Light pollution is not only a threat to non-humans, but also a threat to humans. People gradually realize the harm of light pollution. It is urgent to control and prevent light pollution. In this paper, we propose the light pollution assessment model to evaluate the light pollution risk. We select evaluation indicators from population, economy, transportation and energy to obtain evaluation criteria. We used the entropy weight method to determine the respective weights of the above indicators, and established the TOPSIS comprehensive model to obtain comprehensive scores for 43 countries. We construct policies intervention optimization model, to quantify the policy effect, we consider the policy version time to obtain the policy factor. Then we establish a government control index model and input Population density, GDP Policy Power and Light intensity, etc. The basis of this analysis is the random forest model for regression prediction, that is, we limit the model function form to the relative bias of the variables. The year in which the national light pollution policy was introduced, the longer the version is old, the less effective. Finally, we designed a selection poster advocating limiting light pollution, with the "X" shaped light source on the back of the human body representing the symbol of prohibition, calling for attention to the prevention of light pollution.

Sijing Zheng, Ji Chen, Yijie Su. Research on light pollution based on policy intervention optimization model. Academic Journal of Environment & Earth Science (2023) Vol. 5 Issue 6: 59-66. https://doi.org/10.25236/AJEE.2023.050610.

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