应用Monte Carlo模拟法探讨分层性物质的组合取样精度

应用MonteCarlo模拟法研究了分层性物质的组合取样精度,探讨了组合样中组分含量的分布规律、组合取样方差的分布规律、组合取样方差估计值的精度与组合样本数目之间的关系等.考察了组分含量服从正态分布、均匀随机分布及多项分布的分层性总体.结果表明,当样本数目较多时,组合取样误差规律对于不同原始分布的总体是相似的.     

渐进取样法及其应用

提出了渐进取样法,通过样本数目的累积,使总方差估计值达到所需的精度。应用Ｍｏｎｔｅ Ｃａｒｌｏ模拟技术考察了满足一定取样精度的样本数目及其偏差。将该方法应用于散装生铁块中Ｓｉ、Ｍｎ、Ｃ、Ｓ、Ｐ含量分析的取样,结果令人满意。该项研究对于大宗货物的实际随机取样具有重要参考价值。     

固体分层取样方案的最优化设计

本文首次从理论上探讨了取得量对分层取样误差的影响,提出了总取样量一定时各层的最佳取样量和最小取样方差的计算公式,从而为分层取样的最佳取样方案设计提供了理论依据。     

组合取样的误差理论研究及其Monte Carlo模拟

基于多项分布理论,建立了组合取样方差与取样总体中各子区的大小及其组分含量之间的关系和计算公式,探讨了组合取样常数的物理意义.以颗粒物质为例,探讨了组合取样的逻辑质量单元的概念及其意义,为确定组合取样中的份样质量提供了理论依据.本文对于完善组合取样误差理论,保证组合取样的质量均具有重要意义.     

铅铋合金中金 、银分析取样方法的研究

围绕取样代表性和样品加工均匀性等问题,研究了铅铋合金锭中金银分析试样加工粒度对金银品位的影响,锭内金银分布及规律。通过对铅铋合金锭中金、银分布情况的研究结果,制定了铅铋合金锭的采样、样品加工及化验分析方案。     

粒状物质的微观均匀度及其对取样误差的影响分析

研究物质的取样属性与以取样误差之间的关系是分析化学取样学的重要内容。从微观角度探讨了物质的理论性质及其对取样误差的影响。以碳化硅为例,考察了粒度分布、组分随粒度的变化以及均匀度因子等,分析了取样误差的来源。首次通过粒度分级成功地对碳化硅进行了分层,并对分层取样和随机取样的误差进行了分析和讨论,为制定合理的取样方案提供了有利的依据。本文的研究方法可适用于所有粒状物质的取样,同时也为分析化学取样学的深     

卜松分布下的实验室样品缩分特性及取样常数K_s确定法的探讨

对于一个由两种不同质的晶粒组成的实验室随机(均质性)样品来说,文献以K_S=R~2·W 来描述其缩分特性规律,即取样相对标准方差 R~2与所缩取的子样重 W 成反比,比例常数 K_S 称实验室样品取样常数。一般认为,这是一个经验规律,且只在所考察的目标组份 X%呈对称(正态)分布下才成立。木文论证了当 X%呈卜松分布即 X%处于痕量组份下,这一规律仍然成立;并在此基础上,进一步完善了卜松分布下的 K_s 确定方法。     

分析测试中取样单元数的确定——关于分析化学教材中取样问题的商榷

对武汉大学主编的《分析化学》（上册）第5版教材中关于取样单元数的计算进行了讨论,指出测量次数与采样单元数是不同的概念,在已知采样单元间的标准偏差估计值和允许误差的情况下,采样单元数应该用试差法求得。     

二元颗粒混合物按质量取样的误差研究

二元颗粒混合物的随机取样方式有两种：一是按颗粒数目取样,二是按质量取样本文对二元颗粒混合物按质量取样的误差进行了深入研究,详细分析了混合物的各种参对被测组分含量取样误差的影响,应用Ｍｏｎｔｅ Ｃａｒｌｏ技术对取样进行了模拟。以颗粒药品的二元混合物为例对按颗粒数目取样和按质量取样的误差进行了比较。此项研究对于分析取样理论和应用具有重要的价值。     

提高碘量法测定天然气中硫化氢效率的方法

碘量法是测定管道输送天然气中硫化氢的一种经典方法,而管道输送天然气中硫化氢含量较低,按照GB/T11060.1–2010方法测定,取样量较大,取样时间长,影响工作效率。针对此问题,从两方面对碘量法进行改进:减小天然气取样量进行试验,并与国标规定取样量时的实验结果进行比对,确定最佳取样量;增大取样流量进行试验,并与国标规定取样流量时的实验结果进行比对,确定最佳取样流量。对硫化氢质量浓度为7.2~14.3,14.3~28.7 mg/m~3的天然气样品进行试验测定,结果表明,将天然气取样量减少为20 L,取样时间分别由200,100 min缩短为40 min;将天然气取样流量设定为750 m L/min,取样时间分别由200,100 min缩短为133,67 min。减少取样量或者提高取样流量,均能缩短管输天然气的取样时间,提高检测效率。     

Estimation of measurement uncertainty by the budget approach for heavy metal content in soils under different land use

A reference database was used for the estimation of the standard uncertainties resulting from sampling, sample preparation, and analysis of soil samples from a target area in Switzerland. This evaluation was based on an extended reference sampling of the Comparative Evaluation of European Methods for Sampling and Sample Preparation of Soils Project. Samples were taken according to the national sampling protocols of 15 European countries and were analyzed for zinc, cadmium, copper, and lead. The combined uncertainty for all laboratories was estimated according to the ISO Guide to the Expression of Uncertainty in Measurement. It was found that the sampling uncertainty was not larger than the analytical uncertainty if more than ten sample increments were taken. The uncertainty due to variation in sampling depth and sample size reduction was only significant under unfavorable conditions. On the basis of an uncertainty budget the sampling protocols can be optimized and a ranking is possible, aimed at conditions that are fit for the specific purpose.Electronic Supplementary Material Supplementary Material is available in the online version of this article at     

Sampling and sampling strategies for environmental analysis

Sampling errors are generally believed to dominate the errors of analytical measurement during the entire environmental data acquisition process. Unfortunately, environmental sampling errors are hardly quantified and documented even though analytical errors are frequently yet improperly reported to the third decimal point in environmental analysis. There is a significant discrepancy in directly applying traditional sampling theories (such as those developed for the binary particle systems) to trace levels of contaminants in complex environmental matrices with various spatial and temporal heterogeneities. The purpose of this critical review is to address several key issues in the development of an optimal sampling strategy with a primary goal of sample representativeness while minimizing the total number of samples and sampling frequencies, hence the cost for sampling and analysis. Several biased and statistically based sampling approaches commonly employed in environmental sampling (e.g. judgmental sampling and haphazard sampling vs. statistically based approaches such as simple random, systematic random, and stratified random sampling) are examined with respect to their pros and cons for the acquisition of scientifically reliable and legally defensible data. The effects of sample size, sample frequency and the use of compositing are addressed to illustrate the strategies for a cost reduction as well as an improved representativeness of sampling from spatially and temporally varied environmental systems. The discussions are accompanied with some recent advances and examples in the formulation of sampling strategies for the chemical or biological analysis of air, surface water, drinking water, groundwater, soil, and hazardous waste sites.     

增量取样量接近分析试样量时的取样——理论修正与结果

化学分析取样几乎总是一个多步骤过程,所有的步骤都会导致分析结果的总体不确定性。样品采取之后,不论后续采样过程如何精细,前期采样阶段的误差都无法在后续采样过程中更正。第一次取样是最重要的,通常其方差远远超过实验室测量的方差。但这不意味着在最终实验室分析试样制备阶段可以忽略采样理论的原理。现代分析仪器旨在处理小样本(从毫克到几克)。在这种情况下,如果样品是包含少量分析物的混合颗粒,则物料的不均匀性可能会很大以至于破坏整个分析过程。不均匀性计算和样品制备过程中基本采样误差方差的估计对于开发适用的分析程序至关重要。在样本制备的最后步骤中,新的增量本是父增量本的重要组成部分,在估算样本方差时必须考虑到这种影响。TOS提供了用于处理这些情况的工具。通过两个案例阐明了不均匀性计算的应用。在第一个例子中,评估了鸡饲料中低含量添加剂的成分不均匀性,在第二个例子中,对样品制备进行了优化,以校正用于分析硅灰石精矿中矿物杂质含量的红外仪器。在处理颗粒混合物和评估混样效率时,不均匀性评估也很重要。     

The Analysis of Air for Acetone Cyanohydrin Using Solid Sorbent Sampling and Gas Chromatography

Abstract

A method for sampling and analysis of airborne acetone cyanohydrin is described. The analyte is collected on Porapak QS, a silylated styrene-divinylbenzene porous polymer. Samples are desorbed with ethyl acetate and analyzed by gas chromatography using a nitrogen-specific detector and a teflon column packed with 5% OV-17 on Chromosorb T. The detection limit is estimated to be 0.1 μg/mL acetone cyanohydrin in ethyl acetate. The method was tested by evaporating from 1.0 to 50 μg of the analyte onto sorbent beds of Porapak QS and exposing the samples to a humidified airstream for 15 min. Quantitative recovery was obtained for samples stored for one day at ambient temperature or for seven days if the samples were refrigerated immediately after collection.     

Calibration of the complex matrix effects on the sampling of polycyclic aromatic hydrocarbons in milk samples using solid phase microextraction

Solid phase microextraction (SPME), a simple, fast and promising sampling technique, has been widely used for complex sample analysis. However, complex matrices could modify the absorption property of coatings as well as the uptake kinetics of analytes, eventually biasing the quantification results. In the current study, we demonstrated the feasibility of a developed calibration method for the analysis of polycyclic aromatic hydrocarbons (PAHs) in complex milk samples. Effects of the complex matrices on the SPME sampling process and the sampling conditions were investigated. Results showed that short exposure time (pre-equilibrium SPME, PE-SPME) could increase the lifetime of coatings, and the complex matrices in milk samples could significantly influence the sampling kinetics of SPME. In addition, the optimized sampling time, temperature and dilution factor for PAHs were 10 min, 85 °C and 20, respectively. The obtained LODs and LOQs of all the PAHs were 0.1–0.8 ng/mL and 1.4–4.7 ng/mL, respectively. Furthermore, the accuracy of the proposed PE-SPME method for milk sampling was validated by the recoveries of the studied compounds in two concentration levels, which ranged from 75% to 110% for all the compounds. Finally, the proposed method was applied to the screening of PAHs in milk samples.     

An experimental approach for the development of direct-absorption sampling method for determination of trimethylsilanol and volatile methylsiloxanes by the GC-MS technique in landfill gas

This paper reports on an absorption method used for the determination of six target volatile methylsiloxanes and trimethylsilanol existing in raw biogas samples by means of a special and portable sampling train system. After biogas sampling (no accurate pump needed), the samples obtained were analysed by gas chromatography-mass spectrometry (GC-MS). The optimisation of the used solvent was carried out, and acetone was selected as the preferred liquid medium for trapping the siloxanes. The results clearly showed that using pure acetone and a mixture of acetone and water (97/3% = v/v) ensures very good solvation of silicon-contained molecules; thus the sampling procedure was more accurate. Replicate samples showed that the relative standard deviation of the method was less than 5.7% and 6.3% for methylsiloxanes as well as less than 2.1% and 2.4% for trimethylsilanol analysed 24 and 72 hours after sampling, respectively. Furthermore, limits of detection were determined theoretically and experimentally. The limits of detection for siloxanes and trimethylsilanol were in the range 0.04–0.11 mg/Nm³ and 0.08–0.12 mg/Nm³, respectively. The limit of quantification for trimethylsilanol was 0.1 mg/Nm³, whereas the limit for siloxanes ranged from 0.1 to 0.13 mg/Nm³. Finally, raw biogas samples were successfully analysed by the developed method. Trimethylsilanol and methylsiloxanes were found in the concentrations of 34.5 mg/Nm³ and 1.7–20 mg/Nm³ in the analysed raw biogas, respectively.     

Quantitative Determination of Formaldehyde In Air Using the Acetylacetone Method

Abstract

The quantitative determination of formaldehyde in air using the fluorimetric acetylacetone method is described. Known concentrations of formaldehyde were generated and collected in water using abosorbers. The sampling rate was 0.5 1/min, and the sampling volumes varied from 2 to 20 1, depending on the concentration level. Under these conditions the entire sampling and the analytical method were evaluated over a range of 0.2–1.7 mg formaldehyde per m³ of air.

The precision of the method expressed as a mean value of the relative standard deviation of 7 independent measurements (6 single determinations each) was (3.4 ± 1.6) % (SD). The accuracy was (101 ± 5) % (SD). The detection limit of the method was estimated to be 0.040 mg formaldehyde per m³ of air (5 liter air sample).