BCR®-701: a review of 10-years of sequential extraction analyses.

Anal Chim Acta

Geomorphology Laboratory, Department of Geography, University of Hawaii at Manoa, 2424 Maile Way, Honolulu, HI 96822, USA.

Published: November 2010

A detailed quantitative analysis was performed on data presented in the literature that focused on the sequential extraction of cadmium (Cd), chromium (Cr), copper (Cu), nickel (Ni), lead (Pb) and zinc (Zn) from the certified reference material BCR-701 (lake sediment) using the three-step harmonized BCR(®) procedure. The accuracy of data reported in the literature, including precision and different measures of trueness, was assessed relative to the certified values for BCR-701. Forty data sets were accepted following extreme outlier removal, and statistically summarized with measures of central tendency, dispersion, and distribution form. In general, literature data were similar in their measurement precision to the expert laboratories used to certify the trace element contents in BCR-701. The overall median precision for literature reported data was 10% (range 6-19%), compared to certifying laboratories of 9% (range 4-33%). One measure of literature data trueness was assessed via a confirmatory approach using a robust bootstrap method. Only 22% of the comparisons indicated significantly different (all were lower) concentrations reported in the literature compared to certified values. The question of whether the differences are practically significant for environmental studies is raised. Bias was computed as a measure of trueness, and literature data were more frequently negatively biased, indicating lower concentrations reported in the literature for the six trace elements for the three-step sequential procedure compared to the certified values. However, 95% confidence intervals about the average bias for the 18 comparisons indicated only four instances when a mean bias of 0 (i.e., measured=certified) was not incorporated-suggesting statistical difference. Finally, Z-scores incorporating a Horwitz-type function were used to assess the general trueness of laboratory data. Of the 468 laboratory Z-score values computed, 92% were considered to be satisfactory, 5% were questionable, and 3% were unsatisfactory. A detailed examination of the methodology sections of the various studies showed that despite claiming adherence to the harmonized BCR sequential extraction protocol, significant deviations were commonly observed; particularly in moisture correction, sample mass, centrifugation specifics, shaking specifics, and incorporation of filtration. It is likely that failure to strictly adhere to the protocol adversely impacted accuracy, by increasing the degree of imprecision and resulting in more discrepant trueness values.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.aca.2010.09.016DOI Listing

Publication Analysis

Top Keywords

sequential extraction
12
reported literature
12
certified values
12
literature data
12
data
8
literature
8
trueness assessed
8
comparisons indicated
8
lower concentrations
8
concentrations reported
8

Similar Publications

Recognizing the action of plastic bag taking from CCTV video footage represents a highly specialized and niche challenge within the broader domain of action video classification. To address this challenge, our paper introduces a novel benchmark video dataset specifically curated for the task of identifying the action of grabbing a plastic bag. Additionally, we propose and evaluate three distinct baseline approaches.

View Article and Find Full Text PDF

Enhancing Manufacturing Precision: Leveraging Motor Currents Data of Computer Numerical Control Machines for Geometrical Accuracy Prediction Through Machine Learning.

Sensors (Basel)

December 2024

Intelligent Manufacturing Laboratory, Production Engineering Institute, Faculty of Mechanical Engineering, University of Maribor, Smetanova ulica 17, 2000 Maribor, Slovenia.

Direct verification of the geometric accuracy of machined parts cannot be performed simultaneously with active machining operations, as it usually requires subsequent inspection with measuring devices such as coordinate measuring machines (CMMs) or optical 3D scanners. This sequential approach increases production time and costs. In this study, we propose a novel indirect measurement method that utilizes motor current data from the controller of a Computer Numerical Control (CNC) machine in combination with machine learning algorithms to predict the geometric accuracy of machined parts in real-time.

View Article and Find Full Text PDF

Conventional Fourier domain Optical Coherence Tomography (FD-OCT) systems depend on resampling into a wavenumber () domain to extract the depth profile. This either necessitates additional hardware resources or amplifies the existing computational complexity. Moreover, the OCT images also suffer from speckle noise, due to systemic reliance on low-coherence interferometry.

View Article and Find Full Text PDF

Predictive Maintenance and Fault Detection for Motor Drive Control Systems in Industrial Robots Using CNN-RNN-Based Observers.

Sensors (Basel)

December 2024

Department of Computer Science and Engineering, Intelligent Robot Research Institute, Sun Moon University, Asan 31460, Republic of Korea.

This research work presents an integrated method leveraging Convolutional Neural Networks and Recurrent Neural Networks (CNN-RNN) to enhance the accuracy of predictive maintenance and fault detection in DC motor drives of industrial robots. We propose a new hybrid deep learning framework that combines CNNs with RNNs to improve the accuracy of fault prediction that may occur on a DC motor drive during task processing. The CNN-RNN model determines the optimal maintenance strategy based on data collected from sensors, such as air temperature, process temperature, rotational speed, and so forth.

View Article and Find Full Text PDF

A Novel Eco-Friendly Process for the Synthesis and Purification of Ascorbyl-6-Oleates.

Foods

December 2024

Department of Marine Bio Food Science, Gangneung-Wonju National University, 7 Jukheon-gil, Gangneung 25457, Gangwon-do, Republic of Korea.

Commercial ascorbyl-6-O-esters (AEs) are composed of saturated fatty acids with relatively high melting points, resulting in limited solubility in lipophilic media. Therefore, a lipase-catalysed synthesis and purification method for ascorbyl-6-O-oleate (AO) was proposed in this study. The esterification synthesis (i.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!