The Research on Environmental Security Level under the Current Pollution Situation

Mengyu Shi

Shanghai University of Political Science and Law, Shanghai, 201701, China

Abstract: With the increasing application of plastic products, the plastic waste problem is becoming serious than ever. Due to the fact that plastic products do not readily break down, it is essential for us to explore a achievable environmental security level. To estimate the maximum level of single-use ｏｒ disposable plastic product waste, we choose the ｓｏｕｒｃｅ of the waste, the current pollution level, and the use ratio of resources as factors. Moreover, Leven berg-Marquardt (LM) method is employed to establish a nonlinear model, then de-pending on 5 iterations we get the fitted maximum value of 603 thousand tons. We choose China and Japan as the representatives of developed and developing countries to make the comparison. According to research, we define the environmental security level   as the per capital waste emissions, which should be below 25. Then, we choose GDP, impact on policies, substitution rate and extent of pollution as decisive factors of wastes by AHP method. After establishing the comprehensive evaluation method and BP Neural Network Al-gorithm, the results show the former three show greater influence on developing countries while another greater on developed countries. To set a global target, we choose four countries from different states which are typical in financial as research objectives. During research, we find that the minimum level may influence the substitution rate, environment and the production of plastic industry. By gray prediction, we get the future three-year data to establish the optimizing model. Through Particle Swarm Algorithm, we find that the optimal value is1.512679 million tons, which means the production should be reduced by 721.599 thousand tons, substitution rate will reach 86.9296% and the pollution level may reduce to 79.4013% of the current situation. We ｓｅｌｅｃｔ three factors: export volume, recycling rate and plastic production per people of a country to establish an equity allocation model to address the inequality problem of distribution on plastic waste between nations and regions. From the comparison of all the factors between CHN, JPN, UK and Africa, we concluded that for the developing nations in different states, result indicated that Asian developing countries should take much responsibility than those in Africa. Otherwise, for the developed nations in different states, developed countries in Asia should be distributed more than those in Europe. In the same states, developing countries should take much responsibility. We forecast the lowest level in the next six years. The timeline reflects that the global target of 2015-2024 is steadily rising. Due to the influence of some factors, there is a certain deviation between the actual circumstance and the lowest level. We get the conclusion from above that the reverse inference may accelerate ｏｒ hinder this target to achieve. We find the output of plastic industry, the substitution rate of other materials and the pollution level are affected by the lowest level, and the proportions of influence are 47.7%, 57.47% and 52.5% respectively. If the actual values of that year are larger than these proportions, it will accelerate to achieve ｏｒ will hinder. While implementation of policies and natural disasters will also impact achievement, but artificial factors counts more.

Keywords: Multivariate nonlinear regression model; BP Neural Network Algorithm; Gray prediction; Waste emissions; Environmental security level