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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风化壳淋积型稀土矿床，即离子吸附型稀土矿床，此类矿床轻重稀土元素分配齐全，且可不经矿物分解的形式来分离稀土元素，是中国的优势矿产资源，也是世界上稀缺的矿产资源［1-5］。风化壳淋积型稀土矿床中稀土元素的赋存状态非常复杂，前人将此类矿床中的稀土元素划分为离子吸附相（含可交换性吸附态、专性吸附态），胶体分散相（含胶体吸附态、凝胶态），独立矿物相（含表生矿物态、残留矿物态），晶格杂质相（含类质同象态、内潜同晶态），这“四相八态”被称为“全相”稀土。目前“离子型”稀土提取工艺基本只能够利用“可交换吸附态”的稀土元素即“离子相”稀土，其他相态的稀土元素尚不能被有效地回收利用［6］。传统观点认为，风化壳淋积型稀土矿床中，稀土主要以吸附态赋存于风化壳黏土矿物表面，独立矿物相、晶格杂质等其他赋存形式占比较少。但近年来同步辐射研究显示，稀土元素也同时以内层络合物形式存在［7-8］，而内层络合有可能抑制了矿石中稀土的离子交换率［9］。稀土元素还可以与有机质形成稳定的有机-稀土络合物［10］。如何将离子吸附型稀土矿中各种形态的稀土元素有效地溶出，对于提高稀土资源利用率十分重要。
分析风化壳淋积型稀土矿样品中的稀土元素时，常用的前处理方法有酸溶、碱熔、强电解质交换等方法。对于离子吸附型稀土矿，盐酸-硝酸-氢氟酸-高氯酸-硫酸（五酸）敞开法可在一定条件下代替操作复杂的碱熔法［11-12］，用于测定样品中的“全相”稀土元素。《离子型稀土矿混合稀土氧化物化学分析方法 十五个稀土元素氧化物配分量的测定》（GB/T 18882.1—2008）中则选择使用50%的盐酸来溶出离子型稀土矿样品中的稀土元素。硫酸铵浸提是目前应用最为普遍的提取离子吸附型稀土矿中稀土元素的方法，也是在离子吸附型稀土矿稀土提取工艺中最常用的前处理方法［13-16］。上述前处理方法对风化壳淋积型稀土矿样品中稀土元素的溶出机理与结果的差异，尚无相关比较与讨论。
本文选取混合酸（五酸）消解、盐酸消解、硝酸消解、硫酸铵浸提的前处理方法，对来自中国南岭地区风化壳淋积型稀土矿的多个稀土样品开展了前处理研究，使用电感耦合等离子体质谱（ICP-MS）对处理后的样品进行测定，并探讨了不同前处理方法获得结果的差异，以及稀土元素化学特征和赋存状态之间的关系。以期为进一步研究风化壳淋积型稀土矿中稀土元素提取方法提供新的思路。
1. 实验部分
1.1 仪器设备及工作条件
稀土元素的测定使用的仪器为NexION 300D电感耦合等离子体质谱仪（美国PerkinElmer公司）。仪器工作条件见表1。
表 1 电感耦合等离子体质谱仪工作条件Table 1. Operating parameters for ICP-MS measurements.工作参数 设定值 工作参数 设定值 ICP功率 1300W 跳峰 1点/质量 冷却气流速 13.0L/min 停留时间 10ms/点 辅助气流速 1.2L/min 扫描次数 40次 雾化气流速 0.9L/min 测量时间 31s 取样锥孔径 1.0mm 截取锥孔径 0.9mm 超锥孔径 1.1mm 样品消解实验主要设备：控温鼓风干燥箱；多孔控温电热板；平板电热板；分析天平；30mL带盖聚四氟乙烯坩埚；100mL玻璃烧杯及表面皿；50mL离心管等。
1.2 标准溶液和主要试剂
单元素标准储备液：La、Ce、Pr、Nd、Sm、Eu、Gd、Tb、Dy、Ho、Er、Tm、Yb、Lu、Y、Sc、Ba浓度均为1000μg/mL （国家有色金属及电子材料分析测试中心）。
ICP-MS校准标准工作溶液：由标准储备液逐级稀释至20ng/mL。其中STD1为Sc、Y、La、Ce、Pr、Nd、Sm、Eu的混合溶液，各元素浓度均为20ng/mL，介质分别为5%硝酸和5%盐酸；STD2为Gd、Tb、Dy、Ho、Er、Tm、Yb、Lu的混合溶液，各元素浓度均为20ng/mL，介质分别为5%硝酸和5%盐酸。
干扰校正溶液：Ba、Ce、Pr、Nd单元素溶液，浓度均为1μg/mL，介质分别为5%硝酸和5%盐酸。
内标溶液：10ng/mL 的Rh、Re混合溶液，介质分别为5%硝酸和5%盐酸。内标溶液于测定时通过三通在线加入。
硝酸、盐酸、氢氟酸均为BV Ⅲ级；硫酸、高氯酸为优级纯；过氧化氢：MOS级；硫酸铵：分析纯；超纯水：电阻率大于18MΩ•cm。
1.3 样品采集及处理方法
实验用样品采集自南岭地区的六个离子吸附型稀土样品，编号分别为L03、L05、L14、L22、L20、L28。按照《岩石和矿石化学分析方法总则及一般规定》（GB/T 14505）的相关规定，加工样品的粒径应小于74μm，于105℃烘箱烘干2h，备用。
对样品分别开展混合酸（五酸）消解、盐酸消解、硝酸消解、硫酸铵浸提的前处理。其消解流程如下。
（1）混合酸消解（五酸）：称取0.1000g样品置于30mL聚四氟乙烯坩埚中，加入3mL盐酸、2mL硝酸、3mL氢氟酸、1mL高氯酸、1mL 50%硫酸，盖上坩埚盖，把坩埚放在控温电热板上，开启电热板，控制温度为130℃分解样品2h。洗净坩埚盖，将电热板升温至150℃，继续分解样品2h，然后将电热板升温至180℃蒸至高氯酸浓烟冒尽。取下坩埚，冷却至室温，用50%盐酸冲洗坩埚壁，再放在电热板上继续赶酸，直至溶液体积不再变化，重复操作此步骤两次。取下坩埚，加入10mL 50%盐酸，将坩埚放置在电热板上溶解盐类约15min，取下坩埚冷却至室温后，转移至50mL容量瓶中，用水稀释定容，摇匀备用。分取制备的溶液2.50mL，稀释至10.00mL，摇匀，此为混合酸消解样品待测溶液。
（2）硝酸消解：称取0.3000g样品置于100mL烧杯中，加入20mL 50%硝酸，加热至冒大气泡后，冷却至室温，用水定容至100mL。移取上述溶液10mL用5%硝酸定容至100mL；此为硝酸消解样品待测溶液。
（3）硝酸+过氧化氢消解：称取0.3000g样品置于100mL烧杯中，加入20mL 50%硝酸和0.5mL过氧化氢，加热至冒大气泡后，冷却至室温，用水定容至100mL。移取上述溶液10mL用5%硝酸定容至100mL；此为硝酸和过氧化氢消解样品待测溶液。
（4）盐酸+过氧化氢消解：称取0.3000g样品置于100mL烧杯中，加入20mL 50%盐酸和0.5mL过氧化氢，加热至冒大气泡后，冷却至室温，用水定容至100mL。移取上述溶液10mL用5%盐酸定容至100mL；此为盐酸和过氧化氢消解样品待测溶液。
（5）硫酸铵浸提：称取5.00g样品置于50mL离心管中，加入2.5%硫酸铵溶液40mL，摇匀后静置24h。取1mL上清液，加入5%硝酸9mL，此为硫酸铵浸提取样品待测溶液。
所有前处理方法的试剂空白与样品消解均同时进行。
1.4 样品测定
按照ICP-MS操作规程启动仪器，仪器点火后稳定30min以上。用仪器调试液进行仪器参数最佳化调试。按表1中的仪器工作条件测定溶液中的139La、140Ce、141Pr、142Nd、152Sm、153Eu、158Gd、159Tb、164Dy、165Ho、166Er、169Tm、174Yb、175Lu、89Y、45Sc共16种元素，同时测定空白溶液。以常用的干扰系数校正法来消除轻稀土对重稀土的干扰［17-21］。不同消解方法应选取与之基体相匹配的内标和校准溶液，以降低质谱测定中的基体效应。
混合酸溶采用离子型稀土矿石国家一级标准物质GBW07160、GBW07161进行质量监控；其他前处理方法通过加标试验对前处理过程进行监控。
2. 结果与讨论
2.1 样品前处理方法的评价
2.1.1 混合酸（五酸）消解方法
混合酸（五酸）消解法是基于经典四酸消解法的基础之上。通常情况下，酸溶法过程中引入氢氟酸是为了使样品完全分解，特别是硅酸盐结构的分解。但对于稀土样品，引入氢氟酸易生成难溶氟化物，导致稀土结果偏低。引入少量硫酸能有效地提升赶酸过程的温度，同时赶酸过程中溶液不会完全蒸干，既有利于难溶稀土氟化物的分解，也能尽量地避免稀土氟化物的沉淀。对于离子吸附型稀土矿，五酸敞开法可在一定条件下代替操作复杂的碱熔法［11］，用于测定样品中的稀土元素。本研究中采用GBW07160和GBW07161对五酸消解法进行监控，测定结果均在标准值范围内（表2）。因此，可将混合酸（五酸）消解的结果视为样品中“全相”稀土量。
表 2 GBW07160和GBW07161采用混合酸(五酸)消解测定结果(n=3)Table 2. Analytical results of GBW07160 and GBW07161 determined by open mixed acid digestion (n=3).稀土
元素GBW07160 GBW07161 五酸消解结果
（μg/g）标准值
（μg/g）五酸消解结果
（μg/g）标准值
（μg/g）Sc 6.22 5.67～6.98 8.29 7.69±0.59 Y 2383 2386±205 965 976±47 La 85.3 93.8±8.5 2271 2362±145 Ce 24.7 28.3±4.1 178 187±8.1 Pr 33.8 37.2 440 447±24.8 Nd 170 189±17 1568 1595±86 Sm 115 129±17 286 285±25.9 Eu 1.10 1.55±0.26 62.3 64.8±3.63 Gd 210 234 234 226±26 Tb 46.4 49.1±5.1 31.6 34.6±2.2 Dy 315 314±44 182 183±17 Ho 68.1 65.5±5.4 31.9 35.7±4.0 Er 207 192±26 90.1 96±9 Tm 26.8 27.7±3.1 12.3 13.2±1.1 Yb 184 193±26 78.1 87.8±11 Lu 24.9 26.7±2.6 11.24 12.0±0.88 2.1.2 盐酸、硝酸消解或硫酸铵浸提法
硝酸、盐酸消解处理或是硫酸铵浸提法，都只能将离子吸附型稀土样品中部分稀土元素溶出。50%的盐酸或硝酸能够溶出以离子状态吸附于黏土矿物或铁锰氧化物中的稀土元素，以及以氧化物、碳酸盐、磷酸盐等形式存在的稀土元素。但是对于硅酸盐结构中的稀土元素，其溶出效果有限。硫酸铵浸提法则只能溶出离子相稀土。呈离子状态被吸附于高岭土、长石、云母等黏土表面和颗粒间的稀土元素，在遇到化学性质更活泼的阳离子强电解质NH4+时能被其交换解吸而转入溶液。这部分能被离子交换浸出工艺交换出的稀土，即为离子相稀土［14］。
硝酸消解、硝酸+过氧化氢消解、盐酸+过氧化氢消解法和硫酸铵提取法，在称取样品后加入高浓度标准溶液，随后按1.3节方法处理样品，对前处理流程进行监控。各元素加入量及结果见表3，以样品L14和L28为例，加标回收率在80%～120%之间，满足实验分析要求。
表 3 加标试验回收率 (n=3)Table 3. Recovery rates of added standard tests (n=3).样品
L04硝酸消解 硝酸+双氧水消解 盐酸+双氧水消解 硫酸铵浸提 加标量
（μg）回收量
（μg）回收率
（%）加标量
（μg）回收量
（μg）回收率
（%）加标量
（μg）回收量
（μg）回收率
（%）加标量
（μg）回收量
（μg）回收率
（%）Sc 6.00 6.48 108 6.00 5.96 99.4 6.00 5.43 90.5 200 215.4 108 Y 6.00 6.50 108 6.00 5.72 95.3 6.00 6.19 103 200 183.2 91.6 La 6.00 6.84 114 6.00 6.86 114 6.00 5.99 100 200 212.9 106 Ce 6.00 6.29 105 6.00 6.53 109 6.00 6.60 110 200 208.1 104 Pr 6.00 5.75 96 6.00 6.08 101 6.00 7.12 119 200 192.0 96.0 Nd 6.00 5.66 94 6.00 5.92 98.7 6.00 6.40 107 200 177.9 89.0 Sm 6.00 6.43 107 6.00 6.57 109 6.00 6.49 108 200 203.4 102 Eu 6.00 6.14 102 6.00 6.28 105 6.00 6.18 103 200 200.6 100 Gd 1.50 1.44 96 1.50 1.70 113 1.50 1.61 107 80.0 80.4 100 Tb 1.50 1.62 108 1.50 1.68 112 1.50 1.63 109 80.0 80.2 100 Dy 1.50 1.45 96 1.50 1.67 111 1.50 1.64 109 80.0 80.1 100 Ho 1.50 1.61 108 1.50 1.61 107 1.50 1.57 105 80.0 82.8 103 Er 1.50 1.62 108 1.50 1.67 111 1.50 1.37 91.6 80.0 84.3 105 Tm 1.50 1.55 103 1.50 1.57 105 1.50 1.57 104 80.0 80.9 101 Yb 1.50 1.60 106 1.50 1.63 109 1.50 1.60 106 80.0 77.7 97.1 Lu 1.50 1.50 100 1.50 1.56 104 1.50 1.58 105 80.0 83.7 105 样品
L28硝酸消解 硝酸+双氧水消解 盐酸+双氧水消解 硫酸铵浸提 加标量
（μg）回收量
（μg）回收率
（%）加标量
（μg）回收量
（μg）回收率
（%）加标量
（μg）回收量
（μg）回收率
（%）加标量
（μg）回收量
（μg）回收率
（%）Sc 6.00 6.55 109 6.00 6.55 109 6.00 5.87 97.9 100 106.6 107 Y 6.00 6.10 102 6.00 6.27 104 6.00 5.92 98.6 100 105.1 105 La 6.00 6.76 113 6.00 6.88 115 6.00 4.93 82.1 100 107.6 108 Ce 6.00 6.18 103 6.00 6.56 109 6.00 6.14 102 100 106.8 107 Pr 6.00 6.16 103 6.00 6.10 102 6.00 6.68 111 100 110.9 111 Nd 6.00 6.13 102 6.00 6.19 103 6.00 5.04 84.0 100 116.6 117 Sm 6.00 6.55 109 6.00 6.45 107 6.00 5.95 99.2 100 98.9 98.9 Eu 6.00 6.35 106 6.00 6.31 105 6.00 6.17 103 100 118.4 118 Gd 1.50 1.64 109 1.50 1.79 119 1.50 1.75 116 4.00 4.09 102 Tb 1.50 1.61 108 1.50 1.54 103 1.50 1.56 104 4.00 3.88 96.9 Dy 1.50 1.44 96.0 1.50 1.70 114 1.50 1.57 104 4.00 4.31 108 Ho 1.50 1.61 107 1.50 1.57 105 1.50 1.55 103 4.00 4.17 104 Er 1.50 1.56 104 1.50 1.69 113 1.50 1.46 97.1 4.00 3.92 98.0 Tm 1.50 1.52 102 1.50 1.49 100 1.50 1.53 102 4.00 4.03 101 Yb 1.50 1.51 100 1.50 1.56 104 1.50 1.50 100 4.00 3.61 90.3 Lu 1.50 1.52 102 1.50 1.55 103 1.50 1.52 102 4.00 4.01 100 2.2 样品前处理方法对提取结果的影响
选取六个离子吸附型稀土矿样品，采用不同前处理方法测得各稀土元素总量见表4。不同前处理方法提取出的稀土量存在较大差异，其中混合酸（五酸）消解结果最高，硝酸消解、硝酸和过氧化氢消解、盐酸和过氧化氢消解结果相近，略低于混合酸（五酸）消解溶出稀土量，硫酸铵浸提溶出稀土量最低。用50%硝酸、盐酸等消解方法溶出的稀土量占混合酸（五酸）消解溶出稀土量（全相稀土）的71.7%～97.5%，硫酸铵浸提溶出的稀土量（离子相稀土）仅占全相稀土量的9.1%～75.5%（表4）。这与混合酸（五酸）消解溶出全相稀土，50%的盐酸或硝酸能溶出离子态以及以氧化物、碳酸盐、磷酸盐等形式存在的稀土，而硫酸铵浸提仅能溶出离子相稀土的原理一致。
表 4 不同前处理方法测得稀土总量与提取率 (n=3)Table 4. Content and extraction rates of REEs by different pretreatment methods (n=3).样品前处理方式 六个离子吸附型稀土样品稀土总量测定结果（μg/g） L20 L28 L22 L14 L05 L03 混合酸 208 344 310 511 771 152 硝酸 178 275 276 439 752 109 硝酸+过氧化氢 176 265 272 444 737 113 盐酸+过氧化氢 175 259 267 419 707 119 硫酸铵浸提 19.0 106 160 308 581 15.4 样品前处理方式 六个离子吸附型稀土样品稀土总量提取率（%） L20 L28 L22 L14 L05 L03 硝酸 85.6 79.9 89.0 85.9 97.5 71.7 硝酸+过氧化氢 84.6 77.0 87.7 86.9 95.6 74.3 盐酸+过氧化氢 84.1 75.3 86.1 82.0 91.7 78.3 硫酸铵浸提 9.1 30.8 51.7 60.3 75.5 10.2 注：提取率为各种方法提取稀土结果与混合酸（五酸）消解结果（全相稀土）相比的百分数。 2.3 稀土元素特性及赋存状态对提取结果的影响
不同消解方法结果的差异与样品中稀土元素的赋存状态密切相关，混合酸消解能够将样品结构彻底破坏，样品中所有的稀土元素都能被溶出。受原岩化学成分的影响，不同矿区风化壳矿石的化学成分不完全相同，但有许多共同点。稀土元素在风化壳各层发生分异-富集，原岩在风化后仍有一部分稀土以矿物相形式赋存［14］，离子相的稀土的含量与风化壳各层的风化程度、矿物组成等因素密切相关［22-24］，风化壳不同部位离子相稀土含量占比不尽相同。盐酸或硝酸能够溶出以离子状态吸附于黏土矿物或铁锰氧化物中的稀土元素，以及碳酸盐、磷酸盐等形式存在的稀土元素。但是，还有部分稀土元素稳定存在于不能被硝酸和盐酸完全溶解的硅酸盐矿物晶格中。而硫酸铵浸提只能将样品中离子相稀土溶出，因此，盐酸和硝酸的消解结果低于全相稀土的量，高于硫酸铵浸提法。
实验结果（图1）显示，硝酸和盐酸消解处理中，Sc的提取率也远低于稀土元素总量的提取率，硫酸铵浸提则不能将钪（Sc）溶出。这是由于Sc3+的离子半径（0.075nm）明显小于镧系元素离子半径（0.106～0.085nm），却与Mg2+（0.072nm）和Fe3+（0.078nm）具有相似的离子半径，因而能以类质同象的形式替换Mg2+、Fe3+离子进入多种造岩矿物的晶格中［25-26］。因此，Sc元素几乎不能被NH4+以离子交换的形式置换到溶液中，而存在于造岩矿物晶格中的Sc也只能被硝酸或者盐酸部分溶出。
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图 1 不同样品前处理方法Sc、Ce和稀土总量(∑REE)的提取率Figure 1. Extraction rates of Sc, Ce and ∑REE by different pretreatment methods.铈（Ce）是地壳中丰度最高的稀土元素，Ce作为变价元素，其含量变化受氧化还原条件等多种因素影响［27］。自然界中的Ce通常呈Ce3+和Ce4+两种价态，Ce3+极易氧化成Ce4+，以胶态相Ce（OH）4或矿物相方铈矿（CeO2）的形式而滞留于原地［28-29］。Ce与其他稀土元素不同的富集-分异特性也导致在硫酸铵浸提中，Ce元素的提取率与其他稀土元素提取率、轻稀土总量提取率以及稀土总量提取率之间不存在相关性（图1和图2）。
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图 2 不同样品前处理方法轻稀土元素(除Ce外)提取率Figure 2. Extraction rates of LREEs by different pretreatment methods.比较不同消解方法中稀土元素的提取率可以发现，离子半径相近的稀土元素，提取率也往往相近（图2和图3）。钇（Y）与镧系元素具有很强的化学亲和性，与钬（Ho）也具有相似的离子半径（Y3+ 0.088nm，Ho3+ 0.089nm），因此将Y划为重稀土一组［30］。从图3也可以发现，在同一种前处理方法中，Y和Ho具有相近的提取率。大部分情况下轻稀土的提取率高于重稀土，轻稀土单元素提取率与轻稀土总量（除Ce以外）提取率（图2）、重稀土单元素提取率与重稀土总量提取率正相关（图3）。
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图 3 不同样品前处理方法重稀土元素提取率Figure 3. Extraction rates of HREEs by different pretreatment methods.3. 结论
本文初步讨论了不同前处理方法溶出风化壳淋积型稀土矿中稀土元素的差异及影响因素，能够为进一步研究风化壳淋积型稀土矿中稀土元素提取方法提供参考依据。混合酸（五酸）消解能够提取出风化壳淋积型稀土矿样品中的全相稀土，可用于评价风化壳淋积型稀土矿中稀土总量。硝酸消解、硝酸和过氧化氢消解、盐酸和过氧化氢消解能够溶出离子相稀土，以及以氧化物、碳酸盐、磷酸盐等形式存在的稀土元素，对于硅酸盐结构中的稀土元素，不能完全溶出，因此，该方法适用于评价样品中以离子态、氧化物、碳酸盐、磷酸盐等形式存在稀土元素的含量。硫酸铵浸提则能提取出离子相稀土，可用于评价风化壳淋积型稀土矿中离子态稀土含量。
稀土元素的提取率，受稀土元素化学特性和赋存状态的影响较大。由于Sc3+的离子半径明显小于其他稀土元素，能以类质同象的形式进入多种造岩矿物的晶格中，从而导致硫酸铵浸提不能将Sc溶出。Ce元素与其他稀土元素不同的富集-分异特性，也使得其在硫酸铵浸提中提取率与其他轻稀土元素不一致。具有相近离子半径的稀土元素，在相同的前处理中往往提取效率也相近。
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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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[1] 杜新强,方敏,冶雪艳. 地下水“三氮”污染来源及其识别方法研究进展[J]. 环境科学, 2018, 39(11): 5266−5275. Du X Q,Fang M,Ye X Y. Research progress on the sources of inorganic nitrogen pollution in groundwater and identification methods[J]. Environmental Science, 2018, 39(11): 5266−5275.
[2] 张涵,李奇翎,郭珊珊,等. 成都平原典型区地下水污染时空异质性及污染源分析[J]. 环境科学学报, 2019, 39(10): 3516−3527. Zhang H,Li Q L,Guo S S,et al. Spatial temporal heterogeneity and pollution sources of groundwater pollution in typical area of Chengdu Plain[J]. Acta Scientiae Circumstantiae, 2019, 39(10): 3516−3527.
[3] 李谨丞,曹文庚,潘登,等. 黄河冲积扇平原浅层地下水中氮循环对砷迁移富集的影响[J]. 岩矿测试, 2022, 41(1): 120−132. Li J C,Cao W G,Pan D,et al. Influences of nitrogen cycle on arsenic enrichment in shallow groundwater from the Yellow River Alluvial Fan Plain[J]. Rock and Mineral Analysis, 2022, 41(1): 120−132.
[4] 付坤. 超深层地下水中“三氮”的迁移转化规律研究[D]. 焦作: 河南理工大学, 2018: 49−50. Fu K. Study on the migration and trans formation of NH4 +, NO2 −, and NO3 − in super deep groundwater[D]. Jiaozuo: Henan Polytechnic University, 2018: 49−50.
[5] 张晓沛. 再生水回灌区地下水水化学特征及三氮迁移模拟[D]. 北京: 中国地质大学（北京）, 2017: 58−59. Zhang X P. The water chemical characteristics of groundwater and the simulation of nitrogen migration in the irrigation area of reclaimed water[D]. Beijing: China University of Geosciences （Beijing）, 2017: 58−59.
[6] 傅雪梅. 基于水化学和同位素的地下水硝酸盐源解析研究[D]. 上海: 上海大学, 2019. Fu X M. Groundwater nitrate source identification based on hydrochemical and isotopes[D]. Shanghai: Shanghai University, 2019.
[7] 常文博,李凤,张媛媛,等. 元素分析-同位素比值质谱法测量海洋沉积物中有机碳和氮稳定同位素组成的实验室间比对研究[J]. 岩矿测试, 2020, 39(4): 535−545. doi: 10.15898/j.cnki.11-2131/td.202003090027 Chang W B,Li F,Zhang Y Y,et al. Inter-laboratory comparison of measuring organic carbon and stable nitrogen isotopes in marine sediments by elemental analysis-isotope ratio mass spectrometry[J]. Rock and Mineral Analysis, 2020, 39(4): 535−545. doi: 10.15898/j.cnki.11-2131/td.202003090027
[8] 张涵,杜昕宇,高菲,等. 联合PMF模型与稳定同位素的地下水污染溯源[J]. 环境科学, 2022, 43(8): 4054−4063. Zhang H,Du X Y,Gao F,et al. Groundwater pollution source identification by combination of PMF model and stable isotope technology[J]. Environmental Science, 2022, 43(8): 4054−4063.
[9] 刘楠涛,吴飞,袁巍,等. 长江与黄河源丰水期地表水中汞的分布特征、赋存形态及来源解析[J]. 环境科学, 2022, 43(11): 5064−5072. doi: 10.13227/j.hjkx.202201143 Liu N T,Wu F,Yuan W,et al. Mercury speciation,distribution,and potential sources in surface waters of the Yangtze and Yellow River source basins of Tibetan Plateau during wet season[J]. Environmental Science, 2022, 43(11): 5064−5072. doi: 10.13227/j.hjkx.202201143
[10] 陈盟,潘泳兴,黄奕翔,等. 阳朔典型铅锌矿区流域土壤重金属空间分布特征及来源解析[J]. 环境科学, 2022, 43(10): 4545−4555. doi: 10.13227/j.hjkx.202201127 Chen M,Pan Y X,Huang Y X,et al. Spatial distribution and sources of heavy metals in soil of a typical lead-zinc mining area,Yangshuo[J]. Environmental Science, 2022, 43(10): 4545−4555. doi: 10.13227/j.hjkx.202201127
[11] 许燕颖,刘友存,张军,等. 赣江上游典型流域水体三氮及重金属空间分布特征与风险评价[J]. 地球与环境, 2020, 48(5): 574−583. doi: 10.14050/j.cnki.1672-9250.2020.48.070 Xu Y Y,Liu Y C,Zhang J,et al. Spatial distribution and risk assessment of nitrogen and heavy metals in typical watershed of the upper reaches of Ganjiang River[J]. Earth and Environment, 2020, 48(5): 574−583. doi: 10.14050/j.cnki.1672-9250.2020.48.070
[12] 吴昊,朱红霞,袁懋,等. 气相分子吸收光谱法测定土壤中铵态氮和硝态氮的含量[J]. 岩矿测试, 2021, 40(1): 165−171. Wu H,Zhu H X,Yuan M,et al. Determination of ammonium nitrogen and nitrate nitrogen in soil by gas phase molecular absorption spectrometry[J]. Rock and Mineral Analysis, 2021, 40(1): 165−171.
[13] 蓝天杉. 北京通州区浅层地下水中“三氮”迁移转化与弱透水层阻滞作用研究[D]. 长春: 吉林大学, 2019. Lan T S. The transportation and transformation of “Three Nitrogen” in shallow groundwater and the retarding effect of aquitard in Tongzhou, Beijing[D]. Changchun: Jilin University, 2019.
[14] 田辉. 基于SWAT与Visual Modflow的海伦市水资源模拟与合理配置研究[D]. 长春: 吉林大学, 2020. Tian H. Research on water resources simulation and reasonable allocation of Hailun City based on SWAT and Visual Modflow[D]. Changchun: Jilin University, 2020.
[15] 曹文庚,杨会峰,南天,等. 南水北调中线受水区保定平原地下水质量演变预测研究[J]. 水利学报, 2020, 51(8): 924−935. Cao W G,Yang H F,Nan T,et al. Prediction of groundwater quality evolution in the Baoding Plain of the SNWDP benefited regions[J]. Journal of Hydraulic of Engineering, 2020, 51(8): 924−935.
[16] 雷正国,陶月赞. 地下水水源地水质评价方法探讨[J]. 节水灌溉, 2019(8): 80−83. Lei Z G,Tao Y Z. Discussion on water quality assessment method for groundwater source[J]. Water Saving Irrigation, 2019(8): 80−83.
[17] 吴娟娟,卞建民,万罕立,等. 松嫩平原地下水氮污染健康风险评估[J]. 中国环境科学, 2019, 39(8): 3493−3500. Wu J J,Bian J M,Wan H L,et al. Health risk assessment of groundwater nitrogen pollution in Songlnen Plain[J]. China Environmental Science, 2019, 39(8): 3493−3500.
[18] 李天宇,董宏志,孔庆轩,等. 松嫩平原哈尔滨地区地下水环境背景值分析[J]. 水文, 2016, 36(3): 24−28,74. Li T Y,Dong H Z,Kong Q X,et al. Background values of groundwater environment in Harbin area of Songnen Plain[J]. Journal of China Hydrology, 2016, 36(3): 24−28,74.
[19] 李圣品,李文鹏,殷秀兰,等. 全国地下水质分布及变化特征[J]. 水文地质工程地质, 2019, 46(6): 1−8. doi: 10.16030/j.cnki.issn.1000-3665.2019.06.01 Li S P,Li W P,Yin X L,et al. Distribution and evolution characteristics of national groundwater quality from 2013 to 2017[J]. Hydrogeology & Engineering Geology, 2019, 46(6): 1−8. doi: 10.16030/j.cnki.issn.1000-3665.2019.06.01
[20] 孙小淇. 武进区地表水水质分布特征及其氮污染来源解析研究[D]. 上海: 华东理工大学, 2020: 19-24. Sun X Q. Investigations on distribution of water quality and sources tracing of nitrogen pollution in Wujin District surface water[D]. Shanghai: East China University of Science and Technology, 2020: 19-24.
[21] 庞园,李志威,张明珠. 广花盆地地下水三氮时空分布特征及影响因素分析[J]. 生态环境学报, 2018, 27(5): 916−925. doi: 10.16258/j.cnki.1674-5906.2018.05.017 Pang Y,Li Z W,Zhang M Z. Analysis of spatial-temporal distribution and influencing factors of three-nitrogen in groundwater of Guanghua Basin[J]. Ecology and Environmental Sciences, 2018, 27(5): 916−925. doi: 10.16258/j.cnki.1674-5906.2018.05.017
[22] 左朝晖. 北京东北部平原区地下水氮素污染源解析及其贡献率研究[D]. 石家庄: 河北地质大学, 2020. Zuo Z H. Source analysis and contribution rate of groundwater nitrogen pollution in the plain area of Northeast Beijing[D]. Shijiazhuang: Hebei GEO University, 2020.
[23] 张鑫. 地表水、地下水硝酸盐时空变化及其来源分析[D]. 西安: 西北大学, 2021. Zhang X. Spatiotemporal variation and source analysis of nitrate in surface water and groundwater: Guanzhong section of Wei River Basin[D]. Xi’an: Northwest University, 2021.
[24] 吕晓立,刘景涛,朱亮,等. 兰州市地下水中“三氮”污染特征及成因[J]. 干旱区资源与环境, 2019, 33(1): 95−100. doi: 10.13448/j.cnki.jalre.2019.015 Lyu X L,Liu J T,Zhu L,et al. Distribution and source of nitrogen pollution in groundwater of Lanzhou City[J]. Journal of Arid Land Resources and Environment, 2019, 33(1): 95−100. doi: 10.13448/j.cnki.jalre.2019.015
[25] 李桂芳,杨恒,叶远行,等. 高原湖泊周边浅层地下水:氮素时空分布及驱动因素[J]. 环境科学, 2022, 43(6): 3027−3036. doi: 10.13227/j.hjkx.202109195 Li G F,Yang H,Ye Y X,et al. Shallow groundwater around plateau lakes:Spatiotemporal distribution of nitrogen and its driving factors[J]. Environmental Science, 2022, 43(6): 3027−3036. doi: 10.13227/j.hjkx.202109195
[26] Viktor Y, Еlena V, Valentin R. Influence of ammonium nitrogen on the treatment efficiency of underground water at iron removal stations[J]. Groundwater for Sustainable Development, 2023(22): 100943.
[27] Ashu R, Kiran P, Ramet M, et al. Hydrochemical characteristics and potential health risks of nitrate, fluoride, and uranium in Kota district, Rajasthan, India[J]. Environmental Science and Pollution Research, 2023: 1−21.
[28] 何宝南,何江涛,孙继朝,等. 区域地下水污染综合评价研究现状与建议[J]. 地学前缘, 2022, 29(3): 51−63. doi: 10.13745/j.esf.sf.2022.1.29 He B N,He J T,Sun J Z,et al. Comprehensive evaluation of regional groundwater pollution:Research status and suggestions[J]. Earth Science Frontiers, 2022, 29(3): 51−63. doi: 10.13745/j.esf.sf.2022.1.29
[29] 韩彬,林法祥,丁宇,等. 海州湾近岸海域水质状况调查与风险评价[J]. 岩矿测试, 2019, 38(4): 429−437. doi: 10.15898/j.cnki.11-2131/td.201806190073 Han B,Lin F X,Ding Y,et al. Quality survey and risk assessment of the coastal waters of Haizhou Bay[J]. Rock and Mineral Analysis, 2019, 38(4): 429−437. doi: 10.15898/j.cnki.11-2131/td.201806190073
[30] 罗飞,巴俊杰,苏春田,等. 武水河上游区域土壤重金属污染风险及来源分析[J]. 岩矿测试, 2019, 38(2): 195−203. doi: 10.15898/j.cnki.11-2131/td.201806040069 Luo F,Ba J J,Su C T,at al. Contaminant assessment and sources analysis of heavy metals in soils from the upper reaches of the Wushui River[J]. Rock and Mineral Analysis, 2019, 38(2): 195−203. doi: 10.15898/j.cnki.11-2131/td.201806040069
[31] 郭涛,陈海洋,滕彦国,等. 东北典型农产区流域地下水水质评价与污染源识别[J]. 北京师范大学学报(自然科学版), 2017, 53(3): 316−322. Guo T,Chen H Y,Teng Y G,et al. Pollution assessment and source identification of basin groundwater in typical agricultural areas in Northeast China[J]. Journal of Beijing Normal University (Natural Science), 2017, 53(3): 316−322.
[32] 洪慧,李娟,汪洋,等. 基于统计学方法的地下水水质评价与成因分析——以齐齐哈尔市为例[J]. 环境工程技术学报, 2019, 9(4): 431−439. doi: 10.12153/j.issn.1674-991X.2019.04.160 Hong H,Li J,Wang Y,et al. Groundwater quality evaluation and causes analysis based on statistical methods:Taking Qiqihar City as an example[J]. Journal of Environmental Engineering Technology, 2019, 9(4): 431−439. doi: 10.12153/j.issn.1674-991X.2019.04.160
[33] 马小雪,龚畅,郭加汛,等. 长江下游快速城市化地区水污染特征及源解析:以秦淮河流域为例[J]. 环境科学, 2021, 42(7): 3291−3303. doi: 10.13227/j.hjkx.202011184 Ma X X,Gong C,Guo J X,et al. Water pollution characteristics and source apportionment in rapid urbanization region of the lower Yangtze River:Considering the Qinghai River catchment[J]. Environmental Science, 2021, 42(7): 3291−3303. doi: 10.13227/j.hjkx.202011184
[34] Guo W J, Zhang Z Y, Wang H, et al. Exposure characteristics of antimony and coexisting arsenic from multi-path exposure in typical antimony mine area[J]. Journal of Environmental Management, 2021: 112493.
[35] Zhu Y, Yang J, Wang L, et al. Factors influencing the uptake and speciation transformation of antimony in the soil-plant system, and the redistribution and toxicity of antimony in plants[J]. Science of the Total Environment, 2020: 140232.
[36] Wang Y Z, Duan X J, Wang L. Spatial distribution and source analysis of heavy metals in soils influenced by industrial enterprise distribution: Case study in Jiangsu Province[J]. Science of the Total Environment, 2020: 134953.
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