Distribution Characteristics and Ecological Risk Assessment of Heavy Metals in Typical Soil Profiles of Muchuan County, Sichuan Province
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摘要:
根据全国土壤污染状况调查显示，全国土壤的环境状况总体不容乐观，耕地土壤环境质量令人担忧，已对粮食安全构成威胁。已有的研究工作多集中于土壤重金属的空间分布特征及污染源分析、重金属污染风险评估以及评估方法，但对于不同土壤深度重金属在耕地中的积累与剖面分布的变化及其生态风险分析相对较少。为研究四川省沐川县土壤剖面重金属分布特征和生态风险，本文在研究区选择三个不同地质背景区采集了土柱剖面样品开展相关工作。结果表明：样品中As、Cd、Hg、Pb、Ni、Cu、Zn七项指标中，除了Cu外，其余重金属元素含量都高于国家和四川省土壤背景值，表明这些元素在土壤中呈现不同程度地富集。土壤中7种重金属的浓度与土壤养分(氮、磷、钾)，土壤有机碳和pH值存在相关性，如在玉米地剖面中，氮和磷与Cd呈显著正相关，相关系数分别为0.845、0.747。大量研究表明，磷肥中含有一定量的重金属。磷肥中重金属含量高低与磷矿及其来源有关，磷肥能够增加土壤 Cd 含量。土壤有机碳与Cd呈显著正相关，相关系数为0.934，其原因是土壤有机质对重金属的吸附作用，有机碳对土壤中重金属的保留起了重要作用。pH值与Cd呈显著负相关，相关系数为-0.964，随着pH值的增加，土壤对重金属离子的吸附会增加，从而导致土壤中活性重金属离子减少。土壤重金属之间存在显著的正相关关系，表明它们普遍存在同源性。采用地质积累指数($ {I}_{\mathrm{g}\mathrm{e}\mathrm{o}} $)评价土壤重金属污染程度，并选取潜在生态风险指数($ RI $)评价其潜在生态风险，结果表明土壤中主要污染元素为Cd。生态风险指数显示，玉米地的潜在生态风险较大，其中Cd、Hg的生态风险较高，潜在生态风险指数($ RI $)随着剖面深度的增加而降低。当地应采取适当措施，加强对该地区污染的防治工作，避免对人体健康造成危害。
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关键词:
- 土壤 /
- 重金属 /
- 含量分布 /
- 污染评价 /
- 电感耦合等离子体质谱法
Abstract:BACKGROUNDSoil is a precious resource for human survival and social development. The quality of the soil environment is impacted by a variety of issues due to the social economy’s rapid expansion, and the issue of heavy metal contamination in farmed land has garnered great attention globally. Heavy metals in soil pose a severe risk to the security of agricultural products and public health due to their persistence, latency, and ease of entry into the food chain. In recent years, many scholars have carried out research on soil heavy metal pollution and ecological risk assessment under different conditions such as natural conditions, industrial and mining industries and developed transportation in different regions. Zhou et al.[11] found that Xiong’an New Area was affected by the production activities of surrounding enterprises. The contents of As, Cd, Cu, Pb and Zn in some root soil samples exceeded the screening value standard for soil pollution risk of agricultural land (GB 15618—2018), and the exceeding ratios were 23.33%, 96.67%, 33.33%, 33.33% and 10.00%, respectively. Song et al.[12] evaluated the characteristics of heavy metal pollution in the surface soil of Fuping County, Hebei Province, and found that As and Cd exceeded the acceptable carcinogenic risk level (As is 10−5, Cd is 10−6). Kumar et al.[10] collected data on heavy metal-contaminated soils in India from 1991 to 2018. The average Cd content of all soil types exceeded the limit values, and the potential ecological risk values of Cd were greater than 320, reflecting a higher ecological risk. For the heavily polluted soil, according to the different pollution situation in our country, the remediation measures are taken according to local conditions. However, due to the wide area of contaminated soil and the complex composition of pollution sources, the current soil remediation work still faces huge problems.
OBJECTIVESTo study the vertical distribution characteristics of heavy metals in soil, the relationship between soil heavy metals and soil nutrient elements, as well as the degree of pollution and potential ecological risks.
METHODSThe contents of Cd, Cu, Ni, Pb, Zn were measured using inductively coupled plasma-mass spectrometry (ICP-MS); As content was determined by hydride generation atomic fluorescence spectrometry (HG-AFS); P and K2O contents were determined by X-ray fluorescence spectrometry (XRF); N content was determined by oxidation combustion gas chromatography (GC); Hg content was determined by cold vapor atomic fluorescence spectrometry (CV-AFS); Organic carbon content was determined by high-frequency combustion infrared absorption method (IR); potentiometric method (POT) was used to measure soil pH value. Statistical analysis and calculation of soil heavy metal content, pollution index, and ecological risk index were conducted using Excel 2016. Pearson correlation analysis was conducted using SPSS 26, and the degree of soil heavy metal pollution was evaluated using the geoaccumulation index (Igeo). Potential ecological risk index (RI) values were selected to evaluate potential ecological risks.
RESULTSThe average contents of As, Cd, Cu, Hg, Ni, Pb, and Zn in the soil of YS plot were 20.8mg/kg, 0.35mg/kg, 26.38mg/kg, 0.121mg/kg, 33.29mg/kg, 42.37mg/kg, and 94.47mg/kg, respectively; The average contents of As, Cd, Cu, Hg, Ni, Pb, and Zn in the soil of PS plot were 7.21mg/kg, 0.32mg/kg, 28.32mg/kg, 0.028mg/kg, 47.34mg/kg, 33.29mg/kg, and 116.45mg/kg, respectively; The average contents of As, Cd, Cu, Hg, Ni, Pb, and Zn in the soil of GS plot were 5.42mg/kg, 0.16mg/kg, 22.38mg/kg, 0.08mg/kg, 31.8mg/kg, 30mg/kg, and 75.03mg/kg, respectively. The concentrations of As, Cd, Hg, Ni, Pb, and Zn were higher than the national and Sichuan soil background values, indicating that these metals were relatively enriched in the soil of Muchuan County. The relationship between seven heavy metals at different soil depths was evaluated through Pearson correlation analysis (seen in Table 4). There was a significant positive correlation between heavy metals, indicating their widespread homology. In the PS profile, the correlation between Cd, Hg and organic carbon was very high, with correlation coefficients of 0.934 and 0.955, respectively (Fig.5); As, Cd, Cu, Hg, Zn showed a highly significant negative correlation with pH, and the correlation between Cd, Hg content and soil pH was shown in Fig.5, with correlation coefficients of −0.964 and −0.944, respectively. The content of heavy metals in soil was closely related to organic carbon and pH value, which should be attributed to the adsorption of organic matter and the fact that pH not only affected the electrostatic adsorption of heavy metals by soil particles, but also damaged the inert part of the parent material. Soil organic matter and pH value are important factors affecting the migration of heavy metals in soil. The surface soil had a high content of organic matter, multiple adsorption sites, and a high soil pH value, which reduced the solubility of heavy metals and thus the metal migration rate. Soil pollution assessment results. The Igeo values of Cu and Zn in all soil profiles were less than 0, indicating that the soil in the study area was not contaminated by these heavy metals. The Igeo value of Cd at four depths was significantly reduced. Except that the Igeo value at GS point was less than 1, YS and PS were greater than 1, indicating that the Cd pollution degree of corn land (YS, PS) was more serious than that of tea garden land (GS). This may be due to the difference of tillage conditions, and the Igeo value of surface soil at YS point was between 2 and 3, showing moderate-strong pollution. The Igeo values of As, Hg, Ni and Pb at four depths were all less than 1 and close to 0, indicating that the soil pollution was slight, which may be caused by human input or natural changes. In general, conventional agricultural practices lead to the enrichment of heavy metals in soils due to excessive use of fertilizers and pesticides, wastewater irrigation and atmospheric deposition. Zhao et al.[42] found that use of fertilizers and manure increased the content of heavy metals (Cd, Cu, Pb, and Zn) by approximately 3% per year. The order of heavy metal pollution degree from high to low is Cd>Hg>As>Pb>Ni. Potential ecological risk assessment. According to the description of risk level, the YS plot had the highest potential risk index for Cd and Hg, and there was a significant ecological risk of Cd and Hg at depths of 0-140cm (80≤Ei<160), among which the surface soil Cd had a strong ecological risk (160≤Ei<320). It indicates that Cd pollution sources in the region may be affected by past agricultural activities, including fertilizers and pesticides. The soil Cd of PS plot exhibited strong ecological hazards (160≤Ei<320) at the depth of 0-30cm while exhibiting strong ecological hazards (80≤Ei<160) at 60-110cm. The Cd and Hg in surface soil at the GS plot site had moderate ecological risks (40≤Ei<80). The value of RI showed a strong ecological risk (300≤RI<600) at 0-10cm of the YS plot, and a moderate ecological risk (150≤RI<300) at 30-140cm. Moderate ecological hazards (150≤RI<300) were present in the PS plot, while mild ecological hazards (RI<150) were present at 60-110cm. The ecological hazards of GS plot at 0-130cm were relatively weak. The Ei values of heavy metals in soil decreased with the increase of depth, which was consistent with the evaluation results of Igeo pollution. The Ei values of Cd in the three profiles were relatively high, indicating that special attention should be paid to the control of heavy metal pollution.
CONCLUSIONSAccording to the results of soil vertical profile data, it can be concluded that heavy metal content tends to accumulate in the surface soil, and its content decreases with increasing depth. The Igeo value and Ei value also decrease with the increase of formation depth. The geoaccumulation index and potential ecological risk analysis indicate that Cd poses significant ecological risks to the local soil, and appropriate measures should be taken to strengthen pollution prevention and control in the area to avoid harm to human health. The content of heavy metals is closely related to soil nutrients and physicochemical properties, positively correlated with organic carbon content, and negatively correlated with pH value. According to the research results, it is suggested to carry out further research on the accumulation of heavy metals in soil, rationally assess its ecological harm, and ensure the safe use of land.
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Keywords:
- soil /
- heavy metals /
- content distribution /
- pollution assessment /
- inductively coupled plasma-mass spectrometry
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中国稀土资源丰富、种类齐全，稀土资源量占全球稀土资源总量的近一半。中国目前已发现的矿床类型有碱性岩型、花岗岩型、碳酸盐型和沉积变质型等类型，已发现的稀土矿物有30余种，如氟碳铈矿、独居石、硬钽矿、磷钍矿、铈钆钍矿和棱锰矿等［1］。中国内生稀土矿床多分布在长江以南地区，大地构造位置如扬子准地台、华南褶皱系、松潘—甘孜褶皱系、东南沿海褶皱系等，北方地区由于华北克拉通相对稳定，缺乏形成富集稀土元素的构造环境，仅在中朝准地台边缘出现一些稀土矿床，如内蒙古白云鄂博、山东微山郗山、辽宁凤城赛马、辽宁辽阳生铁岭等矿床［2-3］。
辽宁省已知稀土矿类型稀少，且以往稀土矿床的勘查评价多偏重于独居石砂矿和碱性岩型稀土矿，沉积变质型稀土原生矿涉及较少，矿石学、矿物学研究程度偏低。辽宁省在开展稀土矿产潜力评价工作时曾对省内的沉积变质型矿床(生铁岭稀土矿)成矿模式进行研究，总结了其成矿地质环境及矿床特征，认为其为含有少量独居石的磷灰岩型矿床［4］。籍魁［5］对辽宁辽阳郭家稀土矿床地质特征进行了研究，发现其矿石矿物主要为独居石、褐帘石，矿床类型为与古火山构造有关的沉积变质再造型矿床。本文研究的吉祥峪稀土矿床与生铁岭、郭家稀土矿床类型相似，矿石中稀土含量可观，但稀土矿物赋存状态、稀土元素在矿物中的分布规律以及稀土矿物能否被提取利用等问题尚需得到解决［6-7］。
自动矿物识别和表征系统(AMICS)是以成分点原位分析为基础，连接高分辨率扫描电镜(SEM)和高通量能谱仪(EDS)，釆用矿物边界分区法及图形处理技术，结合频谱列表快速、全面地对光谱进行合并及分类，比照矿物数据库自动拟合计算，能高效、全面、精确地测定样品的矿物成分、元素分布、粒度、连生关系以及孔隙度等信息，在含量低、颗粒细小的矿物定性、定量测试方面是一套先进、可行的技术方法［8-12］。该方法被广泛应用于地质、冶金等领域。例如，葛祥坤等［13］和张然等［14］运用该系统对鄂尔多斯盆地砂岩型铀矿矿物进行定量分析，查明了铀矿物类型和其他伴生矿物；温利刚等［15-18］、罗晓锋等［19］将该系统应用于稀土矿物的赋存状态研究，查明了稀土矿物种类和含量；王恩雷等［20］运用该系统对海城菱镁矿进行工艺矿物学研究，发现其矿物粒度细、脉石矿物与菱镁矿连生是矿石难选的主要原因；胡欢等［21］运用该系统研究了金属铍赋存状态，认为其对低含量铍元素的准确分析和微细含铍矿物的识别有良好的效果；范雨辰等［22］运用该系统对页岩储集空间的微观展布样式进行表征分类，通过扫描孔隙-矿物接触面积计算出孔隙类型和占比，有效地表征了含油(沥青)的储集空间。
因此，本文采用AMICS自动矿物识别和表征系统对正在开展勘查评价工作的吉祥峪稀土矿床进行矿物识别，目的是获得稀土元素在矿物中的分布规律，查明稀土矿物的种类和赋存状态，通过分析稀土矿物及相关矿物的成分、结构和嵌布特征，研究其成矿机制，揭示稀土矿床形成的约束条件，为矿床的勘查评价和有效利用提供矿物学依据。
1. 地质背景
吉祥峪稀土矿床大地构造位置处于华北陆块北缘，辽吉古元古代裂谷核部，吉祥峪—算盘峪背斜的核部。研究区出露地层主要为辽河群里尔峪组(Pt1lr)、高家峪组(Pt1g)和大石桥组(Pt1d)，属于一套火山碎屑沉积变质建造(图1)［23-26］。本次发现的稀土矿体严格受里尔峪组一段浅粒岩夹变粒岩层位控制。钻孔中所取的基本分析样测试结果显示，矿石中铁平均品位为25.07×10−2，稀土平均品位为1.03×10−2，轻稀土元素占绝对优势(以镧铈为主，钐铕镨钕等次之)。矿石主要结构构造为粒柱状变晶结构，块状及条带状构造：磁铁矿、角闪石、黑云母、褐帘石等暗色矿物集聚组成深色条纹条带，与长石、磷灰石等组成的浅色矿物条带相间排列。稀土矿体呈似层状、扁豆状顺层产出于里尔峪组一段磁铁浅粒岩夹褐帘磷灰磁铁变粒岩层位中，与其顶底板浅粒岩呈整合渐变关系。主要的蚀变类型有碳酸盐化、云母化、绿帘石化和碎裂岩化。
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图 1 吉祥峪稀土矿床地质简图及研究区位置图1—晚三叠纪二长花岗岩；2—里尔峪岩组；3—高家峪岩组；4—大石桥岩组；5—辉长岩；6—伟晶岩；7—闪长玢岩；8—稀土矿体；9—韧性剪切带；10—岩层产状；11—推测断裂；12—实测断裂；13—采样位置；14—二云片岩花纹；15—浅粒岩花纹；16—辉长岩花纹；17—伟晶岩花纹。Figure 1. Geological map and location map of Jixiangyu rare earth deposit. 1—Late Triassic monzogranite; 2—Lieryu Formation; 3—Gaojiayu Formation; 4—Dashiqiao Formation; 5—Gabbro; 6—Pegmatite; 7—Diorite porphyrite; 8— Rare earth ore body; 9—Ductile shear zone; 10—Occurrence of rock formation; 11—Presumed fault; 12— Measured fault; 13—Sampling location; 14—Two-mica schist pattern; 15—Leptite pattern; 16—Gabbro pattern; 17—Pegmatite pattern.2. 实验部分
2.1 样品采集与制备
本次实验样品采集于辽阳县隆昌镇吉祥峪研究区钻孔岩心，岩性为磷灰褐帘磁铁角闪变粒岩(样品编号XT-02)，样品颜色为灰黑色，鳞片粒状变晶结构，块状构造。测试前先将样品混合破碎至1mm以下，筛出22～120目样品置于环氧树脂中抛磨出光滑平面，真空喷碳增加导电性，然后进行AMICS分析［27-28］。
2.2 实验仪器及测试条件
实验测试在河南省岩石矿物测试中心完成。实验仪器包括一台超高分辨率场发射扫描电镜(Zeiss Sigma 500)、一台电制冷能谱仪(Bruker XFlash6610)以及一套AMICS自动矿物识别和表征系统。
本次测试仪器均经过调整和标定，并引入了质控样品用于监测和验证仪器性能和数据准确性，对XT-02样品进行重复测试以检查数据的重复性和精确性，测试过程中出现“计数率低”和“未识别”时调整测试参数和颗粒数，以保证测试数据的可靠性。测试时实验条件为：高真空环境，加速电压20kV，工作距离11.8mm，点分析采集时间达到250kcps自动停止。
3. 结果与讨论
3.1 稀土矿物的种类
通过矿物自动分析技术完成了稀土矿物的识别，确定组成稀土矿石样品(XT-02)的矿物类型10余种，主要矿物有：磁铁矿、阳起石、褐帘石、磷灰石、独居石、方铈石，次要矿物有：石英、斜长石、钾长石、榍石、黑云母。矿石矿物含量由高至低依次为：磁铁矿63.48%、阳起石7.61%、石英7.36%、褐帘石6.25%、磷灰石5.73%、钾长石2.20%、斜长石2.14%、独居石0.73%、黑云母0.51%、榍石0.39%、方铈石0.25%、绿泥石0.14%、钙铁榴石0.01%、锆石0.01%(图2、表1)。由此可知，吉祥峪稀土矿主要含稀土矿物为褐帘石、独居石、方铈石和磷灰石。
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图 2 吉祥峪稀土矿床样品(a)电子图像和(b)AMICS分析结果Figure 2. Electron image (a) and AMICS analysis result (b) of Jixiangyu rare earth deposit sample.表 1 吉祥峪稀土矿床样品AMICS矿物定量分析结果Table 1. Quantitative analysis results of minerals measured by AMICS in Jixiangyu rare earth deposit.矿物名称 质量分数
(%)面积百分比
(%)统计面积
(μm2)颗粒数
(个)统计相对误差
(%)矿物标准分子式［29-30］ 褐帘石 6.25 6.62 3386157.37 809 0.14 (Ce，Ca)(Ce，La)(Nd，Pr)(Fe2+，Fe3+)(Al，Mg)[Si2O7][SiO4]O(OH) 独居石 0.73 0.57 289757.48 105 0.35 (Ce，La，Ca，Fe，Th，Nd，Pr)[SiO4] [PO4] 方铈石 0.25 0.50 257590.30 78 0.06 (Ce3+，Th，Fe，Pr，Nd)O2 磷灰石 5.73 7.22 3696466.51 861 0.10 FeFe2O4 磁铁矿 63.48 48.95 25056614.78 1891 0.07 Ca5[PO4]3(F，OH) 阳起石 7.61 9.94 5088796.43 524 0.11 Ca2Na(Mg，Fe)5(Al，Fe3+)[(Si，Al)4O11]2(OH)2 石英 7.36 11.16 5713847.71 1218 0.08 SiO2 钙铁榴石 0.01 0.01 70.14 1 2.00 Ca3Fe2[SiO4]3 斜长石 2.14 3.25 1663198.10 288 0.16 Na[AlSi3O8] 榍石 0.39 0.44 227134.51 301 0.20 CaTi[SiO4]O 锆石 0.01 0.01 1928.91 12 0.58 Zr(SiO4) 绿泥石 0.14 0.19 99300.33 166 0.18 Fe3 2+[Si4O10](OH)2(Mg，Al，Fe，Si)3(OH)6 钾长石 2.20 3.41 1743721.36 134 0.21 K[AlSi3O8] 黑云母 0.51 0.65 334115.41 344 0.15 K(Fe，Al)3AlSi3O10(F，OH)2 未知矿物 3.20 6.36 3255145.74 4728 0.05 / 孔隙 / 0.73 371809.84 22084 0.06 / 3.1.1 褐帘石
褐帘石是一种含有较高稀土组分的帘石族矿物，其轻稀土成分可占全岩类的90%以上，其中Ca可被REE3+、Th4+、U4+等替代，使其高度富集LREE、U、Th等微量元素，化学成分变化较大，Al可被Fe2+、Mg2+等替代［31-32］。
褐帘石在XT-02样品中分布不均匀，含量为6.25%。样品中的褐帘石多呈柱状或厚板状，解理不完全，自形-半自形，粒径0.01～0.595mm。对其进行能谱分析，得到褐帘石平均含有O 37.07%、Fe 16.38%、Si 11.88%、Ca 7.96%、Al 5.35%、Mg 0.55%、Ce 10.69%、La 6.79%、Nd 2.24%、Pr 1.09%(表2)。矿物中富含轻稀土元素，以Ce、La、Nd为主，含少量Pr，未见U元素和Th元素的替代［33-34］。镜下观察发现，褐帘石常与磷灰石、磁铁矿连生，与磁铁矿关系密切(图3a；图4中a，c)。
表 2 褐帘石能谱分析结果Table 2. Energy spectrum analysis results of allanite.样品编号 质量分数(%) O Fe Si Ca Al Mg Ce La Nd Pr XT02-07 37.43 16.07 11.74 7.76 5.27 0.59 11.06 6.95 2.04 1.08 XT02-13 35.73 15.11 12.31 7.76 5.50 0.59 11.60 7.81 2.33 1.25 XT02-29 38.23 15.73 11.30 8.39 5.02 0.41 10.94 7.07 1.94 0.98 XT02-30 37.13 17.78 11.63 8.06 5.17 0.47 10.27 6.18 2.31 1.00 XT02-31 36.85 16.50 12.80 7.41 6.17 0.82 9.77 6.17 2.26 1.25 XT02-32 37.03 17.08 11.49 8.39 4.99 0.42 10.48 6.58 2.54 1.00 平均值 37.07 16.38 11.88 7.96 5.35 0.55 10.69 6.79 2.24 1.09 ![]()
图 3 稀土矿物背散射图像a—褐帘石；b—方铈石；c—粒状独居石；d—放射状独居石。Figure 3. Backscattering images of rare earth ores: (a) Allanite; (b) Cerianite; (c) Granular monazite; (d) Radial monazite.![]()
图 4 样品XT-02(磷灰褐帘磁铁角闪变粒岩)的显微组构特征a—褐帘石与磷灰石、磁铁矿连生； b—独居石被磷灰石包裹； c—褐帘石与磷灰石连生，被磁铁矿包裹； d—独居石与磁铁矿连生，被角闪石包裹。Aln—褐帘石；Ap—磷灰石；Mag—磁铁矿；Mnz—独居石；Cam—角闪石。Figure 4. Microfabric characteristics of sample XT-02 (apatite-allanite-magnet-hornblende granulite): (a) Allanite, apatite and magnetite coexisting; (b) Monazite surrounded by apatite; (c) Allanite and apatite coexisting, surrounded by magnetite; (d) Monazite associated with magnetite and wrapped by amphibole. Aln—Allanite; Ap—Apatite; Mag—Magnetite; Mnz—Monazite; Cam—Amphibole.3.1.2 方铈石
方铈石在XT-02样品中少量分布，多以单体形式存在，含量为0.25%。样品中方铈石常呈不规则粒状及聚粒状，粒径0.01～0.5mm(图3b)。对其进行能谱分析，得到方铈石平均含有Ce 53.67%、O 21.07%、Fe 8.56%、Si 3.67%、P 3.36%、Pr 2.35%、Nd 1.79%、Ca 1.30%、Th 1.29%、Al 1.23%、La 0.87%、Mn 0.56%、Mg 0.28%(表3)，矿物中富含轻稀土元素，以Ce、La、Nd为主，常见Mg元素等被Th元素替代［35］。
表 3 方铈石能谱分析结果Table 3. Energy spectrum analysis results of cerianite.样品编号 质量分数(%) Ce O Fe Si P Pr Nd Ca Th Al La Mn Mg XT02-38 57.32 17.24 8.32 3.63 3.96 3.84 2.80 1.36 / 1.53 / / / XT02-39 52.73 16.46 8.53 4.17 3.58 4.15 2.35 1.29 / 1.75 / 3.95 1.04 XT02-54 45.70 23.43 13.12 4.25 2.71 0.98 1.13 1.79 1.95 2.04 2.02 / 0.89 XT02-61 53.13 25.81 5.44 4.38 3.06 1.30 1.36 1.04 2.02 1.11 1.35 / / XT02-62 66.35 15.50 4.47 2.79 3.22 1.65 1.59 1.02 1.61 / 1.80 / / XT02-63 55.86 21.51 6.37 2.63 4.07 2.56 1.83 1.57 2.84 0.74 / / / XT02-64 44.60 27.54 13.65 3.86 2.93 1.94 1.48 1.02 0.62 1.46 0.89 / / 平均值 53.67 21.07 8.56 3.67 3.36 2.35 1.79 1.30 1.29 1.23 0.87 0.56 0.28 3.1.3 独居石
独居石是一种富含轻稀土元素的磷酸盐矿物，含有放射性元素Th、U。独居石常与绿泥石、阳起石等变质矿物交叉共生或作为包裹体镶嵌其中(图3中c，d)。在背散射图像中，独居石较其他矿物具有更高的亮度，其亮度与Th含量呈正比［36-38］。
独居石在XT-02样品中多以单体形式存在，含量为0.73%。样品中的独居石呈自形-半自形板状，解理完全，粒径0.01～2.1mm。对其进行能谱分析，得到独居石平均含有O 29.38%、P 13.87%、Ce 20.08%、La 20.43%、Nd 8.68%、Pr 2.92%、Ca 1.55%、Fe 1.05%、Si 0.81%、Th 1.25%(表4)。矿物中富含轻稀土元素，以Ce、La、Nd为主，常见Ca元素等被Th元素替代。镜下观察发现，独居石与磁铁矿连生，常被褐帘石、磷灰石等矿物包裹［39］(图4中b，d)。
表 4 独居石能谱分析结果Table 4. Energy spectrum analysis results of monazite.样品编号 质量分数(%) O Ce La P Nd Pr Ca Fe Si Th XT02-06 27.53 24.44 17.99 14.39 7.11 2.49 2.20 2.20 0.93 0.72 XT-02-40 21.03 12.05 28.06 14.69 12.33 4.81 3.46 2.34 0.88 0.33 XT02-46 25.81 11.32 26.81 12.77 11.69 4.49 2.40 1.35 1.71 1.65 XT02-47 26.91 9.71 26.13 13.38 11.81 4.71 2.16 1.64 1.38 2.17 XT02-53 32.08 9.84 24.95 12.25 10.93 4.13 1.90 0.89 1.07 1.96 XT02-55 31.13 20.20 19.32 13.69 7.65 2.45 4.33 1.24 / / XT02-56 38.95 14.45 19.58 12.79 8.18 2.67 2.06 / 1.32 / XT02-68 39.31 14.25 18.25 11.32 6.91 2.53 3.14 2.85 0.54 0.90 XT02-69 30.77 26.29 16.70 15.64 7.28 2.30 / / / 1.02 XT02-71 27.88 27.67 17.08 13.91 7.96 2.16 / 0.27 0.65 2.43 XT02-73 28.40 28.23 18.51 14.91 6.78 1.99 / 0.30 / 0.88 XT02-74 26.63 27.20 17.16 14.08 7.92 2.07 / 0.39 1.01 3.55 XT02-75 28.00 27.00 17.16 14.73 7.52 2.08 / 0.82 0.77 1.91 XT02-76 26.93 28.47 18.32 15.59 7.42 2.06 / 0.38 1.01 / 平均值 29.38 20.08 20.43 13.87 8.68 2.92 1.55 1.05 0.81 1.25 3.1.4 其他含稀土矿物
矿石中还含有磷灰石(5.73%)。磷灰石是一种重要的稀土元素累积矿物，其在变质岩中作为常见的副矿物出现，已报道的磷灰石中的稀土含量最高可达11.14%(RE2O3)，且主要为轻稀土［40-41］。饶金山等［42］通过实验揭示了磷灰石含稀土的机制：①磷灰石包裹微细独立稀土矿物(独居石、褐帘石)(图4b)。②RE3+晶格替代磷灰石中的Ca2+。
3.2 AMICS方法的优势与不足
AMICS系统的优势明显：①以往的稀土矿物鉴定工作需要先在目镜下区分矿物，圈定矿物位置，然后才能进行实验，且目标稀土矿物颗粒细小，光性特征复杂不易区分，这些都使得实验效率和准确性明显降低。该系统通过多种信号联合分析快速、准确地获得矿物微区准确的结构信息和化学成分。通过分析和比对大量的矿物样本图像和特征，快速、准确地识别出不同矿物类型，确定矿石的成分和矿物组合、尺寸分布、颗粒形状、矿物之间的关系等。②该系统可以对大量的样本数据进行分析和处理。能有效地识别出矿物的特征模式和相关性、潜在的规律和趋势，以指导矿产资源的合理开发利用［43-44］。
但该方法仍然存在一些缺点：①在样品制备阶段需保证光片表面的平整度、凹凸表面及倒角会影响X射线的产生和激发。②AMICS测量的面积只有15mm2左右，选择样品时需注意所选样品的代表性。③测试过程中需尝试调整仪器参数和矿物测试颗粒数，控制测试相对误差率在10%左右，保证置信度大于95%。④分析系统不能区分同质多象及成分相似的矿物，需要人工识别分析数据，辅以岩矿鉴定知识加以辨认，改变分类结果，或者借助电子探针(EPMA)进一步确定矿物［45-46］。
4. 结论
通过AMICS测试，完成了辽东吉祥峪稀土矿石(样品编号XT-02)的原位解离分析，得到该稀土矿床稀土矿物主要为褐帘石、独居石和方铈石，其中褐帘石占矿物总量的比例为6.25%，独居石占比为0.73%，方铈石占比为0.25%，稀土元素以La、Ce、Pr、Nd等轻稀土元素为主，且主要在褐帘石、独居石和方铈石中富集，少量稀土元素以类质同象形式赋存在磷灰石中。脉石矿物有阳起石、石英、斜长石、钾长石、榍石、黑云母等。
通过背散射图像结合光学显微镜观察得出，矿石中的稀土矿物褐帘石、独居石、方铈石及磷灰石具有较好的连生关系。这些矿物以单颗粒或聚粒结构与磁铁矿交叉镶嵌，或分布在磁铁矿边缘及间隙中，与磁铁矿呈现出较复杂的共生关系。该结果和样品中稀土与磁铁矿含量呈正相关相一致，分析其形成过程可能为以下原因：①沉积富集：吉祥峪稀土矿位于辽吉裂谷的核部，裂谷为矿床提供了有利的沉积环境，沉积物经过长时间的聚集、压实和蚀变作用，可能会同时释放稀土元素和铁元素并逐渐富集形成矿床。②岩浆改造：岩浆热液可能与里尔峪组一段变粒岩产生反应，形成稀土矿物和磁铁矿的矿化过程可能同时发生或相互交织，使其中高背景值的稀土元素和铁元素活化并在同一地质环境下富集。③构造控制：特定的地质过程或成矿作用可能对稀土元素和铁元素的分布产生共同的控制作用。吉祥峪稀土矿体位于辽吉裂谷带核部—吉祥峪算盘峪背斜核部的穹隆构造上，断裂带和褶皱可能在地壳的应力作用下形成矿质富集的通道，使矿质从深部运移至浅部。
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图 2 三个采样点土壤剖面重金属平均含量对比
黑色虚线表示全国土壤背景值，红色虚线表示四川土壤背景值。
Figure 2. Comparison of average heavy metal contents in soil profiles at three sampling points. The black dotted line indicates the background value of national soil, and the red dotted line indicates the background value of Sichuan soil.
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图 3 三个采样点土壤剖面重金属垂向分布特征
Figure 3. Vertical distribution characteristics of heavy metals in soil profiles at three sampling points.
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图 4 三个采样点土壤剖面有机碳(Corg)、氮(N)、磷(P)、氧化钾(K2O)含量和pH的垂向分布特征
Figure 4. Vertical distribution characteristics of organic carbon (Corg), nitrogen (N), phosphorus (P), potassium oxide (K2O) contents and pH in soil profiles at three sampling points.
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图 5 紫色黏质土(PS剖面) Cd与Corg (a)、Hg与Corg (b)、Cd与pH值(c)、Hg与pH值(d)相关关系
Figure 5. The correlation between Cd and Corg (a), Hg and Corg (b), Cd and pH (c), Hg and pH (d) in purple clay soil (profile PS).
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图 6 三个采样点剖面土壤0～10cm深度(a)、30～40cm深度(b)、70～80cm深度(c)和100～110cm深度(d)的重金属地质累积指数($ {\mathit{I}}_{\mathbf{g}\mathbf{e}\mathbf{o}} $)
Figure 6. Geo-accumulation indexes ($ {\mathit{I}}_{\mathbf{g}\mathbf{e}\mathbf{o}} $) of heavy metals in profile soils at 0-10cm depth (a), 30-40cm depth (b), 70-80cm depth (c) and 100-110cm depth (d) at the three sampling sites.
表 1 研究区不同类型土柱剖面取样点概况
Table 1 Sampling points of different types of soil column profiles in the study area.
采样地点 采样深度(cm) 土地利用类型 土壤类型 地质背景 可见特征描述 剖面YS 140 山坡旱地，
种植玉米黄色黏质土 三叠系雷口坡组(T2l)，岩性为粉砂岩与白云岩、泥质灰岩互层，夹黑色碳质页岩 0～50cm灰黄色黏质土，50～140cm黄色黏质土 剖面PS 110 山坡旱地，
种植玉米紫色黏质土 侏罗系蓬莱镇组(J3p)岩性
以泥岩、砂岩和粉砂岩为主0～80cm紫色黏质土，80～110cm紫色黏质土，
土壤水分降低剖面GS 130 茶园地 灰色黏质土 三叠系须家河组(T3x) ，岩性主要为砂岩、粉砂岩、泥岩及煤层组成的沉积旋回 0～40cm，灰色黏质土，有机质较丰富；40～70cm，土壤颜色变黄，细砂成分增多；80～90cm，青灰色淤泥，水分增多；90～100cm，土壤变灰黑色，水分变少；100～120cm，青灰色黏质土；120～130cm，灰绿色，底部为页岩、泥岩 
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表 2 各指标分析测试检出限
Table 2 Detection limit of each index analysis.
分析项目 检出限 分析项目 检出限 As 0.5$ \mathrm{m} $g/kg Zn 4$ \mathrm{m} $g/kg Cd 0.03$ \mathrm{m} $g/kg P 10$ \mathrm{m} $g/kg Cu 1.$ 0\mathrm{ } $mg/kg Corg 0.10% Hg 0.0005$ \mathrm{m} $g/kg K2O 0.05% Pb 2$ \mathrm{m} $g/kg pH 0.1 Ni 2$ \mathrm{m} $g/kg N 20$ \mathrm{m} $g/kg
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表 3 三个采样点土壤剖面重金属与土壤养分指标的Pearson相关性
Table 3 Pearson correlation between heavy metals in soil profiles and soil nutrient indicators at three sampling points.
采样地点 养分元素 As Cd Cu Hg Ni Pb Zn 剖面YS N 0.186 0.813** 0.706** −0.419 −0.147 0.724** 0.135 P 0.401 0.947** 0.758** −0.188 −0.120 0.828** 0.307 K2O 0.155 −0.399 −0.486 0.795** 0.526 −0.669** 0.638* Corg 0.003 0.759** 0.764** −0.721** −0.340 0.861** −0.150 pH −0.492 −0.455 −0.120 −0.627* −0.088 −0.265 −0.836** 剖面PS N 0.814** 0.845** 0.828** 0.924** −0.160 −0.072 0.724* P 0.458 0.747** 0.504 0.632* −0.209 0.481 0.695* K2O −0.113 −0.266 0.047 −0.295 0.924** −0.121 0.424 Corg 0.865** 0.934** 0.865** 0.955** −0.283 0.065 0.717* pH −0.897** −0.964** −0.884** −0.944** 0.287 −0.223 −0.735** 剖面GS N 0.934** 0.448 −0.262 0.899** −0.765** 0.897** −0.612* P 0.186 0.144 0.661* 0.084 0.265 0.485 0.425 K2O −0.713** −0.237 0.801** −0.721** 0.937** −0.366 0.863** Corg 0.947** 0.552 −0.303 0.953** −0.824** 0.893** −0.673* pH −0.451 −0.039 −0.054 −0.358 0.227 −0.649* 0.110 注：“**”表示在 0.01 级别(双尾)，相关性显著；“*”表示在 0.05 级别(双尾)，相关性显著。
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表 4 土壤剖面重金属之间的Pearson相关性
Table 4 Pearson correlation between heavy metals in soil profiles.
元素 As Cd Cu Hg Ni Pb Zn As 1 Cd 0.546** 1 Cu 0.187 0.644** 1 Hg 0.772** 0.141 −0.288 1 Ni −0.369* 0.141 0.683** −0.769** 1 Pb 0.822** 0.672** 0.310 0.566** −0.311 1 Zn 0.029 0.500** 0.783** −0.484** 0.864** 0.065 1 注：“**”表示在 0.01 级别(双尾)，相关性显著；“*”表示在 0.05 级别(双尾)，相关性显著。
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表 5 三个采样点土壤剖面重金属潜在生态风险指数
Table 5 Potential ecological risk index of heavy metals in soil profiles of three sampling points.
采样地点 采样深度
(cm)$ {E}_{i} $ RI As Cd Cu Hg Ni Pb Zn 剖面YS 10 21.9 278.4 5.0 83.3 5.0 8.7 1.2 403.5 30 21.1 141.6 4.3 72.9 4.9 7.8 1.0 253.6 60 20.0 125.3 4.5 66.7 5.1 6.9 1.0 229.6 90 18.0 95.7 3.7 88.6 4.7 6.4 1.1 218.1 110 20.6 96.5 3.8 96.9 5.1 6.2 1.1 230.1 140 20.7 146.6 4.3 90.5 5.6 6.0 1.2 274.9 剖面PS 10 7.7 177.3 4.8 27.8 6.9 5.5 1.4 231.4 30 8.0 171.6 5.0 22.5 7.2 6.0 1.4 221.7 60 7.0 103.3 4.7 16.8 7.4 5.0 1.3 145.5 90 6.3 80.5 4.1 15.2 7.0 4.8 1.3 147.6 110 6.3 80.1 4.3 13.7 8.0 5.4 1.4 119.2 剖面GS 10 9.6 56.6 3.4 74.2 3.4 6.3 0.7 154.3 30 9.7 101.8 3.8 78.6 3.9 6.2 0.8 204.8 60 6.9 33.8 3.5 64.8 4.2 5.0 0.8 119.1 90 2.3 64.2 3.0 31.6 5.2 3.9 0.9 111.0 110 0.9 21.6 3.9 30.4 6.0 3.6 0.9 67.5 130 1.5 85.1 5.0 25.7 7.4 3.8 1.2 129.7
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