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An integrated emergency response model for toxic gas release accidents based on cellular automata

  • S.I. : Energy and Climate Policy Modeling
  • Published:
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Abstract

An integrated emergency response model based on cellular automata (CA) is proposed for the toxic gas release accidents that happen in the energy and chemical industry. This integrated emergency response model consists of three sub-models: a toxic gas dispersion model, a dynamic evaluation model for accident consequences, and an evacuation route selection model. When a toxic gas release accident happens, the dispersion model predicts the distribution of toxic gas concentration, the evaluation model estimates the consequences in terms of probability of death, expected fatalities and impact scope caused by the accident, and the route selection model provides the safest evacuation route for evacuees. The three sub-models run simultaneously and present real-time results. The proposed model is applied to an ammonia gas release accident in an energy and chemical enterprise, and the corresponding model results are discussed. The efficiency of emergency response for toxic gas release accidents can be further improved through the proposed integrated emergency response model based on CA.

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Notes

  1. The impact scope of a toxic gas release accident is divided into the fatal zone, the severe harm zone and the slight harm zone in the People’s Republic of China. In the fatal zone, the probability of death for a person who is unprotected and cannot evacuate in time is greater than or equal to 0.5 (AQ3036-2010; Cui et al. 2008; GB18218-2009).

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Acknowledgments

The authors wish to acknowledge the helpful comments provided by anonymous referees. This work was supported by the National Natural Science Foundation of China (71431004, 71171082, 71001039 and 71301050), National Key Technology R&D Program (2013BAH11F03) and the Fundamental Research Funds for the Central Universities.

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Correspondence to Tijun Fan.

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Cao, H., Li, T., Li, S. et al. An integrated emergency response model for toxic gas release accidents based on cellular automata. Ann Oper Res 255, 617–638 (2017). https://doi.org/10.1007/s10479-016-2125-4

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