Risk analysis of technological hazards: Simulation of scenarios and application of a local vulnerability index

被引:23
|
作者
Sanchez, E. Y. [1 ]
Represa, S. [1 ]
Mellado, D. [1 ,2 ]
Balbi, K. B. [1 ]
Acquesta, A. D. [2 ,3 ]
Colman Lerner, J. E. [4 ]
Porta, A. A. [1 ]
机构
[1] UNLP, CONICET, Ctr Invest Medio Ambiente CIM, 47 & 115 B1900AJL, La Plata, Buenos Aires, Argentina
[2] Inst Invest Cient & Tecn Def CITEDEF, San Juan Bautista La Salle 4397,B1603ALO, Villa Martelli, Argentina
[3] Pontificia Univ Catolica Argentina UCA, Fac Ingn & Ciencias Agr, Av Alicia Moreau de Justo 1300,C1107AAZ, Caba, Argentina
[4] UNLP, CONICET, Ctr Invest & Desarrollo Ciencias Aplicadas CINDEC, 47 257 B1900AJK, La Plata, Buenos Aires, Argentina
关键词
Social vulnerability; Technological incident; Worst-case scenario; ALOHA; INDEC; SOCIAL VULNERABILITY; ACCIDENT; METHODOLOGY; ALOHA;
D O I
10.1016/j.jhazmat.2018.03.034
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The potential impact of a technological accident can be assessed by risk estimation. Taking this into account, the latent or potential condition can be warned and mitigated. In this work we propose a methodology to estimate risk of technological hazards, focused on two components. The first one is the processing of meteorological databases to define the most probably and conservative scenario of study, and the second one, is the application of a local social vulnerability index to classify the population. In this case of study, the risk was estimated for a hypothetical release of liquefied ammonia in a meat-packing industry in the city of La Plata, Argentina. The method consists in integrating the simulated toxic threat zone with ALOHA software, and the layer of socio-demographic classification of the affected population. The results show the areas associated with higher risks of exposure to ammonia, which are worth being addressed for the prevention of disasters in the region. Advantageously, this systemic approach is methodologically flexible as it provides the possibility of being applied in various scenarios based on the available information of both, the exposed population and its meteorology. Furthermore, this methodology optimizes the processing of the input data and its calculation.
引用
收藏
页码:101 / 110
页数:10
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