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Article(id=1147999695378571315, tenantId=1146029695717560320, journalId=1146123346816638986, issueId=1147999683156370319, articleNumber=1000-8063(2025)01-0093-08, orderNo=null, doi=10.13426/j.cnki.yky.2024.06.12, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1719417600000, receivedDateStr=2024-06-27, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1751634056181, onlineDateStr=2025-07-04, pubDate=1739980800000, pubDateStr=2025-02-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1751634056181, onlineIssueDateStr=2025-07-04, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1751634056181, creator=13701087609, updateTime=1751634056181, updator=13701087609, issue=Issue{id=1147999683156370319, tenantId=1146029695717560320, journalId=1146123346816638986, year='2025', volume='44', issue='1', pageStart='1', pageEnd='150', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1751634053267, creator=13701087609, updateTime=1759123824852, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1179414062141158321, tenantId=1146029695717560320, journalId=1146123346816638986, issueId=1147999683156370319, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1179414062141158322, tenantId=1146029695717560320, journalId=1146123346816638986, issueId=1147999683156370319, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=93, endPage=100, ext={EN=ArticleExt(id=1147999695537954881, articleId=1147999695378571315, tenantId=1146029695717560320, journalId=1146123346816638986, language=EN, title=Numerical Simulation Prediction of Natural Attenuation of Groundwater Uranium in a Post-mining Area at an In-situ Leaching Uranium Mine, columnId=1175805042197152439, journalTitle=Uranium Mining and Metallurgy, columnName=SAFETY AND ENVIRONMENT PROTECTION, runingTitle=null, highlight=null, articleAbstract=

The remediation of groundwater environment in the post-mining area at in-situ leaching uranium mines has aroused widespread public concern. The long-term change of groundwater U concentration in the post-mining area is still unclear. Field investigation and numerical simulation methods were comprehensively used in this study, and a typical post-mining area of a “CO2+O2” in-situ leaching uranium mine in northern China was taken as the research object. On the basis of identifying the distribution characteristics of groundwater U in the post-mining area, the natural attenuation trend of U in groundwater at different times was quantitatively predicted, and the long-term change of U concentration was quantified. The results show that the concentration of U in the groundwater in the post-mining area is 0.273~5.24 mg/L, and the sampling points with U concentration lower than 2.5 mg/L accounted for 64%. The simulation results show that in the post-mining stage, the groundwater flow direction tend to the regional groundwater flow direction. When the natural attenuation process of U is not considered, U in groundwater migrate to 167 m downstream after 100 years of final mining, and the predicted migration distance is conservative. When the natural attenuation of U is considered, the migration distance of U is only 42 m after 100 years of final mining. The concentration of U in the groundwater in the mining area is reduced from the initial 2.5 mg/L to below 1.0 mg/L. Natural attenuation can reduce the migration distance and the concentration of groundwater U in the post-mining area, and the monitored natural attenuation (MNA) technology can be used as an alternative scheme for groundwater remediation at in-situ leaching uranium mines in the future.

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杨冰(1988—),男,河北保定人,博士,高级工程师,主要研究方向为地浸采铀及地下水修复。

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杨冰(1988—),男,河北保定人,博士,高级工程师,主要研究方向为地浸采铀及地下水修复。

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杨冰(1988—),男,河北保定人,博士,高级工程师,主要研究方向为地浸采铀及地下水修复。

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journalId=1146123346816638986, articleId=1147999695378571315, language=CN, orderNo=4, keyword=铀), Keyword(id=1179340521525883022, tenantId=1146029695717560320, journalId=1146123346816638986, articleId=1147999695378571315, language=CN, orderNo=5, keyword=数值模拟)], refs=[Reference(id=1179340523115524267, tenantId=1146029695717560320, journalId=1146123346816638986, articleId=1147999695378571315, doi=null, pmid=null, pmcid=null, year=2018, volume=38, issue=3, pageStart=1185, pageEnd=1193, url=null, language=null, rfNumber=[1], rfOrder=0, authorNames=李元杰, 王森杰, 张敏, journalName=中国环境科学, refType=null, unstructuredReference=李元杰, 王森杰, 张敏, 等. 土壤和地下水污染的监控自然衰减修复技术研究进展[J]. 中国环境科学, 2018, 38(3):1185-1193., articleTitle=土壤和地下水污染的监控自然衰减修复技术研究进展, refAbstract=null), Reference(id=1179340523165855916, tenantId=1146029695717560320, journalId=1146123346816638986, articleId=1147999695378571315, doi=null, pmid=null, pmcid=null, year=2018, volume=38, issue=3, pageStart=1185, pageEnd=1193, url=null, language=null, rfNumber=[1], rfOrder=1, authorNames=LI Yuanjie, WANG Jiesen, ZHANG Min, journalName=China Environmental Science, refType=null, unstructuredReference=LI Yuanjie, WANG Jiesen, ZHANG Min. 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Environmental Science & Technology, 2008, 42(23):8703-8708., articleTitle=Reductive immobilization of uranium(VI) by amorphous iron sulfide, refAbstract=null)], funds=[Fund(id=1179340522972917930, tenantId=1146029695717560320, journalId=1146123346816638986, articleId=1147999695378571315, awardId=项目编号42072273, language=CN, fundingSource=国家自然科学基金面上项目(CO2+O2地浸铀矿山退役采区地下水铀的生物地球化学过程及反应运移机理)(项目编号42072273), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1179340519554560078, tenantId=1146029695717560320, journalId=1146123346816638986, articleId=1147999695378571315, xref=1, ext=[AuthorCompanyExt(id=1179340519562948687, tenantId=1146029695717560320, journalId=1146123346816638986, articleId=1147999695378571315, companyId=1179340519554560078, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1 The Fourth Research and Design Engineering Corporation, CNNC, Shijiazhuang 050021, China), 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figureFileBig=EnH7I/d8Yky0Kzg90Ar6sg==, tableContent=null), ArticleFig(id=1179340522645762215, tenantId=1146029695717560320, journalId=1146123346816638986, articleId=1147999695378571315, language=CN, label=图7, caption=考虑Kd时不同时间地下水中U的迁移距离, figureFileSmall=1qpcYn/2jFcyk8Rz2MRhYA==, figureFileBig=EnH7I/d8Yky0Kzg90Ar6sg==, tableContent=null), ArticleFig(id=1179340522708676776, tenantId=1146029695717560320, journalId=1146123346816638986, articleId=1147999695378571315, language=EN, label=Table 1, caption=

Main parameters of the model

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参数分区 主要参数 取值 依据
采区内 渗透系数/(m/d) 0.6 现场抽水试验
弹性贮水率/(1/m) 10-4 经验值
孔隙度 0.32 经验值
弥散度/ m 10 经验值
分配系数/(m3/mg) 10-10 文献[20]6
采区外 渗透系数/(m/d) 0.1 文献[11]98
弹性贮水率/(1/m) 10-4 经验值
孔隙度 0.30 经验值
弥散度/ m 10 经验值
分配系数/(m3/mg) 10-8 文献[20]6
), ArticleFig(id=1179340522771591337, tenantId=1146029695717560320, journalId=1146123346816638986, articleId=1147999695378571315, language=CN, label=表1, caption=

模型主要参数一览表

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参数分区 主要参数 取值 依据
采区内 渗透系数/(m/d) 0.6 现场抽水试验
弹性贮水率/(1/m) 10-4 经验值
孔隙度 0.32 经验值
弥散度/ m 10 经验值
分配系数/(m3/mg) 10-10 文献[20]6
采区外 渗透系数/(m/d) 0.1 文献[11]98
弹性贮水率/(1/m) 10-4 经验值
孔隙度 0.30 经验值
弥散度/ m 10 经验值
分配系数/(m3/mg) 10-8 文献[20]6
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地浸铀矿山终采区地下水中铀的自然衰减数值模拟预测
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杨冰 1 , 孟童 1 , 张昊岩 1 , 连国玺 2 , 李梦姣 1
铀矿冶 | 安全·环保 2025,44(1): 93-100
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铀矿冶 | 安全·环保 2025, 44(1): 93-100
地浸铀矿山终采区地下水中铀的自然衰减数值模拟预测
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杨冰1, 孟童1, 张昊岩1, 连国玺2, 李梦姣1
作者信息
  • 1 中核第四研究设计工程有限公司, 河北 石家庄 050021
  • 2 北京师范大学 环境学院, 北京 100875

    • 杨冰(1988—),男,河北保定人,博士,高级工程师,主要研究方向为地浸采铀及地下水修复。

Numerical Simulation Prediction of Natural Attenuation of Groundwater Uranium in a Post-mining Area at an In-situ Leaching Uranium Mine
Bing YANG1, Tong MENG1, Haoyan ZHANG1, Guoxi LIAN2, Mengjiao LI1
Affiliations
  • 1 The Fourth Research and Design Engineering Corporation, CNNC, Shijiazhuang 050021, China
  • 2 School of Environment, Beijing Normal University, Beijing 100875, China
出版时间: 2025-02-20 doi: 10.13426/j.cnki.yky.2024.06.12
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摘要
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地浸铀矿山终采区地下水环境修复问题是社会各界关注的焦点,当前对地浸终采区地下水U浓度的长期变化情况尚不清楚。综合利用野外调查及数值模拟方法,以中国北方某“CO2+O2”地浸铀矿山典型终采区为研究对象,在识别终采区地下水U分布特征的基础上,定量预测了不同时间地下水中U的自然衰减趋势,量化了U浓度在较长时间尺度上的变化情况。结果表明,终采区地下水中ρ(U)为0.273~5.24 mg/L,ρ(U)低于2.5 mg/L的取样点占比为64%;在地浸铀矿山终采后,地下水流向趋向于区域地下水的流向;当不考虑U自然衰减作用时,地下水中U在终采100年时可迁移至下游167 m处,预测迁移距离较保守;当考虑U的自然衰减作用时,终采100年时U的迁移距离仅为42 m,采区内地下水中的ρ(U)由模拟初始条件设置的2.5 mg/L降至1.0 mg/L。自然衰减作用可降低地浸终采区地下水中U的迁移距离和浓度水平,监控自然衰减技术(Monitored Natural Attenuation, MNA)可作为未来地浸铀矿山地下水修复的备选方案。
地浸铀矿山  /  监控自然衰减  /  地下水  /  铀  /  数值模拟

The remediation of groundwater environment in the post-mining area at in-situ leaching uranium mines has aroused widespread public concern. The long-term change of groundwater U concentration in the post-mining area is still unclear. Field investigation and numerical simulation methods were comprehensively used in this study, and a typical post-mining area of a “CO2+O2” in-situ leaching uranium mine in northern China was taken as the research object. On the basis of identifying the distribution characteristics of groundwater U in the post-mining area, the natural attenuation trend of U in groundwater at different times was quantitatively predicted, and the long-term change of U concentration was quantified. The results show that the concentration of U in the groundwater in the post-mining area is 0.273~5.24 mg/L, and the sampling points with U concentration lower than 2.5 mg/L accounted for 64%. The simulation results show that in the post-mining stage, the groundwater flow direction tend to the regional groundwater flow direction. When the natural attenuation process of U is not considered, U in groundwater migrate to 167 m downstream after 100 years of final mining, and the predicted migration distance is conservative. When the natural attenuation of U is considered, the migration distance of U is only 42 m after 100 years of final mining. The concentration of U in the groundwater in the mining area is reduced from the initial 2.5 mg/L to below 1.0 mg/L. Natural attenuation can reduce the migration distance and the concentration of groundwater U in the post-mining area, and the monitored natural attenuation (MNA) technology can be used as an alternative scheme for groundwater remediation at in-situ leaching uranium mines in the future.

in-situ leaching uranium mine  /  monitored natural attenuation  /  groundwater  /  uranium  /  numerical simulation
杨冰, 孟童, 张昊岩, 连国玺, 李梦姣. 地浸铀矿山终采区地下水中铀的自然衰减数值模拟预测. 铀矿冶, 2025 , 44 (1) : 93 -100 . DOI: 10.13426/j.cnki.yky.2024.06.12
Bing YANG, Tong MENG, Haoyan ZHANG, Guoxi LIAN, Mengjiao LI. Numerical Simulation Prediction of Natural Attenuation of Groundwater Uranium in a Post-mining Area at an In-situ Leaching Uranium Mine[J]. Uranium Mining and Metallurgy, 2025 , 44 (1) : 93 -100 . DOI: 10.13426/j.cnki.yky.2024.06.12
正文
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监控自然衰减(Monitored Natural Attenuation, MNA)是指在污染场地中,通过实施有计划的监测方案,基于场地自然发生的物理、化学及生物等作用(包括稀释、扩散、挥发、吸附、化学性或生物性稳定、生物降解以及放射性衰减等),使土壤和地下水中污染物的数量、毒性、可迁移性降低到风险可接受水平[1]。该技术对放射性及非放射性元素均有修复效果[2],且成本较低、无二次污染。学者利用U、S同位素方法证明了当地质条件有利于氧化还原反应时,自然衰减可作为一种具有成本效益的修复方案;硫酸盐还原过程是地下水中U自然衰减的主要作用[3-4]。Reimus等利用野外试验研究了地浸铀矿山地下水中U的自然衰减情况,通过注入含U溶液,对比抽出液中U的回收率来验证U在含水层中的自然衰减情况,试验一年后,抽出液中含有39%的U[5]。U共有3种天然同位素,半衰期分别为4.47×109(238U)、7.04×108(235U)和2.46×105(234U)年。目前,长时间尺度下地下水中U的自然衰减情况尚不清楚,准确预测地浸铀矿山终采区地下水中U的自然衰减行为,对地下水修复方案的选择与制定至关重要。
GMS软件在地下水污染物运移模拟预测领域应用广泛[6-8],利用数值模拟技术可实现污染物迁移情况的长期预测。GMS软件中的“概念建模”方法可较全面反映研究区的水文地质条件,其中MODFLOW及MT3DMS模块可较好地解决地浸铀矿山流场预测及溶质运移预测问题[9-10][11]99。目前,对地浸铀矿山地下水的数值模拟工作大多聚焦于对流场变化情况的预测[12-13];而U的地球化学性质活泼,在地下水中迁移时会发生吸附-解吸[14-16]、氧化-还原[17-18]等多种水文地球化学反应,利用适当参数表征U因化学反应而发生的固液两相间的迁移情况是合理预测U迁移范围的基础。分配系数(Kd)是环境影响评估的重要参数,可用来预测地下水中U的反应运移情况[19],[20]2;当其表示为pH、Eh以及配位体浓度的函数时,还可表征U在固液两相间的分配情况[21]。
以中国北方某“CO2+O2”地浸铀矿山的典型终采区(C7采区)为研究对象,通过野外取样调查确定采区终采时地下水中U的分布情况;结合该铀矿山区域水文地质条件,利用GMS软件建立C7采区数值模型;以Kd综合反映地下水中U因吸附、还原等过程的自然衰减情况,预测长时间序列地下水中U的迁移范围,以期为自然衰减技术的可行性提供依据。
1 研究区概况
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1.1 采区概况
C7采区2012年投产运行,共有27口抽液井、74口注液井,采用“五点型”与“七点型”相结合的井型,其中“五点型”抽注液井间距为30 m,“七点型”抽注液井间距为28 m,累计浸采率已达80%。该采区与其他采区相对位置见图1。
1.2 水文地质条件
研究区铀矿床构造上处于松辽盆地西南部开鲁坳陷钱家店次级凹陷内,区域上属于松辽平原辽河水文地质单元[22]。C7采区含矿含水层为姚家组下段[23],岩性主要为浅灰色、浅红色含粉砂细-中粒砂岩、中细砂岩、细砂岩。采区终采时,利用抽水试验获得的渗透系数为0.55~0.62 m/d,水位埋深为18.54~54.30 m。受生产阶段抽注影响,采区内部流场发生了明显变化,等水位线见图2,区域地下水整体流向仍保持由西南向北东。
1.3 终采区地下水铀分布现状
地下水样品采集遵循《地下水环境监测技术规范》(HJ 164—2020)中的地下水采样方法,取样深度为对应含矿层深度位置。2022年8—11月,共采集C7采区内39口井的地下水样品。样品采集前,先利用潜水泵抽出3倍以上井筒体积的水,之后利用SS Geosub2电动潜水泵定深采集深度250 m处的地下水样品,该深度为研究区含矿含水层对应深度。采出地下水样品后,用0.45 μm孔径的滤膜过滤,并用1∶1的HNO3将地下水样品酸化至pH<2之后,使用ICP-AES(i CAP6000,Thermo)电感耦合等离子体原子发射光谱法测定地下水中的U浓度。样品测试前进行空白样品及标准物质测定,以控制测试质量。
结果表明,终采区地下水中ρ(U)为0.273~5.24 mg/L,其中仅有1口井地下水中ρ(U)大于5.0 mg/L;ρ(U)大于2.5 mg/L的样品数为14,占比约为36%;ρ(U)小于1.0 mg/L的样品数为18,占比约为46%。ρ(U)分布情况见图3。可以看出,C7采区地下水中ρ(U)存在较大的空间变异性,这主要受控于铀矿品位与生产过程。
2 地下水铀自然衰减预测模型
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利用GMS软件进行终采区地下水铀自然衰减预测,计算模块为MODFLOW与MT3DMS。
2.1 概念模型
2.1.1 模拟范围及边界条件
在本研究中,忽略其他采区生产对C7采区的影响。结合区域地下水流向,在垂直水流方向采区边界上、下游约1 000 m处,设置为通用水头边界;在平行水流方向采区两侧约600 m处,设置为零流量边界(图4)。
2.1.2 初始条件
利用Dipper-T水位计测试了C7采区56口井的水位埋深,为17.8~53.6 m;结合井口标高获取初始水头,为104.21~140.34 m。根据地下水样品ρ(U)测试结果,64%的地下水样品ρ(U)<2.5 mg/L,可以保守地认为终采区地下水ρ(U)在该浓度水平时,即可以不再进行人工干预,而靠自然衰减作用处理。因此,C7终采时采区内部ρ(U)取统一值(2.5 mg/L)用于后续模拟预测。
2.1.3 模型参数
根据现场抽水试验结果设置采区内部渗透系数,参考投产前数值确定采区外部渗透系数,根据前期室内试验结果选择分配系数[24],弹性贮水率、孔隙度及弥散度选择经验值。模型主要参数见表1。
2.2 数值模型
模型共剖分了21 402个网格,单个网格大小约为13 m×10 m。共设置了365个盈利期,总模拟时长36 500 d。
3 结果与讨论
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3.1 流场变化情况
地下水中放射性核素的分布受控于水流系统及地球化学特征,地下水流速、含水介质的氧化还原条件等均会影响地下水中U的迁移。因此,水文地质条件及渗流系统的演化对放射性核素在地下水中的迁移影响较大[25]。在地浸采区生产时,抽注液井运行且总抽液量大于总注液量,受抽注液井运行情况的影响,采区内流场会发生明显的变化,在注液井周围形成高水头区,在抽液井周围形成低水头区,而采区整体形成指向其内部的水力梯度。采区终采后,原有的抽注液井停止运行,在天然水力梯度的影响下,采区内部流场会向整体区域流场的形态演化。根据模拟结果(图5),C7采区在终采1年后,地下水流向又变为由西南指向北东,与矿床所处区域地下水整体流向一致。
3.2 不考虑自然衰减时U的迁移范围
当不考虑化学反应对地下水中U迁移的影响时,U仅在对流、水动力弥散作用下进行迁移。不考虑Kd时的溶质运移模拟结果见图6。可以看出,终采1年后,C7采区内残余浸出液中的U在天然流场的影响下,向下游迁移了约18 m;10年后,地下水中U向下游的迁移距离增加到37 m;50年后,地下水中U向下游迁移距离为96 m;100年时,地下水中U向下游迁移的距离达到167 m。从整体上看,污染羽中心已经迁移至采区外部。根据前人的研究结果,终采区中污染物向下游迁移的速度远低于区域地下水流速[26]。因此,在不考虑各种水岩相互作用造成的地下水中U的自然衰减情况时,预测得到的地下水中U的迁移距离偏保守。
3.3 考虑自然衰减时U的迁移范围
地下水中U的化学性质活泼,砂岩对地下水中U的吸附作用明显[27-28],黄铁矿等还原性物质的存在也会进一步降低地下水中U的可迁移性[29-31]。通过在模型中加入Kd值,以反映U因吸附、还原等作用而发生的自然衰减情况,从模拟结果(图7)可得出,受自然衰减作用的影响,地下水中U的迁移距离明显减小,采区终采1年后,其迁移距离约13 m;终采10年后,其迁移距离约为18 m;终采50年后,U的迁移距离为31 m;采区终采100年时,其迁移距离仅为42 m,相较于不考虑U的自然衰减过程时,迁移距离减小了约75%,大部分U浓度较高的残余浸出液仍在采区内分布。同时,由于自然衰减作用,地下水中ρ(U)也有较明显的降低趋势,在采区终采100年后,采区内大部分区域地下水ρ(U)由初始的2.5 mg/L降至1.0 mg/L以下。
4 结论
收起
1)地浸采区终采后,流场形态会发生明显变化。在天然水力梯度影响下,生产阶段形成的“降落漏斗”会逐渐消失,终采区流场形态向区域流场形态演化,地下水流向趋向区域地下水流向。
2)当不考虑U在地下环境中的自然衰减作用时,其迁移距离主要受控于地下水的渗流速度及水动力弥散作用,地下水中U的迁移距离偏大;当考虑U的自然衰减作用时,地下水中U的迁移距离明显减小,U浓度显著降低。Kd可作为集总性参数,反映吸附、还原等作用造成的地下水中U的自然衰减情况。
3)自然衰减作用可以明显降低地下水中U的浓度,监控自然衰减技术具有作为地浸铀矿山地下水修复方案的可行性。
基金
收起
  • 国家自然科学基金面上项目(CO2+O2地浸铀矿山退役采区地下水铀的生物地球化学过程及反应运移机理)(项目编号42072273)
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2025年第44卷第1期
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doi: 10.13426/j.cnki.yky.2024.06.12
  • 接收时间：2024-06-27
  • 首发时间：2025-07-04
  • 出版时间：2025-02-20
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  • 收稿日期：2024-06-27
基金
国家自然科学基金面上项目(CO2+O2地浸铀矿山退役采区地下水铀的生物地球化学过程及反应运移机理)(项目编号42072273)
作者信息
    1 中核第四研究设计工程有限公司, 河北 石家庄 050021
    2 北京师范大学 环境学院, 北京 100875
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2种不同金属材料的力学参数
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
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红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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