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Geostatistical modelling of environmental variables at mine sites

Abstract:

The mining activity is considered to be one of the biggest contaminators of the surrounding environment. To deal with this problem, new technologies for monitoring environmental attributes are being developed, in order to sample and record a large amount of variables related with specific features of the environment quality, in particular, river water, groundwater, air and soil. In order to make use of the available information for pbkp_rediction purposes, it is required to model the sub-systems in the mine site and compare the actual data with a baseline, prior to the beginning of the mining workings. Such models make use of geostatistics in order to estimate and simulate the values of variables in space and time, taking into account the independence between sub-systems and the physical laws that govern the behaviour of relevant variables, when pollutant sources and meteorological conditions can be identified. Hence, geostatistical techniques are to be adjusted to the specific characteristics of the environmental variables and objectives of environmental control. The results of this research, referring to Neves Corvo Mine, in Portugal, are given in this paper, in what concerns the modelling of river water and air quality by stochastic spatio-temporal simulation, the integration of dispersion models with geostatistical estimation of groundwater quality, and the morphological simulation of soil contamination by particulate copper emissions.