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Article

Variations of Soil Chemical Properties and Microbial Community around the Acid Reservoir in the Mining Area

by
Jing Guo
1,2,
Fengqin Xuan
1,
Deming Li
1,
Jiaquan Wang
2 and
Baichuan Zhang
3,*
1
School of Environmental and Chemical Engineering, Anhui Vocational and Technical College, Hefei 230009, China
2
School of Mechanical Engineering, Hefei University of Technology, Hefei 230009, China
3
School of Earth and Environment, Anhui University of Science and Technology, Huainan 232001, China
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(17), 10746; https://doi.org/10.3390/su141710746
Submission received: 25 July 2022 / Revised: 18 August 2022 / Accepted: 26 August 2022 / Published: 29 August 2022
Browse Figures
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Abstract

:
Acid Mine Drainage (AMD) is unique acidic wastewater produced in the process of iron mining and utilization. The soil and wetland contaminated by AMD in a mining area in Ma’anshan were studied in this paper. The physical and chemical characteristics and microbial community structure of the samples were analyzed to evaluate the resident soil pollution. The results showed that the soil around the acid reservoir was seriously polluted by metals such as Fe, Mn, Cd, and sulfate, and the loss of organic matter and total nitrogen was serious. With the increased distance between soil samples and the acid reservoir, the pollution degree of AMD decreased, the soil pH, organic matter and total nitrogen contents increased gradually, the soil microbial species increased slightly, and the diversity index increased. Bacillus, Lactococcus, and other bacteria with hydrolytic acid-producing functions accounted for more than 55.0% of the total bacterial community. Desulfuromonas, Desulfobulbus, and other genes involved in sulfur metabolism accounted for more than 24.0% of the total microbial community. In addition, Nitrosophaera, Nitrosopumilus, Methanoregula, and Methanosphaerula, which were involved in nitrogen cycling, were the dominant bacteria in the sampled soil. Our findings provide the basic data to support the mineral industry in China as well as for ecological functional evaluation based on species differences.

1. Introduction

The mining industry, i.e., iron ore, copper, and gold, has high economic value in many countries [1,2]. When the ore extraction is completed, the remaining material is transported to the landfill by the crushing and grinding process [3]. Because the residue reservoir is usually located near the mine, the geological features of the mine may produce acid drainage problems. Acid mine drainage (AMD) is a major and growing problem in the mining and mineral industry [4].
Minerals associated with pyrite commonly occur with chalcopyrite (CuFeS2) and pyrite (FeS2) [5]. In an oxidative reaction with oxygen, the product dissolves in water and produces AMD, which deteriorates the environment [6]. Exposure to the air of large amounts of waste rock and tailings containing sulfides and metal salts from mining processes contributes to increased rates of AMD production. The main source of contaminants for AMD is the oxidation of pyrite minerals. In addition, metals such as Mn, Zn, and Cd can be incorporated as solids into the pyrite structure.
Soil is a valuable, non-renewable resource that provides habitat for most species on Earth, produced as a vehicle for crops [7]. The research shows that the soil around the acid reservoir has been seriously polluted by heavy metal resources produced by human mining activities, causing damage to the local ecosystem [8,9,10,11]. The study of metal contamination and microbial effects in mining soil is an important indicator for evaluating soil quality in mining areas [12].
AMD enters surface water species. Its effects include biological impacts on river and lake organisms through direct toxic effects, changes in habitat caused by metal sediment, visual changes due to orange or yellow staining of river sediment, disruption of nutrient cycles, or other mechanisms [13,14]. High concentrations of sulfates and heavy metals are highly toxic to living things and difficult to restore to the ecological environment, which is not conducive to plant growth and other life activities [15,16,17,18]. The Iberian Pyrite Belt in southwestern Spain showed that about 4847 hectares of land were polluted by AMD. Considering the local average annual rainfall of 650 L/m2, nearly 31.5 million m3 is polluted annually [19]. Nieto et al. [20] investigated the Tinto River and found that the river basin was affected by AMD and the microbial interaction was weakened. Baker et al. [21] found various microorganisms capable of reducing sulfur, iron, and anti-heavy metal in the pyrite tailing environment.
Previous studies have revealed the functional potential and activity of the AMD microbiome, but the functional diversity of the AMD microbiome is rare. The relationship between the level and function of the microbial community structure and surrounding environmental factors is still unclear. Therefore, it is necessary to conduct a more comprehensive characterization of the microbial community to fully understand the effects of soil chemistry on a microbial community structure.
In this paper, there were two specific objectives: (1) the physical and chemical indexes of soil around the acid reservoir in the mining area were analyzed to evaluate the pollution degree; (2) the microbial community in the soil was analyzed to reveal the distribution characteristics of soil microorganisms to determine the relationship between microbial communities and soil chemical-physical properties. The significance of this study lies in that it is a study to report the changes in soil chemical properties and microbial community composition of an acid reservoir. This data should provide a reference value for soil remediation in many similar sites.

2. Materials and Methods

2.1. Study Site and Sampling

The “Ningwu-Luohe metallogenic belt” [22] in Maanshan City, Anhui Province, China (31°46′42″ N; 118°21′38″ E) served as the study location. The Yangtze River Delta is where the mining area is situated, and the flow is in an east–west direction. The Pukou District and Jiangning District of Nanjing City, Quanjiao County of Chuzhou City, Chaohu County of Hefei City, Jiujiang District of Wuhu City, and Wuwei County form its eastern, northern, western, and southern borders, respectively. Because of the monsoon circulation, it has distinct seasons and a temperate climate. 15.7 °C and 1060 millimeters of precipitation are the average annual temperature and precipitation, respectively.
The acid reservoir (566.8 m × 266.9 m) is a container. The reservoir has a northeast-southwest flow. A sampling site was established on the south bank of the acid reservoir because the mine is situated north of the acid reservoir. Samples of soil were taken in the east–west and north–south orientations (depth 10–20 cm [23,24]). The average separation between sampling locations Nos. 1 through 8 and Nos. 9 through 12 was 65 and 90 m, respectively (Figure 1).
Prior to taking soil samples, plant debris, living plants, and litter were meticulously removed with a knife and a shovel [25]. Three replicates of soil samples were then taken within 1 m2 of each sampling location. Each sample is around 1 kg in weight. All samples were brought to the lab as soon as possible in two halves on ice, where they underwent chemical analysis at 4 °C or were kept at −20 °C pending microbiological analysis.

2.2. Soil Properties

The soil samples were placed in a petri dish and laid flat in a dry, enclosed, and light-transmitting environment to prevent dust intervention and allow the soil to dry naturally. The soil sample was passed through a conventional sieve of 200 mesh (0.074 mm) and stored in an air-sealed polyethylene bag after one week of air drying at ambient temperature. Additionally, quartz sand was added during the grinding process for the soil samples used for DNA extraction to improve the extraction of fungal DNA [26].
Typically, analytical-grade chemicals were used for all experiments. A pH meter (Thermo Scientific, Waltham, MA, USA) [27] was used to measure the pH of the soil in a suspension of 10 g soil and 50 mL water (Yamato Millipore-filter, WT 101 UV). According to Pansu and Gautheyrou [28], an elemental analyzer (Vario EL cube, Elementar, Langenselbold, Germany) determined that the soil organic carbon content (SOC) was acidic. An element analyzer was used to determine the total N (TN) content (VARIO EL cube). Using ion chromatography, gas chromatography, and liquid chromatography, respectively, the sulfate, sulfide, and sulfur in soil were detected. For the measurement of Mn, Fe, Cu, Zn, and Cd, the soil samples were digested using HNO3 at 1.42 g/mL, HF at 1.49 g/mL, and HClO4 at 1.68 g/mL (Guaranteed Reagent, GR). The amounts of Mn, Fe, Cu, Zn, and Cd were measured using a flame atomic absorption spectrophotometer (WYS-2200, Anhui, China). Tessier’s [29] approach was used to determine the concentrations of heavy metals in soil samples, including those that were water-soluble, exchangeable, bound to carbonates, bound to iron and manganese oxides, and bound to organic matter, and residual. Table 1 displays the background values for the soil.

2.3. DNA Extraction and Sequencing

The total genomic DNA was extracted by using a soil DNA kit (OMEGA, USA) and amplified by specific primers (Bacterial: F338-GC: CGCCCGCCGCGCCCCGCGCCCGGCCCGCCGCCCCCGCCCCACTCCTACGGGAGGCAGCAG′; 518R: ATTACCGCGGCTGCTGG. Archaeal: F787-GC: CGCCCGCCGCGCGCGGCGGGCGGGGCGGGGGCACGGGGGGCGATTAGATACCCSBGTAGTCC; 1059R:GCCATGCACCWCCTCT) to target the hypervariable V3 regions of the bacterial 16 s rRNA gene [30]. The amplicons were quantified using Qubit after being purified using the Wizard SV Gel and PCR purification equipment (Promega Corporation, Madison, WI, USA) in accordance with the manufacturer’s instructions (Life Technologies, Carlsbad, CA, USA). Sample dilution is used to examine the amplification inhibition of all DNA samples. The D-code universal mutation system of BIO-RAD, the BUGGE electrophoresis system, was used to evaluate PCR results. The amplified product was cleaned using a Beijing Quanshi Gold Easy Pure Quick Gel Extraction Kit before being eluted with 30 L of sterile water. After digestion, San’an Biotechnology (Shanghai, China) Co., Ltd. sequenced the amplification products with various outcomes, and the sequencing findings were forwarded to the NCBI database (submissions grp:5210823; ID:1854608). To cluster the sequences at 97% sequence identity and choose a representative sequence for each cluster, operational taxonomic units (OTU) were defined in the data set [31].

3. Results and Discussion

3.1. Chemical Properties of the Acid Reservoir Soil Samples

As shown in Figure 2, the soil from sampling sites 1–8 near the acid reservoir is strongly acidic (Slight acid is 6.1–6.5; neutral is 6.5–7.5; Strong acidity is 5.1–5.5) due to the continuous infiltration of acidic mine wastewater. The pH values of No. 2 and No. 7 were 4.55 and 5.33, respectively, and the average pH of the sampling points was 4.94. As the distance between the sampling point and the acid reservoir increased, the pH value increased from 4.95 on No. 8 to 6.08 on No. 9, and the value of sample No. 12 was 6.27. The pH values of the sampling sites were all below 6.5, lower than the second-grade soil standard in China. It is speculated that the imbalance of anions and cations in the soil may be caused by the infiltration of heavy metals in the acid reservoir, which affects the pH of the soil.
The 1st to 8th sample points are the closest to the acid reservoir, with an average content of 4.17 g/kg (Figure 3), and the soil organic carbon content is assumed to be very low. Soil organic carbon content increases with an increase in distance from sampling points 9 to 12. The soil organic carbon content of sampling point 12 was 35.1 g/kg, and the average of the Nos. 9 to 12 four sampling points was 31.8 g/kg, 7.63 times that of the Nos. 1 to 8 sampling points. The lack of soil organic carbon is a part of the important characteristics of the soil in the mining area [32], as well as a reason for thin surface vegetation [33]. The degradation of soil organic carbon mainly originates in the metabolic decomposition of microorganisms, and the most active heterotrophic microorganisms in the soil use carbon as energy. It is essential for synthesis and nutrient transformation [34].
As shown in Figure 4, the total nitrogen content of sampling sites Nos. 1 to 8 was between 0.72 g/kg and 0.79 g/kg, with an average of 0.76 g/kg, which was significantly lower than the average total nitrogen content of topsoil in China (1.05 g/kg). According to NY/T 391–2000: “Environmental Technical Conditions Standard for Green Food Production Areas in China”, soils with organic matter content less than 10 g/kg and total nitrogen content less than 0.80 g/kg are classified as inferior class III [35]. Nitrogen is the most important biological survival factor and the most important nutritional factor for biological survival. The soil in the mining area is seriously deficient in nitrogen due to the influence of pH value and organic matter content [36].
With the increase in distance between the sampling point and the acid reservoir, the influence of acid mine wastewater soil gradually weakened. Soil pH and organic carbon increased, as did total nitrogen. In agreement with previous studies, a slight increase in soil pH benefits soil organic carbon and nitrogen storage [37]. The average TN content of Nos. 9 through 12 sites was 1.03 g/kg, which could provide a sufficient nitrogen source for soil organisms.
As the intersection center of water, organisms, atmosphere, and lithosphere, the behavior of sulfur in the soil directly affects the circulation and exchange of sulfur among the layers. It is also closely related to other soil processes, soil environment and fertility, plant growth, and earth changes. Sulfate pollution is one of the most important environmental problems regarding soil sulfur in the mining area [38]. As shown in Figure 5a, the soil sulfate content at Nos. 1–8 is 21.2 g/kg at the highest and 17.8 g/kg at the lowest, with an average content of 19.2 g/kg, significantly higher than the world’s average sulfur content of 0.7 g/kg. The soil sulfate content in Nos. 9–12 decreased gradually from 8.88 g/kg to 7.47 g/kg, with an average of 8.12 g/kg, which was only 42.0% of the average value in sampling sites 1–8. Sulfate is produced by pyrite oxidation [39]. Pyrite oxidation in acid sulfate soils produces high acidity, which also explains the pH difference between sampling sites [40].
Sulfide is among the dominant forms of sulfur in mining soil. As shown in Figure 5b, the highest sulfide content of sampling points 1 to 8 is 3.55 g/kg, and the average is 3.24 g/kg, 1.39 times the average of sampling points 9 to 12. Metal mining and extraction produce tons of waste yearly; most of it contains pyrite and other sulfides. In addition to the sulfates formed by the oxidation of part of the tailings exposed to the air, a large number of heavy metal ions in the mining area combine with S2− to form stable metal sulfides that exist in the soil [41].
The sulfur content of sampling points 1–12 (Figure 5c) is very low. The content of No. 2 is the highest at 105.9 mg/kg, and that of No. 11 is the lowest at 59.4 mg/kg. Sulfur in the soil is not the direct reduction product of sulfate under soil reducing conditions but an intermediate product formed by sulfide oxidation, mainly through a chemical reaction process. Sulfur can accumulate in flood water or sediment. However, it is generally difficult to detect sulfur in the soil because it is easily oxidized by exposure to air and exists in the soil for a short time.
Iron is the fourth element with redox activity in the Earth’s crust, after oxygen, silicon, and aluminum, and has a profound impact on the physical and chemical properties of soil [42]. It can be seen from Figure 6 that there is a significant difference in Fe at different sampling points. Among sampling sites 1–8 adjacent to the acid reservoir, the Fe content at sampling site 4 was up to 113 g/kg. The lowest Fe in sampling site No. 2 is 101 g/kg, and the average in eight sampling sites is 103 g/kg. There was no significant difference in Fe between No. 9 and No. 12, and the average Fe was 48.0 g/kg, less than half of the average Fe content of Nos. 1 to 8. However, the content in all sampling sites was higher than the soil background value in Anhui Province (31.4 g/Kg). It shows that the heavy metals around the AMD are easy to migrate and transform and have different degrees of potential environmental harm.
The total amount of heavy metals cannot comprehensively assess the ecological effect and environmental behavior of those in the soil. It is the distribution of heavy metals that affects and determines the ecological and environmental system around it. Therefore, the form and proportion of heavy metals in soil were analyzed. Fe speciation analyses show (Figure 6) that the speciation distribution of heavy metals in the 12 sampling sites is different, among which the residual form is the highest, accounting for 50.4–65.1% of the total amount. The second is the combination of iron and manganese oxides, accounting for 20.1–32.2%. Following: strong organic fraction (8.95–12.2%) > exchangeable fraction (1.43–6.89%) > carbonate bond fraction (1.43–3.27%). This result is consistent with the work of Li, Y.F et al. [43]. No soluble Fe was detected in the soil samples. The combination of residue and Fe-Mn oxide was the main form of the Fe element in the soil. The residue iron content is the highest, related to the reservoir of pyrite acid in this area. pH is an important factor in the reaction in soil. Lower soil pH can promote iron activation and affect the balance between various forms of soil heavy metal solubility [44]. With the increase in soil pH, the proportion of residual Fe decreases gradually, the coprecipitation of heavy metal elements is formed, and the carbonate bound fraction decreases simultaneously. On the contrary, the Fe-Mn oxides and ion exchange fractions positively correlated with the pH, and the content increased with the increase of pH.
The Mn content of the 12 sampling sites differed significantly (Figure 7). The lowest Mn content of sampling site No. 11 was 0.83 g/kg, which is greater than the national average. No. 5 occupies the highest content of 1.93 g/kg, which is 2.4 times the world average of 0.81 g/kg [45]. The average value of sampling sites 9–12 is 0.85 g/kg, which is close to the average value of Mn in the world. The relatively low concentration of Mn in sampling points Nos. 9–12 is due to the long horizontal distance between the mining area and the acid reservoir, less affected by the leaching of acid mine wastewater and tailings soil precipitation.
Manganese in soil often exists in the form of divalent, trivalent, and tetravalent cations, and its existence form is related to soil pH, REDOX potential, and soil characterization [46]. As shown in Figure 7, the morphological distribution of each sampling point is significantly different. At sampling points 1–12, residue and Fe-Mn oxides are the main forms of Mn, accounting for 43.3–58.6% and 20.8–44.0% of the total amount, respectively. The ion exchange fraction adsorbed on the surface by static electricity by soil colloids accounted for 2.22–10.5% of the total. After that, it is strongly organic Mn, bound by chelation, and the content is 5.1–7.99%. There is also a small amount of Mn in the water-soluble and carbonate-bound fractions, accounting for 1.75–3.16% and 0.99–2.94%, respectively. Studies have shown that the form of manganese in the soil is greatly affected by pH, and residual manganese is easily transformed into other forms with an increase in pH [47]. Soil with a higher pH contains more hydroxide ions, which easily form insoluble manganese hydroxide with manganese ions in the soil [48]. The concentration of residual manganese and exchangeable manganese decreased, and the combined content of iron and manganese oxides gradually increased [49].
As a transition metal, Cu is a major trace element in living organisms, which can catalyze biochemical reactions in human bodies and can also be absorbed by the root cells of plants in a dissociation fraction [50]. As shown in Figure 8, Cu pollution was serious at 12 sampling points. The concentration was highest at sampling point 4, where the Cu content reached 0.54 g/kg, while sampling point 9 had the lowest Cu content at 0.25 g/kg, less than half that of sampling point 4. The average Cu content at each sampling point was 0.40 g/kg, higher than the minimum standard for agricultural land in China of 0.20 g/kg [51]. With the increase in horizontal distance from the acid reservoir, the influence of acidic mines wastewater decreased. The Cu content in the soil of sampling sites Nos. 9–12 was significantly lower than that of Nos. 1–8, with an average value of 0.27 g/kg, which meets the Chinese soil standard grade (III). Although heavy metals are less mobile, seasonal climate changes can cause changes in soil’s heavy metal content. A heavy rain season will lead to serious soil erosion, causing root rot in plants through alternating dry and wet, and the leaching of rainfall on soil [52] will cause the migration of heavy metal elements.
Morphological analysis of copper showed that morphological differences of different sampling points were not obvious. Residual and strong organic fractions were the principal forms of copper in the samples from the 12 sampling points, accounting for 38.5–42.7% and 30.0–33.8% of the total copper, respectively. Secondly, the proportion of iron and manganese oxide bound fraction was 18.9–21.9%; the proportion of ion exchange fraction and carbonate bound fraction was small, and the sum of the two fractions was between 6.04% and 8.28%. No water-soluble copper was detected. Distinct from the distribution of Fe and Mn, the proportion of copper in the organic fraction was the largest, related to the strong binding ability of copper and organic matter [53]. Concentrated organic forms easily enter the food chain in an active form and are absorbed by plants and microorganisms to cause pollution to the soil environment [54].
As shown in Figure 9, the highest Zn content at sampling site No. 4 was 132.2 mg/kg, and the lowest Zn content at sampling site No. 10 was 92.4 mg/kg. The average Zn content at the sampling site was 108.7 mg/kg, slightly higher than the Chinese soil quality standard of 100 mg/Kg. The soil in this area was slightly polluted with Zn, which may be because the area is pyrite with a little lead and low zinc content. Limited concentrations enter the soil through natural dust, rainfall, and rivers.
After analyzing the Zn speciation, it can be seen that the morphological distribution of each sampling point was the same, and the residual fraction and iron-manganese oxides combined content was the same, accounting for 30.0–32.9% and 28.2–32.7% of the total, respectively. Strong organic fractions also accounted for 21.6–26.2% of the total. The water-soluble, exchangeable, and bioavailable carbonate-bound fractions account for only 11.0–16.8% of the total. Soil pH has a direct relationship to the mobility of Zn as it affects Zn solubility and its capacity to form chelates in soil. The concentrations of cations in soil solution usually increase greatly under a low pH condition [55]. In this study, the fraction of water-soluble Zn increased as the pH value decreased. The result coincided with other reports of increased solubility and mobility of soil Zn with a decreasing pH [56]. It also reported that the amount of soluble Zn increased while that of reducible Zn decreased significantly in paddy soil when the pH decreased. It may be due to the dissolution of hydrous oxides, in which Zn co-precipitated.
Cadmium (Cd) is one of the most harmful heavy metals [57]. No. 2 sampling point had the most seriously polluted concentration, as high as 5.81 mg/kg; No. 6 sampling point had the lowest concentration of 4.50 mg/kg; the average concentration of sampling points 1–8 was 5.04 mg/kg (Figure 10). Cadmium pollution declined with increased distance from the acid reservoir level. The average cadmium content at sampling points 9–12 was 1.16 mg/kg, which was still far beyond the national secondary standard for soil environmental quality (0.30 mg/kg). In addition to the diffusion of cadmium in soil, the recharge of industrial sewage is also a primary factor causing cadmium pollution [58].
The formal distribution of cadmium has a significant impact on the damage and remediation effect of cadmium in the ecosystem, and soil pH is an important factor that restricts the form and geochemical behavior of cadmium [59]. As shown in Figure 10, residual fraction, iron-manganese oxide bound fraction, carbonate bound fraction, and water-soluble fraction are the main forms of cadmium in soil. The pH of sampling site No. 2 is 4.55, and the content of water-soluble Cd is 21.2%. With the increase in pH, the negative charge on the surface of clay minerals and organic matter in the soil increased, which intensified the adsorption capacity of Cd2+ and turned off the water-soluble cadmium [60]. The highest pH was at sampling site 12, where the water-soluble content was 12.5%, 8.68% lower than that at sampling site No. 2. An increase in pH would increase the stability of soil organic matter and metal complex, leading to a decrease in water-soluble cadmium content [61]. As seen in Figure 10, the change of ion exchange fraction in the soil is the same as that of water-soluble cadmium, which decreases with the increase of soil pH. The residual fraction is a relatively stable form, making up 28.9–31.5%. With the increase in soil organic carbon content, the proportion of solid organic Cd increased gradually, from 6.04% at No. 2 to 11.0% at No. 12, an increase of 4.97%. With the increase in soil pH and soil organic carbon content, Fe-Mn oxide-bound fraction and carbonate-bound fraction increased slightly, by 7.14% and 3.79%, respectively. The activity of free ions of heavy metals determines their bioavailability and toxicity to organisms in the soil. The transferability and bioavailability of the exchange fraction are the strongest, critical indicators for evaluating soil heavy metal pollution. Low-polluted soils have lower exchangeable content than highly polluted soils.

3.2. Characterization of Microbial Communities

The composition and diversity of microbial communities in the mining soil were explored by PCR-DGGE. The lane images (V3 region of bacteria 16S rRNA gene) and UPGMA dendrogram are shown in Figure 11a,b, respectively.
In the DGGE profile (Figure 11a), the band number of mining soil samples ranged from 8 to 24, and 28 bands were observed. RDP Seqmatch and NCBI blast showed that these 28 bands belonged to Proteobacteria, Bacteroidetes, Firmicutes, and Actinobacteria, respectively. It can be divided into 11 genera, such as Bacillus, Pseudomonas, Desulfuromonas, Desulfobulbus, Sulfuricurvum, and Lactococcus. Considerable diversity was observed in mining soil, as seen from further analysis using the Quantity One 4.6.2 software. The DGGE profile also showed that the number of bands at sampling points 1–8 was between 9 and 19, and the number of bands at sampling points 9–12 were all greater than 20. The number of bands varies considerably with an increase in distance from the acidic reservoir. A certain heavy metal concentration has a stressing effect on microorganisms [62].
The UPGMA dendrogram in Figure 11b shows two main distinct clusters of DGGE spectra. The first cluster corresponds to the initial inoculum Nos. 4–8; the second clustering is performed for samples Nos. 1–3 and 9–12. The dendrogram must conform with the change of sampling points. The Shannon-Weaver index (H), Evenness index (Eh), and abundance index (S) in Figure 12 varied widely between samples, and No. 1′s richness of 9 was the lowest among the samples, while the Shannon diversity index (H) and evenness Eh were also the lowest at 1.60 and 0.59, respectively. Soil with a lower pH had lower bacterial diversity. The Shannon diversity index (H) and evenness index (Eh) were also the highest among all samples, at 2.82 and 0.90, respectively. The diversity index of Nos. 1–3 showed little difference and was the lowest among all samples, 4 to 8 followed, and the diversity Index of 9–12 was the highest. Heavy metal pollution reduced soil microbial community richness [63], harmonious with the DGGE banding results.
The horizontal percentage of bacterial genera in soil samples is given in Figure 13a. Lactococcus is the dominant species in each sample, with the highest abundance being in No. 7, reaching 30.8%, and the lowest point, No. 9, being 20.4%, with an average abundance of 26.0%. Lactococcus [64] has a strong potential to grow under acidic conditions of pH < 5. Its main function is tantamount to decomposing humus and organic acids, producing acid for fermentation, and providing a carbon source for other organisms in the soil.
The Bacillus is a common dominant microbial species in the soil, with an average abundance of 12.8% in the 12 samples. It can survive under acidic conditions, amylase and lipase activity can degrade complex carbohydrates, degrade soil organic matter, and humic acid into polysaccharides, and at the same time can transfer electrons to NO3− [65]. Figure 11a shows that band 24 is only present at sampling point 12, with an abundance of only 1.25%. After another NCBI sequence alignment, it was found to be as high as 98%, similar to Bacillus benzoevoran. Bacillus benzoevoran can use various carbon sources to accelerate the cycle of nitrogen and sulfur elements in the soil under anaerobic conditions [66]. The optimal pH of Bacillus benzoevoran is neutral; only No. 12 had the highest soil pH.
Sulfate-Reducing Bacteria (SRB) is a class of rich bacteria in the mining area. It can use organic matter as a carbon source and H produced in its biofilm under an anaerobic or anoxic fraction. The sulfate is gradually reduced to hydrogen sulfide. Two typical SRB genera were found in the test soil: Desulfuromonas and Desulfobulbus, and with the gradual increase of pH, the total number of SRB genera also gradually increased from 18.0% to 25.3%. Desulfuromonas not only has the function of sulfate reduction but also uses Fe(III) and Mn(IV) as electron receptors to reduce it to Fe (II) and Mn (II) [67].
Pseudomonas was not detected in sampling sites No. 1 to 4 because of its low survival in strongly acidic environments. With the gradual increase in pH, the abundance of Pseudomonas slightly increased. It has become the dominant species with an abundance of 12.8% at sampling point 12. It can degrade complex organic matter and digest tiny molecules of carbohydrates such as glucose and fructose while using nitrate as an electron acceptor to denitrify.
The percentage of archaea levels in soil samples is shown in Figure 13b. Two archaea categories were detected in the experiment: Euryarchaeota and Thaumarchaeota. All Euryarchaeota are methanogens, such as Methanoregula, Methanosphaerula, Methanocella, Methanoculleus, and Methanolinea, all of which use acetic acid to produce methane. The Nitrosophaera and Nitrosopumilus of Thaumarchaeota are archaea that could oxidize NH4+ to NO2.
As shown in Figure 14, the abundance of functional bacteria in acid-producing fermentation was 56.8–73.1%. The second was the bacteria involved in sulfur metabolism, with a relatively uniform content ranging from 23.9% to 34.3%. Functional bacteria involved in the nitrogen cycle had the lowest abundance in the range of 13.8% to 30.0%.

4. Conclusions

The biochemical characteristics of the soil around the acid reservoir in a mining area in Maanshan were analyzed. Sampling points 1–8 immediately adjacent to the acid reservoir were seriously polluted by heavy metals Fe, Mn, and Cd, while sampling points 9–12 further away from the acid reservoir showed a significant reduction in pollution level, and some of the soils had reached the national III standard. Morphological analysis of soil heavy metal showed that residue fraction and Fe-Mn oxide combined fraction were the main forms of heavy metal. With the rise of pH, the content of residue fraction decreased, and the content of Fe-Mn oxide combined fraction increased. The molecular biology of PCR-DGGE showed that the diversity index increased with the increase of soil pH, organic carbon, and total nitrogen content. The function of bacterial flora was complete at each sampling site, and the bacteria with hydrolytic acid production function accounted for more than 55.0% of the total bacterial flora. Bacteria engaged in sulfur metabolism and nitrogen cycling were always present as the dominant species in the soil of the 12 sampling sites.

Author Contributions

Investigation, J.W.; Methodology, F.X.; Resources, B.Z.; Software, D.L.; Writing—original draft, J.G. All authors have read and agreed to the published version of the manuscript.

Funding

This research work was supported by the Natural Science Foundation of China (41372246) and the University Natural Science Foundation (KJ2019A0986, KJ2019A0987).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All data and models generated or used during the study appear in the submitted article.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Boonsrang, A.; Chotpantarat, S.; Sutthirat, C. Factors controlling the release of metals and a metalloid from the tailings of a gold mine in Thailand. Geol. Soc. Lond. Collect. 2017, 18, 109–119. [Google Scholar] [CrossRef]
  2. Chotpantarat, S. A review of static tests and recent studies. Am. J. Appl. Sci. 2011, 8, 400–406. [Google Scholar] [CrossRef]
  3. Pakostova, E.; Johnson, D.B.; Bao, Z.; MacKenzie, P.M.; Ptacek, C.J.; Blowes, D.W. Bacterial and archaeal diversity in sulfide-bearing waste rock at faro mine complex, Yukon Territory, Canada. Geomicrobiol. J. 2020, 37, 511–519. [Google Scholar] [CrossRef]
  4. Kefeni, K.K.; Msagati, T.A.M.; Mamba, B.B. Acid mine drainage: Prevention, treatment options, and resource recovery: A review. J. Clean. Prod. 2017, 151, 475–493. [Google Scholar] [CrossRef]
  5. Charuseiam, Y.; Chotpantarat, S.; Sutthirat, C. Acid mine drainage potential of waste rocks in a gold mine (Thailand): Application of a weathering cell test and multivariate statistical analysis. Environ. Geochem. Health 2021, 4, 1049–1079. [Google Scholar] [CrossRef]
  6. Rezaie, B.; Anderson, A. Sustainable resolutions for environmental threat of the acid mine drainage. Sci. Total Environ. 2020, 717, 137211. [Google Scholar] [CrossRef] [PubMed]
  7. Jansson, J.K.; Hofmockel, K.S. Soil microbiomes and climate change. Nat. Rev. Microbiol. 2020, 18, 35–46. [Google Scholar] [CrossRef]
  8. Bankar, A.; Patil, S. Microbial cell factories for treatment of soil polluted with heavy metals: A green approach—ScienceDirect. Microbiome Stimul. Crops 2021, 18, 315–332. [Google Scholar]
  9. Jia, S.; Zhou, Y. Ecological compensation method for soil polluted by heavy metals based on internet of things. Earth Sci. Res. J. 2020, 24, 153–161. [Google Scholar]
  10. Liu, N.; Liu, H.; Wu, P.; Meng, W.; Li, X.; Chen, X. Distribution characteristics and potential pollution assessment of heavy metals (Cd, Pb, Zn) in reservoir sediments from a historical artisanal zinc smelting area in Southwest China. Environ. Sci. Pollut. R. 2021, 29, 14288–14298. [Google Scholar] [CrossRef]
  11. Wang, R.; Deng, H.; Jia, Z.M.; Wang, J.B.; Zeng, Q.Q. Spatial distribution characteristics, pollution, and ecological risk assessment of soil heavy metals around mercury mining areas. Huan Jing Ke Xue 2021, 42, 3018–3027. [Google Scholar] [PubMed]
  12. Chen, M.; Li, Y.; Jiang, X.; Zhao, D.; Liu, X.; Zhou, J. Study on soil physical structure after the bioremediation of pb pollution using microbial-induced carbonate precipitation methodology. J. Hazard. Mater. 2021, 411, 125103. [Google Scholar] [CrossRef]
  13. Skousen, J.G.; Ziemkiewicz, P.F.; Mcdonald, L.M. Acid mine drainage formation, control and treatment: Approaches and strategies-ScienceDirect. Extr. Ind. Soc. 2019, 6, 241–249. [Google Scholar] [CrossRef]
  14. Almeida, W.I.; Vieira, R.P.; Cardoso, A.M.; Silveira, C.B.; Costa, R.G.; Gonzalez, A.M.; Paranhos, R. Archaeal and bacterial communities of heavy metal contaminated acidic waters from zinc mine residues in Sepetiba Bay. Extremophiles 2009, 13, 263–271. [Google Scholar] [CrossRef]
  15. Mohanty, D.K.; Matty, D.J. Method of Using a Crosslinked Polymer-carbon Sorbent for the Removal of Heavy Metals, Toxic Materials and Carbon Dioxide. US Patent US8840855B2, 23 September 2014. [Google Scholar]
  16. Zhu, S.; Rong, Y.; Kiang, T.K.L. Effects of p-Cresol on oxidative stress, glutathione depletion, and necrosis in HepaRG Cells: Comparisons to other uremic toxins and the role of p-Cresol glucuronide formation. Pharmaceutics 2021, 13, 857. [Google Scholar] [CrossRef]
  17. Gharib, F.A.; Mansour, K.H.; Ahmed, E.Z.; Galal, T.M. Heavy metals concentration, and antioxidant activity of the essential oil of the wild mint (Mentha longifolia L.) in the Egyptian watercourses. Int. J. Phytoremediat. 2020, 1, 1–11. [Google Scholar] [CrossRef] [PubMed]
  18. Ahmad, W.; Alharthy, R.D.; Zubair, M.; Ahmed, M.; Rafique, S. Toxic and heavy metals contamination assessment in soil and water to evaluate human health risk. Sci. Rep. 2021, 1, 17006–17017. [Google Scholar] [CrossRef] [PubMed]
  19. Grande, J.A.; Valente, T.; Torre, M.L.; Santisteban, M.; Ceron, J.C.; Perez-Ostale, E. Characterization of acid mine drainage sources in the Iberian Pyrite Belt: Base methodology for quantifying affected areas and for environmental management. Environ. Earth Sci. 2014, 71, 2729–2738. [Google Scholar] [CrossRef]
  20. Nieto, J.; Sarmineto, A.; Olias, M.; Avora, C. Acid mine drainage in the Iberian Pyrite Belt: 1. Hydrochemical characteristics and pollutant load of the Tinto and Odiel rivers. Environ. Sci. Pollut. R. 2013, 20, 7509–7519. [Google Scholar] [CrossRef]
  21. Baker, B.J.; Banfield, J.F. Microbial communities in acid mine drainage. FEMS. Microbiol. Eco. 2003, 44, 139–152. [Google Scholar] [CrossRef]
  22. Niu, S.; Fang, Q.; Yu, J.; Wu, J. Heavy metals present in the soils from extremely large opencast iron mine pit. Bull. Environ. Contam. Toxicol. 2021, 107, 984–989. [Google Scholar] [CrossRef] [PubMed]
  23. Su, Y.M.; Chen, Z.L.; Lei, G.J.; Fang, X.H. Vertical pollution characteristic and ecological risk assessment of heavy metal of soil profiles in polymetallic ore mine. Ecol. Environ. Sci. 2016, 25, 130–134. [Google Scholar]
  24. Zhang, C.; Pan, W.; Tang, C. Assessment of arsenic distribution in paddy soil and rice plants of a typical karst basin affected by acid mine drainage in Southwest China. Environ. Pollut. 2013, 2, 27. [Google Scholar] [CrossRef] [Green Version]
  25. Yang, Y.; Kim, J.; Chung, J.O.; Roh, J.H.; Hong, Y.D. Variations in the composition of tea leaves and soil microbial community. Biol. Fert. Soils 2022, 58, 167–179. [Google Scholar] [CrossRef]
  26. Wang, N.; Wang, W. Study on an extraction method of pathogenic fungal DNA from farmland soil. J. ZhengZhou Univ. Light Ind. (Nat. Sci.) 2013, 4, 54–59. [Google Scholar]
  27. Voelkner, A.; Holthusen, D.; Horn, R. Determination of soil dispersion caused by anaerobic digestates: Interferences of pH and soil charge with regard to soil texture and water content. J. Soil Sediment 2015, 15, 1491–1499. [Google Scholar] [CrossRef]
  28. Pansu, M.; Gautheyrou, J. Handbook of soil analysis: Mineralogical, organic and inorganic methods. Int. J. Cancer 2006. [Google Scholar] [CrossRef]
  29. Tessier, A.; Campbell, P.G.C.; Bisson, M. Sequential extraction procedure for the speciation of particulate trace metals. Anal. Chem. 1979, 51, 844–851. [Google Scholar]
  30. Muyzer, G.; Dewaal, E.C.; Uitterlinden, A.G. Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes coding for 16S rRNA. Appl. Environ. Microbiol. 1993, 59, 695–700. [Google Scholar] [CrossRef] [Green Version]
  31. Daghio, M.; Vaiopoulou, E.; Patil, S.A.; Suárez-Suárez, A.; Head, I.M.; Franzetti, A.; Rabaey, K. Anodes stimulate anaerobic toluene degradation via sulfur cycling in marine sediments. Appl. Environ. Microbiol. 2015, 23, 297–307. [Google Scholar]
  32. Olefeldt, D.; Roulet, N.T. Effects of permafrost and hydrology on the composition and transport of dissolved organic carbon in a subarctic peatland complex. J. Geophys. Res. Biogeosciences 2012, 21, 117–125. [Google Scholar]
  33. Wu, Q.B.; Xiao, K.; Zhi, Y. soil organic carbon and its fractions across vegetation types: Effects of soil mineral surface area and microaggregates. Pedosphere 2009, 19, 258–264. [Google Scholar]
  34. Gilliam, F.S.; Billmyer, J.H.; Walter, C.A. Effects of excess nitrogen on biogeochemistry of a temperate hardwood forest: Evidence of nutrient redistribution by a forest understory species. Atmos. Environ. 2016, 146, 261–270. [Google Scholar]
  35. Chen, H.M. Environmental Soil Science; Science: Bejing, China, 2010. [Google Scholar]
  36. NY/T 391-2000; China Green Food-Standard of Environmental and Technical Conditions of Origin. China Standard Press: Beijing, China, 2000.
  37. Zhang, J.; Wu, X.; Shi, Y.; Jin, C.; Wang, J. A slight increase in soil pH benefits soil organic carbon and nitrogen storage in a semi-arid grassland. Ecol. Indic. 2021, 130, 108037. [Google Scholar]
  38. Zhang, W.; Zhang, I.; Deng, J. Comparison of retention and output of sulfur in limestone soil and yellow soil and their responses to acid deposition in a small karst catchment of Guizhou Province, Southwest China. Environ. Sci. Pollut. R. 2021, 28, 60993–61007. [Google Scholar]
  39. Shamshuddin, J.; Muhrizal, S.; Fauziah, I.; Husni, M.H.A. Effects of adding organic materials to an acid sulfate soil on the growth of cocoa (Theobroma cacao L.) seedlings. Sci. Total. Environ. 2004, 323, 33–45. [Google Scholar]
  40. Nystrand, M.I.; Hadzic, M.; Postila, H.; Wichmann, A.; Karppinen, A.; Ihme, R.; Österholm, P. Characteristics of sulfide bearing soil materials in peat extraction areas in N-Finland. J. Geochem. Explor. 2021, 220, 106640. [Google Scholar]
  41. Vlachy, N.; Jagoda-Cwiklik, B.; Vácha, R.; Touraud, D.; Jungwirth, P.; Kunz, W. Hofmeister series and specific interactions of charged headgroups with aqueous ions. Adv. Colloid Interface Sci. 2009, 146, 42–47. [Google Scholar]
  42. Zahra, N.; Hafeez, M.B.; Shaukat, K.; Wahid, A.; Hasanuzzaman, M. Iron toxicity in plants: Impacts and remediation. Physiol. Plant 2021, 173, 201–222. [Google Scholar]
  43. Li, Y.F.; Yang, Y.F.; Wang, Y.Y.; Liu, W.J.; Zhang, P.J. Characteristics of soil iron forms in wetlands with hvarious restoration ages around the Caizi lake, Anhui Province. Acta Sci. Circumstantiae 2015, 35, 3234–3241. [Google Scholar]
  44. Martinez, C.E.; Motto, H.L. Solubility of lead, zinc and copper added to mineral soils. Environ. Pollut. 2000, 107, 153–158. [Google Scholar]
  45. Lucas, B.; Seavey, K.C.; Liu, Y.A. Steady-state and dynamic modeling for new product design for the solid-state polymerization of Poly(Ethylene Terephthalate). Ind. Eng. Chem. Res. 2006, 46, 190–202. [Google Scholar]
  46. Liu, C.; Liu, W.S.; Ent, A.; Morel, J.L.; Qiu, R.L. Simultaneous hyperaccumulation of rare earth elements, manganese and aluminum in Phytolacca americana in response to soil properties. Chemosphere 2021, 282, 131096. [Google Scholar]
  47. Sirous, S.; Mahboub, S. The status of chemical forms of iron and manganese in various orders of calcareous soils and their relationship with some physicochemical and mineralogical properties. Commun. Soil. Sci. Plan. 2020, 15, 2054–2068. [Google Scholar]
  48. Sinha, M.K.; Purcell, W. Reducing agents in the leaching of manganese ores: A comprehensive review. Hydrometallurgy 2019, 187, 168–186. [Google Scholar]
  49. Cui, J.; Li, X.; Muhammad, Y.; Shi, C.Y.; Li, H.B.; Su, H. Residual organics removal from manganese electrochemical solution using combined Fenton oxidation process with adsorption over activated carbon. Environ. Sci. Pollut. Res. 2020, 27, 44240–44248. [Google Scholar]
  50. GB 15618-2008; Soil Environmental Quality Standards in China (Revised). State Environmental Protection Administration (SEPA): Beijing, China, 2008.
  51. Arao, T.; Ishikawa, S.; Murakami, M.; Abe, K.; Maejima, Y.; Makino, T. Heavy metal contamination of agricultural soil and countermeasures in Japan. Paddy Water Environ. 2010, 8, 247–257. [Google Scholar]
  52. Wang, G.X.; Zeng, C.; Zhang, F. Traffic-related trace elements in soils along six highway segments on the Tibetan Plateau: Influence factors and spatial variation. Sci. Total Environ. 2017, 581–582, 811–821. [Google Scholar]
  53. Zitoun, R.; Clearwater, S.J.; Hassler, C.; Thompson, K.J.; Albert, A.; Sander, S.G. Copper toxicity to blue mussel embryos (Mytilus galloprovincialis): The effect of natural dissolved organic matter on copper toxicity in estuarine waters. Sci. Total. Environ. 2019, 25, 300–314. [Google Scholar]
  54. Liu, X.; Zhang, X.; Li, R.; Wang, G.L.; Jin, Y.; Xu, W.; Wang, H.; Qu, J. Organic amendment improves rhizosphere environment and shapes soil bacterial community in black and red soil under lead stress. J. Hazard. Mater. 2021, 416, 125805. [Google Scholar]
  55. Wu, S.C.; Luo, Y.M.; Cheung, K.C.; Wong, M.H. Influence of bacteria on Pb and Zn speciation, mobility and bioavailability in soil: A laboratory study. Environ. Pollut. 2006, 144, 765–773. [Google Scholar]
  56. Brallier, S.; Harrison, R.B.; Henry, C.L.; Xue, D.S. Liming effects on availability of Cd, Cu, Ni and Zn in a soil amended with sewage sludge 16 years previously. Water Air Soil Pollut. 1996, 86, 195–206. [Google Scholar]
  57. Lin, A.; Zhang, X.; Yang, X. Glomus mosseae enhances root growth and Cu and Pb acquisition of upland rice (Oryza sativa L.) in contaminated soils. Ecotoxicology 2014, 23, 2053–2061. [Google Scholar]
  58. Wang, D.F.; Liu, Y.G.; Tan, X.F.; Liu, H.Y.; Zeng, G.M.; Hu, X.J.; Jian, H.; Gu, J.L. Effect of exogenous nitric oxide on antioxidative system and S-nitrosylation in leaves of Boehmeria nivea (L.) Gaud under cadmium stress. Environ. Sci. Pollut. Res. Int. 2015, 22, 3489–3497. [Google Scholar]
  59. Lukovic, J.; Merkulov, L.; Pajevic, S.; Zoric, L.; Nikolic, N.; Borisev, M. Quantitative Assessment of Effects of Cadmium on the Histological Structure of Poplar and Willow Leaves. Water Air Soil Pollut. 2012, 223, 2979–2993. [Google Scholar]
  60. Lan, H.; Liu, H.; Ye, Y.P.; Yin, Z.N. The role of surface properties on protein aggregation behavior in aqueous solution of different pH values. AAPS Pharm. Sci. Tech. 2020, 21, 13. [Google Scholar]
  61. Kazuto, S.; Tomohiro, S.; Hideki, K. High-heat effects on the physical and chemical properties of soil organic matter and its water-soluble components in Japan’s forests: A comprehensive approach using multiple analytical methods. Anal. Sci. 2020, 36, 601–605. [Google Scholar]
  62. Diaconu, M.; Pavel, L.V.; Hlihor, R.-M.; Rosca, M.; Fertu, D.I.; Lenz, M.; Corvini, P.X.; Gavrilescu, M. Characterization of heavy metal toxicity in some plants and microorganisms—A preliminary approach for environmental bioremediation. New Biotechnol. 2020, 56, 130–139. [Google Scholar]
  63. Gao, Y.; Miao, C.; Xia, J.; Mao, L.; Wang, Y.; Zhou, P. Plant diversity reduces the effect of multiple heavy metal pollution on soil enzyme activities and microbial community structure. Front. Environ. Sci. Eng. 2012, 6, 213–223. [Google Scholar]
  64. Casalta, E.; Montel, M.C. Safety assessment of dairy microorganisms: The Lactococcus genus. Int. J. Food Microbiol. 2008, 126, 271–273. [Google Scholar]
  65. Majumder, P.; Palit, D. Isolation, Identification and Characterization of Bacteria of Coal Mine Soil at Sonepur Bazari of Raniganj Coalfield, West Bengal. Int. J. Appl. Environ. Sci. 2017, 12, 1131–1140. [Google Scholar]
  66. Kelly, D.P.; Mcdonald, I.R.; Wood, A.P. The Family Methylobacteriaceae. Prokaryotes 2014, 11, 313–340. [Google Scholar]
  67. Thuy, T.A.; Flynn, W.P. DesuLfuromonas carbonis sp. nov., an Fe(III)-, S0- and Mn(IV)-reducing bacteriμm isolated from an active coalbed methane gas well. Int. J. Syst. Evol. Microbiol. 2015, 65, 1686–1693. [Google Scholar]
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Figure 1. Distribution of sampling points.
Figure 1. Distribution of sampling points.
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Figure 2. Change of pH value of soil sampling sites.
Figure 2. Change of pH value of soil sampling sites.
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Figure 3. Changes in organic carbon content in soil samples.
Figure 3. Changes in organic carbon content in soil samples.
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Figure 4. Changes in total nitrogen content in soil samples.
Figure 4. Changes in total nitrogen content in soil samples.
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Figure 5. Variation of soil sulfate (a), sulfide (b), and sulfur (c) values.
Figure 5. Variation of soil sulfate (a), sulfide (b), and sulfur (c) values.
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Figure 6. The iron content in soil and distribution changes of different iron forms at each sampling.
Figure 6. The iron content in soil and distribution changes of different iron forms at each sampling.
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Figure 7. The content of Mn in soil and distribution changes of different iron forms at each sampling.
Figure 7. The content of Mn in soil and distribution changes of different iron forms at each sampling.
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Figure 8. The content of Cu in soil and distribution changes of different iron forms at each sampling.
Figure 8. The content of Cu in soil and distribution changes of different iron forms at each sampling.
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Figure 9. The content of Zn in soil and distribution changes of different iron forms at each sampling.
Figure 9. The content of Zn in soil and distribution changes of different iron forms at each sampling.
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Figure 10. The content of Cd in soil and distribution changes of different iron forms at each sampling.
Figure 10. The content of Cd in soil and distribution changes of different iron forms at each sampling.
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Figure 11. DGGE lane images (a) and UPGMA dendrogram (b) of the microbial community of mining soil (Bacteria).
Figure 11. DGGE lane images (a) and UPGMA dendrogram (b) of the microbial community of mining soil (Bacteria).
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Figure 12. Diversity analysis of bacteria of each site.
Figure 12. Diversity analysis of bacteria of each site.
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Figure 13. Microbial (a) and archaea (b) community composition distribution of the samples.
Figure 13. Microbial (a) and archaea (b) community composition distribution of the samples.
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Figure 14. Relative abundance of functional genera in microbial samples.
Figure 14. Relative abundance of functional genera in microbial samples.
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Table
Table 1. Consulted value of heavy metals/mg∙kg−1.
Table 1. Consulted value of heavy metals/mg∙kg−1.
Project MnFeCuZnCd
Ma’anshan City //32.36784.7330.264
Anhui Province 5303.14 × 10420.4620.097
National Standard (I) //351000.20
pH < 6.5//502000.30
National Standard (II)pH: 6.5–7.5//1002500.30
pH > 7.5//1003000.60
National Standard (III) 583/4005001.0
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Guo, J.; Xuan, F.; Li, D.; Wang, J.; Zhang, B. Variations of Soil Chemical Properties and Microbial Community around the Acid Reservoir in the Mining Area. Sustainability 2022, 14, 10746. https://doi.org/10.3390/su141710746

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Guo J, Xuan F, Li D, Wang J, Zhang B. Variations of Soil Chemical Properties and Microbial Community around the Acid Reservoir in the Mining Area. Sustainability. 2022; 14(17):10746. https://doi.org/10.3390/su141710746

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Guo, Jing, Fengqin Xuan, Deming Li, Jiaquan Wang, and Baichuan Zhang. 2022. "Variations of Soil Chemical Properties and Microbial Community around the Acid Reservoir in the Mining Area" Sustainability 14, no. 17: 10746. https://doi.org/10.3390/su141710746

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