Assessment of Environmental Degradation Costs: A Case Study of Beijing and Tianze Agricultural Parks

Abstract

Nowadays, the community of human destiny has gradually become the consensus of people. The pursuit of economic benefits and the neglect of ecological benefits will bring serious consequences. Therefore, predicting the cost of environmental degradation for managers is an urgent problem we need to solve.We establish a mathematical model to predict the cost of environmental degradation. And we ignore some insignificant factors and choose seven factors as indicators in our model under the consideration of actuality. To make the model more intuitive, we transform environmental degradation costs into ecosystem services values and calculate the value of each service in the ecosystem separately. At the same time, we use Analytic Hierarchy Process to calculate the weight of each service according to the judgment matrix. Then we introduce a concept in economics “Weighted Average Cost of Capital (WACC)”. Hence, we can derive the final cost of environmental degradation. Next, we take Beijing’s construction as an example of a large national project and Tianze agricultural park as an example of a small community-based project to estimate their respective degradation costs.As for the effectiveness analysis, we use polynomial 7-th approximation to fit curve and prove its effectiveness successfully. According to the data we get from fitting curve, we analyze the ideal environment level of 2020. The result shows that land use projects exist many shortcomings and we give land use project planners and managers some advice to help them reach the ideal environment level in 2020.Since ecosystem service valuation is pretty complex and some indicators are influenced by humanity factor, we cannot ensure the accuracy of our calculation. We improve our model and add fuzzy mathematic method into AHP. By using Fuzzy Analytic Hierarchy Process, we can let the weight change automatically over time. Therefore, we success in improving our model and adding time factor into our improved model.Finally, we analyze our works and then discuss strengths and weaknesses of our model.