- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
Research in the scope of geostatistics is applied in many fields of study, including soils and atmospheric air. Geostatistics can constitute a tool for interpretation of results of research on the natural environment. For example, the semivariogram permits the estimation and analysis of the variability structure of selected phenomena. Stochastic interpolation techniques allow for obtaining the value of the studied variable with no necessity of field studies with consideration of a dense network of measurements owing to information obtained from other research. Research on the quality of atmospheric air conducted by the European Environmental Agency (EEA) presents the state and forecasts of atmospheric air in particular European countries based on a low number of measurement points throughout Europe. In Poland, only four measurement stations function in the scope of the European Monitoring and Evaluation Programme (EMEP). An important aspect in geostatistical modelling is later assessment of uncertainty as to the estimated value of the analysed variable. Results of such an assessment are usually presented in the form of a map of probability of exceeding critical values. The last stage of geostatistical modelling usually involves stochastic simulations performed by means of an increasingly broad range of available algorithms. The assessment of generated effects combined with expert knowledge permits e.g., the identification of polluted areas. The quality of atmospheric air affects the degree of soil pollution (primarily as a result of the phenomenon of dry and/or wet deposition). Due to this, it is necessary to analyse such impact with consideration of all environmental and geochemical conditions. The application of the generally available data permits the estimation of the degree of soil pollution with no necessity of sampling in a given place, or performing costly laboratory analyses. The aim of the study was the presentation of the commonly used geostatistical methods and good practices in geostatistical modelling for the assessment of soil contamination by heavy metals based on deposition data from atmospheric air. The work was divided into two parts: (i) geostatistical modelling, presenting individual stages of the use of various tools and techniques, as well as (ii) kriging and cokriging interpolation methods used as a tool to integrate spatial data from different sets. The workflow in geostatistical modelling in environmental sciences using existing data sets was proposed.
The course and selection of parameters in geostatistical modelling undoubtedly affects the quality of obtained results. This is confirmed by results of numerous studies concerning both atmospheric air and soils. A detailed analysis of available data is important. The result of the geostatistical analysis in the form of a variogram model is the most important part of the modelling. It ensures that the obtained results reflect the reality to the highest possible degree, and are subject to minimum error.
In the case of research on the quality of atmospheric air and soils, all factors possibly affecting the character of data and further generated information should be taken into consideration. The proposed new approach to the geostatistical modelling in accordance with a scheme of procedure allows its use in the study of environmental sciences. Owing to such an approach, the drawn conclusions and interpreted phenomenon will be credible.