Cadmium Bioavailability Based on Diffusive Gradients in Thin Films Technique and Conventional Chemical Extraction in High Geological Background Soil Area of Northwestern Zhejiang Province, China
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摘要:
地质高背景区相较于人类活动引起的土壤镉污染影响范围更广，在区域尺度上对生态系统和人类健康构成危害。土壤镉生物有效性是决定其生物可利用性、生物毒性的关键因素，因此探寻可行的土壤镉生物有效性评价方法对污染农用地安全利用和风险管控具有重要的理论和实际意义。DGT技术、单一提取法、连续提取法和土壤溶液法常用于测定土壤有效镉，但已有研究成果主要基于同种土地利用类型土壤的室内盆栽实验，难以代表自然污染土壤中的复杂情况。为探明各土壤重金属有效态提取技术对地质高背景区不同土地利用类型土壤Cd生物有效性评估效果，本文以浙江西北部土壤Cd高地质背景区水田土壤-水稻籽实和旱地土壤-小白菜样品为研究对象，实验应用DGT技术、单一提取法（0.01mol/L氯化钙提取）、连续提取法（七步连续提取）和土壤溶液法评价土壤中镉生物有效性。结果显示：①研究区水田和旱地土壤Cd平均含量分别为1.07mg/kg和0.73mg/kg，显著高于浙江和全国土壤平均水平，Cd的异常富集主要与浙西北地区广泛分布的黑色岩系有关。②相较于碳酸盐岩区，黑色岩系区土壤中Cd的生物有效组分占比较高，水田和旱地土壤Cd的活动系数（MF）高达59.9%和51.8%，Cd易在土壤-作物系统中发生迁移富集；③植物体内镉含量Cd-P与不同方法测定的有效镉含量均呈显著正相关，但Cd-P与DGT技术测定的有效镉含量相关性优于其他三种方法，水田土壤测得的有效Cd与水稻籽实相关关系：$ {{C}}_{\text{soln}} $>CDGT>$ {{C}}_{{\text{CaCl}}_{\text{2}}} $>$ {{C}}_{{\text{F}}_{\text{1}}\text{+}{\text{F}}_{\text{2}}\text{+}{\text{F}}_{\text{3}}} $，旱地土壤测得的有效Cd与小白菜相关关系：CDGT >$ {{C}}_{{\text{CaCl}}_{\text{2}}} $>$ {{C}}_{{\text{F}}_{\text{1}}\text{+}{\text{F}}_{\text{2}}\text{+}{\text{F}}_{\text{3}}} $>$ {{C}}_{\text{soln}} $。综合比较不同土壤有效Cd测定方法的优缺点，DGT技术可以模拟植物体对Cd的动态吸收过程，更能准确地反映土壤Cd生物有效性，预测作物Cd含量水平，这与已有研究成果一致。此外，本文研究成果表明DGT技术评价土壤Cd生物有效性，不仅适用于人为污染区，也可应用于地质高背景区。
Abstract:BACKGROUNDHigh geochemical background has a greater impact on soil Cd pollution than human activities and is more detrimental to the environment and human health on a regional level. Research shows that the bioavailability of Cd in soil is the key factor to determine its bioavailability and biotoxicity, so it is of great theoretical and practical significance to find an effective method to evaluate the bioavailability of Cd in soil for the safe use and risk control of contaminated agricultural land. Single extraction methods with relatively simple operation and relatively low cost and sequential extraction methods providing morphological distribution feature information, are the most common methods for evaluation of heavy metals bioavailability in soil. In general, the available amount of soil heavy metals obtained by chemical extraction methods can better reflect the level of plant absorption than the total amount. However, chemical extraction methods have some drawbacks, including differences between the extraction principle and crop absorption process, a lack of universality in the extracts, redistribution and re-adsorption during the extraction process, and most notably, the failure to take into account dynamic changes in heavy metal concentrations in the root environment. Diffusive gradients in thin-films (DGT) technique is a new biomimetic in-situ sampling technique, which has been widely used to assess the bioavailability of various elements in soil, water, sediment and other environmental media in recent years. The process of DGT absorbing target elements is similar to plants absorption, which can better reflect bioavailability. However, existing research results using DGT to evaluate soil Cd pollution is mainly based on indoor pot experiments. Exogenous addition of heavy metals to contaminated soil not only has high bioavailability, but also reduces the sensitivity of soil pH and other factors to the bioavailability of heavy metals in soil, which does not accurately represent the complex situation in naturally contaminated soil. It is not clear whether the results of DGT can accurately reflect the bioavailability of soil Cd in high geological background areas. In order to confirm whether DGT technology can effectively evaluate the bioavailability of soil Cd in high geochemical background areas when compared to existing chemical extraction methods, 80 sets of paddy soil-rice and 20 sets of dry soil-bok choy samples were collected in the black shale area of Northwest Zhejiang Province. The DGT technology, 0.01mol/L CaCl2 extraction method, seven-step extraction method and soil solution method were used to evaluate the bioavailability of Cd in soil. Inductively coupled plasma-mass spectrometry (ICP-MS) was used to determine Cd content and available Cd in soil and crop. Soil pH was determined by potentiometry (POT), and soil organic matter (OM) was determined by oxidation combustion potentiometry (POT). The migration and accumulation characteristics of Cd in a soil-crop system were analyzed. The evaluation effects of different bioavailability evaluation methods were compared by the correlation between available Cd and crop Cd content.
RESULTS(1) The total content and fraction distribution characteristics of Cd in soil. The results show that the Cd average contents in paddy soil and dry soil in the study area are 1.07mg/kg and 0.73mg/kg, respectively, remarkably higher than the background values of soil in Zhejiang Province and China. The abnormal enrichment of Cd is mainly related to the widespread black shale in Northwest Zhejiang. For the sequential extraction procedures, the average content in paddy soil of water-soluble and exchangeable Cd, carbonate-bound Cd, humic acid-bound Cd, Fe-Mn oxide-bound Cd, strong organic-bound Cd and residual Cd are 54%, 5.9%, 9.3%, 13.5%, 4.2% and 13.2%, respectively. The average content in dry soil of water-soluble and exchangeable Cd, carbonate-bound Cd, humic acid-bound Cd, Fe-Mn oxide-bound Cd, strong organic-bound Cd and residual Cd are 47.2%, 4.6%, 11.5%, 14.3%, 5.5% and 16.9%, respectively. On the whole, the bioavailable component of Cd in the study area accounts for a relatively high proportion. (2) Characteristics of Cd content in crop. The content of Cd in rice seed in the study area ranges from 0.01mg/kg to 3.29mg/kg, with an average of 0.26mg/kg. The Cd content in bok choy ranges from 0.01mg/kg to 0.31mg/kg, with an average of 0.08mg/kg. In comparison to China’s contaminant limit of national food safety standards (GB2762—2017), the over-standard rates of Cd in rice and bok choy are 34% and 10%, respectively. The soil samples are further assessed according to Soil Environmental Quality Risk Control Standard for Soil Contamination of Agricultural Land (GB15618—2018), the Cd over-standard rates of paddy soil and dry soil are 70% and 75%, respectively. The Cd over-standard rate of soil samples is significantly higher than crop samples. Therefore, the bioavailability of Cd in soil should be considered to scientifically evaluate the pollution level of Cd in soil. (3) Assessment of Cd bioavailability in soil by four extraction methods. The DGT technology, 0.01mol/L CaCl2 extraction method, seven-step extraction method and soil solution method are used to evaluate the bioavailability of Cd in soil. The results are as follows: CDGT, $ {{C}}_{{\text{CaCl}}_{\text{2}}} $, $ {{C}}_{{\text{F}}_{\text{1}}\text{+}{\text{F}}_{\text{2}}\text{+}{\text{F}}_{\text{3}}} $ and $ {{C}}_{\text{soln}} $(Fig.3). There is a significant positive correlation between Cd-P and available Cd determined by different methods, but the correlation between CDGT and crop Cd content is better than 0.01mol/L CaCl2 extraction method, seven-step extraction method and soil solution method. The correlation between available Cd in paddy soil and rice are $ {{C}}_{\text{soln}} $>CDGT>$ {{C}}_{{\text{CaCl}}_{\text{2}}} $>$ {{C}}_{{\text{F}}_{\text{1}}\text{+}{\text{F}}_{\text{2}}\text{+}{\text{F}}_{\text{3}}} $. The correlation between available Cd in dry soil and bok choy are CDGT >$ {{C}}_{{\text{CaCl}}_{\text{2}}} $>$ {{C}}_{{\text{F}}_{\text{1}}\text{+}{\text{F}}_{\text{2}}\text{+}{\text{F}}_{\text{3}}} $>$ {{C}}_{\text{soln}} $(Table 3).
DISSCUSION(1) Results of DGT technique. The available Cd (CDGT) content measured by DGT for paddy and dry soil in the study area ranges from 0.02μg/L to 1.69μg/L and from 0.14μg/L to 1.88μg/L, with average values of 0.78μg/L and 0.62μg/L, respectively (Fig.3). The correlation coefficients between CDGT and Cd-P in paddy soil and dry soil are 0.622 and 0.887, respectively (Table 3), which are larger than $ {{C}}_{{\text{CaCl}}_{\text{2}}} $, $ {{C}}_{{\text{F}}_{\text{1}}\text{+}{\text{F}}_{\text{2}}\text{+}{\text{F}}_{\text{3}}} $ and Csoln. The DGT technique is superior to the 0.01mol/L CaCl2 extraction method, seven-step sequential extraction method and soil solution method in reflecting soil Cd bioavailability, and the evaluation effect is not affected by land use types. The DGT technique can be used to simulate Cd release process from soil to solution cased by plant root absorption, and reflects the Cd content in crops more accurately than chemical extraction methods. (2) Results of 0.01mol/L CaCl2 extraction method. The available Cd ($ {{C}}_{{\text{CaCl}}_{\text{2}}} $) content measured by 0.01mol/L CaCl2 extraction method for paddy and dry soil in the study area ranges from 0.07mg/kg to 0.95mg/kg and from 0.08mg/kg to 0.55mg/kg, with average values of 0.58mg/kg and 0.31mg/kg, respectively (Fig.3). The correlation coefficients between $ {{C}}_{{\text{CaCl}}_{\text{2}}} $ and Cd-P in paddy soil and dry soil are 0.583 and 0.795 respectively (Table 3), which shows a good level of correlation. On the whole, its evaluation effect is second only to DGT technology. Studies have shown that $ {{C}}_{{\text{CaCl}}_{\text{2}}} $ solution can effectively replace metal ions adsorbed by soil particles, and the change of soil pH and soil structure has little effect on the replacement rate, giving it a wide range of applications. $ {{C}}_{{\text{CaCl}}_{\text{2}}} $ solution mainly displaces the adsorbed Cd from soil through static ion exchange, and the extracted available Cd is mainly water-soluble and exchangeable Cd, but some bioavailable metals in soil (such as soil particles or unstable organic/inorganic complexes in soil solution) may not be extracted, so the bioavailability of Cd in soil may be underestimated. (3) Results of seven-step extraction method. Compared with the single extraction method, the sequential extraction method provides the speciation characteristics of heavy metals, and can be used to more comprehensively evaluate the mobility, availability and potential toxicity of heavy metals in soil. Water-soluble Cd, exchangeable Cd and carbonate-bound Cd are generally classified as bioavailable components ($ {{C}}_{{\text{F}}_{\text{1}}\text{+}{\text{F}}_{\text{2}}\text{+}{\text{F}}_{\text{3}}} $). The available Cd ($ {{C}}_{{\text{F}}_{\text{1}}\text{+}{\text{F}}_{\text{2}}\text{+}{\text{F}}_{\text{3}}} $) content measured by the seven-step extraction method for paddy and dry soil in the study area ranges from 0.08mg/kg to 3.95mg/kg and from 0.13mg/kg to 1.61mg/kg, with average values of 0.64mg/kg and 0.40mg/kg, respectively (Fig.3). The correlation coefficients between $ {{C}}_{{\text{F}}_{\text{1}}\text{+}{\text{F}}_{\text{2}}\text{+}{\text{F}}_{\text{3}}} $ and Cd-P in paddy soil and dry soil are 0.577 and 0.717 respectively (Table 3), which are lower than 0.01mol/L CaCl2 extraction method and DGT technique. The migration factor (MF) is the relative proportion of the bioavailable components $ {{C}}_{{\text{F}}_{\text{1}}\text{+}{\text{F}}_{\text{2}}\text{+}{\text{F}}_{\text{3}}} $ of Cd in the soil. The MF of Cd in paddy soil and dry soil are as high as 59.9% and 51.8%, respectively, which indicate that Cd is easy to migrate and enrich in the soil-crop system. (4) Results of soil solution method. Soil solution (Csoln) is the main place of substance exchange between plants and soil, so it can indicate the bioavailability of heavy metals in soil. The available Cd (Csoln) content measured by soil solution method for paddy and dry soil in the study area ranges from 0.03μg/L to 2.18μg/L and from 0.15μg/L to 2.9μg/L, with average values of 1.22μg/L and 1.99μg/L, respectively (Fig.3). The correlation coefficient between Csoln and Cd-P in paddy soil is larger than CDGT, $ {{C}}_{{\text{CaCl}}_{\text{2}}} $ and $ {{C}}_{{\text{F}}_{\text{1}}\text{+}{\text{F}}_{\text{2}}\text{+}{\text{F}}_{\text{3}}} $. However, the correlation coefficient in dry soil is the smallest, so the effect of bioavailability evaluation is unstable (Table 3). This is mainly due to the fact that some inert Cd in soil solution cannot be absorbed and utilized by plants, and it is difficult to extract potential available Cd, which has great limitations. (5) A comprehensive evaluation of four extraction methods. Comparing the characteristic and applicability of different methods, DGT technology, single extraction method, sequential extraction method and soil solution method have different application scope and significance, and they all play an irreplaceable role in bioavailability evaluation of soil Cd. There is a significant positive correlation between soil available Cd determined by the four methods and crop Cd, the extraction techniques of soil available Cd can effectively reflect the content level of available Cd in soil. DGT technology can simulate the dynamic absorption process of Cd by plants which can more accurately reflect the bioavailability of Cd in soil. The single extraction method is relatively simple in operation and relatively low in cost, which is mainly used for quickly judging the bioavailability level of Cd in soil. 0.01mol/L CaCl2 is recommended as an extractant for available Cd in soil. The sequential extraction can be used to obtain the speciation characteristics of soil Cd, which focuses on the analysis of available Cd and potentially available Cd in soil. Soil solution can not only reflect the bioavailability of heavy metals, but is also a key parameter for environmental models to predict and quantitatively assess the surface runoff and infiltration of heavy metals in soil.
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X射线荧光光谱定性分析技术经过长期的应用及发展，其应用范围也越来越广泛[1-4]。目前，XRF所带的定性分析软件(SQX)可自动对扫描谱图进行搜索和匹配，包括确定峰位、背景和峰位的净强度[5-7]，并从XRF特征谱线数据库中配对确定元素的谱线，这对从事XRF的分析者而言非常便利[8-10]。近年来刘岩等[11]采用XRF无标样分析法检测催化剂，测定结果的相对标准偏差小于1.3%；张红菊等[12]采用XRF无标样分析法检测轻合金铝合金中的主量元素，其测量值与认定值的相对误差低于±5%，测量结果都具有很好的可靠性和准确度。
自然界矿物种类复杂，应用XRF半定量分析软件(SQX)分析未知样品时，由于SQX软件仅对样品中9F~92U元素进行半定量分析，而对H2O、C这些参数不能直接测定。对于烧失量(LOI)、结晶水(H2O+)含量较高的铝土矿，二氧化碳含量较高的碳酸盐矿物，硫、碳含量较高的硫化物金属矿这类高烧失量矿物样品，平衡归一化计算时对未知样品中的Al2O3、SiO2、CaO、MgO、Fe等主要元素分析结果影响较大，半定量分析数据准确度较低。这就要求XRF分析人员需要掌握未知样品的来源及基本情况，根据测定结果对各元素在样品中的结构状态进行评估，选用更为合理的校正模式，提高半定量分析的准确性[13-15]。为了解决这个问题，本文提出了一种校正模式。该校正模式根据半定量分析初步结果，采用重量法、碘量法、酸碱测定法、红外光谱法有选择性地对未知样品中的LOI、S、C、H2O+等项目进行定量分析，然后将定量分析结果输入SQX该参数的固定结果中，二次平衡归一计算得出新的半定量分析结果。应用该校正模式校正后，铝土矿、碳酸盐矿物、硫化物金属矿等高烧失量矿物的半定量分析结果的准确度得到大幅度提高。
1. 实验部分
1.1 仪器与测量条件
ZSX PrimusⅣ型顺序扫描波长色散X射线荧光光谱仪(日本理学电机工业株式会社)，端窗铑靶X射线管，工作电压20~60kV，工作电流2~160mA，铍窗厚度30μm，视野光栏0.5~30mm，准直器: S2/S4，探测器: PC/SC，分光晶体:RX 25/Ge/PET/LiF200[16-19]。测量元素范围9F~92U。BP-1型压样机(丹东北方科学仪器公司)。各元素具体的测量条件见表 1。
表 1 仪器测量条件Table 1. Measuring conditions of the XRF equipment分析元素 数据库 靶材 电流
(kV)电压
(mA)滤光片 衰减器 准直器 晶体 探测器 PHA 重元素 Standard Rh 50 60 OUT 1/1 S2 LiF(200) SC 100~300 重元素(1) Sta-Ni400 Rh 50 60 Ni-400 1/1 S2 LiF(200) SC 150~250 Ca-Kα Standard Rh 40 75 OUT 1/1 S4 LiF(200) PC 100~300 K-Kα Standard Rh 40 75 OUT 1/1 S2 LiF(200) PC 100~300 Cl-Kα Standard Rh 30 100 OUT 1/1 S4 Ge PC 150~300 S-Kα Standard Rh 30 100 OUT 1/1 S4 Ge PC 150~300 P-Kα Standard Rh 30 100 OUT 1/1 S4 Ge PC 150~300 Si-Kα Standard Rh 30 100 OUT 1/1 S4 PET PC 100~300 Al-Kα Standard Rh 30 100 OUT 1/1 S4 PET PC 100~250 Mg-Kα Standard Rh 30 100 OUT 1/1 S4 RX25 PC 100~250 Na-Kα Standard Rh 30 100 OUT 1/1 S4 RX25 PC 100~250 F-Kα Standard Rh 40 75 OUT 1/1 S4 RX25 PC 100~300 1.2 SQX分析模拟计算流程
XRF半定量分析可选择测定未知样品中F~U或Ti~U之间的元素，分析测试程序完成后会自动报出大于仪检出限的各元素的分析结果，这时应根据测试结果作一个初步判断是否需要进行SQX计算；如不需要，则可以直接报出测定结果；如测定结果与样品实际结构状态有较大差别，则需选用更为合适的校正模式、平衡组分或添加其他方法测试结果后进行SQX计算，以得到更为合理的测定结果。定性分析的基本流程见图 1。
1.3 样品制备及实验方法
为验证本文提出的半定量分析模式分析校正效果，选用国家标准物质铝土矿GBW(E)70036、碳酸盐矿物GBW07131、硫化物多金属矿GBW07166作为待测样品，在105℃下烘干2h，称取4.5±0.1g，倒入放置于平板模具上的PVC塑料环(外径40mm，内径35mm，高5mm)中，在30t压力下加压30s压制成型，编号，置于样品盒内，用X射线荧光光谱仪半定量分析方法进行测试[20-22]。仪器自动计算出各元素的含量。
根据XRF半定量初步分析结果，按化学标准方法YS/T 575.19—2007、GB/T 3286.8—2014、GB/T 3286.7—2014、GB/T 14353.12—2010、GB/T 8151.2—2012、SN/T 3598—2013、GB/T 2469—1996、YS/T 575.18—2007选择性分析未知样品中的烧失量(LOI)、硫(S)、碳(C)、结晶水(H2O+)，计算出定量结果，备用。
将化学分析结果作为XRF半定量分析软件(SQX)中该元素的固定结果，重新进行平衡计算出新的半定量结果。
2. 结果与讨论
2.1 烧失量对铝土矿类型矿物半定量分析结果的影响
铝土矿是一种土状矿物，化学组成为Al2O3·nH2O，含水不定，多为单水或三水矿物[23-24]。由于XRF的局限性，对于H2O、C这些未定量的参数，其含量在铝土矿中较高[25]，平衡归一化计算时会对Al2O3、SiO2、Fe2O3等元素的影响较大。这时可采用烧失量校正的方法，添加烧失量(LOI)作为该样品的固定值，运行半定量分析软件(SQX)重新计算出新的结果。将GBW(E)70036作为未知样品用XRF定性分析方法进行分析，各种校正模式的计算值与认定值对照结果见表 2。
表 2 铝土矿标准物质GBW(E)70036各种校正模式计算值与认定值对比Table 2. Calculated values and standard values of bauxite standard material GBW(E)70036 in various correction models分析元素 氧化物模式测试
结果(%)添加LOI校正结果
(%)H2O作平衡
校正结果(%)GBW(E)70036
认定值(%)氧化物模式测试结果
相对误差(%)LOI校正结果
相对误差(%)MgO 0.136 0.121 0.116 0.120 13.33 0.83 Al2O3 76.94 67.51 64.46 69.74 10.32 -3.20 SiO2 7.91 6.62 6.12 4.88 62.09 35.66 P2O5 0.159 0.132 0.121 0.120 32.50 10.00 SO3 0.182 0.00 0.139 0.047 - - K2O 1.07 0.880 0.810 0.710 50.70 23.94 CaO 0.258 0.212 0.195 0.180 43.33 17.78 TiO2 5.10 4.17 3.81 3.97 28.46 5.04 Fe2O3 7.42 5.97 5.35 6.09 21.84 -1.97 LOI * 13.70 △ 13.74 - - H2O * △ 18.26 - - - 注：“*”表示XRF不能直接分析该参数，无数据；“△”表示在LOI或H2O其中一项参数有测量结果时，另一项结果不参与校正计算；“-”表示未定值或未统计计算。 据表 2可知，GBW(E)70036以氧化物模式的测试结果与认定值误差较大，当添加LOI校正计算后，其多个元素的平均相对误差由32.8%降至12.3%，准确度大幅提高。此外，在确定未知样品是未经高温灼烧的情况下，还可以采用H2O作为平衡组分直接计算，其计算结果也与认定值较为相近。
2.2 二氧化碳与烧失量对碳酸盐类型矿物半定量分析结果的影响
碳酸盐矿物中CO2的占比较高, 而CO2是SQX软件未能定量参数之一，给定性分析结果带来较大误差。为提高定性分析的准确度，可对CO2或烧失量进行定量分析[26]，添加烧失量或CO2定量分析结果作为该样品的固定值，运行SQX重新计算出新的结果。将GBW07131作为未知样品用XRF定性分析方法进行分析，各种校正模式的计算值与认定值对照结果见表 3。
表 3 碳酸盐标准物质GBW07131各种校正模式计算值与认定值对比Table 3. Calculated values and standard values of carbonate standard material GBW07131 in various correction models分析元素 氧化物模式
测试结果(%)CO2平衡
校正结果(%)添加LOI
校正结果(%)钙镁元素以碳酸盐
计平衡计算(%)GBW07131
认定值(%)氧化物模式测试
结果相对误差(%)LOI校正结果
相对误差(%)MgO 29.73 19.57 19.18 20.4 20.14 47.62 4.77 Al2O3 0.759 0.454 0.449 0.451 0.290 161.72 -54.83 SiO2 2.18 1.29 1.27 1.28 1.15 89.57 -10.43 P2O5 0.051 0.030 0.030 0.030 0.016 218.75 -87.50 SO3 0.442 0.256 0.00 0.254 - - - K2O 0.292 0.161 0.160 0.160 0.160 82.50 0.00 CaO 64.54 31.76 32.07 31.50 30.93 108.66 -3.69 TiO2 0.045 0.018 0.0186 0.0178 0.013 246.15 -43.08 MnO 0.038 0.015 0.016 0.011 0.012 216.67 -33.33 Fe2O3 0.435 0.169 0.176 0.167 0.170 155.88 -3.53 CO2 * 45.66 △ - - - - LOI * △ 45.67 - 45.73 - 0.13 注：“*”表示XRF不能直接分析该参数，无数据；“△”表示在LOI或CO2其中一项参数有测量结果时，另一项结果不参与校正计算；“-”表示未定值或未统计计算。 据表 3可知，GBW07131以氧化物模式测试结果较认定值误差较大。当添加LOI校正计算后，其多个元素的平均相对误差由122.4%降至27.2%，准确度大幅提高。此外，采用滴加稀盐酸确定未知样品是碳酸盐矿物的情况下，可以采用CO2作为平衡组分直接计算或者将CaO、MgO换算成为CaCO3、MgCO3计算模式重新平衡计算，其结果也与认定值较为相近。
2.3 碳硫元素对硫化物多金属矿类型矿物半定量分析结果的影响
硫化物多金属矿中的碳、硫元素含量较高，以氧化物模式对该类型样品进行半定量分析时误差较大。当采用化学法测定这类样品的烧失量时，硫化物金属矿中的硫在高温下会被空气中的氧替换，不仅会出现烧蚀减量，还会出现烧蚀增量，使得烧失量的结果是不准确的[27-28]，因此不能把烧失量校作为该未知样品的固定值对测定结果进行平衡计算。这时可以采用化学法测定该未知样品中的C、S元素，作为该样品的固定值，运行半定量分析软件(SQX)重新计算出新的结果。将GBW07166作为未知样品用XRF半定量程序进行分析，各种校正模式的计算值与认定值对照结果见表 4。
表 4 硫化矿多金属矿标准物质GBW07166各种校正模式计算值与认定值对比Table 4. Calculated values and standard values of sulfide polymetallic ore standard material GBW07166 in various correction models分析元素 氧化物模式测试
结果(%)总硫、总碳固定
平衡计算(%)LOI平衡计算
(%)Sulfide模式
校正结果(%)GBW07166
认定值(%)氧化物模式测试
结果相对误差(%)总硫、总碳校正
结果相对误差(%)MgO 0.360 0.350 0.675 0.505 0.310 16.13 12.90 Al2O3 1.60 1.55 3.03 2.29 1.25 28.00 24.00 SiO2 3.34 3.50 6.26 4.86 3.78 -11.64 7.41 S 18.43 33.80 0.00 27.75 33.80 - - K2O 0.306 0.433 0.387 0.484 0.320 -4.38 35.31 CaO 2.05 2.02 2.61 3.27 1.96 4.59 3.06 Fe 18.22 28.58 27.45 30.84 29.60 -38.45 -3.45 Cu 15.50 28.00 30.72 28.42 24.20 -35.95 15.70 Zn 0.025 0.057 0.049 0.055 0.057 -56.14 0.00 C * 0.138 △ - - - - LOI * △ 27.04 - - - - 注：“*”表示XRF不能直接分析该参数，无数据；“△”表示在LOI或C其中一项参数有测量结果时，另一项结果不参与校正计算；“-”表示未定值或未统计计算。 据表 4可知，GBW07166以氧化物模式或添加LOI校正计算结果后，测试结果较认定值误差较大，当添加全硫、全碳校正计算结果后，其多个元素的平均相对误差由27.2%降至9.5%，准确度大幅提高。此外，在没有条件测定全硫、全碳元素时，选用SQX软件中Sulfide校正模式重新平衡计算，其结果也与认定值较为相近。
3. 应用实例
选取3件不同类型的未知样品，应用XRF半定量程序分析，根据XRF半定量初步分析结果，计算对照结果见表 5。未知样品1、2在添加烧失量(LOI)校正计算后半定量分析结果与化学法分析结果比较，多个元素的平均相对误差分别由46.2%降至18.0%和37.6%降至7.1%。未知样品3添加总硫、总碳校正计算结果后，其多个元素的平均相对误差由28.1%降至10%，准确度得到了明显提高。若与DZ/T 130—2006《地质矿产实验室测试质量管理规范》要求定量分析规范中误差允许限(Yc)相比较，除少部分项目能满足规范要求外，大部分项目还是达不到定量分析要求。但是如铝土矿中的Al2O3，碳酸盐矿物中的CaO、MgO，硫化物多金属矿中Fe、Zn、Cu、Pb等元素的相对误差均在5%以内，与DZ/T 130—2006要求较为接近。
表 5 某未知样品各种校正模式的计算值与化学分析值对比Table 5. Calculated values and chemical analysis values of various correction modes for the unknown sample样品编号 分析元素 氧化物模式测试
结果(%)平衡校准计算
结果(%)化学法测定值
(%)氧化物模式测试
结果相对误差(%)平衡校准计算结果
相对误差(%)允许限Yc
(%)Al2O3 86.97 76.11 78.01 11.49 -2.44 0.63 SiO2 2.94 1.82 1.31 124.43 38.93 4.17 Fe2O3 3.26 2.54 2.55 24.84 -0.46 5.11 TiO2 4.29 3.4 3.10 38.38 9.78 4.80 未知样品1 K2O 0.19 0.17 0.16 18.75 6.25 10.45 CaO 0.33 0.31 0.31 6.45 0.00 9.00 MgO 0.29 0.25 0.20 45.00 25.00 9.95 P2O5 0.28 0.22 0.14 100.00 61.37 10.76 LOI * 14.6 14.6 - - 2.58 Na2O 0.76 0.71 0.781 -2.59 -8.72 7.17 MgO 0.29 0.24 0.21 39.14 14.95 9.84 Al2O3 0.48 0.39 0.31 54.13 26.16 9.00 SiO2 1.15 0.93 0.83 38.66 12.45 7.05 P2O5 1.24 1.00 0.97 28.34 2.88 6.77 Fe2O3 1.70 1.21 1.18 44.18 2.13 6.41 未知样品2 S 4.72 △ 3.21 47.04 - 4.74 CaO 1.13 0.81 0.83 36.64 -2.40 7.05 Cr 18.49 13.09 12.89 43.46 1.53 2.75 Ni 22.81 16.18 16 42.55 1.12 2.47 Cu 14.53 10.31 10.33 40.62 -0.23 3.04 Zn 3.04 2.16 2.02 43.24 5.94 5.49 LOI * 37.00 37.00 - - - MgO 0.21 0.200 0.185 14.49 8.11 10.12 Al2O3 0.53 0.472 0.427 23.87 10.61 8.34 SiO2 2.18 1.818 1.650 32.00 10.15 5.83 P2O5 0.02 0.024 0.028 -34.29 -13.21 14.91 S 18.84 34.02 34.02 - - - K2O 0.05 0.048 0.042 15.44 13.31 13.77 未知样品3 CaO 0.15 0.127 0.137 7.72 -7.50 10.81 TiO2 0.03 0.031 0.026 30.98 20.78 15.18 Fe 4.52 6.942 6.720 -32.81 3.31 3.64 Cu 0.68 1.057 1.218 -44.37 -13.18 6.36 Zn 32.24 50.517 48.250 -33.18 4.70 1.15 Pb 1.58 2.505 2.646 -40.46 -5.33 5.05 C * 1.21 1.21 - - - 注：“*”表示XRF不能直接分析该参数，无数据；“△”表示在LOI有测量结果时，该项结果不参与校正计算；“-”表示未定值或未统计计算。 4. 结论
实验证明采用本文提出的校正模式进行校正，分析铝土矿、碳酸盐矿物和硫化物多金属矿中多元素的平均准确度提高了2.6~4.5倍，半定量分析结果准确度大幅提高。其中，铝土矿中的Al2O3，碳酸盐矿物中的CaO、MgO，硫化物矿物中Fe、Zn、Cu、Pb等主量元素的相对误差均在5%以内，与化学法分析结果较为相近。本方法可快速、较为准确地测定铝土矿、碳酸盐矿物和硫化物矿物中多元素的含量。
这种化学法与半定量分析软件相结合的半定量校正模式，不仅可用于铝土矿、碳酸盐矿物和硫化物矿物，还适用于烧失量较高的锰矿、磷矿等矿物的压片半定量分析[29-30]。对于硫化物矿物等多金属矿的定量全分析，因为这类矿物容易腐蚀铂坩埚而很少采用熔片制样XRF分析[31]，通常采用化学分析法，但流程繁琐，本文研究方法可作为一种有效的矿石全分析的补充手段。
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图 1 研究区位置及采样点位示意图
底图数据来源于多目标区域地球化学调查工作。
Figure 1. Location of the study area and sampling sites. The red point is sampling position, the base map shows the distribution characteristics of Cd content in soil, and the data comes from the multi-purpose regional geochemical survey.
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图 2 研究区（a）水田土壤和旱地土壤（b）Cd各形态占总量的比例
Figure 2. Percent distributions among various fractions of soil cadmium in (a) paddy soil and (b) dryland soil. The proportion of bioavailable components of Cd is relatively high.
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图 3 不同方法测定的土壤有效Cd含量特征
a—单一提取法和连续提取法； b—DGT法和土壤溶液法。
Figure 3. Available Cd of Se determined by different methods.
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图 4 不同地区土壤Cd活动系数（MF）
Figure 4. Cd mobility coefficient in different areas. The proportion of bioavailable components of Cd is relatively high in the weathering soil of the black shale area, showing a high biological activity.
表 1 研究区土壤、作物Cd含量及土壤理化性质统计
Table 1 Statistical date of Cd concentrations in soil and crop and soil properties in the study area.
土壤-作物系统 参数 Cd-S Cd-P BCF pH 有机质 水田土壤-水稻籽实
（n=80）最小值 0.18 0.01 0.015 4.9 0.74 最大值 6.61 3.29 1.18 8.0 7.48 平均值 1.07 0.26 0.28 6.1 3.40 标准差 1.27 0.43 0.26 0.8 1.16 变异系数（%） 119 167 94 14 34 旱地土壤-小白菜
（n=20）最小值 0.16 0.01 0.03 4.7 1.68 最大值 2.39 0.31 0.24 6.0 4.80 平均值 0.73 0.08 0.11 5.3 3.37 标准差 0.55 0.08 0.06 0.4 0.71 变异系数（%） 75 99 56 7 21 浙江表层土壤背景值[17] 0.07 - - 5.7[18] 2.26[18] 全国土壤背景基准值[19] 0.14 - - 8.0 1.00 注：Cd-S和Cd-P分别为土壤和作物总Cd含量，单位为mg/kg；BCF、pH值无量纲；有机质含量单位为%。 
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表 2 不同成因Cd污染区水稻籽实生物富集系数（BCF）
Table 2 Bioconcentration factor (BCF) of Cd in rice from different sources.
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表 3 土壤有效Cd与作物Cd含量线性相关系数
Table 3 Relationships between available Cd in soil and Cd concentration in crops.
项目 n CDGT ${{C} }_{ {\text{CaCl} }_{\text{2} } }$ ${{C} }_{ {\text{F} }_{\text{1} }\text{+}{\text{F} }_{\text{2} }\text{+}{\text{F} }_{\text{3} } }$ Csoln Cd-P（水稻籽实） 80 0.622** 0.583** 0.577** 0.634** Cd-P（小白菜） 20 0.887** 0.795** 0.717** 0.635** 注：Cd-P为作物Cd含量；“**”表示P<0.01水平（双侧）极显著相关。
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表 4 土壤有效Cd与土壤pH值和有机质（OM）线性相关系数
Table 4 Relationships between available Cd, pH value and organic matter (OM) in soil.
土壤类型 项目 CDGT $ {{C}}_{{\text{CaCl}}_{\text{2}}} $ $ {{C}}_{{\text{F}}_{\text{1}}\text{+}{\text{F}}_{\text{2}}\text{+}{\text{F}}_{\text{3}}} $ Csoln 水田土壤
（n=80）pH −0.678** 0.154 −0.053 −0.249** 有机质 0.032 0.314** 0.284 −0.126 旱地土壤
（n=20）pH −0.400 0.096 −0.186 −0.515* 有机质 0.241 0.362 0.242 0.160 注：“**”表示P<0.01水平（双侧）极显著相关；“*”表示P<0.05水平（双侧）极显著相关。
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