Abstract
This study explores the impact of road transport on the environment, focusing on noise pollution. Using high-resolution, one-minute data from a low-cost environmental sensor, this research examines traffic flow dynamics, meteorological influences, and their relationship to noise along a major transport corridor. The methodology combines cluster analysis and descriptive statistics to evaluate the effects of deploying a Smart Motorway Variable Speed Limit (SMVSL) system over a six-month monitoring period. Results indicate that SMVSL systems not only smooth traffic flow but also significantly reduce noise variability, particularly during peak hours, thus mitigating noise peaks associated with adverse health outcomes. LAeq values were found to differ modestly between day and night, with clustering revealing a reduction in extreme noise events (LAmax > 70 dB(A)) in SMVSL scenarios dominated by heavy goods vehicles. This study further identifies associations between unmanaged speed regimes and elevated noise levels, enriching our understanding of the environmental impacts of unregulated traffic conditions. These findings inform sustainable planning and policy strategies aimed at improving urban environmental quality and enhancing public health outcomes.
| Original language | English |
|---|---|
| Article number | 18 |
| Number of pages | 31 |
| Journal | Acoustics |
| Volume | 7 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 28 Mar 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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SDG 11 Sustainable Cities and Communities
Keywords
- variable speed limit systems
- environmental noise
- traffic noise mitigation
- heavy goods vehicles (HGVs)
- intelligent transport systems (ITSs)
- noise variability
- meteorological influences on noise
- high-resolution monitoring
- hierarchical cluster analysis
- road traffic management
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