Evaluating and classifying contaminated areas based on loss functions using annealing simulations |
| |
| Authors: | Joaquim CB Queiroz José R Sturaro Augusto CF Saraiva Paulo MB Landim |
| |
| Institution: | 1. Department of Statistics, Federal University of Para, Belém, Pará, Brazil;2. Department of Applied Geology, São Paulo State University, Rio Claro, São Paulo, Brazil;3. Central Laboratory Eletronorte, Belém, Pará, Brazil |
| |
| Abstract: | This paper presents a methodology based on geostatistical theory for quantifying the risks associated with heavy-metal contamination in the harbor area of Santana, Amapá 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. |
| |
| Keywords: | Decision making process Uncertainty modeling Risk and loss functions Annealing simulation Geostatistics |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
