The issue of light pollution has been arousing more and more attention on a global scale. Oceans and atmosphere on earth are seriously threatened by light pollution. In order to identify and assess the light pollution risk level of a location, this paper establishes a two-phase comprehensive environmental assessment model for regional light pollution. In phase I model, this paper selected 12 indicators from three aspects: source of light pollution, severity of pollution problem, and resource availability of pollution. Subsequently, the Logistic Regression model (LR) was utilized to obtain the models of the light pollution source and the resource availability of the treated pollution, and the regression model was developed through several significant tests. In phase II, this paper used Spearman correlation coefficient analysis to obtain 10 effective indicators that are highly correlated with the amount of light used. Then we used the comprehensive weighting method based on the Ana-lytic Hierarchy Process (AHP) and Entropy Weight Method (EWM) to give weight to 10 indicators, and finally we evaluated the risk of light pollution in four different types of locations based on the TOPSIS comprehensive evaluation method. Finally, the sensitivity analysis of the model is carried out, and the results show that our model has good stability and is very reliable.

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The study of species population change is one of the most classic topics in biology. In this paper, we consider not only intra-race competition but also competition between two species. It is assumed that the resources in the environment are finite in this paper. Improved on the Logistic Population Growth Model from Malthusian model, we built the Competitive Hunter Model for trout and bass referring to the Lotka-Volterra Model. In this paper, we presented the assumptions of the model and analyzed the equilibrium points of the model in numerical analysis and the typical trajectories in phase planes in graphical analysis.