A hybrid model for analyzing the risk levels of light pollution

Abstract

The aim of this paper is to investigate the effects of light pollution on the environment and human health, proposing effective intervention measures. A widely applicable metric is developed to determine light pollution risk levels in different regions, forming the basis for a reliable assessment model. This model, integrating Analytic Hierarchy Process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) model, and multiple regression analysis (MRA), offers a comprehensive understanding of light pollution risk by considering regional development, light usage, and geographical factors. The assessment model demonstrates high accuracy and reliability in measuring light pollution risk, providing valuable insights into the interaction between factors such as light intensity, biodiversity loss, GDP, and population. Empirical analysis reveals regional disparities in light pollution risk levels, underscoring the need for targeted interventions to mitigate its adverse impacts. Overall, the developed light pollution risk assessment model serves as a valuable tool for policymakers, facilitating informed decision-making and effective intervention strategies.