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The high‐precision δ60/58Ni values of twenty‐six geological reference materials, including igneous rocks, sedimentary rocks, stream sediments, soils and plants are reported. The δ60/58Ni values of all samples were determined by double‐spike MC‐ICP‐MS (Nu Plasma III). Isotope standard solution (NIST SRM 986) and geological reference materials (BHVO‐2, BCR‐2, JP‐1, PCC‐1, etc.) were used to evaluate the measurement bias and intermediate precision over a period of six months. Our results show that the intermediate precision of Ni isotope determination was 0.05‰ (2s, n = 69) for spiked NIST SRM 986 and typically 0.06‰ for actual samples, and the δ60/58Ni NIST SRM 986 values were in excellent agreement with previous studies. Eighteen high‐precision Ni isotope ratios of geological reference materials are first reported here, and their δ60/58Ni values varied from ?0.27‰ to 0.52‰, with a mean of 0.13 ± 0.34‰ (2s, n = 18). Additionally, SGR‐1b (0.56 ± 0.04‰, 2s), GSS‐1 (?0.27 ± 0.06‰, 2s), GSS‐7 (?0.11 ± 0.01‰, 2s), GSD‐10 (0.46 ± 0.06‰, 2s) and GSB‐12 (0.52 ± 0.06‰, 2s) could potentially serve as candidate reference materials for Ni isotope fractionation and comparison of Ni isotopic compositions among different laboratories.  相似文献   
3.
Accurate pesticide exposure estimation is integral to epidemiologic studies elucidating the role of pesticides in human health. Humans can be exposed to pesticides via residential proximity to agricultural pesticide applications (drift). We present an improved geographic information system (GIS) and remote sensing method, the Landsat method, to estimate agricultural pesticide exposure through matching pesticide applications to crops classified from temporally concurrent Landsat satellite remote sensing images in California. The image classification method utilizes Normalized Difference Vegetation Index (NDVI) values in a combined maximum likelihood classification and per-field (using segments) approach. Pesticide exposure is estimated according to pesticide-treated crop fields intersecting 500 m buffers around geocoded locations (e.g., residences) in a GIS. Study results demonstrate that the Landsat method can improve GIS-based pesticide exposure estimation by matching more pesticide applications to crops (especially temporary crops) classified using temporally concurrent Landsat images compared to the standard method that relies on infrequently updated land use survey (LUS) crop data. The Landsat method can be used in epidemiologic studies to reconstruct past individual-level exposure to specific pesticides according to where individuals are located.  相似文献   
4.
Cd Te量子点具有荧光强度高和稳定性好的优点,应用Cd Te量子点荧光猝灭法分析基体复杂的样品,需要有效分离对测定干扰的金属元素和高效富集待测元素。本文以巯基乙酸(TGA)作稳定剂,采用水相合成法制备了巯基乙酸修饰的Cd Te量子点,基于镍离子在p H=10.0硼砂缓冲溶液中对Cd Te量子点的荧光具有较强猝灭作用,建立了一种测定赤泥中痕量镍的荧光光度方法。荧光猝灭反应的最佳实验条件为:Cd Te量子点的浓度3.0×10-4mol/L,反应温度为室温,反应时间10 min,在此条件下镍离子浓度在2.0×10-7~7.8×10-5mol/L范围内与Cd Te量子点的相对荧光强度呈良好的线性关系;方法检出限为1.5×10-7mol/L。本方法针对Fe3+、Co2+、Cu2+等主要基体金属元素允许量低的问题,采用25%的2-羟基-4-仲辛氧基二苯甲酮肟(N530)磺化煤油萃取回收滤液中的Ni2+,镍回收率达到99%以上;赤泥中痕量镍的测定结果与催化光度法相符,加标回收率为98.3%-104.2%。  相似文献   
5.
随着常规镍来源的硫化镍矿资源的日益枯竭,可直接生产氧化镍、镍锍和镍铁等产品的红土镍矿倍受关注。对于红土镍矿中主量、次量、痕量元素的检测,相同的检测项目存在多种测试方法,且部分相同原理的测试方法存在细节上的差异,使得检测者选择合适的检测方法变得困难。本文综述了近年来红土镍矿中24种元素测定的样品前处理方式及分析技术研究进展。样品前处理方式依据目标元素及后续的分析方法进行选择,其中酸溶法和碱熔法用途最广。酸溶法引入的盐分少,操作简单,但是分解过程中易导致挥发元素As、Sb、Bi、Hg的损失,Cr易随高氯酸冒烟损失。碱熔法分解能力强,适合分析Cr、Si、全铁等项目,但会引入大量的盐类和因坩埚材料损耗而带入其他杂质,给后续分析带来困难。红土镍矿的分析技术依据实验室条件及目标元素的性质和浓度进行选择。电感耦合等离子体发射光谱法(ICP-AES)是主量、次量元素的主要分析方法,适合于分析含量为10-5~30%级别的金属元素;X射线荧光光谱法主要用于分析含量为10-3~1级别的元素,尤其适合于测定Al、Si、Ti、V和P,由于该方法的准确性依赖于一套高质量的标准样品,故更适合炉前检测或检测大批红土镍矿样品。电感耦合等离子体质谱法(ICP-MS)最适合于分析10-4含量以下的重元素,特别是稀土和贵金属元素。原子吸收光谱法(AAS)适合于分析10-4~10-2级别的Ca、Mg、Ni、Co、Zn、Cr、Mn等低沸点、易原子化元素。分光光度法主要用于分析Ni和P。原子荧光光谱法(AFS)主要用于分析As、Bi、Sb等易形成气态氢化物的元素。容量法主要用于分析Al、Fe、Mg和Si O2等主含量元素。尽管AAS、分光光度法、AFS法和容量法检测周期长,但所用仪器为实验室常规配置,可满足缺乏相应大型仪器实验室的日常检测。本文认为,针对各种检测方法的适用性及存在问题,应从开发微波消解法、固体进样直接测汞法、ICP-MS法以及Cr与其他元素同时分析的快速分析方法等方面开展研究,建立灵敏、准确的检测方法,从而更好地服务于红土镍矿的贸易、检验和综合利用。  相似文献   
6.
In the assessment of potentially contaminated land, the number of samples and the uncertainty of the measurements (including that from sampling) are both important factors in the planning and implementation of an investigation. Both parameters also effect the interpretation of the measurements produced, and the process of making decisions based upon those measurements. However, despite their importance, previously there has been no method for assessing if an investigation is fit‐for‐purpose with respect to both of these parameters. The Whole Site Optimised Contaminated Land Investigation (WSOCLI) method has been developed to address this issue, and to allow the optimisation of an investigation with respect to both the number of samples and the measurement uncertainty, using an economic loss function. This function was developed to calculate an ‘expectation of (financial) loss’, incorporating costs of the investigation itself, subsequent land remediation, and potential consequential costs. To allow the evaluation of the WSOCLI method a computer program ‘OCLISIM’ has been developed to produce sample data from simulated contaminated land investigations. One advantage of such an approach is that as the ‘true’ contaminant concentrations are created by the program, these values are known, which is not the case in a real contaminated land investigation. This enables direct comparisons between functions of the ‘true’ concentrations and functions of the simulated measurements. A second advantage of simulation for this purpose is that the WSOCLI method can be tested on many different patterns and intensities of contamination. The WSOCLI method performed particularly well at high sampling densities producing expectations of financial loss that approximated to the true costs, which were also calculated by the program. WSOCLI was shown to produce notable trends in the relationship between the overall cost (i.e., expectation of loss) and both the number of samples and the measurement uncertainty, which are: (a) low measurement uncertainty was optimal when the decision threshold was between the mean background and the mean hot spot concentrations. (b) When the hot spot mean concentration is equal to or near the decision threshold, then mid‐range measurement uncertainties were optimal. (c) When the decision threshold exceeds the mean of the hot spot, mid‐range measurement uncertainties were optimal. The trends indicate that the uncertainty may continue to rise if the difference between hot spot mean and the decision threshold increases further. (d) In any of the above scenarios, the optimal measurement uncertainty was lower if there is a large geochemical variance (i.e., heterogeneity) within the hot spot. (e) The optimal number of samples for each scenario was indicated by the WSOCLI method, and was between 50 and 100 for the scenarios considered generally; although there was significant noise in the predictions, which needs to be addressed in future work to allow such conclusions to be clearer.  相似文献   
7.
An in situ, medium‐resolution LA‐ICP‐MS method was developed to measure the abundances of the first‐row transition metals, Ga and Ge in a suite of geological materials, namely the MPI‐DING reference glasses. The analytical protocol established here hinged on maximising the ablation rate of the ultraviolet (UV) laser system and the sensitivity of the ICP‐MS, as well minimising the production of diatomic oxides and argides, which serve as the dominant sources of isobaric interferences. Non‐spectral matrix effects were accounted for by using multiple external calibrators, including NIST SRM 610 and the USGS basaltic glasses BHVO‐2G, BIR‐1G and BCR‐2G, and utilising 43Ca as an internal standard. Analyses of the MPI‐DING reference glasses, which represent geological matrices ranging from basaltic to rhyolitic in composition, included measurements of concentrations as low as < 100 μg g?1 and as high as > 104 μg g?1. The new data reported here were found to statistically correlate with the ‘preferred’ reference values for these materials at the 95% confidence level, though with significantly better precision, typically on the order of ≤ 3% (2sm). This analytical method may be extended to any matrix‐matched geological sample, particularly oceanic basalts, silicate minerals and meteoritic materials.  相似文献   
8.
For mineral resource assessment, techniques based on fuzzy logic are attractive because they are capable of incorporating uncertainty associated with measured variables and can also quantify the uncertainty of the estimated grade, tonnage etc. The fuzzy grade estimation model is independent of the distribution of data, avoiding assumptions and constraints made during advanced geostatistical simulation, e.g., the turning bands method. Initially, fuzzy modelling classifies the data using all the component variables in the data set. We adopt a novel approach by taking into account the spatial irregularity of mineralisation patterns using the Gustafson–Kessel classification algorithm. The uncertainty at the point of estimation was derived through antecedent memberships in the input space (i.e., spatial coordinates) and transformed onto the output space (i.e., grades) through consequent membership at the point of estimation. Rather than probabilistic confidence intervals, this uncertainty was expressed in terms of fuzzy memberships, which indicated the occurrence of mixtures of different mineralogical phases at the point of estimation. Data from different sources (other than grades) could also be utilised during estimation. Application of the proposed technique on a real data set gave results that were comparable to those obtained from a turning bands simulation.  相似文献   
9.
Here we report uranium and thorium isotopic ratios and elemental concentrations measured in solid reference materials from the USGS (BHVO‐2G, BCR‐2G, NKT‐1G), as well as those from the MPI‐DING series (T1‐G, ATHO‐G). Specifically created for microanalysis, these naturally‐sourced glasses were fused from rock powders. They cover a range of compositions, elemental concentrations and expected isotopic ratios. The U‐Th isotopic ratios of two powdered source materials (BCR‐2, BHVO‐2) were also characterised. These new measurements via multi‐collector thermal ionisation mass spectrometry and multi‐collector inductively coupled plasma‐mass spectrometry can now be used to assess the relative performance of techniques and facilitate comparison of U‐Th data amongst laboratories in the geoscience community for in situ and bulk analyses.  相似文献   
10.
Ría de Vigo is a river valley flooded by the sea, with a bay (San Simón Bay) at its innermost part. The accumulation of Holocene sediment in San Simón Bay has been studied by the integration of 1) large scale high resolution seismic data, and 2) detailed geochemical analysis of a gravity core. In San Simón Bay the majority of the seismic records are obscured by acoustic turbidity which represents gassy sediments, but on records from Rande Strait it is possible to distinguish two Quaternary seismic sequences; an Upper Pleistocene sequence (SQ1) and a Holocene sequence (SQ2). Only SQ2 is recognized in San Simón Bay where it is comprised of two seismic units; the upper unit represents the HST sediment, i.e. the period of highest sea level. A gravity core taken within the gassy zone at 10 m water depth provided 3.55 m of fine-grained sediments (muds) from the youngest seismic unit (4 m thick). Geochemical analysis show high values (4 to 10%) of TOC. Sediment and porewater analyses indicate a distinct sulphate–methane transition zone (SMTZ) between 60 and 80 cm where sulphate is depleted (to <1.7 mM) and methane increases (to >0.4 mM). The top of the acoustic turbidity (the gas front) at 80 cm corresponds to the lower limit of the SMTZ. The methane cannot have been derived from the underlying metamorphic and granitic rocks, but was probably derived by microbial degradation of the organic matter in the Holocene sediments. We estimate that the sediments of the Bay contain approximately 1.8 × 106 m3 of organic carbon and 275 ton of methane.  相似文献   
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