The use of the Monte Carlo method for predicting environmental risk in construction zones

• Published in: Journal of physics. Conference series Vol. 1614; no. 1; pp. 12083 - 12097
• Main Author: Smirnova, E
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.08.2020
• Subjects: Biosphere; Confidence intervals; Human influences; Impact prediction; Lithosphere; Monte Carlo simulation; Physics; Risk levels; Statistical analysis
• ISSN: 1742-6588; 1742-6596
• DOI: 10.1088/1742-6596/1614/1/012083

The article analyzes the problem of determining environmental risk. The author took into account the features of natural landscapes when choosing a model of environmental risk in order to predict the level of interaction of the construction project with the environment. The matrix of construction zones distributions and the risk of environmental vulnerability are compiled on the bases of the study of the anthropogenic impact parameters on natural landscapes. Monte Carlo simulation method allows predicting the process of techno genesis relative to the natural environment within the limits of confidence interval. The industrial territories of the Far North and the regions equated to them are characterized by the highest probability and level of risk, as well as vulnerability. The impact of techno genesis on all four components of the environment (atmospheric air, hydrosphere, lithosphere and biosphere) in all areas of construction work normalization will continue to increase. This is indicated by trend graphs of the predicted values of anthropogenic impact within the industrial and residential zones. The quantitative characteristic of possible ecosystem "failures" as a result of anthropogenic interference is analyzed using a point scale. The worst-case scenario can be defined as post-catastrophic (ultra-high risk, emergency measures in emergency situations, score 26-30). The reliability of the simulated forecast is confirmed by the anthropogenic accident in Norilsk in June 2020, the largest and most unprecedented in the history of the Arctic.