Evaluating and classifying contaminated areas based on loss functions using annealing simulations
Nenhuma Miniatura disponível
Data
2009-06-01
Autores
Queiroz, Joaquim C. B.
Sturaro, Jose R. [UNESP]
Saraiva, Augusto C. F.
Landim, Paulo M.B. [UNESP]
Título da Revista
ISSN da Revista
Título de Volume
Editor
Elsevier B.V.
Resumo
This paper presents a methodology based on geostatistical theory for quantifying the risks associated with heavy-metal contamination in the harbor area of Santana, Amapa State, Northern Brazil. In this area there were activities related to the commercialization of manganese ore from Serra do Navio. Manganese and arsenic concentrations at unsampled sites were estimated by postprocessing results from stochastic annealing simulations; the simulations were used to test different criteria for optimization, including average, median, and quantiles. For classifying areas as contaminated or uncontaminated, estimated quantiles based on functions of asymmetric loss showed better results than did estimates based on symmetric loss, such as the average or the median. The use of specific loss functions in the decision-making process can reduce the costs of remediation and health maintenance. The highest global health costs were observed for manganese. (c) 2008 Elsevier B.V. All rights reserved
Descrição
Palavras-chave
Decision making process, Uncertainty modeling, Risk and loss functions, Annealing simulation, Geostatistics
Como citar
Journal of Geochemical Exploration. Amsterdam: Elsevier B.V., v. 101, n. 3, p. 265-282, 2009.