Print

Kustov M., Basmanov O., Tarasenko O., Melnichenko A. Forecast the scale of chemical contamination under conditions of a hazardous substance precipitation. С. 72-83.

Forecast the scale of chemical contamination under conditions of a hazardous substance precipitation

 

Maksym Kustov

National University of Civil Defence of Ukraine

https://orcid.org/0000-0002-6960-6399

 

Oleksii Basmanov

National University of Civil Defence of Ukraine

https://orcid.org/0000-0002-6434-6575

 

Olexandr Tarasenko

National University of Civil Defence of Ukraine

https://orcid.org/0000-0002-1313-1072

 

Andrey Melnichenko

National University of Civil Defence of Ukraine

https://orcid.org/0000-0002-7229-6926

 

DOI: https://doi.org/10.52363/2524-0226-2021-33-6

 

Keywords: hazardous chemicals, contamination zone, hazardous substance deposition, lesion scale forecasting, lesion zone localization

 

Abstract

Modeling of the emission zone of gaseous hazardous substances under different conditions of active deposition of hazardous clouds is carried out. Based on the differential equations of gas distribution in space, a step-by-step model of cloud distribution of hazardous chemical substance is obtained, which describes the stages of substance release from emergency process equipment, precipitation of hazardous gas by fine liquid flow and free cloud distribution in air. The developed mathematical model allows to calculate the size of chemical pollution zones with determination of boundary safety conditions taking into account wind direction and speed, air temperature, degree of vertical stability of air, width of active deposition zone and chemical properties of both gas and liquid. Based on the MAPLE mathematical software package, an algorithm for solving a mathematical model with the ability to visualize forecasting results has been developed. Automating the process of forecasting the scale of the emergency situation with the visualization of forecasting results increases the efficiency of emergency response staffs and reduces the time to make management decisions. With the help of the developed algorithm the forecasting of scales of chemical damage on various parameters of emission of dangerous substance, number of zones of deposition and intensity of giving of a fine stream on deposition is carried out. A comparative analysis of the results of forecasting the conditional zone of chemical damage during the free spread of the cloud and the active localization of the emission zone by operational and rescue units. The results of the comparative analysis showed that taking into account the processes of cloud deposition of hazardous chemicals in forecasting the scale of the emergency can significantly improve the accuracy of determining the size of the hazardous area, which affects the correctness of management decisions in rescue and evacuation

 

References

  1. Bundy, J., Pfarrer, M. D., Short, C. E., Coombs, W. T. (2017). Crises and Crisis Management: Integration, Interpretation, and Research Development. Journal of Management, 43(6), 1661–1692. doi.org/10.1177/0149206316680030
  2. Swain, C. (2009). WISER and REMM: Resources for Disaster Response. Journal of Electronic Resources in Medical Libraries, 6, 253–259. doi.org/10.1080/15424060903167393
  3. Polorecka, M., Kubas, J., Danihelka, P., Petrlova, K., Repkova Stofkova, K., Buganova, K. (2021). Use of Software on Modeling Hazardous Substance Release as a Support Tool for Crisis Management. Sustainability, 13, 438–453. doi.org/10.3390/su13010438
  4. Dahia, A., Merrouche, D., Merouani, D. R. Rezoug, T., Aguedal, H. (2019). Numerical Study of Long-Term Radioactivity Impact on Foodstuff for Accidental Release Using Atmospheric Dispersion Model. Arabian Journal for Science and Engineering, 44, 5233–5244. doi.org/10.1007/s13369-018-3518-2
  5. Loosmore, G., Cederwall, R. (2004). Precipitation scavenging of atmospheric aerosols for emergency response applications: testing an updated model with new real-time data // Atmospheric Environment, 38, 993–1003. doi.org/10.1016/j.atmosenv.2003.10.055
  6. Elperin, T., Fominykh, A., Krasovitov, B., Vikhansky, A. (2011). Effect of rain scavenging on altitudinal distribution of soluble gaseous pollutants in the atmosphere. Atmospheric Environment, 45(14), 2427–2433. doi.org/10.1016/j.atmosenv.2011.02.008
  7. Wei, L. (2011). Research on Countermeasures and Methods of Disposing Incidents of Hazardous Chemicals Reacting with Water. Procedia Engineering, 26, 2278 2286. doi.org/10.1016/j.proeng.2011.11.2435
  8. Hollingsworth, S. A., Dror, R. O. (2018). Molecular Dynamics Simulation for All. Neuron, 99, 1129–1143. doi.org/10.1016/j.neuron.2018.08.011
  9. Shiraiwa, M., Pfrang, C., Koop, T., Pöschl, U. (2012). Kinetic multi-layer model of gas-particle interactions in aerosols and clouds (KM-GAP): linking condensation, evaporation and chemical reactions of organics, oxidants and water // Atmospheric Chemistry and Physics, 12, 2777–2794. doi.org/10.5194/acp-12-2777-2012
  10. Kustov, M. V., Basmanov, O. Y., Melnichenko, A. S. (2020). Modeling the zone of chemistry in the minds of the localization of the supervised situation. Problems of supervised situations, 32, 145–157. doi.org/10.5281/zenodo.4400185
  11. Kustov, M., Kalugin, V., Levterov, A. (2016). Rain scavenging of a radioac-tive aerosol atmospheric precipitation. Austrian Journal of Technical and Natural Sciences, Vienne, 3–4, 73–76.