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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中国矿产资源丰富，类型繁多，其中镍矿石、铅矿石和锌矿石等均为金属冶炼的重要原材料，在冶金、化工、机械、电气、医药、军事等很多领域中都具有广泛的应用，前景良好[1-2]。硫作为矿石中常见的有害杂质元素，在矿石中主要以硫化物形式存在[3-4]，硫含量的高低会直接影响金属材料的力学性能、抗腐蚀性能及耐磨性等，限制了矿石原料的应用范围。因此，准确、快速测定矿石中的硫含量具有重要意义。
应用高频红外碳硫仪测定硫，具有方法操作简单、检出限低、测定范围广[5-8]等优点，能极大地提高样品检测效率[9]，已被广泛应用于地质样品中碳、硫的检测[10-13]。此外，国家标准方法、行业标准方法中也规定了相关方法测定碳硫含量的应用，如《铁矿石：碳和硫含量的测定高频燃烧红外吸收法》(GB/T 6730.61—2005)规定了铁矿石中碳、硫含量范围分别为0.01%~2.5%和0.001%~2.0%的测定方法；《镍化学分析方法：硫量的测定高频感应炉燃烧红外吸收法》(GB/T 8647.8—2006)规定了镍矿石中硫含量范围在0.0010%~0.050%的测定方法；《区域地球化学样品分析方法第25部分：碳量测定燃烧-红外吸收光谱法》(DZ/T 0279.25—2016)规定了水系沉积物和土壤中碳含量范围在0.01%~10%的测定方法等。但这些标准方法的检测范围有限，多适用于低含量硫的测定。在此基础上，大量学者采用高频燃烧-红外吸收法开展了高含量硫的检测方法研究[14-19]。杨小莉等[15]采用与实际样品化学性质相似的铜铅锌矿石标准物质绘制标准曲线，建立了高频燃烧红外吸收法测定铜铅锌矿石中硫含量跨度范围较大的(质量分数为0.106%~10.76%)分析方法，但该方法检测池单一，仅适用于硫含量小于11%的矿石检测；周富强等[18]采用高频红外吸收法，以硫酸钾建立标准曲线，利用高纯二氧化硅粉对高含量硫的样品进行稀释，建立了矿产品中硫质量分数为0.01%~53%的测定方法，该方法虽然测定范围广，但标准曲线分段过多，对于实际检测中未知硫含量的样品，加大了检测工作量，增加了检测成本。
针对高频红外碳硫仪测定硫分析方法中检测池单一、难以准确测定高含量硫及标准曲线分段过多而降低检测效率等问题，本文在之前实验的基础上，通过高低硫检测池切换的方法，采用高含量硫和低含量硫两条检测曲线相结合的方式，进行了样品称样量、纯铁助熔剂添加量及分析时间等测定条件对硫含量影响的系列研究，建立了高频红外碳硫仪快速测定镍铅锌矿石中硫含量的检测方法，并通过国家标准物质验证了方法的精密度及准确度，将测定结果与燃烧碘量法进行比较，佐证了方法的准确度。
1. 实验部分
1.1 仪器及工作条件
HCS-808型高频红外碳硫分析仪(四川赛恩斯仪器有限公司)，仪器主要工作参数为：供压电压220V±5%，50Hz；分析氧气压力0.08MPa，分析氧气流速2.8L/min；动力氧气压力0.5MPa，动力氧气流速1.8L/min；室内温度15~30℃，相对湿度＜70%。
BS124S型电子天平(赛多利斯科学仪器有限公司)，精度为0.0001g；SGM2880A型人工智能箱式电阻炉(洛阳市西格马仪器制造有限公司)；101-1AB型电热鼓风干燥箱(天津市泰斯特仪器有限公司)。
碳硫仪专用瓷坩埚(型号Φ25mm×25mm，四川赛恩斯仪器有限公司)。高效变色干燥剂、碱石棉、无水高氯酸镁；高纯氧气(纯度不小于99.5%)。
纯铁助熔剂：国家工业标准产品，铁含量大于99.8%，硫含量小于0.0005%(四川赛恩斯仪器有限公司)；纯钨助熔剂：国家工业标准产品，钨含量不小于99.95%，硫含量不大于0.0003%(四川赛恩斯仪器有限公司)。
1.2 实验样品
镍矿石与精矿成分分析标准物质：GBW07145(硫含量标准值0.74%±0.06%)、GBW07146(硫含量标准值1.53%±0.06%)、GBW07147(硫含量标准值3.78%±0.07%)、GBW07148(硫含量标准值18.14%±0.41%)，均为中国地质科学院地球物理地球化学勘查研究所研制。
铅锌矿石成分分析标准物质：GBW(E)070077(硫含量标准值2.90%)、GBW(E)070080(硫含量标准值15.62%)，均为陕西省地质矿产实验研究所研制；GBW(E)070026(硫含量标准值5.87%±0.07%)，原地质矿产部河南省中心实验室研制。
铅矿石成分分析标准物质：GBW07172(硫含量标准值10.26%±0.19%)，西藏自治区地质矿产勘查开发局中心实验室研制。
锌精矿成分分析标准物质：GBW07168(硫含量标准值32.0%±0.3%)，中国地质科学院地球物理地球化学勘查研究所研制。
多金属矿石成分分析标准物质：GBW07163(硫含量标准值6.74%±0.11%)，中国地质科学院地球物理地球化学勘查研究所研制。
富铅锌矿石成分分析标准物质：GBW07165(硫含量标准值29.0%±0.4%)，中国地质科学院地球物理地球化学勘查研究所研制。
实际矿石样品：均来自青海某矿业公司委托的检测样品，样品粒度均不大于0.074mm(200目)。
1.3 实验方法
1.3.1 样品硫含量测定步骤
前处理：将瓷坩埚放入1200℃箱式电阻炉中灼烧4h，去除瓷坩埚自身硫含量及水分含量对样品测定结果的影响，待冷却至室温后置于干燥器中备用。将待测样品放入105℃恒温干燥箱中烘烤2h，再冷却至室温，置于干燥器中备用。
检测步骤：称取0.50g纯铁助熔剂于烘干的瓷坩埚中，再称取0.0400g烘好的待测样品，均匀地加入纯钨助熔剂2.0g，在1.1节仪器工作条件下，开机后示波器信号约15~20s后稳定，因此设置清洗时间20s，加热时间20s，分析时间45s，进行待测样品硫含量检测。
1.3.2 标准曲线的绘制
仪器使用前需要用不同含量的标准物质进行校正，每种标准物质重复分析2~3次，其分析结果重复性应符合国家允许的误差要求后才能进行曲线校正[6]，且使用不同浓度的标准物质绘制曲线可以减少不同含量待测样品的误差，使用相同基体的标准物质可以提高检测的准确性，采用多点校正的方式测量结果更佳且测量范围更广[20-21]。
实验先选用高硫池，采用系列国家标准物质GBW(E)070077、GBW07147、GBW(E)070026、GBW07172、GBW07148、GBW07168(硫标准值依次为2.90%、3.78%、5.87%、10.26%、18.14%、32.0%)，建立标准曲线y1=1.0005x1-0.0027(R2=0.9997)，测定范围为2.9%~32.0%；再选用低硫池，采用系列国家标准物质GBW07145、GBW07146、GBW(E)070077、GBW07147、GBW(E)070026(硫标准值依次为0.74%、1.53%、2.90%、3.78%、5.87%)，建立标准曲线y2=0.9885x2+0.0238(R2=0.9995)，测定范围为0.74%~5.87%。校正好曲线检测样品时，通过设置智能高低硫检测池切换模式来扩大样品测定范围，并将切换值设置为3.0%，即：当待测样品中硫含量≥3.0%时，仪器自动选择高硫池测定结果；当硫含量＜3.0%时，仪器自动选择低硫池测定结果，智能切换模式下硫含量测定范围扩大至0.74%~32.0%。
2. 结果与讨论
2.1 称样量对硫含量结果的影响
矿石属于低电磁感应样品，采用高频燃烧-红外吸收法检测时需要加导电、导磁的助熔材料。称样量的大小直接影响着助熔剂添加量和样品分析时间的选择，也是决定样品是否充分燃烧、转化等的重要因素。称样量过小，样品代表性不足，测定结果稳定性差；称样量过大，样品燃烧不完全，导致测定结果偏低[15]。因此，选择合适的称样量是保证样品检测结果准确度的主要因素之一。
采用标准物质GBW07146(硫标准值为1.53%)、GBW07172(硫标准值为10.26%)和GBW07168(硫标准值为32.0%)进行试验。分别称取样品0.0200、0.0300、0.0400、0.0500、0.0700和0.1000g，每个样品平行测定3次求平均值，绘制不同称样量对硫测定结果的影响曲线。从图 1分析结果可得，当称样量小于0.0300g或大于0.0700g时，三个样品的硫含量测定值均严重偏低；当称样量为0.0300g时，硫含量较低的GBW07146其测定值仍然偏低，超出误差范围，GBW07172硫含量测定值则略偏低，但在误差允许范围，而硫含量较高的GBW07168其测定值则与标准值相近；当称样量为0.0500g时，GBW07146和GBW07172两个样品的硫含量测定值与标准值最接近，而硫含量较高的GBW07168测定值偏低，超出误差范围。这是因为样品在燃烧过程中产生的粉尘及水蒸气等均会对SO2产生微弱的吸附作用，随着样品数量的增加，堆积的粉尘量逐渐增多。每个样品分析时，由于炉膛中碱性氧化物和水蒸汽的浓度无法一致，导致吸附作用力大小不一[6]。当称样量过小时，样品检测过程中释放的SO2量较少，即使少量的吸附作用，也会导致样品测定结果不稳定，误差大；随着称样量的逐渐增加，微量的吸附作用对样品检测稳定性影响变小，对硫含量较高的样品影响可忽略，而低硫含量样品的检测结果则依然会受到影响；当称样量过多时，由于每次检测助熔剂添加量为固定量，则导致样品不能充分燃烧，测定结果偏低，尤其是高硫含量样品在燃烧过程中还会出现较多粉尘。因此，在保证样品检测结果准确度高、稳定性好的前提下，综合考虑样品检测成本等因素，本文确定称样量为0.0400g。
2.2 纯铁助熔剂添加量的选择
助熔剂在燃烧过程中，有氧化放热作用，有助于样品燃烧温度的提高。助熔剂如果不合适，容易造成每次燃烧达到的最高温度不一样，从而使样品中的硫转化率不一样，造成重复性不好。矿产品试样的导磁导电性较差，单独用一种助熔剂时，存在板电流变化较大、信号较低、熔融状态较差、易飞溅、释放效果不好等问题[18]。因此，选择合适的助熔剂不仅可以稀释样品，促进样品燃烧，使之完全释放出硫，还可以增加样品的导磁性，有效提高测定结果的准确性与稳定性。纯铁属于高电磁感应物质，通过高频感应可产生较大的涡电流和较多的焦耳热，迅速提高炉温，使样品完全燃烧，且与样品氧化物熔融时形成互溶的流体，使燃烧过程更稳定。钨的熔点高(熔点3382℃)、密度大，既可以提高样品的热容量，增加热量助熔，又可以防止纯铁燃烧产生飞溅，且WO3的生成有利于SO2释放[10]，此外WO3的逸出，增加了硫的扩散速度，使硫充分氧化，挥发的WO3在700~800℃又转化为固相，覆盖在管道中尚存的Fe2O3上，阻止了SO2催化转为SO3，防止了管道对硫的吸附，保证结果的可靠性。
纯铁燃烧时易产生飞溅，钨可以作为很好的覆盖。在参考前人成果[22-28]的基础上，为提高结果稳定性，确保在不同含量的铁助熔剂中样品燃烧过程不产生飞溅，实验中选择在固定钨粒2.0g的条件下[23-24]，分别称取0.0400g标准物质GBW07146和GBW07168，分析不同纯铁加入量对测定值的影响，每个样品测定3次取平均值，测定结果见表 1。
表 1 纯铁加入量对硫测量值的影响Table 1. Effect of pure iron addition on the sulfur detection纯铁加入量(g) GBW07146硫含量 GBW07168硫含量 标准值(%) 测定值(%) 标准值(%) 测定值(%) 0.20 1.44 31.51 0.35 1.47 31.78 0.50 1.53±0.06 1.52 32.0±0.3 32.04 0.60 1.54 31.88 0.75 1.48 31.75 从表 1结果可以看出，当纯铁加入量为0.20g时，样品的硫含量测定值较标准值严重偏低，超出允许误差范围，这是因为铁量少，样品无法充分燃烧；随着铁加入量的增加，硫含量测定值也变大了，但较标准值仍偏低，不过都在误差允许范围内；当铁的加入量增大至0.50g时，两个不同硫含量样品的测定值均与各自标准值最接近；而当铁加入量继续增大时，硫含量测定值又开始降低，这是因为铁含量过高导致了样品燃烧飞溅，且产生的粉尘量增加，此外铁屑的硫空白也会影响样品的测定结果。综上所述，当纯铁加入量为0.50g时，样品熔融较好，且燃烧无飞溅，仅产生极少量粉尘，燃烧效果最佳，硫含量测试值与标准值结果最接近。考虑到样品中的硫含量范围跨度较大，因此选择纯铁助熔剂添加量为0.50g，纯钨助熔剂添加量为2.0g，可保证不同硫含量的样品均充分燃烧，且稳定性好。
2.3 样品分析时间的选择
分析时间是决定硫释放曲线形态的重要因素[29]，仪器分析时间的长短对样品中硫含量测定值的影响也很明显[30]。且矿石中大部分样品的硫含量都较高，分析时应尽量控制好分析时间，选择合适的积分参数，使释放曲线一直呈现正态分布的形态，保证样品在充分燃烧的同时，也要考虑尽量减少拖尾带来的影响。
选择实验优化好的称样量和助熔剂添加量，改变样品燃烧的分析时间，对GBW07147、GBW07172和GBW07168进行测定。从表 2测定结果可见，分析时间小于35s时，样品硫含量测定结果较标准值严重偏低，这是因为时间过短，样品燃烧不充分，硫释放不完全，从硫曲线形态图中也可以明显看出曲线积分不完全；分析时间为40s时，硫含量较高的GBW07168样品的测定值偏低，样品仍未能充分燃烧；分析时间增加至45s时，样品测定值均与标准值最接近；当分析时间继续增大，红外吸收峰的积分面积值增加，导致样品测定值均偏高，但此时样品中的硫已经释放完全，因此结果在误差范围内。综合考虑检测成本及分析效率等因素，实验确定分析时间为45s，样品硫释放曲线图均表现出平滑、完整。
表 2 不同分析时间下硫含量测定结果Table 2. Results of sulfur content in different analysis time分析时间(s) GBW07147硫含量 GBW07172硫含量 GBW07168硫含量 标准值(%) 测定值(%) 标准值(%) 测定值(%) 标准值(%) 测定值(%) 30 3.78±0.07 3.65 10.26±0.19 9.52 32.0±0.3 28.05 35 3.73 9.83 30.21 40 3.82 10.40 31.57 45 3.78 10.28 32.04 50 3.87 10.60 32.21 55 3.89 10.61 32.28 2.4 方法检出限、精密度及准确度验证
取经过预处理灼烧过的空白坩埚12个，按照HJ 168—2010的要求，采用本实验优化的分析方法连续测定硫含量最低的标准样品GBW07145(硫含量标准值0.74%)，平行测定12次，硫含量的测定值分别为0.675%、0.680%、0.695%、0.798%、0.675%、0.798%、0.799%、0.801%、0.803%、0.798%、0.680%、0.804%，按测定结果的3倍标准偏差计算方法检出限为0.185%，以4倍方法检出限计算方法测量下限[24]为0.739%。
选择标准物质GBW(E)070077、GBW07163、GBW07172、GBW(E)070080、GBW07165和GBW07168，按照本实验优化的分析方法进行硫的精密度和准确度实验，每个样品连续测定11次，根据《地质矿产实验室测试质量管理规范》(DZ/T 0130—2006)要求，依照如下公式计算相对误差允许限(YB)：
$$ \mathrm{Y}_{\mathrm{B}}=\frac{1}{\sqrt{2}} C \times\left(14.37 \times X_0^{-0.1263}-7.659\right) $$ 式中：C为硫组分重复分析相对偏差允许限系数，其值为0.67；X0为标准物质中硫组分的标准值。从表 3检测结果分析可得，测定结果的相对标准偏差(RSD)分别为2.04%、1.04%、0.82%、1.25%、0.73%和0.50%，相对误差(RE)均小于2%，在相对误差允许限内，说明该方法的精密度良好，测定结果准确可靠，满足DZ/T 0130—2006质量管理规范的要求。与周富强等[18]的方法相比，本文将高低两条校正曲线相结合，固定了合适的称样量，减少了样品检测过程因切换分析方法引起的测量误差，提高了样品测定结果准确度，降低了测定结果的相对标准偏差(RSD)，文献中RSD小于2.6%[18]，本文中RSD均小于2.04%。
表 3 方法精密度和准确度Table 3. Precision and accuracy tests of the method标准物质编号 硫含量标准值(%) 硫含量测定值(%) 硫含量测定平均值(%) RSD (%) RE (%) YB (%) GBW(E)070077 2.90 2.86 2.85 3.01 2.97 2.88 2.91 2.99 2.92 3.02 2.89 2.93 2.93 2.04 1.03 2.32 GBW07163 6.74 6.85 6.66 6.68 6.80 6.84 6.85 6.82 6.70 6.72 6.80 6.78 6.77 1.04 0.49 1.72 GBW07172 10.26 10.28 10.40 10.15 10.22 10.26 10.36 10.26 10.29 10.45 10.31 10.35 10.30 0.82 0.42 1.44 GBW(E)070080 15.62 15.65 15.45 15.52 15.36 15.97 15.90 15.83 15.85 15.72 15.68 15.83 15.71 1.25 0.55 1.18 GBW07165 29.00 29.25 28.65 28.82 28.77 29.15 28.85 29.02 28.93 28.72 29.28 28.99 28.95 0.73 -0.18 0.82 GBW07168 32.00 32.30 32.17 32.21 32.01 31.85 32.06 31.95 32.03 31.95 32.24 31.81 32.05 0.50 0.16 0.77 随机选取20个实际样品，采用本实验优化的方法进行硫含量检测，每个样品平行测定3次取平均值，再通过与燃烧碘量法结果对比分析两种方法的绝对误差，比较两种方法的一致性和相关性，间接考察方法的准确度。由表 4测定结果可知，两种方法测定的硫含量相近，绝对误差范围在-0.25%~0.49%之间，说明本实验方法具有较高的准确度。通过对表 4数据进行线性拟合可知，两种方法测定结果之间呈极显著线性正相关，线性方程为y=1.0009x+0.0996(R2=0.9995)，说明两种方法的一致性和相关性很好，间接地表明了高频红外碳硫仪测定矿石样品中硫含量的可靠性。
表 4 两种方法硫含量结果对比Table 4. Comparison of sulfur content determined with two methods实际样品编号 硫含量测定平均值(%) 绝对误差(%) 实际样品编号 硫含量测定平均值(%) 绝对误差(%) 高频红外碳硫仪法 燃烧碘量法 高频红外碳硫仪法 燃烧碘量法 1 5.96 6.21 -0.25 11 2.23 2.05 0.18 2 26.09 25.60 0.49 12 24.62 24.85 -0.23 3 4.83 4.72 0.11 13 2.82 2.72 0.10 4 2.17 1.96 0.21 14 30.41 30.36 0.05 5 2.24 2.09 0.15 15 3.10 2.99 0.11 6 6.94 7.12 -0.18 16 5.23 5.00 0.23 7 4.12 4.08 0.04 17 2.17 2.02 0.15 8 2.47 2.20 0.27 18 15.73 15.88 -0.15 9 3.30 3.28 0.02 19 13.40 13.07 0.33 10 1.34 1.31 0.03 20 17.57 17.09 0.48 3. 结论
本文将高低两条硫含量校正曲线相结合，采用高低硫检测池切换的方法，建立了高频红外碳硫仪快速测定镍铅锌矿石中质量分数为0.74%~32.0%的硫含量方法，扩大了样品硫含量测量范围，有效地避免了因含量范围跨度大、检测曲线分段过多引起的检测信号不稳定及方法切换频繁等问题，提高了检测效率，降低了检测成本。
建立的方法可以同时快速、准确测定范围广、含量高的多种矿石硫含量，并解决了矿石的低电磁感应及基体影响大等问题。但高频红外碳硫仪测定硫对检测环境要求极为严格，尤其是含量较高、基体复杂的矿石样品，其分析对湿度极其敏感，探索出合适的温度、湿度检测条件，有效地节省干燥剂的使用成本是今后研究的重点内容。
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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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