Geochemical Characteristics and Influencing Factors of Soil Selenium in Longzi County, Tibet Autonomous Region
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摘要:
硒是人体必需的微量元素之一，土壤中的硒含量与人体健康关系密切。调查土壤硒含量分布特征、圈定富硒土壤资源分布区、查明土壤硒含量影响因素，对于推动富硒土地资源开发利用、发展富硒农牧产业、预防地方疾病等均具有重要意义，也可为土壤硒背景值研究提供参比资料。土壤硒是当前热点研究领域，国内外对土壤硒研究已有很多，然而西藏地区有关土壤硒方面研究资料非常有限。本文选择西藏自治区隆子县重点耕地区为研究对象，系统采集表层土壤、垂向剖面、岩石样等样品，采用原子荧光光谱法(AFS)、容量法(VOC)、电感耦合等离子体发射光谱法(ICP-OES)等方法测定土壤中的硒、有效硒、有机质、全磷等含量指标，利用统计方法对研究区土壤硒、有效硒等地球化学含量特征及影响因素进行初步探讨。结果表明：①研究区表层土壤硒含量范围为0.14~1.51mg/kg，中位数为0.44mg/kg，是西藏土壤硒平均值(0.15mg/kg)的2.9倍和中国表层土壤Se平均值(0.26mg/kg)的1.5倍，表明研究区表层土壤中全硒含量较高；研究区表层土壤中有效硒含量范围为0.8~26.8μg/kg，中位数为9.2μg/kg，土壤有效硒占全硒含量的0.21%~5.79%；土壤硒含量高于0.4mg/kg为界限值，研究区总面积的77.25%符合富硒土壤划定标准，表明富硒土壤资源丰富；②研究区广泛分布的涅如组(T3n)和日当组(J1r)地层发育土壤中硒含量较高，中位数分别为0.44mg/kg和0.41mg/kg，土壤硒含量与地质背景密切相关；土壤理化性质包括有机质、pH、TFe2O3等对土壤全硒含量影响不显著，但土壤有效硒与有机质、pH、N、P、碱解氮、有效磷、速效钾、阳离子交换量(CEC)呈显著正相关；此外，铁氧化物(TFe2O3)对有效硒含量也有一定控制作用；③土壤垂向剖面研究发现，土壤硒含量还与表生富集作用有关。综合认为，研究区土壤Se含量较高，富硒土壤资源丰富，可以通过土壤养分管理，进一步提高土壤硒生物有效性。
要点(1) 研究区土壤Se含量范围为0.14~1.51mg/kg，中位数为0.44mg/kg，明显高于西藏和中国表层土壤硒含量平均值。
(2) 土壤硒含量与地质背景密切相关，受涅如组和日当组黑色岩系控制。
(3) 土壤有机质、N、P、碱解氮、有效磷、速效钾、CEC含量对土壤有效性产生影响。
HIGHLIGHTS(1) The soil Se content in the study area ranges from 0.14 to 1.51mg/kg, with a median of 0.44mg/kg, which is significantly higher than the average of surface soil Se content in Tibet and China.
(2) The soil Se content is closely related to the geological background and controlled by the black rock system of Neru and Ridang Formations.
(3) Soil organic matter, N, P, alkali-hydrolyzable N, available P, available K, and CEC content affect soil availability.
Abstract:BACKGROUNDSelenium (Se) is one of the essential trace elements in the human body, which has many biological functions. Insufficient or excessive intake of Se will cause a series of diseases. The trace element Se in the human or animal body cannot be synthesized by itself, but can only be supplemented from external food. Se in food, especially in plant food, mainly comes from soil. Therefore, Se in soil is closely related to human health and animal growth. China is a country lacking in soil Se content, especially in Tibet. The background value of soil Se in Tibet is significantly lower than that of surface soil in China. Therefore, local diseases such as Kashin-Beck disease are common in some areas of Tibet due to long-term insufficient intake of selenium. It is of great significance to investigate the distribution characteristic of soil Se content, delineate the distribution area of selenium-enriched soil resources and determine the influencing factors of soil Se content for promoting the development and utilization of selenium-enriched land resources, develop Se-enriched industries and prevent local diseases. This will also provide reference data for the research of soil Se background value.
OBJECTIVESIn recent years, it has been a hot topic to investigate the content of Se in soil, to delineate selenium-enriched soil resources and to develop and utilize them. Tibet is the main part of the Qinghai—Tibet Plateau, which has complex and diverse soil parent materials and soil forming processes, forming unique alpine soil types. In addition, Tibet is one of the areas with the least influence of human activities and is the ideal place for environmental geochemistry research. However, due to many factors such as natural geographical location and climate, the research data of soil element geochemistry in Tibet is very limited, and research data of soil Se is rare. Thus, the characteristics, distribution and influencing factors of soil Se content in the study area were studied, to provide a basis for the exploitation and utilization of selenium-enriched land resources, the development of selenium-enriched industry and the prevention of endemic diseases in the frontier ethnic areas of the plateau.
METHODSThe collection, processing and analysis of samples of surface soil, vertical profile and rock profile were carried out. The samples were collected from the key farming area of Longzi County, Shannan, Tibet Autonomous Region. The surface soil samples were collected in a grid pattern from the third national land survey map spot. The soil sampling points were mainly arranged on agricultural plots, with an average sampling density of 7.9 points/km2. A total of 1587 surface soil samples were collected, with a study area of 200km2. The sampling method for surface soil samples was determined according to the actual plot shape. When the plot was square, "X" type sampling was adopted, and when the plot was rectangular, "S" type sampling was adopted. When sampling cultivated land, 5 sub-sampling points were equally combined into 1 sample; for grassland and woodland sampling, 3-4 sub-sampling points were equally combined into one sample. The samples collected at each sub-sampling point were crushed, small stones, roots and other sundries picked out, and after fully mixing, more than 1000g samples reserved and put into sample bags by quartering method. In the study area, 10 vertical soil profiles were set up, and the sampling interval was 1 sample/20cm. The depth of all the profiles was 160cm except for the profile CM01, which was 140cm deep. In addition, a rock profile was set in the study area, and fresh rock samples were collected. The same kind of rock was collected in a multi-point mode and combined into a sample, with the sample weight of 300g. The surface soil samples, and vertical profile samples collected were naturally dried without pollution, and sieved by -10 mesh nylon sieve, then divided by quartering method, weighed and put into sample bottles and sent to laboratory for analysis. Soil samples were analyzed for Se, available Se, organic matter, pH, N, P, available N, available P, available K, etc. Rock samples were analyzed for Se. The contents of Se and available Se were determined by atomic fluorescence spectrometry (AFS), organic matter. Available nitrogen and cation exchange capacity (CEC) were determined by volumetric method (VOL), pH value was determined by ion selective electrode method (ISE), N content was determined by elemental analyzer method (EA), and available P, available K, P and TFe2O3 were determined by inductively coupled plasma-optical emission spectrometry (ICP-OES). The detection limit, accuracy, precision and reporting rate of the analytical method adopted all met the specification requirements, and the sample analysis quality was reliable.
RESULTSThe results of the content of Se in soil and its influence factors, showed that: (1) The Se content in the topsoil of the study area ranged from 0.14 to 1.51mg/kg, with a median of 0.44mg/kg, which was 2.9 times as high as the average value of Tibet (0.15mg/kg) and 1.5 times as high as the average value of China (0.26mg/kg). The content of available Se in the topsoil ranged from 0.8 to 26.8μg/kg, with a median of 9.2μg/kg. The content of available Se in topsoil was 0.21%-5.79% of total Se. (2) Se-enriched (Se≥0.4mg/kg) soil resource area was 154.53km2, which accounted for 77.25% of the total area. Se-enriched soil was mainly distributed in Longzi Town and Ridang Town. There was no excess or deficiency of soil Se in the study area, which indicated that Se-enriched soil was continuous and had the potential to develop Se-enriched soil resources. (3) The geological background was closely related to the Se content in the soil. The Se rich soil was mainly controlled by the distribution of the Nieru Formation (T3n) and the Ridang Formation (J1r). The median Se content in the soil developed from the Nieru Formation (T3n) and the Ridang Formation (J1r) was 0.44mg/kg and 0.41mg/kg, respectively. Analysis of Se content in rock samples showed that Se content ranged from 0.07 to 11.00mg/kg, with an average of 1.65mg/kg. Se content was high in sericite slate and shale, which further proved that Se-enriched soil was closely related to its parent rock. (4) Soil physical and chemical properties including organic matter, pH, TFe2O3 had no significant effect on soil Se content, but soil available Se was positively correlated with organic matter, pH, N, P, alkali-hydrolyzable N, available P, available K, CEC content. There was a positive correlation between the content of organic matter and the content of available Se (R2=0.2792, P < 0.01), and between the content of organic matter and the ratio of available Se to total Se (R2=0.2597, P < 0.01). There was a positive correlation between soil available Se and pH (R2=0.103, P < 0.01). According to the soil pH grading standard, the availability of Se increased gradually from acid to alkaline soil, but in strong alkaline soil, the availability began to decrease due to the methylation reaction of Se. There was a negative correlation between available Se and TFe2O3 (R2=-0.346, P < 0.01). In the study area, the content of soil available Se had significantly positive correlation with the content of N, P, alkali-hydrolyzable N, available P and available K, which indicated that the increase of N, P and K content could significantly improve the bioavailability of soil selenium, which had a certain theoretical significance for the artificial control of soil Se content. (5) 10 vertical soil profiles were constructed in different areas of the study area, and the depth of the other profiles was 160cm except for the CM01 profile, which was 140cm. In that vertical soil profile, the content of Se and available Se decreased with the increase of soil depth. The content of Se in the soil below 100cm was less than 0.4mg/kg, and the content of available Se in the soil at 160cm was 60% less than that in the surface soil.
CONCLUSIONSThe content of Se in the topsoil of the study area is high, and 77.25% of the study area is in line with the standard of Se-enriched soil. In that soil, the Se content is mainly affected by the parent materials, especially the sericite slate and shale in the Nieru Formation (T3n) and Ridang Formation (J1r). The land use type has little effect on Se content and distribution. Physical and chemical properties of the soil, such as organic matter, pH, N, P, available N, available P, available K and CEC, have little effect on total Se content, but soil available Se is significantly positively correlated with organic matter, pH, N, P, alkali-hydrolyzable N, available P, available K and CEC. Soil nutrient management can further improve bioavailability of soil selenium. Only the characteristics and influencing factors of soil Se content in Longzi County, Tibet Autonomous Region, were discussed, in order to provide a geological basis for the development and utilization of Se-enriched land resources. However, the process of Se uptake by crops is a very complex biogeochemical process, and is affected by many factors. Therefore, it is necessary to further strengthen research on the characteristics of Se content and its migration and transformation in soil-crop system.
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独居石是过铝质花岗岩中常见的富轻稀土元素(LREE)磷酸盐矿物，它所含的LREE含量常常是寄主岩石LREE总量的40%~80%[1]。独居石还可以含有大量的Th和U含量。例如意大利Monte Capanne岩体中独居石的ThO2含量可达42.82%，UO2含量可达2.19%[2]；德国Fichtelgebirge花岗岩中独居石的ThO2含量高达21.20%，UO2含量高达8.02%[3]；中国广西豆乍山岩体中独居石的UO2含量可达1.68%[4]。独居石是有效的定年矿物[5-7]，并且常常被认为是形成热液铀矿床重要的铀源提供者[4, 8-11]。大多数热液铀矿床是后生热液成因，因此，只有当独居石发生蚀变导致铀发生活化迁移，才可以成为有效铀源[4, 9]。理解独居石在蚀变过程中详细的结构特征和成分变化对解译铀成矿过程具有重要意义。
独居石是华南产铀花岗岩中常见的含铀副矿物，因其常含有较高的铀含量而被认为是铀源矿物[4, 10-11]。例如，广西豆乍山花岗岩中独居石的UO2含量为0.98%~1.68%，独居石蚀变形成直氟碳钙铈矿，从而铀被释放，为铀成矿提供铀源[4]。粤北长江产铀花岗岩中独居石的UO2含量为0.27%~0.73%，ThO2含量为2.40%~5.89%，是该岩体的铀源矿物[10]。独居石在流体作用下发生蚀变的机制主要有两种：①独居石被其他矿物替代，蚀变产物主要是磷灰石、褐帘石和绿帘石；②形成次生独居石，与原生独居石具有不同的结晶年龄和成分等特征[12-19]。华南产铀花岗岩中的独居石在流体作用下可形成蚀变晕圈现象[20]，但是独居石蚀变晕圈的结构和成分特征研究较为薄弱。此外，形成蚀变晕圈现象的独居石对区域铀成矿是否贡献铀源也需要开展进一步研究。
粤北诸广山地区是中国最重要的花岗岩型铀矿床聚集地之一，区内产有302、305、308、201等多个大中型花岗岩型铀矿床。诸广山岩体是一个主要由加里东期、印支期和燕山期花岗岩组成的复式岩体，区内铀矿化与印支期花岗岩关系最为密切[20-23]。龙华山岩体是该复式岩体中一个重要的印支期产铀花岗岩。本项目组在研究诸广山岩体的晶质铀矿矿物学特征过程中发现该岩体中独居石具有独特的蚀变晕圈现象[20]，然而组成蚀变晕圈的矿物尺寸较小(一般为1~100μm)，部分矿物无法利用激光剥蚀-电感耦合等离子质谱仪等仪器获取其成分特征，这为揭示独居石蚀变晕圈成因带来挑战。电子探针(EPMA)具有高空间分辨率(束斑可小至1μm)、方便快速、可进行微区原位分析等优点[24]，是研究独居石蚀变晕圈的有效工具。例如，Broska等[14]利用EPMA获得斯洛伐克Western Carpathians岩体中独居石蚀变晕圈的结构和矿物化学，指出独居石蚀变晕圈是流体作用的结果；胡欢等[4]利用EPMA获取了豆乍山岩体中独居石及其蚀变产物直氟碳钙铈矿的化学成分，从而揭示了独居石是该岩体重要的铀源矿物。本文利用EPMA对龙华山岩体中独居石蚀变晕圈的结构和矿物化学进行分析，以探讨独居石蚀变晕圈成因以及对铀成矿的指示意义。
1. 研究区概况
诸广山岩体(图 1)呈巨型岩基产出，总出露面积大于2500km2，是一个主要由加里东期(420~435Ma)、印支期(225~240Ma)和燕山期(150~165Ma)花岗岩组成的复式花岗岩体[21-23, 25]。该复式岩体被北东向南雄断裂带和热水-遂川断裂带所夹持[26]。区内发育北东向、北西向和近东西向基性岩脉，成岩年龄集中在~140Ma、~105Ma和~90Ma[27]。龙华山岩体南部是南雄盆地，该盆地的形成与盆地-山体系统演化主要由诸广山花岗岩穹隆和区域伸展构造控制[28]，对邻近区域铀矿床如棉花坑和书楼坵的形成起到重要作用[29]。诸广山地区是中国重要的花岗岩型铀矿床聚集地，该地区产有多个铀矿田，如长江、百顺、城口[30]。这些铀矿床多产于花岗岩区域内北东向主干断裂附近以及伴生的次级硅化碎裂带中，铀矿石矿物以沥青铀矿为主，成矿年龄集中于110~50Ma[26, 31-32]，成矿温度集中在120~260℃，盐度一般小于10% NaCleqv[29]。龙华山岩体位于诸广山复式岩体的东南端，出露面积约265km2，该岩体产有231铀矿床(图 1)，是该地区的一个重要产铀花岗岩。该岩体主要由黑云母花岗岩组成，锆石U-Pb年龄为225.0±2.7Ma，铝饱和指数(A/CNK)为1.08~1.27，铀含量为10.7~44.7μg/g(平均值为27.8μg/g)，岩石地球化学表明该岩体属于S型花岗岩[20, 23]。
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2. 实验部分
2.1 样品采集及处理
本次研究所用样品采自龙华山岩体的地表露头和钻孔岩心。样品主要由石英(35%~40%)、钾长石(30%~35%)、斜长石(25%~30%)、黑云母(5%~8%)和少量白云母(＜2%)等矿物组成。选取代表性样品磨制成EPMA薄片，然后对薄片进行EPMA背散射观察、成分测试以及元素面扫描分析。
2.2 样品分析测试
EPMA分析在中国地质科学院矿产资源研究所EPMA实验室完成。采用日本电子JOEL公司生产的JXA-8230电子探针对样品进行微区观察与定量分析，定量分析测试条件为：加速电压15kV，束流20nA，束斑大小1~5μm[24]。所用标准样品和分光晶体为：硬玉(Na：TAP；Al：TAP；Si：PETJ)；镁橄榄石(Mg：TAP)；黄玉(F：TAP)；硅灰石(Ca：PETH)；赤铁矿(Fe：LIF)；磷灰石(P：PETJ)；UO2(U：PETH)；PbCO4(Pb：PETH)；ThO2(Th：PETH)。稀土元素标样为合成稀土五磷酸盐。元素面扫描分析所用测试条件为：加速电压15kV，束流100nA，停留时间50ms。
3. 结果与讨论
3.1 独居石蚀变晕圈特征及成因
3.1.1 独居石蚀变晕圈结构与成分特征
龙华山岩体岩性为黑云母花岗岩(图 2a)，岩体中独居石颗粒大小为50~150μm，呈半自形至自形。背散射图像显示位于造岩矿物颗粒之间的独居石常常具有蚀变晕圈结构，由内到外可分为独居石带、磷灰石带、褐帘石-绿帘石(图 2中b~f)。①独居石带：独居石位于蚀变晕圈的中心，一些独居石含有锆石和钍石包体(图 2b)；②磷灰石带：该带位于蚀变晕圈的幔部，磷灰石保留着独居石的原始形状，这说明磷灰石可能直接替代独居石。磷灰石中含有许多微小矿物包体，能谱分析显示该包体是富钍矿物，一些富钍矿物呈细脉状充填于最外带的褐帘石和绿帘石中(图 2c)，甚至造岩矿物颗粒边界(图 2d)；③褐帘石-绿帘石带：该带位于蚀变晕圈最外部，在背散射图像中该带具有不同的背散射强度，即具有明显明暗变化(图 2中b~d)。能谱与EPMA分析显示明亮区域为褐帘石成分，暗色区域为绿帘石，褐帘石与绿帘石的空间分布无明显规律。一些独居石与锆石共生，靠近锆石一端未出现蚀变晕圈(图 2e)。图 2f显示，该独居石颗粒部分包裹于磷灰石中，而没有被磷灰石包裹的下端部分发生了蚀变。
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图 2 龙华山岩体手标本和独居石蚀变晕圈照片a—钻孔岩心照片；b~d—独居石(Mnz)蚀变晕圈背散射照片，独居石被磷灰石(Ap)、富钍矿物、褐帘石(Aln)和绿帘石(Ep)部分替代；e—与锆石(Zrn)共生的独居石，靠近锆石一侧未出现蚀变晕圈现象；f—部分包裹于磷灰石中的独居石。Figure 2. Photographs of hand specimen samples and alteration coronas of monazite from the Longhuashan granite. a—Hand specimen photographs of samples collected from drill cores within the Longhuashan granite; b, c, d—Backscattered electron images of monazite (Mnz) alteration coronas consisting of apatite (Ap), Th-rich minerals, allanite (Aln), and epidote (Ep); e—Monazite alteration coronas showing no alteration coronas near zircons (Zrn); f—Monazite partly enclosed in apatite龙华山岩体中独居石蚀变晕圈矿物(独居石、磷灰石、绿帘石、褐帘石)和晶质铀矿代表性EPMA分析结果见表 1。独居石主要由P2O5(27.96%~30.62%)、轻稀土元素(La2O3+Ce2O3+Pr2O3+Nd2O3+Sm2O3=48.91%~61.39%)和ThO2(4.66%~10.96%)组成，含有少量的CaO(0.24%~2.25%)、SiO2(0.14%~1.11%)和Y2O3(0.93%~2.20%)。独居石的UO2含量为0.05%~0.47%。磷灰石主要由P2O5(32.06%~36.01%)和CaO(42.29%~46.07%)组成，含有较高的ThO2(8.35%~12.13%)。
表 1 龙华山花岗岩中独居石蚀变晕圈矿物(包括独居石、磷灰石、绿帘石、褐帘石)和晶质铀矿代表性电子探针分析结果Table 1. Representative EPMA chemical compositions of monazite alteration coronas (including monazite, apatite, epidote, and allanite) and uraninite from the Longhuashan granite矿物 独居石(%) 磷灰石(%) 绿帘石(%) 褐帘石(%) 晶质铀矿(%) 点1 点2 点3 点1 点2 点1 点2 点3 点1 点2 点3 点1 点2 点3 CaO 1.38 0.47 2.25 42.29 46.07 16.38 16.78 15.61 10.89 11.83 12.76 0.00 0.01 0.00 P2O5 29.50 29.10 30.60 32.06 36.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 ThO2 9.23 8.53 10.00 12.13 8.35 0.00 0.10 0.00 0.18 0.14 0.14 1.01 1.16 1.06 La2O3 12.03 11.23 10.67 0.26 0.05 1.76 1.50 2.13 3.76 5.12 5.65 0.00 0.00 0.02 Ce2O3 24.32 26.02 22.78 0.62 0.47 6.25 7.75 7.41 12.75 11.36 11.09 0.11 0.00 0.00 Nd2O3 7.50 7.72 6.97 0.29 0.27 0.97 0.88 1.08 2.89 2.68 1.36 0.00 0.02 0.00 Pr2O3 7.17 8.66 7.27 0.73 0.48 1.55 1.12 1.42 2.93 2.56 2.51 0.00 0.02 0.06 Sm2O3 3.42 1.90 1.21 0.10 0.01 0.74 0.62 0.69 1.01 0.92 0.89 0.24 0.00 0.00 Dy2O3 2.41 1.51 2.58 0.37 0.00 0.47 0.81 0.54 0.71 0.58 0.81 0.00 0.00 0.00 Lu2O3 0.34 0.00 0.30 0.38 0.14 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Y2O3 0.93 1.03 1.84 0.05 0.01 0.70 0.97 1.08 0.39 0.27 0.34 0.09 0.16 0.42 UO2 0.06 0.05 0.47 0.49 0.16 0.00 0.00 0.02 0.08 0.02 0.03 92.25 91.66 95.09 F 0.62 0.80 0.63 3.82 3.89 0.00 0.00 0.02 0.10 0.29 0.00 0.00 0.00 0.00 SiO2 0.73 1.03 0.40 3.63 2.54 33.57 32.88 33.77 31.68 31.87 32.05 0.00 0.00 0.04 Al2O3 0.00 0.00 0.00 0.00 0.00 21.76 21.63 21.76 18.05 19.31 19.68 0.00 0.00 0.00 FeO 0.00 0.00 0.00 0.00 0.00 9.40 8.83 9.49 11.74 10.83 10.14 0.09 0.00 0.00 MgO 0.00 0.00 0.00 0.00 0.00 0.04 0.06 0.06 0.08 0.10 0.06 0.01 0.00 0.00 PbO 0.03 0.00 0.05 0.08 0.07 0.00 0.00 0.00 0.00 0.00 0.00 2.78 2.78 2.85 总和 99.65 98.04 98.03 97.31 98.52 93.60 93.94 95.06 97.22 97.89 97.50 96.57 95.81 99.54 年龄(Ma) - - - - - - - - - - - 222 223 221 注：“-”表示未进行化学年龄计算。 褐帘石主要由CaO(10.89%~12.76%)、Al2O3(18.05%~19.68%)、SiO2(31.68%~32.05%)、FeO(10.14%~11.74%)，以及轻稀土元素(La2O3+Ce2O3+Pr2O3+Nd2O3+Sm2O3=21.50%~23.34%)组成。褐帘石的ThO2含量为0.14%~0.18%，UO2含量为0.02%~0.08%。相对于褐帘石，绿帘石具有较高的CaO(13.45%~16.78%)、Al2O3(20.43%~21.76%)、SiO2(32.71%~33.77%)，以及较低的轻稀土元素(La2O3+Ce2O3+Pr2O3+Nd2O3+Sm2O3=10.75%~14.52%)。
EPMA元素面扫描可以为独居石在后期蚀变过程中元素变化行为提供直观证据(图 3)。结果表明独居石主要由LREE、P和Ca组成。LREE在蚀变过程中具有相似地球化学行为，幔部磷灰石带LREE元素含量很低，而外部褐帘石-绿帘石带具有较高的LREE含量。幔部磷灰石带具有较高的Ca、P和F含量，Th在磷灰石带局部富集。图 3f表明磷灰石带中富钍矿物的存在，并且磷灰石也含有一定含量的Th。图 3g显示U在内部独居石带和幔部磷灰石带分布不均匀，这与独居石的UO2含量变化范围较大一致。幔部磷灰石中的富钍矿物包体具有较高的U含量，表明U在蚀变过程中可能优先进入富钍矿物中。
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图 3 龙华山花岗岩中独居石蚀变晕圈元素面扫描图像a—独居石蚀变晕圈背散射图像；b~i—独居石蚀变晕圈元素面扫描图像，显示La、Ce、Ca、P、Th、U、F、Si分布规律。Figure 3. Elemental maps of alteration coronas of monazite from the Longhuashan granite. a—Backscattered electron image of alteration coronas of monazite; b-i—Elemental maps of alteration coronas of monazite showing distributions of La, Ce, Ca, P, Th, U, F and Si3.1.2 独居石蚀变晕圈成因
龙华山岩体中独居石在后期流体改造下形成由磷灰石、褐帘石、绿帘石和富Th矿物组成的蚀变晕圈，该现象类似于阿尔卑斯山角闪岩相花岗片麻岩和斯洛伐克Western Carpathians花岗质岩石中独居石蚀变特征[13-14]。质量平衡计算(表 2)表明阿尔卑斯山角闪岩相花岗片麻岩中独居石蚀变晕圈的形成可以简单地解释为独居石被部分溶蚀，并有额外的Ca、Fe、Al和Si等元素加入，主要与变质流体有关[13]。类似地，为探讨龙华山岩体中独居石蚀变晕圈成因，本文对其进行了质量平衡计算，结果如表 2所示。
表 2 龙华山花岗岩中独居石蚀变晕圈质量平衡计算结果Table 2. Results of mass balance calculations of alteration coronas of monazite from the Longhuashan granite元素 本文(%) 文献[13](%) 1 2 3 4 5 6 7 8 P2O5 9.16 9.16 31.70 29.90 7.96 7.96 30.37 28.45 SiO2 25.07 - - 0.70 27.26 - - 0.43 La2O3 2.98 2.98 10.32 11.45 3.24 3.24 12.37 12.66 Ce2O3 7.88 7.88 27.27 24.80 6.86 6.86 26.18 26.70 Pr2O3 1.80 1.80 6.23 7.68 0.98 0.98 3.74 3.67 Nd2O3 1.60 1.60 5.55 7.76 2.95 2.95 11.24 11.93 Sm2O3 0.65 0.65 2.24 2.44 0.66 0.66 2.51 2.42 Dy2O3 0.56 0.56 1.95 1.77 - - - - Lu2O3 0.07 0.07 0.24 0.19 - - - - Y2O3 0.37 0.37 1.28 1.47 0.68 0.68 2.61 2.24 ThO2 2.85 2.85 9.86 8.07 1.94 1.94 7.40 7.85 UO2 0.11 0.11 0.38 0.19 0.15 0.15 0.58 0.42 Al2O3 14.78 - - - 16.26 - - - FeO 8.04 - - - 7.13 - - - CaO 21.57 - - 1.21 21.39 - - 1.44 MgO 0.09 - - - 0.32 - - - F 1.14 - - 0.68 - - - 总和 98.72 28.02 97.00 98.31 97.78 25.43 97.00 98.20 注：第1列表示根据磷灰石、褐帘石、绿帘石所占体积和平均成分计算得到的这三个矿物的混合成分；第2列是指第1列元素成分减去SiO2、Al2O3、FeO、CaO、MgO、F的元素含量；第3列是指把第2列元素含量归一化为97%的标准化含量；第4列是指测试所得的独居石元素平均含量。第5、6、7、8列所代表的含义分别同第1、2、3、4列。“-”表示低于检出限。 首先利用背散射图像对蚀变晕圈不同带中磷灰石、褐帘石和绿帘石所占体积进行统计，结果分别为30%(包括富Th矿物)、45%、25%。磷灰石、褐帘石和绿帘石的平均密度为3.3g/cm3、4.2g/cm3、3.5g/cm3。表 2的第1列显示蚀变晕圈中SiO2+Al2O3+FeO+CaO+MgO含量为69.56%。这些元素通常在独居石中含量很低，除去这些元素(包括F)，其他元素含量为28.02%。将第2列独居石中其他元素(La、Ce、Pr、Nd、Sm、Dy、Y、Th、U、P)含量归一化为97%。对比第3列和第4列可以看出，归一化的元素含量与利用EPMA测试独居石所得数据比较接近。质量平衡计算表明，28.02%独居石成分在蚀变过程中进入蚀变晕圈，这与统计的蚀变晕圈中磷灰石所占比例(30%)接近，这说明独居石蚀变可能是由磷灰石直接替代，并且独居石蚀变过程中所释放的元素(如LREE、Th和U)几乎都在蚀变晕圈中富集[13]。
在龙华山岩体中，发生蚀变的独居石主要赋存于主要造岩矿物之间，而包裹在磷灰石中的独居石没有发生蚀变(图 2)。矿物颗粒边界、裂隙以及黑云母节理有利于流体运移[1, 33]。蚀变晕圈中SiO2+Al2O3+FeO+CaO+MgO含量为69.56%，F含量为1.14%，这表明蚀变晕圈的形成需要有额外的Si、Ca、Fe、Mg、F等元素的加入。这些元素可能是龙华山花岗岩中长石和黑云母蚀变所释放的[14]。独居石由于具有较高的CaO为1.21%，因此独居石可能也贡献部分Ca。独居石的[PO4]四面体似乎直接用于形成磷灰石，而独居石释放的LREE进入磷灰石、褐帘石和绿帘石晶体。独居石释放的Th和U主要在磷灰石带富集，形成磷灰石和富钍矿物。总之，独居石在蚀变过程中，磷灰石直接替代独居石，LREE、Y、Th和U等元素被释放，这些元素受到扩散作用影响，同时流体带入Ca、Fe、Al、F等元素，最终形成了由磷灰石、褐帘石、绿帘石和富钍矿物组成的蚀变晕圈。
3.2 晶质铀矿化学成分与U-Th-Pb年龄计算
龙华山岩体中的晶质铀矿主要以包体形式赋存于主要造岩矿物如黑云母和长石中，颗粒大小为20~100μm，呈半自形至自形(图 4a)。本文利用EPMA对该岩体中新鲜晶质铀矿进行成分分析。晶质铀矿的UO2含量为91.66%~95.09%，ThO2含量为0.45%~1.18%，PbO含量为2.68%~2.93%，Y2O3含量为0.08%~0.42%。(SiO2+CaO+FeO)含量很低，小于0.1%(表 1)。本文利用ChemAge软件[34]对晶质铀矿进行化学年龄计算，化学年龄变化范围为210~228Ma，加权平均值为222±7Ma(MSWD=0.16)(图 4b)。
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图 4 龙华山岩体中晶质铀矿(a)背散射图像和(b)化学年龄加权平均值Figure 4. (a) Backscattered electron image and (b) weighted mean chemical age of uraninite from the Longhuashan granite3.3 独居石蚀变晕圈对铀成矿的指示意义
独居石由于可以含有较高的铀含量，因此它常常被认为是形成热液铀矿床重要的成矿物质提供者[4, 8-11]。虽然独居石是华南产铀花岗岩中常见的含铀矿物，但是该矿物能否为花岗岩型铀矿床的形成提供铀源值得进一步研究。通过质量平衡计算表明，龙华山岩体中独居石平均含量为606.2μg/g，独居石中铀含量占全岩铀总量的3.7%。本文研究表明龙华山花岗岩中独居石的蚀变部分约占整个独居石的30%，独居石在蚀变过程中虽然铀发生活化，但活化的铀主要在蚀变晕圈中富集，也就是独居石中的铀只是发生了局部活化。因此，龙华山岩体中独居石对区域花岗岩型铀矿床的形成可能仅提供有限的铀源。
龙华山岩体中的含铀副矿物除了独居石，还有晶质铀矿、锆石和磷灰石[20]。本文利用EPMA分析获得锆石和磷灰石的UO2平均含量分别为0.23%和0.01%。质量平衡计算表明，锆石和磷灰石对全岩铀含量的贡献约为0.6μg/g和0.4μg/g。通常锆石和磷灰石化学性质相对稳定，该岩体中这两个矿物均未发生明显蚀变，因此锆石和磷灰石不是有效的铀源矿物。造岩矿物中的铀含量一般占全岩铀总量的比例低于5%[1]。因此，龙华山岩体中有80%以上的铀赋存于晶质铀矿。龙华山花岗岩具有较高的U含量(平均为27.8μg/g)，较低的Th/U比值(平均1.62)和REE/U比值(平均11.62)，这些特征都是晶质铀矿结晶的有利因素[20]。晶质铀矿是EPMA化学定年的理想对象[20, 24, 35-39]，而Si、Ca、Fe等杂质元素含量是评价晶质铀矿U-Th-Pb体系在结晶后是否被改造的有效工具[39]。龙华山晶质铀矿具有很低的(SiO2+CaO+FeO)含量(＜0.1%)。因此，晶质铀矿的U-Th-Pb体系在结晶后没有发生改造，其化学年龄可以代表晶质铀矿的结晶年龄。EPMA化学定年获得龙华山岩体中晶质铀矿的化学年龄分别为222±7Ma(图 4b)。该年龄与龙华山岩体中锆石U-Pb年龄225±2.7Ma[23]一致，表明晶质铀矿是岩浆结晶。晶质铀矿相对其他矿物容易被浸泡溶解[40]，元素面扫描图像为铀从晶质铀矿中活化、迁移提供了证据[20]。综上，晶质铀矿是龙华山岩体中最重要的铀载体，是形成区域花岗岩型铀矿床最重要的铀源。
4. 结论
本文利用EPMA对粤北龙华山花岗岩中独居石蚀变晕圈开展结构特征与矿物化学研究。独居石蚀变晕圈是从内到外由独居石、磷灰石(包括富钍矿物)和褐帘石-绿帘石构成的同心环带。独居石部分蚀变释放REE、Th、U，而Ca、Fe、Al、F等元素被流体带入形成蚀变晕圈。晶质铀矿的化学年龄为222±7Ma，为岩浆结晶。EPMA面扫描图像显示独居石蚀变导致铀发生活化，但铀主要在蚀变晕圈中富集。研究数据显示龙华山岩体中仅3.7%的铀赋存于独居石中，而80%以上的铀赋存在晶质铀矿中。本文研究表明独居石对龙华山地区铀矿化贡献的成矿物质有限，晶质铀矿是龙华山岩体最重要的铀源矿物。
组成独居石蚀变晕圈的矿物通常尺寸较小，而EPMA具有高空间分辨率等优点，因此EPMA是研究含铀副矿物蚀变特征与矿物化学的有效手段，EPMA面扫描分析可以为铀从源岩中活化、迁移提供直接证据。独居石是华南产铀花岗岩中常见的含铀副矿物, 理解龙华山产铀花岗岩中独居石在蚀变过程中详细的结构和成分演化规律，对解译花岗岩型铀矿床中铀活化与富集过程具有重要意义。
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图 1 研究区地质简图及采样点位图
Qhal—第四系冲积物；Qhpl—第四系洪积物；J3w2—维美组二段；J3w1—维美组一段；J2z2—遮拉组二段；J2z1—遮拉组一段；J1-2l2—陆热组二段；J1-2l1—陆热组一段；J1r—日当组；T3n3—涅如组三段；T3n2—涅如组二段；T3n1—涅如组一段；βμ—辉绿岩脉。
Figure 1. Geological sketch and sampling point map of the study area. The black dots represent the topsoil sampling sites, the red triangles represent the vertical profile locations, and the blue lines represent the study area.
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图 2 研究区表层土壤硒空间分布图
Figure 2. Spatial distribution characteristics of topsoil selenium concentration in the study area. Dark green represents the selenium-enriched soil, which accounts for 77.25% of the total area of the study area; the light green color represents the soil with sufficient selenium, which accounts for 22.75% of the total area of the study area.
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图 3 土壤垂向剖面硒含量特征
Figure 3. Soil vertical profile Se content characteristics. The abscissa represents the soil Se content and the ordinate represents the profile depth. The content of Se in soil decreases with the increase of soil depth.
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图 4 有机质含量与有效硒含量和有效硒/总硒比值散点图
Figure 4. Scatter diagrams of organic matter content to available selenium and available selenium/total selenium ratio. (a) Correlation between organic matter and available selenium content; (b) Correlation between organic matter and the ratio of available selenium to total selenium. There is a positive correlation between soil organic matter content and available selenium content and the ratio of available selenium to total selenium. The dashed black line represents the trend line.
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图 5 有效硒与(a) N、(b) 碱解氮、(c) P、(d) 速效磷散点图
Figure 5. Scatterplot of available selenium with (a) N, (b) alkali-hydrolyzable N, (c) P and (d) available P. (a) Correlation between available selenium and nitrogen content; (b) Correlation between available selenium and alkali-hydrolyzable N content; (c) Correlation between available selenium and phosphorus content; d) Correlation between available selenium and available phosphorus content. Soil available selenium is positively correlated with N, P, alkali-hydrolyzable N and available P.
表 1 土壤样品分析方法及检出限
Table 1 Analytical methods and detection limit for soil samples
分析指标 分析方法 样品处理方法 检出限要求
(mg/kg)检出限
(mg/kg)方法依据 Se 原子荧光光谱法(AFS) 王水加热消解，盐酸浸提 0.01 0.01 WHCS-FF-CS/04—2019 有效硒 原子荧光光谱法(AFS) 沸水浸取 - 0.0005 WHCS-FF-CS/22—2019 有机质 容量法(VOL) 浓硫酸加热消解 0.17 0.034 NY/T 1121.6—2006 pH 离子选择性电极法(ISE) 无二氧化碳水浸取 0.1 0.1* WHCS-FF-CS/19—2019 TFe2O3 电感耦合等离子体发射光谱法(ICP-OES) 四酸加热消解，盐酸浸提 0.05 0.02 WHCS-FF-CS/02—2019 N 元素分析仪法(EA) 固体燃烧 20 15 WHCS-FF-CS/12—2019 P 电感耦合等离子体发射光谱法(ICP-OES) 粉末压片 10 4.3 WHCS-FF-CS/02—2019 碱解氮 容量法(VOL) 碱解-扩散 - 1 LY/T 1228—2015 速效磷 电感耦合等离子体发射光谱法(ICP-OES) 中碱性：碳酸氢钠浸取；
酸性：氟化铵-盐酸浸取0.25 0.2 LY/T 1232—2015 速效钾 电感耦合等离子体发射光谱法(ICP-OES) 乙酸铵浸取 1.25 1 LY/T 1234—2015 阳离子交换量
(CEC)容量法(VOL) 乙酸铵浸取 2.5 1** LY/T 1243—1999 注：“*”单位为无量纲；“**”单位为cmol/kg；“-”无检出限值。 
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表 2 表层土壤地球化学参数特征
Table 2 Characteristics of geochemical parameters for surface soil
分析指标 最小值 最大值 平均值 中位数 标准离差 变化系数 Se(mg/kg) 0.14 1.51 0.45 0.44 0.10 0.23 有效硒(μg/kg) 0.79 26.80 9.20 8.80 3.56 0.39 有机质(%) 0.37 10.50 2.53 2.45 1.03 0.41 pH 5.81 8.86 8.22 8.32 0.41 0.05 TFe2O3(%) 3.53 14.00 7.06 6.88 0.99 0.14 N(mg/kg) 489.00 4412.00 1822.81 1792.00 571.10 0.31 P(mg/kg) 289.00 1728.00 839.03 832.00 193.97 0.23 碱解氮(mg/kg) 10.00 472.00 100.99 93.80 49.61 0.49 速效磷(mg/kg) 0.66 94.30 10.96 7.51 10.00 0.91 速效钾(mg/kg) 6.00 794.00 111.15 80.00 89.00 0.80 西藏土壤硒(mg/kg) 0.04 0.37 0.15 0.14 / 0.48 中国表层土壤硒(mg/kg) 0.00 49.60 0.26 0.21 0.22 0.80 注：西藏土壤硒含量数据引自《西藏土壤元素背景值及其分布特征》(成廷鏊等，1993)；中国表层土壤硒含量数据引自《中国土壤地球化学参数》(侯青叶等，2020)。
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表 3 研究区不同地层分布区土壤中硒参数统计
Table 3 Statistics of selenium parameters in soils of different stratigraphic distribution areas in the study area
地层 样品数量 硒含量最小值
(mg/kg)硒含量最大值
(mg/kg)硒含量算术平均值
(mg/kg)硒含量中位数
(mg/kg)标准差
(mg/kg)变异系数 涅如组三段(T3n3) 110 0.22 1.03 0.43 0.42 0.11 0.25 涅如组二段(T3n2) 317 0.22 1.51 0.46 0.44 0.14 0.31 涅如组一段(T3n1) 28 0.24 0.77 0.47 0.45 0.12 0.26 日当组(J1r) 401 0.14 1.35 0.43 0.41 0.11 0.27 陆热组(J1-2l) 8 0.28 0.73 0.50 0.49 0.15 0.31 第四系(Qh) 711 0.14 0.72 0.45 0.45 0.07 0.15 辉绿岩(βμ) 9 0.14 0.46 0.37 0.44 0.11 0.30 花岗斑岩(γπ) 3 0.39 0.49 0.45 0.48 0.06 0.12 比马组(K1b)* 23 0.08 0.22 0.12 0.12 0.03 0.23 宋热岩组(T3s)* 78 0.15 0.71 0.34 0.29 0.13 0.40 典中组(E1d)* 24 0.10 0.44 0.23 0.22 0.09 0.42 注：“*”数据来源于西藏乃东区重点耕地区1:5万土地质量地球化学调查数据。
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表 4 不同土地利用方式土壤硒地球化学参数
Table 4 Geochemical parameters of selenium concentration in soils with different land use types
用地类型 样品数量 硒含量最小值
(mg/kg)硒含量最大值
(mg/kg)硒含量算术平均值
(mg/kg)硒含量中位数
(mg/kg)标准差
(mg/kg)变异系数 水浇地 860 0.26 0.98 0.45 0.44 0.07 0.17 旱地 20 0.38 0.58 0.47 0.46 0.05 0.11 天然牧草地 424 0.14 1.51 0.43 0.41 0.16 0.37 人工牧草地 81 0.26 0.74 0.44 0.43 0.08 0.18 灌木林地 115 0.25 0.65 0.45 0.46 0.07 0.15 其他林地 37 0.33 0.63 0.46 0.45 0.09 0.18 乔木林地 40 0.32 0.55 0.45 0.45 0.05 0.11 沼泽草地 6 0.33 0.7 0.53 0.52 0.14 0.27 内陆滩涂 4 0.33 0.43 0.4 0.42 0.05 0.12
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表 5 土壤有效硒和CEC与氮、磷等指标相关关系
Table 5 Correlation between soil available selenium and CEC and N, P and other indicators
指标 样品数量 氮 磷 有机质 碱解氮 有效磷 速效钾 有效硒 有效硒 1587 0.591** 0.406** 0.528** 0.538** 0.385** 0.500** 1 CEC 130 0.749** 0.649** 0.785** 0.601** 0.383** 0.431** 0.446** 注: “**”表示在置信度(双测)为0.01时，相关性是显著的。
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