Artículos de revistas
Emergencies planning and response: Coupling an exposure model with different atmospheric dispersion models
Fecha
2013-07Registro en:
Sánchez, Érica Yanina; Colman Lerner, Jorge Esteban; Porta, Atilio Andrés; Jacovkis, Pablo Miguel; Emergencies planning and response: Coupling an exposure model with different atmospheric dispersion models; Elsevier; Atmospheric Environment; 79; 7-2013; 486-494
1352-2310
CONICET Digital
CONICET
Autor
Sánchez, Érica Yanina
Colman Lerner, Jorge Esteban
Porta, Atilio Andrés
Jacovkis, Pablo Miguel
Resumen
Information on spatial and time dependent concentration patterns of hazardous substances, as well as on the potential effects on population, is necessary to assist in chemical emergency planning and response. To that end, some models predict transport and dispersion of hazardous substances, and others estimate potential effects upon exposed population. Taken together, both groups constitute a powerful tool to estimate vulnerable regions and to evaluate environmental impact upon affected populations. The development of methodologies and models with direct application to the context in which we live allows us to draft a more clear representation of the risk scenario and, hence, to obtain the adequate tools for an optimal response. By means of the recently developed DDC (Damage Differential Coupling) exposure model, it was possible to optimize, from both the qualitative and the quantitative points of view, the estimation of the population affected by a toxic cloud, because the DDC model has a very good capacity to couple with different atmospheric dispersion models able to provide data over time. In this way, DDC analyzes the different concentration profiles (output from the transport model) associating them with some reference concentration to identify risk zones. In this work we present a disaster scenario in Chicago (USA), by coupling DDC with two transport models of different complexity, showing the close relationship between a representative result and the run time of the models. In the same way, it becomes evident that knowing the time evolution of the toxic cloud and of the affected regions significantly improves the probability of taking the correct decisions on planning and response facing the emergency.