RESUMEN
Pollution of the potentially toxic elements (PTEs) is a major concern in the metal ore-mining environment. Active polymetallic industries and mines cause great continuous devastation of both terrestrial and aquatic environments on a local and regional scale. This study investigated the pollution of surface water and groundwater in the area containing six large-scale iron ore mines, which have been in operation for more than a few decades. In order to assess the PTEs pollution, the spatial and temporal distributions of 13 different PTEs (Al, As, Co, Li, Mn, Mo, Ni, Pb, Rb, Se, Si, Sr, and Zn) were measured in 42 water samples collected from the multi-aquifer system including three distinct aquifers (upper alluvial aquifer (UAA), lower alluvial aquifer (LAA), and hard-rock aquifer (HRA)) of the Gohar-Zamin mining area in Iran. The highest concentrations of total dissolved solids (TDS = 164,000 mg/l) and PTEs were measured in HRA. Three trends were identified between the PTE concentration and increasing of TDS based on Spearman correlation analysis: (1) an increasing trend for Al, Co, Li, Mn, Rb, Se, Sr, and Ni; there were strong positive correlations in HRA between TDS and Mn (0.83), Al (0.65), Co (0.74), Li (0.90), Ni (0.83), Rb (0.91), Se (0.82), and Sr (0.84), suggesting a common origin for these elements; (2) no obvious trend for As and Mo, no correlation was founded between As and Mo with other PTEs and TDS, indicating a natural geogenic origin and mutual dependencies of these elements; and (3) a decreasing trend for Si, Zn, and Pb; TDS had a significantly negative correlation with the PTEs and attributing to different chemical properties of infiltrated groundwater. In the principal component analysis (PCA), the first PC that covers 85.09% of the total observed variance is mainly attributed the groundwater salinization. This component is composed of Al, Co, Li, Mn, Rb, Se, Sr, and Ni. The second PC contains elements As and Mo. This PC explain 14.4% of total variance and may be referred to natural origin of PTEs. Si, Zn, and Pb are in the third principal component and cover 9.64% of the variance of the data. Third PC have been attributed to lithogenic and/or primary water chemistry factors. The PTE pollution were evaluated based on heavy metal evaluation index (HEI), heavy metal pollution index (HPI), and degree of contamination (Cd). The results indicated that all of the groundwater samples collected from HRA had HEI, HPI, and Cd values greater than 21, 264, and 14 (highly pollution limits of indices), respectively, and were classified as highly polluted groundwater. HPI values within the UAA, LAA, and salt playa (SP) were lower than the critical level of 100, suggesting a threshold for the drinking water pollution. Moreover, HEI and Cd with values of less than 10 and 7 suggested low-level pollution in UAA, LAA, and SP. However, the contaminated level of PTEs exceeded the WHO standard for drinking water in HRA only. Since groundwater in HRA is a brine with the high values of PTEs, pumping of this water out to the surrounding natural environment may cause harmful impacts on the environment and perhaps living species in Bahram-e-Goor protected area. Graphical abstract.
Asunto(s)
Agua Subterránea , Metales Pesados , Contaminantes Químicos del Agua , Monitoreo del Ambiente , Contaminación Ambiental/análisis , Irán , Metales Pesados/análisis , Medición de Riesgo , Contaminantes Químicos del Agua/análisisRESUMEN
Tracer breakthrough curves provide valuable information about the traced media, especially in inherently heterogeneous karst aquifers. In order to study the effect of variations in hydraulic gradient and conduit systems on breakthrough curves, a bench scale karst model was constructed. The bench scale karst model contains both matrix and a conduit. Eight tracing tests were conducted under a wide range of hydraulic gradients from 1 to greater than 5 for branchwork and network-conduit systems. Sampling points at varying distances from the injection point were utilized. Results demonstrate that mean tracer velocities, tracer mass recovery and linear rising slope of the breakthrough curves were directly controlled by hydraulic gradient. As hydraulic gradient increased, both one half the time for peak concentration and one fifth the time for peak concentration decreased. The results demonstrate the variations in one half the time for peak concentration and one fifth the time for peak concentration of the descending limb for different sampling points under differing hydraulic gradients are mainly controlled by the interactions of advection with dispersion. The results are discussed from three perspectives: different conduit systems, different hydraulic-gradient conditions, and different sampling points. The research confirmed the undeniable role of hydrogeological setting (i.e., hydraulic gradient and conduit system) on the shape of the breakthrough curve. The extracted parameters (mobile-fluid velocity, tracer-mass recovery, linear rising limb, one half the time for peak concentration, and one fifth the time for peak concentration) allow for differentiating hydrogeological settings and enhance interpretations the tracing tests in karst aquifers.