Impact of the oil production complex on land pollution in Russia
The assessment of the impact of the economic activities of the Russian oil-producing complex on land pollution contributes to the adoption of evolutionary management decisions. It also helps to take into account the opinion of society, the Ministry of Emergency Situations. In the oil complex, industrial pollution negatively affects flora and fauna. It's important to identify the level of exposure, the degree of its danger, the location of the contamination. The work deals with the methodology, information-logical and mathematical model of solving the above problem. The main result of the work is a system and procedure (technique) for analyzing the results of monitoring and forecasting of land cover take into consideration the sanitary and hygienic consequences of residual content of petroleum products. As a result of the system analysis, an approach to the construction of alternative solutions has been proposed, taking into account not only permissible pollution standards, but also environmental, sanitary and epidemiological norms and assessment methods. The emergence of soil systems, their categories, is taken into account. In particular, (in importance) risks for soil cover-morphological, bio-physical-chemical, ecological-health, toxic influence and irreversible processes and bifurcations, including taking into account regional peculiarities and restoration potential of soil, are considered. Proposed algorithm of simulation and system analysis is based on situational modeling. Evolutionary modeling allows you to adapt the prediction and assessment procedure (methodology) to the risk factors of the environment. It increases accuracy (formalization and evidence) and completeness of conclusions, efficiency of situation analysis, which affects manageability of risk both for oil complex and for individual enterprise of the industry. The results of the work may be used for the development of software tools, in particular expert and predictive systems. Situational models are needed when oil companies are addressing multi-criteria and multi-factor decision-making challenges.