Memorias de investigación
Ponencias en congresos:
A MAUT Approach for the Management and Remediation of a Site Contaminated by Uranium Processing Activities
Año:2013

Áreas de investigación
  • Física química y matemáticas

Datos
Descripción
Pridneprovsky Chemical Plant, located at Dneprodzerzhinsk (Ukraine), was one of the largest uranium processing enterprises of the former USSR, producing a huge amount of uranium residues stored in 9 tailing impoundments and contaminating di erent buildings. The processing of uranium stopped in 1990, due to the disintegration of the USSR, and since then ?nancial resources were not put in remediation programs until 2003. Nowadays, more than 20 enterprises not related to uranium processing activities are in operation at this territory and a residential area is located rather close to the zone. Since 2003, the Government of Ukraine began a systematic investigation of this territory. Environment monitoring and site surveillance programs were established in 2005. During 2008-09, preliminary safety assessment for the identi?ed hazards was been carried out and the resulting strategies are being implemented during the State Remediation Programme (2010-14), for which an international consortium of experts was created within the framework of ENSURE projects. Among the remediation problems that still are waiting for optimal strategy to be chosen are the management and decommissioning of the high contaminated buildings, the largest tailing at Dnieprovskoe, which is partly covered with thick layer of phosphogypsum and also the wet uranium tailing at Suhachevskoe, still partly covered with water. The situations described above are complex decision-making problems in which several economical, social and environmental con icting objectives must be taken into account simultaneously, being necessary a formal analysis. We have used the GMAA DSS based on an additive multi-attribute utility model to deal with these problems. It accounts for uncertainty about the strategy impacts and admits incomplete information about the decision-makers' preferences. The system provides di erent sensitivity analyses that take advantage of the imprecise inputs to reach a ?nal recommendation.
Internacional
No
Nombre congreso
The 22nd International Conference on Multiple Criteria Decision Making
Tipo de participación
960
Lugar del congreso
Revisores
Si
ISBN o ISSN
DOI
Fecha inicio congreso
17/06/2013
Fecha fin congreso
21/06/2013
Desde la página
82
Hasta la página
82
Título de las actas
Proceedings of The 22nd International Conference on Multiple Criteria Decision Making

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Participantes

Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Grupo de análisis de decisiones y estadística
  • Departamento: Inteligencia Artificial