Distribution Characteristics and Source Analysis of “Three Nitrogen” in Shallow Groundwater in Hailun Area of Heilongjiang Province
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摘要:
近年来随着人类活动增加、工业废水的大量排放以及农业氮肥过量施用，使得地下水中“三氮”（即硝酸盐氮、氨氮、亚硝酸盐氮）污染问题愈加严重，对人体带来潜在健康风险。通过地下水“三氮”污染分布及来源作出解析，对于开展污染源头防控具有重要的现实意义。本文以黑龙江省海伦地区浅层地下水作为研究对象，采用气相分子吸收光谱法（GMA）及电感耦合等离子体质谱法（ICP-MS）测定了地下水中“三氮”及其他金属元素的检出情况，应用内梅罗综合污染指数法对地下水中“三氮”划分水质污染等级，综合运用Pearson相关性分析、正定矩阵因子分析法（PMF）等方法，识别和定量解析污染源及贡献。结果表明：①研究区地下水中硝酸盐氮含量范围在0.021～123.05mg/L之间，平均浓度为15.27mg/L；氨氮含量范围在 ND～3.91mg/L之间，平均浓度为0.33mg/L；亚硝酸盐含量范围在ND～0.65mg/L之间。与《地下水质量标准》（GB/T 14848—2017）Ⅲ类水指标对比，硝酸盐氮超标率为20.0%，氨氮超标率为12.5%。②内梅罗综合污染指数评价结果表明，研究区地下水水质污染等级一级至三级中度污染地下水占比为92.5%，整体上水质“三氮”污染较轻。海伦地区“三氮”空间分布整体上呈现出氨氮、硝酸盐氮流域中心区近端含量高、远端含量低的趋势。硝酸盐氮及氨氮超标点主要分布在研究区中部的人类活动密集区域。亚硝酸盐氮在空间分布上沿海伦河流向呈现出北高南低的趋势。③正定矩阵因子分析模型（PMF）源解析结果表明，硝酸盐氮主要来源于生活与工业复合源；亚硝酸盐氮主要来源于自然源；氨氮主要来源于生活与农业复合源。与中南部长三角武进地区太湖平原、西南部成都平原及东南部广花盆地地下水相比，海伦地区氨氮含量偏低，硝酸盐氮均值则均高于中南部地区。“三氮”的源解析结果呼应了东三省尤其是黑龙江部分地区“三氮”含量较高的分布特征。海伦地区地下水“三氮”污染程度整体上相对较轻，人类活动对地下水中“三氮”分布的影响较大。
Abstract:BACKGROUNDWith the increase of population, urbanization development, the large discharge of industrial wastewater and the excessive application of agricultural nitrogen fertilizer, the problem of “three nitrogen” (nitrate nitrogen, ammonia nitrogen, and nitrite nitrogen) pollution in groundwater has become increasingly serious. Due to the slow flow, weak alternation degree and poor self-purification ability, the nitrogen polluted groundwater is difficult to rehabilitate and the repair cost is high. It is of great practical significance to carry out prevention and control from the pollution source. With the concealment, complexity and hysteretic groundwater pollution property, it is difficult to conduct the source analysis of nitrate in groundwater. Positive matrix factorization (PMF) model, as a new type of source analysis model, has more interpretable and clear physical significance in terms of factor load and source factor score. At present, the application of the PMF model in the source analysis of “three nitrogen” in groundwater media is rarely reported, and the research in this field needs to be deepened. Gas-phase molecular absorption spectrometry is a practical analytical method for nitrogen compounds with high accuracy, wide linear range without color and turbidity interference. This method does not require chemical separation, and uses few chemical reagents and innoxious reagents. At present, this method has been widely used in the analysis and determination of water quality, nitrite nitrogen, ammonia nitrogen, nitrate nitrogen, total nitrogen, and other substances.
OBJECTIVESTo identify the source and distribution characteristics of the “three nitrogen” in shallow groundwater in the Hailun area.
METHODS(1) Determination of “three nitrogen” and other elements in groundwater samples. With GPS coordinates, the 40 shallow groundwater samples were collected in Helen River Basin and Zaying River Basin. The collection and preservation of groundwater samples were performed in accordance with the environmental standards HJ/T 164—2004, HJ/T 195—2005, HJ/T 197—2005 and the ecological industry standards DZ/T 0064—2021. The quality control of the “three nitrogen” test in groundwater was based on the requirements of the national standard GB/T 14848—2017, the technical requirements for analytical quality control of groundwater pollution investigation (DD 2014-15), and the specification of testing quality management for geological laboratories (DZ/T 0130—2006). Each batch contained twenty samples and the test process of each batch was equipped with laboratory blank, reference materials, laboratory duplicate samples and quality control of external monitoring samples. All of the laboratory blank results were less than 2 times the detection limit of the method. The added standard recovery rate of the sample matrix was between 80%-120%, with the relative deviation (RD) of the laboratory repeat samples under 15%. The qualified rate of external quality control sample was 100%. (2) Analysis of detection data. Statistics and analysis of “three nitrogen”, heavy metal content correlation and principal components in groundwater were carried out using WPS Office 2016 and SPSS 22.0. The spatial distribution map of “three nitrogen” content in groundwater was obtained by CoreDRAW X5.0 software. The Ⅲ class water criterion in Standard for Groundwater Quality (GB/T 14848—2017) was used as the criterion for drinking water source and industrial and agricultural water. The Nemerow pollution index was calculated and compared with the corresponding grade standard index. The PMF model was used to identify and quantify the contribution rate of each nitrogen source to comprehensively judge the source of “three nitrogen”.
RESULTS(1) The contents of “three nitrogen” and other elements in the groundwater samples in the study area were determined. According to the contents of “three nitrogen” and related parameters shown in Table 3, the detection rates of the nitrate nitrogen, ammonia nitrogen and nitrite nitrogen were 100%, 77.5% and 90.0%, respectively. The maximum detection content of nitrate nitrogen was 123.05mg/L, and average content was 15.27mg/L. The maximum detection content of ammonia nitrogen was 3.91mg/L, and average content was 0.33mg/L. The maximum detection content of nitrite nitrogen was 0.65mg/L, and average content was 0.12mg/L. Compared with the Ⅲ class water criterion, the nitrate nitrogen over standard rate was 20%, with the maximum value 6.18 times; the ammonia nitrogen over standard rate was 12.5%, with its maximum value 7.8 times; the nitrite nitrogen did not exceed the Ⅲ class water criterion. The content of Mn was ND-3.20mg/L, and the proportion of Mn in I-III class water range was 40%. The contents of 8 heavy metals including Cd were within 10 times the detection limit, with 100% Ⅰ-Ⅲ class water. The content of anion F− was 0.029-0.69mg/L. The content of anion Cl− ranged from 0.0027 to 310mg/L, with the 97.5% Ⅰ-Ⅲ class and 2.5% over standard rate. The content of SO4 2− was 0.46-433mg/L, with the 95% Ⅰ-Ⅲ class and 5% over standard rate. (2) The pollution and spatial distribution of groundwater were studied. The results of Nemerow comprehensive pollution evaluation showed that the pollution degree of “three nitrogen” in the study area was relatively low. The proportion of unpolluted samples, mild pollution samples, heavy pollution samples and serious pollution samples was 65%, 25%, 2.5% and 0, respectively (Table 4). “Three nitrogen” spatial distribution is shown in Fig.1a-c. Samples with ammonia nitrogen content ranging in Ⅰ-Ⅲ class water was mainly concentrated in the north, west, east and central; the Ⅳ class water samples were concentrated in the middle; the class V water samples were concentrated in the center. Fig.1a shows the trend of high ammonia nitrogen in the middle and low ammonia nitrogen on both sides. In Fig.1b, Ⅰ-Ⅲ class water samples of nitrate nitrogen were mainly concentrated in the central, east and north, with the Ⅳ class water in the middle and the class V water in the west. The samples with the highest and sub highest nitrate nitrogen content were located in the center of the study area, radially distributing along the Helen River Basin and the Zaying River Basin. The nitrate nitrogen content was high near the central area, with the low content far from the central area. The nitrite nitrogen in Fig.1c was Ⅰ-Ⅲ class water. The spatial distribution of the nitrite nitrogen shows the trend of high in the north and low in the south along the Helen River Basin. (3) Multivariate statistical analysis and source of “three nitrogen” in groundwater were studied. Multivariate statistical analysis of Pearson correlation coefficient showed that nitrate nitrogen had some homology with Cd, Co, Ni. Nitrate nitrogen in groundwater was significantly correlated with Cl− and SO4 2−, while ammonia nitrogen and nitrite nitrogen showed no correlation with anion. Sample detection data imported into EPA PMF5.0 software for PMF source analysis, and the industrial source, agricultural source, living source and natural factor source were taken as the four source analysis factors of “three nitrogen” in the groundwater in the study area. The PMF source analysis results are presented in Table 6 and Fig.2. The main sources of “three nitrogen” in the groundwater in the study area were the compound source of living and industrial source, which further indicated that human activity was the root cause of “three nitrogen” pollution in the groundwater in Helen area. According to the spatial distribution of “three nitrogen” in groundwater, the highest point of nitrate nitrogen pollution was distributed in the center of the research area, with the relatively developed human life and industrial activities in this area. The ammonia nitrogen pollution samples were related to the dense human activities in the middle of the study area. The over-standard area of nitrate nitrogen was higher than the ammonia nitrogen, which indicated that the compound source of living and industrial source was the main factor affecting the “three nitrogen” content in the groundwater in study area.
CONCLUSIONSThe nitrate nitrogen and ammonia nitrogen are the nitrogen pollution components in the groundwater in the study area. Compared with the water index in groundwater quality standard (GB/T 14848—2017), the over standard rates of the nitrate nitrogen and ammonia nitrogen are 20% and 12.5% respectively. The groundwater quality with pollution evaluation grade I （unpolluted） to grade Ⅲ （moderate polluted）accounts for 92.5%, which indicates relatively light pollution. The spatial distribution of ammonia nitrogen in the study area shows a trend of high in the middle and low on both sides. Nitrate nitrogen and ammonia nitrogen pollution samples are mainly distributed in the center of the intensive human activity research area. The quantitative analysis results of the “three nitrogen” PMF analysis model show that the compound source of living and industry are the main source of nitrate nitrogen pollution in the study area, and the compound source of living and agricultural production is the main source of ammonia nitrogen pollution. Combining the situation with the source of the “three nitrogen” pollution in the research area, the project of the “three nitrogen” pollution prevention can be carried out to strengthen protection, sustainable development and utilization of groundwater resources in the Helen area.
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铀是中国短缺的战略性矿产资源，核电所需铀资源对外依存度已达90%以上，中国铀矿资源禀赋不佳，虽然近年发现了一批大型铀矿床，但其中开发成本较低(40～80美元/kg)的储量仅占全球的7.8%。受开发技术条件等影响，短期内产量难以实现快速增长。砂岩型铀矿是全球重要的铀矿床类型之一，约占全球铀矿资源总储量的50%，是铀矿勘查和开发首选目标。松辽盆地是中国东部地区寻找砂岩型铀矿的主要盆地之一，不同于中亚地区楚萨雷苏和锡尔达林近1000km的大型层间氧化带海相砂岩含铀盆地，其为断凹转换盆地［1-4］，盆地面积与深度比值小，铀大量富集除了受表生流体成矿作用外，还受到深部油气还原、辉绿岩侵入的中低温热液叠加成矿等多因素影响［5-10］，故松辽盆地铀矿为复成因砂岩型铀矿，铀矿的赋存状态复杂，以盆地南部的钱家店铀矿尤为典型，是研究铀矿赋存状态和铀矿物特征的典型代表。研究铀含量配分比例的半定量特征，对矿床成因进一步研究及地浸开发奠定重要理论基础，有利于促进提高矿床地浸回收率，增强中国对铀矿资源的开发利用程度。
前人采用岩矿鉴定、电子探针、逐级化学提取、扫描电镜等方法［11-17］研究了钱家店铀矿床铀矿特征，取得了较好进展，认为铀矿物的赋存状态以独立铀矿物为主，独立矿物主要是沥青铀矿，铀石次之，铀矿物具有与黄铁矿、碳酸盐等共生的特点［18-19］。也有人认为钱家店铀矿以吸附态铀矿为主［20］，占总铀含量的73.5%，独立铀矿物含量较少，而独立铀矿物以沥青铀矿为主，含少量钛铀矿和含钛铀矿物。也有学者对钱家店铀矿床周边相同成矿条件的白兴吐矿床研究认为独立铀矿物以铀石为主［21-28］。目前对钱家店铀矿床铀赋存状态尚存在争议，矿石不同矿物中铀含量尚不明确，主要是由于对各种测定方法的结果尚缺乏综合考虑，再加上没有直接对碎屑矿物进行微区原位铀含量测定，致使铀在不同矿物中的配分认识不清，只是一种定性的认识。
本文采用薄片鉴定、逐级化学提取、电子探针等综合方法判定钱家店铀矿物特征与赋存状态，配合激光剥蚀电感耦合等离子体质谱(LA-ICP-MS)微区原位方法测定矿石中各类矿物中的铀含量，最终对不同方法的结果进行综合处理，得出矿石不同矿物中铀含量配分比例的半定量特征认识，拟为矿床成因及地浸开发提供依据。
1. 成矿地质背景
钱家店铀矿床位于松辽盆地南部开鲁坳陷东北部(图1)，是松辽盆地超大型砂岩型铀矿床，铀矿平均品位0.024%，平均铀量为2.59kg/m2[29］。铀主要赋存于上白垩统姚家组下段，岩性主要为细砂岩、中砂岩、粉砂岩及泥岩，含矿砂岩以浅灰色为主，铀矿化受控于油气还原的白色砂岩，矿体整体形态在平面上多呈块状、板状或不规则状分布。矿区发育有近EW、NW和NNE向三组断裂构造，中北部发育三个剥蚀天窗，形成小型层间氧化带，构造控矿作用也较明显。晚白垩世以来辉绿岩沿断裂带侵入，侵位于姚家组和嫩江组，平面上受断裂控制整体呈北东向带状展布并基本与铀矿化区域重合。故钱家店铀矿床铀成矿受基性岩热液、油气还原流体和层间氧化大气降水等流体影响，有丰富的铀矿化蚀变，包括较强的还原褪色、赤铁矿化、黄铁矿化和碳酸盐化等蚀变特征［30-32］，还有高岭石化、蒙脱石化、伊利石化以及绿泥石化等黏土矿物蚀变等现象，致使铀赋存状态复杂，铀矿物多样，在不同矿物中的配分也异于传统层间氧化带成矿模式。
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图 1 松辽盆地西南部钱家店铀矿床位置Figure 1. Geographical location of Qianjiadian uranium deposit in the Southwest Songliao Basin2. 样品采集与测试方法
采用岩矿鉴定方法鉴定砂岩型铀矿石中不同矿物含量，利用逐级化学提取实验测定吸附态和结合态铀含量，利用电子探针手段区分独立铀矿物种类，尝试以LA-ICP-MS微区原位分析不同矿物中铀的含量。综合以上测试方法明确铀矿赋存状态与配分，具体方法如下。
2.1 实验样品
本次在钱家店铀矿岩心库系统编录了钱家店铀矿床钱Ⅱ、钱Ⅲ、钱Ⅳ和QC四个区块代表性井位的岩心，采集了姚家组下段不同颜色、粒度和蚀变特征等具有代表性铀矿石样品(表1)，通过伽马分析仪现场初步测定样品中铀的含量，样品编号采取Q(钱家店简称)+取样时间+样品采样时排序号方式命名，如Q2019-26样品编号为2019年采集的钱家店第26块样品。测试过程中为保障实验测试分析数据准确性，采用核工业203研究所实验室铀标准溶液(CAS号：7440-61-1)、西安地质调查中心实验室提供的晶质铀矿和西北大学大陆动力学国家重点实验购置的美国NIST系列(NIST SRM610 和NIST SRM612)和USGS参考玻璃(BCR-2G)作为本次研究的标准物质。
表 1 钱家店铀矿床采集样品信息Table 1. Information of samples collected from Qianjiadian uranium deposit序号 样品编号 岩性 采样井号 铀含量
(µg/g)采样深度
(m)1 Q2019-26 灰白色中砂岩 Q4-04-07 240 402.0 2 Q2019-28 灰色炭质条带中砂岩 Q4-04-07 70 433.0 3 Q2019-37 红色泥质砂岩，致密 Q4-45-01 160 316.8 4 Q2019-48 杂色泥质砂岩，致密 Q2-WT-4 140 361.2 5 Q2019-49 含炭屑，杂色砾岩 Q2-WT-4 120 361.9 6 Q2019-50 灰白色疏松砂岩 Q2-WT-4 90 362.1 7 Q2019-51 灰色泥岩 Q3-27-04 145 387.0 8 Q2019-52 灰色中砂岩 Q3-27-04 110 387.2 9 Q2021-115 白色细砂岩，疏松 Q3-39-08 200 339.8 10 Q2021-143 杂色细砂岩，含碳屑 QC105 225 231.8 11 Q2021-151 浅红灰色中砂岩 QC43 100 527.9 12 Q2021-167 灰绿色细砂岩，含泥砾 QC100 150 344.3 13 Q2021-170 灰绿色泥质粉砂岩 QC100 90 347.5 2.2 实验方法
逐级化学提取(SCEE)实验主要被应用于铀矿和煤领域，是利用定量的方法来研究目标元素在不同赋存状态下的含量比例。本次研究是利用铀元素在不同赋存状态下的溶解度不同，选择相应的化学溶剂由弱到强依次将样品中不同赋存状态下的铀元素萃取出来，测定溶解液中UO2的丰度代表对应赋存状态下的含量，以此确定铀元素在样品中的赋存状态，实现铀赋存状态的定量化研究。实验在核工业203研究所完成，所用仪器为核工业北京地质研究院制造的MUA型激光荧光仪，铀检测方法是依据《土壤、岩石等样品中铀的测定 激光荧光法》(EJ/T 550—2000)，《铀矿石中铀的测定 三氧化钛还原/钒酸铵氧化滴定法》(EJ/T 267.3—1984)，分析流程参照Tessier等［33］和《岩石矿物分析》(第四版)［34］实验方法，并将试剂进一步完善(表2)，称取1g(精确至0.0001g)试样至50mL离心管中，分步定量提取样品中吸附态铀和结合态铀含量，其中铀吸附态包括水溶态、碳酸盐吸附态、铁锰氧化物吸附态三种，铀结合态分为硫化物及有机质结合态和残渣态两种。逐级化学提取实验中虽然可测出铀矿石中不同赋存状态的铀总含量，但所测结果是不同铀矿物相同状态的混合数据，此方法不能区分出铀矿物类型，需要采用电子探针进一步识别独立铀矿物。
表 2 砂岩型铀矿逐级化学提取实验步骤Table 2. Experimental steps for stepwise chemical extraction of sandstone-type uranium deposit提取步骤 铀赋存状态 样品处理试剂 萃取条件 振荡时间(h) 温度(℃) 1 水溶态 20mL去离子水 24 20 2 碳酸盐吸附态 1mol/L乙酸钠+1mol/L乙酸(pH=4.75) 24 20 3 铁锰氧化物吸附态 0.04mol/L盐酸氢胺+25%乙酸(pH=2) 3 90 4 硫化物及有机质结合态 30%双氧水+0.2mol/L硝酸(pH=2) 3 90 30%双氧水+3.2mol/L乙酸铵(pH=2) 3 90 5 残渣态 残渣600℃灰化后双氧水溶解 — — 电子探针是识别矿物的重要测试手段，可明确钱家店铀矿石中独立铀矿物的成分并计算铀矿物类型，本次研究为保证可以识别出较大颗粒铀矿物，挑选了铀矿石中铀品位较高的样品，磨制了厚度为150～200μm的加厚电子探针片，在中国地质调查局西安地质调查中心电子探针实验室完成测试，仪器型号为EMX-SM7SM7，实验电压控制在20kV，实验电流控制在1×10−8A，束斑大小在1～5μm范围内，检出角大小为40°，常温(25℃)，电子探针虽然在区分铀矿物特征具有明显优势，但只能以分析矿物表面成分，其内部物质或晶格中吸附的铀元素无法准确分析，需要采用LA-ICP-MS进一步分析不同矿物中的铀含量。
应用LA-ICP-MS原位微区手段测试矿石中不同矿物中吸附的UO2含量，本次选用西北大学大陆动力学国家重点实验室飞秒激光剥蚀四极杆电感耦合等离子体质谱仪(LA-ICP-MS)完成，激光剥蚀系统是193nm准分子激光剥蚀系统(RESOlution M-50，ASI)，包含一台193nm ArF准分子激光器、一个双室样品室和电脑控制的高精度X-Y样品台移动、定位系统。双室样品池能有效地避免样品间交叉污染，减少样品吹扫时间。激光能量密度为6J/cm2，频率为5Hz。每个样品数据包括大约20～30s空白信号、50s样品信号以及60s吹扫时间。对矿石中岩屑、石英、黏土、方解石等碳酸盐、磁铁矿、沥青铀矿等不同矿物中的铀含量进行测定。
2.3 实验数据处理与质量保证
逐级化学提取(SCEE)实验在质量监控方面，采取加标回收方法，在被测溶液中加入铀标准溶液(CAS号：7440-61-1)，加标回收率控制在90%～110%范围内视为样品测试合格。在电子探针实验中选择标准：GB/T 15245—2002，以晶质铀矿作为本次实验标准样品监控样，保障实验测试分析数据准确性，实验室定量分析总量允许偏差小于±3%，实验室实际测试误差小于±1%［35］。在LA-ICP-MS原位微区手段定量测试实验中以NIST系列(NIST SRM610 和NIST SRM612)和USGS参考玻璃(BCR-2G)为校正标准，采用多外标、单内标法对元素含量进行定量计算，对分析数据的离线处理(包括对样品和空白信号的选择、仪器灵敏度漂移校正、元素含量计算)采用软件ICP MS DataCal完成。
3. 结果与讨论
3.1 铀赋存状态
具有代表性的6件铀矿石样品逐级化学提取分析结果显示，不同样品因其矿物组成不同，样品间的铀赋存状态测试数据有一定差异，其中Q2019-37和Q2019-48两个泥质砂岩样品较为特殊，水溶态含量较低，这与泥岩中的铀难地浸性质一致，但两个样品中碳酸岩呈细脉状，故碳酸岩吸附含量较高。6个样品平均测试结果显示，钱家店铀矿石中以吸附态铀(包括水溶态、碳酸盐吸附态、铁锰氧化物吸附态)为主，占总铀含量的80.09%(表3)，其中黏土矿物吸附和常规硅酸盐矿物内部缺陷吸附的水溶态铀占比19.43%，方解石等碳酸盐吸附的铀占比47.86%，铁锰氧化物吸附态铀占比12.80%。矿石中以铀独立矿物形式或类质同象形式存在的结合态铀(硫化物及有机质结合态、残渣态)占比19.91%，其中硫化物及有机质结合态铀占比为5.66%，独立铀矿物或在矿物晶格中的铀(残渣态)占比为14.25%。故钱家店铀矿以吸附态铀矿为主，吸附态与独立铀矿物的比例约为4∶1。
表 3 钱家店铀矿石逐级化学提取占比Table 3. Gradual chemical extraction fraction ratio of Qianjiadian uranium ores样品编号 矿石岩性 水溶态占比
(%)碳酸盐吸附态占比
(%)铁锰氧化物吸附态占比
(%)硫化物及有机质结合态占比
(%)残渣态占比
(%)Q2019-26 灰白色中砂岩 12.10 56.95 1.58 4.97 24.39 Q2019-37 红色泥质砂岩 2.81 54.77 3.35 12.80 26.28 Q2019-48 杂色泥质砂岩 3.60 75.49 0.95 8.24 11.72 Q2019-49 含炭屑杂色砾岩 39.66 40.48 2.28 3.38 14.20 Q2021-115 含炭屑杂色砂岩 33.46 35.51 28.13 0.76 2.14 Q2021-151 浅红灰色中砂岩 24.92 23.96 40.49 3.84 6.79 平均占比 19.43 47.86 12.80 5.66 14.25 3.2 独立铀矿物特征
对钱家店铀矿石电子探针片观察发现独立铀矿物颗粒较小，约为10～150μm，主要分布在石英、长石、黄铁矿等矿物颗粒缝隙中。独立铀矿物整体较少，所占矿物比例并不与铀矿石品位相符，也说明铀矿物是以吸附态铀矿物为主。优选颗粒较大的独立铀矿物并测定了16个点，数据显示独立铀矿物主要有沥青铀矿、含钛铀矿物和铀石三种(表4)。由于沥青铀矿主要形成于中性-弱酸性、弱氧化-弱还原性，故SiO2含量较低，钱家店铀矿SiO2含量变化较大，在0.67%～12.34%之间，平均为6.46%；沥青铀矿中UO2含量在40%～65%之间。沥青铀矿主要呈雪花状、星点状、草莓状、不规则状等多种形态组成细小胶粒或胶粒结合体，均呈它形结构，与黄铁矿共生关系密切(图2)，或围绕黄铁矿边缘生长，或充填黄铁矿的裂隙，或与黄铁矿交叉共生产出。沥青铀矿在电子探针片中出现的频率大于其他独立铀矿物。
表 4 钱家店铀矿物电子探针成分分析结果Table 4. Composition of uranium minerals measured by electron probe microanalyzer in Qianjiadian样品编号 Na2O
(%)SiO2
(%)Al2O3
(%)TiO2
(%)FeO
(%)CaO
(%)K2O
(%)UO2
(%)PbO
(%)P2O5
(%)总量
(%)矿物类型 Q2019-26 0.420 1.141 0.044 2.911 0.062 2.612 0 64.555 0.000 2.225 74.410 沥青铀矿 1.318 1.154 0.245 43.995 0.893 1.704 0.347 32.412 0.052 1.773 84.443 含钛铀矿 Q2019-28 0.178 1.185 0.163 31.252 0.960 1.228 0.000 53.206 0.000 1.645 89.996 含钛铀矿 3.068 3.544 0.714 9.108 2.736 1.382 0.963 54.024 0.006 1.729 77.724 含钛铀矿 0.118 4.991 0.164 0.000 0.200 2.993 0.000 43.305 0.000 2.506 54.782 沥青铀矿 Q2019-51 0.050 3.897 2.142 6.926 1.187 4.051 0.000 55.205 0.000 4.781 78.303 含钛铀矿 0.068 10.685 0.453 0.182 1.993 2.502 0.000 63.436 0.000 3.689 83.032 沥青铀矿 0.338 8.368 1.022 0.249 2.845 4.154 0.000 64.080 0.068 5.543 87.025 沥青铀矿 0.249 12.345 1.569 0.017 1.805 4.307 0.000 63.169 0.069 5.096 89.133 沥青铀矿 0.079 15.705 6.26 0.051 2.889 3.32 0.382 48.621 0.007 4.204 83.311 铀石 Q2021-167 0.79 0.682 0.009 0.3 1.51 4.035 0 78.578 0.021 1.394 88.883 沥青铀矿 Q2021-143 0.252 0.674 0.068 0 1.148 4.412 0 68.405 0 2.084 78.333 沥青铀矿 0.7 1.137 0.138 0 0.847 5.186 0 70.828 0.031 2.762 83.298 沥青铀矿 Q2021-170 0.133 9.615 0.171 0.15 7.379 2.315 0 39.428 0.042 5.759 74.047 沥青铀矿 0.528 9.696 0.243 0 5.628 2.347 0 39.506 0.06 6.544 76.032 沥青铀矿 0.525 16.209 2.902 0 9.301 2.599 0 37.89 0.119 6.373 87.170 铀石 探针片中发现有含钛铀矿物，其TiO2含量在10%～44%之间变化，UO2含量差异较大，在30%～64%之间波动，因铀与钛铁矿交代作用不彻底，继承了钛铁矿的网络状析离体而形成丝网状结构，在电子探针图像上部分含钛铀矿具有网格状特点(图3)，故含钛铀矿物中Ti及U含量分布不均匀，且Ti与U含量呈反比，反映钱家店铀矿成矿过程中有中低温热液参与。矿石中还有少量的铀石矿物，据《铀矿物学》铀石中SiO2含量约18.2%［16］，而钱家店铀矿物中，铀石中SiO2含量平均为16%，主要分布在矿物碎屑边缘，呈块状分布。
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图 3 含钛铀矿物电子探针背散射图像Figure 3. Electron probe backscatter images of titanium-containing uranium minerals3.3 不同矿物中铀含量
对铀矿石中不同矿物颗粒进行LA-ICP-MS测试分析发现，在水溶态吸附铀的矿物中，疏松多孔结构的黏土矿物可充分接触含铀流体并提供容矿空间，平均铀含量为17.94%(表5)，是水溶态主要吸附铀的矿物。碳酸盐吸附态的矿物中，方解石等碳酸盐在所有吸附态铀中占比最高，平均占总铀含量47.86%，这也是铀矿物常与碳酸盐矿物共生关系的体现［2］。
表 5 钱家店铀矿石中各矿物UO2配分统计Table 5. UO2 distribution statistics of various minerals in Qianjiadian uranium ores赋存状态分类 矿物种类 逐级化学提取铀
(%)矿物含量
(%)铀含量
(%)测试方法 铀的配分
(%)水溶态 岩屑 19.43 6.5 0.012 电子探针 0.07 石英 21.6 0.04 0.79 黑云母 0.96 0.043 LA-ICP-MS 0.04 黏土 14.28 1.37 17.94 钾长石 14.67 0.044 0.59 碳酸盐吸附态 方解石等
碳酸盐47.86 10.3 1.43 电子探针 47.86 铁锰氧化物吸附态 磁铁矿 12.80 0.85 0.036 LA-ICP-MS 0.36 闪锌矿 0.91 0.022 0.23 其他铁锰氧化物 2.49 0.42 逐级化学提取测算 12.21 有机质黄铁矿结合态 黄铁矿 5.66 11.6 0.048 LA-ICP-MS 0.43 有机质 5.64 1.20 逐级化学提取测算 5.23 残渣态 含钛铀矿 14.25 1.83 26.88 电子探针 2.78 沥青铀矿 2.7 59.35 9.07 铀石 0.94 43.25 2.30 独居石 1.42 0.77 扫描电镜 0.06 块磷铝石 0.8 0.13 0.01 磷灰石 0.97 0.18 0.01 锆石 1.54 0.19 LA-ICP-MS 0.02 铁锰氧化物吸附态的矿物中，本实验仅发现了磁铁矿和闪锌矿等矿物，从测试结果看，这两种矿物中铀吸附含量远小于逐级化学提取中的比例，主要是因为本实验样品中尚有未发现的其他铁锰氧化物，通过逐级化学提取数据测算其铀含量占比12.21%，还需要进一步开展大量的实验数据统计。硫化物及有机质结合态的矿物中，因技术方法限制，电子探针和LA-ICP-MS无法直接测定有机质中UO2含量，目前只能通过逐级化学提取数据测算其铀含量占比5.23%，而黄铁矿表面吸附铀矿相对含量较低，占比仅0.43%。以残渣态的矿物中，独立铀矿物中UO2含量最高，沥青铀矿、含钛铀矿和铀石三种矿物中铀含量共占14.15%，以类质同象方式赋存在锆石、独居石、磷灰石、块磷铝石等矿物中的UO2含量仅共占0.10%，这些类质同象的铀尚无法进行开采。
4. 铀的配分
通过对岩矿鉴定矿物含量比例、逐级化学提取中铀各组分的比例，以及电子探针测定含量结果综合分析、半定量计算各矿物吸附或赋存UO2的份额(表5)，认为钱家店铀矿石吸附态铀主要赋存在方解石等碳酸盐、铁黏土和锰氧化物中，独立铀矿物以沥青铀矿为主，主要赋存在有机质、黄铁矿周边。
5. 结论
采用薄片鉴定、化学逐级提取、电子探针等方法判定铀矿物特征与赋存状态，LA-ICP-MS微区原位方法测定各矿物铀含量，认为钱家店铀矿床铀矿物以吸附态为主，约占铀总量80%，其中分布在方解石等碳酸盐矿物吸附铀约占47.86%，黏土矿物吸附铀约占17.94%，铁锰氧化物矿物吸附铀约占12.21%。结合态铀矿物约占20%，有机质(煤屑)约占5.23%，沥青铀矿约占9.07%，含钛铀矿和铀石约占5.08%。
通过对本次测试结果进行综合处理，形成了钱家店铀矿床中铀含量配分比例的半定量特征认识，可对矿床成因研究及地浸开发奠定基础。但本次研究尚存有局限性，不能对有机质中铀含量直接进行LA-ICP-MS微区原位测定，部分矿物在本次实验测试的样品中未发现，不同矿物实验测试的选择有待完善，后期将加大实验数据量来增强统计规律。
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图 1 研究区地下水采样点及“三氮”含量空间分布示意图
Figure 1. Schematic diagrams of groundwater sampling points and “three nitrogen” content in the study area. a—ammonia nitrogen; b—nitrate nitrogen; c—nitrite nitrogen.
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图 2 基于PMF的各因子对地下水中“三氮”及重金属等含量分布的贡献率
因子1—生活-工业复合源；因子2—自然源；因子3—农业源；因子4—生活源。
Figure 2. Contribution rate of each factor based on PMF to the distribution of three nitrogen and heavy metals in the groundwater. Factor 1—Living-industrial compound source; Factor 2—Natural source; Factor 3—Agricultural source; Factor 4—Domestic source.
表 1 样品测试质量控制结果统计
Table 1 Statistics of recovery rate and relative deviation.
分析项目 加标回收率
（80%～120%）实验室重复样相对偏差
（≤15%）Mn 90.9%～110.6% 3.40 Cd 89.6%～113.6% 2.40 Pb 85.0%～105.0% 5.10 Zn 85.6%～90.2% 12.6 Cu 83.0%～95.0% 11.4 Co 84.0%～94.0% 11.2 Ni 82.0%～89.0% 11.8 As 97.0%～107.0% 4.10 Hg 85.0%～98.3% 14.5 NO3 −-N 82.1%～96.0% 11.0 NH4 +-N 83.0%～89.0% 11.9 NO2 −-N 82.2%～92.0% 13.4 F− 82.3%～91.1% 13.2 Cl− 85.0%～92.5% 12.4 SO4 2− 83.0%～90.0% 13.0 
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内梅罗综合
污染指数 F污染等级 污染程度 内梅罗综合
污染指数 F污染等级 污染程度 F≤0.8 Ⅰ 未污染 4.25＜F≤7.2 Ⅳ 较重污染 0.80＜F≤2.5 Ⅱ 轻度污染 F≥7.2 Ⅴ 严重污染 2.5＜F≤4.25 Ⅲ 中度污染
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表 3 研究区地下水中“三氮”含量统计
Table 3 Statistics of ammonia nitrogen, nitrate nitrogen, and nitrite nitrogen contents in groundwater.
统计项目 硝酸盐氮
含量氨氮
含量亚硝酸盐氮含量 最大值（mg/L） 123.05 3.91 0.65 最小值（mg/L） 0.021 ND（未检出） ND（未检出） 平均值（mg/L） 15.27 0.33 0.12 标准偏差 28.56 0.79 0.26 变异系数（100%） 1.87 2.42 2.27 《地下水质量标准》（GB/T 14848—2017）Ⅲ类水（mg/L） 20 0.5 1.0 偏度 2.52 3.66 2.43 峰度 6.47 13.66 5.94 检出率（%） 100 77.5 90.0 超标率（%） 20 12.5 0
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表 4 研究区地下水内梅罗综合污染指数（F）评价结果
Table 4 Evaluation results of Nemerow comprehensive pollution index in groundwater in the study area.
内梅罗综合污染
指数（F）范围污染等级 污染程度 样品数量
（件）占比
（%）F≤0.8 Ⅰ 未污染 26 65 0.80＜F≤2.5 Ⅱ 轻度污染 10 25 2.5＜F≤4.25 Ⅲ 中度污染 1 2.5 4.25＜F≤7.2 Ⅳ 较重污染 3 7.5 F≥7.2 Ⅴ 严重污染 0 0
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表 5 地下水中“三氮”与重金属及阴离子的Pearson相关性系数
Table 5 Pearson correlation coefficient of heavy metals and negative ions in the groundwater.
组分 Mn Cd Pb Zn Cu Co Ni As Hg NO3 −−N NH4 +−N NO2 −−N F− Cl− SO4 2− Mn 1 Cd −0.166 1 Pb 0.151 0.220 1 Zn 0.086 0.191 0.172 1 Cu 0.085 −0.037 0.469** 0.196 1 Co 0.380* 0.196 0.423** 0.137 0.112 1 Ni −0.026 0.103 0.191 0.155 0.009 0.400* 1 As 0.302 −0.160 0.396* −0.135 0.020 0.326* 0.031 1 Hg −0.103 −0.047 −0.090 0.005 0.014 −0.016 0.385* −0.103 1 NO3 −−N −0.304 0.370* −0.038 −0.204 0.060 0.329* 0.319* −0.146 −0.117 1 NH4 +−N 0.059 −0.107 −0.055 0.040 −0.067 −0.138 −0.157 0.106 −0.075 −0.132 1 NO2 −−N 0.181 −0.146 −0.101 −0.212 −0.028 0.327* −0.095 0.167 0.003 −0.169 −0.033 1 F− 0.082 0.195 0.189 0.509** 0.080 −0.029 −0.195 0.312* −0.116 −0.287 0.193 −0.009 1 Cl− −0.051 −0.049 0.169 −0.212 0.106 0.440** 0.485** 0.087 0.198 0.605** −0.122 −0.098 −0.098 1 SO4 2− −0.157 0.244 0.044 −0.236 0.104 0.376* 0.288 −0.041 −0.024 0.897** −0.153 −0.182 −0.157 0.796** 1 注： “**”表示在 0.01水平（双侧）上显著相关，“*”表示在 0.05水平（双侧）上显著相关。
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表 6 地下水中“三氮”及重金属含量实测值与模拟预测值的拟合结果
Table 6 Fitting results of measured value and simulated predicted value of three nitrogen and heavy metal contents in the groundwater.
分析项目 R2 截距 斜率 P/O Mn 0.672 10.139 0.369 0.894 Cd 0.901 10.667 0.548 0.779 Pb 0.605 5.161 0.237 0.802 Co 0.870 −10.208 0.856 0.804 Ni 0.557 75.286 0.786 0.781 As 0.733 45.310 0.812 0.870 NO3 −−N 0.749 −1.193 0.752 0.775 NH4 +−N 0.797 0.186 0.756 0.896 NO2 −−N 0.750 0.114 0.756 0.887 Cl− 0.773 −10.369 0.835 0.791 SO4 2− 0.531 −9.631 0.921 0.809
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