Next Article in Journal
Longitudinal Mixing in Flows with Submerged Rigid Aquatic Canopies
Previous Article in Journal
Analysis of the Source Tracing and Pollution Characteristics of Rainfall Runoff in Adjacent New and Old Urban Areas
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Biogeochemical In Situ Barriers in the Aquifers near Uranium Sludge Storages

1
Sobolev Institute of Geology and Mineralogy, Siberian Branch of the Russian Academy of Sciences, 3 pr. Akademika Koptyuga, 630090 Novosibirsk, Russia
2
X-BIO Institute of Environmental and Agricultural Biology, University of Tyumen, 6 Volodarsky st., 625003 Tyumen, Russia
3
Frumkin Institute of Physical Chemistry and Electrochemistry, RAS, 31 Leninsky Prospect, 119071 Moscow, Russia
*
Author to whom correspondence should be addressed.
Water 2023, 15(17), 3020; https://doi.org/10.3390/w15173020
Submission received: 16 June 2023 / Revised: 29 July 2023 / Accepted: 18 August 2023 / Published: 22 August 2023

Abstract

:
The long-term operation of uranium sludge storages causes serious problems: it contaminates the neighboring aquifers with dangerous substances (uranium, nitrate, ammonium, and sulfate). To purify the aquifers can be costly and time-consuming; therefore, it is important to use the potential of in situ conditions, e.g., the aboriginal microflora and its ability to biologically remediate water reservoirs. In this work, we study the geological, geochemical, and microbiological characteristics of groundwater contaminated by uranium sludge storages resulting from the production cycles of four Russian chemical plants. All of the sites under consideration were extremely contaminated with nitrate (up to 15 g/L); in each case, we used denitrifying bacteria as a dominant group of microorganisms for purification. Our laboratory studies showed that microbial stimulation of water samples by milk whey promotes O2 and nitrate removal; this, in turn, started the cycle of anaerobic processes of authigenic precipitation caused by the reduction of iron and sulfate in the system. Thus, a mineral geochemical barrier preventing uranium immobilization formed. As a result, the uranium of the liquid phase decreased about 92–98% after 3–6 months (decomposition time depends on the nitrate concentration in the groundwater probe). The resulting amorphous biogenic phases contain sulfur, iron, phosphorus, and uranium.

1. Introduction

The storage of uranium wastes in surface collectors at different stages of the nuclear fuel cycle has a significant impact on the environment. This is particularly true for repositories built during the early years of nuclear technologies, whose engineering safety barriers no longer provide the necessary protection [1,2,3,4].
The elimination of hydrogeochemical anomalies in aquifers created near sludge collectors is a specific concern. The formation of these anomalies depends on a set of natural (hydrogeological characteristics, geomorphology of the storage area, etc.) and technogenic (volume and composition of wastes, design of storages) conditions. Unique conditions have formed at each of the facilities with varying degrees of environmental effect; therefore, their remediation algorithms should sufficiently differ. In some cases, the deactivation of sludge collectors may be followed by a minimum set of activities for preventing low-radioactive waste contact with meteoric precipitations, and in other cases, a set of barriers of various natures must be formed for safe storage [5,6,7].
At present, one of the promising approaches to groundwater purification is in situ bioremediation using the metabolic potential of microflora stimulated by various additives injected into the aquifer to remove or immobilize pollutants. This approach has shown high efficiency in the removal of nitrates [8], actinides [9,10], and technetium [11] at a number of facilities. Purification is based on the microbial processes at play in the removal of nitrates (the main component of sludge) due to denitrification to molecular nitrogen. In addition, these processes contribute to the formation of areas with reducing conditions favorable for the precipitation of authigenic iron and sulfur, which are chemically active phases for the immobilization of uranium in the processes of co-precipitation, sorption, and reduction [12,13]. Thus, bioremediation forms a new biogeochemical barrier to prevent uranium migration.
The objects are the storages of low-level wastes from four different Rosatom facilities. Extended halos of polluted groundwater with a high nitrate background have formed in the territory of sludge collectors during decades of production. Earlier, we analyzed the microbial diversity of groundwater at different distances from pollution zones and found the presence of bacteria capable of nitrogen, iron, sulfur, and uranium reduction, and biofilm formation, which improves the sorption capacity of host soils [14,15,16,17,18,19].
The present work focuses on the determination of the main factors controlling the formation of biogeochemical barriers in groundwater near the low-level radioactive waste storage, and assesses the possible formation of biogeochemical barriers in situ to remove hydrogeochemical anomalies. For the first time, a comparative assessment of geological, geochemical, and microbiological factors determining the conditions of effective bioremediation in situ is carried out for four objects.

2. Materials and Methods

2.1. Sample Collection

The water samples were collected from the observation wells during summer using downhole pumps in 1.5 L sterile plastic containers. For the rRNA 16S analysis, samples were conserved with ethanol in a ratio of 1:1. To isolate the clean and enrichment cultures and for the purposes of laboratory model experiments, groundwater was collected in neck-filled containers, which were then sealed without gas phase. The samples were stored at a temperature of 5–7 °C before delivery. Three groundwater samples were selected for each site: maximum contamination (the site of the mixture of technogenic solutions and groundwater), intermediate contamination (areas located at a distance from the sludge collector where mineralization decreases by ~2–3 times), and areas with background composition of natural water.

2.2. Abundance of Microbial Community

The abundance of the major metabolic bacterial groups (aerobic organotrophic and anaerobic denitrifying, iron-reducing, sulfur-reducing, and methanogenic prokaryotes) in groundwater samples was determined by inoculating 10-fold dilutions of groundwater samples (in triplicate) into liquid nutrient media. Microbial numbers were calculated according to the most probable number technique using McCready tables [20]. Aerobic organotrophs were enumerated in liquid medium containing (g/L): BactoTM Tryptone, 5.0; yeast extract, 2.5; and glucose, 1.0; pH 7.0 “https://www.thermofisher.com/order/catalog/product/211705 (accessed on 1 August 2023)”. Sulfate-reducing bacteria were detected by sulfide increase in the dilution series in Postgate B medium [21] with sodium lactate (4 g/L) and 200 mg/L Na2S·9H2O as a reducing agent. Denitrifying bacteria were assessed by nitrogen production in the Adkins medium [22] supplemented with sodium acetate (2 g/L) and sodium nitrate (0.85 g/L). The media for aerobic and anaerobic bacteria were prepared in the Hungate tubes, with air or argon, respectively, as the gas phase (except for the medium for methanogens with H2/CO2). All tubes were incubated at room temperature until the onset of growth, but not longer than 30 days; the cultures were then examined under an Olympus phase contrast microscope “Japan, https://www.olympus-lifescience.com/en/microscoperesource/primer/techniques/phasecontrast/phaseindex/ (accessed on 1 August 2023)”, and specific microbial metabolites were analyzed.

2.3. DNA Sample Preparation and 16S rRNA Gene Analysis

Samples for the total microbial DNA analysis were obtained after filtration of 1.5 L through the Vladipor nitrate-cellulose filters (type GS 0.22 um) using a vacuum filtration device VFD-35 (Vladipor, Vladimir, Russia, “https://vladipor.ru (accessed on 1 August 2023)” (GOST 18963-73) including a funnel filter cell, a collector, a vacuum pump, and an ejector. Filter precipitates were conserved with 96% ethanol and stored at −20 °C prior to the DNA isolation. The DNA isolation from enrichment cultures was conducted using a reagents kit -ZymoBIOMICS™ DNA Miniprep Kit (Zymo Research, Irvine, CA, USA, “https://zymoresearch.eu/ (accessed on 19 august 2023)”) according to the producer’s manual.
The DNA isolation from the filter was conducted by a reagents kit—Meta-G-Nome™ DNA Isolation Kit (Epicentre, San Diego, CA, USA, https://www.illumina.com/products/by-type/molecular-biology-reagents.html/ (accessed on 1 August 2023)) according to the producer’s manual. In preparing libraries for amplification, variable parts of a gene of the V3-V4 region of 16S rRNK were selected: for amplification of the V3-V4 region, degenerated primers For341 (5′-CCTACGGGNBGCASCAG-3″) and Rev806 (5″-GGACTACHVGGGTWTCTAAT-3″) were used. For amplification of the V4 region degenerated primers For515 (5″-GTGBCAGCMGCCGCGGTAA-3″) and Rev806 (5″-GGACTACHVGGGTWTCTAAT-3″) were used. Amplification was performed employing real-time PCR on a CFX96 Touch (Bio-Rad, Hercules, CA, USA, “https://www.bio-rad.com/ (accessed on 1 August 2023)”) device using the qPCRmix-HS SYBR (Eurogen, Moscow, Russia, “https://evrogen.ru/ (accessed on 1 August 2023)”) batch.
Denaturation, primer annealing, and chain elongation for the V3-V4 region were carried out at the temperatures of 96, 54, and 72 °C, respectively, and for the V4 region at the temperatures of 96, 58 and 72 °C, respectively. Purification of the desired product from the batch was conducted with the Agencourt AMPure XP (Beckman Coulter, Brea, CA, USA, “https://www.beckmancoulter.com (accessed on 1 August 2023)”) magnetic particles. Further, high-throughput sequencing was made via the MiSeq system (Illumina, San Diego, CA, USA, “https://www.illumina.com (accessed on 1 August 2023)”) using a reagent kit MiSeq Kit v2 (500 cycle) (Illumina, USA).
Diversity indices (Simpson, Shannon) were calculated using the PAST 4.06b software. OTUs derived from 16s rRNA sequencing data in the SILVAngs database “https://ngs.arb-silva.de/silvangs/ (accessed on 1 August 2023)” were used to calculate diversity indices. The averaging error does not exceed 2–3% “https://www.nhm.uio.no/english/research/resources/past/ (accessed on 1 August 2023)”.

2.4. Laboratory Experiments of Bioremediation Modeling

Biological processes were modeled in vitro in 100 mL vials containing 50 mL of formation fluid. At the initial stage of the experiment, the gas phase was air. Aliquots of solutions containing various electron donors and carbon sources were added to the samples: 5% solution of sugar, 5% solution of sodium acetate, and milk whey (60,000 mg/mL COD) in stoichiometric proportion (Agroprommilksbyt Ltd., Utyatinka, Novgorod region, Russia) necessary for the complete removal of nitrate with 2.5 mg of COD per 1 mg of nitrogen [23]. To determine the uranium speciation in the precipitate 5 mg/L of uranium in the form of uranyl-nitrate salt was added to the samples. They were cultured at room temperature, and aliquots were taken at regular intervals for pH and Eh analysis and determination of the main major components’ concentrations. After the nitrates and sulfates complete consumption and the black precipitate formation, the solution was decanted and the precipitate was dried for analysis.

2.5. Analytical Methods

The determination of Eh and pH values was carried out in situ using a pH-meter ionomer “ANION-4100” (ANION, Novosibirsk, Russia, “https://anion.nt-rt.ru/en (accessed on 1 August 2023)”) with an electrode combination. Anion and cation concentration were measured by the CGE Capillary electrophoresis system Capel-105M, (LUMEX instruments, Saint-Petersburg, Russia, “https://www.lumex.ru (accessed on 1 August 2023)”). The measurement error did not exceed 2%. The concentration of uranium and other elements in solutions was measured using the ICP-MS Agilent 7800 ICP-MS analyzer (Agilent Technologies, Santa Clara, CA, USA). The measurement error did not exceed 10%.
Micromorphology study was carried out with the scanning electron microscope (SEM) TESCAN MIRA 3 LMU “https://www.tescan.com) (accessed on 1 August 2023)” at the Analytical Center for Multi-elemental and Isotope Research of SB RAS. The samples were air-dried and then fixed on the conductive tape. To eliminate the charging effect, they were coated with graphite. The samples were studied in the secondary electrons’ mode, with an accelerating voltage of 30 kV. Energy dispersive X-ray spectroscopy (Oxford Instrument X-Max 80 EDS-system, Oxford Instruments plc, Abingdon, Oxon, UK “https://www.oxinst.com (accessed on 1 August 2023)”) was used for microanalysis of solid phases observed by SEM. The measurement error did not exceed 7%.

3. Results

3.1. Geological, Hydrogeological, and Hydrogeochemical Characteristics of Sludge Pond Sites

According to the technological profile, the studied plants fall into several units of the fuel-nuclear cycle: (1) PJSC Novosibirsk Chemical Concentrates Plant (NCCP)—UO2 conversion and production of fuel powders and pellets; JSC Chepetsk Mechanical Plant (ChMP)—production of uranium metal and sublimate production, polymetal production; JSC Angarsk Electrochemical Plant (AECC) and JSC Zelenogorsk Electrolysis and Chemical Plant (ECP)—separation plants. Facilities use a similar pattern for liquid waste removal; acidic highly mineralized solutions are neutralized with lime slurry (a solution of Ca(OH)2) followed by the discharge of neutralized solutions into subsurface storages. In this case, suspended particles are precipitated and some of the neutralized solutions mix with groundwater, infiltrating the underlying deposits through the bottoms and walls of the sludge repositories. In the process of the acidic tails’ neutralization, the solution quickly becomes supersaturated with respect to calcite, gypsum, dolomite, and barite. If the initial solutions contain high concentrations of fluoride ion, then during neutralization there is an active formation of fluorite (CaF2), which in some cases can form the bulk of the waste. In addition to the listed simple compounds, complex salts also precipitate from the solution. The X-ray phase analysis showed the presence of ettringite (Ca6Al2(SO4)3(OH)12•26H2O); voltaite (K2Fe+25Fe+34(SO4)12•18H2O); paraalumohydrocalcite (CaAl2(CO3)2(OH)4x6H2O); sodium aluminum sulfate (sodiumalum) (NaAl(SO4)2•12H2O); rapidcreekite Ca2(CO3)(SO4)•4H2O), etc. Despite the initially high concentrations of nitrate ion and, in some cases, chloride ion, due to the high solubility, nitrates and chlorides do not precipitate and migrate with the liquid phase [24].
Highly mineralized solutions entering the underlying deposits interact with groundwater, in which extended pollution halos have formed over decades. Apart from acid anions, water can have an increased content of uranium and heavy metals. The content of uranium in waters depends on their redox potential; under the reducing conditions, uranium changes to a four-valent form and precipitates from solutions. The nitrate ion is a strong oxidizer and increases Eh in waters to +300–+400 mV; uranium is therefore in hexavalent form, which prevents its precipitation on clays and organics. As shown earlier under conditions of nitrate contamination, the main form of uranium in a solution is mobile uranyl-carbonate complexes [25].
NCCP is one of the world’s top-ranked plants of nuclear fuel for nuclear power plants and research reactors in Russia and foreign countries. The NCCP sludge collector is located at the top of the natural catchment, sealed by an artificial dam mainly composed of loams. Filter-type tailing pond: technogenic solutions from the sludge storage are partially disposed of through the dam and enter the surface runoff, and, partially, water is disposed of through the bottom and walls to enter the first aquifer. After mixing with groundwater that comes from local watersheds, polluted water migrates northward followed by discharge into the same valley [26]. The thickness of the aquifer is non-persistent, varying from 1 to 5 m; water-bearing rocks dominate the sandy loam and sand of quartz-feldspar composition. The aquifer is covered by a layer of loams of variable thickness from 10 (background point on watersheds) to 3–4 in (in areas along the coastal line) The aquifer is unconfined in watersheds and becomes confined in lower areas. The aquifer recharge is by precipitation.
ECP is one of the world’s largest uranium enrichment facilities. Its sludge collectors are located on the watershed of the Kan and Syrgil rivers [14] and groundwater runoff flows in two opposite ways. Filter-type sludge storage consists of two buried basins into which wastes are disposed. The volume of disposed water prevents the formation of dry shores; however, a layer of clarified solutions is not formed. The volume of precipitation at the site of the sludge collector is 425 mm/year, which is almost twice as much as evaporation. All runoff infiltrates the underlying aquifer. The aquifer is unconfined and discontinuous comprising interlayers of sandstone, sandy loam, and light clay. The thickness of the aquifer is 2–3 m, and water-bearing rocks are dominated by sandy loam and sands of quartz-feldspar composition. The aquifer is overlain by a layer of variable-thickness loams from 10 (background point on watersheds) up to 3–4 in valleys (in areas along the coastline). The aquifer is unconfined in watersheds and becomes confined in lower areas; the aquifer is fed by precipitation.
At the time of the construction, AECC was one of the largest uranium recovery facilities in the USSR; currently, the plant is under closure. The tailing pond is located on the gentle watershed of the Angara River and its tributary Kitoi. The adjacent areas are heavily flooded and wetlands are widespread in the direction of runoff even at a distance of a kilometer from the disposal site and to the Angara floodplain. During construction, the bottoms and walls of the storages were sealed from water. Until 1985, the technological design assumed the flow of slurry into sludge cells with the further discharge of the clarified part of the water after drainage into the environment. Later, technological design was modified, which significantly reduced water consumption; at present, the discharge has been reduced due to a decline in production. Currently, the clarified slurry is partially evaporated, but the main part, despite the asphalt concrete hydraulic seal of the walls and the bottom of the cells, falls into subsurface runoff. The unconfined aquifer is located at a depth of 2–6 m. Water-bearing rocks dominate the fine- and medium-grained sands. From the top, the aquifer is isolated from the atmosphere by a layer of soil; atmospheric precipitation is the source of aquifer recharge.
ChMP was engaged in the production of uranium fluorides and uranium metal. “Tailing pond No. 1” is located on the boggy floodplain terrace I of the Cheptsa River. This is a flatland bulk storage with a natural watertight seal of 3.0 m thick alluvial loam intercalated with sandy loam, sand, and peat. At present, the tailing pond has been partially deactivated (out of operation from 2008 to 2016) [27]. Host rocks contain the alluvial Middle, Upper Pleistocene, and Holocene undivided sediments. They have a three-layered structure: the top of the section is composed of brown, light, sandy, and plastic clays and dark gray, clayey silt with organic matter impurity loams; in the middle part of the section there are sandy loams and sands (from silt to medium) intercalated with loam and inclusions of gravel and pebbles; the bottom is dominated by gravel sands, gravel, and pebbles. The total thickness of the deposits is 10–15 m. The first aquifer is from 3 to 6 m thick and comprises sandy and gravel-pebble alluvial deposits; it recharges by the infiltration of atmospheric precipitation and groundwater coming from the elevated northeastern margin. The groundwater flows in the sludge storage site in the northeast direction, the drainage trench located north of the repository is the disposal area, and the groundwater close to the trench flows in the western direction towards the Cheptsa River, the regional discharge area [27].

3.2. Chemical Composition of Groundwater

Background water is calcium and calcium-magnesium bicarbonate, slightly alkaline with mineralization of 0.3–0.9 g/L for all sites. Depending on the solutions coming from the sludge collectors, the mineralization in the mixing area reaches 10–20 g/L due to nitrate- sulfate- and, to a smaller degree, chloride ion. Bicarbonate ion becomes minor; in individual samples, when pH shifts to the main region, a carbonate ion appears. Among cations, the content of calcium and sodium increases the most significantly (Figure 1).
AECC. The background water of the site is calcium, magnesium bicarbonate (Table 1, Figure 1), and changes to nitrate-sulfate sodium with a mineralization of up to 9 g/L due to the influence of the sludge storage. The background well is located on the watershed and is characterized by positive Eh in the dilution area, suggesting the possible supply of oxygen with surface runoff. Groundwater dilution occurs at a distance of the first hundreds of meters. In this area, the lowest uranium concentrations are below 1 μg/L [14].
ECP. The background water of the site is calcium and magnesium bicarbonate (Table 1, Figure 1); due to the influence of the sludge storage, it changes to nitrate calcium with mineralization of up to 20 g/L. The background well is characterized by positive Eh values, which indicates the possible supply of oxygen with surface runoff. In the area affected by the sludge pond, an increase in Eh may be associated with a high concentration of NO3 [28]. Notable dilution of groundwater occurs at a distance of the first tens of meters. This site, in contrast to other areas, has a considerable predominance of nitrates, which are higher than 90% from anionic mineralization. Chloride ion is in a negligibly small concentration in the water.
NCCP. The background water of the area is calcium, magnesium bicarbonate (Table 1, Figure 1), and its composition changes to sulfate-nitrate calcium-sodium with mineralization of up to 15 g/L due to the influence of the sludge pond. Negative Eh values in the watershed (background point) and in the dilution zone suggest difficult oxygen access, and high NO3 concentration is responsible for a noticeable increase in Eh in the background point [28]. Significant dilution of groundwater occurs at a distance of the first tens of meters. In contaminated areas, the predominant anion can change, since in the site with maximum pollution nitrates dominate, and in water interacting with sediment containing mainly gypsum, sulfates are higher than 50%.
ChMP. The background water of the area is sodium, calcium bicarbonate (Table 1, Figure 1), and becomes nitrate sodium-calcium with a mineralization of up to 16 g/L affected by the sludge storage. The background well is placed on a boggy floodplain and has negative values of Eh. The dilution of groundwater takes place at a distance of the first hundreds of meters; the decrease in concentration is mainly reached by the diluting of technogenic water by natural water. The site is characterized by the highest ammonium ion concentrations of ~0.3 g/L.

3.3. Microbiological Characteristics of Groundwater

3.3.1. Analysis of Bacterial Abundance of the Main Physiological Groups

Bacterial cell abundance of the main physiological groups determined by the method of inoculation on selective nutritive media (Vinogradsky method, [29]) is given in Figure 2. The maximum number of aerobic organotrophic bacteria was found in almost all samples. There was an increase in the number of denitrifying, sulfate-reducing, and aerobic bacteria in samples taken from the moderate pollution zone. The number of iron reducers in the moderately contaminated samples did not exceed 100 cells/mL. In all cases, except for ChMP, the number was the maximum in unpolluted sites. Samples taken from areas with high pollution showed a decrease in the number of aerobic organotrophic bacteria, especially for ChMP, since ammonium pollution is common for groundwater, apart from nitrate. It is worth mentioning that in the NCCP samples, the number of sulfate-reducing bacteria was maximum in the high-pollution area. At the same time, the number of denitrifiers in highly contaminated samples of ECP and NCCP exceeded that in the background samples.
Since the pollution of four objects was controlled by several parameters (nitrate, ammonium, and sulfate), an analysis of the main components was carried out (Figure 3) for the relationship between the values of the number of individual groups and the type of pollution. Based on the analysis, it can be noted that the number of operational taxonomic units (OTU) and the abundance of iron-reducing bacteria are distributed in the sites of the lowest pollution. In the area with a high ammonium concentration, no distribution of certain groups of bacteria was established due to its high toxicity. Distribution of aerobic and denitrifying bacteria was identified in the areas with moderate pollution, and in the highly contaminated sites, a distribution of nitrifying and sulfate-reducing bacteria was noticed.
The identification of common relationships between a number of denitrifying and sulphate-reducing bacteria and pollution levels shows the potential for microbiological removal of nitrate for all studied sites.

3.3.2. Microbial Diversity Analysis Using 16S rRNA Gene Sequence Analysis

When assessing phylogenetic diversity by analyzing 16S rRNA gene sequences in groundwater samples, physiologically diverse microbial communities capable of geochemical cycles of nitrogen, sulfur, and iron were found, and patterns of variation in microbial diversity were revealed, depending on the level of pollution. In samples taken from all uncontaminated areas (Figure 4a), representatives of the genes Comamonadaceae, Rhodocyclaceae, Rhodobacteraceae, Burkholderiaceae, Pseudomonadaceae, Gallionellaceae, Prevotellaceae, and Desulfovibrionaceae were found. In the ChMP L sample, there was the dominance of the Sulfuricellacea, Rhodobacteracea, and Burholderiaceae bacterial genes. The AECC L sample was found to be dominated by Rhodocycaceae and Pseudomonadaceae genes. At the same time, according to the Shannon and Simpson indices, these samples have inherent high diversity due to minor components.
Moderately contaminated ChMP samples were dominated by anammox bacteria of the genes Brocadiaceae and Scalinduaceae, nitrifying Nitrosomonadaceae and iron oxidizers Acidiferrobacteraceae. Moderately polluted AECC samples were dominated by denitrifying bacteria of the genes Comamonadaceae, Xhantobacteracea, Alcaligenaceae, sulfur-oxidizing Sulphuromonadaceae, and iron-oxidizing Galionellaceae. The prevalence of sulfur reducers of the genes Desulfovibrionaceae and actinomyces capable of reduction and oxidation, depending on the conditions of nitrogen compounds Nocardiaceae, was recorded in the moderately contaminated ECP sample. The moderately contaminated NCCP sample was dominated by denitrifying bacteria of the gene Pseudomonadaceae family, sulfur-reducing genes Desulfitobacteraceae, and organotrophic bacteria of the gene Bacillaceae capable of denitrification and sulfate reduction.
In the highly polluted AECC samples, the denitrifying bacteria of the genes Pseudomonadaceae Xanthomonadaceae and Acaligenaceae dominate. In the highly polluted ChMP samples, genes Idiomarinaceae and Methilococaccea were identified according to the KEGG database, which are not intensively involved in sulfur, iron, and nitrogen cycles. Generally, there were few representatives of genes capable for denitrification (the contribution of Comamonadaceae, Xhantobacteracea Acaligenaceae was below 5% OTU). No sulphate-reducing microorganisms were detected. This sample has a high concentration of ion and ammonium nitrate. For the highly contaminated ECP sample, 64% of Desulfovibrionacea sulfate reducers and 17.5% of Nocardiaceae nitrogen cycle bacteria were detected. The highly contaminated NCCP sample was dominated by sulfur oxidizers Sulfurimonadacea and denitrifiers of the genes Pseudomonadaceae, Xantomonadaceae and Commamonadacea.
The analysis of the diversity in microbial community using Shannon and Simpson indices showing overall diversity and evenness of community composition in Figure 5 indicated that only in the AECC sites of lowest pollution the maximum bacterial biodiversity was observed; in the areas of moderate pollution, both parameters decreased, and in the highly polluted zone, they increased significantly. It is interesting to note that for the background AECC sample, according to the indices, the microbial community was characterized by diversion and evenness; for the ECP samples, the diversity was slightly lower, and the evenness was significantly lower than those in the background AECC samples. The maximum values of diversity and evenness were common for the background NCCP samples.
For samples from the uncontaminated area of ECP, the maximum diversity was found, while in the sites of moderate and maximum contamination, diversity decreased, being at the same level for those from the highly contaminated and moderately contaminated areas. This is probably due to high concentrations of nitrate ions contributing to the development of certain dominant groups.
For NCCP, the maximum values of the Shannon and Simpson indices were recorded for samples from the area with minimal pollution; in the site with moderate pollution, there was a decrease in diversity due to the dominance of certain bacterial groups (a decrease in the Simpson index), while in the sites with a high content of nitrate ions, in this case, a significant increase was observed in the diversity of bacteria not exceeding background values.
For ChMP, a trend of maximum values of the diversity index in the unpolluted site remains; with an increase in pollution, there is a trend of a decrease in diversity from a sample from a moderately contaminated zone to a sample from a highly contaminated zone.
The minimum values of the Shannon diversity index were established for the AECC, ECP, and NCCP samples of moderate pollution and the ChMP samples with high pollution. In the highest contaminated NCCP samples, as well as in the background samples of AECC and NCCP, a peak value of the Shannon index was found. It is important to note a greater decrease in the Simpson index than the Shannon index, suggesting community evenness reduced by increasing the contribution of dominant groups. In our opinion, a higher diversity index indicates a higher resistance of the microbial community to changing environmental parameters, and therefore, of the greater efficiency of these communities for cleaning activities. Cleaning in areas with low microbial diversity will occur at lower rates.

4. Experimental Groundwater Purification

Laboratory modeling of biological processes in the formation of water samples was carried out by adding electron donors and carbon sources (whey) to the samples and their fermentation at room temperature. A total of 100 mL of formation fluid was sealed in leakproof bottles with the initial air gas phase. Sampling for analysis was performed every 5–7 days. The experiment was carried out before the complete dissolution of nitrate and sulfate ions. A detailed description of the purification experiments is given in the works [7,9,18].
Whey was the source of the carbon and electron donor. As our previous studies show, this substrate is the most optimal for stimulation containing rapidly and slowly oxidizable compounds necessary for a proportional rate of nitrate removal and preventing significant accumulation of nitrite, potassium, as well as phosphates [7,9,18,31]. During the decrease of redox potential, uranium is recovered from UO22+ to UO2+, while it precipitates together with phosphates and sulfates [9].
In all cases, water was purified during the experiment in two stages: the first was the nitrate removal, and after that, the sulfate reduction and the sulfate-to-sulfide transition began. The process time depended on the mineralization of the initial solution. In samples with high mineralization, anaerobiosis formed for a long time (Table 2, Figure 6).
Figure 7 illustrates SEM images of newly formed mineral phases caused by denitrification and sulfate reduction. As Table 3 shows, regardless of the presence of mineral particles in the aquifer rock, particles with elevated uranium and phosphorus contents are formed. At the next stage, as a consequence of sulfate reduction, a sulfide phase precipitates with higher content of sulfur, iron, and uranium [18]. The size of individual particles can reach 150 µk; with the presence of a mineral substrate, biogenic neoformations fill the pores between aluminosilicate particles, and in some cases, are completely covered by mineral grains [7]. Therefore, migration in the form of suspended solids for this type of particle is practically not detected. Our previous experiments [32] show that the aggregation of ferric and clay particles due to the microbial processes reduces the risk of pseudo-colloidal transport of actinides.
It is important to note the high iron content in phase 1. In one of our previous works [33], we accessed the role of biogenic ferric phases in actinide immobilization and showed an important role played by ferric amorphous biogenic phases in this process (see also [34,35]).

5. Discussion

The long-term influence of sludge collectors has completely modified the chemical, hydrogeological, and microbiological conditions in the adjacent areas. However, despite the similar impact on the ecological situation, each collector has its own individual characteristics, consisting both in mineralization, the composition of sludge and its volume, and in the natural conditions of the host sites (geomorphological position, thickness and protection of aquifers, composition of background groundwater and etc.). Laboratory studies have shown that by adding a source of organic matter and phosphorus, activation of the microbial community can contribute to the removal of nitrate and lead to the formation of biogenic mineral phases, which promote the immobilization of uranium. Three groups of factors will be most important for groundwater and surface water remediation: hydrochemical, geological, and hydrogeological, as well as microbiological.

5.1. Microbiology

Based on our studies, organotrophic bacteria of reducing branches of nitrogen and sulfur cycles were found in all samples taken from formation water in the polluted area of four facilities. These bacteria should primarily be used in the removal of nitrogen compounds.
There is also a significant difference in the abundance of certain physiological groups and the diversity of communities. The series of Figure 8 shows the SSA diagrams, which make it possible to track the relationship between representatives of certain genes and dominant pollution factors. Therefore, according to their position in SSA diagram, an increase in Comamonadaceae, Rhodocyclaceae, Pseudomonadaceae, Xanthomonadaceae, Oxalobacteraceae, and Alcaligenaceae abundance is associated with high uranium, sulfate, and nitrate contamination. For AECC, with NO3, NH4, and SO4 contamination, there is a coordination between the representatives resistant to nitrogen pollution (Nitrosomonadaceae, Xanthomonadaceae, Rhodobacteraceae) and high salt content (Alcaligenaceae). Moreover, sulfur cycle bacteria are associated with the background sample. Representatives of bacterial genes capable of reducing nitrate Alcaligenaceae, Xanthomonadaceae, Rhodobacteraceae, as well as genes of sulfur-oxidizing bacteria Sulfurimonadaceae are associated with a high level of NCCP contamination. The largest number of sulfur cycle bacteria associated with the moderate pollution level is seen on the ChMP diagram. Rhizobiaceae, Moraxellaceae, Oxalobacteraceae, and Corynebacteriaceae capable of nitrate reduction are associated with high pollution levels.
Representatives of sulfate-reducing bacteria of the gene Desulfovibrionaceae are associated with moderate contamination levels, including sulfate, in diagrams drawn for microbiomes from AECC, ChMP, and ECP. Representatives of iron-oxidizing bacteria of the Gallionellaceae gene correlate with the background samples at all objects. Representatives of the Planctomycetota phylum, which includes anammox bacteria, are found in the background wells of ChMP, ECP, and NCCP. In the SSA diagram of ECP samples, there is a significant discrepancy in the background sample in reference to located nearby and practically mixed samples with a moderate and high contamination level.
It is important to note the presence of bacteria in the microbial communities of the reducing branch of the nitrogen cycle capable of both dissimilative and assimilative reduction of nitrate, primarily among organotrophic bacteria of the genes Xanthomonadaceae, Rhodobacteraceae, Alcaligenaceae, and Pseudomonadaceae. Only dissimilative reduction of nitrate at its high initial concentrations can lead to the accumulation of nitrite, which is more toxic than nitrate, and reduce or stop microbial processes [31]. For the sites with a high level of ammonium-nitrate pollution (for example, ChMP), bacteria of the genes Rhizobiaceae, Moraxellaceae, Oxalobacteraceae, and Corynebacteriaceae, also capable of reducing nitrate, were found. In the highly polluted samples, the reduction of nitrate was much slower. Based on the results of the comparison of four objects, it can be concluded that in all cases a physiologically diverse microbial community is present in groundwater, including bacteria of the nitrogen, sulfur, and iron cycle. Generally, a similar pattern of dominance of organotrophic bacteria of the nitrogen cycle of the Nitrosomonadaceae, Xanthomonadaceae, Rhodobacteraceae, Alcaligenaceae, and Pseudomonadaceae genes was noticed in the contaminated areas for all objects. Representatives of Rhizobiaceae, Moraxellaceae, Oxalobacteraceae, and Corynebacteriaceae capable of nitrate reduction are associated with the areas with high levels of ammonium-nitrate contamination (for example, ChMP). Representatives of the Planctomycetota phylum, which includes anammox bacteria, were found in the background wells of ChMP, ECP, and NCCP, while only for ChMP were they found in the samples from sites with moderate contamination. Bacteria of this group have potential in terms of purification from ammonium since they do not require organic additives to activate them [36,37].
Notable differences have been identified with respect to sulfur cycle bacteria. For NCCP and AECC, representatives of sulfate reducers are present mainly in the background samples, and in pollution areas, their contribution is reduced, as compared to bacteria capable of reducing sulfur by the assimilative way. For the ECP samples, there is a high content of dissimilative sulfate reducers in the samples with severe pollution. Bacteria of the iron cycle are mostly distributed in uncontaminated samples and their abundance decreases with pollution.
The lowest total score demonstrating areas where purification can slowly occur is characteristic of the areas with high nitrate, low nitrogen and sulfur cycle bacteria, and low microbial diversity (ECP max and ChMP max) (Table 4).
An important condition for successful purification is, therefore, a variety of microbial communities comprising the bacteria of the reducing branches of the nitrogen and sulfur cycles. Bioremediation should be carried out in areas where the bacterial abundance of these groups is not significantly reduced.

5.2. Hydrochemistry

Chemical composition of groundwater for operating facilities depends primarily on the volume, regime of injection in the sludge collector, and chemical composition of disposed solutions. Excessive mineralization inhibits all the bacterial groups studied, and the optimal value for this parameter is in the range of 3–10 g/L. Different anions have different degrees of influence on the process rate. Thus, nitrate ions and ammonium ions have the greatest toxic effect. High concentrations of sulfate bicarbonates and chlorides are expected to have no significant impact. Figure 7 and Figure 8 show the required time for denitrification and complete purification, including denitrification and sulfate reduction as a function of the solution’s TDS. It can be seen that for the interval of 15–20 g/L, the total cleaning time is over 200 days, and for a sample with a mineralization of more than 20 g/L, it increases to almost 400 days.
The anionic composition of pollutants is also very important. Based on the laboratory experiments, the concentration of nitrate ions should be below 5 g/L; in the case of a higher concentration, the rate of removal of nitrate ions and reduction of sulfates is greatly decreased.
The presence of carbonate ions in the composition of pollutants in groundwater will rather have a positive effect on the efficiency of nitrate removal since they can contribute to the development of lithotrophic microflora using carbonates as a carbon source. The purification efficiency will be affected by pH values, which should be in the range of 6–8. More alkaline conditions can lead to the transition of NH4+ to NH3, and the latter is a strong toxicant. At the same time, more acid conditions will prevent the development of microflora [38,39].
Biological processes require the presence of the necessary biogenic elements (P, K, N, and S) in a solution. Given the initial nitrate-sulfate nature of pollution, sulfur and nitrogen are in excess. Potassium, being a chemical analog of sodium, is also usually in excess in water. In addition to technogenic solutions, host rocks can be the source of potassiumillites or potassium-feldspars. A barrier for the development of microbial processes may be the content of phosphorus, which is rarely used in technological processes; therefore, it is often non-available. An extra effect of phosphate addition will be the formation of poorly soluble phosphate-uranium phases, which promote uranium immobilization [40].

5.3. Geology and Hydrogeology

One of the most important conditions for successful in situ purification is geological and hydrological parameters depending on the filtration properties of host rocks and altimetric gradients. Therefore, sites with relatively homogenous conditions of groundwater migration should be identified for each facility. For each of them, it is necessary to determine the recharge and discharge areas of the aquifer, its thickness, and the rate of groundwater movement. In most cases of subsurface storage, the main recharge source of the first aquifer from the surface is due to meteoric precipitation. The major volume comes in spring during snowmelt, while the groundwater levels are maximum, and the water has the lowest mineralization. The maximum mineralization is provided by minimal levels and occurs in winter. The chemical composition of technogenic solutions is subjected to the natural background and, according to the ratio of natural and technogenic runoff components, seasonal fluctuations can be neutralized in the foreground and become close to the background with the distance from the sludge collectors. Due to the geomorphology of the site, the placement of sludge storages and the distribution of groundwater in distinct directions can differ substantially. For example, for the ECP repository located on a watershed with different slope steepness, nearly stagnant conditions with minimum rates in one direction are established, and rather dynamic conditions with a water movement rate of more than 2 m/day on the opposite slope exist.
The most straightforward situation is noted for stagnant water areas; in this case, when calculating, the initial mineralization and the volume of contaminated water in this area are sufficient [21]. More complex modeling may be required in the case of moving groundwater, the injection site will constantly be fed by new contaminated water, and stimulative additives will be moved out by the stream. In this case, the location of the injection wells should guarantee the supply of stimulating substances in such a way as to provide their required concentration in new portions of contaminated water. The hydrodynamic regime, which determines the time of water discharge, is a controlling limitation factor for this approach. Stimulating additives will become an additional source of pollution if the discharge of water occurs faster than the bacteria have time for its complete treatment.
For solutions with mineralization lower than 10 g/L, the bioremediation time is ~100 days (Figure 9 and Figure 10). According to a preliminary evaluation based on the available data on the dynamic regime of the aquifer, there are conditions for bioremediation in all studied areas, at least in certain directions. This suggests a technical capability to create biogeochemical barriers in all sludge storages. Only in one case, in the site of the steep slope and the relative proximity of the floodplain, the water moves from the collector to the floodplain for 85 days, but even there, the stimulation of microbiological processes significantly decreases the concentrations of nitrate and sulfate.

5.4. Technology

During in situ operations, the composition of solutions and the regime for injection must be ensured. At high nitrate concentrations, there should be not many rapidly consumed substrates, since with its active uptake there is a risk of accumulation of excessive nitrite content and ceasing the purification process [41,42]. In addition, the high content of easily consumed substrates poses risks of anaerobic organotrophic bacteria causing substrate fermentation and acidification due to the release of organic acids, which can lead to a decrease in the intensity of bioremediation. Excessive bacterial development can also induce the accumulation of biomass and its ammonification leading to the accumulation of ammonium. A possible solution is adding more complex substrates, for example, whey, which is also a source of phosphorus, potassium, and calcium. The injection may be fractional, for example, in the form of a three- to five-time gradual addition of substrate. In this case, sharp releases of nitrite and accumulation of excess in ammonium can be eliminated. The addition of calcium and phosphates can result in a decrease in the filtration properties of the aquifer, which will contribute to more efficient cleaning of sites at a high flow rate.

6. Conclusions

The laboratory experiments revealed that the activation of the microbial community by sources of soluble organic matter and phosphorus could be responsible for the formation of optimal geochemical conditions for the removal of nitrate into the gaseous phase and the immobilization of uranium in biogenic sediments. An important point for successful immobilization is the selection of the location of injection wells, which depends on the stream topology of polluted groundwater. Based on the comparison of the total microbial diversity, the most optimal will be areas with an average content of nitrate ions (2–3 g/L), where there is a trend to increase microbial diversity due to the input of nitrogen and sulfur sources.
To form biogeochemical barriers in certain areas, a number of conditions should be followed:
(A) Microbial composition. The presence of various bacteria in reducing branches of nitrogen and sulfur cycles is essential in groundwater. In areas with severe pollution, the number of microorganisms in these groups should not be significantly reduced.
(B) Water exchange rate. It is important to have time for bacteria for the complete dissolution of nitrate and sulfate before groundwater reaches the surface, otherwise, the injected nutritive solutions, when entering the aerobic conditions of surface streams, will contribute to the additional pollution.
(C) Chemical composition. Groundwater should be without elevated concentrations of biotoxicants, such as fluorine, ammonium, etc. Excess acidity or alkalinity will also hinder bacterial development.
(D) Composition of stimulating solutions is calculated based on stoichiometry in relation to nitrate, sulfates, and oxygen based on experimental data. The injection regime should be set to provide optimal development of microbial communities at existing pollution levels. While the facilities are in operation, the injection of reagents for the sustainable development of biogeochemical barriers should be performed with a frequency sufficient to convert the compounds to solid (U, S), as well as gaseous (N) phases. Depending on the conditions of discharge of contaminated solutions into sludge collectors, the rate of such injection can be from 3 to 12 months. The monitoring of the formed conditions should be carried out downstream of the observed wells. After decommissioning, these actions can be used for cleaning the adjacent landscapes; the rate and volume of injections are determined by the volume and disposition of the pollution area. Laboratory tests were confirmed by full-scale experiments at the facility sites after whey injection into the aquifer that resulted in a decrease in Eh after a month in the water, with a further decrease in nitrate ions.

Author Contributions

Conceptualization, A.B. and A.S.; methodology, A.S. and N.P.; validation, N.P. and O.S.; fieldwork, A.B. and A.S.; formal analysis, N.P.; writing—original draft preparation, A.B., A.S., N.P. and O.S.; writing—review and editing, A.B., A.S., N.P. and O.S.; visualization and supervision, A.B. and A.S. All authors have read and agreed to the published version of the manuscript.

Funding

The study was supported by the Russian Science Foundation grant No. 23-27-00362, https://rscf.ru/en/project/23-27-00362/ (accessed on 1 August 2023).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

This study was performed using the equipment of the Core Facilities Center of IPCE RAS (CKP FMI IPCE RAS) and a program of Ministry of Science and Higher Education of the Russian Federation.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Othmane, G.; Allard, T.; Morin, G.; Selo, M.; Brest, J.; Llorens, I.; Chen, N.; Bargar, J.R.; Fayek, M.; Calas, G. Uranium association with iron-bearing phases in mill tailings from Gunnar, Canada. Environ Sci. Technol. 2013, 47, 12695–12702. [Google Scholar] [CrossRef]
  2. Liu, B.; Peng, T.; Sun, H.; Yue, H. Release behavior of uranium in uranium mill tailings under environmental conditions. J. Environ. Radioact. 2017, 171, 160–168. [Google Scholar] [CrossRef]
  3. Yin, M.; Sun, J.; Chen, Y.; Wang, J.; Shang, J.; Belshaw, N.; Shen, C.; Liu, J.; Li, H.; Linghu, W.; et al. Mechanism of uranium release from uranium mill tailings under long-term exposure to simulated acid rain: Geochemical evidence and environmental implication. Environ. Pollut. 2019, 244, 174–181. [Google Scholar] [CrossRef] [PubMed]
  4. Fuhrmann, M.; Benson, C.H.; Likos, W.J.; Stefani, N.; Michaud, A.; Waugh, W.J.; Williams, M.M. Radon fluxes at four uranium mill tailings disposal sites after about 20 years of service. J. Environ. Radioact. 2021, 237, 106719. [Google Scholar] [CrossRef] [PubMed]
  5. Harries, J.; Levins, D.; Ring, B.; Zuk, W. Management of waste from uranium mining and milling in Australia. Nucl. Eng. Des. 1997, 176, 15–21. [Google Scholar] [CrossRef]
  6. Linge, I. Special Radioactive Wastes; SAM Poligrafist Ltd.: Moscow, Russia, 2015; pp. 85–190. (In Russian) [Google Scholar]
  7. Neves, O.; Matias, M.J. Assessment of groundwater quality and contamination problems ascribed to an abandoned uranium mine (Cunha Baixa region, Central Portugal). Environ. Geol. 2008, 53, 1799–1810. [Google Scholar] [CrossRef]
  8. Salminen, J.M.; Petäjäjärvi, S.J.; Tuominen, S.M.; Nystén, T.H. Ethanol-based in situ bioremediation of acidified, nitrate-contaminated groundwater. Water. Res. 2014, 63, 306–315. [Google Scholar] [CrossRef]
  9. Wu, W.M.; Carley, J.; Fienen, M.; Mehlhorn, T.; Lowe, K.; Nyman, J.; Luo, J.; Gentile, M.E.; Rajan, R.; Wagner, D.; et al. Pilot-scale in situ bioremediation of uranium in a highly contaminated aquifer. 1. Conditioning of a treatment zone. Environ. Sci. Technol. 2006, 40, 3978–3985. [Google Scholar] [CrossRef]
  10. Francis, A.J.; Nancharaiah, Y.V. In situ and ex situ bioremediation of radionuclide-contaminated soils at nuclear and norm sites. In Environmental Remediation and Restoration of Contaminated Nuclear and Norm Sites; Velzen, L.V., Ed.; Series in Energy; Woodhead Publishing: Sawston, UK, 2015; pp. 185–236. [Google Scholar] [CrossRef]
  11. Cleary, A.; Lloyd, J.R.; Newsome, L.; Shaw, S.; Boothman, C.; Boshoff, G.; Atherton, N.; Morris, K. Bioremediation of strontium and technetium contaminated groundwater using glycerol phosphate. Chem. Geol. 2019, 509, 213–222. [Google Scholar] [CrossRef]
  12. Xu, M.; Wu, W.M.; Wu, L.; He, Z.; Van Nostrand, J.D.; Deng, Y.; Luo, J.; Carley, J.; Ginder-Vogel, M.; Gentry, T.J.; et al. Responses of microbial community functional structures to pilot-scale uranium in situ bioremediation. ISME J. 2010, 4, 1060–1070. [Google Scholar] [CrossRef]
  13. Alessi, D.S.; Lezama-Pacheco, J.S.; Janot, N.; Suvorova, E.I.; Cerrato, J.M.; Giammar, D.E.; Davis, J.A.; Fox, P.M.; Williams, K.H.; Long, P.E.; et al. Speciation and reactivity of uranium products formed during in situ bioremediation in a shallow alluvial aquifer. Environ. Sci. Technol. 2014, 48, 12842–12850. [Google Scholar] [CrossRef]
  14. Boguslavsky, A.E.; Gaskova, O.L.; Naymushina, O.S.; Popova, N.M.; Safonov, A.V. Environmental monitoring of low-level radioactive waste disposal in electrochemical plant facilities in Zelenogorsk, Russia. Appl. Geochem. 2020, 119, 104598. [Google Scholar] [CrossRef]
  15. Safonov, A.V.; Andryushchenko, N.D.; Ivanov, P.V.; Boldyrev, K.A.; Babich, T.L.; German, K.E.; Zakharova, E.V. Biogenic factors of radionuclide immobilization on sandy rocks of upper aquifers. Radiochemistry 2019, 61, 99–108. [Google Scholar] [CrossRef]
  16. Safonov, A.V.; Boguslavsky, A.E.; Gaskova, O.L.; Boldyrev, K.A.; Shvartseva, O.S.; Khvashchevskaya, A.A.; Popova, N.M.; Braga, S. Biogeochemical modelling of uranium immobilization and aquifer remediation strategies near NCCP sludge storage facilities. Appl. Sci. 2021, 11, 2875. [Google Scholar] [CrossRef]
  17. Safonov, A.V.; Boguslavskii, A.E.; Boldyrev, K.A.; Zayceva, L.V. Biogenic factors of formation of geochemical uranium anomalies near the sludge storage of the Novosibirsk Chemical Concentrate Plant. Geochem. Int. 2019, 57, 709–715. [Google Scholar] [CrossRef]
  18. Nazina, T.N.; Safonov, A.V.; Kosareva, I.M.; Ivoilov, V.S.; Poltaraus, A.B.; Ershov, B.G. Microbiological processes in the Severnyi deep disposal site for liquid radioactive wastes. Microbiology 2010, 79, 528–537. [Google Scholar] [CrossRef]
  19. Safonov, A.V.; Perepelov, A.V.; Babich, T.L.; Popova, N.M.; Grouzdev, D.S.; Filatov, A.V.; Shashkov, A.S.; Demina, L.I.; Nazina, T.N. Structure and gene cluster of the O-polysaccharide from Pseudomonas Veronii A-6-5 and its uranium bonding. Int. J. Biol. Macromol. 2020, 165, 2197–2204. [Google Scholar] [CrossRef] [PubMed]
  20. Koch, A.L. Most probable numbers. In Methods for General and Molecular Bacteriology; Murray, R.G.E., Wood, W.A., Krieg, N.R., Eds.; American Society for Microbiology: Washingron, DC, USA, 1994; pp. 257–260. [Google Scholar]
  21. Postgate, J.R. The Sulphate-Reducing Bacteria; Cambridge University Press: New York, NY, USA, 1979; pp. 133–144. [Google Scholar]
  22. Adkins, J.P.; Cornell, L.A.; Tanner, R.S. Microbial composition of carbonate petroleum reservoir fluids. Geomicrobiol. J. 1992, 10, 87–97. [Google Scholar] [CrossRef]
  23. Daigger, G. Oxygen and carbon requirements for biological nitrogen removal processes accomplishing nitrification, nitritation, and anammox. Water Environ. Res. 2014, 86, 204–209. [Google Scholar] [CrossRef]
  24. Gaskova, O.L.; Boguslavsky, A.E. Groundwater geochemistry near the storage sites of low-level radioactive waste: Implications for uranium migration. Proced. Earth Planet. Sci. 2013, 7, 288–291. [Google Scholar] [CrossRef]
  25. Safonov, A.V.; Boguslavsky, A.E.; Boldyrev, K.A.; Gaskova, O.L.; Naimushina, O.S.; Popova, N.M. Geochemical modeling of the uranium behavior in groundwater near the sludge storages during bioremediation. Geochem. Int. 2021, 59, 56–65. [Google Scholar] [CrossRef]
  26. Boguslavskii, A.E.; Gas’kova, O.L.; Shemelina, O.V. Geochemical model of the environmental impact of low-level radioactive sludge repositories in the course of their decommissioning. Radiochemistry 2016, 58, 323–328. [Google Scholar] [CrossRef]
  27. Nalivaiko, K.A.; Skripchenko, S.Y.; Titova, S.M.; Semenishchev, V.S. Radioactive wastes from near-surface storage facility of uranium conversion production. J. Radioanal. Nucl. Chem. 2023, 332, 2499–2512. [Google Scholar] [CrossRef]
  28. Boguslavskii, A.; Gaskova, O.; Shemelina, O. Uranium migration in the ground water of the region of sludge dumps of the Angarsk Electrolysis Chemical Combine. Chem. Sustain. Dev. 2012, 20, 465–478. [Google Scholar]
  29. Gabriel, J. Development of soil microbiology methods: From respirometry to molecular approaches. JIMB 2010, 37, 1289–1297. [Google Scholar] [CrossRef]
  30. Roswell, M.; Dushoff, J.; Winfree, R. A conceptual guide to measuring species diversity. Oikos 2021, 130, 321–338. [Google Scholar] [CrossRef]
  31. Safonov, A.V.; Babich, T.L.; Sokolova, D.S.; Grouzdev, D.S.; Tourova, T.P.; Poltaraus, A.B.; Zakharova, E.V.; Merkel, A.Y.; Novikov, A.P.; Nazina, T.N. Microbial community and in situ bioremediation of groundwater by nitrate removal in the zone of a radioactive waste surface repository. Front. Microbiol. 2018, 9, 1985. [Google Scholar] [CrossRef]
  32. Safonov, A.; Lavrinovich, E.; Emel’yanov, A.; Boldyrev, K.; Kuryakov, V.; Rodygina, N.; Zakharova, E.; Novikov, A. Risk of colloidal and pseudo-colloidal transport of actinides in nitrate contaminated groundwater near a radioactive waste repository after bioremediation. Sci. Rep. 2022, 12, 4557. [Google Scholar] [CrossRef]
  33. Safonov, A.; Popova, N.; Boldyrev, K.; Lavrinovich, E.; Boeva, N.; Artemiev, G.; Kuzovkina, E.; Emelyanov, A.; Myasnikov, I.; Zakharova, E.; et al. The microbial impact on U, Pu, Np, and Am immobilization on aquifer sandy rocks, collected at the deep LRW injection site. J. Geochem. Explor. 2022, 240, 107052. [Google Scholar] [CrossRef]
  34. Sharp, J.O.; Lezama-Pacheco, J.S.; Schofield, E.J.; Junier, P.; Ulrich, K.U.; Chinni, S.; Veeramani, H.; Margot-Roquier, C.; Webb, S.M.; Tebo, B.M.; et al. Uranium speciation and stability after reductive immobilization in aquifer sediments. Geochim. Cosmochim. Acta 2011, 75, 6497–6510. [Google Scholar] [CrossRef]
  35. Zhong, L.; Liu, C.; Zachara John, M.; Kennedy Dave, W.; Szecsody James, E.; Wood, B. Oxidative remobilization of biogenic uranium(IV) precipitates: Effects of Iron(II) and pH. J. Environ. Qual. 2005, 34, 1763–1771. [Google Scholar] [CrossRef] [PubMed]
  36. Popova, N.; Vishnyakova, A.; Artemiev, G.; Sitanskaia, A.; Litti, Y.; Safonov, A. Biofilms of anammox bacteria on mineral carriers to establish a subterranean permeable barrier. Int. J. Environ. Sci. Technol. 2023, 20, 2159–2170. [Google Scholar] [CrossRef]
  37. Botchkova, E.; Vishnyakova, A.; Popova, N.; Sukhacheva, M.; Kolganova, T.; Litti, Y.; Safonov, A. Characterization of enrichment cultures of anammox, nitrifying and denitrifying bacteria obtained from a cold, heavily nitrogen-polluted aquifer. Biology 2023, 12, 221. [Google Scholar] [CrossRef]
  38. Chen, W.T.; Chen, K.F.; Surmpalli, R.Y.; Zhang, T.C.; Ou, J.H.; Kao, C.M. Bioremediation of trichloroethylene-polluted groundwater using emulsified castor oil for slow carbon release and acidification control. Water Environ. Res. 2022, 94, e1673. [Google Scholar] [CrossRef]
  39. Lacroix, E.; Brovelli, A.; Holliger, C.; Barry, D.A. Control of groundwater pH during bioremediation: Improvement and validation of a geochemical model to assess the buffering potential of ground silicate minerals. J. Contam. Hydrol. 2014, 160, 21–29. [Google Scholar] [CrossRef]
  40. Mehta, V.; Maillot, F.; Wang, Z.; Catalano, J.; Giammar, D. Effect of reaction pathway on the extent and mechanism of uranium (VI) immobilization with calcium and phosphate. Environ. Sci. Technol. 2016, 50, 3128–3136. [Google Scholar] [CrossRef] [PubMed]
  41. Shelobolina, E.S.; O’Neill, K.; Finneran, K.T.; Hayes, L.A.; Lovley, D.R. Potential for in situ bioremediation of a low-pH, high-nitrate uranium-contaminated groundwater. Soil Sediment Contam. 2003, 12, 865–884. [Google Scholar] [CrossRef]
  42. Van Nostrand, J.D.; Wu, L.; Wu, W.M.; Huang, Z.; Gentry, T.J.; Deng, Y.; Carley, J.; Carroll, S.; He, Z.; Gu, B.; et al. Dynamics of microbial community composition and function during in situ bioremediation of a uranium-contaminated aquifer. Appl. Environ. Microbiol. 2011, 77, 3860–3869. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Anion and cation composition of background and polluted water in the study sites.
Figure 1. Anion and cation composition of background and polluted water in the study sites.
Water 15 03020 g001
Figure 2. Abundance of bacteria of different physiological groups. Bacteria types: AIR—aerobic, DEN—denitrifying, SRed—sulfate-reducing, and FeRed—iron-reducing.
Figure 2. Abundance of bacteria of different physiological groups. Bacteria types: AIR—aerobic, DEN—denitrifying, SRed—sulfate-reducing, and FeRed—iron-reducing.
Water 15 03020 g002
Figure 3. PCA diagram of bacterial abundance distribution as a function of contamination level. L-low contamination: 1-AECC L, 4-ECP L, 7-NCCP L, 10-ChMP L; M-moderate contamination: 2-AECC M, 5-ECP M, 8-NCCP M; H-high contamination: 3-AECC H, 6-ECP H, 8-NCCP H, 11-ChMP M. Outstanding: 12-ChMP H.
Figure 3. PCA diagram of bacterial abundance distribution as a function of contamination level. L-low contamination: 1-AECC L, 4-ECP L, 7-NCCP L, 10-ChMP L; M-moderate contamination: 2-AECC M, 5-ECP M, 8-NCCP M; H-high contamination: 3-AECC H, 6-ECP H, 8-NCCP H, 11-ChMP M. Outstanding: 12-ChMP H.
Water 15 03020 g003
Figure 4. Diversity of dominant groups in samples of uncontaminated (a) and contaminated (b) groundwater samples at the gene scale.
Figure 4. Diversity of dominant groups in samples of uncontaminated (a) and contaminated (b) groundwater samples at the gene scale.
Water 15 03020 g004
Figure 5. Role of technogenic factor in the change of taxonomic diversity (Shannon index) and evenness (Simpson index) [30].
Figure 5. Role of technogenic factor in the change of taxonomic diversity (Shannon index) and evenness (Simpson index) [30].
Water 15 03020 g005
Figure 6. Changes in Eh, NO3, and SO4 concentrations during groundwater purification experiments. (a)-AECC, (b)-ECP, (c)-NCCP, (d)-ChMP.
Figure 6. Changes in Eh, NO3, and SO4 concentrations during groundwater purification experiments. (a)-AECC, (b)-ECP, (c)-NCCP, (d)-ChMP.
Water 15 03020 g006
Figure 7. BSE images of particles obtained from the experiments on microbial purification of groundwater (a) particle formed due to the purification of the NCCP water (experiment without solid phases); (b) a biogenic phase formed during the purification of the ChMP groundwater (experiment with the addition of aquifer-host aluminosilicate particles). The dots indicate the areas of composition determination. The spectra composition is presented in Table 3.
Figure 7. BSE images of particles obtained from the experiments on microbial purification of groundwater (a) particle formed due to the purification of the NCCP water (experiment without solid phases); (b) a biogenic phase formed during the purification of the ChMP groundwater (experiment with the addition of aquifer-host aluminosilicate particles). The dots indicate the areas of composition determination. The spectra composition is presented in Table 3.
Water 15 03020 g007
Figure 8. Canonical correspondence analysis (CCA) diagram showing the first two ordination axes and their correlation with significant environmental variables in the studied samples: (A) AECC; (B) ECP; (C) NCCP; (D) ChMP.
Figure 8. Canonical correspondence analysis (CCA) diagram showing the first two ordination axes and their correlation with significant environmental variables in the studied samples: (A) AECC; (B) ECP; (C) NCCP; (D) ChMP.
Water 15 03020 g008aWater 15 03020 g008b
Figure 9. Denitrification time vs. total water mineralization.
Figure 9. Denitrification time vs. total water mineralization.
Water 15 03020 g009
Figure 10. Denitrification and sulfate reduction time vs. total water mineralization.
Figure 10. Denitrification and sulfate reduction time vs. total water mineralization.
Water 15 03020 g010
Table 1. Chemical composition of groundwater at the study sites.
Table 1. Chemical composition of groundwater at the study sites.
PlantTypeEhpH;Cond∑CO3 SO42−ClNH4NO3FeCa2+NaMgK MnPSiU
mVmS/cm2HCO3, mg/Lmg/Lmg/Lmg/Lmg/Lmg/Lmg/Lmg/Lmg/Lmg/Lmg/Lmg/Lmg/Lmkg/L
AECCAECC L115
±2.3
7.39
±0.2
0.73
±0.01
96
±9.6
27
±1.3
6.5
±0.45
0.28
±0.03
0.98
±0.07
13.9
±0.7
34
±1.7
5.3
±0.26
18.3
±0.9
0.72
±0.04
0.41
±0.02
0.20
±0.01
7.5
±0.38
0.090
±0.005
AECC M136
±2.7
7.10
±0.2
2.35
±0.05
89
±8.9
1620
±81
49
±3.4
0.20
±0.02
45
±3.2
1.66
±0.08
299
±15
94
±4.7
120
±6.0
3.1
±0.15
0.07
±0.004
0.31
±0.02
7.1
±0.36
0.24
±0.012
AECC H34
±0.7
9.78
±0.2
9.4
±0.19
413
±41
3720
±186
350
±25
103
±10.3
2440
±171
3.3
±0.17
115
±5.8
1519
±76
5.0
±0.25
139
±7.0
0.81
±0.04
1.16
±0.06
1.27
±0.06
0.26
±0.013
ECPECP L−128
±2.6
7.35
±0.2
0.34
±0.01
267
±26
0.55
±0.03
1.6
±0.11
0.50
±0.05
0.80
±0.06
1.59
±0.08
78
±3.9
11.7
±0.6
25
±1.2
2.0
±0.1
1.12
±0.06
0.40
±0.02
5.7
±0.29
0.23
±0.012
ECP M90
±1.8
6.70
±0.2
1.86
±0.04
215
±22
143
±1.15
65
±4.6
17
±1.7
2330
±163
2.0
±0.1
602
±30
71
±5.5
60
±3.0
5.0
±0.25
0.73
±0.04
1.29
±0.06
5.5
±0.27
3.0
±0.15
ECP H94
±1.9
7.50
±0.2
20.3
±0.41
204
±20
800
±40
17
±1.2
68
±7
11,500
±805
15.4
±0.77
5340
±267
127
±6.4
120
±6.0
11.0
±0.55
2.16
±0.11
10.0
±0.5
7.0
±0.35
5.6
±0.28
NCCPNCCP L−71
±1.4
7.01
±0.2
0.88
±0.2
393
±39
24
±1.2
21
±1.5
1.0
±0.1
5.9
±0.41
5.26
±0.26
103
±5.2
12.4
±0.62
35
±1.7
1.83
±0.09
1.33
±0.07
0.53
±0.03
6.7
±0.34
2.0
±0.1
NCCP M−29
±0.6
6.51
±0.2
7.1
±0.14
151.00
±0.6
1920
±96
750
±53
1.1
±0.1
900
±63
3.5
±0.17
556
±28
563
±28
160
±8.0
8.9
±0.45
2.2
±0.11
0.47
±0.02
1.19
±0.06
0.86
±0.04
NCCP H57
±1.1
7.40
±0.2
15.9
±0.32
195
±20
590
±30
2984
±209
120
±12
4740
±332
2.7
±0.13
804
±40
2013
±101
72
±3.6
91
±4.5
2.5
±0.12
0.07
±0.003
4.9
±0.24
3422
±171
ChMPChMP L−70
±1.4
7.20
±0.2
0.71
±0.01
53.8
±54
21.4
±1.0
10.9
±0.8
7.8
±0.8
11.5
±0.81
1.40
±0.07
132
±6.6
100
±5.0
31
±1.5
16.5
±0.83
0.83
±0.04
0.010
±0.001
3.2
±0.16
0.01
±0.001
ChMP M162
±3.2
7.80
±0.2
8.9
±0.18
212
±21
1585
±79
1131
±79
88
±8.8
3460
±242
5.1
±0.26
1113
±56
1058
±53
29
±01.5
234
±11.7
1.04
±0.05
0.010
±0.001
12.4
±0.62
1.90
±0.095
ChMP H195
±3.9
6.50
±0.2
16.9
±0.34
319
±32
780
±39
2260
±158
292
±29
7100
±497
67
±3.4
2940
±147
1549
±77
76
±3.8
47
±2.4
2.4
±0.12
0.39
±0.02
19.7
±0.99
4930
±247
Table 2. Time for anaerobiosis formation and total purification (days), denitrification, and sulfate reduction rates (mg/L/day) in groundwater samples after milk whey addition in laboratory experiments, day.
Table 2. Time for anaerobiosis formation and total purification (days), denitrification, and sulfate reduction rates (mg/L/day) in groundwater samples after milk whey addition in laboratory experiments, day.
SampleTotal MineralizationInitial Nitrate
mg/L
Initial Sulfate
mg/L
Time for Anaerobiosis FormationDenitrification RateSulfate Reduction Rate Total Purification Time
AECC L0.731000 *500 *4250 ± 14.528 ± 1.712
AECC M2.351000 *16156200 ± 10.036 ± 2.030
AECC H9.383290824811127 ± 7.273 ± 4.575
ECP L0.341000 *200 *3200 ± 10.013 ± 0.90
ECP M1.8623341431493 ± 5.52.3 ± 0.340
ECP H20.2811,2003585062 ± 3.71.1 ± 0.3210
NCPP L0.881000 *3583143 ± 8.834 ± 2.07
NCPP M7.061124500 *5161 ± 9.07.4 ± 0.545
NCPP H15.86616917691282 ± 4.59.0 ± 0.6130
ChMP L0.711000 *500 *4200 ± 10.024 ± 1.514
ChMP M2.91000 *11807111 ± 6.08.7 ± 0.690
ChMP H16.9224023702525 ± 1.512.1 ± 0.8140
Note: * In water with low sulfate and nitrate concentrations, these anions were additionally injected to assess the purification potential of this water.
Table 3. Elemental composition of phases shown in Figure 7, %.
Table 3. Elemental composition of phases shown in Figure 7, %.
PointSiAlFeMgCaKUPS
13.0 ± 0.151.3 ± 0.199.4 ± 0.470.3 ± 0.02-2.1 ± 0.1432 ± 1.64.0 ± 0.21-
25.0 ± 0.251.10 ± 0.080.67 ± 0.05--2.6 ± 0.1836 ± 1.84.6 ± 0.230.22 ± 0.02
33.3 ± 0.160.86 ± 0.060.55 ± 0.04--3.0 ± 0.2142 ± 2.15.2 ± 0.260.26 ± 0.02
431 ± 1.69.9 ± 0.5--0.30 ± 0.0211.0 ± 0.55---
55.0 ± 0.251.10 ± 0.08--4.1 ± 0.3-13 ± 0.653.2 ± 0.160.10 ± 0.01
Table 4. Heat map of the main parameters (green is high score, yellow is medium, red is low). of sites for the purification and assessment of its possibility based on the sum of factors (last column). The purification score is calculated as the sum of the scores when ranking all factors on a scale of 1–5.
Table 4. Heat map of the main parameters (green is high score, yellow is medium, red is low). of sites for the purification and assessment of its possibility based on the sum of factors (last column). The purification score is calculated as the sum of the scores when ranking all factors on a scale of 1–5.
ObjectTDS NO3 SO4 NH4AIRDNSRShannonOTU DenOTU AnDenitrification RateSulfate Reduction RateDenitrification TimeSum
AECC mid AECC532515415054545rapidly
NCPP mid332511235041535rapidly
AECC max321325245035439rapidly
ECP mid422511332031431moderately
ChMP mid421324341131332moderately
NCPP max211311455022330moderately
ChMP max211155131113328slowly
ECP max111423232021123slowly
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Boguslavsky, A.; Shvartseva, O.; Popova, N.; Safonov, A. Biogeochemical In Situ Barriers in the Aquifers near Uranium Sludge Storages. Water 2023, 15, 3020. https://doi.org/10.3390/w15173020

AMA Style

Boguslavsky A, Shvartseva O, Popova N, Safonov A. Biogeochemical In Situ Barriers in the Aquifers near Uranium Sludge Storages. Water. 2023; 15(17):3020. https://doi.org/10.3390/w15173020

Chicago/Turabian Style

Boguslavsky, Anatoly, Olga Shvartseva, Nadezhda Popova, and Alexey Safonov. 2023. "Biogeochemical In Situ Barriers in the Aquifers near Uranium Sludge Storages" Water 15, no. 17: 3020. https://doi.org/10.3390/w15173020

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop