (3 ≤ CF < 6) and very high (CF ≥ 6) [49,50]. A PLI value of zero indicates no background concentration, a value of one indicates the presence of only a baseline level of contaminants, and values greater than one indicate a progressive deterioration of the quality of the site [48].

2.4. Statistical Analysis

Univariate and multivariate statistical techniques were used to determine the interrelation and variability of each metal(loid)s to determine the presence of anomalies. The data processing was performed using SPSS 22 software developed by IBM.

The mean, median, range, standard deviation, variance, skewness and kurtosis were calculated, generating the histograms, normality plots and box and whisker plots [51,52].

In multivariate statistics, a principal component analysis is performed with the objective of transforming a set of original variables into a new set of variables, called factors, which are characterized by being correlated with each other. The first factor or component explains the largest variance in the data set, the second factor or component explains the second largest variance in the data set, and so on for the rest of the factors [53]. For its interpretation, the rotation of the components (axes) is used. Varimax rotation is the most commonly used approach in geochemistry, which is adequate when the number of components is small. This technique has been used in different environmental scenarios [21,54,55,56].

Geostatistical analysis through an ordinary kriging of a spherical semivariogram model was used to predict the contents of Pb and As and the PLI along the entire course of the sampled rivers, since this technique provides the best spatial prediction for unsampled locations [57]. The information was processed to develop distribution maps using arcGIS 10.6 software developed by ESRI.

3. Results and Discussion

The different regulatory standards concerning contaminated soils establish generic reference levels (GRL) that indicate possible impacts on humans and/or ecosystems if they are exceeded. The concentrations of 17 metal(loid)s (Ag, As, Ba, Ca, Cd, Co, Cr, Cu, Fe, Mg, Mn, Ni, P, Pb, Sr, V and Zn) in the 102 samples collected in the live-bed channel and in the floodplain (

Table 1. Total concentrations (mg/kg) of selected elements in the sediment samples. Concentrations above the reference values are in bold.

Samples	Ag	As	Ba	Ca	Cd	Co	Cr	Cu	Fe	Mg	Mn	Ni	P	Pb	Sr	V	Zn
Floodplain
G1	4.8	136	502	1453	1.9	18	12	101	24,453	1461	1990	24	488	4035	18	11	293
G2	6.4	84	987	1053	4.1	16	15	60	25,156	1283	2313	22	417	5294	25	17	481
G3	7.3	179	1248	762	1.6	15	11	340	26,640	1049	1062	18	482	6312	35	10	240
G4	8.1	178	2148	1685	5.0	31	16	432	31,229	1620	4492	46	568	7680	29	19	546
G5	7.2	157	1081	890	2.6	20	11	307	25,222	1061	1573	23	474	6558	50	10	329
G6	3.4	85	602	613	1.4	14	12	147	26,791	1477	933	24	461	3152	60	12	276
G7	4.4	98	1242	835	1.7	16	12	166	25,384	1392	1075	22	473	4828	55	12	263
G8	4.5	129	800	1510	4.7	15	15	68	26,592	2494	1093	32	536	4365	18	18	491
G9	9.2	143	6139	3225	5.1	13	13	99	24,682	2625	1038	27	558	13,585	67	16	504
G10	3.3	132	942	1096	3.0	12	11	72	23,880	2122	831	26	498	4674	18	12	501
G11	3.2	103	1036	2484	3.4	14	22	54	32,980	3248	894	31	643	3642	26	23	857
G12	2.6	84	577	1851	3.9	12	16	42	24,977	2879	760	26	565	3894	13	17	619
G13	3.1	126	1345	2690	3.4	15	19	63	31,604	3201	1028	30	644	4226	29	19	836
G14	3.5	153	1680	3093	3.8	15	15	71	31,494	3027	1091	29	621	4646	32	16	838
G15	3.5	138	1209	2893	3.8	15	19	68	32,674	3233	1103	32	664	4674	28	20	821
G16	2.9	94	670	1711	3.8	11	14	53	30,990	2864	880	26	588	4531	14	16	607
G17	3.8	155	1471	2921	4.1	15	15	86	32,516	3056	1129	28	643	5254	30	14	865
G18	2.4	124	916	2010	2.9	14	17	61	32,329	3186	876	31	614	3989	22	18	688
G19	1.9	110	469	1383	2.7	15	20	56	34,025	3100	749	34	624	3226	18	24	597
G20	3.1	157	1455	2240	3.4	14	14	71	31,616	2918	991	27	610	4588	29	14	767
G21	2.8	137	1317	2251	3.4	14	15	69	32,406	2928	1018	29	631	4078	27	16	779
G22	6.8	122	2205	2214	4.7	10	12	51	18,736	2076	714	18	357	8084	27	13	495
G23	4.0	116	1262	1890	4.1	11	14	47	21,335	2291	711	21	424	5547	21	16	538
G24	8.4	160	3321	3193	6.3	12	15	54	25,211	2704	890	23	550	9328	38	15	685
G25	9.4	143	2773	3498	6.2	14	16	60	25,720	2974	1027	25	590	10,270	32	15	668
R1	0.1	10	626	918	0.2	12	21	16	27,860	2751	444	25	408	367	21	18	72
R2	0.1	9	649	545	0.1	10	20	14	28,946	2744	326	22	400	358	16	17	72
R3	5.9	16	8027	2077	5.2	11	16	311	30,981	2437	630	21	493	7674	48	13	475
R4	1.0	18	1513	935	2.1	11	19	21	29,921	2778	668	26	431	1759	27	17	583
R5	1.5	19	4697	970	3.0	10	21	34	33,116	3025	580	25	448	2134	62	18	551
R6	3.6	105	3965	2481	2.9	11	19	55	28,601	2705	582	22	611	4027	54	18	642
R7	4.8	140	2193	1271	1.9	16	17	78	28,330	2011	795	27	488	7697	27	17	445
R8	11.8	192	5537	3768	11.1	20	18	112	37,114	2583	1155	29	719	11,258	87	18	1694
R9	6.2	145	3950	5417	5.9	18	22	76	32,889	3595	1108	32	797	5777	60	22	987
R10	3.8	160	4383	3745	3.1	15	33	76	30,665	3853	843	31	680	4374	68	38	592
R11	7.3	125	4958	3954	7.0	15	17	68	34,018	3489	1192	28	663	7584	48	18	924
R12	4.9	124	5105	4036	4.9	16	22	102	39,019	3744	1033	34	738	5471	74	25	1029
R13	5.8	137	5425	4475	5.2	16	20	222	38,069	3653	1077	33	694	6302	77	23	1010
R14	10.0	137	3865	3723	8.2	16	19	75	33,385	3398	1240	29	750	11871	47	20	985
R15	5.0	116	1717	3364	4.3	18	19	71	35,769	3586	981	33	657	5777	30	23	911
R16	5.9	156	3173	5432	5.3	18	20	76	35,435	3918	1264	33	674	6788	48	23	1003
R17	2.9	114	349	1522	3.0	13	24	60	28,607	2935	711	36	814	3222	20	32	554
C1	2.8	186	1240	3215	4.3	12	15	41	22,977	2693	785	20	532	3254	24	18	687
C2	3.1	105	2907	4713	3.7	12	31	44	23,681	2985	643	32	738	3873	51	21	582
C3	4.5	109	4189	3011	3.6	11	20	48	19,725	2395	689	18	465	4826	56	13	583
C4	9.5	45	11762	2395	12.5	15	19	59	39,207	3195	1167	26	482	15,533	172	18	1794
C5	3.9	120	2610	3678	3.7	12	25	58	24,780	3029	627	27	689	4566	41	17	693
C6	3.4	93	3762	2015	2.7	10	20	35	20,338	2434	590	19	482	3295	53	17	422
C7	2.8	91	2702	2972	3.3	10	24	46	21,273	2693	481	22	757	2925	43	18	596
C8	2.9	95	2891	3022	3.2	10	24	46	20,201	2503	517	21	710	3066	47	17	558
C9	4.2	100	4141	2974	3.9	10	26	43	21,364	2526	544	24	708	3838	60	19	588
Live-bed
G1	3.2	113	432	910	1.2	14	14	109	19,747	1412	1205	20	396	2644	13	15	212
G2	3.8	100	474	601	2.1	12	12	46	21,064	1089	1303	18	358	3598	13	15	342
G3	3.7	180	908	549	1.2	12	11	329	22,189	1114	962	20	378	3007	16	12	270
G4	8.8	180	1149	3132	5.8	32	17	361	28,782	1988	4660	47	585	7391	27	19	593
G5	4.1	197	575	504	1.2	13	12	223	26,245	1198	736	22	462	3599	14	13	309
G6	4.4	126	2244	1022	1.8	19	17	244	31,657	1855	1542	36	518	3579	34	18	329
G7	3.4	132	1138	848	2.5	17	16	200	27,020	1672	1501	33	451	4589	23	18	343
G8	3.4	110	719	1009	2.7	11	18	53	26,541	3065	712	28	538	3909	17	22	354
G9	4.3	100	655	2235	2.9	11	16	35	19,156	2696	702	24	548	5983	21	21	303
G10	2.6	92	233	1393	1.7	11	12	46	21,387	2412	545	25	513	3942	12	13	269
G11	6.7	105	801	2280	4.3	14	19	59	39,565	3076	1124	31	636	6940	21	21	942
G12	4.1	88	499	1777	4.4	13	15	54	29,017	2778	840	27	575	4246	12	18	635
G13	4.4	125	486	2318	3.0	14	16	103	33,253	2892	843	32	723	5083	19	20	695
G14	2.8	104	377	1751	3.4	14	15	50	33,853	2862	933	30	639	3922	12	17	781
G15	2.5	118	866	1872	2.7	12	21	51	32,584	3049	806	30	635	3584	27	25	640
G16	7.6	161	2881	3255	6.7	13	16	61	27,353	2869	1116	25	591	8816	35	18	706
G17	1.7	129	218	1184	2.4	12	17	39	28,185	2606	666	25	579	2378	12	20	522
G18	2.9	106	304	1355	2.7	13	18	50	33,025	2656	740	29	622	3582	13	20	649
G19	2.3	102	346	1499	3.0	14	18	47	35,642	2937	864	33	632	3364	14	19	709
G20	2.6	156	237	1284	2.5	13	20	61	33,697	2767	680	31	614	3490	15	25	608
G21	2.0	92	129	975	1.8	12	16	54	24,534	2490	552	24	551	2285	10	18	463
G22	1.9	67	193	891	2.4	8	10	34	20,390	1935	456	20	419	2531	7	12	409
G23	2.0	77	149	893	2.7	9	11	35	25,326	2032	546	23	471	2785	6	13	465
G24	2.0	65	224	1057	3.2	10	13	27	22,784	2341	705	22	515	2640	9	15	436
G25	2.4	78	324	1158	2.9	9	12	49	24,535	2497	571	23	557	3005	10	14	418
R1	0.1	18	904	434	0.1	11	23	18	37,278	3277	330	27	483	309	18	19	81
R2	0.7	15	1649	522	0.3	10	22	14	31,087	2902	296	26	400	1125	27	19	88
R3	8.2	59	12671	1542	4.3	15	19	81	34,753	2899	692	27	465	10,511	173	17	619
R4	3.2	23	10310	1365	2.6	10	21	23	34,266	3193	615	28	467	5433	146	19	635
R5	0.7	20	1592	630	2.3	10	22	19	35,946	3337	528	28	482	1677	25	18	619
R6	1.3	23	8966	1523	4.4	13	20	20	29,753	2616	1233	28	460	2568	115	20	830
R7	3.3	85	1531	1709	2.4	10	19	49	28,013	2716	417	26	727	3164	26	17	567
R8	4.1	115	3591	5159	5.2	16	28	59	31,304	3690	954	32	989	3607	61	26	912
R9	4.7	85	1446	4053	3.9	14	22	56	33,905	4047	886	32	728	3696	28	24	760
R10	4.1	147	3125	4603	4.6	16	23	85	32,557	4054	1052	32	798	4998	51	25	723
R11	10.9	174	3440	6098	9.0	18	10	83	37,289	3852	1855	28	606	10,606	40	12	1350
R12	3.9	95	1046	2595	7.0	17	20	58	39,933	3268	1516	38	712	4413	22	24	1087
R13	3.6	107	862	3361	5.2	16	22	57	40,213	3645	1022	36	713	4995	22	25	1038
R14	4.6	90	1850	2997	5.0	12	19	43	25,852	3166	823	23	573	5312	26	19	673
R15	4.2	104	1848	3310	5.3	15	21	56	36,510	3522	1061	34	709	4584	33	24	975
R16	3.2	100	537	2492	4.0	17	19	49	31,106	3235	1007	33	645	3423	14	20	865
R17	4.1	118	348	3874	3.3	17	19	60	28,578	3629	946	39	856	5243	23	24	520
C1	6.7	168	5579	1163	2.3	14	14	98	28,353	1898	686	28	481	10,282	66	17	462
C2	3.2	231	1122	1819	5.0	12	13	53	27,583	2288	765	24	532	3916	18	15	805
C3	3.1	119	2491	3822	4.7	13	37	48	18,652	2399	454	30	1111	3634	50	20	642
C4	3.8	110	4669	5346	4.6	9	44	61	19,855	3019	407	32	1251	4631	74	19	688
C5	3.6	148	2767	5043	7.1	13	63	57	22,207	3058	689	39	1575	4784	57	20	888
C6	6.4	197	8727	5604	7.7	9	38	59	22,070	2354	415	21	839	7022	128	15	911
C7	5.4	144	7741	2693	6.8	11	27	58	23,684	2387	545	24	805	4071	105	18	781
C8	4.6	105	10539	2704	5.4	8	36	36	21,741	2145	313	28	526	4211	136	17	582
C9	3.1	93	3735	2754	3.7	8	20	45	17,753	2346	393	19	560	2824	54	15	490

) were analysed. In Table 1, the values that exceed the limit set by the Andalusian regional standard and the Dutch standard are highlighted in bold. Note that in the case of Pb, only sample R1, taken in the live-bed channel, and samples R1 and R2, taken in the floodplain, have contents that are below the norm values.

Table 2. Descriptive statistics of total concentrations: minimum maximum median range standard deviation (all data in mg kg) variance skewness and kurtosis. Enrichment factors referred to crust Clarke values and acid rocks are showed. Generic reference levels (GRL) established by the regional government (Junta de Andalucía 2015) and the Dutch soil standard (Dutch Ministry 2013) are also included. Concentrations above the reference values are in bold.

Element	Min.	Max.	Mean	Median	Range	Std. Deviation	Variance	Skewness	Kurtosis	Crust Clarke Values	Acid Rocks
Ag	0	12	5	4	12	3	7	0.78	0.33	0.10	0.15
As	9	192	116	124	182	44	1.978	−0.92	0.71	5	2
Ba	349	11,762	2622	1717	11,414	2203	4,852,462	1.85	4.92	260	830
Ca	545	5432	2472	2395	4887	1243	1,544,183	0.42	−0.39	36,300	-
Cd	0	12	4	4	12	2	5	1.69	4.92	0.15	0.10
Co	10	31	14	14	21	4	13	2.09	8.31	23	5
Cr (III-VI)	11	33	18	18	22	5	23	0.83	1.09	200	25
Cu	14	432	90	63	418	85	7196	2.62	6.72	70	30
Fe	18,736	39,207	28,724	28,607	20,471	5308	28,173,431	0.03	−0.79	50,000	-
Mg	1049	3918	2704	2778	2869	705	497,429	−0.69	0.15	20,900	-
Mn	326	4492	999	894	4166	611	373,780	4.08	21.61	1000	600
Ni	18	46	27	26	28	5	29	0.74	1.44	80	8
P	357	814	583	590	457	115	13,332	0.03	−0.98	180	700
Pb	358	15,533	5452	4646	15,175	3010	9,061,307	1.36	2.40	16	2
Sr	13	172	42	31	159	28	759	2.66	10.77	300	300
V	10	38	18	17	27	5	25	1.66	4.97	150	40
Zn	72	1794	659	596	1723	318	101,411	1.36	3.94	132	60
Element	Enrichment Factor (crust)	Enrichment Factor (acid rocks)		Generic Reference Levels in Andalucia						Dutch Regulations for Standard Soils Intervention Value
				Industrial		Urban		Others
Ag	94	37		-		-		-		-
As	47	93		40		36		36		76
Ba	20	3.79		10,000		10,000		10,000		625
Ca	0.14	-		-		-		-		-
Cd	54	48		750		75		25		13
Co	1.24	3.39		250		25		24		190
Cr (III-VI)	0.18	0.87		10,000–100		10,000–20		10,000–20		180–78
Cu	2.60	3.60		10,000		3130		595		190
Fe	1.16	-		-		-		-		-
Mg	0.26	-		-		-		-		-
Mn	2.02	2.00		-		-		-		-
Ni	0.68	4.04		10,000		1530		1530		100
P	1	1		-		-		-		-
Pb	689	3272		2750		275		275		530
Sr	0.28	0.17		-		-		-		-
V	0.24	0.54		3650		365		50		-
Zn	10	13		10,000		10,000		10,000		720

shows the main statistical parameters for the metal(loid)s studied in the samples taken in the floodplain as well as the GRL established by the regional government [15] and Dutch regulations [25]. In bold the values that exceed these reference limits are highlighted. The average values obtained for the concentrations of Pb and As stand out clearly exceeding the GRL of Andalusia and the Dutch standards and Ba exceeds the intervention value established in the most restrictive Dutch standard.

Figure 3 shows the variation in the Pb and As contents in the hydrographic basin studied both in the live-bed channel and in the floodplain and compares them with the limits established by the Andalusian and Dutch regulations. In the three rivers Grande Renegadero and Campana practically all the samples collected present Pb and As values above the GRL in the two sedimentary environments although the maximum concentrations of Pb and As are recorded in the vicinity of the old abandoned mining operations and extend downstream in both cases with greater intensity in the floodplain. The Pb concentration peaks greatly vary in both sedimentary environments which indicates its low mobility being more homogeneously distributed in the live-bed channel with an increase towards the tail of the Rumblar reservoir (samples G23 to G25). As presents a lower spatial variability than Pb with a similar response in both sedimentary environments although at a lower intensity in the live-bed channel. Only 14 samples are below the intervention levels for As: the first four samples in the headwaters of the Renegadero River (R1, R2, R3, R4 and R5) in both sedimentary environments and sample R6 in the live-bed channel located upstream of the mining works sample C4 in the floodplain of the Campana River and samples G22 and G24 in the live-bed channel all located far from mining liabilities (Figure 1 and Figure 3). In the case of Ba the intervention value is exceeded in most of the samples analysed especially in the floodplain.

Table 2 shows the maximum and minimum values mean median standard deviation variance kurtosis and asymmetry of the metal(loid)s studied. The concentrations of Pb As and Ba (elements related to the mineral paragenesis of the ore of interest) present different mean and median values. In addition the standard deviations and variances are high together with kurtosis and positive asymmetry due to the presence of extreme values which indicates a high degree of heterogeneity and dispersion along the channel.

Figure 4 shows the histograms box and whisker plots and normality plots for the concentrations of Pb, As and Ba in the samples taken in the live-bed and in the floodplain. For Pb the histograms are similar in the two sedimentary environments skewed to the right by extreme values. Additionally the box and whisker plots are similar in both situations showing numerous extreme values with a lognormal distribution as shown in the Q/Q plots of Figure 4. For As the live-bed histogram is symmetric but not the histogram of the floodplain which presents two families of values. The box and whisker plots are similar in both sedimentary environments with lower extreme values referring to the headwaters of the Renegadero River. The distribution is normal as shown in the Q/Q normality plots except for low values. The histograms of Ba for both environments are asymmetric to the right. The box and whisker plots for Ba show numerous extreme values presenting a lognormal distribution.

A multivariate analysis by principal components with varimax rotation was performed for the sediment samples obtained in the live-bed channel and in the floodplain. The total variance explained by the four components is 80.2% in the live-bed channel and 83.1% in the floodplain. In the live-bed channel (

Table 3. Principal component loadings obtained in principal component analysis of the element concentrations in the live-bed (a) and in the floodplain (b).

(a) Live-Bed					(b) Floodplain
Variable	Component				Variable	Component
	1	2	3	4		1	2	3	4
Mn	0.860	0.233	−0.113	−0.002	Ba	0.919	−0.055	0.143	−0.113
Co	0.855	0.413	−0.023	−0.019	Sr	0.893	−0.047	0.261	−0.164
Cu	0.822	−0.260	−0.125	−0.099	Cd	0.890	0.181	−0.038	0.270
As	0.667	−0.292	0.350	0.054	Pb	0.825	0.218	−0.251	0.273
Fe	0.130	0.866	−0.251	0.096	Zn	0.784	0.200	0.259	0.230
Mg	−0.214	0.837	0.308	0.127	Ag	0.769	0.283	−0.214	0.421
V	−0.037	0.755	0.313	−0.139	Co	0.176	0.928	0.097	0.197
Ni	0.451	0.675	0.327	−0.106	Mn	0.124	0.917	−0.186	0.115
Zn	0.117	0.609	0.426	0.395	Cu	0.108	0.884	−0.111	0.121
P	−0.016	0.186	0.943	−0.022	Ni	−0.049	0.842	0.443	0.112
Cr	−0.200	0.029	0.860	0.161	Fe	0.358	0.527	0.508	−0.147
Ca	0.182	0.280	0.783	0.356	V	−0.042	0.215	0.820	0.037
Cd	0.245	0.277	0.579	0.552	Mg	0.210	−0.038	0.819	0.143
Ba	−0.209	−0.059	0.097	0.875	Cr	−0.052	−0.186	0.786	−0.087
Sr	−0.214	−0.033	0.172	0.842	P	0.068	0.144	0.657	0.596
Pb	0.468	0.140	0.047	0.727	As	0.100	0.374	−0.099	0.845
Ag	0.641	0.070	0.105	0.667	Ca	0.414	−0.030	0.431	0.692
% Var	21.92%	20.25%	19.56%	18.42%	% Var	27.91%	23.05%	19.79%	12.31%

a) the following groupings are identified: component 1 which represents 21.9% of the variance and includes Mn Co Cu and As elements associated with the mineralization of this mining basin; component 2 which represents 20.35% of the variance and is composed of Fe Mg V Ni and Zn (elements naturally related to the soil); component 3 which represents 19.6% of the variance and is associated with P Cr Ca and Cd natural components of rocks and soils; and finally component 4 which represents 18.4% of the variance and groups Ba Sr Pb and Ag which is associated with the mineral paragenesis of the studied environment and therefore with the mining activities performed.

In the case of the floodplain (Table 3b) the following groups were obtained: component 1 (27.9% of the variance) groups Ba Sr Cd Pb Zn and Ag all elements of mineral paragenesis and therefore with anthropogenic influence linked to mining; component 2 (23.1% of the variance) composed of Co Mn Cu Ni and Fe associated with the mineralization of this mining basin; component 3 (19.8% of the variance) composed of V Mg Cr and P elements that are present in the rock matrix; and the fourth component which represents 12.3% of the variance and groups Ca and As. In both sedimentary contexts Pb is associated with Ba Sr and Ag.

Based on the values of the metal(loid)s content of the sediments the environmental factors and indices mentioned in the methods section were calculated. In the case of the EF of the 17 metal(loid)s analysed Zn As Ag Cd Ba and Pb have high values (>10) compared to their Clarke values in the Earth’s crust. The EF of Pb increases when the geochemical background values for acid rocks are used as a reference which indicates that there is a very severe anthropogenic influence (Table 2).

The CF presents very high values for Zn As Ag Cd and Pb with values of 10.3 74.3 25.9 37.4 and 2216.3 respectively. Note the case of Pb which is the main ore of the mining basin with a CF 30 times higher than those of the rest of the metal(loid)s. In addition other elements such as Mn Co Ni Cu and Ba reach significant values with CF values of 1.5, 2.6, 3.5, 2.5 and 2.9 respectively.

The values obtained for the geoaccumulation index (I_geo) show an extremely high level of contamination in the case of As Ag Cd and Pb with values of 5.6, 4.1, 4.6 and 10.5 respectively. The Zn content in the sediments with a value of 2.8 presents a moderate to strong level of contamination. Moderate levels of contamination by Co Ni Cu and Ba are also present with values of 0.8, 1.2, 0.7 and 0.9 respectively for I_geo.

The potential ecological risk (E_rⁱ) values calculated for V, Cr, Mn, Co, Ni, Cu, Zn, As, Cd and Pb are 1, 2, 1, 13, 18, 12, 10, 743, 1123, and 1,1081 respectively highlighting a very high risk for As, Cd and Pb with respect to the rest of the metal(loid)s studied. Considering the set of elements analysed a value of 13,006 is obtained for the RI so there is a very high ecological risk in the study area.

The PLI obtained for all metal(loid)s is 2.8 indicating a strong deterioration of the environmental quality of this mining area. This index estimated for each sample in both the floodplain and the live-bed channel (Figure 5) indicates that in both environments all the sediment samples analysed are contaminated (PLI > 1). In the live-bed channel (Figure 5a) although there is a wide variation the maximums are observed in the central section of the three channels (Grande Renegadero and Campana) decreasing towards the lower section of the Grande River which is the furthest away from mining activity. In the floodplain (Figure 5b) there are high PLI values in the middle and lower reaches of Renegadero with values between 3 and 4 which could be associated with scouring due to large flooding events and the formation of wide bars in the channel. In the Campana River higher values for PLI appear in the live-bed channel (between 2 and 4) than in the floodplain (between 2 and 3). Although the sediment values in the Grande River remain between 2 and 3 a maximum is observed in sample G4 (as in the live-bed channel) and in samples G24 and G25 located at the tail of the Rumblar reservoir.

Figure 6 maps the spatial variation in Pb and As. For Pb anomalies can be seen in the live-beds of the Renegadero and Campana channels clearly related to mining activity (Figure 6a) while in the floodplain the anomalies cover more area but less intense being located downstream in the final section of the Renegadero and middle part of the Grande River (Figure 6b). Anomalies for the As content of the sediments of the live bed are observed in the upper part of the Grande River and throughout the Campana River with intermediate values in the final sections of the Renegadero and lower reach of the Grande River (Figure 6c). In the floodplain As (Figure 6d) shows strong As concentration anomalies throughout the Grande River as well as in the middle and lower reaches of the Renegadero River and lower intensity anomalies in the Campana. Figs. 6e and 6f show the spatial distribution of the PLI values displaying similar behaviour in both sedimentary environments and presenting the highest contamination in the middle and upper reaches of the Grande River and the lower reaches of the Renegadero and in the Campana River with greater intensity and extent in the floodplain.

4. Conclusions

The sediments of the Grande River and its tributaries Renegadero and Campana have high contents of Cd, Ag, Co, Ni, Cu, As, Zn, Ba and Pb with average values in the floodplain deposits of 4, 5, 14, 27, 90, 116, 659, 2622 and 5452 mg/kg respectively. These values are much higher than those of the regional geochemical background and those established in the generic reference levels of government regulations. Pb and As present the highest contents with maximum concentration values of 15,533 and 192 mg/kg respectively. These metal(loid)s come from the existing mining liabilities in the area (ruins of old mining facilities dumpsites and fines tailings dams). The average concentrations are somewhat higher in the samples taken in the floodplain than in the samples taken in the live-bed channel showing more variable Pb behaviour with numerous peaks that indicate great variability and low mobility. In contrast As has a more uniform distribution along the basin and its maximum concentrations generally do not coincide with those of Pb.

The mineral paragenesis elements of mining interest (group 1 of the principal component analysis for the floodplain and group 4 for the live-bed channel) especially Pb and Ba present heterogeneity and dispersion with lognormal behaviour and numerous extreme values.

The environmental indices calculated suggest a high degree of impact by metals in the basin sediments for the elements Ag, As, Ba, Cd, Pb, Zn of the mineral paragenesis classifying the existing contamination as moderate to high. For Pb anomalies occur in the live-bed channel both in the Renegadero River and in the Campana River clearly related to mining with more intense and extensive effects in the floodplain due to strong flooding creating areas used for cultivation [5] both in the final stretch of the Renegadero and in the middle stretch of the Grande River. As is present in the sediments of the entire basin both in the bed-live and in the floodplain presenting only low concentrations in the upper reaches of the Renegadero River. The distribution map of the PLI shows effects on the soils with the greatest intensity in the sediments of the live-bed channel in the upper section of the Grande River in the lower section of the Renegadero River and throughout the entire Campana River.

The results obtained from the study of the sediments of the Grande riverbed show that this old mining basin has been highly affected especially because the waste generated was accumulated without any preventive measures after abandonment requiring competent administrations to take remediation measures.

Heavy metals have a significant presence in the area studied, resulting in highly contaminated sediments according to data obtained in this work, similar other work was carried out in other mining basins around the world such as that of the Environment Agency in England [5]. This contamination was transported several kilometres away from the pollutant sources and is guaranteed to contribute heavy metals to the human water supply reservoir damage the ecosystem and lead to a deteriorated ecological state.

Finally note that an old mining basin was analysed in its entirety that until now had not been studied. Considering the results obtained this is a significantly contaminated area that until now had gone unnoticed by the regional environmental agency.