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[Can trees and forests help in improving environmental noise quality?]
Sante Publique (Vandoeuvre-Les-Nancy, France)
|June 19, 2019
Summary
Planting trees and forest strips can effectively reduce road traffic noise. Optimal noise abatement involves specific planting schemes, densities, and ground preparation for improved outdoor sound environments.
Area of Science:
- Environmental Science
- Acoustics
- Urban Planning
Background:
- Road traffic noise is a significant environmental concern impacting public health and quality of life.
- Current noise management strategies often require substantial infrastructure, prompting interest in natural solutions like vegetation.
- Understanding the acoustic effects of different planting schemes is crucial for effective noise mitigation.
Purpose of the Study:
- To determine optimal planting schemes for trees and forest strips in road traffic noise abatement.
- To quantify expected noise attenuation levels for various configurations.
- To provide evidence-based recommendations for using vegetation in environmental noise control.
Main Methods:
- Review of existing scientific literature on sound propagation through vegetation.
- Analysis of acoustic impacts in typical landscape configurations (forest strips, rows of trees, urban trees).
- Synthesis of data to establish best practices for tree planting in noise reduction.
Main Results:
- Trees and forest strips offer beneficial noise abatement, with attenuation dependent on planting scheme and density.
- Key sound attenuation processes include ground absorption, diffusion, and refraction effects.
- Recommended planting involves broadleaved evergreens or mixed coniferous/broadleaved types at a minimum density of 0.25 trees/m², with cultivated ground.
Conclusions:
- Strategic planting of trees and forest strips is a viable method for road traffic noise control.
- Specific species (broadleaved evergreens, mixed) and densities are recommended for maximum acoustic benefit.
- Proper ground preparation enhances the effectiveness of vegetation-based noise abatement strategies.
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