Risk zones from the filling stations modelling with application of geoinformation technology

Abstract

In this paper the questions of technogenic safety of the city Odesa with a population of over 1 million are considered on the example of the analysis of an emergency situation that may arise at filling stations (FS) of the city. The fire safety of the FSs network becomes very important in the context of urban buildings and traffic flows compaction, a significant increase in the number of cars, as well as in the construction of new potentially hazardous objects (PHO) within the urban territory. To solve the problem of analysis of the risk zones of FSs, a conceptual digital model of a FS was created, a numerical simulation of the scenario of an unfavourable situation development at the FS was carried out according to the approved state methodology (an explosion of a vapour-air fuel mixture with a shock wave formation), as well as the obtained zones were visualized on a map of the city of Odessa using the geographic information system QGIS. The digital model of the FS was created taking into account the requirements for the presentation of attributive and spatial data of the relevant GIS. The components of the developed conceptual model are: universal digital identifier, spatial data in the form of type and coordinates of the object, attributive data, which consist of static and dynamic features, as well as numerical models of emergency situation development. During the visualizing of the obtained calculated data by means of GIS, OSM Place Search, QuickOSM and Multi Ring Buffer plugins were used, as well as data from the OpenStreetMap server. The presented results of modelling and visualization indicate that, when the most unfavourable development scenarios are realized, the nature of accidents at FS can go beyond the local scale and move to the borders of the residential zone, as well as to nearby industrial buildings and FSs, which in turn can cause unfavourable situations on them by the domino effect. In addition, the results of the analysis of the obtained heterogeneous modelling and visualization data to determine technogenic risk indicates the possibility of applying the studied principles to other PHOs and also allows to present the data in a visual and accessible form for decision-makers.