Air pollution modelling of accidents involving hazardous substances

Abstract Air pollution modeling for accidents involving hazardous substances is a critical aspect of emergency response and environmental protection. This modeling aims to predict the dispersion and impact of toxic substances released into the atmosphere during accidents, such as industrial spills, transport accidents, chemical plant incidents or acts of terrorism. Such dangers are among the challenges which the modern society is facing and has to overcome. In this study we propose a systematic approach for organizing monitoring, collecting data from mobile sensors, creating situation development scenarios, modelling the spread of potential toxic-element pollution in dependence with the current meteorological conditions. The UNI-DEM model for simulation of the pollutants’ dispersion and transport in the air, as well as models for spread of leaking gas and liquid vapors are involved in this study. Finally, depending on the comprehensive analysis of the modeling results, an adequate response to such severe situations can be proposed. Assessment of safety, healthcare and environmental impacts should be the final result and the most socially important application of our work. The calculated pollutant concentrations can be compared with regulatory standards or health-based guidelines to assess potential health risks to exposed populations and environmental impacts on ecosystems. The importance of this information for emergency response planning, public health interventions, and environmental management strategies is beyond dispute.

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Publication Details

Journal
Journal of Physics Conference Series
Published
2024-12-01
DOI
https://doi.org/10.1088/1742-6596/2910/1/012002
Primary Topic
Air Quality and Health Impacts
Type
article
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article

Air pollution modelling of accidents involving hazardous substances

Tzvetan Ostromsky, Stefan Parvanov, Kiril Alexiev
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Journal of Physics Conference Series
Air Quality and Health Impacts
article

Air pollution modelling of accidents involving hazardous substances

Tzvetan Ostromsky, Stefan Parvanov, Kiril Alexiev
article en

Abstract

Abstract Air pollution modeling for accidents involving hazardous substances is a critical aspect of emergency response and environmental protection. This modeling aims to predict the dispersion and impact of toxic substances released into the atmosphere during accidents, such as industrial spills, transport accidents, chemical plant incidents or acts of terrorism. Such dangers are among the challenges which the modern society is facing and has to overcome. In this study we propose a systematic approach for organizing monitoring, collecting data from mobile sensors, creating situation development scenarios, modelling the spread of potential toxic-element pollution in dependence with the current meteorological conditions. The UNI-DEM model for simulation of the pollutants’ dispersion and transport in the air, as well as models for spread of leaking gas and liquid vapors are involved in this study. Finally, depending on the comprehensive analysis of the modeling results, an adequate response to such severe situations can be proposed. Assessment of safety, healthcare and environmental impacts should be the final result and the most socially important application of our work. The calculated pollutant concentrations can be compared with regulatory standards or health-based guidelines to assess potential health risks to exposed populations and environmental impacts on ecosystems. The importance of this information for emergency response planning, public health interventions, and environmental management strategies is beyond dispute.

Journal of Physics Conference SeriesVol. 2910(1)
Ministry of Interior (BG), Institute of Information and Communication Technologies (BG)
Openalex Percentile: Top 67%
Air Quality and Health Impacts
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Air pollution modelling of accidents involving hazardous substances — Tzvetan Ostromsky, Stefan Parvanov, et al. · Journal of Physics Conference Series (2024) | TGRS Research Map | TGRS