Visualization of the state of radiological contamination of food products

Authors

DOI:

https://doi.org/10.15587/2312-8372.2018.146016

Keywords:

radiation contamination visualization, factor analysis, cluster analysis, radiological mapping

Abstract

The object of research is the measurement, assessment, visualization and control of the effects of radiation exposure on life, public health, environmental protection and safety of national economic facilities, taking into account the risk of man-made disasters. One of the biggest problems is the need to develop scientific methods for the study of integrated assessments of the impact of man-made pressures on the environment and humans. And also in the creation of specialized systems for collecting, storing, processing and visualizing information using modern GIS (geographic information systems) technologies. This allows to analyze multidimensional data using their display while preserving the structural features of the information.

Comprehensive assessment of the impact of man-made pollution is used, which is a necessary condition for metrological support for in-depth study of the structure of the system, as the unity of components and connections.

As a result of this work, a specialized system for analyzing the data obtained when measuring samples of food products for compliance with the standards for a particular product has been formed. The basis of this system is the development of a database of food monitoring in the Cherkasy region (Ukraine), the structure of which includes a central bank and 5 specialized units. Examples are given of the calculation of comparative assessments of the state of areas of the region, including the radiation component.

Measurement and obtained control over a complex situation with simultaneous consideration of a large number of heterogeneous parameters are carried out. This is due to the fact that the proposed method complements the well-known methods of mathematical modeling of radiological contamination, directly affect the quality of life of the population, and has several features. In particular, the development of a software environment for the construction and visualization in the form of thematic maps of the correlation between radiological contamination and the incidence of the population of the region. This ensures the possibility of obtaining an assessment of the risk degree to public health and making informed decisions to minimize it.

Author Biographies

Volodymyr Kvasnikov, National Aviation University, 1, Cosmonaut Komarov ave., Kyiv, Ukraine, 03058

Doctor of Technical Sciences, Honored Metrologist of Ukraine, Head of Department

Department of Computerized Electrical Systems and Technologies

Dmitry Matviyenko, State Enterprise «Cherkassy Scientific and Production Center for Standardization, Metrology and Certification», 278, Gogol str., Cherkasy, Ukraine, 18002

Senior Engineer

Testing Laboratory for Food Products and Light Industry Products

References

  1. Konovalova, N. V., Kapralov, E. G. (1997). Vvedenie v GIS. Moscow, 160.
  2. Katorgin, I. Yu., Naydenko, V. N., Petin, O. V. (2002). Geoinformatsionnaya sistema Maplnfo. Stavropol: Izd-vo SGU, 54.
  3. Sobotovich, E. V., Shestopalov, V. M., Pushkarev, A. V. (1993). Printsipy landshaftno-geokhimicheskogo i radioekologicheskogo kartirovaniya territorii, zagryaznennoy tekhnogennymi radionuklidami. Dokl. AN Ukrainym, 1, 177–181.
  4. Chernobyl Digest 95–98 (1999). Interdisciplinary Bulletin of the Chernobyl Problem Information. Issue 5. Minsk, 257.
  5. Serdyutskaya, L. F. (2009). Tekhnogennaya ekologiya. Matematiko-kartograficheskoe modelirovanii. Moscow: Knizhnyy dom «LIBROKOM», 232.
  6. Mitas, L., Mitasova, H. (1998). Distributed soil erosion simulation for effective erosion prevention. Water Resources Research, 34 (3), 505–516. doi: http://doi.org/10.1029/97wr03347
  7. Krivan, V. (2014). Competition in di- and tri-trophic food web modules. Journal of Theoretical Biology, 343, 127–137. doi: http://doi.org/10.1016/j.jtbi.2013.11.020
  8. Handbook of parameter values for the prediction of radionuclide transfer in terrestrial and freshwater environments Technical reports series No. 472 (2010). Vienna: IAEA, 194.
  9. Kozak, I. I. (2009). Ekolohichne modeliuvannia iz zastosuvanniam prohramy STELLA. Ivano-Frankivsk: Plai, 189.
  10. Lepicard, S., Heling, R., Maderich, V. (2004). POSEIDON/RODOS models for radiological assessment of marine environment after accidental releases: application to coastal areas of the Baltic, Black and North Seas. Journal of Environmental Radioactivity, 72 (1-2), 153–161. doi: http://doi.org/10.1016/s0265-931x(03)00197-8
  11. Margvelashvily, N., Maderich, V., Zheleznyak, M. (1997). THREETOX – A Computer Code to Simulate Three-Dimensional Dispersion of Radionuclides in Stratified Water Bodies. Radiation Protection Dosimetry, 73 (1), 177–180. doi: http://doi.org/10.1093/oxfordjournals.rpd.a032128
  12. Yanchuk, V. M. et. al. (2002). Metody ta zasoby matematychnoho modeliuvannia mihratsii radionuklidiv u pryrodnykh ekosystemakh: Vol. 1. Vid analizu do matematychnoi modeli. Zhytomyr: ZhITI, 142.
  13. Mamikhin, S. V., Merkulova, L. N. (1996). Komp'yuterizatsiya issledovaniy dinamiki radionuklidov v lesnykh ekosistemakh, zagryaznennykh v rezul'tate Chernobyl'skoy avarii (1986–1995 gg.). Radiatsionnaya biologiya. Radioekologiya, 36 (4), 516–523.
  14. Spiridonov, S. I., Mosharov, O. V., Solomatin, V. M., Panov, A. V., Fesenko, S. V. (2008). Otsenka stepeni zagryazneniya pochv 137Cs, dopuskayushhey poluchenie normativno chistoy sel'skokhozyaystvennoy produktsii, na osnove matematicheskikh modeley perekhoda radionuklida v rasteniya. Sel'skokhozyaystvennaya biologiya, 5, 53–57.
  15. Serdyutskaya, L. F., Kamemeneva, I. P. (2000). Sistemnyy analіz i matematicheskoe modelirovanie mediko-ekologicheskikh posldstviy avarii na CHAES i drugikh tekhnogennikh vozdeystviy. Kyiv: «Medekol» MNITS BIO-EKOS MCHS i NAN Ukrainy, 173.
  16. Serdyutskaya, L. F., Kameneva, I. P. (2009). Tekhnogennaya ekologiya. Matematiko-kartograficheskoe modelirovanii. Moscow: Knizhnyy dom «LIBROKOM», 232.
  17. Dubrov, A. M., Mkhitaryan, V. S., Troshin, L. I. (1998). Mnogomernye statisticheskie metody. Moscow: Finansy i statistika, 232.
  18. Khalafyan, A. (2010). STATISTICA 6. Statisticheskiy analiz dannykh. Binom, 512.
  19. Ivchenko, B. P., Martyshhenko, L. A. (1998). «Informatsionnaya ekologiya». Chast' 1. Otsenka riska tekhnogennykh avariy i katastrof. Statisticheskaya interpretatsiya ekologicheskogo monitoringa. Modelirovanie i prognozirovanie ekologicheskikh situatsіy. Saint Petersburg: Normed-Izdat, 208.
  20. Kim, O. Dzh., M'yuller, Ch. U., Klekka, U. R. (1989). Faktornyy, diskriminantnyy i klasternyy analiz. Moscow: Nauka, 215.
  21. Trukhacheva, N. V. (2012). Matematicheskaya statistika v mediko-biologicheskikh issledovaniyakh s primeneniem paketa Statistica. Moscow: GEOTAR-Media, 384.

Downloads

Published

2018-05-17

How to Cite

Kvasnikov, V., & Matviyenko, D. (2018). Visualization of the state of radiological contamination of food products. Technology Audit and Production Reserves, 5(3(43), 8–14. https://doi.org/10.15587/2312-8372.2018.146016

Issue

Vol. 5 No. 3(43) (2018): Chemical engineering

Section

Measuring Methods in Chemical Industry: Original Research

License

Copyright (c) 2018 Volodymyr Kvasnikov, Dmitry Matviyenko

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.