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Evaluating Light Pollution: An IES Model for Intervention Strategies

Author

Listed:
  • Ruixi Su
  • Yi Chen
  • Zibin Huang

Abstract

There is an increasing urgency to address how the light pollution risk level can be accurately and comprehensively measured and evaluated. Based on current research and data, this paper proposes a model concerning light pollution risk levels applicable to various regions. Optimized intervention strategies are then provided to reduce the effect of light pollution. For one thing, this paper establishes an Illumination-Environment-Society Evaluation (IES) model to evaluate a region’s light pollution risk level. Primary indicators of the model involve three dimensions, each quantified by 2 to 5 secondary indicators, with sufficient data analysis conducted, including data rasterization of satellite remote sensing images, K-means clustering analysis, Principal Component Analysis (PCA), Entropy Weight Method (EWM), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Analytic Hierarchy Process (AHP), and other assistant algorithms. In this regard, the present study obtains and grades some regions’ light pollution risk levels. For another, this paper determines three possible intervention strategies for light pollution based on the IES model after interpreting the results. Non-linear programming methods are also employed to optimize these three strategies. The present study aims to exploit a new avenue for relevant environmental research, providing references for light pollution measurement and intervention.

Suggested Citation

  • Ruixi Su & Yi Chen & Zibin Huang, 2024. "Evaluating Light Pollution: An IES Model for Intervention Strategies," Environment and Pollution, Canadian Center of Science and Education, vol. 13(1), pages 1-1, March.
    • Handle: RePEc:ibn:eap123:v:13:y:2024:i:1:p:1
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    References listed on IDEAS

    as
    1. Gallaway, Terrel & Olsen, Reed N. & Mitchell, David M., 2010. "The economics of global light pollution," Ecological Economics, Elsevier, vol. 69(3), pages 658-665, January.
    2. Eva Knop & Leana Zoller & Remo Ryser & Christopher Gerpe & Maurin Hörler & Colin Fontaine, 2017. "Artificial light at night as a new threat to pollination," Nature, Nature, vol. 548(7666), pages 206-209, August.
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    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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