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Verification of equivalence with reference method for measurements of PM10 concentrations using low-cost devices

Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This study presents an assessment of the equivalence of measurements of particulate matter PM10 concentrations using a low-cost electronic device as compared to the reference method. Data for the study were collected in accordance with the guidelines for research equivalence of the two devices operating in parallel. On this basis, a model correcting raw measurement results was developed. The best results were obtained for the model having the form of a second degree polynomial and taking into account air temperature. Corrected measurement results were used in the equivalence testing procedure. As a result, confirmation of equivalence was obtained for the vast majority of data sets generated from original measurements. This confirms the usefulness of the device as a tool for monitoring air quality.
Rocznik
Strony
84--89
Opis fizyczny
Bibliogr. 20 poz., rys. tab.
Twórcy
  • Gdynia Maritime University, Faculty of Entrepreneurship and Quality Science 83 Morska St., 81-225 Gdynia, Poland
  • Warsaw University of Technology, Faculty of Building Services Hydro and Environmental Engineering 20 Nowowiejska St., 00-653 Warsaw, Poland
  • Gdynia Maritime University, Faculty of Entrepreneurship and Quality Science 83 Morska St., 81-225 Gdynia, Poland
Bibliografia
  • 1. Boggs, P.T. & Rogers, J.E. (1990) Orthogonal Distance Regression. In: Brown P.J. & Fuller W.A. (Eds). Statistical Analysis of Measurement Error Models and Applications. Contemporary Mathematics 112, Providence Rhode Island, pp. 181–194.
  • 2. Czechowski, P.O. (2013) New methods and models of data measurement quality in air pollution monitoring networks assessment. Gdynia Maritime University Press (in Polish).
  • 3. Dorozhovets, M. (2007a) Uncertainty of linear orthogonal regression. Pomiary Automatyka Kontrola PAK 53, 31, pp. 31–34 (in Polish).
  • 4. Dorozhovets, M. (2007b) Proposals for extending the methods for determining the uncertainty of measurement results according to the GUM Guide. Pomiary Automatyka Robotyka 1, pp. 7–15 (in Polish).
  • 5. EC Working Group (2010) Guide to the demonstration of equivalence of ambient air monitoring methods. Available from: http://ec.europa.eu/environment/air/quality/legislation/pdf/equivalence.pdf [Accessed: October 15, 2019]
  • 6. ECS (2013) Ambient Air – Automated measuring systems for the measurement of the concentration of particulate matter (PM10; PM2,5). CEN/TS 16450. European Committee for Standardization.
  • 7. Gębicki, J. & Szymańska, K. (2011) Comparison of Tests for Equivalence of Methods for Measuring PM10 Dust in Ambient Air. Polish Journal of Environmental Studies 20, 6, pp. 1465–1472.
  • 8. GIOŚ (2019) Measurement of particulate matter in the air. [Online] Available from: http://powietrze.gios.gov.pl/pjp/ content/show/1000919 [Accessed: October 10, 2019] (in Polish).
  • 9. Green, D.C., Fuller, G.W. & Baker, T. (2009) Development and validation of the volatile correction model for PM10 – An empirical method for adjusting TEOM measurements for their loss of volatile particulate matter. Atmospheric Environment 43, 13, pp. 2132–2141.
  • 10. Grubbs, F.E. (1950) Sample criteria for testing outlying observations. Annals of Mathematical Statistics 21, 1, pp. 27–58.
  • 11. Working Group (2013) Grupa robocza Komitetu EA ds. Laboratoriów. Wyznaczanie niepewności pomiaru przy wzorcowaniu. Evaluation of the Uncertainty of Measurement in Calibration. EA-4/02 M: 2013 (in Polish).
  • 12. GUM (1999) Expressing measurement uncertainty. Guide. Warszawa: Główny Urząd Miar (in Polish).
  • 13. Leng, L., Zhang, T., Kleinman, L. & Zhu, W. (2007) Ordinary least square regression, orthogonal regression, geometric mean regression and their applications in aerosol science. Journal of Physics: Conference Series 78, 012084. DOI:10.1088/1742-6596/78/1/012084.
  • 14. Myers, R.H. (1990) Classical and modern regression with applications. Duxbury Thomson Learning.
  • 15. Owczarek, T. & Rogulski, M. (2018) Uncertainty of PM10 concentration measurement on the example of an optical measuring device. SHS Web of Conferences 57, 02008.
  • 16. Owczarek, T., Rogulski, M. & Badyda, A. (2018) Preliminary comparative assessment and elements of equivalence of air pollution measurement results of portable monitoring stations with using stochastic models. E3S Web of Conferences 28, 01028.
  • 17. PN-EN 12341 (2014) Atmospheric air – Standard gravimetric measuring method for determining the mass concentrations of PM10 or PM2.5 fraction of particulate matter (in Polish).
  • 18. Rogulski, M. & Badyda, A.J. (2018) Application of the Correction Function to Improve the Quality of PM Measurements with Low-Cost Devices. SHS Web of Conferences 57, 02009.
  • 19. Sówka, I.M., Chlebowska-Styś, A., Pachurka, Ł. & Rogula-Kozłowska, W. (2018) Seasonal variations of PM2.5 and PM10 concentrations and inhalation exposure from PM – bound metals (As, Cd, Ni): first studies in Poznań (Poland). Archives of Environmental Protection 44, 4, pp. 86–95.
  • 20. Szulczyński, A. & Gębicki, J. (2018) The applicability of low-cost PM10 sensors for atmospheric air quality monitoring. SHS Web of Conferences 57, 02013.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-54f004ca-f570-4aa0-9ab4-19f32f374e36
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