Emissions from fossil fuels are expected to increase in accordance with the global economy, which causes the development of alternative non-hydrocarbon sources in energy production. Biodiesel is one of the best options, among other sources, due to its low footprint. Russia does not have a smart policy of state support for biofuel production. The work objective was to determine whether it is necessary to develop equipment for biodiesel production, taking into account the structure of cultivated areas and available technologies; to calculate economic indicators of biodiesel production for agricultural needs; to compare the options for spring rape cultivation; as well as calculate the government support optimal level. As research methods, the authors used the apparatus of economic and mathematical modeling, and the method of absolute, relative and average values. Statistical tables are used to present the research results. Based on our study results, it is proven that the homemade biodiesel production by agricultural enterprises is economically justified. The equipment needed for its production was determined, the main economic indicators of the fuel production type and the optimal value of monetary and labor costs were calculated, and the gross and market biofuel values were obtained. The optimum level of government support for biofuel production in the Middle Volga region should be EUR 13.223 million, and the area planted with oil crops should be increased by 47.1 thousand ha.

The assessment of impact of oil production economic activities on land pollution in Russia contributes to evolutionary management decision making. Oil industrial pollution affects negatively flora and fauna. Thus, its important to identify the level of its exposure and danger, the site of contamination. A system approach is needed. When studying the environment, its necessary to consider the presence of risk situations and stochastic irreversible changes. Its essential to identify the nature and type of soil contamination with petroleum products using high-tech tools, intellectual procedures. The work considers modeling of such situation, forecasting and identification of oil contaminants. The submodel of optimal termination of monitoring is also considered. Ending monitoring of environmental optimization will result in lower monitoring costs, since monitoring oilcontaminated environments is an expensive and complex technological mechanism, often requiring satellite data. The proposed algorithm for modeling and system analysis is based on situational modeling. Evolutionary modeling allows to adapt the procedure (methodology) of forecasting and assessment to environmental risk factors. It increases the accuracy (formalization and evidence) and completeness of conclusions, the efficiency of situation analysis, which affects manageability of risk both for the oil complex and for individual enterprise in the industry. The results of the research may be used for development of software tools, in particular expert and predictive systems. Situational models are needed when oil companies are solving multi-criteria and multifactor problems.

In today's economy, it is necessary to explore the environmental impact of mining. Coal mining greatly affects all environmental parameters of the environment: home, production, hydrodynamics. The environmental situation in the area of the mining company can be changed if environmental contamination is monitored and environmental protection plans and measures are developed. The purpose of this work is the analysis of systems and models of these processes in the ecosystem. The main systemic hypothesis of the research is that the variety of criteria and methods of risk assessment is a necessary condition of order in the system. The main results of the work are the following: 1) a systematic analysis of the problems of environmental security, geodynamics of the mining areas, aspects of the balance of the sustainable process and the cause of the increase in danger was carried out; 2) Proposed approaches (models) for the assessment of evolutionary ecological potential and health risks, as well as adaptive situational modeling of the ecosystem. It is important to note, the study results do not suggest complex environmental monitoring studies.