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矿山开发过程中会产生大量的固体废弃矿物,在自然环境中风化和微生物的氧化过程中伴随着有毒有害元素的释放,并逐渐形成了高硫酸根、高铁浓度的极端酸性矿山废水 (acid mine drainage,AMD) ,造成了矿区附近流域水体及土壤重金属的污染,严重威胁矿区生态系统安全及人群健康[1-4]。因此,AMD所引起的环境污染已成为国内外研究热点。
以广东省韶关市大宝山金属硫化物矿区为例,ZHUANG等[5]发现,受矿区酸性废水的长期影响,大宝山矿区附近土壤的pH多低于5,土壤中铜、铅、锌和镉的平均质量分数分别为502 mg·kg−1、278 mg·kg−1、498 mg·kg−1和3.92 mg·kg−1,远超过国家标准 (GB15618-2018) 限值。而AMD表层沉积物中的重 (类) 金属,如Pb、As和Cr的质量分数高达3 100、1 896和170 mg·kg−1[6-7]。据沉积物矿物学特征调查可知,AMD污染的流域中易形成大量特征性的含铁羟基硫酸盐次生矿物[8-10]。例如,当pH为2.8~4.5时,AMD环境中的三价铁和硫酸根离子共沉淀形成典型的施氏矿物 (schwertmannite) ;当体系中存在一价阳离子且pH为1.5~3时,易形成以黄铁矾类为主的矿物;当pH>5时,Fe3+水解产生的矿物主要为水铁矿[11-12]。由于类质同象作用,这些含铁羟基硫酸盐次生矿物容易吸持AMD中的重 (类) 金属离子,使其演变成为重 (类) 金属离子的沉淀库。同时,含铁硫酸盐次生矿物容易在环境因子 (pH、还原性物质、溶解性有机质 (dissolved organic matter,DOM) 和共存离子浓度等) 改变时,发生溶解重结晶,使其吸附和共沉淀的重 (类) 金属再次释放到相应的水体流域中,造成二次生态风险[13-16]。然而,目前关于大宝山矿区环境中重金属环境风险的研究主要针对矿区土壤中重金属的迁移。
在AMD环境中,可溶性S(-II)可由硫酸盐还原菌还原硫酸根产生,并通过还原、沉淀和络合等途径对矿区中重 (类) 金属的迁移转化起制约作用[17]。例如,在厌氧环境下,S(-II)可还原溶解铁 (氢) 氧化物等矿物且自身形态发生改变,亦引起了所吸持的重 (类) 金属再次释放[18-20]。然而,关于可溶性S(-II)与矿区沉积物中次生矿物的稳定性及重 (类) 金属的迁移转化动态关系的报道还甚少。
基于此,本研究围绕大宝山矿区拦泥库沉积物,采用流动柱进行模拟淋溶实验,模拟还原大宝山矿区拦泥库沉积物中的重 (类) 金属在还原性S(-II)介导下的垂直迁移特征,以探究S(-II)对拦泥库沉积物次生矿物的稳定性影响与重金属环境行为的关系,以期为金属硫化物矿区的环境修复与污染防治提供参考。
可溶性硫化物介导对矿区拦泥库沉积物中重金属垂直迁移特征的影响
Effects of soluble sulfide on the vertical migration of heavy metals in the sediment of mine retaining reservoir
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摘要: 在金属硫化物矿区中,Fe/S循环过程制约着重 (类) 金属的迁移转化。采用流动柱进行模拟自然淋溶实验,结合释放动力学及XRD、SEM表征探究了可溶性硫化物 (S(-II)) 对大宝山沉积物中重金属垂直迁移规律的影响。结果表明,S(-II)对沉积物中重金属的释放具有相对的促进作用,各重金属元素释放量的大小顺序为Zn>Mn>Cu>Pb>As>Mo>Cd>Cr,呈现前期快速释放随后缓慢的过程。在质量浓度为100 mg·L−1的Na2S溶液作用下,As、Cd、Cr、Cu、Mn、Mo、Pb和Zn的平均淋出浓度比10 mg·L−1质量浓度处理组分别高了3.182、3.784、1.973、4.098、2.979、2.582、6.786和5.408倍。释放动力学拟合结果表明,重金属的释放过程符合双常数和Elovich模型。重金属萃取实验和XRD结果证明释放的部分重金属主要来源于沉积物中的易还原矿物相。本研究结果可为金属硫化物矿区重 (类) 金属污染控制与修复提供参考。Abstract: The Fe/S cycle process restricts the migration and transformation of heavy metals (metalloids) in the metal sulfide mines. In this paper, the release kinetics combined with XRD and SEM was used to investigate the effects of S(-II) on vertical migration characteristics of heavy metals in sediments of Dabaoshan Mine. The results showed that S(-II) was beneficial to the release of heavy metals in sediments to a certain extent. The release of heavy metals was in the order of Zn>Mn>Cu>Pb>As>Mo>Cd>Cr, showing a rapid release in the early stage followed by a slow release process. When the concentration of S(-II) increased to 100 mg·L-1, the average leaching concentrations of As, Cd, Cr, Cu, Mn, Mo, Pb and Zn were 3.182, 3.784, 1.973, 4.098, 2.979, 2.582, 6.786 and 5.408 times higher than those of the 10 mg·L-1 group, respectively.. Results of release kinetics fitting revealed that the release of heavy metals fitted well on Double Constant model and Elovich model. And the partly released heavy metals were mainly from easily reducible minerals in the sediments which were characterized by XRD and extraction. The results of this research could provide theoretical basis for the remediation of heavy metals in metal sulfide mining areas.
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Key words:
- metal sulfide mining area /
- sediment /
- sulfur ion /
- heavy metals /
- migration
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表 1 各重金属元素拟合结果
Table 1. Fitting results of each heavy metal elements
重 (类) 金属
元素种类决定系数R2 一级动力学方程 双常数方程 Elovich方程 低浓度 高浓度 低浓度 高浓度 低浓度 高浓度 As 0.915 6 0.875 9 0.968 4 0.968 4 0.713 3 0.991 9 Cd 0.854 3 0.852 5 0.948 9 0.957 0 0.977 2 0.991 7 Cr 0.906 1 0.892 7 0.967 2 0.967 2 0.965 1 0.977 4 Cu 0.950 0 0.905 1 0.985 4 0.974 9 0.948 7 0.982 4 Mn 0.978 4 0.840 4 0.994 1 0.927 4 0.920 1 0.954 5 Mo 0.959 1 0.842 3 0.981 3 0.953 7 0.921 2 0.992 7 Pb 0.941 7 0.993 5 0.981 5 0.999 1 0.952 5 0.898 3 Zn 0.911 3 0.864 8 0.972 6 0.934 8 0.966 7 0.946 7 表 2 重金属萃取前后的对比
Table 2. Comparison of heavy metals before and after extraction
重金属
种类累积释放量/ (mg·kg−1) 重金属的质量分数/ (mg·kg−1) 反应前 反应后 Pb 4.40 544.55 540.20 Zn 475.53 268.43 23.49 Mn 45.97 215.12 206.15 Cu 20.60 174.40 153.70 Cr 0.07 45.32 45.26 Cd 0.31 3.93 3.64 Mo 0.53 44.01 43.52 As 1.68 540.11 538.58 注:反应前后重金属质量分数数据为水溶性、吸附和可交换态及易还原矿物相中重金属之和。 -
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