Brighten or Harm: Light Pollution Risk Assessment and Prevention

Abstract

Light pollution harms health and the environment, but global assessments only measure light pollution levels, lacking a comprehensive evaluation of its risk. The evaluation model was developed to assess direct and indirect influences with 11 factors, ensuring mutual independence through the KMO test, assigning weights via the AHP model, and applying it to 49 cities globally based on varying urban levels. Using the TOPSIS model, we calculated comprehensive scores for each city and applied K-Means clustering to categorize scores into different levels. Four distinct sites were chosen to validate the model's reliability. By utilizing pertinent data for each indicator, the established model was employed to assess the light pollution risk levels at these locations. Subsequent to this investigation, three intervention strategies were formulated as potential measures to mitigate light pollution, accompanied by a comprehensive analysis of their possible impacts. Finally, 49 cities were classified into five light pollution levels, affirming the practicality of the model. The analysis led to the identification of three intervention strategies: "Material Optimization," "Enhanced Artificial Application," and "Public Education and Awareness."