水中总磷测量的不确定度评定

采用钼酸铵分光光度法测定水中总磷的含量，分析该法测量不确定度的来源，评定水中总磷的测量不确定度。     

水质铜测定的不确定度评定

根据火焰原子吸收分光光度法测定水中铜的含量，分析了测量不确定度的主要来源，即标准曲线不确定度、标准溶液不确定度、测量重复性不确定度。计算得到水中铜的测定结果的合成不确定度为0．098mg／L，扩展不确定度为0．196mg/L。     

平皿计数法测定细菌总数的不确定度评定

根据细菌总数的测定方法,分析了该方法测量不确定度的来源,评定了水中细菌总数的测量不确定度。     

重铬酸钾法测定水中COD的不确定度分析

建立了重铬酸钾法测定水中化学需氧量的相对合成标准不确定度的数学模式,应用一个较高浓度的实例,对B类不确定度的分量作了详尽的分析和计算,得出测量扩展不确定度的结果。     

水中阴离子表面活性剂的测量不确定度评定

简要介绍了测量不确定度的概念，运用《测量不确定度评定与表示》的技术规范，通过对阴离子表面活性剂的测定过程，分析了影响阴离子表面活性剂测量不确定度的因素，给出了相对标准不确定度分量，并具体阐明了测量不确定度的评定步骤，得出测量扩展不确定度的结果。     

地下水矿化度测定的不确定度评定

分析质量法测量地下水矿化度的测量不确定度来源，评定了地下水矿化度的测量不确定度，在各不确定度中，称量引入的不确定度较大。     

水中放射性核素铯-137测量的不确定度评估

放射性核素利用化学载带、浓缩后进行测量,化学前处理步骤比较复杂,通过分析测量实验中的不确定度和分析计算公式中的有关参数,了解到分析水中放射性核素铯-137时,主要受到样品测量、仪器探测效率、样品化学回收率和样品取样体积等方面的不确定度因素的影响。     

用离子色谱仪测定水中的氟的不确定度

根据测量不确定度评定与表示理论,用离子色谱仪测定水中的氟的不确定度,通过推导和计算,得出该法测定水中的氟的扩展不确定度U95=0．31mg／L,υeff=174。为有关部门提供参考。     

气相色谱-质谱法测定水中挥发性有机物的测量不确定度评定

根据测量不确定度评定与表示理论，采用气相色谱一质谱法测定水中挥发性有机物。以氯乙烯为例，通过计算和评定，得出当氯乙烯的测量结果为4．99μg／L时，取包含因子k=2（约95％置信概率），扩展不确定度U=0．96μg／L。该不确定度评定方法在实际工作中具有较强的实用价值。     

纳氏试剂分光光度法测定水中氨氮的不确定度评定

通过纳氏试剂分光光度法测定水中氨氮的过程分析，对测定不确定度作出了评估，并得出产生测定不确定度的主要原因。     

Uncertainty associated with the gravimetric measurement of particulate matter concentration in ambient air

This work applied a propagation of uncertainty method to typical total suspended particulate (TSP) sampling apparatus in order to estimate the overall measurement uncertainty. The objectives of this study were to estimate the uncertainty for three TSP samplers, develop an uncertainty budget, and determine the sensitivity of the total uncertainty to environmental parameters. The samplers evaluated were the TAMU High Volume TSP Sampler at a nominal volumetric flow rate of 1.42 m³ min^–1 (50 CFM), the TAMU Low Volume TSP Sampler at a nominal volumetric flow rate of 17 L min^–1 (0.6 CFM) and the EPA TSP Sampler at the nominal volumetric flow rates of 1.1 and 1.7 m³ min^–1 (39 and 60 CFM). Under nominal operating conditions the overall measurement uncertainty was found to vary from 6.1 x 10^–6 g m^–3 to 18.0 x 10^–6 g m^–3, which represented an uncertainty of 1.7% to 5.2% of the measurement. Analysis of the uncertainty budget determined that three of the instrument parameters contributed significantly to the overall uncertainty: the uncertainty in the pressure drop measurement across the orifice meter during both calibration and testing and the uncertainty of the airflow standard used during calibration of the orifice meter. Five environmental parameters occurring during field measurements were considered for their effect on overall uncertainty: ambient TSP concentration, volumetric airflow rate, ambient temperature, ambient pressure, and ambient relative humidity. Of these, only ambient TSP concentration and volumetric airflow rate were found to have a strong effect on the overall uncertainty. The technique described in this paper can be applied to other measurement systems and is especially useful where there are no methods available to generate these values empirically.

Implications:?This work addresses measurement uncertainty of TSP samplers used in ambient conditions. Estimation of uncertainty in gravimetric measurements is of particular interest, since as ambient particulate matter (PM) concentrations approach regulatory limits, the uncertainty of the measurement is essential in determining the sample size and the probability of type II errors in hypothesis testing. This is an important factor in determining if ambient PM concentrations exceed regulatory limits. The technique described in this paper can be applied to other measurement systems and is especially useful where there are no methods available to generate these values empirically.     

滴定法测定的不确定度评定——以EDTA法测定水中钙镁为例

用测量不确定度表示检测结果是当前国际上约定做法，然而如何对测量结果的不确定度进行合理评定，一直是困扰检测实验室的一个难题。作者依据测量不确定度的评定原则，通过实例，简要地阐述了滴定法测量不确定度评定方法，对环境检测领域测量不确定度的评定具有借鉴意义。     

An uncertainty analysis of mean flow velocity measurements used to quantify emissions from stationary sources

Point velocity measurements conducted by traversing a Pitot tube across the cross section of a flow conduit continue to be the standard practice for evaluating the accuracy of continuous flow-monitoring devices. Such velocity traverses were conducted in the exhaust duct of a reduced-scale analog of a stationary source, and mean flow velocity was computed using several common integration techniques. Sources of random and systematic measurement uncertainty were identified and applied in the uncertainty analysis. When applicable, the minimum requirements of the standard test methods were used to estimate measurement uncertainty due to random sources. Estimates of the systematic measurement uncertainty due to discretized measurements of the asymmetric flow field were determined by simulating point velocity traverse measurements in a flow distribution generated using computational fluid dynamics. For the evaluated flow system, estimates of relative expanded uncertainty for the mean flow velocity ranged from ±1.4% to ±9.3% and depended on the number of measurement locations and the method of integration.

Implications:Accurate flow measurements in smokestacks are critical for quantifying the levels of greenhouse gas emissions from fossil-fuel-burning power plants, the largest emitters of carbon dioxide. A systematic uncertainty analysis is necessary to evaluate the accuracy of these measurements. This study demonstrates such an analysis and its application to identify specific measurement components and procedures needing focused attention to improve the accuracy of mean flow velocity measurements in smokestacks.     

Estimation of uncertainty arising from different soil sampling devices: the use of variogram parameters

In the frame of the international SOILSAMP project, funded and coordinated by the National Environmental Protection Agency of Italy (APAT), uncertainties due to field soil sampling were assessed. Three different sampling devices were applied in an agricultural area using the same sampling protocol. Cr, Sc and Zn mass fractions in the collected soil samples were measured by k(0)-instrumental neutron activation analysis (k(0)-INAA). For each element-device combination the experimental variograms were calculated using geostatistical tools. The variogram parameters were used to estimate the standard uncertainty arising from sampling. The sampling component represents the dominant contribution of the measurement uncertainty with a sampling uncertainty to measurement uncertainty ratio ranging between 0.6 and 0.9. The approach based on the use of variogram parameters leads to uncertainty values of the sampling component in agreement with those estimated by replicate sampling approach.     

Estimate of the uncertainty in measurement for the determination of mercury in seafood by TDA AAS

An approach for the estimate of the uncertainty in measurement considering the individual sources related to the different steps of the method under evaluation as well as the uncertainties estimated from the validation data for the determination of mercury in seafood by using thermal decomposition/amalgamation atomic absorption spectrometry (TDA AAS) is proposed. The considered method has been fully optimized and validated in an official laboratory of the Ministry of Agriculture, Livestock and Food Supply of Brazil, in order to comply with national and international food regulations and quality assurance. The referred method has been accredited under the ISO/IEC 17025 norm since 2010. The approach of the present work in order to reach the aim of estimating of the uncertainty in measurement was based on six sources of uncertainty for mercury determination in seafood by TDA AAS, following the validation process, which were: Linear least square regression, Repeatability, Intermediate precision, Correction factor of the analytical curve, Sample mass, and Standard reference solution. Those that most influenced the uncertainty in measurement were sample weight, repeatability, intermediate precision and calibration curve. The obtained result for the estimate of uncertainty in measurement in the present work reached a value of 13.39%, which complies with the European Regulation EC 836/2011. This figure represents a very realistic estimate of the routine conditions, since it fairly encompasses the dispersion obtained from the value attributed to the sample and the value measured by the laboratory analysts. From this outcome, it is possible to infer that the validation data (based on calibration curve, recovery and precision), together with the variation on sample mass, can offer a proper estimate of uncertainty in measurement.     

Estimation of measurement uncertainty associated to the determination of pesticide residues: a case study

In the analytical analysis the measurement uncertainty is a quantitative indicator of the confidence describing the range around a reported or experimental result within which the true value can be expected. Several approaches can be used to estimate the measurement uncertainty associated to the analysis of pesticide residues: a) the top-down, the estimation can be referred to default values; b) the bottom-up the estimation is related to the uncertainty sources. Concerning the bottom-up approach, the following contributions have been investigated: weight of sample, calibration solutions, final volume of sample and intermediate repeatability studies. The commodity/residue combination selected in this study was celery/tau-fluvalinate pesticide. Tau-fluvalinate is a broad-spectrum insecticide in the pyrethroid class of pesticides. The Maximum Residue Limit (MRL) of tau-fluvalinate in celery has been set at 0.01 mg/kg. The tau- Fluvalinate showed two chromatographic peaks. Since the individual standards are not available, the two peaks were integrated separately and the instrumental responses were added. The total residue was calculated on the basis of resulted peaks. The present work aims to compare the uncertainty estimated by experimental data using repeated analysis (n = 12) of a real sample and a spiked sample. The relative expanded uncertainty for two data set, incurred and spiked, was 22 % and 20 %, respectively. No differences were observed from repeated determinations of real samples and spiked samples.