Abstract
This study examines the control of traffic noise in urban planning, considering the differences in noise impacts at various scales. Acoustic simulations and spatial statistics were employed to compare traditional planning variables and planning big data for noise analysis. The study investigates noise impact in urban centres and fringes and analyses varying effects of a given variable on traffic noise at scales of 300, 600, and 1200 m. Additionally, sound environment optimisation strategies are proposed and validated for different scales and areas. The major findings are: (1) planning big data had more impact in single-variable models, while traditional variables were more significant in multivariable models; (2) the noise impact of most variables varied with the area and scale, for example, at 1200 m, the total building perimeter has opposing effects in urban centres and fringes, and the greening rate changes from positive to negative with increasing scale; (3) the proposed strategies reduced traffic noise by an average of 4.2, 3.2, and 2.3 dB at scales of 300, 600, and 1200 m, respectively. These findings provide valuable insights for the optimisation of urban sound environments.
| Original language | English |
|---|---|
| Article number | 105006 |
| Journal | Sustainable Cities and Society |
| Volume | 100 |
| DOIs | |
| State | Published - Jan 2024 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 11 Sustainable Cities and Communities
Keywords
- Multi-scale
- Planning factors
- Traffic noise
- Urban acoustic environment
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