Moklyachuk T. Ecological-economical evaluation of remediation of agricultural soils

In this thesis we study mechanisms of ecological-economical remediation of polluted soils and develop a practical approach to the topic. We analyze the concept of sustainable development, its role and influence on world economics, and the role of the soil remediation in this concept. Perquisites for organic agriculture and soil rehabilitation are reviewed. Ecological and economical approaches to soil remediation are researched. We propose the structure of remediation that consists of four steps: pollution estimation, risk estimation, cost-benefit analysis, and choice of remediation level. We have also developed the mechanism of evaluation of money value of yearly damage caused by soil pollution, using methods of soil sites evaluation given in law codex of Ukraine. We have developed and tested the model of situational risk estimation, the SitRisk model, based on our research, research of the Institute of Agroecology and Environmental Management of NAAS, Ukraine, and research of L.I. Medved’s Research Center of Preventive Toxicology, Food and Chemical Safety, Ukraine. We also have compared our model to CalTOX risk model, developed by California Department of Toxic Substances Control, Environment Protection Agency, US. This model allows estimating risks of pollution by unevenly distributed pollution, such as edaphotope of pesticide storehouse. It utilizes mathematical methods of differential and integral calculus to estimate the spread of pollutants to the soil around the edaphotope of storehouse. Both models have displayed close results. As the next step of ecological-economical remediation, we have used mathematical methods of multi-objective optimization and conducted Cost-Benefit analysis of remediation methods and built a quality function of remediation method that allows one to compare different remediation methods. For building the quality function we used different mathematical approaches such as Pareto-optimization and scalarization. To estimate weight coefficients of this formula, we used method of priorities and graph theory.