Uncertainty Evaluation of Automatic Monitoring System for Fine Particulate Matter in Ambient Air

Yang Shuo; Pan Zhi Qiang; Wang Dou Wen

doi:doi:10.11648/j.ijmea.20210906.11

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Uncertainty Evaluation of Automatic Monitoring System for Fine Particulate Matter in Ambient Air

Yang Shuo, Pan Zhi Qiang, Wang Dou Wen

Published in International Journal of Mechanical Engineering and Applications (Volume 9, Issue 6)

Received: 26 February 2021 Accepted: 12 March 2021 Published: 29 November 2021

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Abstract

Ambient air fine particulate matter (PM2.5) is a kind of instantaneous variation of space and time that cannot be repeated. In the process of fluid sampling analysis of real-time data, there are too many variables and too fast component changes for the laboratory to undertake such tests. The fast automatic monitoring technology provides real-time measurement consistency and reliability, which is comparable in terms of cost effectiveness technical process optimization and life cycle. In this case, suitable reference gas for PM2.5 (mg/m³) could not be found, so β ray or oscillating balance method (X method) and manual weighing method (Y method, as the primary test method) were respectively used. Moreover, related to the sampling frequency of tolerance limit, discussion is given on the detection power (1-β) for the difference (∆) between the X and Y, for their acceptance probabilistic risk characteristics of operational curve based on the trade-off, and on sample sizes (n) under α and β risks, as well as the acceptable level of the cost of wrong decision. This paper belongs to the research category of unstable samples analysis, and involves the evaluation of two components, u_{r, rel(range)} and u_{R, rel(bat)}. The assessment is based on the overall concept of top-down. All cumulative effects are incorporated into the continuous and closed system as far as possible. Under the premise of ensuring that the acceptable level is under statistical control, reasonable estimates of quality objectives and uncertainties are obtained.

Published in	International Journal of Mechanical Engineering and Applications (Volume 9, Issue 6)
DOI	10.11648/j.ijmea.20210906.11
Page(s)	85-89
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

Automatic Monitoring System, PM2.5, Site Precision, In-statistical-control, Two Types of Risk, 1-β, Anderson Darling (AD), Top-down Uncertainties

References

[1]	ASTM E2554: Standard Practice for Estimating and Monitoring the Uncertainty of Test Results of a Test Method Using Control Chart Techniques, ASTM International, West Conshohocken, PA, 2010, www.astm.org.
[2]	ASTM E2655: Standard Guide for Reporting Uncertainty of Test Results and Use of the Term Measurement Uncertainty in ASTM Test Methods, ASTM International, West Conshohocken, PA, 2010, www.astm.org.
[3]	CNAS-GL022-2018: “Guidance for measurement uncertainty evaluation based on quality control data in environmental testing”.
[4]	Dou Wen Wang, Shao Wei Wang and Si Qi Zhao, “Estimation of the Uncertainty of Fe in Metallic Silicon Determined by Inductively Coupled Plasmas-Atomic Emission Spectroscopy,” Journal of Testing and Evaluation, Vol. 33, NO. 3, 2005, pp. 211-215.
[5]	ASTM D7440: Standard Practice for Characterizing Uncertainty in Air Quality Measurements, ASTM International, West Conshohocken, PA, 2010, www.astm.org.
[6]	ASTM D6299: Standard Practice for Applying Statistical Quality Assurance Techniques to Evaluate Analytical Measurement System Performances, ASTM International, West Conshohocken, PA, 2010, www.astm.org.
[7]	ASTM D6617: Standard Practice for Laboratory Bias Detection Using Single Test Result from Standard Material, ASTM International, West Conshohocken, PA, 2010, www.astm.org.
[8]	D. W. Wang, H. R. Sun, Z. Q. Pan, et al, “Monitoring on the Auto-Analyzer System in-Statistical-Control for SO₂ in Atmosphere with Top-Down Uncertainty Evaluation,” Journal of Testing and Evaluation, Vol. 45, NO. 2, 2017, pp. 703-710.
[9]	RB/T 141-2018: Evaluation of measurement uncertainty in the chemical testing field - Applying quality control and method validation data to evaluate measurement uncertainty.
[10]	ASTM D6708: Standard Practice for Statistical Assessment and Improvement of Expected Agreement Between Two Test Methods that Purport to Measure the Same Property of a Material, ASTM International, West Conshohocken, PA, 2010, www.astm.org.
[11]	ASTM D7235: Standard Guide for Establishing a Linear Correlation Relationship Between Analyzer and Primary Test Method Results Using Relevant ASTM Standard Practices, ASTM International, West Conshohocken, PA, 2010, www.astm.org.
[12]	Sun Hai Rong, Wang Dou Wen, Cao Shi, et al, “Applied on evaluation for traceability of the value of quantity and measurement uncertainty by top-down quality control idea,” China Conformity Assessment, Monthly (Serial No. 208), NO. 8, 2013, pp. 55-59.
[13]	ASTM E2935: Standard Practice for Conducting Equivalence Tests for Comparing Testing Processes, ASTM International, West Conshohocken, PA, 2010, www.astm.org.
[14]	ASTM D6259: Standard Practice for Determination of a Pooled Limit of Quantitation for a Test Method, ASTM International, West Conshohocken, PA, 2010, www.astm.org.
[15]	GB 3095: Ambient air quality standards.
[16]	ASTM E2093: Standard Guide for Optimizing, Controlling and Reporting Test Method Uncertainties from Multiple Workstations in the Same Laboratory Organization, ASTM International, West Conshohocken, PA, 2010, www.astm.org.

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APA Style

Yang Shuo, Pan Zhi Qiang, Wang Dou Wen. (2021). Uncertainty Evaluation of Automatic Monitoring System for Fine Particulate Matter in Ambient Air. International Journal of Mechanical Engineering and Applications, 9(6), 85-89. https://doi.org/10.11648/j.ijmea.20210906.11

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ACS Style

Yang Shuo; Pan Zhi Qiang; Wang Dou Wen. Uncertainty Evaluation of Automatic Monitoring System for Fine Particulate Matter in Ambient Air. Int. J. Mech. Eng. Appl. 2021, 9(6), 85-89. doi: 10.11648/j.ijmea.20210906.11

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AMA Style

Yang Shuo, Pan Zhi Qiang, Wang Dou Wen. Uncertainty Evaluation of Automatic Monitoring System for Fine Particulate Matter in Ambient Air. Int J Mech Eng Appl. 2021;9(6):85-89. doi: 10.11648/j.ijmea.20210906.11

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@article{10.11648/j.ijmea.20210906.11,
  author = {Yang Shuo and Pan Zhi Qiang and Wang Dou Wen},
  title = {Uncertainty Evaluation of Automatic Monitoring System for Fine Particulate Matter in Ambient Air},
  journal = {International Journal of Mechanical Engineering and Applications},
  volume = {9},
  number = {6},
  pages = {85-89},
  doi = {10.11648/j.ijmea.20210906.11},
  url = {https://doi.org/10.11648/j.ijmea.20210906.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijmea.20210906.11},
  abstract = {Ambient air fine particulate matter (PM2.5) is a kind of instantaneous variation of space and time that cannot be repeated. In the process of fluid sampling analysis of real-time data, there are too many variables and too fast component changes for the laboratory to undertake such tests. The fast automatic monitoring technology provides real-time measurement consistency and reliability, which is comparable in terms of cost effectiveness technical process optimization and life cycle. In this case, suitable reference gas for PM2.5 (mg/m3) could not be found, so β ray or oscillating balance method (X method) and manual weighing method (Y method, as the primary test method) were respectively used. Moreover, related to the sampling frequency of tolerance limit, discussion is given on the detection power (1-β) for the difference (∆) between the X and Y, for their acceptance probabilistic risk characteristics of operational curve based on the trade-off, and on sample sizes (n) under α and β risks, as well as the acceptable level of the cost of wrong decision. This paper belongs to the research category of unstable samples analysis, and involves the evaluation of two components, ur, rel(range) and uR, rel(bat). The assessment is based on the overall concept of top-down. All cumulative effects are incorporated into the continuous and closed system as far as possible. Under the premise of ensuring that the acceptable level is under statistical control, reasonable estimates of quality objectives and uncertainties are obtained.},
 year = {2021}
}

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TY  - JOUR
T1  - Uncertainty Evaluation of Automatic Monitoring System for Fine Particulate Matter in Ambient Air
AU  - Yang Shuo
AU  - Pan Zhi Qiang
AU  - Wang Dou Wen
Y1  - 2021/11/29
PY  - 2021
N1  - https://doi.org/10.11648/j.ijmea.20210906.11
DO  - 10.11648/j.ijmea.20210906.11
T2  - International Journal of Mechanical Engineering and Applications
JF  - International Journal of Mechanical Engineering and Applications
JO  - International Journal of Mechanical Engineering and Applications
SP  - 85
EP  - 89
PB  - Science Publishing Group
SN  - 2330-0248
UR  - https://doi.org/10.11648/j.ijmea.20210906.11
AB  - Ambient air fine particulate matter (PM2.5) is a kind of instantaneous variation of space and time that cannot be repeated. In the process of fluid sampling analysis of real-time data, there are too many variables and too fast component changes for the laboratory to undertake such tests. The fast automatic monitoring technology provides real-time measurement consistency and reliability, which is comparable in terms of cost effectiveness technical process optimization and life cycle. In this case, suitable reference gas for PM2.5 (mg/m3) could not be found, so β ray or oscillating balance method (X method) and manual weighing method (Y method, as the primary test method) were respectively used. Moreover, related to the sampling frequency of tolerance limit, discussion is given on the detection power (1-β) for the difference (∆) between the X and Y, for their acceptance probabilistic risk characteristics of operational curve based on the trade-off, and on sample sizes (n) under α and β risks, as well as the acceptable level of the cost of wrong decision. This paper belongs to the research category of unstable samples analysis, and involves the evaluation of two components, ur, rel(range) and uR, rel(bat). The assessment is based on the overall concept of top-down. All cumulative effects are incorporated into the continuous and closed system as far as possible. Under the premise of ensuring that the acceptable level is under statistical control, reasonable estimates of quality objectives and uncertainties are obtained.
VL  - 9
IS  - 6
ER  -

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Author Information

Yang Shuo

Government Office, Shahekou District Government, Dalian, China
Pan Zhi Qiang

Runnig Department, West Pacific Petrochemical Company, Dalian, China
Wang Dou Wen

Technical Center, Dalian Customs, Dalian, China

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APA Style

Yang Shuo, Pan Zhi Qiang, Wang Dou Wen. (2021). Uncertainty Evaluation of Automatic Monitoring System for Fine Particulate Matter in Ambient Air. International Journal of Mechanical Engineering and Applications, 9(6), 85-89. https://doi.org/10.11648/j.ijmea.20210906.11

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ACS Style

Yang Shuo; Pan Zhi Qiang; Wang Dou Wen. Uncertainty Evaluation of Automatic Monitoring System for Fine Particulate Matter in Ambient Air. Int. J. Mech. Eng. Appl. 2021, 9(6), 85-89. doi: 10.11648/j.ijmea.20210906.11

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AMA Style

Yang Shuo, Pan Zhi Qiang, Wang Dou Wen. Uncertainty Evaluation of Automatic Monitoring System for Fine Particulate Matter in Ambient Air. Int J Mech Eng Appl. 2021;9(6):85-89. doi: 10.11648/j.ijmea.20210906.11

Copy | Download

@article{10.11648/j.ijmea.20210906.11,
  author = {Yang Shuo and Pan Zhi Qiang and Wang Dou Wen},
  title = {Uncertainty Evaluation of Automatic Monitoring System for Fine Particulate Matter in Ambient Air},
  journal = {International Journal of Mechanical Engineering and Applications},
  volume = {9},
  number = {6},
  pages = {85-89},
  doi = {10.11648/j.ijmea.20210906.11},
  url = {https://doi.org/10.11648/j.ijmea.20210906.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijmea.20210906.11},
  abstract = {Ambient air fine particulate matter (PM2.5) is a kind of instantaneous variation of space and time that cannot be repeated. In the process of fluid sampling analysis of real-time data, there are too many variables and too fast component changes for the laboratory to undertake such tests. The fast automatic monitoring technology provides real-time measurement consistency and reliability, which is comparable in terms of cost effectiveness technical process optimization and life cycle. In this case, suitable reference gas for PM2.5 (mg/m3) could not be found, so β ray or oscillating balance method (X method) and manual weighing method (Y method, as the primary test method) were respectively used. Moreover, related to the sampling frequency of tolerance limit, discussion is given on the detection power (1-β) for the difference (∆) between the X and Y, for their acceptance probabilistic risk characteristics of operational curve based on the trade-off, and on sample sizes (n) under α and β risks, as well as the acceptable level of the cost of wrong decision. This paper belongs to the research category of unstable samples analysis, and involves the evaluation of two components, ur, rel(range) and uR, rel(bat). The assessment is based on the overall concept of top-down. All cumulative effects are incorporated into the continuous and closed system as far as possible. Under the premise of ensuring that the acceptable level is under statistical control, reasonable estimates of quality objectives and uncertainties are obtained.},
 year = {2021}
}

Copy | Download

TY  - JOUR
T1  - Uncertainty Evaluation of Automatic Monitoring System for Fine Particulate Matter in Ambient Air
AU  - Yang Shuo
AU  - Pan Zhi Qiang
AU  - Wang Dou Wen
Y1  - 2021/11/29
PY  - 2021
N1  - https://doi.org/10.11648/j.ijmea.20210906.11
DO  - 10.11648/j.ijmea.20210906.11
T2  - International Journal of Mechanical Engineering and Applications
JF  - International Journal of Mechanical Engineering and Applications
JO  - International Journal of Mechanical Engineering and Applications
SP  - 85
EP  - 89
PB  - Science Publishing Group
SN  - 2330-0248
UR  - https://doi.org/10.11648/j.ijmea.20210906.11
AB  - Ambient air fine particulate matter (PM2.5) is a kind of instantaneous variation of space and time that cannot be repeated. In the process of fluid sampling analysis of real-time data, there are too many variables and too fast component changes for the laboratory to undertake such tests. The fast automatic monitoring technology provides real-time measurement consistency and reliability, which is comparable in terms of cost effectiveness technical process optimization and life cycle. In this case, suitable reference gas for PM2.5 (mg/m3) could not be found, so β ray or oscillating balance method (X method) and manual weighing method (Y method, as the primary test method) were respectively used. Moreover, related to the sampling frequency of tolerance limit, discussion is given on the detection power (1-β) for the difference (∆) between the X and Y, for their acceptance probabilistic risk characteristics of operational curve based on the trade-off, and on sample sizes (n) under α and β risks, as well as the acceptable level of the cost of wrong decision. This paper belongs to the research category of unstable samples analysis, and involves the evaluation of two components, ur, rel(range) and uR, rel(bat). The assessment is based on the overall concept of top-down. All cumulative effects are incorporated into the continuous and closed system as far as possible. Under the premise of ensuring that the acceptable level is under statistical control, reasonable estimates of quality objectives and uncertainties are obtained.
VL  - 9
IS  - 6
ER  -

Copy | Download