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Article

Modeling Changes in the Composition of River Water with Discharged Wastewater: A Case Study in NW Russia

1
N. Laverov Federal Center for Integrated Arctic Research of the Ural Branch of the Russian Academy of Sciences, 23 Severnoy Dviny Emb., 163061 Arkhangelsk, Russia
2
Vernadsky Institute of Geochemistry and Analytical Chemistry of Russian Academy of Sciences, 19 Kosygin st, 119991 Moscow, Russia
*
Author to whom correspondence should be addressed.
Water 2022, 14(2), 165; https://doi.org/10.3390/w14020165
Submission received: 22 December 2021 / Revised: 1 January 2022 / Accepted: 6 January 2022 / Published: 8 January 2022
(This article belongs to the Section Water Quality and Contamination)

Abstract

:
The technogenic impact of the development of the Lomonosov diamond deposit is associated with the discharge of quarry and drainage water into the river, which has a special conservation status. Earlier studies on the composition of bottom sediments showed that there are signs of increased accumulation of heavy metals and radionuclides at wastewater discharge sites. The purpose of this work was to predict changes in the composition of surface water and bottom sediment in the river during the further development of mining operations with brackish and salty water captured by drainage systems, the presence of which was established in the zone of their future influence. For this, a simulation of changes in the composition of the water in the river was carried out using the GEOCHEQ software package by minimizing the free energy of the system using a convex simplex algorithm. It was found that the maximum salinity of surface water can reach 1.51 g/L. In this case, the MPC of Cl, Na+, SO42−, Mg2+, Sr, V, and U can be exceeded for fishery watercourses. The genetic basis of the accumulation of these components in solutions for mixing was considered. According to the calculations, when about 5000 m3/h of drainage water is discharge d into the river, the mass of precipitated chemical elements will be 56–191 t/h, including up to 2.1 t/h of iron; therefore, accumulation in the discharge zone must be controlled.

1. Introduction

The extraction of minerals during the development of their deposits in sedimentary basins disrupts ecological systems and has a serious impact on environmental pollution at the local and regional level. In addition, the drainage of huge rock masses during the construction of quarries violates the conditions for the recharge and discharge of aquifers. This leads to deterioration in the quality of groundwater [1,2,3,4] and, accordingly, surface water [5,6,7,8,9], and to changes in hydrogeochemical processes. Thus, it is necessary to create a clear system for handling waste from the mining industry, particularly drainage water [9,10]. Processes for improving water quality can also be considered for drinking use or for technical purposes [11,12,13].
The man-made impact of the development of the Lomonosov diamond deposit, which is the largest industrial diamond deposit in Europe, is currently associated with mining operations at the Arkhangelskaya and Karpinsky pipes, with the industrial facilities of these sites and the discharge of quarry and drainage water (Figure 1).
Open pit mining has been ongoing at the Arkhangelskaya pipe since 2003 and at the Karpinsky pipe since 2007 (Figure 2a).
The depth of the quarries has now reached 230 and 170 m, and up to 450 m is planned. Mining operations are carried out under the protection of an external drainage loop of 70 dewatering boreholes (DBs) 220 m deep (Figure 1a) and an open pit dewatering with surface pumping units (Figure 2b). The productivity of the drainage circuit of the wells is 5000 m3/hour and of the open pit drainage, 1000 m3/hour. Drainage water is completely discharged into the Zolotitsa River (Figure 1a) while quarry water is settled in sedimentation ponds and then discharged to a filtration field, which is a swamp located north of the Karpinsky pipe, one kilometer from the drainage water discharge point. From this swamp, quarry water also flows into the Zolotitsa River. The low-water discharge of the river at the point of discharge of drainage and quarry water is about 3000 m3/hour, thus it is not surprising that the composition of both the river water and the bottom sediment is under significant technogenic load. At the same time, the Zolotitsa River has a special conservation status since it is the largest spawning ground for Atlantic salmon (Salmo salar) in the White Sea basin [14]. In Russia, the quality of the water of fishery-related water bodies is regulated by the Order of the Federal Agency for Fisheries No. 20, dated 18 January 2010: “On Approval of Water Quality Standards for Aquatic Fishery Objects, including Norms for Maximum Permissible Concentrations (MPCs) for Harmful Substances in Waters of Aquatic Fisheries Objects”.
Studies of the bottom sediment of watercourses carried out in 2018–2019 showed that for three kilometers downstream from the place of discharge of drainage and quarry water into the Zolotitsa River, bottom sediment is characterized by the highest concentrations of heavy metals and radionuclides. Additionally, in this area, there are increased proportions of the clay component, organic matter, carbonates, and water-soluble salts in the bottom sediment [15]. The analysis showed that one of the distinctive features of the kimberlite rocks of the Lomonosov diamond deposit is their large-scale saponitization. Almost all of the original magmatic material is represented by the product of the successive chemical weathering of olivine and serpentinite by high Mg clay mineral saponite, the content of which is up to 75–100% [16,17]. During mining operations, saponite enters the open pit water, forming a finely dispersed suspension. As a result, the quarry water pumped out and discharged to filtration fields also contains significant amounts of this mineral. Apparently, complete purification of pumped-out pit water as a result of filtration through the bog massif does not occur and saponite enters the river water, increasing its turbidity and settling in bottom sediment. As a mineral of the montmorillonite group, it has high sorption, ion exchange, and complex-forming properties, and most likely has a significant role in the accumulation of heavy metals and radionuclides in areas where quarry water is discharged and downstream of those areas.
Another environmental problem in this area is the presence of brackish and salty water “lenses” in the Padun Formation of the Vendian aquifers in the Zolotitsa River valley (Figure 1a). In the L1 lens closest to the quarry, the value of the total dissolved solid (TDS) of water is about 2.5 g/L and since the end of 2014, abnormally high TDS values up to 2.5 g/L have been observed in the drainage water pumped out by dewatering wells in the northern section of the drainage circuit around the Karpinsky pipes; as a result, the average salinity of drainage water discharged into the river was found to reach 0.69 g/L. Therefore, the frequency of the operation of drainage wells began to be regulated in order to reduce this trend and meet the requirements of supervisory authorities to ensure permissible concentrations of chemical elements in drainage water discharged into the river. These requirements are currently being met. However, the problem remains due to the fairly widespread distribution of brackish and saline water in aquifers in the field (Figure 1a). With the expansion of the open pit to the north and the commissioning of the open pit on the Pionerskaya pipe, brackish water from the second lens, with similar TDS values, will be pulled up in the same way. Even higher TDS values, particularly up to 25 g/L, were found in the area of the Lomonosovskaya pipe in lens L2 [18]. Similar TDS values are characteristic of the saline water contained in the underlying aquifer of the Mezen Formation, namely the Vendian (Figure 1b).
With the deepening of quarries below 200–250 m, the inflow of saline water into the dewatering system of boreholes and the surface quarry drainage system will intensify. Therefore, this problem requires a deeper consideration of optimal measures to be adopted in order to minimize the harmful impact on the environment. This work investigates the problem by the method of thermodynamic modeling. Using this method, it is possible to study the formation processes of the chemical composition of surface water and its pollution under the influence of wastewater from the mining industry. The method also makes it possible to predict the functioning of a water body within the framework of sequential changes in various scenarios [19,20].
Computer modeling of hydrochemical processes is widely used in Russia [21,22,23,24,25,26,27,28,29], the USA [30,31,32], and Europe to forecast geoecological changes. The foundation of thermodynamic modeling was laid out by R.M. Garrels [33,34] and the computer implementation was first done by both H.C. Helgeson [35] and, in Russia, by I.K. Karpov [36]. In this work, modeling was carried out based on programs for calculating the equilibrium composition of heterogeneous multicomponent systems and thermodynamic databases available for modeling hydrogeochemical and hydrothermal processes in the laboratory of the Vernadsky Institute of Geochemistry and Analytical Chemistry of the Russian Academy of Sciences. The collection and critical assessment of missing thermodynamic data were also part of the modeling. This makes it possible to quantitatively describe ongoing chemical interactions and to predict changes in the ecological conditions in the area with further technogenic impact.
The scientific novelty of this work is in regard to the calculation of the equilibrium composition of the system by the method of minimizing the free energy of the system using a convex simplex algorithm [37]. Methods such as this are widely used abroad for calculating metamorphic systems at high temperatures and pressures, and are not usually used for aqueous solutions compared with methods for calculating equilibria using equilibrium constants [38]. Therefore, applying such a method to solve a specific physical problem of quantitatively describing the ongoing chemical interactions in a near-surface hydrogeochemical system with forecasting of changes in the ecological conditions of a region under further technogenic impact is undoubtedly of scientific interest.
The purpose of this work was to predict changes in the composition of surface water and bottom sediment in the river during further development of mining operations where brackish and saline water is captured by drainage systems, the presence of which was established in the zone of their future influence.
The following scenarios were considered: (i) changes in the composition of the surface water of the Zolotitsa River (Z) when mixed with fresh drainage water discharged from water-sinking wells and, similarly,(ii) taking into account the pulling of brackish and saline water into the dewatering boreholes (DBs) from lens L1, (iii) from lens L2, and (iv) from the aquifer of the Vendian Mezen Formation (Vmz). An assessment was made of the results of the surface water of the Zolotitsa River mixed with drainage water according to the maximum permissible concentration (MPC) of harmful substances in water bodies.

2. Materials and Methods

2.1. Hydrogeological Structure

The aquifer complex of the host rocks of the Padun formation of the Vendian plays the main role in the flooding of the deposit. The thickness of the complex within the study area is 160–180 m and the hydraulic conductivity or coefficient of permeability kf is 1.5–1.7 m/day. The complex was unconfined laterally and is represented by an uneven alternation of layers of sandstones, siltstones, and, to a lesser extent, mudstones. It contains groundwater Na-HCO3 and Na-Cl-HCO3, with an average TDS of 0.45 g/L. In the valley of the Zolotitsa River, during geological exploration, 9 wells penetrating brackish and salty waters had a TDS of 1.2 to 27.2 g/L or an average of 6.4 g/L. Groundwater of similar mineralization was also found in kimberlite pipes composed of weakly fractured breccias of ultrabasic and sedimentary rocks to a depth of 150 m (3 g/L) and 150–300 m (9–14 g/L) [18]. The origin of the water is associated with the marine water of the Mikulinian (Eemian) Sea, which flooded coastal areas in the lowest relief forms 115–130 thousand years ago, including the paleovalley of the Zolotitsa River [39,40,41]. In the paleovalleys, strata of clayey deposits were formed, saturated with pore water of marine origin. Then, 20–15 thousand years ago, the pore water from Mikulinian clay was squeezed out under the weight of the kilometer-thick Valdai (Weichselian) glacier [42,43,44] and filled the relatively well-permeable strata of the Padun formation of the Vendian. After the retreat of the Valdai glacier, fresh water flowed from the watersheds to the river valleys, thus brackish and salty water was preserved only in the form of local “lenses” in the territories of modern valleys.
A subordinate role is played by overlapping upper deposits, which combine the aquifers of the Quaternary sediment and the Urzuga stage of the Middle Carboniferous, composed of weakly cemented fine-grained clay sandstone with a thickness of 25–30 m (kf 1.0 m/day). At the base of the cross-section, there is a sequence of water-bearing complexes of Mezen (kf 0.03 m/day; Figure 1b) and Ust-Pinega (kf 10−3–10−4 m/day) formations, which are characterized by an uneven alternation of siltstone and argillite, with rare thin sandstone interlayers. In relation to the Padun complex, it is an aquitard. The explosion pipes break through the Vendian deposits and are overlain by sediment of the Carboniferous and Quaternary ages. In them, an upper crater part is formed with a thickness of 110–150 m, composed of tuff and tuffites, and a lower crater part, which is represented by kimberlite breccia. For the upper crater facies, increased permeability (kf ~0.6–0.9 m/day) is typical, but for the lower crater facies, permeability is much lower (kf ~0.02 m/day). The aquifer complex of the host rocks of the Mezen formation of the Vendian is characterized by the ubiquitous distribution of Na-Cl groundwater, with the TDS up to 24.3 g/L. In the slightly permeable sediment of the Ust-Pinega Formation and in the kimberlite breccia, the TDS values of gravitational groundwater was found to be 22.5 and 21 g/L, respectively.

2.2. Water Samples

The following were taken for modeling: (i) The results of the study of the chemical composition of surface water sampled from the Zolotitsa River at point Z, located 3 km above the place where drainage water is discharged into the river (Figure 1a). These results characterize the natural state of river water not affected by the technogenic impact of the mining and processing plant. (ii) Fresh groundwater with a TDS of 455 mg/L, sampled from a system of dewatering boreholes draining the Padun Formation of the Vendian sediment at an interval of 40–200 m. Such water is discharged into the Zolotitsa River (Figure 1a). (iii) Groundwater sampled from the water-bearing complex of siltstone and sandstone of the Padun Formation at an interval of 40–200 m at point L1, located within the lenses of brackish water, with a TDS of 2528 mg/L, between the Karpinsky and Pomorskaya pipes (Figure 1a). (iv) Groundwater sampled from the same aquifer at point L2, located within the saltwater lens, with a TDS of 8418 mg/L, near the Lomonosovskaya pipe (Figure 1a). (v) Groundwater with an average TDS value of 21,664 mg/L, sampled from the Mezen formation of the Vendian water-bearing complex of siltstone and sandstone at an interval of 260–300 m, 3 km east of the Arkhangelskaya pipe (Vmz in Figure 1b).
Water samples were taken in August and September (summer baseflow), 2014 [45,46]. All water samples were filtered through 0.45 μm of acetate cellulose in the field. Solutions that were filtered for cation and trace element analyses were acidified with double-distilled HNO3 (pH < 2); samples for anion analysis were not acidified. The water temperature and pH were measured in the field using portable HANNA instruments with an uncertainty of 0.1 °C and 0.05 pH units. The calcium, magnesium, sodium, and potassium concentrations were determined with an uncertainty of 1–2% by using an atomic absorption spectrometer (AAS; Perkin-Elmer 5100 PC). Alkalinity was measured by potentiometric titration with HCl using an automated titrator (Metrohm 716 DMS Titrino) and the Gran method (detection limit of 10−5 M and uncertainty at ≥0.5 mmol L−1 1–3% and <0.5 mmol L−1 7%). The major anion concentrations (Cl and SO42−) were measured by ion chromatography (HPLC; Dionex ICS 2000) with an uncertainty of 2%. Major and trace elements were determined without preconcentration by inductively coupled plasma–mass spectrometry (ICP-MS; Agilent 7500ce) at GET, Toulouse, France. Good agreement (≤10%) between the measured and certified U concentration in a certified river water sample (SLRS-5) was achieved [45,46].

2.3. Modeling Technique

Modeling of changes in the composition of the water in the Zolotitsa River (Z) with discharged drainage groundwater from the system of dewatering boreholes (DBs) was performed according to the following 6 scenarios:
Scenario 1: DB and Z mixed in a ratio of DB:Z = 2:1.
Scenario 2: The same, with brackish water from the lens in the Padun formation of Vendian aquifers (L1) pulled up to DBs in the ratio of L1:DB = 1:3.
Scenario 3: The same, with saline water pulled up to DBs from the lens in the Padun formation of Vendian aquifers (L2) in the ratio of L2:DB = 1:3.
Scenarios 4–6: The same, with saline water from the underlying aquifer of the Vendian Mezen Formation (Vmz) pulled up to DBs in the ratios Vmz:DB = 1:100, 4:100, and 7:100. The latter is the ratio of transmissibility between the Mezen and Padun aquifers. Theoretically, in such a ratio, the maximum flow in a steady state can be realized.
To solve the set tasks, the GEOCHEQ software package was used [47]. Modeling consisted of calculating the chemical equilibria of mixing solutions in different proportions. The GEOCHEQ complex consists of a thermodynamic database and a program for calculating equilibria in multicomponent multiphase systems. The thermodynamic database is based on the well-known SUPCRT92 [48]. The three-term Mayer–Kelly heat capacity equation was used to calculate the thermodynamic properties of minerals and gases for a given temperature and pressure. To calculate the thermodynamic properties of ions and neutral molecules of the aqueous phase, the Helgeson–Kirkham–Flowers model was used [49]. The thermodynamic properties of water were calculated using the equations in [50,51]. The calculation of the activity coefficients for the components of an aqueous solution was carried out according to the Debye–Hückel model. The calculation of the equilibrium composition of the system was carried out by the method of minimizing the free energy of the system using the convex simplex algorithm [37].
Chemical interactions were considered in a system consisting of 23 independent components: O, H, Na, K, Ca, Mg, Fe, C, Cl, S, Cr, Mn, Al, As, B, Ba, Cd, U, V, Cu, Zn, Sr, and Pb. The equilibrium compositions of the mixing solutions were calculated, taking into account the complexation in the solutions and the precipitation of minerals. The model included 160 aqueous species and 54 minerals. The possibility that an ideal solid solution (Ca, Mn, Sr, Pb, Zn)CO3 would form was considered to simulate the coprecipitation of Mn, Sr, Pb, and Zn with calcite. The entire list of potentially possible solid phases, aqueous species, and gases is given in Table 1. Calculations were carried out at a temperature of 10 °C for surface conditions. In other words, the system was considered open to atmospheric air. For this, a constant pressure of carbon dioxide and oxygen was set (lgPCO2 = −3.4 and lgPO2 = −0.7).

3. Results

Table 2 shows the initial compositions of the surface water and groundwater taken in modeling their mixing. Table 3 as well as Figure 3 and Figure 4 show the simulation results.
It was established that the maximum salinization of surface water occurs as a result of the development of events in Scenario 3, when saline water is drawn to the DB system from the lens in the Padun aquifer (L2) in the ratio of L2:DB = 1:3 when it is up to 1.51 g/L, and in Scenarios 5 and 6, when saline water from the Mezen Formation (Vmz) is brought to the DB system in the ratio of Vmz:DB = 4:100 to 7:100, when it is 0.771 and 1.13 g/L, respectively (Figure 3a). In this case, the concentration of chlorine in the water will be 529, 337, and 539 mg/L. The MPC of chlorine for fishery watercourses was 500 mg/L. Sodium concentrations also exceeded the MPC (120 mg/L), ranging from 207 to 381 mg/L (Figure 3b). The excess MPC for the content of sulfates (100 mg/L) was found to be according to Scenarios 3 (405 mg/L) and 6 (124 mg/L; Figure 3c). According to Scenario 3, the concentration of magnesium (46 mg/L) will exceed the MPC (40 mg/L; Figure 4b).
Of the trace elements, the highest concentrations were of strontium and boron; according to Scenario 3, they reach 350–370 μg/L with an MPC of 400–500 μg/L (Figure 3f and Figure 4d). Vanadium can also be noted, with its concentration increased from 0.95 to 1.28 μg/L according to Scenarios 4–6, with an MPC of 1 μg/L (Figure 3g). Of note are the results obtained on the distribution of uranium in surface water. In all scenarios, it is significant, ranging from 3.8 to 6.1 μg/L (Figure 3f). There was no MPC of uranium for fishery watercourses in Russia; however, in the global literature, recommendations typically vary from 0.5 to 300 μg/L [52]. In addition, the Institute for Radiation Protection and Dry Core in France proposed a new approach: the uranium content in river water should be 5 μg/L above the background MPC [53]. For the Zolotitsa River, the background is about 0.35 μg/L, that is, for this indicator, the data on the predicted distribution of uranium in mixing solutions are also noteworthy.

4. Discussion

To illustrate the change patterns in the concentrations of chemical components in mixing solutions, which were obtained according to different scenarios, graphs showing their dependence on changing TDS values are presented in Figure 5 and Figure 6. Figure 7 and Figure 8 demonstrate the dependence of changes in the concentrations of precipitating minerals as well as major and trace elements on TDS.
The concentrations of chlorine and sodium (Figure 5a), calcium and magnesium (Figure 5c), and potassium (Figure 5d) increased in direct proportion to the increased TDS values over their entire range, with a linear correlation coefficient (R2) of 0.89 for calcium and 0.99 for sodium. There is a decreased correlation of calcium with TDS compared with sodium because calcium plays a leading role in the least saline water, with the TDS up to 0.3 g/L. For such water, a Ca-Mg-HCO3 composition is characteristic. This is due to the disequilibrium of atmospheric precipitation in thawed and low-mineralized water with respect to calcite, anorthite, labradorite, andesine, and diopside [54]. As TDS increases, Ca and Mg deficiency increases, and the relative content of sodium increases. This can be attributed to the saturation of groundwater with respect to calcite and dolomite, and partial precipitation of calcium carbonates (see Figure 7a and Figure 8a) [55]. The solution determined according to Scenario 1 has a composition of Na-HCO3-Cl. The chlorine content in the mixture is 37 mg-eq.% because, in Scenario 1, river water is mixed with drainage water from a system of dewatering wells, in which the chlorine concentration is, on average, 73 mg/L at a TDS of 455 mg/L (see Table 2).
With a further increase in the TDS level in mixing solutions to 0.4–1.5 g/L according to Scenarios 2–6, the Cl concentration increases to 125–539 mg/L due to the process of mixing fresh water with brackish and salty water from lenses L1 and L2, as well as from the Vendian Mezen Formation aquifer. The composition of the water becomes Na-Cl.
The main genetic cause of the strontium accumulation in the groundwater of the Vendian Mezen Formation in the study area (Vmz in Table 2) is associated with an increase in groundwater salinity when interacting with rocks containing calcium and strontium sulfates [56]. In the Permian period, on the surface in salinized lagoon-type basins, the concentration of strontium ions increased to full saturation and they precipitated in the form of sulfate. Deposition occurred at the time of saturation of the brine with gypsum; therefore, the upper sections of the carbonate rocks directly underlying the anhydrite–gypsum strata were especially rich in celestine. Celestine formation generally continued until the beginning of halite setting [57,58]. In the form of strontium carbonate (strontianite) and as an isomorphic admixture, strontium was deposited in the composition of carbonate rocks. Subsequently, gypsum-bearing strata were eroded in the study area and, at present, their border is located 60 km to the east. However, due to the good solubility of celestine in solutions of NaCl and other salts, the strontium from these sedimentary rocks was carried away by surface and ground water and formed new secondary accumulations in a variety of rocks, including sandy-clayey sediments of continental origin. This is evidenced by the presence of rare interlayers of gypsum in limestone and dolomite.
Additionally, increased strontium concentrations are associated with the marine water of the Mikulinian (Eemian) Sea in the lenses of brackish water in the Zolotitsa River valley (see Section 2).
Previous studies [56] have established that the concentration of strontium in the Vendian and Middle Carboniferous sediments is 10 and 71 mg/kg, respectively. Similar values are typical for Quaternary formations. The average concentration of strontium in fresh water developed in the areas of the distribution of these rocks, particularly in drainage water extracted by the DB system, was determined at the level of 0.04% TDS (see Table 2). In this water, strontium has a sedimentation genesis (in seawater, the strontium content is 0.023% TDS [59]) apparently as a result of the inflow of saline water from deeper horizons, its dilution with fresh water, and dissolution of gypsum inclusions enriched in strontium. This suggests that the strontium content in the fresh groundwater in the region should not, on average, exceed 0.4 mg/L (see Figure 6).
In the groundwater contained in the lens in the area of the Karpinsky pipe (L1), the strontium content was 0.026% TDS (see Table 2), which corresponds to the strontium content in seawater. This confirms the position that the origin of this water is associated with the seawater of the Mikulinsky (Eemian) Sea (see Section 2).
Groundwater in the Mezen Formation of the Vendian (Vmz in Table 2) is characterized by strontium concentrations at the level of 0.15–0.18% TDS.
Increased boron concentration in solution is entirely associated with sedimentary marine water. In lens L2, the concentration was on average 1.8 mg/L, and in the Mezen Formation of the Vendian, it was 1.54 mg/L (Table 2). Accordingly, in mixed solutions, the concentration was determined at levels of 370 and 150 μg/L, which do not exceed the MPC (500 μg/L; Figure 6b).
The minimum U concentration of 0.59 μg/L was obtained in the upper reaches of the Zolotitsa River (Z in Table 2). This is mainly due to the swamp recharge of the river and the short duration of the interaction of surface water with rocks; as a result, there is extremely limited participation of the processes of their dissolution with the transition of uranium into water.
For groundwater under oxidizing conditions in the upper part of the aquiferous complex of the sediment of the Padun Formation, the average uranium content was 6.78 μg/L (DB in Table 2). The maximum average U concentration of 15.2 μg/L is typical for brackish water near the redox barrier (L2 in Table 2) [45]. Under reducing conditions in the salty water of the aquifer of the Mezen Formation, namely the Vendian (Vmz in Table 2), the U content drops sharply to 0.15 μg/L.
As shown in [60,61,62], Vendian siltstones and sandstones do not contain native uranium minerals. The uranium was in a dispersed state and was redistributed by groundwater along its streamlines from the recharge zones of the watersheds to the discharge zones in the river valleys. Its maximum concentration, on average, was 13 mg/kg and formed by coprecipitation with iron hydroxides. A slightly lower concentration, on average, was 9 mg/kg and is characteristic of adsorbed uranium coprecipitated with carbonates. The gross uranium concentration in some samples reached 20–30 mg/kg. The average value of 234U/238U was the maximum for adsorbed material and carbonate minerals (2.39 ± 0.36), and was close to that in fresh groundwater (2.8 ± 0.42). It is also increased in amorphous Fe minerals (1.53 ± 0.23). In general, there is a clear dependence of the ratio of 234U/238U activity in the rock on the degree of participation of groundwater in the deposition of hydrogenic uranium isotopes in the cracks and pores of these rocks [62].
As discussed in Section 4, the uranium concentrations in the mixed solutions (Figure 6c) may pose a hazard to river inhabitants.
The maximum precipitation from mixed solutions (not counting calcite) was typical for dolomite (9.64 × 10−5–3.85 × 10−4 mol/kg H2O), followed by goethite (2.4–7.9 × 10−6 mol/kg H2O), MnO2 (2.33 × 10−7–2.73 × 10−6 mol/kg H2O), gibbsite (8.49 × 10−7–1.31 × 10−6 mol/kg H2O), and barite (0–1.66 × 10−6 mol/kg H2O; Figure 7).
According to Scenarios 4–6 for goethite, MnO2, and gibbsite, a linear increase in the molar mass of the precipitate with R2 = 1 was established with an increase in the TDS of the solution from 0.62 to 2.41 g/L. Dolomite and barite are characterized by a polynomial dependence and the concentration of dolomite in the sediment slightly decreased with an increased proportion of saline water from the Vendian Mezen Formation. According to Scenarios 1–3, an increase in the molar mass of the sediment was also mainly observed with an increase in the TDS of the solution; however, this increase occurred abruptly in the transition from Scenario 1 to Scenario 2 and was further expressed much more weakly. For gibbsite, there was even a decrease in the molar mass of the sediment when going from Scenario 2 to Scenario 3, from 1.31 to 1.04 × 10−6 mol/kg H2O.
The weight mass of the deposited chemical elements (Figure 8) was at the maximum for Scenarios 3 and 6, and varied as follows: Ca, 17.7–20.7 mg/kg H2O; C, 8.1–10.2 mg/kg H2O; Mg, 3.4–9.3 mg/kg H2O; Sr, 98–1800 μg/kg H2O; Fe, 440–420 μg/kg H2O; Mn, 146–150 μg/kg H2O; Al, 31–35 μg/kg H2O; Ba, 15–23 μg/kg H2O; S, 3.4–5.3 μg/kg H2O; Zn, 1.5–2.9 μg/kg H2O; and Pb, 0.048–0.38 μg/kg H2O.
It should be noted that, in general, when about 5000 m3/hour of drainage water is discharged into the river, the TDS value of the river water will change according to the various scenarios from 90 to 300–1500 mg/L, and the mass of precipitation will change from 11.2 to 38.2 mg/kg H2O or 56–191 tons/hour, including up to 2.1 tons/hour of iron. Naturally, the bulk of the deposited chemical elements will be carried out by the river into the sea and deposited on the river–sea hydrochemical barrier. However, the described tendency for clayey sediment with high sorption properties to accumulate where quarry water is discharged may contribute to the continued accumulation of heavy metals in this zone.
Previous studies showed that the water in the Zolotitsa River upstream of the wastewater discharge site contained 0.39 mg/L of iron and the content in the bottom sediment was 9.8 g/kg [15,46]. Downstream of the discharge site, over a distance of three kilometers, an iron concentration of 1.5 times higher (14.7 g/kg) was recorded in the bottom sediment, although in water, this was somewhat reduced (to 0.24 mg/L) due to the low iron concentration in drainage water extracted by the DB system and discharged into the river (0.035 mg/L). Four or more kilometers downstream of the river, the iron content in the bottom sediment again averaged to 9.6 g/kg. This confirms the previously stated assumption that the accumulation of heavy metals in the bottom sediment outside the influence of the discharge of quarry water (about 3 km) does not necessarily depend on their content in drainage water and their accumulation in the near zone is associated with the accumulation of sorbing material (saponite, carbonates, and organics).
It is advisable to periodically monitor the state of bottom sediment near the quarry area.

5. Conclusions

The purpose of this work was to predict changes in the composition of surface water and bottom sediment in a river during the further development of mining operations with the capture of brackish and saline water by drainage systems, the presence of which was established in the zone of their future influence. For this, modeling of changes in the water composition in the Zolotitsa River was carried out using the GEOCHEQ software package, calculating the equilibrium composition of the system by the method of minimizing the free energy using a convex simplex algorithm.
It was established that the maximum salinization of surface water occurred as a result of pulling salt water to the system up to 1.51 g/L. At the same time, the MPC of Cl, Na+, SO42−, Mg2+, Sr, V, and U can be exceeded for fishery watercourses. The genetic basis for the accumulation of these components in solutions for mixing was considered.
The maximum precipitation from mixing solutions (not counting calcite) was found to be typical for dolomite and then goethite, MnO2, gibbsite, and barite. In general, it should be noted that when about 5000 m3/h of drainage water is discharged into the river, the precipination mass will be from 56 to 191 t/h, including up to 2.1 t/h of iron. Therefore, the described tendency for clayey sediment with high sorption properties to accumulate in areas where quarry water is discharged may contribute to the continuing accumulation of heavy metals in this zone.
The results of this study provide a better understanding of the dangers of discharging saline drainage water from an exploited diamond deposit into the Zolotitsa River. This determines the environmental value of the work.
In the future, it is planned to periodically monitor the state of river water and bottom sediment in the quarry area in order to compare the results of predictive calculations with real values and to improve predictive modeling by minimizing the free energy of the system. It is also planned to study the effect of the composition of organic matter in river water and groundwater on the mobility of chemical elements in mixed solutions.

Author Contributions

Conceptualization, formal analysis, and writing—original draft preparation, A.I.M.; methodology and investigation, E.S.S., M.V.M., A.S.T. and E.V.C. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Russian Ministry of Education and Science (project no. № AAAA-A19-119011890018-3) and the Russian Foundation for Basic Research (project no. 20-05-00045_A).

Conflicts of Interest

The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.

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Figure 1. (a) General location of study site showing end members involved in mixing of surface waters of Zolotitsa River (Z) with fresh groundwater pumped from dewatering boreholes (DBs); brackish and salty groundwater pumped from “lenses” in Vendian Padun Formation (L1 and L2); and (b) salty groundwater pumped from Vendian Mezen Formation (Vmz).
Figure 1. (a) General location of study site showing end members involved in mixing of surface waters of Zolotitsa River (Z) with fresh groundwater pumped from dewatering boreholes (DBs); brackish and salty groundwater pumped from “lenses” in Vendian Padun Formation (L1 and L2); and (b) salty groundwater pumped from Vendian Mezen Formation (Vmz).
Water 14 00165 g001
Figure 2. (a) Quarries on Arkhangelskaya and Karpinsky kimberlite pipes of Lomonosov diamond deposit and (b) quarry drainage at Karpinsky pipe open pit.
Figure 2. (a) Quarries on Arkhangelskaya and Karpinsky kimberlite pipes of Lomonosov diamond deposit and (b) quarry drainage at Karpinsky pipe open pit.
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Figure 3. Concentrations of major anions, and major and trace elements in solution: (a) TDS; (b) Cl and Na+; (c) SO42−, S and HCO3; (d) K+; (e) B; (f) U; (g) Cu, Al, As, Cr and V; (h) Cd, calculated as a result of modeling mixing of surface and groundwater according to Scenarios 1–6 (see Table 2 and Table 3). MPC values for water bodies used for fishery purposes are given in parentheses next to chemical component symbols.
Figure 3. Concentrations of major anions, and major and trace elements in solution: (a) TDS; (b) Cl and Na+; (c) SO42−, S and HCO3; (d) K+; (e) B; (f) U; (g) Cu, Al, As, Cr and V; (h) Cd, calculated as a result of modeling mixing of surface and groundwater according to Scenarios 1–6 (see Table 2 and Table 3). MPC values for water bodies used for fishery purposes are given in parentheses next to chemical component symbols.
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Figure 4. Concentrations of major and trace elements in solution and precipitate: (a) Ca; (b) Mg; (c) C; (d) Sr; (e) Ba and Al; (f) Zn and S; (g) Pb; (h) Fe and Mn, calculated as a result of modeling mixing of surface and groundwater according to Scenarios 1–6 (see Table 2 and Table 3).
Figure 4. Concentrations of major and trace elements in solution and precipitate: (a) Ca; (b) Mg; (c) C; (d) Sr; (e) Ba and Al; (f) Zn and S; (g) Pb; (h) Fe and Mn, calculated as a result of modeling mixing of surface and groundwater according to Scenarios 1–6 (see Table 2 and Table 3).
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Figure 5. Dependence of changes in concentrations of main ions in obtained solutions: (a) Cl and Na+; (b) SO42− and HCO3; (c) Ca2+ and Mg2+; (d) K+ according to Scenarios 1–3 (without filling marker) and 4–6 (complete filling marker) from their TDS values (see Table 2 and Table 3).
Figure 5. Dependence of changes in concentrations of main ions in obtained solutions: (a) Cl and Na+; (b) SO42− and HCO3; (c) Ca2+ and Mg2+; (d) K+ according to Scenarios 1–3 (without filling marker) and 4–6 (complete filling marker) from their TDS values (see Table 2 and Table 3).
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Figure 6. Dependence of changes in concentrations of trace elements in obtained solutions (a) Sr; (b) B; (c) U; (d) Cr and V; (e) Cu, Al and As; (f) Cd according to Scenarios 1–3 (without filling marker) and 4–6 (complete filling of marker) from TDS of these solutions (see Table 2 and Table 3).
Figure 6. Dependence of changes in concentrations of trace elements in obtained solutions (a) Sr; (b) B; (c) U; (d) Cr and V; (e) Cu, Al and As; (f) Cd according to Scenarios 1–3 (without filling marker) and 4–6 (complete filling of marker) from TDS of these solutions (see Table 2 and Table 3).
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Figure 7. Dependence of changes in concentrations of precipitated minerals from obtained solutions (a) Dolomite, (b) Goethite, (c) MnO2, (d) Gibbsite, (e) Barite according to Scenarios 1–3 (without filling marker) and 4–6 (complete filling of marker) from TDS of these solutions (see Table 2 and Table 3).
Figure 7. Dependence of changes in concentrations of precipitated minerals from obtained solutions (a) Dolomite, (b) Goethite, (c) MnO2, (d) Gibbsite, (e) Barite according to Scenarios 1–3 (without filling marker) and 4–6 (complete filling of marker) from TDS of these solutions (see Table 2 and Table 3).
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Figure 8. Dependence of changes in concentrations of precipitated major and trace elements from obtained solutions: (a) Ca, Mg and C; (b) Sr; (c) Fe and Mn; (d) Ba and Al; (e) Zn and S; (f) Pb according to Scenarios 1–3 (without filling marker) and 4–6 (complete filling of marker) from TDS of these solutions (see Table 2 and Table 3).
Figure 8. Dependence of changes in concentrations of precipitated major and trace elements from obtained solutions: (a) Ca, Mg and C; (b) Sr; (c) Fe and Mn; (d) Ba and Al; (e) Zn and S; (f) Pb according to Scenarios 1–3 (without filling marker) and 4–6 (complete filling of marker) from TDS of these solutions (see Table 2 and Table 3).
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Table 1. Solid phases, aqueous species, and gases taken into account in simulation.
Table 1. Solid phases, aqueous species, and gases taken into account in simulation.
Solid PhasesAqueous SpeciesGases
ANGLESITMnO2H2O, aqHCl, aqCuO, aqMgSO4, aqSrHCO3+CO2, g
ANHYDRITENESQUEHONITECO2, aqHCO3CuO2−MgOH+SrOH+O2, g
AZURITEPb3(CO3)2(OH)2H2, aqSO2, aqCuOH, aqMgHCO3+U3+
ARSENOPYRITEPbO2H2S, aqHSCuOH+MgCO3, aqUOH2+
BARITEPYRITEH+HSO3CuCl2Mn2+UO+
BORNITERHODOCHROSITEOHHSO4CuCl3MnOH+HUO2
CALCITESIDERITEAl3+O2, aqCuCl2, aqMnO42−U4+
CELESTITESMITHSONITEAlOH2+SO42−Cu(OH)2MnO4UOH3+
CERUSSITESPHALERITEAlOH+Ca2+Cu2+MnO22−UO2+
CHALCOCITESTRONTIANITEAlOOHCaCO3, aqCuCl+MnCl+UO2
CHALCOPYRITESYLVITEAlO2−CaHCO3+CuCl, aqMnO, aqUCl3+
ChromiteTENORITEHAsO2CaOH+Cu(HS)2Mn3+UCl22+
COVELLITEWURTZITEAsO2CaCl+HCuO2MnSO4, aqUSO42+
Cr2O3WITHERITEHAsO32−CaCl2, aqCuCl42−HMnO2UCO32+
CUPRITEZINCITEAsO43−CaSO4, aqCuHS, aqNa+UO2SO4
DOLOMITE(Ca, Zn, Mn, Sr, Pb)CO3HAsO42−Cd2+Fe2+NaCl, aqUO2(SO4)22−
Fe(OH)3UO2crH2AsO4CdOH+Fe3+NaSO4UO2CO3
GALENAU3O8crH3AsO4CdOFeCl+NaOH, aqUO2(CO3)22−
GAUSSMANITEU4O9crAs2S3HCdO2FeCl2+Pb2+V2+
GOETHITEUO3crAs2S42−CdO2FeO, aqHPbO2V3+
GYPSUMUO2(OH)2crAs4S72−CdCl+FeO2Pb(HS)2, aqVOH+
GIBBSITEUO2CO3crB(OH)3Cd(HSO4)2FeOH2+Pb(HS)3VOH2+
HALITE BO2CdHCO3+FeO+PbCl+VO2+
HEMATITE B(OH)4Cr2+FeCl2, aqPbCl2, aqVOOH+
HUNTITE Ba2+CrO42−HFeO2PbCl3HZnO2
LITHARGE BaOH+CrO2FeOH+PbCl42−ZnOH+
LELLINGITE BaCl+CrO+HFeO2, aqPbO, aqZn2+
MAGNESITE BaCl2Cr3+K+PbOH+ZnCl+
MAGNETITE BaSO4CrOH2+KCl, aqSr2+ZnCl2, aq
MALACHITE BaCO3HCrO2, aqKHSO4, aqSrCl+ZnCl3
MANGANOSITE BaHCO3+HCrO4Mg2+SrCl2ZnO, aq
Mn2O3 ClCu+MgCl+SrCO3, aqZnO22−
Table 2. Initial composition of surface water and groundwater taken in modeling their mixing.
Table 2. Initial composition of surface water and groundwater taken in modeling their mixing.
ComponentZolotitsa River (Z)Dewatering Boreholes (DB)“Lens” Near Karpinsky Pipe (L1)“Lens” Near Lomonosovskaya Pipe (L2)Vendian Mezen Formation (Vmz)
T (°C)104.64.97.76.8
pH7.58.67.97.87.7
mg/kg H2O
TDS84.54552523841821,664
Na+13.3101.379219605374
K+0.84.246.8833.652.8
Ca2+6.0617.649.64951804
Mg2+3.129.8648.4298484
HCO348.821132525519.8
Cl8.22731009303411,502
SO42−4.233.629223232326
μg/kg H2O
B27.311487.718011540
Al57.2725.234187
V0.6610.280.3110.1
Cr0.370.630.991.5418.5
Mn13.412.578.68143153
Fe33935.1134118726564
Cu0.250.161.21.840.29
Zn5.132.1714.823.849.2
As0.50.60.390.361.22
Sr64.316867112,30138,594
Cd0.00280.00440.040.040.035
Ba3373.333.48.1239.6
Pb0.1060.0451.472.020.06
U0.596.781.5715.20.15
Z: Surface water of Zolotitsa River with average TDS of 84.5 mg/kg H2O at a point located 3 km above site were drainage water is discharged; DB: groundwater with average TDS of 455 mg/kg H2O pumped from dewatering boreholes and discharged into Zolotitsa River; L1: groundwater with average TDS of 2523 mg/kg H2O pumped from lens in Vendian Padun Formation, located near Karpinsky pipes; L2: groundwater with average TDS of 8418 mg/kg H2O pumped from lens in Vendian Padun Formation, located near Lomonosovskaya pipe; and Vmz: groundwater with average TDS of 21,664 mg/kg H2O pumped from Vendian Mezen Formation.
Table 3. Simulation results of changes in composition of water in Zolotitsa River with discharged drainage groundwater from a system of dewatering boreholes.
Table 3. Simulation results of changes in composition of water in Zolotitsa River with discharged drainage groundwater from a system of dewatering boreholes.
Temperature 10 °C
Total Pressure 1 Bar
ComponentDB × 2 + Z(L1 + DB 1:3) × 2 + Z(L2 + DB 1:3) × 2 + Z(Vmz + DB 1:100) × 2 + Z(Vmz + DB 7:100) × 2 + Z
SolutionPrecipitationSolutionPrecipitationSolutionPrecipitationSolutionPrecipitationSolutionPrecipitation
pH8.41 8.37 8.04 8.33 8.09
mg/kg H2O
C26.024.6924.46.2112.410.222.04.3513.48.1
Ca9.763.9910.710.475.617.717.67.9570.920.7
Cl51.202070529012505390
K3.103.5407.9903.4205.200
Mg5.272.349.046.2246.39.36.883.8925.03.40
Na71.601820381010603010
S7.94022.30.00441350.005313.0041.40.0034
μg/kg H2O
Al0.90250.38290.19310.34270.2135
As0.5700.5300.5300.5700.590
B85080037009401500
Ba400301510234002415
Cd0.003200.00800.00800.003300.00430
Cr0.5400.600.6900.6601.30
Cu0.1900.3600.4700.1900.200
Fe0.0000141340.0000144150.0000144400.0000141800.000014420
Mn6.81 × 10−9138.7 × 10−91134.34 × 10−81469.5 × 10−9343.24 × 10−8150
Pb0.0170.0480.080.220.0130.380.00250.0630.00040.066
Sr359874144350180021370431760
U4.703.806.104.704.40
V0.8900.7700.77050.901.30
Zn20.0253.40.43.31.51.31.20.872.9
Scenario 1: mix of DB with Z in a 2:1 ratio (DB × 2 + Z); Scenario 2: mix of L1 with DB in a ratio of 1:3 mixed with Z in a ratio of 2:1 (([L1 + DB 1:3] × 2 + Z)); Scenario 3: mix of L2 with DB in a ratio of 1:3 mixed with Z in a ratio of 2:1 ((L2 + DB 1:3) × 2 + Z); Scenario 4: mix of Vmz with DB in a ratio of 1:100 mixed with Z in a ratio of 2:1 (([Vmz + DB 1:100] × 2 + Z)); and Scenario 6: mix of Vmz with DB in a ratio of 7:100 mixed with Z in a ratio of 2:1 (([Vmz + DB 7:100] × 2 + Z)).
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Malov, A.I.; Sidkina, E.S.; Mironenko, M.V.; Tyshov, A.S.; Cherkasova, E.V. Modeling Changes in the Composition of River Water with Discharged Wastewater: A Case Study in NW Russia. Water 2022, 14, 165. https://doi.org/10.3390/w14020165

AMA Style

Malov AI, Sidkina ES, Mironenko MV, Tyshov AS, Cherkasova EV. Modeling Changes in the Composition of River Water with Discharged Wastewater: A Case Study in NW Russia. Water. 2022; 14(2):165. https://doi.org/10.3390/w14020165

Chicago/Turabian Style

Malov, Alexander I., Evgeniya S. Sidkina, Mikhail V. Mironenko, Alexey S. Tyshov, and Elena V. Cherkasova. 2022. "Modeling Changes in the Composition of River Water with Discharged Wastewater: A Case Study in NW Russia" Water 14, no. 2: 165. https://doi.org/10.3390/w14020165

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