Mathematical model of determining a risk to the human health along with the detection of hazardous states of urban atmosphere pollution based on measuring the current concentrations of pollutants

Authors

DOI:

https://doi.org/10.15587/1729-4061.2020.210059

Keywords:

air pollution, current concentrations of pollutants, risks to human health, recurrent states

Abstract

A mathematical model of joint determining the risk to human health and the identification of hazardous states of the polluted urban atmosphere based on the measurement of current concentrations of pollutants was developed. The structure of the model includes two structural units. The input data for structural units are the results of measuring current concentrations of atmospheric pollutants at a checkpoint. The current risk to human health is calculated in the first unit, and recurrent states of atmosphere for early detection of dangerous pollution levels are determined in the second unit. A distinctive feature of the model is the use of only measurements of current concentrations of pollutants in the atmosphere at a control point. Meteorological or other information is not used. That is why the developed model is universal and can be used in any weather conditions and peculiarities of the urban infrastructure. The operation efficiency of the proposed model was tested experimentally using the example of measuring current concentrations of formaldehyde, nitrogen dioxide, and ammonia in the atmosphere of the typical urban infrastructure. It was established that the developed model makes it possible to determine the risk of immediate toxic effects and chronic intoxication for humans, caused by atmospheric pollution. It was proved experimentally that the proposed model makes it possible, together with the identification of relevant risks to human health, to detect hazardous states of the polluted atmosphere, in which pollutants are usually accumulated. It was established that determining the current probability of recurrent conditions of the polluted atmosphere makes it possible with various reliability degrees to detect the possible occurrence of negative effects of atmospheric pollution on human health 6–12 hours beforehand

Author Biographies

Boris Pospelov, Scientific-Methodical Center of Educational Institutions in the Sphere of Civil Defence Chernyshevska str., 94, Kharkiv, Ukraine, 61023

Doctor of Technical Sciences, Professor

Department of Organization and Coordination of Research Activities

Vladimir Andronov, National University of Civil Defence of Ukraine Chernyshevska str., 94, Kharkiv, Ukraine, 61023

Doctor of Technical Sciences, Professor

Research Center

Evgeniy Rybka, National University of Civil Defence of Ukraine Chernyshevska str., 94, Kharkiv, Ukraine, 61023

Doctor of Technical Sciences, Senior Researcher

Research Center

Olekcii Krainiukov, V. N. Karazin Kharkiv National University Svobody sq., 4, Kharkiv, Ukraine, 61022

Doctor of Geographical Sciences, Associate Professor

Department of Environmental Safety and Environmental Education

Nadiya Maksymenko, V. N. Karazin Kharkiv National University Svobody sq., 4, Kharkiv, Ukraine, 61022

Doctor of Geographical Sciences, Professor

Department of Environmental Monitoring and Management

Ruslan Meleshchenko, National University of Civil Defence of Ukraine Chernyshevska str., 94, Kharkiv, Ukraine, 61023

PhD, Associate Professor

Department of Fire and Rescue Training

Yuliia Bezuhla, National University of Civil Defence of Ukraine Chernyshevska str., 94, Kharkiv, Ukraine, 61023

PhD

Department of Management and Organization Activities in the Field of Civil Protection

Inna Hrachova, National Academy of the National Guard of Ukraine Zakhysnykiv Ukrainy sq., 3, Kharkіv, Ukraine, 61001

PhD

Department of Research and Organization

Roman Nesterenko, National Academy of the National Guard of Ukraine Zakhysnykiv Ukrainy sq., 3, Kharkіv, Ukraine, 61001

PhD

Department of Technical and Logistics Support

Alla Shumilova, Slobozhanskyi National Nature Park Zarichna str., 15A, Krasnokutsk, Kharkiv reg., Ukraine, 62002

Department of Ecological-Educational Work and Recreation

References

  1. Egondi, T., Kyobutungi, C., Ng, N., Muindi, K., Oti, S., Vijver, S. et. al. (2013). Community Perceptions of Air Pollution and Related Health Risks in Nairobi Slums. International Journal of Environmental Research and Public Health, 10 (10), 4851–4868. doi: https://doi.org/10.3390/ijerph10104851
  2. Vasyukov, A., Loboichenko, V., Bushtec, S. (2016). Identification of bottled natural waters by using direct conductometry. Ecology, Environment and Conservation, 22 (3), 1171–1176.
  3. Ma, C. (2010). Who bears the environmental burden in China – An analysis of the distribution of industrial pollution sources? Ecological Economics, 69 (9), 1869–1876. doi: https://doi.org/10.1016/j.ecolecon.2010.05.005
  4. Goodman, A., Wilkinson, P., Stafford, M., Tonne, C. (2011). Characterising socio-economic inequalities in exposure to air pollution: A comparison of socio-economic markers and scales of measurement. Health & Place, 17 (3), 767–774. doi: https://doi.org/10.1016/j.healthplace.2011.02.002
  5. Su, J. G., Jerrett, M., de Nazelle, A., Wolch, J. (2011). Does exposure to air pollution in urban parks have socioeconomic, racial or ethnic gradients? Environmental Research, 111 (3), 319–328. doi: https://doi.org/10.1016/j.envres.2011.01.002
  6. Zou, B., Peng, F., Wan, N., Wilson, J. G., Xiong, Y. (2014). Sulfur dioxide exposure and environmental justice: a multi–scale and source–specific perspective. Atmospheric Pollution Research, 5 (3), 491–499. doi: https://doi.org/10.5094/apr.2014.058
  7. Zou, B., Wilson, J. G., Zhan, F. B., Zeng, Y. (2009). Air pollution exposure assessment methods utilized in epidemiological studies. Journal of Environmental Monitoring, 11 (3), 475. doi: https://doi.org/10.1039/b813889c
  8. Beckx, C., Int Panis, L., Arentze, T., Janssens, D., Torfs, R., Broekx, S., Wets, G. (2009). A dynamic activity-based population modelling approach to evaluate exposure to air pollution: Methods and application to a Dutch urban area. Environmental Impact Assessment Review, 29 (3), 179–185. doi: https://doi.org/10.1016/j.eiar.2008.10.001
  9. Dubinin, D., Korytchenko, K., Lisnyak, A., Hrytsyna, I., Trigub, V. (2017). Numerical simulation of the creation of a fire fighting barrier using an explosion of a combustible charge. Eastern-European Journal of Enterprise Technologies, 6 (10 (90)), 11–16. doi: https://doi.org/10.15587/1729-4061.2017.114504
  10. Semko, A., Rusanova, O., Kazak, O., Beskrovnaya, M., Vinogradov, S., Gricina, I. (2015). The use of pulsed high-speed liquid jet for putting out gas blow-out. The International Journal of Multiphysics, 9 (1), 9–20. doi: https://doi.org/10.1260/1750-9548.9.1.9
  11. Kondratenko, O. M., Vambol, S. O., Strokov, O. P., Avramenko, A. M. (2015). Mathematical model of the efficiency of diesel particulate matter filter. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, 6, 55–61.
  12. Bell, M. L., Ebisu, K., Belanger, K. (2007). Ambient Air Pollution and Low Birth Weight in Connecticut and Massachusetts. Environmental Health Perspectives, 115 (7), 1118–1124. doi: https://doi.org/10.1289/ehp.9759
  13. Ballester, F. (2002). The EMECAM project: a multicentre study on air pollution and mortality in Spain: combined results for particulates and for sulfur dioxide. Occupational and Environmental Medicine, 59 (5), 300–308. doi: https://doi.org/10.1136/oem.59.5.300
  14. Kustov, M. V., Kalugin, V. D., Tutunik, V. V., Tarakhno, E. V. (2019). Physicochemical principles of the technology of modified pyrotechnic compositions to reduce the chemical pollution of the atmosphere. Voprosy Khimii i Khimicheskoi Tekhnologii, 1, 92–99. doi: https://doi.org/10.32434/0321-4095-2019-122-1-92-99
  15. Pascual, M., Ellner, S. P. (2000). Linking ecological patterns to environmental forcing via nonlinear time series models. Ecology, 81 (10), 2767–2780. doi: https://doi.org/10.1890/0012-9658(2000)081[2767:leptef]2.0.co;2
  16. Parrott, L. (2004). Analysis of simulated long-term ecosystem dynamics using visual recurrence analysis. Ecological Complexity, 1 (2), 111–125. doi: https://doi.org/10.1016/j.ecocom.2004.01.002
  17. Proulx, R. (2007). Ecological complexity for unifying ecological theory across scales: A field ecologist’s perspective. Ecological Complexity, 4 (3), 85–92. doi: https://doi.org/10.1016/j.ecocom.2007.03.003
  18. Marwan, N., Kurths, J. (2002). Nonlinear analysis of bivariate data with cross recurrence plots. Physics Letters A, 302 (5-6), 299–307. doi: https://doi.org/10.1016/s0375-9601(02)01170-2
  19. Kantz, H., Schreiber, T. (2003). Nonlinear Time Series Analysis. Cambridge University Press. doi: https://doi.org/10.1017/cbo9780511755798
  20. Eckmann, J.-P., Kamphorst, S. O., Ruelle, D. (1987). Recurrence Plots of Dynamical Systems. Europhysics Letters (EPL), 4 (9), 973–977. doi: https://doi.org/10.1209/0295-5075/4/9/004
  21. Webber, C. L., Zbilut, J. P.; Riley, M. A., Van Orden, G. (Eds.) (2004). Chap. 2. Recurrence quantification analysis of nonlinear dynamical systems. Tutorials in Contemporary Nonlinear Methods for the Behavioral Sciences, 26–94.
  22. Pospelov, B., Andronov, V., Rybka, E., Meleshchenko, R., Borodych, P. (2018). Studying the recurrent diagrams of carbon monoxide concentration at early ignitions in premises. Eastern-European Journal of Enterprise Technologies, 3 (9 (93)), 34–40. doi: https://doi.org/10.15587/1729-4061.2018.133127
  23. Turcotte, D. L. (1997). Fractals and chaos in geology and geophysics. Cambridge University Press. doi: https://doi.org/10.1017/cbo9781139174695
  24. Poulsen, A., Jomaas, G. (2011). Experimental Study on the Burning Behavior of Pool Fires in Rooms with Different Wall Linings. Fire Technology, 48 (2), 419–439. doi: https://doi.org/10.1007/s10694-011-0230-0
  25. Zhang, D., Xue, W. (2010). Effect of heat radiation on combustion heat release rate of larch. Journal of West China Forestry Science, 39, 148.
  26. Andronov, V., Pospelov, B., Rybka, E. (2017). Development of a method to improve the performance speed of maximal fire detectors. Eastern-European Journal of Enterprise Technologies, 2 (9 (86)), 32–37. doi: https://doi.org/10.15587/1729-4061.2017.96694
  27. Andronov, V., Pospelov, B., Rybka, E., Skliarov, S. (2017). Examining the learning fire detectors under real conditions of application. Eastern-European Journal of Enterprise Technologies, 3 (9 (87)), 53–59. doi: https://doi.org/10.15587/1729-4061.2017.101985
  28. Pospelov, B., Andronov, V., Rybka, E., Popov, V., Romin, A. (2018). Experimental study of the fluctuations of gas medium parameters as early signs of fire. Eastern-European Journal of Enterprise Technologies, 1 (10 (91)), 50–55. doi: https://doi.org/10.15587/1729-4061.2018.122419
  29. Pospelov, B., Andronov, V., Rybka, E., Meleshchenko, R., Gornostal, S. (2018). Analysis of correlation dimensionality of the state of a gas medium at early ignition of materials. Eastern-European Journal of Enterprise Technologies, 5 (10 (95)), 25–30. doi: https://doi.org/10.15587/1729-4061.2018.142995
  30. Pospelov, B., Rybka, E., Meleshchenko, R., Gornostal, S., Shcherbak, S. (2017). Results of experimental research into correlations between hazardous factors of ignition of materials in premises. Eastern-European Journal of Enterprise Technologies, 6 (10 (90)), 50–56. doi: https://doi.org/10.15587/1729-4061.2017.117789
  31. Bendat, J. S., Piersol, A. G. (2010). Random data: analysis and measurement procedures. John Wiley & Sons, 640.
  32. Shafi, I., Ahmad, J., Shah, S. I., Kashif, F. M. (2009). Techniques to Obtain Good Resolution and Concentrated Time-Frequency Distributions: A Review. EURASIP Journal on Advances in Signal Processing, 1. doi: https://doi.org/10.1155/2009/673539
  33. Pospelov, B., Rybka, E., Meleshchenko, R., Borodych, P., Gornostal, S. (2019). Development of the method for rapid detection of hazardous atmospheric pollution of cities with the help of recurrence measures. Eastern-European Journal of Enterprise Technologies, 1 (10 (97)), 29–35. doi: https://doi.org/10.15587/1729-4061.2019.155027
  34. Pospelov, B., Andronov, V., Rybka, E., Krainiukov, O., Karpets, K., Pirohov, O. et. al. (2019). Development of the correlation method for operative detection of recurrent states. Eastern-European Journal of Enterprise Technologies, 6 (4 (102)), 39–46. doi: https://doi.org/10.15587/1729-4061.2019.187252
  35. Pospelov, B., Rybka, E., Togobytska, V., Meleshchenko, R., Danchenko, Y., Butenko, T. et. al. (2019). Construction of the method for semi-adaptive threshold scaling transformation when computing recurrent plots. Eastern-European Journal of Enterprise Technologies, 4 (10 (100)), 22–29. doi: https://doi.org/10.15587/1729-4061.2019.176579
  36. Pospelov, B., Rybka, E., Meleshchenko, R., Krainiukov, O., Harbuz, S., Bezuhla, Y. et. al. (2020). Use of uncertainty function for identification of hazardous states of atmospheric pollution vector. Eastern-European Journal of Enterprise Technologies, 2 (10 (104)), 6–12. doi: https://doi.org/10.15587/1729-4061.2020.200140
  37. Singh, P. (2016). Time-frequency analysis via the fourier representation. HAL.
  38. Stankovic, L., Dakovic, M., Thayaparan, T. (2014). Time-frequency signal analysis. Kindle edition, 655.
  39. Avargel, Y., Cohen, I. (2010). Modeling and Identification of Nonlinear Systems in the Short-Time Fourier Transform Domain. IEEE Transactions on Signal Processing, 58 (1), 291–304. doi: https://doi.org/10.1109/tsp.2009.2028978
  40. Giv, H. H. (2013). Directional short-time Fourier transform. Journal of Mathematical Analysis and Applications, 399 (1), 100–107. doi: https://doi.org/10.1016/j.jmaa.2012.09.053
  41. Pospelov, B., Andronov, V., Rybka, E., Popov, V., Semkiv, O. (2018). Development of the method of frequency­temporal representation of fluctuations of gaseous medium parameters at fire. Eastern-European Journal of Enterprise Technologies, 2 (10 (92)), 44–49. doi: https://doi.org/10.15587/1729-4061.2018.125926
  42. Ferrante, M., Fiore, M., Copat, C., Morina, S., Ledda, C., Mauceri, C., Oliveri Conti, G. (2015). Air Pollution in High-Risk Sites–Risk Analysis and Health Impact. Current Air Quality Issues. doi: https://doi.org/10.5772/60345
  43. Naydenko, V. V., Gubanov, L. N., Kosarikov, A. N., Afanas'eva, I. M., Ivanov, A. V. (2003). Ekologo-ekonomicheskiy monitoring okruzhayushchey sredy. Nizhniy Novgorod, 186.

Downloads

Published

2020-08-31

How to Cite

Pospelov, B., Andronov, V., Rybka, E., Krainiukov, O., Maksymenko, N., Meleshchenko, R., Bezuhla, Y., Hrachova, I., Nesterenko, R., & Shumilova, A. (2020). Mathematical model of determining a risk to the human health along with the detection of hazardous states of urban atmosphere pollution based on measuring the current concentrations of pollutants. Eastern-European Journal of Enterprise Technologies, 4(10 (106), 37–44. https://doi.org/10.15587/1729-4061.2020.210059

Issue

Vol. 4 No. 10 (106) (2020): Ecology

Section

Ecology

License

Copyright (c) 2020 Boris Pospelov, Vladimir Andronov, Evgeniy Rybka, Olekcii Krainiukov, Nadiya Maksymenko, Ruslan Meleshchenko, Yuliia Bezuhla, Inna Hrachova, Roman Nesterenko, Alla Shumilova

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.

A license agreement is a document in which the author warrants that he/she owns all copyright for the work (manuscript, article, etc.).
The authors, signing the License Agreement with TECHNOLOGY CENTER PC, have all rights to the further use of their work, provided that they link to our edition in which the work was published.
According to the terms of the License Agreement, the Publisher TECHNOLOGY CENTER PC does not take away your copyrights and receives permission from the authors to use and dissemination of the publication through the world's scientific resources (own electronic resources, scientometric databases, repositories, libraries, etc.).
In the absence of a signed License Agreement or in the absence of this agreement of identifiers allowing to identify the identity of the author, the editors have no right to work with the manuscript.
It is important to remember that there is another type of agreement between authors and publishers – when copyright is transferred from the authors to the publisher. In this case, the authors lose ownership of their work and may not use it in any way.