Spatiotemporal distribution of different forms of sulfur in acid mine drainage and their relationships with environmental factors

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This study aimed to characterize the spatiotemporal distributions of different forms of these intermediates and their relationships to environmental factors, focusing on an abandoned pyrite mine area. Samples were collected from different water stages and the physicochemical factors were determined on site. High performance liquid chromatography, ion chromatography, and Illumina high-throughput sequencing were used to determine the distributions of iron and sulfur forms and the microbial community structure at each site. Pearson and Spearman correlation were used to analyze the relationships between the distributions of different forms of sulfur and environmental factors during the formation and migration of AMD. The results suggested that SO 4 2− mainly originated from gypsum dissolution and oxidation of the coal mine and FeS 2 . The dry season was associated with lower water pH and temperature and higher DO and ORP. The maximum correlation coefficient between TFe and SO 4 2− decay was 0.9308, which could be attributed to the formation of sulfate secondary iron-containing minerals. SO 4 2− pollution decreased with increasing migration distance of AMD and showed seasonal variation closely related to precipitation and groundwater flow. The abundance and diversity of microbial community decreased with the production of AMD, mainly acidophilus and sulfur/iron-oxidizing bacteria. Ferrovum occupied an absolute dominant position in weakly acidic samples, and Acidibacter and Sphingomonas were not polluted. Neutral samples include Lachnospiraceae NK4A136 group , Ralstonia , Sinomonas , etc. pH and SO 4 2− showed negative correlations with DO, temperature, and ORP, whereas the dominant strain Acidithiobacillus was positively correlated with SO 4 2− . Increases in water temperature and ORP promoted the transformation of sulfur. The regulation of sulfur conversion to acid is key for developing strategies for preventing and reversing AMD pollution. Acid mine drainage FeS2 Migration and Transformation of Surfur Environmental Factors Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 1. Introduction Acid mine drainage (AMD) is an environmental pollutant that is typically produced in large volumes from diffuse sources and persists in the environment. AMD can lead to water body acidification and toxic metal pollution, thereby posing a risk to environmental and human health (Wang et al., 2021b ; Ding et al., 2019 ). Consequently, AMD has received widespread attention globally. AMD is mainly produced through the oxidation of metal sulfide minerals, particularly pyrite (FeS 2 ). The main pollutants of AMD include metal ions and SO 4 2− (Xin et al., 2021 ; Johnson and Hallberg, 2005 ). Most previous studies on AMD have focused on the environmental effects of the migration and transformation of toxic metals (Luo et al., 2022 ; Ying et al., 2022 ). In contrast, relatively few studies have examined the migration and transformation of sulfur forms in AMD. AMD pollution of water resources is more difficult to rehabilitate than that of the atmosphere (Zak et al., 2021 ) due to the great impact on the natural sulfur cycle (Nordstrom et al., 2015). AMD pollution leads to high concentrations of SO 4 2− and other sulfides in lakes, rivers, and other surface waters, which pose risks to aquatic ecosystems (Jiao et al., 2023). Sulfate accumulation in the surrounding soil also leads to environmental challengers, such as soil hardening and acidification, which can in turn negatively affect vegetation growth and crops (Lear et al., 2009 ; Yuan et al., 2022 ) as well as the health of the environment and humans (Ferreira et al., 2021 ; Gao et al., 2019 ; Neamtiu et al., 2017 ). Pyrite oxidation follows the thiosulfate and sulfur cycle pathways (Tu et al., 2017 ). S 2 O 3 2 produced by FeS 2 oxidation is unstable under acidic conditions, thereby leading to the conversion of SO 3 2− to S 0 , which in turn is oxidized to SO 3 2− , S 4 O 6 2− , and SO 4 2− (Schippers et al., 1996 ; Xu and Schoonen., 1995). Tu et al. ( 2017 ) studied the intermediate sulfur species of pyrite oxidation in the presence and absence of microorganisms; Huang ( 2011 ) analyzed the form of sulfur in hot spring water; Li et al. ( 2021 ) explored the distributions of sulfur forms in river water in a mining area. The sulfur transformation process is affected by environmental factors and the composition of AMD. Further study is needed on the relationships between different sulfur forms and environmental factors. The aim of the present study was to characterize the spatiotemporal distributions of different forms of sulfur in AMD and their relationships to environmental factors, focusing on a waste pyrite mining area in Luzhou City. The objectives of the present study were to characterize: (1) the spatiotemporal distributions of different sulfur forms in AMD; (2) the migration and transformation of sulfur forms and the relationships between them and environmental factors; (3) the main factors regulating AMD production. The results of the present study can contribute to management and rehabilitation of AMD in the environment. 2. Materials and methods 2.1 Study area The study area of the present study is in Luobu Town, Xuyong County, Sichuan Province (105° 27′ 04′′–105° 29′ 53′′ E, 28° 03′ 16′′–28° 07′ 16′′ N). The study area falls into a subtropical humid monsoon climate zone with a temperature ranging from − 8.5 to 41.9°C. Rainfall is seasonal, with 70% of annual rainfall in summer and autumn. Surface water is mainly supplied by seasonal streams, gullies, and karst caves. The terrain of the study area decreases from south to north and is highly variable. Strata of the Triassic Feixianguan Formation ( T 1 f ) form a band on one side of the mountain; the Permian Longtan Formation ( P 2 l ) stratum is in an inclined trough valley; carbonate formations, such as the Permian Maokou and the Qixia formations ( P 1 m + q ), manifest as karst landforms. The study area has well-developed karst landforms, including caves, funnels, hills, dissolution depressions, and troughs. The underground river pipeline system of the study area is also complex. Underground tunnel mining is the main form of pyrite mining in the study area. The mining process has disrupted the original strata and water flow channels and has led to exposure of nodular siderite and pyrite to the atmosphere. Groundwater in the aquifer tends to converge in abandoned mines, with this water reacting with pyrite and leading to leaching of iron and sulfur. 2.2 Sample collection and preservation The present study collected 63 groundwater samples from 7 sampling points: D1 as a control point, D2, D3, and D5 as points of FeS 2 mine water inflow, D4 to represent coal mine water, and D6 and D7 as AMD inflow points. Samples were collected in the wet season, normal season, and dry season (Fig. 1 ) pH, dissolved oxygen (DO), oxidation-reduction potential (ORP), and total dissolved solids (TDS) were measured on site using a portable water quality meter. Sample collection, transportation, storage, and analysis were strictly in accordance with Chinese groundwater quality standards (GB/T14848-2017). Samples were taken at a depth of 0.2 m. Water samples were filtered through a 0.22-um filter membrane, after which samples were decanted in bottles to overflowing to prevent air bubbles, and stored at a temperature of 4°C. Samples were transported back to the laboratory and tested within 48 h. Sample fixation on site was needed to stabilize unstable forms of sulfur. SO 3 2− , S 2 O 3 2− , and S 4 O 6 2− were added to phosphate buffer and the pH of the solution was adjusted to 9.0 using sodium hydroxide. S 2− was added to zinc acetate and sodium hydroxide was added to the solution to a pH that would facilitate precipitation. Microbial samples were collected by centrifuge tube after high temperature sterilization at 120°C and stored at 4°C. Microbial samples were transported back to the laboratory and stored at − 80°C. Sample microbial characterization was completed within 48 h. 2.3 Testing samples and analysis The present study measured pH, DO, water temperature (T), and ORP of water samples. Sulfur forms of the water samples changed in response to changes in the physical and chemical properties of the water environment. Metal cations in the samples were determined by flame atomic spectrophotometry and ultraviolet spectrophotometry. Anions were determined by ion chromatography. The intermediate forms of sulfur was determined by high performance liquid chromatography (HPLC). S 2− was determined by p-aminodimethylaniline spectrophotometry. Methods used to characterize the microbial community of the samples included sample DNA purification, polymerase chain reaction (PCR) amplification, sample quantification, library construction, and sequencing. Sequencing of samples was completed by Luoning Biological Company. The present study used analytically pure chemical reagents to maintain quality assurance and quality control (QA/QC). The standard deviation of the test results was less than 5% and the sample recovery rate was between 90–110%. Microbial Alpha and Beta diversity were analyzed using R. Heat map analysis and the corr.test () function in the R psych package were used to conduct correlation analysis. PHREEQC software was used to analyze the SI-Gypsum saturation index and to simulate the distributions of Fe species and ion activity under different pH conditions. Grapher software was used to construct Piper three-line diagrams. 3. Results and discussion 3.1 Hydro-chemical characteristics The Piper trilinear diagram allows a general reflection of the chemical characteristics and hydro-chemical types of sample water and is widely used in groundwater hydro-chemical analysis and evaluation (Gao et al., 2021 ). The diamond component of the Piper diagram illustrates the hydro-chemical types of a groundwater sample for the dry, normal, and wet seasons (Fig. 2 ). The results showed that groundwater of the background point (D1) was of the HCO 3 -Ca-Mg type. The groundwater type of the remaining sites was SO 4 ·Cl-Ca·Mg. All groundwater samples were concentrated in the Piper diagram F area, indicating a sulfate type and a bicarbonate background water type. The diagram suggested that the high concentration of SO 4 2− in AMD in the study area may be mainly derived from FeS 2 . Ions in water reflect the weathering process affecting the chemistry of water and material transport of minerals in a basin. Therefore, water ions are a direct reflection of hydro-geochemical processes regulating water quality (Bajjali et al., 1997 ). The TDS content of the background point was between 293.6–324.1 mg/L; that of the FeS 2 gushing points were 4,924.9–11,476.6 mg/L. SO 4 2− and TDS in coal mine gushing water were much lower than those of FeS 2 acid gushing water at 730.9–930.9 mg/L and 1,877.4–2,038.4 mg/L, respectively. FeS 2 acid mine water generally showed high TDS and SO 4 2− and low pH. Therefore, TDS and SO 4 2− were negatively correlated with pH across all the seasons (Fig. 3 a, Fig. 3 b). TDS in the dry season exceeded that in the normal season and the wet season. TDS and SO 4 2− were highly correlated over all the seasons, indicating that SO 4 2− was the main salt contributing to TDS in the study (Fig. 3 c). As shown in Fig. 4 a, samples of gushing mine water and AMD were mainly distributed above the 1:1 line, indicating various sources of Ca 2+ in the samples. Samples of the background point were distributed on the 1:1 line (Fig. 4 b), indicating that these samples were mainly impacted by gypsum dissolution (Mao et al., 2023 ). The results indicated that oxidation of the coal mine was the source of SO 4 2− in coal mine water point D4, whereas oxidation of FeS 2 was the main contributor to the hydrochemistry of the remaining points. The SI values of all points were less than 0.5 (Fig. 4 c), whereas that of the background point was less than − 0.5. This result could be attributed to the good quality of the water sample due to high elevation of the background point. The SI values of the remaining points ranged from − 0.5 to 0.5, with all falling into a water-rock equilibrium state without excess SO 4 2− precipitation. The results of the correlation between Ca 2+ and SO 4 2− and the characterization of the geological background indicated that the gypsum dissolution dominated water chemistry and the background point, whereas oxidation leaching of FeS 2 s contributed to the high content of SO 4 2− of the remaining points. 3.2 Spatiotemporal distributions of physicochemical factors AMD pollution resulted in a difference in the pH of groundwater (Fig. 5 a). The pH of the background point ranged between 7.28 and 7.4, indicating overall neutral to weakly alkaline water; the pH of FeS 2 water inflow points ranged between 2.09 and 3.10, indicating highly acidic water; that of coal mine water inflow (D4) was between 6.84 and 7.00. The high concentration of HCO 3 − (> 470 mg/L) effectively neutralized acidity of samples resulting from AMD. The buffering effect was achieved by HCO 3 − counteracting SO 4 2− , resulting in persistence of neutral conditions (Majzlan et al., 2018 ). Outflow of acidic water resulted in erosion of D6 and D7 to their hydraulically related periphery and a pH of 3.15–3.5 and 3.55–4.17, respectively. There was clear seasonal variation in pH, with the lowest and highest pH in the dry season and wet season, respectively. Strong buffering was provided by the high concentration of Fe 3+ in the water body, where hydro-lyzation resulted in the release of a large quantity of H + . This effectively offset the surface runoff dilution effects in the wet season, resulting in consistently lower pH of the water body all the year round. DO in water samples was closely related to the distributions of sulfur and iron forms at different sites (Fig. 5 b). There was minor variation in DO at the background point; those at D2 and D3 were relatively low due to the large quantity of oxygen consumed during the oxidation of FeS 2 to produce AMD; DO was higher at D4 and D5 due to effective aeration and oxygenation. Migration of AMD resulted in its continuous contact with the atmosphere and the subsequent increases in DO at D6 and D7 from 4.37 to 5.16 mg/L and from 4.42 to 5.39 mg/L, respectively. DO in the dry season exceeded that in the wet season. The water temperature in the wet season exceeded those of the normal and dry seasons. Water temperature differed among the different sampling points (Fig. 5 d) due to the minimal effect of outside meteorological conditions on Groundwater. The integration of ORP with other water quality indicators can reflect the ecological environment. ORP was different among the different sampling points with no clear seasonal variation (Fig. 5 c). The ORP values at D2, D3, and D5 were between 441.3 and 549.6 mV, with that at D5 the highest. This site was also shown to be highly oxidizing. Gushing out of mine water contributed to a downward trend in ORP along the direction of groundwater flow. D4 remained in a flooded state due to long-term blocking off of the mine, in which ORP ranging from − 120.9 to − 99.3 mV, indicating the high reducibility of the environment at this point. 3.3 Spatiotemporal distributions of sulfur species 3.3.1 Spatiotemporal distribution of SO 4 2− The background point showed a low concentration of SO 4 2− of 33.94 to 55.15 mg/L. The mine FeS 2 drainage point had a relatively high FeS 2 concentration, reaching 10,873.93 mg/L in the dry season. Coal mine water had a SO 4 2− exceeding 800 mg L all the year round. There was an attenuation in SO 4 2− along the direction of groundwater flow. The migration of SO 4 2− showed non-conservative behavior closely related to the formation and adsorption of secondary high-iron minerals. In addition, suspended solids and sediment surfaces in AMD were positively charged, thereby facilitating further adsorption of SO 4 2− (Chen et al., 2015 ). The dry-season SO 4 2− concentration exceeded that in the normal and wet seasons. The results of T-test analysis showed that the decreases in dry and wet season SO 4 2− concentrations were closely related to seasonal precipitation and groundwater flow. These processes resulted in the formation of various complexes with SO 4 2− in aqueous solution to form Fe-SO 4 . The simulattioned by the PHREEQC software (Fig. 6 b) showed that the rank of different sulfate forms in the study area according to concentration was SO 4 2− > FeSO 4 0 > HSO 4 − > FeHSO 4 − > FeSO 4 + > Fe(SO 4 ) 2 − > FeHSO 4 2+ . The proportion of SO 4 2− gradually increased with increasing pH. SO 4 2− in the study area mainly existed in the form of SO 4 2− . 3.3.2 Spatiotemporal distribution of metastable sulfur The main sulfur form in AMD was + 6 valence SO 4 2− , whereas the accumulations of metastable sulfur forms (SO 3 2− , S 2 O 3 2− , S 4 O 6 2− , and S 2− ) were minor (Fig. 7 ). SO 3 2− , S 2 O 3 2− , and S 4 O 6 2− of the water gushing point (D2, D3, D5) were incompletely oxidized to SO 4 2− , with a small quantity of accumulation. The rank of the different sampling points in terms of quantities of sulfur forms was D3 > D5 > D4 > D2 (Fig. 7 a, 7 b, 7 c). S 2− can accumulate in trace quantities during the redox of sulfur. D4 showed the highest accumulation of S 2− (Fig. 7 d). This result can be attributed to the redox potential of the water environment. Environments with strong reducibility tend to show a greater accumulation of S 2− (Sun et al., 2014 ). Migration of AMD results in rapid oxidation of the metastable sulfur. Some metastable sulfur forms showed clear seasonal variation. Wet season SO 3 2− exceeded those in the normal and dry seasons. S 2− was also highest in the dry season. The main form of metastable sulfur in AMD was SO 3 2− , followed by S 4 O 6 2− and S 2 O 3 2− , whereas the content of S 2− was very low. These results can be attributed to the conversion of S 4 O 6 2− and S 2 O 3 2− to + 4 valence SO 3 2− before conversion to SO 4 2− . Consequently, the accumulation of SO 3 2− exceeded those of other forms of metastable sulfur. Since S 2− is typically present in a reducing environment, the strong oxidizing environment of AMD restricts the accumulation of S 2− to a low level. 3.4 Distributions of iron forms Fe valence states of AMD were + 2 and + 3 and there were low contents of Fe 3+ and Fe 2+ at the background point D1 (Fig. 8 a). The average total iron concentrations of D2, D3, and D5 were 1,780.35 mg/L, 977.98 mg/L, and 902.51 mg/L, respectively. Fe of coal mine water (D4) was low (3.22 mg/L) and mainly in the form of Fe 3+ . The evolution of Fe was regulated by changing redox conditions during water flow. There was a significant positive correlation between total iron (TFe) and SO 4 2− (Fig. 8b; R 2 = 0.9308), which could be attributed to input from tributaries and the generation of many secondary iron minerals (Bao et al., 2018 ). Seasonal variation in of TFe was consistent with that of SO 4 2− , with stepwise downward trends across all three seasons, indicating that Fe was also affected by precipitation and groundwater flow. Fe in AMD can form various complexes with SO 4 2− , and pH significantly changes the morphology and activity of each Fe-S complex. PHREEQC simulation of the distribution of Fe (II) speciation (Fig. 8 c) showed that large quantities of Fe 2+ and SO 4 2− formed an FeSO 4 0 complex in acidic water (pH < 2.5) due to the high concentration of SO 4 2− , with the content of this complex slightly exceeding that of free Fe 2+ . The concentration of SO 4 2− gradually decreased with increasing pH, and the proportion of free Fe 2+ in the water gradually increased. Under an acidic environment (2.5 < pH FeSO 4 0 > FeHSO 4 + > FeOH + >> Fe(OH) 2 0 > > Fe(OH) 3 − . At a pH > 5.1, the ionic activity of FeOH + exceeded that of FeHSO 4 + . Complexation of Fe (III) exceeded that of Fe (II), with the former forming various complexes (Fig. 8 d). Fe (III) in an acidic environment (pH < 3.9) mainly existed in the FeSO 4 + , Fe(SO 4 ) 2 − , and FeHSO 4 2+ forms. Under an acidic environment (3.9 < pH < 4.9), Fe(OH) 2 + and Fe(OH) 2+ in addition to FeSO 4 + were the main complex states. With increasing pH above 4.9, there was a rapid increase in the ion activity of Fe(OH) 3 , becoming the most important complex state in neutral water, whereas the contents of other Fe (III) forms gradually decreased. The redox potential and pH of AMD are comprehensive reflections of changes in Fe and S in the water environment. Figure 9 shows the boundary conditions in Fe and S morphological stability (Sun et al., 2014 ). Redox conditions regulate changes in S and Fe species. Iron mainly exists in the form of Fe 2+ at a pH < 3. Fe 3+ dominated the iron forms in AMD pollution sites due to the influences of pH, redox potential, and DO. Fe(OH) 3 was the dominant Fe form at the background point. The distribution of sulfur forms indicated a negative oxidation-reduction potential of D4 coal mine water, with the sample distributed on the boundary between H 2 S(aq) and SO 4 2− . This point accumulated S 2− , whereas oxidation affected the remaining points, leading to the dominance of positive hexavalent SO 4 2− . 3.5 Spatial characteristics of microbial community structure 3.5.1 Microbial community diversity The α-diversity index of samples reflects the abundance, uniformity, and diversity of microbial communities. Table 1 shows the operational taxonomic units (OTUs) and Chao 1, Shannon, and Simpson indices of each sample. The present study achieved a > 98% coverage of all 7 samples, indicating that the present study comprehensively characterized the microbial community of environmental samples. Abundance of the microbial community is reflected by the OTUs and Chao 1 index. The background point (D1) and point D2 showed the highest and lowest numbers of OTUs at 509 and 125, respectively. The neutral D1 and D4 samples showed the highest Chao 1 index values of 510.5000 and 472.4839, respectively, whereas D2 under the lowest pH had the lowest Chao 1 index of 158.4615. The Chao 1 index values of the remaining samples were low, at an average of 348.1074. The Simpson and Shannon index values of the samples reflected the diversity of the microbial community and were highest for neutral samples at D1 and D4 at 5.15 and 0.98, respectively; those of samples affected by lower pH (D2, D3, D5, D6, D7) were at an average of 2.47 and 0.60, respectively. These results indicated that microbial community abundance and diversity decreased with decreasing pH. The present study conducted Principal Co-ordinates Analysis (PCoA) to further analyze differences between samples and the possible driving factors (Fig. 10 ). Principal coordinates 1 and 2 (PCo1 and PCo2) explained the most observed variation in the seven samples of 47% and 25%, respectively. In the PCoA plot, D2 (pH < 2.2) was in the second quadrant; the remaining mine water gushing points and AMD pollution points (2.2 < pH < 4) were gathered at the junction of the first and fourth quadrants; points D1 and D4 (neutral pH) were gathered in the third quadrant. These results showed significant differences in microbial community among samples under different pH conditions. Table 1 The α diversity index of the microbial community in the study area Sample OTUs Chao 1 Shannon Simpson Coverage D1 509 510.5000 5.016988 0.972192 0.998961 D2 125 158.4615 2.857449 0.569117 0.995548 D3 300 343.9091 2.313590 0.584752 0.989611 D4 462 472.4839 5.284899 0.988506 0.996141 D5 311 363.7143 2.010801 0.491940 0.987830 D6 286 332.1220 2.608647 0.652277 0.990798 D7 276 352.6842 2.538871 0.697020 0.986049 3.5.2 Microbial community composition (1) Phylum-level analysis of microbial community composition There were significant phylum-level differences in microbial community structure of samples under different levels of AMD pollution (Fig. 11 ). Proteobacteria has been shown to dominate environments affected by AMD (Bao et al., 2017 ). The results of the present study observed a similar trend, with this phylum dominant in the seven samples in the study area, and particularly in samples under an acidic environment (D2, D3, D5, D6, D7), reaching a proportion of 83%. The average proportion of Proteobacteria in neutral water samples (D1, D4) was 36.01%. Firmicutes , Bacteroidetes , and Actinobacteria were also widely distributed in the study area, particularly in coal mine water gushing water (D4), reaching 23.57%, 17.88%, and 8.92%, respectively. Acidobacteria was relatively abundant in D1. The highest abundance of Euryarchaeota was in D2 (8.67%) characterized by the highest concentrations of SO 4 2− and TFe and lowest pH, indicating that this phylum is found in areas of serious AMD pollution. AMD pollution and mineral composition appeared to significantly change the composition of microbial species. (2) Genus-level analysis of microbial community composition Dominant bacteria at the genus level at point D1 included Acidibacter , Sphingomonas , MND1 , and RB41 ; at D4 they included Lachnospiraceae NK4A136 group, Ralstonia, Enterobacter, Pelomonas , and Sinomonas . Buffering by bicarbonate resulted in a close to neutral pH at D4 and this site had low metal ions concentrations. Consequently, microbial diversity at D4 was relatively high, whereas the proportion of sulfur-oxidizing microorganisms was relatively small. The relative abundance of Ferrovum among sampling points exceeded 60%, except at D2 in which it was 9.36%. Ferrovum is an iron-oxidizing bacterium that can fix carbon through the Calvin-Benson-Bassham cycle and is widely distributed in iron-containing acidic water (Hua et al., 2015 ). Acidithiobacillus was the dominant genus in D2 at 27.75%. Acidithiobacillus has been shown to tolerate acidic (pH < 2.5) and warm (30°C) water. The results showed that the distribution of microbial community structure was closely related to water pH and temperature. At the same time, the concentrations of SO 4 2− and Fe in D2 exceeded those at other sites. This result indicated that Acidithiobacillus may have stronger acid production capacity. Acidithiobacillus ferrooxidans ( At.f ) was the only member of Acidithiobacillus at D2. This species can oxidize Fe 2+ to Fe 3+ . The genus Metallibacterium was the third-most abundant in the study area and dominated D2 (21.21%). Microbes of genus Metallibacterium are tolerant to a wide range of pH environments, and similar to Acidithiobacillus , can obtain energy through oxidation-reduction of ferrous and sulfur compounds (Bartsch et al., 2017 ). In addition, D2 showed relatively high proportions of Acidibacter and Ferrithrix . Both genera represent thermophilic bacteria which have a tolerance for high temperatures (± 30°C). These results suggest that AMD pollution significantly changes the diversity and community structure of microorganisms in the water environment, with serious AMD pollution significantly reducing microbial diversity and resulting in the dominance of acidophilic and sulfur/iron oxidizing bacteria. Acidophilic and sulfur/iron oxidizing bacteria further lead to water acidification. Oxidation facilitated by At.f and Metallibacterium results in the rapid acceleration of the cyclic conversion rate of sulfur in AMD, with metastable sulfur rapidly converted to SO 4 2− . Abundance of Acidithiobacillus and Metallibacterium in D2 far exceeded that in D3, D4, and D5.Therefore, metastable sulfur in mine water (D2) was lower than that in other mine water samples. 3.6 Analysis of relationships between sulfur and Fe forms 3.6.1 Physical and chemical factors regulating sulfur and Fe forms The present study examined the correlations between sulfur and iron forms and the regulating impacts of environmental factors. The proportions of different sulfur and iron forms were used to determine correlations. Data for environmental factors were assumed to follow normal distributions. Pearson correlation analysis was used to calculate correlation coefficients (Fig. 13 ). The results showed that pH was negatively and positively correlated with total sulfur (TS) and S 2− , respectively; water temperature and ORP were positively correlated with TS and TFe. SO 4 2− accounted for > 99% of TS at each point, indicating that SO 4 2− content in AMD was proportional to acidity. Increases in water temperature and ORP promoted the conversion of sulfur, thereby generating SO 4 2− . The results showed that DO significantly affected the valence states of iron and sulfur. DO showed negative correlations with Fe 2+ and metastable sulfur, indicating that DO promoted the conversion of Fe 2+ and metastable sulfur to Fe 3+ and SO 4 2− . 3.6.2 Microbial species abundance The present study examined correlations between microbial species abundance and environmental factors. Spearman analysis was used to identify the 10 most abundant species at the genus level for analyzing correlations with sulfur forms (Fig. 14 ). The abundance of At.f showed significant positive correlations with SO 4 2− and TFe and a significant negative correlation with pH. At.f also showed positive correlations with metastable sulfur forms S 2− , SO 3 2− , S 2 O 3 2− , and S 4 O 6 2− . This result indicated that At.f promotes the transformation of iron and sulfur. At.f dominated the microbial community at D2 and SO 4 2− and iron at this sampling point far exceeded those at other sites. Ferrovum is an iron-oxidizing bacterium and dominated the microbial community at the remaining acidic water sites. Ferrovum mainly oxidizes Fe 2+ rather than sulfur. Therefore, the dominance of Ferrovum was dependent on the presence of sufficient Fe 3+ and O 2 to oxidize FeS 2 . The ability of Ferrovum to produce acid is weaker than that of Acidithiobacillus . Metallibacterium also showed significant positive correlations with SO 4 2− and TFe and a significant negative correlation with pH. Ralstonia showed significant positive correlations with metastable sulfur forms S 2− , SO 3 2− , S 2 O 3 2− , and S 4 O 6 2− , indicating that Ralstonia has a certain reducing capacity. 4. Conclusions The present study aimed to characterize the spatiotemporal distributions of different forms of sulfur in AMD and their relationships to environmental factors, focusing on a waste pyrite mining area in Luzhou City. The main conclusions of the present study are summarized below: (1) Along the AMD runoff direction, the hydro-chemical type changed from HCO 3 -Na type to SO 4 ·Cl-Ca·Mg type. The point − 0.5 < SI < 0.5 is in the water-rock equilibrium state, and presents the characteristics of high TDS, high SO 4 2− and low pH. SO 4 2− is mainly derived from gypsum dissolution, coal mine oxidation and FeS 2 oxidation. The physical and chemical factors showed obvious spatial and temporal changes. In the dry season, the pH and temperature of the water body were lower, and the DO and ORP were higher. (2) The sulfur form in AMD in the study area is mainly SO 4 2− , and the metastable sulfur SO 3 2− 、S 2 O 3 2− 、S 4 O 6 2− and S 2− have only a small amount of accumulation in the cyclic transformation of sulfur. With the migration of AMD, they are gradually oxidized to SO 4 2− . The concentrations of SO 4 2− and S 2− in the dry season were higher than those in the normal season and the wet season, and the contents of SO 3 2− , S 2 O 3 2− and S 4 O 6 2− were the highest in the wet season, indicating that the distribution of sulfur forms was affected by seasonal changes and was closely related to precipitation and groundwater flow. (3) In AMD, Fe (II) is mainly in the form of free Fe 2+ and complex FeSO 4 0 . Fe (III) mainly exists in the form of complex state, and the activity of each complex state changes with the change of pH and the attenuation of SO 4 2− . Fe 2+ and Fe 3+ coexisted in the original environment, and were oxidized to Fe 3+ with the increase of DO and pH. The correlation coefficient between TFe and SO 4 2− decay is as high as 0.9308, which is closely related to the formation of sulfate secondary iron-bearing minerals. (4) AMD decreased the abundance and diversity of microbial communities and resulted in the dominance of acidophilus and sulfur/iron-oxidizing bacteria, including Acidithiobacillus and Metallibacterium . Dominant genera at sites not impacted by AMD included Acidibacter and Sphingomonas ; those at sites impacted by AMD but with neutral pH included Lachnospiraceae NK4A136 group, Ralstonia , and Sinomonas . (5) Environmental factors regulated the distribution of sulfur forms. There was a negative correlation between pH and SO 4 2− , whereas SO 4 2− was positively correlated with DO, temperature, ORP, total iron, and Acidithiobacillus . SO 4 2− promoted acidity. Increases in water temperature and ORP facilitated the conversion of sulfur. At.f promoted the conversion of iron and sulfur, indicating that environmental factors regulate the conversion of sulfur. Declarations Author Contribution Man Gao wrote the main manuscript text ,Guo Liu analysis. All authors reviewed the manuscript. References Wang Z, Xu Y, Zhang Z, et al. 2021b. Review: Acid mine drainage (AMD) in abandoned coal mines of Shanxi, China. Water, 13(1): 8. Ding C, Li Q, Guo C L, et al. 2019. Effect of acid mine drainage on microbial community structure in paddy soil. Acta Scientiae Circumstantiac, 39(09): 3080-3089. Xin R, Banda J F, Hao C, et al. 2021. Contrasting seasonal variations of geochemistry and microbial community in two adjacent acid mine drainage lakes in Anhui Province, China. Environmental Pollution, 268: 115826. Johnson D B, Hallberg K B. 2005. Acid mine drainage remediation options: a review. Science of the Total Environment, 338(1): 3-14. Luo Y H, Rao J P, Jia Q X. 2022. Heavy metal pollution and environmental risks in the water of Rongna River caused by natural AMD around Tiegelongnan copper deposit, Northern Tibet, China. PLoS One, 17(4): e0266700. Ying H, Zhao W T, Feng X H, et al. 2022. The impacts of aging pH and time of acid mine drainage solutions on Fe mineralogy and chemical fractions of heavy metals in the sediments. Chemosphere, 303: 135077. Zak D, Hupfer M, Cabezas A, et al. 2021. Sulphate in freshwater ecosystems: A review of sources, biogeochemical cycles, ecotoxicological effects and bioremediation. Earth-Science Reviews, 212: 103446. Nordstrom D K. 2015. Baseline and premining geochemical characterization of mined sites. Applied Geochemistry, 57: 17-34. Lear G, Niyogi D, Harding J, et al. 2009. Biofilm bacterial community structure in streams affected by acid mine drainage. Appl Environ Microbiol, 75(11): 3455-3460. Yuan J Q, Bai S J, Bi Y X, et al. 2022. Research progress on treatment and comprehensive utilization of acid mine wastewater at home and abroad. Nonferrous Metals Engineering, 12(04): 131-139. Ferreira R A, Pereira M F, Magalhães J P, et al. 2021. Assessing local acid mine drainage impacts on natural regeneration-revegetation of São Domingos mine (Portugal) using a mineralogical, biochemical and textural approach. Science of the Total Environment, 755: 142825. Gao P, Sun X, Xiao E, et al. 2019. Characterization of iron-metabolizing communities in soils contaminated by acid mine drainage from an abandoned coal mine in Southwest China. Environ Sci Pollut Res Int, 26(10): 9585-9598. Neamtiu I A, Al-Abed S R, Mckernan J L, et al. 2017. Metal contamination in environmental media in residential areas around Romanian mining sites. Reviews on Environment Health, 32(1-2): 215-220. Tu Z H, Chuling Guo C L, Zhang T, Lu G N, Wan J J, Liao C J, Dang Z. 2017. Investigation of intermediate sulfur species during pyrite oxidation in the presence and absence of Acidithiobacillus ferrooxidans. Hydrometallurgy, 167, 58–65. Schippers A, Jozsa P G, Sand W. 1996. Sulfur chemistry in bacterial leaching of pyrite. Applied and environmental Microbiology, 62(9): 3424-3431. Xu Y, Schoonen M A A. 1995. The stability of thiosulfate in the presence of pyrite in low-temperature aqueous solutions. Geochimica et Cosmochimica Acta, 59(22): 4605-4622. Huang W Y. 2011. Speciation of sulfur hot spring water. Chengdu University of Technology, Chengdu, Sichuan. Li X, Zhao X R, Zhou F Q, Chen Y Q, Huang T, Sun Q Y. 2021. Distribution characteristics of sulfur species and isotopes in sediments of rivers around Zhongshan tailing at Lujiang County, Anhui Province. Environmental Chemistry, 40(6): 1787-1794. Gao Z, Han C, Xu Y, et al. 2021. Assessment of the water quality of groundwater in Bohai Rim and the controlling factors—a case study of northern Shandong Peninsula, north China. Environment Pollution, 285: 117482. Bajjali W, Clark I D, Fritz P. 1997. The artesian thermal groundwaters of northern Jordan: Insights into their recharge history and age. Journal of Hydrology, 192(1-4): 355-382. Mao H, Wang C, Qu S, et al. 2023. Source and evolution of sulfate in the multi-layer groundwater system in an abandoned mine—Insight from stable isotopes and Bayesian isotope mixing model. Science of the Total Environment, 859: 160368. Majzlan J, Atevko M, Chovan M, et al. 2018. Mineralogy and geochemistry of the copper-dominated neutral mine drainage at the Cu deposit Ľubietová-Podlipa (Slovakia). Applied Geochemistry, 92: 59-70. Chen M, Lu G, Guo C, et al. 2015. Sulfate migration in a river affected by acid mine drainage from the Dabaoshan mining area, South China. Chemosphere, 119: 734-743. Sun J, Tang C, Wu P, et al. 2014. Hydrogen and oxygen isotopic composition of karst waters with and without acid mine drainage: Impacts at a SW China coalfield. Science of the Total Environment, 487: 123-129. Bao Y P, Guo C L, Lu G N, et al. 2018. Role of microbial activity in Fe(III) hydroxysulfate mineral transformations in an acid mine drainage-impacted site from the Dabaoshan Mine. Science of the Total Environment, 616: 647-657. Bao Y P, Guo C L, Wang H, et al. 2017. Fe and S metabolizing microbial communities dominate an AMD-Contaminated river ecosystem and play important roles in Fe and S cycling. Geomicrobiolgy Journal, 34(8): 695-705. Hua Z S, Han Y J, Chen L X, et al. 2015. Ecological roles of dominant and rare prokaryotes in acid mine drainage revealed by metagenomics and metatranscriptomics. The ISME Journal, 9(6): 1280-1294. Bartsch S, Gensch A, Stephan S, et al. 2017. Metallibacterium scheffleri: genomic data reveal a versatile metabolism. Fems Microbiolgy Ecology, 93(3). Yang Y, Zhu Z, Hu T, et al. 2021. Variation in energy metabolism structure of microbial community during bioleaching chalcopyrites with different iron-sulfur ratios. Journal of Central South University, 28(7): 2022-2036. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3967490","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":273860150,"identity":"e211cbd2-d9e2-4a77-92c3-f355b0eb5981","order_by":0,"name":"Man Gao","email":"","orcid":"","institution":"Chengdu University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Man","middleName":"","lastName":"Gao","suffix":""},{"id":273860152,"identity":"d30d3b50-f3e1-4abd-a74d-466af1484bae","order_by":1,"name":"Guo Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAv0lEQVRIiWNgGAWjYHACxgcSFTZybOztB4jWwmxgcSbNmI/nTALRWtgkKtsOJc6TcDAgTr182OkEiRtsB9LbJBgSGH5UbCOsxfB27gbDGTx3ctukGw8w9py5TYSW2bkbkiUknuW2yRxIYGZsI1LL4T8Gh9PZJBIMiNMiL527sUEi4XAC8VoMpHM3M0gcSDNsAwbyQaL8Ij87d/sPyX828vLt7Qcf/KggxpYDSJwDOBSh2dJAlLJRMApGwSgY0QAAU7g/p8IPe0wAAAAASUVORK5CYII=","orcid":"","institution":"Chengdu University of Technology","correspondingAuthor":true,"prefix":"","firstName":"Guo","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2024-02-18 16:44:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3967490/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3967490/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":51486606,"identity":"8b7b0efa-0b41-4ea0-9846-1228848d26ae","added_by":"auto","created_at":"2024-02-22 12:54:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":982455,"visible":true,"origin":"","legend":"\u003cp\u003eMap of the study area showing the distribution of sampling points\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-3967490/v1/c6eabcdeb43de115af7d4f1e.png"},{"id":51486607,"identity":"d67ac214-247b-4f6a-9a8a-1f46e99bfc59","added_by":"auto","created_at":"2024-02-22 12:54:25","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":268811,"visible":true,"origin":"","legend":"\u003cp\u003eA Piper diagram of the study area. Blue, green, and red points represents the background, FeS\u003csub\u003e2\u003c/sub\u003e water, and AMD pollution, respectively; squares, circles and triangles represent the dry, normal, and wet seasons, respectively.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-3967490/v1/1ccc26c3961f6b958f70e09c.png"},{"id":51487141,"identity":"78623705-74c6-4655-9ac5-99ce55ddee31","added_by":"auto","created_at":"2024-02-22 13:02:25","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":256857,"visible":true,"origin":"","legend":"\u003cp\u003eRelationships between different ions in water samples. (a) between total dissolved solids (TDS) and pH over different seasons; (b) between SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2−\u003c/sup\u003e and pH; (c) between TDS and SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2−\u003c/sup\u003e. Blue, green, and red points represent the background, FeS\u003csub\u003e2\u003c/sub\u003e water gushing, and AMD pollution, respectively.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-3967490/v1/fe0607dfa83c3f5781039a00.png"},{"id":51486605,"identity":"3bccbcec-47ac-4278-9038-b11e868f0487","added_by":"auto","created_at":"2024-02-22 12:54:25","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":329494,"visible":true,"origin":"","legend":"\u003cp\u003eRelationships between water chemical indicators in the water samples: (a) between Ca\u003csup\u003e2+\u003c/sup\u003e and HCO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e−\u003c/sup\u003e, with the 1:1 line representing the dissolution of gypsum; (b) between Ca\u003csup\u003e2+\u003c/sup\u003e and SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2−\u003c/sup\u003e, where the 1:1 represents the dissolution of gypsum; (c) SI-Gypsum and TDS.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-3967490/v1/cab22bb8407b2650f6efc697.png"},{"id":51487142,"identity":"906ea051-aacb-4d20-92dc-bd60a2b4c096","added_by":"auto","created_at":"2024-02-22 13:02:25","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":329310,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in water quality indices in the study area across the different sampling points. (a) pH; (b) DO; (c) oxidation-reduction potential; (d) temperature (T).\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-3967490/v1/7fdc6c4729990fe052a85cd4.png"},{"id":51486611,"identity":"5080fb7b-d9b2-4e63-90d2-76da0a9c5265","added_by":"auto","created_at":"2024-02-22 12:54:25","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":274125,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Characterization of SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2− \u003c/sup\u003ein the study area; (b) variations of SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2−\u003c/sup\u003e forms in the study area.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-3967490/v1/9ad81dbd10b50a21a7804b11.png"},{"id":51486617,"identity":"7c702aa2-6b7b-4240-8e1b-49286f962652","added_by":"auto","created_at":"2024-02-22 12:54:25","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":209468,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in metastable sulfur in the study area.\u003c/p\u003e\n\u003cp\u003e(a) SO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2−\u003c/sup\u003e; (b) S\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2−\u003c/sup\u003e; (c) S\u003csub\u003e4\u003c/sub\u003eO\u003csub\u003e6\u003c/sub\u003e\u003csup\u003e2−\u003c/sup\u003e; (d) S\u003csup\u003e2−\u003c/sup\u003e.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-3967490/v1/273bd2fca11859cb5e74630f.png"},{"id":51486616,"identity":"aa2be27f-62f2-4513-b2b8-b5b054658bb9","added_by":"auto","created_at":"2024-02-22 12:54:25","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":370301,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in iron speciation in the study area and relationships to influencing factors. (a) seasonal changes in iron speciation (K-dry season, P-normal season, F-wet season); (b) correlation between TFe and SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2− \u003c/sup\u003ein the study area; (c) Changes in Fe (II) speciation in the study area; (d) Variation in Fe (III) speciation in the study area.\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-3967490/v1/526885ef7b617195fd2684d8.png"},{"id":51486619,"identity":"453a8375-fcda-42d5-937a-21c2ad39b3f3","added_by":"auto","created_at":"2024-02-22 12:54:25","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":174343,"visible":true,"origin":"","legend":"\u003cp\u003eThe Eh-pH diagram of Fe and S forms\u003c/p\u003e","description":"","filename":"image9.png","url":"https://assets-eu.researchsquare.com/files/rs-3967490/v1/9647b21da48379152dc7754f.png"},{"id":51487143,"identity":"9415b4b8-0892-4027-86ff-85aef9734b7f","added_by":"auto","created_at":"2024-02-22 13:02:25","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":26855,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal Co-ordinates Analysis (PCoA) diagram of samples in the study area.\u003c/p\u003e","description":"","filename":"image10.png","url":"https://assets-eu.researchsquare.com/files/rs-3967490/v1/8206ebe2f7235ef83b911c54.png"},{"id":51486609,"identity":"e319dc33-5645-46cf-8ed0-500b5c3c259e","added_by":"auto","created_at":"2024-02-22 12:54:25","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":79208,"visible":true,"origin":"","legend":"\u003cp\u003eThe phylum-level distribution of microbial community structure in the study area\u003c/p\u003e","description":"","filename":"image11.png","url":"https://assets-eu.researchsquare.com/files/rs-3967490/v1/1a0c715628c7bee6a9c46a17.png"},{"id":51486613,"identity":"453168a3-c621-4eae-af1b-9e137810b997","added_by":"auto","created_at":"2024-02-22 12:54:25","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":110297,"visible":true,"origin":"","legend":"\u003cp\u003eThe genus-level distribution of microbial community structure in the study area.\u003c/p\u003e","description":"","filename":"image12.png","url":"https://assets-eu.researchsquare.com/files/rs-3967490/v1/3ba960bc3379949e4b739114.png"},{"id":51486614,"identity":"3d49599b-2711-48cd-8b58-7818bf5a8ca1","added_by":"auto","created_at":"2024-02-22 12:54:25","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":687194,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation heat map of iron and sulfur forms and environmental factors in acid mine drainage (AMD)\u003c/p\u003e\n\u003cp\u003eNote : * *: correlation significant at the 0.01 level (two tailed); *: correlation significant at the 0.05 level (two tailed).\u003c/p\u003e","description":"","filename":"image13.png","url":"https://assets-eu.researchsquare.com/files/rs-3967490/v1/ac924e6b79d9c8c6a96166b8.png"},{"id":51486618,"identity":"e1303a30-d304-4fda-8b29-c313371da49d","added_by":"auto","created_at":"2024-02-22 12:54:25","extension":"png","order_by":14,"title":"Figure 14","display":"","copyAsset":false,"role":"figure","size":473178,"visible":true,"origin":"","legend":"\u003cp\u003eHeat map of the correlations between abundance of main species, sulfur forms, and environmental factors at the genus level in the study area.\u003c/p\u003e\n\u003cp\u003eNote : * *: correlation significant at the 0.01 level (two tailed); *: correlation significant at the 0.05 level (two tailed).\u003c/p\u003e","description":"","filename":"image14.png","url":"https://assets-eu.researchsquare.com/files/rs-3967490/v1/c3c2b3ce39bea7b6b8d91620.png"},{"id":57832141,"identity":"ad1a4f18-0564-43c7-b28e-faae4d658656","added_by":"auto","created_at":"2024-06-06 08:10:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6517240,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3967490/v1/5bc50190-365a-4f1d-ae0f-f8c8e2807b06.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Spatiotemporal distribution of different forms of sulfur in acid mine drainage and their relationships with environmental factors","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAcid mine drainage (AMD) is an environmental pollutant that is typically produced in large volumes from diffuse sources and persists in the environment. AMD can lead to water body acidification and toxic metal pollution, thereby posing a risk to environmental and human health (Wang et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021b\u003c/span\u003e; Ding et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Consequently, AMD has received widespread attention globally. AMD is mainly produced through the oxidation of metal sulfide minerals, particularly pyrite (FeS\u003csub\u003e2\u003c/sub\u003e). The main pollutants of AMD include metal ions and SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e (Xin et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Johnson and Hallberg, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Most previous studies on AMD have focused on the environmental effects of the migration and transformation of toxic metals (Luo et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Ying et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In contrast, relatively few studies have examined the migration and transformation of sulfur forms in AMD.\u003c/p\u003e \u003cp\u003eAMD pollution of water resources is more difficult to rehabilitate than that of the atmosphere (Zak et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) due to the great impact on the natural sulfur cycle (Nordstrom et al., 2015). AMD pollution leads to high concentrations of SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e and other sulfides in lakes, rivers, and other surface waters, which pose risks to aquatic ecosystems (Jiao et al., 2023). Sulfate accumulation in the surrounding soil also leads to environmental challengers, such as soil hardening and acidification, which can in turn negatively affect vegetation growth and crops (Lear et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Yuan et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) as well as the health of the environment and humans (Ferreira et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Gao et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Neamtiu et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePyrite oxidation follows the thiosulfate and sulfur cycle pathways (Tu et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). S\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e produced by FeS\u003csub\u003e2\u003c/sub\u003e oxidation is unstable under acidic conditions, thereby leading to the conversion of SO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e to S\u003csup\u003e0\u003c/sup\u003e, which in turn is oxidized to SO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, S\u003csub\u003e4\u003c/sub\u003eO\u003csub\u003e6\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, and SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e (Schippers et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Xu and Schoonen., 1995). Tu et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) studied the intermediate sulfur species of pyrite oxidation in the presence and absence of microorganisms; Huang (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) analyzed the form of sulfur in hot spring water; Li et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) explored the distributions of sulfur forms in river water in a mining area. The sulfur transformation process is affected by environmental factors and the composition of AMD. Further study is needed on the relationships between different sulfur forms and environmental factors.\u003c/p\u003e \u003cp\u003eThe aim of the present study was to characterize the spatiotemporal distributions of different forms of sulfur in AMD and their relationships to environmental factors, focusing on a waste pyrite mining area in Luzhou City. The objectives of the present study were to characterize: (1) the spatiotemporal distributions of different sulfur forms in AMD; (2) the migration and transformation of sulfur forms and the relationships between them and environmental factors; (3) the main factors regulating AMD production. The results of the present study can contribute to management and rehabilitation of AMD in the environment.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study area\u003c/h2\u003e \u003cp\u003eThe study area of the present study is in Luobu Town, Xuyong County, Sichuan Province (105\u0026deg; 27\u0026prime; 04\u0026prime;\u0026prime;\u0026ndash;105\u0026deg; 29\u0026prime; 53\u0026prime;\u0026prime; E, 28\u0026deg; 03\u0026prime; 16\u0026prime;\u0026prime;\u0026ndash;28\u0026deg; 07\u0026prime; 16\u0026prime;\u0026prime; N). The study area falls into a subtropical humid monsoon climate zone with a temperature ranging from \u0026minus;\u0026thinsp;8.5 to 41.9\u0026deg;C. Rainfall is seasonal, with 70% of annual rainfall in summer and autumn. Surface water is mainly supplied by seasonal streams, gullies, and karst caves.\u003c/p\u003e \u003cp\u003eThe terrain of the study area decreases from south to north and is highly variable. Strata of the Triassic Feixianguan Formation (\u003cem\u003eT\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e\u003cem\u003ef\u003c/em\u003e) form a band on one side of the mountain; the Permian Longtan Formation (\u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e\u003cem\u003el\u003c/em\u003e) stratum is in an inclined trough valley; carbonate formations, such as the Permian Maokou and the Qixia formations (\u003cem\u003eP\u003c/em\u003e\u003csub\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sub\u003e\u003cem\u003em\u0026thinsp;+\u0026thinsp;q\u003c/em\u003e), manifest as karst landforms. The study area has well-developed karst landforms, including caves, funnels, hills, dissolution depressions, and troughs. The underground river pipeline system of the study area is also complex. Underground tunnel mining is the main form of pyrite mining in the study area. The mining process has disrupted the original strata and water flow channels and has led to exposure of nodular siderite and pyrite to the atmosphere. Groundwater in the aquifer tends to converge in abandoned mines, with this water reacting with pyrite and leading to leaching of iron and sulfur.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Sample collection and preservation\u003c/h2\u003e \u003cp\u003eThe present study collected 63 groundwater samples from 7 sampling points: D1 as a control point, D2, D3, and D5 as points of FeS\u003csub\u003e2\u003c/sub\u003e mine water inflow, D4 to represent coal mine water, and D6 and D7 as AMD inflow points. Samples were collected in the wet season, normal season, and dry season (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) pH, dissolved oxygen (DO), oxidation-reduction potential (ORP), and total dissolved solids (TDS) were measured on site using a portable water quality meter. Sample collection, transportation, storage, and analysis were strictly in accordance with Chinese groundwater quality standards (GB/T14848-2017). Samples were taken at a depth of 0.2 m. Water samples were filtered through a 0.22-um filter membrane, after which samples were decanted in bottles to overflowing to prevent air bubbles, and stored at a temperature of 4\u0026deg;C. Samples were transported back to the laboratory and tested within 48 h. Sample fixation on site was needed to stabilize unstable forms of sulfur. SO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, S\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, and S\u003csub\u003e4\u003c/sub\u003eO\u003csub\u003e6\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e were added to phosphate buffer and the pH of the solution was adjusted to 9.0 using sodium hydroxide. S\u003csup\u003e2\u0026minus;\u003c/sup\u003e was added to zinc acetate and sodium hydroxide was added to the solution to a pH that would facilitate precipitation. Microbial samples were collected by centrifuge tube after high temperature sterilization at 120\u0026deg;C and stored at 4\u0026deg;C. Microbial samples were transported back to the laboratory and stored at \u0026minus;\u0026thinsp;80\u0026deg;C. Sample microbial characterization was completed within 48 h.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Testing samples and analysis\u003c/h2\u003e \u003cp\u003eThe present study measured pH, DO, water temperature (T), and ORP of water samples. Sulfur forms of the water samples changed in response to changes in the physical and chemical properties of the water environment. Metal cations in the samples were determined by flame atomic spectrophotometry and ultraviolet spectrophotometry. Anions were determined by ion chromatography. The intermediate forms of sulfur was determined by high performance liquid chromatography (HPLC). S\u003csup\u003e2\u0026minus;\u003c/sup\u003e was determined by p-aminodimethylaniline spectrophotometry. Methods used to characterize the microbial community of the samples included sample DNA purification, polymerase chain reaction (PCR) amplification, sample quantification, library construction, and sequencing. Sequencing of samples was completed by Luoning Biological Company. The present study used analytically pure chemical reagents to maintain quality assurance and quality control (QA/QC). The standard deviation of the test results was less than 5% and the sample recovery rate was between 90\u0026ndash;110%.\u003c/p\u003e \u003cp\u003eMicrobial Alpha and Beta diversity were analyzed using R. Heat map analysis and the corr.test () function in the R psych package were used to conduct correlation analysis. PHREEQC software was used to analyze the SI-Gypsum saturation index and to simulate the distributions of Fe species and ion activity under different pH conditions. Grapher software was used to construct Piper three-line diagrams.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results and discussion","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Hydro-chemical characteristics\u003c/h2\u003e \u003cp\u003eThe Piper trilinear diagram allows a general reflection of the chemical characteristics and hydro-chemical types of sample water and is widely used in groundwater hydro-chemical analysis and evaluation (Gao et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The diamond component of the Piper diagram illustrates the hydro-chemical types of a groundwater sample for the dry, normal, and wet seasons (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The results showed that groundwater of the background point (D1) was of the HCO\u003csub\u003e3\u003c/sub\u003e-Ca-Mg type. The groundwater type of the remaining sites was SO\u003csub\u003e4\u003c/sub\u003e\u0026middot;Cl-Ca\u0026middot;Mg. All groundwater samples were concentrated in the Piper diagram F area, indicating a sulfate type and a bicarbonate background water type. The diagram suggested that the high concentration of SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e in AMD in the study area may be mainly derived from FeS\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e \u003cp\u003eIons in water reflect the weathering process affecting the chemistry of water and material transport of minerals in a basin. Therefore, water ions are a direct reflection of hydro-geochemical processes regulating water quality (Bajjali et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). The TDS content of the background point was between 293.6\u0026ndash;324.1 mg/L; that of the FeS\u003csub\u003e2\u003c/sub\u003e gushing points were 4,924.9\u0026ndash;11,476.6 mg/L. SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e and TDS in coal mine gushing water were much lower than those of FeS\u003csub\u003e2\u003c/sub\u003e acid gushing water at 730.9\u0026ndash;930.9 mg/L and 1,877.4\u0026ndash;2,038.4 mg/L, respectively. FeS\u003csub\u003e2\u003c/sub\u003e acid mine water generally showed high TDS and SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e and low pH. Therefore, TDS and SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e were negatively correlated with pH across all the seasons (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). TDS in the dry season exceeded that in the normal season and the wet season. TDS and SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e were highly correlated over all the seasons, indicating that SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003ewas the main salt contributing to TDS in the study (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec).\u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, samples of gushing mine water and AMD were mainly distributed above the 1:1 line, indicating various sources of Ca\u003csup\u003e2+\u003c/sup\u003e in the samples. Samples of the background point were distributed on the 1:1 line (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb), indicating that these samples were mainly impacted by gypsum dissolution (Mao et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The results indicated that oxidation of the coal mine was the source of SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e in coal mine water point D4, whereas oxidation of FeS\u003csub\u003e2\u003c/sub\u003e was the main contributor to the hydrochemistry of the remaining points. The SI values of all points were less than 0.5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec), whereas that of the background point was less than \u0026minus;\u0026thinsp;0.5. This result could be attributed to the good quality of the water sample due to high elevation of the background point. The SI values of the remaining points ranged from \u0026minus;\u0026thinsp;0.5 to 0.5, with all falling into a water-rock equilibrium state without excess SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e precipitation. The results of the correlation between Ca\u003csup\u003e2+\u003c/sup\u003e and SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e and the characterization of the geological background indicated that the gypsum dissolution dominated water chemistry and the background point, whereas oxidation leaching of FeS\u003csub\u003e2\u003c/sub\u003es contributed to the high content of SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e of the remaining points.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Spatiotemporal distributions of physicochemical factors\u003c/h2\u003e \u003cp\u003eAMD pollution resulted in a difference in the pH of groundwater (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea). The pH of the background point ranged between 7.28 and 7.4, indicating overall neutral to weakly alkaline water; the pH of FeS\u003csub\u003e2\u003c/sub\u003e water inflow points ranged between 2.09 and 3.10, indicating highly acidic water; that of coal mine water inflow (D4) was between 6.84 and 7.00. The high concentration of HCO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e (\u0026gt;\u0026thinsp;470 mg/L) effectively neutralized acidity of samples resulting from AMD. The buffering effect was achieved by HCO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e counteracting SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, resulting in persistence of neutral conditions (Majzlan et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Outflow of acidic water resulted in erosion of D6 and D7 to their hydraulically related periphery and a pH of 3.15\u0026ndash;3.5 and 3.55\u0026ndash;4.17, respectively. There was clear seasonal variation in pH, with the lowest and highest pH in the dry season and wet season, respectively. Strong buffering was provided by the high concentration of Fe\u003csup\u003e3+\u003c/sup\u003e in the water body, where hydro-lyzation resulted in the release of a large quantity of H\u003csup\u003e+\u003c/sup\u003e. This effectively offset the surface runoff dilution effects in the wet season, resulting in consistently lower pH of the water body all the year round.\u003c/p\u003e \u003cp\u003eDO in water samples was closely related to the distributions of sulfur and iron forms at different sites (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). There was minor variation in DO at the background point; those at D2 and D3 were relatively low due to the large quantity of oxygen consumed during the oxidation of FeS\u003csub\u003e2\u003c/sub\u003e to produce AMD; DO was higher at D4 and D5 due to effective aeration and oxygenation. Migration of AMD resulted in its continuous contact with the atmosphere and the subsequent increases in DO at D6 and D7 from 4.37 to 5.16 mg/L and from 4.42 to 5.39 mg/L, respectively. DO in the dry season exceeded that in the wet season.\u003c/p\u003e \u003cp\u003eThe water temperature in the wet season exceeded those of the normal and dry seasons. Water temperature differed among the different sampling points (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed) due to the minimal effect of outside meteorological conditions on Groundwater. The integration of ORP with other water quality indicators can reflect the ecological environment. ORP was different among the different sampling points with no clear seasonal variation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec). The ORP values at D2, D3, and D5 were between 441.3 and 549.6 mV, with that at D5 the highest. This site was also shown to be highly oxidizing. Gushing out of mine water contributed to a downward trend in ORP along the direction of groundwater flow. D4 remained in a flooded state due to long-term blocking off of the mine, in which ORP ranging from \u0026minus;\u0026thinsp;120.9 to \u0026minus;\u0026thinsp;99.3 mV, indicating the high reducibility of the environment at this point.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Spatiotemporal distributions of sulfur species\u003c/h2\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e3.3.1 Spatiotemporal distribution of SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e\u003c/h2\u003e \u003cp\u003eThe background point showed a low concentration of SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e of 33.94 to 55.15 mg/L. The mine FeS\u003csub\u003e2\u003c/sub\u003e drainage point had a relatively high FeS\u003csub\u003e2\u003c/sub\u003e concentration, reaching 10,873.93 mg/L in the dry season. Coal mine water had a SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e exceeding 800 mg L all the year round. There was an attenuation in SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e along the direction of groundwater flow. The migration of SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e showed non-conservative behavior closely related to the formation and adsorption of secondary high-iron minerals. In addition, suspended solids and sediment surfaces in AMD were positively charged, thereby facilitating further adsorption of SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e (Chen et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The dry-season SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e concentration exceeded that in the normal and wet seasons. The results of T-test analysis showed that the decreases in dry and wet season SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e concentrations were closely related to seasonal precipitation and groundwater flow. These processes resulted in the formation of various complexes with SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e in aqueous solution to form Fe-SO\u003csub\u003e4\u003c/sub\u003e. The simulattioned by the PHREEQC software (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb) showed that the rank of different sulfate forms in the study area according to concentration was SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e \u0026gt; FeSO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e0\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;HSO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e \u0026gt; FeHSO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e \u0026gt; FeSO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e \u0026gt; Fe(SO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e \u0026gt; FeHSO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2+\u003c/sup\u003e. The proportion of SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e gradually increased with increasing pH. SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e in the study area mainly existed in the form of SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e3.3.2 Spatiotemporal distribution of metastable sulfur\u003c/h2\u003e \u003cp\u003eThe main sulfur form in AMD was +\u0026thinsp;6 valence SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, whereas the accumulations of metastable sulfur forms (SO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, S\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, S\u003csub\u003e4\u003c/sub\u003eO\u003csub\u003e6\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, and S\u003csup\u003e2\u0026minus;\u003c/sup\u003e) were minor (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). SO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, S\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, and S\u003csub\u003e4\u003c/sub\u003eO\u003csub\u003e6\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e of the water gushing point (D2, D3, D5) were incompletely oxidized to SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, with a small quantity of accumulation. The rank of the different sampling points in terms of quantities of sulfur forms was D3\u0026thinsp;\u0026gt;\u0026thinsp;D5\u0026thinsp;\u0026gt;\u0026thinsp;D4\u0026thinsp;\u0026gt;\u0026thinsp;D2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ea, \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eb, \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ec). S\u003csup\u003e2\u0026minus;\u003c/sup\u003e can accumulate in trace quantities during the redox of sulfur. D4 showed the highest accumulation of S\u003csup\u003e2\u0026minus;\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003ed). This result can be attributed to the redox potential of the water environment. Environments with strong reducibility tend to show a greater accumulation of S\u003csup\u003e2\u0026minus;\u003c/sup\u003e (Sun et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Migration of AMD results in rapid oxidation of the metastable sulfur. Some metastable sulfur forms showed clear seasonal variation. Wet season SO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e exceeded those in the normal and dry seasons. S\u003csup\u003e2\u0026minus;\u003c/sup\u003e was also highest in the dry season. The main form of metastable sulfur in AMD was SO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, followed by S\u003csub\u003e4\u003c/sub\u003eO\u003csub\u003e6\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e and S\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, whereas the content of S\u003csup\u003e2\u0026minus;\u003c/sup\u003ewas very low. These results can be attributed to the conversion of S\u003csub\u003e4\u003c/sub\u003eO\u003csub\u003e6\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e and S\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e to +\u0026thinsp;4 valence SO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e before conversion to SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e. Consequently, the accumulation of SO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e exceeded those of other forms of metastable sulfur. Since S\u003csup\u003e2\u0026minus;\u003c/sup\u003e is typically present in a reducing environment, the strong oxidizing environment of AMD restricts the accumulation of S\u003csup\u003e2\u0026minus;\u003c/sup\u003e to a low level.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Distributions of iron forms\u003c/h2\u003e \u003cp\u003eFe valence states of AMD were +\u0026thinsp;2 and +\u0026thinsp;3 and there were low contents of Fe\u003csup\u003e3+\u003c/sup\u003e and Fe\u003csup\u003e2+\u003c/sup\u003e at the background point D1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ea). The average total iron concentrations of D2, D3, and D5 were 1,780.35 mg/L, 977.98 mg/L, and 902.51 mg/L, respectively. Fe of coal mine water (D4) was low (3.22 mg/L) and mainly in the form of Fe\u003csup\u003e3+\u003c/sup\u003e. The evolution of Fe was regulated by changing redox conditions during water flow. There was a significant positive correlation between total iron (TFe) and SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e (Fig.\u0026nbsp;8b; R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.9308), which could be attributed to input from tributaries and the generation of many secondary iron minerals (Bao et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Seasonal variation in of TFe was consistent with that of SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, with stepwise downward trends across all three seasons, indicating that Fe was also affected by precipitation and groundwater flow.\u003c/p\u003e \u003cp\u003eFe in AMD can form various complexes with SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, and pH significantly changes the morphology and activity of each Fe-S complex. PHREEQC simulation of the distribution of Fe (II) speciation (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ec) showed that large quantities of Fe\u003csup\u003e2+\u003c/sup\u003e and SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e formed an FeSO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e0\u003c/sup\u003e complex in acidic water (pH\u0026thinsp;\u0026lt;\u0026thinsp;2.5) due to the high concentration of SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, with the content of this complex slightly exceeding that of free Fe\u003csup\u003e2+\u003c/sup\u003e. The concentration of SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e gradually decreased with increasing pH, and the proportion of free Fe\u003csup\u003e2+\u003c/sup\u003e in the water gradually increased. Under an acidic environment (2.5\u0026thinsp;\u0026lt;\u0026thinsp;pH\u0026thinsp;\u0026lt;\u0026thinsp;5.1), the rank of Fe (II) forms according to concentration was: Fe\u003csup\u003e2+\u003c/sup\u003e \u0026gt; FeSO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e0\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;FeHSO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e \u0026gt; FeOH\u003csup\u003e+\u003c/sup\u003e \u0026gt;\u0026gt; Fe(OH)\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e0\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;\u0026gt;\u0026thinsp;Fe(OH)\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e. At a pH\u0026thinsp;\u0026gt;\u0026thinsp;5.1, the ionic activity of FeOH\u003csup\u003e+\u003c/sup\u003e exceeded that of FeHSO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e. Complexation of Fe (III) exceeded that of Fe (II), with the former forming various complexes (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003ed). Fe (III) in an acidic environment (pH\u0026thinsp;\u0026lt;\u0026thinsp;3.9) mainly existed in the FeSO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e, Fe(SO\u003csub\u003e4\u003c/sub\u003e)\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e, and FeHSO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2+\u003c/sup\u003e forms. Under an acidic environment (3.9\u0026thinsp;\u0026lt;\u0026thinsp;pH\u0026thinsp;\u0026lt;\u0026thinsp;4.9), Fe(OH)\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e and Fe(OH)\u003csup\u003e2+\u003c/sup\u003e in addition to FeSO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e were the main complex states. With increasing pH above 4.9, there was a rapid increase in the ion activity of Fe(OH)\u003csub\u003e3\u003c/sub\u003e, becoming the most important complex state in neutral water, whereas the contents of other Fe (III) forms gradually decreased.\u003c/p\u003e \u003cp\u003eThe redox potential and pH of AMD are comprehensive reflections of changes in Fe and S in the water environment. Figure\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e shows the boundary conditions in Fe and S morphological stability (Sun et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Redox conditions regulate changes in S and Fe species. Iron mainly exists in the form of Fe\u003csup\u003e2+\u003c/sup\u003e at a pH\u0026thinsp;\u0026lt;\u0026thinsp;3. Fe\u003csup\u003e3+\u003c/sup\u003e dominated the iron forms in AMD pollution sites due to the influences of pH, redox potential, and DO. Fe(OH)\u003csub\u003e3\u003c/sub\u003e was the dominant Fe form at the background point. The distribution of sulfur forms indicated a negative oxidation-reduction potential of D4 coal mine water, with the sample distributed on the boundary between H\u003csub\u003e2\u003c/sub\u003eS(aq) and SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e. This point accumulated S\u003csup\u003e2\u0026minus;\u003c/sup\u003e, whereas oxidation affected the remaining points, leading to the dominance of positive hexavalent SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Spatial characteristics of microbial community structure\u003c/h2\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e3.5.1 Microbial community diversity\u003c/h2\u003e \u003cp\u003eThe α-diversity index of samples reflects the abundance, uniformity, and diversity of microbial communities. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the operational taxonomic units (OTUs) and Chao 1, Shannon, and Simpson indices of each sample. The present study achieved a\u0026thinsp;\u0026gt;\u0026thinsp;98% coverage of all 7 samples, indicating that the present study comprehensively characterized the microbial community of environmental samples. Abundance of the microbial community is reflected by the OTUs and Chao 1 index. The background point (D1) and point D2 showed the highest and lowest numbers of OTUs at 509 and 125, respectively. The neutral D1 and D4 samples showed the highest Chao 1 index values of 510.5000 and 472.4839, respectively, whereas D2 under the lowest pH had the lowest Chao 1 index of 158.4615. The Chao 1 index values of the remaining samples were low, at an average of 348.1074. The Simpson and Shannon index values of the samples reflected the diversity of the microbial community and were highest for neutral samples at D1 and D4 at 5.15 and 0.98, respectively; those of samples affected by lower pH (D2, D3, D5, D6, D7) were at an average of 2.47 and 0.60, respectively. These results indicated that microbial community abundance and diversity decreased with decreasing pH. The present study conducted Principal Co-ordinates Analysis (PCoA) to further analyze differences between samples and the possible driving factors (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e). Principal coordinates 1 and 2 (PCo1 and PCo2) explained the most observed variation in the seven samples of 47% and 25%, respectively. In the PCoA plot, D2 (pH\u0026thinsp;\u0026lt;\u0026thinsp;2.2) was in the second quadrant; the remaining mine water gushing points and AMD pollution points (2.2\u0026thinsp;\u0026lt;\u0026thinsp;pH\u0026thinsp;\u0026lt;\u0026thinsp;4) were gathered at the junction of the first and fourth quadrants; points D1 and D4 (neutral pH) were gathered in the third quadrant. These results showed significant differences in microbial community among samples under different pH conditions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe α diversity index of the microbial community in the study area\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOTUs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChao 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eShannon\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSimpson\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCoverage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e510.5000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.016988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.972192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.998961\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e158.4615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.857449\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.569117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.995548\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e343.9091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.313590\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.584752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.989611\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e472.4839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.284899\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.988506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.996141\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e363.7143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.010801\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.491940\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.987830\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e332.1220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.608647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.652277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.990798\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e352.6842\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.538871\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.697020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.986049\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e3.5.2 Microbial community composition\u003c/h2\u003e \u003cp\u003e(1) Phylum-level analysis of microbial community composition\u003c/p\u003e \u003cp\u003eThere were significant phylum-level differences in microbial community structure of samples under different levels of AMD pollution (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e). \u003cem\u003eProteobacteria\u003c/em\u003e has been shown to dominate environments affected by AMD (Bao et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The results of the present study observed a similar trend, with this phylum dominant in the seven samples in the study area, and particularly in samples under an acidic environment (D2, D3, D5, D6, D7), reaching a proportion of 83%. The average proportion of \u003cem\u003eProteobacteria\u003c/em\u003e in neutral water samples (D1, D4) was 36.01%. \u003cem\u003eFirmicutes\u003c/em\u003e, \u003cem\u003eBacteroidetes\u003c/em\u003e, and \u003cem\u003eActinobacteria\u003c/em\u003e were also widely distributed in the study area, particularly in coal mine water gushing water (D4), reaching 23.57%, 17.88%, and 8.92%, respectively. \u003cem\u003eAcidobacteria\u003c/em\u003e was relatively abundant in D1. The highest abundance of \u003cem\u003eEuryarchaeota\u003c/em\u003e was in D2 (8.67%) characterized by the highest concentrations of SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e and TFe and lowest pH, indicating that this phylum is found in areas of serious AMD pollution. AMD pollution and mineral composition appeared to significantly change the composition of microbial species.\u003c/p\u003e \u003cp\u003e(2) Genus-level analysis of microbial community composition\u003c/p\u003e \u003cp\u003eDominant bacteria at the genus level at point D1 included \u003cem\u003eAcidibacter\u003c/em\u003e, \u003cem\u003eSphingomonas\u003c/em\u003e, \u003cem\u003eMND1\u003c/em\u003e, and \u003cem\u003eRB41\u003c/em\u003e; at D4 they included \u003cem\u003eLachnospiraceae NK4A136 group, Ralstonia, Enterobacter, Pelomonas\u003c/em\u003e, and \u003cem\u003eSinomonas\u003c/em\u003e. Buffering by bicarbonate resulted in a close to neutral pH at D4 and this site had low metal ions concentrations. Consequently, microbial diversity at D4 was relatively high, whereas the proportion of sulfur-oxidizing microorganisms was relatively small. The relative abundance of \u003cem\u003eFerrovum\u003c/em\u003e among sampling points exceeded 60%, except at D2 in which it was 9.36%. \u003cem\u003eFerrovum\u003c/em\u003e is an iron-oxidizing bacterium that can fix carbon through the Calvin-Benson-Bassham cycle and is widely distributed in iron-containing acidic water (Hua et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). \u003cem\u003eAcidithiobacillus\u003c/em\u003e was the dominant genus in D2 at 27.75%. \u003cem\u003eAcidithiobacillus\u003c/em\u003e has been shown to tolerate acidic (pH\u0026thinsp;\u0026lt;\u0026thinsp;2.5) and warm (30\u0026deg;C) water. The results showed that the distribution of microbial community structure was closely related to water pH and temperature. At the same time, the concentrations of SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003eand Fe in D2 exceeded those at other sites. This result indicated that \u003cem\u003eAcidithiobacillus\u003c/em\u003e may have stronger acid production capacity. \u003cem\u003eAcidithiobacillus ferrooxidans\u003c/em\u003e (\u003cem\u003eAt.f\u003c/em\u003e) was the only member of Acidithiobacillus at D2. This species can oxidize Fe\u003csup\u003e2+\u003c/sup\u003e to Fe\u003csup\u003e3+\u003c/sup\u003e. The genus \u003cem\u003eMetallibacterium\u003c/em\u003e was the third-most abundant in the study area and dominated D2 (21.21%). Microbes of genus \u003cem\u003eMetallibacterium\u003c/em\u003e are tolerant to a wide range of pH environments, and similar to \u003cem\u003eAcidithiobacillus\u003c/em\u003e, can obtain energy through oxidation-reduction of ferrous and sulfur compounds (Bartsch et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In addition, D2 showed relatively high proportions of \u003cem\u003eAcidibacter\u003c/em\u003e and \u003cem\u003eFerrithrix\u003c/em\u003e. Both genera represent thermophilic bacteria which have a tolerance for high temperatures (\u0026plusmn;\u0026thinsp;30\u0026deg;C).\u003c/p\u003e \u003cp\u003eThese results suggest that AMD pollution significantly changes the diversity and community structure of microorganisms in the water environment, with serious AMD pollution significantly reducing microbial diversity and resulting in the dominance of acidophilic and sulfur/iron oxidizing bacteria. Acidophilic and sulfur/iron oxidizing bacteria further lead to water acidification. Oxidation facilitated by \u003cem\u003eAt.f\u003c/em\u003e and \u003cem\u003eMetallibacterium\u003c/em\u003e results in the rapid acceleration of the cyclic conversion rate of sulfur in AMD, with metastable sulfur rapidly converted to SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e. Abundance of \u003cem\u003eAcidithiobacillus\u003c/em\u003e and \u003cem\u003eMetallibacterium\u003c/em\u003e in D2 far exceeded that in D3, D4, and D5.Therefore, metastable sulfur in mine water (D2) was lower than that in other mine water samples.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Analysis of relationships between sulfur and Fe forms\u003c/h2\u003e \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e3.6.1 Physical and chemical factors regulating sulfur and Fe forms\u003c/h2\u003e \u003cp\u003eThe present study examined the correlations between sulfur and iron forms and the regulating impacts of environmental factors. The proportions of different sulfur and iron forms were used to determine correlations. Data for environmental factors were assumed to follow normal distributions. Pearson correlation analysis was used to calculate correlation coefficients (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e13\u003c/span\u003e). The results showed that pH was negatively and positively correlated with total sulfur (TS) and S\u003csup\u003e2\u0026minus;\u003c/sup\u003e, respectively; water temperature and ORP were positively correlated with TS and TFe. SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e accounted for \u0026gt;\u0026thinsp;99% of TS at each point, indicating that SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e content in AMD was proportional to acidity. Increases in water temperature and ORP promoted the conversion of sulfur, thereby generating SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e. The results showed that DO significantly affected the valence states of iron and sulfur. DO showed negative correlations with Fe\u003csup\u003e2+\u003c/sup\u003e and metastable sulfur, indicating that DO promoted the conversion of Fe\u003csup\u003e2+\u003c/sup\u003e and metastable sulfur to Fe\u003csup\u003e3+\u003c/sup\u003e and SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e3.6.2 Microbial species abundance\u003c/h2\u003e \u003cp\u003eThe present study examined correlations between microbial species abundance and environmental factors. Spearman analysis was used to identify the 10 most abundant species at the genus level for analyzing correlations with sulfur forms (Fig.\u0026nbsp;\u003cspan refid=\"Fig14\" class=\"InternalRef\"\u003e14\u003c/span\u003e). The abundance of \u003cem\u003eAt.f\u003c/em\u003e showed significant positive correlations with SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e and TFe and a significant negative correlation with pH. \u003cem\u003eAt.f\u003c/em\u003e also showed positive correlations with metastable sulfur forms S\u003csup\u003e2\u0026minus;\u003c/sup\u003e, SO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, S\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, and S\u003csub\u003e4\u003c/sub\u003eO\u003csub\u003e6\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e. This result indicated that \u003cem\u003eAt.f\u003c/em\u003e promotes the transformation of iron and sulfur. \u003cem\u003eAt.f\u003c/em\u003e dominated the microbial community at D2 and SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e and iron at this sampling point far exceeded those at other sites. \u003cem\u003eFerrovum\u003c/em\u003e is an iron-oxidizing bacterium and dominated the microbial community at the remaining acidic water sites. \u003cem\u003eFerrovum\u003c/em\u003e mainly oxidizes Fe\u003csup\u003e2+\u003c/sup\u003e rather than sulfur. Therefore, the dominance of \u003cem\u003eFerrovum\u003c/em\u003e was dependent on the presence of sufficient Fe\u003csup\u003e3+\u003c/sup\u003e and O\u003csub\u003e2\u003c/sub\u003e to oxidize FeS\u003csub\u003e2\u003c/sub\u003e. The ability of \u003cem\u003eFerrovum\u003c/em\u003e to produce acid is weaker than that of \u003cem\u003eAcidithiobacillus\u003c/em\u003e. \u003cem\u003eMetallibacterium\u003c/em\u003e also showed significant positive correlations with SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e and TFe and a significant negative correlation with pH. \u003cem\u003eRalstonia\u003c/em\u003e showed significant positive correlations with metastable sulfur forms S\u003csup\u003e2\u0026minus;\u003c/sup\u003e, SO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, S\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, and S\u003csub\u003e4\u003c/sub\u003eO\u003csub\u003e6\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, indicating that \u003cem\u003eRalstonia\u003c/em\u003e has a certain reducing capacity.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. Conclusions","content":"\u003cp\u003eThe present study aimed to characterize the spatiotemporal distributions of different forms of sulfur in AMD and their relationships to environmental factors, focusing on a waste pyrite mining area in Luzhou City. The main conclusions of the present study are summarized below:\u003c/p\u003e \u003cp\u003e(1) Along the AMD runoff direction, the hydro-chemical type changed from HCO\u003csub\u003e3\u003c/sub\u003e-Na type to SO\u003csub\u003e4\u003c/sub\u003e\u0026middot;Cl-Ca\u0026middot;Mg type. The point \u0026minus;\u0026thinsp;0.5\u0026thinsp;\u0026lt;\u0026thinsp;SI\u0026thinsp;\u0026lt;\u0026thinsp;0.5 is in the water-rock equilibrium state, and presents the characteristics of high TDS, high SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003eand low pH. SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003eis mainly derived from gypsum dissolution, coal mine oxidation and FeS\u003csub\u003e2\u003c/sub\u003e oxidation. The physical and chemical factors showed obvious spatial and temporal changes. In the dry season, the pH and temperature of the water body were lower, and the DO and ORP were higher.\u003c/p\u003e \u003cp\u003e(2) The sulfur form in AMD in the study area is mainly SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, and the metastable sulfur SO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e、S\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e、S\u003csub\u003e4\u003c/sub\u003eO\u003csub\u003e6\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e and S\u003csup\u003e2\u0026minus;\u003c/sup\u003e have only a small amount of accumulation in the cyclic transformation of sulfur. With the migration of AMD, they are gradually oxidized to SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e. The concentrations of SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003eand S\u003csup\u003e2\u0026minus;\u003c/sup\u003ein the dry season were higher than those in the normal season and the wet season, and the contents of SO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, S\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003eand S\u003csub\u003e4\u003c/sub\u003eO\u003csub\u003e6\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003ewere the highest in the wet season, indicating that the distribution of sulfur forms was affected by seasonal changes and was closely related to precipitation and groundwater flow.\u003c/p\u003e \u003cp\u003e(3) In AMD, Fe (II) is mainly in the form of free Fe\u003csup\u003e2+\u003c/sup\u003e and complex FeSO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e0\u003c/sup\u003e. Fe (III) mainly exists in the form of complex state, and the activity of each complex state changes with the change of pH and the attenuation of SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e. Fe\u003csup\u003e2+\u003c/sup\u003e and Fe\u003csup\u003e3+\u003c/sup\u003e coexisted in the original environment, and were oxidized to Fe\u003csup\u003e3+\u003c/sup\u003e with the increase of DO and pH. The correlation coefficient between TFe and SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e decay is as high as 0.9308, which is closely related to the formation of sulfate secondary iron-bearing minerals.\u003c/p\u003e \u003cp\u003e(4) AMD decreased the abundance and diversity of microbial communities and resulted in the dominance of acidophilus and sulfur/iron-oxidizing bacteria, including \u003cem\u003eAcidithiobacillus\u003c/em\u003e and \u003cem\u003eMetallibacterium\u003c/em\u003e. Dominant genera at sites not impacted by AMD included \u003cem\u003eAcidibacter\u003c/em\u003e and \u003cem\u003eSphingomonas\u003c/em\u003e; those at sites impacted by AMD but with neutral pH included \u003cem\u003eLachnospiraceae NK4A136 group, Ralstonia\u003c/em\u003e, and \u003cem\u003eSinomonas\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e(5) Environmental factors regulated the distribution of sulfur forms. There was a negative correlation between pH and SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, whereas SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e was positively correlated with DO, temperature, ORP, total iron, and \u003cem\u003eAcidithiobacillus\u003c/em\u003e. SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e promoted acidity. Increases in water temperature and ORP facilitated the conversion of sulfur. \u003cem\u003eAt.f\u003c/em\u003e promoted the conversion of iron and sulfur, indicating that environmental factors regulate the conversion of sulfur.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eMan Gao wrote the main manuscript text ,Guo Liu analysis. All authors reviewed the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWang Z, Xu Y, Zhang Z, et al. 2021b. Review: Acid mine drainage (AMD) in abandoned coal mines of Shanxi, China. Water, 13(1): 8.\u003c/li\u003e\n\u003cli\u003eDing C, Li Q, Guo C L, et al. 2019. Effect of acid mine drainage on microbial community structure in paddy soil. Acta Scientiae Circumstantiac, 39(09): 3080-3089.\u003c/li\u003e\n\u003cli\u003eXin R, Banda J F, Hao C, et al. 2021. 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Journal of Central South University, 28(7): 2022-2036.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Acid mine drainage, FeS2, Migration and Transformation of Surfur, Environmental Factors","lastPublishedDoi":"10.21203/rs.3.rs-3967490/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3967490/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe production of acid mine drainage (AMD) involves oxidation of FeS\u003csub\u003e2\u003c/sub\u003e to SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, during which a variety of intermediate sulfur forms (S\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, S\u003csup\u003e0\u003c/sup\u003e, SnO\u003csub\u003e6\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e, SO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e) are generated. This study aimed to characterize the spatiotemporal distributions of different forms of these intermediates and their relationships to environmental factors, focusing on an abandoned pyrite mine area. Samples were collected from different water stages and the physicochemical factors were determined on site. High performance liquid chromatography, ion chromatography, and Illumina high-throughput sequencing were used to determine the distributions of iron and sulfur forms and the microbial community structure at each site. Pearson and Spearman correlation were used to analyze the relationships between the distributions of different forms of sulfur and environmental factors during the formation and migration of AMD. The results suggested that SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e mainly originated from gypsum dissolution and oxidation of the coal mine and FeS\u003csub\u003e2\u003c/sub\u003e. The dry season was associated with lower water pH and temperature and higher DO and ORP. The maximum correlation coefficient between TFe and SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e decay was 0.9308, which could be attributed to the formation of sulfate secondary iron-containing minerals. SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e pollution decreased with increasing migration distance of AMD and showed seasonal variation closely related to precipitation and groundwater flow. The abundance and diversity of microbial community decreased with the production of AMD, mainly acidophilus and sulfur/iron-oxidizing bacteria. \u003cem\u003eFerrovum\u003c/em\u003e occupied an absolute dominant position in weakly acidic samples, and \u003cem\u003eAcidibacter\u003c/em\u003e and \u003cem\u003eSphingomonas\u003c/em\u003e were not polluted. Neutral samples include \u003cem\u003eLachnospiraceae NK4A136 group\u003c/em\u003e, \u003cem\u003eRalstonia\u003c/em\u003e, \u003cem\u003eSinomonas\u003c/em\u003e, etc. pH and SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e showed negative correlations with DO, temperature, and ORP, whereas the dominant strain \u003cem\u003eAcidithiobacillus\u003c/em\u003e was positively correlated with SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e. Increases in water temperature and ORP promoted the transformation of sulfur. The regulation of sulfur conversion to acid is key for developing strategies for preventing and reversing AMD pollution.\u003c/p\u003e","manuscriptTitle":"Spatiotemporal distribution of different forms of sulfur in acid mine drainage and their relationships with environmental factors","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-22 12:54:20","doi":"10.21203/rs.3.rs-3967490/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7ac1441c-1ceb-40f5-b07b-0e636a64f0f1","owner":[],"postedDate":"February 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-06T08:02:36+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-22 12:54:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3967490","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3967490","identity":"rs-3967490","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}