Trans. Nonferrous Met. Soc. China 31(2021) 1796-1805

Responses of bacterial community to potential heap construction methods of fine-grained copper tailings in column bioleaching system

Xiao-dong HAO^1,2, Xue-duan LIU², Ping ZHU^1,2, Yi-li LIANG², Guan-zhou QIU², Hong-qing MA¹, Yan LIU¹, Qian-jin LIU¹, Li-ying REN¹, Emmanuel Konadu SARKODIE², Hong-wei LIU²

1. Shandong Provincial Key Laboratory of Water and Soil Conservation and Environmental Protection, College of Resources and Environment, Linyi University, Linyi 276000, China;

2. School of Minerals Processing and Bioengineering, Central South University, Changsha 410083, China

Received 15 July 2020; accepted 30 March 2021

Abstract: The column bioleaching of copper flotation tailings was comparatively investigated using layered heap construction method (LM), agglomerate heap construction method (AM), and pellets-sintering heap construction method (PM). The bacterial communities of free, attached, weakly-attached, and strongly-attached microbes in the later bioleaching stage were investigated. In AM group, the addition of lump sulphide ore resulted in the low leachate pH, high ferric iron concentration, and rapid microbial adsorption, which obtained the maximum copper extraction (60.1%) compared with LM (54.6%) and PM (43.9%) groups. The relative abundance of dominant genera and microbial communities of different microbiota underwent changes in three heap construction methods. The alpha-diversity indexes of attached, weakly-attached, and strongly-attached microbes were different, while no significant change was observed in free bacteria. The variation of whole bacterial community was significantly associated with solution pH, total iron, and ferric iron concentrations. Pearson correlation analysis and partial least square path model both indicated that attached bacteria made larger contribution to the copper extraction of tailings.

Key words: fine-grained tailings; column bioleaching; heap construction method; free and attached bacteria; microbial diversity

1 Introduction

Flotation is the most widely used extraction technology in copper extractive fields worldwide and can produce 80% of the copper production of this commodity [1]. Meanwhile, flotation process can create numerous tailings annually. In large copper mining, one ton of copper concentrate generated produces 151 t of tailings [2]. The accumulation and storage of tailings in open-air condition can cause potential environmental and societal problems. The physicochemical and biological reactions that occur in the stock heap improve the trace metals mobility of exposed tailings. As a result of the oxidation of sulfur minerals, the generation of acid drainage (low pH and high heavy metals) poses a great danger to farmland and underground water [3-5]. Tailings can also be considered as a secondary source because they contain a large number of valuable metals such as Cu, Co and Ni, which can mitigate the inconsistency between the decline in high-grade minerals and the rise in the demand for metal resources [6,7]. Hence, the recycling processing of tailings and the recovery of valuable metals from this waste are necessary to increase the utilization values of tailings [8].

Bioleaching is a low-cost and eco-friendly extraction technology for the recovery of trace metals from tailings and low grade ores [9,10]. However, tailings with high level of fines can reduce the permeability of leachate, restrict the transfer of gases (e.g., oxygen and carbon dioxide), and delay the microbial adsorption especially in dump bioleaching operation, and thereby decrease the dissolution efficiency of tailings [11]. Several efforts have been made to increase the permeability of stock heap and improve the extraction yields. Thin-layer conveying and dumping performance accompanied by other technological improvements is used to enhance the heap permeability and copper extraction from low-grade copper oxides of Yangla Copper Mine located in Yunnan Province of  China [12]. The need for agglomeration method of ores with binders such as polymer materials is recommended in heap leaching operation to gain high metal leaching rates if the ores contain lots of fines [13]. These strategies have promoted the industrial practice of highly fine-grained tailings heap bioleaching [14]. However, comparative study on the effects of different potential heap constructions on tailings dissolution is very limited, and there are also few records on the correlations between bacterial community and copper extraction of tailings using diverse heap construction methods.

The bioleaching process involves multiple biological, chemical and physical reactions [15,16]. Microbial interaction is considered as the main driving factor to dissolve minerals via various biochemical pathways [17]. Microbial ecology studies relevant to the essential leaching  parameters of leachate in the bioleaching method can approximate the phylogenetic microbiota interaction [18]. Bacterial communities of free and attached cells, growing in different bioleaching subsystems, are different and play specific roles of elemental sulfur and ferrous iron oxidization in promoting the bioleaching efficiency through direct or indirect mechanisms [19,20]. However, the attached microbial community on the tailings surface, accounting for most of total biomass, is still not well understood, especially concerning the linkage between attached community structure and copper extraction. It is necessary to monitor the community compositions of free and attached bacteria to obtain complete comprehension in the contributions of distinct microbiota to tailings bioleaching.

In this work, we constructed the column bioleaching of flotation tailings using three different heap construction methods. The bacterial communities in three groups were analyzed by 16S rRNA MiSeq high-throughput sequencing. The major objective of this study was to address the following questions: do different heap construction methods alter the bioleaching behaviors and microbial diversities of free and attached bacteria? and how these changes affect the tailings bioleaching efficiency?

2 Experimental

2.1 Ore samples

Copper flotation tailings used in this study were collected from Lualo Tailing Dam of Zambia. Particle size distribution of tailings was ~75 μm (48%), 75-150 μm (43%) and 150-270 μm (9%), respectively. X-ray diffraction analysis showed that SiO₂ (60.7%), Fe_xO (25.6%) and MgO (3.2%) were the main components of tailings. Copper phase analysis showed that tailings contained 0.06%  free copper oxide, 0.01% combined copper oxide, 0.06% secondary copper sulfide and 0.07% primary copper sulfide. The main element contents of tailings were 0.2% Cu, 19.7% Fe and 2.3% S. Another kind of lump sulphide ores sized at 2.5-5 mm, which served as the core of agglomerate ores adhering the flotation tailings, were obtained from Yulong Copper Mine in Changdu city of China. The main element composition was 2.8% Cu, 16.6% Fe and 17.4% S.

2.2 Preparation of mixed mesophilic acidophiles

The enrichment of the mixed mesophilic acidophiles for subsequent column bioleaching is as described by our previous study [21]. Briefly, acid mine drainage and leaching residue samples were obtained from a mine located in Jiangxi Province of China. Two samples were combined and then inoculated into culture medium (pH 2.0) at 30 °C to enrich the acidophilic consortium [6]. Cultures were supplemented with 4.5% FeSO₄·7H₂O, 1.0% S⁰ and 2.0% tailings as energy sources. Finally, mixed mesophilic acidophiles were obtained when the microbial density exceeded 1×10⁸ cells/mL. The top four dominant genera in enriched acidophilic consortium were Acidithiobacillus, Leptospirillum, Sulfobacillus and Ferroplasma.

2.3 Heap construction method and column bioleaching

Three kinds of potential heap construction methods including the layered heap construction method (LM), the agglomerate heap construction method (AM), and the pellets-sintering heap construction method (PM) were carried out (Fig. 1). LM was performed via the alternant loading of tailings and quartz sands sized at 2.5-5 mm. As a result, four layers of 5 cm-thick quartz sands and 5 cm-thick tailings were placed into the column, respectively. AM was processed via the blend of 10% H₂SO₄ solution and mixed ores (tailings mixed with lump ores). Then, agglomerate ores were put into the column. For PM operation, tailings added with 1.5% bentonite were granulated and sintered into agglomerate pellets (800 °C, 10 min), and subsequently loaded into the column. The column bioreactor was 50 cm high and the internal diameter was 7 cm. In three bioleaching groups, tailings with equivalent mass (1.3 kg) were loaded into each column. Column bioleaching experiments were operated at ambient temperature for 83 d including acid leaching process (10 d) using a 1.6 L culture medium of pH 1.5.

Fig. 1 Design of potential heap construction methods and configuration of column bioreactor (LM-Layered heap construction method; AM-Agglomerate heap construction method; PM-Pellets-sintering heap construction method)

2.4 Chemical and microbiological analysis

Column bioleaching tests were monitored regularly for the measurements of pH (pHS-3C, Leici, China), redox potential (ORP, BPH-220, Bell, China), cell density (BX41, Olympus, Japan) and total iron concentration (inductively coupled plasma-atomic emission spectrometry, Optima 5300 DV, Baird, China) in leachate solution. Ferrous iron concentration was measured by phenanthroline colorimetry method, and ferric iron concentration was equal to the difference of total iron and ferrous iron concentrations. Copper extraction was calculated according to

η=(W₁-W₂)/W₁×100%

where W₁ represents the Cu content of tailings before bioleaching, and W₂ represents the Cu content after bioleaching.

The genomic DNA of mixed mesophilic acidophiles (inoculum) and free microbes in leachate after bioleaching tests were extracted using a TIANamp Bacteria DNA kit (Tiangen Biotech., China). The genomic DNA of attached microbes, weakly-attached and strongly-attached microbes in three heap construction methods after bioleaching was extracted by the E.Z.N.A. Soil DNA kit (Omega Bio-Tek Inc., USA). Procedures for amplification, sequencing of 16S rRNA gene and raw data preprocessing are as described in our previous study [21].

2.5 Statistic analysis

One-way analyses of variance (ANOVA) followed by the least significant difference (LSD) test were carried out using IBM SPSS Statistics 21.0 software to determine the difference in leachate properties, relative abundance of dominant genera and alpha-diversities after bioleaching experiments in three heap construction methods. Dissimilarity tests (Adonis) was used to evaluate the significant differences in microbial community composition among three bioleaching groups. Non-metric multidimensional scaling analysis (NMDS) was carried out to compare the bacterial community structure using R ‘vegan’ package. Mantel test analysis was conducted to determine the relationship between leachate variables and bacterial community. Pearson correlation test was used to determine the correlation among copper extraction, leachate factors and dominant genera. Partial least squares path modeling (PLSPM) was performed using ‘amap’, ‘shape’, ‘diagram’ and ‘plspm’ packages to show the association of  copper extraction with leachate pH, ferric iron and microbial communities within three heap construction methods.

3 Results and discussion

3.1 Bioleaching of copper tailings by mixed mesophilic acidophiles

Different heap construction methods clearly impacted the bioleaching behaviors of three experimental groups. Leachate pH values increased rapidly in initial bioleaching process, which corresponded to the consuming proton stage of ferrous iron oxidation [11]. The pH values decreased gradually from Day 25 in LM and AM groups, and finally, the pH value of AM (1.3) was significantly (P<0.05) lower than that of LM (1.6) and PM (2.4) groups (Table 1). Among three groups, the highest solution cell density was observed in LM group during the whole bioleaching performance. Meanwhile, the time of bacterial numbers increase in LM solution (on Day 32) was later than AM group (on Day 17). The lowest permeability of LM group led to the longer time  of microbial adsorption onto tailings surface. The lump sulphide ore was used in AM bioleaching system, and sufficient energy sources (16.6% Fe and 17.4% S) accelerated the microbial growth in early experimental stage. However, the only decline phase among three groups was also found in AM group from Day 62, which can be attributed to the energy source consumption, increase in metal ions, and organic substances in last phage [22]. Non-obvious change of free cell density was presented in PM group. This was attributed to the sulfur element loss in the sintering treatment of tailings and the persistent higher solution pH, which severely inhibited the growth of acidophiles [23].

In acid leaching stage, ferrous iron was released from the tailings dissolution and was the main component of total iron in leachate. With the addition of mixed mesophilic acidophiles on Day 10, ferric iron resulted from the ferrous iron oxidation by the iron-oxidizers almost accounted for all of the total iron concentrations. However, ferric iron and total iron concentrations presented different change trends in three groups. Compared with LM and PM groups, the ferric iron concentration was higher and increased steadily in AM bioleaching process. The LM operation caused a lower permeability, but the ferric iron concentration was higher than that of PM group. In addition, the ferric iron concentration began to decline in bioleaching stage of PM group, which might infer the formation of jarosite due to the higher leachate pH values. After the bioleaching tests, the ferric iron concentration of LM group (2.6 g/L) was significantly (P<0.05) lower than  that of AM (19.7 g/L) group, but higher than that  of PM (0.11 g/L) group (Table 1). The iron ion concentration changes did not alter the variation tendency of leachate ORP values in three groups. In acid leaching operation, the ORP values decreased to about 350 mV, but were sharply enhanced on Day 5 with the increase of ferric iron concentration and then remained stable in subsequent bioleaching process.

Copper extraction of tailings based on copper contents was 60.1% in AM group, which was significantly (P<0.05) higher than that of AM (54.6%) and PM (43.9%) groups (Table 1). Pearson correlation analysis showed a significantly negative correlation between leachate pH and copper extraction (P<0.001), but a significantly positive correlation between copper extraction and total and ferric iron concentrations (P=0.006). In AM group, more sulfur element and ferrous iron were dissolved from the lump sulphide ores and supported the growth of mesophilic acidophiles. Elemental sulfur was oxidized into H₂SO₄ by sulfur-oxidizers, leading to the lower solution pH. Ferrous iron was oxidized into ferric iron serving as the major oxidizing reagent, which accelerated the tailings dissolution and Cu recovery of AM group [24]. In three heap construction methods, the solution permeability order was PM>AM>LM. Low solution permeability hindered the microbial colonization of mixed acidophiles and restricted oxygen and carbon dioxide transfer in ore body of LM group. These negative factors reduced the activity of microorganisms and slowed down the kinetics of tailings dissolution compared with AM group [25]. For PM group, high solution pH promoted the formation of jarosite inferred by the ferric ion concentration reduction [26]. The jarosite particles could wrap the tailings surface and block the interaction between tailings and acidophilic microbes, resulting in a lower copper extraction.

Table 1 Leachate properties after column bioleaching experiments and Pearson correlation analysis between leachate properties and copper extractions of flotation tailings using three heap construction methods

3.2 Bacterial community structure and diversity

Analysis of 16S rRNA gene sequences showed that the bacterial community compositions of free and attached microbes including weakly-attached and strongly-attached bacteria in three heap construction methods were different at the genus level (Fig. 2(a)). In the initial inoculum, the genera Acidithiobacillus (67.8%) and Sulfobacillus (24.6%) were the preponderant microorganisms, and the proportions of Leptospirillum and Ferroplasma were less than 9%. After the bioleaching of the tailings, the most abundant genera were Acidithiobacillus, Leptospirillum, Ferroplasma, and Acidiphilium. Comparisons of the differences in these bacterial genera among free, attached, weakly-attached, and strongly-attached microbes are shown in Figs. 2(b₁-b₄). Heap construction method significantly affected the distributional difference of the same dominant genus in three bioleaching groups. For the free bacterial composition, by comparing AM and PM groups, Acidithiobacillus and Leptospirillum were significantly (P<0.05) more abundant, and Acidiphilium were significantly (P<0.05) less abundant in LM (Fig. 2(b₁)). The most abundant genus in AM was Ferroplasma, while Acidiphilium accounted for the largest proportion in PM. The relative abundance of genera Acidithiobacillus, Sulfobacillus and Acidiphilium presented similar variation trends in attached and weakly-attached microbes among three bioleaching groups (Figs. 2(b₂, b₃)). In addition, the abundance of Leptospirillum and Ferroplasma ranked first in PM and AM groups, respectively. In strongly-attached microbial community, genera Acidithiobacillus and Acidiphilium accounted for the largest proportions in PM group (Fig. 2(b₄)). The genera Ferroplasma and Sulfobacillus had the highest abundance in LM group, but the abundance of Leptospirillum was significantly (P<0.05) lower than that in the other two groups.

The alpha diversity estimated by Shannon index of free bacterial community showed no significant (P>0.05) changes among three bioleaching groups, but significant (P<0.05) changes were observed in attached, weakly-attached, and strongly-attached microbial communities (Fig. 3). Shannon indexes of weakly-attached and strongly-attached communities in AM group were significantly (P<0.05) lower than those of LM and PM groups. The microbial growth of AM group entered into the decline phase in last bioleaching stage. Therefore, the deterioration of bioleaching environments and the consumption of energy sources might reduce the alpha diversity. Furthermore, Shannon index of PM group was lower than that of the LM group in attached cell community. The inadequate iron, sulfur energy sources, and higher solution pH in PM bioleaching system could result in the decrease in alpha diversity.

Non-metric multidimensional scaling (NMDS) analysis based on Bray-Curtis distance was utilized to analyze the overall structural variations of bacterial microbiota after bioleaching in three potential heap construction methods (Fig. 4). The results of NMDS analysis showed that bacterial communities were clearly separated among LM, AM and PM groups. Dissimilarity test using Adonis further confirmed significantly (P<0.05) different structures of microbial communities in the four groups including the inoculum. Besides, it was noted that attached bacterial community was clustered together with weakly-attached microbes of three groups, and distinguished from the free and strongly-attached microbial communities, which might be explained by the similar variation trends in the relative abundance of the dominant genera in attached and weakly-attached microbiota.

Fig. 2 Microbial compositions with different heap construction methods (a), and relative abundances of dominant genera in free (b₁), attached (b₂), weakly-attached (b₃) and strongly-attached microbes (b₄) (Different small letters above error bars indicate the significant difference according to LSD test (P<0.05))

3.3 Links among bacterial community, leachate property and copper extraction

Mantel test analysis was applied to exploring the associations between leachate properties and bacterial community structures in three groups (Table 2). The results showed that solution pH (P=0.024), total iron (P=0.007), and ferric iron (P=0.007) concentrations were significantly associated with the whole bacterial community. Leachate factors listed in Table 2 had a significant correlation with dominant genus Acidithiobacillus (P<0.01), but no significant associations were found between leachate factors and Sulfobacillus. In addition, total iron and ferric iron concentrations had significant associations with the relative abundance of Leptospirillum, Ferroplasma and Acidiphilium, and pH was also associated with the changes of Acidiphilium.

Fig. 3 Alpha diversity (Shannon index) with different heap construction methods (Different small letters above error bars indicate significant difference according to LSD test (P<0.05))

Fig. 4 Non-metric multidimensional scaling analysis results of bacterial community based on Bray-Curtis distance indices and dissimilarity test (Adonis) showing differentiation in microbial structures of different heap construction methods (F, A, W and S represent free, attached, weakly-attached and strongly-attached micro- bial communities, respectively)

Correlations between copper extractions of tailings and dominant genera in free, attached, weakly-attached, and strongly-attached microbial communities are given in Table 3. There was only one genus Ferroplasma in free microbial communityclosely correlated to copper extraction (P=0.005). However, in attached and weakly-attached microbial communities, five dominant genera all had significant correlations (P<0.05) with copper extractions, and Acidithiobacillus, Ferroplasma, and Acidiphilium were significantly (P<0.05) correlated to copper extractions in strongly-attached microbial community. These results indicated that, compared with free  microbes, attached microbes played more important role in affecting copper bioleaching efficiencies of tailings [27]. It is shown that there were substantial negative correlations between Acidithiobacillus, Sulfobacillus, and Leptospirillum, but Ferroplasma and Acidiphilium had significant positive correlations with copper extractions. The genera Ferroplasma and Acidiphilium were able to adapt to the adverse environments in last bioleaching stage. Organic matter originated from exudates and cell lysates of microorganisms could inhibit the growth of autotrophs [28]. The growth of Ferroplasma and Acidiphilium with organic matter as an energy source reduced the toxicity to autotrophs and therefore made positive contributions to the Cu recovery of tailings [29,30].

Table 2 Mantel test analysis results of relationship between leachate properties and bacterial community

Table 3 Pearson correlation analysis results between dominant genera and copper extractions of flotation tailings in three heap construction methods

In addition to correlation analysis, the relative importance of the associations of copper extractions with leachate pH, ferric iron, and microbial properties was analyzed using the partial least square path model (PLSPM) (Fig. 5). Leachate pH had significant negative effects on copper extraction (P<0.05) and ferric iron (P<0.05), but a significant positive effect was shown between ferric iron and copper extraction (P<0.01). Leachate pH had no significant effect both positively or negatively (P>0.05) on free and attached community  structures, but there were significant positive effects (P<0.001) on weakly-attached and strongly- attached microbial communities. Ferric iron concentration changes had significant positive correlations (P<0.01) with free and strongly- attached microbial communities and significant negative correlations (P<0.05) with attached and weakly-attached microbial communities, indicating that ferric iron was a more important factor affecting microbial community composition and structure in the later bioleaching stage. Free bacterial community had no impacts on copper extraction of tailings. However, attached bacterial community was positively correlated with copper extraction (P<0.01), and weakly-attached and strongly-attached microbial communities showed a negative correlation with copper extractions (P<0.01). These findings were consistent with the Pearson correlation analysis results (Table 3) demonstrating the significance of attached microbes to the copper recovery of tailings. A previous study also found that the contribution of attached cells in sulphide ore bioleaching was high at 50.5% [31].

Fig. 5 Partial least square path modeling showing association of copper extractions with leachate pH, ferric iron and microbial communities of free, attached, weakly-attached and strongly-attached microbes with different heap construction methods (Goodness of fit of the modeling is 0.7648; Blue and red arrows indicate positive and negative path coefficients, and solid and dashed lines indicate significant (P<0.05) and insignificant path coefficients (P>0.05), respectively; *, ** and *** indicate significances at the levels of P<0.05, 0.01 and 0.001, respectively)

4 Conclusions

(1) Different heap construction methods clearly impacted the bioleaching behaviors and copper extractions of the tailings of three experimental groups.

(2) The alpha diversity (except free microbiota) and beta diversity in three groups were significantly changed. Solution pH and ferric iron significantly influenced the whole microbial community and the most dominant genera.

(3) Pearson correlation and PLSPM analysis both indicated that the attached microbes played a positive contribution to the copper recovery of tailings compared with free microbes.

Acknowledgments

The authors are grateful for the financial supports from the National Key R&D Program of China (No. 2018YFC1801804), the Shandong Provincial Natural Science Foundation, China (Nos. ZR2020QD120 and ZR2018LD001), and Project of Introducing and Cultivating Young Talent in the Universities of Shandong Province, China (No. QC2019YY144).

References

[1] SALDANA M, AYALA L, TORRES D, TORO N. Global sensitivity analyses of a neural networks model for a flotation circuit [J]. Hemijska Industrija, 2020, 74: 247-256.

[2] TORO N, SALDANA M, CASTILLO J, HIGUERA F, ACOSTA R. Leaching of manganese from marine nodules at room temperature with the use of sulfuric acid and the addition of tailings [J]. Minerals, 2019, 9: 289.

[3] NAGAJYOTI P C, LEE K D, SREEKANTH T V M. Heavy metals, occurrence and toxicity for plants: A review [J]. Environmental Chemistry Letters, 2010, 8: 199-216.

[4] MIN X B, XIE X D, CHAI L Y, LIANG Y J, YONG K E. Environmental availability and ecological risk assessment of heavy metals in zinc leaching residue [J]. Transactions of Nonferrous Metals Society of China, 2013, 23: 208-218.

[5] TORO N, BRICENO W, PEREZ K, CANOVAS M, TRIGUEROS E, SEPULVEDA R, HERNANDEZ P. Leaching of pure chalcocite in a chloride media using sea water and waste water [J]. Metals, 2019, 9: 13.

[6] HAO X D, LIU X D, ZHU P, CHEN A J, LIU H W, YIN H Q, QIU G Z, LIANG Y L. Carbon material with high specific surface area improves complex copper ores^, bioleaching efficiency by mixed moderate thermophiles [J]. Minerals, 2018, 8: 301.

[7] WANG Y G, SU L J, ZENG W M, QIU G Z, WAN L L, CHEN X H, ZHOU H B. Optimization of copper extraction for bioleaching of complex Cu-polymetallic concentrate by moderate thermophiles [J]. Transactions of Nonferrous Metals Society of China, 2014, 24: 1161-1170.

[8] TORO N, JELDRES R I, ORDENES J A, ROBLES P, NAVARRA A. Manganese nodules in Chile, an alternative for the production of Co and Mn in the future—A review [J]. Minerals, 2020, 10: 674.

[9] MAKINEN J, SALO M, KHOSHKHOO M, SUNDKVIST J E, KINNUNEN P. Bioleaching of cobalt from sulfide mining tailings: A mini-pilot study [J]. Hydrometallurgy, 2020, 196: 105418.

[10] ZHANG R Y, HEDRICH S, ROMER F, GOLDMANN D, SCHIPPERS A. Bioleaching of cobalt from Cu/Co-rich sulfidic mine tailings from the polymetallic Rammelsberg mine, Germany [J]. Hydrometallurgy, 2020, 197: 105443.

[11] WANG Y G, SU L J, ZENG W M, WAN L L, CHEN Z, ZHANG L J, QIU G Z, CHEN X H, ZHOU H B. Effect of pulp density on planktonic and attached community dynamics during bioleaching of chalcopyrite by a moderately thermophilic microbial culture under uncontrolled conditions [J]. Minerals Engineering, 2014, 61: 66-72.

[12] YIN S H, WANG L M, WU A X, FREE M L, KABWE E. Enhancement of copper recovery by acid leaching of high-mud copper oxides: A case study at Yangla Copper Mine, China [J]. Journal of Cleaner Production, 2018, 202: 321-331.

[13] BOUFFARD S C. Agglomeration for heap leaching: Equipment design, agglomerate quality control, and impact on the heap leach process [J]. Minerals Engineering, 2008, 21: 1115-1125.

[14] HAO X D, LIANG Y L, YIN H Q, LIU H W, ZENG W M, LIU X D. Thin-layer heap bioleaching of copper flotation tailings containing high levels of fine grains and microbial community succession analysis [J]. International Journal of Minerals, Metallurgy, and Materials, 2017, 24: 360-368.

[15] PANDA S, PARHI P K, NAYAK B D, PRADHAN N, MOHAPATRA U B, SUKLA L B. Two step meso- acidophilic bioleaching of chalcopyrite containing ball mill spillage and removal of the surface passivation layer [J]. Bioresource Technology, 2013, 130: 332-338.

[16] GHASSA S, BORUOMAND Z, ABDOLLAHI H, MORADIAN M, AKCIL A. Bioleaching of high grade Zn–Pb bearing ore by mixed moderate thermophilic microorganisms [J]. Separation & Purification Technology, 2014, 136: 241-249.

[17] YELTON A P, COMOLLI L R, JUSTICE N B, CASTELLE C, DENEF V J, THOMAS B C, BANFIELD J F. Comparative genomics in acid mine drainage biofilm communities reveals metabolic and structural differentiation of co-occurring archaea [J]. BMC Genomics, 2013, 14: 485-499.

[18] VARDANYAN A, SAMVEL STEPANYAN S, VARDANYAN N, MARKOSYAN L, SAND W, VERA M, ZHANG R Y. Study and assessment of microbial communities in natural and commercial bioleaching systems [J]. Minerals Engineering, 2015, 81: 167-172.

[19] CRUNDWELL F K. How do bacteria interact with minerals? [J]. Hydrometallurgy, 2003, 71: 75-81.

[20] PORRO S, RAMIREZ S, RECHE C, CURUTCHET G, ALONSO-ROMANOWSKI S, DONATI E. Bacterial attachment: Its role in bioleaching processes [J]. Process Biochemistry, 1997, 32: 573-578.

[21] HAO X D, LIANG Y L, YIN H Q, MA L Y, XIAO Y H, LIU Y Z, QIU G Z, LIU X D. The effect of potential heap construction methods on column bioleaching of copper flotation tailings containing high levels of fines by mixed cultures [J]. Minerals Engineering, 2016, 98: 279-285.

[22] ZHOU H B, ZHANG R, HU P, ZENG W M, XIE Y, WU C, QIU G Z. Isolation and characterization of Ferroplasma thermophilum sp. nov., a novel extremely acidophilic, moderately thermophilic archaeon and its role in bioleaching of chalcopyrite [J]. Journal of Applied Microbiology, 2008, 105: 591-601.

[23] YU R L, SHI L J, GU G H, ZHOU D, YOU L, CHEN M, QIU G Z, ZENG W M. The shift of microbial community under the adjustment of initial and processing pH during bioleaching of chalcopyrite concentrate by moderate thermophiles [J]. Bioresource Technology, 2014, 162: 300-307.

[24] ZHAO H B, WANG J, GAN X W, ZHENG X H, TAO L, HU M H, LI Y N, QIN W Q, QIU G Z. Effects of pyrite and bornite on bioleaching of two different types of chalcopyrite in the presence of Leptospirillum ferriphilum [J]. Bioresource Technology, 2015, 194: 28-35.

[25] SISSING A, HARRISON S. Thermophilic mineral bioleaching performance: A compromise between maximizing mineral loading and maximizing microbial growth and activity [J]. Journal South African Institute of Mining and Metallurgy, 2003, 103: 139-142.

[26] OJUMU T V, PETERSEN J. The kinetics of ferrous ion oxidation by Leptospirillum ferriphilum in continuous culture: The effect of pH [J]. Hydrometallurgy, 2011, 106: 5-11.

[27] ZHU J Y, JIAO W F, LI Q, LIU X D, QIN W Q, QIU G Z, HU Y H, CHAI L Y. Investigation of energy gene expressions and community structures of free and attached acidophilic bacteria in chalcopyrite bioleaching [J]. Journal of Industrial Microbiology & Biotechnology, 2012, 39: 1833-1840.

[28] OKIBE N, GERICKE M, HALLBERG K, JOHNSON D. Enumeration and characterization of acidophilic micro- organisms isolated from a pilot plant stirred-tank bioleaching operation. [J]. Applied & Environmental Microbiology, 2003, 69: 1936-1943.

[29] ZENG W M, QIU G Z, ZHOU H B, PENG J H, CHEN M, TAN S N, CHAO W L, LIU X D, ZHANG Y S. Community structure and dynamics of the free and attached microorganisms during moderately thermophilic bioleaching of chalcopyrite concentrate [J]. Bioresource Technology, 2010, 101: 7068-7075.

[30] JOHNSON D B, HALLBERG K B. The microbiology of acidic mine waters [J]. Research in Microbiology, 2003, 154: 466-473.

[31] YANG H L, FENG S S, XIN Y, WANG W. Community dynamics of attached and free cells and the effects of attached cells on chalcopyrite bioleaching by Acidithiobacillus sp. [J]. Bioresource Technology, 2014, 154: 185-191.

细粒铜尾矿生物柱浸体系下细菌群落对潜在的铺矿形式的响应

郝晓东^1,2，刘学端²，朱 萍^1,2，梁伊丽²，邱冠周²，马宏卿¹，刘 艳¹，刘前进¹，任丽英¹，Emmanuel Konadu SARKODIE ²，刘宏伟²

1. 临沂大学 资源环境学院 山东省水土保持与环境保育重点实验室，临沂 276000；

2. 中南大学 资源加工与生物工程学院，长沙 410083

摘  要：比较研究分层铺筑(LM)、聚团铺筑(AM)和烧结球团铺筑(PM)三种铺矿形式对铜浮选尾矿生物柱浸的影响。解析尾矿浸出后期三组浸矿体系下游离、吸附、弱吸附和强吸附微生物的群落结构。在AM浸出组，用于尾矿聚团的块状硫化矿的添加使浸出溶液pH值降低，三价铁离子浓度升高和微生物快速吸附。相比于LM(54.6%)和PM(43.9%)浸出组，AM浸出组得到最高的铜浸出效率(60.1%)。在不同尾矿铺筑形式下，不同微生物群的优势属的相对丰度和群落结构均发生明显变化。尾矿铺筑形式改变吸附、弱吸附和强吸附微生物群落的α-多样性指数，但未改变游离微生物群落的α-多样性。溶液pH值、总铁和三价铁浓度与整体细菌群落的变化呈现显著相关性。皮尔逊相关分析和偏最小二乘路径模型均表明吸附微生物对尾矿中铜浸出的贡献更大。

关键词：细粒尾矿；生物柱浸；铺矿形式；游离和吸附细菌；微生物多样性

(Edited by Bing YANG)

Corresponding author: Xiao-dong HAO, Tel: +86-731-88830546, E-mail: haoxiaodongxyz@163.com;

Hong-wei LIU, Tel: +86-731-88836943, E-mail: hongweiliu@csu.edu.cn

DOI: 10.1016/S1003-6326(21)65617-0

1003-6326/ 2021 The Nonferrous Metals Society of China. Published by Elsevier Ltd & Science Press